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|---|---|---|---|---|---|---|---|---|---|---|---|
0015/esp_rlottie | rlottie/licenses/COPYING.RPD | Tencent is pleased to support the open source community by making RapidJSON available.
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A copy of the MIT License is included in this file.
Other dependencies and licenses:
Open Source Software Licensed Under the BSD License:
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Copyright (c) 2006-2013 Alexander Chemeris
All rights reserved.
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* Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
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The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
The Software shall be used for Good, not Evil.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
| 5,152 | COPYING | rpd | en | text | text | {"qsc_doc_frac_chars_curly_bracket": 0.0, "qsc_doc_frac_words_redpajama_stop": 0.25355191, "qsc_doc_num_sentences": 26.0, "qsc_doc_num_words": 770, "qsc_doc_num_chars": 5152.0, "qsc_doc_num_lines": 57.0, "qsc_doc_mean_word_length": 5.12987013, "qsc_doc_frac_words_full_bracket": 0.0, "qsc_doc_frac_lines_end_with_readmore": 0.0, "qsc_doc_frac_lines_start_with_bullet": 0.0, "qsc_doc_frac_words_unique": 0.29480519, "qsc_doc_entropy_unigram": 4.78927363, "qsc_doc_frac_words_all_caps": 0.30819672, "qsc_doc_frac_lines_dupe_lines": 0.37142857, "qsc_doc_frac_chars_dupe_lines": 0.45872642, "qsc_doc_frac_chars_top_2grams": 0.04734177, "qsc_doc_frac_chars_top_3grams": 0.00886076, "qsc_doc_frac_chars_top_4grams": 0.02329114, "qsc_doc_frac_chars_dupe_5grams": 0.56582278, "qsc_doc_frac_chars_dupe_6grams": 0.5356962, "qsc_doc_frac_chars_dupe_7grams": 0.49746835, "qsc_doc_frac_chars_dupe_8grams": 0.49746835, "qsc_doc_frac_chars_dupe_9grams": 0.47822785, "qsc_doc_frac_chars_dupe_10grams": 0.45898734, "qsc_doc_frac_chars_replacement_symbols": 0.0, "qsc_doc_cate_code_related_file_name": 0.0, "qsc_doc_num_chars_sentence_length_mean": 60.3452381, "qsc_doc_frac_chars_hyperlink_html_tag": 0.0, "qsc_doc_frac_chars_alphabet": 0.90128558, "qsc_doc_frac_chars_digital": 0.00550964, "qsc_doc_frac_chars_whitespace": 0.15450311, "qsc_doc_frac_chars_hex_words": 0.0} | 1 | {"qsc_doc_frac_chars_replacement_symbols": 0, "qsc_doc_entropy_unigram": 0, "qsc_doc_frac_chars_top_2grams": 0, "qsc_doc_frac_chars_top_3grams": 0, "qsc_doc_frac_chars_top_4grams": 0, "qsc_doc_frac_chars_dupe_5grams": 0, "qsc_doc_frac_chars_dupe_6grams": 0, "qsc_doc_frac_chars_dupe_7grams": 0, "qsc_doc_frac_chars_dupe_8grams": 0, "qsc_doc_frac_chars_dupe_9grams": 0, "qsc_doc_frac_chars_dupe_10grams": 0, "qsc_doc_frac_chars_dupe_lines": 0, "qsc_doc_frac_lines_dupe_lines": 0, "qsc_doc_frac_lines_end_with_readmore": 0, "qsc_doc_frac_lines_start_with_bullet": 0, "qsc_doc_frac_words_all_caps": 0, "qsc_doc_mean_word_length": 0, "qsc_doc_num_chars": 0, "qsc_doc_num_lines": 0, "qsc_doc_num_sentences": 0, "qsc_doc_num_words": 0, "qsc_doc_frac_chars_hex_words": 0, "qsc_doc_frac_chars_hyperlink_html_tag": 0, "qsc_doc_frac_chars_alphabet": 0, "qsc_doc_frac_chars_digital": 0, "qsc_doc_frac_chars_whitespace": 0} |
0015/esp_rlottie | rlottie/licenses/COPYING.PIX | The following is the MIT license, agreed upon by most contributors.
Copyright holders of new code should use this license statement where
possible. They may also add themselves to the list below.
/*
* Copyright 1987, 1988, 1989, 1998 The Open Group
* Copyright 1987, 1988, 1989 Digital Equipment Corporation
* Copyright 1999, 2004, 2008 Keith Packard
* Copyright 2000 SuSE, Inc.
* Copyright 2000 Keith Packard, member of The XFree86 Project, Inc.
* Copyright 2004, 2005, 2007, 2008, 2009, 2010 Red Hat, Inc.
* Copyright 2004 Nicholas Miell
* Copyright 2005 Lars Knoll & Zack Rusin, Trolltech
* Copyright 2005 Trolltech AS
* Copyright 2007 Luca Barbato
* Copyright 2008 Aaron Plattner, NVIDIA Corporation
* Copyright 2008 Rodrigo Kumpera
* Copyright 2008 André Tupinambá
* Copyright 2008 Mozilla Corporation
* Copyright 2008 Frederic Plourde
* Copyright 2009, Oracle and/or its affiliates. All rights reserved.
* Copyright 2009, 2010 Nokia Corporation
*
* Permission is hereby granted, free of charge, to any person obtaining a
* copy of this software and associated documentation files (the "Software"),
* to deal in the Software without restriction, including without limitation
* the rights to use, copy, modify, merge, publish, distribute, sublicense,
* and/or sell copies of the Software, and to permit persons to whom the
* Software is furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice (including the next
* paragraph) shall be included in all copies or substantial portions of the
* Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
* THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
* FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
* DEALINGS IN THE SOFTWARE.
*/
| 2,084 | COPYING | pix | en | text | text | {"qsc_doc_frac_chars_curly_bracket": 0.0, "qsc_doc_frac_words_redpajama_stop": 0.17456359, "qsc_doc_num_sentences": 11.0, "qsc_doc_num_words": 300, "qsc_doc_num_chars": 2084.0, "qsc_doc_num_lines": 42.0, "qsc_doc_mean_word_length": 5.33666667, "qsc_doc_frac_words_full_bracket": 0.0, "qsc_doc_frac_lines_end_with_readmore": 0.0, "qsc_doc_frac_lines_start_with_bullet": 0.0, "qsc_doc_frac_words_unique": 0.54333333, "qsc_doc_entropy_unigram": 4.64685086, "qsc_doc_frac_words_all_caps": 0.19700748, "qsc_doc_frac_lines_dupe_lines": 0.07317073, "qsc_doc_frac_chars_dupe_lines": 0.00149626, "qsc_doc_frac_chars_top_2grams": 0.05496565, "qsc_doc_frac_chars_top_3grams": 0.02123673, "qsc_doc_frac_chars_top_4grams": 0.0262336, "qsc_doc_frac_chars_dupe_5grams": 0.0, "qsc_doc_frac_chars_dupe_6grams": 0.0, "qsc_doc_frac_chars_dupe_7grams": 0.0, "qsc_doc_frac_chars_dupe_8grams": 0.0, "qsc_doc_frac_chars_dupe_9grams": 0.0, "qsc_doc_frac_chars_dupe_10grams": 0.0, "qsc_doc_frac_chars_replacement_symbols": 0.0, "qsc_doc_cate_code_related_file_name": 0.0, "qsc_doc_num_chars_sentence_length_mean": 37.61111111, "qsc_doc_frac_chars_hyperlink_html_tag": 0.0, "qsc_doc_frac_chars_alphabet": 0.86643234, "qsc_doc_frac_chars_digital": 0.07147042, "qsc_doc_frac_chars_whitespace": 0.18090211, "qsc_doc_frac_chars_hex_words": 0.0} | 1 | {"qsc_doc_frac_chars_replacement_symbols": 0, "qsc_doc_entropy_unigram": 0, "qsc_doc_frac_chars_top_2grams": 0, "qsc_doc_frac_chars_top_3grams": 0, "qsc_doc_frac_chars_top_4grams": 0, "qsc_doc_frac_chars_dupe_5grams": 0, "qsc_doc_frac_chars_dupe_6grams": 0, "qsc_doc_frac_chars_dupe_7grams": 0, "qsc_doc_frac_chars_dupe_8grams": 0, "qsc_doc_frac_chars_dupe_9grams": 0, "qsc_doc_frac_chars_dupe_10grams": 0, "qsc_doc_frac_chars_dupe_lines": 0, "qsc_doc_frac_lines_dupe_lines": 0, "qsc_doc_frac_lines_end_with_readmore": 0, "qsc_doc_frac_lines_start_with_bullet": 0, "qsc_doc_frac_words_all_caps": 0, "qsc_doc_mean_word_length": 0, "qsc_doc_num_chars": 0, "qsc_doc_num_lines": 0, "qsc_doc_num_sentences": 0, "qsc_doc_num_words": 0, "qsc_doc_frac_chars_hex_words": 0, "qsc_doc_frac_chars_hyperlink_html_tag": 0, "qsc_doc_frac_chars_alphabet": 0, "qsc_doc_frac_chars_digital": 0, "qsc_doc_frac_chars_whitespace": 0} |
0015/7-Color-E-Paper-Digital-Photo-Frame | README.md | # ESP32 E-Paper Digital Frame Project
This project is a digital photo frame using an ESP32 microcontroller and a 5.65” seven-color E-Paper display, optimized to display images with a 7-color palette. The ESP32 retrieves image data from a local server and displays it on the screen, with a power-saving feature that puts the ESP32 into hibernation between updates.
[](https://youtu.be/9gdemeaTfyI)
## Project Overview
This setup is designed to efficiently display photos on an E-Paper display, which supports only a limited color palette. To achieve the best image quality, images are converted using Floyd–Steinberg dithering and a custom 7-color palette.
## Hardware
[Note] I have only tested it with this display, so it may not work with other E-Paper 7-color displays.
* [5.65” Seven-Color E-Paper Display 600x448](https://www.seeedstudio.com/5-65-Seven-Color-ePaper-Display-with-600x480-Pixels-p-5786.html)
* [E-Paper Breakout Board for Seeed Studio XIAO](https://www.seeedstudio.com/ePaper-Breakout-Board-p-5804.html)
* [Seeed Studio XIAO ESP32S3](https://www.seeedstudio.com/XIAO-ESP32S3-p-5627.html)
* 1S LiPo Battery 3.7v
* Raspberry Pi 4 (for local server)
## System Architecture
1. Raspberry Pi with Flask Server:
* Hosts a simple API server that serves image data to the ESP32.
* Monitors a designated folder for new images and automatically processes them to the required format.
2. ESP32 with E-Paper Display:
* Requests image data from the server.
* Draws the image on the E-Paper display.
* Retrieves the next wake-up interval from the server to manage its power-saving hibernation mode.
## Workflow
1. Image Conversion: New images added to the Images folder are automatically resized to 600x448 and processed using Floyd–Steinberg dithering to match the 7-color palette.
2. Flask API: The server sends converted images in byte data format ready for display. The ESP32 requests new images and draws them on the display.
3. Hibernation Schedule: Between 8 AM and 8 PM, the ESP32 wakes up every hour for updates. After 8 PM, it hibernates until 8 AM the following day.
## ESP32 Setup
* _Test_E_Paper_5_65inch_7color: A test program for the E-Paper display.
* E-Paper_Photo_Frame: The main program to connect to the server and update the display dynamically.
* This code stores the image data obtained from the server into PSRAM. Please change this part according to your needs.
## Raspberry Pi Server Setup
[Note] The reason I used RPI here is that this is a personal local test server that is always on. You can use it on your PC as well, not just RPI.
1. Clone this repository to your Raspberry Pi.
```
git clone https://github.com/0015/7-Color-E-Paper-Digital-Photo-Frame.git
```
2. Install the dependencies:
```python
pip install -r requirements.txt
```
3. Set up and start the Flask server:
```python
python flask_server.py
```
The monitor.py script will automatically run alongside. It will watch the Images folder, resize images, apply dithering, and save the result as .h files in the h_files folder.
## Flask API Endpoints
* /get-img-data: Returns the next image data in byte format.
* /status: Returns the status of sent and remaining files.
* /wakeup-interval: Returns the interval (in seconds) until the next wake-up time based on the current time.
## Dependencies
* Flask: For running the API server.
* Watchdog: For monitoring file changes.
* Pillow: For image processing.
* NumPy: For handling numerical operations during image conversion.
| 3,849 | README | md | en | markdown | text | {"qsc_doc_frac_chars_curly_bracket": 0.0, "qsc_doc_frac_words_redpajama_stop": 0.20359955, "qsc_doc_num_sentences": 68.0, "qsc_doc_num_words": 637, "qsc_doc_num_chars": 3849.0, "qsc_doc_num_lines": 66.0, "qsc_doc_mean_word_length": 4.68131868, "qsc_doc_frac_words_full_bracket": 0.0, "qsc_doc_frac_lines_end_with_readmore": 0.0, "qsc_doc_frac_lines_start_with_bullet": 0.0, "qsc_doc_frac_words_unique": 0.38461538, "qsc_doc_entropy_unigram": 5.04592234, "qsc_doc_frac_words_all_caps": 0.04949381, "qsc_doc_frac_lines_dupe_lines": 0.11111111, "qsc_doc_frac_chars_dupe_lines": 0.00794071, "qsc_doc_frac_chars_top_2grams": 0.03018109, "qsc_doc_frac_chars_top_3grams": 0.0221328, "qsc_doc_frac_chars_top_4grams": 0.01743796, "qsc_doc_frac_chars_dupe_5grams": 0.12743125, "qsc_doc_frac_chars_dupe_6grams": 0.10798122, "qsc_doc_frac_chars_dupe_7grams": 0.10798122, "qsc_doc_frac_chars_dupe_8grams": 0.09054326, "qsc_doc_frac_chars_dupe_9grams": 0.09054326, "qsc_doc_frac_chars_dupe_10grams": 0.07847082, "qsc_doc_frac_chars_replacement_symbols": 0.0, "qsc_doc_cate_code_related_file_name": 1.0, "qsc_doc_num_chars_sentence_length_mean": 27.10218978, "qsc_doc_frac_chars_hyperlink_html_tag": 0.14731099, "qsc_doc_frac_chars_alphabet": 0.87003938, "qsc_doc_frac_chars_digital": 0.03271736, "qsc_doc_frac_chars_whitespace": 0.14237464, "qsc_doc_frac_chars_hex_words": 0.0} | 1 | {"qsc_doc_frac_chars_replacement_symbols": 0, "qsc_doc_entropy_unigram": 0, "qsc_doc_frac_chars_top_2grams": 0, "qsc_doc_frac_chars_top_3grams": 0, "qsc_doc_frac_chars_top_4grams": 0, "qsc_doc_frac_chars_dupe_5grams": 0, "qsc_doc_frac_chars_dupe_6grams": 0, "qsc_doc_frac_chars_dupe_7grams": 0, "qsc_doc_frac_chars_dupe_8grams": 0, "qsc_doc_frac_chars_dupe_9grams": 0, "qsc_doc_frac_chars_dupe_10grams": 0, "qsc_doc_frac_chars_dupe_lines": 0, "qsc_doc_frac_lines_dupe_lines": 0, "qsc_doc_frac_lines_end_with_readmore": 0, "qsc_doc_frac_lines_start_with_bullet": 0, "qsc_doc_frac_words_all_caps": 0, "qsc_doc_mean_word_length": 0, "qsc_doc_num_chars": 0, "qsc_doc_num_lines": 0, "qsc_doc_num_sentences": 0, "qsc_doc_num_words": 0, "qsc_doc_frac_chars_hex_words": 0, "qsc_doc_frac_chars_hyperlink_html_tag": 0, "qsc_doc_frac_chars_alphabet": 0, "qsc_doc_frac_chars_digital": 0, "qsc_doc_frac_chars_whitespace": 0} |
0015/7-Color-E-Paper-Digital-Photo-Frame | Flask_API_Server/flask_server.py | from datetime import datetime, time, timedelta
from flask import Flask, send_file, jsonify
import os
import random
import subprocess
app = Flask(__name__)
# Folder containing .h files
H_FILES_FOLDER = './h_files'
sent_files = []
all_files = []
# Start monitor.py as a background process
def start_monitor_script():
subprocess.Popen(['python3', 'monitor.py'])
def load_files():
global all_files
current_files = set(all_files + sent_files) # Avoid duplicates
new_files = [f for f in os.listdir(H_FILES_FOLDER) if f.endswith('.h') and f not in current_files]
all_files.extend(new_files)
random.shuffle(all_files) # Optional if you want a new order every time
# Route to get the next .h file
@app.route('/get-img-data', methods=['GET'])
def get_img_data():
global sent_files, all_files
# Reshuffle and reset sent_files if all files have been sent
if not all_files:
load_files()
sent_files = []
# Get the next file to send
next_file = all_files.pop()
sent_files.append(next_file)
# Send the file
file_path = os.path.join(H_FILES_FOLDER, next_file)
return send_file(file_path, as_attachment=True)
# Optional route to get the status
@app.route('/status', methods=['GET'])
def status():
load_files()
return jsonify({
"remaining_files": len(all_files),
"sent_files": len(sent_files)
})
@app.route('/wakeup-interval', methods=['GET'])
def wakeup_interval():
now = datetime.now()
current_time = now.time()
# Define time boundaries
morning_time = time(8, 0) # 8 AM
evening_time = time(20, 0) # 8 PM
if morning_time <= current_time < evening_time:
interval = 3600 # 1 hour in seconds
else:
# Calculate seconds until the next 8 AM
next_morning = datetime.combine(now.date() + timedelta(days=1), morning_time)
interval = int((next_morning - now).total_seconds())
return jsonify(interval=interval)
# Run the Flask server
if __name__ == '__main__':
start_monitor_script() # Start monitor.py when Flask server starts
app.run(host='0.0.0.0', port=9999)
| 2,134 | flask_server | py | en | python | code | {"qsc_code_num_words": 313, "qsc_code_num_chars": 2134.0, "qsc_code_mean_word_length": 4.44408946, "qsc_code_frac_words_unique": 0.34185304, "qsc_code_frac_chars_top_2grams": 0.05751258, "qsc_code_frac_chars_top_3grams": 0.04025881, "qsc_code_frac_chars_top_4grams": 0.02444285, "qsc_code_frac_chars_dupe_5grams": 0.0, "qsc_code_frac_chars_dupe_6grams": 0.0, "qsc_code_frac_chars_dupe_7grams": 0.0, "qsc_code_frac_chars_dupe_8grams": 0.0, "qsc_code_frac_chars_dupe_9grams": 0.0, "qsc_code_frac_chars_dupe_10grams": 0.0, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.01358535, "qsc_code_frac_chars_whitespace": 0.20665417, "qsc_code_size_file_byte": 2134.0, "qsc_code_num_lines": 73.0, "qsc_code_num_chars_line_max": 103.0, "qsc_code_num_chars_line_mean": 29.23287671, "qsc_code_frac_chars_alphabet": 0.80803308, "qsc_code_frac_chars_comments": 0.20712277, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.08163265, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.06746269, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codepython_cate_ast": 1.0, "qsc_codepython_frac_lines_func_ratio": 0.10204082, "qsc_codepython_cate_var_zero": false, "qsc_codepython_frac_lines_pass": 0.0, "qsc_codepython_frac_lines_import": 0.10204082, "qsc_codepython_frac_lines_simplefunc": 0.0, "qsc_codepython_score_lines_no_logic": 0.26530612, "qsc_codepython_frac_lines_print": 0.0} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codepython_cate_ast": 0, "qsc_codepython_frac_lines_func_ratio": 0, "qsc_codepython_cate_var_zero": 0, "qsc_codepython_frac_lines_pass": 0, "qsc_codepython_frac_lines_import": 0, "qsc_codepython_frac_lines_simplefunc": 0, "qsc_codepython_score_lines_no_logic": 0, "qsc_codepython_frac_lines_print": 0} |
000haoji/deep-student | src/components/ModernSelect.css | .modern-select {
position: relative;
font-size: 0.9rem;
user-select: none;
}
.modern-select.full-width {
width: 100%;
}
.select-trigger {
width: 100%;
display: flex;
align-items: center;
justify-content: space-between;
gap: 0.5rem;
padding: 0.75rem 1rem;
border: 2px solid #e2e8f0;
border-radius: 10px;
background: #f9fafb;
font-weight: 500;
color: #2d3748;
cursor: pointer;
transition: all 0.2s ease;
}
.select-trigger:hover {
border-color: #667eea;
}
.select-trigger:focus-visible {
outline: none;
border-color: #667eea;
box-shadow: 0 0 0 3px rgba(102, 126, 234, 0.15);
}
.select-trigger .arrow {
font-size: 0.75rem;
color: #667eea;
transition: transform 0.2s ease;
}
.modern-select.open .arrow {
transform: rotate(180deg);
}
.options-list {
position: absolute;
top: calc(100% + 4px);
left: 0;
width: 100%;
max-height: 240px;
overflow-y: auto;
background: #ffffff;
border: 2px solid #e2e8f0;
border-radius: 12px;
box-shadow: 0 8px 24px rgba(0, 0, 0, 0.08);
z-index: 1000;
padding: 0.25rem 0;
animation: fadeInScale 0.15s ease;
}
@keyframes fadeInScale {
0% {
opacity: 0;
transform: scale(0.95);
}
100% {
opacity: 1;
transform: scale(1);
}
}
.options-list li {
padding: 0.625rem 1rem;
cursor: pointer;
transition: background 0.15s ease, color 0.15s ease;
white-space: nowrap;
}
.options-list li:hover {
background: #f0f4ff;
color: #4c51bf;
}
.options-list li.selected {
background: #667eea;
color: #ffffff;
}
.modern-select.disabled .select-trigger {
background: #edf2f7;
cursor: not-allowed;
opacity: 0.6;
} | 1,644 | ModernSelect | css | en | css | data | {"qsc_code_num_words": 221, "qsc_code_num_chars": 1644.0, "qsc_code_mean_word_length": 4.85520362, "qsc_code_frac_words_unique": 0.47963801, "qsc_code_frac_chars_top_2grams": 0.06057782, "qsc_code_frac_chars_top_3grams": 0.0083877, "qsc_code_frac_chars_top_4grams": 0.03727866, "qsc_code_frac_chars_dupe_5grams": 0.05964585, "qsc_code_frac_chars_dupe_6grams": 0.05964585, "qsc_code_frac_chars_dupe_7grams": 0.0, "qsc_code_frac_chars_dupe_8grams": 0.0, "qsc_code_frac_chars_dupe_9grams": 0.0, "qsc_code_frac_chars_dupe_10grams": 0.0, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.10235027, "qsc_code_frac_chars_whitespace": 0.19768856, "qsc_code_size_file_byte": 1644.0, "qsc_code_num_lines": 95.0, "qsc_code_num_chars_line_max": 55.0, "qsc_code_num_chars_line_mean": 17.30526316, "qsc_code_frac_chars_alphabet": 0.71114481, "qsc_code_frac_chars_comments": 0.0, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.10843373, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.0, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_words_unique": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0} |
0000cd/wolf-set | themes/bluf/static/css/glightbox.min.css | .glightbox-container{width:100%;height:100%;position:fixed;top:0;left:0;z-index:999999!important;overflow:hidden;-ms-touch-action:none;touch-action:none;-webkit-text-size-adjust:100%;-moz-text-size-adjust:100%;-ms-text-size-adjust:100%;text-size-adjust:100%;-webkit-backface-visibility:hidden;backface-visibility:hidden;outline:0}.glightbox-container.inactive{display:none}.glightbox-container .gcontainer{position:relative;width:100%;height:100%;z-index:9999;overflow:hidden}.glightbox-container .gslider{-webkit-transition:-webkit-transform .4s ease;transition:-webkit-transform .4s ease;transition:transform .4s ease;transition:transform .4s ease,-webkit-transform .4s ease;height:100%;left:0;top:0;width:100%;position:relative;overflow:hidden;display:-webkit-box!important;display:-ms-flexbox!important;display:flex!important;-webkit-box-pack:center;-ms-flex-pack:center;justify-content:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;-webkit-transform:translate3d(0,0,0);transform:translate3d(0,0,0)}.glightbox-container .gslide{width:100%;position:absolute;-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;user-select:none;display:-webkit-box;display:-ms-flexbox;display:flex;-webkit-box-align:center;-ms-flex-align:center;align-items:center;-webkit-box-pack:center;-ms-flex-pack:center;justify-content:center;opacity:0}.glightbox-container .gslide.current{opacity:1;z-index:99999;position:relative}.glightbox-container .gslide.prev{opacity:1;z-index:9999}.glightbox-container .gslide-inner-content{width:100%}.glightbox-container .ginner-container{position:relative;width:100%;display:-webkit-box;display:-ms-flexbox;display:flex;-webkit-box-pack:center;-ms-flex-pack:center;justify-content:center;-webkit-box-orient:vertical;-webkit-box-direction:normal;-ms-flex-direction:column;flex-direction:column;max-width:100%;margin:auto;height:100vh}.glightbox-container .ginner-container.gvideo-container{width:100%}.glightbox-container .ginner-container.desc-bottom,.glightbox-container .ginner-container.desc-top{-webkit-box-orient:vertical;-webkit-box-direction:normal;-ms-flex-direction:column;flex-direction:column}.glightbox-container .ginner-container.desc-left,.glightbox-container .ginner-container.desc-right{max-width:100%!important}.gslide iframe,.gslide video{outline:0!important;border:none;min-height:165px;-webkit-overflow-scrolling:touch;-ms-touch-action:auto;touch-action:auto}.gslide:not(.current){pointer-events:none}.gslide-image{-webkit-box-align:center;-ms-flex-align:center;align-items:center}.gslide-image img{max-height:100vh;display:block;padding:0;float:none;outline:0;border:none;-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;user-select:none;max-width:100vw;width:auto;height:auto;-o-object-fit:cover;object-fit:cover;-ms-touch-action:none;touch-action:none;margin:auto;min-width:200px}.desc-bottom .gslide-image img,.desc-top .gslide-image img{width:auto}.desc-left .gslide-image img,.desc-right .gslide-image img{width:auto;max-width:100%}.gslide-image img.zoomable{position:relative}.gslide-image img.dragging{cursor:-webkit-grabbing!important;cursor:grabbing!important;-webkit-transition:none;transition:none}.gslide-video{position:relative;max-width:100vh;width:100%!important}.gslide-video .plyr__poster-enabled.plyr--loading .plyr__poster{display:none}.gslide-video .gvideo-wrapper{width:100%;margin:auto}.gslide-video::before{content:'';position:absolute;width:100%;height:100%;background:rgba(255,0,0,.34);display:none}.gslide-video.playing::before{display:none}.gslide-video.fullscreen{max-width:100%!important;min-width:100%;height:75vh}.gslide-video.fullscreen video{max-width:100%!important;width:100%!important}.gslide-inline{background:#fff;text-align:left;max-height:calc(100vh - 40px);overflow:auto;max-width:100%;margin:auto}.gslide-inline .ginlined-content{padding:20px;width:100%}.gslide-inline .dragging{cursor:-webkit-grabbing!important;cursor:grabbing!important;-webkit-transition:none;transition:none}.ginlined-content{overflow:auto;display:block!important;opacity:1}.gslide-external{display:-webkit-box;display:-ms-flexbox;display:flex;width:100%;min-width:100%;background:#fff;padding:0;overflow:auto;max-height:75vh;height:100%}.gslide-media{display:-webkit-box;display:-ms-flexbox;display:flex;width:auto}.zoomed .gslide-media{-webkit-box-shadow:none!important;box-shadow:none!important}.desc-bottom .gslide-media,.desc-top .gslide-media{margin:0 auto;-webkit-box-orient:vertical;-webkit-box-direction:normal;-ms-flex-direction:column;flex-direction:column}.gslide-description{position:relative;-webkit-box-flex:1;-ms-flex:1 0 100%;flex:1 0 100%}.gslide-description.description-left,.gslide-description.description-right{max-width:100%}.gslide-description.description-bottom,.gslide-description.description-top{margin:0 auto;width:100%}.gslide-description p{margin-bottom:12px}.gslide-description p:last-child{margin-bottom:0}.zoomed .gslide-description{display:none}.glightbox-button-hidden{display:none}.glightbox-mobile .glightbox-container .gslide-description{height:auto!important;width:100%;position:absolute;bottom:0;padding:19px 11px;max-width:100vw!important;-webkit-box-ordinal-group:3!important;-ms-flex-order:2!important;order:2!important;max-height:78vh;overflow:auto!important;background:-webkit-gradient(linear,left top,left bottom,from(rgba(0,0,0,0)),to(rgba(0,0,0,.75)));background:linear-gradient(to bottom,rgba(0,0,0,0) 0,rgba(0,0,0,.75) 100%);-webkit-transition:opacity .3s linear;transition:opacity .3s linear;padding-bottom:50px}.glightbox-mobile .glightbox-container .gslide-title{color:#fff;font-size:1em}.glightbox-mobile .glightbox-container .gslide-desc{color:#a1a1a1}.glightbox-mobile .glightbox-container .gslide-desc a{color:#fff;font-weight:700}.glightbox-mobile .glightbox-container .gslide-desc *{color:inherit}.glightbox-mobile .glightbox-container .gslide-desc .desc-more{color:#fff;opacity:.4}.gdesc-open .gslide-media{-webkit-transition:opacity .5s ease;transition:opacity .5s ease;opacity:.4}.gdesc-open .gdesc-inner{padding-bottom:30px}.gdesc-closed .gslide-media{-webkit-transition:opacity .5s ease;transition:opacity .5s ease;opacity:1}.greset{-webkit-transition:all .3s ease;transition:all .3s ease}.gabsolute{position:absolute}.grelative{position:relative}.glightbox-desc{display:none!important}.glightbox-open{overflow:hidden}.gloader{height:25px;width:25px;-webkit-animation:lightboxLoader .8s infinite linear;animation:lightboxLoader .8s infinite linear;border:2px solid #fff;border-right-color:transparent;border-radius:50%;position:absolute;display:block;z-index:9999;left:0;right:0;margin:0 auto;top:47%}.goverlay{width:100%;height:calc(100vh + 1px);position:fixed;top:-1px;left:0;background:#000;will-change:opacity}.glightbox-mobile .goverlay{background:#000}.gclose,.gnext,.gprev{z-index:99999;cursor:pointer;width:26px;height:44px;border:none;display:-webkit-box;display:-ms-flexbox;display:flex;-webkit-box-pack:center;-ms-flex-pack:center;justify-content:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;-webkit-box-orient:vertical;-webkit-box-direction:normal;-ms-flex-direction:column;flex-direction:column}.gclose svg,.gnext svg,.gprev svg{display:block;width:25px;height:auto;margin:0;padding:0}.gclose.disabled,.gnext.disabled,.gprev.disabled{opacity:.1}.gclose .garrow,.gnext .garrow,.gprev .garrow{stroke:#fff}.gbtn.focused{outline:2px solid #0f3d81}iframe.wait-autoplay{opacity:0}.glightbox-closing .gclose,.glightbox-closing .gnext,.glightbox-closing .gprev{opacity:0!important}.glightbox-clean .gslide-description{background:#fff}.glightbox-clean .gdesc-inner{padding:22px 20px}.glightbox-clean .gslide-title{font-size:1em;font-weight:400;font-family:arial;color:#000;margin-bottom:19px;line-height:1.4em}.glightbox-clean .gslide-desc{font-size:.86em;margin-bottom:0;font-family:arial;line-height:1.4em}.glightbox-clean .gslide-video{background:#000}.glightbox-clean .gclose,.glightbox-clean .gnext,.glightbox-clean .gprev{background-color:rgba(0,0,0,.75);border-radius:4px}.glightbox-clean .gclose path,.glightbox-clean .gnext path,.glightbox-clean .gprev path{fill:#fff}.glightbox-clean .gprev{position:absolute;top:-100%;left:30px;width:40px;height:50px}.glightbox-clean .gnext{position:absolute;top:-100%;right:30px;width:40px;height:50px}.glightbox-clean .gclose{width:35px;height:35px;top:15px;right:10px;position:absolute}.glightbox-clean .gclose svg{width:18px;height:auto}.glightbox-clean .gclose:hover{opacity:1}.gfadeIn{-webkit-animation:gfadeIn .5s ease;animation:gfadeIn .5s ease}.gfadeOut{-webkit-animation:gfadeOut .5s ease;animation:gfadeOut .5s ease}.gslideOutLeft{-webkit-animation:gslideOutLeft .3s ease;animation:gslideOutLeft .3s ease}.gslideInLeft{-webkit-animation:gslideInLeft .3s ease;animation:gslideInLeft .3s ease}.gslideOutRight{-webkit-animation:gslideOutRight .3s ease;animation:gslideOutRight .3s ease}.gslideInRight{-webkit-animation:gslideInRight .3s ease;animation:gslideInRight .3s ease}.gzoomIn{-webkit-animation:gzoomIn .5s ease;animation:gzoomIn .5s ease}.gzoomOut{-webkit-animation:gzoomOut .5s ease;animation:gzoomOut .5s ease}@-webkit-keyframes lightboxLoader{0%{-webkit-transform:rotate(0);transform:rotate(0)}100%{-webkit-transform:rotate(360deg);transform:rotate(360deg)}}@keyframes lightboxLoader{0%{-webkit-transform:rotate(0);transform:rotate(0)}100%{-webkit-transform:rotate(360deg);transform:rotate(360deg)}}@-webkit-keyframes gfadeIn{from{opacity:0}to{opacity:1}}@keyframes gfadeIn{from{opacity:0}to{opacity:1}}@-webkit-keyframes gfadeOut{from{opacity:1}to{opacity:0}}@keyframes gfadeOut{from{opacity:1}to{opacity:0}}@-webkit-keyframes gslideInLeft{from{opacity:0;-webkit-transform:translate3d(-60%,0,0);transform:translate3d(-60%,0,0)}to{visibility:visible;-webkit-transform:translate3d(0,0,0);transform:translate3d(0,0,0);opacity:1}}@keyframes gslideInLeft{from{opacity:0;-webkit-transform:translate3d(-60%,0,0);transform:translate3d(-60%,0,0)}to{visibility:visible;-webkit-transform:translate3d(0,0,0);transform:translate3d(0,0,0);opacity:1}}@-webkit-keyframes gslideOutLeft{from{opacity:1;visibility:visible;-webkit-transform:translate3d(0,0,0);transform:translate3d(0,0,0)}to{-webkit-transform:translate3d(-60%,0,0);transform:translate3d(-60%,0,0);opacity:0;visibility:hidden}}@keyframes gslideOutLeft{from{opacity:1;visibility:visible;-webkit-transform:translate3d(0,0,0);transform:translate3d(0,0,0)}to{-webkit-transform:translate3d(-60%,0,0);transform:translate3d(-60%,0,0);opacity:0;visibility:hidden}}@-webkit-keyframes gslideInRight{from{opacity:0;visibility:visible;-webkit-transform:translate3d(60%,0,0);transform:translate3d(60%,0,0)}to{-webkit-transform:translate3d(0,0,0);transform:translate3d(0,0,0);opacity:1}}@keyframes gslideInRight{from{opacity:0;visibility:visible;-webkit-transform:translate3d(60%,0,0);transform:translate3d(60%,0,0)}to{-webkit-transform:translate3d(0,0,0);transform:translate3d(0,0,0);opacity:1}}@-webkit-keyframes gslideOutRight{from{opacity:1;visibility:visible;-webkit-transform:translate3d(0,0,0);transform:translate3d(0,0,0)}to{-webkit-transform:translate3d(60%,0,0);transform:translate3d(60%,0,0);opacity:0}}@keyframes gslideOutRight{from{opacity:1;visibility:visible;-webkit-transform:translate3d(0,0,0);transform:translate3d(0,0,0)}to{-webkit-transform:translate3d(60%,0,0);transform:translate3d(60%,0,0);opacity:0}}@-webkit-keyframes gzoomIn{from{opacity:0;-webkit-transform:scale3d(.3,.3,.3);transform:scale3d(.3,.3,.3)}to{opacity:1}}@keyframes gzoomIn{from{opacity:0;-webkit-transform:scale3d(.3,.3,.3);transform:scale3d(.3,.3,.3)}to{opacity:1}}@-webkit-keyframes gzoomOut{from{opacity:1}50%{opacity:0;-webkit-transform:scale3d(.3,.3,.3);transform:scale3d(.3,.3,.3)}to{opacity:0}}@keyframes gzoomOut{from{opacity:1}50%{opacity:0;-webkit-transform:scale3d(.3,.3,.3);transform:scale3d(.3,.3,.3)}to{opacity:0}}@media (min-width:769px){.glightbox-container .ginner-container{width:auto;height:auto;-webkit-box-orient:horizontal;-webkit-box-direction:normal;-ms-flex-direction:row;flex-direction:row}.glightbox-container .ginner-container.desc-top .gslide-description{-webkit-box-ordinal-group:1;-ms-flex-order:0;order:0}.glightbox-container .ginner-container.desc-top .gslide-image,.glightbox-container .ginner-container.desc-top .gslide-image img{-webkit-box-ordinal-group:2;-ms-flex-order:1;order:1}.glightbox-container .ginner-container.desc-left .gslide-description{-webkit-box-ordinal-group:1;-ms-flex-order:0;order:0}.glightbox-container .ginner-container.desc-left .gslide-image{-webkit-box-ordinal-group:2;-ms-flex-order:1;order:1}.gslide-image img{max-height:97vh;max-width:100%}.gslide-image img.zoomable{cursor:-webkit-zoom-in;cursor:zoom-in}.zoomed .gslide-image img.zoomable{cursor:-webkit-grab;cursor:grab}.gslide-inline{max-height:95vh}.gslide-external{max-height:100vh}.gslide-description.description-left,.gslide-description.description-right{max-width:275px}.glightbox-open{height:auto}.goverlay{background:rgba(0,0,0,.92)}.glightbox-clean .gslide-media{-webkit-box-shadow:1px 2px 9px 0 rgba(0,0,0,.65);box-shadow:1px 2px 9px 0 rgba(0,0,0,.65)}.glightbox-clean .description-left .gdesc-inner,.glightbox-clean .description-right .gdesc-inner{position:absolute;height:100%;overflow-y:auto}.glightbox-clean .gclose,.glightbox-clean .gnext,.glightbox-clean .gprev{background-color:rgba(0,0,0,.32)}.glightbox-clean .gclose:hover,.glightbox-clean .gnext:hover,.glightbox-clean .gprev:hover{background-color:rgba(0,0,0,.7)}.glightbox-clean .gprev{top:45%}.glightbox-clean .gnext{top:45%}}@media (min-width:992px){.glightbox-clean .gclose{opacity:.7;right:20px}}@media screen and (max-height:420px){.goverlay{background:#000}} | 13,749 | glightbox.min | css | en | css | data | {"qsc_code_num_words": 2063, "qsc_code_num_chars": 13749.0, "qsc_code_mean_word_length": 5.34997576, "qsc_code_frac_words_unique": 0.11778963, "qsc_code_frac_chars_top_2grams": 0.01377186, "qsc_code_frac_chars_top_3grams": 0.0084262, "qsc_code_frac_chars_top_4grams": 0.03587932, "qsc_code_frac_chars_dupe_5grams": 0.51807556, "qsc_code_frac_chars_dupe_6grams": 0.47612576, "qsc_code_frac_chars_dupe_7grams": 0.44314578, "qsc_code_frac_chars_dupe_8grams": 0.39213554, "qsc_code_frac_chars_dupe_9grams": 0.3722932, "qsc_code_frac_chars_dupe_10grams": 0.36359518, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.05163868, "qsc_code_frac_chars_whitespace": 0.01687395, "qsc_code_size_file_byte": 13749.0, "qsc_code_num_lines": 1.0, "qsc_code_num_chars_line_max": 13749.0, "qsc_code_num_chars_line_mean": 13749.0, "qsc_code_frac_chars_alphabet": 0.76488866, "qsc_code_frac_chars_comments": 0.0, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.0, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.0, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0} | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 1, "qsc_code_mean_word_length": 0, "qsc_code_frac_words_unique": 1, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 1, "qsc_code_num_chars_line_max": 1, "qsc_code_num_chars_line_mean": 1, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0} |
0000cd/wolf-set | themes/bluf/assets/js/script.new.js | // Isotope
let buttonFilters = {};
// Update all buttons matching the filter
function updateButtons(filterValue, isAdd) {
// Select all buttons that match the filter value
const buttons = document.querySelectorAll(`.filter-btn[data-filter="${filterValue}"]`);
// Update class for all matching buttons
buttons.forEach(function (button) {
if (isAdd) {
button.classList.add('is-checked');
} else {
button.classList.remove('is-checked');
}
});
}
// Flatten object into a string of filters
function concatValues(obj) {
let value = '';
for (const prop in obj) {
value += obj[prop].join('');
}
return value;
}
// initialize Isotope
const grid = document.querySelector('.grid');
const iso = new Isotope(grid, {
itemSelector: '.grid-item',
masonry: {
columnWidth: 255,
fitWidth: true,
gutter: 16,
}
});
// // navbar menu
// document.addEventListener('click', function (event) {
// // 获取所有菜单
// const menuGroups = document.querySelectorAll('.filter-button-group'); // 监听.filter-button-group 按钮
// const isMenuToggle = event.target.matches('.menu-toggle');
// // 如果点击的是菜单触发按钮
// if (isMenuToggle) {
// const toggleId = event.target.id;
// const filterGroupId = 'filter-group-' + toggleId.split('-')[2];
// const filterGroup = document.getElementById(filterGroupId);
// // 如果当前菜单未展开，则关闭所有菜单，并展开当前点击的菜单
// if (!filterGroup.classList.contains('active')) {
// // 关闭所有菜单
// menuGroups.forEach(function (menu) {
// menu.classList.remove('active');
// });
// // 展开点击的菜单
// filterGroup.classList.add('active');
// } else {
// // 如果当前菜单已展开，再次点击则关闭
// filterGroup.classList.remove('active');
// }
// } else {
// // 如果点击的不是菜单触发按钮
// // 检查点击是否发生在已展开的菜单内部
// const isInsideMenu = Array.from(menuGroups).some(function (menu) {
// return menu.contains(event.target);
// });
// // 如果点击的不是菜单内部，关闭所有菜单
// if (!isInsideMenu) {
// menuGroups.forEach(function (menu) {
// menu.classList.remove('active');
// });
// }
// }
// });
document.addEventListener('click', function (event) {
// 获取所有菜单
const menuGroups = document.querySelectorAll('.filter-button-group');
// 检查ID是否包含menu-toggle
const isMenuToggle = event.target?.id?.includes('menu-toggle');
// 如果点击的是菜单触发按钮
if (isMenuToggle) {
const toggleId = event.target.id;
const filterGroupId = 'filter-group-' + toggleId.split('-')[2];
const filterGroup = document.getElementById(filterGroupId);
// 如果当前菜单未展开，则关闭所有菜单，并展开当前点击的菜单
if (!filterGroup.classList.contains('active')) {
// 关闭所有菜单
menuGroups.forEach(function (menu) {
menu.classList.remove('active');
});
// 展开点击的菜单
filterGroup.classList.add('active');
} else {
// 如果当前菜单已展开，再次点击则关闭
filterGroup.classList.remove('active');
}
} else {
// 如果点击的不是菜单触发按钮
// 检查点击是否发生在已展开的菜单内部
const isInsideMenu = Array.from(menuGroups).some(function (menu) {
return menu.contains(event.target);
});
// 如果点击的不是菜单内部，关闭所有菜单
if (!isInsideMenu) {
menuGroups.forEach(function (menu) {
menu.classList.remove('active');
});
}
}
});
// Handle lazy-loading images
const lazyImages = document.querySelectorAll('img[loading="lazy"]');
lazyImages.forEach((img) => {
img.addEventListener('load', () => {
iso.layout(); // Trigger re-layout after each lazy-loaded image loads
});
});
// // use imagesLoaded, trigger layout after each image loads
// imagesLoaded(grid).on('progress', function (instance, image) {
// iso.layout();
// });
// // Sync top-bar-inner width with grid width
// const topBarElement = document.querySelector('.top-bar-inner');
// if (grid && topBarElement) {
// const resizeObserver = new ResizeObserver((entries) => {
// for (let entry of entries) {
// const windowWidth = window.innerWidth;
// const minWidth = windowWidth * 0.80;
// const newWidth = Math.max(entry.contentRect.width, minWidth);
// topBarElement.style.width = newWidth + 'px';
// }
// });
// resizeObserver.observe(grid);
// } else {
// console.error('Grid or top-bar-inner element not found!');
// }
const topBarElement = document.querySelector('.top-bar-inner');
let shouldIgnoreResize = false;
// 添加按钮事件监听
document.querySelectorAll('.filter-btn').forEach(btn => {
btn.addEventListener('click', () => {
shouldIgnoreResize = true;
setTimeout(() => {
shouldIgnoreResize = false;
}, 1000); // 1秒后恢复监听
});
});
if (grid && topBarElement) {
const resizeObserver = new ResizeObserver((entries) => {
// 如果在忽略期间,直接返回
if (shouldIgnoreResize) {
// console.log(`[${new Date().toLocaleString()}] Resize ignored due to filter button click`);
return;
}
for (let entry of entries) {
const windowWidth = window.innerWidth;
const minWidth = windowWidth * 0.80;
const newWidth = Math.max(entry.contentRect.width, minWidth);
topBarElement.style.width = newWidth + 'px';
// console.log(
// `[${new Date().toLocaleString()}] Top bar width changed:\n`,
// `Window width: ${windowWidth}px\n`,
// `Min width: ${minWidth}px\n`,
// `Grid width: ${entry.contentRect.width}px\n`,
// `New width set to: ${newWidth}px\n`,
// `Reason: ${entry.contentRect.width >= minWidth ? 'Grid width larger than minimum' : 'Using minimum width'}`
// );
}
});
resizeObserver.observe(grid);
} else {
console.error('Grid or top-bar-inner element not found!');
}
// Use event delegation for all filter button groups
document.querySelectorAll('.filter-button-group').forEach(function (group) {
group.addEventListener('click', function (event) {
if (!event.target.matches('.filter-btn')) {
return; // Skip clicks that are not on buttons
}
const filterValue = event.target.getAttribute('data-filter');
const filterGroup = event.target.getAttribute('data-filter-group');
// Check if filter is already in the buttonFilters
const isFilterActive = buttonFilters[filterGroup]?.includes(filterValue);
// Toggle filter in buttonFilters
if (isFilterActive) {
buttonFilters[filterGroup] = buttonFilters[filterGroup].filter(f => f !== filterValue);
updateButtons(filterValue, false); // Update all buttons to remove 'is-checked'
} else {
buttonFilters[filterGroup] = buttonFilters[filterGroup] || [];
buttonFilters[filterGroup].push(filterValue);
updateButtons(filterValue, true); // Update all buttons to add 'is-checked'
}
// Combine filters
const filterString = concatValues(buttonFilters);
// Apply filter without causing layout to be called again
iso.arrange({ filter: filterString });
});
});
// Reset filters and update buttons
function resetFilters() {
// Clear buttonFilters object
buttonFilters = {};
// Remove 'is-checked' class from all filter buttons
document.querySelectorAll('.filter-btn.is-checked').forEach(function (button) {
button.classList.remove('is-checked');
});
// No need to manually hide the button here, it will be handled by showResetButton()
// Apply filter to show all items
iso.arrange({ filter: '*' });
// Ensure the reset button visibility is updated
showResetButton();
}
// Show or hide the reset button with animation
function showResetButton() {
const hasActiveFilters = Object.keys(buttonFilters).some(key => buttonFilters[key].length > 0);
const resetButton = document.getElementById('reset-filters');
if (hasActiveFilters) {
resetButton.style.display = 'block'; // Make sure the button is visible before adding 'show'
// Trigger a reflow to ensure the animation plays
(() => resetButton.offsetWidth)();
resetButton.classList.add('show');
} else {
resetButton.classList.remove('show');
// Add a transitionend event listener to hide the button after the animation
resetButton.addEventListener('transitionend', function hideButton() {
// Check if the button is still not part of the 'show' class before hiding it
if (!resetButton.classList.contains('show')) {
resetButton.style.display = 'none';
}
resetButton.removeEventListener('transitionend', hideButton);
});
}
}
// Event listener for the reset button
document.getElementById('reset-filters').addEventListener('click', function () {
resetFilters();
});
// Modify the existing click event on filter buttons to call showResetButton
document.querySelectorAll('.filter-button-group').forEach(function (group) {
group.addEventListener('click', function (event) {
// Existing code...
// After the existing filtering logic, add:
showResetButton();
});
});
// Call showResetButton after initializing to make sure button is in correct state
showResetButton();
// If there's other code that clears filters, make sure to call showResetButton() after that action
// Function to shake the reset button
function shakeResetButton() {
const resetButton = document.getElementById('reset-filters');
resetButton.classList.add('shake');
resetButton.addEventListener('animationend', function () {
resetButton.classList.remove('shake');
});
}
// Modify the existing arrangeComplete event for Isotope to check for zero results
iso.on('arrangeComplete', function (filteredItems) {
// Check if no items are filtered
if (filteredItems.length === 0) {
// Shake the reset button to notify the user
shakeResetButton();
}
});
| 10,402 | script.new | js | en | javascript | code | {"qsc_code_num_words": 985, "qsc_code_num_chars": 10402.0, "qsc_code_mean_word_length": 6.45583756, "qsc_code_frac_words_unique": 0.26395939, "qsc_code_frac_chars_top_2grams": 0.02358861, "qsc_code_frac_chars_top_3grams": 0.03302406, "qsc_code_frac_chars_top_4grams": 0.02138701, "qsc_code_frac_chars_dupe_5grams": 0.40886932, "qsc_code_frac_chars_dupe_6grams": 0.36672433, "qsc_code_frac_chars_dupe_7grams": 0.35099858, "qsc_code_frac_chars_dupe_8grams": 0.33527284, "qsc_code_frac_chars_dupe_9grams": 0.31577292, "qsc_code_frac_chars_dupe_10grams": 0.31577292, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.00257998, "qsc_code_frac_chars_whitespace": 0.2547587, "qsc_code_size_file_byte": 10402.0, "qsc_code_num_lines": 300.0, "qsc_code_num_chars_line_max": 127.0, "qsc_code_num_chars_line_mean": 34.67333333, "qsc_code_frac_chars_alphabet": 0.81772446, "qsc_code_frac_chars_comments": 0.43914632, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.28476821, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.08124786, "qsc_code_frac_chars_long_word_length": 0.003771, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codejavascript_cate_ast": 0.0, "qsc_codejavascript_cate_var_zero": null, "qsc_codejavascript_frac_lines_func_ratio": null, "qsc_codejavascript_num_statement_line": null, "qsc_codejavascript_score_lines_no_logic": null, "qsc_codejavascript_frac_words_legal_var_name": null, "qsc_codejavascript_frac_words_legal_func_name": null, "qsc_codejavascript_frac_words_legal_class_name": null, "qsc_codejavascript_frac_lines_print": 0.0} | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codejavascript_cate_ast": 1, "qsc_codejavascript_cate_var_zero": 0, "qsc_codejavascript_frac_lines_func_ratio": 0, "qsc_codejavascript_score_lines_no_logic": 0, "qsc_codejavascript_frac_lines_print": 0} |
0000cd/wolf-set | themes/bluf/assets/css/style.css | :root {
--primary-color: {{ .Site.Params.lightColor }};
--text-color: #020617;
--text-secondary: #52525b;
--bg-primary: #f3f4f6;
--bg-primary-top: #f3f4f6E6;
--cards-white: #fafafa;
--shadow-color: rgba(0, 0, 0, 0.1);
}
@media (prefers-color-scheme: dark) {
:root:not([data-theme="light"]) {
--primary-color: {{ .Site.Params.darkColor }};
--text-color: #f4f4f5;
--text-secondary: #d4d4d8;
--bg-primary: #18181b;
--bg-primary-top: #18181bE6;
--cards-white: #262626;
--shadow-color: rgba(248, 250, 252, 0.15);
}
}
[data-theme="dark"] {
--primary-color: {{ .Site.Params.darkColor }};
--text-color: #f4f4f5;
--text-secondary: #d4d4d8;
--bg-primary: #18181b;
--bg-primary-top: #18181bE6;
--cards-white: #262626;
--shadow-color: rgba(248, 250, 252, 0.15);
}
body {
margin: 0;
padding-top: 70px;
background-color: var(--bg-primary);
color: var(--text-color);
font-family: Palatino, Palatino Linotype, Palatino LT STD, "PingFang SC", "Hiragino Sans GB", "Heiti SC", "Microsoft YaHei", "WenQuanYi Micro Hei", sans-serif;
}
a {
color: var(--text-color);
text-decoration: none;
}
.grid {
margin: 0 auto;
padding: 20px 0 20px 0;
width: 100%;
height: 100%;
opacity: 0;
visibility: hidden;
transition: opacity 0.5s, visibility 0.5s;
}
.grid.show {
opacity: 1;
visibility: visible;
}
.grid a:visited {
color: var(--text-secondary);
}
/* 网格项样式 */
.grid-item {
width: 255px;
margin: 8px 0 8px 0;
background: var(--cards-white);
color: var(--text-color);
border-radius: 16px;
overflow: hidden;
transition: box-shadow 0.3s ease-in-out;
}
.grid-item:hover {
box-shadow: 0px 0px 18px var(--shadow-color);
}
/* 网格项头部样式 */
.grid-item-header {
display: flex;
justify-content: space-between;
align-items: center;
padding: 10px 13px 4px;
}
.grid-item-img {
max-width: 255px;
background: var(--cards-white);
opacity: 0;
transition: opacity 0.5s ease;
}
.grid-item-img.loaded {
opacity: 1;
}
.grid-item-title {
font-size: 1.25em;
margin: 0;
flex: 1;
}
.grid-item-color-mark {
width: 20px;
height: 20px;
border-radius: 50%;
background: var(--primary-color);
}
/* 网格项描述样式 */
.grid-item-description {
padding: 4px 13px 10px 13px;
font-size: 0.875em;
}
.grid-item-description p {
margin: 0;
}
/* 网格项中部样式 */
.grid-item-middle {
padding: 4px 14px 4px 12px;
display: flex;
justify-content: space-between;
align-items: center;
}
.grid-item-tags {
display: flex;
flex-wrap: wrap;
gap: 5px;
}
.grid-item-tag {
background: var(--bg-primary);
color: var(--text-secondary);
border-radius: 3px;
padding: 2px 5px;
font-size: 0.75em;
}
.grid-item-date {
color: var(--text-secondary);
font-size: 0.75em;
}
/* 网格项链接样式 */
.grid-item-links {
padding: 0 13px 10px;
display: flex;
justify-content: space-around;
align-items: center;
}
.grid-item-links a {
color: var(--text-color);
text-decoration: none;
padding: 5px;
font-size: 0.75em;
}
.grid-item-links a:hover {
text-decoration: underline;
}
/* 顶部栏样式 */
.top-bar {
margin: 0 auto;
position: fixed;
top: 0;
left: 0;
width: 100vw;
box-sizing: border-box;
background: var(--bg-primary-top);
color: var(--text-color);
padding: 10px 0;
z-index: 1000;
}
.top-bar-inner {
margin: 0 auto;
display: flex;
width: 90%;
justify-content: space-between;
}
.top-bar-logo {
height: 40px;
width: 40px;
vertical-align: middle;
margin-right: 10px;
}
.top-bar-title {
font-size: 1.5em;
margin: 0 100px 0 5px;
display: flex;
align-items: center;
white-space: nowrap;
font-family: Times New Roman, "PingFang SC", "Hiragino Sans GB", "Heiti SC", "Microsoft YaHei", "WenQuanYi Micro Hei", sans-serif;
}
.top-bar-nav {
display: flex;
align-items: center;
/* width: 100%; */
gap: 10px;
/* 确保各元素间距均匀 */
flex-wrap: nowrap;
}
.top-bar-nav a {
padding: 0 10px;
}
/* 选中状态样式 */
.is-checked {
background: var(--primary-color);
color: var(--cards-white);
}
/* 菜单容器样式 */
.menu-container {
position: relative;
display: inline-block;
padding: 10px;
margin: 5px 0;
flex-shrink: 0;
/* 不允许收缩 */
cursor: pointer;
}
.exlink:hover {
text-decoration: underline
}
.theme-toggle {
background-color: transparent;
font-size: 1em;
border: none;
cursor: pointer;
}
.hot-tags-container {
display: flex;
align-items: center;
gap: 10px;
overflow: hidden;
flex-shrink: 1;
margin-left: auto;
min-width: 0;
}
/* 导航按钮样式 */
.nav-button {
display: none;
position: absolute;
top: 100%;
left: 0;
background-color: var(--cards-white);
box-shadow: 0px 3px 6px var(--shadow-color);
border-radius: 4px;
padding: 10px;
z-index: 1001;
width: max-content;
}
.nav-button.active {
display: block;
}
.nav-button .filter-btn {
display: block;
margin-bottom: 5px;
}
.nav-button .filter-btn:last-child {
margin-bottom: 0;
}
/* 过滤按钮样式 */
button.filter-btn {
border: none;
border-radius: 4px;
cursor: pointer;
outline: none;
transition: background-color 0.3s, color 0.3s;
font-family: Palatino, Palatino Linotype, Palatino LT STD, "PingFang SC", "Hiragino Sans GB", "Heiti SC", "Microsoft YaHei", "WenQuanYi Micro Hei", sans-serif;
}
button.filter-btn:hover {
background-color: var(--text-secondary);
color: var(--cards-white);
}
button.filter-btn.is-checked {
background-color: var(--primary-color);
color: var(--cards-white);
}
.menu-toggle-btn {
background: var(--bg-primary-top);
color: var(--text-secondary);
}
/* 提高hot优先级 */
.hot-tag {
padding: 0 10px;
border-radius: 4px;
color: var(--text-color);
background-color: transparent;
text-decoration: none;
transition: all 0.3s ease;
white-space: nowrap;
flex-shrink: 0;
font-size: 1em;
}
.hot-tag:hover {
background-color: var(--cards-white);
}
/* 重置过滤按钮样式 */
#reset-filters {
position: fixed;
bottom: -100px;
left: 50%;
transform: translateX(-50%);
width: 50px;
height: 50px;
border-radius: 50%;
background-color: var(--primary-color);
color: var(--cards-white);
border: none;
cursor: pointer;
font-size: 24px;
line-height: 50px;
text-align: center;
box-shadow: 0 4px 8px var(--shadow-color);
transition: bottom 0.3s ease-in-out;
z-index: 1000;
display: none;
}
#reset-filters.show {
bottom: 30px;
display: block;
}
/* 重置过滤按钮抖动动画 */
@keyframes shake {
0%,
100% {
transform: translateX(-50%);
}
12.5%,
37.5%,
62.5%,
87.5% {
transform: translateX(calc(-50% - 3px));
}
25%,
50%,
75% {
transform: translateX(calc(-50% + 3px));
}
}
#reset-filters.shake {
animation: shake 0.8s ease-in-out both;
}
/* 适配移动端顶栏 */
@media screen and (max-width: 768px) {
body {
padding-top: 120px;
}
.menu-container {
display: flex;
align-items: center;
margin: 0;
position: relative;
}
.top-bar-inner {
flex-direction: column;
align-items: center;
}
.top-bar-title {
margin: 0;
}
.top-bar-nav {
margin: 0;
display: flex;
justify-content: left;
flex-wrap: nowrap;
overflow-x: auto;
}
.menu-toggle {
margin-right: 0;
}
.site-footer {
bottom: 15px;
}
.categories {
display: none;
}
.hot-tags-container {
display: none;
}
}
/* 文章 */
.post {
max-width: 800px;
padding: 20px;
line-height: 1.4;
margin-left: auto;
margin-right: auto;
}
.post a:hover {
text-decoration: underline;
}
.single-head {
margin: 0 auto;
display: flex;
justify-content: space-between;
align-items: center;
}
.post-footer {
padding: 20px;
text-align: center;
line-height: 1.5;
}
/* 头像问候 */
.greeting-widget {
position: fixed;
bottom: -100px;
left: 50%;
transform: translateX(-50%);
display: flex;
align-items: center;
background: var(--cards-white);
padding: 10px 20px;
border-radius: 50px;
box-shadow: 0 2px 10px var(--shadow-color);
transition: bottom 0.3s ease-out;
z-index: 1000;
gap: 10px;
}
.avatar {
width: 32px;
height: 32px;
border-radius: 50%;
flex-shrink: 0;
overflow: hidden;
}
.avatar img {
width: 100%;
height: 100%;
object-fit: cover;
}
.message {
color: var(--text-color);
}
.greeting-widget.show {
bottom: 20px;
}
/* 美化相册封面 */
#cover {
position: relative;
display: inline-block;
cursor: zoom-in;
}
.cover-line {
position: absolute;
bottom: 10px;
left: 50%;
transform: translateX(-50%);
width: 96px;
height: 4px;
border-radius: 4px;
background-color: var(--bg-primary-top);
}
.cover-img {
position: relative;
display: inline-block;
}
.cover-img {
transition: transform 1s ease;
}
#cover:hover .cover-img {
transform: scale(1.03);
} | 9,361 | style | css | en | css | data | {"qsc_code_num_words": 1141, "qsc_code_num_chars": 9361.0, "qsc_code_mean_word_length": 4.80893953, "qsc_code_frac_words_unique": 0.2208589, "qsc_code_frac_chars_top_2grams": 0.03207582, "qsc_code_frac_chars_top_3grams": 0.02624385, "qsc_code_frac_chars_top_4grams": 0.02168763, "qsc_code_frac_chars_dupe_5grams": 0.34900674, "qsc_code_frac_chars_dupe_6grams": 0.25660652, "qsc_code_frac_chars_dupe_7grams": 0.22799344, "qsc_code_frac_chars_dupe_8grams": 0.21323127, "qsc_code_frac_chars_dupe_9grams": 0.1731365, "qsc_code_frac_chars_dupe_10grams": 0.10807363, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.05789022, "qsc_code_frac_chars_whitespace": 0.25264395, "qsc_code_size_file_byte": 9361.0, "qsc_code_num_lines": 525.0, "qsc_code_num_chars_line_max": 164.0, "qsc_code_num_chars_line_mean": 17.83047619, "qsc_code_frac_chars_alphabet": 0.72641509, "qsc_code_frac_chars_comments": 0.0, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.40898876, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.02307199, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0} | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 1, "qsc_code_mean_word_length": 0, "qsc_code_frac_words_unique": 1, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0} |
000haoji/deep-student | src/components/EnhancedKnowledgeBaseManagement.css | /* 增强知识库管理样式 */
.knowledge-base-management {
padding: 20px;
max-width: 1400px;
margin: 0 auto;
background: #f8fafc;
min-height: 100vh;
}
/* 头部样式 */
.management-header {
display: flex;
justify-content: space-between;
align-items: center;
margin-bottom: 20px;
padding: 20px;
background: white;
border-radius: 12px;
box-shadow: 0 2px 8px rgba(0, 0, 0, 0.1);
}
.management-header h2 {
margin: 0;
color: #1e293b;
font-size: 1.5rem;
font-weight: 600;
}
.header-actions {
display: flex;
gap: 10px;
}
/* 状态概览 */
.status-overview {
display: flex;
gap: 20px;
margin-bottom: 20px;
padding: 20px;
background: white;
border-radius: 12px;
box-shadow: 0 2px 8px rgba(0, 0, 0, 0.1);
}
.status-item {
display: flex;
flex-direction: column;
gap: 5px;
}
.status-item .label {
font-size: 0.875rem;
color: #64748b;
font-weight: 500;
}
.status-item .value {
font-size: 1.25rem;
font-weight: 600;
color: #1e293b;
}
/* 主内容区域 */
.main-content {
display: grid;
grid-template-columns: 320px 1fr;
gap: 20px;
min-height: 600px;
}
/* 分库侧栏 */
.library-sidebar {
background: white;
border-radius: 12px;
box-shadow: 0 2px 8px rgba(0, 0, 0, 0.1);
padding: 20px;
height: fit-content;
max-height: 800px;
overflow-y: auto;
}
.library-sidebar h3 {
margin: 0 0 15px 0;
color: #1e293b;
font-size: 1.125rem;
font-weight: 600;
}
.library-list {
display: flex;
flex-direction: column;
gap: 8px;
}
.library-item {
padding: 12px;
border: 2px solid #e2e8f0;
border-radius: 8px;
cursor: pointer;
transition: all 0.2s ease;
background: #f8fafc;
}
.library-item:hover {
border-color: #3b82f6;
background: #eff6ff;
}
.library-item.selected {
border-color: #3b82f6;
background: #dbeafe;
}
.library-item .library-info {
flex: 1;
}
.library-name {
font-weight: 600;
color: #1e293b;
margin-bottom: 4px;
}
.library-stats {
font-size: 0.875rem;
color: #64748b;
margin-bottom: 4px;
}
.library-description {
font-size: 0.75rem;
color: #64748b;
font-style: italic;
}
.library-actions {
display: flex;
gap: 5px;
margin-top: 8px;
}
.btn-icon {
background: none;
border: none;
padding: 4px;
border-radius: 4px;
cursor: pointer;
font-size: 0.875rem;
transition: background-color 0.2s ease;
}
.btn-icon:hover {
background-color: #e2e8f0;
}
/* 文档管理主区域 */
.documents-main {
background: white;
border-radius: 12px;
box-shadow: 0 2px 8px rgba(0, 0, 0, 0.1);
padding: 20px;
overflow-y: auto;
}
.section-header h3 {
margin: 0 0 20px 0;
color: #1e293b;
font-size: 1.25rem;
font-weight: 600;
}
/* 文件上传区域 */
.upload-zone {
border: 2px dashed #cbd5e1;
border-radius: 12px;
padding: 30px;
margin-bottom: 30px;
text-align: center;
transition: all 0.3s ease;
background: #f8fafc;
}
.upload-zone.drag-over {
border-color: #3b82f6;
background: #eff6ff;
}
.upload-zone.uploading {
opacity: 0.7;
pointer-events: none;
}
.upload-content {
display: flex;
flex-direction: column;
align-items: center;
gap: 15px;
}
.upload-icon {
font-size: 3rem;
color: #64748b;
}
.upload-text {
font-size: 1.125rem;
font-weight: 500;
color: #334155;
}
.upload-hint {
font-size: 0.875rem;
color: #64748b;
}
/* 选中文件列表 */
.selected-files {
margin-top: 20px;
padding: 20px;
background: #f1f5f9;
border-radius: 8px;
}
.selected-files h4 {
margin: 0 0 15px 0;
color: #1e293b;
}
.file-list {
display: flex;
flex-direction: column;
gap: 8px;
margin-bottom: 15px;
}
.file-item {
display: flex;
justify-content: space-between;
align-items: center;
padding: 8px 12px;
background: white;
border-radius: 6px;
border: 1px solid #e2e8f0;
}
.file-name {
flex: 1;
font-weight: 500;
color: #1e293b;
}
.file-size {
font-size: 0.875rem;
color: #64748b;
margin-right: 10px;
}
.btn-remove {
background: #fee2e2;
color: #dc2626;
border: none;
border-radius: 4px;
width: 24px;
height: 24px;
cursor: pointer;
display: flex;
align-items: center;
justify-content: center;
font-size: 0.75rem;
}
.btn-remove:hover {
background: #fecaca;
}
.upload-actions {
display: flex;
gap: 10px;
}
/* 文档列表 */
.documents-section {
margin-top: 30px;
}
.documents-header h4 {
margin: 0 0 20px 0;
color: #1e293b;
font-size: 1.125rem;
font-weight: 600;
}
.loading-state {
text-align: center;
padding: 60px 20px;
color: #64748b;
font-size: 1.125rem;
}
.empty-state {
text-align: center;
padding: 60px 20px;
}
.empty-icon {
font-size: 4rem;
margin-bottom: 15px;
}
.empty-text {
font-size: 1.25rem;
font-weight: 500;
color: #334155;
margin-bottom: 8px;
}
.empty-hint {
color: #64748b;
font-size: 0.875rem;
}
.documents-grid {
display: grid;
grid-template-columns: repeat(auto-fill, minmax(300px, 1fr));
gap: 15px;
}
.document-card {
border: 1px solid #e2e8f0;
border-radius: 8px;
padding: 15px;
background: #f8fafc;
transition: all 0.2s ease;
}
.document-card:hover {
border-color: #3b82f6;
box-shadow: 0 4px 12px rgba(0, 0, 0, 0.1);
}
.doc-header {
display: flex;
justify-content: space-between;
align-items: flex-start;
margin-bottom: 10px;
}
.doc-name {
font-weight: 600;
color: #1e293b;
flex: 1;
word-break: break-word;
}
.doc-actions {
display: flex;
gap: 5px;
}
.doc-info {
display: flex;
flex-direction: column;
gap: 6px;
}
.doc-stat {
display: flex;
justify-content: space-between;
font-size: 0.875rem;
}
.doc-stat .label {
color: #64748b;
}
.doc-stat .value {
color: #1e293b;
font-weight: 500;
}
/* 模态框样式 */
.modal-overlay {
position: fixed;
top: 0;
left: 0;
right: 0;
bottom: 0;
background: rgba(0, 0, 0, 0.5);
display: flex;
align-items: center;
justify-content: center;
z-index: 1000;
}
.modal {
background: white;
border-radius: 12px;
box-shadow: 0 20px 40px rgba(0, 0, 0, 0.2);
max-width: 500px;
width: 90%;
max-height: 90vh;
overflow: hidden;
}
.modal-header {
display: flex;
justify-content: space-between;
align-items: center;
padding: 20px;
border-bottom: 1px solid #e2e8f0;
}
.modal-header h3 {
margin: 0;
color: #1e293b;
font-size: 1.25rem;
font-weight: 600;
}
.btn-close {
background: none;
border: none;
font-size: 1.25rem;
cursor: pointer;
color: #64748b;
padding: 5px;
border-radius: 4px;
}
.btn-close:hover {
background: #f1f5f9;
color: #1e293b;
}
.modal-body {
padding: 20px;
max-height: 400px;
overflow-y: auto;
}
.modal-footer {
display: flex;
justify-content: flex-end;
gap: 10px;
padding: 20px;
border-top: 1px solid #e2e8f0;
}
/* 表单样式 */
.form-group {
margin-bottom: 20px;
}
.form-group label {
display: block;
margin-bottom: 8px;
font-weight: 500;
color: #374151;
}
.form-input,
.form-textarea {
width: 100%;
padding: 10px 12px;
border: 1px solid #d1d5db;
border-radius: 6px;
font-size: 0.875rem;
transition: border-color 0.2s ease;
}
.form-input:focus,
.form-textarea:focus {
outline: none;
border-color: #3b82f6;
box-shadow: 0 0 0 3px rgba(59, 130, 246, 0.1);
}
.form-textarea {
resize: vertical;
font-family: inherit;
}
/* 按钮样式 */
.btn {
padding: 8px 16px;
border: none;
border-radius: 6px;
font-size: 0.875rem;
font-weight: 500;
cursor: pointer;
transition: all 0.2s ease;
display: inline-flex;
align-items: center;
gap: 6px;
}
.btn:disabled {
opacity: 0.5;
cursor: not-allowed;
}
.btn-primary {
background: #3b82f6;
color: white;
}
.btn-primary:hover:not(:disabled) {
background: #2563eb;
}
.btn-secondary {
background: #64748b;
color: white;
}
.btn-secondary:hover:not(:disabled) {
background: #475569;
}
.btn-success {
background: #10b981;
color: white;
}
.btn-success:hover:not(:disabled) {
background: #059669;
}
/* 响应式设计 */
@media (max-width: 1024px) {
.main-content {
grid-template-columns: 1fr;
}
.library-sidebar {
max-height: 300px;
}
.status-overview {
flex-wrap: wrap;
gap: 15px;
}
}
@media (max-width: 768px) {
.knowledge-base-management {
padding: 10px;
}
.management-header {
flex-direction: column;
gap: 15px;
align-items: stretch;
}
.header-actions {
justify-content: center;
}
.documents-grid {
grid-template-columns: 1fr;
}
.modal {
width: 95%;
margin: 10px;
}
} | 8,404 | EnhancedKnowledgeBaseManagement | css | en | css | data | {"qsc_code_num_words": 1102, "qsc_code_num_chars": 8404.0, "qsc_code_mean_word_length": 4.85299456, "qsc_code_frac_words_unique": 0.1969147, "qsc_code_frac_chars_top_2grams": 0.01009723, "qsc_code_frac_chars_top_3grams": 0.00841436, "qsc_code_frac_chars_top_4grams": 0.02524308, "qsc_code_frac_chars_dupe_5grams": 0.37958115, "qsc_code_frac_chars_dupe_6grams": 0.30179506, "qsc_code_frac_chars_dupe_7grams": 0.24139865, "qsc_code_frac_chars_dupe_8grams": 0.17483171, "qsc_code_frac_chars_dupe_9grams": 0.13462977, "qsc_code_frac_chars_dupe_10grams": 0.12471952, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.09475262, "qsc_code_frac_chars_whitespace": 0.20633032, "qsc_code_size_file_byte": 8404.0, "qsc_code_num_lines": 568.0, "qsc_code_num_chars_line_max": 64.0, "qsc_code_num_chars_line_mean": 14.79577465, "qsc_code_frac_chars_alphabet": 0.70704648, "qsc_code_frac_chars_comments": 0.0, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.47204969, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.0, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0} | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 1, "qsc_code_mean_word_length": 0, "qsc_code_frac_words_unique": 1, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0} |
000haoji/deep-student | src/components/GraphVisualization.css | .graph-visualization-container {
display: flex;
flex-direction: column;
height: 100%;
padding: 20px;
background: #f8f9fa;
border-radius: 12px;
box-shadow: 0 2px 8px rgba(0,0,0,0.1);
}
.graph-controls {
display: flex;
justify-content: space-between;
align-items: center;
margin-bottom: 20px;
padding: 15px;
background: white;
border-radius: 8px;
box-shadow: 0 1px 4px rgba(0,0,0,0.1);
}
.control-group {
display: flex;
align-items: center;
gap: 10px;
}
.control-group label {
font-weight: 600;
color: #2c3e50;
}
.control-group select {
padding: 8px 12px;
border: 1px solid #bdc3c7;
border-radius: 6px;
background: white;
color: #2c3e50;
font-size: 14px;
}
.control-buttons {
display: flex;
gap: 10px;
}
.control-buttons button {
padding: 8px 16px;
border: none;
border-radius: 6px;
background: #3498db;
color: white;
font-size: 14px;
cursor: pointer;
transition: all 0.2s ease;
}
.control-buttons button:hover:not(:disabled) {
background: #2980b9;
transform: translateY(-1px);
}
.control-buttons button:disabled {
background: #bdc3c7;
cursor: not-allowed;
transform: none;
}
.error-message {
background: #fee;
border: 1px solid #fcc;
border-radius: 8px;
padding: 12px;
margin-bottom: 20px;
color: #c33;
font-weight: 500;
display: flex;
justify-content: space-between;
align-items: center;
}
.error-message button {
background: none;
border: none;
color: #c33;
font-size: 16px;
cursor: pointer;
padding: 0;
margin-left: 10px;
}
.graph-content {
display: flex;
gap: 20px;
flex: 1;
}
.graph-viz {
position: relative;
flex: 1;
background: white;
border-radius: 8px;
box-shadow: 0 2px 8px rgba(0,0,0,0.1);
overflow: hidden;
}
.loading-overlay {
position: absolute;
top: 0;
left: 0;
right: 0;
bottom: 0;
background: rgba(255, 255, 255, 0.9);
display: flex;
align-items: center;
justify-content: center;
z-index: 1000;
}
.loading-spinner {
padding: 20px;
background: white;
border-radius: 8px;
box-shadow: 0 2px 8px rgba(0,0,0,0.2);
color: #3498db;
font-weight: 600;
}
.node-details {
width: 300px;
background: white;
border-radius: 8px;
padding: 20px;
box-shadow: 0 2px 8px rgba(0,0,0,0.1);
max-height: 500px;
overflow-y: auto;
}
.node-details h3 {
margin: 0 0 15px 0;
color: #2c3e50;
border-bottom: 2px solid #3498db;
padding-bottom: 8px;
}
.node-info {
margin-bottom: 15px;
font-size: 14px;
line-height: 1.6;
color: #34495e;
}
.node-info pre {
background: #f8f9fa;
padding: 10px;
border-radius: 4px;
font-size: 12px;
overflow-x: auto;
margin: 10px 0 0 0;
}
.node-actions {
display: flex;
gap: 10px;
}
.node-actions button {
flex: 1;
padding: 8px 12px;
border: none;
border-radius: 6px;
cursor: pointer;
font-size: 14px;
transition: all 0.2s ease;
}
.node-actions button:first-child {
background: #3498db;
color: white;
}
.node-actions button:first-child:hover {
background: #2980b9;
}
.node-actions button:last-child {
background: #95a5a6;
color: white;
}
.node-actions button:last-child:hover {
background: #7f8c8d;
}
.graph-legend {
width: 200px;
background: white;
border-radius: 8px;
padding: 20px;
box-shadow: 0 2px 8px rgba(0,0,0,0.1);
height: fit-content;
}
.graph-legend h4 {
margin: 0 0 15px 0;
color: #2c3e50;
border-bottom: 2px solid #3498db;
padding-bottom: 8px;
}
.legend-items {
display: flex;
flex-direction: column;
gap: 12px;
}
.legend-item {
display: flex;
align-items: center;
gap: 10px;
font-size: 14px;
color: #34495e;
}
.legend-node {
width: 16px;
height: 16px;
border-radius: 50%;
border: 2px solid transparent;
}
.legend-node.problem-card {
background: #68CCE5;
border-color: #3498db;
}
.legend-node.tag {
background: #FFA500;
border-color: #e67e22;
}
.legend-edge {
width: 20px;
height: 3px;
border-radius: 2px;
}
.legend-edge.has-tag {
background: #3498db;
}
.legend-edge.parent-of {
background: #e74c3c;
}
.legend-edge.related {
background: #95a5a6;
}
.not-initialized {
display: flex;
align-items: center;
justify-content: center;
height: 300px;
background: white;
border-radius: 8px;
color: #7f8c8d;
font-size: 16px;
}
/* Neo4j visualization container styling */
#neo4j-viz {
border-radius: 8px;
}
/* Custom styling for Neo4j nodes and edges */
#neo4j-viz .vis-network {
border-radius: 8px;
}
/* Responsive design */
@media (max-width: 1200px) {
.graph-content {
flex-direction: column;
}
.node-details,
.graph-legend {
width: 100%;
}
.graph-viz {
height: 400px;
}
}
@media (max-width: 768px) {
.graph-controls {
flex-direction: column;
gap: 15px;
}
.control-buttons {
justify-content: center;
}
.graph-visualization-container {
padding: 10px;
}
} | 4,899 | GraphVisualization | css | en | css | data | {"qsc_code_num_words": 639, "qsc_code_num_chars": 4899.0, "qsc_code_mean_word_length": 4.98748044, "qsc_code_frac_words_unique": 0.23787167, "qsc_code_frac_chars_top_2grams": 0.01380609, "qsc_code_frac_chars_top_3grams": 0.01223721, "qsc_code_frac_chars_top_4grams": 0.01317854, "qsc_code_frac_chars_dupe_5grams": 0.32350173, "qsc_code_frac_chars_dupe_6grams": 0.23689991, "qsc_code_frac_chars_dupe_7grams": 0.22152495, "qsc_code_frac_chars_dupe_8grams": 0.20018826, "qsc_code_frac_chars_dupe_9grams": 0.15814245, "qsc_code_frac_chars_dupe_10grams": 0.12488233, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.08544385, "qsc_code_frac_chars_whitespace": 0.20208206, "qsc_code_size_file_byte": 4899.0, "qsc_code_num_lines": 310.0, "qsc_code_num_chars_line_max": 47.0, "qsc_code_num_chars_line_mean": 15.80322581, "qsc_code_frac_chars_alphabet": 0.72985418, "qsc_code_frac_chars_comments": 0.0, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.45488722, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.0, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0} | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_words_unique": 1, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0} |
000haoji/deep-student | src/components/ModernSidebar.tsx | import React from 'react';
import '../styles/modern-sidebar.css';
import {
FileText,
Layers,
Target,
BookOpen,
Brain,
Search,
CreditCard,
Palette,
Image,
BarChart3,
Package,
Settings,
FlaskConical,
ChevronLeft,
ChevronRight,
Network
} from 'lucide-react';
type CurrentView = 'analysis' | 'library' | 'settings' | 'mistake-detail' | 'batch' | 'review' | 'dashboard' | 'data-management' | 'unified-review' | 'create-review' | 'review-session' | 'anki-generation' | 'knowledge-base' | 'rag-query' | 'image-occlusion' | 'template-management' | 'gemini-adapter-test' | 'cogni-graph';
interface ModernSidebarProps {
currentView: CurrentView;
onViewChange: (view: CurrentView) => void;
sidebarCollapsed: boolean;
onToggleSidebar: () => void;
batchAnalysisEnabled: boolean;
geminiAdapterTestEnabled: boolean;
imageOcclusionEnabled: boolean;
startDragging: (e: React.MouseEvent) => void;
}
interface NavItem {
id: CurrentView;
label: string;
icon: React.ReactNode;
section: string;
visible?: boolean;
}
export const ModernSidebar: React.FC<ModernSidebarProps> = ({
currentView,
onViewChange,
sidebarCollapsed,
onToggleSidebar,
batchAnalysisEnabled,
geminiAdapterTestEnabled,
imageOcclusionEnabled,
startDragging
}) => {
const navItems: NavItem[] = [
// 分析工具
{ id: 'analysis', label: '分析', icon: <FileText size={20} />, section: '分析工具' },
{ id: 'batch', label: '批量分析', icon: <Layers size={20} />, section: '分析工具', visible: batchAnalysisEnabled },
{ id: 'unified-review', label: '统一回顾', icon: <Target size={20} />, section: '分析工具' },
// 知识管理
{ id: 'library', label: '错题库', icon: <BookOpen size={20} />, section: '知识管理' },
{ id: 'knowledge-base', label: '知识库', icon: <Brain size={20} />, section: '知识管理' },
{ id: 'rag-query', label: 'RAG查询', icon: <Search size={20} />, section: '知识管理' },
{ id: 'cogni-graph', label: '知识图谱', icon: <Network size={20} />, section: '知识管理' },
// ANKI工具
{ id: 'anki-generation', label: 'ANKI制卡', icon: <CreditCard size={20} />, section: 'ANKI工具' },
{ id: 'template-management', label: '模板管理', icon: <Palette size={20} />, section: 'ANKI工具' },
{ id: 'image-occlusion', label: '图片遮罩卡', icon: <Image size={20} />, section: 'ANKI工具', visible: imageOcclusionEnabled },
// 系统工具
{ id: 'dashboard', label: '数据统计', icon: <BarChart3 size={20} />, section: '系统工具' },
{ id: 'data-management', label: '数据管理', icon: <Package size={20} />, section: '系统工具' },
{ id: 'gemini-adapter-test', label: 'Gemini适配器测试', icon: <FlaskConical size={20} />, section: '系统工具', visible: geminiAdapterTestEnabled },
];
const sections = [...new Set(navItems.map(item => item.section))];
return (
<div className={`app-sidebar ${sidebarCollapsed ? 'collapsed' : ''}`}>
<div className="sidebar-header" onMouseDown={startDragging}>
<div className="app-logo">
{sidebarCollapsed ? (
<img src="/dslogo2.png" alt="Deep Student" className="logo-icon" />
) : (
<img src="/dslogo1.png" alt="Deep Student" className="logo-full" />
)}
</div>
</div>
<nav className="sidebar-nav">
{sections.map(section => {
const sectionItems = navItems.filter(item =>
item.section === section && (item.visible === undefined || item.visible)
);
if (sectionItems.length === 0) return null;
return (
<div key={section} className="nav-section">
<div className="nav-label">{!sidebarCollapsed && section}</div>
{sectionItems.map(item => (
<button
key={item.id}
className={`nav-item tooltip-test ${currentView === item.id ? 'active' : ''}`}
onClick={() => onViewChange(item.id)}
data-tooltip={sidebarCollapsed ? item.label : ''}
>
<span className="nav-icon">{item.icon}</span>
{!sidebarCollapsed && <span className="nav-text">{item.label}</span>}
</button>
))}
</div>
);
})}
</nav>
<div className="sidebar-footer">
<button
className={`nav-item tooltip-test ${currentView === 'settings' ? 'active' : ''}`}
onClick={() => onViewChange('settings')}
data-tooltip={sidebarCollapsed ? '设置' : ''}
>
<span className="nav-icon"><Settings size={20} /></span>
{!sidebarCollapsed && <span className="nav-text">设置</span>}
</button>
</div>
</div>
);
}; | 4,684 | ModernSidebar | tsx | en | tsx | code | {"qsc_code_num_words": 435, "qsc_code_num_chars": 4684.0, "qsc_code_mean_word_length": 6.22758621, "qsc_code_frac_words_unique": 0.31264368, "qsc_code_frac_chars_top_2grams": 0.03100775, "qsc_code_frac_chars_top_3grams": 0.06238464, "qsc_code_frac_chars_top_4grams": 0.02510151, "qsc_code_frac_chars_dupe_5grams": 0.13030639, "qsc_code_frac_chars_dupe_6grams": 0.07973422, "qsc_code_frac_chars_dupe_7grams": 0.0, "qsc_code_frac_chars_dupe_8grams": 0.0, "qsc_code_frac_chars_dupe_9grams": 0.0, "qsc_code_frac_chars_dupe_10grams": 0.0, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.00932467, "qsc_code_frac_chars_whitespace": 0.24444919, "qsc_code_size_file_byte": 4684.0, "qsc_code_num_lines": 129.0, "qsc_code_num_chars_line_max": 323.0, "qsc_code_num_chars_line_mean": 36.31007752, "qsc_code_frac_chars_alphabet": 0.7561458, "qsc_code_frac_chars_comments": 0.00640478, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.125, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.15918367, "qsc_code_frac_chars_long_word_length": 0.00601504, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0} |
0000cd/wolf-set | themes/bluf/layouts/_default/single.html | <!DOCTYPE html>
<html lang="{{ .Site.LanguageCode }}">
<head>
{{ partial "head.html" . }}
<title>{{ .Title }} - {{ .Site.Title }}</title>
</head>
<body>
<div class="top-bar">
<div class="top-bar-inner" style="width: 80%;">
<div class="top-bar-title">
<a href="{{ .Site.BaseURL }}"><img class="top-bar-logo" src="/logo.webp" alt="Logo"></a>
<span class="top-bar-head">{{ .Site.Params.pagename }}</span>
</div>
<nav class="top-bar-nav">
<div class="menu-container">
<button class="theme-toggle" id="themeToggle" title="切换深浅配色">
深色模式
</button>
</div>
{{ with .Site.Data.navbar.external_links }}
<div class="menu-container">
{{ range . }}
<a href="{{ .url }}" target="_blank" class="menu-toggle exlink" rel="noopener" {{ if $.Site.Params.enableUmami
}}data-umami-event="NAV-{{ .name }}" {{ end }}>{{ .name }}</a>
{{ end }}
</div>
{{ end }}
</nav>
</div>
</div>
<article class="post">
<div class="single-head">
<h1>{{ .Title }}</h1>
<span><p>{{ .Date.Format "2006-01-02" }} | <a href="{{ .Site.BaseURL }}">↩</a></p></span>
</div>
<section>
{{ .Content }}
</section>
<footer class="post-footer">
{{ partial "cc.html" . }}
<a href="/">访问【首页】发现更多… </a>
</footer>
</article>
{{ partial "footer.html" . }}
</body>
</html> | 1,736 | single | html | en | html | code | {"qsc_code_num_words": 169, "qsc_code_num_chars": 1736.0, "qsc_code_mean_word_length": 4.28402367, "qsc_code_frac_words_unique": 0.44378698, "qsc_code_frac_chars_top_2grams": 0.06629834, "qsc_code_frac_chars_top_3grams": 0.09116022, "qsc_code_frac_chars_top_4grams": 0.05801105, "qsc_code_frac_chars_dupe_5grams": 0.0, "qsc_code_frac_chars_dupe_6grams": 0.0, "qsc_code_frac_chars_dupe_7grams": 0.0, "qsc_code_frac_chars_dupe_8grams": 0.0, "qsc_code_frac_chars_dupe_9grams": 0.0, "qsc_code_frac_chars_dupe_10grams": 0.0, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.01111111, "qsc_code_frac_chars_whitespace": 0.37788018, "qsc_code_size_file_byte": 1736.0, "qsc_code_num_lines": 63.0, "qsc_code_num_chars_line_max": 131.0, "qsc_code_num_chars_line_mean": 27.55555556, "qsc_code_frac_chars_alphabet": 0.65555556, "qsc_code_frac_chars_comments": 0.0, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.2173913, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.19170984, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codehtml_cate_ast": 1.0, "qsc_codehtml_frac_words_text": 0.34389401, "qsc_codehtml_num_chars_text": 597.0} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_cate_xml_start": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_cate_autogen": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_codehtml_cate_ast": 0, "qsc_codehtml_frac_words_text": 0, "qsc_codehtml_num_chars_text": 0} |
000haoji/deep-student | src-tauri/src/cogni_graph/services/search_service.rs | use crate::cogni_graph::{
GraphConfig, ProblemCard, SearchRequest, SearchResult, Neo4jService, Tag, TagType
};
use crate::llm_manager::LLMManager;
use anyhow::{Result, anyhow};
use std::sync::Arc;
use std::collections::{HashMap, HashSet};
use tokio::sync::RwLock;
pub struct SearchService {
neo4j: Neo4jService,
llm_manager: Arc<LLMManager>,
config: GraphConfig,
}
impl SearchService {
pub async fn new(config: GraphConfig, llm_manager: Arc<LLMManager>) -> Result<Self> {
let neo4j = Neo4jService::new(config.clone()).await?;
Ok(Self {
neo4j,
llm_manager,
config,
})
}
pub async fn search(&self, request: SearchRequest) -> Result<Vec<SearchResult>> {
let limit = request.limit.unwrap_or(self.config.max_search_results);
// Step 1: Multi-path recall
let (vector_results, fulltext_results) = self.multi_path_recall(&request.query, limit).await?;
// Step 2: Merge and deduplicate results
let merged_ids = self.merge_recall_results(vector_results, fulltext_results);
// Step 3: Fetch full card data
let cards_with_scores = self.fetch_cards_with_scores(merged_ids).await?;
// Step 4: Re-rank using configurable weights
let ranked_results = self.rerank_results(cards_with_scores, &request.query).await?;
// Step 5: Apply final limit and return
Ok(ranked_results.into_iter().take(limit).collect())
}
async fn multi_path_recall(&self, query: &str, limit: usize) -> Result<(Vec<(String, f32)>, Vec<(String, f32)>)> {
// Generate query embedding for vector search
let query_embedding = {
let llm_manager = &self.llm_manager;
let model_assignments = llm_manager.get_model_assignments().await.unwrap_or(crate::models::ModelAssignments {
model1_config_id: None,
model2_config_id: None,
review_analysis_model_config_id: None,
anki_card_model_config_id: None,
embedding_model_config_id: None,
reranker_model_config_id: None,
summary_model_config_id: None,
});
let embedding_config_id = model_assignments.embedding_model_config_id
.unwrap_or_else(|| "default".to_string());
match llm_manager.call_embedding_api(vec![query.to_string()], &embedding_config_id).await {
Ok(embeddings) if !embeddings.is_empty() => embeddings[0].clone(),
_ => vec![0.0; self.config.vector_dimensions]
}
};
// Execute both searches in parallel
let (vector_future, fulltext_future) = tokio::join!(
self.neo4j.vector_search(&query_embedding, limit),
self.neo4j.fulltext_search(query, limit)
);
let vector_results = vector_future.unwrap_or_default();
let fulltext_results = fulltext_future.unwrap_or_default();
Ok((vector_results, fulltext_results))
}
fn merge_recall_results(&self, vector_results: Vec<(String, f32)>, fulltext_results: Vec<(String, f32)>) -> Vec<(String, f32, Vec<String>)> {
let mut score_map: HashMap<String, (f32, Vec<String>)> = HashMap::new();
// Add vector search results
for (id, score) in vector_results {
score_map.insert(id.clone(), (score, vec!["vector".to_string()]));
}
// Merge fulltext search results
for (id, score) in fulltext_results {
match score_map.get_mut(&id) {
Some((existing_score, matched_by)) => {
// Average the scores if found by both methods
*existing_score = (*existing_score + score) / 2.0;
matched_by.push("fulltext".to_string());
}
None => {
score_map.insert(id.clone(), (score * 0.8, vec!["fulltext".to_string()])); // Weight fulltext slightly lower
}
}
}
// Convert to vector and sort by score
let mut merged_results: Vec<(String, f32, Vec<String>)> = score_map
.into_iter()
.map(|(id, (score, matched_by))| (id, score, matched_by))
.collect();
merged_results.sort_by(|a, b| b.1.partial_cmp(&a.1).unwrap_or(std::cmp::Ordering::Equal));
merged_results
}
async fn fetch_cards_with_scores(&self, merged_results: Vec<(String, f32, Vec<String>)>) -> Result<Vec<(ProblemCard, f32, Vec<String>)>> {
let mut cards_with_scores = Vec::new();
for (id, score, matched_by) in merged_results {
if let Some(card) = self.neo4j.get_problem_card(&id).await? {
cards_with_scores.push((card, score, matched_by));
}
}
Ok(cards_with_scores)
}
async fn rerank_results(&self, cards_with_scores: Vec<(ProblemCard, f32, Vec<String>)>, query: &str) -> Result<Vec<SearchResult>> {
// Configurable weights for different factors
let vector_weight = 0.4;
let fulltext_weight = 0.3;
let access_count_weight = 0.1;
let recency_weight = 0.1;
let multi_match_bonus = 0.1;
let mut search_results = Vec::new();
let current_time = chrono::Utc::now();
for (card, base_score, matched_by) in cards_with_scores {
// Calculate component scores
let mut final_score = base_score;
// Access count factor (normalized)
let access_factor = (card.access_count as f32).ln_1p() / 10.0; // Logarithmic scaling
final_score += access_factor * access_count_weight;
// Recency factor (days since last access, inverse relationship)
let days_since_access = (current_time - card.last_accessed_at).num_days() as f32;
let recency_factor = 1.0 / (1.0 + days_since_access / 30.0); // Decay over 30 days
final_score += recency_factor * recency_weight;
// Multi-match bonus (found by both vector and fulltext)
if matched_by.len() > 1 {
final_score += multi_match_bonus;
}
// Ensure score is within reasonable bounds
final_score = final_score.min(1.0).max(0.0);
search_results.push(SearchResult {
card,
score: final_score,
matched_by,
});
}
// Sort by final score
search_results.sort_by(|a, b| b.score.partial_cmp(&a.score).unwrap_or(std::cmp::Ordering::Equal));
Ok(search_results)
}
pub async fn search_similar_cards(&self, card_id: &str, limit: Option<usize>) -> Result<Vec<SearchResult>> {
let card = match self.neo4j.get_problem_card(card_id).await? {
Some(card) => card,
None => return Err(anyhow!("Card not found: {}", card_id)),
};
// Use the card's content as search query
let query = card.get_combined_content();
let request = SearchRequest {
query,
limit,
libraries: None,
};
let mut results = self.search(request).await?;
// Remove the original card from results
results.retain(|result| result.card.id != card_id);
Ok(results)
}
pub async fn get_cards_by_tag(&self, tag_name: &str, limit: Option<usize>) -> Result<Vec<ProblemCard>> {
// This would require a Cypher query to find all cards with a specific tag
// For now, we'll implement a simple version
let query = neo4rs::Query::new(
r#"
MATCH (pc:ProblemCard)-[:HAS_TAG]->(t:Tag {name: $tag_name})
RETURN pc.id, pc.content_problem, pc.content_insight, pc.status,
pc.embedding, pc.created_at, pc.last_accessed_at,
pc.access_count, pc.source_excalidraw_path
ORDER BY pc.last_accessed_at DESC
LIMIT $limit
"#.to_string()
)
.param("tag_name", tag_name)
.param("limit", limit.unwrap_or(50) as i64);
let rows = self.neo4j.execute_simple_query(query).await
.map_err(|e| anyhow!("Failed to query cards by tag: {}", e))?;
let mut cards = Vec::new();
for row in rows {
let embedding_str: String = row.get("pc.embedding").unwrap_or_default();
let embedding = if embedding_str != "null" && !embedding_str.is_empty() {
serde_json::from_str(&embedding_str).ok()
} else {
None
};
let card = ProblemCard {
id: row.get("pc.id").unwrap_or_default(),
content_problem: row.get("pc.content_problem").unwrap_or_default(),
content_insight: row.get("pc.content_insight").unwrap_or_default(),
status: row.get("pc.status").unwrap_or_default(),
embedding,
created_at: chrono::DateTime::parse_from_rfc3339(&row.get::<String>("pc.created_at").unwrap_or_default())
.unwrap_or_default().with_timezone(&chrono::Utc),
last_accessed_at: chrono::DateTime::parse_from_rfc3339(&row.get::<String>("pc.last_accessed_at").unwrap_or_default())
.unwrap_or_default().with_timezone(&chrono::Utc),
access_count: row.get("pc.access_count").unwrap_or_default(),
source_excalidraw_path: {
let path: String = row.get("pc.source_excalidraw_path").unwrap_or_default();
if path.is_empty() { None } else { Some(path) }
},
};
cards.push(card);
}
Ok(cards)
}
pub async fn get_all_tags(&self) -> Result<Vec<crate::cogni_graph::Tag>> {
use crate::cogni_graph::Tag;
let query = neo4rs::Query::new(
r#"
MATCH (t:Tag)
RETURN t.name, t.type
ORDER BY t.name
"#.to_string()
);
let rows = self.neo4j.execute_simple_query(query).await
.map_err(|e| anyhow!("Failed to query tags: {}", e))?;
let mut tags = Vec::new();
for row in rows {
let tag = Tag {
id: row.get("t.id").unwrap_or_default(),
name: row.get("t.name").unwrap_or_default(),
tag_type: TagType::Concept, // Default to concept for now
level: row.get("t.level").unwrap_or(0) as i32,
description: None,
created_at: chrono::Utc::now(),
};
tags.push(tag);
}
Ok(tags)
}
}
// Note: SearchService doesn't implement Clone due to Neo4jService limitations | 10,812 | search_service | rs | en | rust | code | {"qsc_code_num_words": 1289, "qsc_code_num_chars": 10812.0, "qsc_code_mean_word_length": 4.67339022, "qsc_code_frac_words_unique": 0.19472459, "qsc_code_frac_chars_top_2grams": 0.02921647, "qsc_code_frac_chars_top_3grams": 0.0373506, "qsc_code_frac_chars_top_4grams": 0.01792829, "qsc_code_frac_chars_dupe_5grams": 0.15305445, "qsc_code_frac_chars_dupe_6grams": 0.13330013, "qsc_code_frac_chars_dupe_7grams": 0.08366534, "qsc_code_frac_chars_dupe_8grams": 0.0561089, "qsc_code_frac_chars_dupe_9grams": 0.0561089, "qsc_code_frac_chars_dupe_10grams": 0.0561089, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.01289983, "qsc_code_frac_chars_whitespace": 0.29735479, "qsc_code_size_file_byte": 10812.0, "qsc_code_num_lines": 275.0, "qsc_code_num_chars_line_max": 146.0, "qsc_code_num_chars_line_mean": 39.31636364, "qsc_code_frac_chars_alphabet": 0.78004475, "qsc_code_frac_chars_comments": 0.1027562, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.11675127, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.02793239, "qsc_code_frac_chars_long_word_length": 0.00257679, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0} |
000haoji/deep-student | src-tauri/src/cogni_graph/services/graph_service.rs | use crate::cogni_graph::{
GraphConfig, ProblemCard, Tag, CreateCardRequest, RecommendationRequest,
Recommendation, RelationshipType, Neo4jService, CreateTagRequest, TagHierarchy, TagType
};
use crate::llm_manager::LLMManager;
use anyhow::{Result, anyhow};
use std::sync::Arc;
use tokio::sync::RwLock;
pub struct GraphService {
neo4j: Neo4jService,
llm_manager: Arc<LLMManager>,
config: GraphConfig,
}
impl GraphService {
pub async fn new(config: GraphConfig, llm_manager: Arc<LLMManager>) -> Result<Self> {
let neo4j = Neo4jService::new(config.clone()).await?;
// Initialize Neo4j schema
neo4j.initialize_schema().await?;
Ok(Self {
neo4j,
llm_manager,
config,
})
}
pub async fn create_problem_card(&self, request: CreateCardRequest) -> Result<String> {
// Create initial problem card
let mut card = ProblemCard::new(
request.content_problem.clone(),
request.content_insight.clone(),
request.source_excalidraw_path,
);
// Generate embedding using existing LLM manager
let combined_content = card.get_combined_content();
let embedding = self.generate_embedding(&combined_content).await?;
card.embedding = Some(embedding);
// Store in Neo4j with tags
let card_id = self.neo4j.create_problem_card(card, request.tags).await?;
// Note: Skip async AI recommendations for now due to Clone limitations
// This can be implemented later using shared service instances or message passing
eprintln!("Note: AI recommendations will be generated on-demand via get_recommendations API");
Ok(card_id)
}
pub async fn get_problem_card(&self, card_id: &str) -> Result<Option<ProblemCard>> {
// Update access count
if let Err(e) = self.neo4j.update_access_count(card_id).await {
eprintln!("Failed to update access count for card {}: {}", card_id, e);
}
self.neo4j.get_problem_card(card_id).await
}
async fn generate_embedding(&self, text: &str) -> Result<Vec<f32>> {
let llm_manager = &self.llm_manager;
// Get embedding model assignment
let model_assignments = llm_manager.get_model_assignments().await.unwrap_or(crate::models::ModelAssignments {
model1_config_id: None,
model2_config_id: None,
review_analysis_model_config_id: None,
anki_card_model_config_id: None,
embedding_model_config_id: None,
reranker_model_config_id: None,
summary_model_config_id: None,
});
let embedding_config_id = model_assignments.embedding_model_config_id
.unwrap_or_else(|| "default".to_string());
match llm_manager.call_embedding_api(vec![text.to_string()], &embedding_config_id).await {
Ok(embeddings) if !embeddings.is_empty() => Ok(embeddings[0].clone()),
Ok(_) => {
eprintln!("No embeddings returned");
Ok(vec![0.0; self.config.vector_dimensions])
},
Err(e) => {
eprintln!("Failed to generate embedding: {}", e);
// Return zero vector as fallback
Ok(vec![0.0; self.config.vector_dimensions])
}
}
}
// Tag management methods
pub async fn create_tag(&self, request: CreateTagRequest) -> Result<String> {
self.neo4j.create_tag(request).await
}
pub async fn get_tag_hierarchy(&self, root_tag_id: Option<String>) -> Result<Vec<TagHierarchy>> {
self.neo4j.get_tag_hierarchy(root_tag_id).await
}
pub async fn get_tags_by_type(&self, tag_type: TagType) -> Result<Vec<Tag>> {
self.neo4j.get_tags_by_type(tag_type).await
}
async fn generate_ai_recommendations(&self, card_id: &str) -> Result<()> {
// Get the card details
let card = match self.neo4j.get_problem_card(card_id).await? {
Some(card) => card,
None => return Err(anyhow!("Card not found: {}", card_id)),
};
// Find candidate cards using multi-path recall
let candidates = self.find_candidate_cards(&card).await?;
// Generate AI recommendations for promising candidates
for (candidate_id, similarity_score) in candidates {
if similarity_score > self.config.similarity_threshold {
if let Some(candidate_card) = self.neo4j.get_problem_card(&candidate_id).await? {
// Use LLM to determine relationship type and confidence
if let Ok(recommendation) = self.analyze_relationship(&card, &candidate_card).await {
if recommendation.confidence > 0.7 {
// Create the relationship in Neo4j
if let Err(e) = self.neo4j.create_relationship(
&card.id,
&candidate_card.id,
recommendation.relationship_type.clone()
).await {
eprintln!("Failed to create relationship: {}", e);
}
}
}
}
}
}
Ok(())
}
async fn find_candidate_cards(&self, card: &ProblemCard) -> Result<Vec<(String, f32)>> {
let mut candidates = Vec::new();
// Vector similarity search
if let Some(ref embedding) = card.embedding {
if let Ok(vector_results) = self.neo4j.vector_search(embedding, 50).await {
candidates.extend(vector_results);
}
}
// Full-text search
let search_text = format!("{} {}", card.content_problem, card.content_insight);
if let Ok(fulltext_results) = self.neo4j.fulltext_search(&search_text, 50).await {
for (id, score) in fulltext_results {
// Merge with existing results or add new ones
if let Some(existing) = candidates.iter_mut().find(|(existing_id, _)| existing_id == &id) {
existing.1 = (existing.1 + score) / 2.0; // Average the scores
} else {
candidates.push((id, score * 0.8)); // Weight fulltext lower than vector
}
}
}
// Filter out the card itself
candidates.retain(|(id, _)| id != &card.id);
// Sort by combined score
candidates.sort_by(|a, b| b.1.partial_cmp(&a.1).unwrap_or(std::cmp::Ordering::Equal));
// Take top candidates
candidates.truncate(20);
Ok(candidates)
}
async fn analyze_relationship(&self, card1: &ProblemCard, card2: &ProblemCard) -> Result<Recommendation> {
let prompt = format!(
r#"Analyze the relationship between these two problem cards:
Card 1:
Problem: {}
Insight: {}
Card 2:
Problem: {}
Insight: {}
Determine the most appropriate relationship type and provide a confidence score (0.0-1.0).
Respond in JSON format:
{{
"relationship_type": "IS_VARIATION_OF" | "USES_GENERAL_METHOD" | "CONTRASTS_WITH" | "SIMILAR_CONCEPT",
"confidence": 0.0-1.0,
"reasoning": "Explanation for this relationship"
}}
Only suggest high-confidence relationships (>0.7) that would be valuable for learning."#,
card1.content_problem,
card1.content_insight,
card2.content_problem,
card2.content_insight
);
let llm_manager = &self.llm_manager;
let response = llm_manager.call_unified_model_1(
vec![], // No images
&prompt,
"数学", // Default subject
Some("Relationship analysis task")
).await.map_err(|e| anyhow!("Failed to analyze relationship: {}", e))?;
// For now, create a simple recommendation based on OCR result
// In a full implementation, this would parse JSON from the response
let relationship_type = RelationshipType::UsesGeneralMethod; // Default
let confidence = 0.8; // Default confidence
let reasoning = if !response.ocr_text.is_empty() {
response.ocr_text
} else {
"Similar problem pattern detected".to_string()
};
Ok(Recommendation {
card: card2.clone(),
relationship_type,
confidence,
reasoning,
})
}
pub async fn get_recommendations(&self, request: RecommendationRequest) -> Result<Vec<Recommendation>> {
let card = match self.neo4j.get_problem_card(&request.card_id).await? {
Some(card) => card,
None => return Err(anyhow!("Card not found: {}", request.card_id)),
};
let candidates = self.find_candidate_cards(&card).await?;
let limit = request.limit.unwrap_or(self.config.recommendation_limit);
let mut recommendations = Vec::new();
for (candidate_id, _) in candidates.into_iter().take(limit * 2) { // Get more candidates than needed
if let Some(candidate_card) = self.neo4j.get_problem_card(&candidate_id).await? {
if let Ok(recommendation) = self.analyze_relationship(&card, &candidate_card).await {
recommendations.push(recommendation);
}
if recommendations.len() >= limit {
break;
}
}
}
// Sort by confidence
recommendations.sort_by(|a, b| b.confidence.partial_cmp(&a.confidence).unwrap_or(std::cmp::Ordering::Equal));
Ok(recommendations)
}
}
// Note: GraphService doesn't implement Clone due to Neo4jService limitations
// For async spawning, we'll create a new service instance when needed
// Note: Neo4jService doesn't implement Clone due to private fields
// We'll need to handle this differently in the async spawning | 10,053 | graph_service | rs | en | rust | code | {"qsc_code_num_words": 1106, "qsc_code_num_chars": 10053.0, "qsc_code_mean_word_length": 5.29385172, "qsc_code_frac_words_unique": 0.23598553, "qsc_code_frac_chars_top_2grams": 0.02152007, "qsc_code_frac_chars_top_3grams": 0.01195559, "qsc_code_frac_chars_top_4grams": 0.01622545, "qsc_code_frac_chars_dupe_5grams": 0.15473954, "qsc_code_frac_chars_dupe_6grams": 0.13902647, "qsc_code_frac_chars_dupe_7grams": 0.1058924, "qsc_code_frac_chars_dupe_8grams": 0.1058924, "qsc_code_frac_chars_dupe_9grams": 0.0618275, "qsc_code_frac_chars_dupe_10grams": 0.0618275, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.01057231, "qsc_code_frac_chars_whitespace": 0.29434, "qsc_code_size_file_byte": 10053.0, "qsc_code_num_lines": 262.0, "qsc_code_num_chars_line_max": 118.0, "qsc_code_num_chars_line_mean": 38.37022901, "qsc_code_frac_chars_alphabet": 0.81477305, "qsc_code_frac_chars_comments": 0.13896349, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.12154696, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.05613954, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0} |
000haoji/deep-student | src-tauri/src/cogni_graph/services/neo4j_service.rs | use crate::cogni_graph::{GraphConfig, ProblemCard, Tag, RelationshipType, CreateTagRequest, TagHierarchy, TagType};
use anyhow::{Result, anyhow};
use neo4rs::{Graph, Query};
use serde_json::Value;
use std::collections::HashMap;
pub struct Neo4jService {
pub graph: Graph,
config: GraphConfig,
}
impl Neo4jService {
pub async fn new(config: GraphConfig) -> Result<Self> {
let graph = Graph::new(&config.neo4j.uri, &config.neo4j.username, &config.neo4j.password)
.await
.map_err(|e| anyhow!("Failed to connect to Neo4j at {}: {}. Please check that Neo4j is running and credentials are correct.", config.neo4j.uri, e))?;
Ok(Self { graph, config })
}
pub async fn initialize_schema(&self) -> Result<()> {
// Create constraints and indexes as per the design document
let queries = vec![
// Create unique constraints
"CREATE CONSTRAINT pc_id IF NOT EXISTS FOR (n:ProblemCard) REQUIRE n.id IS UNIQUE",
"CREATE CONSTRAINT tag_id IF NOT EXISTS FOR (n:Tag) REQUIRE n.id IS UNIQUE",
// Create full-text index for content search (Neo4j 4.x/5.x compatible syntax)
"CREATE FULLTEXT INDEX problem_card_content IF NOT EXISTS FOR (n:ProblemCard) ON EACH [n.content_problem, n.content_insight]",
// Create vector index for embeddings (Note: this requires Neo4j 5.11+ with vector search plugin)
"CREATE VECTOR INDEX problem_card_embedding IF NOT EXISTS FOR (n:ProblemCard) ON (n.embedding) OPTIONS { indexConfig: { `vector.dimensions`: 1536, `vector.similarity_function`: 'cosine' }}"
];
for query_str in queries {
let query = Query::new(query_str.to_string());
if let Err(e) = self.execute_simple_query(query).await {
// Log warning for advanced features that may not be supported
if query_str.contains("VECTOR INDEX") {
eprintln!("Warning: Vector index creation failed (may not be supported in this Neo4j version): {}", e);
} else if query_str.contains("FULLTEXT INDEX") {
eprintln!("Warning: Fulltext index creation failed (trying alternative approach): {}", e);
// Try alternative fulltext syntax for older versions
let alt_query = "CREATE FULLTEXT INDEX problem_card_content IF NOT EXISTS FOR (n:ProblemCard) ON (n.content_problem, n.content_insight)";
if let Err(e2) = self.execute_simple_query(Query::new(alt_query.to_string())).await {
eprintln!("Warning: Alternative fulltext index syntax also failed: {}", e2);
}
} else {
return Err(anyhow!("Failed to execute schema query '{}': {}", query_str, e));
}
}
}
Ok(())
}
pub async fn create_problem_card(&self, mut card: ProblemCard, tags: Vec<String>) -> Result<String> {
let card_id = card.id.clone();
// Convert embedding vector to string representation for Neo4j
let embedding_str = if let Some(ref embedding) = card.embedding {
serde_json::to_string(embedding)?
} else {
"null".to_string()
};
let query = Query::new(
r#"
CREATE (pc:ProblemCard {
id: $id,
content_problem: $content_problem,
content_insight: $content_insight,
status: $status,
embedding: $embedding,
created_at: $created_at,
last_accessed_at: $last_accessed_at,
access_count: $access_count,
source_excalidraw_path: $source_excalidraw_path
})
WITH pc
UNWIND $tags_list AS tag_name
MERGE (t:Tag {name: tag_name, tag_type: 'concept', level: 2})
ON CREATE SET t.id = randomUUID(), t.created_at = datetime()
CREATE (pc)-[:HAS_TAG]->(t)
RETURN pc.id
"#.to_string()
)
.param("id", card.id.clone())
.param("content_problem", card.content_problem.clone())
.param("content_insight", card.content_insight.clone())
.param("status", card.status.clone())
.param("embedding", embedding_str)
.param("created_at", card.created_at.to_rfc3339())
.param("last_accessed_at", card.last_accessed_at.to_rfc3339())
.param("access_count", card.access_count)
.param("source_excalidraw_path", card.source_excalidraw_path.clone().unwrap_or_default())
.param("tags_list", tags);
let mut result = self.graph.execute(query).await
.map_err(|e| anyhow!("Failed to create problem card: {}", e))?;
if let Some(row) = result.next().await? {
let id: String = row.get("pc.id").unwrap_or_default();
Ok(id)
} else {
Err(anyhow!("Failed to create problem card: no result returned"))
}
}
pub async fn get_problem_card(&self, card_id: &str) -> Result<Option<ProblemCard>> {
let query = Query::new(
r#"
MATCH (pc:ProblemCard {id: $id})
RETURN pc.id, pc.content_problem, pc.content_insight, pc.status,
pc.embedding, pc.created_at, pc.last_accessed_at,
pc.access_count, pc.source_excalidraw_path
"#.to_string()
).param("id", card_id);
let mut result = self.graph.execute(query).await
.map_err(|e| anyhow!("Failed to query problem card: {}", e))?;
if let Some(row) = result.next().await? {
let embedding_str: String = row.get("pc.embedding").unwrap_or_default();
let embedding = if embedding_str != "null" && !embedding_str.is_empty() {
serde_json::from_str(&embedding_str).ok()
} else {
None
};
let card = ProblemCard {
id: row.get("pc.id").unwrap_or_default(),
content_problem: row.get("pc.content_problem").unwrap_or_default(),
content_insight: row.get("pc.content_insight").unwrap_or_default(),
status: row.get("pc.status").unwrap_or_default(),
embedding,
created_at: chrono::DateTime::parse_from_rfc3339(&row.get::<String>("pc.created_at").unwrap_or_default())
.unwrap_or_default().with_timezone(&chrono::Utc),
last_accessed_at: chrono::DateTime::parse_from_rfc3339(&row.get::<String>("pc.last_accessed_at").unwrap_or_default())
.unwrap_or_default().with_timezone(&chrono::Utc),
access_count: row.get("pc.access_count").unwrap_or_default(),
source_excalidraw_path: {
let path: String = row.get("pc.source_excalidraw_path").unwrap_or_default();
if path.is_empty() { None } else { Some(path) }
},
};
Ok(Some(card))
} else {
Ok(None)
}
}
pub async fn vector_search(&self, query_vector: &[f32], limit: usize) -> Result<Vec<(String, f32)>> {
// Try vector index search first (if supported)
let vector_str = serde_json::to_string(query_vector)?;
let query = Query::new(
r#"
CALL db.index.vector.queryNodes('problem_card_embedding', $limit, $query_vector)
YIELD node, score
RETURN node.id, score
ORDER BY score DESC
"#.to_string()
)
.param("limit", limit as i64)
.param("query_vector", vector_str);
match self.graph.execute(query).await {
Ok(mut result) => {
let mut results = Vec::new();
while let Some(row) = result.next().await? {
let id: String = row.get("node.id").unwrap_or_default();
let score: f64 = row.get("score").unwrap_or_default();
results.push((id, score as f32));
}
Ok(results)
}
Err(_) => {
// Fallback to manual vector search if index is not available
self.manual_vector_search(query_vector, limit).await
}
}
}
async fn manual_vector_search(&self, query_vector: &[f32], limit: usize) -> Result<Vec<(String, f32)>> {
let query = Query::new(
r#"
MATCH (pc:ProblemCard)
WHERE pc.embedding IS NOT NULL AND pc.embedding <> 'null'
RETURN pc.id, pc.embedding
"#.to_string()
);
let mut result = self.graph.execute(query).await
.map_err(|e| anyhow!("Failed to execute manual vector search: {}", e))?;
let mut results = Vec::new();
while let Some(row) = result.next().await? {
let id: String = row.get("pc.id").unwrap_or_default();
let embedding_str: String = row.get("pc.embedding").unwrap_or_default();
if let Ok(embedding) = serde_json::from_str::<Vec<f32>>(&embedding_str) {
let similarity = cosine_similarity(query_vector, &embedding);
results.push((id, similarity));
}
}
// Sort by similarity score (descending) and take top results
results.sort_by(|a, b| b.1.partial_cmp(&a.1).unwrap_or(std::cmp::Ordering::Equal));
results.truncate(limit);
Ok(results)
}
pub async fn fulltext_search(&self, query: &str, limit: usize) -> Result<Vec<(String, f32)>> {
let query = Query::new(
r#"
CALL db.index.fulltext.queryNodes('problem_card_content', $query_string, {limit: $limit})
YIELD node, score
RETURN node.id, score
ORDER BY score DESC
"#.to_string()
)
.param("query_string", query)
.param("limit", limit as i64);
let mut result = self.graph.execute(query).await
.map_err(|e| anyhow!("Failed to execute fulltext search: {}", e))?;
let mut results = Vec::new();
while let Some(row) = result.next().await? {
let id: String = row.get("node.id").unwrap_or_default();
let score: f64 = row.get("score").unwrap_or_default();
results.push((id, score as f32));
}
Ok(results)
}
pub async fn get_card_relationships(&self, card_id: &str) -> Result<Vec<(String, String, f32)>> {
let query = Query::new(
r#"
MATCH (c:ProblemCard {id: $candidate_id})
OPTIONAL MATCH (c)-[r]-()
RETURN c.access_count as access_count, count(r) AS degree
"#.to_string()
).param("candidate_id", card_id);
let mut result = self.graph.execute(query).await
.map_err(|e| anyhow!("Failed to get card relationships: {}", e))?;
if let Some(row) = result.next().await? {
let access_count: i64 = row.get("access_count").unwrap_or_default();
let degree: i64 = row.get("degree").unwrap_or_default();
// Calculate a simple value score based on relationships and access
let value_score = (access_count as f32 * 0.1) + (degree as f32 * 0.5);
Ok(vec![(card_id.to_string(), "value_assessment".to_string(), value_score)])
} else {
Ok(vec![])
}
}
pub async fn create_relationship(&self, from_id: &str, to_id: &str, rel_type: RelationshipType) -> Result<()> {
let rel_type_str = rel_type.to_string();
let query = Query::new(
format!(
r#"
MATCH (from:ProblemCard {{id: $from_id}})
MATCH (to:ProblemCard {{id: $to_id}})
CREATE (from)-[:{}]->(to)
"#,
rel_type_str
)
)
.param("from_id", from_id)
.param("to_id", to_id);
self.graph.execute(query).await
.map_err(|e| anyhow!("Failed to create relationship: {}", e))?;
Ok(())
}
pub async fn update_access_count(&self, card_id: &str) -> Result<()> {
let query = Query::new(
r#"
MATCH (pc:ProblemCard {id: $id})
SET pc.last_accessed_at = $timestamp, pc.access_count = pc.access_count + 1
"#.to_string()
)
.param("id", card_id)
.param("timestamp", chrono::Utc::now().to_rfc3339());
self.graph.execute(query).await
.map_err(|e| anyhow!("Failed to update access count: {}", e))?;
Ok(())
}
// Tag management methods
pub async fn create_tag(&self, request: CreateTagRequest) -> Result<String> {
let tag = Tag::new(
request.name.clone(),
request.tag_type.clone(),
if request.parent_id.is_some() { 1 } else { 0 }, // Auto-calculate level
request.description.clone(),
);
let query = Query::new(
r#"
CREATE (t:Tag {
id: $id,
name: $name,
tag_type: $tag_type,
level: $level,
description: $description,
created_at: $created_at
})
RETURN t.id
"#.to_string()
)
.param("id", tag.id.clone())
.param("name", tag.name.clone())
.param("tag_type", tag.get_type_string())
.param("level", tag.level)
.param("description", tag.description.clone().unwrap_or_default())
.param("created_at", tag.created_at.to_rfc3339());
let mut result = self.graph.execute(query).await
.map_err(|e| anyhow!("Failed to create tag: {}", e))?;
// Create parent relationship if specified
if let Some(parent_id) = request.parent_id {
let rel_query = Query::new(
r#"
MATCH (parent:Tag {id: $parent_id})
MATCH (child:Tag {id: $child_id})
CREATE (parent)-[:PARENT_OF]->(child)
CREATE (child)-[:CHILD_OF]->(parent)
SET child.level = parent.level + 1
"#.to_string()
)
.param("parent_id", parent_id)
.param("child_id", tag.id.clone());
self.graph.execute(rel_query).await
.map_err(|e| anyhow!("Failed to create parent relationship: {}", e))?;
}
Ok(tag.id)
}
pub async fn get_tag_hierarchy(&self, root_tag_id: Option<String>) -> Result<Vec<TagHierarchy>> {
let query = if let Some(root_id) = root_tag_id {
Query::new(
r#"
MATCH (root:Tag {id: $root_id})
CALL {
WITH root
MATCH path = (root)-[:PARENT_OF*0..]->(descendant:Tag)
RETURN descendant, length(path) as depth
ORDER BY depth, descendant.name
}
RETURN descendant as tag, depth
"#.to_string()
)
.param("root_id", root_id)
} else {
Query::new(
r#"
MATCH (tag:Tag)
WHERE NOT (tag)<-[:PARENT_OF]-()
CALL {
WITH tag
MATCH path = (tag)-[:PARENT_OF*0..]->(descendant:Tag)
RETURN descendant, length(path) as depth
ORDER BY depth, descendant.name
}
RETURN descendant as tag, depth
"#.to_string()
)
};
let rows = self.execute_simple_query(query).await?;
let mut hierarchies = Vec::new();
// Build hierarchy structure (simplified version)
for row in rows {
if let (Ok(tag_node), Ok(depth)) = (row.get::<neo4rs::Node>("tag"), row.get::<i64>("depth")) {
let tag = self.node_to_tag(tag_node)?;
// For now, return a flat structure. Full hierarchy building would be more complex
hierarchies.push(TagHierarchy {
tag,
children: Vec::new(),
parent: None,
});
}
}
Ok(hierarchies)
}
pub async fn get_tags_by_type(&self, tag_type: TagType) -> Result<Vec<Tag>> {
let query = Query::new(
r#"
MATCH (t:Tag {tag_type: $tag_type})
RETURN t
ORDER BY t.level, t.name
"#.to_string()
)
.param("tag_type", tag_type.to_string());
let rows = self.execute_simple_query(query).await?;
let mut tags = Vec::new();
for row in rows {
if let Ok(tag_node) = row.get::<neo4rs::Node>("t") {
tags.push(self.node_to_tag(tag_node)?);
}
}
Ok(tags)
}
fn node_to_tag(&self, node: neo4rs::Node) -> Result<Tag> {
let id: String = node.get("id").unwrap_or_default();
let name: String = node.get("name").unwrap_or_default();
let tag_type_str: String = node.get("tag_type").unwrap_or_default();
let level: i64 = node.get("level").unwrap_or(0);
let description: String = node.get("description").unwrap_or_default();
let created_at_str: String = node.get("created_at").unwrap_or_default();
let tag_type = match tag_type_str.as_str() {
"knowledge_area" => TagType::KnowledgeArea,
"topic" => TagType::Topic,
"concept" => TagType::Concept,
"method" => TagType::Method,
"difficulty" => TagType::Difficulty,
_ => TagType::Concept,
};
let created_at = chrono::DateTime::parse_from_rfc3339(&created_at_str)
.unwrap_or_else(|_| chrono::Utc::now().into())
.with_timezone(&chrono::Utc);
Ok(Tag {
id,
name,
tag_type,
level: level as i32,
description: if description.is_empty() { None } else { Some(description) },
created_at,
})
}
// Helper method to execute queries and return results
pub async fn execute_simple_query(&self, query: Query) -> Result<Vec<neo4rs::Row>> {
let mut result = self.graph.execute(query).await
.map_err(|e| anyhow!("Failed to execute query: {}", e))?;
let mut rows = Vec::new();
while let Ok(Some(row)) = result.next().await {
rows.push(row);
}
Ok(rows)
}
}
fn cosine_similarity(a: &[f32], b: &[f32]) -> f32 {
if a.len() != b.len() {
return 0.0;
}
let dot_product: f32 = a.iter().zip(b.iter()).map(|(x, y)| x * y).sum();
let magnitude_a: f32 = a.iter().map(|x| x * x).sum::<f32>().sqrt();
let magnitude_b: f32 = b.iter().map(|x| x * x).sum::<f32>().sqrt();
if magnitude_a == 0.0 || magnitude_b == 0.0 {
0.0
} else {
dot_product / (magnitude_a * magnitude_b)
}
} | 19,219 | neo4j_service | rs | en | rust | code | {"qsc_code_num_words": 2224, "qsc_code_num_chars": 19219.0, "qsc_code_mean_word_length": 4.49280576, "qsc_code_frac_words_unique": 0.12410072, "qsc_code_frac_chars_top_2grams": 0.02401922, "qsc_code_frac_chars_top_3grams": 0.04053243, "qsc_code_frac_chars_top_4grams": 0.01321057, "qsc_code_frac_chars_dupe_5grams": 0.35108086, "qsc_code_frac_chars_dupe_6grams": 0.306245, "qsc_code_frac_chars_dupe_7grams": 0.26020817, "qsc_code_frac_chars_dupe_8grams": 0.2505004, "qsc_code_frac_chars_dupe_9grams": 0.23468775, "qsc_code_frac_chars_dupe_10grams": 0.22267814, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.01039324, "qsc_code_frac_chars_whitespace": 0.32915344, "qsc_code_size_file_byte": 19219.0, "qsc_code_num_lines": 488.0, "qsc_code_num_chars_line_max": 202.0, "qsc_code_num_chars_line_mean": 39.38319672, "qsc_code_frac_chars_alphabet": 0.76460095, "qsc_code_frac_chars_comments": 0.05036682, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.27970297, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.00742574, "qsc_code_frac_chars_string_length": 0.10820732, "qsc_code_frac_chars_long_word_length": 0.00657462, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0} |
000haoji/deep-student | src/components/MessageWithThinking.tsx | import React, { useState } from 'react';
import { MarkdownRenderer } from './MarkdownRenderer';
import { StreamingMarkdownRenderer } from './StreamingMarkdownRenderer';
import { SummaryBox } from './SummaryBox';
import { ChatMessageContentPart, ChatMessage } from '../types';
interface MessageWithThinkingProps {
content: string | ChatMessageContentPart[];
thinkingContent?: string;
isStreaming: boolean;
role: 'user' | 'assistant';
timestamp: string;
ragSources?: Array<{
document_id: string;
file_name: string;
chunk_text: string;
score: number;
chunk_index: number;
}>;
// 新增：总结框相关props
showSummaryBox?: boolean;
chatHistory?: ChatMessage[];
subject?: string;
mistakeId?: string;
reviewSessionId?: string;
}
export const MessageWithThinking: React.FC<MessageWithThinkingProps> = ({
content,
thinkingContent,
isStreaming,
role,
timestamp,
ragSources,
showSummaryBox = false,
chatHistory = [],
subject,
mistakeId,
reviewSessionId
}) => {
const [isThinkingExpanded, setIsThinkingExpanded] = useState(true);
const [isRagSourcesExpanded, setIsRagSourcesExpanded] = useState(false);
// 渲染多模态内容的函数
const renderContent = (content: string | ChatMessageContentPart[], isStreaming: boolean) => {
// 处理新的多模态数组格式
if (Array.isArray(content)) {
return content.map((part, index) => {
if (part.type === 'text') {
return (
<div key={`text-${index}`} className="content-text-part">
{isStreaming ? (
<StreamingMarkdownRenderer
content={part.text}
isStreaming={true}
/>
) : (
<MarkdownRenderer content={part.text} />
)}
</div>
);
}
if (part.type === 'image_url' && part.image_url && part.image_url.url) {
return (
<div key={`image-${index}`} className="content-image-part">
<img
src={part.image_url.url}
alt="上传的内容"
style={{
maxWidth: '100%',
maxHeight: '300px',
display: 'block',
marginTop: '8px',
marginBottom: '8px',
borderRadius: '8px',
border: '1px solid #e5e7eb'
}}
onError={(e) => {
e.currentTarget.style.display = 'none';
console.error('图片显示错误:', part.image_url.url.substring(0, 50));
}}
/>
</div>
);
}
return null;
});
}
// 兼容旧的字符串格式
else if (typeof content === 'string') {
return isStreaming ? (
<StreamingMarkdownRenderer
content={content}
isStreaming={true}
/>
) : (
<MarkdownRenderer content={content} />
);
}
// 未知内容格式的占位符
return <div className="content-unknown">未知内容格式</div>;
};
return (
<div className={`message ${role} ${isStreaming ? 'streaming' : ''}`}>
{thinkingContent && role === 'assistant' && (
<div className="thinking-container">
<div
className="thinking-header"
onClick={() => setIsThinkingExpanded(!isThinkingExpanded)}
>
<span className="thinking-icon">🧠</span>
<span className="thinking-title">AI 思考过程</span>
<span className="thinking-toggle">
{isThinkingExpanded ? '▼' : '▶'}
</span>
</div>
{isThinkingExpanded && (
<div className="thinking-content-box">
{isStreaming ? (
<StreamingMarkdownRenderer
content={thinkingContent || ''}
isStreaming={true}
/>
) : (
<MarkdownRenderer content={thinkingContent || ''} />
)}
</div>
)}
</div>
)}
<div className="message-content">
{renderContent(content, isStreaming)}
</div>
{ragSources && ragSources.length > 0 && role === 'assistant' && (
<div className="rag-sources-container" style={{
marginTop: '12px',
border: '1px solid #e0e7ff',
borderRadius: '8px',
backgroundColor: '#f8faff'
}}>
<div
className="rag-sources-header"
onClick={() => setIsRagSourcesExpanded(!isRagSourcesExpanded)}
style={{
padding: '8px 12px',
cursor: 'pointer',
display: 'flex',
alignItems: 'center',
gap: '6px',
borderBottom: isRagSourcesExpanded ? '1px solid #e0e7ff' : 'none',
fontSize: '13px',
fontWeight: '500',
color: '#4338ca'
}}
>
<span>📚</span>
<span>知识库来源 ({ragSources.length})</span>
<span style={{ marginLeft: 'auto' }}>
{isRagSourcesExpanded ? '▼' : '▶'}
</span>
</div>
{isRagSourcesExpanded && (
<div className="rag-sources-content" style={{ padding: '8px 12px' }}>
{ragSources.map((source, index) => (
<div
key={`${source.document_id}-${source.chunk_index}`}
style={{
marginBottom: index < ragSources.length - 1 ? '12px' : '0',
padding: '10px',
backgroundColor: 'white',
borderRadius: '6px',
border: '1px solid #e5e7eb'
}}
>
<div style={{
display: 'flex',
justifyContent: 'space-between',
alignItems: 'center',
marginBottom: '6px'
}}>
<div style={{
fontSize: '12px',
fontWeight: '600',
color: '#374151',
display: 'flex',
alignItems: 'center',
gap: '4px'
}}>
<span>📄</span>
<span>{source.file_name}</span>
<span style={{ color: '#6b7280', fontWeight: 'normal' }}>
(块 #{source.chunk_index + 1})
</span>
</div>
<div style={{
fontSize: '11px',
color: '#6b7280',
backgroundColor: '#f3f4f6',
padding: '2px 6px',
borderRadius: '4px'
}}>
相关度: {Math.round(source.score * 100)}%
</div>
</div>
<div style={{
fontSize: '12px',
color: '#4b5563',
lineHeight: '1.4',
fontStyle: 'italic',
backgroundColor: '#f9fafb',
padding: '8px',
borderRadius: '4px',
border: '1px solid #f3f4f6'
}}>
{source.chunk_text.length > 200
? `${source.chunk_text.substring(0, 200)}...`
: source.chunk_text
}
</div>
</div>
))}
</div>
)}
</div>
)}
{/* 总结框 - 仅在assistant消息且启用时显示 */}
{showSummaryBox && role === 'assistant' && (
<SummaryBox
chatHistory={chatHistory}
isVisible={true}
subject={subject}
mistakeId={mistakeId}
reviewSessionId={reviewSessionId}
/>
)}
<div className="message-time">
{new Date(timestamp).toLocaleTimeString()}
</div>
</div>
);
}; | 8,022 | MessageWithThinking | tsx | en | tsx | code | {"qsc_code_num_words": 536, "qsc_code_num_chars": 8022.0, "qsc_code_mean_word_length": 6.79664179, "qsc_code_frac_words_unique": 0.32649254, "qsc_code_frac_chars_top_2grams": 0.03293988, "qsc_code_frac_chars_top_3grams": 0.01317595, "qsc_code_frac_chars_top_4grams": 0.03129289, "qsc_code_frac_chars_dupe_5grams": 0.02525391, "qsc_code_frac_chars_dupe_6grams": 0.0, "qsc_code_frac_chars_dupe_7grams": 0.0, "qsc_code_frac_chars_dupe_8grams": 0.0, "qsc_code_frac_chars_dupe_9grams": 0.0, "qsc_code_frac_chars_dupe_10grams": 0.0, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.02337442, "qsc_code_frac_chars_whitespace": 0.41336325, "qsc_code_size_file_byte": 8022.0, "qsc_code_num_lines": 247.0, "qsc_code_num_chars_line_max": 96.0, "qsc_code_num_chars_line_mean": 32.47773279, "qsc_code_frac_chars_alphabet": 0.74925627, "qsc_code_frac_chars_comments": 0.01234106, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.35193133, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.08985361, "qsc_code_frac_chars_long_word_length": 0.00605755, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0} |
000haoji/deep-student | src/components/TemplateManagementPage.css | /* 模板管理页面 - 彻底重写，优先保证卡片完整显示 */
.template-management-page {
min-height: 100vh;
display: flex;
flex-direction: column;
background: #fafafa;
/* 移除所有高度限制，让内容自然扩展 */
/* height: 100vh; */
/* max-height: 100vh; */
/* overflow: hidden; */
/* 强制移除所有可能的限制 */
width: auto !important;
height: auto !important;
max-width: none !important;
max-height: none !important;
overflow: visible !important;
}
/* 页面头部 */
.page-header {
background: white;
border-bottom: 1px solid #e5e7eb;
padding: 24px 32px;
position: relative;
/* 移除flex-shrink限制，因为容器已经没有高度限制 */
/* flex-shrink: 0; */
}
.page-header::before {
content: '';
position: absolute;
top: 0;
left: 0;
right: 0;
height: 4px;
background: transparent;
}
.page-header.selecting-mode::before {
background: linear-gradient(90deg, #fbbf24, #f59e0b);
}
.page-header.management-mode::before {
background: linear-gradient(90deg, #3b82f6, #2563eb);
}
.header-content {
/* 移除宽度限制，让内容自然扩展 */
/* max-width: 1200px; */
margin: 0 auto;
}
.header-main {
display: flex;
align-items: center;
gap: 16px;
}
.title-section {
display: flex;
align-items: center;
gap: 16px;
}
/* 模式指示器 */
.mode-indicator {
display: flex;
align-items: center;
gap: 6px;
padding: 6px 12px;
border-radius: 16px;
font-size: 12px;
font-weight: 600;
text-transform: uppercase;
letter-spacing: 0.5px;
}
.mode-indicator.selecting {
background: #fef3c7;
color: #92400e;
border: 1px solid #fbbf24;
}
.mode-indicator.management {
background: #dbeafe;
color: #1e40af;
border: 1px solid #60a5fa;
}
.mode-icon {
font-size: 14px;
}
.mode-text {
font-size: 11px;
}
.back-button {
background: #f3f4f6;
border: 1px solid #d1d5db;
color: #374151;
padding: 8px 16px;
border-radius: 6px;
font-size: 14px;
cursor: pointer;
transition: all 0.2s ease;
display: flex;
align-items: center;
gap: 8px;
}
.back-button:hover {
background: #e5e7eb;
border-color: #9ca3af;
}
.back-icon {
font-size: 16px;
}
.page-title {
margin: 0 0 8px 0;
font-size: 28px;
font-weight: 600;
color: #111827;
display: flex;
align-items: center;
gap: 12px;
}
.page-icon {
font-size: 32px;
}
.page-description {
margin: 0;
color: #6b7280;
font-size: 16px;
line-height: 1.5;
}
/* 标签页导航 */
.page-tabs {
background: white;
border-bottom: 1px solid #e5e7eb;
padding: 0 32px;
display: flex;
gap: 8px;
/* 移除flex-shrink限制 */
/* flex-shrink: 0; */
}
.tab-button {
background: none;
border: none;
padding: 16px 20px;
font-size: 14px;
font-weight: 500;
color: #6b7280;
cursor: pointer;
border-bottom: 2px solid transparent;
transition: all 0.2s ease;
display: flex;
align-items: center;
gap: 8px;
white-space: nowrap;
}
.tab-button:hover {
color: #374151;
background: #f9fafb;
}
.tab-button.active {
color: #3b82f6;
border-bottom-color: #3b82f6;
background: #f8fafc;
}
.tab-icon {
font-size: 16px;
}
/* 错误提示 */
.error-alert {
background: #fef2f2;
border-bottom: 1px solid #fecaca;
padding: 12px 32px;
}
.alert-content {
display: flex;
align-items: center;
gap: 12px;
max-width: 1200px;
margin: 0 auto;
}
.alert-icon {
color: #dc2626;
font-size: 16px;
}
.alert-message {
flex: 1;
color: #dc2626;
font-size: 14px;
}
.alert-close {
background: none;
border: none;
color: #dc2626;
cursor: pointer;
font-size: 16px;
padding: 4px;
border-radius: 4px;
transition: background 0.2s;
}
.alert-close:hover {
background: rgba(220, 38, 38, 0.1);
}
/* 内容区域 - 彻底重写，移除所有限制 */
.page-content {
/* 移除flex限制，让内容自然扩展 */
/* flex: 1; */
/* 移除所有overflow限制 */
/* overflow-y: auto; */
/* overflow-x: hidden; */
/* 移除宽度限制！！！这是关键！！！ */
/* max-width: 1200px; */
margin: 0 auto;
width: 100%;
/* 增加充足的填充，确保卡片完整显示 */
padding: 0 32px 200px 32px;
/* 移除高度限制 */
/* min-height: 0; */
/* 强制移除所有可能的限制 */
width: auto !important;
height: auto !important;
max-width: none !important;
max-height: none !important;
overflow: visible !important;
}
/* 模板浏览器 - 移除所有限制 */
.template-browser {
display: flex;
flex-direction: column;
padding: 24px 0;
/* 移除所有高度和flex限制 */
/* min-height: 0; */
/* flex: 1; */
/* 强制移除所有可能的限制 */
width: auto !important;
height: auto !important;
max-width: none !important;
max-height: none !important;
overflow: visible !important;
}
.browser-toolbar {
display: flex;
justify-content: space-between;
align-items: center;
margin-bottom: 24px;
gap: 20px;
}
.search-container {
flex: 1;
max-width: 400px;
}
.search-input-wrapper {
position: relative;
}
.search-input {
width: 100%;
padding: 12px 16px 12px 44px;
border: 1px solid #d1d5db;
border-radius: 8px;
font-size: 14px;
background: white;
transition: all 0.2s ease;
}
.search-input:focus {
outline: none;
border-color: #3b82f6;
box-shadow: 0 0 0 3px rgba(59, 130, 246, 0.1);
}
.search-icon {
position: absolute;
left: 16px;
top: 50%;
transform: translateY(-50%);
color: #9ca3af;
font-size: 16px;
}
.toolbar-stats {
color: #6b7280;
font-size: 14px;
display: flex;
align-items: center;
gap: 16px;
}
.mode-hint {
display: flex;
align-items: center;
gap: 6px;
padding: 4px 8px;
background: #fef3c7;
color: #92400e;
border: 1px solid #fbbf24;
border-radius: 6px;
font-size: 12px;
}
.hint-icon {
font-size: 14px;
}
.hint-text {
font-weight: 500;
}
/* 模板网格 - 强制单列布局，彻底移除所有限制 */
.templates-grid {
display: grid;
/* 强制单列布局 */
grid-template-columns: 1fr;
gap: 20px;
/* 让每行完全自适应内容高度 */
grid-auto-rows: auto;
align-items: start;
/* 超大底部填充，确保所有卡片都能完整显示 */
padding: 0 0 300px 0;
/* 完全移除所有限制 */
overflow: visible;
/* 强制移除任何可能的尺寸限制 */
width: auto !important;
height: auto !important;
max-width: none !important;
max-height: none !important;
min-width: 0 !important;
min-height: 0 !important;
}
/* 模板卡片 - 彻底重写，移除所有高度限制 */
.template-card {
background: white;
border: 1px solid #e5e7eb;
border-radius: 12px;
padding: 20px;
transition: all 0.2s ease;
cursor: pointer;
position: relative;
/* 完全移除所有限制，让内容自然扩展 */
overflow: visible;
/* 让内容完全决定卡片高度，移除所有高度限制 */
height: auto;
/* min-height: 400px; */
display: flex;
flex-direction: column;
width: 100%;
}
.template-card:hover {
border-color: #d1d5db;
box-shadow: 0 4px 12px rgba(0, 0, 0, 0.05);
transform: translateY(-1px);
}
.template-card.selected {
border-color: #3b82f6;
box-shadow: 0 0 0 2px rgba(59, 130, 246, 0.1);
}
.template-card.inactive {
opacity: 0.6;
}
/* 选择模式的卡片样式 */
.template-card.selecting-mode {
border-left: 4px solid #fbbf24;
background: linear-gradient(135deg, #ffffff 0%, #fefbf3 100%);
}
.template-card.selecting-mode:hover {
border-left-color: #f59e0b;
box-shadow: 0 8px 25px rgba(251, 191, 36, 0.15);
}
/* 管理模式的卡片样式 */
.template-card.management-mode {
border-left: 4px solid #e5e7eb;
}
.template-card.management-mode:hover {
border-left-color: #3b82f6;
}
.card-header {
display: flex;
justify-content: space-between;
align-items: flex-start;
margin-bottom: 16px;
}
.template-name {
font-size: 18px;
font-weight: 600;
color: #111827;
margin: 0;
line-height: 1.3;
flex: 1;
margin-right: 12px;
}
.template-badges {
display: flex;
gap: 6px;
flex-wrap: wrap;
}
.badge {
padding: 2px 8px;
border-radius: 12px;
font-size: 11px;
font-weight: 500;
text-transform: uppercase;
letter-spacing: 0.5px;
}
.badge.built-in {
background: #eff6ff;
color: #1d4ed8;
}
.badge.inactive {
background: #f3f4f6;
color: #6b7280;
}
.badge.version {
background: #f0fdf4;
color: #166534;
}
/* 预览区域 */
.card-preview {
display: grid;
grid-template-columns: 1fr 1fr;
gap: 12px;
margin-bottom: 16px;
/* 确保预览区域可以自适应内容高度 */
grid-auto-rows: auto;
align-items: start;
}
.preview-section {
background: #f9fafb !important;
border: 1px solid #f3f4f6;
border-radius: 6px;
padding: 12px;
/* 移除所有高度限制，让内容完全自然显示 */
/* min-height: 120px; */
display: flex;
flex-direction: column;
/* 让内容完全决定预览区域高度 */
height: auto;
}
.preview-label {
font-size: 11px;
font-weight: 600;
color: #6b7280;
text-transform: uppercase;
letter-spacing: 0.5px;
margin-bottom: 6px;
flex-shrink: 0;
}
.preview-content {
font-size: 13px;
color: #374151 !important;
line-height: 1.4;
/* 完全移除所有overflow限制，让内容自然显示 */
overflow: visible;
flex: 1;
word-wrap: break-word;
overflow-wrap: break-word;
hyphens: auto;
/* 移除所有高度限制 */
/* min-height: 60px; */
/* max-height: 300px; */
}
/* 预览内容的样式重置和优化 */
.preview-content * {
max-width: 100% !important;
box-sizing: border-box;
/* 强制设置所有子元素的文字颜色 */
color: #374151 !important;
}
.preview-content img {
max-width: 100% !important;
height: auto !important;
object-fit: contain;
}
.preview-content .card {
padding: 8px !important;
margin: 0 !important;
background: white !important;
border-radius: 4px !important;
font-size: 12px !important;
line-height: 1.3 !important;
color: #374151 !important;
}
.preview-content .cloze {
background: #fef3c7 !important;
color: #92400e !important;
padding: 1px 4px !important;
border-radius: 3px !important;
font-weight: 500 !important;
}
.preview-content .tag {
background: #e5e7eb !important;
color: #374151 !important;
padding: 1px 4px !important;
border-radius: 3px !important;
font-size: 10px !important;
margin: 0 2px !important;
}
.preview-content code {
background: #f3f4f6 !important;
color: #1f2937 !important;
padding: 2px 4px !important;
border-radius: 3px !important;
font-family: 'Monaco', 'Menlo', monospace !important;
font-size: 11px !important;
white-space: pre-wrap !important;
}
.preview-content pre {
background: #f3f4f6 !important;
padding: 8px !important;
border-radius: 4px !important;
overflow-x: auto !important;
font-size: 11px !important;
line-height: 1.3 !important;
}
/* 确保预览区域的滚动条样式 */
.preview-content::-webkit-scrollbar {
width: 4px;
}
.preview-content::-webkit-scrollbar-track {
background: transparent;
}
.preview-content::-webkit-scrollbar-thumb {
background: #d1d5db;
border-radius: 2px;
}
.preview-content::-webkit-scrollbar-thumb:hover {
background: #9ca3af;
}
/* 强制修复预览内容中的文字显示问题 */
.preview-content,
.preview-content p,
.preview-content div,
.preview-content span,
.preview-content h1,
.preview-content h2,
.preview-content h3,
.preview-content h4,
.preview-content h5,
.preview-content h6,
.preview-content li,
.preview-content td,
.preview-content th {
color: #374151 !important;
background-color: transparent !important;
}
/* 确保内联样式的文本也能正常显示 */
.preview-content [style*="color"] {
color: #374151 !important;
}
/* 选择题卡片特殊样式修复 */
.preview-content .choice-card {
background: #f8fafc !important;
color: #374151 !important;
}
.preview-content .choice-card .option {
color: #374151 !important;
background-color: transparent !important;
}
.preview-content .choice-card .option-text {
color: #374151 !important;
}
.preview-content .choice-card .option-label {
color: #374151 !important;
}
.preview-content .choice-card .question-text {
color: #374151 !important;
}
.preview-content .choice-card .instruction {
color: #374151 !important;
}
/* 卡片信息 */
.card-info {
margin-bottom: 16px;
flex: 1;
}
.template-description {
font-size: 14px;
color: #6b7280;
line-height: 1.5;
margin-bottom: 12px;
overflow: hidden;
text-overflow: ellipsis;
display: -webkit-box;
-webkit-line-clamp: 2;
-webkit-box-orient: vertical;
}
.template-meta {
display: flex;
gap: 16px;
margin-bottom: 12px;
font-size: 12px;
}
.meta-item {
display: flex;
align-items: center;
gap: 4px;
color: #9ca3af;
}
.meta-icon {
font-size: 12px;
}
.template-fields {
display: flex;
gap: 6px;
flex-wrap: wrap;
}
.field-tag {
background: #f3f4f6;
color: #374151;
padding: 2px 8px;
border-radius: 12px;
font-size: 11px;
font-weight: 500;
}
.field-tag.more {
background: #e5e7eb;
color: #6b7280;
}
/* 模式横幅 */
.mode-banner {
display: flex;
align-items: center;
gap: 6px;
padding: 8px 12px;
background: #fef3c7;
border: 1px solid #fbbf24;
border-radius: 6px;
margin-bottom: 12px;
font-size: 12px;
color: #92400e;
flex-shrink: 0;
}
.banner-icon {
font-size: 14px;
}
.banner-text {
font-weight: 500;
}
/* 卡片操作 */
.card-actions {
display: flex;
justify-content: space-between;
align-items: center;
gap: 12px;
margin-top: auto;
flex-shrink: 0;
}
.btn-select {
background: #3b82f6;
color: white;
border: none;
padding: 8px 16px;
border-radius: 6px;
font-size: 13px;
font-weight: 500;
cursor: pointer;
transition: all 0.2s ease;
flex: 1;
}
.btn-select:hover {
background: #2563eb;
transform: translateY(-1px);
}
.btn-select.primary {
background: #059669;
width: 100%;
}
.btn-select.primary:hover {
background: #047857;
}
.btn-icon {
margin-right: 6px;
font-size: 14px;
}
.action-buttons {
display: flex;
gap: 4px;
}
.action-btn {
background: #f9fafb;
border: 1px solid #e5e7eb;
color: #6b7280;
width: 32px;
height: 32px;
border-radius: 6px;
font-size: 14px;
cursor: pointer;
transition: all 0.2s ease;
display: flex;
align-items: center;
justify-content: center;
}
.action-btn:hover {
background: #f3f4f6;
border-color: #d1d5db;
color: #374151;
}
.action-btn.danger:hover {
background: #fef2f2;
border-color: #fecaca;
color: #dc2626;
}
/* 加载状态 */
.loading-container {
display: flex;
flex-direction: column;
align-items: center;
justify-content: center;
padding: 60px 20px;
color: #6b7280;
}
.loading-spinner {
width: 40px;
height: 40px;
border: 3px solid #f3f4f6;
border-top: 3px solid #3b82f6;
border-radius: 50%;
animation: spin 1s linear infinite;
margin-bottom: 16px;
}
.loading-text {
font-size: 14px;
}
@keyframes spin {
0% { transform: rotate(0deg); }
100% { transform: rotate(360deg); }
}
/* 空状态 */
.empty-state {
display: flex;
flex-direction: column;
align-items: center;
justify-content: center;
padding: 60px 20px;
text-align: center;
}
.empty-icon {
font-size: 64px;
margin-bottom: 20px;
opacity: 0.4;
}
.empty-title {
font-size: 20px;
color: #374151;
margin: 0 0 8px 0;
font-weight: 600;
}
.empty-description {
color: #6b7280;
margin: 0;
max-width: 300px;
line-height: 1.5;
}
/* 模板编辑器 */
.template-editor {
display: flex;
flex-direction: column;
padding: 24px 0;
}
.editor-header {
margin-bottom: 24px;
}
.editor-title {
margin: 0;
font-size: 24px;
color: #111827;
font-weight: 600;
}
.editor-tabs {
display: flex;
border-bottom: 1px solid #e5e7eb;
margin-bottom: 24px;
gap: 8px;
}
.editor-tab {
background: none;
border: none;
padding: 12px 16px;
font-size: 14px;
font-weight: 500;
color: #6b7280;
cursor: pointer;
border-bottom: 2px solid transparent;
transition: all 0.2s ease;
display: flex;
align-items: center;
gap: 8px;
}
.editor-tab:hover {
color: #374151;
}
.editor-tab.active {
color: #3b82f6;
border-bottom-color: #3b82f6;
}
.editor-form {
flex: 1;
overflow-y: auto;
}
.editor-section {
background: white;
border: 1px solid #e5e7eb;
border-radius: 12px;
padding: 24px;
}
/* 表单样式 */
.form-grid {
display: grid;
grid-template-columns: 1fr 1fr;
gap: 20px;
}
.form-group {
display: flex;
flex-direction: column;
}
.form-group.full-width {
grid-column: 1 / -1;
}
.form-label {
font-size: 14px;
font-weight: 500;
color: #374151;
margin-bottom: 6px;
}
.form-input,
.form-textarea {
padding: 12px 16px;
border: 1px solid #d1d5db;
border-radius: 8px;
font-size: 14px;
transition: all 0.2s ease;
font-family: inherit;
background: white;
}
.form-input:focus,
.form-textarea:focus {
outline: none;
border-color: #3b82f6;
box-shadow: 0 0 0 3px rgba(59, 130, 246, 0.1);
}
.form-textarea {
resize: vertical;
min-height: 80px;
}
.form-help {
font-size: 12px;
color: #6b7280;
margin-top: 4px;
}
/* 代码编辑器 */
.template-code-editor {
display: grid;
grid-template-columns: 1fr 1fr;
gap: 24px;
}
.code-group {
display: flex;
flex-direction: column;
}
.code-textarea {
padding: 16px;
border: 1px solid #d1d5db;
border-radius: 8px;
font-family: 'Monaco', 'Menlo', 'Ubuntu Mono', monospace;
font-size: 13px;
line-height: 1.5;
background: #f8fafc;
resize: vertical;
transition: all 0.2s ease;
}
.code-textarea:focus {
outline: none;
border-color: #3b82f6;
box-shadow: 0 0 0 3px rgba(59, 130, 246, 0.1);
background: white;
}
/* 样式编辑器 */
.styles-editor {
display: flex;
flex-direction: column;
}
.css-textarea {
padding: 16px;
border: 1px solid #d1d5db;
border-radius: 8px;
font-family: 'Monaco', 'Menlo', 'Ubuntu Mono', monospace;
font-size: 13px;
line-height: 1.5;
background: #f8fafc;
resize: vertical;
min-height: 300px;
transition: all 0.2s ease;
}
.css-textarea:focus {
outline: none;
border-color: #3b82f6;
box-shadow: 0 0 0 3px rgba(59, 130, 246, 0.1);
background: white;
}
/* 高级设置 */
.advanced-settings {
display: flex;
flex-direction: column;
}
.prompt-textarea {
padding: 16px;
border: 1px solid #d1d5db;
border-radius: 8px;
font-size: 14px;
line-height: 1.6;
resize: vertical;
min-height: 200px;
transition: all 0.2s ease;
background: white;
}
.prompt-textarea:focus {
outline: none;
border-color: #3b82f6;
box-shadow: 0 0 0 3px rgba(59, 130, 246, 0.1);
}
/* 编辑器操作按钮 */
.editor-actions {
display: flex;
gap: 12px;
justify-content: flex-end;
padding: 24px 0 0;
margin-top: 24px;
border-top: 1px solid #e5e7eb;
}
.btn-primary {
background: #3b82f6;
color: white;
border: none;
padding: 12px 24px;
border-radius: 8px;
font-size: 14px;
font-weight: 500;
cursor: pointer;
transition: all 0.2s ease;
}
.btn-primary:hover {
background: #2563eb;
transform: translateY(-1px);
}
.btn-primary:disabled {
opacity: 0.6;
cursor: not-allowed;
transform: none;
}
.btn-secondary {
background: #f9fafb;
color: #374151;
border: 1px solid #d1d5db;
padding: 12px 24px;
border-radius: 8px;
font-size: 14px;
font-weight: 500;
cursor: pointer;
transition: all 0.2s ease;
}
.btn-secondary:hover {
background: #f3f4f6;
border-color: #9ca3af;
}
/* 响应式设计 */
@media (max-width: 1200px) {
.page-content {
/* 移除宽度限制，保持padding */
padding: 0 24px 200px 24px;
}
.templates-grid {
/* 强制单列布局 */
grid-template-columns: 1fr;
gap: 16px;
grid-auto-rows: auto;
}
.template-code-editor {
grid-template-columns: 1fr;
gap: 16px;
}
.form-grid {
grid-template-columns: 1fr;
gap: 16px;
}
}
@media (max-width: 768px) {
.page-header {
padding: 16px 20px;
}
.page-title {
font-size: 24px;
}
.page-tabs,
.page-content {
padding-left: 20px;
padding-right: 20px;
}
.browser-toolbar {
flex-direction: column;
gap: 12px;
align-items: stretch;
}
.search-container {
max-width: none;
}
.templates-grid {
/* 强制单列布局 */
grid-template-columns: 1fr;
gap: 16px;
grid-auto-rows: auto;
}
.card-preview {
grid-template-columns: 1fr;
}
.template-meta {
flex-direction: column;
gap: 8px;
}
}
/* 滚动条样式优化 */
.page-content::-webkit-scrollbar {
width: 8px;
}
.page-content::-webkit-scrollbar-track {
background: #f1f5f9;
border-radius: 4px;
}
.page-content::-webkit-scrollbar-thumb {
background: #cbd5e1;
border-radius: 4px;
transition: background 0.2s ease;
}
.page-content::-webkit-scrollbar-thumb:hover {
background: #94a3b8;
}
/* 确保内容可以完全滚动到底部 */
/* 这个规则会被合并到上面的.page-content定义中 */ | 19,790 | TemplateManagementPage | css | en | css | data | {"qsc_code_num_words": 2444, "qsc_code_num_chars": 19790.0, "qsc_code_mean_word_length": 5.25736498, "qsc_code_frac_words_unique": 0.14607201, "qsc_code_frac_chars_top_2grams": 0.03050821, "qsc_code_frac_chars_top_3grams": 0.01681065, "qsc_code_frac_chars_top_4grams": 0.02124679, "qsc_code_frac_chars_dupe_5grams": 0.4732664, "qsc_code_frac_chars_dupe_6grams": 0.403689, "qsc_code_frac_chars_dupe_7grams": 0.34983267, "qsc_code_frac_chars_dupe_8grams": 0.26920383, "qsc_code_frac_chars_dupe_9grams": 0.20772045, "qsc_code_frac_chars_dupe_10grams": 0.19947078, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.07730955, "qsc_code_frac_chars_whitespace": 0.19540172, "qsc_code_size_file_byte": 19790.0, "qsc_code_num_lines": 1178.0, "qsc_code_num_chars_line_max": 65.0, "qsc_code_num_chars_line_mean": 16.79966044, "qsc_code_frac_chars_alphabet": 0.72963638, "qsc_code_frac_chars_comments": 0.0, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.49950932, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.00303168, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0} | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 1, "qsc_code_mean_word_length": 0, "qsc_code_frac_words_unique": 1, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0} |
000haoji/deep-student | src/components/SimplifiedChatInterface.tsx | /**
* Simplified Chat Interface
*
* Replaces the complex AI SDK implementation with a simpler approach
* that uses the unified stream handler directly.
*/
import React, { useState, useRef, useEffect } from 'react';
import { useUnifiedStream, StreamMessage, MarkdownRenderer, MessageWithThinking } from '../chat-core';
interface SimplifiedChatInterfaceProps {
tempId?: string;
mistakeId?: number;
initialMessages?: StreamMessage[];
enableChainOfThought?: boolean;
onAnalysisStart?: () => void;
onAnalysisComplete?: (response: any) => void;
className?: string;
}
export const SimplifiedChatInterface = React.forwardRef<any, SimplifiedChatInterfaceProps>(({
tempId,
mistakeId: _mistakeId,
initialMessages = [],
enableChainOfThought = true,
onAnalysisStart,
onAnalysisComplete,
className = ''
}, ref) => {
const [messages, setMessages] = useState<StreamMessage[]>(initialMessages);
const [input, setInput] = useState('');
const [currentStreamId, setCurrentStreamId] = useState<string | null>(null);
const messagesEndRef = useRef<HTMLDivElement>(null);
const {
startStream,
stopStream,
isStreamActive
} = useUnifiedStream();
// Auto-scroll to bottom when new messages appear
useEffect(() => {
if (messagesEndRef.current) {
messagesEndRef.current.scrollIntoView({ behavior: 'smooth' });
}
}, [messages, streamProgress]);
// Update messages from streaming progress
useEffect(() => {
if (currentStreamId && streamProgress[currentStreamId]) {
const progress = streamProgress[currentStreamId];
setMessages(prev => {
const updated = [...prev];
const lastMessage = updated[updated.length - 1];
if (lastMessage && lastMessage.role === 'assistant') {
// Update the last assistant message with streaming content
updated[updated.length - 1] = {
...lastMessage,
content: progress.content,
thinking_content: progress.thinking
};
}
return updated;
});
}
}, [currentStreamId, streamProgress]);
// Handle form submission
const handleSubmit = async (e: React.FormEvent) => {
e.preventDefault();
if (!input.trim() || isStreaming) return;
const userMessage: StreamMessage = {
id: `msg-${Date.now()}`,
role: 'user',
content: input.trim(),
timestamp: new Date().toISOString()
};
// Add user message immediately
setMessages(prev => [...prev, userMessage]);
setInput('');
// Create placeholder assistant message
const assistantMessage: StreamMessage = {
id: `msg-${Date.now() + 1}`,
role: 'assistant',
content: '',
thinking_content: '',
timestamp: new Date().toISOString()
};
setMessages(prev => [...prev, assistantMessage]);
try {
if (onAnalysisStart) {
onAnalysisStart();
}
const updatedChatHistory = [...messages, userMessage];
// Start streaming
const streamId = await startStream(
'chat_stream',
JSON.stringify({
type: tempId ? 'continue_chat' : 'chat',
tempId,
chatHistory: updatedChatHistory,
enableChainOfThought
}),
{
onComplete: (content, thinking) => {
// Final update with complete content
setMessages(prev => {
const updated = [...prev];
const lastMessage = updated[updated.length - 1];
if (lastMessage && lastMessage.role === 'assistant') {
updated[updated.length - 1] = {
...lastMessage,
content,
thinking_content: thinking
};
}
return updated;
});
setCurrentStreamId(null);
if (onAnalysisComplete) {
onAnalysisComplete({ content, thinking });
}
},
onError: (error) => {
console.error('Chat stream error:', error);
setCurrentStreamId(null);
// Update the last message to show error
setMessages(prev => {
const updated = [...prev];
const lastMessage = updated[updated.length - 1];
if (lastMessage && lastMessage.role === 'assistant') {
updated[updated.length - 1] = {
...lastMessage,
content: `错误: ${error}`
};
}
return updated;
});
}
}
);
setCurrentStreamId(streamId);
} catch (error) {
console.error('Failed to start chat stream:', error);
}
};
// Handle keyboard shortcuts
const handleKeyDown = (e: React.KeyboardEvent<HTMLTextAreaElement>) => {
if (e.key === 'Enter' && !e.shiftKey) {
e.preventDefault();
handleSubmit(e as any);
}
};
// Send message programmatically
const sendMessage = async (content: string) => {
setInput(content);
// Trigger form submission
setTimeout(() => {
const form = document.querySelector('.chat-input-form') as HTMLFormElement;
if (form) {
form.requestSubmit();
}
}, 0);
};
// Clear chat
const clearChat = () => {
setMessages(initialMessages);
setInput('');
if (currentStreamId) {
stopStream(currentStreamId);
setCurrentStreamId(null);
}
};
// Stop current stream
const stopCurrentStream = () => {
if (currentStreamId) {
stopStream(currentStreamId);
setCurrentStreamId(null);
}
};
// Expose methods to parent
React.useImperativeHandle(ref, () => ({
sendMessage,
clearChat,
stopStream: stopCurrentStream
}));
return (
<div className={`simplified-chat-interface ${className}`}>
{/* Chat Messages */}
<div className="chat-messages">
{messages.map((message, index) => (
<div key={message.id} className={`message ${message.role}`}>
<div className="message-header">
<span className="role">{message.role === 'user' ? '用户' : 'AI助手'}</span>
<span className="timestamp">
{new Date(message.timestamp).toLocaleTimeString()}
</span>
</div>
<div className="message-content">
{message.role === 'assistant' ? (
<MessageWithThinking
content={message.content}
thinkingContent={message.thinking_content}
isStreaming={isStreaming && index === messages.length - 1}
role="assistant"
timestamp={message.timestamp}
/>
) : (
<div className="user-message">
<MarkdownRenderer content={message.content} />
</div>
)}
</div>
</div>
))}
{/* Loading indicator */}
{isStreaming && (
<div className="streaming-indicator">
<div className="typing-dots">
<span></span>
<span></span>
<span></span>
</div>
<span>AI正在思考和回答中...</span>
</div>
)}
{/* Auto-scroll anchor */}
<div ref={messagesEndRef} />
</div>
{/* Chat Input */}
<form onSubmit={handleSubmit} className="chat-input-form">
<div className="input-container">
<textarea
value={input}
onChange={(e) => setInput(e.target.value)}
onKeyDown={handleKeyDown}
placeholder="输入您的问题..."
disabled={isStreaming}
rows={3}
className="chat-input"
/>
<div className="input-actions">
<button
type="submit"
disabled={!input.trim() || isStreaming}
className="send-button"
>
{isStreaming ? '发送中...' : '发送'}
</button>
{isStreaming && (
<button
type="button"
onClick={stopCurrentStream}
className="stop-button"
>
停止
</button>
)}
<button
type="button"
onClick={clearChat}
disabled={isStreaming}
className="clear-button"
>
清空
</button>
</div>
</div>
</form>
{/* Chat Controls */}
<div className="chat-controls">
<label className="chain-of-thought-toggle">
<input
type="checkbox"
checked={enableChainOfThought}
onChange={() => {
// This would need to be controlled by parent component
}}
disabled={isStreaming}
/>
<span>显示思维过程</span>
</label>
<div className="chat-stats">
<span>消息数: {messages.length}</span>
{isStreaming && <span className="analyzing">分析中...</span>}
{currentStreamId && <span className="stream-id">Stream: {currentStreamId.slice(-8)}</span>}
</div>
</div>
</div>
);
}); | 9,416 | SimplifiedChatInterface | tsx | en | tsx | code | {"qsc_code_num_words": 696, "qsc_code_num_chars": 9416.0, "qsc_code_mean_word_length": 7.09770115, "qsc_code_frac_words_unique": 0.31034483, "qsc_code_frac_chars_top_2grams": 0.02672065, "qsc_code_frac_chars_top_3grams": 0.0242915, "qsc_code_frac_chars_top_4grams": 0.02550607, "qsc_code_frac_chars_dupe_5grams": 0.12834008, "qsc_code_frac_chars_dupe_6grams": 0.11336032, "qsc_code_frac_chars_dupe_7grams": 0.07955466, "qsc_code_frac_chars_dupe_8grams": 0.07955466, "qsc_code_frac_chars_dupe_9grams": 0.07955466, "qsc_code_frac_chars_dupe_10grams": 0.07955466, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.00178571, "qsc_code_frac_chars_whitespace": 0.34579439, "qsc_code_size_file_byte": 9416.0, "qsc_code_num_lines": 323.0, "qsc_code_num_chars_line_max": 103.0, "qsc_code_num_chars_line_mean": 29.15170279, "qsc_code_frac_chars_alphabet": 0.80016234, "qsc_code_frac_chars_comments": 0.08538658, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.35877863, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.0553814, "qsc_code_frac_chars_long_word_length": 0.00267038, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0} |
000haoji/deep-student | src/components/ImageOcclusion.tsx | import React, { useState, useRef, useCallback, useEffect } from 'react';
import { invoke } from '@tauri-apps/api/core';
import './ImageOcclusion.css';
interface TextRegion {
text: string;
bbox: [number, number, number, number];
confidence: number;
region_id: string;
}
interface ImageOcrResponse {
success: boolean;
text_regions: TextRegion[];
full_text: string;
image_width: number;
image_height: number;
error_message?: string;
}
interface OcclusionMask {
mask_id: string;
bbox: [number, number, number, number];
original_text: string;
hint?: string;
mask_style: MaskStyle;
}
interface MaskStyle {
SolidColor?: { color: string };
BlurEffect?: { intensity: number };
Rectangle?: { color: string; opacity: number };
}
interface ImageOcclusionCard {
id: string;
task_id: string;
image_path: string;
image_base64?: string;
image_width: number;
image_height: number;
masks: OcclusionMask[];
title: string;
description?: string;
tags: string[];
created_at: string;
updated_at: string;
subject: string;
}
interface ImageOcclusionResponse {
success: boolean;
card?: ImageOcclusionCard;
error_message?: string;
}
const ImageOcclusion: React.FC = () => {
const [selectedImage, setSelectedImage] = useState<string | null>(null);
const [isProcessing, setIsProcessing] = useState(false);
const [textRegions, setTextRegions] = useState<TextRegion[]>([]);
const [selectedRegions, setSelectedRegions] = useState<Set<string>>(new Set());
const [cardTitle, setCardTitle] = useState('');
const [cardDescription, setCardDescription] = useState('');
const [cardSubject, setCardSubject] = useState('数学');
const [cardTags, setCardTags] = useState('');
const [maskStyle, setMaskStyle] = useState<MaskStyle>({ Rectangle: { color: '#FF0000', opacity: 0.7 } });
const [imageScale, setImageScale] = useState(1);
const [createdCard, setCreatedCard] = useState<ImageOcclusionCard | null>(null);
const [showPreview, setShowPreview] = useState(false);
const [imageLoaded, setImageLoaded] = useState(false);
const [useHighResolution, setUseHighResolution] = useState(true);
const fileInputRef = useRef<HTMLInputElement>(null);
const imageRef = useRef<HTMLImageElement>(null);
const canvasRef = useRef<HTMLCanvasElement>(null);
const [originalImageDimensions, setOriginalImageDimensions] = useState<{ width: number; height: number } | null>(null);
const handleImageUpload = useCallback((event: React.ChangeEvent<HTMLInputElement>) => {
const file = event.target.files?.[0];
if (!file) return;
const reader = new FileReader();
reader.onload = (e) => {
const base64 = e.target?.result as string;
setSelectedImage(base64);
setTextRegions([]);
setSelectedRegions(new Set());
setCreatedCard(null);
setImageLoaded(false);
};
reader.readAsDataURL(file);
}, []);
const extractTextCoordinates = useCallback(async () => {
if (!selectedImage) return;
setIsProcessing(true);
try {
const base64Data = selectedImage.split(',')[1];
const response = await invoke<ImageOcrResponse>('extract_image_text_coordinates', {
request: {
image_base64: base64Data,
extract_coordinates: true,
target_text: null,
vl_high_resolution_images: useHighResolution,
},
});
if (response.success) {
console.log('✅ OCR识别成功:', {
区域数量: response.text_regions.length,
图片尺寸: `${response.image_width}x${response.image_height}`,
全文: response.full_text.substring(0, 100) + ('...'),
示例区域: response.text_regions.slice(0, 3).map((r, i) => ({
索引: i,
文字: r.text,
坐标: `[${r.bbox.join(', ')}]`,
置信度: `${(r.confidence * 100).toFixed(1)}%`
}))
});
setTextRegions(response.text_regions);
const dimensions = { width: response.image_width, height: response.image_height };
setOriginalImageDimensions(dimensions);
// 如果图片已加载，立即计算缩放比例；否则等待图片加载完成
if (imageLoaded) {
console.log('🔄 OCR完成，图片已加载，立即计算缩放比例');
updateImageScale(response.image_width, response.image_height, true);
} else {
console.log('⏳ OCR完成，等待图片加载完成后计算缩放比例');
}
} else {
const errorMsg = response.error_message || '未知错误';
console.error('❌ OCR识别失败:', errorMsg);
alert(`OCR识别失败: ${errorMsg}\n\n请检查:\n1. 网络连接是否正常\n2. API配置是否正确\n3. 图片格式是否支持`);
}
} catch (error) {
console.error('❌ OCR识别异常:', error);
const errorMessage = error instanceof Error ? error.message : String(error);
alert(`OCR识别异常: ${errorMessage}\n\n可能的原因:\n1. 网络连接中断\n2. 服务器响应超时\n3. 图片文件损坏`);
} finally {
setIsProcessing(false);
}
}, [selectedImage, useHighResolution]);
const updateImageScale = useCallback((originalWidth: number, originalHeight: number, forceUpdate = false) => {
if (!imageRef.current) {
console.warn('⚠️ 图片引用不存在，无法计算缩放比例');
return;
}
// 等待图片完全渲染后再计算尺寸
const calculateScale = () => {
const img = imageRef.current!;
const displayWidth = img.clientWidth;
const displayHeight = img.clientHeight;
const naturalWidth = img.naturalWidth;
const naturalHeight = img.naturalHeight;
console.log('🔍 尺寸信息收集:', {
原始OCR尺寸: `${originalWidth}x${originalHeight}`,
图片自然尺寸: `${naturalWidth}x${naturalHeight}`,
显示尺寸: `${displayWidth}x${displayHeight}`,
图片加载状态: imageLoaded
});
// 验证原始尺寸
if (originalWidth <= 0 || originalHeight <= 0) {
console.error('❌ 原始图片尺寸无效:', { originalWidth, originalHeight });
setImageScale(1);
return;
}
// 验证显示尺寸
if (displayWidth <= 0 || displayHeight <= 0) {
if (!forceUpdate) {
console.warn('⚠️ 显示尺寸无效，延迟重试:', { displayWidth, displayHeight });
// 延迟重试，给图片更多时间渲染
setTimeout(() => updateImageScale(originalWidth, originalHeight, true), 100);
return;
} else {
console.error('❌ 显示尺寸持续无效，使用默认缩放比例');
setImageScale(1);
return;
}
}
// 计算缩放比例 - 确保图片按比例缩放
const scaleX = displayWidth / originalWidth;
const scaleY = displayHeight / originalHeight;
const scale = Math.min(scaleX, scaleY); // 使用较小的缩放比例保持图片比例
console.log('✅ 缩放计算完成:', {
X轴缩放: scaleX.toFixed(4),
Y轴缩放: scaleY.toFixed(4),
最终缩放: scale.toFixed(4)
});
setImageScale(scale);
};
// 如果图片已加载，立即计算；否则等待加载完成
if (imageLoaded) {
calculateScale();
} else {
console.log('⏳ 等待图片加载完成后计算缩放比例');
// 等待下一个渲染周期
requestAnimationFrame(calculateScale);
}
}, [imageLoaded]);
const handleRegionClick = useCallback((regionId: string) => {
setSelectedRegions(prev => {
const newSet = new Set(prev);
if (newSet.has(regionId)) {
newSet.delete(regionId);
} else {
newSet.add(regionId);
}
return newSet;
});
}, []);
const createImageOcclusionCard = useCallback(async () => {
if (!selectedImage || selectedRegions.size === 0 || !cardTitle.trim()) {
alert('请上传图片、选择要遮罩的区域，并填写卡片标题');
return;
}
setIsProcessing(true);
try {
const base64Data = selectedImage.split(',')[1];
const response = await invoke<ImageOcclusionResponse>('create_image_occlusion_card', {
request: {
image_base64: base64Data,
title: cardTitle.trim(),
description: cardDescription.trim() || null,
subject: cardSubject,
tags: cardTags.split(',').map(tag => tag.trim()).filter(tag => tag.length > 0),
selected_regions: Array.from(selectedRegions),
mask_style: maskStyle,
use_high_resolution: useHighResolution,
},
});
if (response.success && response.card) {
console.log('✅ 遮罩卡创建成功:', {
卡片ID: response.card.id,
标题: response.card.title,
遮罩数量: response.card.masks.length,
图片尺寸: `${response.card.image_width}x${response.card.image_height}`
});
setCreatedCard(response.card);
setShowPreview(true);
alert('✅ 图片遮罩卡创建成功！');
} else {
const errorMsg = response.error_message || '未知错误';
console.error('❌ 遮罩卡创建失败:', errorMsg);
alert(`创建失败: ${errorMsg}\n\n请检查:\n1. 是否选择了遮罩区域\n2. 卡片信息是否完整\n3. 网络连接是否正常`);
}
} catch (error) {
console.error('❌ 创建遮罩卡异常:', error);
const errorMessage = error instanceof Error ? error.message : String(error);
alert(`创建失败: ${errorMessage}\n\n可能的原因:\n1. 网络连接问题\n2. 服务器处理错误\n3. 数据格式异常`);
} finally {
setIsProcessing(false);
}
}, [selectedImage, selectedRegions, cardTitle, cardDescription, cardSubject, cardTags, maskStyle, useHighResolution]);
const renderTextRegions = useCallback(() => {
if (!textRegions.length || !imageRef.current || !imageLoaded || imageScale <= 0) {
console.log('🚫 无法渲染文字区域:', {
文字区域数量: textRegions.length,
图片引用: !!imageRef.current,
图片加载: imageLoaded,
缩放比例: imageScale
});
return null;
}
if (!imageRef.current.parentElement) {
console.error('❌ 图片父元素不存在');
return null;
}
// 获取精确的容器和图片位置信息
const imgRect = imageRef.current.getBoundingClientRect();
const containerRect = imageRef.current.parentElement.getBoundingClientRect();
// 计算图片相对于容器的精确偏移（不重复计算padding）
const imgOffsetX = imgRect.left - containerRect.left;
const imgOffsetY = imgRect.top - containerRect.top;
console.log('🎯 渲染文字区域 - 精确坐标计算:', {
容器位置: `${containerRect.left}, ${containerRect.top}`,
图片位置: `${imgRect.left}, ${imgRect.top}`,
图片偏移: `${imgOffsetX}, ${imgOffsetY}`,
图片尺寸: `${imgRect.width}x${imgRect.height}`,
缩放比例: imageScale.toFixed(4),
区域数量: textRegions.length
});
return textRegions.map((region) => {
const [x1, y1, x2, y2] = region.bbox;
const isSelected = selectedRegions.has(region.region_id);
// 精确的坐标转换：原始坐标 * 缩放比例 + 图片偏移
const finalLeft = x1 * imageScale + imgOffsetX;
const finalTop = y1 * imageScale + imgOffsetY;
const finalWidth = (x2 - x1) * imageScale;
const finalHeight = (y2 - y1) * imageScale;
// 调试信息（只为第一个区域输出，避免日志混乱）
if (region === textRegions[0]) {
console.log('📍 第一个区域坐标转换:', {
原始坐标: `[${x1}, ${y1}, ${x2}, ${y2}]`,
缩放后: `[${(x1 * imageScale).toFixed(1)}, ${(y1 * imageScale).toFixed(1)}, ${(x2 * imageScale).toFixed(1)}, ${(y2 * imageScale).toFixed(1)}]`,
最终位置: `${finalLeft.toFixed(1)}, ${finalTop.toFixed(1)}`,
区域尺寸: `${finalWidth.toFixed(1)}x${finalHeight.toFixed(1)}`,
文字内容: region.text
});
}
return (
<div
key={region.region_id}
className={`text-region ${isSelected ? 'selected' : ''}`}
style={{
position: 'absolute',
left: `${Math.round(finalLeft)}px`,
top: `${Math.round(finalTop)}px`,
width: `${Math.round(finalWidth)}px`,
height: `${Math.round(finalHeight)}px`,
border: `2px solid ${isSelected ? '#FF0000' : '#00FF00'}`,
backgroundColor: isSelected ? 'rgba(255, 0, 0, 0.2)' : 'rgba(0, 255, 0, 0.1)',
cursor: 'pointer',
borderRadius: '2px',
boxSizing: 'border-box',
pointerEvents: 'auto'
}}
onClick={() => handleRegionClick(region.region_id)}
title={`${region.text} (置信度: ${(region.confidence * 100).toFixed(1)}%)`}
/>
);
});
}, [textRegions, selectedRegions, imageScale, imageLoaded, handleRegionClick]);
const renderMaskPreview = useCallback(() => {
if (!createdCard || !showPreview || !imageRef.current || imageScale <= 0) {
console.log('🚫 无法渲染遮罩预览:', {
有卡片: !!createdCard,
显示预览: showPreview,
图片引用: !!imageRef.current,
缩放比例: imageScale
});
return null;
}
if (!imageRef.current.parentElement) {
console.error('❌ 遮罩预览: 图片父元素不存在');
return null;
}
// 使用与文字区域相同的坐标计算方法
const imgRect = imageRef.current.getBoundingClientRect();
const containerRect = imageRef.current.parentElement.getBoundingClientRect();
const imgOffsetX = imgRect.left - containerRect.left;
const imgOffsetY = imgRect.top - containerRect.top;
console.log('🎭 渲染遮罩预览:', {
遮罩数量: createdCard.masks.length,
图片偏移: `${imgOffsetX}, ${imgOffsetY}`,
缩放比例: imageScale.toFixed(4)
});
return createdCard.masks.map((mask) => {
const [x1, y1, x2, y2] = mask.bbox;
let maskStyleCSS: React.CSSProperties = {};
if ('SolidColor' in mask.mask_style && mask.mask_style.SolidColor) {
maskStyleCSS.backgroundColor = mask.mask_style.SolidColor.color;
} else if ('BlurEffect' in mask.mask_style && mask.mask_style.BlurEffect) {
maskStyleCSS.backgroundColor = 'rgba(128, 128, 128, 0.8)';
maskStyleCSS.backdropFilter = `blur(${mask.mask_style.BlurEffect.intensity}px)`;
} else if ('Rectangle' in mask.mask_style && mask.mask_style.Rectangle) {
const rectStyle = mask.mask_style.Rectangle;
maskStyleCSS.backgroundColor = rectStyle.color;
maskStyleCSS.opacity = rectStyle.opacity;
}
// 使用与文字区域相同的坐标转换方法
const finalLeft = x1 * imageScale + imgOffsetX;
const finalTop = y1 * imageScale + imgOffsetY;
const finalWidth = (x2 - x1) * imageScale;
const finalHeight = (y2 - y1) * imageScale;
return (
<div
key={mask.mask_id}
className="mask-overlay"
style={{
position: 'absolute',
left: `${Math.round(finalLeft)}px`,
top: `${Math.round(finalTop)}px`,
width: `${Math.round(finalWidth)}px`,
height: `${Math.round(finalHeight)}px`,
cursor: 'pointer',
borderRadius: '2px',
border: '1px solid rgba(0, 0, 0, 0.3)',
boxSizing: 'border-box',
pointerEvents: 'auto',
...maskStyleCSS,
}}
onClick={() => {
const isHidden = (document.querySelector(`[data-mask-id="${mask.mask_id}"]`) as HTMLElement)?.style.display === 'none';
const element = document.querySelector(`[data-mask-id="${mask.mask_id}"]`) as HTMLElement;
if (element) {
element.style.display = isHidden ? 'block' : 'none';
}
}}
data-mask-id={mask.mask_id}
title={`点击切换显示: ${mask.original_text}`}
/>
);
});
}, [createdCard, showPreview, imageScale]);
useEffect(() => {
// 只有在有OCR数据和图片已加载时才监听窗口大小变化
if (!originalImageDimensions || !imageLoaded) {
return;
}
const debouncedUpdateScale = () => {
console.log('🔄 窗口大小变化，重新计算缩放比例');
updateImageScale(originalImageDimensions.width, originalImageDimensions.height, true);
};
let timeoutId: number | null = null;
const handleResize = () => {
if (timeoutId) {
clearTimeout(timeoutId);
}
timeoutId = setTimeout(debouncedUpdateScale, 300); // 增加防抖时间
};
window.addEventListener('resize', handleResize);
return () => {
window.removeEventListener('resize', handleResize);
if (timeoutId) {
clearTimeout(timeoutId);
}
};
}, [originalImageDimensions, imageLoaded, updateImageScale]);
return (
<div style={{
width: '100%',
height: '100%',
overflow: 'auto',
background: '#f8fafc'
}}>
{/* 头部区域 - 统一白色样式 */}
<div style={{
background: 'white',
borderBottom: '1px solid #e5e7eb',
padding: '24px 32px',
position: 'relative'
}}>
<div style={{
position: 'absolute',
top: 0,
left: 0,
right: 0,
height: '4px',
background: 'linear-gradient(90deg, #667eea, #764ba2)'
}}></div>
<div style={{ position: 'relative', zIndex: 1 }}>
<div style={{ display: 'flex', alignItems: 'center', marginBottom: '8px' }}>
<svg style={{ width: '32px', height: '32px', marginRight: '12px', color: '#667eea' }} fill="none" stroke="currentColor" viewBox="0 0 24 24" strokeWidth={2}>
<rect width="18" height="18" x="3" y="3" rx="2" ry="2" />
<circle cx="9" cy="9" r="2" />
<path d="m21 15-3.086-3.086a2 2 0 0 0-2.828 0L6 21" />
</svg>
<h1 style={{ fontSize: '28px', fontWeight: '700', margin: 0, color: '#1f2937' }}>图片遮罩卡制作</h1>
</div>
<p style={{ fontSize: '16px', color: '#6b7280', margin: 0, lineHeight: '1.5' }}>
上传图片，选择要遮罩的文字区域，创建互动学习卡片
</p>
</div>
</div>
<div className="image-occlusion-container" style={{padding: '24px'}}>
<div className="upload-section">
<input
ref={fileInputRef}
type="file"
accept="image/*"
onChange={handleImageUpload}
style={{ display: 'none' }}
/>
<button
onClick={() => fileInputRef.current?.click()}
className="upload-button"
disabled={isProcessing}
>
选择图片
</button>
{selectedImage && (
<button
onClick={extractTextCoordinates}
className="extract-button"
disabled={isProcessing}
>
{isProcessing ? '识别中...' : '识别文字区域'}
</button>
)}
{selectedImage && (
<div className="form-group-inline">
<input
type="checkbox"
id="highResToggle"
checked={useHighResolution}
onChange={(e) => setUseHighResolution(e.target.checked)}
disabled={isProcessing}
/>
<label htmlFor="highResToggle">使用高分辨率模式</label>
</div>
)}
</div>
{selectedImage && (
<div className="image-workspace">
<div className="image-container">
<img
ref={imageRef}
src={selectedImage}
alt="待处理图片"
className="main-image"
onLoad={(e) => {
const img = e.target as HTMLImageElement;
console.log('🖼️ 图片加载完成:', {
自然尺寸: `${img.naturalWidth}x${img.naturalHeight}`,
显示尺寸: `${img.clientWidth}x${img.clientHeight}`,
是否有OCR数据: originalImageDimensions !== null
});
setImageLoaded(true);
// 如果已有OCR数据，立即重新计算缩放比例
if (originalImageDimensions) {
console.log('🔄 图片加载完成，重新计算缩放比例');
// 使用setTimeout确保图片尺寸已经更新
setTimeout(() => {
updateImageScale(originalImageDimensions.width, originalImageDimensions.height, true);
}, 50);
}
}}
/>
{!showPreview && renderTextRegions()}
{showPreview && renderMaskPreview()}
</div>
{textRegions.length > 0 && !showPreview && (
<div className="controls-panel">
<div className="card-info">
<h3>卡片信息</h3>
<div className="form-group">
<label htmlFor="cardTitle">标题 *</label>
<input
id="cardTitle"
type="text"
value={cardTitle}
onChange={(e) => setCardTitle(e.target.value)}
placeholder="输入卡片标题"
/>
</div>
<div className="form-group">
<label htmlFor="cardDescription">描述</label>
<textarea
id="cardDescription"
value={cardDescription}
onChange={(e) => setCardDescription(e.target.value)}
placeholder="输入卡片描述（可选）"
rows={3}
/>
</div>
<div className="form-row">
<div className="form-group">
<label htmlFor="cardSubject">学科</label>
<select
id="cardSubject"
value={cardSubject}
onChange={(e) => setCardSubject(e.target.value)}
>
<option value="数学">数学</option>
<option value="物理">物理</option>
<option value="化学">化学</option>
<option value="英语">英语</option>
<option value="语文">语文</option>
<option value="历史">历史</option>
<option value="地理">地理</option>
<option value="生物">生物</option>
<option value="其他">其他</option>
</select>
</div>
<div className="form-group">
<label htmlFor="cardTags">标签</label>
<input
id="cardTags"
type="text"
value={cardTags}
onChange={(e) => setCardTags(e.target.value)}
placeholder="用逗号分隔多个标签"
/>
</div>
</div>
</div>
<div className="mask-settings">
<h3>遮罩样式</h3>
<div className="mask-style-options">
<label>
<input
type="radio"
name="maskStyle"
checked={'Rectangle' in maskStyle}
onChange={() => setMaskStyle({ Rectangle: { color: '#FF0000', opacity: 0.7 } })}
/>
半透明矩形
</label>
<label>
<input
type="radio"
name="maskStyle"
checked={'SolidColor' in maskStyle}
onChange={() => setMaskStyle({ SolidColor: { color: '#000000' } })}
/>
纯色遮罩
</label>
<label>
<input
type="radio"
name="maskStyle"
checked={'BlurEffect' in maskStyle}
onChange={() => setMaskStyle({ BlurEffect: { intensity: 5 } })}
/>
模糊效果
</label>
</div>
</div>
<div className="region-stats">
<p>已识别 {textRegions.length} 个文字区域</p>
<p>已选择 {selectedRegions.size} 个区域进行遮罩</p>
</div>
<button
onClick={createImageOcclusionCard}
className="create-button"
disabled={isProcessing || selectedRegions.size === 0 || !cardTitle.trim()}
>
{isProcessing ? '创建中...' : '创建遮罩卡'}
</button>
</div>
)}
{showPreview && createdCard && (
<div className="preview-panel">
<h3>预览模式</h3>
<p>点击红色遮罩区域可以切换显示/隐藏文字</p>
<div className="preview-controls">
<button onClick={() => setShowPreview(false)}>返回编辑</button>
<button onClick={() => {
console.log('📄 尝试导出ANKI卡片:', {
卡片ID: createdCard?.id,
标题: createdCard?.title,
遮罩数量: createdCard?.masks.length
});
alert('🔧 导出功能即将推出\n\n将支持:\n1. 导出为Anki apkg文件\n2. 自定义遮罩样式\n3. 批量导出功能');
}}>
导出到ANKI
</button>
</div>
<div className="card-details">
<h4>{createdCard.title}</h4>
{createdCard.description && <p>{createdCard.description}</p>}
<div className="tags">
{createdCard.tags.map((tag, index) => (
<span key={index} className="tag">{tag}</span>
))}
</div>
</div>
</div>
)}
</div>
)}
</div>
</div>
);
};
export default ImageOcclusion;
| 25,006 | ImageOcclusion | tsx | en | tsx | code | {"qsc_code_num_words": 2075, "qsc_code_num_chars": 25006.0, "qsc_code_mean_word_length": 6.36626506, "qsc_code_frac_words_unique": 0.26554217, "qsc_code_frac_chars_top_2grams": 0.01725965, "qsc_code_frac_chars_top_3grams": 0.00885693, "qsc_code_frac_chars_top_4grams": 0.00794852, "qsc_code_frac_chars_dupe_5grams": 0.20189251, "qsc_code_frac_chars_dupe_6grams": 0.17479182, "qsc_code_frac_chars_dupe_7grams": 0.14708554, "qsc_code_frac_chars_dupe_8grams": 0.12641938, "qsc_code_frac_chars_dupe_9grams": 0.11975776, "qsc_code_frac_chars_dupe_10grams": 0.11975776, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.01726816, "qsc_code_frac_chars_whitespace": 0.33072063, "qsc_code_size_file_byte": 25006.0, "qsc_code_num_lines": 711.0, "qsc_code_num_chars_line_max": 169.0, "qsc_code_num_chars_line_mean": 35.17018284, "qsc_code_frac_chars_alphabet": 0.77019598, "qsc_code_frac_chars_comments": 0.01603615, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.3476874, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.06901036, "qsc_code_frac_chars_long_word_length": 0.0059744, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0} |
000haoji/deep-student | src/components/MarkdownRenderer.tsx | import React from 'react';
import ReactMarkdown from 'react-markdown';
import remarkGfm from 'remark-gfm';
import remarkMath from 'remark-math';
import rehypeKatex from 'rehype-katex';
interface MarkdownRendererProps {
content: string;
className?: string;
}
// 简化的LaTeX预处理，最小化干预
const preprocessLatex = (content: string): string => {
if (!content) return '';
let processedContent = content;
// 专门处理 bmatrix 环境
processedContent = processedContent.replace(/\\begin{bmatrix}(.*?)\\end{bmatrix}/gs, (match, matrixContent) => {
// 移除每行末尾 \ 之前和之后的空格
let cleanedMatrix = matrixContent.replace(/\s*\\\\\s*/g, ' \\\\ '); // 保留一个空格以便阅读，KaTeX应能处理
// 移除 & 周围的空格
cleanedMatrix = cleanedMatrix.replace(/\s*&\s*/g, '&');
// 移除行首和行尾的空格
cleanedMatrix = cleanedMatrix.split(' \\\\ ').map((row: string) => row.trim()).join(' \\\\ ');
return `\\begin{bmatrix}${cleanedMatrix}\\end{bmatrix}`;
});
return processedContent;
};
export const MarkdownRenderer: React.FC<MarkdownRendererProps> = ({
content,
className = ''
}) => {
// 预处理内容，处理LaTeX公式
const processedContent = preprocessLatex(content);
return (
<div className={`markdown-content ${className}`}>
<ReactMarkdown
remarkPlugins={[remarkGfm, remarkMath]}
rehypePlugins={[
[rehypeKatex, {
throwOnError: false, // 不抛出错误，以红色显示错误内容
errorColor: '#cc0000',
strict: false, // 宽松模式
trust: false, // 安全模式
macros: {
'\\RR': '\\mathbb{R}',
'\\NN': '\\mathbb{N}',
'\\ZZ': '\\mathbb{Z}',
'\\QQ': '\\mathbb{Q}',
'\\CC': '\\mathbb{C}'
}
}]
]}
components={{
// 自定义代码块渲染
code: ({ node, inline, className, children, ...props }: any) => {
return !inline ? (
<pre className="code-block">
<code className={className} {...props}>
{children}
</code>
</pre>
) : (
<code className="inline-code" {...props}>
{children}
</code>
);
},
// 自定义表格渲染
table: ({ children }) => (
<div className="table-wrapper">
<table className="markdown-table">{children}</table>
</div>
),
}}
>
{processedContent}
</ReactMarkdown>
</div>
);
}; | 2,488 | MarkdownRenderer | tsx | en | tsx | code | {"qsc_code_num_words": 193, "qsc_code_num_chars": 2488.0, "qsc_code_mean_word_length": 6.69948187, "qsc_code_frac_words_unique": 0.48186528, "qsc_code_frac_chars_top_2grams": 0.01392111, "qsc_code_frac_chars_top_3grams": 0.01392111, "qsc_code_frac_chars_top_4grams": 0.0154679, "qsc_code_frac_chars_dupe_5grams": 0.0, "qsc_code_frac_chars_dupe_6grams": 0.0, "qsc_code_frac_chars_dupe_7grams": 0.0, "qsc_code_frac_chars_dupe_8grams": 0.0, "qsc_code_frac_chars_dupe_9grams": 0.0, "qsc_code_frac_chars_dupe_10grams": 0.0, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.00233236, "qsc_code_frac_chars_whitespace": 0.31069132, "qsc_code_size_file_byte": 2488.0, "qsc_code_num_lines": 85.0, "qsc_code_num_chars_line_max": 115.0, "qsc_code_num_chars_line_mean": 29.27058824, "qsc_code_frac_chars_alphabet": 0.7516035, "qsc_code_frac_chars_comments": 0.07154341, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.14285714, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.08697534, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0} |
000haoji/deep-student | src/chat-core/utils/unifiedStreamHandler.ts | /**
* Unified Streaming Handler
*
* Consolidates all streaming approaches in the project into a single,
* consistent implementation that can be used across all components.
*/
import { listen } from '@tauri-apps/api/event';
import { invoke } from '@tauri-apps/api/core';
export interface StreamChunk {
content: string;
is_complete: boolean;
chunk_id: string;
}
export interface StreamMessage {
id: string;
role: 'user' | 'assistant' | 'system';
content: string;
thinking_content?: string;
timestamp: string;
}
export interface StreamOptions {
enableChainOfThought?: boolean;
onChunk?: (chunk: string) => void;
onThinking?: (thinking: string) => void;
onComplete?: (fullResponse: string, thinkingContent?: string) => void;
onError?: (error: string) => void;
onProgress?: (progress: { content: string; thinking?: string }) => void;
}
export interface StreamRequest {
type: 'analysis' | 'chat' | 'continue_chat';
tempId?: string;
mistakeId?: number;
imageData?: string;
userInput?: string;
chatHistory?: StreamMessage[];
enableChainOfThought?: boolean;
}
/**
* Unified Streaming Manager
* Replaces multiple streaming implementations with a single, consistent approach
*/
export class UnifiedStreamHandler {
private activeStreams: Map<string, () => void> = new Map();
private currentProgress: Map<string, { content: string; thinking: string }> = new Map();
/**
* Start a streaming request with unified handling
*/
async startStream(request: StreamRequest, options: StreamOptions = {}): Promise<string> {
const streamId = this.generateStreamId(request);
// Stop any existing stream with the same ID
this.stopStream(streamId);
try {
const cleanupFunctions = await this.initializeStreamListeners(streamId, request, options);
this.activeStreams.set(streamId, () => {
cleanupFunctions.forEach(cleanup => cleanup());
});
// Start the appropriate backend command
await this.startBackendStream(request);
return streamId;
} catch (error) {
console.error('Failed to start stream:', error);
if (options.onError) {
options.onError(error instanceof Error ? error.message : 'Unknown error');
}
throw error;
}
}
/**
* Stop a specific stream
*/
stopStream(streamId: string): void {
const cleanup = this.activeStreams.get(streamId);
if (cleanup) {
cleanup();
this.activeStreams.delete(streamId);
this.currentProgress.delete(streamId);
console.log(`Stopped stream: ${streamId}`);
}
}
/**
* Stop all active streams
*/
stopAllStreams(): void {
for (const streamId of this.activeStreams.keys()) {
this.stopStream(streamId);
}
}
/**
* Get current progress for a stream
*/
getProgress(streamId: string): { content: string; thinking: string } | null {
return this.currentProgress.get(streamId) || null;
}
/**
* Check if a stream is active
*/
isStreamActive(streamId: string): boolean {
return this.activeStreams.has(streamId);
}
private generateStreamId(request: StreamRequest): string {
const timestamp = Date.now();
const type = request.type;
const id = request.tempId || request.mistakeId || 'default';
return `${type}_${id}_${timestamp}`;
}
private async initializeStreamListeners(
streamId: string,
request: StreamRequest,
options: StreamOptions
): Promise<Array<() => void>> {
const cleanupFunctions: Array<() => void> = [];
let fullContent = '';
let fullThinking = '';
// Initialize progress tracking
this.currentProgress.set(streamId, { content: '', thinking: '' });
// Determine event names based on request type
const baseEventName = this.getEventName(request);
const contentEvent = baseEventName;
const thinkingEvent = `${baseEventName}_reasoning`;
console.log(`🔄 Initializing unified stream listeners for: ${streamId}`);
console.log(`📡 Content event: ${contentEvent}`);
console.log(`🧠 Thinking event: ${thinkingEvent}`);
// Listen for main content stream
try {
const unlistenContent = await listen<StreamChunk>(contentEvent, (event) => {
const chunk = event.payload;
if (chunk.is_complete) {
console.log(`✅ Content stream complete for ${streamId}`);
this.checkStreamCompletion(streamId, fullContent, fullThinking, options);
return;
}
if (chunk.content) {
fullContent += chunk.content;
// Update progress
const progress = this.currentProgress.get(streamId);
if (progress) {
progress.content = fullContent;
this.currentProgress.set(streamId, progress);
}
// Call callbacks
if (options.onChunk) {
options.onChunk(chunk.content);
}
if (options.onProgress) {
options.onProgress({ content: fullContent, thinking: fullThinking || undefined });
}
console.log(`📝 Content update [${streamId}]: ${chunk.content.length} chars`);
}
});
cleanupFunctions.push(unlistenContent);
} catch (error) {
console.error(`Failed to listen for content events: ${contentEvent}`, error);
}
// Listen for thinking chain (if enabled)
if (request.enableChainOfThought !== false) {
try {
const unlistenThinking = await listen<StreamChunk>(thinkingEvent, (event) => {
const chunk = event.payload;
if (chunk.is_complete) {
console.log(`✅ Thinking stream complete for ${streamId}`);
this.checkStreamCompletion(streamId, fullContent, fullThinking, options);
return;
}
if (chunk.content) {
fullThinking += chunk.content;
// Update progress
const progress = this.currentProgress.get(streamId);
if (progress) {
progress.thinking = fullThinking;
this.currentProgress.set(streamId, progress);
}
// Call callbacks
if (options.onThinking) {
options.onThinking(chunk.content);
}
if (options.onProgress) {
options.onProgress({ content: fullContent, thinking: fullThinking || undefined });
}
console.log(`🧠 Thinking update [${streamId}]: ${chunk.content.length} chars`);
}
});
cleanupFunctions.push(unlistenThinking);
} catch (error) {
console.error(`Failed to listen for thinking events: ${thinkingEvent}`, error);
}
}
// Listen for errors
try {
const unlistenError = await listen<{error: string}>('stream_error', (event) => {
console.error(`❌ Stream error [${streamId}]:`, event.payload.error);
if (options.onError) {
options.onError(event.payload.error);
}
this.stopStream(streamId);
});
cleanupFunctions.push(unlistenError);
} catch (error) {
console.error('Failed to listen for error events', error);
}
return cleanupFunctions;
}
private checkStreamCompletion(
streamId: string,
content: string,
thinking: string,
options: StreamOptions
): void {
// Check if both content and thinking (if enabled) are complete
const progress = this.currentProgress.get(streamId);
if (!progress) return;
console.log(`🎉 Stream completion check [${streamId}]: content=${content.length}, thinking=${thinking.length}`);
if (options.onComplete) {
options.onComplete(content, thinking || "");
}
// Auto-cleanup after completion
setTimeout(() => {
this.stopStream(streamId);
}, 100);
}
private getEventName(request: StreamRequest): string {
switch (request.type) {
case 'analysis':
return request.tempId ? `analysis_stream_${request.tempId}` : 'stream_chunk';
case 'chat':
return 'stream_chunk';
case 'continue_chat':
return request.tempId ? `continue_chat_stream_${request.tempId}` : 'stream_chunk';
default:
return 'stream_chunk';
}
}
private async startBackendStream(request: StreamRequest): Promise<void> {
switch (request.type) {
case 'analysis':
if (!request.imageData || !request.userInput) {
throw new Error('Analysis requires imageData and userInput');
}
// First do OCR analysis
const analysisResponse = await invoke('analyze_step_by_step', {
request: {
subject: "数学",
question_image_files: [request.imageData.startsWith('data:') ? request.imageData : `data:image/jpeg;base64,${request.imageData}`],
analysis_image_files: [],
user_question: request.userInput,
enable_chain_of_thought: request.enableChainOfThought !== false
}
});
// If we got a temp_id, start the streaming answer
if ((analysisResponse as any)?.temp_id) {
await invoke('start_streaming_answer', {
request: {
temp_id: (analysisResponse as any).temp_id,
enable_chain_of_thought: request.enableChainOfThought !== false
}
});
}
break;
case 'chat':
await invoke('start_streaming_answer', {
request: {
chat_history: request.chatHistory?.map(msg => ({
role: msg.role,
content: msg.content,
thinking_content: msg.thinking_content
})) || [],
enable_chain_of_thought: request.enableChainOfThought !== false
}
});
break;
case 'continue_chat':
if (!request.tempId) {
throw new Error('Continue chat requires tempId');
}
await invoke('continue_chat_stream', {
request: {
temp_id: request.tempId,
chat_history: request.chatHistory?.map(msg => ({
role: msg.role,
content: msg.content,
thinking_content: msg.thinking_content
})) || [],
enable_chain_of_thought: request.enableChainOfThought !== false
}
});
break;
default:
throw new Error(`Unsupported stream type: ${request.type}`);
}
}
}
// Create global instance
export const unifiedStreamHandler = new UnifiedStreamHandler();
/**
* React Hook for Unified Streaming
* Provides a simple interface for React components to use unified streaming
*/
export function useUnifiedStream() {
const [activeStreams, setActiveStreams] = React.useState<Set<string>>(new Set());
const [streamProgress, setStreamProgress] = React.useState<Map<string, { content: string; thinking: string }>>(new Map());
React.useEffect(() => {
return () => {
// Cleanup all streams when component unmounts
unifiedStreamHandler.stopAllStreams();
};
}, []);
const startStream = React.useCallback(async (request: StreamRequest, options: StreamOptions = {}) => {
const streamId = await unifiedStreamHandler.startStream(request, {
...options,
onProgress: (progress) => {
setStreamProgress(prev => new Map(prev.set(streamId, { content: progress.content, thinking: progress.thinking || "" })));
if (options.onProgress) {
options.onProgress(progress);
}
},
onComplete: (content, thinking) => {
setActiveStreams(prev => {
const newSet = new Set(prev);
newSet.delete(streamId);
return newSet;
});
if (options.onComplete) {
options.onComplete(content, thinking);
}
},
onError: (error) => {
setActiveStreams(prev => {
const newSet = new Set(prev);
newSet.delete(streamId);
return newSet;
});
if (options.onError) {
options.onError(error);
}
}
});
setActiveStreams(prev => new Set(prev.add(streamId)));
return streamId;
}, []);
const stopStream = React.useCallback((streamId: string) => {
unifiedStreamHandler.stopStream(streamId);
setActiveStreams(prev => {
const newSet = new Set(prev);
newSet.delete(streamId);
return newSet;
});
setStreamProgress(prev => {
const newMap = new Map(prev);
newMap.delete(streamId);
return newMap;
});
}, []);
const stopAllStreams = React.useCallback(() => {
unifiedStreamHandler.stopAllStreams();
setActiveStreams(new Set());
setStreamProgress(new Map());
}, []);
return {
startStream,
stopStream,
stopAllStreams,
activeStreams: Array.from(activeStreams),
streamProgress: Object.fromEntries(streamProgress),
isStreaming: activeStreams.size > 0
};
}
// Add React import for the hook
import React from 'react'; | 13,011 | unifiedStreamHandler | ts | en | typescript | code | {"qsc_code_num_words": 1178, "qsc_code_num_chars": 13011.0, "qsc_code_mean_word_length": 6.72665535, "qsc_code_frac_words_unique": 0.21052632, "qsc_code_frac_chars_top_2grams": 0.0113579, "qsc_code_frac_chars_top_3grams": 0.01590106, "qsc_code_frac_chars_top_4grams": 0.01703685, "qsc_code_frac_chars_dupe_5grams": 0.32079758, "qsc_code_frac_chars_dupe_6grams": 0.28268551, "qsc_code_frac_chars_dupe_7grams": 0.24621403, "qsc_code_frac_chars_dupe_8grams": 0.22791519, "qsc_code_frac_chars_dupe_9grams": 0.181474, "qsc_code_frac_chars_dupe_10grams": 0.15812721, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.00062873, "qsc_code_frac_chars_whitespace": 0.26654369, "qsc_code_size_file_byte": 13011.0, "qsc_code_num_lines": 425.0, "qsc_code_num_chars_line_max": 143.0, "qsc_code_num_chars_line_mean": 30.61411765, "qsc_code_frac_chars_alphabet": 0.82877502, "qsc_code_frac_chars_comments": 0.09553455, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.365625, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.03713145, "qsc_code_frac_chars_long_word_length": 0.00552298, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0} |
0015/esp_rlottie | rlottie/README.md |
# rlottie
[](https://travis-ci.org/Samsung/rlottie)
[](https://ci.appveyor.com/project/smohantty/rlottie-mliua)
[](https://gitter.im/rLottie-dev/community?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge)
<p align="center">
<img width="240" height="240" src="https://github.com/Samsung/rlottie/blob/master/.Gifs/logo.png">
</p>
rlottie is a platform independent standalone c++ library for rendering vector based animations and art in realtime.
Lottie loads and renders animations and vectors exported in the bodymovin JSON format. Bodymovin JSON can be created and exported from After Effects with [bodymovin](https://github.com/bodymovin/bodymovin), Sketch with [Lottie Sketch Export](https://github.com/buba447/Lottie-Sketch-Export), and from [Haiku](https://www.haiku.ai).
For the first time, designers can create and ship beautiful animations without an engineer painstakingly recreating it by hand. Since the animation is backed by JSON they are extremely small in size but can be large in complexity!
Here are small samples of the power of Lottie.
<p align="center">
<img src="https://github.com/Samsung/rlottie/blob/master/.Gifs/1.gif">
<img src="https://github.com/Samsung/rlottie/blob/master/.Gifs/2.gif">
<img src="https://github.com/airbnb/lottie-ios/blob/master/_Gifs/Examples1.gif">
</p>
## Contents
- [Building Lottie](#building-lottie)
- [Meson Build](#meson-build)
- [Cmake Build](#cmake-build)
- [Test](#test)
- [Demo](#demo)
- [Previewing Lottie JSON Files](#previewing-lottie-json-files)
- [Quick Start](#quick-start)
- [Dynamic Property](#dynamic-property)
- [Supported After Effects Features](#supported-after-effects-features)
- [Issues or Feature Requests?](#issues-or-feature-requests)
## Building Lottie
rlottie supports [meson](https://mesonbuild.com/) and [cmake](https://cmake.org/) build system. rlottie is written in `C++14`. and has a public header dependency of `C++11`
### Meson Build
install [meson](http://mesonbuild.com/Getting-meson.html) and [ninja](https://ninja-build.org/) if not already installed.
Run meson to configure rlottie
```
meson build
```
Run ninja to build rlottie
```
ninja -C build
```
### Cmake Build
Install [cmake](https://cmake.org/download/) if not already installed
Create a build directory for out of source `build`
```
mkdir build
```
Run cmake command inside `build` directory to configure rlottie.
```
cd build
cmake ..
# install in a different path. eg ~/test/usr/lib
cmake -DCMAKE_INSTALL_PREFIX=~/test ..
# static build
cmake -DBUILD_SHARED_LIBS=OFF ..
```
Run make to build rlottie
```
make -j 2
```
To install rlottie library
```
make install
```
### Test
Configure to build test
```
meson configure -Dtest=true
```
Build test suit
```
ninja
```
Run test suit
```
ninja test
```
[Back to contents](#contents)
#
## Demo
If you want to see rlottie library in action without building it please visit [rlottie online viewer](http://rlottie.com)
While building rlottie library it generates a simple lottie to GIF converter which can be used to convert lottie json file to GIF file.
Run Demo
```
lottie2gif [lottie file name]
```
#
## Previewing Lottie JSON Files
Please visit [rlottie online viewer](http://rlottie.com)
[rlottie online viewer](http://rlottie.com) uses rlottie wasm library to render the resource locally in your browser. To test your JSON resource drag and drop it to the browser window.
#
## Quick Start
Lottie loads and renders animations and vectors exported in the bodymovin JSON format. Bodymovin JSON can be created and exported from After Effects with [bodymovin](https://github.com/bodymovin/bodymovin), Sketch with [Lottie Sketch Export](https://github.com/buba447/Lottie-Sketch-Export), and from [Haiku](https://www.haiku.ai).
You can quickly load a Lottie animation with:
```cpp
auto animation = rlottie::Animation::loadFromFile("absolute_path/test.json");
```
You can load a lottie animation from raw data with:
```cpp
auto animation = rlottie::Animation::loadFromData(std::string(rawData), std::string(cacheKey));
```
Properties like `frameRate` , `totalFrame` , `duration` can be queried with:
```cpp
# get the frame rate of the resource.
double frameRate = animation->frameRate();
#get total frame that exists in the resource
size_t totalFrame = animation->totalFrame();
#get total animation duration in sec for the resource
double duration = animation->duration();
```
Render a particular frame in a surface buffer `immediately` with:
```cpp
rlottie::Surface surface(buffer, width , height , stride);
animation->renderSync(frameNo, surface);
```
Render a particular frame in a surface buffer `asyncronousely` with:
```cpp
rlottie::Surface surface(buffer, width , height , stride);
# give a render request
std::future<rlottie::Surface> handle = animation->render(frameNo, surface);
...
#when the render data is needed
rlottie::Surface surface = handle.get();
```
[Back to contents](#contents)
## Dynamic Property
You can update properties dynamically at runtime. This can be used for a variety of purposes such as:
- Theming (day and night or arbitrary themes).
- Responding to events such as an error or a success.
- Animating a single part of an animation in response to an event.
- Responding to view sizes or other values not known at design time.
### Understanding After Effects
To understand how to change animation properties in Lottie, you should first understand how animation properties are stored in Lottie. Animation properties are stored in a data tree that mimics the information hierarchy of After Effects. In After Effects a Composition is a collection of Layers that each have their own timelines. Layer objects have string names, and their contents can be an image, shape layers, fills, strokes, or just about anything that is drawable. Each object in After Effects has a name. Lottie can find these objects and properties by their name using a KeyPath.
### Usage
To update a property at runtime, you need 3 things:
1. KeyPath
2. rLottie::Property
3. setValue()
### KeyPath
A KeyPath is used to target a specific content or a set of contents that will be updated. A KeyPath is specified by a list of strings that correspond to the hierarchy of After Effects contents in the original animation.
KeyPaths can include the specific name of the contents or wildcards:
- Wildcard *
- Wildcards match any single content name in its position in the keypath.
- Globstar **
- Globstars match zero or more layers.
### Properties
`rLottie::Property` is an enumeration of properties that can be set. They correspond to the animatable value in After Effects and the available properties are listed below.
```cpp
enum class Property {
FillColor, /*!< Color property of Fill object , value type is rlottie::Color */
FillOpacity, /*!< Opacity property of Fill object , value type is float [ 0 .. 100] */
StrokeColor, /*!< Color property of Stroke object , value type is rlottie::Color */
StrokeOpacity, /*!< Opacity property of Stroke object , value type is float [ 0 .. 100] */
StrokeWidth, /*!< stroke with property of Stroke object , value type is float */
...
};
```
### setValue()
`setValue()` requires a keypath of string and value. The value can be `Color`, `Size` and `Point` structure or a function that returns them. `Color`, `Size`, and `Point` vary depending on the type of `rLottie::Property`. This value or function(callback) is called and applied to every frame. This value can be set differently for each frame by using the `FrameInfo` argument passed to the function.
### Usage
```cpp
animation->setValue<rlottie::Property::FillColor>("**",rlottie::Color(0, 1, 0));
```
```cpp
animation->setValue<rlottie::Property::FillColor>("Layer1.Box 1.Fill1",
[](const rlottie::FrameInfo& info) {
if (info.curFrame() < 15 )
return rlottie::Color(0, 1, 0);
else {
return rlottie::Color(1, 0, 0);
}
});
```
[Back to contents](#contents)
#
#
## Supported After Effects Features
| **Shapes** | **Supported** |
|:--|:-:|
| Shape | 👍 |
| Ellipse | 👍 |
| Rectangle | 👍 |
| Rounded Rectangle | 👍 |
| Polystar | 👍 |
| Group | 👍 |
| Trim Path (individually) | 👍 |
| Trim Path (simultaneously) | 👍 |
| **Renderable** | **Supported** |
| Fill | 👍 |
| Stroke | 👍 |
| Radial Gradient | 👍 |
| Linear Gradient | 👍 |
| Gradient Stroke | 👍 |
| **Transforms** | **Supported** |
| Position | 👍 |
| Position (separated X/Y) | 👍 |
| Scale | 👍 |
| Skew | ⛔️ |
| Rotation | 👍 |
| Anchor Point | 👍 |
| Opacity | 👍 |
| Parenting | 👍 |
| Auto Orient | 👍 |
| **Interpolation** | **Supported** |
| Linear Interpolation | 👍 |
| Bezier Interpolation | 👍 |
| Hold Interpolation | 👍 |
| Spatial Bezier Interpolation | 👍 |
| Rove Across Time | 👍 |
| **Masks** | **Supported** |
| Mask Path | 👍 |
| Mask Opacity | 👍 |
| Add | 👍 |
| Subtract | 👍 |
| Intersect | 👍 |
| Lighten | ⛔️ |
| Darken | ⛔️ |
| Difference | ⛔️ |
| Expansion | ⛔️ |
| Feather | ⛔️ |
| **Mattes** | **Supported** |
| Alpha Matte | 👍 |
| Alpha Inverted Matte | 👍 |
| Luma Matte | 👍 |
| Luma Inverted Matte | 👍 |
| **Merge Paths** | **Supported** |
| Merge | ⛔️ |
| Add | ⛔️ |
| Subtract | ⛔️ |
| Intersect | ⛔️ |
| Exclude Intersection | ⛔️ |
| **Layer Effects** | **Supported** |
| Fill | ⛔️ |
| Stroke | ⛔️ |
| Tint | ⛔️ |
| Tritone | ⛔️ |
| Levels Individual Controls | ⛔️ |
| **Text** | **Supported** |
| Glyphs | ⛔️ |
| Fonts | ⛔️ |
| Transform | ⛔️ |
| Fill | ⛔️ |
| Stroke | ⛔️ |
| Tracking | ⛔️ |
| Anchor point grouping | ⛔️ |
| Text Path | ⛔️ |
| Per-character 3D | ⛔️ |
| Range selector (Units) | ⛔️ |
| Range selector (Based on) | ⛔️ |
| Range selector (Amount) | ⛔️ |
| Range selector (Shape) | ⛔️ |
| Range selector (Ease High) | ⛔️ |
| Range selector (Ease Low) | ⛔️ |
| Range selector (Randomize order) | ⛔️ |
| expression selector | ⛔️ |
| **Other** | **Supported** |
| Expressions | ⛔️ |
| Images | 👍 |
| Precomps | 👍 |
| Time Stretch | 👍 |
| Time remap | 👍 |
| Markers | 👍 |
#
[Back to contents](#contents)
## Issues or Feature Requests?
File github issues for anything that is broken. Be sure to check the [list of supported features](#supported-after-effects-features) before submitting. If an animation is not working, please attach the After Effects file to your issue. Debugging without the original can be very difficult. For immidiate assistant or support please reach us in [Gitter](https://gitter.im/rLottie-dev/community#)
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0015/esp_rlottie | rlottie/.clang-format | ---
Language: Cpp
BasedOnStyle: Google
AccessModifierOffset: -4
AlignAfterOpenBracket: Align
AlignConsecutiveAssignments: false
AlignConsecutiveDeclarations: true
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AllowAllParametersOfDeclarationOnNextLine: true
AllowShortBlocksOnASingleLine: false
AllowShortCaseLabelsOnASingleLine: false
AllowShortFunctionsOnASingleLine: Inline
AllowShortIfStatementsOnASingleLine: true
AllowShortLoopsOnASingleLine: true
AlwaysBreakAfterDefinitionReturnType: None
AlwaysBreakAfterReturnType: None
AlwaysBreakBeforeMultilineStrings: true
AlwaysBreakTemplateDeclarations: true
BinPackArguments: true
BinPackParameters: true
BraceWrapping:
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AfterControlStatement: false
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AfterNamespace: false
AfterObjCDeclaration: false
AfterStruct: false
AfterUnion: false
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IndentBraces: false
BreakBeforeBinaryOperators: None
BreakBeforeBraces: WebKit
BreakBeforeTernaryOperators: true
BreakConstructorInitializersBeforeComma: false
ColumnLimit: 80
CommentPragmas: '^ IWYU pragma:'
ConstructorInitializerAllOnOneLineOrOnePerLine: true
ConstructorInitializerIndentWidth: 4
ContinuationIndentWidth: 4
Cpp11BracedListStyle: true
DerivePointerAlignment: true
DisableFormat: false
ExperimentalAutoDetectBinPacking: false
ForEachMacros: [ foreach, Q_FOREACH, BOOST_FOREACH ]
IncludeCategories:
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Priority: 1
- Regex: '^<.*'
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IndentCaseLabels: false
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KeepEmptyLinesAtTheStartOfBlocks: false
MacroBlockBegin: ''
MacroBlockEnd: ''
MaxEmptyLinesToKeep: 1
NamespaceIndentation: None
ObjCBlockIndentWidth: 2
ObjCSpaceAfterProperty: false
ObjCSpaceBeforeProtocolList: false
PenaltyBreakBeforeFirstCallParameter: 1
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PenaltyBreakFirstLessLess: 120
PenaltyBreakString: 1000
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PointerAlignment: Right
ReflowComments: true
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SpaceAfterCStyleCast: false
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SpaceBeforeParens: ControlStatements
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SpacesInParentheses: false
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Standard: Auto
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...
| 2,592 | .clang-format | clang-format | en | yaml | data | {"qsc_code_num_words": 173, "qsc_code_num_chars": 2592.0, "qsc_code_mean_word_length": 12.13294798, "qsc_code_frac_words_unique": 0.6416185, "qsc_code_frac_chars_top_2grams": 0.01238685, "qsc_code_frac_chars_top_3grams": 0.0, "qsc_code_frac_chars_top_4grams": 0.0, "qsc_code_frac_chars_dupe_5grams": 0.0, "qsc_code_frac_chars_dupe_6grams": 0.0, "qsc_code_frac_chars_dupe_7grams": 0.0, "qsc_code_frac_chars_dupe_8grams": 0.0, "qsc_code_frac_chars_dupe_9grams": 0.0, "qsc_code_frac_chars_dupe_10grams": 0.0, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.01615074, "qsc_code_frac_chars_whitespace": 0.1400463, "qsc_code_size_file_byte": 2592.0, "qsc_code_num_lines": 90.0, "qsc_code_num_chars_line_max": 55.0, "qsc_code_num_chars_line_mean": 28.8, "qsc_code_frac_chars_alphabet": 0.92552714, "qsc_code_frac_chars_comments": 0.0, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.0, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.01080664, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0} | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 1, "qsc_code_frac_words_unique": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0} |
000linlin/ConsisLoRA | inference_demo.ipynb | {
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Inference for ConsisLoRA"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "98476b7830664aea946698b0b1511c05",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"Loading pipeline components...: 0%| | 0/7 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import torch\n",
"import matplotlib.pyplot as plt\n",
"from utils import load_pil_image\n",
"from diffusers import EulerDiscreteScheduler\n",
"from pipeline_demo import StableDiffusionXLPipelineLoraGuidance\n",
"\n",
"model_id = \"stabilityai/stable-diffusion-xl-base-1.0\"\n",
"device = \"cuda\"\n",
"dtype = torch.float16\n",
"\n",
"pipeline = StableDiffusionXLPipelineLoraGuidance.from_pretrained(\n",
" model_id, \n",
" torch_dtype=dtype,\n",
").to(device)\n",
"\n",
"pipeline.scheduler = EulerDiscreteScheduler.from_config(\n",
" pipeline.scheduler.config,\n",
" timestep_spacing=\"trailing\"\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Style Transfer"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Loaded lora weights of the content image from chenblin26/ConsisLoRA-London_eye\n",
"Loaded lora weights of the style image from chenblin26/ConsisLoRA-antimonocromatismo\n"
]
}
],
"source": [
"# adjust image name according to your needs\n",
"content_img_name = \"London_eye\" # see \"data_demo/content\"\n",
"style_img_name = \"antimonocromatismo\" # see \"data_demo/style\"\n",
"\n",
"content_lora_path = f\"chenblin26/ConsisLoRA-{content_img_name}\"\n",
"style_lora_path = f\"chenblin26/ConsisLoRA-{style_img_name}\"\n",
"\n",
"# load ConsisLora\n",
"pipeline.unload_lora_checkpoint()\n",
"pipeline.load_lora_checkpoint(content_lora_path, style_lora_path)"
]
},
{
"cell_type": "code",
"execution_count": 242,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "b4b46ae64d33410ba5dd0595d72dafc3",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
" 0%| | 0/30 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Loaded input image of size ((1024, 1024)) from data_demo/content/London_eye.jpg\n",
"Loaded input image of size ((512, 512)) from data_demo/style/antimonocromatismo.jpg\n"
]
},
{
"data": {
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",
"text/plain": [
"<Figure size 1000x600 with 6 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"num_images_per_prompt = 4 # adjust according to VRAM size\n",
"style_lora_scaling = 1. # you can adjust to control style strength\n",
"generator = torch.manual_seed(29) # seed\n",
"\n",
"images = pipeline(\n",
" prompt=\"a [c] in the style of [v]\", \n",
" lora_scaling = [1., style_lora_scaling],\n",
" guidance_scale=7.5,\n",
" num_inference_steps=30, \n",
" # add_positive_content_prompt=\"a [c]\",\n",
" # add_negative_content_prompt=\"a [v]\",\n",
" # add_positive_style_prompt=\"an image in the style of [v]\",\n",
" # add_negative_style_prompt=\"an image in the style of [c]\", \n",
" # content_guidance_scale=0., # style guidance\n",
" # style_guidance_scale=0., # content guidance \n",
" num_images_per_prompt=num_images_per_prompt, \n",
" generator=generator\n",
").images\n",
"\n",
"content_img_path = f\"data_demo/content/{content_img_name}.jpg\"\n",
"style_img_path = f\"data_demo/style/{style_img_name}.jpg\"\n",
"content_img = load_pil_image(content_img_path)\n",
"style_img = load_pil_image(style_img_path)\n",
"\n",
"_, ax = plt.subplots(2, 3, figsize=(10, 6))\n",
"ax[0, 0].imshow(content_img)\n",
"ax[0, 1].imshow(style_img)\n",
"ax[0, 2].imshow(images[0])\n",
"ax[1, 0].imshow(images[1])\n",
"ax[1, 1].imshow(images[2])\n",
"ax[1, 2].imshow(images[3])\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Use content LoRA only"
]
},
{
"cell_type": "code",
"execution_count": 243,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Loaded lora weights of the content image from chenblin26/ConsisLoRA-London_eye\n"
]
}
],
"source": [
"# adjust image name according to your needs\n",
"content_img_name = \"London_eye\" # see \"data_demo/content\"\n",
"content_lora_path = f\"chenblin26/ConsisLoRA-{content_img_name}\"\n",
"\n",
"pipeline.unload_lora_checkpoint()\n",
"pipeline.load_lora_checkpoint(content_image_lora_path=content_lora_path)"
]
},
{
"cell_type": "code",
"execution_count": 244,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "d35f74dfe2854b77b206dd7aa2c953c1",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
" 0%| | 0/30 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Loaded input image of size ((1024, 1024)) from data_demo/content/London_eye.jpg\n"
]
},
{
"data": {
"image/png": 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ArZvgHm2t1ck5gGwcF0Cm9gCNtcbnDiuhjAFk3fuF3ojcvgjzSxJhip4jpyrGI1HhdMmYodSljzsi/80QxAyL7CoqcTorQLYLEGgC2r0xzvC7to5wNzHGadSBDYhhnffhrJvNiZtz5O56Ajn5ZnqoKSd6tnUK0522uZy3hDruBFSd4tjTyqZrn1nHXXei3OE1T3d78bv53p1N7p4uwtx+MCi5Z3u6k74OwJHv97qf/OSv6eskyyBqUdap6kfKsc+0esU1qLSMXb83z7+OFowqmFRwYSKRihEwCff50T2oyua0nTNthWxCV9IKBF/GOr1RZ7VddypnGOvT3HldS49t/R0s2ZsPf33MMW9aQAXwUz/1U/zUT/3UHV0ji3AuCQceIGYkmcggUUZUZDMkGbjjFkq6S1VCpgyVhOCYK1Uqe2I2JhKkAOKhrLaWmLnTeYcpjCRC+ypJdCqoZ5IqZqGoziwjArXHppHdw/slkFtHROmAVELBzCIXKamHl8Ud3KjRUJjdERGSC6pSLCFGcqX1CMOzbMzEqESL4l48ChLhYa4SPBUS96g10QBkY5ISjYaXJQGtwa6Gx8WLh6nyUMbbojuLwcwK0YOFoq3C4EUTATUnu9CVMEEzIaUATK1E+J0TIW1JUvGgBViq1MO7lwPQ9NYgJwdQyOHhgQB0I4GW8DRlhzEaOUCEt6pyYUaAAPAgubDwUlUoe+TIn3LHNPpQCG+PSHijDKg0Fso+7yh7jJdScqxwXON7I4g0UsBDGg+voaYyBwSK645RAYmdCCkFKFVxGhNqiet3LjSW0UII0ji0xD1HxXPlJSdOFaR4viYEyHNiHqkI6o6p0xVijGQ2hPLVJKaeqVAUxTRCMqUfMwdzgZLn1bwBIX+93I115I7kOMByaAM5QpE9aoM5rdnWVy44eGI2NHLtb0dtj8c1ZNlqKhuffUF6LeOQ1dXnWsrGEKpFMPAm0NRPKyfVo06qJB2aL8v9dqgXF+fL60r/vVmhfr3kbqwh64flMOqZf3OKJ940HH7487r0HV+58+nlzubD3Rjb4+0Vp4MC8z45fNVFGDX/xtmphY+9W7gwSaThfXX62JlYdiKaxS3ywqctvHQzIn5e3RNe2qeHYKdo70pzjvpy6b0/3X1OvKSsRejzlqz1N59yCt2JDfFeyZsaUN0dcbIotRg10OXwnLgoe9k4XymeIz9FqakdOonQsEp0YHtL6kw9Qp9SVeGeS+gbuMX/UxW5QmNPEermHqQVBTQkIFsGCY9SlRTvvU1SmN0smPzcYeTBTCgSoVutZzQnKohn6gkFKKQZomRROu8CMGmiNgdVMhlJysQUsaKjY4VhMELdRq7hQdJ57lAFyGgeyjUiiC3SSBgLJFdmFuCjspJrI5FrlPsVxIScI5/IJXwZBzgaSCRC47LQpehf857rqYCOotBblzEJgg0kwhnFI2RSNULY3J2RJhQHs3gW6dnu4rNY5FGZGyKREF9JCRmMlKhgbUQLYATcGJkU0pLonH11diTGQLQ3QCq4oxJEHbNwgjFGg7jEY7SyBZ4da3g0TcLTJlaApocnMHuA/E5BzBBXsmXGrjTuuEItjmXF1ahItKoRz10Wbco4FloIelIUxwvQDM9WSQ+jktJGCVKJqQfJhTkkgykGkhERGo/r1RZGgZboG9UArzWRR5ffODx1l+QuWgQXNZrVHeFuGB9Xd5qjnDbrzl134KF2HaV8nQJIrb3vhnYdeiaf79xLiqMv7+hrjc530cp7t+W0zTquu5f67mRuijeForKAed+kI3VmWfd6rg7Ribxzx9kfVg4dMPHi9B9eoT5nrvx4J/jqdZK7slwuPedyhw6vzmo/+4aul9DlWnMO2jDIRmifDJ1vJcfYCN2vzc5+J0yBmW3q9MWX+PATH21LK+duvOSG697JIrDQ3DtfS47azE7enNdD7ntA1ZmU0DVlFtpiKP3u7CTBpUUEKk+IZFoSak6XnGwdKlXh1Q6PlOJkS+Gl8cIehyHi7EtFrUobfgtqhH3rGEvxVGRABCEhogGYXJm6gTitGiNPuHW4Jxqx8GilQphgoXS3CFmMJAl3ZZLmoMM9QtFUIienFWXHCwIQIKVg8quUHU9kjamW3RAruVNF0XYgaQFgukApHozkNAX8aLn8VAxxSKaYCxOcGXG9TsIu01IWbhOSCg0BHkTCq6MIKlryekKhb0tuUb/cuwXoawkvGSkAoVK8TRJewK54HEmCuJGLdUhShB+OUhqY77qihLkEbX5brN1agFKSAMfDy63CRKPfYA6YBBARKgnwU6tHCGGMOiLxd/YgKTE3tICwqRfwXrxRjVvMsRICive5SAG4K4SWfnGO53CcTo2eS6pVD1ZFYpFHjLGmGEeUBEFc4k419HtsCqVrw8vlpeNFSR5jpsA+hkuwVapFrlhbALUVS5yYU7+Zd+U7laN3s/mu328yd1lbnd9+oSGHzHcL/X8ihqkVVexUw3cK2+Gd9sXQrhXValVpPHT8HchSvkuvja4qI3MFavk4zv7MG9q+jib98Hey8N8Nlzpi+syf+I2EWm/tNWRT63vKZ1880mMM1zkCF5eSlSsdcZeVX3zN5+E1X0RyvvaUxS8EufNpsW5inhAtyaZJvfD9SWbOESlWy8ct/CsrDZ61zq9/EyJJIfQNL0dG9FPRYpxCXpHiWt4znZYz3Bea78MN14K7NW2bt+jwb+uB4ObxXXet42QRuG9kOly85qnnT9EFV0Hbmg44Lk3sbsp9D6hqhJEobcxu6k5oMEQjDX9miZGDS2ZETeM5ku1zLjMhFOaZt1RGAURxjKTIR3ETRhqhfTuaaHCQhJmU0MCOpDWTVNFgJBLjAllMDanidZu4ggijVGNWavp4tLdxZyRR4yeF1k9CqKXC1SIkUYQx8xA2cyd75FF12tfhAq0qqipydyqX4iFTXALwVClCBzsLJXxSwI5JkEQgUijMgeKJqgkPXOOGd+EBacToXAbAVPgSBopwvExACcC0IwE4gtQjyCjaAhwqgVzFgteU41UErwJ0JVFmKTw0yaJm19C+3JMqgObwDpIiFC5TKOQ1QEcuIYJWvHZVAVWGDEBNiRpWWAFJZZZ02Rkno/WElvAp78Et4fRvC66tyvPtm1NLePjqkm9UCXTqmMWYGuG5qooyrhIEEV5qmWU3ao02tB71p7xYybwAow4YQSGSiEVbCE9heO+Cij7YEYNePhcCj6Dp95jLYqQci1QjMHKnLkDOJBgCE5Gz2Ph88/eT0sTe73IShfpumF37e90VOQ4xnvScdbvdSa7RH3vKBzr28NN2tKx4uOb/rNUalg5Y0y5Z7Z1BQ10+7ojmLDTgiDtuGLdTPP7SYXf5VT5qhsy/vR/Wj1Vw0kNUWcbeh44+ydOvzoPFHJz1V1p9Q31FYT/c6wtGgrAcLoTp3oXF5oSvz5mWoxPcd93lZOF3L3+I92VlFq02pahDieQQCXKqvj+D3LcP5PPSdz7kafc3OMihv1GOW1Ola31bN/TFpjfn8Iw4CXJdf5gs/HbokL4BZxyrVcr/VfB+ZKvXbBm9PnKv5L4HVI5hOcLBGu8Qhc4M6TxymsQwnMoT7hl3D9O7KqPiOZg5uCheCaIJFy21gcJL1LUW4VpEDk7SxKhOiMF+hlFVMxEHUSaAi2OWaXOp05MLuQKKJ6MrcXPhTIpFbKzFyyIwQhB1WgtGQfWS/GjQJKhc8SoH8YRU4MauVSDlZRXIUljjLF7ymsjz6RRmOQgcuqIoSyGYmBBU7gGunGkWdkVQNzqIOl+a4vqFZMEIz1YlQfM9daMWobLIwwqu8XhDenDiBNhRCcXcijIeENQHi5RZ1MQywNSiwHFXwJbHIpazkNwjxLCAIrcg0YhMOpgRZBmYUpVXbiQBtlrxQh3uYAEa1IXawzukyAA0KxFmxkAlnsVJlSBiUfTXnCQJs/BIGoWuXSJsry+W3OBUJlDC6bCS01SSsKqyQrcWOWKVJNyCEAKL+SUlpDB5jN+BeeQ65QjF6ztRCvBOfc4U0FowNzpQW+RXZfcgz/AIB220lMr2AGCdS9AVIbjEvLJCFlLZvWXWecOln7R3e6M/xe2PvvFq799NBfU4ZcpPcMzq8aeRxWc5yzOdtM82/D483sp15LST4QxvSFFuHQYvBywoEathj+vw6zo0s6RAbjj2LsrG2Xi3DAtvGtnQoWsHpSwovWFuzdnLsvmIxXycTcq1EIa6cQoCJBaU+UMlahcmhjs0VkLY7+ZgHfWwCzr1OiB6kkucfLGOvTaJlHIw85sXblv68erb8vADwsVJipqQwhDtgUew08vXo/blUjMA9ygHMw+PlxO8c4vH+Nq+6FNj19tpTj5qwzqzxi629O8aELNu5vuG31blJOmawy0X2/cGrB33P6ByyB71pcZE4n1CCz11sTIU1jIhoaJkidyiGcKoStTijKUi1WPGSWm133Ey7SwHeEIxraPmkwSd+ihFgeBUSvQiDHWPDqxFSKSsUZtKBCPTdJlRAUERJhiJ/6aKeQYNT1LXhXIuXU9xbfFcLiQxZoTHo2diA6ctHjDxCAMrtVsHaS0jFkyFnQQ9N0SNLi2seF1PzY0yKuGBVQl3i8UjLmiFdjtydSJ0TEV4QJVOIUp+RVgkGp6NLE5djlMPAgwr1xw48FzIFtT1KkqTy7WB3FAAJlgXdN6pEESoOHUhHpl6hKQlLSQRIuQCGsYI5inCO4XBRFJ5gAbR8E71RXdjERWmBbwkIEsp3CxRQ8pKW00EPALhzJ2sc4DtohEiUHKZxLxYuATTKKAsgJa6TgG1Akgb0fcBWqHNYUEbS3jmECEVRkgvBoKRFC8e4S2zDrwSGndSCfAeihRLUdoK+G6AsSi9E9fc6TwYDCt8MHUqiubICexeT7/7Gy1nxSuLe/xJzj9Rlx530DqN+rSy2tizXOeEAGbjb68zil29/TotYviwro+l6MsLiu6dAHKHwjgzv9AqIrrH3XQn+Oc/odXhBLK+N5aGb+1cWR7gPuo09qnl0fH+v8W2FokIsFMX4CB9xu0cNgznLqzl7nCrjbIly2UFhPkGeUI5xQS6K0vfcFAPHJdPk4W/NDnjKgyboRb050QHuvcsw85D54xHL6dIl1ggt3WPkMBvvJzZb5abN9hlBjvNgsFmoXFLw720aBz9iFH/kkNrwrBknEY2oPI34zv8ettk7ntAlbz4SVwgSSTIi4X13hI9dbSLk5Mx1pqRpgj/ShV1EsZakZLSIbTi4MoII4siowADldZUIuScaT2A0EQUPEUxW4kEfVxoMZJAXf6vLrSFvW1kQes9pSN5Ctrx0v5xqmiBKc5EFEvh3erpwx0gO20SJEfyTyvBABh90WEoM4xkWuo/BVjwPPeqjAmPUuvODkr2qKu0Q3h4OlWUoATXFLWXqhThg1H0Nhjl3CJEsaMwzRUShYoILxvVinfRxjqFVwOJ+k+7CB3hESoOHVR6Wvm+wK0xLd6iCFULFrqJK+FcLF6WsiV4UfSrAj5T9CxikTtkRL6aElTqLU6FYaVNSaHJ4b0SInyuzzlLhc5+jLAvkReVPWo2KQW09KuOxvWM8AiOXUr4YQDMSgohRL94F/IQESHnoI93h0kBj9OSx9V6gF8vrIq4FSbJqK2mGqyXYwcscq6S9YWgHbqeOMRLxqzTpRi31p26MF524qQc/amA5FKocFiwY05gXijiY76/VeWuWF4Xd+vTYIdT99tJTpYz7DR3ivDu9dZ2J2hknay2d8ESvPZRNj/fPIdiVYVi0KSWw1qWL3mSXusx3bG+4NWfj+quowDYmmk2KIVHt+Dksq5P7gtZBtgDuCm910PsQ+BpzdmHOc59rUl/7hFYUdRh4HBxYNqGsc98zWT3pbsMYkM71ryDG5TvjXLsQN+7daQfgcN3CFKt/Tw3GPcQdX5m2dqBqzfhYNpF+Rvt0xvCCNtlYdoauSefkDlsm4/kmudbP6yHZcMxC/Dv8C8ri8/qjFpsw6GcpXX36teDhckyPN8xU2PNLY889iSz4fUEVfc9oOoswEMnHZ6D7jkRVNNjgUyiFaOqamqtkCpBUmpP85dBQrnvzIIFj45ZoTFXDSKHfTMqjTT/REaTsmdOXZL2gzbcS3hWRxZBtGOWnRFVTFRzugJepsDu4F0KzTkT1NQjSbgqbl0o14VBQoi8GTNjIonWgmDBS9tjUuYSXhgALtj+ICUJiniPsK6sRt0Hr0nkWLUI2ROuJd9GNIq2ahTDTSlqJ1mJMU6VF4DgeFasC5rzsfT5VD7kLGWLEIOopRXLVeTqRIhZJ8FYF+BXGXkptEvcz3KEKhjO1PrXNwBFT+OuoghGlSAWlwj5VELxTwX8mBhZhZEL3oPT4oVRiVC/UdFgonyvME7xt3nUper15sqC/r0xYaQBUispBX4lvG11seZpsTgZwVwoZbyrwujYiOEGDcYohRe0lgCpuXiVOgexPsY7DUDRCeINLxtfFAqO0E8sqNI7K6Gg0rMMRp80RIikefFaWow/ZRxJEYZaXpXInfLwgrn2Vs43o/3qLSBHKbXH7hRH/Ogb/7jLsq7xbxX1+JS7/5EDctKxOGytls2HHnOpVYiz5iEW59e65q8Cp1PitTuR02C/t4ysDIUQpVBUlOw+V7RXnlaWTj7BPUps1vrRj/3GV35wnzPQ5T5f3Cn1k3zp8stob3liyMJ/1oKDNbaKM8tJtOkjj1u++SaTiK1DkoeuFPrUczf6XXzl2j7Ps1q8dd+fm4I4+nzx4eYD6FkH/Q43sz9KmAMiL3qeL4yfsHDgXZDV1t3FSy9d880k9z2gypJpCTa11jXY5lTYkZrduqZLFS6ZWoNy3NQ558pMhVoUp6XzEhIlsdBkrISHJdwSLk4yR3PknmCQNZdaUB61rgyyKa20jFEqMVqCCa4lFya4COlCExcYLyQxGi6RvzRyYeaOEjWosoQ3xQqpgYuTVAp7nxTiBArttgftdlTDpXIQtAAhJRPKdeUgWakUpgKp1K1yIrwvSwCVqo48rL4dRoCN3YrIW9MIB0Mi/K5Pem2AVsOrkcRQZCBPiDAzoRkU8QCY7oImqEvSZq6jLf0iYGVVGhYNC7pzkyg07BYbl3h4pqZ9aKKU/DSLQrWNBUAZS6ErzyBidOKldG2OQs5VFMnVQhXeWDD9WX9dC3BZF6r2jgA06tB2QWGfSpu7YN8PAhKJMLu65D5Z4XDv865cBHGhbS1ANRI5fB6hGrXF/bKE5zSAnTBDgmiieDt7ANmIl/AFx5MiOAlHU1CvWwFLiqIW4Lo4Pwv4jXxCIEC/xbwySl00jdw6O5F57S0s9/Lx7pbysXTBe223O21DX0c74klvtXjcScZgWHzWKzmrl9l4qQVL8PycXoW6E3/pCR7iRH1znN347ovf0XO/CaW8girOw7vCTiXsd/DS7VUINJ+APaHTun5YHhFfuscikFIRqmQRWdCvySUSIsrDxP4RZUhiz755YDR5BdIdcjksA65N83pJhvP9iN8Pf7EYgLhpVhw/M+/+3HV88MZsgjzLYHT1h6UPcb4I5yrh4iRqcY5GzqiKWpdLY0gYVZsOmlwAcd8WDx3AvS+NEjlv12aUcd00YpvXsUOyMs/WnT98dYqu33Sl0+4WRz3l3ZT7HlBVVgXVtATlwUgrNCmTusbQCMPTFEqvOeMszCRqRSWNcMDOnFqEWdfSFHCTVMiWyRiVOF3u6LQmGSTPwSznQluKzHoSkmbMlUbjeoKiquRs1JIYk2jUwlVMAKwWR0iIBz1cV3KyKnfcwsOSU4R8dVoIKUoOkghUKhyUosKtObuaqKrIo6pUmRKKeWvOCHBRRIS6eMSSR+0pnKi1pFaARSy4OfR93IKUQ0RoS72kVPqtc3A3JEFlSps8PEwe96twukrIuc/RiRyvuK4z1gB7kqL4cOVxnZwij0gEKorFzcLU05qQkzHyAHdBPW6YBgmEOuBWQiUF6AEeUVC3DYa8rOEJw4MgwyWhCchwIM7IIBdwpCJM3cpiF5vRTK34+YQOIZUaZIUDP0InM4xSYQss7bXyR4QqRp+bBSDLhZii8ULFT2yyWixO5pFDJgQpazAHhpZWIVQanqyuChA4raI/vWhyIvH/uqz+E4l3QogQTiUYjEaiJXwzmAgVGEuEQprLULi6lgBmW+Hwir5pV9i0Y9y1XeFkN54raie58Rl/H3bNDQ99L7DWScZhg5Kz9thjHv3Omr+oQK7/9ejrH6HgnEZeB0SzBCdk0Wp/Hxhk1uSvgHDQxt41zRHtsRQrRezjO5Xw2AXjmRuJabfGYzS/avlyGaQMOT8ijFOEp+ORN9x/LzCEbiulZEYu3pnF1//QUNxbgL22CCybPToLJ572Rstvylnm+8rLuAygVn/YDAjnFyv6jQjjCh67lNndibD/fsycILNqO+H6bdhrwhCcLfQJH6bUHBT3jIWLMgzx2iVYWEq4P0HnnrT7zmIvPPLaGxfEfq6f8CZnkPseUEktjEaCeoWoImmEUMKdPGo6VSWUSSzhKRYSM8OAmUU4YNtlVDRovD2RrCN75JQ0nqlRpANXJRdWuwpBXAdPCcWtH+FagicLt2uYnphph0gie1BO18BIUuTXCFSl9lMiAFEWo9Kg6K7cY8JLAWQWng7TCBEkhSfGe1IKYjEVoLEcFOweSnLnTtZSy4l4G6sCqjRUfGqN65QyXBHqp+GVES2eCQkmPs9GJ0INNBqsdeYFAEh4Z9QdLSw3JKWWyIlKfSiEg+YIgSz0DWQPq13nAUw8B5FFK4AYlVHAYRTybcuGVpWaYi0B+AK8egnBI+pcEe57KR4+LwyIRnjzEBiJ4SnAbeTlKeMCMpMGBbxrJKxqZ1Q5nnVUVu6wFEUdr9YLs19wvQdhSqm/JU4wQopgpR9biXzAVJhFRigdTpvCU1kZwbYn8yLJLdEf5gFwxv0c8LD/jgIll/QppxA20lHCA9QGoGhl3Mwdl8hJ66NVRq6Fil8ir01Aq/tAIVqVs+wEq7Ju8T/uWvdMsV3UmO6yR2BVp1/3jFL+sxTrdpfAwGo73iRSTCbxx4nadnjCrCrUJwZYclasKvesHw+15S4P/xsrwmGDhXC7hf0uFL00FIj3hTOccQXjUUSfFGg0eET6a8vibVwWh3lJW04aNSBzhv1GcJufJ8S6fWXHubKbeWpfyaZzZXqF5q1X6Hvwt3DHuRzxzi9Bw7WTcQOYWvPdRpy3SWTzn6fl0zh0obs2X539Dpp9Iym8fBARQ/OxLSDJY8WetQGk+jDNZZKLOT3/IkbebFpbHcfFCXXWp1k+3Vd+dE4HeE5iF3s95b4HVJN6xCSNmbqREXY8B5pXGYgOBMVzjuK8OXTabInkwlg1wsfqoFGvcijPPbSoqZBU4Z3hIpgoiDH2YOMzwmNjZpyrKlpxjPBOpBxFZpMlNPV1yoVRCSOzMttrgewV6jDRPp42AFuHM0pWWNTCk5M8aNXNYISSCcr1nhEuFVDVaNBrj0zBIzcniwURRsFnYyf8/5TCuQ4TIhwsExThnTq4MC6U3Vi0w6qY3l6Y/jrrax4Fw17Uy4LGDCRo31P53QpICjAVAM0t+r3Pu/IceT9VKp4eiZC0MURdLbywC8aLphIhkVEnLIBNJNRGxLNZ1IlSCTAkwtCfSGxCThk/gZFE+1LJyYrcKilKkhUwWgCIljHLPTlGtDcXcgizIO8QiTDR5BHapxLFkSsRGryw9UQ4ZhwfQNEpIYbWew6djiDFmLjQ+jz8UVSRxiHFM44R0JhzYwlAWREkI51EKIE5TFSGMIMUU7OQTUT/ZCHCXMXxBI2XHDcD6d5kmuydyurKfS+MtMduzKs33bw1Hv378bKwHa+53jEPLRs+bzx+nea1ALTOKmcemxNoSIfMuyft837dj0NXC4Wub44s32bjLVbVl+Xrydpv44vhkpuuvXDpu6o/bpD7YfVwWeklCU//5UkhLlIYaeSuugPiS2D7xr4wVsMq4aCTQcEtKvXihZlrpytt8GCBNe89GHMSDHyI1SiKrRTFu1xI+pna39EX/jpBMOpKe9aO6es00Pf8Nsfd4ATvmCwYPHIZr6ZZPk/mq0d85bI0H/rzl+ZI2bN9PqwsHXyXRESWGCHnbVy43zpZM29PPV5HPcs9ZBy+7wGVm9NkGFHT0WESYXeKU2siE0pzhaJU1IUGYqeOULWa8NR4BzM6VEtOkYfSmi0HKNHETJxao45PJhZLd6hTkBq4OZUKRqLWMt5CoT2P8KgZAgm0cGHnAgpGBJEBqqgFS2Gf87SfBU1C7UZdwIyIkaRiKkEMoZ2Qq6CGz07kTHlHQukwXMObVomQSg5UUi1heRTwKcFKSKm5VWLkssMkRZ0jrBSwdUeK1U3cGEmiEUMKSQJZEAkmvBrBrJBCCMwMqKIPciQXDUWBg4q8KP0aK46LM7OoKxb1nRxLsONpyOUJpkUrXsPwwtSdMCvA0wvoCPrxUujYwxOHg6sP9SSUGF9V78nw2HVhJk4uG1PG8ZJvF4tXeM9EPWo2ubPrkKsAkq1GvaysIBa5TFEUmBIm6IwsiED6549q6s5YhewBRAWJWmFEjle2ADZKGAqiCx2tCqAFakkln89pAmsGEPdCQV9y5qwYCQKqlpj+4u2ryDFernTEe6Ml50stPHtvZVmzxt/hgQty1PFHmfPW/3DERY+y5x0+fvOedJaHvEM50fS5y206lYLhLIV0ycIH5/CFRJhU9RBeW75aeAJf+mf5j0X1aF4vyB2mbTtXYha8FOtGenAErsOvC7+/kbI4BG91ULWWY02cc3Uf9UHoD17Ml6VchRXg05qjGsZIcZ0DGBn+w1xpXv+um8N+uzgHeiC0OJucq/twbT9Ijeb3KNeRw1/N/94wmRaO6//wlWPn83hR01/kyDz8Tpx0TqwzGhx3wup7ck9k7bVjjHcrYbcOwqs6BflZmDQXmtnrJBpzyczDqOmhczRZuNWW/uy7zwUzuN2V3HNZnJlzmoq7IcfaexaOO+qmR60Bw3RZd/OFk18Pw899D6hay1RmSAlHM4RUBXCgitypqrCfJRWwCsdQE3YIhXGWgVKQtrWMpGKPsUIHThrY2KLmUQrQpVHw1cUZMUIEOgTJRnYhS8eIClEneyYTeTrZg7SCDFZFoeBshquTipLa4KgqdSGTEY8aVx3OyCNfrAOShaIeBWlDUe9zhWpJBeRFf3TE9TMwScp+dsYSoK4poWCKMzNhpDLk5YwI6vEWR01RcaoE2QXphJwU8Yxa1LcCCeZFCmFEr0kUADohPDZYqbHc086VelUj0dKXpe0eRZZbmxckRoMe30qIQi7Fdz33xXJhDycZUZNLQapYoEYIlMWrJVPKggEgHv1hZexFoq2NhrcuRzNpXUgGM3cqjY1qJNEnVSmh3lG8X2qleHCJY08lH614hiiL5liUhpIHhaFavF/uAcAL8jWnFIV2xqJ0pcCgliWlYFSAANQedb1cGGpxdTgzdyZaQh+LVzU8aTH25oJahINmYahJlQrk2kGD5EMsQhPfqvJmafqwIxzVoNNshYtbzPptdPPVjgN0DAqTHLr04e3xpBvvsXIUZnw9ZAM6kRWmNAHOjSeklIZT+nW5lxjquVLZfznoCT3qkfjDgXFXz+dIObDLxs2DaX/FBQi2WY7tttcJ3SzOzjfLa3hWGfJQFh6kM+GZW71nCOZj7atnDsq09/mpEkayNhfSJmF5/pWXyheuUapZHAbuwynxsrrPGV/nlz0Mb73Ms6VlaQFpLb3XS3NmZQL5qodruV3L4Y2HjzrRdDzjnL0bzvG1sumaxZA6qoTzY+F8pYxHKepzFuSw6Ll0h84yreUoNVN0Arcwds86jZB971l+S6726l7ih0bsLsg9hjGrdqp1dzv05b1bvO57QDXQhjuIKlSKeFFWOyOlKBbrStBio6FkigW1eXmTIlQsPERNl6klMZKov5TVacwQD09VJuPJqDwVBrQIkWswRpoiR0lgoglyyTERpXWj8sipqVMie093TVgyy65yIEalyghQ9Qj5ykGAIRLMe51kXAvdNxpMf+5UVMwsAFbkL/mgaONGgzAyOChkGrOyaAsR/mciQ52j7MVrRHhFTA1EqQvoqjysJtmjNlSjRDIYHvk4rkHMsGBU68orbURe1kxKqGKm5OUk8B7IgrvRECe4BAOiJBArZBjitIXuXPABXPYgRUTDO6cRW04J5xMRXIyxx6LkEh6X8KQVq7JHHpcBufNiISq5cwKizrhsFFpCBvtNCmIzzRK5Uz2QllJU2oUCcilU9k7W4s0iD2x//dpQJRm8S3UZWy/kE0J4ibqAkkHlTyzOs1LjKnnRzZLQGOxIAKyZOGKCSaLrYi7UQMo6eMK6AuSyCBMPgoqmYOAYTaW9Z2/46ySLoOBNpNktq139N7LhCI757Sj15PiN8XBbjju41+zkhHc4Sk6wSR5lel29uax+f5LBP+oGy/b41VGQhaOWlN2iBcu6E/G5Ai3xno/rqledh2ZrznCw/t5n0i0O6+yHfj7zOG6arq8TgHvdRKAfo2xr3sqFSSE452tl1MdZE4bFK+eMcyPjyWtKk51LIy3kS/PrtybsG+xUEWmz3zr7i+HXIiiliLxECoSKFapuFgCVL/lG3MM4eLtd8G7I4ZE/3vSzONvXz5zFuT84X33ethPNtTucP7LYiBXoFw062zXdfQGsLvw2gOj4T29YluFXCpCN/92YGq/sGU03B0tO6FE29NnqPXxhjm3YOQbSknkbix39lAv+nclRlz/5rUuj72Fb73tAhQuJDFKTO0fNMe/oFJIasxyWf62EyhOz3Eaongh4JnsKFjO1KCBrhhSvzQzAlKh35IW20hkl8CxM6aK2kwiJyJXJAKokd2qBRsPjFBamcJFogmm2UhA1aMrrAqoyxlhTUWwD+AVJhXAOpeuMTgHCE9YCqNN4eGOMFiSFwl1C91zmbIQITHsqbXOyBZDKKZTzVKxXLV6I6oyKFEVwM3QYkhYIE1SoizLf03hLURBqBdyL8i00bmWhDJA1c6PWoGyf4WBpIMuggMJEjAUiZM/ULuRSPBiNsMuqEG2YFaVfAvBkDYBQ9VTnTtQWI5gdW8LjJQSAq1xKGF8QeYw1GBU9R/JnJeE9MiUoz/GSQGqMyupfF+9NHyaJC50KrQlJY5xnDqqJyPqDHem9jc60gLNg44vQAM1KZwGuvezG2aMPzTMqQpMLayLOTGQo6jwqczlgT4DQSqJGWeUxP7JG3a3wvFkp+hhhA/274Ahjc2ZSQhsJQ4MvLO5vdfGTrMWvo+K3Dg6tB1XrzpKlvxblLDXDDrflCHKEIy6/9px1GtVJGnLasTgp2LoL4g57zTTCpOd2kcLctXjDMpYLbRtXFaMqrXzv82MX/hVCERtVaQgFjBxVXz7lrM9xwu/uitwvoGrNc/jCf9cd07njeQ67s8OtBlrTwtQXe1qxoQYhkgMljzZAUV/TKOZFQkv0RB9+V5T7EgJm5S0u2Awb7s5CHaOzPv7CA5aL1Aojnc/b/pBBZxB6ziaywbQbNJhDV9+0sp19di6bQ5aD5E5+hbXvyyqByMrgh142/27x3j3oGtfCpd35XMgZDlpoun4Pdg7yvPVBkb/4BGU/8CAS63PLOXzIHPAfJ774TCftp9MdvfaWR+0B93gN+U8AUDmdJNrcMnIhE+FiboAnGjfqEr7UeBe5NMXDUauAdNSuuAWjX0cw1lHoxMfaq6IwJcBRLuQHqbwEvXI/EmXsiQPvIGksTBLeKYUIM/Pi7SqvjQJ4EBDU5iXTC1qMVoTaoo6RlcSglIIxzstLI0QeTeWRF2QlEbYpyjQeL2ytCaOQLBDAwYjzTCCZIsnpSn2DvlisE2yJCLhJ8eKUFbwTWo3QSJdg0esJIhLCzIxxqBRkm1MNWWGIG/V1pjRe8h2JhWHWh1d6YcEjFP1RqSMGimiJKy4ERbVDW4CbeTAQRn0lASv1mDS8Km2f8eMRgqPEePdFD1vCgpdLGGhOMVpGsDuOpRTWlfAMtl4AEXOa2j7fonUKJNShxlmKOMLwQhG5cyJSapUJlQkNhimMPZj8WuIZ8chjymKlX4RdDxNXW4DnqLRDyxzLxLi5+VA3rCPyCjsPDveMMPPIHxScGR61rxx2CsFLW3LD+gLFnQWwFhGqFevYW1+WgcnrKydRDJbh1eKZx8l6HXv9/fyIP+ZD3gMhWTpUhnPm3pRVOLHYbl96grMjp7Nt2Sc9emFeHHGK40ybZjhjjov60Kz+aXv1qddOBCYT6qrUIVgFmMNt5/9Nmrhy4XyhT3ZuHhwwaxd8xmsG/MgZdieg9TSydO37wiQDnL7LHDjoYA5pQva7+TXBuTqz4dpa7hNLsjDLAaBVhKrkA0+S8fgFp8vw9A2lteVCr5Tz46/VQe8LwcZ+MXgtNrxdm4JMF+fZSJ2dek4HHv/v+yx0gqqKW7ZdRHi0dszMOHTb04KqTavF/PuNVzzJrYoONn8H+yeP9TPULY9wvQ3XVoFLO4mHLkgBnE7TCc9fN25PjWxOm2FqMtxnXMEDkxQpJCUqx9zpsnO95M4dWnuOfbDTfj//dQlBn0b6reXYfj704Z7IfQ+oxKDJVkK4nAPr2JEKFBrrwsuDl2KqEa6UPRXvREWSUGiDLc+oSmFYkVCeczbqlJgWwFLjhcwiLPhePCDJhc5zYdIrYVN4CfXyef6wwliquSqU45U1dzQJDUHprh7KdycKXZgeGo+cmYwwiirBaAbTjsacMRGSZxD5MIS1CjGShyclVUqmMAhaxhSUoMEOlj5AooCse2z87qX4LjGh1PoY7IxbEE9kYmEwFyZEAWR1YZZjk8hFgailXLd859G8yNPRCKscF7DoJSZhpNHvowKOOsKCl0r4o3hEvLhHyJxJhBualZBHD69ivwGJyDCGlUHWaHNnQQ0vpiQNr55KHCNE+OeMADfJ4vm6Pp7RdfDAYUpdgHlHANGRRH5aG0NOXVaIAyIcI5kzKZ3fe6k0M3iHKory5V7OF5IorpkOgsrfJdgCPfLYRh5zpgpNNgr3FiKUMbHAVkQx7OylhlYhuEj0BYsDMIvEccnL/E8FiGoJa9HjVry3qpQd6g3AVadVDWATWDqb+MqHQ9cu7/GcRmrhX5fDLLzl+HWhPMPnQY855imO+PkoKPxGzFJZ/DQAolUwXI5a7Mp1eYlrH674C2XB43C3ZENnnmVurrvOCX54y8nmd/CoXtv0vcz/278/RM2iUZLhyz7gNKmzM4q9alw5ly9EuHprRtP5vG4RPkQW7HfCQZ7Pmzk5xMKLf1S7Vo9ZWS4H50tJJ+hD0YTewFJyzEoucLD3CkkkInCW5uDR/XR62TRaK4BxBXcVO9G6KMiNsngXpwAch8Yc6Ww5BLO/Z4Tr4BmkJTyThErYGswyTNtIWxhsMkS00a1ZWWlkDp2yyZxAqgDl9V23unif/DmHKyxdd/UmJwBnfsY15h7KfQ+oDtw4Z46kyPuZaJCLZ1GSRLKeUei7i3KaPNT/hEMBUC1RqylJWPQ7gX3PVK7UpMifkZYpiVSK97pZeHpUqbWiIuimg4k9kELvLcuSMI9FUPv7ijBViyK9RG6LS6bSSI4JcoEOT/E5aUJUOSfh2WlFiHpMFUjUEIoirxr5LdpbgnxQ5htrIBtN2zLb22O/PcBzy2R8jvG5C+ymXaSq6DDUnFZisU6FoajLBHmGh/VI3KIeFTCycNt3atAGKAlg21tiQznvRJEyZkLkm1UOFG9MpRoeIqJgr5SwSSGYkKaF+pwSK24lFM/daMXCW5JhhlGn8FyRBVHDidy0mp66PsI1s3jUUnJhpEEqUnmMWaVRzyxbMAymMlZa8qNwSBIuPxOYSgRTBIkHQ7Fe976mVnkei3BUsyCN2HfCAiWUsMlgBRyrFCDmhQo3PF4zDzqJyDcrni8in6zz8Mp5Ib4QDwCkHhTvuXwZ/3hQLlp4tzohzGIWNO6dOJ4JkgzmpBvQc4lELP/9IWuW8M27zj28da+wnG5LkZW/1pEdn+RJfPjPyvceJRrEyv/dUYxUzIhZlKYeDbUM+u1xvrku9uWKFrbayHXK/LqH2aD0D3daOGdxk1/u7t4UeoSsoskN4kvtOf28cS8e/RWdxst/pbd6s9ibPniovLdYHWruGuPAavOO0/cXjl83iqeR1dF/q68gqwaC04Oq9ddad51Rgp2RDGyww3UFRsmpq9hDb+5H6H5SZ1zNw8Pc5/k30wxzv/GaAV5p+XH6dxgffc5uWQ6pe6erzP9Vem9brFUaMWnhQfFqAW6x/H4uTr5DDTrtzDzFDO6fs7xifa5X37TVO29aApyIBmoMcpvZz1YYk+cnCjCuDdWOWdMX8Q0dJbvQ5kglCM/jwn09PFZNYe/SpZattHAp1HClsbKuZzb17WqdNF+7Zpz0Wuu/P17u9Tpy3wMq96gHJFbIB4oiWeWMSdB7qwgqKeo1kXETktR0yamzFAs9jKpENqdGsZK7VBW69FziU1UzYpHonylhfdkwa0ATjpJyKBYHeHiviPk1EsW7DJLo1AqbTwnBU/AuU2vQeVtZXEw1KNOrOkANARamlks1baBSag0yBy0ehsY9mA5LxuLMjReuPsvTz3+NZu+Am6++xPUbVxlVI87X55i2Mx5793s5d/lR3vOe7+DCZBerHTWjFF2ndcc0FCqjFJX1sCSpW1lkImRNNbwhFYKlYBNsPbyBFeAFWAoBOJViqdHwsvT5PFF814dFS5SBrp4CFMwjfK4qIKVCwwNZVmvHkaRDPSjVIOPQHuS50HqAxHCPB4OfA41Y5KZ5vzRZcdOXOk4OSOSvdR4v3JhgaexDA7NEMV7LJRG4ZE9JmTteVufkRFFkLbTsGoyHQVBhVIX1Lxgefaiz5R61x2YeIY9KgMSS/kfyQvDRg7Ug9KPz2PSSKJULjURoaSpaaCsRstnkoG4XMTpkYE5sxUqQir7llaGQN8geduRtj1LANn2/rDGfFpRtPNrh0rWrfPvNV5h97Sn09m0q67h4bsL73nsFqWv2W+FfXXw3z73tbQOY6+vdzDHVOtB6zGOsfjdc4thde6McxmnHKLvHabkbrn9c76/edW825WA2W3/vJTy0Ht1kt2I6PAqJlu985aIn0/eH8XyD3pi3hNwrM4wT+VV7rTEUdy17iAOyTyzyS2cs/rWsXPceq9VjV9u/bqyXVpqinKsE4Es6P2DxXehByOjWDUZNQwreeGp1zIMxtjbwruJmJ1Al2s6YuWKXHoCqGu4uw0OvWwfOOkPv1FSweIXVHoxrmgmzDrosa8opyPBJEVTqKOa78Hvfj3lh7HzhPPHQkyp1JhGwhS+cF1FR/VK8fPfOSvrDSuv7I47drk725cIl58aA5dOCNG643xHGs3nr7u2adN8DKpHwhKgbbaEYT9bXK4qwPfUEEkQRgpIqxayjthGqoXyqClM3vOSQZIRzpX5PJpL8p14Y2tyRwrpXp4R2QkpBfW4Qng66Qm1ZkpLVmGYv7HYt5spIlcYztY4DJIzimbIZqRZqr6hRci2kQgThAlktyA9ESAnq1Id65QgpNGXfSviHCtmMJhtf+dYXeeX5Zzh49ilGkrl19SV2d3bwyw9j9UWuvvQy12/uU+mYdz/xXiaToP1NRBJkLdCpIJrQLEzMkRrakg9kFgvA1I1RUhwLlj2JkLS2vBzjTIQSFlCTSm6PlMKyZqUuk0Qs9SgtUsIKlBjxqq9tBcWDVLw0EmC0zwfKqjQEIQQEgUUQiMR4tASAyX1x5BxA0QooMy8FeiWFBaTUamphyFWyQk8ftcNgVyIPTUWHWh9NCY9LPTDSWLiqJJALWMURNXY00aAl5y0AbHJhlJyZKZWEtcrcGKkWggxwC2/aiMjfUiIssUWoi5dMvcxJifnhEgWPE71jqt8YFUxIKajyrdQxkx7JeoRwzlIwV7615U2oGp5BH1hWgjbtPpsvuopThiuUIT//9d/j/ftX+R++9hzfnB7QCTxeJf7Ea9c4P0lctUz60AV2die0mugmO0jd05gcc/dNhsrjGtl/Xkj+PtF1Vq/SLzIbkZOv/XjoWoeasXq95XHxlV8irLcoEr4Mi4Yb0KtV85MH6mlZvs+hpvrKuf1Bp9T+7+SNOXzum/D9O7WsgpJ5jsryKB5+sU9rFsgeRuDh/NXuW/p7AdX44YMGuvfV49ddauly/QXnTzf/dxmhZyHCN8zwnPGuw37xl9m7dpOLKrzQGY+MEq+Z8/goDONiiSev7XM5Rbz+Nam5+GM/yuThK8zfndIGZyXEjKX7n05O8DJsWGrmPbrcL+taECzAcZQMt5XhhB4cCCwRW5SFobzzi3edz6JRgp1Koph0VSJ6FhppXkg/SsRM/zy5MBwXjDusiVaM/Ef259JPpzUlbDheVta/4Y9jy0zfE7n/AZVnyMKBdyRJA/155cqORjhUC4ysZSQ1VswmVdJhDzZzPBtVFTQGVfGetB41d8iKSXiPzDzo2U1QchQAxmm8oyZq+njHEColJDoyu14DEUIYHh2lM0NJ5Do8OolQvpOm8OyI0wQ3NVUO9jZ64JHmRWg7oMuRD1MRnokKLTqv0eWG2eyAtLfH3ld+i9m1V/Ba8VlLe3ALOudmfpFu7wYXLj/M7167yv6tV5lcusS73/khdkYTBKHFGJXaRI7TJqUmlGoFWg12nloLjTtCp0YNuGcqNHLVNLxokfsDjQeBRF1BKnlPtQsH2ZmVPLIJlNA/SIV4QvAIq5Oom5QLeFGV8Ca54ClCFSsEzOkk7usIYj6sTephwzF3Og0Sh4qgDDePfKKeFdAsI0RYpZSVKFO8QCJoCtbF2lM8ixE5ZQRVfB9BJuLUI6i8gC4NgpDWhal79JswkIG4RD0KISEuqPesir0yNQ8ldIlFMIlQx5sCXopAJ6cpfVVLrOG5B4CEZdFKuzVFrloiQkRmFiA5ZpbQIYxxbt8P+tAmOYOyeSrZtEeduU/v7mAIQNNR37zNLz/1Av/DM89y3eEDdeKLTctXc+adL1/n/TuJp3ZHPPjyN/l905f4iiV+6/EPwOOPskyheMLOXOz3QxrnUYjmdLc5fLk7H+xenVrGfrIA2g7fyle+nHeXrPv2kMQ02qRcHqMkb/ryKI1wK0tyGFYsK9Xz7+5UzngN3zR71l9v00wTJAxo/Zwup4uEV2T+9PP+yAbNtetMPv/b7MxmHDQdP/fUy7zSwXlVns8wpqXTxIPVvHboVw+csXeM1ZHa+UNtx/hQ244CTWft79Odd9jEcbiFi32FlFBHWThrJUTSF9eKhVN9Efw6hbF6+a5JoEpOpT152XJjhJIOYJCSLFRniKipSd3TZUQbot5V6HdLN1+86Gm6bJ0F4VT77EI4+1nX/DPIfQ+oRgoibTDAeVBSiyhakpl2EMYYnmoyCRMrtNpSiB8SoYGGV6MrrHFJg+Gv6aLuESYklHNJmFmHVYqUIrKSlPDHhNs6u+GewoOiOZjgsLD4SyxGRh+KCDl3ZCRCxNxKcVmjLgWEEXCFUXk2IzwsQQwk4cFQ4UDgvM9Z9FScZ154mt/+wi9HiFgnPPS2D8OlR1E3ulnDA5ce5IWrz9A++UWm7QH51ss0s5bd1LHz+DtJJD74gY8EuYZAzkHOgRZlnAVAQJBRTEQZERTmMze6AphGCA05LB4EYcc0GxNXskQBw0qccarIFstx7YLkoBMfWQAkJ+7dhwBWqVCDe6ELF6chQF7lguYI41MPkBrWIKfxkt9UvC6VRL+bOOckAHc2H8BSAKfQVnI2KhESQisw1jSwB3oXi0sucylTLD8euVQVlJC98N61pcKxSAD2fgF0j/tmooAzTvGEAiV3rQI6yYWvXwqleQCrWuP8VLyDqkplMWcrDBMQL1S6hVHQDHIGLTujl/DAmYfH0FyorScaiaLS6qdcTN+SsrLarz7vmZX3cu5ZDKlnlkH1PvTtoSOLpTQ99yIf+uxn2clTvtJlrrvRpYr/+tyEK0n52M6YDzxygU9+5yMwzezfmtEKPFUZ1/s7HWKpWJCjnt3XfV7tsLWtP+LCm4mR72Ro5+cIly49yHg0jmsu7PyLnxc1i16dWkyA3zu4zayZFsPJgg16QYnCPaIj3ObXG6zdazvvpA+x/vPK13dt2r7F15ChfO+QUBNrcRKlTkKTgyF3nSP1uL+Pk5OMw6ruWpq4RspevuE6O5Xz6K6w18DNJgyDFF2mKrTouSRpaYq5OuuEazf24BvPMsaYAr96oLySK5CeMTQMtcwKA7I7LjWgfN8DNd/+yEUu7u5uju47k9ypxWAdcOo/LQOfJfHQJSQvnmxDyRnvFYA15DyruGMRxgswqYRJLRF9pT1oWznfA3SZ9MWd5/1gBk3Jie6bbUUXOvKBWD5n45AsWplWDVn9ZY69SPwoZS0dDvdYJ++V3PeAqs2BNiIXBHa1GgqgdsnwwmpSdQSLDNBqjFoFuLdBLSmOeWacS90gnDFOLQkXI2vkTDUWcatY5JV0EsV9k/SIWUkSFN/JYFbY9hJE4r8qRmEIxEhUhc0mWPZUtBARVEP+jQPkKDbclRcBj3A1EwtQaU4So01aCgQ7GeOZp7/K7/3bn+Pcgw/zrvd+iPPveJjR9AFGoxG7D1zmoQffxoNPPUmVM9dfeYFu7xY4XP3ybzB6+RUe+dH3USUNpZlEFTGUCEEs4QXsdQ5VyU9yIvzSPcIRzYO846bnCDMzL6x+kVfWFkbALgdhgohTq7DjEfLWlgU641imLN7BdNgQIC9J1MyaZahLSGA2hoKzVfGsZaEwOxIWmkInLiqlb1MUvS0MPCClblmMe13IGmYOncbfY/EIynNobc6GWBU6dAdGEmA9XO9CX9usy+E16jzATfK4T4ORUJQ5WGxxpA0GyVwo+I0IxRsVICUpwkva4hXroNRJC7bJxvt46jguI6QurFwHFuGLQeUf4QBB6Q4oTHNP/hHvlBiFkGR1YXwryp1urHcoR972dUVb81vi4Ip2mappmeWG76pH/HO7xc0uyjr8gQu7XK6FrzQtX37hJr8/G7nreC0rH/vI27CrX+cbLz/D9YsX+ebj70fren75Jdmwgx567KPAT6zrQsx5keUaUKvXXjp3IWaqxzuD4ltykk47BA9deYSLFy4xb8TyMy4qQhSlZmh7+e3lV5/l5u3X6LHSXFfXOXZy4/bBAU0bBp15IfeFix+Ssygd68foDZidb0pZVaalJAtdmjhPXFa+9LJzYJvPP+KCx3bwScHUZjX4uCsvP53SMyYXhd1j5nV97nGOcysTxrWi5txq4d83wlhrRgrvuTThvSUCohahFkpJjsIEbM7tDPsZ/sx7zvPtV3Z5bleZ5n32G+OWjkiT8UrrTivH98Da7hhuuvn8RW/dki3OY/9NhRm3ZKqUd78cvLFJPWgpxFKU9AfxwrzrPHo+sTsSXtkrBZ3XAR2BUSWkQmgx2Hg8wkm7rgBqXza8DerLEd1y6DufE5Qs2ns2Pt2JbUCv/6pz3wOqADE5gAhKl6KWU2T4V1AlzNqwFrnRuVN3iqvRaPwNERaVtGbmuQASZYZREQV5K41FZCbBPlNpVdiUjJQEPGMeRX6ROkDcuGIMJC8VgZIUmuyEaim+JxEmOPKEJimMPU5rHZVUsZGWsL/WA9iZCI0Xz5BmZh6KsQKenSBJiJoFb3/4CR5/9B3ceukb3Ji9RjU5j52/wu7j7+OcTTm4+i0eOKd89yf+AM88+xR2cMDe/j6XH3kf7/me38/7PvhBUooXs7XI74owNhlqI7UupQBfVHivJBR3F9ActY1mHuFymCMWnqy+EqFKhCyO87w/zIMCXvFC/SG0hcCjkqi33HiAoYzSSnitDEhdAo86TqmsFCqOdyBitFoWGae00xmXekriRi5EJZ0LlWoAbncsR96UlkUlrMTh/UEDOFYOIyKEriseHEsM4X6VO41H7tKsABhzGEshifASfifKqChQkdMXzyw4Bx4A9gIB8scidFihRIeRB2rKnVOXGmbZI+zRLNgeSQXouxQPWuQH9gtw0L2XzcLDWii5MGZqgM3y2LT3A54qsnl7vEtWr5N01Frt57Rqqxz+84jrycq/EbMfY//OX/zXfNuN1/jbCr/y6k1udcEy9a2m4Z9OD3jpQHjFhJfbzP98bco5jEbgR6/fYlYr3/PAhFcuXODJh58ogOqsKvjJznGE3d1LPPDAo/QhufOnW+2X9aQdsWwIZh2vvPwkObeHjjleFrLyh/sv3mFOct4rUxFyA70atDM5z9BChyHQZdCOirKkN5jduB6/LykkCx6vOwJRh69x9+3A988qsjinDjp47qbR5j46guM7bynnZV2/rHuHNr9XRyqwJzqjb7Sz3ylP3bShVuXci+LlkMVQdBhde40rzzzJlZv7/LEPX2SngnqcGNUponbQ2HcNXtzvgvwqB6PvLBtk4xFp2bv2Grtf+DV2Dg5IB8bXzj/O23/ke5fME2cziy0OyIYzj0YMLPVkyUOqUgAdWRz03s4hcGE3jJUHsxIxJfMaXbEuyfC+y8rtuuxcP5jT4EdQTLzrLx84o8YYLeYfLSyDffR1Ub8wn1+878WB6GKxW9ZNlqFRa/ab1T8OganVPj/0pEtt2ix3fyXaJPc9oHIElwopIXF9GFgU7gXBgvBGI1wpFfuKmpM8vEVScmxSihysyiPDvkUjr0k6RlqRSKRKgkCAULhrQvEcaY1bjrypVDFyDQa8QnkuRF7WjhZ2OxPaQqWuIpFPJQGoKo1z3TKNgJtwzmGKYdlIUiEljAuLt2IiQpuNlkI7rlG09eHH3sG3/8DHefZzN3nk0Ue59NAVXrsxxdubaB5hVYV0e7zrygOIvINrV6+SrzzMrZ0x33r567yw9xKPPfFeLl+4xKXzD1Br2D+78gxZw6IhlELBOGYyKOZCeJD6ul0tMT5KPFdfI1iJsAiTqN9lHp6PAFHhoUoei04qVpSeLkjLIt4VZWJGAGXtApy4lwLGxP3rzBDWGV6qWFSSR/+ZKFUB2U4OK1zxzhxIUL9XhHXHsPA8WYTy9UQTpGCo6Swox6dSit9KMBmNXem8FBmWAOutRZuCHCK8Up2HV00D9dCVnq77+lEU72rpXxUvlO6Bwy3H3HeLGmcqZaPzqE3WhyBOHGZl0RUP7xMShBxtAX518oHJcazQudEVWnjsNKbXN6ts2Ezv1lo+mAHPcvIdyppH2wQcvfzormRzvvTMM1zYb/jhxy/RnK/4+aduYGa8VCf+g1Rcf/gxXmuF21ev80qeMfZM5Zmnb05xcf7FzSmTy8oThZ0r4veXG7G+LWfvK9WK0ej8Yo73msutB5WLx2frlpXbE4oD12+8xnQ6DcKd/jllkagAVBLVaEzSiLKYjEbsTiZDmM4DFy/zwMXL6++w8DwGXLvx2lAgdBEgz9m67u58m6vYd+li94MMSuO8x/db2F9jdZq/Asf14qZxO9t4DlP/1FLU3RLGP3+3+j98Pi2LoZpsNC+9zN5/+CJNhk6DO9094arUKUU+5iM7vIbwf/jNVzhwLVEPCffE5Qq+fRzRJJ3v0bXBwHzxPTPe3qMTnwOAEz3aRjvB+rHw1cMOfTd/6yLHKUqJdAOXsCycE/lhB7cqdOHMITSvB2ALzRjOlnhId0oJlfi9Q2IR0DBmjxNcGS0akObj0z+hGwMgg/m/lTi+oNf14KoHYEstEo/2DHeQAtD8mLV9UU6yivjCf/t35nXcP4vc94BKxBjXkaQvKTES6CxyZjJCVYqZTr2jIlFLqRItglRwXisySlItCXyJRiJrZoLRdTCSiqRhtVcUKlCzKO5KTasdY01ME4yLpQGRKJabI1fFC+mBdJmkkVzjHnlZrZS8GY96WW02EkQ9Ki+xroUZTkUin6Uo3rlYIcSFWiuQTCXGtNlnrzngqS//Grf+wy/xoe/+KI+/+91c32u49FhF7vY5X8243u7yie94N1/4+itcvOT87te+zmvXnkfqMdPdK7B7Hpne5GsNfOIHfpQHL15ECHAjHoXlxENJStJ78ILe3fvCTDovGjwRYSpGI4KLRQFhiqWEvj5GhABqedmdABy1KzPxKOib+2TKCHnLaBSrLeF8lGtVBMV4U/q7YC/EYEq4yCsKCYQItSTGKW7aGmiWEsYXhfcqj1VlUIrEC1AqYRAiuFkgOcJ7MxGhtahtJSkW2M6NGYAo4s6sbEoZL2AoniNYDKVQ7wcdu4rSiJVivBJhgwJNYSlUp7D3RJHfykt9L4/+UQqTnzt1jmtBFB+euUf8tDq1FKODUABbhMm2BVS6yJy6/QxK55tVNhnjluS0j7t2v9hwp9Xd+5i95mgVYPFCx5/pCx+ql17kkW98g3Te+aW9Gf/iK89wOxtdF7bp/Tbxxf2W//y/+TSjh97GhbGx+xu/zXuf/i0uvWvEow+M+NKvPcOv/vKXuXj5Ig8f7LHXjmhHY6Qu3pt1XbBxf13+4ZBOJIpIGsCQWxeKwzH9sFYJ8xL7kLu1DoJ1CtbyAc7LV59bauQ8hLB/bAFRLl5+mNFogojwwLnz7E4myzdae5Pli1WpZne8E+HVzH/qug73fPg0ChmTO4cLCJ9cgb9fcNDdlUFlLeM31ywP95es/LvhcnBkZ69T9I865mSL3PK5vvLFuvssqr2eOw5+4zf4xlPP8+9ecfbFMYvIk0dS5k9eGXMhGTdcubpnPDnr+H3vuYygmBuff3HK07dgr0k8OzPwqLU5kRHvfnCXtz324DxEbqkB3jvX18udTtqVzljtyv7nKCVnw0FOqEP9ZzcfcqbmFww9oPfurTZWkKHMymJDREDUSSqMkhRugeU2zcF+KFazDg7axTU/yrzEfh5e1t67FkkecGHsQYc/PKPQ5jC8navCKHyj8cNr5go43DwERw/OpnMXX5FVGpi7Kfc9oJpUdUmKjJC5gDxh7TMyLonaDJEKq4IZjVL0N9Upav2gVFKRS2jW2LSEmVVoZcHuJ5Gb01sFVGGskeOCVUhSdjwx80wnkVujGNMOXC2UXGJTdRzNEb4WxXsNS0LnRpWihpIvLMReVq+xAKSBDCBphHtJtsiXEUgo04Mb/NIv/nNyntF+9T/yHe97F+n8BZ69dovzFx8m1U6aZR67fIHbTz7JZ3+rQ6qa/WnH7NY1Dp5/GtfEvj6NS0W1f5t9rXnl8Q9x4fwFpCj4BzgoQyhDbSDaV2sKL5ZKhNV1JWxOXREL31VN4I5U6QJVsKMWxfw6AmCKxIveEMUusws7ojRuSCVUGGrhHO9yYQlUDea/YmXRokmE96z/LtrfOIzK8SOFrELQFUeOkxG04X1ulyBDjSwdXuFSuyEHBbkKQdggUb8rwjMdcoAT12DOE+vrYQm50P9ZDlAZztC+mFRUOQ8LtDB2pYHBODAzZ0eVrEGYMdIS9inF61eeeUcS+ykPC4MI1B5zsS39lDXyt7KApAByWhgytNCsVlKIRBSSLcRI37dyrAq9fFgvSzvAKXfyfqdes4scpwKfTEXe0J7eUvnCc3z/7/063/UXv5P/5y+9wn//j79GXiBGyJa5fXDA5/4f/5D3/eDH+c/+d/81D//6b/A9u87DowrZ6/jI2y/wJ37sO7CrHd3Xf5ub7vzznUd58UMfKuv1mpv3yOOUycWaalKKnIqmm/Hii19dLnrK/KOvG8/eELOinlpu1uif67f25W8XkdrCVcWX7NZh5ImzrLcgrV5dlq8deo4P8+OhKw/y4OXLCw8Sa8XLL7/AbHZQ1o1eRQuF57Wbt2jbuUYlC22919bfo5Wqt6Y4UT4kCgA6Ijl6chHhLsmmPt5gDDkWWG3u0QF3nKHTl98GWfjUX1AWjvVB13c3pi+8yIvXbvBSO2JnZEil1KJcHivf8bYJdaV8QBO/+eI+v/BKw//5j32Y3cLA/K+/epVffuoG/+PzxswAIqJofG6XP/knfz+T8ztxo+IlWWrd0Kw16Get+OFjF/tgse8XlpJ1vZQEHtwRRrUs0ZX3uVM9BXk2L3lQwk499/4MBo/APUEI4ULTwX4THiCzeY53P7eSGpOkPDBSks6rQw5rBb3hO4jWmhQG8fk9+/VkDuVieZHinXLOjSJ1wUv72gxdIcSq+uicY6H26WR1hm2mS7mXUCrkvgdUmcL0kbSUXBVGVTVQRjtCK0EckAkGOTw8OzuSgl5a4/9jAe0ENACAuRWilbDU5wxumVoWvR4RYpdcaBVGhAcseTC4jetoVc4B3ISEKzTEMeGZCUCRtAaBsQdjU2M2FPmtNK6ronSacRJtzoxUS12kYAVssnP71i2e/51fZbed8uEnHuPGrWu03nGbCdPbezzy0IM8MFZ2auWHf+AjfPY3nufCg4/zSLrMyH8fT+48wAvPfQtvG7zLXP/W13nbez7BIw89hvfhZkSoWNDHxzvYElaXpI54hB1SwGFCGKmW99oQBVdhhpO8eOTilyEEMosz0fBKCRIek6BMYCrBJug2j9fORPjfyMHohmSn5CVkziEnQZJgCXYp7HWpLHweeUyWQSSUjlEqz+URnkMOENYD5D4HyvDwjCKMC1V+U4CneJBDeA6AV5dFVVyGYrtOgLESoVcAFqUvoa9HU6WYV2pCXa5biQeQEkdL2KB5EFd4ieFOplgyGs3hPfSgpm8k6k2lApoyUEv0sUq8U2MR1JRGnSwxtmYRllmrYZJ6h9z9Kb7yx5HgcUVRPxJMrR5z3L1PJmfdtBYVCgdu14nnuhE7//46F78+5VNe8SuSuW5zpYls/N7//G/Je7fR/+2f4tnnXuJrv/ENtLvNh8/XfPflXcaV8zvP3CR3xscuneNiHvFin918qCtXTJlnfLicO3J3sGbs1l/DV/4ayB9KGxdUk4VPG2DskQrXXD0Ifc/pug7KOzedHbB3sL8AvpbvMDByCYxHI1IxF2tfxXxx/nkwe4out9ZXlM+h9StTd/0z3ku5DxaRYSIJeGEQpoDkhZwWXzll42uwrksOzWE/9POR555FFtexJWYCWfh5Yf5LGELzhfPYjQM+nIQ//PCEKiVqVUYGL952Rinz2G7mZttxq+l48cmXuHKhIonyiQvC+995nqs39rnZFnCBMdkV6lG1RMzSI53Dr/ZqR552ddzwjm+6nITh/b1XnHPn6v61Bu89wgE6OjOmrXPQOlWCRy5K1KMs1xCELkdIfTah7ZzbB/DS9dBDWxNutMtmIZVg9tOiL61uL4KjYjz8IOzsJq5fzxzMcqSIFPDZj6xAyeeasyKby9B+9zBOHwC3PJ5LZWFrXAGHAyW8rzVlre3K/qjDU3YV4mu5txSSlHu3jtz3gApRxlUiq6A5PEbizg7CHhSgFIq3SHgf1JWRCgcYaqEgArRJGaVQTE2ckSWmEhlQB96xYxFG2JghaphJ1P0hiup2pQZTgLnwvuQSgoFIKeob9O6VGpUGCHCg9kQCZlLslpoGanBTpcWpTWmryH1Rh0ackUUI1jhF3lWlzrnzl3nfOz5A99zXGZ2/wt71m2jjjGthXO9y/vxlfuQjl7h+ew+pL/Cux/f50vPP8fC5MZcuPMT3f/KP8vWvfYXKlOnePnu544Mf+xEeePCBqJNEmdKlPlKnYSGqCuhpPVEiysCVRLy04e13lHAF1hLWji4LVQkDVC8eHREqU2YaLmY1EC/9kOYLTh9qFpafUoCucmpX9nEmHqCmFUNSgO8mCxOCQXGHngTDmbqFdzPH+CfpwyyD1ME8R4ilOyNXph7Mfp37EG53LglIeCSDwjPAk2t59d1psQKmYglps4XXkaiZFeA007gyyjDyfk5GDqCbMysgVCVIJkapAMtSSDqVPLV50nqxWFl4rARKWJ/QOnQai7DnUutLouAxLuy40KYAqoXzZLCmtS5Uboz1LGr8W1T8OFB16ISFzyc9b81OfYQF9XRXXPXBLHwqup9aS/XIZb6eE0/92xfwa1M+ZJnflsx1eoU8NCdV5cb1Wzz5yjW+MM186fnXaJsDKut4rFJqnJud8AjCD7xyjWuPCZeHhIFVOaJ/1ibnz8W6Fsvd8BzrnvDQNYohpegTg6do2VtzfPuOxM2DcjOHrfFXKCzTvdfo80Bu34CXX3xq/QP2VygK14e/7dt54MLFDcAtjh2NJlAMf4vZVW6GyG1W/XHDiTLvKpGzzN/Ty1t9BREPim8Aweg9rD2/yyAry0exly1c59R35lDv3YVh2gxB/PCn1ffNQVLikU/+QXafe5pvfPaXOZhVmHSMq6hT2WYYizPJwisHzjQLs1lL3k1o7UgtvOd9F/m/vP9SGE4tdIObUvOlmzfZEyWPatLFC8P7u9xMX/huAQhtekeX/j2mU1hcSmTh/uE5euqGo7e7JXa73jPsxD5qFmH0KcGNaTGeDgDVcQ8DdICXYLSe5gBmec0zLMJcZ36cLzRWBW4dCAcZbu4LbRvkGYuwpU/hCJKM/oIliqaAKvcwqDY5iMjClizUCc7XUow2851G6Of4MvA9yTaaDZrOD02x/gJJlIfPZ2p1nrul93CF+k8AUEkhGzALAoNdjGYgBagYE0xwLgFm+gT+mXupSxSTpgawqOdUSQRyJVHGBZknqclVzO6RRbhVEDR4MLQZhXghLFJNZ1Hcl94qIezW4c3pLJIqWxfqVKgrq+K9sELZXtoqVQnDKiFYI61QLyEjAjMybo72DGwJnBZvb/HEd3wn4ytv59H3XqSd3mb3yiNcGLW0+9d55uWOZ1/tmFrHOx68zLNXp5x75B3kXFHbbb79u76f7BOyNVx75gt85T9+jrd/4IOcqyd07qQUlhIzIndJg30vacTTukiptwS4oDk8OqZKpUBJPHUP1rhZyaUKMg6jwYY8twqN3CQv/VYyMRuC8KGnm1OFVoTK53lHGWdGyaXyCJWs1JkRC8nYdKBlTwUFVhJhgObCvoWHrRbFKwdz3CzmT3FxCzCWFMCMUhyYsig5uBa68RJeCMJIIha6UqeLzLxQr8qiIx6Mg65CTmWuC3RYCQeM/KXOS/8TxZ6htyQFADOF2pQpXgowC3WZk4jTWo7jSphrlrg2BmNKTa/CeDgqSl+mgN4S2ugLiuhbUmTtxzu/2F2VDVbojUccfY11xw7JyUD95Dd58Wtf5r+/cYubLx3QWVMSlRMwJ1kYn9tlZzyhnR5wDeeRP/un+bUv/A77zz6HYlztwqOKCs+qUr3jId7+jncuWRGP6rGTQsi4xlyJXffMx5y89HGTFXXjeb3isi55Q2ItmMOp/pOXe9n8fFuw9q/gQl+8nujyO7eqsRdL7ZXLD7FKfQzB1vrKtRswm5WWzbX8QxbeOQ67h3LPb/C6yFwtD7KrIeRrUbFfedSF6mFrf1+SdRPTF76QxYM2t2/5L1/34+bLrDbx0HkyKORJE1U14t/vZfZuzbjdxlyrFHYURhJMs7e6KBVz+8DI7QxxYXdXuXxlwngcRm8pepbs7XPrX/0ir04bbj/6EE/8kU8ifWLPhvZu7pDTzrv1MHP+ikSu/Yt7Cyi6eCbTgHhCjxTv/T/Cawfzywc48wJs+hvEceHdmpNRDHc/hCgjR2q/C92mDzfE4eo+RLxW0TmAiCQqa5PLvHhw/2ALdH+y5KGMUkHKHFSNk5ayQPM10cv/ltbHtV1/mECnD9uer6HzpqkI41qYmjLLcdy9zOe+7wFVFiGbkiRj5kyripEJZCFVFoQTGEk1CsXlUHBFYUR4ejoNr4So0FjHWBRLwXSWiZC7HZQmOXUOb8OYSH7ucoT/4UISo8OoPJHdh7wekfCGdKWIVOrBkji5bLDBQhdBZImSK6NOItFIMVGgYOGVcXHIfSicYJbJyahMefGbX2Ss53jgsfdSX34nOzuKmjCup7xy9RaPpIbffQqaC++FCzt888ZVHnxgh1eu3+aJRy9zc39CJYnZwU0eulDzw5/8Yf7v/+xXuPbMC+y+/wkqwpPixcOWLEgdTMLjNNFglKNQpVcIKKQctRP6grKG0XoA0eTBYHcgQdohHuOhBjOCij24EmIhQgjvikQ18LFKCTkMJb/DAyRL5PyQPECRF9ILnLaDaRJq0WASLJbcFsCEBmOs0eZWYz6MBLokiEXbIrjYUTdcUkny1qEh6s6oJ8oQqEqoo2VizliMZSrLRRRsjufTMhfUA9SIG+MCrlW8hCka6imUsi4KF7vEvK1U6LMBa50b7HqrlTilvpjG8mpBumEKfa0pE8OyoOrkNt4bUQtvVWFtjPn3FleIhFIQ8JTA8MjDF3/c1D8nUt1XrnO6Nh555XVmPxfaV2/w/O98g+9DeEaELw6b//xIEeUTP/qHec+3vZ8vfPkrnBtV1Jcv81/9yU9x9Xe+yjO/+Rtkg73OuNG0TC7u8sEf/jg75y8xsIL11zrVE216rmM0Qjn857BFH33omh+F3d2LTCbn5lTHS2fNP5sb1197iWx9PMKqlB5Y+kkG5crLITI/knWBMPPLLYC20tZFGAfhwd4ZT+i6hlW41TMRmhm5a+dNPNQHdyZneNve1BJviBfAGwp0X1i1H5LVDBB3hpzjRca13vu7xNm4qk3O0duhlix/WtfLy1aEOV3/8i3cl4msV4MWD9H0l5/GN17Fb9wgNVMmr13nI+dGeD1GDDw7z02NF1qjA14zp5Egifp7LxzwgbHw7buJ3alw8B8bbnoCiR0Sh1mX+fzNhie7TLo9410lsuRwx5xATh1tAIcfeKlLYp3sx7uAj0klPLrb14qKo8yjbmUu4fPZoLHQ6ZKGYVehhPmGh26/EW40TjOsD4fb4mU8KaF/UTOsrLVSzCc+Bzy9YcYHw0sJeZ4nog04cHnVDin2V16Z5vn89sPgZ7mPmF933XGses57EDcH/32bmmxMOy8g896uKPc9oEqawJ2cnYkKZEM0vFbZFJMAQa2H10KSIGJIZzTqhSXNgubcHNOANW32QqQQ+vHMMtM2JozhTLSmGzCOM8JpuvBMNB7fq2QSKeJGzZCqCsuERk5RzqGwAlhWWom6Th1AsdyYR90nBFw6IIFDpT6EbmUL9pukcLu5wbe++Dkef9e3MavPowpdY0wm55m1+zRXn+Mb6Qpv/74fYIdEqmpmzRUObl3h9rPf4mvf+CYXzp3j1v5NXrh5wJfN+cLXJrRpl5defZ5zD57nwsXLUZsLI6uUcDLwDPvZQQswyPFydS5Rj8ED7GSLcD9zYWyACl0BG8lTJFwiWHYozIkWl2VacoLq8vLUGoDLgCoFXXukbgXJR4CZ8ETmwrgYYYWQUgCrXNhtag+AbmUhqYuVRjRFHauyCrXuJdxOSCpklVLPrFQdl569J4DSVCOksCJY+RDCk1gWokqigG7jiouhYtSm5H4e0DMFQitBhOEE4APlgMhn8xKimDwWTrPiIStWoaq3FEnEYJvFom0eYNKIXLN+kxeJ2lPqBJmGRK2qoLsMo4Dm0v9vcdb0022pbxR4PKsKerQCsPTRga7jsb0Z56qKP/Hog/xPr7zG//X6dayERpsIVzHSuQs88b73cf7CBd73Hd/Fq08+x7WDp/g//Rd/mLf/iY+z9zee4dzDl2naKa89/jjTpMxeusrvfOtFXr34IDcfetuRXXnyXl535NH9NJyxSdc8tpuFyeQBLj3wYGEXXG3HXJXNueXG9auwYBU+1Pky1+sORSUyNxCvqsrxceHzWi3mMNxDlPe/99uCkXTx8KJomRvXb93kG9/6vUGpvqcib9xbdddEjKHeBLF+jqrw+MvaOVWAK0GmNO0Wi6zGCXOa/eXzWJhJc1mjXA/HL/4+Py/IBiLcbB4sFftIa2FYW1Wge4PC6u0G9Tt3nP8Pv8nBK6/w0gymrfDH3nGedzwwJncwmzn/7uWGz7/WMVIl03EOYa/N/NotQ0z4zp0Irf+Vlw/4F68ZXqKGKIa/Nju6M+YDjz8W+YNrJ8/ilyvtP7PevX405r/I8A6VgA6UILN6+LwzqkJvEKKW1LSDWeu0OUIgyY4SeVijVHSi8m6YCbnrGaEPt6TvnyHvUyQMuB4RLBD5WsH5UbxWZYyt5EEN1DVe6lPafKZl88NzAejDhhcBzYDF1syRw7I6P+O7deUe1g1dl31l/O8dqLrvAdVMrRTlLaxw5ow8YRLekSQRJpWyQuWFqjKK62abh1Dt0UaoX9DukYlwOi3JdkFlrXSAkUOBLnWsmhJ22OeVaPHWuIX3aOpGJ8LIgz68c2OkKdhWLABJMNpFjkx2xy2TU8QaqxmQcDVaySRJzMwZUWg4NbwcN25f56nf+zy7t17isd3H+Opz+7wtN5x75CEqv0F7cI3rV19m9/0fY6eumM0MCqh44NIj3Ni7ydvPP8zbLo74H3/p37I/a7h69WUuXbrCzWsvsvfKN7nVvMaly2/ne77jo0HoYcXL4U4qb1GXy7S32CxEwg0ug3XEaYg+GiuolgLKhJcpJWHkAVKS9YVjI2QtWXhLkABJWFDISynAK+LBmKhGyuAF5LbZGFFASgV1koGqPfggDUkRrqgai2ImvDXSWYyJBJiuNUgZkhQac4/Qu44ISdRcaOU18uj62llarGHqxf1PnDcTG4o/W7jvYqNVJ2E0DmKRH5hLuCcuwdTjc4/oqCyGjUTYX+UBFmORjX6AYPwLBCzkIE6k8vA29SQaBkMEVQDNOFcodae6WMT68MPmHr3f97+cVI08vbq5esa6bWtp6yna3OzZ57EXn+d/88ffwfk2852frfkROc9Ngkm0AX6ThrZKTEYj1J137o64/Su/xe/84q/ypf/1Ezzxv/o4v/v8Tb7tekdKyqWPXUHPG+nXfo+PaObfN1P+1cWHqMbVQjuWN9C5fbR/AFmDNhYUuw3607rvfF0HHddZixnXAwCQ5RMWdvxBaVnVRdc1zZdrVQ233qgb+PxHP9RTJ8HQYYzUVFrK0Cn7syn7syl7zQwIptBhMNZcd11X/ScpC1YJZ6E4qvocg/SKcFmXYz+kkGvHj/O0m6XJRFxCitFOhr/nSu7h2eW+8NsiBi+gSsWotBgie1DvYezMNj9/qKNUDKPrpL98Nue5125z/VbHP7ueQIXverdQVbG3SQuvmfDlA3hH1fJfPRIkS5+/BToznm7gf7phjMR5sXWumhQjJfMOdOc73v0of/CHPopoWloxDq1pi61btaScdlk99C6vv4CszIVp63zjGghW+jg8TtmDdGIokiwg6oyTcF4TXQ7A01kQm93qvBhv+9dRVm7Yt6oEE5Z5ooQe8u4H4cGLSpX65nkZ7zx4qNzBO+Fgmnj5dniA3OD6zNnvFvpgxY4jK/2zdq1wGFcwqrTkZhbDrvbG5jKG3j8FC0aeCC+cZaftc6rmFJqLd1k7JndD7ntApZ3D2CJ0zgCc23RECF5GLGrw1BqfJ5pKQbMODzdSqfEDlrTwBAbKH1vk7owkcPuMoE3XAdF7CcoKCrmgzhYqjepHbQF5qY4QsWDAC8W6yhkSQ92iSlIUHdawQHQeIWUqQaKhyXHT4r3K4W0ojDlYKPxf/cpv8ruf/X9zSeHCyzfYmyo393Z55dkpH3r8Md45abnxzncxefcTHDTGdNZxvq7Yn04ZnTtHPd7l6msv8MDkQfZu73HtG/+RG6+8zO3xDgc3b3Ju5wKzgxu8NHqID73v25GdCZadPXFG/SKfnaoKwKEQin8JIVMJj5v1ibvCkAeECFNK/0hYx3Kh9IykSYIooiuF46Qo/oXJb0S4zlVAWkFF0QyNB4hOzkACMfKI8U1Ef0bKXRS5RcINX4lAjgruVupFdOpMkhRqcY3CtrkPUZTIqbN4+7vIamIkJaTDAVFUQczp6zy6E6F66sOClgjWyT4cwYFxKenVOaUWVezC4jrkSzUeHjGxmMMmgpQ6bBFOYkPYY18cWQqwFZGhnpaz4MUTpxVBLEg3ZoTlUISB8dDM5zHXb2U5sWa4XnnZfMF15x/1e//bSY5bf8byeWseaPWrhRCN7MaOws4DDdw64MJ+xzmH276gdKkwGo3QWEVLmInTNi14h9U137h2wMtfeZWnBfa++C3ef27EpRYeuzTh1fOJ2Tu6AVDNIdXCxizHDcWqknRKOfLiK323Jh5qb/8WOWdUlMnOBE2JueIqgzJqOZNSjaqQc4dZx7rR6nHR6uMc0lEGHXsBeC0jv5XLL8+jZYVzNeDPefW1V3j2hWfW3J2z9/UGGZp5HywfUOLgC9jtTLjdLHiRVgwC85zFlbf2iC5XcSZV2UeI/Sq8CHJIoe0BfZjJVkQgSWZ3bEySsCOwIwW4ALOsPLuvUZPQY6lvixejv/rK7YYLmzufuzll73bDno25oMLXbhnPNQ3mzqyBb+xlrs6ECwI7O0ojFa+1iQdmDS+1madvZh4YJS6May6ei4yHqwcZzHmsdka1c7nZx5/6Fvre9x9+P9eJbPxjg5xmUvbQ1gvoLTO7RKR05rx20P869/j2YaJ9vp1IjJaJ0Fns1W2Gpgtj6kFngydoESv2AHmpRRLzxQbw7BzMnNduGpqWzVZejKgDoMrOdObsN4V0wvsSNCXP25cm2txDL2tqUK20bFLBufGc1r3NzqiK3Ks0rxw8hEFmCxDZdY4kxWYWhFkL91+6xT3M577rgOozn/kM//Sf/lO+8pWvsLOzww/90A/xsz/7s3zwgx8cjplOp/yFv/AX+Ef/6B8xm8341Kc+xd/9u3+XRx99dDjm6aef5id+4if4hV/4Bc6fP8+P//iP85nPfIaqOl2Tz0lF7VJIBqJXRzmUbdwwNc6loPkGZeqZ5FFAVZTiOQIkLHV9OFWFB7FFDhDlEmFqdQIxpbGWpEKyjEuEXplHWFRnDUkUxcgprCeJvvYIxWsGFeGl6tyjrlFfvFc1WAARcmmjiFMnpfIAX7UGjTXupCTggrYHXMozdi49zGtXX0Gokb0J7e2bPNvc5unrz3Cr/hDfnUYFmBktcECmBnbOP8BLLz/D09/6Kt/9/if4VjPjy6/tM9s7YOQCB7e4+fUn+diP/TDnRhMaC4W6tqLoS3gKQ1mXEq5gQdYBdGJ4AsxQj542KAQh4Ro3jX5RzSW2vLAmalhpIArpZov+1BShbIiTczDWRbFfLxSixZNV4tjcnAN3sodlzizObyxyvUQiNI/sAY40nqPTAFlm0BZPVI2zt7/PtWnLuXrCpQu75FK3ybUv8OwkwgKDQRvFI2jxAJOlF8SVRNCUpz63D3ALQo2WmCfu4YlzC+KSTpxZAVKU/ky9oadUTa8s8r9Uejd65Fo1boPXj/IdBNByKIWMveCmIBFRi7w/9ajP1pgFu6IdkRT8Jl9DYlYtWBxPsjgfhalODMyOE1n+eMz1VlTqlb+OOnlZZZ+liv9f0zL+wh57e/v8+v6Ur7mwJ+FJn7nwyHvezY/8kf8lk8l46DJVwbCg9X31Fr/QGl+/vc/zJKY3oJYZY3PGL9zi3R+6wLfvjo6GjGt/PC2IOgqebJBBQViwAK85aDq9yXR6C1Hl7effz2i0u+Z+sfY8/vhF3OH6a89y/eaLm5vhxQuwcJ1+9BYVqOFYVkdvTauH45c79MaN68xm07lnjEjoPtjfI5I8TyZ3Ms3XGwBOJm/OdaTPoyqKKj4om33I+CEIVb6Wldd94T8L71j8vypGMJE5r+CyNSI+dhbGNCFyvxfbmUWYdkqbYY8S5o0WACVBzMTCHFtaYGTNl/H3rsB/8YF30V69wT97fsrPX5vxN393ryjiZZUVQajIGPX3fCfv+/D7eN/+lH/0T3+NX3j6Kjc64We+92F+6D2XyCRyhv/jL7/AN19u+Mm3J0bjzMz2mD31LfyJ94KmQy0Zbrdugp7FMOCbThRqhQujvi5klFuhGJmKzXe4SO99qUv+t8hiAd1SpxJh1glN5zSF2S+MokNQ3hyUeVwjST+GsdePEqV0ECVsV7m179za9/naIfPxXQRUZjawCrJwz2GFKfN7uTeO2hTnstfArITLBN5UxlmpJoXluPfQFz3kxsy53UQJIZVuTsix0KdLVdPvodx1QPVLv/RL/ORP/iTf//3fT9d1/OW//Jf5sR/7Mb785S9z7tw5AP78n//z/Mt/+S/5J//kn/DAAw/wUz/1U/zxP/7H+ZVf+RUAcs780T/6R3nb297Gr/7qr/LCCy/wp//0n6aua/7G3/gbp2qP1kpXVUGpmVtUSslEFSqUZMatJjNRwdSopGJaLOtjyySFhhTEFQiaIr2xw8GMzjOK0OWYrJUkshodwTrXeYCIKKLkQXVOVAR3M7rsJA1KdKqy1TkFADiqQZkdC2QorrUKWSt6zoPditjkEXY8lGgR2C2MehDI/qGH3s7bPva9PPy2K3z5yVeoRzXt7RlPPPYwH3vXZf7dbz7HhW97P10K4DfzjnHZvOtK6VJNIzX7+zM++P4nuPD4R7n4bd9DRvFmn9HsNV56+RU++LHvx6Qo11kG5sSg1w7yhBFCq0blQdEpGmQVBoiF8q6E91AJ97dovPxTi3pbSQLsqDmtSQnVDM/JyKKWlHlQzdcF9JpTwEPkCnUUrGyFxEEhdwEkPPdbHsHmWAoKB1CM+SAFWKccICgVGnaTSKLd2T1PmjjnksbyUrxhqWw2bdFLVILsoiYWucoJ0hHvN7FSL8oDZHUOYsZIlbaEjPahN+ETFfZLTHNdcrBUAmgKwkz70MIS0FgWbvXwlCIwcQ3vYQlDDI8iuCmeMpqFrtyzkWirSowDRA5XEhgBe/nkCtibbQ1ZkiM1/A3HnlrOsJuv06aPOVxW/j7UhJUv+7j8HWv4o5cTP/tbN/jGrYOwBkqsXb0X5SMPXODipUvDXQKAh/Xyld99kSdf/RV+40bLc4UVMInSijBV4crFC1x64p1IkoEopbfcIr1SutDQ0/TzoX5a+/QnuoywrOQuqzHFHOSCuiCSQHRBxVgZ496qq7p0tU03P/TrIV2lKF/lQD/UUGGgDFwzGdyd5196jtdeu7pgQ5gbEw7nhC08xuaWv67yZltHeqKp/kUaJ7i0E8o2wM2pc6vERi+9xaXbhQiBH69qbYOuGOHzY3UuToSdsbLXOPudD2B5cfbVKpwbhfG4NeudJXQG16ZCzpFnHuy0lHknC/OvvNtCT6S78rzzqTXMCYe6nfFIAhnXXKkaPvF4TTWqeXXPePLVrrAyGw8+UPP7P/ZtTC88xM1cc6HOfPA9D7E3m/LrL+0zmrZMX90HUapR4ocegotmPFMlzqM8+uCE3SsXeU2PKPXqA4Y7pRw3y+cvlRA57RdGTlvqikxqXaorNTd+zGs5jROMe6r04tnpPDwyrRmzxtmb9RTpcxiVCnjoCc+SOJqclEoqg4a+IWVSRTkZGBbblWeU0lERaRChlW4RxbO6Fs37UuZfrBoCVm7RH9JfJxcdDRjIW1TmNfOWblEAYS4LnR01LCsGhXshdx1Q/dzP/dzS3//gH/wDHnnkET7/+c/zIz/yI9y4cYO/9/f+Hv/wH/5D/tAf+kMA/P2///f58Ic/zK/92q/xiU98gs9+9rN8+ctf5t/8m3/Do48+ykc/+lH++l//6/zFv/gX+Wt/7a8xGo1O3J6RKqIJxDFJWA4wlD3TaSJpWNnFocmZjpJrkpVWhSoXRCxBl27ZQBQn4w5jtBSfVVrNVGKMSx2rLFbybYIOvXGn8kRXwgnVnboSKs9kqdCc0MIEGLWwIrxsJEIa/Fcwy5mkcU11oSsbt5Bp0cKYR6ltFDlEU++4+uw3efThb8cefpgPPfEQzcF1zl+4RHP9aTgn7L79CR585GE0KTUg9QhxYaeqGFcBVM5fuEJz+zkevjjhuReucmk84gBF6xG7D5zjZgvPvfgsly5dwTySWXMBB6FURa5RgzGWElKpQZrQFtAy1l4dEYxoS1NIFFrvySuCHsl1TkFeCzQi1AsKgA5WGwpbTYRcNICWQnqVOG0hEBEL9kAjGO28ANgDt+jzDmrxAJGFDbIS8IoYp7LoSfHAHUjHWMN5nRXI4eEJz5SCBY1JWLGivVbCKtSU7E7jUew3idBidMVjVPXgzhXToCmP/LNyDfFCXBIhESJBZ28etasgFqAk4Q2sXBANsg6X8CjUBAvigUJjxo4rqkGEmlkIPy2Lt1kQWKhLuWcJJ1gTVfJWWUMG8ZXPR27EJ7DG3TXt816rsAsNzWDXrtMdHPCwK9dduVU8lw7MHDrJVKkaoFTvTxmPaj7+vd/Db7z0DW5feh9/7M/9IL/89We48uLX+cF3naPeGTOdtfDMLd79zoe4fe05Xpo6+4+8vYTLnc1wfLScpe9k2ei5+P3CZ1lQdNpmusDQNv/vQG3uwWradbMTNmlhfi3oQb7w06uvXmVvb2+twijM25FSYlTVxRxc1gUzmqbZ2OEnmN33QE43Vm+2daTfv3ssKhL04FW/Rg7HCFUyJinyZzqLPcs89sq67E99SY5BCqLpLPKOtRAOHMyKXyz08miDwMWRceWCU6lyc2bDW95l2G+VPHgCFnveByVaJKI8mi5yv+fpS/EMYeRcGTWBbzx3jS/+x5f4gUmibVr+0h98kA88ssMXn5rx//n3N2kxvrHXkh+6yO/74Y9Q1TVUcP7ceX7kD3wXl27t8dVr+7RdpjmYoaOaBz/0Dv7Lj74v9vouc+v3nmZ2e8ar7rzaOlYXXaw8++nW8sUDT3qEFOKmWCRaF148iPdLAWmWG9H33TA3iH05iQ+MvYvrqbnQ5ByrizAYaiILoAAqKfn9qeQgaezpssC3bhY6ZtNCY2W1WnnMYCUMHUYGY0zMk0ULoy89fflXYKQFyC3PIrIHk3LuvZKAaBgaztelVmZ5hroKj9pgxymP4OZzFsLFRi8tiMvjcy93y3ueQ3Xjxg0Arly5AsDnP/952rblk5/85HDMhz70Id71rnfxuc99jk984hN87nOf4yMf+ciS2/1Tn/oUP/ETP8GXvvQlvud7vufQfWazGbPZbPj75s2bQBTqHddBMD1zpW0dzR07kuiQUr8gYwo7GWZApjCeWca0oilhgGQnC4ylRrVi6l2pFSSgQkWNF6rzWhRHilIcdYlMo3aQSLALUpRvQzGzUFEl6vm0Yux7sAsm75hJBnUqqSLx22DHIozOUqF8V6gIF3Cl4ZlwURo32tltrr3yMu94x4dhsouI8tDlB2n3rtLcuM6/+d2n2XnHD3FpNGHk8eJ1EtazAwcxZZYzFy9d5rmXL/Klp19iXE/Qi5dQmXAwu41NdvHXbnPt5edovu07sGIZkiTsKkCwyjREOFq/fVQ5XjaTeMmyCa4RQtaUjNy+IHNdEjQ7N7IoTjAYqhHew1SK5hLsjFLAbEfUbKol6OYrjaTaWgOcOQHWaotCz13Jl0oS7RUN1kUxZ5pgR4VawyynBmjkPXUuSNJIDDWoJUW9rRSMeFkilDQ2xzjPCa+QIjQSZBmRbpZLLYrwQDlRR8vKM2Urx2HUhaTDJYCdErWxCn4MNkcNADWWsEomhITRujAiAJ+7I6pUUNoZ1snkxgRhqnGvZMJUnXOmeM402tO7x7wv1YhAQLWvTfHWXEOAuRKxeMLdWJlPBKpWD5AjfjvZLU984OLlc+byL/wqn+QVPvAHrvDQryX+2edf5IYojcfcflJanneLXCr6Piu5f6q86+0P82++9Nt81zsf44//Z3+E27/7DD/y3K/zv3jbAXrxYTyNuP33P0t+8UXSg+f46rPP8C8uPQI7xyDyxbYe9YCH+vssqLYHQbIEqhaB0tJHz7z80pPDmct7fa/A9LTUh8d6UQ05buyG3915+eoL69uz+FFgVI24sHsepOcXjJDotpstvLfL7dpEy35PlJW7dNE3fB2Zo9hQsk14ZW9e9NUMdioYp8gZqapY47scxeZD+VWuL2Hu9Z1z4xpE7aDC4Ca+8D7GDQ9a4XYbRs7OwgBYtmn6+kfzPK4FWTAMVOKQ5nnA5gSbbJm3TV54v8rFZk3L8wcte5VzO8PV1zKXteHmvnGhFgzhfK0c1ImU5jPNesMo4dE2g9xlzOHWi9fYJQCeZ6NtOg4OZswOZnzzq5/l4OGH+PAPfe/CfJ73Rj/nj5bjfl98T2TQHUbFM9SHXwphxDULHSutvpMF7akokzo8W3XlVKlnCJ4bYswiimnWCHuN0OYFkFNAlhR9QzVA2aL/O0L3okSLWdSl6mtNDdB/EeWtdMMAoRYXk4WDhMD4owp2R5Fb3ve6E/Wy9t3xbqHNAqMk7IzCcKADqJI5UCx3zgbTNt6Rpb7fMH6+5hnuttxTQGVm/Lk/9+f44R/+Yb7zO78TgBdffJHRaMSlS5eWjn300Ud58cUXh2MWF7D+9/63dfKZz3yGn/mZnzn0fWclDMuNSkJprHSEYeEJcSflFIxuSanMMA+a55FUuCbUwtsj3tOUZsjORCKsS1CSOyMJ8oGM04hREzTXCaMuXhCTCNsLPCXhPcqRTOmEMi4kRDLumZkH018lieTQSIdWSp0FPLwxJnCgkWdTaSquYo1zJRa729de5L07ztvOO001RpPTji/Q3XqV73zvu/lX3/wG73j8XcVrEwp/LKhG1Se4ZufK+fNc3RnzzNNPc/mhRxlffBBp90idg2Uu7ta8eOsG2jXozg6TClJVwinNaQV2JaEutB70E22JPBm5kqqotaBI8cxAvNgRphnvRKIqtPV1WYA6DVCgJkytjJWF98oKK96OB7jVKsI2VR1xRQsZyERiE4v9RyPkUqINghTQEG74lCgeIpiKoRYARrUw23m4qGfWL2ShcNYJLPdEHJF3lz0KLndujD2AydQjT68W2EFL4WkpeV9OY06rQdoxcYLxsCy47iVpFcDDVd+WeMc6w1StuPyDzjlKCAijAqAyfZ0JSr6Z0BGFgmubhzNiEX441iDvUApzoYfntPc8updaY2eQN8MaclhWVuS1SvqaP0+yJ9+zxX61ws0RcthIOdQd2XnpJR673PDwzgUefewBLu28Rj7ItBKGqCTC7rkLvP8DH+CQLi5FzXJlfzqlaw740LPf4p3/3f+Xq7eucemxS4zOjdFXZjwzHjN6tsEbw+c75qFnWvznjFPshLJ5EBdttPP/Lv+6zorqC2ce7vR1DyNL5yzpMQ6bE0LKQQsusr41MihQvhD+5AvHxnnD3TYZRu5F39/Fd+HNsI748G8MgFG6uYRRKaFIXjmnjJKWUhyhMF47KMxlHUEEcWTnBAsxMIxXP2zarwMl9HDa9Z6Moqb2ijhlfi6Nty+RpolCVTk7aR7mbR51OfEAbK8ehAEQB9u/jb38Eh+dXucT773Ag0n5xWcPeHEvSKuevw1f7EAnO7znOx5k55ErcZP+AST+lVB9+NfPH0CTeNe5Ebd+9zlGT74QhlKHvabj//XkTdocnpwqKYdiy1ZWxOUnPa0sIQ0gwNADE40QzV51KaBz1hrjMZEjNZwyp61QcR675ExGpVZZiYaZv7sBwHMWbu9lnntVmIpSr9idossCqfRs1BCh/51plIwphtj5Uyx00uISu2gQWNNJsvSpZxGk6KA+hITO1y1hUlnkfDMHYOPCsCwFRPVER4tgzIGDznl16kO435KRZ+0A9mvsvUNU9xRQ/eRP/iS/8zu/wy//8i/fy9sA8NM//dN8+tOfHv6+efMm73znO2OKdplSJxWn5CR51ILOWUhmtEihr44CcVWK8q4doexWFhTZ6nGNFsdcqV3AM0JQsVux/ePCTFpEEuZQWyjUaiAlvS9JKMJ1KRSsKIjSRkVYRiRmGi5ToBQfhnFVhScnF4KGBDsp/f/Z+/fgS5LrvhP7nMyquvf36tf09PS8MQAGAEGABAiRBCiGSMlaylqJ9krUasMboZAshrWWKf6jsCPWDjliQ2H9YdmxCkeYod2wQ7Jlh7xyyCuJpB67XFKk+IBIkCAI4v2a90z39Ex3/5733qrMc/zHyapb9/7ur7vn0SBmpATm1/feqsrKyszKPN/z+B7PXyWg0a04E/OlsTLl5Ref4YkrDzKtDdk6B8GIacGtW6/wxHuf4ukPv496Z5eUMq0psYDIlI0QaghQNQ2hqaj2zjNJF3jogcvYxSuktqWaNCxOjnl46wGuP/t1DhbHXN7dLhYYB2ipWEZqM9qs/sJEIUdDciGBsMgUSgwVoMtktL0fb1Ali1OmiwXaAowXKJocBDgY84WJ6AK9BWPaW93Ehro1wgS3rrRWNEkGFpy5JpuMNqQSx5RcQ6RBhg2o6wkr1CnGneHMqd61j9vK3geYuwfOi+tjT/seEGaiHr8UHXiLKELERD3Bs0ATHbmouiCbKTkpcEuZu2p7e1Jw19TkqcqZanEd7PvVHDR1JbDVQ6gcEGVl2ETVPC9axtiSilrcCqgSPNbLjC4rtURUYMpSQOve5CL2nbCG9OVMmdEYBM9TZdNFd1Kk3ROoWmpBTwvRZ1Ww/tt6A5bXnQZTvo1lhOPHr/DsC8+Qfuc2X38hUYUKK5Q+mHiqg60tHn700ZW9a8XdSVu+9eo1Xtp/nc+98hLHt27xwMEBF1PHZFrx4o0FP3t0i8cevMLWe56mmU4GgWMMX87smjscXjlm4x/uAETusXjsQx/23evoy2fpn38MiO6hbukFhZ4ZrG/4WrYqGz3FGACtPIKzqC7rKJrinDmeHbPaD4ZqXk6x5VOuNm6l/vtZ3poQ9J2wjkhRUvmYjubGaM6edEI6MIIsY07VoMsOFPLYN2wl5sVWhm8F5Mvy7RksAeDvKy7ELpek4ayVFUGWh4ZiuAXK81GFpctfkfoX5RE8zFY4ev5Fbn/6M7zv0Utc3qkxYLep+edfP6GOc05S5itHmSfPn+dH/ujHiLEa2urtLfHck4ZJFfi3+4mnp8rDVeC1hfE/3PR9JojQpo5P34rsBLgYjQ/unUdCDxPvPmHvvgyffYYM/7obf1Nc/ilbhBa3/NuzJXPvsteXdRzOXUEVxMGUDAPnpd+ruxRo02r8UG8N6+87Hr9FFqdiL+OlhZ79jlY6MWKlSzIec+uWqQzfN/VqD5L6VXFcYoBpHVdiAgWKAt/vOYabY3dEv3+xiJ5a0PtxHn9j9PcdCKj+2l/7a/z8z/88/+bf/Bsee+yx4ferV6/Sti23b99e0Qxdv36dq1evDuf81m/91kp9169fH45tKpPJhMlkcup3JywvA6NGbcJcMmaKpYyZLwiu+ahQ9eR7C/EcDJMQndIbpUv9hKo8RsqUzpRKhGSJFANqShWCLzIBKpIDI3NrQ5c95oYSDxNMkdgvRErACQemMVJJYEpw5jvcjSoTqKrIBAi1gzwFpsigzFFzxryFKdsWOTq6xY1nvsDi4mMcv3aC3PwSD11+kGwz6mD8s3/927w8u8BH3usU5QHPYZUkeMBj9JuYZaLUTJstZPdBrjywy3O3X+TazSMOTk7Q3HHl/CW2L7+H28fHXLr8AI2IE4JQgKRRCMOlf2gagWyBlDxyquspv4NAFCxbsWiVJL7RTdsSHZA2SCGEcCtOCp7TqwEsChL9mBbfc8/p5Wb1BUpIbrnsANGSecp8YVYFkz7nhnrSO+tpREuchBqt0+bhOaJsiOLN0WnKYwG3EvBs8PiYOhMf1BboRKmjjyUYMdgARHcMZhhNDJ7Q2DzJcIj+/LPSPiHSqKHBmI+XaiuskGIFcLv5P+KEHrEQqCzUrbC1GanznF6pzHETQbNTzvfEJ03057Ki3haix5AFY262TJz8JiJ/v1PWkL54b561GFsvObzx8mYF0je9L5yF8u58kxgC7Sc+wj//4u9z8uwxL2Z3Vc1lDWoRZn0vGZym3HaG0u//gR/k87/9Zex97+WadPzcQskzQ2ZHpWWBB85d5r1/+s9RnztXNNK94Lmh7Wfhx7s95ilgtV7e4MCMZKxeIHjTg7R26/Pnr3Ju7+KgbV6NWOgv2fDrIGAbXdty7fqzmKWVU3JO5ELVvgmyrkG3ey93xKibBuL+lO+YdaR4fYh5cr9ByBxAQ3Fj0tE4Wm/JWsYoIboco/E836AzMaDP5yNLbEVPdLA0/MhgTeiP+ZJWru0F6ZHPmIl7l2gBetondi3tzGUfcLd1J3tadAyxheBu76/PlN3oEdNoLjkgl+YYZ6ODWeteQE/9wHfzvmtzXj56jZSN2TyxPw98+nXjWD22fQ4kao5UuJGEh5my5LA9S3V0qvuWQ3d6MDd+W5nJAiKeH7IfYyfo8mO5Z+ZbH7BS2uE1XSo5ltNCVubE0sI0GuSVNtna3x5u6eCNAox0gjaQXPWVDK775l44/ns/yWxF89IDqZ3aLU6bDNv9vBuLBj4HR8yXFFfPsvb3TJhqzuq8qsMcAa9T97pn/4y3VN52QGVm/PRP/zT/5J/8E375l3+Zp556auX4Jz7xCeq65hd/8Rf5iZ/4CQC++tWv8vzzz/OpT30KgE996lP8rb/1t3j11Ve5cuUKAL/wC7/AuXPn+PCHP/yG2pMt0VkiWKASIYsLAZ3AVGpyVlTdWhKiOSBSjyMxMTpxZ6ZY8kv5VOpo1eNsQok36cyHrKliodougrfCXBJShHRByRZKziWnl+6CC/GN1DShguKD7Il7zdlgglCFwJYWt6oy6SLiMTpYYWkLtJrpJ1ebE5//vV/j4PlvofOOqCeEuuHVG6+wReahh67y+1/9Jh/6of8EJTGpave3DYEGoxMnipil5PExJsTJFrcPXueFa6/xpa9/kX22ODmaMTHlm9/4OpcefJAbX/5NunTC+977QfpAHhGI6tTnnbkrZp/m213zgCju9oa71WUocUruHhnFR0BUiluD7zjBPF5IMU80a+LgCgc+USh0+MrC/AVLaHFVcMujqtGVIEdf/CCa0ae2rK24JxYrTY2Aev8rQhsyVRYIwcka8MWgYrTWBJhEz8PVYUQtcUxQzNvOXpiDj+nE+nZn6iKoptqtW5PSszFDEwQItElpopT5JEyCePxe2SwxB40x4PGD6m6HGkEy1BocdOGLfaNO1S54gr0YlhtxtEByKkQwZ6I03H2jZHEjlw06y70vZ99pa8i9NZqRKvUPurxJAZizLxOE+uSAiwe3+ZcoXyDReqKz5XYvEOopj56/sLoZjyoXYGd3h3zS8sfe8zT/+PYB7J6jnSdizk6+QmAXuHLrGo0dcVJv0+6cXxPEz+roux1fO3U47V777CyUJiMB1Nf5U/XJ8Od0c9fPW8MbdV077XoY17DBAXBduBaKQFtcfHuwK8s6+oVhCaA2lbugzzfQ7aevOy0Evh3lO3cdcYKpJvp6KmXehH4MStyrW3pc+TXrfA0fl3GX3WnmGsVbIgTX/g+gv3encnesSSWD1WNdO1BFGbJVyehvPwM90e8qQCg6lcHd9agSOhFenGdu5Ywo7Le+i58XG2K4Lu1OCSEMzJR97slcgN5kZ8pH33+VG4dzrh8f8gVV2pw5VuFm9r7tLTQ/8mDD917Z4vxj5/09OGOa3W32rYKrMyDZ+J1i6bnSg6l+n+zbN43Ls2S4YnSujPpaVm8TxfNvenyde1tpsTpl8/gk7/9+nJb06OOlwozVHJGj9dDoKdp9SjY9S6kwpBXSgSj0NGgKIuxMxFmGdQxzTj9P/0mKVcqkxP4ZHC6cSl1NB8ITY8luuDoKq2+C09ILF7dh1sJJN1or70N52wHVT/3UT/EP/+E/5J/9s3/G3t7e4Gd8/vx5tra2OH/+PD/5kz/JX//rf51Lly5x7tw5fvqnf5pPfepTfPKTnwTgx37sx/jwhz/MX/gLf4G//bf/NteuXeNv/I2/wU/91E/dUYO8uQiVBWeQw/P0ZFH2QuPItxJicPcpKXEsCzM0K1UV3fUKQSvBkg92h5M/TKgIGC1KXeKXEs7GlrFisKickptMxq0rTm1agUamwQFXz7IUJBIlYsFo6uiLQCFIoFhGjpOzA5l4exWftBGKMAyGYglmmjl67Tqf+MATxC3h+Vef54HLFzi4dcSchhePb9LlbS5dvYIkCE2ZsCaYZYJBRSBrxsRYaKaSmtnshOdv3+TGc9/k9mKBHs8AY//mDWZbe8wMXvr9L/DwX/nP2d3ZdnCKW1UsOW16jkbSPMTbTAq1uJiTfwBO+ICTdGQp5AnAlsBcl8ApmufUaDVRBc/Z1BZrS+qJFwpwNlN34xuWxl7g95xYqWiAIyVBLh5n1WGFAtlpzaW0JUkhe8gR02LRCe7OWFFiv8yopc8k5YvAhOBWzBDoYnHPK0BExQpQC567LBshGFOig79+IwPP9YUgKoTa3RRrgaqYLBvz+dGW5LvqzXGyjuCAMUoYmBhj78KBMZNMhV/T55uvKAHBGFVxV/RcaR5nFcQoqdcIvqMO1tN7Kd95a4iXN7wMrwnF91TBRslog5R86vj6hau/3VnevZM4JoO2+uR3f4fps8/xU1sNv35uh79382BlO1ODJ554kh//c3/Wmbk2tLwvqokrF3f5z3/iT/HPP/E9/H9/+dP8seuv8T/74CNESey+9DxPTeaEMOeXv3DEb37kk6dBw53KqgS0+vumruo/bHLbvJcyyJ55BTjdqal2txPG55or+yQvRblTLZWxqFAUHwVMUQRbk96HdziLO47/qf7a0OB1eUbOOij3/hK9Derk77h1RHop2d39m+CkBUGEpopMC/GA4Ux9hwtoKqMOJf463+097ssSoPodff093ygP7/rhkw4Qj+8RIKlyfkt47QQO5uP3zL1JKulTYgyiyDCBzZyae91yauOZavDEhYonnoR/8K1DfmffrXRKAKl4tpjHOiIfeM8VqirgbO8yCPG9gF83NX/0+99HPjnmH/36TX7nUHiwMmJoXBlrDAL3o1Phhy4F8l7Di+OhOPXhjZTlJO+f985KiNVferKIpUfD2jo9Bjz9r+XAEHoQ4MKeJ0Get47A+9j3Npsz9tlyOTOKcjeUXKkDxOpnyOoLZyqkbBy00JamVhKIpQFmuLxguFxa7jLmImwzaDa64Glv/KH6pxrtDEu0ORi6glLi0WGRjVkaW6o8dGGle3t0uN7zpb1bjVtMZ2mzteztKm87oPq7f/fvAvCjP/qjK7///b//9/lLf+kvAfB3/s7fIYTAT/zET6wk0+tLjJGf//mf56/+1b/Kpz71KXZ2dviLf/Ev8jf/5t98w+2pqoZpbIgoWTN1VZFiTSXR6Z4t+0BEJzGoKiFqooqRIMICpVKcLjhCoGIKQMYiiEWm6gnoOrSQUqhTRheLVoCisTXq2FBH59PfCpFaAhNqYnThWs3zQ2Rx9rbKnDo7qk/CXKgtW80+MTRgElAyvctZI67R6SRQBzh/4TKzeUVub5FTy40XX2d7b4eLjzzKaycLLj9+lWp7i5P5nF0qt9CYaz+mTYWQ/b5Fc0bdUMea3a1tfuBjn+BXfuXXuPb8cygdaZG5VR9hJjz12CegruhQavVFOasWrZz/11vXgnjgsJoz9xGEhXksUdUL/2osxOOBuuR5oBRAC0MgxjYV2RRQd0cqhAiLaCxwsABCxEruBeEEz+8h5u5pubgYpOCxb2LqY1aYkiYizPA4M89rptQa3JqHk1hYcKrzztzNoBEH8kGgC+K+0QYajZlCXeK0Ai7vhOwauSjuNoeUNosVunIpubl88ZyI0SJgQlQjBU/Yq+b+2570t1irCnFENNc6GdCZOoAsa3eKbvmKuvRpbsuzM5rPCRfUQig+2cHnJOKsirlYt2xdvXqH8p22hvgDc1fcsVLWzz171z37mlMH7lTBpmN3a/TZNY23+BK/zjQknvj4OT4hkZ3PvM7Xbifa8t61GF/OLSFW1AVMnVV3CBFF+S//3/+Mv/e//19x/uGW5vwFPjLt+MTTF4mTxP6LX4Vf/Aphq0KmDzI46ozAyspjD110l06+W3fci9r/1C2k/P9sTem9lI2jVQSF27eucbD/+uh5/X0+9bjCIID2ta2IfpZHp95DG1cEvrcoiciGL2+oyjfWp9+J64gLprBTwVZdkqsGuLBjPLjns1zVOJjD4Ws2MLmOH30ptMJ6nwxjOrJE9LmNThK8elIAVMmHVHXLKw87SFmGtaq/j+9LxXpS9CsrDgdS4m7X3sX+qxSFTMDYqY3zlfDUAxPO7VbcvN1x+yiRCdzWwHsfOcflC7tO752LNWj0HCqCBSXXgcfPb/O9l7b4yu0Ff+3pB5lUNTMJZIGD1PF///oBL+3P+c1vdHz3gwvCAwUE9H6OZ2pd7jKGa2efPYVt7aTSeT0oLTFsPV4aoMaASJcd6sdt+Fmysdj3MdqtZAjhVfPclovcWxuXiEpxRXCnDuhWV6vVda+Pkep9ndQc2KzDoXUFlPTrjrmMcXuxAeTgD7n8fnpzFISdGqqg1AJ7TVj2gEkxjnicXjeAtaHqlWLAy/u6Rv9/f8p9cfm7W5lOp/zMz/wMP/MzP3PmOU8++ST/4l/8i7fcnqYKaCzkDXVAxIPyEaMxpQEW5oH7RNiKFaJOy2JAyq0TIODWjlhXBDNirkiS0ejWER+sgBLJDqnYGjkeaxT2YijkAU6GEIPnQlqYgSViHcGMUHyoM0Y0o0oOOsxcCN8OgZMozFGq4BOzxhcSE49HimJMqkDKiePDfS4++XGaas7DH9klzfbZrpTtcw9w7dO/yJWnPu45lrJSWSSbYtEIASaN0JnHbG0lsAp2JjXbzS5ZjQ+//0nOX3mcz3zmdxGrOT64ydNPPMDvPX+LT/7Yf8SF7Ypc/F2DGJUGoqi/oAYTcSuPJpDgoKESz8DtsWlLcooYiolb3OXPNVxO/KDZY4la8cEIRXZQUVTc6tWIOP25liS3goPoXqNV9pJJr78xZ060sqJE3Bp1gsdk9RrhgDCzTCVCVdz5Kg10UTERJip0UalxC11Uf8aMb5hNYR9cFBeAWOK3xKzQ/WuxwPmaURWKaiWQsh/rzEkxorklqg/YdGKMUdLhIqBJIaZYxjjrkN+kErf6tRGkWG+RQm2PW6V6hybfZN2Cp0FpVYgISaBRhli0+AZWsu+0NUS4F7nvLQqbpx75DkLs3cDbqZPvJQz7TlUI2s55gMR7Tyqa1w+4GAMPxchRYducyzJXyia3mqEV4vmofugHfogvv/wSwZSjkzk3r7/KP/jMb/Kr//Qmf9YWvHb9Nudue8DF4nsuOEPUSOu+8Qan7jcuo/6UM37feN29lbc4+istOVWh+D6Etisq7FUxZOletLHW4THvNhfG/fFmtAKr7QZ5S1LMmx0P+E5cR9wqEMScEjtS9jDh9gwO5p5jMGXP7TRri1BclH+be3593m5SCHg9MxXmyZWtFT0Nd2lXARmV2MA851fKMs7K1qeljW/hVogNXR5TYme2Tzs7osvwxx4IfORHn+LRD1/gi791nf/uX73EIcK/PFL+0x/9Lj7w2IODUmAAVCWWy8TZmINUbF/Y4YNX9rh5nPnZl27yk++7zNVpYPvBKZNz5/nB77tMp0K6ecJBPuRgntBpLDHpb7SsC/zj/l5/6FWowIZvfZ/a6Nf1f1c/Lck0eovfceey5E4Nfb7H/pXLKh7XNl4vbEk+MehJZHQnW86msWWrv3bWyoBW+nncA6gwPPOyUsNlUUYtH9rY+x2PunUNj5fQC2Grhu0Su6492CsuptlKDtGxemFtibf+doVB+c06IdxLue95qP6gS+4yVjlpwMQqF2LJhKKoywpddre5ioBVkCXQSHRhmxoJHlczqSumdUVWxWIGc8KK1gQLMNGAqdK6lE0WYVI3TGKFCGjOQ56HGD03looVBhfQrNQiDgLMrQOLAIpSx8iiS8XdC1JWd5WLQFC6ooEQ3Bd7bkKN0rYnLG7fYvJUYu/CQ9STKXb5EV5/7os0aswPZ1x9/HGauqYNDaFQfNYxQFKmldC1mWlVoaYsklJJZOfcNoev3Ob560fEapfHPvQDUNdomjGpJ1zdvsYsHRNCJKsxjZAQUlSa5HE6sWwWAlhwcoqgnvcp4Iu+idt9E06gICoobi4r3GJk6+nsCxNdKFSj2GCiFgKxEIlMY2BuSr8E1cE3shonYcA8xqsNYE7PN+SLiAhdNlTc/7yy4qZXXOkyblI3NabBjxGNiUQinvRWhYF4Y2IRQz0XVhlbxYrVTZzREJ9TlTl5xAIQdfr+ykpOqbI6VxTXOzeLDhqqSoWu+MrnvDTNZ/Ng02mhPq8r90HvgMr8eVP0+msM6d0fzYHolPLcZWGtxBdygD4VQDYtcX3vzHJXvLKyK7G+976le95TVes70Rsup4WCZZX+qVXl+ddOOImZ6uIWH6qVB68fcniShnNcCJISq6ObQY654qSpI5PgufLImZMXX+ZbX/4GL+iCr2likpTzwOULF/ng409wSk0/auTbAWa+I4stZ4GMvxaBagymejIc6amhGY+qnZbehjMY/XifJI03M0Ab5/Q7e6R74bMPrO8BArgckss412IQYRF9/4rCoPjqk7Qfpd5mOxLSh79rq4dRGCL9+3admFY2sAL3BABQGN+SjHG7WwQ2TI1xbkF3SbUhV9TyAMSbN0m/+evcOFY+c3OL79paMN0K1JOKK49tc24aSAk8l0hFiMFd1OljeZeWnFTYcYOU5MY4kdaXD+a0ZmyZ0exEJucrJuLugifzAC9d431f2ec5Jhx+10cJO1urffS2lNW6bOiXpYVv/Eb7iIyAwBnVOdgp8s0mhYiUsRAPSZhEuDgt8Ww2HqO+vuIiOFoX+rnVp12xEhulahwnSrxSv8Z73PXlSZGLpFjKRVbmxPKhbNVqZCwR5fAMqxBIpJ+bTnZC8f7pXWG7oqzNGybmxhEdtf8d5fL3nVZyTuScCUHoaIlS2EGCuWBs7tI0VciSUK1cmBQ/ZxIiKZd4FhFyKolYRZgS6FCausRdiSeV3QkVc3G2vyCulcoCKShNFhLBrSiFjCLSywslP1V2LVISWJgywV/MWHkCXwEqi0SBzjIxFStKCVyRgFN1inBr/3UemLY8vDtnRubk5IDz5/a4sF3z8UenPHNxl92tLapoTKK4O14AmTgFdhJB2wxVxXFKbiVrApPtXY5C4GDW8sCVPZ66+hA3X79GaneZt3NkdsjBjX3aJ52tzkUzt760RUPUkzmIGCEvaTyrsljm0QsZRYqhxEp8l3r/9y5seKxSVBB1s34QT7AbcdczcqEqF8XUk9V6fJPTm3r7cIZHxF3mkBKl60nmtOTIwpRWhCCegX1aNESteSyUVWDi41sPlkhX8NTiJBgd5RwpFPLFR12zJ6Q2PEYuiNBooYAPgqj3R7/hxJ6SHzARquC6wwpnSOxdB50e15jUgaRO0x/FQZBRYqPECOV5XbmU6VkPrYC3ykpdVnJzFXBaS2CBeeJgY4ihqgjM4n1cxb5dZZMyslfIjYTf5W8bzt1U58a65YzPb7B9K9evC853rncsv4cgvLZ/zMlUudk0vHqUuN4mFnhKilROlEKO0kvv63fucZGIsP/6Pv/Pf/Mb/MLP/QL26d8inRzTmfFsCdCvxPjk934/3dMfxEPzl3XdqeVvDBaswJLTQ3CPlb2NWPoO9+wlovW7rEkrvbB+t/uMBOZ7uPkfTHnLyoLvpOK+SVpIA2or7LkCiFEXeSEIUNytz0+UvamixXIVRFgkmO/3HgveQStk4GdIjH3MTJedjbgXLoO/kLjVgTXyidLy8tKtvHu9PF7iltrsysYeIlg5tnU0Z5ISR/PI1w4jH91bMH/xVW4cH3F0u6M1dcuJCBqdmqNT76OEcJTci2gn+AZal/ZW04YwqdmdBq7PnWzMktEdJWKYEwqI7OYdi5MWW8x47VYHT32ArQFQ3W01ObucfmuWdRVHGeZZiixCSXbexzqNrh+tM2Pb4AB6SoXjhAcyfLLR6UWWKjHVvYV20KVYAacj0NsDZ8clyxi+IqJ6FIms0jgI7m3URKgLGWOIfY7MsTZnNX2DjP4u16cleB95qQ7PbaoerlD6xsxT7rR5bUmw0fdNw3k/UdSovPsBlZYkd6nPEOWzZKbOklZLdGEcSBqoyFQBQhZabQlUOCMcIEqLB/ZHjCNLRClJdnEBNwZ324sxUgMpJ/c9De4mlUzImjANmGQqCXSW/aULTobRhIoWF7Ij7gK4kEQjQjChDepMcGZoMW9th0AnwpYIObqfsYhwfOtVqt1H6Krz1NM9mqjoyetEiWxvCRcfeZxFPaHrMjMykjqnLDUjdwFpfPEimFNvmzCJE3R7yjfnB5zbukyeH3C7U04ODplevgo17Gw1aHeE56gp7IosSR0yIKZMxRfQVpYvfjDXtgi9W5y7Os7xTSaG4iaYMyHK8MK3ypBg162IUuLJjC67VYyikQuFyjOog52uREOGsvipFarzArgqyvIW3I/bY6KkEEk4eHYg51r3BRAs0pQ33YEKIE6m4ZYzdaKSJORCCBEwojlwbnHLV68+ShgWXTsziX6foAKxJ75w6uoKBo2W1P67Wg8Yy6Yp4hT0JXZMkcLo6KAtWGF1CoUaW0DIBI2YOlNhLPFcakJVO629e7E4yYgEcbdLC9ThTflZfOeV3ll9pZxSv73127zlGt5aOSW/tolM4m9fu82Xnp1xu0vMSx438C6ZXrrE0x/6ABYiakZkHK/Ta1r7uoX2eM579s7z0R/8frRVrv/+55F6ylY9ZZoSUVsuXbiI5eyCSFjVpjOu704dtn7N+kO+0c5+e4b4HsrZNzmF9TYJvPdSRpV4Ny2vNjt1lzuX+9AnNvz5g34j3nrpIY8CB13gJI2FT9/zxq5WZkJKwtHClY2p+DtpYQ8eRFNxgovBAlbmu3s8LAX4vniyW+euRYrWHitkWTCpCtNaaZoUBr5exF8CqiWY8/b5HmzlmDPPASctTavMu0CigxC49vIhzc05xwlONIMKYhGpot+hrCuqeJymwbQueUANJMDlRy/z/v0D7OCA5w+PSJ1xlDt+87O36USQwvxrphwcLFh0mZfUeBpla+VNOUsDxj2uEatkHH3XdAqHLRy1TrDQFIsgMBBnWA9kerghxoUp1EG5PReXF613+Vwijh6c9PntxiUGlr/bcn3OCkcdHKf+/qvPbGUB6cevv1Pfxv7GhrNaX58XY0QUdhtnRN681PbjWSywoQeXfc+PH6rsDv4CkMxIakOurJTZaC09i71xc7l/a8m7HlAFM0IuEUlFsKwCxGAk3DUqIoQQ2DYhkUgorQWQ6Cx6wdnLDI/jqYsr1SRAzxAn2msEXKsQkGLh8ajSibqAmshUGFkTM4HtUDmJai4vR1AHclKhOZFESGpIdPKEWgJNqBBxt7da3JXNCTECCzOi+OzLBF577Tq7l54ibT3AZFpjKdFppJqc4x/9q9+gnT7OldqfKzdLGuwm+zMeq9KmzEWmVMFjwCa10FU1ppF6skVDQmNg74GLnBzfpkkLnjivfP6bLzkgjBWW3XqmGFWGED2vTTJnCKpx9kS3xFCS+coQO6Xqi08I4laPEKhqwURRyhgmoYpO3NBY8Hvg1q5JKKCtvPEiSlsIKiwUP98gIIHKSmxRVcAQ4taWorVRc6uPx0SpJ8Uty5MGYU520g0JBPMkeiH7YuhkI0Dyz42YJ1k2+nhVp5QvFqRQFiKC+pwq5yRzwhITtwi1RYtTlc2tFojB3SEqYMFysetKPxoO2iSAZRuCj4HiZiIsyMQQMDUacRE5hFDom4V5YTRcqCfAbtT7O5oQkr9ji+LC+u4p9yBovpnnHe/v91L3Rk3cna4fHxwJzmsfVi93i+X+p3+D//WT5/jvp5lf/NohbSHc8cxxbiF+4pFH+MjHvpdUbMLjimzt31jVfOgDH+Dv/V//ER/71Mf4ub/zX/BffO6L/MazL1Fn5cdefY0fevHrNPMD4rd+m8mFLX6v2+aVR54aCXRrfbL+7Pe6b47AyFspb/s2vTYf5IzBPQsv3rWsDfyqPpmloH8vbbzLz2+4b09dcD/TcX77ij9D8FgpWXOFKicYSwAz64RZGsc2GWI2JEM13HNhd+pCaj9eijipgBlt7mm0ZWB+W7ntCFSBgxgp6z+uSx3FW/WCP8t56ZpA1l3I+oNf3l/w5WfmvKYNN3LkH71o1C+1RFrfh8Rjz8/vbTGpawbo2QNEep2iDfHYC/E8mVbXqHgczbXjjpThl184YWFgOBWyBKhE6axjP8JTo+deH5k3X0ZvZ6lKDdrOWy8iVI1RxT7hsVvhYygeLMWVTwSuXorsbAnyqrLoimtjif/x8elTH7gs24c79DF6IgyhDj0ztOHzYxLc+6UHae6SX3p5WKRl5ZlEGCjsB5BNqUMZlPsUsovxetVX1V/Xk/2OYdypUkCgmnHUWaE7l5Fb6abe3/zbt3vNeNcDqtYytWRMXYj25LjGVGIhX3QrT4cRxYgSXAgX99OlCqgGYnS2uTpEOvOssqZOXh1CRFWpxM+hCPFSBbZiQy5CbQIHNP0iYYIVfj6CWyX6RCOGIjGyhZFFsWzUIdLUFVLc05rKGdp6BC/B25OylEk+4/D161x670OcnNxCui3i9g5tyjQ7U16+9hof+dQPIdE1Xk3VoG1HrJwVqK4E7YyqqllopptnJpOGGMHE2NvbYXt3h6PFnJ2dmq29c1R756DrmOg5dm9/ja5rmdQRC5DNaclFnEyhV1y09MlwnVTCDCwXTUuJw1GEqQGihCoQgmviMs6+p7ln4gPElxYtZnJfkHyRyWo0wa1elYBFZ8MDSnJaoxW/t0UQLcmEB76bQhVu0BYu0Kq4uPXJbX0sywaGA64Wo8pCUqUOvqyIBRJarKaFEc8CdVC6HKjC0sjfiTP0NOLArzIZWCW1CLWxUJW3HmXmjIHquT18s3U2vn75UZw8IwTX/psJEqFTZ1AUjFzo06eUvF9igx93IpRn8Wejp2jGaEsMWLLM1OJGX+d3TllqazeWDcLfytl3Wtk3gaN7BVZnlbuCqjdQTNiazfjRw30e2RX+zM55PhsPuJEzSXwtnWF8UWdo7sn8VwXzpROQ336RPCfOQ1cf4qVrryEpszOdcFJXzJoJT86P+c/iDR767in2uddJOiOeS7z+ivDKncDk/Zhi97Ar3z995xl3k0HmKGtd34azZukYPNvKnJO1S95QwPZ9fPB38mpxdlmuvSvjMDo+Bi39WxOAS9twdc8pzHurk//na38fkhJDIVwqseFNJVw/9vAGOeXa6YPfpw8JYuxtC+e3I4cz4ZX9QrsfZK2NZdKsKyHGzHFlj4jisdFWB66dwK0k3Ey1t116S4rysfdd5n/74z/I7u7W6nwsf3rnNzXjMAEZzCpel4Z5mzlf1/zSq0e80iU+22XMIkUVSgD2ppFPvP8htpuGybQpTSztXXcHG78TK8v4aOzOKAMQHJRTy3PrythujPnMI6qCCNMITz4gbG9HeprfyaSiqoT3Pa7DGOdkHJ+4HHs4g3kf5zbMBTcNrjS7PEeguBxG4UKE89bLntBl46jNBVz1lkkdzcPlXFzVVS1Bfx2cMTisrP4ynOfGV1nb18a2TmNMve6H/bmaIMzFrVQreO9OC4SMnn9juX+ry7seUClGVqUhIgFaFVIwZ7kpC4WaMQ3ObifBE+wqSggRE6GOwQPvC+9+ws2bQV2IVnFwEAtw6k25KpGEg5tkuVCpOwBKKFuxYpEz01hTxUgnqUyiCjOP+xKLRAvkRphY5SwlAERQwaJbGKbibfQ4GiOGwHPPPYfefIErT+7x1d+9SZzscuWx93CxCvzIRx8jP/cY0wcfoBKhWyhUbhlqCCzUmDaRrvUYmy5lFqljOmnosmCpYmvnAjkJFx54iHPnL7B/OEfnx9TVhLB9GapnaGeJrWnRmFlPs62QYYbTiAecca8nxozF8ic9wQSAKSkKW8Etckn8Ba7FweCcgFROgNAUbU4IgLpFpsKTCgvuPhjEiRei4IQYgJQEwlIsZifi/ZtMB/cXLZtSAJIIlRmKMwk2iidfVMOyg6U+2S14TJyzD/omoj5YJAsONMEtbiLO3thrDr27qIZFp2gmzS2tc2Mg+DD1hXoiwXNtWSZboBFnR1QVmqLlycHBUvTudeIUVST0rn9O4R+KdbAqboVJhd6jW8RBWzaD7LFdvo4HMKUqY+vxfe/UYhs/vpnL73rOOrC607V3AhebyroKdfi5iFQjSt/hLIGjo1scHN3i5Po2dRAejIFF0iGvXCzB0P12aqHMp7GmkrK50jM/+vtGcWHdbzu+/LVnuX3tBrdfvMYXb7/IK9UJ8y+8wPyVm5yrIl/6yPfBk8tHuCe3+PX+ezMg4C7j8EaH4W636ivaMFTDWU577O/6zvbO4Bpsp8Z4FZ0Pf4uwNV8s6FJ337DRWxZd/iDUzPepbAKrq6N0ttqmyzDvXIjtmc6s1OmEDd5R7rLuXi1JjaYkfk3a5x1awjr/z0ZWhOKWHzxMIpU8jlLW/8GlEBww9W1gafnyPaxYW8x5jz/xkYf54cc/wf/hZ7/OzWvdwBBr5XGNwHRrwvm9LQgeYtG7rI2FbLWly19/bGHGA5Oa/8137xAV/u2NE7723D5JE3MNLDQgBC5MpvzJH/4eqt0d5s32cq0aDYCZe3SsKx3Wx2R9hM54RUdH/cvBQjhuXX4M4t4bosakMra3olPCl1i2nHrrpZOYtJ2yf5JJObA/NxYdK5alHgz1qV28Ce7dc2kSqKMsgUZBwoZblrreWiUswTVuOQMb8oEtn2SVxr1k4R3xTIx6ZG0/E4wc1lUGpQ76sTV6oJgK8cT4qfp+PWtpkJW/43nE6cF7m8u7HlBtVRUxOBPfpMS0TKVy8GEByEyl5OkJSrBIG5yOscEGC0BAIESSZVozpkUzlE2YmLunqaoH9oeAVH5tZ8rcElOJhOirUg+SJES2Y8NUArMY2CoWli4r0WpiCfDOmmjMCQMMN3uH6EK/ZXOmPykTOggTPK7o4LXr7ORj8vwGh9df8Liuk2vsvedDPPbQNp/8Q9/N1/KEbLAgE4hkCWgQqoURGlASEiLHXaI1z0UUWyVlmISaw+6E5ihxsDjh2tE+h6/f5MEHHme6mBImFW3XudCVwJfSypn0ohM+xOJrDerZ0SlBnBharCcSoLLARPw1yuK06CqAFVruaMXCR9Hi9T7nQo05EJXyopa4LTP1XFPZfZVNKQGvxkyVmP3+7qqJLxrmbIMLc5O9ibsgKDAvC1sdIBQyh1yADsEJJ6JEKsnMi+vCJARyb4lSpytPWBFUfQPJlQM+zQ5Mgyo5+PhHC+yVxbmVjAR//gVGbYAEzIyuaBOjucYzRxuAWqdA8Pk+QVjknupcyFkRAjOUWp2dMOC7WjaPJxQc9Kqvq8RC1lKJ0SFYVtL9Xsm+HeWeBbt7eNazdgNbO+deBMrx5r/p86a6z2rU2AepfJxPtrg23aLZbWi3gW943GDCY0JbgCLIDXvsmaYOoapqF7YMCMrzn/sML3z+A7z02c/y+ovX+MLnv8rfub7PlrY0MTOJ8OGtwOG5nZUNqxfI7t7bZ0CeNzIl7+HcN4Nvl8IQpxDi+JuBM2iNhEkBqljx9FMfYNJMluePAdlKPav1K8Y3nv0Gr73+6j22+N7LW8VAsvYM755yhycaJsTqOJnB7Tnsz5eAiLVPy8Vi+X3VMhyW4GFowoCAhnvfnMHzN/3afs6logDZ2NZST29xCqEXkP23OiVC2xFTx2Nb8Inv3+b8rnBwbHz2yzMWaryYWj7+3geYNkJnhVRBoA7GPPfita8pYq6s6VOcJIy6CkwnTsb0RyY7/JGnL5Cz8s3XO37rlRbVTJfnfPZffZbv/9Of5NHL1Yh+e9nHbTJuzO/l7V1VUtypjEFILvtt6IkeRCAIN24rB8cZFY+l1+IY16+hZrBIyklymabLkKwAqr5z1trTj3zVp305NX49IHHZoc9TCf7uTYKTTHRqnOTCTHkK1LA5znIARac1Q1LuvamnbDRjrci6mAzrPL1FcdyEtapGLdtwj/6c+yeLvOsBVcrqDxkUS0JXgZh7+UcBsgfHNBI8RkVLTI+CWiYVEdECiCmdtkTP8FsmR3BqcDImFfOUCWZMLKBZETMkguG5gSoCVG6tkRCJInRSYl4kFIHY2el6axeh8oSwlj2fVnDq7UoK4Cqf52SCCh1OTLC7c44XTmq++c0Z3fGcF69d4+ThJ6m2Hucf/8rvcO2513nsUx9E8HxNUSoqg6wZK/5jSZ1WW7vMpPJEwW1SmDYc0rF47RqzOvB7X/0KN26+xqXLj/CtZ75FCBXnd7a41bV88oFPsV3XNO5XRhWFNuN7R+jd1aJblHAf8RCEWLvw3+JA1ZMVF7p1cbfEhTjA8QBGIVhgEXwDCMrAoNiVDcaDeW0Il5fsIJHC/KimtNmZ6bI5e2OjxcNcChlGWRCSCRNzoLQSX1xo3jNGRYRibSIq2XotFGwVkFxZwIJvJDG41qgSoS4oxcCTPpdNrDfhk8s9CsFFTaAKMiy0dYBWrbhoOgMiAjMzYmGM6mOu1Dy+bZbBgvv3Z81OXqHiVr9g1IW2PpgnQQ5W2BqLtcvwjbVCCETqsgnqO9lAtbHcC9K5w6VDWUdQdzv/Drc9G8OccXxVNLPxp5Gg0Zy7wDMf/m7+T1/6HJ//4jV+91hLXryi4EH4wPd9gg9++CPDRVKOnd68DJNIsIyIsbu1DUc3uPHKqxx//Rl45RonN1/lc13roD4Zu9vbND/wgzz0vg8Nbe6VI+Pg+Y19dddy5/6/Z9HpzGrubZ70QuimSgZcbaPg9V6DhgtnIQTWy9kWPG9TZMTKdS/lD0on8hZete+sco8PIeN/bCTHyijfT3/OcoaOxd0eIw1xTf3qbKMbjG82ACj/FgrRdwywVfm/oZgg+lQc7vLVz0cD0eEeqsato8yD159DX3iG5557hct5wl/64T2evCrc3Ff+b6923Jwrtw/nfPx9V2kqISe/TxVcMbk+5WqBuRozg4hytGhpsnLYZi5MaqoAVy5OkabmoSuBT7zf98rj+YLPP3ebajYjzeZorItitQAr3Dq10t93GJvxl565b/2E5ZqkQwJngO1KuDgJSFAeulhTUfH6UabLQxKZod5Qfmmix0vlAqRysRq66OPjMLj2D3W4C2kdluvEuO1mMKkCV7el5K3sjQTeJ0E8Druue+WV1zte0+cZZnkZp7WCeNa6clixz3gNejClvd7I+vkrrFEALp/iHteklX3oPq5j73pAJRJ9AFVJsfJgPVOCCjNTqqpigpu5W/PBFNMS2BeIarRBaQoRRSSi0YPyA+J5VAxqjQRTugpMAy3CtIqFFc8nm7P5eazUTqzc+iXudlYXkoxYXpKeiCFZcLcxMbYIdOqWB4lF21Fcq0I0trJwoh5XkyRzsjji0e/9ozz81JM8sTjBjveZAQ8+9CTPvvxFXj8IXFEQlJQVoUPEiNloDUDZKsmQgwlN07hVKcBOFTi/tcPN1wLJZsyufZ1bX/sS9th7aZoJTb3L6ye36cIOT1x5lA88/T6gsBOZOjV60ZJsm5CDFIuPFbIKZ7szIEiggwFERilAyXrWHGGKkLS4/AU/OZdcOEmFmXqMXKdGpUIUz7uUzQp7opGLZSbgwktlkILRkpmIE2gUpwiCaImtclKIJM4aifSMeA5WohlWXChCcA3TpKDxZB6UGnBLVCrMhhPPuIXg1rl+Q6wjrrFREDFS7WtLMKgKM6OCu+qJuwiGsgh2fdu15DWJDvwIvggMNLUGkoVOlUZA1K1dFeYEIQKdSGEN9IVebekW6SQg7g6ruBUil832nV5WBPe7opc3d/ieyr0KmOu72V0acRZ4mKTE1TTjZu7ousyResLqHlARhPe8/2meeOp97jIqK6LGqbuJRBDPuvOh972ff/ub1/i3Nw/43/3l/4Sf+9Xf5bP/5rO0J8eELkHXcu78Lg99/AcIVT1sun39p4pt/vnNlrtWt2EclteMRdw7XFB+Xgq0S4HID21oxZpw1P+zQZzb3OTCKne6zWeUPygwVYqN/r5Ti4xnxVqHr4m6y99kee14ViyPaTnq2nwXR2y4xwp5xKk5xADirew9/RwS3C2tCoFpbc58TO/RMJgMSjt6UbkIL8NCYsTFHJ13pM5zaUYJpOxnTmqhToHgARio73jDs/m/sqJoMJagAoSHHnqY3/7Gi1x7+WX+zONXPAVJEKqr59l674POYisVl49us/O5yPPPfJOXv/lN5LEnqZ967zCjDPfUGN6NjcBqSdzRXzP8vqFrh8/FDb5/jE7hsPP4LjnwVDTH8546fhmrHfB93oGS9BhlqMvAY9zKPYJ4DkyPsQ9DO84EHeIy7KTq13K/bzZoUy9bFLWYeD09FT3984jSZik51Nx91AoQkrUbD/N+9H3sXiliPn6l8k1rkg/7muLpVJ2bcK/RW37v51L2rgdUSEYEtsyZ0HrJtlNfiGJOKIETFM0GMXoeHjFP6urpWEkhEoiuqQlF4JaAmTJXcEppiFSYKJVUHhwa3SJh4gQAbSEl6NlQxAwk0IrnwhLx733yWAFMiztcUHpLTLUQLPrkixLInQs3sWiNggUWN19nu5owqRr2rjzKtKm4feNZaltw49UbXLj6PU5JrP4WtEnZqStE3cUuZUVCRdt2RKmYxEibE3UdUVHqSsjdnPMPPszUaurOOHnumxypEZoGiTX13lUaq9Dklo0quBWwEmfJU1uaet0n2IX5EIMDrLJ6CNBYIFNin1RoraePp1in3LVtrm7F6n1wrdj3W6AJ0e+mWny53cXO1C08Kr449YmBJ8FN85U4TTj4fauSa6eRMJCOxOjJGScoLZ4oOKoDkFgYmrYq/11KbBLmeaRK8JuTRhQQ0uHMfhGhKhYkBbdmFesSeHs9CXIkqpFRGg3Mgg05q7ASm6aex2EqAdWy8JkUACtU4s9WU96RAnqDQhd9sY3qLIMR12zNrCSkLs9t6trv3u3DcGXFu7vI5pV6be0fvq9KRW/qdiv1r4Ose+zus04bIEtKPPbpX+c/zgf8k4VyPK/546FiIZ74+jXLfD13LNmkBMnpVHesPLqEkcAnHLUtDz90ib/8J/84r9QP8rXmKSbmKS7MlMsnr3k865BOYRk+vfokb3WrXO8NOf3rqXm8SZLaAHbOKgXX9BaFJaBa2/wNt2yLUMV6CAiPVb1kLr3znU493eAuVLruzfTgvWL7N3v9RgHpHVouTmF7uvlJVgVwRi/LWGy302sIsHxbV+DWMLdO9/L64jHUPhzr43djsMGt2wTmSZkNLmBLODI4Y5U93NT3m9m1V3n++iG/tN/ww4/DrW+dcPsZ4aWbrTMAB+OhS1vsndsjs2SFG7dyTNmu5VPJosX2uV12H7jE7KWXSEVpmrIiswV669gV2CEii46cMzG3LA4WNA/Nec+FCQwAAE465bWTNMgbTvjifbqch5vW+bu/Bf3bbBgpGzc7//31k2LVW6l2NOvFhti15drSj++ShU9E2Kt6yvs7g6h+nPrqrKzDPdlIwKjcPQrNwqJzll6xEg89GvetCNXUhkTAItCpcNT5s25F9/haNmitn3rwVZ6rrPp37EsHveNVYfWKTSDMDObJCjvt/SvvekAlCSqrWFimjkITA3NzEFHj2n6LRqWRgLOeaGVAxNSDKqcEugwWcZY2ose5lKx8QdwNS6NAIU2I4m502RyQ1bkXvAuVdoBp8KDuEPy+VnIOdJIGNG24BgNzFyyJwV3KAsP9G1PaMqVCdHrVRZc4OrrNp773cW50h9hJpGuVR3YrLl+6yGWe5Fl7iCCGRUFjJHWZLkRyKlLzQgl15ng+48Jkl0XOdF2irmu6IMRqwrxNXLh4ib/8v/zr/Mqv/gZf/93fJmhGds4xOXeOnYuP8vCTjxVaULdeCDC37Bo1egY6pzi3DKEyKjVPjmye0NCiW0qiurnbM6aXwGwNLCRTmwyMe/2LmoIMCW0bnGZ9EiOKsY2D1i4Ymos1DGcDtODeoO7q5gJgJa5d2sJ9vbMUABwd4ClGJRRGQmfFW9TeZimrjQzxdr6Kh56lrweT2alBt8riVQioCwB0IpVU4sZUYR5hkvOw6LYIMQsnJeBLxYjOactChJQzQhhcFzW7G6UUYg1ynxOsWNdwrdQcitUJn4uljwUHrQmYUFwRte9zVzyYFEvqu6qsbaJ328DWy5uQEjdu22fsU2+tLBumKbEzP8ZC4kcePMf0SPnMfmYWhHmEqB3fzMkVQ2ZIrIpAuFnDODTXSqP7QAbx9azZmnD58iW2ZyectwWNwYNdx97hIRoCuYrMp9MVgUfu9PAbQOuZ4s+pXfnOg7Rex2Syw97exQIYZWAcXW/B2Ao1FtAEG/Kz9EgnIIPgRAhUMbK7s+dCYlGe1XU9XPFGxYUBT62Aqg2g8YzKz+r5vvvOnK9vuK1Lrfs7tWxPAjtNeYYNDz/+abXflp2/CvHv3oPD+7ZhHp4C7WvHekvzED9V9ugaG/63ufWudK6awHNHia8dZG60TqZxeLNj1sELr2XQgBgEiRBHpDZluvWvxnAXk8IWJ8PcEoBKONbMjUWLYDSHJ0wXC+TF14o7nLd0kTONZK6/dkx3dc7H6nI/+vdA2Gnclb2/gRS3wBFGPaOP13p2w9y38gw5LImhktpAhpFW0KS/25NgntNRlsmBy+gswVTZd6fR92qRtXd4bezNlgM6frYlgHOXywC05oy9yfC4phExlojRLLsKBLZrr/Wk89itpqLQ/Y/XOVnee2Ovrr8Jp3t9hThkfVHZsCipOTFclzZW97aVdz2gqmKFBqWuKoIpCwWLkUkwusJ+1m/+OXrun0qKhqVo9ue5UJEWP85ovhDkQl5RheDJfgu9VZczwSpycLwdLJRcCMEnLAHNsAiFflqhVXV3NIEsJdGdlLghUxp1odQyaFSPvVFPMquSnWAjCFVQTBUJiTRXbvMQuxcepDp3EckdN17/JsES+4fHTB7eI1QRzZ5jyFB3cdSWSV2xEKWxCGpoBdYqe5Ma1YxIpBUjS0TqhluHt3jkQ9/H5fd+N91iTjYjNIFnv/UctSwTuXU4qAjiC2wQd5vMRSAzKUloRdw1zorgr1Zik6S40yptkcWq4HT3ijoIMVvSgBcNX0BKwKwvGrEs2r3CsApu6WvNtWZqUJtA8I3D2YX6VTwgwZgUoTAX3tpYtDuGL5AZQzsXA7pCbYLhecLMfHyLNszMyTY6U6J6vikJnjx4LkqDu9Rp8nnpLEFGlaADTN1FwzByFo8ZFMFyQEtclvdbQLRcEz0xryfkC0zMkyi2fcLlMv+t1K9Fk5XF810lcffHGn+HPJbMCKaF3dLdRcWcYfHdVzaJJ28ztrmXet/IDc+W2lYO9PtSu2j5zAuv8l3nGp56cpf3HRufu32LuRXGLXrdjws64zifsxsgyw2xKDvM3C222a7ZaRIf+t1f5W/8iafYvryHXI/IL3+OcDLja1rx33/8j6B1VWp7c7297NO79a5tPGwbjjfNFpcuPbK0wJUbrWA66YWhIuTIUsMcgwsfIfS9tBEPbngWGdqwZCe+m9BtK/++ETB2xylktvn34fhSMr3TyJ2SiwaA++4osvZltU/LiPbW0E2uU2uj3Cu3zhrEewdSa+2RtZlU9kApe3Q/cfq5GoLvpY1AUOP35sLvH3mczcuHmdoMy8LvH3RcnwsLBb00cc+LXkZe0VPJ8uGGfljODhNhUlUcJuW/fekGc1X+462HeM9eTTDoWlicFAIdhMUscdLlQs5k5flKPFEUzjeRw049b9dAZLVc0U572vYxQavgUmQMqmx0erEsW+9i7+RU2aTnzR1qCQChyJfBrYV9BMAKmMLlq7p41ciovacHefnDmWufi2JkE1o1DgqLb+9tMijDRusOuCwXg8uwVbCVloxVAj0L5PqtV/rW1n608aGyP40Wid6tsn/E8XJhrOb5uo946t8FQBWhKpo88xilhUKIAcHoNPjLJf5SxcJi1qqW7LORRjw2x8wTo5l2ECrI7vVbA50oOXtMjCosYkeQQFanFc4mnhjVlLoXInqXK5GSPM8na4OQSpBxlMgEZVFAjEafsHWfZFU8V5AoiBmtZqoQ6OZzOoy0fYW6inSLGaoth90OLz73Is9+8WV+5H1bTnaQnMa9riv/XhJ2VkFIptRVTS2BW2nOdGsL0eBxQymhAQ6OjtmbzHn4gQc57M5RTbY5Pj7g67//28yOj5l3yjRUGE6DHmKJFauMSsFEsShk7WOrPBHtBCkU3kuXg1a8f3o3OwRyhIk5+MilX7dwwT9Lv+AIauqEHyjbxVUv4zmdpPJ8WL0+qy5AzlCMSIuDMI/bcisRvSBESdJnkSCKqLEwN333CYSlxGmFAsRrgW78xptnBe9jrXrwbmbUlHwgKtTiLo4zfMGjkKVA8FinokGqLKCmDoDMc4BlCjFFCW12l8FAZV7vXNxqGM0Z/DrLBST6ppHF3fxITn0aMbJlkiiNVGSB2iAGt+Aq5rFeyDs6se8g2AJn7wDLTeOegNU9rur3C6T1lZ8m9Vu9U1NXBJnQzTqqa/u0B90Qwyd9zIHIhn1vJAz2H1lqRJcOe0ZVVVx/6TqL1PK+S1Ne+o3fYOfr3+LoEw/w0CcvQbPNJBh1DLyiZVs2YLwxv+Vtcq0zxuVeOr/EFgyijIxnzBhkLnX7S0tVf7kMwkAYHRs+CYOCY0WoHJ9T+uWMJzz1SOtxPWMgc8ptaA11nQZTG2+7udwBwZ0CU4yE7XdwydmGfHy9JaGfduP3ZykM9z0x/nXZEesEa+ty7tnlLj251HWscAFghRVvFYuvtdD3Ek9YL/yxH/k+dPpV/sVnn+f/86Ir2yoJtDmwyPChxy7wJz/1IZC4Yv0Y3O5KP/RrR6/k618UAbZV+LEHL7BXBb58MOeffO42D4ToslwVeGo6IUhgAXzl4IhrXeIj62+A+Jg0MRCSbe5DGT3n+D0QSo6v5XX9Oud9OXr3CzBJ6my6rboCuc8l1l8mvaufMSibPU3PGET7CYLLmDF4THmQ0/FL2ZbjdFYZ7zWdBldiGzzQeMy0DUALOrPB0tX/bsBJKrnHquVeOHjn9WvThnf51FyT007dfeuGaV/uqzDQNQ6W2AL+hrEwO0s/8baWdz2g6qyj1ilZM1mMxipCISswyyV/T3btqEXPzyMQKhfEVZQW18YGE+YpMZFIJnmMlbk1IYm7EGZAYnSGviI8u/AqZE1kMf+cDYp/cs6ZyiLzkIr1K6DB6aoxZWYZK8JrTNDFQC1SLB1uyVIUK7E9apCPj9mSCSFWqEVqURbdjJ2dKddeOmQ6OUcVnbCjy24xqaqASmYiSq2CVTVHszk72w0mLVIFaAIkUFOqasLs5IBrz36DeTVjsndMm2vq7SlxUnFpJ9AeGpVlJuJ9RCiLguAul0AqlHtVFZwgIrvlJAe3MNUmYH3aOCcIsWLhiSa0aEnv7vmYJBTWPHW6cQigoNGvq4PXFUsi4WjuQjlJggZDQxlHBSFQiVFLcMAlRhCjCR6lK8VkryosghJU0eyupM6gJ0SVwXqkyODmt6XO8teKW3eawpoXY3EDFEdPCZgI5LLzSnE/DQKmRk1ASqLiLN5vGFTqZBmtOnCygSHROzwn14ZrcJr43hLXUNwKTdxKlt1NMWhZIoODzYz/HnNEQ8nxJYGFJQefWrLZ2wg8vgPLmS3fILyMf9okGL5Ruf+OvWZnnXWHm9jaKRsb2R8S4mRKfupJfu9rX+BfH8545jjzvLgLSJuVa2UtDT2TFDLsjIOAv3KDkl/Flvx873n0KZ758jeIZrz8wnMcfvObPHPjOv/Df/WzPPvfbnE0M57ojG2B2w89XBQIZxBTvMH+XQUZd+iMO17t17TtCa/ffMUtVHL6+Grblq0XiYQQqKrIg5cuUvV0YIwk7eEyGTTfgpA0M5vPXBFXN0ybZkW4vVvrm2bCdLKFYKgqXdfe+RpjndX7zZe19+c+yjnfEWV/LnRlPCeVUVUupAY8trYHWDAWLgtjZg+SS+cPTGhlyjo724hpzc6ezSugeXzgHkCr9U3YgM5NGJIO9+jrsauXeOjBCyzyi1jZ/H2NiJgYTzxymY9/95MDs5y7ZknJbdivIVbATFlXpPcocTB0NG95SIwKpVP4lUP33HGkmgl2AhhbdeS9V84TIuyd26GkWtwINGyld1YBVj//DXfP7wFRL7BHKWRS43oHRUh/P0/VIuIK1AAsyT0G3YpbXsr9grjHE+WsXOQLJ0uD3alw7pysMP2ZQUpwMpcVMLz6vH6DplYaz7WCmoP/roOukwEIDm6K2RXfPaBpSzhAMJbtH8Dd8jan8kIN3VsU3whNtLEebnVMbIDWHheVhUVaum2uPN9wbv9KjDe9+1Pe/YAqK1XuPFhfhDa4ABxSIJakCRIiodBNV+IASdVzrQgBNXe8bIIQS9BcViNSY+IB+kYmkV3wt4CKuwVuh7pYB5xCvRZDLSHFfS9HJYtrdbaJdKEI09ldw07KS2t4oH8dIqoQaiFJoDGhi0ZdgxSidcnC9fkB770yod7/Gl1zken2Ns38iJ1mi489cYnPtwEk0KnQRWUx79hpGkQTXWxou0wtgqSEhC2O5wvO1ROmBTR2bWJvZ5ummXLu8iNcuTjlkcffw1wqVFvybM72+Y5ffPV1YlCYChE3SxuAunueqEDwF9YnowsRsViWehc1Fc/OEG2puQg4c2Lvhhbx8TO83rKkkClJfvEFTNWY0VN7u7Bfq1cgOAhrtYAmg7kZmLvQpaIRklRYesxju9TKilJUNVk9/sFw8FH53T1Bb/DFbSHqY6swKatOEB9vDEL2/qjFGQxrnC5WxNubzagtkCSTkZI42q2tiQKeTJlIYF5IJERK3FaRdhNuMR3E4QCWfcGugjMlSiVU6hbERfAFaiIeBybiLJSpn6fmVr+6bARqhhWX2Hd8WZFQzn6esbCyJlK/PeWeKhuftKGt640847kkVDz+Xe/nDx29wE9+6Safnxfth5XNX2B37zznLlzwasaCx1ptwy1lFLdQXuRJrKlDzZeeeY5udsyttuOXbh3zey/te364ENiNgUfOP4ZWzYruUk592NAFd+iKN15ktcvKt8XiiMX8iH6d8SaMGmGsAKRe8Axhikgkxsil87sQJ6eewdZ/KPc8OZnxpW9+GVXl6uWrvPfxJzeAqdPic6/of+zhx3nkoUcA2D/c52vf/MpIMpFTY7jeD3cC87bW+HWt+eqxzTVvFPzfoSUZdCaFLa/kVDInGlKzwT16LAT24Lm8bhtHpD/eW3hsqHukJFgfKln5Z6jo9CuzNgJiaxfJ2lQzJzuaL7BvvYCczJFnr3E15LITL+fBrSR0qSvseoI64wGLAghWLQr+AFGcTn1HCnAx0NQBSh0iT2zXfP8F4zePjMPct9B75fy5CT/5H/1hzl3YZWvaMGt1IGJwhbWHX/S08AN0kdVe6NuVrXeFs5Jvsiynwb2hNq9LDlY6llboPiyhf8bBLU1gqzK2qwIyKYRWpU+2twLHrbE/t6Ff6yoMyi0rskVK/u/m8V0uS3Ul7Gz7dblcJ4or0PsWVq7onSKctHDSKobHlitCI1BFltbXZUc6xu4n4rA0yOivX6PmivH1NhpLwG62bGfWlVusXLT8/duzgrzrAZWmjpQyfYyLakaItNYhFohEAq5xDQG6zskIpAjJTVV5It7gfH8aAhIrQnbXOlUjiTCJDdnS4B4FSicAmWlJ6jpXJRSGu2SZnaomB6Em0JoTT/qLZITorG5BAg2hWF7KiySxxLG4P+pEjJMk1CU2J6ny8re+zPvjPtefu8krtzrObZ9jeqHhvQ+/jz//R7+Hl259jrlmQqioLTKz1mlLJbJdC0d5jmFsTSeejyBH5lVgW8xjvyRwoZqys71LVcHeuQdYzGfk6Q7tItMdHBMuvpe89QKzrmMbw3KAkn09BRmSwVa4P7FIT8LgzHwZT74sZQXr3fP6xL7+AoaBPr3NbkFS8Zgq8NgrLQFcnqy5Hx//rVYHBvMSVxUKdXgy8y/iMWxtAV+qQgjqlqcMOXhwbYUD4a5sahOJhKCDG14VPa4qFpayGN1lrnXuexbZrUs7CCfm4DCqsVChCdDizGlm0GjoI7JoLRfNoCcSjoUN0MxBqIblgqU4uOmKZTMCjcGi0NjW9IY+IwYlZ2c9zJpBjBzcXSOqM0AGCYjqsFgJ0JKx4uYXS9Bx0jRsUu/UMogx67vrPVyzSeR8w71x5gVvX7+elrmEyoynTg55oql5KEaiU+H4mBfB6KGrD3PpwQeXqsk7jLXL6uoa93KeqmIBkMD3/dgf5l/+g5/l5IbwmUnNJHlC6V2EDzz4EOeefNJTJfSuHW+iM886fW1rXz2w/mVNrlzFo0tCjtVLZeXcpaAogyLGVDa6t8mGT0ZRWGjGVDHLd4VAqzVaic1wMSDGuHKGjSe6LIX7lfpX/M4EW5tBy68bXG42zJU7vSvvdFDVC+gqhfY7L3tzlj3mSEZAgnLUhUnfL2KRAWTsQz2W3Mfzcv3lOAPP9j+vuxAuW1xaMZjQ7NQ5449ZwRYt3UvXYf+Iq/Nj/s8/dAnDOJpnrr+eOJwZ//TmHNU8CMu2ocqxpdfnu0+ZnuQqCDz9XU/xEi0vvPwCf+zRizx9BT79euL2rGOeYN4pCzK3NPPf/MJn+L6PfTdPP/0EshjYosp65vds+ryRo7KpayJuUTFxwqpe0RLE99KBIEL6I15UpCjKGeWO6h9T+taAwLQytmvjqAu0JXdk/yJmxZP8unjLzRM46XAvGko8tUJK6nHeFgZq9fHY9nedJzicFZdk6938zJmxS7s8KXFPplNmpriSGIOtCrYbkLCMI3VlgCyBarEcrb7Xtnz2flmQ1dVES7xZm9xlkoEyfjlKPYAzbMgM0Z8zrMn3Ubn7rgdUU3GzQ58o90RdYx+DM8YkFFImx0hFoip2hSgVIbhw2tQQtHIQIG4HCjG62xtu3VKEWmq3hFguwr+zpy10yR4XQnSXMfGYH38DYSsImqTE0ERadYF1EiJB3NIQS5xXkuIO1se0WKCJHvsSg1DbgtsvP8svPPs1vuuj38ONV17gGzdu8NDDj7E4qvh/ndzkIDzExRyYREFjoI7RkwqbYpUL0nQd1VZDlxLVtEKD0WUjJEMlkBujaiZsb59jWglxMuG112+hrXHl6iO0dL7Rd8mpTBUsOHhSlUIJ7kliwbUwczMs4omVAfAku6nEdYlBI86yhzkrVir9W5VxnoiQk2IWCjON0uFdvTCF4HT3aKDDWIj7t4cAucQ9mcLCjOkwRIGkhqJEBcUp3N0V1EG4GVjRzqiWxYdAaxSGHqHD48a05PLo5Uo1B15HOKGGaMm3gTpBhQRChm2cUKIz750qyEAYkVUIlZUs4yAlTlBN3M0ULUmQ3S20E6dVR6AqgLb3j57KUhMWzS1QQaIvjOKLUs5+kcdqKcEi0dxlVsWJXSQotTHEDrwryhtYjzc99dsHplYPyx1+uXMFGxiXBFCj3j/Afu03uZUTP16d52U54FUyrxVXv3L5SNja3OCVjTGXYIByxHJiPoeD/dv8Ty9e5dd++FP8d6liZu6KSs5ML17gfX/kB5FmQh9TMVR8r/jhjq26Fy3mJgi1+Rq5x28FUgIBtY5XX7tGPVChn752XQyZL+bF9dyWsQpntmb12l6wsPLHmQkDhi4F80EY7AWo0yXGwKSuBmHlbFISGf6aQJsyi67jnt6IdzqaovR3ATltDkVw9mdfpLMfsO//GNxVMA6kJV7XEAc3QmLLmjfNWU4d6b/b+lTZcN5K2TB0VsDCrO2wLlMJPPpExXTX6Loa+ewJMfnz7O5MmNaRbMIiLy0h/TPqSBDvTDhIDn+2gt9JgccefYBs7+WrLz3LZKdhb3uLP/1wSfUxz6TWUFFuL5TXF0pb+9pVxTAAMxhRtksx50j/NP2DjRkBBx3IqX5W67HyyNrUV2HFRS4bqQBoGQGHID0g8qv2W2F/sXSUm2HDPV9fJFRL/JUJs2TYPAEwKaEJyyFyuaYOgS2Bwo82gHVwhuVZGYPOKC5ya+tP7vuhtDkEgjm7XxQn9uhBP0PdnrtsnjxVjfZXj6qW0r8OhkboB4glzZDh8fR9PFgIRh2WbJT9v2rGIhUXR+n7S0f9wH0r73pAtcCos5Qs1UZDwCyTs2vorfji1gWsiAQmjZCzv1fzQkYh5loHCRW5xC1V5a2P4taJDMWf1YXc1MdJxUBnnksqqZX4OWdX2y65rMRCIc9wavU6eE4iIYBkQhHge5fEBmd/6U3VAaWuHCAggWbnAtNqh1e++Q3OnztHdW6baZxCnPK5L7/Ikx99mp1G3IohQlNVqBiTKiAaaKrIbLFgu9qmTR1NXXkC17YjNFUxvQdoKmLTMM8zdlrlyu4ubaw4aluqOrCzd47UpYF0g2BEdaBT4b63SZ3KuxK3Vll2AFMLJbeR0qlS48/eZk841xZBTkoOqVzc5U6SM+JVIdMmqEIg44l4WxTJUFtPJe4L9BRfOoPAQj25cGUlIa6IAzDB7ZlmWHAyktY8QXFtQsJfKMX6sC3MvN0tDqKieSyZ6XLR9fwbS1c/63xeun+1gUkBPlJM5sqkj4nCWARvVxOlMBPhcVX9wmTudhhKzBjmFiTJheQCQJa5oiYIIfvin3MgiVFnt3hJabsFJxDJFCCmbu5XYCLBWR6l31zlTaCIf1/eTBl384q14gysY6esSctrck488yu/xJ95tObV48yvXT/x+YMrETB34TArcVE9I7RP0bsKwb0YUTdTPvvFL/N//H/8Y/7mf/Y/59Hv+hDT1+aeP04VSYmt7Ya6mb6xzfAtb5z3XsG6E2BBIncug8zmSS8sw7Xrz7M2csvTy3rRH+u16mMgfa/4clNjdra2efqp96Oqw68ni0zKHp+7f/tV2rQY2k5RrEyqip2JuymG3nI4/FkHquO1oC2A6t5x8Tu51BU0xQgoLjkWgXoV6i61//13H9msME9LEgXBYxebMKbTHnVvL5eOfxg+2fpP/tXWPth4Vo/mt7EylONqNMCJGV+4dUh9csID04b2OJC7VK51Z34RY2tasTcJJBPamboSTmCr9jipWVu8OEpxL4/VG5oAwV3349UHePhP/CBDQoUXr1FfexUUZrdmdLOOz7/4PF/5wrM8/Sd+kN3z2/TvjeFeLK2VPXFQNC1JlXrlg+IWIrUhomeoY10Fsl56iw3lut6LMghMgzCtpIQo+FwYLFgrqgqXI7XIfynDQeteNjEIWxHqOKhCBoTTRLiyHUtezPFsWYKkPlaqBy69K7+LJ+7iqOXZs1HiyCiszct7nfns678xAlHDvjK63JYhG1rAXB9rVZWcnB6vJSVkQoqCebX+/t/q31uo3nzp524QT6obg2DBXaNiiB6gH8QHLQYkOI14xF2jJlZiRIKSBCoxsgZyVKZURKdVIag6IUAGMUVMmFYVHUpTGO48rsQTtoJvRq04Dbt2ikQr1hPBYpk2JSamC9CYi+tx0KQUEzP0bynRhEhgd3uPj/65/wVZ5+xs70J3RNDA9qWH+PVf+jn2zl2ESjict9RVRVVBzoo0kdwmsmWauiLlTBMjiJE7RQLs1BVd9piw+ckR8+vPcHTUMQ81+3kHqoZ66xw5dywObnCyaDnO7upYqQxC3CL07g8lyW1w60gUoS0LRjS3gHTqLnNiRitKZe4CGCh+wqJU6v2lOFC05NbAzjImTtGKuCVuITrsGX0+MjUIWrKdFAFRitDo4+DA1/BFXXGwpOL5yWJZFII5cKnNF8OIYAkotKfuplPo83uwUaJjKwvOTmjJmSdzKDnNjLklgkQmOdBFX+1C0VxmkZKotxBz0PuFa3ket+o16sBc8bHs1BFVxGOmnAyDkvPKwVwglvPddaASX7C6Es8WccvbTDJVIWkBJ9PoF+JORrvivy9vazlr+/LNfST5rCscz3DNs16KMgfXF/cmvPraMeEk8WSIPEpgIcaxGF+mW1qozN+XGGvMupF0sQo2tLimWbnbw488wuEEjhJkVTrNWEmoTfCYgFDVhcFpsyB4T2WT9Lex3EPld4gHuueyKs+MPtsG9sXlecPyvw7gepW5nAVPNj9XX09T1zx46cHlyJhx82jObJHcVf7wdfylLq0yYXdrSlNHxpByzM4lp/4yTEeXKVc7bR2WLjvhjXbud17ZbZSdxvdNfy3GecgGR6/iUlV+KR2iBrPO3bK8+5cuTUvdha0Js2vKFMZfx8dGaGF94sny4ym4sALUlmQKSKCrA8dtx27qeP/eHvVNRRGSGq8cZvZzcNbZGNZcsPq54/uWSK/QHN9WsMF/xZU7LtwraTZj8dKrSHDyJ7l9jLbZU7+0Ldom2lu3efXZA57qvs/32NHdg/Q5osTTjrCU80/3n40EdR+jLiuxpLtZDsdoVvdLa5kDVbG2B/F1blrBuakMMcdjt2AXFcqcMXF2ZHOX+1mrzHImBqEq1PUD2UVfgziLoedJ7Y+MUzysutjZ8Gep/FoZhx5MllimNhuzpOTh2p6dWWgqqItL8biO00v6GotpAZt15fPncO4pg+og1MFT3PTt1+F+EGsZ2rcEzGWd0/sni7zrARWmnm+AXIgLFHJAoruCTczzL+XgwrKUDN8NSkCJFkmiRIkFs3iK0pB7a4BPbs9TpSWxq1NXaFSqLKgmEr3/a6AJFQo0EgtDigdHWjZMExqNmAMmiWgCRLdiiROaK06TaeqU6VXJnyXZmAic5I5zjfLxhzPPzx7EpjsE3YODF3lwsuDxSzs0240TJIhrjgyoNBFyoMsGXaaZbKGdEqqKTjNdStQ7DZ0aoRJO2owZXN8/4uaiIh+/zsuHM7ZDw7EKly9cYKaB4/mcK+rU3amn+S5xQE756S/ZUdLBbU+LI20qYKYyd3WrzUGtW6YKqbkFcoJWdDANUwR+f4UDAfHrtMQTBRsSLXfq9zB1oGVBqNRzjPW08iFSWO4UJZA6Q4IwwUjRN8PKfHOsALIQYrFwATE6WYgV7a8VQCYFODbZrVi5uKbG4ioYxYFJLMAeEzrRwV014bT/aJ873hMTdqY0AVCngw/m1s2FZaItGXWy4UQUGC1LS5sUopBo0HjgH4qTS6j6vInBk0x34tZX1OP6FuTSt9GhWHCw+84t90+jdc+3P1OeXEFIp45uFK3HG9odqjbgj+ztsWPHxBR4HGEX4YTAHLgdjGAd0+2tUWW2rHUQBpYAH2DeLphU0d9V8TQKIUREhU6VuUDcm0L0NA5BMxbCqkvbaQnnTZTTF55V1T2J82+mHXKHz+vYcUW4PV3s3lo51LHS3JV+HQnbrvplYG9cuz7lQXw6DaNGDV+KSUuxya8d35cBMNraz++GMksgCc/hNEjbAxSiByV96cNlRHqX7jXwObwQvT0GpLiPLuPUhrOHMSv2oRGBTC81j97d/q+NBdwCHqwHEKuj1IMfEU82nVQ56TI5ZXLbQVHE3eqUr8wS+5p54NykKBCW/XBasB4/x/h5iuVEIGV1YqjjBTz7MunWCaHNdLOWnBM5GNplrDPaNvFq6kiyVq+Np/wylrHXeUrpt5X3cEQEgvoe60BGSr6ltYGQIuiXtdLFnCWjYRCh6QGZrF3Xd3LvMgWUbFqksod3RanaBI/xWrreebqdJizfwdNKoXFyh/72tnpsjA1H4L0HccmKHLsyZmUS24ZhHJ7Jz5O18e6p27enRpsVWcC0EupIUSALiJDVyLqCYum/rrtqqt0/WeRdD6hyUd8ki2DFIhKNFKInnxOn8uzptVUznbn7VS2RJNnjn3IghUxb0G0UcbcxNTppPempFtHdXPsf1f1+KwmFqttYmLJNDaYkUbJkT4iGU316cmBjppmIaxPa4oc8k+T29Oh5m5wS2yMSW3PCBTVhvujYP2k5XnScHOxjs2O2ohMlfPTxC+Sjp3itqsiFiSPPZzTSkGNgf96VxaRCsyIh0onRLhIiHltjSSEGukVHEmGvrrj5+nUm08jR4oQsLc988bO8tn2e+tIljg2uPPIoO5MpmsypY9WtNSZLb28VnHI8O3051pMpuDbG3YsCQQMnkqhKzI6JOi25BU92W8Y1l+vdXa9sI9EZ8CjxVQ6yrWhnnC1QpLgWlDdQg9BkQaPQWuvzIQTfuoqKZSuGgfGxG7Q/RlPY+LKBFDDXYWh2IIkVGtLiPgfuCooEtnEGQWcWdFfFGJyStTMjqm/MLtK4i6iDmhJjpQ5yRAIBc+ZDseLDDD0xBWoYShNKIl6gUkXFKePF+jwZ4rmoCilKNi0+3+6vns01kK0Udz/LhU0wEKs/YFDyFsr6vnu3c++7ELgJVNzLve3UhzveQ8X4/127zs6t23zi6Qf4K1cnvHKz4x995Sa3DVo84fn7P/Sh5eZ8WpJba4OA6egH793p9Vd5TwPh2qtUYmxdPk+oamIViBh78xbNigV/N96U18ZdrrnT4TvD1nu8wT2caesnbbjZKYA1lmttLJaswpjNYeCwQU28oSFyqikGnHQL6FgxbJz1COP7rz/DqVtuuP6dXjp1tlZgECCHMsiRNurtpRDanx7GIzsIjEtJNSDsTZWLu1ryXEYmtZNnHR7Bzpa4lw5S9rzTBAzu6m3cOhK2amFSyUBYYQr7C2G/M1KnoznkzK/T2q0ruRNeSMb+LHPpViJUzmirCK8vjBttRuvAx55+0AXzwTpiQxt0bb6utrHAmOLe1eXsy4r6npZTxlJiPm+Ztx1JFNGMJGHRJU7Uhj4dC9vZ4CTJiivf6ZuzPGbLUXS2xhEgNFZejB78LSfA0pYr4rHVdXBV5xK3LQHCOjaz0aHevT6ZyzYifaLfAi6sn1erdfiwLv+OD2+IrD11rTfEG+u5s2RYTtb7bniM8c932S46E45buDWr3cWSZSXj8bG+DUNd47vbCFgKx+nfW6jedNmeTIlSUQXnRRMRqhCYBmcPEMtF0x/ddIzn4ZGCfFE3YSqdM8yIMhHXqiTNTjQhrsm3AMnykiY6BqZBCNHzKkiECe6epigUNzhwrYaokcRfgkkhrzBcsG9NSXiS18oiC1Wa4CBxkTy2pcMciHQti9zwSn6U3StbxJ0duvkJh0cH/OsvPc/XvvwKH/zhxgGTuNvZwpTtuuK4S0xrQevI4WzG9vYWXWvMZyfsbe1CEuaWkCjMj1u2iUy2d+Hlb/CtL3+ZG/sHNCmxuHGdo/OXkJPXufnyy3z8e/8w4UrNRIIL/FJ8X82ta60oMTt46f17DWMRPIZtWraS1ncJplRO316IOZyZzleYYZGKAIEJTjBh4guOiAdgVgF3ETQQcXfQQKBVj9Gy4LmYAkIXPB9IVRIQxgCY0SFMNZAH97hAMs/MXptQWSGjME/wW+HTqjFjYZ6TTIKDLjGnRU24ZsbpzN06ZwK5ct9uKZtNHfrk1LgAnJeWt2glrk8Uk+A0/+aMkXN8TnseLbfImQWntFdPqJyCu1+15vdpCFhUmhLLV7tfIBrKMwKL4qq1LSUPG4aFQDAhx/unFbr/5Y2JdPddCHwDlS9FZ/92L1aMQQmKQAfblrl0TqCKvPrqDMkMhCuIuKu0eG49qSKqqQiG67vkciceXFnEXWT/RDvnP/jNzzC9POFj1Xmeu3qFq2L8+NMPcOWhq+Tf+gz22S+wOJjxby89gV24OPTz2wXV77WuM/DsPZW71X8KuN1Dg3rhp88VM3anHNe1ceyFwTqwlEZ6YX0k7Yz48I3RedYLw5t7ZU2kukP7717e6cDqyrawPXULhceChNGbyWmFx9giOBL8+ysGOgXpIW/JK0jGLAzxLSH5vMjmbllRnUxIevPXyuiVc9VIGbQO7vpmy9gUpCTvbeIQ/yMYVfBciFGMXAUeeOA8KcHvHRf219L6aKEoAW1QmnoNvapPmCeP49VxHoaRmL9IS1c1MSFI46y0Wck5s0gJS5nn9he8cGtGVpikRJWFZ486XiuyXqGfWIIiNRZ52fXjOTdEKNrq+7UORU7PeVtVeqyc1wOrPv5oqQQZ5oZR8pCtvj99+gkxd9mfCoUcDbYrYbcu7tLS12fFS6rv8fXnY+3VX3+nhfGvw5El/efKYw/r/9oxk/UnWatvdGIdYKdekn71DTw9Pj2SHf+y7PT+/TCMWI8Vem9vedcDKkHdzzJ40l6PYxGsWJpcmBbXfJZ4nVYilThFtJQEqphQSe1CO07nrShdobJUTYQQwZyPLklEOkOrSJRIZYHKnBEQCR63E31BC0DO7uYVzGO1CIpZJJn7xQbzxK8S3BJSq7OrRDNyCfoxA8vKvJvRhEhqJqQYCIc36dqO7e1dnn/hOfYPlajZGdwwFrEiLTqsrlHLzNpE0zQY7mt7fHLiQnnuOMmeeHhxeEJWhRjJ1TYf/tgP8kA44pd/+dMcLmZol0nHLXHxGk9+3w9y5eIDVFRO0hCEidMhuoYJpTFIwTfuID2whAa3kngiOaMJzkDjSe4gaUSD0ubIFI/VmRJJhTq0Ki/VRFzoz+q+1ZjHmxmFIZDoeZXoN5rCrEhVrDQOnjoTpmJoR8mhBSkamqyYmIXKglvNzDeEbB564PFcDmzUlNp97ajECMU5MQbhhEzlkg4TC2jwfFFVWYaieULgUDbJ2FviRAhWQKC4lcrJOczHTxz51D1wM4XCDllJJKkOPteVCRUeKwgezJoQYnTXy5B9LuZgaPYUATG6UiLi1kHEWSeD4jm9/h0o336h7053vBfRf3WzHG+aoap48kc/SXj2S3zp5RvoIvPsfkcaYu16Md0GkCQCaDq7KUAznVBJcfnqrZ8hMNEMBovrr2A3b/P955U/+R/+cZq9hLynInzLuHX7kN9VZT7SVL6d5V5B1f0AU5vOv9f7iAhdWnD76OYphXYPlGzkKtRf01QTtic7Z7auFxbHgjxFEB4EGBv/e8aD3O23u3SOvdHO+w4s21HYjn38aaEAHys5RsK2x0jJ0K2DVxQrOGtZRsNyNBeO5n2FS8AkIrBYnu7/rlVWFLz9HDqcw8F8FZiDx4P31rQxAEjZWV4nVcWf/4kf4aWXX+Nv/P1Pc9SVuVfiwzw/ofD6YcvDfSulPDpGtmVMGRsEcJFQ3Nf8uS7u7tJKzXM3T/jG/EVms0TqjOdvdrx82JIyfH1/zkEKhArqvSkxhvJOrM5xKf0wrWxgVrYiKci4QeNhM1eKJoxJWFqIpR/jMt6twU7lFrCj7ORX/ZPWwWOzTYridBg9l03XnCBX+yMID21VBPFY6LqGGGUgiejb3ec6Gz/vAD1Wnmf0iLKqGlufDeMptGI5vUPZgL9GT1bmbenmSTT3Xxy1Yjnz1lo2Mrf2fbcOA4Nu6sG3p7zrAZWWxK+tuouYqqChJYTKBb9sVBXUUogGVOhyZlK09jnCVgE/GgzVQCuJCEwsQPDJWNc1YKhFdw9TRQs9tWWjC8q8U6qqvEC155bKZtS4q5lGoVIlaGBufrwuWqwQhIkEj2+RQkUtOCOfGCYK6hTxi/aEpqkJKaMi5HpKOL5JmNQcHhxR7+5x3Cm1CLHyWKwgMF8saKrAyWwBEqiqhtmiRTURYxzc1oJmZoczzp+/wATIi0Tabrj6ng/wZ37yR4k7ezzzta9Rb2+xODlg9/KT5OCAJQdo1OjJMz3mxwaKTpWS9M6MBmfAE2BRYsbEQIKDHSxSm9GZMhU339QWmYkD6abUh7klJRQgRokn6nVmAc8fNVOjDkqNL2hBq5HroQBOZNGydPfMolhhXorBSNlzdOUCyrLYKGg4UIuSzfNkWTGPO4W+tyNg7LAk54i4hSoJ1MGJLKAHft6eeXBrlmlwuvKyuIsIE3EtzwKjtojgwM/hTaFxJ9BTxefg8VwpuEUvBGdEzOaKgJg9ueKsjF+tgUAYk5LSxy36lqvu+/8uCCr/Ay2blIUbunR1q+g3nDe2gbgA54Qv5x67zPVnWv7qN17gqHXrsBbNaFJow0iT2qvKWbNOrd0+lxjJQctobikPwe/56ks3OPnMb/HQ4w/z9ReeZ89AXz2kvfE6Jy2kP/S+0VYqqxLA5lsOz/UHUe7c+3eWPtav3XhmOUlV6bp2OQYlnmUQVsdXi7+rMValL1d6dHAnMjU0ZywnosSybvWWMEfQckqIgZRGdOh9bM4Y6K3j+DPKu2vVKGK2wXHXx7voKbnU1pbLpbg/6sD140WZ4S7YrhQsPK+DoiMwrmJEfLH24vSzoApCE1kZX0+k6l4QnTo+65d339X9+gcjXGgqzk0nbEmmtUzGPUQ6nHjL08iEIZRsAHkC25W7v82zXzNYJ/B5d34aOD+tnAk5wDTsIFXkazeP+d1vHbE/V44WiW8eb5M1lutqYgj8lT/1MT76wYe5cG57jCwH08nKnBuWtNKJZRxkvN4Y7kpvNlDXLw+V84cfvO9cBinx4JTcVUEAj2HvlbrLkbdhoMdNXkJc2J64V5OUOC5ZG+sBYgzWrlJz78+5VvxR+rtsfhOXj1UU+qx7QQjjOKyzisEoZ/RaNOYG/+7x8yx/XI0BW9+HxqDyfpV3PaDK4vEwdaidgMFAJGBRIEOoIlYpapFW3SQ6qTwexJ3DBaRyDb6BmFOdZymMfebc+haA5LmQNGQ68XimQEkYbEqNklqjC4FpDsyDUhEIMdAFYUvL8hYDU3P3rRjM41OCkMmICpr9ez+hVIuQjlNbdycLHt1LVMfPs9AdFlVE5vuk430+9vAO33rVIxYPTmZsT6d03QIQulZp8EDwRZeZRmX/aMbW1hbaJmxitIuFB5BXNdJUdCLkg1c4zNs88uCT1NPLHB8d8YHv/Tgnt6/x+d/+PZrzD3keJPXkhTkYwSKdJQ9Kh5KKxRPxTjy4iizCXJU6eg6lqk/Wa2AlsHfeA0mMStzq5PQJbnVcqFsTg5V4KVtauII6YEvRyRQmwYXFhSkTKwyCCbcK2thF0TDxRLvReqjkG4yIkUx92vT5tPp5IEIudOcGTGMhzVJvNwIzcrFwOWU/ah7blMFyoPVHxUTdzdQcRGpQ6uAxehUu+ORipUMjTbCBBMSCscBdrfZ6USoIMbrlKkcHc0FLMGcPYHF3RMw364Tv4KrKwkr+L6BPiLxFQEKgrY22vX+L2LuhbNzSNqvxlsfuLIvf4302bFZWNlA1Tn77d+H1W1hUrufEaI9FJVDXU5q69nnCeCs8q3ohZVci9Q9i5ikIYqiQ+REHByd848Zt/un1OVd/5xmmYrRqVJrY290h/+jeqO51LWVf6+lf30R33eey+Z24R6xx+jqzkt/OBfUYo+e0goEhbFyvyDKp72p/FSs9oN0JOj/CVDm3vY1tbQ0ASUQIkymhrkvC0Jpps0XKiW8+85URqFpKhptkmXsbk3fB+mHFxiElvkXGmnbog+e7XAiRysvW6ykM30N6LxmXAJbHJSwBVMQGljwYASr6OpfgZPxe9MRGvrSLe1EMw+fkTH0S12yBLRsBQXwOdvMF8dYtFoc3uXDS8V//6acIIrSzOa8ezPjVr91mv8380rFSlbhdd6NbumZNY2ASAsnykLh2mCfmyu8YKYDK96EY4HsvnedjVy5yOO+4fTTnZ29kDlsHfUeth2M8fGmbyxf20DO9JkoerbT8Xt6GkSBPAV82vgwBUlquhtKfM5wmzAqftyB0eQmEIw5Yj9pxzM9wGeNfemw3fiv6OgYAU9bHJdHDErmvrAR2b/vCcN/h6cYrlfdZUgpAO7uuM9/kvu5xl47x2LgRw7Li917fGjfd6dux9r/rAVVlUEVDY0VEiKYuTCqE2GvcorO4ZSUTiIgL/Zgzghh0IaFWucXLlBp3Iaww5mrUCTpxjU2MAUnOuNeaJyOri1uhIAQynTrLH+J+u2KZQ+v8PDLRAnWIpOyMMJ5MVhGCu8OZW9U8/qZ/u5xcYD6/TXt8hO6/yuGsJk4bHnrgEg/ubPOjH97hH/7aS5gIdV2Ruw5NiXoyoSNx0s7Y2ZlSSc08zQgRVDqn6c4dZoFzO1NEAlgmWOL2qy8xvfo416+/ijZHmAYOD/eZxgUXJ50H9wQBdbAgKHPrMILThqqQomLqrIqdFatMYdTr8wlI0VIpHhdUqfsOa3E/MQlkS0wJJANTCOqumVGcUj2XBSaTPZu3GJMSF9RbrwTIooM7aDZF3RjpVq/gZuO25JgiKnPtQUhxd0PokrEVBMSTNJd4UXdDVKHL7jrRKUgwclK2Q0Vr3pZQrHambr1qxWhScOtRcZWsopGzMwxqMGopMUuiRcMsSKVUYqhGJ1sprIZaXE6jCTPLRI0eNogRo6cKiCJ0ZCoikqENnpS1Eg/+DVFQLQyHgGihZI0OvrYiPqb1u0Ag2lTerPS7qRpbr2xD5W8JFSy30bOrWDpJmCp6a59PXJzwf5ld5b+c32YGZNyK/FVb8NgHP8SjT7xntEmHO97AMHI2rHe3QZwdS5U4rZl/9Pt55Xde4JjAN0PmBr4WiMBO3fD4dMpOjEsstSKQ8rbI3fdSzdsDzjZohTd8vqdHMjiZz3jl+rUi2Cp7O3u8/8n3jSyHp8uqtnYVpa/fP8Y4jFkvWEoVCdGTz8empp5OiCk66+d669eEwjfyoHLnw++I0ltiAsK5WkbE30NvAnDS5bJfCCfJuDD1l+uwE/amxvYEjmaxECDIYIHqrZGCg6coy36TDX1/qk8HAXX57+psWJJZiAj1pvlrcHxywv7zLzH78leZTgJ/+Me+i3pak45OuPFq5NoLt7kmRnXi7LAr7SvP4GCw5FWSHqz1LbORNc5/y6aoZiZbgQ/9jz5C3NmCIPyPD1rSPJHnHTeuH1LtTUl751gUgigLNsQLSemzvXo0JWU5Lr3L3xh8jjuwH0m/ZpRwufxZ6Wtbgsf+BMPHsFcY9+cNiXBHQK43Mi13inVlycrNVkfKRgoWG7sAriKrZX+vleXiOxwV756VOdUfGUI0R8v0OgI6cz01OX3+qedbs4r1aPOMdeV+ug+/6wEVABaJ2YX62Ds7iec6qoLTTZsFKnFNfkZoTGglUSkkDFOIwTNNByqQ7H6+GpgIpNAxkYp5eema4GbmShJmqbhhSVkEasyU5ATodChRI1EzORg1vjgc5UQTIqJuyUCMJvpisjBBNZJDJppbVuaqGB0vvvw83au32dqfQwzs33qNV89fZv+DH+Wrn3+O6aPfxw5CHSIdiUU7p6orpiVXV7CaGANVJ6hEKowuJ0Jo2NvaIncLdra2PRltjEz3LnLl4ce4dG6bycVHWWhgMTtkdnQb3X0KE8/p5bKTk0jU4jE5pjjTnwoTCyTJxRfZE+smyyQNbnExJZsQQ8QyaCw+yuZa7lT8VGoTqiIWpgKhrLjARXw8Y58DSihsgIES0lG05zYIJlmMWqMvdtGADBbcBQa3eDXisUitZCpxh7fa3H20InjC5+ga5ErcFTAOK41r0GIdndZcpYC7iIoSgsdhRaHMD9fJaPEzj6XNGnC/+2Iy9XmhnhfKBDOloljFyprTGVT0+aUAPLg4m280CXdJxMCawLYImAxsiibGJAYm5tuNiDMd1s5a4MAQZfvdCqj68jYJ8/dU2fhQ0e7e+cTTx+8ECGS04V5sE+fec5H3a8XV5w45EOhEWIgRc0eMFTHGgQo6VhMkdZBHCWCHpvhzTZuKqoq02rpmurjKSCVU3/0hqsevolvbfAm3hFamTKqG//DH/xRy7gK6tc1ZuuVx+XZoJO9W3vSUGPXb3fGGFMVcZrY4Gc5tJ1PPxyObe2vcPxsFboPzu7vsTqfL38vUHKZcLDmoRFxBGQLUDe9/z9OeIHgscJrxwkvPMZsfb27Eu7wMjypL0HOmsqRnMZM+n84SPeRe4O7HopeQy+XLPFbLpLCy+mf9zsvPsn6kb5b/NrS5SLljYbd3d2sPjzi4fUCXDLPM9W/cZGunQsjMjhLgoCHSuQdOf4+iMEV6kGhsRWOnKc9mLi8czRNioUcuS088M3Ly8IWqjp7TM2ZC7bLG1m5kujfh5sGM7tYJ+sBF6p3tUrffWwTq2HdncZvtodHgGjcCEeMBZZSLawTD5NT5q0C3j0bL1icU7p/XSKostDjU96/gAPLW1C9FASzi3i8xyMq9+r89KcQAlEdzxMaPiQ3seSv3WXmWURtsWf9ySi6BzcqutgnV9E2Rca228s/KjnbWgri+H97569ta3vWAyhAndpCKpE53Hqy40qGQKlQUtVwEbCNbJAQXFhuULJ5UNqWOKoKYZ5ruTJkEqGRCK2BUxPISKMnzC1GhmOcOUsCEKigdhZozJLeIqQ4bXxCPZZnihARdCSbOASw4s04UQyXT5YxIhSUjlNxBcnTI8fUX2U8zBOXq4++lXRzx0ksv0O3v84HHt1AJzHUGGIdtS2YGlTCJEybZWKQ5UtfMuyOqmTJbzNm6sEMW46RNhO1A0o5Fl9m69Ahh0tDlltnhIfO0QKVi98GHafYuMgmVz2I1kOBmYVxonwCt+sK1wKnAA56Yt5Vi0ZOMlkDCaO6rHApw6JkZa6qS3TuhIQyvvRZXghScaIEAYhmx6HmYsjl1vLn7QSgARYuLYA5QS4Hh2QU/K+PSa5NKXmiSul+42wkTarGQeSiEQlChJYmf+MYo0TeiCFgq+X1FWSBMgpFEaERIxcJWletiMBqcJp4IUmgtuuwuqOKPRdRIMmNeKHK3iaj4PaSQR0gUtivfNjLOGNnIiEVJjBwEKZufqVIXq54UIBmi12XAVnE9SfgYLTDadP+Yde5/efvA4J2AzGlwJBs/br5u0wHb+E1G/9pZZxtYUl4RRfdb6tsLtiVwbO5GHUxc2BOBsm6JiYMpzQNl8CrTk2/tVnKLMPxnCBnE59elpz/M7idbd18zpzuOUZg+9DCTyXQQNnsBaCP8PKMb70f5dqkKg3TSKgABAABJREFU+udcH+rTIrKfOVgARwLeWVTIp0BbkYOmkwk0k7u2a70XLpy7MFTYC8uqyivXX9pcyRmduPK8366O/naUdTm1FAOSCSfdMg/SjTYM71E7M2TmaTTGwrCDWq9BxJVgl5oCq2RthNZuvLFbVyTXDefIht+LoJ+6BYezBTduK9bNOUovs7vdEKtQ4i6NZzr42Ifew+NXLhGBl5+/wZefu8Enf+CDbn1yHR51FajiIN+7N0+Jix6AglDY7CKWM7e/+jxb5/dc1jjoIIKZ0qSOaImj33qRZ19+jfP/wR/mwQ89dWoNNKHEGY3WGZbWv+H9op+ftvJSjtfX8fnjd0ukuC3KEjwZhmnJr0WRKQy6PLpw9Pc0n6AwkH6UmHFhjF3KlasYhdWjq8eVJUOhbDq7P+a39p+W+HJ0yurVsnZ9afrQZ+s4btPclWFPWTbwTIw1+qzrD/42lnc9oMoh0IRAEI9FMYzt4IQCrQaSGDknn9wmdCI0wTnVnKQAIhVYRwJycv9eKZaW1jI5L0penpasigQpcTqCWlcAUyq5o9zlDasKS5wL95W4W2BnisToMQVEz02FC+QdqcRk+etdG4RQBNsIASXEyPlLD9EoBFPyfI5IzYXzF5hceoRXbt8miaFBWeRMMLew5W5OnSZML06YWcskVtQxkDWhbUcVahBjlhLTZkqDMZ8ntuqKKIHJdJeT2y8wmyn11gXOPXDJJ3GsqGJ06laJdJppgtAlJYSldS7H7HFRBgS3Hpm6e5GEjGhV7HnucpZwlzgN4uQeoliG6Ahl0P7ECk9+i1uF3HJSE6ywP5rRSscETyyae1e7ogCr1F0vOvMYpVyW1gAoCQmR2pz8IkXXooVCPBFQxJRAYFFASIXSqSISqQrJySJ7xu9YtGEe3EqZC04fOxUKUURhJDSjLT7dFUanShXdLzFqWJrfxYh43JovVp482QxqMbrSJxXOcDkp+bViiRGUQlcaAcwti12RkEouX6qS420WHRAn883dqdp9c7qPxDp/MOV+LcqbwNG99N0m6fiNltEeZ2osvvE1/tMmsPvAFouDlsuV8HrrMZ1Bli4qY7Hh+vUXmR3ts3PuAuPcb0FcD7u1NR3onBkCma2AME+RYPWUcOlKyfGGAy4BDfWGxp4l8W3oj3s5527nbTh9I6B7q2VFgli9wx3vJcszbBDNluOzPlHWIfeYWW0jytpw91Uh83Rnt12HmZFVC8hbq+/dtjbcqWygv/bfl8xwWxVUuq5o760l4KKzrbx7Q6wUveuaDNaKs8dsWff417E71Z2Woo3LjMDl9z/FfhZ+7/MvcbJouY5wdVupqkhTXBlvJOEH3/MoF/e2UIOD20fcfv2Q7SaUnEqlT8K4PW59kt6qPeo3J9ERRI3ZizdoMOL2hHb/hKYCQiCSoUu8eLjgv3ltxp9NcHlwKbMCIPp+90ZkE7KGAfCcemeswC07/XYMYzImfRj0G84GeL7xHzIeg53NSGV99JgkGwGA06PWN3VwASw/zLPHq9/11TIYN2/l7TQHH2qrxwVbxjZZDz4LUQdLF8qV/WTc6IKGZUBN47VNBgsry9XodOzl+rJhtlLX8pH6VW/penjS/vs8VG++5EyblRgiVXYTQNJACBUEoy5uYgBEoRGKQJiZSsQQgiz8xTUFiWTSIAiIBc/7gHjiWTxBmyDEoCQCEoWt7LFBMZRw0aBUIWLJV4wkiYxbOObJqEJFkjwwzokJPSFQFtf2d+JuVpUEJDgjYKKl7RJ7DzzCE+//ENOd80jVsLj9Cg80xuT4PLHyzE1TiSRtMc3UsUYleUwTgTpWtGnOVCLHlXlSvBDQlGl2G7o2UxOIoaZbLOjaGSfHc849/Bgy2WZ2tM90OiXSYZY8/1NOLogptOK5mLKBkZG8dBHDjFqcNj5IdsLw6IulSSAE33CIhfI8BFQUi5E4EiPA80JNi8qjFiNLSfwbnYExBmGb4ItDdAGvK7FuEZyQAWNqPi+SGLFQnovVA5teZ4mQXavY9dMJBxLJlMrEc23hGb6rqE5yokZliligloBqiX3q6QwNCNlj3sxzYHWiTAfXVW9kVXs7myA0welZvQ1gMRALi18tngMkAFMxZhRht6x/Kp6M2LV0vaZJmJsD+Lb4gy1E2SrPexyMYIa6pIyE6KxHYiXZot1ftdC7rWwUZt/k9Rt+3jQSq1pLf4NevL3PjdwRH57ya7/+PF9vjWMyHcbcpHemXVau8Mq1a+zfeo3v/UNXCyUwS61pET6sV70PyTWNYLl8LzGhfWBIqdtw95PBNafU2wsxa/vpnSW/dfC0oUPe6Gx9M6DKhj+cgSvEY1UHQXr96LL0pDGjmlmKgKuQ6uxnu9sTjASfJdYdHRoLcL6W5pz56je/wry4IqachuP/TgEpGGJrh7LhYxBhq45MkdWXskzufo6vCO7QbwRgS2KK/uJN3bwRosvpY2Ojuaz9sDLbBvAAVVOTJg1fNeOYQJ4Je9mYRuXJCaCZ/Sw0tbPLosZJ1/HB91+hqfzh+nvGfhnoX3AZQZreutOvQuax8XVTYiwVcla6pKjCyUlHq3C7VV7vMgvt35Hl2zGsj+Whit6HuuTY6heM5Tt0mkdu2TQr03yJeAYILO4J018S8Jj4kgHH3fIpHiEjNKFD36+SlfT4RQFMCjEGgwJjGNNhwRxBj97He+Ux1q1yy0NWBqivaoD5d7SEFigmy/moQxct29jqEuDKciBGDILr5ezFfWVejh78ZHGqkretvOsBlZjHzGAdiywEjR7MHxJBcAuTeILVbO44FUiEEJipYhKZ546JVUiJp7EYsGIBSJpKnii3GgSiU2bjjC2IELMDiJ4xRwh0hlOdR0BzcTHLTCwiRJJmj8GpMyFEWqRQa1ohKQju2qYdfb7yiJt5j2aHVMyY7d90v2bp2I7wse96kvdenvMbNxJHx/ts1VP2W3dprAzO7Z6nTYnd7ZqTtqXLBnVFPjpgEmvEMlX05MWLroWgzE6OmWCcHO3TyRTNhu6/zsIyiwM4uHmTS5d2PQ9RAMuKBLcStuZAMWKIQqhA1HM4mVQOKixQi+dryLHELmnAgtInlOzErUeixoxMg7PpVaKIVSwkuzufOSmJivsrB1yLY2WHyoX0NYoRSvJSLZaaqgCKBqGw5ZOKRj2p0GkoOa+KYChgRDSXRIcIIQmtWEkKTEFrJR+ZebB+Lkt8xAkiCJClzK1ihaxxpqVkHiMVxbDikic4BXuTQYKwdA5xGlzBaMzB/0KUaG69dS518WBdA8lKC9QiqMA8OxFBhW9SSTMZYdH3S/CE1c7OCBaFUAgsUjK69tv95v8BlLcCgtbLt1HYXAFT1gsVhky2ODHhS88e8OnukJ/TW4Xu3N+ZhAwgp9cA5tyRUutAYNEiuRvq1qrGtmp6XXDuY0tzdrCl6vmtKPv7SGJQMqFdOE1/MLrarVWnNJebyh3PWYOZY1S2DryGDruXeu9cNoLaUWv6cuHCw2xtnR/dy1bvb8Jiccyt2y+tgGU/vRDhjGI1l3cY/Ts2hYyeqU9rsX5Mxn/H7WI5h8a/ptQ5nfsZ5QxMu1rsXk76zi6D1/MYHI3KquBqq8BpFfOcCspfCsdvW3NPt+uMl21FzC1NuHr5Aj/wwx/hC8/c4Le/9io2XwDGZ8WllR/6wJP88e99EsE9GT73zev8+I98kO2G8r73lpFVynQDjo/nbFUCMl3OHTNyySN57twW89snzGczFvPkzMqmHJ8kFp2x6JKnbiiS03jdW39qQaiDsFd7rDD4Xj5+6jUYsblfCuIZE3uvA5UohWgD2I7BY6YVDrrMVu2WvdtzXyunAc4P1jwbdJZqMM/CTJ21eLD2jKbG8smWQ7pOctEDqqWytTAP9mapEdTya0tKlx78wkB4swLKbBnbtcg4Jf6oH7P2MbWMrl0OTg+q1JxRODMaN1uCQOiB6PiJPDm1VPdvc33XAyo0M1Ulm2JEEp4lvE0JCZ6ILTmdG50FiB1ZhZ0YySrEkAqJgQumiUTMEbPIVAJkRU09ua4ZJ2ZsG5jUmApVAz3kmasSewBRhH2LbiVLRLc04fFdKk6ORw5+jgSa6LFBPWW7ak+O4G5aXciIZXZ2znH1ye9me2vC1vnLWC20R7f4rW9d58u//SXe88n/CYRIO5vTHu8z37+Fbu1x7qIQqkjXJrfWxS0WsyMW3YIoNW2XaKqao/1Ddnd2sCZSxcDxwS3OnT9f6Nvdpa0KDbN2xsHtm1y4+ITToxtUMXgSWITtylhoprZIDi6YZYFKApUJSXVgqErmvyOCFJ/qhkiSjIjbpWIITHHTf8SI4vQN2xq9f1CCKagz6U1DiWMKzsQoOZBCoqF2MgWhkFSE5dIboFI38Tfm+aI0J0SdYt/USMGoc0USB2wtGRWnyK9EqHD2wZbsBO8ZoikZiCFg1vndxOneFXfzTEUJ7U6jbrVSwwFfccPSsmi4JcwKaYbS4ZhJyhyzoEj2uAYrsVRa+QI3NyeosAwn2RMxS3FBWIjRJWFCpPWsaO6qoAX9ibKwjCajKZtIEqVL98/M/p1T7ixp35PgeJ/LqTYMGkw/0oOpypQ//z3fxX/10vN89VevcXRi6LQerEvy/yfvz4Nsy67zPvC39j7n3Hvz5pxvrvdqRFWhCjMIiigIImgQIk1RIylblhUy7WC73TSlYIjuCJoRDk+yLYWiw7KjTUVLarXc7Q4Fw7StwaIsEqAIjiCIGShUoeaqN085Z97hnL336j/WPnfIzFcDiSIB9K6ol/eee4Z99ri+NXwLKAFiw/hgh0KgrhMHm1uUXrnz6qv80Ne/xnf3BUmJO6OGX6TH6F//E6jzqAidXg9VoayUVFTUQ7MEqyopRMpSeOiJi5ztOh4/vMEf/+3fZG084g5dfuOPfC9aFjOq199DQ+TxOX8Mjt+03dCPPGgOqJxUjkKkE06c4QQ+aXw4X1GUvSN1m6+Wiw2tw83kHtklswkR9SfVTGfeqz0yK7jYByduQr0+U+kT3nUqKJocnDnsNM3U+cjbHQt4f6PyB6hleLvKDCix/pKZb+05c8NiRtDNV8xh3Ndpw3stNveaM0eA8MRd8C01u93k9Fqfv/ix9/Dshasc3tkxsCOJUR2oQ2Sl9PQ7RX4HSwicYiJFsnsoxGSWpdSORgVNyhefvsL7HzvPudPLc8ogTUpslDhoGOyMefm1fZrkGOEYiZJwJDyHIZl1CLFcoZO6z4AkmWkQgTpmYR9yrPAJa8SRciJg1hkgNWOtmYVZSe2dC2lBpaWamLcU6sSlswUdTnKKlmTgbKHEPI7aZepEEH5yUZ1a/VqSd82D0n6bR6CqR61Z7feZwdzWX6AqBF96Wm6V6f3sm4NpTq/2ciVbvc2zKapyGFvPhxk7o05bc+axuccym/PbVL7jAZUSCTneyXmLExlrolCz8iAOp2nCaiXZlarO8SSSPGU+LqKZ6tznOCZj5fNJSKkhiaecBANGFIcEIUiiEqPZTmo5oEQtvqaIfoL6vZDZ6mwwOWfC/jhFelLQYO5ghUqO0RGCcxSYayDJ0QRzvfJll2JxHdIQ3dsjJs/dpub2QLiojm63Y/ffi9zdvM3qhic0gZWqQxToFYWZyzXRjA4Z1YnFhR5FWbG8skoshJgskDzhGDQNd7fvcnv7NlQ9qv4K3U7J4uoGqXTgJIvf1sKRCAJJHY1LM7miNPs7m9UlqfnUBmfZ072aW6CqacTFOzooMZMjYEYfOpYtCtVMGuGhjELE49RikjQZcI05D1TKlppGLe6IhPlwq9KSCvmcIyS2uTGCxQUYvb6QROhoQj0EbcA5KrWEu6hSAA1mJfIS0IwOvTPSiYZoQlJmx/PJku+a46Mn5ED/YdIp0BOLNSOBF0t4XFsz4tSUBpkP0ABPpu33bcyaWHp7DbaQt9ZTVSOWCMHAW4GnSZbgs1GlIdHJTIQpueylJYQMLpvsgCkpg//vpPIW0dEfvCg4v5m8hUvwCTb2h9xeXOeJ//g/5gOpoN79Bn/uieeAaLGNMZKiUAVP7+7TFAeRl373Np/86osM+8u8+vTzfFAidxYUQuLmMPEN3+Xqp36Fw8EhH/n4x9g4s5EVB0Lz0FlGrw2oEsStTdLlV4ndklNPPcJTy47/i7/FwoeXGV/uMHxllLdcXr9hNQsR4uZPnJdI804dj7ivzd6mhSvzRZzDu5blbu6Gr1Mp24NSMte3WeNQ+5xZZ5oYapp6dDKgIrObNiNSCkdiboTR4IBnn//aTNxSG7PG7D/5Y5p8mzmd1eU1HnvkMVNk3aux8+H2uuFoyKtXXjEwJULdjN+gTf7/qcwL4rPfJp/nsNX8oJyNlTqpHIfvJwC2/HUKmt58fY89ZPZwvqGg+MEB5fXrvCse8N9+//0TYfbrz29y9e4Bv/Taba7e2eUdl05jabUSMSTqxiwwKZlCMKacWy1XIakyHNeENJ0npuQRUnJsDiO7VwYcDAIv3N1nmDyD5DlUoCjwRUEtsLzcp9OpEJjEbE2F8kzgMkUrDJPJC7MKh1bgb4GxQmY7PYqI59vcPk9/nwc82X4fZ6eoeY5odusVsaTQm+N0QlfoBADtNzo/HmYBGfMWsqlCrZ3M09Vh9r+5l5krgneOpYKJK6M1XwahCfZru2lZwLmFDqfXe3S7BVK2uTlngZfmfm0JjPJaN47cvjWgCYmVrrAwdtmqlftQp0Qao6g0aabW7TnHe+abVt52QPU3/+bf5Gd/9mf5qZ/6Kf67/+6/A2A0GvEf/Uf/ET//8z/PeDzmB3/wB/k7f+fvcPbs2cl1ly9f5id+4if41V/9VRYXF/mxH/sx/sbf+BsUxVurcsAmZOkdSSOeAofRmqtoJgcQnE9EMUa0EsWJt33YJaIUFMkCFMWbe5xGo4R1ydFgCVEFR4Vp5MdKZhKskWSxKQ5BY6BJRjzgaei6aEI9jgYjwcg5bi0ZXgTvPMYLmAVWJOeiEpxGxrTajISEQOVKqsLTiWNGqoRa2b9zhdArqUoTAjQJ3hfUBG5ffpFzpx8gNg17+3t0F/sQIqPRkO2DHW7euMaZlbOUFx+k7C4QKyEQWQCGTaC/cZqr117hta99mXJxkbXzF9Giw8ryEjsHd2nKHnUYU/rS2BCz1kWSAQzDQQY8CycGHJP9jnOEZEKIw6OSqFPCi2cMkCKNGjiISAZhKSvWFKMPd2hKRn+vBuhUJVtnYjbdmDiTJFHkBMsqtqqlHJQqhVKmTOAQE40YEA8pWWJnjFgkZtfCwnmaZO6kpXiCU8AhamTuEVCNFGLxWV5ddnmyRvJi7IQpOXzMjH6SGAvGaGR2TYu1U28xduIIFnUHSTjQSEetziMShQjRmfZPoyXxbaIBUAmawa75cHtpXRttYRurWbY0m+mTmsts0EhyQid4GhHw0EkeiAwzq+HvJ4TqD3sNObG8iff5/YCot4jX5ou+0ZUzQlYG+kLr0668sxT2C+F/S1CEAknwzrNLfPeHThsNsyRa94rt60Nefv4mj53e4PTt2/x4gitnCwZRGA8TV7RhoUiU5zwf3HQ8crjHM7v7rG7d5LG10hRHSVkaBVwwBU7Y3yHsbZL24fP/9JcY9Bf4UbnJahqx/cwBB0sbc774rch3zOAhgi8WKcolTBCZ1Qe3oqoSw5jQbIHGmR33KCCd700F+t1l1tbuY5oytRWt5k+f1T4D7B1ssr+/daR/s0Cjw8kLCcre7nX2dm/MvdNE4MiPVDKDQRsZn99NE4xG4YigclSUmn0jJmOnvbcl572HAH+PAR5iw87e1gTIvZ4ufLZHThq1R4XF30/5w19HZpBq7ic4LqbmrSQzpx3R+R8Z5G0/HbUMzD7rpFZrz7EQ8pP7R2fOO/oKx/qrHT4xMTg4YPDyVfyVKxQeyo5Dc2x2jFl0j4lUBwgNUtu8+7UvX+XUao9er0en30OjUteR7WHNwoLlOrt7YxvqIfV4bGyh7aNTIpL48n7D//7iISEpUTtoMqClIlA7lMR7HzrNf/YXnqJaXkSKCWYCyTGaMm3FCSGDM/c6R5uNarYxj7ffPFidrjWTXw19zY2D9oyZ5WdCMtFacKZzfnp+S6SRmP19Os/nYN/szScdKPN/8/tPcmmJTtbbnIlsHoxla1anEi6sespCcIW51qkzy+NgFHjpmuXd3FisOL3So9epKCqHdJzlrWuBrSqaov2dvFBCk7kdSnYZVHX0Sj9pD51pK1WoQmKviYSkVIUwbHS+cd+G8rYCqs997nP83b/7d3nve987d/yv/bW/xi/+4i/yC7/wC6ysrPBX/spf4Ud+5Ef4rd/6LcC0nz/8wz/MuXPn+O3f/m1u3LjBv/Pv/DuUZcl/89/8N2+pDqpC15srlBOlTsqiN//7GqWDMHI22DRr7Z03NzoTyI1ZTvGIi/hg7ldRYJws/miBgkIKxqLUyTawyplWNCWh0YgXjxPLX2Ual9bFwpmLXOuuJVAlo7aOkozYIGtfbF4bo5vzLlsQjO5dvdGuFx7e8eA5PvSA8MK1bRb6p1hYucD5jXWawU10/xR93+CLCvEFRRjT7G2i9YBzp1cpvdCMI8krXj0sL/H85mV+59f+GZ3uX+HJD3yIWpPRJieIYUwKi4y377D90pfQqovubVEtLBC6HW6//HX88jne9a7v5vSpszbxXcJjSXEjgiSL4ynEgKZLQsLjXMpA1ARypw4lmlZYs1XJEjcQ1Nzr8ELQRBRz1YNksWpJSFHtN2TCjKcOyhQJXpCogCcKeILFy8V2YVGKBtO4Es2dD7POVYVHk1J5IahZy1J0IJ5OJrXIXY1qpFRnLqIUNgGT4ByMCVTZsmacRK2VyCj3tWiXuRznpI5GIg6X5WIl5HivIObqV+Hxmgh5fI1TxKvHwptaF1ShzlY5IxqwSMImBQrxhJSzsDtF1JPEQF9XFRXLmaXJKOYLTUhSogtIdJSqljT492ig+lZYQ978Anxc6D5+9MgPs7c+Kii91fKGQOpoafWHeZtUeHCpT0qBz46GDEf7HL70KnVM9Do3+fKZq5SFp/BCWdrfp79+yD/7xZv83/5Pj7P17G/x0V7B+h9/nCujMY9eFs4d7uGKffShmqd+a40b3SU+21/micvP8ZG9lxA166iPkWtJCCnSbN8l3r1ORNjZusPnfMG/f9Dwb2xu0nhP8689BNn9GdWpQHhCW4rzONeZkW6m6mBpBROJqLhsUWFOQJ3y1k1hUQubxDmcL6e/zfTrPLCbXAEKTgpUjGCmrcfsndu+bN9vKlPL9BmzwKe96gQXRJXjx2eF77mimOA541vUCjWzcvyJo2xORpM5oH6v0fym4t9mq/r70FB8K6wjTYRRbaLuRI4+Onaw+NjzGwVlYb+3rk4pKaMRjOvZC+av16M3m7RZO7Z07hswARGzRfJJc8DgOK6aKylEtq7d5LP/5Dd5+e6BSU1i8lJ+E8pMxtAEx//4T36bxQVP0zi+dH1MdCU/9IHzLBQFVbmAektrMhomlpYqnCQ++6ufZ3U4YLzkie++hOaUDSlGCidc7Dj+rfsXEXHEKLy6M+JXNy1muisN3gnnVyvuP98Fr6ScH9NlUo8meSimCXzHI6VNp+bzvng0rlDnEe18O06IM2bav6XVm6xBcx016ZNp183+dqQzZrq/vc/cOnJ0LWLat9NemRkZMv17XNmhM1cwCacaR+UwmmVse+RwXuh1PasrJeKEw/2GW1sNSYWVpZJzZ/p0+xW+8kY2JvZ/u8bEmLh69ZC6sXCaNs8oGBA/ODTOgYMm4kVZqhyVk4kMJLkBTSFs33ulYxTi1EL/NpW3DVAdHBzwl/7SX+Lv//2/z3/1X/1Xk+O7u7v8g3/wD/hH/+gf8fGPfxyAf/gP/yFPPPEEv/M7v8OHP/xhfvmXf5lnnnmGT33qU5w9e5b3v//9/PW//tf5mZ/5Gf7z//w/p6qqN10PLx6SOeAVmOA+CmNQT3JQODMja1RIlkQVUSQ6cz9TR60R5yM+Wx/qBLS+4eIZ+UgZA0F8zkPkiDEY+MH8WEeppnAmwEYx64SfAVERY0qTBkYuGoDLhgYRRTUiooyC0BVLQluI8QumrOVtBpuk4W3OP/AIL9y6ST3ch7hLHFbZ4ua578GLxNEtW5SbRNi6SZVG3H75qyx1lcXlVfq9Hpr9W6sUWD2zwUujXa68/DwPP/k+kkYcsJsSzXhMt19x6dKj3No4w+7WXbZe+zpNCPiiixPl0n0fYG1pmUiDx+EyFXkSyVaaZCZ8ZyQImnPShCzcx6wmCpKAhKpQZFczr9m6Q9awJ4vdadRo0qOYhdJl6vRSLGYoieVO0pSIYnVKviFE89iuREjSghvLfZHUIJRmAC7RYqJCzJqYYEBDvfWl5TSDgoiIo0zmVpicZDKM3PeiFOoMrCCIRqI0OApQQd0Y50qzfIljTMSTSE4tb4WakS2QkCjUmMtgkbUxDYmQzOwuXlAN1gYx4RQj7UiO4Aw0FZnsI6bsXummhB3qZKI1bcSI7BVbzFwmto8quJQYE+g5Tw/hUAJvtXyrrCFvurxVge+bubL/Hu5lwyMzL6nwyPlThNeu82VVQoy8+sv/jLtXXwaUl4l80tWIMwHJ54SxSYWOCv/POwf8qb2alxY6PPPqFneGYw63hVN7B1RxSNhWPn3nLpvdATcS7OuQw9sNqrBYdoiibPW6fDAGXBjSaWoUs9A3EniGwD/2gX0CD6fIA0y1yrNvNCuctKJFC0zI2tbpy8uMxJjd9maofI/GtxwXayx/4PG2nxG5Zv1s8rwxyng3+T69fKqRncVQMvP7bNVfR45j8spYao0iJ+Cdv+cMQGvbrgWZWfDw3k/i5iZi2lyzHHn53OAOR5qJTpkt9wJSR/ULJ93391K+VdaR/ToRfbBk9kferZ2LAKUXLp4tmNw6g9oQLKeftkxo+WKF4x5mcgTMyvTzUXw0Cfo/Ft81efwJ46wFB9PPN194hWf/1Rfpry3y0T/2PrMa5dAGiwvK4DAqa3d2uPn8y+hu4Oq+cnO/ZHXREUMkNoEwMhfWpg40TSDFCCR+4+Yhhzt7fOLMGZ4KkeRM6ZhCoEC52IUPrC1my4jy1WrM13Z2aIALZcFGp8M7JVJvHiIrC9A1hUjM75FE0RjRZPtfmmnrhLn5HW8LnW+wI00029YnXXbs9NlrVOZ+k7l/52fMbBzlCb04X0Fp+/XImjIPF6fvPVdne67mf5uk7NdGqrU5sDm/0I2oVwrv2Nlr2DkwxVfhhU7P4zsOV0zXo9mKxQgvvHLI4biZqReIMzDuJ2QblqKmdMZVIDNj8SAEduvAOPff6DC7jzJDDvM2lLcNUP3kT/4kP/zDP8wnPvGJuUXsC1/4Ak3T8IlPfGJy7J3vfCf3338/n/nMZ/jwhz/MZz7zGd7znvfMmd1/8Ad/kJ/4iZ/g61//Oh/4wAeOPW88HjMeT/kQ9/b2ABDN1ikVYrTcQyk5Y5gSizkqvIAk1DtiirjgGYrFChQu4TILXsLIC5IknBfLZZQgOm9uXyKWG0g8LkXqaG5+aMI7o+8UTMPvnaDqqWWME0eDs2eICbqFM+E8igV1q0JHlA4lI4xsIOZYncL8zQjA5z/7G/T0tyjXVmH7Gk0IxCay1O1Tp4ad7W1b2JJYkmAJ7N+6jBsfEA9usdDrI50OVVEi4mhiw/b11yg7FfuHhyTnLHYAI1coxDEa3Kasujz1I/8hRX+Z0e4W+7t3Obhzg4O9bR750Ceg6mYLiuVVEmcTMTnJlO9CqY4GC07SzNjjPOZfm7B2cEKBabKds3c2C5ZCztMkSRFnVigfjbZe0RydVKASIDpqTXR9QSqSWRGTmZ473hGTAVaVRHQOkiOJo/JKg7nXiTdSi8IZmAneWO1ELZg7ZrIJi/mChgZRT1BjHQzJ3AJJCZxSOBsrIpn9z5llqUMHkWSudxIpklCJp0nGppZUGRDpimOS78U5YzJUS/KHgmqklzyIxY0l50hJ6UqBeCMZKMUEIVXLT+UcdLRAMWDlVbOrpM0bS2wsmfK6sFVaE04sl1qhNo5/L8Q63yprSCvLHVn3v/nlmFD0Br+/8Q8nlFkxy8CUE899pdJ59WW+4fsmQKcIMaF1yOfGLHS0VhxTGlwsSj5RLfGBVw+4k+C/v7XHc/94C0XoqMPHQJGMi2nbmVXHC/xyWVF6KL3nLz58lrP1AXcjfE9M/LQr+XeLgkFR8Hcfej8vdXqkFAl94dHlBVZPnZoXFjmhf7KwEptDUhgzsfgcbQ3XYenM44hcZIpQhJOpylvhI7ueiGPcJjVGpwApB2in2LB76xtoGs9UTkgpklKciimzbl2S3vzQel0EMi2F96wvLR9x7TqiEccUQFNQBSKeXn+V29t36FZd+t2FOUA1jXqYgZ6q1E2N3gNM3ev5b2f5VllHXAGFJ2dvt98mLn0z/egEXr1e59Na6Tqzm2Hjq0XF+dOkLwSycsvSZ3jf5q+yPnIcnTVM7jXj75bvmYX5OSvpzLWzugJgPApUp5f52I98hEc+9Li5ZombvybPsa2XXuPp//EW0ii/cq3hizuJ4TjyDz71AlXH47yxgaakjEOi1+3gHVzeDhwOSj717A0u/0//R47fVYbDEaeGQzqn+vQWuhSdEk3K+4sO/+nKCqOgHCZ44NQS3ZVFXFJ2twP1Qjllr8uKxEmolEyJFmZj10TdBJ8et07NrhtHlQ2zedpmT7kH8pohV5hTZEwedeR+M4tguz4edYxuHyezE33a4fni6bmte3/r1je9bBq3FNWsr7O33B9Ennl5ysHXRrF2uh4pmaw1s4oAWzMjzbAxy9QJ7eqJrFWFEWWJyR6ddlDPKA0WyuxXFkwBn5Qc8gHRvZX98q2VtwVQ/fzP/zxf/OIX+dznPnfst5s3b1JVFaurq3PHz549y82bNyfnzC5g7e/tbyeVv/E3/gb/xX/xXxw7XnqxXFNOCWR2aKcGsvJkaBeoJInSG1Ap1DrMksJa0iONDYonZd/d0nkSkdQYsEja+rIHLI4y0WTBUzKF+lCb7C7nSdK6eKWJWTykSCGekRp7XRE1c2maRUej4ly2qgA+CMkFUmi4fecGz3/hNxlu3aHq9ugtLrOwvMzZjXVu7e+wePoBipUO6+cvIgm2b7zC9t2rHOzssrJ8mmZvm/29nUxGESAFNDZsb+3w0JPfx2Mf/j5AIFmdI5FYjwkxUXQCUkVi7LKytMLZC/exc/YCX/3Mp+h1KlCj2fYohZjWU71NW5fM+lOLmdVDsr6xSWBTxMKPzIXPJ5vEmsy64zE2wJiMDTFoJAWzuFiOq5ahxlmcFh4RYSFbJ51AIWaxLFUMFKF4cag6oiZKkTx+hAplnJMCu9QuNC4zQSYcFlflMOBYZ9kiip8k+nUa6eEZa5s81+KzRmIMRMlNafBBSU5ZwDMSc10dE0g4nNg5JZbDbKyRKmujg5qOWJK5J3bUGcDCgFIX43+PmcrW4wiaEG8BsAveSCyM2loJziiuHeBdYeQcKREkUqinJpo2EgOSRfKMs4AY3+Ia9q20hryt5fWE4mMoYfaHt1ZO0qtaVIPjwUKpB4d8WUsDzTgudAJ//r3r7J47h6gplFzydBXkIBCf3eaUJD7yvod5x1bgt7d3+G/HO7wcE6Oc32UiUmZBBRW6ZcGp06u8+7s+yvmLDxgY39/mzzzzedZ7JUmgT+Ihpxw6ZX1hkauLq4By9twilzb68xvtTBtNtbbTb6oB1XBctsmXiRPK7hLiq2m7vl6bz2zas8dnD7sWkISaqIEU67nzZsTYox3SirAzn4/39eQeJyLEk+qea6rMGCFmQ/Czdjv/rjlOqxWoDgYDtra2GQ0PJtaquecdQbLTc/L9Z4WnPzgcBXxrrSMrXjjVdTMgyADVrKBqZWYMtzRo+U/KYF+zhC1i8SpMErebkOmd0CmFTscxGjQMRoGigLIUxrUp0qZPm5XEdVKn+bGtkzrI3LlT0Ld4YQN99mWuPf0am6/eyaHJNu/tNUxB6Zxjb2efr90YUiTYPFCgYtQIn35mM4PDFi1K3jONjCHiUFfy4Pkz/Ok/+qQRLzlhd++Qpz/563QK4dTjD7JwegM0sn1lm/s7wqgJvPDqbS5cWuNgLyAxkVKiCKZwbQHVBHTQ5rzLPSEzCpP8xrMxS9MTZ1tutrSuaMcOH+tzOfpb64Z7BPe0/HvHPL2P3mCGJk9nf2+7Pc/7WdfjdkwmNS+bdj0IWRxVNZY9JxauULh2fTG5rVGZxHaJwFLHUXmhW+UkyVFBM7MXrbufsLtb86Wn7zI6ZkYyMOQEnCaKnI/UlNX2TJ/fTTAr1lLl6Zcuvwfsj5Ummiz1dpVvOqC6cuUKP/VTP8UnP/lJut3uN/v29yw/+7M/y0//9E9Pvu/t7XHp0iVQo+JWTdln3ROdgSQjfrAGVxFqxcgaxGipi+QQ34A4DlKgwNF15g6YYiCoo1EBTdRi/p54b9ajGMF5AkqRhJCEQmx0OZzRDKsasYEGRCPiCgocDQ0Z+1PjcerwmfoaTagWhDAGX2V3xYbdnW1W1s/zzo/8CV793KcYbu/gEe689iJ3L5sArM98jdFwSCMeHxvT+obAxqUP8v4/8x+ysbGBFAWFwv5gn8HwkDvXn+fGJ/8JZx79IMVyn7C/i+v2cIVDUqIZDdCFZaJXVlfO0lk/QxwdsLl1l+HuLkXVxTlP6TyikaBKo5aImCjZrU8mm25So5GPeTEIE+Y6R0EyVz6XiFFxzijSk7aZloSgEefaHA6CtJpSNfc9BKJ3FqmklmchpIijxIvNyqCWlNaJEVeUIjgsZitENUKQ5IguToIuBYg5Ea+YitCyneMonLl0esn07C6DlLwYiJgFtc1tJiQKMSsY3qw9ooXFm6nFzPnsHtmIgo+UUpgXao4tEey+GqfCWeENTJVOiM7ishJCKYW9r8uLUnLGJujIgNFi0ooIzhWWJiAqI0w54JKYQkCTkaiIPd/aLb/7W4jv+ZZbQ/4wy+9RCD0u8h+9n1ACj60tcPulV7jcXcR1qpxIEh4/l/jTf2ydztI60iugYyQjEuHmv7jDN/7bQx76/vtY/u6HePqfvszP3xzwoiso1voUe4dICHyvOvoqjFC+7gK3HSz0epw6d4kz5y+wtLwMCDo6oHEx555zU3QiGM2/85Okv0cbQ+b+6swLzkoNHAOuktvArphx95s5acq6Z+fOApxpt+SjOq12e8b0zBmBRo7WTI680lG0+BaKHP+qQIiR7f2DmZ/zCjEreKkJx24UWLrvEt1ezxLPqxoBT6gZ12Pa+M1jTIkzdc1y8FxQvpxQv9nyxm/61oWgb7V1pOscq73OjLWjLXL89eQES8exsWXnFSvgiukNnHiq0lS1DtAUGI1sj7LY65YQaQqpNZ/bKhNnu2o6NXS+r2dAv4aIr0rGvR7/yz/5AlcPR/mXqcQ+pT9XYoBXm5xzE/uLwPpSRVk6xAmCz+B+QtzN3qBm1Iy4eHqRdz90PitZYXt7n2cKl/M1OqTw4BxaFDkHiFL5RMc3HIaEawIFHRarkjluEZl5sRZg+fY7kImoJnM/W/VkooRQ5gf7LCqb7/MWjLVWoPlyj4VfZwDtpA6zT5oSSJDbemYFeoMyzWeVlwRCUoZNovSeEOEgJJZK83DZr2GpoyyWMGoSTVKqwlFHZXvkp0pUhY6Dygm7uw0HB2miFGitR6ogTlhe7rJfx5zAOCtiZLou1yrcrRVpIoLgnPXrWsezUExp5FvWbs3v0+a3sur8HjbUN1m+6YDqC1/4Ardv3+aDH/zg5FiMkV//9V/nf/gf/gd+6Zd+ibqu2dnZmdMM3bp1i3PnzgFw7tw5fvd3f3fuvrdu3Zr8dlLpdDp0Op1jxwexph+6qMv5mlKkUIsJGanSy/t3k4yhrXSgEhhnrnsXzUpSiOUwatRjWZQgaKBIzvJM5Q1EsuandC77niqNGhsb2uZCSCSxAMcSqDOBRa2WhjUmNXeypBSYtaAhs8bRuk956pRw2nC4t0Ovs0jHV9z32AdY7hU8fGaDG1tDdja3eODi/Zy/cJb7lpRf/vSv8fRzLzLc36Lb6UNnlZVH3g+dCjodak2EGOhvnKU53KcfhjzwgT9O5/QGK8srxKamHhwwcIKEiERl48I76Lp9hF36xSnqqsvqmfu58ODjXLv+Cr4qiGoulHWeKD4LSF6MzS9gFqwqbxojLDaszEGgsY3iyeBUSER1lhMqt7UlVrbgXRRwiYaI1wIvQuELVBJF1mo1YNSn6gkpoClOZmNMniSRIrUiUXb/S0phsIMUo1ml8jUpJRxKLZGIuV0UZDDWEm44aNRiyFQljyuzgQZNeJ9ZntKEYwdVSw5sG7FDfZp4UnRUUGO7IIizuiUDQx6HK1vtjUOd4LPCoNG8jeb12GOuowEj8ChSYiiRyjmaBBJBnGn1xnkjdupADGg2GuwdxRIjA9S0vvOT7fpNlW+1NQR+T5hmUo5tjb+v9fytCZYToZ1ZTabQc54n1he4/vwVLi+s4Es/BScCL45O8XNfWiY9/dsUl5+h0UhVFFRJ6W8LT/1bT/Lgf/pRfvWnf41/+I1rfL0Rls5e4GN//k/w8pe/yotfepr3HgYuJCP/2RFhi8SZc+f4Y5/4IUT8TB2zqw3mhoyQNcJKS9etIrT5T+YIvGVeSJm88UltfPTYZIPVGeFS55pYJ9fp3DVTyDaFXHMgq2USOFIvONqDs+fA1Izze9OiHr1SAE2JcRrf44q2DoruDzj7wlXk4kNUnSUWe112dzYZDg9p6vHkviqtOCi07KjHKvEmy8ktdPKbvdUW+VZbRywG5IQ8UjMli+d2jm9H+mzUCja8wkTchKFmltn8jqo0LkyeU0rB+lpOYYFSLQtt6J8mpW4S++OUmVhnVurZuXVkmAITtzFNiVeffYXnvvQiDz3+MP377+d/+Z9+lTqCVUyYcONp60aXeLCXuK/ruHwIgwYWuwV//ce/i9Mby0RxlIXHFZn2OBk9+pXre3z9uZu865FT+DKvFe27qCMmIYVEbAK4nIS+gRAScazUhw3NMLCztcd+mehcOIuJZpLXndwnudqtXFdEi2EHY/ub7blWOXOvcd8qOOcw1gSlMsnvdOKFRz8e2UhUNSewNVlmohxiOl5SNI+s9vI5QDHzjKTKMCbq2AIRS1VTK/icfD2ostcYCEwiHDYwim2smTAMxjMQ1RSp7RK4MzbPKkYJ1RolJ+dN0ERbf733PKAt8J6O9Vk1QoIJSQii5g0gwu3h8Rht0em6YtH39t6D5s3LIm+1fNMB1fd///fzta99be7Yv/fv/Xu8853v5Gd+5me4dOkSZVnyK7/yK/zoj/4oAM899xyXL1/mqaeeAuCpp57iv/6v/2tu377NmTNnAPjkJz/J8vIyTz755Fuqj6gSJUAyWvEkUNNQiBFWaI6J8i4CnjoI6oz9RTFXPqfmghYFihQJovScsbDVEsw9MDqCmHa+QwFExmI5hzoKmqN9ShWLexFFNFKjJEs8hYih+uSFEjcVWLFg1JgiXoUyZuuERg539+hVPbrdLsOchPehs2d5/5P3U9xQLjxacGm1R6eA9z28zDPPP8t49XFKHaEkiv5ZFE+KDfvDAf1OD9fpcjDYQ1LE+S4b5y+iseHgcI/1xXX2fE1HPEGHRC90FpZZ7gg63uXO5iYrK2dZXllhOB7RqUqcLxjlCemiMHaBSkA1GqgRc8tMwEATC2qLVsT6oY6J6daSyRxaBj+MTtNptnaJ4LOmuYggrrA4M1GSN3ZBwU0CMoMoaMTyjAkxmEuoT0Zt15AoU15cxOLvnCjBWb70qEpUR4kJfxEhhZai2bQvUaBJBrIbNZcMFXsnxYB5dNbnSS0PVqlmRfK2hlNLosqMkA5b5YuoBMQSHmMU8AEDmymalW4YLDBUVXDR3jdqdmdwShMtZqt0gteYf7c2CiGQvAH/sSSqJPZ7sncQp+Yy4Ux1UEYTLktx1HnOeGesg/VbAFTfcmvIvX44Qch4M/c6tn3+3uXnY+X4bWSipcyiGovdLmeBL75yk3ppkcK1cUBTTXQSGPqS3js/zIVHP0R47TmaV57lYw+uUsV9+u9bIe2/wv7zl7lYCT+w3uE3/8gH6ffW+K4PP8VaucD9n/0SF5tATMoFp9ysCh5+7N1MhI9JZY2M2JS9LruK2GZZBqUfzRe/HA1xI4GqgsIfE0Ylz8HXK3OPFSA1DDeft7jFo2cejTma0zwfv/NU5DcwlVID2kw8dtq2nZeJjkhZCtxLwHrdl5nWbHLHI8Lv/F1nL7bPh8MRB9t3WBHLSSjdSF2PODzYy81xFDjNqArm/7ypcvQt5R7H73Xsjcq34jrSyoezYzepsjk8JKRIx5esFD2kI/RO+5wjaUrUrTnnTnMnmKZXFK3nhWQBgsTs2mTu7joZAFlYVcmuUhasH1OiTffUwp+plVEmOgJmzgGoR2O27m7zld99loff+QDveN8j7I8b/vIPf5BhnVnVkk5y1z3//GWePLPG1v4hTxYj3rvS49evD3jpoMZ3Pb1OH6RnMczq6PnC+FuiMh7XPHRhmdcu36RwFs7R7sHEmN9D2Lq+S7kdqDoVo50BdQHDGNjZHnJjHNgKkaev34LlFZ762HfhO9VUgMfacmKRIyExcnZzjyLLIdPz2rOn307q9BZUHJ8b+rpf5y46Mn9VIcTEMLRAuFWLMOmkwjSzjDLWqCaKkJlnTZYA89iJKc3kdZLJdZBDI3ILTMZFe7mb1ksUuqIcBkvBgsJegKRx8vyZiL/8mkKIkeev7U6UWMdUDe3yyMxftUS/hRd6xTxNxwSLHbHS+d9LQPebLN90QLW0tMS73/3uuWP9fp+NjY3J8R//8R/np3/6p1lfX2d5eZm/+lf/Kk899RQf/vCHAfiBH/gBnnzySf7yX/7L/K2/9be4efMm/8l/8p/wkz/5k/fUIN+rSIrmfmeh8XgsriNqJGWLwCiFbMXIhAAkJJq7U3QJ74WYKaiTM1eqmoCKUDlPUMtO7SSaEJ4aY1ZKRipRQyYcAM2U3t7EeorkctLbQFK7P+rwAfDZZ1hTZtTSHKdjwZqHg23El/T6i7YINOaT+sLtQ/S6UFUdOp0FbtYj9GDEb/7Pn+Pu5pjlCz0ubJzjzp27lGtr1IMh+2FM3xeoRFxjpAd7B7t0XQmLfcpOSVlU7I4GVEUFIbVk8nQ7CdGGheXzjNMyMY5xoyEkc+Pp+C5FtOS2yZm5o1GhQ4HLAnxSjFnHWSJb8xUz61zBVJshzuKUokSyJ6BZraL5ZieJBLVA7OQcZQFdlzOyp2z+daYRiZpI4inUkivXUdHkJhteSmZZQiyOKqRkwIyU82KZy2GhECVS4amTUDhHNH07KJmdL+XEzkKV+1AkkzrkGL4GsxRFlEDIKcDFCFUkcYjl7RIUCd7GsDOzvMvSsFBQCDR5EXEYXby5cinjCNE1eBHKVBitdIIQzc0RrF8iijpHIY6Q/dhJniiW082kXrH5o4lCcz4sbLwntVhEl9vgreiEvtXWkGNFj3xod4CZP69XjouyRw4eRWozcuubqtaRW80eXywc55Y6fO2VW/heZwKm5us2pfONJB7Yu8HipQX6972fznM3iRcHVB/sE16peGrU8KF+yfj+M7z42LsYCKRYsNBfgqUFmhggJlZjwcXVZR598n2gmUO/dZPJz1IxRrqYlK8NxrziEj9eXmX9E6dxy6uUhwPi51/g88MeLzzyjiNg5OR2PqE159tMA8Pdq8xu8cfPPtIBk82+VfHIFIyiU839ibVqn9P2bSttzYoJJz715PIWgMzRNzr663AwoAmKZHIbAfq9HmdOnaYJgZ29nXvf/HWw7L2A072+f7PKt+Q6crRT1UZEnfYJKeClC9qFRhjfaiaCq8xeD1lSbY/No2rF1vPNQWMhAS0SOlKJdt6lrMxk5lkWv5sZXWfR+MyC1YzGXH7+RZ750nM88d3v4+HHHsRVBT0nfPT9jxjQaSd4gjAas1TvIYMhZ6oxpxrl7uYeZyqh6SfOXFxibXkBKQsIidKblUpJRAcuZNdygaLITKOlUWYvjbogFgaw9uAaTkrG+xEKj6s8Ppoy8jAogwiqlojWDWv8bMvkNmiTyqIJlyKa0nw7v1E5Mr0n64GeoJfRowdmfphcL5Pvmm8cknI4sjxLmf94SgUjsFh5uoXk3430qhCTWcRN001I7nURoXdSTWYOTKs6P+FnSSpSUg7rxDAaSZfmSvccmQXbbqJAk5SQZsk1TtzFTjhmslFbt5Wu5/ximQlYjlw902aKcjB464zDb7a87Yl9Typ/+2//bZxz/OiP/uhcMr22eO/55//8n/MTP/ETPPXUU/T7fX7sx36M//K//C/f8rPa9SvhidqYtanwSDIK6hAjfWcU4SEbG33Lr+OUSoz4oOc8onY8iZjFKwlIJiyQLEiHZOQG4ggeupRAk/FBIip4cVQ4EjELumJxMimZi5hAI0pQpSOW10hcQZUipUSiRA4OD/HBs7SybPFCMdA0kX7ZZywFjVSUrg+qjDbvcO3GJinB4f4W95WPU8eazsIyMQVUYKmoiKqEKNSxwRdK9J6mHkG1AM5cHQvncU6oxw37ezugQjMe0vVCv9/nzqED8VRhhxWNRoNeQEEi4DKYzHFrGk0wzxTpiNLBNE5F8JRkRkaXLVFCTroLQqJwBaSEBDVXNTX3wE7hKMvCLHyq1DFk6GMWGhcM4BaZhKHVYBgDpPW7REF8IsWIqjEbumQWs0LcZDJPGAYxkoZSLNltxuVZO51AC9uknBqpBo6QGst3lmONyNYncWZNLcRcnYxVKKAqjHP8lJOGRhSPt1ivLACJmP9xEqWUIgM7QIWgtmiWydFxZqsrs0VMMEtSgxJcwiejhG+SkUwU4qm1wRuHOkhevFWokqdJAXJ+NtFk8VvJ+tWpxXF8M8sf5BpyvNxroX/zouHrQ4ET7nl0Y32dGs3u++3mJcBaTrD5mWdfYX19be6q2fpMLCrAICmiibVOh/Gnvsro2ibDP+G47/4z7H7xOnviGBQ9PvnOjzOgxBEQcVx64lFeeeRBXiGToDTCE04QXxp74MxzW3cYY/V0fGkU+J8PanYWhB96vOD8k110eRXRHm73Ls99ZdSGLsy3+D2a/9jhY82nJ5w3X8PZZp8aZqbOfpNYEZ2HUq0wAcLK8AAXE9sL/azsmApw6JF8Wm/A4PCWQcjcsGkBoEx1AgrbN29xX6cHOa5YBE6tr3N6fYPDwSFf+fqXJ1aMkyowJ2++TgVfD+D+QZc/7HWkFfSKsoYUcNieJZogyCQe5njTymQMnrQiOIHl0ud4mGyVmunv+Vrkv4Z7qLO1KsZZdUE+M/d/Mxry7Oe+wuVrt3n0fe/koUcvUVYFCpSF4/zqIpPErEkZD8b8wj/9Zd69tMLnd/bppoT0CtR1ufjBB7ny1Zc598g6p88s5rrYfLB8r0YixVKJE+HRBzdYWqgoK0e1UOFLR7/umKdEUlordwxG2+4pSCrcRthWobe4xB996v0srC5T7eyge0JrjpuCi9y2avPUt+a6Ix1xonLspBGu09V8VtA/WuaN063CZnqyZvCran282PVoVhSHDLJsuRFKgUFIDHMIREgWTtYtYKUsJq6LJ/97j8n8Omtuu2dElM1Um7fO5DShcBa60K4TCojLaV/mwKNO7quTE1sINlOv7G68VAqrHU9ZuKleCo6M3KxEAMpiFkJ/c8sfCKD69Kc/Pfe92+3ycz/3c/zcz/3cPa954IEH+Bf/4l/8vp/t8BRSEiVS+pIykxskcZQ5rqRJRmpQFA6Xk6BWzmxBglmqzP3LGPhSdnmqnOXcCVjunhiNyECxZLylEVATsHxLUUyQtdxReeJm+nXT9nvGGrL7oVAZBzgeoZNdxBIlw8N9tE70V9fx3mKvUgqMtaEoPb7wlOLNpa4O7B8Gzpw9z92tK9x95SU+8rE/xc2716mWz1CIx0mFFAUu1GiKVGWHejRgsazYj5HxcERHSoqkOE10y5JOf4Hx2NEMdrl1/RrjasxgWHMwEsoCDp2yML7DaGeTouhQYwmSSYlSvIFLh71jsjZkQjQBipFLNJIoUXwWVIKhBkq8JT0WJXlH35U4J0YC4U271qRAqdZX4xgoBMTZwmNxS4GaDGbE+tkmvEdFSdHAdRLLV7XSHLJXLpDEgbZuiDm2S5UR0BFHoWqkFZIyu6MBQEWJ0RIOewGRwtxFXXa3EMGLt9+dbYA58xWCpxTjECzyeuPU8pBJ1jqZG6nFK/mkRIkUuOxKGanE5xxTyjg1RAVRZ3GDyVG7HL+XMNO/tDTwapnMcwBp4czahprdt8ksgqoJl6ZBzRFF1GIGY/j9Aao/zDXk7SrH9tMTsdJJkGt+m7jX2bOfT/d63NnZZKQF6+urk19P1IvmC8sEjxWRjUtn2P6nn+Z8M+CVs453fLzL/gs3OPwn3+DMSPjF9TWuV12GhyNW+55OZQogyTleguuwkDq4WJuANom7sU1ONGVqZkHKDi9o4ppGGDf88j97lo89vY2rOgyj4mrl9iPvt81Sj5M8vKGQ/voI9liRE9zaTr6Nzuz+cGF/k8XxkOdO3UfbT8txAOPITq8HON61eZ2bC0vcWVgGEZbGQ5qiZOyLyb2mopmc+Py3BEoMRc1flLtBVFndusv5UxepxeV8O1O65rIsuXTf/aQUubt5l1E9ev1nz7TFSe3X/vpm6//NAl9/mOtI6WSCladRIsq4FDZlkRCNXAgPG8F+a+nSZ0HsvNB+8pLhROh5f+Jwb6+fkoJPj9v6H83jQzDrQQuM1NhbYz3mS5/+Hbb3DnnwHQ/yzvc/gfMCs+Ol9UlQhcGA57/8NDdubVHvR3xs+Og7zvPEw/exuHGavcdW+MpL11Fp/S9mrMUKuKn74WSuq2auCmnJ7hAsBclw1KAoo2FgWEcaAoPGrFMLBawsdDn/wDnUWfxz8kwsUi2gal0iWy+UKc347Pw5vmDPtMKRMusSfPSKuY655+9trOk4ZquUzoOYEUo9IeESUnCMVRklzZKstWpXYaU0eWMypjLenq3E6825o9boVgFjY8/i6irBZIsM6N1s/+UPHugV06eJTtQ9c+3RZFmj9QJAp+NhrVew3PXTOuVBOF/Fo/d/e8ofioXqD7IkjGZaxJNSIjmhpLDcPN6051KY5QMnCKXRbxdCzPl+JAMg58QC6CRhUTfmEqatq1TOmSTq8bnjncOIANSIFVzWtgjJyC5wFnyqEIl0vcv5hjyFdySX8MmydScnjOsh9TiwtraOOAsAdN5R1zVVWVA6T10PGO7cxPUXOdje5cyZs/QWKkLY5xN/4f9M8pGit0J3ZYODwz2SQqdTEgMs9zskEoMmUHQWKKnpdHsULliOrm6HYWroFh1rO6kouz3WT6+zdPZhysOGph6x4JVu7ajDMzRqQpOSWMCDGk16SomxM41LgSAeajHLkWo0hj3nCFgcmcNAYqHOzPVqVhQKo8kku+NpFIIEXEqMRAjBNo/kkjHYqdComY86kGnIlRJPUrN2aTJLVMxJjJNGNkeBqjR/dmNEchYZJ7YAdxVzDXCOhkBSwamndBZ3VFhSLdQpThIJMatW3kRwDnVKkdqF0Z6VJGVCFbGxbPDJGPbIFPKYpieoUqeaTo6qbdQSAHug1kASsxBGp5QJRBJ1UtCGFI0XqhQTsJwaXIxqdP4CJBLDZL+DsRZ6cfgkWXFgQMsS0Mdcvylr43dEmV2P76HIO1pmhcfff0uc7E42q/lrv3uBparixctX6SwvU3beWDsnAp6SR2XIw3ev8Wt3G/6kROJ6xdJDyvKHL+K6H6Xov8w1X7H15Huo1hcZH1rg9rzmU/EaUV+A1mQGF8BNKpqyW6mKw5WesRMOBFxKfPm1bc5tjSnFcWvcsFwIO/e/a/KeLZvxRBY4Ip9MBbA33bhHGjU/5FjnngRpsuApyrnNm1w62OOF9fMtuTHn5IDLRT8LA8rZ/R2Kesyd3hKi8NiNl7m6cR+3l1ZPrMbcI4/09T0wy5HBdlS9PP09hIg7HNE/ZXT3RlvdkoBAp6q4/z5jvBwMDhjVwyNPO1EbMCP8y1T7/gbyzMli6rd/6Zc29ybzM/+z2etybe1xwFxex4MBazf28DPvfa+me10ZfHZetMd1OjOP39nmbsd522GS4rCk8K0LaGpqPvPLv83OzgF/9E99L6fPrOXLp3NkymIohHHgS//Hr3Hj9jaPryxSO8fH/sz3875HzlKeP0V9YYl/+HP/gtP3XeTdTzzKsE7EBHVjSkhTMiZ6pdVtHGDvsKZfVYQm4usIpXkGCfDa7gH/n3/0q+xHR1RhmJSDZDkfkzh+8kf/CJceOk+qMhjpKn4pm3iSokXO09go6RBKp0hwyLjMr9guODLBV9PWzHBK7qEsm+m9OYCcT5aTp9AMFLK/TUqMYqRlJU1qISm1Wpqe9h4xMxu77AEjairgAgHxcxNNZsdCHiMi94CAJ0xHye8h+XldjFV4lhvVTQhZbP+Kqpmh2e4gYpZAcwuUmQU8A8J2MIujtZx6gYXSWd/MuS1M6Yvm587bK4d8xwMqxJLt+szQkpxjTKJQE1oLKXDJfC9dMrc/Y78WRIqskRcqEYJEeq5k5IxgQgGXDGUbBaRSSJHjpjIDXFKzcEhC1OHEmVsW0JGCkC0xRdv9qc1BBCSLUSrU0QBNHFAPDjm1fprkPM6bMOwx1zQpCgOC9YDD/Zs02561jdMULlAlz8b6OdZXV7l5/TX6/WUK5+lLycAFtE4UvZJaIhqVTlESQ2Mg01cURUEKgQUSYzHw44gU3T7nH3iC5u5X+caXf5NxZ4PO0ml2kxKjo7uwTq+s6IgnqhF3JIl49YgKPlN3h6xnkZauSKEST53ZAaMaqQSYUK9qjIyZIJGahItmlRExYGMJaK0PVIz22zKLMXG9HBEpKCyOLQfji6bMKmYJgi0qFuqkLLSEEuJJWNJnTW4SJGQA3oEamYM4q7tkM1jlzQIUnC01RfYx9tlSKupRJ0Z3jhitfgy0FLIp0zMZW78BlTILPlEjRCVFcwfUsmPjTLPFipgp2BNFTsTXuEhKasyRmSglJhOqOhTZ7cKCVX2yxXiMxalJzkPSpJBZK23RdljsoargSJNkzd8ZZV5zNi/hnCDRc/Khk277Bmfc89dZYXsKpizf232nV3j2hSt0VlfNJWJmBzWihKztm9EKdl3BI/GQ3v4+vzg+zVPyJfrnOxze2ad6/zLSO8vwU/+KSiNfePQhLt930YhhPBlMzTeLo6FMWyQRovRQc2ya1HssBZ/2y/Qj/LmqZLss2C08SYTfVeXaaEQjgld4SgvGLl/dIqnXwTu/3+3zZNjUHpneXSeITek1DSOEhJ/ErxQJlmvHegrc1oRzHqdKFdMkz06VxrQUyidpV49V6k3U+573mJxkgkuKET+uWRoN2FYjaJo9b/Z+nU6Pfq8xamsRRqMRIdRHbn20BjPOY/eYJifVciIQyUm/fpuVmbE6B5CzmxrO6MJ90JNf9XXa7Q2fe9LnuXtPR3WRJep2W3OaLSAHhzz9W18CEZ78nnexsbFy5JatxdjCFjZfvsY3vv4SqRHWFhZYOxhSbvR48s9+hNgv2JOCwzpxSGTRC1IYNXcTE4NxC84U78BjFtPNg8DhoEZXlVEdadKI/lJJCgEvynqvw2NJeG1gVimnyuZhTUzgS88Lz1/H15FKCnyngwyVKjpTXSZMA+XEqOQaIThFYzRijekIptLSUptwgiVEdbLd3auPZteVNzOqbfgbMFooCjq+ZU+0uyVVc8/PwEKZm942dLIC1ouli8m3pCpNkdw0mZ4+ZfIN87ecm8sZMjK7CrYLxBTHC6c6Bc67SSbpSWza5CIjQoltW+n02iYph425hRtmnMZh6cxTwEjA9sbKsIkmq3hhsXLGWUArpf/BrRzf8YDKOUvAWzrT1jtVMpMBFR5E6AjUYj7DhbfkrikvDNElapSueISSVDpLdGm6m8wZZ91WO3ND82LWJ5HM3AYWBIkQXMR7Ydw0dHxhHS9kVy4lFm3yW0flCkI2l0pTM94/4OzaWRpv1jFNQtdZbJiqo1OWBrLUsbdf88D9j9BZ2+DwYIs4GLN6/hKjdEhUpSr7VK5g4KCKSlV1SGJm9LppKDsVaTw2kg7nUSkoKs9eCIw0csqVjEdDKl8wGO7w7AsvsVcnOrqJX7rFeDjg1MYqurhsCXy9JZUlRUJyFGK5lupk9K4+uUwQQaYfT4yIJOfpiKLicjyRWQgrVZJavFCh5kKXspvemJAHtuKJOPUEsUS3nRy7JuKz1sZ81jVTsZfeUZOZg8Tincw6o4xTbY57asGUC85ilDQvDpZcUWwT0Jae3KyZJYKoWa0KsYmecjJcj1mXHFjiZoSIGrkJtiiNY0MpBUEhSECj4CShzhYVkr1LJOHqhoYG8RU+GaFFgy0qSRPqDMw3GLFHgUA0tsAEjCXSMZhOAzgN2S3TrLFB22TEBjQLTUQXLPYteRpRi8tSpUHMsvg2a4b+0MrR1zqq+G0/n6S1PHrdGzTRcRFVJoLQ0d8WOhWpifz6557nwsUNvG/JJ2RSR4uVyluimOJgrSh5YHiXm0N4rulzvrvHe90BzdcPqS52ac4sk7SEWzu8NC740uopiqqDJqEqbCMzN7kZ6S9rdoWcH6a1yaaAqnJQVPw96bLaE/7E0gJ7Fy9xcOEhVIUBwh2EsvC8+8JZri4v0l/boJy5/bHNcqYxZvNIvbVyr5sfPUePWL+UD195mYvdhtB3nO5GdgbKxu4B7zrleHSww+6u52NPPcjCC4GxJnwWFnqHNe/ffpZPffApkrgTHn0SvJvW5US5uQUiLSiabbfp8CEejHivwDsG21x75RV2zpxhODzg1OoK68v9mWcoD116iIkEpfD8yy9wd+vO/IMzmcHUlejNO9rcaxp8m8Mp4AiQAhBzU0ecNZRzFJn4iixMHruee7TFvdaQe02QLN0evaRlc4v5YtXE1q3bXH3pGvt1wwOPXeId73lkBl7MP8qhNHtDvvTMy2wcDuhqYExg7+wKy0+9l8sI3ZC4O6pJoYduN1w4f25i4fAC3SJbp4yzy8ZQUkJIXDy3zvpq35SLQWlGQmgs7+cDp9d49+MG9EIdGDXKp5+5yXAc2RkHDr52ha+/dJt3bJxi5d2ncEWk7GXuOgHEQG1LsoBm0o46EvfiZNi7FgXopBknLSBwZE24R5HZ6Xi8Z+XIByUDIG+OiPPPhWllmACQOUXE7NyfGQIhxKlCSMF942XKoqR+/GEm6h2dBfk6d4+jg0BT4s7OLqvLi/R6ndwW86uwilB4Sxt0ZPlEJBGj5FxpUEdl3Nh+10bfplylKXTMFq5CWKgslr19ogM2KqFXtuk3eNvKdzygKsThvSPkWBcvRkU6JlHiiAhDsktZRRasjd2m9EKhJgwaE44J6AhoUjquopGAdxCd0E0laEKc0tOCKJFGa3AOr44Co50uxePLHFeF0BHJgrlQOM842jOaFFGEEAP72zssrZ0mFrbwNkRK8VTiGYwPKTAa0Z29Tfb3dqjWNnjumc/S6a+wvLrBAw89TtUtuHNnG99ZQjod6hTwKRK9R0pPGEek4xmnQEWPbqfHYLSJ73YoqpKkSqcqSFHYPtxnfzAEYP/mi1x59iv4hT77MeJ9xcGtWxysrbO9eYtzZy7w2Pu+x1wZUQqEYYoUWL4myWx+pXhqEo1GChXzCgqRIeY6WalRhuA8tWDsO4BIAPUQjeI+YJYbn7zFbgmWiDlv8BWAJGpsuonAIAW63qMEIy7RYkKkFFDQRBqNCQh1ChQODnO+J83JfnvJxopRubvstqfmVpc10qVzRCeQBBcs3im5iCPhnbekuTm/QoW5ANrCmf3hvVmFSgeoN7J0tXitQqCDZ2c4wIvSXfBQmF98cpbvql186qiIF7xTvDrqnGS4dhYQndrAdExZB+amOEoWV1VlDVDKq5NLZvWrSUbtDxiNvOn1ThIPvy3LGy3Gb0Yl+U2pxlRTNx+2LKz3OxxsNmyOBly8dConyTzy/CPStVfHAy7R397ks3QYEpHS8XAxpnPxPbjP/y7hT5asP1AwulwjD66x023w5x+0TTi7hyRMITRXJrKHIs5RdrpojKQ65u1QaWJD6vbQqiI88Bg8eWDxh2DWtqrg/nfeT6/0RngyIzy4rNmf1YCeCC5OeP22BeZrPM3lctKVk0+ajFhn8ovl1zs12GP9fffB/iZ/4Xs8n/61Qw4GA7orPao7tzg17HBxsWQQIs6b8ggRnPMMF5c4OWfbSZYrKIoS5/x8nWf8kCZCj86/o7VfFkdS4rOf+zx/Moy4P8BHfvV/5X/72J9hsH6Gfq8H9GdaQCyecvIoZWGhz1KdHQVnBlprQDQXd6NFPhzsM3HNOfEt7/39214lM4emshitFludWncoISdBz7FT2ZXuJKz0JnQwb6ViGSy0z2USW3zt+nW+8bWX2Ns+4Mmn3sX9j1zMz595l4mgLuhoxLWvfIUwOCB2Kp6+tcO7Fj1PvOdh1v/Sx3l6P+KDY3E4ZOef/gr+cES/vzCJI3YC3dLWFOdy9E/2ykOU+86ss1C5nH9KGR02bL52B5cM4q1/8GF6q4vmHdQE7vvoExzsDnjphSucW+tx9/YBC4M9CjXXZqnbpCzkNczmRYrmkiaAREt70r6y6Iw2ou0IbcM/jvTxHNPEzAqkR/pQp21qAC+jgvzeczNGjs8gbQ+qTgHi3DUzz54BVi2YEiz8Ynd1mTIJC3k0aAu8NeW4JbNMT6nlZ14AoQmBX/nSN/je9z3OpV5nBtRNz5WZ+kx+UdMrlOIpe35yy5iUMENk1MaNNcHYBNu8VQpohPEoMWiVOZgho59MlnfFrGXvm1++4wFVWViAv7jCZiVqcUvq8c5RZTWdJXk1y1TjDOGGZCQJQYy2W9RY1Qo8iciYmDWyNg2cNJgDnlGoOwKC5SAy+4ejK0YkME6ABops+VJiDv60AUACFQ+pZn93i/7qCkVlAnHhLMDVaMOTsdh5z+7uJtdf+QZd5zjc36Hra648/2We+K4/Tm95iZhqwv6YtLzMQlFQNzV1SCwuLoBzhDgwkFYVDOOYyhfEssI4EoWhJioNLHV7HKbIzt4W3mHxUMNDdm5chpCMOVATYbyNpi5Vt89eHFMqBiAUvLPkb5JJEFRglBqkcJTJxO8oJmhUIkRprR2WgcqYYYRKHE3KeaWyi59hMQNnkQBqtOdRDBy1yZVz9huzOIrgFGqFUj2NSziFkSiFCDEqIYxzAltwyWWGv4Ti6La5PpIgmfDCck05VAxQOzEKdZdAnOIL7MUlAz8chWhm7ytovD2bvOmKt3csEdS7nNfBGqOHJ0oiaGQwGhBlTE/OELG21gzsJHrLveWNsCOo0fKDECSRRKnEISnQwVEnJZpBF0XoICRxE+ugihFRRDWCFQvkxQSElPsXyRS637lFT/h04rJ9lEXhdU++17OmGsfpVmi3eHi5z9W7A+6MByytdGiFMTttfkNVtbG14DyPu8S1nV2+6rqIJIoEj6zAh27fpvrnL7P/1CpLj1SkU+uw1WXrf9/k1c5FOkuLhBTxvT7NeEQdI+UR3/n29aSNO2AGHmRhQ0WMjSsq45jA+RynaG/nxFPbgoFM7mf/Ly6cwntjp2NGzpnUQo7WxCqhmcwnaZg2i2vvDuJK2vxU891j94jNXTTuz8nJThNlijjvcH2hWih5R7jLy8Mt6DzG3rDG1Y3VLESE0PowIOIYdbst8ekUQEnb58q8WCX0F89SVQsnjh9t+3wyTqZAdGIxVmHz5i2uvXqNYiFSaKI5HDIaRzptDWbxz7RBJ18vXbjIpfP3zT9bps8wuUvY3Nni+Ze+YaM1a7xnZ8vJAOHe4Ovbr0xRbRtcPypLttcWJ+NWBUK3Q/ADqnS8NWbuxHSkTo8dW1uOS91HvuoJjd5Sp8P+7j5XXrzMlcu3+cif+AiX7j87ndsyvUtL5LBzZ4fnP/MV1ta7LJWey69c51TpoeqiCwv0gNNOcKo0o8TBKzdZ7JfmEi9QeguPCCG7fM0QYijZOiNT9ztN0ITA8OomHQXx5nWU8honTljoFkjo0F8oWF/qkA5M5UodIJq7v8UgW0M4Z5aM0bimDuEEjYzJDG26E2gBVjtX8rPnMM3MOJ6df9j6NunPfNh7z/qldeKwYbQ7nO+i15sOOn+CoDNMovM30AmwssHXKUvEeXYevMheVBbU3jMvlgxjQFAKb2zPZacg1uGIogCubu7x//30s1zZCfxf//xHLQHzSdqAo19bkJdlb++cuXs6oSqmbd3eKsXEQjUJf5sA4XY/bOwgglAn2BklCq8Tt/S3o3zHAyrvXCYzSDYJnCPiqMS0+pY8NuJdgQalkoKE0nFkmm+zCBR5pCcw7byYq1U7hwpniVMbCXTEkRKUvsCh9PLEE8204ZJYEEG8J6CoM2uZ4nImdYdIYhwb9va2WV4+RblQ5DgkpSHRzWxAdWxoYkO9vUfV6fLYo0/yzO5v4kdb7Ny5hoQuFy7eR79bcbh9g/rgkO7qBRu0MdJfWMQVnhQD/bIgNIGy7AKBQhxaViSUxqsxJIoHCrpVlzgeEOsDRvUiH/3+P8Xu7pg7116gqQf0Cs/+9k1OveP7uO8d76RyjkGKJqxnwCgKFr4kaFBwMEoGfgtnvtuFK4mYf7RZnFLWDKvFQMVAk6biRpFzqAQs31SRChqBOkGFkYOImh9xXRobUZOi5eNJCZ9jo0qxChRq/uNehI4melFoChMEk0SLl3JuGrDqUo6tMm28IMb6RyY2ARqBKk616Qr01NlmqnnDcJbM1FOQMuufqoGdmkiRDOTWEgxsIZmRyLFz+zrBN5y7+JhlEnc5YZcK4m3RcfnhBVZPMmOSk4YYjVVwJCYElwrBYS6zecx7tbaL4hGn9lkNtI2TWqJgn/DOQGf5HRNDdbLYN1dOkEPfsLQnv+6tZ+42IwcpZqX5rsUeL1zb5Q6R5eXO/PnSCrY6wTGC43RRcl8a8vxBza2yb0qnZL7o777yAhtXrzIoEjzloX+K288vcH5Uslmd5YV3vgPLVq+Euplrnzl7Sq6oaELT0BRMWf6YAAcB9YmxJsYaKZcXICZctBhC7wWkTf57NI1pYe4Fk2j4aUPOwdu59lVal7QJAGvdErOpQFwBk+8z92kFCPFzgli+hVkVnKKlBymoUkOnHiOVI1UROYgIkTAa8+CjJWvvCzz3ck0RzbVZpn5yR8bQ8dEk2bI1laPa956hDJZ5YKk6zZVFgtcuX+PG5ib/94Fy/3hIsbCMX+hNEavMgPITBrUcPSefNtHMq7J3sMf27hatVaxtq4kQdezNpsdPts19+xcFXj21zJ3SlFoCxKDcXepTjRsevbPPGzbQzL3mylFgda+F5djhVogGDZEvfvrz3N055Af//MdZXlvKSelnHpEBuyDs3t7m4OUrdMs+d0YDgi/4s+9/CCUxPr2M/LmPIl3P9X3Hu/sNN27e5cubd4ml4wNZcF7olGiM7IdocdOma6C13Cx226Q27TEDAxICpSgL79ggFYHNK9dxKuzfHaERYkzUBw07bsDu4Qjf6bLR62RXaDejrhAWV7q40rO1ecDB/qE9SZjOqPZPBlGTpm6Fwbm1x9Cg6kza70xs0S5HE287na5rTqDTr2gERrvD4915Qj8eGyKCPecoZp6tf/veInSqimqhx1rdcGvYoKGZPDGhjKKRXkkIeEmUjYVCLLZ05blPYgwcjhu2d3Zxcw+Xe1R0tm5muNgcJVY7zpL1tkQg01NAwXnB+/LY/VRapm1FW0K3PEYLL9RNw9tVvuMBFZpJHlIJGUA5SYyx/ASVmNXC4WkKE2KDmhtU64pV4ZAcb9WgNClaUrkkJElG3BBtE9Nsvo9eEOfxKaEuTyoU9dCopygdpTjKlBDnQcz9LWFCs1PY299mYWGFqlMYWYFaYtlGlaDG/OZDYHjnLq7ocu7CRcbjfXpLq2ycOcUDj7yH1XMPs3H6NEJiZ/MG+/WIJV9wUI/odjs0o4Ex5CUoehVhlHBi9Ysh4bynWxW4BJQOdQ6RQKfyxOEBve4K1PsUXjh19izr9z+IL7q48V2uPPsFFs+eo1+Z2Xc5ucz7Zq5iXhyNBkR81hKVLJgN2vIqiceLUFDQSMJHR6UABbUmfAE+KZWqxfgkY+jz4ildwiUFb6QUVZkDMb2D7C5pfSuIy4ksxeNEcd4bEFGbnHhw9Rgv5nroJFM9U+BzwGQgGoEZDidG4lAlZxpugaiRRnVKpJH8hFyjI9760wm1h0o9mgFTkGiW0xaQqV3vxRL2ls5AdhClysyJu1dfhBLk/WJMkGDEFTm3VYklnHaqlEAQwXmQpET1pBxHGGRqPQwkKjW3lGg1J3lz9XNOSDk5n89uiikpqiaMxuwu+51TpmLeXGk3xhmh5C3LgbOBLXO3ndfOTf+aZeNC1eGrV7fZLoSlXjVXVclC/9QqoUjyPFEokPjSKFEt9eiOlcHYQMW7FpV3Xd4n7df4f/9huN8xHCZWqgH+Xz7PvjxMkhz064QkloAzS9LzTTV5EUUk53VrsVZWPLYic1JlOBiZlaZ0+Mrx0PoiG7FhdecmUYW6t4AsLiJka2gcWyqD1mdq0jJMQdRRaT/XR1MDGlu5LMdqWpsl9Ufu2boGZcdeDfPMimruWs4JEEhFXlNCTW9ngHaV3ihxbm+fhKMejthYKrj/nYlqb0BTx5nYqak16l4zR7D8gzE20/PmMffMyYL4nOBcZEJGoqKkNKRPzXBcMFhwLHd6VL4i5eD1Y0N4rj1l5t+Zdm+P5S9bW1vcuXP7+Escx93Hfp5/0rd3mYwkVRon7Dtn8bcIcRTQJiErXYZFcWzc3uv95zDTLPI9OiDmTr73MY8SQuQ3PvlZlh88y8MbK6ydWmVqcplqf7Lqge2bd7lx7SajrS1e3RnxQ3/2e7h/qWTn174K4nHnL3CnWqCioowHjEcjws6ITnKoK7hwapmlxS7GAWXjLiWlzbbhhAmV/3R9yX8TkKLFJntwLiJhbLJfM0brRHNYsxojhzd3+d0rW3RGynvPrpr3RgvytQUZAklZWVlkcXlhsqQJrSIqz0udaWayciYmYghGYpF0Qsc+SxQx526rauyCmQPd5xAEEWFw94DU6ExLt/01A0pm95zZNplWLB+V4/PsCLASJxTes1RG9mswIoBpf2ve51GLMW+CKaL7s09VuHpzC0JgNB5QNyM6vg8ydWa0f2dXieP7XZNameEe+6hM3upYaY8lgW5hXl2t26IINM3bJ4t8xwMqV3gKn3MzqVkP1BnDnKQaRCwXE5akFRG6FHQk006KCUdNCjZkncXpJFHwFjdSqkm6FWVm9VNiTBMShUIdTrLFIQlNakjOk1yBaMrsaIlCPbWaEH2wt01V9PDdLqKYW4pzaHJUzgZLSg1XbrzGwsIyS2urljhWPIurG6ydv0Sv22W5v0JvocdguMV495BBbcnuFqsK7529UwwUpWl4lztKoKHjFxg0A/COoiyhqUlRcVXHhA0X0Rg58+DjLCxFhjevcf+7vovoSvYOD5DqQUavXuZMf40kDkeidkKlDucw0oIMSkUw4V5zfipvVp1SspbBeUQ9uJznSw10eAF1BlQKB2W0hM1F9tlXL7ik9L3SSMzuc67NYAXiaZKB4EosX20tiS6KS8rIefpxSLcOHFIZYYZYLi3NTIzd5oBB0TGBJVudgmYQ5DJVvpr9yEua5I8Q1JLgtiQPOKPpR7MboVI4R8om9yC2s5Tq0WT9Fkj2vjl/ltPEqBly5+oLFIUn1Acs9JaRZDFZzpuro2S3wyBqygYHEFEpLLAzJirnLBOgV2Im84hlJEUQPB3xRgIiiVEKODyVt0TJHosNrDVlynmhJW/89ixvpB7OucAcOTfIhMPuiEwkzOxrrwMxp5vMifLPjBDvnePx9SVeeeEGuwsdepWfedRxgVxRSl/wxHKXa9duc7O7wPL6MptbQ8tBg7BSeT709G9QXb9C/Lc/Qr28y2B7jwc+epZyAeq7G1z/zCqWttHe2/mOjZfsvgYT5fWkDhbofRThmABjVhOzPNcHA+qt26xduo/7Ty/x13/wER7cu4v/X/8VzeY+v1Cc4dXH30V21KGp72AkczkCZGaPnhPIj1hJRY6eAdOIqPlz9egxmcqX0/5QygB6X5+Sa6gUpLqmHO3y6pe/wal/JMTtu9y5tsvw6++g3jkgjXsoia6Aj4Fi4ublpq/RWhU5WpSD/VscHmSxdub9dPKP1dX7ilNnH8oJ2nUS0B1D5Ma1yzxRen5oocP3PXyeSxun+Htf+DS/VVVc+FP/5kx/zdxw9gFy8jidGqgkuxVPzzrSE99R6pZ7FVHN6Sba762C0RKzD/eGuCSUXW/KuaxcmVgb5ejcmW3ReWQ/B2pnTzza0G0/tjK6KPVoxLPPvoQsdnnfR99DVzw7O0Nmk7S2qgWnsL8/4MqXn2Wsns39hh//iR/i7KVT7L9wxci9BMpH72NpUdgfJLpeYDjmhSs3ecepZW41YzY2eiz2u9Qj2/vWNvrEmLh1cxfnhDP3reO9xSgfbg8RTVS9kqJw7N/dJe4NKPGI5LjjZMzHmiIpGfECTSTGxLgOjOuaejCCUUCbyNzobJu5xW4i+E5BtWxuxVNdgsw1ewKISr09JtYhgxzNxF7TfptEvWYAloIlJBYB7x1Vr4vzjlAHc6mbHUOTO8x35sn0IEdGgc59s/vMXBaiMqxrUoosZlxpVmSTL9a7JTp72zxmXAaIiLK7f8j46Wf4iyuOhb0tPvnrX+CHf+BjR55/rCLTGuX5EU5wd509/eivc2+bseS+T/TUHXvPt1M18x0PqIpeRa/XndAnepxRg6tS7w6pqj7d7gJRTGgcqgkplXpqbSzPEOC1NMuUWJB+VJctHB5BaDQSJOHEEcSEVonWkQ2JRsFyByUEE35Daux+CpKEJBGScDDYQ8XT6S+QxLJbB2yQTTKoa+TK1dfodXosLPYJIoyTWeCCCL7os7SwjPhEWXnGt3ehrEjpkE5ZERRIkZgiop5O6RmMhpSug69K6mTvEpuGpBW+6KDjEcRkiY2ToqFhsV/RhBEL5x/n+pVXWV1eZ23jHON6RD0c4fs9QmqyXUqpk1JhNN5JTYBJqsZomCIqiSKZBUXUmPAkJXx2U0nJWPPEGTOiYpTzHRzJQ1E4i2HKoEScWRF98niEhpQZ7pSUMpNQvp8mi2PqjA9ZiYfc6p5lfzTk4PCAzupp7quMiOKBsMmVYp3kEqOdm+jaBVRKkksTbY8TUDEqFKceyZm0lEBHQSVNspsnMfe5cV6UOjlmbJRJSQrMX1snm6XlZfAKwQcTvUSpI9y58jyHmzcIouzevEz3/ifwPrdHZh5Ul3OK5DY2N0ulIFGAsSJqovDGQpgwrb1PFsc1igEym5/m+ZEI1MlR5GfEZPmvUjJhwae3bxF7u4ve60OrKRTH973vfh68sMKoUX7lcy9xa3cwJQS41z2PKudmhK35S6fEE+3OoFiy1Qudgueu3ma81KVTuPnNkpmtQ4SkiQ7CY2sLPHvtLsP+Mv1+l8PBONPtWiqBdwx2uP/ObZoffAK5ADdfu8LFP/Ygvlrnzt/8HPvPKdcfemKmpuaWIQKFLxGZuorMioCtECAT0gXNyuBEGI0p3QpNEwj7u+w+9yxVGLGjD/G3/8nX+OntV3nf3V1CwmJTXdYWzyGHqaByrBGFqWveBAjNiCfThsp1nRdcZ9+VqYh7BDCaFBJXexS9fdLYIZpYHQQuiCM9f40zjy3Tp8vtv/+PCeNEatYRSXg17VyvDvhqEXJ8pmggpfH0JWaFESW7PxtYPGotm315JwkRl90Dc0+kxDjW3L19kwul5x/HEQ8n5WFg7bUX2Fo5Qx3TCS1xZGAfaefZLxYDMytMHilvZVl4vQn1bVCcc3OEHj5rYJLmdkpm2U/JFF3dlYJUB+qRsrDWyyk8TpJC858Z9KStK57MAyBmx/rM3/baF595jZeefo2Du7v8yM/8efpLPW4+e9OUnvmkwhtBQ4qJ/adfZhdLBCxO+ON/7iOcPX/KXOcTuKIAcRSrnnI44u7uEt2u49prmxxsDdCgNDk2x2XLlCIsLHYtncfNbbzzrJ9epuya0lfCFhoji2s9fFWys7vHMzdvQdTJe4ZRjYbEzRu73L09IiQjkEkFvPtf/2OsPXSeYm2VcHsbHTQ2f2WmLYGY51bbOM3B2Nz4Xau8mFeQIaAJRsOGkAHVdE0/urZbPUVkBifbh9VTK5TdksPNPcJof6arZjlLZ5QZEx3SUYXSGysqpO1/YDwOHNbJck+6NoQgj6f81xyI2sXHnm1sfCZDhahUIXKmcnRJHBy0+2DbSvOryRQaZgtbPrdp17WZut7rXWaH82xrB6czGrLZ57995TseUHUKY9TrICAFjSgLWhBSYj8GnAZ85TNVtVApaIZfvo21irYpeF/gcHiJjGfQuVMo8agYu1sXgYLMlucRkuWmihYTIx5Ssp6eWCEcFAqHwx1Q6C0tUmtNaXxppqkS20DHYczWjdv0V1ZIKVBrQ0861BrxUrBQdimrCpXAYrdPGB9SHwxxVYWTIaHw+AiaIsNmRH9hjSZGYmyM5l27hDCmW5Q0o+GEllxLz6geUxUlRROQJpFEqEdjOtUCqxceYjDYIR1uWxxGVMreAiRH0jAJBgzRrH1mOTH3ykBDypt+RKlTxHQzkQKyg6ZAcqhLuGicNAWOoNAA6hVSxKsl4tWcP6nIFpKQMokFZkEpvenYSQ6NlhunI8JgNGJ3d4vq0hn27t7i4PZN3r2+yv39hmdS5Bu377B83zqNKi+99hIX+2dwvQ5elZjMshRznIemzOYoDYWa9cA7nxMNGnmGVxgTzMqhZDZJlxMnK01SCueNJl0VSZYLK4lAMqr5IEqoB7z4+d/ExwHjJvHi5z7N+rkHkU7flmIxIS0ls/y1pEUlikRHo2pEIM5isUIMjJ3SxTYKh1DHSEpGo+LyamU5vSyXhSUZjJQCLnkCgeQgylT3/+1YThKv2x+6Tc3Ka1c4v+GgW7Hcrbi9Mzjh2rwJTST62TOOfpp9xFRSzriHsizYGI64cueAsLSE9ye7P0y2K4WF7gIXxPGNqzuMOws4J3Q6JVvbAyOIAR5OB/yxl7+K+553cmNF+fJXn+fP/Nh9vPzlMWcuXaD7OfjKwLP3qAnmkl3CnCiIo1NVcMRHvX1Vs1ZGfNkDDTaoAI2B0eEuf+TH/ir/j//9l/jKr36atL/Hnae/RhyNuVFUVHdf47HxIVWvx+ZjFy39RXvzuXbO/6rONfFkUz9y8CS97tH7zjemXbzoahbKOBU11PYPCZ7DqgtqCde5vc3CRfjof/ZOuPQgRdexduUm46cPiM/t4n0EHSNNxEdlRSLvPdvl6S1zK04BJNVMHYZmFONz7z4DW4/+CKQU2Nm6ngmUTBKKMfDlLz3D4M4WH19ZYaAjNqqKWML9Cxv0T9/HuB6ze7Cfu0qnSp0JUJpvrtl5IhnEqirjejQH7ufFyjcp5nx74ynWHlplabGfBWlTaC00sDWRuzOUz11YbXRJ+zUpBZbPL2XCBSZAaa6PZ4AAc3FO0/5ux6/MrkEzd3n5a5fZvbnDeBg49/A5tG4gdZlYZbIlvlt4vCqj4Yjnbt/h1JllNseBD777ft71yDn8aIzWns2nL7PfKVi47yzjxXX2xp7lcsDt4Zibv/kMtz5/mR/++ON84I8+zmKvg4jQX++hislkMXHhgdOIOFJINOMGV3gjsGgVSzHS1DXOJU73erz69A26V7cZ7g8gwo2tIZv7zdTluef5vo99gPWzG6hC0e+ipZuZXVYsiridbwaeJAswbdu3ZGTTOWHXLix3SdHaPE1crXU6NVXNnBWnBDt2PwOt491D4sBDiJTdYvKMUAc0tcogq4cvClxV2TkpkRojBCOlGaD1OiWf43NS9aJToZLTwMREHDXmvk92QGgvyq+UMlmVJii8MlbH/+tlYXuvpOMi3zdqEyK3FZE5z4VWeSUtMsQUw5f3B4yawPtPLb0hqmqx6CyYUlXLIXbUbfH12uKbUL7jAZXTrAVylVk6MIpoIRGdor4ghExZDYgmghpKbwd7IOJEqSjQZIlmS5LFnoij0Zg3ZzMcO/Xme+4dMUHhPJqUbuks15Uz4TaoMspWrqiBwWhMCMra8orlt3LmCjeESeLVcTPg6q07nD13no4odQgU6ukWHUYYnXbhhK43QNjpddjavIU42D/cp6oqNDYkX5CanGmicITBECm6jEJND480Y5x4E5azDcL7kno8pBFh2BzgvFDHmlE9ZmNxnY4r8csbNON9tndvMkxK0enhUkNEaCIkIj3niWJU9ZogukhMgs9uIbb2m7UNzAUwRUuQ7DQaAErm8tZowouARGgSAaUQc0Ui5hgLtUlaerNKqRjZhCUH9gQiRWHWlADcefWrnB/eprj0CFsvfoGNnau8913n+czv/ibv+tgSn33+swxXz9AH/Dd+h+HaOZYfeZcxk0l2S8SC+4WcLBiyH3ZBVOYsj0NNdKQdPQa6NNk9WuCTJNFgQpYXR3LJNjiUBockJextMn7pC6zpIRtlIr76Berhn6OoehS0WjelidY+BUYuEfNi5rAEw0ETjdi9F5JlkaolkpKlHHACqp4qv0fX26YdUVQzUYeS+8JcMJN8W/v8WZnZnWYh0F4q+dqVfZ449Rq1X+DOjV1j6ITswjClkJ5cfWRlPxFI6dHfbUPoL/RY3R9w/fCQuLw0ATX3up93juXg6O0Mec4lqApMbeS4c3c/b5iKE+X89jX6Tz7CzZUhP/+lV3j/UwuIBlRqNA0o1LHfW8iEEpqFN8kKJ0cIIdM+5yab0ZrbGhkZDnepijJr3EGjxWpu3H8fL7x4mb06gvfEpuHus8+AKD/fjKmc50//8Mc4f+H8bNpZJhLmRCqawMjpbgtUztZx04Fbe44p8nlGBsPcLbIkIBwJ7FY+tHaTD52+hWRaZ7DcKb/0yqM0HpBEKiL+pa9TPBopFwrSmRKpRxRnSqqnVqFTUWuD7gyoWGCQhDWgHGzxlWHOL5fraVU5GcCc3OszRSzea3Bwl9mxV4+HfOPzv8bpcMAfOX2Kbdejf7qPXxae2FngsaV1rt64ys6muSRZU7TE2m/wzCPHWxAxf+StlePw99urdJZ79BZ7tOMqoZS7Icdfk7s5C+kCWhVIFcFZYnRpG/E4jjpSEqNx4uXdEcMgnOk6Lq118/l5PE9RGQq8+pXLXP7Sa9y9c4eLD5/nIz/yYVMIqMXsFs5Yar1zdIuCL33haQ5eu0OShs+9NuLf/g9/hIvnVnMOJ5OcuqfXqTceYOkHvosrh7A9aLjkaz6/E7ny/BbX7mxSVJ6NtWWa2hJDV51yAgYT0Fvq2ecYbU8VncTsgqJNJIwaLvS7nC06/L+//BqbKbGfBNSS0aQIZSn8lb/wCe4/d4pSoNk/pOxUlkynzdGnisYW/uiUNCcL+jIBFPcqU68Al9lCJwQzohMFEirZxa9dhfLVYiCtGY7Muu0E54yGvB0TrZtyy87unOTQDVCXY5xDNC3nZKRNy6zlfVbBIQhlr8Qt2TjRcUOMkWETctqUI3CkBeMu7wPe7rPc69JdWebm7RGFg/e8+1FWLpzKKXAst0qKCY2JZjRGJ406XbPrRhmJIivGeOrusdrNlrmwYzH69+CMtbv1tpwqv94+WPUdD6hQy0XVaD0RcING9gd3eOnFL7O0fJ4nH30/CjSKJQTLWgBjUctdqo6RWI4dJ2ZFcGqBk2YanSbCqyXbuNRoH2MKNmAT1CKgQqNQiKcjEBTqOjCuG9ZX13LslcOTcGLOYqhQD/cZbO7w8PlLFKVn/+CQquogIaLiLTGwExbXTlFVBQuLfVKoqQ92ObPYsHk7MMYj2Y8xNA1lp0OTIqOmZmVhmaHWhBipXUGhCXGOUX1omgscZdUhxobRYJfxaI968zJSj7h95euICpV4Uqq5dv0lqIdUVYcGAzXWJkIdapL3GGec5SdRgSI5mgykXHI4sfxO0jh8glg0JPVoiEY7rkaTHrIJuhI1NrmkqAvE6FGvFF5yArnE2ALS6ORYgqgR49zyQEJ0zNrmK/xb95X8mo5Zd8JjSxWD61/jlVe+zuPnT/NvdLb4nZ3rdFdP80RPuTveN1eOvCC2gk8lBYi560yS4GJJnwvnUCIxQUegFCOU0Aygohi9Z8jjzWkG7s4SEZcYnb/LgpZD6PiKTulYLSoG9ZhOtzDyk0Iooy2aUa2NokuoWI4HzeMUhbFqZleEwnvTspFImhMeiqeTY8gKZyQt1m4QsBg+pxY35TRS4u3aP7gZ/7aUk5VkeYvxSrlcUHz3JUa9h2he+U0YhTkBuL3uzbTDSeKqCVzCmeU+g5vbvBpr3NIizp1smWrr573jfFC2m8BNlxBvfeHE1rrDxqCVauKBZp8PLXX4Sh1Z/tD7Wers8EM/mKgWEo9/d8nw6ue5fHmTuw+voZlspS1OE01oEBJdh4GTGQnaZqj9m1JEyUH35KB8BzjPuOySzt8P9RgGh3D7Nm48ot+rWOj16Pb7OD9ltZvhzqIQ+O71G6x3Rry6v8TX9zbyT4mOhz//0POsdQaT/DoxFvzTa49ybdA7oQ1bBxpbs+ySaSB54QPdsm7FXyChzlFJtN29qHGhQc8lkreYTG0c0uTY2o4iDxZUdYLhgKLoErrLvHL5Bt3DAO95Ly1vvLyOAHCiqHFULd0qAbLKuig7CMr27TvEUeD+qmCp8qz2u2ysLRMESrfPe+qGp7XJyp0WVOqxQSzHH3S8NeXNjf2T3u/t1ir/QZXLQXn3rPIj6cTyl8XvFr9bjHRmvmvzeB1twXupUVTh+Wv7/L1feRUVz7vv6/Mf/MBDRgc+ucvUNnCwc8izv/11NAgf/JMf5sEnLpjSLJ9dlZ7VxZKFzFH9v/3ib7OyP2bsYfvMGv/un/zXOH12dT6GL4FUXTi7wQjhtb3IA+WQg6iUW9d59elXWHJFJkvSHPcwW7PWAtS617aKAJ2cQVKuvnyV5z77VTpFwdpih7NLHbZ3BoTGEqTkZqYZKf/Hv/wi/8Gffoq7X/oG3ZVF7v/ud+F6XVJMlqYmJA53ds3sMqPLOKnMrmyzXpgpJWKa9sO88kwn17Z9NwVV87MomCMdosK17X0WugUrC92ZCuQQiCaiaZjvYSRQFust4B3i59fpFrbIhHVQ2yuRosj1znHc+T1ag7Kbu4cVL/N71OGo4eb2CDBSH9ft0D+zhBTZJTlBrFMe10fWkrxfHg4bepvbdFY7pIEydVLmzS0IeZ1K2QOpTb/xByGEfMcDqhgDJCMxCBKJMeIksrN1k62Xnqazug8PP476BQpntNrOZ7/+LPArxjpSqKORRIHQJGhVFkYlmojJhORSLRanxjSDiJCwuJiUc1tJEsgWllTXyGDIxuqGAZ0cvBqTbeIex97BXUb7I86eP2+sdFEnwb7JQSMNSWERz+LZM0iM9KqKvf071KPEYPU82htTDpMxWyUTyCUVEGoKcaQYcFLShESnqDiIkX5RUqtSRocvPQc6onKOva1tFqpTLJ19CH94jc7GA8RODxVHMx7S29uk0x3iCoeqqeBUzcJC9r9WiTin2dqk2XXMNB6NWqCo5N+SS8QIpZoLX1Ijc3BixwKWVNYhlMmsYeoCEiNNMvBkft3G2qjRKJqdd3hRUsi5mJKyQ49tv0inPmDncJevHezx7Cv/iqt7NZ/67U/zYx/9CFXhceMBNxcvUDeBbop0vLMEzQq4HJekbR4bh8uWnALrWxVH4ZSOeho1C5w4iESMOt/RUTEadpfoJdNal86AUSHmdmdZ04XB/jZ3BwOG2lDXgeWFSGzGLIiAV5qUEO8pxCjwoxjDZFLTgJbJIy6QoqNyNh5wjkatXkYcIMb0iOUFU4FaTblQiOZ4K4v1K5ylbi5SoCq/fS1Uk21edWZLtBV6MA6Wr06Ndj82I2LI8Xs6I0j+Hhb0dqNuY2QuXThFeOEyd0ZjOmvLx0gWju4zKwLLTeJqCNRuGgMhQL9T8p5HV/j0F3eIQekT+Z7hdX5DCr64tM6fKwcUZYdxvUcar7H13C4r5xf5X/fvcK3zDlbFTUQd274iEx1g1qRPNaDzLyXO6MZdhigpRfCQfE5wXhYWA1IUiHdU9Zg/9a99P6v9LlU53bImQKPVlqI8sbrJA/09kjIFVIAjcbp7wEpnNLkgaUnH60SQnbWAlKI8tLiTKXtnu09BlLXuEJE0A+hsTHinJIfNgTJruZOgxRJx8X2w83mc2zer9XkHsUMKEWGElDA+2Od6apVzGaxNBtCbLHr8iynZlarqcd+lR/FeuPmrn6OslZWFDl2XWFgrcQ8W3PrNK7z4/A3Olac59cCDfPnGmFEyZsDZqsi9xvOxjn9j29LJ0OD1z/l2K7dqeBIL8CfP6VnXvNbSLAjR5RQrmAW4LXM6mpMaRAERqqJgcWmZaqlP4ZpWip+X7xHGhyP+5d//FMtnVtl4YIOH3nPJ+jWm6bgXwTvHcBz4nd99hmUv7FcFL91/gXf96+9ibXkFp5oFb6tUvbdPvHKT6mOPsTsO7IwjF2XMK0Pl7PY+UiceX4ssxTGHu4eQUo63GtHS8GsGJ4JY2gSgaSL1uMGJeZvcfPU6d559hUc2Vjj3wCl+9t98is3nrnP3uRuMYmD/cMzWrT2uDGu21VIVFB1HHFdoSDhf4HwGtj7hC4c2M5y0c2tM23jTNAQzlCETZUuMcXoJtu56b2p3Iy1K077U2ftgmkzEUkbktCvROVzpKCpTxO8P49TKEhUJBlb63tMpsi+K9yw/fIai3zGlaNOYzIVO1gKSTgxnsQloNIr1CUPHLIoRsxTNulJbCIq9eXvP167fYWd/j6yG5TNffIXve/9DlJURhiyeWmJhrT9BadP1ZDoqC1UQZ+RZYve1vfRE9dH813yKydv5VTJWn7AZvo0ryXc8oErAgIiKbW5V9nvdCzX7RRcdBx6vlU5h1phx1ggW6okxTRL7Ws4SG/1RhcJ5S6ibtaQRu38ZS8YS86IpjHGUeVMVtWMxKQ1K1wnjccPB4ZC1lTUz2SZz8yODKkTY3LtLGI04ffYs0ZkrWGjGxlkdhdJ3CTFy5/JV2DjFypLQ7S3ShCHj3Vvs7mzi18+zvrLGHXYJoaFGKF2XlIbU45qy2yPEQOGENFZiRyhGkbosiMA4BBa8I6YI3S7D/W06S6v0V5eJaZe9Zki/qBiPBogvceUS3ZWEFgVjNe1xF2dEC8kINHpi8WMpa06TBgyKagaSkvNOOVKwXFCNpmy1SUYln6IFxJMFWhESgbEqPji6riCJubGZW5NF/jhvKsA2TsnisCJuNKTcvMr5911A3SbXmy3OdGo+O65Zc4oe7rFRNazs3+D8qRUO9q9wq9ujFONrckHBl0YyQqJOll28QhilROExggZVamfB6EMaPDkGIwmlU3tPBBcwDTdmxUKEoEogWF4tcWimb7979zZ7g0OiA6+enZ1tBjubLG5cygxCtrgXyU2ClhsijRPKpCDRCDoERBJaWKyfx4MoXsVSBGAaVCXh8wYTHBSpAmloAApPqZJz4Bghwrd30SPfbJOx2EPT+lOUiDYUreAp0ytntwI54djJT7FSeMdyt+LWK6+w5zzV2gqzUv6sArT9vLbYwV3d4pV+Cc4f20TqOvDK1W2W+h2WXOKxZz7La92CL65eRDVSVJFe3xP9Av0ysXb/AuNv1MQ6cTBq6NYN3Y757rduMfbOgm29WWiQk/Y7N3ckZktz4x3NcITUI4hKubzEwsY661VBd6FHUfo5IV7n7mngTAVTZmSFhPkSCIgpJQw85St0xo3qSMP3XM0P3/cy/XKcBbwWwOnM02bfYip4pSy8aoDmcjT3n1Me7l9FUyBVHo0AEXUJiRFSQ1MIEpJZ+XWqyZ5SIr9BeR3MlZ2Q8UVBWVYUAv07BzxZCN975hSrC8raJx7DPX6aOCw4d3OPC/cFytWarRf2eb6/PPegidVgrgcmkHpGxHzrwsvx1/h2h1JWYpoKka1MC1nAc0rVL9FGjY3VBVI7T441yL2Q1PRjBHynpOyUljdzZqEQIARl88Y2v/YLv4HvFLzvE+/lzENnEKAWh9MGn1rgBwcHQ26+eIPRzpjFhS5fOlTu+/h34btigmpbpfxyzZ1digunKFccd+oxj/QTO0NluB/58le2GY7HnO2WcO0Kt19cp1rs0l/pc7g3MGHaCXWTGIwTpXcs9itC3RAaA3r9xQrtekQtDrtc6tJ/z0N0z63T6VacuW+NUAf2tgccDiPvVyVGZefWLjeu3GTlwhke+J734rI/mwDqhMUza2j2FGnGY2JT229JqYdNlslmyG9mpoEiE+WXUbxbu5RlQXd5Ad+rqPeHjPayRWlmfwDAORbvO0VyMLy5ydJSDxyslomVboelXkm94Lj7/NZkReiVJRvrS4hAZ3WRTrdNmaH4bmlrV1JG+4empGlBde5bFEhKqAPhoDbwlTJLYqZzFxGKqsAXU0drVajrhqa2ICVR5XA45r//hc9yOBgjYkqxX/nCq/zFj9/i0uk1S40ToT6sJ/GV7SSwvcM+D0PMhgdPb1nQJlhsdrBwG9K00eccISZKA4udr2OOB2+Ve/lE7+Ydxr+Z5TseUGlIlNGC7Uv1JJSbN5/ntc/9Gp3BAcoht7/+OR764EdJarE9knMTSE5DknELglCoz4xYxoKnThH1+BQsTsQJnfwcJ45CHZoJKDTn9HECHRStA6PBkPW1VcQL4xDxGGNdkEiDsrd1B1Xl1JlzBEn4PJZCSBSupEkNrkxsbV5j+8oLPHh+nSI6lnoLDAabbN59jVdffInY69MrHRdXe+w1AV92Ca6xYPQo9H3BoEmkArRIdASGGuhKRfKOuqmJrkPlKgoVmtGQxe4iB3v71IcDvnHtRZZXz7LSXaa7vMLuaEhnbZ1SoYtYAuWsZZBCkWggVwRStFgerwI5fi2IZNYe+01VEG+fE0blTVRcATELJ2W2MJpDUcJJJCgoDtQysDsFL0pI2dUou0qKpMki5cMY10l0O8rja4s8mBJnTp8jlYkiCmvhGg91FtlYOMWLpy9R9yrqpAzCmLB7SLm8YcDXmSbJizJU00xqEBpybiwxa07CFgDnTGBsklA4cwd0zpn1QyGKMSwmIiWFMf95hTgm1IGrL36N5YUOjXqapkESXHvpWc5eegJXFDSughhpkqMozdI3SMZ6aDZUIwipxdq7SiUNivjMSEjEO49LZhmVHHArCAUJkWhB9A6qBOKaDB69sZh9p5UsFTnn6fUV3IiqqumUwkE4wrLXnj8ju7cuNW3w8OyJkw2z22Gt3+HmrVvs1dBd6MyIr/P3jjGy2HG86/wiL13b5/ZiZ96Kld2NFRiNG/buDHh80XP2ma/y/Kjk8rmHrfOInFlv+Mt/uk9HTlGE27gysfMbN3i5qfmlp1/m0fIU3/u+R/ImlWvkwPkSmBJOTF+cSTC8997cj7LFrx6PiYXna08/x2tf/Cpy7SqCY+ncGU5fuMBKVTAUWJxps6mu8TjQFVHOLx3yvRdu4NTWgZ4b03PhBFlUJn8mLjptD0iboHtWXatzl84zWMlEcSdtgvFtU6BIAJccuvEkSg2pga0X0ExCpCpsJyU0ytlBzTdefYX04AM58ejss18fXMzCGcOKOSZTjPCmbhLXb1zhFBUPS8E7Omu8s7dC2d3BjQZInegOhlw8tUQZRpTXr7Ecq0lgubSWiEn7n/Tk4zV6s2X+bOFoe387l1ZbPkuXMutC6Rc8PhUUhScRsjVDZodoLnq0ZezojGaljccBpSp1ThGREjz7uW/w6X/5BULR4wOfeJK1h87QklncRlgRx6KpiQkkXvjaC/g+1KMhzwzhwk/9WTQFS3UgR7pGoH71FvUpS81yReDRKvHyYWCx2ea7Bzf5+IdXOddXFnpGaV60gny7pySmuZycWaNSFsANA+RjOX9TsdGjc+kU4kvo9XAbUMRIVRRwMCIGSE3i9qt3uHt9i8ZXjHcGE2WKiOaEsLkhEwwOhoQmTPouKmhMGSydAIimr09ZehZPL+O7JURFD2t0HKYyP+C6Jd31ZQY3twGhf34F3ymIIbJ/2OCjkaU9/9oelzb6dDd6jPYSZ8pisveU/Q5rj5xhOKq5s7nNgxsXjg4GFKXZGrC/M2CGIuNYxYsZBsppImKb4+vvOE9npT+nBdx69TY7VzchM/L9i88+zfNXb1DgKdX4ibd2hP/5U1/jr/0bH8WXnjhoMnNo7sv/H3v/HaRZlp73gb9j7r2fTZ9ZvqurTbU34y0wmMFwAJBD0EIilxC5JIMSl7vc3VgjhWKdViEFVxuKDUpcBkVoBTLoRAIgCUeYwWAwwAzGt5v23WWzqjKz0n/+mnPOu3+c+32ZWd0gSC5HUk/siajKzM/ce+65557zmud9nmP3dBoRLKZMl2jm7lsAwFeewUYP74XuSjsyZNZ2OMT7UhyMUUl01EaJRjwsPLBGJ0niEyNxLOzwiDDq33b7vneonALnodB2BlsKWHQeON+aQyTQCR6hLrpUiuAk0nerWJ8T63Vi5KGss0YeTSoBFep6F+qHHI8YDQGMBEoCSY1rFe0wdTahdIFef8DCwnwktvCaTIGoqBDuXOBgd5tG2mRuZQFqSmrlo0NhvSNJMnwo2bj5Om/87pd55OH3004MttFCVKAc9xge7JBUExr926wurPL5T7+Pf/C7myhrEQIjl5M2kwj/MzZCIrUmwZLbFC/Q0hZvPCKBFCAE8smIhZVlrt94k6LyDA8HZEnGjY3brJ45Q393k4X50zjvwETol5cadhSERkgQUUxUwGhPKQqrwHiFMpZEIiRQalHfIJDWK3dQtRFf15oFCaTKUoWAV5GiPlZExWifr1XoBUPAU3rIDGRMwXIqUqZrIRcH1mA7lkdWrpPNVSxKm/c9s4Y5m4BNkEHB6WpC7q6wlvYYmyXGXsjLnP29O6wtLlAFaISadNRFAggUVHWOPdWaIIKXWP9klZ2Z0ZHoJEbepux4Fok1gFpIfIzqT6Mx4hybV19h843v0LQppReszUACV1/8Kpce/wALpx5EB0+lIpnFVNzOiMerqMEmCKI9aTARrkqkfhWv4mgqFdkJAwhRhJQQIakGO6PsD4RYWyUqYqaJRC/fD226Gc4MGoH5bsqHfuz9sDhHptq8/4MJv/HVF07Uvsxi+ScDycf+Pzry9COptay1FDc3Nhl6TaPVOhn5nxlaiktnu7TTwIPnmjz38hb7ldQUze901YKPrHzl/gH+1oDXslPcOX8WoRb19CXWOAw5V1/Y5sFHLNXLfcKLI37INvnSzjV6NzuEpx6oi69BhzpSSR01uue6T/TAC1J/T0QoqopHPv/D9MqCG996CaoIkyYEcu8wlfBc75AnkoT7V49gfLO9XaZXVr+u4f7OARc7h7XT/86+TA0bPbWMZvcq3ocgxz40/aY6ev/EnzC7ZpH4fBkP3gmoWDCuJEKOk0t/HGVTEEf56n8THaoAWM1fe+MlVu+O+YudnI3fWmfh3/l3ac21/9X9iBPR8ulLunaE6rXTe4bDHgujwIJRlGmDfHmO7v/+T6EXWtBskp37IMo7VDDotMXluzkvfPPKDEkwPcORO/Wv5zT9q7cj5/l7dYb/IVuogydHi0AMYx3NYyEvKhIgMxECH43fkzPg2C04yjhw/EWYEiEIRJrvaR+88PzX3uA3f+3b0F4ge/Yy11ZWedDB2Swer3LMMhiuLHj922+xNxrRDA2ylUU+8sc+wRuJxpXH746aeRjF7T38Tp/Gp97P2FtGCC0V2PYlZV7woO3x2DlDCIpKeY4D5GbXcTzwJLXdfIy/IARBfIgkYURo5GhzmyL3FMMJ5aiiHFYEAt3V7kxk14kQ0hRnEspRfuyEdXZ7OpgS6x4THQMaQqw39kSysGmPZ87kNMutYhDUppbmYgfbauDyknxYQlnX4ye13mOrQTLXQjb28S5wuNFDmQHjwvM764c8c76LNbBZlOhxSiPTfPvWIR85PUeDSKJjAog25M6ztXfIpQtnTzjWCFAFVAUqnFwcTtC6K8CYo5oupUhaaayr0grTTGM9Vt3y3oh8MI6wPwXXb+7wz37zOR7xI348AzGWRRQ/HRp841sv8MYH7ueJR++nMZexeOFoDT9ypSIjIiEwGOeEO9t4rUnujwREvqzwaYYAzbnIoiqVwx8M43wwsZRkVouXgio0upViW60YLKgvNfkeej3f9w6VxWC1ARUjC14p0iylaDQ5EMOgf8C5zjwYRaihX6mOC0UloAxoHx8khYqQQVUX86vI6BehJlFo1iuwQTBE9rhUAUooUWgf06ClVAz7fRa6C1HXQDRGokEvRFaXg7t3mZ+fJ2m3ooVQR0+0gA1Q6bhRJ9oy2d9F2yaPPP0UEhxznQ5FOWZ4uM/h1i6NRsapU+fAFzz/0hXEzONNIAmgxJNkTbSPRXyaSASRB48yUYS4EIsyFud9hM14j+Q5aZYxuXmbYT7g1rU3GNxaoBxMGN+eZ+Pmm8wt3M/lpz9MMj8HXuNUJFOwGCot4AOJKKoQIxqpEgod63GoHdjIxnycFUehXUAZat2vWEM2lDJmVVAkQWNMoFQK5SNRgg+xMF2hqQyomrrc6ugAxGCe0FUwlwrLFzuk1SHDyYTu4jLmyUeRlTZKWag89nCH5t0dHjYle1rTVwafF5T9XXQIpEoRxJMYjQ6R7tYYiRkmK9gQCKJIxEaaUlWrwdeOSyYWrwUVhERFXShVF6KWBKwWtAesUEx6bD3/CzywJqTaUDRhudFgLm3hy5LqlV9CL/8lQtqNDIEqUqho7anEoCVKHTsVNb+sCtHBVgbrA07rWGQcQu14RY0pRYS+qtoxDAoKKpp1JsSi8dpjQ2T8e8+3dxiskRXxvjNLzC89CiZBa82TT3R44dVr7O4fcvzT8bd3N49njHT1iTKtOL/U5DuvXydrz9FoJO/oyux3JXS7GYPDA7747QG9URRxfmfnp7aCp0PF++7e5s2nP852FRm2ps6HVoEkjRtpOXaIJJgW6AXNKZ2RupxqsE+QWgz9mHNHiNEMCcezR/eYxPd6NiLMLy6wsLICU6NTAv1XX2Xw1ltkWYP5RgP1+OV3XPvxF45H82cb9ZGdczxvEzuhAl3jmLM1rfIxQ6Oty7o+8d3au71aO8NTJ7fytZaDntUeRf4zg8LWBlgU6TbeMJkE1g8GXC0qDoKjSpuY4ZBmtzVz6n5f7P8JQ4kI6z1mIM3sb1GYw33OzDfRTUXaahLWztG7tcn8guX2XkVIm6ykGe32IqwVwNsn59zxE/5+7d+SR/Sv7Fj+T7Udd87fxVlSwPpz1+gstGk9scrIQws4Yva799NHx3mHS6WOngFdP1POed566Tpf+hffZe/UBdoL84z6Hq0y3jysOH06i2G1IASEa3fucuX5q4zv3mW+bSnTNk9/6n2Uq3MkeU4ZD87x51+UwlcVrm2RpmbXedYqzaQS8lJjvnqD2y/02FIBLx7b0nz2k6djXY140iDomh4+KTzV/pgktbTmWwQfGf3yUU7aSDHNBq7ee6wCn08o7g4QVRF6JZPrI5zR9CcVpfPkpefupOKH/8IfYn5pjla7ET01dRTcERfwhYvr2NSRIzpjwYM3/ugWqnfOSaVqEeBGSrk7oLQjGmeXaV1amy1Endl4KfK9PgRQPlCEgLKGg7HjpfVD7j/bwGjFzgTmFg03hwXX9sacXcxIyoSDouTj7RbDN7cYVyX9/QFVfwIiKKtRzbQmohGyi8sksni0NogQ8jwyPYf4t0nTaI9SU7g3UtLl7vTCTsy8YjChHJegFYe9gv/HP/oCo+1tfjRtkqaW+S68PBA+nw54YVLw97/4HP/X+87SWZnHJPZkZLFeo0XHcR4OhpSVw5We8TCn2UwxWcLc/ascH3Hxgmm3ZntI49IplNagNPnBDuHKBt5aaDaZrp8CKHdSLPnfZvu+d6hCbcppqKtzoBSP2BTbWoTCoU0DV291DQyVkVpINkYqjdERV6slZkTQZDqSQiiISlHK4CgxIUMpj1KBTBS5BDyGRAlOgxfPcDSgMd/FJJpYKQRKeUoJqCqwt73NwvwizW4bHyUFsAQmwWOMofIFWEsQT1CGEDSPPP4MjY4h0SmpVfR7h/R27qKyOfKy5OqdETbsc/1OTvfyWq2vVaIxZCplHHJ0aqm8IVE6wuAwVPVkT7Wmch405PmIUBR4l7PSSTlcv0lrMsJNRriq4qDYRwXNw09/jHariwRF0Dpi844xV0lNTp+gscrgg8cS9QMCivnWHFXl8VWO1QEvgUoFjNFoI1AptGiUCJmOkXFHhOhUIWYNtarhhrV6eqWjs6uDxILzEIVzlQFEoUNAV/DWz77GvFFcaLZZWGgSehUqTCBroILghwr31iHGJsy3LXcQKMeUo4Oa4l7jjSIVQzASWXdqan4tEb4Xld81BF+Pd20EoZgp0tU1YZHCPqA0ZEqjQiAYBQQWWiV//f/yJKfnHuaf/syL/Pakz/s/OcePPXSRM9kat7csv3x9TK66eDRVHcmxKn4/VaDEolVkPXQoMtGEEGu5lAhKhzqjFtABkqBRWvA13XR0SjVZMIiuKfGnOCGt3uuanMRV/7hTEK9tbSXlc58+g8gBVRn11dqNJp//Ax/kH/zTL1G5I4z+sS+fPMyx3wU4u9Jlb+eQb716i87CYqz3O9mT2W9KwVzT8rsv3Ilw4czOPq+O/Tc9TydL6YwGPNixfOPh9+NqzahptJVAhPIwBjxrD6XojhCWLKwmKO9pKItpNNDGHnNUpjZfAEmJ3sTvMZLHor5xNGJBusAMqiSAm0zQRcGF+y7w4cceY6HdnF2PUpDqQGaOYpxGBYwJs/rAY6N0Tw+iKauV43Nn36hJa5hlkuJ7npb1Rx//vaz5E/NazeDg1HsDdTBI6vlTbb6F6i5jOx2kHKO9RTtDqAJlmfOTzTn++NIK/8n+HlVV3nuC37sLJ+0TBsMBNmnQbiXv7LwCxPHawTZv7+2yOt7gwptv843/9L/mM2cW+WsvvMnmqOCvJAkf/1M/yvDzPxaJz97FgPyXtqkj9a/x7E+PLyf++td04P4n2oKKUh+69rormT4FR2QUMnG41OElsCGeBSVI1E+BYzbHDC6M1PP9mFslNWt2CFEGZpSzt77FP/mlr7EoTUhTFh5/gCS1aJNgTMJ+qSmDItUKL5reYY/r33mL4RDmLy7DWPHRP/QJ2ksdrodQEwcQl0UlSE0x48Ylu996i959CzS0cBvNA3j6hadJYLi5z3gslOJZaGmyLGF+tUtjoYPPq4jAyOKc9S5gU0uSJXSXuiCQ98eI83SWu7SWu9wajXltv8dHYnwEYJZJ8S4wGue88OY2AxcYuAo6DX641STLUnx1lPaajpsrPcW4qpkHj824GooYjmXJuOd5EBStpo3svEVZryc2ZgjvqduJy4QQhiXNViSO2DocMFGBnjhGuWNkSnInbI4dq8FzbWOHvcMJPZ2R5wkHPUdzqY2ymnJnws7+hGrzIJartDOSM4vxZFajTMrRKkfU78pLVPAn2PxOihZPo0PTnxwNiJ6SpWiub+zz+u1dnOry//ELlIOEbOwpAlhdoJlgXl3nK8+/wo92P4xzUXMz0dP1vj6dVoQEXr29i/Ka4cGI9Td3OH9plfnlBidrb0EZhek2Zn2a1cOiUD1LCIIPvgYgHNsTv4ft+96hsrr2hnWMpkagGxiTMcoHiHckChIiq45TEKeeR5t4IzwmMtIBaEFLAIlZjSkhiq0N5khxbqLKPUKmLZ5YP6OAYjhisTkPWRrZX+oN2CiLq0p293bprp5irhnpzNE61tVIwCYWB1ROYdIGyjnS1NKeW+aphy5BOaazukTlciTv0VUDwrxF2RTVEAZ7ntOrlpRAFaAoS7JWg0oHgo7Cw40aagM+UpvXE1ErUErjvWc86FOGwNypM3Qy4YH3fxYXKvb3d5n0ekyqCVvXrvDkJz6HshHulyjBGEPpAl6H6C7U9QFGQRIiXAwjJMFgbYP33TfPrf6YK1slSXDomhZdIYRqGn0WtIoEDkarmg40gAokKNCR1EKJAhNZBitxKGNIqelJlUKL4FQgNQqlFS+8vc2HTs3TWOiivUdeeAMRiwSHYNjb6aM9zLfbdDNDajTloEdxsIOizhAohfceFcnDoxMXNEbHc7kQUEQ4o9GaUqJBnikIouv+x3qroDyoQCVCgq7JHixGPBfmhnSWLzDMB0h7hV4YsbWYIa01bPsxmqN92nLAWE5FqIF2eBOzsV6gVIIh1lwpoyh9LQ2gfaRlZ4oZj5kt0eCJjH+RcXa6IMcyau0tXlcYBTrERVf0e9sYmjY58b8wHBzSTe8QhrcYDVNSM0S1H0RNCsT5d4Yxj0HQjo6pyMsQ2TVTw5X1HZzzdBbn66zldDOod3GJTkmnmdDa6bHvE1oNe6K25R1NxfOcdTnlpOBrlYFGFt+qHbkIWc75yLOQmoqDjQI/cIR5xeTGmOFzIxKgowzrW5ts3l7n/IX7Z5vY9GCBGDGeGdP32vN1ndZ0KAP1Opek6IceRCoXr9VoPnL6LI+vrdFM7cl6MFE8vbjDD57eYEqXpZXQMsU7nBxOjMtRJlABDVvS4GQ7qTl1fDzvMevl5KeiDVbXxIkwE45R9UG9o/rGP0ffdxnz1KegKlFeo4LGe4cT6GrDuVSRaU+qhSOKqnfc0eNnPtlPga2tLRaXVmm12ycTRPUvd4oxf/+N77JXFfwf73+cZqdDKygSVzEvQlg9xeU/+xMkh3dicPHY16fHU+9yb9+1W79/j9/lve8fqN+0Xb+zxy/cTSJ8W+I2O/Axbxl3AiEUgWJYMLw94m0j3A2OalzRGgyxJhbYz6b01CETQOrsaA1t2tovqapApgJvvLHPzvP73D5sMVhYwJxP8Yee9hNL6HYDZQ0DJ/QrYTFTjA76XPniSyQKVi+vsvXGDp/70z9INt+OTkUtU8LMGD4KYFTDCWUhZJdXaGpFUXqs87x2mFOMxzyUFrx9OuFX3xryX/yJD/HoEw/R7DbrTMrUQ4sXZ61mcXU+Zkym9VTB14x5EHzAVx4XFJs3DhgNhNGowImjyh3V0FG4wPakpLCWsw+eo7XQouwXHOZHYEuZMXnGALrzUyfrWOALZuN+tB5z9JfUDL5LbdqLnfiOUrX9dg/huByFeBpnFmI2LAReeHODftPR0Qk+F4ZmgkkVlx4s0e09GE5ITKA0FUNRlE4w7RRjNcWu4+03rsGTD8e5NSqRcYlqJHWk7vi1xEycVJ7gAhLCsXEnQue0Qhld1/cKwXny3rhmlxaKQT6bg/3bh/zHz5xh0onEWv/4ecftPnzq0ZSPPTQHUjJnclYnexSVozj0GKM4dbqNSUwdbBUqJ4zHjjP3zbG/N6FjDfc/vkazlc7CB+++t03fPU6QEo0bPyUdORmp+Z6173uHSikQrcl0hF6ID/R372Jcn+JwhHYKlw/xKtAwCdOYhVYaCUJeDhj0eywtnyHVMXJSGI8NsTDQ6ki5qakhI76kkWZ1fFdhRQEGnKOcDGlkGe2sRSDUC2CgBEI+ZrTfZ3X1FDbL8AGchYZE3SFXM5WYEBiYQCszVOJJbcrlRx7BpiXKtWg2E/LhkK4uuTnYY2sfUtugvXDAmZVlPvr+x7hyUNFXhhEBnSaooEmSFHxFI8uQsqRU0aFsWIuIB5XSSBVVUeHGhyzNr7DUbaFbZ9n3YMVy+twl7INzXH37BbqHA0wWIy9WG1wQghJsvcA4BKuFhIjrRyckhlrPSxOU58vPv4EXTXNujqAiYUNCzRqX1ppN6MjaIgEXFEYpFLqu2dGgYy2bRpEo0CHKFEutc2Xrtc6gMVpF2m9fsZRqzs1ZTFeTdAR9sYMyIIcl6sCx7Cz52HOn1yNXJUVwjAaHuGoCrqTSmkybiAvWkVpbKfCqwoqpndZIsYyKYrui6+vz02Uj4EJ0XjIUIUQnSymFUx6rKnDC1/7F1/nVv/MthrtDCgd2XlCDJl87e5WvTV7n7q0J/aWPkj79IIkxOF9jwzVI8FG4Os4uRAIGIVWRUTEohRGNq5ixpCll4vyV6NwaHee6rqN4ogSrDBaNkkAuVcTCvldb7Rjca5SKCDL0qN95G9Xp0BiUGKkg2SNdvRCNn9qwltlmIOSFI0mO8OqCsDcsSJXm6QdW2O/n7I6KY9kfqW0WxVon4YMPNkhtitvq8WuHNso7HAsiHnX5aMwzq3n8cIedIKw3OmibHDmHdT9DgPWtDf7DP5/SUhPaZztYYPcXNrjy1+5gexW9TDEeW/Lx+EivRR0ZF0fDc8wcPuF4CMbW8EWJtMjD/Qldm+CUJiwvxs2eKMK+srxKmqbHjgVT+HOqHPN2UBeTH7EMHm27xzVijgyGo76+OwBTTrx45Ezdmwk6dknHPjM1sKiD36o2cutMb1mAr0A8ygu6rnYvx1FAs0IoxPODq11aN95iY3mZfrt1rBe/9/mPVZExGg7JstY7vjH1cUtjZ5DNVpJgshatLMWkmiWjGXpPa28f04gF3bMjT/3E6fnqRMV03O8dtd9zqH7P99/D68Tv01780gZp2ooGtaiYcSLWa0/vXVlWKOPo7VRRsB4gxoNnbJO6DiCEY6RAx0WpJYD3QjbXQiQw1hlDtYLMK7aDQnY85cYByf1LtDvxTlY+sDMukVHFxjff5DB4Tp1e5OAbt/j8X/k0aq4zE7qNTyd1/VdtzCogCNV+j2KlSWO5zR1p0BZFrgKDkNAthKyIYjSlj3pDeeHphOhSBh9iIM9P6bmPZr02muBiVsUYRTGYcLjTp+yP+NSnHual20P+2S++zASDr+G7MZ4RZ9SjD5/j//QXPovVNiaQj0F8pwuYzDIgx7JJ08yf4sQ65iTu3TFWEu+HBIW2BpUcY1VVKlLQA+8QlA31k6VAtCJoReE9zSxw5umCPXNAahRzq7EDi6eEdleQVkWVBnwR7QtVefr7Q157a5OyimUM4h35rT2wKtaaHXe+65mirIpaaNM9ysWJppPoTMXsevxuNSw4vLGLc7FmLUzHT8H8muX0vqFsBS4/AK9sGW73PR98OOEnP9Xm+esZT59t8cr1hBkphgiHw4JpQZoCKhcovbDTK0ESKhHKsqQoioiGOHYPjg+lQmi321hrj2JKEhkFfQjvWHS+lyvM971DZTJNZnRNoxuNeK8gXTnDwgPzNFRAJQ6tPGIaVDhSidF/pwtuvvpt1N4+cx/6EZLlOZTSJBINX0ysk1LWUYnj6ou/A/0RZy9/lM7iUtSRsgarPJPJgOAKDrbX2S1zkmaXsxcfAaOoxkOqXsHqmbPUNcR4KzSwmACOQFKrYFN42raFQZiEik7SYqGdMjg4YHnlPMF7qskQ5QM+eNJsnpWVVTrdFs889BAfe+IS1evXeXnf0TQJ2iqoSlpJi1wqssRQBhMzZ0qTJAnDMicYg1WaRFvG/UMWlpfxIZCKJsvaONF4Kcm0Z3iwx/z8CmlicUpACWmItWbKRDIJOyUpCAqxkfkuMSpqeBkQAnu9G6R2jtbCEt4oUCHWDaHwSmOVQgfBBUVpAsZEBfVUJyhRtTCyJogm1CJyjaBBh1rnSpNi8EFq7S9FxyieWZnjvPPMLzWRS13UhRaEHCqH6gjYQKI1yWrCo3oN4xf4rq/YvvYq/e1b9Pe2aa9eRGwA0QTvMQKlMogYKk103PAQdCQ8mUFBojaUDhE2FHBYIr271tHBiXTvtUmjodnM+It/+c/y7a98lV/64kssSMK/+wd/kvsuP8PN57/CT//O32X+3BweG53XoHDO4cZ9km4XqzReIkW6ro3CaCvH/hQwc5pSraicxMyZ8iijSZTC1HWGg8mIRpbSIKXQHlvDQVJr3vX5fM+1aUBYYFw4kqBxBxVlPkAOBjAZUc2tkndTfH2Pj5uaPgjrGwecP7NIltmjSLMPfOzxVf70n/g4dw8n/J2f/SpF6U+cWiNcvrTEs88sc/WNHr/21iaumdzbvXv+FkyrgfWe9TywNzd/gv6WOqMiwO7+gG4nwVjD4b5n9UKMXvrcEfKUptF8yDZ53PbYcOUs+xENagPaYhNLqGuyTjhVHBn8moopzXqRC4dvCWdtg+DCjMhDoTASSHxO4jSiTZyEanrco59Tg/7kdR//+yjq/W6fOe4GHsWfT37lHY7AbEc/ijrHSFwMTUgA/BS+OHM/4L5HMcvnCMGjQmQzC5Xnyy9s0Vlc4lyry3hS8ScvL3JwfZffvdRj0G6fPNeJa5hewbFxFsEfblMmCnhgZggf/7Y2mjmb0NYJXZuitWZhuYHc1+F9hyucwrPQyTHzrRm1NLVRNj3WCZazExbOsRkv94zrPdbMv+yKvt+yVOfPztFqdd7x+lGoBbR3PHLRsL4lFE5OjsasHu5YlnD6Qn2k6b0oK8fdw5zJYcHaxfkorxETIeTjiq2r+7hx7bTUEYRx6fjO87eodoZ0zjTZ2Rnyh/+3P0KiLZWazuEaZogihjP97PXghfI711h5+iJpp8HGRHNKQz8v6ao+3/2Hv81XXr3NYeXpKnj1t95m7/k7/MBf7mIaGdWopNmwJJmlKh0qtWijcaWj1W2S9ycUwwJjNd4HinGBFDnnznXpzjf58utD9gsfUTComkRCKFDkouvssTpyBurBl9kkOzlXj7hW6+dHjp7j4BVFFWV1jIrweO8C7aIijPJ3vf9uXCGFBzUlwDhySCEG+wslHAbIlrocHMZykIgOioRpJtPsji2+ziCFShAnfOG3XyUvKnCeoCIhjg9H4vKzGaIVYjWq8viN3izjJAhFajHdBtlDpwAo+3kNiwSRmNE6Pmuns7OZpSgrmJCTJAmdVnw3iEIbwWYRzh3ZK0O0fQIcHBYR3TJdT7QiSRIyiQHANEmYjHPu7gxBhdo5OoqKqXrqaxQPPXCBTtfOEvoicsyZCpxceL53K8r3vUOlJMKpYlbEMxbPuL9HORqzW01IC4HFM6x6Q2IgwdalyIEmhpXVZcQmzM+1QRscCmsStEAioLCIjgX4S/MLjPo9Xn/+C1iTkJkOSTujHI8QUbS6Hfqb10iVx7bXOHv+YSb5BFVUrJ1bxagUJfGBgPggGQGLRXQgCYZhNSJrNEBDp9VmrmEJkx6JSmk1M0b5iH5vm929Q66v79FebtAf7nNnc4eVU+f5R7/xTYZ0CGlKM02jsKuVKGpMgtWawoKUKhIUGE1XWVJjGXshSRP6vX1W77tMiwnGRop2hcH7jDZ96N9m4eLHMEl0BKoQQEMiGq0j615QU7UaicyHRHiUr8MeLjjy8ZDQ7rC81GF7OMa5EgMoI/gQoydWC0pZmpKgEEoVcbNS33uvat2qmk6hUoHEHcEsMJGZTBnBS7xmRGilCarbwO0UGGtQKylis+hU+RypNPiAKx17wTFs9DjY28CPRhxs36a7dj4ux0rQQdVU5LG/MQwXF6RUW6o6gxZbHa1TEbpoNNGJFE1FrNdzKsYGrSg0hovnl3nqo5/GBeE3fucV3vfBB3nyY58DnfL4D/0R7v/NL7EbKSJQmKgDEAp2925yvnWZYCM+Wdu4OTa0RvtpVtTGzJMRkijyg61ZWzMUjgiXLbQnCQHp78HSMipJSXTULUsNFFOA+3u0HUX3phEyYb8/Yk57Jsun0BaYP4O4Ej+Y0L50GfXC9tH6fyxyVhSOECKhCsQIm0GYDyV2+yrLcwvMZ5ad8gjfrxWcmU+ZL3b463/zOvulIV0wdbT6uAswdQ8iVDRrpJze2eZm0mK0uHgCNjczylQ0tLa2+/zo5wytRsVeP9LeHn5rwuDX+txNKvJS0fRV1CATIc+L2rqro9yVxxqNOUGb/s7NS1PE2s8Yl+SyyREavP6tl2A4wbZbnD6zxucfuMQn8tuc/9Vf4Gb7Ai88+ZHaWD/mqNQe3cmk0j1k6vdC845d/8n2brHL6Sgdc5zqg5TO4LyuHVKFBEMQAyOh6KVT/yoSdChBm0Dzo38UKbfwWy9AUcR6TO/5+hub4CwtZRjlE7rOofIKNcpPOOQnr+ueX+tMaKOo+N+MhvRai7waPGLuDWYIzbTBX7n4GOMSznYW0CtneOB/9yfh1DI/vHEN5SaoC0+h8cjNaJAcF/WcJl9jhP0el1SOz8mjc077+C8d7uMO7PdZsspojZ0FBU42paJD8sh9GZ/7A2f5Rz9zAz+qMz/HqdNnhvjxL8cfx8x/MmVZ6maMcwfNLIrK17prqiYZmvRy5nwXrRSh8Lz05VfJX15nZDQ/eP/DfPyPPol027hJeeTYqbqWSMFUomD6Vr6+jeQl/tEzDCXjZuV4nza8PpjQqITtu4fsjz1aCQ92Mi51G2gFPq8iE7DzeK8wThGcR5tY8y4+RIp05/F1Teo0IxaCp3l2kY9/8nE+/ic/yfoLW7z4d1+g8MI4d0zw3PFAWfFbv/BN7r98P0uXzsawoRwftZNrxAn1t5nzpY4cMKNhuUvDGJI0RQ1GhLxAj8ZUk/HR2jT9ngLaLVTToCqPquprItSINQHROA/VRDOhhbZx/Zhm2ZSKkM+J1aROsCIUk4Ableztj7mxdchwkjO/2EKpQJiE452P15UkmLkWUjicHc6IIERFB817we8OQYGbVDVTaXyetVbMne1gs4TDuwPKcYXUUj4hybl4XwwYqqREmXhcJcIH7hMoQZt7gCo1yVYcHpnRtgeJjp9W0cG6cK7LYJyzuzeaLeUasEkSWVpDnZGaOcIKVzkkeMpJye6tHRSa9lKbtNmYOYLfi/Z971BpncRCftEYHSiHY3bu3oWixB+MGDvBBUEO97Bz98XMjK7p0kVhbIKYlKA11iha9cOhTdzmDFFgtkTIGvPQ7tCZDCmqEYP+HmpP011YRFlFM1lAL62hFNjWMuPJAKUNC6trJDpGI7xEVjrwWIlLp9b1gyygsgQSgy8rmklKUzmG+YDu/GkEjyn67GzexNhFzp9aoXvqPEppOt3AZm9EYhPEeNJUgdUYBGMzrGgSC4FASxnGiUa8I7WWka0QCbSU4AP4fISlYrC3Q5W0kd71SC5hDf2qT/9gwKX3rUSl76DxWrD4mAlCQEEaIgwwcoRJNMB0oCDWCKngadgUbSxnFjSH4zoKJB5VqkiSgKLykU1PicLUUYyo52YplZCYCDsrRWMVEQqopyrc8fNRJFiT1VpJC6nQST10PObcAmplHvQYnTaQUBIGHt1wyNhj85yF0tHfvI0aDwHLcOMmPPFRghgsQqHBakWqdNyQgqYikGhIFRFqeIyOTKlIQh6wBDy6hoYkdaTZSNTbEu0xQEWIMMB8RIliMKwi1lxHaEJVViityHRCGXn+SXWCLUvGk12SuTNRb8eYukDVoLMU4wW8Q3SFU6HWVAs1IELjAogWquCj4agC48E+i2srpFrwQKpNNJ7V90774Xvd3n35jYawhEDS3ya9exdvm5iqIl1aZpwlM0rxEwa8Erx3fOp84H0PRNJ+54SbO5ZWO0HybZLlRT730XO8+sYtJk4xKQNnVtqcX4Of/9IGeZqQttRJCIQ63jOQEHgcT7bQ5NV9jba69j2mG/1ROXw0lAXwNMmoCkezHQ9oRyWLVYNGVaBLYZw4nrQNvjke8uK3vsqZ8xdiTUMdMAjlKDqK6t046e7NXAjiK1Alo1Bx+/W3qV59g+bjl2m3LvHpZ5+kzeOc/vKXUHf3ePGJaIxqiBIY0xDl7PDHxvt4RkbF7PMsEl3HNGb35J7fTt74eCB17LU4voZbO4ts9hoz4zKIZleanPc9fKlh5jCDCgF1cBvKR1C7L6OufRU1yuMwhEDqHVKUhKqN9xLZt2RKaDGzaY717fisPO5QQ6OqeJ/WjCdD3qw8lTaza5/+tMYwZw39EAl7wriHXVhFicHtFdAbIsUG6vFnETsGNo+d4SjqLSf6cmz8Z5Hxk317pxc4/c7R62r6/zuu+R136D3XZgLY90QBIoucp9vM6G/3GQwqhGQWrKD+zvHxjy+pk4Ge2cuKdjMh+DLOoxP7i2ASKCcV3TRF+cCrP/9lzoQxupHw+J/5MBcee4Chg1EVyx/mVbR1Yq1WTUigpuRDdUbicIh64hLpQkpPaVIV4Xd7XnhAJ/wvLi+xcF+C1gGNYaGZ4ERIvIt6UlD3dbY8zF6jTk6ceC8I+IDRmixNWKgCjQc7nP5zTxByz403d1k+2wUU5SSwuz3GTIbMJTJdAo8FX+rIDNOAwPF7M/tttoY7o9h2AatSBnlFxzMTQpb6fpyoPJSa+MqAquXwQgiUZRljT0pwXvBKx0enZtFtpI7EBvLSTjuMMA3+Qj7Kyfs5lIG8LMlDxUI7gSTgRtWsPyIBnVqkCLAzABHCfLMW15pmqSLssBpMZnNtyvo3fRyn2qCq1v/SwMTBL76Zw23DpJrw2h3Q2vCLz+/x+m1hrqNpp3DudJNz6shBm81HiY7VKAQGUvDKjR1Mo4vP4KVX9rhwRkeR3imUAlDG8MD5U6TW0h+M4uGm9ckijIZFHHkfWSDTzOBKj83C93QZ+b53qEzN4jYxcRe1jYzl8/ex39sjyzvoKpA1MryBalocHQLBV0yqHE3AK8fdzWsgQhY07VPnaDdTCl9hRVMoQdsQ4VRYFhbP46VgWE6gFNqteUQHsmaHfLyHEk3hClJtmV9ejIudrqFwQSLxgNLx5mhqSmqNEk+qE0QbBEcjtfi8jxZDp9um9DnFaJeD3T1aKwvsj4WFZpO9QUAlluWGJWt2OBweorVBG4sXhbGK0sUQgtR1R4hHKYVXQrA2ZlCMpiwGUDkaC6tYJrTOXsb7EqsseVWxszFkXCmy7jziY2bCKMGHaLDFuhtNpTxBeUQpUqLjVYUASlOKYMRT9rZxeclLL7dIGqsopcjQVCogAayK2kllKLHKICHWe4lRaBxOJEaxxEeInLZopahEoUIsVAooEh11nUQcTWN46OwiLe+R+SZ6uQPtNgQHnQY4QesUUo0aJihS2nstsrvQWTxFyBqkSYJVnlIbdM2GFMWFo8MsOqBrWukiigKRaChFMwVUxJkUYsZU+5gaD3WEUNXSNRhEhK2b23zrt3+dr33py6TZIt/99tv8i5/5aR593yd4+1u/y8uvb3Hhgqlp1+NcE3E0kgDeo7XFSGSgFGWotOLDl9ocjDRvbhwgAZK6sNaYuODneKy22KDABEoVWQCL4AhljqQd9MyckmMZuPdou2cVLkof8eRJIHnw6RgEeeQZtFHoN1/BaF3XUFEv9syMTC9CwylWbRNlFLqZcff2PqgJsh/w5RYXl5s8/MOXEKWZjA74+jdv8t//Yh/VWYiC48C0EP3I2I9RujnleHgVNq9NuFOW6LoG56SLcwxOVfcza8AH3z8Gl2MkABXKB6zVpEAJtLXiTzW6/OJglzJ4psxL79ykfu9tq3alcC5QDIcE6yhtnNSh8oRrV9j1BV/sH3Jq+xpvf/c6ebfBHzv3Kp1WjNoaIywkw2OXc6/E7/T1+OrtvZwbd0d88OF5GompR+Do/6O+nTRQEZiMLcNh1M2TEKU3XND0xhofZCaP44hwclXXR0ZHLNbH6FChBluIK2HzdZiU8d4FONgXgheUE7SLhpYfVxGaFAJ4wQQhJOZEHYac7HgcV4n9WK8cbSVxnXuX5q2lyhISyeN61l6C+UsoY0jOfIRIuqQJkzE0tmf3TMnUuzzuKNWemoTaRq2N0xM+0dHn73Wdjl+JiDAejTk8OOD0ufN1UELV33tve1RSC5YC+JpcQStFCLEeWPmKRx5f5rnvbDIZV6jUROYzqYV6dVxIhKh1JAhT2jmROkqgNcELrgrYRBMEhuOCNLWY1MRbpSFtGbTzbL5wBcYF/nDM+OkHufCRDuWZhCHw2mEkEUiM5gcWFpmbJmyOPTJG1f6Oc5SvbVL+0P145XhlnLMC3NgpcaWw8d0bZP0xCy1IG4bBWKgqx6QKMClonVrBWEOSWqzVYA06sWgbIRo6tZgswZYem9gIIwshOgrO43pDhncOkNKRtDReBbKOoruQQNCU1tHfA6MFeyyrNnVQjgd7Tviw9d/3ZgZv9kb8oy9/l9WFBe7e7fP0pWU+cCbl/nQZLfqYptXRYIXDyQx+i8T5EOubYt1x8I5goqZWM6uwBi6f79PJKl65uUhexaB7ZKuO2ayyKvnqy2/yW6+8QlE6vvHqDT5/bjkSWcnRohDrJZk5T7MHU9c30E8Lt6MjF45lmWc1kyIMtoZMyTt0PUjDUnhl3ZOpqAt2UFlOt1KKYSCRQKuvGIljsqhOwoSJzlR0+ISvv3SFzWLM6zdKfuhTj3P6zBz3Xejw27/6Fo8+OU/SULP4gXjP1vY+Wmuc8ywag3OO3f0B8wsdDg/H0V7MEuaX5tDaEFzAFQ7x37t15PveoXrr+d+m0WpQBqHRbOCCY7x1i2J/F8Y5o909htawt75OozNPUY1weYk3wniU88wT76Pdgm//xs8xGU7wwZGYjCRLKSvP4twKw1GfwpU8/OiznDm/zMadLcqijCLA4mllbVbPnY/GPtDLJyy2V1mYW0SUxovHSDRMHAGrNUapKJGg46OuBVyo8EbRBBKT0jCOIu/TnltCGcHkI3q7m4yqktH2dowmTHKSfMxiZ55O1iCksL95l7nF+3EKrEBqEsauwiYG4wOliZCB3FcQDI0aRmeCJR8c0O0uMjffYTx0jPZ2UEmGt2Bsh3JckXXmoZURCBhRKDwioDFICDNaZKUMGVLD/ITURAPFoHBVQWftIl5pJoMdKt1GpW2EKI4rIWo0ee2xomoYnIuGbPCUKmAwVN7jdWQvNCqgBcrZ56baYx4thqDA4LE6EPZz/O097EPnUCaFEJD+IaoYAi3Y3kfOnoEK9IGQj0cEEawEqskQvMck4EJ0fIyKdOQQhYgnSuhgMVoog2CxpESad0eEVDigCo5Em5h9E0EwpAioKAhgpaJRBf7uf/a3ccHQeOAZNrY3+Zv/9d+j3fhZqsphkwZFUZB4T9AKQkLwnsSA9WMY7NGd75ImNfFEqHj1lbfI5pfpJorSRyigr/wMm54iICWVj2yW3hdMevu0g8PYJGpooTDKzCJu7912b98Vw7wkd45gheAqlI2sUwSHCQ49zdpMvz7NEIgQJOCGgvSjBpqQs3MIi/MW2YMXbmxzMNfk6Q8+hZaSL379Gs+/Msa2FrDHNvd7o/ciwpo+5EP3r/LanT53mik6iVDYIzAER87HzK4QLpyfcOGBBs3GBJ2OCC6hzAPFQGO7TR5arHh10GffK+5IzkAFTOWiNp2dSj9Mj8YJ8oJ3jmB8td8bcfk73+GPyz5/6x//Q9zNHfTogGq7z96bb/DTX/wiUUDB8FTi+IvzG7Ratl4UZyY+Jwfi6BRTQ14Efu5rm/zUr97g1/7TD3NxpVl36vgYvguwTiJN9WCUcHerNcuOjYKiUCbWM6owG1lBzTSnojMlMzIKvEcGA7j9bRgOosMShDIP/Jc/f4uiH6ICvfOIgvXDnKUAwXnO3l7nI7sb3PjoR3ihMswq7pGTWbm67Qv8R5s7/FUvhKpEmlEIM0KGDChFaLZ4czzAlWPuG7UZ/tOfI0sGNDtCMBbGHhcs2raohlF/L4RAmZckSYKxmrQsosOXJJwe7HB6/W32Tp3n6umLcUTrifCvRDQhR8/KndvrfPXLv8X/7C/8JbI0/f2/+x5pzgveeZwP9AcT5roZiTXsHxwQfOC+lQbtdmBjL6e7ULCxo0lTy2A8IU0tzWZKnlexpmiuhfeesjdEm5qaIktJ2g3KsacYe7rzCc57xoOStJWSmWZEZqAQFfCTgp3rN5lbbvPon/gYpx46x2RxD60VhZIj4flp5qWe2FNtI3QMtCnxuFt76EaKum+FiUrZ8RWrStgWYTGD8pXX2d08QKWG4AMTF/e6SRCefH/JuXMriI81SSoycDBjEaxbY77NZHeAyRLS+QbDvT7iPeogZ7y+j+tPGA8dVRkIlTAeOA62hiCKsggUhSevhKGrj1/XDknNUxufoWPrZP2zpQ3JPWvtXvCk8/N85BOP8ItfeI2Hnz7PpLceNbHqdcXMtVDGnFxzZ5n7+L/NSyb7gzrrFvBBY1E0U1fXZ0V0odbHVrq6L/k4Z+/OFuP9fQYHI7Rp8au/+xo/8PQl0qRRr18cC8LUDMjTa9WQppYydzNC0ilL5NGlTveO6Yj4Y1nW2IwIP9Zs8VgwDET4G87xYKeD9oE/fVbzzJJhv/S83WlGZ7AuAvQuBpJCiIHv3d0eQxMoKw8SsNZgkhTvFCJ1uULdtyCB/V5vdl39YYQp5oXQbDdwlUNrsFZTFSUqKEa7Y9KmRdrfu3ru73uH6tf//n9JotNYw6IUSmLEzqPQgPMOpYRbN19HiKK8AZAQSG2bZx55moXVUwz622zf3cEYjXeeBEWBYsNcRaoSqxKeuPwsi/NdfvdLv8De9iFlNUEFRZokLC6tQrNBYjIoKz7wA8vk3pGQxcxQrcLtVYQbJqJxhFk9nRDZdRo6o8LTSUC5MUaE7nwHgqcoRuxt79C2hqA9B66iv3sXZWC00+ew57n81GUaSYbSCheERmJrHK0mMYZyiutFoZXFEPW3ggro4NnZ22BhcQWro3bM9uEOrWyOpN0m8SN6g0NWT9/PnKkLJ330CqdZIKsTIFDWJAy6VvwWLRivccrjQ4VlwKmFBhWK4Cs8JcY08QjGgzIWcVHctqwjvcFHZkIDNVwy3nMjdXzeR7FmpwJKe0Q0VRAyPYU8KRIlpK0Gpm2xnQYkKWIVkIA0oCzAtBCnUGkKyuPKMfn+PnayiyuEHp5yOCDNGiRaoxUUoggKktpEbCsTFxeBTFPDpAxViJnBhEi7nutaL0oUVkNJRahhF0nQKJVgkwaricXZlMF8l8P5RUzRxweDNRFyR9ZCaYNBYUxFMtpBZIKxc6hmk4lPqXwUSQ7jHuPdW3QbXZRKESxePJi42Iuu9anQaFPFiGleMNjfoNFMkXKMbc0RtMIojwmKoN67S83JDabeWOoIXhCF947gIbz+HKYYQzfCTI6+Ew8idaYqBhcCiXFRtFoU2oKxFaMs5W99eZ2vvX6dxbnfYrXV4P5Ta3S63RPs5EctvmDQXOgaPvPsCm+9ss3rhw2aTXvMmXq379ZGfwg88uCIH/rQBd648lzEwVPy6n/1BvtfGXP+UkpPHL1g8F5xsdPix0eL/He313nj9Vd4+pkP8PtTex8f0PjDBVgpSz4+HPLff/mbBIHEhxpDX+uuYfj006v82c+cotGYOlPTi1H3HvJdrg/WdwrWvz3hry49QPHNDjsfNKytTTWe7rGUpr8FIR9FZs1ioiiOrcNeapiKrqGE9eoR6vuraghlRGoHzFyKPdWEtRVkvIOeDGM2zgvjOzmbm0OeUpY7YcJcqplPmjil6DHhNzev8seKJR7Me4xSiypryMosin7PlQtMyoKt8ZiD4ZDBrXWyx58AwOiE+YW1iAJowc9MRjxaHPKx1qNkH3iS5uY30cN19FoDITC6CsmP/yQH13uot3bAeQ739knQrFxY4/TuDVb2b7FoLcUTzzKXneeQBtNS+6ljPbsRHD0/x+/P8SsQFKPBMBpT2jB1iOHkc/hebCGEmrzA4yqHdzHYkecTrFZ8+rMX2dqsKCrP2XMpt+8K3gdc5WPtsQ8456mcMCk94qPzYG1dA6MCOgu4MtJhe18LyYeA8wFTOowEqt6YMB5ghoJNLK0Lqzz4oYukyrAewoyFl5mRHc2Qaa7TH3uvo6LQu3/lKurcHFVmWC8d9ycpjeDZHg/I3ryJ7I1JAqjaiC58zBb5ENcfhYrwMkWdjaN2qI6lNDSRXMzEz+aTgnx3jL19wLAs0cbwxnOH7O8X+BAYFSVeQx4CoZnyyR/+AAtnlsksx2YozHIt0+J16kUaFdkMJVC6I8dEROGTlCyJNehKKdpzLaS0UfPSCwRF2swwmeVojXlnEEwbTX4wrLO7qv7IkW6jkhiLPB6YikyLcPfabb7421/FlPB/OH2edtOSDiZ846e/wPv++A/T7NwrCAHHj6S1prGQUm17lJs6TMeCNHLv3hHH5HjoSQG5hxcKzbqHCYFBgCv9IVoU/90dYWnPoIJmJRvzRPDoJI7Ji7fvcrrTRWuhDDDKS6RlUUQovNIKYxQ2JY6P17WUETMijbiA1G6iTFkJPUVZkmhFkhrKMiYspHKohkHk3bP2/zbae9fK+VdtOhITxN3Qo4Ii6Bg19KgIuQkaI5G1zGmFkgoIOKmogiDiCaEEKvAaqy1eYjbDVwGrPEKCSSBrNEmNZTLuYXUk/51Ujupwl05YIu/dIVQVWzdu8egnIwuK1Cn9UNf+KOroEIJRGhUsWiqcGBKjCcFjjMeP+jTb83hrCPmEw+07HAzHtBqWrN1hks9TYZnvNjnsj7BJidMpKxfOIiZmcrRJSURH9rY62trERgFdHTWeElGUxlL4itHeLpdOX2R8eJfrdw/Y6/VYXjoL+zssLy9iTMr8xYsEG2m0lY0boiXWQKE8PkStrwphogLKBxJlCEaz2vB84ozh/oWzZE3LIPfcubvP1cOU13oOJUmMrEigUIFKKdJ6vJSNxo4H8iA0DLGgVQloTSWCNVNq9ShG2zJRnUzXrxiRSKbRSKBpwRpIEkjmYnF3BpQallqItiglFOMexfYNRCqU06jBPgd3b3F+YY3KxM0uUZq8dkKaGjwmziGtSRA8mkIgVTEq5QhYDC1TR4WCJgRoaB03HhGMiYZ5Y3EF3dAMxTJKWygvjPOSVMdNtttdpbWwhFKKuUxxsTHi7niI7rbw2QIuyahEgbLE5czh04ygEiqgJbE61iqFE4kOUm1MIgZUILMtTp15kNFkl9Gkh0lS2t1lUAZnQ2RXeQ+3E0bfDKtdb27KwDMfJ00baKsQrSLDUv09OXaQIxhGwFeB/bxE6YQyOPIAd8VzezSkKHvs7ggL952n3emccIzkRKcEXwU+/qziA4+U/PIvO17f1LRXstknj0c14zdm4WYU0M7yyIClA2ktRGtJOH9+F98ydHsZg7HHB0USFI/Nz3Hfbo/gBjh3BPPS6qgua5pykGPnPp4BUkDpPXuP3M9r5S6rkyGPe8Wh0mw0WogGKSYg8IlH2/yJD3fATKE0J/NeJw3y45t99IB2tsesjOCPnFuluqOYPD414/W7fg9AguZwJ8N7GOZJhOoe+4gmMvRN7293ErCFoloFJR6jo5M87AWC9ix1GlTjAl32oifphH6vQDYqmoXjqQr2AzznCp5ZWEANcvri2T7YwzRSUh0DL1NH/ujG3tNEePWlVzjvA4/bFs31LV65/BjB6EiSYaKmi1cerzVBaWySodtzqGYKOag0JbQUKhNUliHWoLRFKU3lBVeMCUEYtTqcHTXZXD3N6fOn8H6esDGciZ/GDO09N/+ePh/3Caez9eBgn8WlFbpzi7FGI5/gffV7XPB7p42GY1wlOO+pnGMwHEdShkoxv6A5f67B17++x7AoKfKMcT5CJhrnHT54qqrCuyjEGvouQsZcIITaUK8cVTnGlQEJiuGBj9AvL5RVjhtMSKSi6k8IyhGWM7IipV8MeH3wNolJyJoaTcrx3K9CUaA5DI7NMqdfs6cZEVKAPMeFivK+Dl5rNkYlD6Saw0mJmYw5uLHDV97aQ6oJiVFRPD4Ii+2MP/e599E5s0AxGCISSFOLTgxVEdBWRUjXlO00CL5y6CzCHSdVyauHjte/vk2SKozWjHsRih2Txx5jNZjA6eUOZ9//MFo0pSPWMsWI61EAQNUEVUfLY6wV4lhgoIbMXVnf5aBX8OWvvs6V6we8/MYGDy/kDGRAohbAQKhcdAw55hjWz4QCfOkIeRWzZPWDoORojVczx+GkA6hEYh2cFuYSx24RGHmwlWC9ZWdYzp6ro73iaL2fZspQR04swObeAaeWFo4KTKdNEbW6pn+qYw4f8NB9qxwsLfON2wfENTUwmTgIiu2xgKpotDL+5GInkhZZjQuKOwdj2mkDY+HOZMygKkiCQkTPCFSMViSZoRjCeBuWLhJrdY+v1/qIDbPynkmes3cw5vRaiwrFazc2WdMN2kQ2Y/L/v0P1b9xEIiEAQdDGEFQkkdAKvA81pjVGQiPYTDA6I+BRdR2TaINWhkxbFLYW7QXQGA2GZDYJvA94V5FqjWiNEU3a7NDuLNLrbVK6CiPCW699mw/d/XEWHzgX4X46GvheC4RImpBoE0WEVRSbS4zCK2grSMoBKpS057rRqCl6bO/eIsssnWaKURUJlvsfehAXchrNBu3uMqfbbbor82zljv4wOhdOeYISUqWptGeaBo8bYswuaaPolwNCf0A45Xj7+k16IWHUO2DBJBTiMMUhd69eJZ+MePD8eYzN6mUgMurZuobHqrjQow1R+SmmYBcbgR99IOX0nKYcDUlsi8QM6BjHw8sary1X9it0klG4HDCkEovqNVEgOBCpORNtCSKRJQddS8Koelxj7ZYPkAVNsNF5TcQw6R0Q0hKTBcQqlE4Qm+G3N8CD37+F7p6huLpPe/Uc3gkvPfcSut9nNbH0fKCpCvZf/zar910mnVvASUBpRVtrRDxeGZw4dM105ol6WKIE70qSoGnYjBApwvBKaCqNNzFb5epIeKjHdmV5lZA18DTApJz78GfYeeWb4MagLN0zp2hnTTq25MlTQhocH3roSQ77Jd+6ukfVCmQ6IMHgQ8H+YY9qeEgiDqPSKMorEWpppkEIpdAh1AXJmkRpuotLiEzIRxMGB5voRNNsLmHRVPLepU0/XiA9XbpnjoJShGtvErZu41wtJOktN+wqeW0IzIx1OSoq9yIcDnL+n1+7w844kjh88olVumsdHj2zxsHeGyzOT1hbGs2gGNNjcGxzG00Kbt/Z5WDU5EsvKlpZm2SxBUrX8dVj13HvdRHrudqNMY+vFuy8ucHqyirWdJjcHdH77QZ6I9BY8CRVnHAmBMadgp1EwURRi7pA8BhFLWjL72n7HndKinJM8rHLcPsN/oOe4ycRrnQW+M9/8CdYywr+nebvgi959oE0MpMdO+xxR21GzHHPuYLAV962/L9+ZovP/sgP8VNbm+x/903+8z/4VG1EqZNpFDne7SMDZEp8fvwEqnZKhZhFOHXomM/HNJMuCxu7mAdBJZbnv7ZDmVg+99gah//w23QeatF6tkF1IPyNf3iDP5N1+ejYMxc0f+nyg6TnuzSTlOJqSVnGQIxyAdXJONsUFvuBfcysDmPaG1VzmfsQWL9+nX/PNnikmWB3t7nWH9Bb6GIkyjVMfUltIiGFUoJYkBqeJKIJiYpBkNqRUrUB5gXC3U3MQpPtxQV2G49Dq0Hj+gbn76yTLJ5GOjU1uLwbVfo9IXp5xwdwlWN17fQJRsr3ujMFMMkrfC0fgkCRO6j1/B5/5BTNVovvvvoqt7YqbtwqCejZGDgXM1tTJ8eVtTCtjgFEVQdppPBMZ60rp3TRglQeNRlTKiEYE+to2wbv471vt1OMngkrzaL/MfEsjCXQ84GtoiQINIymrcGWJZNr68hgSLHYoNKKvhgaqbC9X5EZz96kZCv3GO9paTDK03eevGlZPL9MmiiGOztxbZtvkjQyBjsT0oYhzQy93VgPo0y8Li8ONIx7Y9b7BbcG45g1g9lzrVQkb/rk46v8xOc/xsLaHNIy4ISO0vQM3MoMRhQNL5waVaACqdXkWnG3oTEinB8FbJAT63/hPXdHFQ9fPsdTl7q8efUuzz52mtHWXkRy1FN1sjUAxZEYszq2pugodu/rmh41g9GpWYKsLgGvIZZMOxA/IopxgJ5JecmP+MrBgIbSfPLJC5ya7/CHkqP99mjdnDp1kQSivtUoDXlR8F/93Bf5j//M5+l0moCa6Xhx/LvRu4r2ocSk3qWz8zx5vs1bt3cQ4Mc+dY6lbsbP/NK1md21en6JT/7Ag8zNZ5AKg8Ma4YzQMAnzWUJnYQ7dNLTSHBWi3IiyGpNGEhXdAE/AKTfLkk4XbQWIh7JyBIkYq9QmOB91MlsNQztJMKmmdO7f/CH+fdr3vUOFUlQh4Gvq2EpFOvRKAsraWBukdCQuwEaYnTIErfHK4F2F+LiIOOLkjun3WGjvdaBC07QQgqPVbOCsUKoompi050nbHXp7G1ShjIueMhz07/DV3/gl/vD//N9HWRO1hRBcrR0g9b4XlKAl4L1HJQlWBZTkuGpIlrUJqUWqCTLa5dyC4rHza5xaXMT5wJ2bN7h0uoWIZms/ELxjqZXx4UdXeXtzi9+5UhcgBiFYTQzcaKzWaAcjSgKBQjQGzXCwh/aBleUFtm+9zOHNdfp7B4zTJmPvaLcbTPZ3mV9YBhSi4wOQiJpRmHsUTkXnJcVHgTxgzgpPrkAVKq5swbjX45m5ORTCbq9ApTmLJrCQNjisXDx+beD7EGKUn4Cua7S0CrXjEdMIIjGRbFWMgJSh3oQMaIk6WE4cv/u13+IPPzrmwn1tOLeIjHchS9FzpwlqDpqnUVLgTw+g8uy8uc233thhTkCVnknlON1u0C/2yMd90vm5WEQvEuu0dMyFWRGUCiQ1ljsoSJTizvpNrFGs3n8Zq2KkLVWGUjlszTyZ1otcpT1NSVjKUpYfvp/vnP0A7dZZeq+9gHJDgjhKAojDJJpLS4q1VmCus8pg7NkbR42OYaFBNE40c8aw1M7oVSuM8yFZc5GpOFopUXgxVQortXaXNijlcVJGmz9N6cyvMR4csvH2a3TmFlk4fV/M4rxH23Rzm/1NHTkUhRPNIB9zdS+nEcZQKH4jtCiyLpW2M6M7fu8oEhmCpyodg8qx0S8ZjAoKV/DGZo+Xru1y4VzO089O6CYTHl07i6sUpVPcuHPA7v4gGhgIw0GPz/1Ii858ilKe3sGY/t0EcIzzZm3435N/kbovQFUFrmyWNBD27+SsnFvEJsIknyBvdQiTIXZZkSSW1BekRtFpWX7k9Dx/q3/A7tYmU4r0WWxVnTjbyYEjBgG2N3a5eOMmob+N7lUYLbSUolpZo3nfRZ7pbvBnHljAUiEEZEa7r44ONL05996sqeEicKO/yHfWHf+r/+SzPPf88+x8+22MMhwZCEdHdV6xt59FOF7QDHNLCFB4wz379+yCvFf8+reu8VfHCatzLd7/za+xPCfoB07hg8aEwNndijv/4Apmc0LpodipSFTCbk+o5hWfWZmntdBi+UcfRT+6gDrwqP0hXVeQ7WwhVYm+fIHl195iTi2xv7TCNG591P/oaPf7Q8ajIak2aGvYGxxgn38B+aEfQETwgxxfltztHXK4fQs/P1dnJ+VYgXqEYYk2oJM4/72gfMDkI6r+kHBji0MFg6IkSSecpWDNOazzhHqMGvhIHCTCRJlj903RaDbIx5PZdaj63okoqsqxsnoqZmIIJ7Ny7+HW6jRoNtsxACpCkiq09uSjCR96/zLXr+zRGyW02g2UMRgLWitKF2HgWRJ1dsrKYRNNYhWVi2RASWpQSuNdIHii1pwGglD0R4RJifiAXWxCrQdkGgmhXx1lH9TRJD++YgQRXhscICi0REN6UQnPZk3MzXW4fRN9LuGgZdjpO05ry3hYsbs+ZrRV8Nq3bvN0M+HHFho8dCpjLtX8yp0B36oKrr1whabNWD2/hrIm7ifGRJSINTHoqqMDorRGvCc4ob+9DwcDfuLDD5CL4erLNykrHwOUSjj0sFUqhrnm8iP3oVspBZCoGETIreFuGkWr2y6wOKrivqwChTbkSsjwFMR67dlwiLBR5gys4YIxeNFUolHGooyhCGWsoxSZKUd4pag4co4sikai0WnEr6l6XzjSBKshxDIVUZ6CimsHV6Jws8kUH//Ew9x4/hrqoI/ODH/5z3+UzZtDtJlm3+WeuIVixvSqaip9FC9dXedbb9zhzfUtPvDY/TMkwPR7M3mEev9SM9rQ+JIx0/pcuHi+y+piIzqQEgPaWauNhCgPc/dmDzEtCCbC361GScYDjz1KXg4Z1CiuEOIxtVHkFSTdkhEOXwf7jZ5mF4W7WxUGYXN3SGN+nrysSLKM0sX67yxRWOOxVpOX3zsJl+97h8qLxhnAexbmVnnsg8/yja9+EVUGtLiYFRCNImavIiXltHAv8I1v/CqNlzNGBz10XbtC0LGgmADGkGmNaTW48sa3GO7fYHh3F02C7S5gGymHu3diMbpSGElqe6Pgu899gUfe/zEe+cCzkRBBFKmK9JgFHqtsdHgIlAhda+nqgPgROlQ0uqdQQTDFkFdfvUKroVhoCD4UjEYTxkWPfDRgXDoqp9nZ2WXxYskrV+9w8yDHqDmCiZtlWxkQRTAx2zN0Q/pb2xSdFiZt0ZmfZ7C3zdLSKmfOrDG38Dlab92kd/M6VT4hdwUHhzssP/IhPvSDfwjSDEdk13MqFuKjomFiMQQVRWQNYGxgranIc8XNAgpX0HIxkuWDMCgNOmmztpBSSsVwT3BiSNE1aUNCUIpGUHhT16BhI+mRxPuojcUFh1cBow1GhKAVocZpWxF8WXLlxltcbadcuO8M6EmE9dR0sroBdq4N45L5S4vI5JC71zewOmG5kTC0BWoMq60mSIXKhwixHkppNaup0ErQ2NkCZ5VQ6KhLceetl2llCRfuvxxVo5QmVbH2agbCqI3LFhqrAo3Ti8iFP8b9do5nUs8/ee4WOrFYLFUV8KJZ7VrSTHOQK3ZGFQ64O7RIcDhfYZOUvBjT9Nuca0xYvq/FgavY7N3lzkHBmQv30QJe/fbXWZrrcvbhx0AcojKsh7xybN26zvJcC6MVS815bt24ysgPkcc/Srp88X/4h//fUksbGWmWEuoosPOBvHSUZYk+tcrXlu5nvOgYHYyQBA4rhVIa6k1oRlkMiNJkjYTv7hb4tEmrM48c7OON4tXNCa9t5fhQsXxeYRPP8pLjD37mLEZnSMj4ez/3Ai+8sB4LlVVg9bTlRz/boNGMEYLKw8bNAc99M6EomnETv8cHmTbv4ZnHUp6+aJjrVix8uAkNxWRoKD2gpRbmZiaG6QOYSugEgxUVA04SOKLGOpHGmbXjcU4Bdq+u8x9tv825beFwVJADQWnurJyBLOVSa4wx/shfUvcY1MeNwHpXnwVxQzREBQU6w0zZ0USw6LgOnehZNNi9N9y53cS5OjQ/NTyOn3JW0BMtm+CFN24eMpGM9iinHI7YkyZvffWAK0Fw/YqfuLhGv/IsXppneyPn7SsFc82MQaFwKE4vdtErbVQrIYhGq1jHeipJ+HONORaI9VbeF8xlZTTWZoMqs4i1QnF40KPIJ6TtDkFBIRC29wneY6sxy9du0t9a52vXXmA82If5+RNZTwmBg1s93t4ccJlzaF/ghgOKYZ+kmKCuv4RUGdIv2XnrOjuFI8lSHlxp0WlorI9rtiXwebfH+TPz3N3t87N6LWrQ1EZllmWMR+P61iquv/02VVly+vx93N28w6NPv59JEYM04XiE/j3copEsHOyNCD5w+nwXmyjaWcbqfMKXvnwVVzkmpVAUmsUVjbWawajCB+HMakZVeXb3KhYXUxqNhP39MfnEceq+FtrA8KCiyD3LpzskiSFUFXIwimUFCZhUR31BayJToFb4mv3MtOIuIyrUTtZRxVtk6Z1mNqKIbWIdMhoz8Z6quUhlltgdCBdWUg4OYNBQrPX2+CtnAk1p0FDCyqUurcUWP/nUGv+egvWNIVe+9E0mTz3MI5/+ONoKNjPMrXTQ7SZIoFUpsqUWyhqGGwdkK13+6X/xD5lH+NHPf4hGarh+/yL5KMd5z3C3z63+hNtjoTVnuDnsYxrz0GqwXHjaourgeFwjAkTpAAWVgcnUcQhQicxovafXX44Lets9tlML5SEH/ZIXXr/BXDoh2MAp7TBTOLEoch+4XQWqeg3qKs2FYFCVO5rb6miOR8erXl9CLAU5DsEUFeHSz7+9zlsvDulPJrREkZQFf+dnv8lT5y+gHpjOuKO5p4ymNd/CJPoo6BSic3I4LMgrz+2dHh947MS3jn6Tk8eLv9SOXn250/6FIxcQlMJYgw8axHB4UJJ2EkxdVzzWFTfz6DZubexRBseZtS5FniMSEK05TCfRWSlczMS7uLF12lFWaJwHijFs78Z9eXt/QiPT9IZjensj+gMYhHgvR+PJv+kj/Pu273uHSllFZ26JzsoyF9Ye4rGnnmBz8w7l4JDdjU1OnT6PSRRbm7fpNhaYm1tgb2+LoAxLC0v0hofsbt4lSTqsrCxSTsYM+yOWVpdxVUF/UtBdXkZXBRt3b3Przjpow+KZ+0gzzfbtdQRFq9OBoJjkI7SvqNAo1+Mrv/KPufDQQzQX2lQ6Ri8QRSOCqxDiw29MUusQFfhyQmYsSdomhIr+3iZXb93l0pl51nXFcFJx++4h6A53J4HFuXmadsL9D9yPryZcP7CRVrLdxWgVqdO1wfkIZbx75zoH69cZDYc4iZmg5ZWzDLdu8vQTz9JVE0Yh4fKj78c+9kEqF1hcVPzKL/xz7r/4QbL5BYISrIAJBgPk2kWtJOKCnGjwYjG6Yll7Sg97uaEQONMyLLQyRnnObq+sMeeK0aEmSVLmspxyUqGNQWnBOkFMxNUqBVqiXHCGwakSTawLMkmMiBjxWAXYpE61a7SGg/42k2rM+tgyuTOkqQ3ygYuR4e/a67CwgEoUklcwGeIncHM/6nTMKc2cTTlQngebCUnaxDUtqhgjaYboJBasEinxg0Sa/KpmHTECRenobdxk0jQE70hsgkGghqQadUT5OikmDF1FI1HMn8m4kOY8kd9mPH+KdpIgwVBoR0gUCyun0NayNzZshxyfa7qdjIM8shtGqkIP+YDhxvNkTz5Ed2mFB5sG5Sb8ztsVE+tRwXDntReo7j/P8HDEYLTNBz79+Vpbo6SlKxDH1RefI4SSyeE+OuT09zZRxe+RtXgPtLTZIG00EcD7ilF/wM316ziv+OwPPER3vsNDK0v81mtvszMa1FH5qk6WGFRt7AIorVg7vcw3r29xO7RJ0hYh7B8VRKto8IsCpQOFP2R79EWayRKGU/yBH1H84Gcuo7VDmVhLmaZlHVHWpDYwv6o5dWlCUEN2dprcK1I1lWcNPmB0yZm5MekwR4qCYWfCzp1dGGmCEvoharfFWaoolTAeCpnTzFkox0P2d++yurp2jF74ZJv5IPXvzntaUtFONCmBHoptH6OX2wsrdJXnQb1LhB0fy05MU0R1X2LdpKCdiw5TEHwlKN2ARCEYrNUo5ZEyJ5+Mj6AvU5avAM5FDamyjOT+Zgp5QtVGV2zWwOpyiVLCwaFlPNYED06BvrjI3KUVPnU45ttv7PGFtye8ReDJzND68Cm68y3UrR53b03427t9bqlApTz90tOz0MkMmfOoOwNk5CAI7cTymaUlboyHVN6jH2nyzJ0er/hTM4HMeCfjH8PBiKtvXyE4T4YG52OQqTdgvL3LQ6bF2VHK8OYVdjavolWE+FktaKmz1CPhtRcP+W+/doW//tk5kjsv0NoZYoqA9hWHkwkqGArlmQSNFoXVlolJca4kHU7w7TKuVfmExuaARr9ELa0iJo75JC85uHab+blWpAUPgZdf/BbbmxukWYPDvU1+5wu/wM1rj/FDn/3RetK+d9ePWZvhuCLZVJSx8Hzs/W2yLLC+OSJttCkDSB6zddG4DrFeSog/g5/BkCWE+A8iEiMItSJIdHyqQI7CZprGoo31JkUJWIKPAZ7JjmPn1UPOf3hlFvGQe8dbjpwrFTydOxv0t3bQ4wHXn30K/+CjaBdQakDphZu7B6Te42/vUpYVikCpBN0rGdUseFoUfuJxo5y8P4p15D4QXHQutNYEJ9gk0sfHpbHWoMwLnnn2fpYfWkMJPNpRhKKEynHw5h0e3B0w8cLIC7vjAUHatI2mE5UdI9nV1FlQ4DQMjGazkSJoFl0MXMxyGVNILULflzTTjNWlLg+ca9NtrfP45Xl29nY5PBySM6FlWvW4xbH0tW5TTOdQs4EeowGfBUujvVW5yO63c5hwODSx7ovoRAQR9jb3GfR7+MGIzzmhtQAug1/59sv0Nnb4sfc9RrvbipphxxyjclKicjW7p8FFohSDZjlZIM/DMSTB9NLlJFxx+oscuVwydQohIp7C0fxRxADXpPRc3e+zbwXrxrSXDCNdMSwVo6Fje3dCf39AplI+9LFHeOXVa/QOB1SVZyHVbG+U7B6OcYzZuDrioafn+fKv3KS70OTDH3uAQQ9u3xL4kGbz9iGtZsr17REHuzlhrcEUNB5+DymJfxvt+96hspnl9NqDfPjTP0Qz6bC7e43PffJHePP6d9ne2OaxJz+OXszY+Rf/hJXzj/LE+5/ld37z52nbeT76Bz7LS9/+La6/esjSwhl+8Ed/nJde+V2qV97imU/8QSaTHb77nW/z/mc+yqllw8/94s+jCmH5zEN87GMf5u0br7G5fo1WY54PfvrzLC+0+KV/8tMIkKARL2yuf5fnv/xFPvFH/ihGxwc48eCqCowmJAZfxUXFpODGAxI3Ri+cxhhQkwFvvn2Vkddc2xtyNmQ0um063Tbd+QUWltZoNxJyZ9kb5lw81aE7l2J1YMcLLiisimx3WimGO3e58+br5OMhxiZoLYQStrc20YNDjPUcDAYUyVmUeLzSpInH9m8R+gcsnVojjVBlJKhonKiYi9LiUTpqg3kDBEcqDi8K5xUTrekkQtt4hiNHv1dQVEIhCl85nMkoClhsWJCSuxNHalOwUtcUKQxR6NcoheAZjA4xPhpc3ZVTKOcZTw5IEZLuCmiDJ37eD/q0U8NzeyWfMV3OZQa5cp29w5y5boO0HamTq80hPhd+6Z+/xk+9sMfHLl4glyoSeGjhgYUWhWqyEzxXX36B+5/+KCqL+6iaZiy0UBCwStcaTYJUBdXBDmlusb4Em9QQVEUTjavG9HsHDDbXuXHlCmU15GMfusziwiLz119nUOSMHkpwWjMuc6y2rJ49h0paDPNIOBDGI/YGY07ZCxRiI8lFbcAvtDMyrSknBZtDw+s3D5gfvMgf/NgneXFXcf1QWJprcabbZK834PDuTYrhPmXwhBCzXKITdu/cgOEWxldUpefWq68gjTf+x1wG/n9qv/zFr6G0YnCwj0kS8I7JaMTC4gJPPfgQnVbG//vv/iKysMRr371COS5othJ6B4eIDzQ7XcR7hoM+nVaL+cUl7qxv8tyrV7j00AUmztCbeNLEALp2pqJR4aSi57YYyl0Ub0QtmkaMWCa6Q2IXj6Vm4o/FuYTHnppw9sIWLzy/xNb1xfqtGW6FEODihTmW5keMdhSrixYkoEXTMIrOfIeDBLoqoLWnDNCXkrs+UK17fvAjD/J35gx/9e2rfOlXfp4/8ZN/ntRajgjaj51uelYRgii+8eWv8vH1a6ydtkgQ/mnvkK8OK6w1nHvxS/wv3U0Wezc4+ESDpafnqaV8ZwesXZ3osAYVI6cRH4MKGnEJlAbRHZ5++BJpAgfbu+xtH7I3KenvDOiuOUBTVYa3r81RVao2UKeGQ3SqVM10VdtBzDXjZjzQ0XB1tVPWz4W9wwne5WyIsKdgQMAFIe9VhGrE3rUhLx9UXPMV+0BbCWNgyzlOD3NaxmIrh/K+zmzWDqXShNJhX9zANVewi4KWI8JnEfBoymLCrbeukmJ4ywmvDXM2xLNXjLj9lS8jjSbtQlGNxjw9v8RNHWuEO1KgfI8wKhi+YpjsQFV4tANZWiLhgKQq8N7z3c0tLrbPY1pDUjJSlbLcTtmVlIOdA85N7jC/scfCuVXOvm8Z9dWXybpzmGJCmWYIiiIvGA+HLHQbIBowzM8vU+ae+x96kq//9s9z6fIHeeiRh45Novd+iipOUyFpROie0uAKx5OPLfLyyzvsHIAYgzFCoxbuFomOvFaqJq+CNNMYE9cAY8GmU9SCQtmATWMd9Hi/z3h/QMDgVU1XLaC0IQTwVSA0FvGTIdW4to6JrLyeKYy37sTUBgesK1m7eRM9ySmCR5pLdGzKQTFhHBTKC+rWPma/h7p6h4PcYyTKfBzsFZixwweFD4qyqBh5KNF4pRjsV8hhRaOdspSUlIMCYwziAniQKuAmJUYp0rbBBE81mjDZ2CRMHOIDaTswv9akt+8YrZd4IkTNoRgaxV2lOTRH9ayRwVBRaU1JhAPH5TdMEXgzJPGd8Yi3JttoOhijSRNN1DH3NFuG3oGjX41p6hbUrozUa8SMj2jmsMgsa1kr16H0tGbe4IOw329Ex1sdhU56+31+9599HZ3nfEYLTxlPdrbBdRX4v6VL/ObOHj/1sz/Pn/+TP87cXGdKWIhAJPiYdgTwLqCVYmt/xLDU7OwXs/eUIup4IpgaQhgd+/rvI7+sRhDW4MQghHAMBi6CaIPznr7OaSwbbh4MaKwmvPjiLV59cwNRDe7cOWDtTIeFxNDutvnt33qev/3f3Obxxx7gM2cepxj1+bt/4zcje6VXPPeNJutX+zRalltvb5IttDn3wMNoZXBliLDi6hDlZbaDHHXqe9O+7x0qBPLxPrduvcX7P/CDfO07b9GfX2Z/cIDSsLW7QbNMcSEwmozY620TvKeUgsP9XXweMcZBCsbDA8rRJELYkgTxGeRjivGEcr6N1Q2aK8tUriDNUlSakCnIlOHs8n1gd0kCOGKmBKMQVfDcV36B+x55jLOX7qNSgb3hHi9+4wscbNxg7fRFzt7/Ps6du498oum4AVpnSHceVEXlFSOxNHRgTieszLW5uDaPc571OzskScqwGLA/MrRai2wPRjQaCc/ct8BLmyN2qgxrLaUEVIBe/5B+XuJ9oGkEyT2ZJgrAGkNqNRNpE7SlmhSkqWdYCeu3B7Tbp2gszBEIWLFUGqp6cbJKIUrTEMErwXqFCiXaaCYorCjaVrHcFDb6Ob4MtBtjjG1SeJCqpHRR28pqzUKqCJVnWJWoJCNIwGhQQWjYhDJERsfDjWsk+ZBWM6NamscNRtx9+2XOr6QknUW0sgQVo6Tj3g7KlRw6yyR37F8bMUozrt7pc/nSHKfWMlAVb/7mNfRKxkvrI8oqZ1A69itHMxNMM2Wl1WR7r8fNnTtceekbLD/4APPZOVKl8AQmRR/vhNRaSBsYnRCI9PCVKxEfiSoaOhqnWikSCextrLP+rd9g0O+RO8fZSxcYHO4yuj4gdbu0rGHrYIDNWjQbCYurpzDtFt5P8CEw9sJkWNBIDMPSUwwGLGQjchIKH7hvXvHkD32Ifh54cSTsbe9wdnUZFQIPzHl627v86c8+QUMZrm4POegsc+vtlyl9g0RKVs4skmUNFtbOszkccWo+Yb/fY+KFxGb/Iy8E/+at8IL2gf29Q07ffwlcRbl/gJHAgxfPcdgf8/zL6zzwVIvhMGfcn5C1l5hMKnwZSJoRVjMZ5SQ2oXKeSV5QVZ48zym8ZTAq6DYNWgfuf2zI2ftKsjSp4YK1m6JCvRfGmGYIfapqQitZQs9o6WON4EKnRat1SG80IZ90OLybztjXYi2X50PvW+bigiFcKRDnUC4gZdw49VxF53+9xoV/kdLc62PxVF7xS0nOR8j4rBGWJQqUehfx7jNYyD1pqmkRPhJZOId7+yyMJxRlk7HX3Bo7kipwVgx/paF5+HCDGzcPObjQZuXpuSNGp3rnVqIY5RlXDlYogkF70BKj9mvpIWfatVZOEMJgm6LM+Wc/9fe51htxTgLbtyd0l1NcYlHa4J3BuWMcijXN15HJFaE+rjRcv9plkleIjknFygljUfzNK1uUbwo97dnXikJp9ivHOSu88mu32Z447pSe12v8v53C9jS0lxI6n3sIeewsYX0H9odIwyAm1nN1zy3gLq+Q3N3j4uOOv5Bci8b52EEp7OxMeOHtQ8QZ7gosZy2cEr7dH/OKd2BTOr0ho8GAl8RQaEvbpLRNQiKGhgooP0BXBar0BO9j8AcNqeN0O+WZc9DvTxCiBlirKJivKp6wis/0hvw9p2k9colHJgfcemWf5rlF7MGE4Y1DWj90jo988+tIu0tpDC80u+xklj/85Dzh6h1Km/KKKlk7s8TplXlezRp8+vJ5irXTR5NIMcvyvlebD7HeqdXNascGum3F4oLlt7/Wp5Q2BMEmiiSNQRUJMN9p1DWTkCaaU2st0BDwzC9bRGvEVgQVaK0GpBLGuz2qfo54D80mThsmhZ89mq4okdxhm3MElTA+dEx6FUk3Csu6+oGNUDOpsxHx2fCuT1+NKVSB1yk2bRMCjMsCV004GCoka1CqEb9yc59FSh7IPFcnwvVbh4iCkfeIBNZalv/gww/RWmjF+ieJGQ6ROhtVB1J8P8eNS6rhkOFEqIoSnQSGO30G65uMrl3HlR6tFbpjyX3KaBLqPsVgcQXcTVI2k5Spl6SI5E6FhlIb/Iz5c3r9tXKNin06qEbohNq51RhjCBIrnZRWiFUclCNWsiU00yBShEz6Osrk9dTRihmvaTlIEKGaeKriiFE01FlJfNStwweywnGhMvR1yo62/HriGax78lBwLa3YsIq1jW1evbHOx55+/NjVHMsu1U1p+PqLt/mtl9YZOXj5xi537h5w7vQiiOL2zV1+9jee4099/oOcP7vMK1e2+Oe/8yb/4U9+nFbzmEacmq6WUWw5hOkZp+fUVKVnfz8naBhNKvbujHjp5S1efPFu/KwWtrcOeOKh0yjReDK+89JN5lYWCQ4ajYTJqGTYL9DK0N+foA2MhvD6y9ssnu5y4eFL+BAHN2mk5GXAO8H5EO8HMhvb70X7vneosvlVmkurJO0lWg1Fb3/A3MIZbHOFpDlHp9MlaSg688t0u02KqqK9ssRoZ8hw1CPoisQ0yLKEb375CwwO92l0ljGTXeZtQaOreeHrXyLtLHD29P1sb93AYrhx7Qr5eISyCR5opoG9cR8STaZanHr4EWyo2Lj9NqPROj/3U/9nHnn/J/CJY/P2a9y5c40wGGCzJlnrlzh36mH+wGf+MCxZSua4dNrhygHDytKfCOMSbBajLKNRwc7BPjdu3qVzfpfJaJszpy+wd/cG4caE5oOP8PVtyyRbYVCMWZrrkgiIVjhrWG6miPTx2lJkGYPxkKTocemRR7hwbpHtfkWY7FP5FCOB4XifjY07BJNx5+ZNzj/wAJUKJAHKOnKmJeKRDQErAedyrBLEa4I2dFJDy0K/gIORI7OBcjyhSiyJsoz7PXbdhG4rYySaYtCjYaHTXGXockRZDvs9xAsrS8uR/tsG/KiPvv0mZ1aafOfuXZphyObNdc4++zDeVzhjUUETgmPn5mtQBULl+Mr6Ab/81jYLawu8fXObP1dd5E+f71D1+nz3zpDenZw3Cs9Qp1wZDvDOoceKcVXxU29s8FZvyLj3VYb9PQ42btNevoDTjjQI++u3ONjZpNFuc9+jT2EbFlGazatvstJOsL4g37hG68FnUFqRKQhFTihLQjFBdMLq2VWUr7j+9h1u522evlRhxZKPHc25Bc5efABrUgpXoKVguHuX7vlFJk5oNizj0vGFX/hHfOSpi6xceowbt67RXvK8efttzj34EN+9fZ03vvlFfv1wm1NrK1x+5v0YZXjtO89x4/o1fuRTH+L0uYd4463rjLI5KudYubCKSQxJkiFJhs/aVJmHqmI+Tf7HXgr+jVvlHa4o0FrFOZNHxfulpXm2Nu5w8842VTVm+84G5XiE1YpyMkG8x1iDBI+vKrSGyleUbsLKmXkGvTG31rdodBaQquJwcAChz8d/2LC2mrKw2CYf+HeQYjDbbH0M9lCLHtbGgCIymA4mY86dg/PnW3zl1xW7m4q80JENMwhalSiqyJolDlUoBkPHd6+O+MSTQvMxQ3ZpifBNi35zizmb4RmyP3EM1g95EMNHG01+Zn+bm9ev8vDlR5mJdh8fwLoewAd4+Y1bpFsHHB4M+L8PegzRvOkCpVa0jYZGYKsq+EJ/xMfa88cwJdNoLigSBsUcr44eZBwUkhfgPQ740Jzh3NwhAPpAcfOLz+HHBZ/vD/jl4RCvMvybFXeY47Cd0mw38Aqm5B0n0n3HCq8RQUkgBI2raxoCgXEVte1ECdtKyFFUIZI8lEHYCfCcC2yKpzDgxXDJpBy4QE8VLJ7OuPgTjxLuO09pu2Q/9mHk2nVkf4B+9n6YjFjMPTQbkOQ0ssApM45adCagE8GUI7Ir65zRGR9JhI/Pz3NLCUs2pZxUbEtMBCVGM0IotWboA0EZMhSp0ejDIapfYaCW7wCsRnUbrJyyPJWV7Ny+i64LxROJIuZSaX6tX3CQVBQXHiHJlrjsLOahBXQT9GNnMMsdHlqzdEyFVwVr55bZ7mY8daFFduWQsHiW/9ZN+Pc//iDfvvYGpzLFHzvj+Fl3zCD7Pmj52KFCpH8PvkS88IEPLeDKius3xzhvwUfWv6jF5CNLrYo1mWlmgIB3kaERFfDBR4ifiSA2VyZ4J/x/2fvzYMuy+64X/Ky19nTmO9+8OWfWrKrSXJIsybNBxtazAT+DeO5oN9FhvwAMAf7DPBPwCBy0AQf9wpgI22G6ceAXmOb5YfwsbAvLkqyxVCpVqYasysp5uJl55zPvs4c19R/r3JtZMtAWLfeTXvSquHXzDPfsffZe67d+w/f3/RYHBTLyNLoxPoaiBK1tYHck2AeYU+DbmuENzxvDexx/J7SW22QnlgPp0GFgIQ5rKB7rdnm2t8sszWmmy7yn2+TKvWscDPaoTcnNveu4fok9EEyt4Gys+FOdhImpeGOm+e4zPS4MK6YV9JoRj5xaIeu1QlIRf9T3KaR8gCjFgdF85vef51OfeZWVhiQVnhc+9RV2LmzSwlNoR2FcSHhLcBKQEvVwTnvOZhmCHDis9nigEoJr7Qbez0Fh89e9Dyx0gTfRU1jH7ekQkUicB11rhtMp4/GUza0BCwsOkXhmRUltNVmIvELg5AMMzotQkdIWDBbtLYlQbE5rKudJ58LLKlJzSOi8POYtvtQIr4mE40MbDc51gqzA527NyDPL+77lJLtbB3Sv3SWXiuRQkPloBoq5SXtzsuizr97gy9f6eDK+eH3MZ1/b5iMbi4BgmFd8/MJV/vS3Ps7pjSXu7Y/5w1fv8NeKilYzuY8W4D6GQHjw9vDA88BKCibaYfIKqQTXb+zzb//NVzD2gXPzHmOh0iW1djz2xCmUkHjjMXOW2ePdNief2SDLQjAnJOja8cILd0kTRSOVaB3WQhxLSmO5udPHzWY4IEsiTjb/5HyRP5GA6u7du/ztv/23+b3f+z1msxkPP/wwv/qrv8q73/1uIETtf//v/33+xb/4FwyHQz7wgQ/wS7/0SzzyyCNHn9Hv9/nrf/2v89GPfhQpJT/0Qz/EP/tn/4z2ISXrH3NkjZRed4OHzr6VfDZGWFg9cZJZPiJOU5ZPnKLVyLh05RKrqyc59dCjTIspJt/j5ENPkdczioHhoUfeSlnNuHX5IlmjR6vTRepdGkqSHn+EjUcfQ1VDBv07ONqsn3iErNhm8+JForTBOx49wb2bO/yBlMRRk3e9/R3s3HmFq7dyfKQReoftzZcZDO4xHg7nWQnwaGblFtfzEf/L8CZLrQa5T3nbk+9DqoreypPs3HqZ8f6AVG1w6dIWxWCZExtLdJph06v6JbfGl1g8cRrjQcUt2sstUi3Y2drBRAqLwCuJ8hA1Gqx3Fkhjyeu70FzqEh1MePT8MQaDPtdv3+P5L32Gt73t21k99xiLepfnbl8hyVbZe+GL3Ll5FYcjazWpZgWxdoyrCVGtkaminTQodInTmiRr8MSTjyM7DYooZTzNsbqgrqY0FxWNhQYqiRlv3WU08yS9FuNSMdi9R6/VoHu6jSRGehjeucysciwvvy/0okkwxjC4d4skF1y5M+Dxc6sMdraZTTaCKKEIelhKWPLRlNxqpiTs+oiximhFglY3Y9fH7F0dMtrc5XObM14tHDNrGVaGapLjtMUIQT4r2ascs2JGPDM004Q7rz3P0rENGsdOYPMJmy99lvG9yyTdHuceeYJIgMDgBnucWkpZSVJ6dkpbBYag1JTcvXEBl9c4CYtLC9Ta058UjEcD1KkU7w1CW6ZFRXNhhYODfcaTEd5VpFlGtX+P1vp59Fxc8iuf/TS3XvsyD53qcDzJuPbip3n0W95KLprc3dzhE7/5MRrNlLyoyPfGHDz7HIudLo3lRRbqMxSTihdev8Tr17cgUvSWj5Em8ZyZSYCCrYN9oliy0GtznNk3rQ2RsaTOA9V/Pp0FDbAkpTCOv/ZT/3fy2iKTFgfbW9T5jONnTjIZ5zhTs7K+iMcynk5YXFkkz6c4X9FuNynyEhVLyvEBdVWTtiSNVkKkKlQUk6SSemb5I1o+AOKQGQ2c10gZPxAKCCLRZLFxBmM1XtR89/ceMB4KPv4HNfU0ZlY0cL7E2CkWDcbia8ukiNjs11yvI1QUqIrFmQ7bx3MaWxMa1rEnPJ/enPADKy1yPNZ4vvzsF8jHE97xzDPzrPIDgck8Lerx3Ll5h9XplNI6PmkFMyHRSdiY7wF/8YVrIBxTBD/JW9jdXJ4HlCHz6QFhBSpZZEZMJTxDLSjqAKV9uj2n/nZQFJY9bUOWn0CUoICH8oqdiUd5i294DvlDDi/vg+7GYf+ZB/JaYI1nNHEIr/ECtp3EesXTWcxpAdrB2HjGOEa+phVHvG2lydtSRZkbkljyW7s5Lw4LWlLSeO/DjCvFpV/5AkmvwTv+xyeQp07gsxi51oIB+MShrEMtJtj9GgeoXgKz0O+w2G3yPY9uYEYVq50EjODbehkvDyq2as++EExwNGToFY2B1EMiJTECKT3qc69DXjAdOEYjgxMSkIgoIbIe88Wb+Ou7CCNoRJJECd692KTnBAd4ai+pmwuIH/geHv7wDugCISKyH8hAKhrf/ShyLlOytLyG8BXi7jaM9yn6BdPxjObqMeR+jhIJ16tFTOSCwPkhacZ/RWT1jWRH6qlBaA14dDGByvP04+fYPSjZ3ilQ3UBXXY1DRVomkDQ9phYIoWiuepwZkt9bImka0pZhejemGMP627ZJGpbJ5ROUMxsYhrOY1nIDZ6AuNOXEYJwDZRGNGoTAVAOUT4lFh2JaUY8gSxTWhF4t6TUCiynuoG0VgpzygMo7Su+JVUQsI6p8ijYl3paY2U2srKkQKOUohWBTW7yCx1YyPvz0Kj+UxNQ2VH8m4zETC9mkjyYKvVTezzWSBM569nf3yacjDg5GzIYFwyjhxWt7XL7b5/b+BIWgNKEK5AAnLN2NFqeeOIVabwfyLfxRtftoKs3XvZkD7+eTgplRVF4wE45IhWRLbkqipsV5hTOOWlsqKxn0J2zvj+n0HFHmmeWerULTSkIPnPGCJIKAtvPU3rJbW4wPQWqq4NJgyrA2tFoJkRJEkQjEQwTyIe8FlXfUpcLUMC0dD5+SpFHE63cqFrox/+0PnGdwbYEvHUy4WTtMpanLikPZGickQgV2vLBFC3COrnA82Q4wz74JlRzhA/TxVn/CoLL08xovoHIGYyuMMUcBqpsHQxxe2cPM1wPDIxlIwZ6pkaXn+Ze20ebwtTlXn5cBuipq6qpkdblHq91GRYr9vT750LKYNXjPM8f4yqsDvNN8+PufJhJw7doWT7/9BOudiO17oyAKHEfgQtJhWtWh1urB/gmCZb7uAdVgMOADH/gA3/md38nv/d7vsbq6ypUrV1hcXDx6z8/93M/xC7/wC/yrf/WvOHfuHH/v7/09PvShD/H666+TZUHd+Ud+5EfY2tri4x//OFpr/vJf/sv8+I//OL/+67/+NZ3PamcpZNVExP5kQtRos3dnE10V9LqLHGzvMI4jOnGXMp9ysH0PUTnaWcxkexdZRiz01jnY34NI0lpepNVaoipzqGp6C8fwyRJuOsbWFYvLJ6iMQFsPtFleO8Vq9zgnujGFKFjuHUNFKUsNR9VISLyjVoapteS3LyKNJ2u0qIsS6wXCK6qyRtYTdsoZ1XKPSHZpZ47Pv/h5Rtv/gUI4Hj/zGDdvvsbWndsIp/jwd30bjaxF1FvizOoyymoWlhbpDw8YTEYkmeLp0y1ee/0an/iDjzOuBIutdRYalm5rmX2vUFrSW1LockxpDTNjuXLjMl984cvcu36ZG5de48mnnuHxtzxG2uhgvMCVUzZvDRHes9DrUtua2aTEO03aaNImZX9aUJsaJeHk0gKtdpsKiY9TxtWQzMOtW1ucbW3Q395kdWWVrdu3GJaOy1/cJBMwzXMeO36ccV6wtHGavXHO1qVXqbTFPPokrt0L2R5dkirBE2dW2Ti3Qqeb0o4lV+8OWHKWTDgaBLr68bRgIYvodhqcPbnM9x/r0mokIE/S7aRMB32uDRzPDXN8q0UjjVlNFdNc02i2cDIYSKskWSPDWkMnajG5/iqzYxu01zaQjRaRipjlBVokRwxDaI/TBYmKGY7GPNlr0Y48MQKtNbf3NolUwsLKMpOJZlbmiGJM0b9Hvx9jVyJKUzP0YJUkL6bMZjOiRLB7Z5N0WlKdfAQMXL98iS998jepzYRyPKSRKt721OPIyHHi9BmuXLxIXeYksUDnJTNkgKZVBc1pl2anxcLKKj1tudIYMPISoggVBeFpU2ukE0TeQGVQOCaj3W9aG1JOJrha45zDGY3wHl2UTMclkVSMh0OitiBSCmc9+XgWqJGlpK7qQHygNUZrnDbUZY3VnrqsUVGErxx4R9SM6a1Dq2NopJClkiJz3Nrb4/z62lzP5P5GdZgdLPWEpkyRh3Tg8yBAoZAqwmOJU2ge8/zwDzuuXpuyszVFdvfYdVPyTsU+llppbt4t6WuPWmmTxIEgQx6XdH4qZv/nbvH0rsEMYS/zpK0mfyXt8HE/ZefePXoLi7zzmfd8FTTrfmA1GE7Z292hEQuuoJjEisornPB4JDKOEe0mURLTyzJenBzjyvUeAndUofIEeN+xjsKKAuMls5lB20DnbB2h6m3gpVcGfO7yDoL7emAeR15orHbI0lIXFqvmEdXcu3IEqPKDzWDeSd4YKoZ1YNdcI2gCjW3odTrWjDg7hyzdqB3/cVYwc452BMdTgUliokZEoxMx3JpivQLvEAuWht7mkUcVUnlENcBrg7cakQmccMhTG4i7faoLY+xmjmwoWE+QY4O0oAtNU3tUoujEklx7OkJwICVjKdFAPXd6lPUUQlDYwDoGEucVotL42mIrNxdSlUQyxTx7lb3ffZ3dl6+Rm9B7txQJIuHoxRHVqCT3Ch9DaTwiSuDGFcRsBEmCUgnuoXejhlPExatgJfatj8O5DUgayCVH/6V7jCYj7MWL7F2+TS4VX6olxOJ+lvs+guiPPb7R7IiIwg/z5MDxkwnHNhb55CevoY1HCcGRdtd86Qgp7uuAecBHqIaHGBQJSkUoIWi6JTJv2POhorV8qhtEbQV44Y4Y2pwP1EhChD49ROg51hQ46xj1c+LGGG+foNy9zUI6odlO2M2vMBxv4yyMJg5nPVKEKSkAAQAASURBVM4HeRjnPX6+/gRzPRLlUYlnoWnZzR2/0a95x6ke/91Tx4gjMEKTxlBPHcZaDJZyssO0cwwnQMQxQgZ7pquKFz7xOXx5wJmHVlk5+QSfeu0e/+A/vEgmPMZB5QRjC9IrjieLOGs5dWyNR//8+zAuxs6lSwSeNyvaHY75c3O2D+PmtuSBObedj8jainricMaBFyRxQiQEaSSOYH85gpszw+JcOy+WgjNNy92ZZGbBxYaDyuMQGAtCGvq2pLcQ+ucOtb8E0O5EpGmE8Jax8NBRxGspk2ttrm5rpPDMjCPyEkYGU8DdGja6it/4g2cxN2+z2IgobZB/8EjGBi7kmuUsIUsk8vYO//StbVQs+MU3ppTDKXfv7BMryWhvCNbRPxgz2R8x2O3jdM3Wdp9eI56TysBkOmfOm+v9+CPInw/EGN4HGZei4sLzN7h2cW9+1Q/XeAggu0sNNjYWcc7Q6TXRuiSqNAu64MZruyy0myTK8/kvXMEj+d7vfzwEvAp+9P/8DG9czvnFX3yeb/22VYSMiUrHmY0WkQp9VULfF3P/kxhf94Dqn/yTf8KpU6f41V/91aPnzp07d/Rv7z0///M/z9/9u3+XH/zBHwTg137t11hfX+e3fuu3+MhHPsLFixf52Mc+xvPPP3+USfrn//yf833f933803/6Tzl+/Pgf+3wyW+KKPVYakr0bt2jpIdPbBzgbsRgr9N4tfCRZbkr8bIfBtR1iL2k1DdsXPsesqknSBsK36KY9OvRYWmgRDTZRpmCt1cUnhmk5whhHNxFkKx1Gt14hbiWcP3OGR8+8hS/dvsdnn7vNw2fPk0aOz372MxzkfeJuwmx3SpYFXLUBymKCdQ5vakw159t3kjTLcL6m0YHh9AYH/TvMtMVWlsuXvkItHKkQuMrxxYtXWFk+Ta/fp5vGLCx2iSKFryoiEhpxxqxUtBtt9jdfY3t/h60oIZKwsriBBEajEYmIQ0bRVnzlK1/m1vY97l6/xiyfUlYVX3nx89y8fZvHnvkziLqk6u+QqQSlFK0so5Us0+tUyFgRxwmJIDBxRbDUVqwfO0nSWWKytcnN115h52BIr624ef02T5xcBgztDUlZzkijBmY0ZOPkCpf3RtTxaaaznJ0Lz7O3t8tsNILKMtq7R1SM2Ny+yfb1l3mkKXnrmRVmmWNvmDOeapSqKe9eorO2QTkZsrd5jZVMs5i0ebiV8P7zTV4cFCx0W4zynElRc3BQkZcKFbdQKuOdjy8gveYzL+3ggF7aoRnFGCdIZHDjlIRxZdgvctZqjUMhk4S01SRrZAhX4a1jvH2b6d4tVjLJYjPl8V7KWttQCcGW1TSrMYWxoINekRM1j/UkfpxAXSKyRZxto70k8SrAkmyB1hEpllOp4qXPfJR7JmK8swl1TiojxtMhmTK868knePnLn+bRd5xhmE+RCoQ3xI0EQ4lyLUalozY53SzmRCui7STFSsqrgzFJOyVRERjLscUmyZ0pj2clk6Lg9mjAdDr4prUheX9CFMUkaQNdVuAsVVFwcmOVX/hH/5i/8j/8U166fJPaQdRoMp4WqEgSpxmTaQXeESeKfBroi8ejHD/X+rEzi6lKJA5bTPFaIISj3UpIU8nKaor2JkC8cKij+MTjRQgyFILKVkgMiWoeBTReeIwrqM2ISLWIZEqWRjz5ljZPPGGYFlOkUPg24CPacYP0+hg5M9wd5KwttOk0JE7AifdvsPTrS6zu7DEZaO48V7D32yWfk4ZKBIHuqqgYjaZ0221kdL9KdXjKeVFy9qmaRjNj6iNWJ45iBk5LjE1ZWFxnY/2tZHEHIYJgaX8welPmeL5Fsz84qiHdP46DYVSzt2cYDeHOrmVvpgnCUh7rBZEA7wLbqLWefr9kOBe0PcRWaicYicBOeqgdY7yh9p4mBCKd+SlVXqKdZM8LEgKblwEeizIuURIj6OeeUX/GQlOy1y9pOcf7UslVB+w71FKH7jGFX14AqfD1DJ/X2Jc3wXvcyYewty+jDmZ4a4icYHxtSquhqLXFVJZEgFeKvDJ0ZMKLk5rbZY0WHg2UxqHFXFzdeQ50Ta5NIPEpHHiLwJHMYWQIhagEe//hGrsX93g4idmjDE6jF8yAcQ23q8C+ZrynMB4vI6RzUMxwCxuIaoJnhjixBm/cwM9q7MuXEM+9hPQeYT2Nh5cQX1a0n3qa8dVt1rOEE8ttro1rjFUkkhAcHAr7/DHHN5odsblHazfvhTSc3OiQZg3euDYKjfZzYpXDhn6cwFowJlRNy1rgyoxy7ImagkgJjHZYL5iMEqpZTJm7INZ7CJG1YU5aZwOBiQSR6kBQQXBovXQ4CqwT7O+MyRZzjCkQqkZJjRIeJUIvr3Ge6bQOgZ+CtoDYerQZo+sR3hcI6QJUMfYstg3TMlRYI+HQ7RqNwNtwbNsBESUIJdgZ3aHuSoSSeNfkYJKh59DpteMLtCpYfHSFZjPlzniKvjvku5oJAkfuBZ8tPHu9iHf84AZOaJqLTcp6GyEXEKKH85777vSh9tPhOKyyHCZW/FHgGx5aRtWI9UWB8w4zv65KSBTqCJYphCRKHHfuFOznZt6z5rkmHMYJauvmzMrBPmsb7vWsNshIIeZVGzGv6mtniCOBd45iaogiT6xgZ2mBj71xm7LUGByNWtH/5VdQ3mImhmfOxAzfKNi+u097oRGIN5zAO8mosLx8b8IzWcLQG0pvsL0uiQrdc3/wxRf57edf5HsXG6RC8t5Oiy9+6lWiV26wYiz/zUKDX/rXn+I7llq8MquJgZWZ51QEtzXgQ1XxQS0zT0hUXb5wh1efuzvv5w3BlJSCMw+1Odgd811/5mFiY9B1hSDG1IamqXh4VvKpz13nfX/hDMobBCVCpWE/lKAiQRwrZJySz2ra3RSHYjK1TIYeJ4I+3lLyNWZlvsbxdQ+ofvu3f5sPfehD/PAP/zCf/vSnOXHiBH/1r/5VfuzHfgyAGzdusL29zfd8z/cc/U2v1+O9730vzz77LB/5yEd49tlnWVhYODJgAN/zPd+DlJLnnnuOP/fn/twfOW5VVVRVdfR4PB4DodFwZfkEjaU2l69fpCVK/tKHHuYLL17k2niFt661iIXhwp6hudgjjRJmVU0kHTMVMdra5uTSOsurC8RJhjElk/4OzUQQpzEzM2N99TwqOc7MVOzvbXJv8wYfes8T3BtX1DLixPF1nN5hqWXwXtNIYyI3ZjDeCmx+kUSXmnbWwDuHtgI7czSaXY6tbCCTiMFoC9kWjAYTilnFYO+AYjxFJgpdV8y0Imk0oSFAplzfuspoPEWkMDjY5s9834+ihaAykkYz5oVXPs8bWcJnnvsU2/v30OWYSVURy4ThaJ8614Fdx8Hdres0my1ev/k6eVWhJzNcbfDCgpUM+lf4yme2UAhqD63WMo3mIqNhg6WNhzl79mHiRgupYoSDSMV0Eui2UkSSUJYFk8mQqxdeoLI1ycoyeI1XktPLC5w/sUgzi2lmDc6dWuTJjSW+bynhY7t9dmcV1htiHM1UUfqaqy//IfeuvU4+GdDqtumeXuG9bz/O1FW88oWKv/iW07RbCR0u0KivUuRjpplj5Xyb2wclSklWTnRZqUoePdPl//XRW1yZxHz0zpDRtKSsa5qZ5OFjLVJqvvCSBiFJMoHPIY48GQ4rFFkiGdYp4/09Ln/6d6mQ5PubLC13kNrx+u/+a1xzGaEiEkqyRpO3rmQ8/dgy8ckedpLTv3aHrtR0XM6dvOKg36cucmadiAUEaZYgV5ZJjUdvFdgooZMJhInx1Yyzp46xGCvKi29wuT/k2LF1HjvdI00kvdiSCcu49rQzaCpBJBRn1rvEGES6wHA8IbcpIoJuU/H046ucW+kxGGg6nQXc/oRWmtKUEZXx1FqQCMH50xvsj2dQavrT1jetDXn63e9HxfG8qdxRFzNG2zd56m1P0e20WVo/xresHCPwEM83Eu8xxgSafqUIRRaP9R5tDdZ5tDYM9vbYunWdrJPx2NsO6CwZkjRiPC5IEugtJlhvuL5/j5XOAsutJs4H8e+8mgKSpU6XrcEmVV3z0MZTKBkj/GELrkO7CfddCYEUgfMoiiTGWJSMEEIhheKh8wusrreYVR5PGvTbTBA/j2LoLSV0FyOkyvg9NWa4e5zvm66ineHCS4r/8Adf4ge+9xk6vc7cKRFHTNEWwcppOPuwxLqYu/cEe1sRQrTp5xLDDOvqQGsrmFNE39dfAeaO4ldj9u9DIjcHgg3vECWUBup5g7J2QV8wwmOEwHhH7YNMg3SB7GPPxey4iFjASVWEHiEn6PuETZtwXNR0fI0kkAsIApwnF57PV5auFDRFcF4HTuOx9EvLF6cVFk97InHGETvNGSQ3nEFfHlJHEq88YqUkOjNACIP0CmU0Xir8rXvIgzEqUah26EftZgHiGcUyJDK8RUjFYhIzq+Du2JB7QUN4tBc0ZYA0RSIIi8dCEsuItThifSPDtx1MNbW3HBiDMwI9qdm5M6K3ZChKyeY0dOtNRMqNQnMlgalQeBVRY8nLAkTEcM+T9DV9V7OclORXd1CJwLVX6E/GLEwN8Wcv01qIGS432FeWqNNk+Vu/hfHvf46za44zpzu8+qVt4iQhySK8O2x0/+OPbzQ74nQgMhESvLKcObtMWVX0+yXeibn5mMPSQrMN1gpsHZZSWUhskaFnHqEsJhVYE9ZJMZGhR68OQYB1jtlIMxjWQHjsvUfG3Pf6xCG89bDXxmNqiS5K5OBzdNJQIZoVYF2FkgprNQd7JViIM0VvzdMfT5iOXmaSbwe2OmHx0uNTwfiJNuup5/qFIV9eKyjOTHFGMJvWSOWJIsVDJ9aQSuAYkEYFUgi2CsknLn8BozXeC1pdy2MioyNFoOUWMJae11zo0fZe0sk8SU/RORdhhSKKBUW9g2SPKFrDs0oSdZE+kFKIuYUU/gHImr/P7HlYsfLeM7EDXFyDiDHeYJyaJx5CoBkCKoWUnrQBIrZkCwG+F4YiEYLmPFY7NGh5DUnsWaRxvxr2AMx4cWGZLE7YORhz+nSbRiPQBZ88fZ5Xrv4Ox4ZDei3Plb6hJxO6TUkVR/zG5X1kmnLPCKJC8JntAePa8N3LS0yNp19q7qVQu5pbuWd5GpGlcEt7JtqQa8drE8mxVsxUWK7mjl4EG5Fg7Bw3cst5mfNCv8QC72wm1CJU5JzzWHs/4SUAGTm01uzdG4Z5Pn+11YgxRvDIE6uUxZSkEVEcaGb5jMXFDkma4WuQtaB9rMvCsqAUgu//bx5BKIVUBuegEUmkkKRpghAxnU4b7yXSCLIkOrrf3Uzgvf7jmpCveXzdA6rr16/zS7/0S/zkT/4kf+fv/B2ef/55/sbf+BskScKP/uiPsr29DcD6+vqb/m59ff3ote3tbdbW1t58olHE0tLS0Xu+evyjf/SP+Af/4B/8kefL2YSVlQ3wM3RRsrHQ4dsf7zIbpLzw6S0ee8e7WEvh5a1NktYpFtZXqLY2OZE0Of7ow/yOFaTdZeLOIkJPSOIWi8ceYa0pOBaVPHfzADqrWCkZDq6xPRyzvrLOX/zOt/Jvn73MjX0BzQZPry5TT8/zwqu3ybIerbUO5naJ1hZTWPCOKovRwqGNgbkKdElNXvSJTnYY391GjwtUFKOcxyuBiCVisY0vDbqsqb0EoYMAXT3i0sUvI2LNpz77b+j01pmM75JEHbZ3bjEYDKl0QRS5INJZ1ThV04mb1A1FWRkyYKYrZtOCJAY/0zjtiNIIg2OqK+LCMN7ZBynBQLEwJl3oo03QyqmmWxQomtKzfuxRlo+fQhFR1DM2b15iNtynGOxw7eY13vnE4+z1d0mjDlIpIiXpNDKW2k28FYhU0CyGrC726NzdBuuQ2rK6skihPHUWY8sRnUYDUefEkSKWEiMUg50pzU4Lm2jaDUE7VXRSQXelQXNoOaGbFBU4WyBaKWvrXQYHE/Zzz0o7Ra11SToNBluCbjPi6bNLvHzlLnGjiXAJnVaHWWXothKEdigVsdRRxE2L8EMmmwMKEZEpkNYyMpaV/IA7l16hu7zCW44tEAtHUXv89g1YyODqNbZffZ7rwwnLMai6oNfpcKKT8kQvw3dGtLtdRBwhfYGpK+LIsdJZpJ4NaXSadBsZT3VSRicX2JWOXg8ePbFIbTRLS12sKXASoqzBtKo4fqzDemMDq0s6C8s8//INaqlYWlrBFwU3Lt/k+5ZbtIRkFml+4KkVVs73qBpwp/aIap8rO7dQLPFQbwHrXHC2vkltCN7j7fy3c1hTEyn49ve8C+ccg9EU7RxxlITNY975XNdBpd3KkOU0zmOcw1mDtR5tNFobVCxIUkGz7ckyQSQlRVkzKyJ6iwHwbbzGCYiidnCY0LSyBCHknBXLYb3mTv8qUirWu2dIowZKpVjvGYzvBhdBSFa6J4lVRiRiZqZECkGkUrzzRCLi+OICadwJ30VImomn0gXjIsfNATNrpz2djTb2bsQZ43ACHnpfTD6WnD//BmlDYa3A2whbR3zmU23uHpScOCOQXuK8QziBzi2xLGlWllhp6mIMOjQN31fvehPS8fCZo+fFfbeQK5XjIQFt6Zg5T0VwUqt55SjxHiMFxntuScGuV6QmAIHu+pRNn9LF0LKGiKAFtO8SdkSDyIMGhD+k4RVMSZBRyDwfOM8Qz3atuVmXlEJw3RqqumQwh12tWHilmtK3jgjJhZdusSeDYHw7a/DWMy/SXM+ItMVeGEOsEDsl1dU9xLjEVgFq6JxHKkEcRRQ6kP/0WpJJXlIbEQR2rQ+07hzq1wWKeekFsZCkUtFJFL23ncK3FNz8IqkylM5itWWyN0LKioffFXP7UsJkpkgbbe5lGc/dvknPS7K0A67gmGsxyQNs7PU/uMzStudXbvw6P/7hd/HS9mVWuxHn3/9uLl28wRNPnkB5RVIp/rc/3OViZYjXmvjasj+acK6q6b92k0baJYojjsR6vsbxjWZHvJ/rmjlotT2PPrzOi1/ZZW/HBR20yTw4mNsaV0m0E7g6PC62Q9ORd2BmgpkBW4cLU07nVQ0XjjMeGrQO8E3jQ7+UlAop3NFaOrqkh7BWwOoOs4HHVgcUlWdswjyy3s4DMBko3KWnqi2X37jF3Ru/iLFjPIFEQ0qQCGKleM93rBAJuH6nQMQxlhgnPKQxFhP0iYzFa4giRewCbM44T2Fn1FYHWvFUMeokVHhSAyIRlF3BlXlWxTmH8Z44MiGRrCRxHAUNKyGIom3qekC7cRJnWxw62JEMep/iEGrpw5qvA0QD7UucM+zmW2hTUTmojcN7dYgOBObBci2wtcRoEF7TaTVIk0OiIM+R+u38GYCGjkgSG/qH/P1Xgq0WPP7EKZaXFnjpwi1On15nsddBCIk1jo/9+pf4zmMxT59M+J8+u89/+57jLHYixsMZ//ELBTe8411PrPBdDx/nlY++yMGe4UN//mEoPL/9/3ie73r0GFns+J9f2+HH/9L76DWbvPbP/gN5XfF4lrBfw++OZ7ytExFheWlS8dS5Bl8qDLmVfHFUYQUUzjPWjtpFIYXnHmihEmFmlZM+X3luxN2bozCPvEBJwZ/+7lO8enGH7sYia2emoCQylpR5werJY4F8wkIqBX/+B89xTU6prOXRx1aRKmKcl0gkaSYQONIkIo487WY7BHZaz6thIUhWRzP9T2Z83QMq5xzvfve7+dmf/VkA3vGOd3DhwgV++Zd/mR/90R/9eh/uaPz0T/80P/mTP3n0eDwec+rUKe5tXeftVvPajVfY7N8h8av81V9+BWM9iYBf+9xXIAJlGojpFlv7t4iVYH9hg9HuiG6ny9bBFne3b3GsF9NdPEncyhjne8yqnHa2SCoF+4MbXLp6gZZLaawt8GufvcqzVy8wqSXRzTVev7zDwd4ud/u7jKoBdw/u4bVGOYmPBTJJMLZGENHtdLEa4sxxMN6m0U5pOoNqNRlOc+JYUecF3nt0pYmbDZKGorIVTjviOMIogU4KjM9RLmZvcIutwSZ1WVDNSoRyGJUQCdC5YVYGBQYZR4xFBU6SCIn1wcgbLDovaXa6JLENPQsGbF4FPHEiUc0EXxuKcoIdS9Y3TuNRVOUMXRbkxPTdRarRPSwFk8kUW1ZkkeDqzWu0Gm1cJJlMxxw7cQylJDMToE2xgiSKiNtdmlHBTEScXO6yDqy2l7FFRby+yv6sZKgdJ84t8/mtZV7f3cd7wbP/8RVGpSFKBEWtmShJQ0paWQy1ZibBjmpWDBxbXcSXcLbb5ODGDv+Xt6+hREqilvjSzoh/vNuntoI/eGGbm3szEAorCY6zdSgkhde0ZELTKw6KIb1em2Ya4WNPVylKrWm2FEu1hdUl4kbCgtAU3rEfp1x+9ll4+SUqn1Ipi0wdD7VjxjVMD/Z5x9IClTEsdzo0AV9a0AbpHZYAW/KmIGn1iKTl/FoLUa1x4lseJu5K7mzv4Z1kUoPyFb3OMk+89528dmOft7/9EfY2FXhNp9fm5MYCV167xrd/y2km+3tcvtznZNMgdYVJoLWa8Njb1vjUVLE5swwnOfsHezw7HvB6oPwhS7M/9lr+RrMh1y5eJGm0aDQaYDWmynH5iLWlFoPRlJs37lAWOYtLiwyHI5IIOu02UZLhPExGYyaTHKkC051wFqlibFUAjuPnxywdGzMd14yGiuMbgjTzGGPJc027Hc1hJwGPLkRCJGIiCeCD7pqMQMCsGiMQ1K3VeXY0NBk7Z8KmjqQ/uRc2Pm+xrkZKReI12list3Q9xKoZMrhiDlGSGhWDMjCtPNOyxhlDK4OGV9TOcvLcbI78L9EehAIQyFTw2NsnnHm8RlBTFYJ87JmNHUVeU7gS7wVZWuD9DPwi97mjOMrY3s93zh0UgvN42GMjEDQxFFgOSsdu5anm5GS59lTG0YwtOIOtBdYqXm4soufyBI7QYN33CQMfHx0yQPwFm6LJJnPBTsS8ed4h04Td6YwEaHnFgoxYlhE71tMUEatxQorFOUfTS3pJxsholHMsNGM6BBaw7mqE0iWMPC6R+Ee6iEQRJVBfBDKFU4ReG23RCNRcq8o5jzAWaktRGYZOsGUdey40vwfgYwimlkSEdRaDIzee+mBGpj261lQOShcc2nxWsFl4Lv1+zah0bJeGJGmxvLLMrbt3UUKyvXObRrvLWm+JcV7hhSBaaLFz9TYzb7h2fYtboxlp2cEPDarb5I5s80KywqKDe42ag3LAqXPnSBdXGOcVsnbs39ohObNIHL+ZxvprGd9odsRYhzAOIaHd9PQWumzdOwgMZkJi8rDXHvY2CcBVngB+dTg9n+sCtBHoEpjDfu0cg3ooMTSbWpz3GFfTH99ASMmT70o4fiIlzeaaQkdneAikDTZBJgbrbCBQ0AZrPNY5Ku0pShu08ACsJ88LirycV2lAKUGWBJ0sKUJPlZCS4+dboT8IUApajYiVhR5SCKz2GHNIJR6YNJ1wJBkU2oaqhxLUC56LesBkV7P07S0+/J2PM9MabR17uzMuXxshW4rt3X0EnqyVEiUKBHRai3SbMYXYoqwOu6gEjSibJ2TEUe8STlB6GeytdzhjyesJVjjGM0eeQ104qspQ1RrnLNNRTZVnGO2pikDTXRWBke9+Wsjet2Ui3CyFw1VmbsfmEMxAF4EQkjt37jAaDhkNJ9yTnvFghJxX6SpTcjMvsdKQV5ovXd6jFQvquuK1O/vsOsOvfuEW/+tzt+jXFd5H/Nyvv4iRUAnLb16+RxoL6go+84UrdKImk8LwaKvFD60t8nI+4/LdPt+/vsyLQ03fOr7r+CKv9/vcFAUf2ejx6YOcG6Xlh9tNfmMCB8Zg7RxeeJQH8dx85c58rsojCw6Kut3i/FuPIzsZzYUuJlYsHmtTVRWtVoM0jqi1wWhB5CRX92N2pvMgSVh6XcFDx1P+0p97G92GZHEhotkyNNIMa1zo7Ts84nxp/Unypn/dA6qNjQ3e8pa3vOm5J554gn/37/4dAMeOBW2JnZ0dNjY2jt6zs7PD29/+9qP37O6+uYndGEO/3z/6+68eaZqSpn+UviOvYPnUab7y+u+QHwy5YwXH1zdwKNLlNZI05tbmDYRyDA40cdzkeG+NE6dO0kxjaqEpihJHhNGOVizJEgl5jbGGmdSUxYjnr77I1uY93nL+aQo34zOXr3N3fxtt4dnnPsp0uMdsPENXlt5Ki6quaK2tkrabTIdDZuMZUZQwORijFhuki0uMDm7jKk2SKfbGOaqo8Z0exng0hqyT4ZUkbWZEzYTewgITXdNpNMhtiZmUeJFi4ohJmWNqiGqHUw6rLZEtcMLh8WRe4GJJEJEWmKpCSUHSbjOpStLKob3CFBVGWBKlmBY6qJMLSRIleO1p9jooFdPrHiNt9igqja9LnIOTy4sURY4Snv3dHYzz9HoLbO3eZTorOLm6Rl5oqtqwsriMjCKk9UghKeqaTtZEZ02m+RRlxxClLBVTjknJLJIkpmDsHIvOcrLbZHWSkk27LMaaZ5YEiJisqfAyRdcl3gqS5QYy91gZ8fsvT9kvDRSepN2i3Nsn6fWIUouXEqUcS1ULVxjG2vOx526jCY5upCTlJEcIyPMcIRV1VeIXOrzz4Q2iKKGTRiw2FVEjJZ/UTKylhcFdvMfbz/fopgnNXptOFhrLXdbGeM/qQsy3ra3Q85p4ucGJezGRzPDGs4wkVYr+TkF/XHBrIlCtY2xPphzMDN2OYvveAZxfpddu8vqlbWy3xUGeUhQF2lR0TsxYPrXOzf2aSCr2Rp5rX7nCcOcWi902q+cfYmg6/NYnLkCtqcea7PvX6RSG2O0SrbcQrRVkKcnLAl0L2rFkp6zY1SVWGBac+aa1Ibvb2yyuHyNrNdH5DG8qHju/Qa/X4BPPvkJ/MKIRBedhf2uLlaUu3eUmXlQUWpKPR4xHOYtLHZTXTMZT2gsLHLrwcezJGpb+WJJPYJ4Mpigq9vcNjWwZGQsmxZRa30ZIyWJ7kU7aDSd4tFMcOv+e/dFtlAzUu86b+WvBIatNwSGEXYo5BFAIkjgCFMZP6c+K+ceGv1FKksaSNIIsjugkCk/Qd1FSYJ0nLw8dM46yvuC5d5Czn9R4DM7C1h3Lqy+G9XekaOkdbt4zEHlLIA9+gCyCw2rUVw0PEZbjcobyEHvNVaf47dsTxqMRg7pGek9pLMZZht5wRU/J9sYkicFuLKOPNCrFAx/7gONz/1BH4zDc84DIEm7ORngELTzfKjPWo5hPFSOkkqyIiLYQxMIxI2LBW24LCxaWGxGPNGOitYj2Ix1UDAzH1NMZ1bNTZBqRrme4NKbzwZOQeVCC7ZHnX15K+NDOHZaqAqxl38dcsZa7pWbLeqbWYjzUXqBx1HOtLoujcJ7aORpnVyERuP0B+cixmTuGdi6Ubh0rWN4Y1uxqw641iGguRO4hjSJ0rYm9Q1tLPimw1rCwtoJr7nJidYXF8w+z9aU3eES1WWn1KN75Tj67O+JzSycxk5y7+S4TK/mROQPtpKi5GSXUkwlL4s09Lv+Ju/9fHN9oduTCay8hlaTRkHzg/WeIleKlF6/yylduzYOJ+eoRghMnVlhcCtUIgTzSobp/OR585I/WfeirdOG3MOAqrK4QEfRWHKfPxTSyUCGYF6aOfHzvoT+u6Y8KplOFkoK8NGhtKErHfr8OgbsQIAW+8sx2xAMJj1CE2TgDMg5Q31mhiZTg/Nt6GG3RNpCQHzLNpbFCpuKoeGNs6OVDOLpdxXAaePmckDghmGU16nSonMdCYQoQxqGaUegrywRSuKOq22GgqE1NURXz8+eo+u60CQ53wA6HyqALrHrOWLzzWGsDkkBJRnnFy18WVKVjOKkYjgq08RSlp64irBUYa8nzAq3TeaB7v8L6YGoo/LY8mCgyRjCdBXgmHvqDbZQE6yQHezsIEXqunHNMizEfvTGEGx7pHP/zc2MifHDqZYNeLOkKeCyJUVnYnwye2ntOL8bMtGE00wyt55985nIg43GhT/fLxTY1DhT8880BxgYyjx/93Jip9pQO/sXdksIJjJf83wZjKpchpcJYjzaH6/V+r1qaKLSBWEpiHxHHKbqR0T29gBCSU08ew8/J862paTZTWq2MvVHJzXsTTAyFqZnNDIdhUhJBkVuWlgXTac5Cd412Cq1WgjEW71y4sg/GsV+jHflaxtc9oPrABz7ApUuX3vTc5cuXOXPmDBCaQo8dO8YnPvGJI6M1Ho957rnn+Ct/5a8A8C3f8i0Mh0NeeOEF3vWudwHwyU9+Eucc733ve7+m81lMV1k5tsTN37uCxuGs5WDSx8aSyd0ReEtdVVgZ05ERS6snaK52sd5wrAUXTR1YbBAooTHasLHY4y3nWly+eYM/vN7n6q1X2Lp1BznTXHjjRWQaU1YVSIgqQTUcQSzQtkY4j5aholPnU2bjKeWsBgUWC85RDYeUoxHeW+I4oRiX1BNLw0tEEmFqQ2upSdJQWA0uazIa5NRIkk6DSVkhVaBCb7caTEdDqrzGR4o4SUgXmvhSk3rJ2BnSVoRtFMQOhBVYpXCNCDOpcJMckQh0EmFrTVWURGlMJQzCB/xBomISJD6GuvScOH0GL8CYHAiwg43VdcrpANlpsn3vDkpKZrmm03Ds7Q5ZbHSwxtLIYnRR01tYJlGKJA59SKasyOUUKSOqYsZSUtCLljh+vMNi09JKusS6pCWbOG1ZWFjkLcJyb2ZQ7SU2C49ShnbSoMYQk+ClQBQxttY4FdFe73G+6Vhbydh9/SrTmcHLCFvUpFkDGUn0qE9bWKYuCrSw0gXxROERygV6VOdoSxF0h2YlriiwcYRPFUkUobFMSo1FYZJAP7xWlbhC08hzomYLE7WI8wkNa9kcT3ltf5enji1xe2/IrjE8ffIsTzYkCwn82tU7XHi1Zjw94MRb3s5Z4zB1wXBUUC4XeG3YvHybJI6RK2e4cHOfO7tbCJmQAGcP9nnLU08yqNvsXPoi21NFWUGGoxyPeP1zn2Pt/Gme+Z7vZNrfpX+wR9brYvI9pKgoqoxyWDFwAuMMxIqbwwlxGqPiiLoq2R8dfNPaEJj3PumQjVRS8uf/9AexzvArv/5REB4nJNoYVBQjVehTcU5TlgbrHVIpDrt/JEGd3gt55EAJwRzXdj8LDWCM487mmFOnu5SiZFbNcDgQkmbSQiJw8/9qG+BgcSTRtsYGgaU53ISjfdt6KGpHrRULrYg0jh4E1xH+wh09VkIhvJz3ZUGiIMlk6IuygeULJN1UPCDCe+gghqDRWEtdh16OWnuclfdhfPO9d1wnTPVlIm4RxV1W208Riejo1A8/+H7wExzJhjC8uznDOM8fDjMOTEyj06HX3+dPRZJGb5kNGfOdDcX7z57hbCfhYGK4PZ1x1Of11Q4rD7o5/6kZAYf9clIK5LzKVeP5DAVCeEyqGHvBLVuT4jlpQTrDMoo0icFabKyIm4L2+xLEeorvCRBNpKkQnz+AXFPsz9DWMf3ELb7c7nEji5kYz2vGcLmxSJz1iObB6n5xwI6Zknsb2P2charAeHDOYgnVqgCSjLjTH+DuDvn05h4X+5ph7bhl50KjwGoiMa2M3WGOdgZPivdhfjfTCCFgdLBDtXKMoqyp64pmu82B1SjvsLMZ46qkcppIwEJnlTPdLtHAMNo+4GZtEU5y/MQJZlXFrKhwCwnGHzqab7riX9P4RrMj+SxHoIhjxbd94DFuXj/gY797mb39/M0TTQhazYRmK0ZKRRwlSCG/ao7Oe39CuIEX/qgPykvHyScmLCxApTWbWx4pPb2uIFKHh5qvowcTMQiM8dS1I00VwnuMcdTGo+esfocitd4KjBHo2ZvhmEIBPgRLeM/OwQQpBadOdGk0IvoHhrIMGaNipkPiRcHqcpNmFnHj4hRbe0491sJ4i5Chj9F4yyAvUAIiFeylA8rKBjbkxLNyIg7BnhNM9hx6DFJaGhsw8xOc80RRhDyydn6uayc41ItirheFD6LlIaBygURIOqraMZnGpKmjqjSTPIiaV7Wi1jEQkB1CSA72AunOkaET963rkZMvuJ82ch7jPLUG70LAa73D+sN7O7+/PkB+e2ttWo0Q4B5f6rK80iaOBJETbL4xpMg1As/YGZS3RM4QW0NmHS3rwQV2xke95aWSgAaaa9C1YkEmIHGCllMseU9DhIqdSTxTbxg6x8QKBhouI3FKoDxUWqCi+/uJBxZbkr/8Hcf59IUJTx1vsCxPUKZNdhah1g4RwWxUUlU1WTMCZ8iyhPX1RV596Sb/w8deoa4F1qtQzRNuHhQH2Ycohe/9/oqP/MXjGJ3Q7aZYbeeojvvbnxT/NZbkjz++7gHV3/pbf4v3v//9/OzP/ix/4S/8Bb70pS/xK7/yK/zKr/wKEDKef/Nv/k3+4T/8hzzyyCNHVKXHjx/nz/7ZPwuELNL3fu/38mM/9mP88i//MlprfuInfoKPfOQjXxOrDsCx0w8R+ZLxnbso4xjmY4qyotZlEIDzjoSITrtBp7nItBqzt3WH4+sL3DwQWKMZHdzBipisnaC95dbePptXbrM7PGBcOOpZhYpj6pZHGE09NjSbCWVdBorkKBg/YUIzZTGeoVDYWY0ToPMKpRJMPJ/k3qDSFOk8JGGzj+ogVucrTdpqUo5nlINQjladGrShEAJtND5WoECoCF3U2KLGTgqcFMgOMIRIRUFTx3kqV1KZOtBeewKuxzi0dyg8iY8CbMQEQg2kRNeaKIlIezFRkmBNjZIZ6+tnaSQJSRqRTyaMBmPOPfR0gKM0O4z6B3gU93b2Offw49y+fYUsUqyuLDHYH3Dm7HmazQ69VoI3lnihSRwputKyJBS+0yLaMnQFfMuyYu2DpxDrMdRjiDagHsFYwIkTLFw2fOnqNgtNePpda8j2FLG6BNYGQo1ZiVhYBl+BSHjojS3uPLvF0ok2nWdaiDgBlUBdgYohabJ41dD+rYIqaVJ5HZziWtNIO6w0WyzZIZdKgSsKRJpxPEl4TDmst7x7ZZHjCxGzouK13RmRkiwsNNloCFZXYkysMFOIsja1i1G2wtc1n7qwyZd2hlzbGXJpktNYPc3WjVt88Lse5aXLd/iDO0O2BxNqk7P2iAjN9AhW2i0eWhJIA1fuDVg++Qi7U8lgUrOy8TA2ikniCJG0aaWKnVnBnVdeo3XiJJNGm/6NAC9dWlllePsuty9cZDQr8bu3Ed//NNHxBv7qkPFuhVwrMK3Qi5K2e+BAuhoXZ1B5qkNMyjehDWmmEbHT6Ok4UDsIaLfblNoEnbtei2leMJrkNBZ6OCXDJixCz1WkBGkWByYvGzSsrK5DM4R3YcvxD+TgpTgqxwgv0GYuLSkg0CoL+pM+k1nOemcD7y2TXPPR39lndTnmW791KbB4HW0k4sjZgtA/NJiC0ZZGIlFSz7O2IVN8iIhQUtJuNJHivgsS4j+Hto6isnM2JwLFsRdHnwOBTveNW7tsD3IqbRmNLVp7tu64OQ10yBYfHi80h2uM10gfUVcDZLKEEOqrKkhBpDPsjA7nIfcK7Ty1VFQqoZPWNBqeH+oscqwd01IRT/mac+fXyRotlvolN6YWI7+KRveBzP+bgqn7HeP3n0IcZV8FcyeS0KslAKEkA+CC0tTWg/JICU6IEKDiEZEgihRCRYhYBIEoCWopBQnO+DnlsKPOLW9IyQu+OQ9cQ377XJmzZGpeyBZxGydZWT/BigxEINVkyvs2bzKTksp7Ku+4oA0nasN1D9oJpoXmd29OuTYy9GLJyEFbSrptRU9YtozjYl3Rlg6vBAaPd4YsDmLBrd4KDqhqG+Dkccx2XbM501w4GLA5yrl2MObueIbrNrl76xqjzT3G9Yz0ZAezOWVleZHZLAh6xkrNIW9fDfP72lyhbzQ74sKtJU0UrXbG1u6E4bAgrMw3pw3u3t1je/uAbrfFE0+cD3pwR2l2ceRgH12VQ4d7PgdPnNWcPg/aGJqbMeBZWo6JojfN6sPa1gOfFOZbKNYIDoY105l+4PM9w13NbDgvbYXSWFgHh7mgeYLosBI0fwdKzoMhQqKo1CFpIyT0upY0VUSpABl6tqwLPVkQZE22BmOSWLLQTkOlRsDd/Rwz7ydM0jBjnPOoWELp0bkgWwOvQJuSSXkQ7JmYX8+5FEXsG0QuIQRZoQnImcCeYE2omPsy4t71iknfUmdj8mXFbJbhrOXu5hhhJWpe7ba1QKtQcXqgQPVVl/pQBH1u7/2DlXGPt56qssxqcz+YPQxovWDt+DKnFpZQQvDQ2TXW17rgQVeWwd4lSgocnsk8kRd6m0IAjgfhxDyItHSspe1C4MicAt8ZuN0vMMYj/Vx22c8TacQYQt9aqcK5Se9wwlFbT/TAdi+ASntevjlld1Lz/G2LEreYOM8TDz/ElRfu8PgzJ/nKx2+wvTnku77zODxzHoHj4XMn6O9MWVlucuPWkFluEZIjxIQQgqp2pEnCw2cfQ0WwsNJkZbmD1iawNL5plosHC6pf9/F1D6ieeeYZ/v2///f89E//ND/zMz/DuXPn+Pmf/3l+5Ed+5Og9P/VTP0We5/z4j/84w+GQD37wg3zsYx870n0A+Nf/+l/zEz/xE3z3d3/3kZjeL/zCL3zN53P2oce5tXeNyXCIrz2m9GgxI0oSkjjF+pokAj2bMvI164srPPrkYzz6+OOUIuH63g75dI9elDJVi+hYsTfoMx1M6CaQAaacETVjjHYkNsb7iumkCFz8XmJKjZqFiaWyFDezOAUyipF1RZYm1Fi0CrhdgyeR4J2hGBuiOCaSEkMwcjqvEEqhq6BrI2clEkGNx5SWuNMka2Xk+yO0dyRpjJEKqQRZV4GxTEcF0nsQijSVSCupSo2VAmUEIoPMxjhtcDLGlhq0pTY2NN8bi2plqGYCpiZSTdZOPYTLS8o8Zzr1VLMpZx5+gkm+Syo7RColjSL2+7usrG4wmQ6YDKesLfaoa42WCeMihyjlYDBhdbFLp5ESxzGZdLSMhrjL2EhkFNGKagRxUJ/3BkyJm8yQowJWVqmnOTYO2g6qrnHTJrAHaQJ6hqgkLsrBTRG1YHhjyN7E06kclGWAB0Tgaw2iROCZTTyFSmg2IqqZwomIaazpRSnLjSYfWsvYvjGmLiU+yVhptVlJauqZYaEVky4K8BHNWJJkEd00IcocclEhVBvrFGnDI8o8MGMlERU1UyGZVYbW2hk6MqKcVXzstbv8/qVtZiamzEck7Q75NA+U3apBriWj8ZT3PL7MYjXjYtZhd7ciW1zBqxhnPSYS5HVFqsL8aWysku/v0Vp/nKrRxOkZ5WjE0uIyo+1tiuYK8dpx9LEniRsJ9uUrXNouubZT0jgbYcoKIWFh/Ti6HKLrOsA49B8f8veNZkMajVAJ0lWFszXtrEmaNqnKkv7+HtZoGkkEeKJUEQkxN+Rg6ppIChqJwgGJVMhmM1AF4zFWIzgIwcXcOc9zhxeOLJEsLao5HMbDPEsNQTumqAp+41OXSGPJu96ZMRo4ssRjNPQnGomg146ojWFzqyBLBatrCUki6GQerQJFdl4eVrFCgOPmMDwl1Zz9ah6cHVWUHMb5ebOvxNh5YEQg4hCANp6DYc3uQcHOvZqyDMFEkga68iC5M4+mhJ8X5/xRWUj7AXvTlzjWez9xFJrI4b6DdvTAw4SIj896eC8wUaig6ahFHjf5zb1bNMaCv7Z6nD8sJ+T7A55uWr4wttxuLOLkodfn/8sb7VHh8AHH97BhhQecSO4XGsNLnoZUaG8D46A8DGslUgpetJKmhs5tR2Zqji+0kUC8EePTAEny8yqaQCD9Yfg2z7jiWXWaDVtywTukVBx5dd5jheeFNA7EJXNHrI6h8gI9z36Pipq9UpM4w9moycvGsIAgUaHhfGRCgmZNhIqJdQ7jHFVdY5whsoaqKjDWkOcaJPybO9t8YnvIZ+/tQaT4zU3P1hff4D1PPcq//c0/5NWbm8TveITk6XP4/QMWel3yWY62HiUDBHXOYv9mdNvXML7R7Ei48YIPPnOcXqvJhb0tjDPMCyPAYVAS+ieNsUwnBffu7SKFZHVtmTQJTr/gzY76Yeh5/JGc1ROGxUXmkLqI0yc6OO9JYoWUglkRqir3A7HDmeopKo2xDm0sXgQo7+HnQ5hWhyxuUSxYWg4lL3GYDRKCKOa+zeI+i6CUsLySsbzimUxr7t2dPXDywek/djbFzRlRvfFHC0owt03eU9SBdMs7gdGAOjz78FtIT/uYx5aC8c0YkAjhsdZQFgVJmiClvG9MPCifYK1D6yBYKyD0hhOgr1IEog3hJMZC4gVGG7TWGOOoagvCESWKNFG0Ox5jFe2WvG9fDg/n7/8crusjoXYIyaL5Am85yE007+cKNtfOWUnF1LLSCLTjo70Bo71+6PmyjiT1dLoRjsAa6Z1nNDFHFZuj0pggsOFFc/KMOcOh8BJbw/5+Qe0CzsA/YCD9nLzDc0hA4Y7OuTaOxM2N4DxTWNSeT74+Cvdi4MHnxGnEI5VjNipxpcVojzMeXYfgzeiat731UV740hXe+rbjnDi5yJWbQ5Ik4uSpZc6dWmIwnHLr1pid7YpZbYlUzf/pI+d49OEV9vZnHMoHHA3h8fJPrkb1dQ+oAD784Q/z4Q9/+D/7uhCCn/mZn+FnfuZn/rPvWVpa+pqF8/5T4+xDj3Lp9U9gxzmoGC8FUayIoxg9neAlTKRDOklXtHDFhC987tNcuXyDD37HDxGrlOW1s7SaEZNpzeCgT9bKSNOIarLP3cmQWg8o8gpdHeoKBFYlbUI5NmqkMG/I1EUJxoFQyCQmihIa3TY2zwPb1pKgGFdU0xlW6NBnIAV1rPDG4WtHnEbU1mKLImSwPcg0RfTagdJXV+T9GqEdWbeJcTWimdBspTSimNmsxOFDVlSCVkArIZqa4CzFEtVIkUJQHYyJZjNEJBA2LA4rdDCAswpTauKowcLJszjjcQpmRY6ta86dfYLJeB+ra3rHlxnvjOgfHFBbwcmzi1y58BKR87Q6Le7t7LDUW2E6zmk1WwyG+0i5TiOOkXFMiqXwGl9VdJOEZmqpZhNatoK+DmDayCOqNs5WyLqiLqAczuidXMHIoJGk/DG8mSJ8FO6JifGVwss2EzmBrqVSCeSCe89fQzZaHDu3hlAetGM2tkSxovYWg8BaQyZC78eoNnxmK6fCsJR5Kmkp6xKZCCqpMVITL3eI4wS5P8OriNwCrqYb9ZjNFIW1RBrK3CIWUu5t7rFXK1KlqGSTRTxv7Uh2Jp7/7eIWQwsUOc2sRVHVVPWMLElRcQLestYNVLN3lze4E7UgmuBVTBKlxLVFR4JCa4S0NBptrFgAMSNtZcQPPUY53MZqw8QYukbz+OOn+eRnv8K//Ee/yPc9vcGv/d5LfEks8vgHDI95Q1VMiXG0khijFtit9nEi6Kt9LeMbyYZ0FpYQKqKua/Y2dzj76DKtVsJ4krPcbWLn9Oh4zyG8zviAw1eNFo00OBT2MAMcNfBxihAV0lV4JNNxCGR6y56bN0qW1wWdJGFlSc6dLEk76zAtxkfK9A5Pnmu2Rpo7WxOMgYN9y8f/YMBoaHAevu2DK8QpvHpxyupKxOKKQlpFHEGsxNx5uF998gSbFc7UMSnywys+f09wbA5Z2K2BovSMJiWLi02qSjOeVBQzizaBE3BtVWCc5JVXa+7e9FT5fU/m0BE8JJl4kNHNe0tlCrxXxFGGnMPQHtSSOfx//UCoJYQAFZN0emzfrMgLzbVsxoW6YmU64/G4xQtxm4vt3puDKH//M9/0nQ8feY4EUueX4sgTTgQsCkEhZXBgfHguk5LSWyIh8TbMCSEEbS94TAleMpLFQhC/WLKw7dh4Mjg6002PlgrhNR74jGpxJ47ZERGpDVAWMw/i9mVEFWXUQiAPHTfnUc6TIimTBlYbDIaRDjTHV2KJc4LbecUvv3ab7aLAGssL4wmTqsYIx3bl+Lm9ksu1ZdpI+aKzRCrCOIsTimtbB9QWiuEEWzvcuXNMpgULacbqQpfm2PHM2TVWWzH9KuUvnj3JMx98lIuX38k108ZHGX5qkUC312K8cxfnAumBF/fnyJswO1/j+EayI34eHT752CpJq8Nv/rvfmwc2h1/ufsUznByUZcW1q3cQUpCmEb1eO4RTQpKkIbgK8XaAY61sWB5/q0MIFWBRAtqNNEACETjveePmHnlRzQtM/oG8gDhqbxgUJcAR/fX8G8A8sEF4VAIrpyVKzfsl75uR+XnNKzB+rijhQMhwDSIlQ9LJi/sL+tD5nfcyHf1b+CMb4ZwnLx2zkacYg5CCbOE/vWaFmtsx6fFSgPMYa4md/6qlHRBEznqK3BBFMlCizys7GEiVwEuJ9wrnLM4HkhlrLM5q4lTQXQyQ/kRFCDllNAx9dFJFR9XrwwrgYY/UoQES82A02ONwQYwVzGYaJ+fX48FADICQ2HoQwogLBCJrJyJWnDp6v7OOm3cqan0/8PEuyD84d5i8mCe25gmcigB1d/Ng95Ba3h9dmTf/F15x1MbxJkDK4RKeB16hvy+sPW88VnusuX8PqzokcOqy4PxDJwIrrA1VzbvXStpLEU8+mfLEExt84bmrlIUOvnMcUVUlC52YNI7QlQEZGFmlDLptUoGLJX9S408koPpGGisbS3z8919HWfDY+c0VlLMcJ2yoxliLSmPyyYzrs5Io7XNne5Mnnvwg165fZn9nj+WlNm465PWtm7hGQhxrVjsp/WGfeiYwBZiqQkqJyBRKSmRVEmcZcaIAh9UOKRI0GpzEW4M3gqosSFOF1hpdWWQq8M6jbGB1ssbgygD7EToQJKRKouMEayxJHOOjGKpQ4kxchBcOmcYkwiMsxM0m5XhCMfKoRkrSzOZ/26DWFZT1fH3HpF5QFRUmFmSdjHpSUh/qTpnQ+yDjBIQkayasb5zFeYEpZwjviKzn+ImHMa6m7A/pdZbId7aY5TNG05zHHn0Lw/4udWlZ6C3iUCgUrd4Cyjl6q6voyZimiGllKVIldOKAhhkjaTVSFloG0YyRx9oBlpfOIE6haWEQ4deWWTxbsdC4yLIsUMtrkACLx5Amx3UWoO5DHCFdDy8kJ42nl27ReWQZjrdxexVlv0As9iCLQSkWT1qUqejbCKsNwno0FkzN1nDM5fGYOI7om0Bf/nQ34ZHFHgcTR2spDjC5fJ/jkceKigawuNwmObWIur1PN1PIpS7pqIkwfdZ7KT/+tnOwvsxzr97ks3s1qi54OLb0Y0lqam7EHkjQByMSAYkUYGp6aQzjEsUqV3LPQT5m++YNDoZT0qwBwOlT65w+30E5zepil+aJc0gZKLqT9TPEiSTyAiMFURIxKC1rZ07y2y++wm9+8XVK5zj+2DGc9AgZUc40tfZMZjO6Wcx6b4FYOgYH+19zUPWNMrQNENiyLMHD+9/3Nh5/+1P8k1/8N0xm1Rxz/+CWEpwJ5x3O+rlQp0DbkFnMOgc00xFKzJBoHBXbm4ok86wd9+j6EAYij0ghrIFm1iFLMhyOWZWz1w9i4saE5A1eUFWOrXsVUgYc+4XXR6QpREJQVZ7bmzUb6ymtRlCmP0r/+/u/nBPMpo5WK0B0DqsdHkF/XFPPWam885j594uTCGeh1UhI4ohbkxHehc0siRyJgLc+GXP+FAyHnrKA2zcN68dCBXmWGy5frpg3NcydBs2d/eegznj07Hfg5/1UD57v4ThCAM6/j/ACLxS1FFTWs1/VRM7xdLeBq0tm8dK8sfl+t9iDnxmKCQ8+4WnXNd852qXhLSMv2LUO62FUlgyk4lTk8TLhLhA5Sy1CA7b0CushlqEiFEvFk0g+FMOnxGEfQPgNMtBi+yau08X2C4QQLMzFhM+WQ5qzkGn+eKtHP07YjGKEiFDWsGACPEs4T6kdibXItI0QFq1LhNGkXlAKR5qFDPbLgzEegZU+NKUTEgIH2rJpDIPDDPWcSMA4g5SKtNElafUY9ftUZQ3Ck08L1joZC5mkEaXUTmCFhLqmbYLD8ejpFc7f3uLileuMvnSPxXaTdrvJ3SsTvHdBgulNt8PzJ4rT+f/ROHRH0ywln3le/MrevB8E3uzhP5DgOFx+zvPGxZtIGSo+q2uLPP7EwxxWgERUB/0nYTgsld4nWwifeVjXNDYI04Yg69BuPRjUzR1k/0BV+vDsxQOnKI8ONa8k3X/J+/tSBni4tzeew/fmrr91cwKKQBe+dzBjOBU0WhJrPMM9h9Z+XiHzmNqxsKrmUGGO6OOZO+aHlZCjKziv/DjvmA0FaWMOb3MCV5rAOCiDqHGkBFJqhAXvNEYLjHOBTVOAkhGNNEOKGKEKyrxE155yPcU4i3cVk0nNbOKxqYfU4YDheEglKzZWT5GkGcKH5EEIXsT83opD84o/vJeHt9+AGZkjxMBRQOU8Qkocjqm2oXp2OFGcC0LO1h3dLD+vRi6tR3O7KPDC4ZxD+tA35bzHCQfe4wgJm1Hf4C97hDysiR8G4IH+P+wJbh5wHRbiLNpWSNFAyiBIfz9c9/N5Mf/e3mFKg9Waugj9agB1FQSRdZWzvrFErBTa2KBV5iom/RJdGbI05t6dMaNBSRo3SZSgrirSJEYpRVnVkFQ4a0mymIVeAoXHJfH/p6X6Xz3+Dx9Q1aJg6/ZdbDKH4UiJcMFBEl5gEchIgFJYo7F1jRfQkAlKzol0pUfriMgDdka/v4/3UJdt+sMSpx2mqEFbaMY4H4NxeJFgnCdzNbPZDFuD9IrDXDU6wgiBLwxiLhIXRQotJE5WQIzIYqwuwHi8VyA9ta1QQiCSiFgm1GWJrzUqUkgRUQmQjRipFK6sUQRBP2cNToNNDJlM0LaktmEBVrMZUkUoJbCuRlgLrZTKmIBHzmv8HKpjncFjkSpiVklub2+y2FvCF45GlLKyfhIXw2D3HiQRU2koRwP6oxELqw+Rdprc3byC9J72QovBwR5SJKyvrHDv7k3OLS+xc+c6JJIsSxFSEqWCFSExyjMTis1+yfG1iKQpEUkPRBxK/60crARpmR1sQZRxakXhmxWi00M0wFVAt42wVcgauzpQUfcMC70hYv1xRLfFyTNN6oUYFpcQaZgjUWeIsDUq6uKkIGk0MJM+qYDFZsJ6lHIzNyQiIo0US0lCIxIsS+ilHpYWEEtbJI0CVUXE7RW0h4YuEYsJfjxGVBpXa3YujXipjEglfM/SlOzcAseaBWebU944aHOpv833PLLEr1ybMRpuY43GOwsJNIXkA4+u8t5Vz+9cHvHCjiOOp1y68CL37t05crgXeBcPPbNOZAuWuz0eOn+c5vIQqxIGyTHkgcHWNdprtHEYPePEQsT05Cpf6g9YiQztRoYgQqLQusZFBpzBWAGxotVeZXjQ/9/PCPx/OXbu3gkbmPMkStHqhCrjG5dus78zmm8y7n7mkSM3h8Mu8AcAKUTZFEy4Hg6PtQEiJ+cBlzNz5j0PxoKSnt29PuNpzlsePk+rkREpRZlb1tcFi71DYIc7OhdjbdhYvUUbyBqhGl1WnnY7njNhPcB3JKDShmluSOKYZjNi3spy9LrHkyWKYmbw1h9BTyBsgnt7I9IkQkXRA9nMw+shaDUUzQzixBFFUOSKM+ci0gQGfcnVK9WRE33oN6nI4muL9XM2rvnPm7pO/ohDCsZotrbvskio1BwXoKxhZiy3c8NdRmzPaqI4pt1uBQjQ0Z2bZ2vFfWcA74nrisenuzSt44tOkmiD9Z5H65obSqJUhJKKk16yBryMYxXwUlJ7D0IywbMgFZmMGMjQP5cSTJfyoW9BSo+9dIfieh8lJV7BB+IKQXl0LjmCzwuNNp7H8hnNiKOg3gEF8EJu2JnVoWfUBsFXKYJchHEh8yzFfcpoKcW878+QC88nC8PAHjrb7oFra4/mBNZS5jlpFCCv00lB+60n+fY/9V62n7/M869cZ2uk6EWSN/Zv86R/C9/39jOMxxV3Dqb0b18jW+jQamYMRtNwGPGgg3boF95fW9+0w8PZ5ZQzJ9tMJgVVdfQtHxiCNz37wPcP1z1cA+MsXkDarZCJ5h3fOqLVVjQaD1aKjlbT/cf+ftJnnjX4qkTCm8/pcC0EIgTmCRTmAdthZeWBs37A1lnjcRZk7PFflU3zc8jwYZWkqA1CedaTBF3B7VsGPBw7kWINHNwzdJcVcl5R9/OShz8i5njgq87PtSrACcfglZjveN9JugstWu0GkQoJb7yirDTddkYcz5kHCXDG0bRmYamHwCGFRyrJwaBm1fd4fNnjUXS6GYtLTZr/3VN02y3Onu3S60bkZUm7s8zduwO09vRaU7LMMCstC70WXhzq2Cm8E0xmhm47Qcj5OhRhXTrvWeq2WVlqzStXh1bvsJK1At6zO5ywutiaU9f7o/sphEQC/WHBYq85D+BCRct5GIw1rVYUejrn/VHeSWptKIpwjt/6/Wb+uRHOOUaTgk4zQ87XqHOOuq4pioosjbDe0GpEJFHE+75jnaKyoRLlPPms5g8/eZNpXockoxeMbu/TTiPuvnaXhrIcP9Yki+MA365LFpeO8dAjDWw9RVrD2joUlSdOgohvOatoNxXLyw2i2KFrTRpFCKlothLWjy1jTYi+HR46ktp+Ewn7fqONnZ0bzMoKmShsHVj0wmJUeBGam2MVI1GotElVDnFVRd1OuHXvdeq6ohE36bQ6jGdbaOPQpSaNUwb9IdZYZBKTCoWeSQQxLi8QWQORAd4zHdc4G6FkuOFCRPNKt0M1MqJYUlU1IHB5FajLjcWJQPkrXDBokhDsOScRWgQ2sSwBWxPN+xGM0zgPcSTwxobGxlrTiCMaix2qSUk1nDCdaWQs8WkMzZioqtC1xnuJFkEJoZrVoRIVe2QrwVeAAlfUeKdCZtrXIYPhYyIlcE4yLUsGt+9gPKTdBUajbabjITKKUGbG7t1rFGVJnEjG4wOm5YwkbtBaaDC7nHPtyqtMphMSKbly4xYvvPQVfv8Lr7HSXsO2O2xfu8KJ5S7dnQNWXttDqoyslREzo5zlFIXl1FvexY2rd/jCqxd54qHv4Pf/5fO0VrrErR5KKGT7Bg2ZUJX7eD1DRin1dEaxs09n83Va3Qw/nrC1ecDKo1NarQZSSPp7fbYLw1AOQEhqWzM1MyhgOJ5wYilif3uAr0q67Q6XRymf3oamqdi5K2le2EXs1AzGGqKEnd2S1VHFujdIleCHBVnPUJY1o4VlXn55l8V4xNuHDRrdJqepWX3kJG989jLj8ZjVtUdZunWLq3XJ6bVVMiFAG84uxDy60iIh4WxD8wWTU4mQ/W21myRpirGOG/f2GU8nUI1YPXaMG0WNvXkHhyFeFxR7+5jBLuNCU2vLpNakKyvcunGHQsDFSUFUSNacQ3iNrQtcJMHCdJrTbqU0khZLvUVmd/73tQX/tcOUY4RQOOc5fuo4rXaGMZbB1ibjrVsAc2dv3tAdngl/PMfqexeSM3hwE0F6JkYCRXFIMeuJk/Ande2C4GXluHKp4PxDKbE3TI1lNM6ptabdTji+scDGhxcOvR4gBDh5UWMtJOlcSwU3h86E7HMxK3AWIglxdD8e8d4zHNXEStDaUHgHVhzmtT3WwySvGY5q8IJmUwHcpzP3MB6XWBeqXPd39uAICB9YALVxGCs4fV6QF4YLFzTlbH4Sh84zhAp4A8pSMywu0Gs/iqL95mDq8FI/mJ1GEMUxqtNmc8dzAo/1jkuTnJ969nX+/qlTlN0F8lKTOIgiTaSieQAFb/bbDwMqR18b/q1sEDnLbQGjKApvbiY47+gLT4rnIW/oKjjm4f2RoCs9BbBvPS84yTkHOxg+YT1/3tWcsTZQ5W8bbv76dTrrDeJBRTtTpIKwTx3WEeYQHBCs2prMVHxQzjghgpPsfIDXVkJyrdK8NKsfLDMggdyFQNA4Q1fGZA9UDoyz5FVJ2W6wHwve3lK8kBuKefnVe6jrGu8M1jlwgTnXyRDIjwdTGic2+FP//V9Anf5DPvOVW1w5qJmO92mdO80Pnn+Y5cdjFq/tIJ2DSNJZaJJlMf3RiNDHd/Rtw629H9N+cw/h+ba3LfH2d57kM8/epiwfdOz+CxW4+fy+L2EkGA6mvPzKZd7/Q57zj8HyeptGKh9YFGFoY0OMOm/kZx6AvDnU+uqzeHO/j64EQgqGu5bbL1lk5mit3D+X+/mMYGMOP2PWFxRD6J1yxOlXHW9OaLFzu6aYOtYfjlBzOGywl+E9QgmEBTeHHvpDTKTyiBimQ8Nw39HdkLSWxSFaEGMcg3tQjwVl7rl+q6TbheUlQRzHROJQ6Bhmk9n9YEZKpAcroDJ5qP4IR9ZocfvGDKwjiiVKWmw9Y7A3Y2UpJoo0+3u7HBzAcKxZXEhIkpgkiqkqj65r8sLgjAlJ/Tkc0jo4GMxYXlT3kzrziW6tZ7+fMxomSBk/UAkM5xrNA8Dt/oy6aKHkPNnk3Zz6PVzD4bBk1EvC6yJcI208/bFlZUkiheKwVuk9VJWl1J52I0bKed+uEIGG3GvwyRFdXuj3ssjIkDYb8+MbSm1wVDgsrWYGzlMbQ6+bkGZzMXobYJbLixneQ7sRvmOWRJTaYY2m3W3wzndtsL9zAIsxp0+doNaOE+cWWV5p8N3fdWyefBRYvYWulmg3OggZMx6XXLqyiYqjEBh7z/HjS6jo/w/5+68et65dRJcVadagEiVWW5RKES7QlEdpglAR1tWYInQ4OhHY/a5cv4CZTVjqnaKZKqoswlaeqJZEylNVjsh5dFnhWxmR0AgNMoowyqCExFaaqJD4KBgFiaDRzNBFID2QhIkTpQkeC7VEGB0yLxa81yiliLLQh1UWJVEcI5MYpzxmMkN6h0eBDyxMWZRircEbh4si4iRGKEGcNTBKIosCU9VIGlhrUEbQarbJ6zG2DsdTwiOExHmHiCIacUptKuJYBngHDiklBkucJMz8AD2znDvxODvb9zCFJmk3cZMJejpmsd2ldp4kjqn6d6hHI0oF1rWJUSQqxRUF44N73Ll9hROr6yTS8MnPf55/87/8BqY2rGwc5+zZ01y8eQ171c4Nw4xYJDxz7iymHvPKnT6VMHR//woIyXA85qf/1UdZWVplf+clOkvHsFXBQneBPB/T6S2wc/cmdRWcRCMhEW8g5xk84xxCvYiaE3jU3qE9WKvnm4Oklo6B99zdUhz6rk447u1GXLlxg18TDokjVjLsbPMy+GH/ikcGaFASml5jAa3FHlFrgbo2NITno9f6jKZjohS8TOnvbEEU8z9+5g3u3t1mUsyYzqZUHq7f/TXqyYT/VWpSK5l5Q7qwTK3GOG/JWk0W2gsoBZGQPH/xJsfPneX9j7yD9mIHcXyduCrodVJm2UPk0iHqmvGoIJ8VXLy5xeZ+n7GuscYjG220dcgoppoNiBotytkU4UpcvIAz0zns7Ztz1MPdkO2Tkve/+8/wjrc+RlVrRrt3KA6251lR8UA558HxQP507hlGUYwQS3g/r/K4wz89rOYEXoFmD6Jono2cf/YbV26RJilvf/oMMg6HjY6IFQTCe5rz6rRSzB3UOSueEGjjuXs3p6otEk07c0dZ6NoYvLNBMPJ2NSeOmH+LeZbaGD/fqGE28/PKR9hYJRJtBCIKxwt+gccYENLTPwhVy1s3azqdiFZbcrBvuXvHgJnDSo6y6/d9tFpbhtMBC00XHJ8Hru3Rvx7wEI9qhF5inAznN9e5GnkYe4vIMrpZGyFEoCV2lkgq+CMu5v3DGA87QmKEY8x9qOChw4GHGGhh6TjHW4A172k6hwV6XtDzlo53bBiYSHjIOZbKCi8klGAnUN2b0WxFqIg5DCYEUcLPSeg9RN7zZ/2Ul7xiQfij++MOE9TeYb07qkoczkQH6Psd8WhrSVQgbq60pT+eUhuDRrJvoLaHlYTwIUWRM9i9i3eOhnJoZwB7RFQx6Ac9LqkUT/SW+Z/+zHsYTwrGoz69Eyv8q//nb1Jqy8U37tJUhqzR4thim1ZqGQyHKIID5w+rEP4QBvVfCDi+SUYkBY8/ukLlEv7xz30RYw47Ar+27+bxZN2aZGlEnCWkaTKHjb05mrLO8fqtXWZljZCec8dXWO62jpI/4bP+88d280qP1kEWwFYhuaGAlj+0Cf6+7XkgGSJE6Js6ZKc7bFvyhGApVLwERgeBYmfmSRIn5zBp5pWmYCOtc3P/KdThkSBj0LVj2nekPUXWEwgZ1kGt4caXPWYscN5w5/YdpPKsrzZQUiLmwsOhwUYhZUgwSSGwHtIsC+ybwoM3tFsNrl2fMBtXBMcsVJelAKEUUSTnP4IoarDQS8P1EYdafQ4pYlTyAFZhfu3ySpBm9bzP6j5ywPuQcFNKI5Dz/WMOJ3fMdf4ETki67QeSZx6OCCQ8SJmSJip82aPkl0fTJpajo6rXYQrDOglKIJzGI496q6w1REmE1pq5ajuCgE6wQBJL6toe9YcF3TERju0941HN5asWZ+SbEo/B1odzkMKzvNykLEqsDZWsT3z+Ns8/fznsY14QRxHLq1v8+996ic3NbbQWIByPPbzMf/9/fR9JGoMQ3Nva5Xd+5xOh8CDC/fre7/0OTp7+T+vHfT3G/+EDqrtX30A6R6OzhmrVTHf2QHhUlqBkg7jVQE/GdLuLaF3Ns2YxvaVVnnrynVz8yhcZbt8mzyIqM2Na1vhIUJUlttEAoYjzAjso0N4RRSHY8daACT1SVnhUHCMSiS1CD4JQMSLy2FLjpENUCpVEGONByEC3jADrcFJS1zVSKSQhSDN5gYwCexM6COERKWQc4TNJo7GAKR34oD3i2xn5dELkFSJKkY04ROrW46ZjShWTdtpU0xysQyOgrBEiInESozXeV9g6QsUp2tTgHFKl6OkMlOfcQ2/j6ac+yDtaCwwORuxff5nB8IC142c5dvoR1k4/Rj4d8soXfpsnTr6FyTRnef0k3ZNPoAQ06bNy+lHMzUtIqfCSYHScRyYpve4qjz3+Hs48+h5efeMSLh8zPLhNHClOPPQYjYZkU1+mtbxGNe6j0ozGusOlTdbXzrL2aMFwa5POYod6lrN49jHS1jLHn3wf05sXmBQ1K60Mn2TUaY92Irh6+TKVLiFr0l06Qa/7/2bvv6Nsy+77Tuyz9z7p5spVr+rlfp1zsxEagUiEmEXJChyZkkaikmdky5bH8rLl0XjNjMf2skZaHs9YI9GyhgrUSBRFCowSCJIgQgMNdECjw+t+OVauurduPGEH/7HPvXXrvdcADLIJAWv26n517z3n7HPOjr/vL3x/c8jYsX7+6/T7XaLqDM3ZZYJ6hUa9wq23z9Mf9Wg1FpC1BrVqhTCQbF67hE5HLCwuEiZzyDDAYti+9hb5aEA8v8LizByNasja0hzdgx431ndZWFohjiuk0iEO2vQ7bbo7O9SbS8weW0OLgOMiQW/eIAgUqt5ChgmNSp16OuStWzcYmZRjzXnPKOUMcbVCb3RAXKYN2N6bo723QRRXmK3HmNkFknybQg05EHPs9TNGeZ+9/QHrnR4Xbm2yu7dPJqFaqTLXmkFaA0iyzFCpWAKl0FZg84zcFRTD/nd6Kfi2y5ixzzlJvV7j1MllPv2ZL7C9u1fGIRwFREeunfosyhOzoWHrQhupIJqtl9q+MjAYh4x8/pdGM/RWZ+0IQ2+BlmiKwvK11y4hA8Xi/BzH12Z8sHdZLN61yyexdKWFY8xC52g2JcIptrdH7LXzKbe+iTQ+CUafaC7tIWgReGtIllqEVYAr3VQMee5QWA/m8HECN29rspHkwtsjhkNXPpf3AfLxZ2JS7xgMjankHV4YGxYabSwyCEqQYA8tF7jJk4IgzzX77X32O20yFWBVwrVQoasVjFX8TFpw4ByxElOCursDD7ujli8HgYp4JAhJneUld5g8VOCQzqEEhM5R4EglrJQ4KxeeIj0SgmUJVjqOIVgUkhtOsS4dqhxD1glqIuAUIU5YnDp0miyRr28TPIXyww4Mii6U1iswzpEhyLEI9AQUy8m7iInwnTmBLSzOOtIspzfKESpkPXds7wx8nK+xOKtxxlCkI7JhDxmE3Ly16V22jMWU7d7t9DwrmhJUuwPec3yeT799A9Go8RP/4SfoZpb/69/+Z3z2tRucPrHKar3CYjUiDB2ddpdAgijdnfyAPeTxvztT2HdXUQHMrtYxokJ3kL8jmLnnr4dR/QCsPWa5/4MFp4/XmZ9JkMphnfFzREqU9BZ1pCNMfDvach7fa50qb8LYec8B+zuabOAYtP1cy3KLiDTChVgxbeeCCbWluPP5BaNdRR5CUDWoyLG3YchHfl7nmcUFjt3bBicdezsajCAb+QCtaxdTT0iQCS6/lXmhWjJZL/OBd+XqbOT09gHh3aUrYcx991VxGpz183xxrs5P//EnieIYKRVKSYT0FBCHSivBhWtbHFucJQjU5C0Gac6Fax2WZytEoSSQoKQgCCRKOgLlUNLb685f3eeRc3NHXaad5MrtfZaXaySJt9bLUhFz8fqA+9bqntJeqInF3wp4+0aPk8sNT/whxpYtvxf4EBbL5ds9HjhRJ5AlOLfjhdGDwys39lhdqhGHAV7p5teOK+sZD56qHnFtdk7Q7ucMMsv8jM/rNY7nzQvNzt6AEyv1kpjIH0uznL39PqfW5kqSFb+mD1PN1u4Bx5abSGc56Gf8zD+6SL+vmaTyGOt2sJProlDR72VYZ3Am56d/+of5/g89SKC8UjMIFZVqjSAIsNYDOKMhHRygpCAKfa68973vBP/gv/uLpVVOYI3lrStd+qN3T7n7PQ+oNtdvoa1md+s242zjzjgKl+GkxeC1LL3OPoXRKOljHgb9AafXzlGMUkQQEkQhmVYIVcEOekinUA6i+RpEjtF2gcoFttBopRBCoUcanEVWEpJ6lTTNEM5hlKOxMEPa7eNSg6z6JGShFkSNCkIE6CxHDwYEtQpkBTKKiJREjyxEAYU1PpdNGVguLajCekd8JKN0RCgj7MBibE4yA5mTZAWoqIIrCsxwSBjHuCAgTUdEauxHrxC5RsUh1hZQRJAVKAIfYG20X6gUOKO9dWIgCZxhY/MKqCaN5hzLJ+6nuXqGjSvnMc6wcesSgQ1YOfNe5ufn6La3EEnE9puvcO6J95AXAQ89+V46G1dQAuaSiFiAEIpKkFBrLTLqdWgPFMVwyMHWDR+/E0T81utvct/DzzBz/BRX3n6VEyfvZ+vWdebmWgw7feSixORDHv/gR7h18SKNpRlS4+Mnuu0t3vvBD/PK+YvM1+pUpWCnm9I/6CHiBrNzS2gLsYoRUQQ2Y/nck8wVBViDSJpU51qY3h7zy6eZl45+t8fC3DKRkGRZxvzSOYQZksQJycwclaU1Nq9f4sQTH8T1e6TG0Fxc4sSJE3S3dihqTdYePIYpLM35ZSpJlY2N67hWh+7cEklcpb58iqA+z+bF1zk9u0Q9VgxSw9mHH8FRx11/i2GtxUFvn1hJKvVZDvb2AUmlGqG7+xQYtHD0egdQtvOoLwj39tH5Fq4ecvnqDqFtc4Cimw7IhMEIwUxUZW5mgaWFYzxwaoEg8NYAF8YszC7RWlmjNrNE3tlmb+cqO9cvfEfXgt9LGbtbCBEQRSH/6l/8It2D6YSchwLFXaXc31RFkcxVvEBQAp1JLpfyujwVDHuG3U3N6rGYKBKE0dH4Hpx343V5wc10i82tfU6enGN+robDMUiHdNo5TmRIWVL/WkccKaSSbG8PPauSuwMIOsAdIQafbHqlp8rk9QQQx97yM8lrgsAJQ5Y7RtoLgBY4aFuuXM4ocofP1+p9+CfGk/H7i2lMd0i3bI2lt15gFw0nTs5Sr1WoJhHNWkytGqOkxBpDqKBZr5Dmhl/79PO8/5Fj1KsRSaXCrTjgD1diAhWQJBHX1nd56rFzJHHok2iWWlUf0zGFo8aqYjwgCSVgLe/V2rtxOg9GZElMIvD5WKRzqCnd7xgcTFyLlESWGlkpxHjZxgmBVZJtKQ9jIsSYsKLUPIvAM45JiUAicSWduu8Z47yG/49nmh9KC25ubHP52jo/9slnkUqVfV4yCkw0xQJrHYXWvHnpJhev3fZsXdqitUYXBbooyHPNaDRid3uXzt4B8wuz2DJ+sN3r09nc94xuSmGs5FfeusX/96tv88efe4Tw2Glm0oxr166ydesGp1fmCbSmhWTY6TPsHPAn7j/FH3ryUcIzDxO952lPnoC3hvT7A/7uO87Qf//LqYWIUw+u8PaFbbIs8z/esV68M8RyR87Y3zHcumQ5uejQ1rLbGSCEYKczYL5VZ2nOu8Y6Jw5rdWWOpTvvKUqlCd4S6V12wRR+3uepz0+krfXyRjlfjhrE7qjUCcJY4GolDLZeSSKkK61IFluyu3k3M4cMQMbWE3aV606Re+ASVtQk4a6UYyWWIIhkSa7jyvg7EIHnqerrnKIrKDIASzrM+Te/+XXCUBEGikY9IVIeFEkpkdJ7Bux1Bqxv7BAoxZj9Pddw4armdeNQgUVJJgm9x+x8WIuSil46pDPsE8ppYg7BYJhze7tDFEiEkBPw1+sX7O90CAPprWflNiJEQHdQ0O/0JoofT+xQWvicRSpJu6/pdTqTHF/j/vAWLEl3ULDbHnjAVc55ZwXdoaU/aI/PnowRY32uwq3tMkdiuV5Y6+gPM3b39o5YjJ1x9Ic5WzsDxruHtd7tcmdvyKuv74GDNNVcvdJmOLST2Lfxu7jSXd05RxhK9tpdtDZkWUqrNcOb57e9okYKlJKEQYiUPqk9pVKuXoOTq6sEYYgTkvXNA15+5QoIUYJdiaNOXrx7ipnveUA17AxQQiCtQTuBUN5XNx8OkKGPqfIu5AJUiNUOwgBRFPQO9pFRjDWSoRN0igFu1MfkBSJSiDSj2G2j8L6+MlboXFOTNeozLXZGNxBhgK1F6AR0WhDUIiphxGDQxzmNDAV6mBHO1qguzNDd2oMCqjN1+qO+dy2repO+NjlaeVZCRICgKE3jpfuJkgRxjO0X2IrChAWiFWL3M/ZvbyPCYBxqgcsKpBIgJUEYYrSGKEJaiwoUpq7AhWA0I2WJZ+soY7BOYbtdAqcIpEIbg8VSGM1u54CHnvsR3njheYT2yWM765dZPXaClXMP8fpXPoPrFZx59MMcDPZpJA0ax1ZZf/UF0vU60cIK/W4XY3KcqBEkAiscxhbkLmaYDqmEktevvIhxklprkWLUQwmDIuBgc4tub58oUrQaMdf0AJITNBPJla//DssnTuOEI80HRNXjhMUety5c5eFnP8wbN29Sb61wtZeR7l5nsHuLE488hRgNKApHc36Vg43z7G9f5un3foAbV64hREKyuEp/+wrpaI+l42cZHnit7rFTD9LZvsSgMNTn19DDIa3WIkm1wc7629wXplgUemSotuaZay7Qb19me0NhA0WYVKhjscWA9be/ysrJM6S9PeYWjlOfWyQbpOytXyaqbCGKfR555n2Ygx02ejk3L55ntjnLrf029eUzNKVCFn36/QMMlnqzxcLiSa6++RUil1GVAS1hcU4zN9+ivbzATLJAI+9hrODcgw+ze/VrKCUYWsmChr2dPvVqlR//wHPU4oDtgz6ra4JjJ+7jxELM/Z/8IL/zla9TWZynkw155r0f5aXP/sZ3cCX4vRdZavJUKRQfkSHeYY2eMnDgjMVkKVGzQlSJQIyZnpggiSKFYU9Qb7jSf3/iTTYppaHCAx1jyHPDxmYHbTTDoSbLHTdvDFlZg0rFu4sVud/kBJTxCWNzkzusdYyrnBfcnRPkuRewhgNLa2YKUZWKKGPsJN7BAcYKDg6g25FEiaHIHUUKrYZkMHQM+mbqPbxw5WGB1zgX2rsKTRerHfrA8MZLL3Pt7QuEShIGiihUNOoNVo8do1qJfOxXNcYZy7VLV9jZ7eBMQRSFzCzMEkYhUvg8Md1eH5fnhGE8lsPAgi0hkCitYHYiEnnLmi1jmOwRi1EZ1zRuUzeOX7ATrKikRCmfe0oKSoFMTvrTW6DkuFUYe1IdDjM3EUDGAMsLZYdgH1dq3CchApIs17z4tbcwVvDZ579earH9ywphx4+Lzy1m0IVmZ++Ajd0OOtcYbUrykdL1D4F1gqIoiKsVFleOYazGWssoNdy8scGVT30W0R/RvbrBF89f58Z+jyI3mNEQbR3zx9Z4TCdUowhnDNe+8BJ/48f+Krf3BvzZv/ZTPPfh9/Pl16/wta98ifW9LuDfK8/evWDyP4jy6IkKx8+u8Pf/yy/Q7ZVsfPdcOMYA6s5jh8Cqf2DYvGnpP2oZNh03Nvo+n6a2tGqltQEvoLqS6MNYz/A3seiW69n02pKllv0t48e6AQxY4Sh0QXvdopUmrhi6ewH7fcWJ+xwqFIePN/WhviAmOaW8YO7H3rFTQUlRnvPSr1oONhOEENSPFZz9UIYZwrWXY3QhOfGE5f73RkjlQNpDa/v4Vm6crLacIaVixOqCzGSMlGb7fAgGwHDtlicDUnHIA0+fY211gTMnFpFIGkoxIx312JXJc8f5r/x68MQD8Pf+4Ytcu3p7itafiRlKCMfKao3HHj/Gww8uEMkANZ6gzlGp+3Y/9Lj0bzJX8W1ESS0/ntQOCELDdmoo9TVM679qAupKMRMJKMAW43YYgy//txaWm4gdd7v/fabmoBjHq6qJAscEigzH0Jqx/b18HoFJHH1z6NY3XgNt4Oim4ztKhHPk3ZSDg5Cf/+dfIc88oYodKxDvGC7TYzAMAnq91Cd/TkeoIOErL97g6qW2H5MC4iRgZiZka2OIcJKF5Tof/uAxJCWgcoKdtuX8pdSDZeGB2vG1GbR99/iGv/cBlc0hAJE7sI5KHGKsRQaxD6wdjYiCKjNra6R6RGdzE1GkKBUh6g0UI4a7u+hun3y/g/HRgDhn0BJcT3uNjdFgHMJK4qBKFEQYW6BsCIOMQhgkPoO0zgc4IQmrEUHFYg4sujeinxuEKShsTtqzOCUhd1hbYEvNohISMNg8QyCJggDjcRFWOLTOPYnFyMdjBfUQO1vBDVMCFSOrFfRBDwJL1KijtfZuNArIclykyNPUaz9CsHlBIBVWW3SWeU1TJNCpxhUGAs/vrwcZdjRCdLu8/+HHqIohFzbfohFGnDt9gr20TzVq0XY7GN1GSIlIaqSDA6qtBapzs3TaG7xx4VKZ3NHhs2wUKKmoSMNMaDm2UOXMqSW2NvZpzJ+lNtykHoXopEpkh9TOPEwqJM4N2T52klprhjjvkCaWUOTs3LjJ3NwS6bAHvS1a9Tob1y+ztLLE7RvrLFYqHEhLUWkwyjRxpQFa097eoBA1pEzpDR1ZWGUuCBjs76O1o5EY9tubFDonCasMux0azWUGvT0khtZMjUA5jM6Ikyq3tjq0ZuaZabbQOqdaEci8jh3tMDu7RlSt0O13WDu5CAm0tzeZn1vDSEkiLdHMHPt7bXZvXuTcfQ+TDgZUQkVzpkXR3uHCG19l/tSj5IMuSWBIM4vLBhTDfWwtIet1CIBABTRqIYPRCFPkJDMzJK05gnAR1w+oDQqWTqxx+9p5gjigmllWZme5IG+TGcvzt7Z55OR7KPb3WLSSLDtgfzRLburIyjyX3/gqSyceZJB+9wpDAket2eTkA48yNz9TCvQ+fcBU+pWpclSbDBDEgnjGxzLKI3TljnrNsXYqBOED/DGlUC8A4XzfWahWDq1H4/gGUdbR6fTpHPTZ31Ncfzug2TS0twPmjmmaDUFS9QHA1gikOkqcMRbIx0aO/kDQ3vM7eF6UeU2WlLcuTYR1h9EWYxxFIegfCGo16PU97W4QCrJUkA5iKqGkspQzGuXshF6B5awjCARrqxFYSBJBVsBbFwo6baZMVb5EjRXCWgWjPCtV7gSDHFwRc661jHQODfRy3x7nHn6S00bzwhc/x/buAWtnzqCU5MvPv8wf+vj7efLxR3zcT1ayIVpLnmuyvCiZ7w7B40RumLIoifH/QJrlvP72ZYwxTBAPYtLHUgjqtQor87MEYeBdt0s3T0phTUlRAiwxRT4A1o1jbKZNev5SJ8bCno+dM9Z40O8c7YM+WV4w16ywtrKIsY6r17ZpNWvkhUZbx8JMHWOtj7ERlq++fJ680CgpGQ563kqhC7TxDIvpKMU6gVIh+ajH7NIqtza7dHbWyYddPvEDH+fW9Wv8J/+Xv0MgBc449qxkIYkZjQqyzgAbBzx57lEeOR1wfuM6r1nLg5/8II8/cIrz/+RXSZYW6ScRn3rhNTZN1QNRKVEqpNMdfivT9d/bMtuKyLTj+rX9w/k/pXLxc3nq91LonrjTTYMs5wX43d2UILYc9FOCwGKdZdFUcWUszjAtSPMCENjigN1wQJZrxmPpiJEJUCHUWj6/nLUOk0H3wCFDQd5JyIMRWjsGHYfpSXRxOORdKawf0TONF5epZLVSgpCCIFLowpIPPI11NDKYXGAyy/DAk2FkA28FUmFp2aLMlVS2j4+PHFs7SiBiHUioz4FFsnMZnDCEcV5alwKSWhUrJUFSoTY7ixKS5TjmVKgmFrspG4yPrQJOntng2tXNqX4rX0v4mM1arcb9p4/xffedJVBy6pxSUTL+PgGB43c5NItPCI6APWPAehe96UBRieCYgCUlGROBjNv6iOuyOFTCjG8wptMft+UEUpfXbRjPpGftIc05HlahsJMwDHBH8vId6W/jKGSPICx5CcYgZkqHcLSNDz8Z4xgOC5/cOktZXGzyxBNNdm4P6A+8ImBlbZaz99XZ2byKdXD6XIOVVe++qAIv48/Ntnj0kbNTg9yPHz38n1j+vu2igDCpkuseKlQYKciNRkhHRIAWFlFx1OKIWj0gdJosS1FBnaef+D7+3Wd/iXQwQLsRQRRijMFZi8kdcQSZLiBOcHGEMBabW9r9DTpdg7AGa4T3Qe9qyDVF1RseBZKim1FgcBKkcTitCcMA5yy6SImCCkJZzwYky3iIUGEECBVic4t1Bhl4xj1UuW6JkuNfG+wgRYUBRgSYUUYUx1QWZ2nf3kBmBdrkWB0SxhXQBUVviHB4EGUzgtAzsDhjUEZ7oaqWeOtRWhCEAQiLsI7EaVpBxuLMKnpgmQtTKknIQ8fneevmBqzM0pAHqO5FVpuLzM96EoPZ+1c5vqTYk4oHn3sIna9SrzSoVxIeu/8sP/bJj4ARyGqd3mDEqeOrNMIQqzS2uYKxhmw0oBGFdIdddgdDkmqLlYV50v4G3UGf2dkFsoMOSbBNXqkQ6i4m7SKF9QGjWYVY77Nz84AnH36Qy1dvsNfeIIwbpIMdiuEQKQVrqyfYvXmZSqVKXY24ffM20gieefojvPD6GwgDo8EuO7v7LC8dQyUt9ve3CaOArLPv80TUGizOzHGwv4MeDohlTre9jVQxzeYi27duUKtH9A8OeGz1aa70DrC1JrduvsVMdYZBJBmlm1RiQ3X1DLvtWxz092lUGwwLzUKj4Lk/9H387otXKQhpthrM1ZvYRoPt9i7WZez193DKC7XDvGA0zNFFQRDGdAeWjcttRH+fGwcF+4v30zEJvb0+RVqwlw1QsSKXksJCpjOazVmWEvgPP/E0v3thh/PrW+SjA1ozx+jvXENE3+mV4NsvzglUGDEzv8gnP/J9/MK//nVeevm1UpH4Ttrko0WFispinaO7nS9hJJibF+SZoN8vNzt7eN7+nkFYQbI63uxhNPIU20kyHVPgqNctJ8/l6FwyGGouvQXLK5YTZyTDgaWzD8dPevrhSRC7mMIvThIqwdwMIBxb25o8h34X9jPDyopPjiiAPHdsrMOobymM88yiTpYxFmCtwVhDvWFAWmZalrVVL2RY68hSyHPNMBW8cdFRFN7Fxzf6WMQsNdtRnShJDpmwSq1vEEUk1QbOGMADUmc1Ah/3IcuHLYoMKRMf4yolSZJ4927GQfOONNNkWV663YzvPe6FsRZ6rB8XE2EoTjRrq6seDJenji1IQngAXa9WOLF2DFMUPi7JWawTWBTOOWYrinoEW8OSCOdI7hf/rgKQShGGQRl/cSgiOefK+BlHrkGGFdJRSqPq4yCsdaggolZNCAoNCBbmWpPxmGYFJ08OyfOc9VubFKMc50zpzleSgbgyJtgYsJp80KVvHTr1SYGdhXPH1/hLP/IsywszUGTs3djmK+tDLhSOmze2yMKAFy7fZL7epD/KwFne+/3fx8c++BR//3/8NGl/m+3zbaSKObV2pmTHLLsiTL7hHPv3vawem6MzgitX20f7FpjYIcvxthw6Yim4kR6Og8kyMyUgXr86oFeMkHEOgaceHxUFWer7rdCWovBt2M69UDt2KZtYPCeP4JASai3pcws5yEcOsZ4jHTgboLfmvCIZUJFj+5qhWvPzJKrD7IqP03HOsb+doTM/v2QAcysRQgi2r+ekA4vOLc6WCgMBg+2IN37Z5+z06dR8ot2N6wWjoWXtvphaq2wIx2TsOndI9OAowQ0OFQjCCFTs3XilcojAuxYGsfREF+V7iomWyk1nDp80ugOUEMw3EihjeUTpSmaMd0MMA8V8q0qzmkxcBY+aY+6OmhuPgvGpbgI8vaKlLgSnJsalksJKgMKPDymPViZwR2/guGvLGdvcJ1j3jmeakaAiMbGK+XPHZylS69hM77byiKl/J3eZxJreq9wNpzxudIxGhrwosKZgdr7BiWPL1Op7GKFxVtCaiZmdrVFvBBjraDYUUeLfVQURxrqJi+hhze9++Z4HVDEKa/wGYi2YACpxTC4MUobUw1IzqARnTp5GHV9ja3cbZIO4XmPY65BmI6zVJXOVQxYGk2kyAj9F0gIRB4ggwOkCm2sProSa5J2SIsJKMKMcV4kwRYHKNEY4ZOQpe7XWJU26QqoQLSxBqEBrTK5xQUCgJHEYYiKD6wzwFOzlUJYli4t0hGFEno1woyHGxlg0tjCoLMIGAqeh0CkyCXyclBGoUOFG4JzFSIGsVCjw5tUiG2HyAqwgzAtUVAZICoeNAnCG3mDA7v4eYtTDKkmjMY+UIReu3MBYz1SzeuwcsSioxTVOzD7IrrxObVGwunqMh0/P0Gm/RRgrluYXcarJ8twC3//eZ1GiQRC2SPObVGoN0rUH6JuCbLBFnubUGu9nZ/8SdZOyJENmZh5g/fbXcMxSmIDZmfvY230D7QyVZJm49iDd7jr5aMDKysPs97ZYXlzl+Mn7icJVjp9tkXR3iIhYfPg9XLv9Os4aKmGT1eUa7bQNKuHRJ54jG+zx+tWL1CoB9x87zcH6TeaadZwMcKGgEcdElYBo8SyhcwiT+sV++ST1egOpJLrfpd5cpN/bJ5o/g7CG5qNP0U97nFpdJg5DojMnEKFFOYMoNN1hHwHMzR7HqYgkEChbECQBjz36FOdOXwMKWo05bF6QDdp89IOP0h5p9ChjmKcgHMdW1mg1Y7S1hJWYTnWezvJDVJr7LD+2TL9t4YECvX6d3ArqOue+2nFsUdCUIWFukNWAfgpf/syXUMfW6G9ewOU9RlaT1APSzuZ3bA34vRZRaigDqajGIa+/9ja7u+3yqLt7R7pXOVTQ+q9isseW2kUfj9Nsxuxt56UW0aednWlJBNDZ0zRmvHUjDoW3vItpgQLCwDE77wBL3BNkNxW9ruD6VUt/YFk55t0h0sKRZY5KxW+aRSawRhKEgt0tQ6MeEoUWY/16ctAz5JkAZ8twIEmRC4ZDw9KSd5RTarydH7L8pUNNkozZuryGMM2g39dcuWzZbktwntlLCDwFLuOcK6UO0xmKnbfZ3fRa98N7wA6Sy6+8SKVS5cknH+bmzQ3Wb28hAxDYiWb0la+8VFqdJL/zO1/kS1/8KnElpjW/hHHQqFZZXlpAyrH1iYlH1rRQ4WDCruXjoST1esLjD5y8t2a+/CJVQG1mHlMU3L5+A609S6hEkRUFH6l3eE+zy39+cY6t0fjeJWQTJZgSkvm5FssLM55iGg5FI+GQYtwPDkyB1pr9g2ICTB2CYTFE4GjWE6+MK58xDiXf9/hZsqzg2oWrDNptiiItW9qTHh3qx33P9Dsj6Gx4QU8IPv/Zf8sPP/d+Kp/8BCvPPIjZvkL/F1/g9d1NLnX3+L//03+Hdjm/+YUvlNpvg9WGKIjoD1J2Rzn/t3/7ErWZOooFHgvtlKDlmHPvHt3xH0RZmG8yHGry/FBDflQI9cXh+OCsZiWS/Pc3p0U0wTQCEpQJXfExMcL6/fi11/f4N7/bxxjLmfc6Vs4e0qlPC65HyuFQBfAuuCXA8pNhMusmwM5ZGHU9yAYwTjGz7Bc2ax39jiZLLdaCCiWNOZDKsr9d0GtrhHEIlRDEvp+ddKUl5lChtHVZsHfDsXDOsXzKgy0xRYgx7AqGPUmtZUvLV+mi3HeoyLF8ImZpSbF1Q3PttQI7CtjbC+nGBeGj+YRwSAoYGcd1o1kMFdXwaCON3/6P/eAJvvDiGwxH3nWy0VC0dzSNmYS5uYgf+9g53vP4mZIAZqxycR4giaMY62j731vgj4QgmvCylPWMu2TqHq60dN+pADr6yR35c9cjlH9rAqpBuc6Jo8cdgq5xbKYcsXCKO2sSfhzbQ//Ge+6T7uhVk99GI02ep56cLVTMz82ytFRhHtBGc+7cPI8+NMPGjTq5tszOBYTKN4oKQqylVHD9wQCpcfmeB1THVk8zNEMkkkE6whSGxtwS/YM97j/xICfOrrG/12Zh/gRPf+hjVMKUy5cuUmvMs7SyQjNO2M+G2CDA5QVhFGEDQ2ACrJAI6bDa4PrGazYcIAXOlc6eQnrWP2ER9QCRWoTFZ6iOgpJb1CCi0GuBSlTvbICwBbnOfR1SIoTDZgUmEmgMhMonFJYCGcoy94tnUDHDIU4JZBLgrEZqi0DispxCKmS9Agd9bGoIGgkOsMYzoWBdGXA9QCrlKTFlgBUGEXsN1Kg7wAofBxBIR1SN6dsh2+1t1k5+ABnG3g2nKAiiGOFS6rElcoJKIlBYwtYxZus5moKeE8zX5pFFE6NChrJK7hrk1BjIAuXmaERzdPtbDJOESm2RIDtgt9dlKEMq9VNk3R4y2COpzNBaeIDb7esIChpqhnjuFFJv4YYj6rPHieMamRpRma1zcu1BspvQO7hBNa7y4Ln38sIbn2Hl2DI2FZw+8SS9wTqBEizPHGNhvslX3ngZkJxZe5q9zjad0SUwkkfv+xBp7WW+fO0GXWNoNBexeU5hLEYbKjOzyKKPSiqcOvZe9nr7mPQSlVqVB+57mvNXXkWJHiIPWZp5L7c2fpPZZkAULbLcOM6VrZcxRcHp448zMzhA6z1kENFceB/bt79EJRZUggW6nRVyt44KFUW0xOqx4+zsvEoxLFhceYa9zhWU2SRwguWVTxCJt8iyjHoropIss5t02E473Dd3nGqmmVsYkrbbnDr+YW5df4m5ekAkYuZWf5hhuEU1UWRSMhCLVGRAoGIefvzH6XdGGC5wMPjuZfkbC+9KglRlgvDJJnEvNDWGTmNhlyObz73UlALBKIXrlzPiGJAwGllC6y3hYQCVumA4sMSxJJgwfLt7VglQrzlO36cZDB3bWwKjBe3A0TswFNrRG1pC5YgDg8sVzkmksOQ57G4aBAIZGOaX/UZuq0wYpISwxDHMBs7nspJT2lGPOrDOESWO/iBgOJC0B95an6awc9sy6itmIoUTsK1zYuCUs9wQsBpK3l8L+NQww8kAgQHh1xPPM+9KTbsCK5HVCo88dB/zsw1CaREkBGHg45aEJ+NQ0lvXIiE43e8SVWrU3/+Ejz0tLT+HnHrTqt13EkTGVitZxiOJoydNgypnGXb3wUG9FmKtpxK2DioodlyT14eKY6vzzIytk+LOWwmiIEAKLyiMvYTGrF8CGNMRr8xXMDPxIYCHiVDnx7Is89ZMFOJIJDKJ+ND3v59Ll5b5+ssvkNRb9Ds+IHzaUOL/Tn+SjEYZSMFg0MfmGcONNt3OkLZ27Gl4/kuvU6QD0mGKKPepSCmatZDRKGVkNDv9gIGTLM2FjONXfJJlSyC/e1MvAKw89RBf/N1LFFkZu8a05v+wSCyxcp68QI417XJqOI0XEzuxInhFg2dwSzPD+tUCrS0rjwb3llrHX+/o06O/eyA1ztd554nOWYZDg3HeIhvWFdN5rvxz+bFpCsfW9QyBYNgxJDU4/kDkrdhmTGbgn3/QcbzyqQijBSYPMLl3LxbSHYKIMiZo1BXsryuWj8OY5G5/R/PVT8Px+y3v+1jIzGqELAre+pym1wnJRwEqFAxPpD6+XjgSpQiUpCjp0H1g5RScL9u5UUl4+JFltvZTNm72aS1U2dnY58TpGVaXI2r1ClGoxg3k/xzpsyOtXJ52ZJYefnI+VcPAHFrS/DwXKAGt8GhM6zuh5W/Q/e+oCzyiD5r6UQIVAWcqwSGZ4HjNLDVQFshywy1Xug2+wz3u/c5+RRsONXmWl8PdkcQJWWbodLVntLR+Td/ccmgtOLbmvKunEASBd4cx90jV8m4zhX7PA6oic2ij6XXaHiRYjYgbLLcWuL11k9vb17FCsXzQY2XtLMsrM0RRnaqKGLQ3UFJRixKMlaRKY9MMGYbQDLA6g0wijfEgSirvfpNrKH3fndFQOIRQOFdgDKi8KDcLhbMGwoBqVAXlGHZ7XjsT+QkohfI5o1RIlFSRiURLh+jkfsCU7FG2sIhAjONMcQiCQGGV9MmAnQIZUDhHWBSEgcKUE9bkFqFBCu1dBo1BITBWIZ3AjgrPbqe8tS8OmhRBQWE1wkrIDYXJCOKE3jDnINUoG+CsZW5mDucECSHoPnkesTM0DEdtLu9/niSpsrJ2hgtX1+n2P+vjU4QgYovshTeJVIAgZKg3yQtBa26ZpdoM7fUbaAwqWqKIJK9efwWDoBrOEJmIg53zDOIFkrhKVmi2ty5SaZ7k+JlFOnvb7PW3SWbP0KzUuNBepx8EhKsPEbRm+dLFL3LswUcpioxaHLPZ32PugWdQSAyGq2nOwv3PEEcxwyxFzkasLjxIEAdc2rmBrqwx/9ASzbRPpCJq1ZggTsgGPteERLN8YpX+QNOoNpiZ/zC9Toe9SkBt9Qyx1FTrTTqjLsmJh6jFIdlI06/PENj70VJxcVRQqc9RCeZotma43u4QzK8ShwH9qMJgsE2ldYwigtzFhFmfvLJE9cQsrjCcXD6DZJW1ZkTvYJ+srxllKQIYmCE7usJON2Ln0jYFETOr5zBhlXZvyMq5NXIzQygCCjsiajRpzFUIZcD9D57F1gXyySepBouEpx39LGLQ7/Lp7+xS8G0XgcIaR6/X59d/60UcUK9X6PeHE8z0ja8/1HAe/jJ1XHgSAqN9bqdq3cc83bqdI5XkzOmQMPDuXGF8KLDcfduxeO3/BtIRxN7CIVcA68hGGpN7mt+Zio9nqiQWVR9bnrwFKUs9e5YTjiITVKt+E58msxhbx8ATWHS6kjxzVKueASvPITeaK9cF2cAxTD2Jhc4ccVdQMZKPz8zjhObn+rucDCV/76k1/g8vr3M2qvGhQPGvujlaByRRROw0Q1sw0kyEndW1VT7+sQ8ThAHVasyZsydotRq8ff4Kly5dwTlHoCwzQYVMWZRSLMQ1fnRvn2JhlvPVCBEEHNp7xr01rbJ3R9q3fP0jPTCVleoefVIWo8FBEoMPWj28dp0W61kLmTiq7g5gdpcdwxw5Nia6nh4TYeDj/O4tzIyl6LEQNvX2wrGw0GJzo+n3HxVxmCvpnqr1w/dwFiECdG+E7fXZ+vSLpFu7mKtvE3eH3CczdGzJoxYaR2YMB2lKvRIxHPUIpOO/+ennuO/EPD//lQ4HhfbvNFEc/MFqm3/fi6rwa//2GtpwlNQAGLdjJAT/sxXHY7WIWCr+wppkpC2f39dcT+XUSPBunNdfz7l13s+/hfvhxJM+vsYDGem5t92YLfIdJG64i/jmiF6grO6u9caBChxBLLAG8szQ72jGBBhhDeIyP9J4/IwtLVJAbaZ0n7XSxz+VoENMmCeZTEVXSA42NVnXzxfnvC5a54qFNYeUrkxCC84K7MCy/maA+2CAUqBCRzYKyQc+MhsrMblAOh8eYYxGl4BlZD37IEJM5lQoJYESBKHixGod7QR7mynNRowKFLPNhIfuqzI7U/q2l3Pr0CJ1rzk9/X3K7W/qV+3GubzslKW83E2cZ/JzckKrc9e93mH1mnx6Z7D1DtDLQSwFx+NSozcdC1Za9x3QE451N1YGjFfVbxHMOOFd/rIcKRxGa4aDIdubexz0DDKUJTu35aCdk+WWr75QsDyTIHBIpbDGJzf+xmbB3//yPQ+otNQMux3Sfo8gCSi0YX3zGkKMJ7ohTBIaScKvfPpn2Xj7IsZZVBBTSWJEANpZBBapDYXRyDgiigJMVmCN9YNIGIQZazK8Bluq0GsujSWsVijSIRifJwRtkIErNd6G/mhIEESopEKYJESViG6nQ6BCXGaQSmDTFKNBVCOiSkKuLVaWmWRlScVpfXI3ESiMU4SE6CLF5R7ZG1uQ25hakpAnITJQJHFEkeaY3Hia5VD55xIWpyBIQvI8nwzQwKTe/U949hRnLEIpjNXcunae9vptIhkgAyCHM8dP8Lf+xl9lc/smv/XqbbI0o7N5A6MtzYUFXrr2FqGUXHv7bW8iVoogECwsrHIwGDLsdtFFgdWaRqNJtZ7gjOPc2eMcjEY8eN8qpxcarKzMEwZw/fYm589fIa40ePLpR7E25Pp1zeKi4tOf+SVU0mJu6Sw6lezvbWKyAdsb11FOsLR2HGfh9uXLJPUGb119G4XlxP0PAV4Dl2Z9Nm/fJo4rzM4v0+n1cUZz0Fln2G6TNBdYPn6a7qhHEMZsddq40YBs0Kd57BSBgINC0O93yNpbqCgiah2jvtdBWMVwMKC7+SXCWovlk/dDHKJ7XYS9xdatG8gool5rEEcVtCmoimtsd/bJjWG+Wqc1N0+v30MQ0KhWGOQZjciiIh83YtJ9ji3ME4URw02DkBnCaUbpCLAM9q8xGkquXrlFkGzSas1SWzlNTzt0/wZ7VtPd36XXH1Cf3+TBhQ8RxTV0kXJ54xpn7rufXsdwo/1yaXkZEoXfve46KqqRFwGDXspXX7nA/+l/+eO89rVXeOHF177lOqYVvJMYcxy1Oj4GAYdwsqTeBSkceQZx4v3kCw1xLAiUI8/BGYhCGAck3+OO5Q0dSQhxsxRmmsVEa8xEcJcTDTc4X2/Vb4zWCYzxmuOxxtlYS1E4kjKkJdfeitAfOi5dEh6IOcBZFpYF29uaNBXY3Fu+bWb4T0+t0Estf3djm8K/NhJBOtAMUsGvDDMu6gqdtkIU8Mmm4szeiBec4At4jb1DkFQqrK4t4UGdb9OlpTmCQHD+9dfIRgOc7vGArHCBAVpVOD6zyM0f/CijNAUlSsHHHfG6mYZK3OuzOPzu7rFXT0TX6Uon+bbEtCzCFLnyUc2wm+rZw0Fzx3n30gC7qfPEkZ/HAtkdeHDq/DJZaaCo1OuoIEBIdRTDvUPxMTmGYpSipGBpaZYkd/zFs/dR5AaBN3B+Lc+5bAy3trd46dolatUqW502CMHCfJWZ2Tpx1ENoe8fbvbva5Xe7aCfRxpRj4o7+FIJqLSIO4dyMY1ZZQiSfqEiGheHtvuZ6egj5wXq5YaOKTr2VtzKTUXKyIZD4+JU7SAp4J1h8xzifyNzlc96BcMZn1xYE9QXB8MDR3Sk4aGeTy048KmktKL+ulXKtsbB1WWILNxnfR59HTOo/xGECqx3dXUvPeXdCXViK1NFYFKzd592Ve3uW7VsGWREoGaCkpLdtGawr3vy6wVpBq6aohILtnkZnhrfeuMWVt9d56OFjnD6+Si1WpHFIjs9AMw5pMs56DyInWFqskWnYuD3koQeWuPRGlw+8Z41zJyFxYenmNlZR3LuNjxxxR/4cKSGOaJyB+A59nF+f7YSSfrr2d9J9iIkC5u7in1oc+Tb5NEnxcfiwd/WeFXSynPYop9PL6ByktPdHHgyOB8BdU/hec9qRZoYiK3BCUGQpEkUUgrUW4Xy4iXEg0GS5QR9k5dARCKHY2tljNEqnbjH17O/iOvI9D6iwGSbPcM4gSRDO4pRABAGxAuEq3P/Y46zfuMZgNCCuVak1G3S7XZ548j3UZqp8/nO/RZr2MRJENcRiGe4foBDYzOBCQaXVJBum2FQjDYgoxCrvEqeEQEsDsUKmFmHAlcHICjDCSxTaFijrGBWO4WgIRYGwOQ6DNp7IgswiA4kKoNJqkWYZptdDBhIXCFwBWIUKAqRyBE6jQoVNJHpUIBBIYZE2RxqNLLXQUTUgsxlWSqy1GK2RQvqg7mGOxSGF9G4IxuCEAWFxytOnK2sRRUE22md0sEXVKZqtFvedOA26zfO/+Vucve9BwpkTNFxAa+lBBsNd+ru3EFIQRTF5us1MPeHq7X2SqMJSo8Go02Z/c5PC5pw6dZqT95/m+o1LqMISN1s8vLbCysIClWadMIkRRrO8dILTJx/CFn3yrEdj8QQPnz2OxdCa/6NcfPMWZx9+kG4/pZIsM19JOMie5uZWwWwjYKYWcdAryK3l+NwiQjoqSQ2EotCaY1KysnAShEAnNRoyQpiCz//SP6ZarXL/+76fSm2GlSAmcA6hBCYdUUhNvdJCSkkuJYva+GR0FqJaC1lSwvb2t7j++vM8+sAzLB47h0sC6tLn/5pZPYcxhlar5b0enCHM+zTaOygH1Tjg+tvn+dJv/xq3N26SZxqFwlhv7RAyIJCSpJZQq1eR1mGcYHa2Qppl3Hf2fs6sLWCTlKd+8BlmKjk333yNN7MGQaF56XO/zuzMHAtLS8zXApJqRH/QppJY8mFBFAqKXJMO+/QKR3/nFr1Bl9Hg4Du8EHz7pTnT4qkPfIIf/+SzPPf4Kv/P//YfcvnKjcMT7tgo3lEbN9a2lsK7VI6zZySVGqSpI8vFxM4x3tiyzHDxYkazKTl7xi/XSvr8MMZREtyML5rWUk490wRAMaG7HesVjZZImOSrmkg+TmA05Lmg05Y+PYOAzoGjUpUMB46lFc+8tdMW7LUtw75nBBt7RDq8tWplWZBpL2w759i56fjSRg/roG8MunRxe0sb/uzXNtnXkqUA/o/P1fif/+oAWwlZaCUsNxWVUQZX92i1Gpw5e4pKtcZY4Ju24zQbDT7ywWe58YUvcmso+ZOLM/zSEJys8MnFJTrHl7BBjBCHlqJ3NMJ8y+WOi+/Q6t9peLrLKjC5bBxcPw3yjgLnbxVmHKn/XlaG8VljOcmBMpYgrLBy+iHS0YjBwS66GHFoDbv3nV2pTS+GBTKp0vrhD9M4f43l5Q2MsISziR9DL95g/douneIWKhBUkph2p4+SgrhSxSG90nF8hyPC/HdvGRXSK2CZsiiUnyqViL/y1z7Os0+eZEEplNGMbrXZ/7nfBj04wjzngLwn6K8HWC0mK4Cz0o8SNxa+7+ifI1+OKgcOmeA82DvSy2UnOHfH6HGU8sRh0ugJECrvX8q4h0uSEzgt2b3lEFhWzwnq8+NYiUMh3d3xDjoVzBy3yFigU9i57Ej7Dodh2Auo1RXb1w0v/GJA/XiKCgKMsfzGP/Q56opMEtUdD52OuO9YlX/5mX2GByl2OWdnM2VluUGxnDO0itujzL/b2CQ0XhPxCac7A4cKFNVGxPxcnTAMqVcSlCy4vp+ymR7d68br0jcHslNLdvmzLd2CKa1yYsyYMYV5x4yjR+bnHXPGTV0zySFVVjD2aTj8Z9KBR7CZOPL9KND2Vwgq1QbPvvdZ/uu//UtcurjOzRu7FPm4bw+VXu+AoyZlOEppd3oU2tHtdhgdDIlVgKJAWUG70+H6tRyjczASGfhx6Erm1O3tXW5ev01amCmI6FBS3lMB9vtVvucBVSMRdJ0lcBY9HCDwVI/WaHIpsFJx/eJlz7421JDUSDNJOhzx4isvEMiALMuxufXMSsbibIHTGq0tBAEqDCl07o/HCicdTlqCKPGugMKis5QwUIiKwmQOazVKgFUhUklc4J/JESDTwlN4Ga8hlkhMkXsTbyBRxhI3aljtEKlGRQFiZLGBBqlwSnpLmlOEzYAiGyKdIq5XMJnDBTA86OEsBFJibUFYr9KMA4pc45wh645AO2RhkVIhhSSIBAuLiwyHBVmeI40hd15jEFZjQiF45NgZjIUPP/skwd41fuiP/BS/+dIr/NYrX+MLVw54/Ad+nIqCOJZs9mdoLZ1Ev/U8xX6XZz/6E7jBJkljFyUEYRhyfG2VlaUltLPUWjPUG3WWl5boZxFvXtpD2IJGdZO4knjLnhJoY1BOY0d7HHQOOPPEB/nIsw8xV1Ocma/RXZ1D6T793JAWKasNQcUYhEw51qgx2wzpdDIiGdNohUhpkc67z+SBRLuARnMGn6NUUEFiRECAI6w2qc4uESApcCgZeI1KNaQmA6TwXhihczgliFsLSKdwgFIQCEUviLC5ZW5hFVmvIIXP/aLCmEYQUjjjx6Fw4HLCuEVruUaAxoyGLJ97kGdtivv857l68TWMcxTaJ2eshDFaC0wAMggInCWSDjF0vPGFz5P/mT/H3MwCkdkgSVpAxsHxM4QXeyytHOdDn/wJzr/4Fdq7baxQPHzqMQIREgFqpkV4sISq1ll+4HHq2YiQZzBWMxp0uPD5X/mOrgXfbgnCiLn5ZVaWFzDW8iu/9jsMBtldm8I303tNFL6AVBCGZUwWgpu3HL2DsevVWEhy4Bx5Zuj1LZtbsLSgUEocJrOEkq54WkaaUnk6wUFHECc+BungICCuWg46AcJa2u2gpPW2hIEhSQxS+EDyUeoZBjv7EYO+YzjSOCkIQtDasb4pUcqzaYlYUKsrGk2BwKJzw5U3Cm52JKrpsIlFhh60ZQX89kHKchCwKALWnUHgeHh2Folie/uATBuKHlgrefLkcS702rwYLtIvugjRYWVlmR/+oU9gprPwTnVAGIWsra4wSkJ2c8WzjYjP55JKIHm8FvBVFIVQh0IJ97b1fLPi7vFp/Cz3FJXuBFX3+nH6VaYEo3dymbkL4kxJsN8KCJsWZVU65IcHm7zRz3FIhAqIkiqjQecdNMxHK7K6gJGPc7NW4rKCXFte3G3zgWOniEM/8AWebj6OQqpJQLvdo1VpcvtGh6VYYcbsBGW9307f/PtWPv2Zi9y81uEQHB+KqkJAo1nn1OklKnGIQxBUauxEAS6X2KkrBI6sUyXrVDgiWZf54ES5n4zL0ZabVqj479OpvKfPtXjliMDHVo6tR8Ah0J8I6Yd9dKhQ8uJ92nN0twL/eFYwPLB01yNsYZhdlNTnJAh7WNnUhBbOEcUQEoDUXnBWoI0l74bsX4g58aAliaX3lMGR7sT+zk5hUjlZH/VQMEwNVgikg6yfE4QCKR0KibT+ic30Qj3VKqWxzM8L4cm66o0EFYgJmY3GYa25Q/3BHfNG3PvnO08pn9ufJEvwVD7RkTVkaq6Ie8z4MSi8q4+mgc2916Cj/ImHYMzddZn3gKgGsDA/g9GWfqfPoJ/e403LzeouRYkPU3ngoVXWVhukuk6nPaBa0SwdX+I9H3iOh4YFgRI0Zxq41PGDP/T9CBxKGNZWExAJRZ4SCGjv9Wk0GiRJSBAGzM7Nce36dbT+Fszt32b5ngdUiZIQK8xI+SRzwhEoiXAGkxucg67eQSpJYS2NeBZb9AnjCnmaQm3GSz55hlHSW6WMJa4lFGmKKQy6yBDZOE23QEmFRVCkGXIcNarwLDZYnDYQSAwWm+UEQYiTAoyh0BpV0hI765BhgosCn8+qyJFBTJTUGBlBrZmQSNAjQ04PaUCGIUZJrLIEhaYoNM4FqCCkUhH0ck2tkqDikHZnSC4sygW41JBHglgpZufrbBYZgYnQ1lFLYqzy6P7M3AJitc5XC0eRDRC5J81QQlFXEX/mBz9KrRrw7IPPsPTISba6I772M/+AK9s94pUaT7fm0UGAkQHVQJM7x1zaQ4e3WH3gadbf+C3ePv/bFFrz5BNPc339Np3tbUZpxvs/+qPctzhLrguiQtHt9wjjOs1Gk8zCyEoIYqwsoDJPuHCWhWMF7XTIz/7Cpzho92guHiMrFEmlQqE1UiV8IVQo410nX/469NobbFw5zx/9yb/AieMrhE4hrUBJSSAVqYGiEDgpSY1FIciRpFJSEwqnLQM0SltSBHngA8CzQhNHdRymVFdbVBhiAS0sISFGWlxuSAcpozwjsj6AfGQNgXE4ZUtXz3JjtAEFOWHJDFmgkaqGEDEECUopsJ46Fpy3YjpHIBVYn5Q5kiEVKUkoMGlGs1GhOjIEC4s4PeTMKGP99Vd47a0d6tVFBjubbNx4E4Sgeew49ZWIpKqYVzEyrqLjgCKpUgsSrDRUHYgg/k4uA7+nIoSgEksa1YT2wZ5njruTlWlK2LyX6DdJOlnuksvHFCvLijD0W5XVjmxkQHjr03DgiGLvEgyQjRzrG5p6TaGUJZBlPheBz4OHp+61VoD0m5uUZWyW9ZTkWkuMVWSpYH09JkudzzQvLdsdRTpy1CqO08ctQmiM8ZTutWZOdwi9gV/jXCngHrQNGEcoBHkIMipYmFcsLgQ45Xg8sPxn8zP8o/0+/7ptJptyIOA/ObfGj8y3+JdvXub/NSyQVvBnH3oAHVfYf+kqFVVBLi3wd/70Of7F89dJ4yqNpMIgS3n/c+/h8ccf8rTF6s52nu4LRyIkUkhiAYEQVBDMCOM16lMCxpH9/RuUiYbVj4xDGXPa/CTGAuUR3e471Tj1+W6h5u5zv/FTTu74TkjqnucfnnwwSvntz71MNlRYEbCX9slGvW9eEb4ts2FBAThtGLz4Oq88/wq7meJqYah95U3mhKW2MeJcnvN6nmKTkDiM6B0MubHZ5hd/4yVOVp8h1w7GCUXfTZXyH2C5enWDdJixuDTDzFyVg86Q3c3O1HAtwU1pCbI4jBQYpLdSHOn6Q9FYOFduJwLhxjZrCWNL2ERj4KYvx5qyR6XzzJCHWcbp7xn2b1r2bwsqi542f8LpPpbsncBZr/RFQBiXiakdGC2wWmK1YOcqvPLLYWnhEiAinLNYY8lHjjy1hJUxAcmhFWNsc4kjy7FjknxHstUxWGPo71jyvsI6yWAfkgiKoeDEsSqf/Nga/+oXr9Mf+BCFcfpsV0g6+wW91YJACJSukPUMc60KyvkYsDCRhwQcZftO/i21VlIIn0c0CAnDyLeNLM8aLwlTfXX4WdxZ7WF7Ts6785zDjj8CScTUhUfKPdaII1UeqpDuUevROh2T+N47X+GIImisv3Fuwjhbq1doNCPE+r0f6eijHt43ihXf9777eeLhVc6dniMKI6yTPPz4aVZOrWFKl/hqorxrcrkPhoEgDgOiUJIPh5w6Vmfz3AKPPXKWVquJUgGNuWV+8ZcOWN949xiHv+cB1SDNmG0lpKMMUUBmHHEUUuQWY31Qn7UaZyyVWpVmaFk7cz9Xb93kYD8jH+1iy/TMIi8gkKgYEAYhFCrEa0aiAJv5JL8EPhmhyzwSFkogqz6w3Y58FnIhLAQ+0NtaDakDIfFGe4ktNATCU5qnGilDomoVFwYo4bAHA9J0iFAggxipAqwrCBRoLJUgRhtNoiRRpYpUFhk6FucUg9GIYU+jDOgCAm3JHdSCCn/6j32CH/3E+/hf/2//c4ZZQIahHidUwojVY2ucmJvhwsUbzFVq7OR9avUKtUodKUNCB1+7tkcSat56+ybfv/8cL7/6ddqDPmk6INu+RdHdQyPYWb9NJZklqdRptFbY2WsTRRITNIiSOibtI6XCuYBCSJxwKDPkwFYZ2CqN5dPUVwWxc1gZIArt3YyzIVEYobMRUnQROicUcObEKslxD1L2+inNWsiNdkpFOo7PVxkVmq2OYb6mOD2zwGzjaRZaswRILJJCgnQWbQKM0YQqRDtvzTNSECmBlRKimICA4d421y+9RhRKZBAyN7tMElXZTW9S6BQRBBgVEyGYWTxGLiAOKtQrEThLmndRwuCwaCcQMiA3OTY3BNaic4jAAxYkzlkyY+kZRxzEaGeJVEigAjJyAiGR1hFYsIEo6WW9j7IRjkQKKkVB0TugtjqDbMzwmc9+lZ/92Z/jvic/THP3GjocsrWX8+Rz76ezfR2dj6jXW5w49xi1Rui1o1YQIqlHipEw4AKcFYR3Sr7fRUUIy7nTMzQakj/3Z//PpNmY9vjuXeLeFguvBV1b8wBFSqjULHkhKAqBsZBlPsgWAe19x8FBwdkHFM3Z8dYl0AW8/pYmCBwPnvU+5QL8uuJABTAaCYZDR28gUdKRVARzTe9kJBXESYE2Am1yugNDez/zihtlWV4O6PQFr7zmsE752K3Mv4e1sHImQkkf1+Jw9Nvwh7XiR46H/O0LAz7ft6Qjzc52jtGWD2aCBQMNPQaT3oPfIsiznF+7vsFX+zknCokVPifaR95zH+9/9mF+46tvEzUkHz62wFdv5Lx2uY2TPn5rYWGO+fkZxkLXdIuLyWcHzhIKRYAgKOnYAwWVsdvMOPnWlLb9SF/eExPdobmeVhuPpampfv/G5V4CkfgGx771cuSx36HKO8EUQOHgxY7hT8QRz+cj/se9LZwzJTfH3QLX4Q38/9pZtLUYa3C64OYg5WahcCrgtRtdzmYDKgWcHFneo6r0W02SIGLUHyGEYC9TfOG2IwgiYmPJjJkSt767gdWrXz4PQvKRH3icD37sYT7326/zqX/xpckYFHd2VhxAPUJ1S++YSSvc0Q/jr9bHOk7qm6aZnwJTDr/vf/3XFP0uNE8Ynvi4Ld32fD9mQ9i5qbn9ZsADH5EERyRFMblHkTmKkcAWPnfRxBKSgrXC/68Fzk45t5UWk8FuxBufdZwdFpz9PsFoaOntC4qBYHW1waDr6OwXDLoheabJroZcflVxfC3kqXMNvnJ7gLXw2qcVUgFCcHolYG05IAwVYkL1X8KISSJtg1IQC0n7RsEjH1oi7ee89uoW73vPMQ+QphDR3XPIk2goJVFKgJOHh9zhiWKyHhyuC0drdXf+OPWbKLHKNwJh73DsXsePFHHH3+nHmVpBx3jpjmqOrrp3K4E8WYZBSDm5Vtx19hicH11gi8KwfnubVl1w49oGQvrchsY6kiQkjkPiUDLbFGWuP1BBSBBFntFVehAYVRvc3EgxbpOZ1ogoivi+Z5fK+t69deR7HlBt7/ZwgWamMUeepzBIOffwY1y7egHd7qCE8BhIJVQqTVbXztBPO/T7XaRSRHGFUdrDuQJXWJ/LKY4plMNJiTAWtCk1SApZxiAJ4RNueqWMghTP7BNIlDZYBKFUXrDVjjAKMdLhcoMKQyQCWYkJEZjckhtNNkhJgojqTBVbldiwirE5whaoIEYYi8ssUilkIgjDGImkVY34kU9+mCzb50svv0q308dYiVSQCEklCqhVazRnqsSdPhe/8EXuP36MaGaJ9d0uKrM89dAz/Ok/9adoNSP+xt/6WyRmyEpcYZSn1BF0c42oRtw8aLO1fp39rQNeunKbr1+5xIn5Fs04ZCg0Iu9z6/pVLl98kyCa4eTJM1SrM2S6YG9vC0FGv99BqQihokkC0qTe4sTj72PPKlZPPsLc6vHS7UkQBYI00z5u2hlwDu28O6POcnShcdIhVUBdCKLCenrT1JIIQSUUzAhYs4rZwHG2othIDQMc2gDCEClFSEBFWIxUdFxBRIwm8FSrzhFYSxRGdDttfvvn/t/kg32CJKHWbOGcIh+lFFlKLDyYEVFMGEgiVWGkLUFtgfmFOo3ZZQrtMMZrZy0CJx0BASZwOC3wykA7STAYIYiU8XT7WhHKBCPw1P4IAuFBlBMOpWKkDBDSJ5F2zhEJkJmhu3Wb5soJrp8/z+98fYt1k7Dxwit0b7zIIw8/xPzZNXbXr3D/M+/jzeefx0QxmTHMicjneVOKDEGOIrCesjcThvy7OIdMHAVUKwmjUcb6xi5jL7O7tqt3NEh4RryZFkQV7+s9ygVvnzee0bPUHk8cgRwY7bBlGo2xO42zkBWaXAl29qBeU1RiD/jSTNDtSjb3LHnuMM4x6koqNUMQ+pxJgQKhJE5KzqgaH69V+XRvg2tpSjp0bGxq6jVBpJxPHBk5Rlay2w4RzlGpWoLYTSxj1jrmBBy3gor1QfCmEAwKh3OCL6eWv3Rlh2uRhFgc8mAIWDrVgGSRR+9zvKdaZ7S/QxyF1Jym6nJik+NcDCZj2B2QpylvXL7NYJDxwLmz92zu6a1ddQfEO/ssCcnZuELgAlbiKou1BnEUIX0eYMYa/nt25R3Y6R3lkyNCwd3a7XuOkXtX9A1u8v/HOe80Dqce74h4Pe4XJxgOM3IZsh2EDKy56/pJ1Q7COKE1t0JeFAwOdrDWKwu1E+gs9XlS8WuYATbCmB9571PUooDfvHCTX9va4S88fpqwWiGzGY1qwv/+L/5pzj58Eovga6+8wW+9dcnT0n+XgykArY2PSZYSbWE4TEuLjBdeJ7FK5fmVVkJSDbDOIicWJ3cH8aQ7/Ou8MvbQouDAleRbAhy27GiJNbC34ei1JUTgnJwQqDivi/AYzYkyiXRJEDJN9+egv6exWrB5PmHYkTgpWHlQk8w5OruGYV/Q2VX3iFvxFqysD/12wbDj2L5hePN3Ypq1mP/iP/sBXnlpnX/yT74GOHp7wruQAitLM/zQR05z+coF+kNP1GWMA+HIi5RsOCoBqJiAmlYtJI4V9SqcWK3z/vdX+fGPLvKZlztcvtql0HDugSpjXr/DqTNZgBmj1bEVTRCUKXJKa5rwMVZ3qg6/2Yy+u2W+hQu/WaV3ga9v4do7rnkn1c5dAMsdLi3jc40xE1fLOys/Ss4xDSwFRW65dWuT+SXJ1Uv73LjSodvzXhsnjldYWazSqEnOrJZ5AIEgaaIqLaQQk/lVnTvG1r6l2+/QamjiOOLxJ/ThvHiXyvc8oAoqCcPBPqOs71mmkFy7eon+fgeED5QWTjE3X0UozVvXvk46SkkqCbV6i/buLjYdYV1AmISEwsdUOQ0CizWasBpSaB9sGlYiirwoTZ8G6cBLxhInIWpVCEOBFYpKM0GkIw72UlQ9IowDst0errA+eNM6XBhAoIkCizWCIA4JayGxKBgOByRBTJ4X1Bo18tB4F0RdYI0jiUOkMCy16nzsfc/w0msvMjgYUa3EVBOD1ZpEQi2OmalHfPzhB/hLf/l/RVyvs1r7R9zMK4RLM3z1s1/lE089zLmHzvKP/95/TYeYxdUZKtUmTmvWb11GbR9gZEBvkFKpztBJ19ka5NRrNW5sbfPU00+wu6/J1Szn3vcAp7/vowgkUklCIZlpb8KooPHAk8wur7C3tQOBIjeGJIj4wCf+MIRNwlDRWFwhqNTIrPHA1ViUCCiwWKfBSgplEAa0jAmqFZw1OBmQG0MUCZwNCGTqY+esd5NQCKoqpqdzcmNJAkWv0ARIMqEJkRSlcJA5Syo8m1UoQtKioBLGSAz7GzcZ7G8QhZLazCoHvRH9foHIC3J9gMkP/KJbblRWG3AGXViuBAonJM3lFTIliZ1DFhkqkGhnSJTESNATxkXFyOYMHQhtyHNDHAqSpEFgPC22swJjJYHyrIyiTEYjtSFW0EDgtGW3O+LqG69z7LH38Tu/+yJaLfL+D/0Av/pz/x9WayHt7Q2qx/vcuL3D0888zPraSepRFWMt0glyoQFLFUFhJfvGEjnjKU4ndAvffeWZD36QuVaNnZ19jDHjbZrxhq2kKIOHxwlpy+IgqisqMxFRoihMxKCtEQLyMp3SmCTi0Fd+cqnXppZganffMep7xj0nBL22IwwN1arg0YcEeWbp9g2DvqTXN+QDyLoQ1QQIR1E4Cu1dCCMDH49ifnq5wa2wzU2dobUizxxZ4IgqXiGktUAqSxhYBgO4eePQbQ/hIHP8/TTjV28OuRgFeDKvcYCz4AcrNX5qZZn/Lj/gy6MOYeAtudUKVCLF488+yEePHyeQAb/6a7+LEgWqliCLgmfqAZ2O4Xre5sZWxmA4YmdztzQIjbfuQ8FnWuaxznHia6/y+P4B1aVlIrlKmnb5iw8+RVKrom3Kwxcv8MoDD2KjsOzJb6F8s334rlw991Dv/kGWKfn3LoA4fQ5QBofw2psXWU8aXFQhI5vfZZSaRmVBGFOfW2U4GjEcHCDylEjn1EZDdL+HEQJjPbi3DpCSqBITRwrCgCiJqdfqEHh3+0goooMBxc1NTJFTbO9SqhLexUb6gytuIkoKhFQYM85n58exHPswIUqCD4E05Zy705hxx7ASCIZtwa2vS0ZdB1YgnWTrkqUYSIQULN5nqc358609RMd5Kti+7mO6wVsY8hGAwhWKncuACyhGigntQWnNcMa7/RWpohiFIET5Xoa8L0m7kmHXs7LJQHDf2Tp5rrh+rVsabhybb0TsXwKjQ0Qh0KngYLONy/LJe27cLHMuCeXd7Z3E88m4SVyPRWCcRReOMIKwZDAPleTP/eRp7jtd5fqNA6JYcDASzM8l/OTHV/nsa/u88tYB6dB4god79Nz4j3NeGWo0ZVsInMsZpZruwKC1IAjHe+y9+2ry27cxrL+t1eQIAP8Ger/pRxoH5d7zOe+t1BlDWAQ44yZj5N6aHabm9Xjg+Utq1SrNRoPZ2YLLeReryz3SiZJS3x0535WPK5RCqNhboSwkcUSoArxFsdyfJ3vHu1O+5wFVtVqlt7uDTjVIiYwlSRTROnWcZjPk+q1thA145onHCRdn2d/vcGtzlyAI2Fq/jc58DBKRROsCZxwuxNP/aoeKFLowIELAUIxyLyALgQokLgyQQqECibEFtVpIrVahMIZ2d4DKcwInMP0RxSgkjCNEbsmNIXQGkYF2miQUnDt7H3/pT/9JLt58lV/93BeoDxWjoYPcIozPIRVJkIFCCUGtGrK6WOV9j85w8/WvoG/eZq3VIG04pDUURrGy0OLU7AwPHFvhJ//8/4bd7jr9a1f52E/+NTq3vkZOyA89+UFax0/z6hc/y+XNNidOnkNGVYzw8WRBtUqv9yIPPvkcs60W6aBD+vprnFiYwySWF7Y22N9sY0WFQCikCKlEIQoYYpBKUWnOsd++QXPlOB/6xI/wqz//T70VxRnue/RpwtDRvn2TxvwcjfubqDAmAJywSGMRVmKcQWpDXhRI5V3bAut8EKpWaAUqDCb5HEIZU5USKyxWCzLr2CxygqIgChU212TO+6FnaFphQug0Q61xwlsnU+2IpCPXBSefeT/OKVozczz7kz9Nvr9Df9BlcP0KiUxxhaGmWgjXYKAzXKEJtGaYjtBZCoFAKoEprU6JCqhKha4IAgRaCwoBeVEQS4kWFiIIckVne52djasomxNKaK9fJR3sIqQhCBXSgi0FvjAIQAQ4VVL4GkteaPZ6fd545WXe88f+DFc3ugxaCdV6nf29DSpzMXMyZOf2ZRaPrfHC5z/Lcz/wwwTNFgSSkQSnIZCKHD8QayZClVrqgdHfqSXg91zuO3OGmQj+8c/8IieXjlF3mh+dm+NzO3t0E8ePPXcftw80v/mV82zt95k4NQhIWhELZ2aQUrDfgYO2PXQ5uMcmd1imNiJv2J7ERFnr6PcFYWApMsn6hg+K1tZiRIFGYBA+5cNUrHelBkkFsn3Dz1+4gbu5y5WZkANMCUYcWSboCOnvJxznBPz51Qq/LXI+d2DBHgrnwjj+ykyLc7WEv9ntMMSWArwACdoYltZm+eHlFstbIUpIAnxy34pIaFRiFmoCnCRWgthJAgyjQco/f3WPi4MUZxwvv3EZbTIQh8lrffu9A2AR8CsSfmZvn1VgpHMyY6n3+tQDxYcbVb7ebDL/wEMEU10h7qjjSB/d/eXe5c5T3F01f4vlG0lc30gk+uaPdOdtnIUizzHG0NnfodfuY4ocUxSTRM7TTzUuVkhyFNaV+WeEINQZwc1LXP9nGyRRgtEGa33eGIXzii0HFH0eaRhqtRinJM7FnFtoUbl8nuJ2iM4MNs2gmhy+xXd7LNVU40kxBa4AISVOKrLCkfZH0O9h0wKR5mAplTX3rtQrMBwHG4qDDXXkyNZ5yeZbDqTg6ZagMuMBm7UeOAkrEAbyfvl4bmyhkggLTofsvB1w91jzTHx5TxLivSbAuxwOdyR6SGlZFGRdP0/rlZC/+FMPsN1O+Lv/zZcnQNHkilF+WLPOHTfevMVwOJVbrWwvIRzd7pBLFzcZDPVk7Sx1hOS6wFnHX//phwiVXy/futzh5FpMo6Go1UK0KZCyQFtJJAXVakQUB6Du8Zp39J11jls3u7TbGY1GFWcNxhS8+uYeC7M15o/FJEyvJ9/MzPQHNKa/wWO88xMcJWO/dz3u6KGSvKTQBmvvTHvwzR7Kn9tsVphtNditDOkP3GS9F1OnHY1lLeWauEK1tYAQfn6txDNMcjIGEodPcSTeRWeZ73lANer3vI7LgQoUlTBh7fiDPPDYabr722hXY751jL3BkM3bb1GLKlRlyHA0QBc5AosUEpsbnHFYDAIFhU9aZmWJ5GVRsvKBCAMCZ0p3MR8rFTcSsHDqxBpPPXA/mBGfef4FtgeZZwt0DhlIbBChQk9Pnhcp1hmQCoNic2ubX//VT3PmTIIZGQIXolyKxSFUgaDwgr60JKFiaSbhw0+e5M/+8B/h2OoHkYHljed/nkvnn+fizQPyWoMPPPooZ9fuZ/Wpj/Lm+Tf43Re+wP6tPR579SIf/vAnCKoB+7s7PP+VF3n9xg6v3dgmrlgas5mngzcSk/bp9zqkO1v0ioxRf59KvcZLr79Gno4Y5CkH3QPCaoABlFJYLMpalPV+90rEDLIRbmebrWvrPP7Ue6mIgPmFVU4//Dif+9WfZ362xeyJRzj9+EdwEs+iZ33AbG4sttDkRmOwkAtCJdFWo4HIOWxh0BYiqTw9vDFkErTROGdRQtAvHCGWg8EIEQRE+IDHdDRCWMiKgnoSESnJUAUoHNZJFLC4fBzpfMxao7GIEZJc5jytrQ/8zQ1OeSBmnKY36CJMjs4LRnmKQuJMwe7OTW5dfhOHJFAK7QyF8hY06SQidGh7KLym0jLodugebKPSFD3qMBx2GWrP9Ciw5GhCJzEIKk7ibMnQiGMUQKANaaF588IVBr09Rij29/fY73qGykEfOt0RLX2BJz/2R+m80GN/8xYPP/5xRi4gEYoCi/Bi0yTmYiQNAZLKd1JT/3ssQSgZZiNeeuMVv6iHAa1alaTbw9Yda8tNRFUTHLF2eE2d1o6Ddl7u+O+wrx3Jmukm/+7v+vxzzVnBTEvQbAiKAkap48b1AmtASEF/6Nn2un0PtsKkDOavCmZnIPaKY+9CKB2Jlfz4QotnVpf51M6WF9amAs5l4FhaEMQBPHjT8mfaOWEv5wtOYMXYRc6zbT3bqvLoTJVK9wCkZ88ab1r95YSt00t832qDDzz+AGGQIIzkrdcvkO0c4DLQuUHaApvnSCV4/q19fvuNTf75hS4fefo4djSk1xtibME4F1MQjhNdjQWSaS2oQwjJI889RxHXWLm5ztvdDnmuOdacZUYofvLU/ewlkrwMDJmuadJ/99TKfpPyjqfceWBadX0XAvvm97nn+e8wv75RdeWxnd09/s2//k3yomA46OMjT0qaZqm8d4Xz8ZxiyloipSJKKhRpSanuBFcGml/e1kR7XRLZZ5SlVBuKwPjN8cbOHijLjz1+mufOLvCV7hCERAUR33/6GMfOLaBCAVawsdeDdnH3A3/XlpK9sxQGjfVWeyc8oBoW8NKFHW48/3Xue/53GaJYNQrhQLuSQl/ca8yUlUzdp/zxUOR0ePKaUkFvrd87hJMMd0MufFaVgqqY1FfkbmKREtPzbOr2ZqTQocaZw2fo3Y6nnslbyCUgy9yfE9L48fvcoXRwVvrUC/LogilKzZCQFiUc8zMJQnh3QiV9/rS1Y5JaEnPyWI1mPcA5R+cg9Sx8CKSSRDLgwTMJsiT7KDKDzQx72wek6QqVSnSkKcfWptEwZ2urS6c9YGdzRKNZQfm8M1jjmXh73SHpKGNmtkacRCUkEdPVTY2BO0fHuNnEXb+V3Tm1O3wzMCbu/niHbucugp3J/ScHJ4eOJF4GpkmZxkPSCUGaZfzyp55nd6/jc66NFTITU7mbut091iznrad5YSkK47U9THkiTJ04gVmOCfFQpI62r/cUcz4/q3WHyPtdKt/zgCqsJwSDAJ0WKBUytzTLweYNdiqGU2tL2LMroAX7nRTlcoaZYW9ziyJLqSSK+YUWhdZs7xx4il4FIglQscQOUp98UAicdiAUofQEAkb7WJ5QBDhrGPWGJGHIIyfex9/+L/4rZFDwl//Kn+S3Dl4jUwanPRBwke/soHRiFkYilaFZjZitCB5YqcJ+l4frFfIg4q3BgGYtQASOaKZGgEBpw2yrwifuv4+f+iP/MTvtff7Z3/yPOX3/k3zkYz/K4x/4Y5jhPjKJUPVZdtZv80v/w39Pa3WO+SXJi2/s07t6kd1Kwpsvv8LZY7N0TMZGt8eN9cvUqh0W0io2Nwx0TppbMIbhwT5PP/EERXiKSzev0715m4N+F0VpHQmhO+jR0Ia8BAQgsU6jrcOanP2bt3nl5S/wsY/9KLVWlYX7Huazn/llet02s/ML9LbWSYcDwqSJECXFqbHkuqAwOZEKkFKhjcSW9xEacqUw1qCsINeGHEekFNoWCOmwQhIJgXagdUEt9jlTIiHAOuK4SqQUvTwnswZtNYXJSZ23bBVWI4ygkA5lDIW2VCoh0oYYCTawyBAqIvS09lZTmZn3rJPG54IKZIC1BQv7Z6jPrpFUErRwxAQ4JwnicluzjsB5cpJEGmyYcHs0YLBzg0G/j81STDZC595HXzqBUiHGaQLjhWchlV+rrMZayFFkUrHZG3Dr5hWS5jzz1Sa9kcUJb/1Lc4Pq7OGwzK6d5fKFSzz2EyEmdeTOkVtNUfrya2vQtvDugEqSunePqvTdLkL4NARb+220NmxKwc8Lw7WDIQ/NzoMMvKspnlRCVRUq9Mk2VRJMNsFD4WRSc3mEI5vd+HiRC6wJSEeWQDrywrK+YchSQZaW1zjDXq5RUrIsFNVKxM22ZqgNTkDWE568QozJ2AWVFM65gAfDgMQwtTf7OxsNm5t+51wYCf5Jf8S/FQ6q4aFAgEMoxQvNGvWnH+aHY8iVJJAlo561nKtXaJyapTXTYnmujkszeu0+LvP57pJazNevHvDvXrrBF758k7/xoeN85sIB//DVLpnRdHojEiU489gjXH7ta5O9WJbBqUf3xaPtG6oAFUZ8am9A7gKqSPZHipNzi/zvNtex545z6kgvHHbC3Tal329B/t8fYOCAKIw4c+4UeZFz4fxlsiJDypCg2kBIhcCRHuxg9XSqgDJFqC3JVMrOaRvLFS2InM+5dDoKUQhwgqHR/D++/BJpZvjZ/+CjRJGikoS4wpAEIU88dw7xxKp3wxQC9/Il3H5xKLB9h9ro968cOgv7XI92sjZYZ9nY7NDuFfT2B5zLU6+gFbVS0WYBeaSub+V+paQLwvkYV13eTztcaZIxuWTYVketCdNy7z1r9W+SDj0QM/pQ5HVTJ05baaxxtHe79PuGo7m4ptdBf32ubYmz3FjCn8SYBVJQrwT8p3/1aSqxB2+yjKeJY8mVa9sTjCYQKOVdnrUWk5xNJ1artDtDrtzKuXGjz95Oj6CSkaWFB1RT49wYSxgFtPeG/NovXcQYKPIyTh48sZk2GG1446VrjAZDPvjJx1lIPDAb5+S+w85y97uPP7lDmf8Qa5YKOXcI0O5O0evK/+5YG6ex0fTiNgFKd5SpveDeF951MghBr5eiVMH/8A9+k2o1RJdWqsNnE/euY3w/4V3yajXFwnzC66m+4/x7uP86hwwUC/NLJLUahIf7rSstWc45wkD5dQpXxiO+O+V7HlBF1lGvJRSjlLNnVjmzOsOrX79Ery2pnIn5+PIMqlblrUsjOFanP+zwet9yEEb0MktSbXGwueGBkgpwkcTlBcZBEEQ4WTLwaE8DapAcW27h3Iit9T5hIpFCECeKqoro727w67/0r7FBzttXruOMoRoICq0wwiHTrNykAGtJEsdas879q8f4Ez/xhzm3uMbao09y680v8hu/8UvMjEbso0kqs6ysnaZ99QIPHFvhuY9+goff8xG+9NlP868+9Yu005yrldf58j+9yvsfeoCFapPFlVkK16PSXGBHD4jFOQJpuHZtn2Z1gYtvf51TT7yHimgz7HdoaI0bphQqpxrMkYeSmfkVFk4/xEtf/G1qcZXuwS6vfu2r7N2+gTIWSQF4DX8x7FF0OmRLOYW1uNC7JiEsFJb9jWsUW9eZm2lx48KrPP7e93P76lsEesTS8gr1aoXa3BkqszNkwhE7gRUSI3PiMCQJIoRzjJwBaZCBouIibGzBCKSseM1bpjEUCOswZeJlL6MJEulQUYWKVATKc5KNckuBoxlG1B1I58itQUpJbDRCBoQyIFWCJJRegx/A0BQEBvI8Q0UhQoaYwC8RNaGwQYBVClXSoVecBCcp6k2WF09RqyTUlG9BVTLdpMoSCEUiQEmDRVFxBQFDHAad9xhlKSL3udJya3DGYKwjQHiOUeldIaWwuCjECEmmcw5SmLGaW9ev8+CD9/OVGzsk1YSo0iR3QwoLzjoG+9usnnuM9s3X6OwdsDy3jAAOrCNPcwILsYwoAoNSIXlhUebd0wq92yUd5Vy6tIkrg/SdE3xicY4bKy3WixQ36iOE8puOEMQLFcJaVG7e7q495JsZMqaPZxlsbkOr5YWKXhfyTHjuFe0Y3mxDYXkyqvDXl5b46E88zF99+RKf3eviwLsQAWN3uQDIneRXzJDXb93kptYQjPV9h2xYpnTt26lG3G7U6R50veVirOJGEALXFeTLC3ysOM4wHZFqLyxmaY7TDlEYbDbApg5jDHFsUUqQ47BS8crNLj/3lS3S7YztTkZG5LdNo7l8YZ21RkS3ZydgygH7+wdsbO6wvDSPUnLKUHWoC86N4crNTfL6HCDJbEEe1RgahVhd5UxrBq0LwjA8RLR3qoP/gMu97njXrLnzpG9zWgnGcrZnK3vmPU8gBKxv7SJ6A9J+j2LQRUZeKHTWTkHWcSUCawrS/i7WaP9wzrJqDSeVQAuoixBlHCmaJxZn+CuPHOfl67dI0hQLPFtJ0M9/ndnC8PAjSxxYS5HlLCzUceN74+4SHb8rSyk4OgRZprFGlEKto98f8Uv/5PNIFbBYaB5oFpi1JldGiitXB2zm4xgiuLvTp9vmHYReBxe/ILn2kge3zkLWlZPz3T2E6Ok8RUlV8cB7l9i7OeL2xa5f15xgsF9hWN73CFX4PZ7FaMfuVoe9TndKuD60kCjpQDiUdBijWVup8kMfmsdqDxJ294cszCQcX41Zmm8y06hQiYMpS4sryXcCtBaHxhDlY7+kA5zAOIFDcTAc8vIbbXINRQoisJx/bZ04jg6NOk4wygpwsHKsSa1RYzAoqDYD5hcbxHFMEIXMLzVZXmqxsNwiG424cXGD29c63u1xEk91xygulQRjEpCisAwH2fhVjpwXBJLltQZKyZLKfAyeHNPJ2g/5cdwETODGlhp/wuT38W3Gx5iuxx2uufbwmmmGvMl3J7DGcePWLqEK2N/psee8RSjPzTsuUYcGKzEZD05ArSY5vlbz7+knyMRq58fkIbjzTyMxQjLKNS7X47Mmz2edN3a+8spFtrc7/5OF6vdSVJaTDQZoY3jr4hUuvC2JY8XJYsR/8N5zPPbYMqa9y/ONJfau7nDyqXPsPTDDp17apNN8Lycff5hP/ct/gNrvUI0rbB1sYQvPziWkwOqCAEkQRdhQ40TAXrtHaDX3Hz/Bsx96jJ3dHc6trvD1V14mGNxk/eJXuP72eZpaslyt0u6OkNohhEFqgVHQaFQICHl4qcWPfPBZPvHJH+LClUv8nZ/9B7z//vt537Of5C//9b9LPrhJe/8m6ICwOksS1wgrTd6++Db/6Gf+Wz538SKoGkokVBrHWVxeYDcKuXjrPCvZCrP1ClXdYjfNufjCm6yeqLKz36PXdzzw6FmUtBhdJ8FTDi+vrhFHDR54/ydZO3M/aS7Y2rxJKCXpqMvvvvBZ0DlCWAqnEVKgLez3urSiCiOTYTCoQCG1xSmBdQpjc/Zvnef0Yp1P/uQfwYSSwUBzZvUxPvnhp9jqjPjK119HywhnLaGUWGGIhETJBG1NyTwGiQuIbU5eWIwGaxQSi9GGUEgS5citAqmoRxJtLUJKEgTapYAgc1CgUU4Qh5IE0CZDSMiEIhIB2hgMCcZZAiSR8xrH3OKjUpz1lNahZ9nDeXBllUAjUNYQSs+6ph0MhSO2lmYUoCsJs3FIM4SBFoywIA3Ket/1Ap/c0FpvIUuzHCWgqirkdkCR53T7XYosxYmSrlqCUCHaGZQQICRxtYooNHlWoNKcflgl15ZTj57jy197ifnTD/DAffezc/ttT+GPY+fyeR756B/GDFZp77SpN1pUXUGQQqg8c2VucrTOEVqhpGN0Z96m76Jy5ep1fuuXfwE7SesiqESSOQObBDSkYb4ZE85XqAaOMAnKjdRfP17+3ynk52g5FDJ6fctglGOMoNue2jCnNkmTW0SuOakFze0hyU4XN8zKhJxMmLtwjhUDf84lLB5b5MN/aJV6tcJnf+EF9vqjI1YzAWVwtuAHFhr8zcfu5796+Tx5qomEVzQoJViUgkerVbI0Zemh0yyemMcYwBTsX7vOK1+86NNIqACVRIzSgvV2nwv7BXvbmvnzm1Qbc6hIkUnJb17vs6lCn35AKv7I6Rnes9LgP/rVV6faRvCFz3+Fl19+gz//5/44jUb9HURIS/dgk7mF+4krDZqtCtqENJXkpxZHrOg93hiFtIPgUHZxpcgjDvvsWy3fDs75hjPiUM78JpWIb3DOOz/VtBVhOBrxC7/wa0BI0GhRaUVkwz42H2Hy4eRsMb4fIFWIlAFFOiDtbOKMmdSbGzNh5ksLQV1YKlLSUIJjcUQzChFaIxFUsbjb29SlpOo0b37+NQbG8MkffARb+MCa6SSy393Fv8AoT/nqi+dZWIipNmIG3RRnHQf7A5wThPWY/L0fYPkTj3Dl0ib/8u/8DtrJKcvQnXp6cectjh7zyn+Ge8HYWMVYiBX3uuQeg78yE/ChP3Ufr/36DrcudkuZ1p84cb4aWzvuAn3j30W5btnDo+XNpXR89P0Jj5xbQEjBbDNhphnz3FNLxEmMlPClF6/w2EMnWFme9zno5NjaZ+j1U5qNGJy3ZGV54WPEhERJxdXNAbu9goOB5sb1jM99dcAoy9jcHOCEYNjXDAeGr+7d9OQg43UQ6em/geEj1qe8kZJ6q8LsXJ0ojomimIXFGZaOzWCMY3drj1e+fJ08M0ewkaCkRxWHAGLSOhNK93LxmbTl4eB//SU7yZF1J7A5BGuH68HhKVPgaepaN/V0Y/6J8XiY2ILKZzkKBL1izdlD0OocGOfItSYvzMTyNcHp97CEOSAIBK25ClIIBoOMYd/S7uRcuLTHcGAmY56p/52bqgBv+TxoD45srq5kpfTkLh5YbW5sY92QueXKXc/y+1W+5wHVD3/ofn758z16vQxlHM16xJ/+Qx/kz/xHf54H1irEs6fp3/wqoxevEiQRRXONajrgidMn2Bh2OXj7Vd57ZoE39YitYVYyZ/rAcmdDAqXAOawEpwKklCSxoC5DhumQ61vbPHXySf7Cn/8J3vjcr/PU05/k5s4uT597kv/F6VP8m1/513zui59nuz/AOIu1UAsVy4st/n/c/XmUZflV34l+fsMZ7hhzRGZEzpmVNauqpJKERgSSkCxhS3iUoW3AjfHDC7yw3fbCr8HDatMs+7lpA2+Zabnb2AbbuHkGjLGMEBjNQ42qqqyqnDMjI2O+cecz/Yb3x7k34kZWlpBAMhK/tSLixr3nnvF39tnfvb/7u9/4mgd43ze9j/kz9/Bv/+3P898+/Xu0Oobn11t85PmrHJuq8Pgj5zhz5CQzpx9lbafLEx/9j6xvb7JdrdLLoNo4xjDpsd7dIL+6TS8B7UAVA3aGPRZmNd3rq1y72uPsqRWefv4SSNjt9Ch0nQKHDCpUm0c4c7qBj+cZdnskA8dnPvZRdlqbDAcdZJbjwwCHph5IAqFIXY4UGoQjzyw1obB5QqVWITcGWQkR3uFMQSwDVu57jMHNp/nshRfZ8zUiJQkqdeIwQAYhSiqsz7G6bHYrZClbigGPJfVl1ghrwDBK9Y8UAPMc7wxCRUghShqFsgydR+EInadnHFmaUg0DAmExuSf20JMgnUQLGJiEYZpBVCGQGqkV/TwjKgwirGCFRBuLpezv5HILypD7HIIYJRWFM7g8xxiD0xGhkhQ2p5CCqtRY53Decq01oFqJqMi4bAotx0Xdpcy+8hBJS2Ysw26HrY1NfJHTTTKytE/hDcY7hBs9hr3CKoswFl+pEIXQyQpMYRAy4s992wd419teT3PuKLe6jvu/4Ztx1SZvfq9n+/rThM0Z5uZmKWxAfPI+Vu5/iH43o99t4asVKBS21yGrl9x05UEqicsN+uu4oNxYS5bbyWcVU1ryzmNT/M0XO9wchLzvoSn+xac1AeFBIBkmXr26o+4P/zp433qsLR8pB7zwg4hyUYxqMBCjk+3x0mNG1IaJwC0e2MkM9Iec62yR1HNm33qcMelIjhYWQox64QmElAyEZC93vOH8Mb7h6FwpTSugtdmh3R2CUGjrmAsVzWppC4XTJMrjrEU4i8DipeTnfm+Vn//8Lt1C85bAEV+6ya9uttgbGhCaxxfqpDPTtEXE84MBrUJwsl5nfnaaW/0twBNGISBGGZHJkymYfNIqIYjDmK1rl6g15zi7dIaddp9rtxNkc4Yi1uzZuzetHF+k3w9UfcVmtH/lvwcR8tGuTXi+k4uLV3z/7nt12KU6fFSVKGR+ZgYRViiKgtVrN3G2eOW69jOBglpjGrB0N67gJ2g9Hs8147jhCiIl0N7xkJbMe0lBSZ/KvcTZsdsmsEKgRIh0BiHy0lYNE2yejrbn7+qQfT0OIQTGGMzQUQvlSJxiooYRh2jGHPtTb2NxfopuV5UBMT85L8aZZDic5XkVFD6eN6NFXwmzR6Bo32CUk1+Ise0ZveXL/RATKxSiJD2UU6D87iTYGu+AgFHDcUE1FtxzpjFqCuzwDnTgue9MkwfumSv7ZymFEh6t9ai/kKQ5VSOMQrSeECb3Hms9W9sDGvVRZklCZ5AxX2i0loSR5NmLbfqJJFSCIi2Fn6ZmKzy4PFO2HtnvmeT3b6rSNsgR0IG4GvDyxW3SVKA0rK3uMd0ISZOUtdUdhAdrLNtbezzw2DHqjXhfROggU7S/2xP2fOJpMQKj46TWeJ/8eG7Isaqh2F+2jLH5Q+vbxzATF90dbPQA9I5qjMpap0mQxmHb6O+I3fhyzjjK9h6FsVy5uMXqjc6he/UwIDo8LwQgJESxQEqJtQGmMCXjy3mcOQBm5WU5UNcdl0Md7OvEvo9O9D4wHGfSRid0skbtKz3+2AOqo4tVTG6phAF/6d0P8vC5Bb75ze/m7Otej9h7HmwfFWb0Mssjp85y9PVv59MfvlD25bEtLr54Eyc0aZaRpn2Ud4gowuKxuSHUAcvHT1CJY1ARswszJK01quyydstzavoIr33wPAvzJ7j3vrfwqd/97/zSb/0GRZLz1ofeyDd/49v4lrd9M0EjJO3u0hu0mZk5zcLSHEma89lPfpzP/Id/xWcvbTJ//FHIrhKqgEJHfPbyda72doiDZ1g53UKGkudfeBEPxMvTBEFMoAxV57BpRmt9m94g48jKMlEu0DgyPyRNM3q9Aa1uj6yAU8ePcd8jj3H83CPoSp0iMXS3d7l2+WUuvvQCkYy43h4gAo8QIcmwwHTbVGs1AlugaxoTgPVlw2TpPZKAzHvssEOsQ6TWKK9wEmRQCnbEjQVa/QRRAVFt4gnABaT9FMUA4wxWeKZEQOpA2YLMeIwqKUZ5UexHl5IspxLqkeVyhEhUWCvFMHAorciNh8JSyLJnWBBoVFAlRmOLgsBlFLpUJdQKnC+IfYSuBlgPuRDkSUbgPV6UdXPZcEgcgNBRKUuvA5yKyfIhgTU4YTGFwaCIowjnDJEOEMLgvCL3HmNypA7pDAYkSUK9EiN9SVkwwuKlJx1oNIJqLBFa0O+16fa7aGdRRVoqTdoyWldmK8p+adaV9UzSlb2QAqnw1hCrkEs7Cdsfu0SjvkNYbRIJidAtXGWamfPvRCHIFHgp6HdTfKFIrGXWhSSuIHM5ucnZ3d7GOU/Rb6OUgnAGk2Z/tIbgDzFKHvgoCjiK8EpZPuydD+kmkjx32FFfI5hwbe6SmTt45wAE7MecD774Ss9n7PAIgSkc1pYOqQScBCPKuW7cAUVu/6u+lNofZp5CZRiTEoQV/tSZY3xgcYF0mNK+tYFUGi1AK4jCgI1c4t75KCc2brFyYn5f3fTiUwUiLdg1YL1DNENwFucFeWZZ78MLPbinv0cxXaHXy7naLVh3EoSm56DtND7LiYRgEGiEhLmKJq4G+FDxTDvjiqySDrqjh6Fi9sgizbmSBhRF0YSX6Q+dJ4GgWp8h6/Qxw5yPfuw5QNBcXOaXTZN67pirK6bvPL938UXvCoC/yPiDPq79Ha8ne+L4Oz8cvRg7B6/MNIjDC98Buvw4OuCh0Zjig9/2PrZ2Ozzx1AsIUTZFnXS4mGx74Edy6NmAIkv20d64Z15WenhkDrSHl1JHbB1X257PpCldU2e1HeJH0WYjJNed5PbnHUVRxzjB8x/eIxvX0fDKapGv55EMcu657wiD7gBnD4QpxplnayyDQUbSLEjSnH3C4x0T6+Cs7CPdV9ni5ByZOI/7tkmw8HBEbSHEDBzrTw6wE1ogQvhStVOWsuT795vwPPKhZe57YJHf+D+eY9B2IMo+dVqW39OyZPIgoV6DOFScPFLjOz74GIHW+5QsAK3GPa8oPe2REzyWRf+G195bNnOdOKaR2j+FGQW5kVgHL10dsrbtqcQRzmqmZ6qIOGV2ISJQgkHPMj1X5577jpbCEqPaKjkpWrB/65TXZTjMEL99laRnUBp2N/us1gOSJOH2rV0Cqcizgt3dFo+8/ghzC83x3XuI9veK6zDe1F3iF/tXzYNNu2Ud48TOeQQqqqHCO7Muk6DmLtuaXOoV0+bgGXb3WM0IoLkRg8I4kqTgyuVtqtWobOnyitWVNEVjHFl60HDZFIKN1RSE4LFHF5merdGo1dlYz2lMxdx77/z+nDh/epqlhZh6VbIwI/cfkSqooSvN/W3sZ9fE+BjEyJR5rq2t0uuldx7wV2z8sQdUH/rz7+Ppp55hSc/xvR94A2fvmUEtLkO2h8s6CAcmGSBFSD+Hyxcu0d6xDIaO6bDO3/qf/grtbJdf+fBvMNdvsLa+RW5Bao2oQDbIGW7vMX/qDI2jR5mdnaWjCloXd3jzA4/yfd/+lzhxzwNstzv8+9/+MOvrfbacJDGKZ7ptfu9nf4qHTtzPt33gA8S5osIREqX5T7/2m6x3Uz717Ge5tbrFg49/IyfuuYe97W2qM/OEsyFRt8f0yTegpSITnu5gQHB0ifaNm2xdusw99zxEPF3l5o2XafV7RNbTjCK0hmRgmG9IGvUaM0cXuf81r2Vh9giXb7zE1eeepYia3Li5xtr1K1xdvwlZQeoENs+oigyLxPQMRT6kGLQxImeQGqwG60EqVTp+ziJUaRSc9ajKFKmxOFcwsK40ZrlBBIJ+p8WLVy8zN7tAtZlSOEFzah7MgN2tdfIio370frq+QHlFXmQMspwwivEItJBkWU6gJForvJS4woK1OOuQ2oF19IsM0j5eeGKpGNiUoNkEk2KLnEHmCOsV6mHMMEkodI5SERSQ5Qk6DMs6E2EQolQZ9EIhhUYUKVlekGeGQAlSkxMHMVU0xnlMmiKsw4UxwkHgHP1uq8wkRRVcniKsxfkhIqiQW89u0qemNWmeM3AQ5BlhGCECTT0qJW2NUUhj6Kd9Aimw3pYRQQOIkh5Z9iYRUFgy0QercaIEB056sDlJOqBIc4JaihKSIk+xXmJ9qXaZ5TlB4AnjKjJXOA0bziKcoxIE5KWFI65GSDzWGJorTfKv376++5SK/QeiENxIUuLOkEjkXNvp8f881WWYlwoPB87wQZTP7z+5Jh3cww86VzjSVr+MFk40AJqsHyr7cICvxIgwQAiBQ/CSzfnlHD777CqXtgYU3pfZWyijcl5CbknQOFeWt4vAMhdpHnr4DL1Wl4EforSkXosI4ohO1/DbV1uIzKCtxGRlNNI5OHnPCvNLs/z2566VBdm5p9st+L8+cZ2PX+yyupswJ5u8a5iSXr7Nrcyxe6OPHMkj12cUqQz4e287zmdud/nZJ1N+Zcfxj85F3D/jeFIF3O50+PTVDfJ8gNSa17/xtdSbdaLaFDdvru8f32EqZQkWev0EdEA4VbZYOL1QoVGNqU6f5INTCUfTDp+y1dE3vrjDPnZVv5ou/SsANeOI8GGVsP1F/MF8GL+3H6mm3OEyqzF2bu50uicymEJirCPLsvLanr+PNCtKJdA8pd/ZIRt0DoHXMipcCjBVpqYYtneBsndSPo52j5YfGBDWU00dosgIgoDLbcO4ySxlS3aubVmUUCgEum+Yjiz10KCkQKuvYwMyGiVmsnzm957ncx+7gPeQ5wVCHMiDewFpnvHS2jq7/QFXr64fgCZ/tzn4yut65+d+fIMculEmllNw7188yrHXzdG90Wfn4mVMa0JEyIMTjkI4MmP33xTSM3W6zsL5OaRW+LIimrNnJMdXBI0o4tzibEnvl6C0JI4kYaiJAkUQ6v3M252jfE8yWdvJ6H64E/AIoD0Ycm0VmrWQ3W7OVnvIjZ2cWrWCEI50KBl2BOfOzzK/WMcaTxgFJdNlnPHh8HoPnWPhqVRCHnn8KB/76Crd3ZxWvUejITFFSp4NsPmQPEmZn4toNCr7sGTylI9f78MqP4ZNr7xuh/4rkzYl5RABQh0WrjgEM8cv7gKwfbmtg+XuCABOfu3OrPA+fbx8v93q8eTnrpEOLM5CvR5QqcoRQB4FY0RpJxhliYbDgk7LEESSwaAgz8qWNXjByxd3UapTZgu94Pz9U5w520ArSaAVjzywwvxMTDXSBHp8IktKp1CyzOSOqPZelv7nOCslhcQ7x2/850/x3IXVV56Xr9D4Yw+oip0Wp08vInoB0yunCObnYDiEhZBk9zoyOspge8CwiPm1J9fYKzY4GQX0hGK3PeTm73ycb3rTm/iOb/12Hv2G1/PSlae5cvE2l65e5MbNNZZPnKHZmGXlxBlq09PElSonT30rvVtXeeIzV+kwx3/91DPs9DrYqQeYrVua3R5VnfDGb/qT/Oav/Ws2RcSHP/d5vNecOX2alSlN1lxBF3vMrxynMxCcf83jeGnYbXeo1o8z1ZhlO9hgduEEXjmEgyUcgUzZufwyg702L730PFPNGrl3VKcazDZmWTl9hhOnHmRhcZ6Z6XmCUCC9oj/MWd/a4OXLF9nZ2aXrnufShS+goxqJEYjCM0iHCApkqLFuiHGOQX8Pkw7RKqDaqNPtduknKYH2gAShcNZT4ND1I+i4xvbadaphTOY8WlWwwqGVZ5C0kT7FCouOFGYwpFmtYwrPzaTFzPQ8tbCBzwyJLyiSpJRNdyPKhBIIa+n32ygdIWVAp91FBwIrBbPBHM6Bsr7MDvmRzGYGkZNIoTDSQ2RJBh3QEblxaB0RGE/XOrwKwRqUVzQddEcFmdYMkEKilEYEIcpAbjMKkzNsbyGDBgQBeEde5FjfI5iahTxns7tHtd4kDCEKagRakpohoQ6QSpKkA/rDAcJZ6kGVIiybGBdZD5srjHGo2aPU5lYQvRZZ0UMVDuUU1ttDzTnHNABrChCWEm95nFLIQNKoVFFRFeHACkclDOgNuhiT4XND4QyFDJBWoHVAIEOKPCU1DlfkhFEFKaEY7BEah9Gl4EctjP7ojMAfcpT9NMohvOBMKPlWD5dv7fCmKOC/rK3zkfW07G8hmWAold9S3hMJh0eSMuH0eg4e4pSOvc8FKrecCxWxLBtLX04yFrSmqspG12tFgQjDUlV4roofFlxMCi6ZFPeFDayf6EUjRlkMD4tSoOphGTFuOwYvdnndnkO8sE5rKqIX1hHe0R16VFbQG4xUlqyhNl1j8dRC+XC0Dt8b0NKCvnVgCjAekxo+d6XLZ9cS8J44dGwOHDuthE/d2ObpnoKwBlJzrlLlL85LktjwVKtFEUqeG3j+l7U+3awMUgyyhH/1ic9h87SkjgoIo5A4VNgiHZ/CEnT4SVDkefqZC1y+skrt/CMEYcyx4xXmGzF5HvKNUY/KZouP5JrqTH3f8fliBW5/EDB1yEn5fcfkPBi50BMA5uDD0jlp7XXZ6wxHzkq5jBtT0UcQ8SASPs5yjaK33o/qCkpnzOFLQJUWLCzOUhhDf1gwHPTot7fAWJQKD7JVHvIkw7sCjyfp9XGj/djdWKPT2tk/nhIslABLKkXpiAukPDjWA2d5gtQzqpGRlJSyd37T2zl6ZPHLvQRfY6M8tjwzIy947PB5hPLMna7jPHRbCZ+8do10vUfr4i5UNXI/6D+Kue97vuOrPIrcIA/mzL7NFweLjv9MBCCklDg5YmwoRThbijrgRg8OYSmc4TO/cYm91Zx4LsQLi1AOp6CbpNhxA2LhWZyf4vGH5qiGIaePzqNU2SdvfHspJVAj2t6rMjlHc/quuGAiXSt8Oa9vbA14+XbG7HQEUpIWjo3bXe59uMLRlRmEVDjnaUzHRJEegZLJINnhO3ASoO5DFSl49NEVnv38Du12l421LbY3tzDGcPnlm2zcWKfejHj/n3192dfq0HoYYWLPgc0/XA932F74iddlEC+sTQHNg333o/t7gpt3sLXJkzaJ6CbXOnG0d7F9B3NsPJcOLAoCGlN1Xv+mc6VoxeSTTIyu9QjATzZLHlujXi/ho791heEwxxnYuJ0yHIB3Bo8EB5/79BpSjvcPfiN6Ga0kQo5jaRNCKGLih/EdMRFcGl3fbFRq8dUaf+wBlQ2meOGG5898z19ls36K333RMrx9g4f39hDFeVZ3+kgzT2eqRm4HNCtVNvpb9FKDnJG4LOE3r17m/PKjvHX2NPdR5d77ppCRp3X7FifOn6UoDFFUxeQ5F69tMugl/M4nn2Ira7KwlVKpzBCIgN7Llzn3wMO0Oveys9Ziq9UniOeYW7mfT7/0BJs7OzzShW89+c1E8waVGWQcsXLiNGmWsNvaILE5t29eZmn2LJlxdDpbSA+xFlgsSadPbWaRoyenKUSFWnOW+fkmq5deQrmQo2dfz+zRY1SUYef2OjfXb7Czuc1ut099qkGn04FRh/ZWL8HtbGGUJqo3iapV8qzLzt4uPgyQPsB7Q+EzUIrOsA9CYK0gUjGBTEkoUB7i6jSnzr2WZmOaIIoxUUCRFyhviIOQFM8gzXEipDCGvUEfaTzdQQ9swuzsEsI5tK5CXmZc4rhKmhc4Z7CubO4LEq8rpMaQ+xRCjbEZhYW9zi6xjvBoukWGFgJjJNmgw97mGrpaR3tPIARIkLEizxK29nZROqZWq2KLlH6nhTWKxlSVJB9Sq88TiIB2v08vTdFxQFxplOfRC2RtsWy86j3pcIjSIRQ5g24PnGW4fpOi1qBWnaK6uEJYCbEyYphmDPc65C5FCUccxqhIIIhwhUGJsOTjJyn12izm9Gup9ndI2ltk9T6dbh+sRXi3b63HEUHvxk+QkdG34PKcfNBC5wn9vFR/E16QZykuN1gEoZC0OrsMe7vEYYyO4nIVOsBEMdKDTft4IzBBhiSm0+0SEr7aLfo1P4oiR3iHEorlUPDOQHB7fYdPDfp8HMdASpQqrbYX42Jmh/AW4TxLAv6Pk4s4qfiba9tsmoOH16Emvx4qznI0EPzcyWVO1ENeaKf87K1N3j81x5unZ9j2lu+58SI7WYIrslGNs+Q7zi7y2JEG//7SLk9sDPGiRHZjcQmP5fvrU/y5Wo12ntG6PCC9+RJWSfLPXeO+f/AdTL3/7WATXNHDdvt84bef5qUdD67Ai7LvXpJZvnCzQ3t3yNbmDp9ZS1hZ6PPA/WU2cphafFGKslzLJT/+lOVDZ0K+6dxRelsJmy0NQtCSEicUJ5ohJ5oxH78tyKSg5QVOKVwgcSZHSU9zbgqAKxdvcP3qLRpTDebnZkoqyMGZPHTN5hdn4UWP6e4i4irPXtiiWY1oTs/wv99oU8tzdlckp3lFbPcPPb4Y+LpLYnJ/SCGJqzHG2hK05NkhZ4mR82itLYNUxu3XZ3jvcaP6SrGPxPwECDqokympeX6/WNs6jzHj9YCSgmZVU69MMzfdwFlTOswT20lSC96QZynGFGXQ4SDlxSFnceTQyECXIqNKohQIOYZQYr9WXwpZAiklUUKipEQJT7US3/WcfX2N8lijSCNH/naaexa+ZYqFb5wlv5Yy89gs4VzAAw8eRwpHkeTYoqxxKTPXHiSHMivjTqWCg/sdyms8BlNi1ENMIhGibOngR1RNKSzVKU0YB3gvOf2me/D5KCo0zmgIX/aZk2VtshAOg+PSjR0uXutROVbD1zMGaz0W5qd56xsfRgsoRTjHoGQCJIhXwA0mFjn8cpyF9ZCmeTlvR3NZAHlhkSqgKKCdCKJQcvKeo8wsp8wvNGhM1QhCtQ8aDgD8/mU5/Bd4ZeqsPIb6VMh3/b8epbPXpt8tsyngqdVrxJGmWq9RqcWHVnhnXMSPAPGk6Z8EiZMAp3w9DpJM7ORkPdT4/9+3NuhOkPgqS+zHaMbbGtmS8fUb7XsYasLZxqF1jW3NxJHtm6LJ0WjG/MW//FqEgDQxPPPkOtaO7JUv673lWMNj9J3p2QpBcKeaZJmBtSbHFKOaSxQyiCYCSKNjHqkGplnKL/ybD/8+5+oPNv7YA6p8d5P5aI5o8Y3860sZ/ZefRYcxw/Wc9kZCoeeYqYGuD3jN6SMEKiEf3oNuTpMNegyHkni2CWnKp6+36VjIhuvUZuaQeobrl1oQRhSt2xSJI6tEtDY7HHn82zlSF2zstJjSS3hZYe7eNxMvLnJ/bQ73+ohs6gRve/O3o2TIwnsTrHVIqdioVmEuJ13Y5Z6lB6gLy8zcHINkj0de/00kwx5PfPxj3PfYm9i9dQnhJbXmDHOzM8zMn2Lx1GPMTE+jVIRDste6RS8tiKo1bm1c4eaNF0nSFBNWkIUh0AG6WiUbpGSdASoQ9JMOSXuPsFI6zNL0wApC7+hkA7q9IRVZoVKtotCESGZrs+wlAywZVdFA0EYCutqgsXwWE0fkwlELYxCSNEvIsiFZbgnjANHPyZKUsFKgOwMCLbl19TlSazgys0huIDMFnUGHalylyAyZNxSFQTqDVQGBNQgLUgS4IsF7WyofanBGMRwmZMUAhC2NoS+Lr6uNOkVOKcKhNRUVUlhHkiXEOgIckTGoIGJmeYXtzhBfZEiraLVb4FXZfyzPSY0h6adM15tYIO3v0Rn0EUpTiRX9fkFUnS7dXGuoLy6zsjhNr2fodLv00xTjSxpdmqZYDENTkGQW4wWBihj0+5h0CD7BygqDJCkV/IImsirobm7jvUIFISZPEaOmih47Uj7So9ogAaOGvyAwWuKxBPUIJUOEcdSmpwiUAuMIlGIqL/DeIU2BDmpsDjvE1hMHGqMcsVYIUeCkRArobW+T5H+UVuAPNz7/8U8ghOIH/uc/y6//lw/zOV+gTq7wA299hB8IFUJL5BhQefDOIfIcBgbhPCQp05euoiox//FbvhkTRPtNK0uTX/bx8c6DddDrc7Q/RFnDucLzIw+eBSkwWJYDxW+84wyFGMn/WguZYaY/IM5y3vrwFNmjESLUoMAoiTq7AllC59eep93P6EjPy0XOk0nO6TDgG8IAt3EDc23kGFuHK9zowenAZnQ2BogCNvZy/vbvbnB7t0vR20PnBa9b6vG5Z7Yht/R2s7IZrHXUw4A3nZrj3L1V3v66s5y80uLir19jo59zuZvzC7cVryn6DJzHiTKLbIXEmxwGQ4SQ3Pfgg/y///Zf4unnrtHa2yPUimpUZm7HKl+HR/nkllJyZGGedq+NG3RIdYA2FZx1XJpucHJhidmZ6Vc6VZOr+XIw1qTDIF750Zfi6oRRxH3330unl+CsZ/X6FexkMQuQF4Yb1zd5z3u/meWVGda2uly5ucGZE4vsbmzQ2tm9Y4cmovl3xOA9Jbjqdodcunq77OnHyDGTEuUdMtA4LQm8m3DpPPXG3Y9CynE2YgSqRkBpfrrBw/ecI44qWGOoB2FZq0XZWkAw8gelQMlSMSy1BX2TlQ1CvSdNk9/nLH5tj5VjDZAByydiZuYiAuV5cWOPt/6fb2C4bmm+I2Ll4VkUEjnK9pRnG8aZAcGoG5WXI8f8IC9bflZWVToc7tCkLCuxVEn2HRFBy+up8MgR2PJeUm967CEn/mAPxtsXeBKf0bu+wWDXc/Lt97N9cZ3+Wp/Csj8HDteQ+v3fB7kOMQE2DgME6w7uHO9K4PTy9RZp4fZFBsZJiSCMcMOcUAcICfVGzOLyFFJKpFSHM1ATWRooM4ZFYSeEI9zo3mA/yMA42KAURWEJQpieHfWZEoJqtYLAMxzm9Af5qBzOj+a/QElJFIcle2N/W4dRxuEMlTg4vvG5vAO6lKdp8u/Bd/bPzBhEilKZVSl5GDcKQRCoEpOPPnCuDJ6N4a8Z0TzHfZblPpifOI37m78bUh2/PADGUgpCWWasw2bE27/pFIcWFuOtH+y/GBmJA2pmeYzeC5JBm6S/XV4jHVGfWTqcdZtAisNkCP+Gr8r4Yw+onngpoxU/zheueRbcJR66V7IwNcW9ywXPBHCr1aN94ybnz54nZJcwH7JwfJkbGzcIfEBlfpZbl7/A0ZMnyRmgjKGyNEMQWCojw7S5dh2NIgtiOjeuUJ2pk/mUYqdFtTqN7e8Sypz52gydnU0aDcmmOEFfLmKcRBaSSlglEWWvIJVDmnna15/jtBiwcvo8YbHHckOS1Zf4zf/ySZ77wrO8423v4IG3vJe8P0SqkEotwmWOzGRs76zT2txlZ7fFcNBj0O/QKASNaIqwMUM1Luj1+7TaOySDHhUp6Qz7VCsVXG6oVuc4efYo+IwkHdId7tHudynShNRm5Mag4yozlRpOB+RFQZn0l2XDQiURgWI2mqIydYSoHrKwtEjRWyfJDd1un1sbN0mTBKckJt2jd+tFTFGQdXsEU5q+tfQ6bQhC2r023jnM1irXX3iCqDaFTTNUqHAqIAxjnLXkSYew1iwb34YhQhiGhcGZDGMcxo6MuDeE1Zh+t0tFg9NRafy8I0kNmbFUlETYHKE09UDTz4Y4UyClAmeJhCNLUlJXqtR46xgUKRUdYryg4zIK5xEGKiNKnfQhsfbIoiAvUkyWIb1g2B0wHBQMjcH5nLDSJNKaWEuGvYRaFELhcMMBg7yDFYZqrYLMczKfk2QdlK6gbEFSDAmjKkEQUhQZiPLxKSml4r0Daw1aSKxiX0UqH/aZnW5ijCCiQNU0Fo+2GdZITOaIZ6awgyHKW4ZFgc4F+d42zjni2XnMwJAWGUIJCufJ+gPUYkglav5RmoE/1Oi2d4nDCu1+gUkNP/Zd38qbHjlHHIz4fSNgVD7DRq6qpYzyjvjd7m2PgoCjI9rTmF8+/v6hMQrrC2Daw/Ihsvx4OxMEN+8RrnQy6jAO9ZdgzTqoR2Rru3QHzxDHcO8DTVY2Kvzci6t0EsPrpUYYgSwlqTBFwY225dev5Vxpwf/z7AbH45izccpO39IbZGS9Pi7JmI4DzswrPnXT8c4jMW9cmebG7ZTcayqh5E+crXAyirl5YYPNjiH3ElTAU4Ocp/s93lPTmNiVYjJe4l2ByQ33nDjNuTc9xo1bN/m/f+UT3Lq9Q2Ycc42Y1z+wQmMUBb5bcBng/ntOcvrEUa6ubjBIC6Iw4MzKPEeqFd6x2GAmDPhMe8ilYf6HT04dcozEnZ4R3BnsPrz0/mdZmvDUk0+X9EUxdqUP71wYaM6eO8rmxi12d7dIswJlLDev3EB4SxyFE9sab/juWx+/K6ckZ08dxbkD56zTHdBsVrHWcn11g6KYjGpPOioH+zj+XepEjp0gQaAUR6YaLMQ16pU6eVEwq2ImPeL96yglodYI57nVbdE1yURs/Ot7NGaraBXwzOfXscaBDDj/fUeImlWSiwOOvW66bCQ/Aj8H3bf8/nsjmMogS0E46lGVg1nkkQiMM2MVbtj/1JfiNdaT24J41ONLTqwTL2jlfSpBBSUOatbuhOQCSH3OXjpk53fXyF6oo+OMdG2XKJQ4bzDWIpScEJG4ExaO/zuYo/vvekEvLXhmtc0oaTGipkLuwSsJ4kBIQglBbSnmxAIlYJCCQCuUVryCyjZBP0OUc/3lC7e5cnEDZ8ZS234iKVM692PBikArdKQ4d36WublxnzRI0iHGGG5c71AYhRSCMFLUmxGhVoRhQByHmNzwiY9fYjjIRlnfg/N6cML9xJ8RKJNj8FA+zv0448y4FtLvx0LKe2+U3hnPodH+Ky1Hwl0gEdTqMW95xzmqtdGxeM9TT17mwgubeGepNyKqtZCNjT2EKLOrjXrE8socp04dQWtFpRqV6spMXse7GVWxfzyH35uYX+Lgbve+VCZMhynWmhG1cPz52M6Kkj1hCzxlCwwhJIem2cGJncSYX5Xxxx5Q/fvkdbhHF6jqDV634KgFinpFMD/d5FQ6oLt3k8ZsxNnlJpXakKn4OPWpaRbrGZYqNzo9zFKNo7PTGGWJlxoUKmRuqkZDBSRFiqTAGcWt9g62VjB3Yp4rF15CCcmxE9O88NTTHDuyTNSE9rVNpo7dx1O3GyS9gsI5Aq2wspyKQgoqCoLWCxwzqywvHuX4dE41H0A0zWevXMElfSIp0bFChRKTG3Y212l1tsgGGYW3FHlCWKkTxU2OzC6yupoQVGqk6ZB2e5tKtcHc3Aw+6eKzASIKWawvEsaazfVVhmmPQhe0t9aQWpInQ7pJH01JY6sFAZVYI4WgUmtgkyEmN9jcMDAOWaTM1SNOzU+Ti5BqPaR79VmG9Tprmcd4SeFBhSFFv0O6t07W38VaiykKisEAYQpcnpMmGTUdUw0DqvUKmgGuEAT1KpWgAVpAlpI4SxgEpK0NlBIEQQUhJTYdkvqcOKphjUXHMabISLp9CmOI4ipFEBIEAf3eLs24QT0Myc2A2ENuEopCIiz0em28NxghCaVnWDj2+gNEMSSuzeC8YkCOJGZAjheKIIrIsxwwyLCO9AIXh9Snpol9Tmt3g2o+TZKVSoXVelmLpo1DuozeYI8gjpieWybwijjS2DBC2AG5SzFpQkDK3q3LeOGZiSvIUJBNN0lEgSxAmhw7UlRSSKwvGxBLXxYcSzx7ey2CuErqLNO1JirtkxUFSE2eZWSDPr3eNL32gHwwoOeGKKHJB208sLF5g8wWmDzFe4sGlIpZrh4ld19FK/ZVHkoI3v2Gh/jtj/wubzm5wlseOksQKMZNB/dBjh/V8gmJlwIRl3QQPKho1EB2TL8cOU77T+47omni8Ivy9ViEYZ/qw4GDMIqElsUp4wxB+XAzScbuU6skqcFrz/W8YNWGnKpWGPZTsB7XHbK7PuRnL0ku7g64vjPg1rYgthX8pSHvOaGZmlXc6qUMi1Kq2CEppOSWqPLQmTlWFiqsr3fwYYh0js2s4Pv+6xX+59OLfEtgWdUxQyEZK8g5BENEmdFyHrvTorW1izCezGv6W5tElYjr/R0knjjSzE1ViEL1CrAx6dZPOv5CBmXBvBAMM4cPHA0teGov5VpaHAROxd1dgP2VT1yGP/SYEI44RL4RIPwkpeXgGvqJt6SUDJMhIklfGRUW4pBQxUFk9s5o+MFag0CxtDBNURiK3GKsYzjMGA5S8qJgn0R2l2M/2Hb5YS2OmJ+ZLjNVogw0aa2I4oi94YDUGKxx5MGB0pYXE46UKKPo3sN23qPAHaI/fT2Pl56/DV4zrjVSDcO933Oazk7CiUeaKOVxPj8IlDBS0BTjbJQvpbmdZ8+mzEY1rDdlxmoEbHMPN3rrLDcX0F7dAWYEW/0+YaQRZXhtdB+VdmjoDEPpiYQo7dQoc+j94butMI5WJ2dzNyG5YqnOHaH/5Cf4oW+tsjC9UPYh7FwilRGFC8mMZKcvmZoq62tjrQhUqQSoZJnxUghyY3Cu3HQ/d3SSYpQ1HUldi9I/khNgSggJoxotNQINQkzUbL1KYGL8rxCC+x9e4b4Hlw/dS/tWZDS398Hpfmxr8iqN90VwZOX4nfBof5RgIOa973+0DIJ9KZNmcqH9wMwrt3AATCeyVpORnMkM0higj2NzUtDe69NqJayt9rh5fYv5ZsDSfAMQWA8zJxfw3pc1TMDqpW2ee3Id7wXvfv/DLB1t3tGHzN/1PBy2Zr8fwAIhPEEUoL06ZAAO6rsOHyKe0Rx4tdP41fVD/tgDKm/3GGQBay+/gLs+5NjCHEeOGrJBB1sUnJiqIKagYofcd+pRVFhmKhaOniPPB9S31zkxP0/iI5QOERKq1RlOLi2gpcA6x8m5aVZ3d2lMBQxmqtjCcv/Zk2Asda140+sepBFFxFGF1509ws7AsfWZayQmAjxSlClXIzUqCnGR45HpFo+ePMK9x4+zvLJCEJwiKSwDMvZ25njp4jwPPHwWH3me/NRLFFYzFIra1ByVuMagtYNzntxkdDop9bBZ1hyFIXMVjVcRg+4euemzsDxLpTZLniR0tjfRQcjG7k2m8ybdfhtvyxoMhSJSIYV31OoNGpUaYRCRWoNPE1JdMF2r0dACl4acXJnmG+49weVWQlcqCtdFFhI5tYyXNXJbEIY16vNHMUfPsPripwk721hnSPME5UCLAKUKhkkH72tUi5zhzjaimlHJDX3TAmHQorwWeZEhi4xIKdKghg5ClLMoqSnyFFNkZEkHrSXCOepS4F1O2uvQHSYURYGq9DE6IPUJMi/VroSSOEo1rCiKmas38UphBglHmhWS1FFI8EWKFw6bbmJN2WBwiEE4cG6I1DG1+iwyC9nr7hFVqoTVGs35JrHXOAu9foep0LCwNAdC0OlXSZ2gUqtQFBlF2sW5iJlqxHy1iWeGzGUcnanT7/Xo9TsMRI7GwIjiF4Rl9gokxnu08KN+Qx6hFDJQZEmfre0tpBa4PEcUFiHBhRW0K7CuoEhSimJAnvYosj4i0AhbSun6IsVbj1IhSnriMMYbx7B9mzDt/hFbgj/4qAYBf/09j/PDN2/w0NQswVBC4UeRS49XDlT5IPbCMa6a9TiEd0wE3Q4SBpNO9ahmT9z5AMSVV+gAMR0SGCm/f7AehMT70gEd13LZvGDw4lUu/PqTdBNLMmV497TFDSW9oqBnDS1ryZ+4QXOYk6ZzfHrVkBdlzUUgBI+dO0Iy6PPcxU2M1ARK4eIaYn6a2vE5ekpxarrC0uw033b+CKv9TS72CqyDXQMX4hqPiJST/T5TPmZ7tG/ews1ehozA5zkuzZg6cZza3BRFd0i4u875Y0epVmJCrQgCTS0OCHSpbCm482QcjEGas7rVJiksXkiMg71eTpoJVgc7WG+ZbsYEwZgCcxe3625Rzrtkn1513HHNnXN4Z8tWAqOs8CsyPGJilfuI6OAai7EIhYCDUvAxMD/YqOeO777azo2HAGs9SZrjrKNerZSCNkOoVWNyoxkO70K523c4R4CqErMyPztBzxk7P55hkZLZUva5X4wPw+OUHUXWS3BdAohSLZbRaybvja/TMdEZB+8F8WxE1rDstHcIRYdep3QEnYACi8ktEoOuSJClKItDMthIqVYjvFbYJMd5i1cSKzWD7Yw4DLkZlfW5iFJcyDkwhUBmmrCi2Mkt4MvPEOAU6Zbn6NIMt/NNcCVpEKERTpN1UxrTdZRTdK95dq4PufKJm6hihkgJzt8D73q8QhRIwODdHs6BNYJPPN/mCxfafOg958idxliNKSR9pzBW0h54djow6KfU6/GI3ixHQjNjEmMZqJoMm0jEiIYmJgIRhwMUh8ar+NJKqbJemDuCE6/2pdF96yeMwZjad7dx0ENstO8TjYMPPP87jc0rMz2HTY+4c3Ems337z5k775uJzbV2emys9xgOM9a3enR6BVrBfWfqrCzWiEPF5Jf3A4jec3ypAt6xttFjY22bRiOkWo8oZWTuctZGpuiV+/7qAGdcq1X2HVN3fvoqJvgOA32Xy/lq1+krMb7igMpayz/8h/+Qf/tv/y0bGxssLy/zXd/1XfzwD//wQaTJe/7BP/gH/PzP/zztdpu3vOUt/PRP/zT33HPP/nparRY/8AM/wH/+z/8ZKSV/5s/8GX7iJ36Cer3+Ze3PyeOP8/rja1S6izSqNV77wHkWT5xDB3p/X4xJ2Nt8GZPukBRVavVpQBPFsyyvTJWcUu/JioytXofZeoNwFAlWSjBTbVAJK9xzxJNlKV+4+jKfXd1muhLTWr/NiZlZHrh3hVgrUud4am2L+lKT0ApcnhBqi3GgtWax7nj3fTEPLT9GKB0mS4jqcyhf0tVec+8b+PxaxKm3n+f6jS0GeZ/7H3s9e1s9bt1eIxvuIRWEtVLtJpACcCR2QG+4TSNcogBc0ibNBvSGXXbbWyh5E+McmcnxSUaRpXSSnMwZwiAgrNbwaUJzepagWiWuNOh1Www6e3STAXOVCt57Wr09jlUV73v9MvctT6F1jFKOF3uSrhUQBOSufAgEQmPzIQaFL3Lq03P0mk0CGaCCkEAIvFRULRSuQMVNTOCR1YCgprH5AGty4koVLSRxJSBKQdRCICQSox4XWiMDiSlyQuVJigKPIxSCWhhRGIsSgiDSiGpMoEHYnMUgptFoIlVpMNPcoqSgMJZ2r0fiLZnXBDhCqcmSDsZ6tA5Ba7R0RCrCKY0SMSJcIh81zPTeUo0kKhAo5bEmY9Dv0u8NEFpAkZF2WhRClVnLoAKFJZABInQYYSm6HfrCo0NN6i15keNcSlUWREFZn+ADhRIGZwVOawIJaiS5KgGHI5AhUqlSWl2Byxw90y+LQgNNkAkyazC2wBhLmueoUBDIBqEMKRjinSEMY5QQeCcIKCPbudJYHJ297a9bG2Kc5Wd/9ePc3uvxwPIiDDK8lvtO7diIm3RI3l5DSYHv+xLcODfyd8V+Ib4f0/VGzuKgcIRxSKUeIazHp6Z07wX4kcyZZ0RzUQKvFEU3gaIULxBSoGoB3nsGw5zpWkSRG4JaBFqxt9ahPZLB/qZvPUlzJeDqy9usF5bMei5kBTPPrHHqfIW3nSl4rqXZakNrkOOt4bnLO/zF+6Z435kKqYj4vd2cl4Wi78B2M3r1mOdv7eHSnNA4eklKkhiMs3gEQym4GtX487e2+E3r+E1VgaLA9odcu9BHYPC7O4idXXa2btOSkqlaHRvGXLI3mZqZZX6mSbUaEwXBhBjF3T1sj8BaT6QVUa2CdwJvHTOBInIZS9aAUPQQB3jmSyrqfsWGRuPVvzfpjjz51FO8+OLzvPtd7+bo0aOHvje5hkO+xp2HOOkv7mduJgQgxiBsX+L44It39r65c6VxJSSuHFB/vIO9Th/rHNpahsP0YIUTzqvYX0uZQShrAsUrtmiNLTO3ft/DRAASiVSl2pwUCinFvghecSib9+WNrzU7gh8fV7ntoBJy7VcvkQ1zzFIdbcGrUQP3oaF5MkBIw+bTXUxh8LoMqsTTipW3N1m9mHLj87uYIsfbMs/TqGrOfOM02Sq89OEWqgo+lLjcIVPJ+bcfQU9LrvzuFlmR4CNQQuITxcrj8wRxg9VP77J1qTtqBAvKBCzeM8vRc/OoPKJ3tc76cztc+IXrvOYd55mhw8PHPcMkoyh02U9q1BB3p1fwqed3eON9NU5OJ+V5H9EJSwdd8JkXOvzWZzvMTis++KdO4b2gsILcQG7L18YJrICbewUvr3lOnzg+EUMog1jCjTKdSu5b5fEtdHBrH25DIO74e6f3PZnYHQcGDu5LsW+n7xy/HyabBG53AqdXfOkQGDk4jsNg6/DdIcbvTeIp72nt9EmGBmsszz+3yvqtFnFF8obHjlKJq6OG6GWWeH8z++s8+CfUErzk5JEmnWHO1uoOJ+45ig4mirHG+/GKk/yljztrBO+6zMRrP2kovnq46VXHVxxQ/ZN/8k/46Z/+aX7hF36BBx98kCeeeILv/u7vZmpqir/xN/4GAP/0n/5TfvInf5Jf+IVf4PTp0/zIj/wI73nPe7hw4QJxXHLjv+M7voP19XU+8pGPUBQF3/3d3833fu/38ku/9Etf1v4sVPdor96i4wNWlht84cVrPK4q1GZjBBoVRBCEhDMnSXJb0hGGBVXlieNSvUur8tFQIJiqCwrn6KUFQVAWxCmpCLTCefAy5OSpB+hUjlD1luu9nOXZOnOzs2it2dvucjOvsbTQZNsYKrHEeUEIVLTgoQXP+x+vECgxUlQqwCVsb6/zzIvX+MTtGlv5Ud585CVkZZndYoHdgWTxrGXx9FnSQYZWjqS9zsbGbQJXUIsUQxFzbW2Xbqsg7ycMkz7tfAhKkaUJrshxvkyhZ8ZRiWKcUNSdJoxrLM0vEasQVa8ipaJvoD9cx3ZaxFrSTiyRlCw0qrxmeZr3P3ycxRnJ7e2Mj3WHbPYFaVhDmSHCamTcwIlSzQkPxhcMuy2krhKEEikDCjzCS6SySBmCFIg0I+/20LqB0hppU2SeM7QZ+VDSDAJS4xj02ygpCQX4qEo1ijHOYtIUmyQ4DYXL6eQJwkkCBFp7nFNESjAoUk41m8SBQIqQzUGX0Bvaw4LEWpwUiFqdQtbZ2V4FZ/HCMTCeOCgjKk6FCMoagizPyfqdMoUdhPggQjiJGQ5Q3rMQWAa7XfqDIak3SAHZoEpmcpTyqCgqsx1InBXoWNLQmiCQZEOLFgU+z/A2pZ30EIFG6QgdVCicw46VoVxpzJ2izFw5jxeSAiiGGdp38N4RRCGokCzJKMQAEUicE3gyFFDkKWGlhjdDLA4tNVIpbGGxWYH1FutycmNxPsLypfeR+VqzIRXnGF65xZ9tzHLMOIqNHfyIRoYvMzlCObxeA79G3nJ0nkjLKOtISt0IyXQ9IhjVrBkLQimM9ewVFu1gCkliPC1nmVUaJXRZWu4cpY9aRumcFGXNlLPgBTLURIs1pHXYzNCLQ6T15XJC8Llnr1E4z2ytQv2h06Sz8/x7/htd6XjksVnOPnaEpSii8cYpPviOJd7zIUl7UPCZpxLiWJPnjqZwfNqkSFXwV761RkHM//c/rnJrU/JrWz3Wj1gWHqizM7AMc4+ZoKcMheSFSshHZpts9DSaADtow9oaD3zjN1OLQ7TpMby1yvve/lo+8cSLnD19Co3nxUurzEyH3HNmljAIDmcr7haVpsQSzWpELdL0ewXWCkxhOO8T3lbN2VYz7MiQS0pgJr/t/X5m7/AKeaU3/+V49750dzrdLusbmwyHfcY1dCVFdNI9uhMITWSbPHgxQaXxMEwSXrjwcile4wzOee695xwrK8tMOo8H+bdX7riYeNtT9hlLkoKssLTafTa2WvuF+q+M4B+cokoYMFdrEGld1lT4UkSoLM2zKKnwTuCsY9wfSwjJ0akmtUqMDBSLMmRKlH3+rg7aXEraX8aJPjy+1uzIQdawDLLMrUR0/397dLZ7DMI5XCZGHwnqZzzhn49pX0p58p/fxGR9tI5QlRrLb68yv1Sh8/khF35yE5zCjyQoznxjgxPnp2lfTbj8f25g8xHI8IJ4TnJsvkZUCbj6L7bo3U5B+JJCF0hqPxxSL+Dyv9zg5u+1wPtSuEl4Hv2elFN12N6O2Pi8pr9ZYLMcu7uDdIbXPmDJi6L0WaxCSY8Ugts7KY+da/DmBxo4ZxAjyq8Y0fdy49jY6PDn39FkuhGy2CjK/ZkEM6JsJH1zs8uFjS0aqeKDZxTWS4xTWCcxo5/UCD53I6eoTtNo1HC+1DZ8BXQaoaxxlvQg13twfx1Q5yYu4AS4EYfuW5hU5BxT2w5vdRIkjWfDF8/QHJ47kx9ObPsQnffwksaUNsE7z3NfuMmFL9wmCiTTzYB6pHjT44toJZibClHyYG+Ev2OLh+IogkoY0KhFTDerHFlqkhvP56/sUp2d2a/RGgddxnbtD5pg/v1x0YEBu8vj4H/o+IoDqk996lN84AMf4P3vfz8Ap06d4t/9u3/H5z73OaCcpP/8n/9zfviHf5gPfOADAPzrf/2vWVpa4ld/9Vf50Ic+xIsvvsiHP/xhPv/5z/P4448D8FM/9VO8733v45/9s3/G8vLyl75D3Ut8/sILnD1xiucvtdneLTuPqxoEukZzfpZcV9kZDEiynGcvbnNk6RSveSBipt6gEQqqgcRYQ7vXI/A5VzfanF6cR2pDq2dYma7SSjOEjFFKsp5kVETMLQFJEJILx+WtLaoC/s0nU57tz9PO9xAI6jKk8KUufk0rzgUW6zS5txSZQWDBDNkbJNzuZjx5pcbrFy5xbGmeorrAjecvc3vV8dbHH+TWWp/BQPH2Nz9Af2eeBx54G3/i9StMzUSk/RbXb91gfWuNazdu8ukv3GBjY5PObouelaBDnDWkmWW6EtOo1YnCCnONaUSlipAOKwKkUPQHCa3WNr5ICOoVpBaEhFS0ZqEWc2JmEVyEEIq+zZltVFgWIddNBSEjbJrjxJAoDiiKhKBw6LxPYFMqsUYREgaSQnq8LwFExYtSfa8WU6lWyLMeohAI6+grWzpNPqeXZzhviITDWJBa0evv4dMAZQu8gEAJpLCARlTqxBKaQUBVlMW0tUDTTUDYjEJokiIlyXOGI4dLa1BYomaToDpD0llHGc8QyZQOMICxDu9TnBX4vkQHIV6WDwbrDEHh6ecp3kNFK4TPGQza5MmQ/t5tAhUQTS9SqTcQQmCzIdKXD7cwCBHG0OkkVCth2Q8sG5I5X563JMPbAqE9CpAqwkuJ0gFBEKJlqeQnJERCEFYUlbjCkaUlGvUK3V7KXrfPMMuQhSXFElqNLwpy78kcYAtEkuBwWFtSdkgCAg85FiUClA6oVmLqU9OY/Es3p19rNqQiYT1L+Z7mPPq5G1x+8VYJ7sWBAa+fMCz/OUPg4OY1xX/77ymJlFzvDuhkeSmJbUuDKyQYLzCy5Kd3hOe20gRIvFfEAXxLKCkc5MIzp+CdczVSJ/h3a7u0C0+ExHhHX8J6ENLdisuqbWupesH3uICTUhEIwY3dHu9emOPUdI1gvcpHnrjNL164wvd96B7+13/4BqLpGbyPEdIjlScQnqb0HD8zyoJ4wFucLWscnPMY5/jUhT3Mc55e5vG+j0wUNekRWPyI5yKlILWe1Qx+Ipplx1pC48h8gU/6VDqbNIMGzYrkyfYOH/nYJ1m93eLqrW1CHVCrViiA4Uu3iaOIMNDEkWZlqVlmAu+WWBIHSSdbWOppyqO9TU7FlpnCMiU6tGpzmNoCZZ52Er18KZmqu3FovsgYO2FjB0OWEfTJPlN3o6H4O/4pM1BlPc1wkPDc8xfodAY8f/Ea1o8aFQlJLxHc3uphncNah3MOrRSve8059JjiOP51ByPIGMva7W2StMB5T56XDIUszw9FqO82tNJUggitNM1KhTDU3N7ZLTOV3iFFiFIar9Qh96qbF4hAU1GCji/oC0NhHbeLIZPO0pc7vtbsSFxMQoJ2AADv60lEQVQJECicc6SpIc8tw3ZO/1pBEu7hcOVzyXvUfIxorZCvOqSoIeSIVoxC2QC7C+muRYU1nC0l7AWCaqOC2w0Z3MiJwwpWlsqdzkOgA5qiishA+gAV2JEEusAJQSUNiToxfqAQMiIMy2ySKTzDdejtOPYuWUw7wQ8KvDH09jr0sFy81ae5lxIpSaAUSik8iudvJMw1Ilq9BCkloS6VX5VSZLlldWOA0pbX39coXW/n8MIfgiLOerLc8d+f3eLMfIPl8yH1KMX7kUpkCW/wSFb3DE8/c5U/941LPHB0pgRaXlJYSe4kuRMMckUuKuwVMbtdR1wJ8ELjkfv35FgQxPsJGY1R4nc/qLC/7ERr8H3gcbfM1ZeaOhkBucOptcPf37cn/uCzyWw7ZYb2t/7LC/Q6GUFgcU5Sq1U5vhxw/lSzLMkdB1Imd35/jEGhQEiIwxCpJPVqxOJsg7mZUjW1PzTc3hry3LNrPPrmOtVKNIky94/3i93Jd56RL/WO3z/vX9IavvpI6ysOqN785jfzcz/3c1y8eJHz58/z7LPP8olPfIIf//EfB+DatWtsbGzwrne9a/87U1NTvPGNb+TTn/40H/rQh/j0pz/N9PT0vgEDeNe73oWUks9+9rN827d925e8P6a/TpYPCMhpt/bodiyXb1fYbm0g1DT3PnCC9bYBJD6S3Fzr0IinefZGheo8rNQ8uQy42ktZtC0WXZ+nn3mJ7N5zYHtc3yh47NwRLqxtUDtyP+cXQtY2bmCTJhdVhRXbQdck3Qw+c3vIk88ZbpkeTmRoL8mCGOkMQgR0/JCP3Vjnzz7+TlRQ0G13aUQjpTZTsLZ6k1tX1znnenQap1kItqmpguWVaW6vvUBQZBytLdK/9Rzbu12OLJ6lGRxlJq4gmmc4fuwsQih6gzZLn3iZpy4NCCoCHVi6WzukrV3yokNWJFRdQWEy0l6PbqdLpzsgTROEKptqhloRTE0jA4UkQDjHdDXi3lPznD4xTRBHrPUsL257VGUKNzBMCYePAoyukUcVQKJ9Xjbt1DG1qXkiHTB0GaEOcSgCqSicQwsQXgExCIVUakQv8aUEuBIETqPcKJtlHZABqgQsoUIUlkoQlIDKl8owUgYUUmKVpBHF9LKUvsmZiQLSzLBTWJSGUFcwpgAn8UrijaU5O0OeG4hqZL4gHAnrSAxOCEIVQaDIvcBrQdWVRIRClLUxSkYoYQmV5OTKLKs7PYoixzmPlQJvM6aqc5iRDC5IgiAkywqUFtTCAOFLKftCeUzWQaqIoFLDqZhqw5SA1HgIACRhoKkGFcIgQsuCuKK598wyRxbmOH/2OHEUsNVNuLHW4sqNDTZ2u/QKhwKCEVVwaApskQMCR9kTRwqPdo7Ce2qBwooIiSMKFPXmNLb40p2irzUb8jebc3wyG7JVWI5kFlVYSg7/gUpWul4gPwuBLHhpVfCZXoHXkp0kQ8kc4RQNK7lvVoGCJ7cMOzl0RcBWpYaPZnjg/jNMV0PeN/8SYrXNL32uQy2QvG4p4Pj75imE5Mi/avHMdo++kAwF7CIpTq8we+5USdcYJGTPv8xWZoiVQSq4bQpWhzkWz9wvfp6dpIPWgne8oUkkC0gHoC04sAV4a0oRDcoHrRcKpENgURKU9Ggs/9vfPM4w8SSJp0gsYV/S3jb8qWbEet+RJAVPXNNsdYb4QYFl5EzpUqpXRp6bl19i/UbJBDi+coxGtc7RI6dGkfFSpj8MozLTqxVSqlLmd3xxJhyaO4fyjsgZptKMe/MOzVCSmgAdCYqR8+SFn3zmv3KMPhvz+b8c5/6gz8xEVNx70jRnOBhSrVYRd8uITW57/2UpZfz0sy8w6A/ICssLL17F6wpi6VGUDIAS5F/tO65eSsB5RBCADqj5hFMnE6JA0qxHJTNgYgNFbrDWkeWWre09sqzAA3ElZmZmms3tbbw7OE9jOt9kBF4A1WpEFGiE9IDDOofSIarUSmZfm8YfOKz9NCUzBZVQgxQ4UcqmF+O2DuLVqVVfbHyt2ZF/8kOPQRBwY63HT/zM87SvtRFYTrxtpaTd+fKcee+Ja5ZiK6darXHvW0O8LzV0hRRE05beDUNYneXcN8T7tXkA1WlF3hpSrUxx8k16pCTnEN6jIkF/K8FKyZFHj2IGHoTbP63ZnuLWjYTGqXnONmbLLOqol099vkrrhiLd1mWrBuPBejrbHUSa87krCZVQoSRoJXDGI71jve25/1hMSBe1L0QhkQiS1HFr2xBUIooiBV/WzyklcQ7StGwZ0BsU9IYFgfC89YEmSstREG88IeVIqEdSDwuWpmCm6mgE+SG7MNYP8gi2uy0+96kNdjsDvueD9+GEInOK3EkMksIpch+SFIpWEpEUUIk0qGBk+Ufo6lCOa//fUcBkTO0+mAP7WegRD87vZ6q+yHiFybkj2zzaFWMMQghuXt8iGaY4Zwl0yvSc5MhsjfmpCIQg0KPKtMm6yzvQzjgDJ0a94GrVkHtOLxCHZbA7HRZsbrbZ3Oux0/EYL1henkZrecgu3AmnJjN1B8LsB59Pbv/3B1+vyPt9kTWIiQW/esDqKw6ofuiHfohut8t9992HUgprLT/6oz/Kd3zHdwCwsbEBwNLS0qHvLS0t7X+2sbHB4uLhruhaa2ZnZ/eXuXNkWUaWZfv/d7tlEXxuUtrdAXmW41yfjZ2E+cVFbt7awnvD0vIcTz13lWZ9niOnGmzvdtha7FNsrfNgLEklfLxbYdjLaAQ91rMNbl+7zomlOnvdLVprsDkjuHDpMvfqY6zrgKoU+EpOZpoUFrJswGZueb4NG60djAlxNsdLATrAFgavFBkDMneNLHsjJh1wc2ODhh1SeIVThuu3dkjzea7euMmJuTra9uh3c2q1Bpu3bjA/M8XUnODa2m2Mc8xHjuefe4IwDqjMnOT4tCLNMzb7jgV3g3x1g2OveZTt21dYv53zmkcf5/b6FrGF42dP4NIh3cGQMLIkgx3arV2S/i7KdImUJ/ceWRiGScqgP4DCsTUQ9PMKLqxRB86crPDCxgA9yKh7hZEVBjKmIgOsAOVDlBL4PMNFM5ggIDAWKaGCBKUQKiZSiiTtlRTMQBKqEKNUqaKHxHlJ6j1VafHOk3mD8jEai/Iar0rOujAerSUShZYe6z0VPJmz7FqBFwFOh+wJhVKWircIDM4JQlVhiCcWglQ5ms0KG+ttZmpz6LplmBWkAiyS0FqEyQmlxkuIhcI6g3ACr0CrAONsqbQUCkQUUWvWyQuDVpJYa1QUg66jhEB4SyBLWqKUAWkqyEKF8oZASJSsEasI6QQFjrDqWagvMjWbUHhHqCS5GWCdI1Yx05WQowsxizMN5poxr7n/DJVawOLcHKubLWYb0ygVU611SHNLkhuGSYHFETmFlZYCgfKO3IwK7V2OQ1HTAVbEWG+JZAn4nPjSKX9fazak6TzKGl7u5QwziIQkEKW4pBo9U4tWwnsXBgR1w8efDfmvLYd1Q+6dTvmR92h2Tcjgacmff/MUairkX/xqm42rhmek44WpU9x3Yo6f/4n/hWbds/dLf5PPXBkQFAVvqwf85aUYWRXosM6Uha6DF6tN8uYxvEn5vj/5Hv7Xv/fXsM6xc2uNv/uBv8yvtDpASaW97YZ8PE05oxX/YHkBsIRaUvEFnWvbeNEmqFZHvbQ8QcWC1kDZld7LStnXSoMY1Y4JPHEgiEOFbwoEGuE9y0j+t3fEOO9JMsevfTLjdsfRzQv6uaSfQzcRrPuj6KMzPLB0lGoYjgrgPThPno062Y+Us5RUKFXK/SopicNgn65z4AscZJZEeeBo42k2I1wt4L/bOlII8kCT6YBCjZ2ww3jqrgXL/tUf7ocW2h931F6MPnXe47zjt37rt2nUp/j2v/jnqNWqh/cbxgrIFKYkJHa6PT7zmafwCK7d2qYIpkGFMH0WdAy6wrhg34tR8MU5hHDImXlUc5be1Zf45d/4Apqcv/DBx5mdqu1v0HvP9vYeaZqX1LAwRkmN9568sGzv7I4i4mJ8WUr6sDwQnRBAoEd9ZQKNVKWAz3jZcYjfA6EMCJVGCOj2euSmwArBjJ4hVMF+0X6fgp7L/sDuz9eaHZmb0ry4us2LL7VKAZBblmghZOWxk0xNlWIMTpbCM8b0kHlGY7bBkZPjukuPkB5jMpy1iLkGi8fVPm0UAFXg3YCZI01mFkYwd4xFhcElXQySk2+ujSTNy2sotSdJ+mTJkOVHVgiCsAS9wiOUxwbAwONuDfH4stee9WgtcEIRBJ5KxZbBSil4ebVAWEt7EHB5Azp9TxQ6Ql2yQxSeJHWsbWfMTCU8c9GgyyJTQq3Bl/2hnINnrqcsNTVJBsNsgLZ6vxeSFIKssHSTnL2eBSc4uyhYbAicKUoVwPHwBznWdJiys77Ln37XCkcbFoQ5dM+ObUJq4F/95iqXd3P+9p++B6kjchuSOk3qAnKrybymcJpuCsPckhnHVLO+P+cngw53vjpY4lWy3v7gxaF4jjgIYvT7BW9780N87Pee5td/40m0y6hVAk6uNHjo7DSBLnv2TfaGu3OI/V/lH601i4szzE5XqUaaaqRRStLpDrl6s83OXp+8MLgyQkYgBWaQ88SnLvKGt943upZ33codx/1qn7+6xfV3/e7dtwD72PV/yPiKA6pf/uVf5hd/8Rf5pV/6JR588EGeeeYZfvAHf5Dl5WW+8zu/8yu9uf3xYz/2Y/yjf/SPXvF+p90nHTh2kxwz7NBqFwyGlq29HkbG3NzrcGt1i6UFRdCQJN0hw1afdr/F7+0mPLjS5PpuSYVozw956ekn2NvscWP1FpdeeplauMTzz3W5dXWX+eU9nr18mzfcc5LZeU9/UNDKEjZ6Cdd7Betd6JqU3BcoZ/Fegc9R1iG8RpqU7d5tfudjn0BoA4WlrmBgJe3BgBtbCcoI2q1NdrdnqVNQ7OyRDxKy7ip908H7jKTdI7eazVvXqPcNrZ6gPp9TLMOFtQE9H3Oq3qVWlSR7t4jMNrGrkLWu0bp6ARkuMTPtePHZLxDXVnjDN97H51Z3mG2e47v/wrdhkHzD2UXwhizL6A663Fhf59mXL7K20eamh6KjOD6luJ0O2XYKHRcUVuJkRKwkUoY4DLmljJoEEWKqSZFqlHE4LEaBsZ44VGWEf2YRRARRA68EIRInNSXX2xP7svA/LyzK21JJScZYHFI4oEBpRyOWNILSECsBzgsqRQrGkniBlSGBUkRSIBwUzuOcwbgykymRhAHEQUw11vQrOcYqvAiIPETe43RBJhV4T1VIclF64FIERKVWOVqW6k2BFhRGAgFhGBEKgbceUxhCqdGVEGvystFmqHBALUiJZYD3EUNjUdIQjXpMBUDgCgolCSsK6z2NKKaw9ZEanWZxtsa543UC4SnSlK29Ho8dOUugY04sLFCtZmSFB6FY2+piREwoBR6DkJrMFigh0U7S1I7CBwjvMBQoHZaCK94SATKoYE32invz1cbXmg25kgxZdRk3bItnszK6OtYcEnikg2bgeG81Qs4KPtftkmYe61NaSUo/rROHnitpwKee73HyhOSBI47VTUuWWnCKIskQ29cIMoXrFXQSz8A6nuhYsgs9HkmGxIFib5AwHwpyZzBCl4EBHBWTkuxtUmy8RCfPaRtL4T0WR4qkITVHRcjsgqSWguyCSSydm11wnlAHjGt9qrMKoRUmVQRhgPc90BDEBbIZIWJdCj0AMowIZ6dKp00JEBIlSk2mIJT8T3+iyii/Uv72jsJ6NnerdPaq5ImlyHIGfU+WC/p9ydNfSNjaVfuORkmxKZUTpRQszjaJlZqosRj92c8IgRVgR+pQQkNfRIzdx7EC3Xjhww7Gq9FyXp1CIoQ/7IyNFRXuXHKElLLMoFUyAoyTmSJBXhQYa7HG8zu/83F22z0KY+n0C4QMIJ6FuXsPS6uLUezXQzQ1hW5MjbI/FsIQlEY258iRuDjk0tVVTq4ssLQ4y5gutXRknnET0yTJsMbhnGdnr8PGVmtUHF5ei6W5JkeXFka1Luxn3oQQWAW5Lylm3oMOwkMnWACBKkGxAPqAdB4lJSu1WepxZZ9mup716CfZ/je/WL3J3cbXmh2xxrKzO+DW2hBvS/q3M4J0YLHpcJSVBZSnsqKgWaO9npEPzKhCyhNGirnFBlrA3nZSUqlHgElIaC7UCOJpeq2EdGjw+6qQnnozoFafJuvm9HeTiWnniac1cbOKtxH9bQs+KYGa9BALwuWQQhbkziCFKue4FQiliKsVtjqSzgD0qDFzP8nopznOSaJGhq9CIQS5F2zuQqenQcLujmapKNBXDYEuqIZlFktLjx7Vmr68npK7gGEuefraKlpptCozWVop8kzS7lmurg9pxgHVWgWNIxtRrcdZYOc9rc6QtHC8uGZ46HjI0bmoDHTekSkuAYYgTTICkfKGUxErjQIpDILhCJyVNfTeC6yT/N6LO/zuZ1Z50+vOcs+xFVIjKVxA4TWFDTBe4tB4FIUTOFdS6ZQUjAsZ/SHv/7DNOaTUDmys77F2c4s4qvBd3/4eXn7hCjJPmW5WqVY0tWqIlopA322dkxmjcoShYmaqhpCKqWaV5aVZQiUYJikbW222d/vs9YYYMwp+CfAOdnb7dHs5292Ecw+cLmuoxKuDni9lfImi8l98iEN/vgxuwR98fMUB1d/5O3+HH/qhH+JDH/oQAA8//DA3btzgx37sx/jO7/xOjhw5AsDm5uZI6Yj9/x999FEAjhw5wtbW1qH1GmNotVr7379z/L2/9/f4W3/rb+3/3+12OX78OJdWN9nd22KvvUi/3aaz59hp7dLebYF29Fqz9PZ2qKga0Yyk3d7GDefIOwNyO6AfHMW0+tjU0Qoinn/hIku1Jpvbt7h2dZXlExE3n9tle8dy7+sS9upNPteF+7Sj3UsRieGmNdxKJNlggBagbZmdSZWmoCAS4H0pU9pvb/GLv/IrzE1NE0SKbNhlYf4UraSgn0p6JifuZ7T2Wmzutui2YXpasdfapd9LmcpyNAnpQHI92WX2dJUbty361nVqwzrP3wyJMeg5Q14s0F69hJIZ88059m5fRmQpc8em2bl1kSTZ5eTZe1i/foHO7ducXnwtN3Zuk3QDHlpeYnG6Rq1aZ2FmnnPHz7B84iyfuLjL9taQ59a7XBIxs8uSrNKnYnMkCQxTTGaIUOQ2Z1YaBkYgvCNPPXEkKIZ9tKpghEKFMXlWEIQBQaAxLsTpCBlqQhkyxBJ7hQVwAisMWpVlqFgDQYAoHM47qjoGUSDigBQP0tH3Fm8FyArEjprXOOFwVuKkBe9Kw2ctYZ5jhSDUpcMYxlWCMCYMwReSILSkxpNLCE2AiiTOOaIgpiICjHJ4m6McpBJqWtDQIcszhgdPSBYqFaLaMsVbjpEMU7ZaLaSwJC6jlwcUIsQ6TwAIFeJxCCVpeI81lr514ARRTeC8gSTFyYC68TglCV2AUIJavYEIPO2BolaLOHvuJMeP1lGVKYyUFNbS61mM08w254gqM9zY6eMHeSmxi0RrSuVALwmFJUThnMUJME7i0x5GBARhhFKKvLxCX5c25D+lHXakZ0A6op0ekBbEiDoxLxX51DQyNpwRqhQ9EXUGRZ+f/R2HEEOOG8k7TsacWBHcvDFgtRiy4Qt050k2+4IP/9CnefupWZ5c3eX6umHaGmquQNQlD90flP1nXlYsiRyV7uC2+njn+a//YZPa0x/lu87tooshR3uKB4ppwGOwXJM93iiqLAiBqplRk1ZBqzckTcvahvlalVqgQQiGWVk/g9UEocQaT6UaEjfA94qS5isBWbZ8sO0SHIT1EKEVKIkIZUmzlQKh5bipPUpAoOHUkkMsAj4va7+8Ai/Bex55MOLaTVM24jYeU5R1HP2hZ22jpPt4J8eclH0A45wjzy1RIDC27JXlRyDGM8qwjHwXj0Drst5DiN/vUXu32oLRq7tGYcdUoDuW9yC8IpCa40enqYQa5yzDNKUSxzjr+ejvfpKrN3cAyWCYQX0RWZlG1jSgIIghrh2sbwSIgrgExDKqoqK43AMhcBLwgnDlFGJqEdPe4mMf/ySve805FhfnGcfs5ejcOFeep15/iLWlqunRxenyPIpSprpRqxKHAbZceelbCYESJXVzmBb7zpSUaj+y7kaS/okxpKaksBGHRHGIEJIL/c0SYY1BovzyaX6T42vNjlgLvV5Bnrl9AIwog2BlO4QRjVIATuCswBqPtW6fOlayxssMqDPgjD+Q5ZYCnEBYgTMCZ0q/grHwiS0/x5b+sHdjyphAuFKwyDvwdmKdjjI6MXrfuQmFPqewVuC8IMtibCFGrfIEkaoQ1Eqa6u6eZa/jUNISSE9/aOn2SnqgMZJOX3L9dkghUqq10fEhUXjywrHRKmuhhYSXblu0cCjl0aoEcNZohonkZqugWXXUBoZnL/tRk99ybktR9jbrdlM6Q8vTtyzvOgfPXrjOw/fMl6IoQo5EM8rgQF44Ll7a4sSc4t2vW8Rbix0D+9GcLwM0Ho/Cm5R3PTbF+95QQclS1MN7gfPg/IF4xk7f8jP/6QrHlmqcOXeChcU5jFPkRtJLHVsdw/xsA8dEc15fBorz3KBEmf29cW2N1tY2959fxiRdqoHj4fPzgEQpiAKBlK5UXJy4kUb4ej/jHwSKKFBMTdU4c/oIOtTkScHmxi6tvR7dfkKalj3BnAfrHP1hQW+QY6zjU5+5SZLC428+x7nzR8pz+IcCU1+B8T8wKzU5vuKAajgcTnRNLodSZSEmwOnTpzly5Agf/ehH941Wt9vls5/9LN/3fd8HwJve9Cba7TZPPvkkr3vd6wD4nd/5HZxzvPGNb7zrdqMoIoqiV7y/udFm59pFXspS2p0titzjioSbV15CRQ2y/ja3b1wjndvk5jXB7tYmz/Vus9deJ08ykqv3cf3KFephE7e8QOfKFdTRYwwGO/R2d2lHVTY3b5Kllhuf+k02bq+zrmIGR+a5fPUm9XqTnUbIra0OUWURP/U4RhcYWxA7TQ3NQBiU8AQW9gY98tDQkxXi3GOGQ/KmIeulbLUMaWWeQTLgyvVbvPTCU8xNH2P5eJ/nn3uRkyceIM8Lbl6+yvGzD2L7e2QdTVBdotjdYkbV6Q+myO0eDFOGeQ7ZOkmeohYistYtOns9jriT7O2uIfoDGhVPa2+XmixYmonY3tlir+25cHuR7TQkLxRT1ZBAC67s9FhqRlz+wlNcv7LDI699LU89+TxFFnLvax6k2/KIvMHSiRlC70mSgmpNcFTmdIcZsR0wLdsU/Q6Z13TTgsgFdApH7mOEUhQiRIkAIT060CgLwguck6TOIYQh9oIcQ12I8sEdFJAbhFRIBJGOyCVYr0tami2jVxZH6CVGOGwgRr0NcxACZQyf+NhvMTM9xaOvexPOS1ARIojxkcTEIXho2iHGaxQa6wuMcQQE+DBAOINTmlDCsbrk3pWIR5anmGoGEMTce/4h6rUGURwRSFn223EOawxZkbPXHfDZ5y7z9Is7WGepaUsqPKAphjm5N6g4IsgdmQ9QVUFIhSLNCRV4LFIF1HSANJahD5muxlSqIYUXDKwhIsQoTXO6wU7P0NnqcHV7Fyc0URzhTYZVIToIyRD4zKC0x45yJdbkBFhEOI2xijDwOBVQCStftzbkihAsigoPywrhOPkwopzZ0j9hOoCqlQR5xGtCjVeGnrA42URllsI7uli6Wc72rubXnvFIV+G0jDhaePLc8ZsXBEvHVvjo05tsZwUexbqFY14QNRQbA8G/7GWkps7DNEZqaR65arjUu0X1oZRdo/C5IFKypCOiqKMJhUQKwRM3HD++sYcNBZ1eSg+BVAKTOCKt8VKgAkFaQDMq61la3Zxjiw1025Z1f9oRhgpVBSkk4cAgpKDYU6PopEA3NMFUiBcSWY326x2FKkGb1BM8Oi9G4dfSgXjwvOeBe0tnxY+lppE4J7l0KeXa5dsjSqHmk9eOYqhQA7zxXFztkeUZzjrKK2NGmaGyfiuKRlQ1CfOzUxyZbiDv+vT94o/1/ajnvgfsJ751B4VndKhulGeYrxr+P98ZsKra/Mtfv8bLL79EfeYIxjo63QE2OIKKmhCXGQAR6jKT5Skz8kIiZVlHVvaJdlTm5hA6KB1twPY7FN2dctvW4JIhzhhUWEE1l+j0uly5coszp44gVRkkSNMcax14z8x0CdomI/d+Ig1nrAUs3oMxjjwzVCsR0oiy+ecrTqkny3N0EPBq3s5+Z59R1lBIQVwJRxTAL398rdkRRykNf9AQnBKoFB5r/L5NofD0NxxIQd73uGJUsSYgN9B2ZVPkfOBKD3eMi4DeRorQgjw1mGIkVEKZeRxYQ9H3ZLnZz2yVE8QzMIasZykKv1/vul+35sC3DEXuyuZgXuAtZTbFMQoUAO6gAS+UfcilElgTjFQ/D4Bao1r+jUOHEJ7Ee5oNSbNRoAOPkhbpPWubgsII4noJyDcGJUizI6BnrCdNPFIYNvcE1Yoh0hanBtRCQag9gRLoUY2VLdgHLTd2c0QgqN4oCIOS0qbEiFosJGkuuLU9JPOC3c4AoVQJQKRCK1Fm40bUtpdvddjeG7CwEBIIu5+1BYEWlMhUKbyQdHoJx6Z6/PX3r6B0D0Qf78A4wX97coubL/f5U3/6PMYpijEQs4qf/9WbPPtSilaK1o7hzJmAN77hGCtLTZwraFQVJ481cZSXYKSyj2TU1806jHNl/0khaDYqLM5Ns7A4RSXS5RwZprTWttje7dLtJVhTTgHrPLkpW/dcvdnnhYs7XF/tU4k0P/r3/wIvXLzEuUdPlmBq/IzcNxd3CS59GePL/sYfEZiCrwKg+pN/8k/yoz/6o5w4cYIHH3yQp59+mh//8R/nr/yVvwKUBvoHf/AH+cf/+B9zzz337EuVLi8v88EPfhCA+++/n/e+97381b/6V/mZn/kZiqLg+7//+/nQhz705Sn8AcI4vHBsbq7hcERCsH79OsqH4HI21m4TKE3e72K7hopTbF6/REGBQrD20ouQZSSh48rlPbJhili/zd6mQPiCna1dBt0hNnd84ZmnKPo9XBjSvh3R7+yQRVPsKkeaJkTVJcJFgZEhOozLm0j4ERc9InQDojTh+qVN4sYQhCMbdjnTC7F4zGYLKbeRSrPbt6jKNEUYsLqxQzF0ZIWme2uHXjLEecXu9i6t4YDTj0xza+Mmm7fhode+DRKHyRWLcwG7aznb6ztMR1t0t1dJOinZ3i2CzgbBYIjqrqK72+huQtbeJGfA5pbh8vEltnYL2h3FkZU5bD7g4q0uJ5bn0BWoT1WYntNkwy20qRDmm1z6whNUwxqLcw/wzGefx9ebvOctj/DSy9dZXpjng9/0COdPL+Mpz1evN6Dd3uPCzXUurCuG/ZRBWlIRfFA6aQ3lKDxYJ9BeYB0UviByitwrlCpFIqSqIQNFM47QWpE6X7Lf8hE/3RsEkApHRVkiJ7h9a5VrV7/Aw+dfS6VZo9PaIM+6WPVO8BqpQupBTKo1eIcVHkfIQeo+QogCb3NMnjLXqHF0KuLcYsBUM0aLkNQHOBPQjCoIVcV5Ba6kAiIEQRQQRoqaD5iZqrE0WyUonuAT1wYY5UsJdRnh4wJVOLwUhJGlMAO0r+ByS+ZzbNggdopaJaBe9aSZoFKpYIzk1m7CTLOGNuBtBt7T6iQUeUY27FJTBdYZhrknR+IpxTw8nrCi8caiEBSjnmXGUPa8CgOUBrwGX3zd2hCcYpmYdzOPkoychjEtZJTtsILP/HeIpKLal5wXo4i8HelFyfKhsn3V8fnbknuDGc76ccS5dF5E6ln7Lzs86k9ig9IzFoGkkho++1FHkSjebiqjhqelgyI9KKlo5pLPf8SQDTTvJCp5n66Mbu65pCx0l4qaVrQKcKGkn3o0EEWCztBS+KJUL/SCQeZYaCiccOQZbLUGCO8YJglR4HEWmg1FEEqWlqZG2SePLJNMxPWQSteAEkiRsF/K4CVOKqKlCrqhGHU0BkQZMRcOEcgRyBmR/mTpDAmlue/BOe57UIEX9NKA//AzQ9ZSS2wcoTD4EzWyJMQVBUUvx3c1EolyDolDBOG+sF8/cxgvUH5M3WMUvqV8cWfR9v443MtmnD64E4KNfear167R7Q/Z2W4hEES64FTzKr3sGC+uh4hT76cf1cB79HSOMEWZXTc5wlmEUKgowFOCYi88teWjZRNcT7mMkpixWIzzmNYmRWsLqUOcigBFUJ8m9H0kbayRWJfu10F54VFa7bexONy09HBPKTHxG1FSnGv1EVC6ox7sYAgqUXywhrs6PYffFIKRBPMX66H16uNrzY54W9oKN/mmE9jMY4oDL9Tj8e3J+aTG74LwFN0C4f3oR4wyOiVSSTsZB5N4vI7yd94p8CIvj30ia1p+1Y1flJ+JcZYQvHT4LVsCaiPxdkRXG90vpaiURpnxlkfXd4K+JiZeiHHsxHsY9TsSAvq9Br3ewVEL4bHW0qhbBgMIAoeShlBbKsoSSId1lhdbmtwI+knBVBMIDT0J3VxiEsosmhVkuaPIwRnLdkdycdcxVVNoXaC1RYxEc+Rof5LM0xp4docFL65uk+NRUhBIQUVLQqVwXlFYwfOrffZ6GdX6FK3ukECWFkxKRiBNYZ1lr5tz7faAqbpCCIsrSnqsw2McXLi6y3sfnWE2HJSZw9GcMF7Q3t3h297/GuIw5Kd++hmkCClyQ6+Xk+eWrdaA6+ttHCU1+rF7FpkaC9AIQaeTEEYRcRQihadWC5maquO9YWOrw8Zmm04vHQmZlGUu1oL1jmdf6vHscy2EhO3dDOcdoMAHnD19gpvrGygp9/vH7V/0r0i66csck/vwP3h8xQHVT/3UT/EjP/Ij/PW//tfZ2tpieXmZv/bX/hp//+///f1l/u7f/bsMBgO+93u/l3a7zVvf+lY+/OEP7/d9APjFX/xFvv/7v593vvOd+830fvInf/LL3p9mxbKOoDvsl1KdXqCELR8ShcSQ4ZAoMkqGK5BInPTgJB03QEuJdUOkKDACWq0dTDKgUp3nHQ++gRfbbaTPSIcJ8dQiSb/Lxu5tQq3wFUf31iZvfOu76fQ2uHbh1zBF2Ycj7/VwQqKjmEDFhMKTidK0DZNheWNLxQsXnkF5R6/TxjrHMA5RQZ0ojnBFj6gac+zM/ehQE1UXkHGEDxRJ7kkyy1xiaW33mNIBa60WLz73JCpXnHxQceHJJ1FBjXOzfZ5/4WWmphbZbG1z9crLTNcX2NzZpLV+A5dV6O+t0hm0GG7D3tVpbpkWw04A+Wluba7S7SpmZMLG1asosYBpbxN6S2VuhjRrY92Q6bklTHeXQdrj9JEF2tvXWLt9lYXQ0t6aYtOnLK0sU49ipmp1jh1dpjCaZ69eoVZrMrO8wu52DydLzrcdDHEmJ8CR2pww8UjjEYEiKxK0VCjdIFZBWdguIAwjprzDeINRZV8x4QOEE8QIMpdSCTXd1hrPPfm73HPiOEuzDRh1rcl0WbvS2tjF/f/Z++9o25L7vhP7VNjhxBtfjv36dQ5oxAYTwEyBIsWhNKJFBXpGGv0hyxovjcfjGdujNabXzPIaa2QujTWyxxpTFIMokgqkxASAAIgMNIAO6Pi6+/WLN9978tmpgv+oc8499777Gg0QJIFeql797jn71N67qnbtqt/3F74/BbvjPq6xgFYKSULsDTiolCfSmtV6ykMnIk62Au2okTEyqqGTGkmsqCWSOIrB+hA7VWbUkzpJHAQcKTXgEDjaMuH84oi6jillhMPiI42ZuILYahwEr7SBcIo0UkT1IJTqSCOFxTgPscFIx4Xjy9TrQYCNawkCKIdjxpmhAhaPtbBdRb/yKJETKQ0+BRWRICkVRHi8ySBJkUITRxHOB7O/9RUqUuivY4X7VltDPIF1rO9K1KRf85TpIJAInr8eUiV79lmfxMRJMnzxrHfAi4nwMqk9r8krJrmVxBRkWRhlgtevCIQ3JARr6j6db2BsKjO48rKeuKMUE1e30I4Sw9BrnIOm8CRSMAa2esHHq1mXVGVFnEgWm4FtLDeBDt1ZT1FAWRVYoMgdx9oS7zxKR8hSULkMJT2JDgKwjgS+V1BvFESRmHrmIaRA6pBLSg/GqFSFsZMSHUfESUjdoBrhuDUClUaTpNMClSSMnCTHI0TEqBQUNUW6vEDsHWdOLBH5KSOc58brt1lqLAbKbutQBAHNWEvic37kTAlYfvcLI7JMcPpYi9WllJ3+mN4wm5C9hDiN5USFJOnT5z5DF3NSgz+YXNcaiwM+98WvcKvnEE4hVAMpQlxU5PcQ4jQybiJFCMh3WpAcO4Gspfh8jLABLKHDmAgzoSBXCqSauHNJvLdkt69S7K4hfEhEH519AhHVUf3b1Po3uTR6le+oXuPcd7yXzfvfE2I3JqhPCEEc310cmM1hf+DIHR+/8TIHaqfAwt/5+9dTvtXWke3dgvG4oqoM04E0eUXnSid898HdbKqkmZk2p4AJj5KeWmKxTpCXEcIfhprz1tK5PEuHTYYzCwr7wGdq6ZqStQhmrroIP1tTsFB0CrwQjIeG3e2CYgTLqaJRk0gZXOYmYY+Ty8+1cgq2RGjDfDzgfNYi78PakNY0ZQllCaPxfrODqx2kiSCOLXGUoFSwVlWlJ9aeeuJQMqxL213D6zfDOdbAGEunJ9gqBcqD8C4oMQPZJJ2eJVIEr5/tMVqHGO1IS7QMoHJz11A5x+1uhXCgN3s8U4NTCzFC+Emie4f3imERQNqVG0NUJOh2C3COwniMFZTG0+sX3HdKU5Y5U1IeIQRZBb2BpSwqxkNLWQmM8axvDMhGjt3dDhubXW5vDUJcdiR57eYuqVZESnD2zDIPPXCW+iSPqPcwGIy4fmObvV5IGWRtCI0QBK+F4bDit37vJnnhGY5hPDYT11QmsZ8CISK80qgotHPGhOoPPfOvo8wvM1/rrb9rvSNAlbhb3W9i+aYDqlarxc/93M/xcz/3c3etI4TgZ3/2Z/nZn/3Zu9ZZXl7+uhPnHVX63T2MyydB1AojgtkfPFoEEXkyNUAIHBIpgyVbKo1QHiEV4BA+JfGSQvapMEip2Nre4+J972FxcRmjPb3eCFdZFpoxUkX0R12e3f04OkqJm6d43088iR73ePpzH2aju4sQETqKJsTYGi0EFgI9ORaPxIuQT6SyDqzFVwYvKvyoolRDegPBlpAo45BKoHTC7uYetWad1sJxdjZ3aR+7gAP6Q0tSX0XEknGWUxqPiiU7u7sUZVgk93a26W13aKenuHX9Fq+98BJnLr2DF198la2b1zh+8RFeu/oCNh8T1Y+TD+rcvvYSmmWG25btN15h9YSlt5mxt/YG55I23fUReXeb5vl72V6/Tj7ucHy5Tr+7hq1GNBYXeOPGVb762uu8/5GHWIwr8gqiZou19Zu0ytuoyPDSc6+yfnuLcxfO0e23WL/ZoXl8lfsvnKR/awfdaHHPxdNs74xpSEctFbSlQwsTktN6hfMGX4AzMdYqCu+pnMU5S+oc7Til8OCw2MojpcLpQOWaxIKlRDMajXnp+S9x6eHHuf3qczzw3u/HItCJokKTRIYzLc/F5Zg4ifAywekImcQ0dJ2ammw4WpLEmlgr4liw0Iwwm6+StC+jdQtmsUeards3+Njvf5J/8TufoXbmcY6dPUcrEZSupK2h4zxp2qJyBmENkVAYW1HagkgrKhOCgvu2JNWWxEh6iylnV1dZatdppCkOiTGOVrNglOccX6hTlrCzO2BsAuBLorDhGAIhQ6o9Ua1F4UOi2rqMKDxUeBIXTwDEW7dQfautIQA5lm2Xk3h5gC1pKm+EFWQqyMwlVBVTPbHfp+iGfSHiENPchKttv5+T68iJkI4HJyZpPL2Y3X8GwuY2suntBqIiQnDaOagC0Ypz0MkVr93MeNf9KR9/pssD5xIev1gD73FW0s08VenICovzIQF5M4HmJKdYZDy+9Gx2BuAFjbqgN7BcOpPQG1YstFOkdMSRJIkF1kKURNTqEWJQzCwfiKDJjeMILxVJLAFLZ6vAWh8270hx8oHT/PL1lN/bbiG1xWO5tpPh0l1SqVDoffc959gZVKgGSKFIU81iqwYiuN7VdMlK+xbCWxqPnqPIIkbVmOONmK08Z/HSKax1lJVhvTfi5b0BsZYoHNJ7IiFoxQlna3V6VYW1BgVoEdIZVJXh9z72earSsJXXiH7obyJdhf/sP0eVT+FxmMEa1fombv0VvIhQS6eQyw8i8xHG5MTtRZTSINWcst8jvAuxMdaSXXsBP+oiEVgixKmH8CpCrj2PvPoJFqsO7xF7/NR33ccH/rP/jMYv/B95JtV8VKtZst7pTJv/NJNHDksfd5FG5mx5swMHQ9PuIt0cWaYgb18u+1o5sI4q32rryH//j5/BeChKZhT0Va/g1uduAZ7lYy2OnV5i/UaHUT+bgct5K9PpyPGjJ8fcziL+1VYzWJaEP/Ss/NwCM3/2/lq1/5s4JPfe8ST38dYEqIcDEiFixl3JoGcQ3rORQKwlWgmiyFKvSU6dtcHhbGrQnLNgChVi7g4Lxf7At+ka6Gc/zvdVTBRQUkSoROGcwJawteMRc8nkp7a/40vB+iJkhVR9GrFjcSkjiV1IRuyDWW5UCG6txcS6QuSO527neBeIMqT2wYVeKPKRxHnL3sCjtCepGW5uD8nGwUokJHQHBmcEa11LZ+Tw1nNqOebKtS0k4JygN4rwQjAcGzr9MXk2jecK6rpbe7DX81y71aMoRIinqiAvYZhb1m/uMBpk5EUVFMc+YrdfoCajYCcKm9MnlzGVZbfbpzsYU5Rm8kzD+OSF5ff/4BbOawajiltrJe6wgX4eAAsV4id1BJOkzf6AhfvQKW/RfHR0jaPWgD8lU9RdyjcdUH2rlf5wROQ1HosP2UcovEMjsF6AVEQuaKBREosLIMcLjLcoL/CuJFYRzgucA7Qiai9iRcmVF76IkjFxPUW4wH5T2hLhJe1Wm8LmOFvx1Bc+ipCaxvVX0aKiu7WFjFJQCukD25PEBV9joTHeEglB6S2RUxTGgQzB3b4q0ToliuIgcKiwiCkvcTrCCIsxFXl3D+FsCCScRJzeunoFpRN0nJCXhtUz91BL60RxnfseeiexrlGWGY32Cl5Jbt6+TVFVSOHZ3V6jKMfUErh94xrVaMiZexKef2qDoixZvXCCvY11lpaXSFPB9ddfob+3iT3dZXtvjfHeOq7Yobt5ldHeLr7osn37dXrbI1JhuPr6G2x2Ss6vrvDq3jVudByPPPYYr199leubIy48dB7T3UD4Ec1WxNPPPUdRZFw8HvPc567Q7XZ46P6HuNYxXFvb5Yn77+Hs6hKqqPiJ73uU5WMrmLJinGV0B2M2t3b44us9qkJiR4CXVMLjRIWXEiMinILMR/Rkk9JBbg1jNCMEo3yAkJayGIAzNBPN+dWIE8uChbpGSo/xCSpKieMUr0B5iRWezDgiB00piRNJLYnRUdg+6/Um0hiq3m28t2xs7fD5526yvjXkV37114lrNZryFc6cbBA3lhE+ZuAcsQx0tBUKrKGUFQZHlCQIpRFlhVUBDAkRgonHRcGzr2/zTiVpNdtEkaTVqLHaKnjjjQ1u90uGBaQ6QkeK3AZ6CSEg0jXqSiJ9hRDQUppchrxUXkhi65E6LDFWvXVA9a1XPFuUfE5Ygm2SiRCzD2im9eb2mtmxYNWYWq32N5Sg+N03dQkCcJo5OM2OT+7jJ3rraZz5RNKR+KABmkA5J4Lly08IG/aoOIFnxSmGpcLjyArHH36lw0pb0a5rLp1p8MWXu7zwxohJ9xBCcP6k4oefXAR8SOpbevaGHlPBTr9ES8HiQoLAMzaerPDsDgqqyjPcGDHOShbaMYtNzSi3eKFo1HWILdSSZi0IDXlpadcipJAoHTyBTOkn1jgBcUTeGXJ7zXB1UyK1RgrFYC/D+DEjHWEG1Swo3nlPMcoCk6oIws26DvFTSgqwFZ9d6yAF1M82IXHkZYUvKgaF5WSrhlYh71rUTjBnlkh1FKxWEwq7a5sdnutXbNuS86fbeGPZ6Awp+xafj7l2a5dq2EfECdFwD+FKaLWpti3drqc/zHDVFFRGuM413HiX4ibIxUu4Y2ehHKAbbWSzjVo+AVWJHfbAlmAMlQVTWw6CjfOo7g2S3i1+aHXET77bsPBCh8dqUH/HCsl9F3HHU3RukYIQByrcLDZq3ohxJI46YKE6oohD5x344u/2w9f4bf/Qt5bo9PWX3sBx5oFjtJZrvPjZNRaO1Th+rsnt1/bIRxXLx1vc/87TDHoZw0EWTpqhjLDSxNJzIvJkVYg98pNcSHdq6g8Krkd9mkM5R7R2/2GLyf1rx+oIKRjv5cS1GGM8UnqKbESzobGFYziqiCLNUi3sd8vHmmjBxNMiWHylCvLO5tomZZEzVU5JKSf50Y5o6mHAf4SldAag/DRR9mH/s5B8OhxXjEYp3nv63TCGgYHDIaRDSqgLR5kXNGqe1lJIqC1lCBWQWNa3HJsdx2AsqWtLLRGsdT3jKuTNDPuBm6RckfQzGJeeWFgWi5zrWyXShxinp28meCHoDEqubg1JtEIKQaQkUmheXZdkQ8Xa5hhjBcY4bq2N0GlEXsVcvOcCt24Pee75pxBCcvZMA4gmMU2C7W6Xl672ePDSHrU0jIEQ093FUxnPF57qcHtzwGvXhtjpJk8Yy6k3xOElQEw3wEjsA7M5S/2RU2tmNz3iMd+lzAO0I2bw3U46osIf7yrytgdU42wMtYSaKinLIgSkFg4rVHClcAKEwEtFRIRSnqimiRoxw8EeVWZwUpLYkomXLZYChMAJS2EFi42UfrFHPW0Gtj5T4irDbncQXGBij8BQYRl11xBSEDWbKBc0hEKCd0HQFsITI7DCURUWawxOWqp8jHeGwApksGWO9QKvQxCgReG0QwkLUgVg6EETAieN9yH+wwmc82TjMaNBhlUe5QJFriTkSYobLeJ6iu11aDWaHLvnfpxUCF+DqKLby1i/cRtX5NRbp9jYeC0kn/VtXn7+C2RFzgOPvpNnv/I5fOlZObXFV5/+AspGjLt7vPrqa5RVRK+3yfr1m5Q9Qza8zeuvvsjmnqf7+L088/QzbHYVZ04t8fILL7HV0zz24H30OptgEmqxgLwPNqZZq9HpbFPhWViq8+Kzz2NMTtI8y+c+/0XuWWrS65ymEQnSeoOlhTZLrTZnVxvs9J/lc9ckO7t9mottmseP0d3pYL1H1pvBHUkJGhrqtTqR0tQiSY6mMhWR9NSV44ffd4L7TjRoR4p6Khk6SWZipNZ4HNZJrBeUxlFNhFNpHZEWCOWJpUF7QZn1GeyuUSs2efHKTZ5fqyjUIpcuXeKHHk5412XH6Xvfzx987mVe60bk1qPxJEphK0fhXIjDmmiPHAIrYiILVljqkSSu1xHScmKphoot3Qw2ep4o6bOy2KQsKl69nREvLFCOtzHWo1UNHWmqqkJ5RSk0kQtBx5GKyb2gcDZYgRXEk1gaLwRIT/GNWf+/ZUoPTw8zCfmZbMBwQMg8cBzmrApz5Q5ZUtwpT06/+yOOwdwu5veli5kP4hTUTRsVtqINX3G7GvPqbkXHGXLrefXGiOOPLxNFikuna3z481tcHduZ9Oy9wBBTOkiiSe4hPLUFMdtscZ7+hEVT+IrMVqzvaoQQSA+m8AgZ3JzywqO0oCgVRRkSZVobhKn+wFK1LEJKdkeCk02IlUDIAPxt6dlcG3D7tmNnJ95nJassTgisrMiIDmi5fWmosjLQrStFNbGsOeegMhSZB++wowLhPLvbXV7ZGRPVBKNoAryYsqyFJMOtpBaAr4C1YcbN3YxWInnXUptESjIv2R1Y8nGG7a/hiwqfC8pP/QLRqUv44Q556djtR4wzGdg4hQ3trgyuHIQYiLiF7ca4UQc36CGXjpMsncRs3KC68TJ4F2JJl0/jowi58zqnxmu8v1HyoQtjvucvv4+VyzG9/+7jtK3DlZZq6xYqq8Ie4EWwbsym1J3izZ3KgTcpX5ec8maLwUR0E5NpPas9nXPfxkUI8pEhSiqiRNFcqnPu8ip7t0cUo5C4XfiQLnyKTsXcuQA7RvPP1tv0bQBTYu63ry2hThU5bz6OM3fDg4sbx+87RroQc/PpdRZOtSkzRxRDZ63ifd9zie3rA7761HUWFmv85b/+bhCSY8ebM1KRGSiflGsv32R3s4OckJjcvHaLvLcPJIUIrmf1ZlhPZm6Ch/oz3/XpWM1HOR7+O/s0DfiZeglMGFy9DQyKtdhTi+ogYGMtnLev//J4B+26oZaCsDmQceoYLDanLt2hznbP8/KaDoylRrDUirkxkOwUEi0sCsO1zYI08fRHFa9uDieshMEbwtqE7b0UWykG/QrrArQpC0+vV4ALAElHEf1BcAlOkhIlxrRihZaCXhkYEc+fqofkyirk8PrqK3vs7pV0egWvvTGiqFxQYB16+d8EF2GLMetf/ArPdQc023Ue+6HvJEriA2cexjbzAOnotOxH1/1WL297QKWcQakEmdYDO0xVTRYqjzTBElHiEU6gaxqpYyg9SlQoJ8h9hTSCfOI+I4WbME85LBYpIhCWsyfOQhJzYmWJzdu3GY8DyndSEMvgppNqTewjIq3CfauMMs9YWT6O0hFagJchuWx/PODmi8/jyrCZW2ORcYzXCb4qwOTYxIcYhsoi0zrHj7Wpx4qFpE4lLHnlGWYVvvLExlIGeRAzUe8o6dEOChUoTKUPVOZmPKTMx1Rlxq4Aq2OEh1hHRFGd3fUOC8vH0PUW2+s7YFO0EAy7fZwVCKcCUce4QAhNPhwzHoxQaY2dTofN9XUacYutGzd46cUrRI02z7/yGi+/do16fYkrt2+xudshJ6bX3+Xm+k3GWUrZu83uxut40cZun2K8dQuXNMk661T9HVSSYrMeeW8XGddQRtHd7bEpFFdu7HLlpZc5eXyBleOnyfpdslGfRlzn6vNPQTHi/LGH+eJnX6LsD7nn/AVEKVDErA8Ny80Vzr3j+2ivLiAXVliUYSH9kQ88TLn7Vf6DH3gf3lZoKSZzBCwJUkE+6rPVKbEWfGyDD7MKQnFVZCSjHm3nMK5DvrXJtY8+z7poc+v4Be558DLnVyWL9TrOWk6fe5gvPfUqNwcRFk3pHPHEt8sE4z6x9Ix0oI2NZW2Sv0eS6JRY+UAVrUL+re2+YXmxRqQlg6zEuR7D3KNqmqyvEXIRKSqUCBYqpwqqMgjWAo3HY53Ay5CfS+HBVVTVBMxLRWEtuf12tlCF+B2BoNVuUGQZ4+FwBmb2hfg7wdRdNwo/lQ/8wc3GHyFu7purmCWn9BP/vrnfxCQewR88EYAMz7YztAvFiozIXI7SngfPtamMDHmznJhtbpHWPPTggyjt+f/81jX+2ocWWGoIhPZoPdUABwauX/q9W3QGhr/6oZOsLid4H9ZTsMjIk5d+wvIFMZBXLgR8d2BDhnGTQmCMobKKVzbhahqEfCkdJ5Zi4kjw1a2SKy87xnsCFpOgiVrrB/IOrZDnPFJNaLrxuKoi7wyDAqsWTwQ3MSHe8GAtzjkGt7dQWuFKi62CS05/u49QQaCbxpQJAcNaOYkV8HS2B7i9iiyBl27soDXsdHO6/Yp8b4CbMPB56xHdNVxrEYoM50BHAmlLrKsCqELsu7YJR7X1Rcx2THThAyT3vQ+LpdreRqQLxPc+AdkAc/1l2ree4Vzc48FGxd/66SUevacgsR57aojLHFdv99nbMjz/2sdo/dZT/MXlgu3VE+yd2mNhcXFf6PFTS+qBaf+nVmaxGLOGHFRWfHsWwd7aCCScf2yJRq3BibNLSH3zIKA94GJ18CGMHFzJQ8hC+Pkg6LnzrLf4EA+jnfkyubyWijiK0UlE+1ib3mZGlAbrqtIapUOSYSUFi0t14iSagZUDLpuTNevig+e5+OD52cEL958ln+QdC0urYGtjm1deeDnk/MZhnUcJHxLHTro/XYt0pCdxgPuxWPOi+p2uhXPA8cDUmsSAAVOj1yzlwhwYC3GhMVoCOsL7Fls7jq2d+TuGWMDFFApb0RlmLK8ULLbtTME9HHoGuSczklEGg1FBoidWOxSVge4gIkpSrr6aIQjpJ7KhZe3mCH8y5AWcBqx579ncGrO1lfHOJcVqIvnqhqOWKLbWhygJUWQ5vtrk2Zf7DMdu9vzFNODVv8m7Nttzwjhfu7HJRz59gz/bavKi63Dm3SOOn9QTS8E+XPpmJNgVb/LtrZU/3jXk7Q+o0ho6bdFINLYsgr+Ms7iqwjobMpMTcphktiTPNI2FJSKZoKMIkTFhPbFhsk6SsrqJz773nkG/S5WN8ZWF7AInz5zl9to1+r0+EoWTGi8k2oFQnkpAKhSq2eBYq42QGi8EuXcoNFk2pshL0BG4kLtoOimVEIHaOIloLS8w7vTwRUVbex45s0gjFTSjlMVmSiuJSJIUqw3WVOz2Hd3cMhwN6fQde2PDaJwzrEqMEyGwgkArq4VG6RgnBTqKMcZiBDg/ZjwoGFY5HoPJC+KoRqwU69euo5MYncRsb2xz6txltNZ44Thz7h6cSOjkI+I4QcYpOzsdjCtZjBL2trv0+gMSXeOrz79Gf22dlWMn+MqzV6jHirOrK9y6vU41HpKkio21mwy6t6ktrtDdep3h9hs02sfor12ls3uDZnOJvY0bjHY36GJ45dWbbK/d4NSxJqcvFtx44zpKOhZPXkCWObUkYqFeJ9u+gUKy0r6Pz199CS0Mqy3FS099HpMZltIGf/bdq9x7/DT/4Opvc/nCSRqNOlI3EdogRRwmni9RwiPsiDQSnF6KKA0MxsHC6L0JsQ4RdLtr6O42cWdMe9PyvmMPUD5+P1etZ/lsSonltbVdPv3Ui6xv9hmV0Dh5iWaSEJGDMDCxbioRYUxJhMCUEudLtAYlYoSPQEoEJVlRYDNLmjSIdEQjSVmo6ZB7RjhS6akpTSQVMpbEkWCtn1EYi7SA0iEXiAQnBIn0GGuovMQ4RTNVmNygXElLg0qjP7U14I9eBPXFVWSkePTR+1m/eZPXXniJqeSzr8vdF4a+5lI/03QeqvumyntBa3GR5WPHEXKSsHLyV07asb12m35nlxkym13cYpGc0QmraYt/M1hjWFX88z+4ThIpCmMRRvLAmVPIpRWqfMwHPvjdZHnOhz+yzqDUM2au0L+wURor6WeW73nvKRaWaiACm95U+1s6z7/5XJesCHljvve9J1luCJKoQC9OQaggkhIZO3wu0VqQJoF8wyEZG0HuBcaDGxtMt0TEMvgFjqrQT+0YbfYRUqCbMUJA2RngnUdqQbLcmjHGIQRKCZJYYq1DGrAysAwaE4hFBr0MKQXWmqAcEYGNMO/nYU3znmFvjPCecmRZu7mNihTGgjcOl+cTmUQw4ZQOijgZ4YWkn2n6w0kQtw8a7SkgDjzV4X+z9iVGgw302UdRQiG1RlU5C5sv8Wh5i7/1Vxd5xxNLaOkRowEqH9O/XjJ+9Tm2OhVfWR/SHMIvDyTHexU/UCX8y+e+yNOLt/hzf+lnkFrtu/y9FWFjXxr9YywHXYK+/YHUpEyEVaU1cS2l0UxJ03hiUZmzmtyJj2bfp8qC6eWm5etxnzqyzEu7M3DlDx6XIuSYk5K4rokTTetYSvfmbhCtxT5j3x1WobnYqTtuNZl/S8cWD3ZIwImzqzzw+OXJuHiMtdy8epMqr0Ic4eR07xzX37jBeJjN3XPqggY60kRJYKK8czYdmml+cu4hy8mBb3OgY/r2SAlMrVwHFl+PkJAKzcmFlHHPkg9D3KiU4Jyl1XCBJc+kXN8wRELivcMYQZZBbkxQ0Nh9POMR1JsJx08tBPduJ/dBog9e4M55lDdY6+iNKpyHv/O3fpCrN3b4jX/5zP5zPfhEmJ9t+8NzkN1UEFhqjdPsVorPjCw7TrL1W1/g/MVVfuCH3hX6NLU6H/bEeIvlT1Gv83WXtz2gslWJdH06Y0eZj3AeqqoE6yYvW3Cbk5M8KUtLxzhx/jxWQGkNo2xEZXIUcTCTKoGtXIh7QiE1lNbiRY4SguFgh/XbFuIGcd1hijKYvIVC6RglJAJHSUWqm4HVC0Gel5SmxJgMsAjnQGmErpBOTujVNU4ohFAkScqZpSUKBVeG24hYcXq1yfG6plVrktRSmpEmiRVWSogl9wiBEgmpAOkkGZrMebLxiJ2RYac74nZ/wF5nQKc3pDPKGYwyHAKhQs4mKcArhRbgjARdQ+kIpwTGOUbZCD0estvp4rxD++CjL5UmSmpUwwbHVs+goxTvFZcvPYpLavRzh9BNhqSUW3vsbXUZiyZbw5u8ceMKqysFUbLGjdu3OX484rmXX2Rne50TcS3QEu/tkqQN1jZv0ulsUU8VW5uvsrV9A+cqXnpR0tm4waB7gs3BmCtX3+DeE6vsDiv2dm6xurzA9sY6vqyImk3yqiDPuwilaMXw3LPPknd7RP2bfPGU5sbxFbp5jY9/+gX6eYtXXrzB9q3bRKLifd/3fhQFrhphTYmxkqosMKYgUjVKV6D9mGqcsbPV5dmnX2GrK7j3wmU++L5V5GiEjT3Li3V0a4nnbgz45Y99ga2rV1haXEL7mNhVaFkRe41zjsJUFE4QSwVRAyksSkUIV+FLy7gq0cYSGU1Z0yymDZqRpNWOWIhSjINhFUgIoonb4gKWY3nFZnfMcFyhkRAlqFRhvaSqDMZKYqlDrIsQSBvk3GHpgwOW9wwqR8q3M6ACZyqQoHQ0Iam5s7yZkvctl6POnwnmgvbiEhfvewCEQko5o70ONQL7Xjbs7zOJzbxaAoHIslbc00yJRmGD+x7VYGAcn8+HfO9Kg//yr3yIP5ArjEYj6mmKUorv/I7vY70QbBSTHZ19QcXjWDouOL6qGeQhkbXAhvlgBYOR54VrJaPMISTk9Ekjz49+Z8qJJTXbbL319DNJZaCyM4MJeMHraxl56XBCMhw28MYh8uBdgLV4BN4Iqt0RwnsaqoXQUHYyvAWpHbpVo+jnVJ2Qwydpx3CyjfOefDgMFrVIIdIG3luKIkcKGTTmUiKjkM1bWh8AFQQg4jymLNla64DWxDoEk1eFmXumk/HCg5BEGlZbJV2nAzD1kGAR3iOncXJ4wODybYQZUH/kHaTtY6x+5d/yg40eP/Sg4aFLEYt/832IlR+huPJJtv4fv8YfvjDkV7YKrBNsesGTTvCT2lN6z1Ur+E+6CeLMZd752CM8dP9FfvP3Po4AHrzv0mSqzehUvv55+k0th4S5Ofnu272ExKdhH98neQgakZBsd6qSubPDRw/7PiHOW7j717zaHZfygJjmhQtxQYKJzCQkqMBkOgV4YvZlrh9TS8VhBdL0BO/nejxVQgRX3Vrt4Hr78BOPTJo1sVpOlrlTF85gqmrf7jRHAnTr+m2uvX5j+gtCBmbbQFAREhtHsZqaxoL3gBBEOsR8TVt3GGLdbRSPtKTMEjRpvAupXsJqGoW8XAJqtRQpLVaEHIOVtez1DOMxFKVn6s44nS9SSpSa5IGYgVYxG0fhBREhuswJT6vZ5C/91Pfw4Y+/EADVFOFOn4u/o/FhrGevoydRwR288uCcodlUvPPdJ+l0DYMbOzyyoti6eZuyfIxaup+P7cCl57587aXkG3z5/xSQ2NseUJVY8nGOkBIvJM4UgZ56OkG8D+DFhY0SPL2dPSKd4GRJJDSq3iap1Si9oaE0JisCqIk1g+EQ5UHFMd5adBQTRYrcFjTrbZrH25iqJC+CxtOZCuU83kjISmyUIKIISwmVndCgmhDvZS0SgfMOJVWwQhBIJlIluP/EAq2Li6xtd2glEZdW6yw2WsTSA5JcBDYo4WMilVDaGnUZFhCDoKEc9VhhFxdYcRH3ZaDrChUL9jLD5tCiqiHjccXNnR5r2x02u136vSHjLEdZi6gqnHNIobEInFCUwge6YR9yQ1VOYKVDlAXdytDb61L4kA/DOUuqNCpJ0WkdOxjTrjVZPnEPol7HCMfyynniRot+vwdCQRTR63YwZUksJJ2dbcajHoWtuH7zOoPtNcximzfeGDLc3WWx1ubG2nU622skjQa5gtHeJtupwPX69Hdu0tQlN69VDHeu05In6a29hh0PSHTE+rWXEUWXbuc2e1svUuSbdIeWUdbj0196BmElt6/f4rlnvsy99xzn1977P6OVIh8PsTZDqAY23yXPRkT1ZcrhLr3tDT75/BY3h5oz5x/hyfeucmE5xvkSV8UsXLoHW/W5XbX5zNYuz+8aWlmJ1hk1kzGOtsl6exBFNNsrCNUgNSUZPjxzFyxhyk2YLXVKLBVaSaS11OMY56ByklKDVQ7rBCqGUVbivCYzjtx4Sh8xdorCQRwpRlWB9goZaYx3WBwFIbgWKXDeopwDLbFSoZ0hqoo/rSXgj1w8MOrtsnBslYcefYgqz3j1q38894G57eOIPcRaQ5EXDAfZBLxAEmvSJEUKwYP3Pcjli+f4g9//CPdbR0dYNifXjAhM21EUXOyklzxUT9m1lqerMQtSoZVGemjWG4Cnlta458LFiUDFHQKRBxYWTrA36NIZ7dP8TgFgt+hTlLfweLyTvHClR6w9P/xkbUooD17w/I2c3/rYLkoJnA9xixKo1xR//vuOcyIOLqrq1QEM6tgMhPT4ygahTvhA2iMVZb8Mml8jZslHq8xiRwaTB/cWWRiKvMJ7KHYyzNig6hHpmQQ7Lhivd5gKKUIpdCMiXm3gSxM8EexEOy4Ezk3a4D3FMA+eDONiLhHuBCLt3UTYElkXDDuafKwRVJxU8HeaMSdSxcJxgZAWJMjlGk5bxhV07b8lvjbi/T+5yJl7GiTXBhit8DyML3Oyndf4bz/X5am+5bKEe7XgWSH5qo3JrGUgDFbCdV/jB554Dz/+k9+PEpLXr90ADw/ef8+h6XYXyerflz9CmQKn8C454YMbuLP7Vdx+zfnx/+YInXcCgFneoMOnivk1yM+MVWFKB+VIUOYIhHSzvs3xjh5h6zhk8Tpwv6/V48Orzr7CZaoEOHn2xKzavsda+HDi3Cne8eQTE+r38F5LIbDWIYRg49YuN6+uobSc5cxz3rGxfhtny1l/5CSNwj6JYljn4jhG7ifb24deYq4Z81atOx5VUHB54XFO4X24llIRp85AWQpu3FAMRtn+iIrJiE8oXoUIAGoaUru/+kwBmAARLIxIefc33N/5UUlPO7acOl7nyRM1nr/eZ03W+Jt/47t473vO8t53/w3+2a99hf/XP/4IaXuVtNzh+vUNzp49QbORcvf15E9yjfnjv9fbHlApFVGUOUkS4+PgtuGqHOn2Vy7vLcgg/OVVhR+PGYoBVjqk1LQabXQcUTMl7bRGupqQJCnjYowRMC4MUijieop3iqzIaS0ssDPsQyY5f/ICvp4iUPgio9frgHFEOmbQ6xInnrwsgjBtDVhBVZUIr1EILBVOhVw3kZIUwlOL65yo19nq9fEiIpKaiAhbVWgdQSwRVpGmTbQUtNMEYxXKS7wvZ/EEgzJCRkHLYVLB2IIbC8ZVIH6o11rQ8Ny3fC9nLjo6JuRNGOZDstIwGvfJhwPy8YDBoMtwPEBkJVWRUxYFFcEcr4XGSrDOThYzHV56KUGEOJvRsI+iR3f3Jr6yGKmIVITSCUnSoVFvsHLiAmmUkB47SXthgUb7GFYLmuUyzXqdjbUtrPc4qRnsblFUPYys6Hc6VL1dhr09bNkjrgYkHEd5w7FU4k1Jf3uDUX+b0VKM2MrJRz288HRuX6XYHVLkfSIsH/iu9/C//Mpv8OD9D/Iz/+uf5td/9Z/z5/78j/OFL32G2zsDPvL5lzHWstyqIXAU5TaLaXDLc5u3+MJXb3KjO+aRR57gR+85TkN6GlrQSATdvR2Wjp8gqdWwScxgpyBWCiljxrlhsZ7Ru/ISWXaZU6dO8+g9Z1g9dZqnXtsk9wWlEdSQCBlRVAVFVWCFJ5E1isiTe83xpuLsaooSJZUDkxds7ljuPbXIQiNiywmq0pN6TyuO8KlHuoqscgzKCu3AOhNS48jp6q3xAiLpMSLIm7W4hi8tVQTSfTvHUIV4tFMXz/D9f+YHGezu8JnpbjlLivKNXvlrHQvxb0HrKBiPRqzfeIP2ymmSpAY+5Bg5e2YVAIlge3MbJSX3eMWp1WV8EmFu3+Y7lefH3rdI5Bxyw/LeqMZ3Hlvk2SJHD/aoCYGwQVjy4nAr7uzjdItcWFhmYWH5QL1p1WZjyDve+TjeuZnmWirBjX7O+mjCHIhifTtlb7RLVU6A90QT265F++55Dux4D8YedDKZdw5khFcJyASUoNyt9oUIHK5yZDd6QQvuHQiFKx1VLwchcaUNHnYWjHM4GwDT1DCI9zgTkoi6UQGlxXRCQhy9VEO16zgfBKJqZ4jNCkQ5nrhQB1c+ELi4jjQKZIeldsXm5JVoSckHTrQ5flJy9idKROywSOzCCXwzgpMX8Vbhf+UPUD/z01Tdgs5v/zrjLKce/TKqKuis9flq4elqxU+nEe9Wln9UwT/xkuLcKf7v/9u/iK7X+MJzr/HRp57jd/9PX0VHmjyruLhU2392/778MReBKR3l2JJHOZ2dEWU58ePyUxfQqbZXzLn1vRWAK2bz9cCxI0qrHXP/w6szN73pHcDPKUQmZuIJvb5fThm5CXvoxIITViU/wwvzgHH+7m+h5XNtOKrc5ZcJqDgAAqbW7bkx01oTRVMviXlFRyiXHqxz6cFz+5edxEnu7nYoizIo3j0MhiO2N7fm7uex1rN5cxM1GYmQQ2sfqUqhqDeSCTnHQfR6hzFwmuiJqdVOzNrjOLrs1zmMjifH/fyxCdesn6/PXabXdH8TnK97/uP7JO//mYf48Bc2eObpTYR2fPxTX+WDH7iPD//h83z8E8/x2GPL/OD3X2Jja4Vf+KWn+A9/6rtpNk4eGm3uUMzNj8XRc+Uw6v8aM+qovvwJlLc9oKrXGhSDIRaDMQZKh9YxU4Ox8AJHgdARwkucrSgENGoJSmissESxxAqD9JbSGYRT5MMhmS2IE403liRKkc06416PqLaITlKOpynWhhxHK3GdKIl4Y/M6g84u1lmUlLgiZzC0GOsonQFjiIRAC49WAu0llZZImFiBJCJJGPmK57e3ON9OiaShkUQsNiOMrciIsSYiTSChQOg6SnicFvSMwDhFIiR9o5AyQsuYzCpUpAgZYqGZaIR05EZRE5DjMMHhF+0stahOrV6j2T4ZXHC1QghJkmpq3hGLgn4+phgNGXV22N7bY7ezx2i0Rz4oKPIC5SzCgpIK5wyRivBUaBljvUHJCCegsgXlOCcbd3ETtwjnJi5l6jq1RpNaUqMa9Dh+7DQnj58krjdxwiOjGKlTdnf2KPKCrvG88cZN8mGfgVpkb3uLzuY6q5fuw2djuttr1NKELJZoAafOnmBvsEevGFH6CoFka2cNaxxpZFhtSrytWGpp4ggQiiRNSNMUa0G64PI5okVVGtZ2uvzBH36Fxx9/iO9+6Dj1Zp3ecEgsCkbjIcPBOgurSxhbgozpFYayrKjHEerYSVRjkbh+nfP3XeDyxcssRNCqKyIzIC0KJAkmViEjetpAuxScwaGQ3qJiSek1V9Yy4sjRriseON1CKQ8S1ndKGg3FQqoYlTH9ccYgL4iThKgoEFbghEMqSWYczSQJ+bkmC+Q0thBtqbykFgEeRu7be6lx1jPYG5MPxxR5AUwdK+Y3pG+uf5IAoijiPe9/klq9xjivGA3HgKfVahDFCUIIGvVgnZqdJwPLYyIl91x+CHdqlau/+W942Enefb7FeCxIhOTxWo37GwlPF2OkgEiAsg7kdCOf688R+9H+ocOgckqcAa1Wkx/5ke8LRyceOB4/iUudSj6Ckxctu4OY/mCEFGLiFgWRMmz0PPHAYqwgKzJE1kMi56jjBRfuu4/haMTW9l4ww4kInx5HSYvP+3hbTIQ/Cc1VzCjFjnO8FAhTgRC4zFOu70BpwU6sU1MZtfK4QYUvfWCGtRNR0gSFERN6d+8I2gQz8VucnwdJCz9x98oqT16FhLxCwaVLx2muauz7L6DaEeXY88b/+dMs1yQL/7cPQRThoj9ERJcoB5vcfrWgV8DrV67xKVOyh+DepUXiUcm/qzy/L2MW3/8oP96qc+P2Fr/94U/zf/m7f4m0fYzX7/kzdPZqxFZjrr2IuPYHcw/vjz5vv6nlbYbyBILxoERFiqoq6O9kjHoFQgSLgTMea2yoeVgCvftF54o/tPwcDcQWFhPe9b6T+yQEBADhnZt73T3gcN5jneVmXzLqmX1rCxMpSgiCuD+xgswg1vQa00Z6jhKb34yu/y3PxiOHZ38g7uaqd7fr+4kL4srK0gF8ehK474F7D1zNGMu1165jK8s0ncbUou+8Jx/nXH/t2hzQvRugEoEIR09i0fx0W/GTkMpDrT30dR+uidnaIybzaIqpAqW5xx+aFwGHzwOzaXPDiTfGkl+46Xk8K9kbwX33H+OJB07w4qvX+C/+3i8zHI/5ke+9yLvec5per+DLT29TFW7CDMsdiaXfjNfv7qqDb/3F4NtbynkLJev1ArFDVSG8R2kdJp6fLiAC6Rze+JDPxTgQFmEFMo1wIsJ5SRQlyMjSkFEIDPSOSEZUyqJSRVJrsbh6nPjEaRqtRZZbLbzyZP0+W9tdXt9aQyvNYNDHlTkDZ/GmCgxteJzw1JXECk0zTZEexr0A2AorUF6gVIhRMEXB6aUT/MST91COMz7yeU0kE6zTqDilJh2Vd1ifsONqxDZmkBlSKTFouqUmEpC7CCsCS5xEUFqPFRBJFfJvmQhjBAhH6TwNJcmUInOWfuFRRYmQEicMSZpSrzeJMRyvx6wurVA4RV55MqOxFgoqRnZMXliqQY/+uEOvs4Hp9yj6XbrdPfLxGCpDJSu0E1ifY52YmdalCNnKnbQ4AhjLsiHjcY9+T+GNxRiP1ZJIC+pxjaqXE7dqrJy8iAdWVk9StpdJGi3kcIBqNGnEKZtbG9iyJE0lvW4XZyqW6jFZz1COM/CCKILlOCRTbCZwqulpUHKpVdFOJPVU8+T5hHotYjDIQaQM+30EObWTCY+ePUnefyf3nTlJrD1vbPW4NrR0r70C2ZiLi1BEW9xwx3BRzNbQU7gErdsMh5ZTbcsP/NSfY+n0Ja6/8hKjOtR6DUbDjBuvX+Xk5UdICsM430FFdZySREKRSk9lDFJpsqKgoKAWRVQ24bWdguPtiFhbYh0YLHuZ4KXbIwZ5RakF4yyASes1SjiEMCRSUYlAWiKtwJkC64J7hBOOSEPlHd4K9F31a98OxeOtpXt7DfmpT6Nu3EIIwfHjx3nk0Yf5zKc+S1kW++4zky1BHLpGKHeJdjisVZ4oXZ2Hra0d2u02T77/3ZOk5BzMszK3We0bzDyRh9g6IjwKSIVHKIHQElDEkx04n1CrazHFhGLWjPnyZtvZ3fp6QHiYfBVCTNyr90ukND/6Iz+8X39yQWMs/X6PanLyB35ghDVuX6Dznv5wiI4Ur792le2bexNJRCLyDovHVxnbPsV4NBt5ETdAaMAF8GVMGG8jcdVknk4Ys3AVFHt4u4oZ23CaL8FUIGN8afHZJAGxsohxHzEah/MmrlKzDnkJHmIpyEvHuAyuXrn1bK51kWNNcn0Jf6GJHUT0blc0UgmlwDtFcQ3UL/wqw+0Bv9oteM4Jnisr/sOG5T9paP6vvZznS3hBOBZrKf/F9/8A7z/WIBvt8vprG3zkU1f4Rz//Efrv/gtUlx5n+PJTnFAFDz708Nd8om9WDs/no878WnXeyjXeFsV7knpEYzHBVjneO6SUxElMEkfU6/HMIj05Ye7kb1RRc1hEFWysDfm1X3hhZo2aLidTK1WQrR3TOCWP59jDp1GLSagnpnXdzC4jZmvfIQXLrCsH+/RWWPC/Vo+P+l0cOPjmgvuRX+Z0ZFN8esddAwIBQGvF5Qcvzc6Zh5N4yIsS6wSmnKwJYgryYBqbxuRya1c3GQ3K2bUcHm+hKDzD/hGxux6mls3Jx0nDp6BRzD2Xuf1hir5m0Hn2QA8AqXBAYLxgYxxx+0aX7Y0hr7xSsrZ+g0cfrXH2bJ3v/e53UE8inn3mGq9f32Nrd0xZKITS+wB9boy9OBiP9i2mxvmGy9seUDnrSHSCjjWjsmQxbdIddDDWoZwEHwKokR6nPUYIIge5ydClBSewY0UeZzTilLIREUURzaTOSrNJ3F5AIxBeonRgiiqto9vtU45zXGzZ2lujKnOElwQa3UDUoDygNUo6Eq2IpKCVRsQ6oqZgbR3qaUQ51lRCUIlAbS5ERFOnrOgancjgcIhIo+p1KlsgVIoyBh05vLCBGMFH7NoQY2A8VD6YwROtqLykESuEdLQSxbBQREIAlkzosOArSz8vqUeWymSUKsHoikgkVEKhtQqsO6LGnhFkfUmkHAZB6TVG5dRUQmIi0khQpYs05D1cuGzRVpJISWlz8mKAKYbkgy7Dzh69zjadfo/ezi7ZsEdR5JMYIYnCYQSkPsZ4QyU9Wmri2OG0QkgY2QJnKwZbXSoMSEnNK0oF0Y3rLNQXOLa4QmVLTl08x9KJVWrNFpk16GrMaJyFQHEJsVNoIfEe0kgRx3VuXlujtrCMPn2ZnISldhu1dBGvPWk0xJclaSPFeIESYPKSdz72MBGWTz39AutqkSJZZH1jxIIquXisho1rPN+pwtg7yZIteHA14rvf+100pUGn0GjFtB86Q6IdV2/uUI132bj1Es3jJ0nrbRAgncGqFOcNHo2M6hRFiZSWNNI0ahErzYjSCLJKs5dZ2klCWRpu7IzpjTLGuSUvS5ROcb5Cy4LCQkzIAq+8AlNR4im8IYmDdsxWijLPiaXEas0wM1/rVf3WLRPA0ZCC9zjB5yoPSN77nsf4b/7ef8qPfOgZdvcC2cG+7DLnRx8uMtujdBRTS2uzXe2gQnmaFNFz4uQxms0mCEGSJmgdXHMPuIWwv0lO98HgcjIJHEcgvAr3lQLFxE1HCGIEUof8YeCJRIh/87OrHdbu3qldvvPbfDkig8ibCFFy5mq0f34cRayurM6Em9nnaWs89AcjdnZ3WV5sc/HimUDhLIJLc3NpiZdf7FBQToCWQIxvEdkG5WgPITRCKEAioxTbuhDG0016bXLor0HSxssIxgN8bx0RNRCtk9iRxY1zvFDBFarygELYcjZe0yc1FVqkFCy2PI0RIDzrxvPTL9zkbzQS/urPdnGpJ7OKre2MYyfqwWtAeMotwWeff5oXS8cVZ9j1kqEXxEIgtcN4yf33nOWv/qXv5dyZJX7jdz/Npz/7Ku+59wLHzx3n2d11huMSv3EN4Qz2qX/J/U8+zuULT8y18xuAMgeE0aPnyFGnvFmNt4uANV+iRHDufAsdK/JigMMx6uZI5VBRjtQlRVYe6vzhUQpaj0MZEw7VfzN4Gn43RtDrlXd5k/1sHZl9R7BcebT34PXkaFgjJARgMAshmru/OHjN8Ed8renxNXs039q3BDPndERveW59rYpH0IuL2b/7yCVNE554/6Pc0W0xV9MD3nPz1CZ7OyOs9Rjr6HaHPPW51zhzdoFaahhl9mDDPJRFxdU3Ntnd7SFlWGecCxNEAWo65gQrunOeWqrQkcCU034Iji1ovvvhFi/czLjnvgvoNOajH/0qauIqaY1hc7Oil0nqTcGf+eHz/IUfu4zD8aUvX+fazQ67nSHjsWX9eoa1U0uYvGOcpl0+Ynb/MZW3ti79UcvbHlDFSiMiSWUNsa4Rtc/SlnVkOcRUBYN8jBAqxDSLCKkUSkRIGSOEQscRMklpNZrE9Qa1Rp1YQk0lSDR2bCikDYx8RuBtRWU8xWgIFHS2tqnKoN2PhKP0gkgoEi2ocMRSkcYRHkcaCVbadVpRjDLVTJsZaYFDU020/B5LGimaccS4DEkA66nmtPQMvUJGnjKJUSJF6BqRFESUtIwijgTDCogiSldSeU2kNImQlD64xCSRpy09zke0U4HEsl14irGgbzyOGqmMMMKTWZBRjPIOby0WT+kl3mbB2qEjvCiIdVh86jomtw4ZgfYW5RRl5SDyxFqj9QmoryKWFf6iDVnVkRSVpTQZRd5h3Bsy6Gww6G/R3dkj7/YYjfuU+RhLiUUTK4XHEUmFR6C0mrDeQSwkifeBlXDUpT+syKsKay3a+5BUD0VSi8nzgvbSCo8tneHVN9YZjUY882qX3Aj6RvG7n32acbTKWC9jvCSTNfJoAac1RXQMa3JMmeOLHqkZUMiYtZuvcM/FC+xsbrE53KOK23Q2Njhzqkbel/zORz7NA9//k2x0upwdjrj3+qs8cPksD9xziigqaSQVmVtglMa8sbbDwmqDlXofbyOiSEEkwSuE1kRopPe4bIystdG1FINAxpLSC24NPOdXJcpXCMKzyCtPI1bESmEiwWI9obQe14jIcsN2d4SV4K2iNAWJUsRSoqTE2pBfRwKVVqgJZfTUsvLtXHLr+MXPfpHnbt9EIFBCIMw8+cCk3LFTTFWe4e/KyjHe8cS7A5HB3MYrZ8QPod7xYwssLDZme5FUk0DiqUvG5J9ZAPL0nwmzppgGXxPie4QA5TzCh3u1hKe1ElGue+rACeCkGpFgKdiPrbhTsjgMtI6u5o86eHhM7vJ1evDANjjp52H63VarTqtZ48K5M8wIqCdjWFWGdrNJWRZIAUJIpNRs73SpzOrkguHCzsPNW9epynxCdBEsaVFNkHffACHBVgjnwQcPA7yBcie4bKkUX18GHSG8OdR3P2uTEB7rFcZF4CucE6xZSa/0ZDsVTnosllU8qfMIa0DFYCS/1614oaj4z5c8v9EXPO8jfjFL+XhzCX8i4vSZk9xz+UFOHDvJd/3wffSWNvnkRz5C3SxA62F4+CGq9eeIrn2eD7znES6cP3voiYm7fn2r5bDo4u/6yzd23W/XomPByvEkJLPOHe/67vu48uwm6zfXOXO2SZIoRsNtjMkPWA9mFo3ZAByh8v+6yj4UOVrM5eCjmrjxaREsrFJM1nI/pYNQQckzm99BJpnRp8+u4b+ORz9f0d/ltIN19o+KO2JAv7ll7sW4W38OkW8chrTzR+bICDl3+SRn7vVceWmL9bU+g8xSOkuUCJT2aGFoRNArFQL44HvP8sADK3z+C6/yAx98mP/mv/pxhqOC//Eff4zRuJo8HRBeoYWhLkr6mxu898E273lwkWdf6KCEwyFII1hq5dx7TvFf/Ocf4vS95/jEJ5/n+EKdV17f4L/+2X/FLz5dYYXhP/jxS/yZ77/I9dtdnnnuJmsbAyyS11/N2dk01OoJ73rfcRYXG0ctBHeM4+Fh/JOBP9/88rYHVF5qkqjOycsPMxqP6HR6CBqUw01wjnqzhUoTlIxCDFCk0FLjpUZpjfYOoWOElxR5hTR9HJqRKBBKI3yBlGCEQhBY1LRU+KrggUfeRbd3mysvPY+zlth5FtKYeiOmdJaa0qRaIoVnoRbjnedUO2WlnrLZHeKUYKXZYDgchvwlhcXJEKvUSmNqtRg5UkilUR5GOJLEE8Xgywpvw6afqQYDFEiDqyJKIanj8EJSygghJakMMRfGWmIh2KwEOEtmHJn1OKvZqwrqCHIJzpUYHVNJqAlBhSSKY7wIWqwoUkRa47XAeocznkoKIiFQTuIVJELilcArRSoVWEmJC+xB3lL3MDBQU4pICbxqkaYtGm3JmbOPIpQDFTO2BVk2osgGqFGf3X6HqrfD9u4m1aiDGWUMB31MlVPZ4M5gjEE4jxAaP3H5FM5jpEU5gfUlqgRvJTdu3KYzKFBeU7mKZ15+AVyEQvKe9z7OHz59k0U5oCZznJT0DSQisDNCDDoG3SKmz+7mBs988UWsS8lyy6rqIoev0PYDfEezJU7xF77vSb70zO+x8dIVHnjy+7hFRb1zg/ajZ1GqhiOhNyjojjwbu4bf+d2P8NLrLxEldbRuoFQKWmFdyOMjhSRt1QIxROmpRQKf5/RdxHI7JdWSYy2NsZLbu2OWGjFKQi2OKFzFRneMEzAuMmpxExFFuMqhREikmlclSZTgvMIrjysNKGiqGkIrvC+JvP2a7+q3bPECqWI+9Nd+hn/5yT/gys3bCK+ChRt/wKpzOBy73mzRarXCrz6wi9ZqDba2tif63XlXSMHSyipKaaJIo5OQvHYWx8NEWJjmKzq0QQnCzuxcSAbuAS9hGjskAeFAlhaJwziQeyOMd6wCF7wjyTJ0E4qZA/+bDMuBe+8fORp+zde7+9HD5SgN5ixpsg9a8pCDS6DVnUKMTGLe/94nDhw31vLc81coSzOzw3nvqCpDr7ONidUkgFyyuLhAvV7jpedfYUqnDArKAlHuhfY4AziEbkC6wIws41AfhC0RtqCbeTYHEYWJ8KJCCo9G8m+N4+lBBnjuF4L/qJkgMsver36eqN3E5J7cwY6TfCQzvFQqvBX82E98kP/qf/8fUeYVG+sDdsfwzz+7y6c++lH2en3cyQfwK2fINl6D4RZytE49TXj88ceopemh5/FHEWXmJMM5APlWBP+7CVR3P/DtV8YDeOqzHQTQXIr4QC1Fa8X6zZLN23u0FxPuvXeBqgrxSDNR88hHEtaaO8HqHRXvcvyoOv7Qt4MWGF9W5B2D1BXeikCg5aPQUjd5k0RokzEWn3uqytKoJ0gt+YYwzvwL/yZ19hPuTg/dfe4daaX6eqf7nGbnKIPc4XvsuzfeHRpOYaNzji9//mW0rTBFyaVjCWo4piYqImk5Vo/oFYQ0JTrC+ZhxVvL6Gx2MtSwsxCgt99c2AC9430LFB9tb/MHf+4ekcczZPcs7TlkuxCCdZ+RKXrzh2C00N7aHnLxQ8dADp+j1evzTX/o9lpYF3/Wdp3nXO1bQkeLDH3+Jzc6I3l7B1nrFzo5lOLJICfc+uMST33EP9Xr6Vpf6t0V52wOquJ4S149TRvejF4ZU65/g5KljDF0dLWocu3gOqYN1JTaSvHLE0mGswVmPEBIVqxB34BzKGkblAKEjYp3O8u9ULscTI9wIn5U0GjUG21uMihGR9DhnaNRrnGo1EIkl9zF16xHW42NJO/JENgoxDy4QVEg0FZ4Sh1TQqKXk3lPlip6VvLJjGfcclYVKxlRWhgSupSOrKqKojtQJpSlR1PEq5HlxUjC2ish7asqSl5bNwpMT3GSiGEonsKVD6hBjljsTjPvSU5tYs7BQl5JIQqQUVBYrHZEW5NaTC4O2AbBIoShlhfMVStaorEdFArxCQ3BBMR4VSRwSLcFiKIuKqrAoAWktBhfizaxzaCvoVzmNKKHWTHFJk3j1PKe9oHA50gms9yArhsMB5bjHuN9hc+Mmo70dxv09Rnu7DIaTRKElKBfi0Q0O6x15WTIqS6TwgVLVaRrtBnlmccYQGYOKY8q8j/IlSkmKsgrtJAi+zgS3CKMto+GAT3/5Rc7dfy/LTc13vee7uHBc8YWP/T6vXN/liYcegKzkAx/4Pj70oz/GjdducfP6VYpBnSRNcc5y7cZtNnsFX/rydX7rt3+H/qiDE5603qJKYqyKgmVqkhtMypDwz3uNlIbBYECceoS0pLoOlWenX9EZWAphQ94PF2h9y6qgMhVOaRpJSj4uw/UmSU9L74glVLYEIqTzDEyJsoa6TvBe4mwQYr9di5QhyfWxU5do175CLGp4oRBeYK1FCo1W8az+lDpcCDh//gKPPP745BePMZYsK+l0ehNihpDawDlHFMecv3iBSGu0EsTxfmD6/EYtpD9SYAgJLsXM1aIUjjiNiSY0vxKBdEBeIbzDOke/aXn3/Zp/u+b4f/d6HH+1S/WEAMlbEGL3EdcRzn0Hq82fccemehiIHa21PHQp5l2fDoiKh4bmsGeOVoqHHrgXNyWTmNxMAO971yNIOdWuhzw4o3HGpXvOT54XzAXLYSrLlSuvIAVcu7WNGGyEa1XZPr7wBDbMcghVzu7Ys9lRlCYMshaCS1LQd5YXraUEbgnJvWPLRpHR/tWnOVOPeF894YKM+U2T84uDBCESdCK5cu0WP/vf/xLDLKPIK5onLpAdv583XvgipqqIvuNJxukiBTXOim1+8M//EHEckSbJmws4X5fwc8Tzn/I3/xEuPU+i+e0ui4kZa5/HWccXPnGVrfVBYJTD0WprLt+3wvWrA0ZDEyDTkS/MvGZ/H20dfjdmE/uP1mqmYvnVZ9bxCBYvLFINKrK9Ia3VBOElL33uFsaG2MbhsOAPP/wqo1HOzZtd/uJfeSfnLqy+qX7GH/5yyCrn5ysdHo+vtU69RSP5m9U90pI3rzyYB3Rivv4dB+4wMM53yznPeFgw6I85f7pOrwNvvJEjpcNawemmJpEaP0k60Rk61ncNO52K3/3YVUbDLu98YgXnAjzrlY41H3h0to3gs90I060w3mA8vO49zyhJJARSeB45t8oH33mBhYWYf/fhL/Jvf/MTrG0NeeL+Jd7x6AOcPtnkhRe3eem1NXqDnLJUvPFaQa9jccKhtOf85RYrq012t8acOLHMLLfdofF+M/fib9d3/W0PqB69+CjRQo3PPf95Eq1oJpblNCaLF1g9f46TK4s4aymtQSlFZA2ytOS2QlqLlzFCeLzwSOdwNiKJYrwQGGPIjcfYEmkMpR0SCUO7VsMXfa699lWcGVP6inaakkQCpzxaKGo+xBcl0pFGHmEEaexp1QTG5gjrsEDuJF6kxDpFJquo2DDs7JGVZhJLEeE85F5zOw9Wk0xGIFPSUhBpMCoAkayMKAk5CJy1SKmJE/CVJI0sWhMSCFuB9QoZhQSVldf0jMc5R24MWkpy50NSS2sQsSTPDDUt8YnAI/FFhagEWhm8UGgtMVYxkAZts+DyqOpI66msR2pJYR3SFMgophQWKQSJDvkdKgSZscRKBUbGCHILsfCMsoxmLQnLvhBYPLmIiaQLfUHQWDrJ6vGLVNmYyw+/H2cVUluqwRZXvvIJdNFnu9PBu5Lu3jad3Q6jwlLYCmchrdVJ0jqJ8bzvve/iC1+6gtQKudCgUnuUVRWeh4wpK4PwHudDrIp3wTJRmoKqrLh83zmWd/uM19dpfOc7aTYWOX3+BBcffYKxP4YbKXSV06otMhx1ePTh87SXj/Hqq9eJmy02ti0//4u/yUuvv0xVWUpTUpYjFpZWiJ1BVCVlOSRWCc6OkHENQ40kjmlqxWJqGVeWc6eXEBZu7w04d7zGPSfqKAneSTb6FSaHs8cWWGgU5KUlyyxVnE/mjsDLCO1D4KwWUOQD4jilETWpvMf6oNUMi6N8s9f0W7r8w//x77O00Gb52Al++B1/l2w8DgJQo46Kl/iH//DvY6xnQjsHUtBs1KglCVGiqdXTYHUVYuJ2NgkinrjmTS1OUgiSNN1P2Cv8IWaniY1q4l2znyhzAmo8dLsD/sHP/TxChBxUH/zxD6C2e7xEeDcQjsJXKAX/qsrZeLnHX378DFG0x5ZQIPeT7b7prjaTIQ5JBXCH/HDHqYd/vEOdOw+wjmiEn/89fBJHCe5iv+5hDXGjls4FcB/uwNwR72m3mjz88IOH6gURvyxKtDIsLra48eu/jR9v7HeotRg+9feC8n60Da5CKMWVzYRxJcBLpIAFrSmdILUwxrMLfDIv+ZhzvCuOEHnJo/U29zYTzmjBX//bf43zZ5awZU6Z5ZSDnEF/wLOv3eC3fvv3aFweoh/76yg8eusV1O3PEQ93WDyxwMrKElL+SYos3+C9/Jt+/bYrx081efjRE9TragJ/PKeOp5jHlimLEmsNN29tc/mBFtwnEd5TVZ6XX+iR5wct2ftKiH3twR322fkD/tBvb6FM35mppWqqTBBC4Z3AmYlhSmrWb3Qn5yhGI8NnPnETpEBpwXhUztow//Ycfp4HDHET08qRxqm5JUfMH7izB3e//pudBne6cR91/txxMWedO3DdSdLcA7B31i9x4CIe2Fjf41f/2WfIspxuN6csPOMi1JVCooSmMxdmt7GTYeQQISV5XtDd7tHv1yc5CgWvjOCVyVx4LYu4bgWrx2soJZDSTxIDg1agpeeXXtzkbz52llc/+jy/+C9+n3vOtvmP/+I7OHu6ySuvbPHcS3tcudLl9tqY3R3H7o6hMobmouPifTWOHU84fW6Vy/fdTxJHE0v/neUbitX8esqbofc/xvK2B1S3truUazdY8oZsUHDi7GXihTrZiy9zcmWJ1eU2TgiKosJJgbee0sKSCwDL+0CxbmyFsAbnHCWOqrT4ImeUjRiPC2IpaCWalXqL4TijX5U4UaGVYCGpcTJN0ZHCCYsQEbWkhsITAxGWRCuEThjnkKHYGBuEh8gJrCnJSknRu4FKE6QOoCV3nrE3xJHCVyWbfU1fSbxzpDollWCVIpZghMD5iEo5WtKhlERIz7g0WCMpSGCy7o2Eo/BlYISrKpy39C3EaIYuwlcVxiliHaGlAyPx3lBYSWwirDcIPNJLKidQOkaUHusqajLELpkoxpoCLTyicrg4ItZh7JUXNKOIoXMIrymrDGst9VodVxqklygJtvQ4WyFsxdC7EIAZxZRYUqHwQhJrgYpaWFdhqhKlIkofgS8xY4MrNb3eiJef+SzeWKI0pSgyhHMoYZHO811Pvoe/8tN/gV/8Z7/Gcy+/wVKjSXt5GaTAjDVxadjoFIxNxKKtEMbghMf4YBWovCPkE/WM4xbvfOwBrnzxdZo2I04SVLrA8olHqC9f5plrPep1S3NBE6uId77jMTrbXXqlZ21vxB/+5qf4xKc+wqAYYrxgMOxQi2POnTvP6sXLSBWRRlOmqAoV1ZAOIm/Jsj1aS23OLh9HKEleFOTGsLLUoFsY1KCkNIpCWIpxBk7zxloXpTSDrCC3Gi9iHDkNFVOUIQm1cDAqxsQyUEKrCcPZcNzHWYEkxIR8u5aXXn6Req0OTPb5iXXHWYu1NiR2tQ5jQ9Jt7yFKFInWeB8S0lobwNEkVpg4jVlcWQ10uBOLRxAy9pOOH6ZkEoc34dnXCa+Uh8pYBqNA6/6KNfz8b36MDeORHnIhEWXG+ceP8d+dbPG/+/Uvszm2bN0YUXpJLDUfXtskfbhCqYRZQpdDUtB0rzpC5rjjuD9wspjEdR066bDgfKDK1MqxL0X5I068Y//0hy471+6pxDYfHH80rroT0h3CjUDIrRcnKd/53e/BGkdRVnz12Rco01qo1d8LnXIGrWNajRonH/pz9PMC/vDXePKHfoAPfegHkULxT3/+57n6wsusCo82JUuR5gaSgVX8D3s5Mk450045vdDk8ccextmKD3/iWT7+uRfobG2yOXKIJ36GMl1A2BxlxtxT6/AdH3wCKRVJnKCmQs6c5W4m4EyH+usWRo4QkacxNV/vpd6m5dzFBKkrUIHkSACR9rSSmKWlxYCBRKAu9z6QV+VZydUrffJ8fxznZ+WhKEOOtBS/GZgSR3w5TLRw6H323lKOR4x7fdZfyCg61f6LNb2ECElm8WCNYzwsDjdk/1YTsDZ1iWa6Bs7QyXRlFEfNsoPgR8zPxP0F6473VjC3nvoDc35KLb6/5IR16+A17pzVR67Pd1SarISzf/Y75D1srnXp7I75ju+5h0Y94fobXb767DYgcV5wpeOmS+nkRDcdRJx3bK4P+Nyncqpi/iUWTDNGN1ua+x9ukkYKrRRaSpSGWqRYbkb8xu9e5zc+/AquyPiRD1zmR3/wAbLC8PFPvs7NG7tESczmVsnV1y1Z5pHacPai5vJDixw/WWNpZYGTJ8+RJvGckuvgjP2TL39y93zbA6rdzhomH6G14vjKCRptT9qC8w9epN1osrS6jI5S0MHfV0mFcoGxzOUgnGVkDB7FqN9hd3sHUWQIKqT2nKp7XKuNcw5nSkRVUU81C40ldArHWw2OpSkmUhRFQZGVCC2IpcAUBc46lNIYCbGoMDKipjReeAqTM8jHgKMoC2IhsLai3qiT1hTDLOe17T18lEKcMLKOKEoh0ngnyLwBZ5EyJnMST0lsYKAEznpkKSlNsFIltqBCMHaemkyosMTKkVWONHGkDqxQSCMZGdBCMDIGay2N2BGplNKMSaIllDGMTc5qrU3lDMplFF5SlCYEbEuFGWeoWDPyDuk1RkiEsRR5jqQgjzRGQD11YDxCarKywjmDrQwSAalCqwhRWqSDSiqy0mCdR1HivCS3JYnMESqhqkbIJKEuDSLRxDpiUMLpS5dYOX2SrLODKwYMRkOsNeyubdKsN/npn/pfUfMVRTFmVGZ8+ctXaNTb3Li+xj/5//0yp87fy8btXQrrGHb2+PLTL1AvK8bDITqtsXDqOF5HdK1FacmD7/h+3PkHObVQp9FcJasUewOoLRmWmop6EjKL28rR2xtwc73H1bWMX/wX/4obG28gnAFrycYDavU6qyfOUj97ibS+SmQ8Qkt0JCmtJNI1rPM0EqirhOGo4GaZI6RAKkkjjujuVuhU4ZIUYw15KdBCkWNI0xoSz2CYMeisUTlNO60zcmC8QkpFJEE2F/A2vAM6EjgPiW7gigqRCKi+fRP7/k//6H9GSD3ZiKdZ7P1EK+nxzk6kjpmukvlFXEpJa2ERqaKJdUmyvHqMBx9+9A7LylQ42N98xEwCOJCI8YAGer+eQEzcKwU973hhb4DxMMDz+6Zg5aUdfsomPNH3HJOKUWV4rjekOy7pCMP/8voaf/2DhmY8cWGcF0bm4ynm//pJ+zi4dXpCvjiYMPgJP1f/oCAopqCQfRe8qWr3zu3wMFqa3u3gBn5U1X3x7GB/Dta4E7QdBlzTHGTee55/4VU2tjp8zwffQ6QjBqMxL7/4CsXO2oG+Cjw//dM/ybvf/S7Onlrlk5/+EnjByVNneODxd4P1k3cq5vs/9EGevLBC7zNP8Z3f/W5+99NP82JliCIJSnBzZ4voxWsMM8O/++Rtvvj0Gt4VyNoiunUaU41oX/1NzqzEnDl1jIX24pyweRfV/DcqdxyJpb45QszbCYydOrtEFKeEXEXhOVSl4dVX91B6jxmB9sQybZ2jKEqSFqzU5CQsT87ynRnjKCuLc362bkzn9T71NYeezVEqgUNlPg3DZI3bl/oFzhjK7pCinzPeHCOE5iADxdzr6wW/869fQcorMwxw2JZ2GERNgdVsns6afIT247AWReyDnQPz/EC355QH8z8esXzgD1QELzgMrY4CigfA1ey688DPH+pO6Hyt7qg3E156cY80ShgOi7n8UJN6k0Vs/jzhA7PrKLO0fEygXHQH+uDx9LqOL36my0zBJTxKeqT0xJEgTgqeeOQkP/a99+Kl4otfucGtjT06OxnjseH2bcPOXmCWPnOv5MEHlzl2rMbiUhMdRyRpnTRN5wDfn1I5sDf6wwf/2MrbHlD90I/9CMNeL2gZDJy7cAYRR9jzD9JqNfE4hFToOKaJwDqDV7AgQu6Z0nrc9i7jLKO/t0N/b5uFdo3UeyI8OgpapUpArBJ8XCGriXVLC1Ln6A4GJPWIVMLxhZieD+56ReFx0mIQWBSLChqRpFvmNEVI1qulIEkC6QRopFIkUuJw3NrrMB5XNGsJ1ueMxx0aUiFTibUVUjiUrKOkIJUe4cAKQewFHVuiZI00hVSHtCleWKQRRLWQu6aSUE80Na0o8wolc5aTwEiYI9EIFGNUmeATSWVhu9OlpjT1CLaKEdJAPYkoiPCmpCoLSuHxKiapAkAqnWGsI3yRgRRYJDUlcM6x5QypiNBxirUl46IiUmnQrLRjXAVJlKKVpsj79GyBlimR9lQqJXIw8h7cmKoaoIVgoCOUTvAKBnmObt9LWstpLNzPuCqJ+xusXf0ypA1KZ0FabNmj5T3eevrddRbqCc3lOpfPNrnRMwxNgXEeS8W1rVv88t//B4i9DolOefef/WHOfMeT7F65Qg3FiWPHWKoNkM06b1zb4LHvej/GVhhnWGgqSiN4+oXXOX/+Ihtd+Kf/8g/47Fe+SFaO8TYwy+XlmEa7yYnV00TtRRYaLdIkwmqF1IY0qoGtISQ4IxnaksRBOw3xNNaW1Os1EgVj44NLyWjMYi3ibFNQUymj3NLLLd2xIYpSVpaP0W4k9IcF1jpiLbBOU1FAFVwcrXBgFHgB2qPTCOMdSn77svzpuI4UmsbCcd7xwT/D53/n1ymyEd/x3of4jvc/zj/5hd+g2x9wUCM4/ejQkead73uSRr0NQgbt7UQAcTAnAE0EI+9nYsk0T4w/IDzMswFON20xO16ZkHyzAm7fuIIxnntVzIrSDAeSnY0xn7qyw9a44oqveKqf4SZCkZQ6KCu8mNuwj5Y15vt5lMzmPQyGObu7fbRSNBoJy8vNg+d5x3CYU5QlOtIstOozQayqKorS0G7WjnwuhxTTd7QOIC8rbtzewVmHELCy1GZ1uXWgR346fAcucRSQ2hfwPJLKVHzuc19gd6fD+to2V155lSnIKoyCaGH/Ps6AGVBbPEWul3nuRsnNrRwQ7HWH3Li+TT323LpxGyEUQy/5xBtbPLu+x7GNLlEs+Hv/9d/lwrlzGOGoKse/+Ncf5p/84sfIF5+k8Y6fpHbiHorNlxl96R+hhOPEhZP8yId+CDERrKZjdFjEuGPUvk65Y154/qaW+cv9Kcpm36zyxDvPUqvPz+Uw+u978tIB/UggnfRTWTlYwb3bXyd8sHoPBgM2bt/GGjtnpRHz0/SAMsSz/87MkpILwdQd2/v9dK8y+CYH1+PJb+PRiH6vYnO9hCLj3BlNljm21sX+fef7Mfk76Nu573ebIxMwdIeuZNomcfCHwwaYAz8cOn547og7Phz59Q4tytzbcqeS6SC4m8dTRzVmXmEzO+KDddIRs71RABkg0JGaG7uwR1jnYeY6HsCUx+EFtJcabGzlYMKARlFI9B5i9QRVMeVCncT6SkB4KuP5K3/xAR5/8AS9Qc7zL69x7Y1djPNcu1qwsyspK0G9Jbn8YJ2TZ2s89sglavUoKM4mysL5R3O3of2TK3ebNH885W0PqI4dO83Zc5fQ0oOU6MpQAiYVJGmMcA4vPcK5Sa7viNF4zHAwprO1xiDPwHucBl2PWVlaotPZpVMWLNV1CO6NFVGiUU6A12hhEdKBAiEVSZLQrAlUFIRKOzaYIqemPN6FJH6RMPQL6OcGISWZk9QaDYglrtDUUBivqLBoKbFVgckKcm+Jaim1ZhN0grIZvqgocaS6hncFpgo5meJIBcHWO6w1YEc4D9IphNTgJcttDRSkWpFqhVQGaT35IEMD3lakxlNag7QVxkOWJDRcgcr7mEqjmnWcl3hb4Kxls1NRazTxJpj9y8pDnCDiNLhFVhXearAl3ki881RaIrQk1hE4R7ezQ5X3aS+voHxJlVsKMwAHanGVQlgwOaPhHqbM0DKi3lgkMw7jSoQLgb95NgIV0UwaxEmNvKoQUUw6oUrPR12MkTRXLtEbWKQb4X3MbhGxKyK8dySNJqPxiPPHT/Hnf+LP8XP/319DWY8znsJAObTYUUaSj6jkGJlVNNUyT2+s8a4HLvO93/MI5062MLu3+MpLNxmXFSfOncc4Sadv2OuPWBtqPvrLf8hHP/5R1nduEOsUZSyFydGJ5uzJkzSWTlOrL1JbPEV78RRxnCK8xBYVRVbhlZ7loTDC4ZTEyAgpIanF1HXEyHmaTUW7oVmIJLmDEsHmXk5nZPCuxFjwQiJEyqhQlFQoKUKCVW1QTiGUoHRVyP9jPZGEkmA5jISm74o/tTXgj1r+9t/+P/DuhxWthQU+9qzki78To2RJI41Ybas5muCwYCsVNHVT0CSVZO3WOnHcRUqFlFOBJpQpgUUoR1hfBHf49B9wq5vKXhMJatDbDbn1EAx6fRCCtqxx3ii+N0q4bTQ/W5bseI/1kmPHTnDu3GlKJ8hLz253xGBc0azFh5CGOKAJd87Pfp4GQYPEWoe1FiElu3s9tra7rC63yYuCsipJYj0bM2MdV167zjjPWWg3ufeeczgXwHleGHa7I5qNGrFWnD25gBRQVhbr3JFxDvttDX/y0uCsI63FdLsjdvf6tBrJRDSZPLN9RIAnJAtXWh5pwPKekMRXeIrScOXlK5SVxQvIXczExxPqpxGqNnmcHqo+3vYpjaM7LNnrDBnnITWG8BJnPGiHMQ6nWnzsM6/ivMWUEb/8218mlo7/5//0S6ysLuM8jIY5V/Yk/WQVdfm7EXsvMfrih/HFkB/64HtYWWwH1+UDgPiIDom3KGLMWQzulkdoRt//78uRZaocOSDQe5hmlDgohO8PsNKT+NM5wAOCei1mebk9k+WD9XvemjGZ40w/7/87f7N5a+LMsiL2n7MQAuc9b7z2Cvk449I9E9KbzPLKixmDXhlcl6fzY4LTqvJgP+buvn8/5sRczyyu0R+qEBRKcxPsbmD7kHvwfp0JMJz9PFksZ30Xc8cPt3ru7TlqTTiyHYfrHgUTD//quXS5zb2Xl1BKISeAyTmCu7gL68PttR5PfXEz/GZdYCyexPR778jyEj9Zj0+cqPFTP/kwaRJNQLJkZh0TATgrJVBKohWcPh7zxrUtnn/hBpX17GxX3LjpGI0lAsfps5aLl9vce98pHnz0PsQhRekUqIsDx76Vyh/vCvW2B1SRCix0cRSDdVQ+YqGRsNvrMx6OaCcpGM+uyTCjir1Oj0akidMU1VpA5GP6vR7dzg79fg9TFSAFaE1R1EAVxHFFO0mo1xSNaJJEM/Y04hSlPMI7UpVSSwWohOVYsDt0KOsRxqKtwktBIhxKK4aFoRQGGXnSSFGvxVgk2guMlUQquAxWJkdZSyQl9Ugg7ZDSC8YjQb2W0E4sxkmkj4L7wFgEFzkJdlySO4PzEpvEwaqU1hHGUjpPYj2lqBFZTaEqlhsWZy3Xtgf0C0+VJDhniYVHmJxRrvDeECmFHRUUZYXzZXjppaYoOigPhTFUVQZpDZ00sRJskhJ7hXeWcX+XxaVVpAugpDSezriAuEEjSZBVhhAWLR3FYI9xPkKMdsBYrCpQqk6ruRgIGbQnUQpReJz0xEmbzBmMq9CmQ1L0yF2BcYLeaIBUdaKaRErLeLjB9o0r5IMBf/s//S/58z/5/XiXUas1GGcFPit56ss7vPr6Nbq9Lv/D3/+HZNmIi4w4497g1MmEkW7R7w+59twXOL4gqHc2uPblAR8e5Jw/fQIV5WSVQUuFLeHp566QHDvD7et7/Po//01eufoSuS9ROkKYnDwfsnJyle96xz1833e8h+e3JOtZExelxAKEMWitkFEa/NydQHmBTELSaFNaepWgFkeIwlFqx+piihZQlYYbI89ikmCEI4k0D55QbA3gle0xsU5w0pGVOVKGvGCmKjGVRSHRuoZ3HpN1qHREmtTAeQpj0KJCF9++iX0fvT+hs7PBxuY2b7ww4snvfB94w/Mvf5XPfeUKWV6E3CyT7O/t9gKnz51HTjav/e2lggnJCRMyiqkkJMT8JnRQWjggF8zt3tPPhwkunDUIJHG9SX1hld72dQyeHChLxbO7Qzp5ga61iIRmcXmZpeVlKiMYl47Xb2yhtaJViybtEgeEGTe5j7VuQovrGY9zer0hfqJBnYKtKdC7tZ7jnEMKQZpGeOcoyhIEM7fAbm/I08+9ghAhFYSYaM8H/SGRlizUFDpSvPzaGuOsnFjzptr8fX38QdvavsDmfJAnNrZ2mWnEEURaoZQEL/AiWLHuvXgS72F9fZfFhSa1egIEMHXljbXgYZAVFMaiFh7ClX1863y4U5XBhErfiwnAmjxTY2wYq/6Aogqxhs1mjWMrTawd4fE4vcLIL4VzJp6XJYbf/UKOcNeQFAjhaLznp9GPn6UwliW7xWK6Sy5K2s0ap06fOgCivplihAcOeJ/Ola8lPB0lDx9V7pBH3wZFCDBFRlXks3c+SlJ0HBNm4iGJfIaEJs9wskbMIICSJCo5eI8D3/wRn95SS2cXEpOGSwErx44x6Hbpd/sID3GieOixOg8+2kAgsc5hJu9ymVs+8/EBxUyPNnk3/Xwrp2qNyZyaIZ65Fh+of2TX5ho6f/wAVAs/zV/7QP35lfdOM9X0KoKDiqyjLVCTix6Y6Idm81wb5z0PvPesbfQZjgqSmkSpqQXqoKZiMCyYeiR0+0OstyCgKIK85Z2bge4ir/jKszfRWu4nXp41bLq2+7BPCUcaS7IsIx/nbNyGjQ2HsY5L96Wcvyeh3hA8/u7HaLcX5sDo/GXfjtx9b7287QFVPhhAnmCiiMJUlFnFzbUBw14PnKT0Jfl4SJGNUXFKs5YiFpvc2uqyt7MRzNyjDFdOVgal0EnKQtokWW4Fa09l6BWGWwPLgpAIF9ztlhslp5oN6qlnozsi6gkiMaZwVQhq99BMI3QCWItzoH3MQhyxWitpxxovJfV6k1FRYIxHS4mOCHmyYkliNDDGFCOUVTSUoF3XtOueRFRESYxzIFKNk4KqHFNYTakLUhEjhSBShmbiWV1ReAnSQmahZIQvDUXHsjYqqRwMcsPKyioLx1aorCFp1LC2Ii8LRoOcndsdSBN05PHGAILcZBTGQFzHoxDSkziDHe8gJDRkm7SZUGQ5l87WSZuG9Y1tFpabjMcjYlshpGdQDBiPLfl4TLNWw3gREhIXnSC8lAbrevT3blNPa0iVEGuNKy1OCby4gSmGaELS37waUWU5Q2vwRHhn8Epz6YGH+OpT1/FY6otN0iQhqrfojgxZnnHy9HFu39ykqnK63U0kkGcJZVVgopiL9z7E3/nftMh8yT/9ld9nr1fg4whnHB/+/Gf41x/7JNoGV7AP/fAPsHriPA89eD8yWeRf/Mpv88nPfJpxPkCjiJxlnI/xseDEmTM8eM9J7jm9SmvlOPfEKbu3ChIZYfFUUiGkwzmLE4pIeApTEpUSCHE1CQ7laxgUPeModkecWG7RatSxWYUXksGoZDwacN3k2MzivWZclUQqRrlAfBDLCJ0q8IF8A2+J4oQkXsETBNPUSrwGGaWU+tt3MX3qmdtIpTHGcWw15tjqCUDw2msv88ijD9JeaASWpCikCBhlht3OANjfoGdbqghEJdMd+q5WlhlQ2D/gD1xoX1OtI0V7oYnSCucdvY7m9hsCnTZorpylt3eLr1YZV4Xh6fWCrNHk5Nn7kTq4f3opuLG2QxInLC8tThigoKyqifVMzgSr2X8TV2Q/a1eg0Z8GdIe/U9dEMBM8vbDYpl6vU1Yl452d+Y4A4JyllkY0G/U5LXu43mvX1wFJlhVUxs0YEGfAwbsZfBAzQWXfRiMEOBtcqKYaaqU0i0v1ifASLGZZUbK710Mpxc3bmxRlyfLyAh6w1tHvDej3RvR7XUxZ4NxuyEXlynDdqoOv+kyedDhmcwBGWYnY67K3s0uWjQHPOP//t/fnsZZmd303+lnTM+x57zOfGrqrR4/YYOOmiTHc676YQQRyI70MVkQIAUGMBApBDkJMuZGw4Cp5k4hAIiXwRyJQIoF5hQi8xjZxIKaDHQ+0h6K73d1V3VV1qs6w52dca71/7HNOnX2mOlVd3TV4f0v71N7rWfNaz2/9hrV+K2FzsMm1tavYMsf7dSiG22O97b3ACzwKj0KtvhG5+BBlPsI9/38jLv8Vjz3xTr7+W76bPE+3p5bfx6DfDuxhTjk5e3QrtTgszb1LQSYQAnQQIPVkCxaAlGoPEy8OWPn2suLTWn9xgg7ZIyjsd6pwGDO8PaiHlwet1jzVaoNGc4T32x7ittsigCzPSdMUgSBNUwajkrKYnP1ybpK/30PShFCAxFlBkSeTawzYY0natdxvm6629To72/92HVoAzrvrDn62O9G7PW3ebpvg+jY3uf3Z2+i9Vj6/82/vZN81cTkGQz8517Y37b48dp1P7Hm227c7ZW+fLR0NMy69nHLllYzGnCCMmJzX9YLdLdgeivJ6Pw0HY8qywMPEUZoTXL2cYu0kRl44Xrywyfa1envOdm0LVLuWO4/AYQJIRpb1qx6bS6oNQbtiOfdAha978nEanRZS6Cl5f18XT+HueWdfn5rc9wLV2pVLVKtVLCVJlpCkKdpO7n0ZJRnjfIDUEXGgwedc3tiilrdYWp6jOVdnmAx4eX2T7HIX5y1IQRg3qMYT98a1uEniStIipRwVlNaRpxaflvTSMRe7KcpZNI5KKFmIDaFSFM5TD2GcB8zXQiKtkYGn1m4zGPdJhwG6WqVMM/r9EQ5J4ez2lqGYSCuM12yMhySlpbAFztmJxz1RoHSwfRbJI0wJgcOVBqk1TVVQlw4pPIOiJM0dw0Ki5QbVeHLWLM08uZ2c1bqwmaFCRT0MiJXk8rXLXLiyxjizqCBCB4o8HxGjqNcjXDGgzAqkDiitASvxpUI4izUO4wXDZIjRCqxFuoxq2KShcgQSmcFSNSJHMF+r0B902ehtsrLU4MXLm4xTR5KMCHWIkBKnFMI7kqyYmLaNxOYZzk8u2hUIOq0KUk4uKT69UseWluFYoehwrbvJVndMmo65tt5n/ZU+/W5KbJoTpwxa80d/8jSjwSbOWl65cAWkp0hG5KMROtATJx9hyIULm/z/fu0/U6lWsTrEqdN0luErVzP0wiM89NYqW6MB+XCL0XDAn/yPp9nMFE+8c8j//dGP8pXLF5BlTu4sLh/hioxmq8Pi8kSYeuhUg697+8OMy5L1UcZypaSbOEorEVbhA4Erc1LrETpEaYPTAuU0pSuxBpSQ2NKSZxmZEpSFp3AlZeFAeSwK4cARMibBuZJ0OMLFVUxUJ9YC6QWZcyhpcU7ihUZ5h0WC0tgyIRCGcttKJbN71ynFYNDH2onVRQox4XGl5Gve9kYeODVPrRqyY4nqDsa8fGkTtoaTxHssVLvbIbaFFBB4sdej1F6NsjvAVR7Q2ovJQluv1zh1ehnnHJ//3BfY2thChzHjwRbpc5+mLHOGwpKogIGJqAQ1WkGIVGLiLIIJE2KdZbO7hRRyey/89UuErwtUoLUmNBohr5+9cNsXe+5szdnNl20t6/aG6t5gRH84mha49mGc5CTp1nZH7IpseA/1SsRjZzs8f7HLKC2p1yIePLuw6wbcO0dZ2onbYCkYjVJeubyJx+9a206fXqBejRBCcG29R3dztN3n25a30rJ2ZWOyrdV5XnjpCi9eWGNHCPMegkBz7twZtjZeptu9PDmfsNUDJHg7cRwzpQaftOLq5Q02txK2ul2KpAfAx/70o/zPT/4VzlnyLMf7a1PCthB+IlihEMJg8wXIhhRbz3O60uct3/L1LC8uI4UnCsPrQtye2fSqsX/ynZA/uW0i3d3Dmb0qKKUn56v3NmjnzOReZnsv9klZB2WhyeAc1kXXjSEncFR9VPl7HOUYE9BsB9vB06MbVSo0YXf7Wa1RuW7S2ZZK/PXsUEoThiFKKUbDPkWW777rO3f5OefoddcnW9h2znQJMfFiuytwCcKoSrA797n+TOycHbqe585ugH5vg3KyL3HbEnS91yZ30EnCuHo9nz0vQZIkjEbjKWMXeJSUSCmpNtpIdd0kNCWcbtdZbPfhYNDDO8fVK2MEFlvAYJTRG0ycH+1c0r5byh4hLh2XFLnHlQJbOLwXjIduW4jzFJlna6ucLnzKijc10EghKHLwpWRpQfCOdzVYOD3P4uoy9WYTue2c6bC59NUuTMFXgUDViD02H+HLgoYWGFK8T+kOh1y+vMEwzciTAisFoQmIqhWskDSLNp1WjUa1CirELyzT39wijmOs98RRlVazQpEmBIWlngVEPiUtc8pkhBUQhsFkd2AYoUWBs46r6eSsVhRoQi9xCaxZy+m5gPlAMx71qAqwWYa0DoMgVoJRURIKTS0IqMcBW4Vn2C/IXUS7XiMwAYUPSQFrwfYEK0sVcg1n5poEClIhyJKcZOhY6w3wWLI8oyIVqRVk2YB6JWKclSgnkMozsCWRkwwG0JxvsOUFhRZEWqGrAikcZZbSnqtQDSMCYRgVgkG/R5qmaOFxOCwFVeVxpaJwDuUhLUuiQBM3IhyekXdUhKQ/LhnmOXFoKWVIq1VDmpBxXnB2ZZHhqGBrmE5cFBc5Mk2wHoyQZIOUXHqMgMgYmnVFgOdUI2apXSV1ASu1GoP+gJfSggtrG/gyp0y7JM4yGFxl6+qXtrVlOy5KBTqMCMMYJwRpkRNUIpyYXHDrvMTlBUFUIUn7PPOFp1E6Qkizzci5yf1OVmC9xDO5t8mWOa7IePovPsGXz38FT4koMzJb4NMUFMTtOq1GlfkmfO3jLd5wZolqUCHJYgKVsWFDim3NXhkIMjtGOYMwBlEUgKMsNVE1xJeK0ARIC15L8iwlKTWBCVFKIAJDOzaUVrLRH5MkY+KogncWEUYoY7DlRJs1dsXEuYXQWFcSeU+eZ1glCWSACg2FEoDGWkde3rtu02tVgwmC3RV3536xlYUqWgu8n9z5YT288NIal69sbLuthx1mRwpJtRJjnaNer7M43yRJC16+tI7zE8tMWZZU4xDwDMcJO8knG0PEFOPVatZZXuxQ2omb9CxJKUrLaDgmSVKEUpNtsKVFSI33gkcff5zVlVXSvKTbG1GWFq0VSk4ugBYIFufaLM612djqs9UbIaUkCCZadOss/WGC9yXeOZr1KmEYbJ8dgzTVDIcpyyuL1Ou1bSFHMByOeOHFlwEIQ4PRk74ZJylKCk6fWppsudvu20uX1xknOQKI4wC1zTxJAUpqLq2PqVUjqhVPox6z0GlMNOVC0O8PSLMMJQNarTrWOubmW9su6z0XLq7hracsHVJIAhPQaU/KFkJgnWNjo0tZMrlbDACPMRolJ+9ukU/OEMZxxNkHH6M9GOKd5crli9tWJ3mACd4Zy888/adTwipCMOp3GfW71yNNipy4nRbXGeilpXne+pbH+dz5S1z7ykUUjlMPvZE3Pvb4daF3m8N7NSzESXY13Qlm6Xbb215viN1B2hZudpQoN+jMo8bgetB0z9xsPx1Q1JygLvutETsCy04cYwwL80sHX4G9kuMegaxSqUy2tu3LNBkPSca9XacyOwqpvVKlEIJGs0290ZoSTKcrLaZ+eg/JaEhZFHssZtuFbluFdRCytHJ2V/m1N/1g0EWINZz1hNFky2aaTLbDSymZm18iCMPt+h7di847knSMLQsWFgL+X//vNs7Bp/+qz4UXC0Zju2ugu96U634MbeEoc8/KmSpYT1E60swz6E6s5aWFYry37B0Bd8db4fW6CCbeWKUUvOuJKo882kKbCs1mk1anc9CqecS83ZlPN2PFvl9w3wtU//tTn0FFhma9yspSk1YjQKKoRorheIyVAhMarPDUoxpnHnyIpYdOU6/UUYEkTVIeW5xjdXkZKzO0MqggoNNooLxife0aG9111tY2uPbyJsOyJIwkxSCh1mjifUa7WqEsCi5fWUcpB2XBoJ+RpJ7FRot6cw754ArSFFTzMWmSMVdPUa02Y2tpDzOuXt6Y3C+jwHpPM1CESjAUAhRAiRIgoxqNOGKxFRJEimoY0KhGpKM+eZrjhEQHOQuxxtkSG2h63QKtNc1AEPkELwSF1lgvMDokc2CqLXrVBmcfWuFNtZBGvU7UrKOiGIljMEhIBwOGgyGXrlxloz9EqirKgHeCcZ7TywqCIKBwKdp6CmcRzjPuQnulzVK7Tr+fUqvW+ebHV3BK8OLlLa5sjukOuhSFZ+AHxLUa1uUT1/auABlvMzwOm0PTaIIA0qwk0gEL9YizCxXGackbzq4QVySXewOWljuoRoUkK2lsNdnolyS9nM1rVwC3eyxDSI3UGoyCLCdQYJRGSLW7fQAhCZXCKxAq3A6f6Ja89/iixNrJtiLvLYUoUQ6syxH5iPF4nUBXsDbDZwlaS+pzc5xeXebr3nyOd77xAd702GPMtTp85ksv89zVhCwH4wVGMBHGvMGWIZFReEpQkkKHaAHjEnzpcSKlVqvgZEAYthmPC3p5irSWerXO5lBgcaAN7fk2IncUmcdEASBJrEV5gbeTsZNBhTA0+NIijKGuDPiSQghE6SgmJ2cx8t5lhyqxIgwnDhqK0vL881dwznPmVAtXCl650iMMDEtLLZqNGlevdbetNNetIkFgeOThVXqDBKMClhY7eA+rK5OFqtcf88wXX+TRc6fwzvHX51/Auh0hdCJM7eybDwPDXLvJ6VOL5IXl4//9f7G+3sN5R57n2x6gFFIbPKB1jFaa+c4cywsdgsDwpWdfotsb88i5UywtNPn0Z/+GwloqccTq8gK1WpXFhZwoCKhWY7TUDIYj/upzXyQIJkLU2TOLLC12JlX0nvWNPi9dWCMKQ8Jo8g7gBVpPnNEIBG987Axz7QYAzz7/MmmScu6BVbRWeD+5mHjQT1BSIaXkzW98iEo0cTcvty1cn/vCRd7xtnPEkd7DsE1c9Z//yhr9wZj5Tp12u4ExmvlOY6eKJOOM0Shl0J8waI1GldOn53cZFe89n/7ff0OvPyIKJ2fIrHWcOrNCo14jzzPWLq8BUBSWhYUllpZXkUIyGg1I0gyt9DaTNdEwF3lOnmcIJMnoujfIna1Eux7XdtkPSavV5A2PPwxics+Vd7C0tMCjjzxCe36FUZKAEJxeWUTuvShoiie9uXfurn5D7+rKnQw7o3zTTdmf4JA9eYdt0zs0/W3icAVMLgqfytbv+30wza4wuZv++h7AA4KHmDj0qTda29v39jTEbV9XASAkxuhpYe2QvK4LsROElRpi+yLzvYLiTh2VMZPtzodsjzQmoFJtTrY+bjuQUDrcVZJItb2Vc89rLfb83bF0CyGIKxO64k1EWPHgPO94V8TC/ID/+T+3Jtv3PLtn6A5uXfA88GCTfjchCB3Pnh9PlbP71+/fEzBxrrPT8c2GYnU1orNQ5ewDDeaWmiyfOTXZsbCvL/d+PX4+3wGR6kYaiNcQ971AZcOAer3G0tIcvvRoP2H4LHDqzCLBRp/RCNLSsfzgGVqdFm9+01vpZxn10BBWA4SXNMKYNBuhoog4qtCMNb08R8Y1zrRbLJ97hHQ44svnv8KF59fQlZQ0y1mtRgQabGxQ3Yg8kwgyTABKayQBo75FyTqqE3BqucXGc8/SSw3pMCUMLenGgEYQI4VCRBGxCDjTrFONYX2rP3EtHIWsViXLdUl7TrGxuU4jmCNShlotYjDs057vYIIIax2b6RYvb0zOEDkZMcoF13Iw0mGdx4qAEomUGqsM48RRlQmD3os88qZHeOjcAs1WHYtHo6nFVfpRwGgwor+ZUa81GfW7FOkY4UJCFVIqT+kzIj0RgCJKcBmDrODytS1Wls9AP2Pcz5G+RZlnVEPFcrvOeJyTpo71wYjBVo9YhzihcUzubBKBBl8SxVUA6rHAuCGDfko9Crna8zx8qoH0BVevljzxxscYZ5aXNjbpj0uESUh1RlxdQ4jJVkfBZLuSdFAMRxgdABNPixVt0FKSb+/Vdr6cLJhucoauyEqk0iAkZZniXYkUCqkDnAclti951hMLT5aluMIiA0NzYYGFRpOHz66wvDTPu99whscefZBuP+fly5dIc4t3ll7mKLxAaI0oPTbpkqUZ/dwS+QJbOqJKG6s0hVRIKSglZDZAyIw0zQikIvcZRkGeODI3YZbzIscnI0qhcVpighq2dHTqVXrDMVpolACXDhk6j9MBWigSmyJ0gLMWLTTCW7RwSBPcQSrw6qCNxgSaHeJc5CVl6XjuK5eI4oiiBJCMk4zBMCWOI4SAxx5apVaNQEq2toZ88fwreA+nV+YYDcdUKhHxtnaziCxaGr787CU8nkcfOovRiivXtgDHtfXJOcE4DHj7Wx6htI7nvnIZozRvfvwhkrMTC5XzjudevMLSXI3hMCErCur1BkEQ0BumfPHZV3jzG87ypsfOMhglrG8O8N5tO5EQbG71KJ2l3a7TdI5nz1/glbzg9OkVirKkEoa88x1vQGuFMWp7a99ksZ+fb9HuNPjSl1/i8pWru/1VlhaxramVQmxbowSPP3oG78W2Jes6S/jYI6cJtvtb64kXKWcd3e6QwTjDaMX6xoCF+TpxHFCUlhcuXqG0niTJ8Dh2lNh7t9cIAQ8+sHx9YKf5HSaWRAgDw8Jckze98SxCCAbDhC/9zWXWrvZpNSPe9jWPbGutr8u5HhiPNmg0GiwszPGOr3sTctuF8P/+zF/zF3/+NOCoVKu0Wk2K0nLt6tVdxxpBGBGYkEcefZjcwsJcm7e+9XGsB60UtUq4ezbjsUZ1u7bi+pbIPergnW2aR2E/f/1ayiq3ws7cB7LTsdg7365vprv1Vt/U5s4jzAa3UoP9FqrDMj5u/HcFDHFI2dsBYRSzuHx2O+gQydJvO/PYVjYdN+/3F95uz++rpNj3/0EReOdJHFeI4speeXCqXrseEvcJNlMC5PbfxaVVdvwT7TRg7dJLeGv5/9QVRekmF8NPZC2KsuSZzwzIc8Hc8sRTaaPlSVNwpJx7RJFnalchPHW/nwex7SbfOU+7Y6g3QqRUVCuG+cWAVrvN4vLpyV2VO0Ty0MmxXwzd++QO2aaOEKZeazq3g/teoApMhygKUSLi3ENNfDZE6IAgiylzS6c+z2YK45GntbjEm97+RtqdFnNKYaRBKIkrSwZ5hgurVOIqtSBAhQHLNUWr0WYwTnEe+ija84v0NgpkllCJA5Y7MSoveO7SJq25kGScMhhlJElBVQlSrZFa8NzaJq35h0hthcrSA1TTl1ltWwSO9fVrdK/1USomHxWcWTC8eSWiJiyX4jk+d7GH0xUqtSYoRz+HsDlPvbNI1GqShYbKSkirzBmXjl7fsbTYIggkVzcKklwgCkPuDLktkIEnUhrhFN0iw9uMufYCubUEvqDdqLCxtYVDsjHoUY9DQh0y3BpQZBLnHFlZ4rXGuCqF1WgFaT5CSUB7clvgvECLANSI1VNLxKrCuVXPm84ss9YbkeWOWGta8zX6vYTnRxlB1CQvS4a5Q3s/0c6W4EtBLjVhYEBqUu8JQ0N9tU6rXeXxh86w3JSsztfIvWajP8JEjkWjyS5fo24DBumY3ETUOvN4Z7FFjitLfOnwwuPKEukdgYiQOpxot4TAIyfb3xzb+75LpAbv8uuXLgoFeHyZghdYse0owk/u5JIO4maHRr3GQ6dO02pVqVZDlKqwmRmev5ySesXL10ouDwpsKehUaxQCysJS5CBFhagSEgYeoyyFD/D5mFAVNGPDKC9AKMajPi6oEpqIMs8m54NKjRaScWFp1wOq1ZCw3cApTZFbxmjwDqUkYRRPLgB2DqMMSoAxIQZPbu1kz6koKWwOIkAiyQt3hynBrWPvVhalJPPzDfK8ZJykrC616czVcR62uiPm5prMdepIIViYb2GMASA0hjCYWFSiMKASh2izc1kw1GoR73zHI7uLcCWa3DS/uDjHcDTe3hboEFJy+Vqf4ThlOEw4tdTm7JkVxuOUtWvrhFHEy9eGdObnqFRyrLWUDvJy4pHPWsfa+oBmPWau1aIoJwv16VNLINj1eCfEpK0PPDgRpPK8JEnHrCxPLFzG7HOXu817aCVZmG8RxxNtrQCEFATG4JyjWomuH8yecjs1YQza7er+3gc/2Qo4SjOccywvtdg9E7V9riKODKV1nFmdR0pBbfuM1JRLaK4LWAcW1x0rj4eHzi1vW/YmB+6b9Spve/OEqdNaodS2U4Fda9Dk75kzZ6lUG9RrFWrV+jYtsGys95BS473n1OkzvPubnqTfH/IHv/9/UeQZQki+9p3vAO949ze+C6U0eE+57TVNCnmd4ZpiK/ew49uWrtvJNBzHEr1W23nud2EKePWNvM0dv9e6dZKqHRbv1VZpf/odu8oOfZzMt/2S1/bukG3F52EWrr1yzMFCD2H7pzLZ0VAckXwq/t5I+2xxNzRNTguCQgi0iai1KlSb8a731okHV0eel5z/6xE4waOPTzxJG+MJI0m1VmG+E+4qavYK77t12z7j6j1IPdnxoLYdjLTml6jWqkgp91fx8PYfCLmb3uDXikodjfteoBImQMuQWlQjEBG1TkRgIrzIubreZaNXUBZDrAip1FukpeDixStUqjHVVoMoqmCkp1qdOCeoBiEWQc2EOCEprMdZydZojM0kneocyXJKd3OLskjJxikrtTrnFuH8K+sMNIyGA5LMYgPJ0EYgPSV9nvz6Dt4oVL3B6kOP8dKVVwhw1BvznHtojmpgGGYFGseLecDLawPSUiPCObpOci2FqFnnVKtOHFV4pZ+yGKWc60jmqxHW1rl6YY0r17okfuIRLEs1pQwmF3tqIJxsr8mdQgtB1UjmHnmY0WBM5BUL7Zh6pU5UMchYsdw6TdYf03MF9cUGm71NAjW5y6gsNIkoCYTFS0tNS6wSKBXilZioW1yKJKC/OeKq0Lz76x5kfqlOVA0pcXRHBRde3mRYSLqjDC8igrBBml1DaIVREms0okxw3pNJQTWMcFaRyBKdSBqLNTaHGedWmoyGCdIa2nGFYVEiZIRYbaDWtlhbV6yeepgoClnfuESYF4zHfXILCIfNC8JIE5s6eWoJ4xglW2ghcUy8ovnAsvrAKWzpKG2BlIKisBNvgwi0FgyHQ7yT5NuXTMRxneUzj7HUXmCp3qAaxTTma6yeajPfbNCuV6lXAy5e7VPVJWdamvVBSacq6KYOr8qJe3KpEErjtAZboIQDGTFIJ2e1VFDBS40tCkJnkXlJng+RUQ0TV6kYTegFmbNEJiQ0CryiaQRXkgJnFWnh0dpTbLvvLwqHxxMJQeE8aV5iJJRao6wF7bB4BqPunSUErwI7nqHwoKTk7Nn5yeLmJxYNISaavIW5OgvUdjWB1+EJw4CVpbmD2uRtRkApQaMe75a4k0GkJGFYo9N5w/Yh8MlCeP7Zl5F4zp5dRiq17bRGkQwzTq0sUjiYX5xjZbFNbzDm4sWrvOGxs3g8n/nrF9jojmnWqzz28Bmkmt7Wcn0rmqBai6+f4Vlss8vh7N8mI64vXSvLbaB9naHYva1TXI+/27nTTNL1nPcGTi6nPH16nr0L5CSWxwjNqZW5AwzS3kPzU9uB9vawOBBCtRZPMSNCCqrViGlMtOMTp1+TdGfPLHLm9MJueTsC+Lvf/QRe1Rn0e7Rbc8y1mxitWFhYJs9TvHecXj3FysoSQWDYOf6umZzZmmxJcrta+Gk+YVo7vK+Zh+I4vvO45HeaXbpDOu/bBgEHBYLtb9MuJY7o5ZvogKmxOsRIclRer/kY75Xejgo/pAIHjEj7nx8WPtUB05kems3+TPwJ0rBnG504unk3NaTeM7ewRGdu4Xoy7xmPh1y+eAEhHG/4mjrpCJYWKjgm9z++7X1fRxCaA0LUwTI8G5deIU9TvAAVRERxjFKKdmcOtSNMHTPfjn50G9/S/fP2JDhyAF4f3PcCVekL+mNJYQs6saReMRQOklKz2F5m6IZUbUwdSbrR55pQtJbbRHGVKIgJazVC71FCk5cp9bBKHCm8F+R5RqMSsVCJCGXJs+trjEc5HjDVmHmlGQ0T1rKERjtgIQnIxmOSOMCKnLIsKdMtGmEDFRg++fnnePyRVU6d6VCaIbVOk9Eg49HHHqXwis+dv0gQGybH1mMWFwO2hmOMqlI4x1g32fBtsmFAG8npMx3OtEIqVbAF5FbS6iyTm5iXN4Z011N8rNAWKgYCYSm9RgaCQoeEQhOFEeNxRlCt0jIhva01zqeWpdUVTukq2qfIMkUlKYury/DAWWyu+PznzyNERmQ9aZmgdIQLIqTPCUWO1wqEoSzM5B6mSsBDDy1TbUw02NVII5UnK+DlzZyrQ0FYaRAHIV4FxKGGMEY4T2kLsBnOSVSZYG1JGClMFNNuhswtVlnfHHFhrcLj5xqko4wXXhlyuZ9QFA5XChCagVb4egdjHS0V4ccDXBDBqIf3BcIWNCoRaZpRlAn1Wohpdmi0Y7q9IcNhwdx8kwfPLJOkKekoASFxeOIwoCwLvuFtD/Pi5S5FkfP8Sxtc7o6oxg1qlYhmM0AZgSehbWqMhxlrrk+gJdd6Q7JSUI0VkYL+OOPqOOL5zTG+FEhXgBYIqZA4irKgIgS6GhFENfIyR6vJwXplHanNiYMAHXUwAGWOjULmmjFYT1ZYhND085yy9HhboIXDyZA89xRFhhUTBYNAkDqPlJooBOkdhXVIERACTpRU6/stD/cgxJ7/xOSOr8MiTZ7vWQX2nCjew39PMb9TelGxzazv6GV3LTrXNZ5vePTURMO4va+t064y16lNHm9LajsCWxgaOs0qw1FOlua882seYmOzz0Y3o1avUtneVie2bRy75Yi9LN9Om/ZqX/dYSPZ10jQDNN1P00Ge6bPoYqrr2Jf3AcbKH73N57CzD8cLD+K6YHiIoHUQB1XXe62ZO386nQbv/Za3450jMBqjJZ12gx/4/u/e3m7pCEww5UJ7Z5vOdVZ7D3fxGjMLx+l1X3c+5W5SeL+GOFacuqGAfNgcnb7Xald5sE95cXN1uxUO9yaxlzbutuD1mATi2GJuvq92cGt1F0JMHAvtyTMMIkwYIqXkLW9ZIE0yHI7R2BNVBHFsCMNDFD8HaugxYbR7IXCtUac1v4jgcMF077Q5OBf2rRF3KV4vMnLfC1SBjFEm5trQ8tyllNPLAY1qQC9J2ep1ubSV0RsNCI0mTa+xaKC1Ok8chmxtrFN3npQSqwMiSq6MM5bbHaLQ44sUBFzsrjNOErrDPoPLfUbDIf1kzJbzdIxAlwW9YUloLUYI6u02K9rwykaXUgg69Sq1Wo3llXlWTs3jrUOETWreEOUbpIXkSrfLqUadrc0eVgmc9BS5xskWCaADhQwMg3FJLiWDUjLWsLBY5eW1AUjHxvqAWmQwUY0gkngDoiwxKqFrIZUhsQ4ppCFJckZSUAkq5OOEB5YWqNQMzYUm83MLFOSEUYAxBhtDmYy4+NJLfPGvX+Zav5i4do8CCiuIwxIvJCkFiAiLwitNaUsq1QpnF2MWF+Y4NTdHkXu6VlKr1RkkGVsjT6XSpN2OEYMC56D0JUYarJN4U0PHGudKvHZECPLSIXBoZYnDKs4GvOmhOouNmHq1itZV5t0QUQvoDXPOX0xJU491EOCpVaoEUpLJkKjeRtqMMu3T37pC4QoSclRgCCsxc+0qlcigZYhkwFJngTCsEMQVlF8nCkKajQYiCFFS4a1meXmOL3/5AgDNKOAtDz3EmaVTvPWhBTpRDROF1CuGTCpkHGJlQFw4YuOJ45DLGyOCZcNXep5KrUKROcgFBQ6tFF4ajICRTYmcJBAa7yypLWlHkjAI6JdQOoE0kiCMiYykKB1Xt/oYBHlesiEVoTS0a5qSiLQAlztKQOkQreWk363AupxSSLzwSBVgkDjvwAsSL3fvIbo/sLNvn0M1Yn7K9LGXAd5mE3ZU1VNpd55NCzN7T1ns3oEi2PWKN12n6fx2Uisx8eCo0hIvPEVZcmZ1bmJh285HTP/Zn+MBC89O03breqM9QDej7TxQj6NSbF8evLceO8/237uzJ9mOwez4Kl4XYw53SH0QRwl2Wiuajcq+uILxOKdej9BqrxexPWaEnfklpp8eXszrwOwekfvdz07dS9ivmpgOnRa42f11o1E4oIi4aYh93/0Rv26MXcv8vsSHGReuv3+Hl3Dwya2+Bzcwkd0yjhWVj02yf6iCMOLMAw9jrcWWBZcuXiAZj8BJQG7fy3ewjMMoaXtpkUY5cSiklN7jJXQn5mHU8HXGUdP6JEP0+u/2A74KBCqpIFAlcRBSb4Ysz2uKrEcn9MSNkiRPqBjY6g2IKzWay22MF+Q5LK2eJktzolqdxBVUCahEFeYaVYT3hDpgPcloVtu0Wx2Mifmf3c+hVY3FakwjEDQqIQ5Hno54/vw611KPKnNUyxAEDSoVRWECKq156q0OeS7RgcJQTl4cbegx5lovYZiOGWdjakEFhCGTEl+tIW1GJ/BIBLWaRGl4eKVNLahg0ZQupF6r8ehjywyyAf2uI3cJiQ/YUhrrDd5ZQq8YeIHPc7w3pAV0N3tUjOLalas05usoEVCtJiy26zSqAaOyxOgAbWq89NKLWDVxp27zlNBEZEWKtyHSOiraUIrJhcYSqEcxRgcEpo53jq9cG7G0UKVmDOMR+FKxkUK1UaOjU0Y2IXcOSUjmPFJHuFKihMPoACUmng+VKlmcC9GBRuO4lmnmVIvSKK6NYZhYkkJgE0WWG3IFWeBYWexguxFu1CdUGltaQilQxuETycJKg6trL5NcyraZMocOAqJqkwffuMxXnr1AxWiUlsRxhUZFY2RIXI/QOmQ8GnItK1ia7/DGx8/x4KOQjaAetTk9t0gtqtGKQ0Q9okgzuqMUaT0XupskmcVbx/JCg42+o1WPUFhUNrnnbJTmWK1QxqOdx5aCpN+HMKOM2wht8A4yK9BKECtFFGrqcUhWlHjrkcIRBjGhsiwsVtkc5pROcHVsiRV4LKLIsFmJDg2FVSipKYTFKVBeEAhNXpQ47wmlpMSSFynqAMd9L0Ew2U62rS/dq+49IGjscQjgj2PGxQGCf7h28DrLdHhWE83q1B783TpeD1cC2q2YZjOiP8i376Da473psEV82yJ19Lp0UqvJUUzFSZmXGzBJN+AWDwyROPTrgQGY+vVqp++erY07X8Nt74WTSzUPgz8gyN5OYeoO7445Ge7qyt0u3Hhrmdj35HCr1E5uh231OrmgcLtFimncmNO9WV54b68c1SPTMW+eBh0n0h1UurzK3tvXARMBdJKnUgqpFNpoVh94AFdanAOl5bab9uk6H8x48teYAKPNgbYcsizdeSvxSSfD66NTOhb3vUBVDw2PPLDAg3N1hJS80LUMEkVFWISsUJ+rEoz6JIXEtFY49+BDRPUKHsGgN0BLTSwVjSCgU4kpnSWzYIyiVxYUSuGcpxjnpFnB2dU5/uZLLyAdDK3AFiUeSSuqUm+lbIw9TnmGVImrAXFT0k0tF9bH5GKDRjRg9ew8K4tVXKDodnOq8TIPPjLHF5+9TKtyDqkcpfAEIdQCjbMBFaUQJmCu08L4jPVujmsaamNPXI9I05RhrjDKMBpvElTqxHXJsDdEuAo6yqlJR6+U+BLCoKQhFF6AVYKiyNhYV0hhibTh8mbCY+cMKpxcDGulIWh0GK1foyxTapU64Am9RUqDjTTOajQW71O88BDUmG/FVGuaQIXUKhOvWFuDMZnXhFLSaFdZWahydaNkUI7oJxnjzBKJyb0zhcgIhMEFGu8mrpVrFQnSQAmPn25jrWXQ79KpNekNJGuDlKpRqECg8pwzDcWF9RFrvQxrNWHUonSC+nwFXYxQWGxcJx0McPRYaDoqFc1Su8pb3vwAztRozrWxaUo2zqm1mtSqdULjcEKiEBRpwerCKjKQdPsZtU6LtnRs5J7FoE21UmXdlmQDh3YFK9WQ+XaNUaB52/wcUagYZhllnhFXJFe2CtJSkRUW78EKiRBq0q94cg31egOht7cSCYnPRtgwxpiAkIDIeYrCT+4pEpJAO9oVTWlDekmJVDGhcazEisEgo5tPhHYpFC4vQXsQCuMlmQBsSeYspQDB5H9rJwdg99tT7mXs7rw7dMvf3ojbNP7gzrAj8zwmqwPfjg3ao/7dy04oIWg1JpuGj81gF8fEuxm19+5it1+aEQc652jWZH85+9nM6UfH1epAf96oCcct1nvK8vuf7zWh7Ykn8MSxObTY60VN99WN2dDbhzslbL22zPzdiFfT2pvlNG+1dw+Ws1fNcvOuUPZIDDtfb5jFwUjHvP03zGv6dd7vTPxGqabjHGcT2p/+ZFsYxe6aMVWvHdOen+QVRfE+pzvigEX7iNy3a7HTp9dp4FG09Egc15TDxvVmdWi38vxm1qXbjPteoPIEjEaa8WKF+XqA9o4wiEjzggqeIk2pVFukY8U4T3n+r5/j9GOPMP/AHJUoQKHISofBM8wdUnlwOYPUYZ3DCMeVtWv4wmNQKFPFIomUp9lp4JKMUXfAsLC0dUS+oLg6tGQOqnXF8vI8i95hEYjSM3+mzrX1a9QrkjLLaDbnGPS3KJKCSjUiSRw4S+IdCk2Z5jhlSJRBWUlhHSkK7R0ikFzqj5lvN8izjNR5nAMd1li/mnBl6MlEjVArrPWMcFQVpIGiW1g6wbYTCa1pViuoiiYbW8oSVlaXGOeWRqCBEoGjXatQrDbYuGrZ7JcYBVpEWDtCFG7iWQaHVSE4RZkl9JKIKJAE0jLX7jBXU2htuLI5wHsIRcDlbkLqFDhPJayDyrBJRmGqk982o5QafE6uJNoFVJWkU5fkznOmHdGMmiAdw9zSijXWeQZJyVrPc7GbkZUBFRPhtAUEpdHYMoOxoBj1SYZ9fJFgCJC1Ku94wzLveec5Kp05Xrg25qULfYZjSSQCxv2EwBha7QWsnZy/a7QUNWEYjEY8vFphs29ZHxas1Fo0KoaluQCXBWSp5kyjQmgkaVbgcstWnnJxPSXJSrSaOHn4ymaGdYLEi4mr9ljgS7BZijaSmtSYSn3iktpKrC/IoyrOWxqRpLSCDE9FKHJrGeYFRhXEKsSWGRooyOgnDikl2iicLcnKnNBZvNQMhyNsaDAiRCmNFRatNd6XSBFO7jmTktL57W0J9yiOoMv7gw/TC0+CtpeuY5nxkwlKhxQ4Hf+QMg4TQ/Yy61OL9pR88SoXpOOkhUPCjnp0aL+duPATiAa3pg4/+rmfMkhNxvgk43KUvHpo6J0RO16P0o/kuV5//ug1xMEW3i4h9qCr7lvJ43bh1YvIN2P7uV7a0eWKI75fDztM8Hn1PXJddnw14zPxhjqtEtpp683Z9g7dxn27cJQwddSzw+LdcoF3jlDc9wKVFDBMM/rdEdKOaVQisnSM9I5cOHwKV4cpI2uo1Rs0Ow2UhP6lPtHKPASOPC8QQY1Qerx3SBR1FaKMZDBKmG/W+eKzL6DDmFHSR/oS6yTDbkKWW+babZpxyKWrQ/QY5mOBiSOcCrBeMNfpYMnpzLeoNkOWFhqkWyO0MvQGQ8aJptcXWBeipKca1UFYinGO0KClYlhCHGo2E0uRF9QDyTD1VKOQtSsDlBF0+wM2BhlKOda7BTUtCF0+ueOkLJGU5MJgck9DOTJvEVYQa4nPElpLZzDLMdXQIGSOFJ7MVRgMHaNRinMlqbVkUqFkSWIdpQIfhTgb4BEoJVAovHBEgaRRiTizVOd0J6LwcLWfM1eBqjIkDlKX089HDEeKvJSMbYFQGmUyUpuidIAxIThP7sA6x8A5xl3JpUHOahRQ5gWBKAgDSegLhmWJjCKMVmR5jlGSB9oRL230yBNLZCZnqKTU9MoeUaWBqlXJhj2E9qyurDI/X2EwkHhjsV6QeMfIS4IoRriMWlzFi4AwVhgk1uYMlKVfCvobOVeupbSaTQZ5Rj2UjNZHFCXUGzVGwIvXhnQTS61Z4eWtPrVqQJ6WnL8ywAk58ewmAkRhSfIhQSAoC4cvLJlOEXhq1QomiPGlRQqPkxohNWVhSZ2jZgxeWuYrhiCxDJKMvCzIC0lpc3AWKxRFbhlkBUJIQhOQiRKlDE1j8E7grMN6QDissgQYnHcoZwBHHFZI7OAOU4JXh5No7vYy/9NrxrZ4IuDwleQoieLwlWc39IDwM9l6Ny2AHJLHMRrMA4LUUdzMcYviLaxnxyocxb6ibrRuHmj/rdXpJOzJwbMGh20D3S9RHTo7uHUu49YY1uPnwK2lneFux1Hz7CaY/JuRcA7J+8AmYj8d67h8JrU/ngBMx5muw0nn7V7B50TGkG0c3x3X23/jeAdLva5wOa5Uj5j28nNC3AZVyY1I2EnlnZvd8zlVgTuL+16gysuUM3Pz1GuaSmSwRUoQQa+XU3jPZl9S6gqtcyt0Fju8/PxFkiKhUl+g3mlSMzHVWsDGKKGwnshonC/pjgdUNAyHKakocSVIaXjswYfJvaYYJlSzhADojTPWN8Zc6mWME0EYxPQ2x1RCT2/ouNZLOb1Yxcx70o0hK0tt4npA6QSjTGEiR7tj0L2UkS8oBAQoQi0p0ozE5nRaIUtN6I5TjNSMhhkYSVZosnxMGGuqUUh6bUCjFuOUxYqJ4wNrBdWwSp4XbGZgnCEVUKXAKEEpBKraIh0mbG1ssbyyiKwqnJK4LGF9fcBCu06nVSMMJTjB5dwROUVvOMSICt4ovLN4KTACOrWYwklqsea5r/Q5/9Im73rTKWINL1zt0anX6KcjegPHej9gmGfkKDKXEWMwKiaSBoSjSPsE8eTuBInEC0GejdkcDOibLdaTDsudkFMdzVgr0kyQ9wpyFFeSgk6jipAaSUxkxhgsw3JyXsgEMblLsbnFW4OQAb31lG4sCYTg6mZCZmKC0vGGB1eIggBfZDhvGSdjKqI5uUndxKAU1VpIUVhWgjpbo5zEOcgUlzcGhMZQ61sqpmSuEaDDiav4Rx+YY7Nf4DV8wxtOk1mLtYJr/YxB7OkOJUU5JggMZVRFC0UhSnQYYb3HRAbnBcp6qpEmMpo8L8gKyWCcUjiITYQSOd1eiTSaWhAyKHNKLyhchvASEytCZWgQMxxlZLbAlWC1QlqB0AGxhwKPK3OskDg0RV5gi/vKK8WROHCWCQ5n8A8k3Plv/2J7MP4NtacHFrbDyjyOqTosyd5F+sQc0IlwI/5MsFcLu5NA7Im/X2A8WhA9DCfjAW7EBB0s5TCx6UZ1OSqvw2p0O+1Ed54VuY77esvfke/m3djqI2bFPoZ3v5izN+2tzPob1+pm87k5YWo61SEB/ui8bkTLJl3nT0RPDvbdUdTxds2dW8jnVob0KMvVzrObyvMoentncN8LVMPU8fnnLxFfimhUA04vVKnFijDQhEKxJR3KVDDeEQch3/C33k4QxSR5jhWCAk8xGDLOS4TzmEaV0Aja9QpGeVQQUMlT8nZIb5zQS0M6QczVYZetYYK0niSzFBaEUKRuQDaSqECzMR6hMWgDoyBALXvm2zWU9WylOf2NEVEYUu9UGWwUSBeRWehlJUVeUggHBDjl6WeQ9y3j3FCvCjIvcIlnnAwxkWLoMlJZcHahyfpWRiQEWenoBKCsJU9zNJZ5Y7BliRcC5zV5oUmTjMAl9GWOM1WMNVR1gMvGVAPJAw8tEzjPV17aYG2jz1Z3TGolkXcYWUFSgrNoEZDZkk61QSU09EZDXljbIk1zKhXDK5sD0qyH8ZIL62OC2OCsphCgTESRJoRy4lku94JSeIxQWKHoJ0NCHSIDQ8NAsxqStRpI58nyBGsFgYs41YoYRgEvbli2+infcHaVRlXy3HpC4RLSjS660SSSIUQRuZaQFhTdDbJ0gLcjZKhYXlpFm4D17ojNawNy76k7ix12OXVmASEMAk1SeKRWkwtBvUKbgtwL5iuauWpAb+QJlCZYmiMSkqIsibWigkS4gtQ5yiTHUFAJBGvdFGsLnPVYLwnQSGPoRG1K69gcjdDGEOsI4Sxl5qnUAkrvsVohmFxM2okdTgpaNNG6REjLqTNtBkmCkpr1UUGoDU0vSRSMS4uxEldaclPihJ/caWUUQoJQMMxHBCUobQhVQOomVktUiD1wAParCDdQCu9dEk6+IBzGVuwXOvbgJGcUjlzI9ttQbt/SdXPK7qNafBjbNi1wHWSpbqb+Ys92nZvDTQ/DDPc/BHDI+cud+XXLCvpDczyyAjeZZh/80T/vBjfa12Wfw9p6m03oJ0zi9/1/XKbikO+vLe14lbnf6m67/Y17FcLU/uR3gtbe9MGGT3ziE3zXd30Xq6urCCH48Ic/PPXce88v/MIvsLKyQhzHPPXUUzz77LNTcTY3N3n/+99Po9Gg1Wrxwz/8wwyHw6k4n//85/mmb/omoijizJkz/Oqv/urNtw4QlQalbpD5GutDxWdezPjKVYstKmjdhEqV7kiyvuH4yvNXuHJpyJWL6/TXx4yu9DClQ0pFICSxlqRpzmCYM+iOufBKl81uxjDxSN1ikHjWLvfoJg5XadMThr6XuKgCQYA0nrlqjVq9jtISFccE7Tr1uSZRLebi+oCLmyNeutbHOk2tWaOg5NrGFmtbY9Y2Uoa5piwkQ69AapTIaVQMWZYzGuUYEmqB4tHlBmcXm5xajjk7X2W53UQFFTYyTdyqcmapxdkFQ1wJGHhJ10dkVIm1QWhNICRag9QZ1aokjkKqnTniuEo2KrDdMWVSEOgIspIXL10jEiUmgFBaVJGRFRbrU6QrUUZiAkNkFINhl5evXmVQgtRVOo0KzSikyHLmaw0eXF5gvt1ioVLj7GKVRmjIkoLFWoWKMThv8FIjhSO3BUJFBKaFliHelvSGGcm4JFAhUltirak321wsHE+/OOALlxN6gyFFlnG5P+bPvrDO5qCgICBqdnCAL8Zo5dBRlbDSor1wilazyvLZhwkqy1y62qc7SrnStThdZb5Zp9kK0PUq40SxvmkRKkSEilGa4pxknDte3kwZ5iVYQy2uUa80aDc6nJ6rMzdfpdGOKZSguVDhzEPLLC92uNZPeaWfIrxlvhkifMbzL36Fy+sbPPfKC6SDTTyW1FqCahMjDShNUXgyIekmCcNsiJQFlpJxnpPmJRu9MUmWkGWOMvNsDhJCoxkljsE4oxxnbA7GKCWZq0aEsaReiSjd5AJhIwWB9EhrkdZTIUYYgxACa0uU0wRKo6Whoq/rbu41GvJqMLVLY/9nG4edvbp1lkTsz/4EB1KOY7ym8zu4hL0eOL6sI7p1z7PDnkxwM4vuURrnI7v3kCKvBx9Xa44I25tuJprd03TkwLDfKSHk6Hfj1nJ7FXnd6JW4ycyOdrd+jInpdYM/lmYdjmMWkd0YxynGDsvvZCWfGLf32Nk9h5sWqEajEW9729v49V//9UOf/+qv/ir/+l//a37zN3+Tp59+mmq1yvve9z7SNN2N8/73v58vfOELfOQjH+EP//AP+cQnPsGP/uiP7j7v9/t867d+Kw888ACf/vSn+bVf+zV+6Zd+iX//7//9TTcwG21OHDUkA7K8YJCPGBUl1xLFlS3LXD2kphNsntBeXCSo1cgLT+oCSm24tpUyyCxoRYankI6N0QBtwIuMUTqiOxigjeTs6hz1agUjFb1xwmBYcnVg2RrlYCI69SrSKHTgqdU7VBtt6vUqRsWUQhKbiHqtiisEL17aYpAJrow01wYho0QwslCthMzNhQRVjSkLlNAomxAHimajRr3ewnrFeq7ppSVWK2rVgE4Ay7HidDOkU4vwErwIMFJRCQOWaoZK4EmtZly6ife4QiKUwcYBpVHEUUCnbphbDCiVQ6qAfj/j0rUh0gRU6g2WF5osrnSYm2uidERkqpQ6RImQ8SihyAtcEBBWmyglCbUgiiuoSsyzV/t86rl1nv7yOuPMkznHK9f6rG31GZYTJxLWOaQC60GhcM5hvSPBkbmMvMxw0uN1gCBlazym3phcXjqnDWfqMVjHOPNsjnKuDgq81uSuBJfitKAQEi8rpC7CZ45xCYMyxas6hZXkKMaiSX/kUNZRiSLarTbIiEhXuJZ5VL1G7jyXLo3ojyQbvYKtscMHMaMy4vxWxpcvDahIhbcpX7rU5bnLA5RSlM6zkZRcutSnHkV8/WOLvO9t51ieb1Kmlqw0vPEtb2KxVaNaqeHDFuNCkJUZNeXxEsqiwKmQRiUgCkOciBiOHOMs5crWgH5aIp1iME5YH6WU1rM1ynlxoyAvSmo6oD8cMRwMuNZNeWVzxNWtIS+v91kfZAzGKYO8ZOigV1gG1uGEwCPxUpAIQa48uRd4X2L3XER1r9GQHQvFrbKwN7OuHC68HI6j63OCEsWe0o5kYA535307WbCDWtuDZR2dcu/nZsr0x6Q6rMTrsY9q+5E1uCkG8ZDIByTjVzMT73Hsa/a9R0cOacw+oWpa4D4mzUn0Icfi9gtSt90ydRzxub3VP74Oh2tpTpbumHh7N0keiL4vwO9LOU0Hduj4zQpT++nIa0BXTiqz3eJ47iTZvxrcKQopvL81H0oAQgh+//d/n+/5nu8BJhqh1dVVfvqnf5p/8k/+CQC9Xo+lpSV++7d/m+/7vu/jS1/6Em9605v4q7/6K975zncC8Md//Md8x3d8By+//DKrq6v8xm/8Bj/3cz/HlStXCIIAgH/6T/8pH/7wh/nyl798orr1+32azSZPfNv/gdSAK6jWGqwuLVGtVwjw2MKTFh5bqRJWqtTmmgipQHmG6wmgqEWGHIfPc5I8o77QYb4Z0azFZEVOXuQEUqFNwGZ3yPqla6RpTnc0JHSC0tmJG3IEDotVhmFeYhNJEFoi6WgttHE6pCYDbFCio4iaEZRZQVHCxuaAwGhUkZEnJQQhPpDkSY98lNKMDe96wyqVWo3cBlzpDnlhY4zwEAl445kmghKtDFtJyqifMCocznm8swgnGRUluYXE6YlbeOGItGRsNXEYkFrLYifkwdOLzC+1ITA4UVDmJbbwjNOS8bCgWosZJSm99ZS1Xo8sSRlmk4lflgVhpIiMQomAWGu6yQCJ4WzHkOWQlgUL1ZBKFCCUJs8yxsJzrWfJxiNCaSikIS/85DbxQFE6h7XQDDS1SFOiGVlHNVQ4O9lueaoZ0golUsOlrS1CHUw8FypJ7j3X+mPGg4SNzKK9ISsFUitKOyIrC+S4ix1dxqdDAi3YGhR8zcPzVBoLDJ1hfSunEhuaNTBRHTHust7ts54IyiJnabFDYQ2j7gCcp9Oqc3quilWawCjW+wkKwRtX53nbQ226w5z/6+m/QUUxjy40iCsBo8yy1huz3rfkMqLdrKJ9wUuXNymERihFGMaU1k6cQkgJ3qO8QygDviRJUyKtCQKDLy1pkSJVSCMMCSPNOEvJC4EwGuctpRMoClLnKTwEdrIdNAxCAqVIvcR7B94hco+XFsjxGKxXCC3QHkgT/uv//8fo9Xo0Go17iob805/9FcJo4mr81azhx7scuHULyuGs1zF7cg5JdJQu9zgm6ebdJZ8cN7bXTZ+eOlDPY4w4R9d77/J8dM2Osw8da3S4lf2CU2nuV0Fqut+PamWWpHzoQz93gIbAvUFH/tX/+S+J45hpRniq6ftwon3Cx6Tfl+xunz5HkZrjtoPdoE2H38kFBz3dnLA+h9XlBsdRrz8/zFXGCYQgf5hANV2QuP71BLjRZLiFyXIjy9RhRz9vg0B88rOt15EkCT/5Uz91KB15tbitvoxfeOEFrly5wlNPPbUb1mw2eeKJJ/jkJz8JwCc/+UlardYuAQN46qmnkFLy9NNP78Z5z3ves0vAAN73vvdx/vx5tra2Di07yzL6/f7UB8BEnnOnOzz68FnOnV5iPgrQzhJJQRQF6LiKciCtQ+U5iolThbCqqDYlraZhaaXFqdNzrJ5eYmWuznKrTq1WwQoIwxCH4pVX1uht9jAKXOpoKY3yoKwBL+iXBf0C8AXtUNFoOqrGYcuSzfUxvVFJ2Ag4u1gh3epx7UqXzX7OZlYyt9yhXtcUEhJpGDrI04KRq5KqFpuiyZeuFVzpZeRlQqvqeWS+ykozIgg1F66NOH9lyFeu9Oh1LYkIQUbkdiIw9S0kTuGkoBmWNIISaQChiSqaYZ4hpWKcWT71pct85M+f5ROffJ5nv9hlY71k0M/JshxbjPnc55/jM599iRe+cplxL0GZkFoowVu8c4jCkQwSxoMueVFQNTWWWiH1KEIagdaSa+MRL69tMBqljEeWja0SSkm1PgcmIC1LcI6iyMhGXdxgHekzUjwFAnTBgx1FswaekooWvLKxztVxQlJkaGcZJilp7kgzy2BU4kpFL5f43KO1ROoClfcJi5KWMNQqLUTjNNRX6fqIoLHCK8M6hWlTa8/R7MR0OlV0VCMrcghjolqdx1cbVAKNzT2jUUqlFrF0ZgndavBK4gmCmNOdCl97psOpjubBB1q0qiHVquab3/4g/993P8o3vv0cb3/sFG86O4eJYjrzNRoBGCxZ6Vnu1IiNIjSavCxxtgBXorFgC6SQGCFBKWphAFJirSC1OUYFRIHCuQKbFygvKMoMO+pT94LFQKGFIZYhC5Ua880Oi7U2kTQIJzAWtC2R3uJ8iRMgZUgUGKqhoRoYnLVYezKydzfSkOu4eUvVYbrEk8S7GexPd8MdfkfkcXy9Dv47LNaxFbsJTGsb/Z7w66UfaxXa+/+REY4q9fiaHRdjqiduOKh3Tp962Jy5cdhrZRY4QR/cZBfd3XTkVnFM3x9nETnJkB1nOXg12G9R2mNxOfGQHtau/RkcVo7YaznbGyiOTnOzOAExOEgvrxd/bJkn7KSbE6Z2Mj4pbpNJcG/yG2R1M6W8lkq9W8FtdUpx5coVAJaWlqbCl5aWdp9duXKFxcXF6UpoTafTmYpz7ty5A3nsPGu32wfK/pVf+RV++Zd/+UB4TpNL4wZzdUWjWiNN7OTMiKoSVSOKQUGZp6TKIXopoRWUQBwqrCvo5wGRttSjAOVzBv0RNncYk5PnBUEcMRj26fZGXFnrolWExiOkxxUFHs+wFOQJhNoidMDmOKNV0WSZoJ87EAW+N+CqgfEwAKMhT2lHESsLLfrZmN5IYEtDLXb0R5YiTQiMIkXjpODSRk6/X1ALQ+p1xWqjgnEFK82Q3tiS+skFs8o7pLVsbbsYT3LHqJx4xwukp1tIxnmKUiEmlpxabbPVHaCsZH5lkSBQOJ9x4ZUNXCkYDDMatSpREKClIowSxnlK7iRaKsZpRqDM5IyUdlgshcgJtEZrAd4jZUTuQQhJM9TkTjK3UCGSijRyDLZSVMUwSMbkeYpAkSsFQhKYJpXAMPQO6yTWg8/hSmYnd1qVOQObgdKUKDa7KZkMONWusjW2DMYJo2JCuUrvCOIKJg4oc0VuHYGHwhVk4yFZMaIaRnTmzlHXCamVvLgxpJaMqASGZjUEITGmSjYaomjhlKDSdIwHKUFQpZAB/aFD+SFhrNnsD9C6ST0KmW/OUwwtL6Rj+lnBhWs5X750jWYkwTv6qeDSsMSXBcYIit4WmRXUW3WUckgt8U6Q5QLpS8rUoQQU5BTWIjzbd01NhFecRMYhVmhKW5IC85GhoMR6Sb8YoF2IUDFGSqT3aDHJM0egpCAXnhBD6jyR8eSBIveeMrcENsHEVYIoosTdszRksgDdPhXv/pxuZPE4aak3jPda8MLHZHwbFZE3KF3s/XHiVK9uPG/cOr/36SFFHVDq3tBAdtjM2ZvfEdr4I8o8qqjXkkU5XpF9+96xu5GOTAum+3Bo02/xzbnZbryhAuI245D67SggbnTB+ZGYetn2lXUrOEk6f/Dr8ckm9pSduB6BOKre+14U4Y+ZP7d93PZX6qRS3e0r/V7FfePl72d/9mf5x//4H+/+7vf7nDlzBoMkIKM/CDFuhHKeHE/kEsqyhhcKU5FIZxkOE1qLTfrjEeO0pF4JiSuGIJxcWlq6gkpkKLIM53JG44SLF9axWUZ/NKbeaCBdSZmVeOswQYRyJXPzDYajMcPeiH5/RFIWWB8iVEjFVNkscnLnubjWo1YNWVno0GwYytJyZXODZDjC+hAZeIaDnDItkUhy73hwoUazatgYZ/RGBdc2hqhNuFAtqUg4s2AohKc3ynE4tNQkY08/F0SBoFlV+FFOYQOsEBhlqIeKVErGZcHaxXUq9QBXpLxy4QrVRpV6PaRSqxM1qkil0YGkt76F3PYsFwhJpWkYbm2BgyKC0qYY67BCU1HQjDxxoFgbZOSlZ6Tg7Hwd4cdk4xKEIMlTpA5oVxW5g36uiaMGJtAMM0fhPFJrbGFpCsfYORySQQlKetLeCKNDjM5ZrYcICqKqQSuDFAInYJwN8dbhZZVQKEqb0+uPcYVHYrHeQjnEyBxlU+KwRVEqrvQSHj4bcDqusrDQphkb8nFK6kpevLQFImRxrkZFK1YXW0ibEMuQQeHJvaM3ypBKsVKLqIaSQV6yOSqJIsliJSZJHIvNgItXtnjxasqZhSZxICAbYoIKyueMrcIrQ5qUVCKFc5KsLIljjc4E/aSLVAqsYK5WRQqFd4qBd4jMUg9ilNYIPEZrstKSFSl5kSNVQL09h0ZM7tlKc3IvoPAUSUJpDJQlzgtK6RBCMbIemTqUL6lEMQWCbFuQc+XdTyaPoiGHcRyTJefwNk0vfAc3edyIqX1txLbbkd+NcCvl7ZciDpMqxBHfT7Rb5oZl+wlrc4Nc9j+/OQ7i8HqIg5HE4czZbvo9W5V2v15/eGRtr0c7ql8PC7/RGBxb0yPK3/tb7HujjlFc3Lwa/o7haDpy9NhMdaU/vGdvCTfK4DXs0uPacFva9VosKTdZsUOrsHe58PsUPhy/ZfjYeu15708U8dBKcSul3wbsbffBNfFYjdO98doDt1mgWl5eBmBtbY2VlZXd8LW1Nd7+9rfvxrl69epUurIs2dzc3E2/vLzM2traVJyd3ztx9iMMQ8IwPBiuRizWYlyRMU5zdLWCURKHwRaGkpKwzPBhTFStsLm5yaA/QukG5bBk7eqA7maXxfn2xE154SfezuoRYWQ480ALrQOKvCQ0Bl3RXH5ljcHVAVaCHw0phj3KwuNDg7SOaqBpzrXxQQBJSpE6ImnwoaIoBNe6Q4KwgQwDrHV08xTrcpzTJE5SAMJ64jDk5d6QdGiwoqQdwVLNTJxOmIB+4riwNSAIJWWRsdhqcm2rx7hwoAIK58kKSV4aunkOWCLlMUIgLHjpGSVjsiwFFKXI6Y8ztoYxqbWsXe6RlwUtLcjyjLASEIdV6hXBOO1ii4zCKyIqCGHIlQObk+c5faFp1+qcbQswMMpKrgxH1IDFZoU4NIShQRqFUoIX18eUWPqJwjiPFIq88KjRGCsSUqFRYci4EAgpUKUjigRGKUprkCrA4djKLKnNGThHJAwlddr1iFpFcmlzTJKXCAdIS1nmjNOUqg5ozzdgSzIYDlAoIiVZ27CEYcalq2vMLS9QCQTVOKZRF6RZwWZ3yEtJjjAxNVNS1Y5GNSBAUglCOrFBC09kIs50NL2kJE1yMudpBQpdMXSaS9jcsZXBWq9gqSO5ljvSYckod0SBnYynhDg2COdJxgXgiGs1Sj+xtHbTAiMz5hp1lNNsDkesJxl2rJDC0QhC4iikUm0R1kryQlB6zzgvMXgKSlzuGSGIw4BQaBIlcaUgFR4vBVXjcUiyzJOlI3pJRlg6VBxTcrJ7qO5GGjKNvcT/JJR+vxXh9cT++h3Gzr2KVevAOrhP2BE3au3RgtJh/XbYTpEDS7NnV9I4+XYQcTSje0RdDoYejuOF60Pi7dV6++1UR/BCx51+PrqOR9X6eLb3cNHq6DTH2dGOw7E2tpuYonc/HTkCh1huppp9ZB/sEXJ3pWwxncHtEkKO49kPnXj7FQcHEx+w5B7Szr3JjhVLjmvjqxLM/VRSf5ilTexEEdPxbyTjnOCZEMdldtKMbyXdUeGHCUa3Ws4hyqUDxe2ZHHepkHVbBapz586xvLzMRz/60V2i1e/3efrpp/nxH/9xAJ588km63S6f/vSnecc73gHAxz72MZxzPPHEE7txfu7nfo6iKDBmcn/NRz7yER5//PFDTezHQZsag8wQVQ0dY8itJjTgnSBshvhCMhyNUbkizwracy3m5+dpdhqsb6xT1QGtUw8w3kqphAakByfwXnCtOyK9NKDZqBOHnkIH2K6lKjWuYli7dJWqLEGEYB3KSbwDoTVXNzZROmBhbo5a4KAsUdLw0AML+LwkS3I0mnFu8V6SFBZXeBIMsdZkRZ9hUdKoGqKGocggc4L1wcTbmnUZOEdsBFI6vFL0ukOywtM0kpycmpHYwuEMxErgVIhxktKXBDhGlAxwhMKAUigkMjDMzzVx0hNKweXuiCvrXdJRhs5LOh2Bco6rG0NMpUosAypKkzmPE4oMAYSURcEXXr5KxYTMRZJ6HJDZMdZLrJXY3LGelvTSkq3UIRGgBFUpcEIgrcc5izAC4TWFh9JbRJFQDQMaVY33kmyUMExzeoMhi60WRgtalZA5pTBKccFnDMcjoIorLcqW5IUFBSZqEcoxBdDPIAgbFOUGthwzHA2JUkF49gEkgo2NPmWoGRsYJzmxkZgwZLER4VAY6Qljg9SKflJyeSvDpm5yt9Sgz8ZQo9Eko4JRNqCwjmGSMioto1IglCEvITaecVJQCSJadUVpPcNxTu5yBlsjUqHxKIzRRNowKh3eO7QRFLbkcm+EkxrtPbYoKLMRwls2PYg4okObSGicCZEC5loV0iRDDoeU3qNNSGQ0wntcVuK8J0RA6bASpJDEJiYtHJEEUQkQQUCenWzL391IQw7iBpzJiTjuW7Gt3MiKcoPkh6/SN6jHvrymmPsjFnh/WOSbwBHJTsILTnjJw8Svoxb/m3M0stcidKBbdo1HOzppP53yFviPSXm3rl3ecR194jbe5LQ7sjZ+39fdPMTBZ+xlFo/O/GZafnfSEQH++qavyZy5Pg9P1r7t+FPShdj+ebg46vfMnwPzckcBcdik3p/Pni+HTQm/b7pPDfm0KfUABT2Q3w064+CrtDOvbtCPflt9sme+HeWXTRzzazp8uj/3WmH2X3o8Jdvut0Rua0/2e/+bfNkryR1e0+snS8WhMoffNya3TJ/99Ew7dgnZ2zUnLW5/v+z/jZ+a0zesw+uImxaohsMhzz333O7vF154gc9+9rN0Oh3Onj3LT/3UT/HP//k/59FHH+XcuXP8/M//PKurq7ved974xjfybd/2bfzIj/wIv/mbv0lRFPzET/wE3/d938fq6ioAP/ADP8Av//Iv88M//MN88IMf5JlnnuFf/at/xb/8l//yxPXceUmEihjnlt44oaYUSof0K4Yil8hhgreeqBrSqNWoVAMuX7pMu9lkczRgsJkRS4UzG5RJRr3TIc0yKnHAOPDU4ogwMNhxRi91YIes9wcMeymhL/BekJsCUST0khItJak36KwAqcAnbFy8iNOapcUmnbqhrlL66ZiakqRFikgdtVDSqmteeXkdWUhGgDYgS8e4Z3lhc0zhHa2GhtKRCYcTkgKHRbAxzKhFknFeMhhaqkYQxYZrXmBLcL4gNAFCpoy9JCkFdUqqgacWBsSdJjjHZj9lPN7ii8/1qQXRxNmCtay06/hahSLLyMcluS3QVqJyhwok/WECtsDaAmkLnAkxgSaOA6wtWRsm9LKAKJYo73nxpT7GCRAa6zxSeAon6DQqSHJ6w4L+KCG1GVpO7jpyQYz00IgkVSHZHIwJZEie5fgipR0ENLXDupJLr3RxwmHQ9Md9BqMxWzJAVwNyKwhQjIREJhlCqskFuVaQW4+WFcIoousjtoQjXx9htrdWVpQlzTO0LMlKiSpKXuyNEVJSrUZURmpyzkwJHl40KOFYuzpg2Btz2YRU4ojTCzWu9XIKB8I5ktyjvcMoy1JF8/IghUwhgoy13pAkycjSEYWC0nuqYQ2Eoiw0QhpSazFSIYQgFprClgzzDIEiiDUag8RSCo0WkixNCU2MzwdIqVnvj0nLHKUVobeocoAipJemCCSl93i3TSwFSJuQCoEsLSiDkgKXjhB5tvte3ms0JM3SQxaj47Sj28+OpPJiahEXYt+ifESa/UyPF7ucyk3hQK2OE2D8IVEOckpHVfHY8m+k5N5f1HTFDot0/flelkQcOl57mZDr6W60MN+KT9wbGhVuB/a2+SQK3GOElZvWAxzWtceN0R6mU+x9eMg47kWWJZPg7UG45+hIkk1LJXB9wp1gYok9/TRFP5hmwm+Uy2Ean5sV6w7L7XbFvKmSd3Qn+0WXqQl9SHu3+/3kTq5vQhq4RYh9gvEUpTyG/l33dHfISyeuC29HFzxd2hHFMG2Sm67joXTzJEvaYclOoqXZL+6K6RhHWzA9aXqdF7nt8DeJj3/84zti8NTnB3/wB7333jvn/M///M/7paUlH4ahf+973+vPnz8/lcfGxob//u//fl+r1Xyj0fA/9EM/5AeDwVScz33uc/7d7363D8PQnzp1yn/oQx+6qXo+//zzh9Zz9pl9Zp8797l48eKMhsw+s8/sc8ufixcveu9nvMjsM/vMPrf+2aEjtxOv6h6quxndbpd2u82FCxdoNpt3ujq3HTsHXS9evHjbfenfadzPbYOvzvZ57xkMBqyuriLlbb2t4TXDjIbc27if23c/tw3uHxoCMzpyL+N+bht8dbbvtaQj942Xv/3Y6ahms3lfTpQdNBqN+7Z993Pb4KuvffcaMzGjIfcH7uf23c9tg3ufhsCMjtwPuJ/bBl997Xut6Mi9o+aZYYYZZphhhhlmmGGGGWa4yzATqGaYYYYZZphhhhlmmGGGGW4R961AFYYhv/iLv3jr90Hc5bif23c/tw1m7btXcL+04yjM2nfv4n5uG9xf7buf2nIY7uf23c9tg1n7bjfuW6cUM8wwwwwzzDDDDDPMMMMMrzXuWwvVDDPMMMMMM8wwwwwzzDDDa42ZQDXDDDPMMMMMM8wwwwwzzHCLmAlUM8wwwwwzzDDDDDPMMMMMt4iZQDXDDDPMMMMMM8wwwwwzzHCLuC8Fql//9V/nwQcfJIoinnjiCf7X//pfd7pKN8Sv/Mqv8PVf//XU63UWFxf5nu/5Hs6fPz8V51u+5VsQQkx9fuzHfmwqzoULF/jO7/xOKpUKi4uL/MzP/AxlWb6eTTkUv/RLv3Sg7m94wxt2n6dpygc+8AHm5uao1Wr83b/7d1lbW5vK425tG8CDDz54oH1CCD7wgQ8A997YfeITn+C7vuu7WF1dRQjBhz/84ann3nt+4Rd+gZWVFeI45qmnnuLZZ5+dirO5ucn73/9+Go0GrVaLH/7hH2Y4HE7F+fznP883fdM3EUURZ86c4Vd/9Vdf66adGDM6cnfMxb24n+nIjIbcfzQEZnTkbpmPO7ifaQjM6MgdpSP+PsPv/u7v+iAI/H/8j//Rf+ELX/A/8iM/4lutll9bW7vTVTsW73vf+/xv/dZv+WeeecZ/9rOf9d/xHd/hz54964fD4W6cb/7mb/Y/8iM/4i9fvrz76fV6u8/LsvRvectb/FNPPeU/85nP+D/6oz/y8/Pz/md/9mfvRJOm8Iu/+Iv+zW9+81Tdr127tvv8x37sx/yZM2f8Rz/6Uf+pT33Kf8M3fIP/xm/8xt3nd3PbvPf+6tWrU237yEc+4gH/8Y9/3Ht/743dH/3RH/mf+7mf87/3e7/nAf/7v//7U88/9KEP+Waz6T/84Q/7z33uc/5v/+2/7c+dO+eTJNmN823f9m3+bW97m//Lv/xL/z/+x//wjzzyiP/+7//+3ee9Xs8vLS3597///f6ZZ57xv/M7v+PjOPb/7t/9u9ermUdiRkfunrm4F/czHZnRkPuLhng/oyN303zcwf1MQ7yf0ZE7SUfuO4HqXe96l//ABz6w+9ta61dXV/2v/Mqv3MFa3TyuXr3qAf/f//t/3w375m/+Zv+TP/mTR6b5oz/6Iy+l9FeuXNkN+43f+A3faDR8lmWvZXVviF/8xV/0b3vb2w591u12vTHG/9f/+l93w770pS95wH/yk5/03t/dbTsMP/mTP+kffvhh75zz3t/bY7efiDnn/PLysv+1X/u13bBut+vDMPS/8zu/4733/otf/KIH/F/91V/txvlv/+2/eSGEf+WVV7z33v/bf/tvfbvdnmrfBz/4Qf/444+/xi26MWZ05O6ci19NdGRGQ+5tGuL9jI7cjfPxq4mGeD+jI68nHbmvtvzlec6nP/1pnnrqqd0wKSVPPfUUn/zkJ+9gzW4evV4PgE6nMxX+n//zf2Z+fp63vOUt/OzP/izj8Xj32Sc/+Une+ta3srS0tBv2vve9j36/zxe+8IXXp+LH4Nlnn2V1dZWHHnqI97///Vy4cAGAT3/60xRFMTVub3jDGzh79uzuuN3tbduLPM/5T//pP/EP/sE/QAixG34vj91evPDCC1y5cmVqvJrNJk888cTUeLVaLd75znfuxnnqqaeQUvL000/vxnnPe95DEAS7cd73vvdx/vx5tra2XqfWHMSMjtzdc/GrgY7MaMi9TUNgRkfu5vn41UBDYEZH4PWlI/rVNuhuwvr6OtbaqYkAsLS0xJe//OU7VKubh3OOn/qpn+Jv/a2/xVve8pbd8B/4gR/ggQceYHV1lc9//vN88IMf5Pz58/ze7/0eAFeuXDm07TvP7iSeeOIJfvu3f5vHH3+cy5cv88u//Mt80zd9E8888wxXrlwhCAJardZUmqWlpd16381t248Pf/jDdLtd/v7f//u7Yffy2O3HTn0Oq+/e8VpcXJx6rrWm0+lMxTl37tyBPHaetdvt16T+N8KMjty9c/GrhY7MaMi9TUNgRkfu1vn41UJDYEZHduK8XnTkvhKo7hd84AMf4JlnnuHP//zPp8J/9Ed/dPf7W9/6VlZWVnjve9/L888/z8MPP/x6V/Om8O3f/u2737/ma76GJ554ggceeID/8l/+C3Ec38Ga3X78h//wH/j2b/92VldXd8Pu5bGb4d7EjI7cu5jRkBnuFtxvdOSrhYbAjI683rivtvzNz8+jlDrgkWVtbY3l5eU7VKubw0/8xE/wh3/4h3z84x/n9OnTx8Z94oknAHjuuecAWF5ePrTtO8/uJrRaLR577DGee+45lpeXyfOcbrc7FWfvuN0rbXvppZf40z/9U/7hP/yHx8a7l8dupz7HvWfLy8tcvXp16nlZlmxubt71YzqjI3fnuByG+5GOzGjIvU9DYEZH7uax2Yv7kYbAjI7cCTpyXwlUQRDwjne8g49+9KO7Yc45PvrRj/Lkk0/ewZrdGN57fuInfoLf//3f52Mf+9gB8+Nh+OxnPwvAysoKAE8++SR//dd/PTV5PvKRj9BoNHjTm970mtT7VjEcDnn++edZWVnhHe94B8aYqXE7f/48Fy5c2B23e6Vtv/Vbv8Xi4iLf+Z3feWy8e3nszp07x/Ly8tR49ft9nn766anx6na7fPrTn96N87GPfQzn3C4Bf/LJJ/nEJz5BURS7cT7ykY/w+OOP39GtOjM6cu/MxfuRjsxoyL1PQ2BGR+6V+Xg/0hCY0ZE7Qkdu2s3GXY7f/d3f9WEY+t/+7d/2X/ziF/2P/uiP+larNeWx5G7Ej//4j/tms+n/7M/+bMqd5Xg89t57/9xzz/l/9s/+mf/Upz7lX3jhBf8Hf/AH/qGHHvLvec97dvPYcXf5rd/6rf6zn/2s/+M//mO/sLBwV7jz/Omf/mn/Z3/2Z/6FF17wf/EXf+GfeuopPz8/769eveq9n7gqPXv2rP/Yxz7mP/WpT/knn3zSP/nkk7vp7+a27cBa68+ePes/+MEPToXfi2M3GAz8Zz7zGf+Zz3zGA/5f/It/4T/zmc/4l156yXs/cVXaarX8H/zBH/jPf/7z/ru/+7sPdVX6tV/7tf7pp5/2f/7nf+4fffTRKVel3W7XLy0t+b/39/6ef+aZZ/zv/u7v+kqlcle4PJ7RkbtnLu7F/U5HZjTk/qEh3s/oyN00H3dwv9MQ72d05E7RkftOoPLe+3/zb/6NP3v2rA+CwL/rXe/yf/mXf3mnq3RDAId+fuu3fst77/2FCxf8e97zHt/pdHwYhv6RRx7xP/MzPzN1f4D33r/44ov+27/9230cx35+ft7/9E//tC+K4g60aBrf+73f61dWVnwQBP7UqVP+e7/3e/1zzz23+zxJEv+P/tE/8u1221cqFf93/s7f8ZcvX57K425t2w7+5E/+xAP+/PnzU+H34th9/OMfP3Q+/uAP/qD3fuKu9Od//uf90tKSD8PQv/e97z3Q7o2NDf/93//9vlar+Uaj4X/oh37IDwaDqTif+9zn/Lvf/W4fhqE/deqU/9CHPvR6NfGGmNGRu2Mu7sX9TkdmNOT+oiHez+jI3TIfd3C/0xDvZ3TkTtER4b33J7dnzTDDDDPMMMMMM8wwwwwzzLCD++oM1QwzzDDDDDPMMMMMM8www+uJmUA1wwwzzDDDDDPMMMMMM8xwi5gJVDPMMMMMM8wwwwwzzDDDDLeImUA1wwwzzDDDDDPMMMMMM8xwi5gJVDPMMMMMM8wwwwwzzDDDDLeImUA1wwwzzDDDDDPMMMMMM8xwi5gJVDPMMMMMM8wwwwwzzDDDDLeImUA1wwwzzDDDDDPMMMMMM8xwi5gJVDPMMMMMM8wwwwwzzDDDDLeImUA1wwwzzDDDDDPMMMMMM8xwi5gJVDPMMMMMM8wwwwwzzDDDDLeImUA1wwwzzDDDDDPMMMMMM8xwi/h/ANsUJdeXWem7AAAAAElFTkSuQmCC",
"text/plain": [
"<Figure size 1000x500 with 3 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"num_images_per_prompt = 2 # adjust according to VRAM size\n",
"generator = torch.manual_seed(29) # seed\n",
"\n",
"images = pipeline(\n",
" prompt=\"a [c] in pixel art style\", \n",
" lora_scaling = [1., 0.],\n",
" guidance_scale=7.5,\n",
" num_inference_steps=30, \n",
" num_images_per_prompt=num_images_per_prompt, \n",
" generator=generator\n",
").images\n",
"\n",
"content_img_path = f\"data_demo/content/{content_img_name}.jpg\"\n",
"content_img = load_pil_image(content_img_path)\n",
"\n",
"_, ax = plt.subplots(1, 3, figsize=(10, 5))\n",
"ax[0].imshow(content_img)\n",
"ax[1].imshow(images[0])\n",
"ax[2].imshow(images[1])\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Use style LoRA only"
]
},
{
"cell_type": "code",
"execution_count": 245,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Loaded lora weights of the style image from chenblin26/ConsisLoRA-antimonocromatismo\n"
]
}
],
"source": [
"# adjust image name according to your needs\n",
"style_img_name = \"antimonocromatismo\" # see \"data_demo/style\"\n",
"style_lora_path = f\"chenblin26/ConsisLoRA-{style_img_name}\"\n",
"\n",
"pipeline.unload_lora_checkpoint()\n",
"pipeline.load_lora_checkpoint(style_image_lora_path=style_lora_path)"
]
},
{
"cell_type": "code",
"execution_count": 250,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "f37e7bea9ad148a7b552279d374d17f5",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
" 0%| | 0/30 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "2fae4b58000c4e2c9494259ec8f3db84",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
" 0%| | 0/30 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Loaded input image of size ((512, 512)) from data_demo/style/antimonocromatismo.jpg\n"
]
},
{
"data": {
"image/png": 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4xDtSvyE5SwyB4h24llzvs5112OUSrKY0X4YP+Zmo4TVNwy//8i/zW7/1W4fXcs781m/9Fr/2a7/2536+bVtOTk7+zB+AGDNG7CFjD2HShR4S4zgRs2B8Q8iJYZq4vbqFtiUvOuavvYTrmnpABWKM5Bi1AhmjBplmXztGK2BkJtHDPe0GbNfgTudkowf5OI6atTsNEqy3xGliNl9ibaFM19BA0zrsdAVxS9lekXeP6CTDtMOmAe9n+OUp7byluJGm6+jmF9yuB8bNjjwOjMOWYgtTmTBNQ/Kek1dfoR8CcTtAKpizE8bW0jYNYbvF5EIJA9fv/hh/fkqcErEPsJphG0d2hmY1J22vIe+wM4vvCn4xg9kFbrakmIlYBkrXIM4jBdK0hWHH8OQGmTLGz3G+0YpkHBFGjCSca4gxM46plnC00mGwkCDWqqoYCwWmnMg5I7lQQuD26krv52LOS2+8yuqVe0zOsg2BxfkFi9MzZmcXNCentN2ck+UpFmAcOOtmnMznWGsozhMQimvpmhkL19LYBucN237HmDLWeNqu4+TiDqVt6Dc3pLFHGocsV5SzN2jf+Bv4B98gGUsOEbBY22ilw3hsEeyL1kCtoJtD4H2oKJV9qsOfS5Tyn6nA21rRzfWzHNr5qImMgSKFXP9vnyrtnW8qWZN/BIqH4hAsQtGuCI59bmoEkEJMgZTjoTJcanVNxOLdDOc6tM3407X/Wh/ynzKpVTlvHd5oVw0EUzSJLUDMiVgSMefDM8m10ik1mDSA1HtshMOzhlrlR5MqKWBq0kU9kI0YStZKvC16+KUCsSRCyvW7tBiUi1Zetauir+cCJUTi/s8YkAy2gCk1ec65tiQTTgxODCL2UHk2IkjWQNmaLxw2pdYqSmEYA1PStZtSISZNqihogUDKvjGpiT3qGxtrNAAXwQo4sbVAUBP82vUpSRMMkVy7FtqpMoBFE1FKxuy7skUT+n0Arutb77MzFhHttcX9faodQVer0LbunYR2s1prdH9kffY5F1JdAyVrdxB0Tw3TRMoFm8EjSAJf6k4uuRYuQMToc6/Xv28+llq51jzW1oRE930KkbGfSCETY6RufMiZXFLd3XrPc9bq8BACY8qQaw5ZtPLMF56/rV0xKwUhk3OkkHVN1k80Ao31tMbisDi0Km5r73Lf1ZYvdsrhsEYBTaayFgNyLdRoSGvonKMR7cjqCqiFh58B5+cvy488e/aMq+sbLl5+ieXJHFLEtw0nZ0saMp13yDRy9aP32H70CXkYtOMw9VhbiCGw3e0Yx4lS0P/WAppBO5iLxRxjLCUExBuwQglBk6ESSYOe+2m9IV0/J91cqW+v8UgphWIN0jgOVTqBEiOh35GmkZwytB0yn2NOVrjWYxqPa1tmF6eIFBbnJzSdIm4o0D+9ZLp5zubjD9h8+gmLO6dcP3nC+uk1MRZFlBSQWYtYg7MOcsB1M1KKlOIoU0SGG6RE8maD3DyjrG9pvMN2HmMhh0DcbJhurpg2t+RhJMVUfXShlAgpkFLQM1REkwwEMfZwnkLdZ2aPmsiH7s2LROgLVhIlZ/VNUYtdCfXbmX3jKVJSoJREzomUAuM40O92+r5a/CJnvR5Ek6F95SVnyC/O65wyJRf93n37fP/3ov/d+0xT4wpq8WLf2Sq1wFYqjEEMWnwy6l9d9U/GCFLjgjEknKnNgXotvmkYQ8AAKUe939NAiSPGCPP5kpISq8UMsYZtH/j0k4958ughMYb6jCIlRahxjkFYruZ0d07Z7XoyEdM62tUS5y1l3GlnL4wUa0hhJNysSSEQNzskade/GIO0DcVZwjiyu7r+r/YB/6X2M5MO/43f+A3+5b/8l/yrf/Wv+MEPfsA/+Af/gO12y9//+3//v/gz4jhiYsamTNj1TLuBHNVJp5iZ+omYC3Y5486bLzO5QnvnVINx70jDREmZKQR1EvnFFvniIVCKtnttFkpISMqM2x5vLQaBnBmHgZQis/kcY622RAXEW2TZMnpHefll5j/3bYpkdpef0IwjZf0UJ4EoA6ZxFGPJjcGdnBFNJLcZf7KC2Qnt4oQQtgzTyFQspVi6bo44S/Pqfba7LdPT51iBQTLNq3dxbcPm8TO8sWTv8MslLz14iXx7Q3PiWZ4t8RdLZncvGKYRs5rRvnQfe7KgtIZoPXZ2Fzc7IfqErFa4Zo5zHdlm8jQSt2vitidebxHxZNeQCMQQMGUi5IlihExLiAbEEUtiDDvCNJGmSA6ZFBLTNJFiIkwRpGAESgisL68o44StB7WZt6TVDLOY056fs3r5Jexqgb9YIfOWZCzMF8zu3Kc7vSADbSmcuZZX79zn1Zdf5ma7ZRKLmc24e3bK64s5M2/pp0SxjuXdM777K9/l5TdXuOk5ZRhxyweki2/iX/lF0gBht8ZLRFoPjSd7Q3HyxY46XwwB/kPxyT9TAan/lCsECNHKV97D9uoPHKrwpZBSBPIhQE0CU8okhCx7GEBdw1LQsDAikr9wEeZwAbrm9V0xTuyGrQZ0tsL86rrOpWB9Q0Ho++G/eM/+Zdpfhg8BSIBhD7+1FUKlQf8XYW77A0wOsCbq4aX3PpeM1MSXokGpq8VGYwzOVphehZkY0QRAStakCe0ACCjaBPOFgD0Tona5Ys61wq/vUX8X2e160hQgw7Ab6Nc7TClYowG7MVrVL2V/XZmUIqno4ZULYC3Z7rtW+l1SoWQp6vdNUyDk/XUWTa7qgW7q9ZSs99OLdsFy0Q5MKlkTh9og1URBoWP7hEevRaugujsUhmrUGWNq8G5yxiGYXOr376Fm+t6Qk1ZZ62eVoggk6s+Uop0uEfA1iYhpXwwo9U99fvW6KHLYnzFldsNUn2WFrIoe4lKzilLKi6QJvReuVpmtMYdukRQNu1KIDP3EMEwM/ch2syPHVPevXv++06swPA1eUtI/e8imebFstYNZ9LtJCclZodO1Mm72XaGiz9Ebi3cGYQ+j24c4agoD3pdiXhR1qPcl1wAv1dc1cNVKev0ajGjQbIqgObzw0xJ1+A/tL8OPTOPIuO25vLoEZwnThLcWmSJNTrDZYMeBTqBdLSkIY99TciSHwG694cmTp4duXwwBAcLQQ04VRWAoMQK1KxECOUT1+2GiNAr3LcNA6XeEp48p44RYRTjsu92UAq1CorBWuychINaSpYCzmJMTStMincc5MAb8vKNdLmjmDbOTJcQAVrAW8nDD9OQTnvzRH3L98CFusaR/fqO/h9eOTk4Z03akMFJMAeuwTYedtVgCSKZMO5yFNI5I6CmbS2yckDxiW4ebtdimQYDUD4SbG9L6lrBdU8ZJv0OMgpGN1LqX+rNpu61JjxYHpBYs92fa/r/7jrsApa7JWp4iTiOSy2H9l33Bqgbuh9O+FAyCc+5wXpQ9tv4A4dYOmP6phYf6rEtFLuz3s57h+wLoPunTc+NFDFELNbUI5ayllHg4r8kFJ2hjIGcMBVsTRP1uTdJCSKSUGcbINCXGfqTfThA16SsxkEIgp8iq85xdnCLGsJx3UDKNM+SU6HcjMUwaD+8Dkb1PNcLJ3QvuvPYyt7e32GVHToHWO5zJmLZVPxInXf/rDdosNNimIadAmaKiEuYLbNsy9T3T7fa/2Q/85+xnxln6e3/v7/H06VP+8T/+xzx69Ihf+qVf4t/8m3/z54iW/0lLmbjdMQ47hr6niGVxekqh4AvgCtYJy4tT5qcnzK/PcLbBjUGraCkRp4kYgi4eUWy6iByw2FIrvgIwJcp2IHrHfLng5vk1p994DWIiTgHvHN57UkqH7oGxBpm3xLv3WZ3fwzJj9u03uf3R/5s49ZQC0UxI52EsGG9wviWEHucLGEfIgmkaxmGLzYKxLW62wHctI5nuwQWZwvjpM4p1PHvylO7BORIit+98wmI+w56tSLMWe+cM5g3l+VPc/VNun17R3b8DQ2EWenK/RToDXggh4MxdijgoPe1ySZAOmTJxvcGfXRBki7EthUAatuSlwblEMY6u68glYf0JxS3pQwI7I5uCtYY0jaR6aJOjwl0aR0oB5zwmZyRENlfXSFS89cfvvY+1jntvvYKZtczOT0mSsX0mTZoIlBRpfEM5u4CzC+J6w+bjj2AU5gh+mCjW8erd+zx5+jklB7o0ccpIagRcS7GZ89fucvrmKWUJOXfIYoG7902a1R3i+iEkB60jRotZ3YFmQS6OfVM/i5D3AfcXkqQvQvGonaJ9FShnDUCkOuG4X0vwZ7pSh4pQrZAXgSFMTCHR+IacNGhxtfVtD90s/VyRvK8Ta7AmLwLHepUAeN/gnNMg8eC4K2zMClOcSCX+N3qBv5j9pfgQNAkSatCG/gkxkWoguH9GtXJCTuXADiq8CHb30CbQzoY3VjubFWfvEDBOoXhGKFnqvRPMHotfL8CLkKVQMkwhI8ZgJCFOg2xBDhDJUgopJmIs7HYbcox47whRf6/ZosE1Dm8dWPVxyrkxhJK0ECSHPiQ5K8collyhIkCCFDPjNCHFEG3B2ERnHQtnGWNiPPACdR2lnJlZV7sWYAWKiB7SIjgRUq6JnGj3zlScfypUOB+YUnCGQ8XU1XuaS0KKvjcfkpKCYA7FACn6fQYhVGiOQl0M3tbnmwzG7ju6GiiZCr0jQjblBWSuwjIbY5TDUWBKic4p3HEfFSgQEX22sk8qYI+9zdROYimEpIHUOIzEKXF7tWaKEzEmZl1HIjFfzpHGamcBKDlREGIuhFgYU6rJe6qwvnzoqonZc6VKhfFy6FgImggWtLvpjKFxTu8le+6RYIollUJJiiDbN7oE5dkdPpQXXSzQ551TBiNYYAoTFMfceYVt1jWBCFPcQ5J+uvaX4Ues83z+0YdsrpfIay9zcn7KfNeTdxukFEwKLJ2hnXucCDmPEAvtxRlTTFzfrrm6uuTs4kL5ZMYQY0JipDjtkDprEWe0I5LBNJZkLblEUgA3RVIpmG6GTIFye8P4/Bld9xpi94l+RXUgtftr93hrxCosNfY9xjcY78lth4wTnkIssa7ljG21WGssyKLF5sB4/Yz15z2Xn17RPXiVV+/fY/vsEll1ev4MIzkoj0i6GdYFZBQsGeudcnR2W5LNmHkHKZIvH5GWHebsDNIA4lBIqyWJwSSQmMlTYMw77ei2HbabYb3Tde8seUzkcYCuBe8pKWKcp+x5vl+sYZoXHECT971oIZeE8Y0W16Se6YeCOoit5QNjIGWcdy8OFJFDp71kRX+UCkE+JDuV6/lFbjO1GJ/R84UvQPOVs1WLqF84p/bc5T2nq5QX31Wq77VS/612vCzVh5RCCLUTVvmEpvOkmBmGQNcZwjgxjhN3TmdMkmgaR2qbAyTSOEvTtYy7Lda4Q0tGjKndMz3PrBHmiznz81OamTDdCjGMmDwnTVush2wMjCO575UbJpmUEsY5EoKddZTZjGkYNcl0X17B5Wcq8PDrv/7r/Pqv//p/8/vDbscQImUcFIfrdOOYXJCpQpFS5PTOCgP4WUMeMiVEiIkxBSS6iv9PtQrwoqq6J0XCiyp+Pwx0zYrSOBZnJwrJS4rhdk2jVcz6mpFKJLQts9M5qZthSsbcv8/ZN75LePw5PgspB7ydkUxWHoA3JAIGTzEt4hxFEeLkBLad0yzmyEnL4mzFOAb6J2vcvfuYV+7QtR3TR59x8/QJTdcRZxb3ygWz0wukJKb1DW7mSRvP/M4ZvvHE7Q1hWiNpC9MGYsTaJSkAEsA3hCSIzaSyRfpEmnWIcTCfEbc7hIhtRiyBZFrGMGKbGdYsicUxxaQdCt/ivTClxMw7hn5DKgbbzUgxkHPUQDAnnj95gt0HFsOIDBFjCj4WovcEa/DLOTErBKHrZpRxQ4mJ2Z27jCdLnn34EenympfuXsDtmhwnjOnw1nJnec7N7RM+vX7I8rSjlMzZYoW0lhg2JC/407s0915jCppkj7dPyc4xv/c2tNr1k2bJlEqtotTgWQtOCo3bdwy+YFrNgUNyVPbJSq3WVqcoxnwBticHYrhIqYEG9MPA9XqDWEdMhc63iIGYs1bsTSWYIvqdRh3Wnr+aUwAKUvzBeVvr1MGVipcWoZREyhEMpJIYxgExhZ+V/UV9CLzovIGS/1PJ+jtXHsyeYJ9ShUyh1cFSNAEQgFQQm0EshoK3QmsM1hgFRRbtGFor2KKc+ojCHyFTG4n6mUYq76ggVohjpoSMcZoUzHxbIWgVv54KaQzcXl5ze3vLzdUNpuLS79w95/T0hNOLU3LT4FunwUA9bBuvnbS4D7Zr5JAqnMxjGHJkFyZSDMy9VU5krWDmlOhjINXg4oWEgSYoRsBI7YxmaIwhFRUnsNpeOXR+vFjEFoakhaucMlkEL4lGLClDNrkmXLyAyxSFmKZcCd9FdWucGCKprvv6mbUNKHV/yReCDodo5dMIIUEUrShbY3BGDqIU2gWBeePZTYHtOLHwTv8NgxTBGj1TpCYdvIiHDlXinFQwI0wTIRWGzY6ry2s+++QzqMHR+cU5p+UMZwRnFwq3rV26mFWsYztFUi601lSkg64bK5UjUP3QFxMkW8whN6eUA8+psVbhObzI3UuF3FkMU8mY2j01NSmzNelVbkU5dJZUCOKFv4oVdpRyJqagyKOaKPUxkr/Q7P5p21/Uj5zU4HDYOp4+u+L0a19jPmvZ9luaxnN6dkLjQMaRdH2FPVnSdnOM1aR7N/ScnJ8RU2SMEyKGcddjBbpWE4c0TbiilX3jhGmciONITCPiG+Jui5l1YBvKNMEYCE+f4JdL/PkZuSIVKJkyTGCEPPaUYUS6hrLnwKKt57JcYncb2G1IpsVsE01rydKQxh2mURETIWtXJUcsiUcPPyNf3XDn7n/PhKHYhtw6bWfvArJaIo3D+Rlx7LFhpDSNdslCVq7W+R1KDJTdhnz1GLNaUCYwTYfYrnZGhRwjErN6m5zI00RMUFJS3nfbaCHSN7jlEuPU/2mRsToLMV9IltQJ67lqkBTVV6TI1bPnnN+9wGCRBNns94nynvafmw/cYgM5VQjq3j9WXlXJLwry7M+f+mwqDE+P4b04hDl0sV6gngQMh0J/rlwlY/blmv2Hqw92IuQUsc5iyt4RoZ3mlDFFUQPUDlOqsN2+H8mpcH19w707K6zJtF5U10Jg1jjas1NCjMy7lhIjq9WS2cxhXE3kvgBtNAXSMDKu10iI3Ll7joxXjCkqTJhECRlSRExD3u0Uep4yaZyIY8TPHW45J8+XmKahf3ZNGEbil4hy+Uqo4f3HbHx2TZh1tJ0nlETjZ5RSCCHgZ56UA7YRXGOZ4oR3jpv1FbIZaE5mtWlpD9V3MVIhJwnn7AHfakQD+xgjpuJ/8ZYSgBArSbngnKOIVvssBlMSKSaFjeGwWAgDJQss72Gvn1JiT0kTYiPNyhOJRFQ5LkpCsJg4UgRs28CsRVYz5M4Z8/tnDM+fMU4TJ9/8Gsk4hvWGh3/6DifWMrt3weylu3TnZ5hTT5gipjcYN8e2Dnu6hOWc3E+UcYuVSDQjOM+svcuY1+AjdBZpZ0iMMAZc64njoKTJ+Qo7CtePHmugYWdIceQ4IG7JGB1NcUoApkDTkqUh2oyfJ0qGdHODnc3Z7nbMuplCSFLg6uFTjLU4ZxBjWW+vkVRITmjmc/xScNYyfvYQOyTEOlbnp3TLhv6TJ4TViuaVl3jt9Iz48gP6P/k+dkhQEl3XkjolKzayYVxr0Nh5w3Jl8TNHsYlAg1ndZ7INJhvSZo0/vU85OSdIg/Vz8F6DiarORck1QYIvkufLvjKNVKUyhULtSZlIdbylUkfVF2rQUfmjyinQ9+ZahV9vtowhaBBXhMY6pKhaWcnKS8jkqkSlFXktj9mDYs4YJry3WFPqNRrIL6phh0MkF2LMJCmElFRNzDU/tT3/ZZiqz2kRJRatnDoxTDHpgZorfKtokrQ3TW6UBCtfOHBb19A5VxOFPYxDu9wpFrxUuIxU7Pued1Y/dw8Fs7VkaY1hiBECh66QFw7wuZQT6/WGR48e8/jRE66vb3QZpsj9l+4hwLe+9Tb3Hlxw6s5IU6rkcancJD1si0BMdZ1kkGLIRUipsNsObDc9J6sFgnbMS4WmjTErcT8nRAwzo4maN8qLUnU8QyBiqlBBFIgiNEUYSsSKoTFCH6LCGbNgvcdp7055UTWpTMboQV4T+Fi5MYgmSUE0GdsnAlI00S1ZyLFQbKkJgaUR8JJpnXa6cu1KuYxyvqyKS9SPxwHeguRCI8I2JWJR0Z/sFW4ilRRtzb7/aKAGNPqzmRgzpMJunLi9vuXh5494+vgpP37/Ax4/eozzlvl8zne+8zbdbEZoW2Qh7IUivBGGWD8rZb1Ou1fCMsrpypVcfkiK9t3sCugtL+BHRrRbplVnOUCSFIxXIcGyh/9W4jcJVd/SZ6QdrYOkDFXTgVILR9r9g5INYw0WU1LlQlX4+xlmS39Byymy3mxpbMPZbMG4vuV63GFy4vTeOcv5HJkiYqGkEWdOyKauE68iMecXZ1zfXKuSWNbE0nunhayiYgXTdgdurt2Okiok1BBvN1AKbTcj9yNE3f8yX9A/eog0DTLrNKBPQjaqq4Y12MYzoYXhJGAaT4kRM59TGoedtZgcmQZ9lqrS5yhhgsYjpsKBU2C4veXm6RNyt+P9H71Ld7JESuFEvAbJsbapcyDmBtoGMa0W5QwUo0URVzKl8aqIOwXssEO81U6pT+Dm7PHEeRxJw0SeJlKMuNmcXFrsfEGOUc/XFBHUt7qUKX7vc190XdmjNkCd+76CVcUbXnjyDP1OE675nOroocK3Zd9lLVWBb6+wXFmBL8pKX8zR9n/bJxV61lKvMZdc/240nqgwQCPaYc6inG8qQmW/x40oR9SUQs4JZ4QSE9loEYWcKVFjCoXo6j1SaG/GOHPofllj2O22zHzh5PSEaQy0znPnbMU46Dk2hYRPiVnbcjluasms9rlSRIwllUwYRuWHpUjebvCm4BvPbN5AnLDNjJwLJqPKd2IRycQhgDhiNrh2RnENYbOjv7pmGifG8OWhXL7SyVK6vkGcJ1CYnayIVjCNpWkbYgpYWxMbY4hjAIQ4BmzOWGdx3tG0nhKTYuaNYi1fuPs9NEMdecqZ1jdaTXOOYIVpHAlJH1AKqjpjKSp+ILqpMoXcOty4o8QdpWlwb71OuvyQMgUkQLKJFDKNmyEm4ovDWcdABt+SY6K9e4prWqxrCcWzvrzG4Fl97WVunq/xNxPD7TV3v/Ya8wcnTKUQtjvCk0eYx4bSWeTuXU6+9fUagCRII8Z7jIMyXtM2C/J8QQxPsK1g2oZSHEwBKQlpZkzThtZ2JGexJytkHcjjhrZbkkrLmAvGdjhmSkZOW4p0eN+SncfYwjhsaZpON8SiU1zzEOgvr1neveCmv6ZMCbPoIGes84dk9eSle0RnsNYyu3NOe3WjmPymQYxDtre4Uug3N1xcfJP2zde4PV2RZnOe/Lvfxmy3dM2ckAJ9HhEGTry2h521mM7CvTNe+rW/rZULgXL7nO3Tzzl59eew5y8TUtKExVWVmyq1rDCkvfOtzrCSuF/wlfZQHQ4YZeAFxIai8Ag0kbJiKXtYkSgXgKIJ0xQnUspYY7GNw/uWrm0pFKYUlNeSAnbWMhU9MIwxui/K/tsSSKIfR2ad02C4tvsNVHIwep2i708lq8pX3sP5vroWkqrP5ZyIpXJ8akC9J/drtZwD/vxw0lVYGRSMOJVkrcmHE0OWgquac7kengfIWA0ihaKcvhRrsKr3F5S/4Cp3KaUIjaWztnZohM24A7Sz+MGPP+AH3/8Rj58+pt/soEC76Jg3M95/7wN+6Zd+ga99/U2WqwWLkwXJO5xzZCnsRT6sWPbMtn0CkkpWcr+1ergKeGc1sLKG1qhoQWMt3hiMVciVM6VC3bS7aoG5dQxRRRycQJak8FtRie+ctePjrAbuoR7+rkJK9spqGVQJqdRgocIg4xc6sAm97lA0sUIyqXZQDmiCAnPjsPV6MEI2AuJ1vRtDY512HGvQoAqnMO5Vv1otllTuNiVVfk7R/to+ZUpRO4zDEOh3I7fX13z44cd89tlDvv+nP+DTTz9lu94SxoAItLOWy+fPsWL5zvfe5uT0hDxGuq6pyaXFGhWPsKI+wBmpkMoaKMEBtqPxn0qSV9BD9S9GRRzQgGgv7nEQ/VBGGLmq5KnQQ01saqfLoB3DUv++hwPtu35kU3lcWiiKlSheUUaaG3yFk6Wb9Y5pirSLjrO7Jzz7+HPCds3dkyXtYkYeR4U3lgS2IfSDIiw6hbvZG0vbNSzzikcPHxFTpmu8QkxDODyvJGDmLWHckGctaduThond5TXiW9zZGUyRtA341Yy06zHXN0yzp7SvvEJxFnJSZdxxIiNM00REu8SWQkkK2aLtwDewmCHrNdYZrO8o04izHckUxAG+Q4wlDBNTrQzGfsfH7/yIMiVeenDO2998DV876iUE7KKOq/Aes7xLjgPGdoh12OLIuw2l6Sgnp1BgunxGe/clGHYKRcs9iNNgOwcVHJgCxEQIEy4uADDeg3e6JmvxMYYJYsD6RkcIVFKWQuikFsXK3tkrBNoIFw/u65mZEzR6xkpFfkhtw+ZagDjABNinP3LoKFPSAXoPX4DbofsxhqDCDEX9v+5fLbzlvTBQDS7UF1Z/l5KiEnJVF62JnjHaIUoUpCohGmfJVRmxFCi12+RMOXyGLZkUC6137IaJtjGYvGbb7xDgbHVySDa71iMGpmGgKYHWOXbbXhMiqwJsYrTrpkIkufLRI4wTzYmnzGb41pBFu57GGMrYk4OixPCelATTWWzXkX1L//yK7bNL+ifPofGY5Zc3duArnSzJZkc5jXTLU4yxNIsZrvNaTSv6wJ1xlFLo+56SC9MwcLFcYazBe6cJkqRD1WxPrP8iEX8vCx5zoiSt9Iq15Ay79RbbOrxzTNs1M1nWgNkrJ2kcafycWDLjZk3bGQgTaXuNzGZIucIamKYtrltRWkN2OhdljBNusSD4ljIl2tMlQ8z01zfEaDDzlvnihO1VT0fLTgJ3f/HbpE7YbtbYIeHDjmQSfnUXFnOa114i5IIZgrbtGzCdbmXXriAXpv4xJd3SuEzIc+gnTM74ZUdhi/WeWFqak3NKiOSUaM8vMP0EgLUtInNySkhMlGkHrqMYB1KwtuBbrwllShTvtcIlMG52PP/gUxbLFbbxSkpGE9EsBbvsmJ9rVa67OCVerUlGWLx8D9c0DB894vLdjzhbeG5+9CPi9TV3f/mXuf/z32G7WHD78efw/IppsyXHDTKuWa8vmXWenC3tbMbJt77LyS/8MjJfYH1m89n7LJs5vpsRDYSrx7jlCa5rNPgdA8WrYzrAqZSJrRyKg/JZ/Tf2UJyC5KlKTasEeKnyo3sXuDeDVq1j1qDN2+rcxbBcLhlDYBxHMoXrYceYAuvtBm8NJ7MOGbQ937jmCzCmooIaaWIKW0CIoWeaehrf4V0LYhUmlQJjmGgbDwbiGMgxYq3V7ulX2co+KAQp5SBhHHOqsCsOlbqcM8baOp+o8payrQdCohSLrSpsykyRAw/MFEOqB6U1KuOsCXP9knoY7vkye+S52ELrLaZ1zLwj5cQujNrJpDAOA1M/8NHHn/KjH72jYhDDqAT7q2c40/L5o8e88+MPeOv11/j5736bt77xFquzU07Oz3Cto22Ua2fRGT4qKQsha0LXNI6u/psrqgDYaJuAxip001VISIwKU5Oa9O1nhQgQSz4c7uyl0ylVXUpq5ZuajGe8ERKaNFkRTCmkonC+UGFDULtsFe63r/7WJi77eVNZUO7GFwKTjBAKmLwnROvzj2kv5a7wsYX36p9COsjyisCsUdjaXtRBRGEm1Nf28MQYM8MY2A4jl0+f8fizR7zzzo/5wQ/f4eHnD7m5WRNG5bA67zFi2W16PvjgI+7dO+el1+5z58FdZm2LFNj0AyNC510VxNjD4TLkfZGwru/aASzsVS/VFxVR7gdondvW6vn+WcmLt+t/y57/aCoUj5ooQREN0OJeuVE0QFLoqYYZKeu8prGEer0aPOk8PQ00v6pWrOXVN9/kzvmS2+dP+fD9D5ifrtiGiWuEt85XNM2CsB3Iw4S5N8N3Lc57+hgRU2hnHVOYuFmvtYiIJkq2EuYxytFI1pJTqvDVRAoj4j1u3hKnibwZoFjwlrxeY+7cI242uF2PWS30+cQakOcIKWrB2Bjll6XKe/EeubhHyRN5d4vxqtKapGi32Jk6e0ehy6ZtGUOibTsePntCkwLmA2EaH3ByNuelzpKGEdsIeYggCX+ywp6fUy4/g7bDLk5J6zVp3GJMYXq6w919gHUTue+RxUI7NLWrRYoKLXSQhliLj5myUXSH6WaY5BBrVREvBRBVqy1kUoUXizFY5yqHS7shpfpkASxNXc9JO3MhKD3CeZWrrgVFU/lOpeQX+4Z9IpUrOuOFoM8L/vILNbv964fdUDKCim8oZHg/Aw9K0Tgg1bPq8KVfiB5SVC6SKYV+vdMzHIi7gZLAOKdJX1XlsxS8QPHKU9wNGtcN/Uga11jn6TfXdO2iqpfC0PdIaZBxxxh6FicLuqZC+nMGa/X+RdUlLTmTY8A3jqZrgUzXNlibsE1HdoYsRpN99NmlqGeJdA0yXzDcbLj54McMT3WcjD09JUzjl7C71b7SyVJTlJMUY6ShrbKMmRyVtGycxVtLjol+19Nkx7TtiYuFOmtnSSHoYqwVXx0yVqvqtZ2ZY2JYb5m2OxaLJSllYj+SQySZQts4Ur/Gm8TmamB5doIlk8cN3neK900ZG3pS0kPEN3OkXZAGSw5bDI5Ij+tOyFaJcG42YwqRnAdMLBATzjhMpzOIutMzxt2EbVrW2x0X332dOPWk9Q7JQjaJUnRGQWkEOZlRbGFzc0l7scSNhSZbRIJCfrIlT7d0c0ewS233ihDGK1ozQyYDTkh+hl/eZQo92XqYCk17hpGJMPXk3JBNRsxEDoU4nVC6gjQgTgnBrm1JxZKmhLMNRQrtaoGzAWsd1jqSCDlMSjYtlhADi4sz3KylWS2wjeP2dk077+jOTki3Gy7feZ+GzO3mmpl3mOfPef5v/x3WWc5/4bu88T/+LT7+v/8bto8/J6UJ74RV0xIjbENh8Y03kZdfg9mMePsx0s05efAN4vYG30F6/hFmdUFqOkrr8OIxTalVbeWs7JMkSianvVDIC+7RHusf44gn1gjLaoU8iwbede6Jzk4AEHb9DrGGIQasTLRNy5QCu23PGBP9NCLG0sfIZuxZzGeY2tGQYihTZAqRZjYjJXWqMUZiCoQ4ISRGdqSUaBqLsUtKkSpJrhWikBLOmUNVbd9k+SqbKtkplyLlQkQHxRp5kbDowaQB6f7QE/ZS8FSwQanqdihvpM7vyLXlcJAKr527/c8ZeaF4aGrQaCtGXWoQOvMVUmUKw5SYe03MU0ykKfLej97jvXfeJUwqPYwxSMqUYglhJMbA++9+yGcff86P3nmPX/jud/ju977Dq2+8wt0H97EXZ2SruPVi9nK0pUqeC96q5POuH3UkQox443XmkTOkVNiOAQBnLF70tUmUm2QrZn0/s0dhW2CLraqDAFX1rfZjDvXWrNeU632OORGoghEV3laVfMFySFDKodJbmErRIKdoAmaFQ1dPivZJphqoxAQharnCGEM2mZkvtNYyxURGSDESYqJ1llgyHU45ZLkclPQVZqZ8onEMPH92yeNHT/j4w0/5/T/4Y9577z1ubm+Jw6gBVk0gU4xkq0FVv9nxwx+8x/d+4Rd4483XmLWOKRamogISQkEMNMXq4GrZz7nac+TMiyRyz+mq3W+lGu6liSvXVsBhDwKZcli3HP4LgFFZ+r12JvJCBv0wzHPfkUqxVt81OYo16NTrrJ3WA0/vq2m+bfDO0q97+quIdDPOVjN2Y88Hz25wzrOar1SoJKgSmThDCBHjhKvra+xyrnNlMpXztscoFMIUcE2Dc5YYJi1CTJNyxKZcu9awe/gc2zQYKYRnV8xKgRiRtiNu1th9N9lY0jhSnFcFOe/JMWF8HfYqkGPELFaU9QxpGkgTpV/jGkscAsYachbtPtmGOPXMbMPMRebdCbNFRx9Gtte3fPTx5zT3TjE3axbLGc3MYzIY2yCrU0rYIl2HObujEP4wEtZb7T62G4xviZfPadoliQFxHmKPuIaSBnCKiEipjoAZR0zXYZpIHiLiVf3P+OYF4kMAqyqhiA6uVv+ZsMZhvNczW/acYi2IFosWzEQwvo7vQF7MS5R9glRPxv3eOVj1T7nU9i6HtV/Qbj2lHCDwpvKr/ozoA2jyV73kiyRr38GqHOXKR4q7XpFPIWLbhjyOGhsIIJmCqhV6YzAk5p0jDYEQMmHSgnjJkFJL1y0wXgjDSD9MWNcwDAOdFB69/x5fv3tCe7bEiNDvek4WrcrHp6RcOQFyhBIwjcY3TacIIozBe7Bdp/DpqMI8rmsJm61ew26kmIGrDz5g/fAJ/c2G2bzBGR3Q/GXZVzpZSingakVXSqbEAJOtEBbw0iAFwqCynjFZbBHGOLHUki6g1T+FperB4Cp2G3Tx55jIu5EyBsoKSizEaWJab8mTpesc0+1zsJnF3ZeYhh0dgTxuCa1gfAshAYKdr7DTyO52hxl6sjGUxug8AzfD2Ea7C8uOsewDpAhOcE1DZMKtzulOVqRxJOfIWArnr95hvPkMExISVYGqxFuIE+3FfaRpmc1aNlfXNKdzDAY385T1GjM1ZJthWGN8BGNpfEceErkfkFkh+QV+vqA4R8oW46ImOWbG5acf47cDZWZIzIibAWmhFAt2wTgZZs4TJGqlxjWUIJp0DgFjfcUiF+xJRygw5ogXraJKhjRNpJzpVguwhna+4PrhEza3a05Oz5BYGD59xO2779LazPx0SYclpUgTdtz8f3+X+cUF7fkJq/vnPH3+iIt7r2F2D5mi4WYUnJ9xNTrOHnyN7MBd3KVZ3GX74x/Typrd5lO6izmRr9G89D388s5BLjTvJTxLVMJkSQe8sc54UEer1aOiM6VyYUojuYBtbK1+wd6Zyhc+exhGrPfsxh2b7YblYknYBXbjwJgCY4pMKZEoWONY+gZXoDEWUmRMEW/1nk+bCWtd5Rppn8t7CwQ2u4da3W48Lp9gTAc5EeJUu1+JEBLDMOC808r+oZr11bRSCqEqAu2TFqg8pqT+QA/ipPPTeAFjLDlhrD9Itx8yx/KiSniosidNxjSwV8GWvazt/j0HJaOiwXpKCvuwVXXPFJXFLcVgDWy3W3JI3K43XF1fqyxsUf6kcQZqAlPQAHUcBh49fMIwRq5ub/ju5bf41nci1hraeYd1Fm8cMb/goTSNY0iJPAY2/Yh3M6QkwNM5hX7FqHwia5RDJbHQeK+49yriEOv9SCVXKXBhrCG/pQoo1KBg39VJBahQxlwSqcK4CsKUUxVT4CCTL+WFSMq+N6uFCv1eSft5PgpNESkYkyuEzryYFSRAvecUUSy+3Qs9aIctxIQX5Vq4OufkQKwGQszEWJj6gdubNZ9+9Bnv/uh9fvf3/4hPP/2McVDFu8Pjr7pb+4JKyjrXa7freX75nOvNVrsRTVMFPlKFTuq7S6zwRE8NenJN4JU4vud+SS1wHLptooIeDp19NeVA4xVsV0qsQBtdl+kgXFOVCkUp/gU0oDoEhhUuuR+my4uZcbkWH7KK5GGtIU/hz3TSv2p2enKC5MRuN+CL4eLsjDQOfP75U0rjeT6NXA0D94DZ2akG36KBsTSO3XbHj99/n2+9/Tar1VKD9Np9JqGcDWMIQ0/rMsarApmEVmOD+ZwUEiVBGBO2cTAkhue32EcPcffuYhUDSprNAKFUARXjfV2Huu+0oFEQZylToizOoF9Thg20DhMitnWECvXNpWCaBmmgXS5YXveczOaMJXMyWzKMEz/+6BNsTry26FQeunFYm8lXl8TljPb+q5RGlfnEO3LjKNueFAvh8UNKSbSvv0nerrGrlXZuklCI2KbReVPOYqIQtwN2eUKeBlh0eu7WroYu/ka/Q6gw1T03qVRBo6KzN7cbLbwDkqOqRXYdtmvANYjdcxTlACcpMbBXRtkDtPfMY6lDqrVcVmoCViii5ypfKMIpbLbuo33SVO/1fp9IPa8yyldyzh1497Ucor/HoJwuby1+0dE0XhEqVFnxlLS7W0dTzJww9RFvDJvaOdptd3hnmC+WhDBxdrIiZcvQBxYLjxTh+eOHlM1zzl8/xZbIuO3Zbrdw/1yLQMOOUmf07flcZRph7yO8wzYOsQlpGuLtWpNSW7mp20H/Pk70N58SnjxF0oTzFt805BgQ331pe/wrnSzlpNUVXzpIgca25BCxFScfxwmL4erZJWlKTLuBzfUt56/dP8A3ctLKrUqclsOMJKiQnCkQhpHdzS0pTDRnK3IqTFFx5WkcWD+f6Njhm0U9nBKMax336RqSNTD0RMCHkf6dP4DrS0IayO0c2W0xXYMxC4xYgrdIMyMNW1rndJCc8Vp9OBfmJ2eEfke8eU4zm9Ou5mw/+xiXEq71FFsoOWJspJzfgdUJeTljIGJF+QA+G0rrIAqpsZhB6OZGyZXdipwiefcc4zNm1kK3YCwNPhZgILNCujuw2dCWEX86I3hHvr4kx2u8v0N2FwRjsI2FEinZUopBxBOGoZIFFcpGUkiOeIXC7AMsW3Tzb2/XOjR01insbLulf3JZK+GG8eqap3/6A7h5rvKqjQcRrXIvZtjGc/OD91l97+dwqzOatiPGkZIir/0vfo3TceThk55X/8bf4OqdH3Lv218Dm1h/9u/Ijz5lMnD6tbc04fMz7PyEbJX8bFOhGFudatDZACVTrENso9W/RC19G3KJmuQOPSnuiKlw2i4q1rm61+rwQkpMKTHmyLjZst2sgcymQExRpyZVKELnHb5tdfJ5qjKhWYfoiTMEsg6YzRlXOxwatAeMi9zcPiXFG4oUbteekhcs5iqf62xTBQUsu35DSpF23pFCqnLnX13LFEIMpC8iGPY+oP5PSlWAo8KZStqT52tXqOxJ8ELOkWL84fPjfhhfylChFCGrchFFh57mPVRDVL6XXHHepVRuR6Z1tkL9hDHp8MD5csH7P3if9955nzCFCv9QlUPnG6JEVXYqCiFOJlOS4er5c/54t2az3YEVYhp54+tfp110YGrVMhdiSNhSMBSmoBh3hw7Mba05iCdAqYOPSxU2gCFFWqNS5crZEqQqRdl6Zhr2sDm9JzYrJy8lJStb5w8Keoh+X8mZyRhSrBxRqzybLAap3JfyBUhXqkMZc9ZhtLY+41yLUTEnvFEIZOYFXzumVEVR9tA0Fa0IVSHLVkVIL64+x6QDN1G4kg7gjlw9u+aTDz/mD//gT/n+D9/ls4efMw4DcYqHboxyeSyUjPMNueiMqCLCdrPlhz98l7e//S1efuk+Yq12nw6JSanBjxaWQkq0qg6CPkx4kZG9mNlijZK3iyi/K2OgHn9azEk6K8y+4E/qRygRvIqL19eqUiDqu1KpBHTzQnRCv1e7SBHt5AYyY4iHeUxfVWusQsKarmPYbDnvThludqzXO+6en3M7BH7nxx/x1y/Oefvll8nW4YwgThDJFMk8e3rFW2++RbeYUdup5JBUjMBa+s0OEwLSNIo7mHWUzQa7mJO2PePjW0zT4VpHGQO5CMZ64jCx/fhTTr7zLWQaMU1LSQlpG/LVjc5a6gcNaOt8pxTjIRaK3iPNHLENRhQtUWwdbu6F1I+EETIdkuD0/JQn4RJ/fofT5YqHH39KySPf//GPufPdt5n1Pb5E/NkcSkImFZXCOdK4VWVR12BnmbAZCUOg3NxgVte45YlCyowDEib0pGaOeI9xHtqC7ZTjRc6kKegMxJg0udEZAZSoRc20H/cg+2Im7If1Ou+IQNlt2X32GbtHD0kx0Vycc/rm15g9eICbL8By6PqI0fcepF1E45mUU0WUpIpxNdX/FbYhMU2Bk3mjcUOuSqj7uU21q6Xo1n1RpiZipVT4n8WI1cJyzvhGR9ikkMgxHwZJN12rCVlKpPUWmgZcS56S8p6zFuRA93AMqvSccsZmaFzLovPMWs/VTQ++5epmQ9htuPzsQ95aeWwekZKYz7sDfzpNkRK1+0nQc4raoY8hHMQryFnF04oQx0jJBTPzjLtetQdyRmJkvL7SxDAk5l3DvlAVh2Nn6SfavOvoEGxSDkeOkZyqmkuFHhlgGiacWLwXWt/im1bFH0RqZbxuEiOkHHXYrOiEZcmF3WarxLVGsZ3WGUzbYJcz4iZSpgHcRDJn5JwwkonTFmlWKsmYMsRImybiJx8QHr4LwSKnZ8zffJP4zu9BYygyozBhWkcarnHiKk55RQiJWHraO6fEaSBvnuN8R3v3nNuPPqKRguk6UhmJROaNQ8aO7BbgBdMZJBuQhEsByTp4cGw7zLzTCmKOWNPo/JdxS7NYsBsnZn4GRUgieERFGro74Fb0D39I6q9wpyc0baPy2t09cnuHyUR8C9kO9D341R1iNLiuIaQd3liSVQJ7FYzEuxafddCqWFehG4XN7ZrZaoUgrK9vGfueabPFdR3TFGh9Q7i+wsQdyXYKbWk8C9tiaKCd0Zwtybst09WGtvGYeYP79q/yyv/8P7F+74f473+f3/+3/0/+2tvfgeefM20fYcZLmte/hljLNNwqb8sZjHcEdJ3lPXGZTMmBOG5rlceQcgLqrIZsiSkQw0hOgSkM3N7eYKynm0baucdUmdD9XJgpBZ5eXtJPE03jcY0nxwnrDLFKIM9alUHvuk6DHClE0UCsaVTAJKdEzFGHJfpGg3ZJhNiTS89uc0lMGz0Mc6BpJsROIBMiHp19q7CBXd+zH3I6pvBi/3xVrSYsRZTcqlKtCqmSPdlVrFbF6sG473xQdGaGzeYAf9JudTrMzRrqgeONxZgXkCaF89W6YykItirF7quO/BkisKrTARRS1uHDrbP0w8hHn3xGCmMtV2uxQbtLTgfpYmgXM6ZpZBwHkmhF9N33P2C32TDt/iY5Zd78xtdAVnirc8IETRStCCfzVpNwgcY7nFHe5hT1d7FGdHAuWeeoZYV3hKRB9158IVdScqhiDjoYsd5TowRzI+pr97LrxmgVt9S2SMxZAx/0kN13K2AvYqX3WR9ZVf8yGogYu4fh7fslev9j0oRPhSM0mZpSYeksvvLD9qpxsWghpojorD4nrPwcT2EaB8KUGMaRze2aD9/7kD/4wz/lD//wj3n27JJxCqSkgYAYtMBhFNpYcp1Mn/fKczqgdHN5Q5oU2hYrJEYTrKq6mUQ5XF5hLbEOoGyqVLQUU6vX1Hsu7IdcGqPJqgZ0GoRNNWgzxpBy0cC+7gWtJSh8SIsFiT1fI+UaTIvWwGJKVTSE+nm2Bkq6jkJITCEdCg1fVcul4LIQhoGUAouTJTeXT5ES+ca9u3z27Dk/+uxT5o3n9W7GyXKpsMkaFIeUefTkae3Q7ee+FTCafE9DIERofUu2luw9hEC2FtN1lM2gMDbrCX3ExExxDaXAeLmmiGE4P2f51hsQK9+mPuPU77QgmrVjladYOyyZLDBMERFHO1tgtpFiHWmzVSGUnJm2AwEdkNyVgLmz4n6B+Te/QX5+RT9veXZzTYzwo08/45fvn9OmpD3PmdfB68MWOzsnG08WX2GdII2DbU+42TAun+JPzzDLJQDFei1IpoCxFtt6shEc7HVHICcED84yjSNN2+h6L0l9ZVa1PMRQcjhwj/Yy4MYIuWvp7l/gcyDebgjX19ze/h67xw9oX34VO1/RLBYKf7RO1z6m+iv1LfvCRJ0UoQWsWkhwUlR4Q0QL49RElBdoFFUrLbUgIftmGYghxVCRKzWNqr6SnLU4RcF1Da71WO8I/ci43pIGbSYgHnHaadMB1sqbnMaRUmAalVd9upjTNkLbzShiMWaipMzjx895+vE7LPOOwXTkdBcnsJy1mtLFoF0fQ1V2rF2+XCAm0hj1XneNCo61HakfMDSUVnQOnmtxbWFab0gh0M5UXZK2Uc50Y7DeEta3X9oe/0onS2WaIETKFOivbmhPTw6Ba7aCy4nd+paUE2erM24/e4o40WTIWqRKrdpKli+VvL2X86UouXfY9oix2NkMyZlpigzTxJ2TFTf9LctZi6SMkFXmm0ixphKGExIiNkSuv/872NtHUFTSef7mN/CvvsF0dU26/lw3pvU62d1B8S34OdGtSBJg5TGpkHfX+JM5fnGHcXMLOWAaRykTRkZa78l77X8RTMlImHDtjGxa9b/0xOIws5lyQRuB2GjQGDdgewqCn90liKd1njSuCd0dcrPELE4JN5eMV4+RPcNg7JH2DokFSMHXieKYhjAWZhdz3GxBSAmsIUxgI1irPB1n0Ap47SztByiGcSTHQLeaEaYRAYbrNSnBtBu4WCwZdxtaD1f9jrOTU2zXqUxvTHTioWkx3jFeb/FtQ+8cr/2t/5HX/of/juH6Cdff//fEzz5k1bRs3nsPezlx8tY57es/R7Yt/dUnGG4ZWeLvQukvsTikWFLRICWEQSWJLTpPyjgdtKmkH3JKXF9fses3LNqGzc01m+0tbtGxzCt8FiQ7Ep7Jeta7Ddu+Z4oByJQUEOuqmp1hPp+ToxKlG+9pnCPkid041J59ZNgNCu0SIcdAjBnnW0AHmU7TlmfX7yFNwVhHigURj8EjQ483I16kcjcgpIkpBGaLjhB1mPNXvbMUYmKKCW8ADMYUShV9gBcKsogG+Yf5Wai/d3bPWHphJRdVyRRqdyiTRGW4jdTDGu3EKBUk42SP49NkOaUXXbtMHZSd9edThQ5KDOy2a0IIlKyQz5wzyWZiDBrQ146JtZblYkXKkWkaKP2ImQKfpMf8+z/8E0KCYYzcf+UB83nDnXt3NaAXJQcvGsvoLYiqsGGqDElWFbWcIjp6odCnhLdClIxBi0+m1PklaJJoRUhGqqBGTbZCRCN6DaBLLkwGuqwwmVgKXuMQEvoZIWkXwzuqUmSlr7KXAta996Kroklaax37YY85l0PiEYuqn+75Os7sZ6fUodH6IRWamWs1tpBDYMyKRnj42SPGceLZ8yv+9I9+wJ/88Q95+uyKsR81USJTxNJ6z2y20AW2H6xI0SrsQWxI6KeJKQWGKdSiXqZYU4ValOBNhfcmq9dZjAbje+J+QdewlFq+2f8qlSuQpKh8MPr5xohy4kSHce4hgjqwcz9E+4WAh74uh0g110q4qg/KHo3EfraYdq80YJ/2whBfVZOC7RrW11dAZths6fsdZ4sFdy5OuF7fMOs6JiN8ePmcby7mtHEi9ELbLJgtZuScGYeBxXJJESFkFYgJqTAMgZhhXgeOi/WkBHa+IpYevwj62mbU4ljTISkxbkc661Qx79NPaV9+BdtYXFFOUomJeLume+0VHfSZss4iKomUIsY6nj9+zs31JW91hbk1qlrXbCFG5bOETAgjWPCtx3jhzp0lq/tnSFPob654+PQxN+PIDx4/5eLXfpnvLuekFPHNimK0KKr4NIu0S1K4pRhLHnvMfMZ4dUu82RFuL3GrE+ROhy0VzmUVEUPb6Aw75ygxQt8jTgUbTIWl69Bmr1QAgIoYKFXcQEVntXhTcqmzjQTxFnu2pEwjtjvTYvnFObSeHAf6yy1FDLad6R/vMbbC4vZrpKjoxJ4vWKokf9t4mlKTqQrnL7kqagpgDaW4Aw+65H0mqPtFjNPfo3AoXCrHSDtm1jvEGpxTtABJx4fEksljwLpGET1p78tfwID3M9O8d4gkCg3OeYYJEMfnn37EZx+8y/NPf8TrFyf4u3P1SSVijDD1PWFr8Y0nTztQrWigEMOkMvS1AJND0WclQhgCpIJrPWmnHLU0TVixtKcrwmbLlCOGzBQCbjEjhoA/v/jStvhXOlmyFiREhvWG9nRFvFlD5whTRE46TNMwmy+4er4jWaG/WeOcpWl95eHXxQYV376fH1IP1Er4C8MEaCu85MJs1pFiwnjP8vSEYf2c1WqpA+bCiDMCxqlwbY6UuIXxBvP8CbPGE5tTSqsk3mw89uwcSRuMX2CmgZQnshVM05CaGRir3SwvTI8+xs5a/NkdprHHL1ua83O42UIfSdbTzFdMcaJpPbZrofVIOyNb7TY4aZUs7R12tqBIJk87gukoZoYTRzYjISaQGcZZhjTSzE9J3ZLm5J6qAe5ukDAx4YhDol2dkuaO6eo5voW+twxD5uzVc3wjTGHEdh3bmy0eJUYWhN001YBeZXDFmgPxsogwrjcYazHeahA5BqbdoLDXtmFzc0W3vWa4uWR5eod5d0IaRxDDALiZ5+T1V+gpjM+e0L36Eqev3GPxCz/PVOB3/6//F+6vP+f8/JTv/957zJxwt1mRLm9Z9z9E2olSCs1yhTt7i+albzE++4QsH+FO7mObUyR4CFuy9XjXUUpDjrYSZTM5JdbbDf1uTU6B7bhm3NxipDD0O6YwqaJNddDbcWTX72p3Q/kH1hpyDoSYVRmnFJyxLFZnNK6FAl1rcI1jnAb6ODKFkaZt0STAMJ834Oo0cmAMa1K+xUhLLhbMjFIMqbSkYvC+xdMQciW/Sma1XNJ2LZutPpcphZ+VC/hLsZxLBYJpNdGJBv9TxfEbKgG3ctCMqdX5Pb8oF7JRyNOexF72uPMKpSsVJgUKG9Xzbk/qFSiqHKcT2fZkd+HAd4o1OBblzEhMiFMhiJPVCbPZDGMh1mGNJC1rGmNpZ/M62ydSrHaZrDhynsjRs9sNvP/+B3SuoWsczx495q1vfp1Zt8A4y1RHJeRSWMzaA+Qr5SptLntxAjnwWsjCVMUUfC6MVQEwpcR+RON+UGwRyFk7H1Z0TlgqCidp6+TDWHLtuCoUw1LlzfN+jpCq9+35M6JKGerbk0qIVwH/GtxXZT9jyEnV+IxosSxUnP5B/h2VBXe1A4MxWGehCI0pOLE12CtsLtdcXV1z+fyKh48e8/xyzfsffsqjJ0/ohx0pjhRRoW6V9HWa6JaCdY4SNVEspPr89HdpmxZTEiVMiPc1mNKEGYrOostFoW01SDLGHAYXG6lwRDkgTOtirAFZqQOsnaNUZa2SSx227vV5Jap6Ye0ClQMrTBNHqLCgF0peyovKVc1Tn40zhpDk8IyL6DoV+eqqaoYpYJ1lM4yYDNttzzRMNAjD5SXDbssr5yu+/ep9nj95xNmduzy4e45YQyLx+huv8+GnD7m+vuHl117RfWGsQnoziPGMfSB5CzNHnqBkwc5PkJCxiznhdlDBBWsoYogl6flDJvcD47Nr1u++x9n3vk3YbrC+YXp+pXLSMSqKpXZ9JSufMqeElMRuM/B5MryxmtP019jOE29uyCkTxZASpH5LzAZ/uqJxwtm9M6RN3P+05dN5x0dPbygWPry95efuXJBChqz3rRirQgQx4do5NhXC5Y3u60nXPCUTNmua3QZ3dqFdfud1hqNkRKxyp4yQ+0LpZocZQYjGCrZxL6gWe9JcVT8te1hqrYKVmvcLGZylzGeUrkXEUrzylpw1FOvAer1WfTNpGpnKiDGWKQactXjn6v6rM8ukjggR5apiQJJC440VsFVVVVQdNUbtwLzooOt8tykahnGicYnWWhrv2M/pqqBxSkrElJnWG0iJNA40y5aKEEfQwpPzFl+EMmpCHuNAjhHvtZXVdnNc0xD6HWOK3K5v+OCHv48tAXM+51vfexufNKEb1hs2N4Z01kIaESJiHDkVKAbnGxWRGAbCbY+fGaSBkirEOGfYjeSoMHe/mFHaogie3Y5iHTGP2P3ohhBYPHjlS9vjX+lkiSmQppGuXRA2ChsTI+DA9AoRuXz2nGWnA676caRrG2gE620dPusqXARApVSLKBQkp8z65pYcE411WOM0i20b2vkcY8D6hmgcrpuTSqD1lpxGWj8jCEhK2DIy3nxECdekboX1Qgobxief0D54i3T5iBxuEBsYxwHXnWP8nGRbkrEIAds0DFcPkXSLP3mdmCPWK7GyuXvKFEecn1GsZ0oF3zT6PdxgW0dxmWyFpmkOoPxiPc3iBExBvGF7dYlLA6SE7U4o2ZGHQiwjbnmXIVuWq/uY+QIRTzSe3XZNd/oS0Z+STMfs1JEH/fz1tuDmS8axzmOYBggzGhwlQuwDbqZzPKwYxa4mJbzPFwsohSlM7K5v6U5X7AmTYZjItTrSJKGVwuX3/5i0XjObr5QMGyLtzMPpGd23v0G+syRerrn/89/h7rffxp4tEePYPX7Mt/+3/zsWuXD9R3/A6u5j0vgETjJxuMa4Br86VehB22LyLet3/i1mNqd98E3FCKdJZcjpAU+2lsiMMUVC6mmMMI0Du+0NNze3GMmE3RWEHWa24uTiJQoNMMM1nn4YCNOkks3OUbKq+eQYSCWprPKUiGFU2WLgdHWGt46UBoZhyxRGpnHEGksKEWs91rqq7GO0qptGvC84r5wZ55cMY8HZBmjpmqVi8YvRtV60QzY/OVW4qvOMITJOX97U7J+GFfajAhRTXoxnSrkG/rX8LgozylkhTdZIPYir9HKNDjMvZiiRpQ7aLHU4rRyq8Fq51G/fw/oqCJ2SVTY750wIUa9PdB6UGA1ATVGp16urK+azjrfefJ0njx6RplHFW5zHVInhmAree7xz7FU+RYwGKDmQY2LXC+988CHGCG9/8+t8+P4HXD2/5o03X2d1cQqSiSninUXb9wZv7KHC6UQIovCvGDNNDUhSKgTJtFaIVaXUCUwUQuUWGTTwT6kwQpUsL3hvDl25bHXQaqLKmpNJWRXZYp0Nkg5BxJ4EvZ9tpUFPSglTKn+KQrYv7oUqQVliLvX9QiLROA03DFrtdaYqlToDSTtW3nnlHqx7Hj58zEcffMwwBbbbnh/+8B0+/PhTdsOWHDPgVTjD6JBFseYgrZ1z0eJE49luDSnvEFGY3vnFObc3t+y2W2YnJ1Dh/5RCyXodexnugnKYnAhRas9TOKhxllL0vlaYpSrxlSrlnfYpJSkr54IslQxuDgp8BzH4sq9C60ynwF7dsQp31AQzpqRBZslMURUCBRU4yGHEGE/r7Je0w798iymRKm+km3lsO2O+WJE3t6z7iZtdz1//1tdo48QnH39GXzzZW1IOfP0732S9WfOHf/Qn3Dm/4BUlDZKiJkpxSlirwlQxNuRiwDikmSlkF0tOYOczYq4Iktsd25Rw04gtGVYzxqeXbK9vaO7fY/7SXfqHD4nPb5BGA3bbOC0Co4NuxTlyGDi9e8YHHz3kd378nJf++uv4Kh2SRTs1cTsRbkbsfI5NASTTdh2zkyXIyHLhOWkbXm0b7izn2BiZnCHHQLEWnKtIH1vnvqGw2bYl9xPT+gbTNsTtDte25M0ayVHRMyVji5DE6nDcYmqHp6X4pNwkMlTOEDXZkFJ0D+ZMthbZj7+wtnab9lwh6hpOmKbF37lQYQu3lwvPVb58f7byontkFdmTx6xQZIqO2qCQQiSGiavLS1JKrE5PabuObj5XJVOrs58U7q0FqEI5wHcLVJl+Yb3ZMUyZWdtg26xIIkGHUteCXM6JHCKP3/+A5WqpghWLmaKPTEUkTAnbGFKEYQqkKRBjpPNW1SvdDOccm+2oiWEY+eBHf8Lls0eUOPGNly9o5nPi9S2SovJIo4peFKbKtewVAWFbpk2vwmm5YJzBNA1u5YlDTwFM48i7EWl18KyslsTbayQFpn7CNR2j1VlOu6tr/L0LUpy+tD3+1U6WhgF8yyQqs12m8aBqt3nyjMX9c1q34uLOHba7Hmct8/MleIVKWe+oE2cULrdXNMoK3Rh2Pf16i+RMCAk3ttDooa/a9Cj2F23zUgoxbvFWCGMgSsHVACldbQj9Br+8hymG0F/C6QlxuCRPT3GowpVxM2LJFHFkMwO04hrGHXnc4GZzokkUAtiGYgU3c3DvjNCPSHDYNGAFokyIMyoLahN+1mrFsEJXrBiiKOHazztmrEibkVgsxp1BvyWNO9rVKTEJzeIOxTVMJNriyeOImy8xi3PyCDINmHaGW84JE7i54JqOoe8x1tI1M6b1gJWGHDLjMNE0DVIy29tbpnEiRR3Sum49d159QIiRsR84efmlg7z2drvD24YprbGbHeHmmunjTxnXW7rTJeM0alWo7bj/N3+BNJuzvrri1e98j/vf/jahqwTwlJnduWB29vNY42jaGa+UyO0Pfhv7xjlN58n9Bm8b7bq4hpQGrDF0bokxnT6zvCWXCZGg0tPTmuRgikLJA+MUCSlxc/MMMR7nG7abhJjMcjknW0+RhmEqOONo/Aw3RWxjadqOUrbkHEh7yV3nCAmadsHMC9bCbndLSRNjWDNNO1W6M15VzYzF1ODU0lKSrcGWVtGc9QzZU5jjZ4p5T9FysjhVsQjJFGdopVGCvwipaFA1DLuqdvXVtb1MdymQUQUqIwplMKLDNFOFMWk3SVQYRiwaiUsFp2vgGesAVoWDVQhe0oDVWHuALgkK49vLaoMmZKHCklKVxQ5Bk6SYdN6G9kgy/RDYbQMPHz3Fecd8scJYVQVaLBf4ZsY4DBjrMCLM5h0iwjAMTEwK2ZCCFCHFgZvLxPfzu8wXK25vej6Vz0kh8O2f/zZ+PsNbQ8jK7Wm94L4YGEiF0onCF/cy2GMIOPGYOkAVtCuXcx22XHQ4dqnwN1WmUmijk0JRQheSUMXO+n7l6+j9TbEK87g9rkyDfc0RKuzPmDpXRkX5O+dUV6YGTrqmM1NQAY1ctchLlQPOtiq3iYGqEOe9IdXuU9juuLm85vLyhk8/e0xOhQ8//oh33n2PfthWHoqSv4skLDrrpWk65vMZ1nmMcZqMUwckTyOmwHw+1wDPOPrdiOuizrqrs6BiToRYu3SUA9wwl0yuEElNyHmR+FursL0KJ9yjK0rZK4Tt4Z9Zi29itUtq5ACP3HM9KKmq4tXPR6pPUCjpfm7NfqCmziajfo7UJAqmr/C8tmm35dU373Hz+CkZGEYNKFuvwjiOzBuv3OejTx7hEAg97777Lr/0N36BWTdj6EfWmw39dlAh6gKt91UVVhQyJ5qkxFSwTQchkFJQRbvZjLjpkSlo53HesH66YWEcrRSG7Y6cA8PzS5793h9y5+e/Td5smNZr/FID9JwU+qrykhmTIjlluuWK3RjodxMfPd3y8+ctknYqjhKTdsqnzOR1qPbc60Dn8fqSk9M5bjnnfLngjr3HnZWldAvCNDEJ2l1KSWfqjKMqakrBuobUdpRwDRik6yhTZHz6nGZ1Snz2FPfSS+xn0yGC+IacRh1gbwSJqFOvcGhQjq9UPhLGaOdIMyKFpybtsO1heaYmQaUOjGc21zl6MVVYndFuLBy6PlpA2ycpCoH2RmefZaM+yVDIccIbyDHx+OOPGYYe5z3dYs75xV1W52f4pkWcynrnlBUmWbvnVJ6lbxrGnBiCctVzoUa1VC6hJk45KB8/D4OeJ1OEYrHeUVKm6RpGDJnKITQqhBGqyu5tP7A4PSNlCP3EJz/+mMeffIARw/X2lidPnvDZx5/xYDHXWXzokNo89vhZp37TCGTIlcdECsR+IAcV0ykpkqeg87iWJ2QzEW42dU6TiuZM17fY2Ux/xnumMFHI5KEn3h45Sz/RJCXKOCk8pWsp4wTWEtc7XYxjoKTI6LRzcnL/nNOXLmjn7WEGyj54AcE5JcaZCkkYx5GwGyhjRIrQzCLOe8I00XY6X6Odz0nzJSFHnaJO1LZ2mZHHra5U54kl0d19AzO/SykBiRPp5hF5d0mQgDTnNCev0T/9FIhIdojpsJLIeaBMPVE8uV1gc6RtHalo5i4e7N0TTLa4JPTXn5PCRMlLmm5JaTzSqkOwriPlzMx7UmNBEiLCVAI4g5kvyUUD7VAa0tQSxGLn55j5rCrzNYQUCVPCd+cQCi5lbCfkRYvrTth+8hhXQFIkhYC3C3JsdaK2EWIMWO/JubBdb3AYZk0LVquQMSVun10rz+L0FFcHqY39QEmJfjfi2VGeP+Wzf/e73Hz8MYijzAPJgDk54+7f/GXsySmX773PS7/817n7175DRGFxcQhIyngn7D79CDfvaGYNr//3f5sn9+aE/sf4PFFCYLIjZZxo5vdozJJkPck4cuMpJuFSxBhLLJacFQsdhxuFSqSg5OgKXVmdnTHFiFmcgMwJzZyYhbQbSJPBi6drPcvFCf00sl7roRRi1KBHhFgSTdsxjj2b3UBrDVYKOQdyHsll0qqw9RXvLGTREDuESeGrFYoUYiSEhOk6tlNmzCNnZsnL5y/jjCOkiMdiovL4phh1+nfKjGPAitXu01fYMpq0FLNXW9Mgca/VltMefFRhGTUgrGxbQOpMjKoumME6FTigUGf9CFlyhUTpjKRMbcwcIti9XHapM3qUgzJOkcZbrXDGiKvQJhFhjAHvPbutyvha52rRpoBRf3X3zt1a2TcYa2l3PVMckVhI1kKMlKJczc16xw9++A7f+853mHcdT59ccv7ZE+69dJd2taDxjlwyrbUYyYwx0zhDjFFhVjkdVJSkZGbOYDXvwBlhypnIC5iWBvTgZH+86/qWCok8CAegEthCJuaCV71sxd2nQjY6+HXPpSGD1OvRoDxXovVBz1ATCaf33BvDGDOKgkskUPVBEqWoumDrVHq/FB3amHLGCeRpot8NXF/dcH19gzGWzx9+znsffEjfD0o92vMySFjbYSsMxTuPiOXs7BwEnj27pKRECEFnvdRrn6YJsnB9fUsznzPzlpSFLOUgy15KIWblYqWcdT0jL6rMYpT3AId1trdUVMRkDyUqoPwNEbAqw25rkqT7pUKHSqrPraKaMBUiLDVZtVVIYs+w0EJkqT+jKEKjle0Xl/OVs4vzM07PTnR8w5RqEBdprKXtGpZdR9kFxm3P219/jdXdMz54eMUHH33Kut/y7MkzhZEZozDFXY9vW9rGEnIiJTDO6uwfMQqVTgVrm8o1KiSxmOWCuNli7t6lTBkJGpCWMGkwPptz/UffR3Y97Z1zpO8xFyuFlUId2qwdv2IKJkKxhtYWfuXte4w5ch0bzoxFvMNagxTl1PqSiMXUEQWB208/4WT2Js1yxtm9u5hdw+krd9h9dokUQzSFPE7EnGko5H4kigNvidsejMOUglvMyUMPMWOahunmhkVJ2gGyCVyjfCOrs5EyFTodA5KS0s/DpMlUmNQ/iAp8FWt01EeWmjyp8AjWVc6gwuYKlhh0tpSpw1al0fEM2dqqZKnnQa6y2Pv5aqUkHQdTlfIwDts5Zs7pOJacufdAfVcIE8N2IIXIsNlS5uDaljAFpikozNJUNASqMLpXytvPr8g5YYwWxcUKJSVSiAgF23iGy2u8dTTz1YErVqZMdkW51iJ03uBspps5+m2k8Y75csFuGIlTpMSRadiyWK5oWk+YenbbkevLa+4t5uj4rRbnrXYoUwBKVToFwkAJoVIPsqJnjI5DIBWMbwj9wObJJbfP15x88+uU2y3T82vEGpo7dxk+++jg22POpGFg72W+DPtKJ0t5DNBlWucwudCPPSZFVcGbNXTWMSvK4SAl2tMZzbJjDBOLztfMu1Qya4XQVK8+DiPTMGIqzrrvexanS7bXW5ZnJyRjyRRmqznNckk2E16i4jIB0zRwdUWcMubslPb8Ars8o0RL2j7EtDPSdsf0wQ8waUJ8YHr+Ob5YRjtDuoU6xRyASBzXNGf3GXPGSSCUgnIXrU70NoI1LaVk2vYeJkfKJCCe5DKmazF2TjGOpkpjFqtVnBTV0ZROW+Dezsk04AziemKOYJckcTRiMeJAMuI6huyxrhC7xPzkLpM7oVijw34niHaJ8Zb1tmfRrZCYtbpRscSm9cxkye3za2a+JcSpkqmFxWLJ+uaW+f0LJYbHxPrpJeNmy8JAO/bsnj1hfPSEoR9YzJf0uzW2ucP9X/wF3Pk5T9/9kAff+w6v/I1fJEpiHAeuHz/hfHFCCBPT84+5/v1/y/PNju/9L/83vP8Hv0O+fcLS3pKma6R2qZIxJDujGI93LeI7ijTY4nT6vDiSm4GdI0zIcENO0yHovdlNtItTsnEESYy2oZmfsiuCCQVvDYvFAt94Qs6sdz23/U4dXlHeUkxRk/gYieOOnAKNyaSpx0pQR1+r6rkUSnY4v9TgeRrJospKzjoKSefWJCg4xpgZc8E3c7728tc4sXPFFpvq/LOSsqVWN1Ptvs66GXH88lrfPw07DEoV0VEXpsqC74sRpqZNosNSrZGq8FbV1GriKZWXoXC9ojCJlCvRfd+AUn9iqqiAUJOrOoiQqngUc6YfJ0JQWJuIwdqqcleFIPopcHV1Re0JqCKXVW1J6xzOe2IIxMrBEYTVYkWIkRQT/bDV39Fo5TVnHVD87OqK9z/8gO+9/W22my2PP/+crvOElFiulsxar5XuvRR47V74nJkqJG8sGYsq0TVOg2GRL6ag+19Xe/upBia5lNqxetHd2Mu0yz7Az5VjKnXWSioUTw0epQ4YBhF9X6lRuDW28s8SoLP0LApPMyI4K8ywjICvQ4M9gi0ZWyxeFG4lNVkrqUCIbK5u2G1Hnjy7ZrfRQOfHP/4xQz8g1qry6v4Pha6dEWNgPpsrzLdpMcay3tzqVHvnMdZjXIKUGHtVc93cblguFnXVKmTcGGFKgRBThQrm+myUH5atBnF7+fZ98rT3EwpVrB2z+lD2s8aK0cJBSRpMJtE9ogVGDpw7I3rqiewVCfcqffnAz0h1REeqz7oK4h06UcgXiPBfQVudnLI6PyVb9dPndy6g37J78php0MGvV5e39MPES8slN8+uMCnR3+74/c8+Z7MLLGdz2sYxbrcQCsVGXQe1QNM4h6oI1s5CNyMMW8AQdwO+bQlTr12StuVKCjePHvKd116GHImpYGImhcj6x59QQqTpWuViO4XsGq8Kr9Y3GhtNEyVMrBrHGy+fwjTw6eWEaRc0bkvk/8/ef/34lqXpmdiz7DY/E+7YdFWVXa4tKFIaqYcUhBGgf1KA7nQ5gC50J0iaIagZskFyupvd1V1dnWXSHRf257ZbThffikhCmDuxSCQwO1HIzKhz4mRE7L3XZ973eSdSGCW0tmhKKpiU0KXQNE62BOOIai370LFZX7Ffrtl/+TX9Tz4jpkKnZaOQUuDuwy3308wPznpcEXWIOR7QcyFliQqwlViaw4zqOkgLyjVSNxiNznWjE2YIi/iYqkTu6X+PRDyla46REnJefc+U+g5X6rsAdus8JSeUiqjGSw4Vj7HMNQ+p+g1V0SxL4Hg6sV2tniR5UtOViuzXGOtko1cJqKZpaDeb+r6XdbYE1RuUEWlyKlnO7VwIIXAcI+9v7mUzNnjWjaVvWxor2ywq3CbFKCj1XIg5MO+ONOsNWSWpV3PNwEuJJQTCvDCfDhhlmeaBLrVovotJOBweSKmw3l4w7O4w2sqgL2e0kvq0ZIlZUNTBVUrkRTKr4jTBIjLwOC7kFDDGU/KIch03v/oNH75+D9sNq1XH7tdviYcjV59/yvH6PWF/wnUdMUam44jvWjaffvp7e8a/181SRAx6KUXiKeOcQxeN6zqmkrj7cMPrj57hnJUMhG2LcqZmZ4gh2FpJFhb6mhY0bi6CTcxioC86y2GTEuPphHNGgiiNIaFw/YpcNHEc0TFU2UEhHAfMEnDrBm0aZmOx0cLwhmg9Kmemr39L/9HnhHGWm01bcGsJpy2RWBaMTuA0xWqKcqw2Zxx3D2RTpwzZYJTF2vrA9peQFGUaBCOsCtiOWJCHMxdKEXY+KTOfJpr1Rg4r25G1RXQnIquDTMJii8dgycWR1ULwBn9+he0MxIHcn2HsFus06aPXXP/jW6xxKO3QzGQdsa6hpMI0LkDBOItzjvk0kpYkcpVqAAlJpqO27ygKHt7fMNze47RGlRFzPGGWxJQEhWpVJqTA1Y9/ijvbMHzzDc9++ge8+Bf/FSjN8OYdd9cfyAV2uzuyV1ypmU3bEw87vvm//V843d5w+elnnB7e0WwKYtkxmGYtiivtwPTEorGkmv7tRA7Zb5izJc8zcVmARCRxOE1EOoztSGjZbhnHw5jRaNbO4Jyn8Y4QF47zwsMwcH84ULSiay3eCA5jiYFhmkg54K0hpQDpRCp7FAlnV2jln/IcUsq0vpWw0ioAiEma0ZIUxqxo20vGYLG65fnqkpVfo5LFqQxFVvBjDHgtJL6QE9MSMMbSesfx+6ueAWrh+DiVe/Sn1IybokVWpipGWdUi/lF6qJCtiFUSKJzydwjmlGWrtDx+7zV4DdYKiTOlKJjZ2iSYx0O7RGnetCamRfDj04w1LcoKUGPlHWPKOGOZ0sg0L4Ql4LyQj0IMWCcbv3Ge0UrjG/m4d56ziwvyXWaaRCLr2o5SCvPpSAqJb968oWs7/uhnP+P9+1s0muevnqNyod308r60ns4rDIWQpIFYsnoCWsjX+dgcVklIbfQUIt2qaLaKapefQ6q/HmQblbM0SQpkgqxkw6qVJhEZlwVjVQ0PluJGa02IoggoNdxRmASVxEctmACnFLZKB5VCvDxamlSTFM5KwxRmyQNRSTyDJST2uyO317fc3+3ZP+wYTiN/+8tfcX84kkhgHc53pBiQqApLyoWmabGukfdxKYQkG7aSZfuWc6qNixC6DuOR+4c7Xrx+hm8czmjmnCnFEGMmLBFrLVBR9oAzstXR2og8Usu2M9cptDSO0jCZx42SUpVoKNJRGWpJoa4KKCPvD1kCKkyRCbdR8ntzyeIsLTIQeJTrKV0lm7VBEt9YRcLr6sX4z/K0/34uaw3D4YjWmvOLC9q2o6AY58DsFrzztH2LcyLhOu0OvPz4NW8e7lj1PUtSfPbpJ3R9x/3dA5/+IKOMYjyNqCybku3ZBqsgUv0v1srAou3Q3SJQh7gHbwn7Pe9+/Rs+u1hjWpHm9uuOYX9Eu5aoC8v9A+7VM9LxILIt81gLGYq1qBhFeloyOiw0ztE08vz8+u2RZ9HTFo9d98Q4EaaAb8UHU5Q0xKnIlikmCeHeH44kZ5kOJ27f3ND//HPitMBKzv4lR/7Vv/1ryh98xg+fnwti2juYowwVOodbrUjjCXNxBhSK72RrWpJsNcnkZWJ5uMM2TR1SaSHiKvFbCkrQ1BBrVTc/Ih2W+1BLJFO9lwvIr9eA9vKu0KbCWtSTL7LU6I+sZJiwWvVPYeWlZMiFXJ6EdHUZJYfA47BAPI3iz1YlC1ilkiZT3ZRroyhK4XXLyhbWMZOHmc5a4jQxLpEJSHFBxVSz+xIxJEIQ4Eu8eSAvBbdRONNQImBqTl7JjNNETonjcGKYF87PL8gEcioMpxN3t9ecXT2DEtmcX+HiJANWJfeRdwbrKgJTi68uLREdIyFGgEpmnXGtR2uRhNu24+HbWz5c7/h2OEJJ3P71L0jv33F1eU57fUO+vycvC6SELlK/d9sNpvlfQmn/Zy/TtayeX3K824kPKMvkN+URWo8q0J6fgVboxtKaFcZYjDYSQKsqYaQIIapEkaos08y8H8kxkyyoBOM00YSA0Zowzjg7UpwFvRWs4bCnMRltDaUY8hIFm/hwIOsF3bX4s2eUOWBtT+lWJCVUq5wKrllTKEzeo7stOmm0XYhqhjzizi6YosG5lnkpGOXAKkqcMcqRi0z8lbEU09Z0aZmUaG2JWdC9OUe8b1hiwVoHytBXVGkKEessxThBpfvEMi4oDNpq0hIo3Qqqr6P0PY2CtAwod445f04JhpQjqdkS+EBrW8ln0tCtV8SQuXl/I1NRb9AyfkBbxTIEVJZJcCiBvD/QnIlEIE2R092OkCKbfgUPdwzvPvD+i6+4Px44W68pSrP+5GP0+Ybh+gabC/2rZyzDzJtf/IJv/upv0E1Ld3nJ5R9+TqOPjL/7exyRh3/8O9oyMk8Tt7sbnlmNNhnXFhZt0c0W3W3Q2pG1RbkV2jhSkUyYEhPhdCJrxzSOFV2cmU8Hbq73PPv4RwxhYJ4KxWiM9cTTSGsazjdnKKV5c3ND6z3HceT2eGIphSUuTMHSNw6jE8s8siyDhGIWi7GZx8wIbx2FhHOOJToe83mGeRZkuDdCzdKauCzkAs71EFc4bbg4f8VHm2cV5JBJZMZxJOnC3f6AQrPebp5UY13bkpZFNo/f40ugC6qqzB8LyOpmVKUW+6p6iyoU4DH/xyga47BGk7Kkt5ciz0fMhSUlYq0CVRK5b04Jo+p2pEBWRQKXjWKJsrEyWpD6nbektBCzBKKmmu/jrcUaw/X1DV/+9hvevb0mhEW8ehqMdvXPKpxOo6D5lxmlLd55nPNszy4kJyksUvBqS78+ZxwOpJT48qtvWa/W/NFPf8zX33zL7nDgB2Hh4sUzVn1LdhEbLUuRia7rPK0R8IR2Bq1E3iaHr0jrrFKEx+8HkrEWVa6SMIU31U/5tH0q3xX5WTPPC15bVGMr0ECyeuZlwbYy3Ta1CdNaSyo9CBwi89SQyraw4LQR3D98Ry5MIk12RQrFEiJFK4a4CMp5DqQYmcaZ92/ecXv7wO39Dl0U33z7hm/evCWmgrIdTdfWrYpsmEouNF3P2XaLeHoi8zRxPd/AozwwJoz1IrsphbQE3r15z3Z9zuWLF3weY/XSyddvraF1jozCW7k3HrH3tU6TOAqlQBcshqTENxaWiNVC80tFSIWxZEKUEGPqRF4ohhARmp2tTdVj9pKuDZ5Gy3BOixwoK0iVQ1jBfVV2w9NEniK0we9zszQcJIS+dZ6z9Zqm60il0HgvW1WozaFGzZI9lZXl5v01P/7TP+T+eOLrb75huznjZ5//AfM4o0gCc8iFsAS81QzHicYgMtQYyWhKTmQrcB9tLOTCOI1sXeKP/jc/R72/Y1GgWo+OnhwSWIjTQo6RmCJlHFBX57Lkq012qv5BbQ2FjHUWZwrnW8UnJ8+vvt2zDorzokihQI6YBnIOGG3wWrZM5ELXNVxuVhzfvUOPM9vzLSlmxv2Bs+db0jRh+hVXLz3/9R//hGZZSEvENZ60XwhWvKPNegvey3Cnyu9ANvYoaXAyMN5e89t/+f/hsz//39FfXUg8TAyUHOswysq9WHLFeD/Kc+XSqpC14hFKKrEMco8+NkQygFEi6eNxSapq3ljCe0eq4eJyt1eEf5FGOGXJQdJVzqoeGzYlQzkq9CeXiNGGOUl4s3mCSxSk8SvkpCnG4ZqGtu1oGouxmjyLQmo67tnfP7C7eeD0cGQZR9Icaddrrl6+Zvsy4M7PmYxmRnM8jDxSAN36jMutIhbZXIdp5uuvv+a03/Py4x+Q00BrNWV382RvkWYvEZYZ1FYyAHMhhYVU4VUpJHKK6FJEzluql9J7huOJ6+ORm9OJ25t77v/+H/h0u+Hm/p4frTsaZ1lZS5lnUpIAbdM6jg+739sz/r1ullaXF6hWghJVKXTthllbmtWK7GRyG+aFVc0N8G0j2yQjuntjzBNes46XBS6w27OcJAlYW83xfmAcR9ZZpi5WC5kpI3IRtMI7QzhONCisXxOnwtn5BXcPA+Hba/yrl0zmiMMQdEJrizcXore1ihhGVHNOt3pJQKNtZpkP+LWjRIXbXGJMS5gn8rxg+5ZlOaGtIeaFfr2WIEFjJQE+BmzT1QfYoWqmAhRCDBVZaUk8erWk0QQLdbI4L5Kz8DjZMN6RKKicKBGU9tgLRzxoSjSCSncWrVp2D9+iTIPSBl0S7nxLKorrr95irQTDpSUSpwXnqt63KGIQlqWyUgy1mx6VC4fre9IcOb84o1eJeXfk3T/8iutvviWjMQncsyvYXHC4veby4oppCdz++teor75h+fYrpt98Qbc9o+s0p/uviO/+ivg3f8HufqE8nBhXnubsEtW29CuDWxWKDcRkRWZgW5I2uG6N3lyStKeYhlQgKof1gio1rhVaoXUcxjs2mzO8t8ypkFMmhEzIma5p2DQ90zhySOLVWrUdS4wUawjLwlxgCInrcaJ10BIxaaa1HmsVMc2i+S+elIU0FeOCa1eUAnNYML6Dmh9WUmRJi5jSM0xTwKIJc2Tlelauk4wXIGZJj9fAdr3m7nBifzzSNg06J5ZZAne/1/oZEEnHI3RBIVj96pUpRT2R7+RoErx9yhmr5f9TuuCtIhfLEjOxVKlkKowx1aBhabhSkc8NUrhrpUFlfJWpySZF5LdWWxoPIRt0+s4XpasEeLWS53u33zFPEyktEARk4HotWTpGzP05KkKK7Pd7zi+u0MqhCDR9TxlEiptMou03YAzDwy3TPPN3v/wHQoy8vnrOw+5ADjMpZ4bNmovLC+IsOn7bWHLItMYQSSKvUxpDRueEUZLzMSuRyOgqY0tKtkayJZL7rjXiWzIKsjIVHiDvZ2MsBUWMNTwcGE8HjGrZ9E0FTlS5nFKCy8vShggrojx5CJ2SAMumIoNTkWa1RIFrOK2JMTCOA33TYq1lXhaWaSHGzO3tAx+u7/nmq69xruFut+c//P0vmeYJZSzb8xcibQw7QJHRNK2V8OhUsM5gkOK2pIK2ShDm2VDUo+FcptFhmtkf9jTe0bYtIcu0WCtphJwXAEPnDSUntHqUb2ks4Izct6VIIbbkTIpFVBdIw05RzDXvSBAi9UattDyVMy2qbgQlqFcpCEWkeeapCZI6Lxcgy39fqvlOMpiQyXrJhVglpFXl+r297m7v2FxcsD3f0raNQIC6Fr1eY60ijYnhcETlhCFhVObdN9/w0ccfcXH1nP/+3/4Vu/2Jr776ildXV9zfPbBetbTrnlJKvS9hXgK6saicsQmUtYT9kXCcyaNkLRFGHt58y5/9/BXn3YFhvZCLJYwZSs/p/R2qbVBek4YDinPCNGDDDL4h1WZHk8FAVhrlPKbtRBZoAi/ODnBs+PXtHVEptDU0psNoj7WW3ndy9muLaxxJWUxILNcPxNOC3/RMFJhmllkC183G4i82fP7HP2e5/kB4fwtOvlaDQm/XmPVawrCVRlfZHKo2O7pitUtBuxbbNHKv5lQbP4UKi5zR/YaSFnmXFtA1bFsrJZQ9yhPhVHIfbZXvAlXyrHLBGvXkm0Epiq7E0cftUs4C+FCyuc1FBg+qaMHCp4hzvkrteaJz8jRgqHlmBcnttI+ZcIqUAgUBPkg0QEYDzlq8cyhVSEazPt/Q9IbGFDZ9z3Rx4nh9z3A6MYwT9w83zE4z3t9zHyLJefANSyqEpNhsOpZcOJwmGmeI88L+/o6zyyv61YrpFHj+8gW7ONC0LcpqjJGauO9XtU2UTMwyB0qI0tzHJAuJsJDjgrKOoi15OLLsHvhwc8N9XDhpwyFnDjFx+/Y9Vz/8mEu/IS0LWWdRVPStKMGa7vf2jH+vmyW/6gnTVNORC/M00z3bElJEWwcxEYaxyi6U5NSk+oBlkQyklGTiV2T9uIwzu7t7TJJQMEImLTK5Tylh3SN9KOK7RvTgzqHoKZMnjgvGWpSGMSma9YbxzS3l+oBTLanLaFdQeMJiMF1Dtoo8F7TZkpaCbiMpz6hGE+OA6bYk28pLwFjmcqTEiMkJpS3FaUI6kZXHmJ6cF2Ja8L4nZ0PKWsyhNhJDkHBFJKRSockJedCRhzLH/KTzl0mGRztLMQalLCVm4hxRuoGmgewopxltGrLWFGUY9gOb8zPx+1Tpyv3X78XfYC0Gxc3vvmXTNqTOE0+RYTehi8G1hmIKpnX4puG4O7GcRuZ54nlzzvTNW779q7/h9OEDRWd660nG41+8ZDqMnPUtp7tbnG8Z/vEfMRp8muBwi3Ua2xSuuONw944l9IQ84bZbgi10V8/ZXF0QPvwj6tUVAGUIuM0K3ayxZ88p62cku0HpnoQhKUA7KIaSIsRE41oxM5qO7XYjaG5tmcPMmEQOaZWtWXJiWo8UDuNIBg7LwpQSQcHDODDOE40ufHzesraepmlQFGKq+S8FxnHGGFjikVY3+PYClSzLHGVaGJYqGwS0JSnDnAupwLrb0llJw5aiqhptkBTzxhtWTWScRsYYMEDrPSlHYv5+6/BsJXfFlDFGYYogXlHy3hC/ksZVWqauUi1dzR+6SvMUCms0cwh1EwKoirku4o/ROYIyWC2yMUrBGoPRtcAv4l8z2mBUJALbvmVYxCwOiZBgnBM6J374w0/59us3KKOFwlT/O1LIQGK13rAsCzFkUJInNM7jU56Xsw3ZZ6Z5Evx2nNluz6HA8eE9pyHxxa+/wBvL+XrDl99+QPmOzaojzjP9ek3XeEpy5BDF79O1jONM0hZTLIsWL4Txpn4vFU5JOaAVWCPbZKMVMT4W26pugaQwMchhpc0jvlrkeZnC5dU5jbPVl4PkryF5VHUHiFEaYyvtTcvmziktvogia40YBb9NkkZExYVpnPHWySBif2AcJz68uWaYg0w893uGcUAvkf/wd7/gNBwpBZqul68nJJQSeZyzjlW3ppTCOI7YIJt1kRhmSh24rNZbTsc943Enfjh5DPns00/4/A9+QEYGLmhF17Y4WzdKWhqYlGULaox8n331LcUc672mMQUg4Y152uplMpnyhK2PRTy8jz8P2ZqKx1cpK9ut+r0tKTxtDnPJUOT+LhpCTjwSwB4bKemMKnlWSZ7U9/ktcjycCOMCpdA2Ht80+K5n5p5xWfC+wbct65IwvmG/P3G7RH74+mP+5hf/wD/86te4ZsXt/T1/9bd/x2pzxs9++jnLEmWYqOB0OKC0YVgS2svGScck0mFTN3zOk2Jke7bl2Udbprv3zMcA6oyyBPx6I4OfOVG0+NDiPFFKQqVALhb9uJ7WgLEoVzBtQ9IOuz0j7e8wfc/V84WuLBz3M/fOcZwihwQXyaF4fIcqts/P4TiT7neEJZMwqJSxTUNasig0YqHMo+DzNx05X6J8Bx8+EJ1Dp4hzDdpbVNs+eeGKqndVDWUudUvcvXjJj/6b/yMqLtK15wTKkMdR8ODaoJtWPOHmu1yibKxkcAIoQyGKrCzLoLmI74Fw/yCU0XNbNykypFDafJdFVn+PRNOIzFiiCSCHKBCGoshBAAoiJRQZrTRx6WkTK3VqDZtW8rO21hKiyBsVhb5p8FZjbN1aGSUAijCjcyKNgzQuVrPadnTO8PzZM3TXoddb5qZhpR3v7h7YDycedkeMW/OwO1VytGGaZuI8gVG8/uQzjFY0dDy/2GCGC3rf1KxSw3Q6su6q9y0V0jQRppkcIznK/ZFT4jQKLVQ3Vea+v4V5hL7F2C2//Ku/5MVmy83DA828MObMY7hDOEnId3u2IRvNMJx+b8/497pZisNELjAfTyhnWW23JJ3R1uG3K+bbhbNnF4CskgUxKfpo2ZvKC0dZKXpKRogxlYplFORKIWta0ZfrygReUsRXIX4quU7zLFk7inHEYZSprffYVnH/9TWr2z3NJahOY+wFw3yPImHMGW7bs8wKY3uS0sT5nqa1ZE5Yd04uiQKEHCpOeqBkh1IesWApjPaiS80T2jrJKrC+kqEyOUSMs4SUsdaJ3hlBt+Za8AolqlAipJhxxlVT5HdBkkrJBsg1nlAsMTvmMLIkUMoQx5kUI6zWpJzx/Yr9hzvycaK/PCfnwvH6hnh34O63XzHmQru+YB4DfefISmG8Y3W+JZbIdBhZTifa1pNOO+5+81t217fYIhNY21i2n33GYRhZ9T1pGRjv7mm7NcZobKdYwsC2X7F9/py+dUzf/Brfv+Kug9MUscoSo6yzl4drzLRIFldS2G6F7y/Q21fk1QW5v6CYTk53W10CcSbnyBxmeUHlxPF0ou86jsNIv3LMy4xzDYsS6Z63jUz9KxWqIIbRlDLTEghKM4cFmzJb71g1jpIjU4EUj7RWis8QIznNOGMIcSQkhfFRgksl1ZIQo/jzKtDDtQ0p5OozsKybNToWsKXqomXKpYtsXaw2nK9WkCOH4wHjPTFFlrBwGob/Is//f6rrabKNTOJFDaEpJUuuEDwdfIpSJXmimPDWyoZDifRCFdk+Ccwgida8vieKUsS65TBKEVOSQjwVlv/oe+7QWB1RqtB5KdRbZ2WLVYlluhp2u67jpz/7KX/9t79iGhfZGBehSTZtx/Pnz5mWhf3DThp2JyGoOUQZmpRM07QorQmLIFzncWSz2bJMR8Jw4nAa+dVvfsPnP/ghq7bnH//h17x8+ZxhnNEl8uz5M168fIGyCmcdbd30qwLTcaE0DcZYmkyFKkiAqam4h1wiWSnJtlKqTlE1MSe0MrK104r4qO8vRWQ1KVJSpmk8VovQRSlTQ1BBFWmWNLIldVo/BkXQGIUuicb5CpGqHoKQMI8QiSywCWcLJUVuP9zwxa9+w/t3NywxcTgeSbmw2Z7x91/8ituHB0JesM2KpluzhImcBDNuvadvBewQYgA01jlSElm0sRbdOM7PLjg7u+DLr3/H4eFOtjXFcnZxyaeffUyIMzll+raVs6g2LK2zqBJpvRH/bM54xG8FdflbpTuhYumh1pFFJr8hVwJjkjwr6sdMHQrYOvjyTjZ6Mn0X8Ij4oxIooRY+NlWFIqRDxVN2GbVgfHr6SqEoLe+d7+mVqnG9hIhG4bynbVrmxhMPI05LcCkpk8PCaZoY5kAYRq7fXxNC5OXLM4bxxNsPH/jVF1/w+qMXeK0lF8doijWMpwWlCtv1GXmcKOMCCWKBWGWTqYBJiZvfvsGoI+mYUargbEdeZuz5OenuDm2lJ0pxIu53hOFccoxyoIQgPytVJKwVLUoKbXF9D0TS8UC7blEl4XThzCt0tyZ6z91xZI4FNyxgHSGcCKdJ7qpK92j7Dne+IWSFM1a8cDowHSLKb+D5OXF/pDwcwLnv/G6uqRlLoLWQ6XKWwFq72cqgT2ts35P3gbIklBWfUi65+pUmeVc6J1htFKpEQLbM0qxUwENO1ZBUxNOUEvO797QXz2BbUI9SAS3l9OM7TN7nCu8dj0HlKYu/M4YkEAQrsuFYs5103dbKZcjEJ/9fiPLPRtua31eHSbluoWJEJreSoWa9RTcGbRVhjPj1hrQ7iET6bE1QAyU+btAyvm1ojeXVR69pTwuri7pBv9+TlolTSIzTgk7iipzmhU3fsr66pKme0a734hrNUh86L0qlHJJkwaXEkiXuJC4J0/kKktJC751OqGWgf3XJj7o1v/vLv8PEjDeWfDrJsMdqGuexWjEfRpTWpGGkxMTp4eH39ox/r5ul6eGIThmdJWRvSQGnAGcwq46LrsFue4qpBrlciVG6mlnrilMXkQqM08g8TpIwr/JTB2+cw+ZMiIGmX0ljoetDUgscvJeUeiNNiNaZYR4wxqLPzmmOE8thhwsGv7okF4u1LdobgrIU3aKcBaMJ8YhroCwHVFMI4VgDGRu0MqikiBTs9kIe/BTBNDKhSQMUgzGdrIQ1KCUgB1UnPVpJ9oWQix7/XlfJWhOXSFwkwFErzThNdHUiSQ1FLVq0s0Jl0YK0pBKrDiM6ifY+pcRpGjnc3rNZrSlz4PDVW0wpbBrP/ddv2Lx4xbgfyElL4yBvB4z35FiYBgnKbTpHPh4Y3r9HZShtD5PkkJyOR0zXAgvx4UQ+PnBzeGApmk9ePwNT2Dx7hnp+hjYBe/kJ43EhXBlaGm6+/YbgHH3IND6QvaYYz2mZWF89x20/Jq+uSM2aYnsUhpIjOmUoEVMesdoe4wzzKTAMI5vNhulhxzwvFCXBsKYkrHZYbZ+C5URaFFCiukErQ5gnGuvoWkdYJkxBMptMZOvFGB3TIgIfYwh5wliD055hnMgErMs17M8Qc0SVjNGWeV5w1rPpzojR8/LiBZ6GcZzwXgJNU0UWpxhx/QqrFauuY5pGQsV+LmHhMP7+pjn/Oa5H9U+mQBLoRjG14FbQGPN0VkqhLkMGqkcEMjV2A2mdZeAQq1SXlHliJlVpxpKVENXqXyElnKm5R6rQGE12ksY+hkgY5iqTRWS0SrNdr7i/33N9e49zDb7p6PoVp9NBJKxdyyeffYpS4m26f3iQZPVpZlqE2mmNZGw0bYcxEgwdZsHV9+szTstMzJnd/sA//PpX/PwPfkLrG3775df85re/wyrNq5fP+PzzIx9/+oru6kKaEec4jTM5KTrXCJihIE2NElKbq76hjJIQVa1ZkhTSLQVdZZFWKyIQY93gaV0zlpJEK1WIAVomr49EQaMl3gGlaIyFIjQ+qwxeaRor25dUJTQiDcukkOhbJwKXpkGrwsP9Hd9+/S1/98tf8f79LaUk+n7FarvlV7/9grfv3pJjxtiG7foMZy1TWEBD63ra1slEOT1KAWVr3/YdrW/xbc+zq3NWmzMKsDnbcvPWEhfJdTqdJn71xe/4+LOPyDlzOh3pug7XikypMZrGemlsFOKN0rJtyzmjshYJdfVZLHWLWT8iE+8iuVMJOVYet1rShKo6vxZoTLby5wjtU2RSQp1+xJNr7GNulJKg91AJmkoj50N97z2iyvUjke97eIUcsN6yPd9inSEsM8uy4JqWtmTSeKQsE/N4osQtrTE0DRx3O8bTkRfPX1FK4f39LRch8asvfkOMkX/xL/6c/nzLPC4sIXK3P/HRqwshRGbIUTYm05zQ2w3LcSBMM7v7B377N19yO+z4Jx99zFmvUJce34B9dsFpOJLmSDQjzUXPdHtD+/Fr8jJKY6HqhtY4Sl7oNy3GO6Hl0aHDXHkIAbvu6JsGFxJhTLStQjUbdI6MhxMxJabjyJIK0TqcddDItnU8jvjjCZxB58LiMw83ew7miFKOc93gTpPIEcksIWKy5B9hvdw744Rpe9z2nKfQZa1EOt82lGGUJlapKjEv0PbkZUJrK7VcyRRt0SWTdc1NqjlKqm6sKQpioMwzZRGCXCmlwheyZG5WYIR6BNcI51tUA1XyN4f4NMBMOdM15ilCIWuFKpL7J7jtei7V8yYjnlCKRBzIA5nrBl2atBiCSHS9fC7jCssxkJeRNE1SnzYOu+pZdgdKkmFHNJpxDEw5Mi5SU0whY/sVhkILvH1/zd31DWEcUNYwqsizy5ecrTum2w2rdUdGPETrzYr+bEuJB+I8kbI03tZYtNGkcRY1E5lYEmGaUacH0pKJUZYg480NF21Lg6JfrThzmv7qGebinPj2XQVuyPnRaMPD9fXv7Rn/fjdLx4FeS6dp2wZnHdY5mqsLJjIvf/oZ/mxN0Fl8SrFOeqmbkvJYAclkaDoNLIeRNAXQUsQsy0TTtE8maKUNzmrmZcR5K6vEJ2OrpxiIqqBCwJLRplCSwjWGMM5kvSa7nlwiumvFV0ALukF3miUcMHkg60wuI1ZtIE+kYGSqbBQlLtJhG0sMiRwCqnjicsC5gvNrMA2xHv7kKBNvYwkpoYyjFHBODvCUIlAIIaKUSPDiEnDakWLCN14mMjHiGlcffDH+Oi1p2Yv34lNIhXQcsBniNKNbjysO37ZAYbi9pewPKGuY5xETInmKRJ/oNmuR3zlLu9lgfcv97T3OWGYKnTeo3YiNidZ7HmKgW20xzoHNXGzXXFydsX/zhuA9b96/Y9VvmULkfHMJXUPYv0HZjnj5mvXnf8b7+Guabsvv/uELXj1fQZmEOuc6gm5Qq46yuiB0W7JpybpBITkmggl9zNBRYBzKeaYUmYtiffEMYx1tXxiTFMihKMCSi5KU7FyIoUoRkqDcrbXEKVZhTGScEzFljmFm1Wm8MU8BytM0YnTAaPGJqBp2GaaMcRHbiCxGafWEGCsVqdwYwyeXLxnnAV0sS1gkOBLLHBaWGJ7ynR7JXDIxTixJGsTD8STjye/xVfJjSGptgnJGZSsoaWPwVkuyfTVqKyVBpEpV8pt6xI+XJ2N7qmeyAlI96ELKspHSkrMUqvzLaVXR8AWdASMDnW3rCDHh6z87a1hyYb9ElhzYp4izjsNx4v7unjDPNPU5yyFyPA2M48TPfvJjOu9pXMN+f8AaS4yRsMy0jaNYTYiPDZNhOB7JYWG12pDCyGm/p+TCOC386je/4cc/+hFpiVxffyDEwM3dLUYpnDV43/D8VUfOidZZhjBjVMFbaWoeY8CdEoDFmCVM1VUpqS4Goxu0iqRSCPOEMZCVfP0xlSeJsEbJht81dSv4CINQWJWFqocSUltOEnhpNE7JhkpXCY/8VfBasVDElGwVOmWsVXhvOOwO/OMXv+PNu/ecDiecs5ydnbE7Hnj7/p1sFVH4tqfvN5QY0bnQdh39akOKM2FZxN+lPc5ZlDJYZbDOcXn5jMtnV4xhpu9W5CyDOkqs+GItXscQGYaJpuulkdearmuepHxWG2nEVA0NLqV67x6zmKqHKIvcM9dGMeUsG6ci26Rct3JGfbd5yiWTta5bjIw1IknSiJ/OaPf0+RS1+UIM70sWSp7WGpViFfx9N7DPJT2h4r+P1xwCjXOYIoGdACgIqdC1HSgp9JU2xJBo2ha3LCQU++HE2cUlX37zJWEJXJxfchhG/uKv/xq/avlnf/anXJ6fE0LkcDqxuzes2OIA5QxpnjHes6TMmCDuD6R54XAaiUEJMXEJzMcRc37OvDtA3xNPN7jGE6cRRWF+uEP3Hp0N+BaVFkpcIGdKDMzDQFx5nNKkAAWPwZGWyONkydhCWQbGSdHbS84uV9y8ecft/R6Nwp+fMc0BQoCYaZbEsB8xqxXL7kRerxnuD9gLz5e3B94cbviDDGVcMN7QdlKfhJzxOUt+kjKUlChV1vVIc6x6cxHPFZGWlpjEUjCNKLulxBntm/pTlOEBtXmnSlXLk4g0yZA0JprzM8yqI4cF61aSaZZzle7V31w3sinVyI1CxX0nljijrWzFhinQeotSGZOrzLtKYXNOUuelqmxQMvjXWv47BO2fsBqCEmly6TxGJeK0R8+FJSyMtw8cvnlDVhZ7eSWe/CnAEtBdT4xRhk5WEyZ5lxlrKUSWlAlBrCcJS7va4EtCm0LjDcYq+r7l1atXTwokjGEeZuI4oQg84sbriI5xf8RrxzQF2Ti3LdoWkkvMKZCsY7i+oSPTbjqstax0Yb1uOHv98on8rJGgWqWlUTze735vz/j3ullCKbxzkgWjFcNuz+psw5wCzWZN8/KcZMuj1kAwjepxwiuFo67p5uM4ctwdSMeJ5TjQrFrQhVXTMs+B9WbNKc7sDgeeXV3QO5mQKYRMl3PB+p6SNSkidKBKX7HWQx7RrqC7DkwWeYbxlGwoqqOQ0aWg4wljI6oklHdCfUqJ6FayLs0DtAaVNGo5ScaIcTi7EFMAtUIZQ8gRjBcylaq5FyBBec4LpjxJbotGJETGaGIs1dwpmQkghYUyBowl5iLmxJhJMaKsNJUACxH2I+9/8yVpmVHekmJkvdkyPuyYdwf27z6wNpoyDZRlJk6B0/7A+tNLMPLyt21DMYYlJJZhIS0T2hlapzns9qRpwXlNRtM9v2LVWPptx+b8kuF0YFCKt8NCv33Gxarl7OIMvz3Htorh7a/xz/4M5z3H04mP//BP+eJf/o+o9SvWfsbnHQ/XM7dLof8s8ezTz9CrK4K1KK2xVhLZUVCMJhcpYpQuuEYRlwlCYNztuHz+CozH+ESaZx6GgaQLSlmcE2pgCBGyeEWMlSnUNA6gICmR2IUseRBGO8ISMChU44GI8y05BeYQ2HRrSlJo3WJM5tEIr4ypE22p4GMOaO05a9bokGi0BzSmtdhSmGfZJpRqGn3Uni9LkI1SKSwhoLVmCYH/SDfwvbwM6mkimUkkrckUUkwkKzltruaO5JpZZHj0XkhzZZSCuqUoT9KmmvFThAj2OJ2cQsQ0Gqw0UVMQbLLTGmerHKkIHjbVbRYFQkwYbdj0nnGc2e8Hvvr6G5QyaCOZGimlKnGSrLP9wwP9queSIptvq7m+vhWzcG2amsbjW8+yDELEW60J8wg58uz5K8Ay7O8opXA6Hfndb3/DDz79DO8dDw93DNOOzarjcrvho9cvJbutZJHK5cQyTaTWoZtCSVlktlA3TfIwzVEhNhyRBi5Z03lFYxWFRMm2bh4K1gJkrDM0RqTRVelFFeoJVAPEj6MEmx1jEMlkNYVbq8VThPzeBshaM8fAchLk8XrdootlHCZ2DweGceQw7Hl2+QKM5dtvviGEBWs8OMvzyyusdRymE771XJ5d4IxhyBnXOE7TSK6FHRpc07I5O2OzXTEMA23X0Xgrc2JtUcaiimK12aKV4Ytff8355QXPn13gnHkyluecajSA0LVEdZTRGFC5fk9kc7TEVDdJUnSGVCMy0IxLfGrqKekJ4qBq8acepdvIffloLi+Fp4EDVb5kdG3YgJAzpcqFTAWjhJihyCZK8TS3/F5e69WWnAXFn0JiHoXS1axXrFpHPhqOhzvZCuQk8J5xQrczu8ORaTcwHA9YEfGSU+QHn7ymbxuub28kKLnAOA18+ebIy2dn+PxoHxBP0XiYGWYBnzjveN50mK4nn0byVkJyV0qTTkf8xRn65HF9Q4kB3W4IN+/x656y7XHakMcjZRox3RqVM2GOpAQqCSmxRCFMMs+yXXSypU5aWoxcCsvpiHeOpm9pAqyt5X5/4sPdzJvbB7rDifVh5GKKqJQx/UDXNKRhYhkGTtf3vPRZZNDpDNV1mGGkSYk8juimReVUfdlWIAHLLJa4x3u3AhJ0XZcJ/j9BmNHWSl1YoV2pSO0m+HMt26R6PQ7GTNOiL414uB9zmarMWi6ptVR9FnKR+74o8bPmGkuRQiRiWEJgnBfONy1OF5QREJQ2tlofpEnS2nyXCZoSZFFBqFxqsC6UmCljIOQRNZ8owxG0Y373nvjwQNQed3YBKRJH8fvnFFFZ3gnzElmtNrAEDpM096uu5SGcOO5PhBjZ9J4hOgkln0aUvqw5eoY4RwSmJiCjNI9Yk0mLeJVShN2HW85fPiNnmMNMTIFw2jGfNM6coFeofWJ8uOei74QQq6F3DVcvXuA3a8Jxh7MW7S3hNKMzzIcT/vf4DvleN0u6EfS1aRxJaawzTCmy7VtM26AbmXSpIhrOUk3ZT2taJRNzQfVqdBFilBh+i3TuJWO7BqU1JkszscSE9zU5GcUj9lAZTwozKgXSNEOIhGFEbx2oCeU9qSS8kYdQWQ/ZiKESYD6i8iLBYMc7mosNeRmxdktUirQcsGUh+Q6thLimnENrBzbg9JpMS6CgjCaXhNFWXmxKk2LAPVYW1bifchQGnrKc5gnXtOSUaZuGm3fXbC7OaVxHrp4MkzVhrinYWnDLKacnDfz++oawP6Ks5A8UBcYq8hIY3t3QqIJrNMf9gFWOuCxYVSQAsWR82+LbDuMa4hzRSRFLYXt+RpmP3H31Dq0dpmvofMCfrTjb9viuxTcNhyWwbM/ZffmWq8srtudSiOjNisgDLz56RS6K+y9/g//jZ/h+xdf3N/jznlcvWuY379Cq4Y//7EesXr7GtGfopiMYL1kB9aWYq3wkxojCkGMkkFiWWaYyujxhQLN2DMvA7WnE9RJuWXQhxVL9BUIA1EjBIedpxhVNzCKL0VphkOyT4xhZtZ3Qs1JCZY1RDfMiU0yF5XB8wCXH1q+EvpaLNNFRJkS9tU8yEVVlNKmIdDKEBdd65hAZx5G+7aRhjxJamkOUYivOki/B93uzhHjX0YXqaxG/olGC6y6Pm1SKJN1nIReWBNapWqxKkRryd1NJ6ZNkWhnFf8wQopDncsA7LWQrJebfjHxekcrCaQqMS4Ca2aSQoL9cJIh70JppjhyPB6wxaK2x1mGNTOtQhTEEck5cXWzZ7w7MrqWrUkqyTPs6Yzk/OyemFff7I4qGxTvmccK1HS+ePedtGAnTDLqwO+7YHfa0TUvjPPMycXf3wP54oJTCNAfSkmh6T2MMeZ4h9aQQyAnRsmtFVlUmB4x1s1PQpKJRGIyOWAuhGDptWJAmNeWMNQZFxFvZDlktfjytFAUjw6rH57DI72mbBqckoNVrU6l8mjxLun0aR9Q4s9aG4+7I8eHAxeoTlsMgBKe4kJaAM571ds23b99w2B9ksl0SlxcveHZ2xX4Y8E3Lxy+es+1XzHOgtZ6H41H8EIVK9BJFQymFruuYa9M8LUGm0YB3Lcpo2rZhHhfGg+DLc4EpFozK4gMogmmXnUbirGvwWotMrkocZbtU6vMq75lHCd4UI/spsB8Fw943jrPOP4X7ogrOio+Pop4CmR/hGBRBJBu+a6ZybciUlm241TL5j6n+HgVZ5RrO/P2euTzfnhGGCWutUB+Hgf3uyKprabqO4eGeYRhZW0WIif3+yDEE2vNC03U83O0BMNawanu8MvzxT3/OJ5+95ub+gf/h3/47fv6Tn/Dmm6/om57hMKJTwqbMkoDGotJIgzxfizacbTaUEJinBWMnOqu5/903mLM18XCkW1ni/oRrPWleIEWWm2u8/4gU9+TdTpruAtNwIJeEdgpsx7J8oIQFYpYBXVbEOYgkappYosHnTMaBKhwOe9brLWuXaVcNTdrw4f1EioUP7z/wy6/fUJTCrta0FPrtmr1ZYeZA9J6HJRKWiJkzvhga7cjDAG2P1qB8S9GC5kcptHOEOcmQF432IvvDeh6RjSUKjU7Ryia0hlaXmmX0CMuBumR6/JgzPIXcWssjGFzqSgNUWl0u/9HnKVIn5vRUg+acGYbI3W7HL/7+l/zhTz7nn/zJj7FZtsEKgY6leiY84ZeVItWaM9fAaFVDtJUGXTKME3laiMeZ+fYt834vULDWspxOxHFApYyuGXCWQq5+xdNxYC6KOQj8bH88Mi0ZjMWVSC6ZqAxhDqxXF0xzIMyJu7sdz/oLIZ2WgrIG45zkIWEFMrWIhz2kjAqAssSYiMcjeiqo5h7jDNdffuB080CMUQBZ1nD+4or28oK72zu6ZWQdM8a3mCmwTJH5NLLerv5/H83/ZNf3ulmy1tO0K8ZpFOlSKbjG48+3qE50kTJ5ozZGdcqQxb5aipB8cs6EELBaM+SE9gbbWKY54dqOxSga7wkxMh0mYswUFrq8piBZGUopsFaMisMRFSIlBvZvvuHKXkKsUrgMKS2YtiNnWx+mRIkzxIlpuqOzVsK/Cqjk2O0PdFcWNe/AGKy+IgUxLWrjsE5TMOTiMDXnSRV56GVj5IhRvmbnLaXanB+xlKrSShrfVlKMJk4jjXdV3lKD0h5F9xRSlS6FEMQUnUHtBw5vrmlcw1gSIUWapiMrmI8jjAvOwzyOsjmaqxnWKOJpQHc9tmlk4j0E5lAx6cbSn/Xs/+ofCbsT1gsYwZmMcSIrUU3LzWFkWArvrm/wStNbw+ZiQ04FS+G4f8D7ie36jJMzrM6u+Iv/x38HqxU//ulnmPf/Xig1q55m69BeQdsQtJNNGyI/kUP9u62B+EwSYQmicy6KVbeqJlGF0ZacFcfTSGNbjIIm1wlWJXrFsKCywxr7FMCZEaTvo1jIGFtX/ZrdsKBXmsY0tWAS79O4RJFwnV/w4eGEaWdWq14Og1TvAWP5weuPOR5H5pSlWdJSCIVlJsSAKVYkfkZLhlBMhCh+tcMwMKVC6zXaaEL8/hqz4TFXqf4cShFCWhaZkTO6GtTl14i8SKRjpR6EqMfD9PFfRXoUasBSKpmUC0uC+8PMvCQOo+Fs5eicxSDyRl0lnamS8eYIqaiqeS9oDcscpLh24lnzzlJyDW3VFucb8U0ejvjGs1mfcbHdYg1cnG84HAasdXjXsMzL03vJA5umY33lub27Y9OvGa1jSYHLs0us/gFff/OlAEaWwDfffMOrly9Z9yvZLpTC/v6BeRwYd+JviOOCzkLCyykz704S6xATxlm0o+aqKdkwaZGpWCUNqdYWbTKNMoQiBLeihCDnNKx9Q4iFqLQ0XxU+oxQ0zkgzwSMWXqbM1oBHYask1RpFdoppP9IYy3h6kJDMJZPmyHIYWFLk7uaBaZyxxtK2PcsSedjtySXSuI71esuf/vinJDTH8cSzzRkvzy5pG8fgZh727yUrx1iSNsxzwDqL0Q5nGxm6ZBm+nG23PLu64vb9hnk80rQtXdMLYZHIHCLLHLHeEpVAP0IIYCX6wlnDEjNFl+8UskV8REm0QPJuyYklFcaQ2U+J3WnmYT9VKSN4a2jsY65S/RRGPz0zOclG9TE4V5dCjEmiNR7z85R+EkM9JpnJx6psuOSaOfZdKOf38dpu13Rtg+16TqcdOWamceDFqxc8++Q1b2/eix901TFPs0CSloX9wwMpJsbpRNOKfDVN0hB3XoLKb+/umWPg//2v/nueXb5AKc2H6zvwllXvGbDEUIhKYQ2UZSHMi6DuxxnrHeNpkeFOn9lsVugUxVOTpU5inijFkw4H4u0tNBp9PJGsSL6Ns2CtQIHIqBSJSyDHTA5QvEYVwzLPoDXTNGGOB3qjSOMsQKkguVB6HDnb9Jh0zlzghTbMvuFhCCxKSeZTVty8/YpOZY6hY2Udq6tLkm+5351Y3tzQP39GW0A5aYBkSCUNSsygiiIri+56yJEcA4Kgqy/sklHWQT1fnxobSReXX1tVM1ppJG9VyJLZKqhgn8ezWvFYb+oqRZVj4/GdlEIkpSwD9zmglGFaAllpfv6zn9N1nnkO8m5/lAIq9Z1lRMvZUkoNd86FFGSAqknkrCTXKUdUBqUsRSmm+3sIgRgDcUmsL65EkW9kgK6bWiurIkOZpRAXydU6DIEpFMZ5ZhhGPrlaMY1HjGuY54hqV2AqmRAhAhujUAms/S6jjZxJc2Lan0imIZ8CcZCNZMypSj1PFL8w7+H44Q41R3oDV21LXK3Q3Yrf3e0o48gPO8/KW9SiKBrmacKVc/Gm/p6u73WzNOVCVmCsJS+BUArnVxfYbYddNQTy07TxkY4EshkoVbeeETiESFZ2WBQhCU1KWUPWir7vBEfuJMF5GE/0vRZUeYzy4leCHA7zTDwNLMcjriiG3T3Ne5ngozJ6vcZZS9QeXRyxBPkppBOFgEkZNezwq3MQ1xP92SXMAzov6NVHZDxGjSIrsVYe3qhQOhHGEbJoYa1zKFNlPUokWBlddeJZjIsx1WwSJQj1SgFTStP4hmVaUHbGNk4S7x8xlpUSVkohhkAcR27eviMfJ5YlYvtOdPHOE2NhPBy5PNugU6g/q0jWmaZrCceBxIGzs3Pxf2nFvD8JuSksnF9u2H/5Nfe//Ya2a8kapuOe1VnLum1wqzWxW/Htb99ivWf48J6r1ZZV42k0KN/xcPOWZy8uaJpCblr81Uv+9i//nt0337J99QKTC/HunjgttBsj01XvqRZkFGLCF4KQTHZzzpU2BzFEodEUwDZ0zQqFIyjJNzFotLLsTxONb0ghoY1i7RpSCFhTv58p1ReiYsxiglchI1oj8cqQYDjNNBXpLrh4SUk3WBRCXtpsNihVg5eRl5auL5PTeOJ0OhHCzKppyTEyLyPjNOC8vLRVETy4JrMb9pyGiZQi+3nGNC1TitiCSEu+z1eVMBhdN0wodFE1nLRKkFKpgxaR85YqjSv1pHzEh5eaG5RLRYqnjEKTSuEwBU5z4jTMxOjQCi5WmdZCjqCNNK1zkMDbKUiDqpTiNC6sei+TxiANuVaa29sHcobt9oIwJbxv6FdrliVitMiUrTU0ztB2PbnmEzlnsb6lFBiWiePpSL9a01hDcg3rsw3NZsP76/coBc8//phlGnj39muMVszzibv7Gz776DOWZWYaBm5vHvj6d29xxrFa98K6Sxm/XTHc3bOp5vdEXW4rjXYWoWPI1uixlsEaQCH+68ScMs56wVQr+ZitKfagMUajMkjsicHVnV5OsnGxtdH1WuGr38zZiodvNMktuFw4e3bOF3/5C0pRfPKDj0gp8e1X7/nHv/81h92RlBL9xrM/SrAjKFIMfPTyJZ+9fs3b9zf85JOPAcFoa6W43+05DoNMrJO80zIK3zSs12tKyhyPA5fPzvHO8YNPnnN9/U6CPV3LxfklvqkxFcYynybmJTCnSOM9RSX590XROEtMAaXAV5BRb63kTdXCb6rxAGgBjMQM4xwZp8QcElqLGuPkNLZzUCJOi3xRxM8VUV/1i/K3Rwx43URl8TI9GuCVEoR5TIH0+GuUfNwkviOKfU+vf/rn/4zhds/ubsdyHGBzznqz5vzynGkY2d0fML5FW88wjIRF5Mu5wOl0IsUovpGUGMaRtusZxonDceKwP3Gx3XBz/ZZv336NU57zfsP2pz9EzZnboslT4Pm6hcEwp4JbbyFNxCWSjGa16gghoGJiHgfaxpOnRLnqSCGivaXMC2kOmLtbUufJSxByWttgna0bjgJkVMlCWjtIHEGJmWI0cQmUtiNmkTGH44k4juJjvjhnGRZMTpQYaL2Whlkpmu2aL2+/wpiGjTPEuNBttlxeXdL4QpcihYwrmVXTYkzDPIzEhz22azH9Cqe8AFuQ9/E3v/uaZ5fnEkGgjURIZjnLcww1uFmamqKluScXipbMMnh8YmRrqhAUfskJZQTi8JjNp0qpmXb5aWj29Psez4ZMHUQsaGMYxoUQM843dN5wselFHl2oKiiePICl5KfPmR/VC0qeJ7Sh1ZYlJCiJHGeRFFYAhO46wjIRhhGzbUkxYBpPGCZULjImVIoYE2OQoVuMkWIs0xwYTjOn/UjrHbvdSeroAk3byznnGoqCdr1iPC6sfEtWCucVpABJmsMYFWEu2N6Qg7yDxhjkTJsm0gypWO7ePDDsTlijOVv3XPQd6sVL/sOb9/ziN7+mUbD65CNevX5FDjMlAMayvrri/v3vD/DwvdbPLFYTnGHKAdU00DbErsF2rZiuebxJa2GTS6XAlSqTqT6FlGWFPC+MNw80RVOGWdbcpRBOA0TRtm+2K0quK2GlmcaRlMQcl3OElFBRKE0pRFrnGa5vCMe9EERUJqEpqiekyv6nZluUTE4DOU2YRpHnHegIXgOBpcxE2yGPcKz6b8hJvABhHlFFmidTJxIp1sTqp8deJihGayEJaiOFl7FVphXJKVUTunirwjQRxglyEsJdkNT3EjNeaXQu3L/7wHi7k1yOVJhOI3GcMakQ7w+0OVFKIJUsD4rWdKsO0zgo4DYt9nJD0bLFMNagpwVDIdzfsfvFr8WM2DZEY4hWsVn1kgnV9hzHiOlXvH/7hvNuBSajGshoduOJmA/E4UCzviKpFW+/fssXv/glD6eR3Ho++2SLZUAtgXAa8K0nqURJGSpKV2sh1pWcn0iKypinnCGNFsiDb8nKMsdMQGR4xnXMc+I0LFzf7tjtThznhdMyP8lVQowkJbkkOWeZ5sZYJUeKnBLGapaSUdbXDC3LkjQRi7IdmJYxiJbc+YYQxGeEkuDIEBaM1YxB8gn2hwemeWR/3HEaTwzTgLGyGqdA33j2hx27444lTiwhgjYs40SaM2C5G8b/Eo//f7qrVIpjFqStDBKg8Q7Dd++QHJMUiUU9yRIfN0s8GluLTNnMkydSiv55ES/RsgSWOTNMgRQzMUbmkLmvqN1QN1DDkipsQzHHXPXq1I1uZhonDIWzzYaLizParsF7j7WOfr2lW61Yb854dnmFMYbbhz05wapfC562EuWgkGPmOJwY5wVX4MX5lm3jOfeWn/3wh5ytVnTO8Of/7H/Fp598inMebS3DNPP+5kY2kily2B959+VbxrsDp7e3NErjNOy+eYtOiW7dgyqSLu8f88kqGMIYWmPxVtFaQ281vXcYbVHWs/Ke1tqKrS401uKNpbOWM+9YWYMzjtZaemPonX36X2sMaye/rqlhqtZarLNoLXLL9XaF1orNquPZ+Tl3X73j+OY9xw933L2/4fr6mmkcSEkkx4fTkZQDSiu6puHZxTnozPPzM642G3rv2W42nKaF/eEo7xEKU1xIKYqs1llSTmRhlxOWxOefvebzz15xtt2y2mxxzpML9P2Kru9wjZNmdZJCByVTb2sNRlfKXS3Cl1yYY2LKmZBlWDIvid0wMwTxJk0hi4cpJZaQiCEzjgtTSNXnKOOix8BYpeR+fsphq1AUOSsyy7yQM0/+pMeQWo1IXL2WEJs6txTEcvUHigHm+3k9/+QjXn7yEefPLlEVF312doZznuvrO6YQcJ0MEDOK0zBCkucmVIx/QWSxCdkQtqsVMRU26zNKSISQ+HB9g2k9v/nmd3zx1RuGGAk5MsdEjovM6rzFlEyeE8VolBHPXYiJeZ5Z7g+4RmBRJFEulJhIw0QZZ0FsnwR7n4sizzPbiwva9eq7GmBZKFmz1IE1SslZ1VjSsjDtj5ThRLzbM94+UKaJEiMpBGLIpPsdaVlQKZFPI6kSVlVcyCVxfNixf/jAh7dfyZ91vhY/XYyMtw+o05H+7IzNq1f0z5/juo44jpxu7xjv9yz7E33TEpYgdZ62YDxZy+BK1tpSI8nAs97LVf4mqoH8NBB44pYjQzOlJFhZayXEvMcNq9JPHiNV369Gy/ldKrxBV9n2nARzkhFvakAsB/lxS1aVBqDQypBSfjL2mep5SknL8zoM6DjjKk01x0QJC+E0yhkWEyVGcGIlyHGBqjTR1lRqpcIaw7JkckysGk8pirwsqGXionMkDFNIrLoOZ6j+OhkaqyJDG+MbitI43xKWREGG8DmB7SRI/bE2V8bWr21hHhSHO820D6QpsN00vLpYs1n1uKbh/c0N+8OB4zyhvcU4g67kPds5lIp0fcPv6/peb5ZW6zW6a1g5y/FhR/fDT2guBNu6hEm6/drdCwpcbsTHSxVYQiCcJubDyHwc0XNAzYEhTJi+wXgx9gdknVpiQivRgD+CI3KW3Iq+bl7m/RE1L8RlwvuWL3/9Sz62mu7ZGQVFyEbMb0hzpSlYd0GJd7SdIipN1gpSIpYJlyeKOuH6FxRaQh7wWmO1IlUssTKFxp3Li8BLUnvMpSKgY9WZW3nmtfiMyJlcRCDhrJECuR6+S5jIWTJMlrBIpknJOO8oQTxZ3jXM80LYH4m3u6eDcBlnsrPYzpPGkeGrb1DDgN30jCmKeVyJBEdbDyTayzOGHNicXxLngEqJeT7BMvHw5ltJp7+8IKbI/f01l8+f4fqeoj0jmpv379Elc2YtRgm+UhvNEDLGJZ5v18SSePurL3n+py/45b/5dwzjzA8+/znNEkm3Hwj7XV2p1yBIJUhKSe+W1b0YxRNZU02g1PW9yPSU64jGE43l7c0dyTq06zjlwhwLb6/fc3Z+haMwHmbcmcWhaKxMiQSbbnBNwzDOoBxBSSHvlWFcFjAKg6JxDevVipxGTuNRxvUZrG3IyJRvGmeMkZ9tSpGYInkScXPvG5qmYVpmdsc9MUc2a8nGyik/TZOnZeY4DLS+5fY0sSQh0BSrCWNk+r7T8ErGavW0gQbxL6matfNEvStyoJRqcDaPdEF40qjHlMgpUkphSUnobWiWmDieZqZh4fBwwpytmGMkZiEgaq2loPINsYiXphRVMz9E1hdTpZLlzO3DgeFw5ObDDTEKbMO3Hd43WC3NWkqJ3eHIvES0MZyOOzbrjsPQ0i4Lp2FEY8gqsiyB/XhC5cizzZpGacmK6+BnP/yUKYuE5bNPPuXdh2tSCBQKu/0Dzy+uhOzkHHd3O373d1/wh3/yE9Q8Mx9PWKU4vzyn8Q6sETCKEjKdSWCy5E2FXColTt5P3hSSskTAGyHCHaeFtvV4FJ1JmApvSCisjjhjsVUzkBF/QNRSvLtaKGmtycqAVrRWQjytNTSbnngY2J6vWa86bt98IBvNb379Gw6nE+MygvXc3N4xnUZQEh/gvcM7x9lqTXfRcDwcWKeOm4cDb969Z5xkoBZLkXtDFdlqJZFeWiP3z6bveHa55WG3Z5zG6l9Dfm2Wxvr4cOTNm/doa9hu12itsG2D1oqs5EBX1auEklytlIUWZep7LSaRhdqnAYHcW2GJDKeREjMqBeKm5TTNWFVo1x0gG6FMIRVVvUbiOZJcsoS3tvo3pIiqGnjxd+YsXgv1WJvK2ZzqdpDvb68EwPbqkma9YQmLvHPfB+ISJX6k67BGMd7d0irJ/SrWQS50TcNhWcj155KBVBLGNZymRL9ac7cMfLh5QBvPV1/9jrxkxtNA3zas7ArfNOQSICbcuoPBM0fou5asYBwiWmn2w0i33TLOC00SWb1a9zhvsW2DZLRFdAZtLSlP2L4SNlMhKSUe2Mcto7Hgk9RXOaOmSJ5m8VbOAYrAC1Z9C0FqojLMT3TW+X4nw7cQ6Evh/OVLrFac9gdeecfaGHKYme72mIs1qmkwbSsqj+MRH6/QXYdpLbprcXFFHAbGm3vS7sR4OtFfbPGbHm1AG/Wk0tDWUmJA+UbeGKrKBHJteqqE9HHzpEpBxUD1c3z3g9ePAQjSAGj1KDgtTzj8VCRXiZTquaEq9l08Yc4ZShGPElSLUj1vyCJS1RKoKduvnChZnr1piWw7i84BnQKqgrsKmZICBaFSKqPJ84LzjjSdIEeK9zzmP80pM4wjKI+zmmGcmKaF3f0Dy81XTD6wWV1wtx94OO24uHpGtpYYAopG8qTGQFpmrO3I04wukq1UUmEZZkKsNemcsK1Hzx7vW2zXs0yKUBK5aJSzbPsVruux1pFSZtN4lNJ0fY+3DooMhpQRuMTD3Y7m6vL39nx/r5slHRJ6bcmhMKXC5UfPMa1jGUf2+wdWLy6k+K3wgIJslDQQpuWJXDUPE8tpFL+KKszHAXQmzUIZ8q0jjLNsoUrGdI60ZJZpwjSWbA26TpOn04kyzaRhJCXRpbZ+zf5+T/f8gjmASxDnnfDo04LRDQqDqgZK25+BbcgGVFmTxwd0msGtUWERrWlKVeajMLYhlZmQFjFUagk9VUoTUhBvlhbqizYSWpkpFKOEpuIcqRZouYh0ZjkN5CVgraV1jhCEnlKWBU0RqWE8ctwfWQ4nVMrEAo1vMdbSNS1Oax6+/Jr7X/+W3nmOux2ma4gloJBJ8GEINM8v0K3DFCVo2pwxIdBdbvjwt99w0a14v7tnUg3Xd+95+foF282a6TizevGCt++v2VxsOH37hl4bFlVQS6Z1K1JYOFtZfHEcbg/Edsu/+Zf/mg/vb/jBxy849wqdFsYvbygLmH6LurqiGA9JU1rPgkIV2cClXGqApRTXKUViTGgMyTqs78E23J9GJgrzsnB8OPD+4UDTtQy7PbuHI22/YrPdokvhYr3GqFIzugT/m3LBG0FFS4UcJWzWNuQ44LQcTsuY8L6llBkNNK0nBXnJtt6IDMu3zDGyxEDOkTHMHOeZH734hCkG4jRzCoGm4oxDyISY6HvP8XhkdxzItuPvv37L//DXv+Sf/tP/Nc5o5iWBgel7XuSox/wX0ddJ74uQuoRql+uGViSYoLDWoHR5wh2nJJvhEGUaGys1T2vNGMU4G4I0T7l6jEopxJTpnaH1GmsV8oeopyYNrWSLW8AbxTzNlJS5/nDL7fUdMUlxI+GnshVLKcm0GsXt7T1vvnnH1dWWFAPLkujajv3hSOcb8jQxV/LSFBOmTPTO8uLyglIS7brjfN3Rnb3gw8Meb8W/QsmEFCBn7nb3rLueYR65vrvl1XrNcPvA+9s7zl+/4MVPfki77oWC1niCFpeAM0o241qhsmKscv/OaTwi0SnGEJDpr9OW1ihCkoKkq5sr+T4ZuiL+p2qrwRgJTrRWsLypbkmWXPDW0JmaOZQFTOCcw/QtndWsnOHrL7/mPiR2x4Gm6ehV4ThPLPMEJVJyQGlDCoGXz59xeXHONM08f/2Sr795x/ubO8ZJ0Ma5BFKd5srzqoSwqBTKKLbnGz756BmH/cAcArfXt8ynE8t0IvQtwzARwoKisLntubq6ImfF2bNLQn70HBaMkvwipfTT/dVUlUCp3ruLTQtKDNwp56eA2MfmX1eMe6q+MasfYSWKx9dRKVlgEVrVEEppyHSVqErMhkh7VM1SeaTd6erPS+W7kFqlqp7v+3qpQogL7arj+etXHB72+Maxf9hxun+gO99iVOFwc4uv93CKmdYYLi4ueL/bCwypFrkJxAawBMiF+5t7uqbl7OyML7/8NSVEfve7L/hvb6/5P/35P+ezjz9HG4u1Cp0MynkuXzxjPuw5HQaaruN0OtG0DalEdCpoozBtQ15mcrCwbsgh4lIhh0COCddJRloYB+bbO87PPxIam1UkZ0hplldW49BLxjiFspo0zyQMuTFM44TzDSpGlBapedGGMk9gpUk53O25+PQHAgRIEdM0vG4abJGgb+sMXdejrSFpjVv1ElSrFSnMEGsmUcykaUYb8L2vEnqYd0dKKVhnsa3FNZZiLKKrh6I1uvqNUTWIvMrn5DyQd4VGmpeiqJphgPriKrWJKvVeLgJTUXXTZJxBJakxjc74xhFixjsZhnnrnqSZqaqDHmFkKWX5Y9Sjc1bOqFwKSxKirpOCULaUQ4SQUd5j1hvcYUdJHts15HkmB4ktUUGynnIBYoaYmdMErmEOmeE0oqcHmG85vB0wV8/QIWH8OUuBRhtUXCAmVt2KEiIhZlqlWYYJ1QggKRRIymIbwzguWKOxXYsD3GoN/YYQZsJcmOZKOnWaYuRnn4yRSIUidZFvPXGaaY1Ftw2EJOTn32Ow9fe6WRrGgYurS7IpqLM1/vkFScNYkZAhRdGo1hTzkr8zAeYUCYsgPKfjiRKEwU8upHkiqYwuGa8a8gwNmtN4wDceXQrTOLL4FTiFpsE7zziemPdH8kHkXMs0UObIZnvBHPZ4v4WmRcVASQtzzFjtybYQxiM+nVjyiVatifMMtoe8YFjQ9oxlWVD5RLvZEHOgICQjoz0UC0rkawUrEof8yOSvGSbKkqO8JHOJJDTGOCq9l5SkKHRFUaaFNC8MIUgmhLVM80zMqU7XRbqoYqbBEI3FN77mMjlMo1nGgbf/8I+oYeT89ceEObCcJrRVtO2K3XFB9T39x6841VwXnWWCEg30qxXKOd5e3/Du+pYff/YZLz59zctVz2F3oH/xmg+7E6Xr6BrHfhylkVwKvvNk4PLyjM3GcP/1G5ZF8+70wLe3ez67uuDTy+cYJYbru7sDrWmgv2Lz8Y9Y0DTFYl1DMjWFusir11iBMISKAU25kJXFtCuU65mmmf1pIORC4xoWV++3eeLHn3zMVBT/8OYNw7Rw+/4d/9t/8k+wTsJNc13RN8Yx5sCHqRCV5dxrGh05DSNN4ylKjJ3KeVIs9H5NLjM6ZoyxjOOEsuJbOw0ntHUYZwjjhLJOir4cOY0TTsv03hXYrLbMIbFMC957Dvd7ppD54qu3/J//r/8t6qMfcNP+Iz/95Bmvt2vyUsmI3/PLGiV5V0qMuqbmc+SUSBpAcL4a/STbKEieTT25iEloSDEGoeKVUkMIk6B1rdDA+r7BaPDOEnMmZilulZJDUinR3avHfy4Fo8Fay2mYWKYZ7xw37z+glBZpTQiEZWEA+tUGYzTD/sDtzQemZcbXqdwwD3jvOVuvmQ4nWt8SJxkElZIZl8AwSzjx8/MNRmka57Da8KPPPuY0nPjFL/6eaZrAKMI8E8LCYg3TbNEZ3u4eUP9h5I8+/4jtiyvOn11QkEKlGDFN966h5IA2jqxFoqiyFNBea7y26FKEpKk0SluMUnRGMYRIzgIYMbmgrUFrS866ymAyaQ44I/kfumakCNtA9PnGPEpnCiWKLLmxBp0i3brj7HyNKpkPtzc8e/WCcusYP8yoBKt+QwiRcRpkWJIzJRXivLBedwxz4H634zCciDkSU2bd9RyOichCSQGswXpPTpHtZsMnLy/pu4YYFwyKaZqIYSaGqZqkI/uHe0peg/6Id+8+8NkPPyGkRNu0LLl6b6vuLeYinqRccLpglUh9VCkCIcqpCiOkuXRWKF5GK7QzkqGUS1UTyLYzZLkPlRYDfVun3+LneCQRlkrrK08DA3KWcHQe8c01xqMItl9pWP6j/Kzv49V0LSoBRdGu14yHE2kKAk2q0q0YFk7TTLvqKIWnENH94YBSivV6wxwWMhrXdAzDRLtaMY6BjOHzH/0Bb9+9ocTC1WpD2zl+/e1b/u//3f+Lf/FPT/z5n/wRtu3wTjHvjjRtD0WTosh226alGEUsmTQucNmjUpTeoDZlyljSLJ6cMi+kpsEox3i4x9pNhUZlinci42td9deIZ0dpgxkNjfcYJe8s5y2NdxJfEiBryNNMmAJJG5YkTcp4fU07R9rzNduLM5qS0THQGIW1mlK3y3iHW/fos614hGIgxUieF+IwEU5HjHOk44E8LbjtC9AW7Y2odVJiOgUcBnzC5dofKUNR9Z6t/iWltdROWiBV1tbtTpLcPdn5VElqbYweTUuSzawhBbQS6Zy1Bo9mDBNWCV1VG0XfepEzR+h8JfY9XvWxkOgPVbdKIhUcwszd/Z7L5oxGgS3AspDHkXg6Se3nWvR6K2eaayDOqCjgr2yMbJZKJi4zvfPsx4mI43BaGG7fEx++4vXzC7TT/OpXv2Iujk9/sqVpGuIUKEqkhrlEco50myvSMmK0wJ+c9aSqJgpBbAXGady6w6x6Ln/8OeayI13fUIxiSeB8T9O3tP0KpUsN6K3bcmOYh5G0WqFcDbhNkXXfMo7D7+0Z/143S+r5mnmcOS2B9WevCGRWvWd1vmIahhrqJ0nXSswHT96lFCJaCwY7nibG6zviccAbTTidRC5CZokLvm9lKpELTDPTMlG8hMHZ3pL3I3OIzHEiPhww88x8OqLIzPNAKJH12TOGY6a9yOg0kIHWeGI9MHJ8IIYjtumZpwhNJ1OX4YGgNLrzgpkd7lHpBLYhZINxG6Z8Aq0FIpEeg1ItShdMbZiMk0JNiEWCdbTKoB5BDTkLKCMkwrgQp5kwjDSrnngaKdYKajwmUkzERQySBs28zORpZpgmbNuwpMjKdrR4Xr14xXB791RQS2q8BmVQ3tM9vyI1njzNNOsN2oCxmuDBtY5RFa5PR/7pP//nqOGIUQt5mdg+e87kPBcvz7BO8/DFF+KHQoHWJK0JOmJdIC4Dc5wI/pz37+44zwMXt3uWHNj+7E9QumGaFHlpaC/PSKqlWIuyLbloNIaYJJDRGJFl5phkO4BICZVtpXEpMM8BjaapRUdrLZfbFa+ePyMOkVFpFmN49+6G27fX/Ju/+Pf81//VP2PdO5xtKVkxzJEvbyf+3bdH3h0S/+yHa35yoWjbhuM0c9E3FGU5jTOds09SstY7Yil0bYsqSehl04jx4nfSxjKFyBAjd4cD68s1Y4hY13JxdkaIibfv3/Hi8oqMYkHx7d2R/+f/+O/56mHk//Df/DHrbQt+xVIrIPc9N2cX5KwzRgAOylTvgNJkJNAxBQkH1RR8zfuhUo6WEEhF5BSP5ttcVN1EilQCpVg1lu2mYZkyTsumKWcx/jr/KPkU6UeIQpyMVYLhrYIYWa0aDIV53TPFyLs3H0ilcDocGYcBbS3WO5GaaEsKgbuHBz6aX3J2vmW3P3A6HGnbjovLC27mgLOOMI9EMt53zCFwmEc2ccV6ZQnzTL9dQc786Aef8ezFc95cv6XkRNf2rFYrcoxY7wlEbk87Xmw/Ekl040khYZ3CGUPRBqPEhumsQwoLSbZfU1BKaEohSlbNyvdoYyqIR4F1gAyCGucxFaQhPgN5l8U58P6bN7z46DXOaUiCCAaRxygn0+RHUIu20phprXCNp788B6PJ2vLq1StefPoJ19fXlHnh2dkF/fkFw2ng5u499/vbCitQ+K4HDNfXH7i53UkjHALWWJx35BjRWclGyjV0jefq4pyX51tWveNwOLJadVxfPzAcD4JazyIHPQ0DwzjivePttx/Qn33E5mKDc+bJixiSTLBjiiLFFM46XjsxsyswxlIQSbBSCqMUIQt+3FnDet0SU2TdNbSNoXVCCyv13MxZsZSC0rK1El9lejLLSxxFkW0n4qelbs8U1M2qPCepNmMCrNXV4/H9vHLOrFY9ISTa1tMoxbI7kGNiOY3EwxGtYAaOqTApJWHqKMZhqsMWwbbHGDAGXNMwTiMvXz/nOBz49tuv2d/f8/rZc56tenaHBz7/6DW7ceSvf/lXrFvHH//gB5ilYNa9+HZjRK9WsCSabcPt/R0NPcoodNGUEEQKXCf1ausFAodB6YS2stXOMTMP1dpQs4rivMhW3mhKjqDFotBsLKuTx5aGkgJnmw5VLHGcxa+tjQx7G0sOmWmZSLYlh5lcCsMwkkLArTq6tsGve9quxfUitzNdS24aCoWitci8lkgaR9LpBJMQ+VRK6BjJ84zZtmjvUCmLv69rMY0nKS2wjSWgrRFwlXocunznyys58earb/jo049xTksAbpWSPpnwVKme1ep70tXXpAQMkZLkvIWU8FYy9eKjx1VrlJZhmWQbysCh2p4AkdYtS5Stb0rSCKfMMA5odYEuEnWj5kA8Hhnv95h1y3Q8YM8uUBjicCLrljBOZA+m6YV+XICSKSHUWAfNfrdjvv0KaxT3uyP/09/8DdpvefXJjzDGYIxB+USeIq0F3XpyaVDLKBj6mFg/u2CaTqRUA3815Ci5brlABDYfv0aZSFQ7lNM0qx6zzFjjaZxsRI2W91WhME8Lp90Jd3FJKYEwTrh1Tx5HlP9faHj/s9fV55/ivj2SYmL78WuWZeHKOWzvaSzkGMkUjPFVDpAhKVlfUpimgTQHdl++JeyOInHL4pdxTStSiwRhnkkqyw/6kR7SWny/QR0fyLs9YRgkaPRwIh4PEGbG8URajrSNR7kVfrUlx8ySZozZMO2O9FcXhP0eWw4kHTF2jWl6YttjMWAKKoHWDbZE6DwlLpRiMKpB5ZoqrcQkSrEylbBZwuNKwXlPxuCsGP+MsYLSRVNilu+GlZmIMY45nCgpC+Z8nGR60jTE6p3RKcMcyXUbEqeJNC9snz9jiAt+06FTJOyPoBSu6SXlG/F2rbcXTGOC1rN5cckUMmebc2zjWfJCTBOXZ2tco/n0j37M6x9+wtXFhoe/+wfybiZveszFJZdXzxiXifG33zAdjsyl4FIBY7g7nvjRjz8h794Q88jd+we+Gd5y3O943iCoza4VgmAIzHNhjJZVuyIvCpW9bIt0QyoGrQwZDUbLZK4UqAh2bTzKtVDlUikLcUyyqSIrr0htJxIA37CbIz96dokGvIFwmvnXf/EX/Omf/CHriwu+evdAs92SXcsPn2lg4KpznPUtcREK3pJqI+8txmssnlwUD8cj55s1uoZ/LqnQOIuxjinFpxfWmDM308LVIqbM56s1Xne8vX2Pdp6u8ZQU+bAf+O3NA3/z2/fE9QVTjJRhxDp43p3R2I6Qpv+Cb4H//y9bNwy15GZJCactDpGELksgzgltFQ4HyDNk9KMsUw7WpaLVxacEsXomtQZnNMYWrrYdB7MQQnySMj7kzKVrJH8NkT9Jw/Wd510l2VS1BrpVwzB2/PTnP2UaZt5/uCHMCykHhsOe8bBnvW4ZjztSFsne6eMDrvE0zrO728nn1OIZ8cbQ9D3TMBBTYMFwc7/HYQQuskg8QLNZM5fEtutRiMzt1YuXfPziFV7D/nDCGMtyPNKcnbF99QplLMtwor/YYLWqDbuWAkKJ9j6HhNUVTGMkaNEbTde3mFJq4aEqJAG6xkMR8p0R+zJoJcGMUWhOH71+KbKyEGSTE3PdQBlUnWSrAtoKHKGkTImLEC1z5vzZBX/8pz9lSIXf/fYbzDDy6YsXbLYXXHz0movnz/hX/+Zfc/jlgca1pLgwHI+8f/+BDzf3AmZI4k3qm4Zxnqu2X6GdxXlP07YYowkhst+daPuW/e7A1199y3AaBAPe9mzOL7i9uSbnSCqZi2cX/PBHH7Pdrmkbz1xzWApFJLS5UKwEbFqt0dpitJFhUp0MCAVRIi9CrB48q9Eatk3P+cbTNfYp18trU29E8dTEDEtOIh2rg7BYM6QKgryfZkl90s5gMIQkhtmcMzHz9MzlUjAI5OL7emkjeG2lDfZszeAM574RT3DTsbu7JofIOAc0ipAyvW+IIbHue8ZcGMdRcvO0BJ0fDiPTHOi6M+Yl8OH9By7OL2A40ijNP/nTPyMrxVfX19x+uObf/vVfcvPuW/73f/AHPLOOaB0pFlTToJ2HVNiuBfDSXJyj4kQ2oKuvqnWWFBPae3TFaosapzDHTD4c5IebMyoEjDUEXUmgOUGj8W1PmiPtMZIWKEFhE0J9ax3huJcBkLPEYSJlkSZHIgpRRLR+w7JEzq46urMVjVXorsOueopvoFKKSxR1Tane4RyCSPwQMIPSiKLjcMT0DXE+Yfs1plmhmwbTd1hrQUl4doqBuAQoQuTVRmAmoqxTfPKjz1BAikEaxBQw3lUp33dgiPxINVHqSdatVPURpYIzpTZLomFYJI3libKac5YIFx6XSqWCZWCaxJ9acqGkROuk6SJHNJmyBHJYyNMo8Iw5YLwnzxKSjPNCx1UK7TzKOk5jAKJs8WNE43i433G8eU+aD2zPL/if/sMvuD+cePnRc1zT8PCwo+3X9G0jft9cWDUKqzzxdAQ0GcU81+ZOG5YlkHURb2JjsM49+R3Hh71IknOVvyuDW63QSrbixjkBVESJaDG2Zqi2Dryj6xrGacZtNr+3Z/x73Sz5tuE03hCdxqxbVJp5+/W3fHr+Y1LKTMNE0zaoXMiqHro5S9p5TDJZiVkgCSGhY+J4f4fOiYvnz0klUOYF4xsimabzqBxJhz1+0xLuFaZV2DFilSHsj0J9GSeW6ch0PKBLBNOAdcSsMdaTlKUcR8iwjBMMN2DuwU7E7EBtUFmDLii/YT4m3HKglJmiAtZ0PDL0oRCnI7ZONUsRI/Myn9CmraFsBlMlRUVbmeQZCaYtVe8uSziZZEzjRNd2nE4TKUoy9zLPGO8oKUEslJpLZa1jzgrfrcA1NEqj8gynI8PNLUZZioYYM8s8UbzDrFYoJs5ev2QpkTQtuGfnRCVI0cYarJUw3cY3dM4QT0fi4Yh3Dfbsgs1HLxnGCYUizYHD4SiSE+95WEYuzy+wWZPIXP/2LQ8PgcPpwAtj6GeRT/VKMd5es7RXuO0ldBF/dcnudk92idXrF6SiwVpBsGqZxuWENE8ZjHVgnTRGqYh/wBhMpecoNK3RXL18xcPpiNKKGYWJhcuuxzy/YlnNnG/WvHn3gWYKuPWW/XDiMAQutmv+7OOWn71u0QXmpJliZsEwF08nThXZhIZERnMaRvrWE3Mi5iQyyxhxzrGbBo5hYkqKJWimYvji/pZm1TM/3KGMZu17YshMceRvf/uWYzTcjYFXn/8B7dk5t8c9G9uwn2deuQ3Z/P4INP85LmWMSDCqKDzmzJIK5IWCJeZCKOCL0AlV9ZTZrCtGQLHETEi5Bn3qOn2V4t5QaJ3k4Sgl26uhPJKUqkS2SPZPKrWILBCSFJUhRIo3aAdLTIL+NprN2YaXn3zM2fNnTHFh/HaSSabVnK2fcfP+FjLs93tO08zWWbZnG3aHg6BcQ6RpPHmepMgNCyFF+s0Zy5wk3803sFmxLAG/WXE8DDzc79Bozjdb/uQP/5AfvHpJWCJt1/Dw4RqN4fWzM9YXG3SMNMVhvGTAWUqV/hjpBIsUGFoXVJbD8v/L3p/G6ramdd3o7+5G93Szb1a3u9rVQVFVFEqVAkElIHKMKF9IiMGESEIKEiRRY4JEUUNCTDQYlJzEgCbyxeQVI8dwBDyCSlFCCVVUt6v2rt2vtWb/dKO9u/PhHnPVW4qmti++h0rO2FnJnnM+85nPHPMZ97iv6/r/f3/pE6QgyjFjJASE1MQx9yQb/QFCpG5sQvqm3ZGIDpFniEymtTj4J2hynEOYpKGXo1dBeJ/k197jmo5oHbFu2T89pOkGhtfOaM8uOZ0uEJmhC55n7x5TzBZUWU6Z57jBsmka8qqgaXvqrme5SQ2zwuR0w0C93SCTMx5tcubzBZOywAiwQw8+0jU9PgYury6pNxu8c+zt77OYTVkubzBZyd7eHienR1TTknZwZC7SuoRWdyHSWY+IkSGmgrswCSUtVCDTCcwiRQokD+NaZZQk0yp5DUxGmWnyLJECQ2TEjKdsJufVCJNIG/4oBPk4NUKkTnGiPI4FkR/JngEQitZZ+tGzJ5+Y6v0XiWRfocf52QVFllPXDbnOyff2mO8uUFoSbxyb8MWQ0rrrEUpTLfZo+57DsmLz5pus6y0ARVago2RoA4ONnD1e0tbJqzhdzPHDwN27dzk4OORzr7zGfLZP1wfEds2d2Yx5URC6Dm97hhjp6xZhFB6Pd2Bm0ydwgOAtJkak9wh8ksbmO0g3gABZVYnwOvrZgg8o5whKJQCBVPihQ+kEogkKEBE/9PhOQS4pJwWidvT1gDASXJKwC62xG4sxOd5GWjxKgdCaameHMAzo/BCdgZ5UUBTITCfp2FjURW+RxuCVGsPiASHxziWQzLZOHmO3kwJz2xo/dGT7+whjUEqNdFCFMAZdpIZLsEOa7Lo+NXdG2FGMt5THMUpCjGGwPFFjj3CGL05C0j7g1gs4TsJFHCm3KZMsirQcVlnKvYy3hF2Rol98CNT1QNf5VJykXzOpOtyQijsfECEQhiF5kgaH947s6JD26gK3qSlOjnHb7ehBlLjOsw2RolLYpodqmvyjqxsuX/08mYb/8l9/j1W9TX6oECmMwbmB2/wnLQXBWnQecG2ytLi+xfu0zzK5YugDXWex3YBUAl0Y+nxAzip8M2CbhnKSEzYOM62o6y35bIbfbDGVwcvROxxjgq0ZTd937M7m5LOKYdugioz/nZSYr+hiqWt68qKgFh4zK2kvat587RXuvetZQohcX11xfHxMVJ4gkgHVxVQs+eDp6o5+29LXLbkPtMslYbtGeceQG6IMiOhweUa2M2OoG2S/JQuOcL2mYMDszCCMeFUfcPWWod6kDqkbL2SZI5RJHqmNp9iZs7x4ndnJXYZ6Q1i9waTsURMQwpMCRJPnRasp+TSA9MmwJw1BTFP3zvpkaBYeYX0y7EUItkOMfgAvM5LGtkepjCGkxSgivhggOAb13gaeCSlYLm/IYpKArC+vKYoiGXu9QylDluepQyRkMkhnhqGuEXZAdC2hbSiLAikU9dBhMokRBa6qiFIxOT4gziYMQzdKXxagFcr7ZCgGbtYr5ODYzTTbR+eICGslOTk4JBqNuO7ZXix589Ej2uApSNlENgRODk4w0wUuexub15Zs61dYRMeBMYTOEYShObvERA0HHrM3Z++5ZwlSYdaWbmsZhkA2kWNuDkhlRglhAmwoqXHeI6VJcsaYsJ3A+B4bKYmzilxDJgOt86ybDVkBU5EzeIENkpt6y/7xHT5/tuLhKw+5e3LIqrbcdD37ZUTGSHDQWYsTjryYYaMDMsqsIDqHDRKPxgbP4G+7vonwkxmDVZEyz9j4SNt1nB4t2K5WnK9afoszFJanqjnvPp3QWcvVumWSK/7t//ErhGpGcXSHvu95550TLq6viSe7BO/YDPb/Z2vAH8QxhIAbJbsjy5g+hCS1sBE7RPrBUaLJlUiRAkrTh4CUqaN+WyhZ/8VgVCVufRpQjKF/Skj0NEsdM6OY55I81+RGjlECCRMbosd5keSfpOwl6yPzTOGDp+ktRVVx9+l7XF3eMJvPWV4ux8ZHZD6bUlYVzbZms9rwuZde4b3vfDtaCA52F2zrlqaG9TAQBpdkNAjs0DPYntlil95bnLVY52mbgV3vmM0nGCUoTM7ufId6vWHxzrczm04Y1huqw0PKIuPuwQ7ZZkue76TNOBHtXSqKvEeGJAfDj5uKsYAStx4wQGgJUqV1Z/yaGGVdUQqEVqmrDCNGO46m7YT7R2tGPnrah/sUppWgAiHJZpwnek8YLLHtcF2X5Cx2oJAC3fcczibkWnN2c8Vi7xBft7z4xiPmkwnTcsK23rC8vmF1s0YZQzmZsN5smFYFAcnl1TltvaYspiilMcYwm05QpPfDbDrBE4nW8/DsguVqg3U9pii4e+8ei70FvJ7yreaLOTvzGeV0grzNZEHggsB5ksT61mgOCJLspwgqhVqKVNgURqOmkn5I4aRKCaaVIdOSXCeQhh6l27lKMBN9K6UmEbksiS7We48REj02GqxPQJPepymrEDJBT0KgDxE3+vtglOV58NE92ZB/JR6f+8xnxoBdTfSwmEy5+67n2J5dcn55RTmfsqhKLl+oyauSWWlQ5SR5a+qGtmuJhIRRtoFKaZpVzdYHci8Y2g4pYLtcMZeCLAq65RLbtcymcxZlwbd80zdwEh0slwzO0fUd3XKJG5vEdujJpxWqKrFDn6SR7QDTMgGE+hox3WcIEbltmZweo+Z7eDdQTmYgMsRYREgUYaTAJbKQJqiUz6WNIcszVjctPtNEqTGFYmgijvQ3tyESBwtlhvTJuy2DR4xNp1IbTJXTnp+RP3U3NVvKlAsndAbBj2XICC/xHqHShDj0Q5LU5TlBKQYHmXeYyTy93hAJbYOTCXgSrE3Nm1TFpNDkzKCNJjiD73vazSbJvcbiSpr0/E+ilMcq6ZaId/teFmPHQYxFlZQpPynXhhAjde/JtUryYMETuWwI6R6TvH+RtrM8PF8iomZvVoxNokQJXcwqVIyEvgfhCUODiB4RXIrTaepExNQaZz1ysY8cOoLORvCQpfQObfR4/8oZ2pp6s+LF6xtMNaO7PCMNpjLWqxX5dJoAZQltRaYCsW9hzGcUUtFvt1BkBFkwBMH1TY3rembzAtdbtHNMqwk9EWsMvm+ROvkhe5emZFmZ0Wxqur4eMfApDqbtBor796DMGB5eMbQ9i705rRv+t13jX9HF0vpqSbzekN87YtPUDOsav+lwrcXkhlzniW0/koJiTJvO8R6NGyy26ei7jtj1MAzU55fMMsmmbylKgxaBbHcHtdWo4EBaRByQsacYBsTlDWaxD0XG9uoa22wZhg7ve9rVimw6YzJVtG1POZ1ipgdE3+G9SBOa7QbtHbFbQTEZZVYrhK6Iukw3vxSmBEFALPCjvEurbMQLO1ARu21St0FHQnSpg6sjMToEEedtmjZJleAXMlG3nEt4SZkSHZnM5gz5DXFosf2A8aCsZ9jUqDJPnRopMHlB1/VkWZZkQs2GbrlEOKjKKXW9xUhHX69RVUVVVAxKQi6pjvcTMjZG5LQiL3KafsAYQ9dsKWVOfXHD7mKa8MCTEu0jUYKqJgRrcZuG5uKG7bYhMxnT+ZTzywtOj4/JplN6ZVhtWrzMUBLuFFOM82MGUmSzXaFCB23HyeydlNNDeqGJukOIgIyCoevxhcZImdCbMVGlUu5N6niHGBB+DBQdHM5ahr5Pnd2iSAF3yqG0ot9aNpsNq66n9YZuCCxXLXZoWbdLHjeBj79+ye989nVCn4Lb3v/u+7zvzhQXBprO0tgGoyQmBNZdjXA2hSGPUo7gOw4PFhRa4cd8sCQ/cuTa0ATHZR0ZRIbJPXmlaZyjCJbqMGdwLVFpHq+2fOLjn+blz73A/ge+karMePeDfR5fd1ghqK3nsQhfNHJ/BR8xiNF0nTabMiQjch980nNrgxs16MFD5iNGSzxxzMu4DSS8zXFL1J7eOpSIGCHpY8Iu51oyKQ1VnpE8x8kDkMhJSToZ4hfx9WmaJJFRsOodlVGgM4a6pd9u2W7W7O3u8lg/BKDIc566fwfbtnzu819ImR5tz2q95vjkkK7PmBRJtqIluL7DuQFv+1Q4dAPZrmRaLcYQ+4htG1775OeZHB6Aj5RlwdNPPeB4tmD18ILJXUnc1PiLG2RVEBH0fUsZIqLInngHJCZ1eIceORZAqRcYkidJaVAjKCAyTs/TJDcqjRD+/yRvSd4CIkTcGK4dICafF9oQw5ijkoT+t9QbRj45wbqkNGhtmiq5FLApmp5CSI5OD9heXnN1s+Tk6JjpbEp9fc3udMJ0f5/XH75JU2+4vrxKGv+mZXV+wSwrcTLy8NGb9E2NIGKkRmvDdDJBhohWgkmZsmDQmqYd2G4bVssVSmYcn5zwjueeY3BdmvCMkqHzyxtklVNMpmy7gTjq/60PuCiTjCipkRmCIyP5jtJEfMQbj8Z0MSK/pUjG8kJ7hEw4cy0gakminEesC5RG3wofQUT6ENC3EqSxELptPjghcCLlMNkRI+5GT0aISd5EDCOCfDTOf4Uej954k+XVNV/z3vdjdM7lcM3J/bsE69m7vEJlGrKMLMsIxrDZrLl+/fUUBTHK34qiRIjkPW5Eev86WyOspe1THp+QKTw+9DWqXLC8vqFc7PK2Z57hwf4e4vKMxgfa5QrX9jgFbnBoLbHOEZ2jefMNHhwfJel+pqHvCCiCEsjSoVSGrCaIyQzyApUb4nVHsMnGIKTCeQcoMJI4JK+wypMaJAaPyTQiRPJCk5eaOjicSHMW65JcLsiRf1C7NNGPHuUjylrqZktRHCcPshAEY5DGIItinOIIfD+gqxKCSKRe7xlWa6ROhn9pNHJa4tseWRaIPIV6C6XSvyzDDQ4h0s+XKjW9U2xDBKFSr0WrRA3sLP1mS980qCynOtgnX2ikYiTk8oSIF2+bN/G/mXTEhM6WIdlCMiNRKoG6jEjTE+I4WUeMU6XIattzdtMhQ6RQkWmWobVExsjetCJYh+sGyARKRHrniEaR5wV92yGDQE2mRCUQ2iAmM1zf0y43TBaLJJGeTxi6SOgtbVNzeX2DKecgIs62KKlwrmOzuaacz6jyjGAHcgWhrVNArpD4vk20QyGw3uNt4Or8hquzG2zwTGcTuqZjcrRHfbWka7dkpYagiDZgjCavKqKRSJXQ4D7CdO+AvaMNrm4QgCmKRHWOkWxnTtSGvvn/Ax5+38NZh28HFlVFsJb6ekmB5vzlN9GTjOvVDXv7uymHIwYk4MabsxAJRVtbhy4MyzffRF5dIWzPZrPBGEXjB2azEiE9AUdVFjjfIUoDTkC0BJHTWMdsnhGHgbbZ4L3FW4s2GmVyrLOU1Q7ZwQFeBDY3VxTzfVzX0S/PmJg0lhcxSQbb1TXVjgRR4aVHyim+bwnkhKBROmWceBdQIoDUidnvGqIWBMaFJS9T93Ts4iEVUmmsS7krCWGcqC5Juzs2SPIMWWT0dZt6B0IgXCD4iMgMapKnTWOMtE2D8WBipF5e4zdb8jwR1cqqpK+XZFpRVQWdTbK6sDOBLMP1PcEY5ieHBOfSpr+zNNdLbKZxTUu5s8DXLSFKgsmSTlUpmosr1pstjx+fo6ShrCrOr655+qlnmVY5Xnmuzs/oz1+jPnsTFTzKJ0SwlJEoI0ELRAZFqSgmJVrlrHtLtrvAiH5MTkudfudGOY8MCCUTOU3JtCN5MplLshNiZDYpsdZRFTmZSn6isqgo8EhKel3y2ccrfueTn+V0b4ftxRlX11suNx1d08DmCqKmi4rPDRf8pl5zuj/Ftx1nlxc8+83fgC4U68by2tXAw/Mbms2KQoNtVyzefETsWoLrmExLjk+POb17J5FjrGXTdPzi73ySP/r0Ce/e2+FyGPj8m2s+Hi6x9w7p2g3LzvM7n3uDcv+YfOcAaQyDkxAEp7s7THLNamiJw1d2sRQRqcMYAz4wZsZErA/Jl5RafUm2opL51YeIiS41PMbHhtFgL2UiJwoiRo1bSxFRQaZJURQUmWanVGxHTbcbC6QAKXck6fHofcDb9DUpIoqQpsckwIGPgquzC+r1BqUkeVHQdTVCRp5+9mnOrm64OXuT5c01F9c7aKXZmU25alomZUlVVqwF4w22R0TB4Hqcs2Tlgmo2oVmt2W63LNdr5psNhEhVlLTrDdl8l93dHbaXV7BumBnDXEsKAZlSaDvA1RKrBPpolxhzKDIEgjB0CGWQRo9tVZLJOJknk7x0RFFJRkvLSKZMmxIxbvmTeTiECD7BapIFZjQuJFMFMH7rKF+ONp3jOIYNIwXS+ZS7lBsmiwmh7zl9+j7V0QG26bi8usGUJWVh6ERgMZvymh9YrW741KdfQI1meJNPuLy+YLm8huDJTc6imqK1IVM5RZ6zM99FxEDX9pTTGbZdcXV2RrNaUkwqdvb3QAkeP7rGdinEtG46usGzmC/QxiSJXYRuCPggsNaPpvKkFAhCEbyg9wlkoUibVUiABhdSEZQpxawwOC/oBkcMikAgy8RYMI8FKvGL078AiCRDtVEQBdgQsTE1tXwgUR3F+LcRERcS2vz2/hWAKAWOLyLMvxKP1994SPCRyWTBu77qHWRZwaqumd49ZXfoaV56mW3TUlQlV3VLOwyIPME0kKlh4qLHB8tgB2RR0EUIUWKHRETMtGE6qRA2AahsTGHXbdNzuLeP9g7bD6jgkbmhvVkidYZvUhMkrwqCiGhT4G839Eph1zWRDKE0ruu5Xi05uXMP5juIvESoiJkNdNc1PqRpqNIGJyOhHdLGPkCw6ZrUJk1PnXXIXCNzjVp3mCyj1TZBpPoenRdp36IlwkWKLMOrCF2N1hq/WaOPDhiahmwxT+RGkyFlTE0OF/B9ilIBcG2fQuL7HlXmCK1R0yqtDtokwIPSKRvqdl2wfkTdp/chQFDjeiFVmoCFNHlGCWSeU4pExbVdw+AG9GSKGuEwYqR9iico8Tg+v/g/qUyTZEeKkJpg8hbik3LLpEjeyjgqU25WNUM0bPtA7Du6WcnEpGl6LlXKohoGVEh+qjB61ZXS+LYmSI0bLCpGsqrCOk82z1FKUkSJrCryIiMIKLKMdW8TfCTLGPqawaUmu8kz1tstWeE5Vpq6blmUOaUMKd8ppglmDODcgLMe13lksKyuaq7rFi2Tn0wawzBY/GaJtz3ZJEMQQSZU+BACgjRxM7Mp/nLF13z919Mt9vjd//yfkULRd31qYotIMSkZ+h7b9f/brvG3zPz99V//df7sn/2z3LlzByEEv/ALv/AlX48x8mM/9mOcnp5SliXf8i3fwuc///kvecz19TXf8z3fw3w+Z2dnh+/7vu9ju92+5RffjqFZWZkjQxrbFTonNgPNzYbDnT1MZhA6dWOkkBgEWiSvzWAtZVmileTp559Gl5p6qGl9y/LqMX27pumW9P0au7miuXzEcHNBd3mFGBySCNqgJxVDPyBjwm0GIn3X03UD7TAQtUBMJrTbjn5zgcoy0CmZ3ciACw0iz1OIZb9Fi4K+6XD9hjAMDP0WrQzIDIRJUhFA4MEOBK8Y3IAaenKV/FnS7CY9bFQ4P+CFQumC6Dx6vJC1SfSXRGFJnT8lFU5Eit05xf6CWBjMtEwSiq5HZxmOJGcJ3hPajrDesnz4GBEFeVYmeQyObrMCPNoYbJSY+ZRWCWanJ2lMnRn2n76HNCaNwr2nWy3pHp3TX1yTx4QYjVWONAU365ajB/fYXF6xfHzGay+9Qj0M6OmE85slk9mczjqWTcfjmysYWi5e+QLnyxtMkNje40i5KohAmWUIodi9e8z0+ICmtQkDv7+HXszo2i5dIlEhVSLjeQ9D7/E+pqRrTyIPhogdBoxWqDEzYTaZ4K2lHXqsT/rwvFLUecH/+5Nv8NFXN7jFHd5YOx5uHOfbgHMKcb3Evvwphpd/h3D2MpvrSz77yuv85qdf5PVe0O6e8DP/5j/z//zFj/GvfvM1fu1zG17tCl7uoJnPeNcHvpoPvP+r+WPf+PV87Qfeh9aK3/u93+NXfu0/8F8/8RkeP7pBZTlbN3Ddb8mMIBcd69jx+ccXnK1r/v3HX+Df/MYnePFyhS/maJOzu7PH2SoSTYaRiscryxAyZiOh7Ms9fuInfoI/8kf+CLPZjKOjI77zO7+TF1544Use03UdH/7wh9nf32c6nfJd3/VdnJ2dfcljXnvtNb7jO76Dqqo4Ojrir/7Vv4pz7i2vI34Mj/UhbQh9SJlhPiZ4Q4AnKes+pA56jNDaQBvSplAgn5jfY0gI5qRJTzdKJSS5EuRaUmqBGZs23kO9tZzftDR9QmiHUcrn0r0WpKBuBlbbHkiNDaE15WzCnft3uXf/bsLX+4F2W9O1AxfnV0RruX/nlHIyZ+gGNpsaOzikVOzsTHHdgB4ltUom3G8IHf3Qst5sWK3WrLc1rz8+42bbsKxbPvPSF7i6vKA0Gc899wymMGgC8/mMyWKCHKMHciArMhhsKkYGR2iHlCQ/uDT9MTp5iGJI5t0YnmxYIqkojSHAiOy/NVAn7hrj4+IX/897nHMpE84mCVgYfTFBpjZ2VApMguDcRkkIISHP0pqkFCozZEVGlmnmJwfcedt9To/2EqgnRhbTOfPdPVz0rFdrtJAMTcP15QV11+FlQmy3mzUyKipTsTdd8OD+PfZ2dtg9PODe/RP2ducYozk43EEbSTEpadoGoRT7Jyc88/Q9sszQtX0CcZQFdx7c46m3PYXUyfuSG4Ul4hG0vadtB5wL9HY0Vo85SjHKROr0IXkVHGxbz3o7EAIYldD4RklyLTFKkJkRp56a++RZwrffetdDuK1BxaheTZj7MOLu06fS+zySsoVCGDOboiBE+USS5eO4Ln+Zxx+2NeTs/BzrLJ974dN88hOfwA+OruvpYuTo7c8zPz0FQmpiGs1kd8G9+/cpyhJn3aiaTGtLEGL0ICfvy3Q+Y7bYQwqJNppt2zP0jqFtyLOcnd3Fk8mezEy6tytDnqWAZzPGBmilwTr6phm9lwL87WQyeZtcs+Uzv/cZrro+NSZI8RRCaaSUaao4TnNFTJLBqFMmGj7FrwgpCG5gOivJihxIRc1Q1/i+x3mLqkqCt0iSHynfnaGVJlMaOwxEIegGi3WJNNrf3NDXLUFI1GSOrEpcXePH3LlgbZISbmp83eP6gUjEVCXl6XHKZBICIdOk+ZY6KkxCZzMS/oL3eGsZmhbXd3jXE7xNEKuhByIq05hJQbGYM9ndIa8KkJK2adluG/rOEvwYUzNOxm7z+MSItxMxyf2MFEm9pBLNVowX122m2TBYLIbGK9Z1Rz842rpJjblRBZFrhZHgrX2SFRjHPpETEq8SIddvNtjtFqnTVG3z+JJ2tSGi8EGiRZIXtkPP5cPXyaSk6xqazQ15WRGFSdeuDxijMJlBGzWCgmIC0PTJy+R6h+1cktj6RJcNPlBMquQKaXua84sUY9C2IzDki0RSIVX6pwT9tiaGwMWrr/Ho1dcp8zz56YoSPVkgi1HJ4Bz+yf3gD/54y8VSXde8973v5ad/+qd/36//5E/+JD/1Uz/Fz/zMz/DRj36UyWTCt33bt6VcjvH4nu/5Hj71qU/xy7/8y/ziL/4iv/7rv873f//3v+UXH3xEKcVkd07ftsxmU6Z7c4oiYzqpMLlJkoPRl6O1Ruq0gFg7IAVkZcbunQOGoWdvOmcxndBvV5zszdmf52jlwbbY7Q3CbUGByjPatsflAlWlcDMtJW29RoaIMgXBR4qqSnpyKaCYcXXxCKVB5gn7LLSga9dIGWlcj1Q5BIMUCcgwdOn5pHBErRAqS14kodM43HZ4t02Fjg+0qyu2V1d02z51yaMkuAERQCo9Yr9dQojfSllkSrIWUvKFz36eizceQ4S8qsgXM3buHOONIijJZDZNoXk+PCEY+U2D3zRQdwyNp9cZNgaUDkTf0l5fM13sJi+B0cyfecDs7j1EkTPZ20EUI7bYJ2qVcg49OK5fe514syYoCUXJtunY1lu6Tc3jz73Iy7/3WS7Oztn2Heu6QRrN+dUVspqwjoHpvOLR5z7Fa+c3tENAoumdp2kdEQXKIJVhfrjH5HCBNJL1ZksxnaN3dnBSs16uCd6lTBJEyqSSGki5LzFKQpBpcRwXqeA8udHYoU/yFgm4lqGzfOaVC/4/L13w//rdV/ncwyUPX3/I1cUKT4GQBd7WuO0lQ30DMqPYv0++c4gYPI9eOucTnz7jP35uzUO7w9Nf9X6ef/tzvPedJ7x93vLH75f85T/5Pv7C1zzP83s7TAqNMYH9ozkf+MDX8E3f/Me589QdrtYbPv3pz1Ff33Bnf0rHwHro2C0mHM9LhI588rVH7B4d8+bFY6YnpwQkm6sLzjYdZ/VAM/RsbcfjbYOWkkU5eUvX7a/92q/x4Q9/mN/8zd/kl3/5l7HW8q3f+q3Udf3kMX/lr/wV/s2/+Tf8y3/5L/m1X/s1Hj58yF/4C3/hyde993zHd3wHwzDwG7/xG/yzf/bP+Lmf+zl+7Md+7C2vI37cVCYUa+rU+5G8Zp0njCGomTEwgj18SHLOGBTeC4L3uJg2gxFBpkTqGqqxwxhBa4mWCbscQmC1HXA+sO0GVpueurGsm4F15554OkKEphtoW0vXWDZ1Sztqt69uVtih5869U97xVe/i5M49lMlI71DJ8ck+733vu7lz7y7OO1bLG0yucK5lPptSTUtmiwqj0o3SKEMkmZhjsHTdljfffMjZ9QWPlpcEo1FKIGOaxnzhpVeQMVIWBrdtyZWi3FuglUJLyHfmFPMpOjfI3CTJjzZEo4nRjzvtmLxJmUnTJKXwSuNDgsLchvgGBDGQNgMw7jrGwiqOQb8uTQZ9EAyDww6paIqJ6T5uWNJGJCqdusBCpq6zTJQ6WWRIrUFKstmEYm9OUeXMdufcefuzvOeDX8vezhQZImevP6bbrFCI5F8wmjcfv8EXXn2RV15/lVlZcffghHv7J+xP5+yUFZOqZFqVnB4fEJ1FSEmeTwgucr1cs1zfMJ1N+br3vZev/8BXc7y/y8nhAdP5gr2DfQ6Pd9FZ2jipkbY4uEBwgW3d0feO1bbF2fSekyQKXmcdQ4j01tO5QNM7VvXAct2zXHWstz3WBeq2x7lAZm6N6mnSKkkevEwpZEgNgQjjVDTdD6xP4Abv04Y/CkkUKvlrw5hHl/4UOOdHuSpEnzJo3spm5A/dGgK0fc/ZxRWf+czn+NznP0c1r5CZou4HDh7c5+Dpp2gHS5nnCC/YbBvqtkny3xH+MJstqCZTXIhs65psBB1lRQkS1ssVSimiCEQREUrgrGNSTZJczlls2+L7Fj2dsbh79wlkw485kgSfxCZaEYbk5Y4BYmbobpbErsUj8DJ5BYM2dG1LZy0eiQyA0Li6S3J0l/y0AZliUAY3Noo8cWwgVnsTpEl7B6H16GtJmXVqUqKrYowZ6JEixbcE77DbhuZmzdD0DIOjObuiWa2xPkJW4LxP9DeRpqp+8GniVPdEG9JUOi+RRo8FjEiTqNusvJA26EIqopZgdJLihpFAZ12iyMkRf68kYpQEPpHzEcnynGI6oZhUCCEYhoG+HxgGl6TwtwWTSGH2Shm0kiiRBlxGpWtM3k69wxgu7gNeKDZ9KuCDC2ilEcE/yTczSuB7nyZKIRAEqMJgh55V5/itT3ya1WqN64YUbSMVvu1RkwmyLMepJvRS0/mIyhT3nnsbp/eeoiwnKG2SD80YpEzk1DzPkErgXMoeTFJoCVFgB5umS4ExuFqDVORKEm0qqFxMfurm5oZgfdpT+rQX5VZ+nRkgxdmYsmD58E3stubk6Ci9d4qK/PQeWTWhb1okkmpaveVr98s93rIM79u//dv59m//9t/3azFG/uE//If86I/+KH/uz/05AP75P//nHB8f8wu/8At893d/N5/5zGf4pV/6JX7rt36Lr/u6rwPgH/2jf8Sf+TN/hr//9/8+d+7c+bJfSy4MjdwipzlZ11Mc7aBnFWanQucZIlOY3KBV6pwImTSecQzgMlmSesRM40Ngu96SS81T908p80hlFK3vWa+XqCxDK0c128N5SV7Mcc0N5WSGMhnCeaJrCUJjvUS6wBA8g3DM949ZXd6QE6h2dnA+o+22+HaNDA4fwZCBL5GqwA8tUmqMmhBJQWwuSqLvETF1l6O1+OE8FV2yQHRbhBiwtSMrdkeyTZfUJVoxdFs0Bu9A5QXCJ7+NVKnjKISkiIqHn/0Cz33NO5GDxZNkR+XOjH5wKDlSZkIkz3Ouzs+QzTCOtCXBBUqZFryhbwldR2Y0N8s1ZjpF6Izy/j1qIcl2FsTgsHUDI4a0b1pc3Sa0dddy59mnESYjDJFmveHkmXv87m/8Biwbhi55dIahJ2pF6DuMEqy6hv3jGeb6NW5urqiHhuNqQvQ2Yd+FAzxZURIkHJ4eYKocosCUM8zBPk4q0BVCbBHWIpwlSIk0efJZjBMmnRXpoo7J86KlJgSffGRKQVSYLKcXHVs7cGU1v/7pV/nsSw/xtsc3WzbtlvrG4JYbtCrRqsbsLmC+iy2myMmE7uxVeqkRD97OFs3ZxSXvf+Z5vvZtd4iu5qh4juV6ydnrr7DMMk7unpKrAkgFm1KKLM94x/Nvg/wxy2B4dPaY7W7Bg/1TQujZqaY8vZjTesXjNzf8h49/gRqDzzR5EXn+uae4GAK7JUyzCbieB8clOwpuurcGePilX/qlL/n4537u5zg6OuJjH/sY3/RN38RqteKf/tN/ys///M/zJ//knwTgZ3/2Z3nXu97Fb/7mb/LBD36Qf/fv/h2f/vSn+ZVf+RWOj4953/vex9/5O3+Hv/7X/zp/62/9LbIs+/JfUEymUi0j3icZROqEe9RIZbM+gHUUxiT4QgDtU9c8RJ/MrlE+kSeFGBHRowQYo1CkrI4qM9S9JUbB0Hu6wdJ2A94LjNaoEAk4tDFIJel6x3rbs910aCnITMnlzcAs12hluDk/Q2tFNa04vXcX6wKTPGd3d86dO8dURYGIkXrTsFktuTy7ZPbgLlJKdnYmuKbh6OiQGPd449VXKbOSwmQoRmmQD6zqmrqtmc8X7FQTdNSYPGOSFWOej6GaTsjswHw+YTqrEtI2RMy0xOwt0Htz5CQHlSbiwiQJqxAJ4hClSpMkROpWM8pZZATnksfGmCRrEU9s1eNG3OOsp2u7FBEhSIGsziNiknVok8AEIl2syfcwdppTtpZG5HI0KEdMkeGlAusxRU6WD0QdMbnBlBVXdcdTD+7x6OqS2eYApRVnF2d07ZZhaIh9z/ve8wFsH7Bdi5IjxlkIslyzXW45e+MRJ08/IBKwduCN195AAgcH++wf7GKyjH7oGYYeoyXHd04Q2tAP6XwM1tHXLRbDYB1Db+m6AWLESMGsysGnXD0ZA20cgEjbDAwh0vSOpklU0xADeaYwKm1iog/kRqew5hAwUpOL9DhPQq9HEtAmwngPEeP9Kn09ENM9xEdGjeUTSVLyCKbiSYzXy20d/JW4hhhtGPoePZmyqbd86jOfIsbAc889z97eHvVVRzXf5+jkFJ3lLPY7Xnn9FUSM7O3ucrm8xo5hyxGBbVticOh8Slbk3Jxd0LUdWZETbNr0bzcttr/djEf84J6g4W1dUx4eoXf30C9+niF4gkvN0aZpiT4VOFGkjCgVBLHrwAiOZjmry0c8eNezxLJKUy+TEWWf5GHej8QzS0Aih0jMBFrnBDsQnSPGJMcbdckIGchkQBtFlhtcbyGmTX1sO/TePoXO2F7eEEi+nq5uMXlBiD4pYJoOs7vAWocqMtrthlxMcd4lqqV12G5I4d+txQ8eNSkSfOnWH52ZdC9PEMYkIRQCgkcyhiwLCIND6DwVVsE9KbBkiKAVcnzOW4KwJzV2MpOiPJCpcIgx4H1q3ISYYlrC6HElJgWBvM1jkgY5Fk8+OJxz+KjphjSpcj7F3mqjEtQiKKSIeJd+fx88IagkbTQ5TWh57eKas5s1lbfk0xnTWcQ3G1RWkE2n1Kst0TrUZEbrFa0PoAT7p0ec36yZnD9OUmJpmM1mCB+5f//plIcnFFmuGYYaLxVqSN5KISTgEOPv1/UDzbZDmAyTZbgYmRiN7VpEsOS7M1SuEL0HIdFKIrIEIUsyTY02SVElREyQNiQqz9HTGeViTt/WZFnGdmi//EXkLR5/oJ6ll19+mcePH/Mt3/ItTz63WCz4+q//ej7ykY/w3d/93XzkIx9hZ2fnSaEE8C3f8i1IKfnoRz/Kn//zf/6/e96+7+n7L2oR1+s1ANPdKUIK8vmMqCLFXJLvThlEQFcFk9mEqBI5SSqJkslQrHSaBA0h3TDL6ZRhMqHa32c7bMjUFKV7kBEjS6QO6MmcbvCYaNDlHEFAq4DWedIH9wPWKkI2xwhPGwakhXx3Tms93fKayTxje7WlbxT5NEO1N3Ttmmq2Rww7RD9nsBtU1qPIiVEhHQgjkCEQbDey5jf09RqkQKk50W0Rfo2IASN2cK3F+4QvFgBKorwlSo/UBQTP0DuycZMSQyDEwL1nHrC9vEpoSQE604kwU+SQGbxLoXmZ1vjLNeuX32ReTtBKcXN+DhKkAekTAtx2HpNlqJgkRZPDfar9PaLJaPqefrkBoRB5kRYh60AENn3D4ugIszsjaoVrO7K84PrxOcvHV8TB0tqOfvAcHB3RtjVFXmJDZNXVHDvJZz7xCV67uubAaDJr8UbjokjnIM8YCOweLciqGVFqVnXD/Jl3IPI8jYuPTrF5xqZuqbIIuUaojCgVIJ+8j4IQTzo6foRxSJ3heov1kW7bEqTk8brn86++zEEZuHM05awpmR+dsuki1guYrDmea3LxLCqfsmk81+1AOZmSPf9OpPSo3SMuLjsuH77JZz4eWL32Ot/4De/hC+eXHFQZ737b81yvNrzwmc+wd7jg8HCBkaCMZqImBCG4f/cYs9hB+s/y2f/8H3nnwbeR7RQQLXmmuFmtKMoZU5PRRYsVinvPHvKup5/CXTWURqIYQMF2WzOdlbx58X/NVLlarQDY29sD4GMf+xjW2i9ZR975znfy4MEDPvKRj/DBD36Qj3zkI7znPe/h+Pj4yWO+7du+jR/4gR/gU5/6FO9///u/7HVEIFK3e4SoeBcTZGDkAKSb4WiiD8kMr0NEyDDmavDksYFRAhElQkakjPghYXVzncz0uU4GaV0ZmsHSD54Y4Gq9pchGWZxOXpIQApt1w3bTE6MjywSlDCw7Sa4iXe/IvCM3msPDXd587dUE3JCa9abFu+SrOTw8YH1zzXq9RmdPsbq5TpKXtqUqCrTRXGY5Q7Nld2+Hk9P7KK24PD/DOYtzls3qhokpOdq/Q1kann3qHvff9hT7syn0lokRUHdI58lmJeVihi4zslmFLPJEtFMS4VM3MmqD14rbTGM/bhSdhxiSjEwqiZcgXMp70SLnltfA6JsMLtA2Ddttjbee4B1ZmX6nhER3IDKUFmMeCekJtAbhx+dOnVGRZ8TeEjsLKkmTs0kFUmF6h4uge0fMcoKQlItdPvviq3z0Y7/JzfVFOvcx0HU1L37+BSpTMpvNWdw5hRjwTU1sJlwNN0mPnxm0FAzWUjcNs2rK6ckpk1yzvlnjrKeu23Fy1HJzdZMQxIPDxcji8Agv0/ozWEtf93RdIhpWVc6kMLTeo8ocvMQ5z3Lb0TuPs4F+6BHKELUhRiiNSnIcKZMfIJ3mZAuJoydPgBejHDWdohQOSnwyPYrxdkIZn5C+wihZDSEhgOX4GBhDat9KtfSHbA2x3pFpg7U9oCHAFz7/UgI87B4wn8xR2vCBD/5RPLDd1LgYaF3yqZRZNgb6WvqmpigXbDdbZrv7MLryijynnJQ01zVXlzeUeYGWEAdLdAGKZDWQo+SpvTynkApdTVDVDNclbHZZ5E8iDxIWW4MbED4ktHimWF1c4r1LuTchMHRd8u94j8xy/GARQeKGhKzGgaBHTzXCW4wWuLZHUiavpZZP/DtqWjL0qahy1iKiQ9Y1UhkMkcY7ettTVVPWyyvKsqTtHX6xSBvnXDOxSUG0ubhkcrCPX6+wN1tC00NmElp8U1POpkiTpIkyz8a5cvKXKpJPKcb0Po7OJVmuNgzDinxSpj/y6KeUkZS9pFJwrVQp3ynVPWF836dpb/QhNedHOVnQ6UIarKW3ltVmyzBY8txQFoY8z1EqKRhS+HPyoifa4DhJjCKdd1KkglYQx6gAvMf3jmgSwKHb1LxxveL1R+fM5gvOt2vu7O6m6IDVEjnfwcucpneUVQqtDkqjhEfZpJ6Y7Owz3z/h4uKCTCgyU7BzMGN3d5em7ZEqxQSgMkK02D4QCYTeYofRM+k8rR1YrtfozJApiRmncSozSARGJsWAjwHpwEzKBMnQObZryacz1puaMi8Ifsn11TVPHR8Q6g3DdoWYLyiGHl1kLN+o+d91/IEWS48fPwb4ksXn9uPbrz1+/Jijo6MvfRFas7e39+Qx/+3xEz/xE/ztv/23/7vP7xzvcfL8s8g8w24iMhfsn+wTJGMQazKeJwoeiYpHRGuD0QYnh5E2p4hlxuT+IdUs4/ozn0TWK9ROhlnsIJwmXxwR+p4hBOT8APolwTe4IZD7nug7opBYN2Cdw4qCSSUpDu9Qbzt0LnACumXP8vGK6+Ub7MkzdiaGfqgopvtELzCixytNdDlR5fhoMbkkujW+qVNXadgihx6R72L9JsELZESGgjYMzE6nCKESFpzIQESomPCSeMaozETJKQxKKkLwtEPL1euvE9dr7rzn7QkDWmTossA5j1/XzIoM1/a8/l9/D9M7LD2ttdi6oXEdRWlgXERUWdI1PWUmMLMpO29/Bqc1hEDXdbRDx2Sxi8lL3Lom9APB9ti+xcxnDCJSScHZ2TnBSD760d/GhJhCQkNgujNnuV1RZRot4aZv2PMV//nf/Se2Z+dkUbNb5GgC/eDwQpCJSCY1sVAs7hxiZhM265by2QfovR1CbxEBKCvEYp/+5pLM5KiiApWhTY6QChnEE+lEyggZpSlSYofApu5Z1y3bNpHlVp3n7ukhT+Ul1dGWy0ay2W5ZbjoubhqGmBPwrAdH363ZbjsyJZgOHX30LOYV+/sKPUi+cBn45Ocf8lV/+hv51OfPePf9Y3ZLzbpruL5Zs77Z8MnP/h7f+m3fzO5iihcp48cOlllWondzTv7YB3iuymB7Td3kXGSG1+uamCkWqqQoSlxowVTsHh+yCQPWdezmCw4mGVFGCgoeXtds/i8Ys0MI/PAP/zB//I//cb76q7/6yRqRZRk7Ozv/03Xk91tnbr/2VtaRNE0ab1LjjTOFcY5SX61QiidZGFKnfCUbQBDSpjDyRK4RRbqzhpE6lo3UIiUFLgq6zpKS3iOT0nCzkmzaHp0ZlIboBow3KCVpOk/fgoWEzQABAABJREFUW7p2IKuyJFEJKY+ka3tWNysO93YSgdM6TFYQe8/N5QWH+7tj8LFkZ1aR5QVt1zF0HUWecXNxRVnmLC+v0FKzM58T7cDQDnjv0iZ+W6epeUg37bbd8mB6lw/8kfdzev8O870ZyjqCgCzPMNMpVZ42NCo3qDKDMiNkCqVShghKpRM8znpCGHX2yCTXcgHnUjCk8wHn0uQy6zNmOwo5IqwRKXh86Ae2yw110zIMqTuf9wNlVVEURSJtOY/3AaXSeb9Fa0dJInrFiHApiBMl8V0/epjGbLl+PB+rLcO6wfpAvdnw8NXXeenFF1heXyT8OWnCIhGIGHC+Jy8Mp3eOWK82uI1gu1oj84zF6RGdc0yKKTc3S2zboUTg+uqSzWqL6y2b9RalJFlRopXizvEB02lBQFDM55hc09iUneR9YNu29E1HEJG6GcizDKESUbFUCu8jMSqIHj9inn0EbTS5kiNFY6Sk+kA5Amx8jAihnng7xvlg2lymSpMxW/MJbCOE5PtDyHEjmeShYaRGjnqb8Y4E5jb49i0efxjWkK7vxwydJOfc9i1CwM3NNfV6i8pKZuWEp599loPDA/r2FQ53d5nv7vPqy69wfn7Gtq3JihIfHGiJVIp2WyOsZjKdsFSK1WqF73t8VT0BCslMovIMkeeIcoKNiqwqubm8YOiH5J/c3eX68+ej3FGwvVlSyBlFWWKMINbrNKERgkpH8gUo7dL7xHvaukmKinFP4QU4KYlSYQdPXPeIXiNkRawMstAIlTIIoxCpyFISk0koKoa6TVP5YUCVFXo2Zagb/OAw4zTTdi1d3xGnAVFYuhdf4fqNh8x2Fhw8fZ+uyCj3dxmaBomkX69p1jXlYooPgni1JNvdQRY5jGCKGG5DYr+YySQEvPjZz1JWFacP7iCkoDrcS4CZEeyT/JQSL5Ln/RbsBGMOHJLMJAmdD560IUiT8Tj+fxybO0MAkU0Q0tJZh20spYtMQsAYM+YxpXDbEKEdAm1vKSclIaRgeSFJcIoQiNalMO1xQhyjYF33rNseKQVD26TJjHMQwQ4DnD2mfOptzI8OcDpj3Q4UyhBIPesoBSozFLMF+WROcJ6D4xNi6JjPK7TJkhdXpyldv3WURiKaJHeWWoET+D4RFL0QZCPNURsN0SHHhqOOIVlFIsjMYNseXZR0XUcpk7dr6DpKoynyIklDTc662aJvlujJnKGpub6+5Lp+6+yDL/f4iqDh/Y2/8Tf4kR/5kScfr9dr7t+/T+sHZjsTVuslKEE+n5JNyrQYjya6OBI60i0gtQG8TynAUiQca24M+v5drr7wBdSkotrbpXvtgh0xxcyOOJinpGEnN4iDE5x17CwWqLofO2cK6RzD9pr1m9cUB/s4rwnVLnXvaLuBoFrKYp94VWOaG7qLV7kRA3tvfxtqehdd7eK3b+LEFmMPiE5BIfDeo9ua4Fuijbj6Cm87tJjj6w6y5CPwNuAGi5gfkU0XWOUJY+aIdGn064UghCHlkAiDGqkvad/gQYJB8Pnf/l2OnroDWiGKAjmtKA/3qG0aVfu2Y/nGI3YXO8gsY6hr1tfXBCFotwO7Jwf0YcNmvaKIksZZju6fIvZ28Ahc2+L7AVnkyEmeDIBDT+wHVpdXiADX55fs7O1w9fAGUxR8/tWXaZsOioJN3zObTumjxwVLcLC8foy3W65feEx7viQ4gYoOvEkLZ4wgHYXOEICalejZjO16S7Z7h8nJMYO1aCFxdiCrZviYYfIpQWqMSiL+KBilJrfW8rQAeB+JUtA1KXXddh0yeBZlmYhQUlEZQ4PByJZFIZnnc9Z1z2xe4qcltm+Z5zugDGerLXIYqETLVz33HC5E+mg52pvR2AfcvPEqH/2vn+Adz5wwfdtdptOc/Z0Zu9Wcw70ZR4/mqWOvVKK1RQjKIKWkDJ5QCP7YN32IbbukGVqWbYeh5O37U3wvqbueOFtwPN/HBcPgBo6nCkNkv8yQyuKHCDLjYvu/Pln68Ic/zCc/+Un+03/6T//Lz/HlHv+jdcRD2rfF283eF7vjjDLV3Cj6wSJHZENQMlGswm0XPX2zGFeZ5OkjbcxjIAVGp59jpEqp9W6k32lNlAkaknCx0A8ekwusCzSNpWlakJHtVnO4PyUTHqEK9k6PMRrKeUWeG6q8YLO9ol5vuDw/p7p/BytNQrgOLU1wNHWLArRWnD++IAyWoCP3n3mavaMDXnnhBV594QXm0wUMnkleUruWLlhk1/DpFz6LLJJGfzop0cFhtMRMSrKQ8Nw608hMJWuASth9VGoqCEIKjEyGl1F+J5NPafAMgwWRzkHfDbRNQsUWZYkyhqnRo+dS4KxPQbmrLc3Q09UtMSq09FSDZTELFNMydWqjJzMKlECrdC0LlbKEcJ44ZreEGPF2lPZoh2t7uosl7abm/HOvcHV2zcYHXmt7vrBa8vDxG6PUTqX8lxCQJiM6TzZdsHNwzM31irZp6K3FzKaYsiQ4R2EU203Da6++hu8bZrsHzKdzhmGgLJNXc7PZMJ1Pedvzz3B4sMArQVFNkVlBM67J7WATtjmCQ7C+qXlcrinzHFlqwugDswG27UDXWaQWoyE8SXiGENFRpGw4lYrbZDZPXorwxC8mwSfZaZQigY5EgkwIGP/GSZJ3+z1JHZZQ+4zPFW678ILkf31CC3trxx+GNSQzhkj6OwQ6hsFRT0qGGHn2wdMEIi+99BLn59e87498HYudfdb1pzg6Pear3vvVvPLodeL6JvlRYqDebrn/9AnO96i8YKgbxKho0Eph7UAXU7Fv++SPcZMpKIWZVVjX4YcBbXLynTk3r72SlCdZjh16Qt9ju5xid4KzfYKx9Elpk5lIsQNarrBWgyiIUlHXCXjkrSP2Ll23QuD7iL1poJXoSUG+U9F3LUSPcI7oUuPJFIZizzBsLWaS0zc9UUlknrN45m2El16inFhWmw2a0fviA2eXl7QhUOzWyBC489R98smEamdCVmTIYoHUmujGAF4B2XRCDBI3WIzzCGNS48skb1AYiXa31Lqr6xsWIXBXjQW7VMiYCp8YIHqPkgplNMGntTOMfqdITP4x5G1M3xf3oCG9xxNpNdD3Hm/TlNU6UCoVk1KbBNFqB4JL4eARiScbZZZp4teNfaI8M/i2xeg0bVJKInwkDJ4QIttmYFN3rC5vmEwq8rKg6zuqXFBSIooe0bdYZ1jVLeViwnyWc7Np0/kJoIBCG4zUOJXO1e58hyLT3GxaQkyDjmEYcCG9N32IqWizFq0SMGdTr3n15oK3n5wSiWR5Br7Fx0A1zRAigbLCeK689RTTGT46itkOvmvIypwYBLO9XQohuYqOj59dMGs6IHJ19oib8wvs8EU2wh/08QdaLJ2cnABwdnbG6enpk8+fnZ3xvve978ljzs/Pv+T7nHNcX18/+f7/9sjznDzP/7vPZ4sp070Z667F94FsUqZuYIhPcpUSznA0ksaxEo9JFiOMJurUEbYiMjs5pAmBuL+Hvdnj4qbl6KkSs7ObOqfZKb6YIXHYy0uKcp8YRKLP6QIjJIUKdNsV2WTKzukJV/WWYloRUUzzGWxrvL9hR/TsP/s82e4h+eIIhKL3EkmFDhlSpspb6YBrLlEmRwqFQKBkhcjnhPaaok9dBudavDpgenqPQY0mTgkIk9CUwuBjwIUUpiqkAHHb+RjDS8ucp97zLvrLJf1yQ7E7R4xSC53l6EmF2NRsX3+MjhG0xNYNtutomhqtDKGzbK43CbleVNiuRx7ssPP2Z8EYfDfgu47gParMUrHZt2zOHjFcXaGlISqHHBz2ekO92tJMSz7+6c/y8Pyc6XzGvKiSXr9tKfOcdd/BsGQSW8LGIZ2glJKTqkpb27Hrr6Vg8IE2OEoE3iu8UkzvnoDJGLYbgtYQFWHoyGTKszE6R4j0Pk15EBap83Tzj4HBWequTR22mDKNTGFQhUZEQdcOVARyISg0vOdkzkUXeO3GcudgHxkC55fnvH5+yeH9u8x2Z0x3Z2g/sB9bcjzXmw07swIXe95cn6Fdz+uvXPO+dzxDVeQoD5mR9Cawd7Bgb++raFzNcrOmyCuCzmiCBWeZFAaHZGsF09kxcnvD6+sGXUzpQ+ALVyuYzdlVOb4TvPnomqfvHxBcj8kNZ+uGWQlt7Vh3HmffMicGgB/8wR98Ani5d+/el6wjwzCwXC6/pDN8dnb2ZI04OTnhv/yX//Ilz3dLunqr64hCJJ/G2Bn2ow5dSJHkKnbMXhIp98HFgCGS6N7jZnCkGKVQYkHwcbyhuhFvCiBx3uN9ouBpo4jWpzyKSPIfAE3bs9iF+bxMlJ/B4qyjrVu6SUGmFEZLQvTsHuywPL9gsB1VUfH2dz7P5eMF3qepQVlVbFZrpkXO3t4eF+eP+dxLL/HOp5/B9R3GmFFSmuSEp6d3ePOlL9AMW5bLmzSZQVAoTW1bGtvSu4FPf/zjlDawvHPM0axCrBvmx/vsHu9TTUqyTIORiLwk6lSkE1xal00y8SLFmE81kp96m+Q5KOzQs1lv2NQ1bdPibaAsM3wIFFWJyTOIAdsPXDw+443XH2IjDEOPQKERbNc1/tCyyw5FlfxVzjpEHEMg1ZiN5RxRymTyDl0qmEIgWo9C4Joeu9xQv3lBe35Ns97gipKiKPDXDu8SRW7UDUJUFCanyEuyLOfxw4cMQ8fO4RH7J8eo29iETjGsGs5uVtSrFXlpeObpe7zrXW9jvjfDRyimBfeevs9sPiHPJKtNzem9U2Y7CzbtQOyGJGUWAqUkw60h3Qe6ZqBvB6SQOO8ICC5vWh6fbxEEdhaTFEyuJJLbMGQSqCbVP6mgGX2ZIYgkxxPjVTN23INIfuD0vSJ5MsKIgEcSQlJ12BCIPkleCeNUUUSkD0gtxo78Wzv+sKwhHhj6DjskiftsWmHtwHqz4eLigmefepY7D+4ghOHho0ecHt/lfV//QUKfJHXveOZtdIPD9m3ap8S06Y3egk046Fun3uAszinsaKz3Ppn7VZbhkQQn0VlJdXiCEoJ2syZ0PVppohQEO6BMicySv8XkJX5wSJXInzIzTDODvX6MVxFVndA0NcNgUwlsDME6MBX96oL+ek3oHaaYEofIUFuy6QyTXSHGpgQi+caxDvyAUkmCKXTCjFvv2f+a99D97ido+oFt0+BipBtDsclzrm6u2d3d4+LhOXsHB0wXU+zZFTYmdLRt+gRdEgLfdphJkd63TQdlmaiOBLxL03+pJd6lKf/X/tGvQ40eqzhqqhMcJl3WQpkkDYujJy/4FFIfx7w3uO204UPEeoc2GcKHJ96mENJ1ISTgx9xPkeIkbPAIqdA6Q8hEBGzbgfXqhutNT20FXTNgXdpj+MElr6G1+H7A1j0iBmKWsbluOX98wQuf+hRGajIhyCYlmTIMnUdKRxkC9fU1rtzBDZ4qm+K9G0EtI1hHamSWERCYUVFzeHSEiALb9VRFRvIipqLZ9gMiCoILKKno+wFMoMgLptWUSVkwr0qyQuGbiBmbacF6orUp13KzIQrF0A9JHqgUwuSIaoY3Am0vaa8veOrpO+TacHN5Sang7PyCer1mt3hrZN63cvyBFkvPPPMMJycn/Oqv/uqT4mi9XvPRj36UH/iBHwDgQx/6EMvlko997GN84AMfAODf//t/TwiBr//6r39LP296sIcqNZUqCFWOG4shZ23qXo3UtxBCulkriQg+ITDV2BUJKZgwq0p6Zyn29xMJpRnoX3+Z67Mz9vcOULsL1HSG7FNKNVVNfXPFZDLBX2+gzNl7+hnq6xsKo1k8fZeApZpMqI4OIUS6qxUirKkmnri/g1KGbLqL7XswEVVNwGbE4BOuM2ia9ZsY0zO4Dm2mqCzH9wpne3QQEIfRo6CgLMapkUCiE6UkRFwAGTx+6DGTOYEUUCezMTRNpDugEIr9B3fxIXD+0ms8/TXvRhSCwmTY3iWtedNy/uIrKKBtajI029UaYzTNtubi8SP2wyGTaYFTGXaRc/9r30O2t4MdUl5Bvd0m06cFth325oK4XdFc3zA7OOLRtub48ICoJXFW8fHPfZZHr77B4uCQ3lsa51BVjg451qUpj3KOzXaLlQqH4+2TkonStMHTuX4sCDOE1jCZURwc0zeO4qk7qJPjtM/xEd+1CF3gTY9VyackTQ5EvB3SJM5kBJcWcReSKZHBszudE1FstjVllhZeHz1BpI6PjpZppplKSSUkcgDjLDeNY7a7x/PFnNXyip1DzV6lcVYwVZK6h+PjHJMJisMJl8sls6Ig2i3//pMv4U/v8f/46jucBEeuMwwJGhJ0xkxMaHtPby1OJBNubQOZMrRdZNNuWExLFpOM//Lia4jpHq9tO4LMqFRGKDTe9QgfeHonZ1YoOqfZKzU+j2zoOLt6awtUjJEf+qEf4l/9q3/Ff/gP/4FnnnnmS77+gQ98AGMMv/qrv8p3fdd3AfDCCy/w2muv8aEPfejJOvL3/t7f4/z8/Ims95d/+ZeZz+e8+93vfkuvh7EjJuIXpXMuBCSpE67GSVDKXLrNTkqG20wJbEg0thgDBJnQ0SrlP0ilcN4mSp5Mno4hRDrrmZjU3fQh4VWtDSCTKMlah/Me29tkhg5gm55607Jcd8ynmqrU2L5jZ3+Perni+uaGg/1djg9mdG2CG2yWN0Tnee7pe9i+Y3tzzc3ZOc3RCaFtCc5xdLhP3TasLq6ZFgWT6Yyu6en6jnboyfOc0hcpH2ckyBklsU3Dw8+8yFJEplJRPzonvO0p5LP3mOxNR8qUBALeujTJUDL5SElSkygEPiaZnPOeIATb9ZrNeku9rVmuVtgR1Z/nCi01J/dO0MYQCPR9z5uvP+TifEUz9HibNh1SQ64lNkSUGXPktERLiQ8e6SIyyhEwkDybxORbSF3glOXiBkvoBkAgpSZfzNnLMvy0Yio0N5s1dbNH4xxlkePqJvkwjEHlOU29JbiA0Iq33b3D8ckJ7WZDzEvWyyWPNw2X6zUGxcHxKXePTwghYH3g4uqavut4cP+UoJI0sZxWDDGy7fpEvdIa5yLbumO53NJ3A9771OX2gXU74CNMqiIVUy7l1OVK01uHGzyFTlM86xJYI1cKG6D3kAsBpMDtRG0bSVUjatzZSDYCTIjp56a+gUzFlrWgdDqfJPlqFKQA4XiL1RcYIcnUl78d+cO2hlxe3aCUpiwKYoy44Mlzw/XNmq2qKfKK3GQELygmDWVZUVUFhydHXF2ueOapp4g+0HrP4/NzyvkBVZlx/viavfkcJcG7BOiQUo1EvHQe+q6nbTrcEKGYoE/v4s8fo20gdBu65SopZmYV3XKZfEoq+ZXabY84KCizHJNJQj9QzEr68y0US+S8IJpd1ssVBEEwOhXVSHAe37Rsz24YhGTy3PNEmaJMiDpdc4AwCTYkfAoc7WybrqcygyBTE3Zo0fk+06ND6m1D23cpWmGAXkTqrqV2DtMP7BzuUC837O4smB/vE53Hjg0VP0oEfBobJ6mXUqmo0CpJuAIEZ9FFRpQigTmURmmVwmWDGD12IUl3pRzzHQV9PyCVQo1REWJUmchxQhpipLUeISRyzOkT4z2GmDL4ZJR4b9ECfPQYYzBa44LHR0+RZRRSo3WOyQrMzPL4ckPXdFxeX/NiaBAn+xRKYoLDbjqEtQxdR54bnLX01xsOp1OGkKjF1gVi+oFEb4nDwND1eDXgejcWdIy+uUhddynYWhsmsxm2H/AurYeZSECsQmmi9fRtTzsEJiZDeocLqVFnKkHrLdMy573PPmBSlEwXGYiIqbKEO/cpBse7mOTtNuBINE2hM6zzWKG40hmvP3wTv7rkeJqxKAzaOYII7O7uUh/tEYxgv3wLYKe3eLzlYmm73fLiiy8++fjll1/md3/3d9nb2+PBgwf88A//MH/37/5dnn/+eZ555hn+5t/8m9y5c4fv/M7vBOBd73oXf/pP/2n+8l/+y/zMz/wM1lp+8Ad/kO/+7u9+SyQ8AE/EBofWAicT8SuOiNjbfy6GMQU5da28Dwx9jw8OKTVaadzgsL1H5xW2gt17GUVVcFEq+s2SerVivnfIMKRNgjKa6t1fDZ/7PYarS/xSojuDzjR7d+8RvaWa5AwxdW6Cj4iiRMoVmUqs/t3jOyBzpBRkGQQZKPbv0VwuCcMlXgiGeoXvV5hZBhiUzPBqTHLvWqId6F2PLCuCUKg8YKIFG6FMFCyER3mRpiZGJyqXkJhMpY3MSD4SpM7oEAOd7VmeX9F0HdXRLgMhbf4A33UM1yuU9zSrJbuLPSaTCcWsYLl8gSIOieY1KakWOxw8fZfi7ilOSNww0K03eBHQWhEHT315id6s6JdLTJ49SX0v51NsP/Dq1Rlnj8+4urqm6TsOjw8pdZb8AMoQXMRow6rpUJ2njZY705JK8sTIbUQgSo3MCszOjMXTT2EFDNWE0/tPQwdiItBSEdxAwHNzfclmsOzODrm8WlJMcupmy3RnD1NVDC5QTudJ2CkF08kkIXq7Dhs9IuqkF3YRqTKqQhP6DjlqvVOExcBEB+QsZ9i07E7mlKXhzYsL7t45xAhDlhtQge2mo5hNEYXhbU8dsXx0AZsN96sFl5fXfPJRwbA/4bhMRL662VJUGWU1pQ0N0adcFhlgYjKi0AzS0viAsY6pqTie7XHlcrpmiwgJ/jGZlETZE4mYTLKtW+4cTCiFpR5SkOs0f2vG7A9/+MP8/M//PP/6X/9rZrPZE3/AYrGgLEsWiwXf933fx4/8yI+wt7fHfD7nh37oh/jQhz7EBz/4QQC+9Vu/lXe/+938xb/4F/nJn/xJHj9+zI/+6I/y4Q9/+Pft/P7PDiWT3yNTAke6r6VwWvEE4OBDmkBpnShGISatto+3DYckPZJSIEYJn3Opuz7YAEgCjs7BprG0fQAp0FImT1Jn0yY+JN9I2zlUMzyhUColkFlG23SsVg3RKib5LuWkwrcN6BSsfHZ5xaTMcYPHdgNdlqNdQBvN4XyHZ0/vsF6tuXrjTbRQ6AhqVnFweMTmasn5m4+edKBNbnAjXWo6mRGFwhhNWUw4OTzg+P5d5PUNfrXBCYEl0tUdQz8kaS0JMy4EI2xGJJDASL4TQhEcDINP2Gkf2W5rri6v2Wy2bOuWpu2p1zVSCbJBM51OcYN/0qm1/cDZ2SUPH1/SDD1SaYRUuH5gWlVPAoCryYwcjZABI9KaF0PabEY35qLENJFPn0u5UCg5dpEFWWmohgIlIJQF090d3pkpfFVyvtwwOMsQBNVUEoVkubyk6TuKas7+zj5HO3MOFjPONhuurq9QQoJM2UV3Dve5c/8OHrAucP7ogsEnKuIbbz5mvjfl5M4x5ST51ozW9G2PtYHgPDeXK9pNh20H7DBQVSXeetabjmGwqSgxepS/QecCuIiMkY5I3Q2cyBneeTaDZ1KYpDqIAS0EblyzJcnb52OC2YiY4Bg+hJS1E8d1VwgGQsrFIfmY8BHn/Ygk/+I0F0jKDf3le5b+sK0h1iXFihsnFU3TgYSiyFhM50ynE86XNxwfn/LKG6/y2htv8J53vZtiMWV+cIAPnp3FDntFidSGozv30Jnh4vEbFGXG+uaM+aSi7wVBtAkcIGSKRxHJNxMlhEmF6y1tlBS7+7hVpJzOkJMK166QziG9B+eor9fMj48odhbojQNrQQqGdZtktI+XZGqBXERsb59MmeMY2NpvG9zgabctvRe46R7MFSqHIDw+Lwn5POXvxKRgcX2PJKbCqSpH6VyDXq2Y33/AZG+X4uqabNsy1FsyremdIDOa1bChLIpxquxxdUtft2T5AtcNxBgwmaGvO4rZLEURhEgQEoR60hS2TYcfm7+qyMmyFCab6pmEESf6Wx4nYfRPxiBSxt0YPOZD2heBIowgVGTKh8rznCS+TpOoENKENnljPUal+4uNCQIUYlrnhUxEUIQcX7JnWuYcH44eMC843cmpSk19ecn5zZr1qsbZnirLCUXG5eMV7eDYXyzouhQaLEJAZUXCdtvA8nKJOFmQTaHMNGUu0ToSgmewXfKxe4vRit29Hc4ePWIynRF84Phwl2VriQ6Eg653eEaSKRGdpcJPCEEmJSoTHB/ugHdUlSZGl7JG8fhBp/DiGAnRM3SWwUdefPFVvvb97yHs7nG16bncnnPz+qvsLipOTo+4fPiQdz04ZjLPaddLjjOF2Z0S7R8iGd5v//Zv8yf+xJ948vGtfvd7v/d7+bmf+zn+2l/7a9R1zfd///ezXC75hm/4Bn7pl35pvNDS8S/+xb/gB3/wB/lTf+pPIaXku77ru/ipn/qpt/zipRDjOFimwUqZJYOb++Lo89Z4751L5BAhkUKBUAyDJStyhFbJWOZbVKlxFvThHhP/DPXZGdl8htCakCkGBVme00uNPriDf3SJO38TKzX5fEZWKUxe4KVn7/QB67pjev8uqzceIfsVUvZkkz1MNQdSAeELjZztMFAwO77D6nFN6Frc+gLvWoq8IptOU7c7agLDmJQcyIoCIQxD79HDwPryMbMHi5Tl4gXCQnt9iQ8OPd0ZJ249WqWbfowh4V+9w3sHBE5Oj3j5Y5/G24AschQKqVJele8G8tzQnt/gnWMLzPZ3af3AzuEBhwf7FPsLmrYhVppSZRTVLG2GQsC1FlPkSZLTtojNNfXNClNOKIqKNy8vKTKNbXvWMfDSK6/x5muvU/se5Qy2G4izgsEGXBhQec6Dd76Dz33kjGLoKQhMhCDXOa1NY2Els9RVKXKYzBmk5uDoDtW9UzaXV1TzgOvaJMVJeCGas0sePbrm5f5FHr/2Bl2wDETe9p53k1UTHjz1LPJUMd2Zsm1q+qAQRYb3SUolCHRtx6QscWMQpHeOIUbQGdqPHSwKBAOzqkRLQ9P0ZMWML7x+znuff4aq8OwVJRe6I8YkQZqeHLJQOWev1FSxRSpLpQpeX24538DJrODezhHBdmzcQJmX3Ny01EEQbUCRNqeb2xR1NEbn3Dla8Mnffom6leiyxFQZeMe93QUhBs6XLff2pogQqZ3DImnalvmk+J9ep//t8U/+yT8B4Ju/+Zu/5PM/+7M/y1/6S38JgH/wD/7Bk7Wh73u+7du+jX/8j//xk8cqpfjFX/xFfuAHfoAPfehDTCYTvvd7v5cf//Eff8vryG0mkvW3PrRUIDkXnmBsE1bWY4cU/6CFIBJSRlP84vcQSOQnIp7UaXQjAczFSDtE2j6wbQYG5zjeT1j+5c2GLFPkeUbvk5fF+0jbDeRFRr3ZEhtLkef07UAnNTfLLfNZhpSK6WyCzw2rzZbL6xXtpsZ2PaenJxzuLuiutygfOdndI9QdlzdX5CZjZzplf38fgWDncJ/je0d89uOf5gsvv0TbNRRFSVXNiM5zkFdMJzMODvY5Otzn7v1D3HwG3UAx+h1VnhN9xNmAtx4TIdrkQRIimaIFEhHS+XEu4qwjCslmveH87ILtpqNuOtqup6kb2s4iVJLBrpZruq5jFmYQ07Rltdrw+hsPaaxFaolRqbu4rjds2xpBZHf/ALM/SzlAJLoVbiB6n+4hI+bNdT2h6/HWEawl+rQxUpMS3Q8U0afNjwiYUvPg7jHXqzVeKq5WK8IwYIyhXqf8JSHAtg2yd4ggmc6mbCdV6lBrxXbbcXxwgMo10/kUXeQU04r1VYMbejrvWN9siQSyIuf+/C4HuzP6pCNM+TdNjxq1nUqALvPk5dBJNjcMFucDIqZOuXOJAKiUYFm3GJUmCu5ohyBgs+1RcQzIzDRCpolSEAE9TpiiD6kIliOrLYQxI+aWbCeeeAB751EqSaBvfUrEmO4vWhGkxIYke/pyjz9sa4hUGh9TLhsxorTGe8/d40OO93f5xm/8Y/zCL/4KH/uvH0MQUSh+q2m4Xi158OBpPIF8UnL04D5ve9dzDEPH47NLhr6m327IlGDv7l3aesNSwNA1RBHxCuqmwXlPt91iJlMeX1zSr1ecnt6FZsvk/lMMV48heEKuEV1ylOVVnprIWuG8R3YOKcBuLWIicesWtdvi++QLUaSmEhJc2xCVZOh6BueJWUHrPLlZsHvnBJ0r3GdfxcoZ0l4TaksQiYCmi8DQuRSSqwFhCB66umV6dMD07Jz11YohBvquJ9cC27cczhdUWYaOqdiSRuE2NVvrQQvqbYtQEjVmpanMjFjwRNIMIRJ6OwJKwDU9wQdUnpGVGU9afjES/Yh5lCrtHwOJTBwDKtdpX0lqiow52mnKJGA2mdA5P/r9wiifjKNUdtxLhdQwyES6/9xitmOEzgecjSidHo8PZCqyO83wuzMy4zFas5hOyENA+8jZpUNnJatNTasMZ/1AGLbMyhwpJX30rNoBOfQUo3JBZTdk0yl7B/tUpaKxnpubFX4YyHVgs02h5XkxQ4oLsqxAZRnGZMyKAhUibdMhZVJXoBU+Cow2qOCILpBlEmEgFxKhcmIYuLi+5MFT9/DtME7bwA8JbqG0p+sHLrcttpjw2qrh0cOH2NU100xivWW7XNKuV2gOaPqe7arGBI/2Hv/Wo2O/7OMtF0vf/M3f/KQb9PsdQgh+/Md//H+64Ozt7fHzP//zb/VH/3eHlKOdWiRNdJYZnE+dQecdWutxcQZCxPphJPqMnxvpJMhEA9KyTCPdYUCQsdCn5JOSGB2uLCinc6JMm6dcafzuLuLBPfqXX0L2FmUj5c4CpRXDbIGYTlHa0LU1sb5C5wNGS4RykIMyE4YuEHyBFhm+a7BlSb53SvfKx5GxS9MuG3HbNaqokCISbIss9vBmjpORODj60FJMF1Sn9yCTKO/xAtrNDVJJit1jos5Bpg65QD/ptDjviD6Rb4QMTA8WTKoCMymRKoXieSKut2w3NTLPEZkhug7fb/Ebyd7RAfv7u9xcXiGuJfPTCV5A13fILENYR2jSht93lmlmqOuG4C3WWor9GSYvWb/ecLx7SMwML77wApu6ZXlzg41JStl3HV2eEwZPXuQ8/7XvYX9/lzc+MWXSb9lVgokRDD5thISNeCORJoO8grxkvtih14JKCfrtBpVlCKtRVU7bW7wVXL15hXaCMsC9nR2mh/scvOM5zGLKdLFD2/Ysr6/p+pq2blgPKaRUoxkk7B0dUFUThJRoLL336CxHeUelJXlesn205WLpqGY5fmjZm2h0AdHBwckBVeZRskdRUhZJemEby3yyj+8j+f4en/6tjxIurth0gq/7mud482aNioqnZgalU0fJObAmY107hICdomDdtmwd1HVLneXcaEvtFNsBmqbhYGdOJgOzsmInDzy/P2fT95y3HbYXTAqBlob9Wcn55VvLNvifrR+3R1EU/PRP//T/MPwa4KmnnuLf/tt/+5Z+9u93tNYh8xRGK2ICOmgt8c6nBHJnkRGyQmGyhI4PIRKiQMr0femqik+oZDGkDjwieZsiMLiIGwugbW3JraSuUiAtpATytH6RTFAiBYLaPqGB0+uLNJuGST5FBEd0IgWpZhmr6xukVFxd3pBlOTIzXN/ccHKwz87OguAGqlzT2xSiPC0LJlmB6xKg4ej+CftHh9i2RYSA9R5Xb9BScXh8ilKGbrNFSsHO4Q5lWaDvaGLTI3qH6HryIkcXOdKoJGshEKxHZTptG2LEy5iCLEOga+24yeyp65rr6xuGHlwciATaJ2HmERcEm/WavmlGoEYK5Ly5ueHi8orep/OnlCY3GabI2G4byiLjubam7DKilhg0MgR8PyQ/iPNgVPoX0iYpepfkj+NGKESBLHPCZpuQwCESNlsmuzs8d++Ey5vP0K5XINVIVEznT0tDVUyYTirmO1OK2ZS901Oq/T3cYDk2msE5pARVFkgNwchkyO5azs6viNZx58Ex+/u7gKTtesgyMpOmNraxBOsoREg+sczgpCTLM5SBofc4a4lErEsydHRksJ5626aoh1nOZtOBjPS9xxYa7SRKeoQCEMgw+k8YfRwR1OjREyNm/DZ4M474OzfYNFFwIjUPQkQl8gmMkr0wNjD9W6Bq/mFbQ4RKKpJN25FnBmUdoo5cXl2zWa1Zb2suzi/Z1k2aIu3ucrm8wH0+gTaODo7IigJveyYHc+ZmwSsvv4HvWqLrCcGNmOk9hu2WTZugJyLensUEFbBtQ3dxwayY0Dc1EYEuS3zTIKVKOT4yoaeDD6hSk8/nxO0loVfYoUNq6NZNwnR3FuEChEhW5Glq0HbJk+YD/bYhhPR7i4fniKqiHByzvUOy/RM2jx+jdiXWRtAGu97irMMNAaXSBCLKgJARYRReG+b373F5dgWDQ5eSpm2YlxXWBnQQ9N3AtChSI3QMlMYnH/r1tkEowW6Ro3qHsp4spgxIVArgdf2Q3pNNh7QFWRQokyGlTFEPIYxQhpQRdltceZ+k2dJHok75lQBRqjQxGtfnJzlu6dIAvkhiFjEmlUCC1yVSoYoIoXEjXbcfPMt1y6TU5FqNBZmgzDRGMxZqac+mRSRTgoP9XaazjMwIZos5L33q97hZW6azGSs7sFl3zPIShpbQO6JRZOqa/ZMjMgXrVc3lcsv12TXXV9fsHp2SqUQnnc9nZEUCg+ANSgj2dmYMbY+Rmm7oGUJk8JFMqeR98klt4UKkEBKlIlkuadc988k0kUN1UmGEfpSTDp4AXLnA7t17PLxe8plPfYrjqiDWa1SMbNc1g9EYpem2HX07oMscbQW22WLU/yIl5ss4viJoeP+jw484RkmSJfgxFdw5l8zDIV0cREYvUwokva3ildbpDSxTRyBKgReJdKW0RgiBkYIoIrKoiMokTOfgaa/XCBxq/whdt/iLM0KQFDv7+NygVcEwWEw5Be/AWWSREYcGHSS+bTBqQpFrAh7XOmIIrJsteZUzyDlaZRBbgovkskRFgw9rhC7Q82P0dBcjFUL07OQZZBNCWSaoRUxENt9tyPcOCTJL/LaE30IITQhizALQOB+S2U5Y8v0ZXXQM0SPHm79WEHAUmaEqJ7TCoKdTqlnFtJww1A3Nak2wDlFIyrJiGyLHzz5F7x3RWpZXl+RFhnaB9eNzqFu885R7C+aHB9TtQB8DB/fucrVe8+j8gsvHZxwcHPLm+WN8SIhcNzjmuzvce8fTPPuOt/GRX/2PtINlqiJFGgEQcpN+rgRHpDA55vSUbG+P1XLNsNoy29nBtT3NcEm+M8c5R10PvPL6GcIKuk3NernCDY7Xri55dl5i2ikL13Pv/lNcv/I6e8f7mBC4ePkztMFwve147eIhQkbe9TVfw7ve/35yJSl02jyKYUBKyabrEUqwd1jh8Uy1psoC7753yuPrFY9WA6HvcEHTSZB5zs58guwd1g4UU80QMqr9e7z40hd4tP0tTFXwjV97n8oPY0dKIo2hbjtscKisIDhH4wQrJ3AUXG6XiNIgJyWvXC7xJmNWGkpTcrCTobqO5/d3KURPpyJ5lnGx2WCKCV3XMy9yuvx/Xzfn/44jRFBCEBQjFCZ1iO3g6VtLmRtiDAQlCCaFxUilUGP+RowCSUAJgfcBoxP9SIzEtjj+Z93tP+g7h5QZdWPpW5tkgCZ7ImPypO6mszbJGYoMbTSuHxIG1ntkVhB1CvFbr1YsdndY7O3QdC2f/cSnmM8XnB4dM4yS5DwvqaqKdx7s8mD1FO1qS9cmEtakyJnMpogYOTo6YD5b0LuUWYQPici2s4vUgsnOjJ2DfcqJJG4ahNEIqQlREILHOT+e10iwHhEdxJAM1CFJTkLQtO3A0Dt89LS9ZbleU7cDTd0ilGC1XtN3luAiXd8k/f9iThwndbf+1LZtubq5pncDMYIxBUWWIRuNm09Zrbb0raWrW0KmMYIUGBxB6BTwHTpH7FLjKYZ0o7dti+8tGJ0oc00C0witic4xbLYYKdk/2OftTz9g1bVcrrbYYUBnOTOdABvC5IRJwRfefMTrZxcEICpQmULEtD7t7O+yfXRNlBInPJfnF4Cg3dZIBabM0UZjnaO3ASlcoikKmZ7HZLTNiuAjPgiKeYlWkr4PEBNEw7owyosShVGOPW8pJDIK2mZIvoEYafqBMjcjxiyh7xEjFlkmuWmC4KWNt3+CkhQQ/BOfmbLJ/9VaB1qhc024nUoJGMZNbhglrV+phwuRrmsRwIBESof3Saq1O5vx6mtnSCGSlwNNW29puobtZkXbNnzgAx/g6Pguewf7PH50xs58wXNP32d1fZkCooeOtmmZVCVlNaHfbpLPxYcR322TN1t4Tu7dpTt7TEAze/AU7ePXyPd2cOslQoHJdfKMWYvUBpWXaRLiPEpLXJcKXIJPkRM2NdmyPGMYHCok4EK/fjPJRnvL1vdcP3wNc3xC/9mXefede9z5mvdy+TtrlB7QJk0vlRC4rEQEh+8iKJ3IgReXqOoN7p6cYPOcam+XZdMRvMB0yR9XVSW5VEQXmFQTcDEBcnRCWAsfsG3PdDYBF+g2daJuKkkld8h0RrCOblOTVWXCeK9T8yOflImeHFK+XiCBB9LekRE57gk+eUzNiL73IWJUqmDE6CEzOvlV40h3ezJxjYCIKCGSDSF6tAJBxDqHC4D0NK1jGHyiNEtw3nFL9Z9UBdINKBkJIiaPUy7S3mw+SSHcg2dnMadraoo856Zp6LsOawf8ckOMgmpWcry/SBLArqEJA856VLR0myuy01MyLQhC0/cGIRK+HgHKSHItqaOj77s0QZaS7dBzmOdpHRUBxmm4UlCUSXZnMklusieQGB8dMaQ4n3awPN7W3MiSz776WV58/WUO9w6pux5hPQyWUgAigcp679CZodl2zKYlQ9fSNl8hOUv/dx96NNHfGutiCE8SqeUYQOudT1SrGMeJkiAm3QxZnsJRpRCjvjXlbBhlCESEMRghMUWWwAoxYoXD2JRs74YBrwX64BjVd4Rmi12ukadHqNzQO0eUEXd1hWEMabOSvneoEAlmSJuAXUN9fUNZlZh8Tuw6yt07mKrCdxeIvsFkE9rhkmJ2SMz2ENUJ2c4OUgaG7ZJytsAODtG0CJ1jVcBu12TVBJkV+MEnnPH/l73//LUry9MzwWfZbY69npdkMBg2I52qZEpq9YygQqNbA8x/O5gZ9Ggk9airIZXKqbKy0oRnMOjJa47bdrn5sDaZ6oG+FEap7gB6A0zDCF6S5+699s+87/PqvELWRpNkfokqaYgiEtyIlpZqfcKgFc+fPOX0x5+8MzxbrTmEiLQF5fkZ5xfHDPst199+T1lYitUCuV4i6jl9TBx/9pDi7iltNzK0DdYoCqMITYtynqIqGfDI5QwnoBkHLu7eIxjDrmlpDw2+7dkPHSLkbWGKkaooqVZzLj95wFdff8nf/s0vmauRlcoTooKYg+CMZfCO04tL7v+DP6T86DOefPEtNy+es1gf4TcNYxqxdUkMgnGE7x+9ZL9t2Vzd4PxANw5sb/bI2YzPfOLD++/x/Yvn+JNzyrrEjwOzquR0teKblzeszk/5F//oDyhE4ouvv+H65Wveu7zE6nywYRUh5IN2phVD6+ijotIlsR/Y7g/cPVmh454nt7eoconzioMQ0DlWKrJclgwdzI/P8S92jPKKolzwb375Hatjwz/79JzrrsdK2HrJVZvwQtL3I6u64tXmgBOSfdNQKMusnKZaymCrivUigxwWk/zs2EpcSsQx4YaRo1Wdi6EomWvJUfGDPkbynlXnwE4hM7FOxERwWUMtx4gSiV03InzBfGFJAYzRuMRk1M1DGy3zRkEyZWGIlCUK03QypsgwBnyE0Xl8MBlIMIU4hRCzF0GpXAiljP1X2hC8hwjjMBIrxfZ6hz5fEqyims/Zb3fcvrriyeOnvHjyiNt6wf7Q8OVXn3Pv/B6l0sxmM6wW7LY7Sl1SGsvmsGe8uWXdtFzeO0OWMy5OLilkwaE75FwRn2hubjk/W3O6XrKcl9AdGLctYd9itKYoiyzBUBn/6toO33UoCWZWEsqIVCH7uVJ8R/kbYwaQdG3Pbn/gsO/xwdM2LbvdnsO+wfmRwmisVAz9kMMZBQTvcd6z329xwWeSVPB0g0RrzaE9sF7WbLY7ZlVB8Cnnz5UWIcKEvVaI6InOI9+aua1FljZ/L1UmtYXgiW2D68ZM+JuVxOQxRO7fu8P1myuCB3dUYaYckn4Y6UPgTe958qtf53BJrWkOOyKZjhW9o5zNqOsZhS2oFjO6pmV7u0FJyfJozc3NjqIqOb9zTkwR7yL7/cB+1zGOCUT2ZEqf82CMksSJsJVCyj4JKVjUBWHI21LnE6XWCO8RIX/NIqfPEn32L/gIJgiEypQvPW2N5PTOjdP9ryfZXZykfsF5xnbENyP9ONIlgZxXJKCwaspiERm0wTSV54fbLHVdR5o8ekPXYosCoS394Ln2W+6cX0BKHM/WiBR4+eoFIURmleL1mxf8+Z//GT/9+R9yfveMWT3j9YuXzBdzfvrZZ3z39bcw9oyHBiMlUmYgRnAOrXNOlhEZXDJb1AwyUp8eM25u2H/5a8J+S7mo6N7mF44OrSVKS2xZ4saO5D2qVsQ2EH3EzMrsnSHXDHLKV5Iik94iiTCOxBjpYiBKweOnT7j42R8ymy8YDg3FfEl950PGV99AUZC2e5SR4COytFke6j2H3nFz6DGzFfNXbyhXS/TUzNjFEq0kh+sbUvR4lSilxhbFu7y7FBKegCefyaVWOdzbasqyJAXo9lmuKqRAW0uICak1YqI9xhiQQZJERISc+xN83jLHlNUBUgAhIIKe8vckWqkpbilnOKUJta9EBvrA9M9SHtxLBIPPdhCtxQROyZhwYwyDz/Lv4LMEUaPxQCKilcJag0ohR8DEPKATJOplgRYZDhRC4M7DB1zf3IAxLKsKY2T+HgPCKqxWjDFSSsk4jnTjkHPVKsvZ5V3awU++a4WUCm00lbWkNGaiKOQGOBnGQ4euLE3fcVFY/NBlfLj3GAW6MkglEEKjtcnvw3dpvhl/P8TEVTfwN89f8fWLV9xe3SKFoG16TgrLWkWOVzU3t1tcGOlHRz96rMmkT6U1QiuM/bt5Df8u1w+6ykmTZjrLzSd9Z3btvgsuVEplCcJkxos+m1bFNBUICXwMaEFGYnqf19opgtJ0TZ/JRuSJma0tbt8TtMAsVogYiMaij05pbjfgepLuqC9n6OWCFME3W3xoUTExDgNjhJmM3Lhb7J17JA/j9gAOkmyphCdagz0+woWSQhf03R5ZHBHLE+T8HLs8QmqNH/fI2ZxBKIbBIbqOqB2iUPnFtDqaQjJ9/jsHj7YFSURCEhM1KaNmnQsEHyjmC+68/4BSaqRSpJgf5hgUh11PefccX0iunj5n3N5SW8MoI4vlguL4CIJg7D1nHzzEp5TtAX2HH3oigdj3VIXNpLF6RlXPGXrH89trTk7OqZYLPn/0LS/evKYqSt7cXOdJTIicnZxSL5asjtbcP73gX//f/kcWsxnFbuT0+BgZBwqRaVLtELj85FMe/r2foI+PefT5d2yevELuDwih2ewPzI5mxKJEmJI3z99w8/IaLw1dklDNqBcLdNK0Q8/TL79m1+zytuzQcHF6Sj/03DYHejdwulrQVxqhElVdcf/ygrunp7i+x8ist0WVBGnwzcDCKNLCUEbD0A+4yTjdDi13jytMIXndSwbX4CnpE9QzQ4iZVvXeg3s8evYGc3yKc4HWOf7mbx8TxgP3zs9ZFobbwbPpA6ZObMeOxWzGzWGgntcIpXlwtGSuA5s+sJiVHCXJs92eeV1REjlfLphXJa+anqbrqAvDSW15edPkjQGWZfF38yz97+1S5MnhvDDs2pGUBF030GwGUt/jQkJZmfNqekkqM/xCWIERAi0EfcjSCzeBAxABgSKkt+CHnMnhXD57hMxo8ezfidR1iTACqzWjzwVAN4wTfixRliVj0+RMGpHlT3707N7cIplTz0uqsqSvK4RUFOWCGBODj6xmS4qjNY+//YbDo4bbN6/Y3rxhNltyenaJ6weGvmc2m3N0tKI2JVpr6qNjzGxOcg4fPdpaSlOirWR4fUXqukxyWmcfmwiRMGbPhju0yFigrULUJcFHYj/kTY4yuD4wDiNjn318TXMguoR3gd1uR98NuOC4ub5is90yDH0+36Pn9ffPuLxzxjiOuGFku9nS9R0uZmy2lBohJEpnecztzSnb7ZaqrrPBTK5RRqOLAlIAaQitIKURdC52jJCExYyxH/GHhrHt8ybH2jy46XrSOIA1xM5THh3x4cP3CMayMzXV+gRhCw5tx9PnL7l985pmGOhdRyAx9i3lbJVDgg+3qMOBuw8ecv/ijKPTE0xR8vVXX9MdWlanJyzWSzAao+VUtWUIiHPgowApsVVJd+gyAjqSAyFjwBYmN5YhUiiBUSC8AhGZacmsrvAktMk/JyeJXUZ+Z6m78xGt8wDgbeBuiAmrJErms/nt5r/1MbPxmw475mk/SdCTiLFEiAJrFUZAYbNU3pPwvz8Fze/90irL+8ehfws+o+taRIoMShFfvkQLwWxW0/cdwTsKazFKcPAjr16+ZBz/jKs3r/gH/+iPOL1/jydffY2J8NFHDxnblmVV0jQtIiYW6zWb7Y6ymrHrB5i2FT5Fjh7eZ/vlN4xXz2EcKMqSNDRYlYjeoxKTRgwQCT/26LJCuESUDmUMKURkVYFQuK57lx+WQTUSd2hhNsePI0nAwQWuhpar6yv6w57l6TmnZys6XZOKM+LtDcnn5kYriw4QrKA7RPZdQ6gXbPqG2atX3Dk9Ri/m2OUMUdW4vmNVltnbMgwMRSKKKcj0rXR2iipQano+8gwEksfkVTIQkcpmOIPPQa7KWpByGihk/53vR2JMmMLQNUMWWPvs7QpEYu/Qhcmb6WloIKdGP8a8lnoLdOBtw6nUu5iJuixywxkEUkq8z1TT2bykCR4lBUVVEFPeNqXJM9h7DylhjYQJEORD/jmlBLgeWZSUVUFdWpSQKGuo5xXpZqC93bCsyjz0sBZjNKau2QyBaCQpKYTSlPWCQxcRSuKcQytFaYtMgx0j+90BgoSo8M6jtSUOHVLb/F7Uhji0FLM6D+ZLSxodGAO2RHkHSuWzWhlChKfbDX/79Cn7kJtCUxiGfqTZ7Tg+PeVw6LAjjC4wExZEfs+2uz1WqrxFHD2r49Xv7xn/vX3l/wqX1BO2UcqsCZ02S9oYlJy6KPJLIoaM0s1Y1WzkFuSJcN87KmuQRIzWELL8LISIKQt0UTCKbEZNQ2RsHf2+oTKCwhjSvMZzgX/2lP3j7yl1Qsxrju7f4/bVi6z9LRTjdUNoB3Q5w8lAsit8lxDDFhUEKIOKO/zYIcQSKRX18QmxaTG6RGqLqI8pZycoo3GxAatJ0ZFcRzxckboePc/s/Pn5eca2jnljJpNHkHW2kUSMHiUVkkjfH7KpUQhMbbGFITmXddFC4IJgcIF6vWK4ueb60WPKcSTKXL1ZYxGF5ej8Dpvn1zz4x3+IPTvJOPdhQPnA2hZsrq6orCWSUGX5Th5GgMv33uPk+IxnT1/y8tkLnr14QS30dCDB+uiIer7CzGYwn/P5F9/yxVffoID7SdJVgqqIqKrgcLtntj7l/T/6x4gQefH4BVV9yvzuJdsvX9M3B3QC6RJ97+nGPb/94lvO798HJKaeYauKL3/1K+qhx+B5/7OP+fn/6Y8ICNp+IBCZLRdE71jNZ4z7jtEk5jrx9PG33L28x6zW7FrPMHQIaQlJ5kwOH5iXJbFrSSrhpScpmUMkw8Cbw46Ly0suZcFNswej+atvniOXlzjnaUbNX/36Cz78+ANum46Xz54w14Iu1vzt9zeE+oQ7SJ5c7ZFK0x82XJ5cMjiDE4pZWeA6x1JKmt5lKEXySBzd1S39rKBYlVyss0TjVTMyiEgRem4Oketx5LgyuOSmvIUf7qWVRL3LypjM6gmEd4jRY1KkUAo5CsY00FuVDaulRklJaTKiOoacEo+IpCQhSbzPpunRxSnsNHuPjFRYKfCDQ2tNCoEUMkLcaEHbdln65SPKKGyhCd6CFDnlXajJk5nJfKQ8Aa3mc87PTthfnVDUFeuTM95/cElMguH+Pa5/+Suubq5xfZfBE0KjtKE77GjGgcM4sjo65u6du5weHyGcY/PqJcN+x7wsefDgDncu76D6DmVmhF0Lw5jx+DFhZzO6Q481hmJVZziASMiyAFvgUw5wHgZP9BEXPM2hpe8d3TCy2+14dfWG5tChlGLXNry5vXo38GoPW7798ms++OhDtq9e0CPZbTb0fYeLkRB8DpoUGV+tpOT69ppf/uZzvn/ykghcXpzw3r27fPrJ+xwdrzKKQyqwA0lKZOnxTQ8Lj52QucF5ghtyUaUlsphw+Ubiuh6Zbjm+c8bPT4/51W+/5eWL55Rnd5it1pxGQRcSnohNK3bbawQtfbPHx4iQJkvfuhyse382Y991HJ2ecHx6hp8kjMerOUpLKqPYdpnmVVUFoemRQuW8mmrKlfOZjpYi+DCymFWMg8MYSWEVQzNQaY0sLDo6dGEpC4NQ0HcDSkj85JOLTF6PKZjTirxlkiLfx3oqUJ3I+HvXjcSuJ3UtsXHYEDFS0vqcs1XXFpkiMQn0NN+0QtCGv3vO0v9eLltUDH2PsQUxhrx5CS57q6Rge9hNZLdMgysKSxKRpu2Yzea4MdB3PV99/ls2txt++vO/x7Kec3v9BucGfvqzH3H74hrvci5WRGBtgReK28MBU1q0ViiZKJc1u+Coj08Ihy3JjQR3ACEQRGyRB8hKSVzTYSc7A4MDLREuoKsCEsSQkCEgYpYe98OAmvKCXNfTjyPOR3bjgIqBzdUbnm62nJ+cZvvBzWvS5gotF2A75NAijcm4/i6QjKZzjlE5fv3oEVebG9q+Y3n3LkFr9GxO5QeGoclQkRhZzJckbRn8iB6zr8ZaTd8OxJAwRTFtbDOFLgwjDB5RWoTSSCXQhSV5nRsl3nr6JmDJW0omEz7cT5K3vNhHpoD3HhP1JN1LMEm4cwSEn+rP3DDlpinv6aScrB0pe51CiCilsEXeusaQCCF7nHyQ+JihEiEJxjGg4V1o7JScjlAi59pN8Qd6VjA/XrG8OM2h0T5Hqef8tCzBFUZj1ytUaQn9HjAoY+h3DV3jiEHSdx5RzEmMCCPox57h0PIyOM5Pz2m6DIkRMRJCJik6KdFCYKwmeE81y0M7YTTaGKSb0OJKE3TCa8tvn7/i8ZtrWue5eXONVGWGZYRIObPc3NxwXposI5aCYZKzBwQ3twcKpfEpUClBs93/3p7xH3SzhOAdy78sy+kwSBnvqGQOm3UOozWyKDNP32ii9wC4EDDacggdURS5eYpx2lAlhJEoWRCnaZpSGj945GKGHAe6qw1Ja2brFU4U2PO77F+8QmiLOTvHJ4WJZMrWOJB8oGsD2grmR/dR1Zphc4VKAWMq6BvKVZWxuqs5sqwxdoaYe/yk0UdpvFGE2KO8z58BEre9JQzTYd016NmCmAQiSaTRRAGE7OMyOktEpEgQPUPfIIRHT4GDSQqOlgta5yHkBz4RKKzg1dVrwusr5j7iBPgkkS6BhXK9Zuc9d//4H3Py939G40fSYWBsG5T3jIcDynvUrH43eamqGXGizsyqGT5ErvfZ2LdrDiRtkVoxn82p6hmHvsfaAuPh//kv/w2dDwztDikk92aC99dHJA0Hkfjgk08Z6xm7L79BGkM5m9EPDaOKrI7WaCNAK5KxXL+65vT9hwiXuHr6BN91tGXJfDWnShXD5hZdl0ilGN2EKU3g+oGyKOmVRlpNYTX7m1tcO1KXNS4GitrSHQa0UChhcM6BzNj7RTWn7x3zMhJz/iA+RLqh49vvX1LaCqkFl3eOWM8LnrzcUBjNi9ev+fLzbyiT4u79S267Eb9vudkeKBC8um04rdZsx467xyvmZo2KcL1vGFzEjz1zJbHG8ujVLWaRJVTCd5wfLZF9j12XKC14frNDSsN7i5pKwrPNSBoj84WlEAOy9/+bHQH/Ja6UQiYmRYWRkihiBql0DX6zp1ivGXuPiQFBiXMBAxMKFqxSKDyTP5cUJ+O1zNsmn7KPJE7xBd4HUsjeKK01SuQJHhMVSSuD84FhQnBDoq4MfuhBGJQEqRT1LJ9Ns/mcohA0TUtVW+48uMfNZs+yrtjsdvz6118wBs83v/ktzXZLGEaE1MwWK4zNNL16uc40TG2Q2hBEziQ5vzjm7M4ZV98/ZhEcd5Zz5iLRbA6MbccUEoVIkeJoRYqR0DSI03X+Z1WGwURj8doSpcJ5wZAEu87z7Pkrdpsdbd9zc7vh9nrD1etX9P2INgWb/S2H/SZnvKQIfuDq9RXt7sD1kxdQ15OkbMyku5BlfhMEmKAU3z95zNVt3k5LqVkulvz0xz/HzBbIuqK0EmFt9kH5gBAaJxTBFFCURLGjUAKpBV0/Ti/tLIfKEpWEiyPp0FIdr7hYVjx9+g1XzsF2R+MCbXtgHEcCCaEM1eKEJMB6R3fYMQ4Nt2/eEEJis2tIMVLP51zcv8+d4wXHqxW6qNDW4nzOfimrElmDspLNbcvQKwqr6fuREAVS5MBIQqLtRpaLcpLnRazRyAgg2Y1gk8tDQvJkKvhA8IoYElHF3BhpiZqGkzGKdw0TgNEZcDCkiJbg2h4OHa4ZSFIwDB5f1+h5Rd67RBQ6B2uG/H7T4oe7WhrdmOuKaZuQUfS8y+iB/Lduu466yiHnUsl3YchHJyu8D0TnaHZbfv2Lv+a9Dz5EJ8XV88c0my0P3/+QcjUnjT1WGVYXP+aXf/0rtNRYWxCmGkVazeL9ewwvNaMUDC+fMLY9ymjWnzzk9utvcW86dFkQRpebDSWIWhGbAVlXJKsnWIckjh6jNVZrhMu+cFnWxG6XA2BlBkDJFNm+eklIiS8//y263XNURFRoiU2LLKpMK5agC41oHG4caEaPTw1Nu+NWRr794hsupCGVJUFKZNtiEySVvelWCbSAcjlnbDuKwpBipKxKEplwJ60FH7NVI+ZheYohE/JCQBhJkiLDnbTIGyoBKQS8GwljzgdTUjBGn+EjKteHMuXC3SYgRNpuYD6f/S6fbQpk1kq+a5Syp0mipSbEiFE5iwspcS5SGD1hwydLSconmItZppoB/QnvHIehZx48doplMKVGyBxRokwBRpHO1yxOjwm3N5RG0qWELSzaKFSS2PkcM5vRusBu31ClmlFFDoeGQxtp+8Dy6JTGOaRUpCQJPtF1Pd4a2n4koqltyaE7UBV5wC60JClNMhGtBCFFJAozm08+rSyDprAMIfD10xf86a9+zQf373Fx5w7Hy2PeXG9p9jtkPYck2Gx3nM9O80DBO05mc5quZ7dp2PcO8BlcvpzRtH832NTf5fpBN0tvCSNSSHwME/P+d+CGbAKe7NWCnJnh/butUYz5JZ+EYNuP1EZTSJEbJZEzh6SeskiUQiiJLBRaFSg3Z3toCEmwu96Cd/ii5vwf/5/ZXV9Rnp+yf/kasXnDeLgmdgd8ypuvUMzxek43OiSC4ByFkhhVUqyXNLd76qMzMHVe+4aA0EXW2ALBdag0kvBEo3Ia/DCipSD4BmHmJG3xAXTQoHWenqaIUBOVKkZUypp/UtbgCnJ6dwrghUErRe8GZuUMmUakEnS7A3ORdbRBgrUVMknEYsb8w/e56R1HH31IFzOi1pAojMap3MhWdT2ZigV+GPIBXJWIBDfPX1DYgl/82Z+zub4hBk8winpCVZa2YN936MIyPn/OxeUJj7/6LUWAXkSSKSi0wbUtdz79CYv7H9DtPc3uFhkFanHOft8wv3OX9z+8S1HNaLzBCYuuFvjB8d7lBbHZ8mRzhWw79Okx19sbhIDj+YoweqJ3DH2LNZZRSEJKFPOa20ODiYLOOU4vzun9SOEN2lp0OcOHgJEw9InReZIUeJmY6UTnJb1SJFVw8/o1hZbcdAe6cODseMFH5oI/enjB188O9CHyYswBdF8/esbPfvIBZfR88P45f/Hb77D1A2JMvNwMtEPHydEdrm9arl3PoXeopPAucbkw7JsuB3ymSIGksIbVLPDRnRNmRrFv4XaA5Vzy2fGSZuh5sus4X1So6Cnq/Hn/kK8QAtZI5oUmpYALAu8CIGnblrKuKReW5EPO5xg8RiSMmkKtUyBGMkwmTvhmlb1KMaWJjpfou5D9AhKczHI6mTwi5ck7WlBZQz+47DH0eTpqZPaUFUVJcA5bKdYnS4yRCGMYYqJUhuV8xjj2lDYj3589e0EMnsVyiakqVqsjkvOksiYJSbU8wmgLfmRou/z7OccUwcMwOraHDnc4cLxe8N68ZDGr8E0LfoSQIQdKGar1AhE8oe8xswphFVhNtJZUVPggEC5TOIfR8/L6wJPvX/Ef//IXfPHlb/Fh4HA4ZDQ1cGgOLOcrmkPDMLjs3YoeTcnuzRXNbk9SitfPXvDqzRvGqVANIWRBzNvGlcThsKNpD3mwpAzX16/QxZw/uLrl8t4pZbnI/oKyoDTZn2FnFbEfGApNCJ7umwPj7X4aOpG7YWuQZYEk4do+KxMKw8l6ztpKfvv4EYdyRrE6paprBj+w226I3qG04fj8krZvs8doKFiu1thqjpKaajWn2e948eQJ6/VP2DYd1WpGVViaMWdCaaPxPiKVZLWuGUeHCipvGyOgFO2hy/43H+l7R2HkO7m1QuVthNIYo1FaTiTZhA6R4APj4EEojJaEkD1LIqWcifROehpyaOrkr4sx5ZDhboAQ8DH/Od0wUiRwo6eqKorSYhUIqfET3vyHfBmrGcecLxNTDjHN0V2OwuZth3z3c+Fdgz4OI5d3V0TnccOAFJKu6/jmi9+gTcnl+R1e3N4Swtf86LMfEYzm+ffPqI/W3Ll7wa7PaG9BQhKQWrF6/x6vHj8idi3q+BRDRPgByLlcSkq0MbmB8BG9XOG6PcmHTFpTgmgKfDdgFnlTKYXE+YCKnnGzQZgSmbKfMzpHJQUXc8vrZuD29Qv258csqwrtE5SSMHYkJajmS5q+R5eatA3viHHOe1yMjAL84YCpCvr9hqOjNa5vM7grReaLktXJPDdxVqGMZOy7LBHVGrQgSpk3ScaSgieFgBsjdrnMbUec4C4pEjzIOof8IiRqapwQAtcPxJSfnbf5cDJ4ypQHComEEBLnPIlMOlWTfyx6gS7UO5hJRl3mZyYfThk77vyA1hIpFUYrkvA5P01kgItMgSTAjQ4zQX9GEbJfSUmEiO+IzzGBcCMqDlgFTUgko0CL7K8yihQl0mZYzO12z77pKVdHbG4PXN02vH59w8X5HWLwVLZm03RIkTMWu85xK3usHlmuZhw6l6MVpoyo0XuqSfWYlMqNqc5bM58yB0AKwX4Y+OW3j/iLv/kVn37wIR/fvwSfGMYrtJDURcXN7ooteTC12zdAznHC5LDa65stxXzOuN1hpaT3fort+P1cP+hmKYVMVZcyY37ltGX6HeQhG+uyvzo3AxEx6XUTanogpFJ0ITH2jlJJlkWBjp7Qe3SppqlD1sEqrYkxUSyX3KnneDcyHhqG6xua3rN+/wHFrGD0nuHZS3SzoTSabRMpqppo16Q79+mNRg8j7esbFssZLkTqyjKMA9HmCUFwA7JQ7/xXGZMeCW7I+PEgkIBrB1zfIDWosgZVZ1y3UtlU+PavLDWCHASplZ7IRpKx3SBjzLK4ITEEjzleEfsxr6sBmSS2qjHHK/bfPKZ1HTEEdKlI1nLy6UfIoxUX1QJhLYwBKxXeewqhCSlnLBhrQOVchzh6TFkxGE0UildXt4xdx7//9/+eSMRqg9U2U5Wkpe1HzHxO73ruHZ3yp//2P4DzOOeRRrHzA/txhHLGvYcf0ey2dLs9ISqGrsdstpTrNT/9J/8MoRO+d5geNldbVKE4qgzffvkbjmcVh/WSp4+ec/Hx+/ziP/w5Dz+8i3QjKXhePX/JYprK901PoTVtN73kmpakFfPFnG4YkIVFKosQlhiz/+UQAkIaxqFnlIkwetooELqgCY7n19eIkFifnhC84vPHV1hT8em9JXdmkr/9/FuuvvuOZtNgbM2T56+52XbEoaE/7Gg318RwzKtdInjNF9/dMpIoNGwOPbUtSF5QGwM+IqRDqxmRRNMPrBYlVZmnSd/ve161HZWV9N0eayvG4JkZw6wwzJTiJv5wjdkAJIGd6ERWa0gjkAhSUMxrXNcSDJAiui4QMuJdIIbA6AOCiIuJQgvyHA0QmQYmyJKJEDNWSaWcSi9jYlYYylIyKzV9yFPQymZAgZYCJ3JYpzYmexKMQilYnazAaoYUqa0iCIFPZHP3rc/3ndJsb7cEP/Ly2TOq5QopDQ8+/QnaKDZvrrl37z7SGF4+f87gI7pesDw6AiE47HbQdzz++itWVvHgxx9TF5bFrKJ509HvGugHyrpCaYE/HHAu5+ksTtfouiBWFWPKlKqIwBhBHBP71vPk5YZ/+6d/ya9++Ve8efmUcRxyWKE0yCnstD0csqTMuWzkjhFp4bC5IfiReW15dHvD5nZDCH461idJkciUwly8ZzKTkJl0JVWWaL9684ZXN5ckBPN5RV3PkDrLknVREGYevZhRnRyzq2uu/upXhNfXkBKmLkArRIQ4oZj7N6+xi4rju3f48NMDL2+37La3XDd7RDVH6IKUyCHVswX1bMH6+Izx4pIUHKvlnEfffMWrF69Iz8FozdnFXdpDy/sfvMd6NWeM4IKYtgjinRJCCsdsXrI/9MxXcyATEPu2z1IfkUOShylrUEmdA9PTfyKlS1kOZ5UkhkgYI7GKhCAxOm+8C6XwMaFEQsksSwoRvAuEEPJmNk75Y5CHk6UiqQltPeamVpLBEKXW9EObjfY/YBqe1oboHAI/yXmBlAg+Ymwm0QoihbGZwhYiOma6qBsc3z/+nvVyTmmrvHHQgqbtcPsd4zjw4MH79H7kyfePuXvnkuM7F4jkOTs94vGzF+y7ltudZiFnHEmJrkqqB+8Ru4bN8+fMLu4Sm1vGNzf4fYuxJvutyc9a7JsJdGWJKUCbkLZCTlI9HUFGcujrzT5L88dADk/NsQkLazmeW25udwyj43Bzw3j0AVIVFG5AonITEXK+5WAGgtU044CICS0FV9tbsAXd2KDqmlU1IwiJRORGAoFOkWJeMe47ZIDgPL4bSEhsZSmPlhhdoOclUkn89O8IpRFGIWQmPhqdh+ZamQwqMSpvpQWoQuN8QCeDj2BjyrK5CUyiptrSjSF7BEPAh8Q4+nwOGoMYB6TUFCb7+t5NcYgTdj//ObKMXWUaHlOmGYI4BfclmUFlxLy9EzEyeocOkcoWJO8QMYMi9EyR3ADe5/82Cq0Es3mNTzLHOkiJKStcFPz1L3/N3Xv32G53PH/xmqcvX3Nx7wHalkSh8D5kL2P0jOOImS/pxo6o8xnqnKdUgjgFUifymQSC5AJ6URKR72pQqQ1eK/7df/gz/urXn/Pzzz7j4d0LiqKgix1SZwnfrKp43rWIosCYgutdw2y1wMXEm+tbDk1HTILzqqZ3ebMkrWR5NPv9PeO/t6/8X+HyPtNUtDWIqaHQWk1SjIRzbjLcvSXh5Sv7YQWkLCVQShNiohlGep3TpxdSIjHIJLP8IwnkRNlLSuKmF6rVM5JW9NcbFvUCvVhw/vCS4fUb8D3l6ZLusKU6ucAojU8V6vweRWFpvvsepk55fragbXZIK6jtCte0VGV+wKQwhJhIKh+4RiWi6xGiJA4N42GL1honBFoUKGlIQqKsJOFzQrLWoDTRuwllKRBa0uz2iBgxlc0TDpmnKqd3j7l+/Iz+2XMGW1Afn4DRPPzpp3zz6iVqb2hvGnTSVCdnVB8+ZDd4Pv7kPp6Eems+DJHukAMyxUQNiykQAFWWyMUc4RPt4cC2H7h68ZLbzY7RDSipGWJEFyVjEtweGs5P1ux2tzz65sCbp8+I6FysqJRhFYs1D3/8U/aHkYXwhHZHde8hy8tzYllx/rPPqE7W4AP4hD203DZfMnQNf/k//S9snz5jvVqjCkPSgna3Bz9gpeHqy29y9o6WpCo7SP3QYylwTYcfHa9ub3j4kx9PZBtPs29JWIY4gnfoeU2bElEqlDSMXY9H04yRmdHgOpbzBc9eXvFguaLZBYZNx/NNy8mqot1t2Ly5Ztge2Fzd8PFPLrn/3gNebAbe3D5H1Gvado82htve4YNgvB24PJ4xdj3JQ7JwVhqOqoreJwqnJ88NVMpwUpeIELgeAs/bkRACtRLM6pJtMzL2HcdVNf15HT78cIscACOmXDahs6zO6HeJ7s0wUCxmIAUqSSR57VIVBqMEg8uYcYlGiYSUGYecpWB5wp+zUCbwTFacggclIsnF7GGoLGYyuwcf+U+DOlLM+RXK6glLG3AeqqogkQu1lCKHMaCsZbFeUZQWYw2HzQ1d29K1Q9bPS8Uf/qN/yOH4nPl8xs1mg6nmKH3ADT2b7ZbZbE7obnm9vWU83PKzh++zmlUsz45wuz3+0FKXJUEqwtARtgPDOFAUFYuH9ykvzomzOaKs0HWF1JoxQjt4IoLbTcPVzZ7toeX29pp+7CZ/10COdM4wjOFtknz0U7MUcN4SvcMWhm7ncb0jxEBKgWy5FKRJu/82iyelHEopMUQVKeoFJ8dn3F5d8eVXj0iffoCuKtIQYcxmbSEScRxRJLQyzH/0CdXlJd3T5xweP2XY7ggh4J0nODfFVSj2r6+ZFSUnJ2tOVnO+e31FF0aGww1FnRvR0Q2Eg8MTWayO8+ahKnn+7AnN9pboHNZa6sUCW1hOzo+o6oLDEDAhwxukUBkaMmWpuSio6wIf0/TuC3kIYDVucLkZIk0KgpSH3CHfO28HBcTIojSMbWQUEx4ciSIj8a3O5K+Q8tcotYIk6cNInDJ8hM7+iCSgT2DrCrRCpWyqFyJlJLISeSDgJ3+HD6i3mr4f4JXIUjwhBKYowEnG3r2LLnHeUVclPmbplLIlSUj6YYSUqJRCCoVzjuA9w9gx9gMoxe32htV2yfkHH/Hm+gplDffee4+yLNhtdvz4R5+wmpeMPhIQCJXlUOsff4roevbPX7B9+YLl/fukdoMyCmN1Zh6IfP+k0aGP75Cuv4EUkbMabYrsW4uR9XqFlJLxkKl/Kea8rrfPgNVqggwMzCvNy+2BXbMj9j1yfQqHAIeBYl4zSkUSAmVyzo5QmgBUVcnrq2v8y+fMZjOcKfiHP/k5su8RUjC6iCnyFjT5QLUoCc3I4DqE0Qz7Htf1rC7PUHVNuZ6TQsi1URrQ1kyQikytCyG+a2BSSvmsFiDzFB2l4dB0CJHQWhCFQCaBKXOGYY6dyWhwKTJxMoaINpoQHFVhcaMjRYmxk58VCCnL6iJZlm20oh8DSZhpCyUYxh6pNcFHlM4DOCkEeIcbHVYLhCqQOuH2HhE92mq0gDE4gp+URuS/j61LhEuU85qEQFUVQwgUZY0sar55/JzHz15ydnrGrCwxhSGEyBg8UUtclOgI3o3ErmPfDAjRUyiDcx1BJapZDa5FFwU+HShms8k7GhFFgUqR3jn+7Je/4sunT7k4XXOymGG1Zb9rcd2AUZl2ent9g9aGqppnavPQMqbItmmRXU87Oqwp6ad7IyIYhpEY6t/bM/6DbpaUnjYnKm9fhBTvjHlvX5RSTod3jEQhUEIRRSS6ESnBp5zz0A0DIQmGINgNnj6MHBeGQuSHIa+4s55bCYEqc/p1EFAuZ3TrmtXpKfOjNXGmcS88s/UMsVAs75zRTWF0dbHCG0O/3SKkZPbeHdYXp0gcMQyY5REoS7Uuca6jMEtAYqSa9KwRvEP4RAw7ZJq0z2KgNAsiGmk0GEOaqEtGZVyjNoIk84RWJEGz74mtY75aZ5/GtDWTg2O42fDqV59ztFjhakhHU2jiomJ5ccLu++9xPjAWkOqS+eVd/M2GpDKBKohEZFoZx2xGVgJ83+MFBK05Oj3Ca0232fM//t//JcuTI75+9B1912fajZBoo3n/vfdYLI9IZc1Nu+HO8Zq/+tN/h0jZTG8EnFczJJr1Rz9BH59hXrxADAfmRnFx/z1ujeb84/cpViukMCShMTqRysjpnXN23z7jzdffsywEx7OS3oOva26++pr//r/7Y4pixs3VG+zxERsjObp/Hzd6huCRXSbEbLZb1sfHhBBpuo4kJDc3G65u91SLJe+dX3AbIlEKnAvIJFlXc767uiXYmhgid2ZzUj3ne27opcElj61rvn9xw92Z4Lsn33Lv8oxvX+35+U9PGUTipuvwJKQuENUSU3qum4E0GR9PS8Un50t+8ZtbTLnAJs9n5ys61xMxeeJD9moc1wUzpemHwOs20Qa4rEserGcU5KL/7tEaQ2Q1K7i6OmDMDxvwoNS0gVAJFyJaSVaLmuuX11ztDxwdramWcwghk4FKg1JZMmF1NvUWKmfOGJMn9D7koltLkWl6Kae2K0SWHhkBo8PWJau6oHc+TzaFyLQqJTEmG7ZtbZktLG99ODElrMy5HtZqlEqMMXugRhewVcn5vUt224bZfMb169ccDtngfXv1ir/+q7/EjQPVbMk4jPRtR0oJpS0qCbY3r+l3t8jgOZnXPLw8p9YC+gEVIlYqXPLEvmM8HAh9T316wuzyDov37zJ/eB97cpRlGDL/0DGAjIxBIrTmxZtr8LBYHNHsNyhd4N1ASmEqXCJC5DwYIfLZG1IewLTDSLc9EL3PZvrJIwCBGH+HoX77Hkgpb1OydyFSljWz2tLcbvg2fsd8vUJoiy4rnMtf0yqJJiIJmBSYWU1dFlQfv0/94C7DzS2Hp88Zr24Yu57YdDRNgz4kQt+zOlrz8KMPeHq9pX9zRT+MdPGWen1CaeYoJWl3O/a3N4SxRxqFHzqkSMzXR8zmNRf3Ljk5OeH09AhdmBzoSsJagQsRHybflErEHpLIA41xHDOxTkBZWmTKBZlWOZPL+5jR0SJ7jwptcoEsFXEYwLlccE/Nf84ey82NhvweVYKyMIQoEJOhXVtFDDm7TxmNqcpMJKwt/s2GbnvgtLxEypR9xFLgXYap4APiBxzXFr3LYfVFRfAjIiW0LtBa4YYemaYKQkJZ1wgh6NqO4D3L5RwkDGPOxxvHEedy4b2o54xioNlv+fKbL1iv13zx3bfs2oaf/exnlLMqAzl0wX5/zelylrcKURJFoH74kPmLV6TvH+G7kcUHnxE9iN0GhEJqjbGKwiwZeof3DhCkYYS+xxZllu72A1aI7MvqWpIy0HdZ2p9y+PCsKqitAu/Ytwdev3nN8OAOOg4oIwn9iC5LbFnih5YUBVhLEpKyLLlpD9n8rxXL1YohSfqba7y2E30xYkJEWU29muHbgWEajANT4zYyjCP12Qk+BMrlgnG7x9Q1ojAkBD6Qc4pCHih4n6VzagpUlUogtcqWh5BzlFzXoYoMhDBGYrTMAJX0lngHaqJFipTyJgkxAXim6IEY8/Zp8k9BnHDcb4dDI0nILDWTBuc9MuUNni7eDtwCRgiMzO+U7D/Nsjplszc9hUgKDiXz2Vkuasa2o6xLpLUURYWyhqZtOV2vePbiNd+/eIFWios7l0htGZxDKZtrnDGiFOx3t9T1EUMI7PuB5SKhRaIdArbWGUsOJB9QpsSNHltoJCp7+Izi868e8cvPv6SQBYv5/N0GTSQoy4J26DjsdvjgWSwWtEOHCxEL+CgZXcBN+XII8Aiiz1LQqrCMQ/+feTr/y1w/6GbJWJt1oFJhigIXXNYJx/9E+zwNvXPi9JTFJN+SS+IUyJdvcJETJjn0Azp5qtJilcSkXPQIKabHQmRtfYzE0SELzZ3PPsSJhKnrjIiOkSjBzpYEU2DUgiQCQitsCAxDx/LOKaoQSJ2I+w49m1EvV4gQ8OOBopjjfcbYChkJ0ROTwyRPTB6tJJuXjzG6xC6OiKrIckOlsSbroeX0OQlT4F0mAkol6buWcGiZLxaoMuvQfTdAP9Bc30Js6IYNsd+xvH+KwGdEbWGYn51g6xq56UhHaz74p3/EkCL3PnxIpkQkFNn8bFYLqqpg0/VI74j9CErC1JiNXU/TtvzJn/zPjG5k7BrGOE2XCdw7O+P/+i/+e37xy9/QAEPTcP3kNa53WG2oVGBdlvzBx5/w0aefsb5zj82L55h2x+2b19y79z6vX75i/tmPkWWNVHmillLOw1HWcHp6zi8OBz768Wek29e0fU86vcT7kUrB/ffeIwZoDoqvvv6aT/7oHyEDXL96w/xkSfPiNVdXN5zfvUvUiuAi3b5l1+aJedMfOD2/xKdE348Mo0cgkUYRlcLWBX3vUHWF0pLBDfnedpF5ZTgMI+9dHjFGENWKvchBl/cvjun1ir9+fotLgeM7d+muNwQ0Vzc7Lu+cYXzkv/vx+2wPGzaHPYtqzqdnR6yNYj/AtsuYVGskow9omRhTYBckjXMoJTipJUdaYGKiVHBiFAKB71uQUBr1X/fB/y98SaUmuUae9wkJ2ipOz07Y3OyYHS/RswqjBaVVVIv5hGMWFFbS9AEkU06TorCSOAZUVMg4actDxowHASblYtVqhSBwcVTRDo4gJL0P2FLT+YixOk9tjUYKwawqaLoWLQRFIVFWoFSWOIxjZF4oVGGITlCUJfcuz7m6vuL1i+e4oWMcPVoZdtsN3WGPvt2gbYXRhqqe0zYH+u0twfXIFKkUnJQlS1tSlgVKSJp9Q+w7Qjcydi1JJhZ3z7CzBdX5CcuPPsCcHNGGSD94fHQkoUAklLEMg+fx8yu6rmccGu7df8DV65eMQzt5v3wO1SYiRCSi8qYH8ssxxezfmlV4N+T1SI55fXfW879qlNK0WRIksnTZDz3NvuWwvyW+fM6rzQ1nlw+YHZ1RlhVjPxDGjsJIjldzLtYzjhcly0JSp0BlLXK9YlEYurpE3m7xr6+xMXvXdq/eUElJWWoqq1hWFcFpbsaOdrfFzhYIURD8iNIGUVa4sSMEz2w55/LeJVIp7t+7pJgAOFYrhFa/U1Co3A7KkIdSVSEZXc6vqmuLGwPj6LGFwUzEL6PKPE33ebtR1xYtJXUhpjMp4pxHC0H0DoPFyHxWSjKiOSHeESBJKecNxoiLkpnRJJlYLmqS89iJSKvnFXtgKSSz5YyiUPn3yiquTFxTIhNhf6CXkJLVYpUhDk1AFwrGEWRuLo22xAjKGmLMn5kPHiUSxmgikXbsmM8WRJEY3EgUMLiRk9UcN47stiNEj9KW7188o7CWD99/H21KhsEzq2qK2RzvHTpZhEjYu6ec/f2/hy0U8uiYoBSrP/iHhO+/Id68hrrAKgE+ENsGJRVjP6LfhdsLFBItJNF5xkODzSmtxJBx0IFEXRjKQtN3HVpLtFRYBWNzwzIt0FLgrcWHhPIOXWioK9QM6sWcNDiCG6mlwCjJ2cUFVzd7BIlh6LGTfcKUNocYx4i0miRAFpY0ZgVEd2g4vLlmfnLM6r1LTFUQQiD0jqEbUTORA8hDmGSSKec+aY2dZ296jNl3JpXi+HhFt29wCJQUqJnFGINQeeua1QICITIEpbSGECPOJ8Yxb8BjjISQkELl/E4hGMbsb4rzTIREKkYfafsMOxEKnIt5a5WpW5RWMx4iSkRUSojgc1Nncmh5GHtkTIShz/fYmAmi4zBSzGYkqVBFgaoqhNQUGpzrefLkKVVdsV4dEWKkawfc0LM4mSGtyXJHmd+R2khcyJmdcRwJlSaKhDYFKSRkSiQpiJN8z6WJPKgUX373mH//17+gMhUffXzJq+tbxmbEriVFWdCNHUM3YJWmMAXbqyucALNYkZygiSl/H4xBKEUXAuuyYtwfaIaeRWlpmuH39oz/oJsloTWmmMJip0DJt/KLMJF9Ykp4l+VgwXtESMRsKsja0JRfx0rAEB1h9CTAzmoaH2HwLApLnKDbGtAyGx0hh/t5mTC6wGqFF4neB+SsgtWKMD+iqiqa2y1VUbG7vaYuCs7u3sc3DcPNNfOjCqclppghU+Lw/BlJjnDxHnI+n5qekRg9UiRkGhn9mOlqzmSK1UriXI+wM4TRWYObBE0zUFaLTNMjodD5RbrtMNqiZ2U2EvqEGgKHm00+NIMjjC1mpokqZIxyzAeNWSw4fvCA69uW+s4Flz/+BFNa7LwGnT9LlQSjTwQBzWYLE75dCsF+s2W1XjIOjuATX3z1Jfv9hqsXr/DR4QjIlHXtP/rkU06P1ujCsN/u2HcdzTgQokcSubOo+cNPf8KDjz/m4vIOchx4/fXX2NgThkAsdxxf3Gd9dspqfZRzAFKcAuMEMQi2Q8fFjx8ixj0vb15x9MFHnH32E7777S+5f/8u4+2O9eU5V29e8/7DDyhQPP3mO+o7p9xeXfPi6TPW5+c4IXCDww0btilSLlacnp1zbDRvbm6QRX5ZBB9BKcYEvXMUZUmNgxSIQuBC4Pj4mEIKZqtFNmMeejbbA9dtgrBnVsLtzZbPb3ZcDz1//ycfZkT42DISCYOD4LizXCOiZ38YUWXBsgj89O4RjRtpR9j1I7OyAiVwbmT0ATcKDsEgo2NdKj48mVNpiUZwOqvyvF1ogmtZlmVG2P+ALztpzoXI0jsJWKtYLEtWRytWJ0sWU2E5m+XssarUMBV8IYpJPpFBKVJnn2CWnYIQCZKksoowOuykmS+0IkzNkSwV+yESXESRJupYLvtlDFRFpr4VSiGVILpIWQmk8HnLZSRGTkMcYairkgd/8CnefUhdVfzt3/wtN2/e0LZb+rGjnC2ZzRaMPncYu801wY0YrSmlxnUORaTSeWMfyBj0JAWjGxmaFsbAbL2kPj5m/v59Vj/6GH205rr1PH2953rX5m11gqIuKcuSrh/5m998xd/85X/gZDlHKYXW2SMVks+G03dXQMrc8KgpUE8IiSks5WJOc2goigJrDPSQjUrwtnFKk9jl3c+nRBSBYey42bzm6feP2Oy3CKVRtuTkzkN+9g/+WQ5+HXMocYoN3aHh1go+vnfC6u45xmbUu/AWO6sJ7UAxm3PY7OlGR72YI1KkLCz1Yoa/2VBozbo8pvWecRzwwUGK9O2ORKAoLIvVOUfrJRd3zvnZTz7h/nv3eLE9UNf1u+wR7xMuglEJLfMQ0KjcEMYx4X3CltnQ7caYc4yUxNjsE621xr2VesZEYbNqojQKPYXkEhJWS6yEFFIutEWa8r3yuZxDUHNQs/MJIfL2TYrIvLaItCCsV9mLpiRHZ8dsO0dRWAprftfMhlxsVtWUefUDverZEbP5gv32DcaWOWsmbIjBU5YzUsjk2sIUmdzoPFoq6iIX57Yo6A4tbfcmb/kQ2KJApcDQt/iYiEmwa/ZYa5nNVry4vsanxNnxOdENfPTwAVJOG9ihQ9eSRE9xccTcf0SIgs3Ll9j5kvP/9p+z+Y9/jpAue/iCpDw9Y7zZEpueOOHylY+EEFBa55oqRnzKFF1Z11DlzbEU5AZqsj2IBKU2+L6lOirxnQMBoe8RpUBEQWpbjCmoqprObZiXFq0FRmlsUWKqgZACLkSiy/XL0A2YqiAyYbZdmORteVPkfeDq2ydUiwXVeo2QCjWr6bttxoRP8rs8TveMvYMAujAE50nR5e39ZO0QU5iSUirDvrRG6Lw9FWRJas7tfEtiBnzG6Iu3mU8i1xlJTBtzqRBKoaxFqgxkCWOk7R2HxtEO2eEmJ6qiVIK+G5hVGmUkFkXoO4zJZD3pPYd9iy4EaZ+BPC55tJWgJLoo8WIguUhZF9mSIgVBCX7z7SPqxRFSwdHFXWISRD/io6AfBqLMcRXD4AhTcHXynrEfGUNCe0+UMAbPvLCEPoMdZPLTeZ7BDn/7my/48utv+fDBXY4Wc9QYaIoCmSJu7BFS0fcjSQhsYfFdxzD2eK2RIWJVgTCK1nu2bVbtbHZ7VvMeZQrGrqMbPbPa/N6e8R92s6QkUUhiTKRhwFqT8w28J/o8OUgx4r1DvB0+xkAUmUYzIayI0xQsFZrWxSl7SBNI7PoRayuCC1gtUVrnoFUtgYhQ2XTonGddrQhJIKVGrtaIwiCKOW5oqddzupsNJiakh/12R2ES1fGMUQSKo2N0MrSvX+H3t5TzGSJMOlVyYrNW+X+PTYMOgqZrAUtRaYKIeVvh85ZMpkR/6DLQQeSsk6ytD6R2IPQj83tHDERkkiQn2G97QjIgC7SVnN99n2aEtZ6Bl0Q/ZMlfEoiy5ujHHzH78UcctjtO5uckBciEEApiwqfA4XaDGh39fpflTt4zOIctCra3W+xyzf/n//2vGA8Nzg8M5KmFzt5GDjc7vvnN5xAjTdPSDwOD90Q8x+WC95ZrTs/PUWgWdcmrL79Ei8irqw1FsWa367h79w71+RqsRMQ0SXsEg4sMnWPz+BWP/92f0z35jrOPP+bDP/pv+foXf80qaugDeqb58rtHnJ9fEhPs39xy07c0Q4eRisqWdM7Rdx2HQ8PZnUuOV0c4bWmGEULkza6hPnbsOo81Mw4+0Iz53ur6LUZl83elCwpVYBdz5kXBcq5wQ8QeL3nyJvHq0HFeQV2VPH/Rc/3mwPxszYOLNb/6+jtWpaQ4OqZxERE92y7y/DBwaOF4tuSn50tq6Xi9Hdh0EWMUpSlwyeFDAARGVfT7PUel5qenCx7MalQEKXNRNRuh85GyKJkFuG1/f9kG/zUuIUGnhFYQRNaiq6nZmZWWyuosvZsM7bVRlCYXJWoyt2Zzb+RokfGoAoWWeRIWSWBg7KbA2gS20NQLS9uOIAWjy/lDafpRa4knN26lkSiZtf3RjxRlzleSQkyZtYLCyN/FAoiR9ckKIyLH6zkff/Q+VWHZbjf85tdf5m1ACPR9RwyJ3vUkoNAFSivCEFFEVrMVs3qe0efOc9h1HK5uaZ+/YVaXnH32IfXxEceffgCrBaPSbPYdj55v+f7ljsOhJersoVJuoHu54+njx/zqL/6UZ9/9lv1yxfnpHUR0QMh+GpHeknbJBVDMXisydCCmSDWfIaVEFYb5csGqqni+u82NkZA5+0Rk6VjeKEVgIldF6IeeL774DV23ZxgaSFnS0e43hHHk/R/9IZf37nPz5iW4nsW84O75KRd3zgmqRJYGNTpCSlRnpznQ++qGRV3hgM3NjkU1QwjJyWLBajHnanAIFErqnI/lRlzKwcVVXXNydsJ8OWe9XHLvzjmXl2dEJajKgnllSUpCFDkLT+bi0EeBkBqkR5IR1FWlUCqhgarSxBjpmgGZoDA5A0WL/I4g5NyvyiiMEvnzNwZLzoKLZLO781mip5REIKZNct4yjT57Vwbn8FFRaUVBwnmDi5BUyRhCbopV3qYqmc3tSk6Y5ElK+QO2LGHLgkNzQJoZKuVMNWVLVIqYomDsWpScSIQxZXkiaSINWra7A23XE3ykKHS+592A1Io4RFaLJaSIqSoKa4nJc7PfsLm9wY8js6rk+esrZnVFOfj8PS40thCECsr3Lrj58nH2SxlJOllx/sd/TP/ka9LhJcIs6NssY9OFxvU90lggP39KaQY34kaF1RmJHb3DHzINLfmAHxzjGDBVRZKb7MFJuZFyw5B9b0WB1gI3Dkg8ySVsYXBKcrJa5IK4HdFCwuCYna3wu46222OlzFLjrie4gABUZUmDx/UZ8NL3Dhs9+5evKBYz1u/dpTheY6qSWOTQ8NBnmWoUMgevjgND21MPFdpMCqK3Z5CQ2LokRVClRer/5Cad5HNZb5TtGUmprFhR09kTBUm89VICSeNcZBgzITWErBDSVmOCQDuBHEe6vicFGJ3HKs2itrm5qioYB6S2GSK0b/Ig3I3EziPSiO8HvO/y9yTkTQ8pUM1K1KRucAm+efaSbbPnztEpQhm0MYxe4UXEK8O2GQgmMQ4uA6nGHfVs2uQpSTeMOQg5QJI6v6N8QEw2g6QVvff8x7/+G17cXPOjjx9wul7Q7A50vSO5kCmD60g79Nk3bAzNocGN47tIGZEii+WSQqR8BknF4viUrQts24aLo2Nc3xIEqOL/aJb+s5fzI7PVinb0KCGzVyYGQop0w4ASCkWWHMQYEGSgQyJBjCiyxKAsDVVKNPsOH1xGOsf8MMooaJ3DCkHXD6SZwBqJjDGvlr1HS4NQejLMVdRKEZRA1xXRR/px0gIXGn894rcN4nDgNg2cv39OUVY0+x65f8PuxXcsrKa7SQh9wMyWeJFASVR26yHMgnZ7RexyQrsbG4pUEfYdfTighj2L80tC8uj5ijAVEEpIXNvx5vFzTh/cBasQcSD2A353YNi+yT4LkYgyYVcrRJk3CXJCv0oSXgT0rOb8zgV+tkAEsGVFkGIqVDIkInY9/eYaPTjifkuSsN83rM8uiSGyub0lHhpub69om12miEUBKRIkQOSwb3ny9DmbccRHuN3esCxLpFAc1QXHJ6fM5jWzes7V48csyoqnTcshQjsOLMwx8/NzVFkAKadh+8juds/Tv/2KV199S//iOdoFPvjxzxFHK37xb/81y5hYLleU1nK13bK6OKVYLnh9s8GNLdIarIMoPF30qNpydLTmwfv3kUYRlOZ2hGb0PHt+y9PbDlfvmVVzwDFEOIwjOkoiir5xFHXN45evOTo+5dXultEImus9H59fsm1H/tUvX5OkZDGricnz3fMneD2jnM0JvSO1Dd3tEx588B63hz2uH7h/fsxxUfA67Li/rvjkZEXrRm4HhyP78VQKjC4yjAGEoO8HrFVclIrPThaoNGCEZVEommFgUdWkXUtAEFPAih+2DC/FPAUMaUKTkgNWZ6VluZzl7QgZEWvlVOzJ7D/ySlAamTe+BJTML1ApwuSjzA1AiJnGhhJordBC4H1Glnv5O7NxjtqLGLLkL2g5kaqzPFAoRYi8g9IorQghYaXEaIHVkIKiLgqGrqcbHUdHGR7TtAcuzo+52ezZbTc021uUrtG2wBQVhIgPEVvNWCyWHC3mWGswAvqu4fW3T9g+fcq9y0vu/8FPWd07pzo5wiwXiKqgKgrCoUcKGPqe3uVNUT86qtIy+MCjb7/h0W/+I93+Ne3+msP+ht3+Bud9BjMgp+3SpKkTQBJEkf9/jHB8dp7FeS7kgn1wSCQxTdjm3+nxYGqXgCm7JNK1e3oh8X6cvAMZX+yHhts3Lzg6ew+E4Or594y7K8Dz/PwiT1qF5dP3LzgpNDIqkrIUyyXlxQlt18O+YWg7TNfRxcAwjiwWC3zhcN2IDgkfMjrcFiVDd2B9vOLhRw/p24YQPE3X4xEYZbGlwgtFrbN5WxWa3idAImXC+ezXyvleMXspkkBKSWlzsGRVGZSSzEtDdBE5vQtkjIxdQM+rTAsTGXUcpu2cUIp3kkby2a7kNO0WkhQC80JNM/WCymTIiTCJqrSE3kNMWKsp6sT6ZE1VFYgpxiKGiQ2W8o/wA0aHv/XT6XJJGvvspS1nRDcglUVqjxQCF0Gp7HlxY4tUktF5um6gaftMWROCuixys+kiq/mMputZzGvqqsYHcqHsR5St+ObpE05Xa+pqBkbRj46iLgGBdzlTLamEKjJNU88rXLPH25LVJz/l8OWA9B0mjIQYScZMXhgBQhLGHC/y5NF3VB99QJrkXcwWUNfE6+tcX0kyEVBajKmIuqCwkqFpSKMnimmIgcjnp7GE247CFujVitAdsPMCXTqs0dM5CdIonMx5Ti2RfoiM/YjSGr2Y40UDg8nRLgIG59g+f0VRlZiiyL5JRM4e0wYhVVaAeM/oPLNZmQPAXW70pJZT+KzI4BMhUHVW4AgyHCw/c3K6lwVSa1LI+Xz9MOBdYDarEBqYADNpGsoIKVAG4rsstLxljbz1+ylUsEgjObQ7XNchYqSQEekhucQ8RbRSzO/f5/rRd3TPnlPO8mYuRp9NDCH7qdqmo04JqVUGc2jNbdPw/M01d84vuXdxyss3eyKKal6zHyLO5TBehSCI3PA5P9B2DYkMMemCpxKSICVCJJLLPnMfHC5AHzx/8dvf0IwtP//px6wWM66uNjx/dsXpek1MeXvmQ0CovFEcdwfC6EhqkgyWJcuTc9r9LcV8hjaW5fEJR8cr2u2GoesZQkCXJR7/lkX5e7l+0M2SkgqXIs0w4hyUZsY7V5GQuNGTFO8IKN7HiX8fsg576lIBrNaMzqGLkoRkCAnhEzIF7BgRRmUKic1p61JkGY01uQgPMTdFuihzunWIVFXN2A0UZQVakIYDRgvePHnBxf0LVicXSJVw+4FSSvpxYDGbk9CEYcC3W9qriJrXOQTOWFAWLxMpGfAjUnnMbElwAt92iNAR+z3drCZoS12onEuY12oMTcfxe5eUJ2ui84RuILmR9nZHu71lvqpRRQG2YH73jGQybjP0PmtwpaBcLOCzJV0SSFOwuneeq8eY19GRhEiR3cvX0PY0b27oXr1AJRiqgrNFxf76mvX5Caaq+YM/+Ht88be/zuG5w5CpM5Nv8qtnj2lcgzUV1+3I9rDn7vkZ7CpmRrJaH7HZ3rCs57z+6guWd+6y6yP1vQcUywV3P/mA+fkJ1paMzvP65Uue//orrr95TP/qNUIETk7WSLHg1fMXrJXgR/fusX1zRRMc15sbzt5/SJSaJy+eQ2FZnK4Yg6OLDavFkpOjM5K0BCnyhEUX2cjvGx5dN3yzB7E+56bxtKLjbD7HO8++dazmhs3+QBwl292Gi9WM+/fvIqxn6DraQfDJe2f85ruXzM2ci2XN3MKf/NkvsWXN0eoOy6Lg86++p5KRUNfMq5KbzRVWa/7wvXv4YY8sBZ9cHFMIuHKJLuaS0uoyyzhTpHMj1WJGjIFaJf7e5TkrI/FeUMh8mNW14na3p7KaQYCbDuEf8pVCIKQsa9KCCeGaG8HVao4xOgcYxyxPeovyN1phAiyrwOgEShiMypEFFJKxjZPXcSoGY0QbhfcJpKbpBoqymFLcJUPT4UePEvn3qo3Bp0jvMywiYw5EpniGhLZqCr4UOB/RRpIS3DRDlkqVBXWl2W4O3N5uiKPn7v27/OSnC77+9gmf//ZL+rbDDQM+RPTkddT1nHpW0fcDB99zfXVDu9lw+/1TLs/Pp8lzmyUuxiK1RlrLECK3Nzu+/uIR3377lO2hJSrD6vIu9z58yHoxQ5lcJKYYGIeWN68P2VOU0ruz+53/KNsU3qG+pcjN7NX1DdF7dGGRRpOEnGQxKhcuUhGCe/c13356QuSixA3du81VFpWlvF6UhtPL9/jRz36eQ6yN4c1zxbNHX3B7/ZLb1y+RgNL/mN28ZN51VHiQiaAtQWfPxvWb13x39YYwn/PidkMwBYdmx+Z2gyxnSG0Zx45qPqdczHjw8AE/+8nHAAzDwHq1AplhIX2EfgxIHfJmxmiqQuFC9uDGTEln9FOYukyolMNQBRGrJVEotJy8D1EgUyKMDpdCLkR9IIz5HhRa4ABjskrDRSi0pNCZjhdTvg+VEEQpKN+Z4fO9rpXKFFQiSuZf41PEGM1sXiFFltpJJJIMR1GJrA754fZKeC+QxYqYBKpaoFJgf/UM70dKqbD1gjj0KCupypKhaxHSkJA0fTb2V3XNOIy5fvCBqqo4PztlVuWaIobA1c0GU5Zokz2Tbuhouh6rFS9vbnj6/AUP796hb5n8KQXeDxmCoAVmPkNXC6KP2LlmMwyo0weIYUPovsNWFf2+wWoDSRLHiC4kcYh89/gpD++/T/HWy7Q8hvRtVmuQtydj26JMRTEvKAuNUQLf5i2JizA/XuG7jqQUQkWsgTRGxBSlgEzMq5JSK3SKmBBIMqKBQmq0kCQyAn/sHL4fqQvN0A14oQjW0o8e04/sXl9Tnpwwv3ORvVXdSL85oOuSlDJs423sg0HQtwPVMjdOyihSnM4ckUcG19uBWV2ymAm60TO6yHpuM81xkrbFkKirkkE4lFJMo3kEWZUgRESmPOTWIktQlcw0wBgzBVWpTKBs24Ew5HM8CoEpLMiA15axa5nPa7rtgZvvntC/fMnR6Zx6NSNOEJeEYAgj+9ZTLmeUk38rWsvm9StOljOCqZCDY1ZYjJJ4IUjB47oBipKhH3DDSIwhb3t8IDhH3zSUyzWBTJL107mSYiQJxU3T8zePvuG7l0+YFzW31zsef/OMJPOQJo4e348UKhMgTaHZtwN9N4AAaS06JYZhpNltiX2LPTtHWYuafs3Y9dTaMA4DWkq27UBZlb+3Z/wH3Swx6aZdzOGNIU7pwBGi94xTzo2Yigshsrcgh9fmF3Catk3OZ3OukhoibHc7jlfr6UZJdH0OHRzGESlLlJBZ7y8Tkpz8rm2Z9akxYq3ND4eW9N6hvMd3e6yRnNw5wZxWRGDYNmivePzXf0mlOur7d1idP0DfbgiuQXiPDj6bKbXBdy3aRcZNi4oetTBEVeIPLXLoGMcdupzhbm+gmmFOzrJ8JUSGzR43dhSLAu86gne4saMUEmk0y8v3qOdzfPSZGleMbG72aCwujln2EyJyMaeczWhf31Av51RHs6yBTxExSdy63Zb+6gZDhBBYHR3TvHrJ+v4dpIL+esdsPgMi/+L/8i/4d//mT/j+1Usm0ioiZtPvi+01Qxo5Xhxzdv8hX3z3G6TW1LMaKwzF6ohqVRM1BCkZ5ks++x/+Bz748WdsNxuuDzseffmYX/7JX9HcbnLo6OsbXPLMljXSdbz+9isWRcm9u3c59B2vX7xh13Ss7l5wfnHO7W5Hc+s5Ojvl/N4lZWnpY8axa5uLJCI0/Z51qTlsO/beU81rtJ0RpWOtyebVSPZ/CEOMBUMyRFUhikStCurFnO+fP2W+KEDVXB12/M9fPkYPkX/44RnVvObXX3/HCye5eP8er5+/4oXT3Ls45eb5cz798Y8RKfs0zk5OWBaa2wFOrODBUcWu3bPr8wQxG7FzUHI/5GBDQqDUktNCcW9eUJnE4AV1aXPYZHA5S4XEEBPdONAN7n/DQ+D//yslQc6+ixk/LWW+nwHEFGo9FaBp8hJJmUEyRpKx3jIiBGitGXoHUbzbKCEkQkei1xA8hc2RAEophsHhgbb3dK1jGDxaCezM4GMe6BidC+GYcuaGUhBSxvZqpfEJKqModJ5KS21wzk8hjYo7d86w6udZvUVge7vj+uqW/+af/hO++/57nj76HqkUbuwJbsCWFTe7PeNuQ6OgPWzRbuTj83NECAzDSO8Tw2aPshaTEml0XLc9f/GXv+Yv/vIXPPvuO0IMzE/vsrxzJ+etGc3p8SnKVIzdJlM5Sb9DfP/uG/JOtiJEIsaQC/WpmZLWMjs7wsxLqqdPsYWd/GbZdJ3ewnpEnui++3rv8sB+t3maGKdIWXB88T6z+Ypvfv1XdH2D6zu01BydXLC5gZcvn/G//Mm/wRrNxx9+xDyMpO+/57jUlDNLP4w8ffGc7b5h0Jqvvv+eTmqq5YoQfIY4eIepFiht6Q5b7t67y8effIiQcH56zPp4jZSgrSEoQxcHXMobCTlpQ8cpH0lOG0nv0/TuyiHIQgqsUmgpmdeWrh2orMYIQdsGosuZLeMYUDHRdw5jsvl88Bk3LpXM8h0h0CqrNt5+arZQmbKlFTqCEirfa+Jt45mHXUoJUiCHYAow2iIyGysb1MmT6CFkj8vvmuUf4CU1qlqhk8fYkt3NM9puT1FUWeJUVAzeUxlLJFLUNckbQnQMbsjnREoZEFNYlJJZwpXAxbyVGFxPEII4OJJPGGvwIXB2coqW2XdZ1iURB2Y+rRtTRnqnhK4KoovYMmcIhSAY2o6yXiDmNVVM3Dx6wni7pTSGKBRSqbxRDYrOjZkKd7TEbTvC1CBLkwEkQ9uzKBek6GH0zGRCjR5RCvrW5XwjNyJ0IrqAVgbXDxg7IwwgpYIUKXRBMa9RKmfuoBUssux4sV4wXy4wUuCEIGlDEwKj0IzS00oLF0f46xd02z37N1fMLu+gq4roU/byZq4cQ0goo7HW5IFWDHiXNzYpRIRQyOlc8TGy6xxIRVVIpJAYrVBvoV/TfwjyOWOMend/x2lTK6cnKIbIm1fXnB4vwGR8jfc5bkUJSXIjhdEMMhD9yLD3OA2Xp2v60SG9Y312gm8bXv72C149e4n2HenKYRc1yWqIAsdIcoGyLEjKIK0h9Yld0+TPOQTuf3TJZtvQR4U2mnbIkLSQRtIo0LagcS0ypjyEinkLJNU0GHGeEMWESM9bryiylcJqQ9t2VOWc221LcIlSReZ1gTTQjT1CG8ZuQEmFHwLaFAilGJoG5x1lPUOkkAmK40ihJO1+R2lPESRMUb6z2pgkUP/HZuk/fwmpCIAuCvQUhDWOLrPuZQ5LDSEgUn6JOu/f3dhKm6mTF8SY0eF1VRBERGnNYBUSz6y2pOgprabQlqHvkVJnbO+U9Fxoja1KbFngY75RJJJxylBQWuH7IRc8MqGXFd45QtOguoAfPau5wjdb2idg9F28kBlVqVIO/ppnKZCWBulbQtsiFYzNiJwVuOaG2G4oipLgHPJmgysHDqaiWpzgA8RDT7moKdYzlA80yZF0yjdhbRmcJ+mELSqSEIxA0/WMKRFFbnq8VBTLJdvXW/Yvb/joRz8iBk9wIWPNtSI2PU//9je43S7LkAqDkTNMXREOBzq9AWmQbY9rBtanp3zwyaeoasZXj75l71pkymZuCfhx5Gq35bguMMbw6sVL/vDyDmF34OACok+s7pzywT//Y84/+ynPnr7gf/p//Uua6xsqa3muDceLJav1mv1+y2q9YOg6nj/6iuH2DZfHZ9jFkudPnjPu9mihUdbw+tVrrg8H7jx8wOXFA5Is6PqBIBJ6VpN0we7QM4osnYlSsGteUVYFi5NTZoslz799ycJUKNfhCkVlNT5FhrHlEBy7TT5ACxIH5zns3yBjR9qP2LJmQNE9b/joZE5gg1Ylv338iosPfsTN948Y/Za7733C7sWLbCwuNM61jOOIionNYU9MiZ/cOUamkU07oo3mSFsEiSACQhQcWse8rDiazfFh4NPTI+ZFDtssbTnlJQi6rkOpTOZiGHPApf796YT/q1wCJAIZcwE6ppT3DSlnkBDTu21SStMELUSQAp2ZMpQmFzYp5WHMWylY4m0wKigN45iwOpPFQCFFJDqfSRApZ2qIt749k+MCjFQYLXPQZ8jyCAS4PsNAs8gk69CdD/iYNyXWZNSttpKLe+fgHbebHS+vNlSzOSk6tBSUVU1M2dCrlOb26iUxOIxIFPMFbr/j06MjRudwRUHjPcNmSzdfYGxJTImDNvzqu5f8zd/8mu+//oK+a0Ep2idfsr19weOL+7z/ox9jZ3POH37G88/3uOFASv7/55vx9nN7ZxqYPvc0FTRwGAbMfMbsdM3sqxVVXSOVmb5nghTdVCiK3/VFb7Vq777l4t00XCjN6vScf/hP/zmv31xxdfWSbnfL0OwIzqGMQWmFUoZnjx/zb//Nv2J7e8u6qimaLcddw535nM4PXB1aXtzcsD5as64rfMyT1+vNLaP3SKsZhgbtRtanJ0SRePrsOXcvz9hs93wiBHcuTglKM8b0LlA9FypZdqekJHg/5R1lH5NKMA4uI8JtnnQnMuUSnbG+Sgm0mQh0ivzrlMmbzJQwVgEyZ7WkgCBL/0KCziWkTBRT4S1lLgYrowj+Lbo9e/KCD5PXNk6T87f2j5BDgbVAxXzPJhlRIst4BD/c1VKOotAU1Qq3v6G5fYUAtK3zFrXvcmPoRsI4UJRlptaWFQweNzQTC0Dgo8BWFaXVOA/CR3zbYAqVpVdFwcXFHfpxQMXEcrXGGM2dkxOszgMbqfI7LKUBKSUeT3W0hqSQxmCMJYwDRltA0oZIefoei8/+PsN2ICaPtAWDi1lW7gNC6+wHR+KFQkqdhzJaI6UkEkjBY4OjlILhcEAdzacPKIGUjH2HNpqoFX3nckjpMIDzJAtJSJbzOnumJOjK0rzeYBYVq8WcYqpNAPy+QQpJeXLCGBVD7+iVwQ0jpTIcupZV73BtT1HNCGOPUllWGMXbqWyCkPFdti4zlAGR60aRAWBxkocWE+UtBCispDISId6W51lALURG6Hufh5BvB0Egpt41S7XXixlGGxCKdhg5dA5bzUh4pJJ5c+ZzhuEwDKjS8voQoA2so8LtGvavX3C1aXjRO1TfcJ4sx6PL36focSFSKMmsUPjkacZISopuGDBaUy9qKhHYAjhPjOC7Ht8P78LAR+dzHpsSDH3DfH5MFFk657zH2gIXBlSxyoHXISFEpLQlP/ngI/Ztg9SSvuk4XSyJfqRrs7LAjY4oNdoaRtcjTaJtW/o2U/3KeoZdrBj67t2wq21azqp6aqyhNIZi2vxZEYnx9ze4/YE3SwLvApC7/3EcKXSm/mRdaZieUTUlncs8wVGZWqeNxocw5RtIdPSUVmCMZj47QpGNiJW1GCmRMWHKkiSgHQZ2zch6mWUVRVllX0ICH3JGQgiBEDyj9wgf89S3rjL6uzsQDh0uQggt1cqQijNCPCImj9u8ZPbgHDuriCn/3VRhEESuXl9BcCQ3YgtDOOwJ29copTgcduhyQWUsqu/Z/PYr9I8sSRcMbcfq7C7Jlhx2N3l6YhQUWSs69g5Z5cIjuURpC/zQYxS0wdMPDllrdIjEduTk4pznL19y/ODu7xKpY+L1V4/YPXnOfDWnGQeO7lzgr7e4END7PfsRqvce0l5doVSBOD1l27TMyhlnizVxm/MFSIlSKESE7X7H9e0V9+/e5eWjb0n373F0ec5ud8PZg/tc/vznzGYV/+7/8a958+h72r6l32+5OL9AScFiWRFl5PT8lCeff87Vo8cZ+X75ADE4vvr155w8uMtYGnoXmM9Kltpweu8u0pbstltGIRBGcKSOYWZ5ddtys+9o3JBDQMs5elazvjim0JrgJM3oOLIlC5sP4cPgKWKi6wVSaJohEkRCqcRus6EfIhhDu+s4XpVUleVONUNpTZ8Uj168Abtm3GwYdtcs15anf/rvOfvRzwhGsJgvuH7xHbP1KZ5ET+KiKrm/0Lzqe5ohcGRz+GrwWZrROcHrqy2ffvweKTnWleH+vGJhNfumhaToh3Ey2KdJZ5wLIx/i77YwP9Ar74tyHoZGYqWgd1kqIeU0FIFMmxPkQjRMxCIJWTY2pbojSCrr5kk5IDW9ncoLgbI5UNFYhe8dWktSHxAk6tpwaIZpyp4otGDwMWdvhIjSCjeEqc+KU+5OfiGPIU3kpiwTFCLLS/qQqJQG73j2/A3Pn75AAstFxXY7oJVk7DqGcSCMQ86EMpowdiitMHLFzBbomOjHgVdbx6pvKZNgeXrBGDyuH/n6xUt+881TXrx4ztB3OD/S7W6Q2jA/PuaTH/+Ef/Lf/COKsmBsduyvXrJ//RjvmwxxmKRwQrwFMvzuytu87GMSKnu4pFaUs5qTu5es12vMy5f4iWQlpMpDlpjDxN/6nqTIHoxcwCQkCqkM69NLHn70KburV3z/xa/omh3ROyChpaa0C0Y3MHZ7SPDk+28J3vPBBx8R+z1r72i7luOqpi4rDsPA5uUL7pyes9Sak3uX7IaeXdcTvEcZi9Z5g1BWBdubW85O1sgkePTNUyJwdH4GWpGm4ktKiFECWTaXkKQYSNNWJsVAigk/5sGelhlSIhWIQhKm7VMIkcIamtFT1watsgRSKYM12f+WUd4y00Wm70kkEfI6K2+Opik4MU1Kjcl3ESdUe8p1qJ42sDEkVBJoITKmWsi8oU4JKaYG/39FQvxhXUIKjIDxcMvu9hluaLOfMEZSP+BFHkR4NyCArmmYzecIFIW1BDfm8FQ3khK0fc+sPkFISV0URCWprebjjx5y/+KCo9NjQozsrrfMlmvmleX88oIUwlTQBwRl9vvFHJSKLiBJkpCk0YMUCBTee0ShaGKi/OjHrA6O3bef0w+OSiXG3mWZplT4EMGanImzuaaoCpTRaC0xRZHlv1oRwoAUiTEGTFGja0m/72FhMwGxKghNi1SaFIcsavAhA7KMRoweLSRGSbSWVHXB4vwI4QSmtPhhRAnB4ANSwOnZCU3TEp43+AhbKVjVc4KyDIceOx8xRUHfjzm4WQiSEiAzJGfsPNVqGqBIMW2mcwitCAJioC5k3qL4SGHzQO3tNjCRm6qmd1ir3g0Xs6L4PxkAiRxge3SUw1NDDCipqOs82CJFwuRfionJz9Yzr+c8eX5DGT1WDYw6kGLkzauXvLl6w1w5Shn4/7L3X7+aZXl6JvYsu83njz9hMtKXz6rqrmqySQ6HRGsGlCBQggQNCGGu9HfpVpAAmbuhmsI0B/TVhuyu6nJpKm344z673XK6WDuiCIHSFYtUAtxAIRNZGZFxvm/vtX/mfZ/X+UgZPcIqJiYSdBxjBmC92bNYrFA6EFrH6miVFVUolIgYKQltQ7ffk4TEeYfzCaU0MQ1ZfRB8hpx5lzeUwRFTpHUJZ1T2Q3pB8lDWE04WK0SK7NuG3XZHiD0xJgpbEYaIsDmnK0lB3weElkQBxWzKEBK+d7i2Ybpc8eDNt4jdnpOTCxBwdnKGDhGjFI1ziOgQqvqdPeNf62YpjVroGAUGhdbZwJtfqwmlJbt9S2lVfkkyGoDHlwNAWRQEJPvBURc5bFLbzJQP3lPaOhOorEWljKcUSmGrgq7rx4mzpO17/DAwnU6w2tD3PSEkXDfQbLcURFRRklJAD4J+CGhjsNaSfCbVqaMHdJ1iMtH02wPN9hanI5OjY7AWkcAdWkTbk/oDSQa8NojdHtUPOSwwKlLXg9WIPvLiL37N8fkDNkPg6OElti5x7YBwMUtophV979BTTbe/ot91lNU8U2NcQrisKY4BhpCYKE1zu0XPaj599pTvvf8IHyM6CVIS9PsdL379CaFtcVWZiUBCMjQ7RN+RCKxv7rCTEuEjelUiReL53RWu7Tm/PCWEDikU09mMl0+e4FLOV9nd3nB8tOL2C8n2sOW0WnK4u+Pk8pIXXz3FNS3rp0/wm2vC/oAKOWjz/MF9SmPo2gMf/+qviIPDTGc0wfHLDz+EoWFal0wPcx49epuirrh6+hI9X6BXRwRU/hkrw9A27HY9Tx5/wk6XqNkctVrgqppdlAhV8uTJDqMEy8WSTR/RRaARAk0aAyglW59wAfohsAsDV5s1oevwqmSzztNsLwJnWPppQlQl75sT/o//l/8XXzYls1Ixm5S8+OoJxeKC2ckFNLc8++IJxXSaZX5uoBKR02mBVIL1wTEpKkqRp9V63Fbs93tKpakkBAJvHS14uJoT+xZD1my/OvSjEAw+4hNjMOarKfLX+ArkybvIniApcrMiksiY+RgzbQwwSpK1RZLoI8LkAYGSo/wr1+MICc5nwIEQuXiMMeIGD95nYqbKco6ytMghIIPHTAyD81STAqEkBZCpwzJvtIZAd+jBGqppiXMBW2QUcxhfHJA3WoxStqEb+PSjz7hZ71jMZri7Ox5/9Zir5y/pXGJ1tKDtWq5ftEDIP17oieTtY6kVTRz48uoOE+BsPmdWVOy3d7CYcrVr+PWXT3l+dUvfRxKB/f4GpGC2PCN4z1/96z/h53/2T6nrCQHFZLbAt0u6vcDRkdLwurgQ/96fXUo1SulAK4PRhsVqhdY5UPPk4X3efvstfvnFY0JM+NjnsEs0MsUMhkivmrCsRhCQv1sJVb3g7//Xf8TnX3zKX/6bP8G59t8r2hN+bFTr6RSpCoZ+S+wH7tY3LO5W+KHl87trPlPwndMLTq1lNZny+fU1j29uWB6dstsdKG3BdFITkJiqZDqdce/yIoeEh0jbdrz55hskIfjyi+cc+sjpvdPcfI/Fkza5rfdJjGbyDMMRJPrO4Tqf85MKhdIWmZXRWCWIgiyni4aWHlVrlrMCkcixD1YSeo+xhkFk4IvSKue2xNy4AwyDZ1KocXP1moyMDxm2EUffqhAJrTIxMo5SVhUjIuRCNH9/iTiE8ftI8DXeLFmt2N1+xe7mKX2XNx5SWiLZl+JdC6l6NVfBFobCFhTWYs1RllYGj1SGGBxW1oSUKKsSNzhOVnN+/IPvcXy8oDYKZUuKquLs6Ih6NscoST2fEpzPcAYhSUmiZUEUDpIn+hZZlsT+Vf6You86irrOEIjo2W12pNN72Laj++oxg0tEGUEJjDYYa5AyZwRanSVyoc/kYSVysGjf9fgEwkpkNQEJXQr0LnC4PVAuamz0qLrA7Q60fY+MnqRz3mOG1viROJw4eXjOsNnjh57Z2QVGl/S7PsMk0AzbA8IOlAgKqXDdAaETg7Gs2wO27ZkmQZKSFEd8t8l0R6Wz1Df4SPBhVBq9kl7ngFwpJYW1uCgZhjw8U0q8HrqEGEhE1psDN7dbLi/Pc3wNgRgC2mhCyDJVJUdgj/ittz6MOU9JJKzRGBWy9DHlpu7pkyfYmx2T1ZJFbdnIjotVgVWSs+Mlod2SugMCgS5LpAYhPDocsCkHw6bBs2962nqKtAXSBmazCU3nKMuCSTAcbtcI71ASDJ7WdxhhSdEh9RjDEwYgEXWWkBtjUcayO3RczuZ0vcfGiFCarnX4IWS25uDxwTP0OQB4aAekNQitRzpySYhDhhUpjUtgreSw27NYLHnn3fd4+913OJlXTFbHCCV55949Hn/8MZW17KxFuY6q/C8yvP/wlQcDaClRKWaakoSYQn7gksLaYjRvyzxVGcNpR8pszgMwmqPZlD7kh8SFME4A84u1KEqiz9sqRMZCCgRVYRBAVVa0bYeWgq5tRzJRznrquh6rFEPXZzxknzKr3iXK1QzX97R3DdpoDk2HsCX75hZbTqimK9R0hlCGFAL761tk25G216iwR04rjFrh++dEIn7XkJzGGoiVZv3FM/rPv+TJn/1bVr//A1IBKbW49oDzLUU9Iw09Ogmi1llz3jkOmx12mgP2Ukh0u/0rpzXNriGlxGFoOTo5oTYVSYAnT9uffvQZoRsojCXpnMEQmobu5WO66+c5ZXrXsv75X1Gszhh2e57/5kv6l1es+w6THKfzGX2ITOuadVWy8w1Ga66/+orusKNWknToeNk+pa4XrLcNZ/cvadc7/LYhDI4hehbHx5y++ZBmu6cl4qKjMwXrQ0vcrhmaNSdlyfnqnHv3H5FsQbPZ8dnnn3O8OGFyeYF9520+/fwpH/7mU3zfUk6z/G6NpbeS41lBQYGOhl3f0TcDTZ94erPhZvs5m12HNpaToyWoBqUSvTLcdoLlbIYSgsfXT1AehDBE1dMPgflCE/otP753yYvnV3z4q1/Sv3zO7R7MxJCM4nmaUb75Q1Z1YPfsNxzNJ0xOThmk5e5uyw/ev+DhvOJoVnKz3tJ3gdkUjDK4mI2zeNjt9yxqQxE9U6t452iOEh5PQmhJ23RoqfHeMziHEIYhMGZGeWr7dZfhJXQS+TCUORXcGIUfXPZkxCzrlUIgZRqbw3Fa6LORPcUwFvbZrO5cbpB8Bn+h5Ph5xTjKPyRJ5LyPqlBUVnE8lYTxUApIhNE0/cCu8xSFIkXyJvN2h52WKKORRuF1bpKkVHlqOnqwjJU0zcDt9TV9jLzx8IJnT5/z5adfsm96iqJiuSgw5oRf/fojyrKGlOi7FqlLptMpKubt/Fc3NzRNy+VyxbbteLnbYbZb3Gdf8unVLb/56iua3tG2O3a7KyKR0s5p1ldcPfmE6Ifxw86SK2UrynpKPZ3TteAHiZA6k5yCH3G740clVM6/UhqjLWVZoZXOU/f5jG9+91v8y3/3M5q+hwjJOZKIJJkR1zHmF2iWeymUUihdIgQ8fPSItx894svHXzJfnXF3/fR1EQRQ2gl1NaHrWpQ2SGWJYaBtD9zeXeP6lna3ZicS292Ot6YLJuTt3m3XME+eZr/DaMX9exf0PnB0cszR8Yq6Kji+OOd2m6Unn3/xmMvLc84uT9k3HTfrBmEKrNH4mDAqN+UuZH+uC9ljMfSevhno9zkfp9YiZ9YoUAKCgMIqppUh1hpxNMENDqUVsesJSeCQ+BgoBASfQzVFiBnFm7IcOn+4cnxmXgX9itF7locBQjDKlvL2SYiAlnn4oGNCxkRhJa+UqIn8JVsleXWHfB2v0G/ZvPyCvlnn4YnKDWUhNbIoUMaCVGNWIkip6VyPKbIkrqoqDvt9JhCGMH6eWYplpGBSlZydLnMxbQxFNaGaTlBCZQkxiQxu00iVPdxKmuwfihFULuillAgNCYtvhvx9iURyPSkq+n2HGCJOFEzefI+4W9M5h/CJ1WJFtVqhBMRRrSMR2MrSeZOVPj4ijUbLSLfdk+IKJTTtPntbq9KQUCRl6A5t9oQ6T0LQdJ6izFI/4ROFMhhb5Ial0HkIPvq3lFWIToIPJDdkub/MHidzSFRSMK8LigRD27Lf75GtzXJRbUAKlNY5fma0D2idqabZey0ZBvcaUiKRWX1kUpaVCoHQ6vWgMMS8USuMpekyUlup7JtkHB7kdWtumqSCwSdczH8OpTWdj4SQkeJSZtS+1hKpDbc3dxBhZpdQKwKCotCcrGqaK0EQFqENUhtiHPDDjlIHZK1o9ntEhMpqmkNLNV9QzhdEoTGFyoO+JjDsDtjJhH5/yHmUApTyTGdzDk1HijnvTuvcNqRxG6ikYDKpcjRNFFhtcIMnpgEEdC5L9lIMIz7e4LwjpUwjFEIRR8lluAMzm2GbDuccs0nNB7/3+8Smx293HC1XvPHt9yirkuZuw3w6xRhDu1tjBFx/+dnv7Bn/WjdL3gcMoGXKkykpUWp8iKNECYU1Yzq5zCQgIRUp5QInxoAfDbGlFnRuIEqDGeV5+Y2dCR9qnNgqbfINn0AowXRSE2PWYieVjYB5p5zDcIe2x203FIUiKs3gHZWSICztfsh0JbtAi47g9oAnWYkuKkRZIVAE55FmQr/pqLodRkSSsZTVkm5/TWg2tLsdsutQbs7d5ppjbbj7+AtC0/Lxz3/O3/7bP6YoK6JvaO5eMl0cobUiuDYfoqIilSVh06A8hKYnyYyuPKzXlNMp/f5AWdckrdhf3TA/OsZIRRscMiZuXr6gbxoWJ8eEvicIST2Zog5r0vaWvmto1p7N5haagXL2FDVf0c8WTELgrmnZIHjw1lu89/47/PzP/4IPTs+4bg7s2obFpOS4LCnqki+vr+nrmtVJzUcffcTJW28yPTqm7Tsikfr0iLKc8pt/+2eoWcV10jz9/FP2m5eUCN6dLXhvsWI+m2KE5uXmjjsH0/mC+YN3uFGWf/HhVzz/9DlyekyxeMjQHHJORlIcuh4p99hlx3pouL69ZT5b0A6Rr263RG3pDgOpDZRVjZGSqqqoKsNV0+Ncw/VBIxMMfcQDSIFvDtT1FJwnrLf8y3/yP/Dks8dsN7fo0zdRk1OObc1XT16AVITmjtjsefPePU7ffMCVj7y821Brw7I2HNWaNAx89eKabReoK0tP3rgFFxi6gdg3uKHDhIr78yOWZUkMQyaMJUE/9KhSgcyksZhyyoqPHi0TlU7/X5/Rr8OlZQ5STjEhEyNkJGGVwLUeqRNGFhgtx0R1IObMn1ckQDlSmhiDaUPIklwhXm1JspQskRi6gcIIrNFYY5AiIIRmWlmUzvkzbe9p+kBlNTEIjBI0vaPbHfBdj1AS0w2EIoclKglRi9c/Q4qRw8Fx2DW4pFgen3Bz9YK27Xjw6EH2bQq4f++Ujz78hMVsxvHRCTFGPv/sM7q+5fT0FNP13N5ec7vbMi0KhBT0KfLR7Q2/+eVHmMWSl7e37HZ7pNLstjc4H9Da0rVbvGuwuuT4/D5X1y/xQ0ciEYYWrwT333iX9V1Jd9gRhGBoG8LowXoV9yCSQsiE0hqjNGVZvPYfmcLwnR98wPk//hPutlsY8pntvYdkUMniXU+IDqSknMyoqxm2rBEkfvDd73Fxec79e4/YrDfs19e5+JeawlreefAWP/zg+/zkL36CLgo+e/IF3gmCG9hs1kg5vjd8R9QFXyY4UwXaakLnuN6umdsCdB6sHS8X3L88pygNxaRiMZ9x7/45d5s9ylYcmp5DP1DNZzRDwDUt82lFVRuUkDlTJb6ixyWij6QhkFxgaHtC72imltVigtEKYfOQUCswKm80tDGEITeb+xQZ/CiD6SIBOHSOSDawywR6DPZ9hSSP48ZK5Bs8qzVilvOlUfqYg0IjWkiEyIUShx67nCAkpLF4VDIXYN4FFF/fc8S3G1y3z7WHULngF440HHCuZTJfkZTiMASUstn8nzSH3YFpXWN1gTOBrjugTDFipBVN23NxesxsOiX4QNJ5S3H15Bn333ojN02TKp8xQyD2GeyCC/TrPabM/kmZMrAg+YFILs4RA8paUgTnPP1uT7M+MFstsxSw91QnZ+jtjkL2HC0X6MJm6aTW2RYgJUkkjNVIIiKCqit8s0MrSRwGBiMYhkgwhj4kbEqjfULQdY7OeYwIeTMf8wY4JgXGZihBDDk6ZSQo9ndrhLG5IB8jGLSxOUtMS5zOuXhVXWMKQ1VaJotlDvYFhkS2NbiEkZZCaazWSGNyzRcTQkExEgfz7CRvfTL4Lr3qe/JfZUZ+F2VBPUv5M4mJ3mU5pDGZbClymzgeXZJ+GLjeHJhOZ1Qiy/tiSviUn+1Zbdgmz/b6BegZ+3bP7VZyMZkjCoVKiumk4t7Zks16TdB1zgnsA0oErMwb3zB0GGtQwgAJlKRtffbWSom0NVF22MpycA5tCrqho7SGptlxkJp6OqMwJm8iy0neKivJtK4YnCMCd9ueGji0Pqu8UmToRrqdluz3LcH5HLZsC8Juh6oz/CQpwCeKespMGaze0nQ9j958izQE+m0Dx55H3/wmD968T7vf023y+d9ud/SHDr2YkYr/QsP7D15hlAAplV+oMYScoxNzJorReWrQDzlDQmmdszhkzo8QUo424mxGtdbSuSyLiGODpI1BptGXIV5hg9PrKVrXNTkPwCisNQxDn28IbQghcHt7w7K0xN2BfuuY1pr2dk1RVWAksetAOzZPb0kcmNVLPAaHpru5ZeIXxBgJzS3hMNC7HcEHdDnFx4TbvUA0LWzWeCcg9OATL/7iQ9yLLZumpXxrgq0KQgz0TYtwDlNWBGEIySGFRgpNWVh2zR3r3XPqsyNmszkGwbBv0GVJu90zmUzog6M/NNwOgT4FvIR+s+P5r3+DHXNkRCzR0wnGap791UeEuzVt2/Hk2RVVaSEJ/NBRCNgOHbNpRdUesCngr67YRM+b8wlu17GsKpyRnM9rvvPGQwSRf/7zjuL8jN/7e3+H93/8t7gePIvFnA7QwnA8mfPy6UsuH13yF5/8mmdfPuW9WckHsxm1KtDa4so5X24aeiU5f3TOYrbiy87x1cHzvPMMskBNTuhDReoAUSAKwWwx59FiwlxLhB8YXMu3332Xoe1pu4HL1RJsxXq7551HD7jd3GG15fJkSucCupzxm2d3/OblBhcU18bgYmRqHFWRmC41qd/xxa8+5FBpLi7P2JgV6zjhnMD6y485vHjK8b03sCoSk+a6heefPQVbUU9rHi4Mj45qCIGbzZakFPN5QSlzMKVMCY2gaRpOJwXFsuaN02PeeXCJTFmC1nUNzRAobUHvBvqRqpgpbZph6JmVFSp8nWfCUIxyOMRIwM9Wrhze5zyzeZk9eSn7LqTKhaNIo2l3lGwIKfDBMXJjYJz4Zq9M/mdiNPx2fcal9n2ft05tT2xgdVQzRJ89JDoPZWIBYYh5gNF2+LYDmYMgh3agLAu0EEQXMUoQvKc5dAQhGaKgKAuc72l7z2Jac3F+RN803N7u+PLzJ6zXDefn51ycHdG7gfX6DsICLXIuRx88PZETbTm0DZ2QXG+3qMMBc3eb8cjljEO3pzlsAI/vBwQwKecU1nB8dMJmc0dwLXW1wGrLpKp58+GbFN/4Nj//678iAZvNDdvNLTH4sRDP34tU+VVVlGWebMosi1RKcf/hJd/65ns8ef5yhCEIpOjzSzzlTCrIkI7l8pjVyX2c67Fa8u7b7/D+m5dM3PcJz59w/aXBpTypLrTkjZNTfvzm++hmQMymbLuBm5vnpBQYXEfftlkrnwQuOTo5sDOCSllKm+gT7JoDy4tLBiJFWfL2Ww+YHy3Y7Tv2+x1SCR48uEAYw83dgSQ1SWQMcXcYkAEqq4gqT3F9jNlIHYEQcghq05E6Byky7BvwDhkFWgmMycHJ6tVnhqBrBqKL7DYHglaUU5u9Lj5vP5PMJveoNF5F9FgquAg+JnRIKPtKjpcpfIxFXgoRobOc1ciMBI9+zGEhosVv85ukEAiZ36df5wACEXoQkcKWuVGXOX+q63qIHpECqpiitRy3yhCDR2lLMwxoKainJZGA1QYffN4OlbmmAIFUlgS0+wPN/sBmveXo9ALnHIVWqFIzIHBdxo+rqiB5jy6K7HFLoLUhJslhk2VbSJmN/Icet2sJh5693jF9eMn2yXMOmwNaacqzKQ/vXSCNQsaACOD7AakVtrL0+4YhBGbTkv7Qk/qe5Ez+OaPPYa5dJIksTfP7BikEhQGTsrw7xrEaS5IhuAy0UhqdEkFka4TrerS29O2A954eiRU5w05bzWxaE7oOW9fZQyUyuTH0HXpSoyYTrJA0TY9Igabp6LqWybRm7jwxmiyPHmXTKeYcN6ElSiR8yhs7NSYoC5kHVEIojJEUNoMSMml5BLSEHLGRkkdJmZ9hH9jse1wU7NsOpSdZFUCWyFeFotkNxN5xenzEp59+wXy1oDybUVUamXKjl2zBdDWnbRq8neTGc/AoGUEorJVED1FC1w70pkBHyTAEXJlQ2lAUJdIa/ODwrqNQEi8VWWPhGTyUSSC0RYpMAPTBZWT44ADBoRsQKVFKjSMSek9ZltnTnFym+nVDHhiG7L/0IYddh+TpDgN974hu4HC3YbqY89a771IWU5589BHLaUU1n3JycU5Kkaunz9leb9httgTvSDLX4r/LZOuvdbMkRC5GSmNJKWYevgBTlLmpSRGtBbbISeZiDDtUSuY895QPaZ/IhJVxWhBTwpjchaeY18rBD9kXkLKpOk88wZq8iTJGE0I2XUupaNt8GCyPFsSuITQd3ePHFG9eIpIkHFr8tCT5QHe7QSWNkgW6sIhyDghc05A6R3IOt2nROJJIOUGZgGvWsF8zrDvSbiAETXQH6KB5cUtMgr73PFgdE/xA2G9pr68QaUAGz9ClnKIsDFLDsN5i64L2+o7D9Q3SR1SMtLcblLF8+eEnLE6PQQrc9sDFB48QMtG+vOXFV08RQ0QIT+MHlKmxZYnbXrP98nN017LZHRBScLRY0ewaiip7xD798NfcOzliOq3R3vP+6pil1Wy3W6YPzkki0R22rKoSmXpOzk75B3/0d7HnZ+jTYxbLCXU9Z3u34d433uP288fcHhre+MMf8cd/8j/Cy5e8ZQseVDVTO+HFoWUnWyZK8eBoxXS65Hky/Olf/zXP24Hzh9+g8Zq2MCwmNfP5FBMiq+kMWVgQgqPFDIvHtVsu7YT5bMadgZOzCZWtiF7RH09ouz3r7Q4lI9OJ5v7pEVJEios5760qbjcdv3x+y1cv1nTbltTdsfmoY9d55vffxK4ueXb9kmbzEjsRlJN7PHnxksXFJeWkoJQWWc9oiCgB80nFSan4O9+4x7FxpCDxUmbMuRIUgjFMeUB6x1FdcjydYLXg0dkxE2MgZsN6CJG+6ymqmhh8llEUBaWStM5TGk2hFP7/E2j2NbvCSKKTkhGzS6ZsKoEZNz2aNPrds4k954Cl0WegMrKZnPcTCMQkCCnDGWLwaMBqSZcC0Xm8MsSQUzm7JhB3PUlFqlKijEQkn1OVYsKmyH5wxL5HhBx2a5QkdR3lrMgSZJcwpSEOnq51vHhxQ5Ka1dGMtveomHhw/4Jlkf+si9mUk6MVL1/esjpecnFyxGa95s//4hccLRYkF9je3qCGgV2zH8882Aw92xA4xER0A6ZrUMbifGJwHQmPUprFfMXl8oy37r3NR5/9nC8++RA39AB417Kspvz3//AfcXS+pDpdYFXi8ZMXkCLNfocLecCVhMzbB2myGb4smY5YYTFuNebLOT/44Qf8u7/8BS4Gmr7LzZVo8C7k5kdkOV/wkWk9IzjLxfkx9x/cJ/U9R03HD46Oeb444vHtyxxKHCLfOLrg8PyWt954k6ftnsm05MWLPhdhSeRnKYQMWUh58+NSYlFXrOSEXikO3YGVTFRFyWRS8OTZMxbLOd/6xps4F2g6Tz0tMVVNFBqHZNM4dtuWMCSakDjUispMKXT2Hw0uIFJ2le3bHislh2EgBk8sJd2+YVoZyrogxYCS2SdEgG6fB2q79YH1usFMC+ppOU7LM22vDxEpoCpyjpdRvIZspJEsGEdSpBjl8K+8GEq9giRn9YYElJHoqUEYmbOgZJ60e8dv/Vdf482SIFHaCmMs7TAwmS7o25bDYYcSkoAi+oHoEtqC1pO8mU7gB480eeA6qycMbkAgiTGrYszRguOzU/zQ0+880mhI0DcdN8+uOb04xrUDVDZ/HzFi65IAhLZDR4OuDIJA9J6QFEZpkhEMbjy8Y2A49HRty+pkRnW0JAHNk5e4kHHzu8YRSoORCZ0iWhuE1BhbIJCUlcWNQ2gls7KHmCV7jQ8QEkoUueFZlPn/y7pl3DBQ2IKo4LBviSSKskAXmhj6cYuTiIPHAdFnCIYTmmo+pz8cEEJRVRXrJKjKCqE1CegPHbvrO6bW4p1HFBZTFQQ/UFIjCZRVQRSJYcggjqiyxC54z36zp5rWqEpjrELqvEmKKctKU8rSPMQo3w6JwSVCyHeGVIznVYFSmjT6twYX2O1GyBcqk1CTwCqJloLGOxSR2LeUwmNdg5XQdx5nNMFncrMyJcrUlEczYufyNsuarJgVDingcOjwsiQYxe1tw9B7iqpkMilp+gBJIYnUdc3+ds20MPRDxIhE53r8kIdXPgyE6BApi3C7dkBKSUumBXbjPVVKcP1A8D1Jgh/yEKB3PSFFmkOTQUJjje06R0ggpeTexRlvffM7dJs1t89eMp/POHlwzHf/xgdInXj+5Dn94BlI1MsZSEnyA8Nmh9C/u5bma90saWsoTDbyCilII9JQKo0YJ4kheJQWRCcIMWv7hciZKVk6MFL1ItnABK8lHpC3V0Lm4E3vA4VUxODzullJwuAorYaUpR9aG/qmzZM2skzn0Eeuv3zOWVXStz5TRLZrFInh0KClZXK5oOu3UB+RgqNPLbOTFcPdnt47zLSgu3rG9PiU6MEqz+HuBtkN9NsGd8iI1tD3bK/WGGs47A4opTEx4l6+RB0qRPSY6ZwnH37F9OKM6BzldIrSBddNgykrimnJ53/21xxfnOO8p9/s2d1tiNsGkwTe5a3bxVsPef6rT/j0Z79kdnzEbDkjXr9gs71j9iBjIncffkz7/CnzxQyPoLCWwhTIqSDqxJAGOOzwg+Ptew/5mz/8IVWpCdsth+2Woq6whabfbNFScPbwAXqx4Hy5oE2JQRWZ9oNgOpvx3f/qD/nN6ccoK/m//Z//T+i25Y3VnPP5ivX+wMuh52roOK5qpimybTt+cfuET1sPSXHx8E3u+o7ZxZu8/c77TFcrvFJ8+dVzvni55eTyhJLA888/p9le84c/+j7fe+cdEpFD17BvetZdy2xRs77e08uS8/NLXl5d8eLuwJAEvu344L03MESsXHN2/hb/9F/+lF/ftdw+eY7re8z5Wzy/3vHsZs/u+ilqdkYoFzx5eo2YTUhWYCZTRFnT9UMO0SwMEyv43sWSt48mKLfHuSxzCDFilcYaRdO2dG3HrDBUhcTYAiMi88oivKN3Ld3Q0Qdyw+t9LgjJQam2NMTDHgrLxFq2ffOf5fn/j3aJhJCjBynEHFCdEhiJrQxFaXO20mhlybCGkRhGDotkTGIPPmS5zLhpIkQKLWiHgBaCwmha4VCvzqqckQ4jrTP2gdligo+R6ALWKrpmoNs1SMToj4q4pkOkyGwxwaq87dYx0jPKH3rHdr8naI0RiXkhOD5aMjUCLRWVlYTgmM8ngOT2ds3zq1umlaG4POfF1W3W+Q+O3jvOJxNKZVh3DY3r6MdU+hAdtZRIA0bnhua997/LD779A97QNe/de8SfKMHV1XOCcEhhmZqCtyYL3rk4R0w0dj7jex98gCk+4ermGiUNXvYZaqEsSmalgJJZhnN0dDSG0OaBlTGWd7/xHm+//QaHX7YIKelDznXpRZ5AZ3ljjouoqgnJWB6cn+Od45/+s3/F33z7bd65/5C/uz7wl8bQtS1vHJ9yNKm5cXsKdcpHX3zGy6uXuaQfmwWhFCpoCpE9bz44+mQ4e/SAZDRNCHzx1Rc0hz2Fypl+Rhpurm5R1nC0nHN0NMNWBUlKlrOau9aT4pARukllMldMOeA4JYxIWRIaE32KxG4APzZEQiNcYNgPpEUgjKRXqzMNUGtIIkvVfRfwQ8L6SOgdmtFbZAzd0BK9R2FQQo9Y9t8SwLKhVYx/L7LJPTHmyojRwJ69TEKALTSm1hlr/uqxE2kMuv33M7C+npckw5/62FOWE6QyoBxlPc1DFKUZRrkmkLd59Sz7Y5Sg956YFPNpRdrHDJEZ6b3GVtiyJDJKzpJge73B6oqXhy9YLGbYwhKHkMExJvu3tVKoxTzLiqNHIYkioYUijBTE5HONIkc/lZkU2LrAOYedlPj5FNd7/OC5ubllbxJHF2cZEU8iuITvwNoSQYQAA5FhcDkDLEZMFITWZXuDG1AYQhB0g0OPsQgCBcGhvUaRB0pSaVw3UFQlwWV/E9Hjh4gThn1IRC0pm54UHHYyIQhFtVqiq5K+6yhLSwwBqfLmyvc+D3a6gfm8ZhgGqtKgrEFbgx7x7LnRTxy2O54+ecniZMX5vWOskTmDLI1xEmLE94sRuiIlIsXX2XBhDIeNMWG0IBJBapKSdMJzCJ7eeSZ9ZKEVRgtSYWianu2mxWhN6HtqASelYUZAuwGCBJkR7n0fabuE3/cUIhE0dI78XhE5e69pO2IFUVr23XieWoNQEq1yNqkSEWHLHJWgJIMPXN9cY6aWKgS6wxaBRiApakvbNBzPT9BGo7Wi6Tt0TNiRDImEwbkxZoBMrWs81mh0kQh9IMbE0DqUVMxnC85mCxazOZurW4bdgcJI6vmED/7wR0yOV6zXd/joubm7JQwDRWmIQSCjJ5CylPJ3dH2tmyUxTqOEGCl1We2C1hoRAynm6axSkhDS6w2SkjIb+0bEdyYkJVLwObU8eKzKU5rcXAn6fkCJjCU3Mk+biRFrS4rC0nZ9LlKGAedzNx9CwLlIs49U0xVdPDCpa7SSOK2wleHq2ZqHjx7S+D1SV/jgUDIwmaxAGXzaMKkmhMMdIXj221umy0v6kLt11SXaux2FnjM0HTFAvZjSdwMpQjmbwNCy+fRT9LSiXC4ZPHz28494T0MsDNXiGCFhdXbBYbvhqydPsMsZzeHA4dDimo7rF9csz85RxtLc3PCtv/+3EFrx+Fcf4Q8NR2+9QbPZ4nZb2rsNR9+p6K+uef7Tn6Fc9nS1LjAtSrqho901iEqTnGNZFZw/fMDv/eEfcnR6CoUi9B03L14ym0worabfbVFCoKZT1GKFsyV2Pmd5do4uJghhuX38hKK0/P7f+D3+7b/+Z3zw/tu8eHpNaSzXfcPB9bxxepapQlrxi8cv+NObA20144PvPOLlzZ5n24E3v/ctvvv977EfArdNz3rf0+47dF3w5MkT3rs45837Dzn7g+9xsqxZN3dUVUU3NBRWczlbceh7lqdzbBtYDoGz6b1xMuuZHR/Rd3vu9gdu9p677Q2T5Yx7wrCbTrlz0EZF2NzRRYG69w2iS2SkTsRqyeT4AlkW9L6lMIaizDK7QiTeOJqyvr6hqA2lyjjrqrDUyuSCKcHZ0RGL2uKaA70bWK4WGJm9Lk3XZmxxyNPDzvevMxsqqzJARWT5GjFQaPn/+0H9//PLjM+yVPJ1QyJDhpYgEnLEpSMy8EQqkSExMo3ZShmXrMbKMJFIMWCEQGqIPmJqnQ2xMWGtYhgG6qokxPwi16XME3o9SvdSzK7hGLMxtu3xLlAaha8MLuTm6pWsIwkILlJVhi3QD46u9xkDbTVI2B06qCylCsSk8K5nt9lz/fKO7WbHcrngjQeX/OWf/4ybq5d0rke6HBh4PlsQg8fvwtgsOhJgTA4FTMkTkyNGz/puPcYzCAoEv/f+B/zqo59xs1tjpeZ8uuQ777xLch3/1//H/8i7P/4hJ2dn9K3j+PiU9e11lkuTM99i8LkxkgKpJauTVYZpZMY6QkTOL4/43ve+xfXthuc3V6i+yxNiHxm0ISWJKSpWyyP6dsfxcsXt7R1/+pM/489/8i+5++AD/ugHv8+j9k1kodgdDui65ov1DfXFPX79yYf86uNfcNhuUTLnmAjB6796JIVVnE5nnC1W3H90galKPnv8lEldc/3ylmmI2KJgtnzEW++9gRCK27s11eBZHS2RZcHgPMH5vB2QivYwkFKe1g7OMzGGLmZCoxIgYkIL6F3EaItvd3lAKCMiBcKQqXNKS1TI96rRhkCinhkWWuT8Lp8b9uAjYXBYJahKhbUib0alRgiBUTlg9rcN05hFE/PvrXQCIccMw7yNEmR/cfbJCbSWCAmhjzlEUiZkfAWR+Hpe/dCjtBr9HJKuaRBS5sBXKejbNgf7CknfZ9+e0Bpja8qywncdQkgOh4aiLomHA1oryrpmsZhTFXloJYzlsNkTeofvHc8eP2W+WnF+7wIdIahcm/g0Fuilyf65fiC5Aanz3xttGAaHkILoPClGdGlHIpzEWkMYEtXJCnG7zZLYBNFB5xyqbUFakgCtFY78s6UE0Qesymh7Y1Ue/hU2++siBJGISRCVQiiP0TnY2A2e2PdE3zEpS6JWxDEuQakxHqb3YCzb9YEX6x0+JtTZKdWkRoRI0ho7nTD4jOQOMZ+lzg2Y4OmahjZlRH5hB+R472clUnrdXJASz1+8YDmb5uDVYcj1ohTZjqGyxxUlR9Q4HNoWrfXrodjgPFLnwOacYJYgCryAbZ9onOR27wgpUveR5UxR2CwbXN/u6JqW/nbLajIl7XecTxfMg2emNNEFfMpeoa4ZOBw6SqWoTxcoIwiHTQ6N9Sn7HHVB1yf0vKRPGoEjBEk/eFRdIkRAiQh4irJks98ThWC93nO50CM5sMoExyJLTUsr0YVEK0OKMSs0dF4zSzV+nikRvcdIyeAjxhiEUGhVoUVLqS2mKJhOZxxf3qfdt1w/fkHqW1CRi3fv8e53vsHq7JgXL16w2W558fwZL589gRBymLbP79ri1Tbtd3R9rZulV59LCCEDGMbCAuR4SOf0ZEUOhBRKIGJEyDGRXIwpxDFkja/WiEgmoghBYbPmVyBQKlNnjNEQBqTM05iqLnF+pH2kbErO9AeZoQ8odFlTnZ1g+gqURkwKiukFvtnz5g++A3iskxgS3d1z6qMlspyThMR7SQgNQ3egKieI5PFJoKZLxI2h3w9YoUj+QHIS7xJSJLqmZ9t3PHz4iLQ70D9/iXhwTvSBAonve5p1w9HbbxCIeWLTDdSzOcenZ3z57NecHB+ze/Icf7MluoCYVnRKUK6WFCcrDjcbkstoTOccfrPHCs3i3j2i83z505/y/PEXzAtFhQRpSErTdQ1KCra7lhgcZVnyve9/wPz8GLWc41OgmE44K0tCP8DgKE6O0EKQbEFvJFU9J9kJQRhKWyKU4vj0iF/8659w+fAe/+v/7T/knygI23/H/+Zv/A0eP/+Cf/anP+UPf/hjltOaj6+uuJodcXLykJPZkqg1X6y3vPett3n329/gdjdwsx/QVcn27gmL2QI7nXI+OeKtyzMeHc2JYuDQ7FEhN4P1ZE6UibbpUaqm6TuWU8uiqklJUdY5vyamwF0b+Grj+HLb0DtFWy6zzruAbv2M/+oPPuDZ7RE/+2qDGyJC9BBb6spy7+EFlCWu2zO4wKKuKGVCuJ6378+ZWnjy/Jp7984xZPO/FQIjEiolZragUIpaaVJVs48NpdJoBId+ACXHcNX8osuGd8Hl2QmSxHa/x7mQIShKYoz9z3cI/Ee4XkERFHnjLCUYo+i9QyqVzw2RvUf5JZARxzGOy+g4GpJ4pV8HreUo/Y35BRJzgSBTQMtEkhmwkETMKFoJBRpbFsQQkSkXpsPYMAkhiN6DDxRaI0VCCYWxBu8DDklVyizpEYLJbEZiYFFZfPSIlH1ZMUSEknRNx37f4n3k6HjO0WqKRPKzv/wFX372mPXNNdZanHfURUWhDC8Pu/xZ+EQG4Sec6/E+0Lse5x0xOK6unvHXv/gp1Q9+xG+unvFgueKDd77Frz/6JUtbMq2mPHj0Dv/Tn/0Fv/zsE258y3e/8322t2tm0xnnl/f56suOwhQIIXAJUnCo0US9Ojkafaop/0zRM5vN+P2/+SNevLwh/Cpxu95S+JxD1HR7YoTClmhlaHc7qvtvcHv7AqUV3/vR3+Rqt+VnVy8oasN2VtFoSbmYE0Pkk49/zi8/+4z9YT16XF8hswVSG0pdIpNgNa355rvvsCxKFtMcK9D/5ksQiiE5ttsdSST++q8Vp2dnvPXWG8znc/phIDhHUJnIpSQURjOdViip8uZXyVysZm3P64w8bVWOgDDZw9QOGpsSsnOkISJMJPmEa7M6wpqsjJBWIwuNajPxsrAa32bUvdGSUisKLSh13hpmohdomfH5So6fRIzj1glAZmx7ys9KJhnKTGRLuSDWSmJklrpHkX0hOXwjDxy+rtfgBqTKkIC+6/OWxtRjnIDElCXzsmZ9d0W739F7R1FUGFvT9z0yIx8QSZJQSFshVA5+nS2WOaNQ69FXFigmFV3TcFhvePn4GadnJ0Qpsxl+jIUQxhJdZPC5WZG2JJI3Hb7pEUlgypJ+u0frvFmJhUPbLF9jzCFCKYyx3Lt3RnO3xrUO3w1EIqqYUh0ZYu/p254YA6a2qH0OL/dNj51N8nAnhrGBrnAhYiUMIt+XrvdZDQTErsHq3GxrdYJ0juQTfXLEgXFD1PHg8pyXu5bb3YFjIVFHRQ589xFZWEKzQ7b58w/twNB0UJZ0jeN2vce5BYu6QOvsm8uColy79X3PP/4f/pj/xf/8v2XftJxenORgaq3G4Np8DzNKsoOAuqpyPEQICBlfA1CIufaUKvvVBhc5dIFuRJVLCnoX6AOEzuNcoB+DysPgqQqLlAarbZYSh4iWhtg72u2OqxdrnlzdchayFG6ysogUxucr/zm7KDi4xEQIGjSW7Ge1MsuyrbVsmwHvUyZhCs3hsMZ1LUPf0TlHUU2odUEalwhVVXF+fszQRza3OwDSq9o6OFy/z5CeCNoUHIYBhMzyuxCxZUW9XKKrisn0iO3VjtTvEclhZ4rzt97h4ftvMgTPz37xS54/e4F3nqurp2xubhAiYZTJn69IWSr/Oxzcfr2bJZlhAqQ06tezBAXBqA3NN7KP6fXkIGdAjHQqBFKpLKkQGe3LuGIdvEeO+t+sqxwtqSmbDqUQlEVeV/ZtNwbfZmS59w7nXcZnEwgyIhYl1musjIhCI73ATiRBa4KLWDtHqMRU63yTC0hCcvTGA9ztY6Sa0d+tiX1C7A6EuKPf3ZF8Ntj5BF3Xo0UBQvFisyVpQ+oDgzsgrSB2Pbo09OvnvLla8uzxFfXRPQoFzASTkyXt5oCIgrXvaZ8+47PPP0duGiarI1YX5+yahvtvPCL5yPPffI6723H09kO69R633aPvnTI/PWb34gVPP/okDx91wb7p8D5xs9tzv8qI4N2uwRaGajnHVBXFpEYWBp10XsNPCgbvCUohJzWmqimmC+r5HFtOkDb/rEppAjnz5r0ffI/5bE65POHv/f3/mu+/9Qbl7o4YV3z3W+9yerLgkxfX/PHHX1BdPmQ1qeml4KMvvuB73/uAe++8x60L7Ns988kMoQRvXpzx7ffewhhL0oKT+ZRSwmHfM5/XzIqSBGyHnqubHcZO2K23bAfPF8EzdFeEpJF47q1qzo9mfPb0iudNoouS7WHP3XZHe3C8vL3BmpJ96yhKS0Gg218jYmB+fs789IQgFbI9sP30E2aP3mLwWYZjXES6ig+/eMpiUSGJgEKSKKSkNhKTIspISqsxWtCO9KSyKjPEwQ0URUHTdtS2Yt3sCTEwn2W5VzcMOJ/o+4AjEUW+Z7/OlxrlQK+KthiyPNdKmZ9dkV+KSZFlFDGRQkCPZLBcFeY8mhzWmYMHhQhoMj45jQbmyiqaXY+2MufQuJy3JvCUlQEiQo7a+gT4gPSJqrS4tkeELDmVKgfcSqDrAzF6ohfZtyQEi8UEazR1IRiCprYSayWl0SQCMXnqWmNMhZHQNC0/+8tf89Of/ZKvnj7BC4lWCllWLKzNsoyQMLaiRBC8o/cBiEiVC3qhFK7PPq5PP/kQkRLbN9/jq5trjJ1wfv8dXOgxixN++vwlVz7x/nd/n+l8yqFLnD14yL7ZEZ8/xxYlWuX/rnejwdoojlYrTo5WOW2VkciGwGjFg/vnfPDBN9m3HXz+lN2hoe27LLlOAykl9ocdy8WStt3xzjtv0vWeL778nP3ujp8FN/rwct7YJ7/5kD44nj57hk8w+H4830OekJIxubbMoaJ7N7DtW97/xltMl0t2h4bz81Nudnumizl95/DO8+XnX/Kv/sW/YVrVXD44oywrkIY+5eBYqxVSBqa1zQ28URglidGxbyUhCNzgSD6gpUIbjdQeNXgm2lBbgfAREbPnNA0BOVEIlT23WkikSlTTikMXscaQwoCSAqEFRcoTY6M1WmTvnvMjNliJcbPEGMg8Gt1TDp5llMMLNUrZUzbJCxjzysZf+ypnhiyPl4kcRP41vaSQaKNpDjuCy8+EDy572YKimExyYSzAGEMKkWa3pawXFFWNcwNSBi7mC17u9iQESWhigv2+Qdr76MLSN1sQGqkl3jt2+4Z2s+XmyUvuvX2JGxzROdqdx6YZtjRICa7tsZMKbTPiO7QDxhb4GNCmQOhAYQ0y1aPKJmRvtetJzr8GqhitOWx22Ufd7FHlBGtLwqwlyi2ibUHlDYQUCmlLkioQUuY+RBmUEigD3aFHSoHRmkEO+d8XgjAMaFlQTTTdZkNpFTFFhEsoYzlsG2IS+LsND+494MX1S4bgEb0jScuh6Ri6JktjQ0CHxOACqesR2nJ3e0vTBKwyLCcVSsuxkRlv7BQpSss/+t//dyiVz+vJrM4e0hEtDpkGJ2S+lwN5sxpCxDuPGzzqFSlSpXHgJggp4WLCh8ShddiiyPlHXabneRLO5UDe4DzWKPqeHPxrzevBmkyBGBJ3L7Y8fXHNi82GxWxCChpiyB4jqdm3gSgTd03PZLqi7SNdCAht2LaeaqZo9wNeSAahGIIYQ78tXbsnuAYRfYax6AJVlWhjKQvD+fER906WbHYdt1e3uK6DYgopb+q8y7Rpqww4hxESrTR1NaHZt1TTBdPZiu5uQywcRaEQdY3Vc07vn3J8fsKL21t++tOfst82CCIxOpwbQGkikcYNWGPz5z64MUz8d3N9vaucmF5nlrxKEdfK5ARxcto7MScYiySIUeTGqdCkECDmPANJ1oOrmPIkOIKR+vXv07UdhS0Z3EBh9digBYqiyKnm48Q2xdykGWPG0NsxkE8LzGyCTgkRBnx7oCDLnerlEmmnRB8QeJq2x05maPkqk6VHVBYxBHRVE4LA76+RMZAah7AlsUi42xa6SC8d182Oddfz4P4FQ8yJ0jF5rDUkImlcg87qGqFrqnLG9fU13WbNtCgZdgfOVqf85H/6F/z6ww/54J33OX/nTWYXZwxSoooC0QeuP/uC07NjtLQE5yiqmlTVuChpr6/QXUO1WGCVIKSBlAJtCEyXp1w9e8qQPFoYlqsVSuUcmaHPq2UjZCb4GA3asjq/TxcTcr6kPjoiaTV+1+O2NwpMUfLGt76B1ookBZN797GTkuaLL4hXaxSBu+sn/OmvP+ejZ3dcasvDN37Is5e3/OiHP+T03iUxeQ43V5xOl2grOb08pS7vMdEGIQyqVBSFgDBwdDRDS4PzkbvmwNW2Y9v0HLodd/uBvY/c9I7WC55fb2n3PW/fO+W0fslqNqFJARcS2pZ4v0VoxfzoiOnqlN7MEEQuLxKIQFlOqRZzhEwcTSvczYE4qTmZW5598hmHJJg8fESTJpytZkyqiCUPBlfTGh8TVmrMuEWsS/16sEDMfrtYmjFALzCpag7tQJKQQqCwmnZo2R0cm6YnioJn6yveOF0y9L+7A+o/xSWSHjMxACHzNDxkY/puc2BRabBqfEmq7EWSufmJIW99RMyeEKEEqQ95C63IeUtjqK2Wgqqy2KJDi9ywyiTQRFYnC6wVSJkbJjlOGZWPWCVoElR1RVe3Gf3sPGYxIYyab+ccwQ/MThckEpXRmDqNL9dEWWqsLSgMDE2HjILD4cDW9fjB8emnj/nzP/tLnn71NA9dbIlznuPViioGmuB49NZDOiRX2z2b5sDdfodzAV1YtC2wcsJhlGfFFPn4o1+w2ax5cPmQibaY+QwpF+y14DA4VFkAcGgGoiw4Wq347KsvOGzXlEWdt0rOZRmLzCGeb739JidnJ2RMO7wCDqQUmE4rfvCj38OF/L08fX7D7rDFFiUMv/UTrDdrjpuGq/WBZ0+f8unHv6BtdszmiywdkplKtdvvEUrnwhXQ2iLGxszajCS3Wuf7IAk6F3FCoaYVoi7ptwekzOGdR/MFO90itcE5x/NnV/zlX/01h+YdlqsZs/mCYjphIJNYq7JAyUCmJmfTdwyJu3EL4IZA2wUmU0s9LREu0g8OVRpUSjBkD0NQEisF0rk8qa8NUgkKlYmCR8e5yDvsI0J5CpMx+kWpmVqJkSLDPTI4DSUyIEmkHD6LkiSfYzaEzDJTqUYpasrfjxxXT33bM51akJlyqIUgyZjR4SFQ/A5JVr/rS0pJ02bvphgzamL0yJQHs753NG6f/TNGI62ibfY07RZT1QQXmVQF8/mc23bINL0x6Pr2bs311S1hNkUMQ5a5Wctuu8UHx8e//BWzyQxLYH68Grd4iXBo8LFAWJPDUAcHKWGqElZLQj8gRxuCa1t8WaC0yaRFn3D9kJU2SuAHT/COZnsgtS394Njvt+im42gyRcyW1NMZ7cuXBFswXyQKHVH1At93WQ4cs4w5hkDoFd0AyQqKUuMGjQ+Z4qmlyTTM6Eg4UtIZVa8zJdIPnrYLOJHonj5DxgDLmq7zdF2HI3J7c8vZcsnEmjy8DoHUdrgQKbWixaN1Jj4iixwpw6v7N6uWJtMK13lOL04oJ2UeALxq8oUghoASWeYuJeOQXiB8HuLEUS6bSIikCSkSpcjhtCoTLreHfmxCJV3vSDGQfKRrehbTmpe3+0yJI+GlBKVR48C/73pu11te7A40bUfXtMg0JfQOoTUxkmtI51i/vMLoiq4C0PgkcV7QtY4ey7aHJgikUfQh4bxnCBLQuBAw2vLw8pRSG6wtOD094t0371FZw8vrbf5ZpcCniEfio8+ydqVQUjP0LVVdE5Kg6QeSNRAEt0+uWM4nzE6XFIsKocEBL/drPv/ZU7766hnNYZd9dykB+fdFwtA5hr5ns9nTDT11VWaoyO/o+no3S2Qs4zhkHIlHv0VQ8ursTRlLKkUOfYwx53jkidYoGQie0hiCkMiUg+GklAzBj+hZMTZBCqkE9pUJzrn8shxHzEZr3JBDyVJKLBbzTHnpe4KEIeWXzWK1JN4GcC2xLJBSE33PbFbjUyQ2Ca1zno2UmmhKAi2pvWF/9RnFYs5iecHudgc60O1v0ViUkVy1BzppsJMJlQiEvqU+OSbpmmFI9G2gHSLbbsPhq8+5HAau7q75d3/6E77zztuc37vkdrfnLgwMQ0/btRy/+RBRWvY3N7gY8XcbZsZy6DpOTi19e6BeTChnc3a7HdvHTyhlbh61ikgip9Mp+92W4mSFe/4UrSSL5YKiKjO9JeUwv+A8LnqUVZjJDLTm4HOzKIoir/BNzlqRUmWEvMzFhNYmH3iAKKbYIwtDYvr8mslXT7n2kn/z5I40WTFZnPLksy/4+3/rD7je7anLkrv9AaMkWiUeXqx4681Lmr5FItCqoOk7rBDZfBott23gan2D8wLXJvZDwqG5bjv6VLBvA4+frbm9XuOT56b1SCJvLGseXR4hlWF9u6EoK+pJjQkJH3KhlkigE2+++xYApTEspyUyDrx0By7vXzCbLzisVhwdnaHmFXc+0D1/yY/fPcGrXMRPlcKOeSaltmiZ8vZDGpR0dG2bg+kgF+Lek5Kg7QcG70djPax3O5o24WNiM7QIqZhVE9b7q/+0D/1/5CuJHFo9nsEwbsyCSAyDI43FHT7kjJiYIIwvwfHFqIwawyYlpVF0g8saPZmLJ2KeKtdWs5yVeBcx0SNUQiqd/Q6FgRgIfSD1A+HQQwyYBIUClxNSMv0OwOf8iWhslj4h8L1HWUFRKjqZ/WSyUEwKnXM3+oHb2w37uw1tO3C3XrPebNhu9vnXFhV1UeH7jrqecXx8RDkMPLw4YbGccLfZMd0vuOs6th9+hPM++5dCibGaqprRNgekkgx9y4unX3L94jnTyYRKFwgh6YNn8IEkIkU1Y7464URKykPBfntHd9iRhMCWBc61IHIe1enxGd/65reYTOus/3dhLChj3kRLxenpgu//4Ft0fc/uX/8l0+2M7WFGRhckhjAgk2S3P3C33dAcDgx+YBhaNmuXs87cqzBKOWar5NycoqhpuxwgPgz9a6mZVgo3ZAnSzW7PISSWRcVd09EngSkrknNMZM42ms6n3Ls8JSH47LMvOFovWZ10HJ8smaxWTApLG2DwmdBYlyojd2OmyGVKpUcEcC5QTjRSRFQKyOiRKaLLMssUQ8hRAF6RQiKkBIXFVCVVodFK0vcD/SFgJkWWe0mYGkUpwJLlqVGkjHJGoAj5/RZGSEBKEBIx5AFliiNSOQXEmEkTQ2K/bzg6nqCFHt/B+TP2Y9H5dfYsee8Y+i7L+kOfm0FrSdIgjSWlkOVar/DqKv/8zfoOo0uMLemGyLOdB5EhByoF9psdcbGgWTfMTEFocoi8jzl+4MX1Hc12w+LknElVorVgslpmOdVmiz8YVF1SrhZ4FxAqvy9tUTCEQAhZzivLCqSgu93ifaDr2vy9ddl/HYcB3/YMXZ+Jf87zm9s7NNCvBpZFzcn9C2RRsrtbc3lxgb99gZ3O8IMnCoUq8oZRaYlPAlFYkjB4t8mbi6QQSoOyRJel0YU1EFwG4OiSwz43aiEm1vsbqtUxZjLHJcHN1TV92xGEYLffMJtOKYxBK01IieAGPvnw1zz85ncojEQjxnDU/J2IfEfmYZnI/iI3OAhpvI9HEqocASZCvvbJxxBHeW7+NfvdjqPVMjfNCQSa3nu8B+cyXXU+Mex2DYUW1IVm6AeGwWGVwuQJEaXVtKogCkEfIkorGAa8VjQONoPj+rChLAxt1xMSJDMBPN1mRyESbXAMQ0eSYETCBwHJE5Jh3zoGIVh3kS4oSiMynGRwED0pBeq64vJozntvHrO/OxAQLKcV3jte7Fo26x3eB2IQOJdD6uP43EshiMlnCaMpGEIeKE3KimG9pTqfUywmzC+O6eJA6wY+/PhjfvPxx1itqaqCFAaSDKNcsERpQxkD/eCQ2qCFpN1saZo+3y+/o+tr3yxBLl5CyKvRlDKlKucYRCKvOlLG7KScvSTJ08++H7IPKQEpvZbQZDlqxoALmc31LgyoaYm1Bi1/O2WAhC0sQ98RYzaxvcqA0lahEgwkYnDUszlSTtj1HZOjI7rr51hRk5LH+y5P4/ohp6BrgbECpSyUlqFybLdrRBBoWRKipG97ko/4EXSxbQ40XY+ZHXHoPHMRUFqQlKLdrEltj1Y1u33H49s179y7oJjXnE/u88X//RkXyyMqU/DV51/ys1//gm/OVpxdnnP86D7ldIKeVFhr+NWf/RWHxy84ev8R1dGCYmrpNmtCCrhmT9g2WYLhM03QGoXWOfzt06dPCFpxtDyins4QxtAMA/VI/7HWEp1HKMtsuUBNajCWiETpApVU/i6tRkkNIk+IiqrIwXsiy0Ly2t9ij49QRyeIxRH/9uNn9NWS+2+/BwreuJzy1smSqTV8fnVNKCrOz04pFzPu3TuhVJmKJgtLCok6aaZFxXbf8eTuwMYFoihQSjCZSsI+0ArLbb/h+dU1d3c79m3HdGYZhOUgJUYZUlmxPezY7Q5UZc3p6Sm98wxh4HA4YLTFlgWzaY0tDPN6wrQsSX3L7cuXrOY1KGgODYOuaJxnIgKdUDyYLylFQRCRIAR+33IyqSBl+ZARGjPKMfa7PbP5PPv3bN5YaGPZ7Q6EmOj6AW01TdOBMAQymrRt9pyuVrhuwH2NvQYARglUIhdsI51LCZnjAnwOy0wx5Ibplal99CYR0msza+azJQR5OCBSxMiUBzoiT0WJHkNEqZQlwL3HqowIFzGnt+MDafCovAdG+YjwufA0WpCix1gLUhKHQJCvppiB0HuMUdRFgRCJwii0FkxLhdWSwTuWixmracUwOI62c8Lg6F3Ph9OKz754wqHpESP2t+0cj958yPnpDCkkZjLjyc8/5vn1Hd6PgVLj2Rl8Bt70XYNSCltV9F2P9y1+3ZEmiyxXG1oigiQidYJqfoTzIWvjW4cPeWvUtm3evEnFfHnM+++/z/e/8w2sHc/rsQFKJILL8BNVWC4vz/jBD77NZtOw2+3xPvDkSTsSrDRCSG5vr19HRyhpSCT6vstI4OCIQoGQOOeRYxZJ1zXE4OhDbqaULtDG4F3IjYQ2GF2x2zfsmgYvJaZUTFdznPNUVUVRFhij+PY332F1tMqo5tWKej4nEhFaUmmBayPWaETF+J0HQshwhK4NEALRRaKXtIcOSBgrCEMe2qVhgFggoia5MNLVdPaMWJPzmbQghEgKo95fpNFbkR1pMuZMpuQzNthIkDL7xBi3bWkMyRUpkpGyuTHSUmcgh4hEn6VLfdfySp0nyJvYGPJmKcj8z76uV4jxtfQ/RZ8b89ZhbUk1q2iajpTy6SBFYuja3IT4ga7Zo7XNQZ1JUFQVd88+Ya4DbZtek3U3N3fUyhJlGjc9nq5r6SNcPb/i+XKJGDq0shSFQUwrXDsQu45+I1GlBQRaSZJU6LoixgYxZM+tVgY7rfBXdySfpXgpxOxpHmVh9bSm2eX31rb3dK5hVk+oqpp171i+/Tbuyy8JhWV179sEtycMPn/vKaFtQRIakQRDUoSqQok9Sht615GkJIRAwhAcUCT8EEAonAu4wTE4T+cCLngKwIXA7YuXtMPAy6vnDMGzWqzYt13G1lcFeM+w89zd3PEAwfJ4jhAKH3PjuVk3FHWB0XkjqKTE+wxaaddb6lmdFXrBgzCv/XUpJZC5UcpL9URdFRid84jEqyGAAIVCCZnVB1rgGZjVBX0/0LUtrnfsDw2nqwUmRcrCYEz+b6aYgV61sZlkmvKZs+961u2Bs0kOLfbeE53Du4YQPKnL6O4UE95laSAkhNJ0PjGVBb2P9H0gCU3Te5yLWULX90hTMpsuuHe8ZFjv2N7cgqmo65q7uz1Nk2vVEDxCRJKAqlKIVmAKk2u2JHOTN5kzNYbDek3vHILIoAKzyyPu2j2ffvYbfvOb34zvjICeyHGrL9jve3yICDluKYXAeU/bdfgQcRH2+xZrw+/sGf/aN0t5q5C9R7/Nf8ibhlfJ4q+O4NeBsilL3ELMN7xzPk/EfJYWKKkJImtSo896akFisVxgTZbsFNbmgxFQOhvWirIct0oaKSRuyGb5qBLVfEIKgdD3dH0gtZ5yPkHNz3C7DV3fML84JnR7+v1zjJggZUnoD4jpgpQUs0XkKkSmF29T1pbrz75A+pBBCSIb67ad5+AC5xJkf6CTAaMrjCvwG8/ybEI0JYWM/O2/9YdM33jA1d0d0/mSR5cP+Ff/4if87R//mKvbO4wXnE4X/PiP/h691hzP5lw//orF7IAAZkdH1PWUgcDpvUue7rbs79a56AsZ/amQiNCTjKXHM68qmm2Dconl5Qmtd0xtTuoevGO2mDGMTP8kZZYQWIuZzIhCEIYAUuSHT4xrXq0JMeQX/ygDUlrhkocoSIWlrab86dNrfnOz5uJozsPjkuHuJd9/+DYrnXgSHNuu4XQx4+jsBLtcgMiT3cWkJiBogifqxE0/8Phqze3eg7WoFClLTSsibVXxyeM1v/roMd0QSEYyP12i6wmh9dih42w6ofYDbd9xdn6CUprr62teXm0wZU01nVGUJcerKUWRAzW1kqQQ8SGhTEVl4cNf/gq9PGF1fEnyESMttbVMSosSEX9omdY1i+mUNJKsUgRTGozWrDcbiqpkv9tRlMXroUJK2efXdT0hJlTKhYyWBqk8PjmWZcGiLNk0W7rhax609OosyFmSiJRlRlnO5BAxJ68nkYEWKWaplAhZR5+SAq3yRDJFREooJYgevMtUJgjIJCmUIBaawecisbAGqyQypbxtMhJRWfTgSb3PSmMlKScFvZBUk5inpwmCjwil86ajC7h+oF7UGQzR9wTviKpAK4Me0blladC1Zug6UkycXxwzqQxfffWcsiw4Pz/HOU+Miecv75jWJfOjI8y0JLQDX37xmEPf0bQN1hYoa7JfSuQNXUx5ej14R2EK2rbLjaSSDF2TYxqSJwJSGXRhQAnc0HFz59HWoo1h6DvUCOqZTCc8uLzg97/3bd5882H2zIQRVZ3y6Da0HW4YKBdzdGF5+OCc3//B+6QE//xf/oSbmyn9SMhLwH67BiGYzBYsj8/ph4bDfk1yjkQOT2XcfGigJxdRuW5UKKsIpIzGhSyfFOCFw8X8Plotl3zx1VNSklhj+eb7b9H7gaqqqeqK1WpJms+Jo4++MJZ+zG3RUmJkxJaarunzEE1A3weG1mViHgJioDsEZO/RUqClRIjwim8PSqDrMjfbUiJNptpJmwu+4APCJ4qyBBHBeYxMWJ0leK/UGoIcZJ0VGuSBgMifEiFDJPAxs07GWA5Io8ojIWWiKvJ7MY0whzxUAEQkBJfBSl/TS0tFWRt2ux1SZP8yJAqruXd+BiLx7NlLrm52oy3GAyLnDKWISDB0HYWtCSlSFhV1Gbnre2bTCW3TUE2meUigFMPguNvt2bYNzdDx5O4l4cOAVN/Cpyfce/MeWmvKWU30gX7X5EFMyptQlEJqjSkKko/Ezmeyoi2Q1uJ6l2mS/QDBZ9VHYQj9QGEVne+YTWraqx3JBVxK9O2BPgRYzunXd1Qnb+OefQ7WEALYogCpQWpiiqRuyI2RiEQp6dHcNjvOTIE2mmqWtwRh8FkK6AdMYVHaI1D4zpNMSes8/dCzP+xZH7ast2tqpTmUFdWkxjNK3tZr7KSmmk3QpmDocv03DA6pRqpjkqQAkAguMrQ91hbEUZ0kRsPeK997Gn0AYhzcQKYvv8ayjc9OYpQzxixXVQoKq5gta2a+oDk03F1vaNuOrZRMpKJSElEUIAXWGnxwtO1AZSy+dQQEF5cXXDy/QA4dWiZc74iDQo7wCeciQUNd5uzRlEZPrtKEyBhCnQnRzeCwRmeZ5KjWQUgKY/B+YHtouT4MnJ9NefHyFucVJ8c5E1RbQ/Qjhl1LirrgsO3Q2mKMoZ7P2O8aZNOQeocoDMViwr1vvMVdf+DzD3/Oi+fPWa93lIWlqkpijISQ1S3b/QEpsg/wsM+kyWFwOJ+zDLeHjqQM6OJ394z/zn7n/wRXJvWm3H2ON64Q6XWT9CowL/gwJoVnk+Kr/0mlIQm8Gxi6jrKsUFLSDS3GFq9X5koIFtOa+XJK8I6yKJACnHPEFOHfExCUZf6Shzi8znIahoHONUghESHjWZNLHNqArWroelazBT56UvCoyjJsPTo26DprS73rEc0GoUCXBT54ZILd7Zow5OTwofPsekdUitVxTekcbT/QhJI//3d/xY++9x2Ko4DSCd8ObL58xurhfVZHS7p9w+/9wY/4x//kj/n88RMGCYXQ3Hv7HR794ANaKemJhKbjsz/9SygUs/OH1NMpwoXc/d+ukdJgrMVFh9KGoW1IdLRtIuiSupxx2B+Y2opD0/LGN96jOppjp5MsxRvzfAKRuiryitsHhqalnM0o5lkuIEdJSyYu5YZVqvHwiqC0QCTF0PfosmZ6doqazKjUU46mFkLHd966z4PjOf1w4NNnzzi795D7xxOmywl7mQkx2uSchjZEXuw61vsWU1parYilwTUtp7OSOEhe7nc8Ozh+8lefMvSwOl7RHG6xY/iuLhQLC+lwTbCS2XJB1weeXN2QdE15dEGz3RL6nmq5JAo5+iMy2n7oe/bNhuOzFdZIvvXBBzy52TCpLIWdEGVgLhNzK5iUmmlVg7LcNAfmkxqSZF5UGJ3lo1kqA9babFJ1LueE9QPGWsKYQ6bGQUQIntIoUl2ymsy52+049I5t2//nePz/o11pyBvQpBMkmUlGAYQLTGSGKAQXUEbhg88ejUiWfvV5CkqSo4VmJOulLHlSQiBS9ssEN6BintgbqTFKIBTICLH3BASEiDQKVRiij4R2QEkQUZAODrQh6UDsAn6IyFrnTYyPCJ/omw6hSia1QQZBoRUiJYaYmJi8ZRgGT2ELqqMs/2ubhtJqLi8v2XdPWB0VvLjaUJRTTs6PKcuSqqq4aTqCkDgfkcqQ0oAxBmum9MOAdz5nbihF2/f0UeSNe3dg8C6/yIJEjL6IenpMVS8oy4q+79ltbihHdG7wLYqCul5ysjriDz74Ln/37/yY6aTkFWVNiCxHFDEybA48/+hTlo/us3h4SVFavvW9b7KYz3n++Cu++PJzupTzxowuIO3pmoYYA7YsUcaOWTNh3JblQiqkSPIDIYwkJ6nGd0Z+7xhjkTJnHpEiREGI0PYOHxNixBfP5hOSEDmDB4U1JWVVMqlLBhfwMZFSlnzLkDeZSgj63iGQtM2ALQzRp7xRchERAmmMtvAJZBRopVFak6QkahBaoEqF8BIlNbq0mMogZKRvs4Tcu5DlhiqgFKgk0SJDkZKLvPK+K5Gx9qMZCULKVD6RSM6ThgBRZtmqznCjTIuMiBiwISJ9DmB9tZkNIpGGiIzA13hBXVUVWiv2+10+N2OkKApAcNjnYdSkLtlt81nqXcySSBIhOEJ0WDXJkn7v0LbOGWFhTwiBerqiqkt0CPihZ79ec3N9RRc917s1V5s7fvEp/NsPf8733n2PP3J/yFvvvIEqNDJGtBQM+yYPeaQELSlFxvGbSYlU+flNbaCa1gzbPWH0uZGyl9u1HSJkP+WiKrEpYZdHVFaxu72iawzr9Q2PvvMd/KRid/0MudvS7htUYdF1jbE5my44DyLR7Q8k8vZ93w88uV4zPz9F7BoWJ4GQElEKoooYD86PflEPpqpZb/eooqQLkf1+n7MEZT5DysIyOIcHktZEITg6OaOaTvBeYqc5NqKeVNTTTBjdb/combN9hqbNg1jXv64Zc7ZYHh4mKbPEOgMgcyAzOZw5t015TJ9337lR8T57xEhZUksIOQg95o2tLiyqMFRGU2tFOykpZ4a4i9w2e87cgGkCyTtC65nMppyujtiv70DIHDNwcCgTCa3PpEolqIoCnM8kVSdxASZWgwhoXTLEHOQttcaFiLSGEKEqJkhtuTsErteRF0/W3O0DylScz2pEyD+tdwEZA3Wpmc5q2rsNuiyYzecsjo+JMXH77Dl1VTE/P+Ls3gX33r7PJ198zpOnj9kfGrQ2zObTTMYUuTE9HHa0I5K9rApCKBhcYL3Z0XU9pIwkdy6H7Npq8jt7xr/WzVJK8bWJNMY4bo5GHKnIUIdXuuoQMx0oI8VFxn07Twq52ZFS5ymi1SBzroWQCqNNDjyzmSomxvyAADifp0Np1GeOCh2AnHAsBO1+j0DRbBukEAzDwMnxCV3vubm54f7lKXZ1wqHbEruW0FtKc0k/PCZ6TxQldp5Rrc3tDceXZ2xePKaerGi7SNsOxM5jbYU3Jc0QmK+OefD2Q65+/RlKTLjb9Wy6jqvbO84fvUW73VPXE6ZHRzR3G+rTY/b7A3KzZkgBOV/w9PlTLoLk/u99n7V3XDx8wM12w9HJCT/7pz/hED3f/wf/M8zRnKHZ4w8Nd4+fcv/d9zj0La5voG9puz2plNikECGHvCljSEiOz8+YLhfousxegaFHG50nQbMJUsu8JRwpSno0JUcpXh9GWQU0TnZSHGWTIhvshQajcfS8/e7b/B/++/8d//pP/pg/+/kz2tuON96/Rz3T/POf/hpVn3L/eMnZ6TFxljXkUhpSEmwdPLnbc70faF3PVGkChiF4klJsup7OJT5//pi//utPubk7UC5O2bkeUSzogqVUksokXNtxdHTEtJ6ydp61FwxTjQqBF1e3zOsJCEXT7GgbxbY0XJ4smFYWmXrOj48oipwnsDg9Ze8jRW0otKCwmnfPJxwXYswdKHFRoFTB7tBxeXycg/LGTCEfAtHngYB9HcSXZaRNnxsnqQVVWTJqbVAxcjyfc+h6mn7g0MPT/de8WQp+3AZlY3QaC8giReqYdfvKMJ4VBkLE7Xq0eDWcybKxFGPeroT88hcp05LyIiSDILRSKO1QUWE0SDJMIvhMxnMhYWzKEikfEErmDdEAQsnRK5NxzELkhHmE/u32qxtQk0y404UaYQuCYYgoPFYIJmWmKmlpAI3rHVJoDr3n3sU5s3mFR6NVQdcN7PtI5SIDmvWhpaoK5F3eHgslx3MvBzEGl4loQkn6vkVrhdIF0XWZMCp1pueVBluUWFtDjBy2a7r9Bh89XXNACIE1ltOjE3747W/xd/7mD7n/4AI1bkYYh2RARhvXFW7fcvXx50ilmd87w9Ylx2fHvHH/jGKMfuj2a1qyjGVwPS46YE4KCaVtnvqPsssUM5EwvT5vUg4SFpGYFFIpXN8hyjIrGyIkKRmGvFX3qcMLTRKBxdECkmRW1UQC1r5qSKCwGiskMWl6n2iHgaHzhCRJKTeF2iiMBFGanDjZkVPvtaYoDUKrLJdLEJMEn4Dsb2q3LaW1COFJQRGGjJj3QySMQBOZxkxB0piFpEaAUpbLIUdfhopj/MZ43pLydsB7oo85C04L8Iqk879HdOAcC6nQXY8syryxGgecw+BJISH813dDHUIYJZaGwQ0wYtGd92x2DXJ/IISA0Qbn3WsZYkoxgyCUJomc2RNFlj+nqmJx8pD5dIaxCqTAdZ7YObbrDX17wPcdRkoa33MYWrbDnpd319zc3fK//G/+AW+984jaZhCSThF6Rx8PaGuQIWJnNdpItCoQrUT4SCgCpi7pd/vsOzEGho4wDCTvqLXk4WrGTiYWVua8tv2B3d6DkHySEkcnJ+i2RfQ9Q59wbUAf5Xyv5CPDYQCRaPcNxlhCkjzb7mlcYL9tsPOSIUXKlGDwIAocEJ3DTivwPckl0JrbzZq277P6QWlmZUWtDaSAc47BB8IoHa2XK9ohZPBKoagKSxCgrCWmrAQYhpaytCMhD+pqjjI5X5CY68dckbyiKmc5XhL8dov0Cp2fS/8xZ0yhlKD3CRdG2bKW3NxuiC6fLSLl+BcnPLI0mKpgdXzG1c2B5rBjs2+5uz5wspwSh57kO0RRomyW/iWhiDHXSglJ8BE9KShEzGqo4CjthNaDNRZrDXsX8p9ZZmS61pqm6xDGEFLi5c2GanbGZh+5Xe959uI5Ryf3OZ7URLINQilFoQzWamLwFNMa7yRnlxcYI9nfrVmu5kwWU+6/8wbzs1N+/stfcn19hZJQVZYYYVpMsLaAlLi9vuarx18wdD1IidaK2XRGIOG9o64r2s4RXQRhOOwP+P9Cw/sPX5nQ8yrPYXxxjka9GH7bPL1Ci3vvsVqPk4yI95HoPVJK1IjsJoVMxrMF/QhuqCd1NrRGj9L55vDejVL9rFXvvaPvBiaTKq9epUTEiDGW/a5lNlsSfWB3uKLvBqQxyCTYrfesjpf0+466npB8Rzs4ZscXDPsNIgrau+tsunaSarqkHgaGwRCDYbcf0EkhROS62bJ3AxfTAuF2GCPZ7PacXiyYrC6QbuDlk2ecXF4SjGbXHKiait2Hd8xVQWgH7tcT0mLFRx/+muqNR7z3t/+Ay3ffoioMm8Oeu+s79vsdb7z/Pttn10zPjkky4XZr0qFB1RbdHwibHWLYYkXEB7A+4cIAtsAWJcerE+rFnD44hg4mpcV1HVJJzGxKNa+JSZGkQhUWO5nkQ3tMg36Viq0Ur7ceWXqZv2sXsuFbKYUQFpk873/vO9xefcVPfvYVJZ6LkyVN73naSn703Uc8uDhnmMwoZ1MG51EKbtqep9uBq71ne+iZzmtCkuwGTyc0kcTd9Us+/egTfvHXvyShWJ69QW8VZjalDyWd97jg2Hc77l2egi14tm246geitLjDlqNa8M13L1nNl4QoiQL6fqCuTAaLSMG0rjKyesRmihDQ5MTsxUTy5nHN/ZlBh4AVku3BcUiaQ9NwvJqhtMhNrDa8olVNJhOMVuNnRw5CFfm58d7jY2Q2Kcf7WVAUGu8Cu0NL4xKf3m5pu//0z/5/zEsFnwuWoMYpeKJIIYMvoiD6gNaZ5KSMzh6klBBxLO4GkHXMOvYRK07MeSYIiR9cLg6VQhmYSIV3maqWYiJGRdIwuJj15Ycu05R6z3DocMDgEmH0BqXGEQePtvmV3TmPVYloFcpoJpVhVlv6CCEGutZxPC+pdMIIgXmFok4xNwRSsdkPTOoJq0WdMfxCkqQBa3AoTDXFrQ8spjVDYXjy4iVRCHxw+C5mX0UKtF1HSJ7gIim5HOY9ZtK9WkjEmKfT0bu8RY6BFPIUu2/2GWqhC6b1jPffeMQ/+u/+Ie9/+y1sZV5PuiE3ZYSQw1JLy73vvs/hdo1rWrrNjklZUNUVbzx6wPFqyXq/QymD857gc7GWoqfrGmxRjcGXBc71pBSA8Rwf5Svw6j+fIAb6viMCk8UcJTTe9UwnFSdHM6w1uKRo+sCsnBCSIApJOSnxKdC7iA+CGLKfMybwSSJSoDSSaW05tB6UQI2m5TgazbVQoATGWowA3w554h1yk59pWYnQDXQym+Tl0IGWxNIQwkAUgiFJkJGikJniJRNamNz8j4MoqQSBQEpyzCLLMneVchkYyFNuUs6WIQmii6RBoowhxOxZ0iFhXED2PbLLeSgBnSVPKSGSZ9Q/fS2vBCxXJ6w3GxIH9JhfU5ZlJrS5gdJahmHAxzDS1Hx2JY5ZjiJlII+IkmHI1DqlBcqY7OP1WQo2BE/fDeiyoihLmq57XeNoZUAIfv75b3B//P/kf/Xf/LfcOztjdXGE0orQuixz3RxIg0cagyoUUkmU1cRos6ne5YDp9mYzSt5BV0V+zoceIyK1VbghkFJkvphwe7PGWs325XN0DKjZBKsEw+Dpveew2zMtCqQKo10C2kMLc03T91zvNhQx0u737BWErOkk2Rwl4kMa3+cCbS2h66A0tIP7f1P3Z8G2pedZLvj83ehmt9rd5c5OylSTaizJkiVZHGMsY8PRMTgwUXWqHAYiqBtKJjCuoCgILugCCG64wRAUQZiLCgd1KI6Lwrgwso0tt0eyZCmlTKWyz92vvdrZjeZv6+IfewvVsU8obeRmRKzYueeauddcc47xj//7vvd9XkKI1JMpcXnG/nRGUxaEYWDn0hVUVeViSWmq+YIkFUKDKQpEoRBjdlISkqqpiKOxTiiZ94alQag8rXLOkVQGnyBykSyUfFgUPSiSH+xJ0yjxVsrgfSQkGHxi2XkGn+Xcw+AgJubTis46tM7gqr7rMYXGEZEpjnJ4KMoKI/PrlnKGLmr82DiK3hOUxg4R/2CKb2p0kdCFoQ8BZRKl0ZQGkBIPeKEIwVNKgRtVWYXWVE2D0Jqb946ohwt0+wobV6O5hlCKwQ4YDUImXIwsNx2TwzmzRclksc/BozvcfOV1Umy4/PhVLj92jbtHR/zG5z9H13cUVYm3DqMkQ7ScnV8wm0x59PHHQakMxRgGIomjoyPOL1bUdYMcKcQJgdDZCxaCx7pvXrH0pgA0//Af/kM+9KEPMZvNuHTpEt///d/PV7/61a97Tt/3fPKTn2R/f5/pdMoP/MAPcHR09HXPuXHjBp/4xCdomoZLly7x1/7aX8P/jrpKWU4Ugsd7P6ZPjydpyt3cBzEoIWT2vLOe6ANKClCw6XpCiDjrcIMj+WyGSzHrxgsJs0mZpQgy61KdtfmiiTGbXVPWHjsfRoxs3gBYl9OZhZJ0rcP7iB8Gbr1xm3t3TkiyYBCKbWcJfaJdd5gYEd7jqoZBlXiX5RV222ONYQia2ZWnmF19C0HVJFmx6Sx2GHB2wAvN1cuX0VGw3vZEodnd2eOtj17n8auHVMZkyYbWKJEzDqq6JPY9shv4c3/2zxJSJuC856Mfodnfy5IsF3jl88/z3C/9Ou35OevVGq1LZIxUZcFyvUJPZ9S7uwzdEuU6qjHRO/iADInBOqKEaT2hnk6od+eoqkCWJgcsmhywOF3sZM9SyrlV1XQGRmGjJ8Qc1qbGrpz346ZGyJGMF0dijQSRtfJKCYQyhEJz6fqTNCVU4YxuteI3vvIaO9MFlxYLbh6tOVtnkzlR0/aR9RC4e7blzt1jVhdrnE8sNwNn24Gb98/4wvOv8mvPvsobR0vE7iVmT7ybZvcQXU1BVUQ34M9PaE/vo6Y7DNKwSXBqA3Gw1HbD44e7vP+dT/Lux2d829sv8/ilKVVVsb8/pyklEEhEJk3JzqxiVgl2Z4b9Wc2sLMFZ9kvNno5UUqCl5ub9M+5uNtxdbRiUwadIu9k+LISscxijETLlSYGSOZx1NLgTczq2UmPBmWIOqFSG9XaLD5GbF1teOrrg9nn7O7h28/GP/tE/QgjBj/zIjzx87Pd2DQG1HpA24rseOVh0cMgwIKwH70fNfswyKQmETByTguxbip7k7Qg5yIVSDGH0hMQcDIjCxXxDTiHjlX1KpHGtGm0ESJ+lTbF3eBvwfcC3eWPvrSO2FikThVbEzTZLAVPKr9NHTMpBohGBG6E3+5OS3VrRGIOGPEVMiWHwDM4xWE8kcfnyLrownF9sSRF29nawIRLIsrJ+cLiQKMuCqiyI0TMMPdZbUghYaxlch+v7DEmIIU/pfIaC+ODxIXuCMuczItTY9DLZfB6iyyAYU3L18DIf+eB72d2dYcoyy6b/K0AAAjLCUFLMGhaPXeHS29/CzrVLVJNmnE4Z3vHMO3j7Wx5lVtd5KpIiRhr0ODmWUlIUJUU1GSlO411D5BpEKEVZNRRl9VDi7b1/aATf2dllf28PrTQC0GXF2bKj99A5wXk70A2e+/dPuHHjCD9YgrOcnZ7hBpvBEqSM7DaKppDsTDRa5w61EhGjsmeo0pLaSIwABkfqHXJwSB8QLo5ekJ40ePza49uQ5ZyDJVqH3XR5qvRgc21UhhUlkFqNTSgBQhOjICVBFCr7HEYcMjH75XLR6IEAbkBYB8EhYxgja0b/KIngXJ584ZF+i/ItCo8mYroOdbZE9b/zrsvv9zqitWbSNHkyr3NsiJQKITR9P2AHx+A8znt2d3ao6uKhxwXB2LBSo5c6UU7mlNWE4BzR56yq2DuGdsD7lGVJZZlpbaN3ujE107LOcAnvuHn/Nj/3a7/M81/9Ks9/6QVaJ5CFJlibKW0h0J2vRjBHQhqJGT0ns8uHVIsF1aTBVAXEQBocbtvmEFehkIWmLDWFlsTesmgqYhgoRWJzfkq3tWxWA1sfOe5blpsuSw+lyqGxIjGkRO8Tg0/0LmCkoncuB10v1/j4IKo2S9y8dWA9i8UCXVb4sUgyRZ4KT6uGnUlDYwyl1rjtNhfvQmSZs1IUTY2qSroYiMYgTG6gCyHRpkBIlSNmlM6+aJH971JmiasYVRhCSpQ2eQ3Pw+4sw5b5ezFlSFgiy3kREusF51vL+WbgYt0x2Iw7l0ogVM7mU+Tm04O8Mu8TVVMidC5olMq5UEVhMpjDlFTNZFRTMU7qBzbbnpA0QZdEJYkpoApJaTSzRnNwMCdqgYspE59TQhUFQUoKYxCqROsaKSTL+3d4Zr7hu/eO2G2gmjVonZUS3kHfDUQfKUtN3VQ00xLftVzcv08za3j8HU9x9cmrvPz6K7z82msMzsE4IdJFAVIx2HwfOTk+5kvPPst2tWF374DJfE6SMkc3SIXUWbHhvCeGyM7OHs1kglA6g4m+Scebmiz94i/+Ip/85Cf50Ic+hPeev/k3/ybf8z3fw/PPP89kkrWCf/Wv/lX+43/8j/zbf/tvWSwW/PAP/zB/5s/8GX7lV34FyEXLJz7xCa5cucKv/uqvcvfuXf7cn/tzGGP4B//gH7ypFx/jqBWVWQLjx0mDFII0Ljxu9MAIJFJoYhIUY5egiImyqvFJUkiJCAEZE5YsD1AkZk1JioEhBGpdEr0fiTdjKK7RDDbQth1aZSx5GjsLkZQ3Od7y4gtvsL874+rlA+yQuHfrHpCoYiD2ltWde6xee5VJjGzOL/jA/+FPMbl8jfWNu5RB47ZruoueyRPXWDtHkondR6+xPV2ikyDYjtZGkBVVPUeyRkrJdFJSK0NdFgjtSMYRlUU1+wjTIKQmWIeuKorLB7z9iWuE//Kfqadz3vfeD3B2fMz+tUNuvn6D5b0T9OCpvGe4WHP35ddYHE44P7rL3qOPcOV972JwHrluUdYyCE+XPJOmQWnFvK5IzYRZMx0fk+jZhFQWyNogJBTzGVEXaJW7rC7B8cUKoTS7izlJC4QxmWgoAKHGCVPuXEupcpcnxpz7QUAJkwunFDi4dplnnnmKixe/wsX5lvtd5L3ve4zbt88R0z0eWRyQFNiYODpr+eJLr/LFF2+wmE1413u/BSsqXj854fnbR5xfbBGDwyiDrWakQtLJTHDxZQ29x54coQGxc4gsJ5yebxAEhqFl18D73vYk3/r0JQ4mihQVN856BuuZV4LOWYw2OdtEqDHnS7LbVMQYcMB8WtC3G67ODUpF7l+cczDbpapnnG2XNGVN6wLL1jErJPtFgUpQjabV6aSmrsxDSasc0bcxxpEepkaQSUIXmvunG9res43w0tma22c9vtu+qev2wfHZz36Wf/Ev/gXvfe97v+7x38s1BECvNqjFHLXXABERHZIsMfM+55rIBLLIunYRI8kOOUndQBIaos8UTZEbJ0JK3BCIMW+2PQqRRAaRREgqjdNqgSoy7UxLictcS3znCdZn0ppzOTtDjBI0a0ntkAOcRU6GDzZQaIlSGpFACTDkRpExGi0BH2nKgpQ8WhuKELAu4dxAUxm2XcfJ6ZKzsxXeJwbvaNue1arj8v4OnU/0AWbzetToZ9DBfLpAKsnJyVHe2AWfQQ9IhHqQh5YLukTI8kIkUuRUepmTO1E6+xE0iros0Uqx2WwpiiL/3g+yfUapi4hhlOJlMqmuS1RZZLmYzNSpKCT7hwf8qe//BOerLZ979jlW7YoY8zQlPhDLKE3dKIierRvwo2xH64KqqjHVhOhtDoMd0e0xCHwI+bOrasqyJAnJxcWaxe4BJ2cr1ustpSk5Od2wOzMcn1xkeMjVgtkk0XVbJmqaN6/eY7REovOG3ef7kRCCUmYqnhQgC0lUgmhGabge1xyydzN2A0WhkXp8t6xF+ECIES8VOgkwGlnkBkkSYEqdpxwhIpTI7RmhMuYikRUbKWU5XkpokadXApDBgRvACoTJ64WMDike+Dk8WiWcSqTkeJhV43rwEjX0yHaLNL+zjc4fhHVEkCVMSub3NMRcfAy2J47NXLf2KCVoJg2MtMeEQEnFdLpgMjvgYrWlampSiBhTUuzs56akAGczTCRFTwbdHrkAAQAASURBVJRkgFRMRCKlKdA6SwCFzOHByijO2hUvH93Bv/oyR6enfOuH3s98tsD3A8qU4ALtxZbmcE4cfcZSgCexuHwJvGdzckZMuWWXJKRxCqGEQimD0o6i0BmS0+VzIwZPt16iyxorFRf9wMF8RtcNCGnwNhB9IFhLLBxB5twiHwVBa3rrGHzE9z5PSguD7waSkkhtMjhLClw/kIJjO7TsTadoVdOUGcAltcIPA8r2OFvhk0AWZbYBqBF0ANl6ISQyI/tQRTni3TMQLIVMqUwi/2w/SpsL1Ai1GX3yoyXka26lONbC+f/1ITH4iA2MpFlH8B5vLaousQn6LqBlZFIZBu+x3UA/DOPal48YsvpJ2EhZGqqqYBnzehwYs/3ImaKD88iQODzcJ4iSQUsWE8X1xy+BlDhXId2a1PaZuBcSdV0hasV2U9C1iq7doo3mM7dXHMir6GpKpRUHOxOO7t6lmu5SFCV1kVgsJpSlJCWH1JJyNkVXBZ0beP2V17lz5x6bbcdm22VioFaYIrFeryEJJosFm7tHnN4/pm37PP0TifUq3weGwbLdbDNkR+fidf/gkLv37uX+1jcxf+BNFUv/6T/9p6/7+7/+1/+aS5cu8bnPfY7v+I7vYLlc8q/+1b/iJ37iJ/iu7/ouAH78x3+cd77znfz6r/86H/nIR/jP//k/8/zzz/OzP/uzXL58mfe97338vb/39/jrf/2v87f/9t+mKIo39QvkILwISeKsoypzYnUu8gUpCkJIedQ9ajl9zJ1N6bKJdjtYOh85WEwIocdok6VjRU4wb12kNCUkcpo8ZLSh1jjr6HuLFKB1HgXGkBGOQmTJRlM3aCXphtw5s3YghkC7WiP1lPOb93n2P/wMO6uWnaJg58nruK2junRIsXAMmxUheS49/a5MiDm+h3eRozfusrO7z/m6y2PuJGhjpBIK1Xu0TxglcX1HaQ2x25JcYn7pCtvoUIOnNhXrrkUBZn9OUor9WPDBD38bk8M96rohJcFzn/8ip7fvYO/fR6fI9vQYud3y+qc39M7yxPvfx2A7tudrttbjmwmb8yMms5pCazyJ3dmCcrFDUec0bDd4jDRIXZKEoJzU1NMF6CLnlvQD3ghEVdOebVjeOkHNKp546unsnxlTsR/ILfOGKpFERGpJIiKTIEafkeJImvmCj33s2/m5N17h1c2WWC5wXqCKHfYvH7K7aNjGgVt3L/iVz7/E/dMzLtYdaXaVW73k2a+8yGvnK6wydGcdot+iTYK+x7vAbH8fMZmiY2B77x4YQ9w9ZFrV2LbFb9fU0nFYN/yx9z3GH3vmOiIGVu3AjWWLxVAXgnYIlFpjh566LBHeUzcNQsU8fvae9dCjsDx1bZ/HdmecbZZcP9xHklh3HfO64nzbMSBIyrBabhG7U8KI+lzszGmqEsGYMzFOAhOSMGJuhcqG7aKqOF1tWA+BtYUXj0557XhJl2A2mb6paxZgs9nwgz/4g/zLf/kv+ft//+8/fPz3Yw2JRKTK168wEdHbDHapJOW8QhUaIbJJ3W+2qJBwvctFFAldJdDFwwk2CUIeSRCIBJepzUkCUhEkRJspUFLJh5EGSkJwguAT1keCzTjW6CwhJKgySckhCD6itEeKLP9TSlIqhSkVGjAx5utDayqRUEKji4gSKd/wvSN4x+1bx7Rty3bdcuvuCX0Q2CFyfHLBctMhi4bzTc+LN46opGQ2m7HuWnxKxBhoqilNM6O3LSG4LC1KYZTcRUTKpmPSg/DYOO6VR2Jg8qikKYoGNwwYZSirgsJUJCIhhLwpHN2gwQfUeNfKhLi8mXHtgKmLvKmXcpxMZxlZ2ZS87Zm38d//9x/n6PiU128nrBuwbmCE/uK9zbSx6YxhGPBDQklBWTc0zRRd1KyXPTGGPF0RAkTAW8dyuaLQBm0U0hg23UC9yDKYmAwIhQ2JJDV+sJwvVyglMt43HqAYyXNS4geL81lKPis1waQMcogCN96TXIBYGqKNGRGuJEkbdAyIAaLS2Z8bBUok8Cln9wWZCyepchGmIPosicutPUEU4mHmTFIyd7hDRAaB1DJDK2IimdHVnvLUW6RM4JOjd1SkQHKj3Ny77FcrDdJIZMqEyQgILwjW5XNGvvli6Q/KOtL3PccnxyilHvqn5VjUJwQhZD+Z1iV933N4uM/Z2XnOPiKvFSnJhzIzmxzOO/b3Ziip6Nc9Wucg3+XFQAyR1XpDTFAUNbPSkGJk8wDgkEBLDRHuHN+jriq++JUvc7G+4B3veoYnrj9KrSWmKIjeo+uCclZmiaCSmAi+SNSXDgnW4rZbhMxQLN3UWWLbDcgE9WSS9zxdR2mK7PeTAusGgq7pREQWFSHB1nqGGKkKRXABqYtcFMQxJ05EhFAMMZv2u82G6eEhw/kFKSQoxjw7Mq2YmNBScHJ2n8PFglLmyVgIHq0jk6YgKY1AUjY1kjR6zVVuYqWET4GYRFapKInQkmAHZJSYIpP7YshhtYjsAxIiYUzKk9fRs/4QLDauPTFlz3WIGWTS2pCHeELkmBDvEUnhQr5fpBSpmyJ7IcdG0GbwhBgwWlJohZEqDwNiHAtzj5QiN5TGCIN+iCATtu0wpsQkj0WjCkW7WrGY7XJpX7IOBZs7PcP4860PFGgOdmtOj7c0VcHQNETXMpnMOTtJ3B/2aWY79N5x694pg42YmPe/aVwbo8iTnyhS9q93K+4fn7DdtviUwWgpBU7OlgghaJrJw2aAiCVS55iZwQ344CnKDN9JIyk0uITUoAuVvfudJThPWVZY983zBPyu6rDlcgnA3t4eAJ/73OdwzvHd3/3dD5/zjne8g8cee4xf+7VfA+DXfu3XeM973sPly5cfPud7v/d7Wa1WPPfcc2/uxUs1FvIyG+ZS7kyGUcceY54+BT92D+UoC3OBoctdGekC24s17eA5bwd8ALyjVAKRAjHkjrGUuVDyzudCSUqizxMlby3BW2IMdO0W5+zoo4lIBHZwPPLINaqyRpmCuq45Oz5GCUVQmmE70B6do0LWLZ+tlnSrNb7v8K4nAWq+IFQTzu+e4FZL3MUxs2mBHBypDxgyyaTUCbe6YHl6DkIw39ulc5GynhKExlc7hHJBMZmRgmVz8xZm6Fhd3EcagTjf8r1/5I/yP/zp72Oyt+DRtz5Bcp4XPvcs/mzNye0jRISL+3dY3b/NzS98gX51ToiJdrXl7M4RQUooK2ZVTSk1hTYsFjtM53N2d3ay6VdlLbbd9qggUFEgA7hu4M7rN7j32g1e//ILfOWzX+Tn/+1P8cs/+TN85Tee5e4rN1menI1wB4WUkJMg4nhO5KmSHXqc8/gQ8aNsJqtGBFefeorTouEXv/Qcj19/gp29q1x98lEOrl/CS8+dO/f52U9/ns++cIvn7yx54eYFv/HGBf/2Zz7DF1+9z1kn2Vx02NUFLkW6ztGenZPaNcv7xyxfe5Xzl18kypLY7OHJKGcxXNConrdcu8wPfce7+NPvf5RLtSe6nrPOI0xCmcDgPYKEjIF502A0aCOIbkBF2HQDW2tRQeJOz7m6O2Hd9+wvFjRSZXN4FFysOrqYWNmBdtuzO5siQh59T5qaQkm8sw+vpwcZZM77cdMfmU9rjJK024711nLc9jx39z43zlusU9lnU7254gTgk5/8JJ/4xCe+bq2Ab+4aMgwDq9Xq674AvJFEmUgxy1OSSAgNFAK1W+dVMmUcvYie2HdIFVHKo2qJLLLnK42m9Riz9C4kcEiiLnFJ4HwaiWtxDOVMKC2zIV7KB0xmMJlgZK3HbQei9QjvUSHkG7pUYECIPEk3RlNOpyglWMwNuzPNvJAczAwzDbMmS2+Mkjhnid6zXrYc3TsjBY82gm0/oHTJ9etXqKdV7qoKgbOWzXbg+OScZdtzthl44dWbnJye4NyA9ZaQIqvVEts7Yszyu5gCMeVrripLJtM5ZVVjTIlSJUrpbHSXkqKqMDqDLKqioaxmaCVymKXzGeyS0khQy17FKDJMgQeAApWNzWKUoojRe0bMMujpzpwn3/I473z6CZrC5Py7QueufcZsZOm1Uhit0UpTlGX2uobAdnlBt90SHxR7KRPPnOs4Pz2h7bbosqDd9vQ+8eLrR5ydXhBDbm7YKAhJcOXKPk8/9TiPXT/k8OCAru3YbLY5P6brcTYjwFWCWSmZl4LGCGqTqHRkUml29ycsdmtKLSgmBcoYpMnvUep6VAzoIhceaRgI65ZIwg8WbMh5Xyp7FFUxUrrG9zaEMHp30/j7pSztU4Ik0ujVy+/vA5+MFAJZ5UkWKiEM+X0PAREDgpgL4N0poswggxSzFV5qAUW+BpMWv/WF+wdoHfnt1hA1+lus9SQhUCpL8QpTPLQFiDGAt+s6vM97FKky8EQXFYN148/oUUrRNCWCiB8cw7Yn9A7bW3zwdF2HEGSZXFkSgaKqqZoJ0+mU6Ww6ekocWzvQOctkb4d7qwu++OVn+blf+HlefPU1un7AxkC/3uCtyzCPEIgx47TLpmRy5TKymaDKOiPnvRule2LcxErKZoYWgkI8UOmAFJJBRFRZc2V3By0kfYjcOT5j1Q7ZU4kgIvABojKU9ZQuRrQpCD4QVZEzAMuMhI4uX3eC7N+qm0wwNsZQKc1kVlM3FUoXRJH/PVMZZFGiraPoO2zb4mzOwtq0LRKRwUcuy7ogT2lizHK4OHrX4yilK0uNNtmSEbNV8KHdI3vn8zpuvccF6AbPuvOcby29j/iYvXkKhRscwfpMc6vKLIs1hjhGdwy9J3UDcXA5ZDql3ASWkjjuZ6VQeZqoTQYhGIm1FmIYqaxgCoOpDPWs4Gxzm1defI5f+NRPszk7yfaQB9e/dyTXs78osV2Ltz1lZQg++8mlMmhdgTIcna7wUaB0kadkUWDD6B8vFNYPtO2Ws9MLrPWcn18AoAtDUZbs7e+BgHt373LjjRt0Q7a3TGZzmtksk0FH6IR3NjcFjaKalKhslKKeVEiyfWC2WJDe/BLyDR+/Y8BDjJEf+ZEf4WMf+xjvfve7Abh37x5FUbCzs/N1z718+TL37t17+Jz/enF68P0H3/utjmEYGIavEbceLFAhepSqcDFkOon82gnu7ABJj56BPHJt+4HSGBQ5fM+lrOWeojjvB86BoU8czkvqIqDGrKaJUQQ/4HzuGmdNexa0r86XWYKY0uhTSFhr8wKZ95uURcFZf4FRmhAT08WUq49cxQ0WTUmsGsxiQXAOq+Gt73uG5mCBqg3V4YLVjXssmilRJlCaYjLDB4GtKtb9GXreEK3Enp6ymM1wbUtTlBidtfFFoXNSeIpECam3JJnQquD09deZzSrmj15nGCJhO/Cej30b3d6cy1evIYRgtVxxcXRCigVe6pwaLyDiafst7c0bXBzfR1U1YfAs6hmn1hKCo9I18+mcoqiY7OxiZhNq6/BKoqsaEmwvlmBgtRIEc5ENi22H3Xa4AQ6mC0wtidZz+ysvYd3A+77929g/PMzIXZlDyvJ5mXt53ns8ks2mo21b+naLGyzznV2sLLj63o/w2vJX2b98nebSIbv7M5pKE5ThxiZyxza8cXSDVb8kUKEcuDaPlqNfIUNCCoOIHolCzhroN6TtGdQ7pHoHV+SbqLaS0N9jZ264cvURPv4t1/ngoxWNjBydrbl13hLKGc5LXAwUSpBCHmVrPCIFjFJomRDRZQ+DVtTacvnpt7DeWJqZZBE9PkWkTpyerSmKOd22ZW9X8taru8xKgSQbr7VSYxJ57s5BTpd3IeOVtdHMpg0iRtbrnpAk5+uBk7ZnUJqlbZFJU5YV2zfpNfg3/+bf8PnPf57Pfvaz/6vvfbPWEMiey7/zd/7O//obtcJMNdIEYoroQhIBowpqIdFSQspQACkCQkdoErg8DXooYSSBGDPfXMx+9ZBQxuFsyFty5UnW4XuH0RkGI5FZtqOyzAWVNfA+ROLgkOSsN9n2lFHipBrzfTTJBspGYkYa4t6kYNKoUYIaQSVU8mSmrac0ebK+3Wypq5JhGOhax9WrV3j0cY0Pia6zaHmCNiVKF1gHq9WS89MzysqwXm/YrJcEZ6nqhvX6jO3mPGfHpNHoM0pQsmQtMZvvIFSOBnC2J4yFiSSvkxmTX6LLCiUEtSk4XOzw9NvfwuJgF6E0q7NTirKink4QI+wAIUkioZuS9GADz0gufEjKzH6cx596ko9++4d47qsv09+zyKJmYMDFDI8zKaGNyV+hoCgqmumUFCKrdpux4unBjEs8UJNlIiGJqjAc3z/CTOaocgehNBFLiIHpdM5iZ045kVw63GPWlJmw5UtS1Kw3LYvFZITSSKTICGmJJPhAoTWmVpTjRGdWa+J+Q7cd2G7smPOV/bYUimQd2iiwIRc2Nkt3UsxKDEn22BalIQJKCVzbEzqbp0qizhtBGzC1zpMwP1JJSUSfJ4OJUR4pQZaCZCC5OG4aAyKOoc0ITBJZaikyNU+M5nmmBXEkK76Z4/djHflt1xAhMLpACCiLMgMRtB69beHhxImxUZKnyZncGokM1jGb7eRA95iYVjO8j2yXK4Zyxmw2gejp+oGiKqh3Zswu7/Lsb36eduioynKcksRMgAueqiwxCsyIxN90LYeXLhFS4mh5wf1f/iVeff0V3vrWp3nkymUisLiyj9QPEPqS5AN62jC/coluvaZzFpHiOKkMBBfxCtrNhhASpjDZxiYyXZE6FzOFF0iXsjexqnnj+JzDnSlyBG4VZcHh429Dbc6QZwOTuiEiKecz0jDgrc+RISLvoYpxb6aNgaFDS02pJMlaqoMDUuFQpUFOpxDAO099cEDQhmLoSVWBd7nYGKyjKWSGdvmAKTX9aoMUgvn+HDk2Fh40BtLookokXAjcP+u4ejB9CCgZYZ0oJQkRlDaZYphyDIpWksIo+t5SVSY3elLAu0TfDehJQds7vPXo5MFZRPC5KBaS0uTmkBQRN4S83AoQSiP1CJiIOfOs7yzGBqazijSd8KXP/ya//uwX+cAHP8jnPvebXH3iJu/+2J8iBYfWkmhbLs4t927fgRi5tDPFTBbcvH0XtKESOjdCEASRG0DtMFCVhkmtUCZT/c7PViQlqKqGzbZjvdyiTcXJ8QneB5qmpiwUWuWM0vV6gylLdqsSYzTGjECMkRwphCAksny8MLgQKXTJbDJh0w14bxmszZXrN+n4HRdLn/zkJ/nyl7/ML//yL/+3fD2/5fHbLVByzNmRSjP0FoUihCyFiTHnFyDzORxDytkYQweDw6VAtTtDkahEYiolJ8s1vqqJceDaXoGRHk2JSom+7/Ax62qNyebgvm0ptGG1XDKdzYgun7jWZiKRlIrgI8EnXD+w2W5ZrS7Yv7SPqksSEj849g4OObU9kyTQUrD72CNYKamTIjooVMHm3jF6WhFtJHjB6njL1atPcvraORNdgqmx5SlGCPYO5qTtBZevXaNuFlysVgQMzWRCUhXxfEU930cczKmX05zJQUFdTuiNY3blACUEzXxKjJHXXnkVrTTr7QbnHL2R2KGjbzd01tMguPnVl3jbhz9MLDSPPfUunvv5n4aUqKOkqBqaxS7N/h6yKpCDpY8gdJmzDdYbutWW2f4ue1cOEdqwFYnJZIq6e8GwjZyenbK/t8sj+4dc3D/jq89+hQ9/xx5qRKrGRJYQpKzpvXvvhNduH7PpHV3fsl2eMasKbBLsXX+KS088xcdnB5wFyVQrhIJCa26vep4/S7widlhWu7h1T3H5EXzIZJ7oLSSbzaAiUQnB008e8vqtllUoKJpDgqghOqQ1KJNI/THTRcPlgwM+8sQh77o8pVQJtOKN0yWyaFifLYlmipESgaBnYFppCqMopUaLmENRk+dwMmFRFpytHfVUEqOkVIG+b5nWDa/cWrIJisJGUgy8/fCAw/mESmV5hEZluEN2lWTCkZAPJ6dSCGzfUTcTzpYb2iC4c7rkxuk5xXxGio4AoDV+GDLc4Bs8bt68yV/5K3+FT33qU1RV9d9sjfhGjr/xN/4GP/qjP/rw76vVikcffRQpQWmJLFUOoh0GpNCQoNEiF6BKInzeKCSTwAdEKTNgQKicnRHzBslGhwzZ89jIAMFjxuaJCRq72pI2FuciojToRYXSihRDppj5gLN5DZOlhu2Qs5pUiSkkNgjibIH1DjPmqBQhMZ+VFAYIgYCgby1FZSAkJk2ZJXsINsuOybSh7wbm8wU7e4vROFtwdrHBuQCqYDKb0FnL5uguXdeijSIRaMd1gBSww0DXd9hhhDqMcqw0TvwjgX7oWK2WzOa7dN2GfojoB4Sv4HPOzDCgpMprK5Fpofj2D7+fD3zk/ZRNhQDmO7t58jb2qrI5bIxt8AGhxENghlDqYZcxjdKYqq5413vfxVuffIyj41MCIKqSaIeReBfHQGxJaUqaZoIQkn7Y5gnsWCyJlDdKMYo82U6J09NzTk9P8UEw2V2SpMtNpaImipxZpnTBMAzcvX+GvHqZiVQUZUmhNaSIGwbqsswh61rilaDdBvohMi8laqRiSakojWRaa7AWrwVdjFjnIUVKGVFaoZNHOUccqWUORVQCE8E8FPiPv8PgiKuWsGqzjKiQoAK1FugYSEkgXJ4EiZgQWmdtqR8QWoEXCKlIImSEukpIMqgkhYQ0Bl0kFB4hM9L8QbVpFDDJOTjf6PH7tY78dmtIjNnXWTf1+FkrClOMPiaFqlSmaypF3w9s1i1lWSOkphsGJk1FWRtWa09VVhhtWG9OmVcGIRVDPyBEfChLKqgoJgU7B7voUuO9Y7vdZh/KSNsLKbJar2j7LSEkqrLkbJ0lo3VdMG0mvPjqq7z08ss88ugjvOeZ9/DO9Ay7Vw9GiMF4inhPvb/gwF3naLslWYtznmHb5Sm3D3QXS5JSbNolE6WpqxqhdcbDDxuSs+i6RgjNtKrpBseds2UO3O1agjRcP7zG8ZdvU5YlPnpEUeL6LlP6QsT6iEyWendKIhGip6ga6ir7G40UCOsydKue5rUzeChryrJGTecErfP0uxtgovEhw2dCCOAjUkNwDim/Jh1GZE9giBFEeEhEBokUkUldjvLTB5MlRipvhsv60WOklcxrTkpURiAmBikEZV0ikJlqKMaJK2QoS9chgs8kVTRJS+rDPQQe0XqiEJiqpJxOod3wgPSc97+ZYqllbp69+NJL/PrnP8966BFKY8qCl57/HFeeeC9ycgjB0RjBq6/dwijFzrzh+iNXePnVu1TaENBgxmgCoKgqktL4mHMdre3pes/eQuGGjvl8wfLshKIsuXxln/lil5OzS3z5S89xenrB3uE+pixy4K9SKCnZbjaklCFqaQTFCJnzCEVIVGVF3dR5wmUKTk9PODtf4t0wMgu+eaOl31Gx9MM//MP81E/9FJ/+9Ke5fv36w8evXLmCtZaLi4uv6+gcHR1x5cqVh8/5zGc+83X/3gNCzYPn/P8fv90CBUBK+BgRUucTJEZiEDiXpUTG6FHvHVgtNzmIrRvorUUWBWWl0dYytYEueC62jtsnS6J1PH51jhSCbTcQYiaIKZnH7a63uesiJFoo3GC/lpBOThfO0pIMl6jrmugClx+9Qp9szlRxgc721HWJKAv6VYfxBrdxdG+cEOeWpBLd8Tnx+IR6UaGV4OzefbY3b9C4gSYN9HbL3aN7tN5Ta83923e4sjNhs95A0NjOYk0ilhrrtkSlUbalqveYXb/CG59/Druzw0QlkoLNek29u8eDbJ3P/PKvYqTk9OKcxw4u0W5XuYova5qdS1RVyRuv3uKt73kfl69dIzZTQr3ArJdoU6CLkupgj2IyY/CWTd8x2EjEEIj4EDCihCCw1jGdzNg7OKQ7W6P6xL3nX+GNoyOOLu/yyPXrTK9ept92bFdbFvuLDNtQIt+UpeTk9IKf/A8/w/2144m3vZP9wz3e/+53MzOKFOBk2SJmc7pYsAkFfUxsnEe7xAv31/zmUccrd89hchlV7WZN8vn9LNOqaorplElToNsts9Sz3iyJaYra3acfHMI7DBLpOkrXs384Y1Y3vPf6hHddq5mJgMFwutxSVlPuX2xxKVFIT0wSJRKmgFJDJQUiBrQComdWaS7NSvp2iykVCIMRjllRE6zj7tGa82XPvdMVxaxhRzgeP3wHmiFPKB5QxMau+wNipLUD1o4A0pgbDKdn56wdvH664YWbx6Sy5PJUYGQ289qQddVh+MbTJD/3uc9x//59PvCBDzx8LITApz/9af7pP/2n/MzP/Mw3ZQ0BKMtyDIr8+qMoJCJ6lNAgFKRR2jWSLkPnCSp7ZWSKSJUIIiGI+RoxeUon5Si9VQKtIloFcHmK66MjJkVYd6T1ANYTaUFOcyd+RNcmNdIczWiyHzwijEli0WOqkqRLMOA2a4RSGMDo7HvJzryc4SGlpN9aykU2iCulabc9yedpS1UZrE+4ELFdz3K95P7JmuVFx3xnD11NePGlV2i7DikkdnBMmmkmQEGWHY9FVA4HfzB2EePSHBBREJ3D2Z6u22JMSV1lQERdVJCg69p8zpsCRWIxn/Pxj36I7/2+j7N3aY/kHCElTFMjiCQfc4YeOUdPjKTHZtY8jJJI5ElfRJBGiW4Crj56jT/+Jz7Ol154keV6ixGapsrGaCkFzmU0v1B5aqpNQXQeW9jceY4PzvXsdRIItDYoZTg/O4ME927fpZkf5I6o90i9R4qRaVOxN2lI3nJxtiRMS5rG4LSmqgx1YVAm+1bC+Jnb0bsgyDIu8VD+lIOPC5GotMAlMFWF74bc8Kg1wo2fR0x0waMmJYXOPrgsaZEoKQiDh8GBD4TlGq0V8mCCMolKelS0CFkRjfkacUvokauR4RpSKwIJ4Xz2QMUc4ptSIvSOQhUoIxFJgE8IlbOhkBAEOY8rfuNd4d+vdeS3W0PKwnD50iW6toW4yRtUwGhNitkj9/B1+pz/E2PADo6irCirhuBzFk6MkZBCppIGgwCGtkMW+fNKIuFtR9dd8Njjj2KdZ7Nacb68YBgGxDpPwyOAFKw2G7Q2LLuWs82G0mR8/Gy24NLeAXVZ8OprN3j11df5wrNf5Ds//p089czbMFWBNJo42Ix6T4lyMWNz83aWtAtBcJaYEsoYtl3L/nyH5AfKMssL7fI0T9iSyPAIJF5KDnZ3OF1J7NjYcc4h7rzBQkpcVAwuEK0lDg4zmeBEhx8suqhyZp0fUAiUEBRliRl9ekIphsEiJhVGZSDX3pU9MCWyqhhixFczGHPCZrOawVoGqzHBE4ZA3ZSjHC/Rb3uauSKpEdTAg2JopCzHwKzWX4O+PAhylzIHvYdAO3iM1hids/QKKZksGoLzLNsBrTK4JfmIkhrnQ55W+0DqMy0uiSJfz1VFc+kSyba4rsdUJXG1RqacuedDzGAVRI6xEOCcRXQdz7/8MhebNUXTPPSOOtvSrk+ZTfZQMnJ0/xSlSnZ3Z+zOp2w7x5OPXeHOvVOOL7YoXeVok0QmSgNdN7A3nSOiJox0aiEE927fwg+O+WxGUe1SlCXNtOHi4pwXX3iZbtsidW7cbmJgs22pJw12uczrhMjRJtYOkAJNZajrkrKq6a1lu1pibVZeFEUB3mfs+TfpeFNz75QSP/zDP8xP/uRP8vM///M8+eSTX/f9b/3Wb8UYw8/93M89fOyrX/0qN27c4KMf/SgAH/3oR/nSl77E/fv3Hz7nU5/6FPP5nGeeeea3/LllWTKfz7/u68HreaBhf5Cj5MMDc3U2TmcZXs5NqqaTfPELwaSZkLYDcRgv9pTYMYYqOIbVwOu3TumGgBscg03YIYzdIxg6y3a1xdssu6vratSZ5r0TMY8PrbWjltPjY+Dy9UeIJJqq5Or1RxicZXd/Tt1ULC4dcB49q85y/3yJHTz3btzi/I079KfnLG/e4v6XnmP52qvcefZZVvePWZ9fcL6+4OT0Ppu+43R9wdn6lOVmxcnJOck62tWS5HqEHdienEC3Rrk2X9C+YDhvmU1n3Ds95qWvvIRGkYaBnZ0dYkq0244bL7xCsgNVkiwOcjfAWksbLLPr19l/y9uxLnD/zr2MJJ/PefJjH8OXU7QySKmpdheYqqRppgQH6+WGm2/c5P7RGSkKSqUplEQPntB2+E3Hjc89x+qVm+gA82ZC2Fo2mw6SoO8cJycn2G7IEryUUZ8+JG7dO0HvXObg+lvYuXSV+aWrbGJBszjk2pWrvO2J6zxyeY/1EGmj5qR1nHWObT/wwu0Tnn3hBsGrTIwaWuLZXeKwRAiPNNDUJca3TNUWQeD4dIMdWkzfsjcxTGcFMW0pdM9OqZgbwVv3St7zyIKdJm+MnPW8cuuIm6drRDNhNp9TKcG0kCjpqHSkLgQpDBlXHQNXpjVvu3JAkRxaSAoMfgxl2wyW1+6c8psv3ubFV4+4f3TK0dER164dMC0NtS7QsiARRtJglirFlOi7juXFEhKZGBmzCbZ1gWXvOes895cbWg9Hy5bOJVJIY+iie9iF/EaOj3/843zpS1/iC1/4wsOvD37wg/zgD/7gw//+Zqwh/1tHPuczGlelhFQGKVQOPSRLOIZtDj1Mo/QEFElrhNHoB13Y0dekZaCQDsWA0gEZOnSwGGGRwSG9Q9gBhoE0WESIo0ckEYaciG6UQMlMulNGUWidsb8iN2simXinU0T6SCnyVFqNRKcYcqbH8ckGm7L0Mj3U3ieMlHlDHiNusLRtz+Ziw3Zrme7scbC/y9Bt6VfnJG/xbiB6y2a9ou9aUlKAHqUpY4mWHg4LHtRLJPzD7u1sMmcx30fqmrKc4Ed4g0Jjioqi1MynU9711if5o9/1Ma48fg1dGlRRoqsKHvRcR/y6SClP+mKkmjYPSYSjVjrfH3ggi0mZZKgE7373O/jwB76FxWxGoQ3GaIqiyNjg8YXroqAsS6oy/6m0yZ4AGAEW2eSNzFPFBz83xcTQdXjbZ8lg1TCfNFRFhe3zlKGqS1LwDMNA8AEzwgBiSEQbcuaZlIQA58suZyI5nydpISJDzKHDGlSKKAJ69HCUVYUpMkghkel1wnuKwlDEQLIjGAeyRC/FfM6PmYPRWpLtkd5jokMkl6XG0aLpUWJA6ISQHmIOi5RC5klTEsSksdtA8tlfQsySvRgSKQhkFCQMQuqM3Q8JpQwiSCR/eNeRoqyYzOb44PN0VGlSElRVna8xm3MAQ8ySzYP9PYqiYHd3B1NUo/ck09ac92OMg0ZrQ7fZ4K2l7zuaeUPXbggu0LUtt2/d5t69uzhnmU6n7O7scv3Rx5jt7jKZTh5Otmxw9NbiU8SmgEfgk+Do7JTXbt/meHlG6yxf+NKz/PN//i/4n/+fP8mdN+6OtM6SGCPFbJIlaDJ7obQpcwC8MqjJnNliD6MKTFLgAtFZCpmbEIqASqBMDmZNzrO32MFFQRsiXfTgLZ4sD63KGsi5Ru1mS+otwQ4Ekd/LXAnmTLsUPIXSxJgLgKIoOL+4wJsKvdjFDgFUSRQKVVdsA2xs3hsOvaPrLV3XP9wNu8FlyWSCdtthrcO7ACmH0Oa4Eh7CHCKZuuzDSMYbFU+IMdPOKOI4MWKM4CglaCWojcaoPGnNdDdJigFnHSpkb5Y0irKZYBFQFmy7juPzDV0I2M5m6I3MUm7vQ5ZijtNFrSXJ+0wNTNlP1LddlufpghgTq9UFfdfRDxakpCkMB/Oaawc7HO7uMvQWY0pKU1KZklkzpSxMpsKGPHXuewtBYJLE9gOrixWFKZnOp0znDVU9oWl2uHR4wLe+/7088653AHnPrk2B1hpIWGfp+36kHYvxd1NUVYEwBqlNboKcnY/ESMVsMUXKTJc1b1LK+2aONzVZ+uQnP8lP/MRP8O///b9nNps91PUuFgvqumaxWPAX/+Jf5Ed/9EfZ29tjPp/zl//yX+ajH/0oH/nIRwD4nu/5Hp555hl+6Id+iH/8j/8x9+7d42/9rb/FJz/5yd+yY/O/daSHKe6CFDO33YV8o+z6ARGzpCUmQdc96MyU2L7H9z3xoiedZwpboRRSSK7VEqcCWwrOukh/95TpbJoXMClIPjCcr5Eo9LTJOT4yV/N9P1CmBx3H3GUWMiM8VVNytl2yszNlGDpkEEymTZbDbHs+/Ee+g2c3Drne8Pz/8nk+8ie+m/3Lh6To2WzWmKri6JUbhG1Je/8eLiq6bc/90xNKJYlKgzKsthu6RiC0AeERtWFnZ0FVFJACLXB46RA/rHEXJ9RB4EzFZFLz//nUf6CYznjb1UNiUxIFHN29h+8sbnDoyYTzoed0fUEUkTC0BDz7b3kCdXSXV7/yIkXZMN+PXH76ac6uPIK/OM1dyAiuHVgtW7rzAesTN4+PmNYLyrIk2IBIAycvv8E7P/ptvP6VV3ntiy8wBMHrZ+ckWXDpsccIRYULie0qm2Q3qw2BSDkpiQTuHp/y3K1zmmtvpY6Bu8uWL756FzWZ8YGnH+EdV/doTOTkYk2LZLu13NgMXD20fPBq4vb9NSGVJB8Jdgmr+4ihw1Q5GFeJBGf32Nmd8MQTT3Pr1h3e/9gVXnztBkfLjnbdkyQUk4a6rrh6/THmleSp64cczht2G02IghtLjy3m7M8rCpmotSL5QDs4tK5pu45CCnQpETHn6jx6MEMysO5ajtcdbQBZThhsor9xj9OzU1ad4+jWEX234gPf8nYOS0UMA5XMfi4pMr5607YURiOlYtt2D43tbdvTDy0IWG97VlbSth2PXLtCG2FIsL7YMPg85tdKYTfrb/ianc1mDz2OD47JZML+/v7Dx38v15B8CDSZsyCIJG1INsudXHhwQwikmCWSKSn6VUezO8nhSGQyU5ISYkCLhDdA64hj7gYqEe2AFAqlR7mAGDuNPkDIaHEVodAC5wNlqQheZwu0C7k4UxqcR5uS1ExIQmJERNoBhRw19QKkYrsciBR0Xc7akQKKUiOVpGs7BALbu0zaS1mPb4xi6DNkZLvpiNKgq8mYwRPZLI8ZrEXI+BCRrMUo6BxJag8CXB9UTMaUHB5cQsscxF2amhgc282KyWyX+bSiqitKI3n7o4/w/d/3x3nrO9+a/Qgp5qpwhA6IlGVvIpH16SNwQI3nNyJnmgghRte1Q5BRwyEEko8sduf80J//H0kh8au/8ZtIrQlKYF2gqkr6ceOqlXqYNVY1DSn6TNBLYqRG5kDyqm4y3heNKTNp0A8984OauiippcBv1xzfsdCv2d+dsZhVFMoQbKJNPZNUYhqVgzhHKfFgfd5MukhdSJLLzbkUsj9WpYTQBiki2gcKIfDGIAoJ6gEAI5G0olASERxSaIxR6JTyWmbdOK3KeWFaKYqmQOqIktkfyfjZSx8yellEIGSJlRjP+9xmhwAiqixNJeSi3edpoKwkKUrk2H1HqLypDLk4le4bl/P+QVtHBIKL89McH2KK7KspH4Bv8robRzpvQrBcbZBS8Za3PsVLr99ESonWMu9TpMJoxTZmLH2KEesthS4Y+gFdKMqk8BjOzs9YblqQMRf0IufvVFrRe8G0yedmgaFNPdoYQgwgJdt2y5XLVzk/P+Hi9CJ7WEOebv3Sf/lFXnv5ZT72R/873vuB91FWBfViweTSJbanS8rZFL9tIUmSkkwPr6GUYPvGq1STBtu3CJeLmkSmt2klcS7LXKWAaB2LumYzdJwvl6idfZz3GCXxw0BINdIYRAIvFbKsCCF74CIJYwyyqUhBUVXZ6yikJDpPqRVnp6cc7B8SXE/cEUyrEivImZR9zpJUsmBS5LiF6EaP6LhxjzKhygLrbF5/pKVoqod7TikTBOhdwNosP55UOlNNx3VQSUlZFpxvetwIvXAxR0oYJVECqsKw7R0xSTbrgXlTIQHvst9RjWQ51UxZdxZ/74zSKGqpcmbmWJir0d9omhJhNMXeLkIEQpQZrqM1k2ZGa3uc68dbV2RoVzRVwXJ5QXCB2bTm0qUDBjswWyw4XbZUleLyfoEdHNKUtFEQUw4z9iHmRpLrce0Ai4LpfIoyWdock6AsCubzBusG9vb3eN/7v4V+sLzyyquAoJxMcUOPHDPEhBT46ClFSVXXSJmwLrLdtkiR862U1hmmJhRFWaAT8Du6/39jx5sqlv75P//nAHznd37n1z3+4z/+4/yFv/AXAPgn/+SfIKXkB37gBxiGge/93u/ln/2zf/bwuUopfuqnfoq/9Jf+Eh/96EeZTCb8+T//5/m7f/fvvukXH8ZJTxir28HmrmxVZKKI3XZ0XYuQmr7vmVQFpISSmiB8viEWRTbV1TnbIEXPfh2YF4Ivf/55vu3D72O1WjKd1VgbWN/dsH7hFXSpuPrM22BRIKUY8ygkp6fnLOYTiqJisAEhcpdwMptk/KSEdnDMm1whpwidtexevcRb3/MMd3/zWdqjM4azC6pZRZCgdxdoCeX9e7Src4qmJm567GpFoQtcDKAUQUBtNDvVhEYa6rrCknIGRiGJhWS2t0uMHVW3xL9+Qn/iKKsJB6XjyWuX+fxzX+GxD78fH/MG6NOf+nkKKbnYrFjsXcIauH1xQulaKmO4/drLPP2B97N79Qovf/E5Xn/9DVyMXL22z96TT9K/aIkxcXH3FGTJ0AUEhuPTuzS6xAhY3Ttme3GGkI6j23foVz2v3zvluRs3oW54/Jl3MZ3tsmpbXrp5k2o6pV5MCS53yUqfu5dJel544w43OkEhEifHp/zmZ77Ejddfp6k1nz1Y8N73v5+PffADnHU9n3nhNU5evY18/G2cDwse36356vE654TYAS5OkVhkEUnDBrc9Rxl467veTrNY8Ov/yxfo1h03zG2ci8SiRjQzdAFxaNnZ2aFSkicuL3jsSsnURJKLvHy+4ou3VtRNTe0GShFJhcBIkOQpWzWbUiuFxGGI7O1NabcX1IXC+sR561hHyfL+Ed1mQA+R5dk5YdjySCN457e8g49+67t55Nph9kSISLQ2o0oFDHagoULhqUYvxfL8bOyWJYZuQEtN326o6hz4ZwePi6N0L0lSksTof3dIzd/i+L1cQwBkoUBKYhqnJKPXRghA63yzDANSlSPFS6F0kyfWITf8VYIYctc4SRAuInSJcDZ3B7XK8oU4Ti6kBJmN9cGD8iAIlEbgrSBoBYWkX0WSlNiUw7RTBboyOXskRSqjkDKC0VnSFAIhSToPnUuoUjP0nvVqS13p0aicM7O8j7h+YBgC7abn4vSCk9MNNkqEMbRnJ3Tnx7SbVe6SVhXeZjpnkhpkbgY5F1CmwAdPGklPwKiFU1T1BDVSMZvpjG2/pfc5+V1rjS5LSl1xdW+HP/rtH+Kptz+OLlUmzyXyhn+Uvbl+yPuW8Sv5PL0gKyZHGl7MPkYSMpG9fiJvXnzwBOc52N/lf/e//36iknz+S8/hpSTGgcEHpB6N9ynSblu8cxRG048F7gN7N+RA3Ehi6AeCd7lISJYwbOmXJ2iliH5OpS8zm1fowbE+OqM7Vxzsz9nf38EUZZ4quYCpssxoGDxHJxs2baBOgjQrwMgsyQwJoXOuXFKKoGTeKHYdoDCFzp6JSQXbjiQTyQVKoyjK3G3O2W256JTEERwusgdOijyJ0zmgWhU1MoWMTpaSNBbGeZyWMcWEXDAkZH7/IrnISgk3RIpJTh9OSiNV1vkKKbMfsCyyF+r8a1K1/xbH7+U64qxjdb5kOplxbs9IIVLXdW4omQLlPcGGLNcVktOTc7TRHB0dEZ2nKgvUGD+AEAijkUrjnKPrWmaFoawqonOZAGciPlouHR4wmXacn6+w3rNxW8QASmrqomI2n1ENJYO3lKVh2w84l4lsk2aKHXq6dptVOTEQU2I79ESXJ8Lnpye8/OJLfPQ7Psalw0tMr1zCdR0nfaZ0mkZgvePWKy9x8ORbmT7yKPb2TUwSJJlhNzYEhNR4H7LyRGmUCbhNByFQJcF0OqeNHtGUaOdpbWDusrwvGkVI+fOiKMaCKofUBmsR2TaK0IqyaYjBM60nbIbIcnBMJlPkdgC9wQqFi4mhH+lyEYwDlyItERUCooQUM+jBYRE6b85xHhOzvxUYi99E13u2bWDVdjx+aY5RD5pG2RPonCeMkDEXI95HJmXBYId8PiiRp0JBcH6+QScwY26fiIKyMnRa4dqETwklPErApnc0Lo7rkQQtUTHfy3affiuqFKxfeglTZ9l0XT/w9mXliDZ5Ur6+OGG7ygAyoRXBe45PV1y+eomQYH9vxvL4gsNLB9w/OefOeUdRTnKIsM4y0RBAx2w58S4iTL5PFqYElYPvQ3RURUUftxRGce2Ra9w9OmK92WQiqVTk0jpTIwuts3RXRAplcn6fKTNASSqsHbKqQyrqUQk1DN94w+XNHm+qWPpax/C3P6qq4sd+7Mf4sR/7sd/2OY8//jg//dM//WZ+9G95WJ+wLhBCwvlISJKL8xXzScGsLtHGUKV8Uhs9JTg7njQNvY9EE3EuUBYlq9MLymlFsAOawFQl3vPUk1STkgdvU9dt+PVP/RLXWscT738b3XJFXS5AaHxyuSundR4HmoxIFUoTgh3pOAo7dBRFyXq7YTqZEGygrGus2/CW972b9uYd6HrOz84we1Nm+zvEoiDVNZeefIKT5zYUKIQ2JCQqJdpVh9MGWRXMHezvHTB0LUO7QSSBHzpC1yKn2UiuYsmyW5LWPWEZcmL1eof3veVJfua1N7BVNixuty1ffvbL7DY1x6sN+1ceZRMt2+i56Hvot9jVGe7fSd75LR+lKEue/fSvMP2e78IUgif/2B9le+ky9vYtalPR9pYUHCcX50Q3IAfP3eE4I0vXLUu3oQ2W137p05xtLQc7h/zp7/s+rrz7nWxFnur9ys/8HLdu3eCSejQjeX02Y/rBYaPnhbtLnl9K5P17/OZ/+J+4tL/HkwcNL3/5ixx/peWFL36Wz3/mo8wPL3F6fB/bBrbbyB97+3cio+TibEXcDIi+J52fEExEscUvz2kmM2ZXn+bWhWP7xku0JyfEJAnVIUnlQEZVSIiOxc4O88pweV5ydVJQCo8yC371uTe4bROUdTYklongBmxQ46bTEIacL6DqKSYFnry2w+HeBOdKLi7O8RHOj1uOtgOqMHSnZ8goGNqWXRzf9vQjvPft13j08oS6kiMAI1PX/NhggJw/5rZbLu6f5POzLDPMTBtsktiUKKqaMkT67ZbGKLxND8P5Bt+CCNT1765c+oVf+IWv+/vv5RoCIOsCtMgJ4EWN8IEU8o2ObYdOuTuffEAKRcy78jxNiSJvBIKjMCVJSgIaYTUQkVpnCdIITUCDrCNOePSkyf4omacGMsW8IU4JLciQGEWGi0iJVwojEjJ4iiJTpNIwIGqFMUX2COW07Bwqu+0Ytha1U1DrmqKYIUSWl4TOszxZ4QbPxb0zTk6WxAjTokA2UzbLJfbkiLRZI0Og67dsLu6PchLGzCQxSq8iyhRIpYl+gAdRr0KjpMY7j3WWS3sNaImzPcZolFKURlNozWRS8+6nn+DpdzxJURVZ0hcTQo7epFHDb7dd9kjJHJjKKC2UIeVw8pFWKrQCneUwIozRAmNh4+yAiolHH7vC//F//H7Qia+8cgsXI33XZ9N1WRJipO97nHfYYLGDzVIaAHIumZQa7x9gzXPuiTE1i8mcmUw0OMphS50c1y/vsX84J3jP8uSM7dmGQkgMU6r9Kntb+h5dFggpGSIgBb0P9DYwNSoX3nL0CimFEgGNIASHMAKtdJblKYlMkSREzlQyEqWh0MVIc00kG5BaZEO4z0WLqDPJTZZVltpJg0gj4jpFkEX+AlJyCJlA5KIZqVA6SwazYydjtJ0fPw8yuAIxTmgBGQVokdfPqv5dXce/n+tISpHBDjjncN5TFMWY/5e1qUKIbFRnxLOnfJXcuXOHyXTB5Z0Zq/MtE62QpsSoEqX1eK1FpBS03TZPLkRB3TR460BAXRXUxuBDoB16tiNMat1uUIOiaRpKXTErDOs3blMYTRhyduR6uULEiCLR2yzDAsHGWrg4Z9Nt6D7bszo94S1Pv40nn3yc1HfUl/YzzOreCck6SgR3Xn6Jx558kubgENnXdOs1SiSsdwiZG0QuJLzzI7040xmjgJ3ZgjhrsOst29u3mUgoCpO9Q4UeYVkBfBgnzlCUBV4b2s2KFHLuJSGhC/WgbGfwEeMSetsijcYrhapKrLMoAbFQbDuLtg7ZGIrS4JxHyyz19SHQzPKEWejsTXLO50DxlIgp30dDSAx9ICIy5IYHWUt5Eh5DxIecG6e1orWWFBLOBdbbnqIs2fQDg420bcdECgyJss6B3m3nGQJUxhBiJKREHyI1Y65cbmEQQ6DcWSDrgtWN1xARXJKEvkeTG3oxZGDZA66n7TZszu8x3X1kbIoV1LMZk0mdG3IpcfnxK6TtwBqYaUlIEa0VWoALGTkvpMaOES22d0zLGq01ptTYIUuxZWMAhVEaKQS7+/vcu3svv58UaJPvF5oCoiD6QFRZYlhUdd53dP1IySNL9Jo67wFDZOj/gBRLf9COKCRJZJOoLiQyOExREnwOhi2LIgdwukAMeerkU87dsSSU0qQYabcd7XLDfHcGChaLPVrvWBzMKaea1cYRvKG9vYSzFV6qbMarDNt7Z7jdCfPDPQohaCYlF8tzqmYHM8ZAWZdQo8zPbRxNWRJ84OBwn/V6S1EYktb0mzWObCTcbrdEKVjePmZ98x5GJiot2bl6lfM7DhUEod+glUErw9oHVq7nSlVT7+7hJw3teoNbrVFBgTY0wuC7lqqpiL7IOSKz/F7NDq+iioq3PXqNK49fxyXPG6+9zupiTd3M2YaAE4IbN25x0Q1jEvVAlRJfefkFXrh5l91JxeUkefUX/gv73/e93F6vOLj2KGY6o719h86ucH1HcB2nF2ecLFfcv1gyV4qJVJwMLXe3W+65nsbUTA4P+Nmf/xRvPzvmvX/kY0x2Frz1mbdz9+SYDZHzixX7VxdoI9CywLaJF14/4fVhh9WXfp0PveUx/tSf/T4uWs+z73oPn/6VX2O9WXN6fMTZzdeQUrI1UwTQrS5ol4opHnqPHFakcIHfbrA4prMDdp94Cyd9wLbnpPP7lEVDLBbYSO6YlhNkCOxNplzdmXJlWpPcQGkis/mcz7xwm1fPLaYumKAoRUC5SPSQZKAqNYlM9TKqxEfLtDIspiV2s2E1WC62gXurAV2WPD6ZQqXZSEt7fs5iR/LW2Yy3PTJlUipM3SAKgwwpSwwyI5joAs4H1ufHyM5ycXxOlLB7sAdS0rrEhRfcW7dsBk+UBiU0SSgiWUbhfEcpI1cu7XBY7PL87+tK8Ls7cjBnDg9NCSgrhB+IQ16onQsoBSLlbAeiQOmAUgVJjmGcYjRUiyxNiCaicKSQ5yDeOWTRoEuNsgohBqyPFPM6S6ZGn40YxjDr0TivhSDEMQ1dZM27RFEbja0UIliKlNc8pUzu3juPTBl44kKgqMqxuMlyQd872k1LWRUE73FD4PDKpZwnp/NUc7udsrx7j+X5Bdo06KLiYnUf72w2ajtJxOdJJLlokKoEMeSiTeROYQKc7+n6DeebC1RfUBQFKSYm9QRTFCgpONjb4YnHrzCd5NdK8NkH5UM2HeVdB9WkAZ+nbMRAcjkXKFmX85VKM5q3EyIpMhllxD2k0YAt8hRJuMiV65f5U9//P7D8iX9HPwxsxIroPErUhFEuU02n9Bfn2KEd1QGaFH1WDYzdf5AIkyd3SinmZcGkMFRCMJstmM8admpDowVmOmExrTg7WaKAJCTttmVnb5EbKDHHZdjBImXFatXS1YY0LRE6QxPi4JFk+ItKnkKC0oGIx0EupKQB2WW5orXoqiKJcSKW8rmUfM4dlIVGBYGeT5FKIE1JkkUOMY4BQQ6xRRfZn0QGTkTfjRaxXNAHm3IAuFIPUe7aFKNniTx1VYKkC0QM+bwvDaosUPGb5zf4Zh+zeQ4zdt5jtKFuJjiXr+XCFNjBYgx47wneo4VAm4K+a5GqYLke2G8aVsWKCxeoBaSYcM5iqib7cmMkeE/wYczjkZRJ472gLAtS27MzmzKbTOinU5CCddtinWPb9vjliqQkAlhMp5RGMXTZHL/eDtmzKgXeeYRIRFGwGQZ2p3D39h28tbz0ped4/InHKaNgr85UOqJgXs+YNBWVKVBaUU4niOmc7e0bIDS6qvAhZgVMDEDO9IsxUmjN2fkpfrMEbZDTCZUQJK2wPlDmJQYfApUxpJhzBBE5Py46T6EzgtvZDqM1q9UFNmhmu7uUE8PQO9J6Q7m3wDqbg2ULcM5je4vbtsg0pTSjl07JvKY2BqEkSsqxkMxNb0aYTYqR0ig6FTjcn6JHOma2F8Zx6C0IIeJcHCdILv/uPmIHT4ygkPTW4VxkaC2TOhMyq6rgYrkkJJMVDeqBpDMxuMhUZOl1oU2WDwroty1hu8WvN9nvKQtQ+d6mtWGiJX3bP1xLVhfHnJ/eZufwGgrFfNqwvzfnYG+HnUKyPj6jW7aI2YQrdiBay6YfqJspnVRoAkW0DN5htECavI+ROsu6+64j+kAzbei6jsLkRt9s2rCYzyirmq5t0dpgihIpHcF5XPAUHjAqBwkHHhLyHnhiu67LE1w/Ukz1N6+k+UNdLGWanMeHXNELEmUhmRYVhVZ476mqEiktweUiJMiAjQNeJJIUmKahiJHufIlb9zQHDcW1fZJzlEYzdFtUiDz7pa9y41efpxQadXUPGyPx6ITpdEqyHpki5aQmCEAtCDGM2lrQZpTNIGjqmu16jUKyDjnduSkLLjYb0qal7y1GGe6/epNHnnorz/6XX2Faljz5jie58fJXmS8qmMzY9p5mZ4+6mrDpO0iJSlcIY0jK0LuWupnQnS1ZW4coC0obKJoFLiiKyZx+Y6l2dhi2W7pli9oved/730u/aUlK8v/+N/8vdqY7rNqWXoFYTNgdDrn1xuvYmMPOpCnZuoG2v8tmDdOdPe6+3vPFf9cxf+JxxNNvQxU1xaVL3L9/xObOfY7WS145P+HmxTnBOvqywMTIynrueccm5hvFZ19+Ce89P/3cF5n8+/+Zj3/39/DxP/bdbJzn1tlR7rzFRBSZIGY7y4tf/jJH/Yy3lZ5P/p//T5zfv8UvfOZz/Pwv/TqirNl99J1U0nHn2V8hSEO9s0+3bfnCF5/nXU9/HDb3SA5EKRBFQmxWLC5dZXFwhaNtyACRdouuFwxOkZzNm4iyxGjFRAUuHewzrzLm86LdcOtI88adM4ZYMqnKnJXUrqgmkkVRMJ3P2XRbdATvI0aq3JEdVly9epV2vcLoknunLV994x4v3L7IGSlaMZ/PWd88ocaxP5E8eXmf3b0dmsUCJascNofHBUc3DDlBO0S8HRi2HXa1oahqTFORhKLvPUd9y0YZWu8ZQiBFAdLQBkfUOZfeeMuTB3MePZwxjd+81Ozfi0PVFbJpsi9HZbN+FCPNDZHJXQoSJgMikZhJ7rgLkXFeslCkpJHKZGmiKYgpBwkL06BEJClJaD3RGJA2T1d09qiImD0m0YWHExMtJYNICPsgGFuSUkHZlCACwluKWqNEoFB5WiBlQtpELRKV8FS7DdpkPC0kvI2szzdIkUE4Z8dLZvOaej7JnXCpsN2AX7fUStNow1nfYUOA6BFjQnumoRWAJwZP324zTECMEjCVJwkJRwiw3azx7g2uXn0r8+kcawNGV0Qv0EqR7MB0vsgT85TlJ8KMIAefPRZRyYwaHyy+Hwi9JfWZ1IVUuXs/WNAaaVQuAJQEZUhGE50jep9xyErlTXphePyJ6zzzzNu4d/+cotrQ+w1Ej+17pNQsdvbYbDcZsZ9AqDzZkmOIpreWiBuBClkSp4JD9FBMpxgRqUIktj1DDIidGULD3v4CO1icdZiyYH2xZLaY4ZWlKEvms4Z2iMxnFZWRqBhRcixyyGhiowROJJTO0kjvEzGInLHkLFoJiJ4oBdEnjEooEcDnzV9II2UvJUSSqEzAx/tIUY4EuxCQyWeppyky/W7cEIJ+QDVC6AJVkAtJaTJyInkINl8rKntBpDZEKRB4pM4ymoeyxj+kh9aG1XqdYSN1PebE5I2dKQvqWLNarYghIoRE6ZwvE8evZW+xPnG0bZHlFOdzkHqlJFpmP2Ezb1ApoAud12BTopVms97kYOLCgxAonahFbkpMJxOEULS25/a9e7TW0g0DIHA+k8S896jRLkAS1EWBUQolJI0xGKNY7OzQbzr2d/Y4u3GTUhjqvQMG71lcvYKwltn1a+jplKLUnL/yKrqRyHqK8OuMmR/lUy4EUBkwken/GdbirKWsSibTfZK19ClBWRAEJClQhUIWkn4IaKmZ7c+xa5sx2MowtC1mlI7GJHBDT0EOcl45Sz8M2OWacncnk0JdQOaQN86Wa6bTGn2xZTorsT7H5VayeghsEGm0Lo0ovDhCeSojKbWiKNSYZZan3d5nAISPEZ/Ax0g3PMCSQwiCfkiUhcm5VT7ghwGXJKLIO0bvLAFFs1iwuehIQlFWguAjDrBFkSmaXQt1SbeMsN5QTmoGFygP9xhiZFqV7O3tIkQ+/wbnmDXzcVcaicGN4BnBY09c4+knr3B1d8bq6Jz5fMZ0Nsdtzii8QlvN2drnmxYe4XtM51mGQFOWOGeZLWoKY+j7lhiz16iZNmw3Wz7/1Rd45zvfSVlW2c9U1wxDT2GKMYvMQ/JE7+i3mWdqiirHuxQGURS0fU/X9kgpcqZYPUGLxNW9Ob/yzbrGv0n/7u/NIXL6M9pAjEjp2Zk3FCLjc6WI9IOjKAxeJGSKeBK2SxR1iZCB3lrKQlNMalo/8Mgjj6ObEpymH3qGrqUIhsfnO7zaD0xne5TNLiEKmqpElIqi0vR9R7WYoAtDIMsD45i0bHS+gS7Pz9FCM51MMVrj7MDW5QyV+c4ci2bn2lVU3eBu3eQrn/kCV55+ksPL+0wXDYvtOasbN9Ap8cLdezx19TozU3Gwd8DJvbvUpmLwHiE082bG6dFdjDEMNrIeBsR6y24zR3mP225R0tBerFGqQMlAHLqM/jYVX3ruy3zxi1/iqaffwfL2EVNt2D3c4aVXX6J3Fsid6t5HOrJ3qIiKN1ZLNt2WYbAcnB0z3LjN5Xe+izSrsFJzEhM3ui1vHB/n1wqcDRYRE20MbMP4+g+v5AIyeM62G87vt/w/fvJ/4qJd810f+SOUS8HFxRmCa/iQ77fKCNLFDZqN5P/yt3+YqhA894VneeFzv8zZK8/RzHdpTAH1hLA5Y/AR3JrgFV/5fM8/OTvj9VfeQDczom8JF0sm5Yynn3gLL986xrpItBEDBLslFFPEZJE12EoQ+xUHT1zHVJrWB9pVx6yUfOGFV7h89TqHOw2zKlHKvDncrRuefuyAzbZn6HKXV5MgDtgY2Z2U7NUVt+8esXFw52zNajvgB4+0llQb7r1xi3SxRmhLWRZc2pvR9gMzrYnRElzuZDlrKYzCdZbtZovoBm585SW0kOwd7LPcbrh09SpDjAQkw2ApTc71WXUDKIlGZTSwCNSl4PEre+xWicvF5Pd5IfjdHbLOieCR0fMyBmYmk30W0mh0acCLhx26rK8GiKQoiClL8khZbpOCJAmN0AlUzrkA0LVChbwpEEplD0oCYbJ0xMvRh2M0wlqMEIhSEGwkGE0UkqbMXjFXKkocRV0jjULrsctoBPQD81LiFBTj41IK1hcdyQush6PbJ9TTOfuXZtjB4QdHt+loT1aETct8UuVMn6KmH7Ih3VRFznKxQ5YBpkgiEINFimL0JEwgObzd5l9aQAgOa3MmWlE0SBGQKocfO2fZP9hlZzEhOZenQ1plF41WmULqPSHlhsj2dMWw7YibLWE7QIpMDnezX6jUyEYhUkQETyU1dZVzmrQxqKLA2W0Ofh19Pz54DvZ2KI1GA4Ux2f+x7WjmM1xMWOfJ6OCM8tZFiTYlcdx0MuZUCZkotWJiDKXIagdhe6rKQAy4rcfZQNGU1LsTJouaEMmZNaVhdbZk/9oBQsF8UhDxFCbQ1CZnyolI6kMGB9Ua0Yt87qqMANcGSgloiYh5AxylzuGkhcheoZThLNHncEtIOTw2iZwJpGQuNI0GPU4IhcnTJSkz5t55RBJEzEgcDA9xv6pSuShQGqEkpqxQhQGpR/BEnkIhikzxGqm2X0Mp/uE7HtzPQVAUJULK7PUUCWU02mhWqyVKStJI+ZKaUb4o6IaB83VL7y3TRuWmh1R5mKEUkcR0OoXoMIVmu13nCXQSVFWJW1uKosA7n6M0tMaHHA/Q25yFprSiLismdc1mu8W5gVJl+Z7SGhU8WkjMWDQVSmcfi1Q05YT9S3N0TCzKfWSQ2HbL8vycx7/tg+zuzLm4eZv25i2WKTA52Gd7fJ8kc9MC78GUefId8++ti6ywSd5jpCAMFqzDt6cU8wVJQLftmOzNSd5TTkpCiJhJSVGURHKhqY2mMDLv+ciy9mgTlZBU45QZMozGDQMzJSjqgnbZYyo4unfE5vyM3WnJ9NIe3qcsaR0LH8GDDCW+Rrojf08KiRCBujLZ6zeCCOR4Ojs/Zjgl8CHhI6QQkOOETRqBkEVeeweX6YJCUBgwSbDdOFRVjrLYnqLQeG+JPhIiVKYgnhyjlGFwnpgCwUesldnzYx1lUzGZTCgnsyyTG9dvKdRDmWdZFNRNzTuefJIPv+8pahkYOocuS/rNfS7u3GXYXrA+OaUfBiSGIOekaLg2aVilHK2TgUQiSyLHXLC+7WnbdvTfdTz++BNAlm9nJlKWUCotSc6hlcD3NlNFFTA2BqRSJKHxztG1Pd5aqqZBScm0aZgSWW8337Rr/A91sSSEIMDDTXepZc6mUZoQPKCopMQ5hzGS5CJGKebzKS5EulVL326YzCY0O1O8a3OAX0gIn4ibjjT0rPotTW9579WrtHrCamkpK8PepKG+MkeVOVup61p0LEkxa11jimiVx8fWeeq6QSSYVA1tu82J33Hg/PyC2WzG0e372EITfZagNM2MJz74XhKRuFpRNQ1iscP27IJ+8GwHx3F/PFKbMi6zmE149eYtZgKEDwxDTyCQhoQsG2zbUUwNPgmKqoK6RHiN3j3guG250tQYpbn/6g2uHRwwnc8pr1+nkFe5drhPu7lgNbSUKuuwbQSbQEVJS8RHSWU0G9vTtEtu3OpxJntl7pyfs5WSQWtSiMzKEh8iTggckVYEhM/j6+OLC5LWfOy/+w6+8IXf5OTuXQ7mc37tF/8LVxcL/sSf/F5U2RCjREiDjwFTaXaKyEf+yLspE/xff/T/xs3bN7j+5NOgJXZzyv1XPsf1x55gWJ3iiPjuhChLLAWrXpCkJB2/ivCOK49/C/u7Da+/+hoXJxcIU6PqGbFdIWMglCWMaOHdSYlXWTrguzXKRQqp8cnQ94LNqmU+qbm0mNEUkWamuXq4S3Q93vc09SjnEYphiMSQ2F/sQITTVc9Zm7sz/WaLDgN+GNhcnGJ8pJSBCS0ffOYdNDtTzGRKPZ0ScZlC2NvcWIiBbbtlfXrK3ZdeZ3l0ymwyRaMZoqeazAhFloZUVQ1asO4HBBGXPACVljgVuXx5n6ZQhNDlDtof4iMiCCJnJQEgFcG73DAXOXMpugRa5pNdAJo8ZfPjHi8IlIyZCCZk9jMpoBAPPSJCSISGQivCeA0kKYkyS2yEFhByt5KQMbhKZDN8lnNI1GJCFBIVQBQKU1boqsheybJAlYboHbpPVLXC94KyLqhqk83QSeDcQNsFJrOGySxTkoILLM/WtCdrUog0heJg1rA3q9ier9BKU5qKbmiJMRueox83xTKfWzFkOML84Cokz/m9N0gxT1xCyDlVuiyQxiATmLJCRIk2JfNpgzEKH8JIb8gdT2LKOGEbOT+74Px0zfnJGT563HKNFpqi0Khb91HKYBYzwmbIWNnKMGkqDpBMplmmo5UaaVd54+N9JsBNpg3aSLTSdLHFugEfPbqscD7SbVtCzM4ALQWLvUOa6R6npyfoYkICfHDoBEpIqhRZaEmlJVVp2N9bUE8aiJ4c4RLotx21biiriiEm0ugXSORTrK4Mg4sYramMRDJ6lbRGpoxi1tMaU5QM1iOlA+ezSV0IVFMhvSMqYHB5szd+1lFJdJnPd6Uy8EGELP9USqHJ/icp0sMNvZTjZjElxChhJ3jA5ClqyPLLKFJuLIQ8/ZJVQUqCZCOp0tkfpcnTwpHQ6dqB6P4rOMgfsqMfOrz3CKlQRo9FKJRlxaSRnJ46jDG46LL/JvoxFydkbPSYX1WoEiUEEPP7n3LTNUaBiNDUNSFZpvOM8R7alhQDWpm8ObUuT1N1niQKpQghF3BadWitGfoBoqAsKpxzhBTz+jP6qiBPe2PKSOydvV2apqKqSvSQ0NJgYmDb95wfHXP02us8+f2f4NI7nuLi6Ah7seT81i2mly6T7MDmNOK6fpwbitxkUJJ2tUZpjTQGnM20xcFmb83FkmIxY1hv2Iicb6cBaQzVfJ6VpSFhmpLl8ZZgHWZqcCFhCoVwjsVsQvSOzXKFsx4vMmEt+JABOyly9+59bt64SWMkm21HOzjK0iDG0PEcC5AIUWRpcwJSHAsCgYwyE0/xD304WTWcfZuDC7S9J8ZMsvQxgshxFJOqouv6DPnqLEpEqjJPcvEeHzwYRTWb0TMyA4TIU3sfcH1HLDWmMvSrjuQ9qjTgY4YtiEiVLPXiKgpJrQ1NNeX44pzZLCCJORtUSoqm4fLBDh/5lqcwwdK2HcO250uf/yInp/c5u3dE3VQIH/N9zVuUlDRFzWDhxCW8VCBzQyWmSN92rJbrHGUw0khn8ylKKpbLNURBsHmClBsyIzwj5ADfqipQOkeZDP3ApJiQeWUZly6VZjKdMV3sMdGaKwpOL755e5E/1MVS1kSQR7wpd7cedNDSIJESXLAjTSnLCqILBB1JQaALhUpQlSVdijmRGIEPntIF3PmacjHFyMhw+5yJtDSLmgsKbgjDE/szVKWz5CYElEgk57k4OSMZzWQxgxioyoLzbctsOqXUGucGEtmkF2KkbGq0LJiWE147OoOLDU09wfeWzXJNtTMjYTD7uxBatmen7MymrLdrVFXwxGNPcbfvSMdH9LHm2Tfe4B17e+xMGnxRsFqfs19P8kl2ccZ0MUPphqpZUEmJPVsj+paibkiFYn1+ym/84qfR0XF4sMfN1Ya9R6/kjI/NmkBkm6BI2ehnRUSJSCkSloANnv3dHUIKWODuxSlXp3O25yespWYoCkxZoHzu4BdKsXI9wgcaaVjGQAqOoiipTMUTjzxKmeBPfM8f5+d/9uf49z/9/0W4wJ/8E3+SrikRaQ9VKVQs+PYPfZj5zoIf+2f/d7Q0/NAP/jlePzrn+P4Rp7dfJzrPay+9iFRiJDgpRDlFGENcHRFtS9U0yHqPs3svc3ZSMDgNrkd4R2jPENUEPTtECjBCsr9TYVfnmP2rOSiSXLj7oaPzFiWhKvPGgxjwbmBS1dRGZVNtSuzUFa0IdD7i+p5JbagKwUuv3eT5V+7jHSxq8H1Ht21xbUudEsJbTBp42xOHmRBUlcwOD/AIhM3YWW8tsihxITH0HZUynN6/YDLfRRQFISTKqkLXOX1+UhWoymAR9EpQiKwdD5HcrTeCaQEIT2sT0Xzj+Sh/EI/k0pgVNP7pXd70+UBKUDQ1MmSvixAxa72FAJ+lFilC04xSMJVpRCIJknf4kG9IYxQYMiZUoYgbHqKvVZXlSUEk8Jl05GzOXzKlJvYGVQuoS1SpWA+JQkjK6QRZasxEI23IQIjEKEMrKISklgqtM5RCaoPSntnOFFkMWTJHpG171qdrumVLVRuUzJKQGEoe2Z9zcnGBlTCkSHQdLiRkUaCqGdicT5Jsj1YGVU3QVU1TVqxO7+L6HOSaAxod3meaYgKkLOiGlrA8Z+dgF6lkXqNi3hwJFNF5To+XvH7jHucXG4YAd27c5dXXX+HGjZuUZYkksr9/SFmWCCXh/8fef/VqluXpndhv2e1ec7wLnz7LZHdWdTeb4ojDISFBI4mYkSBAI0C60ZU+jC6kTyBIA90JA3AgCpyhMASnh0PTXd1d1eUzs9KEjzjuddstp4u1I2oECLphF1sJaAN5k5kn4pz37L3X3zzP71GSlARCa5azGd/76D2++9F9du2Ou/fP8ucRpuIw3wEcnxwzmzVoKQnOMbQOQqQuKzrXE1yfgROAkIqyXjDbO6LzCTf29LsNyQd87HAyEXzDKCPKa86aiv1SU2oB0rJa73DBoRL0xlHUFcvjJYSAkgJjDFEIjM7ZUGWhkITsf5u8K6RM+lNSgFZkGnQuZJIWeB9RE90uhhEKmzdTJKLzxCCJhccUBUrmQl3IlLO9EhgzSeaEzD4jpgbpDZfwjQxPQNu2E7oYog8Io8k1ZQZLlHtVVuykmEOEdQ5glnIywfu8IfCj+xt4+v96rn4YM8dLZPm/nprOsspQJW7IYc5v+CBB540kiRSzv9oHaHs5ZfUYpDFUpkQgqGY1VVMRwwAi8eH3P2J1fcXTLx8TosGWBaFtkUpOdLU8GE7ek6KnqgrazjI7nXF5fY3SKkciTPeSDx6tBFYqtMw0shADpmyYVRU6CUI3UiRFWWrCqmO3WdGOPa+fPCGMI8XxPsezRwAcvfOIq998lWMUXN5aK1uQpEb0I6RICFmGqaSi0JbGRpT3uVkX4PsRUQA+ZtWId+jGsLpd03eQigavbc4JIzfyBI9WFoSjLKv8fCfwLhB0Ds+ujSa6nn69IrhAoXK8igiC3XqH61rmdcHBUd5uISQuerQs8hZOZriDUoqu6yeARc74SSmiteBNLNq6H7ndDUhlcCFm2ImQ7M9rFqXFjY6296w3PUrA6Dy1MbTdiASqZY0pNIPLNFGZElZC63NGnRSJFBx+vcYPHUJJ5BRsXAhF0TTsHRwgVeJUwMHeksvbq6nBzue2tjV37tzjnbMF1y+esLm+ZteP/PP/+p/z/MWLvPkNgb3lMnudhODk+Jja9syrBVfrgbUL2KLEp0l66AOSDGFwo2M2n+Wts1T0w4ALgSQSdVPTNDNub2+wusxLDgkoSWFKClsQUZOnGIw1CDWj7FoUgqquiT6y9gPX7ZpiNv+dPePf6mZJTcnxCrIhLHlEUTOMPmc7pGkSh0BKDWQkqpYSlEDUFWkx5/b6ivnBkoOTPaQ1JO9ZrVZQWHRhcZuWYjlj//372LMl83LOZy+29KaksoaUMqFFiUxkGnYtZVNTloYY8jp8Pp9hjZnWn+R1NAmhJNubW4pDxdi2XFycszGK28dPWMiGp7/6DR/+7R8QK8vq+Rq/zs3K0eE+6+sVzWzB4vQU8+wZpETRzKiWe8zOL5AKnn/1GZspU2VZ18Sx4/LrrwlS0d/cYI3JyeHsUx4cIWcLfvOnf8nN8xd89IPfQ/oAAqJUDJNUR0jFNrqsSmLS56ZMNzJTxsBVN1AYzda1tLeKo2LOwcEh3dUVRVCc1A3r3Yb0xjAfJCopqvmS1vV88vs/pLvZ8qN//ad8/5OP+OD9d3lw/wGffPxdqr7norTMtGB/OSPFbJLU0vAP/t6/z//+//h/4OnjZ3z8/odcPnnJv/lv/4wxeIrZHsvlMVZJXj19jAWqgyNuu4E4rrAkTs4O0dUpX371DUJBmJ2Dj8gwEFIAU6CUJQ4tsqzYs4nx5hmzo/u0SVCgqJRCxchiXtCOHR5JYyWVjFgZsVJQVSXdMFBqzcHRjEIKXt4MRKApDXfOjwij4MefveZyO1DHnu0QuX5+BYOklBFpBCpGzivDO/dOMHXFwek5KE3kt1jnummISNbrayprefn8krK0HBztY6wldB2mKfEpMIaYJ40pF+9CKtww5sT5JFBaUJcVRVHgpq2BUN9e+QyAEFlOJrUmJMgwgEkqFCJ68mmJOFHPXJZiJecZRkcyUHmLNBmeoUpJkORGCLI3JGTfjdYZsCCEyKjryQeD1ROeWRLcCM7lSbxQyKbGpIBqSlr/261TUpJ+cMxLhbYZdJPDLPOGQBclVuWB0tA6Cg3a5I1AM69JCNbXt9y+uqVdd9lvU1uMyj4U3QQuNkc8efI0+xiHjhQyWCG4KazSWEBg6oLoR5KQdN0OowxS6akZyWDqlCLbXZbz1XWNE7DabZilkrosiQJiDIz9QGVKvA989vlj/uzPf8WmG1G2pB06Hj97zS9+84Sr598QYkSZguLF6ywrEWTfUww4NyCV4JdffM7L1z+k3a749NPv8Mn3350K9YkiJWB/f0Fdvwm+zShfU5ZEqQh+yPcDmS6XpMSWNdvdDh/ISoTokSSQFYXSzIxlv66RVcX87BhhBNEIklKU+w1tN9B7TzkMbFdbpFIsFnVu9iaTfbfrsUpRWo1V+V5J5PsqN5Y+h0uPHu8iBZBCIpmcNROdJAmQSSHUBPfoAqrIpEbhEqqavBhTH5abmSlkeZKMiZTl5GkKusxn1xvuRj5fwyTLIzFBT8iQD6EyFGUCmOBj1glOfo9ERky/kfd9my81SXS7rqWWM7Qp8C4gVZY3gqCsK0LwhG6YthQSpRTNbEbn1pRlRVPXqCnsuG07Dvf3MUpnySKK+bxhNm/otmt0YcFlaV7XkXOt4gSUkgLvAkVZESXUVY0tLGVdMo4jfnS8fv2abrtjdALXj2idN4QheBIWSUL0I0IU2FJhpUaFxLDdQcxystcvXrDZbGnCEbrItMXqaJ8jo7H7exTzGU/+8sc4qUjWYoeBwY14HwiuxRSWogBhDaHvM51PkJ+nlLJcrU9oJdmuBrpRMoyeofOUsyW+G3LGjgsQIzoljMylrXcBYXzebsdAVVckH+hut1MgaklTzzBCMpuVSJGVGGrRMIyeWuTGs1CaJLK0FCWzRz7Bb755Rtv2LBYz3nt4J9/iPiLIviBrLVWl6QaXA5ynjeysMrRdTzc42sExOo8fcg5c7zrGEqqioCwr2tHho0DpKeDWZ0CTC55+dIjVgCgsejAIVSBCxKaOaj5ncX4fpTRH7z3kwBru/uTHfPb11znAlzzBC26gtpJ+/ZL//L/6Ea+vLvn68VP6bofWEmsKBInBjegpnPvlzSVVI7gaX5PMjH70SK1JSU54fME4OgQSZbIsT8kMOQtjoN+1mLKgqktMYfL9msg03ghKacrSopUlqQIhFbaqcnTBmFgsliip0FrTtzvKsiKaguJtttlf//WtbpZSCBRaEYcRrWBWzvEhU4LiNMJRSkJSb9PPESmvRIWCECiEpN7bI6gERmWz8JARzqq0eXo8OlKt0fN9VFNy1FRUy5KnNy1RzDlbGpQgFzY6Im1CW0klNH1yuBgoqzJP6aLP+UqT8bOeJ1L03NxcUzc1ayV49MPvcX3ngJuX1zTzOb/4r/8V9x/cRflI0gVJCHzf4oPHu0AUgsVySQqRm5sbLu7cYRCSqBTeFIwi5x2kEFDasHMeowXJJwbXU8znbF3g8OKC282Wv/hX/4pZP3LQzFmcHvGjf/Ev+f6nv8+P/uSf45wjpexrkUJyYBRWwBglazdiZCZ4rXrPQTGj77ZcnOzx+PqKpraUCXAOn6AwFiM1u2EkpYRBsm03VHVJJSKLgyWffOc9UvR85+CIc5U4+4MPsSFy/v5H6GVJfbBAGkUKEOPIo/cfUJSWO2dH/N0/+pTbdct/8Lf/Fjf9irqesVwcIxX8Z//Z/43U7Tg/O+UgKJCau/fu8uQ3v+KLn/8LYhDIYoHQC5LWhNgj52dEWRG627wRmzWo/jmHe0uShYDGp0BdN4iho6wNula8fHzJclZy53BBKQKzpkQRKI3meG+JFonkRpazmlfXzym04fbmhp9/8YLn12vGYWRpIlVlsUoQZaQuDEO/Ys8EPn7/EQd3Tzm6cw9TlrRjR2EMkYQtC5zzdLvdREmDJBPnDy6QxgKJxjbM9ha03ufpV0w453FC0Y85zVwrhfMOH0BFwfXtimpWMrMWXPc3+h74t72k1YSYJXRS5SBa3ETdGT3CxZxY+4YF++Ygl4KqMKhKkybpmFSTTGky+ycZic7n5ogsz1AhkpQg9TkjQ4S8RXlDfQs+IbXCt2PG4BpJNwq8S4TksCGiZabzCZEPGSUyGj4XrAmpsxG/LgW3u4525zlaWmaLOX3bYpVgdbNlvR7wCFJpsVJSzguMmihTtxtqbThYNGz6Dj9lZWzHERE9foiYoibKDF4gReI40CdPU9UoXZJER0o9gkQSCl2UdC5QKpuNz8Ex27ugns/Q1mC0zHkaIXB1ecM//S/+GU8vdwhr6X3i8dOn3FzlYFysRbgsfUoiS5+EtZAi3jvGcaDvd/zkJytS8hzNl5ycnfJ7n35MmhDnIEBIqrLk+OSImEJGjxMJ0VMVlsvXz/PPN3kWtCpIIuNsvR9JwWeK19Qcz6sZERgE3LtzxsmDc1KhoTIUdYFwgbIuEG8SjuQk9URQGPM2JHi7alG2pNivM/VO5YDqJCWxz89yTAmtxaSFVgThEaND+Zgx9YXG1AlBIElBUCoXMICKuVGUIm88U4zIfHMDOaA03+zyLXTkLYMhxmnDFbHGoJMgupg/uzdSPClI+ZtEykTyERFzBMQb1LhIieACQpLP3m/pdXB4xDgObLfD5FvMfjHnPEWZBwophAyCkTnLRpKIAqSQFLZE656qyvdiArRU2KLM97UU1MsFhZH0uzVXz19PjVDJdrUluIgSirIqGIcRlfI9VVYGHyPGFvjR0w49Ukrm80WODAkRkiDttvRdP0WpaAbvICSWZYOKCZUCvm8RRUXaJYL39M7RjQOXL7f8s3/yT/lff/i/e/veQyqkMZiy4Oj9Dxmd5+U3jwk+obRCBME4jBR1xcHFHW5fvqAUiZ2L+DQipJo2mUwF9sh6NaBnFS4EbkRCW0FFppFqKUkiZsy/czTLBU7lvM0EKC3wfY9WS9quJRlFOZsxth3zpqIqLaYsaRqLTgE95Z0JOTX7IoevSpUR1dZoIomH9y9wLiAn6RkyTd8zGK1QUdKNO/z0KL0ZLg6j43q143bTI2X2ZY7OZTmvlCStJzmyRAhNIQ1dP76ta7fdjl3b0i6WWKVRyWCqGSkMJAKzvQNO7t+nOT1idnDIwd1zOhc5OTnFGJMHQiEQU2Cxf8D+/oJ/+s/+hC++/Jp+u6ZrtwiRsfRquk/Wmy3TJI6i1Fxc1JSqZNNuGPo+g1sQWRUhM8mxqipMYSavV35fSgmFzfaFFNPbpidHReUaykiN0Tb72pJGylxvvnnHF7bA+4BSgtJOUInFfCIt/m6ub3WzBIkUAlblD3Loe5QQ2ClU8I22FKWRYtKKxiy/UuQbttvuqCXouSVFj48y5yTUJTIl+uv19IuUCAlGGdww0DQV5wcVn726RTSnnNmst/ST5E+QD6A8Se5yNoBIbHa7bLxTKmO/dUbdypAQ25HbpkLUJQ++/x1O3+3YXd6wef6KL//sJ5w9PGHv4BD/8pLRFjzrXlPU9zFac3t9RWk17XbN6ycJvd7Rji27dkUlc2jrOIzUOpuwwxSmOXYj0Xp6VaD3Flx99YTTyy1HD99h7+yYEc/ZyQHHJwdcX74mhZh/LiEoEDRaUYqEVRaVIikFFqZgSPD4Zs3dvT2uXr+kFwlx1XJYN7gYCMai8viRcQgYa9DGMg4dqXP85M/+nMXBAX0cuV/Pef7l/5PDD88pT495+Ht/i+WDR4xFORnuc5HqiVSN5X/zv/pPGC5XHKbIsxdXpOD4+3/8x9jlEfXRCb/6/OfcvXePb5484Tdf/AqjG9T8Lq+vv+T68U+JbodI2eclqj2gBtVk6pnWCNeSNLzz4JTTueb9Rw9ZB8XntyNSG1o3UE6ab60mTbBKLAqFTo6z/TkqOe6cHRHGHoHEySx1S95BUvzoZ7/mahCEsUP0O0LUdCniosCWiaG95u6s5A8++ZA7D+6wd3rO3tkJY8qyUyHk1BhB1+/ouo6+7XKt4zxNU6HKLFsySuPJtY+2BqskXUiElFDa4IcOyBKNTdtxdLDId7hS+ORZt3+9YZL/rq/M4ZKkkFG2aZLOZYnK1HxIPen6ycWjy0b5ybkLIXuQKBKkkH1HKVMa307OyejqmHKwKEoikswNFuRpu49EL3BREG1GgYvKoExi7AMy+txcR0lwEZTIBbcDoXJhmkQ2GosUIGmuX6558vQ1yx+8S5g2aH3nCQn2j2fo1mL7kXlTU1UWxhHXQhg0y7N97veP2PU9TsKt81hpGILLgiypIXjC0OW/OwVEgs3qhqJu8H3L6PJnIqXBx0RVapTIxaNQBfuHpyAEWkqKqiT5gBs9XT/y619/xtYLrtYrOhe5fPUSomM+n3N8csboIyklZrMaEChl8W6kFYGxy/kx3faan//lv+Hv/tHf4er5S37x48/44KO7aP1mQyIwRnNyekpVNVizZtQOXVbMZ/OJGJWbqoTAFCWjj+y6LvvKZKYMIiRaSYwSlFWDrBtO7p9RH8wh5pwVGxxlbWHIPhRTz3KQr84DrUwmE7jBc325oiw7To9nuaGW04ZTCpIQOTPFRQgQQ0IUGiEE0edzz8cA2CkXTRFdJAiJMeSt5Zizq9AqS+Yy/yFLOUOcNm/5vhTT5/SG25t9ahImX9mbfCtixinHlCWtQsn8gKXfFopCCFKMpDE3fgKIWpH49l5l2SCkAXbElGNJYnCUdQ1A8AGlFVqbLCfTKp/BPuP3d12PLRu6mxt23cByuYcpKxpyNs9if4+yqkh+RGvNZr2lKDIqerG/4ObqGm01cczBsmrKz6obk/1tWlBYy+JwH2M0bduxXm+oZw1d37LdbVBKYI0iODe98ySNLSBGUnSIIClKQ1GUXL3q2a1uGd3ALgR+/Bd/wd/78gl3Ht1DFVnKauoSuVb40bF88Ii27Vg9e5Eb5D7LjIe2586HH3Hn/Xf4/Ed/TnSefkiZYmwLkg9oqfDGUJgSFwPX/Y7nuuDym6/47z/6EIh5A0bC6PwMSGMJPuXPuigydjoIQgSXNIFA23doAVoZCquzJ1QqyiYDcwqrccFhUzHdw4mb1Q4lJYcHM6SUVGUB5BzNNyomMWn/Ijk4duhdtmrERGUUy7pEpMCuG+ldyBtb8sDX+YguNEPIZGchJVK8wYYrFFmKL5VCGpthDQmMMYQB8I7Sak7efZdy1jA/PGR57wKpNYUWnJ2cUVjL/t5BrlG15fs/+EPm+yfc/XhBaM745rOfEdVLtJK4fuDyZj1JRsW0PQLtDZuvvqZZdBT1Pk09J/qcpTT6gAwC7z0///lP+fi732U2n2fHzOTpm+8tcD5gtKKwBmvLaZHhCdPQUgiJNhaZdN6qx4gWCjdlBWqjETHL/qzR2Y/6O9xOf3tHOeT0ZmTWPyeyNGH0ARfzdEPp7BXw3hPim6mXwmDARUqTV3bWGiCvrgulsVWJNJqQIkVT527aGMSENrR1iU6CmbFcHM355dOXdNKghMMIyXx2mA1sJJBpWg1mqQ8y33DKaHyME2pcoppJr+kCjIHb6xtsVZKGQLmYo6WkfXbNsOqxs3l+kS0WCK1oV2s0kUorCqlZjx2v2ltebm/Y+QGhclJ6HyK73Q6GkbqssoGUrKWuDw/R2lJdrbhwcL63zx/94R/QBLh/csr1q+dcvX7Bpt+RZMJIQUGg1gofE2McaZTktM65RatxpIUJwNEjjKGLiUHCdddyvdrgkMz3T6mXx+i9fU7ffcj7D+/zoCx5MKv4zv37pOtrtk9+ydmRZbkouXPvHuPOc/v0GhkVKWaAxtBPeNqU+MMf/oDvvf8eRdezr+DjgwWz3Q65u4XLp/zR+/f4T/5H/0MenV1Q1iUthvUwcvPqOckrEpJo5lAuM9EsOaQfUIzEzTOSEixPTjkqNf/jP/qEdw72OCkrPjza593DBQezOhdXPlIpyd6sxspEgeP8aMmitpwdHyKCgxRw3tGNLmdX9T1p9HzxxRPGTYe7XaFDYlxv0ClRFAXDbs2D4xn/3h//Pu98/CF7d+4xW+4hrSDKjAD2PpDIGSrR5yLGGIMSmZKzf7CPMZPWXST8f7dUyWqa3DikhDEmT9jQ1Lbk9GDJvFBIEruY2Kbf3er738WVfCA6l2PIQx50pDAFvCqBLEzGaiuZIQwp5hyS0eWvzdq9yZM2NUJp8lPGXEzG4DM5bgIYJPJLPgftpAlLK3OCespfRpLZLG5NHkS4iRo0HcxKCmxZZHy5nAL8fEBK0FKQuURZVrntRvABOfliYvTMD+YIqRi6nrK0GJMzOnbrFqE09dE+tixYLpfsHx4ACqMLjK3Q5RxVNChjsm4iBkgepCclx9h3mKJCFfVkHNcoXSBS9n6NCbZdi5SS25tbbla7fEDqfJh265YYIpvthidPv+Gbrz7j5eMviMMWiDSLGWcnB1ycHXF2esyd8yPOjubcP9vjZL/h/sUJ88qgkkNLaNsN3eo17vqSr754kjd6UmcpWIwYbTg9PsBazcHBYfZ3GcN6u6Fv8/eG0ChtsGWNUir/zCFM0pMsk5pVDfuzJb4oMXsHjLpg0+fk+agL+iBxIQMydruedtsyuEg/RNyYi2hSIgwBHUE4Txo7tIi5+QWCc4TRvZWyKZMbpzB6lEgYLWAYszx92uIkpXBK4wIklxtadJbFiJS3QFFKgpikcaN/WyC+KYLiRPV6u2F9m7qZ783kIimG/OwIkDYPLaXOz41QcsrlynKxN18LkFze3H1bL+9zFIDRBVobvPN542EMtihydtXUbAohEUJN1rNMAsxNdwYKaDlhqNUEw5A5cmToO07unvLu997n9O4F/TCyXCz46JPvMFvMKWxWwmghJ9tHHuDUE8q8rgskCW00h4dHPHj0IAc65702AoHz+SQorUFMw1SFxBiDsRZbzujbjt2uo42RkCRBCLpx5L/8R/+YsWunzfaUkTRfMu46bKHYPznGzmYgc+6SUToPTP3Ie3/wQz75B3+fxcEBVVWhVAbWnD16hGnmOS9IGwprGaTk4M4dboeBF+vr/E4BiBFjVAbeFJY0gRSYpLNRZpm1c47b1Y7dZotUElOWE7lU5YYzJqw16NJkb1fK96iUkpevr7i+2eB8IMZEOzguV+10F2QJb5xiVUJm6zNrSowWKCknIq7m+nbLaj3gfRY8+ZRwMtdpIULvfYbhKAgpkiRIrZBE3NBTaj3J4S1aZc9odJ4kNCFqXNdS7y3YvzgDKfEx8vLxM8Y+cnh0F20bmvkBx4cXBHPEN6vEq8Eg56cUy3OK2RH9EAhI2nYHQlE0M3yIRCHoR09IkiQNSIOLAR8DUUS01Xm7BNxer/DeY3Te/PfT9kwIgbWGqq4x1lJY87bRFaRJcmiRSlEUdvrdWEL0bzf/IsWMmm9K6rpCK0lVlb+zZ/xbvVlScpJCxIiREiEELgSGlWMxL7GleSsXyBKYgO88dI6uH9DWUNQlSUKzqCnnde6arSEAhaqRjcAFj2/7bN5W+i3yUCbFcVUgjjWPb2+pjhZUMXF4eEBZFXgZJxRrNsMqbdjf38eNI922w9oaoRSJHiElzfERY1Ngy4rHv/gNqrDcrjecf/guv756ybyZ0bmIkoa9o1NeDZ6Dk1PW6xXJew7rBT51uOBph8AweCqTQzW9lXhlMEYjtIGigKLMuM2jQ8LBIcHD6qsvIY3YesnNk+ccLw9wxz3XN7e0m1uQYCJYkTjUGiskl85jo6ASliF4vFCoJGjqmpHIGDy3r14zayqe79ZsxkClG2L0bFYvcW3LkCJBRh4cHbP86D0++OQ7WCFh/Qo73MAQePn5S1w4RB0Ijt7Zx9YljoCRkstnLxFGs9hbkhLsHe7R37+gPN7HrbbIxRzvHYtZSTmveGemOLaag9/7O3z2zROevHiBCKt8yBenpNkRyBo5rPOkSpe49UtEUaPqGcv9C44Pz3jxekUpQQwekyyLw0O23mGF4zsf3OHiYMG//LM1B03Bwaxguaix9s0EOJDIngg9vSTOTk+4enbF/mzGsN1Si4hVgvO9PTQOtXrJ+2eH/OHvf8jFo7tUizl1XTOEkZmYEUfeEnxSSKzXW2JM+QD3ntE5irpmjOFtDk2MEsaAHz1OOuJEyIlTgrlUWbaTiCQZuV63BJEYBdwOHje2/98f1P9fv6bPPoaYPSApy40EEjH5L5IUKG0YO0foBlSh8f1AConS6MnHoxAmTZP1mPNqQiA5jzKKyFRshpRlXOOQfT2FnIzfCURCxpQ3Cd5hKpPDUYEQA0XKW2hVSIYQ8bseIQtE+WYDJrK3SqaJ4ucgBurCoGTKRKYQKArFru159nLF7U0LtNw9W+J3AwnBGGIms9kCYQV33nnI9RDpX79m3PWMIaBTIsQJByhNng2JN42DxsfEfHlEHEdCDKiiwoWIGhy7tGZ184r9ozsEoblZb7LXQkjElOb9zS+/YLtZs92sSMHR91tAcLZ3zkfvPcK7kfW25fToKHtXbcHr168wStNvb7m5fsZ2s8rwHaVY37xCP3rI02dPSCll4uG09YDIyXEu1FY3Gw4ODikqy6ysODg4YTnfz+APKdk7u0cXJGl1mxuLmDfjTb3P/nyObhrErGR+94xWGtLO4dHIN7IoB6vVhnEIWCRu3ZPSjniem9NSa6rCY4JHW5sLA5WLMCWY7D+JMIYpoDIiUyR6j5Uim/p9zlISViGnsFytMtacGED8FicvRb73UxRIJUijIxlLHF3erJKbGjFJTDOpcPo+XMjyO+/x7YgsNTLJCY88+ZBSvt95c0+GPDSMTP67aa4gwrd3t+RDpKhmDC4SfMI5R9XUeWutJr+0ELk5naZRuTecvMtSZECL0SSlUMZQliVlVm8SwsjR+TmPPrrP2HfoQnN7fY2WguvXl1RFgTOWzljcpPmKyeOTppTZS6WUwo2Bbb/KRamR7M9mrK+vKZsZbhzRIm+FhMigibKZ4X1ibB2LekG/3SK6gb7PwfRtigxSkvqWn/7oT/kv/tEBH3/yPS7eeQdrLc6NNCdHdOsVzdkZi9s1w+0tPgaKwlLYEr/LGW0Pv/9d3GbD53/6p5nSN3jcOHL87nt0l6/YvLoiJqjmMzoZGUPAkUPFMzFUYq2lnjdEaxCdy/JkKTGlQo4DIcKmG6dmdurVVW6OkiDLaQl4NxJjpuZFmybZWuT+nTOsmZDqQrDetDx9dcnp4aMswxOClDJgJYZECEzAn0hpFCYFLm82bLqRfnAgNWVl6ERurlKEXdeTrCCZAqELiAklDVp7knOZbpuy0iN7Wz0uBoYYMEJzeHzA2XvvcnDvnKHdUu7t8/zxS7741WNmzTF/+Hf/I25uX/L48x9TzhYkM6MNEo9kHBOoCl0uEOqWbnOdj6yYaNuO4LM3UeuSSB6UhxiRQmLLikBePmxubwlh5J133qcoKvybIGWt3/qlhJBoqZk1NdvNlr4f0MrghEKrLOXU2hImAEwKYaL6ZsqjRKK1wpYl0TmKokSk3x0k5lvdLBXWoITAC5HpQcZQhEjrRlIQxCCIMX+4kOV3wUXGmy0hZm11tTejaCyz/SVRCVKIGTZQlkiZdZ2qtOACLowIr3DbLhNQhMwTzrriZdB8sXW8W1mM6JnXBRENUmGNmCgo5MR6ZQhesNv1eYpRFgB4nXjww+/Qvbzh0fsfMDve5+qrl5RFiS1LjLWMu5bFckmxaLhnKm5XGyqjaeqG/d7zYt0xoIhjxJoaXQg0iaqsCUHgpCA1NcGUDB7ibElxek79wUf47YBfbbF1SXV8hEAR1xvuvvMOn/2X/3fm/YB8myItOahrtn2fD1khwUj6lPV9+/WC0lhW3Yah79iNCZRm8D3NbMnh4oBdv+bF7ZaQEu9d3OPddx8w14oPP3jA5osvcLevCePIEPNEttc1ZqW4c7ygPtwnFQohIuMwcHtzy/Vqy8NHj9i2a+7fe0Dz4D5VqXB9jxoj7asXqOQIQ0fpIv/bf/g/5V8+e8Gzp49J7Q3JtyRdIc0cigNII363QxbzbNBvDrAHF+w3JRenZ4gYkMbw4O4RbTfyq8eviavXLGXk3/uD9/j4w4d8/vWX3DlasD+znB4ts9xG5qlinPItondstzueP3/O/t4BELh5/YTTo3PmRUMYd2i3o4wDf/v9Ew4evcfZO/dp9pcURuNCjzaW4AWabPQPIeC9h5A1wUP0E80ty/OMUnjyVNOUBWMYkDplWYK1jIObNih5OxuSx0vP2vdcX0XqpsZqjYyGk3r2N/oe+Le9Usxyuex1jFNDM5n5rc6h00pkmo9WhJTwnUMYgxCO5DyxFTkQOqZJxifAjcTR43qfUfKVmV76MW95JhpbGj1yVpJinLxHAeUcWmagRmLycyhJ8gFFRi8no+m6ASEr4pgT06NIk/cKkomEbmRWWxaLEiUSiogoNG078uLZDdc3azCWvhtoe4+tLFUzQ8ks1xuFwl1vWO8S9cUdltJy9fQZou8QwaONJfoBIVImnsVITB6lDE2z4M7FA342OPzYs9g/zj+z0mw2t4RhR7e9JR4c8fLyhrYdmM+qnEtjLT/+8V9xs94wDHlH3be3hOj5zRfXXL1+xjD0pCTYPzhkf/+IzXrF6uaSizv3ef3yGa8uX8Cbe1wbfvXkMfODc/72P/h7BLLcbGKZkJKgKptsNq9K3r17St3UzJoFR/tLXl3dEL2jqmbM5kuGcaAUcLPaZAN4kd/ByhSE5QJ7uM/KCWLbo8oFThu0FFAUKKtphER2DmSkMBapDduuw/UDRWnQJuN253OLFhEtI5CBRkJEhIxoK3FjhJgbthhTRu9aRdgNRJcms7Qkq9JT3lTYfB8okT+DN8ho+ebefdMfBY8QkhADwXmqRZO3oCFmkIT3eYsaUy7+5RRW67M3J+fSkK1hb+AUMeahY8wyvyTy34nKm/hv61WUNbPlHm3fMXYdUhS57hAiwxSmYOWqqfGbLba0uZkJuZgfuoEoE34cp1BYiapLZkXNnopEPHtHS4IfGfqeEBz1Ys6Lr55gyyxrur1dZ+WMtnR9R1GYvDUSEi0VogAhHCYYksgy4iQFh3sHnJ2c8/Oupd3uUNN2xExeOiEk5WKZqaGlYUgdPmYPYp8iIyIPNdqW/+v/6f+MLQpOTs/47ve+ywfvvotSkqYqWBzsMz87zY3Wl19T2JKynhFdortdM3uwx53vfYf25pbnX32ZG6a24/LrJ9TLvJESUtKN8MWXX7PebLhebTg7PEUGctCxkoxdD2SMt0fkUFuhiMLSOY+SGpfilJE2UtqKxXKO0Tm2pXMDqExAffXyhqO0T1EWmMpQFiLnAZHP7+V8xjtaE2MOnX0zkAopEskbfxEnW4aA1a5j0/Zs2wFhFOtdj0+J4ANd1+fmTQiGpLjqAsVMcNt56jo/rwgI48CsbpjpGToGxhgzAEJJFnszvvNHP2B+vGR7dUW7adn84ktublsG0RCURinDw3dOYdyyvnnN+cGcy9Ex9NlfK1MEJM5HnPOoKeMIpQkhZEm6UFk2PA543aKaKuf5kc9TYw11UVNVBWrKK0whS3WlUvkcDWALk6EjRY62GEOc8sJGCpk9SsZownaHFHlzlz+GRFEWqCLn/mmjKQpFt/vd+ae/3c2SAklgiIlRqPxiUIokBF03UiidJUbBo6ZpToApY6BANSWzw4b5ssETs/FUiDxxnzwLb+R9QQkKU6FLk1/8ThBCIikN0XOoFbvW8fmu4+OzJhuFY0KlKc0+gReJzo9UpsRUFa++eUZjKqIQNLWlMpJCzyiM4a/+0T/jXvkxD777IbePn3C4d8CLX/wSoxV33v2Uem9Bx+d89md/xsnhHseHx9yuWqrS4MeBWhdUxmI0CDegdEUMAWuycXHbd8wX+4i9fbwpmJ0d8/onv0IGiarmlPM5pqhZ3z7JSHbv+OBgyeW249qPjGQKXpcCtRLMC0vvI5FIpQqG6Hn2+gUujPmwlhIH2Mn8/M3rp3SuY7/Z48H9R1zcuwvbFglc/eYr4stLllVBXe/TyyobVr1ndnrI7J077L9zJ/8ufZ7k/ewXn3F70/H61YoHD+9xdb1BKdhbNJTLhmHdo9sdbLe41ZYGKNOO//Dv/R2+fP2K69uXvHjqwBQELRHDhhQFan6BmO0TXA+zA/T+Bb//yUfs+VveOZlx1JTUKTJ6z9nMsn+4x8XpkvPTPbr1NU+/fMzJbMG7d85QRSbhWJkD9ISWjK4nCMHlpkVIC1Fwc3PN6d6SOwcHxDCy7tcUxvDRww8xs4bZo/tEnQv7jIgtcqhoMSB0noDlZsyjjWJ0Aak1RoBIEaUEykiMkIQkefr8Jcu9PZIRlNowBLAJVFmSxjEfAkYRXMSoBS/WtxSjYz7fx3tHm769+SgAhDyxi9NzmnNksnRDpISYciKY5EXiv3MACplBMchiei9k8lLuufKLXRc6F5ijnwrRkMMTBVPDbSGGvE0SICe/kZwkBcoo5GTgltGjmwKQiOAJzpGCR76p/KfCUyiBUJ5iJmicxlxGbF3A2CN81noXheL4eEHnEk1dIErLEAOub5FKs7tpWW1aLkfBVpfc+i2DLDg4vYPd3rK6vWF0I1KqXGAlnzcPMctl7l9ccH5xRvIf03c7msUeTT3j8npFSBlpnIBx7Gi3uzyVTwk1vXOPz04Y3cDQb9jsbvB+BPJ9fXP96q2Eqe82XL56nqlZQvDNN1+w3a55O74XWcry6uaGz5494VNgGF1u9OJEDwuBurH84NPv8uVXL7i8fE1RwcvXr/jTv/wpm80WgaRZ7nH3zh1ODw84PjpAykS76xlcoO89qBLdNKimZucjYesxpWcIO+rK0k0ySZJgdJ7ZvCa4gEmBvb1ZJjM6j9ASXeoccKqyT0CJyWgaQt4kBd5636LP1DV8ftb1lFmlRMqbOhdQRmMLnwNCU/bWMnmVpMxSvhQnCIn3UJi3kjo1yWhSjNMWVEwyupTPzZiLoEyAzNLVnMmUt7ZS5wGRCBFEzJ4+mfJ9H3MRleK3t1nq+45uyPhnPdEEg/eURZbXZ8N/Nqpna4vIw6vp6wfXk0TK+O7C0HUd89KijKCZFcyKDPjpuw43jvRtO/mdAqaoaZqaxfyWMDi23kPMJLimyfcCQqAGgTUG2xiGMYNJhkFysL/EOZ8BVCmhrWUYB7TSGGMx2mCKKr8Dy4rV85d0CDoC7TiwHnsikX7s80aq2zC2W7aXr/nmF7/i/OKCUsD5o0ccnp8StaQ5PWXXDvksNJrV62vq42Nmxyc8+Ft/RDKWr3/yE0SlGPqW/fMzxDFs1hvGsOXxN98QYz53ITH0IzFCUZa4rkWXFeViCR7KRUO3cySpGKNAe09wnhA9Megsk3Ye0RhCijmgV0m6bmR0nn4YGccRXeQNoXeeqDMeO8R8f2+7nq4bOVxWWbIdYL3rGcc00VYT4+BwLtK2nu1uwCeFd4E2DGg9yc1CDsNWRcmqj9jdSB9Ah5DzpxIoaxiGkcNmBm2LUWC1pt475r2PHiItfPmzX3L99CVXL5/TDyN7d94lLRtEhMoUKBJVUWIP53z8zj6fP93xZNfTuwEfetp2hVaCRESbkmHokSikMkQp0NpmTHjy1FKgiwIXPEjJzbrl/HSflDzK6Ldkxjd+JK2z/2oc889dFhVKWZR2lCbRd4nKWKy1ObTcJ5QxhJiVE1JrbGEzJl8oSltRmISS4N3/n4b3//kSCa0UyTnGccyrQCGxVcmw2uBiIE1J2ISA0RIPoCTjOHBycEq9KEkiT8bUJD8KKaIgP4iTWdNPBX82b0qCA1sWk7wPVIrcrSTftJGrjWPZaFQc0dEStM7BjzGT77zP+uz7j+4ztgOXL1+xaC5wKWKUxCXP4uKI8XZLqgrmB3vcfv4FJw/vsXn5is16Q316iC0Mq82ae+dn+G7Eh8Cub4kuUDUltZQoJZnrIvsfpCeEAbceYIxI03C8f8B6t+HRssCNHUlIzKKGgwXPnzxj43uOZvuE21saa+h0T0IyxEwwMlJQlk2WCTGAF+z6nqqEwiq8M3lLJwRb55Cjp3c9VVFwUM/Zr2qqpma3abk/X2JNoOt37B2foOs5BEMhLBWao9rCokSeLxhNnt4YB3/6z/9b/vE//id89/f+kGcvX/Ls5XOSgH/w9/999vZnVE2BsiHTU4IgoCmMYVivOT9d8L2PPuTFzTUvnl8SnUdbCDrC7B5pfk6aL9CVRTjH+ekJlRF8/OAud5cWEXoMI42O7N054Oj8mMPDPaJzXK9XnB0dcniwYG/ZMI4dlZaUKhIQOGFyLpgSPH29YdeDa2949+4pL79+wuvLVyyqipkuODg4ZHnngmI5p/MBa6vsW1GaYRhx3k3GXoX36W0jlV/+U3aGS5A0Xgi0kTnpu+sJ40gYR7SZ5HuDZ1xtkYsZymhKskwvCYWOiapoWG239OGW4/2aOI5/o6+Bf9sr+ixZjG7MB52AOMl64+hznEDI97tQ2WaEVqQxh/4KPRHtfCSZKXpxOiClyv/tTaR7dC4H+0lQMWY/JJHkExCRIRKutviQMDOBVBDfYMhjorQZIBATWAHCR2TMPij5RleSYjbFEgnJUVvF3nI2GbUz6EVKQVVorl7tWHUuF/HaAIJ6ViFVILjIzglW7UDrBEkXKFuxXxYcLhu6vSUhJWQaefHyOS9fPMWPjrpp+M5HH/HRew8RQqAf3EdpxdHBAS7Ai9f/muDzhDf6ARkdP/z0e1RW4Z3LdDYlubg4p6rniO0GIX4LAEiTpAkmySSJ0Q2TYdkwjmOWegiwpsg+mQQH+wfM9w7Y3z/IKfHe47zHOY+QgqqssNbws5/9gpvbFU1TcXJ6jNaasqxxIbLb7vjq6+e8vNlhdA7gbqo586WhDzGHeNuSsq7wIRu6bVURU5bqjc7R954QAsYYhusN88KwX5fgPIaSOCF3rcnBjKUtED5M3omAiD5vmKTIMRQqZX/dRJYSJhHnBX6bEffEhNCgYoAUGbsR7yJ2XuagWZFBSXKSrItkIAaSn/wDRiGtzlulCQOe0jQQcHFSj4rc+Os30aPZhzP2A0M/MNufv5W4pslTnEIeECQg+ZiHDt/Sa7fNvjajixzAi4CUC+rsw8jAhTBJQrOcKX+tQFAqieq2pH6HnNcQMyZaK4mtS5ZLi/OOlORbWiJR4EZPURR5aFYVFHVN1w9IMxHEdN4CkBJlVeZA5OgxSmVSn8g+wUJnCdsbxYOQGUahC4uyFuc9VTXHjQ6fEqu2ZdW2IKCQkjZ4IjkzSirJkDy3uw3qWjOMPZU29MGz3WwotSH2Dq8ycr4WgpvXl4gvLOfvvcP85Ji7n3xCe7vGjz1x9ISQmD24h3h5xe2T5zlTaVpqjmMO7U6DZ+iyvSINDlNLTGUyeKWqiV0kJhjGyDg6SJIUEmPfEmnwCYIUmNLgUsIUkqbJtY0LCeczydRHgUo++6q0xOiMfzcTOh4x/f+RiTYYcSEyDCPD6Nm0ualcb7qMmh9GdMiesHa7QUmZPdjaotqAipFQWCpjCHLA9QPz2ZLF0SG7VxG3VTSzku/+4feI/Zrf/PorHn/5Da+e5viTOIyEoqRJihAMOpaUiwMqaymXhxzMG/7+Hz/gT370a37y61vcMDJ2O7p2CyKT8N6AjZLICPDgBzQh31sChmFgXhVonZv9tuto6hI1odLfhCUHH5Ey4eKISFmhpKWkLAtCCHSTj1UXlqKqQCiECBRFDlCWSmUy6BSOrYREEHIkRsie7t/V9e1ulmImKBkl6UJgcHl6gBQ4EeljwIg85ZEyawusNnRaUlQVptR5ygXZ1D4dsBJycSJlltz4PHWJ5IYqkeU4CfDegTYIIbEp8XC/4uWmRRVzSpFRvgqQQqGUIOGyR0Imkkxoq+i2Gza3G+pFgyBRzSoeffoxLz9/Qtu2tOPI8uSY7asXVHXD+vUVB2fHzBZzDg8OuX19yauba766ek3nR0prsYVCk5jbiqppUBrGzY6IIwbJkZboOJJuVqi9JUKWGYxUlcSiwi726G+fsXh0QexblM8buplRIBIVGqEKBi9AF6zaHZXS3MSOMQUYe5q9PZqyYfSeLoz4FPFuREXBUhYUaDAlOmreffCQ7eUz/O2W2XIPDs5RtsEkSXKRODjUvOL4nfs0p/t4PKJL/ObXX/Kf/l/+U370yy+gWvCDH3zKX/zkzxn7gQ8/+IC7d89IUqOsRWtDt7tCmIqymaGjIwTHwckpT1/c5FDH4ZbgC8p3P6Wrj0nGMqsrDo7PaTSc6JGLBXz84Jh94+m6nHa+11SIQlOXApFcDuIbR5pSc7As0XiiFBhrMaVFBJfX0kLy9TdP+NWvP0fbik/+zh9w+/QbPPkFIkjs7e9z/713WZyfIKyhUpZhHFFK40ZP3w+5CEkTsSulaeoVMCoHcMqUQyUxQPLsdhvKoqSqKi4uzpBSMQTHGPO0frfb0jQV2mQSpCw1SWk6N6JGj7QVITn2C0vhv93o8DQGonA5VNNkClQSWWoUY3zTz+QXv3A5dHMYcoMic66EkPn9kXxAakUgQyJ8P+aMlTgBXlLeBgghJ0qegMlkHWUO/5MpImNEE5BFiQghp9KriKwyWMNayTC4LJtMAl1MmF0lSIMj3o6omUEmSWUVwvW4TYdQEYoCoRRFbTg7nrMf4Wbd0QbFpu1BSGxh8MJhnaJuKqQDnRxazBn6ltevr9lst3TbFVolqqLi0+//HkYJZss5i70Dut2OfnRcXt2y2Ntn3tR0o6drW1y3QWmLlJJZXXOwbDBTaGqYZCkHB4e89+h91u0O5weCd8SYJ8kxhinDZ5rNp8T0Jp+m91mWopR66xV59913OTo9o+8HusExMxWj8wx9j7aGsijRUpNSZH9Rc+/OOfv7C86O9jJ0Iym6fuDp61suVz277ZbQ99Szhot7dzlcHqCN4ehgn6KuaJRmXkhqK6mLHL4dIgiVz62D/Rl7jaUygr15iRUCrXLzHkPEaE2lJAyO2Lm8NU4eERMyZq+LtooxeuI4YuYFRiuEBqQiuA5TSlSR/UBCiYwTFzkPWUzSOWLIxbzi7eeZYkA4SFLm5A0XkSoRRQ7zTeFNk5Ry4LDgrT8JmIrZvO3MLp1cSOcPQJCiR4ap6Zpoe/FbDHio6ux39krhYkDKnIsTIpTW5g20FChlSLHL2+mJngaQQsTt1kDEICa8ssp5Nc5Rz/cZhgFZFTjviUSUVRhrKMuCbteSxogfXI4T8YFyZrFGQ4gUZZkp8GGS/k2yY2sN1lp6P05SzZyJlj1s4EePsCVKSIZ+wInsZ8xdOujpGYwhYpTGxckLRPZ57vouwzuWCy5fvGBcbZjtH0wRCY6+zZEEEvjy8885/vIrLt55RDlbcu/TT3nys58jpcDWFftnZxT7B4if/5SLuxf0fTtJozV+zMPAthuwMbBE0q430Mxo2bI4v4tThqurNW5wKG0I4wAih/++vtkh6wqNJfYOK8CY7IlXE+1RTjh4JunqMEVC1IVGK4GsNMPgclOcQibDuRxsPnhPSvlzGgP0zr8d4gQfCD5wvtewS5F112OKihQS3eBoCkNTaWoR6XX+HppZlf1CynDVDxzd22fXbfn8F7/hr37yYzbbLZvtisqWlCQu11v25i9QzR7m8F2Em3F6vE9SnpPTI6JQ3D1Z8Fc/bQnjMIFacjZU9uibSScxRTu4gTim7LmV+dkfvXsbOMvgmTclMQS6toUYqeqKsqxIBELMAe5aG0xpqeqSvu9z02kMWhqkMihlgJClzmXJ2A+M40jT1BRFgRKRYoKhFJWl3W5/Z8/4t7pZEiKTqerC0rqOSGL0HqMstqnZ9gMHU55ACokYAuM44LxjcXiQzdRKZjmCn17wQhC8h5ARnM65bIwfeoy1WdMpJUpKQOQXfXKT/CVvCg7nDc/XPUVRspcCByZP9kXMzVqKIRuhRcLWJadn57x4+oIH5UNsqdFWoaxhP97hV//8TymSoEpw8+ULqkXFbG/O1ZPn2HmBQdCtNnTktfJFM8cYS/Ij3hpEaTh89yFlt+P11fPcrEmNadfY6PFfK47P/4CBKTQzKYLUbHc929WWg9M9fv6v/zXCaIzQSBk5rCwuCTYhoaViUTcM7Y7Be8bgc0Ma4ermltL0nOwfIMZIt91hpcIkyeg8SSrunt3h6maFfPIVaXvFoTEsqxl6/4zRe0prSaNjdmfG4Xv3mT88RRgDMXH11VP+yX/+/+Dx1SW37Zaf/+oXHB0fUtc1/82f/DfsL/b49IefMFcaTKBqKkYJPvp8wOsSLw3FfI/F2QNePP0c3C4rqpoGe3CBiAP3zva5c7Sg2+5ogqcuZ9xsWuomYWX276QQKeYNVdOQJIwqewqszOtkKRLzpkRZDVoik8btOi63Pa+3nuhHPvjwIb0b+fWza+zykP3ScHKw5P6Du9SNnTDRiXHosdaSYqLd7fKzMN2P3gfatiXFHOKnEQzDQDv4rJN3Hgk0VY2QkhihLCt2Q08/DGALhLWc37+P04ouvZHGJIwEZSJWQyU1pTaczhtubp78Db0B/nquNAaECIQUETJnRSAn/1KIed0/FXtCyyzRS0xwjGmUGLPoTqQs35UhUwhFH4g2Uxrxk/wo5UZKSpElc2Rvh0y5URApYIREjCMy1girUCkiVMKUBVp4VAxoLTIRlEzTI6W8gUBkz9UwEf1CzuTpdh1qppFEEpGm1pSVnfTzkt2rDUNI+F1PklAbxdlRRVlKNq2gayrU1S3XKAJrYhBYWxLDgEyJy6tLLi9foUzB6cVdlss99vcPuX/vDvPZnN5Ffv7LX3N7+QzXrSlmxyhlWRwe58N2GDEmezlIEWM0h/M552f3cL5jt7maimvycKooiTHkKb0Q+OABOD+/y8sXz3BuQChNU5WUtuT51YaPPr2Dtppt26OkYHO7IiXJbA5JJJZ7S7770Xts244nz17w5z/7FV0/EIPHFBWHBwc8fPiQew/m/PwXn3E9DgwusNu2PLx/j8XBPseHe8xnBXVhSMHhhwE7bW0F+b6x1lAUBWVlaazIeGeVs1ukUbg+kxZVSuAiYYjIJDOFMUTCOAVk6oRw2VQtIUtstUToCE2RJdBElM7viDiAJCK1JIlMuJPk7ZJUkphClukVNp9tIZBGAEFAIAvLm2iMLMmbDE7w262mziTaNMn7jNX5z1SCFPM29A0FLzdOEGOAbzHgYbZYMo4D42ZFDB6lChKSqqgyVVTk5in7XaaBzFRkCiWIRuH3D5EqS8C8cwxtx3wxQ0hBP4zMYkHX9ZliqxQxRvaOlhxfnNFtW4Z+pN/13N7cEkOkb3vk/gEqyTw0SyC1YNj1mRzcdZRVwXxWEzeOpq5z/ZNi3hJNmWMTCBSCx4U8lJPkLYpQClyaUOgRqzUxREpbEH32nyhTEKVleXyC9BGhDcNuw8uXL8Fadi+fY2xB7z2f/ct/SfUXf87JnXtUxlCXDdpF1tc31IcHyKbm8GCP7dVNzjwrCmxTI2JkFClvcDY7mqMRZWu6YcQLy+p2xenFOSEmXr9eA5KyqnI9WBYEJK+3I0OMFHj26wKr64luB+PocCGifVb/AFirSXFC4QMkQUTw8nrLfDFDK8Wu3bHtRuo6b/Wud45ujNzuRlIUuGHI2/iyoC41s3nD1XpHEokxjMyUZF5XnOxVGNdztY288+gufjswjoFtEgy64psXK371xdd8/sVnXG9v8M5B8qz6FQpobEFQirBdMxs9e3dPuf/oLs9evWT0EV1alo3m4cUBr149R5iCJFV+zr0HZH5GY0+MOcsUIsF1DP2In3mknuXtD6AwU8h7xBaWoc3o8RizL0lrg9UWIXL9oY2dhn2GqipzEpzSJClRKm9flTb0bcfZ6SmzpqLtOqrS5FzOokBrlb2Bv6PrW90sESNKJDSRWWHpQiQKCSKRJKiyYLvrsSLrTK1K6MpSLxvsvGJ9u2KpMn47hfwCe4NLTiESpulZZtrnbBGZ5JS7ZCiLbETzk5pGxUBS0ChBYzQ/eXnF/eWcg0U90UAMOuZ8E2MMbsp02T8+ZBg9r5694ODsgL16mVeNRZaLCR9Z3DkneEf34iWb9Y5htaIuDaodaRZzXr1ecW9vH5MkHoHXBpciVVVR2wnZW9TY2OHGnt61tMmzihH/6iV3pCDobBgv75wS5zWtiezHwNXTl6TVhiQVVV0TQqDSlpvVmv265qCuGKuK7RtJhda0Q5YopXFk7Dv6NhtHE0BhaUmc1g273Y5VGCnWLZUTOGVwuuB2u8UKgQiembXogxmz+6eIWY1Qgt1mzY//8q/45ZdfMQJlafn0977Pq6++guToupYvH3/DzWrN8Z0jhBS0fiAWFhEUkQEqS1FYvBCcv/cxrx9/wfPbWxgSIiRm0rNXamTfcfvyGXHoWTaKwlq6rkXM6pxDlMCWlrqZZS0vDqkS9ayiLGpCzDknWiusyoXJq03HP/mv/hWdqDFlyfLwnL29I3795WPMbM69izl3T/aRMlI0JarUDMET/IAxJRIYuj4Xid5nTHDIE6o8Sc/4aN/1iDFw+/wVR+enWYYzjMwWOe9KSJnJPQKikoQEQ/DYes7ODQSRsxGSz8Z9aQTNTCN6z/F8jgyeefntRoeL+MZgniEw2DcFYN78iCljTbhAUnmyRko5DyIAOuaw0MFNAcmJ6GLeBoSUzceDnwIFE4wRrALihCTP8IjoM/FHGIuOLhM3JRACtrSY2mMKgR4zRtakCRYh8uEtSYQ23xMYCL0jqTy5L0oNImEMCAPCajqfuHy9ofeRq+3A9abHhyyjiDFRNRVGaw6N4uRQse0alsuG/teP2T/YZz4rUXHg5YunfPPkC7rdBq0Ve/slFycnXNy9Rz/0PH7ymNnimKIoWK3WhJBQtkJrjSkrNIm+d7Sdpy4jkhz3YK1m1pT0XcedO+8zmx3w6tVjhm7L4eEhu3bHerMCIafBWX4GXr9+xcnxCSkmzi4u6McBoWv2Dk/Z29/Hx0TbjYRxoN/1lHVDyqnW3Ls45875Kc9fXnN+Jimrms2uZ7tr6YeRTev4xZcvOD31fPLxh/zy8y9pu5753j62rnjnwSnzqsrFkWuJwaCLTFDtXWC92+JcZL329GOg7Qwny5KDZd4gVkYgVSKJ+JZAIQafce8hZDpjn8ELKUSUMTgxIFJGwksg+YQpFdFGIBP0pJEQQVtJsBmZLt9sl5SYvGa5mX+7FYr57As+kMaJOGtMvo+FyFLHlCMKpMiDHKEkaP3bc1MbRPIZauP8W1y4YMKHJ+DtgvDb2yzFEGnbDj/4KZJj2qelTNXMjmqZDfJMhDalSCoTc+umpvOCYRjRCbxPtFvHwZ5FKUnbB1brjr1lgx9H/Ogoy4Kjk0MWe0sWe3u02y23L2/Y21uy23WUZf3Wg0lMWGPouxaJZLtr+eVvvuLRO3c5OT2ldA5pM3JbacXY5fBa7z3KWoZhyDLjrPjN9D6tSIPLzZ+QRJlIASpbEJynLCvqxR57+3vMTEVAoArLbrWi3W3pYqLdrBlvrmmHkYFIcCMiQfPNY+4cHnJ2dMLx2R1E0rx+8QK73OP16xt+/dnnDH1HM19S7h8w9iNxHKeAbsW42aF1jS4bXMjwk/U6Z2Z673EuIPyIfiNptiU3V2tSb9mrLb0aKQqF0OUUTJtBHSEEZrMaKQWFlm8hHm/MZ1kWm4fpeWCQ2Ow6PHKS4A30o2McQx5aCWiHDikFv/ry2ds/KvQ9ppqhlOBsT3Nnv2RoHSI03F5uGTXEJBhdRBYVPnhqW1FXmsvbgX7oGMcRIyVGW4btFjE12Lru2D/a5/7dPV5eXiIwXF3est60dM7TbdeQBFrZHLqdAjH0JJFlh1Lkd1EmBq7QigxlCIGyrrClJQ07hmmoG1NCG0gpsFl3+BBZ7O0hYx7yWJ2lfU3doPWYPb9J5HeUIg+XlcTYkoVc8sn3P+brb75+659USmGLgpQi86b+nT3j3+5m6U1RSMKQM4uGELLETSQy0cPhfURJQUiJopDMqiUhBbq2o65LbFPll4KaSFchkKacmjd5NT4GtLGoKTjQKIWPAaEUKuRfWhKRSCb0aQLzSmNnNVIbfBiQZDlNYTTBAyl/T0lLjs5OefH8KSFGrM5ryLiInL73gOe//JJRCtTxITOl2H39jP7ZNwxDh5WSrmtZ6ty4aTlNmSMYYYjbnm9++kvuvf+Qe9//fbrr65yOHRTJGNCWhz/8I5I2DKVGHh/gtWL99AUffvABl9eXvPu97xF3W/rrS8LQsu12vHx1g5gbDud7hKEHpbh7fsFeCvQpEV+8ph06fBi5WV/iQ8JOSc1CShpTZBNqiFycXzCXGrFVJCyIIpuDfWDoB+o9SX0wRxZTHhaKq1eX/PLrL9HzOQ+bh/wv/mf/cx4+epef/7f/mm+++ZJPP/keaMXNakUMEaUkxaxGHR0Q2kA39iihEcbSDS33L84Iv/99Xn35F2glEZfP2V09oZWWcQgov0MWCvXd77I5P+JiuY+yGoGjagrK2YyitkAkBkFdNZCGvIbuO4ydEYPnybNXXF5v+Dc/+w1fvl5z5+5D4hjYOzri9esbLi7OKI1hv7QoFSnLhhQjXddjCk1VlkSfWG9XaGNwLqMyh2Fgb/IDODdSTBliu+0Gv+4RPvHs66dUi/kk2cpp5HnaqEgjCKFJSGRh6VKk83kDZ7QikSikZr8ssKrnsC5xPtHGiNbf6rg2UorE8bceAlwk6Qxv0KXNMI4kiFLkjAdr8Js+NzJyOjxiRERBGjyy0IBEeEgBwhgyPU9nWU0OGgSMIon02783JYRU2EoThIba5pMzZq+KEqCVmPwpudDVOsvGpt1X3mCFADrjakVtIESstpCyH08WKlPzUsD5wHYXGMaIHwODC4xDgEVF2pvnd5YxKC05nTU0VYlRkqf7c37xyy/45suvuXzxjHFw1HXN++99wNHxGa+vV3z2+Vf03RZjLJ/+8JCittiypmyWjN2OhECZfMiOPtDMS6RKjD7mokfCBx885M9/8Vd88dXn2KrK4Z/A68vXhOCmxhXiG7JgigxDy6vXnrpu+OKLL6hmcz75wcccnN+lbmbM65Jx6HKYb4r44IkR+nHEWsV8Oefx81eURvLx+w/RNgNUXBTc7Do2Q2K76/n62Ss++uhDrjdbFssF9+6ccnG8ZFaVhOjohYEQ0Eqw2bY4F/EuRzooKYnevaWmBRcxM4vSEhkzKryqK4R8I33LMJDoE95HpJ22hyFmAl7KZ5bQCqE1MngUKW+zRJZ1pRARVqMri0wiv7+MnDKORL4/E7n4c7mQc8kjbC4Too/EIcMnEhNmn4wf94PPG9pCTQGSk8yrtJmcBrkXCvlwSjHbbgTkodpbP9S389ps1hmQIUAKgw85SiKEhDUaIRXjMGLHkcPDAx4/fZKHrvDWCy2EyuABYzG2QBQWazIpbx0dRiWqskDLXJQqElVdkGJkfbuiLAqKsqAeahbzGdrkKb2yeoJ+aGyqQEhW7QaXIApDWZd03Q4FlFVJ50aMnoiMIofZEh1eQDUr6HYblDHZ0ymy/DWkiNY6Y6Rlpu8ZYzi/f5emmSOcx7UdpioYvEPNa7rVDZvtligEm3bLZuhxKVLYknq+ZNe2bDcb0vg154/eJd1sCF1GhA9dh7WWISZedgNyNqO9veZ41kBySG0JbiQYyxgSchxpb7YYa5jNG26GEaIiRMd21xO1wTtHuwssrKAfIpWvkC4QEIhtSz2rKIoCFwKvXl5x7+KUwprfUk2n6Iaj5QyfBJLIYlaz3nl2Q26Q+j5nPGmpGEOuL8d+ZOM9YRyZlyVFUXJ7fYtZRKxIvHO+ZFYp1reezbbl+mYDwuCFpvWgbE24fo5wt8yKhuP9E55dPqPtWkbnsW6k0JZuHKnqGaZeEpKjsprDeUWdelSpuJGK25sNZVHQD12m+cVIcgNSCbSMjH2LH3bEGFHKgpAEPxKRiAhaG2KKjN4xDiPeO65ev+bZ06d8883XXF/f8Ed/9Mf84R//MWHCsSutKcuCvjdvIRFK5XvJFiXBeR48uIuPiaaqaGYlRJ8lpmQfVIaIacbfoX/6290skSdvSkhKrXI4pMhDsTFk2lBygTSMlJXBFCXGgHOebtuipMYqQ/SBQIKQ81FEyhhIMWlxx37M2yaylCHEiAseIXKysJaGMXo6Fyi1AZWYFZrlYLEyG+/FBI/I/ocEKUug/HSKBJE4vjhj7He02x3Hhwf40nP47l1effmEq59/hSIS+w4XAWNJyWFsQRlKhn6HMppEwvUjRbUghESlLavdhi+++oqynnN2esYQA7dPn6MErLY7vrv3H9P3nutXt/zsT/4Ff/gf/4e0XcfNZ19w+fVj/PWGSiRePf6KcexYdztU1XD+wTuUShO7nme3VwyDow+BiKBIAWMyj39UivUwMojcdFYhp2PvNUsaO2evXnD9+jlzoRh9pB09VepJARaLmtnJEcXREgqN1gYhYdbMObt3l48+/SEff/dDHj64x816xVFlWd98l0EZ/vIXn9EPPXEqWITR6MIQu4z8TtrglKbQirP9hq8CKLOgH8CmAEVNLGew32BnC2Z+xRfPrgjjXzD7g/d55/ABPjrq+Yxq0RDdQPCBXet49foWYzR1XTCrCsLY8cXXr/jJz37DZlRsvGKxv4CwRsmCR4/eRTOwP68JziNIGFvRDUO+b4REJYnrHX0/EkmUdUUIgeVyyXa3RUxGd6U12ua8iGY25+p6l43GUtLMmrx1SDGTI33CuUypEUkQfOQ29TilqIqCcvLqJZGR5xo4aWqGGHjW7miKJmfsfKuvCYygs68gF3uTeVFN+Fxyc5JGj9u2xGHMHiSlSdogjUBoTRQgfMqKpJByppKcqJkhZTFToRGDJ0mJLE2WJ7mQi1udtf4xihyNkBLJKOIYEEmA80gNsc9yB5lyCGhy8Ibc+WZiL7XKm4IU0UYwDgmtJny5DCgJs9rQzGqOfcQqeH7dEYPgZL/OvZrWudhLibJQiGSR+pCX1xuUrSjqOUIp7t+9w3vvf8g3T17wo7/4OVIEirLi/N67XFzcYXZwxLptGXbrTE5DMO42VIVhsZhnP4UUBGImp7kBUxY8ePiQ73/4PTbbLU+ff0PX9zg/4Fw3Te3TZKZPvwVApPwchI1D64LTuw84v3POw3vnLGpFoyLaj/T9NFkuS9pupB88Rht+8Ml3aLctP/vFZ2w3O2bzPJTrupa6KDk8WvLF4xdctx03mx2ffvcDuqFnrykRMRC8Q2mRUb9SIUVi1pTAiF/MuF3vMFpwtCy5f75gUetMP1QCYw2u63Gjn5ri3HynEJEiZ3iJlDJZUZq8+RxTDjPXU7aRzMRLUt54KjQiZJKekBJVaEKXB35viHZSiRynEVLOmxHTtkdO1DsfcwNlIuINxCGbXLIaI0Ti6PBuhM5RVCUqZtCMmEJSw5vt1RvJ6BvYw5thS/r2bpaWe3tst9tp4u7z70vKTFqLmQAYoqewBWdnFzx99mxq1qdtc8oD3bIwzJoKrQ2zeU0zr7m63FGUFaOP3NysmDUaM29A5KJys1oRx5GqLimrin43UNgCW1issRleNeXamKIAIkfHRzwaB86Oj4gp0TQ1dVUyeM/gAhaFLSqavSU5tUlQH+/ngfLldZYaJzHJOAVmIjYaNd2rWmd5uvP5zxUdsUtEJVHzGen2hlIJnJFcbna5rpLgQ6IuC5ZnF2yePaVuO4wqePX8El2VDP01u82OsqopCsuTl6/Y7lo+uHc/A71Soi4bhFQEKejanlA1dNuWoD3DdWKMkX4cMCE/Y0ImxtHRdh2ysgwxoqPg8YsXnJ2cUNqE0pmEJ2VCKsVyPodJzpyQb2/dbM/IA3ZrLSkNVFVBP4Y8cPGTJ2wcQebBgiby1a9/yeLwhPlsRugGZApo4bl/XHK0tFxdrfnVr5/QdSPdtmfv8JTtJiCjgJQH/UZa7py9z+aLz1DXr/KGyo0kLQl4og/YsqE6uZNDyoXi3sk+P/+TPyGWDa9SQVmXeKmnbLA839AmZwIOQ0cMbnpXZ3Q45AZJKoUqcvi0UpqhG/jp11/y05/9mMdff0XXtbhxZLm/TyTiQ140iDc5WCY352WRP1WpLZWxpBg42t/jP/i7fxvvRzarLb/54nOqwrLrBqyyCJmHlUVhf6dEzW93syQESWTggNUiv+RdLshTgKEP7K5bDiqN6zv0rMyp1C6jlZUUGbv6hhIVPXL0+d+RwyFXT16Q1i1yXoFS2dxNzGGP5HynpCPBB9YDpFlEioBVBfeWS8oyoUUkSJlR1FIwKYKzEdxNB76MaCUpizl+6PAxZ570Xc+jTz/gyZ9/jt/s0MExljMOPvgu4fIFsb2FdstyuWC1XhFTyvk35OTu6AeUhHG1Y7hpWT95QR8dM21p9vZJtqRa7oFWuOjYERmC4De/ecrp+TF+0zGMA9erK7rVDSF4KhFJfcd4s6ZeHnB2eof5fB8X4c9//lesVjfc2V8Sd9vckA2wiZ7RR6zIK1VbGHAOCJiyYucjhc5oU+8Cl9evuHt4BEZij/dpDg/y70QJiqrg7N4F//B/+R9R1DXzuqG0lmpRs3+4h4iJZ0+ec3h0xHLeMIwj9XxGaQpW3Q3by1tEGDCHmd5ysFzyZHXFo09+yL/64hWSBWNZYQtBwCDLBcyXpN4Tuw26nPH02Qteni3Y35tN0ANDGiPPn1/yp3/5U17e3PDDH37Kvm948fyaL79+wu2u5/TeQ0olOTOao4Ml+415mxA+q5ZIH8BGRufZDiMyZROuVhK33TGMI1FIbGk5Oj7CeYcxGlRCKdBKYia8fXCJpA19jOimpKgrdus1zXJG0grnpulaCLgUGQJctQOXQ+LgYEEhBFokhhAZQiAIgSLRFBXtdsussFQU/PL56m/uHfDXcSUQOme/CB8mL8Hks5g2oW8kRGM70N1scJe3SA/lco6wBVpk2ZGwJr8bsjUpv7yThOjzgetTJgumrJ4T5Im/NJLoBKoqctieCyiTKYRojSZThJi2CjnSKFKUuVFNPq+akvMZHBFCbvRilqjJlOjagZjmCJEwOqOl9xYVnY/sbgduNy2VVSihWK07lDIs5io3cDGx6xyjc2ht2F/WXJwfs1ld8/F3v8Odi3N++rNfcrtaoUvN3vyQ46NDbm83/OznP+Pg+ISLu/fZPzohck2zPGQcWx7ef8D15Q2rmy1Xl7cc7c1yoR4TEsneouLjD97j62cvScry4sXXtN0UuOlDNiLndumtdyDGnHMlleXg8Ijj42MKa9AEZlpikPTrlr7tqOYN0QXGvseHQF0VlGVBYTVd3/OrL74mxsD77zzk+OyMy5sNq/WORVlxOYWLxxA4PFgwawp2fU8AajIlqu2HvBUSgtVqS4qJi5M5q21HP0R6Fyl9YFHnHKbgHRBJKUxa/UheI+YzgxgmVH2GkIjgs/e1zKHAMSQ0CWQihmmzpDMNTZoMHIqzCjWX6Cr7QXN+SUKEXKi82XSmEKHQMA1aksjeotQndGXyxsjnrazbtPkfHzJR9XBJKkzO+9ICvM/ku5Tlf//vf8+kB/z29kpvv3epNMk7pM5y/SQSPmSstRSS5WI5AS0mv/Mk/e/7AS8VxhYobdBaMe5abh4P2GVDEhBCZIiRGDyFLtC1oe/6qdlVbzOyUorsHexDipRV8TaA1Wid6WzacDSr2dtfIENgb2/O9U3IGVBTk6dVBp7UdU1MgaIoKOYLhs2aqi6zzcEo6LJvyUrJKCRV0zCsbkEK6mZGs9zDO0dV1fSbHSkl2ptrhs0aQaQsK+JmQ9uPhBApbUlTNmxvrjg+u8PR/imuc6y7gXa7xTZLPCIT74DLqyvGfuCjh+9ysH9EYTIAQeo8nDKFpo+BzXrNKBSbbYCyRCcw0yYIIm3XMYwjVmmubjYUp/uEAF0/UlYNPgl6FymSRAnBYl6iVZawW6OmGyAPyYTIweB97/IyNXhMjqEk+MA4vRPqskBpQSsCvRuZa0NZZ+iMLgz7M83H75xw+fqSr5+85uXzx2w2LfPFCVfXt+w6gTKGQimKmcGkBp8Sm9Ut86Ji7SKlLog+IJTJeAZlOD47oe97drsdySX+zU8/4/yjj7kaHNe3O1LI/melJGVd07cDY/BTbIYGElJmlYALUw0OOB8orEXJhCkUz1694Fe//AUxZPpnUzW8++i9/CxISWEtgxswOg/BjbEksvTzjS8PJfn4o/dp6oIXL6559eIFfdtCkrlhE1CXZf6dK0UWIv9urm91sxRjymm+EiBmHOaUFSES+CF33qMLNFrlqQ+/xZqGkHM+EFlXHIee1atLqoMlxlqECwyPX5G2HXGvojzcQy5mWaaVoOs6pNZZdiclWsK2d5hSYGSkEp55XSMmkooPEZ3ywcXkKZEpMpvN2Nzevg3zq6sSUkBKyd5yzkxbLp9fZ6PxdtpwLRaEsaVbX0G/y9koIlIYjS0KnIflbMYQAoW3xH5AkINIB1VQaovVBrFXsTjap5eCwmje++6HmBg4OdyjLjWx7zLjP4GUlkqXzIxk3e3YXl3TSc1X6xtcn4NV1dBhwgBtQPlAHwNdiOxCxCdBJTJVbTMMWAxVDFxdXnF9dUuxtyBJRxU8xhpMYbB7M44e3kXobHo18xkuRbQxHBQlamLuCwRWK+S8xhiLVJre9Wx2LT5kMs0kAEHWBWEIYAuqeY2Mjl9+9g1/+bpnOPs9/GZFsBq/PEDsWiAyKE1x8C7HJ3cQocPMDZ6Cql7knzspbm62/Olf/AJb73FR7/NXP/0156enrNoebSoOzo9R1rBoCo72Z5weLhHAdtdiiwIpEtrkqUwYcrHkuxEvE2MMqBCRJlNplJITbSlnbZRlkb0p1hJiJPpA3w+M3YAtS4bNjr7r2dzeYusSqQWIkLXBIVJay23fcTmOjEKjRMhTwpiyvltIlIjUpWU39CRlSSLy4xcv+OZq/Tf2DvjruBKQXES8mRP6RDIJoX+bwQH5oBtuN2y+fILWNmO+qwK/2cFYoI1GDFkGEIYcViuMJI0exYRczonBeQKpZC6KkyLE7PdQVlMokXFS3iFE3l5Fk9AyIcW0WUAgjJwQ5RExyfByRg8Ikw8OQQIJtjKkWwhuoChrYnIYK4nJ8PmT1zx5uWZWFGipWO8cSSaqIpvzlcxyQWMUPiici9y/e8Kmj7jwLu3tFX/5s1/R7jqEVBweHaMF/PqXv0Qpyzsffsh7H71HIhdrV1c37DY3PHr0LqvNLXvqkH/zoz+nEJ8Q7pywXM7xfQdas1m3zOYl80ZnH6fSWG1pDs8yVW/s6YcWmDw95A1oVTUZAJEE33zzNWen5xwYjZovkTHhfMCqjGF2PmImOIEgF1BKSla3K7wbKArL5c2aq03H3TtnCMAD5+dnXK/WvFptuTg/RGuJc3niHqJgGH0GL4iE0ZK+KXn96ob9Rcnd4wXd6Hj24oYbq/jw4SEz+2Zbk/0AwgeYlcQwZeCEkJtlmfC9R5WZdEaKxGFATrK9HH8S0BLiFCotlJwKCYUSmiQVyirCG4BLBAgQp0ZGTNLGOMFJtMjSdCnACKIPMHpiO+DbgXHTMlyu8C6QrKZ9dpWx8bMiy33DFD5L/t6EzJ6EtzLUN1TDb+l1c32DVBLnRlJMVFX2TvhxzNs/FGVVc35xweNvvsG5MdccYSqyU0BpgZAZ6T30PcM4YErFflNAMviQpZEpRPq+Z7msJy+2QFmDG0YKazHWUmiJKXPGjRsdxur8+yg1+8u9jPA2JUpkL6M19i2eX2mDVppAJgEbW6InzLd3Iy54lFE454ghEIInSIHXmsFnb6bWmn67QqbAfL5gs9kgpsG0LQxjGylLw269fbsNMEpzdHAEZHm4qubs7IyoEsNmzWrX0W1e8+z6ktv1FUJKqmoOJA5PTzm8f48qBNrbS5zzWVY8OvowoouGgKAbWoqJXhrSVC9VBdthxHtPVJI+QDc49vf2WC4XJKEJKLaDp/S5mbQyr1+9T2gZ6ccRqSRKCpRUdONAApxLdP3I5c2a7S4rT5z3VEWBNYqx7Xj56hVCasrCUlQWOxaQPP+9T99DRsePf/JLvvrqOS+efI0ymm07gKhpZkeMo0RIz3oYkG3LbX+LNQWtc2ilkFoyxIE3ca5l0bDqRg6tQiKpJPzD/8n/gG/agb/60ecMPqCkRkhBvTjAtSvKomTsd/gI2mYACUkipM1gGpmbJRHze08qjY8QXCD4ONXZWXJ3eXWFIBGcR0uFE3KiAmZPHUJgigLvAmVZUtclzazmi998+bbBs1rQdy1WG+q6whgzeTUzKOt3dX2rm6U0IVAJiZwDF9Ays/RFzHkSTVlB6BnaDnmQaR0ihbcSg5Ay9Y4E61fX7F6vqJo5W9dRCYHbbJFtT7ms0WNg3LbIukBMRatWina7paobtEisWk9p8rSyVAE/SIqyRgIxZmMhZKlIUxl8DPihp6lrovcYo5Ai41WNVoxhpFjW3PvwEZ8/fomZz+i7W2LX0rctj589oY4t3ndYpTFKoQLM6hlN1VA6T0g9O3qizuhWi8k5HX5kIecoYLjd8PzZc46Pj3n269+wPD/m8a+/YLvbsZzP2F4NOAH3715QFgp39Zpus6NbXyO15HbTMvQ9rt1RJE9wOftgSIKbMeAClGWNSJLRBYgCtazo3UApJdoUBGXZxcSuHzmezbDLGdXBEmnylE4VOTRTS0Vpi1wKaoUnIAAjJfgsVZkvZ5yen5FevoQUc3hnStiqYGwH6uqAVNa4mEhK8GLb8TJaRjrMvELYEu8GbIpgaqKHjUzMtGXvcMHjq2+4u3/LsxfP+M73PyKMK37+669oDs8w1tDUBcdHhzlrZW/KBNCaqrY0jWWxKLCFZNwNFEajpCCFkJGwWmK0QkagLrBGE5xnFB5tLBKB91kPrFSexGS99JQFFhJu9Lgxoz8RAluWSJVzI3IYJ/QxgFQYazOuGSiLGj/2zGoDIrHzgS4mhq5juahx4whBcrvreLrp2SbDyO8u2+DfxSWmTQYiG7LzkDh7QoRSpDGAFIyrLe2La5KLDLsdRhtcPyB9QuxJ6Aa0mSQZKcI4kuQbyRKTeT5DI5KPE85ZEZRAK0kSAmFEDsFuHShFsnnzLFNCxZBR+sFNeGxJcI6xH2iKMiOhxWTQF9MQKWaaX3IxN3DjgAya/OpPbNuO63XP8V7N2eGCoRtIKfL0cse6nZPEyHKh8mbGSKSoGF2WFt6/2GNze8Vf/eXX9JsVMSYODg8opOLp8ydU8xk/+L3v08z3+OrrVzTLOdc3t7i2xQrotzdcX73i0YOH7LYtT56+oJBkIqhUDNst3aZjfXVL6HvWt5cThCBS2hoRBdQNelfSd1uS0qSUmM+XFLZi6PsMJwjw7Kuv+f0P3qOweZLsvacfHYW16Ojx3YhSIBG4caCwlj/4/e/z5eMnfP7VN1xd3/DOo4d8/sVTZk3Bu48e4INivcvm6MRDFnVJ3/n8WWlB1BpSYPSR3a5n13l2/cD19Q0fPjziYFay7iI3647VumN2WJDeRm/ld3XeLOVCIOcqTVsjlf1zUgEuw0aC84hUvAWS2FqRJJPES2VPnZAZL29UbsxUjsKIvSdN92ia7lchBIzZa4ePeRsS8/cBWeLpdj1u2xH7gdAO5LcIdE9f05wcwIShzoeyhODJU6CQA5+VICmRB4r/7h75v/YrBo+1NVLkIYjSOsdHKINRmhgddV3y4P49rq6uAImx2YObe0VFUdaUSuYMoBCzv7TS+JRJjN57yirL6mICH0JGxYu83fl/sfdnMbdm+V0m+KzxHfb0TWeKOBEZERmRI54HDKYKcNOFhIXcDVILtWkkRDV9AVKLC8QNIFoIBAi1EFz4ooUsI7XVEheFikJ2GZsCPGBs4yEzIyMz5ogzfed80x7fYY19sd44biQuyk1lu6LFln2RzvB3Tpyz97vX+v9/v+cJKZcBY1OVKKiQpTi/aEu/NQSOjo6ZrRbs1zuqxpSemlLYkPEhE2LCqBKfHMaBPEX9Yow8/OY3sEpgIpDLwC6RQICPCbJnHK/LpJ+Mzqn0nJuC5B+6HmssbnQFQ50TQ99jrSEIgSpvbbSAVhv8cKA6tXB0xtOrGzofy2dcTToLpYkx4WPk/W++hf38F/js938v8eoZT959h935msF7huC4uVlj2xmr2YyqUkgp8UOh+CHkpN+A0QeUtuz6wOpIYds53RAIPlH7hI8CFSJalwiZUJBIZVA2sR7iNLB3IdKPnq5z7PeevvdTL7J0UWPMfOO9j3j28XuYZoH3nqvrNYvFklfuLlg1gm984z1+86tvcfPsgnZ5xNX6Gm42GN0yX/Ws5kv0Uc3N5QYrQM7mLAg8+eBAEmXAV2Kggm50CJEZd2vWJB4+uaHhQEyJ9z9+wuEwYusZgSuUqjC2IrgB15etppxw9zGBrgxts2Bw4zTApYCBSAy+kDytLm62GCKnZ7c4PbvD7du3qJsGbXXp68dMCpkYY4ktSolUhkM4ICiC53EYy0XdBYxVuDGXX1eX99Kzp0+ZzWYltfVfaHj/6VcB9ghIiUhGKYHOmZgF43ZfJrqzhn7fc3Qyw4/u+WSmqipCKiQxqTXBO7IQjN3I+QcPOXnjPqRccOH7jtQP5LoureNYYnNGKfw4knzJqEvvORx6pDS0OlEtLcNhxJoaaQxG6ymWkydfU6I8bsrt2lRFzCWEeN4T0abEpI7vniHmFZurG269dJvrBx+htSAbzXrXI1MgJoHRiYWtsbXl6PSY3XrHmDJ57ECBTBBTKm6WnNBSMKZAvz9w54UX8S4i2pqTF+5iKsOVNIgciWOHyw7Z7Vmve7brIi/zAq77A2NM1MagJfiQ8FnghOLKO/Yh0pp6cs1kjDbFv5QzwXvuzRfMlisOwVGZCpRheXJMrg3zk0L5WZ0dkSqDtBaTRXFySElyge3NhouLZzSzltsv3GO/3jJ2A03b8MXPf346BCdCTojKUi8XrM+vi5hy2/H+g0va5Qp/cUVTG4RqkHi64Ag5IJuW6EaUjORUsuOmXfLR+TM+e3vJh+9/xNDtOXnhFQ4xM29r6kriZaSSFp8STVOjtWaxmDNfNKiJHGQqW4hCIRCjZ97W5TLUDwQ/Mp/NSN4Tp02jkpKbq2vuvXi3SB+dK++XVAq2aZqQx+kClUSJLAwhUDU1IUaGbmBMAbWo8DmTQ8QJME2DjY5ZZRA54zzcrDvW19foLHFdjzyeY4SlGwNiMpCLpH63HwX/eS+XybOJ8CQKnU5mUbLo0+ZaIsgugI/EMRToA5ncj8RGoWPpdAghiId+GuRkmLLpecKEZxen7cHzPVOJ4lE2S9kV0h4hl75IbRDBF7eV84QkUVUBROTgS7E/OnIuhyhZa6TIiDTBHpj8NjIyHjoQc5Isz80UElc3PbUSvPriim7bcXnd8ejphs7Dhx9fcnI0J2RJU2sSAaMlSE13GAHJhx89pt/35ATNbM7s6IzD5VPuv3Cf+fExulnyG199i7ZpEdqgbcPRCy8xqwzd5gKhFL/2K7/Ian7EnVtn3L2X2B0GaiXxw4hdzLGzGZ955TXOHzxkM+y5URKtJNVyiVYGkQXOeRKBxtQoZQg5kZUEBavljDdeu89i0SBNRZqGNwHJzFiIkdEfaOoC59m6wK9/5U2+9vV3WCwaPvfGZ8kCnl0deO21V3jvg4/4D1/5Bi+8eL9Y42Pk0I2MIbFYVYic2XcDXe84HAacz1zdrBl6z7jb4NeeeThw//5tTmYNtawZuo54bEpck4AVkZAS+IiwplwymCKbFEiHNGVbIEShcWYtQUygD61IISBzRmo5Iaol0hhSyEzsurJBSsWVFHKJhqVQNhhoXXoPqfyaORU/YOoBBGmiQ6aYyS6ilCCNgRgmOfBmj5pXiGkrVaYQn1yJROmmiYlCG8KnOoYXYiAEjzGGmMqW09iCX/fBEVMZhDZNg9ZFOFv6ZZLKWO6uWoQOjIctdX1MkKUDJHWJ12ml8TGU7VKMxAjdfmC1bMrQN3hSSCVml0AiMUZPPWaFQNCYCiUyvj8wmzVUdUMio6zBhkjOESkLElxJSV3XZbAjQGVY1hUgilBUKUJOJAQhFQ+OyJLaGBQZKcAqhRaAEvgxkKQkiXJOwxj6cXgem/W+eANdt6NuFwjvCbst148+ZPbaEcevfwcXv/nzpOFARJKyoLINWmgQkrc+/BAhBC999mVeef01gqlYD7/FYdex3/Vs1teE9RUew3x1i3m7oNIK78FWNbaqSKNj7Ecqq/EZpCldxggIYfAJ9oPD6LpAWVKpc2T1iSi8vIGVlGy6kd1hJKXMMDpIiTRdNHIMrE6WeD/inEfYFrSlHweEFBz2e/Yofu3XvsYHH33M48dP8ePIkCVS1xx2z6hs2Vr3KvL18wtO6iUGTdusQPfPCakCSWUblNLUdY2WmZkMJFvx+HqPlSO/+Iu/wAHLvD0lykxlNSkUqbk1NQ6BkCVemrNHmYrVYslydYpHszg6AVkqFHrqS2trMFVVRM2m9OfaWYOxqig5KDRFrSV6gur0w4iqag6HjqquiyzZVngXqG3pfecYeHr+lM3NFlM3jKOjrix13WJNwZF/q16f6stSiBEfyroRgFQoLN3YI31Ep0gMA6u2JsdI30UQ0DY1LgSkEoSckKEIwpTWiJyQoyfteqJRRVjoAv7QI+YzpBaEDmxdIZVm9CNSgAuOyiiWdcV219MsW1wSWA9j1zNb6RLzyQklPok/ZOazGbt9h5uoZmVaUw4zuZypCpbTwOe/9zt58+oX2A5b1ocNRydnvPYd38mb/+ZnSCRETozJUaNpjWKzWWObFqFADTuyEBgl0HWLbVuqEJBHS3KG4xduc3b7hGcPn7C4teDq6hnrDx+Shj39zRX9k0cYf2DotwhjmBlDDB4XPDlFbs+WWCRdGPFC4WJikyOXo0MYg1YKIxVkRT1bloOAVGAqZFPTx0BMES1KDtflxH4cMHXFfLmkO+yp1RKpUykfKo33kQ+++g2+9u9/jbffe4+zl1/ktTdehxB5//0PeOWN1/i9P/j7OD47Yew7kpREqcnKk5G4EHjvrffonGR7fY0JiVm1RClDjAND7JCzRYkuiUzs93gLXVToZDh95Qu8/uoJfbfDhcyQBEpnKlt8W1pWRGkwqpS8T45WNLWlrSxGlViNi2XLmSn/f4LM5vqGxlQI6uJRSpmYixTV7w+QEvP57HlPI8ZykYKyhSg+MTeRptIUM81kJRmGAbfdk4yibS1ZSTyCISXKccwzl5p48Dw5v+T9j8+5e+8uuTbc+ETtEkJHdqNj0zkOzqGGT7eUFlXKz5my8aEyZF0iToUul4gpEXpHnsAK5AJiEMaWuAERrSWhG0idI2tILj73UQgxRW5C6SBlMnnwYBUqJURtn5f8U8xkW+IxKZTivBQJYwSikoQEIkSUzL/deVJykqmX58cnm4ksEkIrrJY0bYWYHDkieLJLVGnk1dsVVRrYDD032wP96LBViw/l+doNjv2hJwlF3Vhs1TC6xPmzNd2hRxoLtuXWnRc4OjmhsRUPPvyIiGZ7c42YRq7WWPy4I6VE3Vb4oWF1cpuLxx8gqzJdXq9vOKkMzb3bZBz9Ycv+Zsf1k6ckF6jrlipGQND3PUfHDS+99BlGP3LY77h7+26ZjhuN0ho3jtw9PSVlQXezZa8qrC3b2royyAy+G5gvakxtyZQI3OnJEZvtmrffew9jDPdfeolv+/KXqSrNKy/f5+PzZzy7eIap52xubvjo8QWro0VJTzrHZnfA+0Q/eEbn8SFDzixWM7rtlvOLDS/cWVHrhpmBQxeQfsAYYPIiuRxAS3IYf9vnogpPXktDUpIUI0qUiFRORVkgRSEHaTVdwyf5pTDqObhBkEsVyuiydYwFFJJ8mD4Dijw6lNHIVFDiwlNOzUqQ+pHYuUICiwFcRCieb4/CMBIG/xwzjJLkoTjBCGX7WRyF5dIv1CdEiU/nK4SAD+H55RMSjS4x5n4o3jsQXF5ectgf0NoQQikFWKOZt5qb/cgQZRHGGoVQkkPX0d5alu1TznT7HmM0IeYiPKVsEVMsQxGpBKYyQEkMKC1JIaEr/byU387nVPM5/bZHZoHM5btjvlpS1TUxlUuTlAolizhUK40OgeZoye5yjdnvylsBMNogcyKlTKVV+WyZ8r2nlMQaw/X2wOPzc9r2VZQ2KKPLmWAafmrnSSRS9NSVIfuRMUbkHG6ePqLDYpsl293D8t7NCVDU7RyRyqV9TJFuGDmMI2effRVhFP1vvonZH3AIrq6eoqsFqmoxRqN1g8uS1pQo/3YYEEngYyHgHfoBKNv/WkyfAYqnMSSBShKlStRZCInI5QIVc0JpQyawPewIE/kxOIdQAqkMSMV23z0nySqlpu/zjLWWzTjy/gcPuHz6DHRNd+gQKFpbl4HU5obu0DEMHY8evc/xF74DkRWu65CpXDJGV+BQQgmkEEhpuOpgWHsWpqNqLFqOfHB+jq2X/P7f8208PL9Ci4TRsnTfRcvmWkwD/IRUFUJXHA49Kd9QLW6R0KTRUR8tESEiMowhcXRyStPOyCnSNA3Be955511u37qLlooYAiEltFboaKgrgY+Zumpw3mG0YvSOQKLr9pw/esTV9TMen1+hTctsecRiNsMIyaxqqNQnoudvzetTfVmSYvrDEQXzS5omGCGyambEdCCTqK1C5VxQ31rRHQaEzMwWBQUupEAFRUVRnvTbHWfDLWLMyElIVuUSyxl2B2bmCN8NeCHKNA9Bt++ZL5YsVOYQS5Y3o8k5Er0nBV+ibxQXCLIQlmJwKCJtawFBjH5yWwSSVog8XehSBqtYjx3bD97le77/O3lwtaO76hH1DO2gRmKzoBsGZuOIzYLNeo1QYI2gWR0RZSYHyep4RTpscG5AusA29Tx57z0ONxvqoyXRRdx2R/foMVI68rhHikRWmdFnEJp50+IPe86qGQttUcYQDxFvBfthBGuL4DIlpEzMqoaMLhejmGkSLJo55+sNXfTU1rBYLFnMlxz8SNsuS6HcaqRVKAlWaaQxKKF48zd/i3/6//x/8dZX3yRLRfXeB/yz/+5/YNG0bPY7ft8f/EFe/uxnma+WWFsxmy84uEQKPf3hQNQLPnq65ejsDnk8oKsWrMC7npChOlrhQqBSiuAiUjUMIbDuR+4uFzy62PD5OzPapmG/7ck5crKco0WiaeYMznMYR3SmRO2EQIiEC66wA4Qs7oYQiutHFK9LmDUc1jvGGEvPTZd4kQSuHj6mPTuhmc9IwaMmd4KUcjrw+KlAzJTVCBgh2B4OjMGhhGC/37O6exsjNTe7Ho8gW0saAzcPz+m7kZlVPNtsuX37PvroiMu+IytFDIkcXcHehgPJD8Q4/C4+Bf6XeYksSt9Fq0KfS6lsbz6RbibQs7pAYvY9sR/RyhT8chJF8uk9yUVyKL0R4tQt0qr0NIz6beDX9GOfT9NTKv2mBOSEzKlE+FJExnLhtarElkJwBT1OIriRXCmiG1BV2RrI+QwRR4QbEVUp75eCrZqieZkcPFpIjkyimmvcGNjcbLi6uEHoFu88R0crYoTtYaSuKmIU6JCQOvH0Ys3Xvvp2iRXnxGI+5+T2HULwPHj0BEzDfggsZw23lpbjtmI77hj7jlZJDlcXuMMa5yO377zEG5//At/2hc9w//YxjVRkInpmuf7wQ8Zux81hTVxU091fMGuXdGJHZSzL+ZK6quj7PUpLXrx7H1tV9OPIbr9l1i45Xhxxtd4zW5yStccoge9HxustORyY2Reoj5YoKRkHz6PHT/nSl77I8JtfYb1e8+GHH3KzH/j8577A59/4HA/OLwkCknNoW/Pg8TPu3j6jtobgPMMYCDFjrMLa0veLIlJXNbHbMES4We84WdXUrcHOJRpXBmPeYxVEJUhdT+EzqCKFtYYc5SRSFoiUSCkgoMhog0NUGqkFUiaSS6X4/Ml7TZTonVCiQCLyFA1FlFgoZVLOc3JdIvmETNP5dIpBZi1L2sKXiI+gQFGEKpd0qSWqMWQlyH4i31E2feSp+xRiofqZEvP7pNP0aXwpqaiMxUdXtkpKTxsTz+gGUsoEH/jKV77Gs6dPSTGSYtlMuJh4uh6IomUImVYU7LY1km67xrkGIQXGVqQo8dERM/iYcaMrZXcEWYrS3xUdVV2Vv1cliS5iBSg9gRFyLimbEEq/qa2IyTNfzIpSQFCEr0Zjaosyqnid5kuoNVkKTNsitSrS4QQuRqxWWK3QGWpVyKkyQ/COmDzjOEAWGGMQ0tKPlhAC0Xu0lKW3m0sHM6eJNOcDOXgON+ccDttCInYDSMlssWQ2W+K6PTEFHjx5wr//97+MC56j4xXzxRGLO3doLq4RuXiJtDF0/QFtLLaZoShwMLOasz10dPuO9U1PVVn2nWN0gflqSRwjeTOitMVoQW0sY4holVHit0nMKWdGlyELfEoMLjIcBlxIJFni9beXFRlFYy1NVaGMYbFccnpyymq54OrimotnF4TREZRl7HvQNTkrnIeUND4WoIKhbOV8Lp1tLSA4X8i1uigfhnHAaFvi2VbTJUHad9SLGYu6xLmNrfjw0RVPr9YIpbEqQgoYW+J4QxYIaZC6QqqCxt8ddqzufwHnA9UnvbkMZPGJZYwsYLfbsdsV+JiaRLXPvwYL/QYlJFEWAYZQkhwEh13HMIwcreasnz3la195kwSoasbi6BZNu6CdtYhhRI8JhoSov3Vk3k/1ZUkrDYKJ0pMJY2RzvUWkjNEtVkFxeQhMyChbsd4dEDmzWDbkDD4E6soSRUY3FWbZFMrKzRX76w025rJB2neYxawoKA49sjK4FEmpWLp976BN2OSwKRBcx2E/YmYN0YN3A9KUSVNOAkRB/EoEbW1xwTObzXGufHF5lxl6VyhY1jKmkSgydVUTQuY3fvpnuP3Fb0e4hNFNiWgJWYrbRjE6j8wCHR3jOJIErHdbshAEYVnUDf1mQ7/vCPuO5miGqSy377/InW//PF/75d+gy5nZnVsMjz+m1kWUqaUghGIkDykyBodWlqgSzo8kLen7EaE0bhhpmoarbocGhuAJQrDdH1jMj9h5z/byigWZp9eXvP7KK6yWK4zS3HvlfnErKUV0nmbZoJuqfJBy5vL6iv/pX/9P/Py/+3dcrjegNCEklosF5xdXZBLHt+/w3gcfcnRyxL3bt9BaM5vP6G52NIsZ79107Hxm5Q7Iw4GMwWhbENKjp1IKgyGLRDurSDnTaEFjK4xOLE+OuD6M7MdMXRtO5g2zSnE0n9OPAVlrtCwOnPmiZfA9LpQp+6xpycpAymgEIRYkb0xFEItSWG3pN1t8dNTzOf3NhqcPHvHq6YqqsvTBE0LZSBZkdCiF21QkpuP+QPaBy48fs9/v0U1NZSrqpimfmZi5enLB1f6Abltygt16y9n9+xzNDLfuv8A6Kh7cbIjS4uPAHKiMwfjEoqrIMtHNPt1SWiYKmFSKJAVSFEdRocoV43z05WKqlMJYgzaTSTNlUIq0H/A+IGtD3A/IeemflCK7JGdZ8MsTbEQIEG2N8B6iQk5lfUEu034hCaMvv34uklIpFSJH9ERLyxm0MUBCxEjyqmwRDiMwolIoHZJc8N+zWmCERMTyORY501aG5BwpZNzQl0I3juPTFp9cmdyqCX0hJDHB5dWGi4s11zdrNjfXxJT47Bc/z/LklK9+/ZvodkUKjlprjmY1czXy5PwaLw3Ht2+xsIbHD7Zcnz8mxQFxehvR3cZt14hbK4bB42KkP+zZuIG3P/qQq+sbUkoEHzg5PWa+POGl5j7dYc+TJ4/o+gPBe9Y3a2b1nCY2HLqe+bxlVtfM64a6sbihRyG53uyKH8g7zk4WCEoMNgRFiJ66bfjwwRO+/PnP8au/9ZuMzrPb7/nmhx9x69ZtTo+XfPzkgqYxxJzZXF/z8eNzZouKtjIoY1Aacg50+wMzJTALy8lCQ2e4eXrFzRXEl2+XjZmdfGWu/N0oKZAx4fcDqi392OyARpfUwxjRi6ZscyRlIxkCoCecMIBE2nJgzjBh580nCZ3Sz/OxHEi7EVwk7nqQElEp8AX0oGoz4elT6RcJBT4Rx0DcdggFsq7Kr90XcIFuqxI9GvzzGJ6AUsgyuXSkJj1HFuX3SPrW9Q2+1S9jKuaLFetNAVsopUgx4IbhOYSDrNjtdtjKstvv0NYQR4eUiqquCbliHB1KW1LKdIeudE/7kaEfaawkU5DxUhUh6jA4QJfo1OR7NMYQY0mxmMowP1mghSg0RFEABApJUho5AaF654gJhn6gqSqqqkIbW4AfSVBXlsM4snmyZr3tiC4gtcWqEtWsdUY0NcJWqBioKlucikpgqoaYNujKFlJrEAhhUbYqnkprqKWk0gVy0FQ1A57eRUK/R6DL91xOkHyhfhIhlxqFUIqcAlkqnl7c8Kv/7tdZHs2oFwuOz+6gq7qkW4wlOMdyfoRIAZUis9mcLBWHQ09wHdvtBXUzLykOJNo27F1E5MTeDbRtzdGiQFu0KJeC0XnmTUWe4DLdOBCzoh892+2ewTm8T6icOJ4v+Pwrt/nw4TOG8YCUkrptWCzmHK8ajhctzx4+5OrhB4WUSOkR2npZahm2YQgJXS+orEIJT0qBRKTSxTWUnQcpMIsl3X5NEgJrLRHonaMViuHQ40ePV5lhOJB1y2q65EcZCVIyr2f45LD1bKLNVei6mVRpBVQWcyaEyKxuIUfaukZPZDprbYED5Vwi5wLadkZVW5CQciLljJQKayciZ4a+LyCMnCI5Wy6vtlzfbJH1ApEEy9UptplhbY2IgrQrnxO1aMn2v1yW/pMvKQVayHJbyoKxc0SXMVqgVWReV7gARgqMTex9BGEwlUAZiZAKKQo/XwjIWqKtZb+/ZGENd156gSfP3iRv9+TaUI+eXBmy0YzOUS8XhBTKl03O7C5vsPOaVg6QDDKpCaWa6QdBqwsC1KeAlua3C+UZlJBYLUlBIIUiEMpEOINIoIRGakl73HDpPFZYht2WN778bQzDlmff+DqxzuSsSQFUJdFTnj0JMYkBBVJVjDFytTsQ9gOhhWwFm6trlG04ffE2p6/c5ztnS35l+Je4Bw9ASuqqBg8yJwIOJwVIhTU1PiUObmRWzVipliA0w9iTCZwtjxijZ3AjKXiSLGRAVVlCVbHedohZXybmMdGPPbNly359g2g0kSOGrqPqK2TdIBWIGHn/m9/kG2+9xWa/Y70/oOua3/t7f4BDtyeOA8+envNzP/tzOD9y5/Ypq8WMyiiiTMhK0afEx8/27COcLZdU8xYRGmLZs9N0O/qnH3Pn89/BRedpKktdVyWW5CJ98CyPbvPw8oYvfuaU01WDaRRGwb4bCAi64KmrQh7044ixRaJWafucG91UGtc5ZrXFNhUhBA7dQAgZdObk7BQxuUyCyLzxnV/k2773O8nOl8KjlkijSVKiMiTKIURLTZ88Fx9+yPm7DxFSs7h1hmwlwlpCEnT7jscffUh7epvVfE6zmkNbszyacbKYEbNks+2htvgoiBFUSjRG0nc9lYJj0zA7WvwuPwn+M18FbDRJPSUpx0IOk4LsEsGVPkXoPaKyqMqUDkhIJSbVe2IIKFH6HWn0RQqrVSkju1hoV1aTfCg9LyWQo0cuG7JOpGRRZPIUI8iC54hlctmcZ1WcSRnKsisFxm5gXs+JhRlM6kfc+pr21gLCiDqqSkbcjzTLGoInD4GcVZl0VpZhCGyuttxcbVloya27cxoteHC5YesjdnHEYqUxuiDFHz5+yptf+QpPHz0keI9s5owILnc9UlukBWM0y0ZRVYo3336vRJHItEZwtTtgqoredcxqy2ufeZEvfvYVqiwZNj1D1+O6jidPnvLo2ROuL65AGc6OTwhhZNft6fZrbtae/X7P0ydPGF2PALbbG3b7DYvFCikV4dwxDj1Pn53zuddfQ6YnHM3mdEPpcFYKTm8vijHFDww5E72jtjVVU/HsasOL917gwwcPEFIQQuTh02d89v5dPn7ylO36BtMuqKqaGCVD50k+0FaamCKb6w0cdhzPLbXVzAW8djbjKjnSGHn60Tkvv3iMsBWESOwcSkt0LuoK3bYkAanPpQvTR8abA0oqZG1Kx06A1hLnIghJHANaq4mMWLD3pdskEb7g8Mt3Xp62jOXCFPYd2XmykCA0+EKrS5NrKcfSc8oxkUMkdgPpMICd/GQB5KxB2wBIhDZlWyQKvKSIp8oG6RN8dsk1feLI+vSWlqRS+Bhx3pcodMo435ctsBRoaxECTs6WHK2WrH9tg9GGGFMB+MQSY6zqppxFUsRqSecGEGfEWIh6RVwbp8VfJguJ95Ewjggh8CESY8KNBQYRQ6ZqFcEHaluEoVIViExx26ipOylKwgGB0prK2jIUMxopBMoo8jASPDRHS9bXkaPbdzjs1qWSIBOH6PF+ZNk0aCVZrVbMZjOqtkYrTY556oBKdL3Ehky7XLK7uKRWChFCEU+3NVlZBkaQmX7YUdUt45DxfiRER06J5B2ibnHeY23NmBJBSDqg347sH1/SPr6kbVsGN9LMVgQ/EoPDLlZUs5rZrKFpLA8fPeTpk48Zui2zpsFO4vay3wI/BrQUXG8PHC8tq1mmrRQ+lAN/yr+9Fa3qiv1uZBg9u82BYT+QyLS15WzZ8M6HDzk/v8D1PTJG5rahqRvc6LnZ7Nh2pbvU7a6BTD07pqoMzgWGYSDGUKKRtnhCP4lL2rZFjCMuF71DMAa3uaIy5SIttWRwgVpItFLs+x5rDClBjOV9Ko2iodRWunEkiYTUBql16Taq4jKSRhJjQd6buS6RbQRVZYuU1oXiXtKlm0eeou4loYoSBUaVIxipGaNHGTPJ1YszUtiy2RxDRpgZ8xNBCiCrGqEs2lQI7xFjqSHY+YxcfeuuNJ/qyxKAVoqUIIWIGx1aKLSSU0wlIyV454lk+sHjoiBEz3K5nP6ZqdSacymcSUmtNON2z7A9FLpNVWEX04dy3hDJRHIpKxpDcmW637sBmyusEhzcSD8IRBQ0swovA8545ITojGGysssJJT6t6ZUSuLFw+GUuEYp+7LDS0O/2uBhZvvIy/cePefGV15CLli//kf+a5bzh5uEDGmsYr67YjT1KAjGhkGgp8VqU3nguhc9diAgl2Y1jmT6cHfHo4pKzJKiPZnzbH/g+3v03gf16h4iJMI4FLWlqhDLsesfBhcLVV0ViF4WmFooZikNUKGunFbAiRBi9o9FzhKrQdo6QrvTZYy6Y77MEujzM67qmqivqpgYhCN5jq5rdZsOv/eqv8/TZFYMvEtzv/u7v5ktf/hLf/OZbfO617+AX/+0vcP7onP32wNXNjsubDavlHC0VylZkIVjvOmI9Yzab8fJnX+etd55xq6nw655n7/0qixc+Q9NIjlVbYB+kUnR3kiprGqGp24ZD74rfaFT44Ir3KMPRak7KiYubNbOmJvlEMzmTkndoXXP77JTRzafukcc7R11XyLllu90zhpG4OfDeb32Vl197he/8ge+hWsw4DCO6tkjSRCvKOD8J7wQMNxs++o03+fDNtxl9xlvDvOuZLeeMGc5efZmcM/fvvkB7+xbNvOV66EBkVkcLfHSMoRSM67oq8AJZcbqaUVeSGCs6Fzg4R20+3Y+RPJHo8BERFUIqkgvkmBGhFOTRElUb9HJGODgECaknCEOccKWhuD+ii6BKpAoTobFlaxUCcbp45ZhIPpCsQi9b8JFsREE0x4jKEGTZjGchkTIXaW2GHIEoEMYUAqJSJfqkIikGhs0e01YYK5FJImUCrTEJSAGyJHYOMZuROsdwsWP/dM2ybrk7rzi+s2Q8DLQi0ZPQIrLddmRgP2aenF9wfXVF8CMozentu6hqxhAzdtZSaYPGs1hY3nv/Ay6uLxDJM5sviONIv9vB1E/Qsqa2hqoyCJUJORCS58nlE9579CH9OLLpb3Ap013suLm5ZrPfEUIgpOLvIP82Pj3lhIiJ3XZduo0p8t77byMQvPfBN6mM4fbZKcumpTGSl++/wP7mipPjFX3n2O2v+Y2vvse/+re/QBSBF+68yO6QMaYixEKCe3p9w2fu3+P22Rkff/yQuL5ALI7Z7rf4cEZdWW42+yKWxCOzZ1EyncQhc/d0zkpmupsDzTDSP7miikdUyxoiZUqeFVVTIWMmB0EcIrKpCbsD2SeSonTSRo+0Gq0EffBkWbQWOZYtjczPUQ4TvCEitSoRPOcL5S5GyL6AjKYejNQNOWSSluShUDdTDGQ/ofTFhBJPBR9QLlIlnZES2JMVdtGWz44ovT9hNNElki8xValKHzenTzKpn97OUo6J4Eq0TRtFyrF0kkTGh4CSBeV0684drC5o+k9iSVmUnowQRXA6jo62tkgtOfT7oheQBfhU6n+CYXBUM0MInn3X0R8O3L19q8BjtCLsRpzw6MoQXERN1LzKVhNuEZRW04VJUzVV8f2J8vOl0rSLOSlltKnKe0gWJHRlSzTvZncow96YcKMjR89qtWBeN6iUaWcNs/mc6ANGa4zShDFATtSzBVId2K635dxjDUqCVgKrNKMqEUGqhkePP2K9uURKS92skGKSompNCBGlLTkLbNOy3h9AV7SrY1wsG8zd4RopTYHA5JIckEJQVYZbZyuyyOToMMYwKEOSGZBEBJvDMPVNI4JM11iudyPLRjNvzXNQE4iJaFs2Tj5mXD+Qxh5ieS6nynB5tebi8pLDdovQCl1ZlNXT37fi6vKaPIwopWnmK8Z+x2F7RQiO+epOcesZixa5SOebGVXVThcTjXERrxXaGGQKSFlgH0hBQIC2IAQOxegz/TASJ2iI0YbV0YzNbo/vdqWDVjVIVWKTWmWE0ihR+nEplTi4VpqqaZBS04pEEmraiFHi+oIippYlmhpjIWsKUSAPITgKTkkSUi6I+8m3mYXA2goVEiqk0sPMgso0ZWvlOqQPVGdHRfD7LRRbf7pPOZQkjNaKcfQFv6tL7jrFQnozVjP0ZfKgoqDf7jg9nZW+E5kcAxiLkpqAp57P2PiSAV9+5kX8usSXZFMxpIDVAj+OSKtJZIwUjJMoMApBtzsgc6H7SCEJgycojRCSUTl0kgilSSGU8uVkP6+sIThHVRmSUghR1puBhAiJxx99SFM1HB2d0N7JhKplvd3CvEUdLVh+7ovM7tzD7Da8c/GUlCO9d7RZoJUtcAer2fcDcuq0JAHz+YKbJxdlw73vef31z/HgrXdZvnDK6vSEozdeJ/YO/05EWksYDgyjw2XLaDXNUqIIVFohlaWarcgp0ekDFs2IZD475t7t2zy5eMrHVxcIW9Esj1CmwZg9q9URV1cXuJg4jCOzoxXLeU3KsN/tuXW6QmjN6ALj9Zp33nqLf/5TP83Xvv427WzG/ZfPuHfvDkrCrbMTHjx+yMndW/QhsNl1/Pp/+ApucHzPd36Z27dvYeqBxXKBthWmrhmcpxsHZpXBrS/Zv/3r2Dxy+uoX+P4vvMzb7z3ASM2saXmwGRDKcXs+hzTSzAV9cFgvMabFRbgZek6PVlxvd2gFIkAYHG1jyc4xkpm1TUEAU8SBacIES2tYreb0g+fseMVH771PpTTf99/8IQ7dgXfffpvPfv5zhJxR0wUfqQjDWOIzWSKGgV//V/+ar//6b7I5DLz0ymus2gVdd+Dk+IjTk2POTk959OQCayoapTBa8vDjB9x65RVCjoXmJsrqfF4ZZHI0dcPcSqzODBqULNOt6+3N7/JT4D/vlWNC6EIWy0Y9J8llIciaEkMTglwbhJHISpE9yEojfCCqEtdLIZCEJg0DUjckVaSdUkAWReqZZdkY5BhL1MoHsnOoqMm1LQOcWMzrQijkhIn+pOAkjMXvC9Qmi3KIUoASGfY92TmM1cQxYJuKvO0QtULUEMeIXS1AZqQtlC13fUDsHa0QVKcLjk4XJCnZj4n5rMFIwWbsibKirgzddo3MsZA7fYuwDUlqnj19hlCGGCNqPGAqydvvPMSF4gEjRe6cnXF++ZSmnVM3LY1t8N7z9Mkz3m3e5ez0mI8+esB2e8PlzSUPHz9kvd0xjCMhJsYYCJ9Q4SZKoZJFcl3OpaLEfqZJZpmKG4wpUZDRDQx9xzD0GKW4fXLE6dkxpqpYX6/Zj8+42h74pV/9dbqxY7tZc9geeP2Nz3N2csyTi0uCG1BSc3m95c7ZMQ/PnxF6R9W0DMPI42fXHC9mWCOIQw/jgbkx9Fnw0qrEdCsJdllTC4FJEZMgdSNJKfTMknxEKoWkRN9CH8gpE/Yd0SWiK9JTMTqELc8XmwUyUTaPIZGlgqncL2tdtkgIspq2lROMAFUuUaVHC0KWi03YFWeWtBoUhNGRhkjynhwywk7oZK1KFDWDbJsiUgaa20eotkao/Bx6UHxlpXvL8AngpwwLc0z8fwznP3WvTzYLWuniv4tFVF/EtIX+lVJgs96w2W4IISJELiCADLU1ZGXxfixKgpDIE+GOnMsmqNKslidcXt6UiJNWpBToux5lLC6W53a/659307wLVE05X0ijixdSFWKZmJw4WUjUJ50WSvJjNm/pugNpfkSSGphAMZXFVJZVU+PaiuuUEBlUzoiUaKRCxTTRz1pErdFVRQhT/FgJZNbF5TRtrVLKqKnj1A+ONpZtTRYKhOKw3xF8T7uYIbUh5UiOgnp5hFUTyKXb45yjbRsO48CzD94pdLQMUiik0lR18eaZqikbuRD58ONHxBSwdUWeZLz9fo+UkUVrWW87jLFc79YYKRnGBVatyjktFsdQqfhNF6yp5ydSwBrJYjGnH66xlaUxBX4hcyaHTAyO5ckRIjki5e95t90S3Q7vDlT1kqHviLFj7K+ZL44wpireo764Gdt6jrU1pqqxdUPqCopdCFkw3MYwq+dENxKnjV7M5bIeQipbSe+L4DsLjpqaQ9ehlCKO0wZYUsjDOaFsU9yDcSSmgJ860rZqWbYNlcj4JIgpUTUNShnqukFJydAP1HWNnC6JzvtymZMSIVIZIIg8xfaALMs2Veris7KzUlsQkqqpiwKIwtdUMdJUFpfCt+wz/v8HlyVBTglrDF65aTtTVstGS7JMtPOG0cGhd9TtDOdGwJaHvQQ1TQIkAu8LaECFzO7ZFVVdMe731EZjUnHWaCFomsnRk6FqG7YX1+VC5BKmmcHgeHLzkOPVCjcONKuWRhbDt6I4Ckil52ONJcRC04qxXNSi95AKSW/z5JJaafr1FqMET86fQHR84fu/i3e/8hafvf09sJTooxVf/dmfplYaHTLDMKCNpbEVuTEMw4iWEhFGetfR1hXtfM7VV97mydvvEZTiyVvvcv/7vo2xn7O+fMbJSy/gosc3NfvLS6rDgWq7p5mvWNSavF8jNjdIUxFtQycU++2BZBru3T/FSUlGcf/2Gc4FPr66ZD8eqPs9TcpIPLvtDZlcyDFkXEygzDRhFYwhUFG6UsF5Hj98zNV6zX/7f/k/81/91/8Vd+/dpW0bTo6OmM1abtZr3n3vfd7+5nu89dY3+ejjjxnHjhfunnJ6dla2gmREjiiR2XeOTdehkMj9E9bv/Qoxw+2bS0T8DP+HP/Td1Frz0//+TWwaOargbCZptAKRWMwkL5zMOTs54/zqGtX3PHv6hLu3jzlZLujXB+rKoFNAARqNChFTWdabG47mBYGchEQYQw0TAlNw++5tdkOHXs1YzUvfaMgRKUoBVylFjCXrG4moGPmlf/bP+Y2f/0Vuup4xClrTEC7W3L59i7zd04XE0xgISdEeHVFVGlEZXnzlFexygZCgp4qmnzaotdYYJVjUihxHZrVF+MzoPG316e4sCSVLf2I6LCRfooz4jKxNUcRoiWkq8nJGuNmDKvGCOLry5VEyeEiViLIMa0SMgCL1BfgijCKGSAgJbQrVLHUjqrElniBymez7QkFLoyuHUFE2SiEL8hBKpylHlA9YKZAhwD5OWOkiL467PanKiFgOv1JI0LbIjo9mZbu03ZEODhFhVVvk8QIlIGk4Pa4xLTw9OPIhMvgD588Gnl3csDv0tEenLE7O2O8OhODx3UWJ8BhL0yjWN9d0zuMPG5J3nB4f8ez8CdvNhrsvWga543Ovv8bjxw8Z+gNf+epvcXJc5JU5J55eX5FEZpzQ69JIWmGnrmeZgmqtJgJZxrkRRcH31nVVJqtCMqsNTTMrEuCcub5ZI0TBNS+WK5I0fP29R/gYiBn+w5vv8PD8HG0MOcFme817732T+/c/w/mzC1LfEYNn8BGlCyXv5mZD1dYMXc/15TXJeWbzGiMzRmikFdi2ZtZIVgtL6F3x21Sa2Je4pXCZ0JWfmYVBSEN2u9IPSpBDII+RKCTh0GOOF4WSGBK5kohYytyfENFSjuTeIxpDcgFVFwVE4SCXz3Y5hCtSiogpWpdDIFOAJCkGcojIxpaO4xBK/yaBMCX+Vz4cPKe3oTXN3RPsvEbaqYuXSlEfF8omNiWEmuAUofyMTCqI+0/pK6aA827qEQ3FOy+K58ZYg3cOITT7Q8fN1ZocM1KLcrCVUNeWrCoGXxw+zgeY0jJIgRsD9mhJThmjLdZaQihKibpuSqc2FUJcDBmRBUPnSD4xX8wgF99VlBEjDEqVS5x6LrYunykpp16m0vjRk7PANBWh70jlLYNBsR0DbiwuJyEzzsVCvpOStjIsT46QCJqqIWmDkhIjZfGF6ZpEIbSRM8ZorFY0SpPrhtoYhK1xB4+PJc4lpKVplghhSQRSrspWfYo3fgLFGseANJL19QXtfEGD4vj41iSvr9jvdghRIBNXV1cMhx1KZprlkqaeoRGYpqHvO2ZjA9lhjcXq8r7VIjKrDbrs/IFJA5PLVhAoMXiRkTkxm1UshgajS6Rxu7kplyklqIyltRraliwElVSI4Hjy8EOi88znR5iqJgSHkomToxkCRfRgpGLRlriglILBjZja0qeEGzxCKtqqoR8HQkxlyCQkti7vBa2LJr3vR3xwVCS0NhNV1YK0ZA4geS4NlkpjbIUbHTHE4sSS5SIqhCSZhsuoqIYBYypESqhP+pKi1F6U1ozeM7ri2nI+gABTVYUIPQHbYsxUtkYbw9CPkBQpJmxVUVlb4qtkpPcYkZFDjwxz1LeusvTpvyyVVyamgJDlAYT8BP5QEqceSe9HqqahOwwcnR0hRYnBySk7WdWWoR+wbc1OS7rrNadvvMrV4THyaIbXTF4ZDw6cGXAk1EKhqopD13M8WxBcIjCQRs/u8oaTkzN8HDA+4PqeqqoQQhSBVypTt5wL7tnniDF1uTApRUyZm8cXuF2Hc562qtjsd9y5dcL1R494++d+HhdGHr/T8Jnv/m7C2POlP/iDfPSv/y3V1ZbgegKeQ3aEfSnNCVuxSx7b9SwXC7qbNUiLv75i9fKL3HrxDrvzx8xvnzCrWp585RucrlYML3+Gk1deobu6QV9ccbnfs1rNSbYAHXIz4yoE+hCZnd5ibir2KXN5/pR7d+9iqxl3775Ie/6Agxtxfs9hv8GPB3zsEELgvOfi+opudAwuYI0oD0RT7OVSSLqu4/GTx/y5//bP8sf/9/87mrpm1raFqpIzMQRqa+l2OwSe3/N7vsCbb32D1z/3WZYnSyKRmDNJQKsFg8zc7Pb0QeJ3W/z5B8T+Bp8tCni293zj4yc8fXzO5QgvtpI7pysqkdg9u2a5aljOZsjkieOBe6dLwqMDfXDMEpwsl/RKEJOjFhoJGDKp79ntd2QRmL1soJVkrckxok1FoPQM7rx4j3uqPIxTygzBFVypUGXbFnwRLUtg3/Mr/+J/5N//zM9ws9+SVcXtF1+ikplKJmYSZlIiUkIMnqoxVLXBNBWPrq9Z946jtkbnUgI2WaFISFF8YLO6xWpBkgnGhHcOCdhPeQyPWGiCxXsmnh8CU0ykmFBWo5qmbG0WM+Qr9xifXhFuDkU2qwTYUmZOPiLritQN5Uu+UiTnyDkT9sMkCc5gK5IfSb58CYhc3EjERPIe4TNCy0mIW+LG+CJXJrhyWTOiSHBDKICCUAATxIhSBoEkJI/oI7K2oEtunZSJY3G1yDGipaA5XRFUgT6IypKVZe16+j4VapzPrNc7Dv1APVtw/+5dtsNItd0xbG7YDtf44PDDnkotuXp6TsrlEqq1IeXAxcVjtK3Zbm8YO4G9c4fDONK5kXHsebq54vhkidWaalajteLY2CmuJEtBOyRG51jOZ8SU6bpCTNLaUleWHCN1W3N8dIQGKi1pmpqmbUEZwgcfcXl9w/5wAFPx4M23ub7Zo43h27/0Bt3Q42PCxwO2NoS9Y3NzQztb0swaxjGQcma9OzD4wOmdu9w/OYWUMEqSxoHHDx8xW8y5dXbEUS1pqhoXE0OyrITGNpk0gp43eBmQXbmwlhghSF1w21lJ8n4s8awYSGNE1TVq8kxBIvYjSigEunSUAJEDeQilK5BEiX6TC8J4DMSrDWY+Q1UViNJtyuNYLisulkOxK7zjGEs/BquATHJuijeW6a+c5LZZijLhtQZ7dow6mqNqW953MZBHX6TIoVzM0Kq4nET53AmpIHx6Y3huHFGyXDyzgBdefBE39FxfX+OdxzmPNpr9dvv8jtlU5b0tKaCWrFRJo7hChxNS4KOnO/Skk6NC7k2hDN40+CFw2PWTxB6MUowHj9AW34+QC6tod73H1hZjFUrKadMXysZFTr4nIUgpTqCgVHxDdYutKjKJiCBMseyc4ySGNrTW4KObCJ6SShuapuboaFm2KbM5mz6ihSyiep9QlaZdLpCxp61qnA80tqa1hle/67s57PacX28xCmbVDK0rtApUtrja+m5TLvMhImxiv73i9Owem5sbtJIMfsT5HhMbjuoaYy1WFGx605Qkh9SSYXAcDnuSH0Ea5ssVoa4RRrJYLgjRI1Jkc3MNKdK0M7SWGAl2EgrHBIiMkWoiHIYyhCVRa8Gi1pjbxwzdwGHf8fTxI5SyWKOomob5vAWR2G23LBYt8WzFA2sI3uPcyGy+LAMzmbm+WnNyckZVVyQpado5xpaLr9KKqjLkWYvMK5o80sVynrQago8o2xAm6b3QmnEcSFKQkkAJgdaCPpULvDGaLhUMeLn4S4QtEAuhFMqYgliPEaXKxlJIiYugZPE7Gll6cZ8Qq6EoUvJE1BxHj7G6kHw/uZCJQpdOuXwPRiEpSKNJeYEihYSVQAyIvkcEh+89eFd8bt+i16f8lJORQhIJZarRVERZCFAxJypjiNGhpKYbdwQ3+Sv88BzVrbRGGoWPY/kCasqHKxlDqBXNyYrD5SXtbFbMxBQOPnnK/2YQSnF27w6HqzVCaHIKmEpy5/YteueoKkXXDUitOGz3zJYLoikf3qpRBBcQlAfXMDiapkHEjNIZaQ1qUZMPgvnZCZvrK27ef8TZKy+zefAx4XzN1Xvv8sb3fwdeGqqzO9z6zu+ie/Nt8vk5VkdCDhAzSlYMGVyWaGNYvPwCl0+v0VLSaMH+w4/ZP3lKNw6sH1/xhf/mD3H5+Anhw8ccv/oS7e0zxj4Q2xEtBdJaBmUZj054cHNDuzzm/tkdYsrsQ3ngNkdn7PuR48WC+69+lluPPsA9ecTQ7RjHklWNfXE/7Q49x87x9PqS1XLOcrnEVAbnHHWukVLStA3/xz/zf2J+vCKmhNGazfqab37zHb75jbcZR0/fjyyWLS/ev8e9F17k+77/e5k1NcvWQvQIBFEk7qxmcHzCW5dbsqoZ1u+SLz5G+ojS4Alcbi9Z30CdJG1wVAjaWnC6WFCHju3FBQnPkObovOX4aMGZlUijODKKWgq0VQhsOYz4gIkRGTybi2e89+bXWX/uDX7PH/wDJGNLvComkJJ+GAgh0FTVNPERNMqQJ2lx5xyJsr5mHPj5/+6/551/8wsshMQcn7DrPKe6KiLVcCBEz9XTc2arY4xQVMs5q5MZ0hieXFzTnpyVP5sEu77naHVC8iNSClpblYdgioxjyX5rpTgc9hw39e/2g+A/6yUqUw5xTUX2vhzgRl8wpUwi5MoQJCij8SnhlUJqUaIKWkAI5CAQlSa7QBg8iIBR5eGOUUSAEJCVIA19mbgjkYee3ChUNWN8ek3c7BAyU909e57PJwbEMKAo/UyRUzlUj45kNKmRiEk2SvTEIZJTWyAURiKShzFOGysKFrZpCYsRGQNIsLUiK8UQYDeAV4blqeFqvODq2Q2bmw3JJ+x8gSRxerRCG0tXt9jZgicfvM142HJDBj11OYWmmS+4uHiMDyOZxH6fqZZLPvrofbaHAwgI3rPd7xFKE6NjvpiRkRwdnaCUpLIluhNT4tAN1HXDeruhaVrK92wihYhWllnV0FpDO2sKOKduycDHjx7z0aPH9L3nsNvz+PySPHUfmmbBr3/l63zu1Ze5ub7h0PtCOczFSXR19YyTszsIXfx+fYw08yNM03Dv9inOOXzf0aeAkIr9dkcMIxy33Fsa5vMFEcE4JmolUCgwAlt9gnMthxGlJqjC4BAxksngAyqEguuOftrAlNiTmAAgKXlIqdRRnC8iY60RQiONLIf40dNdrukfP6W9c5v5nTMQRaoedx3J+XJxSpEURMlpq7JVJSfCUNxKpm3IRhVcfi5iZowhKY0SlLhXZQoSnDQNCCTZB5ILBV2eKP8OKhVang98mnN4MUaGoUeQuXX7jP/ND/0Q77zzNt/4xjdZ31yXS9F0KeETWXQuRNKZrYpTJjO9hxXJR1KKxIlCOQwj3o3UlZ3cPoJ+cHzjm+/ix57v/a5vJ+bAeBhxnZsUDxGlFDKNZauUSodNyOI3Kn81AqQk5hKBE3kieIrih0IKYirkvEyB4EQXCCEz9ANSKlIs6GcpBFpJmqYhx4RpG1TVoNyIEkWoLnKJ/ilhMKZi0bYchoHlYkEOntpaLg4HlKloGsEuZuq6wQdPM5sTMtADZNr5jP1mT4oKHzJSao5u3eLi2ROENKXbUje0bQtZsN1tqZuKmKGpKjbbG5QpF412PqOd1VitUVKxbCzr3a48W3KhxFVGYbSgHwe6TiNmFVrEAkhQxag3joVQW2nB0bJl9B7lwI0CIQVNZad/lxatFFrBrLZsrjy2KnFZYyuiD1TGoKua8pEuTiYXAjFLKlFEsUrrqVOkCEKQpSxwqKSJYyH/ha5nudAcUMgEJpeOYQwRIWOJ3kqJc4G2kUU0HMJEQ0yTWk0gRRnwG2PphgNSGzK5bClznmipBeBhbI2lLAPIeXKKlWF2AYIoXCjDxspaci6+pRhF6UcZ+OjDh6xO7qCqBh9jAd7EcvE2SJRzCOfAh0lrEMC7b9ln/FN9WfrEPyVl+TJQukxmYnLk+IlWQnDoe6QxVKKUZ21lC8JbluymlLJgPBNQWWSlCZM0VtWW2fEKqSRSC7wP+BgwSUOMVKbFeYewivnJku16h9UaZKLShovDHqHn1EpDEqSQ2Wy2zMWSxWoxreozWmmkEjgXGJ1HGYuUiVc+9wouRty+Z/PgCbdefgn/dEt/s+Hki68ja8v66TMefO1t7v3AdyOPLdvrDS/+4Ckf/btfgqfPqKVCWMt29DSrJV9+/bNgKhKJ5fKIWdWwGz2xP0A/0FQNPLuidZ7P/cB30X3wgIsP38N/9DEsjmhWS+ply835OYPUPI6Zo5c+w8nRKcIa3n//A4yp8S7iQmaxXGBnLfXMcufui5w/eYofPSkntK7J0rA4vs2YrnAxEXLi0fljXnnlBdr5jGHoyZtM3S6ompbZ9OempSDHwLPzc9575z3+3S/9CovFEcdHR0Q/cnS0QGtJ3VTM5nOkiM8FrjEmWpWYrVr+x996m5QrjMqsd0/JBFLoefbhe6zO7nN2dozuNtR1S/Ke8aajT5InH7/HzDvOP3xEe+uIF1+7i9lekXZbjpWGww1uowvd0I1IkaEbuXj0hLDb8PT9d7l48JgHb32T3W7HH/jjP0zWJU7wja99ndXJCSe3zohieo9P8tGcM7gCAZBKorTksN3x8W99jTx2fOmzr9P1ge0YkFkSc+L09hmby2tm7ZycM8Za7r5wG1krHp6f09YzFvMFUpReQ0/mar/jEBLCGHKOk+C2YH61UdgEt45X2LH7XXwK/Oe/Ui7eGMKE9BYF+JJ9IFUF1hFDfB67S6N73sPIrnzZZB9KF0mWiJIPgW534Hg6OIbBlUtuToisces9ygikAzNrC+Z7GIm7A+5qQ1hv8Ls9i9deRFZlQ6NE+bJRJpNcQMgKKSH5iJqr0i3JGVlpfBdLjyIlcpAwRESVyX5EWIWqK/x6i64UomqKDwcKJTFJOqGoFzXXTy7I41gIcUYxpsRSJWrX066WVHbB05wJriMKDcrQra8QxhYfWg502y3eDcXv4keMMWwPOw7dvryXhSCnMqHc9QP9Ycf1ZouUkuv1jnbW0LYVd+/c5Wh1RM4Qc2Y5W2Cs4YJLnB/o/B6BQBtF3VQoo7G2ZrM98PW3vsHl9Q2HfYdQBh8COQekriELurCh24FMkfv37/Lu+x+htMQJQcqi6BdCxLRH2MUR9fIUqSRNXVNpyXEz4yaOZfObR4bDgdhFOnXGg3MFIrO4c8QoLCoHpI8FjFJLklSIoEosKfoCPRgdMmaizJAiWUqigND5sv0zIH1AWklWEqM1YnMo3qdcLvA5F0eXEJI4OA6PnrL7+AlWKPL1hjRrUW1Lco7Y98S9mw7pGmHKIBClyvdoCgzrLcllTF0VMIGCnBxIiaREBQmlg1fEzRlKXQehZPnZY0A25jlIQIgigi5f5Z/ezdInJL+c4eWXP8PtO7f42te/Vr67cpqeF4kQi+RUalU2BoA1liwL+n15ssL70lXabw/E0U+I5lR8j9qi0cTR8/DBEz78+BF+7Pncq29QCUP2AhcgxYg1xZ9GFHTdiK4NtrKkyTlkrGKSA5FCpG3LUEGrcv4RyNIvqQ1hM3DY9IyxDJO0VNRKMuQCnmmsKZ2pqZumjEGhQahClBMZo/WElC6RwUIALoJuITKmbbl59Jhhs0Mf3QIRUEJRVS2Hwx4hFbN2jhs2uP5ASIL56S02l+foukX7QEoSW9cobac+kWaxXDCOA3Y0CAHzpsUqRX/YIzI0sxnz+QxrJffunpGSoKkN+4Nk33U0rcUYW6oYZNzgGH3ExlSoqEIQg5tEywCyfF9GjxHFWSVToK4URydL9oeO2axBAm1tcFLg3EhwgbZpWB0dEwZP1cwQpsLWNX2naeoaHxKNrVAplM6XlGhdyJtKa4JVJBJVVdGncskLpmzjmaAKUoLWgiFnnPPFi6Q0KUT63Q6rTIm7mSNkcGylnCAaoKSmbmZ022uMrabCkJq6eQVYtutHFlah0SV+J6aYey5d0+AKmOf65obj1apg6rUipExKAasUT67WbG7WLI5ul2ehVBijqK1FBY+VedIsSERdQ44kMlH8F8DDf/IlRCn0ilzKpllmskrEqJEyI7WmHyJZK2YzQ7frSh4SiEJjtMRYjZayRBSmn6uWM/TRnOg8WWYwmqwVuExVVYz9SOp66sWcvu/AahAZWWvqeVOy4ChSTjS1Yj16FiEyn7dIrenGzOXjK17NmeOzE0QrIGZSFszmc3zw5aGldSljB5gfL6mMYTz03Pq+L3G4vCbHwCuv3OfynY+5vl5zJ0aUiRyfnfDhV77KS3/g+/jwn/8MKkaCMdz/0pcZhoH9s6f4wzP2Xcfx66+htcBoS9IehUA3hr478Oa//AVe/9/+QerPfZahG3n4zgfcPHjM/O4yoxu7AAEAAElEQVQdTu7cppeKdcrcfvnVsqpt51xcXrI5dMxnmq4bCWPiMDh2/UAUicv1NV1KZKEm+g8IZVBSUNcN88URMRVcp122eKnZb/cspGB+fFzoKcNYpp1SkkPi5c+8yq3b9/jCF7/M+dNnzNqWGD23b52wWiwZh57YNiXTrxTaWhbtAuJDRA5cX2/46GlHf31FcrHEGpTh9NZtXrxzBx1H0AYfMsFnLq/2PPrmB1SHG7Ipca2zmebw9rscvXqPPA7UVcP+2VM2+x2qbjHW0GrJ+t232Z9fs7u6ZFhfkQ87tpcX/Nw//x+497k3eOGzr3Nzc839+y/SLhZoqYmUC6SQZSooUyKJiFIWKRLdesMHb77L0jbce/ElZlJTtZa2KoCMTgu8d1TaICc8p20rbKtRVtONPffu3cdLRUKRZWLWzhBITK3YuxGhBY3SWFXEz6Prpz6cIfnD79oz4H+R1xQJEikiqoL0Fz7C6FGmKrlrHxBV8aLE3pcDYiguphQBLUsnI5bLpdKGej4nKYHQgIPSwBdl4xAikjKdT9N0vXhyIA0jaQyEp5f0SqBeewFpFCFFcoxIUyibOQZqo6YIV4ltqcoiKk+86UEpqCZBbgZcRDaFO4TImMX0jNPF5xFCxEXBIUBTG/qu46QR+IXgei3o9wMVme3FY+a1pl9foZbHzBQ83WzJziHqRelijj3aWrwvEaTpdFy8IpVls7kphW85gTVyoqokw3Aof7ZS4saB65BYb7fkFLl4dsVrr77K7dtn7PYdLiX6bmR/2LHb7xj7Hms1PgV8Lj3W/aGjd57L9Zrdfk+M5QAfc0TmOA3NEsGPSGV5dH5OJnH77JTL7ZZEKRxLYRizpKrnpCw5bDcoAduD47h16ATaDwzrK2LXUVMuKTJ6jhrLvNJobXHCgJA0RiJUoaCqpgJlyf0A2pK1QMhQtrrT302KGV1ZfBgxRqLUdPggI0z5/tCSsnWICaXF5F0LiBjw12vc4ytk5xFVhkNHdo60mBW/kRLIWuJ2fbnApnJ5Nu2sABgAbSyisaD1886CCJOglqmfkApUIoWIMsUdViLEEbRCmlxgKlo/J9YmHwpoYuoMfipfuVz4QooMo+Nw6NncbOkOHUKWibuMEaQsItYQybYMu2JKkCInR6eY9pjz83PC6NBalYtuSBy2HeFkhVxAjIkQEvtdz747YJTisB/QtWF0HjdFpNVM4gePWNYMfcR0EaUjps5IUUjBUmQiJYJnjSpxOiFx44itGnRVkSVEBDHn4gvSvtDTpIJYOquHsYjJbVOVfpIx1E0hvBmjESlT24aMIglJ1c4Yu91zd5qPkXuvvIDvepQsFQQtS3PWVjXGVDRVSz1bcX0pSES0tSitC1RDlJSQMup5N2a+XGErS1Vb+mEsIesM81mDVGLyNuUCgjCas+MVR8s51+ttSQ5piWob2nmFNHaK/FuUKDFZ7zyo4tQiZ9TkbRuHxDj0UxxaTsNJhXcjRkClDXai8eVU/h6s0cRQIGWL5RLXdxhjkLbCOUczW6KVJsZxilcnlC3ERKnK35+QZQFAhNoYmmQLMXBwaG2olEXIzEylQqvLqfT3cy4RYFku2UJpKluhvEDa0qPWdUMIrgzkpuhdihGVS/dssWjRUuBCJIXM0paur/e+wGOAOPUbP9lyXFxcUlc1i2XZRoVpuKckbK6v0UIWiW1pWFJphRVgQkSkgFSAtQQHIkSG/QHxX9Dh/+mXmCaSUhZBpNSqMO9jkZb5lAjkUqYF6raUApUuGcpPPsgASikGPFlJFvduc9juS6FbZA7DWL6EpCSnjJ7kssWdU7C9yPLF1cxbxm4osr+UaI2mp0HNGlwYCV3iwcWOk9NjfEiMo6NpKlCKwXmSoPQQokDm3/53AjCLBtPUYA3NnWPyYWB7fcNLP/BdHO87qtMjTM7IF854Y/Y9PPiVX0ctV2xvrnj12z7HcN2z/vBjGAeMVjTScHZyht/3VE1DHseSmRaK5WxBPgxcvv0u9ekJ54PDzRfMT0+4XK95vNtStTPObt/h0A/cbHa888GHrNcbqqplvR0YXekHHfqO9z7cIJTn0ZOn6KYlpIREldiiFPT9YYoYGGxVU80XHEbHoqrxQjNmSe8j2eTnskNjDFqX0qGtG759ecTnvSelxDh0aClIKWGr8hBIqnzociyTtCgE3RCIzpUyusuEXKFlS3vnVY7u3Me7A9dXTxGjZ6ZrslA8ub5Gb3a8vppzuqyoU+Tq6oZTKdj4wNFrdzGziqaLuKtrdocHnN4+ZRCCR7/6H4iDZ9cf2Hd7xsFxvl3z8ccf8f/42/93/q9/+//G8vZZMZ9T3kMilfde+uT9LARBCiQBt97z1Z/7t2SfOLt1i/U73+T01l2ylLRo8uCIIcPomTUL6tkMrGZ+NEdXmqqqqI1h3lTsvGcXHFbpUrJVGpdgqRUyB+aNRWUYvKfWmpQTtdaob6E1+/8nryk6IFTBceNK0VQ3FTIl4uAKtauExxGmfCazUeAlykpwsXz5SomQ0NxZ0cREWB9KzE8W1HJ/vaNZ1KVUHT2ibTC1QFpdonUxQjeiJAihyL2DGEuh3juELDGn4DIieHROiMoiq0zSiqw1urYoUQ6hQorypYVAKT1FbzQ5C5gOFlIKYu8QzYxu0yOzZKEiVS1oVM2HH/TMas2rL93m8uqai8sd77z9Jq9//kvcfeke66trQgjIqsGFgDA1IgTSWLZpmVLuJRkWE2XLe1fuT1E83zB4n5BSTGQxVUr/uRCbcgpsdju++rWvcXJ2SlO1+JS4vr5k6IvPJk8Z++sbw+Pzc3LKxJio24YQEzGE54RqQQHPiFz6ruRMCo6cE4+fPOXWrTPunJ1y2B2IKaBMS5IVwQdS2lHPV/jRsb66YG4iizvHHC9bPvA9MxlYHc2JSO6crZA4ZpXCKo+pW9abQK4bGu0xsmxZktaIXJEkE4o+T/8jCD4SdiMpSfy2pzqpUUqAmcrttYatR+dIzgFEJMUieVSk4rf7RFJeGUQIBS6SirdLWo1ZNeRrhxSJKDJhHFHztmy7fERVmvp4idQa2dTkGMgxkii9pTwR8TAKWVvEFDVLoYBH4mFEKEXKvvxMMfEdP9lWTx2dT+sreD91gCQPHz7iZ3/uX3F+/hQhJM573DiSkqaSFv8JQAbKvzuyeLpS5OrJOW70xBgKWY1EyOUAm5Ig+oj3Hms0J3fOWDxYMdcV3gcG7cpjSILzkZtNwXIHITD1QEpgakOdCt465eK7YUoopFz+/EOMjL4IqdWkUYgxEXMi5kjOhpwiMQS0lFRa4Q8F9mCVxrSW6APBB+aVJW0HbN2ilMaa4uypmpY+54J/FgpT1eU57AOmsiRTIVMpzNR1SxaKiKCdz/CjQynD8dkZ3aFHal1ihTLTLhd0/a50wYG6bZEZamvZC8F82WLrEiezTQspMV/NaRuDkhEoFOVZo/GjRs0aIFLXmqpWWC2oTYbkkEkVnPvky4wTVdKPjrHvicEhJ+JypSW9yLRtidRXlUZbSW013kdmdYXRkqqpmLUNw/KIqq5QtkZIibWmDCcQ6GljKKf+mVYFyS2EQNeFVphzJO4P2NYQcqCuGqIqvdq5yVyFQJycfZmMVILGWkYXMEpQGY2xmhR7lBDkXP5XUuL3TB03ISSVrZDT+RXAKIHPEQXlc54LKhwJSmtWq+UnbFeUNJMcvFyJlCqfl2EcEWaKnGaJNYa2qtHDSDVtRTMKnzPejfjDgW6zYXHn5Fv2Gf8djXJ+7Md+jG//9m9nuVyyXC75fb/v9/FTP/VTz//7YRj4C3/hL3B6esp8PudP/sk/ydOnT/+jn/Hxxx/zwz/8w7Rty+3bt/nLf/kvT3nG3/lLTdJVmAan3jN6T5YCXVXTwaUIu7TRpZQnCjY7U75IU5pQhTk/p6rIuuL4pXvs3YjrR7IQxJxQRpfStSiOAkTBDssMhEx0gRQizaxBmPLP6ZBYIglIkixC0E0ASeDNd97jZrMtNmxlqKwFQZlKa4WCKQdcCDVCKYJINKsZJ6cnHH3mHve+/fM0929x/Np9UAp7tGJx7xZ3v/A6r//Xv58Xf//3c/T5Nzh/72Nu3n0P4xxSghKKuZ2xP79h7AYWd0+JM4O4c8qL3/s9hLpFpQQ3N+yfXnK+3nD00n2Yz6lWx4iq4TA6UhY8enjO++99RN+NNM2cYczsu4Awlv1w4PLmmsvtDV/75lskZUmirPkjFUFaUpbsNlv0VPSLUuNtzcUQuehH0mxOqBaMsXgMhNAIWXg0xtiCHdWauq7L9GfWslotsdYip0me826a6HmG/Q5rDBjN9tCxnFdUsxl2eUQyglwv+NLv/2Pcvn1CHg5UQnB5eU0Uka7vGYfEcnVCUhpnDGI1R8/mKGMZNlvoR9w4kEaHzJC3O9zjx4yPn7Dd7ti5jqAy17s97z87Zz/23LItPL3mwVtvo7Qum0YX2B0OXG+3bG62XF9veXJxxeXVGrfrGNcbvvpvfp5Wa9LVDU/eeRepNMOUEddSsjo55uz4lOOjI45Ojog5sTo9ol20z+WHOUZqqbi1XJQeNyV7ngs6ixwTx02NVWKamGWs1NRa01hN/f/FZenRo0f86T/9pzk9PaVpGr7t276NX/u1X3v+3+ec+et//a9z7949mqbhj/yRP8I777zzH/2M6+trfvRHf5TlcsnR0RF/7s/9Ofb7/e/49yI/mUalVDpABU1HGB39kyu6RwWy4rsSxZKNQRmFNBp1ukIt2gJ4aBpEY5FWY2cVIudykBxKdErbAtSQspCSbG0wtSq0sZRKnwOBrMvEVOnp9yXL5qVcbigmVVNEkcnHQu/TutDHxDQcqmrSfkSWFhOyqsrlwQX6x5e46z0iC5CaKDRJmqJgSgIrSsRLK1hfXGLqhjtnC4gjQzdwelyKzpurS+h3vHj7mJM7dzDLY4w1pFBwsuSCntW2QRlDO5sRY6TvOzITHjinEoMkEUOZQsZQDmeZUv5PKZByxHvHodvx5PwxH3z0Ph9//AHr6wu6wxY/Djg34vzIOPTsd3v2+x3jONAdDhz2eyZodsG4k0uPZurhZSClSEqBEB0Xl1dstweaeoapWurlCSGL4swxFjVNdKXMnB3NeP2VF7E58vJqxv1bp4z9iJaZuycty/mM62fXXN90yOiZt4YuBKJQRCnIlEN20prD+sDh2Q7vIhFJygXkIqQgubGguoWAukZWqji0cqFhmmkCK2uDqAXCiBIb7Ycyga7U88uzMIosp8Oe0ZATyhp0azFt8eiYpkJUuoAixlDkqm2FaSv01DuQbYWoa/TRArloymejsmVbmyLZOfxmj7vYkA7Db39fT6j9nEHUtmxmf4ev/zU9Qwqoohwo1zcb3nn7XYpSTZYNBGXg5Zwv28xpK2htIZBpXQ6f+82aFCPjMBC8w7thOhCXrVGcNiFVbbl9dsYbr73OvbsvopRmGEKJf+WITyPfePAuz/prdGXwvohTfQh479n3/YTnLoV6ITRdP5JzxoVyjhKiIKAjgpgCIQS6Q08MCUS5BGitGF3pd9Z1VQ7ZWk81NVF+v3VVYmLGkEVJ88wXLcbocnHMmZgF2UWsLtutmCKJwMnJMU3TUFnLfNaUZwrF91M18yJDLplPmqopPR9jy68FGGuo5y1lNiSppy2VyGCURivJfNYyn7U0TY2VUBlNZQSL1jJrJJVVWA1aRNzQ0+07xm6g7wZSKHqNECLBFyDQOPQc9gObzZZuu2V9eUX2HmsstTUsmprloqWpLXVjMdY8hypURtPUFUeLOU1ly4XJlM9U3bTkDNrWKFsVBLitysaXUilRk2dLAHVbI6XBmgqtNUqWWOTNOEWfc8Y5Vy5dUrCYt9RNjSRxclQQ4zFCFrpszlTBhydKpFRrTcqx+EalIlOeLSElXEjTGa30FVMqZ9mmbks3KbiyVROyDO6kKt7BkHj25Jynjx4yn89omhopcvm7M4a5tRgpini5D2Vzqi2uHxgPHc5963qPv6PN0v379/k7f+fv8MYbb5Bz5id+4if4kR/5EX7jN36DL3/5y/ylv/SX+Bf/4l/wT//pP2W1WvEX/+Jf5E/8iT/BL/7iLwKlBPnDP/zD3L17l1/6pV/iyZMn/Jk/82cwxvC3//bf/h3/5pUoxcKYJsmVLrnL8p8lYyg2cqVkEYPJInVLuVjFXQgM44g1paCmUdO0rFxstJRIH8FHdF2VRLUQZUonylQmDCMhBISU+BgIlcFkQ9O26Ebz6INzts6Tbi2p7ywZk+EwOPZjgvqYdz5+SmVrTpTGWl2AQKn0D6IPpY+gzZTtLwVzMkU6mMFIiWwqXBqQwpZoyzStmL/8IljD448f4q8OyOCxTV2KwQJcdCACOWSq1YLlrTu0L7yI9wVTLIzEX69ZLFbcWax4882v4UIkS42LiYvLK549u6E79FRVzaxdMrpAVcPVzZZdv8fHwGHs6Ycdu9FTN3MCCWkbpKxJKaCFQKTAZrfFNHO6EFk0M3rVoKQpkjoPekicrSxKgciyXCCnD72aRMQ2F6KUrWvIib4vmXEoBVQ55WZ3h45uGOmcQOZAuDlHVZZqeYIMEaoZ/fqS3bNHXG4Cr7z2BWyt8OOe5BxHd46o8sDDi2uuVOCLL99l3g3UIdNdXqF3e5qzM1afexlT1Xz4S7+IIZOlYXSO8+srzi8vQUlW9QzQVFrw+Ktf55UvvVE6ZSkxxoTSljBEdn1HEIk0DGwfPWT95AmXDx7wxVc/i0iJ+ckx2gey0qWgaQ31ak6jFFlJopT49YYsMvN2RjufM8bAMPQoJYjBMxOKKA2SUkg+OE9tNEqBotjmr7s9QleQIkYWz9nv5HVzc8MP/uAP8of/8B/mp37qp7h16xbvvPMOx8fHz/+Zv/f3/h7/8B/+Q37iJ36CV199lb/21/4af/SP/lG+/vWvU9cFKPGjP/qjPHnyhH/5L/8l3nv+7J/9s/z5P//n+cmf/Mnf0e+nOGMKFeyTI1vYd4TOEw4j2kf0cgbV1K1QCtE2KD+VZGuDnjXEbVfieylPOXxR4qKDR9cFzCEmNKuqMrrWaC0QOaGMQjeadDhgJvF1VqDnFWFwCA+qlmRfttiFmJZK7E94pJkTk0dlgbYaMyty0NB5kkuIti7T6f1A/3SDOVkhZgtEa8lal61FP7I6akp8KwlcN4BuuH2mefj4GUR44WRR4hJxyfG8xg97Ts7ucXx6wvWmw2RX4nk5E2P5IhO6Qs1PyXHE93uQhfoocp6IpZBzifmkaaPiRocQn1zXU7no5XKwCt4/p0OWg2d4HhUT5EmuWU7lOWfSmKfcfNlgpBynZ8LkCJrQ1SmVEnJxlFh2YyKiqVcrTD0jS01Vt0gpGfseESNRRU5mLf31JanvePmF2xx2e6JYUcni/7h7q0bZVXlGhUBbKxqtybrEs7KUhAwpZLqnN7A90N5ZkHWZtoeQn3dBzKLCHteYpioHNVm+q1IYEKJ8ZrOMoIrrjywRzqEAYxXxIFFNhWwrdGuRRpEcyJxLj8QoZFUR/YDQCqElIqlPlqqo2pKng7S0BmEb1NGc1I8F7LCYlUu9VgVGgSCPHlwgxQgTMl/Uhiwm2HJKZXNq/uc/R/7X9gxRukzIUypDgFrPQaqC2taGWesZnCPEQjJNU/RJK4VQYpJbZ6Q2RBJaF/dMnro9TVuXjQtQzctGpGkrXnzpLhePb4gxIRO01hApl46YPMG7EgOWEjdEoocY4fz8EvWCxtqKcm0r6ZryQCxQmXH0RXidwA0BYUx5r8Xi8tKyvG9iSjgfWZ00CAlx8ETpISasteSDQyNpm6ZskCjOROciQhVZrjWG5XLBsN0wOs/BbZgfnTKbzUocTZU0j8oZSGUT0lQM1rCTgIhUVY3MZcijJ8x1zJlDN0zuqFnp+WgBslQqRC7gBlJk0awwVqOGEWMN1fQ8sFkzDCPXF9d457h7+4xK3sJoTdtUaCXxwzjFZRObzZarmz3r7Ybr6w2jc9y5d5fatkXfECNaZpQS1EaSYxGH15VluWhZreaM/UBIJZ6XaZBSoISmqgo2vosepQRqutyRU4nACYGdVbiNI8SEcIHFcoHvXXn+Z0HIk/YkRVKM5VwkBcdHc4QauLjaYLRFNS1GhQI+m7pYxAkKMm3uYph6Q9Nzm5yJMZCTxo8DMidEFs+lyEfHJ8+TBsbaaVOZETmUwYDSPHt2TrffMl8sEaKc89qmghzpu45KQsHQZrQxaAXO1kRRtnvfqtfv6LL0x//4H/+P/vPf+lt/ix/7sR/jl3/5l7l//z7/+B//Y37yJ3+SH/qhHwLgx3/8x/niF7/IL//yL/MDP/AD/MzP/Axf//rX+dmf/Vnu3LnDd37nd/I3/+bf5K/8lb/C3/gbf6NQ5n5Hr5ITzTkTYi4Ujwwxl9VoyJQ1cpxumxKkKFKwBBMMIk8isbIYBEAI6tmMMOvR0pdpoy8PjkjG1JbkfBHtpVgkgVNp0w8jmYwWltB5uvWIQLOqah5vI7t+T2UavAdT10TZ8MH5mtpmrF2hEaXISwatGPoe+8nEUJZiZYyxFLlDmCIMMKsqumEot3hKjtZkiWxmfPb7v5f31jvGBw9IaZqsaompNdn17DY9zipe+fbv4sn1NZvrqzLpmy24++ILbC83VBIePPgIbStQFTFLlotjnAsYbVnM5+y3B3xI7IYDV+trEArbzEgCtt0OWxc6TMoRY1uk0sgEOmUCCZREVTXC1Mh2wcELVFT0Y2JW19yMgdsps1TlsIUQpfRa2SIEBYgZP028PnkYpBiZtzOs0myubtjvD+wPXcnnysCbX/lNxMFhTl/AC4Mf91x98BZPDuc8ff9NmvvfywuvvsZ2F0hDRwoHqtYSh8Cu88Q48iA/5mG/5oXG8BlzC7/p6C9vsMuWe9/1e/j1n/9X7B98TKTi6WZD1pmj4xUhCmKmiIiV4Gu//MvcXDxjcXzMd/yRH0KcHrMfPWnwIEuOentzxcUHH7J//Jjh6TVpdYf6eEl8ZMk+st3vOG3nJBkJzlG3LcZWVLOGY6OoKst+u8XemtMu56xOjoqQkszJcsG2Lz6UwQ+4GKjJzBYWqwzr0CO1JIhIW02TMH5nNLy/+3f/Li+99BI//uM//vz/9uqrr/72pzpn/sE/+Af81b/6V/mRH/kRAP7JP/kn3Llzh3/2z/4Zf+pP/Sneeustfvqnf5pf/dVf5Xu/93sB+Ef/6B/xx/7YH+Pv//2/zwsvvPA//ymSMjn55y6e7CJp9MRDj6oqhC2TfdQUxYsJ1VYIaxDbA0JrVFvjuCRcbZEUa3rSErkLJe40Tc7EhOq1TY02AqlLIIwUkNKgjACRUYsaYSV6OSsXKiWIuw6MRpAL4UxOMlpRABS6NoiY0fMKO2b8biDF8kyLLlAtW0I3ElGFrubd/5u9P43RLDvvO8Hf2e72LrFHblWZtXEripsoiSpJHrVHsmQBQsOAxsvAsPnBsAHBssfWBwMy/MWCF8BfvGBkCzKMmWnAgoG2WzNuwWPZTZlaLImkuEikSBaLZGVl5RaRsbzrXc46H86NlNgtGqp2a5oE+hJZREa8GZH5xr3nnOd5/v/fH0RNRKKqgtKoMddE4l0gALPaYFcDyhQ8+8wuq9UGHxNlHWkmDe225cHZlxCy5kaVKOYH2PUly1XC+wEpFVUzxXvH0Insi9RVnjokO0o01Hhcy4ULANGTRP6YFJJIyh6jK5l1ykjr9D9bu/N+nTOzBOPkNOX8U8bGWt4pMp0qT79c/lopIIRB6ApRlviQyVSmbLJRWWuEKQjOUTdT4tCye22P5ZMTzlfnHM0nxLqgPtjlparAby2znZq1DVyfGua7EyQ6U8GIRCGIRlMWirTuYRgoYgZz+Nai9htcO5DWbfauSklZGERVEoIlqRySLLRCxA0kR/AD2ghCP+SMJhLSekQImFmTvQox5Xu3NiTvENYhjEHoPIHykiwLLVSWi43TN4UheT/CZkBMK/SkwhztErohd4rnNRhJtMP4LGc/HhJ851BekMoConoa8yHGUNq3QsP7RltD7NAhymoM6i4oqoK+71Fa41yHlBBcyNPS0ZuhlYIkUVJRViWbS0dwnpA8RVEidc63QkqG3tJqlb1AVaBuSgIRqVT+OiHloivxlKj6zNFNmmaC0QqlIiHkXJ2JLblz55lcyAjyuWiUVgmhiDGSRMxNF1MQXIZn+SGihMkAinFCVhY6y+2JVCob8OWYpZWtbypPPcqMkK6bElUrlIgEZynLEiUVjSno1+scmisVZVFloFCMaKmYNlMmkylS5QJUonIGlZBZ/aw0qsxFelGUCJU9glpr+q6lrmpMkSc7VWGwPVltpA1aS1JyhDjgbJ7SihjQUqKLgna7Zb3asN2scT7ks+UoO/WDpRf5/h2sZfCBJBTbtsW6lNHrQow+zBxuPpnU2R5gFEWhsC5nJTZVgTGCZtJg9LiWK4EP2UZijGJSF+ztVFyejBEiStNMpnnikxJlVWBjBi2UVZVPjkNEy+zrkqbAxZijApTGx4BUBq0NRVFytAOPn1yiyT9D21ukNqAVwQ4UIv+bSblJJcSVJzGiVT6PaZUoS0OwWeVQ1iWFKZnPd5jv7FKWVc7MdD6jxUn0q0vqsmLrI6asOTg4pCo0WgpCoSmqgtRbRJ1x+5kGW2RvZwyYZkrqxLjm/eFc/6sdlSEE/tW/+ldst1teeeUVPvnJT+Kc4/u///ufvuad73wnt2/f5td//dcB+PVf/3Xe8573cO3ataev+cEf/EFWqxW/8zu/83W/1zAMrFarr/kF2bMkhUCKkUgSAm781Q0DgYgLYdxM81hYjAazFHOHJeTnMUvxlCQqgdSZIJYEWEPG/rossROA0AKhBT54hq4nOY8fLMO2o5CG6AKu85zce0J7usG0Lfskzk4usTGQUqCqSi4WF5wvt3z0136b04WlHQIkgVaZmCOUZDIZDbYp8+kZ/18qPSI/Y57UyKxlRWV/jtQKGyxaQHHtkOd/6I8SDvaxIRGkIghFipJV13MpAp1PPFmsmezvcfzibY5eeIb96zfYDh7qErkz4daLz3N8+1mme3vYENm2HcEHJpOG5XJJ221p+zXWdUAgMi7qrssLeIwE35HCQHKWYFtcv8YPLZAwdc3O0TEOxdlyw3m75bIbuFz3nCw2XNjE5SDohoSQBYOLbIccEGlDJITciVZS4aylMHkhjD4QvaNbrXj85n3Oz84ZBpelJ1KxuLxkuHxId/I6dn2O7xc8+PwnOP3y57FtR3SO0/NL2tWG89NHPHpyj499/nN88dEpVmpM2bC1iSdby5PBsW6zdNP3LV/6nz7Kb/3qf+ZcJu6en/P5N19nObQUps5FYdGgqhnoEolCh8Tmtdc5+8Rn+NX/7mdp795FtRu6kxMWb9zlS7/6q3zu//3zPPnkb7N67S79/RP60wUPP/MFqigoixKtcx6VTDCbTJjPd1AIfD+wu7dHOeLxjTFIKTk6PsaHgNGKpjagPJFAY0qulSW392ZMC0mjBROjMCkwkTAtBDtNRanfmvXx3/7bf8u3fdu38Sf/5J/k+PiYD3zgA/zzf/7Pn37+9ddf5/Hjx1+zluzs7PChD33oa9aS3d3dp4ccgO///u9HSsnHPvaxt7SO4EP21oyTCr/tCC4gpHg6YZPlqBnPGtbcTEgROamzjC5ERFFkSa4YJ7/j1xUh5s5+pTGVwkxKREwk5zI4JgSks7nDXmnMRKPmFdXBJMusjCIODlwm8vlVS+h6UgjZp6N0boB4R+j7HOYsRl9eSgQXCGtLd7YiCkV1OM/TGu/y65zHmNwdlFIitWbw4KPHNCVBGG5eP2Y60VR1jS4a9vamuCAYYsHpo8cs33yVG1NYPX7AXlPm1HZdopVGl1U+iCVAGMTYKIFsYB8bkmPhciWVS08PlTFmP1gc106Io3T6akJ0VWr9nq7i1ZqZfzP6l1xGbGdsUz7Mxfh00iSEQuoCWVRPN11d1QitQWrqyQ6kiKnKvAcIT10IHt2/x8M37rHebFm2A4tNj9aa6W6BKUtKqRm6fpRZenz0oBVKCaSIxGCR0hHtBqRDlYCBbt0xrAdC7wmtQ7gIhUb6RHKjhDKMxaOUY/c95qDkYcigkcYgK4mqNWZWUO1WmMagJwVKCmL0CAkiBAR56qGMQY7yu6KpQApkiiAFSmeAQwqBZD2qyX4FPWtQTZHl6ZKn+5QQAlEWWSooJSlEkvcokScpxJQlV/1AWHfftGtIjOOBsTAwFhSCOHbaE6u1IIlMXrQ2A5xiSjjvc7ZMSvm9G+9/5xxhGEjR0Xc9ISTWq47lcoOPkbbtcT7/md2jKbrQVHUu5FPM9/ekmtDUU7xLeJsLNWt9NtqPkRZSj9L3ELEuE2qDD089MXHMm5PIMcZAjpLViJQKH2KGoJAotcZ1WaorAD8MI85eIIWiMAVucAip2a7W9MsFw7YdX2uJPmLKKtPzYoYjKKWzxL5skEKhdJGfUymyDJYsrxMpx4gokdBSogQURQZExOCBiFJQ1YayHAWrMWTkOeCjo7c91lsg4qNHqURdGUiJ/b0ZL779Bd75zuc5Ot5DisB2s6Lve7q2Y+y20LU97XaDMZrj/R2ef+4G73jnizxz6xrzeZOzI9N4jpRiXNMSk6amaWqqwrA7a5g2FUbnqVelMnCnKHQuooCyqhFKoKRAqyx3lFLk2JuQbS0yJaJ3eJsx4LOqolHZQxpRFMagpBoBD7DT5DNBinnPkDJnaIrgiMMGER3BdcRhi4iB5AISidGSqjT5fQtZgi1IObBYiBznMN1hd/+YJyenGT6iM9BCpEhVKMKwQuuE847jo2Nu3nmOKEXOhVLZxyqVRBUmT6aRKJ1hXUJIZFmgmwYX/uANl7d6vWXAw2c/+1leeeUV+r5nOp3ycz/3c7z88st85jOfoSgKdnd3v+b1165d4/HjxwA8fvz4awqlq89ffe7rXX//7/99/vbf/tv/i4/HUU4mrjCk8iqNOpsjfYwUUj31I111IdMovVBKZtOvUU8LKiSZLuUDRVnQxcBkZ07s8g94iDnD4Eq6oZXO6dwyV/lKSHxMLM9XPLr3hOXDJ5ycvcm3VAa7u8fZyrIrI29vatJqjbeBi0XP//jR3+b/+t9+F5OqfBpWK1Iu7lSZR7chBCLxaQo6MSOOB+8odYmwYexWKaxzJA1yVjJs10xv3eL2d38njz76n1mdnWGKht0b1ygLRSMC9WyX+mifELPwZYiJ+bSkaSZ0zvOfP/EJHj++oG0HEpKutxweHOK948nZGReXl0gFPnmiFLiQjaknp/fZbhdMZ3tcLs8hZUQmwRGFJNiekLJP7HB3Dw8gFKtNSzFrSPMZVT2hrCusVLx2tqW8sZfDELVkvVziIkzqfGjfrNacPHqAUWIM79MkHzh58Ai8Y3F+jg+a9SYHYS57gfMBKWA4eZPkekTc0PcdkNDVDC2yXHG2u8vi4YbF4gmi2cHMDgn9glv7++zPah7ZDSfrFVNTcH02RWpD3LZ8/iO/zIkd+OpqS/CeZ5opoprz0nd+kMvHpzz60t1MmpMCowUyeqzv6N/4Cr/y//x/kaYz3nx0iveeRsCh1BQ+YVRi0In7FyekvmewlkldonTExcRuoaknMxIw9D2iLHA+I0fbvqNqW/Z35hitcSFgZEF0PdNK0fuE0pqjSUNloNbkkXpluHOwRxKCQgqmRtG/RV/2V7/6Vf7ZP/tn/PiP/zh/82/+TT7xiU/wV//qX6UoCj784Q8/XQt+v7Xi964lx8fHX/N5rTX7+/tfdy35euuIXWxpdg2UJTLmQyBppHaN0iOh5djRYkSok0llNhB6S1huSYttLnhSJBWjv4iAFOkptEAak0lh3iNlDqNFZkojMaAKRbFX58ZIqUeJRCIVmkQJIkI3ELVCaoNShthZ/GpAzzUxJISRBB/wzhHXjiQ1wYOyClkFzE4NTYMoQQmLrgqCHzJWP0HwHh88USgWmwFZVEgViEkTUof35BylFJgUEiMCr772O7TLCwYbKCYzZk2NcwO2HxAhr5NBKWIqM97VNoixCBKMzaqsL0akXGTmSieN1DdGr2mejMD4mzG3Jn8NntKWrsqmvO4nksi+pLywZp9Gig7I4atZXlkgixrGQF8hc/HkU6KuJiAExlTUTU1jEmcXWx6+eRe/2dAkz8XOjFvzHU4XC6pixc3ru2w7y+5sgpOSwXmKMoc+ohLeWxQCoQJIh64TbmYgROyqx0pBcInCBVLbo+cQt5ZgDFQSafME3bkxiDEbBnKRogpEcAhpkI3JOO8+omcVovQ5uy8OqJSIRiKUzKAJyJhya/M2k/IhLIw/n0QapY2O1A0MSuDbHj2fZK9U9BD10yw4MU72UWMYso/I3pMKi5jWueAdPNE73PIPTtX8RltDCpMzZ3wIGJmN/t4Hhq4jxYgdPNoofHDE5EgiEpMHUSGE5NHDM4TeyR6iEJGFHPHdOactJeitp3YJ67MvyWiFKRQxFMzmU6QP+BizYiJGtDFUVYn3+bU+BnwStINlSoXzLj8vUozUsjia7BUhRmJIDNZSRIGqS7wMuBQoTUZGC5XlWD4mSqWfZsCVVZ7EhzEvMMnsuTZlmW0CSbI+v6BfrbNfMUWC8yil8M6jpKY0BiEyVj+liCkVYqQGphRIIgO2EokoIknk2IeyKDOAK2UoTF0olDSIlFAiUpWKptJAluuVRiFxREf2Im17jClYrwTOO3ZCLkgLU+HsQN00YxMgUtY1VVngrGXSVNTTXZabjAX3efyFKQzXjg9xwXN6uqAqDUPXA7nwkRJc11JpwcHBnJQy5e/h/cfUKbK7O+Hicj0uZil7QlNk0jQ5uJosRUu9zcCleoLWCpUCzbxhvekoy5w3JzpH6QbWuiEgGWJitjvHbvYpi4LaCDZdtkRE6zJZVSWGbgveEgHbJ6pmzpVc+WpQ4UPEh3z+dN4y9B1F8qhRSTGZTpH6d60TYpSkm8LQ1JJnnrvOZtCY3mUoR9lmlHjKmVgigpKSJCKmLsFaUi9z9p4PBJetNekPkRHzlould7zjHXzmM59huVzyr//1v+bDH/4wv/RLv/SH8Xd7ev3ET/wEP/7jP/7096vVimeffRYpBEJkRn+Igd4GIjpjwEV+WIeYKIR82mUM4QpEmHAxIIMYmf/jpjt2wKqqAuvRE8XDL38FHUCWBiU13lqczZht5wekzlkRVVPlHAWhuNhaPvHaA1If2Fw6ildf5/Z/c8iDjWNTGFYbSwwQg+e5l54jkaVPIeWHXqaIFInBe6Qci7Dk82YVApA3OJFk7vCkgCo0g7VoLfOCQcRZz8HhPpvFime+7T20p0/Y/MYWuTNjq7Iscef6NWRVsdhscesWPa3pQ0C0PWVZ8/lXv8xnPv1ZhMlp20IbnHWcnZ3RDWMXKQw4N7DcrGlmc4qywfWW9XrBzs6Mi/PHeN8hyBpZ3w8ZGxwhiECygn7TIq5Ltl0HpqC3eQy8tzsnSsHGBb56ueDxxZL33NinFp7L85O8iBUT1ps1SiQOd2dMSoGKkTfufwVVFjRlzbDeIMieIVMWlGVNe7HJHV1y8rQXYSS/5A7FZDrn4Gify8ePSKslp48fE4WkqGsenJwg3YDrHT/47d9CqgsOdm7gSbyxWLBTVFTljPPV6zx8/JiL3jKrKpAlVDUXiw3v+vZv4+L0kv5ik7v4BNY+/5yDHSjPz+hPTgk+UpQV+9M5x8/dQbUdd7/4RRZA2W2Jy3X2Fs0bfMhUnGFS5lA8BE3dIKsCqjJ3eKWgaSasVhuaqsp4dRLD0DOpa+Z1xbofiMkiUagk85Sy0tSlobfZt2AkePnWdMIxRr7t277tqU/xAx/4AJ/73Of46Z/+aT784Q//V68XX+/6eutIRn5nj5Fr+7yBDw49rRFj91UkoJRZfhIyxj0kSNbhztekbUs6X+YgzpRAlETvs4dGgS41bjzISpWJeWg5Nm5i7gyOKFtRmfyMh5D9HylPkCgEdjMwrDuEKdAoXNcT+4RMCV9MUaXGr7cZjTBkqbBPLiOevURTMDhHsVMguxbdgNATQKJJ2OAJXHlBBT4pQrB4H1iuBoJLlEVJu+2YTOccH0/50muBvm95+PARO/sHPPrqqzQHN9mZTTjtM6mOGEFpFHmNk6bOUw3fj1RxmX9/NR96yjvnaSMrFztXv78a4f1uJ/Fp02z0MYJ4+mfFGMaJHKdZKYxd/BwEJFSJLBtQOZ9FpHxwds7SNDNS9Cg5IQXL/nSXfnXB+uwRYVNyfX+f3mU0rrUWoQ2Di6y2Awc7U9a9oygM+0aSQiIFm8l0CJQCSSANPSJ4fGsZ1g4nFAMBoQ3WWVSKuN6hq0gikAZLwBAl+LbHLrekTYtvFNJIiB4xnyKb7ONFCJLKe5yuNSJZCIkUFbGzGbZgsw9Wao0yerzvU/boqfy+oRVpyCS84D3xbJXR31JQminR6FyvpoylTjKHkcayIAweSSI4D73N/luTKZFXYbh/0OsbbQ3xMdO/Yggk7ZlNdrhYnOG8zcWLADsMuTgZhbox5Gm294HV5ZbZ4S7BR6Jz6KJEJklZVJSmxA0+S3HJloPJpMTZgRAEQ2fZmdWIwbLZ9DSTHOIaUqAsMvkyAboQDMHjRp+Rj6CSzqjz1uLcGOUxovyN1nmtE5JgM7kxpjbLV2WWUBqjKaJnUpQZGR8z1CamNKKiJabMHrtENvInoDu/IHQDxDy5L0oDImL7nsIUFNMZfchTo6au2XYDTV1jU/YRkQRD12Ypl9IUukAKjZJgdI5GEAKUEggRnjZJtBLYfouUUNcFMTqsy0AEYyTrtmW+u8dytWQYHH3vmTc1h8/cQu3Osd6zWayZVgVHk5qqqbm4WFCWmtnunLLUbB8tuXhywfxon0o3PDm/ZNtZNqs1CEW/7ZBK5SlYaRjswHxnmr1KdkC5yMH+HtY6TCFpSoXWBQiFKxTbTUvdVDjfM7iEVNlqEkLAekdZlvSrLUOf1VDuqu+kND15Oty6TMd8z7vfzuleyI3wbcfQehLZUhKCY71YIEcUux/6vAaMa7BQiRgs0Wc/XvRu9H+NUl+lUEpTVhWmLEkhUFYFPgR88BRlyeBdbuBqTXQKXWT7iZByRLVXGG2opCBZ9zQjU8asDrN9IArF4AI+WPTkrVp5/uDXWy6WiqLgpZdeAuCDH/wgn/jEJ/jH//gf86f/9J/GWstisfia6dLJyQnXr18H4Pr163z84x//mq93Rcu7es3vd5VlSVmWv/8nU8YeBhKD85kuNEryErlgimpEElo7jj7HblmMRK4QmvnLCSASCSlhvceu1kwns5xvojXBWkg5SM51PTIkfNcjEPjSkcpEZxWf+tI97m0C33LrNu9/14vs3JqAEhzPGj77+JzDuiZ0jkpKnjvY5X3fcoe9STaa5+1/rNSLAj9YcvJ3ZHAenTKp7KpTKq50LDJz6Rn/LdFHlNK40FPvTBAJ3vaD34vQBauHJ+idGeXeHsXePu26xW5bjl96iS5aRN9hqopiOucTr71KUJqdZkKNYNP1KK0yFSoEBtux3i4QSqFNQUoy5zltLpBSsl6v8bZDiJAlLyNvX6REkiqPbJWEGDFFNgYuHm2pjw8oqoLgHRfblsergcW65fXFkvP7byAuT3j1c5/BWcd8fsA73/MenLfoBMSBG9f2kVFwba/GEHBJsBlalJD0fUe3XmV0qu0JCJwEocfpQnSkJFm3Pf2bDxgcLGczZDVhvn+HYu+Qy0fnDJ1HhI77lxs+8IFv5Yu/9TtM51OOdnZZnV8yqEhsGpJRFFWFEJreRTZtx+LzX+Ti/Jz9o2vcu9yyGnqmZSbWWO/xMd/HAyCnU6qi4uU/8iFeePllPvU//gJ9gNZalFDs7h7QDi1WFcwO9pnN54TBslmsKMuKYmeCDR6dEskOTHYnbPuBZAp0rZlOp6zalqIsKbTJqP0xh6yQAkXMafASdIKiqVDG5IN8/9ZoeDdu3ODll1/+mo+9613v4t/8m3/zNWvByckJN27cePqak5MT3v/+9z99zenp6dd8De89FxcXX3ct+XrrSNxa2Bt13K1F2KzPjT5gJiVyUuUp0ljMXHWwpJLYTUfatMTLJfgsEQsuoGoDLstwYsreSiESBI9oJiTX50OiHw+J1pGqijTkSQwxT0uED3inIOQdzy9awsYhphr6gNt0hLWlaA4h5b9Xip6YIAXP0DkodE47nzf4mDLlsnMwKOJiQ+ocTKaIBIWMWJGnRXWZcFFQ1xXLdUu3HfAuMJsGJoc7BKWZzSfszCfs7R+xWi/w0bFeL1l3LfXudWTI5UgIHmU0IfmRgiVRJiNuY3RAblJxhZkdjdy/OyK6+k96OoUSiLHwiU9flJ6Ol8YrZQ9YPiyNII8YII0kNgQoiTTlmPkEMeUcESlVDmtMERECtt8yKTVzE3hwch/bbZDBEec7hBDZPdwnKE0zK1m1PTtJsDOv2HSOvVnNtDakfkAGslzThZxjEj2p7cH6bGguDbKLJJHwdkAPHuddnkxs1hQ7IJo5KXiIAnu5wV1s8mTfxux/8o4kK0SZUH48YI6SUGIiRYEkglJI8oE9NwtD9sAREBGkGU0tSmRIUtuTBkd0jkBAdoEUPLJSxHmDROSJVBhVHwiSkvk9FgJvA0KJXBw5n6WDw0DYtsTe/hdWja+9vuHWkOAx2mRzeyrp+hbbd5CyNCk3dD1SqoxcvoISSYnth5EKlm/XqERukgqBMoLJfIYQkq7vmLgCrRRFoSEFFJJum7v1uiioZxO8sxRlSRyfEVUovAfbO4RSrLY9TVtSBjWqOHouFpv86nGqJEWGVnjrsEhCAucdUiuSyV6mGDL9rdGaXucpx5VX0A0WPR3vKyXxY2M4RE8KDt8NY5BpXteElNk+oDSmrnAyF5IhZo9QXVYIIVDI8bmHGCw5LikgiWgZkELlJlVkLOgtxkiMzlIuawcUCdcP+RkksllvaOqSzcrRDh3NzoxJUVOUBUoXWGd5882H7OzP2Gxb3HrDzu0b7O7NsTZyfr6grkpuFiU3rh3zxr2H9G2L2Rict7jOcu3GLapmyna1IjoLUnN+fsFkOiXYwO7RnKLQTCcl29bx/AvPYF0mF+7u7fDgzQfYwVNVDdFIUlHy8MGbXDs+oplMuLxcZFvB2IgzWmPbFikEm/WSWdWgq4qBhB0suiixg2VvPqFdNITwhG6wJHLIbRQSoxRawLBdY/sWEEhj8H1H6FuCiDil8bZlWl2n7/M0VYlE5wYmxjCZTOm2HUYXONtnmZwUSCRal1jrsopFyCzRloKu6zHGMJ1Pmc2qDFBDoCsDPmG3fV6LfMq4fqWxKFySqD9Ez9J/dc5SjJFhGPjgBz+IMYaPfOQj/MiP/AgAr776Kvfu3eOVV14B4JVXXuHv/t2/y+np6dPx93/8j/+R+Xz+v1j4/kDfO/M3EUjKoiYJjx2N/1GOEoJRnkdKOUyM0XQ6mrV9jITRbBljyoeNAIN3SKno1i0QEVoiQ8j4aecotcG5gNvmjcnGiDQVQlYs156Hl475fM71wwYtodKKVR/ouh4VJZ+6d8pxYditJJPVZsw4qrJPwBhsP+CiIPQbdpoG23cIqUhR4OKYteMdWquneGwlRE7fDhnvqAuTkbo+yxKbumbyzA1e+KHvZXn3AeeLNd1mwF5smF0/5Pi5Z4lKElZrClOy6lr+/b/9eR4+PqUxNUiJs4Ft2zOdzwkxYcqK3naYukKIAjl2a4e+JYaBqpyxXm/y4jYiU0HkbkhKJDySTGtbbRa0mzUqwuXqAuc3zOSHGG48y8OTMy5Xa84ePiBcnHMxXLI+e0RZaLbblrOzNcVkRlmXGCl4/OABX/xyxe2X3sVvvrHhxeszar9hNimZlQXdYglRUZQ1SuaAOVU0JCTYPO4XY/p0CBXF7i433/ZOEoKj40PuvvEmgykQzQRtBMvNwJPzFe94+V1ge84vznnSeYbLS268+AIn7ZbWR6LzrKJnefqY1lludgPdTosVAJHQbrLfQIL1FhXhIgRCD3cmisev3eX0y2+wPV8QlWF3Z46qpoSQOLp1C7O7w/2zJzRVw7Se0i0WCC1p5jMGItVkxuniAr03R7mcjJ1SRMqcpl6ZAiMzYrgSmhA8hSmpVA5ezrKx7BXUMqPbu7eYj/Ld3/3dvPrqq1/zsS996UvcuXMHyEbt69ev85GPfOTpwWa1WvGxj32MH/3RH326liwWCz75yU/ywQ9+EIBf/MVfJMbIhz70obf098nJ4gHfBeKmJ3QOMXoX1aTG7EyyDlzkg7UaDel+tcUv1/iLJWnUrcsgkcaQfFbyhzT6DMdplKpN7qiL3FEnJqLPuv5kbZ4CjLSpfGgViOQJPmKXLds3zvCdxzjQSRJDIgyOfrFBTxTldAc1MTjvcM7iNy1yP09GYt+jfECVhugcqZNEUSKNQPo8MbMxUpSaYmqYSoNa9KzP18TO0sxq1huH0AYQHOzOIAp2dzPoZbtajQcoix22OGuZHTyDl/nf6AYH3hFjyD4NWRBMQoyZdCLpDHVIY5TEFWeaxO/aa8dDf7oS5Y2vS/+zP3JVMF118q86ooxF2FWxJSWYKsM7UsrTPCUwZU1SOYfq6s9KEcG2/NYnP8F6cTn+nQWbtqWpCpKUzHdmxATnzhGCxLWORgkKlZAx5kykFBEuolJCRGA7kFpPGPIhj/UWnMJOS7yUSOcR3pGcomry5AaT5TK+9djLDcPFinI+IYZMQAzLLSmpfK9VGrwneT9ODTIVNHqLmOQDcbKJlMaD/Pi2KaPG0FSf/W2FGQmtWTbHYPFCIS2oywI/3VJUBuJIeBMCKTP6XB5IwrpFqHGq53yejsk0ekoDybs/8DP7jbaGFEWZC0SZmxXbNkvMQsp+mRxTkn9JlTHjPgRMiFjriAGcDbkU0AqjNWY+48lDwXq1YjbdwTuHd5GyyN6mSVMwtH2WkolMKUujZ0MJQbCBKAMxZaKiLBXOB6INXGwtZoDeRvrW0Q8Oa4dRYpbXejv0GfaQcvZQ9JbpvGE6n7JdnGJtNvqXxrBbZ08TIpMstSGfYdoO6uap32S9Wme/4jDgrRsz7gRucAzSUs1z8LdD07nEZOx1SESmyaYxNJ7Ek4dvcLh/mO2jwaEkT5vHWun8vkdPrWe025ay0AQ3ZJlpimPor8gNXOCrr3+Frnd8xyvfxbe+72ViSnz19Tf59Cc/zfG8YXL9gOAiXnZUdYOSgu22Y73qWDQLSIF6UnDz+jUWlyvefPMhF+s1733/+zi6fsi1wyO0FKw2W+6fnHH3q/dYnD9hd2+Ps5OHuBee4drxM5Rlz/7eLEcZJLDOc/vWEV99/Q1ev3uPiyfnFGVNCpah247EvNxcDwj0pMasN9SpwgaPNIohOISCQL5PnHcoEYmh5ebxAZ9/9Ssomfc8rXOzFmUIKcM/hDJ5D0wQwkAKjpQ83WYBrqdM+fvIUmOdx+gcr5PIUs0Q83PgbI93LmPIvcPogt4nkncYrUdKJDRlniqlYCmkRImc/dRvsh3GKIndDjD6NNEaSJnU+od0vaVi6Sd+4if4oR/6IW7fvs16veZnf/Zn+ehHP8ov/MIvsLOzw1/4C3+BH//xH2d/f5/5fM5f+St/hVdeeYXv/M7vBOAHfuAHePnll/lzf+7P8Q/+wT/g8ePH/K2/9bf4y3/5L3/9ydF/8Rq7ZCJvgaYosD5rdvNBPAdNxtFwllObc8dCIpBK44eOEE0e7QlBFJlaYrTGy5zM7hOU8zo/+ClRmZKh67GDxXU9ft1jyoY0i9hB8Km7C964aPmjz99B+kBUirZNtMqxOBvo2o6NKKkOC+pJyRuXW9yv/RavfOttDvZ3me5lXKZwgeVmyyZl4pwdPD5ErPMjUSnlbvZYCAYfRoRpnuwURUFZVeiigFFP7WKkOdzP2E7naYKGiaLYn6HLrP8UEvrOcvnwlN/+7OfQaLz1bFLLth9ASPohY2FDCiRRMNu9zmp9ynp9iVaGvu8pywnb7WI0hGbKkyB3z65MgDLmNPEYcvL5ycM36eczNt2a3b2Gj33k32MmcwSKy0cPKESk26zYXFwyrUvifMJzL72N42s3eOHOcxQCTh7e4yR5Xrz9DLdu7iHMjN+6v6ZupryrSKycJSTDgOfuw3uEbiAGlxcH53KnN0mkCMRgqXcOqa49w2KAg70Zi1XL5fklRVlio2RLTVAV27YlOI9OYGa7pF1L1Ufu3n/EurMsuh6fIqVWlFIym85INrC8XBCloNDZ0OqlY9u1bF0HUtF5gdGB3lm+8tW7TIsKJUvqnWPaBObwmP29HYa+4/zknKgUJ2fnhKJkdjCnaEpSpSEEzp+c0UePbDu0iwjlcdstzXRKpTW+76knE8w4RRqGRKFyxz+Gqw0GUm4Wo6VAvkVMzF//63+d7/qu7+Lv/b2/x5/6U3+Kj3/84/zMz/wMP/MzPwNkGchf+2t/jb/zd/4Ob3vb255if2/evMmf+BN/Ashd5D/+x/84f/Ev/kV++qd/GuccP/ZjP8af+TN/5i1RrIAMcxl8PkOL3EGXWiOVoNidIY0mikTsLYKEvVgTrCVebsZO+0j+Cj5nFSkFbpT2+UQU8ul5XhSacIUoV4KkFLEbMdpDzmOKMRGHMK5vgBYkIXHLjmhBNHWW7LqAmE6QSIghG2aFJEiIXUdKI72xVYjOY0QkBY93AyJogoxQFCgfSMOADglRaIgRHy1CKgrv8Ouerg9IqZHRI02JaSpmO7s8ObvgHW9/iU9/5reJztP2bQ6w9JaUEtvLR8h6TtXM6DpPkuQDnc4BpUIYRCiuFgWyFl5lAMU458/wBZF/PzZbhLgqehin7lcWpq+dLgkSCP3UFMzouwHyx3QBMue2EfPrtckUKV0U8BRtG2AYWK7PWZ+fAR6BwkXL4dE+bvA8fHzOcy89j7WB2WyGHXyWMwWoU6AwCjFKDWWMSEBYl8EPvYfeETY9sfOE3uFFyYaEIaKix59f4OpDUqkRlcqvsxakoDjYAy3wrQUEsi6JvcWttkg9J25dPmhqmacDMWQ5bgKCICYF5IaALHIxf3WvEsYmSRyloTmQa/SOORCS2A+kyzVeQpg3+ftUBaIyqFLnjMFJSVy1uXngMgBFhHxgzYqIP/hC8o22htR1w3qzRqTEYPvRsxNyXliKOJ+nZjFmtUeMATv0VFWTPy5yTmQaPz90HVpEYhJstmuqeoIEShJKSqa1zhO8XmbYynbIkzwtKWSJdZ4YM6xBKYksJBiDJVEpxdZFtIcHDx5ysLNLitD2w5gxdwWsyJOhSmpSypOmZr6LH1pECDnWWes86SLRTOpMm+w9w+DQ0x3Wl5fUVZUhl1IztD0DK2Tb5mmzkigt8dbhyopqfI7RBXZoWa7X1GWJd3k16K0b/00C260py5t4X2WvjB0wylBVBUZJorMM2y21MXjbUxUThr7PkBw75HtbZLR217WcX1wymczIIa05bsb3Ld1qw0nb8vjeQ9rNijsv3WZn9jLaaGICqQ3lZAZCYUyOk3nzy1/l9fsPMtwkQFOWTJsiNx6rguV6Q93UrC4Sd1/7Il3f8va3vx2hDLefvUld1yMpNEfScOOYm8/coBscv/KL/4kUAreee46iPGToOoieYegIaUY1r9k+UQgRM/DKlGgxTmaGDPHR5Gnfa19+gy/9zm/iKHiy2NKnEiEVGsiwyog0OvvlU8C7fnzufc4OlJrkXT5vj/J+IbJHT0wnJHEVojuwXa8YKUn5TK41QimkNCQtUKaEdktRFUznJTuzCu+yrUQKlXM4C5GDzD0knUto3/U4H/AxkdxbswS8lestFUunp6f8+T//53n06BE7Ozu8973v5Rd+4Rf4Y3/sjwHwD//hP0RKyY/8yI8wDAM/+IM/yD/9p//06Z9XSvHzP//z/OiP/iivvPIKk8mED3/4w/zkT/7k/6q/vJJXZjFIzmGkQAT/tLsCEELMZBSjn9KutJColEkiYSS+jNFLWXdMQiVBN1guTs+ophOqaU2wDrvt8vTGOWzXEwabO3PkQ8VQ1nz07kO8mvBkCEwnDTo5Wp84O+95fNaysRY1b3jSWeoSqtbyZhvYfvo+9vwzfPcH3s673v0sdVkzmzQsNmuKAqKFbddhySSaeky9VnLs1gmRJ0xaUxQ5/RgpqMqKELNc8CqHqtqbsb89ZNk/4dL1TCo9klk8pi5ZXCz41Cc+iUZRlhWL7RYzav5jzKbOEEPO3zEa6wLrTR7VrjcrBILYeXx0oyk7d92uDjNh1EILcu6JjgkpDd1yiQpb+rbl848fkYRgtjMDYD7b4fTklGR7ZBQ0h/u8+73v48bNW+zt7FArwWa14I03vsLy4oxucYTsZuyUktu7kS9d9Hx+G7g1L1gueypT0rsB73tiEsgudzYTBQKbzfTNhObokJ3jPR4+ueT+ww2lMkRVEXVBNdXsThrms4bptESmhGsd6/MNQZXEYspvfeU3WZw9yQbUMlPvRIBaGkppKOs6o6X7lr7vWK4XuBhw3tHjmUx3OZ7voGPES0MvK+aTPUw1ITpHmyTTWzfYfOnLKCF429vfxv7+HsPpKW3oOLx1jNgMrC6WdClwudli0jFplCVpqVExIWKkqnL4rJFQSE2yA95aTJGT16+s80rmDlQ+wr61Berbv/3b+bmf+zl+4id+gp/8yZ/k+eef5x/9o3/En/2zf/bpa/7G3/gbbLdb/tJf+kssFgu+53u+h3//7//903wUgH/5L/8lP/ZjP8b3fd/3PV13/sk/+SdveR0RhUFV+XAZx4yeGGL2WsSQ6WI60ynt5Qq32CCyroS47UlSQO9I1mW0d4LoYvZ8IJBa5Y/HQHBZNimEJFmADCohRiDTzqKzuWmhBeFyi5yWJGXw1uJDQKqSFDNcIroMZAl9j+8K/GqNnNU5p225ztOEroeQCD3IpiQNCeoZwQfkMBA2ET2tCT4iQiJNinwollnKO4QcXOudx4acwq4E+JCoqoIb149420svst1sqJqK9XrB4DLpyQ+bfFhpI3U1ISRFTBD8gIz5AJ6Ufkq5G1FqQMqHyuBHmA6AyEVNXjWyXUnkJ1YoSYzxyrg0Qh9GScYI+UH8nq8z4nwhd63FSNeTpkKYMksEQ0JXdZ6iJgftgs3FGT64LP9RkePjY55//jk+/8UvcXS8l2lvSbGzM2F9seRs6zJoZdNTFQJlJEYJUAnRO8LgwXnCtif2PXFrSXnsgxx6tPekYcANHWE7ELo2Sx/sQHIZREJMpH6AwoBJRBcRKefd+D4gXSBuB/SsyqWiD9CUpMJkOZz1+Z4lq0yl0fnQGyNakDPatM4+FR+I1hGcI1pLkiqfqrzHb7p8nw+OOK2oJpN8b4sEWiLrAhHHe9bkoEuSyDlfwiHqyTftGtK1bY4pIeeAGWNwvssepqw6fyopuwKZpJinoyE4Vqs1zxzcIsUw5hZZdFkgBLTdGu/22BWJ5zRgLUbWCLJUzyiBnpQQE0PZ47p8JokpAxpScMhC56w3JbLNICa6bgBhCD4xDEMONB0BWEVZ5swknycGdsih7sl7krcQc3B0Mf58q8LQ1BX9pstk4pQY2m2WaadMzPNEPImh3VAEB1pRiIa4XjDEwH5V4rzDJwGqoLcLzNBSlDOCd6RUIEWiHIFX3g4YpZ9O1bz1iDoQokOXBcYoYnQM/RY7dKxcR1UVRFLOByw123ZAC/0UHmGMou9aTk5OcNbz5pv3efDgTaq64vpkzst37nDzpeeZzSf0/YDUOZzcj4HaRV1w7XiP99y+TSUku7eu5bVgvRnDhw3ddj0Ww4mzk4esz89Yt5bFck01nVEYladk5AmkGqNwtNb0fY9QJlP+UmDTbmhXW1YX5zmraOjz/lUqXJ/XVh82VGWJlJGyLPCDp5nULIfIycklD+8/Yu/4BqerDlMptJLZ16rHqZAPGCVxLo0h55GIRBvJfH8PHz2X7UBZVlg3oAXE5BHkIjj43CwYbI8pMwglxsikmY1UYlC6wKV8li2U4mBnSl1IKBtiChQjqEvOCmJVsjlbEcdi25Gbfq5rkeatWQLeyvWWiqV/8S/+xX/x81VV8VM/9VP81E/91Nd9zZ07d/h3/+7fvZVv+/UvIUhkUkxhNBOZA7E2fcagupSLCnXV+haSmPJUJvqQJUiMm0TMHWYxjpKjSAz9wGxvB9cNVMrQhYRCYrseby2h6xkWG0LfIw809f5NvvpoSztoLmNiKBsWZIN0e7rhroNWaR6fb9gPjpMt4Ha5YzShSBTFjM+3l/yH//vP8v7n9vkT/5cf5m0v3qZpZgyDxZQ1RUysNguULNA65smZ9zkxmyzHQwiqOge+SpnRoM77rA82hmAtSUDRlExvHiCdo1AZt3210H3hC1/ky/fvs390zGrTgtKsthvKapI9GCon2Ds/0NsWR6SZ7NL3G4QYSHhcHEhR5qJjLGoZ+8V5OptDKNMoUdFKsF4uaJcOow3T3UOCjNj1Bhkjb54+RowZU0XVMJk1XD45Z17NMEJyslpw7/4beGt55ztfpt6dcHBwwLWjY46PBfsPn/Cxz73BZjvj4mzFTgOf+PTnyHVmIIUOqUuSKZHJgq4oj1+g2j/m+VvPcHK6pJcVw2BJWoCMHO7sUOC5HCyVtWwvT5AuMKlrdpuGbZR86Hv+CL/16U/RL9fUSpOspYiJ0A34EnwbkTGhiazbDWvbI5TCpkQyDfXuEQd7e9jVEmlqhKoIdUMxnTFHMtuZsdlsiCEw39thtjvP2RlVwfF0TrvaoqPg8WbF4e1nmDUNs4NDhhCZSk1TVqgUc1K4FqgUSCGg0DRl+dREL8ZDrBQKmYNrclaZ92/50f3hH/5hfviHf/i/8GgLfvInf/K/2EjZ399/y+GRv9+lmzJ7fIR4erARIhdRweaDRmY2FBkPPqtJF0uS9Xn9cD6HbTogeOJIOUsqNwaiy1MrISW6LPMBWRu0zmhsoTT4hJjUCCNJa5e9MtY+7da5yyWh8wipkVITfMoTLaPywcs5sNlMnroev+3JmgkPLpMncR6fTMZEO0tMhnC+RFSGKEDWVfZwOk8MEWcky87zsLOsu4jRJdPa4H1gOmsgOo6P5vTO8h2vfBuvvvYaJ48ejWuuJsUsr+rbJVIanO0o6il1oRjQpKAJYYDkRhhAyvlU0ec1+Ip6J7I3Sciroir7TBESyVUYbf5fIktEr0ZNafQ/SSGyz0yobGMSmdKVXxpH/0MOSlRaUyhNEAoVPf36EqUiVTMmz4dAUoqj/UPe/7738Mb9x0ybCQf7u8x3pqzWA01dYZLgcrMlzRS6i0ydRxUa13oKkYi9Q4YMHUIlfOsh5olNTCFnS4WsAAjWoxKkbY9brLOkph1wFpLLGXOyc3ilkJUhdQlhCpIPxM4iSkUaelKhQCS0mSGrinC2QoTsv3MdiKJAmCLn2ThPusIbjwTI6F0u0hhrnZSl69El9Pjc4iOmLFFGk0h460khEQZLVBIZxgbLqJlUVUUSArn9g9Pw4BtrDXFuyGTKlClhw/gs/q7pLqsrlDSkCJPpLJf8IaKFZFJoKim4HCwuBLQpaeo6T6BHRUaIkYuuZaqyL8eYLLtPBHQh6bY93abDDTbL2oYBnwIueJr5FLynaBrKssQ7T1MWSG1wNmSceX6oCCGw3TriQQ4cDyGQlU5XsJGE934sRiwiCqbThm67JYU8bZJKE3wYrRL5+SPmn4mzlgJyll8/MASfC46hJ0qFtRHf9fjgccFTpHx/Ci2INqGLitD3xOhxriXGga7doGdzNusltu9GNURivV5m6qQUpJAR3NO6RGvDMFjaradpCopmn2HouTw746P/03/i13+tIkU4f3LK8uKcl9/2Et/y3G2O92bceP42dZMtE103MHQDy8slzg4URrAzrXjh8IDrO/tErXjYWzbLFbUWUM/ou57Tk1N+9Zd/lXa1ZLvZcHB4jX7bMrQ9zlqM1sjRPiLI73ff9Tx68IDkeprdGbZvs3TVD6wWZzy6fw9EZFIWpELS+5Y4Fi5S15haU3jox+KnKkoGN07uU565x5Q9pkpmJHi2I2Q4j7ddHv5GUORpz2AtIUVchDg4BusoSsNOWfL47JztZsXQ9yMNNuKspa4qiqrIGYMjQyBTEVOm7FYl0/mMsigyiMRFaq0JUqJjYCChKkMxayiUYTAGZS3J9qjJ9L/6Wf5613+1Z+l/zyuDAvLGqGWiETkZPKZE7yIpSZz32Jh1wMFnPGYUMeechDwKjCJvvrlOyn4glCCJhG4qNpdLHt17SLMzxfZDXvQHS3+xYv3oBKUke+96O1uhWS0983rCJgZO1hck51DzJvuRvOerTy4xAhQJ0TpOLjqmRztcN4ZoB6IUbOdHfOTVEx789/+B/9uf+xFevD7HaElnW7yQzKZzlusWT0ImkCmQw+1yoeP6AWNMNlL7zL13zhOTIDdqc8fAJ8/kYM40SfrVFonEO8+nfu0TfPITn2Z37xBVTzAWVO+I2NzBDQGlNYLA5WI9SpYKVusFMfRjRzoRk0LIvHmQrlQ2+Wd2JbjQBEIS2VMRHeV8joqJoxvHzHaOcHbJyd0vcrG4QBUTkotYv6UuNQ8e3mfbWYQqeXxxzrQuKSZz3vv+57lz6zqnjx+NWSoeFTx39mrK99+htYbfDBt+6+O/zpM33ySOwZ4kh9I1AYVXFdX0ANsH0uD41Gdepe0iqCxlmu5NaUi45SXCSJ5oSdeu2S8MNw+OKaNl/eQEpQtmheL7v/uPcnF+xv3797DbDWm1QQpYrpcoY9BIgrd0sadLgSJKXBIYM+HFt70X1W3RVUMYAuuhhzBQppAxxFKwPl8wa6b00bNxAwfTHYqixAUIUbCxA9XeHmU95fbtO2xTxHpP4R0ZX5tlv2WhCd5e2XNG43HGq+dxeD7gSCnHg+3VNOCb9xLjxiqVQkwagswSjGQdcfAEORBTRJcGURqkL/FFlskiRaaKJZ99ISmhioJUCkQURCF+N98tJpKI2WRfalLbI0PW+YooUGVJxCEKmXN1QkCWClymhWmTw2IFETWt6Rd5shA7m0OYx7Uw+Yi/XBNthiUkH5C1IblA9DGHjbYdAotoqhzuZwTB9SStcVbg0Kz7gTdOWpzQzCaaMiZMWXN4+zrbrmez7Ti4tsfiyYK93Tkf/Nb389FfXBJDIKTI0G+pqiZvpnZABI/rtjTzPaZVgzeay4tuzF/Khz4BSGFGf1wYi53sG8qT0LEoiiI/izFn00VELp6kHkv6BOLqEDCCIEQap0lXz3sEoUjJIdFIaTBSsFMZyrri8fkF/bAhDj1BwnLhn3p6mmbG3nyfi/Mlq+Ul3/NdrzCZzZFS01SReVOy25Tcvd/Tth3nybBnE1JmZDFxlBQONmeWtD0yeoJK4HP8glcQlMSHMOZ4abwb70ubJ0K4rIxQTUHcDE8nOFl9OE4sNy1yYrIXTAmoNAGHCiUiCSISH2zeEwud5VvjmEmaHAD+lDIIo4wuNwpEiAjvEVUF2oAAM69RTUmIHrt2KKVygdm7nEM0+oVlUZB0lvGQeEuAh2+0S3CVmZNDNfu+h5SbST75PBEeJ9W6NLz3fR/g4YP7eJdzrvq+4/xymT3Rtmc6u05KHj1OOV2IDGXFqqiYTqvs20mSwoxQlxQxRqONRMiSobcYURCdpbnKiHOe2pgRNpPDbEXKYbYhRrohy/CEkuAzXc05hxWGvm9z4eSy/E4IgVQSo0wu8EN4Oo0fnEWN2O8YIt4l2m4geJ8nWIIsLQsWkbLcL/hI2w9U0xmbvkfUnk3fUvmdvBbIq2Izh8m2G4cTgccPH+T3PQS6doMx2cOdomdwFq0hGk3d1MxmE+azGTs7c7RRbNdbrl87YD6bcXJ2xsH+Act1y1e//GWMVvyff/AHWFyeZ3lfSrxw6xo2BebTKWfnC5wfqcQpjWu8xJgCVZbcePeLaCf4lY/+Km+slkhT8NyLt7j1zG1c27G5XNOuNkzqhn6z5c6dO1muOXScXS6ZuDEDSpB99SHw2pdfp9u2CCQiKVbLLcfHgulsl8Pjm1hrOT9fEPamXDw5Y9PlDCtZKCgS+/sllZUkBlxwSN+Tg7gFIXjC0DNv5qS6gjri3YC3Ld72SClQCYxQqKagiw4B+KFnOmnYnc/YbgZIChkCwQUWm0vW6yUiwbAe8LanqEpAEmKmYqZKEEJ+/wqtaGNPVRUUOoN7tBIoaVBGgcvS7KKQqMrgjaLrHUOKeJlIJkuM/7Cub+5TzlgJCyHGTTPkvUApZqWhUhlfakOkDwmhNAHGRGUxdpLzjZiEyF3c0bfkvMdbT7fqIIIpDcVkQtCGaD1+07M5u+Di5AQhNJuV49G9BfOi5I+9cIPnpiWr1nJzPmVwlrOhRUXHjXmDrEtk1fDCjesYJbmwAz5G/OWKqU/cevEFrj//HCcbx8//4sfYbodMhKmq8WAhmM4aBuvQpkBpgws+K3mSYHCBbsgBczGE7FXy2UgaQsjd7AAHh0eYwmCMQmlBURa88ZW7fPLTn2EQkmp3j8neAUobSIqiaAhA2RQg8+g+BxVqVqsFXdcihB79GQmlGhAlY2lISpGUsm/s6tYTY3ZNnpBZZvMZ+wcHCAGuO2N1ep/NcolWJYwHyqqc4YaczTCfzwlKsfHQJU093WG+t5/N5c2U7Xbg/qMTLhZLRIzUrmXqz6nsGfdf+x0IdtTRArLAJwl6gpweocoJol9xeu+rLDd93lzWKw6ait2ywXUrWruhqCe0HlbCcLJas+1ahq7j/sP7pAjL00te/+wX6c4WvP2ZO7zrbe9gfu2YnkjvHevVBSeLJyxsT2sdxtR4WdCKmtMIb7Y9opqiiilb60hCkZIguMiib5nuz9mfz3GuZzbfQydFcBGnJJt+QNc1X3r9DWJRE5oapySz/T3quspwB8G4QGlS9LmL6bOcVYyjFm0yBlSpbPoeSR0jvv+bexkJ2z4fELIJi6uAarftiW2P7y0iCexqm4lx04bq2j5U5ShN8tDmaS1aPg2kzabWBFEQfQQlSb3PUBiAEXIC2ZQcuyE3cCQImaU6IkWkzBteig4ZE6ou0bMaVZfETQ+DQ8qEntYkBLEPmZHQ5+8vhcgH3kIhekvQCqoyH6rHg1bsWhhlN9YGtlHy+mnPIBt2q5KjIkcw1NOGqq7oraMoK6z1nJ+c85VXX+fG9Zu88La3IaRib/8IY6p8kJfZs2Vdj3M93XrBZn2JTIF5U+WOXYpAlgFLo8b1mTxVkiCVzhNNXYxo6wptxrDbcdqWm1wKofTvoq7JhC+hNVIW2Sc0yvFyIK6ElMUlVaHZrQwyBh4/uke/OMFv1xDdiDXPZueirJjv7oJQ3Lt3n5ff/jbm04ZJ03B5uWRaV6iiAK1pyoYmaWwfuPtkYN1LnI8Myy1u3RG0zEWCEqgyNyOShoikdxC1Ggv1Iu9RvWU4W2coSFPn26vt8YtNnjIqlbNplACb30uhZF5ujUREC8Ei3UDatjlc+eoeGT1Mvu1wgwcPyQZC74g+4Aeb4SNxbNKNqe4ZmJQQpULvTpGzBgpDjIJua3EuZOCJj/kejxFRFSSjECbnL8W2I6w2//998P83vJTW2SMtxvdTMU7fyVN6mdeVDDcRHB0dsr9/QEwRZx2b7ZbOOZQpMc0UIWE+r/Lhn0QzaZCFYb43z/EDYmycxKyNKcZ8xnJSUxQqk/SUzAqYELCDQwpFsAElFSmCEQatBdbmjL6iNEgtnmbhIMjBxd5RaEOKgZQcMWV/ZKFNRkr7wGa9ISZwKdE6j/Uj9ZZEUUi8d4iyICiFDwFVlJh6glCaqiyp6wqhFD6BRdLZgcEOVHVFEp4gHVu74XL5BNv32ZceE0+enNC1W7btlr7vcqNEZLiVMrmBJHWOC3n29rPsHeyy3iw5Ojzgbe94kWdv3+CZ2zcz8iUGvvd7PsTO3h66LLHeMZnNqCdTNtbxlZOH3Du/RCjFemvpbSL4POkuiuppYK+QAjv0nG9WnMTEG08WuGICsma1bHn9K2/Srjo+8L738a3vfw/f8cH38p73vIO3v/0F9g522HYDlxdLzs4XLFYrnHUMLrDZbkhEmtmM3g1oI+n6FZ7InZdeIsbE+ZNT7t59k8vFiiQSg7ecLy5pfUcSgRC2pLBhbxaoi4HaZDl9ChbRLqjTioMmMDOBIvb4YUvyHi0VWufCmCQIPq8DB4fHvOMdb+f4eI+dwzlFJTEqsV2ec3l2Qt9uaNdrXN/h7JBzl0SmSRdliY+Jts/7oUs522tnOsEUJoPXpKRUKqtXxgBzEjkzTEpsioQYGJzLOX7iGwTw8I12xZyMNkKM8qFOIqi0IkaPqTNGe9WPwIdxEjVYS20KtMzozujDCEfIRmqJQEnF8mKF7DzehhwMqzWiqehOzmgXa4YYqY/2MUf7nJyu6MwENTHsCMsHDifcjZHeWZxUrENAK8k1rdkrpySRKEzkhWu73D9dcK41h8clb791wG+dLOD4GbqHd/nEq19i/5cMP/y938neTNM0JZfrDUpoqqrA9pbKaIQybIYWHwSDDVRVLoq0EDjnSUngAwgZqERGjIcUqYxhu9lgCkW37bj7ldc5Ob+knu1hEwzLNc55yrrGDhktjZQ4F/FJYmMkxZ4QtuzMpxTacDpixBEKEUXW2I9j2CudYx65pqfdYKEV82nDrDIsLy4IFz3tdoHdbokIbt1+Bh8lqqmZTDPp7XK5YDlY8IG9g0OqWc2zzxxy89Z1Qt8yv1GzvzPPidkj0cf7nk9//FP8ykd/mXazQaRMkLnSzUbVIOod0JreD8TgSes1sj5EJ4kc1sS1oA3Zs1bPGpZtx/H+HrPdKfvsk1wGPbRR8Juf+21MtOyXFUTH+uQBNkX2bx5xsP82LhcrLs8esVwuGYKj1BWUB6yFZmMFWwKf+erriKMjCjewN59Q1w3eB043C+68+20oLbGrnFt1evKYd968BgEWl0tme7usnePw2WcQdYVo6pzN4i3TuqQpCxQxE4VSDufVRYEM6qmPA5k7+S4kytKMRZN+KncSb5Xw8A12pTBOqLVAmQK7WGXYgpIMTxaY4ghZVcgqS4ukBNlU+aApR3S1DxnEgCCqXEDJUhNbi1Ia4S1R6KcHlxIgRWTIB1yhJfSW5LLUSgoIShBdlpOJcfKlaoGaVYQQUIUkKKCQpEITlEaJHEAaO0tyDqnziFCWBSJEZFlkZO60hEI89ZMELzKRSxe0xvDlRwObqNkxnp2yxA6JphCU05rOWpLP0t7oI3VZ8uDuI+68+Czf80e+k+V6y4N7b3J0eIPTJ48Zhi5PIFOG0bghZ1QF75hOG6qixIXA4FIu3GL2GwnCGC1g8kBaCYp6losWKbH9BunNeI9eeWAS2hS52yyyFya/1XnClxCIdAV7COP7aigLw3RSs9lsCCnS99s8DQ8+T1nI8jWEoCgrbj3zLKvVimvXDnjlu76di7NLhsERrEX4xOJ8Q0qBo+Nd6Evc0PFk1fJg2XOjkewUDcl3JJ/hDcqY3MjDo+aC5AakjOgUMVWRi+Unizz1aYdc+FUGpR2yKvBDD6XJhUv0qEqDdeR2cC6IZczrYAwDutQk6fL7diX9Kw3Bg/Bh9NrkyVyWc/5uCDoqF1bYcUoXEqHtKSSIpkRNa5KW4AJVU6CEYHh8iV9tSYNF6TonXRidvXh+g990xOEPTsP7RruMKbB2i5QK5xxxRCR7G0Z4SVbCKKUIKXD/wX0uL84ZhgFTlkSZi3dTGELIXr3dnX2aZkpdNpRlgRCRopQ4Z5FRUlYF23XLdD5BkDBKYozGdh1KC2yXqWMp5XBPHyKllvRDhoIIIttNjx0cxMh6vX2qGkwpjYTgDLtJKU90nPBUUmWfCJEQ/OhridkrpwRG5Wlku15zuVyjjjIsJo7h2yKOsQG+py5rXIh0NtODnVTMr1/DKom/iJyvzgg+0A1txpInhZa5uZSnyAFERGrBzt4hk2ZsAI2SwsJo1ssljx7c5/q1a7zyXd+BuvMs8/mMojSEGHKhM8p+P/3bn2Xwjt46fuk//SJV1WS6qVa8sVxxsDvFFJrptCbGxGq5JSUH5Cw8MRZnqS5Z9wNfuv86bz64z/l6xb37r7O7s4sMguPDHRaPH/Lakye0mw3bbc/tF16AYsKAxBR5+jqpDTefuU1MkdVqybbd0HUrhqHDFCXr5ZI4eG4+8yxFUzOs1migKA3WebZdR1EUfOXuA54sNnlQEAVl+QSlFF3X5SJIJHzsePTw9RHmUTAMjs1mQ1mVCBIHB3ts24zD7wVUheaZm8fUoqdxC2Z7E/bMDJ0CD+05m2Czjz5YlNBIpZjNd9jb32M+rTk63KNte9rliklZgpDUdcFsNkWr3GiIMY0k2izvTCFgXcB2Fh8TutS5yZc81aT+xqHhfaNdvYc65M5UCAGtsgayUCCUYvCexkhCSFiXOysiJZRUWGtRGBgDJ6+Sf8WomyzLknoy4cG9uxl3e76mTpKhsyzXLacPH+L8wDN3nqU4OsY+dkQ0zjr2ZhW3dUTMFPjE+cUCPZlSlzWVgkmp2YhAALxrOZ5XuGFg03memZVIJA8uVrz9uRc4uft5PvbqQ4T6bf7b73kf072SeVnlEMRgEcAQJMkopClQKTKZ5BvTRkE/BKzPmVGl0dlQ7S2iyBMgu22fdkTuvXaXu1+9R99b9q9NuLhcoFRBGzxd31LXJZZMyFFFwaTUPPf2O5yfPUIy0HVbzs8vskcpxizbG2VbafQqZYoVXIkeAwqtDFopjg72idGT/MDlk1OSHzBCUVQ1Z4sl73jfB9m9cZMb166xbXvkyQl1NaEoC+b7Ew53GvZ2GlK07Ow2HO3uYMbcG2cdj84W/Pc/9z/wkV/9GJsOSlMztJs8qRECTI0opwSbQBtSUWbWpu2JFw/pk4TukotujZodEoeOdrnm5gvPUVUlb15eQtWQeotNHmkMl4snTIWksANlIVn0LTIGZMzSKVVPeOnt72axWvGVr36ZgYo1U7Y6m/RVcrSD49H5Oe+5/Qy6UPTOsl5vOLh9Dbda44VGeCAqbLfhyZNTdmc76GRYr1vibsP99YJ3v3AbRA4erc2Epigy1r5QGAFejLK7ERcbEiyXC+a7OyhTZK2yyjIHNS5mV5vSN/Pltt1oXPf4OGYshYBfdRmTPmuy32inznITH/PhYPCZXhZjvq/TmHkmBUKPHo00pou7gFQZ9x9TzleClDPgRAYpIBPJOkLn8F2X39Y+IJsSPZ/gE+iQnyGVIEmRs4uiQc0n6HnOg/OBEYWdJ0wiZJqckAIxqXIXdVplWZaBIASYAltWrFPJkzaQCs1uiszrGukjZjpD1RXBGKzPh+iiKNBKUhnJ8bVDXn31K9x5/g7f/oH30m5WbLZbqskEvxyeNkwiKYc/uw6iYbVOaCR1VaDLTD+yzmYqICN4Z/QYSVPSzHfzQU5KbNeiTE30XfZIIFAiU0512WRPwyBJzubvjyLJseOfMVbURcVsOkekRNf2OG/zBDzkDmocKRI5lFZSNRV7u7uslyv6bs23/jffg5CSxWJDVQ08f+dZ2uUKM9tl2/aYwlAUkrgMpF3N2kUKJ5BGMq8rkrP4+W6WOQsDyhMvN4hSU0ZQW4ssS0SwmTI4yhKjCwiyjE3VJaLLMigpQg6fJiKmJUxqRCFJ2w1utSXaiKo0bqrRtck5Sle5P1ojnSOcLXHJEWWWyoQQM5hEjvlQozIjX7mAjEngB4vpLaEu856SIoKEXWzxq5aw6YgjiEJqhe9tLpgGm31y/3s8/P8bXdYOI7goZ19JqQjBM2lqlFScnZ89ncD7wXH/3pt47/JkJoTxwDrCj7ylLvOZQI9Nx+gjs1lFVdVUZYERETn+zJTKGXCm0mgtqaYly4tVnkQiKEwOEZcye01STJiqIIoMapIqy1y9809jJIQUOO8ZrKWsNG5wlFVFCA5Bzr3xwWXvVFEglKcoCqpmQhISHyKL1YaicxwojawM0TqWdkM1maLKku3lmtZarDbE3T0uZPavWZE4PX/M0LdsNiukMiAlRhtSlGP+maDUBiENRhvqomR3f5eyKp/KDI02zKYTLs4uICXOz89YrZYcH+3TDwNVXY/wU09dV/jgWS8v2G5avA94n+mnOzu7PPSO00cP+BN//AcwpuBwf85gPd12IDpIKVs50qjEcINju+lZbnoulxc8fvwApUuapuHlt7+EDi1njx5zenLK5eWCGQVHoubxyQkff/SQtt8SYkQQufbMcyQSj998g9XlIud34RFCs71Y8Owzt+imM5zNP6OqLEkykaSn7B3bbZsnwz48hYb0g6WsKlLKMQxGarTSGC1ou46261heXpDsQDVOeoZh4PrxNdpuS3QDMQaWiwte/fxnMaP8OaSIVhlStLw4G+E8+cxXVRW9bdlsNhkWEj3dZsvd11+nLAz7R4eUlc5eP5HQQjD0A0rKDHJwDmcdEsF8Z0oIa1IyCKWYzhqM0Uj5fxRLv+/VWUc5jPlCMsuDtBK5eIqBUkt8glgKlMhhhtJnmkdZ5W6CkpmYEnwgaoMS8ml3YP/aNU7fPOf89ITYDgS9RSjNarnl81/4Is8+d4ed27fRuzPE6gy3DpRjtd5LC8Gx3vbs704JogARcrfatlzf3aGcVCycZfADstAcTSfUyXNYVXz87A1OJlPe+b4P8uarX+DV0ws+ffcJH1DHlJOKGB3J53+fTA4ZNSpm+UXwjuChSzGjPQGix+CxfqCaTNFaslmukDHR945HX77PL/2HX+LBo1Pq6YxHp0+oiho/BJyINDuzp54vU9Xcee4O82nDx3/z17h37zVcu8rToqf4XzHCNFSWc8GYWyTy5hqzLFKbegRuRB4/uE+MkfXyMhvlRU5n1kXDc+98H8d3XmLn+JiyKBii5PDoJjIJ9vamzKead710h4lWTOuaetRpB+/ZLDdstj3/j//uZ/nV3/gYQxC4qBAy4oMHneV7IVWEBCkO0CVEMSHpIpO3VqfZk+I2qHqfKCpE0aAKRb2ziy5Lyp1dNr2F3rLaLJjPd5nMdmAIFNMJg+vpo0ILQecCcgjETYdbb9l/6W3cfM8H+exrb2KLKUKabFn3gipYiiRolxt8qdkOA+XOBNtZ+tM1By/VTCYlUTj2qmt8/vNf4APv/1YuVhvqgx1Ozy+48eLzVLOGqqo532yoQmBHCKqqIEWHiApdKNIYIqq0RgrJ7t4uIz0EY8zXFEqQrixo39RXWm3x6zbji+PoDdn2udMtBGHdZlpekTfp4CxpCEjvkWYMkyQXJ3hQPktr3LYl9APFZErwHiELhm2XqXbLLVoJkpbEYUCphKgNwXrccotbbEgS6D16p0Ef7qKP9vDLDUJKgndEm8NBIRE3bYYAKEESGjGZkfQ50TpMiDmjpMn3t6kLpMn+K1UZXJIMpmSQFVtpCIOj9APzWufpmFHookZVJj+/QbKzO0VogzIFu3u7zGZTTk9Puff6G9y+c5P3vPe9/MZv/AYyJqpqig+WrtvkAi6OMQ1hyHR0rYha0kx2KYJjphSb5SWDFcjkR7iApCoriqKmrCZsVucYY7J0ts+yGxkCypQE7zBlhQsjNU6Ok5UkkEJRVjXJBybTGbuzOTF6npw9wbtRtqjGaWEi+6iiRKscUFlXDd56njx6xAc/9O288Nxt3nj9Ho8fPuS7vuvbqCVse8t8HmnKku1ijdmfYaY1e8Hht54NgloUlMkRpIKyRBmH8o7UtcQykDZbjFYUB1PExSVi2SNiRJUGPc+HTVzIGPAQid6hJlkWGhmFz/MGOS0IfY9btMSth0CmO6LRRSSJDJJAJFLvYHCkvsO3LW61xhhDtJZhtcnFcWmymsOQwQOGHK4cc0PArztEYfD9QNKKFCPuYkW0wwgWElmWqSRSC2Lb4VebHFga3joo5hvlcs6ilcY5h9S5KEoxsbu7x2Dt0zUypoBEslwu82QjxJyfGHJQsu09pixJAkJwlFVJUVQUlUakSCFAyhyDEqNnMi+RpAyr0lA2V9MShTIKNzj6bkBISWUqlMjqlJgSWiu2JLy1SBEwZZZaX1F1UwqEGLDBIxR4nwsuOwxIKRBFQdnUFFXD4uISVdQ4XZMEOBy+qtBViRKB6U7Do8tLLtcriIH93V1SmuM2LbHdcHdxgfWeRMT78PQcYUxBUVRZiqr1qAJLCC2Z7e4QvKcoC3Z293nxbS/QtQN+6Dk+PGS5XLIzn3Lz1jXK4r1MpxOOjg6ZThqqymQCm+159OiUr375dc5OT3HB4/oepQSNkUilWK+W9F3HjWtHzKZVVmKkkcbpLLZtWS8FfdezuzshxezTbpqSyaRiMpkxm0wI1vGub3kHQ9fRdhsuNkuK2QS2G6IdeP/3fBu//pufZ7JtaYcW77Oq6dnbz7NuWx7cfeOp/DBP+gRaS3aj5w6JcmeXpevz2VZJjPW4fqCMgcJIikJRFBkNnifvMSvPtUYXBVoXowzTImQgjnJG5xzNtEErSSSws7uDEXB6+oTClFmSp8Y1ICZstLihZbtZE5zNni+taduWmODh/Yd8rqrz+aieMq1n+fwOrC5X+BAJ1jKdTTg82KMsCkxZ5Cy2mChGMMn6aEM3eNre0lSCtm2pyj+8kuabuliKZIqGlhqlJXIMhBPk7gMpj519DDilGKxHqSyFccHnwEEJSmiEllkGkY0/aK2IhSSWOo+FrWU5WA6Pj/BlRX14iNnbJ+7sYEtFKyNRlXS9w7qBXkVCyrk5btigy4ohFQhqmqqiUYJdk3DbbGoVMnGx6qnFhGfqgsPdGV984yGFegatC6p6zv/nF36Rj6ueH/pj38/h9SNaD9YFduYFE509F5sAl31C+J7jnZqZAUSimjSAoChLQvCIKCiLiuXpE+5+4Sv8h3/3H3n85BKvFJuuYzLfodtu0cqgygLnPEqX7O/X3Hz2One/+hq/9NEvMPSWGDIhzUeXDxljGrkSIk+YYhh/YiNtTGSCUlnW7OxfY71aEr1ls1xkml/KidxCCKLSHN16luPbt5kdHmDqitVyQ20KiomkLkumk5Kb13eRRLz1rN1AKxNpPmV3NmG+s8tHf+UX+Nznv4R1ClHUqBgYui0ITxIF891j2h62mw0iOZRIBKeomhm6bmiXS6LrM9gv5cwKEqhqwny2gy4VUwXVdALOoYaBwbc0O4dsu4GT0HFjvsu29+zfPODGzUOWlyvSZst6ccGXX/0Km919br38MvfuP4FRklQYwVRJJnVF0ppu8LgIzx5f5+SNNxjaDZLbOBt4cL5g5/gmBzdv08bE5Pohp92aw2ducufOLZQRRGVoLz1qu+X6zhznfxcO4HxApYyCF3JsGqRMDyuKIj9najwIpEw2km8xkPYb8UoC/KYjVQUUGmEUYrBEawkBxMWGpCRmDKdOvSX1A1Ep/JBNvplqJzOa13mSEmy7gaGz7E8Ewjn8dst6uUbHRGzq/H1SzHk/EmKfjfvBety6Q1QFwnmGRYuYN5SHe3mDNgaG3OBJhQGb8C4RegfzKW59jt1uoZ4gRI/QhpgEwkZ0owkj3EAUDU4a2nLC5RCRIh+2a+WZT5ssDSwKdD1lcAKhcrabkoLtw0t2DwuM1OxcO+LsySXf8aEP8J8+8st86dXXeOGdL7NZrvi8kJydPWGwGQwTfU6J92nIUrvkESER+sTWXSCUppnOMeWUoplmD43L5KsUEwqBFtnf2OweEG1PHwJKGcBT1RO8zREJRmu8yDINISJGF+iipKwbGBs4l6slfd8SR+9NDuUc74us/cu+EaXZ2dmhKjIa/ca1W3zre97No/sP+fQnP8l73/MtPHvzCG8ts4MDtJI0kxmLiwVCaerZHn69Yr8QrHvLIAp6oCgLWg+zaYPuu+xfqhqYJSrrCBGELsFUyCogtCKGRHe5oTjazVOfzmYJemHG/F2BNAZVGFRdMlwsGS5amE0QXY/sLbrQmUznsvTWywQ+gvWEEBi6jn65oZjO8nQpQrftqFRuqmBz6DIjeVbqTHYDsOernLcyrYne4Zcb/GpD2A6o0XuVCUMBt1gTu5GwZ7+ZAQ/8nmIvwx6MKTg7v2AYJWRcAY4Q2L7DaIUwmrKsxulQQEvF0LUoCqaTfaaTmm03jITIAmkEbhgwVUUMUNXlCCtJyJSomopu2zE7mNFtesqqwLctRWkoCo1KkdAP+BCwJM5PTtBGsdqs2KzWWY2sVKYhMgbkTgzRCgojWW5zY5fJhNLsEGzH2cWC89WaXRuQ2456Zwc1mzK/dh2zN+Pxk1MuLi948817Y1hv4Eunj1iulwz9QARCt8WUGUolpMB6h9KKqqyYTKY450gJbLDYvsdIzf7+ERCfyheX5+fcuH6MFAW7O4ekZ2/gY+Thw0fcuHGdm9cPKQtN0+Q8qMVyye984VW+8upXef31ezjnclBwoXnmxhHP37rJcrnis1/+Cs4NBB85eXiGcx6tNMKE7A+NKVNOY94LpFJIbahNxTteeBE7WPYmhtAP3Lx+xN17p5xdLOmcYm9/jioWrNcbXv+1z1I4x/mje/SuQ5mKnZ0JJ4/fZLCe+e4ckme1uCT4jEvHOz70zpd5x3veyy//zmuoSUlZT2Cc/HnvKJsS7z1aK+aTnSynDIG229D5vKfpIje9gutxQ4d3lqG3o3c0UjU1k8kE6wa69YYQE7u7c4wxFFqPsQPZZ3olN5VKEcezeCJ7wmII3H39LudPzjk4POL4+JggI49On7DpOy4vLhFJoJSm7QY2m5b5tKGoSmbNhGbSZH+1KdiZ5YyylBLDCzdZrjas1+s/tGf8m7pYYqRlaA1GCUQKCEH2J/0e3HGWueQxv9YaFfK4Of8A86G8twNlpSlE1gu74BmiJyiBR+F9Ji75APXhPnu3nmX+7LMsnacbetJ0wmLRjqGxjkIqYsxUPZEkxIFpPUOZKbulopCB7XrJzemElXesQqSup3zpdMlLt/Z49+1D3li9yWuLDd/x4h3uPniDyzfu85Hf+CV+89Ov8n0/9AN8y8vv4Nq1fdYu4QgcNCXK90gpWXcDUiR6V6CVoI6Cpsj/tpQSyhSsLjd89tO/w2d++eM8Ob9gGRzL7ZairlhcnpEiFEWFkNk7MN+fU08qfu3XfpWLs5PcUZeSwtQM2z6/2yIforNRPSdQ55/VaLaWmT6mkmQym2OKCufOSW4gBDdigEd4QILCVMz2j5jMDzg8PGbbbVhvL4hSUmjFzsGEmzcPkQS6dotLgUoJpvMJWkE9qel7h65KFps13eARxBxkPBbGpMh6vSZRkaSgKaf0XUcSHjd0FM2c+eF1NmeJIAypmiK0ItVTfFGzXPfcunZMIaecn1/Sa8mqbSnCQDQN+MT68gn96pJaFpw+OeHm8zd497d8Cxenj/nK5weCmHK6SYTXH/HcnTtcXpyzulhwfP2Il4726C8vaZVkNt0lOsfB8THJDQyrM0RV8fh8zb3Tjnddm7B745Bmr+FsecH8+iE3blwD79FFCWWBKs1ons+Bs6U29HZAVwXRuVHaoYgx5s4yOcjuajKYu35Xz9d4qPwmvqJ1pHbIMqZUjnkokuQzmcxtWpiUMKkwpiYMmTCJlESjSFcGep8JVVm7rjG7Myh6kpL4kCBC13c0uiARSEKCs1DWhG7IGUsp4lYd3keM91m+mjKAJo7PV/KJKDQ+5eI3KLJPJSqMB2cjweVGgzrYz7Kn0uS1cFYRUl7TOlkx6AqrazpnqZKgVgVeeKRM9MmQos4YcDxFaYCEdRkIMqmrvHE1NfOdQN1v+d7v+z/x//35/8iXP/cFPvD+93D95nW++vobfOpTn0IJSWk009mUh4/v021bkvBjw0sR/QC+ZzVsMwnJGOrZAbPJEdeuXWN/b59Hj09YLC6ZVFOqZsLjN79EcAN109B3jmGzopntMHQdMkX2jo4JIaFEgJhouy3tZoW3FoGgrJscYRBinv6JCCGvYdpoUpIoJdjbP+LWrWd5eP9NZjt7vPdb349W8KW7b3Lzxg2+5498J/sHcxYXS6ZB0cwmuBTR1tJ2A1pr6rpmV4qR+aGIzZyuH0iFwpuCdtljVIMyntKo7CVJkPZ2ESPRVWpFiAl6j1ANDofrI84U2XcbE7KzKFOBUfjBEYeYqa+DI67b7AWrSxiy80Q4T3KBQMho8DHjLRkBMiFkQlWaJHT2r8SYp1Aiy4/yQwTBeZzNBUMsFEVMxMHhB0toLcLILAm0FlEZwronrFvwAZkiwoav94h+w1/Oh9H3mqdpUkoKU7DervK+NqoupJCE6NHK4EOeIhlj8N7lYOkUiL3F4ijKAhAszi842DnEAV3Xk2YmNztEApHJtG7wmEJhnUQahUuRJ5cXrNuW5WoJa8G9swdEBdZZBudpt1suLxdILTi/PMN2A3VVj5OdjAovm4pm3uTGc6nofSD0GusjlXAQEi4m+pgQ8xliNqMrCzaDZfHgHosvfJ5t1xNCYDqdPpX3LbdbuiHvNZKE1IqiKJg0TT78Ok90kbouOTjY4/zJBdoUiET2ZQ0D+7tzihHioJWmX7fct29y48YR+wdzrt84phscN68d0dQ1+/u7CBLr9ZqTk3M+89uf5dGDB9TllKPjI+7e/TKhtfgouffwlPuPn6BUQRQFVZl45pnbyOSJzmKUwUuBKjRCCRhlwEiFkBJpNPOdGbd39+jv3KaoK44PdwlJcrLseXx2htGCJ+cLVtuWrQv8D7/+y3Ru4PzynK5vSUAzm1HNJiMgBJrpHGsHLp48JsVI7Dac3L/Ptb1dJrMp+/t7zOYNT05OePTolMP9Pbq+zz6qlNjZnRNtR9d1KD1DoJk2c3Zm+zTTHbwt6Iaesu9HIq6iLAyFySHt83qOIscdCC1ylqCUaKVIKhBjHP1fkBVGGQkeQ87NS2QoRgiR1WqF855ClywvVygl2WzWGG0oq4rTMwEpMZ/PMdowaZr8dxpx9qYokAJMWaD1GGcS/w8Z3u97yZxumE1eXHUExRVBF8h5eYXMWvYYcwqxHA8eMUWkzGGLGZ8YYZRsJJ+leqYqidYhnKbddNgYufX2F7AxMdnbITY1tSjY1QNnTzacXQwkEruFRhqJdBJEhTaJQgj2Ss28FAgZkLFE+cCU3CFaW4epS157csmd67e4uXPJCs3DdWRv7zoPHv9nRFXz+S/fo/sPv8yv/9Zv833f+0d4+wt32KyXpOduU80aUtwgTcGjZY/YJly/5XBa8O7nb1IZOYb2Sk4fX/C5z73KF+/f596TR+imoesHtu06k3RiwsmAxHJweMTDh3cJMbG8WACKKATlbI6SgqFdjI2ziJIFEU8Ibjxk/14JXj5cS6VQytB3Qz48hDCS1648ThlNvbt/xOHNWxwcHWBCYPnoAcPlBdP5jHe//DI7s4au2xARTGqDCo7D3V3m0yllVbLtelabjnXXM5nNWW0uAYHWJU4MwJiYvl0TwzbnCVSGiEC6nrA5Zx2h2bvG4TN3ODl5TDHdpao1caaxQ6CqNclbpNbcur7PuoRNGrh485TbLz7Hoy9/AX9yjzZYqAtS2/Kff+VXOKj2cCnQeUm/s4eVBT4m3nh0wbe+9134zYb7d+/y5vpuXmBSoDSGd778TmKhOLx9G7fZ59HGskHx4vvfD6XkdLPgjbP73Lxzk9sv3sndRGfRumYz9CglKY1CG0Gt1Qh1MMQQefzwIUfXrzE1O08ld7owhJgD6SCb6698Shn5/s1dLIkhEAaXQQfnq9/NRpK58HHLNWlS4ETA2BnFtCastrjVlkAE5zOJbDyAizG8tywK0uAzFKI2RC1pu45qqsF7AhLFKFOViRQ9KfkxBynibUexU6MnNcJHUjdkP9Nmgy9K+raHaUMyFakxKFPh7p8Stm2ODawKolHI+QyISA2y0IS6oTMF1uV4hKKIHO/Pcq6Jjej/H3X/9avZladpYs9y2372+DhhGPRkkmkry/S0mcaU1CMzc6Er3emvEwToQsBIkDANCequqq7urqruqsoyaZjMJBk+jv/ctsvpYn0RmY2ZOyElcANEICN4DjPOt/faP/O+z1vk2F6hhUEZjRv9W5JoWeRkucAu5thdT3Z+RPSBoipQSnGkcv67/+5f8T/+j/+GV0+f8cf/q3/JRx+/z2w64Sd/+xNWdzd4FzlYHHNlL7FuTFsjn7bSv5nAe2yfPBHFfMGHB9/h/P475EieBc/Z4TE2DFw8A0RAZxlqHPHjwHKx5OSDj5jnmq4Z+OLZN1zfXBFcwv6/2ZBJKdBSMtg9LRCHlIYiL95SHp2LLOZzzk5PefXiOWVZ8vFHn/DOw3NuVjuMdvzX//xfcHZyhMlzdqs+ZcOqZIrvW4vIIqEmJdo3LZWUdC6mJq4o0CEZ5a3RtIOm0jladIhphYzgbMBqgZoUQEwI+LbHvryAumKYVgSVojHQErvZIQjILEeSSGwsasYXF4TOgpGJThdjQl6TAqkZLRAIMaGenfMp/ySkRlMva+hc+lotiMMe7a4krhtSXtkw4gE9X9BvttibNe52A9YjiGRlTmwHxjGdGymANxD68b8Ik/+2XQKIIqRwc6WYThY4P6bQWFOQiJepmLTOM5nutyVExnGkbzb4MfkzkMlG8M03z7i9W+HsCATuVrcsJoqTgxKfaSKBrh9xtuXm6ppusGxWG65v7lhvtnz5q1/hY/Jzyz3hThqN1oq+7xm6ka5vGceBzWaNiIKiLN/mapVlQTHNkblkebgkuEDdOqyGtVZstGIIim1Zst41dG1Du1rhoyeyJwp7j3cp73Ic7W9k2yJSlgV5nidCrwAlNbvdjqqqOTo45OTglGdPnmGbjvOTE3yEjdJ465IfcRw5mp8ym9TMlzNMrhOSnEjb9thh5HAx5+RgSd919F3D7WrDV1894ZtfP6FrOg4WB0glkeaE5dEx67sVfl8PmswAAuU8D+6f8f0ffI93Tg6xPiJVopZKnchsJsv2RL03v68SeOH8hI0bmB0fsjhYUNQVt13Ps+evaLuW0Y9gDJe319z0XSIzk4AcwTuUkJzdOycKhVKKIjP89Cd/y83lawD6EPl//PTv+entLefvf8j/9p/8iBgjz3/9FauLCx5/ckSwjizL+fCTj/npP/yEl09/iSkqDo4e8eDRGV0zsttuGJxEkqGNwSiJ2m8Z8yxtPlNeaTqjR5uyMKuyRmuzj+ZJtNBoMsZxLweUicyY5xnjaFPk+Nvctoi1PZlW+CAYRwhBsGu7FPlCAgKJmLK/LglokzIGE3PGpzDg4BmHIUFjfodk3m91s6RlyhYSe305Qu5NuXvt+RssNZG6zHAMafqmJNGnwLUY49tpUPCRIAJGG4ie2bRgdrTk7m5DEIrK5FgRmR/OmD04obMpUFIFKOuCk/vH3OwuAUXrPd4OTDNDpjRVkTOvCo4XGXYcCU6iUQwxQFbQB0cbHO04cDd6XvzqKe8dTPjPr655savIzk74zv/6f8df/w//R/pn3/Crv/kLLt95lxevLvn4wT3+1f/in/GTX/yMo9NzFvM50acD9ubull9/9RWP7p0yq0reO5unNbeNfPWrb3h9fcWXl8/R2tCsbsmriiIr0SZjO44EYzhcLnjx4mumiwU4xeHymPnhIY1zLE9OuXj1lM3lN+zdSgRvU56MSInVYZ/ULhBvuA4IIdltNkSZp6na/qvTlZrZxcERh/fOyY2mubrg9c0dX339K05ODnn3s0+YVSXNZkPf9dRlRTUrmU5z5tMJZVEyOs/ry2sWiyXvPX6P6eKEi9ttWvuTo4opRE1ZVey2PXJPebJ2b2L1I1JEhO2wmzWTdx5z26ciV2QaMTTMpYHVc/r8kJeXN8zmcw6Plizvn3F4fEZV5dhxi7AbXr78ho2PqKBgHBj6WxwKn09oNhtCOd0HGxr++u9+Ro0j9wHvE1QDKWjcwLOXrzieT5nVE9qY8fLqBY8/+pDj00Mubl/x8uaCTz/5mHtnx4mopSS6qPFCsNlt0TJyfnRAhkCEtGWz3pOZjOOTU6pJjdb6tyh3SW6nhNxTst7gOtjn3ny7r7jPzok+ZRRhU0Edg9uHAXY0X3eIqsANPYsPHhPXu9R4NMlLIqwnKoEWgAwJZ20thiQp8P1I1BonFf0wEgeHmBbEQhOtJRYJdy2tQJWGeNfs6W6BKFLc6ni9IgiJFwrrPX03ooqCIDUSwXhxi9jsoOkg17g9/S5t1ZPxNun90rZdRZ9Q4krSIBFZgSolYzdAliEleOvZ9QPZZILSadrsraWsCla3W0JjyeflnqqXoWtBZMIf/6t/zp/96b9jc3fHx+89AudYLA/48z/9E+xgMcYwnx1we3dNyrbTRN+nAhr2jWMk2Eg3WraXl9z/7g+5vL3m66Hj9fULLq8uGMcBfAJkGJMRvOX2+jV1nnFgDjmeL/nq2ZME5HB2n92033KjaJsNhIAUCqSirifM50uabYvKciZVTW4kL16+YL444J/+03/KBx9+QLdrMGLgX/6Lf8l77z6gqnJQOgU7B0FeFUSbwmtd9GT7AUwfJMV0AsOAtPvNtguIGIijpXcOhcJMKlTTgVLErknZgaMnyyTCWsTVgBod8TAwZpqxHVF2JOYJ8axcxDYDxo1pODUOaQqs2Z+/IjEafACfYBpCpngHZ0dsTEVf9CnLSyqBDDF5awQJAy5lmhyrQPCC0HWMV3fYvke3He3lNWybdK8ps/ecRKKLiNFBYfZwJYHINOy+vUMXrTUhJjl6WVTcO3vI7fqW8wePUFJxeHBI2+34+ulXbNcrirwAAYXJkmeMFIxshz2iXmQ8f/qEF09+hVaaV69eUmUZ3a7h7m7NyxcvWW+3aCXp2oGrqyuk0vstv+Dw+ISf/vIXKT/HOTRZignRybcihaQqK/RWsttBbjKGYaBpduRZwpDPD5ecPTqnyDV9b+m6nrvNitvLK67u7hitpWlbnPCMwbHZpE1R8iunXCkZSVWmT6G66W8a09a4KCmynM16gxdpgFpmE4zKOVweY91Is72jzDSzxZTvfPYd+rbjiy9/Sl2e8OH77xGD5+z0iCLXHJ0dUS+m5JmhrMo0FIkBOwaapuX2dsU33zzn+cuXFHlGrjVd32F7R9t3KJHopjrPKLShmsz2kBLB/fN7vPPgjJOz4/SM54ax7ei94+Lujvfyj3BhL00VApmZhMKuMrKyxu+foaooqPOCvmtRUjF0fSIZ5iXIvfxdpXyqGDx9b/nLP/93SZGzr5GGrk/b/ugRUrJzgRe7He/WOYJAUZZ874c/4tE779CMkcm0YTpL53dk5PF771PUFfP5Oa+vNhyenKK1pKoqou/Z7GSChWUZBZKszFHKYFTGaAcEkBlDVc/I8pKyLvH7iAhrRwpTIoOnyHMQKbohocA92mSYLCMvCnSW4BwmL+j7hIkPwe7jZyJKKCZ1zTAOqSGyFjGo/QZXYEdHDJ6u6xNUw9rfqcrlW90smSxNS4IPKfH+7WBKIfYl8ZuHUxKZ5xprJINLfwa/2XSEkKRGvfNkpOw+nWmWpwes21SMt1e3dHagnlSUkwI3RMYALjhwKf/Eh5FMV0iRIbwkqMBsOWGiJJPc4OyYclukoZMQpKQfR6yMBOfQYwAbudo1VErSXL5kNUrKaHn86ITP/tv/PX//r/+vNN/8nPDiBc3lLbrr+b93A+9+8hEn20C7+Uce3zvl+OSMydEcGe+z23bs1i39JIMMnjy/4eX1Hc/vrimmU46PTxiHjiIvWSyP8Dqniw4pPO3NLYeHxxzcO+Pg+ISu67l37wH/+OWvGYcd16+eMdqRtFA3xDggZESSoWSOswNKyf32zqcgROfpbEOWp48hbW1D2l7swyc//e4PWR6dMm7v+Mlf/wVXt2v+8J/+C46PlswnFWPfc319R1WVaJ2K23F0WGdhiDSNxQFVnTGf5DgUWVmgTMXs9GPCsGK1fpEyRWIk6pxInsIeg0MKRfSOOG6IPvDk5z9hcnSOtT1lljGbHOD6DU9+9hNuntSEvmccLeWk4vDwmO9/9wccLgqy+4d0VzO4TAeiqiYoWzH0DWsX8H2Ds5GJMfTba8TEo0WgdS3z5QEGzURPmCzmXF5d8Pl3PseFkS+++YbZfMG9d+9xfP8QLxQ/+eJLvvPDzzl58ABBT5Ul1LeVghdX1+R5xiTPyGNAe4/ShiAVhTEALI+PU3aWkjjnkFqxb3OTjEslb4IQco/j//ZOg99cMQQ8HvNWnplMtIiELXVNQ5SS4e6WzXaDu10znU6QkwpFQIyWODpkoYj7IU1oOsgNKle4vkvSxyAwVYltO/ZlMnG0UOagIpGQft4yokuN1KAnJb5tGdwI0uCiIE6mKcyzyBk3CRMMIIYhbcVzibceYRTRBcQ+x0eUBTI3qAB5rsmNxPURS6RtRozcp6orlYoGY9gOO8pZjSnzVNQ7l7IvyhxpNP31jrwwOOvoh5FyVlKWFSaueXzvPv/n/9P/jT/4ox/wT/7ZH7A8PGLstjx99prn33zDcrFARMeu2xGlJkSbhgLxN8n1MTqadsPPn37N8i/+gq9WV1xfv2b0jnFoUz4Ikq7Z7n1Nga7ZcX35knpwVFnBanVLdAMk+zgipK113G+WhNFU1YTgI2VR0o+Oop5xdHAIwWL9yB/84R/xwx98nwcPztltG7bO8oMffM7Z2THVpMDkRZIca00YPP22I59UlFVFbBuMG8irmt4oOp/w5u1uRyYkxvXo6JiIgCokuZckrYRnuNvB6GDv+3QxYEIiLKoYcXertIGrK0LTYmKRmvp2QDmPCGNCxnuPqlOumvCg6jxJ8PYwixQDkCTpPvgUN7EnWQmtUAJoU9AqWiYPnItg93JcKfBNj7OO7dUNw9dPiUOPDpF6WhOVRi3mhGFEIvdnvUkkSesI+2DTb+vlQ1KpKKXJTUVwgcPFIZ98+ilXV6+Zz2bsuo6htyhh6LohmfCzLIVCC+g2t0ip8c4RbM5q9Zrd5o7pdM7dzSVqueTyNvDy5dfc3N5QFjXvv/8u213Lru04OFjSti1SSL755teofeSD3mOZlVLEGNjttjRNQ9/3bDZrhmHAWZs+CykZ9xvyv/7r/8zF60sypeiaBpkyWtBS0o8D1juiguAD0/kMa32CWUiNQkBMAIEYQZj9/QXEIAhRklezFDeSF6mQ1gYpBNN6wqQuePHsJVIqdJ5xdLjgw/cfIJXh//I/5Pzo977Pf//f/zFd12LyHC0lIULTtviQIi6Cj6mRvLnj9dU13/z6K8ZhpMxyjJasV2tWd2t8gPlyxtHhITGksN2h3eG8Yxw76qzg6GDJ43cekqlAlmmikNgguFw1fPP8Ce9dvsP5/eME2VSGrCjohh6Va3RZJv9xppFSEInkRtGMls06febtbosLbq/EEQn6sb+nhORtKLQUSakjjULERDGOIjKOHY/eeZciL6iqEqkMi+WU29st/TDj4HBB06740Q++j8lzvOupJwuUMVRFzunhjM8/e8TFxTW316+pqgmZydFCMKlrDg4PE8nVW7wQ1PWER+99wGy2RJuMru/w1mLtQFlUDI3m1YsnEFMWY6IqpnNyMp0l71FVpiGKUuSZ5uh4gV8kKwNEFosFJtPETaBt0j0ZQ2IUSCHQWuP9b4Vlp3/jd/aMf6ubJed9OqTEXlKxv5ES0SxJuQLpIAPSqld4jHyDSRa4GPe/eoQLaAFWSobomWjP2fIAbx3XNysOTw+4Wa15dXXH0fEp/eUtzgf6weHiiNcSj0ALjXcDKka0yhKtpTJIkV5GmTas+gFbFNihp6xrJlpyZBRea6re0l4ovvrmGd3la6KY8MXdHa9eviC4iFu+h985mnbLxEhub9c8/frX/PXf/oQPP/sep6dnXD69pN/+OR998Ij3PnmX+dGUy+sXHM8E1aymG0ZMWXByfs7pg4dUdU273VGXE5RRqDKn6Tu6cWS12nL88F1ssKw3O3rn+PIv/ooYIk+++mqPHzdpAknSZosokHvajxIyHRL73J7g9h+GVGmrFD3sy8c0GZAcHR9ycHTI069+wVdf/IIRxXd//E/43vc+Z3d3xXI+30sqI0pEyiJLRbw2jKMDIajrikwICpOmmtVkhi5mfPj55+j5CW4346SZ8eTnvyCaIVEJlUKonCDYp4sP4FtEDLhNS3FQ8L3PPuXF02cU1SkvtltsrLi6bZjkBdrA9cVrtte3XD55wny24N75GW1hOP7kM24vXuMjfPbhD7i9u8PcrWnWN7Rjjxu2+H5NG3rm0wOOlzPunRwyLSecnJxQT+dc3lzR9C1OKcTsgBe3N3xyskSbnL//8tccffAR2fIYrzWTaopWydvy+uqGwVsOiwln8ykTrbi9fE09m6CKgtl8ng5h/SY8MdGHIhBiesmlTLOQmts9YpYo3+Lhv61XGB3ChzT59PtcFCmIRuJVKg4Jnjh0qNEixg6cQdxZmKYXISYhedGS4COxSB6haH0y3uuUibRbr5llOfsyFD9aEBJzUKOCJQRPVhUIm3JMwjgQvYXOEvodsSiwPhCqitjs9nIxA02LVwoRLC4AyqStwDgSioyoE9VMDTlxUmKVIfqILAUGmMSAHy2iKlC5BiUZeoezkWyWMZ3UDG1Ps+upq5owWsoyp7vZUs8KooQwetrdwHxeUVUl73/4DkcP7vGP//AL/uOf/Sd+/Iff53/z3/43fPH1C/7xJwtu79YYk3PPaEY3cHH5ms1mh3cjLqaGXJCa89tux5/+4m/xMdJ2G/xeMYBUSceuBG60iQwnA5vNiqftSCQwuhFwSGHSOyECMqCUYDKd8fDRO4zWsVvtMFnBZLHg/tkxD85OsePA+YNzPvnOp1STCVcXl9xdXfHuOw85f3BCrhKaOcbAbtsRnANnKepJeg/FVLjlhNSwBU+WV0kyUnkkHlqBiiKpJIxG+QjrEcaAGBPG3AnBYC0mgAwBpcGPY/JaNT29UCjrYfSQJ6XFeLkmyICOHm8U0idARMomUWnLryVRRsK2J0pJMAKHx7MfGoiIGBwySxPdMAYYPdJIQvB4kSR8Hk90Ed8FXNMwes/Qt9RZohMmedkeOe78fqOUpvBxtEnC+i1uloQQyWuR55gseZUOjg558vQJ4zjw6vUlt+sbok+j2xTyDUZrqsmU9bpBqZw8K+nbLVqBknFvxh9pmhVu2HJzncZW2+2W8zPD7e01m01DjJHddoe1ls1uw+3dHV3f0/d9kpm9CciNEecc4zgwjpZx6PEhpDiD/Z9BujXGcaDZbGligODRRI6mUz5+9xHboeenX36JH9OWuuv6lL0nJVmeIaRKABo7kqmUhfkGtOJDSDmYWuOFYHawZFKXxABVWbGYLjAZ1IXh04/e4+PPvsP5vWMWyxkXl3c02y1aCu7dO0l0Uh/o+57VeosbLN577u4STGq93vDi+Wtevn6NlJLlco61npvra3a7hqZtKYqSxWzCOycnfHJ0ys9evuD55i69++zIj/7wD/jk4bvkUbE4WBBiGuh0g2VwluPjE+rJjO2uwSX9XPKe7nH4VV2Q5YayTIHexmjsOLBrEvHu+OSYy6vXeDcmHyukZilGpLRvbQtvmoWUexj2rUHaNpXlEY/ffYeiKAlBJWKiyUFsEXt/272zM+oyYzab0nVbrI+gSpS+wY4dJyeHNG3L8ekRN5eXSSaZzZjOJhwdLun7HlvmXF7f8uDsIZ989j20yrm9XSNUDiEwjG0aPoaYfN/OErxPkBipmC8rJtMJ09mMPM+xQ5IaegTXV1d7ZLunKArWmw2CRHS21uF8YFJP94qXSFnm7HZbhBA4a5EC+n74nT3j3+pmCUhhh9qkYjzsJxdREJPrhIgg7jWPQkQkaTKiBdg9ttOGZKCOPuCFQCHx0dO0HbOy4mAxoSwMr67XjEKgZCrI67qg3TQok/53Pql5/P573Dy7oa4zYnQYnQrMPniOZxVjP9JqlbIFiEwm9X7SYJAqMArH0bzkR3XNYa1RY8OqnHPZDdzdrdNK3UNY3oeZZxt6tncvUdYyXr/kZ//xml9Nah4+eEhRTrhZ3/I3P/0FJ2f3+PzDhwg0q5sNRkjeffwOr599w3Q6ZdfsODo8oGsGXr18RtPvsDqnNxOmD9/jydOXRB+5u3hGkWXcrteMzQY3dsmv4Uu8HZPpVCpkDDjnMCJpq0HuaUFv5HaJIOa9S1K3vQE2AlJEZtMpP//7n/D1r36G955Pv/cH/NGPf0ytJdnBgtm05vXrVxwfLqnrkjwz6cGMIq2ztU5kHe/xQ8/V9RXbtufR+x9z7/Qe7/7gu2QK7PUd/zid8PriFVe3A1eX14RxByo9kEooMCXl8hBZLSlOzvnBP/kD2nbk599cYKeHyHsTTBjY3t0xzRwfP3jI5voGmU3Y9iPxasPDR4/olKEyp/T9HT99fUezbsmLCcePzqmnmiovMCEg48DR/AjfjcwnM6L33N7sePl6RTmtmC4PsEIzDJbZSc5107P+1Zcsjg6ZHB1i8ox26GE6oXeOTTOg8xKNYjEpmWiFjB5lFEVVYfaTL2Py/QH927rftF4Pb7HwpNU6Yu95iN9+dHjw+HZI0ztrEV5AZlAqI1704C3ReYxSGK2QzhO7HpFnxLZLAcxhP6CxHpXpfVEUUD4muZ6PCJVyUZARCg0xTftV8AiXpKuSlJOjgicMIzSJvOecJTjwIj0fssiQY/d2g+THATWdEbwA7/BKJTLoYFFFDgriOBK1wseIdYGizpHBQ2NR0eCjw9pIPp8k2Z72SJlRFIayNPTbHu/E3sQfEVoz7LY0L++ozxYM1tL7kdZIHrz/kK7tWDQdy8UcqSUvnr/g/Y/e48ezD/jed97lP//kZ/ynv/xbirzk4vVLJtMZt3c3fPPka4TNidEjSblJgUjvRpazBbtmlWAQJPWfwxPZ4e2Q8piiQgiFV4LRQVlWjGP3dlMi94bw8/P7fPd7P6DrRl6+vuT0/kPqquTjDz7g9PSQPFPMDg44OFhSFDm72zvuLq957/3HPHh4htEKvd/MNDtHs+uSEbsdyGZzOinJihw5JmmniRl5liFMKlzzRY3dbJJcD480AhclSmUIsZeYK4l3MG5bohRvlJkEJaFLWHTpAnq1RQeLVBJ6SfAjctekaIRMpXtGC5hMkLMJsjQQLIw2bVMneWpW2hQ0LABMupdk8KD2yy0tED4QoyPaCEYliakSSZLXtmg80jvKIqfUyc9JnkP0mFmdApwHS+jG5FcJKeMsum9vs2RMhpBpG992OwDafodAkhclCMhzxaMHH7Hd7Lj/4JTDowUHBwtWm4Z/9+f/iSxT2LFFaUGII7vNBh8C3WZFLCuy+ZQYJW3bMY49t3e3SOno+pEsy9nstsmLNA40bUvYZ5XZYSTLsr08Lu6bo0R+jPtz/DdZnknGl7zfkkhSXRijyYnU0TEVno8/fI9Cwte3a17fXNH1A0opsjwnKwpiiPRY8j091fuIC47oPXYY6NqOptkQQ+Dg/BGHR8v0fIZAWZcsZhXvv/uYutQsDg7f4rBvb24hRIbBJmm4kmnsJCDTktl8gguRtmnZbDuevnjFy6fPqMoCKRMSfRgtXTsydA5vPeW8YFaW/PCP/iu2tztuUGybhkhkUp3w/U++w6PpAilBmwyPJDiPkIL79064uH9CZiR1XaFkClLVSqOzHG0dJh9QRoNM+VN93zPagdu7FVlecnp+ztfffEkaFu8/hbAfSvoUNJfUHMnbzf4xSQNM8VYaW08n+00xnJ4cUFclJ6cHxBDIi4yqMGRZBoCbVXgv+MVXl6xu1ng/YF3g4HBJN7b46HChQ7iBYlJQVoqqXhBQVLMTTs/OiVHy6vUVd7crijzHW4dzPc4O3N1epyWF1kh4S+CbzeYYne3lzjNev36daLTO0XcDu92G+WJBmZdsNxtcsHjfvgU6fP7d76CNQWvFi5dX9OOIkB3KRJy1b2m9v4vrW98sIQSjtcmXIWUyMybgECEGQhBv0dXBB5QUyJjSrkfr8FHsH9KUryGkJATIVMbd6hZHYFFPKLIMlGb79BXjOFJVFWjBqm1wo0KJDI9leVag1RQjHZPZgudPLpGZoSwKXIzs8Nz1DusF80mFET7l1whBzGtGHEYJPjqasZxqnn71daLVOI1wFSF2hOgJdQ0uIEVNjIJstmS8eooKLZ89fkBdSL789c+oD8/59A/+Od+sB9q//4o/+X//W4pCMqmn3Ds9p+tbtptdYu/HyMvXL5kslgz9hPmDhzRe8PTZJTehZHf9Et81xF2PCA4XRmSuUVnG2GoQGqJDhUAcdyngNHqQyWMRQtgX1wIpJT4kL0zw9u2E5A1d7euvvkrG3+hA50znCzQBP3ZMF1NePH9OURiWy0VCWg4DUSUddpaXzBZThm2LBNrtDusCMis4PDnj3Uf3ee/eMVFCfnLK0emSqp7y7/7qC/6f//pf429fYMcOVSwR9QJfTuhVjZgdsynu8fPnO+aPH1GsfkWvSuTylNw46sUhH9Ujz598wyo/YbftWB6ecnF7xfO/+GtElvGdz3/Aj3/vn9E3O54+eU0MguurO+QgGJsBxoGjsmTVbjFGYYc1RiXSS1XVSJW0wtaDzgOTg3ugIkFYZpOcQgfAUuicwY2sh47RpmnU/ZMltVY451BacO/RwyQB2eNqg07PQHqs9tKu3/ImhRB/a5b1BvAQ3h7w39ZLBA9jykeJIcLhFJVrhhcXaeItBEJGbDcgpEDlZl94BKRzeBI4gd4nD5IkNVBKgo5EEdFKMNoxgQSUQuQCpUEWBl1ViGFE5QaXSeiTz8T1adMUBkd0NgXN2h6pJa7dIN2IbzpklYEPxK4n5jkhSBhGQpmj5yVSy+RnEAZsxJSR0oBwAyIzeAlCQcgkUcKuHSiMYjarKMsUzprnGZNJCSFS1iWrmzXWBVx0xHbEbnvyWmOtZ323JS9zQHK4mJMpxS9+9jPKquJXv/iaew+OmR0e8IPvfkq/7fiHn/2CxWKZmr4wpomzG0FoBCk7KkkuPIN1xCj322ixn4h7hJP7om+/vSbQh8BgB1Bp+yTkHi4jNSbLKMqKfhzZ7RoOD5Z8/tl3OD6as5hNKeuaZtdjjME7x+Xza4bB8eDBfWbzinzf8CiZgsibTcoS6bs+vStMyv0bR4d2FlnOUwBriEQfMFonRZvQKAMmRmQIRKPxmx0mk7h1QIT4dtMvrCU2DcGmYN8gU+aRjA7V9eBGHJFMS4iW4MZ0f+5Jll4adAiEoQcDqjaJ4FiYlM+0bZEETJnjvMd2AxwWydNnNDG49J6Ke/qjiWmQAODTNB3hk+QveIRPZz1RE3tL6Af8MJAv5njRENcDcdslwmP0fJunLlU9I9MpuLPYExalEhwsjzg7PWN+sGAYOo4OD/nmm+f0/ZrtbkPXNXz5q6/o2oZqssBoxThGuqZh6NsEdwj7ZiYmi9lgLfVkigspsDwSsW5MGyM7YF1S3IzD+PaeDyGgpEoy9whSGEK0QPqxvwkOTZ8XSfghBFIkOXCMATf2oCLXT59y/6Dmj//g+1x1A3/5Dz/jy5cX2JA2U0VZkZkMsd3t3xue4BOJcuw849jTbDSv/AWLxci7773HZDpDBMdiPuP+/XuUmWEymSDlPofKRfqhp931fPc73+fk8GgPIPGMNnl7Rpeav67t+frJC375xa9wzmIyw/X1NfP5fC9lE1hvGb3DxUDX9dxc3vHB8UPq5ZzlbMK903N8CJyeHHL/0QOmdcEoHFFEQvCMPiBlZL6oMFnOrmkxxqCkShRg5TFGYfKconBvh/lKCg6WC87P7/PVV1+TFzljv0OQcgyHvgd4G82RrvTG/U1ch0xLAvYeUu/Ybjb8409/wY9+9ANOj485mE/QRiW5dWYQIllN+n4gIMhNhtaCV8++4a//8j9ycv8ewVuOFzOefvM1WDhaHtJsb5hMcqIUrNcNuSk5P3tIEJqXLy+5en1B3zTU9RxpFEo6umZH37YJHGWyRAkUkuV8SaYL8qwgzzJGO1JVNW3bJ/y7VpRVRT2ZII3CE/A+MI4jREFVJdCUiIEySz7Zqq7Z7TYIn94PSMXv6vpWN0taybTC8x7rIlGnjj4E/5b0k8B4EhvS+lvsU9kDkcHZNOWNCRYRY2RwnkylIrEoa9ZdT9uNnMznVGXOwazi9m7H6C1ZpsmUoCcgVMam7xmdQ89yysmUZvDspKB0ltOs5q5ruB0sUWvkPiVe5RItBaYo2XiB1xmLWYlzHWUWOT9bsqyOuXi25qofiUITRI7UChiR0kE5od051PQ+oxv5hycrDqcFxcG77LYb/u7f/Slbr/kpinEYeHz/hN/7/DH/9s//gosX3zCvZug8oxtHPJqTx1OKozM6q3nx9AXffP0NQ7PDdluiT3Q8IshizmK5ZHt3R4g7pMk5OD7HNbdsrkcIcHRyAqZgs7ql263f6CNxzicTvEwUld+WmsYYEnqcN5CInK+//prFYsEH7z1mMq2ZTSqkFMiYpnreecqqZjKpyYymLCuwATcMjCGZkXdtx737D3Ax4gZLZhQvb644Pj6krueU5z0Hjz9hPbaI4JAHDwmH94lmQrSCYnFEJzV//fSWUnvO3vuE4foGlcG0rsjlwNortvN3KMopi5ORcWiQh2dUp8eo7R27y695aiLvvf8RP/7BAU+eX5DpgkqNiKElF3OUf7O5sahMM1tOODxYpLW+EAy2ZbKcM6lyOu8IUTCZzVjMCwojqMqCOpMgPJ3tUDJyfLjgeFIj7ZiKNiWRWYEQCi0VoqgQ8jeN0Ztf3zxHv71VkgjC25eqfIvp/9ZeMfkmRJc04bHpcI0n7Jq0KbV+7+kAQkQG9hI7RyiSpM47hyImqa2WSLnflGZqn0XlMVVOWRcJ5Z9pVCZRBOgtZDIV9TbljMVuTAGhdiSEiAsifT5RILVGOYf0FpxFjBEhNSKMRLvfsEuJCiFBHIiEPHmQCKA7hy4sqjT46PFKEFRgzDVdhKrMqLKU6J7nZp+ZRtp0BMi0wiDBBW42K07KKv1/lUlyq7Xi7mZLWeTYbmC+nPDBhx/xV//pJ1RlTvPLloPTjtODOT/88eecnt/j6ZOnbNsWIwUXr67ou4asKrm5uUQpjSBJvbouyfSIASFNuh9j2j69mbzKPUAmkhonJRVKq1QgBoUSyeRuTE5Acni44LuffcaHH7wDAl68eMnF5TXHB8eoGLm5uEpQlPvnSKXI8oJhcFSFIQw93keid6g8Z9hsyYs8/cCk4m6zZSY9wuRATFkyWU5hMm6ublBuoBKRjIDKFFkY6Z3FDy7ddzJJ9LQQeOeIfWoecSk0Ejego8XaMcldxhEp9nLS4AnBI5zDe5F+v4OoQAYNIiLqHLoR7JiKuVmO2QSqIiPPDTKTiDFBlKQSSBcSknwvBwrDnpanE8VQEDFaoL0gWL8PTE0kuDhY7MVN8tY5T2x7krYvIrz7NvdK3D9/CEIy9n2KXfB+HwJquL65ZLW+Y7Q9L548xfvI7d0l290mxXw0G/KiToZ+n7KmhqFLg6sxIfRtTF7cOIa3VNkiLyAmFDM6IbmlVvhhSAOD4CGkPB4fEnAhBaaCVoLjo0Ourq/xPk32BSINNPfKAedTM6WVZhz6JM3rO4Zo2VxfUuSKew8e8vsfPELlFV+/vqDd023zsmISBWVZEmJgGBIl+O5uzThagt9icoPzA/3Q8+47jzg+mCFkJDNJwjz03Z6oq3nx9Queff2E9bblow8+4OBgwctXFxRlRgiRECTeRS5vVvz93/0Dr15dpI2GEvSdxWQZ09kU7yyXF1fc3d3RNgPeOhaLQ2RVYDNBf9uwqAu28wRbqkpDOStpncUIRW8t5k18hpC4MeKtpypy6qpIP2MpQMQENdg1mEzR9Y7MBoZhpB16Xl9eMZsv8cHy5Ouv8TY1YrD3AQtB8PuxpJBJpbAPDI77bbsUAqkMRVljspK/+7t/IM9zsh8aTJ5hhGA2r1FmD/XRGqMznN+HlyPx1nJ58YJqWpEZw6uvnhCvbjhaHhKjJfQB0Y4gAwezA4TQ5GXOzd2GVy+fcXN5ATEQhGQ+nyTSYtcyOof3e6m+0kzqmsPDBdPJBG1SwLe1Fq0zROjJs4phGKmnM6azJdvtGjsmIBtAINB0Pf/4s59jx0TiK4qCdtckymmMqL1K7Hd1fbubJdLDEKJMH07UeMlvMJkkJ4z10HvoXWBiNEoknbbDM4wOI5MZUAhBnucEb7FRoEyGb3pWzY7RwcPTI86Pj2j6kX5wTIsJs+mExm8JTtAOiq0NCK/ZrDwmlwxKoqqKXkpWXY8NqXjSRhGFw0dJkBk77xn3uNnoBKNQuKh4950H/Js/+wsm+Zx1YRiCQwmBi+mGV0Nk6BuEtwQJY5aBmeKE4sHZI07nC7abLTdPn+GGNcFafv7lr7l6/hXr65f4oaOpGmReMDt/h8nJI2bvf8T06AC7bojhGf31K5QCqXQKiMQxXZyyWCy5urhA5DmyuyMrZkwPT2BS4L2j2W6IpuD4/CFFWfH8q47o0ks5imQKjj4g9qS8tK1IXg0h9jpnkQyXm82KX/7qKz759DsczKdkWSQrSrTOwUNuUl6F1pq6LokhMIwWIw2HRye0wy+QWcbV3Yp2yDh8GDktCu6fn2OUAmF41Y5kp++gNysOHn3IHRlR52QiZ2x6pFbUiwnbpgNVEodIqTWhu0U6yb2DOVdWU5QnPJgo3l0UhLHlq+cv2a4H3nn8kPXLX3G3uuCXv5KcPrxPKA0n947RdPhtwUk9Z7tbI4IgBk9RG07OD1jOJ3S7HU3fM62nkBnuNisoMoTOybSiLjN0tCxrg5aBu3WHcJ7z5ZxJpsklmCLHh0Ce5wmh70Oaxshkf5d7XFaM4b/wIoUQEVL+1l5JJB/+b4V4fluv2PdInUMAkWvCaps2mrsmyRVJxXChFC5EtBYJc7/Xp8cYU4iwTvkaKk9+IRkiYgiIPIAIKJVRaElpNFKAKg0i+PSP1kRvCZsdcRygb2B0xGHE92kDFJXERwjaMDY7gk2bBzGOqFoT7Uhse1Rd40Ii8uEHkAUiOIgO+h5ZTmB0BOfTZktK2jxj1aesl8U8NTxZWSRyndKIAEWmUzEeArnW2G3DiOem23BWGaztkVUFREbnkg9BRJwNPHznHmcPTnj+5Dnr1YbdesPTZsfB4QGff/YBjx/fY3234We/+CUvXrzg8uqS2fKAoeuwzhP8+FZylzZ9aQympQIUxhhGG95uOq11bzeeUmhMViUaIDkCwWQyo65qPnr/Pb7/+Yec3bvH3c0t33z1nBAchwcHSKXYbjbcOzvj9OyI3bbd+zwGsrrAth3jekOUGeVswtC2IAT5tCKrctxoGfueWBl0VWKUTA2KVGgVmc0rrle36G4krzRxGJExYKxN0jyRpOOxa1GjIziXCHaENEVVAqIlDkkmGkIaAtoI0kWEUGnDZBPAIQ5jUk1URQpVbtMmScqUTahChLJA9ZblYkpR5Ui3n2QNLm1Li9QkCyPBDUnurjyuG1BvAnGVIBNJMqoArSAGSwwjbrtGjT1CqDQhl7yFV6C/vQfJ+u4OZx2RlEFjtCF6j9IKJQWTyYR6UjGZ1hRFSVForq4N22aL93tZeoz4MCCQDGMHJPlaxO8BSRKpIwFJ2zZIMUmncYhYn/xrox2T2sYlXLizyb8rQqpvsjwVy6fHJ5yenfAnf/pnyVcs9X64kDYYUqbBc5ZlKCnQVmKEgXHHbmi4fv6KsNswbDfYKDkwmldZTlnNkpLEOd55/B7T+Qwl4frqhoODA6RU3Nxc473n7N4Z3/nscx4+OKcqEmhAapGIcDHiXZJ8bncNLy9u2I6B6/WGw6KidZHb1Y5js0RLzXa344tf/oqf/+xn9H1Pvt9MNbsdUkqqskBrxdXlNXe3G9Z3a5pmJM8Mfdcy9JZx1VBkmrKaMpk0TGczYnRY5zF6nxG5l4yF/edcVRln5yeI/X9Dij06TAiUTFmFo7UoqRmdR4ypTm27ESEVSsK425LnGc57tNY4a1ksF2w2W8ZhBN5I4yNFWbGYH1IvD1kuFszmS97/+BPmk5rToxNOjpf4EGh2DbkxmFwjZUm23y4JLVFBIxD0Y+Dm9o6Xz59Q1hV9P5JNliwevp+Cdn3HTD2m0gGZK4p6jqlL7lrL19/ccnN9yWZ1izGS5dEpRZbRDwleNJ8fcLCcslmvGMLAdLZAm4Kj84ecv/OYWVUxjB6dK4rilq7p6LqBMq9RypBl+b4xTMsOQcBZy26zQwrFbrN9mwWmlUZqwbDZIPXvrqX5VjdLQrzRnytGF+gGh93rFjOjiQEcgjZAYwO7dmATOqrcJNmJSDIwuZfwOefoxyFNx5TBDSNaaoQyrNqO6XrL0XLK8dGClxc3bHY7lvMZ27Hn5rajGwPbIRFDpkXGOIITgl5ErpuBIDOMkGQyQyvQGqRUWKloJXgRmBYlEkE3BJySVMsl7376ES/+7E8QjUCXJ4R8gjIGOe7w/Sa9QHWVUL9jy6gKxGTKa6fpKLgce9zJB2R+RNgev71mtb1ELR+hbYtzgaP7j3jnu59z/zuf8fLJS66fveQfvvglVxevYX6EjwlvK01OZQzL01O2XjF5/4j+6gnSbjBVgZCCIAwfff4jLl4+Iy8LqnrC6uYqTWTd+JZAmFb0b3xm+1/TJ5vKcZklr73SeBcYBstmteXq6pJ7Z4eMw0hWVPvtVNIOSCWxzhJEOrAjgc1uRduNBBQ36w3bIeODAFbA8XxBpjQv73bMpjXz8wcs7p0yiIJu1SGI2K6nXs5o+5apdmSVZHO7RRQGU+bIwfHDdx+RK0nhI8W2Y2h2FCcTTqYHnE8XfPn0mi9fPOd49g6LumS0lnboKbMC4yxtP1DNZjgtQWTMy4rdqiWrC1CKIAJi37COo6NvLWVd45QgrwsOZyXLaUlBRl1ods2GTCsyWXFQ12jhwTuCUiiVssje0I9C9G9x7r99vZkyvs1RevMBCZkkN2+kAt/2bkmkQk6KiPchGd67dp8v42BIZ4KWSXuttUqyNy1gGNOD7B0y6uQNiTbR5zKF2EtaRJ4ajcPFJG1pdCQMPSoKyDWit2kr1LXEm2Y/7U8FsggxBeGSXr5+9CAMPkiUkYlINTiEBIUnOodAouKIUqDxBDfiswmmH9EhJC+TFpBLpAp0nUVWE4SIaTNZG/IyhUBGG8AHMq3ofDIW56VinhleR3ixWnHv3imZi+w2O8R8gkayW3fMDyd0nSUvPctlxey7H3N1uWKzWdM3PV3XM/Y9y/mUMst4990H/Oj7n/FXf/03/OVf/Q3z6Zy7zRqCwMdIDBalFSLkSCQ+DsSQDL5xL7MWe1lX2Mv1vHNpKgsUZclsMuXDj7/Ddz//mB98/3OqMuf26prr61smk4z5/JC8mpDnFfdOj8iyjO2moW9HhBQIJO16i2s6xGgplgUSyfb6lqwqyYqMIjdsdj231zfIaYEyOSY3iOBSoyACudEErWmVYRY82o2EfgA7JF+QltD2abs0DineQkLEEaJLlEMt9pqdgMxkIjGG1FDLbkihmuOAI4KEzHr8tkERUZlOX680eA9GIryjrDJms4o4WmI0CKWRVZ7+e1JAqRA+JkP6MBBEAGeJco8jR5AVhviG7MX+nBj6VJDLmM72Ik/RBeOADB7xLfYsNbstMUaMKchNQZZlDGOLMZqiyFguluR5xmKxoJ7UjGPPdrfhdnWThlRaJF+iTdtpozR92+yZGBIl9iS1KBBCEYJLmW0hS1uIfZB2isSKb9UbkYhS6m2dlBc5427k5evXfPXN16npJh3h3gWkSsPc5AdSKJXiPwiOMkhkHxL4oWnBjnhrUfMlwWkWkzk+yxljpBRyn80XuXfvjNl0yur2huV8Tm8tw2A5Pznl8eNHzCcl3XrNRdtQTafMlzOyIqM6KgkxUnc9bWsJTy/IJ1OmswXnDw6ppzXD6PnmxUt+/vNf8OrVC6KPe9muYhgGhJIYrRn7geura9q2pWk7+sHiXUfUgqZp0EYTphl9jKhc8+DBPZQx7Hbb9P2MQWqNCwGTGYZ+xEiJyhUnJwcslzOM+o1IPeX9RJwP+0wxTxwFznrqsuLw6JgQLLerG5RWZEWODqlJHUdF1/X7rKfsrRpHCJEgGJOajz/5lOOTYz797DMePrjH/eNDtFJ0w0CZZ2/ljzpL7/sY07nzxi8eYmQcHav1Jm0RR8u0yigP5giT4Xc7ynLG0A1IZahnZUqH0Arv1/ihZWh3DLZhMr/HfDZhOq8IK09RlDx6eMbq7hVlVRMRjM7x4NFjvvv5d5geHVMXhr53NP1A23vGYKhmAZMb+tHRD2mrlGoURYy/OUuKIk/yy2GgmiQLRvI0GcbfYbD1t7pZipG306wgFEPw2CiR0tAMHuuhcY5V2yO0IgqJR9F1nrow5DKn1mmKnqI3BMEmCZgLlpRabSi8QylDFMnvcW85xQjB3XqLFoH3z04xWUdnrzEm42bTYJ1lOp9QnC6w3cDWeoSFUgkg3bhKZgQhaIYRn2dkxiC1JKsMmMAYAQQffPwBk4ND/sN/+Fu++PqCaHJUPqXQFUNfEFCQC2LbAIEoAqMP2G3DatWgdY6qMlQmkLpAuIxiLKh0zThOKOsJJ598SqgmbDYdrt3xk//471n1AldOKKcVbndFaSqyecbs8Jht5+i6hrC+pdKasw8+Jcs0fdtycnLKfDZluVxycfma3WaTyCgigpRIkQ7iPCvoO0vYS4VijEQhESpD6jy9FNxIbgrG0aGE58H5Kc46Li9XHBwf4kJAqoDSiiIv8DH93bumITiH0prpfMZ0uiCQkZcV3/+97yNkTDrePd0tyw3ni5woIMsOWO8Gpkay2m7YjpbZrKJrt8zrEqOgVpLVXUtmJEenx7RRcrke8EQOqoJeC37xzTP8YsrxwZLjsyWv+4FrJ3hy2zGtcw5EQZHXBNmzyJKe/Hq15WA+w0ZHPs/Jcs1gB3Q2QeczQutYrUdkJvBSUBQ5SsFiViCjxyjYbLf4EBDBcbiY7bcaaW0vpETl6ecAaToWQppovQnUg72M6U2ekuBtwRMRexJZ2q4klOnvTif8/4srhhEfWyIVIpD8MEOfspO8S1I8IRG5Rqs0OWd0RJmCZn3XobVEZxlaS2RdIqLbf3eFDJ4YwQ+e0hQYDfQWGSVkBoiIMoO2IQ4OXArEdc6nPJuYzNbCRYJKWVfD6OhDoFQ5KpNI71OwqxTgbEKyVgY5dLj1GjGdQt8RiPibO3RVIGclsh/o65qYVywPZxRFyWRakOcZUim01ozDACGkzDopGLuBoipYLCdMn2n+8cnXfPz+I2Z1Qdg1dHdbZF4ggDtryfOMjYAi15Rlxr37R8yWE3zf09vAzfUtQ9OxPJijjeLTTx/z0UeP+f0ff58/+7f/geu7O375q6+5vbtlHAeUgLBvgqzL8M7uTdVFGrbsp7BZVuKVIs8nKCV4/M4jPvrwfd579x3Oz894+PABIXhub26RUnF+dsRsMWM6n6OkpK4nOJdCRK1L+UyZMQxNh+86gh2Y1gV5rul3HT5E6oMZeZ0zjslD0nQN01zst5CBwuQIGfE+BT5OpjUxM9jVJcr71Dj0HXHdo+ReCtX1SBUwUeJEkkKGkDw+MYoE+2gCMQjGGDCjJVqL9IFgHXq/nU/PbkD2FiZpyhydQ1j/9hmO1iKEoCoyBJqoDfqN36vIUGIvbBeeUBlcP6R35v5sj1Gkbco+oDVE8fa+Cc6j9wVlrAx4C/vA1RgTqvzbemV5hVCSSblAmQyJR0jItCY3Jg1dEbTbls1qxWa9xtsUxCyROOtxbk83DDGFbXqfJuX7IjXJotM2P4REZPMhYEdLWRYEAnlh2G4HpCCRDGUKMxWkJmq72aSwWOdp227/vdMzLsQemBDT+S+lSudOBCUUY79DjSM6wt22hbog3K4pVYGZHSCjYvTJk9d0HdftBX2zpKwKFrOa+eOHTKdTjMno2o7d3ZbQdIyjR2QZFxeX1IsZm+MFR/dOWBwuMbmhLDI+/PAhZ+en7NqWu9sNPnhevbrk66++5vWLV8QQUUrj/Ih3ke22QQpBVZU0TUvf9tT1hO1uR98PDONIEvqDtSMueFrnU27T/TPGcUigpG867lY7jo4We1CGRilP1/YEo6knNfP5jHpS/5b0N90TMUZCFNzeNQzWI6Xi6HBGXmU8evwO11eX1HlN4wJkgtwYnHPkeYn3PtEE914jARhtKMuaGCLf/PpLjg8OkzwyBKSSzBdTij5L+aM6Q+ASUGa/hY8x+fadD4QA26bj+bOnxOgTCAaBlIHFTCEmE+qqIEZB36WBjVApQyuuHApHkWnidME7Dx9xdnpE0/ZpWKAzbq9esN7cIZTi6OiYxfKI05MzJrMJxhguVzva7cjmbkvf9XggCrVH63v6rtsPYffDFinwAZTRZGVGlJCVOZnRrG5vKaskcx7a7nf2jH+rm6W3U+0IRkm08InrLwSZSetjhMLnYIm4GMiNgRjIlCCTYKQgBPao1BTOKYVicH4fdisoioLVZou3PV0nuXd0yNF8Dt4zhtRc/cGHD5HK88uLNYqMKCVFDiHPsCHig01GVmfpRk+RZTipkqk8MwidpvVKS1wMRJWwudE6yqzg5PSUf/LP/yva8Je8bka8DBiRMeicIEmeC6NR2RylMnw/4PsmebFsQPsJzjkqKcjbDXF7xdoNVA8+pXjnA+RiwdBs+PrpN/z6yy9YrdfE6RnZ7Ij5ck779JaHDx9QlBMubjeMg8X3LctZwaPzY3zbc3yyJARLs9lSVQV+GNjdrbE+meSLqmLoGsyezNP3ffKPvfFVRJBSU00WSJ3S6nEjox1wPlCUFc47Vus78lxTz6ZsthsOD44YhpHppCKGgPVJTmZyRZWbtNoXgdxEtAocH0zQQpArtc9mkWjv+fjBKZN6gwwSeVgTYuD5peDZBShTIe2CTEaWs4qMwKLI6LohFUIyUlYpNyTzA8fTnG0maaPhb76+YDuOjEJjqoqh6TFB0QXDq13DySQnukjsB+YHh4x9T1nmTCepsJ7VBTpXdOOArEvurtaUGBbzKiGpg0NJQZUbKiUQWrFptuRZlmQ9WmO0Ti/NfbbHm9yGN9u9N/KL374SmfA3fqU3GQZSiP3LSb2Fp3ybLylAaAMqIEgob2E0tCPC7ol/OhUVMtNpSlMXCBL6WziPnqSUc5ErFA7wRG3w6x5Rlcgiw0wSvltuGyCFczoZ0AV4l8IoUyeqCcK9DewMuSEYje2Trl0Olugjo84pcg1Duz9bPFEAdZGkM6SiJ5h9KOndHXIyIcokgZJagBSMXiKnJQKY1Bl5YdDG4F0KNO4G+5vmOEboOvS8JKs0i7zg8vKCVxevOPjB5xQh0Ny2jM4SN46izBn7kUVhWN81iXaFoMozdF0yOMtkUtK2PUObNg/aFJhM8uHjx/g/8tys7/jD3/sRXzx9xsWrSwSB2XRKP/R47/j6q694/uwZDx4+IssMo3WM/cBkMiFGz2K5ZFrX/PH/8o85Pz/l3r0zRPT0Xc9u27CcTZjOp8wXy7dSXu99ymwbLevVlnG0iCxj2w4IG4kDFHlJtVygjOLy2XOqxZSsyPZgB5tCPrctxdkhUkt0lsAgWWbe5o7MljN26w0iHuJetWihEUWO3rW43iLcgGwaxLTGq4AehuQFCPsg2b3WTRYFnfeIILBtjw7pHeJMluR6zibiqE4ZWnF0KRg5yxLSOQik93ifzP6Z1sijZUJOb7fQuSQbVRKsReQG1fZoJQlhr7nzAT2fokaHHyyomJDjREI/pq9VGmkMEIhjmwKgpdwHiH57zxLrRrTI6McexgYRPc6OjADVlF42LJcLJnnO8ugeF1clm3aH95BlOXmWJwgJkfAWdx8wWcloB/Iy4/d//D26tuOv/vPfvW1siInw6FyS6gURcT5JUOMeR58XBX7fII17IETwnhgceV4k7421e+/PbxQfzrm93yxtt23XYXzKAmqcpXBFQk1PHaGUUGTkKHLt8dsNcnD4zYbLp88R52csDuYsl3PyokSEQL9YYvsR23VoYzifvEMxqXAhMA49XdcSRQkxMLrA6CzrTct6vePli+e8evUCvYc6IQS7piHLc7bbLYeHR0gRadqG29tbvA1kWUFZFHh3lWiaUTH0jrLwtE1L8D59BkrT2x31bMYwuiSF3A8Kg0/SSCklxqQspNFa+mFIcjDkfqiYJAVZlrPetYSYyII2rqjLHFPUTGZLml2LVAYtItVsTqYNm82GsqjoujaBDpwjM6m2MHlBWdYYpXn5/Dn1fIobLVJpyrKgKnK0ShE6Wu9z1WLc02wThMUD4+i5uL7j7m6FdZa2bWiahukkS35wAlVZpLMgU/TdiHOwWu24vevYbBuMMTz+4BPOz89wPtJ3ju1qzdB1XO6uGMeOk/NHHB8dMF8eUsymOO8Jfc/t1Yr1ZsRZy/rimhAj1o5JbSUcu80W6weU0sQ91MJkyQuYtqECJRRNs6PZbaknFVIloMbv6vr2N0sxdd1KRGZVjoiBPjiQBiUluTEUPkmQJBIlAkapJKkhooRARIkPfl80Cjof6JyFEBjDmPJ6MkXTdjiTkW1bjmY1h4sZr29uk95bDvzhR49QPONLdUNvQUvNxXaL1IpRhIRfReD6Mflp8opIWhPneUFmFEIK+jEZ+5Eqpby7RJGrq5zf//H3+fP//BMGncJGJ/IY23Z02y2iMsS+JfYd0fYIBdHoxL23Bj9auvaarLmm6XfMH36OWJ6z2TYMd9fcPP81zXaNyidIs6BaHoKMuHbNux98TFUX7HY7yjpjQCAU3Dub4Ycds/mcPM+YTeYMdcXd9Q0yQt+3zA8OUlZMcElTb+0+8TzsfTDpYBdSUtQTXBRkyjB0O6osp21WgKIsK56/fMnY7Dg+PcLk+R4+EJIBsG2QCqqqou06DmcT8iwBP0T0/Is/+iGbbsdMB5bTOSpEFpOCIiswQnNclNTKo6NkUZYMYeSsFHzn4QP+4devmE8OGO3AJM9YHiePy9XNLdY7Zrlm3GdoHE4OWU4LrAg8eblGCM0sWHbbBiQsJjXtPsB2OpEUecakzKlmM7brFS4MOCEROiaSmVHoIk85AoNjcrQg0xkbN1KUGevVDdebCbmZ883zF5RlyWJao4mUeZZyLoLHAXmWisG2bamq6i1dB5IR+E0DlXTuYf/7cj/J3BN53v7e3gws5f/8A/otueQeMS+CRyiDyA2CHO52iAh5VSEnFSLLUVVB3G6JxuDHHuUsel6SlzmmLjBKIlRI4IuQpFQSgZ7UaROYSWKwMA4EkSh6AVJxKzUx7mWPUuGNwXqBqyucEgy7OzQ5VnmiSRup/GCO3kTi2GOtAm9TSK70yLpA1TVEj2g7pLdEO0BmCEIQdx3x5BDmS4q8YDGbU5QlUsoE/ZBgcWT7bBylJFmukSpJf6rDOdokT+Avnjzj488/ZXp6gJWSNkpGF6HIkAp2q91byW1eFJhMMdq0Yc9zRV5kjEXOZrfDOs90kmFHxaeffcCmabm8fM3pvSOubzeM3nN3c8M4Wg4PFhwtF9hh4L/+F/+MCFxf3nC32jCbzzg9PERlmu9+7zM++ug9lsspUgp224Y8z8gyTVmV1PUEBCgp8T7ghaLrWla3G5pmZK/yxWiTprMCZrMJVVkwNC3jMLCcnhIF2D4Zyq0dic6RmxTXrZRIxZRMU+TgPdNJmhQHIZDTOSHEJF/TEuFGdAzJR5dpcD2UOSGM0KctsNAgpEIUGaKawO0KoksbySAIxhDzHKHkftvjCUiC0sT9xgFtkGNI5V2ImCJL8x+xDxJXGpFLRCYQDqQxRC1QZYEeR3yTMPKx98jBoasKnYGXgFREN+L8LsFP8gw5m0K3I0aLEBFPRChF6Pr/fx0B/19f3g0YbXC2J8syEm1dkRvDfLZgMZ1xcHTM4XJGUWu6sU3FbVXRDS2IQD/0SKlIzjOBNlki3Zqc2XzBxx99yM3NDT/5x18gRwkIrPUEoOs68rxgsP2efpdk1HHvX8nyPEEhygIhQMm0Nc7znPVmvZdhswfZ7ME+IhGFtVZUJsONNc3VhjFAIRQOhZeGdTuQzyWFyVkulhgF8uwMawPdZk07tLR3G+azGW7wHMzSQCHTCsQEY3TaGkhJUeUJyKLSfR2RNNsNm01P03m26xVff/UFl68vKcqKqqywdsSHgDGK1d2K6XTKYrkg2JF+HOj6kehFqr188jIrnRODo6wSLKue1CBgcJ6m61Da0HZ92vIF2O76vcwyRxtPVWSYTKN1qt+U1HuQTxoppmYzKTayLKPZdYAgaEFLRGvNdLrkJr8iMhI8tLsGn+cUZcnoPCYv8D4NrIKLxKhQwoCPmMJg3chuvaLSmqvLKyZ1yfHhkrLIqEqzf6+nwWbY/72tS5Co4CJXV7cMXYdSCmdH7DiwXCzQiX++z93yCAL9rmd13SBkoM5LPv3kO7z3eEAVKVfsyTcvuL64ZLdeA46ynnF4cML86ACTCx49fsToHT//9a+4f/aQTEv6tqHfdVy/ep2aSwE6kxgT6ZsWLxxFKYkibTiVMsQ98CLPUuuSl0nBkOcZOz8m1cfv6PpWN0sp3Czsb9K0VJ1WBXQjdk+6C1JgCo3vXUpLV2qfKh1TEyJTg+KsR0iFC5beBYYACoEW0DUd0/kEHyKr3YDKLaVzzDLF6cEBt+sdt9uWg0XFH37wEKkjX7xc0/SBKsvIdU7IKjY360TSkjXReW7bllLP8DYhiKWM9COUdYUNnmEcUDHd8MGNRD9ydjznn//hD/nbf/gFvVLo4oAi7xg3t9CuUN4y2CGZiMuSqDOyKtFljIkIN7Bb32IOzxlFRmi3BBfZNht6G/D5FDU5ptYCZXuOF3PqxQy6jrubHdPFku3qhjhuyXHs7iyzuiSIwHRScTibQl3R3K349Vdfcf7gASbLGPsGP7YQ0+RSSpnIMVGD8EAypB4cHnK7aQnRo7OMLC+gFeRZhlIa7x33HzxgtpgSSfKmvmuT30YI+q7DB08UkhgcWmU4b5lkikdHM55ftDxYTjiaz2jbjkWV1tSikCBH7i8qdtsG6xtcb8mIWFoen5Zc73qGMU2BMhnpxo7zkwVRGcZuQEaLljlBCC52W8bBEnJBpTJETP6ArvfMZcGsENw/njGrMxgHcI6oJJNpiZyXSZaiBdJoZGZwkT0FLZLngpgZlJMYoTg/OqS3A683t6g6pXcXeU4WPZnWiJh+tkKnwlyIRCn6beod7H1k6XZ76yl7g52Ve1rk/9xR9O0Vz6QrKJH8j1lG2vg4VFmk6blS5A/OUdMpxTv3sBfXuNwQmpbQelSMyDxHzytkBIxEakWUQBQoU7z9vuyJbezhJdGYvSdPQZ4R2x6PIohkBu6lpvUDY7vDu0B0Hi2T6X/YNQQpcFJhlE5+ESKqKvAuoonoKFCFSRsyowGPDCBj2m6YRcatBTGZUhcFhRYpS8qYt5+93m8kQxrmIZUktCMxN2STivn5Ad9Vn/Gn//7f0zQdy0nJ8uyAzAt2u46hHagXU7rNjr4dkUqTF23yfQnBdtPirScrc4xSzJdz+q5nvdqSaU1W5kxnBWVhePn8gvl7C9abLc3dLc9fvkRJzc3NCu8cT569ZOhanPUsl0s++fA9Do8Omc7mPHx4j6oqUlEwjEQfqKqCoqyw1tG1Fq0FUScpTbPtWa8ads1A142URUGZaXQIbHaeyXJGtZjg3cjudkVeFmRFtofgCUxhkEpR5Bn3zk7JixIp9X44B9oYnIBc5sxngvUwoo5O8NYjux3EJFfG+UT6kwomFWLbEo1MTRCRICRCK4TShKrEvb6kynKCTN7Nvu8Rux31tELoJAkNxuADuCDIdAYmI9gBIdIAKwqQdYGZFITeJlmjDsiqQIwuESEFKeC2KNMm1I/YMSTPktGYk4O0pVsu8Ks7+ssrfN8mCmxwCDcCyW8ntCJY962maiqjiUJiTEZmSoJ0CCKLyZzZ/Ij5rGI6nWCKjBgD9WSCUGk7NAwDLgS0hiyX2HFMAymV8iOlUKzXW/5f/+bf0zYNZTlhPd7g3T43TEsimtG6tPlwEYQgyzIODpY8fPRoH9URmE5qbm9vefrkKaNN3pDkTdII/YaGlwjDIYJAUhQVrmmJPm1dVl0HwuPbltPlCTuvwAnee3if5dkpMsJutaWYlGw2O8ZxZDafcni4xARo1y0hRHa7hs2uBQmXl9dkmeH4ZInWhsXBjMOjg7SdbXruVlt+9cWvuby8AKUoyhohYLW6A1Jz0vbtW6/W9dUVZZEzjhY7Jupa2lwklUU+T5Lfw4MlWVFyfHKMyXPafscwWJxzdF3yZlnncQ4EgeAdxLR5FySIg9Ga2bRKzSlxn42U6pHMaBbLBcPgGMeRADSbBhEiZW6Yz0pePb8lhOQVDdbjRotSGdb7tFmJHmsdUmjapmVQgq5vKcqSh+885nq1Int9RWYM3nsKYyjKjNOjJVpJrHP4IPYgjz0sIUZ++eUvCcElMt1o+duf/JTz83OMkhSZQZkUXO4t3F5vODpeMD+Y4GPkdLuj7zvuNhuev7hmdbfi6uI5znqyXHJ6esRn3/ks1YQnc4IKPH31mmlWUhrJuh1Yv3rF7q6hvb1J1OPcEAdwWboPtVFIlaBrRkqkUvv6Bar9JsmNFn24TJvRjd8TBH8317e6WUo6zBR4mjREASUU8yqnG0eaMWEnVYzkOhWWUibd9httuwshSQCkYOwtLgQG52mtJ5NQ5QY/Dmy2u3TDCcXz6xui7akfnFEWBSdCs2paumZgXkt++O47DMMTvtmMZEGCi5ArZosJYzdCbnCDw3vYdD21qtCpX8CJlOeSJkGRfrR4IQlRUmQ5SMV8WvD7P/qYL379AiYLvnqyRU1rpA7IrqWezgkuMArBGCGMjkmuCGGgdx5z+B5UU6ztCW1OsTgkm0wIzYSsnKBFJPeB9z/+gHdP51xdveTFq5FsvuT27gb6jrPFguXBgmKSIQksy5yDWY2KnrvVirZpOLt3RlZk3Fxdk2nJ1o5p7hJiki8JiTIZzqYJo9Kai4vXyKxkvjxIoXqD3b80krFeSMHx6RFllUynuc5S8wsMzpLlOaPtiYBzmhCzNBFXmrNlxfXVa2ZFTmlAlYqj2YRt00Amkhl6cGTLKXYYEUVFmXu+ef2SUgfO5xVVVTGOQ5IQzubcrFu80IzCMSklizLDWRhdTtd2ZBiqUjE4yPM5G9lS6Ixhs2Fsd2ycZlqVWCJ1kSO9R4iAlAaVZegyI2hN0BItNXKwTMoMKRVjsJgw8OBwyjv3DvCuwYqQQvt2W6pptTe7p3v9jazutyV4/5NrP02UQr4FO8R9IO24N1xmmXlrOpUI/Oj+p9/nW3TJfWCgCAGZJYiCGHq0FMQiJz85IqpUSJMZsuMlQ9fu8f0GlSskgBKoKodMIkZHDILYjgilkC7go0dPDK5QhCYQrUNUhiATgdBLhbeeEehtoPORzbpJmnocMkjyucLGFPPs2h6/Hz4IkdDgOs/RJqD2WzDlPdQTYtchSE2Q0oqs0qhlDUypJnWiIyqdzNyk7YrcU+dS9laacEqj6ZsBGSLSKIqjGXWzBSV5fX3DwfkBRVVglKaoc14+uWJ3tWF5MmdoeqT3dLsOJSTzw7SZuVzfcXu9oZ7XTCY5eZYRbWS73VHWJfN8wtHREVlWsL5bcTCrOTk+5vzBfWKAF8+fYZTm5OSM5bTk7OyE6WKOt46T40MOj5bkWiOtoxsHtFHUVYnOc7bbjnaXzNRHxwukFKw2O26vV7jBo4SgECn+YTat6OzI8mxJPSlSzpUNrG9uOXrnPIVg75837yyCiNKRxWKa/oz0bBmpEVKkoEabgstzkzDu2fER7sKjTk8J/YAKgiAgFiVCC0TTk7IKNG6wCB8h0+lzvlvhhgFR1QhncX2Sy2gtcW2DOjpI6oogyaQBNEEopI9gDHQ2FYSjQ0x0Kvq838fnBaJzoCUipjwu4QOiHdIZNYLIAqjkg5JlicwNIgaqRw9w1iEbA+sVcuxAJ/iJB4TW+4Dyb68MTyiJMoJqMkvntIBxHCinU4SWyUPsAs+ePWM2nfD65pLrqxtGm4J5lcnI8vztFkDEmJpkbZAq+UQvbjeMXUuWaaRSWD8m3zZJiu19apKKquTo8IB79+7x3nvv0DQtd6s1T58+48mTJ2zWG7q22WPEUxFtTEaW5fR9jzGacRySLHc6oVCK6fExt1KwanZscXTesd40hCkczQ4JPtKvt4SDA47un3Lv/IRhtCwWc7arHd552lWLnpVkWQlCsd0NfPHLr7F2xJgMpSWb9ZaiLBmsZRhHlDRcX9/yjz/9WZKhZQXbtmV9t9pDHHrcOKKMxnlHXVVIKZlMJiitiOst221DXUt2TcvJyTGz+RxrLacnJ0gpOTg6RGrFrmlRWrHdtAQf0FoSUXTDyIyI85FdOxIDzGaKstx7JPcQKqnU2wFTdMkb1PQjk7rkRYxkZcF6s92/OiXWO6xXIBSTTPL+8RFr63l28Srls2UmDSJCJEaHDxHvI8O+KfPW89Of/ITPvvc9tqsbritFBJazKWIdGfuRo8MDpAKlkmzQWofzgvWmZRg98/kSEHg3slrd8friloP5DCUVRWmQxqCk5pPvPk4xEkLS7KmfzgXs6Fld3fLy6VO2u2tm8xN++MPf4weffcjjRw+QErq+Z9VsKUWGnnhC32G7jn63o13d0TV3hADVdIrKFUZoijJHqEiZl5T1hKqqsNYyjmOSvztPlmXkpcaLnLHruQqeLM9+Z8/4t7pZEgikVHtDIqS1RdKdllmakK52LSATESbuA71c2N+Ae3ZJCAw+5Vb4GPEB/F4aobRGKWjans4LrAvkuqQbE0AilwGTwUKVNJ1gu+uopzN+/+NHlE9e8cVFy6gjwUXyOqPbTz+m8wnbbcd2sORS4KROZvoQyYVi7Ee0UmBKdl2bTKPxzXhX4ETk4GTGxatLHi7nXErB2E+IuzVht0WLCMGhBWQC7HrNOGyxMWJmU6I0GK0ReFS06GJKJSVBKVhd8P7HH/DBg0Oev76iUBPqasuu3VDWGfmiZjGdUhUlwY8sZ1MOq5yu3XG9umW9XrM8OqRtm+Qb8xbhPe89fofbi5dAxO/zgURMGSjsNasRSV1MCN5TVBM6m/S7RVZS1xWz2RRlQKpIlmlyo/YyPFIydowoBcpkBBfQWU5wIQUzmpS31Y2WzI4URSoU6qyg79bgPLU09D6Q5QVaKIRreOf0iJvtjiAUmQZnJFulGVAM1rDa7MBH2k5jfM/hwYy7XZJULKoShEWZjN5GjiYZOZEhGsaQqEXWj0gpGb2nNBId0yZNKkEQkj54XNuhtMSUOUM3oIA8F3g8np6hW3PvYIITIkkyyillnkyPUuu9pAGM+S8f+TcNk1IK732S4uyNxJAmdsOQNpXdYFNmxjhSlDm5Ngmh/S2n4cUQCWWOdB5Gj8hSfo+QCjGboPMM13XEvWk4BoHKMkRliWNET1JTKjJFEKlwilrjtw2xs7gAcaKQeQoBDc7tC1FJ9GmaHoWEKIhS42TEo4l4gnfsmi27rqOsKmaLBZlQjK7HDQP95RV5FhHep22NC8i8wEwqdJ7Qz3Hc46O1QWYZsswxRuJlhSrniM6CyMirhN+PgnQWhphy1TKNiGljgkjbqhgiQkmKWUlWGE7un/LFl1/x4YfvIYsIIr3sF0czXv/iKW2MzE5mb03nCIkdHVmhmS8q+t5yc7mi3RVMZwV1nbMoFvRdR9f2zJdzFgcTTCZp2pGjmWY2zbm6uuH9xw+5ub7kw/cf8OH776Jl2rYcLCbU9ZSyKuh2DXZMhmdlMqyHm9d3DN2IlpLZvEJr6IeRcXDJMG8btLfkwVHlZSrqygJhFFqnHJTN5TXaCOYHM6IQeO8oqhpkeg4X0ymL+SxtZveyb+89QibKWNiDH6aLKbbTdNYhVAIrqLpO90XfJzKjzImTGq0Voe9SNsv+6+2uw9o99MEYwpCkg7u+RcTItKpwCLxWxCDxURGVQegcYQR+2xJcwPn9tkJJiAkr7pzDbbbIrsccHxB1Gi4mPZdO22gXEEWeEPdREZxF5ga3WhP38nJT1/i+ZR/IBHIPLlEKjyCqb6+cdxxH6mpOvs8VGvsepTXd0NO2W44Wi+Qp8vuMx75P73exH0RoQ14UtLtd2jRrSWYKhFb0TYMu0uaimC4SmdO5tDVEMww2NQjTitPTUw4PD6iriufPn/Enf/JnNE2Lcx47WnxwECNSG4jxbSaU3AcXz2YzlNbsdluqekKWFxxmink+oVqeIaoJ4dUrJjGitSJO52SnJ7z7yXscHh5ydHRIrjUiBnSAvCzJsxw3uBR1MES6mw5ZGObLJZ9850OGvieQYiym8wlVpciKktF6vvzVr3n5/CV1XWDyjJcvXnN3fUvbtCgtaZqGqiwJziNiZBxGfOlYbzbkmWHoeoLzEME7cM5S5CVZVlDUE/q2pa4q5vMpow9sNw2XV7dopbh3/4S26+m6gbYfU2SLTxLJRFFOEQVXV3eYPGM5nyQcgVCkHAqB0RllEZBKc3u7ASJudLRtz2Q6Jb7waCl5Zz7l//B7P+RPfvFrdn3PerdDINBKYvIKbzMyk0H09H2XaLptS5kbXjz9mjx7n922Zj633K5WGK0JAdabDffvnzGtS6SSqRG2I7d3a+4/eMzy+B7VZM5mdYNSGaXW3DuZUVcTlFJEAkWWtpbDONL3A9Za6jon4rm8vqUfHQcHx9y7f84HH77PH/3wc+Z1iR89DsnQelwXmGY1Q1ToMuPp0yva3Y5haNl1a5TQsPNMsxlSaHJlwEBelJzff0BRlVy8fpWejSiQUaKFYracg5I02y1lVaXBy+/o+lY3S8A+kV2+/TVN9tJkXMfI0bRmN4y0Q6LTBO9S8KSUeJ+IM+nAUgx2JAqVpBLB4kOgbbqU3hyhc+HtOldmGevtDj0rKXONkoFSaPyQghHrwvAHH93naDnlZ09fsO09692Azg3BCKyEkKf09z4GSqWxMaCVTr6gPCcOLsEhhMS3A5VWSV4oJNNqBrpEZxW7mzWZqLlbjXQtZHVJv7pFiiS/isHhVSQqjZkcQDklBEVUMfkulEJPp5RI/GbF4YN7lGXJarWjqiruXl/Tr3YoYH5wgNSGyXSKCpbptGRZF8zLkuV8wsnpMUJIfvnFF2ny4izftA2PHp7z6N4pf/uf/mJvIk5X8An17lz6XIQUKQSvHynqfR0ewLpANanJ8oxJXZLlirooqYqcpu3RRjOMbr8hiORKo3TGODrG0bMbLPUkZwhwdbdG5wqpDM5HlJTM6prNtqHrd+R5Tq4iZZY0yM06UtdFkt8JQYhplb8ZPcwKZnlCtq76gAqSdrMhEDiZ11QmYzmdcbHeIXxPWQroOuaznN2wl7cBzo6EMBK8oJpNE0DBKPpxRAuDzjNidAQck1mVClnrWdQ1QjuudhtOjqdMTclEZwkEIOX+/k46aiHFW2DDG5/Sm2fIe//29/1e6+59Mq86a0m7DLn/c0/fD5haoRD/xff6Nl5BCERMxVqIe6BDbhBlQSwKnEikHr/ZofMCWWTExQzpC/zNTQoR1DIBNVX6GbmhJ1pPcA6yFAjKPhRSakOUySMWncOvdqijI3wUeCHwIYLR+GHHMPQJo7r3dcQiYzCGYRiJwRH7HS7mSB8wkzJNOOsKFd+EtSpiBlIrhFDoPEchsORsnUJ6gckKirpI8IqEPcRZlyQh3ZhemlHshw86ZaAMI8Z5pssZKtOcnp/x87/5e3Z9T1gHsoMZIUJVZSwXM9zlNb4yFIsJRkWqyqA0aKmYTUrcQeDmxuOs5epqoOsrJtOcqqjw0dN1HfWkoCzytLntGtxoOTg85JOPPmS9WrOYTdhttiwPliyns2Qmz1NgtTIm+YhGS7MbaHYtIYAWkTLXzOaTfTGbfH5j8PTBkbUD2nrUdIJTkij2Ms0IDB3ddsfhg3sUk4phtEQv3m4Cbm/vmM8mFEXO2/BQIxEkCqXSCmOyhIZXHkzGKCQsFtiuQ85mCTMvIJQFURtC5pB5ho9gPIxtguSI6AlNC5lJ/o0yI24d0XvG4Ml9Grhwcpj8aj5t+EPvCEHiBo9txrdwkzBaZF3jiIxtR7DJfxFsyuKSVQnsByvWgY/IukRNaoiCfFITBAnz3vfoIsePA7IoUG7AExCZ2UMlHILwrZbhSSUY3EjTbFBSYoeBKi9xfiQGS9N3CKmo6xwfPUcnR1xvblm3O7QpMVlO13dIrcmztAGQWcnYNwRn9xAMTZZVKaMQwegsCo2SgrPzEx4+vM/F69c8e/qU9WaDtRY7jPu6SOwjIzJCdMmOoGT6viFiTEZVT+jalq5rqaoaIRXPnj9j/v6HjHnNbD5jdvh9jh68Q54pskwznVRMq5rT01Pu3TtCCYnrHWNr6TZpuJRPJ0wP5zjr6UeL3g8C0YrDkynDYNGZIssy7Niza1suXt/yy1/+Eu8Dp2cnOG+5vVsRgufFi+eMQ8+9+w9oupa8KChU8mY77xn6kcyUCBTWe8YwYoNFaYnSmqqaoLRkNqvJi5x2GIjAer3h+uqWruvJckXbNQm8IxU6M+RGMZnUzOc1SktAYq2j6S0hJtBYCCGpLkj5ntebLmHDpeH6tkkeqKGnNAofNZPpnNXlKz48POGzz7/HBYovrSOrpmzWt+hMI1WKSbDeYZRhsBY7JkLp1dUVQgrqesJkNqPvWmazKV3X0zQt89mE589f8+7jR9SVRkrFZrfhxcsbnj17TlVWzOZLppMpu11D1JKyqkAmH55zCRYyupTXlWcKbQo2u46bmxXNtuHDD9/j04/f4+hgztnpEUaA7QLd1tHajlxJplXJfDEhKhhswA1fMLYb7taXtN0OIxUierpNUoDpqqCsZ8wODjBFQW8dWV5D6Kgm/x/q/jxW0/Q87wN/z/Ku33bWOqfWruqFS5NNURIlMfJk7MhM5DHhaJwAM8IIE8EwECBwkDgBjDhAHCSQHSdGYAS2Md7iZJyJ6RWB7YwSW7K8yBZJcROXZrPX6q69zn7Ot73Ls80f93uqqYmDIT3DjPsFyO4+p+rUV9/3vs/z3Pd9Xb9rBEixXo5HlHXBql2zcfWqFFM/oOsDXSylgTnih85IjAEFpAFhqlVAIUnrSud0bYvWUehPSaZIMUjgoTYZfdR0A51nlGfoBJFE2wfQOatuSVbYZ36D+WpNZRVlNkEpi1EBTCLGQO+hzHM+enWXq7MJbz894+2DU87XAecivYu4tkNVJWddh3GO3MpBlKJg0TqszeichAKWeUkXeqq6xMaeaA3OGlRmqaqCxbIln4zpq5Kd6YS+a1icn3N2esFqeUG7XoKx5JM9bDWmdWsyIwnr3fExs+mYza0Z1WiTlBzT8Yim88wvLoihZXtni9V8zsXREePpFF9mzLYmTGrNdFKhgbquJBgxRHa2N1kvF7ge8izjwy/d5uMf+TB/5XM569AMn52SbKgoUjuRqQTp4GotyGYMdTUias3N27f41I99ghwlxmgC6+VKDusxEl1PUctCllSg9YG87ViuWmxWsGw9yhbS2Q2B4DPWrmNU5ORasTmZMA4B6fRZ2q6l7wNVZkkDgWVcluLpURF0YLMe07dOshxCYrHuaPqMxgcS0lFdNStGpXTyRmWOqQuapqEGyiKn7QOpHGMJzEb5s9ywZDXeeUqdURgFUZOSJ7OJOstQUVPnGTmK0loMFkXEZIaYIAQ/FGKOBIzGExjMksD7lLvvIt7FcInw1bgQaLoOra00H2xGCI6EHOidD+gsk4nGB/hSw/0jMjtFdEm67hsZdiJBfCFB7Dqy2Qh/cSF5SPr9QN6EBCyHdU+QG3mIIPC4pytsG6nzEiHLWDEBd04gLMaQ5guiEhJm7OVAzLm8xyFGcptjY0I5h1oviV1LpofPrSjQXU/ShmRzdFaStHxdeUdqe9R4RDaqMEWOrmrCleu0nWN7a0ZdF5iqEE+LEWR56D2+D4Q+kExCqyRZPEk60Vy+H3WN1YrNjRknZ6ecLJcEO8OuepRN1EXBzo0dzhcL0mJNGyM2y/G9ox5PMJlIo7d2RuSl5fxiTe8ifdezVpDPNEonXO9Zr1qIEnL66OCEVdOgraZzjqvXb9CuHZNqxNbmjOm4JqXIerUm+IDvPd5HfO+JCQySmzXdGDPbmpKXBd57qiqnW7f03qMXDbrpKEYVPYk2RHzjMSphtIfVivHGmJ3r++RVSe+8wBEGSdnZySm5ku5wipEUFC4GbKZJ6jJ1Xg9SR0vMItpaXFmhJjOCMmRKE20ONickkVt6JdLxlOfggmTxZBZlND5EfNtSljkayK2h7wJt30vApbEEFF4r3GqAfTSe6GTSH0koHyRrJST6+ZL2ZI5NoDKNHnK20rohBU/oHVjQpXSyldGE+RJnLdnGBqkQIAbWYPKxxFs4CaWNwz0Vk8aFRLLZ/x9Xgf/vrqIoUDpiDLi+oygyTG7wBMqyIKhA49bYqPjwcy+wc2WHcjrm3oP7qBjxfQ/GkBelUCh1RmZzkvWQJfKi5sr+DW7fvoM2muPDpyj1AluTinvv3CUS+PrXv0m7XsukPEHwAZtlpKjQViABeZaTyISWmVkUGptZ6qoCDNFHiiIny4TY6Jxj3nvoWi6OezamM25e22f3ygZVaSmrmsm4YnNjg3pcE0OkXTboJM9aO18zGgOuYzSpKFVOikNezwA9qUcFIQZWq4bTswveeuse9+/dZ2tjxv7+Nn3fcXp6Stv2+BBYrpes12u2fWC1XjGdTIl5BJXoO0eXeergQVuRbrUtvnCs1w0Jy2gmlLjeB3rvAMXh8RkXFyuOD0+Zn18w3ZzQdj3aGvzQcDRlLUQVlEzgoxR/b7/zHhsbY164dfXZ/ZCUonOR88Uak2V0IbHsPEWWoWxOFwKFBkJPURS8fXLE6eMD1keHHD89YNlLA9i1LdUoJ2mFWzW0QQq4vhtymLIMt27QvaNdtZwcHxO8Z7axhXees9MLUlLcu/+I69f2GI3Eo3nrxh65jRQ5rJdzinKESklkyY2jLiwgQfQ6iUVi3QlynaToe8fmbMJ0NMK3PXVdMxmPBNTTOnQWKUaRnc19bK7pmo71ak0fAqfnS85Ojjk6ecqquaDpVjiTofKccWZJREajETYrQBlWizVGG4iJ8XjCeFIxmU1RWjObTZg3DefzOX0cmlg/oOsDXSyFgdhxqbu1dpDkJSOHlwRKJZHQidyaGMHgZePRglnWWhODR6WACx5trSQf+4gh0rqO3kdGRY6LniyzMuad1nidiVFWK5KRwi042XBWyzVFXbJRV/zo8zO2xxO+/u59jhYtPmrq2QYEWHQdPYITz3JLSJFqo+b48Ix106K1xcdEkVmarqMuMzKb0TiPLjNS9ORlTtc02Lpk79oeIfYsNseYsoBHjriq6LXCboxIDkprMES8W3NlY8JzUxiVCW0yNrf3OL1YEPqGHPFa6BjY3pyhdzTz+ZzF+Qk6NUzLK5RlSWGNeF0MPH78mKZdkecZx0eHgsAc6FFZlpHWawntBGThEa12SgkVZQoymm6Q0OisIFOarMi4ffM6s0mNifI75xdzMisyvOADdVmggL5p0Smjp2epIuu+J8TE4fExzWqJDpH9nR36vmexmDMqtoRsg6ZMGdbKREYp8ek411FlQg8yJEiJwmhUVdJ3nrzIhglOZGuc03bQeYWxgtr1PsP1np2qpo+Rzmmm+QjlE5k1LNsOH8Aqgw49VT6iMEZCJMc1uVFkRLSWsMKqtORZRt8F8A1Zbtjb3qLIZIGLw2bZO48LHmOMjKiNJQyBhYr0TEInlLL3sxgElTLATwf5njLv0++IQkq6lL7qD7gMDxjMzAMFUIMuShKe5D396Tl2VEEr+FxlFARPchKwrMSkQvSIhK8baGSdp28867MV1gf03i5FPRFapclIsSe5gAqKiCf4iO8kX8OHBu86QgzPIDTaiGzPtw1mIEDqHlTfQWaIbQ9FJfjfEAnKYcYlOkX0qJImUl7gr1whpMTG/g7luJZprLEYK42g6APBefo2kAZ5n2jzFUkpVJHRH5+TbYzJrGF3f5fTtiNqeP3tt/nUj32KbtlSbxSsXGBSZmxe2yGcnuN9JDU9vvUE5yWTJ5Nie3NmqEcli4slfSgYTyoMgXXTYQx0bcfi7IJHjw948vSIb3zjO5wvLigKy+Zkk72rV3j85CHLZs2H7txmtjUl+sB6scRmJUlBWeVkeUaMgdzmVJMKm1tQIuslBNZ9B02HbXpMaYllgbeWziesSVibKAvD4qxj69oe1aQmDBAUazQhBVzf43vHC3duYjNL8Il115PlGnwkY2jAaI21FhcjVucUGxuk+Rz2r8DjCEUJy5UABHpHWjbgO6JS4CSgN3QOgyJTCgP4ZkGvRkQSpc3ofUDHBFwGyTrKbCYI5M4Lct5IER8JKBSxzHFNy/ndJxjnUGWO9uBbhzZBpme9I/kAmGfhuKFvgThkuyBePxcxVY47u0AVBbFrBzpqIGiZyqs8l3yxD+jlnKPMSnwMoBLaylQjRAlGb1PEGsPtF5/jR3/8R9BGcbFYUdUT1utmwIbL9FZAR/tEpRhNx6wWc24+9xIbW5us24bF+Sk7O1sYBXVdMF8uOD87Ba2JiKQaH58R79KAji6LgqqSEHetJQrh0soQiSTf89GPvkRe5jy4/wizbsjzgtPTU7z3rNcrzuoxP7L1Scajmp3dGQqRdq+WC4zRTGcT6rqiHVfMrgS65YrQhQGzHYRiVmYorajynJQSbddxdnbG4eE5r37rNRbzOVevXacsM5zrZN9uO6osp+87QnBolairiuduPUcKka5pBbqg9LBfKbQWv0+WVYSQBjqdoa5ylss1F+crvO+pRolwcMpyseLhg4e4znN8egIpsbWzTVGO2NrZBtOSWzNEnIivc1RV/Pbf+pPs7G4O3t5ASJEYEpuTir0rW3zn3QMeHZzhfYQkShrX9RQYtMlRJPK8YHF4xCifcevGczw5OwESV6/uCVbbe+Z1xen5BX4p0BfvesZVzSt7+1zPC9rekRcl54sVTefY3tzGWMPR0RFd19G7nudv3+Tm1Q0WqxV7WwUv3NqnadeEpDEqsH91n1GRDfmlFpSofrp2TecCXR/wPhJ8xCRNmeXYvKaqJfNIGUXKLWVpyEw1qBMc7arn6f1j+r7j4OSMo8NDFssL+bOJGGOYbmxy/dZ1rl2/yWhcs1ov6Zue2WSDnXHN6Rz0eMxkNmI0GZPnlohi1ThC0mR5RW5+cA2XD3Sx9P6lhgmT4CdTCERlCEEq4/NVjy4ktA0SKgEkCiN+hfNeDpiTsiAlRR+jYMU1ZNpgDVjtqZXFReidI89yGuc4OLsg+sDVjSk6KZTVaCzLi4aQDMfH51zf3aCoFbf3J0yq23zprQe8fbLCtQljS0yMdDEQlcKFSF4UzOdrmtYTMbTOk6ylGFUUVUVZWHbKirXrxaycZ1Rmhe5bVo3C92t0BrlVTEYl5Y1rPJifQ5ETcvHImAAxafZu3+HlF29x+PAuGsfW7h7L1TlZnjNWFevkWKxauj5iVWRUjcg3R5QDyvrBe+9SGtjZ3ebi4pwnTx6hUFzd2+Pk6Jjz81NWq/ngdxCaltIid7Jao7RBq4w+tqLRzSQYtqhHgKKsM+qq4tr+FW7fvE6VG5RXnJydMh7XFIVMDC/O55RFDShC0mANreuIKbBqOoy2bNSC0766d4XC5lhtmM/PGZWFBNRGARYkpOhThcWoEXVRslg3UpwHCXBLvseaDJOZAV8uxXkInlIbyVVIAxRnVGFixCrD47MzgneM6xFbVUUMjsZZmranbxq2ZlN87+mdyBLzIpOAw+gln8FqwaoqT14aDBpDfJbanYCu62laB1pJvoJRLJseN19TFDnj8QitFb7viSFQlQV5lpFQ+ChFUtt1OH8ZVHdZPJohKV4J9UsYqfwvApo+YFfKM6KPmDhAHKx4KHSek5o1qi7wy7VQp3qRvymjwCehzAVPjEqQyijiuoc+gMlIaS3Uzqajf3qCybMhVDWBzYlOpjYpeYILuMbhgqdfrSF6DJApjdGW3FhU8NLYIWASZMYI4l3lBMDbTIJFNWiVE01GtrUpOVIa9MYGPilMkZMVBaHt0JszQVU/w65qSBrvOwiBVCNm/M5jywKbWzofCOsOpmO2tjcx7z5gPBnz2muv8qkf/xHxSA0Uxno2AhXx1pC6bkC1R6Jz6CqDOOR9pUSRa8y0oguBLFOQMvx8SbPs+Pa3X+fuO+8RokLrhDWQlQV913L/0SOWTYPCsp63HD444OVPfIRbz10jy0sSitG4IiNy+uQx29evc3rwlPH0eUB2ENd1dI1AKOi8gEyqEjOqaI2lyBJGRbYnJf3FGdYaxpsz6RwvVhitnxXd8/M5XbNmZ3uDzBh6Hwg+kmcKkh4OxjLBSVqLdKv3IhesKno02f4e/ugUZmIYJwxgDx9IxhLQpNwQ+4BOEoURY4QuEnORa+ukKbRF5VYOXW1HnqBvOkxdwrIFa8VLF4cFK0FykfXpgubwjLIqyKpSsmY6R8otkgQRSZmR+9d7sBm0bsikicS2leBVHwWq1Dt5HTYnhUjsA8kaIkG8Tz9Av8EP+vLOE73D+55RPSEEh+8dGOjXa/Isx3nwwXN4cEBe5MyXC5FQGilyBL4Ds80d9m88x3g6o+nkGXzppQ/x6NFDnjy4S6YSWxsv8Nqr3+D46ID1cj40bQD0sHcorM1QiiH6JGdv/wrz+QLnPdpotDIUVmR5s9mIm9ev4RI8fXLI1f2rXL9+jboec3h0xOHhkexXvUjAyryApBhPaowyZMZQTSqyzGJsRlEUxBhws/GzLKI0kPaS1qLqSUmyzlYt9+4/5dd//StMJjOu37xBXkjY9MHBAV0fqMqKvlny5OEjurYly3KB0SglhDoSwSfyshIPetdTViOu7u0xn6+ZXyyYTcfcvH4V53va1tGeLymrCucEjnG+mLNaLkAplosLsryg61tMXvLhj76M0g7FivGoID4D64i83eiheZgUxlhccM98fX3vqIsSNxvjXSBT0prs1wsmsy1U36Kt4WDZUO1s86FRyYfKj3B8ck5Vj/nRH/sk63bN57/wJbJHT8hOMpq10IGVd7y8e5X9/Wv82sUp84uGelShlWa1WjCdjBlPxlyczyFGjsdjiut7bG1uEJxnd1d8ljFqtIY8N2RWPKnee0L0LNuW07NzwNB1HSRF9B4TFGUuWV4loNYdrszIc4PVmn7ZsThZcnZ8zmrZsLpY0a7XvPfeW5wfHoE1zHavsHXlGtu7e2xtbnHr6g67u1s454k6sTOpubk9pbhYYYuS9WhCXUqeVOcDjw9PaLtIlk1o1ktW7foH9ox/cFen4RJIQxzGzh6TScieC54QFK5zLLtAci3jKkNHwYXHmNjIFHWVcTxfsux6yjxjnOdiwkwQtSRlW6AqJHvCo3BWEYKTjkojwYiTcc0ks+RK4zNNNRnz6PCUo/MzMIkraYO61GzUGZ968SZJH/Dm0YJlF6gzYfq3vRNtd+ewypIpLb6GQTbV9T2ZAUKgbVvqcU5s1lidU29sMDKKx92SMrfoXNHN57jlkno8Yrq9iUGT1QUX3QpSx+07N5lsTSjCmo+9+AKLZoUxiVXbkNcZAS/BvSqRgsf3Ld3KM5mMqAtNVVbszkZcnJ5xdnqGUonnbj1H1665urdLaQ1vfPtVnnvuJi+99AIXFxdUdc3p+QVGG5GeDNKSZ5cSGZC2GSrC3t4eBwdP+fjHX2Y6qsh0xBQZW1uSDE6M9E3LqK6YjGqRii3mBA1d09M7j7EFmc3pzk+ocinGXPBYY5hNp2RaAjeTHtLlh4wJozSmEC9KihnrrkfZjCyzckjzgc452eQQLwJKxvZN2wuue+jiZVqjUuTW/ibrPjAqRE4ZogFTkJiS2QwNuM4xv5gP/i1FWVRYLYtZSokQpXuVWclvIUaeHBywtbEhxuohn6LrpWByvXT2MBmNc/TzCzEXx4hRmqIsCIPeG21wTvx6zxLjh2Io+B5j5P2wWvIlGCa7H+Qr+EQqSkJKaJfQZYZBIAfKGlRuSfOGVFiBZWQGrxGpXYoMRh9p2PSe6MWfFJqOEDzB9WiV4VcLwnIiAZFNgFy6ijpFdPCkzBKJxKYnto7gFVpZbJaG/J8kE/GY0EmwwyrLSEUpB908J+QF9D06eJQB4zxhPCUrcrTS6N0raCLlqCZ1DrM5Jcvt8PeQplGKIuUsxgUqRPIiJ2rJnRPyuSWbjrGZIYVAVReMCkttLd95513uvveQH//UKzQhUVgjk/rtDVRM5MU2fd9TTXJBRl9OOZUiL2SqroKmzi3OB+aLJY+fHPD5z3+R/+l/+p/pesd0ssH2zi5WIXKWLGc2m3Jl9woK2JzUXCzWfP7zX+btu9v86CuvsLk5YTIRiW41qkjasL13ZSAapkEmJ4cuHZOk0+9OiTZDz0b4PpKajo1pjUlCZZpsb1CPS9AIWTUErBbf1/nFAqMNs41N8aHI44YmoZGmnjKSEZcGIqvRGh8DOs+xPhBtRWb36M7PUS4Q5uckrfGd+Ag88hyqUQ1IzoxrPCrPCC5gMouxilJl6NyiVcIt1ug8J+SJOMz2tTWEphVkdOfl/m564mIlv6Kw+KZDG8HPoxApaYhS9GjAJ7SVSZJOgyeqyFBdKwHrIUCRkawl5jmx64h5PsB5pAj8AFuWKIqcFD0Ej/edNM6SByfvsesdWiveeecd1us5W1vbvH33Hn3bDCh2JTeIhZ3dfbJcGlj1aEI9HhOVosgM64szIPLFz/8qfbNk3TTSeEHhvcdmGZgkb6bRGKO58/wLg8cGmC/YnG2KqkZFqjLnxRee58q1a7z6zVd5eP8B48mMj3/iZZ67dYt10zKejNje3KFdrymyjFE9Aiyj0YQiz8jzbKCtScyA0SLTTgmSVgJyMhZtxctHiiJhazvOzhd8/Wvf4t6Dh+xducJkMmIynXB4eMTR0aGAnoqSo8OnxODwzsOlPyhEKcR9pOtbrC3QPuJiIO8CKcJkc4OsyCnKnNF0DCrSth0nJ6doa+naFh/FD+284+q1qzx69JAUA67vyLKCvWvX8CjaPjEaKexg+dBKbBvL1ZrNrSkpvs86ci7QO4FpjKpczhwxcbFYsjWdYvKCxdkZ09EG1yYjJnlGvrvDzoee5+rmBvVszKMnR7z2+ltUswkbV68wefMe7f2nzLZ3ycoS3zk2xyOKjU1mO3vMTM5kukldWy4u5jRNS4yevSt76I0ZXdtycHCEsYYb169Q5Dkhesqifj/kWAlZuus8nQviWRpy/5pVJ6HqxqBCYlLUQtjNZR/o1w16KLbW8zWHd4+4eDpnebHAxZ6T5TmNUjw8eEQ5Knnx6iuMN3e4+fyL3HnhJnWRMysthJYQImVluXFzmzIzPGp7gq65tr9NVeVoqzk/umC+DCzmK/ou0rU9xwePf2DP+Ae6WLo0LqJkUehch+97kopEZUg6IxlFPRnz+OAITUltDdNaEuOdC4yqjFtXprz9+IygFEYLja4LgS5GyUJAY5DgWxEpIUbsIMbhedfz+v2HfOzmTfE6qURUjmtDTsCDp0dYNKkupKOD4aX9baos5+sPj1HG0EQtxDYFIUnmQsyERKSMIqoo6dyDsW1aZmgLJiQmZUXvHA1DyFqm8a6ldx1VWXB2fsLWc/uYdSC0a1JpuPHCC0QV2N/awDc968UKVGR+egY653TxlKTE7G5SYLFakmdjmlVL7NdcnMjoeHNjxmwg6FxcnLM8v+Do4AkP3nmbva1t+vWSG1f3+PjHPsqb33kDN3jCYkoYNIn3pZQkyTFI2lDkOTtbOzTLBS/cvs7FxQkxRYyxVHkhmQSkAfFpKcuSLM8kAFRpUgyoQVJ2eHLG06NjYopUo4qz+Zyru5tyD5FwfU+VZyJjiPFZdzWqNEwYE0Yl6qoQipcPmCCjY3VJdkpyP2SZIM61MXROshVGZY4x0jksjGFSZBTWkGIGKgNj8D7KdMtHRuOCwoxIcUhQjwN9J5MDZPKCDdUDp9hYi9EZ54uVdBKripQiPia0MViT4UJ8n76kkA6fAmUkbNkaMauizCChUYOsIA7esURZlJRFjhlAEVq9jxX/IF9JG1Ilmu20auW9zXI0SfZlNUxCjcHOJvRnpwTnUYVMpHRiKDIUatWB1XJQ8l66vUoaOZ0PFCh0RKYEA1smdh4zqYhJvJQ6RFRuUK4hyy0k2Yz0pQTSaEELKw3aQFHgO4FwJNeD1hgssYvESS6ho/v7GKUwdUVWV3JY0kLok5eonkkxTWZR1mBCTuh7zDAtT0oRXZBAyckIVeaE3mNNxtX9fVaLC05PDnjrrbf4sU+9zKSuWa8afG2oJzV6e4ImURUjAZBYQ991VGWJj57QK2wuEmjX9LTrli998Uv8jb/xt/jmt1/l/OKcejTBmoL+6QFVmXPnhTvcuXWLED3X96/Srhu8d6RM8Uu//A9ZLpb8zGd/B//n/9O/ivc96JysKlBak5W5rDnD/7QxGO2w40r+zllO5zy6rrg4eMhsY8p4VLC8kENBPp2ghpBabQ22yCF4gg88fvSErV059OjMQopUSrxaeZahjcboAbzCUDBlFluWKO8JXY8OoMY5o6qkPT3HK0OPImqL6zshc3UeXZSYqiadzgkxUmYim0wDLc9oIUcpJV5e70R2F4G4ErJmUpA6L8++F99ccg6tDLELUMi9RwikdSBVSozrLqCtxtSVHJy0FEo6t6gsQ9WlTBG7Hqwd7l055KZRha4r+pMzXNcJvvwDelX1iLZt8cGhvSPPSrKipF0tscaSVMIHz/HpBct2jX3vIWdnZwQfhpxI8K7DGEs+BIe36xW39q7SdB3BB4rRhBu3X+LhvbdYLs9kmmit0EqBPM9QVpEVJTG8ny10eHjAdDbBaMP+3h7Be4qq4Mat6+zs7rAevEIf/siH+fFPfZK6nlIUuUj1jCG0PbubW1ijscZirGE6GQ2FUk6WCSzCZjlJSb5XDFLMBO+GKYwaiqRI3zv6znF8esZXv/oNnjw+ZHN7k9vP3aTvO05OjlmtV+LdDZ6L8wv6tiPEyHi2gc4tLngWywWbG1usz07E52XT4HuWBsBi2bBcrjDAeFSyv7tDipGL+UKmrsBiJVO/vu3Z3NgSQMS994gxsXftBrt715lMNijLnCJTzCY1dSEUWKUSJlNMJiMKKyHhIP9Qw9m0dwKYOjtbcHRwiEqKZdZhjKYcjdmcFWwWmtu7W0zqnGJzTL4zIS9LrukrAuroHbYo2L9+g3v3HzE/PyErxxjtWK4b7j94iI6GvizQStF1jvnFAqUUru9JUfHcnVtMpmOCdxweHlEUGftXdsmzDJBCSUBNAngC2Zu01vRNg+86zk9O0cpSlRmTuiYER705kkw5bYiVTBVPj+c8efeQ80dnKNcTaTnt1hy04mVUsxH706vcfv4O5WyTJihGowmhW1OPRiSXCElT1RUqdazWS67cuU5eVBRVzun8nLYzTFxcbAABAABJREFUPD06o+kcq+USReTs9Iyzg6c/sGf8A10scRmSmRJowXz3Xk4gUUnX25pEheL5qzuMMoXVIuEwlWGxjNioGWWRO/sz7h2dk5kSqzP6ViZQIQZa57B58V1mbodSQj3qOk9UhrMu8M7hCS9e26dQUGYaqwN39na5G+Hh8TmLyZS6yLAWJmXFTqX59Av7vHF8RmkKwEpYayYbUbVZs1w11PVYQgcHpGsEVp1jW1s2xyPOm46Ldo1XUgxslCXz8zUvPHeDb3/jO1zZ3UJZaPsl1XhCoRWriwte/PAdYujAwjJ1EBJt21IUhtmkwubSde0Ly6guuZifsTw7pWvX5HlOWRWcnx5jNeR5ztHRMWVZ0KyWvPzhF/ndv+t38OJz16hHI7Y2Nnjw4IE8vOn9QlclRUwynQkxonAYk5EZxbWr+3zp197k/jvf5ODxDX7HT/92trdH1FVBjInVWhCaZVkKmtZKqGJdVazblh6RhpxdLJmv1kxGJdevX+Phw8d86M5NAFT0LFdL8nwmIcTGSIGqlEyUVKLIM7wP+KToXZBiLEVyrbFlgQsBrS3OdcAgLzSQmxyXGawSspzJc6xWAmEY5AgJhR6KxhA8RhtictRVQYqWmMQ/Yi6JjwqsUWiVYbQUdZkVk3wasPdRaYxRZFp08yiGjp+RbKShyHl2QFaa3gU57OtBOx9l0hBCoCwsdV1L4npKwyRNCQUO0PqDDXhI2hLzgtT3aJ2hVEDn4jfDBQnjVFBsb2LLHD+/QCUFRYGxSbDL2hCaHiOtU0B8dNFFGKR6OiQYgC3xEipBJDQdVCWqMJjphHS2EO9eEDphnllC1w8hfVr+bK2lE28s0WZEJwdQbY0ECabLz9aKzGtjg2J3C6sh+ChBuQqRKkeZUoJMebQxg9l3ydOHR7z04g1MIY2n6OXA43snAY+ZAh+4srfNc3du8+vf+A2+9tUv8mM/+gqvfOJlNrfHOOfoOkc1roldQ1YXpBQgConQR482lhAjwQXaVmAEX/jCl/mrn/vrvPbW20w3tkjK0Pc9neu4cv0aAAcHZ4SoIXqCT8znC06PTnjv/n0ePXnM9sYO/+TzX2Y8rvndP/M7GdURlQRmIcPVIS9MS3PEFBkqQTYq6fuessoJKHavbDCe1HTNiqTBFDnlqGa9XnP37fe4c/sWKskzvDib8/DRU37olZepqlIaHsqilGCCU4wYrQbZThr8YMh02mjooRqPZD0cDtJd0wmFMQQCEIzFY0h5jg0epQxk2RDGndC5RieD0lYKbgAlEnUJus7ReU5se3zrUIVBZ5roIsYqId5VJUHJdDJVuSCmgYCC3uHbDp0g2QKFwkxGpK6X9bysMHWNnY7pj45QpsKMaqLzhLKArAWb4VIiaENEEfwHd7TU9/0wVhBIU54bgoesEElTunzWfUfbJYo8l8kiEsUwRCSR2Yzo/XAQt1SjAudbmtWCvCjY3t9jcf6ElFq6piP1XvJmygxr5Hlcr1tsOWK9WqNRzC8uGI1r9vb3sMayuTFlPJmCNhR5xYu377Czu01ZlGRW41ygadYs53OMsthdLYWYVozGNZnJqKuCvMopi3w4ZMvGEgfwj3MO75OIxFUU2i0CvOl6x/0HB/z6F7+Mcx17+9vMZhscHx/z9Mljzk7PpTHjPXVVk9mMTrXohMSCyGAJYzKapmfVtOR5hvORSI9S0DY9MSpS8MxmG4NCB956+13aXsiOPgRsUeCdZ1wWbG/OOJsvuXbjeVaLBZs7e+SVEEatVuxujZmOS1ARrSUs1mjFbDqW51bJeqK0IsVE6xPLpicmmbqVo8lAz+vIrZYMT1MQdWQ2GzHZnNC4nm6+pvARm1mu7l9lvhbc/ny5YLle0zYdXdcRnSNXsEJRZgWZzjHa8ujJI05PzijLiuATmV1xdnLK/t4eDtn7777zgOjh6v62eKi87OdlWaA0GKvIyVj5lpPTCx7df0yelWKLqHOy0jKejBmNKmII4pNDcXJ4ztHDU1bzBSqPLKNjFT16s2ZWgSksH/3Eb2UynbExlTiDiGU2HjOfQ2EMphiL1y54vNMoKupJRdu1OLdisXzC01NYL8XjW+SGi/ML1ssF69XiB/aMf6CLpctgzYHjJebaGEnJkHxC64SOHoOiqDJKHSEGPJHcKkxmOF6s2d3ImeWwP624WHtQmUwBkmxeIWnWrRuMwJCSdGVjkG4kAULSvHd6QeM8+9MRm9Oa3Gp631NVBasQ+fa9h2zvbmNVYmvi2NndoF6uqIor3Dtc8PhsSVCWQmfUdcW5cRRVQdsF8twKuUUjOEmt6ZRHB+lMRd+zOjnl2sYOmzbDa82jt96iILIxqbj7+uvsX9mjKCx7d26zu7FFHzz3Hj4gDejQi7MzutWaQmfsjLYpKktRFpydnIOPPH60AiRRvGkanO9ZzD3WwGwy4eb1fba3tnj5wx/ix370h7i+v8u0zpkv1tRlxUc+/GEpQrSWhZUkHYkk3VitEjF6qrIkBEfbrDl8+oj14ojnbt8ePDSSmZWiRyEp5V3Xo60sVnmWs3JB8LdaMb9Y8u57D/jmN79NpgMvfOgj3Lx9i9WqES23sXRBZG0aCZUzRqR0iYQPgcxmFHkGLqIyTdcLelUumWrGpKiKMd47oneUeSFGWmNouzUpCZ5eGUgEkU0lMddeYtN9ioSUJAw1yYQrpSQktuAxajg4RwlWtoMsxirZCBhG6bJg6wFWoJ4VpnoIJI1Rwh8vkd9pwBqXZQVIB1QuMQXXdUVmFGrQySilB8iDPHsf7LkS+D6QvMPWFbQOU9fovMAUFjuqiEYTc4sZVaQEdjqhPz5BZzlJDZ34+Qo6R8w0+F7am0ahMyk8UkqoTEMMYtRPEXqPyhQR8YKQ55h6hLIW0/XolFA+otQw7fQBnRJYLYduo4WaZw2qzIirDo/CDjIXTQZake1uD4COQB8SNstZH55Q7WyRFaIvl89S8ORychOp2Hq1JimFtiJdTgMhyeSGGLzEHVh5Bj764Q9TFBUPH9zn6994jb3r17iyt4O2RsikWnxgzgfKMpNn3mh0nhGjJ5Jw6x7ner7zrdf503/6z3FydsLm9jYxwe2bt7h2/QZVWYIxXFzMBXKSYDSa4T2cL5aso+LK9es89/wdlvOGyXTCd958l9V//1f5v/zs72Ycasq6wicBZlgrz4y2Fp3pYVIYUb08T8E5qtxwfnxE27QooxhPJlSjmkcPH/Lo/gOev3Gd6DwaeHpwjPOBvf0raGME5W0k7Nhag0p6iLuQHKMYkWc9RqIPnD05ZLa7hbKWGAI+RMrphGVVSWFszIAR7zERwmotU0ythH6WZEaYFRm5lYwspZVMLO3glyLJfW00Ye2wKREzTUyBlBR5ghQ8Ksqkn5hIMRGUeBaVi6TeE9QlqAfUEJqutcZsbZBtTIkxYZsWjMWOa7qzc3Q9Qq07KcYGSFMiET7AgAeFIreSlVhkuURvnJ2R2Rznxbcl3rmAUQalFDdu3mQ2nfCd114lOAEU2NIwX14QVCKzGffvvst6PSfFRFmVzM9Ph4mPxemeyXRMjAL6uHb9GikGHj58KodpJCC1LEqMttTjMePxRNQIWc7HP/oR9q5sUZX54Ev1qBQpiwybjanLgrZpZS9M0PeOUV1QlTU2U2S5eKIupevBeVwveTyS2afk2Row+b7rWK9bvvnN1/mN3/gGk+kG2zvbbG5OOT4+5d133mF+NhdEdVmiUWzsb7Bq1/TeU+QVF/MFfe9Jg2QYIPpE1ApMlIalUlTlmBCESllVBa7vePjgsWStlRX9uht8uNIYLEvxIR0eHhMTTLd3yasRSsHmbEKRKcZlTpUNcskkXl2VEP/k4BkLMQ0NT/EWrtYto9Lw4z/8EncfHvHw0RF952iaNevlGj+qKKqabDLiYt2wVobQnlK7KaNRSV5mrI5WdN6zXjY0y4bFxVIKM+cYjUdMxhVKawlkTRGrDd4F1mFNTDL5VU/OqOoRV65s0zQtujO8/tY7LFZLbt64SpZZurYjpEQ2rFnOB7q2wyhDVZbs7G6iSWSFpR4VjOpCMt+0om8dzbIh9J7gOtrUc9HNKWYTroxmTLYmjOuS8XhEXgigrKhHOOdZLtd0nWN/ZwNjkgT6eo9zQSwUqSW5C5ZLx8nZIS6uUWlEZnOia2QqP0CWunb1A3vGP9DFEsjBk2HBtloTtaILA7UryWE8MyKjC+lSkymRj4VVzNtA0yemVrNZF6zWjj4GokrkVg6k3lp6FPOuo8oK6ZaEQB+i4Gij4qKRMXHbLzm5WLI3G7EzKZmNarZNRtQKk+U8OZnTRDhY9mxdNFwZV2jXs1NpVg14JX6T08UCZUrcMLlKKTEd1WS5TLtc0Dw5O6XQBt009L6Fdctpe4+1USxOTzl/8oTdG9dw7YqdrRk/8aOfEFRwVTG/WNIFMdEVRcFquWK9tYFKifVyxfbOjOVywcX5BatmTZZb7tx+jvliznq1wocerSK3bl7nX/7MT3H71k3q3FIomE4qkWqR2NraYrqxAUR29/YYT0ZcLNbEkDDZoFFCEuEZTJEfeeXjWKU5Pz+lWc1JSdO0PY8fPeBjLz0H2uCTvxyRkOf22aKnlBb3UFIcn15w/+kpB2dLytGE04OH3HvvPerRmIOjE24VufjcSsv5fMHWdCabvVKDRyRI8KqSjRAdJfgRQfRe+nlKk0mwYvAiucmsTKUGNH2VFfiYWKwb5osF08mEKi/wvqdPPdZaQhgyeZTCBZkWKaMgMmRlyUE2xIAPjiwXjXymDV3fkYyh8Z4YE7NigovS5dZDYaO1SBYZ8L5yxh+KpgQRcCEM8iyNIlLkhRAah4nS8EiJNE8MVKiEBA9/gK/gPGnViJskBsyoxk5HqK6VQ7RRYqpHJns+RpLSEvDpgkymtML3AmRAa5TzJAORiFEKnWnoOlLbSsNlvSIZC8aSYiBpRV4WdOdzdJYRtBiFtREikTYKMJhaJGxxvkbnUvimheRjhL7FhkA0hlAW0q0vSsxsQySsWu7R9ck552/dx9YjssmYGBMml3tCK41DJqujUckrn/wQNjPymi8Lm3WLzqXYUYNvSWvLh55/npv7V3ntnTf5jd/4Klev7vG//20/iQ89ebZBCgJNcK4nBpF7ppQkSqFt8F3Pet3zy7/0K3zhi7/O2+++w2K9ZHOj5db1m0QXyGzOx17+KDt7Oyzmcw4PThhPJoQYmE2nvPjiDfau7ZFlOe+8+S6//pVv8O4773D33TfxrqF3Db/35/+vqCzDqkz8Yx6RkgzS1OCDFCldL7lVRvPo3n0Onzxhc2eL8WzGeDImxsDV/X1mn66JvUfFRNO03L33kK3NGVvDeqrQEghJJkvWJVUSCQJV+v3JgzKG5nxO7Dxbt6/Tty3aZri+R1cVemMq4ITeETTQrMh6mWjH4PExYkyGzXOCStjcknzA5Jn4iJSR/TIBWUbILCm2pKRFGtc6mSA6R1yvUQSUNaCkAGfIaApa3qeEwiQFVS7yz9GIvnMDUVMyB6M1KK3xzkECOx7TXyzw6xbnA94FoZW5D26xVI8ngw+nxWjNcr2SvchYYt+RFVZAACaXfJi8QOnE2cUpKPGhus7jXc/y/AiTAt5m3F/Mcb6nKERmnmlpeBVlRl1uklSiWcm+dHR4JI2wpCjykmo0oSxzNqZTyrLk4uQCq3I+/rGPsndli+3tIcfLiILEaDnwp+hRIWGNFoy4DyQFVZU/y2sSCfpAPIwB5z1N09L3DqWMkDUR6TkK1sslp2cXfP1rr/LgwWNm0xmjccFkVPPwwSPuvvE2bdvJflLmCNcxcX52TlIBUhjC0SWaxWY5WV7Qe48PHuVFrt51nSgoNhMx9AQXOLq4GBQZGaNRjUX+zlEb1k2DRXHw6ICz83PJRtvakaiWtqfenJFSwGrITEQ2UGnM6qHBRIpD4SgKkYhM11CKUV1yNl/jfc+V7SmrzuNdZDGfkzpH5yPJ5hydLZiMS1ReMK1rzGVeWmbZ2Nrm3sPHxJgoiww/qokKcmuxQDnZ5N2upc1zut7R944QPG3r6FyH1oqyLHn0+AhjNZubM1CwWC741quvM5+vuHPnOnVdsVw1MnXzQmdFwfb2jDwfQqqVoqpLqkpkt957OcEZRV5a8toSskjMYe/WHnv7O0wmI1H+5DnGWjJrKKsaY4cCzUd8iNI4UQL9csHhQyLPM3wXadee5cpzcgLJVqyayOHBAa5PONeDht61lNXoB/aMf6CLpZQizzQMDFQSYzBJ3nit3tdiKsD7XnDOiNwoywzjsiCEiLOazMDmOON8PRwytXhfQHI58qJg0XXPfp5WGY3rSEgGTdv3uAjeK5rjBaeLlo16zd72hM3ZlDxrGdcl954ec7J2HARF0zoyLI22rCLUyuOiHFgLrelVYlZoiqogBVlQeyC1jsXhGWedZ374hJ39Cd3FOReLc3avbnH12hWuX91l78Y1ru1fI3Utm7Mxfd+zahqi79je2GBcCrAgOM/x0RFN01BYmE5qylwQ6efnp2xt7dDWBWWdE9wGbbPiR3/4E/zID/0Qu1e2QEVsDIwLg0a6vUkbtDYYJYSemBIxCZQ6yzJJE1fh8tMkoUhRs729h+s6xvVYZChBc3x8xGvffpXf9lt+nJAZ2TAo6LpukIFJp0keygy/aji9uKAPAVPk3HjuFh9/+UOcHh2QfMfZ4QE2dexuz6hm8ucdHhxydX//2aTkcgomG4T4ZqOJcqhWaYDASaHmk8daKSAG1APOOay9lBvCeFQLlEEpfHAYo2iH0E/nekJIZHk+0OUSwTu8Dxhj8cHJYdYYbCZd6sxmA/5bfFQxRuqywpiBBKkUWWZF0jFQ06QjF549PwaZkhqjSSmgkh7oPlr8SUPHWw534ml59vw9e/I+2FciEH2PO3EiFTm9oC8ydJIDQzvvwAfCWPKW3HKND1Fkdd4R25ZojcjJvIbkZPJmDYSAJgpgrmmJyyVqVBNjJIUeNRQ8oW3pl43QsXwYin7IMmkAhT5gywKqnNT1wwtPhD5gfEdUgvzu53OyrCQbj4jjEabI6JYiM23XLVlmaI4viJ1/VgDLPZuQ/2folmqUioMUFzkgIKbxy3GIb3tUBLSssbt7O7zwwgu8+s6bPHh8n8ePH7NYrrGZ4cG793nuuetYM0FrJR1LDShF8B1957j33gP+h//hb/O3fvEXWbcCHEgxcXp6xGq5ZDrb5vpzNymLjM3NTZz3VFUj75WKjCdj9q7ssLE55qtffZX7j494+513efM736RpFyQF//1f/Wvs7F7h//iv/k7KEEhaC/ly8CnqYbqrlKKajIkp8fT+U956400MitnOJkVVAOB7J0RIH0k+4bzj/GLOm++8x8d/5BXKsRigrdEDE0GabFprlFXSnB4Ok88m7skR247Tx8fMrmxircF5T79uUHmO73qik8m0ny8I7RrQIo9MvN9ltVq8cSkMqGiDtppcaUxhUAricgVe6IreSUHvmhY7KQldT+zdM/WGeI0kEyl5D5nAeaKWqZBvHUk1qDLJhLxphfSXPK5p0Wh0leOaBu88vu8JTU/wcrALyeO9+9/ysf//6WW0ofMeYwQTH4JjPBnhgyfLs6FRIUTRpIQOeO/ePY4On9L3raCYreX0+IjdPctqtcBai80L2qZBx4ihJhtVtKs1mzPxSB0dnZHbnDzPSWiquuTO8zcoc4v3jiv7+9x9512szrHKUmUlZ6dzxvUIrZbUdUmISaZLKJQSqb8i4XpHcIEQZDqRZRab5TzDjSeE4Ok7us7Rdk6mkoU0V6R496zWDY8fH/D5z3+F+aLh6tV9NjZGkALvvv02b7/1NueHxySf2NjaYrYxwxQ5p8enWJujjaZtPUVWylQ0Jdq2p+t68ryg7VrZ05SSsNaUWK5WVFnBar3CO0emNCpLJGOZTCYUecnh4REmCC12MRevtTY58/k5LgQ2d66QaQXRo1N8JjUzWkmDS4lXVamE8x3JCAGXCJlRFJlmNqk5WfRcrB3BR4H/KJjOJiJ5jpGzdcd6tWJ/Z4Prt6bkVU5dZiQ0WiV2Nkdo9uiaNU8fzBhVQnYOfWSjyNjZ3OLuvEHFiDWKyaTmwX2ZsHnvWa3XmNMzxuMRR8dnaKXYmM3Y3NygWbe88cabdK7nhedvUxU5TeeIPrBatVSleJSmk5oYBxtAJkHIZsiHS0nUBi4k1m1HOaq4tT1lY3NGWUp+Zuo9pvcUeY7OM8m56nrarqP3Ip30IdK0HQk1nOs0senwqxVN03DeSEZqQM6l8/MLugGiFElkWcl0Y/sH9ox/oIslGEgriLY/poTWA4hBScfbWvMsF8ZeSueULPLGwKwqWbQt666nyjXTUYHG07hIHxOtU1gdyUzCB6n0+xjpB1JIiGKgTwjOdd33uKRpo+a86TlYOJ5eNGityDPDzb1tPvniHS5WLfcOT2n7wEWzxlRjTEwkDWWunx10rZJw0/VqzcoFQhIfDS7gIqgI460d7r72La5vzPjoyx/i6u42H3rhDqNRTl7kkoXhK5bNEoUnU4lutSTbmDHZmNCu12zsbFIaePDgAS2BujB86pM/yt2777I5GwvBziR2tmZk1vLczRvsbG1SWINNiYSTf1fDwEfMZKQh4LV3cHF+jtKGelTjnUfCTWVSY40QuZIyvPH6G/zYpz/Ng7t3iTFitOb0+Ji333qHw8NT0s4ms+lYPsuBEgcy9gbIi4yoBFNe1zW721tE75lMJ8S+JXrH2fExo0Kz+8JzTKsailI8T0NeCkrQNglBnCotkoKUBu+Qlo0jJSnSiiT+HqEMKWKIKETeJp3cIO9NnuO9kJF67wZZZ0CpwaCrtXiCYoCUJNDQB6wxxMtiRmlymxG9SEqjElJiURQi9/F+eN8usebv+2jgu+iDiYF4F3HOU1UVdV0NkyJ539VwcPzNEIfLKZ58wh/0Kzg/0Lg8Ck1qe9z5AltkqDIXf0YIqNVaAiRXK3zfwcEaiCQn5KTQNyRTMaRzohEZHlbLM5jLZpsG6RGAX66HvJoEWU5cS2aScgZlMmyR8M6hi2IIuo2DAiSJD84FYmGIvZMwytajR5boAhhN6BwqJWIjHpG+1/iLFcZaBhWLEOG0lglmQjwWWjbFGKPQKRWYzOIThLYjuiDTgs5jygzlAoU1vPKxj/PL//gfslou8MFx/8FjXnzxJnffusvDx4+5/dwt9q7sYLPBY+cTx0+PuPfgMZ/7q3+dL3zpC7R9A2hG9YTM5vSupXMd5xcnfPv119jZvcJ0d4dxVeE3NqgnI1KKbG3OOLu44J13H/Lg3mP+wT/4+7z33jsig1WgteV8MedP/Zk/Q/CB3/Ev/0tMNzco8pJ+LSZ5m2eDIkHhY+Tpwyd87YtfYn4+Z+vKDgnJheualrIocZ1kRjHgkN977wHrtuPFF1+gLHNQ4l9Mw7qotEgWlUpDJ1rWlogSyqExlJMxq6cntMuGfDoiOcljguEpDhF8FJBFHzCllfUKUQc5F8hCEgKZkuaMSTJxUtbIJHlYt9x8Rex6bJkR217WOx9kj9GyhhIiKkVUlgOJZIxkyfiegCJ0QskynSOkczSJfjQi2aGRtGrQZYlat/h1Q79a49uOoKUhFLtWct0+wJ0X58V3a/KckAa40LDs5mUlOUDGkIiQFH3X4NqW9WKFD27YUzTr1ZKz0xORgruMkS0pypqsyBlPBNxjrSGmxHLdkpLC5hlFWbC7u8snPvYyo9mUt99+l/vvPmC9us/+7lW01kynGzRNz/HRnL6LzDbGXNvfwbctZmtCngnt85IGbKylMEoKpmcNNvmcvJesyq5rWa3XeBcwJqeoJJQ5+USIkYuLOa9/+w1+/StfoyhH3Lp9m8mowHUNb731Ju++/jZtK0S/za1N9veuDH5wySuLSSZlISaSUrSdExWcgs472t6xXq/ptVge2maF0QZjC3Y2t+naliIrsEphhjVqVhYYpdidjjk+v+BsuaJZr+V1K0/yin69JKYtykrueVIgeAeZfdYgTFHOmyQB+GgksFZkpQGr1UD91YQksTCjyYi+dzTrBjUAp1zb0XQ94XgOeYkpxCc5m0wJ3tG5noumo/OJziXarifLC5brFaWCViWwimXT0PWeECJt1w3QDTv8WXBwcMAuV0jxDDBUdcnO3g5ZVfDmm++g0Tx3+zpKG3JrGY0r+qYl5QVVVQx4dPWMfnt55r5UcaXo2NyaMtsYY6ymGGiXwUfaZU89rdFagpBJQzO4l3iStuvFcxYS2gjErGk6nEpUo4KqUjx85wQfIn0nhNm+X3N29BhtLUkJYKOo6x/YM67/P/+S//XrP//P/3OUUvz+3//7n32tbVt+3+/7fWxvbzMej/nX//V/nYODg9/0++7fv89nP/tZ6rrmypUr/IE/8Afw/wx6ZaHv6GeHP5n2DBImhOTlnZdWKUmMa8OmhpKiyqjEqCjwMdIFjfOJUWUYF5rCJDYnOYVOjHLDJLfUCqZ5TplZfAp4Dcu+pY2S7aSUJSVF5wOtMhx0nnfmLXdPWr5zsOQfvHafL715n3XvePHmHnf2t6iKguhabJ5jck3rGx6fnnB0fs7BvOGw7ThuIos2kZJBKwkxPD0/I9+oSWXOnQ9/hI9+/IcoioqbN29QVjlKJ4yOFFajkyIvKrQxRO/IreHeu3fJtWZjUlPlhv3dTV7+8Au8cPsmm9OaqjC89NJzfOqHX+FTP/Qx7lzf50c/8TE++fGPsr05G/J+oqRJh4BEAQ+dSC05DvKpRM7PLzg5PQcU0+l06ChHUtJobSiLAmUEVEDqKQrL3bffkAIqJXzf0/WetUu89/Apq3Uz6P7Tswd4NExujFLUZflMRlZaQ7NccH5yKp0LbagmG9x54UOUZSX47Fx021IcxcGfMeThDHfbJVwhzwyZ1XK41gmlIlonskxLDpKWiUCeW2wuPiWVIDeGTAuG3hhFXmSMR9VwJ8sBTcb6Mnkz2pCi+Bqy4c/MrMFocF0neHzkAGazjNwaSYJPcp9f5naQLjMTAjFFvHMopBsqE7komTIkUvSE4MXH8l2F0jNiIeoZZvryvy+9T9/rFULgD/2hP8SdO3eoqooXXniBX/iFX/hNBVlKif/4P/6PuXr1KlVV8ZnPfIa33nrrN/2c09NTfu7nfo7pdMrGxga/9/f+XpbL5ff1WuTPCoSuR6UgsQNWQYji0fCeMEgN/KrBLRr65Qo3X+JWa8J6TegbKUYuvSFKuo0UVohzVgzsurAEDXGgLoovbgiyjh7ftsS+JyrBDscoCHfyAopCpH8u4mPAOfGWpMzKPSsLn+T0jMaowhKWDcEH3KqjPz7HNw3JaIrtGdXeJrbK5Q1QMl28nBzaIntm1k4hQhBYhfeBoBCZXwTno3gjQhhkZIlXPvYRrl65iusdJycn+HWDa3tmm1u8+c3X+dx/8zn+H3/hL/Grf/8L/PL/+Cv82T/1X/OH/8gf48//+f+GV1/9Fm6QksboaJoVNivQpoAUCb7n8aOnvP3Ofb75G98CYDqrmI5yNqcjqrpkfrHk/tv3eOP1N3jvvbusmwsSCaNzOfPEyNHpKX/iz/wZfuGP/XF+9dd+naODU/o+EGIS7f26pW1aHt17xFe/8hucn89RKjGd1symE8m+shmxd0PwcEfnPU3T8Op33mI2m7KzvY0PDA0XMc2HYfLNQHBl8BkqY4cDokEBk91NZtf3JLepd/imBaBbrEitTF+S92RZjrLim/MukJRB5ZIV6Hon+6MVrDMwvK8R56PID3uHDx7XtXjvCL3HOy8eySiS3QGJJfJia0hDI0U5L4dqJwcX17Y0yzn9fEG3WtNezHEXS1wjGOAUE75p5X4emlppCHZOwUMMA3Xze7v+eVtDvHOAwgf/LIhWwtglvNdYqKoCa6wApPpOACsxPJuodX0ntLi2oe8cznvadkHwjqZp6JzAj+p6ynrdkpTm+q0b7Oxu89GPvszLL3+ci9WaL37+13nztTdRUSbSycPWbJut2Ybk6OQ51grN9PzkgnbtaZctJJGXky4VAwLzMUpLmPzgw/E+sm5aLuYXXMzPRXqYlWRZRvQOhTR4Dp4c8kt/91f4R//4C8w2r3Dr9nNkFprVkm985au8+8bbrJs10Qf2d3fZnk5xa2lIxeF1aJRkVPVuUANZQnASAo/kGwXX0XZrlotzkfgO8ve+9yglDZ/oPbNxwY3dbTZGFWWZY7Smb3r6dlACaJGLVnVNVpQQxe+kiMN0Vg+qDDWoSgbSxNAwvDwrSCi8yPNyq8mHLMYY1IBXV1SjmiyzrNcNbR9YtYGnZ2veeXDI3UcnfPvuAd98+xFvPjzhaNFz99EF81UAk+OiZrFqqUZTdDni7fOG9w5OmC/WHB6fc3I85zKct+vknvLec3JywcGTIw6Pz/nmd97k3sOH+BjY3trkxo2bfOvVV3nzrbv0ztF2HYnEbDYFraRBmxXYLCPLM/Iix2YZRZ4/U2+VVcVoXDMa1RTD9CiEgA+B0e4UPRuR1TnZ4BEVLHnE9Z4sM9RlTl3mMokfvOMxRs6XC5q+YTatuXPnOjY3HDx5xMGDd7k4O+Tk8SPa+RmLk6cy9f4BXf/Mk6Uvf/nL/Nk/+2f5xCc+8Zu+/u/9e/8ev/iLv8hf/+t/ndlsxr/9b//b/Gv/2r/Gr/3arwGyyH32s59lf3+fz3/+8zx58oR/49/4N8iyjP/sP/vPvu/XEQZZw+UiqbUgWfPMSs4MwCAtuvRvBM0wYVIoHTERJnXNfN3RBMhMoiwsJXLInJUV664nH0gszieyIkPFwIWP+BhFp21klG0TZGVOEyIhKPpoxZ8SE26dOG0VDy+ekJlAZnLaPuIT7MxqdjemnF8sqLRH+ci1yZTD5YJJURHKkiaI2ThFza0Pv0TftExGio9cv0HuepomcXpxQV0YbGXxnXS5jbHETqAIk4ngd7/97ddYLebcuL4v3fComOxuce3KtsjMiFR5RplbxlXJjf09tLGcz+dizNZyuIo4MiVmYjsUHBL9IF3UFD1vv/0Of+Nv/A90TqQKxhpMyIhJwvPyIiPEgrZvWJwdYXSibdaIRsWQSGzt7vPWe48Y15YPvXRHFmkj4AKQrofNLPnQvR3XI8J8zaO7b3NydMR0MqbtHaPZJq+//fd5enjI7/pX/iX8Rk9dlmgjenCRrknYnTFmoNBJ8RGVTDJlcCY+gTS06PWQixUGI7z4CORAbIwa5GxSeBgt4HSlNUYlvFF0vSMm8baF4FFDIWONkd8XJe9KDQctYyxdcKzWLWWRkxlD0iKXSnEI11VJOtkIQth5h9GSkXIJhAjBEaN0h/peMR7VEs47PFPPJEKoYQr23QVSGjau7/36L/6L/4I//af/NH/xL/5FPvaxj/GVr3yF3/N7fg+z2Yx/59/5dwD4Y3/sj/En/sSf4C/+xb/InTt3+EN/6A/x0z/907z22muUZQnAz/3cz/HkyRN++Zd/Geccv+f3/B7+zX/z3+Rzn/vc9/V6ZAoYJTAzREFAlxnYQW4RIr7rMSmiQoIQiD6gDfiuR+mEdz06goqDdEmLtEtZMbbHtJYu3KVkasiGGyJD5MC0aghOZAcxRAFtxAhlia1GBL0WyXDnhKRorNAPnUPVJVpr7OaMmBl0kMNsaDra41NZr4zBJoXODbYYEZH7/bJIxggBMMUkBVLvcG0PIeBDgjyjc57QenJr0TbgOzeAGhRg2d3Z4hMff4W37r3Dew/uM5nULM4v2JxNee7GdbIs5/z0lHvvPeRifs4XvvhFjs9O0Noynkxo+475UoiZPvS0nSLPCnwQiYuPjlUzZ7Fc8+q338S1LRsbM5Q13Lp5gzrL6ZcL3r33Hr3rADmcyAQ4DtLtxPn8lF/++7/C2+/e47f91t/GKx/7KC+9eJvQdEymExKet15/k4uzc0HkzsZMtjYp6xKGrDHfObpFQ0C6ocdHx9x7+Igf/cmfICRYLNYiX3G9TJiiF6IhhnhJAx2kTyiBBCijUXXJ5q19YtvTdx1d27G+uMA3DX3TCA58OsaEIDlbTSN/PxReS1iscQFTW1I9kqlN06CB2DlMBt3FnNh3EhbrIqn1RJVEdh7jEGIsr8fWFdFYmbr1CYwRLLmsUPheJDOpj6Azgk/EToq81MrrjcVQfBmLmk5hPhd/VIwwTLVi+N6LpX/e1pBsUAw478jzgroa07metusxFra3tlEqkFYR1wuxV8AJMqG/pK8aI+oX53qapqHvO8qyZzbdoG87iixnY3NXZK/WsrW9TVKR1WrFd157jel4yu0bz7G/uUfvE6cnR0TnKaxmXOcotYWxlu3tDZHcRdAhkEKi71qRmCqBnCQSSRuU1YQhbyck8cx639O0c0CT5SPybIhzj4mu7Xj7nbv843/4ec7mKz76yivURYFWMg197dVvcXhwQLNekZmMjY0xqes5PXsqQasXc/KNTbyLoC1t0xFcpGt6lk2D95GqHksR5TqSVnjnxA+TFxRZQZllBN8JUdQatrc2+fCHbrO1vU1Vlxw+PmB+cgLBv5+pZAw2L8m0oahHVGVJphXZEKvR9x12AOVorWSyr82wpnx3I3HIU1OKIldM64LFAJQQCmZB7yMM8Ivz8xVFVbFarWgCvHb3iQRvK01RF6yWS/rOc354wKpxpKgGhLvFjqZctB3z9ZoqRJbrTia9IdKs11hjqOtaAFZRmltpfor3keODA65evcrLH3meW7f28KHnjTffgZh48aUXAPm8izJ/tnbaLBsk+/KspiGU3gc5W2ZW4SNigzEaawvGIzv8u5WfOdAh4xCXMh5JVl2Kib53tM5grCapFl2NMbogzzVbk8Tx+ZJ2vebk8DGrs0NChMxInlxdb0gj/gd0/TMVS8vlkp/7uZ/jz//5P88f/sN/+NnXLy4u+At/4S/wuc99jp/6qZ8C4L/9b/9bPvrRj/LFL36RT3/60/zSL/0Sr732Gn/v7/099vb2+OQnP8kv/MIv8B/8B/8B/8l/8p+Q5/n3/DrSd6HDnwVjpij66GfkrzQEbIon4zK35tkpRYHRCZUUZVFycrEi6IL1omM6yhnlmq6NGASRnAqNVp7MR0bTMaPgWbnEhe05nDeSLJ0cVkOpDH2es3ZKUIxRxrlNhOgNNhr6XpGSZzoacd54ztfHrIdOkPI9WaG5YivWLtH7nhh6aBN10qikSUVNbdfsZFCUJSE3PHzwkP74mJdfukUxyYdOIWTakhQ8evSQ5aIdHmjo24bcaqzRGCUboNEDbz8FtDLYzJIyWSDqqsIHjx46gUZJKJ+RMYZI0QBUfDZpevzoMXfvvodW+tnh2hhBWSsjAaeNNmidMSpKHj14RNsHyCr5rGJP3zucD1hT4r2n61rGoxFZJrpZm0mit2s7kX94hyLy6te/xt2336IsCrZ3r3Dj9gucrzv+x//57/H6t7/NT/zIK/zwD71CZjWTccVkMmZ3Z+fZz2WQJV16M2JIQ8GUhoJJaEGRAE7+PonLkTU0yzWj8ZiQApDkvXQyUTDIyDm3hjwrWDUtkDDWoJJC62xYnDVcoo4RGl4Mnt4LtjO3mUjvrB708YNPSSmG+ok4LOpp6BxnmaXvRQKSZUbCBfWABUf+3nroAoHImC4bE8++pr6/qRLA5z//eX7mZ36Gz372swDcvn2bv/yX/zJf+tKXnj3X/9V/9V/xH/1H/xE/8zM/A8B/99/9d+zt7fE3/+bf5Gd/9mf5zne+w9/5O3+HL3/5y3zqU58C4E/+yT/J7/ydv5P/8r/8L7l27dr3vo6oSAyBQC6Fd+8IVpNChlHDQcF7YsgG1HIvHbEYISRUCCiria4nRD/IM5VgwrUa6GR6kFtFNGLolo+yGHi4Ft/3tGfndOtGMrU6J++5h2Rzku5JPhA6h49JJn8DzllpgxkOgKFxkjOmM1xMKOdxowq/ahlPPf50jtrfIYtRZsFaiwwsDERIIIUkwdy96Nd7H0heoDaui0SjKQuL6jVd51C5RYdIWeX86A9/gl/5J/+Qg6dPafqG6XQ00BZLjA8cPHzMa9/6FifNHI2hyAsW6yUhRbY2tumcp+sbIJFSoHdOpijaYI3l7OSMg6cHPHj3AfOLM6F+oXnpxZdYzxcsVktOz46J0Q2NFEWIvcijlBnWKE09nlCVFV/7ylc5evqE48OPM5uMCQRC0xGjw3UtZVVy4/ZtNneuSMGZZfggk8HOOUxdCoXs0VNCity+c1vABX1PbmQSU5Q5Co2xVsKPU5KpkhqCnwdvINqQlRnLs3O60wsoC6KGfrWmefiU4DwoIThiLTjp9IeE+AdwuBDRLoILpDxHDbJn1fdyMFwtKXJL4WvseEIsJchdKU1Aii1iGLJihLyXBgBNSpHkAykzqKFpEEMgBAli1rnE7gakq0xmSK4ntJ3kkjUyiUp9Dy7A4PMk16Tug7uGzDa3uDg/lQaJLP5Ci4yevc0dxpXlfL7CIPKyMi9E5laNcX2HGSa5ZVmSZSVFUQAtmTFklxL1GMisxfWe7d1rzM/PePr4CajArVvX+Rd/8seZTTdoW8f5ybnsTd0N8qJGW43vPVuzCUWZs3d1R4LKg0xUstyQKUQiBVK8a7k3lZZYD+cCTSsfkvMdIWnG442hcPCklFivG37jK9/kS1/5GspkfPyVTzDZGFHkhqOnB3z7m69y+vQpIUBZlOQqwy1bVuenFGVJWZT0PtA2LUVR0LcdZVlj8wrnPW7wa9b1hKZpWa/nEk4bQCMSr6vXbqCTxvWdPHNGcfXKLpu7u0x3ZrQXK1zbYEmMyoLWe5pWo7KSvCzJ8kKKor6na1vatUalTSn6Y3wmr7zc+9q2o6yqoYCQ5m1MMmEiBrYmBa2rGJUF54s1fecorMUWGfPlWmJBgqg+lqtOokiykq7tyJrA/HzJYn6Ob9bEvuW5K9vcurbLN9+8x2K5xvUdvfMoHbhYLCkuw/2Qff7i/IJ6VGOUYbFckXVyRuh6x7vvPiDPcj72see5dn2fFBPvvXcfm2lu3771rPldFBYfpeDKrEBiYpIwaVmnk+SnMeT0KaQhbiWk9vKYEKI0V/VA+s1zCZiVBrAit4ax0uR5Tp4NFpckU9aj4xPu3XtCv16xvbNFVeTorKCwGeONDfavXeXBg4ff+yLyfV7/TMXS7/t9v4/PfvazfOYzn/lNxdJXv/pVnHN85jOfefa1j3zkI9y6dYsvfOELfPrTn+YLX/gCr7zyCnt7e89+zU//9E/zb/1b/xbf/va3+eEf/uHv+XWIiuF9DeXlhzb06IRkh5BajBFaT1JJFiYG43IQHHeWIEPMd00/fFl5CpNIyhCHT1sPBYG1oAjUwWNRhExxqhJRJbS1+L6jyAvGEaLvaTINQTHOczywahtylWOtPODO9eTliD4ZLtYLDg/OWXWere0NTAqURUW3XnJ1WrNZCx1pNCo4Wyy5Uu+ASjyZz6XjXRYcHTzmPVo++vLzzGZTUoAYEkdtg2sa+rZhOq4JfUt0JUkZ8nIiExUEaysa1QEZnCCkRBoACjZqjAJNpK7yZz6XZ1NprQdZWWQxX3D37j1kcq7p2sGUPeBzjR3w2dqSYs/BwTGrr32baEpULoc4NSyudVmyu7UJSZDelzKyoijkz1big1qtViSVeO/ddyFFiszg+oZH997h6PCQnRt3qCZTHjw55NHf+kW+88bb/Cuf+SlckORtazO2NmfyGqNHaSuLZUosFnParpMHOs+fmU5TYshUeX8qY619BnXoo4yklZYui9EaTRSimQKlEkWR45zHeUeRZc9wwwwTKY0UL1kuQbOud2xtbhKdl3OHErlppg2XipQ0HKzTQIfUz7phPCPxWWuHr4dn3qtLUMVl8PP7T93lxAkxSXyf10/+5E/y5/7cn+PNN9/kQx/6EN/4xjf4J//kn/DH//gfB+Ddd9/l6dOnv2kdmc1m/MRP/ARf+MIX+Nmf/Vm+8IUvsLGx8eyQA/CZz3wGrTW//uu/zu/+3b/7e349Wis51HmPshbsIF8cJAS+6UhDrhBBkuHlcCgHGKUQuUsfSbXBlIXkHmWG5KMglUci8VCmIBgtBVLfidGfhCaSVKDrxfSqfA/JSCOnyFCbm9D3pK4Tyl2MqBBJbSsTpbYjdQ4TAllRSAdDRxSBFBzJaNRoRA8U4zFmNIYsx8fEctlg8oy6KChzCeJG8YzOGJJMNV3TgRYUug8BPSrJgO5sifeBPBP/10c//BIv3H6Rr3/767z15ltc390jhp69vSucPHrEztYGF/MLKpPjes+0ngxyxMh0Y5vxbMbDRw/oukaIjibDe4exCZXnBCIPHj5gMp5gipKzwwMmoxHz83OWixWH8zNWjdAN3/fVJazJ0FriH3Z3drh18yYxBFzb8eTxE+bnc4iO2WTC5mzGlSvbbO/usnNlh5u3bgmeNy8gCL2pax0qz8hKg2scb7/9Ljt7V5ltbtGsW0aFwbtWitGYiYwtBimMlIIk4JQYoWnDoOP3JKXFo1YWAsbJNSkTnK/JDN26JcSO0Lb4dQtK5OaXsvMYIxZwSaaB2ZVd/MUF2rX4KNjiGMQ4r8cjyAxRIV120pDt5jB5DmORDSY9xAVYS7IJhcQt+JgwKNIwEdHeoXQOrSPmPamXyWdKoGMkOUdycl8NOm6iG4Lkw/cuofnnbQ25c3vEwZHi5GTNyeEBbSPF/vb2Dnu726xX55Q2Z+17qrpEW4uLnvF0i6ODA1bzM5S2VOMxk/GUuhpT5C31eMJkMsG5HmMyQpQ1fL1eA4FXfuhj3HnuOru729SjihAiVddTlRbvE7FvKapKwFbKYPTghTaDtHtkpNESIXY9RlvxxyklMKYY6DqRpq5WK7QS4IgyMJ5OyXOLdz0heE6Oz/m1X/si33n9LXZ39rl24yb713ZRJI6PDnntm69ydnIm6k6grkY0p+e41QptDBtbW2RZTn+xIISETmKZUFmGix6dNJ0PQtD0/bNpkEoRm2m882xtbjMaTTk7OSa4ltl4g0lZURSFxIycLzh58Ji4XKO9J0uKjbrEZpaLriPZjLwoqScT9q5eZWd7E2PBR48Zsugkz3DwBA979uWZMyVpXIQg+6LVmsLAlWlN0wdGRcYTpJByQULgTZ5BMrj5GhU8tsjoekfwnrhYMhlXzM+P8a4nucjR2QX7V7YY1yO6PsjELzh8b1jOV3Qq0PeOGEQB1bQNZVXRNA1VPSZmCuccrne4vuX1t95id3+L3SvbPHf7JlVR8MYbbxNC4EMvfQitFVZJAR9CoGlb8rxAazVIfDMYpOVCAYYmOLJM4GHDRGMAcOnhrBGJVBKYbe3g5bRohUj7rCUET9O20paOkRgVJqvY3Nri1vPP03eO5aqFFElKYnz2t3a+52f2+72+72Lpr/yVv8LXvvY1vvzlL/8vvvf06VPyPGdjY+M3fX1vb4+nT58++zXfXShdfv/ye/+0q+skhOvyms/nz/798mD6Pq1Lblg9dEm0sfQpifnfGnRKDBCmQZsrnd+AZEeOS8Wq70gmobKCi3XHcrVgNp2hUqL3otFXShOVTBcMgUlVcGWS8NqwaltMNUKnyLTKCAR0SHg/HFIxVFVGco4iNySVk2LGqvcct2u0tmxtTSh9RwDaXvPkdAEucvf4kFlZsj494/qW4YdfvsXZfMnFssdEx4t7I67duMpiQ/OPfuVXUKHjzvN3GI1KgndYEhmXpBrN04On7F3ZxntF1/YSYKj1AAeQyYl4dyJWafrBv2G0QkXPqLRkhuEhkWJJGT3k/GjatueX/t4/4m/97f+JxkViUrSthxTEeK4sShm0SuTGEsoaHz19BGUzcpuR2jU+KR7cv8+oyLHG0jc9eT6EdBqDMiIBDMGTFyVlmVNnBa7rmS8WdA6ZOGqF73sev/s2xajm+edfYHNzl29863Xeu/eQ3/5T/yIv3LmFD4nVco01mo3pmLqu6HrP0fEx7773HteuXwcimxsbKBRN66nqCmslYtYWVoypPpGXItGwWoIfGUAkLslUSA9dxdwqtIqoGIcU9Muwt+FKwyEWPWiKFRvTCZnRzwrcbECdBx+GqUYSot0AoMiLAtASejoUOsbawaAq9LdnBL9nxdLgCVSJ7/YExJj+35oV39v1B//gH2Q+n/ORj3xkIPcF/sgf+SP83M/93G9aB/5p68R3ryNXrlz5Td+31rK1tfV9ryPeR3mvIpBng5lZCT3Q9fhOcpFUEL+F954+eFTvIURsmROUEj9HUeDzHG1AZ5aQelAWPa0xkzEqelitBD2vQK0bmfZ14hXxIeJCIIZEUWf0yUNVMb59i+b4EKzCKUhaExAfiM0yCSLWClPkRBfJqxwMqK7HOY9Zt+T1GB0T9ZUtdF2gDLR94N6TOT5pJlXB8zdmlKUefGoQ0rC+JoEMuIHuRZLJUzYqSN4T+kAcyEc7V7b49Kc/zatvfJunB4cS7Dyu8C5y86UPse4Dy3WPOj3m/OJMtO7TKatmjdGK5+58mO0r13jj9VdZLi7QJsMYkcF0bcPh4WNyW7Ax22R/dw9tFY3vOTw5wsfA0+OnhCGH7VLumGU1Whtsbtnfu8onf+hjrBcLjg4P8T6S8Hh/zqjKSSQmkzE7u9vs7G9z87lbQ49AZJR97xhaqhTjisxGztdrnpyc8GP/u98iE9u2Y1RVuN6RF7lInlQkePEYpqQggouBVeu592SBZPXA9khjRiVZCPTzpRS084Wgun0k9p7QtfSrRrrqXgAk4kcU2W/KLH6Yfy9OTrEhYJ2DKIe5qMCrhO09Jiow70+QBRGsSbMZug7EdYNOkaiRtXacQdMguXHy7AQveVAytXPkSRqLMbihWErYzHCZqSSywcFLfLl8fB8RBP+8rSHPXT3m/CJntZzjupZkcyCwuzWD4MnymrIw5HVCZxnrVcPN2y9KYGxRobgJKPLCEqIjkXNxLiHle3v7uBBZLVfU9YRXPvFD7O5MGdWana0tqtIOqhmRiBmVKHOD0bk8t0rgLZeqAPtd2G+R0CZsnqGzUg5Gw3nKu4B3nrbtWK6l+RC8R1nDdGMG0bFeLXEu8OjhY371V3+Ng6fHXL12jb1re+zsTFEK7r17jzdefY3FxRl92zGeTNjc2OT04SMWZ+dURS75giZnsrFBG2GdEr1z2CxjvV6zXi7IbEHftQNNcz1IGDVVPZIg4Cyyu73L6ckRfbNmMhlTFRmz2ZS+WXP/9bfJBtooIZAZg/MBFWFzPCGra5oQqSZTJrMpt25elUmtdwNIatgPtdAAGQBJ1op3W3IRB39yluEusxpjYFIJoAltmU1LlmvPcuHxMZG0pu8CNisIsUMZQ2Xg1s1dzubnXNndY7k45eD8DNBczNf8xmvvsre7w8bGiCPfAYqub8itleJNGfKiIiGNZGs0WVngfIdfB1AWow3OeebnC770pd/gJ3/LT3Dr+h771/fAwptvvE237nnllY+IlF9LzmNKkb7vpQn8XWfFNEwiUZpJbocGrahuLj+rGN5vrpZFPkDZRMXkfS8Nn5DwYcm66VguVowno6GgyplsbvJDV7aZTCdczFc8PjjFe0dRZPTO/fPjWXrw4AH/7r/77/LLv/zLzzS//1tcf/SP/lH+0//0P/2nfu/9Qumy3/2+OfGS6GWNfiabyIyMFeVGFxSz96Idtmh2RjWTIrDqelrf43WiUQbVR1Z9x9nFkpvbmyid6IPHI8SRUbIsVcvhfEnQlnVoMUZTWs3OZMxy3XHcLynrCWUEY2RsO28b8agAjQtENOvW04UFIQWyIicvLJU2bNQz7j5Y0QTHZGvC5qygVpa9vU3C5oqXru2yW8og/XEe+Yl/4VN8/euv8+VvvE5dV/zYD3+cuspRSjM/b9i/OuWlF26QG9F9rtuGPua0bcvOzjZG6YFyElEYog8YouSqKENdlDLNCJE+9Sgk30ElDVFxdHTCP/pH/5g/+X/785ycX2BtQecEEZuGYklZ2WhNkeNDxGQFqJKoNDYvSS4QtQFlePjoMU+fHrCzPePR0yO2ZhMmQFlpbJScCJm+RIy2nJxc8Np33uR8vgBtCN4904bvbG9yPp9z7+5dVjs75GXF1tYuX/3qq3zpS18VD8MLd7hyZYfxuGLvyi6vvfYG9x/c58Mf+QiLdcdbb71JVRacn835+re+wysf/zj/0m/7FxmPsiFct0KnhIsyqYlBqHYpCe2nMAUkwQBfZhtYozFlQebNM4kcKNpGJlkxCWI9RhlhGy3FVvDvL0JqkAJw6eUb3hvnovx+JaQ+gUcorFJYrYUYNPj6EtJFHp6yQcYa33/WLsEa37vN4Nn11/7aX+Mv/aW/xOc+9zk+9rGP8fWvf53f//t/P9euXePnf/7nv/8f+D1e/6vriJbutzYZoemwZSnvjxpyYlwANYRnGkPvPW3v6ddrcqsprRSeaqDHqaKSKULrSJMJoQ+CmY4RkxfQdWAyghMNOMELknswMTNIhr0PRIbQ0aNj+tVKiHRGE7RQqqJSA9FbfGxeQZZnRJvhjcZkVqwiZUkadOExz0hZRlKarnWsmsC685xftGzOSvayaiA9acHmavCIYTmzhugc9aQipEBuC8qNMc25mOLzcUUyih//sR/mF//OVd599z1C77G5AGd29q8QfEtdl7x59z2qk4rOOWxRsn/rNvPFORp46c7zLC5OeZKgHE05vzjBeYf3jrKs0FqxWC5ICdpe4gP6vscNAdMiC5KpSFGI5j7PCnb39viJT/8YBIfLK6q6JiGHySzTbG1tc/36Ps/dusnetWtcu36VopQ8NjGa99gso12sJfS1NGiTcf/eQ8p6zPMvvSjrGaBjACuZRwlpLhiQ1msSaEbAcHy25uBkhcpypoVmVhdyLxoDNiP1Haas8EUuh4HckJwhaUPKZMoXlSaEiKprutWKUmt0inTrNYvzc2zfMQoRE7zI42IU7LmSLLAYBhSyUiRrSWWNrip8e0HUQmY0eSZhy5klaUtYtoSulwm396xXDaYsyawUQilGUrjEJUuch7JGvtc7tM1QhYSZpuAvnaDf0/XP2xry5Gnk6HjBarEghEhMjnpcklUl63VLXtasmhZjM0bjMXt7Vzk+PROUv1GMxzOu7G4yq0Enx+HJmtVijs1y5vM15XjGix95if0ru2xuzphtjJlNMvpuxXy+5sbVfQEsDN4S3zuKzKJU9myPkInIoCFLiKwvyzCZGUiY0iBJQN+0hBBou45m3YrXOwTKqiArcrxrnwWHvvGdN/nCF7/Eet3x/Ic+xNbWjJ3dXc6Oj3lw71Xu3X2Pi5NTTG7JMktd16zOLmgXC3z0QIE2mryqZIqtNO26QWWCsTZRyf2NyIZNlpMIrFYLUkr46OmaNdPpFk+ePibPS8qywBhLUZUYY+ibntXTIyZVwXRjJmHhGuqqJDqHNVAaiylzRrMZWVnSBz+EsYuAou89thTFRgyiUNJKi/c08cy7nJJAopz3ArpKic47tB6kqwkJoO08MSlChMVCAl2LzFLmFhcis3HJj3zik6QgOVXnx2esz8/QSRGjZtl0mLwQv5xr8X3PZDIlhEAYvM5pUKZ0fQ/W0nY9dV6hDASVSEnRrNccnxi+/o1vE4Pn1s2bTKczrly5ym9845ucX5zyW37Lv0BmDdYM+X9K4QZKap4JpCvGwcUoi90AlBpiMC4lnUrwgUZfcl7kLNN3Ema8XDdkWUZVldgsZzzVlHlO7x3KajY2xkxGFd4HxpOaF+qC84sFXdcxm45plosf2LP/fRVLX/3qVzk8PORHfuRHnn0thMCv/uqv8qf+1J/i7/7dv0vf95yfn/+m6dLBwQH7+/sA7O/vP9MVf/f3L7/3T7v+w//wP+Tf//f//Wf/PZ/PuXnz5jDxGLT7l3ShZwvu4J8hDLJohQ+yiCsz8B4HqtegMIAgG0htoKwzlr3Qxk5i4Hg+xyewdcXdwzOu7W4RvDww/apnc6x5+daMO01OllccrnveenLC2hnaZcfmdAIqsEqBpuuZZiURqPNcCDhJmpWrlafzkdpmnDaadtmRmZ7QL3nuwxv89pdvcXNaspFHprlha1RS6khmJiznZ6x68S5tTkfsXdnl+Zc8v/jL/5jpeEL/hd/gU596BWyBMSWPHh1RVxnZnT0oNY8PDxmNxriBtJRnOV3TQkrkZSl4ayvwC6U0PnlCUpydzWlWPZO6pKoDh6fHvPraG3znzXf58pe/xtmyI69GNOv1YBSNkiejFCo4YihwPkh6dDmmsAU9RmhQsSeZjBAs63XL2dkF88WK/+ff/pvcvHGVf/V3/R+wWYaqBGdtM0sWPH3T89p33uGNt+8RtSEvDC55UhQm/8X8gphgMh2zWq04OTnBKM3GxhaowK/8g3/Cr33xK3z05Q8zmYx47uYNjh895Ud++JPMT875/Ld+FWMzlssVeTXi6GzFX/i//2VCVPzUb/tJcguu89R1jYqXG1EkRNE6G4mqgWfFh/iNYpSpXUqasigGX5EUSlpr8Xw5T12XwyYoPyizduika9FAJ/GOGSWyqeAdVVUREepe73rpNhrDqK6xKWG1oY9egv2Gidb74YPvT5Uup0lxSEj/fidLf+AP/AH+4B/8g/zsz/4sAK+88gr37t3jj/7RP8rP//zPP1sHDgYD6nevE5/85CefrRWHh4e/6ed67zk9Pf2+15HgEiEksFo02loIVloZyZFRlxugGPHTgG5WWhGCbDgxKSmIB/y8ShasHe5dJ4fEvidVBRhLyHOZaA3vZfAigVLGojKDb50Ej6JxB0fMlyv+X9T9Z6yuWZqWCV7LveZz2x4f3mWYdJVZkJVU0aWpoguaGSRajKE1wzCAAOE0EiPBH0AzCP7wAxgQiJ/TUqPp0ah7ugfTFEVBMXRDufQ2IjLDnTj+bPe51yw3P5717RNJQ4vsJmnilU5mxI59tvm+911rPc9z39c90ZnKThmHEWZTdNY00wl6DOjGlYI8E5VCh4huRfOv9/cIPjCdTnFtKz8/QlnURWE5jIG2Nqw2PUcLi1GAypjKMnYRW9dl+pWLxwlsJZ63pqlpFlOGbY9yIjd8+ulrvPbKK3zpK1/iYr1i72CBqaVRc+vZp6lnM9oj6eAvu4EcPJPFnM36gHEYOTiY88KLnyAmg7ZNyZvZkGK4xPGHMBJz8SYq2G6l+9n1PSkFwEjmVFUzn844OLrCdFILLdUa2gzoq+wVY/7x0RHP3LzJjZsSpnjj+g1m8xlD1+MmDVUlTZBxO5JSollMUIhq4f0P7/HMiy8ymc8Zt1smlTw1rnaiOCv7U8wZnbIE0QJjCKw2IyFEhu2aeq/BB4crkQC6qUj9gJvPCPU5fr0hayV+uVlLuliTncNcm6HWW5RSDNst4xixBLwC3/cMF+c0lSPnSCqTrUyRn6YyjbJOQpaNEVldipDKQbCuUYsFsduSh1H2y3J/JzRJKfHHoWRKG0VWmK0lag9W4xDPqxRm4uuIsRAotyPhhwDF/Pu2hnz33YZ7Hz7E9z3GVvhxIMeazWbAWct2uabvOmxdM9vfZzqbM5tNyPkaX/3a17k4ecjxYcOLT+8BmSFNuXrjaebzQ6xtqaopbTNhvR2wdsNkWuOsyK0P9vdLfqFM/ipjsZXQaHdU1IRM+pSRcHKlFcqWCbgWqIvSWiAVPuBHT99LVo+2BkJgMp2ICiJ4yToaPF//2rf4tV/9Nep2yud+w6exFvYWCx49fMCXf/XXuXh8xjAIoe5g75C+7+m3PQyDBJo6R3Owz3azoRtH9q4ccbbeolTG1pWc4LKcF7peio+MZuwHerPGWMN2vSL4js46prOFmP3blhQSfhioj65gfcBrARIM246qtjRNIyCTumHTjxhnqKZT6rrF1DV916Nrx2bdcf/RKRB5/tmbIGzTMoQr01GK97C07IWca0uAuWH0I0pXdMOIMQprDOTA0HusEimkshmsfIUYArc/fEhVG84vNty/94jFZMq4WknYc4a+8yhWGK1ZHBzz6MFdgUA5kWlXOHwQ6EPTNoxxi7GWzve0ppUmWl1TxwAJHj54xFttQ8qKW9ePufnUTWIY+e63vk2KmZ/6yS9w7fpVXJJmr1KamAL9QIFiQcrSOAzF36hNCTQHdiCMXPyaxkDWRlQUjaOd1Bwe7olvTkM3jFysR/oxMYwDdW2YTiqJBzKKOitUZXB2QRg9MSeeuvHviQzvZ3/2Z/nGN77xAx/7fb/v9/Hqq6/yp//0n+bpp5/GOccv/uIv8rt+1+8C4M033+SDDz7gi1/8IgBf/OIX+Yt/8S/y8OHDyxH4L/zCL7BYLHj99df/ld+3rutiePyXrh2Ro/zjDiaQy3hUyBviN9Fao4ofpVbVZbCsvKEKlWXB7wcxW1qtmThDZVtUhG2ACEQFG6eIg2fIET92LJzlYN6yqCO5rVExcbOuuWKv82sfPKDan/Lo9JTkPbduHHE+bjGxZ4NFWUM/BgYyW++56FY47dAJ9qcV2UcOWseN/au8OE9cW1iuzQ0HbYWOnlp35DEwrEdm1rLcrFBK5CLP3LzFrVtPo43lv/r//n2GzYT2OxOuXDkmxIGcA+++8w6bzSmfeO0THB4c8M1vfJtPffINHtx/wGw2ZxgHFIlje4AG2smUnAKurlhuB9763vs8eHzGeh04efiAB3fv8s3vfIvVZiMELaVQriGGbTE87iQYQEqY0r1HObKCup2SVUXdNHR9xzCMZGTsnVPm0aNH/L2/83f5h7/wT/i5n/stvPPuba5cvUKM0oU3WdF1W7bbgYePzvFJFlcfhlJQm8ucCGU0JyePWcwXtE3NnQ9vc/++SHjmiz2qfuSf/NN/gQ8jWmum7ZT/+ud/keX5KZvNmhSzLA7aoK0jxchf+b//Tb7+jW/w8ovPcbC/4DOf+TR7hwcYJ136GIMcnJhgC5RBCnZdspGeoLkljwWappFDRUE8Z6WJaUdSkskQyOKVCp3G6AKZ2E0EnBNkfpIw1coUnbA1ZJUJKRFGKSTbtkHtpkyXJjT1g5K7LLSf8X/E2Hu73f73cOM7TCjA888/z/Xr1/nFX/zFy4PNcrnkV37lV/gjf+SPALKOnJ+f86UvfYnPf/7zAPzjf/yPSSnxhS984V/5ff+16wjFk6FBGUsyFuWcgDyMmN6VVShriKMn6WJujWAq+0R+qjQxRJJW6OChalBNDZuO7D26chjnCMYWQ38WApjVkJ1IAPOy4MYtGMU4ePoxkMYBtz/HZvG62Pmc1HncYg81DDCOREAPA1SWVDWkBDaDzhpXVRL/pA3GKIgRhaB3Kx2plUy+bBY5lXReBWdt61oCvesKoi9d6IQ2tUiGcsJMKmwSOp6btDRNzec/91l+9cu/xlvvvMsnXn350tPXTmpcXXN0dMDR4R6rvhcP5nxB7yOrixV1W5GNYxsyjx8+4OWbr7Hdbnh0/x4+RHyMkMWLKgV7IpYDS/RenhUkJ2g2W/Da659ks13z0ksv8MILz7HdrMRQ7DTbTjKWnn7qJotpw5WrV1jsLzjc35eD5XRCVdfS7AiKGDoms1b4Cj5xfrFmEzWvffpVrLFoZ2ms+ItQFKmtJkdp5uwaJKmg6XUOECJWKZpKWh4xCRwnodBVRdU05IMF/mIl0p24k9OV/37tKkN1Tlpt0a5BGQdGE87OBTTQ9QxBEL3GOMHXa0M2FuU0UQtJMwFOiYRaOyeHPa3AR6zSZCUFqXgIMtlogizrZKWI40Aufy8hDSyheGaZGsQMaLJzpJBLgGtmTJr4Q0yW/n1bQ0J0NO0MP3pG71HWUrd7bLYDKW8Yfc+V69e48dQNjvYPsVYzm7ZsthsODw65eeUKT9+c4JpM19ckteXoaMHe3hGj11ycb3lw7zF1XaFT5OhwxjJHJi4znUwZB6HMohTGVpBGoR/GMo3ZqQSKPNI62R+0LZEBOTP0vQSDbjuZghqD9x6UZraYM/pRmiXAxXLNl7/8Nb77nbd5+vmXOL5yiFaavb0F3/3mt/jO17/BZinQlsXBAbP5jOlsysmjx/jNFh0RHxWJ+bVr9PfuUs0m0lRMkawzfd8JCdOPBD8Qx4SPQnsTyFDEb0eGfotWQi521nHj2jFjt2WMopgZ+47VyQlViiSjGYcBZWAyX+BTYq+ZwOhJpsJOp0St6fqOqprSh8BqveLD2+9yZzHl6GDOdFqjbekyFftHyhJoLR5EAR3oElyvtMLVNX2QM2rjjGRRgjTRUkQZhVWWrtsQfGAxbTFWc3G6whiHNZq6rVAFhlA3NU6bQt4F0MymB7iqBZ1JGEYfMaYWP2DWqAjGaZqmZhgHmnZSUOi5SDQdJ49XTCePmc8mXD0+onKa69dv8c733+Kf//Nf5zf9pt/AtavH6KRLHpc0X70PWFvCrktAsDFCv9vRc3cf10kx+kBVWYwxuKZCBC2pAMAS3TDQ9SPjEFG6TPVslgai6mkcKCUNdrKs/2RdmmQ/muuHKpbm8zmf/OQnf+Bj0+mUo6Ojy4//gT/wB/iTf/JPcnh4yGKx4E/8iT/BF7/4RX7iJ34CgJ/7uZ/j9ddf5/f8nt/DX/pLf4n79+/zZ/7Mn+GP/bE/9q85yPwPXeojf+Tadb93Wshd8aSVpnKawQtZo66c3Ow5XRrhUaLdTQnGmCRULHuOJ4bV6FnGDMqxt2hxyuBzjVET2kozrQAjhDqjhYx2bQY/+cpVVsPAK9evwJi4sb/g4vqU9057RuU46wY+7Dv6zchnjo54sVW8+NQVDmaWxilqpZhVlok1TA0YmzEqoXIk5CjmfxxWWW7fu8+D08c88/RTVE2DaWrWJ6d87pPPo/lt/K3/7L/gw0dnHO/tc3B0wOc/9xkuTh9zsLjKvQ/uc/Opp8gR7n14n6wUDx+d8cKLz5PClpPH93nphRdIClZD5OG9+/yTf/ZrnJxveXR+wcnFBRcnj1hfnGJUpqonDBsJ3fN+ZBxHKZbKe7SDO+zyZnyImLqmahr2D65wttpQNxLYFpUmK0PMni9/+Ss8vP+BbOa2IgGr1Yq6OmC5WnN+saSuHP/il7/Eg8dnl4fYlEUSIqGx5f1Ogke/OD9HKUVd1Qz9IGF7j2Qa1jRTNtueTOJ0uRENeJLxeQbB6GZQ44hWiu124O/+vX+I1pm6rnnj9df5j//j/xUvvfQcR4d7VJVlMp1QV3LI2xHrQF1q7wVV/kTqlpK8TkobxmFEGcnNykjuki6/Y847OV85CNuCaNgRwXKidhVOKeq6Ztv3DNGz3GyptKata6Z1Jc/MLrH0I8+V0h+R4JX/3DQN4zj+UE/t7/gdv4O/+Bf/Is888wxvvPEGX/nKV/jLf/kv8/t//++Xx1BJdttf+At/gZdffvkS+3vz5k1+5+/8nQC89tpr/Lbf9tv4g3/wD/K3/tbfwnvPH//jf5zf/bt/9w9FsQLp9qMtGEeuLAkNEdxsAiFA3kIUfX9MQXwbTYO2GlOZy7wkmdeUaVORe2YfpAMPxKwZO/E8pgJLyTtUdw6ARteN5HR42UB96BkBXdXkjGBZ0ZhcsM5tjV8t0TGhjCSdRR+xexW5dlQHB3Jw29/DNBW2cZjaIY5OmDjLs9dmTFVC2Yq9eSMQi10MkFa4xqKC0LQwEsRsrJE8rqoiFB+kKwHKKUWMsbz2+qsc7R/z1a9+nd/+c7+FtqnRVnKnJPA2UrWOfhjZdB3z+QxtHRfLDZvtQDOZ8eHdE/xsIMTE/sE1Tk9O8GGDxpSRh8AnEqnQT5NIfI1IVI+vXuP61etUzjG7eoXf9IXPcfXKAdv1GlfkPGdn5ywWc44Oj3GVY9LWLBZzjJUiR5fGQEzSZKmaCle7y9yi+/cfo9s5R1evQk5MnBGJXtvgrJFJlpLMo0Lg/wFCqyGxP6+ZTiv2ZzVGiSTONQ0xD+Q20/UDdjalnk0ZNxtSmfYmpXBVRY4Z5Sp0m1CbjaC+XUUKgZgTHpEGYcqBy1li1sSs0c6QS7SBrmuStgJv2PaQErZtwFjSMMp+6eX+jcjhRWkFxlJNJmhA19IEjCqThvESCaPqhhg78cHFQEiR5AyJClLEn3cf2zVkulhgnMHnjD99xMHhMVU7oRt6fBiZTx0vPn/Is88doZOlbvYx2uF9Ym8+5/rVGVf3B8layhOuHzYsuwplWh4/fsx23ePHgHFCGNs/3VBXmjgTLPM4DNy8cUjbuIJzFhJaGHKR1AY5bGt9SUxNOaGyEqhRmfQMo+Sc6R2501mqEhCaSxrsg5MzvvqVr/PB+7d5+ZXXOb52gFYyDfnyL/8Kb3/3TfquJwP7h4fceuomrqp49PCR7GUZFkcLgu9Znnd0neD3u26LA8ZhkIykypBVKg07hXYWo+RgHFKi67eSj6hktlM3DccH+0zqCpVGatuIhGu9QSNF2Dj0ZOuwjZN1CIudTqhdxExaupKHNvSe87TGWs04eIZh4NGjjnfevc3+wQI3LWoRlVDKfERhoYvkFoZ+JClN3yf6oHi86qUpGRLTScvphVg1PEnWcqexZspmuZLzjTY8PlnRNhUpJJYXa5EEjh4mGVtVks2mFSkFjq7u8+KLL/H+e3fgYivnkrIndN1A3bZMqpaqqQvdcKSpa04uLrB1y+GNA8aQuHf/EZWV3KP53oKc13zqM5/i9nsf8k//6T/njTde57nnn6auDChNtxmF6FsnKlsAIZlLf5w2T84mu8FGY2uctVhrpEBKEuUTYmTbe1bbnkePz0kB8fGFwMXFSI6Z2glKLISezieGsdCCs2byUY/3v+Xrf3TO0r/u+it/5a+gteZ3/a7fxTAM/Nbf+lv5m3/zb17+d2MMf/fv/l3+yB/5I3zxi19kOp3ye3/v7+XP//k//0N/r1weon85OHP3J+cspnh2BnU5kIYQCoJao5AumSpkMoUmKY1XAR+DdO4rw8JY8rZnVInKOFwOTFXAKEPtBFAQE6gi+hUJVOLYKo6aCSYHoR35yJLM2cUFs70DZnXDQRt4er/mNz5zgMsNi7oCPI0FgyKpSIqBSjtCCmy6jqYSPPHYR7Q2RJU4unpEMooHDx6xtzhgNoVGOx6eXqCA3/97/vf843/6Jd794A5v3X2bb797hysHB7x/9wxNZP/gHaaThsEn2nbCh/fuoY3l+vGCm9ev0adAHxQfPL7g7//8P+Pr3/oe2shGd//OB/SbDc4ZvEokpViuLxi2W4heQvgy4iwW1IL8I0jWh1YYW/Pqa69x+8M7kgA93WMcfJFtyAb9/u0Pib6jaiZMp1Ou3bhWqHtwcrrkre99n2effYZ33rvDvQcP0EaQ6SGJNp9cwAXqB24iUll8tRbYB8qQ+p6hoEpzlu+v1S6/SLTMKaQyvYmIv3knWYtstx2/8qu/yte/9iWeunWDH/vcj/Ef/fbfxssvv4i1ThaPFIvcUNKrjRK0rDW2hNyVzpHSBfEqJntbOoVKiV9ld18rBVXlypQpiJk3JcZSQKWcydbQDwPBe5yzDMETs3T6cpkk7XgpOzzq7vkCMbB+1Lv0w15//a//df7sn/2z/NE/+kd5+PAhN2/e5A//4T/Mn/tzf+7yc/7Un/pTbDYb/tAf+kOcn5/zUz/1U/yDf/APfsAr+bf/9t/mj//xP87P/uzPXq45f+2v/bUf+udJxogZPhdfidU4YwpyX6agShlJso9BZGwOVBITtLFy8NAxC9J7vcW2Da4CFcW7EfsRrEGFQMgyGchGg9Ok7UCOEdM2MGlJw4Buq4IU7wlDL4fTvX1oWlivSYPH1bVMS2MQL0J6MhHQtqI5PkRVNdViBpXFThqw5hKBTykG9hctk7YmFy25KbIcrQ1Sk2RcJZty9pLzFWJEZyFPaqPl+6uMrmyRbmUO9hY8/dRTfPvN7/LenTu88tILpBCk+NCGGD11ZSGPEpitoJoYQmzIGLSteeaZp8A4zs7PuHHzFh9+8D1C6ASnjyl0u0ROHq0cIUUgorKhco6DvSNSVnTDyCuvvcL1G1epLdTVHk1dMQ4jdVVTtxXzeSvRD9aITEZplMqk4CEjnqjei49BwdB5Qkw8PFlydO06TV1jkvx3W0tYo3NOJCso8ZUVZ84OuGK04crBnMXM005ajFGEYSQRZepeGbRpGLfiW0pHh4zeM3SjZLx1AzEmXE7orPBDkOagtVA3eDLn3QZFIrczknWoGInKkSZTVNsQt71IiqJItHRMhEGM/DEmGAN2UkExZ8cQSD4IHlnr4rMTCqyWCptYgkCTEr+JNoYA5NoR+0GKuCjFZxiD5IX9EHLef9/WkGY6J6Kpq5bQTpm0C7JSrNfy2l95/hrTycC4eQRMZWoRM4vFnOlLz3M8G1hMHrLdKjabkdRbTvsBn2XdWS4vCOOIcRbjNNeuHeBHhbMt5+dLjIIb149lfU/S8R+2A48+POPBvcc898IzXHn6kLqWkPSsNTkp+q7Hx8gwevwwYp0EaceSCaaUYehk7x594OH9E776tW9wenbO6298ksXBAq0yd+/e41tf/Ron9x6IbLxpuXLtOpPZFFdXxJiYTmesLpZoY2naKVYLQXG5vGB9sWTezqhK3IGPidQPxEKN67ZrrKtYLc/w44i2lpQ8UKNtRV05rl+9xrVrV7BW88qrr5BC4vzRCfF8TT90xBhxkwnGOfpxpA4BN5mCtVSmwrVTPH2hy0WGHkYtNo9X33idbrXk9PScOEbUTKGyrP/WqiJbfxJWu9323Ln/iJu3bhBi4mLZ8dY7d7h69YimclijaCpH7wNkQ/BJgGGlcRcQOX7KmYePzghB9t+qaQh+QCkJxlZWE1LgpRdf4Kd/8rO8+e597j5YMtuP9MslwxgIQdQsIWYiimY6I0bJlhrGEW0d3gcuzs4YGodSC0JI3H/4iGefqtjfmzJ6z7MvPM93vj3y8z//izz37FN8/jd8jtl8Kk0fpUh9JtqMrYz4n50pAwuNNarYZsQnrY2Ws5iGULDzwyDo88cn54SkGPtA9HKOUkqXM0tk0jhWKgMR60pek1FMJormcP5DP7v/ptf/5GLpl37pl37g35um4W/8jb/B3/gbf+Nf+3eeffZZ/v7f//v/U7/1k6uMhjOCbLS2tO8wlwfj3QZlrQSOej+ilOCblTJlwiR6a51FipCioR89PkcqU7FoGoY0opCDQtZOQtSkEY3OGkUQw3iWG8jlIkegguzBJQ6N47mjfd58vORs27PfWF6/dpWFG3EYVAqEOBBULRV0HgsaO0JMtKYhBzExx5iomkoObOOIMxrrHB98+CGbTcdkMiOieXS+5s69d/ntv/U385VvfJuvfft7nJytuHNyzkU/osi4uw9Ynj3kcDFju9mglOHrX/8mn3v9JT7/2TeoJi1d1nzpW2/xzve/z+mDDzk/fYwftozbnrpuGbRhDB5Uxg8dKhUmU86XUg2VxdSnlQZtCFkkHfsHR7z3/nucnDxmtn+VyWzBMMr0ZXkRYAwkrYhRpgFHVw6ZTSdibM0KZSzNZM63vvt97j06IcSA2RnmSz7SLmdImScYECmyy3Rmh8hWprTWJbBT5YRK+dJjIr4U0SaL5l++doqpUGDk9/ZhwG8T31kuef/9O1hbs79/gKssi1mLLdIRbUQeGKPklpDBWnNJZjOleIokjBHct7NWZHspymGlqAKkwBHkc0oi76mcIwwjvR+JKtEYx6RtGWPAak0Iga4Xg/au+DRalyTyfGnMFKnrk0fvkqD1Q1zz+Zy/+lf/Kn/1r/7Vf+3nKKX483/+z/8PNlEODw9/6PDIf9WVjWaMiTomlIqYRpEKOROtCSjJkEiBGAtZMyu8jygrHcYUIiqDiRGdM6r36DoJvS6LRCRsOymcUhCiZoikQQucI4mF0kwa8sbiN17AANYQhkROmlQ5bDtlcBeX8hq/XEnmmXMoMqaqMNMJ1A3N8RVMU1PvLej9wHR/gSbjrDSJtNZo4c0zqTVxlObQTmaltARNXk5ktUGpJNhrtXvvM3EIQoEs3WhT1eTgmc9nfPozn+ZLX/kKv/ZrX+bpm7eYtg2+D8VTIT/D0K3JWlG1CzabDj+KdKuqKqqmYu9wn8pZ5q3jg3eu8O77q7KeiIm4qhTkBpQlpRGlKlxV006nXLl+ldVqxauvvszzz9yirhx972lqh3OCLldATrJ+pCy5MyHK8x3GUTbqviOMAZUSIStiDmyXW6JKnF6seO7VWzijqLWEbBsrEhNrJYBbAqm5XH92z7hW0LQCiqgqAVEkr0rhC1VlSX0ia83kYJ96MgFnGLc965NzWddCJGwHtC0TQ20IKeGqCpxjO/QC96gbKWRyFu9cOyVmBC3vBVGfokKFhBk9ikgKnqwVykgTSQcJUI9aE7Ii5IzVlqwSefSkIuuKORYipy77ckYHaTiRBJaCMcTSwEkpoZr23/iZ/fdtDdHGAor9gyNB6+eEKXuIUomtHzg9t4y+pbWZcVyhrEVly7C9IKw2cBhwWpO6SL9ObNcZnxWr5Ypx6FieP2a+2Of85DGb9Q0GnVF0rC+27O/PSDnRbwVxba0DPdLsT1jkOdV+TTWpZY/QIuPuulGmJv1AKHIqMd9rtHISgO0Hckxst1s+uPuAr37la2Qf+fSnP0tVixfn9vvv842vfIVusyX6QDOZMJ9OaZuaw+Mj/Djgx0BVVTRNQ9tMmE2nPCwSTa1kuiLALCQEN4ZLEufZxRlDv8aMFePYE/yAyTCdTiTYPcN0MuVTn/4kt27cYDpteOHF57l3+w5hvWbwCb/dgFIlooMCRRqpzBxTSVaPcZZWt2zP1ygtAe4qZapKM5vNee7p6zSVpZ00QvsFIY1+BCleFI1orZhMp4iCNeBJzOdznHPYymJQzBctp+vuEshhrZHJszEoK9lns3lLGD2+WzJpKtZRJMMpRZSTAPn1es3jsyXfefcBZ+cdwxDwSYOrSYNkGoUSrr686PDhhL1ZTTuZslyey8+YE6vzM3zl8H1PCj1Df43nnn6avb0F/eBZbx5yeHTAu+8a/rt//it8eOc+P/uzP83V61e5uFjRtC3OJRpAV7b46AQSlrJgxo0Wj2QKkZQ1KXsJYQ6RB4/OefjonL73AgPreqy1bLY9Wim0Vmw2W8LY0G07jMpcuTJF6cRkNqVtK8bh33w6/cNe/9YnS/8uL6Uvk2AujXWgCCHinBzuxG2xI3mBTgFjDDk7Rh9wVonc7lIWlkHJyUUbqCtXusOCQKyNkwcURVSgjSzKOmcpZkrQI0oJxSRI3kVIgsvWhaBy86BlPquJQKWgtWBVJid5EHJK3L9zl/lsTjWpGbMvYABT5ECelDLdpue99z6knU24cnzEteND9vcWLPYPeOt73+d8u+XR2YphDKA1X/rSV0AbPvX6Kzx4fMp33nyL07Oevh+YLebEqPm1r3wTUiSjsBr+f7/0j2idYtJOUbZi2Q1s+xHvR3L0ksejDF0x9V0ObqKo0JPA02VDKRIBPgo7sELsulivmFqHdi0hJI6Pj9g/2Of+3TuM45Y4enlfmgXtYo/XX/8ks7alqWtyysymC5R6zDu3H+Fz6VpGeV/kzC+4Zk3JDCkafekglwkKoDCgLGQNKbI7yQoevRCDysIIoIomLauMNkoCIJFgR7K8BjEG1qtTfvHn/xt+y8/8NFevH9ENIwezqQj+lWIcBrbdlradXBZxMSUoQYaxTJq67Yb5fC7IzeALgl2JobeMuhVyr1qlqZzc68aPMIi2eDKpsFpTJcvgPZvUE1PmfLNi0rY0VXP5dXbeJ7XbCdQTXP8OR/txvnySadvoI5VxqJRRQYJXQ4yCO81JQj8V5MoJkMFagcNYK5tCwTJrBaqupGiOkeBHxhAwSpFMIHtPAJLSqJhF9qciJgaSEj8H9CJ9shUBjTIWlGVMCWxNMorsbAnMzSSj0U2NPTxkevUK1fEB1d4cbaA5mOFCgyZdUom02sEddJFCQFRKMNrF9xZDkCweWyZWSRFCR6bkiYSEtZYUA1rZ8tyADyK9Mlbz2muv0E4mfPVrX+dnf+ZngIzTAo1ABdAR5Ryx79GTTExKprmqwdYVR8dXcNUEd/MqjkjT1AhxSZoIzzx9g//lz/0Me/N9/t//9d/h29/5pmRMKWgnE4xx3Lz1FK+//gmuHB+yHSLbrS9+lx7fbxm3HU1dS9ab0thKENE+BPHYFJiJJku2FUqyhZTm/GLDdjuyvzeD7GU/KFKQEMtaqNTlWqPKMy3YfSkYTWVBaen+Bi8HJquk86o0dW2YLWZUWjOuVkwPD9leX9McH/DwzXfwyw0xeFw5oAgFE3A1ZjKV4tcosnEyNQiB5ByqfH6SyhdSJmkIOeHHkRwgDQGTFXr06KYhWkt0hjgGktVkbYhKoYwj2oxRBp8QgllO5DESsmD4dQiyhhpDMgbvRwmp3EFRfkhQzL9Pl9KGF17+BMPY8Z0v/SrT6YzDq8eszk/xfmC62Odi4wWIUgfieMLe/h6bdc+4WbNsoF965m3N2ePAw/PEw4se1+7RDx7IxBzpy1Tu4vSMrltxcDgjD5Fb14+IQXJ7svc4N2G6N6eZT7n+1DHGCjZfwaWsbBwC/XaEDE1bo0jELD6ynAR53fcDm+2WOx/e51vf/ibzxR5PPf2MkA615a233uK9N9/GdwNOG/av7DHdW0DKzBZzhu0WV1fUdcV2vWY2n4kfGIQMaRQxiWdWxAwKZZ2oekwlz2CZRPsg4JaCQMAXxYrRmraZcri3x40bV9lbzFDBUxnFwXzO44sNKUhwsh+D5NChBIISM0YbOUMYxbSuOb3YYo3l/PQxfb/mueefpa4FPnCwP8Nadakeatr6Cehhp7jIEhdy1TliloBVayLXr+xBwZVX1nIwa+iPF2y3I6v1mugToQTy6v0FzmqmTc3BrOXD25nlOfTbDc4YaleRg6znbduw7QYePbpAGysNvTHRtBOII2HUDL6nsSL9H32gHx05Jw72D7jfD6y7NXUzIyHRKo8ePKK2iu+/9yGLvTl93zN0Qka8cvUK52cXfOvrX8M1LT/1H/wUV44W5JwYxnw5XZuYihDFKrKzQegkZwcfPGfn59L4DZnVpufBgzO6rdA63dThjBD22qohpChZWueJnAb6dUfb1ORgqSc1WlfEYPD+R/eMf6yLJdhNBkqOcN4Z0MuBQD/xcuwM9LuDuisbmh9HtBMmvCSWSzd+t24brXBARDaunUMqBI9z4okKORW8ZCqddyNIyJjpxkhETGdimhdDuDNwbE0xAmpUwZwLr1+hTM1isWAymRQzeWa9XeG9R5FYrtbs7x3S955HZ2ve+/p3OTu/4JOvv87NqwdcvXGNz77xGr/2pS9z9XDBcjVwdt7z/Q9uo7Xm+q0bHBweMZ/vs1pvsREm0wUP76+FNhM8SmmG0RO8EPzO1gNaO8SjqwGNNpUYSQs/8xJYIG9ISXlWpRutL30vICP4SDlAFH1tVbf0XtNMZyz2BIPZbdY8um9xVS3a3GvXpfPjhYyltZIQtxS5c/8B603HerMkZylQQ+iJcSzFUjnYq50pWeQ2lE6RVvKepmIchITapegVCc1lMahKEB2gCpK+djXK+kL986Jgjh6VAjlH7t+5y//jP/1P+b/9hf8r07rGj4G6qoCMc479/b1L2Z3RiiY1jD6y3m7l/ivFz+5woUBogJSO4UezmbIUb957jDFCwyv36Dh6bFtTNzVJQRUT237AWM35asO0TUyaBqPKb6jUD+Q+fRTZ/7G/TDlcWg2VIalMVCKZTTGLEX5nUvWysUeVyZVo1U3KZCX3fkQgIyEjqexDOYCkSEqCc04xEqJMMHIhNOUskIkYM6qqCdWIahps25K3W9CG5BwhC8hAZXmmQsmIU1pR24pq/xCFoqpr2qMFzaSFHJnt75NlaZHGQAGJWK2LdEpoftZp4riLcc2X91NWYGtDHWo26w5nRfqLAm0LyjwU2acSuXWIgZs3rnHj5g3u3bnH7XsPqSfPse021M6hVSSHDYSeqKHvN2AaAhofoUqJ+WLGYtqgjGVWa/YPDtDKgAplQuN5ePKYk9PH0owyEpBtrebmU0/xxidfYzGbcnSwwFlI2qDbOV0MEHty18PYs14vicZgjWXwggkPQXJmKmcLfl8iCax1xK7H5MzZySm2qnDWYMoxLinNOARmk0aktjtpa5J9I5fXWp5PLR1XtWvc5IL9VwXIoalqg1JTVE4QAmHbU1UV/eixxhFrJzKeQfKWohLPri9NlIyiqVrMYkEcBlKwmNmUpJRIYFBCuzNaivsMyntMWxOMlsnrENB5QFcSjBp8QZ/HiHKaFBJZyYRaVVYmoqaQ9kqhmCmFkpLXKFtLrCvCtiNKLPP/PM//v4Wrbqcsjo4Z+i1HV64Rgycrw+HxFS7Wa04eLzk4OGDYelYX7zJt5pwvB2k0hIBln3vnAw9Y8+jBktMuMWKYH1Zo7UAZFosj6rrBVZYHDx9ijeb4ylX6dM6Va1dRyLNorcWYEv5pjOxBRdkxjkJg67Yjvit+suIxSQXlHMcAOhNyZtuPfHj3Id/+zne4+dRz7O3NqdqG7WbDV375Vzh5cB+VI1VbM2knHB9fEf9T37E9O6edTElGZN8+BPl5rJOsRBHGS4GPwsdMP4xst53kDHqPqxpQmWGQiVKMCWfr0ozOaGWwxjGdTVmenfPg9m3ilWP2FwtSF+gvtmwvlsRxlGa5USI/b6dkU4F1Il2Mibqpydayf7ggpki9mVE5i7EOaw2zMi1LpdlhjWDDhcIr3iAyhfQrVFqyAFFizrKnGwEnKTKL1pGPZjw2G5racb5dYZ0lG00fIlW2pKxopw1XjhbEvqdvarpVIuXIYj7FVRJgCwKY0OX91JVjGDasNxuGccSHSO42TLQRwNC8Zr29AERlM242OF1j6gpTSL53P7wrU6DoeenFF0k5ceXqIWP03Hz2WWbzBat1x1tvfY/5j3+G1hiMkmHFcrVBAfNZXTzYst6FKIG56+2WGBPaZLpRfGsgzd/9xQKSxND4GHGVpRs9y4s1OmZsVuxPZzRNQ/aa9UWP9wnjtOwhP6LrY18sAZcQhycHuN2kQD0BPpTDZcoIJlNlrBaS0DiOQuUoX+uSKlZGB64cALp+EK+KUmKs3xE+KBOALF2KXH6efhhIOVFZkVEZY8o40RRWucjT9M4gkhOZRFKRvu/LoVk4+KfnZ0wnLfsHeygUB0cH8rO5gZdffZ7jW9d48PCMx49O+fp33uT6tavcuHLI8fEN3nz/Hp0PdON4aRQ/XwtGsmonHFQTHj1+RFVVrNcb0A6ln2CNbT2FVJGTxlY1yQchJCkJq8wxiqevvMa5QDN2Uwmh8TiUtuzCyYSWki8XFpRlb++Qppli2wWYijEkxkLDq+qGbrPG2Apta/phy4f37vGZ158Tv5lORcrTMo4DH7zzPcRsmUQOGEaEEggQZYKnAGUxRsyewcv0LqtMyqLzzbFQ5+CJnLOEEitlyMpi6waMorEVdT1Bl7wXyJic6M8fwbDFZJFrNq3ITSrrsNZd0sUMSPZOMaqnmLDGYhq5//pewhDVLhVbS/dap3QJitjJ+pRS+FFkBDvpqbWWdjpl6Ee2/YAymtpousHjU8a6Sg5x2rDqOrTVTOpG7nmeTJEu0eHlnlcf88nSmMAbA0rhg2iukSYtKcl7RswkrQhZC646ZYbNgKut+DJCLp2zLNSwMQiKOWd8yCQrB+4cEknvwp0VypkSCGxkgGktuWnJtiM4S9QOO5kxek9Qhspo2fiUQm0HyT1LmaoqAYvW4I4WLG5cYbKYCnShoOB9CkX6JgWwGG4lt0srjTbyDAdTirdSWMcYUVmjjaZpa/ER+EDV1B/xhyaZdMaI1ZVMK3Jm0ja88sqrfP/td3jn++8x3z9kOqnxaaAGUr8lJQnfHsdAM7U0kylxVOUwE5lMJ/jR0zSW5555hq999csEDyjFnbv3+C/+P3+XFANN0+AK5bGZTPjpn/wiv/k3f4Ft70EraSrYitVqxCVNHwJ2GKj8wNBrttrh6hZXVww+CXUui2fUqUztKhQKoxSDjyirOXn4mGlTU1kk0DtLUn3bNExnrUzWs0BbckiXctacM8ZYXOXQpmD/w25KL5JetdNFaE1UMoma7s9RKrNdrgnBE1OQnCKfZEqT5f7yKVID2ViytSjrxPOUM9GPZGPR1pB9IEhOOgRRNFB+njiES9lcMAoLpL4XObNRZGNJRiay2li5Z5RG+YwvHfvUSmGp0PiY0AKtIiaJHYhZFBpJK0Hif0wvZSqGMbE4OOYTn/1xDCKL3m7XbN9/H1Kmmhzw4Pb7rE5O2VZb2nbGjWs3mNYth82Uu6dL7tx/wJ17t8m25vDG81yslihlMNpRtRWTtqZtWh48vM+t61fZri84PthHK4qvJWBMI42bQlBNORN8wA+eoR+JZV/VVs4jwXuiVyQy3o8Ya1HGEbY97733Hg9PzvjEa58EJVOC8/Nzvv7Vr3DxSM4Mzd4eY9/Tti13v/82BsnGcYsFVdvgY+Lk4WOcFWnffL6Paiq8giEEukG8M6vtFrRl03VEH1DG0TYTNpslilSKKglst+VZzFlCVydNgw+enDLzyYTVwxPuvPMB9z64ix9GElBbUQQEn0i2oZ5UdGMk+5HDgz2qSUNUcLA/R5cpbBg7jo732NubUVXiyTu5uGDSNBwe7EljSJlLFYh1ToAFBc2fkaKqrSv6MdE6acjEINLaOgb2pg1XDxZcnK+IIeFcRV1JaGwYPam1XL92QB57uu0G6yqsVsxnLaZyrDcd2lq6ENAhUxtFszdlvfQMMTCGIEU5RdijNf04kGLm9HzD8uxM8uumUzlbkHDOMpvWfPD++7z5ne/wW/7D/5BPf/oNNl3H1evXmc7mPHz4mOl0wZ0Pb/OVr3yLz3zyNWazhhgTde3Y9gN1bWlKgK+8HkUCrgyVjTgTSZWmc4a9/YrJpJWMumxQWVMjuXk6CdRsPp/gtx6jLWGM9NuB0fe0swZUwIf+R/aMf6yLpSdIwmI8Lzr6J4SxJ5936TNR4pfJWdKxlZLUbl8oZEZT0po/QiYr/hZjDUbL5xvUk4Kq6G61Rv5efqLnn7UNdVXoIMh4W5EpeyYghdt2u5VxbSEntW2L0UJcMs5w48Y12nLIDt5L2K5SqEnCxchsdsD+XssnXrrFhw9u8Cu//h1OLyI53aWaaD7z6TdoJw2mnvL+nftstj3n5+fcuXuPYRipq4rl8gKlDe10zmLvQFChIUCa4IeO7bYjZI2pWjDCuk9+wMceYpBDmJa0sZ1HLGeEYuMcSjvGcRBttBJtuy1eiLqeECK0kxknqw2zeUvX9wxdzzB4tLY4V18+dIu9fUHvxsw4erquZ9rO2dvb5+TxY4bNmqqqxB/iB0Tot5sNPfljbM1kviddr6wlHDFFVE7E7EV2lnZC53KfIVMyUzUo11K3E7StAIVPimo+x3cdk+mMxaThXr9BxYCKntc+9Rovv/qKpFJryUPQKGy5b1zRP1vrijFTiaynchitJD2+eL9SiAJ6yE/u81jyTYzWRO+prPgmklKM40jYeQViYEyZfrWRaYbRqCRhthrBocvtWeR3/4pnT+UnHq6P8+UThFLY7CRqKQS0dUQfRZ6lFSpkotZEhUyOyqRHlY1PPBi6SEpkIp2sBevJXjwoKUSR9mlFTqBjJjrHOEbqpEReZwwxZ0zdoGYRNY5UroK2JhrDmBPBe/A91koo9higrhRpHGkWc/wY6JcbVIpUs5lMjazdjZYEXJGfePYyggoOOeOcvcTCpiIt2T3PSmuaViahWuvLCa9Co4zCaCUI38qhncPg+Y1f+A38o1/4R9y9d4eXulep2xqtZXoNDjVEWhvYuDmrPpEqqCctde3QSlE7A7Ullk5z2844H07K9D+K56/sBdrIz/jUU0/zhS/8OJO2BSewhbZtWQ0JtYkMY8B3kWkMmHHAWEeIAYsmZU1E0xW/UkiZae2YKIurLLbIliKJtO258cJ1aqdxVpGiwVrNZFrLFLYQxFIsjSRkWiRyP3cZH/BRea8qU+WQilxQQdVYmeSMI3EIuLZBOYepK/J6Q4ietNkwpkBImVS3+CRhtbaZQNUwpIzWVrLAkLUzJyXF/uhFvpfk50hkXMxCctSmFEyCYk85E5XEaERKTo+zhL5HGU1SBp+LVNFHker5UFD8YLRh1IYhwRgjQRl8joR/xTrzcblSFAl9RvH0s88zn7WEMPD22+8y3TtG58D58pzNegMpsV6eUjlHv9kwqyY8fPwBdx494M7pY5bdmqr1zCc1p+dLfIxY59jbP2QMkdW9e4y+J0TN6nzJzevXuX//BPIxbeuo60SICqUSKiWGYSSOnrEPqKwJG08YIsYmRokIJqTAGCOuqcE6Nv3Au+9/AMpy/fp1lDFYU/Hu977Pm9/9Ntv1RvZUZ1mdntGv1ixVRseIbSdUrqKylum05fTsjKHrSE72Cx+9AIeqikRmHEdiivR+IG82dMMWnzKt02y3W2bTBX4cCEHQ4RnJMKKoHq5fv86P/4bPo2JkPpmyvP+YB+/e5tHdBwx9zzAKrU0byxiiEAWrCm2sNGFSZjKpUc5QWYOWngdWHzL0Hc8+dZVrx4c4K1Pgo8P9y7PjTsWUd56vspZqJWoFoxW1VbSVBpWxhidra4zstRWts1j2WW03PHi4FI+o0TSNYeoqpk2FzoGmbZjOFxz5KL11LeuKVdAV2vBkUjGZN7KnrxMhCMUwo8AYmtqSSYRR4hqquirTvI3YJJRI3+bTGte2tCHw3nvv8l/9l/8lo/d86tOfIoSR4+N9rHW8+8Ftrt24wdnZGV/+2td59dVXmE9anDPUtSn5SDNppOSENpq6qbDVRxQM2bK/cOQEMSpSFLx9GKVAPj9b8uDeA7wPXD06op5P0NbSb3p836N0JKUebUbgR9dw+VgXS7C7SbWYrsuh7ZKE9y9dTwqlXLqmYsy0ksyGH0dCSJJFoYU+lmMQLSoK58xllz1ffn9QSjT/xkgXxygFRrOYTaT4yUFM2OWgAjvTvJjwc4aqlgNEFE2XHF61QqnMbDa9LAxjWThTUvicsFUNSdrglauJIaFVpvrCZ7lY9nzw4T22fuTOvfs4DTH0NHXFtatX+fr5OWPXiRQxhpKeLVMgH2Ph+xtQFWMINBNZAMQgGhjHEZUKThkup2Uffe1zlg5XbSztdMbZ2ViABlzKkHTJnUkJzs6XuIlkENVNLYSmFOV1F4PYLhIOrS3r7cBk0jKdzuh6z/LiQgo8kJFwFDhD+cGLVLNkS5QOR9+PaK0w2uDDKAccVfDYmSfvdSiBxtoIZtpUVO1EPCTI4ddWNbZuaIvhd73tUUY6+InE7TsfoExmMWmxWpGylslmXWOMHCAF/x0u81kUsuhqZ3HWMgwDIeVL3KYu0jhV/tlqjSazt7cQkpk1Qt2R4SU+ROq2JQQZ36uCr5azpwQtN5MJtbWYUjz9q567nT77414sjQr6XQaOtpiQUDIYlLwYbVDO4FMi54TPXGYtZSOQmBgCUUFVVyQj3cVRKhhS5UhDQJeMnbjdErQmRcmu8SSy1QRdvJFGEZUugYaKZn8fPwaylntuDJ7takUwBqsy9WTCdDIlAc3eHIMmdD3bJGtZ3QbQlfj1tL4EDZAK+rmyUnwrucdyFLmyqjXsPFuXMlWFNZqmrggZOfx0o8ApjFCPUALBcFZ8Vq++8gIvvPQS3/3ud/mNv+knWW82XDnckxwxA35YMY4dwSq6ZEVbX6bRVQPTtobgWZ4vef+D96XTrMQHGIJMp60xrDdbYo40dcvx8RWmdU3b1HTbAWUdQ0wolXGVpusVTlnGZBlThcoOpSUwWNmKGDxoy3nviQH2o+Job4Y2ijiMYKBbrgl9x8GipSo45l0XuXLF9A3l0CRhx1qJ7FEpjXPVkyKUDEpkj6WtJuAQMlrOmMQxsDlfsb1YyjoUI2YyxfYD3WrNOA70o+Ti6Hoia1LlMM2E6cE+2lniIN7ErDVBCc1uVxSbqqIo2nGuImrx4vogUmQrYTJE5O9FpfFAVYk3IWpD8pFcyaAqlrVh8EGamohUdfQZrw2+nTEC3RiIKIaP8Tri/cjZySkxRJqqoRs8zmSGwXP12nXOz04ZVh8yX+zTaei2S9brC5yxLK7NOE+eR8vHLFePUaZivd3wvbe/zjB6tHVMJ3OR1TnD6uwhe/MF3vdM2jmnj8+pjGFYfci1G4dolZnOJ1hb0/c9MSZRvphM2D3v25HBBzyRru+w05aqdSxXK85Ozzk/P6OZHTA/PCB4T8qRb33jG3zwznsM3bbQfxPrswvyOGI05JCk4asU/WqJtQajLDHK0cBH2ZcvlmtyNtSTKcpYRu9l3wVZO2IkxpFhyNSNoh89Q98X+l3CmZpx8DiXaeqaq1eOWbQ13ekF64en3Ds5oztf0W260hRI4im3hqqqSdZhnQQHq7q6DHxXQO00Pka01SwO59Run4O96W75QyuFqys2214sGs4WqqXITi698yqj8k6KkpnUhqay9F7udecMpsjyhjHip46nbxxyfiH+cas0k7pi2jjm85q+G6gmExb7I8oa1qsNVhvq2vHo8UjfbUX2p+Xse3FywtD35BQwZgc8i5KvWPz7AUU/SnZWRjF6T1VLdITWDqUMz7/4EimOfOMrX+YXfv7n2dtf8NJLz2N0xXwBTz9zk3ff+YD9/UMe3L1Lt/06n/uxTzKZtjSNTP+8D+jKfKTBKlChjEHpiqo2ZCXxMlUl/l/x5Y9knwkJttsNla1o2op22pBCRhGJqUHbyGQW6LsVy4vVj+wZ/1gXSxpVPElc+kwyXObSOOcuP/fShFeuDIK/LRIUqxS6rhn9KJuDE6lYzvpSUua0hGzlQgCTiVY5RBSSzM6Sk5Uw5kHkbM5J5zpd5ms8KZhSSj+QCbWTAsrXU5dhe8FLpkVCJGeq3OCC8hX0tNOWvcmc6qmW1XbDEHv+uy+9yXe/9yFNW5G14daNY+bzKc88fYO7d27TbVb0cSj46Ipuu5FCLck41hqHUhbX1iJVM5ZxM4rNslCddh6HXREqAATxNJAS282GfhiF3LZ7QRWQBU+rdGaMER0CldIc7O3JdE7JocFVlUiJQsTVDYeHe3gf8Unx+HzFlcMFk7bFKHjw8CGuqvE+FI9OeU/KRCbnUlRrRQgeqzRaWUL0Qj3LBUOfnvzFLO8kYMgYXNWiXUWMGWMS/XaD9wLdmMxmxCThfk7LtCqmhDGa/8Pv+z/xv/tf/2+oXUUIoxz0nCPGgLP2koglkk05UO/0zz4FSBlnLEZlspHsI7mXw6U+WinB+xpjmLQTeZ0LHEOxIwEJxefy9TGa4D21q2iaisqUEqm8V0oJSSgXb9ruGdIf4wPO7srWsPWepqmYHh/gl2tMAoYgtDAjmHujFNnLpCBqQ9Si0daVlWDOFMBVAm4whtxUpDGILt9ZUozoukLVFakfwVrxhIwJZUsxhmYMiRATcb2VwkUbCWXOUtDatiWcnxOdI2VoTEU1n3F06waLG1dFIpszod+i1D67RzHFhG3s5XQjxEBlnEw9SvFmtJUcKaVJWUhKPovB/KNS510m2HozIP0kIT+G0VPXFufK2uUsx1cP+bHPf4b/13/+n/PB+x/wyuQTrLY907qmRqPaOedjQ58dm5AgZpxKdGNgHAM5QRh7xs0Wjazb3vegNNZU5ChyZ5IoAWKIrFcrzpdrqrZmGD3jkDBWYZ2sIT5lYtYk3ZKdoXUTruwtUFXFGIVEedGPnG8StbPMJ60cOrJI85TR9OstIcqkxI+JEGExE3/DbnlLxZcE8twZW4l6oZAAQzGwJ6TTnMnssP8U/yRkkYN6T+xHnBW08P6t64w+kY1hfXpBHEbGGDFW0S6mAm9Qiso6TIbQ9wLJ0QLy0BQqlXPkEEVWrIX+mbJCZ9lTVVVB7S6z5ZI1YCxUgVyNUmhbS4qe7CqSNYRciisjYbPZWFRK8r0T5LpiOmnp7o0E1UFdCtSP6bXd9gy9p7YNH95+QPIjs/lUuuMpsTk/ZT4/YL0+Y7M8Zxg6yDJhDDFRVzPmx9fxKbPdrBnCyIMH74lHzrXk4Ak5UdU11hrGkImDJ4bMetlxYlfMJy32ZIV1muliStd1co/5wDgOKGXE45JGaDQqWcZ+xC5ahsHz8L2H3Hv4iEenj7l54xppu2FmF3R9z1d//dd5cP8uKSRizEQ/YHYScKUIfSfwqX7gYnuO0QpTV4xDTwgRPww0E5k0KAXVpMZnmRxEL/7DmBLnF6d03Uakg8YLMS3J1FObirqeklOi6zcEP5Kqis224+1vvUU1jCgvjZ4QEoP3hBAYc2QIXvyVU0tlBNXtAasiKQSCDzhTS9C4MXjfUZuK+bQVSVx5pnek2c1aPDnWWpmsksuURyYzyuTL5n3lBK8fk1CSY4JJ46iMqKI0GR8de21F5TQ5jKgcmdaO2hmMMcXjqTk43MM6S+2EgJyL9zSMA3VlaWpHbQ1+HNiu12QlVL/sPSrXnK5WTCatkItjFNhMjKQcRdWgYBsCtY8cX1sw+o6nnnqO99/9gAf37vAP/8F/w/3PfZ6f+I0/gQ8Bpy1P3XqKO3fv8uxzz3Hy6BHff+82V68cEbynqqRgT8kyaVq0ES+mNhbDTKZssYB1jC3nd5F3aKcJY8ZWmpc+8QIxZZqmwVaOLgzErLBVha0iVa3IqWUcTn9kz/jHuliiFEoxxstiQ0x1cmiX7rz+iK6+HPJyFu2kVpIjoXKZCoGrKmIIDKO/zK+5HLfGnU31iYkvIxsi5dAqknP5eqidd0eVv1MIbElgDruN8qNeEL0jr6nC3Nt5Q8iyWSue4Jwp9CEfhOznxGuktKJ2jro94IPbDxlXayb1hIBiOplwfHjId978Ll/7+jfFe1DVrFdLQgq4OoqHJiacldDT6GXKFFKkaiaM48h0vmAcO4YYwCJp1QVlLq9zkRzqgosEcgwiccqBFASxbJwhkbFW0sJnzjGbTuk2G0xl8MPIOA6XGUKy6ERmsxmnFxfcfXTC/mIKJG5cu05dO5ECKiPknNL9VrvOuTHiB8gihcw5EEOW4Vwp9nISQIVMW2S6l5BQSVM1VIUKWLma6AP9akkYt2LqjYFNfyFTsc2GkBW6qlG24lM/9jr/2//kP+HmtevkGKSDVWb+WqtL+ILW5rKoVshitt10KK1oJxOIGaVkqtT1HXXbIlh80QbvQAx1LaSeUKiEWmsJjVQiCdpNOsfiaZFch4jcZh8p/CkLv1goLmtdLp+Gj/cVi9fCmkKFo/hMrMEHKZG1rOLElAgK8YPJcIYQM8bV1FWLihFtneTPIIVWHKXowhlMEvRy2hWq2pAqR+4HTF0RghTWUStyEDqSaSxYC02FT5GQIGQhkVlraQ4PaPcWXHvxGWztqJpWfC+6wD+sIeZIjoGUyuauxHtHQQQrK8+qTiI7zjwBDRhXMr+i+Oi0QcIQU+Z8uWW9Gdmft0QvhC2VIfrIaD1tK9lFP/VTP8Hf+zt/j3fefpuXXnmZmDJVY6ELVPWElAa2Y2brI5Pe0+7V1HWFjxGPyJwePnrM7Q8/JIZC6jQiYYshih/RlgDnnHjn+9/jn/3yr/HTP/2bCVXFTnjg6ozVyNcdMzWOK/sT9mYTqlqM9EYl1l5zvk4Yo5hPa+atJackgJ0c8X7k5N5jdFODcdx/dMH+/oLDPV1kxupy7ddaMqqsMQU5vCuIpOstctck70fO4vlMkt8W05NwdWUtzXxKGAZMjDirWVw/Ynmxojo6pvOB3HuCUoyDR9XSxdXWSm6bUoxIMep9QCUp0sQrK5N1oZkKfEdrmfjHkDCjUAuV1RJb4QPKVkIWiwmjFbFK5GwupUgxCz0wakVUSuIdsoSSOq+w6y2UMOUYBU7xcb2G9YbJfJ8+JvJyjS73pdWJcRjY3ztgu76gX0ecMeztCahkeX5KSpnpzQOeuvIih1eu8ua3vsbF6oQQvQBjVGIIG/I2Y80+PonypduuRc5adeQ4UF2/wsnjDftHrXiPjMZ7T7fZUjcNxhr6bYcxDmymX3YYp1gv19z+4C5vffvbnKzOePGTnyEoQ1s5zs/P+ObXvszJwwekIOHbQ7elqWuszdiY2J6c4Zxhu96SxpG2dmhlGfte/MxKpPgiCxUJnVKacfSyfoZIjJmL5RnD2IvkGDCukmBc46hcha2nuKpitT6R5105lFKsVxv84oj1yTmtcVgjjemx7wSCEz1j8LjRoXKmqhp5bWJm2HSE3pNjxIfAuh8wdUMujWdX6MNKVTgnz7FWiitXDsV7vmskpvzEDgIla07Wd1c8OzFFnDVMtLnMabRGoRVYrZg0FYtZw2YqqhMfAxMtRZK2Bl05csyEDM18etn8rKoKig+2iRFXW2xlUBZCGBiHEasVWUN/6UNVZFWT6GXip8CZihgS/bbn1HuUTjxz6wZny8cc7O+T/MC777zD3Tt3CWPg537ut3DGihgTR0dHbIcNL7z4HK4yPHj4gKq6iXMyCOiHEa0NNQKj2llSYozEJO9/ykISjknWwBQTVW2p6sVlETV0njBGwaPHjLIWPwY2OZNSi9J7P7Jn/ONdLMElue7JZCZfypF+8PPk0KNU8XukndQmE0iCvlUZUsIZi2uteDxCIELR+5fOOvAk6FZudNkAeXI4pxQ1PIFLyOFKkLc7bbr8vZ3vI4tETO0OpwWSGQPGCnFIGyPa6JxIJQQ1J0VTTcgF/ZljoutHfBh5+voh/4vf/Hm++u13mOztcXS4xxufeIGjvZpf/uV/wenpKcZY5vt7XFyckwvqcXdIsQ6UkY56SpGgAigBVjR1Qxg6KUqieAfy5cRIkZURL492qBw+ImF0pBwJ0ZPRmKpC6cAw9sQEs7197j98wNWrVwg64qyjKyGZlatAaep2SjNpcLVjDIFtP7Dteu4/esxqucKHAUWUbCQkCVxyYszlFEyRSdELrQ5dVjnFzvS+I/flgvA11qJVlt+537ItnqIYpdtWWS2m5xTwmxV6lIOltQtefuPz/J//L3+AG9euoqzBxohGKFqqeK+sUWizmyoqUgj40XOxvODBgwesNmueefZZjo6vyEucEnVVQym+SalkV+lLSY9SgmLe+Y+sMYSoymIElEJV5EHy7sQYJadD/k0mcWUBk4r1I0XSxxzuAIDZNVoUadvJIp4zOQiuXddWoCaFRCe+kIRFCHZYQ46ZHCFX+tLn42MUSpgxgClp6sVnB2SlMTmTtAYn609WEFKQ7CUrha/OcqA0WnI4Bi8Btx6oq4pqMSdpzfnZiv1DCybQzBqmBwtcW4vHRPS9RTuen0ziy7Qo7wJHySVTSYmRn50WH/woAIBUJh9CIc1sOpHQTBpTfFAZ7z21bkRa4R3PP/cUL7/yErc/eJ/gpXMqm7zCEdhXhm3yEpYoFGtaq6B1dIMU8G+++Sb379+XYGhlRYdfntmUkhQASpoLq4sl/+yXfolXX/sEt569Rao0jZPGR8wikUnK0DaW2byibR3WNTir2Qwjm1ECZ2ezmivTitooyJGciz4zw/2Hp9STKas+MWrNsTPi9ymTup1yQO/gEpR+gyrPZwhSqBT/QipymJR2NEKeTH4VmMqizVSIctstqR8KWCFLsOb+HnoYZfrvBHOPKV4AnzAa0hhQpviUFOQsP4uymqxKEeQMwSiUc5ASqjbEsv8Rk3iYrEJlL1RGY0g+QBYf5ag1afS4lIhKQSGIqZL1kq3FfcRLo5QqcIp/h8/8v+WrmQrSvtsI2llbQ7e8YFpbppOaFAJjHtFJSIv7h9c4PzsjLc8LYTRxdvqIg+Nr3HruRbphyzQMVE4zndcMvSehWa/P0NpiNAx+gr844fBwn/Um8ujRyNHVowIoyixPz1FKMZ/PSvEwoEzFZr0iKoWZNdz/4B5vfvNN3rv9Phd9z6ufeo39gzmNq3j88D5vfvdN1qs1MWmU0fhhpKqbonKJQoU0igQMQw9BKJDKGIyxhBhpJ005N5WpfILNZoUftwQ/iOwueMl0ImLaKWSoXS33ccpMJsdYpQlhZKsMxrgi8fIo7Tg9vSCs17DYo0YRh05kzIAPvkh2A15pur4nmQ22aUlKJrbjehBKnRX1kHEG4zRJJclN0+pSPSTnn0JGVhofJFPRGGmEy+ReSVOTcvbMsvbK16Gg2UGVZz0mAYE9c22fvbaiqSqMguAD20Ea+X2AZZ8YY8lzM5rkI85UkCCGSNvUjH3NwcE+Xb8uZ1HJ8UvB45LYLcYUiUajqBh9wI+BoR9RTTk/GM1mteHs9Jz7D+7h48gzL77I+++/z/LxA379V3+Z5154jpdffpmu6zk43COFKV0YuHL1OtZA1/e0jZMzTkak5CmXCVLCh4AvU8Xg42XjKKYkGYZaYwoLTTy2AlYafaLrAsvlBm0VQzcQo2Dl++5Hp3T52BdLOwa/1iVFHlVoT//9z9kVNDomwZemhNNGiozSUSXLEVEpCfKUg0aUTixSaKnSFZC6oCQSF63obkokkpknci/BJ+4yafITzwdPpl67rJ+dUf+j0kFjDArxZhljGHwuFDrpKAzrnhgzjx4/pmkqnLNsh5Fvvf027XTOT37hsyjT4FNkvbzg3Xe+z7YbMa6iaSfceuoZ0LdZr5aM/YgplDafJIw1pVDypUQGtkNj737XnJ/QA2XiJl1N10zkJg8SIGnQgt5NshDtist+GJkdHHL91i2S0tx65hluXrvC99/+PnVdSDc50zQts8U+w+DZW8xFjpYSbSMUlvWqY7vdkKJHJ8lGSVkVLO1OkifYZsmzCgVzLodZirxxV6jKZ8uiF4Ms6ko9KYAjipQU1gkRD61IHhl7m5roFK989vP8wT/0f+Tzn/8E82mDxtIog8OidUalzHq1wvsRsCUR3DJ0A3fv3uP07JSu2xJT5K033+SpbcdTt27JFPQSTKIvPUQUf9vu3rfWygIYZWGqnC3yTXmvdjJPxRPAxC50r9i05XsoyR1CFzJeSuXA/TE+5SB5XGQYNgM2RJE8RVkPog/kvpegxpSIOTF0RYJaJnDRB7nntSX4hJ5Kdz2WCYtqavJ0Am1DToHw4DExC7gjG0UqvsicpEADXWS2kJqaISSRUY0jWSuGFOnCyGQxw82mxJzYni2JY6CuHPvzCcaZ0m1MVKYiRy9h2TsUvpFGTQjSHIkxYhTFNBxRRgzRkrkka4CxjjD0JJ8kODErFrMJ9x+uON8M9KPlYCLyPmeMZAZZRYiRpm35zI99mvfevc3DBw+4euMKY4y0zpL6QKvgcNqwshFlNK7IgCeVJfjI3YeP+PUvfYV+HIhZgpkzyCF/3NH4uJSwpWy4c+cD3vzON3nm2etYVzNpDJsuXBqvp/OWxawmGVBO/F86BbIy+BCYTmqO5y3H85pGp6ImkMJsudpw/+yC46efYdSiUnDOlC6CJnmZhJtCogQum2hKSehmSvFy+r0rsvjI/0ORwaUs0zxFAbV4sjb0vefeex+yvlgJ2t7ZS7n2Zr1h3k5k7XKWpDMxAbbcm14KmRyliMo5EU0S5HeSLDqzt8BaTdoOIhHMAjFwRhH7kThGkoYc/OVBxiNY5TprBu8lfykMRB8Fze8MOUa6kDBWiorkB3k9PsbLSLfdsL8/oW1rrHWoGMmhx5kKMyYODyZcu/ICi/mEK4eHnK87hv4us/kCkdtnaitREkobXnzlDcKwxuoOH7bYY8vJac96e4ZKcBoG+qHncP+Avm9QLVBNcI1jve14//07tFXN1avHop7R0PuRfivRIFpn3nvrfd568/u8d+d9bF3xxo99lsPjAypnuP3+B9x+7x2WZxe00znKJMnqU9D3HVbJbiq+48Ty7Jy+62hrkZG3TY1ra7S1xG4oBUNCFQKn0YaUizInRTKJlKVp2W03TGcS4DqbLRjGnumkpakcddWgjebuvQ/l/JEU2/Uate1xIWJsTcoR7/2lBE0bAymSkpDVUk4Q5bDe+YG5D/RbIbdVdUXYNYyQ+BdnNVXxq/9gZIYihshquWKxmJezXzmzpVTsBbp40XeqoswYkzRrYsIa+ZqhYPinjSWnutgYRK3kY2I7RFadZ9WPZbIyMJ/U4ue0Mv1XSDP0+PiQe3c+YHVxTiahnaw3OQ44NSGSRZYPIm9Egq1X6w1ZacZhpNKW+eFVHjx6yGa9kXym3nPl+g3SOHL/7h3+0T/8Ba5dvcLR4QGPTk6Yz6bklHl0csqVowOZfvY9etJKs0iJf6nr+2KRkdfXe0/OsoYGH6QwionQe7QTqd3gozS0tWbdDWx6z6oPnJ+csTo/J5EY+i1F8fwjuT7WxVJMCa1N6cyoSzPd7qD7A7K7XDobFF9HlsIp5iIhiDJiNiUIazftsVr8IhJOGS/zMXYTCNn81EeKhjKKVeoHvvfu31WZWMhhm8s/ZfD1g9MxvdO8OmJ6ktUUQmS97OjHgawyd+7d52vf+C5DST5+441X2axWrDeeMbTcevo6+4cTvvWtd6CaUNeGxeFVfMpUTctkNpeHRlucrQilCIo5oXJJsi6yP63kUJCSdAoA6TTKKE26M1m0sNo5khZNf0oChUhZOoxm55g0Bm0bmvkh1289zfHVY7b9IPScmHAlK0Jw8CI/mE5atDFcOb7CtGloXM20ruk2HdvNVqhLameXSmUiIveF5MY8KUrFmyG6a11klVmSgeV3o6SzK2ThKTJKpYUcg9IS9merMtpPUAmOXAUwteHhg3v8o3/493np1oKj/QOmxqCIcgACUJm2rQXcEILASoo/YLJY4FOiG3oq59Ba8fjRI6wxPPXMU8QowaFKC8HtEiFu7Q/ce5d5OYDNkE0JHd0dylM5gKaELge8nWdpl3+yk5Huin/1kUL/434l70naEKe2eAHEFIxCENLFpB7xhJxJXoh2VS3GdQX4FEWzTkbt7pG2IWlDspZqNgOVsCGguw5QklvjPSEkkU7UNbkfyFbyM/RsShxHKIHPWVmGnceldCxd27A5PSemxPL8gno+wzUytcRaYkyMg5fwUy++GKcrkTB7L56anCEb8a5YVbKXiucwC+UzITkpPqZLfL6zcLA/4+6DJcFHruzvYZS/lJvFmBjHAVc5XnzheRaLBd97+20+82Ofot92TA/2oGlwWjELCYvBNhXaann2dWLsO776la9y/+5tiVowWmTB3uNMxUBPVr4cAl0pQhKb1Yr/9r/9F7z+ydd56unrpGpObRWzxmKyTFfa1orvwlYSejgGYgSVFceLCYetoVJFFqcyY/BkMmerLYMzVPM5nY8cHU520XNyGMvSadZWACCyNeWy1geZJMVMCFKAhRgJBdgi3lY5LEUfyNritL5sWtSTCevzc87PllycXBBDoplNi3yyFFTBXxr7Y8z0yWNnFbppyeNIJMtksxKpb4wZrCMDIWdMVcN0ArWsI2HdoZTGBkEOi8xOiWRPJbKWBlQck+RttRWBUkipslfGXMxzWaTQOjKG8bJx83FeRfKw5urRS2Qta2gOA9ZCbQJ+s4a9Cmtabty6znYxJ9+5T3ftJut1dzlh7buepCQ7aRgHzh9FqnrO4SRxvjqnmU5YeIUftmQU05kcfK1zXD0+YD6fUzctq/WanFsOyyF20jiUc/gEtm14eO8ht9/9gHfeeZf7jx5x5fpNrt+6wdWrR6A0X/vKl7j97geQMm0jBN6UlYCWrGHv4IDQD6TQU83mrE9OCOPIdDKhNoaqqYGixslZpkZ9L5JC5xj6AaVlKiQw8DJdzUpUPZVkS8l+FJlUjmv7B3z202+Asvz8P/klrl+/Rddv6LZrfBjwKlEZJ03FobvcyzGacexASWRHVehySsPFek1QRSprhSjq+4C2lpwUJAijh9zsRsKXZzJxXii00Uynk49AlsSGoYpkXT6YyYXaGWLBiWtFALZdwIdI30fWfaTrPZvtSMqZtrIoZ/EhsdqOjFnOp11KZJ8waiR6z3q9wVUC8FGIxxIyJ4/u4rs11go5M6lM32/Znx9iCwXPpFSUNHK+HQZPTDCMAVIkhsDJ48fs7x9CzkzamuMbNzg/PWUYA1/9xjd44eln2D86Yrlc44yQn+98eIdp/SxtuxAbgFIYlaU5Ejzr9RbnqtLkFUkmouchlvzMECI5arp+K41stUPhJ4ZhYLtacffuPdbLc0KQiXrdND+yZ/xjXSwBoIQgt/NXXBYlRQq26wbK9ZGpT9m4csrEkEoBs5uQ8IM+Iq0LrOHJ90i7Qq0g055I6XYH9Hx5GFcq7xr+l5/z0c6//PtOv/bk6+QcL7+XjLbKlCvDarXE1jVn5ytsNeW11z7J/uEBs9mE1ekJ8/ke7354wtRU3H5wzle/+zbP3nqGoyvH9P0Ga8+ojEEZS920KGMZhh6lFHXTCCmtbNzOOca+Q6tM13f4cigfhhFlXNngxdwYhg6VFIqIdbWYebMUoipTTNJJDMRaAuom0z2a6T57+0d86lOvs1wtuThfY40p8IOIMRIcLEGRI03boLRM/4ahQ+9NWK+XPHp0Kh2dy8WqvM/l5dXiri7TI1Omd+JZQRVaS3pSZOSdAFmVyZPSl1p+V7WgLdo46skerq5kEVqvyP2W4fyUrutYPX7Md757l+++dZfPvfqGGGBUKd6LhLSqpZs09D0pRvp+ZNOPZAWzxT5NO+H05DEpBW7dusrR8SEArirI649AQnbBsbt72Frp5oYkk0ijIZTAXed2iHJQ6kl482UTQGtBiSfRGO+AG/LK7j72oxt9/7u4FICGqDJhDKQoctIYduuEIqlM1gKezMXroRH0O8qgshy4Te2ksKlrREMgniadE2mzlgnGpEHP5nILaAXjgK5KXltl0Sljqgh5BCXadbJMu5IWyVySEbgUFlrjmlooVH2P33SkKwciIUSoVSEmchBtutKaYRipnExtlDGYyjyRYAUvwJtdQ2O33inxniiEUBkQufNiUnFWawafGEOkmVTyjEcJ1dmFl+4f7FPVNffv3uP05IxrN66QyVS1w6NwfiuyVWeZTCs679FasTy94MP3P2DTraXY1Fbu6RxxzqI1RVIqh4lYipWsDA/u3+erv/4Vbl79Wdw8k3WiNqAqhVaWeSWdVZUTPiRGZDo8mzYsas20yhiVi19DZHghZ04uluiqpplOcE3NtHHUVnLkYpBJr9b6EoAiZ61dISSvTfDjpdRu988+ZUKK8volkXJaNHjZC0gJaxUqR8lKoUhUosi7RTohQelYgwrS3BjGgVbPIWp0VWPmU/nZohSH2Vp0XaFnE5SPuOMDMIaw7oWamKFCDjs5RJlUOylmU5Lsr5SFnBhzZgwJPXrs7v0peWVKcjUwxjD2mTDEUnzxsa6W/LAh+w3WVtLcjImkM+SEcRX90BNzwDgBtdx6+iazvX1uv/8+MUauXr/OZr3F9yPWGIYMi4MrVM7QTBzr0XJjb8pi/0BgQSozncyprOHGtavM92YM3YhKiivHx/hh5MG9hxwdX8E2tVA9Q+SD99/jve+/z4OHj3h0dsqt55/j4OCIm089hVGRX//VX+fe7TsC+HESRh38wGa5xDjH0bVjtusLjNMY3ZDGkWEtQAatFFUlUK3ddGAcBrS1pSiS7L9tv2UcB5L35OiLoSFTV7U086xBa9mbnLHcvHGFz33207z84gs8eniCtYqXXnyFdbfmre9+C2crrHaoBH3XSTir1SR2MTKapnKSdWVs8RZ5XGWZLw6o24YxZ8IYIQ9MZvrSM3h5DkRk7ygjsS+lG6u1EgLqjgRc/lfOfMX6Aez89D4WuWnKXHQjp+cdRmm6MbLeelKEde+prJVpkQIfUmlCSyM3pMToPcOwJY8jF+dLZrMZKQZWXUdKFcfHR7TthHGzpN+uUEZTtTNc1eK0oqodWZWzrzUSHK1SadpEGtvw+PFjVOxx1uDHjgcP10ynM+qq5dU3PsXF2RmP7j1k3HQk4MWXXmZEcXS4z3Ta8MHdB2RtOD4Q4FVMMklz1qKyBBXvLDPGGAkjLpmnSulSUCeBV5kosJ+c6bYdPnpOL865f+8DtpslMQbqumH03Y/sGf94F0tlTLkLmRVAAj8gCduFMKIo0rb8EV+ReDJSzhie+Id2BdWlPEkVacpHpFnWWpGlXXbWd3+eFETwpBiCQqRWu6+5+5h4Aj5K9dttqEJakxEqyEFAG8tytab3keP9KS8eHrFZb0U6ZzQpeB71nq98603OtxI+OpstODg4wDpDWysO5ofcv3sfkqepaxSKo6NDvv/tUSYJWlNVkokUfUJXFU1TMw79kxyOtHP9KFzdysJxKSUaLjuFkkkkB8uk1KVpPKTdxEZTVzWTtmW9PKeycDCfoaNi220J3uN9LN3kGmMNXdcLVYWdhwB8SvRhlIybLJvUzk+zyzeRQUEJBaZMR0oBtwNkS6CueHNSucd2NLJdYRQBYxxRWSbTBdPFPq6ZMl/sM/oR7SrW55rh9AQ7mfOZ/+Bn+Nmf/kn+o5/5KSpjiQiF0UZN1ulyMmGd5fxsy9ANLJdrxpjovWccA9PplMPjq5w8foAxgkBVWjaf3WK+81h9FDt++StooUeSM65MOnbJ2qbkvuiCHq1K5tBHnwXgEj0NSBaEkgX2410qyYQ6o8HYS4xylp0QTSIGMSUbnUmIdj9Haa4YK/cwyhRSEjLhMFpCIq345LT35BQxusHHgJ5NCKstapRwWlPgHAoDNpPrWjZna+QZsiLbs1YaCBQZS0ryLIZC3Yt9pNv2LIoG3SnET5USuWDqVSFqKWtIg6D9sy/yWS0ezJ3sSukiOS73ggQmR0IomOusmE4c16/OuVj25e9IL0CUN6ng8QeuHB/y/HPPcPfDe9y9/QHPPf80KQuEIsRMO21RKeIRU7jRmhgT7777Pndu3yb4hDEOYx0xRKq6oarb0rW05XUvJL8kgJLVxTnf/OZ3eOONV9lfzAFoScynElDpVCZkzWrd09Y1bjJBO43VkUZlKiWSHUWiH0cykcGPnJ2fc/XqFfb2G6x17E1qtEoiL84RbSp5n4p0QLGDTxSJSSwenxyLbl+hdJkoZZF7pwLUyEoKU6NN+VgkFKle1op6b0rsPDFl1E4CpjS6djidGM4EQY9SKOtE9lneT+McWZdCTMk6oEymmdSoGKB0eYmQDUQrv1P2UUJqkWw9XSn8EC4R9OJDkgwykhDxFAmDQV12/YV4pZMRBPz/XAvAv4Xr/OKEOx++R1vV3Lh2A1dZ3MGCYbNF5czyfIXRmb39GXXbMDvY5/jwmKvXjlieX7B3cARasb7YULUNw3bg4mJJSpHF3oLpYo/aGU5OHtM2LVevHwsQJEVUVtiqpp5McI1ltVzjqorjw33qVqRQXdfz9nff5q3vfo+L1QqfIq+89gaQeOrGFSa15Zf+yT/j7u0PGYdACEMh7zmGcaBpW/b29hg2a6wC0zYsT86I247ppCV5TwwerVvcdEptJdR1vr/Hyfk5ympSlPiMTbfFOMtY9lmRpCayH7GuKplksFhMuHX9aW5dOeT5Z58hp8Djh4+x2uLHkTh0Jcjdk2tHIGOQZlDWinY6I3lPFSsq65hMWqq6Eu+yrdif71Et9lC2ohsClWtEEVKapoaMReTPIUrhdjkuKoVLqZwoi7eg98uzpHQBguUS6q4S1sA4RLYpc7rq2IwJP0h2VOcTXTeyHgJzFJ0PmCKl3oU4D4OnX3cCzwgjOcoUf7G3wFrLZtujQ0DlzMHhMf12i/c9PvTkKB/frtdgrPiSTS6mIM3lsTmLakgtZoR+pBt6Bj8yDh3r1ZLnX3iZ5595Bv388yyXS+4/PGF1cU636fjxH/8cyknES123PHz4kJxHjg8P5PycRCroKo0yLX0/4EfJk5vOZ2w3W5Znct8ba2kmE3RSrJcbzk5XbMrZ6NGDU87PVyxXJ6xXZ1jtZD62+dERNT/WxZLaVfdKl2KjeCjIWG3IpbrPlDT63eExZ5wRiIFSRXdbyG27DiA8CbHdGeWBIl3SJencFJ28fP5lJ0FdqgHZ+ZjEaC9vpHicpIObEmV6s5tAlXDIEMr3TgyDp2ka2cyM/LyPTi/QtoYcqWuL95nT5QXvvPse79w7p+sj+weH7B8ajvb3mLc1h/sTXGUxriKkzLDdsl5veenKTd55+2261QV1XRPJBC9mTpmOyaGpqmp88UyFEIkpY2xFVTXEGAnBo1wlv7+XcY4uhy0ZsOoysdIoWzOdLejGkfV6hXHSFfj2N7/FYrGPcxO2204ynRACjFVK0quto64sh/sLKufwfSQpxWqz5vziDD+OpbiVfhYU3G8Z+abCKchpV/wWFHzW5X4R/5jeyTuRoEVJD5GPRwzzgyOuXr/FlatXmUxa+pgZY2YyHtDuHdEtL7jy3DP8xE/9BJ9+5Wm67ZJlrZlOLOBwpCeGUBRDP7DdblmeXzB0I13RXTftlHH0tNMZN5ua05NHNJNW8rcQmSOIkVVrfYkfB35gynSZtuCjZLyU58EYgy6yAldVP1Dg74ql3bMgsIsn088foUT439kVciZEcF7IXdo6ko9yuKsr0B68aN1TEshD0lZ0+yljKlNIlDKdpHYyBUIJenwcSVqKWb8LNk4JM5uQ1mvSKpJDIhmDiUnu91QOECkxJuksaomnoJ3N6LoNujZUtcWWqc/06FAClZ2g0CfWMUYI/YgfB5wC56yEWjuHMlomYVD29MzYjyRjyEljbEIbW9pI+ZKiZ1yF9vEyr0M7zWLeYHWJbchIwZ2kSIvek6yibRo+8coraCzvff8DvvDFL6Ar8R41TUXwitgFHAm9C1v0Hu8D/XaDVQrT1Ght6VNH0zQcHh9xevaoaPw1xlhcUzH0Hc46gh9ZXqxkjUiZymimjQMyQwHlDIOXtbzQI3UKtFbL65oUYfCSE0Iikbi4WNNve557+Wmc1ezPa5pKOtDRi7RVJIRP1AIxFThGEnnJOAyCRE9SLGsjHWsVn3hAd2uRQHuCNIS2A1ZDVhIgHIYRqy3GWpEIOgu6lSDq0cvEKWWUFiBGtkqKZ6VRqtzPRa1gZyLTdZUjbwfSMKIGmW5mpQhapHQWIfPJQTeTDJADYMkyTCVlWXOsk7UzJnBF2psAq0QCH7PQ0IZLYMjH8+pXS85OHjN96hZJBbC1yAsdNMZwUC1oZi0nJ49Zb1YcXTni2tUjhnDA2cURZ+cX7O3vsbe/z8npOevNmvPzExaLBbNZw3RakXNkb+85coTJpGLoerSW8GOjJAZjtd5w88ZV2smE8+WS0ddsNiNvf+/73L59m7t3P2Sxf8Tnf/zHGceeK0dHtG3DP/2lX+L9d98nhcBm3ZOJuNoVGuQUazWP7t/HGkNVObbrFf35ionR1NbSGc128CQUi4NDVE7YtiGj2W439N2WiCEBm9UadKLbLhn9wOhlv9ZmF68SmU0WvPTiyyxmUypnOXt0Qk6BGzevcu3qFZFxaYW1layRQ0/OClPVosaY7jGdTekuzqmtwzkh6ilVYCuuQdmKdjoFV+EzQMJpUDFRa4XJiTSM5Epe3x2kK5dDf0aoxx91yO8mURowyjyxVSArgSnnjm4b2HSBswv5udEZksJHSEkzZkVMMskfxshqMwi1VsMwdKTRs92uCH7gYH8fnxMqRILvcFQs9vZ58aUXWK3OWV1kQGOsrPkpBcLQkUv8giKhckBlOcOlEBhSZu08ccwYU7HdriAHTIGSfeMbX+P551/k6WeeZhgGxr6n73reeut7/PjnPsvh0QJlHOfLc25/eA+y5trRISkltmNfKKkGbVr8KLI8HSN1U7N/5ZA7H9zh7vff44WXX2QynbBZbVhfrLnYbCXIm8DQX7DYm+NqSxhGXN3gqtmP7Bn/WBdLu8mBTDVLsB8iCwq7wx27f5bPN0qJOiZlrNb4TOm6ysdUMa/vxBO7YmeHdd4Fhj7xhEhHFnb/L19LplJPKHxCTItlsmHZAR1ySsQsMjOt1SVRxTknZriuk4JDC2kplpN+O235+re+wTM3bxDGANpx/+QE5SquXz1kb3HAGDPtbEaOA4vZlNq1LFcj9x7fZ8glWDVJbpEdtqASm9U5yhqcq7AF1DB0neTA7PDkKMFSXxaXAgFIWWGKv0qZIt/KkgFkssxustJlYgODL2bqGDg7f4xxFb/+a1/iU5/+MVw90PdSzCltmExmpOjZ29tnGAb2ZhOuHOxjYqCqazabLXt7+xzsLdAFulFSM0vxU0h4GSk40VAM+rmQwtKuUNKmFNhlpG40pAJQ0EZ06Wiqdko9mTFG5PBoGxSBrA3NbC6TzgyP7jzga75nUr3BwcGMHGDMiVxVpB2aWikxgxvDdrshR3ndtanYRjBVzYMHj7h67QhXV7zz7rt84uWXhYhXMhessSU7SiZLHy1ylNayoXqPVqrkv5jLqakpDYUQgiC0S4F/2Q0v9+ROjrXzMz2Zqn6ML6XIFrLRqMoRMyQvz3DwkYSQh3ICrJVw2RRRTUVCYZRM+LAOVUnQcbZGcCLF55VyQqeMGoJMso1GxYCpLLF25BwFH4+sQSnEIg2O2LoSGZii+CsDoUwccTUjimo2Y3H9Kq511HsLsJbHZyv6wXO0P0VZSxgjVeVQpnjNCn1IG4M2IpeTSIMIFFJllkmw+pdkya6uGYZRJhxKYZVmPqvZbAdImeAlXHkcPSpKEWZdzdPP3uLBvYfE0PP4wQOOXn9RmlvGkLMjVwkdAmnoiNmw3YwCG6grtHXUtsFVVnJHjGUyndI2DV1MOFfR1A3Xbtzk8cMHJDIheLphTciRsRtxs6b8HhIg248BhRDLSs+BprKo4EVzGRPGaUIKDN0GdKbfdFSu5uhwX9C2BmL0gHi/2skU40oXevcMpSxREUnIT34UmbPSsqfsyIQ7maRGntWcZWoexsAYYbXcMG0lPHZ+dEh+GbrTFeO6g3HEp8wQI42xpFjQ5FokVWhNioEcAjkGspUw5eBH7GQin6e1TIyWa6LKqJDIzhJzotY1WotfQtbPsjb6TIqFQKsStuwLKEVSDqzGITJSQdobfEbgHLkTEErIJPXxbb2EMOKswlWGoR+I2VCbxFNP36B1iuQHjLW086eZzxfs7y+YzFq8B2tbDJoxBjabLd1qAyEwaWpCCJw+PmHvcJ8UE/v7MxQaa8XboVDsHy5YrzaEMXF0tE9VO9abJSEE1psVH957zJvfeZNh6Lnx7HN88pNvMGy3PHXtmHY+45d/+Vd577336bpOaIZxIIaAWsGNG0+xPD1leXEBOTIOgc1yKd877KAJUbLPYsRUldDhQsRWDcuzc7p1R7/t8FmR0dRNwzBu2KzWEngbJa6kco7KOWbzOW+8+irztqVbrXGTKcvzJUfH+9RNw3wyQWWFjx0Sz5IY+17CpEm0szmubRn6HnLGOourHdpIALOxFbquMZVjTAGnIYfM+mItk7xZi3MCRPJjINRW1l9nigpJvEo7DyJQHnVNVbWEMAK5kHh1ISBLU98Hz7rveXS2JiSRJ3aDpzKGtnUMccsYInkoX1eXDM2c6AcJIz87OSGnxPLiXAh3dYvPSxaLGQezKWOILBaOZ597nuVyzfe/9zZhGISGWJQ+4yC+MeMsMQcJzLZOgBxekY1QdIdtJ2cmrUnJ4OqaZ555hrOzC779rW/SNI7jQ8lUGocBBdx/+IDj4wOmbUvwA8kn7ty5T4yBw72FyIL7kaapxbtuLdPpRAATXibks709rmf5/bddL/dVjlRNhQ+ew2tHzA+m9IWCfHF6wv7RFRbzGf/4F/6fP5Jn/GNeLO2mFk+wxv8yYQ4u5aXyV4qkZCcTc9bgQ8m9yOIh2ZFILqlomSfZN4ArAWHlxHhZ+Hx0wpQSl4XUznCstbqU6vhC0NLGYJS5hA486eSLPM85W2pCJV4ha2malhvXr7KYT1hfrHhw/4R2OuG5Z55m8IFp03K+6VmdrUjrDXVlePeD20Q0pplycrbl3XfexYeErWoOjw758P23aeuKLmcyCe8H2HUjEQlXDJLV4v//7P3Hr2Vrmt6J/T63zLbHhb3+5s2bvixZxSKL1c2WBDQaaEhQa6SBoKkECNDfIo0EjaSBQEA9EohuiGiRTbLILlZlVmVmpbv+3vDmuG2X+ZwG77dPRBbZmjSziStwAZEZceOcOOfsvcxrnuf36KEY6YqvIQNZY5Qhx/FGKpKSbMkIoTyIFSlSNhpi8Lx19y2OT894+PAhOQU+/MZ7vPXWG/z4p79AaUvX7SEnptOJBNzFSIiB05MlldEMfWS12+CqCqcc09kUZaQhTfowATroi8WMn0vOATGTo2yODg93rZ1M2UH0ycaBdhhblX9HUdUTbDNjcXTGdL6krh0kOcMqa0iD4uX5S/wwsN3u6caB3/693+KbH7xHowM6gjJlJV3CRiGjjcVaK9kMztKESEiZ4Ht23Y6Ul+x3LU1ds9Wahw8f8e47b5ORZvxgPj0097Zk+RgrfhRtDFZbmS5loROqQ5OWJdE7HYo1JabzmGQzJ5u4giYvk2/KIOHrfsRYmsrKgK2kSLa6yHylWI470VcHBQH5pUKiaSX82FpHqipULXlkIUGeTYv8cyT7kVxVxOjFOyRVMFGrm4aV0ZccJ8W47/AhCvDBSC7QsO+lsc+gtGFMmWH0VG3L4t4pk7Mjju+cSsNlLbve8+ThM5y5Q+Nkujp4T+NqaYCMEShIkQAba8p9R+IKtLYonUhBSJ5CdqPMoxSubthdrcWXYuUctgUWoW/2pUK1S1EaqLt3Trl79xaLxYxf/eIj3nv/bZqJPahYUNoQksePgTFn9ruOL774nO12e0PzQ8Hy6IiYMqcnp+gPv8VHv/olddPi6lpIntYRxwGlErvNjs8/f8A3336btp3AYQjkA2NUGCcbs5gE9mMQmalzDj8OEg8wBqytSDrT7QZmkynTxgkBLyUUhrEfqeqKqqoL5l3fIMEPssYQhSqWlUgvjdGSw8TBE6GLck8kcoyRsR9IaHb7gfOLFZweM3YddV1z5703eM5ToUitxW+w7zvBOwchTYWUwIvcxw8DxEC/7wVFjhDu0IbsxRMQnCaNETdpwBiR8NmK0RosChsCAS33VmPwORGNJmhF7D0+BJpJQ9aW0UvzpK08L1XBTCsMqtIyLNhJEz5+jXOWYvCMg4QmL5dT5vMZp8dHLBZTCRI1hhBlcLVYTEqwvaKyAto5mrdcrLakYWA+rWmbE46O3ycGzzB4Bu+Z1BPa2lLXNWRF7SqGYWS7WbNYHnF8sqTv91xcnmO04Wq15aNffsJmfQXUvPPe+3zw4QcYnbl/5038MPCzn/2MTz76iH63Zzqbs92uUQEJaFcNF+cv8F0nsQEq44dBng3eY5LkjhkcMUuzq5tGhs4pMoyefnVNN4wkBT4GjLFsttdsNlcyfFAKU3KUmqpm1k5YLpa89/7bzNsZpFO0Mkxqx/zkhO1uj0bTTmb4y3MaVxcJridlkbcO3rPtOiqgqmpsipiy5W6mMyaLOUPWBIXkPaZI148YZYh+JAWLz5m2bplOaxaLtmQyJsYhUFVOZNMU9RDc3JNjkuBpZy3jGBhLGO7hA4fRY5ShcjVdJwRIaw1VXcjLSSwLpIyPmRQhlvvtsO959PAJ29Wa/X5L33UYa3hxdcXx0SnNJKKtZT6bsOsHdMrcvnOPvvds1it22w3pMNtMorjyQ4ff74tMUNQnFMR/dBCCp9/vMArqSiIAHjx8yBtvvoXKmUcPn9DUDZO2LfJ1AXHtho6jxYw7Z6dUpuJ6rXl5fkm/33FyfEzwgbZtOTpaiv2xsrRtw367FxVNWzGb32UMET8G5sbwhlUobUkKJpMWpTTX6zX7fUffDaX5+s1d41/rZklpJQ96EDTjYWJ+oD1QJHKHNehr8qHDRCDnTOUcow+vob3L31GapBhLbsbBvPdqJZuyFKrWisQrlqDRgy8plZvigdon8gqE9PKaRO+w3pVp/quv0TQVoEv6cyaVlPPWOtqjI+aTiYAGVGa9XXNyfIuuH3n4/AVbr7i+fsYbZ8e89+67mKrh6cUlVZN48PmXmNIcPnj0iP16RRhHQYKriAahQml5yMVQtm9ZXvcYBC8udEGZouYshs2cJJw1xwQxIFCAeKPHF+KJRyvNMHR03V4AEkSePPqKTddxcbHl6PSWpH/7EddObrZzxycL3n77PtZqVuNIyIn9eosOlrFk0CjrMEoTkxQrAiuQzZYyDo1kGChKWKI5NEwHSadC2wrtakzVoo0DrYhBGkXXNGSfuHrxrND5LClF9sPAajsCkXq+4M233uR/+7/+X/CDt2/hbIXOGrRssCCSkzT1okcesMZS1XUxMQaapqECbMwYrXj5/DnTVh4s+67j8vKS09NTxnHEOSfNltKYgiQV5Hxp/JMgW7WxeD/egBuMMcQkXp2EKkZMU6ARRnK+SlF/M0zglY/ltUvma3l4Mj4rdFvRHk3YX20ABG5hNCqJ5yMXOW42Gp8zOuXikQNVtNghAVquV7Qh1444RjIVuR8E5pAkqyYXkERW4mOJiPm333cSBxATNiRCLyb7YQgkZdGVE3iENaiqIiKJ9WOMDCHgKidgGy2h0rZyjDGgsiKOicm8fZUZUqTCxmjBhRfITYzSqOco26asBDxwCDM2RTbmKieIcOOIKWJFIybnRE7UlaVfj5Dkmq+cYTJrmS3m/PP/zz/j8YNnfPM77wH5JnNjDJluVPRhZHt9ycXz54x9R0oRVGYYR2wvQcovnj1Dlc38IRQyl+1n8rI1AsXDhw+5Wm1ZHC2pnORB+ZgYo4Rb+nEg50R7NCsT4Sz/rjMM+544hBJcLsSus7M5IMCZ2loBZlQV8/nsJghdfAaBw4YpppKtpMFaJyG1ZVPnvZdnRTooGQIojY9BsNwx4UfJInG1Y7Neo6gwTs5H3bRE50jGMhaVRI4leHYcQYOvPdloQi9TYGfk1UFrCBFVyTMvhqKYKEjfpBpy26DrGq1hHEf5vAxkw2gcPgaRkiL3Uh+hUcXflyEbizHSTCWtqCaOqnbUMWC2PWOKv/bs/bodQ7dju1lzcrTke9/+gLqtqNtWctAqhzEwta4UzbIFTRm67Q5nLPN5y2RWc+t0wXq7Z3V9TdM4nKlJiOevtg7jHE1dgaLEOMDJ6RJrFKv1hq4bGfqeLz/7nK4f2e0HrKv49ne/xVvvvMPYDdw6XeCD56c//wV//ZO/JubMG2+/w3a3Y/d8RwgD5EzXdVxxiTO2gLCCqHDKCtZoRQ4yjLR1RRoGlJHvMcaR7XZLU1WEGAp0RQZv3vcSgwCQwRlNW9U0VV38Spq2nfDt737Il58/ZBgGJkdzusHz5edfcnlxTnt8xLe/813C4Fmdn6PgRn4fQyJjaI+O0DmKhy9z43fUrqIyFRsfaAu0aRhHmqqCJMMVY6CtHMHJfS1FkdCmmEjZYkr9eKjX5BmeWG9XzGetZCAViBKHukeJcqgbOqxRtM4QalHqWGfwQcAuMUdSUuioGGJAxcRus+f6ek1CE0ls1pck7zFVje4aTk7OCNlwtdnR1AJturq8II6eyXRKCBFtJeTbVY5+39F3HUO3JnQbjK1IYSQGX9RYgTyKJzVh6PcbcqpYLJc8f/GMy8sL5u2MyWxBfWdC7wNV0/Lk2VPqxvLW2/e5ul6zXC44O1vQTBzjGHnx8jmb9Y6qrtl2PaMPLGbTgla3zBYzdC9DnZRF6ZJSpm0bjo/maGupqqrAMiLzxYTNZk83jITgqV6r/f9dH1/vZqn8j9ES1Aq/TrF7BUsQDanWv06hE9qcPLCqyhHGcCMoSmW7lMgiXzisigBlKMWuuvl6IYhE7dD8HL7GQQYl/71QYtIraZ8EgNobud6BsidfRxF8LkWCTLq7ThCuIWRCHJhMW+7fa9nt99y5c5fnL66pXMud0zv0Ty9YtDPu3b3N0dGMZy+usUrT7TdM5zOGvqOuWyrX4EMJpgyjkGQODVsuVBhrSAc4RRJpW0xRpoRFviEBi4GUPEoqSAT5XTxjINP6UhTEsWd9+YzN+oLoRfLy+NEjjoaMoin4T2k0Rc4nmtZp29BYgzIyjdTK8uL5c9arnqdPz6WxLDI7baxMI8obK0WeBmIh3YkMSRlTmiojGThVja5aJrMFtqoBORe6nQRaEkYunz9AKcXLnME56tkS3TSc3L/F7/7Od/jlX/wZTTvj3bMTmhzxYaTPUlAGP5JDwBWZTt/3jOPAenXNOHoppLRh3/WytdQWlWX6s1lvcNZQVRUXL89ZLpbizwiBqqrKZlPO/7HQZaTpESphUiKX1FkkpTFnIa6VnIiQEjYlQipOs3Lu5ptr7oDNfx1u8vU9QtYo51icLJnOp5icue6v0FZjrWHY7aXJrhSxi7JhtJaEIviEcrZ4gEzx82WC0di6luGIcyLL63uhDsUok4iY5F4SIxEZuuScGYL4U6JSVCUQ2laOSMLEgB88Y4joKBKYfhypvScp2O/2mN5QzSZcXa6YLqYyDNCG0QescaLzp+DiK1ummdwQFXMSaZgPEiIYchRjPglbcnpS2Ug6JwMg8TCW7eaBkBhTmTLDuOvJQD1vWSxmhDFy695d1pfX+G5EWfHd5Cj0zRATIcp9eN/Llk08XNLM7bsdGs3q+ooYxnIvHUFJjpizhsEoQbBBkbH0BYKg8X3AewFVOKXxIQsRMmeBF1i518WQWF/s0MnjJpbBZ7rVyK13TiWjyuhCmZTG0dhXPgVffKcpi9c1pVQgNxrnzM00N6Z4c7/V5pW0OcdU4DYOQ6KdVszjnNEPTBczuvWOFEQK2flRXqNDsKOCMYz4MZCMIQYvdMIiUR/9iBs0tBUWyIcMmiSNmTJC31KVI1qHbVqyc4Q4oELGIGHL3keoanTQjKGX59thC6k1WSmikWeXs5ZgBP87Xc6ZLFoCkaih94Hw7+n6/3dxTOdL3nn7PY6XS7SWIed8PqFtW1KKKMSrnBJYW6GyAKe00agQ5DmfE4vljNl8ytFyRj/0XFxei9S6qdFas93uUIB1hrqqmM+mbDcbVqstwxD44rMvePTwAd1+x6RtOTo95dvf+TbLozm79RVHyyM22z0ff/QxX371AGUtb999g816zcsXz0jRyzUfPTaJ6mEcBw4Py5Rl65pjvsmajDnSdz2ZTLfdYon0XYeqW/Lo2e13WG3wWWqdqhJwhNaiaGjqqgzsIrqoKowxPHj4WCSIR0tSTvz8L3/Ci0fP2F6vefLsBXffeovgA9ZYYgnyNrIrxaiM7zqqtqKeTNBkdFXho9DkdO1IPuBDwKYo4In9BmeTNLdBsdtscFbRd4bppEFIwRXG6uJxL7TloltSOlNXMgQfvb/xpEvcjNSPlZWw3n6zw1hHXctgViC9BqsNgl0VimkcIzolht7jx5HJZEKMS6rrS3bdM3IO+GHKarulaidoEi8v1/hxgATjKFEkGUXTtFSU8NwQbwZEIWYwif3mHK0drmrYdzusccQY8KP4mPa7QFU3LGaO/W6L0wZb1VytrlkuFnJPy5mHDx9htOYP/+D38GGkqlraumbSKlI65uWzF1xcXHJ269aNnHsxnwtsIsOkrvBG041iGdBWmsx8qKuLASzEIBK89Yauk+wmVZl/6/X57+L4WjdLuciDDhKr13OVXj8Om5u/+XcHeIHUe0J6iiGSc0JnbnjkSh/yeORzD0G1ztqbAkN06enGK3L4WgeU80GGBxRfknzMTSGaD+bocjLnhIpSvPogFD/J5DAM40hUiSGMqN5w/nKF0prr9Z4nz16iXU0fFZvdmvv3brNYTMk5MplUbLuOO6cnzKcTAbmExOnpGV82EzbX51ilUSUwM6aD0jCKZrdcyFpJwK9IS4J4MrQjZWHza0qGT9HW5CRT7Fykhbk0hqREGnbEgVI4WGpjGPsercQsHbwnxESjhQA3n7Xcvn3CfNKWjaJi7CMXlxuenV+zH6S4SMaTo5TxRlsoN1G0NEbiLZLsEqUM2lTk0kwo66inS2bL4yJnKSjfocdmw9jJTaYf92Q0s9kRs+NTTk5O+faH7/D7v/NdPvzG2/zfH37OX/7qAQ+fPKa+tyQbgScYBSoGQt+T2xptCpQhxpsJXlPVzGdzNtstfT9gLGjvqeuK2XSGH3rGcWS+mNMPPYt6gVUW7wXy8Op6UK9QnGXzmsqmFSU+gxAiShUSHEnOt3yQ4wnFSB2uHXWQtaqve490cyQy86Mpx2dHbNcb3KRBO4E0KCUDgYPfMGhDQAzvvmiqK2sw05Y4Cr55DIk0bYusIpG0GOGzNahBQmf1DQJcSwGiBXU7hkivMsEYtDEMITCib+41OYMHvDEYpdn3A5Naka0VguLgWZwdySbbuhuJhzGKzWpdtj65BDPKBiP6QE4V1hkhxLlKfETWSoNdCJhWG5lmQ/FRSnF/2JP60RNGT902qJQggST3ZIZuZDeOHFWWyaTletxy7/4dnj1+xne+9QH1RDDoyilyUDRGE1UijF7IT0mkizplClmDEAPaGhT25t5JVoyDAC28F4+Q957KVhwfL7FOYxQ0Tl5f1UXJPFGZSWVIRUZmpzU5w/Zqy/Zyx2wxwY+W1fmKsBvL5jXLtjpnUKb4jtLNwEEQ85RGL6KIRZ5XbvjlgR9CkPMkJvRrXkOQxqUqW13nLO20pS7PqeebDdOmIVldcpPE20i3ZRwC07YhG0t2FlM5OsAZQ6ocXilikR6mQlyQoFH5fVYQtBRyyliSVmQ/itLCWkLfodCkMuwBRdAwHiTpGYacSxSDkeGP1WStcY2jmVR433Ny94yvHj4ryPr/0S/9f2fHh9/8Ht//7vc5WZ4ShkgcI2H0bKLHOUtlHTHKYHcYRmk4MgxjZN8NXF+tQcH9Sc20rUjJM3hYzOYie9Yiw5/O55ydHOGcYr3e8uzpCzabLcM48MlHn3B1fo7RmuNbt2jamu99//tM2obNes+d22esr1f89c9+xqPHT1keLXnnnff49NPPefb0sUjLtGa3XmMrK+dAjBKWW5QgMZeBidZk7/F+JMSRoduTlWJ1eY7vG0LK1Fpjgsd7jzIGV1dyb7Ca6KM857NI0YP3oBXWyHPn4199xMnJMSprumc7fv7Tn/LyyTOST8SUySHy4MEXghtXQsZVJRcSL5LmhMI0DuesZNmlKMHaKaJjIJEZvEePI0PfEbxnMW3wfWLV7VDMOTlbyGAdqb9suT4PiiUZckhtqMr2yY+JnA05y7UhmZLl+tRwNGsICXZjQo0DbWWZNBX9mKidISOkTJ01Rhv6cWTwI7aWoe3wsiP4Uby01hFTou+6EiNqeXG9YeIMldUY53BVRSj1auUs3TjQzibsduJ5stqgs8J3O4wpW/ZC3EwpkpPURdpVbPd76qZmMp0yBM+EyH6/5ej4mDEmtl1H3dR89NkXjMHzR3/79znnnHYy4e6tM2pb8/jJM378l3/F0fEpv/t7v4NWhu2+4/hYhr7jOEqdppRERCgZdu12O6bTKYwj+zGw7TtSBGctvVIMw8DQ/+YgMV/rZukQinnz59d8Sn+zYRLfkSqr30Ojom4kRLpsorQVKlooq1sU8vAs4YKxSPJyfmWGB26apL/59WU9G24aKpGrHRopIVwZI0VJKtPImKRQ8THix7GskCV4lKTY7fZcrXac3T4GrTm5dcb1es1XX34lcp/oefzsCXfPTvj2B++wmE5ZXV9jyCwXU3bPV9RtRYoBrWG/3zGZztlZMZoL5cWSTQmW9JLrkGIkR08sJ7JSoJLkaxw8B1JcF+lOlG3SIaRRHySRh+0SWrw+OUpTRWZ1dckUTcax2x6LR8w6lNIcHS+ZTSfcOTuhspZh9FyuNqyvdlyv91xcb8QLVgpCrRB5UwgivdOajMZWDSqN2HoiGF00GCceODK2IIkzmqFMVSSQV4sHqxRHk9mSZjJhOl3wzjfe54//1vf5nW+9wdFsztPnL/HdyHqz45OHT3j33gmNa1EpyM1HJ5rptGwiPKMf6fqeXPS4tmwCJpMJ1liGMdD3vWyNKpHaQWK/70pGEywWi5vtpVKHRjzfnD8xhiL9fEV4VMqUjWAuw0ORC+3DQGUrVCXFneYQ3FykeAV4Qi6btq/xYWzJ0CIzW85QSrO92DDuR0YfUEZ8NMYYokqMMRGzkmm9UmgrQa3KGvY+EqsKjCbsBXGfjUG7hqHv0AqszqQg70Xp5uXBFDMe2I4D2lUo68gxMl3OmNSO3AeoHKHLDDnhVBnkVI719Zqky6BDC31NWYVrysbLQsIwjiJXcMpKdlSWa0R7LzIzMmP0JTsN8fcc8nMihCFSO4s1uUj95HII3kujMmaqSooL7wMZTVSa4Cz71YZ2M1AZR/QBky1Pnz1nu9uRNEytEeP64MldJO5G1ldruv2eBIQU6f0IoUzIckZFD2Wzj9JYl7m+umQcPeGwcQqey8srul1P6AJRGWxlyCET93uqeUPjoDKCt9Y6M46Boc9cXXV4rehiokIRjGNy9xYYjfcDmYw2FbWxN0MJ8VVGcpbEelOGbQcZUk5yramciy9QXt/Re3TJRRIVozwvEpmqrohjgJTZ7zsmbUvVNGxWK8b9wPZqzRASfRSpHkbhY6aaT5g5S1aKcRwYU8JNp+y3G0wwZOdugsZ9TJI5RSRpS8qK3NSY2sLYw+jxSkvToyAPHtXU4BWDj/iQ2MWIyQmlaqkMUeU1CSSP4Pgry/G9M2IM9P0o8mZexXJ8HY9vffgtppMJs+WE2XRK9D1XLy9Znsxli1+GVzFKzZByZhgj4+C5vl6z2Xf44OWZjmRVWWPRE8fQjTRtxa3pBOMMGs2+2zOMnosX53zy6aecX12x31xxfHzCfLHk+OSE73z7m4zDSO0sbj7l8aMnfPHFZ3z++WdY07Bab/jFL38pw7lmwvXlJavrS0IY0HrKZDJj2k4Ye491mr4bBbttBAuODtLsjyLZ9SSG4Am7hK1rhu2W6CpCEItDVWIHtDa8+d57xG7P9eUl3b4T75/OtFVDvx84f3EhECkFLx8/od92hDEQevH7zdoJZjFhDIH91Uq2nUZg9uInSjR1hcoRP3RFTqawjaHrRpz2xCgbMesa6spRGSWhqoiaR1tRY+x3HcvlFK0rUjaQFMpIcSijoPRKil6sGjK8ESmuLuhwoRsHyBFroLKatq5onaUyCpzmeNay3e+JXrLaYuF5a6XEM5SjbNL7LZXWLJZLtoN8/X4cScC+78htzWo7UDnNYjZjMp/hx1FkbCozdAOVMVgN7WyCtpZuv2f0PcbWaO1QOSLj0ygDsSyDp9X1huZuw3w2k9xKBecXFyyWC6q6wg9y3/34o0/IOfGdb32TGCPnxtI2E47PbjFE+Pyzz4gx8oPf+W1u37vF5dWKk+MTsoJ+u6NtW6Edh0BENm9hHBlHebYYoGkrKqexKrPdd6zW69/YNf61bpYORy7FHuWE1Erd3HhvmqYyVb+R6OVMzq+2Ojfp6qXql9BDmRAeJoFKa5m2HiYY8VX47OvN0UFS98rbVC6pMsVTpRDJ5cYRghj9QjyAIEyZ+MnvvY9oncskIzGbTanqBowiRMW+C3z8yZec3TlFYfnFLz9hOp3yg9/6DsvFnBfPXpKVwTQ13eaaXT/y2eefFx0tnD9/Trfb49oG33WyHVJabi5Vhc+p5Dmk8nqJPOfgA8v5VbK1ygKDSAWJnsoE9dUa4rXsHgWk8l4VqUIOUVLfc2DotrSzBftuRCvFcj7n7u1bfPD+OyyXCy6uXrLb9by4uGK93ck6dhhuJGJavhyojNIZSChtca4mp7Ld01LkubolDQM5xxI2qyUnRImEqZ3IBij5RLfvqOqKybTl5GTBn/zxH/GHf/v7nBxNOF62NLbh+M49vvPLL/nRly85Pj7D2RpTsONYKWSkGC5mb2NwtaMaRdceQxBPnlHMZ1PcGNl2A/3oBSowBiZty2Q2JaN4/uIlSmuOlotXW6R0uC7izetvzCt8e0iIx0Sr8mAIJWS25ARlwHtqo4g5woHWhkiLjFY3Utiv89ENI9vNlvVqx/JkwWa1YfAyeczOkMjE+kAOzEStGFOSjVPw6Ghxh3NaKyorRlm/2xOVYJqpHWn0qJwIRpGjRpkitR0zqrbEfWAcPVHJdTd6z7SdYK3FTqbESrZAPngGP9Kmpnx8T9pt8SlhqobRpwIGGDlazuQhWKRYmkKhRCZyPoQCyYE0evE7hShBhaWRyjlKqCWaq+sNxmiOljOcUUWCZlAqoHSmait89DeN1pgEf17XFYOp6DYDrrUcHS8JCfrk+fzBQz785vvkVaJpHGnbk8dA2HZsLi/peymUck54NQLIoEkpwfNykFUHYtCMeRQEeqJc+1rw45s9YT9wse7RzlA5S+xGolNklUiVwwI+R0KObPtANwbqyQSv5F62Hga6YWA6jjgDdS3Xii6bphACIQg8YjtKGO9y4qiM0Chjjjd+wIMaIZZ7v/dCsTTom61k1poxBNnsKBnw7QaPtUK2W12t6FZbNusNyVq2fqAbeirjqKzl9lv3qPcd6+sNk6am7wdIiTFnhgi1llDelBXZig8ujLH4vopEdLvBUSSKIeGcIlvHEDOhGwgpMeRMHzMB8FnRqIIXz9K4qSLxjcDoI9erDSlEHj58ynbXC8Dka7xaeuPN+yymM+azCVVTEYYoEASlpGgvw9J+9FgrHusQIz559n3ParWRDJ7R46xktmknQavzWY2xSaALWiTQXed59OQFn3z2OV9+/hnGGO7dv89kfsT777/HyfGSlBLz+YIYBl5cvuDFy3Oevjjn5eUVKiu22y1t23B2dpvHjx5yefmS6CPtbMLi6JjTs1tU1rKOa1arDX3X45wlWSuehhtbwWGanzGVI6VMHyNJgQvhJoIj5QwxMmlnTKdTkrOMQ18sDtBOJxyfLAkhspjPGLuep48f0+86mqaV/KeydZBmUtEPQt80SqRrzhickQ1K09Zk3xN8wtYtIWS6rqfRjtF7+nEEqzE60VqDKRt4rRVvv32f05M5k0lN3dYyQLb61+pKAbGom589v2bVkPpOFEi2hMummHj87DmT2Zx524KSvEVnDQawteHe2QTr4Hq1Z9cNWKOIRiA0TevIVLSzBdo1jGPP1WqNtg3WODKKrh8JQ+DCC/GyqSwp7agdDP1I1/UoMlXlODo5ZRz27HdrVEqEsSf6EVdPUFWDMbWAoGIkhcwQ++JHy7y8uKIfAicnitPjOSkl1pcXHJ2cEn3Cjx1uNuGTTz/HjyN//Hf/iL7bc355Qd1O+P5v/z7//J/8Y37x819QNw3L4yXWOJ69fMmt0xNm8zmr1ZqqsjRNg9UKKoUs6SKTRgjAIXhaZ5i4I6a7CsJ/yFn6tx6v+5J+7b+XLvhvTqq89/SDGOHryolEgFefH9OrFZ4qJg2NEtM/BxnSwcOhyCpK8mL5eIE76JuGSR/Wrzm/1kQVQ2ACY8U/lVJiHD3aWsYxEeKAdSKpUkrTdf3N91VVFbWrUCRCCmy7gT/787/knXfe5mR5wssX5yyOlty5dxffefZ5ix8GFssTtp1n6CLnFxfcvnsP5TRdt+fq6pLRdzIFsVYyZYJkj6RYsni0lSYmFtOi6LRIEbSrKSMVMXkbXVLZ0826+qDrTTHKFF8ptLECOJAXQaQsURq1cRzZbVZoazHayQwnZ06OFkzqGh8C292e1WrLZj+w3fd0+46+78SMnyWjSpFI0ReTumiHJW/JUdVinBXjm0M7sK7CuBpthB42my9ER20tOSd2cQ1aMfjA22dn/M/+J3/EH/+d32ZWa2bTOa2rqbUlK83dWye4qoKQhLClImjRNtZlepMLeW4cBOVtnCWM402qNdmW/AXxcmgrk73F0UQknq6inUyYL5fsNmsmbct0MuFGd3o4lylS1AxGHYhUIi8DwauOMYg/TB2gE5KRU9la5s1Zsd3vUFpCmU3SWCUhlF/nI5BYbfZ8+ulXLBYzQc7HBBgJaC1Ns0eQ70PwjDESY8AZeXCHJJtmV1UkawijR41BXl+jicMgyOacMU7jNQVzpFF12aY4C1GmtXWGylhceb9Uztiqotv3AgkoXpmQEyEM7HcdyjhmZyOb7Z4qRcYYGX3EVYYQA+M40rj6xhMnGw2ZDNdtzTgIybKqHDGmsqWVKatsDjJ+jGyGjtFHjuaN0OOMZix+G5MSIcqJlsqUdxwDRhua5Yw4BELvGfqOvu8x2vHpLz/hzskpTV0z7h1VjAyPztkNnucvLojJk8v2OoUoEqAUadsKciKkSEriDzDaEFUAfdigyvt3fX3F5YtLblVLHlyu6ELgG/dvYRtLP8jtzKaE73qoarzR6Mpgp46ohS64HQZWux2TxqFIUKSrxhxCrhX9ENgNgZerLTFl5m1FP0BUAmghi59NqYPrVXKGxtETon811EPke6RcCF9BqJZZ8u36/UBMievVlv35inHXo5zDGI0H+hiou4HtakMcRyptJFYgyRYnxCAkRmRbHrOi0oYIKCeFVywbxxylcVNI1p3yGbTg3DfXG7QpPqii246I727fD0znTRmIKVAZHxM5RD7/9CG7zY7rqzV+jKAcKXX/nu4A/8OPtqmYHc9E9uQ0Tbso8tbA0HW0k5YUI0PnOd9cih8wG/b9SL/vqZqKo+WETGaz2ZNyop00VG3N9fUap6yAqPqeJ0+ecH2945e/+CVPHj3ENi1nt25xdnbK0dExzhqcViyOluz2Pc+eP2ez3fPgq8cF/LCn73qWR8fcufsGL148Y7W+xhrD0fKIxdExy+Uca5RQFjP0w1h82bJBDVne85DEgxZTIls59zLQDwM6CzXYthUheVRMuLrh1tltqtZx3e/p+p6qbphPp5yenlK3FXfu3eat+/f403/+3/HyxUsa25Bih+96UkwYW9Q6zqKz4OuV0uiUqaqKtqlpnSN0O3QWaXROCeVkAJW7jpgyHkVbt1JbaHBGNj/OVZwcz2gnlYQLV4Zx8NR1jTUZZeW6zUlUM0q98rDf1HsJpHrM5V6hsVpzenKEs5VIW3Oidk5iO8rr1ixbnNE4NEYrrJM8v27SUNcNfvQsj064nC4wriKi8GNg322YhSOh3WpDSDJ408YyJkUeI/ttRxgH2sqRWyc1Uc74sWe37SV7KUVi9Bg/4KopIYuHM2epE4yucW0jtdb+JSEm7t9/l9m0ZbW64urygju3b3Pn7ikvLy7odjs+/vQLJpMpf/xHf0DfrVitN3zrm+8y+j/mL//1X/Dpx5+QleIP/+7fYfSBJ09f8Ob9e8xnM9brNdFH5vMpxgo8xhlbSKOBqqlRCObcD4Y49v89V+j/8ONr3Szl13693vQc5HM5vWqXxnHEe480K2JIxpRV9yFHSR3kSZTpuinkt1jWoWVRwSsZkoR0lkDc12AOhwbp3ySGyeTCB4/Jkt0SYyJE8YmgXsOfoyGLnyWWr+esUJ+iH9gPI//6h3+FNpbbpyeoHJlMGo7jkv1+z3IxwyeYHR2x85EnLy959PwlRyenTCdTfvZXP+TJgyf8/b/3R/yLP/tTrnfXKN9TFROwdk6kdVqTQ8RqLQ9EWY+RlcjR5DstPogUCXHkEMQmBDbBp+csjaeEu2ZSjjTTJWnYFYqhIaWRsd+RYmbc7xjrhnoyxyjFer1ivdmw2kgY2/n5FS8urlitd+y7QWRqSWg6kimihGxV7mxCKwykFKnriUiLskx5jbEYU6GspZ0tqOqWqhKM+OA9ylSQMs1khraO6WLG3/vjv80f/53f497dY3TKNKYqGUVC3mvaitpkIKCsoaosSkXRoEu4CMYIbEEIZELriSEK0tkYNIqqqaiaBrPrGWJAG03dtlhrJMcGRTuZ3HiZQsxYKwGdsqEUn8lhW3rYKhBzCRa2JJXK1umwLZWNLUoaQ61gCDIFN8VhGWO8kUd9nQ+lNL2P0PWMKUFIOCVeHx0VYQxCT0Q+rveeUAYGKUfqlOn7URpdH4ldT2UdttLETqRLMWeyUqhWTMaYRLRgs3hBiLIBMdqiraFtaoyPOFvJlnYYGfoRP/Rsu64YcA2r7Z7JZIJxFSjNEDwpi1RXa4v3RSrjPcM44jvPbN5SOUvwWWAuStH1gl5VGsYQ0Ekkx76Ep44+Fi9bonKOoRvYaMW0qVHIOSnXkSIE2ZjlmNn3AhjJKVNNHENMjGNitw1srnumkwVX11c8e3LFW+/cYbveMdMCJhlD4GK9YbvfSzh1obsJAEfoaakQMgW2JZucGKVx1QX3631gu12zXm/YhJHPnz7HY2i14fTOEpW8FCf7RGUMgYBqG0JIBfJhwSiur3fs9jsmk6U0nu0EW2RsSilGL1KzTTcQfcAqxbjfEQZFZbTIoawmJY01lkwiZqHcBZ+KjE8Vmlem73tQinGIjIWi51zF6EfCKNIb6yq0VcQUsNoRlaILA5W1eCLb3Z44eipXMbM12RpGbbDOUlWOrDJD8NTOEbIqMy8l/lRn5evGiA6BSgnIJxo5Z/bB43NEjxmSyAkjqsglI9YHVD9gTYVPspn2IbL3Az6JBCrmfNO8qd8k9/c3fGijqJ3BWvnlnCPkTAqJsR9lC6F1QXJLMPput0MZK7JGP3J9vcZUFafLJXVdldojMJ+1Irl7ec6Tx0/59KNPePHynCFEqnrK7fv3qWtH3U5EaoWh7wfG0LNeb0FpvvriIb/4+c/oux0JWJ4cc/vWXdbrNZcXF1S2Yn5yxumtsyLBleZYao8tGU1WGp8CPiZcVaFp6dCMYWSMgYRmU65VnxKWTD8MmBgF6GAUx6en3HvzPioFLp8/A6V48523+c6H30STWRwveevtN/nRX/yQx48eEvqRrCPWOPFNQZG+CtAo5LIFzeC0kNIWyyUqSERDiIGqbaibFo9hv+/Zj1tMzOi6FipcVTNpLM4oZvMW1ziMM3T9UMifMhiIMbJeDSwWM8mrK+kxuQyDM4fa8/D7onbikJ8Hi9mk0PMUk9oxehmK5HzwtIsSqa41zWjo+pH5bEJKsrHebHuayYTm+Bb++gKCxFzkrIvVRBOyKJRSCDJgiok+ChQoJ4kkqF3Ffrdiv74GBRp9I/vNYSTmLN50XTxUZFSWZ0L28dWQJ2TGmJkv5hwfLfjyq6+4vL7gSB1T6YpNTOQ08NOf/ITbp0f84AffZfi058XL53z/e99DYfnxD/+Cx48e85d//kM++Na3aWdTHj9/zt1btzg9O6Hve3b7PUfLBU1Vo1XC2gqoXlkCssJXgeVy/hu7xr/WzRKqmKMzv96cgGyFXtvy5FwMyylRVbUUzxw01epGtqS10IkUBbaAudkyHaYG0sRw87l/k773694lir8ky+SzIJ11gTiI3rdkcQRJS3e2LlCITMya9WbF2AfadoZPgaEb+OrBE672e9a7Pf/gT/4uJ7MJq82a09u3qKYDg+9xleH582e08yMu1ztWmw2TWc3Z2QnHszn/r1YyEVLw/Mf/6X/GJ3/9V3z5s7+kv96QlKWqBdctgtEyaS5SshQTaDG6H8yPZNlIaQSnLH+n5GNJZdth0aaSxgpI2mGqCZVrJVE6B3y3JxmD73fsVsLtR2mWRwu2+56Lqy0X0cuqeue5Wq3ZbraoRAn3LQq/shrXBz28tiijoLze2tU4xNislDTUlauo6hbjapEeBS+gA2uobEXlDCorTu+e8MF7bzJvLCpFalfhlJZpDYlMwjQVf+eP/oDldFLIaQFnACUQD1Iu2y85JGepgkqRbESVh0BKibqqWCwX9KNn2/WkGLF1TTOtbrDe2lkqPZHk+AJ5MNaR06GZL3RGMcpBDsTilUEJEtmPndAly2uSM4zpcA2BczW1NThz8O15DqHMX9cjhkhykZgM3eClYDSSpK4ShJjQGlIIBWpCkZ8pKleR9GG7liXkOSh0AmpHRyEHagQrjpbAUgc6SbEfRi+0Ri80p2kzZdzvmbqWnAK+D6ROtraSeO/xCbbDyLFS6KomjkKUExhdIJS8pGwU49DT7wfWqxXjruPOvdNCSMrYg7BSSbAmKuOqSqAiRmNdxdALZU5pxbAfyUpT1zUhRLrR01ROGvIMxhnqQvyLGbq+wxnDfNaSE9TzhrjpmM4mNNstp6dnrDZbcmPYBU9tFav1ntpqhm5ku9kIjalIdVJOpDDKdjTGsrWWAiqrIlVGNk1kXSTa0pRc+oGPX1zz5LrD1RVx2lBNW6IfaWqDTgY7qQoQwdDveuq2YRh6xjHz9OU5fuyp6jNs5WjaWuiTHDa0EjCpCFgV8UNAuULHKz5XrRwJGMKI0Qd5krwXAiMdUSiRCGXFOHa8ePmS9XbP2e1T2uIb0Ch2+46qqYlRiJZp9Gw3G4IfWSMgnmq7EwN0P1BnKSzGcaS1Fa0ymCTNERqSs4RSJJm6EqR9EDmjsVaelkrRebl/jiGUBgmZ8o+G/TDI56mMT5HdoHBOZuxKS1SBj6GgfuVepI0m9FEyab6mR7ffkvMR1kLT1FS1g8YALSCve0YxW4j8Tke5DwyDZ+gHfJB6IY2BybSRRjoWKqP3PH/0jJ/95K948vQpz148R5uWN9/7gOPjI8ZhL5CEMDKfT9jtVnz5xTPatkEZw8//+md8+smn9GNPBO7eu8/i6Ijnz56VYNOIcZa6aVjM5/RdR0qK5fIIP3qJDzAa7yV/rXIVk4lhXA1Qhiuh2BR8DKRwCG0tA+ycAc1sNuHWyTFnp8c8e/SMytW8ef8+f/+P/w53bt/i4cPHfP8H32GzXvOLv/65hKiWaz5GgaQkJaTbSiu6/V6uKaOYzmfQjzS1BIYblTkQ6JytMM7R+0hQGZ9EPl05S6UcyY/oSmOQqINMZr/bCzihH7jtTgTUYDVPnjzlnXff4sgtUFHu66XSk//NB82GAZXJquBviq9XlbsV5ftzRhOD1KbOai43O86vN8SIbOqtwRjFYj4VmmJGhrWzY3b7HhXWzI+PaWcLbOVuttK5kGxDDPhgcLoQcYkMw4iE+UI7mRHiwD5FjK8wVqSRZPC+L/Ew8p1nITsRciCkAEqIm1ebLc1Fxe2zE9557x0eP3jAZrXGWMts2nC9WuOHkQcPH/HNb77P6dGCodhbfvBb32M2n/BXf/4jPvnVp/iUePeDDzhaLDm/uuKO1XKOF+iE1sj7WeosgappsInJxHH77Og3do1/rZul1xuTX8tH+hu/l2mjYCuFFKbIWXCmort9FWgbiwzsIDvIKhVtqujINQUXWZorUyRIr2+RDtulg5b39Ubu9Y8FMZcP+0HwzSHQtE3JKskYp9itB8iGlCOPn7/g4nrDg0fnfP7FI+bLiv/pP/hDbh8vCIOnaacoZ2iSZrmQda9OmScvNzLBJjCZ1swajVae0+WcT8LIyfGSo3v3+O3vfsj2P/1P+H/8X/9vPHv0pGjmM8ZZcsgkZWR9rBJZRUxBS+YkWSCaQ3ipFDCaA0FQfmUAo3BNQ9hLRoRs8CzL+ZzN1Uui78SsDQQzgu9oosfGSFO1bFZbXr64xJhM1wXWmy1XV1eMoyenhB8HYvAoUpFZ3nTTkl2iNcEPaNegjKWdTMhJ8iNMzriqpqlrfJIGzzkx/+fkMWjevHubyjn60HH31hmTpqWtJlRG45Q035mMVfDmrTO+90Hk3u0zdEbgy+WCT6Sb4Eofg/halCErQ8zi+dAZee1vvGJC45m1DUPwWF30zuWGmlMUmYQq9DZT2kQl70ZGGrIDnVEK0HRDNzTaUJeBwkGC6uoiXSjfv1byE6Yk0BJrLf+m4PXrdYQsGPxxGIs8ArAJm6SnDDmTvFzro5ctilGOFCNNVVHbiowhhIRDEX2kJ+KHnj5KGrsz+gYbnrVFTxroA7XJaB+ISpGsocEyT4l9ivTB43TF5HhB7Do2q54ADFkmtSGLtKQfA8pYxpzpBs8wBqq2YrPbst3WOKMJPoIyPHtxzsvzS4zT2MrRdSMxRqaTFqOrQukUff44eMnuqhxhTCQfqeu6yDNHlNZ0IZJDpKkdKHDOolSQ/KKUMEqz3nbYukbnTOgDrqmYO83RuKDpPPPrOd0wUNcVvh+xjaPfj5xvOnovwp5DqCtF7pIKdU6mzFpQxry6v0JpoBAfkR9HLtYrmjMI9ZTaGeaLhrY1oComlaEfA0NSOOuwlcWOJTzYaK4ur9iuNxwvj3FOM5tNqWt5aOviAwwhyn3cy+c1jQQcG4VAMayWaylBM6lRKjOOkZhKZl+MdP1wgyT2PrDZbnn+/LxIY2HfSQBjCkKoin6ErGnmU643WxluaccYxgLekUHHpK4JZHzODEkIgCBZU8YJBh9XSYZYae4IgpH244hXkkdmEQ+eShofPFkJXl9rjXUBE8tAAUVEiv+QMpPa4kNk9BJFkWIkRUhZcvSUVqXQ/HoeKchgzVorwcwpll1DIQvGxDD0ZBTPn72Q4appubpaE+LIdDpjMp1SNQ1X12uOj+dMJw3XV2t++de/5C/+7M959vQxPmWWt2/zzQ+/w63bt0kpkPyUZ0+fc319wbMsfkOjFGPvefT4CZ98/DH92KGs5d33PmQ2nfHgwZdsVytyFIevqyrmiznz+RySwhqFVpm6qWimE67WG3JOGC3Fcy4KkzFIAxNTQicBU6A1Ksv2dOh79HRC21a8/dabfP+3fkAYA894wu//7d/jww/e49bt21xeXvKNDz5A64o//W//JeuLa0pEajmfZKMcs9BakxqK8gFa20AWCBEhkWPE1ZUMbq0lBc8wDjTTBR0iefbjSFU5JrUMOYkRrWpRXBipYeazKdoo2qbCVrKJfefdt5lO2xv1kVJIDl9WxYcYi0cLZO1x8PXK/yuVbyJRjClRNloVeJh44VOSwUJrDamoRFJOdH2Qga8y2GbC8uwO/a7l3bffYDKdcL3eCcF1FGhK0rLNzEnR+4GchZ4XQiTt9hgVOTk5xTlFt9uKpDn4ksUo2YvZ+7KAKJmAKeH9KBluaKIPrFdbnHYM+z1vv3mX97/xPqfHx/zys094+MUDdqs1YRz4+ONPuX3rjG9/8z1OT2/z9NlLBh/5zrc+RGXNX/3wRzx+8IhhGPnO976HtSc8f3mJUpqz4yXWiNdPanZ5HhiRD2CNYdK2xP/gWfq3H69vjeBVhtLrPqaborAcxpqb0k4CIaVJCiHcSM7SQXNaNHdKyw4qJcmwOCDCKUAIfbMbePV9/f8K2Dt4m+T7lcyLjKBBbUgYHYR+5BOxT1xe7OhT4POvHvH48Uv+7Icf8e433uWdN9/gm++8xcuXz5hNlkzbCdtxz7S11LYiJMWYDOvVmuniiMlkxnvvvs2Lp0+pXMvp7Vuk5Pnolz/mf/P3/4A7t08J4Q3s/77iv/yH/09ePH7M6CX8cei8UNG0IyaRlWVliu41yCQ9HTZvh4IlcYBAgHiGlDYY5zC15BZIhohmv+tuthc3izxVXssUZWKeouQqWIdzhqfPnjD0I30/iHHeD4zdnuhHsveQRD52yNQiy4WVs8iFrLXl66iCtG2omhZtDM4YhqEja4NSMD9acu/uXd568x5Wa7748nP8EHh5fk2KismswihF8FHkdshNpXH65ua673qqSqR1wrwomyWlGMv0vHJVyUCQgMesjHxMTNQotBWqlnKWnIXkpzCycldKpBnOorQ8wMzBH1beK4pcMmXknFdyo1Y5o8g0VcXgPd4HrC4bxELzgYSzFqNKMKnWInf6G+f/1+3QKhf8rMLkRExKZENG8ttUGZ70Y8mySfLayXRLpqhjkPBlYsQ6RxcDu9Hjc6I2TraESmPqWlSoyCQ/kgh7RVCayWwKIQgpa7+Xc7KqmbQtu35AOU0Oid6HG1rWQVbctDXZGIaQuLpe0QwNCcvmes1yOUVp8F5Imw8fPWW+nNEqRQiJFBHSlQKdLCkLtAGt2e32ZGSzUBWvYEpFHpglrDdlkRFbKyAFfZickmhax37wElC4mDOmCH1i3HXoQh112vDZL76Qokclbs1nRGCLYtv3N5CYTEFRH65pAV3fYN0P5vdDlp38fdksxcBms6KqFbrSHB3PqTW4pKiA2Mk9uBsjZppZb/Ykpalrx/6qoxt66mbCYjGjKTTKdHNfgtFLblNWudDlrPgqjIAkUs7s9j2m/JvBSyjnOIQbEmq/7xiGAVO2Uf3oOT9fcXW9la36bl8kzSJbC90gmF0rcnF2cl5VrmLwI0MqIbYomqamaSdcr9Y0WSbvbdPQtjXKGAalMDkS0LhJS+x68jgK8S95Rh9ROct9U5sy3EE8WDFicnlOak1ImTEkxm7PtJ2UojrdUO/86IlBNnGZTMgQvsaNEsAbb91huZxR11a8FYBSTmoL73GVAIJ8SNy/f5/tdkfvA2e3T3CuZrffy47XKJq2wWjL04fP+Mlf/Zif/vjHPHz0EGUbvvvbv82H3/k21jpWl+f0XUfXdTz48nOUNuy2G05Oznjjrbf4yU9+wvNnjwTGU9XcuXeP2XTGw6++ZLfdkjP0XYetDIvlguXREcvlDJUTw76jbRsZKh8GjioJbnscbp6rcijQooQpjFuRIzpLvAkbNhyfnLGcL/j0k09opzV/+w9+n299630ePHhIzpmzW0f86b/4V/z4xz8lIXQ7BcQxlC2CyMaz1WAUOUFV1WhniUOPSciQWYnwjZzwMZK1xqCKNN/TdXuMrXBKURtNXTym435g3HUCZKgMVaWZzlq01WUIpKkqU8jEBXBRmk1y5sa39Guln/zXlGWzKDUrKCPXElmoeDHmm5DhyaRiDOK1UlrRDTI8VlpTFb+9c47p/IimbanbCffOjjHG8vJyjVGWlAPJB6JL4IAoKgGTZeMdfGDfrTBa1A2T6VIkd+UZl5VkVaUyuNbaoLVkSKmiN0wZUgrs+w67rdCqZdMNJK1wuy277ZbV5VUhvyquLq959vycb3/3Q5xznB6f8NWjJ1xvNnzrOx+irOGnP/ox6+sVH//qY37rd36b46MjHj18AjFwfDwXf5zPuMpii2ILJc1SJh0erb+R4+vdLPFvNiWvb20Ooa8HiYQxQrY6NFMS1ikbIOfcK88RQEmrfh3UcBM+pl6ZvlFK/AiHaebhv5fjlQ/qbxru5SfwXoK1qrqBrFFIAWFjIkXNw5cvefTyiifPV3zx4DG7/RX/0T/4fb7/4Td48+4ZcQycndxiREzEx7M5jau42u1Y7Tu+evoCVVU8ePqEb33wPrXKvPfmm2wLgQfj2A8j15sN87bFZJhN5/zP/5f/K148eMw/+kf/CBJ49jfEOqPEACzyIovKBvJIOiSuFL1zLhu4fLOr1kXb74Wjr19hqfe7PcSAVgWAoZNkqvDKR7bf75hNajabjaRS+0jf96QQiNETg+Q+aF7hynMWGhdlOnLIgOK1oksbiyETYkZXNe10QgiRphUJxWw+YzqbcP/OKWfHCy7Oz/n93/2BNGBGsdpu2A+WvtsLra5p0BTzdddxfn5BXEzRWbKxQM6p2tU0Tm5ATlvGMJBiwBpFUghZKgSausZZkfGoXLxHQULxbqyhRQahEJmOMWIuDQV7T5lmHaZ0CRk0WGulAC0+pVSkAdbUYoL1AZLkP1hlhIhY3rfXr6Gv8xFCoL7ZQohCm6CwTvCvusiXfEr4FCW93WiS0jKpLynjgniuxdcX5c9DKP69kpPk+hGjLNpEjKuYTKbsQ2KaFAsrmyeVArthIKBopy05BFIMjCEKRVFrVExYbalaR121+BCY1CL9WF3vSEHRLCzaWoYQqNsau9mzOFpwcbHi/HzDLQWuFr+cT2B8wGlFGiJKRw6hrMMoUkvJA7O004YYAlZZQhQ4QYyR4+WCdtKw261vZCA5CWBi241s93vGIZBWPTZkVGXRKCazOc+evmSz6xm6nol2qKYmavHivNL+UyYpZW+ttGCYbyR6Acr2M+QDmSrLlDUlxkFoT7ePF9w5mSCTMEU20F1uScaiF1OGLrDpOpQ17MaB86s13keWyzntRIqmQ2bcdDphGAfZbGeZxlunSVGuLVN8OKMPpahKDMNw4y+IQbxvPni5L5YNsg+Z1dWW509fYMvjQmsjAzVnCT6w2/d0PpAbV4DfEoExbyeMYwGBIBk9+37EugplNS5aGmNo65b5Ysqw2xGNFV+lNZgc6fxIv+8I3YAiSVAtWabelaY1RrbvWabwaJGzlt0eIXm0sgzjiDEaZ0W+HGJgjJLd4rTGWI0KIi9CfX3Lkdm8ZTKblOdXoqoqebYZg7G6wJMqxtChjcZWFYt2QtePnL+8Ytd1nJ0uuXvrBKXg8aMn/PVPfsZPfvgjzi8vObp9n+//1u9w995dnM0sl3NqZ/n5T37KrttS1RWuqqgrix96fvJXf8mzp4+J0eOaKSent7hz9w32my3jONJ3O/wYcZVjsVgwm804Xi6pKydStFBhtcG6qgRPi88mlYFoLsO4rBBabvE5y8RFFdWJZDKFIF9HaXh+fo6rKt595y0++OA9Mpmj5YLpZMonH33Gv/gn/y2VVszu3uLls3OGbSc1lTaSda0VIUSqyZTJ6QlOG+J2i3OVbFRyQuWIcxW6qYk78VBVkwn7vmO33ZJSZt406KwYtnsmt49pmglGKfqdhJvWqaLfilw4xigesHHLyekRVWVf1X8lNzLdDGl4ja102IQf/ijPWGNE0WSNRD1ksuR7FpDKdNKgR1/yDQc2+562qWRcmROuqXBNgwoeXRv6AE8vNswnDdNmZLcfwIiHKQWRQzsnCPrWahSJYexv/Mz9bif2g+YMP3j6sWMY9je058O9HMoigizPRSWD7ORlU9d5x+p6ix89l5fXPH/6kuA90+lUhj/9wCeffk5Smb/zh7/PW2+8wZ27t3j+8pLLy0veefMN5pOWn/70rwnDwMsXz5lMWmaLGc/OL/AxMJvUjH1PU1VMp1NcZSWeI0ntmdVvTuXy9b07lePQ+PzbtkohhJtGJRYsN2X6eAiclWLZlMyQksysFM5VeO8lhyfJJP7wb77e+By+5k1TVXKGxLCnf62Ze+WhKtQ8DP3oCTFLwn2Wdfi0auTh7jOjTzw/v+RyveP4+Jj//D/7E96+d8KisSynC/b7ns6PDGFgNpvS1i1DP7IbRp5dXpNz4PnVmvmkoa0Mw9jTzBfsVj2T+RLXzAhR01RTLq/X5OTpVhvibiQox/LsDlfPnxCjJ3mPMqFs50zZAIkOXZPIIbySH0hdcCN1VOgbEIb3A6pMKfzQEf3AtG0IQyCEHkiQpeDIURCspESK4eYGnYIEPI7jSAyCFQ7eS4ZRymVDWOQ5BVtLoVaJLCdQtULkc1a2L4nIdDplMpkw9B1jEPKUH0Z2wdNPG8xywrfeu0fVOCY1jOOenc9YV9N3e5rJjCGIT+tyu+dXn3/B++/cZXV9RVNZFvOZbAFCYLvZsZi00qjHcAOfIBfynZH1plB4Dr6SUCZcFSF4AZTcZEMkXNk2xChQAko2WNaCytcF9z2OI1oZclL4JOe0Rch8KDFvOm3EqJ8o2ySonLs5p1WRsH6990owxISLEachJCkIMZroEzhDVhllDaGTSX0uLEFtSn5GVqQYJKATCZc1ZJnQxUwg4VXEYhj9gCPTOINJEiaYx4HGQEWmT4k4eCqlUNax3w+kYWAcBkJBu1eVwxTt+q7rcXZCViIXlU2QxVY7XHSE6GAQ1Or8eIKy8MWnX0kTUgZHxhrG3jP0PcYY/DDSTtsbX6UEURefZUqS/ZZgjF7IS2OgK5KtW05kIkO/I4SIsYLNFSy2xmcYVMbqSF38oMMYuTg/5y9++Fd849vf4dl2x+ntU1I7FQ9EDDeeO1MejLKZFXSxc1U5D7V8P30oQxuRHqrDUERDW1vctGa5nJCMpd/sid5zcbXCThp0TuADu2FEOc122DOOEd+PtLNaZD1EzCGTJWe2my0pxfIcyBJKiYRtaqcFEBSEyplylMJZiYex63piAaQ4I16wQ+bZEDxZG45vLwkx0rYNXT8QQ+B6vWa3K6+xqwTAMg7lOWZQtsK6ms6PpBhwSpPbmsoY9gqssVitUMPIpK0Zk6YfPcYHcjCkoSf7QGV02aaWAVZZpdkCcxiKbCcEX7Z9B8nvq4FZVoZmUgGKbTeUxjYRs8aPnnHwZev59UWHV84KIKVI8CW0WZ554lMW5L9QATXOVmy2ex49fko/dLz/3vvcvXvKOPQ8+Oohf/Gv/4IHDx6w7Tq+97u/xze++U3iONBtN9z9xjskFJ9+/jlj9Ny9e5e33n6LZ8+e8eCLr/j8s89ZX1/Jc9dqTs9ucXx8wsXL58QIm92efuhx2rJYLGgnM1wl/qacobKOnd9ijaGuqkJlLSqRsinJyrD3I32KRCPZfCiwzuIqAXoY50QKXor250+fkrwQH9997y2JRqja4j1P/NP/9p/JAEHByxfndNu9+HpTQiM5O5TIgBwD4zhgbCWby2Gg0TI8UVlkgtZorJNIDlLEjx1+HEEZSHKekyOVVUznLcO2J44BnSEYjUbClKviBXJWJHQiA5YN2k2RnvJNbfe6hVfmkAcp/EFqemg8Dr5g8QMNSeIotFE4pxlzIGv5XOcsOcg9kJAgBqaTmuW0IRcfo6sci+WEl9crgQIpTUAaNGc023HA4kAZXFVDGglRNrohJIx1qMZgUqDOU5TRdLsNqd+L7BKEkFw8/TlmUpIMwkym77ZsrTS1OYz4bsBZy9vvvkPTtjx79pyuH/j5z37Fbt/zJ3/y97h964yzkyOePX8BCu6/8ybtfMJHv/wVDx8+oGkbpt94n9EHvvrqEfdunXF6uiCGyHazoZ20MphQEWP1Te7pb+L42jdLhybl9QYmpYT3vhCR9E0zlbM8wG5gDIpiRMw34aDWuSKLSGgrU0sfvMhSXmvEDl/n8G/92vcjI9DXispf/5jDtFEQ2YGMYbvbMXhPO2mYIJkeV+sVfgh86/1vcHJ1we2TI777zn0mVYWyiW7o2Ow7hujFUBozq+2OIUQeP3lBM5kymyaOhsB7b72B1pmYM5dXK67WW1wtN6qqqiAE3LTl+YtrHj18zEefPWDjM2NSdMOOqCPKVmhjxPNjnWzCMmSCwClyLOvvVz//gRSji5lZRpGS7aKwJD8Qfcfi1gnXfiuSO4vcnFWCUpiAeM/G0bPd9UQf8X5gv98x+kEez+VhexP2eVi6IHJJo6SY0sZSuQqNwSgt+n8FdVWRYyT5HuKI0warLU5r/NhztVrx5Ilmt99x6/SYJidmiwkaS9etaaoKSkCf1pqxjzx69ITr1YZagx+tNLfdjrOTY9q6YRV3NHVF2zQYVxOHXopYI0Slw9bM2koIjkgmiyk+gRjFnIsSmWPMGVUa9ei9TJMNgsKW7qkUltKYj6NkLhltyvmccU5uCyKVSTSVK1N6yXk5TBdvzu3/wVfxv98jJJmchyI/y8rgcyRpaRKHYbjx4YUUqcoGT9LaA9rAGCVYeT7VxGFkFz19KfItCLoZ2A8jLgSSUTjnUIMHLySpNGkIKTKUIECVDQwjMQZ8ilTWllwRuR5ErhlQ4tIv9DRNDAMpW+aLiUhOrSMjfiJjnTRHXV/eR5EHtm1F34nMJeXE1fklGI11DmMtRmlcikwnDT5n+n0v17WzhUKXub7e0g8js6bCj/IzRT+KJCRGum6UwtFA0pa+76mMYXm8pF0s+eyLT5jcuUewJ0yTYhx7UhTPktFavIVZYayEeKMoQcky0dXGiJSlSFEHRk8AAG3ISURBVLqyKsVdlkHLuN8zDr3EARiFU5FxLWGgmxgZV1uWzmG8x8eRqmnLNihSOyONXxYpaoiB/eB5cXlNv+uwzlBVNd7LdrtpGnSlGAeB9gTviaXA2/cD/X5XtilyTU0nE8HOJ3nuECP9ILLdpqlICCWr1Fy0kwn79ZaYEk5TvJBGYDg3OnM5pxtrGcLAZrsViZdS5BTou446OVTQxARjiujK4tqafhgYQ8CJwki24j6iYsZNGqKCGL3InCggnyyFbSgF4yHA3eTEZtuVoVkmI/fIXBrMjDCE/NeYqllV7gbeZIocURVFSgiRECUeBKCdTtnsLnj+4jknxzPu3P0G1lmeP3/O559+xs9+9nMeP3yCqyp+7w//kN/63d/m8cOHKBK//VvfYzeM/LN/8k958uQxP/itH/CNd9+j2+/46osv+OLTT9lvt4SYqOqK01u3Obt1ysvnz3n+7Dn90JFCwrqadtJSN41sO7RmGDyjE0nnpG2E2hsFeGOswenMOPjiFTKMQWTG481mN6OLZ69uLLPFXKJOKhkA7Hc962rLW2/f5/79e6QQ6boe6xz/9X/1j/nFX/+M2WSKHz3DvrshwiqE+uiMNC1jli1x1bYsT4+43O9RKUHxpItKTPzLpAwx023Fz6eMRWeFRRRErqpo2obJpCYNnhyEDptLg0aW69M5x3Ta4ipbGuIi+z14JQ+lTSGOFaXaqyOXEG9es2ko5LmdlMhWo1B5QxK6ZwiJHGXQNIye2oo00FamEAAzVWWJZGxlsEaxaBuayjHuBwwCKJLBiNwj+i6hUsAoha0alE+kuiaFxHx5ymS+4Or8JevLlySlaCZzuhDwQ49KHpWSwIzUwcJSmuGc0KYmoej6Hp3FH957z+XVNb/z7rvcvnOXzz//nKePHvPJrz6h7wb+k3/wx9x74x733rjH40dPSc+fc/v2Gd/88AN+/KMNj778irquOTk+5uX1Bj/0TKbfYDmfMQ49282Wqq5p2xq0bDN/U8fXvll6vQl53af0uvTtQOE5tPKHAv71f+PQ+IRygY7jiNa6yPNEU344+2OMgsMtJ/3rzVrOWUJri/EmJgFLpOJZkOmZ5AGkKA/5nBX7biSlzHa3o3aayaxhOq+5/cYpDx+/oNYKmyNDv8fkSL+XVOP1bsPRYkHtavrR0w0Dz19eMJsvWK+3dLuOb7x1n8mkIeRAozTb1Zb9dlfCxgbW1xf4GPny4684f3HOz3/5GVfdyPLojHa6RNsabQzz43scHd/ixYsH7K9eYlUjr0mKRB/KEqncIbJ+7ffy/H41SUnycLdWCgDgxfOnxLFHKSlstKtQyPencqTrOlw9YbfvWSyWjKNns1mz3+8IXrYoh42eyNXED1T2jeLvKEQqlfJNknZOBw+aZAb5fuCy21JZzWazLcVXZrZccrSckYxhtljQ9wNWnfD5Rw+wpuJ6v2Wz26J1zWK5JOfI9WbLpK54/OQpFrh1esLt42OOZgJS2O/3TKeTktMTaasWrRV914nnQ0lDo3ISSUNp5IX/cfCslKa9bIwky0V8JBRUush4XmV+ee+xlYOyVTC6+PgyKF7JVp2z2GxKkyrXQ4gHqc1BcFOCh7/GRyi+xxgy2mYgUJXwaR09plCInLX46Ale9PAYTWUFDnHozS9XKzSZ0csWNMSEVYH9mNC6eNlShtHTdz0mJ/ARrSxpHBlJDDGy855UGqOoFD5GlBKggtIiZ6q1KxvogWwt+37Aas3FxSUqHzOcHbPvRmbzCbV1zOYN4xC4dfcWaEMI4s10lVypk0nLrttjrAFl2K7W9MNI3bTMZhPmWnLZDiGTu25AD6MMKmLGVo719YbQVtRtRUyjyO6SLgUGxCAbVKUN8+M529WWdtJwfO825umXPH/yFSd3ztjuB3Zdz9D3JQJCOoucuQmLFoVAkbOpWKAP4ppQJRvvMN3PpZkc9nvuTSoJqR0CDCNKJfadJ1uNbZwEx1pHPw6EkKgrh9WWpnJFNitKhavLS7rBi7+xH1mvd+QcmUwmMum1FmsFebzf7djsdmy3G0IQyEvdNNRVTdtUUmxbcxMd4P0IKKaTqUQYGEtM0HUDtrJcX19xcX6JjhlnrWyogjyXfBBoR0hCVwwpM2ZPGgUCkkLAVBVOa3pdkbwnFIlVwDOkiA/pJjg1p0SOSa6TFGC3p9cQcyKULXgIvoQdJ7QB7yPWZsgOlRSpkO9q59j3exn8aEUum7acowS9f00PpUSWaYoBX6i6smkIMZIyWNcQ9ntenr8gp8y3v/0hdV1xfXnJo4cP+OlP/pqXz55zvVpx6949Pvzw27zxxl2ePPiC2WLJO++8y+X5BR9/8ilPnz7h7HjJNz/4Bs44Pv3Fz7h4/oxuv2P0I8YZpvM5OUW++PQT+q5nv9sRibRVTdtMmMxnQixbLErMRChUNoPJmbppbghomcwwjKQYZSCgZUscsgwxcy6e4uixxnF0dMx8PqNpWqaTKVfXV6xX10wmDc2kZbmcizzRB1brNX/2L/8VKQSuLi4Yuo6UMrWR6A7nnMjFtRBcfTfIwCSMbK9X+L7HkG48i7aphO5YnosxibRdZ0PjKgrPmLauqLSicpqqrZlrw/Zyg1aKuqpk+xvkWnCVfiU5LzXMzfmaD372g0St1CC8ojFTsOAUmdihV0o541MmRAiRYmUoWWs546zAeYZ+hEpCxCtnmDS2DJRlu55jJlrxJR8t5uy6nrwV6e4wjPicJEPPVcQomW6V0zeDjsXt29y79xbWVtTNlJxgu1mR8CQiILYUZVQJMxdKYk6ZHBM5eEgVyihi8ITkMdZSty1ffvUFw9DzzW9+iw8++IB+1/Hs2TO++uxz/vWk5Q/+8A+4c/uEO7fOeHF+zssX5xyfnPAn/+A/4snjJ5y/fEnynuVywWa95uOPPuf73/+QxWImWPSuY7PdUDdNiQf6zRxf72bpsLl4rdk5AB0O2xy5gOTEPGSBSA6PGNViCOWBKtuPg8fJlN9jNMqUkEl4dfLzqjmDX98ylWw++RgUIaYS/JcZRpGj6LL9kuYqE7Nitdpzerpk3/VMp1OyT3S7DU3TUFcNOXlevLzEVQ5bVaQcmc9n1HXDdtux2qzZ7Lacnt3i6bNzMBXTpqGtHd73bPcdp8enRBLHx8e0kyl57GiV4tmzC37ys4/48osvaOYLvvnhd1ivr8hxQt1OGbs1R3fewbXHvHPnDl/8+M8I+/4mwFTbhrax7DcXKAFygxadvphBo/ibkCnmAccdg7wf4zAIVYaMM0LacUooQuMwkHVPVUtRse+2UhReXTIOPX4UDGiMHoJH5UjKEaXyzQ3TWEVIBUGsDWHcEX2FqhohWA2DeH3sSIqeaVtx92TJ8+dPWW02NDaxdPcJ3Y6f/+Qn7HdrPprPeOuNNxhCojk6pZqeMIyebCy77Z47t8744L13ySnK1G5M/PKXn3L7bMmbb92mnU4JY0+ymmwNod+hdaapHXsfhUcRI5URYmDMCrSFFHBlWxCTgEko5+ToYznZJcAtJVnZG21fyV/IVKXZt/aVgfdAozqc4+kAcjAGa8WfkkK8yZK6+bz/Ma713+ghDZ9WUtShBNmqsmwqamuZtJZu1zOOmj4JvcsqxeA90ZbcnJy52kn+ESljkRus0RIwbJUhJXBKiWS1+JpihoEIumLfD4RyD4opo7RjCL6ADTLaWdI4kHIm5Ci5P02Nz5l2MqFZzKlrQ4iZq/M1dd0w7gPjZCRNpVCo64au74jJo3QjRmolQyVlp3T7jqqy1JOK66sNKSY2G6EHzJdzXBk6VJVltdqyPr8GnZjOp7iqYbvd0k6k2HBVjbaKaevYdCOtc/S9R1lDezRhyCLpeue9dzi/WPHxL35MzpnZ3/pbpCDQCVuZmw2NDKESSh3kIIqkC6I3S7EadYJSwKkb6UumGwb6YeTiasOsclx1I3fnE8auJ6jEnTvHHJ/OOb/e4L3IKo3OVNZQV4qjowUpSIaSjxJ0WxlLriqur1aEEJnNxeNQ1xW2bAJ32w394Nl1e1CK+XxGVVfknKmrismkltgAI88g7wMxZNlyx0SMmaYy9Pueq4srlscLNtcbwjByfLRks91xdXlFt99LDk6QzbItOW1wuEYTfQg4leljwOIwQehpvR9IUYKnJYg4FxCJxmTwqjynYiTjCT4QYmLSTvAxMsRIREzfSmm0zlitWTRCGBPkc8Jpi9IWCIx+RJtXBaTSX98ddc5gjUMbXZrdgjrIQhnNMbPfrtlst0wnLYv5gt1uy6cf/4ovPv+KL7/4is1mw/z4hDePT/nu975LPZ3y8sUL3n7jTU5v3+L58wv+m//mn/Do4QO00tz79jeZVJZPPv2Ejz77mIuLS1bXK1LKLBenxBi4vt4zjl7C2hPM5nPapmE6m6O0ZjafYa2lqitOjo+ZTOoSng1V3ZQMvUzwo8REoAjBEwulNRcqpQyUSxyLKnk/RTJurGG5XGKU3CPv3b0LCqrKEJPhh3/xI66vV9y5d48nDx+RYhTlR9ZSvxX1QopSsNsyONitd3TXGyyZyjkSiqTl9c8ogenESBhHrPPUVUuylnEQQmOIgXpaFymXo6oqacSQMNiUMuPoxTdKvhm0i6qunKvFtiHu4circFppnA7PUl2GN4fXKyeRqqI0o0/sBs/59RZjNE0leX3kRMyR3vfSjBtF9J62Nty9e8xm38szQYkbO/jIet8TM0Wer7DOiGhcK+q2pkLho5QL0Y9YH4k+cjRb8p1vf5vVZo1zjs3mlH4c6PcrtK7IJso9tsCNJLZBvN8+DIy+oo6V1NPkAsCRWjz6wKOvHsjWT2Xa2YSjk1MuXz7no19+xPHJCbP5D5jP5xyHYx4/eoQi8+Zbb7D47rd48ugJq+s19aShqhzXV1c8ePSEd996g9l8Rt02BB/EV9b/5oKtv9bN0uswB3i1UXqdfndYkQri+NePw4YohvBrgIebQFVeNUSvk/cOHqgDgvlAtzt8zOHPwI2G+YAwH8expGBbxsGjlKx9zy+v2G1HtvuRpq6JyXF+NfDf/flfc/+dt2VrkBPNvMbVim3XcbJcYJXmxfOXbLuRfui4c/sWT19cUNU1wzgwm7UsFnMuLs85Xi4Y/EiImZfn12z3I0k7njx7yT/7l3/Gxb5nfnbGZDLDe8+smRC6oRBRFLthz/FkgQFZ5SI5UDL1eXWRqAJykIT7V6+hQgJ4BUSgCj42FKlNyWLKcjEeJDUR8MHTWCnQgx/xBq7KVmkYO1JM7MNAjkHCg7NIHIWwVC5w78lojFXk4NmurqmaKWjD4GVKAlC5AaehqSr23ZbT27eYLudEH/jFLz7m9PSUW7dOaKdTfA5Enahax9XlCzSWtm159ugxdTNlsxl48uSS2ycLhm3HvXu3CCh+8uljnq87KuX55rv3SYhvY9Y42rpC2fLaFdgDKhNTQBsnTYrWN8WhNpacFNa5G0CDEIgE9WysEN0CgsQPoWxNys97AJzEQndDvUZ7PDRN5XqqnJNNm1wQr64x9fUtckAMymMMIitTGmU02ikWk6YUGQkbM29MJ6yN5vPxkphk6qeUYoxJsmVSovee7D1zWxGLvCWRqaylMpZ1HwRcogIpQ6XkYRZINEaRrSENshEV6ZWEIsZcaJ+leXXZ0ZSGedtt0dZReUvbONq7t3l5fkUMI/XxlPnRXOaDKVE1jqWdsV9vy0ZcDMd1XRf/Ty7kTzl36qYiJNiud/hxFJpakXqk4Am+Y/A9282e682OtpZNwr4WSdnxyRFZK+rJBMj048hkVnO92qNeJsYAdVPRNjXf//632O+uePzlx2w+/ICh25NzuNngpzL51kphrJMMmhil8ejFJK2KZF3uQdxs/VMpak4WM2xOhCQ/t5m3bGOgnrVErbi6WnO12TNbzokx0E7EEzGZTsjRs1lJI7XrBV08aM1u+5K+65jNZ+TcCn44Z66urtjv9yUnRhqLtq0xhwm4sczncyT2TGR+/dCjjTwzmnaKrQTNrDRklVkuFsWjGbl194zZfEb/6Cnb9QblI1ZpRpVuspvQ6mZrba0tAyELFE8ogg8fUy7htglX8sWs1kUyHtFAF4W+GWJiP46knGkbkQUPPhRfoyakhFOKN2dzzhYLNjFxtd/jKkNbOdRa5tkhBkFuJyEyfp2bJaM1IQVyyUvSxpRQZM1QtqR933N0tKRpWq5XGz777AE/+uGPePrkKTHDrVtn/L2//8fUTcvV1SX9bsO3v/Nt6qblo1/8kj//4Y948NUXWG341rc/pG0a/uWf/ik//qsf0/cdu31HVop2NiGmWJqbXKbthsl0wnI+xzhpNqwRf5nWIsWvnKNuasYeKmNoJjV9L0CRGCLpIIM1IgN75VE7SMxEwaGUZr1ZM53NmM/nnN06onIV223HYjFnuZgTg0frORcXl/zVj/4Si+L6/II4DLR1zaRuGXohvIYQwEhmoihyFH4YAfB+JBnDpGnFdxwCQSuCMlROGggNoshREvo9mTVYU+GMZn48Y366KD8THJ8sCaNsdrU1uMrdPAspdaHKMgAmiwztMIzISVQd3ORLleboZhgp9yFUgSMc5HvFA1VXTryhCnKIjEOi7wL7Tc9ODRynOUZrnNGoxpVrKNHWjuwyo89s+oHVaisB4lpAXLrAnu6fHHOSBp4839FhMGSOVcuV8gzDQNtUaOYkn7G2QilHM7+FrntivyUHaZ58vytbvnQzhhGIFgU+MzIOA/0wsFpdy5Y8wVdffMXFxSVvvvEmd++ckaJns93w0x//BKUUv/0736eylqPjEx48eMgwDrz3/ru8985bvJxccnlxxWzS8tbbb7K6vuLJ0xe8oTXTaYNzLc7bArX5zRxf62bp9SBYKPr11xqoGzz3YcOUM38TlpGzmPZSPKxsCz2tiE5jiOXGVyRIN9OFf3OrdCgqrbU3DdXrheQBDpEzDENB1XYDvc9su5GL6xV3NnuMgsnkiGcvL7n/1jt8/PGXaKN4+627XKx6tk8uOTmaMwwrNusdxijaxnHr9j2ePHvJF4+fcu/uGSfLCXfvncnKNMPEOUaTOY+RJy8uIBvImsnymPnRCUyj4K9j4urikjiIDOYgQUq+Z7s+J6eOMYxoVcIGlSPmRA4JZWpyPNiFVIErFK+N95JYjhITZMzipcm5IHFD2VhIw2lSIhVEb1NVDPudTKSs5mUxBCol25UQAtEPReuniWEs728qhtDSpGWZcGqrJd/DuBvqoWR+dHz/w/eZtS2PXrzk6OwWt05Oefb8kRim9x1hSAz7QNKJi/XItltxfHKbZjpDa8vMtDhn0EZxevuI5y/O2W9HRqeZHS04dlNiDrhmzpdPL5nUG+7duc3Hnz9itphx7/YpjU5UbUNShj54QWOOI85ojIasBVzhtGQk5Rgk7yInjHHkKN4wl404YKKXQsg6yUoqoIwc040++5Dc/m/zAB7Od/M6+e5vyFm/rkdlHN6HG3+PIbPdFsBFSjTWcVRZamA6mfBys2c99IQsvgufYgHAiAQ3xYiqaxol95+Jq2RaqRSNtZAEl5xykg03Wch2TqO6QCITFHhg5iy1tmy2cl+onIVeFciAISkJhWysgD7GcaSZVEznM2LKbNYbZos5TVOTYqauHNk58dBkgVAIsUukoVopjFJ0wyB6+n4gZ/Eq7XJGacN2veNyGLCFiLYfBno/UqN5sd1hlKJxFVXVEP1LKcB8ZNd7Vqs9y8WUq9WOYTpBVxVRW5pJw71Jxd/7k7/PPx1Hnr14xtX1iuiDFCAI4EQrw2w65b/4L/5zjKv5h//wv8Rqh9eeelrzR3/3D/jlLz7iyy++vHkemCJX9d5z8fKSpau5f2+GCpoxJ5JVeKPZ9oEuKza7jiEFmqYheKEhrvKO5HvGYWC7HQjhVTbQbt+RQqaqRFq5Moah30OGpmkJKVEV4zvFK9s2E5EiaYUxVortKCCFvh9xtcU1ljwC5fmiy3am6wdm8xmnJ0uunl/S7zrJ/9OCMo4xMXE1VpvS7Ciq2jEUJHCIiWwUQ8pUKTJvG/Y+kBIkpRhzxijJedNG0Qf5+o3RJF2z8Z5YhmA+RHJpssTXm7FGMTWOW67irLIknxisYzP0bHcdIUQG7yXUNoM20LSOGH+T4N/f7JGVIhbPyeHWGUMQuWffY63h5PiYEBPXVys++ugT/vxf/5BHX30FxvBbv//7fOMb7zGZTXn24gWurnjvjTukGPnRD3/Ej3/4Q4aQ+M53v8O7b71J0zT8y3/1r/jlz3/G0A1MJ1Mmkyl1O0N8UgNKKXbbLQrD8ckx89lMQCNFet62DUbrAkoaUMpgrSOagDESzhrCeKO+OWiNh3GA4GXYWYZzB+/ZAaCVkkjnnz17zMnJHJyAGd64f4+h71AcE2Pk448/5vzFS3KKrC8vbwAKwzAKqERrdJJNvdYaV1UMgwwDY84kA1ErxnFk1IrppCGUDKDsA7F4ckOI7PsR006ZzWYsT08wJNppTTtrySlLDqITv4/aiw+tbWogYYxsytXNE0/dKI0OMsWDBO9A4qV83A1PXZUhfhalTUYGc0ZnJrWhsi1dPwpkSMEQAiFJoHYck9SiVuBLSilmjXgLZ5MGlOLF5ZacEsMwopVsx4axxxihTo4hst1cg/c0WdFiuRj2XA4D9XrHg0fPWc6n3L1/mxA9q/Uak44Jux0xV2S1QRmh5Ekda4jjSBx7Yl0LvKMAtVxVEXzFMAyM/R5rheA3jCPaGWzjOD47Yej3PH/6lB8DXb/nt3/nB8xmE9p2wqOHj2mahnffvM/tW8fUlePy8hITLKcnt+mGPV989YhZW3F664zZdEo7mfzGrvGvdbMEv+5TusE5wr+BNM4p35C+XvcaHY7DqvTwsTcNV1knWisbqNe3T4ei8m/6lg7G+9dDal8Z4uVmYIxM97s+su5GVtuO3TByebVmOZOJdkyR4+Mp7737Bj5Erq62XF2NDKHjxcUVq1XH6CGFgTfvn6K/fMqjpxe8/c6b1E3LyfERTWUZhj3GGCn0U2az2zMGKZCtAR+FpDI1FZvNRiQvKbHf7wR/W1XsrwdcP+AHT9xdCJlGC6pRT5dUOWNVRoWBzfWlaNtLolAum2nJSZEQ1BxjKVA95GJop0jBEuRUfDJOM5tOJNBx7GmblquLi0LXkvygnFW5sYqX4nCTFYe3yHZkdV6mIQlcWzFtp2Arch7x44g2mqOTsyJ9Cew3W7789FNOj2Z88/23+flHv+LFy0sePPyClDJ3795j6AO3b99h9fwp9Z3bfPnkAmzNbDaD5Hn3rTsspwueXz7i6tlzZjtP8oHjRcvT68Dp0SnzrHj088+4de8+P/7pF9w9vuR779zj/m2LbTWuyDuSEKnFqNl7jDW01SufWEqKMUogblNpTM6EUfDmGdkW5VimQeXhF9MhBdtwwKzrwyTttcMYU85jmSAesPn//0DDe+vt+zx/ds7gA4PvqZLDqprVaoslUS9mkGv8KAj72hxgJYJ2DzmjCSV8MlJrg82ZuzOZ5o8hkaLY2HNIWGfLRD/TRZE1DllxsZbsldFHctaSV5ShVppoK/bRE7wvDZdj8L4ERieGcSReX+OcQ4AEFS+en3NydsJ+PzCZtfgYqE1LVRnC0BGjmNFTlCYahAzaTlps5cRThabre4yWosD7AFSoIEX7mIKkwyt346saY2YMA8euYugSaVBkNTJEWO9EBtft9lRNy7233yDudpweL9iNkdt3b/Fbv/d7fPzzX8pE1JRrWIFWDgXcvnOL4+Njfvd3f4//6r/+xyynM56/CPz+7/8O/8f/w/+O/9P/+f/Cg4cPSOmw7QYyGCWhlkM/0gWhHyat6OPhPQ5crjdsu5643TKdz0ghcHI0F09B35OCZ993KKXo1nsJjCyyIaUy+30vPq9K6GjaaNra4azBVRU5R2rXMJu3OGepSnQASJhxiiJVM9bQ1pWgxTHFR+HwVeLZk+f4wbNd71hdXLPb7PCjl2FTks1g7WpCCCINrBtabUEl+qTJRuFzInpP7jVBa8YMJgl8KCeRpXoyLmVqraiV5qiakJWmu7oGeUkZSgikD5FsMjoppnVNTok+eK53HVfDwC5GfIxs9nsG7wVUUhDsGXjj3dtcX2/+x7zs/50eWhc8urKlEM4ltNsxmztCSGy2Oy7OL/jyi6/4+c9+zvOnz1gen/L+Bx/wne99m0Tm4vKC+bTl5OiUy6trfvLjn/Llo0dY53j7rbv84Le+z4Mvv+C/+cf/bz799FNyTkync7Srmc6P6Psdm/UaozV91xNjYjFfsFweEZNgpIOPVLWlqmqathHCZ2laYxRrwH7f0TQ1fhhJMZFSkGbQOoIP4hlKIkkzRYIst8RXOYub9QpyZr3Zce+Nt7h97w5vvPWmbGuBi5cX/Ok//efsV4KbzocBngJlhGKpnYNYwl4pcn39qk6r2ikpeCHRGoWtK46nE3K/Z+h28v2jSMoQcqaZz5m3tQyojISvGqNp561c05ueHBL1pMa1FcbqmyH7r8XUFKjdwf+eUhIy742fvajhbyR56tVQGFBILpVW0FYGhWa7H+mRDVpbWYbKst52aG0wlcEVWb3SEm6tlaZuLIrArhOADClSWfF5RW8Y9lGGczHzYr/n2arDZoVNkcEYrshsQ0/qtjx/cUk/DNRNzQfvv8euH/npzz8jZ0NQC1Lscc0xxD3juBMZYRoJwwBT+alCCLLVVhkfA8MwlFy1TN221O2cy6trtIL7997AKMMXn33G+bNnRB+waN7/xrvMlzPW62tePn1OpRTHp0csljO0NayurgXAU9UMKfP85RWr7Z67t2/jqv9Aw/vvPQ6Nz0FWBEXSUDwZ/zZZnVLqBrrwuszugHSFV9siWa8WVHCRLB0+/3BhHI7DdukgBfybEj7v/U2DlnMmhMSTZ+dsxsB+N3ByfErKGaXBVIZJW2Mrx7e++QZX1x1XkxljCnzx1Yon5x3bzY5+P7DvOz756jHHx0dMJxPGcWQYRpnm7nqGYRQPVlJcbVdsdwPnL6/ouh0xDvi+Y+x6fFLMmwZvLavrFVorxjASolAFnREjb7/fYdtpaTwii5NbhBAZ91s0hqxXQMJggUxSB0mijKYO6csoLZrfMrJK+TW6YPGQ5BSYTSd0+y3WNvT7jnHoCT6iEKNhCNI4KCWSQD8EtC4eJnR5/zI5ecr6haHrCjRB4f0oN05rGPqBrx5c88bdM9LYs95esL3I1Mlz7+iE7WrPxWZLO5uhraLbrFiR6MaBzx88ZNOP7PeR+3fvc/fuKT/55Wd89XxFHxTNdE7TnPPB+/dIrqLbWT768oIYe9rW8WT3iF3neXb9lL/41UPevzPhd777HrdOjyAFJk2D04rKKNrJRDx24f/b3psHWXqW592/593Pfrp7pnu6RxrtGxICLECSjbADMkIo2MZ8XwFWEQcIFFikICYURdkYyAYhKSexK4nzhw1JxTafXR8WX9nEtpBYbCyEJGsbLaNZNaOZnt5On/3dnuX743nPmWkY2SiOmOnxe1WdUs85r7rPu93vc9/3dV+XQuZp0bX0yaUBESO1HWKNx9avqTkT4WlJJfCLc3DK0HNyXWutrfTqaV2lCY3Uqk7anyc6+lMz6G1Ow3NcB8cVZKPMKmSKYrFjFLXAx5GSNE7wDIwzST9OAOuNI5U1PnSBVClkrvB8gVskOSF2IHYs9bRjFGc5wnNIlY03yrWqcqM0YTCO8VxLy3Qdh0TmIHw782EMaZYRej5OEJEW1MFKEFnqiVGkWUpNhHiBhxIaP/SIKgEOgqhiPVOEwIo+BBHVetXOa03mObEVVeE4OI5HEErCSoQymuFgxHgcYxQo3yHAJ0ssXa89W6e72SWLM6S0CqK+K/C8iAo5odGkUmM8h831AXma4yqD2+nQqFQYJRnaCIbVFFyPYTxmOOpbpUpdWBI4LlJKlk+u8Kd/di/XXXct8/M7EMoQVSLe8A9u4c/u+QbffeB7lipTdF1tV8ohzXN6cYyKU+LjK8zPNm1nMI1JM0UQ+AxGI1ZXOjjCJck1jUadRNv5m83NHiZL8TwXlCZLcrxGhWq9Yl3vC1+lqFLB9Rxcz6NRr+F4Dq7rUa1EheiDi+87+L6da8oL8ZR4PCaKgsLQVlHVNaSGLM2sEazj4DoJYNXJ0jQjl5I8zwhcOwDvOVbQwXVcNDmZVihHMM7zYj5UkGuNNNpaE+R2HkwIMK5fPLfsnEggBFXXgzwjcq0JtRMGeK4zVYzN8hytlfVOwsNz3KIibuglGQIHH6gJh8CFvi7ivrBKWR4OnutjNKRxetZiwN8VSil7HMktvTYMcX0fHEOeKbr9Lo8//gTHjh5jfX2NWr3Bldddi4MVker2+rRm2ly4dAFG56yvd3jwwYc4ubxCY6bJ9S+/DjLJN++9j4ceeoDNzU3AEFVqVBtNdswvEicpppA0Go1ipFLUG21q9QZJmllmR3EvBEFgJd8ziQG00owGQyp+s/DWM4X1ilU1y7VCGYXQTlHwdUDowgzUMjgms9+i6AwZbYgiy/C45JKL2L17kZmZGeo1q7T3F9+8n2f2PkkyGOMIQSWqWIYPhUBRrjGOi5Y2kfI8H5kmpBiMW1A+lUQmMcbAKHaQMmP+gssQueTk0aOkcQfX89DGdoICzy3U4BT1dp2oVsH1BF7k2dkybQtiQRTg+nauGgBHTOeObEF2UggvzJmnszx62tHGmQg2nF541IV2ky3mW1VgO3ckHEM1tMVbhKERBXSEwMF6tmljyKQVE5LKridz30H6lo7sCqt0FwVeIdJT+A4J2yHUGnInsP9OJYmSZFqisaqdaydPMupF5GnMNVdfwbVXXkG302PvxjOoTCNEgBN4qDgvZrW86RoulxmZtMqtWuW2u1fMpmtjMHlGEsdElQqbWUY8GlFrNpnZOUeaZSyfeJ7hoM8Tjz3B3OwMF19xCTLfxcFn9vP80WNcfNmlXHHV5bSbDerViI31TYbDIdValXprht5mh4OHDuMH/kt2j78o+ZnPfOYzp4QTitfVV189/TxJEu666y7m5uao1+u8/e1vZ2VlZcvvOHr0KHfccQfVapX5+Xk+/vGPW07q/wZO7ypNF24F9e70ROn01+nbT+l7pvDuKdQ9Tu8EYU4Nq02q65OFppSSLMum209uktPnm2xyJE5LrAqjVGPY7HZItWSz37ND5cKlXqlTr9VJkoQkiWk2mgy6QzCG3qDHiZUNnjlwhCef2k+3O6DX73Ls+RMcO77G4aPHyfKM+R2zVKIK40TR2RwgU0vDO7ne4eiJVY6dWOO5Yyc4dOQQMo8tnU4IGtUqge+QZTHCMYShnZERNtdAGKymfVTFC+sINwThEAiXKIrwPB9jLA3OKqzZNMhxvVPS62iEYxsbQpgpT10XCakxE9lNW2HxHJdBr0c8GiFlRpqMieOxTby0xKgcxzHIPAVsBeqUIo3Apgx27seYHK1iHNf+PBx2icd2dsNxYTzo0t1YZTQasnz8OPV6hUrokIzHPP7UM3zv4SdY29jEcTyuveZq9uzezc7ZNr7nsTkac+mlF/KyKxa59ool0nGX5WPPodKY+ZkGO9s1VpeP8vzxZZ7ed5yDh1ZQue36DBLNamfMxuombp7T8D0W5ufw6jM8e3yTh/Yd476H9/H1h57hz7/3FPc/c4zvPfEsDz/2FI8/8xwHj21yspOzvD7iqX2HGI8zVKYxUpBLgVKgpcRHImS2JaHfep1uvbdOv5a3YEun1MqVT/Dtb3+bt771rSwtLSGE4O677/6B3/trv/ZrLC4uUqlUuPXWW9m/f/+WbTqdDnfeeSfNZpN2u8373vc+hsPhlm0ef/xxbrnlFqIo4sILL+QLX/jC3xovXhiasBJiKOSQpUQYQ831WajU2FWtEnk+WkMitaUPaUt3yrUikzlxlllfNmN9iNI8J8kloyynl2SM85x+LkmUJsWgXBfhu4SVCM8LSFJJluekWtJNUxKtSLUiU5pBailLrgDf86kHES4ONT/EMbYzFCcJWZLS6w/Y7A7J04xaFNFo1Gi2ariBRxgUnlzGFpTCyCfwPYS2Pii+ZymyvuvZRb1vq+UTKfkgDKz/l2PVmoQrEK4LbsBolCA1jOKUzW6X0ThmoztgfbNPohXrG33W17usrKyRFB081xf0N7v0BzHDYULcHzLq9dk8eRLyBJUmqILuI4prDQFpmnJieZnV1VUuWFpivdOl0WrSnpnlq3f/Md1u117Xk+tbK5vgCEGcZIxHY4zM6QzHrHcHdLoD1jeHbG4OGfRH5JlE5oreZo/eYEx3MGajO0QJj3ic0l3tsLGyxmgwYjiyJqM4giAMCYIQrRRRGFpZZsfBdz2ajYZ9L/TxfJcwDInCwM6keZ6V2HY9wjDAD2zS4ham09VqZVqN9z2fVqNKJQoYD4fTgpkjsAtHlRMEPqHvEwZ1hOehEAxyychYT5xYKVKtbSe18DkSQYBfqWBcDylAFHL4gzRhpCSbWc4gl3QGMTJXyFySZhlJmpGk1rcuk1YNL80zpNH0ZE6qNDNhyHwQsDOqUPF865k3Gf42kiD0iYKwsCrYnnFkbW2jkEf38P0QgUOW5oxGY46fOMGhw4c5cvg50jRjz8WXcuXVV3PFlVcwjmP2Pf0UyWjIwtwsURTRWe9wYP8BNnp9Go06V192Ob1ulz/586/x7W/dx2angxAOlWqdXUsXsLTnMqJKlTQZI4RAavtcbbXazMzMYYQgiZPimFsxBM91cAuDVwdBd6NDt9sjzazXnxGa9bV1OptdRuNhUby06qrGTIpsHhSLft8PCMOIKIiAQvzNsYp6uxZ3MTs7Q3umRZ6nDIYjnj96nIe+9yBZmpEWlN5Ws2nZPcbSSbUx5HEyZTtMjNSNsl0mmefEwy5ZOiaXtsOhtaHWbFBpN6jUqnhhYJ9PQlCv1whC2y1zlaIaerTaNcJCJl0ICCsh1VaVoOLjBd60S2YKzr9hQlaZPPOKZ6Qpnqlq8mxVUxYGRUIkpglXkXJNumhCFHLzws5Oaztf6nmCnTM1LliYZa5dw/fsmqrfTxiPM7I4I01yGrUqV160yOUXzrNjtoHvgTCa0PcIXJvUWrl3bPLnukgHtNA2qcLa5mx2N1jf2OC5w8d4Yu/TnDy5TLPdpjk7h2f6CKzokHEC/KhFpdbGD2vFfllPKrfwtDTakOXWE27SqU6zlDiOGQ4HrK2cZP++fSw/b4v8e/ZcBELQ7XXZ+/STrC2v0KzVaLYajLOcx594kr1PPUN/OCQIPGZnZwiigM5GB6N0cZ371q/pJcKL7ixde+21fP3rXz/1C04TTvhn/+yf8Sd/8if84R/+Ia1Wiw9/+MP8/M//PN/5zncAe4Pdcccd7Nq1i7/6q79ieXmZf/SP/hG+7/Nv/s2/+d/agcliblIBF9+3kDt9u9NnnPI8xymoR6cjLwbdT0+Apv9fkTAlSTL9/adT+k43rD3195zpjSWmvGYXgyKXknqjzpHjJ1mcX2BjfZ2e79DpBHi+T38wxlleY31zk0wLvvOdRxhnsLa5gZbStrmFsAPHm13arYvZMb+D3mBAr9fFdR1a9QrtRg0tEjb7Q54/sc5aLyGRivWVZYyStHbsIKpWyDNpfRiUVZLL8gxHaxxt1ae80EcIh3p7Bzqzxo+2TS7t4KKSVrq6mP9xHd8GKnv3WJUdNMpgzeSKOpgGG1AcbFVzMndm7EKh3+syu3MXgecyGAzssKRW1nSt6HxZ+UxpTSXRCNfFJUDnmT0HWMl2rQyuZyWzReGkLQTILEVlMY7OSRJNPFBsdlYtX9vzMY5LSk4trLGj3USPx6xudhgnMc3WHGif5488z4W752m0XK64ZA+PPXWAhx55hFQKau2duL5PZ2OFJI45fDin1ayy54LdVskl0xztDmi1m0iTgQsXLS0x12ww04hoN5q4GEbDASbL6cSScSpROuHIkeP0+33azSomH9N49Cl2zrQxCJ565jA7dy/wD9/yEyzO1qkFCg+rQCjEqbm/SYdp0kWadGMnXdQt1zanzs8WagIwGo14xStewXvf+15+/ud//gfu1y984Qv8xm/8Bv/9v/93LrnkEj71qU9x22238dRTTxFF9kF75513sry8zD333EOe57znPe/hAx/4AL/3e78HQL/f501vehO33norv/Vbv8UTTzzBe9/7XtrtNh/4wAdedAw5ubpGnk1ovM40WXc8hyD0UMAgThGOYGQ0xnXtTJwp1DeNnQPRShbyzR6uH5BgpZ5xXauT5PskWoLjUfF8Wo06GIdGGJDEKc8N+2TGEEurMuQi8B1D1fcL6wPwHQ/PCwgCa5CrjQI8O9fi2AphlmZkWlJrV6k3q1SrEUbYpMcRtjGotaWheAKcwAdtrJCEsn/HcQSOEigAYT23rBS69dARnkMyykhlTqI14zxnsz9g0O+jc0mm8uKOS8mUpFFv0k81SZJTqUXIfEwtcEnjHKkU1cBj0B8hVUpv0Kfb69Dd3ERqm5jaOWhTzO5Y49yDBw9zxRVX8tBDj/HK66/nwOGjnFheLqT27aLvdHq0VJLBsE9Qq1GLdjAYJsR5ak2Bwwo5EpmmhL6L8VyGgxFybY0kaeA5gmTUJxv0CV2XNMtsqTEK6A+sOqcrrAKl7e7nthoMhcO8Ahdcx8cNPHzftya9eYLAsXL+nlcIrNiDbmnSrk30jEEYQ+C71Js1HNehswZZboVCEintnILr4kpD4IY4RiGFIS2eYanRpDInlRlKa0I/BKNpeg5RGLJrcSer6x0Gw5HtWmpDluf4xbyUcl3ixHZ/HNdBKXC0sgpkWiOUIsscosBHGlCOw9BotMzxDDiOTcIpZisxBoNDmqWcWFkhyU51lrZbHMmVIQgrCMfFCOunFo9j1tfXOXHiJKurazRbbRaXlqjVq6xvrHH48GFWV1dptWeYmZlhNBzQ7w9Y6XRZ73Ro1qrsueACOpub3P/d73D8+DFrjuoH1Jtt2nM7uPiyK0G4dDsbzMzNceLYMQSC9sxOojAkyzNymU3p/37o4weFsbjrELg2tidpQp5Let0+ruuSpimdjU2k1GSJtGMI2iWXeSExHuC6XlEgaCBcl8XdF7K5sc7K8vNWXW9uJ7t2LRAG1qw3TXOUzFlZXuWhBx7iiUcfQ2b51DMwS1McB/Jido+CjudglVwtZdPghz7SOCTJCJ1nVlTCVnxp1GpoY9DK2jaEzRa+sBTXIIoQvofj2UKRH/gEUYDBoPK8oP45eN4pI2uEvSHjYcwol7RnW7boLaxSrMZSETFWvtsUEt1FXYeJwNhkVl1MFhyTmOZYIao4syIpUilrEOtaAZpmI7QqnomkO0yRuR1PAEEY+gShX5hZezhuyOJC26pj9kfFPKSDzDIc10V4Drr4N8Xa1PW9Ym7W2mFIZZkxy8eXSeIUL6gy16gxrESMBl2MtqJSQoQI19J2Xdch8IuOjijWX1imlrVosVToKAqZnZ21ti/dLp3VDVzXJ8kzAteuR6TMOXzgCL4b8BM/cSPXvOwqqs0Gz+57lsOHnqNea+BfeRmB7zI31waj6feHRFGFubk5rGPbS4MXnSx5nseuXbt+4P1er8dv//Zv83u/93u84Q1vAOCLX/wi11xzDd/97ne56aab+PM//3Oeeuopvv71r7OwsMArX/lK/uW//Jd84hOf4DOf+Yw1R32RmFS9Txm/FgMybK2On77tZDHuem7Buy2SGezQtVs03KZKYM6pRaLh1EyS5SR7047T6cnatGullRWVEMXPFJV+nZOkingQo3NDoxoxqvh2IC5X4Hn04jFHjnU48Nwx/FrEY08+Ta06g1vx8aohOrcmhIHr4wQ+C0sLxEnMiVWoRCGV0ENqK0sZpxnHlzdY3xzQHWYk4xFy3MGRiubMDjKTWxUWbXCBOElIRkNMntrFtYEsHhI226B8MjXE6BQNDMcD6zifjIqHop1J0kYhjLKtba0ROrOdJddBG4kjvGIBVMi6Y1tYRa8JDPR7XYwTEI9HjMZjslwTRjWEG5AXQ6xaKlzHw/ECjDK4TmCNcx2DLgIaRuM6gRV0EHYxq3HsbS0lKksxMkPmiU0WHQclPJQliuCGNVrzF7CzPcuOVoVRf4PN7ohRouilXYIgIu4oxvkql108z3zkctNrXslll1zOvv2HeXDvM7iNNkFkVcHyXLG82qESVrj60kWef+4g3aP72TgiCOsRtVaTJ9c2mJ1f5NrLL2Sm0qbdqhOnMW4YkY2GbHT6rK+PGKcps/M7cXXK0q6dhI5kOBrz2BP7eeC7D9Ba2EWvs8L7fvH/xm271JwQg3W89guFu4lx8FTJ0dhBzUkyMEmoPM87lcwWOD1huv3227n99tvPeK8aY/iP//E/8qu/+qv87M/+LAD/43/8DxYWFrj77rt55zvfydNPP82f/umf8uCDD/LqV78agN/8zd/kLW95C//+3/97lpaW+N3f/V2yLON3fud3CIKAa6+9lkcffZRf//Vf/99KloaD2BonopG5xPcDEqVIZEamNXEu6Wc5udYkRpGh7UC31kglrZeNygvxGIERmkESUwtDlCsY5Rk54Bjr2eU4giRLqNYrlrqTgeM7EHokI01eFIAC1wWtkHiEnq3+RUGA1FaNLJUZCIdU5hjHIZMZQWC7xDJXhFFAvVW3qmWha2cTHEMQeqRjO0clhIPnOoVCpS0k2BgnpnNraZIyGo/IMkU8SiwVN83p9QaMM/vfeDxCaU21XqWz2SOXmjjNcP2A3nCEH0S4jku96uGhiRotgtBnY22NerPOfCuiGbkcPHCYzto6KIXKxzhmUlAxpwwfC3W5w0eO8pZ/+HJarTqvfc2P8f9+5f+znShj6buYSdW28MRTiiyJGfSHDIcxKs0JXHAjH9fR4Hpo1yMKHPzIx/es8E+SxIgwoD8ckcUx9WqVUTImCkNrdptmmMCn2x9Qq1YIwhCT2vNsfYqqaG2oV6v4niZ0RGGyawojWUGa2gWW1LbjK4z93HOsWJCllks818X3AmQ2JEmyooKtQAhSmePg29kOLalFEWNpu3Ke5xLHhYFyYcLtCk2GJpaKWqGepg1k0lJLlVQIo0m1ZV3UHVtIGGfpdMbXYMjzFOM4COEitZ1VcD2fYZ6TKkWUe8zVKlRdK26RZJk18zQC3xF4wmNjs0eeJts2jrSbDXzfzgXneUZvMGRldY3O5iZZpvCDiAt2L1Jvtuj2e6yuruEKl8suu5wsG/PUU0/TbNbo93rkSrC4sEB/OObBB7/HkSOH0BqWlvYwGo/J05R6s8WFF19GVKuT5TlLF+whSWM66xs0Gs2plLLSsmACaPuMdNypeazMcoJqQJpY24wsS+kPBxgNo9GYOE6AU3ODSuZQsD2CwEdKh1075qg32qCh0WqxvrqC79vu2uzsLDt27KBer9MbDEjiEYPBiJXVdQ4dPESapiipqQYhURhas+zCIyo3uVVu9e1sD7oQHsIay/uuh5v4OIHA86zK4s72LNV6zS7GN7ukSUZYr1GbnSHPbXzOc4njOTgOdt4wl4wHfYyBMIyoVCJbSHTdYizDrgWzJCeLUxqNOoTFyIUpmDGTuL9F4GHy3kRe3artTQYoJ92oiZrqyU6f7jDBdx3Go4S52SaNMCCQmq7nkTjK0t2NVb/DcQgjnx3tOpXIMhN8z6VVq9BuVljvdMnGKWhFnuV4YVjEEAfpiIItVRgOO14xbqbQ0vr8OWiyLCWqVPG8kHp7jjSJUXliDaGKuWfP9Ygq1clUlp1jLmaWJroBubHCUJ4f4nk+rXabKIzoD/oMBgNLhc5z8jgp5tbh4KFDtOfa7F7ajSMM1WqdzsYmaxsdqidqzLQa1OpVduzcgef5jEYjfN9ldnb2Rd23LwYvOlnav38/S0tLRFHEzTffzOc+9zn27NnDww8/TJ7n3HrrrdNtr776avbs2cP999/PTTfdxP3338/LX/5yFhYWptvcdtttfOhDH+LJJ5/kVa961Rn/ZpqmpOmpqlO/35/+POnq2NeE0nWKSncmT6QJZC7xAn9KpaN4KEklCwnMYnT+tGTLKSrtpydEk+/gF6ahp88lTVRyTFFJcISLLMRSxnFGb5TQHcZEnU3cIMIokMbn+HPrHD3WY/fCAq6zzJNP70d7DpVWhUqtztLiIoPRiN5gYLnxtSoXXLCEaxSh51CPgmkbeBinrKxt8uQzB+iPYjLtMByPrcACLmEQ0W60OPHcMQbDIePhkDRLydIYmYyJxyNknlspX8dHaYVjIFO2Ep+mKUJosmSE4wUEgUcWZ4V6k8FoaRMmY6bGsGiDFmY6TwS2cjrxUTHFzEFeGCimcYzSBi+sEPg+jh+gihuyEvqooqpTr9e46vJLMTrn2HNHWT52fEr9o1hwGalQSYofSITM0Upag0ZtMBSzB76t4DNx/RYuZClZmnJseUASD6hXmyzOtkizBMf1yIzGqfjsvugykiTjyLHnWe1YWef23ByDzCr+GKUIwggvDAhFytV72rz55rfw1KOPc/DQMvsPHMAd9BlmQ8TMLEmWcnh5lV3GkOPR2RzQ3+zhOQH97iF2Lc3z9BMPsmtuhpuv+3Fm6h6dzognn3iadLyBxwz/18+8hZlGDS0zUgFRFOC43nQWSZjCj8bYmTL7MDiVKNlAaAUiLDXhNE8m9cNVcw4fPszJkye3xIhWq8WNN97I/fffzzvf+U7uv/9+2u32dIEDcOutt+I4Dg888ABve9vbuP/++3n961+/pbhy22238W//7b9lc3OTmZmZM/79F4oj2iiq9SrDwgfHoMlkTj93eW4wRDgOoywnyXIUVmZdaZuAYwSB76EzmzgJe5OjhWAzTcilQgphpcWlRkltlc9qFXTPQWY5ShsC3yNHkyvbKUiVHZx3hEecS1Qxs6TSlNCzxqlxnhMGAY16jTTLcR1DKlVRlLFy5VbYxrH3ZGIH/r1CLVKryN4Pwir6iQSiSkhxYvFc2y23MzY+eapI48QmK1ISVapsdFfobWyidGZNpl0fpTKkllQ8H9exPiLd0ZgwrEAqGXV7GM9lo7uOyRJ0OkbK1Cr0ac2gt2GNl5kY0NoQMankOq6LEIbnjj5P4An+wU+9DhA8u/9ZJjORiMIUu5hF9V0Pmef0e33as7sYD/p4OETNiqUFY5BZwqCzShxE5GspCsiyjPkdC8g0IR6OcERhrlt0zMMowihFrzPG8wPyLEO4gma9zmgY4wWS0A+oFcfVPjPsXJEo/J/SNEVp25FEWwqPKPRpfN8WdBwHMNbItRL5uJ5DrVah67t4oWcFFoBqJWKUJgzzBKkVmbCLQid3iFUG0powCyGQynKrA6NY6/bpxSmu71sp/Twjy6SVODaAhmwUW9EYY8itpJr1ZXIEnrALp1TmqNzB15pMuTgY8igi6UtCL2GYJkglMdo+Y4PII4pcxj1ZeL6d23HkhWJIkiRsbnbJUsny8jKjUUq318VxBLuWdtNoNAgCjziOqVQrXHvdK9Bac2D/QY4/f5T9Tz+DQTMzO8f8rkU21zc4dOBZTq4cx/VD5ueXwHWp1uo0lnYzHsesr63QGwxoNJqsnjhOb3MDt1izKJXZBCCqIGUOovB6zC0tyqtYYRKZpSiVFovjjLCggOZphgCSNCbPU+utVJgpF8wyKtUKs7M78dyANJNsdtZBWcGj3RdcxNzcHI4Dx0+cQBsrbnD4wAEOHTxMb7PDqNuzqqy5VfPUgFEGqW0HVCmFo2yxWTgC4dskJs+thUAQ+Ah8rn/lK7jm6itxEURhSDoc0u90cYKA+twMlVqVeDS2ohT9Iel4zDiwoikTD7A4iUkTK27gOsIW0bWlqhmjqVQDWjMNvMjHOBNpcDsTZIoCjsAwIdnZFY2xBWNtzZd14btlCg84x7VbCqOL9aZLGPpM1T8dEI7BDz2cOC9Mq10qjoMXuNQqIZUwIIpCPKOpRz6eDjksNDIdk8UJwvOoVKxfltCaIHBB2oK2yrNiFqnodgnroZUnMSpP8YKA4bBPpVon8ARRJSRFY/IxXhAS+pE1165U8DyHnXNzGKPJ0tzufbG2E0YxkVOvVqrMtWaoBhGe7zEaDMnzjHScFv5YBh8rCf/E3qc4eOAIu+bnWdx9AXMzMwz7Q44ePYHcvYtub8D8jjatdoNqJSJJbfHopcKLSpZuvPFGvvSlL3HVVVexvLzMZz/7WW655Rb27t3LyZMnCYKAdru95f9ZWFjg5MmTAJw8eXJLojT5fPLZC+Fzn/scn/3sZ3/g/cmMkOd5RYJiphcxUGTxp6BNcQnrU8mP1Kf8kqyMuJjOJU0WidqcUrtz7JPVOqXnebHYtDLUk4HiSZfrlNz4ZHHpFJUIg9bQ2ezT7ccMxileZ4NxlnD5xZdx+OjzpMrl4NETLK+uECcx4HLTjTdz+eUX8s37/oq11RWyLKdRr9NqNPB9j2OHDluRh4UZhoM+Uhpc3yfNJc8vr7La2UQqQ5prKmFIqz3DMFO0Gk16G2sMNjfodDdJxuPCd0CRxkPQCscxOFriqsz6GSlr0qs1uEra9quyg72OkWglQWuMya2wgrE0oSiKyKRGOEXFyCmGJif8XoqhSWwrHVzbjZMSIxyEMSiV4/mRrcQmI2Q6xvN8+zd9w2y7yZ4LFkkGPU48d8RWK7TGCIUrHLtI0Q7j/ia6ag1etc4RRiOwia1KlZUddX1QimoYErmaLBngeD5KePTGCbkGB0WrVkVlI9pencHaMrgRYbuOSlJW1/oEUZMg75NjHcaFa8iyIZurCa+65u2oZEDoaq697krGSY+jhw+ic4cTBx+jTocLFxeRkaHWaOAYl4WddYSA1/7Ym/F9uOXVVxEIj3rkkiZD9j27nyf2Ps7sXJs3vuH1NJs10jSjVvULuVeNZ+xCyCZHDkJP5upOnyM7VQwQhilFrfigKAD8cAIPk3v8TDHg9BgxPz+/5XPP85idnd2yzSWXXPIDv2Py2QslSy8UR+I0odcfFrMxAnCshLPWmMyKZ2S5PWaqmIlzRSGI4AhGSWxVBZWd+0HbmmKc226UwnLulbFD054jkCNDkkmiwMVxfcZJQjJOcF2XTElLxXA0scmRSWzprcVD2ctSpJakUlpaRW+TKKxgsN1y1/eo1GuEtYqV4C0EEkCjMokJLG1FGUWuJFEYYqQmU4YgtIpzE/qx63kYkxKPEkbjEa7vksSS0TBGeC6OYwgjj/4gReUpq6tHGQ76+EEFLwxpNlvkMsOTHn6tQpbakef19VVwFH7gM5IKaRxWVtetSIzjMh6lhfz9hCtwytVeK4XjOvS6m6yvrPCmW9/AV776NYaDoY0pU06vAix9euK/4boCXEOepUSVCgDD3oB6s4ZRmlF/AE7MOInxwgqtRg0DhdKVng7jb66vE4f+1Hw1CCNaUWg7Msoa4AZ+gMkl/f6ARqOK6/s2ocT6wUzmIdI0s3YT2AUlxs5eTmKmiyBLrU+cTXIURmu7sMLGYCkVyhg2x6NiMS9QviYzBjJwPSuG43seqihSOUpjdIoMA4SnSZRCZynxOLaxValCLhkcYchyje8UpqPCmRrNWrqSS5zGgLBFMKMwuX1OamyMiEJFksbYsC7wfceKVOS5pQZtGYR/YZzNOPJCMeTEiZO2gKJdOp0N/CCiUqszNzfD3OwMykBvOCSKQmZaLdIs5+DBwzz77D6efPQxhv0+rhdQrTXorK9x5Mghet1NwiiiPTNHc6aNwRrFaqVY7hwlG4+ZnV8kHQ3pdzcxhZKdwRZ9w1oVcCG31hM4AherlAYC13PIZUaaJIRRZM2tpV1wKpMTxwlZnhOPYzv353vTOSflG5qtGYQQzMy00AiUmaXZbPKqV72CWr3Kd//qr9BSUU9TVKboDwYcfHYfeZJO5x4dpclVxngUE1QjcB3S2MrLW2P1IqnxvYKRYv0DjVG4roMDLF24m0uvvAqjcg4+s4/e6ipRtWLnumo1VG5N6z3PRfkOblShOdOgWo3wAw+/ElKt1uzsvKGgA1r1Wbs2Acd3cX1RsIiY+gpNqIGmKCxOrmFbsLefS6OssA6TZ8hEtVlMaX+V0GN+xqr+9gvanlSacZqRptKu2zIFOORZgh941KtWwW8wTql5gl7fFri7gz7xoI9Mc8JwhkajSRwPcY0k8ByGqaUMaqzXGWA7jXlhfm4gixOUtM2E2EiE69u5KiEQXojrBVYCHNu5b7WaXLB7iZMnlwuRDFHEMEvbC8IIRzgMhgOG/UFBQ/YIg5A0jRGioOUaazGT5zY5V0rz/PIymZRce921eGEFpRQnjq/gOpamXK+GNGs1S3su1DlfCryoZOn0tvj111/PjTfeyEUXXcQf/MEfUCkePC8FPvnJT/LLv/zL03/3+30uvPDCH+jiTGh4U0W70+hCetL2ZCt1L89yhD+h8RWqbYgtfHdhOGU6e9qM00Rxz5hTCiiT9ygoewhb6bReGnbWxnUFuYFxnNDtj1hZWWNxxxyt2QZBAEGlRo2I1998A51uh/XNIf1+ytLOGYxMqVQd6u0K66sjWvWKpcoFHjjWfHS1s4lXLDhc12UwGnJybZWV5eMgPGZnd5LEtvIgteTZp58gVYrxYFjIeRfyn1oWdBZrnpsmQ9JkYJMXY3D9AEcY8nSM0BKhcrRRaOz2ZkIRYaIQ4eC6Lp5jh+WFsCpWxijSsfW5mSSWrmMNbR3XKYYQi4q8kugkxvdDVDYmj0cYlRFVInJhSNOY1ZPL7Gw32HPBIk/vfZIoqtPrdyylTEg7F5Ap8A1GZqgiImqt8IQNdKekUCXCdTBGEvoQhoZGo0qnL+iPEuIkKWhPI1xy0nHMxupJ5haWCDQsNELyJOL48rqVCgWqUYRbqZAqGCVjfu//+RNeee1lPLp3H51RxmWXXMzC7BytVpPG7E6uuuJiknFGvVmj0ogIPB+VpeTSoJIc3wloBFbNJwwD+gNNrTlDdzTm5ddeTqPZ4Ov3fp25mTZvevMbCN1CzVFPukQg82x6jU/mEE9JihdzgZMcqfj/Jtt/vzjEuYoXiiN5LhmPxxhjDZC1NghfM1aKPAjsA8UI61GCnU0KJobUxcPFMfaOl1LihxHGWK8iablgeAgr760USgiE0lbuWQUIkU6yUHKliu+gSdKsSJIA4ZJkGUpajr59WAtrKKoUStiHuOc5pHmGKhYTvu+R53amLww9stQuhkHbKmKWEwa+TYq0vfeMZuo7p4vqoOu4YCyVeOJTP+z1ULlVuwqCiE53E4XtWJgss93WNKNeqxAnI6SM0K6guThPTyakwwGOFxCGAdWqz1yzzonnjjG/sMiGD/3eJq47MbgWxf1vO9UKjzhOufcb3+bgoWPc941vFvLZRWWxEIyZ0kULGrQq9kfmOdoPmJlp4BgrTtBu14nTlNGwQ9Ro0mo3uXBpgc7mJnE6xvWh1ohYO9kFBEmSsdHpUglDZny/WEw6hYhADZlLrAS8lXHWzQauY+c+HKPxXKsq5jpusTizSZCUloonc6tEZhXzcktdcxxqlQjfc5HSzoXqgrmQ5TlpllmlvCxnnBdzpa6LyHM818ODooDnFIu4gNwYhDKoLEbKnCyzcdxoXSTL2lK0lUFjh9EDz2OYjW2x0XFIMuuvpI1BaYN2XArLPBJlq+5xmuIYijkGRVxQLEyxsJws3M5lvFAMWT6xTpwm1CoV/CigNdOiPdemWqsz6PXY7PWo1+sEUZVuf8iBfft55KG/5um9j5FmGTsXL2Bp94WoPOHQgWfodzepVKrU27NWDQlY3LXA6voGhw/uZ9DtEoURw0EPMexbYQDjIGUhye75IDK0kQgtrAqsC9pxrAm8kIxH1gcqjWN0GDIYDCydGIfhaEyWWnWzOB5PKbBS2iS91WqyY37eWg3Ua0Shz6WXXcn6+jqNesRzR4+Sp5IsS9FK01nbYGOjw3hoF8paKYzShXG8IJYZWlqD+ByQxkpy5zq3ayfXrkektLFMKokXBORJyv3f/kuOHTqMqw0qGbOwc4Fao0G1VqG9Y4Y8Thj3B6TdIZEjaM3OMn/BLuqNCpb2L6zYjfFJk5TxYIzv+xiDlfvXGr+4tyko/aao4kzrhjAZNiwK9jaxsd3SYhDR2DlEIwymmM+2SnjQqPpI5ZLkyhagBShpGMeSNJHIHKQSOI6H54WWzaC19c3ThmGcsL66Sn+zw/pqF8cLcYWLzFK6mx0QBldo8lQV9EJbdNJKTWfY9CQBFIUyulJoJUAYVJrZEc1KiCcCvKIzpGRGFAYgXI4+f5x4PCqk0W0H3XE9jMjBsTT+0Whs4xqwa2k3cwuLDPpdepvrdiQDW3hJsxw/HrMwv4AfRhw/cQKjDNdedy3aFzx35DiOgdFgxM7ZFhddtJu5uRlq9XPUZ6ndbnPllVdy4MABfvqnf5osy+h2u1u6SysrK9MZp127dvG9731vy++YqOWdaQ5qgjAMCcPwB96fdG9OwRQL/dNnkOyDfTqcPlUxKWhyWiOltBWDYnFgTht6n6yZzaQaUMwfOY5d+CtVDFoX803ORA2keCgYY8iy1N7wRTKGsN2R9Y0Nlk+sM9OaYabZpFIPqNZ8hnFCr7fOjlaD4ydHuK7DG265kWYj5NjyCW758Vcz257hwIHDHDpynEOHnuPiiy9mptUkH8f00gzX9Wg1WmR5ymjQ47kD+xh2Ngn8Kn2tSeMxw0EfoxXHjx1GYznkdl7BtYvhwmATz3bTTJ6hc0tBEF6I0S7CNRiV4Rorea5yiTHSPmgdOycxPWiAcD18x0UrG/Bs2zZl0pGbHEOlDMKzQ+fGFLNjQiAcO6Q+jsek4wG4Hq7nkWoH4wZ4nkut3mQ4GDAz0yYoHLht8mOYnn4BwijbIStMhJ0gtEmBaxXBEI5tuQOp1PT6A65/2RX0NnvEvQFppjDCQxsHzxU4rubpQ4fZ1W5TiVpUmjOMBj0C11APDIP1dXCsWe3OuVlqtSZHDx2hl/l8++FniWWV1s4dEAS02nWMVBw9foRqw2ezM6RRC9m9a5YL5hephQ5PHzlElgsuumiRHXMNKlEFpRVhuESawZVXXM6hA89y002v5af/wU9Sr9dxsEOZWsnp9TtVIMQmSGma4jruaYk/06rPNJEugut0ru+HwOQeX1lZYXFxcfr+ysoKr3zlK6fbrK5uVbSRUtLpdLbEke9X2fy7xBFHWPl4g12w2cKKxHUDhMjIle1MeK6H1hItFZm2dBZnUjApDGiFsUP+UoAW1rRTKY2npOWJS4kSDi6WyqW1NSx1XQ+jJFkuLZ/et4mB5/vkWYZUObm2Aimh75ClkjAI7GydtmaFRmvCaoV6I6JSqxTnVjEaxbRnW3YmRdp5kizPyXwrqZsnGW7VesJMaMfCFZauqiSOK3ACh7ASkStLG/QDj7wvSXNJt9snzSVGSQLfp1KrkmaK9fV1ZmZnCrVPgREOgedTqQbM7pzjeJKRa8MoTlhfXscThlqjynA8ptFoW1U4Y7sbeTFn4boOwrGFIWM0+589xKGDz7GytoLWVqnL6EmBxmU6aT3xfMsURtnu0q5ds4S+pU93VtdZX10nTlPCap25mRmiwGM0HhOnOZvrGziOz4bqFR0ae66DgtWQZRlrqxtElQpRFNFsNIqKuE+zWbXPFmPNoV3HMvy1MeBq/NAvvGysCbrKpRWWYTIzZilxNkGS9v7F7lalFtCSFYZDgdQ5+URAyMmtH0sa4woPX7hIBDqzilZhUNDNlYuWknFm5TikknYh6zCd601TmyA72NkltMDz7fyDMpaapXQxa2fsiG+R51nBFGVnppRSeI41H5eZlYoXjibw7f5nP2RV+GzGkReKIc+fOM7c7A4q9Rq7Fhdo1OsI16PX75HEYxqtJvV6neUTJ9j35FM8+fjjrK6uEtZaXHn95eyY3QnGcOz5g/hhSFSp4Qc+UkpqURVhDEeOPMfq6knG/b5VPKxWiKIKYSUiHo7IU7vOkIUamyM0tVqtuLZsgStNErI8w/M920lUNhFOkpSN9Q0C3ydXkjhO7O8xlm3gOlZ9ThfxH9eOPdQqEUqmjPOUlZVl4vGYE8eO0Ot1bRLsAK6gs9qh39u0bBOt8QBXCLQj0Ni5zn7PdvGV0CgkjrHiE5YqTCGYMpkcty+NIoljjh99HvKcxfkdBGFIvVGn1moRVioIbRgl65hxjAZiOiTVCN2ooyJFrMYEYVDM6lrFX+FaWw6tNVmaWCsGbSllwljjYZswneY9WHSF7ew1aGms2qDrYLWkrJy3g0Br+92tQ7wg8ARKgzaWGuhghXjyRJKmklw75NoWIgz2WESejyzmubr9MUeOr7CxukKe5FNbgjQeI/MMLwzR2pDnEpVmYKywDkVnzPFcMMo+M4rnhnAsC0VnVjFRG4UX2WvOKyidnuvQaDXxg5D19bVC7MuuKaydjwClyRNL0+4P+ujcdimF5zM7v4uoXmM0GpKnA4RjijlyQ7/XZ21jjSsuv4pWo83JE8u0mjUuvuwKWvUGhw7sZ31ljY1WA5klhME1BMFLV7j9OyVLw+GQgwcP8u53v5sbbrgB3/e59957efvb3w7Avn37OHr0KDfffDMAN998M//6X/9rVldXpy3ye+65h2azycte9rIX/fe/30tpspgDuwCaCjxgOa9O0Zkw37e4myh9OViX6cni75RgA1N1FlMs5k//DpOLwlY9UkupEFbSN81S0jjHkOO7HpXIK76Px86dC4xyl8cef5qndM5V11xBGDTY3OixstGnFkb0BwP2XHQBO1oRKMWepR3guNQjlywdMRgNmFtc5Kn9B2nXq0S+S5xm+EHAZrRG6AscFEvzM3ROHkdJxUilZGmCQeEGIcLx8B1RDLd7+GGATHM84eFGLhJDlifoPMYX2prV4VqKh1KYwm/GYNuukwqBMacSJau+Zr1AsnyixoJ9aCpLTUKLwljWejnYhY9ByxylNDLLqDYDS1PJx6TJEJWlVGpNtBNY93GdsffJfdzwymsQzsRTy0dgky6ruGdwHdu1yrMUXFtZd8MQYQyu49nqfeGwrQu3bYXHsedPTE3ysmyMwcF1fHLjUA1r6DRHGMXzR/Zx0VVXszBfp9sZIFpVemuCJBsTmoAdFYVjBrzp9a9gbfkwKydP8JpXvoJXv/pV7GzVCB0XqQw7F2ZxhSLNFUbnVCIfo+zg+WtefQMr65s0myFZOiRPR8zt2EkUeMTjAXOzbV758rcQBS71akAlcjE6w+hwmpiePndnaaguSlvPELB+Lp7nW874pMMkTrmXn1Fa/AVwySWXsGvXLu69997poqbf7/PAAw/woQ99CLAxotvt8vDDD3PDDTcAcN9996G15sYbb5xu8yu/8ivkeV5QSmwcueqqq16Qgvc3QUmJ6wmkLuhPAhzsgwLHt1VbYYfTpbSL9yyzi1FXSLS0AT7wPDzHIclS4syavoqCZmq0QLgU1DXXeusIBz9wMA4kWWKLO9jOwoROnMsMjX3wSG1dibXS+MKhUalY0QlpBRqscpqVvA08qy5UiULrl5amU/lgYTS68LVRTUnmGgJjufNG2wKSKmanZK5Ik7x433odea5HZ9hlsztinKRkEjt0HUZkShOEEbiaOBmTrSmyOKZSqWGkpNlq0d3YoN5ssbhnN+Nhn+VjR2lGITMzDSr1Jitrmww3N0niBCH0qfmAaazXoECSEydJcT06U9ENcGzBxyrW4OARhhGuZ4Vw/DDEdw1awMm1LusbPVZPrqEch9kdO5jZMc/G2homduj1B/R7AzobHSsOoxQ7d8yQaUOlUrHD7449p5VqhX5viMolcaNCq93CYDs+Ks8Y9rsImkR+WFSpHdAUzyVd0E+s/LfWVhnLAau8h/XYkrlESY1Kc6JKSBj5pEmIGCV4roPvWcW5JM+tSbDj4rk+QeBPO/tpoaYlHFDazh8JrLmokrmNk1pYL7BCjllpXVg05GjPI8tya4xZPFMnNElw0MU5yrNTgjCZNHiuT5pn5FIXMywCqRWeF5FKSZ5l2zaOzM3t5LLL9lCrN6k2qsRpghzH+EFAY2EX/cGQfU8/y94nnuDI/v30Bn12LV3M1dffQFSpsHzsOVZPPE+1UaE1s8POu/kBzVYL3/dZWVmms7E+NZB1cYqfNaPRwDIDXMd2HxH4fkCj0aRSqzIcDNDFM1dKayOSq3yqiGkc1xaNlZ131IVnEIAw2L9DIXhlJFpreps9NiodgsXQJsjAoYMHEECeKZJEkuQ51UqF8XDAcDhkauBKMfdmJqmPQecZUmkcz7Uy1I5fsH2Kro1wrFCTcECoIiFMrLiIUqgsxXccMqkIogr1RgOhFSaTyGFM1h3gGhs7s/6I7vEVwnqNVuCjKMQuogDH9yy9zLcS/47j4PmulRF3HIwpRBu0Xddoo6YFejs9IHBdD40o/IcUHgICK4YysTOwlQRL5TbGJkpJJklzW2CgYDBVqxFVaUhG0gou5RLHGHzXGtXmaWYpi2DjnhvhhS5BFNnEyISWbmssC8IoRZ6llvlTeKX5nkOz0SLLM4ajEWRjhJEIJ0Q4DjJLbZJa+EgJpfCjEFc40+tQxVZ4hEIvQBtFlqZ2NAJbs7JiNQ4GS9MbDQcsnzhedJY93GIWV+e2sOj4LoPNPseOHqXdnsGf38mRY8fxKzUu3HMBcZZw+JlnGGyuIVRGFIbM79rxou7bF4MXlSz983/+z3nrW9/KRRddxIkTJ/j0pz+N67q8613votVq8b73vY9f/uVfZnbWclf/6T/9p9x8883cdNNNALzpTW/iZS97Ge9+97v5whe+wMmTJ/nVX/1V7rrrrjNWa14IkwXeaGR9BZzCGFYr26YV5lQCpcEuWAoFuyyxreUJ5W5CoXNdd9p6nc4+Tf+eXVhP5o0Ep+TJbRfE/o6sUAmyv8cucEZxQhbndDd7LJ84wfXXX0OtUWOcS5544glWNweMhkO+9fST9Ad9fvx1r+bE8hq5dOmsDah4LjvaNdK0z3A4YvcFexgPxug8od2o06rWWesMaVZqpElMOs65/PJL0UrRbtVp1iNmWjWOHDzM048+glKKNB+ipCxkhAUuLr4fEASQZQlJnOAIB9cvzCkFONpFI6iEIWEQoDO7YJ7MGxljK5NCFF5SFEVdxwFt5X4nwVo41vhS5XkxU1FUN4qOndY2QbUaxzYY+a5HriQqi+25TkeQDgg8nzwdo4zlGXsujIzh8cf3Uqt4JGmK0cU3FZPzZgfqZ3bMsbLetYaXuHZmyWiENlPlQmPskLvGJXAadHsjtFYkmUHqHEcYXMfgexXkKEZoieMI5uYaJP0Nev2Yhd27caVD/dpLSbKUKAx5/sBTyHHCtYsVXvPjr+K7DwmeP7CPqit57Wtfgd9oM4oHtDKfPE6I44xqFDLqdZAakjhBWkkr4vWck8eOM+6nzMzMMTvX4oGHHqRSr3H7W+4gDH2SNCPXijAMkEm2ZTrASkbbxDbwfLtgO73KW4ia+BODPk6ZNqM1/f5gel8Oh0MOHDgw3e7w4cM8+uijzM7OsmfPHj760Y/yr/7Vv+KKK66YSv4uLS3xcz/3cwBcc801vPnNb+b9738/v/Vbv0We53z4wx/mne98J0tLSwD8wi/8Ap/97Gd53/vexyc+8Qn27t3Lf/pP/4n/8B/+ww8dQ06PI3ESg0jsNWJsgmN8XXiDWQ61UlbhKM9TSwvVBiM1OacKJloJGo0m49GYTOY24Ltu4aHh2yKblLgFDSWXEikzXN9DpamdjckzlLaLfM/3yJVB5rIwjZXIPGNorFoRsRVBGQ3HxLE9P1meEdUiq1A3ikFpFubbJKlHt9PDCEOr1WQ0HhEGAd1u1zrDS43rOoRRYDtnWW7FWDCMR7GldY1GbHb7pEnOxtqarR4L0CqlPxxafr6GpPBC0wZcL8dgGA66aFXHAK4jyHPF7Fyb6o5ZjvX7HD/xPMLdTWd1GVRmK4zaikvYBYUCYbsg0lhqDkIwGFolK1GYI1LQx4wQln5kjO2oFbM1fhDQbjforZ2ks9kjHgzZ7A4Yj0dU222WFncyTjLyOAGt6W1uMByMiwrzEJUmaJUT+h5xkrBz5zzxOCGNY5IkIfA80iRmfW0dmUtazRpJ7JJ61usMA2Mh8HyfMLSLB4QgSdJikN6qmOVZbk1GC+EgrTWbnR6ugCRN0VrS2dggiRM6nU16vYFVcnUc0twlTawpqeO6pCpBFTNQnhcgpSSORwhhCLyIOB7ZoogfItMUjLaxX006dYXwSNFNzbIY17EFm0myBPY5rLWeVr6lVKihpekFYYBxrKBJnqdWWa0oqnW7WUE9VNsujkxiyNLuBWbmZlDSsL62QS5z2rOzYGB1ZY0nn3icpx57jF6vi1SGxswCO5cuQuYp+w48zebGCnNz8yzML7C2uoxWGY5XxWDobm7Q2VgjHsd4hZmsEIIsiYlHg4Lm7+J74TQhSeIRHSPxBj55av1udLFYnsA+24vOSNFdV0pOi79BEJDnivF4RJ5nUyGfNEtxPJe19RWkVuSpnZUJwohmq81oMCBLElzPYzTqMex2kVmKEDbxEsYyfnIlC/W0UzR9Y7Tt5CtbtEL4OJ7Ad63Hk8qtQa2ZdFC1Ic0TtOMiwtAyWnwXN/JRWUY8HpKOBmRxbDsmFHO2WYVcKdI8J6zXMI7t3AipUVKR5cV6pjhOyhSmvGLrsdPFDFKaZIwLs3LP88iytJiZd3DzHJkn0/WHVpYlYxwHpSEzAmkEcWYYJ5o4lXgCwsAhzWw8iMcZOrdiVMZoxuMRDrll6EiJUhlB4OH5bkGvzohHA6Q2VnhGKmScIPMElVsmj1EZMo0xuUMSBGit0DKznUiZY5IhwnUxStoZS2MTRKMleR7j4OAJtyiWWHsJ4Qhr8u4UJr1SWuVj4xbNBvs3crRlNhVmzkpJjGuLRzjaPoOMNTxfW1lhMBxQrVSQWc6Tjz+O0jlzO+fYWJ3jxOFDPH/sKEolXLjnwi335f9RmBeBd7zjHWZxcdEEQWB2795t3vGOd5gDBw5MP4/j2PzSL/2SmZmZMdVq1bztbW8zy8vLW37HkSNHzO23324qlYrZsWOH+djHPmbyPH8xX8McPHjwVB+2fJWv8nVOvI4dO2a+8Y1vnPGzX/zFXzTGGKO1Np/61KfMwsKCCcPQvPGNbzT79u3bcn9vbGyYd73rXaZer5tms2ne8573mMFgsGWbxx57zLzuda8zYRia3bt3m89//vMvKoaUcaR8la9z87Wd4kgZQ8pX+Tr3XseOHXvR64G/DcKYlyIFe2nR7XaZmZnh6NGjtFqts/11zktMBlePHTtGs9k821/nvMT5coyNMQwGA5aWlraN2AOc33HkfLm2Xgjl/m1fvNC+bcc4cj7HEDi/r0M4v/fvfN43OPP+vZQx5O80s3S2MDkIrVbrvLwIziU0m83yGL/EOB+O8XZcKPx9iCPnw7X1N6Hcv+2LM+3bdosjfx9iCJzf1yGc3/t3Pu8b/OD+vVQxZHuUb0qUKFGiRIkSJUqUKFHiR4wyWSpRokSJEiVKlChRokSJM2BbJkthGPLpT3/6RSnolXhxKI/xS4/yGJ9dnM/H/3zeNyj3bzvjfNq382lfzoRy/7Yvzud9gx/9/m1LgYcSJUqUKFGiRIkSJUqUeKmxLTtLJUqUKFGiRIkSJUqUKPFSo0yWSpQoUaJEiRIlSpQoUeIMKJOlEiVKlChRokSJEiVKlDgDymSpRIkSJUqUKFGiRIkSJc6AbZks/ef//J+5+OKLiaKIG2+8ke9973tn+yttC3zuc5/jNa95DY1Gg/n5eX7u536Offv2bdkmSRLuuusu5ubmqNfrvP3tb2dlZWXLNkePHuWOO+6gWq0yPz/Pxz/+caSUP8pd2Tb4/Oc/jxCCj370o9P3ymN89rEdY8gPc//+1E/9FEKILa8PfvCDW7Y5V6+tz3zmMz/w3a+++urp59v9vrn44ot/YP+EENx1113A9jp33/72t3nrW9/K0tISQgjuvvvuLZ8bY/i1X/s1FhcXqVQq3Hrrrezfv3/LNp1OhzvvvJNms0m73eZ973sfw+FwyzaPP/44t9xyC1EUceGFF/KFL3zhpd61F4Uyjpz9a/H7cT7HkfMphsA2iyNmm+HLX/6yCYLA/M7v/I558sknzfvf/37TbrfNysrK2f5q5zxuu+0288UvftHs3bvXPProo+Ytb3mL2bNnjxkOh9NtPvjBD5oLL7zQ3Hvvveahhx4yN910k/nxH//x6edSSnPdddeZW2+91TzyyCPma1/7mtmxY4f55Cc/eTZ26ZzG9773PXPxxReb66+/3nzkIx+Zvl8e47OL7RpDfpj79yd/8ifN+9//frO8vDx99Xq96efn8rX16U9/2lx77bVbvvva2tr08+1+36yurm7Zt3vuuccA5hvf+IYxZnudu6997WvmV37lV8xXvvIVA5g/+qM/2vL55z//edNqtczdd99tHnvsMfMzP/Mz5pJLLjFxHE+3efOb32xe8YpXmO9+97vmL/7iL8zll19u3vWud00/7/V6ZmFhwdx5551m79695vd///dNpVIx/+2//bcf1W7+jSjjyLlxLX4/zuc4cj7FEGO2VxzZdsnSa1/7WnPXXXdN/62UMktLS+Zzn/vcWfxW2xOrq6sGMN/61reMMcZ0u13j+775wz/8w+k2Tz/9tAHM/fffb4yxF7fjOObkyZPTbf7rf/2vptlsmjRNf7Q7cA5jMBiYK664wtxzzz3mJ3/yJ6fJUnmMzz7Olxjy/fevMWbLtXYmnMvX1qc//Wnzile84oyfnY/3zUc+8hFz2WWXGa21MWb7nrvvX+Rorc2uXbvMv/t3/276XrfbNWEYmt///d83xhjz1FNPGcA8+OCD023+1//6X0YIYY4fP26MMea//Jf/YmZmZrbs2yc+8Qlz1VVXvcR79MOhjCPn3rVozN+vOHK+xBBjzv04sq1oeFmW8fDDD3PrrbdO33Mch1tvvZX777//LH6z7YlerwfA7OwsAA8//DB5nm85vldffTV79uyZHt/777+fl7/85SwsLEy3ue222+j3+zz55JM/wm9/buOuu+7ijjvu2HIsoTzGZxvnUwz5/vt3gt/93d9lx44dXHfddXzyk59kPB5PPzvXr639+/eztLTEpZdeyp133snRo0eB8+++ybKM//k//yfvfe97EUJM39/O526Cw4cPc/LkyS3nqtVqceONN245V+12m1e/+tXTbW699VYcx+GBBx6YbvP617+eIAim29x2223s27ePzc3NH9HenBllHDm3r8W/D3HkfI4hcO7FEe/vukM/Sqyvr6OU2nKiARYWFnjmmWfO0rfantBa89GPfpSf+Imf4LrrrgPg5MmTBEFAu93esu3CwgInT56cbnOm4z/5rAR8+ctf5q//+q958MEHf+Cz8hifXZwvMeRM9y/AL/zCL3DRRRextLTE448/zic+8Qn27dvHV77yFeDcvrZuvPFGvvSlL3HVVVexvLzMZz/7WW655Rb27t173t03d999N91ul3/8j//x9L3tfO5Ox+S7nOm7nn6u5ufnt3zueR6zs7Nbtrnkkkt+4HdMPpuZmXlJvv8PgzKOnLvX4t+XOHI+xxA49+LItkqWSvyfw1133cXevXv5y7/8y7P9Vc4rHDt2jI985CPcc889RFF0tr9OifMUL3T/fuADH5j+/PKXv5zFxUXe+MY3cvDgQS677LIf9dd8Ubj99tunP19//fXceOONXHTRRfzBH/wBlUrlLH6z//P47d/+bW6//XaWlpam723nc1die6KMI9sXZQz50WJb0fB27NiB67o/oFyysrLCrl27ztK32n748Ic/zB//8R/zjW98gwsuuGD6/q5du8iyjG63u2X704/vrl27znj8J5/9fcfDDz/M6uoqP/ZjP4bneXiex7e+9S1+4zd+A8/zWFhYKI/xWcT5EENe6P49E2688UYADhw4AGyva6vdbnPllVdy4MCB8yo2Pffcc3z961/nn/yTf/I3brddz93ku/xN99iuXbtYXV3d8rmUkk6nsy3OZxlHzt1z8/04H+PI+R5D4NyLI9sqWQqCgBtuuIF77713+p7WmnvvvZebb775LH6z7QFjDB/+8If5oz/6I+67774faE3ecMMN+L6/5fju27ePo0ePTo/vzTffzBNPPLHlAr3nnntoNpu87GUv+9HsyDmMN77xjTzxxBM8+uij09erX/1q7rzzzunP5TE+e9jOMeRvu3/PhEcffRSAxcVFYHtdW8PhkIMHD7K4uHhexaYvfvGLzM/Pc8cdd/yN223Xc3fJJZewa9euLeeq3+/zwAMPbDlX3W6Xhx9+eLrNfffdh9Z6usC7+eab+fa3v02e59Nt7rnnHq666qqzSsGDMo5sl2sRzs84cr7HEDgH48iLlqw4y/jyl79swjA0X/rSl8xTTz1lPvCBD5h2u71F3aPEmfGhD33ItFot881vfnOLtOR4PJ5u88EPftDs2bPH3Hfffeahhx4yN998s7n55punn0+kJ9/0pjeZRx991Pzpn/6p2blz5zkhq3mu4vsVaspjfHaxXWPI33b/HjhwwPyLf/EvzEMPPWQOHz5svvrVr5pLL73UvP71r5/+jnP52vrYxz5mvvnNb5rDhw+b73znO+bWW281O3bsMKurq8aY8+O+UUqZPXv2mE984hNb3t9u524wGJhHHnnEPPLIIwYwv/7rv24eeeQR89xzzxljrORvu902X/3qV83jjz9ufvZnf/aMkr+vetWrzAMPPGD+8i//0lxxxRVbJH+73a5ZWFgw7373u83evXvNl7/8ZVOtVs8p6fAyjpz9a/H7cb7HkfMlhhizveLItkuWjDHmN3/zN82ePXtMEATmta99rfnud797tr/StgBwxtcXv/jF6TZxHJtf+qVfMjMzM6ZarZq3ve1tZnl5ecvvOXLkiLn99ttNpVIxO3bsMB/72MdMnuc/4r3ZPvj+ZKk8xmcf2zGG/G3379GjR83rX/96Mzs7a8IwNJdffrn5+Mc/vsVnw5hz99p6xzveYRYXF00QBGb37t3mHe94hzlw4MD08/PhvvmzP/szA5h9+/ZteX+7nbtvfOMbZ7wWf/EXf9EYY2V/P/WpT5mFhQUThqF54xvf+AP7vLGxYd71rneZer1ums2mec973mMGg8GWbR577DHzute9zoRhaHbv3m0+//nP/6h28YdCGUfO/rX4/Tjf48j5EkOM2V5xRBhjzA/fhypRokSJEiVKlChRokSJvx/YVjNLJUqUKFGiRIkSJUqUKPGjQpkslShRokSJEiVKlChRosQZUCZLJUqUKFGiRIkSJUqUKHEGlMlSiRIlSpQoUaJEiRIlSpwBZbJUokSJEiVKlChRokSJEmdAmSyVKFGiRIkSJUqUKFGixBlQJkslSpQoUaJEiRIlSpQocQaUyVKJEiVKlChRokSJEiVKnAFlslSiRIkSJUqUKFGiRIkSZ0CZLJUoUaJEiRIlSpQoUaLEGVAmSyVKlChRokSJEiVKlChxBpTJUokSJUqUKFGiRIkSJUqcAf8/DrW9XiIk0ToAAAAASUVORK5CYII=",
"text/plain": [
"<Figure size 1000x500 with 3 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"num_images_per_prompt = 1 # adjust according to VRAM size\n",
"generator = torch.manual_seed(29) # seed\n",
"\n",
"prompts = [\"a dog in the style of [v]\", \"a street in the style of [v]\"]\n",
"style_lora_scaling = 1.2 # you can adjust to control style strength\n",
"\n",
"images = [ \n",
" pipeline(\n",
" prompt=prompt, \n",
" lora_scaling = [0., style_lora_scaling],\n",
" guidance_scale=7.5,\n",
" num_inference_steps=30, \n",
" num_images_per_prompt=num_images_per_prompt, \n",
" generator=generator\n",
" ).images[0] for prompt in prompts\n",
"]\n",
"\n",
"style_img_path = f\"data_demo/style/{style_img_name}.jpg\"\n",
"style_img = load_pil_image(style_img_path)\n",
"\n",
"_, ax = plt.subplots(1, 3, figsize=(10, 5))\n",
"ax[0].imshow(style_img)\n",
"ax[1].imshow(images[0])\n",
"ax[2].imshow(images[1])\n",
"plt.show()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "blora",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.10"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
| 1,607,768 | inference_demo | ipynb | en | jupyter notebook | excluded | {} | 0 | {} |
000haoji/deep-student | src/chat-core/utils/tauriApiClient.ts | /**
* Tauri API Client
*
* Simple client for direct Tauri API calls without streaming.
* Single responsibility: Non-streaming API communication.
*/
import { invoke } from '@tauri-apps/api/core';
export interface ChatMessage {
id: string;
role: 'user' | 'assistant' | 'system';
content: string;
thinking_content?: string;
timestamp?: string;
}
export interface AnalysisRequest {
subject?: string;
question_image_files: string[];
analysis_image_files?: string[];
user_question: string;
enable_chain_of_thought?: boolean;
}
/**
* Tauri API Client - provides direct access to backend commands
*/
export class TauriApiClient {
/**
* Perform step-by-step analysis
*/
async analyzeStepByStep(request: AnalysisRequest): Promise<any> {
return invoke('analyze_step_by_step', { request });
}
/**
* Start streaming answer for existing analysis
*/
async startStreamingAnswer(tempId: string, enableChainOfThought: boolean = true): Promise<any> {
return invoke('start_streaming_answer', {
request: {
temp_id: tempId,
enable_chain_of_thought: enableChainOfThought
}
});
}
/**
* Continue chat stream
*/
async continueChatStream(tempId: string, chatHistory: any[], enableChainOfThought: boolean = true): Promise<any> {
return invoke('continue_chat_stream', {
request: {
temp_id: tempId,
chat_history: chatHistory,
enable_chain_of_thought: enableChainOfThought
}
});
}
/**
* Get chat history for a mistake
*/
async getMistakeChatHistory(mistakeId: number): Promise<any> {
return invoke('get_mistake_chat_history', { mistakeId });
}
/**
* Get all mistakes
*/
async getAllMistakes(): Promise<any> {
return invoke('get_all_mistakes');
}
/**
* Get mistake by ID
*/
async getMistakeById(id: number): Promise<any> {
return invoke('get_mistake_by_id', { id });
}
/**
* Save mistake
*/
async saveMistake(mistake: any): Promise<any> {
return invoke('save_mistake', { mistake });
}
/**
* Delete mistake
*/
async deleteMistake(id: number): Promise<any> {
return invoke('delete_mistake', { id });
}
/**
* Batch save mistakes
*/
async batchSaveMistakes(mistakes: any[]): Promise<any> {
return invoke('batch_save_mistakes', { mistakes });
}
/**
* Batch delete mistakes
*/
async batchDeleteMistakes(ids: number[]): Promise<any> {
return invoke('batch_delete_mistakes', { ids });
}
/**
* Get supported subjects
*/
async getSupportedSubjects(): Promise<string[]> {
return invoke('get_supported_subjects');
}
/**
* Get subject configs
*/
async getSubjectConfigs(): Promise<any[]> {
return invoke('get_all_subject_configs', { active_only: true });
}
}
/**
* Default client instance
*/
export const tauriApiClient = new TauriApiClient(); | 2,908 | tauriApiClient | ts | en | typescript | code | {"qsc_code_num_words": 292, "qsc_code_num_chars": 2908.0, "qsc_code_mean_word_length": 6.38356164, "qsc_code_frac_words_unique": 0.34589041, "qsc_code_frac_chars_top_2grams": 0.07725322, "qsc_code_frac_chars_top_3grams": 0.0944206, "qsc_code_frac_chars_top_4grams": 0.12982833, "qsc_code_frac_chars_dupe_5grams": 0.23497854, "qsc_code_frac_chars_dupe_6grams": 0.14484979, "qsc_code_frac_chars_dupe_7grams": 0.09763948, "qsc_code_frac_chars_dupe_8grams": 0.0, "qsc_code_frac_chars_dupe_9grams": 0.0, "qsc_code_frac_chars_dupe_10grams": 0.0, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.0, "qsc_code_frac_chars_whitespace": 0.2156121, "qsc_code_size_file_byte": 2908.0, "qsc_code_num_lines": 129.0, "qsc_code_num_chars_line_max": 117.0, "qsc_code_num_chars_line_mean": 22.54263566, "qsc_code_frac_chars_alphabet": 0.81718544, "qsc_code_frac_chars_comments": 0.24140303, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.12307692, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.12188491, "qsc_code_frac_chars_long_word_length": 0.05074762, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0} |
000haoji/deep-student | src/chat-core/styles/markdown.css | /**
* Markdown & RAG Styles - Markdown渲染和RAG相关样式
* 提取自原项目中所有Markdown和知识库相关的样式
*/
/* ============================================================================
Markdown基础样式 - Markdown Base Styles
============================================================================ */
.markdown-content {
line-height: 1.6;
color: #333;
font-size: 0.95rem;
}
.markdown-content > *:first-child {
margin-top: 0;
}
.markdown-content > *:last-child {
margin-bottom: 0;
}
/* 标题样式 */
.markdown-content h1,
.markdown-content h2,
.markdown-content h3,
.markdown-content h4,
.markdown-content h5,
.markdown-content h6 {
margin: 1.2em 0 0.6em 0;
font-weight: 600;
line-height: 1.3;
color: #2c3e50;
}
.markdown-content h1 { font-size: 1.5em; border-bottom: 2px solid #3498db; padding-bottom: 0.3em; }
.markdown-content h2 { font-size: 1.3em; border-bottom: 1px solid #bdc3c7; padding-bottom: 0.2em; }
.markdown-content h3 { font-size: 1.15em; }
.markdown-content h4 { font-size: 1.05em; }
.markdown-content h5 { font-size: 1em; }
.markdown-content h6 { font-size: 0.95em; color: #666; }
/* 段落和文本 */
.markdown-content p {
margin: 0.8em 0;
text-align: justify;
}
/* 空行优化 - 使空行变得非常窄 */
.markdown-content p:empty,
.markdown-content p:blank {
margin: 0.1em 0;
height: 0.1em;
line-height: 0.1;
}
/* 处理只包含空白字符的段落 */
.markdown-content p:has(br:only-child),
.markdown-content p:not(:has(*)):not(:has(text)):empty {
margin: 0.1em 0;
height: 0.1em;
line-height: 0.1;
}
/* 使用CSS选择器匹配只包含空白字符的段落 */
.markdown-content p:is(:empty, :not(:has(*)):has(br:only-child)) {
margin: 0.1em 0;
height: 0.1em;
line-height: 0.1;
}
/* 全局的空行处理 - 适用于所有可能的空行情况 */
.markdown-content br + br,
.markdown-content br:only-child {
line-height: 0.2;
}
/* 连续的空行处理 */
.markdown-content p:empty + p:empty {
display: none;
}
/* 更强的空行控制 */
.markdown-content p:empty,
.markdown-content p:has(br:only-child) {
margin: 0.2em 0 !important;
height: 0.2em !important;
line-height: 0.2 !important;
padding: 0 !important;
}
/* 对于包含只有空白字符的段落 */
.markdown-content p:not(:has(*)):is([children=" "], [children="\n"], [children="\t"]) {
margin: 0.1em 0 !important;
height: 0.1em !important;
line-height: 0.1 !important;
display: block !important;
}
/* ReactMarkdown生成的空段落 */
.markdown-content > p:empty {
margin: 0.15em 0 !important;
height: 0.15em !important;
font-size: 0.5em !important;
}
/* 全局减少段落间距 */
.markdown-content p + p {
margin-top: 0.6em !important;
}
.markdown-content strong {
font-weight: 600;
color: #2c3e50;
}
.markdown-content em {
font-style: italic;
color: #7f8c8d;
}
.markdown-content del {
text-decoration: line-through;
color: #95a5a6;
}
/* 链接样式 */
.markdown-content a {
color: #3498db;
text-decoration: none;
border-bottom: 1px solid transparent;
transition: all 0.2s ease;
}
.markdown-content a:hover {
color: #2980b9;
border-bottom-color: #2980b9;
}
/* 列表样式 */
.markdown-content ul,
.markdown-content ol {
margin: 0.8em 0;
padding-left: 2em;
}
.markdown-content li {
margin: 0.3em 0;
line-height: 1.5;
}
/* 空列表项优化 */
.markdown-content li:empty {
margin: 0.1em 0 !important;
height: 0.1em !important;
line-height: 0.1 !important;
display: list-item !important;
}
/* 只包含少量内容的列表项 */
.markdown-content li:has(p:empty),
.markdown-content li:has(br:only-child) {
margin: 0.15em 0 !important;
line-height: 1.2 !important;
}
/* 连续的空列表项 */
.markdown-content li:empty + li:empty {
display: none !important;
}
/* 减少列表项中段落的间距 */
.markdown-content li p {
margin: 0.2em 0 !important;
}
.markdown-content li p:only-child {
margin: 0 !important;
}
.markdown-content ul li {
list-style-type: disc;
}
.markdown-content ol li {
list-style-type: decimal;
}
.markdown-content ul ul li {
list-style-type: circle;
}
.markdown-content ul ul ul li {
list-style-type: square;
}
/* 引用块样式 */
.markdown-content blockquote {
margin: 1em 0;
padding: 0.8em 1.2em;
border-left: 4px solid #3498db;
background: #f8f9fa;
border-radius: 0 6px 6px 0;
color: #5a6c7d;
font-style: italic;
}
.markdown-content blockquote p {
margin: 0.4em 0;
}
.markdown-content blockquote p:first-child {
margin-top: 0;
}
.markdown-content blockquote p:last-child {
margin-bottom: 0;
}
/* 水平分割线 */
.markdown-content hr {
border: none;
height: 2px;
background: linear-gradient(to right, transparent, #bdc3c7, transparent);
margin: 2em 0;
}
/* ============================================================================
代码样式 - Code Styles
============================================================================ */
.markdown-content code {
font-family: 'Monaco', 'Menlo', 'Ubuntu Mono', 'Consolas', 'source-code-pro', monospace;
font-size: 0.9em;
}
.inline-code {
background: #f1f3f4;
color: #e74c3c;
padding: 0.15em 0.4em;
border-radius: 3px;
font-weight: 500;
border: 1px solid #ecf0f1;
}
.code-block {
background: #f8f9fa;
color: #333;
padding: 1.2em;
border-radius: 8px;
margin: 1em 0;
overflow-x: auto;
box-shadow: 0 2px 10px rgba(0, 0, 0, 0.1);
border: 1px solid #e9ecef;
}
.code-block code {
background: none;
color: inherit;
padding: 0;
border-radius: 0;
border: none;
font-size: 0.85em;
line-height: 1.5;
}
/* 语法高亮增强 */
.code-block .token.comment {
color: #a0aec0;
font-style: italic;
}
.code-block .token.keyword {
color: #63b3ed;
font-weight: bold;
}
.code-block .token.string {
color: #68d391;
}
.code-block .token.number {
color: #fbb6ce;
}
/* ============================================================================
表格样式 - Table Styles
============================================================================ */
.table-wrapper {
overflow-x: auto;
margin: 1em 0;
border-radius: 8px;
box-shadow: 0 2px 8px rgba(0, 0, 0, 0.1);
}
.markdown-table {
width: 100%;
border-collapse: collapse;
background: white;
border-radius: 8px;
overflow: hidden;
}
.markdown-table th,
.markdown-table td {
padding: 0.8em 1em;
text-align: left;
border-bottom: 1px solid #e2e8f0;
}
.markdown-table th {
background: #f7fafc;
font-weight: 600;
color: #2d3748;
border-bottom: 2px solid #cbd5e0;
}
.markdown-table tr:hover {
background: #f8f9fa;
}
.markdown-table tr:last-child td {
border-bottom: none;
}
/* ============================================================================
流式Markdown样式 - Streaming Markdown Styles
============================================================================ */
.streaming-markdown {
position: relative;
}
.normal-content,
.main-content {
position: relative;
}
.chain-of-thought {
margin-bottom: 1rem;
border: 1px solid #e0e7ff;
border-radius: 8px;
background: #f8faff;
overflow: hidden;
}
.chain-header {
padding: 0.75rem 1rem;
background: #f0f8ff;
border-bottom: 1px solid #e0e7ff;
display: flex;
align-items: center;
gap: 0.5rem;
cursor: pointer;
transition: background-color 0.2s;
}
.chain-header:hover {
background: #e6f3ff;
}
.chain-icon {
font-size: 1.1rem;
}
.chain-title {
font-weight: 500;
color: #4338ca;
font-size: 0.9rem;
}
.thinking-content {
padding: 1rem;
background: white;
}
/* ============================================================================
RAG来源样式 - RAG Sources Styles
============================================================================ */
.rag-sources-container {
margin-top: 12px;
border: 1px solid #e0e7ff;
border-radius: 8px;
background: #f8faff;
overflow: hidden;
}
.rag-sources-header {
padding: 8px 12px;
cursor: pointer;
display: flex;
align-items: center;
gap: 6px;
font-size: 13px;
font-weight: 500;
color: #4338ca;
background: #f0f8ff;
border-bottom: 1px solid #e0e7ff;
transition: background-color 0.2s;
user-select: none;
}
.rag-sources-header:hover {
background: #e6f3ff;
}
.rag-sources-content {
padding: 8px 12px;
background: white;
}
.rag-source-item {
margin-bottom: 12px;
padding: 10px;
background: white;
border-radius: 6px;
border: 1px solid #e5e7eb;
box-shadow: 0 1px 3px rgba(0, 0, 0, 0.05);
}
.rag-source-item:last-child {
margin-bottom: 0;
}
.rag-source-header {
display: flex;
justify-content: space-between;
align-items: center;
margin-bottom: 6px;
}
.rag-source-title {
font-size: 12px;
font-weight: 600;
color: #374151;
display: flex;
align-items: center;
gap: 4px;
}
.rag-source-title span:first-child {
font-size: 14px;
}
.rag-source-meta {
color: #6b7280;
font-weight: normal;
font-size: 11px;
}
.rag-source-score {
font-size: 11px;
color: #6b7280;
background: #f3f4f6;
padding: 2px 6px;
border-radius: 4px;
font-weight: 500;
}
.rag-source-content {
font-size: 12px;
color: #4b5563;
line-height: 1.4;
font-style: italic;
background: #f9fafb;
padding: 8px;
border-radius: 4px;
border: 1px solid #f3f4f6;
}
/* ============================================================================
数学公式样式 - Math Formula Styles
============================================================================ */
.markdown-content .katex {
font-size: 1.05em;
}
.markdown-content .katex-display {
margin: 1em 0;
text-align: center;
}
.markdown-content .katex-display .katex {
display: inline-block;
white-space: nowrap;
}
.markdown-content .katex-error {
color: #e74c3c;
background: #fdf2f2;
padding: 0.2em 0.4em;
border-radius: 3px;
border: 1px solid #fed7d7;
}
/* 数学公式容器样式增强 */
.markdown-content .katex-html {
white-space: nowrap;
overflow-x: auto;
overflow-y: hidden;
}
/* ============================================================================
图片样式 - Image Styles
============================================================================ */
.markdown-content img {
max-width: 100%;
height: auto;
border-radius: 6px;
margin: 0.5em 0;
box-shadow: 0 2px 8px rgba(0, 0, 0, 0.1);
border: 1px solid #e2e8f0;
}
.markdown-content img[alt*="icon"],
.markdown-content img[alt*="emoji"] {
display: inline;
margin: 0 0.2em;
box-shadow: none;
border: none;
border-radius: 0;
vertical-align: middle;
}
/* ============================================================================
响应式设计 - Responsive Design
============================================================================ */
@media (max-width: 768px) {
.markdown-content {
font-size: 0.9rem;
}
.markdown-content h1 { font-size: 1.3em; }
.markdown-content h2 { font-size: 1.2em; }
.markdown-content h3 { font-size: 1.1em; }
.code-block {
padding: 1em;
font-size: 0.8em;
}
.markdown-table th,
.markdown-table td {
padding: 0.6em 0.8em;
font-size: 0.85em;
}
.table-wrapper {
box-shadow: none;
border: 1px solid #e2e8f0;
}
.rag-sources-header {
padding: 6px 10px;
font-size: 12px;
}
.rag-sources-content {
padding: 6px 10px;
}
.rag-source-item {
padding: 8px;
margin-bottom: 8px;
}
.rag-source-title {
font-size: 11px;
}
.rag-source-content {
font-size: 11px;
padding: 6px;
}
}
@media (max-width: 480px) {
.markdown-content {
font-size: 0.85rem;
}
.markdown-content ul,
.markdown-content ol {
padding-left: 1.5em;
}
.markdown-content blockquote {
padding: 0.6em 1em;
margin: 0.8em 0;
}
.code-block {
padding: 0.8em;
margin: 0.8em 0;
}
.chain-header {
padding: 0.6rem 0.8rem;
font-size: 0.85rem;
}
.thinking-content {
padding: 0.8rem;
}
}
/* ============================================================================
打印样式 - Print Styles
============================================================================ */
@media print {
.markdown-content {
color: black;
background: white;
}
.code-block {
background: #f5f5f5;
color: black;
border: 1px solid #ccc;
}
.rag-sources-container {
border: 1px solid #ccc;
background: white;
}
.rag-sources-header {
background: #f5f5f5;
border-bottom: 1px solid #ccc;
}
.chain-of-thought {
border: 1px solid #ccc;
background: white;
}
.chain-header {
background: #f5f5f5;
border-bottom: 1px solid #ccc;
}
} | 12,291 | markdown | css | en | css | data | {"qsc_code_num_words": 1442, "qsc_code_num_chars": 12291.0, "qsc_code_mean_word_length": 4.85991678, "qsc_code_frac_words_unique": 0.18793343, "qsc_code_frac_chars_top_2grams": 0.14982877, "qsc_code_frac_chars_top_3grams": 0.02739726, "qsc_code_frac_chars_top_4grams": 0.01997717, "qsc_code_frac_chars_dupe_5grams": 0.28139269, "qsc_code_frac_chars_dupe_6grams": 0.20176941, "qsc_code_frac_chars_dupe_7grams": 0.14326484, "qsc_code_frac_chars_dupe_8grams": 0.08789954, "qsc_code_frac_chars_dupe_9grams": 0.06421233, "qsc_code_frac_chars_dupe_10grams": 0.05893265, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.05582548, "qsc_code_frac_chars_whitespace": 0.17948092, "qsc_code_size_file_byte": 12291.0, "qsc_code_num_lines": 648.0, "qsc_code_num_chars_line_max": 100.0, "qsc_code_num_chars_line_mean": 18.96759259, "qsc_code_frac_chars_alphabet": 0.63906792, "qsc_code_frac_chars_comments": 0.0, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.38703704, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.00479987, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0} | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 1, "qsc_code_mean_word_length": 0, "qsc_code_frac_words_unique": 1, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0} |
0015/esp_rlottie | rlottie/test/test_vrect.cpp | #include <gtest/gtest.h>
#include "vrect.h"
class VRectFTest : public ::testing::Test {
public:
void SetUp()
{
conersionRect = rect;
}
void TearDown()
{
}
public:
VRectF Empty;
VRectF illigal{0, 0, -100, 200};
VRectF conersionRect;
VRect rect{0, 0, 100, 100};
};
class VRectTest : public ::testing::Test {
public:
void SetUp()
{
conersionRect = rect;
}
void TearDown()
{
}
public:
VRect Empty;
VRect illigal{0, 0, -100, 200};
VRect conersionRect;
VRectF rect{0, 0, 100.5, 100};
};
TEST_F(VRectFTest, construct) {
VRectF r1{0, 0, 100, 100};
VRectF r2{0, 0, 100.0, 100};
VRectF r3 = {0, 0, 100, 100};
VRectF r4 = {0, 0, 100.0, 100};
VRectF r6(0, 0, 100, 100);
VRectF r7(0, 0, 100.0, 100);
ASSERT_TRUE(Empty.empty());
ASSERT_TRUE(illigal.empty());
}
TEST_F(VRectTest, construct) {
VRect r1{0, 0, 100, 100};
VRect r2{0, 0, 10, 100};
VRect r3 = {0, 0, 100, 100};
VRect r4 = {0, 0, 10, 100};
VRect r6(0, 0, 100, 100);
VRect r7(0, 0, 10, 100);
ASSERT_TRUE(Empty.empty());
ASSERT_TRUE(illigal.empty());
}
| 1,149 | test_vrect | cpp | en | cpp | code | {"qsc_code_num_words": 165, "qsc_code_num_chars": 1149.0, "qsc_code_mean_word_length": 3.91515152, "qsc_code_frac_words_unique": 0.2, "qsc_code_frac_chars_top_2grams": 0.0495356, "qsc_code_frac_chars_top_3grams": 0.1006192, "qsc_code_frac_chars_top_4grams": 0.08668731, "qsc_code_frac_chars_dupe_5grams": 0.63003096, "qsc_code_frac_chars_dupe_6grams": 0.39318885, "qsc_code_frac_chars_dupe_7grams": 0.34674923, "qsc_code_frac_chars_dupe_8grams": 0.34674923, "qsc_code_frac_chars_dupe_9grams": 0.34674923, "qsc_code_frac_chars_dupe_10grams": 0.20743034, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.16686391, "qsc_code_frac_chars_whitespace": 0.26457789, "qsc_code_size_file_byte": 1149.0, "qsc_code_num_lines": 58.0, "qsc_code_num_chars_line_max": 44.0, "qsc_code_num_chars_line_mean": 19.81034483, "qsc_code_frac_chars_alphabet": 0.59763314, "qsc_code_frac_chars_comments": 0.0, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.30769231, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.00609225, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.07692308, "qsc_codecpp_frac_lines_preprocessor_directives": 0.07692308, "qsc_codecpp_frac_lines_func_ratio": 0.15384615, "qsc_codecpp_cate_bitsstdc": 0.0, "qsc_codecpp_nums_lines_main": 0.0, "qsc_codecpp_frac_lines_goto": 0.0, "qsc_codecpp_cate_var_zero": 0.0, "qsc_codecpp_score_lines_no_logic": 0.23076923, "qsc_codecpp_frac_lines_print": 0.0} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codecpp_frac_lines_func_ratio": 0, "qsc_codecpp_nums_lines_main": 0, "qsc_codecpp_score_lines_no_logic": 0, "qsc_codecpp_frac_lines_preprocessor_directives": 0, "qsc_codecpp_frac_lines_print": 0} |
000linlin/ConsisLoRA | utils.py | from PIL import Image
import torch
from torchvision import transforms
BLOCKS = {
'content': ['unet.up_blocks.0.attentions.0'],
'style': ['unet.up_blocks.0.attentions.1'],
}
def is_belong_to_blocks(key, blocks):
try:
for g in blocks:
if g in key:
return True
return False
except Exception as e:
raise type(e)(f'failed to is_belong_to_block, due to: {e}')
def filter_consislora(state_dict):
try:
content_lora = {
k: v for k, v in state_dict.items() if is_belong_to_blocks(k, BLOCKS["content"])
}
style_lora = {
k: v for k, v in state_dict.items() if is_belong_to_blocks(k, BLOCKS["style"])
}
return content_lora, style_lora
except Exception as e:
raise type(e)(f'failed to filter_lora, due to: {e}')
def load_pil_image(img_path: str, target_size: int = None):
pil_img = Image.open(img_path).convert('RGB')
print(f"Loaded input image of size ({pil_img.size}) from {img_path}")
if target_size is not None:
resize = transforms.Resize(
size=target_size,
interpolation=transforms.InterpolationMode.BILINEAR
)
pil_img = resize(pil_img)
return pil_img
def unet_lora_state_dict(unet, adapter_name):
lora_state_dict = {}
for name, module in unet.named_modules():
for adapter in adapter_name:
if hasattr(module, adapter):
lora_layer = getattr(module, adapter)
if lora_layer is not None:
current_lora_sd = lora_layer.state_dict()
if "lora_A" in name: name = name.replace("lora_A", "lora.down")
elif "lora_B" in name: name = name.replace("lora_B", "lora.up")
for matrix_name, param in current_lora_sd.items():
lora_state_dict[f"{name}.{matrix_name}"] = param
return lora_state_dict
# Adapted from pipelines.StableDiffusionXLPipeline.encode_prompt
def encode_prompt(text_encoders, tokenizers, prompt, text_input_ids_list=None):
prompt_embeds_list = []
for i, text_encoder in enumerate(text_encoders):
if tokenizers is not None:
tokenizer = tokenizers[i]
text_input_ids = tokenizer(
prompt,
padding="max_length",
max_length=tokenizer.model_max_length,
truncation=True,
return_tensors="pt",
).input_ids
else:
assert text_input_ids_list is not None
text_input_ids = text_input_ids_list[i]
prompt_embeds = text_encoder(
text_input_ids.to(text_encoder.device),
output_hidden_states=True,
)
# We are only ALWAYS interested in the pooled output of the final text encoder
pooled_prompt_embeds = prompt_embeds[0]
prompt_embeds = prompt_embeds.hidden_states[-2]
bs_embed, seq_len, _ = prompt_embeds.shape
prompt_embeds = prompt_embeds.view(bs_embed, seq_len, -1)
prompt_embeds_list.append(prompt_embeds)
prompt_embeds = torch.concat(prompt_embeds_list, dim=-1)
pooled_prompt_embeds = pooled_prompt_embeds.view(bs_embed, -1)
return prompt_embeds, pooled_prompt_embeds
| 3,304 | utils | py | en | python | code | {"qsc_code_num_words": 437, "qsc_code_num_chars": 3304.0, "qsc_code_mean_word_length": 4.48283753, "qsc_code_frac_words_unique": 0.29519451, "qsc_code_frac_chars_top_2grams": 0.10413476, "qsc_code_frac_chars_top_3grams": 0.03675345, "qsc_code_frac_chars_top_4grams": 0.04900459, "qsc_code_frac_chars_dupe_5grams": 0.18785094, "qsc_code_frac_chars_dupe_6grams": 0.11638591, "qsc_code_frac_chars_dupe_7grams": 0.09086269, "qsc_code_frac_chars_dupe_8grams": 0.09086269, "qsc_code_frac_chars_dupe_9grams": 0.09086269, "qsc_code_frac_chars_dupe_10grams": 0.09086269, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.00379747, "qsc_code_frac_chars_whitespace": 0.28268765, "qsc_code_size_file_byte": 3304.0, "qsc_code_num_lines": 95.0, "qsc_code_num_chars_line_max": 93.0, "qsc_code_num_chars_line_mean": 34.77894737, "qsc_code_frac_chars_alphabet": 0.82278481, "qsc_code_frac_chars_comments": 0.04207022, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.05263158, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.09203036, "qsc_code_frac_chars_long_word_length": 0.01834282, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.01315789, "qsc_codepython_cate_ast": 1.0, "qsc_codepython_frac_lines_func_ratio": 0.06578947, "qsc_codepython_cate_var_zero": false, "qsc_codepython_frac_lines_pass": 0.0, "qsc_codepython_frac_lines_import": 0.03947368, "qsc_codepython_frac_lines_simplefunc": 0.0, "qsc_codepython_score_lines_no_logic": 0.18421053, "qsc_codepython_frac_lines_print": 0.01315789} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codepython_cate_ast": 0, "qsc_codepython_frac_lines_func_ratio": 0, "qsc_codepython_cate_var_zero": 0, "qsc_codepython_frac_lines_pass": 0, "qsc_codepython_frac_lines_import": 0, "qsc_codepython_frac_lines_simplefunc": 0, "qsc_codepython_score_lines_no_logic": 0, "qsc_codepython_frac_lines_print": 0} |
0015/7-Color-E-Paper-Digital-Photo-Frame | Flask_API_Server/monitor.py | import os
import time
from watchdog.observers import Observer
from watchdog.events import FileSystemEventHandler
from PIL import Image
import numpy as np
from concurrent.futures import ThreadPoolExecutor, as_completed
# Define folders
IMAGE_FOLDER = './images'
H_FILES_FOLDER = './h_files'
# Define the 7-color palette mapping
color_palette = {
(255, 255, 255): 0xFF, # White
(255, 255, 0): 0xFC, # Yellow
(255, 165, 0): 0xEC, # Orange
(255, 0, 0): 0xE0, # Red
(0, 128, 0): 0x35, # Green
(0, 0, 255): 0x2B, # Blue
(0, 0, 0): 0x00 # Black
}
def closest_palette_color(rgb):
"""Find the closest color in the palette."""
min_dist = float('inf')
closest_color = (255, 255, 255) # Default to white
for palette_rgb in color_palette:
# Cast to int32 to prevent overflow during calculations
dist = sum((int(rgb[i]) - int(palette_rgb[i])) ** 2 for i in range(3))
if dist < min_dist:
min_dist = dist
closest_color = palette_rgb
return closest_color
def apply_floyd_steinberg_dithering(image):
"""Apply Floyd-Steinberg dithering to the image."""
pixels = np.array(image, dtype=np.int16) # Use int16 to allow negative values during error distribution
for y in range(image.height):
for x in range(image.width):
old_pixel = tuple(pixels[y, x][:3])
new_pixel = closest_palette_color(old_pixel)
pixels[y, x][:3] = new_pixel
quant_error = np.array(old_pixel) - np.array(new_pixel)
# Distribute the quantization error to neighboring pixels (convert to int16 before adding)
if x + 1 < image.width:
pixels[y, x + 1][:3] += (quant_error * 7 / 16).astype(np.int16)
if x - 1 >= 0 and y + 1 < image.height:
pixels[y + 1, x - 1][:3] += (quant_error * 3 / 16).astype(np.int16)
if y + 1 < image.height:
pixels[y + 1, x][:3] += (quant_error * 5 / 16).astype(np.int16)
if x + 1 < image.width and y + 1 < image.height:
pixels[y + 1, x + 1][:3] += (quant_error * 1 / 16).astype(np.int16)
# Clip pixel values to be within 0-255 range after dithering
pixels = np.clip(pixels, 0, 255)
return Image.fromarray(pixels.astype(np.uint8))
def convert_image_to_header(input_image_path, output_path):
# Open and resize the image
image = Image.open(input_image_path)
image = image.resize((600, 448))
image = image.convert("RGB") # Ensure it’s in RGB format
# Apply dithering
dithered_image = apply_floyd_steinberg_dithering(image)
output_file = os.path.join(output_path, os.path.splitext(os.path.basename(input_image_path))[0] + ".h")
# Create the data array
data_array = []
for y in range(448):
for x in range(600):
rgb = dithered_image.getpixel((x, y))
color_code = color_palette.get(tuple(rgb), 0xFF) # Default to white if color is not mapped
data_array.append(color_code)
# Write to header file
with open(output_file, 'w') as f:
for i in range(0, len(data_array), 16):
line = ', '.join(f"0x{data_array[j]:02X}" for j in range(i, min(i + 16, len(data_array))))
f.write(f" {line},\n")
# Handler for folder changes
class ImageHandler(FileSystemEventHandler):
def __init__(self):
self.executor = ThreadPoolExecutor()
def on_created(self, event):
if event.is_directory:
return
if event.src_path.lower().endswith(('.png', '.jpg', '.jpeg')):
print(f"New image detected: {event.src_path}")
# Wait until file is fully copied by checking file size stability
stable = False
while not stable:
initial_size = os.path.getsize(event.src_path)
time.sleep(1) # Wait a second
new_size = os.path.getsize(event.src_path)
if initial_size == new_size:
stable = True
try:
# Submit the file conversion task to the executor
self.executor.submit(convert_image_to_header, event.src_path, H_FILES_FOLDER)
print(f"Converted {event.src_path} to .h file")
except Exception as e:
print(f"Failed to convert {event.src_path}: {e}")
# Monitor the image folder for changes
def monitor_folder():
if not os.path.exists(H_FILES_FOLDER):
os.makedirs(H_FILES_FOLDER)
if not os.path.exists(IMAGE_FOLDER):
os.makedirs(IMAGE_FOLDER)
event_handler = ImageHandler()
observer = Observer()
observer.schedule(event_handler, path=IMAGE_FOLDER, recursive=False)
observer.start()
try:
while True:
time.sleep(1)
except KeyboardInterrupt:
observer.stop()
observer.join()
# Run the folder monitoring
if __name__ == "__main__":
monitor_folder()
| 5,007 | monitor | py | en | python | code | {"qsc_code_num_words": 684, "qsc_code_num_chars": 5007.0, "qsc_code_mean_word_length": 4.32894737, "qsc_code_frac_words_unique": 0.30116959, "qsc_code_frac_chars_top_2grams": 0.01654846, "qsc_code_frac_chars_top_3grams": 0.02836879, "qsc_code_frac_chars_top_4grams": 0.02026342, "qsc_code_frac_chars_dupe_5grams": 0.14353259, "qsc_code_frac_chars_dupe_6grams": 0.09186086, "qsc_code_frac_chars_dupe_7grams": 0.06484296, "qsc_code_frac_chars_dupe_8grams": 0.03242148, "qsc_code_frac_chars_dupe_9grams": 0.02499156, "qsc_code_frac_chars_dupe_10grams": 0.02499156, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.04039845, "qsc_code_frac_chars_whitespace": 0.27821051, "qsc_code_size_file_byte": 5007.0, "qsc_code_num_lines": 133.0, "qsc_code_num_chars_line_max": 109.0, "qsc_code_num_chars_line_mean": 37.64661654, "qsc_code_frac_chars_alphabet": 0.77891533, "qsc_code_frac_chars_comments": 0.16436988, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.04081633, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.04701061, "qsc_code_frac_chars_long_word_length": 0.00506268, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.00771456, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codepython_cate_ast": 1.0, "qsc_codepython_frac_lines_func_ratio": 0.06122449, "qsc_codepython_cate_var_zero": false, "qsc_codepython_frac_lines_pass": 0.0, "qsc_codepython_frac_lines_import": 0.07142857, "qsc_codepython_frac_lines_simplefunc": 0.0, "qsc_codepython_score_lines_no_logic": 0.17346939, "qsc_codepython_frac_lines_print": 0.03061224} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codepython_cate_ast": 0, "qsc_codepython_frac_lines_func_ratio": 0, "qsc_codepython_cate_var_zero": 0, "qsc_codepython_frac_lines_pass": 0, "qsc_codepython_frac_lines_import": 0, "qsc_codepython_frac_lines_simplefunc": 0, "qsc_codepython_score_lines_no_logic": 0, "qsc_codepython_frac_lines_print": 0} |
0015/Fridge-Calendar | sdkconfig.thatproject | #
# Automatically generated file. DO NOT EDIT.
# Espressif IoT Development Framework (ESP-IDF) 5.3.1 Project Configuration
#
CONFIG_SOC_MPU_MIN_REGION_SIZE=0x20000000
CONFIG_SOC_MPU_REGIONS_MAX_NUM=8
CONFIG_SOC_ADC_SUPPORTED=y
CONFIG_SOC_UART_SUPPORTED=y
CONFIG_SOC_PCNT_SUPPORTED=y
CONFIG_SOC_PHY_SUPPORTED=y
CONFIG_SOC_WIFI_SUPPORTED=y
CONFIG_SOC_TWAI_SUPPORTED=y
CONFIG_SOC_GDMA_SUPPORTED=y
CONFIG_SOC_AHB_GDMA_SUPPORTED=y
CONFIG_SOC_GPTIMER_SUPPORTED=y
CONFIG_SOC_LCDCAM_SUPPORTED=y
CONFIG_SOC_MCPWM_SUPPORTED=y
CONFIG_SOC_DEDICATED_GPIO_SUPPORTED=y
CONFIG_SOC_CACHE_SUPPORT_WRAP=y
CONFIG_SOC_ULP_SUPPORTED=y
CONFIG_SOC_ULP_FSM_SUPPORTED=y
CONFIG_SOC_RISCV_COPROC_SUPPORTED=y
CONFIG_SOC_BT_SUPPORTED=y
CONFIG_SOC_USB_OTG_SUPPORTED=y
CONFIG_SOC_USB_SERIAL_JTAG_SUPPORTED=y
CONFIG_SOC_CCOMP_TIMER_SUPPORTED=y
CONFIG_SOC_ASYNC_MEMCPY_SUPPORTED=y
CONFIG_SOC_SUPPORTS_SECURE_DL_MODE=y
CONFIG_SOC_EFUSE_KEY_PURPOSE_FIELD=y
CONFIG_SOC_EFUSE_SUPPORTED=y
CONFIG_SOC_SDMMC_HOST_SUPPORTED=y
CONFIG_SOC_RTC_FAST_MEM_SUPPORTED=y
CONFIG_SOC_RTC_SLOW_MEM_SUPPORTED=y
CONFIG_SOC_RTC_MEM_SUPPORTED=y
CONFIG_SOC_PSRAM_DMA_CAPABLE=y
CONFIG_SOC_XT_WDT_SUPPORTED=y
CONFIG_SOC_I2S_SUPPORTED=y
CONFIG_SOC_RMT_SUPPORTED=y
CONFIG_SOC_SDM_SUPPORTED=y
CONFIG_SOC_GPSPI_SUPPORTED=y
CONFIG_SOC_LEDC_SUPPORTED=y
CONFIG_SOC_I2C_SUPPORTED=y
CONFIG_SOC_SYSTIMER_SUPPORTED=y
CONFIG_SOC_SUPPORT_COEXISTENCE=y
CONFIG_SOC_TEMP_SENSOR_SUPPORTED=y
CONFIG_SOC_AES_SUPPORTED=y
CONFIG_SOC_MPI_SUPPORTED=y
CONFIG_SOC_SHA_SUPPORTED=y
CONFIG_SOC_HMAC_SUPPORTED=y
CONFIG_SOC_DIG_SIGN_SUPPORTED=y
CONFIG_SOC_FLASH_ENC_SUPPORTED=y
CONFIG_SOC_SECURE_BOOT_SUPPORTED=y
CONFIG_SOC_MEMPROT_SUPPORTED=y
CONFIG_SOC_TOUCH_SENSOR_SUPPORTED=y
CONFIG_SOC_BOD_SUPPORTED=y
CONFIG_SOC_CLK_TREE_SUPPORTED=y
CONFIG_SOC_MPU_SUPPORTED=y
CONFIG_SOC_WDT_SUPPORTED=y
CONFIG_SOC_SPI_FLASH_SUPPORTED=y
CONFIG_SOC_RNG_SUPPORTED=y
CONFIG_SOC_LIGHT_SLEEP_SUPPORTED=y
CONFIG_SOC_DEEP_SLEEP_SUPPORTED=y
CONFIG_SOC_LP_PERIPH_SHARE_INTERRUPT=y
CONFIG_SOC_PM_SUPPORTED=y
CONFIG_SOC_XTAL_SUPPORT_40M=y
CONFIG_SOC_APPCPU_HAS_CLOCK_GATING_BUG=y
CONFIG_SOC_ADC_RTC_CTRL_SUPPORTED=y
CONFIG_SOC_ADC_DIG_CTRL_SUPPORTED=y
CONFIG_SOC_ADC_ARBITER_SUPPORTED=y
CONFIG_SOC_ADC_DIG_IIR_FILTER_SUPPORTED=y
CONFIG_SOC_ADC_MONITOR_SUPPORTED=y
CONFIG_SOC_ADC_DMA_SUPPORTED=y
CONFIG_SOC_ADC_PERIPH_NUM=2
CONFIG_SOC_ADC_MAX_CHANNEL_NUM=10
CONFIG_SOC_ADC_ATTEN_NUM=4
CONFIG_SOC_ADC_DIGI_CONTROLLER_NUM=2
CONFIG_SOC_ADC_PATT_LEN_MAX=24
CONFIG_SOC_ADC_DIGI_MIN_BITWIDTH=12
CONFIG_SOC_ADC_DIGI_MAX_BITWIDTH=12
CONFIG_SOC_ADC_DIGI_RESULT_BYTES=4
CONFIG_SOC_ADC_DIGI_DATA_BYTES_PER_CONV=4
CONFIG_SOC_ADC_DIGI_IIR_FILTER_NUM=2
CONFIG_SOC_ADC_DIGI_MONITOR_NUM=2
CONFIG_SOC_ADC_SAMPLE_FREQ_THRES_HIGH=83333
CONFIG_SOC_ADC_SAMPLE_FREQ_THRES_LOW=611
CONFIG_SOC_ADC_RTC_MIN_BITWIDTH=12
CONFIG_SOC_ADC_RTC_MAX_BITWIDTH=12
CONFIG_SOC_ADC_CALIBRATION_V1_SUPPORTED=y
CONFIG_SOC_ADC_SELF_HW_CALI_SUPPORTED=y
CONFIG_SOC_ADC_SHARED_POWER=y
CONFIG_SOC_APB_BACKUP_DMA=y
CONFIG_SOC_BROWNOUT_RESET_SUPPORTED=y
CONFIG_SOC_CACHE_WRITEBACK_SUPPORTED=y
CONFIG_SOC_CACHE_FREEZE_SUPPORTED=y
CONFIG_SOC_CPU_CORES_NUM=2
CONFIG_SOC_CPU_INTR_NUM=32
CONFIG_SOC_CPU_HAS_FPU=y
CONFIG_SOC_HP_CPU_HAS_MULTIPLE_CORES=y
CONFIG_SOC_CPU_BREAKPOINTS_NUM=2
CONFIG_SOC_CPU_WATCHPOINTS_NUM=2
CONFIG_SOC_CPU_WATCHPOINT_MAX_REGION_SIZE=64
CONFIG_SOC_DS_SIGNATURE_MAX_BIT_LEN=4096
CONFIG_SOC_DS_KEY_PARAM_MD_IV_LENGTH=16
CONFIG_SOC_DS_KEY_CHECK_MAX_WAIT_US=1100
CONFIG_SOC_AHB_GDMA_VERSION=1
CONFIG_SOC_GDMA_NUM_GROUPS_MAX=1
CONFIG_SOC_GDMA_PAIRS_PER_GROUP=5
CONFIG_SOC_GDMA_PAIRS_PER_GROUP_MAX=5
CONFIG_SOC_AHB_GDMA_SUPPORT_PSRAM=y
CONFIG_SOC_GPIO_PORT=1
CONFIG_SOC_GPIO_PIN_COUNT=49
CONFIG_SOC_GPIO_SUPPORT_PIN_GLITCH_FILTER=y
CONFIG_SOC_GPIO_FILTER_CLK_SUPPORT_APB=y
CONFIG_SOC_GPIO_SUPPORT_RTC_INDEPENDENT=y
CONFIG_SOC_GPIO_SUPPORT_FORCE_HOLD=y
CONFIG_SOC_GPIO_VALID_GPIO_MASK=0x1FFFFFFFFFFFF
CONFIG_SOC_GPIO_IN_RANGE_MAX=48
CONFIG_SOC_GPIO_OUT_RANGE_MAX=48
CONFIG_SOC_GPIO_VALID_DIGITAL_IO_PAD_MASK=0x0001FFFFFC000000
CONFIG_SOC_GPIO_CLOCKOUT_BY_IO_MUX=y
CONFIG_SOC_GPIO_CLOCKOUT_CHANNEL_NUM=3
CONFIG_SOC_DEDIC_GPIO_OUT_CHANNELS_NUM=8
CONFIG_SOC_DEDIC_GPIO_IN_CHANNELS_NUM=8
CONFIG_SOC_DEDIC_GPIO_OUT_AUTO_ENABLE=y
CONFIG_SOC_I2C_NUM=2
CONFIG_SOC_HP_I2C_NUM=2
CONFIG_SOC_I2C_FIFO_LEN=32
CONFIG_SOC_I2C_CMD_REG_NUM=8
CONFIG_SOC_I2C_SUPPORT_SLAVE=y
CONFIG_SOC_I2C_SUPPORT_HW_CLR_BUS=y
CONFIG_SOC_I2C_SUPPORT_XTAL=y
CONFIG_SOC_I2C_SUPPORT_RTC=y
CONFIG_SOC_I2C_SUPPORT_10BIT_ADDR=y
CONFIG_SOC_I2C_SLAVE_SUPPORT_BROADCAST=y
CONFIG_SOC_I2C_SLAVE_SUPPORT_I2CRAM_ACCESS=y
CONFIG_SOC_I2S_NUM=2
CONFIG_SOC_I2S_HW_VERSION_2=y
CONFIG_SOC_I2S_SUPPORTS_XTAL=y
CONFIG_SOC_I2S_SUPPORTS_PLL_F160M=y
CONFIG_SOC_I2S_SUPPORTS_PCM=y
CONFIG_SOC_I2S_SUPPORTS_PDM=y
CONFIG_SOC_I2S_SUPPORTS_PDM_TX=y
CONFIG_SOC_I2S_PDM_MAX_TX_LINES=2
CONFIG_SOC_I2S_SUPPORTS_PDM_RX=y
CONFIG_SOC_I2S_PDM_MAX_RX_LINES=4
CONFIG_SOC_I2S_SUPPORTS_TDM=y
CONFIG_SOC_LEDC_SUPPORT_APB_CLOCK=y
CONFIG_SOC_LEDC_SUPPORT_XTAL_CLOCK=y
CONFIG_SOC_LEDC_CHANNEL_NUM=8
CONFIG_SOC_LEDC_TIMER_BIT_WIDTH=14
CONFIG_SOC_LEDC_SUPPORT_FADE_STOP=y
CONFIG_SOC_MCPWM_GROUPS=2
CONFIG_SOC_MCPWM_TIMERS_PER_GROUP=3
CONFIG_SOC_MCPWM_OPERATORS_PER_GROUP=3
CONFIG_SOC_MCPWM_COMPARATORS_PER_OPERATOR=2
CONFIG_SOC_MCPWM_GENERATORS_PER_OPERATOR=2
CONFIG_SOC_MCPWM_TRIGGERS_PER_OPERATOR=2
CONFIG_SOC_MCPWM_GPIO_FAULTS_PER_GROUP=3
CONFIG_SOC_MCPWM_CAPTURE_TIMERS_PER_GROUP=y
CONFIG_SOC_MCPWM_CAPTURE_CHANNELS_PER_TIMER=3
CONFIG_SOC_MCPWM_GPIO_SYNCHROS_PER_GROUP=3
CONFIG_SOC_MCPWM_SWSYNC_CAN_PROPAGATE=y
CONFIG_SOC_MMU_LINEAR_ADDRESS_REGION_NUM=1
CONFIG_SOC_MMU_PERIPH_NUM=1
CONFIG_SOC_PCNT_GROUPS=1
CONFIG_SOC_PCNT_UNITS_PER_GROUP=4
CONFIG_SOC_PCNT_CHANNELS_PER_UNIT=2
CONFIG_SOC_PCNT_THRES_POINT_PER_UNIT=2
CONFIG_SOC_RMT_GROUPS=1
CONFIG_SOC_RMT_TX_CANDIDATES_PER_GROUP=4
CONFIG_SOC_RMT_RX_CANDIDATES_PER_GROUP=4
CONFIG_SOC_RMT_CHANNELS_PER_GROUP=8
CONFIG_SOC_RMT_MEM_WORDS_PER_CHANNEL=48
CONFIG_SOC_RMT_SUPPORT_RX_PINGPONG=y
CONFIG_SOC_RMT_SUPPORT_RX_DEMODULATION=y
CONFIG_SOC_RMT_SUPPORT_TX_ASYNC_STOP=y
CONFIG_SOC_RMT_SUPPORT_TX_LOOP_COUNT=y
CONFIG_SOC_RMT_SUPPORT_TX_LOOP_AUTO_STOP=y
CONFIG_SOC_RMT_SUPPORT_TX_SYNCHRO=y
CONFIG_SOC_RMT_SUPPORT_TX_CARRIER_DATA_ONLY=y
CONFIG_SOC_RMT_SUPPORT_XTAL=y
CONFIG_SOC_RMT_SUPPORT_RC_FAST=y
CONFIG_SOC_RMT_SUPPORT_APB=y
CONFIG_SOC_RMT_SUPPORT_DMA=y
CONFIG_SOC_LCD_I80_SUPPORTED=y
CONFIG_SOC_LCD_RGB_SUPPORTED=y
CONFIG_SOC_LCD_I80_BUSES=1
CONFIG_SOC_LCD_RGB_PANELS=1
CONFIG_SOC_LCD_I80_BUS_WIDTH=16
CONFIG_SOC_LCD_RGB_DATA_WIDTH=16
CONFIG_SOC_LCD_SUPPORT_RGB_YUV_CONV=y
CONFIG_SOC_RTC_CNTL_CPU_PD_DMA_BUS_WIDTH=128
CONFIG_SOC_RTC_CNTL_CPU_PD_REG_FILE_NUM=549
CONFIG_SOC_RTC_CNTL_TAGMEM_PD_DMA_BUS_WIDTH=128
CONFIG_SOC_RTCIO_PIN_COUNT=22
CONFIG_SOC_RTCIO_INPUT_OUTPUT_SUPPORTED=y
CONFIG_SOC_RTCIO_HOLD_SUPPORTED=y
CONFIG_SOC_RTCIO_WAKE_SUPPORTED=y
CONFIG_SOC_SDM_GROUPS=y
CONFIG_SOC_SDM_CHANNELS_PER_GROUP=8
CONFIG_SOC_SDM_CLK_SUPPORT_APB=y
CONFIG_SOC_SPI_PERIPH_NUM=3
CONFIG_SOC_SPI_MAX_CS_NUM=6
CONFIG_SOC_SPI_MAXIMUM_BUFFER_SIZE=64
CONFIG_SOC_SPI_SUPPORT_DDRCLK=y
CONFIG_SOC_SPI_SLAVE_SUPPORT_SEG_TRANS=y
CONFIG_SOC_SPI_SUPPORT_CD_SIG=y
CONFIG_SOC_SPI_SUPPORT_CONTINUOUS_TRANS=y
CONFIG_SOC_SPI_SUPPORT_SLAVE_HD_VER2=y
CONFIG_SOC_SPI_SUPPORT_CLK_APB=y
CONFIG_SOC_SPI_SUPPORT_CLK_XTAL=y
CONFIG_SOC_SPI_PERIPH_SUPPORT_CONTROL_DUMMY_OUT=y
CONFIG_SOC_MEMSPI_IS_INDEPENDENT=y
CONFIG_SOC_SPI_MAX_PRE_DIVIDER=16
CONFIG_SOC_SPI_SUPPORT_OCT=y
CONFIG_SOC_SPI_SCT_SUPPORTED=y
CONFIG_SOC_SPI_SCT_REG_NUM=14
CONFIG_SOC_SPI_SCT_BUFFER_NUM_MAX=y
CONFIG_SOC_SPI_SCT_CONF_BITLEN_MAX=0x3FFFA
CONFIG_SOC_MEMSPI_SRC_FREQ_120M=y
CONFIG_SOC_MEMSPI_SRC_FREQ_80M_SUPPORTED=y
CONFIG_SOC_MEMSPI_SRC_FREQ_40M_SUPPORTED=y
CONFIG_SOC_MEMSPI_SRC_FREQ_20M_SUPPORTED=y
CONFIG_SOC_SPIRAM_SUPPORTED=y
CONFIG_SOC_SPIRAM_XIP_SUPPORTED=y
CONFIG_SOC_SYSTIMER_COUNTER_NUM=2
CONFIG_SOC_SYSTIMER_ALARM_NUM=3
CONFIG_SOC_SYSTIMER_BIT_WIDTH_LO=32
CONFIG_SOC_SYSTIMER_BIT_WIDTH_HI=20
CONFIG_SOC_SYSTIMER_FIXED_DIVIDER=y
CONFIG_SOC_SYSTIMER_INT_LEVEL=y
CONFIG_SOC_SYSTIMER_ALARM_MISS_COMPENSATE=y
CONFIG_SOC_TIMER_GROUPS=2
CONFIG_SOC_TIMER_GROUP_TIMERS_PER_GROUP=2
CONFIG_SOC_TIMER_GROUP_COUNTER_BIT_WIDTH=54
CONFIG_SOC_TIMER_GROUP_SUPPORT_XTAL=y
CONFIG_SOC_TIMER_GROUP_SUPPORT_APB=y
CONFIG_SOC_TIMER_GROUP_TOTAL_TIMERS=4
CONFIG_SOC_TOUCH_SENSOR_VERSION=2
CONFIG_SOC_TOUCH_SENSOR_NUM=15
CONFIG_SOC_TOUCH_SUPPORT_SLEEP_WAKEUP=y
CONFIG_SOC_TOUCH_SUPPORT_WATERPROOF=y
CONFIG_SOC_TOUCH_SUPPORT_PROX_SENSING=y
CONFIG_SOC_TOUCH_PROXIMITY_CHANNEL_NUM=3
CONFIG_SOC_TOUCH_PROXIMITY_MEAS_DONE_SUPPORTED=y
CONFIG_SOC_TOUCH_SAMPLE_CFG_NUM=1
CONFIG_SOC_TWAI_CONTROLLER_NUM=1
CONFIG_SOC_TWAI_CLK_SUPPORT_APB=y
CONFIG_SOC_TWAI_BRP_MIN=2
CONFIG_SOC_TWAI_BRP_MAX=16384
CONFIG_SOC_TWAI_SUPPORTS_RX_STATUS=y
CONFIG_SOC_UART_NUM=3
CONFIG_SOC_UART_HP_NUM=3
CONFIG_SOC_UART_FIFO_LEN=128
CONFIG_SOC_UART_BITRATE_MAX=5000000
CONFIG_SOC_UART_SUPPORT_FSM_TX_WAIT_SEND=y
CONFIG_SOC_UART_SUPPORT_WAKEUP_INT=y
CONFIG_SOC_UART_SUPPORT_APB_CLK=y
CONFIG_SOC_UART_SUPPORT_RTC_CLK=y
CONFIG_SOC_UART_SUPPORT_XTAL_CLK=y
CONFIG_SOC_USB_OTG_PERIPH_NUM=1
CONFIG_SOC_SHA_DMA_MAX_BUFFER_SIZE=3968
CONFIG_SOC_SHA_SUPPORT_DMA=y
CONFIG_SOC_SHA_SUPPORT_RESUME=y
CONFIG_SOC_SHA_GDMA=y
CONFIG_SOC_SHA_SUPPORT_SHA1=y
CONFIG_SOC_SHA_SUPPORT_SHA224=y
CONFIG_SOC_SHA_SUPPORT_SHA256=y
CONFIG_SOC_SHA_SUPPORT_SHA384=y
CONFIG_SOC_SHA_SUPPORT_SHA512=y
CONFIG_SOC_SHA_SUPPORT_SHA512_224=y
CONFIG_SOC_SHA_SUPPORT_SHA512_256=y
CONFIG_SOC_SHA_SUPPORT_SHA512_T=y
CONFIG_SOC_MPI_MEM_BLOCKS_NUM=4
CONFIG_SOC_MPI_OPERATIONS_NUM=3
CONFIG_SOC_RSA_MAX_BIT_LEN=4096
CONFIG_SOC_AES_SUPPORT_DMA=y
CONFIG_SOC_AES_GDMA=y
CONFIG_SOC_AES_SUPPORT_AES_128=y
CONFIG_SOC_AES_SUPPORT_AES_256=y
CONFIG_SOC_PM_SUPPORT_EXT0_WAKEUP=y
CONFIG_SOC_PM_SUPPORT_EXT1_WAKEUP=y
CONFIG_SOC_PM_SUPPORT_EXT_WAKEUP=y
CONFIG_SOC_PM_SUPPORT_WIFI_WAKEUP=y
CONFIG_SOC_PM_SUPPORT_BT_WAKEUP=y
CONFIG_SOC_PM_SUPPORT_TOUCH_SENSOR_WAKEUP=y
CONFIG_SOC_PM_SUPPORT_CPU_PD=y
CONFIG_SOC_PM_SUPPORT_TAGMEM_PD=y
CONFIG_SOC_PM_SUPPORT_RTC_PERIPH_PD=y
CONFIG_SOC_PM_SUPPORT_RC_FAST_PD=y
CONFIG_SOC_PM_SUPPORT_VDDSDIO_PD=y
CONFIG_SOC_PM_SUPPORT_MAC_BB_PD=y
CONFIG_SOC_PM_SUPPORT_MODEM_PD=y
CONFIG_SOC_CONFIGURABLE_VDDSDIO_SUPPORTED=y
CONFIG_SOC_PM_SUPPORT_DEEPSLEEP_CHECK_STUB_ONLY=y
CONFIG_SOC_PM_CPU_RETENTION_BY_RTCCNTL=y
CONFIG_SOC_PM_MODEM_RETENTION_BY_BACKUPDMA=y
CONFIG_SOC_CLK_RC_FAST_D256_SUPPORTED=y
CONFIG_SOC_RTC_SLOW_CLK_SUPPORT_RC_FAST_D256=y
CONFIG_SOC_CLK_RC_FAST_SUPPORT_CALIBRATION=y
CONFIG_SOC_CLK_XTAL32K_SUPPORTED=y
CONFIG_SOC_EFUSE_DIS_DOWNLOAD_ICACHE=y
CONFIG_SOC_EFUSE_DIS_DOWNLOAD_DCACHE=y
CONFIG_SOC_EFUSE_HARD_DIS_JTAG=y
CONFIG_SOC_EFUSE_DIS_USB_JTAG=y
CONFIG_SOC_EFUSE_SOFT_DIS_JTAG=y
CONFIG_SOC_EFUSE_DIS_DIRECT_BOOT=y
CONFIG_SOC_EFUSE_DIS_ICACHE=y
CONFIG_SOC_EFUSE_BLOCK9_KEY_PURPOSE_QUIRK=y
CONFIG_SOC_SECURE_BOOT_V2_RSA=y
CONFIG_SOC_EFUSE_SECURE_BOOT_KEY_DIGESTS=3
CONFIG_SOC_EFUSE_REVOKE_BOOT_KEY_DIGESTS=y
CONFIG_SOC_SUPPORT_SECURE_BOOT_REVOKE_KEY=y
CONFIG_SOC_FLASH_ENCRYPTED_XTS_AES_BLOCK_MAX=64
CONFIG_SOC_FLASH_ENCRYPTION_XTS_AES=y
CONFIG_SOC_FLASH_ENCRYPTION_XTS_AES_OPTIONS=y
CONFIG_SOC_FLASH_ENCRYPTION_XTS_AES_128=y
CONFIG_SOC_FLASH_ENCRYPTION_XTS_AES_256=y
CONFIG_SOC_MEMPROT_CPU_PREFETCH_PAD_SIZE=16
CONFIG_SOC_MEMPROT_MEM_ALIGN_SIZE=256
CONFIG_SOC_PHY_DIG_REGS_MEM_SIZE=21
CONFIG_SOC_MAC_BB_PD_MEM_SIZE=192
CONFIG_SOC_WIFI_LIGHT_SLEEP_CLK_WIDTH=12
CONFIG_SOC_SPI_MEM_SUPPORT_AUTO_WAIT_IDLE=y
CONFIG_SOC_SPI_MEM_SUPPORT_AUTO_SUSPEND=y
CONFIG_SOC_SPI_MEM_SUPPORT_AUTO_RESUME=y
CONFIG_SOC_SPI_MEM_SUPPORT_SW_SUSPEND=y
CONFIG_SOC_SPI_MEM_SUPPORT_OPI_MODE=y
CONFIG_SOC_SPI_MEM_SUPPORT_TIMING_TUNING=y
CONFIG_SOC_SPI_MEM_SUPPORT_CONFIG_GPIO_BY_EFUSE=y
CONFIG_SOC_SPI_MEM_SUPPORT_WRAP=y
CONFIG_SOC_MEMSPI_TIMING_TUNING_BY_MSPI_DELAY=y
CONFIG_SOC_MEMSPI_CORE_CLK_SHARED_WITH_PSRAM=y
CONFIG_SOC_COEX_HW_PTI=y
CONFIG_SOC_EXTERNAL_COEX_LEADER_TX_LINE=y
CONFIG_SOC_SDMMC_USE_GPIO_MATRIX=y
CONFIG_SOC_SDMMC_NUM_SLOTS=2
CONFIG_SOC_SDMMC_SUPPORT_XTAL_CLOCK=y
CONFIG_SOC_SDMMC_DELAY_PHASE_NUM=4
CONFIG_SOC_TEMPERATURE_SENSOR_SUPPORT_FAST_RC=y
CONFIG_SOC_WIFI_HW_TSF=y
CONFIG_SOC_WIFI_FTM_SUPPORT=y
CONFIG_SOC_WIFI_GCMP_SUPPORT=y
CONFIG_SOC_WIFI_WAPI_SUPPORT=y
CONFIG_SOC_WIFI_CSI_SUPPORT=y
CONFIG_SOC_WIFI_MESH_SUPPORT=y
CONFIG_SOC_WIFI_SUPPORT_VARIABLE_BEACON_WINDOW=y
CONFIG_SOC_WIFI_PHY_NEEDS_USB_WORKAROUND=y
CONFIG_SOC_BLE_SUPPORTED=y
CONFIG_SOC_BLE_MESH_SUPPORTED=y
CONFIG_SOC_BLE_50_SUPPORTED=y
CONFIG_SOC_BLE_DEVICE_PRIVACY_SUPPORTED=y
CONFIG_SOC_BLUFI_SUPPORTED=y
CONFIG_SOC_ULP_HAS_ADC=y
CONFIG_SOC_PHY_COMBO_MODULE=y
CONFIG_IDF_CMAKE=y
CONFIG_IDF_TOOLCHAIN="gcc"
CONFIG_IDF_TARGET_ARCH_XTENSA=y
CONFIG_IDF_TARGET_ARCH="xtensa"
CONFIG_IDF_TARGET="esp32s3"
CONFIG_IDF_INIT_VERSION="5.3.1"
CONFIG_IDF_TARGET_ESP32S3=y
CONFIG_IDF_FIRMWARE_CHIP_ID=0x0009
#
# Build type
#
CONFIG_APP_BUILD_TYPE_APP_2NDBOOT=y
# CONFIG_APP_BUILD_TYPE_RAM is not set
CONFIG_APP_BUILD_GENERATE_BINARIES=y
CONFIG_APP_BUILD_BOOTLOADER=y
CONFIG_APP_BUILD_USE_FLASH_SECTIONS=y
# CONFIG_APP_REPRODUCIBLE_BUILD is not set
# CONFIG_APP_NO_BLOBS is not set
# end of Build type
#
# Bootloader config
#
#
# Bootloader manager
#
CONFIG_BOOTLOADER_COMPILE_TIME_DATE=y
CONFIG_BOOTLOADER_PROJECT_VER=1
# end of Bootloader manager
CONFIG_BOOTLOADER_OFFSET_IN_FLASH=0x0
CONFIG_BOOTLOADER_COMPILER_OPTIMIZATION_SIZE=y
# CONFIG_BOOTLOADER_COMPILER_OPTIMIZATION_DEBUG is not set
# CONFIG_BOOTLOADER_COMPILER_OPTIMIZATION_PERF is not set
# CONFIG_BOOTLOADER_COMPILER_OPTIMIZATION_NONE is not set
# CONFIG_BOOTLOADER_LOG_LEVEL_NONE is not set
# CONFIG_BOOTLOADER_LOG_LEVEL_ERROR is not set
# CONFIG_BOOTLOADER_LOG_LEVEL_WARN is not set
CONFIG_BOOTLOADER_LOG_LEVEL_INFO=y
# CONFIG_BOOTLOADER_LOG_LEVEL_DEBUG is not set
# CONFIG_BOOTLOADER_LOG_LEVEL_VERBOSE is not set
CONFIG_BOOTLOADER_LOG_LEVEL=3
#
# Serial Flash Configurations
#
# CONFIG_BOOTLOADER_FLASH_DC_AWARE is not set
CONFIG_BOOTLOADER_FLASH_XMC_SUPPORT=y
# end of Serial Flash Configurations
CONFIG_BOOTLOADER_VDDSDIO_BOOST_1_9V=y
# CONFIG_BOOTLOADER_FACTORY_RESET is not set
# CONFIG_BOOTLOADER_APP_TEST is not set
CONFIG_BOOTLOADER_REGION_PROTECTION_ENABLE=y
CONFIG_BOOTLOADER_WDT_ENABLE=y
# CONFIG_BOOTLOADER_WDT_DISABLE_IN_USER_CODE is not set
CONFIG_BOOTLOADER_WDT_TIME_MS=9000
# CONFIG_BOOTLOADER_APP_ROLLBACK_ENABLE is not set
# CONFIG_BOOTLOADER_SKIP_VALIDATE_IN_DEEP_SLEEP is not set
# CONFIG_BOOTLOADER_SKIP_VALIDATE_ON_POWER_ON is not set
# CONFIG_BOOTLOADER_SKIP_VALIDATE_ALWAYS is not set
CONFIG_BOOTLOADER_RESERVE_RTC_SIZE=0
# CONFIG_BOOTLOADER_CUSTOM_RESERVE_RTC is not set
# end of Bootloader config
#
# Security features
#
CONFIG_SECURE_BOOT_V2_RSA_SUPPORTED=y
CONFIG_SECURE_BOOT_V2_PREFERRED=y
# CONFIG_SECURE_SIGNED_APPS_NO_SECURE_BOOT is not set
# CONFIG_SECURE_BOOT is not set
# CONFIG_SECURE_FLASH_ENC_ENABLED is not set
CONFIG_SECURE_ROM_DL_MODE_ENABLED=y
# end of Security features
#
# Application manager
#
CONFIG_APP_COMPILE_TIME_DATE=y
# CONFIG_APP_EXCLUDE_PROJECT_VER_VAR is not set
# CONFIG_APP_EXCLUDE_PROJECT_NAME_VAR is not set
# CONFIG_APP_PROJECT_VER_FROM_CONFIG is not set
CONFIG_APP_RETRIEVE_LEN_ELF_SHA=9
# end of Application manager
CONFIG_ESP_ROM_HAS_CRC_LE=y
CONFIG_ESP_ROM_HAS_CRC_BE=y
CONFIG_ESP_ROM_HAS_MZ_CRC32=y
CONFIG_ESP_ROM_HAS_JPEG_DECODE=y
CONFIG_ESP_ROM_UART_CLK_IS_XTAL=y
CONFIG_ESP_ROM_HAS_RETARGETABLE_LOCKING=y
CONFIG_ESP_ROM_USB_OTG_NUM=3
CONFIG_ESP_ROM_USB_SERIAL_DEVICE_NUM=4
CONFIG_ESP_ROM_HAS_ERASE_0_REGION_BUG=y
CONFIG_ESP_ROM_HAS_ENCRYPTED_WRITES_USING_LEGACY_DRV=y
CONFIG_ESP_ROM_GET_CLK_FREQ=y
CONFIG_ESP_ROM_HAS_HAL_WDT=y
CONFIG_ESP_ROM_NEEDS_SWSETUP_WORKAROUND=y
CONFIG_ESP_ROM_HAS_LAYOUT_TABLE=y
CONFIG_ESP_ROM_HAS_SPI_FLASH=y
CONFIG_ESP_ROM_HAS_ETS_PRINTF_BUG=y
CONFIG_ESP_ROM_HAS_NEWLIB=y
CONFIG_ESP_ROM_HAS_NEWLIB_NANO_FORMAT=y
CONFIG_ESP_ROM_HAS_NEWLIB_32BIT_TIME=y
CONFIG_ESP_ROM_NEEDS_SET_CACHE_MMU_SIZE=y
CONFIG_ESP_ROM_RAM_APP_NEEDS_MMU_INIT=y
CONFIG_ESP_ROM_HAS_FLASH_COUNT_PAGES_BUG=y
CONFIG_ESP_ROM_HAS_CACHE_SUSPEND_WAITI_BUG=y
CONFIG_ESP_ROM_HAS_CACHE_WRITEBACK_BUG=y
CONFIG_ESP_ROM_HAS_SW_FLOAT=y
CONFIG_ESP_ROM_HAS_VERSION=y
CONFIG_ESP_ROM_SUPPORT_DEEP_SLEEP_WAKEUP_STUB=y
#
# Boot ROM Behavior
#
CONFIG_BOOT_ROM_LOG_ALWAYS_ON=y
# CONFIG_BOOT_ROM_LOG_ALWAYS_OFF is not set
# CONFIG_BOOT_ROM_LOG_ON_GPIO_HIGH is not set
# CONFIG_BOOT_ROM_LOG_ON_GPIO_LOW is not set
# end of Boot ROM Behavior
#
# Serial flasher config
#
# CONFIG_ESPTOOLPY_NO_STUB is not set
# CONFIG_ESPTOOLPY_OCT_FLASH is not set
CONFIG_ESPTOOLPY_FLASH_MODE_AUTO_DETECT=y
# CONFIG_ESPTOOLPY_FLASHMODE_QIO is not set
# CONFIG_ESPTOOLPY_FLASHMODE_QOUT is not set
CONFIG_ESPTOOLPY_FLASHMODE_DIO=y
# CONFIG_ESPTOOLPY_FLASHMODE_DOUT is not set
CONFIG_ESPTOOLPY_FLASH_SAMPLE_MODE_STR=y
CONFIG_ESPTOOLPY_FLASHMODE="dio"
# CONFIG_ESPTOOLPY_FLASHFREQ_120M is not set
CONFIG_ESPTOOLPY_FLASHFREQ_80M=y
# CONFIG_ESPTOOLPY_FLASHFREQ_40M is not set
# CONFIG_ESPTOOLPY_FLASHFREQ_20M is not set
CONFIG_ESPTOOLPY_FLASHFREQ_80M_DEFAULT=y
CONFIG_ESPTOOLPY_FLASHFREQ="80m"
# CONFIG_ESPTOOLPY_FLASHSIZE_1MB is not set
# CONFIG_ESPTOOLPY_FLASHSIZE_2MB is not set
# CONFIG_ESPTOOLPY_FLASHSIZE_4MB is not set
# CONFIG_ESPTOOLPY_FLASHSIZE_8MB is not set
CONFIG_ESPTOOLPY_FLASHSIZE_16MB=y
# CONFIG_ESPTOOLPY_FLASHSIZE_32MB is not set
# CONFIG_ESPTOOLPY_FLASHSIZE_64MB is not set
# CONFIG_ESPTOOLPY_FLASHSIZE_128MB is not set
CONFIG_ESPTOOLPY_FLASHSIZE="16MB"
# CONFIG_ESPTOOLPY_HEADER_FLASHSIZE_UPDATE is not set
CONFIG_ESPTOOLPY_BEFORE_RESET=y
# CONFIG_ESPTOOLPY_BEFORE_NORESET is not set
CONFIG_ESPTOOLPY_BEFORE="default_reset"
CONFIG_ESPTOOLPY_AFTER_RESET=y
# CONFIG_ESPTOOLPY_AFTER_NORESET is not set
CONFIG_ESPTOOLPY_AFTER="hard_reset"
CONFIG_ESPTOOLPY_MONITOR_BAUD=115200
# end of Serial flasher config
#
# Partition Table
#
# CONFIG_PARTITION_TABLE_SINGLE_APP is not set
CONFIG_PARTITION_TABLE_SINGLE_APP_LARGE=y
# CONFIG_PARTITION_TABLE_TWO_OTA is not set
# CONFIG_PARTITION_TABLE_CUSTOM is not set
CONFIG_PARTITION_TABLE_CUSTOM_FILENAME="partitions.csv"
CONFIG_PARTITION_TABLE_FILENAME="partitions_singleapp_large.csv"
CONFIG_PARTITION_TABLE_OFFSET=0x8000
CONFIG_PARTITION_TABLE_MD5=y
# end of Partition Table
#
# Compiler options
#
CONFIG_COMPILER_OPTIMIZATION_DEBUG=y
# CONFIG_COMPILER_OPTIMIZATION_SIZE is not set
# CONFIG_COMPILER_OPTIMIZATION_PERF is not set
# CONFIG_COMPILER_OPTIMIZATION_NONE is not set
CONFIG_COMPILER_OPTIMIZATION_ASSERTIONS_ENABLE=y
# CONFIG_COMPILER_OPTIMIZATION_ASSERTIONS_SILENT is not set
# CONFIG_COMPILER_OPTIMIZATION_ASSERTIONS_DISABLE is not set
CONFIG_COMPILER_FLOAT_LIB_FROM_GCCLIB=y
CONFIG_COMPILER_OPTIMIZATION_ASSERTION_LEVEL=2
# CONFIG_COMPILER_OPTIMIZATION_CHECKS_SILENT is not set
CONFIG_COMPILER_HIDE_PATHS_MACROS=y
# CONFIG_COMPILER_CXX_EXCEPTIONS is not set
# CONFIG_COMPILER_CXX_RTTI is not set
CONFIG_COMPILER_STACK_CHECK_MODE_NONE=y
# CONFIG_COMPILER_STACK_CHECK_MODE_NORM is not set
# CONFIG_COMPILER_STACK_CHECK_MODE_STRONG is not set
# CONFIG_COMPILER_STACK_CHECK_MODE_ALL is not set
# CONFIG_COMPILER_WARN_WRITE_STRINGS is not set
# CONFIG_COMPILER_DISABLE_GCC12_WARNINGS is not set
# CONFIG_COMPILER_DISABLE_GCC13_WARNINGS is not set
# CONFIG_COMPILER_DUMP_RTL_FILES is not set
CONFIG_COMPILER_RT_LIB_GCCLIB=y
CONFIG_COMPILER_RT_LIB_NAME="gcc"
# CONFIG_COMPILER_ORPHAN_SECTIONS_WARNING is not set
CONFIG_COMPILER_ORPHAN_SECTIONS_PLACE=y
# end of Compiler options
#
# Component config
#
#
# Application Level Tracing
#
# CONFIG_APPTRACE_DEST_JTAG is not set
CONFIG_APPTRACE_DEST_NONE=y
# CONFIG_APPTRACE_DEST_UART1 is not set
# CONFIG_APPTRACE_DEST_UART2 is not set
# CONFIG_APPTRACE_DEST_USB_CDC is not set
CONFIG_APPTRACE_DEST_UART_NONE=y
CONFIG_APPTRACE_UART_TASK_PRIO=1
CONFIG_APPTRACE_LOCK_ENABLE=y
# end of Application Level Tracing
#
# Bluetooth
#
# CONFIG_BT_ENABLED is not set
CONFIG_BT_ALARM_MAX_NUM=50
# end of Bluetooth
#
# Console Library
#
# CONFIG_CONSOLE_SORTED_HELP is not set
# end of Console Library
#
# Driver Configurations
#
#
# TWAI Configuration
#
# CONFIG_TWAI_ISR_IN_IRAM is not set
CONFIG_TWAI_ERRATA_FIX_LISTEN_ONLY_DOM=y
# end of TWAI Configuration
#
# Legacy ADC Driver Configuration
#
# CONFIG_ADC_SUPPRESS_DEPRECATE_WARN is not set
#
# Legacy ADC Calibration Configuration
#
# CONFIG_ADC_CALI_SUPPRESS_DEPRECATE_WARN is not set
# end of Legacy ADC Calibration Configuration
# end of Legacy ADC Driver Configuration
#
# Legacy MCPWM Driver Configurations
#
# CONFIG_MCPWM_SUPPRESS_DEPRECATE_WARN is not set
# end of Legacy MCPWM Driver Configurations
#
# Legacy Timer Group Driver Configurations
#
# CONFIG_GPTIMER_SUPPRESS_DEPRECATE_WARN is not set
# end of Legacy Timer Group Driver Configurations
#
# Legacy RMT Driver Configurations
#
# CONFIG_RMT_SUPPRESS_DEPRECATE_WARN is not set
# end of Legacy RMT Driver Configurations
#
# Legacy I2S Driver Configurations
#
# CONFIG_I2S_SUPPRESS_DEPRECATE_WARN is not set
# end of Legacy I2S Driver Configurations
#
# Legacy PCNT Driver Configurations
#
# CONFIG_PCNT_SUPPRESS_DEPRECATE_WARN is not set
# end of Legacy PCNT Driver Configurations
#
# Legacy SDM Driver Configurations
#
# CONFIG_SDM_SUPPRESS_DEPRECATE_WARN is not set
# end of Legacy SDM Driver Configurations
#
# Legacy Temperature Sensor Driver Configurations
#
# CONFIG_TEMP_SENSOR_SUPPRESS_DEPRECATE_WARN is not set
# end of Legacy Temperature Sensor Driver Configurations
# end of Driver Configurations
#
# eFuse Bit Manager
#
# CONFIG_EFUSE_CUSTOM_TABLE is not set
# CONFIG_EFUSE_VIRTUAL is not set
CONFIG_EFUSE_MAX_BLK_LEN=256
# end of eFuse Bit Manager
#
# ESP-TLS
#
CONFIG_ESP_TLS_USING_MBEDTLS=y
CONFIG_ESP_TLS_USE_DS_PERIPHERAL=y
# CONFIG_ESP_TLS_CLIENT_SESSION_TICKETS is not set
# CONFIG_ESP_TLS_SERVER_SESSION_TICKETS is not set
# CONFIG_ESP_TLS_SERVER_CERT_SELECT_HOOK is not set
# CONFIG_ESP_TLS_SERVER_MIN_AUTH_MODE_OPTIONAL is not set
# CONFIG_ESP_TLS_PSK_VERIFICATION is not set
# CONFIG_ESP_TLS_INSECURE is not set
# end of ESP-TLS
#
# ADC and ADC Calibration
#
# CONFIG_ADC_ONESHOT_CTRL_FUNC_IN_IRAM is not set
# CONFIG_ADC_CONTINUOUS_ISR_IRAM_SAFE is not set
# CONFIG_ADC_CONTINUOUS_FORCE_USE_ADC2_ON_C3_S3 is not set
# CONFIG_ADC_ENABLE_DEBUG_LOG is not set
# end of ADC and ADC Calibration
#
# Wireless Coexistence
#
CONFIG_ESP_COEX_ENABLED=y
# CONFIG_ESP_COEX_EXTERNAL_COEXIST_ENABLE is not set
# end of Wireless Coexistence
#
# Common ESP-related
#
CONFIG_ESP_ERR_TO_NAME_LOOKUP=y
# end of Common ESP-related
#
# ESP-Driver:GPIO Configurations
#
# CONFIG_GPIO_CTRL_FUNC_IN_IRAM is not set
# end of ESP-Driver:GPIO Configurations
#
# ESP-Driver:GPTimer Configurations
#
CONFIG_GPTIMER_ISR_HANDLER_IN_IRAM=y
# CONFIG_GPTIMER_CTRL_FUNC_IN_IRAM is not set
# CONFIG_GPTIMER_ISR_IRAM_SAFE is not set
# CONFIG_GPTIMER_ENABLE_DEBUG_LOG is not set
# end of ESP-Driver:GPTimer Configurations
#
# ESP-Driver:I2C Configurations
#
# CONFIG_I2C_ISR_IRAM_SAFE is not set
# CONFIG_I2C_ENABLE_DEBUG_LOG is not set
# end of ESP-Driver:I2C Configurations
#
# ESP-Driver:I2S Configurations
#
# CONFIG_I2S_ISR_IRAM_SAFE is not set
# CONFIG_I2S_ENABLE_DEBUG_LOG is not set
# end of ESP-Driver:I2S Configurations
#
# ESP-Driver:LEDC Configurations
#
# CONFIG_LEDC_CTRL_FUNC_IN_IRAM is not set
# end of ESP-Driver:LEDC Configurations
#
# ESP-Driver:MCPWM Configurations
#
# CONFIG_MCPWM_ISR_IRAM_SAFE is not set
# CONFIG_MCPWM_CTRL_FUNC_IN_IRAM is not set
# CONFIG_MCPWM_ENABLE_DEBUG_LOG is not set
# end of ESP-Driver:MCPWM Configurations
#
# ESP-Driver:PCNT Configurations
#
# CONFIG_PCNT_CTRL_FUNC_IN_IRAM is not set
# CONFIG_PCNT_ISR_IRAM_SAFE is not set
# CONFIG_PCNT_ENABLE_DEBUG_LOG is not set
# end of ESP-Driver:PCNT Configurations
#
# ESP-Driver:RMT Configurations
#
# CONFIG_RMT_ISR_IRAM_SAFE is not set
# CONFIG_RMT_RECV_FUNC_IN_IRAM is not set
# CONFIG_RMT_ENABLE_DEBUG_LOG is not set
# end of ESP-Driver:RMT Configurations
#
# ESP-Driver:Sigma Delta Modulator Configurations
#
# CONFIG_SDM_CTRL_FUNC_IN_IRAM is not set
# CONFIG_SDM_ENABLE_DEBUG_LOG is not set
# end of ESP-Driver:Sigma Delta Modulator Configurations
#
# ESP-Driver:SPI Configurations
#
# CONFIG_SPI_MASTER_IN_IRAM is not set
CONFIG_SPI_MASTER_ISR_IN_IRAM=y
# CONFIG_SPI_SLAVE_IN_IRAM is not set
CONFIG_SPI_SLAVE_ISR_IN_IRAM=y
# end of ESP-Driver:SPI Configurations
#
# ESP-Driver:Touch Sensor Configurations
#
# CONFIG_TOUCH_CTRL_FUNC_IN_IRAM is not set
# CONFIG_TOUCH_ISR_IRAM_SAFE is not set
# CONFIG_TOUCH_ENABLE_DEBUG_LOG is not set
# end of ESP-Driver:Touch Sensor Configurations
#
# ESP-Driver:Temperature Sensor Configurations
#
# CONFIG_TEMP_SENSOR_ENABLE_DEBUG_LOG is not set
# end of ESP-Driver:Temperature Sensor Configurations
#
# ESP-Driver:UART Configurations
#
# CONFIG_UART_ISR_IN_IRAM is not set
# end of ESP-Driver:UART Configurations
#
# ESP-Driver:USB Serial/JTAG Configuration
#
CONFIG_USJ_ENABLE_USB_SERIAL_JTAG=y
# end of ESP-Driver:USB Serial/JTAG Configuration
#
# Ethernet
#
CONFIG_ETH_ENABLED=y
CONFIG_ETH_USE_SPI_ETHERNET=y
# CONFIG_ETH_SPI_ETHERNET_DM9051 is not set
# CONFIG_ETH_SPI_ETHERNET_W5500 is not set
# CONFIG_ETH_SPI_ETHERNET_KSZ8851SNL is not set
# CONFIG_ETH_USE_OPENETH is not set
# CONFIG_ETH_TRANSMIT_MUTEX is not set
# end of Ethernet
#
# Event Loop Library
#
# CONFIG_ESP_EVENT_LOOP_PROFILING is not set
CONFIG_ESP_EVENT_POST_FROM_ISR=y
CONFIG_ESP_EVENT_POST_FROM_IRAM_ISR=y
# end of Event Loop Library
#
# GDB Stub
#
CONFIG_ESP_GDBSTUB_ENABLED=y
# CONFIG_ESP_SYSTEM_GDBSTUB_RUNTIME is not set
CONFIG_ESP_GDBSTUB_SUPPORT_TASKS=y
CONFIG_ESP_GDBSTUB_MAX_TASKS=32
# end of GDB Stub
#
# ESP HTTP client
#
CONFIG_ESP_HTTP_CLIENT_ENABLE_HTTPS=y
# CONFIG_ESP_HTTP_CLIENT_ENABLE_BASIC_AUTH is not set
# CONFIG_ESP_HTTP_CLIENT_ENABLE_DIGEST_AUTH is not set
# CONFIG_ESP_HTTP_CLIENT_ENABLE_CUSTOM_TRANSPORT is not set
# end of ESP HTTP client
#
# HTTP Server
#
CONFIG_HTTPD_MAX_REQ_HDR_LEN=512
CONFIG_HTTPD_MAX_URI_LEN=512
CONFIG_HTTPD_ERR_RESP_NO_DELAY=y
CONFIG_HTTPD_PURGE_BUF_LEN=32
# CONFIG_HTTPD_LOG_PURGE_DATA is not set
# CONFIG_HTTPD_WS_SUPPORT is not set
# CONFIG_HTTPD_QUEUE_WORK_BLOCKING is not set
# end of HTTP Server
#
# ESP HTTPS OTA
#
# CONFIG_ESP_HTTPS_OTA_DECRYPT_CB is not set
# CONFIG_ESP_HTTPS_OTA_ALLOW_HTTP is not set
# end of ESP HTTPS OTA
#
# ESP HTTPS server
#
# CONFIG_ESP_HTTPS_SERVER_ENABLE is not set
# end of ESP HTTPS server
#
# Hardware Settings
#
#
# Chip revision
#
CONFIG_ESP32S3_REV_MIN_0=y
# CONFIG_ESP32S3_REV_MIN_1 is not set
# CONFIG_ESP32S3_REV_MIN_2 is not set
CONFIG_ESP32S3_REV_MIN_FULL=0
CONFIG_ESP_REV_MIN_FULL=0
#
# Maximum Supported ESP32-S3 Revision (Rev v0.99)
#
CONFIG_ESP32S3_REV_MAX_FULL=99
CONFIG_ESP_REV_MAX_FULL=99
# end of Chip revision
#
# MAC Config
#
CONFIG_ESP_MAC_ADDR_UNIVERSE_WIFI_STA=y
CONFIG_ESP_MAC_ADDR_UNIVERSE_WIFI_AP=y
CONFIG_ESP_MAC_ADDR_UNIVERSE_BT=y
CONFIG_ESP_MAC_ADDR_UNIVERSE_ETH=y
CONFIG_ESP_MAC_UNIVERSAL_MAC_ADDRESSES_FOUR=y
CONFIG_ESP_MAC_UNIVERSAL_MAC_ADDRESSES=4
# CONFIG_ESP32S3_UNIVERSAL_MAC_ADDRESSES_TWO is not set
CONFIG_ESP32S3_UNIVERSAL_MAC_ADDRESSES_FOUR=y
CONFIG_ESP32S3_UNIVERSAL_MAC_ADDRESSES=4
# CONFIG_ESP_MAC_USE_CUSTOM_MAC_AS_BASE_MAC is not set
# end of MAC Config
#
# Sleep Config
#
CONFIG_ESP_SLEEP_FLASH_LEAKAGE_WORKAROUND=y
CONFIG_ESP_SLEEP_PSRAM_LEAKAGE_WORKAROUND=y
CONFIG_ESP_SLEEP_MSPI_NEED_ALL_IO_PU=y
CONFIG_ESP_SLEEP_RTC_BUS_ISO_WORKAROUND=y
CONFIG_ESP_SLEEP_GPIO_RESET_WORKAROUND=y
CONFIG_ESP_SLEEP_WAIT_FLASH_READY_EXTRA_DELAY=2000
# CONFIG_ESP_SLEEP_CACHE_SAFE_ASSERTION is not set
# CONFIG_ESP_SLEEP_DEBUG is not set
CONFIG_ESP_SLEEP_GPIO_ENABLE_INTERNAL_RESISTORS=y
# end of Sleep Config
#
# RTC Clock Config
#
CONFIG_RTC_CLK_SRC_INT_RC=y
# CONFIG_RTC_CLK_SRC_EXT_CRYS is not set
# CONFIG_RTC_CLK_SRC_EXT_OSC is not set
# CONFIG_RTC_CLK_SRC_INT_8MD256 is not set
CONFIG_RTC_CLK_CAL_CYCLES=1024
# end of RTC Clock Config
#
# Peripheral Control
#
CONFIG_PERIPH_CTRL_FUNC_IN_IRAM=y
# end of Peripheral Control
#
# GDMA Configurations
#
CONFIG_GDMA_CTRL_FUNC_IN_IRAM=y
# CONFIG_GDMA_ISR_IRAM_SAFE is not set
# CONFIG_GDMA_ENABLE_DEBUG_LOG is not set
# end of GDMA Configurations
#
# Main XTAL Config
#
CONFIG_XTAL_FREQ_40=y
CONFIG_XTAL_FREQ=40
# end of Main XTAL Config
CONFIG_ESP_SPI_BUS_LOCK_ISR_FUNCS_IN_IRAM=y
# end of Hardware Settings
#
# LCD and Touch Panel
#
#
# LCD Touch Drivers are maintained in the IDF Component Registry
#
#
# LCD Peripheral Configuration
#
CONFIG_LCD_PANEL_IO_FORMAT_BUF_SIZE=32
# CONFIG_LCD_ENABLE_DEBUG_LOG is not set
# CONFIG_LCD_RGB_ISR_IRAM_SAFE is not set
# CONFIG_LCD_RGB_RESTART_IN_VSYNC is not set
# end of LCD Peripheral Configuration
# end of LCD and Touch Panel
#
# ESP NETIF Adapter
#
CONFIG_ESP_NETIF_IP_LOST_TIMER_INTERVAL=120
CONFIG_ESP_NETIF_TCPIP_LWIP=y
# CONFIG_ESP_NETIF_LOOPBACK is not set
CONFIG_ESP_NETIF_USES_TCPIP_WITH_BSD_API=y
# CONFIG_ESP_NETIF_RECEIVE_REPORT_ERRORS is not set
# CONFIG_ESP_NETIF_L2_TAP is not set
# CONFIG_ESP_NETIF_BRIDGE_EN is not set
# end of ESP NETIF Adapter
#
# Partition API Configuration
#
# end of Partition API Configuration
#
# PHY
#
CONFIG_ESP_PHY_ENABLED=y
CONFIG_ESP_PHY_CALIBRATION_AND_DATA_STORAGE=y
# CONFIG_ESP_PHY_INIT_DATA_IN_PARTITION is not set
CONFIG_ESP_PHY_MAX_WIFI_TX_POWER=20
CONFIG_ESP_PHY_MAX_TX_POWER=20
# CONFIG_ESP_PHY_REDUCE_TX_POWER is not set
CONFIG_ESP_PHY_ENABLE_USB=y
# CONFIG_ESP_PHY_ENABLE_CERT_TEST is not set
CONFIG_ESP_PHY_RF_CAL_PARTIAL=y
# CONFIG_ESP_PHY_RF_CAL_NONE is not set
# CONFIG_ESP_PHY_RF_CAL_FULL is not set
CONFIG_ESP_PHY_CALIBRATION_MODE=0
# CONFIG_ESP_PHY_PLL_TRACK_DEBUG is not set
# end of PHY
#
# Power Management
#
# CONFIG_PM_ENABLE is not set
CONFIG_PM_POWER_DOWN_CPU_IN_LIGHT_SLEEP=y
CONFIG_PM_RESTORE_CACHE_TAGMEM_AFTER_LIGHT_SLEEP=y
# end of Power Management
#
# ESP PSRAM
#
CONFIG_SPIRAM=y
#
# SPI RAM config
#
# CONFIG_SPIRAM_MODE_QUAD is not set
CONFIG_SPIRAM_MODE_OCT=y
CONFIG_SPIRAM_TYPE_AUTO=y
# CONFIG_SPIRAM_TYPE_ESPPSRAM64 is not set
CONFIG_SPIRAM_ALLOW_STACK_EXTERNAL_MEMORY=y
CONFIG_SPIRAM_CLK_IO=30
CONFIG_SPIRAM_CS_IO=26
# CONFIG_SPIRAM_XIP_FROM_PSRAM is not set
# CONFIG_SPIRAM_FETCH_INSTRUCTIONS is not set
# CONFIG_SPIRAM_RODATA is not set
# CONFIG_SPIRAM_SPEED_80M is not set
CONFIG_SPIRAM_SPEED_40M=y
CONFIG_SPIRAM_SPEED=40
# CONFIG_SPIRAM_ECC_ENABLE is not set
CONFIG_SPIRAM_BOOT_INIT=y
# CONFIG_SPIRAM_IGNORE_NOTFOUND is not set
# CONFIG_SPIRAM_USE_MEMMAP is not set
# CONFIG_SPIRAM_USE_CAPS_ALLOC is not set
CONFIG_SPIRAM_USE_MALLOC=y
CONFIG_SPIRAM_MEMTEST=y
CONFIG_SPIRAM_MALLOC_ALWAYSINTERNAL=16384
# CONFIG_SPIRAM_TRY_ALLOCATE_WIFI_LWIP is not set
CONFIG_SPIRAM_MALLOC_RESERVE_INTERNAL=32768
# CONFIG_SPIRAM_ALLOW_BSS_SEG_EXTERNAL_MEMORY is not set
# end of SPI RAM config
# end of ESP PSRAM
#
# ESP Ringbuf
#
# CONFIG_RINGBUF_PLACE_FUNCTIONS_INTO_FLASH is not set
# end of ESP Ringbuf
#
# ESP System Settings
#
# CONFIG_ESP_DEFAULT_CPU_FREQ_MHZ_80 is not set
# CONFIG_ESP_DEFAULT_CPU_FREQ_MHZ_160 is not set
CONFIG_ESP_DEFAULT_CPU_FREQ_MHZ_240=y
CONFIG_ESP_DEFAULT_CPU_FREQ_MHZ=240
#
# Cache config
#
CONFIG_ESP32S3_INSTRUCTION_CACHE_16KB=y
# CONFIG_ESP32S3_INSTRUCTION_CACHE_32KB is not set
CONFIG_ESP32S3_INSTRUCTION_CACHE_SIZE=0x4000
# CONFIG_ESP32S3_INSTRUCTION_CACHE_4WAYS is not set
CONFIG_ESP32S3_INSTRUCTION_CACHE_8WAYS=y
CONFIG_ESP32S3_ICACHE_ASSOCIATED_WAYS=8
# CONFIG_ESP32S3_INSTRUCTION_CACHE_LINE_16B is not set
CONFIG_ESP32S3_INSTRUCTION_CACHE_LINE_32B=y
CONFIG_ESP32S3_INSTRUCTION_CACHE_LINE_SIZE=32
# CONFIG_ESP32S3_DATA_CACHE_16KB is not set
CONFIG_ESP32S3_DATA_CACHE_32KB=y
# CONFIG_ESP32S3_DATA_CACHE_64KB is not set
CONFIG_ESP32S3_DATA_CACHE_SIZE=0x8000
# CONFIG_ESP32S3_DATA_CACHE_4WAYS is not set
CONFIG_ESP32S3_DATA_CACHE_8WAYS=y
CONFIG_ESP32S3_DCACHE_ASSOCIATED_WAYS=8
# CONFIG_ESP32S3_DATA_CACHE_LINE_16B is not set
# CONFIG_ESP32S3_DATA_CACHE_LINE_32B is not set
CONFIG_ESP32S3_DATA_CACHE_LINE_64B=y
CONFIG_ESP32S3_DATA_CACHE_LINE_SIZE=64
# end of Cache config
#
# Memory
#
# CONFIG_ESP32S3_RTCDATA_IN_FAST_MEM is not set
# CONFIG_ESP32S3_USE_FIXED_STATIC_RAM_SIZE is not set
# end of Memory
#
# Trace memory
#
# CONFIG_ESP32S3_TRAX is not set
CONFIG_ESP32S3_TRACEMEM_RESERVE_DRAM=0x0
# end of Trace memory
# CONFIG_ESP_SYSTEM_PANIC_PRINT_HALT is not set
CONFIG_ESP_SYSTEM_PANIC_PRINT_REBOOT=y
# CONFIG_ESP_SYSTEM_PANIC_SILENT_REBOOT is not set
# CONFIG_ESP_SYSTEM_PANIC_GDBSTUB is not set
CONFIG_ESP_SYSTEM_PANIC_REBOOT_DELAY_SECONDS=0
CONFIG_ESP_SYSTEM_RTC_FAST_MEM_AS_HEAP_DEPCHECK=y
CONFIG_ESP_SYSTEM_ALLOW_RTC_FAST_MEM_AS_HEAP=y
#
# Memory protection
#
CONFIG_ESP_SYSTEM_MEMPROT_FEATURE=y
CONFIG_ESP_SYSTEM_MEMPROT_FEATURE_LOCK=y
# end of Memory protection
CONFIG_ESP_SYSTEM_EVENT_QUEUE_SIZE=32
CONFIG_ESP_SYSTEM_EVENT_TASK_STACK_SIZE=2304
CONFIG_ESP_MAIN_TASK_STACK_SIZE=10240
CONFIG_ESP_MAIN_TASK_AFFINITY_CPU0=y
# CONFIG_ESP_MAIN_TASK_AFFINITY_CPU1 is not set
# CONFIG_ESP_MAIN_TASK_AFFINITY_NO_AFFINITY is not set
CONFIG_ESP_MAIN_TASK_AFFINITY=0x0
CONFIG_ESP_MINIMAL_SHARED_STACK_SIZE=2048
CONFIG_ESP_CONSOLE_UART_DEFAULT=y
# CONFIG_ESP_CONSOLE_USB_CDC is not set
# CONFIG_ESP_CONSOLE_USB_SERIAL_JTAG is not set
# CONFIG_ESP_CONSOLE_UART_CUSTOM is not set
# CONFIG_ESP_CONSOLE_NONE is not set
# CONFIG_ESP_CONSOLE_SECONDARY_NONE is not set
CONFIG_ESP_CONSOLE_SECONDARY_USB_SERIAL_JTAG=y
CONFIG_ESP_CONSOLE_USB_SERIAL_JTAG_ENABLED=y
CONFIG_ESP_CONSOLE_UART=y
CONFIG_ESP_CONSOLE_UART_NUM=0
CONFIG_ESP_CONSOLE_ROM_SERIAL_PORT_NUM=0
CONFIG_ESP_CONSOLE_UART_BAUDRATE=115200
CONFIG_ESP_INT_WDT=y
CONFIG_ESP_INT_WDT_TIMEOUT_MS=300
CONFIG_ESP_INT_WDT_CHECK_CPU1=y
CONFIG_ESP_TASK_WDT_EN=y
CONFIG_ESP_TASK_WDT_INIT=y
# CONFIG_ESP_TASK_WDT_PANIC is not set
CONFIG_ESP_TASK_WDT_TIMEOUT_S=5
CONFIG_ESP_TASK_WDT_CHECK_IDLE_TASK_CPU0=y
CONFIG_ESP_TASK_WDT_CHECK_IDLE_TASK_CPU1=y
# CONFIG_ESP_PANIC_HANDLER_IRAM is not set
# CONFIG_ESP_DEBUG_STUBS_ENABLE is not set
CONFIG_ESP_DEBUG_OCDAWARE=y
CONFIG_ESP_SYSTEM_CHECK_INT_LEVEL_4=y
#
# Brownout Detector
#
CONFIG_ESP_BROWNOUT_DET=y
CONFIG_ESP_BROWNOUT_DET_LVL_SEL_7=y
# CONFIG_ESP_BROWNOUT_DET_LVL_SEL_6 is not set
# CONFIG_ESP_BROWNOUT_DET_LVL_SEL_5 is not set
# CONFIG_ESP_BROWNOUT_DET_LVL_SEL_4 is not set
# CONFIG_ESP_BROWNOUT_DET_LVL_SEL_3 is not set
# CONFIG_ESP_BROWNOUT_DET_LVL_SEL_2 is not set
# CONFIG_ESP_BROWNOUT_DET_LVL_SEL_1 is not set
CONFIG_ESP_BROWNOUT_DET_LVL=7
# end of Brownout Detector
CONFIG_ESP_SYSTEM_BROWNOUT_INTR=y
CONFIG_ESP_SYSTEM_BBPLL_RECALIB=y
# end of ESP System Settings
#
# IPC (Inter-Processor Call)
#
CONFIG_ESP_IPC_TASK_STACK_SIZE=1280
CONFIG_ESP_IPC_USES_CALLERS_PRIORITY=y
CONFIG_ESP_IPC_ISR_ENABLE=y
# end of IPC (Inter-Processor Call)
#
# ESP Timer (High Resolution Timer)
#
# CONFIG_ESP_TIMER_PROFILING is not set
CONFIG_ESP_TIME_FUNCS_USE_RTC_TIMER=y
CONFIG_ESP_TIME_FUNCS_USE_ESP_TIMER=y
CONFIG_ESP_TIMER_TASK_STACK_SIZE=3584
CONFIG_ESP_TIMER_INTERRUPT_LEVEL=1
# CONFIG_ESP_TIMER_SHOW_EXPERIMENTAL is not set
CONFIG_ESP_TIMER_TASK_AFFINITY=0x0
CONFIG_ESP_TIMER_TASK_AFFINITY_CPU0=y
CONFIG_ESP_TIMER_ISR_AFFINITY_CPU0=y
# CONFIG_ESP_TIMER_SUPPORTS_ISR_DISPATCH_METHOD is not set
CONFIG_ESP_TIMER_IMPL_SYSTIMER=y
# end of ESP Timer (High Resolution Timer)
#
# Wi-Fi
#
CONFIG_ESP_WIFI_ENABLED=y
CONFIG_ESP_WIFI_STATIC_RX_BUFFER_NUM=10
CONFIG_ESP_WIFI_DYNAMIC_RX_BUFFER_NUM=32
CONFIG_ESP_WIFI_STATIC_TX_BUFFER=y
CONFIG_ESP_WIFI_TX_BUFFER_TYPE=0
CONFIG_ESP_WIFI_STATIC_TX_BUFFER_NUM=16
CONFIG_ESP_WIFI_CACHE_TX_BUFFER_NUM=32
CONFIG_ESP_WIFI_STATIC_RX_MGMT_BUFFER=y
# CONFIG_ESP_WIFI_DYNAMIC_RX_MGMT_BUFFER is not set
CONFIG_ESP_WIFI_DYNAMIC_RX_MGMT_BUF=0
CONFIG_ESP_WIFI_RX_MGMT_BUF_NUM_DEF=5
# CONFIG_ESP_WIFI_CSI_ENABLED is not set
CONFIG_ESP_WIFI_AMPDU_TX_ENABLED=y
CONFIG_ESP_WIFI_TX_BA_WIN=6
CONFIG_ESP_WIFI_AMPDU_RX_ENABLED=y
CONFIG_ESP_WIFI_RX_BA_WIN=6
# CONFIG_ESP_WIFI_AMSDU_TX_ENABLED is not set
CONFIG_ESP_WIFI_NVS_ENABLED=y
CONFIG_ESP_WIFI_TASK_PINNED_TO_CORE_0=y
# CONFIG_ESP_WIFI_TASK_PINNED_TO_CORE_1 is not set
CONFIG_ESP_WIFI_SOFTAP_BEACON_MAX_LEN=752
CONFIG_ESP_WIFI_MGMT_SBUF_NUM=32
CONFIG_ESP_WIFI_IRAM_OPT=y
# CONFIG_ESP_WIFI_EXTRA_IRAM_OPT is not set
CONFIG_ESP_WIFI_RX_IRAM_OPT=y
CONFIG_ESP_WIFI_ENABLE_WPA3_SAE=y
CONFIG_ESP_WIFI_ENABLE_SAE_PK=y
CONFIG_ESP_WIFI_SOFTAP_SAE_SUPPORT=y
CONFIG_ESP_WIFI_ENABLE_WPA3_OWE_STA=y
# CONFIG_ESP_WIFI_SLP_IRAM_OPT is not set
CONFIG_ESP_WIFI_SLP_DEFAULT_MIN_ACTIVE_TIME=50
CONFIG_ESP_WIFI_SLP_DEFAULT_MAX_ACTIVE_TIME=10
CONFIG_ESP_WIFI_SLP_DEFAULT_WAIT_BROADCAST_DATA_TIME=15
# CONFIG_ESP_WIFI_FTM_ENABLE is not set
CONFIG_ESP_WIFI_STA_DISCONNECTED_PM_ENABLE=y
# CONFIG_ESP_WIFI_GCMP_SUPPORT is not set
CONFIG_ESP_WIFI_GMAC_SUPPORT=y
CONFIG_ESP_WIFI_SOFTAP_SUPPORT=y
# CONFIG_ESP_WIFI_SLP_BEACON_LOST_OPT is not set
CONFIG_ESP_WIFI_ESPNOW_MAX_ENCRYPT_NUM=7
CONFIG_ESP_WIFI_MBEDTLS_CRYPTO=y
CONFIG_ESP_WIFI_MBEDTLS_TLS_CLIENT=y
# CONFIG_ESP_WIFI_WAPI_PSK is not set
# CONFIG_ESP_WIFI_SUITE_B_192 is not set
# CONFIG_ESP_WIFI_11KV_SUPPORT is not set
# CONFIG_ESP_WIFI_MBO_SUPPORT is not set
# CONFIG_ESP_WIFI_DPP_SUPPORT is not set
# CONFIG_ESP_WIFI_11R_SUPPORT is not set
# CONFIG_ESP_WIFI_WPS_SOFTAP_REGISTRAR is not set
#
# WPS Configuration Options
#
# CONFIG_ESP_WIFI_WPS_STRICT is not set
# CONFIG_ESP_WIFI_WPS_PASSPHRASE is not set
# end of WPS Configuration Options
# CONFIG_ESP_WIFI_DEBUG_PRINT is not set
# CONFIG_ESP_WIFI_TESTING_OPTIONS is not set
CONFIG_ESP_WIFI_ENTERPRISE_SUPPORT=y
# CONFIG_ESP_WIFI_ENT_FREE_DYNAMIC_BUFFER is not set
# end of Wi-Fi
#
# Core dump
#
# CONFIG_ESP_COREDUMP_ENABLE_TO_FLASH is not set
# CONFIG_ESP_COREDUMP_ENABLE_TO_UART is not set
CONFIG_ESP_COREDUMP_ENABLE_TO_NONE=y
# end of Core dump
#
# FAT Filesystem support
#
CONFIG_FATFS_VOLUME_COUNT=2
CONFIG_FATFS_LFN_NONE=y
# CONFIG_FATFS_LFN_HEAP is not set
# CONFIG_FATFS_LFN_STACK is not set
# CONFIG_FATFS_SECTOR_512 is not set
CONFIG_FATFS_SECTOR_4096=y
# CONFIG_FATFS_CODEPAGE_DYNAMIC is not set
CONFIG_FATFS_CODEPAGE_437=y
# CONFIG_FATFS_CODEPAGE_720 is not set
# CONFIG_FATFS_CODEPAGE_737 is not set
# CONFIG_FATFS_CODEPAGE_771 is not set
# CONFIG_FATFS_CODEPAGE_775 is not set
# CONFIG_FATFS_CODEPAGE_850 is not set
# CONFIG_FATFS_CODEPAGE_852 is not set
# CONFIG_FATFS_CODEPAGE_855 is not set
# CONFIG_FATFS_CODEPAGE_857 is not set
# CONFIG_FATFS_CODEPAGE_860 is not set
# CONFIG_FATFS_CODEPAGE_861 is not set
# CONFIG_FATFS_CODEPAGE_862 is not set
# CONFIG_FATFS_CODEPAGE_863 is not set
# CONFIG_FATFS_CODEPAGE_864 is not set
# CONFIG_FATFS_CODEPAGE_865 is not set
# CONFIG_FATFS_CODEPAGE_866 is not set
# CONFIG_FATFS_CODEPAGE_869 is not set
# CONFIG_FATFS_CODEPAGE_932 is not set
# CONFIG_FATFS_CODEPAGE_936 is not set
# CONFIG_FATFS_CODEPAGE_949 is not set
# CONFIG_FATFS_CODEPAGE_950 is not set
CONFIG_FATFS_CODEPAGE=437
CONFIG_FATFS_FS_LOCK=0
CONFIG_FATFS_TIMEOUT_MS=10000
CONFIG_FATFS_PER_FILE_CACHE=y
CONFIG_FATFS_ALLOC_PREFER_EXTRAM=y
# CONFIG_FATFS_USE_FASTSEEK is not set
CONFIG_FATFS_VFS_FSTAT_BLKSIZE=0
# CONFIG_FATFS_IMMEDIATE_FSYNC is not set
# CONFIG_FATFS_USE_LABEL is not set
CONFIG_FATFS_LINK_LOCK=y
# end of FAT Filesystem support
#
# FreeRTOS
#
#
# Kernel
#
# CONFIG_FREERTOS_SMP is not set
# CONFIG_FREERTOS_UNICORE is not set
CONFIG_FREERTOS_HZ=100
# CONFIG_FREERTOS_CHECK_STACKOVERFLOW_NONE is not set
# CONFIG_FREERTOS_CHECK_STACKOVERFLOW_PTRVAL is not set
CONFIG_FREERTOS_CHECK_STACKOVERFLOW_CANARY=y
CONFIG_FREERTOS_THREAD_LOCAL_STORAGE_POINTERS=1
CONFIG_FREERTOS_IDLE_TASK_STACKSIZE=1536
# CONFIG_FREERTOS_USE_IDLE_HOOK is not set
# CONFIG_FREERTOS_USE_TICK_HOOK is not set
CONFIG_FREERTOS_MAX_TASK_NAME_LEN=16
# CONFIG_FREERTOS_ENABLE_BACKWARD_COMPATIBILITY is not set
CONFIG_FREERTOS_TIMER_SERVICE_TASK_NAME="Tmr Svc"
# CONFIG_FREERTOS_TIMER_TASK_AFFINITY_CPU0 is not set
# CONFIG_FREERTOS_TIMER_TASK_AFFINITY_CPU1 is not set
CONFIG_FREERTOS_TIMER_TASK_NO_AFFINITY=y
CONFIG_FREERTOS_TIMER_SERVICE_TASK_CORE_AFFINITY=0x7FFFFFFF
CONFIG_FREERTOS_TIMER_TASK_PRIORITY=1
CONFIG_FREERTOS_TIMER_TASK_STACK_DEPTH=2048
CONFIG_FREERTOS_TIMER_QUEUE_LENGTH=10
CONFIG_FREERTOS_QUEUE_REGISTRY_SIZE=0
CONFIG_FREERTOS_TASK_NOTIFICATION_ARRAY_ENTRIES=1
# CONFIG_FREERTOS_USE_TRACE_FACILITY is not set
# CONFIG_FREERTOS_USE_LIST_DATA_INTEGRITY_CHECK_BYTES is not set
# CONFIG_FREERTOS_GENERATE_RUN_TIME_STATS is not set
# CONFIG_FREERTOS_USE_APPLICATION_TASK_TAG is not set
# end of Kernel
#
# Port
#
CONFIG_FREERTOS_TASK_FUNCTION_WRAPPER=y
# CONFIG_FREERTOS_WATCHPOINT_END_OF_STACK is not set
CONFIG_FREERTOS_TLSP_DELETION_CALLBACKS=y
# CONFIG_FREERTOS_TASK_PRE_DELETION_HOOK is not set
# CONFIG_FREERTOS_ENABLE_STATIC_TASK_CLEAN_UP is not set
CONFIG_FREERTOS_CHECK_MUTEX_GIVEN_BY_OWNER=y
CONFIG_FREERTOS_ISR_STACKSIZE=1536
CONFIG_FREERTOS_INTERRUPT_BACKTRACE=y
CONFIG_FREERTOS_TICK_SUPPORT_SYSTIMER=y
CONFIG_FREERTOS_CORETIMER_SYSTIMER_LVL1=y
# CONFIG_FREERTOS_CORETIMER_SYSTIMER_LVL3 is not set
CONFIG_FREERTOS_SYSTICK_USES_SYSTIMER=y
# CONFIG_FREERTOS_PLACE_FUNCTIONS_INTO_FLASH is not set
# CONFIG_FREERTOS_CHECK_PORT_CRITICAL_COMPLIANCE is not set
# end of Port
CONFIG_FREERTOS_PORT=y
CONFIG_FREERTOS_NO_AFFINITY=0x7FFFFFFF
CONFIG_FREERTOS_SUPPORT_STATIC_ALLOCATION=y
CONFIG_FREERTOS_DEBUG_OCDAWARE=y
CONFIG_FREERTOS_ENABLE_TASK_SNAPSHOT=y
CONFIG_FREERTOS_PLACE_SNAPSHOT_FUNS_INTO_FLASH=y
CONFIG_FREERTOS_NUMBER_OF_CORES=2
# end of FreeRTOS
#
# Hardware Abstraction Layer (HAL) and Low Level (LL)
#
CONFIG_HAL_ASSERTION_EQUALS_SYSTEM=y
# CONFIG_HAL_ASSERTION_DISABLE is not set
# CONFIG_HAL_ASSERTION_SILENT is not set
# CONFIG_HAL_ASSERTION_ENABLE is not set
CONFIG_HAL_DEFAULT_ASSERTION_LEVEL=2
CONFIG_HAL_WDT_USE_ROM_IMPL=y
CONFIG_HAL_SPI_MASTER_FUNC_IN_IRAM=y
CONFIG_HAL_SPI_SLAVE_FUNC_IN_IRAM=y
# end of Hardware Abstraction Layer (HAL) and Low Level (LL)
#
# Heap memory debugging
#
CONFIG_HEAP_POISONING_DISABLED=y
# CONFIG_HEAP_POISONING_LIGHT is not set
# CONFIG_HEAP_POISONING_COMPREHENSIVE is not set
CONFIG_HEAP_TRACING_OFF=y
# CONFIG_HEAP_TRACING_STANDALONE is not set
# CONFIG_HEAP_TRACING_TOHOST is not set
# CONFIG_HEAP_USE_HOOKS is not set
# CONFIG_HEAP_TASK_TRACKING is not set
# CONFIG_HEAP_ABORT_WHEN_ALLOCATION_FAILS is not set
# CONFIG_HEAP_PLACE_FUNCTION_INTO_FLASH is not set
# end of Heap memory debugging
#
# Log output
#
# CONFIG_LOG_DEFAULT_LEVEL_NONE is not set
# CONFIG_LOG_DEFAULT_LEVEL_ERROR is not set
# CONFIG_LOG_DEFAULT_LEVEL_WARN is not set
CONFIG_LOG_DEFAULT_LEVEL_INFO=y
# CONFIG_LOG_DEFAULT_LEVEL_DEBUG is not set
# CONFIG_LOG_DEFAULT_LEVEL_VERBOSE is not set
CONFIG_LOG_DEFAULT_LEVEL=3
CONFIG_LOG_MAXIMUM_EQUALS_DEFAULT=y
# CONFIG_LOG_MAXIMUM_LEVEL_DEBUG is not set
# CONFIG_LOG_MAXIMUM_LEVEL_VERBOSE is not set
CONFIG_LOG_MAXIMUM_LEVEL=3
# CONFIG_LOG_MASTER_LEVEL is not set
CONFIG_LOG_COLORS=y
CONFIG_LOG_TIMESTAMP_SOURCE_RTOS=y
# CONFIG_LOG_TIMESTAMP_SOURCE_SYSTEM is not set
# end of Log output
#
# LWIP
#
CONFIG_LWIP_ENABLE=y
CONFIG_LWIP_LOCAL_HOSTNAME="espressif"
# CONFIG_LWIP_NETIF_API is not set
CONFIG_LWIP_TCPIP_TASK_PRIO=18
# CONFIG_LWIP_TCPIP_CORE_LOCKING is not set
# CONFIG_LWIP_CHECK_THREAD_SAFETY is not set
CONFIG_LWIP_DNS_SUPPORT_MDNS_QUERIES=y
# CONFIG_LWIP_L2_TO_L3_COPY is not set
# CONFIG_LWIP_IRAM_OPTIMIZATION is not set
# CONFIG_LWIP_EXTRA_IRAM_OPTIMIZATION is not set
CONFIG_LWIP_TIMERS_ONDEMAND=y
CONFIG_LWIP_ND6=y
# CONFIG_LWIP_FORCE_ROUTER_FORWARDING is not set
CONFIG_LWIP_MAX_SOCKETS=10
# CONFIG_LWIP_USE_ONLY_LWIP_SELECT is not set
# CONFIG_LWIP_SO_LINGER is not set
CONFIG_LWIP_SO_REUSE=y
CONFIG_LWIP_SO_REUSE_RXTOALL=y
# CONFIG_LWIP_SO_RCVBUF is not set
# CONFIG_LWIP_NETBUF_RECVINFO is not set
CONFIG_LWIP_IP_DEFAULT_TTL=64
CONFIG_LWIP_IP4_FRAG=y
CONFIG_LWIP_IP6_FRAG=y
# CONFIG_LWIP_IP4_REASSEMBLY is not set
# CONFIG_LWIP_IP6_REASSEMBLY is not set
CONFIG_LWIP_IP_REASS_MAX_PBUFS=10
# CONFIG_LWIP_IP_FORWARD is not set
# CONFIG_LWIP_STATS is not set
CONFIG_LWIP_ESP_GRATUITOUS_ARP=y
CONFIG_LWIP_GARP_TMR_INTERVAL=60
CONFIG_LWIP_ESP_MLDV6_REPORT=y
CONFIG_LWIP_MLDV6_TMR_INTERVAL=40
CONFIG_LWIP_TCPIP_RECVMBOX_SIZE=32
CONFIG_LWIP_DHCP_DOES_ARP_CHECK=y
# CONFIG_LWIP_DHCP_DISABLE_CLIENT_ID is not set
CONFIG_LWIP_DHCP_DISABLE_VENDOR_CLASS_ID=y
# CONFIG_LWIP_DHCP_RESTORE_LAST_IP is not set
CONFIG_LWIP_DHCP_OPTIONS_LEN=68
CONFIG_LWIP_NUM_NETIF_CLIENT_DATA=0
CONFIG_LWIP_DHCP_COARSE_TIMER_SECS=1
#
# DHCP server
#
CONFIG_LWIP_DHCPS=y
CONFIG_LWIP_DHCPS_LEASE_UNIT=60
CONFIG_LWIP_DHCPS_MAX_STATION_NUM=8
CONFIG_LWIP_DHCPS_STATIC_ENTRIES=y
# end of DHCP server
# CONFIG_LWIP_AUTOIP is not set
CONFIG_LWIP_IPV4=y
CONFIG_LWIP_IPV6=y
# CONFIG_LWIP_IPV6_AUTOCONFIG is not set
CONFIG_LWIP_IPV6_NUM_ADDRESSES=3
# CONFIG_LWIP_IPV6_FORWARD is not set
# CONFIG_LWIP_NETIF_STATUS_CALLBACK is not set
CONFIG_LWIP_NETIF_LOOPBACK=y
CONFIG_LWIP_LOOPBACK_MAX_PBUFS=8
#
# TCP
#
CONFIG_LWIP_MAX_ACTIVE_TCP=16
CONFIG_LWIP_MAX_LISTENING_TCP=16
CONFIG_LWIP_TCP_HIGH_SPEED_RETRANSMISSION=y
CONFIG_LWIP_TCP_MAXRTX=12
CONFIG_LWIP_TCP_SYNMAXRTX=12
CONFIG_LWIP_TCP_MSS=1440
CONFIG_LWIP_TCP_TMR_INTERVAL=250
CONFIG_LWIP_TCP_MSL=60000
CONFIG_LWIP_TCP_FIN_WAIT_TIMEOUT=20000
CONFIG_LWIP_TCP_SND_BUF_DEFAULT=5760
CONFIG_LWIP_TCP_WND_DEFAULT=5760
CONFIG_LWIP_TCP_RECVMBOX_SIZE=6
CONFIG_LWIP_TCP_ACCEPTMBOX_SIZE=6
CONFIG_LWIP_TCP_QUEUE_OOSEQ=y
CONFIG_LWIP_TCP_OOSEQ_TIMEOUT=6
CONFIG_LWIP_TCP_OOSEQ_MAX_PBUFS=4
# CONFIG_LWIP_TCP_SACK_OUT is not set
CONFIG_LWIP_TCP_OVERSIZE_MSS=y
# CONFIG_LWIP_TCP_OVERSIZE_QUARTER_MSS is not set
# CONFIG_LWIP_TCP_OVERSIZE_DISABLE is not set
CONFIG_LWIP_TCP_RTO_TIME=1500
# end of TCP
#
# UDP
#
CONFIG_LWIP_MAX_UDP_PCBS=16
CONFIG_LWIP_UDP_RECVMBOX_SIZE=6
# end of UDP
#
# Checksums
#
# CONFIG_LWIP_CHECKSUM_CHECK_IP is not set
# CONFIG_LWIP_CHECKSUM_CHECK_UDP is not set
CONFIG_LWIP_CHECKSUM_CHECK_ICMP=y
# end of Checksums
CONFIG_LWIP_TCPIP_TASK_STACK_SIZE=3072
CONFIG_LWIP_TCPIP_TASK_AFFINITY_NO_AFFINITY=y
# CONFIG_LWIP_TCPIP_TASK_AFFINITY_CPU0 is not set
# CONFIG_LWIP_TCPIP_TASK_AFFINITY_CPU1 is not set
CONFIG_LWIP_TCPIP_TASK_AFFINITY=0x7FFFFFFF
# CONFIG_LWIP_PPP_SUPPORT is not set
CONFIG_LWIP_IPV6_MEMP_NUM_ND6_QUEUE=3
CONFIG_LWIP_IPV6_ND6_NUM_NEIGHBORS=5
# CONFIG_LWIP_SLIP_SUPPORT is not set
#
# ICMP
#
CONFIG_LWIP_ICMP=y
# CONFIG_LWIP_MULTICAST_PING is not set
# CONFIG_LWIP_BROADCAST_PING is not set
# end of ICMP
#
# LWIP RAW API
#
CONFIG_LWIP_MAX_RAW_PCBS=16
# end of LWIP RAW API
#
# SNTP
#
CONFIG_LWIP_SNTP_MAX_SERVERS=1
# CONFIG_LWIP_DHCP_GET_NTP_SRV is not set
CONFIG_LWIP_SNTP_UPDATE_DELAY=3600000
CONFIG_LWIP_SNTP_STARTUP_DELAY=y
CONFIG_LWIP_SNTP_MAXIMUM_STARTUP_DELAY=5000
# end of SNTP
#
# DNS
#
CONFIG_LWIP_DNS_MAX_SERVERS=3
# CONFIG_LWIP_FALLBACK_DNS_SERVER_SUPPORT is not set
# end of DNS
CONFIG_LWIP_BRIDGEIF_MAX_PORTS=7
CONFIG_LWIP_ESP_LWIP_ASSERT=y
#
# Hooks
#
# CONFIG_LWIP_HOOK_TCP_ISN_NONE is not set
CONFIG_LWIP_HOOK_TCP_ISN_DEFAULT=y
# CONFIG_LWIP_HOOK_TCP_ISN_CUSTOM is not set
CONFIG_LWIP_HOOK_IP6_ROUTE_NONE=y
# CONFIG_LWIP_HOOK_IP6_ROUTE_DEFAULT is not set
# CONFIG_LWIP_HOOK_IP6_ROUTE_CUSTOM is not set
CONFIG_LWIP_HOOK_ND6_GET_GW_NONE=y
# CONFIG_LWIP_HOOK_ND6_GET_GW_DEFAULT is not set
# CONFIG_LWIP_HOOK_ND6_GET_GW_CUSTOM is not set
CONFIG_LWIP_HOOK_IP6_SELECT_SRC_ADDR_NONE=y
# CONFIG_LWIP_HOOK_IP6_SELECT_SRC_ADDR_DEFAULT is not set
# CONFIG_LWIP_HOOK_IP6_SELECT_SRC_ADDR_CUSTOM is not set
CONFIG_LWIP_HOOK_NETCONN_EXT_RESOLVE_NONE=y
# CONFIG_LWIP_HOOK_NETCONN_EXT_RESOLVE_DEFAULT is not set
# CONFIG_LWIP_HOOK_NETCONN_EXT_RESOLVE_CUSTOM is not set
CONFIG_LWIP_HOOK_IP6_INPUT_NONE=y
# CONFIG_LWIP_HOOK_IP6_INPUT_DEFAULT is not set
# CONFIG_LWIP_HOOK_IP6_INPUT_CUSTOM is not set
# end of Hooks
# CONFIG_LWIP_DEBUG is not set
# end of LWIP
#
# mbedTLS
#
# CONFIG_MBEDTLS_INTERNAL_MEM_ALLOC is not set
CONFIG_MBEDTLS_EXTERNAL_MEM_ALLOC=y
# CONFIG_MBEDTLS_DEFAULT_MEM_ALLOC is not set
# CONFIG_MBEDTLS_CUSTOM_MEM_ALLOC is not set
CONFIG_MBEDTLS_ASYMMETRIC_CONTENT_LEN=y
CONFIG_MBEDTLS_SSL_IN_CONTENT_LEN=16384
CONFIG_MBEDTLS_SSL_OUT_CONTENT_LEN=4096
# CONFIG_MBEDTLS_DYNAMIC_BUFFER is not set
# CONFIG_MBEDTLS_DEBUG is not set
#
# mbedTLS v3.x related
#
# CONFIG_MBEDTLS_SSL_PROTO_TLS1_3 is not set
# CONFIG_MBEDTLS_SSL_VARIABLE_BUFFER_LENGTH is not set
# CONFIG_MBEDTLS_X509_TRUSTED_CERT_CALLBACK is not set
# CONFIG_MBEDTLS_SSL_CONTEXT_SERIALIZATION is not set
CONFIG_MBEDTLS_SSL_KEEP_PEER_CERTIFICATE=y
CONFIG_MBEDTLS_PKCS7_C=y
# end of mbedTLS v3.x related
#
# Certificate Bundle
#
CONFIG_MBEDTLS_CERTIFICATE_BUNDLE=y
CONFIG_MBEDTLS_CERTIFICATE_BUNDLE_DEFAULT_FULL=y
# CONFIG_MBEDTLS_CERTIFICATE_BUNDLE_DEFAULT_CMN is not set
# CONFIG_MBEDTLS_CERTIFICATE_BUNDLE_DEFAULT_NONE is not set
# CONFIG_MBEDTLS_CUSTOM_CERTIFICATE_BUNDLE is not set
# CONFIG_MBEDTLS_CERTIFICATE_BUNDLE_DEPRECATED_LIST is not set
CONFIG_MBEDTLS_CERTIFICATE_BUNDLE_MAX_CERTS=200
# end of Certificate Bundle
# CONFIG_MBEDTLS_ECP_RESTARTABLE is not set
CONFIG_MBEDTLS_CMAC_C=y
CONFIG_MBEDTLS_HARDWARE_AES=y
CONFIG_MBEDTLS_AES_USE_INTERRUPT=y
CONFIG_MBEDTLS_AES_INTERRUPT_LEVEL=0
CONFIG_MBEDTLS_GCM_SUPPORT_NON_AES_CIPHER=y
CONFIG_MBEDTLS_HARDWARE_MPI=y
# CONFIG_MBEDTLS_LARGE_KEY_SOFTWARE_MPI is not set
CONFIG_MBEDTLS_MPI_USE_INTERRUPT=y
CONFIG_MBEDTLS_MPI_INTERRUPT_LEVEL=0
CONFIG_MBEDTLS_HARDWARE_SHA=y
CONFIG_MBEDTLS_ROM_MD5=y
# CONFIG_MBEDTLS_ATCA_HW_ECDSA_SIGN is not set
# CONFIG_MBEDTLS_ATCA_HW_ECDSA_VERIFY is not set
CONFIG_MBEDTLS_HAVE_TIME=y
# CONFIG_MBEDTLS_PLATFORM_TIME_ALT is not set
# CONFIG_MBEDTLS_HAVE_TIME_DATE is not set
CONFIG_MBEDTLS_ECDSA_DETERMINISTIC=y
CONFIG_MBEDTLS_SHA512_C=y
CONFIG_MBEDTLS_TLS_SERVER_AND_CLIENT=y
# CONFIG_MBEDTLS_TLS_SERVER_ONLY is not set
# CONFIG_MBEDTLS_TLS_CLIENT_ONLY is not set
# CONFIG_MBEDTLS_TLS_DISABLED is not set
CONFIG_MBEDTLS_TLS_SERVER=y
CONFIG_MBEDTLS_TLS_CLIENT=y
CONFIG_MBEDTLS_TLS_ENABLED=y
#
# TLS Key Exchange Methods
#
# CONFIG_MBEDTLS_PSK_MODES is not set
CONFIG_MBEDTLS_KEY_EXCHANGE_RSA=y
CONFIG_MBEDTLS_KEY_EXCHANGE_ELLIPTIC_CURVE=y
CONFIG_MBEDTLS_KEY_EXCHANGE_ECDHE_RSA=y
CONFIG_MBEDTLS_KEY_EXCHANGE_ECDHE_ECDSA=y
CONFIG_MBEDTLS_KEY_EXCHANGE_ECDH_ECDSA=y
CONFIG_MBEDTLS_KEY_EXCHANGE_ECDH_RSA=y
# end of TLS Key Exchange Methods
CONFIG_MBEDTLS_SSL_RENEGOTIATION=y
CONFIG_MBEDTLS_SSL_PROTO_TLS1_2=y
# CONFIG_MBEDTLS_SSL_PROTO_GMTSSL1_1 is not set
# CONFIG_MBEDTLS_SSL_PROTO_DTLS is not set
CONFIG_MBEDTLS_SSL_ALPN=y
CONFIG_MBEDTLS_CLIENT_SSL_SESSION_TICKETS=y
CONFIG_MBEDTLS_SERVER_SSL_SESSION_TICKETS=y
#
# Symmetric Ciphers
#
CONFIG_MBEDTLS_AES_C=y
# CONFIG_MBEDTLS_CAMELLIA_C is not set
# CONFIG_MBEDTLS_DES_C is not set
# CONFIG_MBEDTLS_BLOWFISH_C is not set
# CONFIG_MBEDTLS_XTEA_C is not set
CONFIG_MBEDTLS_CCM_C=y
CONFIG_MBEDTLS_GCM_C=y
# CONFIG_MBEDTLS_NIST_KW_C is not set
# end of Symmetric Ciphers
# CONFIG_MBEDTLS_RIPEMD160_C is not set
#
# Certificates
#
CONFIG_MBEDTLS_PEM_PARSE_C=y
CONFIG_MBEDTLS_PEM_WRITE_C=y
CONFIG_MBEDTLS_X509_CRL_PARSE_C=y
CONFIG_MBEDTLS_X509_CSR_PARSE_C=y
# end of Certificates
CONFIG_MBEDTLS_ECP_C=y
# CONFIG_MBEDTLS_DHM_C is not set
CONFIG_MBEDTLS_ECDH_C=y
CONFIG_MBEDTLS_ECDSA_C=y
# CONFIG_MBEDTLS_ECJPAKE_C is not set
CONFIG_MBEDTLS_ECP_DP_SECP192R1_ENABLED=y
CONFIG_MBEDTLS_ECP_DP_SECP224R1_ENABLED=y
CONFIG_MBEDTLS_ECP_DP_SECP256R1_ENABLED=y
CONFIG_MBEDTLS_ECP_DP_SECP384R1_ENABLED=y
CONFIG_MBEDTLS_ECP_DP_SECP521R1_ENABLED=y
CONFIG_MBEDTLS_ECP_DP_SECP192K1_ENABLED=y
CONFIG_MBEDTLS_ECP_DP_SECP224K1_ENABLED=y
CONFIG_MBEDTLS_ECP_DP_SECP256K1_ENABLED=y
CONFIG_MBEDTLS_ECP_DP_BP256R1_ENABLED=y
CONFIG_MBEDTLS_ECP_DP_BP384R1_ENABLED=y
CONFIG_MBEDTLS_ECP_DP_BP512R1_ENABLED=y
CONFIG_MBEDTLS_ECP_DP_CURVE25519_ENABLED=y
CONFIG_MBEDTLS_ECP_NIST_OPTIM=y
CONFIG_MBEDTLS_ECP_FIXED_POINT_OPTIM=y
# CONFIG_MBEDTLS_POLY1305_C is not set
# CONFIG_MBEDTLS_CHACHA20_C is not set
# CONFIG_MBEDTLS_HKDF_C is not set
# CONFIG_MBEDTLS_THREADING_C is not set
CONFIG_MBEDTLS_ERROR_STRINGS=y
# end of mbedTLS
#
# ESP-MQTT Configurations
#
CONFIG_MQTT_PROTOCOL_311=y
# CONFIG_MQTT_PROTOCOL_5 is not set
CONFIG_MQTT_TRANSPORT_SSL=y
CONFIG_MQTT_TRANSPORT_WEBSOCKET=y
CONFIG_MQTT_TRANSPORT_WEBSOCKET_SECURE=y
# CONFIG_MQTT_MSG_ID_INCREMENTAL is not set
# CONFIG_MQTT_SKIP_PUBLISH_IF_DISCONNECTED is not set
# CONFIG_MQTT_REPORT_DELETED_MESSAGES is not set
# CONFIG_MQTT_USE_CUSTOM_CONFIG is not set
# CONFIG_MQTT_TASK_CORE_SELECTION_ENABLED is not set
# CONFIG_MQTT_CUSTOM_OUTBOX is not set
# end of ESP-MQTT Configurations
#
# Newlib
#
CONFIG_NEWLIB_STDOUT_LINE_ENDING_CRLF=y
# CONFIG_NEWLIB_STDOUT_LINE_ENDING_LF is not set
# CONFIG_NEWLIB_STDOUT_LINE_ENDING_CR is not set
# CONFIG_NEWLIB_STDIN_LINE_ENDING_CRLF is not set
# CONFIG_NEWLIB_STDIN_LINE_ENDING_LF is not set
CONFIG_NEWLIB_STDIN_LINE_ENDING_CR=y
# CONFIG_NEWLIB_NANO_FORMAT is not set
CONFIG_NEWLIB_TIME_SYSCALL_USE_RTC_HRT=y
# CONFIG_NEWLIB_TIME_SYSCALL_USE_RTC is not set
# CONFIG_NEWLIB_TIME_SYSCALL_USE_HRT is not set
# CONFIG_NEWLIB_TIME_SYSCALL_USE_NONE is not set
# end of Newlib
CONFIG_STDATOMIC_S32C1I_SPIRAM_WORKAROUND=y
#
# NVS
#
# CONFIG_NVS_ENCRYPTION is not set
# CONFIG_NVS_ASSERT_ERROR_CHECK is not set
# CONFIG_NVS_LEGACY_DUP_KEYS_COMPATIBILITY is not set
# end of NVS
#
# OpenThread
#
# CONFIG_OPENTHREAD_ENABLED is not set
#
# Thread Operational Dataset
#
CONFIG_OPENTHREAD_NETWORK_NAME="OpenThread-ESP"
CONFIG_OPENTHREAD_MESH_LOCAL_PREFIX="fd00:db8:a0:0::/64"
CONFIG_OPENTHREAD_NETWORK_CHANNEL=15
CONFIG_OPENTHREAD_NETWORK_PANID=0x1234
CONFIG_OPENTHREAD_NETWORK_EXTPANID="dead00beef00cafe"
CONFIG_OPENTHREAD_NETWORK_MASTERKEY="00112233445566778899aabbccddeeff"
CONFIG_OPENTHREAD_NETWORK_PSKC="104810e2315100afd6bc9215a6bfac53"
# end of Thread Operational Dataset
CONFIG_OPENTHREAD_XTAL_ACCURACY=130
# CONFIG_OPENTHREAD_SPINEL_ONLY is not set
CONFIG_OPENTHREAD_RX_ON_WHEN_IDLE=y
#
# Thread Address Query Config
#
# end of Thread Address Query Config
# end of OpenThread
#
# Protocomm
#
CONFIG_ESP_PROTOCOMM_SUPPORT_SECURITY_VERSION_0=y
CONFIG_ESP_PROTOCOMM_SUPPORT_SECURITY_VERSION_1=y
CONFIG_ESP_PROTOCOMM_SUPPORT_SECURITY_VERSION_2=y
# end of Protocomm
#
# PThreads
#
CONFIG_PTHREAD_TASK_PRIO_DEFAULT=5
CONFIG_PTHREAD_TASK_STACK_SIZE_DEFAULT=3072
CONFIG_PTHREAD_STACK_MIN=768
CONFIG_PTHREAD_DEFAULT_CORE_NO_AFFINITY=y
# CONFIG_PTHREAD_DEFAULT_CORE_0 is not set
# CONFIG_PTHREAD_DEFAULT_CORE_1 is not set
CONFIG_PTHREAD_TASK_CORE_DEFAULT=-1
CONFIG_PTHREAD_TASK_NAME_DEFAULT="pthread"
# end of PThreads
#
# MMU Config
#
CONFIG_MMU_PAGE_SIZE_64KB=y
CONFIG_MMU_PAGE_MODE="64KB"
CONFIG_MMU_PAGE_SIZE=0x10000
# end of MMU Config
#
# Main Flash configuration
#
#
# SPI Flash behavior when brownout
#
CONFIG_SPI_FLASH_BROWNOUT_RESET_XMC=y
CONFIG_SPI_FLASH_BROWNOUT_RESET=y
# end of SPI Flash behavior when brownout
#
# Optional and Experimental Features (READ DOCS FIRST)
#
#
# Features here require specific hardware (READ DOCS FIRST!)
#
# CONFIG_SPI_FLASH_HPM_ENA is not set
CONFIG_SPI_FLASH_HPM_AUTO=y
# CONFIG_SPI_FLASH_HPM_DIS is not set
CONFIG_SPI_FLASH_HPM_ON=y
CONFIG_SPI_FLASH_HPM_DC_AUTO=y
# CONFIG_SPI_FLASH_HPM_DC_DISABLE is not set
CONFIG_SPI_FLASH_SUSPEND_QVL_SUPPORTED=y
# CONFIG_SPI_FLASH_AUTO_SUSPEND is not set
CONFIG_SPI_FLASH_SUSPEND_TSUS_VAL_US=50
# end of Optional and Experimental Features (READ DOCS FIRST)
# end of Main Flash configuration
#
# SPI Flash driver
#
# CONFIG_SPI_FLASH_VERIFY_WRITE is not set
# CONFIG_SPI_FLASH_ENABLE_COUNTERS is not set
CONFIG_SPI_FLASH_ROM_DRIVER_PATCH=y
# CONFIG_SPI_FLASH_ROM_IMPL is not set
CONFIG_SPI_FLASH_DANGEROUS_WRITE_ABORTS=y
# CONFIG_SPI_FLASH_DANGEROUS_WRITE_FAILS is not set
# CONFIG_SPI_FLASH_DANGEROUS_WRITE_ALLOWED is not set
# CONFIG_SPI_FLASH_BYPASS_BLOCK_ERASE is not set
CONFIG_SPI_FLASH_YIELD_DURING_ERASE=y
CONFIG_SPI_FLASH_ERASE_YIELD_DURATION_MS=20
CONFIG_SPI_FLASH_ERASE_YIELD_TICKS=1
CONFIG_SPI_FLASH_WRITE_CHUNK_SIZE=8192
# CONFIG_SPI_FLASH_SIZE_OVERRIDE is not set
# CONFIG_SPI_FLASH_CHECK_ERASE_TIMEOUT_DISABLED is not set
# CONFIG_SPI_FLASH_OVERRIDE_CHIP_DRIVER_LIST is not set
#
# Auto-detect flash chips
#
CONFIG_SPI_FLASH_VENDOR_XMC_SUPPORTED=y
CONFIG_SPI_FLASH_VENDOR_GD_SUPPORTED=y
CONFIG_SPI_FLASH_VENDOR_ISSI_SUPPORTED=y
CONFIG_SPI_FLASH_VENDOR_MXIC_SUPPORTED=y
CONFIG_SPI_FLASH_VENDOR_WINBOND_SUPPORTED=y
CONFIG_SPI_FLASH_VENDOR_BOYA_SUPPORTED=y
CONFIG_SPI_FLASH_VENDOR_TH_SUPPORTED=y
CONFIG_SPI_FLASH_SUPPORT_ISSI_CHIP=y
CONFIG_SPI_FLASH_SUPPORT_MXIC_CHIP=y
CONFIG_SPI_FLASH_SUPPORT_GD_CHIP=y
CONFIG_SPI_FLASH_SUPPORT_WINBOND_CHIP=y
CONFIG_SPI_FLASH_SUPPORT_BOYA_CHIP=y
CONFIG_SPI_FLASH_SUPPORT_TH_CHIP=y
CONFIG_SPI_FLASH_SUPPORT_MXIC_OPI_CHIP=y
# end of Auto-detect flash chips
CONFIG_SPI_FLASH_ENABLE_ENCRYPTED_READ_WRITE=y
# end of SPI Flash driver
#
# SPIFFS Configuration
#
CONFIG_SPIFFS_MAX_PARTITIONS=3
#
# SPIFFS Cache Configuration
#
CONFIG_SPIFFS_CACHE=y
CONFIG_SPIFFS_CACHE_WR=y
# CONFIG_SPIFFS_CACHE_STATS is not set
# end of SPIFFS Cache Configuration
CONFIG_SPIFFS_PAGE_CHECK=y
CONFIG_SPIFFS_GC_MAX_RUNS=10
# CONFIG_SPIFFS_GC_STATS is not set
CONFIG_SPIFFS_PAGE_SIZE=256
CONFIG_SPIFFS_OBJ_NAME_LEN=32
# CONFIG_SPIFFS_FOLLOW_SYMLINKS is not set
CONFIG_SPIFFS_USE_MAGIC=y
CONFIG_SPIFFS_USE_MAGIC_LENGTH=y
CONFIG_SPIFFS_META_LENGTH=4
CONFIG_SPIFFS_USE_MTIME=y
#
# Debug Configuration
#
# CONFIG_SPIFFS_DBG is not set
# CONFIG_SPIFFS_API_DBG is not set
# CONFIG_SPIFFS_GC_DBG is not set
# CONFIG_SPIFFS_CACHE_DBG is not set
# CONFIG_SPIFFS_CHECK_DBG is not set
# CONFIG_SPIFFS_TEST_VISUALISATION is not set
# end of Debug Configuration
# end of SPIFFS Configuration
#
# TCP Transport
#
#
# Websocket
#
CONFIG_WS_TRANSPORT=y
CONFIG_WS_BUFFER_SIZE=1024
# CONFIG_WS_DYNAMIC_BUFFER is not set
# end of Websocket
# end of TCP Transport
#
# Ultra Low Power (ULP) Co-processor
#
# CONFIG_ULP_COPROC_ENABLED is not set
#
# ULP Debugging Options
#
# end of ULP Debugging Options
# end of Ultra Low Power (ULP) Co-processor
#
# Unity unit testing library
#
CONFIG_UNITY_ENABLE_FLOAT=y
CONFIG_UNITY_ENABLE_DOUBLE=y
# CONFIG_UNITY_ENABLE_64BIT is not set
# CONFIG_UNITY_ENABLE_COLOR is not set
CONFIG_UNITY_ENABLE_IDF_TEST_RUNNER=y
# CONFIG_UNITY_ENABLE_FIXTURE is not set
# CONFIG_UNITY_ENABLE_BACKTRACE_ON_FAIL is not set
# end of Unity unit testing library
#
# USB-OTG
#
CONFIG_USB_HOST_CONTROL_TRANSFER_MAX_SIZE=256
CONFIG_USB_HOST_HW_BUFFER_BIAS_BALANCED=y
# CONFIG_USB_HOST_HW_BUFFER_BIAS_IN is not set
# CONFIG_USB_HOST_HW_BUFFER_BIAS_PERIODIC_OUT is not set
#
# Root Hub configuration
#
CONFIG_USB_HOST_DEBOUNCE_DELAY_MS=250
CONFIG_USB_HOST_RESET_HOLD_MS=30
CONFIG_USB_HOST_RESET_RECOVERY_MS=30
CONFIG_USB_HOST_SET_ADDR_RECOVERY_MS=10
# end of Root Hub configuration
# CONFIG_USB_HOST_ENABLE_ENUM_FILTER_CALLBACK is not set
CONFIG_USB_OTG_SUPPORTED=y
# end of USB-OTG
#
# Virtual file system
#
CONFIG_VFS_SUPPORT_IO=y
CONFIG_VFS_SUPPORT_DIR=y
CONFIG_VFS_SUPPORT_SELECT=y
CONFIG_VFS_SUPPRESS_SELECT_DEBUG_OUTPUT=y
# CONFIG_VFS_SELECT_IN_RAM is not set
CONFIG_VFS_SUPPORT_TERMIOS=y
CONFIG_VFS_MAX_COUNT=8
#
# Host File System I/O (Semihosting)
#
CONFIG_VFS_SEMIHOSTFS_MAX_MOUNT_POINTS=1
# end of Host File System I/O (Semihosting)
# end of Virtual file system
#
# Wear Levelling
#
# CONFIG_WL_SECTOR_SIZE_512 is not set
CONFIG_WL_SECTOR_SIZE_4096=y
CONFIG_WL_SECTOR_SIZE=4096
# end of Wear Levelling
#
# Wi-Fi Provisioning Manager
#
CONFIG_WIFI_PROV_SCAN_MAX_ENTRIES=16
CONFIG_WIFI_PROV_AUTOSTOP_TIMEOUT=30
# CONFIG_WIFI_PROV_BLE_FORCE_ENCRYPTION is not set
CONFIG_WIFI_PROV_STA_ALL_CHANNEL_SCAN=y
# CONFIG_WIFI_PROV_STA_FAST_SCAN is not set
# end of Wi-Fi Provisioning Manager
# end of Component config
# CONFIG_IDF_EXPERIMENTAL_FEATURES is not set
# Deprecated options for backward compatibility
# CONFIG_APP_BUILD_TYPE_ELF_RAM is not set
# CONFIG_NO_BLOBS is not set
# CONFIG_LOG_BOOTLOADER_LEVEL_NONE is not set
# CONFIG_LOG_BOOTLOADER_LEVEL_ERROR is not set
# CONFIG_LOG_BOOTLOADER_LEVEL_WARN is not set
CONFIG_LOG_BOOTLOADER_LEVEL_INFO=y
# CONFIG_LOG_BOOTLOADER_LEVEL_DEBUG is not set
# CONFIG_LOG_BOOTLOADER_LEVEL_VERBOSE is not set
CONFIG_LOG_BOOTLOADER_LEVEL=3
# CONFIG_APP_ROLLBACK_ENABLE is not set
# CONFIG_FLASH_ENCRYPTION_ENABLED is not set
# CONFIG_FLASHMODE_QIO is not set
# CONFIG_FLASHMODE_QOUT is not set
CONFIG_FLASHMODE_DIO=y
# CONFIG_FLASHMODE_DOUT is not set
CONFIG_MONITOR_BAUD=115200
CONFIG_OPTIMIZATION_LEVEL_DEBUG=y
CONFIG_COMPILER_OPTIMIZATION_LEVEL_DEBUG=y
CONFIG_COMPILER_OPTIMIZATION_DEFAULT=y
# CONFIG_OPTIMIZATION_LEVEL_RELEASE is not set
# CONFIG_COMPILER_OPTIMIZATION_LEVEL_RELEASE is not set
CONFIG_OPTIMIZATION_ASSERTIONS_ENABLED=y
# CONFIG_OPTIMIZATION_ASSERTIONS_SILENT is not set
# CONFIG_OPTIMIZATION_ASSERTIONS_DISABLED is not set
CONFIG_OPTIMIZATION_ASSERTION_LEVEL=2
# CONFIG_CXX_EXCEPTIONS is not set
CONFIG_STACK_CHECK_NONE=y
# CONFIG_STACK_CHECK_NORM is not set
# CONFIG_STACK_CHECK_STRONG is not set
# CONFIG_STACK_CHECK_ALL is not set
# CONFIG_WARN_WRITE_STRINGS is not set
# CONFIG_ESP32_APPTRACE_DEST_TRAX is not set
CONFIG_ESP32_APPTRACE_DEST_NONE=y
CONFIG_ESP32_APPTRACE_LOCK_ENABLE=y
# CONFIG_EXTERNAL_COEX_ENABLE is not set
# CONFIG_ESP_WIFI_EXTERNAL_COEXIST_ENABLE is not set
# CONFIG_MCPWM_ISR_IN_IRAM is not set
# CONFIG_EVENT_LOOP_PROFILING is not set
CONFIG_POST_EVENTS_FROM_ISR=y
CONFIG_POST_EVENTS_FROM_IRAM_ISR=y
CONFIG_GDBSTUB_SUPPORT_TASKS=y
CONFIG_GDBSTUB_MAX_TASKS=32
# CONFIG_OTA_ALLOW_HTTP is not set
CONFIG_ESP32S3_DEEP_SLEEP_WAKEUP_DELAY=2000
CONFIG_ESP_SLEEP_DEEP_SLEEP_WAKEUP_DELAY=2000
CONFIG_ESP32S3_RTC_CLK_SRC_INT_RC=y
# CONFIG_ESP32S3_RTC_CLK_SRC_EXT_CRYS is not set
# CONFIG_ESP32S3_RTC_CLK_SRC_EXT_OSC is not set
# CONFIG_ESP32S3_RTC_CLK_SRC_INT_8MD256 is not set
CONFIG_ESP32S3_RTC_CLK_CAL_CYCLES=1024
CONFIG_ESP32_PHY_CALIBRATION_AND_DATA_STORAGE=y
# CONFIG_ESP32_PHY_INIT_DATA_IN_PARTITION is not set
CONFIG_ESP32_PHY_MAX_WIFI_TX_POWER=20
CONFIG_ESP32_PHY_MAX_TX_POWER=20
# CONFIG_REDUCE_PHY_TX_POWER is not set
# CONFIG_ESP32_REDUCE_PHY_TX_POWER is not set
CONFIG_ESP_SYSTEM_PM_POWER_DOWN_CPU=y
CONFIG_PM_POWER_DOWN_TAGMEM_IN_LIGHT_SLEEP=y
CONFIG_ESP32S3_SPIRAM_SUPPORT=y
CONFIG_DEFAULT_PSRAM_CLK_IO=30
CONFIG_DEFAULT_PSRAM_CS_IO=26
# CONFIG_ESP32S3_DEFAULT_CPU_FREQ_80 is not set
# CONFIG_ESP32S3_DEFAULT_CPU_FREQ_160 is not set
CONFIG_ESP32S3_DEFAULT_CPU_FREQ_240=y
CONFIG_ESP32S3_DEFAULT_CPU_FREQ_MHZ=240
CONFIG_SYSTEM_EVENT_QUEUE_SIZE=32
CONFIG_SYSTEM_EVENT_TASK_STACK_SIZE=2304
CONFIG_MAIN_TASK_STACK_SIZE=10240
CONFIG_CONSOLE_UART_DEFAULT=y
# CONFIG_CONSOLE_UART_CUSTOM is not set
# CONFIG_CONSOLE_UART_NONE is not set
# CONFIG_ESP_CONSOLE_UART_NONE is not set
CONFIG_CONSOLE_UART=y
CONFIG_CONSOLE_UART_NUM=0
CONFIG_CONSOLE_UART_BAUDRATE=115200
CONFIG_INT_WDT=y
CONFIG_INT_WDT_TIMEOUT_MS=300
CONFIG_INT_WDT_CHECK_CPU1=y
CONFIG_TASK_WDT=y
CONFIG_ESP_TASK_WDT=y
# CONFIG_TASK_WDT_PANIC is not set
CONFIG_TASK_WDT_TIMEOUT_S=5
CONFIG_TASK_WDT_CHECK_IDLE_TASK_CPU0=y
CONFIG_TASK_WDT_CHECK_IDLE_TASK_CPU1=y
# CONFIG_ESP32_DEBUG_STUBS_ENABLE is not set
CONFIG_ESP32S3_DEBUG_OCDAWARE=y
CONFIG_BROWNOUT_DET=y
CONFIG_ESP32S3_BROWNOUT_DET=y
CONFIG_ESP32S3_BROWNOUT_DET=y
CONFIG_BROWNOUT_DET_LVL_SEL_7=y
CONFIG_ESP32S3_BROWNOUT_DET_LVL_SEL_7=y
# CONFIG_BROWNOUT_DET_LVL_SEL_6 is not set
# CONFIG_ESP32S3_BROWNOUT_DET_LVL_SEL_6 is not set
# CONFIG_BROWNOUT_DET_LVL_SEL_5 is not set
# CONFIG_ESP32S3_BROWNOUT_DET_LVL_SEL_5 is not set
# CONFIG_BROWNOUT_DET_LVL_SEL_4 is not set
# CONFIG_ESP32S3_BROWNOUT_DET_LVL_SEL_4 is not set
# CONFIG_BROWNOUT_DET_LVL_SEL_3 is not set
# CONFIG_ESP32S3_BROWNOUT_DET_LVL_SEL_3 is not set
# CONFIG_BROWNOUT_DET_LVL_SEL_2 is not set
# CONFIG_ESP32S3_BROWNOUT_DET_LVL_SEL_2 is not set
# CONFIG_BROWNOUT_DET_LVL_SEL_1 is not set
# CONFIG_ESP32S3_BROWNOUT_DET_LVL_SEL_1 is not set
CONFIG_BROWNOUT_DET_LVL=7
CONFIG_ESP32S3_BROWNOUT_DET_LVL=7
CONFIG_IPC_TASK_STACK_SIZE=1280
CONFIG_TIMER_TASK_STACK_SIZE=3584
CONFIG_ESP32_WIFI_ENABLED=y
CONFIG_ESP32_WIFI_STATIC_RX_BUFFER_NUM=10
CONFIG_ESP32_WIFI_DYNAMIC_RX_BUFFER_NUM=32
CONFIG_ESP32_WIFI_STATIC_TX_BUFFER=y
CONFIG_ESP32_WIFI_TX_BUFFER_TYPE=0
CONFIG_ESP32_WIFI_STATIC_TX_BUFFER_NUM=16
CONFIG_ESP32_WIFI_CACHE_TX_BUFFER_NUM=32
# CONFIG_ESP32_WIFI_CSI_ENABLED is not set
CONFIG_ESP32_WIFI_AMPDU_TX_ENABLED=y
CONFIG_ESP32_WIFI_TX_BA_WIN=6
CONFIG_ESP32_WIFI_AMPDU_RX_ENABLED=y
CONFIG_ESP32_WIFI_AMPDU_RX_ENABLED=y
CONFIG_ESP32_WIFI_RX_BA_WIN=6
CONFIG_ESP32_WIFI_RX_BA_WIN=6
# CONFIG_ESP32_WIFI_AMSDU_TX_ENABLED is not set
CONFIG_ESP32_WIFI_NVS_ENABLED=y
CONFIG_ESP32_WIFI_TASK_PINNED_TO_CORE_0=y
# CONFIG_ESP32_WIFI_TASK_PINNED_TO_CORE_1 is not set
CONFIG_ESP32_WIFI_SOFTAP_BEACON_MAX_LEN=752
CONFIG_ESP32_WIFI_MGMT_SBUF_NUM=32
CONFIG_ESP32_WIFI_IRAM_OPT=y
CONFIG_ESP32_WIFI_RX_IRAM_OPT=y
CONFIG_ESP32_WIFI_ENABLE_WPA3_SAE=y
CONFIG_ESP32_WIFI_ENABLE_WPA3_OWE_STA=y
CONFIG_WPA_MBEDTLS_CRYPTO=y
CONFIG_WPA_MBEDTLS_TLS_CLIENT=y
# CONFIG_WPA_WAPI_PSK is not set
# CONFIG_WPA_SUITE_B_192 is not set
# CONFIG_WPA_11KV_SUPPORT is not set
# CONFIG_WPA_MBO_SUPPORT is not set
# CONFIG_WPA_DPP_SUPPORT is not set
# CONFIG_WPA_11R_SUPPORT is not set
# CONFIG_WPA_WPS_SOFTAP_REGISTRAR is not set
# CONFIG_WPA_WPS_STRICT is not set
# CONFIG_WPA_DEBUG_PRINT is not set
# CONFIG_WPA_TESTING_OPTIONS is not set
# CONFIG_ESP32_ENABLE_COREDUMP_TO_FLASH is not set
# CONFIG_ESP32_ENABLE_COREDUMP_TO_UART is not set
CONFIG_ESP32_ENABLE_COREDUMP_TO_NONE=y
CONFIG_TIMER_TASK_PRIORITY=1
CONFIG_TIMER_TASK_STACK_DEPTH=2048
CONFIG_TIMER_QUEUE_LENGTH=10
# CONFIG_ENABLE_STATIC_TASK_CLEAN_UP_HOOK is not set
# CONFIG_HAL_ASSERTION_SILIENT is not set
# CONFIG_L2_TO_L3_COPY is not set
CONFIG_ESP_GRATUITOUS_ARP=y
CONFIG_GARP_TMR_INTERVAL=60
CONFIG_TCPIP_RECVMBOX_SIZE=32
CONFIG_TCP_MAXRTX=12
CONFIG_TCP_SYNMAXRTX=12
CONFIG_TCP_MSS=1440
CONFIG_TCP_MSL=60000
CONFIG_TCP_SND_BUF_DEFAULT=5760
CONFIG_TCP_WND_DEFAULT=5760
CONFIG_TCP_RECVMBOX_SIZE=6
CONFIG_TCP_QUEUE_OOSEQ=y
CONFIG_TCP_OVERSIZE_MSS=y
# CONFIG_TCP_OVERSIZE_QUARTER_MSS is not set
# CONFIG_TCP_OVERSIZE_DISABLE is not set
CONFIG_UDP_RECVMBOX_SIZE=6
CONFIG_TCPIP_TASK_STACK_SIZE=3072
CONFIG_TCPIP_TASK_AFFINITY_NO_AFFINITY=y
# CONFIG_TCPIP_TASK_AFFINITY_CPU0 is not set
# CONFIG_TCPIP_TASK_AFFINITY_CPU1 is not set
CONFIG_TCPIP_TASK_AFFINITY=0x7FFFFFFF
# CONFIG_PPP_SUPPORT is not set
CONFIG_ESP32S3_TIME_SYSCALL_USE_RTC_SYSTIMER=y
CONFIG_ESP32S3_TIME_SYSCALL_USE_RTC_FRC1=y
# CONFIG_ESP32S3_TIME_SYSCALL_USE_RTC is not set
# CONFIG_ESP32S3_TIME_SYSCALL_USE_SYSTIMER is not set
# CONFIG_ESP32S3_TIME_SYSCALL_USE_FRC1 is not set
# CONFIG_ESP32S3_TIME_SYSCALL_USE_NONE is not set
CONFIG_ESP32_PTHREAD_TASK_PRIO_DEFAULT=5
CONFIG_ESP32_PTHREAD_TASK_STACK_SIZE_DEFAULT=3072
CONFIG_ESP32_PTHREAD_STACK_MIN=768
CONFIG_ESP32_DEFAULT_PTHREAD_CORE_NO_AFFINITY=y
# CONFIG_ESP32_DEFAULT_PTHREAD_CORE_0 is not set
# CONFIG_ESP32_DEFAULT_PTHREAD_CORE_1 is not set
CONFIG_ESP32_PTHREAD_TASK_CORE_DEFAULT=-1
CONFIG_ESP32_PTHREAD_TASK_NAME_DEFAULT="pthread"
CONFIG_SPI_FLASH_WRITING_DANGEROUS_REGIONS_ABORTS=y
# CONFIG_SPI_FLASH_WRITING_DANGEROUS_REGIONS_FAILS is not set
# CONFIG_SPI_FLASH_WRITING_DANGEROUS_REGIONS_ALLOWED is not set
CONFIG_SUPPRESS_SELECT_DEBUG_OUTPUT=y
CONFIG_SUPPORT_TERMIOS=y
CONFIG_SEMIHOSTFS_MAX_MOUNT_POINTS=1
# End of deprecated options
| 66,367 | sdkconfig | thatproject | en | unknown | unknown | {} | 0 | {} |
0015/Fridge-Calendar | sdkconfig | #
# Automatically generated file. DO NOT EDIT.
# Espressif IoT Development Framework (ESP-IDF) 5.3.1 Project Configuration
#
CONFIG_SOC_MPU_MIN_REGION_SIZE=0x20000000
CONFIG_SOC_MPU_REGIONS_MAX_NUM=8
CONFIG_SOC_ADC_SUPPORTED=y
CONFIG_SOC_UART_SUPPORTED=y
CONFIG_SOC_PCNT_SUPPORTED=y
CONFIG_SOC_PHY_SUPPORTED=y
CONFIG_SOC_WIFI_SUPPORTED=y
CONFIG_SOC_TWAI_SUPPORTED=y
CONFIG_SOC_GDMA_SUPPORTED=y
CONFIG_SOC_AHB_GDMA_SUPPORTED=y
CONFIG_SOC_GPTIMER_SUPPORTED=y
CONFIG_SOC_LCDCAM_SUPPORTED=y
CONFIG_SOC_MCPWM_SUPPORTED=y
CONFIG_SOC_DEDICATED_GPIO_SUPPORTED=y
CONFIG_SOC_CACHE_SUPPORT_WRAP=y
CONFIG_SOC_ULP_SUPPORTED=y
CONFIG_SOC_ULP_FSM_SUPPORTED=y
CONFIG_SOC_RISCV_COPROC_SUPPORTED=y
CONFIG_SOC_BT_SUPPORTED=y
CONFIG_SOC_USB_OTG_SUPPORTED=y
CONFIG_SOC_USB_SERIAL_JTAG_SUPPORTED=y
CONFIG_SOC_CCOMP_TIMER_SUPPORTED=y
CONFIG_SOC_ASYNC_MEMCPY_SUPPORTED=y
CONFIG_SOC_SUPPORTS_SECURE_DL_MODE=y
CONFIG_SOC_EFUSE_KEY_PURPOSE_FIELD=y
CONFIG_SOC_EFUSE_SUPPORTED=y
CONFIG_SOC_SDMMC_HOST_SUPPORTED=y
CONFIG_SOC_RTC_FAST_MEM_SUPPORTED=y
CONFIG_SOC_RTC_SLOW_MEM_SUPPORTED=y
CONFIG_SOC_RTC_MEM_SUPPORTED=y
CONFIG_SOC_PSRAM_DMA_CAPABLE=y
CONFIG_SOC_XT_WDT_SUPPORTED=y
CONFIG_SOC_I2S_SUPPORTED=y
CONFIG_SOC_RMT_SUPPORTED=y
CONFIG_SOC_SDM_SUPPORTED=y
CONFIG_SOC_GPSPI_SUPPORTED=y
CONFIG_SOC_LEDC_SUPPORTED=y
CONFIG_SOC_I2C_SUPPORTED=y
CONFIG_SOC_SYSTIMER_SUPPORTED=y
CONFIG_SOC_SUPPORT_COEXISTENCE=y
CONFIG_SOC_TEMP_SENSOR_SUPPORTED=y
CONFIG_SOC_AES_SUPPORTED=y
CONFIG_SOC_MPI_SUPPORTED=y
CONFIG_SOC_SHA_SUPPORTED=y
CONFIG_SOC_HMAC_SUPPORTED=y
CONFIG_SOC_DIG_SIGN_SUPPORTED=y
CONFIG_SOC_FLASH_ENC_SUPPORTED=y
CONFIG_SOC_SECURE_BOOT_SUPPORTED=y
CONFIG_SOC_MEMPROT_SUPPORTED=y
CONFIG_SOC_TOUCH_SENSOR_SUPPORTED=y
CONFIG_SOC_BOD_SUPPORTED=y
CONFIG_SOC_CLK_TREE_SUPPORTED=y
CONFIG_SOC_MPU_SUPPORTED=y
CONFIG_SOC_WDT_SUPPORTED=y
CONFIG_SOC_SPI_FLASH_SUPPORTED=y
CONFIG_SOC_RNG_SUPPORTED=y
CONFIG_SOC_LIGHT_SLEEP_SUPPORTED=y
CONFIG_SOC_DEEP_SLEEP_SUPPORTED=y
CONFIG_SOC_LP_PERIPH_SHARE_INTERRUPT=y
CONFIG_SOC_PM_SUPPORTED=y
CONFIG_SOC_XTAL_SUPPORT_40M=y
CONFIG_SOC_APPCPU_HAS_CLOCK_GATING_BUG=y
CONFIG_SOC_ADC_RTC_CTRL_SUPPORTED=y
CONFIG_SOC_ADC_DIG_CTRL_SUPPORTED=y
CONFIG_SOC_ADC_ARBITER_SUPPORTED=y
CONFIG_SOC_ADC_DIG_IIR_FILTER_SUPPORTED=y
CONFIG_SOC_ADC_MONITOR_SUPPORTED=y
CONFIG_SOC_ADC_DMA_SUPPORTED=y
CONFIG_SOC_ADC_PERIPH_NUM=2
CONFIG_SOC_ADC_MAX_CHANNEL_NUM=10
CONFIG_SOC_ADC_ATTEN_NUM=4
CONFIG_SOC_ADC_DIGI_CONTROLLER_NUM=2
CONFIG_SOC_ADC_PATT_LEN_MAX=24
CONFIG_SOC_ADC_DIGI_MIN_BITWIDTH=12
CONFIG_SOC_ADC_DIGI_MAX_BITWIDTH=12
CONFIG_SOC_ADC_DIGI_RESULT_BYTES=4
CONFIG_SOC_ADC_DIGI_DATA_BYTES_PER_CONV=4
CONFIG_SOC_ADC_DIGI_IIR_FILTER_NUM=2
CONFIG_SOC_ADC_DIGI_MONITOR_NUM=2
CONFIG_SOC_ADC_SAMPLE_FREQ_THRES_HIGH=83333
CONFIG_SOC_ADC_SAMPLE_FREQ_THRES_LOW=611
CONFIG_SOC_ADC_RTC_MIN_BITWIDTH=12
CONFIG_SOC_ADC_RTC_MAX_BITWIDTH=12
CONFIG_SOC_ADC_CALIBRATION_V1_SUPPORTED=y
CONFIG_SOC_ADC_SELF_HW_CALI_SUPPORTED=y
CONFIG_SOC_ADC_SHARED_POWER=y
CONFIG_SOC_APB_BACKUP_DMA=y
CONFIG_SOC_BROWNOUT_RESET_SUPPORTED=y
CONFIG_SOC_CACHE_WRITEBACK_SUPPORTED=y
CONFIG_SOC_CACHE_FREEZE_SUPPORTED=y
CONFIG_SOC_CPU_CORES_NUM=2
CONFIG_SOC_CPU_INTR_NUM=32
CONFIG_SOC_CPU_HAS_FPU=y
CONFIG_SOC_HP_CPU_HAS_MULTIPLE_CORES=y
CONFIG_SOC_CPU_BREAKPOINTS_NUM=2
CONFIG_SOC_CPU_WATCHPOINTS_NUM=2
CONFIG_SOC_CPU_WATCHPOINT_MAX_REGION_SIZE=64
CONFIG_SOC_DS_SIGNATURE_MAX_BIT_LEN=4096
CONFIG_SOC_DS_KEY_PARAM_MD_IV_LENGTH=16
CONFIG_SOC_DS_KEY_CHECK_MAX_WAIT_US=1100
CONFIG_SOC_AHB_GDMA_VERSION=1
CONFIG_SOC_GDMA_NUM_GROUPS_MAX=1
CONFIG_SOC_GDMA_PAIRS_PER_GROUP=5
CONFIG_SOC_GDMA_PAIRS_PER_GROUP_MAX=5
CONFIG_SOC_AHB_GDMA_SUPPORT_PSRAM=y
CONFIG_SOC_GPIO_PORT=1
CONFIG_SOC_GPIO_PIN_COUNT=49
CONFIG_SOC_GPIO_SUPPORT_PIN_GLITCH_FILTER=y
CONFIG_SOC_GPIO_FILTER_CLK_SUPPORT_APB=y
CONFIG_SOC_GPIO_SUPPORT_RTC_INDEPENDENT=y
CONFIG_SOC_GPIO_SUPPORT_FORCE_HOLD=y
CONFIG_SOC_GPIO_VALID_GPIO_MASK=0x1FFFFFFFFFFFF
CONFIG_SOC_GPIO_IN_RANGE_MAX=48
CONFIG_SOC_GPIO_OUT_RANGE_MAX=48
CONFIG_SOC_GPIO_VALID_DIGITAL_IO_PAD_MASK=0x0001FFFFFC000000
CONFIG_SOC_GPIO_CLOCKOUT_BY_IO_MUX=y
CONFIG_SOC_GPIO_CLOCKOUT_CHANNEL_NUM=3
CONFIG_SOC_DEDIC_GPIO_OUT_CHANNELS_NUM=8
CONFIG_SOC_DEDIC_GPIO_IN_CHANNELS_NUM=8
CONFIG_SOC_DEDIC_GPIO_OUT_AUTO_ENABLE=y
CONFIG_SOC_I2C_NUM=2
CONFIG_SOC_HP_I2C_NUM=2
CONFIG_SOC_I2C_FIFO_LEN=32
CONFIG_SOC_I2C_CMD_REG_NUM=8
CONFIG_SOC_I2C_SUPPORT_SLAVE=y
CONFIG_SOC_I2C_SUPPORT_HW_CLR_BUS=y
CONFIG_SOC_I2C_SUPPORT_XTAL=y
CONFIG_SOC_I2C_SUPPORT_RTC=y
CONFIG_SOC_I2C_SUPPORT_10BIT_ADDR=y
CONFIG_SOC_I2C_SLAVE_SUPPORT_BROADCAST=y
CONFIG_SOC_I2C_SLAVE_SUPPORT_I2CRAM_ACCESS=y
CONFIG_SOC_I2S_NUM=2
CONFIG_SOC_I2S_HW_VERSION_2=y
CONFIG_SOC_I2S_SUPPORTS_XTAL=y
CONFIG_SOC_I2S_SUPPORTS_PLL_F160M=y
CONFIG_SOC_I2S_SUPPORTS_PCM=y
CONFIG_SOC_I2S_SUPPORTS_PDM=y
CONFIG_SOC_I2S_SUPPORTS_PDM_TX=y
CONFIG_SOC_I2S_PDM_MAX_TX_LINES=2
CONFIG_SOC_I2S_SUPPORTS_PDM_RX=y
CONFIG_SOC_I2S_PDM_MAX_RX_LINES=4
CONFIG_SOC_I2S_SUPPORTS_TDM=y
CONFIG_SOC_LEDC_SUPPORT_APB_CLOCK=y
CONFIG_SOC_LEDC_SUPPORT_XTAL_CLOCK=y
CONFIG_SOC_LEDC_CHANNEL_NUM=8
CONFIG_SOC_LEDC_TIMER_BIT_WIDTH=14
CONFIG_SOC_LEDC_SUPPORT_FADE_STOP=y
CONFIG_SOC_MCPWM_GROUPS=2
CONFIG_SOC_MCPWM_TIMERS_PER_GROUP=3
CONFIG_SOC_MCPWM_OPERATORS_PER_GROUP=3
CONFIG_SOC_MCPWM_COMPARATORS_PER_OPERATOR=2
CONFIG_SOC_MCPWM_GENERATORS_PER_OPERATOR=2
CONFIG_SOC_MCPWM_TRIGGERS_PER_OPERATOR=2
CONFIG_SOC_MCPWM_GPIO_FAULTS_PER_GROUP=3
CONFIG_SOC_MCPWM_CAPTURE_TIMERS_PER_GROUP=y
CONFIG_SOC_MCPWM_CAPTURE_CHANNELS_PER_TIMER=3
CONFIG_SOC_MCPWM_GPIO_SYNCHROS_PER_GROUP=3
CONFIG_SOC_MCPWM_SWSYNC_CAN_PROPAGATE=y
CONFIG_SOC_MMU_LINEAR_ADDRESS_REGION_NUM=1
CONFIG_SOC_MMU_PERIPH_NUM=1
CONFIG_SOC_PCNT_GROUPS=1
CONFIG_SOC_PCNT_UNITS_PER_GROUP=4
CONFIG_SOC_PCNT_CHANNELS_PER_UNIT=2
CONFIG_SOC_PCNT_THRES_POINT_PER_UNIT=2
CONFIG_SOC_RMT_GROUPS=1
CONFIG_SOC_RMT_TX_CANDIDATES_PER_GROUP=4
CONFIG_SOC_RMT_RX_CANDIDATES_PER_GROUP=4
CONFIG_SOC_RMT_CHANNELS_PER_GROUP=8
CONFIG_SOC_RMT_MEM_WORDS_PER_CHANNEL=48
CONFIG_SOC_RMT_SUPPORT_RX_PINGPONG=y
CONFIG_SOC_RMT_SUPPORT_RX_DEMODULATION=y
CONFIG_SOC_RMT_SUPPORT_TX_ASYNC_STOP=y
CONFIG_SOC_RMT_SUPPORT_TX_LOOP_COUNT=y
CONFIG_SOC_RMT_SUPPORT_TX_LOOP_AUTO_STOP=y
CONFIG_SOC_RMT_SUPPORT_TX_SYNCHRO=y
CONFIG_SOC_RMT_SUPPORT_TX_CARRIER_DATA_ONLY=y
CONFIG_SOC_RMT_SUPPORT_XTAL=y
CONFIG_SOC_RMT_SUPPORT_RC_FAST=y
CONFIG_SOC_RMT_SUPPORT_APB=y
CONFIG_SOC_RMT_SUPPORT_DMA=y
CONFIG_SOC_LCD_I80_SUPPORTED=y
CONFIG_SOC_LCD_RGB_SUPPORTED=y
CONFIG_SOC_LCD_I80_BUSES=1
CONFIG_SOC_LCD_RGB_PANELS=1
CONFIG_SOC_LCD_I80_BUS_WIDTH=16
CONFIG_SOC_LCD_RGB_DATA_WIDTH=16
CONFIG_SOC_LCD_SUPPORT_RGB_YUV_CONV=y
CONFIG_SOC_RTC_CNTL_CPU_PD_DMA_BUS_WIDTH=128
CONFIG_SOC_RTC_CNTL_CPU_PD_REG_FILE_NUM=549
CONFIG_SOC_RTC_CNTL_TAGMEM_PD_DMA_BUS_WIDTH=128
CONFIG_SOC_RTCIO_PIN_COUNT=22
CONFIG_SOC_RTCIO_INPUT_OUTPUT_SUPPORTED=y
CONFIG_SOC_RTCIO_HOLD_SUPPORTED=y
CONFIG_SOC_RTCIO_WAKE_SUPPORTED=y
CONFIG_SOC_SDM_GROUPS=y
CONFIG_SOC_SDM_CHANNELS_PER_GROUP=8
CONFIG_SOC_SDM_CLK_SUPPORT_APB=y
CONFIG_SOC_SPI_PERIPH_NUM=3
CONFIG_SOC_SPI_MAX_CS_NUM=6
CONFIG_SOC_SPI_MAXIMUM_BUFFER_SIZE=64
CONFIG_SOC_SPI_SUPPORT_DDRCLK=y
CONFIG_SOC_SPI_SLAVE_SUPPORT_SEG_TRANS=y
CONFIG_SOC_SPI_SUPPORT_CD_SIG=y
CONFIG_SOC_SPI_SUPPORT_CONTINUOUS_TRANS=y
CONFIG_SOC_SPI_SUPPORT_SLAVE_HD_VER2=y
CONFIG_SOC_SPI_SUPPORT_CLK_APB=y
CONFIG_SOC_SPI_SUPPORT_CLK_XTAL=y
CONFIG_SOC_SPI_PERIPH_SUPPORT_CONTROL_DUMMY_OUT=y
CONFIG_SOC_MEMSPI_IS_INDEPENDENT=y
CONFIG_SOC_SPI_MAX_PRE_DIVIDER=16
CONFIG_SOC_SPI_SUPPORT_OCT=y
CONFIG_SOC_SPI_SCT_SUPPORTED=y
CONFIG_SOC_SPI_SCT_REG_NUM=14
CONFIG_SOC_SPI_SCT_BUFFER_NUM_MAX=y
CONFIG_SOC_SPI_SCT_CONF_BITLEN_MAX=0x3FFFA
CONFIG_SOC_MEMSPI_SRC_FREQ_120M=y
CONFIG_SOC_MEMSPI_SRC_FREQ_80M_SUPPORTED=y
CONFIG_SOC_MEMSPI_SRC_FREQ_40M_SUPPORTED=y
CONFIG_SOC_MEMSPI_SRC_FREQ_20M_SUPPORTED=y
CONFIG_SOC_SPIRAM_SUPPORTED=y
CONFIG_SOC_SPIRAM_XIP_SUPPORTED=y
CONFIG_SOC_SYSTIMER_COUNTER_NUM=2
CONFIG_SOC_SYSTIMER_ALARM_NUM=3
CONFIG_SOC_SYSTIMER_BIT_WIDTH_LO=32
CONFIG_SOC_SYSTIMER_BIT_WIDTH_HI=20
CONFIG_SOC_SYSTIMER_FIXED_DIVIDER=y
CONFIG_SOC_SYSTIMER_INT_LEVEL=y
CONFIG_SOC_SYSTIMER_ALARM_MISS_COMPENSATE=y
CONFIG_SOC_TIMER_GROUPS=2
CONFIG_SOC_TIMER_GROUP_TIMERS_PER_GROUP=2
CONFIG_SOC_TIMER_GROUP_COUNTER_BIT_WIDTH=54
CONFIG_SOC_TIMER_GROUP_SUPPORT_XTAL=y
CONFIG_SOC_TIMER_GROUP_SUPPORT_APB=y
CONFIG_SOC_TIMER_GROUP_TOTAL_TIMERS=4
CONFIG_SOC_TOUCH_SENSOR_VERSION=2
CONFIG_SOC_TOUCH_SENSOR_NUM=15
CONFIG_SOC_TOUCH_SUPPORT_SLEEP_WAKEUP=y
CONFIG_SOC_TOUCH_SUPPORT_WATERPROOF=y
CONFIG_SOC_TOUCH_SUPPORT_PROX_SENSING=y
CONFIG_SOC_TOUCH_PROXIMITY_CHANNEL_NUM=3
CONFIG_SOC_TOUCH_PROXIMITY_MEAS_DONE_SUPPORTED=y
CONFIG_SOC_TOUCH_SAMPLE_CFG_NUM=1
CONFIG_SOC_TWAI_CONTROLLER_NUM=1
CONFIG_SOC_TWAI_CLK_SUPPORT_APB=y
CONFIG_SOC_TWAI_BRP_MIN=2
CONFIG_SOC_TWAI_BRP_MAX=16384
CONFIG_SOC_TWAI_SUPPORTS_RX_STATUS=y
CONFIG_SOC_UART_NUM=3
CONFIG_SOC_UART_HP_NUM=3
CONFIG_SOC_UART_FIFO_LEN=128
CONFIG_SOC_UART_BITRATE_MAX=5000000
CONFIG_SOC_UART_SUPPORT_FSM_TX_WAIT_SEND=y
CONFIG_SOC_UART_SUPPORT_WAKEUP_INT=y
CONFIG_SOC_UART_SUPPORT_APB_CLK=y
CONFIG_SOC_UART_SUPPORT_RTC_CLK=y
CONFIG_SOC_UART_SUPPORT_XTAL_CLK=y
CONFIG_SOC_USB_OTG_PERIPH_NUM=1
CONFIG_SOC_SHA_DMA_MAX_BUFFER_SIZE=3968
CONFIG_SOC_SHA_SUPPORT_DMA=y
CONFIG_SOC_SHA_SUPPORT_RESUME=y
CONFIG_SOC_SHA_GDMA=y
CONFIG_SOC_SHA_SUPPORT_SHA1=y
CONFIG_SOC_SHA_SUPPORT_SHA224=y
CONFIG_SOC_SHA_SUPPORT_SHA256=y
CONFIG_SOC_SHA_SUPPORT_SHA384=y
CONFIG_SOC_SHA_SUPPORT_SHA512=y
CONFIG_SOC_SHA_SUPPORT_SHA512_224=y
CONFIG_SOC_SHA_SUPPORT_SHA512_256=y
CONFIG_SOC_SHA_SUPPORT_SHA512_T=y
CONFIG_SOC_MPI_MEM_BLOCKS_NUM=4
CONFIG_SOC_MPI_OPERATIONS_NUM=3
CONFIG_SOC_RSA_MAX_BIT_LEN=4096
CONFIG_SOC_AES_SUPPORT_DMA=y
CONFIG_SOC_AES_GDMA=y
CONFIG_SOC_AES_SUPPORT_AES_128=y
CONFIG_SOC_AES_SUPPORT_AES_256=y
CONFIG_SOC_PM_SUPPORT_EXT0_WAKEUP=y
CONFIG_SOC_PM_SUPPORT_EXT1_WAKEUP=y
CONFIG_SOC_PM_SUPPORT_EXT_WAKEUP=y
CONFIG_SOC_PM_SUPPORT_WIFI_WAKEUP=y
CONFIG_SOC_PM_SUPPORT_BT_WAKEUP=y
CONFIG_SOC_PM_SUPPORT_TOUCH_SENSOR_WAKEUP=y
CONFIG_SOC_PM_SUPPORT_CPU_PD=y
CONFIG_SOC_PM_SUPPORT_TAGMEM_PD=y
CONFIG_SOC_PM_SUPPORT_RTC_PERIPH_PD=y
CONFIG_SOC_PM_SUPPORT_RC_FAST_PD=y
CONFIG_SOC_PM_SUPPORT_VDDSDIO_PD=y
CONFIG_SOC_PM_SUPPORT_MAC_BB_PD=y
CONFIG_SOC_PM_SUPPORT_MODEM_PD=y
CONFIG_SOC_CONFIGURABLE_VDDSDIO_SUPPORTED=y
CONFIG_SOC_PM_SUPPORT_DEEPSLEEP_CHECK_STUB_ONLY=y
CONFIG_SOC_PM_CPU_RETENTION_BY_RTCCNTL=y
CONFIG_SOC_PM_MODEM_RETENTION_BY_BACKUPDMA=y
CONFIG_SOC_CLK_RC_FAST_D256_SUPPORTED=y
CONFIG_SOC_RTC_SLOW_CLK_SUPPORT_RC_FAST_D256=y
CONFIG_SOC_CLK_RC_FAST_SUPPORT_CALIBRATION=y
CONFIG_SOC_CLK_XTAL32K_SUPPORTED=y
CONFIG_SOC_EFUSE_DIS_DOWNLOAD_ICACHE=y
CONFIG_SOC_EFUSE_DIS_DOWNLOAD_DCACHE=y
CONFIG_SOC_EFUSE_HARD_DIS_JTAG=y
CONFIG_SOC_EFUSE_DIS_USB_JTAG=y
CONFIG_SOC_EFUSE_SOFT_DIS_JTAG=y
CONFIG_SOC_EFUSE_DIS_DIRECT_BOOT=y
CONFIG_SOC_EFUSE_DIS_ICACHE=y
CONFIG_SOC_EFUSE_BLOCK9_KEY_PURPOSE_QUIRK=y
CONFIG_SOC_SECURE_BOOT_V2_RSA=y
CONFIG_SOC_EFUSE_SECURE_BOOT_KEY_DIGESTS=3
CONFIG_SOC_EFUSE_REVOKE_BOOT_KEY_DIGESTS=y
CONFIG_SOC_SUPPORT_SECURE_BOOT_REVOKE_KEY=y
CONFIG_SOC_FLASH_ENCRYPTED_XTS_AES_BLOCK_MAX=64
CONFIG_SOC_FLASH_ENCRYPTION_XTS_AES=y
CONFIG_SOC_FLASH_ENCRYPTION_XTS_AES_OPTIONS=y
CONFIG_SOC_FLASH_ENCRYPTION_XTS_AES_128=y
CONFIG_SOC_FLASH_ENCRYPTION_XTS_AES_256=y
CONFIG_SOC_MEMPROT_CPU_PREFETCH_PAD_SIZE=16
CONFIG_SOC_MEMPROT_MEM_ALIGN_SIZE=256
CONFIG_SOC_PHY_DIG_REGS_MEM_SIZE=21
CONFIG_SOC_MAC_BB_PD_MEM_SIZE=192
CONFIG_SOC_WIFI_LIGHT_SLEEP_CLK_WIDTH=12
CONFIG_SOC_SPI_MEM_SUPPORT_AUTO_WAIT_IDLE=y
CONFIG_SOC_SPI_MEM_SUPPORT_AUTO_SUSPEND=y
CONFIG_SOC_SPI_MEM_SUPPORT_AUTO_RESUME=y
CONFIG_SOC_SPI_MEM_SUPPORT_SW_SUSPEND=y
CONFIG_SOC_SPI_MEM_SUPPORT_OPI_MODE=y
CONFIG_SOC_SPI_MEM_SUPPORT_TIMING_TUNING=y
CONFIG_SOC_SPI_MEM_SUPPORT_CONFIG_GPIO_BY_EFUSE=y
CONFIG_SOC_SPI_MEM_SUPPORT_WRAP=y
CONFIG_SOC_MEMSPI_TIMING_TUNING_BY_MSPI_DELAY=y
CONFIG_SOC_MEMSPI_CORE_CLK_SHARED_WITH_PSRAM=y
CONFIG_SOC_COEX_HW_PTI=y
CONFIG_SOC_EXTERNAL_COEX_LEADER_TX_LINE=y
CONFIG_SOC_SDMMC_USE_GPIO_MATRIX=y
CONFIG_SOC_SDMMC_NUM_SLOTS=2
CONFIG_SOC_SDMMC_SUPPORT_XTAL_CLOCK=y
CONFIG_SOC_SDMMC_DELAY_PHASE_NUM=4
CONFIG_SOC_TEMPERATURE_SENSOR_SUPPORT_FAST_RC=y
CONFIG_SOC_WIFI_HW_TSF=y
CONFIG_SOC_WIFI_FTM_SUPPORT=y
CONFIG_SOC_WIFI_GCMP_SUPPORT=y
CONFIG_SOC_WIFI_WAPI_SUPPORT=y
CONFIG_SOC_WIFI_CSI_SUPPORT=y
CONFIG_SOC_WIFI_MESH_SUPPORT=y
CONFIG_SOC_WIFI_SUPPORT_VARIABLE_BEACON_WINDOW=y
CONFIG_SOC_WIFI_PHY_NEEDS_USB_WORKAROUND=y
CONFIG_SOC_BLE_SUPPORTED=y
CONFIG_SOC_BLE_MESH_SUPPORTED=y
CONFIG_SOC_BLE_50_SUPPORTED=y
CONFIG_SOC_BLE_DEVICE_PRIVACY_SUPPORTED=y
CONFIG_SOC_BLUFI_SUPPORTED=y
CONFIG_SOC_ULP_HAS_ADC=y
CONFIG_SOC_PHY_COMBO_MODULE=y
CONFIG_IDF_CMAKE=y
CONFIG_IDF_TOOLCHAIN="gcc"
CONFIG_IDF_TARGET_ARCH_XTENSA=y
CONFIG_IDF_TARGET_ARCH="xtensa"
CONFIG_IDF_TARGET="esp32s3"
CONFIG_IDF_INIT_VERSION="5.3.1"
CONFIG_IDF_TARGET_ESP32S3=y
CONFIG_IDF_FIRMWARE_CHIP_ID=0x0009
#
# Build type
#
CONFIG_APP_BUILD_TYPE_APP_2NDBOOT=y
# CONFIG_APP_BUILD_TYPE_RAM is not set
CONFIG_APP_BUILD_GENERATE_BINARIES=y
CONFIG_APP_BUILD_BOOTLOADER=y
CONFIG_APP_BUILD_USE_FLASH_SECTIONS=y
# CONFIG_APP_REPRODUCIBLE_BUILD is not set
# CONFIG_APP_NO_BLOBS is not set
# end of Build type
#
# Bootloader config
#
#
# Bootloader manager
#
CONFIG_BOOTLOADER_COMPILE_TIME_DATE=y
CONFIG_BOOTLOADER_PROJECT_VER=1
# end of Bootloader manager
CONFIG_BOOTLOADER_OFFSET_IN_FLASH=0x0
CONFIG_BOOTLOADER_COMPILER_OPTIMIZATION_SIZE=y
# CONFIG_BOOTLOADER_COMPILER_OPTIMIZATION_DEBUG is not set
# CONFIG_BOOTLOADER_COMPILER_OPTIMIZATION_PERF is not set
# CONFIG_BOOTLOADER_COMPILER_OPTIMIZATION_NONE is not set
# CONFIG_BOOTLOADER_LOG_LEVEL_NONE is not set
# CONFIG_BOOTLOADER_LOG_LEVEL_ERROR is not set
# CONFIG_BOOTLOADER_LOG_LEVEL_WARN is not set
CONFIG_BOOTLOADER_LOG_LEVEL_INFO=y
# CONFIG_BOOTLOADER_LOG_LEVEL_DEBUG is not set
# CONFIG_BOOTLOADER_LOG_LEVEL_VERBOSE is not set
CONFIG_BOOTLOADER_LOG_LEVEL=3
#
# Serial Flash Configurations
#
# CONFIG_BOOTLOADER_FLASH_DC_AWARE is not set
CONFIG_BOOTLOADER_FLASH_XMC_SUPPORT=y
# end of Serial Flash Configurations
CONFIG_BOOTLOADER_VDDSDIO_BOOST_1_9V=y
# CONFIG_BOOTLOADER_FACTORY_RESET is not set
# CONFIG_BOOTLOADER_APP_TEST is not set
CONFIG_BOOTLOADER_REGION_PROTECTION_ENABLE=y
CONFIG_BOOTLOADER_WDT_ENABLE=y
# CONFIG_BOOTLOADER_WDT_DISABLE_IN_USER_CODE is not set
CONFIG_BOOTLOADER_WDT_TIME_MS=9000
# CONFIG_BOOTLOADER_APP_ROLLBACK_ENABLE is not set
# CONFIG_BOOTLOADER_SKIP_VALIDATE_IN_DEEP_SLEEP is not set
# CONFIG_BOOTLOADER_SKIP_VALIDATE_ON_POWER_ON is not set
# CONFIG_BOOTLOADER_SKIP_VALIDATE_ALWAYS is not set
CONFIG_BOOTLOADER_RESERVE_RTC_SIZE=0
# CONFIG_BOOTLOADER_CUSTOM_RESERVE_RTC is not set
# end of Bootloader config
#
# Security features
#
CONFIG_SECURE_BOOT_V2_RSA_SUPPORTED=y
CONFIG_SECURE_BOOT_V2_PREFERRED=y
# CONFIG_SECURE_SIGNED_APPS_NO_SECURE_BOOT is not set
# CONFIG_SECURE_BOOT is not set
# CONFIG_SECURE_FLASH_ENC_ENABLED is not set
CONFIG_SECURE_ROM_DL_MODE_ENABLED=y
# end of Security features
#
# Application manager
#
CONFIG_APP_COMPILE_TIME_DATE=y
# CONFIG_APP_EXCLUDE_PROJECT_VER_VAR is not set
# CONFIG_APP_EXCLUDE_PROJECT_NAME_VAR is not set
# CONFIG_APP_PROJECT_VER_FROM_CONFIG is not set
CONFIG_APP_RETRIEVE_LEN_ELF_SHA=9
# end of Application manager
CONFIG_ESP_ROM_HAS_CRC_LE=y
CONFIG_ESP_ROM_HAS_CRC_BE=y
CONFIG_ESP_ROM_HAS_MZ_CRC32=y
CONFIG_ESP_ROM_HAS_JPEG_DECODE=y
CONFIG_ESP_ROM_UART_CLK_IS_XTAL=y
CONFIG_ESP_ROM_HAS_RETARGETABLE_LOCKING=y
CONFIG_ESP_ROM_USB_OTG_NUM=3
CONFIG_ESP_ROM_USB_SERIAL_DEVICE_NUM=4
CONFIG_ESP_ROM_HAS_ERASE_0_REGION_BUG=y
CONFIG_ESP_ROM_HAS_ENCRYPTED_WRITES_USING_LEGACY_DRV=y
CONFIG_ESP_ROM_GET_CLK_FREQ=y
CONFIG_ESP_ROM_HAS_HAL_WDT=y
CONFIG_ESP_ROM_NEEDS_SWSETUP_WORKAROUND=y
CONFIG_ESP_ROM_HAS_LAYOUT_TABLE=y
CONFIG_ESP_ROM_HAS_SPI_FLASH=y
CONFIG_ESP_ROM_HAS_ETS_PRINTF_BUG=y
CONFIG_ESP_ROM_HAS_NEWLIB=y
CONFIG_ESP_ROM_HAS_NEWLIB_NANO_FORMAT=y
CONFIG_ESP_ROM_HAS_NEWLIB_32BIT_TIME=y
CONFIG_ESP_ROM_NEEDS_SET_CACHE_MMU_SIZE=y
CONFIG_ESP_ROM_RAM_APP_NEEDS_MMU_INIT=y
CONFIG_ESP_ROM_HAS_FLASH_COUNT_PAGES_BUG=y
CONFIG_ESP_ROM_HAS_CACHE_SUSPEND_WAITI_BUG=y
CONFIG_ESP_ROM_HAS_CACHE_WRITEBACK_BUG=y
CONFIG_ESP_ROM_HAS_SW_FLOAT=y
CONFIG_ESP_ROM_HAS_VERSION=y
CONFIG_ESP_ROM_SUPPORT_DEEP_SLEEP_WAKEUP_STUB=y
#
# Boot ROM Behavior
#
CONFIG_BOOT_ROM_LOG_ALWAYS_ON=y
# CONFIG_BOOT_ROM_LOG_ALWAYS_OFF is not set
# CONFIG_BOOT_ROM_LOG_ON_GPIO_HIGH is not set
# CONFIG_BOOT_ROM_LOG_ON_GPIO_LOW is not set
# end of Boot ROM Behavior
#
# Serial flasher config
#
# CONFIG_ESPTOOLPY_NO_STUB is not set
# CONFIG_ESPTOOLPY_OCT_FLASH is not set
CONFIG_ESPTOOLPY_FLASH_MODE_AUTO_DETECT=y
# CONFIG_ESPTOOLPY_FLASHMODE_QIO is not set
# CONFIG_ESPTOOLPY_FLASHMODE_QOUT is not set
CONFIG_ESPTOOLPY_FLASHMODE_DIO=y
# CONFIG_ESPTOOLPY_FLASHMODE_DOUT is not set
CONFIG_ESPTOOLPY_FLASH_SAMPLE_MODE_STR=y
CONFIG_ESPTOOLPY_FLASHMODE="dio"
# CONFIG_ESPTOOLPY_FLASHFREQ_120M is not set
CONFIG_ESPTOOLPY_FLASHFREQ_80M=y
# CONFIG_ESPTOOLPY_FLASHFREQ_40M is not set
# CONFIG_ESPTOOLPY_FLASHFREQ_20M is not set
CONFIG_ESPTOOLPY_FLASHFREQ_80M_DEFAULT=y
CONFIG_ESPTOOLPY_FLASHFREQ="80m"
# CONFIG_ESPTOOLPY_FLASHSIZE_1MB is not set
# CONFIG_ESPTOOLPY_FLASHSIZE_2MB is not set
# CONFIG_ESPTOOLPY_FLASHSIZE_4MB is not set
# CONFIG_ESPTOOLPY_FLASHSIZE_8MB is not set
CONFIG_ESPTOOLPY_FLASHSIZE_16MB=y
# CONFIG_ESPTOOLPY_FLASHSIZE_32MB is not set
# CONFIG_ESPTOOLPY_FLASHSIZE_64MB is not set
# CONFIG_ESPTOOLPY_FLASHSIZE_128MB is not set
CONFIG_ESPTOOLPY_FLASHSIZE="16MB"
# CONFIG_ESPTOOLPY_HEADER_FLASHSIZE_UPDATE is not set
CONFIG_ESPTOOLPY_BEFORE_RESET=y
# CONFIG_ESPTOOLPY_BEFORE_NORESET is not set
CONFIG_ESPTOOLPY_BEFORE="default_reset"
CONFIG_ESPTOOLPY_AFTER_RESET=y
# CONFIG_ESPTOOLPY_AFTER_NORESET is not set
CONFIG_ESPTOOLPY_AFTER="hard_reset"
CONFIG_ESPTOOLPY_MONITOR_BAUD=115200
# end of Serial flasher config
#
# Partition Table
#
# CONFIG_PARTITION_TABLE_SINGLE_APP is not set
CONFIG_PARTITION_TABLE_SINGLE_APP_LARGE=y
# CONFIG_PARTITION_TABLE_TWO_OTA is not set
# CONFIG_PARTITION_TABLE_CUSTOM is not set
CONFIG_PARTITION_TABLE_CUSTOM_FILENAME="partitions.csv"
CONFIG_PARTITION_TABLE_FILENAME="partitions_singleapp_large.csv"
CONFIG_PARTITION_TABLE_OFFSET=0x8000
CONFIG_PARTITION_TABLE_MD5=y
# end of Partition Table
#
# Compiler options
#
CONFIG_COMPILER_OPTIMIZATION_DEBUG=y
# CONFIG_COMPILER_OPTIMIZATION_SIZE is not set
# CONFIG_COMPILER_OPTIMIZATION_PERF is not set
# CONFIG_COMPILER_OPTIMIZATION_NONE is not set
CONFIG_COMPILER_OPTIMIZATION_ASSERTIONS_ENABLE=y
# CONFIG_COMPILER_OPTIMIZATION_ASSERTIONS_SILENT is not set
# CONFIG_COMPILER_OPTIMIZATION_ASSERTIONS_DISABLE is not set
CONFIG_COMPILER_FLOAT_LIB_FROM_GCCLIB=y
CONFIG_COMPILER_OPTIMIZATION_ASSERTION_LEVEL=2
# CONFIG_COMPILER_OPTIMIZATION_CHECKS_SILENT is not set
CONFIG_COMPILER_HIDE_PATHS_MACROS=y
# CONFIG_COMPILER_CXX_EXCEPTIONS is not set
# CONFIG_COMPILER_CXX_RTTI is not set
CONFIG_COMPILER_STACK_CHECK_MODE_NONE=y
# CONFIG_COMPILER_STACK_CHECK_MODE_NORM is not set
# CONFIG_COMPILER_STACK_CHECK_MODE_STRONG is not set
# CONFIG_COMPILER_STACK_CHECK_MODE_ALL is not set
# CONFIG_COMPILER_WARN_WRITE_STRINGS is not set
# CONFIG_COMPILER_DISABLE_GCC12_WARNINGS is not set
# CONFIG_COMPILER_DISABLE_GCC13_WARNINGS is not set
# CONFIG_COMPILER_DUMP_RTL_FILES is not set
CONFIG_COMPILER_RT_LIB_GCCLIB=y
CONFIG_COMPILER_RT_LIB_NAME="gcc"
# CONFIG_COMPILER_ORPHAN_SECTIONS_WARNING is not set
CONFIG_COMPILER_ORPHAN_SECTIONS_PLACE=y
# end of Compiler options
#
# Component config
#
#
# Application Level Tracing
#
# CONFIG_APPTRACE_DEST_JTAG is not set
CONFIG_APPTRACE_DEST_NONE=y
# CONFIG_APPTRACE_DEST_UART1 is not set
# CONFIG_APPTRACE_DEST_UART2 is not set
# CONFIG_APPTRACE_DEST_USB_CDC is not set
CONFIG_APPTRACE_DEST_UART_NONE=y
CONFIG_APPTRACE_UART_TASK_PRIO=1
CONFIG_APPTRACE_LOCK_ENABLE=y
# end of Application Level Tracing
#
# Bluetooth
#
# CONFIG_BT_ENABLED is not set
CONFIG_BT_ALARM_MAX_NUM=50
# end of Bluetooth
#
# Console Library
#
# CONFIG_CONSOLE_SORTED_HELP is not set
# end of Console Library
#
# Driver Configurations
#
#
# TWAI Configuration
#
# CONFIG_TWAI_ISR_IN_IRAM is not set
CONFIG_TWAI_ERRATA_FIX_LISTEN_ONLY_DOM=y
# end of TWAI Configuration
#
# Legacy ADC Driver Configuration
#
# CONFIG_ADC_SUPPRESS_DEPRECATE_WARN is not set
#
# Legacy ADC Calibration Configuration
#
# CONFIG_ADC_CALI_SUPPRESS_DEPRECATE_WARN is not set
# end of Legacy ADC Calibration Configuration
# end of Legacy ADC Driver Configuration
#
# Legacy MCPWM Driver Configurations
#
# CONFIG_MCPWM_SUPPRESS_DEPRECATE_WARN is not set
# end of Legacy MCPWM Driver Configurations
#
# Legacy Timer Group Driver Configurations
#
# CONFIG_GPTIMER_SUPPRESS_DEPRECATE_WARN is not set
# end of Legacy Timer Group Driver Configurations
#
# Legacy RMT Driver Configurations
#
# CONFIG_RMT_SUPPRESS_DEPRECATE_WARN is not set
# end of Legacy RMT Driver Configurations
#
# Legacy I2S Driver Configurations
#
# CONFIG_I2S_SUPPRESS_DEPRECATE_WARN is not set
# end of Legacy I2S Driver Configurations
#
# Legacy PCNT Driver Configurations
#
# CONFIG_PCNT_SUPPRESS_DEPRECATE_WARN is not set
# end of Legacy PCNT Driver Configurations
#
# Legacy SDM Driver Configurations
#
# CONFIG_SDM_SUPPRESS_DEPRECATE_WARN is not set
# end of Legacy SDM Driver Configurations
#
# Legacy Temperature Sensor Driver Configurations
#
# CONFIG_TEMP_SENSOR_SUPPRESS_DEPRECATE_WARN is not set
# end of Legacy Temperature Sensor Driver Configurations
# end of Driver Configurations
#
# eFuse Bit Manager
#
# CONFIG_EFUSE_CUSTOM_TABLE is not set
# CONFIG_EFUSE_VIRTUAL is not set
CONFIG_EFUSE_MAX_BLK_LEN=256
# end of eFuse Bit Manager
#
# ESP-TLS
#
CONFIG_ESP_TLS_USING_MBEDTLS=y
CONFIG_ESP_TLS_USE_DS_PERIPHERAL=y
# CONFIG_ESP_TLS_CLIENT_SESSION_TICKETS is not set
# CONFIG_ESP_TLS_SERVER_SESSION_TICKETS is not set
# CONFIG_ESP_TLS_SERVER_CERT_SELECT_HOOK is not set
# CONFIG_ESP_TLS_SERVER_MIN_AUTH_MODE_OPTIONAL is not set
# CONFIG_ESP_TLS_PSK_VERIFICATION is not set
# CONFIG_ESP_TLS_INSECURE is not set
# end of ESP-TLS
#
# ADC and ADC Calibration
#
# CONFIG_ADC_ONESHOT_CTRL_FUNC_IN_IRAM is not set
# CONFIG_ADC_CONTINUOUS_ISR_IRAM_SAFE is not set
# CONFIG_ADC_CONTINUOUS_FORCE_USE_ADC2_ON_C3_S3 is not set
# CONFIG_ADC_ENABLE_DEBUG_LOG is not set
# end of ADC and ADC Calibration
#
# Wireless Coexistence
#
CONFIG_ESP_COEX_ENABLED=y
# CONFIG_ESP_COEX_EXTERNAL_COEXIST_ENABLE is not set
# end of Wireless Coexistence
#
# Common ESP-related
#
CONFIG_ESP_ERR_TO_NAME_LOOKUP=y
# end of Common ESP-related
#
# ESP-Driver:GPIO Configurations
#
# CONFIG_GPIO_CTRL_FUNC_IN_IRAM is not set
# end of ESP-Driver:GPIO Configurations
#
# ESP-Driver:GPTimer Configurations
#
CONFIG_GPTIMER_ISR_HANDLER_IN_IRAM=y
# CONFIG_GPTIMER_CTRL_FUNC_IN_IRAM is not set
# CONFIG_GPTIMER_ISR_IRAM_SAFE is not set
# CONFIG_GPTIMER_ENABLE_DEBUG_LOG is not set
# end of ESP-Driver:GPTimer Configurations
#
# ESP-Driver:I2C Configurations
#
# CONFIG_I2C_ISR_IRAM_SAFE is not set
# CONFIG_I2C_ENABLE_DEBUG_LOG is not set
# end of ESP-Driver:I2C Configurations
#
# ESP-Driver:I2S Configurations
#
# CONFIG_I2S_ISR_IRAM_SAFE is not set
# CONFIG_I2S_ENABLE_DEBUG_LOG is not set
# end of ESP-Driver:I2S Configurations
#
# ESP-Driver:LEDC Configurations
#
# CONFIG_LEDC_CTRL_FUNC_IN_IRAM is not set
# end of ESP-Driver:LEDC Configurations
#
# ESP-Driver:MCPWM Configurations
#
# CONFIG_MCPWM_ISR_IRAM_SAFE is not set
# CONFIG_MCPWM_CTRL_FUNC_IN_IRAM is not set
# CONFIG_MCPWM_ENABLE_DEBUG_LOG is not set
# end of ESP-Driver:MCPWM Configurations
#
# ESP-Driver:PCNT Configurations
#
# CONFIG_PCNT_CTRL_FUNC_IN_IRAM is not set
# CONFIG_PCNT_ISR_IRAM_SAFE is not set
# CONFIG_PCNT_ENABLE_DEBUG_LOG is not set
# end of ESP-Driver:PCNT Configurations
#
# ESP-Driver:RMT Configurations
#
# CONFIG_RMT_ISR_IRAM_SAFE is not set
# CONFIG_RMT_RECV_FUNC_IN_IRAM is not set
# CONFIG_RMT_ENABLE_DEBUG_LOG is not set
# end of ESP-Driver:RMT Configurations
#
# ESP-Driver:Sigma Delta Modulator Configurations
#
# CONFIG_SDM_CTRL_FUNC_IN_IRAM is not set
# CONFIG_SDM_ENABLE_DEBUG_LOG is not set
# end of ESP-Driver:Sigma Delta Modulator Configurations
#
# ESP-Driver:SPI Configurations
#
# CONFIG_SPI_MASTER_IN_IRAM is not set
CONFIG_SPI_MASTER_ISR_IN_IRAM=y
# CONFIG_SPI_SLAVE_IN_IRAM is not set
CONFIG_SPI_SLAVE_ISR_IN_IRAM=y
# end of ESP-Driver:SPI Configurations
#
# ESP-Driver:Touch Sensor Configurations
#
# CONFIG_TOUCH_CTRL_FUNC_IN_IRAM is not set
# CONFIG_TOUCH_ISR_IRAM_SAFE is not set
# CONFIG_TOUCH_ENABLE_DEBUG_LOG is not set
# end of ESP-Driver:Touch Sensor Configurations
#
# ESP-Driver:Temperature Sensor Configurations
#
# CONFIG_TEMP_SENSOR_ENABLE_DEBUG_LOG is not set
# end of ESP-Driver:Temperature Sensor Configurations
#
# ESP-Driver:UART Configurations
#
# CONFIG_UART_ISR_IN_IRAM is not set
# end of ESP-Driver:UART Configurations
#
# ESP-Driver:USB Serial/JTAG Configuration
#
CONFIG_USJ_ENABLE_USB_SERIAL_JTAG=y
# end of ESP-Driver:USB Serial/JTAG Configuration
#
# Ethernet
#
CONFIG_ETH_ENABLED=y
CONFIG_ETH_USE_SPI_ETHERNET=y
# CONFIG_ETH_SPI_ETHERNET_DM9051 is not set
# CONFIG_ETH_SPI_ETHERNET_W5500 is not set
# CONFIG_ETH_SPI_ETHERNET_KSZ8851SNL is not set
# CONFIG_ETH_USE_OPENETH is not set
# CONFIG_ETH_TRANSMIT_MUTEX is not set
# end of Ethernet
#
# Event Loop Library
#
# CONFIG_ESP_EVENT_LOOP_PROFILING is not set
CONFIG_ESP_EVENT_POST_FROM_ISR=y
CONFIG_ESP_EVENT_POST_FROM_IRAM_ISR=y
# end of Event Loop Library
#
# GDB Stub
#
CONFIG_ESP_GDBSTUB_ENABLED=y
# CONFIG_ESP_SYSTEM_GDBSTUB_RUNTIME is not set
CONFIG_ESP_GDBSTUB_SUPPORT_TASKS=y
CONFIG_ESP_GDBSTUB_MAX_TASKS=32
# end of GDB Stub
#
# ESP HTTP client
#
CONFIG_ESP_HTTP_CLIENT_ENABLE_HTTPS=y
# CONFIG_ESP_HTTP_CLIENT_ENABLE_BASIC_AUTH is not set
# CONFIG_ESP_HTTP_CLIENT_ENABLE_DIGEST_AUTH is not set
# CONFIG_ESP_HTTP_CLIENT_ENABLE_CUSTOM_TRANSPORT is not set
# end of ESP HTTP client
#
# HTTP Server
#
CONFIG_HTTPD_MAX_REQ_HDR_LEN=512
CONFIG_HTTPD_MAX_URI_LEN=512
CONFIG_HTTPD_ERR_RESP_NO_DELAY=y
CONFIG_HTTPD_PURGE_BUF_LEN=32
# CONFIG_HTTPD_LOG_PURGE_DATA is not set
# CONFIG_HTTPD_WS_SUPPORT is not set
# CONFIG_HTTPD_QUEUE_WORK_BLOCKING is not set
# end of HTTP Server
#
# ESP HTTPS OTA
#
# CONFIG_ESP_HTTPS_OTA_DECRYPT_CB is not set
# CONFIG_ESP_HTTPS_OTA_ALLOW_HTTP is not set
# end of ESP HTTPS OTA
#
# ESP HTTPS server
#
# CONFIG_ESP_HTTPS_SERVER_ENABLE is not set
# end of ESP HTTPS server
#
# Hardware Settings
#
#
# Chip revision
#
CONFIG_ESP32S3_REV_MIN_0=y
# CONFIG_ESP32S3_REV_MIN_1 is not set
# CONFIG_ESP32S3_REV_MIN_2 is not set
CONFIG_ESP32S3_REV_MIN_FULL=0
CONFIG_ESP_REV_MIN_FULL=0
#
# Maximum Supported ESP32-S3 Revision (Rev v0.99)
#
CONFIG_ESP32S3_REV_MAX_FULL=99
CONFIG_ESP_REV_MAX_FULL=99
# end of Chip revision
#
# MAC Config
#
CONFIG_ESP_MAC_ADDR_UNIVERSE_WIFI_STA=y
CONFIG_ESP_MAC_ADDR_UNIVERSE_WIFI_AP=y
CONFIG_ESP_MAC_ADDR_UNIVERSE_BT=y
CONFIG_ESP_MAC_ADDR_UNIVERSE_ETH=y
CONFIG_ESP_MAC_UNIVERSAL_MAC_ADDRESSES_FOUR=y
CONFIG_ESP_MAC_UNIVERSAL_MAC_ADDRESSES=4
# CONFIG_ESP32S3_UNIVERSAL_MAC_ADDRESSES_TWO is not set
CONFIG_ESP32S3_UNIVERSAL_MAC_ADDRESSES_FOUR=y
CONFIG_ESP32S3_UNIVERSAL_MAC_ADDRESSES=4
# CONFIG_ESP_MAC_USE_CUSTOM_MAC_AS_BASE_MAC is not set
# end of MAC Config
#
# Sleep Config
#
CONFIG_ESP_SLEEP_FLASH_LEAKAGE_WORKAROUND=y
CONFIG_ESP_SLEEP_PSRAM_LEAKAGE_WORKAROUND=y
CONFIG_ESP_SLEEP_MSPI_NEED_ALL_IO_PU=y
CONFIG_ESP_SLEEP_RTC_BUS_ISO_WORKAROUND=y
CONFIG_ESP_SLEEP_GPIO_RESET_WORKAROUND=y
CONFIG_ESP_SLEEP_WAIT_FLASH_READY_EXTRA_DELAY=2000
# CONFIG_ESP_SLEEP_CACHE_SAFE_ASSERTION is not set
# CONFIG_ESP_SLEEP_DEBUG is not set
CONFIG_ESP_SLEEP_GPIO_ENABLE_INTERNAL_RESISTORS=y
# end of Sleep Config
#
# RTC Clock Config
#
CONFIG_RTC_CLK_SRC_INT_RC=y
# CONFIG_RTC_CLK_SRC_EXT_CRYS is not set
# CONFIG_RTC_CLK_SRC_EXT_OSC is not set
# CONFIG_RTC_CLK_SRC_INT_8MD256 is not set
CONFIG_RTC_CLK_CAL_CYCLES=1024
# end of RTC Clock Config
#
# Peripheral Control
#
CONFIG_PERIPH_CTRL_FUNC_IN_IRAM=y
# end of Peripheral Control
#
# GDMA Configurations
#
CONFIG_GDMA_CTRL_FUNC_IN_IRAM=y
# CONFIG_GDMA_ISR_IRAM_SAFE is not set
# CONFIG_GDMA_ENABLE_DEBUG_LOG is not set
# end of GDMA Configurations
#
# Main XTAL Config
#
CONFIG_XTAL_FREQ_40=y
CONFIG_XTAL_FREQ=40
# end of Main XTAL Config
CONFIG_ESP_SPI_BUS_LOCK_ISR_FUNCS_IN_IRAM=y
# end of Hardware Settings
#
# LCD and Touch Panel
#
#
# LCD Touch Drivers are maintained in the IDF Component Registry
#
#
# LCD Peripheral Configuration
#
CONFIG_LCD_PANEL_IO_FORMAT_BUF_SIZE=32
# CONFIG_LCD_ENABLE_DEBUG_LOG is not set
# CONFIG_LCD_RGB_ISR_IRAM_SAFE is not set
# CONFIG_LCD_RGB_RESTART_IN_VSYNC is not set
# end of LCD Peripheral Configuration
# end of LCD and Touch Panel
#
# ESP NETIF Adapter
#
CONFIG_ESP_NETIF_IP_LOST_TIMER_INTERVAL=120
CONFIG_ESP_NETIF_TCPIP_LWIP=y
# CONFIG_ESP_NETIF_LOOPBACK is not set
CONFIG_ESP_NETIF_USES_TCPIP_WITH_BSD_API=y
# CONFIG_ESP_NETIF_RECEIVE_REPORT_ERRORS is not set
# CONFIG_ESP_NETIF_L2_TAP is not set
# CONFIG_ESP_NETIF_BRIDGE_EN is not set
# end of ESP NETIF Adapter
#
# Partition API Configuration
#
# end of Partition API Configuration
#
# PHY
#
CONFIG_ESP_PHY_ENABLED=y
CONFIG_ESP_PHY_CALIBRATION_AND_DATA_STORAGE=y
# CONFIG_ESP_PHY_INIT_DATA_IN_PARTITION is not set
CONFIG_ESP_PHY_MAX_WIFI_TX_POWER=20
CONFIG_ESP_PHY_MAX_TX_POWER=20
# CONFIG_ESP_PHY_REDUCE_TX_POWER is not set
CONFIG_ESP_PHY_ENABLE_USB=y
# CONFIG_ESP_PHY_ENABLE_CERT_TEST is not set
CONFIG_ESP_PHY_RF_CAL_PARTIAL=y
# CONFIG_ESP_PHY_RF_CAL_NONE is not set
# CONFIG_ESP_PHY_RF_CAL_FULL is not set
CONFIG_ESP_PHY_CALIBRATION_MODE=0
# CONFIG_ESP_PHY_PLL_TRACK_DEBUG is not set
# end of PHY
#
# Power Management
#
# CONFIG_PM_ENABLE is not set
CONFIG_PM_POWER_DOWN_CPU_IN_LIGHT_SLEEP=y
CONFIG_PM_RESTORE_CACHE_TAGMEM_AFTER_LIGHT_SLEEP=y
# end of Power Management
#
# ESP PSRAM
#
CONFIG_SPIRAM=y
#
# SPI RAM config
#
# CONFIG_SPIRAM_MODE_QUAD is not set
CONFIG_SPIRAM_MODE_OCT=y
CONFIG_SPIRAM_TYPE_AUTO=y
# CONFIG_SPIRAM_TYPE_ESPPSRAM64 is not set
CONFIG_SPIRAM_ALLOW_STACK_EXTERNAL_MEMORY=y
CONFIG_SPIRAM_CLK_IO=30
CONFIG_SPIRAM_CS_IO=26
# CONFIG_SPIRAM_XIP_FROM_PSRAM is not set
# CONFIG_SPIRAM_FETCH_INSTRUCTIONS is not set
# CONFIG_SPIRAM_RODATA is not set
# CONFIG_SPIRAM_SPEED_80M is not set
CONFIG_SPIRAM_SPEED_40M=y
CONFIG_SPIRAM_SPEED=40
# CONFIG_SPIRAM_ECC_ENABLE is not set
CONFIG_SPIRAM_BOOT_INIT=y
# CONFIG_SPIRAM_IGNORE_NOTFOUND is not set
# CONFIG_SPIRAM_USE_MEMMAP is not set
# CONFIG_SPIRAM_USE_CAPS_ALLOC is not set
CONFIG_SPIRAM_USE_MALLOC=y
CONFIG_SPIRAM_MEMTEST=y
CONFIG_SPIRAM_MALLOC_ALWAYSINTERNAL=16384
# CONFIG_SPIRAM_TRY_ALLOCATE_WIFI_LWIP is not set
CONFIG_SPIRAM_MALLOC_RESERVE_INTERNAL=32768
# CONFIG_SPIRAM_ALLOW_BSS_SEG_EXTERNAL_MEMORY is not set
# end of SPI RAM config
# end of ESP PSRAM
#
# ESP Ringbuf
#
# CONFIG_RINGBUF_PLACE_FUNCTIONS_INTO_FLASH is not set
# end of ESP Ringbuf
#
# ESP System Settings
#
# CONFIG_ESP_DEFAULT_CPU_FREQ_MHZ_80 is not set
# CONFIG_ESP_DEFAULT_CPU_FREQ_MHZ_160 is not set
CONFIG_ESP_DEFAULT_CPU_FREQ_MHZ_240=y
CONFIG_ESP_DEFAULT_CPU_FREQ_MHZ=240
#
# Cache config
#
CONFIG_ESP32S3_INSTRUCTION_CACHE_16KB=y
# CONFIG_ESP32S3_INSTRUCTION_CACHE_32KB is not set
CONFIG_ESP32S3_INSTRUCTION_CACHE_SIZE=0x4000
# CONFIG_ESP32S3_INSTRUCTION_CACHE_4WAYS is not set
CONFIG_ESP32S3_INSTRUCTION_CACHE_8WAYS=y
CONFIG_ESP32S3_ICACHE_ASSOCIATED_WAYS=8
# CONFIG_ESP32S3_INSTRUCTION_CACHE_LINE_16B is not set
CONFIG_ESP32S3_INSTRUCTION_CACHE_LINE_32B=y
CONFIG_ESP32S3_INSTRUCTION_CACHE_LINE_SIZE=32
# CONFIG_ESP32S3_DATA_CACHE_16KB is not set
CONFIG_ESP32S3_DATA_CACHE_32KB=y
# CONFIG_ESP32S3_DATA_CACHE_64KB is not set
CONFIG_ESP32S3_DATA_CACHE_SIZE=0x8000
# CONFIG_ESP32S3_DATA_CACHE_4WAYS is not set
CONFIG_ESP32S3_DATA_CACHE_8WAYS=y
CONFIG_ESP32S3_DCACHE_ASSOCIATED_WAYS=8
# CONFIG_ESP32S3_DATA_CACHE_LINE_16B is not set
# CONFIG_ESP32S3_DATA_CACHE_LINE_32B is not set
CONFIG_ESP32S3_DATA_CACHE_LINE_64B=y
CONFIG_ESP32S3_DATA_CACHE_LINE_SIZE=64
# end of Cache config
#
# Memory
#
# CONFIG_ESP32S3_RTCDATA_IN_FAST_MEM is not set
# CONFIG_ESP32S3_USE_FIXED_STATIC_RAM_SIZE is not set
# end of Memory
#
# Trace memory
#
# CONFIG_ESP32S3_TRAX is not set
CONFIG_ESP32S3_TRACEMEM_RESERVE_DRAM=0x0
# end of Trace memory
# CONFIG_ESP_SYSTEM_PANIC_PRINT_HALT is not set
CONFIG_ESP_SYSTEM_PANIC_PRINT_REBOOT=y
# CONFIG_ESP_SYSTEM_PANIC_SILENT_REBOOT is not set
# CONFIG_ESP_SYSTEM_PANIC_GDBSTUB is not set
CONFIG_ESP_SYSTEM_PANIC_REBOOT_DELAY_SECONDS=0
CONFIG_ESP_SYSTEM_RTC_FAST_MEM_AS_HEAP_DEPCHECK=y
CONFIG_ESP_SYSTEM_ALLOW_RTC_FAST_MEM_AS_HEAP=y
#
# Memory protection
#
CONFIG_ESP_SYSTEM_MEMPROT_FEATURE=y
CONFIG_ESP_SYSTEM_MEMPROT_FEATURE_LOCK=y
# end of Memory protection
CONFIG_ESP_SYSTEM_EVENT_QUEUE_SIZE=32
CONFIG_ESP_SYSTEM_EVENT_TASK_STACK_SIZE=2304
CONFIG_ESP_MAIN_TASK_STACK_SIZE=10240
CONFIG_ESP_MAIN_TASK_AFFINITY_CPU0=y
# CONFIG_ESP_MAIN_TASK_AFFINITY_CPU1 is not set
# CONFIG_ESP_MAIN_TASK_AFFINITY_NO_AFFINITY is not set
CONFIG_ESP_MAIN_TASK_AFFINITY=0x0
CONFIG_ESP_MINIMAL_SHARED_STACK_SIZE=2048
CONFIG_ESP_CONSOLE_UART_DEFAULT=y
# CONFIG_ESP_CONSOLE_USB_CDC is not set
# CONFIG_ESP_CONSOLE_USB_SERIAL_JTAG is not set
# CONFIG_ESP_CONSOLE_UART_CUSTOM is not set
# CONFIG_ESP_CONSOLE_NONE is not set
# CONFIG_ESP_CONSOLE_SECONDARY_NONE is not set
CONFIG_ESP_CONSOLE_SECONDARY_USB_SERIAL_JTAG=y
CONFIG_ESP_CONSOLE_USB_SERIAL_JTAG_ENABLED=y
CONFIG_ESP_CONSOLE_UART=y
CONFIG_ESP_CONSOLE_UART_NUM=0
CONFIG_ESP_CONSOLE_ROM_SERIAL_PORT_NUM=0
CONFIG_ESP_CONSOLE_UART_BAUDRATE=115200
CONFIG_ESP_INT_WDT=y
CONFIG_ESP_INT_WDT_TIMEOUT_MS=300
CONFIG_ESP_INT_WDT_CHECK_CPU1=y
CONFIG_ESP_TASK_WDT_EN=y
CONFIG_ESP_TASK_WDT_INIT=y
# CONFIG_ESP_TASK_WDT_PANIC is not set
CONFIG_ESP_TASK_WDT_TIMEOUT_S=5
CONFIG_ESP_TASK_WDT_CHECK_IDLE_TASK_CPU0=y
CONFIG_ESP_TASK_WDT_CHECK_IDLE_TASK_CPU1=y
# CONFIG_ESP_PANIC_HANDLER_IRAM is not set
# CONFIG_ESP_DEBUG_STUBS_ENABLE is not set
CONFIG_ESP_DEBUG_OCDAWARE=y
CONFIG_ESP_SYSTEM_CHECK_INT_LEVEL_4=y
#
# Brownout Detector
#
CONFIG_ESP_BROWNOUT_DET=y
CONFIG_ESP_BROWNOUT_DET_LVL_SEL_7=y
# CONFIG_ESP_BROWNOUT_DET_LVL_SEL_6 is not set
# CONFIG_ESP_BROWNOUT_DET_LVL_SEL_5 is not set
# CONFIG_ESP_BROWNOUT_DET_LVL_SEL_4 is not set
# CONFIG_ESP_BROWNOUT_DET_LVL_SEL_3 is not set
# CONFIG_ESP_BROWNOUT_DET_LVL_SEL_2 is not set
# CONFIG_ESP_BROWNOUT_DET_LVL_SEL_1 is not set
CONFIG_ESP_BROWNOUT_DET_LVL=7
# end of Brownout Detector
CONFIG_ESP_SYSTEM_BROWNOUT_INTR=y
CONFIG_ESP_SYSTEM_BBPLL_RECALIB=y
# end of ESP System Settings
#
# IPC (Inter-Processor Call)
#
CONFIG_ESP_IPC_TASK_STACK_SIZE=1280
CONFIG_ESP_IPC_USES_CALLERS_PRIORITY=y
CONFIG_ESP_IPC_ISR_ENABLE=y
# end of IPC (Inter-Processor Call)
#
# ESP Timer (High Resolution Timer)
#
# CONFIG_ESP_TIMER_PROFILING is not set
CONFIG_ESP_TIME_FUNCS_USE_RTC_TIMER=y
CONFIG_ESP_TIME_FUNCS_USE_ESP_TIMER=y
CONFIG_ESP_TIMER_TASK_STACK_SIZE=3584
CONFIG_ESP_TIMER_INTERRUPT_LEVEL=1
# CONFIG_ESP_TIMER_SHOW_EXPERIMENTAL is not set
CONFIG_ESP_TIMER_TASK_AFFINITY=0x0
CONFIG_ESP_TIMER_TASK_AFFINITY_CPU0=y
CONFIG_ESP_TIMER_ISR_AFFINITY_CPU0=y
# CONFIG_ESP_TIMER_SUPPORTS_ISR_DISPATCH_METHOD is not set
CONFIG_ESP_TIMER_IMPL_SYSTIMER=y
# end of ESP Timer (High Resolution Timer)
#
# Wi-Fi
#
CONFIG_ESP_WIFI_ENABLED=y
CONFIG_ESP_WIFI_STATIC_RX_BUFFER_NUM=10
CONFIG_ESP_WIFI_DYNAMIC_RX_BUFFER_NUM=32
CONFIG_ESP_WIFI_STATIC_TX_BUFFER=y
CONFIG_ESP_WIFI_TX_BUFFER_TYPE=0
CONFIG_ESP_WIFI_STATIC_TX_BUFFER_NUM=16
CONFIG_ESP_WIFI_CACHE_TX_BUFFER_NUM=32
CONFIG_ESP_WIFI_STATIC_RX_MGMT_BUFFER=y
# CONFIG_ESP_WIFI_DYNAMIC_RX_MGMT_BUFFER is not set
CONFIG_ESP_WIFI_DYNAMIC_RX_MGMT_BUF=0
CONFIG_ESP_WIFI_RX_MGMT_BUF_NUM_DEF=5
# CONFIG_ESP_WIFI_CSI_ENABLED is not set
CONFIG_ESP_WIFI_AMPDU_TX_ENABLED=y
CONFIG_ESP_WIFI_TX_BA_WIN=6
CONFIG_ESP_WIFI_AMPDU_RX_ENABLED=y
CONFIG_ESP_WIFI_RX_BA_WIN=6
# CONFIG_ESP_WIFI_AMSDU_TX_ENABLED is not set
CONFIG_ESP_WIFI_NVS_ENABLED=y
CONFIG_ESP_WIFI_TASK_PINNED_TO_CORE_0=y
# CONFIG_ESP_WIFI_TASK_PINNED_TO_CORE_1 is not set
CONFIG_ESP_WIFI_SOFTAP_BEACON_MAX_LEN=752
CONFIG_ESP_WIFI_MGMT_SBUF_NUM=32
CONFIG_ESP_WIFI_IRAM_OPT=y
# CONFIG_ESP_WIFI_EXTRA_IRAM_OPT is not set
CONFIG_ESP_WIFI_RX_IRAM_OPT=y
CONFIG_ESP_WIFI_ENABLE_WPA3_SAE=y
CONFIG_ESP_WIFI_ENABLE_SAE_PK=y
CONFIG_ESP_WIFI_SOFTAP_SAE_SUPPORT=y
CONFIG_ESP_WIFI_ENABLE_WPA3_OWE_STA=y
# CONFIG_ESP_WIFI_SLP_IRAM_OPT is not set
CONFIG_ESP_WIFI_SLP_DEFAULT_MIN_ACTIVE_TIME=50
CONFIG_ESP_WIFI_SLP_DEFAULT_MAX_ACTIVE_TIME=10
CONFIG_ESP_WIFI_SLP_DEFAULT_WAIT_BROADCAST_DATA_TIME=15
# CONFIG_ESP_WIFI_FTM_ENABLE is not set
CONFIG_ESP_WIFI_STA_DISCONNECTED_PM_ENABLE=y
# CONFIG_ESP_WIFI_GCMP_SUPPORT is not set
CONFIG_ESP_WIFI_GMAC_SUPPORT=y
CONFIG_ESP_WIFI_SOFTAP_SUPPORT=y
# CONFIG_ESP_WIFI_SLP_BEACON_LOST_OPT is not set
CONFIG_ESP_WIFI_ESPNOW_MAX_ENCRYPT_NUM=7
CONFIG_ESP_WIFI_MBEDTLS_CRYPTO=y
CONFIG_ESP_WIFI_MBEDTLS_TLS_CLIENT=y
# CONFIG_ESP_WIFI_WAPI_PSK is not set
# CONFIG_ESP_WIFI_SUITE_B_192 is not set
# CONFIG_ESP_WIFI_11KV_SUPPORT is not set
# CONFIG_ESP_WIFI_MBO_SUPPORT is not set
# CONFIG_ESP_WIFI_DPP_SUPPORT is not set
# CONFIG_ESP_WIFI_11R_SUPPORT is not set
# CONFIG_ESP_WIFI_WPS_SOFTAP_REGISTRAR is not set
#
# WPS Configuration Options
#
# CONFIG_ESP_WIFI_WPS_STRICT is not set
# CONFIG_ESP_WIFI_WPS_PASSPHRASE is not set
# end of WPS Configuration Options
# CONFIG_ESP_WIFI_DEBUG_PRINT is not set
# CONFIG_ESP_WIFI_TESTING_OPTIONS is not set
CONFIG_ESP_WIFI_ENTERPRISE_SUPPORT=y
# CONFIG_ESP_WIFI_ENT_FREE_DYNAMIC_BUFFER is not set
# end of Wi-Fi
#
# Core dump
#
# CONFIG_ESP_COREDUMP_ENABLE_TO_FLASH is not set
# CONFIG_ESP_COREDUMP_ENABLE_TO_UART is not set
CONFIG_ESP_COREDUMP_ENABLE_TO_NONE=y
# end of Core dump
#
# FAT Filesystem support
#
CONFIG_FATFS_VOLUME_COUNT=2
CONFIG_FATFS_LFN_NONE=y
# CONFIG_FATFS_LFN_HEAP is not set
# CONFIG_FATFS_LFN_STACK is not set
# CONFIG_FATFS_SECTOR_512 is not set
CONFIG_FATFS_SECTOR_4096=y
# CONFIG_FATFS_CODEPAGE_DYNAMIC is not set
CONFIG_FATFS_CODEPAGE_437=y
# CONFIG_FATFS_CODEPAGE_720 is not set
# CONFIG_FATFS_CODEPAGE_737 is not set
# CONFIG_FATFS_CODEPAGE_771 is not set
# CONFIG_FATFS_CODEPAGE_775 is not set
# CONFIG_FATFS_CODEPAGE_850 is not set
# CONFIG_FATFS_CODEPAGE_852 is not set
# CONFIG_FATFS_CODEPAGE_855 is not set
# CONFIG_FATFS_CODEPAGE_857 is not set
# CONFIG_FATFS_CODEPAGE_860 is not set
# CONFIG_FATFS_CODEPAGE_861 is not set
# CONFIG_FATFS_CODEPAGE_862 is not set
# CONFIG_FATFS_CODEPAGE_863 is not set
# CONFIG_FATFS_CODEPAGE_864 is not set
# CONFIG_FATFS_CODEPAGE_865 is not set
# CONFIG_FATFS_CODEPAGE_866 is not set
# CONFIG_FATFS_CODEPAGE_869 is not set
# CONFIG_FATFS_CODEPAGE_932 is not set
# CONFIG_FATFS_CODEPAGE_936 is not set
# CONFIG_FATFS_CODEPAGE_949 is not set
# CONFIG_FATFS_CODEPAGE_950 is not set
CONFIG_FATFS_CODEPAGE=437
CONFIG_FATFS_FS_LOCK=0
CONFIG_FATFS_TIMEOUT_MS=10000
CONFIG_FATFS_PER_FILE_CACHE=y
CONFIG_FATFS_ALLOC_PREFER_EXTRAM=y
# CONFIG_FATFS_USE_FASTSEEK is not set
CONFIG_FATFS_VFS_FSTAT_BLKSIZE=0
# CONFIG_FATFS_IMMEDIATE_FSYNC is not set
# CONFIG_FATFS_USE_LABEL is not set
CONFIG_FATFS_LINK_LOCK=y
# end of FAT Filesystem support
#
# FreeRTOS
#
#
# Kernel
#
# CONFIG_FREERTOS_SMP is not set
# CONFIG_FREERTOS_UNICORE is not set
CONFIG_FREERTOS_HZ=100
# CONFIG_FREERTOS_CHECK_STACKOVERFLOW_NONE is not set
# CONFIG_FREERTOS_CHECK_STACKOVERFLOW_PTRVAL is not set
CONFIG_FREERTOS_CHECK_STACKOVERFLOW_CANARY=y
CONFIG_FREERTOS_THREAD_LOCAL_STORAGE_POINTERS=1
CONFIG_FREERTOS_IDLE_TASK_STACKSIZE=1536
# CONFIG_FREERTOS_USE_IDLE_HOOK is not set
# CONFIG_FREERTOS_USE_TICK_HOOK is not set
CONFIG_FREERTOS_MAX_TASK_NAME_LEN=16
# CONFIG_FREERTOS_ENABLE_BACKWARD_COMPATIBILITY is not set
CONFIG_FREERTOS_TIMER_SERVICE_TASK_NAME="Tmr Svc"
# CONFIG_FREERTOS_TIMER_TASK_AFFINITY_CPU0 is not set
# CONFIG_FREERTOS_TIMER_TASK_AFFINITY_CPU1 is not set
CONFIG_FREERTOS_TIMER_TASK_NO_AFFINITY=y
CONFIG_FREERTOS_TIMER_SERVICE_TASK_CORE_AFFINITY=0x7FFFFFFF
CONFIG_FREERTOS_TIMER_TASK_PRIORITY=1
CONFIG_FREERTOS_TIMER_TASK_STACK_DEPTH=2048
CONFIG_FREERTOS_TIMER_QUEUE_LENGTH=10
CONFIG_FREERTOS_QUEUE_REGISTRY_SIZE=0
CONFIG_FREERTOS_TASK_NOTIFICATION_ARRAY_ENTRIES=1
# CONFIG_FREERTOS_USE_TRACE_FACILITY is not set
# CONFIG_FREERTOS_USE_LIST_DATA_INTEGRITY_CHECK_BYTES is not set
# CONFIG_FREERTOS_GENERATE_RUN_TIME_STATS is not set
# CONFIG_FREERTOS_USE_APPLICATION_TASK_TAG is not set
# end of Kernel
#
# Port
#
CONFIG_FREERTOS_TASK_FUNCTION_WRAPPER=y
# CONFIG_FREERTOS_WATCHPOINT_END_OF_STACK is not set
CONFIG_FREERTOS_TLSP_DELETION_CALLBACKS=y
# CONFIG_FREERTOS_TASK_PRE_DELETION_HOOK is not set
# CONFIG_FREERTOS_ENABLE_STATIC_TASK_CLEAN_UP is not set
CONFIG_FREERTOS_CHECK_MUTEX_GIVEN_BY_OWNER=y
CONFIG_FREERTOS_ISR_STACKSIZE=1536
CONFIG_FREERTOS_INTERRUPT_BACKTRACE=y
CONFIG_FREERTOS_TICK_SUPPORT_SYSTIMER=y
CONFIG_FREERTOS_CORETIMER_SYSTIMER_LVL1=y
# CONFIG_FREERTOS_CORETIMER_SYSTIMER_LVL3 is not set
CONFIG_FREERTOS_SYSTICK_USES_SYSTIMER=y
# CONFIG_FREERTOS_PLACE_FUNCTIONS_INTO_FLASH is not set
# CONFIG_FREERTOS_CHECK_PORT_CRITICAL_COMPLIANCE is not set
# end of Port
CONFIG_FREERTOS_PORT=y
CONFIG_FREERTOS_NO_AFFINITY=0x7FFFFFFF
CONFIG_FREERTOS_SUPPORT_STATIC_ALLOCATION=y
CONFIG_FREERTOS_DEBUG_OCDAWARE=y
CONFIG_FREERTOS_ENABLE_TASK_SNAPSHOT=y
CONFIG_FREERTOS_PLACE_SNAPSHOT_FUNS_INTO_FLASH=y
CONFIG_FREERTOS_NUMBER_OF_CORES=2
# end of FreeRTOS
#
# Hardware Abstraction Layer (HAL) and Low Level (LL)
#
CONFIG_HAL_ASSERTION_EQUALS_SYSTEM=y
# CONFIG_HAL_ASSERTION_DISABLE is not set
# CONFIG_HAL_ASSERTION_SILENT is not set
# CONFIG_HAL_ASSERTION_ENABLE is not set
CONFIG_HAL_DEFAULT_ASSERTION_LEVEL=2
CONFIG_HAL_WDT_USE_ROM_IMPL=y
CONFIG_HAL_SPI_MASTER_FUNC_IN_IRAM=y
CONFIG_HAL_SPI_SLAVE_FUNC_IN_IRAM=y
# end of Hardware Abstraction Layer (HAL) and Low Level (LL)
#
# Heap memory debugging
#
CONFIG_HEAP_POISONING_DISABLED=y
# CONFIG_HEAP_POISONING_LIGHT is not set
# CONFIG_HEAP_POISONING_COMPREHENSIVE is not set
CONFIG_HEAP_TRACING_OFF=y
# CONFIG_HEAP_TRACING_STANDALONE is not set
# CONFIG_HEAP_TRACING_TOHOST is not set
# CONFIG_HEAP_USE_HOOKS is not set
# CONFIG_HEAP_TASK_TRACKING is not set
# CONFIG_HEAP_ABORT_WHEN_ALLOCATION_FAILS is not set
# CONFIG_HEAP_PLACE_FUNCTION_INTO_FLASH is not set
# end of Heap memory debugging
#
# Log output
#
# CONFIG_LOG_DEFAULT_LEVEL_NONE is not set
# CONFIG_LOG_DEFAULT_LEVEL_ERROR is not set
# CONFIG_LOG_DEFAULT_LEVEL_WARN is not set
CONFIG_LOG_DEFAULT_LEVEL_INFO=y
# CONFIG_LOG_DEFAULT_LEVEL_DEBUG is not set
# CONFIG_LOG_DEFAULT_LEVEL_VERBOSE is not set
CONFIG_LOG_DEFAULT_LEVEL=3
CONFIG_LOG_MAXIMUM_EQUALS_DEFAULT=y
# CONFIG_LOG_MAXIMUM_LEVEL_DEBUG is not set
# CONFIG_LOG_MAXIMUM_LEVEL_VERBOSE is not set
CONFIG_LOG_MAXIMUM_LEVEL=3
# CONFIG_LOG_MASTER_LEVEL is not set
CONFIG_LOG_COLORS=y
CONFIG_LOG_TIMESTAMP_SOURCE_RTOS=y
# CONFIG_LOG_TIMESTAMP_SOURCE_SYSTEM is not set
# end of Log output
#
# LWIP
#
CONFIG_LWIP_ENABLE=y
CONFIG_LWIP_LOCAL_HOSTNAME="espressif"
# CONFIG_LWIP_NETIF_API is not set
CONFIG_LWIP_TCPIP_TASK_PRIO=18
# CONFIG_LWIP_TCPIP_CORE_LOCKING is not set
# CONFIG_LWIP_CHECK_THREAD_SAFETY is not set
CONFIG_LWIP_DNS_SUPPORT_MDNS_QUERIES=y
# CONFIG_LWIP_L2_TO_L3_COPY is not set
# CONFIG_LWIP_IRAM_OPTIMIZATION is not set
# CONFIG_LWIP_EXTRA_IRAM_OPTIMIZATION is not set
CONFIG_LWIP_TIMERS_ONDEMAND=y
CONFIG_LWIP_ND6=y
# CONFIG_LWIP_FORCE_ROUTER_FORWARDING is not set
CONFIG_LWIP_MAX_SOCKETS=10
# CONFIG_LWIP_USE_ONLY_LWIP_SELECT is not set
# CONFIG_LWIP_SO_LINGER is not set
CONFIG_LWIP_SO_REUSE=y
CONFIG_LWIP_SO_REUSE_RXTOALL=y
# CONFIG_LWIP_SO_RCVBUF is not set
# CONFIG_LWIP_NETBUF_RECVINFO is not set
CONFIG_LWIP_IP_DEFAULT_TTL=64
CONFIG_LWIP_IP4_FRAG=y
CONFIG_LWIP_IP6_FRAG=y
# CONFIG_LWIP_IP4_REASSEMBLY is not set
# CONFIG_LWIP_IP6_REASSEMBLY is not set
CONFIG_LWIP_IP_REASS_MAX_PBUFS=10
# CONFIG_LWIP_IP_FORWARD is not set
# CONFIG_LWIP_STATS is not set
CONFIG_LWIP_ESP_GRATUITOUS_ARP=y
CONFIG_LWIP_GARP_TMR_INTERVAL=60
CONFIG_LWIP_ESP_MLDV6_REPORT=y
CONFIG_LWIP_MLDV6_TMR_INTERVAL=40
CONFIG_LWIP_TCPIP_RECVMBOX_SIZE=32
CONFIG_LWIP_DHCP_DOES_ARP_CHECK=y
# CONFIG_LWIP_DHCP_DISABLE_CLIENT_ID is not set
CONFIG_LWIP_DHCP_DISABLE_VENDOR_CLASS_ID=y
# CONFIG_LWIP_DHCP_RESTORE_LAST_IP is not set
CONFIG_LWIP_DHCP_OPTIONS_LEN=68
CONFIG_LWIP_NUM_NETIF_CLIENT_DATA=0
CONFIG_LWIP_DHCP_COARSE_TIMER_SECS=1
#
# DHCP server
#
CONFIG_LWIP_DHCPS=y
CONFIG_LWIP_DHCPS_LEASE_UNIT=60
CONFIG_LWIP_DHCPS_MAX_STATION_NUM=8
CONFIG_LWIP_DHCPS_STATIC_ENTRIES=y
# end of DHCP server
# CONFIG_LWIP_AUTOIP is not set
CONFIG_LWIP_IPV4=y
CONFIG_LWIP_IPV6=y
# CONFIG_LWIP_IPV6_AUTOCONFIG is not set
CONFIG_LWIP_IPV6_NUM_ADDRESSES=3
# CONFIG_LWIP_IPV6_FORWARD is not set
# CONFIG_LWIP_NETIF_STATUS_CALLBACK is not set
CONFIG_LWIP_NETIF_LOOPBACK=y
CONFIG_LWIP_LOOPBACK_MAX_PBUFS=8
#
# TCP
#
CONFIG_LWIP_MAX_ACTIVE_TCP=16
CONFIG_LWIP_MAX_LISTENING_TCP=16
CONFIG_LWIP_TCP_HIGH_SPEED_RETRANSMISSION=y
CONFIG_LWIP_TCP_MAXRTX=12
CONFIG_LWIP_TCP_SYNMAXRTX=12
CONFIG_LWIP_TCP_MSS=1440
CONFIG_LWIP_TCP_TMR_INTERVAL=250
CONFIG_LWIP_TCP_MSL=60000
CONFIG_LWIP_TCP_FIN_WAIT_TIMEOUT=20000
CONFIG_LWIP_TCP_SND_BUF_DEFAULT=5760
CONFIG_LWIP_TCP_WND_DEFAULT=5760
CONFIG_LWIP_TCP_RECVMBOX_SIZE=6
CONFIG_LWIP_TCP_ACCEPTMBOX_SIZE=6
CONFIG_LWIP_TCP_QUEUE_OOSEQ=y
CONFIG_LWIP_TCP_OOSEQ_TIMEOUT=6
CONFIG_LWIP_TCP_OOSEQ_MAX_PBUFS=4
# CONFIG_LWIP_TCP_SACK_OUT is not set
CONFIG_LWIP_TCP_OVERSIZE_MSS=y
# CONFIG_LWIP_TCP_OVERSIZE_QUARTER_MSS is not set
# CONFIG_LWIP_TCP_OVERSIZE_DISABLE is not set
CONFIG_LWIP_TCP_RTO_TIME=1500
# end of TCP
#
# UDP
#
CONFIG_LWIP_MAX_UDP_PCBS=16
CONFIG_LWIP_UDP_RECVMBOX_SIZE=6
# end of UDP
#
# Checksums
#
# CONFIG_LWIP_CHECKSUM_CHECK_IP is not set
# CONFIG_LWIP_CHECKSUM_CHECK_UDP is not set
CONFIG_LWIP_CHECKSUM_CHECK_ICMP=y
# end of Checksums
CONFIG_LWIP_TCPIP_TASK_STACK_SIZE=3072
CONFIG_LWIP_TCPIP_TASK_AFFINITY_NO_AFFINITY=y
# CONFIG_LWIP_TCPIP_TASK_AFFINITY_CPU0 is not set
# CONFIG_LWIP_TCPIP_TASK_AFFINITY_CPU1 is not set
CONFIG_LWIP_TCPIP_TASK_AFFINITY=0x7FFFFFFF
# CONFIG_LWIP_PPP_SUPPORT is not set
CONFIG_LWIP_IPV6_MEMP_NUM_ND6_QUEUE=3
CONFIG_LWIP_IPV6_ND6_NUM_NEIGHBORS=5
# CONFIG_LWIP_SLIP_SUPPORT is not set
#
# ICMP
#
CONFIG_LWIP_ICMP=y
# CONFIG_LWIP_MULTICAST_PING is not set
# CONFIG_LWIP_BROADCAST_PING is not set
# end of ICMP
#
# LWIP RAW API
#
CONFIG_LWIP_MAX_RAW_PCBS=16
# end of LWIP RAW API
#
# SNTP
#
CONFIG_LWIP_SNTP_MAX_SERVERS=1
# CONFIG_LWIP_DHCP_GET_NTP_SRV is not set
CONFIG_LWIP_SNTP_UPDATE_DELAY=3600000
CONFIG_LWIP_SNTP_STARTUP_DELAY=y
CONFIG_LWIP_SNTP_MAXIMUM_STARTUP_DELAY=5000
# end of SNTP
#
# DNS
#
CONFIG_LWIP_DNS_MAX_SERVERS=3
# CONFIG_LWIP_FALLBACK_DNS_SERVER_SUPPORT is not set
# end of DNS
CONFIG_LWIP_BRIDGEIF_MAX_PORTS=7
CONFIG_LWIP_ESP_LWIP_ASSERT=y
#
# Hooks
#
# CONFIG_LWIP_HOOK_TCP_ISN_NONE is not set
CONFIG_LWIP_HOOK_TCP_ISN_DEFAULT=y
# CONFIG_LWIP_HOOK_TCP_ISN_CUSTOM is not set
CONFIG_LWIP_HOOK_IP6_ROUTE_NONE=y
# CONFIG_LWIP_HOOK_IP6_ROUTE_DEFAULT is not set
# CONFIG_LWIP_HOOK_IP6_ROUTE_CUSTOM is not set
CONFIG_LWIP_HOOK_ND6_GET_GW_NONE=y
# CONFIG_LWIP_HOOK_ND6_GET_GW_DEFAULT is not set
# CONFIG_LWIP_HOOK_ND6_GET_GW_CUSTOM is not set
CONFIG_LWIP_HOOK_IP6_SELECT_SRC_ADDR_NONE=y
# CONFIG_LWIP_HOOK_IP6_SELECT_SRC_ADDR_DEFAULT is not set
# CONFIG_LWIP_HOOK_IP6_SELECT_SRC_ADDR_CUSTOM is not set
CONFIG_LWIP_HOOK_NETCONN_EXT_RESOLVE_NONE=y
# CONFIG_LWIP_HOOK_NETCONN_EXT_RESOLVE_DEFAULT is not set
# CONFIG_LWIP_HOOK_NETCONN_EXT_RESOLVE_CUSTOM is not set
CONFIG_LWIP_HOOK_IP6_INPUT_NONE=y
# CONFIG_LWIP_HOOK_IP6_INPUT_DEFAULT is not set
# CONFIG_LWIP_HOOK_IP6_INPUT_CUSTOM is not set
# end of Hooks
# CONFIG_LWIP_DEBUG is not set
# end of LWIP
#
# mbedTLS
#
# CONFIG_MBEDTLS_INTERNAL_MEM_ALLOC is not set
CONFIG_MBEDTLS_EXTERNAL_MEM_ALLOC=y
# CONFIG_MBEDTLS_DEFAULT_MEM_ALLOC is not set
# CONFIG_MBEDTLS_CUSTOM_MEM_ALLOC is not set
CONFIG_MBEDTLS_ASYMMETRIC_CONTENT_LEN=y
CONFIG_MBEDTLS_SSL_IN_CONTENT_LEN=16384
CONFIG_MBEDTLS_SSL_OUT_CONTENT_LEN=4096
# CONFIG_MBEDTLS_DYNAMIC_BUFFER is not set
# CONFIG_MBEDTLS_DEBUG is not set
#
# mbedTLS v3.x related
#
# CONFIG_MBEDTLS_SSL_PROTO_TLS1_3 is not set
# CONFIG_MBEDTLS_SSL_VARIABLE_BUFFER_LENGTH is not set
# CONFIG_MBEDTLS_X509_TRUSTED_CERT_CALLBACK is not set
# CONFIG_MBEDTLS_SSL_CONTEXT_SERIALIZATION is not set
CONFIG_MBEDTLS_SSL_KEEP_PEER_CERTIFICATE=y
CONFIG_MBEDTLS_PKCS7_C=y
# end of mbedTLS v3.x related
#
# Certificate Bundle
#
CONFIG_MBEDTLS_CERTIFICATE_BUNDLE=y
CONFIG_MBEDTLS_CERTIFICATE_BUNDLE_DEFAULT_FULL=y
# CONFIG_MBEDTLS_CERTIFICATE_BUNDLE_DEFAULT_CMN is not set
# CONFIG_MBEDTLS_CERTIFICATE_BUNDLE_DEFAULT_NONE is not set
# CONFIG_MBEDTLS_CUSTOM_CERTIFICATE_BUNDLE is not set
# CONFIG_MBEDTLS_CERTIFICATE_BUNDLE_DEPRECATED_LIST is not set
CONFIG_MBEDTLS_CERTIFICATE_BUNDLE_MAX_CERTS=200
# end of Certificate Bundle
# CONFIG_MBEDTLS_ECP_RESTARTABLE is not set
CONFIG_MBEDTLS_CMAC_C=y
CONFIG_MBEDTLS_HARDWARE_AES=y
CONFIG_MBEDTLS_AES_USE_INTERRUPT=y
CONFIG_MBEDTLS_AES_INTERRUPT_LEVEL=0
CONFIG_MBEDTLS_GCM_SUPPORT_NON_AES_CIPHER=y
CONFIG_MBEDTLS_HARDWARE_MPI=y
# CONFIG_MBEDTLS_LARGE_KEY_SOFTWARE_MPI is not set
CONFIG_MBEDTLS_MPI_USE_INTERRUPT=y
CONFIG_MBEDTLS_MPI_INTERRUPT_LEVEL=0
CONFIG_MBEDTLS_HARDWARE_SHA=y
CONFIG_MBEDTLS_ROM_MD5=y
# CONFIG_MBEDTLS_ATCA_HW_ECDSA_SIGN is not set
# CONFIG_MBEDTLS_ATCA_HW_ECDSA_VERIFY is not set
CONFIG_MBEDTLS_HAVE_TIME=y
# CONFIG_MBEDTLS_PLATFORM_TIME_ALT is not set
# CONFIG_MBEDTLS_HAVE_TIME_DATE is not set
CONFIG_MBEDTLS_ECDSA_DETERMINISTIC=y
CONFIG_MBEDTLS_SHA512_C=y
CONFIG_MBEDTLS_TLS_SERVER_AND_CLIENT=y
# CONFIG_MBEDTLS_TLS_SERVER_ONLY is not set
# CONFIG_MBEDTLS_TLS_CLIENT_ONLY is not set
# CONFIG_MBEDTLS_TLS_DISABLED is not set
CONFIG_MBEDTLS_TLS_SERVER=y
CONFIG_MBEDTLS_TLS_CLIENT=y
CONFIG_MBEDTLS_TLS_ENABLED=y
#
# TLS Key Exchange Methods
#
# CONFIG_MBEDTLS_PSK_MODES is not set
CONFIG_MBEDTLS_KEY_EXCHANGE_RSA=y
CONFIG_MBEDTLS_KEY_EXCHANGE_ELLIPTIC_CURVE=y
CONFIG_MBEDTLS_KEY_EXCHANGE_ECDHE_RSA=y
CONFIG_MBEDTLS_KEY_EXCHANGE_ECDHE_ECDSA=y
CONFIG_MBEDTLS_KEY_EXCHANGE_ECDH_ECDSA=y
CONFIG_MBEDTLS_KEY_EXCHANGE_ECDH_RSA=y
# end of TLS Key Exchange Methods
CONFIG_MBEDTLS_SSL_RENEGOTIATION=y
CONFIG_MBEDTLS_SSL_PROTO_TLS1_2=y
# CONFIG_MBEDTLS_SSL_PROTO_GMTSSL1_1 is not set
# CONFIG_MBEDTLS_SSL_PROTO_DTLS is not set
CONFIG_MBEDTLS_SSL_ALPN=y
CONFIG_MBEDTLS_CLIENT_SSL_SESSION_TICKETS=y
CONFIG_MBEDTLS_SERVER_SSL_SESSION_TICKETS=y
#
# Symmetric Ciphers
#
CONFIG_MBEDTLS_AES_C=y
# CONFIG_MBEDTLS_CAMELLIA_C is not set
# CONFIG_MBEDTLS_DES_C is not set
# CONFIG_MBEDTLS_BLOWFISH_C is not set
# CONFIG_MBEDTLS_XTEA_C is not set
CONFIG_MBEDTLS_CCM_C=y
CONFIG_MBEDTLS_GCM_C=y
# CONFIG_MBEDTLS_NIST_KW_C is not set
# end of Symmetric Ciphers
# CONFIG_MBEDTLS_RIPEMD160_C is not set
#
# Certificates
#
CONFIG_MBEDTLS_PEM_PARSE_C=y
CONFIG_MBEDTLS_PEM_WRITE_C=y
CONFIG_MBEDTLS_X509_CRL_PARSE_C=y
CONFIG_MBEDTLS_X509_CSR_PARSE_C=y
# end of Certificates
CONFIG_MBEDTLS_ECP_C=y
# CONFIG_MBEDTLS_DHM_C is not set
CONFIG_MBEDTLS_ECDH_C=y
CONFIG_MBEDTLS_ECDSA_C=y
# CONFIG_MBEDTLS_ECJPAKE_C is not set
CONFIG_MBEDTLS_ECP_DP_SECP192R1_ENABLED=y
CONFIG_MBEDTLS_ECP_DP_SECP224R1_ENABLED=y
CONFIG_MBEDTLS_ECP_DP_SECP256R1_ENABLED=y
CONFIG_MBEDTLS_ECP_DP_SECP384R1_ENABLED=y
CONFIG_MBEDTLS_ECP_DP_SECP521R1_ENABLED=y
CONFIG_MBEDTLS_ECP_DP_SECP192K1_ENABLED=y
CONFIG_MBEDTLS_ECP_DP_SECP224K1_ENABLED=y
CONFIG_MBEDTLS_ECP_DP_SECP256K1_ENABLED=y
CONFIG_MBEDTLS_ECP_DP_BP256R1_ENABLED=y
CONFIG_MBEDTLS_ECP_DP_BP384R1_ENABLED=y
CONFIG_MBEDTLS_ECP_DP_BP512R1_ENABLED=y
CONFIG_MBEDTLS_ECP_DP_CURVE25519_ENABLED=y
CONFIG_MBEDTLS_ECP_NIST_OPTIM=y
CONFIG_MBEDTLS_ECP_FIXED_POINT_OPTIM=y
# CONFIG_MBEDTLS_POLY1305_C is not set
# CONFIG_MBEDTLS_CHACHA20_C is not set
# CONFIG_MBEDTLS_HKDF_C is not set
# CONFIG_MBEDTLS_THREADING_C is not set
CONFIG_MBEDTLS_ERROR_STRINGS=y
# end of mbedTLS
#
# ESP-MQTT Configurations
#
CONFIG_MQTT_PROTOCOL_311=y
# CONFIG_MQTT_PROTOCOL_5 is not set
CONFIG_MQTT_TRANSPORT_SSL=y
CONFIG_MQTT_TRANSPORT_WEBSOCKET=y
CONFIG_MQTT_TRANSPORT_WEBSOCKET_SECURE=y
# CONFIG_MQTT_MSG_ID_INCREMENTAL is not set
# CONFIG_MQTT_SKIP_PUBLISH_IF_DISCONNECTED is not set
# CONFIG_MQTT_REPORT_DELETED_MESSAGES is not set
# CONFIG_MQTT_USE_CUSTOM_CONFIG is not set
# CONFIG_MQTT_TASK_CORE_SELECTION_ENABLED is not set
# CONFIG_MQTT_CUSTOM_OUTBOX is not set
# end of ESP-MQTT Configurations
#
# Newlib
#
CONFIG_NEWLIB_STDOUT_LINE_ENDING_CRLF=y
# CONFIG_NEWLIB_STDOUT_LINE_ENDING_LF is not set
# CONFIG_NEWLIB_STDOUT_LINE_ENDING_CR is not set
# CONFIG_NEWLIB_STDIN_LINE_ENDING_CRLF is not set
# CONFIG_NEWLIB_STDIN_LINE_ENDING_LF is not set
CONFIG_NEWLIB_STDIN_LINE_ENDING_CR=y
# CONFIG_NEWLIB_NANO_FORMAT is not set
CONFIG_NEWLIB_TIME_SYSCALL_USE_RTC_HRT=y
# CONFIG_NEWLIB_TIME_SYSCALL_USE_RTC is not set
# CONFIG_NEWLIB_TIME_SYSCALL_USE_HRT is not set
# CONFIG_NEWLIB_TIME_SYSCALL_USE_NONE is not set
# end of Newlib
CONFIG_STDATOMIC_S32C1I_SPIRAM_WORKAROUND=y
#
# NVS
#
# CONFIG_NVS_ENCRYPTION is not set
# CONFIG_NVS_ASSERT_ERROR_CHECK is not set
# CONFIG_NVS_LEGACY_DUP_KEYS_COMPATIBILITY is not set
# end of NVS
#
# OpenThread
#
# CONFIG_OPENTHREAD_ENABLED is not set
#
# Thread Operational Dataset
#
CONFIG_OPENTHREAD_NETWORK_NAME="OpenThread-ESP"
CONFIG_OPENTHREAD_MESH_LOCAL_PREFIX="fd00:db8:a0:0::/64"
CONFIG_OPENTHREAD_NETWORK_CHANNEL=15
CONFIG_OPENTHREAD_NETWORK_PANID=0x1234
CONFIG_OPENTHREAD_NETWORK_EXTPANID="dead00beef00cafe"
CONFIG_OPENTHREAD_NETWORK_MASTERKEY="00112233445566778899aabbccddeeff"
CONFIG_OPENTHREAD_NETWORK_PSKC="104810e2315100afd6bc9215a6bfac53"
# end of Thread Operational Dataset
CONFIG_OPENTHREAD_XTAL_ACCURACY=130
# CONFIG_OPENTHREAD_SPINEL_ONLY is not set
CONFIG_OPENTHREAD_RX_ON_WHEN_IDLE=y
#
# Thread Address Query Config
#
# end of Thread Address Query Config
# end of OpenThread
#
# Protocomm
#
CONFIG_ESP_PROTOCOMM_SUPPORT_SECURITY_VERSION_0=y
CONFIG_ESP_PROTOCOMM_SUPPORT_SECURITY_VERSION_1=y
CONFIG_ESP_PROTOCOMM_SUPPORT_SECURITY_VERSION_2=y
# end of Protocomm
#
# PThreads
#
CONFIG_PTHREAD_TASK_PRIO_DEFAULT=5
CONFIG_PTHREAD_TASK_STACK_SIZE_DEFAULT=3072
CONFIG_PTHREAD_STACK_MIN=768
CONFIG_PTHREAD_DEFAULT_CORE_NO_AFFINITY=y
# CONFIG_PTHREAD_DEFAULT_CORE_0 is not set
# CONFIG_PTHREAD_DEFAULT_CORE_1 is not set
CONFIG_PTHREAD_TASK_CORE_DEFAULT=-1
CONFIG_PTHREAD_TASK_NAME_DEFAULT="pthread"
# end of PThreads
#
# MMU Config
#
CONFIG_MMU_PAGE_SIZE_64KB=y
CONFIG_MMU_PAGE_MODE="64KB"
CONFIG_MMU_PAGE_SIZE=0x10000
# end of MMU Config
#
# Main Flash configuration
#
#
# SPI Flash behavior when brownout
#
CONFIG_SPI_FLASH_BROWNOUT_RESET_XMC=y
CONFIG_SPI_FLASH_BROWNOUT_RESET=y
# end of SPI Flash behavior when brownout
#
# Optional and Experimental Features (READ DOCS FIRST)
#
#
# Features here require specific hardware (READ DOCS FIRST!)
#
# CONFIG_SPI_FLASH_HPM_ENA is not set
CONFIG_SPI_FLASH_HPM_AUTO=y
# CONFIG_SPI_FLASH_HPM_DIS is not set
CONFIG_SPI_FLASH_HPM_ON=y
CONFIG_SPI_FLASH_HPM_DC_AUTO=y
# CONFIG_SPI_FLASH_HPM_DC_DISABLE is not set
CONFIG_SPI_FLASH_SUSPEND_QVL_SUPPORTED=y
# CONFIG_SPI_FLASH_AUTO_SUSPEND is not set
CONFIG_SPI_FLASH_SUSPEND_TSUS_VAL_US=50
# end of Optional and Experimental Features (READ DOCS FIRST)
# end of Main Flash configuration
#
# SPI Flash driver
#
# CONFIG_SPI_FLASH_VERIFY_WRITE is not set
# CONFIG_SPI_FLASH_ENABLE_COUNTERS is not set
CONFIG_SPI_FLASH_ROM_DRIVER_PATCH=y
# CONFIG_SPI_FLASH_ROM_IMPL is not set
CONFIG_SPI_FLASH_DANGEROUS_WRITE_ABORTS=y
# CONFIG_SPI_FLASH_DANGEROUS_WRITE_FAILS is not set
# CONFIG_SPI_FLASH_DANGEROUS_WRITE_ALLOWED is not set
# CONFIG_SPI_FLASH_BYPASS_BLOCK_ERASE is not set
CONFIG_SPI_FLASH_YIELD_DURING_ERASE=y
CONFIG_SPI_FLASH_ERASE_YIELD_DURATION_MS=20
CONFIG_SPI_FLASH_ERASE_YIELD_TICKS=1
CONFIG_SPI_FLASH_WRITE_CHUNK_SIZE=8192
# CONFIG_SPI_FLASH_SIZE_OVERRIDE is not set
# CONFIG_SPI_FLASH_CHECK_ERASE_TIMEOUT_DISABLED is not set
# CONFIG_SPI_FLASH_OVERRIDE_CHIP_DRIVER_LIST is not set
#
# Auto-detect flash chips
#
CONFIG_SPI_FLASH_VENDOR_XMC_SUPPORTED=y
CONFIG_SPI_FLASH_VENDOR_GD_SUPPORTED=y
CONFIG_SPI_FLASH_VENDOR_ISSI_SUPPORTED=y
CONFIG_SPI_FLASH_VENDOR_MXIC_SUPPORTED=y
CONFIG_SPI_FLASH_VENDOR_WINBOND_SUPPORTED=y
CONFIG_SPI_FLASH_VENDOR_BOYA_SUPPORTED=y
CONFIG_SPI_FLASH_VENDOR_TH_SUPPORTED=y
CONFIG_SPI_FLASH_SUPPORT_ISSI_CHIP=y
CONFIG_SPI_FLASH_SUPPORT_MXIC_CHIP=y
CONFIG_SPI_FLASH_SUPPORT_GD_CHIP=y
CONFIG_SPI_FLASH_SUPPORT_WINBOND_CHIP=y
CONFIG_SPI_FLASH_SUPPORT_BOYA_CHIP=y
CONFIG_SPI_FLASH_SUPPORT_TH_CHIP=y
CONFIG_SPI_FLASH_SUPPORT_MXIC_OPI_CHIP=y
# end of Auto-detect flash chips
CONFIG_SPI_FLASH_ENABLE_ENCRYPTED_READ_WRITE=y
# end of SPI Flash driver
#
# SPIFFS Configuration
#
CONFIG_SPIFFS_MAX_PARTITIONS=3
#
# SPIFFS Cache Configuration
#
CONFIG_SPIFFS_CACHE=y
CONFIG_SPIFFS_CACHE_WR=y
# CONFIG_SPIFFS_CACHE_STATS is not set
# end of SPIFFS Cache Configuration
CONFIG_SPIFFS_PAGE_CHECK=y
CONFIG_SPIFFS_GC_MAX_RUNS=10
# CONFIG_SPIFFS_GC_STATS is not set
CONFIG_SPIFFS_PAGE_SIZE=256
CONFIG_SPIFFS_OBJ_NAME_LEN=32
# CONFIG_SPIFFS_FOLLOW_SYMLINKS is not set
CONFIG_SPIFFS_USE_MAGIC=y
CONFIG_SPIFFS_USE_MAGIC_LENGTH=y
CONFIG_SPIFFS_META_LENGTH=4
CONFIG_SPIFFS_USE_MTIME=y
#
# Debug Configuration
#
# CONFIG_SPIFFS_DBG is not set
# CONFIG_SPIFFS_API_DBG is not set
# CONFIG_SPIFFS_GC_DBG is not set
# CONFIG_SPIFFS_CACHE_DBG is not set
# CONFIG_SPIFFS_CHECK_DBG is not set
# CONFIG_SPIFFS_TEST_VISUALISATION is not set
# end of Debug Configuration
# end of SPIFFS Configuration
#
# TCP Transport
#
#
# Websocket
#
CONFIG_WS_TRANSPORT=y
CONFIG_WS_BUFFER_SIZE=1024
# CONFIG_WS_DYNAMIC_BUFFER is not set
# end of Websocket
# end of TCP Transport
#
# Ultra Low Power (ULP) Co-processor
#
# CONFIG_ULP_COPROC_ENABLED is not set
#
# ULP Debugging Options
#
# end of ULP Debugging Options
# end of Ultra Low Power (ULP) Co-processor
#
# Unity unit testing library
#
CONFIG_UNITY_ENABLE_FLOAT=y
CONFIG_UNITY_ENABLE_DOUBLE=y
# CONFIG_UNITY_ENABLE_64BIT is not set
# CONFIG_UNITY_ENABLE_COLOR is not set
CONFIG_UNITY_ENABLE_IDF_TEST_RUNNER=y
# CONFIG_UNITY_ENABLE_FIXTURE is not set
# CONFIG_UNITY_ENABLE_BACKTRACE_ON_FAIL is not set
# end of Unity unit testing library
#
# USB-OTG
#
CONFIG_USB_HOST_CONTROL_TRANSFER_MAX_SIZE=256
CONFIG_USB_HOST_HW_BUFFER_BIAS_BALANCED=y
# CONFIG_USB_HOST_HW_BUFFER_BIAS_IN is not set
# CONFIG_USB_HOST_HW_BUFFER_BIAS_PERIODIC_OUT is not set
#
# Root Hub configuration
#
CONFIG_USB_HOST_DEBOUNCE_DELAY_MS=250
CONFIG_USB_HOST_RESET_HOLD_MS=30
CONFIG_USB_HOST_RESET_RECOVERY_MS=30
CONFIG_USB_HOST_SET_ADDR_RECOVERY_MS=10
# end of Root Hub configuration
# CONFIG_USB_HOST_ENABLE_ENUM_FILTER_CALLBACK is not set
CONFIG_USB_OTG_SUPPORTED=y
# end of USB-OTG
#
# Virtual file system
#
CONFIG_VFS_SUPPORT_IO=y
CONFIG_VFS_SUPPORT_DIR=y
CONFIG_VFS_SUPPORT_SELECT=y
CONFIG_VFS_SUPPRESS_SELECT_DEBUG_OUTPUT=y
# CONFIG_VFS_SELECT_IN_RAM is not set
CONFIG_VFS_SUPPORT_TERMIOS=y
CONFIG_VFS_MAX_COUNT=8
#
# Host File System I/O (Semihosting)
#
CONFIG_VFS_SEMIHOSTFS_MAX_MOUNT_POINTS=1
# end of Host File System I/O (Semihosting)
# end of Virtual file system
#
# Wear Levelling
#
# CONFIG_WL_SECTOR_SIZE_512 is not set
CONFIG_WL_SECTOR_SIZE_4096=y
CONFIG_WL_SECTOR_SIZE=4096
# end of Wear Levelling
#
# Wi-Fi Provisioning Manager
#
CONFIG_WIFI_PROV_SCAN_MAX_ENTRIES=16
CONFIG_WIFI_PROV_AUTOSTOP_TIMEOUT=30
# CONFIG_WIFI_PROV_BLE_FORCE_ENCRYPTION is not set
CONFIG_WIFI_PROV_STA_ALL_CHANNEL_SCAN=y
# CONFIG_WIFI_PROV_STA_FAST_SCAN is not set
# end of Wi-Fi Provisioning Manager
# end of Component config
# CONFIG_IDF_EXPERIMENTAL_FEATURES is not set
# Deprecated options for backward compatibility
# CONFIG_APP_BUILD_TYPE_ELF_RAM is not set
# CONFIG_NO_BLOBS is not set
# CONFIG_LOG_BOOTLOADER_LEVEL_NONE is not set
# CONFIG_LOG_BOOTLOADER_LEVEL_ERROR is not set
# CONFIG_LOG_BOOTLOADER_LEVEL_WARN is not set
CONFIG_LOG_BOOTLOADER_LEVEL_INFO=y
# CONFIG_LOG_BOOTLOADER_LEVEL_DEBUG is not set
# CONFIG_LOG_BOOTLOADER_LEVEL_VERBOSE is not set
CONFIG_LOG_BOOTLOADER_LEVEL=3
# CONFIG_APP_ROLLBACK_ENABLE is not set
# CONFIG_FLASH_ENCRYPTION_ENABLED is not set
# CONFIG_FLASHMODE_QIO is not set
# CONFIG_FLASHMODE_QOUT is not set
CONFIG_FLASHMODE_DIO=y
# CONFIG_FLASHMODE_DOUT is not set
CONFIG_MONITOR_BAUD=115200
CONFIG_OPTIMIZATION_LEVEL_DEBUG=y
CONFIG_COMPILER_OPTIMIZATION_LEVEL_DEBUG=y
CONFIG_COMPILER_OPTIMIZATION_DEFAULT=y
# CONFIG_OPTIMIZATION_LEVEL_RELEASE is not set
# CONFIG_COMPILER_OPTIMIZATION_LEVEL_RELEASE is not set
CONFIG_OPTIMIZATION_ASSERTIONS_ENABLED=y
# CONFIG_OPTIMIZATION_ASSERTIONS_SILENT is not set
# CONFIG_OPTIMIZATION_ASSERTIONS_DISABLED is not set
CONFIG_OPTIMIZATION_ASSERTION_LEVEL=2
# CONFIG_CXX_EXCEPTIONS is not set
CONFIG_STACK_CHECK_NONE=y
# CONFIG_STACK_CHECK_NORM is not set
# CONFIG_STACK_CHECK_STRONG is not set
# CONFIG_STACK_CHECK_ALL is not set
# CONFIG_WARN_WRITE_STRINGS is not set
# CONFIG_ESP32_APPTRACE_DEST_TRAX is not set
CONFIG_ESP32_APPTRACE_DEST_NONE=y
CONFIG_ESP32_APPTRACE_LOCK_ENABLE=y
# CONFIG_EXTERNAL_COEX_ENABLE is not set
# CONFIG_ESP_WIFI_EXTERNAL_COEXIST_ENABLE is not set
# CONFIG_MCPWM_ISR_IN_IRAM is not set
# CONFIG_EVENT_LOOP_PROFILING is not set
CONFIG_POST_EVENTS_FROM_ISR=y
CONFIG_POST_EVENTS_FROM_IRAM_ISR=y
CONFIG_GDBSTUB_SUPPORT_TASKS=y
CONFIG_GDBSTUB_MAX_TASKS=32
# CONFIG_OTA_ALLOW_HTTP is not set
CONFIG_ESP32S3_DEEP_SLEEP_WAKEUP_DELAY=2000
CONFIG_ESP_SLEEP_DEEP_SLEEP_WAKEUP_DELAY=2000
CONFIG_ESP32S3_RTC_CLK_SRC_INT_RC=y
# CONFIG_ESP32S3_RTC_CLK_SRC_EXT_CRYS is not set
# CONFIG_ESP32S3_RTC_CLK_SRC_EXT_OSC is not set
# CONFIG_ESP32S3_RTC_CLK_SRC_INT_8MD256 is not set
CONFIG_ESP32S3_RTC_CLK_CAL_CYCLES=1024
CONFIG_ESP32_PHY_CALIBRATION_AND_DATA_STORAGE=y
# CONFIG_ESP32_PHY_INIT_DATA_IN_PARTITION is not set
CONFIG_ESP32_PHY_MAX_WIFI_TX_POWER=20
CONFIG_ESP32_PHY_MAX_TX_POWER=20
# CONFIG_REDUCE_PHY_TX_POWER is not set
# CONFIG_ESP32_REDUCE_PHY_TX_POWER is not set
CONFIG_ESP_SYSTEM_PM_POWER_DOWN_CPU=y
CONFIG_PM_POWER_DOWN_TAGMEM_IN_LIGHT_SLEEP=y
CONFIG_ESP32S3_SPIRAM_SUPPORT=y
CONFIG_DEFAULT_PSRAM_CLK_IO=30
CONFIG_DEFAULT_PSRAM_CS_IO=26
# CONFIG_ESP32S3_DEFAULT_CPU_FREQ_80 is not set
# CONFIG_ESP32S3_DEFAULT_CPU_FREQ_160 is not set
CONFIG_ESP32S3_DEFAULT_CPU_FREQ_240=y
CONFIG_ESP32S3_DEFAULT_CPU_FREQ_MHZ=240
CONFIG_SYSTEM_EVENT_QUEUE_SIZE=32
CONFIG_SYSTEM_EVENT_TASK_STACK_SIZE=2304
CONFIG_MAIN_TASK_STACK_SIZE=10240
CONFIG_CONSOLE_UART_DEFAULT=y
# CONFIG_CONSOLE_UART_CUSTOM is not set
# CONFIG_CONSOLE_UART_NONE is not set
# CONFIG_ESP_CONSOLE_UART_NONE is not set
CONFIG_CONSOLE_UART=y
CONFIG_CONSOLE_UART_NUM=0
CONFIG_CONSOLE_UART_BAUDRATE=115200
CONFIG_INT_WDT=y
CONFIG_INT_WDT_TIMEOUT_MS=300
CONFIG_INT_WDT_CHECK_CPU1=y
CONFIG_TASK_WDT=y
CONFIG_ESP_TASK_WDT=y
# CONFIG_TASK_WDT_PANIC is not set
CONFIG_TASK_WDT_TIMEOUT_S=5
CONFIG_TASK_WDT_CHECK_IDLE_TASK_CPU0=y
CONFIG_TASK_WDT_CHECK_IDLE_TASK_CPU1=y
# CONFIG_ESP32_DEBUG_STUBS_ENABLE is not set
CONFIG_ESP32S3_DEBUG_OCDAWARE=y
CONFIG_BROWNOUT_DET=y
CONFIG_ESP32S3_BROWNOUT_DET=y
CONFIG_ESP32S3_BROWNOUT_DET=y
CONFIG_BROWNOUT_DET_LVL_SEL_7=y
CONFIG_ESP32S3_BROWNOUT_DET_LVL_SEL_7=y
# CONFIG_BROWNOUT_DET_LVL_SEL_6 is not set
# CONFIG_ESP32S3_BROWNOUT_DET_LVL_SEL_6 is not set
# CONFIG_BROWNOUT_DET_LVL_SEL_5 is not set
# CONFIG_ESP32S3_BROWNOUT_DET_LVL_SEL_5 is not set
# CONFIG_BROWNOUT_DET_LVL_SEL_4 is not set
# CONFIG_ESP32S3_BROWNOUT_DET_LVL_SEL_4 is not set
# CONFIG_BROWNOUT_DET_LVL_SEL_3 is not set
# CONFIG_ESP32S3_BROWNOUT_DET_LVL_SEL_3 is not set
# CONFIG_BROWNOUT_DET_LVL_SEL_2 is not set
# CONFIG_ESP32S3_BROWNOUT_DET_LVL_SEL_2 is not set
# CONFIG_BROWNOUT_DET_LVL_SEL_1 is not set
# CONFIG_ESP32S3_BROWNOUT_DET_LVL_SEL_1 is not set
CONFIG_BROWNOUT_DET_LVL=7
CONFIG_ESP32S3_BROWNOUT_DET_LVL=7
CONFIG_IPC_TASK_STACK_SIZE=1280
CONFIG_TIMER_TASK_STACK_SIZE=3584
CONFIG_ESP32_WIFI_ENABLED=y
CONFIG_ESP32_WIFI_STATIC_RX_BUFFER_NUM=10
CONFIG_ESP32_WIFI_DYNAMIC_RX_BUFFER_NUM=32
CONFIG_ESP32_WIFI_STATIC_TX_BUFFER=y
CONFIG_ESP32_WIFI_TX_BUFFER_TYPE=0
CONFIG_ESP32_WIFI_STATIC_TX_BUFFER_NUM=16
CONFIG_ESP32_WIFI_CACHE_TX_BUFFER_NUM=32
# CONFIG_ESP32_WIFI_CSI_ENABLED is not set
CONFIG_ESP32_WIFI_AMPDU_TX_ENABLED=y
CONFIG_ESP32_WIFI_TX_BA_WIN=6
CONFIG_ESP32_WIFI_AMPDU_RX_ENABLED=y
CONFIG_ESP32_WIFI_AMPDU_RX_ENABLED=y
CONFIG_ESP32_WIFI_RX_BA_WIN=6
CONFIG_ESP32_WIFI_RX_BA_WIN=6
# CONFIG_ESP32_WIFI_AMSDU_TX_ENABLED is not set
CONFIG_ESP32_WIFI_NVS_ENABLED=y
CONFIG_ESP32_WIFI_TASK_PINNED_TO_CORE_0=y
# CONFIG_ESP32_WIFI_TASK_PINNED_TO_CORE_1 is not set
CONFIG_ESP32_WIFI_SOFTAP_BEACON_MAX_LEN=752
CONFIG_ESP32_WIFI_MGMT_SBUF_NUM=32
CONFIG_ESP32_WIFI_IRAM_OPT=y
CONFIG_ESP32_WIFI_RX_IRAM_OPT=y
CONFIG_ESP32_WIFI_ENABLE_WPA3_SAE=y
CONFIG_ESP32_WIFI_ENABLE_WPA3_OWE_STA=y
CONFIG_WPA_MBEDTLS_CRYPTO=y
CONFIG_WPA_MBEDTLS_TLS_CLIENT=y
# CONFIG_WPA_WAPI_PSK is not set
# CONFIG_WPA_SUITE_B_192 is not set
# CONFIG_WPA_11KV_SUPPORT is not set
# CONFIG_WPA_MBO_SUPPORT is not set
# CONFIG_WPA_DPP_SUPPORT is not set
# CONFIG_WPA_11R_SUPPORT is not set
# CONFIG_WPA_WPS_SOFTAP_REGISTRAR is not set
# CONFIG_WPA_WPS_STRICT is not set
# CONFIG_WPA_DEBUG_PRINT is not set
# CONFIG_WPA_TESTING_OPTIONS is not set
# CONFIG_ESP32_ENABLE_COREDUMP_TO_FLASH is not set
# CONFIG_ESP32_ENABLE_COREDUMP_TO_UART is not set
CONFIG_ESP32_ENABLE_COREDUMP_TO_NONE=y
CONFIG_TIMER_TASK_PRIORITY=1
CONFIG_TIMER_TASK_STACK_DEPTH=2048
CONFIG_TIMER_QUEUE_LENGTH=10
# CONFIG_ENABLE_STATIC_TASK_CLEAN_UP_HOOK is not set
# CONFIG_HAL_ASSERTION_SILIENT is not set
# CONFIG_L2_TO_L3_COPY is not set
CONFIG_ESP_GRATUITOUS_ARP=y
CONFIG_GARP_TMR_INTERVAL=60
CONFIG_TCPIP_RECVMBOX_SIZE=32
CONFIG_TCP_MAXRTX=12
CONFIG_TCP_SYNMAXRTX=12
CONFIG_TCP_MSS=1440
CONFIG_TCP_MSL=60000
CONFIG_TCP_SND_BUF_DEFAULT=5760
CONFIG_TCP_WND_DEFAULT=5760
CONFIG_TCP_RECVMBOX_SIZE=6
CONFIG_TCP_QUEUE_OOSEQ=y
CONFIG_TCP_OVERSIZE_MSS=y
# CONFIG_TCP_OVERSIZE_QUARTER_MSS is not set
# CONFIG_TCP_OVERSIZE_DISABLE is not set
CONFIG_UDP_RECVMBOX_SIZE=6
CONFIG_TCPIP_TASK_STACK_SIZE=3072
CONFIG_TCPIP_TASK_AFFINITY_NO_AFFINITY=y
# CONFIG_TCPIP_TASK_AFFINITY_CPU0 is not set
# CONFIG_TCPIP_TASK_AFFINITY_CPU1 is not set
CONFIG_TCPIP_TASK_AFFINITY=0x7FFFFFFF
# CONFIG_PPP_SUPPORT is not set
CONFIG_ESP32S3_TIME_SYSCALL_USE_RTC_SYSTIMER=y
CONFIG_ESP32S3_TIME_SYSCALL_USE_RTC_FRC1=y
# CONFIG_ESP32S3_TIME_SYSCALL_USE_RTC is not set
# CONFIG_ESP32S3_TIME_SYSCALL_USE_SYSTIMER is not set
# CONFIG_ESP32S3_TIME_SYSCALL_USE_FRC1 is not set
# CONFIG_ESP32S3_TIME_SYSCALL_USE_NONE is not set
CONFIG_ESP32_PTHREAD_TASK_PRIO_DEFAULT=5
CONFIG_ESP32_PTHREAD_TASK_STACK_SIZE_DEFAULT=3072
CONFIG_ESP32_PTHREAD_STACK_MIN=768
CONFIG_ESP32_DEFAULT_PTHREAD_CORE_NO_AFFINITY=y
# CONFIG_ESP32_DEFAULT_PTHREAD_CORE_0 is not set
# CONFIG_ESP32_DEFAULT_PTHREAD_CORE_1 is not set
CONFIG_ESP32_PTHREAD_TASK_CORE_DEFAULT=-1
CONFIG_ESP32_PTHREAD_TASK_NAME_DEFAULT="pthread"
CONFIG_SPI_FLASH_WRITING_DANGEROUS_REGIONS_ABORTS=y
# CONFIG_SPI_FLASH_WRITING_DANGEROUS_REGIONS_FAILS is not set
# CONFIG_SPI_FLASH_WRITING_DANGEROUS_REGIONS_ALLOWED is not set
CONFIG_SUPPRESS_SELECT_DEBUG_OUTPUT=y
CONFIG_SUPPORT_TERMIOS=y
CONFIG_SEMIHOSTFS_MAX_MOUNT_POINTS=1
# End of deprecated options
| 66,367 | sdkconfig | en | unknown | unknown | {} | 0 | {} | |
0015/Fridge-Calendar | README.md | # Fridge Calendar (E-Paper Google Calendar Display)
This project is an e-paper-based calendar display that integrates with Google Calendar to fetch and display daily events. It uses the ESP32-S3 microcontroller, the EPDiy library for e-paper control, and the Google Calendar API to retrieve event data. The device connects to WiFi for API calls and keeps track of local time for accurate scheduling and updates.
[](https://youtu.be/2Iy_9JYkWGs)
---
## Features
- **9.7-inch Black and White E-Paper Display**: Displays a monthly calendar and upcoming events using the EPDiy library.
- **WiFi Connectivity**: Required for API calls to fetch Google Calendar events.
- **Local Time Management**: Synchronizes and maintains local time for accurate scheduling.
- **Google Calendar Integration**: Fetches events using Google Calendar API in JSON format.
- **Automatic Daily Updates**: Refreshes the display at 00:10 every day.
- **Deep Sleep Mode**: Saves power by putting the ESP32 into deep sleep between updates.
- **Robust Retry Mechanism**: Handles API call failures with a retry mechanism and enters indefinite deep sleep after repeated failures.
---
## Table of Contents
- [Hardware Requirements](#hardware-requirements)
- [Software Requirements](#software-requirements)
- [Installation](#installation)
- [Usage](#usage)
- [Configuration](#configuration)
- [System Workflow](#system-workflow)
- [Troubleshooting](#troubleshooting)
- [License](#license)
---
## Hardware Requirements
- ESP32-S3 Based, [Epdiy V7 board](https://vroland.github.io/epdiy-hardware/)
- Support for high-resolution displays with 16 data lines
- Much faster updates thanks to the ESP32S3 SOC and the LCD peripheral
- An on-board RTC, LiPo charging
- 9.7-inch black and white e-paper display(ED097TC2) compatible with the [EPDiy library](https://github.com/vroland/epdiy)
- Power supply (battery or USB)
---
## Software Requirements
- [ESP-IDF](https://github.com/espressif/esp-idf): ESP32 development framework (v5.3.1)
- [EPDiy library](https://github.com/vroland/epdiy): For e-paper control
- [nlohmann/json](https://github.com/nlohmann/json): For JSON parsing
- Google Calendar API key and OAuth credentials
- [Learn about authentication and authorization](https://developers.google.com/workspace/guides/auth-overview)
- [How to access Google APIs using OAuth 2.0 in Postman](https://blog.postman.com/how-to-access-google-apis-using-oauth-in-postman/)
---
## Installation
### 1. Clone the Repository
```bash
git clone https://github.com/0015/Fridge-Calendar.git
cd Fridge-Calendar
```
### 2. Create a Components Folder
Inside your project directory, create a `components` folder:
```bash
mkdir components
```
### 3. Add EPDiy Library
Clone the [EPDiy](https://github.com/vroland/epdiy) library into the `components` folder:
```bash
cd components
git clone https://github.com/vroland/epdiy.git
```
### 4. Install JSON Parsing Library
Install the `nlohmann-json` library using the ESP-IDF dependency manager:
```bash
idf.py add-dependency "johboh/nlohmann-json^3.11.3"
```
### 5. Configure Project
Set your WiFi credentials, Google API credentials, and other configurations in `app_config.h`:
```cpp
#define WIFI_SSID "your_wifi_ssid"
#define WIFI_PASS "your_wifi_password"
#define CLIENT_ID "your_client_id"
#define CLIENT_SECRET "your_client_secret"
#define ACCESS_TOKEN "your_access_token"
#define REFRESH_TOKEN "your_refresh_token"
#define CALENDAR_IDS "<multiple_calendar_ids>"
#define TIMEZONE "your_time_zone"
```
### 6. Build and Flash
```bash
idf.py build
idf.py flash
```
---
## Usage
- Upon powering up, the device connects to WiFi, synchronizes local time, and fetches Google Calendar events.
- Displays a monthly calendar and a list of upcoming events.
- Automatically updates at 00:30 every day or after a successful fetch of calendar events.
- If the API call fails twice in a row, the device enters indefinite deep sleep.
---
## Configuration
### Google Calendar API Setup
1. Go to the [Google Cloud Console](https://console.cloud.google.com/).
2. Create a new project and enable the **Google Calendar API**.
3. Create OAuth credentials for your project.
4. Obtain the API key(Access Token), Refresh Token, client ID, and client secret.
5. Add the credentials to your `app_config.h` file.
### WiFi Credentials
- Update the WiFi SSID and password in the `app_config.h` file.
---
## System Workflow
### Initialization
1. Initialize Non-Volatile Storage (NVS) to store state information.
2. Display a splash screen and progress bar if this is the first run.
3. Connect to WiFi and synchronize local time.
### Main Operation
1. Fetch events from Google Calendar using the REST API.
2. Parse JSON data into a usable format.
3. Display the calendar and events on the e-paper screen.
### Retry and Sleep Logic
- On a failed API call:
- Increment a retry counter stored in NVS.
- Reboot and retry the operation.
- After two failed attempts:
- Enter deep sleep indefinitely to save power.
- On success:
- Reset the retry counter and schedule a wakeup for 00:30 the next day.
---
## Troubleshooting
### Common Issues
1. **WiFi Connection Fails**:
- Check your WiFi SSID and password in `app_config.h`.
- Ensure the ESP32 is within range of the WiFi router.
2. **Google API Fails**:
- Verify your Access Token, Refresh Token and OAuth credentials.
- Check if the Google Calendar API is enabled in your Google Cloud Console.
3. **NVS Errors**:
- Ensure NVS is initialized properly during startup.
- Erase NVS if necessary using `idf.py erase_flash`.
4. **E-paper Display Issues**:
- Verify the connection between the ESP32 and e-paper display.
- Check if the EPDiy library is installed correctly.
---
## License
This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details. | 6,219 | README | md | en | markdown | text | {"qsc_doc_frac_chars_curly_bracket": 0.0, "qsc_doc_frac_words_redpajama_stop": 0.15344311, "qsc_doc_num_sentences": 105.0, "qsc_doc_num_words": 911, "qsc_doc_num_chars": 6219.0, "qsc_doc_num_lines": 181.0, "qsc_doc_mean_word_length": 5.09769484, "qsc_doc_frac_words_full_bracket": 0.0, "qsc_doc_frac_lines_end_with_readmore": 0.0, "qsc_doc_frac_lines_start_with_bullet": 0.0, "qsc_doc_frac_words_unique": 0.33479693, "qsc_doc_entropy_unigram": 5.20752519, "qsc_doc_frac_words_all_caps": 0.04565868, "qsc_doc_frac_lines_dupe_lines": 0.15909091, "qsc_doc_frac_chars_dupe_lines": 0.01386106, "qsc_doc_frac_chars_top_2grams": 0.03617571, "qsc_doc_frac_chars_top_3grams": 0.0211025, "qsc_doc_frac_chars_top_4grams": 0.01808786, "qsc_doc_frac_chars_dupe_5grams": 0.14534884, "qsc_doc_frac_chars_dupe_6grams": 0.08419466, "qsc_doc_frac_chars_dupe_7grams": 0.08419466, "qsc_doc_frac_chars_dupe_8grams": 0.0544789, "qsc_doc_frac_chars_dupe_9grams": 0.0544789, "qsc_doc_frac_chars_dupe_10grams": 0.04069767, "qsc_doc_frac_chars_replacement_symbols": 0.0, "qsc_doc_cate_code_related_file_name": 1.0, "qsc_doc_num_chars_sentence_length_mean": 20.59722222, "qsc_doc_frac_chars_hyperlink_html_tag": 0.1181862, "qsc_doc_frac_chars_alphabet": 0.85558685, "qsc_doc_frac_chars_digital": 0.01652582, "qsc_doc_frac_chars_whitespace": 0.14375301, "qsc_doc_frac_chars_hex_words": 0.0} | 1 | {"qsc_doc_frac_chars_replacement_symbols": 0, "qsc_doc_entropy_unigram": 0, "qsc_doc_frac_chars_top_2grams": 0, "qsc_doc_frac_chars_top_3grams": 0, "qsc_doc_frac_chars_top_4grams": 0, "qsc_doc_frac_chars_dupe_5grams": 0, "qsc_doc_frac_chars_dupe_6grams": 0, "qsc_doc_frac_chars_dupe_7grams": 0, "qsc_doc_frac_chars_dupe_8grams": 0, "qsc_doc_frac_chars_dupe_9grams": 0, "qsc_doc_frac_chars_dupe_10grams": 0, "qsc_doc_frac_chars_dupe_lines": 0, "qsc_doc_frac_lines_dupe_lines": 0, "qsc_doc_frac_lines_end_with_readmore": 0, "qsc_doc_frac_lines_start_with_bullet": 0, "qsc_doc_frac_words_all_caps": 0, "qsc_doc_mean_word_length": 0, "qsc_doc_num_chars": 0, "qsc_doc_num_lines": 0, "qsc_doc_num_sentences": 0, "qsc_doc_num_words": 0, "qsc_doc_frac_chars_hex_words": 0, "qsc_doc_frac_chars_hyperlink_html_tag": 0, "qsc_doc_frac_chars_alphabet": 0, "qsc_doc_frac_chars_digital": 0, "qsc_doc_frac_chars_whitespace": 0} |
0015/esp_rlottie | rlottie/licenses/COPYING.MPL | Mozilla Public License Version 2.0
==================================
1. Definitions
--------------
1.1. "Contributor"
means each individual or legal entity that creates, contributes to
the creation of, or owns Covered Software.
1.2. "Contributor Version"
means the combination of the Contributions of others (if any) used
by a Contributor and that particular Contributor's Contribution.
1.3. "Contribution"
means Covered Software of a particular Contributor.
1.4. "Covered Software"
means Source Code Form to which the initial Contributor has attached
the notice in Exhibit A, the Executable Form of such Source Code
Form, and Modifications of such Source Code Form, in each case
including portions thereof.
1.5. "Incompatible With Secondary Licenses"
means
(a) that the initial Contributor has attached the notice described
in Exhibit B to the Covered Software; or
(b) that the Covered Software was made available under the terms of
version 1.1 or earlier of the License, but not also under the
terms of a Secondary License.
1.6. "Executable Form"
means any form of the work other than Source Code Form.
1.7. "Larger Work"
means a work that combines Covered Software with other material, in
a separate file or files, that is not Covered Software.
1.8. "License"
means this document.
1.9. "Licensable"
means having the right to grant, to the maximum extent possible,
whether at the time of the initial grant or subsequently, any and
all of the rights conveyed by this License.
1.10. "Modifications"
means any of the following:
(a) any file in Source Code Form that results from an addition to,
deletion from, or modification of the contents of Covered
Software; or
(b) any new file in Source Code Form that contains any Covered
Software.
1.11. "Patent Claims" of a Contributor
means any patent claim(s), including without limitation, method,
process, and apparatus claims, in any patent Licensable by such
Contributor that would be infringed, but for the grant of the
License, by the making, using, selling, offering for sale, having
made, import, or transfer of either its Contributions or its
Contributor Version.
1.12. "Secondary License"
means either the GNU General Public License, Version 2.0, the GNU
Lesser General Public License, Version 2.1, the GNU Affero General
Public License, Version 3.0, or any later versions of those
licenses.
1.13. "Source Code Form"
means the form of the work preferred for making modifications.
1.14. "You" (or "Your")
means an individual or a legal entity exercising rights under this
License. For legal entities, "You" includes any entity that
controls, is controlled by, or is under common control with You. For
purposes of this definition, "control" means (a) the power, direct
or indirect, to cause the direction or management of such entity,
whether by contract or otherwise, or (b) ownership of more than
fifty percent (50%) of the outstanding shares or beneficial
ownership of such entity.
2. License Grants and Conditions
--------------------------------
2.1. Grants
Each Contributor hereby grants You a world-wide, royalty-free,
non-exclusive license:
(a) under intellectual property rights (other than patent or trademark)
Licensable by such Contributor to use, reproduce, make available,
modify, display, perform, distribute, and otherwise exploit its
Contributions, either on an unmodified basis, with Modifications, or
as part of a Larger Work; and
(b) under Patent Claims of such Contributor to make, use, sell, offer
for sale, have made, import, and otherwise transfer either its
Contributions or its Contributor Version.
2.2. Effective Date
The licenses granted in Section 2.1 with respect to any Contribution
become effective for each Contribution on the date the Contributor first
distributes such Contribution.
2.3. Limitations on Grant Scope
The licenses granted in this Section 2 are the only rights granted under
this License. No additional rights or licenses will be implied from the
distribution or licensing of Covered Software under this License.
Notwithstanding Section 2.1(b) above, no patent license is granted by a
Contributor:
(a) for any code that a Contributor has removed from Covered Software;
or
(b) for infringements caused by: (i) Your and any other third party's
modifications of Covered Software, or (ii) the combination of its
Contributions with other software (except as part of its Contributor
Version); or
(c) under Patent Claims infringed by Covered Software in the absence of
its Contributions.
This License does not grant any rights in the trademarks, service marks,
or logos of any Contributor (except as may be necessary to comply with
the notice requirements in Section 3.4).
2.4. Subsequent Licenses
No Contributor makes additional grants as a result of Your choice to
distribute the Covered Software under a subsequent version of this
License (see Section 10.2) or under the terms of a Secondary License (if
permitted under the terms of Section 3.3).
2.5. Representation
Each Contributor represents that the Contributor believes its
Contributions are its original creation(s) or it has sufficient rights
to grant the rights to its Contributions conveyed by this License.
2.6. Fair Use
This License is not intended to limit any rights You have under
applicable copyright doctrines of fair use, fair dealing, or other
equivalents.
2.7. Conditions
Sections 3.1, 3.2, 3.3, and 3.4 are conditions of the licenses granted
in Section 2.1.
3. Responsibilities
-------------------
3.1. Distribution of Source Form
All distribution of Covered Software in Source Code Form, including any
Modifications that You create or to which You contribute, must be under
the terms of this License. You must inform recipients that the Source
Code Form of the Covered Software is governed by the terms of this
License, and how they can obtain a copy of this License. You may not
attempt to alter or restrict the recipients' rights in the Source Code
Form.
3.2. Distribution of Executable Form
If You distribute Covered Software in Executable Form then:
(a) such Covered Software must also be made available in Source Code
Form, as described in Section 3.1, and You must inform recipients of
the Executable Form how they can obtain a copy of such Source Code
Form by reasonable means in a timely manner, at a charge no more
than the cost of distribution to the recipient; and
(b) You may distribute such Executable Form under the terms of this
License, or sublicense it under different terms, provided that the
license for the Executable Form does not attempt to limit or alter
the recipients' rights in the Source Code Form under this License.
3.3. Distribution of a Larger Work
You may create and distribute a Larger Work under terms of Your choice,
provided that You also comply with the requirements of this License for
the Covered Software. If the Larger Work is a combination of Covered
Software with a work governed by one or more Secondary Licenses, and the
Covered Software is not Incompatible With Secondary Licenses, this
License permits You to additionally distribute such Covered Software
under the terms of such Secondary License(s), so that the recipient of
the Larger Work may, at their option, further distribute the Covered
Software under the terms of either this License or such Secondary
License(s).
3.4. Notices
You may not remove or alter the substance of any license notices
(including copyright notices, patent notices, disclaimers of warranty,
or limitations of liability) contained within the Source Code Form of
the Covered Software, except that You may alter any license notices to
the extent required to remedy known factual inaccuracies.
3.5. Application of Additional Terms
You may choose to offer, and to charge a fee for, warranty, support,
indemnity or liability obligations to one or more recipients of Covered
Software. However, You may do so only on Your own behalf, and not on
behalf of any Contributor. You must make it absolutely clear that any
such warranty, support, indemnity, or liability obligation is offered by
You alone, and You hereby agree to indemnify every Contributor for any
liability incurred by such Contributor as a result of warranty, support,
indemnity or liability terms You offer. You may include additional
disclaimers of warranty and limitations of liability specific to any
jurisdiction.
4. Inability to Comply Due to Statute or Regulation
---------------------------------------------------
If it is impossible for You to comply with any of the terms of this
License with respect to some or all of the Covered Software due to
statute, judicial order, or regulation then You must: (a) comply with
the terms of this License to the maximum extent possible; and (b)
describe the limitations and the code they affect. Such description must
be placed in a text file included with all distributions of the Covered
Software under this License. Except to the extent prohibited by statute
or regulation, such description must be sufficiently detailed for a
recipient of ordinary skill to be able to understand it.
5. Termination
--------------
5.1. The rights granted under this License will terminate automatically
if You fail to comply with any of its terms. However, if You become
compliant, then the rights granted under this License from a particular
Contributor are reinstated (a) provisionally, unless and until such
Contributor explicitly and finally terminates Your grants, and (b) on an
ongoing basis, if such Contributor fails to notify You of the
non-compliance by some reasonable means prior to 60 days after You have
come back into compliance. Moreover, Your grants from a particular
Contributor are reinstated on an ongoing basis if such Contributor
notifies You of the non-compliance by some reasonable means, this is the
first time You have received notice of non-compliance with this License
from such Contributor, and You become compliant prior to 30 days after
Your receipt of the notice.
5.2. If You initiate litigation against any entity by asserting a patent
infringement claim (excluding declaratory judgment actions,
counter-claims, and cross-claims) alleging that a Contributor Version
directly or indirectly infringes any patent, then the rights granted to
You by any and all Contributors for the Covered Software under Section
2.1 of this License shall terminate.
5.3. In the event of termination under Sections 5.1 or 5.2 above, all
end user license agreements (excluding distributors and resellers) which
have been validly granted by You or Your distributors under this License
prior to termination shall survive termination.
************************************************************************
* *
* 6. Disclaimer of Warranty *
* ------------------------- *
* *
* Covered Software is provided under this License on an "as is" *
* basis, without warranty of any kind, either expressed, implied, or *
* statutory, including, without limitation, warranties that the *
* Covered Software is free of defects, merchantable, fit for a *
* particular purpose or non-infringing. The entire risk as to the *
* quality and performance of the Covered Software is with You. *
* Should any Covered Software prove defective in any respect, You *
* (not any Contributor) assume the cost of any necessary servicing, *
* repair, or correction. This disclaimer of warranty constitutes an *
* essential part of this License. No use of any Covered Software is *
* authorized under this License except under this disclaimer. *
* *
************************************************************************
************************************************************************
* *
* 7. Limitation of Liability *
* -------------------------- *
* *
* Under no circumstances and under no legal theory, whether tort *
* (including negligence), contract, or otherwise, shall any *
* Contributor, or anyone who distributes Covered Software as *
* permitted above, be liable to You for any direct, indirect, *
* special, incidental, or consequential damages of any character *
* including, without limitation, damages for lost profits, loss of *
* goodwill, work stoppage, computer failure or malfunction, or any *
* and all other commercial damages or losses, even if such party *
* shall have been informed of the possibility of such damages. This *
* limitation of liability shall not apply to liability for death or *
* personal injury resulting from such party's negligence to the *
* extent applicable law prohibits such limitation. Some *
* jurisdictions do not allow the exclusion or limitation of *
* incidental or consequential damages, so this exclusion and *
* limitation may not apply to You. *
* *
************************************************************************
8. Litigation
-------------
Any litigation relating to this License may be brought only in the
courts of a jurisdiction where the defendant maintains its principal
place of business and such litigation shall be governed by laws of that
jurisdiction, without reference to its conflict-of-law provisions.
Nothing in this Section shall prevent a party's ability to bring
cross-claims or counter-claims.
9. Miscellaneous
----------------
This License represents the complete agreement concerning the subject
matter hereof. If any provision of this License is held to be
unenforceable, such provision shall be reformed only to the extent
necessary to make it enforceable. Any law or regulation which provides
that the language of a contract shall be construed against the drafter
shall not be used to construe this License against a Contributor.
10. Versions of the License
---------------------------
10.1. New Versions
Mozilla Foundation is the license steward. Except as provided in Section
10.3, no one other than the license steward has the right to modify or
publish new versions of this License. Each version will be given a
distinguishing version number.
10.2. Effect of New Versions
You may distribute the Covered Software under the terms of the version
of the License under which You originally received the Covered Software,
or under the terms of any subsequent version published by the license
steward.
10.3. Modified Versions
If you create software not governed by this License, and you want to
create a new license for such software, you may create and use a
modified version of this License if you rename the license and remove
any references to the name of the license steward (except to note that
such modified license differs from this License).
10.4. Distributing Source Code Form that is Incompatible With Secondary
Licenses
If You choose to distribute Source Code Form that is Incompatible With
Secondary Licenses under the terms of this version of the License, the
notice described in Exhibit B of this License must be attached.
Exhibit A - Source Code Form License Notice
-------------------------------------------
This Source Code Form is subject to the terms of the Mozilla Public
License, v. 2.0. If a copy of the MPL was not distributed with this
file, You can obtain one at http://mozilla.org/MPL/2.0/.
If it is not possible or desirable to put the notice in a particular
file, then You may include the notice in a location (such as a LICENSE
file in a relevant directory) where a recipient would be likely to look
for such a notice.
You may add additional accurate notices of copyright ownership.
Exhibit B - "Incompatible With Secondary Licenses" Notice
---------------------------------------------------------
This Source Code Form is "Incompatible With Secondary Licenses", as
defined by the Mozilla Public License, v. 2.0.
| 16,726 | COPYING | mpl | en | text | text | {"qsc_doc_frac_chars_curly_bracket": 0.0, "qsc_doc_frac_words_redpajama_stop": 0.37520938, "qsc_doc_num_sentences": 171.0, "qsc_doc_num_words": 2426, "qsc_doc_num_chars": 16726.0, "qsc_doc_num_lines": 373.0, "qsc_doc_mean_word_length": 4.91178895, "qsc_doc_frac_words_full_bracket": 0.0, "qsc_doc_frac_lines_end_with_readmore": 0.0, "qsc_doc_frac_lines_start_with_bullet": 0.0, "qsc_doc_frac_words_unique": 0.21805441, "qsc_doc_entropy_unigram": 5.22031161, "qsc_doc_frac_words_all_caps": 0.00368509, "qsc_doc_frac_lines_dupe_lines": 0.04095563, "qsc_doc_frac_chars_dupe_lines": 0.04658114, "qsc_doc_frac_chars_top_2grams": 0.04531722, "qsc_doc_frac_chars_top_3grams": 0.02232293, "qsc_doc_frac_chars_top_4grams": 0.01384693, "qsc_doc_frac_chars_dupe_5grams": 0.15651225, "qsc_doc_frac_chars_dupe_6grams": 0.10532058, "qsc_doc_frac_chars_dupe_7grams": 0.07418597, "qsc_doc_frac_chars_dupe_8grams": 0.03575025, "qsc_doc_frac_chars_dupe_9grams": 0.01594495, "qsc_doc_frac_chars_dupe_10grams": 0.0, "qsc_doc_frac_chars_replacement_symbols": 0.0, "qsc_doc_cate_code_related_file_name": 0.0, "qsc_doc_num_chars_sentence_length_mean": 29.69174312, "qsc_doc_frac_chars_hyperlink_html_tag": 0.0, "qsc_doc_frac_chars_alphabet": 0.89673292, "qsc_doc_frac_chars_digital": 0.01073795, "qsc_doc_frac_chars_whitespace": 0.21493483, "qsc_doc_frac_chars_hex_words": 0.0} | 1 | {"qsc_doc_frac_chars_replacement_symbols": 0, "qsc_doc_entropy_unigram": 0, "qsc_doc_frac_chars_top_2grams": 0, "qsc_doc_frac_chars_top_3grams": 0, "qsc_doc_frac_chars_top_4grams": 0, "qsc_doc_frac_chars_dupe_5grams": 0, "qsc_doc_frac_chars_dupe_6grams": 0, "qsc_doc_frac_chars_dupe_7grams": 0, "qsc_doc_frac_chars_dupe_8grams": 0, "qsc_doc_frac_chars_dupe_9grams": 0, "qsc_doc_frac_chars_dupe_10grams": 0, "qsc_doc_frac_chars_dupe_lines": 0, "qsc_doc_frac_lines_dupe_lines": 0, "qsc_doc_frac_lines_end_with_readmore": 0, "qsc_doc_frac_lines_start_with_bullet": 0, "qsc_doc_frac_words_all_caps": 0, "qsc_doc_mean_word_length": 0, "qsc_doc_num_chars": 0, "qsc_doc_num_lines": 0, "qsc_doc_num_sentences": 0, "qsc_doc_num_words": 0, "qsc_doc_frac_chars_hex_words": 0, "qsc_doc_frac_chars_hyperlink_html_tag": 0, "qsc_doc_frac_chars_alphabet": 0, "qsc_doc_frac_chars_digital": 0, "qsc_doc_frac_chars_whitespace": 0} |
0015/esp_rlottie | rlottie/licenses/COPYING.SKIA | Copyright (c) 2011 Google Inc. All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are
met:
* Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in
the documentation and/or other materials provided with the
distribution.
* Neither the name of the copyright holder nor the names of its
contributors may be used to endorse or promote products derived
from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
| 1,507 | COPYING | skia | en | text | text | {"qsc_doc_frac_chars_curly_bracket": 0.0, "qsc_doc_frac_words_redpajama_stop": 0.20454545, "qsc_doc_num_sentences": 7.0, "qsc_doc_num_words": 222, "qsc_doc_num_chars": 1507.0, "qsc_doc_num_lines": 29.0, "qsc_doc_mean_word_length": 5.43243243, "qsc_doc_frac_words_full_bracket": 0.0, "qsc_doc_frac_lines_end_with_readmore": 0.0, "qsc_doc_frac_lines_start_with_bullet": 0.0, "qsc_doc_frac_words_unique": 0.55855856, "qsc_doc_entropy_unigram": 4.45126941, "qsc_doc_frac_words_all_caps": 0.43939394, "qsc_doc_frac_lines_dupe_lines": 0.0, "qsc_doc_frac_chars_dupe_lines": 0.0, "qsc_doc_frac_chars_top_2grams": 0.02985075, "qsc_doc_frac_chars_top_3grams": 0.02819237, "qsc_doc_frac_chars_top_4grams": 0.03814262, "qsc_doc_frac_chars_dupe_5grams": 0.15257048, "qsc_doc_frac_chars_dupe_6grams": 0.11276949, "qsc_doc_frac_chars_dupe_7grams": 0.11276949, "qsc_doc_frac_chars_dupe_8grams": 0.11276949, "qsc_doc_frac_chars_dupe_9grams": 0.11276949, "qsc_doc_frac_chars_dupe_10grams": 0.11276949, "qsc_doc_frac_chars_replacement_symbols": 0.0, "qsc_doc_cate_code_related_file_name": 0.0, "qsc_doc_num_chars_sentence_length_mean": 39.75675676, "qsc_doc_frac_chars_hyperlink_html_tag": 0.0, "qsc_doc_frac_chars_alphabet": 0.96314103, "qsc_doc_frac_chars_digital": 0.00320513, "qsc_doc_frac_chars_whitespace": 0.17186463, "qsc_doc_frac_chars_hex_words": 0.0} | 1 | {"qsc_doc_frac_chars_replacement_symbols": 0, "qsc_doc_entropy_unigram": 0, "qsc_doc_frac_chars_top_2grams": 0, "qsc_doc_frac_chars_top_3grams": 0, "qsc_doc_frac_chars_top_4grams": 0, "qsc_doc_frac_chars_dupe_5grams": 0, "qsc_doc_frac_chars_dupe_6grams": 0, "qsc_doc_frac_chars_dupe_7grams": 0, "qsc_doc_frac_chars_dupe_8grams": 0, "qsc_doc_frac_chars_dupe_9grams": 0, "qsc_doc_frac_chars_dupe_10grams": 0, "qsc_doc_frac_chars_dupe_lines": 0, "qsc_doc_frac_lines_dupe_lines": 0, "qsc_doc_frac_lines_end_with_readmore": 0, "qsc_doc_frac_lines_start_with_bullet": 0, "qsc_doc_frac_words_all_caps": 0, "qsc_doc_mean_word_length": 0, "qsc_doc_num_chars": 0, "qsc_doc_num_lines": 0, "qsc_doc_num_sentences": 0, "qsc_doc_num_words": 0, "qsc_doc_frac_chars_hex_words": 0, "qsc_doc_frac_chars_hyperlink_html_tag": 0, "qsc_doc_frac_chars_alphabet": 0, "qsc_doc_frac_chars_digital": 0, "qsc_doc_frac_chars_whitespace": 0} |
0015/Fridge-Calendar | main/epaper.cpp | #include "epaper.hpp"
static const char *TAG = "[E-Paper]";
#define calrendar_rect_width 114
#define calrendar_rect_height 110
const char* days[] = {"Sun", "Mon", "Tue", "Wed", "Thu", "Fri", "Sat"};
EPaper::EPaper() : temp(0), fb(nullptr) {}
EPaper::~EPaper() {
// Cleanup if needed
}
void EPaper::checkError(enum EpdDrawError err) {
if (err != EPD_DRAW_SUCCESS) {
ESP_LOGE(TAG, "draw error: %X", err);
}
}
void EPaper::initialize() {
// Initialize the E-Paper display
epd_init(&DEMO_BOARD, &ED097TC2, EPD_LUT_64K);
epd_set_vcom(1560);
// Initialize the high-level EPD handler
hl = epd_hl_init(WAVEFORM);
// Set orientation to portrait mode
epd_set_rotation(EPD_ROT_INVERTED_PORTRAIT);
ESP_LOGI(TAG,
"Dimensions after rotation, width: %d height: %d\n\n",
epd_rotated_display_width(),
epd_rotated_display_height()
);
heap_caps_print_heap_info(MALLOC_CAP_INTERNAL);
heap_caps_print_heap_info(MALLOC_CAP_SPIRAM);
// Get framebuffer
fb = epd_hl_get_framebuffer(&hl);
}
void EPaper::splash(){
epd_poweron();
epd_clear();
temp = epd_ambient_temperature();
epd_poweroff();
epd_hl_set_all_white(&hl);
EpdRect home_area = {
.x = epd_rotated_display_width() / 2 - img_home_width / 2,
.y = epd_rotated_display_height() / 2 - img_home_height,
.width = img_home_width,
.height = img_home_height,
};
epd_draw_rotated_image(home_area, img_home_data, fb);
epd_poweron();
checkError(epd_hl_update_screen(&hl, MODE_GL16, temp));
epd_poweroff();
}
void EPaper::drawBar(int x, int y, int width, int height){
EpdRect bar = {
.x = x,
.y = y,
.width = width,
.height = height,
};
epd_fill_rect(bar, black, fb);
}
void EPaper::draw_progress_bar(int x, int y, int width, int percent, uint8_t* fb) {
EpdRect border = {
.x = x,
.y = y,
.width = width,
.height = 20,
};
epd_fill_rect(border, white, fb);
epd_draw_rect(border, black, fb);
EpdRect bar = {
.x = x + 5,
.y = y + 5,
.width = (width - 10) * percent / 100,
.height = 10,
};
epd_fill_rect(bar, black, fb);
checkError(epd_hl_update_area(&hl, MODE_DU, epd_ambient_temperature(), border));
}
void EPaper::drawProgressBar(int bar_x, int bar_y, int percent){
epd_poweron();
draw_progress_bar(bar_x, bar_y, 400, percent, fb);
epd_poweroff();
}
void EPaper::drawText(const EpdFont* font, TEXT_ALIGN align, int text_x, int text_y, const char* string) {
EpdFontProperties font_props = epd_font_properties_default();
switch (align) {
case TEXT_ALIGN::Left:
font_props.flags = EPD_DRAW_ALIGN_LEFT;
break;
case TEXT_ALIGN::Center:
font_props.flags = EPD_DRAW_ALIGN_CENTER;
break;
case TEXT_ALIGN::Right:
font_props.flags = EPD_DRAW_ALIGN_RIGHT;
break;
}
epd_write_string(font, string, &text_x, &text_y, fb, &font_props);
// Update screen
epd_poweron();
checkError(epd_hl_update_screen(&hl, MODE_GL16, temp));
epd_poweroff();
}
void EPaper::drawCalendarBase(int offset_pos, int max_date, const char* title, int t_day){
epd_poweron();
epd_clear();
temp = epd_ambient_temperature();
epd_poweroff();
epd_hl_set_all_white(&hl);
drawText(font_header, TEXT_ALIGN::Left, 22, 60, title);
EpdFontProperties font_props = epd_font_properties_default();
font_props.flags = EPD_DRAW_ALIGN_CENTER;
EpdFontProperties font_props_2 = epd_font_properties_default();
font_props_2.flags = EPD_DRAW_ALIGN_RIGHT;
EpdFontProperties font_props_3 = epd_font_properties_default();
font_props_3.flags = EPD_DRAW_ALIGN_RIGHT;
font_props_3.fg_color = white;
int current_day = 1; // Start from the first day of the month
int text_x = 70;
int text_y = 100;
for (int x = -1; x < 6; x++) {
for (int y = 0; y < 7; y++) {
if(x == -1){ // Draw Calendar Headers
text_x = 65 + (y * calrendar_rect_width);
text_y = 108;
epd_write_string(font_mid, days[y], &text_x, &text_y, fb, &font_props);
}else{
if (offset_pos > 0) { // Adjust starting position based on the first day of the week
offset_pos--;
continue;
}
if (current_day > max_date) { // Stop drawing once we pass the last day of the month
break;
}
int cursor_x = 10 + (y * calrendar_rect_width);
int cursor_y = 120 + (x * calrendar_rect_height);
day_coords[current_day].x = cursor_x;
day_coords[current_day].y = cursor_y;
// Define the rectangle for the current day
EpdRect border = {
.x = cursor_x,
.y = cursor_y,
.width = calrendar_rect_width,
.height = calrendar_rect_height,
};
EpdRect sub_border = {
.x = cursor_x + 70,
.y = cursor_y ,
.width = 44,
.height = 40,
};
epd_poweron();
epd_draw_rect(border, black, fb); // Draw the border of the rectangle
if(current_day == t_day){
epd_fill_rect(sub_border, black, fb);
}else{
epd_draw_rect(sub_border, black, fb); // Draw the border of the rectangle
}
char sdate[2];
sprintf(sdate, "%d", current_day);
int date_x = cursor_x + 108;
int date_y = cursor_y + 26;
if(current_day == t_day){
epd_write_string(font_mid, sdate, &date_x, &date_y, fb, &font_props_3);
}else{
epd_write_string(font_mid, sdate, &date_x, &date_y, fb, &font_props_2);
}
checkError(epd_hl_update_area(&hl, MODE_DU, temp, border));
epd_poweroff();
current_day++; // Move to the next day
}
}
}
}
void EPaper::drawTextInSlot(int slot, int cursor_x, int cursor_y, const char *text) {
EpdFontProperties font_props = epd_font_properties_default();
font_props.flags = EPD_DRAW_ALIGN_LEFT;
int text_x = cursor_x + 4;
int text_y = cursor_y + (24 * slot);
epd_write_string(font_mid, text, &text_x, &text_y, fb, &font_props);
}
EPaper::Coordinates EPaper::getCoordinatesForDay(int day) {
if (day < 1 || day > MAX_DAYS) {
return { -1, -1 }; // Invalid coordinates
}
return day_coords[day];
}
int EPaper::getWidth() {
return epd_rotated_display_width();
}
int EPaper::getHeight(){
return epd_rotated_display_height();
}
void EPaper::invalidate(){
// Update screen
epd_poweron();
checkError(epd_hl_update_screen(&hl, MODE_GL16, temp));
epd_poweroff();
} | 7,320 | epaper | cpp | en | cpp | code | {"qsc_code_num_words": 911, "qsc_code_num_chars": 7320.0, "qsc_code_mean_word_length": 4.28100988, "qsc_code_frac_words_unique": 0.22283205, "qsc_code_frac_chars_top_2grams": 0.04153846, "qsc_code_frac_chars_top_3grams": 0.02153846, "qsc_code_frac_chars_top_4grams": 0.03051282, "qsc_code_frac_chars_dupe_5grams": 0.37, "qsc_code_frac_chars_dupe_6grams": 0.33153846, "qsc_code_frac_chars_dupe_7grams": 0.27923077, "qsc_code_frac_chars_dupe_8grams": 0.19641026, "qsc_code_frac_chars_dupe_9grams": 0.17948718, "qsc_code_frac_chars_dupe_10grams": 0.15897436, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.01842211, "qsc_code_frac_chars_whitespace": 0.31775956, "qsc_code_size_file_byte": 7320.0, "qsc_code_num_lines": 262.0, "qsc_code_num_chars_line_max": 108.0, "qsc_code_num_chars_line_mean": 27.9389313, "qsc_code_frac_chars_alphabet": 0.76251502, "qsc_code_frac_chars_comments": 0.0726776, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.32967033, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.01576079, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codecpp_frac_lines_preprocessor_directives": 0.01648352, "qsc_codecpp_frac_lines_func_ratio": 0.01098901, "qsc_codecpp_cate_bitsstdc": 0.0, "qsc_codecpp_nums_lines_main": 0.0, "qsc_codecpp_frac_lines_goto": 0.0, "qsc_codecpp_cate_var_zero": 0.0, "qsc_codecpp_score_lines_no_logic": 0.01648352, "qsc_codecpp_frac_lines_print": 0.00549451} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codecpp_frac_lines_func_ratio": 0, "qsc_codecpp_nums_lines_main": 0, "qsc_codecpp_score_lines_no_logic": 0, "qsc_codecpp_frac_lines_preprocessor_directives": 0, "qsc_codecpp_frac_lines_print": 0} |
0015/Fridge-Calendar | main/g_calendar.cpp | #include "g_calendar.hpp"
#include "g_calendar_config.hpp"
#include <esp_http_client.h>
#include <string>
#include <ctime>
#include <nlohmann/json.hpp>
#include "esp_log.h"
#include "app_config.hpp"
static const char* TAG = "[Google Calendar]";
extern const char server_googleapis_root_cert_pem_start[] asm("_binary_server_googleapis_root_cert_pem_start");
extern const char server_googleapis_root_cert_pem_end[] asm("_binary_server_googleapis_root_cert_pem_end");
using json = nlohmann::json;
GoogleCalendar::GoogleCalendar(const std::string& clientId, const std::string& clientSecret, const std::string& refreshToken)
: clientId(clientId), clientSecret(clientSecret), refreshToken(refreshToken) {}
static esp_err_t _http_event_handler(esp_http_client_event_t* evt) {
static char *output_buffer; // Buffer to store response of http request from event handler
static int output_len; // Stores number of bytes read
switch (evt->event_id) {
case HTTP_EVENT_ON_DATA:
ESP_LOGD(TAG, "HTTP_EVENT_ON_DATA, len=%d", evt->data_len);
// Clean the buffer in case of a new request
if (output_len == 0 && evt->user_data) {
// we are just starting to copy the output data into the use
memset(evt->user_data, 0, MAX_HTTP_OUTPUT_BUFFER);
}
if (evt->user_data) {
char* buffer = (char*)evt->user_data;
if (output_len + evt->data_len < MAX_HTTP_OUTPUT_BUFFER) {
// Append data to the user-provided buffer
memcpy(buffer + output_len, evt->data, evt->data_len);
} else {
ESP_LOGE(TAG, "Buffer overflow, data truncated!");
}
}
output_len += evt->data_len;
break;
case HTTP_EVENT_ON_HEADER:
if (strcasecmp(evt->header_key, "Content-Length") == 0) {
ESP_LOGI(TAG, "Content-Length: %s", evt->header_value);
}
break;
case HTTP_EVENT_ON_FINISH:
ESP_LOGD(TAG, "HTTP_EVENT_ON_FINISH");
if (output_buffer != NULL) {
free(output_buffer);
output_buffer = NULL;
}
output_len = 0;
break;
default:
break;
}
return ESP_OK;
}
std::string GoogleCalendar::refreshAccessToken() {
const std::string url = "https://oauth2.googleapis.com/token";
std::string accessToken;
char local_response_buffer[MAX_HTTP_OUTPUT_BUFFER + 1] = {0};
esp_http_client_config_t config = {};
config.url = url.c_str();
config.cert_pem = server_googleapis_root_cert_pem_start;
config.cert_len = server_googleapis_root_cert_pem_end - server_googleapis_root_cert_pem_start;
config.event_handler = _http_event_handler;
config.user_data = local_response_buffer; // Pass address of local buffer to get response
config.disable_auto_redirect = true;
esp_log_level_set("*", ESP_LOG_DEBUG);
esp_http_client_handle_t client = esp_http_client_init(&config);
std::string postData =
"client_id=" + CalendarConfig::getClientId() +
"&client_secret=" + CalendarConfig::getClientSecret() +
"&refresh_token=" + CalendarConfig::getRefreshToken() +
"&grant_type=refresh_token";
esp_http_client_set_url(client, url.c_str());
esp_http_client_set_method(client, HTTP_METHOD_POST);
esp_http_client_set_header(client, "Content-Type", "application/x-www-form-urlencoded");
esp_http_client_set_post_field(client, postData.c_str(), postData.length());
ESP_LOGI(TAG, "Sending POST Data: %s", postData.c_str());
ESP_LOGI(TAG, "Sending POST length: %d", postData.length());
if (esp_http_client_perform(client) == ESP_OK) {
int statusCode = esp_http_client_get_status_code(client);
if (statusCode == 200) {
json jsonResponse = json::parse(local_response_buffer);
if (jsonResponse.contains("access_token")) {
accessToken = jsonResponse["access_token"].get<std::string>();
CalendarConfig::setAccessToken(accessToken); // Update the access token
} else {
ESP_LOGE(TAG, "Missing 'access_token' in the response.");
}
}else{
ESP_LOGE(TAG, "HTTP status code: %d", statusCode);
}
}else{
ESP_LOGE(TAG, "HTTP request failed.");
}
esp_http_client_cleanup(client);
return accessToken;
}
esp_err_t GoogleCalendar::getEvents(const std::string& accessToken, const std::string& calendarId, std::vector<CalendarEvent>& events) {
const std::string baseUrl = "https://www.googleapis.com/calendar/v3/calendars/";
const std::string timeRange = createTimeRange();
const std::string url = baseUrl + calendarId + "/events" + timeRange;
esp_err_t ret = ESP_OK;
ESP_LOGI(TAG, "accessToken: %s", accessToken.c_str());
char local_response_buffer[MAX_HTTP_OUTPUT_BUFFER + 1] = {0};
esp_http_client_config_t config = {};
config.url = url.c_str();
config.timeout_ms = 10000;
config.cert_pem = server_googleapis_root_cert_pem_start;
config.cert_len = server_googleapis_root_cert_pem_end - server_googleapis_root_cert_pem_start;
config.event_handler = _http_event_handler;
config.user_data = local_response_buffer; // Pass address of local buffer to get response
config.buffer_size_tx = MAX_HTTP_TX_BUFFER;
config.disable_auto_redirect = true;
esp_http_client_handle_t client = esp_http_client_init(&config);
esp_http_client_set_method(client, HTTP_METHOD_GET);
esp_http_client_set_header(client, "Authorization", ("Bearer " + accessToken).c_str());
if (esp_http_client_perform(client) == ESP_OK) {
int statusCode = esp_http_client_get_status_code(client);
if (statusCode == 200) {
parseEvents(local_response_buffer, events);
}else{
ret = ESP_ERR_HTTP_INVALID_TRANSPORT;
}
}else{
ret = ESP_ERR_HTTP_CONNECT;
}
esp_http_client_cleanup(client);
return ret;
}
void GoogleCalendar::parseEvents(const std::string& payload, std::vector<CalendarEvent>& eventsVector) {
json response = json::parse(payload);
if (response.contains("items")) {
for (const auto& item : response["items"]) {
CalendarEvent calEvent;
calEvent.summary = item.value("summary", "");
calEvent.description = item.value("description", "");
calEvent.creatorEmail = item["creator"].value("email", "");
calEvent.organizerDisplayName = item["organizer"].value("displayName", "");
if (item["start"].contains("date")) {
calEvent.start = item["start"]["date"].get<std::string>();
calEvent.end = item["end"]["date"].get<std::string>();
calEvent.isAllDayEvent = true;
} else {
calEvent.start = item["start"]["dateTime"].get<std::string>();
calEvent.end = item["end"]["dateTime"].get<std::string>();
calEvent.isAllDayEvent = false;
}
eventsVector.push_back(calEvent);
}
}
}
std::string GoogleCalendar::createTimeRange() {
time_t now;
struct tm timeinfo;
char timeMin[40], timeMax[40];
time(&now);
localtime_r(&now, &timeinfo);
// First day of the current month
snprintf(timeMin, sizeof(timeMin), "%04d-%02d-01T00:00:00Z",
timeinfo.tm_year + 1900, timeinfo.tm_mon + 1);
// Last day of the current month
int lastDay = 31;
if (timeinfo.tm_mon + 1 == 4 || timeinfo.tm_mon + 1 == 6 ||
timeinfo.tm_mon + 1 == 9 || timeinfo.tm_mon + 1 == 11) {
lastDay = 30;
} else if (timeinfo.tm_mon + 1 == 2) {
lastDay = (timeinfo.tm_year % 4 == 0 && (timeinfo.tm_year % 100 != 0 || timeinfo.tm_year % 400 == 0)) ? 29 : 28;
}
snprintf(timeMax, sizeof(timeMax), "%04d-%02d-%02dT23:59:59Z",
timeinfo.tm_year + 1900, timeinfo.tm_mon + 1, lastDay);
return "?timeMin=" + std::string(timeMin) + "&timeMax=" + std::string(timeMax);
}
| 8,241 | g_calendar | cpp | en | cpp | code | {"qsc_code_num_words": 995, "qsc_code_num_chars": 8241.0, "qsc_code_mean_word_length": 4.99899497, "qsc_code_frac_words_unique": 0.24020101, "qsc_code_frac_chars_top_2grams": 0.03799759, "qsc_code_frac_chars_top_3grams": 0.05227181, "qsc_code_frac_chars_top_4grams": 0.0482509, "qsc_code_frac_chars_dupe_5grams": 0.37454765, "qsc_code_frac_chars_dupe_6grams": 0.30377965, "qsc_code_frac_chars_dupe_7grams": 0.25693607, "qsc_code_frac_chars_dupe_8grams": 0.23039807, "qsc_code_frac_chars_dupe_9grams": 0.18536389, "qsc_code_frac_chars_dupe_10grams": 0.18536389, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.01405302, "qsc_code_frac_chars_whitespace": 0.24014076, "qsc_code_size_file_byte": 8241.0, "qsc_code_num_lines": 206.0, "qsc_code_num_chars_line_max": 138.0, "qsc_code_num_chars_line_mean": 40.00485437, "qsc_code_frac_chars_alphabet": 0.7802619, "qsc_code_frac_chars_comments": 0.05254217, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.19753086, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.10630123, "qsc_code_frac_chars_long_word_length": 0.02727971, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codecpp_frac_lines_preprocessor_directives": 0.0617284, "qsc_codecpp_frac_lines_func_ratio": 0.00617284, "qsc_codecpp_cate_bitsstdc": 0.0, "qsc_codecpp_nums_lines_main": 0.0, "qsc_codecpp_frac_lines_goto": 0.0, "qsc_codecpp_cate_var_zero": 0.0, "qsc_codecpp_score_lines_no_logic": 0.08024691, "qsc_codecpp_frac_lines_print": 0.01234568} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codecpp_frac_lines_func_ratio": 0, "qsc_codecpp_nums_lines_main": 0, "qsc_codecpp_score_lines_no_logic": 0, "qsc_codecpp_frac_lines_preprocessor_directives": 0, "qsc_codecpp_frac_lines_print": 0} |
0015/esp_rlottie | rlottie/example/meson.build |
override_default = ['warning_level=2', 'werror=false']
common_source = files('evasapp.cpp')
common_source += files('lottieview.cpp')
demo_sources = files('demo.cpp')
demo_sources += common_source
executable('lottie2gif',
'lottie2gif.cpp',
include_directories : inc,
override_options : override_default,
link_with : rlottie_lib)
if host_machine.system() != 'windows'
executable('perf',
'lottieperf.cpp',
include_directories : inc,
override_options : override_default,
link_with : rlottie_lib)
endif
demo_dep = dependency('elementary', required : false, disabler : true)
executable('demo',
demo_sources,
include_directories : inc,
override_options : override_default,
link_with : rlottie_lib,
dependencies : demo_dep)
demo_marker_sources = files('demo_marker.cpp')
demo_marker_sources += common_source
executable('demo_marker',
demo_marker_sources,
include_directories : inc,
override_options : override_default,
link_with : rlottie_lib,
dependencies : demo_dep)
lottieview_test_src = files('lottieviewtest.cpp')
lottieview_test_src += common_source
executable('lottieviewTest',
lottieview_test_src,
include_directories : inc,
override_options : override_default,
link_with : rlottie_lib,
dependencies : demo_dep)
uxsample_test_src = files('uxsampletest.cpp')
uxsample_test_src += common_source
executable('uxsampleTest',
uxsample_test_src,
include_directories : inc,
override_options : override_default,
link_with : rlottie_lib,
dependencies : demo_dep)
lottieviewer_sources = files('lottieviewer.cpp')
lottieviewer_sources += common_source
executable('lottieviewer',
lottieviewer_sources,
include_directories : inc,
override_options : override_default,
link_with : rlottie_lib,
dependencies : demo_dep)
| 2,107 | meson | build | en | unknown | unknown | {} | 0 | {} |
0015/esp_rlottie | rlottie/example/demo.cpp | /*
* Copyright (c) 2020 Samsung Electronics Co., Ltd. All rights reserved.
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "evasapp.h"
#include "lottieview.h"
#include<iostream>
#include <stdio.h>
#include <fstream>
#include <sstream>
using namespace std;
class Demo
{
public:
Demo(EvasApp *app, std::string &filePath) {
Demo1(app, filePath);
Demo2(app, filePath);
Demo3(app, filePath);
Demo4(app, filePath);
Demo5(app, filePath);
Demo6(app, filePath);
Demo7(app, filePath);
Demo8(app, filePath);
}
void Demo1(EvasApp *app, std::string &filePath) {
/* Fill Color */
view1.reset(new LottieView(app->evas()));
view1->setFilePath(filePath.c_str());
if (view1->player()) {
view1->player()->setValue<rlottie::Property::FillColor>("Shape Layer 1.Ellipse 1.Fill 1",
[](const rlottie::FrameInfo& info) {
if (info.curFrame() < 60 )
return rlottie::Color(0, 0, 1);
else {
return rlottie::Color(1, 0, 0);
}
});
}
view1->setPos(0, 0);
view1->setSize(300, 300);
view1->show();
view1->play();
view1->loop(true);
view1->setRepeatMode(LottieView::RepeatMode::Reverse);
}
void Demo2(EvasApp *app, std::string &filePath) {
/* Stroke Opacity */
view2.reset(new LottieView(app->evas()));
view2->setFilePath(filePath.c_str());
if (view2->player()) {
view2->player()->setValue<rlottie::Property::StrokeOpacity>("Shape Layer 2.Shape 1.Stroke 1",
[](const rlottie::FrameInfo& info) {
if (info.curFrame() < 60 )
return 20;
else {
return 100;
}
});
}
view2->setPos(300, 0);
view2->setSize(300, 300);
view2->show();
view2->play();
view2->loop(true);
view2->setRepeatMode(LottieView::RepeatMode::Reverse);
}
void Demo3(EvasApp *app, std::string &filePath) {
/* Stroke Opacity */
view3.reset(new LottieView(app->evas()));
view3->setFilePath(filePath.c_str());
if (view3->player()) {
view3->player()->setValue<rlottie::Property::StrokeWidth>("**",
[](const rlottie::FrameInfo& info) {
if (info.curFrame() < 60 )
return 1.0;
else {
return 5.0;
}
});
}
view3->setPos(600, 0);
view3->setSize(300, 300);
view3->show();
view3->play();
view3->loop(true);
view3->setRepeatMode(LottieView::RepeatMode::Reverse);
}
void Demo4(EvasApp *app, std::string &filePath) {
/* Transform position */
view4.reset(new LottieView(app->evas()));
view4->setFilePath(filePath.c_str());
if (view4->player()) {
view4->player()->setValue<rlottie::Property::TrPosition>("Shape Layer 1.Ellipse 1",
[](const rlottie::FrameInfo& info) {
return rlottie::Point(-20 + (double)info.curFrame()/2.0,
-20 + (double)info.curFrame()/2.0);
});
}
view4->setPos(900, 0);
view4->setSize(300, 300);
view4->show();
view4->play();
view4->loop(true);
view4->setRepeatMode(LottieView::RepeatMode::Reverse);
}
void Demo5(EvasApp *app, std::string &filePath) {
/* Transform position */
view5.reset(new LottieView(app->evas()));
view5->setFilePath(filePath.c_str());
if (view5->player()) {
view5->player()->setValue<rlottie::Property::TrPosition>("Shape Layer 2.Shape 1",
[](const rlottie::FrameInfo& info) {
return rlottie::Point(-20 + (double)info.curFrame()/2.0,
-20 + (double)info.curFrame()/2.0);
});
}
view5->setPos(1200, 0);
view5->setSize(300, 300);
view5->show();
view5->play();
view5->loop(true);
view5->setRepeatMode(LottieView::RepeatMode::Reverse);
}
void Demo6(EvasApp *app, std::string &filePath) {
/* Transform scale */
view6.reset(new LottieView(app->evas()));
view6->setFilePath(filePath.c_str());
if (view6->player()) {
view6->player()->setValue<rlottie::Property::TrScale>("Shape Layer 1.Ellipse 1",
[](const rlottie::FrameInfo& info) {
return rlottie::Size(100 - info.curFrame(),
50);
});
}
view6->setPos(1500, 0);
view6->setSize(300, 300);
view6->show();
view6->play();
view6->loop(true);
view6->setRepeatMode(LottieView::RepeatMode::Reverse);
}
void Demo7(EvasApp *app, std::string &filePath) {
/* Transform rotation */
view7.reset(new LottieView(app->evas()));
view7->setFilePath(filePath.c_str());
if (view7->player()) {
view7->player()->setValue<rlottie::Property::TrRotation>("Shape Layer 2.Shape 1",
[](const rlottie::FrameInfo& info) {
return info.curFrame() * 20;
});
}
view7->setPos(1800, 0);
view7->setSize(300, 300);
view7->show();
view7->play();
view7->loop(true);
view7->setRepeatMode(LottieView::RepeatMode::Reverse);
}
void Demo8(EvasApp *app, std::string &filePath) {
/* Transform + color */
view8.reset(new LottieView(app->evas()));
view8->setFilePath(filePath.c_str());
if (view8->player()) {
view8->player()->setValue<rlottie::Property::TrRotation>("Shape Layer 1.Ellipse 1",
[](const rlottie::FrameInfo& info) {
return info.curFrame() * 20;
});
view8->player()->setValue<rlottie::Property::TrScale>("Shape Layer 1.Ellipse 1",
[](const rlottie::FrameInfo& info) {
return rlottie::Size(50, 100 - info.curFrame());
});
view8->player()->setValue<rlottie::Property::TrPosition>("Shape Layer 1.Ellipse 1",
[](const rlottie::FrameInfo& info) {
return rlottie::Point(-20 + (double)info.curFrame()/2.0,
-20 + (double)info.curFrame()/2.0);
});
view8->player()->setValue<rlottie::Property::FillColor>("Shape Layer 1.Ellipse 1.Fill 1",
[](const rlottie::FrameInfo& info) {
if (info.curFrame() < 60 )
return rlottie::Color(0, 0, 1);
else {
return rlottie::Color(1, 0, 0);
}
});
}
view8->setPos(2100, 0);
view8->setSize(300, 300);
view8->show();
view8->play();
view8->loop(true);
view8->setRepeatMode(LottieView::RepeatMode::Reverse);
}
private:
std::unique_ptr<LottieView> view1;
std::unique_ptr<LottieView> view2;
std::unique_ptr<LottieView> view3;
std::unique_ptr<LottieView> view4;
std::unique_ptr<LottieView> view5;
std::unique_ptr<LottieView> view6;
std::unique_ptr<LottieView> view7;
std::unique_ptr<LottieView> view8;
};
static void
onExitCb(void *data, void */*extra*/)
{
Demo *demo = (Demo *)data;
delete demo;
}
int
main(void)
{
EvasApp *app = new EvasApp(2400, 300);
app->setup();
std::string filePath = DEMO_DIR;
filePath +="done.json";
auto demo = new Demo(app, filePath);
app->addExitCb(onExitCb, demo);
app->run();
delete app;
return 0;
}
| 9,226 | demo | cpp | en | cpp | code | {"qsc_code_num_words": 944, "qsc_code_num_chars": 9226.0, "qsc_code_mean_word_length": 5.18326271, "qsc_code_frac_words_unique": 0.22245763, "qsc_code_frac_chars_top_2grams": 0.03433476, "qsc_code_frac_chars_top_3grams": 0.0472103, "qsc_code_frac_chars_top_4grams": 0.06519518, "qsc_code_frac_chars_dupe_5grams": 0.46985489, "qsc_code_frac_chars_dupe_6grams": 0.30656039, "qsc_code_frac_chars_dupe_7grams": 0.28448804, "qsc_code_frac_chars_dupe_8grams": 0.22624157, "qsc_code_frac_chars_dupe_9grams": 0.22624157, "qsc_code_frac_chars_dupe_10grams": 0.21091355, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.04679209, "qsc_code_frac_chars_whitespace": 0.32592673, "qsc_code_size_file_byte": 9226.0, "qsc_code_num_lines": 257.0, "qsc_code_num_chars_line_max": 106.0, "qsc_code_num_chars_line_mean": 35.89883268, "qsc_code_frac_chars_alphabet": 0.73999035, "qsc_code_frac_chars_comments": 0.14404943, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.20095694, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.03535226, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codecpp_frac_lines_preprocessor_directives": 0.03349282, "qsc_codecpp_frac_lines_func_ratio": 0.09569378, "qsc_codecpp_cate_bitsstdc": 0.0, "qsc_codecpp_nums_lines_main": 1.0, "qsc_codecpp_frac_lines_goto": 0.0, "qsc_codecpp_cate_var_zero": 0.0, "qsc_codecpp_score_lines_no_logic": 0.13875598, "qsc_codecpp_frac_lines_print": 0.0} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codecpp_frac_lines_func_ratio": 0, "qsc_codecpp_nums_lines_main": 0, "qsc_codecpp_score_lines_no_logic": 0, "qsc_codecpp_frac_lines_preprocessor_directives": 0, "qsc_codecpp_frac_lines_print": 0} |
0015/esp_rlottie | rlottie/example/lottieviewtest.cpp | /*
* Copyright (c) 2020 Samsung Electronics Co., Ltd. All rights reserved.
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "evasapp.h"
#include "lottieview.h"
#include<iostream>
#include <dirent.h>
#include <stdio.h>
#include <chrono>
using namespace std;
static Eina_Bool onTestDone(void *data);
/*
* To check the frame rate with rendermode off run
* ECORE_EVAS_FPS_DEBUG=1 ./lottieviewTest --disable-render
*
* To check the frame rate with render backend
* ECORE_EVAS_FPS_DEBUG=1 ./lottieviewTest
*
*/
class LottieViewTest
{
public:
LottieViewTest(EvasApp *app, Strategy st, double timeout) {
mStartTime = std::chrono::high_resolution_clock::now();
mStrategy = st;
mApp = app;
if (timeout > 0) {
ecore_timer_add(timeout, onTestDone, mApp);
}
// work around for 60fps
ecore_animator_frametime_set(1.0f/120.0f);
}
void show(int numberOfImage) {
auto resource = EvasApp::jsonFiles(std::string(DEMO_DIR));
if (resource.empty()) return;
int count = numberOfImage;
int colums = (int) ceil(sqrt(count));
int offset = 3;
int vw = (mApp->width() - (offset * colums))/colums;
int vh = vw;
int posx = offset;
int posy = offset;
int resourceSize = resource.size();
for (int i = 0 ; i < numberOfImage; i++) {
int index = i % resourceSize;
std::unique_ptr<LottieView> view(new LottieView(mApp->evas(), mStrategy));
view->setFilePath(resource[index].c_str());
view->setPos(posx, posy);
view->setSize(vw, vh);
view->show();
view->play();
view->loop(true);
//view->setRepeatMode(LottieView::RepeatMode::Reverse);
posx += vw+offset;
if ((mApp->width() - posx) < vw) {
posx = offset;
posy = posy + vh + offset;
}
mViews.push_back(std::move(view));
}
}
~LottieViewTest() {
const auto frames = mViews.empty() ? 0 : mViews[0]->renderCount();
const double secs = std::chrono::duration<double>(std::chrono::high_resolution_clock::now() - mStartTime).count();
std::cout<<"\tTestTime : "<< secs<<" sec \n\tTotalFrames : "<<frames<<"\n\tFramesPerSecond : "<< frames / secs <<" fps\n";
}
static int help() {
printf("Usage ./lottieviewTest [-s] [strategy] [-t] [timeout] [-c] [count]\n");
printf("\n \t-t : timeout duration in seconds\n");
printf("\n \t-c : number of resource in the grid\n");
printf("\n \t-s : Rendering Strategy\n");
printf("\t\t 0 - Test Lottie SYNC Renderer with CPP API\n");
printf("\t\t 1 - Test Lottie ASYNC Renderer with CPP API\n");
printf("\t\t 2 - Test Lottie SYNC Renderer with C API\n");
printf("\t\t 3 - Test Lottie ASYNC Renderer with C API\n");
printf("\t\t 4 - Test Lottie Tree Api using Efl VG Render\n");
printf(" Default : ./lottieviewTest -s 1 \n");
return 0;
}
public:
EvasApp *mApp;
Strategy mStrategy;
std::vector<std::unique_ptr<LottieView>> mViews;
std::chrono::high_resolution_clock::time_point mStartTime;
};
static void
onExitCb(void *data, void */*extra*/)
{
LottieViewTest *view = (LottieViewTest *)data;
delete view;
}
static Eina_Bool
onTestDone(void *data)
{
EvasApp *app = (EvasApp *)data;
app->exit();
return ECORE_CALLBACK_CANCEL;
}
int
main(int argc, char **argv)
{
Strategy st = Strategy::renderCppAsync;
auto index = 0;
double timeOut = 0;
size_t itemCount = 250;
while (index < argc) {
const char* option = argv[index];
index++;
if (!strcmp(option,"--help") || !strcmp(option,"-h")) {
return LottieViewTest::help();
} else if (!strcmp(option,"-s")) {
st = (index < argc) ? static_cast<Strategy>(atoi(argv[index])) : Strategy::renderCppAsync;
index++;
} else if (!strcmp(option,"-t")) {
timeOut = (index < argc) ? atoi(argv[index]) : 10;
index++;
} else if (!strcmp(option,"-c")) {
itemCount = (index < argc) ? atoi(argv[index]) : 10;
index++;
}
}
EvasApp *app = new EvasApp(800, 800);
app->setup();
LottieViewTest *view = new LottieViewTest(app, st, timeOut);
view->show(itemCount);
app->addExitCb(onExitCb, view);
app->run();
delete app;
return 0;
}
| 5,437 | lottieviewtest | cpp | en | cpp | code | {"qsc_code_num_words": 693, "qsc_code_num_chars": 5437.0, "qsc_code_mean_word_length": 4.89177489, "qsc_code_frac_words_unique": 0.37373737, "qsc_code_frac_chars_top_2grams": 0.01858407, "qsc_code_frac_chars_top_3grams": 0.01179941, "qsc_code_frac_chars_top_4grams": 0.01327434, "qsc_code_frac_chars_dupe_5grams": 0.15486726, "qsc_code_frac_chars_dupe_6grams": 0.11740413, "qsc_code_frac_chars_dupe_7grams": 0.04778761, "qsc_code_frac_chars_dupe_8grams": 0.03067847, "qsc_code_frac_chars_dupe_9grams": 0.0, "qsc_code_frac_chars_dupe_10grams": 0.0, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.01013514, "qsc_code_frac_chars_whitespace": 0.23781497, "qsc_code_size_file_byte": 5437.0, "qsc_code_num_lines": 170.0, "qsc_code_num_chars_line_max": 129.0, "qsc_code_num_chars_line_mean": 31.98235294, "qsc_code_frac_chars_alphabet": 0.80791506, "qsc_code_frac_chars_comments": 0.26705904, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.06837607, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.00854701, "qsc_code_frac_chars_string_length": 0.14145729, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codecpp_frac_lines_preprocessor_directives": 0.06837607, "qsc_codecpp_frac_lines_func_ratio": 0.07692308, "qsc_codecpp_cate_bitsstdc": 0.0, "qsc_codecpp_nums_lines_main": 1.0, "qsc_codecpp_frac_lines_goto": 0.0, "qsc_codecpp_cate_var_zero": 0.0, "qsc_codecpp_score_lines_no_logic": 0.15384615, "qsc_codecpp_frac_lines_print": 0.09401709} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codecpp_frac_lines_func_ratio": 0, "qsc_codecpp_nums_lines_main": 0, "qsc_codecpp_score_lines_no_logic": 0, "qsc_codecpp_frac_lines_preprocessor_directives": 0, "qsc_codecpp_frac_lines_print": 0} |
0015/esp_rlottie | rlottie/example/evasapp.h | /*
* Copyright (c) 2020 Samsung Electronics Co., Ltd. All rights reserved.
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#ifndef EVASAPP_H
#define EVASAPP_H
#ifndef EFL_BETA_API_SUPPORT
#define EFL_BETA_API_SUPPORT
#endif
#ifndef EFL_EO_API_SUPPORT
#define EFL_EO_API_SUPPORT
#endif
#include <Eo.h>
#include <Efl.h>
#include <Evas.h>
#include <Ecore.h>
#include <Ecore_Evas.h>
#include <Ecore_Input.h>
#include<vector>
#include<string>
typedef void (*appCb)(void *userData, void *extra);
class EvasApp
{
public:
EvasApp(int w, int h);
void setup();
void resize(int w, int h);
int width() const{ return mw;}
int height() const{ return mh;}
void run();
Ecore_Evas * ee() const{return mEcoreEvas;}
Evas * evas() const {return mEvas;}
void addExitCb(appCb exitcb, void *data) {mExitCb = exitcb; mExitData = data;}
void addResizeCb(appCb resizecb, void *data) {mResizeCb = resizecb; mResizeData = data;}
void addKeyCb(appCb keycb, void *data) {mKeyCb = keycb; mKeyData = data;}
void addRenderPreCb(appCb renderPrecb, void *data) {mRenderPreCb = renderPrecb; mRenderPreData = data;}
void addRenderPostCb(appCb renderPostcb, void *data) {mRenderPostCb = renderPostcb; mRenderPostData = data;}
void exit();
static std::vector<std::string> jsonFiles(const std::string &dir, bool recurse=false);
public:
int mw{0};
int mh{0};
Ecore_Evas *mEcoreEvas{nullptr};
Evas *mEvas{nullptr};
Evas_Object *mBackground{nullptr};
appCb mResizeCb{nullptr};
void *mResizeData{nullptr};
appCb mExitCb{nullptr};
void *mExitData{nullptr};
appCb mKeyCb{nullptr};
void *mKeyData{nullptr};
appCb mRenderPreCb{nullptr};
void *mRenderPreData{nullptr};
appCb mRenderPostCb{nullptr};
void *mRenderPostData{nullptr};
};
#endif //EVASAPP_H
| 2,957 | evasapp | h | en | c | code | {"qsc_code_num_words": 387, "qsc_code_num_chars": 2957.0, "qsc_code_mean_word_length": 5.32299742, "qsc_code_frac_words_unique": 0.43410853, "qsc_code_frac_chars_top_2grams": 0.04271845, "qsc_code_frac_chars_top_3grams": 0.01893204, "qsc_code_frac_chars_top_4grams": 0.01650485, "qsc_code_frac_chars_dupe_5grams": 0.0, "qsc_code_frac_chars_dupe_6grams": 0.0, "qsc_code_frac_chars_dupe_7grams": 0.0, "qsc_code_frac_chars_dupe_8grams": 0.0, "qsc_code_frac_chars_dupe_9grams": 0.0, "qsc_code_frac_chars_dupe_10grams": 0.0, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.00255319, "qsc_code_frac_chars_whitespace": 0.20527562, "qsc_code_size_file_byte": 2957.0, "qsc_code_num_lines": 80.0, "qsc_code_num_chars_line_max": 113.0, "qsc_code_num_chars_line_mean": 36.9625, "qsc_code_frac_chars_alphabet": 0.87404255, "qsc_code_frac_chars_comments": 0.39228948, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.09433962, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.0, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codec_frac_lines_func_ratio": 0.24528302, "qsc_codec_cate_bitsstdc": 0.0, "qsc_codec_nums_lines_main": 0, "qsc_codec_frac_lines_goto": 0.0, "qsc_codec_cate_var_zero": 0.0, "qsc_codec_score_lines_no_logic": 0.37735849, "qsc_codec_frac_lines_print": 0.0, "qsc_codec_frac_lines_preprocessor_directives": null} | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codec_frac_lines_func_ratio": 1, "qsc_codec_nums_lines_main": 0, "qsc_codec_score_lines_no_logic": 0, "qsc_codec_frac_lines_preprocessor_directives": 0, "qsc_codec_frac_lines_print": 0} |
0015/esp_rlottie | rlottie/example/lottieviewer.cpp | /*
* Copyright (c) 2020 Samsung Electronics Co., Ltd. All rights reserved.
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include <Elementary.h>
#include "lottieview.h"
#include "evasapp.h"
#include<iostream>
#include <stdio.h>
#include <stdlib.h>
#include <sys/types.h>
#include <dirent.h>
#include <error.h>
#include <algorithm>
using namespace std;
typedef struct _AppInfo AppInfo;
struct _AppInfo {
LottieView *view;
Evas_Object *layout;
Evas_Object *slider;
Evas_Object *button;
Ecore_Animator *animator;
Eina_Bool autoPlaying;
};
typedef struct _ItemData ItemData;
struct _ItemData {
int index;
};
std::vector<std::string> jsonFiles;
bool renderMode = true;
static void
_layout_del_cb(void *data, Evas *, Evas_Object *, void *)
{
AppInfo *info = (AppInfo *)data;
if (info->view) delete info->view;
ecore_animator_del(info->animator);
free(info);
}
static void
_update_frame_info(AppInfo *info)
{
long currFrameNo = info->view->mCurFrame;
long totalFrameNo = info->view->getTotalFrame();
char buf[64];
sprintf(buf, "%ld (total: %ld)", currFrameNo, totalFrameNo);
elm_object_part_text_set(info->layout, "text", buf);
}
static void
_toggle_start_button(AppInfo *info)
{
if (!info->autoPlaying)
{
info->autoPlaying = EINA_TRUE;
info->view->play();
elm_object_text_set(info->button, "Stop");
}
else
{
info->autoPlaying = EINA_FALSE;
info->view->stop();
elm_object_text_set(info->button, "Start");
}
}
static Eina_Bool
_animator_cb(void *data)
{
AppInfo *info = (AppInfo *)data;
if (info && info->autoPlaying && info->view)
{
float pos = info->view->getPos();
_update_frame_info(info);
elm_slider_value_set(info->slider, (double)pos);
evas_object_image_pixels_dirty_set(info->view->getImage(), EINA_TRUE);
if (pos >= 1.0)
_toggle_start_button(info);
}
return ECORE_CALLBACK_RENEW;
}
static void
_slider_cb(void *data, Evas_Object *obj, void *event_info EINA_UNUSED)
{
double val = elm_slider_value_get(obj);
AppInfo *info = (AppInfo *)data;
if (!info->autoPlaying)
{
info->view->seek(val);
evas_object_image_pixels_dirty_set(info->view->getImage(), EINA_TRUE);
}
_update_frame_info(info);
}
static void
_button_clicked_cb(void *data, Evas_Object */*obj*/, void */*event_info*/)
{
AppInfo *info = (AppInfo *)data;
if (info->view->getPos() >= 1.0f) info->view->mPos = 0.0f;
_toggle_start_button(info);
}
Evas_Object *
create_layout(Evas_Object *parent, const char *file)
{
Evas_Object *layout, *slider, *image, *button;
Ecore_Animator *animator;
AppInfo *info = (AppInfo *)calloc(sizeof(AppInfo), 1);
//LAYOUT
layout = elm_layout_add(parent);
evas_object_show(layout);
evas_object_size_hint_weight_set(layout, EVAS_HINT_EXPAND, EVAS_HINT_EXPAND);
std::string edjPath = DEMO_DIR;
edjPath +="layout.edj";
elm_layout_file_set(layout, edjPath.c_str(), "layout");
//LOTTIEVIEW
LottieView *view = new LottieView(evas_object_evas_get(layout), Strategy::renderCppAsync);
view->setFilePath(file);
view->setSize(500, 500);
//IMAGE from LOTTIEVIEW
image = view->getImage();
evas_object_show(image);
elm_object_part_content_set(layout, "lottie", image);
//SLIDER
slider = elm_slider_add(layout);
elm_object_part_content_set(layout, "slider", slider);
elm_slider_step_set(slider, 0.01);
evas_object_smart_callback_add(slider, "changed", _slider_cb, (void *)info);
button = elm_button_add(layout);
elm_object_text_set(button, "Start");
elm_object_part_content_set(layout, "button", button);
evas_object_smart_callback_add(button, "clicked", _button_clicked_cb, (void *)info);
animator = ecore_animator_add(_animator_cb, info);
info->view = view;
info->layout = layout;
info->slider = slider;
info->button = button;
info->animator = animator;
evas_object_event_callback_add(layout, EVAS_CALLBACK_DEL, _layout_del_cb, (void *)info);
view->seek(0.0);
_update_frame_info(info);
return layout;
}
static void
_gl_selected_cb(void *data, Evas_Object */*obj*/, void *event_info)
{
Evas_Object *nf = (Evas_Object *)data;
Elm_Object_Item *it = (Elm_Object_Item *)event_info;
elm_genlist_item_selected_set(it, EINA_FALSE);
Evas_Object *layout = create_layout(nf, jsonFiles[elm_genlist_item_index_get(it) - 1].c_str());
elm_naviframe_item_push(nf, NULL, NULL, NULL, layout, NULL);
}
static char *
_gl_text_get(void *data, Evas_Object */*obj*/, const char */*part*/)
{
ItemData *id = (ItemData *) data;
const char *ptr = strrchr(jsonFiles[id->index].c_str(), '/');
int len = int(ptr + 1 - jsonFiles[id->index].c_str()); // +1 to include '/'
return strdup(jsonFiles[id->index].substr(len).c_str());
}
static void
_gl_del(void */*data*/, Evas_Object */*obj*/)
{
}
EAPI_MAIN int
elm_main(int argc EINA_UNUSED, char **argv EINA_UNUSED)
{
Evas_Object *win, *nf, *genlist;
Elm_Genlist_Item_Class *itc = elm_genlist_item_class_new();
ItemData *itemData;
if (argc > 1) {
if (!strcmp(argv[1], "--disable-render"))
renderMode = false;
}
//WIN
elm_policy_set(ELM_POLICY_QUIT, ELM_POLICY_QUIT_LAST_WINDOW_CLOSED);
win = elm_win_util_standard_add("lottie", "LottieViewer");
elm_win_autodel_set(win, EINA_TRUE);
evas_object_resize(win, 500, 700);
evas_object_show(win);
//NAVIFRAME
nf = elm_naviframe_add(win);
evas_object_size_hint_weight_set(nf, EVAS_HINT_EXPAND, EVAS_HINT_EXPAND);
elm_win_resize_object_add(win, nf);
evas_object_show(nf);
//GENLIST
genlist = elm_genlist_add(nf);
elm_genlist_mode_set(genlist, ELM_LIST_COMPRESS);
evas_object_smart_callback_add(genlist, "selected", _gl_selected_cb, nf);
itc->item_style = "default";
itc->func.text_get = _gl_text_get;
itc->func.del = _gl_del;
jsonFiles = EvasApp::jsonFiles(DEMO_DIR);
for (uint32_t i = 0; i < jsonFiles.size(); i++) {
itemData = (ItemData *)calloc(sizeof(ItemData), 1);
itemData->index = i;
elm_genlist_item_append(genlist, itc, (void *)itemData, NULL, ELM_GENLIST_ITEM_NONE, NULL, NULL);
}
elm_naviframe_item_push(nf, "Lottie Viewer", NULL, NULL, genlist, NULL);
elm_run();
return 0;
}
ELM_MAIN()
| 7,405 | lottieviewer | cpp | en | cpp | code | {"qsc_code_num_words": 1019, "qsc_code_num_chars": 7405.0, "qsc_code_mean_word_length": 4.81648675, "qsc_code_frac_words_unique": 0.26202159, "qsc_code_frac_chars_top_2grams": 0.06112469, "qsc_code_frac_chars_top_3grams": 0.01466993, "qsc_code_frac_chars_top_4grams": 0.01833741, "qsc_code_frac_chars_dupe_5grams": 0.16035045, "qsc_code_frac_chars_dupe_6grams": 0.11878566, "qsc_code_frac_chars_dupe_7grams": 0.05664222, "qsc_code_frac_chars_dupe_8grams": 0.04360228, "qsc_code_frac_chars_dupe_9grams": 0.04360228, "qsc_code_frac_chars_dupe_10grams": 0.02159739, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.00654022, "qsc_code_frac_chars_whitespace": 0.17407157, "qsc_code_size_file_byte": 7405.0, "qsc_code_num_lines": 259.0, "qsc_code_num_chars_line_max": 104.0, "qsc_code_num_chars_line_mean": 28.59073359, "qsc_code_frac_chars_alphabet": 0.79594506, "qsc_code_frac_chars_comments": 0.17690749, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.12903226, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.02723544, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codecpp_frac_lines_preprocessor_directives": 0.08064516, "qsc_codecpp_frac_lines_func_ratio": 0.06989247, "qsc_codecpp_cate_bitsstdc": 0.0, "qsc_codecpp_nums_lines_main": 0.0, "qsc_codecpp_frac_lines_goto": 0.0, "qsc_codecpp_cate_var_zero": 0.0, "qsc_codecpp_score_lines_no_logic": 0.13978495, "qsc_codecpp_frac_lines_print": 0.00537634} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codecpp_frac_lines_func_ratio": 0, "qsc_codecpp_nums_lines_main": 0, "qsc_codecpp_score_lines_no_logic": 0, "qsc_codecpp_frac_lines_preprocessor_directives": 0, "qsc_codecpp_frac_lines_print": 0} |
0015/esp_rlottie | rlottie/example/lottieview.h | /*
* Copyright (c) 2020 Samsung Electronics Co., Ltd. All rights reserved.
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#ifndef LOTTIEVIEW_H
#define LOTTIEVIEW_H
#ifndef EFL_BETA_API_SUPPORT
#define EFL_BETA_API_SUPPORT
#endif
#ifndef EFL_EO_API_SUPPORT
#define EFL_EO_API_SUPPORT
#endif
#include <Eo.h>
#include <Efl.h>
#include <Evas.h>
#include <Ecore.h>
#include <Ecore_Evas.h>
#include "rlottie.h"
#include "rlottie_capi.h"
#include<future>
#include <cmath>
#include <algorithm>
class RenderStrategy {
public:
virtual ~RenderStrategy() {
evas_object_del(renderObject());
}
RenderStrategy(Evas_Object *obj, bool useImage = true):_renderObject(obj), _useImage(useImage){
addCallback();
}
virtual rlottie::Animation *player() {return nullptr;}
virtual void loadFromFile(const char *filePath) = 0;
virtual void loadFromData(const std::string &jsonData, const std::string &key, const std::string &resourcePath) = 0;
virtual size_t totalFrame() = 0;
virtual double frameRate() = 0;
virtual size_t frameAtPos(double pos) = 0;
virtual double duration() = 0;
void render(int frame) {
_renderCount++;
_redraw = renderRequest(frame);
if (_redraw && _useImage)
evas_object_image_pixels_dirty_set(renderObject(), EINA_TRUE);
}
void dataCb() {
if (_redraw && _useImage) {
evas_object_image_data_set(renderObject(), buffer());
}
_redraw = false;
}
virtual void resize(int width, int height) = 0;
virtual void setPos(int x, int y) {evas_object_move(renderObject(), x, y);}
typedef std::tuple<size_t, size_t> MarkerFrame;
virtual MarkerFrame findFrameAtMarker(const std::string &markerName) = 0;
void show() {evas_object_show(_renderObject);}
void hide() {evas_object_hide(_renderObject);}
void addCallback();
Evas_Object* renderObject() const {return _renderObject;}
size_t renderCount() const {return _renderCount;}
protected:
virtual bool renderRequest(int) = 0;
virtual uint32_t* buffer() = 0;
private:
size_t _renderCount{0};
bool _redraw{false};
Evas_Object *_renderObject;
bool _useImage{true};
};
class CppApiBase : public RenderStrategy {
public:
CppApiBase(Evas_Object *renderObject): RenderStrategy(renderObject) {}
rlottie::Animation *player() {return mPlayer.get();}
void loadFromFile(const char *filePath)
{
mPlayer = rlottie::Animation::loadFromFile(filePath);
if (!mPlayer) {
printf("load failed file %s\n", filePath);
}
}
void loadFromData(const std::string &jsonData, const std::string &key, const std::string &resourcePath)
{
mPlayer = rlottie::Animation::loadFromData(jsonData, key, resourcePath);
if (!mPlayer) {
printf("load failed from data\n");
}
}
size_t totalFrame() {
return mPlayer->totalFrame();
}
double duration() {
return mPlayer->duration();
}
double frameRate() {
return mPlayer->frameRate();
}
size_t frameAtPos(double pos) {
return mPlayer->frameAtPos(pos);
}
MarkerFrame findFrameAtMarker(const std::string &markerName)
{
auto markerList = mPlayer->markers();
auto marker = std::find_if(markerList.begin(), markerList.end()
, [&markerName](const auto& e) {
return std::get<0>(e) == markerName;
});
if (marker == markerList.end())
return std::make_tuple(0, 0);
return std::make_tuple(std::get<1>(*marker), std::get<2>(*marker));
}
protected:
std::unique_ptr<rlottie::Animation> mPlayer;
};
class RlottieRenderStrategyCBase : public RenderStrategy {
public:
RlottieRenderStrategyCBase(Evas *evas):RenderStrategy(evas_object_image_filled_add(evas)) {
evas_object_image_colorspace_set(renderObject(), EVAS_COLORSPACE_ARGB8888);
evas_object_image_alpha_set(renderObject(), EINA_TRUE);
}
void resize(int width, int height) {
evas_object_resize(renderObject(), width, height);
evas_object_image_size_set(renderObject(), width, height);
}
};
class RlottieRenderStrategy : public CppApiBase {
public:
RlottieRenderStrategy(Evas *evas):CppApiBase(evas_object_image_filled_add(evas)) {
evas_object_image_colorspace_set(renderObject(), EVAS_COLORSPACE_ARGB8888);
evas_object_image_alpha_set(renderObject(), EINA_TRUE);
}
void resize(int width, int height) {
evas_object_resize(renderObject(), width, height);
evas_object_image_size_set(renderObject(), width, height);
}
};
class RlottieRenderStrategy_CPP : public RlottieRenderStrategy {
public:
RlottieRenderStrategy_CPP(Evas *evas):RlottieRenderStrategy(evas) {}
bool renderRequest(int frame) {
int width , height;
Evas_Object *image = renderObject();
evas_object_image_size_get(image, &width, &height);
mBuffer = (uint32_t *)evas_object_image_data_get(image, EINA_TRUE);
size_t bytesperline = evas_object_image_stride_get(image);
rlottie::Surface surface(mBuffer, width, height, bytesperline);
mPlayer->renderSync(frame, surface);
return true;
}
uint32_t* buffer() {
return mBuffer;
}
private:
uint32_t * mBuffer;
};
class RlottieRenderStrategy_CPP_ASYNC : public RlottieRenderStrategy {
public:
RlottieRenderStrategy_CPP_ASYNC(Evas *evas):RlottieRenderStrategy(evas) {}
~RlottieRenderStrategy_CPP_ASYNC() {
if (mRenderTask.valid())
mRenderTask.get();
}
bool renderRequest(int frame) {
//addCallback();
if (mRenderTask.valid()) return true;
int width , height;
Evas_Object *image = renderObject();
evas_object_image_size_get(image, &width, &height);
auto buffer = (uint32_t *)evas_object_image_data_get(image, EINA_TRUE);
size_t bytesperline = evas_object_image_stride_get(image);
rlottie::Surface surface(buffer, width, height, bytesperline);
mRenderTask = mPlayer->render(frame, surface);
return true;
}
uint32_t* buffer() {
auto surface = mRenderTask.get();
return surface.buffer();
}
private:
std::future<rlottie::Surface> mRenderTask;
};
class RlottieRenderStrategy_C : public RlottieRenderStrategyCBase {
public:
RlottieRenderStrategy_C(Evas *evas):RlottieRenderStrategyCBase(evas) {}
~RlottieRenderStrategy_C() {
if (mPlayer) lottie_animation_destroy(mPlayer);
}
void loadFromFile(const char *filePath)
{
mPlayer = lottie_animation_from_file(filePath);
if (!mPlayer) {
printf("load failed file %s\n", filePath);
}
}
void loadFromData(const std::string &jsonData, const std::string &key, const std::string &resourcePath)
{
mPlayer = lottie_animation_from_data(jsonData.c_str(), key.c_str(), resourcePath.c_str());
if (!mPlayer) {
printf("load failed from data\n");
}
}
size_t totalFrame() {
return lottie_animation_get_totalframe(mPlayer);
}
double frameRate() {
return lottie_animation_get_framerate(mPlayer);
}
size_t frameAtPos(double pos) {
return lottie_animation_get_frame_at_pos(mPlayer, pos);
}
double duration() {
return lottie_animation_get_duration(mPlayer);
}
MarkerFrame findFrameAtMarker(const std::string &markerName)
{
printf("Can't not [%s] marker, CAPI isn't implements yet\n", markerName.c_str());
return std::make_tuple(0, 0);
}
bool renderRequest(int frame) {
int width , height;
Evas_Object *image = renderObject();
evas_object_image_size_get(image, &width, &height);
mBuffer = (uint32_t *)evas_object_image_data_get(image, EINA_TRUE);
size_t bytesperline = evas_object_image_stride_get(image);
lottie_animation_render(mPlayer, frame, mBuffer, width, height, bytesperline);
return true;
}
uint32_t* buffer() {
return mBuffer;
}
private:
uint32_t * mBuffer;
protected:
Lottie_Animation *mPlayer;
};
class RlottieRenderStrategy_C_ASYNC : public RlottieRenderStrategy_C {
public:
RlottieRenderStrategy_C_ASYNC(Evas *evas):RlottieRenderStrategy_C(evas) {}
~RlottieRenderStrategy_C_ASYNC() {
if (mDirty) lottie_animation_render_flush(mPlayer);
}
bool renderRequest(int frame) {
if (mDirty) return true;
mDirty = true;
Evas_Object *image = renderObject();
evas_object_image_size_get(image, &mWidth, &mHeight);
mBuffer = (uint32_t *)evas_object_image_data_get(image, EINA_TRUE);
size_t bytesperline = evas_object_image_stride_get(image);
lottie_animation_render_async(mPlayer, frame, mBuffer, mWidth, mHeight, bytesperline);
return true;
}
uint32_t* buffer() {
lottie_animation_render_flush(mPlayer);
mDirty =false;
return mBuffer;
}
private:
uint32_t * mBuffer;
int mWidth;
int mHeight;
bool mDirty{false};
};
enum class Strategy {
renderCpp = 0,
renderCppAsync,
renderC,
renderCAsync,
eflVg
};
class LottieView
{
public:
enum class RepeatMode {
Restart,
Reverse
};
LottieView(Evas *evas, Strategy s = Strategy::renderCppAsync);
~LottieView();
rlottie::Animation *player(){return mRenderDelegate->player();}
Evas_Object *getImage();
void setSize(int w, int h);
void setPos(int x, int y);
void setFilePath(const char *filePath);
void loadFromData(const std::string &jsonData, const std::string &key, const std::string &resourcePath="");
void show();
void hide();
void loop(bool loop);
void setSpeed(float speed) { mSpeed = speed;}
void setRepeatCount(int count);
void setRepeatMode(LottieView::RepeatMode mode);
float getFrameRate() const { return mRenderDelegate->frameRate(); }
long getTotalFrame() const { return mRenderDelegate->totalFrame(); }
public:
void seek(float pos);
float getPos();
void finished();
void play();
void play(const std::string &marker);
void play(const std::string &startmarker, const std::string endmarker);
void pause();
void stop();
void initializeBufferObject(Evas *evas);
void setMinProgress(float progress)
{
//clamp it to [0,1]
mMinProgress = progress;
}
void setMaxProgress(float progress)
{
//clamp it to [0,1]
mMaxprogress = progress;
}
size_t renderCount() const {
return mRenderDelegate ? mRenderDelegate->renderCount() : 0;
}
private:
float mapProgress(float progress) {
//clamp it to the segment
progress = (mMinProgress + (mMaxprogress - mMinProgress) * progress);
// currently playing and in reverse mode
if (mPalying && mReverse)
progress = mMaxprogress > mMinProgress ?
mMaxprogress - progress : mMinProgress - progress;
return progress;
}
float duration() const {
// usually we run the animation for mPlayer->duration()
// but now run animation for segmented duration.
return mRenderDelegate->duration() * fabs(mMaxprogress - mMinProgress);
}
void createVgNode(LOTNode *node, Efl_VG *root);
void update(const std::vector<LOTNode *> &);
void updateTree(const LOTLayerNode *);
void update(const LOTLayerNode *, Efl_VG *parent);
void restart();
public:
int mRepeatCount;
LottieView::RepeatMode mRepeatMode;
size_t mCurFrame{UINT_MAX};
Ecore_Animator *mAnimator{nullptr};
bool mLoop;
int mCurCount;
bool mReverse;
bool mPalying;
float mSpeed;
float mPos;
//keep a segment of the animation default is [0, 1]
float mMinProgress{0};
float mMaxprogress{1};
std::unique_ptr<RenderStrategy> mRenderDelegate;
};
#include<assert.h>
class EflVgRenderStrategy : public RenderStrategy {
public:
EflVgRenderStrategy(Evas *evas):RenderStrategy(evas_object_vg_add(evas), false) {}
void loadFromFile(const char *filePath) {
evas_object_vg_file_set(renderObject(), filePath, NULL);
}
void loadFromData(const std::string&, const std::string&, const std::string&) {
assert(false);
}
size_t totalFrame() {
return evas_object_vg_animated_frame_count_get(renderObject()) - 1;
}
double frameRate() {
return (double)totalFrame() / evas_object_vg_animated_frame_duration_get(renderObject(), 0, 0);
}
size_t frameAtPos(double pos) {
return totalFrame() * pos;
}
double duration() {
return evas_object_vg_animated_frame_duration_get(renderObject(), 0, 0);
}
void resize(int width, int height) {
evas_object_resize(renderObject(), width, height);
}
uint32_t *buffer() {
assert(false);
return nullptr;
}
bool renderRequest(int frame) {
evas_object_vg_animated_frame_set(renderObject(), frame);
return false;
}
MarkerFrame findFrameAtMarker(const std::string&) {
return std::make_tuple(0, 0);
}
};
#endif //LOTTIEVIEW_H
| 14,747 | lottieview | h | en | c | code | {"qsc_code_num_words": 1590, "qsc_code_num_chars": 14747.0, "qsc_code_mean_word_length": 5.87735849, "qsc_code_frac_words_unique": 0.19874214, "qsc_code_frac_chars_top_2grams": 0.047084, "qsc_code_frac_chars_top_3grams": 0.04173355, "qsc_code_frac_chars_top_4grams": 0.01219904, "qsc_code_frac_chars_dupe_5grams": 0.37324773, "qsc_code_frac_chars_dupe_6grams": 0.31396469, "qsc_code_frac_chars_dupe_7grams": 0.24216158, "qsc_code_frac_chars_dupe_8grams": 0.23199572, "qsc_code_frac_chars_dupe_9grams": 0.23199572, "qsc_code_frac_chars_dupe_10grams": 0.23199572, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.00656298, "qsc_code_frac_chars_whitespace": 0.2457449, "qsc_code_size_file_byte": 14747.0, "qsc_code_num_lines": 458.0, "qsc_code_num_chars_line_max": 121.0, "qsc_code_num_chars_line_mean": 32.19868996, "qsc_code_frac_chars_alphabet": 0.83358806, "qsc_code_frac_chars_comments": 0.09791822, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.31016043, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.01210253, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.00802139, "qsc_codec_frac_lines_func_ratio": 0.25668449, "qsc_codec_cate_bitsstdc": 0.0, "qsc_codec_nums_lines_main": 0, "qsc_codec_frac_lines_goto": 0.0, "qsc_codec_cate_var_zero": 0.0, "qsc_codec_score_lines_no_logic": 0.35828877, "qsc_codec_frac_lines_print": 0.01336898, "qsc_codec_frac_lines_preprocessor_directives": null} | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codec_frac_lines_func_ratio": 1, "qsc_codec_nums_lines_main": 0, "qsc_codec_score_lines_no_logic": 0, "qsc_codec_frac_lines_preprocessor_directives": 0, "qsc_codec_frac_lines_print": 0} |
0015/esp_rlottie | rlottie/example/lottie2gif.cpp | #include "gif.h"
#include <rlottie.h>
#include<iostream>
#include<string>
#include<vector>
#include<array>
#ifndef _WIN32
#include<libgen.h>
#else
#include <windows.h>
#include <stdlib.h>
#endif
class GifBuilder {
public:
explicit GifBuilder(const std::string &fileName , const uint32_t width,
const uint32_t height, const int bgColor=0xffffffff, const uint32_t delay = 2)
{
GifBegin(&handle, fileName.c_str(), width, height, delay);
bgColorR = (uint8_t) ((bgColor & 0xff0000) >> 16);
bgColorG = (uint8_t) ((bgColor & 0x00ff00) >> 8);
bgColorB = (uint8_t) ((bgColor & 0x0000ff));
}
~GifBuilder()
{
GifEnd(&handle);
}
void addFrame(rlottie::Surface &s, uint32_t delay = 2)
{
argbTorgba(s);
GifWriteFrame(&handle,
reinterpret_cast<uint8_t *>(s.buffer()),
s.width(),
s.height(),
delay);
}
void argbTorgba(rlottie::Surface &s)
{
uint8_t *buffer = reinterpret_cast<uint8_t *>(s.buffer());
uint32_t totalBytes = s.height() * s.bytesPerLine();
for (uint32_t i = 0; i < totalBytes; i += 4) {
unsigned char a = buffer[i+3];
// compute only if alpha is non zero
if (a) {
unsigned char r = buffer[i+2];
unsigned char g = buffer[i+1];
unsigned char b = buffer[i];
if (a != 255) { //un premultiply
unsigned char r2 = (unsigned char) ((float) bgColorR * ((float) (255 - a) / 255));
unsigned char g2 = (unsigned char) ((float) bgColorG * ((float) (255 - a) / 255));
unsigned char b2 = (unsigned char) ((float) bgColorB * ((float) (255 - a) / 255));
buffer[i] = r + r2;
buffer[i+1] = g + g2;
buffer[i+2] = b + b2;
} else {
// only swizzle r and b
buffer[i] = r;
buffer[i+2] = b;
}
} else {
buffer[i+2] = bgColorB;
buffer[i+1] = bgColorG;
buffer[i] = bgColorR;
}
}
}
private:
GifWriter handle;
uint8_t bgColorR, bgColorG, bgColorB;
};
class App {
public:
int render(uint32_t w, uint32_t h)
{
auto player = rlottie::Animation::loadFromFile(fileName);
if (!player) return help();
auto buffer = std::unique_ptr<uint32_t[]>(new uint32_t[w * h]);
size_t frameCount = player->totalFrame();
GifBuilder builder(gifName.data(), w, h, bgColor);
for (size_t i = 0; i < frameCount ; i++) {
rlottie::Surface surface(buffer.get(), w, h, w * 4);
player->renderSync(i, surface);
builder.addFrame(surface);
}
return result();
}
int setup(int argc, char **argv, size_t *width, size_t *height)
{
char *path{nullptr};
*width = *height = 200; //default gif size
if (argc > 1) path = argv[1];
if (argc > 2) {
char tmp[20];
char *x = strstr(argv[2], "x");
if (x) {
snprintf(tmp, x - argv[2] + 1, "%s", argv[2]);
*width = atoi(tmp);
snprintf(tmp, sizeof(tmp), "%s", x + 1);
*height = atoi(tmp);
}
}
if (argc > 3) bgColor = strtol(argv[3], NULL, 16);
if (!path) return help();
std::array<char, 5000> memory;
#ifdef _WIN32
path = _fullpath(memory.data(), path, memory.size());
#else
path = realpath(path, memory.data());
#endif
if (!path) return help();
fileName = std::string(path);
if (!jsonFile()) return help();
gifName = basename(fileName);
gifName.append(".gif");
return 0;
}
private:
std::string basename(const std::string &str)
{
return str.substr(str.find_last_of("/\\") + 1);
}
bool jsonFile() {
std::string extn = ".json";
if ( fileName.size() <= extn.size() ||
fileName.substr(fileName.size()- extn.size()) != extn )
return false;
return true;
}
int result() {
std::cout<<"Generated GIF file : "<<gifName<<std::endl;
return 0;
}
int help() {
std::cout<<"Usage: \n lottie2gif [lottieFileName] [Resolution] [bgColor]\n\nExamples: \n $ lottie2gif input.json\n $ lottie2gif input.json 200x200\n $ lottie2gif input.json 200x200 ff00ff\n\n";
return 1;
}
private:
int bgColor = 0xffffffff;
std::string fileName;
std::string gifName;
};
int
main(int argc, char **argv)
{
App app;
size_t w, h;
if (app.setup(argc, argv, &w, &h)) return 1;
app.render(w, h);
return 0;
}
| 4,908 | lottie2gif | cpp | en | cpp | code | {"qsc_code_num_words": 558, "qsc_code_num_chars": 4908.0, "qsc_code_mean_word_length": 4.41218638, "qsc_code_frac_words_unique": 0.27598566, "qsc_code_frac_chars_top_2grams": 0.0341186, "qsc_code_frac_chars_top_3grams": 0.01299756, "qsc_code_frac_chars_top_4grams": 0.01462226, "qsc_code_frac_chars_dupe_5grams": 0.06417547, "qsc_code_frac_chars_dupe_6grams": 0.04224208, "qsc_code_frac_chars_dupe_7grams": 0.0, "qsc_code_frac_chars_dupe_8grams": 0.0, "qsc_code_frac_chars_dupe_9grams": 0.0, "qsc_code_frac_chars_dupe_10grams": 0.0, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.0427724, "qsc_code_frac_chars_whitespace": 0.34739201, "qsc_code_size_file_byte": 4908.0, "qsc_code_num_lines": 178.0, "qsc_code_num_chars_line_max": 213.0, "qsc_code_num_chars_line_mean": 27.57303371, "qsc_code_frac_chars_alphabet": 0.72588199, "qsc_code_frac_chars_comments": 0.01976365, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.12328767, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.00684932, "qsc_code_frac_chars_string_length": 0.04843068, "qsc_code_frac_chars_long_word_length": 0.00457285, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.00914571, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codecpp_frac_lines_preprocessor_directives": 0.10273973, "qsc_codecpp_frac_lines_func_ratio": 0.11643836, "qsc_codecpp_cate_bitsstdc": 0.0, "qsc_codecpp_nums_lines_main": 1.0, "qsc_codecpp_frac_lines_goto": 0.0, "qsc_codecpp_cate_var_zero": 0.0, "qsc_codecpp_score_lines_no_logic": 0.21232877, "qsc_codecpp_frac_lines_print": 0.02739726} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codecpp_frac_lines_func_ratio": 0, "qsc_codecpp_nums_lines_main": 0, "qsc_codecpp_score_lines_no_logic": 0, "qsc_codecpp_frac_lines_preprocessor_directives": 0, "qsc_codecpp_frac_lines_print": 0} |
0015/esp_rlottie | rlottie/example/pathtest.cpp | /*
* Copyright (c) 2020 Samsung Electronics Co., Ltd. All rights reserved.
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "evasapp.h"
#include"vpath.h"
#include<iostream>
using namespace std;
EvasApp *APP;
static void
_on_resize(Ecore_Evas *ee)
{
int w, h;
ecore_evas_geometry_get(ee, NULL, NULL, &w, &h);
APP->resize(w, h);
}
class PathTest
{
public:
PathTest(EvasApp *app) {
mApp = app;
mShape = evas_vg_shape_add(mApp->root());
}
void setColor(int r, int g, int b, int a) {
evas_vg_node_color_set(mShape, r, g, b, a);
}
void setStrokeColor(int r, int g, int b, int a) {
evas_vg_shape_stroke_color_set(mShape, r, g, b, a);
}
void setStrokeWidth(int w) {
evas_vg_shape_stroke_width_set(mShape, w);
}
void setPath(const VPath &path) {
Efl_VG *shape = mShape;
evas_vg_shape_reset(shape);
const std::vector<VPath::Element> &elm = path.elements();
const std::vector<VPointF> &pts = path.points();
int i=0;
for (auto e : elm) {
switch(e) {
case VPath::Element::MoveTo:
{
VPointF p = pts[i++];
evas_vg_shape_append_move_to(shape, p.x(), p.y());
break;
}
case VPath::Element::LineTo:
{
VPointF p = pts[i++];
evas_vg_shape_append_line_to(shape, p.x(), p.y());
break;
}
case VPath::Element::CubicTo:
{
VPointF p = pts[i++];
VPointF p1 = pts[i++];
VPointF p2 = pts[i++];
evas_vg_shape_append_cubic_to(shape, p.x(), p.y(), p1.x(), p1.y(), p2.x(), p2.y());
break;
}
case VPath::Element::Close:
{
evas_vg_shape_append_close(shape);
break;
}
}
}
}
public:
EvasApp *mApp;
Efl_VG *mShape;
};
int
main(void)
{
APP = new EvasApp(800, 800);
ecore_evas_callback_resize_set(APP->mEcoreEvas, _on_resize);
APP->setup();
VPath path;
path.addRoundRect(VRectF(100, 100, 200, 200), 20, 20, VPath::Direction::CCW);
path.addCircle(50, 50, 20, VPath::Direction::CCW);
path.addOval(VRectF(300, 100, 100, 50), VPath::Direction::CCW);
path.addPolystar(15.0, 106.0, 34.0, 0.0, 150,
150, 231.0, 88.0, VPath::Direction::CW);
PathTest test(APP);
test.setPath(path);
test.setColor(255, 0, 0, 255);
test.setStrokeColor(200, 200, 0, 200);
test.setStrokeWidth(5);
APP->run();
delete APP;
return 0;
}
| 3,620 | pathtest | cpp | en | cpp | code | {"qsc_code_num_words": 505, "qsc_code_num_chars": 3620.0, "qsc_code_mean_word_length": 4.31089109, "qsc_code_frac_words_unique": 0.4, "qsc_code_frac_chars_top_2grams": 0.02480478, "qsc_code_frac_chars_top_3grams": 0.0404226, "qsc_code_frac_chars_top_4grams": 0.03123565, "qsc_code_frac_chars_dupe_5grams": 0.1423978, "qsc_code_frac_chars_dupe_6grams": 0.11116215, "qsc_code_frac_chars_dupe_7grams": 0.09646302, "qsc_code_frac_chars_dupe_8grams": 0.09646302, "qsc_code_frac_chars_dupe_9grams": 0.04960955, "qsc_code_frac_chars_dupe_10grams": 0.04960955, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.03572772, "qsc_code_frac_chars_whitespace": 0.26546961, "qsc_code_size_file_byte": 3620.0, "qsc_code_num_lines": 130.0, "qsc_code_num_chars_line_max": 100.0, "qsc_code_num_chars_line_mean": 27.84615385, "qsc_code_frac_chars_alphabet": 0.78300113, "qsc_code_frac_chars_comments": 0.31712707, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.1011236, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.00648561, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codecpp_frac_lines_preprocessor_directives": 0.04494382, "qsc_codecpp_frac_lines_func_ratio": 0.08988764, "qsc_codecpp_cate_bitsstdc": 0.0, "qsc_codecpp_nums_lines_main": 1.0, "qsc_codecpp_frac_lines_goto": 0.0, "qsc_codecpp_cate_var_zero": 0.0, "qsc_codecpp_score_lines_no_logic": 0.12359551, "qsc_codecpp_frac_lines_print": 0.0} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codecpp_frac_lines_func_ratio": 0, "qsc_codecpp_nums_lines_main": 0, "qsc_codecpp_score_lines_no_logic": 0, "qsc_codecpp_frac_lines_preprocessor_directives": 0, "qsc_codecpp_frac_lines_print": 0} |
0015/Fridge-Calendar | main/g_calendar_config.cpp | #include "app_config.hpp"
#include "g_calendar_config.hpp"
// Define static variables
std::string CalendarConfig::clientId = _clientId;
std::string CalendarConfig::clientSecret = _clientSecret;
std::string CalendarConfig::accessToken = _accessToken;
std::string CalendarConfig::refreshToken = _refreshToken;
// Getters and Setters for clientId
void CalendarConfig::setClientId(const std::string& id) {
clientId = id;
}
const std::string& CalendarConfig::getClientId() {
return clientId;
}
// Getters and Setters for clientSecret
void CalendarConfig::setClientSecret(const std::string& secret) {
clientSecret = secret;
}
const std::string& CalendarConfig::getClientSecret() {
return clientSecret;
}
// Getters and Setters for accessToken
void CalendarConfig::setAccessToken(const std::string& token) {
accessToken = token;
}
const std::string& CalendarConfig::getAccessToken() {
return accessToken;
}
// Getters and Setters for refreshToken
void CalendarConfig::setRefreshToken(const std::string& token) {
refreshToken = token;
}
const std::string& CalendarConfig::getRefreshToken() {
return refreshToken;
}
| 1,148 | g_calendar_config | cpp | en | cpp | code | {"qsc_code_num_words": 116, "qsc_code_num_chars": 1148.0, "qsc_code_mean_word_length": 7.43103448, "qsc_code_frac_words_unique": 0.29310345, "qsc_code_frac_chars_top_2grams": 0.12529002, "qsc_code_frac_chars_top_3grams": 0.21345708, "qsc_code_frac_chars_top_4grams": 0.09280742, "qsc_code_frac_chars_dupe_5grams": 0.07656613, "qsc_code_frac_chars_dupe_6grams": 0.0, "qsc_code_frac_chars_dupe_7grams": 0.0, "qsc_code_frac_chars_dupe_8grams": 0.0, "qsc_code_frac_chars_dupe_9grams": 0.0, "qsc_code_frac_chars_dupe_10grams": 0.0, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.0, "qsc_code_frac_chars_whitespace": 0.13327526, "qsc_code_size_file_byte": 1148.0, "qsc_code_num_lines": 44.0, "qsc_code_num_chars_line_max": 66.0, "qsc_code_num_chars_line_mean": 26.09090909, "qsc_code_frac_chars_alphabet": 0.86633166, "qsc_code_frac_chars_comments": 0.15853659, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.0, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.03623188, "qsc_code_frac_chars_long_word_length": 0.02173913, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codecpp_frac_lines_preprocessor_directives": 0.06666667, "qsc_codecpp_frac_lines_func_ratio": 0.0, "qsc_codecpp_cate_bitsstdc": 0.0, "qsc_codecpp_nums_lines_main": 0.0, "qsc_codecpp_frac_lines_goto": 0.0, "qsc_codecpp_cate_var_zero": 0.0, "qsc_codecpp_score_lines_no_logic": 0.2, "qsc_codecpp_frac_lines_print": 0.0} | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 1, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codecpp_frac_lines_func_ratio": 0, "qsc_codecpp_nums_lines_main": 0, "qsc_codecpp_score_lines_no_logic": 0, "qsc_codecpp_frac_lines_preprocessor_directives": 0, "qsc_codecpp_frac_lines_print": 0} |
0015/Fridge-Calendar | main/application.cpp | #include <esp_log.h>
#include "application.hpp"
#include "app_config.hpp"
#include "g_calendar_config.hpp"
#include <algorithm>
#include <set>
#include <esp_sleep.h>
#define WIFI_CONNECTED_BIT BIT0
#define LOCALTIME_SET_BIT BIT1
#define ACCESS_TOKEN_KEY "access_token"
#define FIRST_RUN_KEY "first_run"
#define RETRY_KEY "retry_count"
static const char* TAG = "[App]";
Application::Application()
: event_group(xEventGroupCreate()), // Create the event group
wifi(WIFI_SSID, WIFI_PASS, event_group, WIFI_CONNECTED_BIT), // Initialize WiFi
epaper(), // Default constructor for EPaper
localTime(TimeZone,event_group, LOCALTIME_SET_BIT) // Initialize LocalTime with TimeZone
{
// Any additional setup needed for members can go here
}
Application::~Application() {
// Destructor
}
void Application::run() {
ESP_LOGI(TAG, "Applcation Run");
esp_err_t err = nvs_flash_init();
if (err == ESP_ERR_NVS_NO_FREE_PAGES || err == ESP_ERR_NVS_NEW_VERSION_FOUND) {
// NVS partition was truncated, erase and retry
ESP_LOGW(TAG, "NVS Partition truncated, erasing...");
ESP_ERROR_CHECK(nvs_flash_erase());
ESP_ERROR_CHECK(nvs_flash_init());
}
ESP_LOGI(TAG, "NVS Initialized successfully.");
bool isFirstRun = true;
std::string nvsState = getDataFromNVS(FIRST_RUN_KEY);
if (nvsState == "updated") {
isFirstRun = false;
ESP_LOGI(TAG, "Skipping splash screen and progress bar on reboot.");
}
std::string retryValue = getDataFromNVS(RETRY_KEY);
int retryCount = retryValue.empty() ? 0 : std::stoi(retryValue);
epaper.initialize();
int epaper_x_center = epaper.getWidth() / 2;
int epaper_y_center = epaper.getHeight() / 2;
int bar_x = epaper_x_center - 200;
int bar_y = epaper_y_center + 100;
if (isFirstRun) {
// Show splash screen and progress bar
epaper.splash();
epaper.drawText(epaper.font_mid, EPaper::TEXT_ALIGN::Center, epaper_x_center, epaper_y_center + 60, "System Loading");
epaper.drawProgressBar(bar_x, bar_y, 30);
epaper.drawText(epaper.font_mid, EPaper::TEXT_ALIGN::Left, epaper_x_center - 200, epaper_y_center + 150, "[OK] E-Paper Display");
wifi.init();
wifi.start();
ESP_LOGI(TAG, "Waiting for WiFi connection...");
xEventGroupWaitBits(event_group, WIFI_CONNECTED_BIT, pdFALSE, pdTRUE, portMAX_DELAY);
ESP_LOGI(TAG, "WiFi Connected!");
epaper.drawProgressBar(bar_x, bar_y, 60);
epaper.drawText(epaper.font_mid, EPaper::TEXT_ALIGN::Left, epaper_x_center - 200, epaper_y_center + 180, "[OK] WIFI Connected");
} else {
// Skip splash and directly initialize Wi-Fi
wifi.init();
wifi.start();
xEventGroupWaitBits(event_group, WIFI_CONNECTED_BIT, pdFALSE, pdTRUE, portMAX_DELAY);
}
std::string currentDateTime = localTime.obtainTime();
xEventGroupWaitBits(event_group, LOCALTIME_SET_BIT, pdFALSE, pdTRUE, portMAX_DELAY);
if (isFirstRun) {
epaper.drawProgressBar(bar_x, bar_y, 80);
epaper.drawText(epaper.font_mid, EPaper::TEXT_ALIGN::Left, epaper_x_center - 200, epaper_y_center + 210, currentDateTime.c_str());
}
//Need to complete Screen drawing first
std::vector<CalendarEvent> events;
if(fetchCalendarEvents(events) == ESP_OK){
if (isFirstRun) {
epaper.drawProgressBar(bar_x, bar_y, 100);
epaper.drawText(epaper.font_mid, EPaper::TEXT_ALIGN::Left, epaper_x_center - 200, epaper_y_center + 240, "[OK] Fectching Calendar Events");
// Mark the state in NVS
storeDataInNVS(FIRST_RUN_KEY, "updated");
}
// Reset retry counter on success
storeDataInNVS(RETRY_KEY, "0");
std::reverse( events.begin(), events.end() );
auto [startDate, endDate] = localTime.getStartAndEndDates();
ESP_LOGI(TAG, "Start Date: %s", startDate.c_str());
ESP_LOGI(TAG, "End Date: %s", endDate.c_str());
// Need to make another function
int offset_pos = localTime.getFirstDayOfMonth();
int max_date = localTime.getLastDayOfMonth();
ESP_LOGI(TAG, "offset_pos: %d, max_date: %d", offset_pos, max_date);
epaper.drawCalendarBase(offset_pos, max_date, localTime.getCurrentMonthYear().c_str(), localTime.getTodayDay());
printEventsInRange(events, startDate, endDate);
int epaper_y2 = epaper.getHeight() - (epaper.getHeight() / 3);
epaper.drawText(epaper.font_mid, EPaper::TEXT_ALIGN::Center, epaper_x_center, epaper_y2, "Upcoming Events");
epaper.drawBar(20, epaper_y2 + 10, epaper.getWidth() - 40, 2);
epaper.drawBar(epaper.getWidth()/2 - 1, epaper_y2 + 10, 2, epaper.getHeight() / 3 - 30);
epaper.invalidate();
// Sort events by their start date
sortEventsByStartDate(events);
printEventSummary(events, localTime.getTodayDate().c_str());
}else{
epaper.drawText(epaper.font_mid, EPaper::TEXT_ALIGN::Left, epaper_x_center - 200, epaper_y_center + 240, "[Fail] Fectching Calendar Events");
epaper.drawText(epaper.font_mid, EPaper::TEXT_ALIGN::Left, epaper_x_center - 200, epaper_y_center + 270, "Check the AccessToken and RefreshToken");
storeDataInNVS(FIRST_RUN_KEY, "");
storeDataInNVS(RETRY_KEY, std::to_string(++retryCount)); // Increment retry counter and reboot
if(retryCount >= 2){
esp_deep_sleep_start();
}else{
esp_restart();
}
}
epaper.drawText(epaper.font_tiny, EPaper::TEXT_ALIGN::Right, epaper.getWidth() - 20 , epaper.getHeight() - 8, ("Updated: " + currentDateTime).c_str());
esp_sleep_enable_timer_wakeup(localTime.scheduleHibernationUntilMidnight30() * 1000000ULL);
esp_deep_sleep_start();
}
// Function to increment date by one day
std::string Application::incrementDate(const std::string& date) {
// Parse the input date (YYYY-MM-DD) using sscanf
struct tm timeStruct = {};
if (sscanf(date.c_str(), "%4d-%2d-%2d", &timeStruct.tm_year, &timeStruct.tm_mon, &timeStruct.tm_mday) != 3) {
ESP_LOGE("Main", "Failed to parse date: %s", date.c_str());
}
// Adjust the tm_year and tm_mon since sscanf uses 0-based months and years
timeStruct.tm_year -= 1900; // Years since 1900
timeStruct.tm_mon -= 1; // Months are 0-11, so subtract 1
// Add one day (86400 seconds) to the time
timeStruct.tm_mday += 1;
// Normalize the time structure
if (mktime(&timeStruct) == -1) {
ESP_LOGE("Main", "Failed to increment date: %s", date.c_str());
}
// Convert the updated tm structure back to a string (YYYY-MM-DD) using strftime
char newDate[11]; // Buffer for the new date string in the format YYYY-MM-DD
if (strftime(newDate, sizeof(newDate), "%Y-%m-%d", &timeStruct) == 0) {
ESP_LOGE("Main", "Failed to format incremented date.");
}
return std::string(newDate);
}
bool Application::isDateWithinRange(const std::string& date, const CalendarEvent& event) {
if (event.isAllDayEvent) {
// For all-day events, exclude the end date
return date >= event.start.substr(0, 10) && date < event.end.substr(0, 10);
} else {
// For non-all-day events, include the end date
return date >= event.start.substr(0, 10) && date <= event.end.substr(0, 10);
}
}
void Application::printEventsInRange(const std::vector<CalendarEvent>& events, const std::string& start, const std::string& end) {
std::string currentDate = start;
while (currentDate <= end) {
// Extract the day number from the current date
int day = std::stoi(currentDate.substr(8, 2)); // Extract "DD" and convert to integer
ESP_LOGI(TAG, "Event on %s (Day %d):", currentDate.c_str(), day);
EPaper::Coordinates coords = epaper.getCoordinatesForDay(day);
if (coords.x != -1 && coords.y != -1) {
printf("Coordinates for day %d: x = %d, y = %d\n", day, coords.x, coords.y);
} else {
printf("Invalid day: %d\n", day);
}
//ESP_LOGI(TAG, "Event on %s:", currentDate.c_str());
bool found = false;
int slot = 1;
for (const auto& event : events) {
if (isDateWithinRange(currentDate, event)) {
found = true;
epaper.drawTextInSlot(slot++, coords.x, coords.y, event.organizerDisplayName.substr(0, 4).c_str());
//std::cout << " - " << event.summary << " (Start: " << event.start << ", End: " << event.end << ")\n";
ESP_LOGI(TAG, "Event: %s", event.summary.c_str());
ESP_LOGI(TAG, "Description: %s", event.description.c_str());
ESP_LOGI(TAG, "Start: %s", event.start.c_str());
ESP_LOGI(TAG, "End: %s\n\n", event.end.c_str());
}
}
if (!found) {
ESP_LOGI(TAG, "No events\n");
}else{
epaper.invalidate();
}
currentDate = incrementDate(currentDate);
}
}
// Bubble sort for CalendarEvent objects
void Application::sortEventsByStartDate(std::vector<CalendarEvent>& events) {
for (size_t i = 0; i < events.size(); ++i) {
for (size_t j = 0; j < events.size() - i - 1; ++j) {
if (events[j].start > events[j + 1].start) {
// Swap elements if they are out of order
CalendarEvent temp = events[j];
events[j] = events[j + 1];
events[j + 1] = temp;
}
}
}
}
std::vector<std::string> Application::truncateString(const std::string& str, size_t maxLength = 54, size_t maxLines = 4) {
std::vector<std::string> lines;
std::string currentLine;
size_t i = 0;
while (i < str.size() && lines.size() < maxLines) {
// Check for line breaks (\n or \r\n)
if (str[i] == '\n') {
// Add the current line to the result and start a new line
lines.push_back(currentLine);
currentLine.clear();
i++;
} else if (str[i] == '\r' && i + 1 < str.size() && str[i + 1] == '\n') {
// Handle Windows-style line breaks (\r\n)
lines.push_back(currentLine);
currentLine.clear();
i += 2;
} else {
// Add the character to the current line
currentLine += str[i];
i++;
// If the current line exceeds maxLength, split it
if (currentLine.size() >= maxLength) {
lines.push_back(currentLine);
currentLine.clear();
// Stop if we've reached the max number of lines
if (lines.size() >= maxLines) {
break;
}
}
}
}
// Add any remaining content in the current line (if under maxLines)
if (!currentLine.empty() && lines.size() < maxLines) {
lines.push_back(currentLine);
}
return lines;
}
void Application::printEventSummary(const std::vector<CalendarEvent>& events, const std::string& startDate) {
std::set<std::string> printedEvents; // Set to track processed events
const int maxEventsToDisplay = 6; // Limit to 6 events
int eventCount = 0; // Counter to track the number of events printed
int epaper_x2 = 20;
int epaper_y2 = epaper.getHeight() - (epaper.getHeight() / 3) + 40;
ESP_LOGI(TAG, "Event Summary (After %s):", startDate.c_str());
for (const auto& event : events) {
// Stop processing if we've reached the max number of events
if (eventCount >= maxEventsToDisplay) {
break;
}
// Check if the event starts on or after the given startDate
if (event.start < startDate) {
continue; // Skip events that start before the given date
}
// Use a unique identifier for the event (e.g., start + end date)
std::string uniqueID = event.start + "-" + event.end;
// Skip if this event has already been processed
if (printedEvents.find(uniqueID) != printedEvents.end()) {
continue;
}
// Add the event's unique ID to the set
printedEvents.insert(uniqueID);
// Print the event summary
ESP_LOGI(TAG, "organizerDisplayName: %s", event.organizerDisplayName.c_str());
ESP_LOGI(TAG, "Event: %s", event.summary.c_str());
ESP_LOGI(TAG, "Description: %s", event.description.c_str());
ESP_LOGI(TAG, "Start: %s", event.start.c_str());
ESP_LOGI(TAG, "End: %s\n", event.end.c_str());
ESP_LOGI(TAG, "isAllEvent: %d\n", event.isAllDayEvent);
epaper.drawText(epaper.font_sml, EPaper::TEXT_ALIGN::Left, epaper_x2, epaper_y2, (event.organizerDisplayName + " - " +event.summary).c_str());
epaper_y2 += 20;
epaper.drawText(epaper.font_tiny, EPaper::TEXT_ALIGN::Left, epaper_x2, epaper_y2, (localTime.formatRangeToCustomDate(event.start, event.end, event.isAllDayEvent)).c_str());
epaper_y2 += 18;
if(!event.description.empty()){
// Get the truncated description lines
std::vector<std::string> descriptionLines = truncateString(event.description);
// Print each line of the description
for (const auto& line : descriptionLines) {
ESP_LOGI(TAG, "Description: %s", line.c_str());
epaper.drawText(epaper.font_tiny, EPaper::TEXT_ALIGN::Left, epaper_x2, epaper_y2, line.c_str());
epaper_y2 += 16;
}
}
epaper_y2 += 20;
ESP_LOGI(TAG, "epaper_y2: %d\n", epaper_y2);
if(eventCount == 2){
epaper_x2 = epaper.getWidth()/2 + 20;
epaper_y2 = epaper.getHeight() - (epaper.getHeight() / 3) + 40;
}
// Increment the event counter
++eventCount;
}
epaper.invalidate();
}
void Application::storeDataInNVS(const std::string& key, const std::string& data) {
nvs_handle_t nvsHandle;
esp_err_t err = nvs_open("storage", NVS_READWRITE, &nvsHandle);
if (err == ESP_OK) {
err = nvs_set_str(nvsHandle, key.c_str(), data.c_str());
if (err == ESP_OK) {
nvs_commit(nvsHandle);
ESP_LOGI("NVS", "Access token stored successfully under key '%s'.", key.c_str());
} else {
ESP_LOGE("NVS", "Failed to store access data under key '%s': %s", key.c_str(), esp_err_to_name(err));
}
nvs_close(nvsHandle);
} else {
ESP_LOGE("NVS", "Failed to open NVS: %s", esp_err_to_name(err));
}
}
std::string Application::getDataFromNVS(const std::string& key) {
nvs_handle_t nvsHandle;
char dataBuffer[256]; // Adjust size as needed
size_t dataSize = sizeof(dataBuffer);
esp_err_t err = nvs_open("storage", NVS_READONLY, &nvsHandle);
if (err == ESP_OK) {
err = nvs_get_str(nvsHandle, key.c_str(), dataBuffer, &dataSize);
if (err == ESP_OK) {
ESP_LOGI("NVS", "Access token retrieved from NVS using key '%s'.", key.c_str());
nvs_close(nvsHandle);
return std::string(dataBuffer);
} else {
ESP_LOGW("NVS", "Access token not found in NVS under key '%s': %s", key.c_str(), esp_err_to_name(err));
}
nvs_close(nvsHandle);
} else {
ESP_LOGE("NVS", "Failed to open NVS: %s", esp_err_to_name(err));
}
return "";
}
esp_err_t Application::fetchCalendarEvents(std::vector<CalendarEvent>& events) {
esp_err_t ret = ESP_OK;
GoogleCalendar gCalendar(
CalendarConfig::getClientId(),
CalendarConfig::getClientSecret(),
CalendarConfig::getRefreshToken()
);
const std::vector<std::string>& calendarIds = _CALENDAR_IDS;
// Attempt to fetch events with the existing access token
std::string currentAccessToken = getDataFromNVS(ACCESS_TOKEN_KEY);
if (currentAccessToken.empty()) {
currentAccessToken = CalendarConfig::getAccessToken();
}
ESP_LOGI(TAG, "currentAccessToken: %s", currentAccessToken.c_str());
for (const auto& calendarId : calendarIds) {
ESP_LOGI(TAG, "Fetching events for calendar ID: %s", calendarId.c_str());
ret = gCalendar.getEvents(currentAccessToken, calendarId, events);
if (ret != ESP_OK && events.empty() ) {
ESP_LOGW(TAG, "No events or token might be invalid. Refreshing access token...");
// Refresh the access token
std::string newAccessToken = gCalendar.refreshAccessToken();
if (!newAccessToken.empty()) {
ESP_LOGI(TAG, "Access token refreshed: %s", newAccessToken.c_str());
// Store the new access token in NVS
storeDataInNVS(ACCESS_TOKEN_KEY, newAccessToken);
// Retry fetching events with the new token
currentAccessToken = newAccessToken;
ret = gCalendar.getEvents(currentAccessToken, calendarId, events);
if (ret == ESP_OK) {
ESP_LOGI(TAG, "Events retrieved successfully for calendar ID: %s", calendarId.c_str());
} else {
ret = ESP_ERR_INVALID_RESPONSE;
ESP_LOGE(TAG, "Failed to retrieve events even after refreshing token for calendar ID: %s", calendarId.c_str());
}
} else {
ret = ESP_ERR_NOT_ALLOWED;
ESP_LOGE(TAG, "Failed to refresh access token. Cannot fetch events for calendar ID: %s", calendarId.c_str());
break; // Exit loop as token refresh failed
}
} else {
ESP_LOGI(TAG, "Events retrieved successfully for calendar ID: %s", calendarId.c_str());
}
}
return ret;
} | 18,199 | application | cpp | en | cpp | code | {"qsc_code_num_words": 2164, "qsc_code_num_chars": 18199.0, "qsc_code_mean_word_length": 4.92005545, "qsc_code_frac_words_unique": 0.1922366, "qsc_code_frac_chars_top_2grams": 0.01502771, "qsc_code_frac_chars_top_3grams": 0.02723772, "qsc_code_frac_chars_top_4grams": 0.02704987, "qsc_code_frac_chars_dupe_5grams": 0.29435522, "qsc_code_frac_chars_dupe_6grams": 0.24213393, "qsc_code_frac_chars_dupe_7grams": 0.22588523, "qsc_code_frac_chars_dupe_8grams": 0.21348737, "qsc_code_frac_chars_dupe_9grams": 0.16117216, "qsc_code_frac_chars_dupe_10grams": 0.16117216, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.01459525, "qsc_code_frac_chars_whitespace": 0.2696302, "qsc_code_size_file_byte": 18199.0, "qsc_code_num_lines": 454.0, "qsc_code_num_chars_line_max": 181.0, "qsc_code_num_chars_line_mean": 40.08590308, "qsc_code_frac_chars_alphabet": 0.78641288, "qsc_code_frac_chars_comments": 0.13885378, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.20447284, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.09927901, "qsc_code_frac_chars_long_word_length": 0.00267977, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codecpp_frac_lines_preprocessor_directives": 0.04472843, "qsc_codecpp_frac_lines_func_ratio": 0.00319489, "qsc_codecpp_cate_bitsstdc": 0.0, "qsc_codecpp_nums_lines_main": 0.0, "qsc_codecpp_frac_lines_goto": 0.0, "qsc_codecpp_cate_var_zero": 0.0, "qsc_codecpp_score_lines_no_logic": 0.03833866, "qsc_codecpp_frac_lines_print": 0.00638978} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codecpp_frac_lines_func_ratio": 0, "qsc_codecpp_nums_lines_main": 0, "qsc_codecpp_score_lines_no_logic": 0, "qsc_codecpp_frac_lines_preprocessor_directives": 0, "qsc_codecpp_frac_lines_print": 0} |
0015/Fridge-Calendar | main/wifi.cpp | #include "wifi.hpp"
#include <esp_log.h>
#include <cstring>
static const char* TAG = "[WiFi]";
WiFi::WiFi(const std::string& ssid, const std::string& password, EventGroupHandle_t event_group, EventBits_t connected_bit)
: ssid(ssid), password(password), event_group(event_group), connected_bit(connected_bit) {}
WiFi::~WiFi() {
esp_wifi_stop();
esp_wifi_deinit();
}
void WiFi::init() {
ESP_LOGI(TAG, "Initializing WiFi...");
// Initialize TCP/IP stack
ESP_ERROR_CHECK(esp_netif_init());
ESP_ERROR_CHECK(esp_event_loop_create_default());
// Create default WiFi station
esp_netif_create_default_wifi_sta();
// Initialize WiFi driver
wifi_init_config_t cfg = WIFI_INIT_CONFIG_DEFAULT();
ESP_ERROR_CHECK(esp_wifi_init(&cfg));
// Register event handler
ESP_ERROR_CHECK(esp_event_handler_instance_register(WIFI_EVENT, ESP_EVENT_ANY_ID, &WiFi::event_handler, this, nullptr));
ESP_ERROR_CHECK(esp_event_handler_instance_register(IP_EVENT, IP_EVENT_STA_GOT_IP, &WiFi::event_handler, this, nullptr));
}
void WiFi::start() {
ESP_LOGI(TAG, "Starting WiFi...");
// Configure WiFi
wifi_config_t wifi_config = {};
strncpy(reinterpret_cast<char*>(wifi_config.sta.ssid), ssid.c_str(), sizeof(wifi_config.sta.ssid) - 1);
strncpy(reinterpret_cast<char*>(wifi_config.sta.password), password.c_str(), sizeof(wifi_config.sta.password) - 1);
wifi_config.sta.threshold.authmode = WIFI_AUTH_WPA2_PSK;
ESP_ERROR_CHECK(esp_wifi_set_mode(WIFI_MODE_STA));
ESP_ERROR_CHECK(esp_wifi_set_config(WIFI_IF_STA, &wifi_config));
// Start WiFi
ESP_ERROR_CHECK(esp_wifi_start());
ESP_LOGI(TAG, "WiFi initialization complete.");
}
void WiFi::event_handler(void* arg, esp_event_base_t event_base, int32_t event_id, void* event_data) {
auto* wifi = static_cast<WiFi*>(arg);
if (event_base == WIFI_EVENT) {
if (event_id == WIFI_EVENT_STA_START) {
ESP_LOGI(TAG, "Connecting to WiFi...");
esp_wifi_connect();
} else if (event_id == WIFI_EVENT_STA_DISCONNECTED) {
ESP_LOGW(TAG, "Disconnected from WiFi. Reconnecting...");
esp_wifi_connect();
}
} else if (event_base == IP_EVENT && event_id == IP_EVENT_STA_GOT_IP) {
ESP_LOGI(TAG, "Got IP address!");
xEventGroupSetBits(wifi->event_group, wifi->connected_bit);
}
}
| 2,391 | wifi | cpp | en | cpp | code | {"qsc_code_num_words": 333, "qsc_code_num_chars": 2391.0, "qsc_code_mean_word_length": 4.65765766, "qsc_code_frac_words_unique": 0.25825826, "qsc_code_frac_chars_top_2grams": 0.03610574, "qsc_code_frac_chars_top_3grams": 0.06705351, "qsc_code_frac_chars_top_4grams": 0.0825274, "qsc_code_frac_chars_dupe_5grams": 0.33655706, "qsc_code_frac_chars_dupe_6grams": 0.22114765, "qsc_code_frac_chars_dupe_7grams": 0.10702772, "qsc_code_frac_chars_dupe_8grams": 0.05673759, "qsc_code_frac_chars_dupe_9grams": 0.0, "qsc_code_frac_chars_dupe_10grams": 0.0, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.00251004, "qsc_code_frac_chars_whitespace": 0.16687578, "qsc_code_size_file_byte": 2391.0, "qsc_code_num_lines": 68.0, "qsc_code_num_chars_line_max": 126.0, "qsc_code_num_chars_line_mean": 35.16176471, "qsc_code_frac_chars_alphabet": 0.77610442, "qsc_code_frac_chars_comments": 0.05938938, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.04347826, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.06847488, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codecpp_frac_lines_preprocessor_directives": 0.06521739, "qsc_codecpp_frac_lines_func_ratio": 0.0, "qsc_codecpp_cate_bitsstdc": 0.0, "qsc_codecpp_nums_lines_main": 0.0, "qsc_codecpp_frac_lines_goto": 0.0, "qsc_codecpp_cate_var_zero": 0.0, "qsc_codecpp_score_lines_no_logic": 0.06521739, "qsc_codecpp_frac_lines_print": 0.0} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codecpp_frac_lines_func_ratio": 0, "qsc_codecpp_nums_lines_main": 0, "qsc_codecpp_score_lines_no_logic": 0, "qsc_codecpp_frac_lines_preprocessor_directives": 0, "qsc_codecpp_frac_lines_print": 0} |
0015/7-Color-E-Paper-Digital-Photo-Frame | ESP32-Arduino/E-Paper_Photo_Frame/EPD_7_Colors.cpp | // EPD_7_Colors.cpp
#include "EPD_7_Colors.h"
// IO pin settings
int BUSY_Pin = D5;
int RES_Pin = D0;
int DC_Pin = D3;
int CS_Pin = D1;
void driver_delay_us(unsigned int xus) {
for (; xus > 1; xus--)
;
}
void driver_delay(unsigned long xms) {
unsigned long i = 0, j = 0;
for (j = 0; j < xms; j++) {
for (i = 0; i < 256; i++)
;
}
}
void DELAY_S(unsigned int delaytime) {
int i, j, k;
for (i = 0; i < delaytime; i++) {
for (j = 0; j < 4000; j++) {
for (k = 0; k < 222; k++)
;
}
}
}
void SPI_Delay(unsigned char xrate) {
unsigned char i;
while (xrate) {
for (i = 0; i < 2; i++)
;
xrate--;
}
}
void SPI_Write(unsigned char value) {
SPI.transfer(value);
}
void EPD_W21_WriteCMD(unsigned char command) {
SPI_Delay(1);
EPD_W21_CS_0;
EPD_W21_DC_0;
SPI_Write(command);
EPD_W21_CS_1;
}
void EPD_W21_WriteDATA(unsigned char command) {
SPI_Delay(1);
EPD_W21_CS_0;
EPD_W21_DC_1;
SPI_Write(command);
EPD_W21_CS_1;
}
void EPD_W21_Init(void) {
EPD_W21_RST_0;
delay(100);
EPD_W21_RST_1;
delay(100);
}
void EPD_init(void) {
EPD_W21_Init(); //Electronic paper IC reset
EPD_W21_WriteCMD(0x01); //POWER SETTING
EPD_W21_WriteDATA(0x37);
EPD_W21_WriteDATA(0x00);
EPD_W21_WriteDATA(0x23);
EPD_W21_WriteDATA(0x23);
EPD_W21_WriteCMD(0X00); //PANNEL SETTING
EPD_W21_WriteDATA(0xEF);
EPD_W21_WriteDATA(0x08);
EPD_W21_WriteCMD(0x03); //PFS
EPD_W21_WriteDATA(0x00);
EPD_W21_WriteCMD(0x06); //boostÉ趨
EPD_W21_WriteDATA(0xC7);
EPD_W21_WriteDATA(0xC7);
EPD_W21_WriteDATA(0x1D);
EPD_W21_WriteCMD(0x30); //PLL setting
EPD_W21_WriteDATA(0x3C); //PLL: 0-25¡æ:0x3C,25+:0x3A
EPD_W21_WriteCMD(0X41); //TSE
EPD_W21_WriteDATA(0x00);
EPD_W21_WriteCMD(0X50); //VCOM AND DATA INTERVAL SETTING
EPD_W21_WriteDATA(0x37); //0x77
EPD_W21_WriteCMD(0X60); //TCON SETTING
EPD_W21_WriteDATA(0x22);
EPD_W21_WriteCMD(0X60); //TCON SETTING
EPD_W21_WriteDATA(0x22);
EPD_W21_WriteCMD(0x61); //tres
EPD_W21_WriteDATA(0x02); //source 600
EPD_W21_WriteDATA(0x58);
EPD_W21_WriteDATA(0x01); //gate 448
EPD_W21_WriteDATA(0xC0);
EPD_W21_WriteCMD(0xE3); //PWS
EPD_W21_WriteDATA(0xAA);
EPD_W21_WriteCMD(0x04); //PWR on
lcd_chkstatus(); //waiting for the electronic paper IC to release the idle signal
}
void EPD_refresh(void) {
EPD_W21_WriteCMD(0x12);
driver_delay(100);
lcd_chkstatus();
}
void EPD_sleep(void) {
EPD_W21_WriteCMD(0x02);
lcd_chkstatus();
EPD_W21_WriteCMD(0x07);
EPD_W21_WriteDATA(0xA5);
}
void Acep_color(unsigned char color) {
unsigned int i, j;
EPD_W21_WriteCMD(0x10);
for (i = 0; i < 448; i++) {
for (j = 0; j < 300; j++) {
EPD_W21_WriteDATA(color);
}
}
EPD_W21_WriteCMD(0x12);
delay(1);
lcd_chkstatus();
}
unsigned char Color_get(unsigned char color) {
unsigned char datas;
switch (color) {
case 0xFF: datas = white; break;
case 0xFC: datas = yellow; break;
case 0xEC: datas = orange; break;
case 0xE0: datas = red; break;
case 0x35: datas = green; break;
case 0x2B: datas = blue; break;
case 0x00: datas = black; break;
default: break;
}
return datas;
}
void PIC_display(const unsigned char* picData) {
unsigned int i, j, k;
unsigned char temp1, temp2;
unsigned char data_H, data_L, data;
Acep_color(Clean);
EPD_W21_WriteCMD(0x10);
for (i = 0; i < 448; i++) {
k = 0;
for (j = 0; j < 300; j++) {
temp1 = picData[i * 600 + k++];
temp2 = picData[i * 600 + k++];
data_H = Color_get(temp1) << 4;
data_L = Color_get(temp2);
data = data_H | data_L;
EPD_W21_WriteDATA(data);
}
}
EPD_W21_WriteCMD(0x12);
delay(1);
lcd_chkstatus();
}
void EPD_horizontal(void) {
unsigned int i, j;
unsigned char index = 0x00;
unsigned char const Color[8] = { Black, White, Green, Blue, Red, Yellow, Orange, Clean };
Acep_color(Clean);
EPD_W21_WriteCMD(0x10);
for (i = 0; i < 448; i++) {
if ((i % 56 == 0) && (i != 0))
index++;
for (j = 0; j < 600 / 2; j++) {
EPD_W21_WriteDATA(Color[index]);
}
}
EPD_W21_WriteCMD(0x12);
delay(1);
lcd_chkstatus();
}
void EPD_vertical(void) {
unsigned int i, j, k;
unsigned char const Color[8] = { Black, White, Green, Blue, Red, Yellow, Orange, Clean };
Acep_color(Clean);
EPD_W21_WriteCMD(0x10);
for (i = 0; i < 448; i++) {
for (k = 0; k < 7; k++) {
for (j = 0; j < 38; j++) {
EPD_W21_WriteDATA(Color[k]);
}
}
for (j = 0; j < 34; j++) {
EPD_W21_WriteDATA(0x77);
}
}
EPD_W21_WriteCMD(0x12);
delay(1);
lcd_chkstatus();
}
void PIC_display_Clear(void) {
unsigned int i, j;
Acep_color(Clean);
EPD_W21_WriteCMD(0x10);
for (i = 0; i < 448; i++) {
for (j = 0; j < 300; j++) {
EPD_W21_WriteDATA(White);
}
}
EPD_W21_WriteCMD(0x12);
delay(1);
lcd_chkstatus();
}
void lcd_chkstatus(void) {
while (!isEPD_W21_BUSY)
;
} | 4,991 | EPD_7_Colors | cpp | en | cpp | code | {"qsc_code_num_words": 759, "qsc_code_num_chars": 4991.0, "qsc_code_mean_word_length": 3.88801054, "qsc_code_frac_words_unique": 0.21343874, "qsc_code_frac_chars_top_2grams": 0.13012538, "qsc_code_frac_chars_top_3grams": 0.14232464, "qsc_code_frac_chars_top_4grams": 0.01626567, "qsc_code_frac_chars_dupe_5grams": 0.42053541, "qsc_code_frac_chars_dupe_6grams": 0.36428329, "qsc_code_frac_chars_dupe_7grams": 0.33954592, "qsc_code_frac_chars_dupe_8grams": 0.28566588, "qsc_code_frac_chars_dupe_9grams": 0.27346662, "qsc_code_frac_chars_dupe_10grams": 0.24635717, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.10620618, "qsc_code_frac_chars_whitespace": 0.22841114, "qsc_code_size_file_byte": 4991.0, "qsc_code_num_lines": 240.0, "qsc_code_num_chars_line_max": 92.0, "qsc_code_num_chars_line_mean": 20.79583333, "qsc_code_frac_chars_alphabet": 0.65930927, "qsc_code_frac_chars_comments": 0.07012623, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.29787234, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.00301594, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.04739336, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codecpp_frac_lines_preprocessor_directives": 0.00531915, "qsc_codecpp_frac_lines_func_ratio": 0.09574468, "qsc_codecpp_cate_bitsstdc": 0.0, "qsc_codecpp_nums_lines_main": 0.0, "qsc_codecpp_frac_lines_goto": 0.0, "qsc_codecpp_cate_var_zero": 0.0, "qsc_codecpp_score_lines_no_logic": 0.11702128, "qsc_codecpp_frac_lines_print": 0.0} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codecpp_frac_lines_func_ratio": 0, "qsc_codecpp_nums_lines_main": 0, "qsc_codecpp_score_lines_no_logic": 0, "qsc_codecpp_frac_lines_preprocessor_directives": 0, "qsc_codecpp_frac_lines_print": 0} |
0015/7-Color-E-Paper-Digital-Photo-Frame | ESP32-Arduino/E-Paper_Photo_Frame/EPD_7_Colors.h | // EPD_7_Colors.h
#ifndef EPD_7_COLORS_H
#define EPD_7_COLORS_H
#include <Arduino.h>
#include <SPI.h>
// IO settings
extern int BUSY_Pin;
extern int RES_Pin;
extern int DC_Pin;
extern int CS_Pin;
// 8-bit color definitions
#define Black 0x00 /// 000
#define White 0x11 /// 001
#define Green 0x22 /// 010
#define Blue 0x33 /// 011
#define Red 0x44 /// 100
#define Yellow 0x55 /// 101
#define Orange 0x66 /// 110
#define Clean 0x77 /// 111
// 4-bit color definitions
#define black 0x00 /// 000
#define white 0x01 /// 001
#define green 0x02 /// 010
#define blue 0x03 /// 011
#define red 0x04 /// 100
#define yellow 0x05 /// 101
#define orange 0x06 /// 110
#define clean 0x07 /// 111
// Macro definitions for pins
#define EPD_W21_CS_0 digitalWrite(CS_Pin, LOW)
#define EPD_W21_CS_1 digitalWrite(CS_Pin, HIGH)
#define EPD_W21_DC_0 digitalWrite(DC_Pin, LOW)
#define EPD_W21_DC_1 digitalWrite(DC_Pin, HIGH)
#define EPD_W21_RST_0 digitalWrite(RES_Pin, LOW)
#define EPD_W21_RST_1 digitalWrite(RES_Pin, HIGH)
#define isEPD_W21_BUSY digitalRead(BUSY_Pin)
// Function declarations
void driver_delay_us(unsigned int xus);
void driver_delay(unsigned long xms);
void DELAY_S(unsigned int delaytime);
void SPI_Delay(unsigned char xrate);
void SPI_Write(unsigned char value);
void EPD_W21_WriteDATA(unsigned char command);
void EPD_W21_WriteCMD(unsigned char command);
void EPD_W21_Init(void);
void EPD_init(void);
void PIC_display(const unsigned char* picData);
void EPD_sleep(void);
void EPD_refresh(void);
void lcd_chkstatus(void);
void PIC_display_Clear(void);
void EPD_horizontal(void);
void EPD_vertical(void);
void Acep_color(unsigned char color);
unsigned char Color_get(unsigned char color);
#endif // EPD_7_COLORS_H | 1,750 | EPD_7_Colors | h | en | c | code | {"qsc_code_num_words": 281, "qsc_code_num_chars": 1750.0, "qsc_code_mean_word_length": 4.47330961, "qsc_code_frac_words_unique": 0.35587189, "qsc_code_frac_chars_top_2grams": 0.04295943, "qsc_code_frac_chars_top_3grams": 0.05727924, "qsc_code_frac_chars_top_4grams": 0.03500398, "qsc_code_frac_chars_dupe_5grams": 0.19570406, "qsc_code_frac_chars_dupe_6grams": 0.12251392, "qsc_code_frac_chars_dupe_7grams": 0.07637232, "qsc_code_frac_chars_dupe_8grams": 0.07637232, "qsc_code_frac_chars_dupe_9grams": 0.07637232, "qsc_code_frac_chars_dupe_10grams": 0.0, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.08533333, "qsc_code_frac_chars_whitespace": 0.14285714, "qsc_code_size_file_byte": 1750.0, "qsc_code_num_lines": 63.0, "qsc_code_num_chars_line_max": 50.0, "qsc_code_num_chars_line_mean": 27.77777778, "qsc_code_frac_chars_alphabet": 0.75266667, "qsc_code_frac_chars_comments": 0.16457143, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.0, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.0, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.04374573, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codec_frac_lines_func_ratio": 0.69444444, "qsc_codec_cate_bitsstdc": 0.0, "qsc_codec_nums_lines_main": 0, "qsc_codec_frac_lines_goto": 0.0, "qsc_codec_cate_var_zero": 0.0, "qsc_codec_score_lines_no_logic": 0.75, "qsc_codec_frac_lines_print": 0.0, "qsc_codec_frac_lines_preprocessor_directives": null} | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codec_frac_lines_func_ratio": 1, "qsc_codec_nums_lines_main": 0, "qsc_codec_score_lines_no_logic": 1, "qsc_codec_frac_lines_preprocessor_directives": 0, "qsc_codec_frac_lines_print": 0} |
0015/7-Color-E-Paper-Digital-Photo-Frame | ESP32-Arduino/E-Paper_Photo_Frame/E-Paper_Photo_Frame.ino | /*
ESP32 E-Paper Digital Frame Project
https://github.com/0015/7-Color-E-Paper-Digital-Photo-Frame
5.65" Seven-Color eInk
https://www.seeedstudio.com/5-65-Seven-Color-ePaper-Display-with-600x480-Pixels-p-5786.html
XIAO eInk Expansion Board
https://wiki.seeedstudio.com/XIAO-eInk-Expansion-Board/
XIAO ESP32-S3
https://www.seeedstudio.com/XIAO-ESP32S3-p-5627.html
ESP32 Arduino Core
Version: 3.0.7
*/
// Image byte data is stored in PSRAM, so need to enable PSRAM.
#include "EPD_7_Colors.h"
#include <WiFi.h>
#include <HTTPClient.h>
#define S_To_uS_Factor 1000000ULL //Conversion factor for micro seconds to seconds
const char* ssid = "your_wifi_ssid"; // Your WiFi SSID
const char* password = "your_wifi_password"; // Your WiFi Password
const char* getImageUrl = "http://your-server-ip:9999/get-img-data";
const char* wakeupIntervalUrl = "http://your-server-ip:9999/wakeup-interval";
void setup() {
Serial.begin(115200);
pinMode(BUSY_Pin, INPUT);
pinMode(RES_Pin, OUTPUT);
pinMode(DC_Pin, OUTPUT);
pinMode(CS_Pin, OUTPUT);
SPI.beginTransaction(SPISettings(10000000, MSBFIRST, SPI_MODE0));
SPI.begin();
connectWiFi();
mainTask();
}
void loop() {
delay(60000);
}
void connectWiFi() {
int retryCount = 0;
WiFi.mode(WIFI_STA); // Set WiFi to station mode
WiFi.begin(ssid, password);
// Attempt to connect for a set number of retries
while (WiFi.status() != WL_CONNECTED && retryCount < 10) {
delay(1000);
Serial.println("Connecting to WiFi...");
retryCount++;
}
if (WiFi.status() == WL_CONNECTED) {
Serial.println("Connected to WiFi!");
} else {
Serial.println("Failed to connect to WiFi after 10 attempts, stopping WiFi.");
hibernate(3600);
}
}
void mainTask() {
if (WiFi.status() == WL_CONNECTED) {
// Start downloading the image data
downloadImageData();
// Fetch the wakeup interval and go into deep sleep
hibernate(fetchWakeupInterval());
} else {
hibernate(3600); // Go to sleep for 1 hour if no WiFi connection
}
}
void downloadImageData() {
HTTPClient http;
if (!http.begin(getImageUrl)) {
Serial.println("Failed to initialize HTTP connection");
return;
}
// Make the request
int httpResponseCode = http.GET();
if (httpResponseCode > 0 && httpResponseCode == HTTP_CODE_OK) {
String payload = http.getString();
// Count the number of elements based on commas in the payload
int elementCount = 1;
for (int i = 0; i < payload.length(); i++) {
if (payload[i] == ',') elementCount++;
}
// Allocate memory for the uint8_t array
uint8_t* dataBuffer = (uint8_t*)ps_malloc(elementCount);
if (dataBuffer == nullptr) {
Serial.println("Failed to allocate memory in PSRAM");
return;
}
// Parse the payload string and fill the array
int index = 0;
int startPos = 0;
for (int i = 0; i < payload.length(); i++) {
if (payload[i] == ',' || i == payload.length() - 1) {
// Get the substring for the current hex value
String hexValue = payload.substring(startPos, i);
hexValue.trim(); // Trim whitespace around the hex string
// Convert hex string to uint8_t and store it in the array
dataBuffer[index++] = (uint8_t)strtol(hexValue.c_str(), nullptr, 16);
// Update start position for the next hex value
startPos = i + 1;
}
}
EPD_init();
PIC_display((const uint8_t*)dataBuffer);
EPD_sleep();
free(dataBuffer); // Free the allocated memory if no longer needed
dataBuffer = nullptr;
} else {
Serial.printf("HTTP GET request failed, error: %s\n", http.errorToString(httpResponseCode).c_str());
}
http.end(); // Close connection
}
int fetchWakeupInterval() {
HTTPClient http;
if (!http.begin(wakeupIntervalUrl)) {
Serial.println("Failed to initialize HTTP connection");
return 3600; // Default to 1 hour if there’s an error
}
int httpResponseCode = http.GET();
if (httpResponseCode > 0) {
String payload = http.getString();
int interval = payload.substring(payload.indexOf(':') + 1, payload.indexOf('}')).toInt(); // Extract the integer value
http.end();
return interval;
} else {
Serial.printf("Error fetching interval: %s\n", http.errorToString(httpResponseCode).c_str());
http.end();
return 3600; // Default to 1 hour if there’s an error
}
}
void hibernate(int interval) {
WiFi.disconnect(true); // Disconnect from any connection attempt
WiFi.mode(WIFI_OFF); // Turn off the WiFi
delay(1000);
esp_sleep_enable_timer_wakeup(interval * S_To_uS_Factor); // Convert to microseconds
esp_deep_sleep_start();
} | 4,709 | E-Paper_Photo_Frame | ino | en | cpp | code | {"qsc_code_num_words": 616, "qsc_code_num_chars": 4709.0, "qsc_code_mean_word_length": 5.03084416, "qsc_code_frac_words_unique": 0.36525974, "qsc_code_frac_chars_top_2grams": 0.02516941, "qsc_code_frac_chars_top_3grams": 0.02452404, "qsc_code_frac_chars_top_4grams": 0.02710552, "qsc_code_frac_chars_dupe_5grams": 0.18005808, "qsc_code_frac_chars_dupe_6grams": 0.13617296, "qsc_code_frac_chars_dupe_7grams": 0.13617296, "qsc_code_frac_chars_dupe_8grams": 0.10713133, "qsc_code_frac_chars_dupe_9grams": 0.0761536, "qsc_code_frac_chars_dupe_10grams": 0.0464666, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.03304904, "qsc_code_frac_chars_whitespace": 0.20322786, "qsc_code_size_file_byte": 4709.0, "qsc_code_num_lines": 165.0, "qsc_code_num_chars_line_max": 124.0, "qsc_code_num_chars_line_mean": 28.53939394, "qsc_code_frac_chars_alphabet": 0.79291045, "qsc_code_frac_chars_comments": 0.30346146, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.20618557, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.12191405, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codecpp_frac_lines_preprocessor_directives": 0.04123711, "qsc_codecpp_frac_lines_func_ratio": 0.07216495, "qsc_codecpp_cate_bitsstdc": 0.0, "qsc_codecpp_nums_lines_main": 0.0, "qsc_codecpp_frac_lines_goto": 0.0, "qsc_codecpp_cate_var_zero": 0.0, "qsc_codecpp_score_lines_no_logic": 0.13402062, "qsc_codecpp_frac_lines_print": 0.02061856} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codecpp_frac_lines_func_ratio": 0, "qsc_codecpp_nums_lines_main": 0, "qsc_codecpp_score_lines_no_logic": 0, "qsc_codecpp_frac_lines_preprocessor_directives": 0, "qsc_codecpp_frac_lines_print": 0} |
0015/esp_rlottie | rlottie/licenses/COPYING.STB | MIT License
Copyright (c) 2017 Sean Barrett
Permission is hereby granted, free of charge, to any person obtaining a copy of
this software and associated documentation files (the "Software"), to deal in
the Software without restriction, including without limitation the rights to
use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies
of the Software, and to permit persons to whom the Software is furnished to do
so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
| 1,073 | COPYING | stb | en | text | text | {"qsc_doc_frac_chars_curly_bracket": 0.0, "qsc_doc_frac_words_redpajama_stop": 0.22772277, "qsc_doc_num_sentences": 3.0, "qsc_doc_num_words": 170, "qsc_doc_num_chars": 1073.0, "qsc_doc_num_lines": 17.0, "qsc_doc_mean_word_length": 5.06470588, "qsc_doc_frac_words_full_bracket": 0.0, "qsc_doc_frac_lines_end_with_readmore": 0.0, "qsc_doc_frac_lines_start_with_bullet": 0.0, "qsc_doc_frac_words_unique": 0.57058824, "qsc_doc_entropy_unigram": 4.19089328, "qsc_doc_frac_words_all_caps": 0.38118812, "qsc_doc_frac_lines_dupe_lines": 0.0, "qsc_doc_frac_chars_dupe_lines": 0.0, "qsc_doc_frac_chars_top_2grams": 0.10220674, "qsc_doc_frac_chars_top_3grams": 0.03019744, "qsc_doc_frac_chars_top_4grams": 0.0, "qsc_doc_frac_chars_dupe_5grams": 0.0, "qsc_doc_frac_chars_dupe_6grams": 0.0, "qsc_doc_frac_chars_dupe_7grams": 0.0, "qsc_doc_frac_chars_dupe_8grams": 0.0, "qsc_doc_frac_chars_dupe_9grams": 0.0, "qsc_doc_frac_chars_dupe_10grams": 0.0, "qsc_doc_frac_chars_replacement_symbols": 0.0, "qsc_doc_cate_code_related_file_name": 0.0, "qsc_doc_num_chars_sentence_length_mean": 50.14285714, "qsc_doc_frac_chars_hyperlink_html_tag": 0.0, "qsc_doc_frac_chars_alphabet": 0.95647321, "qsc_doc_frac_chars_digital": 0.00446429, "qsc_doc_frac_chars_whitespace": 0.16495806, "qsc_doc_frac_chars_hex_words": 0.0} | 1 | {"qsc_doc_frac_chars_replacement_symbols": 0, "qsc_doc_entropy_unigram": 0, "qsc_doc_frac_chars_top_2grams": 0, "qsc_doc_frac_chars_top_3grams": 0, "qsc_doc_frac_chars_top_4grams": 0, "qsc_doc_frac_chars_dupe_5grams": 0, "qsc_doc_frac_chars_dupe_6grams": 0, "qsc_doc_frac_chars_dupe_7grams": 0, "qsc_doc_frac_chars_dupe_8grams": 0, "qsc_doc_frac_chars_dupe_9grams": 0, "qsc_doc_frac_chars_dupe_10grams": 0, "qsc_doc_frac_chars_dupe_lines": 0, "qsc_doc_frac_lines_dupe_lines": 0, "qsc_doc_frac_lines_end_with_readmore": 0, "qsc_doc_frac_lines_start_with_bullet": 0, "qsc_doc_frac_words_all_caps": 0, "qsc_doc_mean_word_length": 0, "qsc_doc_num_chars": 0, "qsc_doc_num_lines": 0, "qsc_doc_num_sentences": 0, "qsc_doc_num_words": 0, "qsc_doc_frac_chars_hex_words": 0, "qsc_doc_frac_chars_hyperlink_html_tag": 0, "qsc_doc_frac_chars_alphabet": 0, "qsc_doc_frac_chars_digital": 0, "qsc_doc_frac_chars_whitespace": 0} |
0015/esp_rlottie | rlottie/licenses/COPYING.MIT | Copyright 2020 (see AUTHORS)
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
| 1,053 | COPYING | mit | en | text | text | {"qsc_doc_frac_chars_curly_bracket": 0.0, "qsc_doc_frac_words_redpajama_stop": 0.23115578, "qsc_doc_num_sentences": 3.0, "qsc_doc_num_words": 167, "qsc_doc_num_chars": 1053.0, "qsc_doc_num_lines": 7.0, "qsc_doc_mean_word_length": 5.08383234, "qsc_doc_frac_words_full_bracket": 0.0, "qsc_doc_frac_lines_end_with_readmore": 0.0, "qsc_doc_frac_lines_start_with_bullet": 0.0, "qsc_doc_frac_words_unique": 0.55688623, "qsc_doc_entropy_unigram": 4.14781315, "qsc_doc_frac_words_all_caps": 0.38693467, "qsc_doc_frac_lines_dupe_lines": 0.0, "qsc_doc_frac_chars_dupe_lines": 0.0, "qsc_doc_frac_chars_top_2grams": 0.10365135, "qsc_doc_frac_chars_top_3grams": 0.03062426, "qsc_doc_frac_chars_top_4grams": 0.0, "qsc_doc_frac_chars_dupe_5grams": 0.0, "qsc_doc_frac_chars_dupe_6grams": 0.0, "qsc_doc_frac_chars_dupe_7grams": 0.0, "qsc_doc_frac_chars_dupe_8grams": 0.0, "qsc_doc_frac_chars_dupe_9grams": 0.0, "qsc_doc_frac_chars_dupe_10grams": 0.0, "qsc_doc_frac_chars_replacement_symbols": 0.0, "qsc_doc_cate_code_related_file_name": 0.0, "qsc_doc_num_chars_sentence_length_mean": 94.81818182, "qsc_doc_frac_chars_hyperlink_html_tag": 0.0, "qsc_doc_frac_chars_alphabet": 0.95588235, "qsc_doc_frac_chars_digital": 0.00452489, "qsc_doc_frac_chars_whitespace": 0.16049383, "qsc_doc_frac_chars_hex_words": 0.0} | 0 | {"qsc_doc_frac_chars_replacement_symbols": 0, "qsc_doc_entropy_unigram": 0, "qsc_doc_frac_chars_top_2grams": 0, "qsc_doc_frac_chars_top_3grams": 0, "qsc_doc_frac_chars_top_4grams": 0, "qsc_doc_frac_chars_dupe_5grams": 0, "qsc_doc_frac_chars_dupe_6grams": 0, "qsc_doc_frac_chars_dupe_7grams": 0, "qsc_doc_frac_chars_dupe_8grams": 0, "qsc_doc_frac_chars_dupe_9grams": 0, "qsc_doc_frac_chars_dupe_10grams": 0, "qsc_doc_frac_chars_dupe_lines": 0, "qsc_doc_frac_lines_dupe_lines": 0, "qsc_doc_frac_lines_end_with_readmore": 0, "qsc_doc_frac_lines_start_with_bullet": 0, "qsc_doc_frac_words_all_caps": 0, "qsc_doc_mean_word_length": 0, "qsc_doc_num_chars": 0, "qsc_doc_num_lines": 1, "qsc_doc_num_sentences": 0, "qsc_doc_num_words": 0, "qsc_doc_frac_chars_hex_words": 0, "qsc_doc_frac_chars_hyperlink_html_tag": 0, "qsc_doc_frac_chars_alphabet": 0, "qsc_doc_frac_chars_digital": 0, "qsc_doc_frac_chars_whitespace": 0} |
000haoji/deep-student | src/components/BatchAnalysis.tsx | import React, { useState, useEffect, useCallback } from 'react';
import { TauriAPI } from '../utils/tauriApi';
import { BatchTask, ChatMessage } from '../types';
import UniversalAppChatHost, { UniversalAppChatHostProps } from './UniversalAppChatHost';
interface BatchAnalysisProps {
onBack: () => void;
}
export const BatchAnalysis: React.FC<BatchAnalysisProps> = ({ onBack }) => {
// 基础状态
const [tasks, setTasks] = useState<BatchTask[]>([]);
const [isProcessing, setIsProcessing] = useState(false);
const [currentTaskIndex, setCurrentTaskIndex] = useState(-1);
const [showDetailView, setShowDetailView] = useState(false);
const [selectedTaskForDetail, setSelectedTaskForDetail] = useState<BatchTask | null>(null);
const [availableSubjects, setAvailableSubjects] = useState<string[]>([]);
const [isLoadingSubjects, setIsLoadingSubjects] = useState(true);
// RAG相关状态
const [enableRag, setEnableRag] = useState(false);
const [ragTopK, setRagTopK] = useState(5);
// 工具函数
const base64ToFile = (base64: string, filename: string): File => {
const arr = base64.split(',');
const mime = arr[0].match(/:(.*?);/)?.[1] || 'image/jpeg';
const bstr = atob(arr[1]);
let n = bstr.length;
const u8arr = new Uint8Array(n);
while (n--) {
u8arr[n] = bstr.charCodeAt(n);
}
return new File([u8arr], filename, { type: mime });
};
const generateUniqueId = () => {
return `batch_task_${Date.now()}_${Math.random().toString(36).substr(2, 9)}`;
};
// 基础函数定义
const updateTask = useCallback((taskId: string, updates: Partial<BatchTask>) => {
setTasks(prev => prev.map(task =>
task.id === taskId ? { ...task, ...updates } : task
));
}, []);
const addTask = useCallback(() => {
const newTask: BatchTask = {
id: generateUniqueId(),
subject: availableSubjects[0] || '数学',
userQuestion: '',
questionImages: [],
analysisImages: [],
status: 'pending',
chatHistory: [],
thinkingContent: new Map(),
temp_id: null,
ocr_result: null,
currentFullContentForStream: '',
currentThinkingContentForStream: '',
};
setTasks(prev => [...prev, newTask]);
}, [availableSubjects]);
const removeTask = useCallback((taskId: string) => {
setTasks(prev => prev.filter(task => task.id !== taskId));
}, []);
const saveTasksToStorage = useCallback(async (tasksToSave: BatchTask[]) => {
try {
const tasksToStore = tasksToSave.map(task => ({
...task,
thinkingContent: Object.fromEntries(task.thinkingContent || new Map()),
questionImagesBase64: task.questionImages?.map(file => ({
name: file.name,
base64: '' // 简化处理
})) || [],
analysisImagesBase64: task.analysisImages?.map(file => ({
name: file.name,
base64: '' // 简化处理
})) || []
}));
localStorage.setItem('batch-analysis-tasks', JSON.stringify(tasksToStore));
} catch (error) {
console.error('保存任务失败:', error);
}
}, []);
const handleImageUpload = useCallback((taskId: string, files: FileList | File[] | null, isAnalysis = false) => {
if (!files) return;
const fileArray = Array.from(files);
updateTask(taskId, {
[isAnalysis ? 'analysisImages' : 'questionImages']: fileArray
});
}, [updateTask]);
const removeImage = useCallback((taskId: string, imageIndex: number, isAnalysis = false) => {
const task = tasks.find(t => t.id === taskId);
if (!task) return;
const images = isAnalysis ? task.analysisImages : task.questionImages;
if (!images) return;
const newImages = images.filter((_, index) => index !== imageIndex);
updateTask(taskId, {
[isAnalysis ? 'analysisImages' : 'questionImages']: newImages
});
}, [tasks, updateTask]);
// 加载支持的科目
useEffect(() => {
const loadSubjects = async () => {
try {
const subjects = await TauriAPI.getSupportedSubjects();
setAvailableSubjects(subjects);
} catch (error) {
console.error('加载科目失败:', error);
setAvailableSubjects(['数学', '物理', '化学', '英语']);
} finally {
setIsLoadingSubjects(false);
}
};
loadSubjects();
}, []);
// 组件挂载时恢复正在运行的任务
useEffect(() => {
const resumeRunningTasks = async () => {
const runningTasks = tasks.filter(task =>
['ocr_processing', 'awaiting_stream_start', 'streaming_answer'].includes(task.status)
);
if (runningTasks.length > 0) {
console.log(`🔄 发现 ${runningTasks.length} 个运行中的任务，正在恢复...`);
// 建立全局状态监听器
await setupGlobalStatusListeners();
// 恢复流式监听
for (const task of runningTasks) {
if (task.temp_id) {
try {
if (task.status === 'streaming_answer') {
console.log(`🔄 恢复流式监听: 任务 ${task.id}`);
await resumeTaskStreaming(task);
} else {
console.log(`🔄 监听状态变化: 任务 ${task.id} (${task.status})`);
// 为OCR和等待阶段的任务建立状态监听
await setupTaskStatusListener(task);
}
} catch (error) {
console.error(`恢复任务 ${task.id} 失败:`, error);
updateTask(task.id, {
status: 'error_stream',
errorDetails: '页面切换后恢复失败: ' + error
});
}
}
}
}
};
// 延迟执行，确保组件完全挂载
const timer = setTimeout(resumeRunningTasks, 100);
return () => clearTimeout(timer);
}, []); // 只在组件挂载时执行一次
const setupGlobalStatusListeners = async () => {
const { listen } = await import('@tauri-apps/api/event');
// 监听任务状态变更事件
const unlistenStatus = await listen('task_status_update', (event: any) => {
console.log('🔄 收到任务状态更新:', event.payload);
const { temp_id, status, details } = event.payload;
// 查找对应的任务并更新状态
setTasks(prevTasks => {
const taskIndex = prevTasks.findIndex(t => t.temp_id === temp_id);
if (taskIndex === -1) return prevTasks;
const newTasks = [...prevTasks];
newTasks[taskIndex] = {
...newTasks[taskIndex],
status: status,
...(details && { errorDetails: details })
};
console.log(`✅ 更新任务状态: ${newTasks[taskIndex].id} -> ${status}`);
// 如果状态变为streaming_answer，建立流式监听
if (status === 'streaming_answer') {
setTimeout(() => {
resumeTaskStreaming(newTasks[taskIndex]).catch(console.error);
}, 100);
}
// 异步保存状态
saveTasksToStorage(newTasks).catch(console.error);
return newTasks;
});
});
// 监听流开始事件
const unlistenStreamStart = await listen('stream_started', (event: any) => {
console.log('🚀 收到流开始事件:', event.payload);
const { temp_id } = event.payload;
setTasks(prevTasks => {
const taskIndex = prevTasks.findIndex(t => t.temp_id === temp_id);
if (taskIndex === -1) return prevTasks;
const newTasks = [...prevTasks];
newTasks[taskIndex] = {
...newTasks[taskIndex],
status: 'streaming_answer'
};
console.log(`🚀 任务开始流式处理: ${newTasks[taskIndex].id}`);
// 建立流式监听
setTimeout(() => {
resumeTaskStreaming(newTasks[taskIndex]).catch(console.error);
}, 100);
saveTasksToStorage(newTasks).catch(console.error);
return newTasks;
});
});
};
// 为单个任务建立状态监听
const setupTaskStatusListener = async (task: BatchTask) => {
if (!task.temp_id) return;
const { listen } = await import('@tauri-apps/api/event');
// 监听该任务的流启动事件
const streamEvent = `analysis_stream_${task.temp_id}`;
const reasoningEvent = `${streamEvent}_reasoning`;
console.log(`🎧 为任务 ${task.id} 建立状态监听: ${streamEvent}`);
// 监听流事件，用于检测流开始
const unlistenStream = await listen(streamEvent, (event: any) => {
console.log(`📡 任务 ${task.id} 收到流事件，切换到streaming状态`);
updateTask(task.id, { status: 'streaming_answer' });
// 立即建立完整的流式监听
setTimeout(() => {
resumeTaskStreaming(task).catch(console.error);
}, 50);
});
};
// 恢复流式任务监听
const resumeTaskStreaming = async (task: BatchTask) => {
if (!task.temp_id) return;
console.log(`🔄 恢复任务 ${task.id} 的流式监听`);
const streamEvent = `analysis_stream_${task.temp_id}`;
let fullContent = task.currentFullContentForStream || '';
let fullThinkingContent = task.currentThinkingContentForStream || '';
let contentListenerActive = true;
let thinkingListenerActive = true;
const { listen } = await import('@tauri-apps/api/event');
// 监听主内容流
const unlistenContent = await listen(streamEvent, (event: any) => {
if (!contentListenerActive) return;
console.log(`💬 任务 ${task.id} 收到主内容流:`, event.payload);
if (event.payload) {
if (event.payload.is_complete) {
if (event.payload.content && event.payload.content.length >= fullContent.length) {
fullContent = event.payload.content;
}
console.log(`🎉 任务 ${task.id} 主内容流完成，总长度:`, fullContent.length);
updateTask(task.id, {
chatHistory: [{
role: 'assistant',
content: fullContent,
timestamp: new Date().toISOString(),
}],
status: 'completed',
currentFullContentForStream: fullContent,
});
contentListenerActive = false;
} else if (event.payload.content) {
fullContent += event.payload.content;
console.log(`📝 任务 ${task.id} 累积内容，当前长度: ${fullContent.length}`);
updateTask(task.id, {
chatHistory: [{
role: 'assistant',
content: fullContent,
timestamp: new Date().toISOString(),
}],
currentFullContentForStream: fullContent,
});
}
}
});
// 监听思维链流
const reasoningEvent = `${streamEvent}_reasoning`;
const unlistenThinking = await listen(reasoningEvent, (event: any) => {
if (!thinkingListenerActive) return;
console.log(`🧠 任务 ${task.id} 思维链流内容:`, event.payload);
if (event.payload) {
if (event.payload.is_complete) {
if (event.payload.content && event.payload.content.length >= fullThinkingContent.length) {
fullThinkingContent = event.payload.content;
}
console.log(`🎉 任务 ${task.id} 思维链流完成，总长度:`, fullThinkingContent.length);
updateTask(task.id, {
thinkingContent: new Map([[0, fullThinkingContent]]),
currentThinkingContentForStream: fullThinkingContent,
});
thinkingListenerActive = false;
} else if (event.payload.content) {
fullThinkingContent += event.payload.content;
console.log(`🧠 任务 ${task.id} 累积思维链，当前长度: ${fullThinkingContent.length}`);
updateTask(task.id, {
thinkingContent: new Map([[0, fullThinkingContent]]),
currentThinkingContentForStream: fullThinkingContent,
});
}
}
});
// 监听流错误
const unlistenError = await listen('stream_error', (event: any) => {
console.error(`❌ 任务 ${task.id} 流式处理错误:`, event.payload);
updateTask(task.id, {
status: 'error_stream',
errorDetails: '流式处理出错: ' + (event.payload?.message || '未知错误'),
});
contentListenerActive = false;
thinkingListenerActive = false;
});
// 注册监听器注销函数
const taskListeners = [unlistenContent, unlistenThinking, unlistenError];
};
// 处理单个任务的完整分析流程
const processSingleTask = async (task: BatchTask) => {
console.log(`🚀 开始处理任务: ${task.id}`);
try {
// 步骤1: 更新状态为OCR处理中
updateTask(task.id, { status: 'ocr_processing' });
// 步骤2: 调用OCR与初步分析
console.log(`📝 任务 ${task.id}: 开始OCR分析...`);
const stepResult = await TauriAPI.analyzeStepByStep({
subject: task.subject,
question_image_files: task.questionImages,
analysis_image_files: task.analysisImages,
user_question: task.userQuestion,
enable_chain_of_thought: true,
});
console.log(`✅ 任务 ${task.id}: OCR分析完成`, stepResult.ocr_result);
// 步骤3: 存储OCR结果并更新状态
updateTask(task.id, {
temp_id: stepResult.temp_id,
ocr_result: stepResult.ocr_result,
status: 'awaiting_stream_start',
});
// 步骤4: 准备流式处理
console.log(`🤖 任务 ${task.id}: 开始流式AI解答...`);
updateTask(task.id, { status: 'streaming_answer' });
// 创建初始的助手消息（空内容，等待流式填充）
const initialMessage: ChatMessage = {
role: 'assistant',
content: '',
timestamp: new Date().toISOString(),
};
updateTask(task.id, {
chatHistory: [initialMessage],
currentFullContentForStream: '',
currentThinkingContentForStream: '',
});
// 步骤5: 设置流式监听器
const streamEvent = `analysis_stream_${stepResult.temp_id}`;
let fullContent = '';
let fullThinkingContent = '';
let contentListenerActive = true;
let thinkingListenerActive = true;
const { listen } = await import('@tauri-apps/api/event');
// 先定义一个占位函数，稍后在Promise中重新定义
let checkAndFinalizeTaskStreams = () => {};
// 监听主内容流
const unlistenContent = await listen(streamEvent, (event: any) => {
if (!contentListenerActive) return;
console.log(`💬 任务 ${task.id} 收到主内容流:`, event.payload);
if (event.payload) {
if (event.payload.is_complete) {
if (event.payload.content && event.payload.content.length >= fullContent.length) {
fullContent = event.payload.content;
}
console.log(`🎉 任务 ${task.id} 主内容流完成，总长度:`, fullContent.length);
// 更新聊天历史的最终内容
updateTask(task.id, {
chatHistory: [{
role: 'assistant',
content: fullContent,
timestamp: new Date().toISOString(),
}],
});
contentListenerActive = false;
checkAndFinalizeTaskStreams();
} else if (event.payload.content) {
fullContent += event.payload.content;
console.log(`📝 任务 ${task.id} 累积内容，当前长度: ${fullContent.length}`);
// 实时更新聊天历史
updateTask(task.id, {
chatHistory: [{
role: 'assistant',
content: fullContent,
timestamp: new Date().toISOString(),
}],
currentFullContentForStream: fullContent,
});
}
}
});
// 监听思维链流
const reasoningEvent = `${streamEvent}_reasoning`;
console.log(`🧠 任务 ${task.id} 监听思维链事件: ${reasoningEvent}`);
const unlistenThinking = await listen(reasoningEvent, (event: any) => {
if (!thinkingListenerActive) return;
console.log(`🧠 任务 ${task.id} 思维链流内容:`, event.payload);
if (event.payload) {
if (event.payload.is_complete) {
if (event.payload.content && event.payload.content.length >= fullThinkingContent.length) {
fullThinkingContent = event.payload.content;
}
console.log(`🎉 任务 ${task.id} 思维链流完成，总长度:`, fullThinkingContent.length);
// 更新思维链内容
updateTask(task.id, {
thinkingContent: new Map([[0, fullThinkingContent]]),
currentThinkingContentForStream: fullThinkingContent,
});
thinkingListenerActive = false;
checkAndFinalizeTaskStreams();
} else if (event.payload.content) {
fullThinkingContent += event.payload.content;
console.log(`🧠 任务 ${task.id} 累积思维链，当前长度: ${fullThinkingContent.length}`);
// 实时更新思维链内容
updateTask(task.id, {
thinkingContent: new Map([[0, fullThinkingContent]]),
currentThinkingContentForStream: fullThinkingContent,
});
}
}
});
// 监听流错误
const unlistenError = await listen('stream_error', (event: any) => {
console.error(`❌ 任务 ${task.id} 流式处理错误:`, event.payload);
updateTask(task.id, {
status: 'error_stream',
errorDetails: '流式处理出错: ' + (event.payload?.message || '未知错误'),
});
contentListenerActive = false;
thinkingListenerActive = false;
});
// 监听RAG来源信息（如果启用了RAG）
let unlistenRagSources: (() => void) | null = null;
if (enableRag) {
const ragSourcesEvent = `${streamEvent}_rag_sources`;
console.log(`📚 任务 ${task.id} 监听RAG来源事件: ${ragSourcesEvent}`);
unlistenRagSources = await listen(ragSourcesEvent, (event: any) => {
console.log(`📚 任务 ${task.id} 收到RAG来源信息:`, event.payload);
if (event.payload && event.payload.sources) {
// 更新任务的聊天历史，为助手消息添加RAG来源信息
setTasks(prevTasks =>
prevTasks.map(currentTask => {
if (currentTask.id === task.id) {
const updatedChatHistory = [...currentTask.chatHistory];
if (updatedChatHistory.length > 0 && updatedChatHistory[0].role === 'assistant') {
updatedChatHistory[0] = {
...updatedChatHistory[0],
rag_sources: event.payload.sources
};
}
return { ...currentTask, chatHistory: updatedChatHistory };
}
return currentTask;
})
);
console.log(`✅ 任务 ${task.id} RAG来源信息已更新`);
}
});
}
// 注册监听器注销函数（任务级别）
const taskListeners = enableRag
? [unlistenContent, unlistenThinking, unlistenError, unlistenRagSources!]
: [unlistenContent, unlistenThinking, unlistenError];
// 步骤6: 启动流式解答
console.log(`🚀 任务 ${task.id} 启动流式解答，temp_id: ${stepResult.temp_id}, enable_rag: ${enableRag}`);
if (enableRag) {
// 使用RAG增强的流式解答
await TauriAPI.startRagEnhancedStreamingAnswer({
temp_id: stepResult.temp_id,
enable_chain_of_thought: true,
enable_rag: true,
rag_options: {
top_k: ragTopK,
enable_reranking: true
}
});
} else {
// 使用普通的流式解答
await TauriAPI.startStreamingAnswer(stepResult.temp_id, true);
}
// 等待流处理完成（通过Promise机制避免状态循环检查）
return new Promise<void>((resolve, reject) => {
let isResolved = false;
const resolveOnce = () => {
if (!isResolved) {
isResolved = true;
console.log(`✅ 任务 ${task.id} 处理完成`);
resolve();
}
};
const rejectOnce = (error: string) => {
if (!isResolved) {
isResolved = true;
console.error(`❌ 任务 ${task.id} 处理失败:`, error);
reject(new Error(error));
}
};
// 在流监听器中直接调用resolve
let checkAndFinalizeTaskStreams = () => {
console.log(`🔍 任务 ${task.id} 检查流完成状态: contentActive=${contentListenerActive}, thinkingActive=${thinkingListenerActive}`);
if (!contentListenerActive) {
console.log(`✅ 任务 ${task.id} 主内容流已完成，标记任务为完成状态`);
updateTask(task.id, {
status: 'completed',
currentFullContentForStream: fullContent,
currentThinkingContentForStream: fullThinkingContent,
});
resolveOnce();
}
if (!contentListenerActive && !thinkingListenerActive) {
console.log(`🎉 任务 ${task.id} 所有流式内容均已完成`);
}
};
// 设置超时
setTimeout(() => {
rejectOnce('任务处理超时');
}, 60000); // 60秒超时
});
} catch (error) {
console.error(`❌ 任务 ${task.id} 处理失败:`, error);
updateTask(task.id, {
status: 'error_ocr',
errorDetails: `处理失败: ${error}`,
});
throw error;
}
};
// 开始批量处理
const startBatchProcessing = async () => {
if (tasks.length === 0) {
alert('请先添加要分析的题目');
return;
}
const validTasks = tasks.filter(task =>
task.userQuestion.trim() && task.questionImages.length > 0 && task.status === 'pending'
);
if (validTasks.length === 0) {
alert('请确保每个任务都有问题描述和题目图片');
return;
}
setIsProcessing(true);
console.log(`🚀 开始批量处理 ${validTasks.length} 个任务`);
try {
// 严格按顺序处理队列中的任务
for (let i = 0; i < validTasks.length; i++) {
const task = validTasks[i];
setCurrentTaskIndex(i);
console.log(`📋 处理任务 ${i + 1}/${validTasks.length}: ${task.id}`);
try {
await processSingleTask(task);
console.log(`✅ 任务 ${task.id} 处理成功`);
} catch (error) {
console.error(`❌ 任务 ${task.id} 处理失败:`, error);
// 继续处理下一个任务
}
}
console.log('🎉 批量分析完成！');
alert('批量分析完成！');
} catch (error) {
console.error('❌ 批量处理失败:', error);
alert('批量处理失败: ' + error);
} finally {
setIsProcessing(false);
setCurrentTaskIndex(-1);
}
};
// 创建优化的文件上传点击处理器
const createFileUploadClickHandler = useCallback((taskId: string, isAnalysisImage = false) => {
return () => {
const inputId = isAnalysisImage ? `#analysis-input-${taskId}` : `#file-input-${taskId}`;
const fileInput = document.querySelector(inputId) as HTMLInputElement;
if (fileInput) {
fileInput.click();
}
};
}, []);
// 保存单个任务到错题库
const saveTaskToLibrary = async (taskToSave: BatchTask) => {
if (!taskToSave.temp_id) {
alert('任务数据不完整，无法保存');
return;
}
try {
updateTask(taskToSave.id, { status: 'saving' });
// 复制聊天历史，并将思维链内容保存到message中
const chatHistoryWithThinking = taskToSave.chatHistory.map((message, index) => {
if (message.role === 'assistant' && taskToSave.thinkingContent.has(index)) {
return {
...message,
thinking_content: taskToSave.thinkingContent.get(index)
};
}
return message;
});
const result = await TauriAPI.saveMistakeFromAnalysis({
temp_id: taskToSave.temp_id,
final_chat_history: chatHistoryWithThinking,
});
if (result.success) {
alert(`任务 ${taskToSave.id} 已保存到错题库！`);
// 可以选择从队列中移除已保存的任务
// removeTask(taskToSave.id);
} else {
alert('保存失败，请重试');
updateTask(taskToSave.id, { status: 'completed' });
}
} catch (error) {
console.error('保存失败:', error);
alert('保存失败: ' + error);
updateTask(taskToSave.id, { status: 'completed' });
}
};
// 为统一组件创建的适配器函数
const saveTaskToLibraryAdapter = async (saveData: any, chatImagesToSave?: any[]) => {
if (!selectedTaskForDetail) return;
// 从当前任务数据构造完整的 BatchTask
const currentTaskData = tasks.find(t => t.id === selectedTaskForDetail.id);
if (!currentTaskData) return;
const fullTaskData: BatchTask = {
...currentTaskData,
chatHistory: saveData.chatHistory || currentTaskData.chatHistory,
thinkingContent: saveData.thinkingContent || currentTaskData.thinkingContent,
// 如果有图片数据，可以在这里处理
};
await saveTaskToLibrary(fullTaskData);
};
// 保存所有有内容的任务到错题库
const saveAllToLibrary = async () => {
const savableTasks = tasks.filter(task => task.chatHistory.length > 0 || task.status === 'completed');
if (savableTasks.length === 0) {
alert('没有可保存的分析结果');
return;
}
if (!confirm(`确定要保存 ${savableTasks.length} 个任务到错题库吗？`)) {
return;
}
let successCount = 0;
let failCount = 0;
for (const task of savableTasks) {
try {
await saveTaskToLibrary(task);
successCount++;
} catch (error) {
console.error(`保存任务 ${task.id} 失败:`, error);
failCount++;
}
}
if (failCount === 0) {
alert(`已成功将 ${successCount} 道题目保存到错题库！`);
} else {
alert(`保存完成：成功 ${successCount} 道，失败 ${failCount} 道`);
}
};
// 清空所有任务
const clearAllTasks = () => {
if (confirm('确定要清空所有任务吗？')) {
setTasks([]);
saveTasksToStorage([]).catch(console.error);
}
};
// 处理聊天历史更新回调 - 添加防抖逻辑
const handleChatHistoryUpdated = useCallback((taskId: string, newChatHistory: ChatMessage[], newThinkingContent: Map<number, string>) => {
// 只在聊天历史真正有变化时才更新
setTasks(prevTasks => {
const taskIndex = prevTasks.findIndex(t => t.id === taskId);
if (taskIndex === -1) return prevTasks;
const currentTask = prevTasks[taskIndex];
// 检查是否真的有变化
if (currentTask.chatHistory.length === newChatHistory.length &&
currentTask.thinkingContent.size === newThinkingContent.size) {
return prevTasks; // 没有变化，不更新
}
const newTasks = [...prevTasks];
newTasks[taskIndex] = {
...currentTask,
chatHistory: newChatHistory,
thinkingContent: newThinkingContent,
};
return newTasks;
});
}, []);
// 为UniversalAppChatHost创建稳定的核心状态更新回调
const handleCoreStateUpdate = useCallback((taskId: string) => {
return (data: any) => {
// 实时更新聊天历史，确保批量分析详情页面能够实时渲染
if (data.chatHistory.length > 0) {
console.log('📝 BatchAnalysis: 实时状态更新', {
taskId,
chatHistoryLength: data.chatHistory.length,
lastMessageLength: data.chatHistory[data.chatHistory.length - 1]?.content?.length || 0
});
handleChatHistoryUpdated(taskId, data.chatHistory, data.thinkingContent);
}
};
}, [handleChatHistoryUpdated]);
const getStatusText = (status: string) => {
switch (status) {
case 'pending': return '等待中';
case 'ocr_processing': return 'OCR处理中';
case 'awaiting_stream_start': return '等待AI解答';
case 'streaming_answer': return 'AI解答中';
case 'completed': return '已完成';
case 'error_ocr': return 'OCR错误';
case 'error_stream': return '流式处理错误';
case 'saving': return '保存中';
default: return '未知状态';
}
};
const getStatusColor = (status: string) => {
switch (status) {
case 'pending': return '#6c757d';
case 'ocr_processing':
case 'awaiting_stream_start':
case 'streaming_answer': return '#007bff';
case 'completed': return '#28a745';
case 'error_ocr':
case 'error_stream': return '#dc3545';
case 'saving': return '#ffc107';
default: return '#6c757d';
}
};
// 如果显示详情页面，渲染详情视图
if (showDetailView && selectedTaskForDetail) {
// 获取实时的任务数据
const currentTaskData = tasks.find(t => t.id === selectedTaskForDetail.id) || selectedTaskForDetail;
return (
<div className="batch-detail-page">
<div className="detail-header">
<button
onClick={() => {
setShowDetailView(false);
setSelectedTaskForDetail(null);
}}
className="back-button"
>
← 返回批量分析
</button>
<h2>📋 任务详情 - #{tasks.findIndex(t => t.id === selectedTaskForDetail.id) + 1}</h2>
</div>
<div className="detail-content">
<UniversalAppChatHost
mode="EXISTING_BATCH_TASK_DETAIL"
businessSessionId={currentTaskData.id}
preloadedData={{
subject: currentTaskData.subject,
userQuestion: currentTaskData.userQuestion,
questionImages: currentTaskData.questionImages,
ocrText: currentTaskData.ocr_result?.ocr_text,
tags: currentTaskData.ocr_result?.tags || [],
chatHistory: currentTaskData.chatHistory || [],
thinkingContent: currentTaskData.thinkingContent || new Map()
}}
serviceConfig={{
apiProvider: {
initiateAndGetStreamId: async (params) => {
// 🎯 修复：检查原临时会话是否还存在，如果不存在则创建新的
let workingTempId = currentTaskData.temp_id;
if (workingTempId) {
try {
// 测试原临时会话是否还存在
await TauriAPI.continueChatStream({
temp_id: workingTempId,
chat_history: [],
enable_chain_of_thought: false
});
} catch (error) {
// 原临时会话不存在，需要重新创建
console.log('🔄 [批量分析] 原临时会话已失效，重新创建临时会话');
if (currentTaskData.questionImages && currentTaskData.questionImages.length > 0) {
const stepResult = await TauriAPI.analyzeStepByStep({
subject: currentTaskData.subject,
question_image_files: currentTaskData.questionImages,
analysis_image_files: currentTaskData.analysisImages || [],
user_question: currentTaskData.userQuestion,
enable_chain_of_thought: true,
});
workingTempId = stepResult.temp_id;
console.log('✅ [批量分析] 重新创建临时会话:', workingTempId);
}
}
}
return {
streamIdForEvents: workingTempId || params.businessId!,
ocrResultData: currentTaskData.ocr_result,
initialMessages: currentTaskData.chatHistory || []
};
},
startMainStreaming: async (params) => {
// 如果任务还在流式处理中，重新建立流监听
if (currentTaskData.status === 'streaming_answer' && currentTaskData.temp_id) {
console.log(`🔄 重新建立批量任务 ${currentTaskData.id} 的流监听`);
// 不需要调用API，只需要重新监听已经在进行的流
}
// 如果任务已完成，不需要做任何事情
},
continueUserChat: async (params) => {
// 🎯 修复：批量分析使用临时会话API，因为使用的是temp_id不是真实的错题ID
console.log('🔍 [批量分析追问] 调用参数:', {
streamIdForEvents: params.streamIdForEvents,
businessId: params.businessId,
currentTaskTempId: currentTaskData.temp_id,
chatHistoryLength: params.fullChatHistory.length
});
await TauriAPI.continueChatStream({
temp_id: params.streamIdForEvents, // 使用temp_id
chat_history: params.fullChatHistory,
enable_chain_of_thought: params.enableChainOfThought
});
}
},
streamEventNames: {
initialStream: (id) => ({
data: `analysis_stream_${id}`,
reasoning: `analysis_stream_${id}_reasoning`,
ragSources: `analysis_stream_${id}_rag_sources`
}),
continuationStream: (id) => ({
data: `continue_chat_stream_${id}`,
reasoning: `continue_chat_stream_${id}_reasoning`,
ragSources: `continue_chat_stream_${id}_rag_sources`
}),
},
defaultEnableChainOfThought: true,
defaultEnableRag: false,
defaultRagTopK: 5,
}}
onCoreStateUpdate={handleCoreStateUpdate(currentTaskData.id)}
onSaveRequest={async (data) => {
// 保存批量任务到错题库
await saveTaskToLibraryAdapter(data, []);
alert('批量任务已保存到错题库！');
}}
onExitRequest={() => {
setShowDetailView(false);
setSelectedTaskForDetail(null);
}}
/>
</div>
</div>
);
}
return (
<div className="batch-analysis">
<div className="batch-header">
<button onClick={onBack} className="back-button">
← 返回
</button>
<h2>📋 批量分析</h2>
<div className="batch-actions">
<button onClick={addTask} className="add-button">
➕ 添加题目
</button>
<button
onClick={startBatchProcessing}
disabled={isProcessing || tasks.length === 0}
className="process-button"
>
{isProcessing ? '处理中...' : '🚀 开始批量分析'}
</button>
</div>
</div>
{/* RAG设置面板 */}
<div className="rag-settings-panel" style={{
margin: '1rem 0',
padding: '1rem',
backgroundColor: '#f8f9fa',
borderRadius: '8px',
border: '1px solid #e9ecef'
}}>
<div style={{ display: 'flex', alignItems: 'center', gap: '0.5rem', marginBottom: '0.5rem' }}>
<span style={{ fontSize: '1.1rem' }}>🧠</span>
<label style={{ fontSize: '0.95rem', fontWeight: '500', margin: 0 }}>
RAG知识库增强（批量分析）
</label>
</div>
<label style={{ display: 'flex', alignItems: 'center', gap: '0.5rem', cursor: 'pointer' }}>
<input
type="checkbox"
checked={enableRag}
onChange={(e) => setEnableRag(e.target.checked)}
style={{ transform: 'scale(1.1)' }}
/>
<span style={{ fontSize: '0.9rem', color: '#495057' }}>
为所有任务启用知识库增强AI分析（需要先上传文档到知识库）
</span>
</label>
{enableRag && (
<div style={{
marginTop: '0.75rem',
paddingTop: '0.75rem',
borderTop: '1px solid #dee2e6'
}}>
<label style={{
display: 'flex',
alignItems: 'center',
gap: '0.5rem',
fontSize: '0.85rem',
color: '#6c757d'
}}>
检索文档数量:
<input
type="number"
min="1"
max="10"
value={ragTopK}
onChange={(e) => setRagTopK(parseInt(e.target.value) || 5)}
style={{
width: '60px',
padding: '0.25rem',
borderRadius: '4px',
border: '1px solid #ced4da',
fontSize: '0.85rem'
}}
/>
</label>
</div>
)}
{enableRag && (
<div style={{
marginTop: '0.5rem',
fontSize: '0.8rem',
color: '#6c757d',
fontStyle: 'italic'
}}>
💡 启用后，AI将从您的知识库中检索相关信息来增强分析准确性
</div>
)}
</div>
{isProcessing && (
<div className="progress-info">
<div className="progress-text">
正在处理第 {currentTaskIndex + 1} / {tasks.length} 道题目
</div>
<div className="progress-bar">
<div
className="progress-fill"
style={{ width: `${((currentTaskIndex + 1) / Math.max(tasks.length, 1)) * 100}%` }}
/>
</div>
</div>
)}
<div className="batch-content">
{tasks.length === 0 ? (
<div className="empty-batch">
<p>还没有添加任何题目</p>
<button onClick={addTask} className="add-first-button">
添加第一道题目
</button>
</div>
) : (
<>
<div className="batch-summary">
<div className="summary-item">
<span className="label">总题目数:</span>
<span className="value">{tasks.length}</span>
</div>
<div className="summary-item">
<span className="label">已完成:</span>
<span className="value">
{tasks.filter(t => t.status === 'completed').length}
</span>
</div>
<div className="summary-item">
<span className="label">处理中:</span>
<span className="value">
{tasks.filter(t => ['ocr_processing', 'awaiting_stream_start', 'streaming_answer'].includes(t.status)).length}
</span>
</div>
<div className="summary-item">
<span className="label">失败:</span>
<span className="value">
{tasks.filter(t => t.status.startsWith('error_')).length}
</span>
</div>
</div>
<div className="tasks-list">
{tasks.map((task, index) => (
<div key={task.id} className={`task-card ${currentTaskIndex === index ? 'current' : ''}`}>
<div className="task-header">
<span className="task-number">#{index + 1}</span>
<span
className="task-status"
style={{ color: getStatusColor(task.status) }}
>
{getStatusText(task.status)}
</span>
<div className="task-actions">
{(task.status !== 'pending' && task.temp_id) && (
<button
onClick={() => {
setSelectedTaskForDetail(task);
setShowDetailView(true);
}}
className="detail-button"
>
👁️ 查看详情
</button>
)}
{(task.chatHistory.length > 0 || task.status === 'completed') && (
<button
onClick={() => saveTaskToLibrary(task)}
className="save-button"
>
💾 保存
</button>
)}
<button
onClick={() => removeTask(task.id)}
disabled={isProcessing && task.status !== 'pending'}
className="remove-button"
>
✕
</button>
</div>
</div>
<div className="task-form">
<div className="form-row">
<div className="form-group">
<label>科目:</label>
<select
value={task.subject}
onChange={(e) => updateTask(task.id, { subject: e.target.value })}
disabled={isProcessing || task.status !== 'pending' || isLoadingSubjects}
>
{isLoadingSubjects ? (
<option value="">加载中...</option>
) : (
availableSubjects.map(subject => (
<option key={subject} value={subject}>{subject}</option>
))
)}
</select>
</div>
</div>
<div className="form-group">
<label>题目图片:</label>
<div
className="file-upload-area"
onClick={() => {
if (!(isProcessing || task.status !== 'pending')) {
createFileUploadClickHandler(task.id, false)();
}
}}
onDrop={(e) => {
e.preventDefault();
e.currentTarget.classList.remove('drag-over');
const files = Array.from(e.dataTransfer.files).filter(file => file.type.startsWith('image/'));
const remainingSlots = 9 - task.questionImages.length;
const filesToAdd = files.slice(0, remainingSlots);
if (filesToAdd.length > 0 && !(isProcessing || task.status !== 'pending')) {
handleImageUpload(task.id, filesToAdd);
}
}}
onDragOver={(e) => {
e.preventDefault();
if (!(isProcessing || task.status !== 'pending')) {
e.currentTarget.classList.add('drag-over');
}
}}
onDragEnter={(e) => {
e.preventDefault();
if (!(isProcessing || task.status !== 'pending')) {
e.currentTarget.classList.add('drag-over');
}
}}
onDragLeave={(e) => {
e.preventDefault();
if (!e.currentTarget.contains(e.relatedTarget as Node)) {
e.currentTarget.classList.remove('drag-over');
}
}}
>
<div className="upload-content">
<div className="upload-icon">📁</div>
<div className="upload-text">拖拽图片到此处或点击上传</div>
<input
id={`file-input-${task.id}`}
type="file"
multiple
accept="image/*"
onChange={(e) => handleImageUpload(task.id, e.target.files)}
disabled={isProcessing || task.status !== 'pending'}
className="file-input"
style={{ display: 'none' }}
/>
</div>
</div>
{task.questionImages.length > 0 && (
<div
className="image-grid-container"
onDrop={(e) => {
e.preventDefault();
e.currentTarget.classList.remove('drag-over');
const files = Array.from(e.dataTransfer.files).filter(file => file.type.startsWith('image/'));
const remainingSlots = 9 - task.questionImages.length;
const filesToAdd = files.slice(0, remainingSlots);
if (filesToAdd.length > 0 && !(isProcessing || task.status !== 'pending')) {
handleImageUpload(task.id, filesToAdd);
}
}}
onDragOver={(e) => {
e.preventDefault();
if (!(isProcessing || task.status !== 'pending')) {
e.currentTarget.classList.add('drag-over');
}
}}
onDragEnter={(e) => {
e.preventDefault();
if (!(isProcessing || task.status !== 'pending')) {
e.currentTarget.classList.add('drag-over');
}
}}
onDragLeave={(e) => {
e.preventDefault();
if (!e.currentTarget.contains(e.relatedTarget as Node)) {
e.currentTarget.classList.remove('drag-over');
}
}}
>
<div className="image-grid-scroll">
{task.questionImages.map((file, imgIndex) => {
const imageUrl = URL.createObjectURL(file);
return (
<div key={imgIndex} className="image-thumbnail-container">
<img
src={imageUrl}
alt={`题目图片 ${imgIndex + 1}`}
className="image-thumbnail"
onLoad={() => URL.revokeObjectURL(imageUrl)}
/>
<button
className="remove-image-btn tooltip-test"
onClick={() => removeImage(task.id, imgIndex)}
disabled={isProcessing || task.status !== 'pending'}
data-tooltip="删除图片"
>
✕
</button>
</div>
);
})}
{task.questionImages.length < 9 && !(isProcessing || task.status !== 'pending') && (
<div className="add-image-placeholder">
<input
type="file"
multiple
accept="image/*"
onChange={(e) => handleImageUpload(task.id, e.target.files)}
className="add-image-input"
id={`add-more-question-images-${task.id}`}
/>
<label htmlFor={`add-more-question-images-${task.id}`} className="add-image-label">
<div className="add-image-icon">➕</div>
<div className="add-image-text">添加图片</div>
</label>
</div>
)}
</div>
</div>
)}
</div>
<div className="form-group" style={{ display: 'none' }}>
<label>解析图片 (可选):</label>
<div
className="file-upload-area"
onClick={() => {
if (!(isProcessing || task.status !== 'pending')) {
createFileUploadClickHandler(task.id, true)();
}
}}
onDrop={(e) => {
e.preventDefault();
e.currentTarget.classList.remove('drag-over');
const files = Array.from(e.dataTransfer.files).filter(file => file.type.startsWith('image/'));
const remainingSlots = 9 - task.analysisImages.length;
const filesToAdd = files.slice(0, remainingSlots);
if (filesToAdd.length > 0 && !(isProcessing || task.status !== 'pending')) {
handleImageUpload(task.id, filesToAdd, true);
}
}}
onDragOver={(e) => {
e.preventDefault();
if (!(isProcessing || task.status !== 'pending')) {
e.currentTarget.classList.add('drag-over');
}
}}
onDragEnter={(e) => {
e.preventDefault();
if (!(isProcessing || task.status !== 'pending')) {
e.currentTarget.classList.add('drag-over');
}
}}
onDragLeave={(e) => {
e.preventDefault();
if (!e.currentTarget.contains(e.relatedTarget as Node)) {
e.currentTarget.classList.remove('drag-over');
}
}}
>
<div className="upload-content">
<div className="upload-icon">📁</div>
<div className="upload-text">拖拽解析图片到此处或点击上传</div>
<input
id={`analysis-input-${task.id}`}
type="file"
multiple
accept="image/*"
onChange={(e) => handleImageUpload(task.id, e.target.files, true)}
disabled={isProcessing || task.status !== 'pending'}
className="file-input"
style={{ display: 'none' }}
/>
</div>
</div>
{task.analysisImages.length > 0 && (
<div
className="image-grid-container"
onDrop={(e) => {
e.preventDefault();
e.currentTarget.classList.remove('drag-over');
const files = Array.from(e.dataTransfer.files).filter(file => file.type.startsWith('image/'));
const remainingSlots = 9 - task.analysisImages.length;
const filesToAdd = files.slice(0, remainingSlots);
if (filesToAdd.length > 0 && !(isProcessing || task.status !== 'pending')) {
handleImageUpload(task.id, filesToAdd, true);
}
}}
onDragOver={(e) => {
e.preventDefault();
if (!(isProcessing || task.status !== 'pending')) {
e.currentTarget.classList.add('drag-over');
}
}}
onDragEnter={(e) => {
e.preventDefault();
if (!(isProcessing || task.status !== 'pending')) {
e.currentTarget.classList.add('drag-over');
}
}}
onDragLeave={(e) => {
e.preventDefault();
if (!e.currentTarget.contains(e.relatedTarget as Node)) {
e.currentTarget.classList.remove('drag-over');
}
}}
>
<div className="image-grid-scroll">
{task.analysisImages.map((file, imgIndex) => {
const imageUrl = URL.createObjectURL(file);
return (
<div key={imgIndex} className="image-thumbnail-container">
<img
src={imageUrl}
alt={`解析图片 ${imgIndex + 1}`}
className="image-thumbnail"
onLoad={() => URL.revokeObjectURL(imageUrl)}
/>
<button
className="remove-image-btn tooltip-test"
onClick={() => removeImage(task.id, imgIndex, true)}
disabled={isProcessing || task.status !== 'pending'}
data-tooltip="删除图片"
>
✕
</button>
</div>
);
})}
{task.analysisImages.length < 9 && !(isProcessing || task.status !== 'pending') && (
<div className="add-image-placeholder">
<input
type="file"
multiple
accept="image/*"
onChange={(e) => handleImageUpload(task.id, e.target.files, true)}
className="add-image-input"
id={`add-more-analysis-images-${task.id}`}
/>
<label htmlFor={`add-more-analysis-images-${task.id}`} className="add-image-label">
<div className="add-image-icon">➕</div>
<div className="add-image-text">添加图片</div>
</label>
</div>
)}
</div>
</div>
)}
</div>
<div className="form-group">
<label>问题描述:</label>
<textarea
value={task.userQuestion}
onChange={(e) => updateTask(task.id, { userQuestion: e.target.value })}
placeholder="请描述你对这道题的疑问..."
disabled={isProcessing || task.status !== 'pending'}
rows={2}
/>
</div>
{/* 简化的状态显示 */}
{task.status.startsWith('error_') && (
<div className="task-error-simple">
<p>❌ 处理失败 - 点击查看详情了解错误信息</p>
</div>
)}
{task.status === 'streaming_answer' && (
<div className="task-streaming-simple">
<div className="streaming-indicator">
<span className="spinner">⏳</span>
<span>AI正在生成解答...</span>
</div>
</div>
)}
{task.status === 'completed' && (
<div className="task-completed-simple">
<p>✅ 分析完成 - 点击查看详情查看完整结果</p>
</div>
)}
</div>
</div>
))}
</div>
<div className="batch-footer">
<button onClick={clearAllTasks} className="clear-button">
🗑️ 清空所有
</button>
<button
onClick={saveAllToLibrary}
disabled={tasks.filter(t => t.chatHistory.length > 0 || t.status === 'completed').length === 0}
className="save-all-button"
>
💾 保存所有可用的题目
</button>
</div>
</>
)}
</div>
</div>
);
} | 55,570 | BatchAnalysis | tsx | en | tsx | code | {"qsc_code_num_words": 3990, "qsc_code_num_chars": 55570.0, "qsc_code_mean_word_length": 6.55112782, "qsc_code_frac_words_unique": 0.17994987, "qsc_code_frac_chars_top_2grams": 0.01882245, "qsc_code_frac_chars_top_3grams": 0.01009985, "qsc_code_frac_chars_top_4grams": 0.02551743, "qsc_code_frac_chars_dupe_5grams": 0.43880791, "qsc_code_frac_chars_dupe_6grams": 0.40051264, "qsc_code_frac_chars_dupe_7grams": 0.37457439, "qsc_code_frac_chars_dupe_8grams": 0.34389227, "qsc_code_frac_chars_dupe_9grams": 0.32426642, "qsc_code_frac_chars_dupe_10grams": 0.31340143, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.00640005, "qsc_code_frac_chars_whitespace": 0.40109771, "qsc_code_size_file_byte": 55570.0, "qsc_code_num_lines": 1480.0, "qsc_code_num_chars_line_max": 141.0, "qsc_code_num_chars_line_mean": 37.5472973, "qsc_code_frac_chars_alphabet": 0.77671945, "qsc_code_frac_chars_comments": 0.02436566, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.5024, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.05797075, "qsc_code_frac_chars_long_word_length": 0.00684287, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0} |
000haoji/deep-student | src/components/TagManagement.css | .tag-management-container {
padding: 20px;
background: #f8f9fa;
border-radius: 12px;
box-shadow: 0 2px 8px rgba(0,0,0,0.1);
}
.tag-management-header {
display: flex;
justify-content: space-between;
align-items: center;
margin-bottom: 20px;
padding-bottom: 15px;
border-bottom: 2px solid #3498db;
}
.tag-management-header h3 {
margin: 0;
color: #2c3e50;
font-size: 1.4em;
}
.header-actions {
display: flex;
gap: 10px;
}
.create-tag-btn,
.init-hierarchy-btn {
padding: 10px 16px;
border: none;
border-radius: 8px;
font-size: 14px;
font-weight: 600;
cursor: pointer;
transition: all 0.2s ease;
}
.create-tag-btn {
background: #27ae60;
color: white;
}
.create-tag-btn:hover:not(:disabled) {
background: #219a52;
transform: translateY(-1px);
}
.init-hierarchy-btn {
background: #3498db;
color: white;
}
.init-hierarchy-btn:hover:not(:disabled) {
background: #2980b9;
transform: translateY(-1px);
}
.create-tag-btn:disabled,
.init-hierarchy-btn:disabled {
background: #bdc3c7;
cursor: not-allowed;
transform: none;
}
.error-message {
background: #fee;
border: 1px solid #fcc;
border-radius: 8px;
padding: 12px;
margin-bottom: 20px;
color: #c33;
font-weight: 500;
display: flex;
justify-content: space-between;
align-items: center;
}
.error-message button {
background: none;
border: none;
color: #c33;
font-size: 16px;
cursor: pointer;
padding: 0;
margin-left: 10px;
}
.create-tag-form {
background: white;
border-radius: 12px;
padding: 20px;
margin-bottom: 20px;
box-shadow: 0 2px 8px rgba(0,0,0,0.1);
}
.create-tag-form h4 {
margin: 0 0 20px 0;
color: #2c3e50;
border-bottom: 2px solid #27ae60;
padding-bottom: 10px;
}
.form-group {
margin-bottom: 15px;
}
.form-group label {
display: block;
margin-bottom: 5px;
font-weight: 600;
color: #2c3e50;
}
.form-group input,
.form-group select,
.form-group textarea {
width: 100%;
padding: 10px 12px;
border: 1px solid #bdc3c7;
border-radius: 6px;
font-size: 14px;
color: #2c3e50;
background: white;
box-sizing: border-box;
}
.form-group input:focus,
.form-group select:focus,
.form-group textarea:focus {
outline: none;
border-color: #3498db;
box-shadow: 0 0 0 2px rgba(52, 152, 219, 0.2);
}
.form-group textarea {
resize: vertical;
font-family: inherit;
}
.form-actions {
display: flex;
gap: 10px;
justify-content: flex-end;
margin-top: 20px;
}
.form-actions button {
padding: 10px 20px;
border: none;
border-radius: 6px;
font-size: 14px;
font-weight: 600;
cursor: pointer;
transition: all 0.2s ease;
}
.form-actions button:first-child {
background: #27ae60;
color: white;
}
.form-actions button:first-child:hover:not(:disabled) {
background: #219a52;
}
.form-actions button:last-child {
background: #e74c3c;
color: white;
}
.form-actions button:last-child:hover:not(:disabled) {
background: #c0392b;
}
.form-actions button:disabled {
background: #bdc3c7;
cursor: not-allowed;
}
.tag-content {
display: grid;
grid-template-columns: 1fr 1fr;
gap: 20px;
}
.tag-list-section,
.tag-hierarchy-section {
background: white;
border-radius: 12px;
padding: 20px;
box-shadow: 0 2px 8px rgba(0,0,0,0.1);
}
.section-header {
display: flex;
justify-content: space-between;
align-items: center;
margin-bottom: 15px;
padding-bottom: 10px;
border-bottom: 2px solid #3498db;
}
.section-header h4 {
margin: 0;
color: #2c3e50;
}
.filter-controls {
display: flex;
align-items: center;
gap: 8px;
}
.filter-controls label {
font-size: 14px;
color: #7f8c8d;
}
.filter-controls select {
padding: 6px 10px;
border: 1px solid #bdc3c7;
border-radius: 4px;
font-size: 14px;
}
.loading {
text-align: center;
padding: 40px;
color: #7f8c8d;
font-style: italic;
}
.tag-list {
max-height: 400px;
overflow-y: auto;
}
.tag-item {
border: 1px solid #ecf0f1;
border-radius: 8px;
padding: 15px;
margin-bottom: 10px;
transition: all 0.2s ease;
}
.tag-item:hover {
border-color: #3498db;
box-shadow: 0 2px 8px rgba(52, 152, 219, 0.1);
}
.tag-header {
display: flex;
align-items: center;
gap: 10px;
margin-bottom: 8px;
}
.tag-type {
padding: 4px 8px;
border-radius: 4px;
font-size: 12px;
font-weight: 600;
text-transform: uppercase;
}
.tag-type.knowledgearea {
background: #3498db;
color: white;
}
.tag-type.topic {
background: #9b59b6;
color: white;
}
.tag-type.concept {
background: #27ae60;
color: white;
}
.tag-type.method {
background: #f39c12;
color: white;
}
.tag-type.difficulty {
background: #e74c3c;
color: white;
}
.tag-name {
font-weight: 600;
color: #2c3e50;
flex: 1;
}
.tag-level {
background: #ecf0f1;
color: #7f8c8d;
padding: 2px 6px;
border-radius: 3px;
font-size: 12px;
}
.tag-description {
color: #7f8c8d;
font-size: 14px;
margin-bottom: 8px;
line-height: 1.4;
}
.tag-meta {
font-size: 12px;
color: #95a5a6;
}
.no-tags,
.no-hierarchy {
text-align: center;
padding: 40px;
color: #7f8c8d;
font-style: italic;
}
.hierarchy-tree {
max-height: 400px;
overflow-y: auto;
}
.tag-node {
border-left: 3px solid #3498db;
margin-bottom: 10px;
padding: 10px 15px;
background: #f8f9fa;
border-radius: 0 8px 8px 0;
}
.tag-node.level-0 {
border-left-color: #3498db;
background: #ebf3fd;
}
.tag-node.level-1 {
border-left-color: #9b59b6;
background: #f4f1f8;
margin-left: 20px;
}
.tag-node.level-2 {
border-left-color: #27ae60;
background: #eef7f0;
margin-left: 40px;
}
.tag-node.level-3 {
border-left-color: #f39c12;
background: #fdf6e3;
margin-left: 60px;
}
.tag-children {
margin-top: 10px;
}
.not-initialized {
display: flex;
align-items: center;
justify-content: center;
height: 300px;
background: white;
border-radius: 8px;
color: #7f8c8d;
font-size: 16px;
}
/* Responsive design */
@media (max-width: 1024px) {
.tag-content {
grid-template-columns: 1fr;
}
}
@media (max-width: 768px) {
.tag-management-header {
flex-direction: column;
gap: 15px;
align-items: stretch;
}
.header-actions {
justify-content: center;
}
.section-header {
flex-direction: column;
gap: 10px;
align-items: stretch;
}
.filter-controls {
justify-content: center;
}
.tag-node.level-1 {
margin-left: 10px;
}
.tag-node.level-2 {
margin-left: 20px;
}
.tag-node.level-3 {
margin-left: 30px;
}
} | 6,519 | TagManagement | css | en | css | data | {"qsc_code_num_words": 851, "qsc_code_num_chars": 6519.0, "qsc_code_mean_word_length": 5.00822562, "qsc_code_frac_words_unique": 0.19741481, "qsc_code_frac_chars_top_2grams": 0.03660253, "qsc_code_frac_chars_top_3grams": 0.00492726, "qsc_code_frac_chars_top_4grams": 0.01220084, "qsc_code_frac_chars_dupe_5grams": 0.36250587, "qsc_code_frac_chars_dupe_6grams": 0.23181605, "qsc_code_frac_chars_dupe_7grams": 0.14969498, "qsc_code_frac_chars_dupe_8grams": 0.11684655, "qsc_code_frac_chars_dupe_9grams": 0.11684655, "qsc_code_frac_chars_dupe_10grams": 0.10441107, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.08160548, "qsc_code_frac_chars_whitespace": 0.19358797, "qsc_code_size_file_byte": 6519.0, "qsc_code_num_lines": 416.0, "qsc_code_num_chars_line_max": 56.0, "qsc_code_num_chars_line_mean": 15.67067308, "qsc_code_frac_chars_alphabet": 0.72912307, "qsc_code_frac_chars_comments": 0.0, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.47443182, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.0, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0} | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 1, "qsc_code_mean_word_length": 0, "qsc_code_frac_words_unique": 1, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0} |
000haoji/deep-student | src/components/ReviewAnalysisDashboard.tsx | import React, { useState, useEffect } from 'react';
import { ReviewSessionTask } from '../types/index';
import { useNotification } from '../hooks/useNotification';
import { TauriAPI, ReviewAnalysisItem } from '../utils/tauriApi';
import { useSubject } from '../contexts/SubjectContext';
import { UnifiedSubjectSelector } from './shared/UnifiedSubjectSelector';
import './ReviewAnalysis.css';
interface ReviewAnalysisDashboardProps {
onCreateNew: () => void;
onViewSession: (sessionId: string) => void;
}
const ReviewAnalysisDashboard: React.FC<ReviewAnalysisDashboardProps> = ({
onCreateNew,
onViewSession,
}) => {
const [reviewSessions, setReviewSessions] = useState<ReviewAnalysisItem[]>([]);
const [loading, setLoading] = useState(true);
const [filter, setFilter] = useState<{
status: string;
searchTerm: string;
}>({
status: '',
searchTerm: '',
});
const [statusDropdownOpen, setStatusDropdownOpen] = useState(false);
const statusOptions = [
{ value: '', label: '全部状态' },
{ value: 'pending', label: '待处理' },
{ value: 'processing_setup', label: '设置中' },
{ value: 'streaming_answer', label: '分析中' },
{ value: 'completed', label: '已完成' },
{ value: 'error_setup', label: '设置错误' },
{ value: 'error_stream', label: '分析错误' }
];
const { showNotification } = useNotification();
const { currentSubject } = useSubject();
// 从现有数据中提取可用的科目选项
const availableSubjects = Array.from(new Set(reviewSessions.map(session => session.subject).filter(Boolean)));
useEffect(() => {
loadReviewSessions();
}, []);
// 处理点击外部关闭下拉框
useEffect(() => {
const handleClickOutside = (event: MouseEvent) => {
if (statusDropdownOpen) {
const target = event.target as Node;
const dropdown = document.querySelector('.status-dropdown-container');
if (dropdown && !dropdown.contains(target)) {
setStatusDropdownOpen(false);
}
}
};
document.addEventListener('mousedown', handleClickOutside);
return () => {
document.removeEventListener('mousedown', handleClickOutside);
};
}, [statusDropdownOpen]);
const loadReviewSessions = async () => {
try {
setLoading(true);
// 从数据库加载回顾分析会话列表（复用错题分析的模式）
const sessions = await TauriAPI.getReviewAnalyses();
setReviewSessions(sessions);
console.log('✅ 从数据库加载回顾分析列表成功:', sessions.length);
// 验证错题数量是否正确加载
sessions.forEach(s => {
console.log(`📊 回顾分析 "${s.name}" 包含 ${s.mistake_ids?.length || 0} 个错题`);
});
} catch (error) {
console.error('加载回顾分析会话失败:', error);
showNotification('error', '加载回顾分析会话失败');
setReviewSessions([]);
} finally {
setLoading(false);
}
};
const handleDeleteSession = async (sessionId: string) => {
if (!confirm('确定要删除这个回顾分析会话吗？')) {
return;
}
try {
console.log('🗑️ 开始删除回顾分析:', sessionId);
const deleted = await TauriAPI.deleteReviewAnalysis(sessionId);
if (deleted) {
showNotification('success', '回顾分析删除成功');
// 重新加载列表以反映删除操作
await loadReviewSessions();
} else {
showNotification('warning', '回顾分析不存在或已被删除');
// 即使删除失败，也刷新列表以确保数据一致性
await loadReviewSessions();
}
} catch (error) {
console.error('❌ 删除回顾分析失败:', error);
showNotification('error', `删除回顾分析失败: ${error.message || error}`);
}
};
const filteredSessions = reviewSessions.filter(session => {
const matchesSubject = !currentSubject || currentSubject === '全部' || session.subject === currentSubject;
const matchesStatus = !filter.status || session.status === filter.status;
const matchesSearch = !filter.searchTerm ||
session.name.toLowerCase().includes(filter.searchTerm.toLowerCase()) ||
session.user_question.toLowerCase().includes(filter.searchTerm.toLowerCase()) ||
session.consolidated_input.toLowerCase().includes(filter.searchTerm.toLowerCase());
return matchesSubject && matchesStatus && matchesSearch;
});
const getStatusDisplay = (status: string) => {
const statusMap: Record<string, { text: string; style: any }> = {
pending: { text: '待处理', style: { backgroundColor: '#fef3c7', color: '#92400e', padding: '4px 8px', borderRadius: '12px', fontSize: '12px', fontWeight: '500' } },
processing_setup: { text: '设置中', style: { backgroundColor: '#dbeafe', color: '#1e40af', padding: '4px 8px', borderRadius: '12px', fontSize: '12px', fontWeight: '500' } },
awaiting_stream_start: { text: '等待分析', style: { backgroundColor: '#dbeafe', color: '#1e40af', padding: '4px 8px', borderRadius: '12px', fontSize: '12px', fontWeight: '500' } },
streaming_answer: { text: '分析中', style: { backgroundColor: '#dbeafe', color: '#1e40af', padding: '4px 8px', borderRadius: '12px', fontSize: '12px', fontWeight: '500' } },
completed: { text: '已完成', style: { backgroundColor: '#dcfce7', color: '#166534', padding: '4px 8px', borderRadius: '12px', fontSize: '12px', fontWeight: '500' } },
error_setup: { text: '设置错误', style: { backgroundColor: '#fee2e2', color: '#991b1b', padding: '4px 8px', borderRadius: '12px', fontSize: '12px', fontWeight: '500' } },
error_stream: { text: '分析错误', style: { backgroundColor: '#fee2e2', color: '#991b1b', padding: '4px 8px', borderRadius: '12px', fontSize: '12px', fontWeight: '500' } },
};
return statusMap[status] || { text: status, style: { backgroundColor: '#f3f4f6', color: '#374151', padding: '4px 8px', borderRadius: '12px', fontSize: '12px', fontWeight: '500' } };
};
if (loading) {
return (
<div className="review-loading">
<div className="review-loading-spinner"></div>
<span className="review-loading-text">加载中...</span>
</div>
);
}
return (
<div style={{
width: '100%',
height: '100%',
overflow: 'auto',
background: '#f8fafc'
}}>
{/* 头部区域 - 统一白色样式 */}
<div style={{
background: 'white',
borderBottom: '1px solid #e5e7eb',
padding: '24px 32px',
position: 'relative'
}}>
<div style={{
position: 'absolute',
top: 0,
left: 0,
right: 0,
height: '4px',
background: 'linear-gradient(90deg, #667eea, #764ba2)'
}}></div>
<div style={{ position: 'relative', zIndex: 1 }}>
<div style={{ display: 'flex', alignItems: 'center', marginBottom: '8px' }}>
<svg style={{ width: '32px', height: '32px', marginRight: '12px', color: '#667eea' }} fill="none" stroke="currentColor" viewBox="0 0 24 24" strokeWidth={2}>
<circle cx="12" cy="12" r="10" />
<circle cx="12" cy="12" r="6" />
<circle cx="12" cy="12" r="2" />
</svg>
<h1 style={{ fontSize: '28px', fontWeight: '700', margin: 0, color: '#1f2937' }}>统一回顾分析</h1>
</div>
<p style={{ fontSize: '16px', color: '#6b7280', margin: 0, lineHeight: '1.5' }}>
对多个错题进行统一深度分析，发现学习模式，制定改进计划
</p>
<div style={{ marginTop: '24px' }}>
<button
onClick={onCreateNew}
style={{
background: '#667eea',
border: '1px solid #667eea',
color: 'white',
padding: '12px 24px',
borderRadius: '12px',
fontSize: '16px',
fontWeight: '600',
cursor: 'pointer',
display: 'inline-flex',
alignItems: 'center',
gap: '8px',
transition: 'all 0.3s ease'
}}
onMouseOver={(e) => {
e.currentTarget.style.background = '#5a67d8';
e.currentTarget.style.transform = 'translateY(-2px)';
e.currentTarget.style.boxShadow = '0 8px 25px rgba(102, 126, 234, 0.3)';
}}
onMouseOut={(e) => {
e.currentTarget.style.background = '#667eea';
e.currentTarget.style.transform = 'translateY(0)';
e.currentTarget.style.boxShadow = 'none';
}}
>
<svg style={{ width: '20px', height: '20px' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M12 4v16m8-8H4" />
</svg>
创建新的回顾分析
</button>
</div>
</div>
</div>
{/* 筛选器 - 重新设计 */}
<div style={{
background: 'white',
margin: '0 24px 24px 24px',
borderRadius: '16px',
padding: '24px',
boxShadow: '0 4px 20px rgba(0, 0, 0, 0.05)',
border: '1px solid #f1f5f9'
}}>
<div style={{
display: 'grid',
gridTemplateColumns: 'repeat(auto-fit, minmax(200px, 1fr))',
gap: '20px',
alignItems: 'end'
}}>
{/* 科目筛选现在由全局状态控制 */}
<div>
<label style={{
display: 'block',
fontSize: '14px',
fontWeight: '600',
color: '#374151',
marginBottom: '8px'
}}>状态筛选</label>
{/* 自定义状态下拉框 - 保持原生样式外观 + 自定义下拉列表 */}
<div className="status-dropdown-container" style={{ position: 'relative' }}>
<div
style={{
width: '100%',
padding: '12px 16px',
border: '2px solid #e2e8f0',
borderRadius: '12px',
fontSize: '14px',
background: 'white',
cursor: 'pointer',
transition: 'all 0.2s ease',
display: 'flex',
justifyContent: 'space-between',
alignItems: 'center',
minHeight: '20px'
}}
onClick={() => setStatusDropdownOpen(!statusDropdownOpen)}
onMouseOver={(e) => {
if (!statusDropdownOpen) {
e.currentTarget.style.borderColor = '#667eea';
}
}}
onMouseOut={(e) => {
if (!statusDropdownOpen) {
e.currentTarget.style.borderColor = '#e2e8f0';
}
}}
>
<span style={{ color: '#374151' }}>
{filter.status ? statusOptions.find(opt => opt.value === filter.status)?.label : '全部状态'}
</span>
<span style={{
transform: statusDropdownOpen ? 'rotate(180deg)' : 'rotate(0deg)',
transition: 'transform 0.2s ease',
color: '#6b7280',
fontSize: '12px'
}}>▼</span>
</div>
{statusDropdownOpen && (
<div style={{
position: 'absolute',
top: '100%',
left: 0,
right: 0,
backgroundColor: '#fff',
borderRadius: '12px',
border: '1px solid #e0e0e0',
marginTop: '8px',
boxShadow: '0 6px 16px rgba(0,0,0,0.12)',
zIndex: 9999,
overflow: 'hidden',
maxHeight: '300px',
overflowY: 'auto'
}}>
{statusOptions.map((option, index) => (
<div
key={option.value}
style={{
padding: '12px 16px',
cursor: 'pointer',
color: '#333',
fontSize: '14px',
borderBottom: index < statusOptions.length - 1 ? '1px solid #f0f0f0' : 'none',
backgroundColor: filter.status === option.value ? '#f0f7ff' : 'transparent',
transition: 'all 0.2s ease',
minHeight: '44px',
display: 'flex',
alignItems: 'center'
}}
onClick={() => {
setFilter(prev => ({ ...prev, status: option.value }));
setStatusDropdownOpen(false);
}}
onMouseOver={(e) => {
if (filter.status !== option.value) {
e.currentTarget.style.backgroundColor = '#f7f7f7';
}
}}
onMouseOut={(e) => {
if (filter.status !== option.value) {
e.currentTarget.style.backgroundColor = 'transparent';
}
}}
>
{option.label}
</div>
))}
</div>
)}
</div>
</div>
<div style={{ gridColumn: 'span 2' }}>
<label style={{
display: 'block',
fontSize: '14px',
fontWeight: '600',
color: '#374151',
marginBottom: '8px'
}}>搜索</label>
<div style={{ position: 'relative' }}>
<svg style={{
position: 'absolute',
left: '16px',
top: '50%',
transform: 'translateY(-50%)',
width: '18px',
height: '18px',
color: '#9ca3af'
}} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M21 21l-6-6m2-5a7 7 0 11-14 0 7 7 0 0114 0z" />
</svg>
<input
type="text"
placeholder="搜索回顾分析名称或问题..."
value={filter.searchTerm}
onChange={(e) => setFilter(prev => ({ ...prev, searchTerm: e.target.value }))}
style={{
width: '100%',
padding: '12px 16px 12px 48px',
border: '2px solid #e2e8f0',
borderRadius: '12px',
fontSize: '14px',
transition: 'all 0.2s ease'
}}
onFocus={(e) => e.target.style.borderColor = '#667eea'}
onBlur={(e) => e.target.style.borderColor = '#e2e8f0'}
/>
</div>
</div>
</div>
</div>
{/* 会话列表 */}
{filteredSessions.length === 0 ? (
<div style={{
textAlign: 'center',
padding: '80px 24px',
background: 'white',
margin: '0 24px',
borderRadius: '16px',
boxShadow: '0 4px 20px rgba(0, 0, 0, 0.05)',
border: '1px solid #f1f5f9'
}}>
<div style={{
width: '80px',
height: '80px',
background: 'linear-gradient(135deg, #667eea 0%, #764ba2 100%)',
borderRadius: '50%',
display: 'flex',
alignItems: 'center',
justifyContent: 'center',
margin: '0 auto 24px',
opacity: 0.8
}}>
<svg style={{ width: '40px', height: '40px', color: 'white' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M9 12h6m-6 4h6m2 5H7a2 2 0 01-2-2V5a2 2 0 012-2h5.586a1 1 0 01.707.293l5.414 5.414a1 1 0 01.293.707V19a2 2 0 01-2 2z" />
</svg>
</div>
<h3 style={{
fontSize: '20px',
fontWeight: '600',
color: '#1F2937',
marginBottom: '12px',
margin: 0
}}>
{reviewSessions.length === 0 ? '开始您的第一个回顾分析' : '未找到匹配的分析'}
</h3>
<p style={{
fontSize: '16px',
color: '#6B7280',
lineHeight: '1.6',
marginBottom: '32px',
maxWidth: '400px',
margin: '0 auto 32px'
}}>
{reviewSessions.length === 0
? '创建回顾分析来深度分析多个错题，发现学习模式，制定改进计划'
: '尝试调整筛选条件或搜索关键词'}
</p>
{reviewSessions.length === 0 && (
<button
onClick={onCreateNew}
style={{
background: 'linear-gradient(135deg, #667eea 0%, #764ba2 100%)',
color: 'white',
border: 'none',
padding: '16px 32px',
borderRadius: '12px',
fontSize: '16px',
fontWeight: '600',
cursor: 'pointer',
display: 'inline-flex',
alignItems: 'center',
gap: '8px',
transition: 'all 0.3s ease',
boxShadow: '0 4px 15px rgba(102, 126, 234, 0.3)'
}}
onMouseOver={(e) => {
e.currentTarget.style.transform = 'translateY(-2px)';
e.currentTarget.style.boxShadow = '0 8px 25px rgba(102, 126, 234, 0.4)';
}}
onMouseOut={(e) => {
e.currentTarget.style.transform = 'translateY(0)';
e.currentTarget.style.boxShadow = '0 4px 15px rgba(102, 126, 234, 0.3)';
}}
>
<svg style={{ width: '20px', height: '20px' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M12 4v16m8-8H4" />
</svg>
立即创建回顾分析
</button>
)}
</div>
) : (
<div style={{
display: 'grid',
gap: '20px',
margin: '0 24px 24px 24px'
}}>
{filteredSessions.map((session) => {
const statusInfo = getStatusDisplay(session.status);
return (
<div
key={session.id}
style={{
background: 'white',
borderRadius: '16px',
boxShadow: '0 4px 20px rgba(0, 0, 0, 0.05)',
border: '1px solid #f1f5f9',
transition: 'all 0.3s ease',
cursor: 'pointer',
position: 'relative',
overflow: 'hidden'
}}
onMouseOver={(e) => {
e.currentTarget.style.transform = 'translateY(-2px)';
e.currentTarget.style.boxShadow = '0 8px 30px rgba(0, 0, 0, 0.12)';
}}
onMouseOut={(e) => {
e.currentTarget.style.transform = 'translateY(0)';
e.currentTarget.style.boxShadow = '0 4px 20px rgba(0, 0, 0, 0.05)';
}}
>
{/* 顶部装饰条 */}
<div style={{
height: '4px',
background: 'linear-gradient(135deg, #667eea 0%, #764ba2 100%)',
width: '100%'
}}></div>
<div style={{ padding: '28px' }}>
<div style={{ display: 'flex', justifyContent: 'space-between', alignItems: 'flex-start' }}>
<div style={{ flex: 1 }}>
{/* 标题和状态 */}
<div style={{ display: 'flex', alignItems: 'center', marginBottom: '16px' }}>
<div style={{
width: '12px',
height: '12px',
background: 'linear-gradient(135deg, #667eea 0%, #764ba2 100%)',
borderRadius: '50%',
marginRight: '12px'
}}></div>
<h3 style={{
fontSize: '20px',
fontWeight: '700',
color: '#1F2937',
margin: 0,
marginRight: '16px',
lineHeight: '1.2'
}}>
{session.name}
</h3>
<span style={statusInfo.style}>
{statusInfo.text}
</span>
</div>
{/* 元信息 */}
<div style={{
display: 'grid',
gridTemplateColumns: 'repeat(auto-fit, minmax(140px, 1fr))',
gap: '20px',
marginBottom: '20px',
padding: '16px',
background: '#f8fafc',
borderRadius: '12px',
border: '1px solid #f1f5f9'
}}>
<div style={{ display: 'flex', alignItems: 'center', gap: '8px' }}>
<svg style={{ width: '16px', height: '16px', color: '#667eea' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M12 6.253v13m0-13C10.832 5.477 9.246 5 7.5 5S4.168 5.477 3 6.253v13C4.168 18.477 5.754 18 7.5 18s3.332.477 4.5 1.253m0-13C13.168 5.477 14.754 5 16.5 5c1.746 0 3.332.477 4.5 1.253v13C19.832 18.477 18.246 18 16.5 18c-1.746 0-3.332.477-4.5 1.253" />
</svg>
<div>
<div style={{ fontSize: '12px', color: '#6B7280', fontWeight: '500' }}>科目</div>
<div style={{ fontSize: '14px', color: '#1F2937', fontWeight: '600' }}>{session.subject}</div>
</div>
</div>
<div style={{ display: 'flex', alignItems: 'center', gap: '8px' }}>
<svg style={{ width: '16px', height: '16px', color: '#667eea' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M9 12h6m-6 4h6m2 5H7a2 2 0 01-2-2V5a2 2 0 012-2h5.586a1 1 0 01.707.293l5.414 5.414a1 1 0 01.293.707V19a2 2 0 01-2 2z" />
</svg>
<div>
<div style={{ fontSize: '12px', color: '#6B7280', fontWeight: '500' }}>错题数量</div>
<div style={{ fontSize: '14px', color: '#1F2937', fontWeight: '600' }}>{session.mistake_ids.length} 个</div>
</div>
</div>
<div style={{ display: 'flex', alignItems: 'center', gap: '8px' }}>
<svg style={{ width: '16px', height: '16px', color: '#667eea' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M8 7V3m8 4V3m-9 8h10M5 21h14a2 2 0 002-2V7a2 2 0 00-2-2H5a2 2 0 00-2 2v12a2 2 0 002 2z" />
</svg>
<div>
<div style={{ fontSize: '12px', color: '#6B7280', fontWeight: '500' }}>创建时间</div>
<div style={{ fontSize: '14px', color: '#1F2937', fontWeight: '600' }}>{new Date(session.created_at).toLocaleDateString()}</div>
</div>
</div>
</div>
{/* 描述 */}
<div style={{
padding: '16px',
background: 'rgba(102, 126, 234, 0.05)',
borderRadius: '12px',
borderLeft: '4px solid #667eea'
}}>
<div style={{ fontSize: '12px', color: '#667eea', fontWeight: '600', marginBottom: '4px' }}>分析指引</div>
<p style={{
color: '#374151',
lineHeight: '1.6',
fontSize: '14px',
margin: 0,
overflow: 'hidden',
display: '-webkit-box',
WebkitLineClamp: 2,
WebkitBoxOrient: 'vertical'
}}>
{session.user_question}
</p>
</div>
</div>
{/* 操作按钮 */}
<div style={{
display: 'flex',
flexDirection: 'column',
gap: '12px',
marginLeft: '24px',
minWidth: '120px'
}}>
<button
onClick={(e) => {
e.stopPropagation();
onViewSession(session.id);
}}
style={{
background: 'linear-gradient(135deg, #667eea 0%, #764ba2 100%)',
color: 'white',
border: 'none',
padding: '12px 20px',
borderRadius: '10px',
fontSize: '14px',
fontWeight: '600',
cursor: 'pointer',
transition: 'all 0.2s ease',
boxShadow: '0 2px 8px rgba(102, 126, 234, 0.2)'
}}
onMouseOver={(e) => {
e.currentTarget.style.transform = 'translateY(-1px)';
e.currentTarget.style.boxShadow = '0 4px 15px rgba(102, 126, 234, 0.3)';
}}
onMouseOut={(e) => {
e.currentTarget.style.transform = 'translateY(0)';
e.currentTarget.style.boxShadow = '0 2px 8px rgba(102, 126, 234, 0.2)';
}}
>
<svg style={{ width: '14px', height: '14px', marginRight: '6px' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M15 12a3 3 0 11-6 0 3 3 0 016 0z" />
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M2.458 12C3.732 7.943 7.523 5 12 5c4.478 0 8.268 2.943 9.542 7-1.274 4.057-5.064 7-9.542 7-4.477 0-8.268-2.943-9.542-7z" />
</svg>
查看详情
</button>
<button
onClick={(e) => {
e.stopPropagation();
handleDeleteSession(session.id);
}}
style={{
background: '#ffffff',
color: '#ef4444',
border: '2px solid #fee2e2',
padding: '10px 20px',
borderRadius: '10px',
fontSize: '14px',
fontWeight: '600',
cursor: 'pointer',
transition: 'all 0.2s ease'
}}
onMouseOver={(e) => {
e.currentTarget.style.background = '#fef2f2';
e.currentTarget.style.borderColor = '#fecaca';
e.currentTarget.style.transform = 'translateY(-1px)';
}}
onMouseOut={(e) => {
e.currentTarget.style.background = '#ffffff';
e.currentTarget.style.borderColor = '#fee2e2';
e.currentTarget.style.transform = 'translateY(0)';
}}
>
<svg style={{ width: '14px', height: '14px', marginRight: '6px' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M19 7l-.867 12.142A2 2 0 0116.138 21H7.862a2 2 0 01-1.995-1.858L5 7m5 4v6m4-6v6m1-10V4a1 1 0 00-1-1h-4a1 1 0 00-1 1v3M4 7h16" />
</svg>
删除
</button>
</div>
</div>
</div>
</div>
);
})}
</div>
)}
</div>
);
};
export default ReviewAnalysisDashboard; | 28,833 | ReviewAnalysisDashboard | tsx | en | tsx | code | {"qsc_code_num_words": 2351, "qsc_code_num_chars": 28833.0, "qsc_code_mean_word_length": 5.48149724, "qsc_code_frac_words_unique": 0.20842195, "qsc_code_frac_chars_top_2grams": 0.02110654, "qsc_code_frac_chars_top_3grams": 0.04128191, "qsc_code_frac_chars_top_4grams": 0.02017537, "qsc_code_frac_chars_dupe_5grams": 0.48219136, "qsc_code_frac_chars_dupe_6grams": 0.43687437, "qsc_code_frac_chars_dupe_7grams": 0.39241096, "qsc_code_frac_chars_dupe_8grams": 0.36082874, "qsc_code_frac_chars_dupe_9grams": 0.34344688, "qsc_code_frac_chars_dupe_10grams": 0.32319392, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.09365969, "qsc_code_frac_chars_whitespace": 0.41195852, "qsc_code_size_file_byte": 28833.0, "qsc_code_num_lines": 672.0, "qsc_code_num_chars_line_max": 345.0, "qsc_code_num_chars_line_mean": 42.90625, "qsc_code_frac_chars_alphabet": 0.66605721, "qsc_code_frac_chars_comments": 0.00908681, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.54258675, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.00946372, "qsc_code_frac_chars_string_length": 0.16747165, "qsc_code_frac_chars_long_word_length": 0.01196976, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0} |
000haoji/deep-student | src/components/AIChatInterface.tsx | /**
* AI Chat Interface using Vercel AI SDK
*
* This component replaces the custom streaming implementation with
* Vercel AI SDK's useChat hook for better performance and reliability.
*/
import React, { useState, useMemo } from 'react';
import { useChat } from '@ai-sdk/react';
import { createAISdkFetch, convertFromTauriFormat, MarkdownRenderer, MessageWithThinking } from '../chat-core';
interface AIChatInterfaceProps {
tempId?: string;
mistakeId?: number;
initialMessages?: any[];
enableChainOfThought?: boolean;
onAnalysisStart?: () => void;
onAnalysisComplete?: (response: any) => void;
className?: string;
}
export const AIChatInterface = React.forwardRef<any, AIChatInterfaceProps>(({
tempId,
mistakeId,
initialMessages = [],
enableChainOfThought = true,
onAnalysisStart,
onAnalysisComplete,
className = ''
}, ref) => {
const [isAnalyzing, setIsAnalyzing] = useState(false);
// Convert initial messages to AI SDK format
const convertedInitialMessages = useMemo(() =>
convertFromTauriFormat(initialMessages),
[initialMessages]
);
// Determine API endpoint based on props
const apiEndpoint = useMemo(() => {
if (tempId) return '/api/continue-chat';
if (mistakeId) return '/api/mistake-chat';
return '/api/chat';
}, [tempId, mistakeId]);
// Initialize AI SDK useChat hook
const {
messages,
input,
handleInputChange,
handleSubmit,
isLoading,
error,
reload,
stop,
append,
setMessages
} = useChat({
api: apiEndpoint,
initialMessages: convertedInitialMessages,
fetch: createAISdkFetch(),
body: {
tempId,
mistakeId,
enableChainOfThought
},
onResponse: (response) => {
console.log('AI SDK Response received:', response.status);
if (onAnalysisStart) {
onAnalysisStart();
}
setIsAnalyzing(true);
},
onFinish: (message) => {
console.log('AI SDK Response finished:', message);
setIsAnalyzing(false);
if (onAnalysisComplete) {
onAnalysisComplete(message);
}
},
onError: (error) => {
console.error('AI SDK Error:', error);
setIsAnalyzing(false);
}
});
// Handle form submission with custom logic
const onSubmit = async (e: React.FormEvent<HTMLFormElement>) => {
e.preventDefault();
if (!input.trim() || isLoading) return;
setIsAnalyzing(true);
try {
await handleSubmit(e);
} catch (error) {
console.error('Chat submission error:', error);
setIsAnalyzing(false);
}
};
// Handle sending messages programmatically
const sendMessage = async (content: string, role: 'user' | 'assistant' = 'user') => {
if (!content.trim() || isLoading) return;
setIsAnalyzing(true);
try {
await append({
role,
content,
id: `msg-${Date.now()}`
});
} catch (error) {
console.error('Send message error:', error);
setIsAnalyzing(false);
}
};
// Expose sendMessage for external use
React.useImperativeHandle(ref, () => ({
sendMessage,
clearChat
}));
// Clear chat history
const clearChat = () => {
setMessages([]);
};
// Handle keyboard shortcuts
const handleKeyDown = (e: React.KeyboardEvent<HTMLTextAreaElement>) => {
if (e.key === 'Enter' && !e.shiftKey) {
e.preventDefault();
onSubmit(e as any);
}
};
return (
<div className={`ai-chat-interface ${className}`}>
{/* Chat Messages */}
<div className="chat-messages">
{messages.map((message, index) => (
<div key={message.id || index} className={`message ${message.role}`}>
<div className="message-header">
<span className="role">{message.role === 'user' ? '用户' : 'AI助手'}</span>
<span className="timestamp">
{new Date().toLocaleTimeString()}
</span>
</div>
<div className="message-content">
{message.role === 'assistant' ? (
<MessageWithThinking
content={message.content}
thinkingContent={(message as any).thinking_content}
isStreaming={isLoading && index === messages.length - 1}
role="assistant"
timestamp={new Date().toISOString()}
ragSources={(message as any).rag_sources}
/>
) : (
<div className="user-message">
<MarkdownRenderer content={message.content} />
</div>
)}
</div>
</div>
))}
{/* Loading indicator */}
{isLoading && (
<div className="message assistant">
<div className="message-header">
<span className="role">AI助手</span>
<span className="timestamp">正在回复...</span>
</div>
<div className="message-content">
<div className="loading-indicator">
<div className="typing-dots">
<span></span>
<span></span>
<span></span>
</div>
<span>正在分析中...</span>
</div>
</div>
</div>
)}
{/* Error display */}
{error && (
<div className="error-message">
<div className="error-content">
<span className="error-icon">⚠️</span>
<span className="error-text">
出错了: {error.message}
</span>
<button onClick={() => reload()} className="retry-button">
重试
</button>
</div>
</div>
)}
</div>
{/* Chat Input */}
<form onSubmit={onSubmit} className="chat-input-form">
<div className="input-container">
<textarea
value={input}
onChange={handleInputChange}
onKeyDown={handleKeyDown}
placeholder="输入您的问题..."
disabled={isLoading}
rows={3}
className="chat-input"
/>
<div className="input-actions">
<button
type="submit"
disabled={!input.trim() || isLoading}
className="send-button"
>
{isLoading ? '发送中...' : '发送'}
</button>
{isLoading && (
<button
type="button"
onClick={stop}
className="stop-button"
>
停止
</button>
)}
<button
type="button"
onClick={clearChat}
disabled={isLoading}
className="clear-button"
>
清空
</button>
</div>
</div>
</form>
{/* Chat Controls */}
<div className="chat-controls">
<label className="chain-of-thought-toggle">
<input
type="checkbox"
checked={enableChainOfThought}
onChange={() => {
// This would need to be passed up to parent component
// for now just show the current state
}}
disabled={isLoading}
/>
<span>显示思维过程</span>
</label>
<div className="chat-stats">
<span>消息数: {messages.length}</span>
{isAnalyzing && <span className="analyzing">分析中...</span>}
</div>
</div>
</div>
);
});
// Export utility functions for external use
export const useChatHelpers = () => {
return {
sendMessage: (chatRef: React.RefObject<any>, content: string) => {
if (chatRef.current?.sendMessage) {
chatRef.current.sendMessage(content);
}
},
clearChat: (chatRef: React.RefObject<any>) => {
if (chatRef.current?.clearChat) {
chatRef.current.clearChat();
}
}
};
}; | 8,100 | AIChatInterface | tsx | en | tsx | code | {"qsc_code_num_words": 648, "qsc_code_num_chars": 8100.0, "qsc_code_mean_word_length": 6.53395062, "qsc_code_frac_words_unique": 0.33024691, "qsc_code_frac_chars_top_2grams": 0.04534719, "qsc_code_frac_chars_top_3grams": 0.02243741, "qsc_code_frac_chars_top_4grams": 0.02054795, "qsc_code_frac_chars_dupe_5grams": 0.10392064, "qsc_code_frac_chars_dupe_6grams": 0.05668399, "qsc_code_frac_chars_dupe_7grams": 0.04109589, "qsc_code_frac_chars_dupe_8grams": 0.0, "qsc_code_frac_chars_dupe_9grams": 0.0, "qsc_code_frac_chars_dupe_10grams": 0.0, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.0003753, "qsc_code_frac_chars_whitespace": 0.34209877, "qsc_code_size_file_byte": 8100.0, "qsc_code_num_lines": 290.0, "qsc_code_num_chars_line_max": 112.0, "qsc_code_num_chars_line_mean": 27.93103448, "qsc_code_frac_chars_alphabet": 0.79376994, "qsc_code_frac_chars_comments": 0.08814815, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.32520325, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.0846081, "qsc_code_frac_chars_long_word_length": 0.00311358, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0} |
000haoji/deep-student | src/components/ImageOcclusion.css | .image-occlusion-container {
padding: 20px;
max-width: 1200px;
margin: 0 auto;
font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif;
}
.header {
text-align: center;
margin-bottom: 30px;
}
.header h2 {
color: #2c3e50;
margin-bottom: 10px;
font-size: 2rem;
font-weight: 600;
}
.header p {
color: #7f8c8d;
font-size: 1rem;
margin: 0;
}
.upload-section {
display: flex;
gap: 15px;
margin-bottom: 30px;
justify-content: center;
align-items: center;
}
.upload-button, .extract-button, .create-button {
padding: 12px 24px;
border: none;
border-radius: 8px;
font-size: 1rem;
font-weight: 500;
cursor: pointer;
transition: all 0.2s ease;
color: white;
}
.upload-button {
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
}
.upload-button:hover:not(:disabled) {
transform: translateY(-2px);
box-shadow: 0 8px 20px rgba(102, 126, 234, 0.3);
}
.extract-button {
background: linear-gradient(135deg, #f093fb 0%, #f5576c 100%);
}
.extract-button:hover:not(:disabled) {
transform: translateY(-2px);
box-shadow: 0 8px 20px rgba(240, 147, 251, 0.3);
}
.create-button {
background: linear-gradient(135deg, #4facfe 0%, #00f2fe 100%);
width: 100%;
margin-top: 20px;
}
.create-button:hover:not(:disabled) {
transform: translateY(-2px);
box-shadow: 0 8px 20px rgba(79, 172, 254, 0.3);
}
.upload-button:disabled, .extract-button:disabled, .create-button:disabled {
opacity: 0.6;
cursor: not-allowed;
transform: none;
}
.image-workspace {
display: grid;
grid-template-columns: 1fr 350px;
gap: 30px;
align-items: start;
}
.image-container {
position: relative;
background: #f8f9fa;
border-radius: 12px;
padding: 20px;
box-shadow: 0 4px 20px rgba(0, 0, 0, 0.1);
}
.main-image {
max-width: 100%;
max-height: 600px;
border-radius: 8px;
box-shadow: 0 2px 10px rgba(0, 0, 0, 0.1);
display: block;
}
.text-region {
transition: all 0.2s ease;
z-index: 10;
}
.text-region:hover {
border-width: 3px !important;
box-shadow: 0 0 10px rgba(0, 0, 0, 0.3);
}
.text-region.selected {
animation: pulse 1.5s infinite;
}
@keyframes pulse {
0% {
box-shadow: 0 0 0 0 rgba(255, 0, 0, 0.7);
}
70% {
box-shadow: 0 0 0 10px rgba(255, 0, 0, 0);
}
100% {
box-shadow: 0 0 0 0 rgba(255, 0, 0, 0);
}
}
.controls-panel, .preview-panel {
background: white;
border-radius: 12px;
padding: 20px;
box-shadow: 0 4px 20px rgba(0, 0, 0, 0.1);
height: fit-content;
position: sticky;
top: 20px;
}
.controls-panel h3, .preview-panel h3 {
margin: 0 0 15px 0;
color: #2c3e50;
font-size: 1.2rem;
font-weight: 600;
border-bottom: 2px solid #e9ecef;
padding-bottom: 8px;
}
.form-group {
margin-bottom: 20px;
}
.form-group-inline {
display: flex;
align-items: center;
gap: 8px;
margin-left: 15px;
}
.form-group-inline input[type="checkbox"] {
width: auto;
margin: 0;
cursor: pointer;
}
.form-group-inline label {
margin-bottom: 0;
color: #495057;
font-weight: 500;
cursor: pointer;
}
.form-group label {
display: block;
margin-bottom: 6px;
color: #495057;
font-weight: 500;
font-size: 0.9rem;
}
.form-group input, .form-group textarea, .form-group select {
width: 100%;
padding: 10px 12px;
border: 2px solid #e9ecef;
border-radius: 6px;
font-size: 0.9rem;
transition: border-color 0.2s ease;
box-sizing: border-box;
}
.form-group input:focus, .form-group textarea:focus, .form-group select:focus {
outline: none;
border-color: #667eea;
box-shadow: 0 0 0 3px rgba(102, 126, 234, 0.1);
}
.form-row {
display: grid;
grid-template-columns: 1fr 1fr;
gap: 15px;
}
.mask-settings {
margin: 20px 0;
}
.mask-style-options {
display: flex;
flex-direction: column;
gap: 10px;
}
.mask-style-options label {
display: flex;
align-items: center;
gap: 8px;
cursor: pointer;
padding: 8px;
border-radius: 6px;
transition: background-color 0.2s ease;
}
.mask-style-options label:hover {
background-color: #f8f9fa;
}
.mask-style-options input[type="radio"] {
width: auto;
margin: 0;
}
.region-stats {
background: #f8f9fa;
padding: 15px;
border-radius: 8px;
margin: 20px 0;
}
.region-stats p {
margin: 5px 0;
color: #6c757d;
font-size: 0.9rem;
}
.mask-overlay {
transition: opacity 0.3s ease;
z-index: 20;
}
.mask-overlay:hover {
opacity: 0.8 !important;
}
.preview-controls {
display: flex;
gap: 10px;
margin-bottom: 20px;
}
.preview-controls button {
padding: 8px 16px;
border: 2px solid #667eea;
border-radius: 6px;
background: white;
color: #667eea;
cursor: pointer;
transition: all 0.2s ease;
font-weight: 500;
}
.preview-controls button:hover {
background: #667eea;
color: white;
}
.preview-controls button:first-child {
border-color: #6c757d;
color: #6c757d;
}
.preview-controls button:first-child:hover {
background: #6c757d;
color: white;
}
.card-details {
padding-top: 15px;
border-top: 1px solid #e9ecef;
}
.card-details h4 {
margin: 0 0 10px 0;
color: #2c3e50;
font-size: 1.1rem;
}
.card-details p {
margin: 0 0 15px 0;
color: #6c757d;
line-height: 1.5;
}
.tags {
display: flex;
flex-wrap: wrap;
gap: 6px;
}
.tag {
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
color: white;
padding: 4px 8px;
border-radius: 12px;
font-size: 0.8rem;
font-weight: 500;
}
/* 响应式设计 */
@media (max-width: 768px) {
.image-workspace {
grid-template-columns: 1fr;
gap: 20px;
}
.controls-panel, .preview-panel {
position: static;
}
.form-row {
grid-template-columns: 1fr;
}
.upload-section {
flex-direction: column;
}
}
/* 加载状态动画 */
.processing {
opacity: 0.7;
pointer-events: none;
}
.processing::after {
content: '';
position: absolute;
top: 50%;
left: 50%;
width: 20px;
height: 20px;
margin: -10px 0 0 -10px;
border: 2px solid #667eea;
border-radius: 50%;
border-top-color: transparent;
animation: spin 1s linear infinite;
}
@keyframes spin {
to {
transform: rotate(360deg);
}
}
| 6,106 | ImageOcclusion | css | en | css | data | {"qsc_code_num_words": 841, "qsc_code_num_chars": 6106.0, "qsc_code_mean_word_length": 4.6979786, "qsc_code_frac_words_unique": 0.23424495, "qsc_code_frac_chars_top_2grams": 0.01670463, "qsc_code_frac_chars_top_3grams": 0.01290812, "qsc_code_frac_chars_top_4grams": 0.00607441, "qsc_code_frac_chars_dupe_5grams": 0.27587952, "qsc_code_frac_chars_dupe_6grams": 0.20197418, "qsc_code_frac_chars_dupe_7grams": 0.14452037, "qsc_code_frac_chars_dupe_8grams": 0.11111111, "qsc_code_frac_chars_dupe_9grams": 0.08782587, "qsc_code_frac_chars_dupe_10grams": 0.08782587, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.09718252, "qsc_code_frac_chars_whitespace": 0.19783819, "qsc_code_size_file_byte": 6106.0, "qsc_code_num_lines": 361.0, "qsc_code_num_chars_line_max": 82.0, "qsc_code_num_chars_line_mean": 16.91412742, "qsc_code_frac_chars_alphabet": 0.70947325, "qsc_code_frac_chars_comments": 0.0, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.33660131, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.00343924, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0} | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 1, "qsc_code_mean_word_length": 0, "qsc_code_frac_words_unique": 1, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0} |
000haoji/deep-student | src/components/RagQueryView.css | /* RAG查询测试组件样式 */
.rag-query-view {
padding: 20px;
max-width: 1200px;
margin: 0 auto;
color: #333;
}
.rag-query-header {
margin-bottom: 30px;
text-align: center;
}
.rag-query-header h2 {
color: #2c3e50;
margin: 0 0 8px 0;
font-size: 1.8rem;
}
.subtitle {
color: #7f8c8d;
margin: 0;
font-size: 0.95rem;
}
/* 查询配置区域 */
.query-config-section {
background: #f8f9fa;
border-radius: 8px;
padding: 20px;
margin-bottom: 20px;
border: 1px solid #e9ecef;
}
.query-config-section h3 {
margin: 0 0 15px 0;
color: #495057;
font-size: 1.1rem;
}
.config-controls {
display: flex;
gap: 30px;
align-items: center;
flex-wrap: wrap;
}
.config-item {
display: flex;
align-items: center;
gap: 8px;
}
.config-item label {
font-weight: 500;
color: #495057;
}
.config-item input[type="number"] {
width: 80px;
padding: 6px 8px;
border: 1px solid #ced4da;
border-radius: 4px;
font-size: 14px;
}
.checkbox-label {
display: flex;
align-items: center;
gap: 6px;
cursor: pointer;
user-select: none;
}
.checkbox-label input[type="checkbox"] {
margin: 0;
}
/* 查询输入区域 */
.query-input-section {
background: white;
border-radius: 8px;
padding: 20px;
margin-bottom: 20px;
border: 1px solid #e9ecef;
}
.query-input-section h3 {
margin: 0 0 15px 0;
color: #495057;
font-size: 1.1rem;
}
.query-input-container {
display: flex;
gap: 12px;
align-items: flex-start;
}
.query-input {
flex: 1;
padding: 12px;
border: 2px solid #e9ecef;
border-radius: 8px;
font-size: 14px;
font-family: inherit;
resize: vertical;
min-height: 80px;
transition: border-color 0.2s ease;
}
.query-input:focus {
outline: none;
border-color: #007bff;
box-shadow: 0 0 0 3px rgba(0, 123, 255, 0.1);
}
.query-input:disabled {
background-color: #f8f9fa;
color: #6c757d;
}
.query-button {
padding: 12px 24px;
background: #007bff;
color: white;
border: none;
border-radius: 8px;
font-weight: 500;
cursor: pointer;
transition: all 0.2s ease;
white-space: nowrap;
}
.query-button:hover:not(:disabled) {
background: #0056b3;
transform: translateY(-1px);
}
.query-button:disabled {
background: #6c757d;
cursor: not-allowed;
transform: none;
}
.input-hint {
margin-top: 8px;
font-size: 0.85rem;
color: #6c757d;
}
/* 检索结果区域 */
.retrieval-results-section {
background: white;
border-radius: 8px;
padding: 20px;
margin-bottom: 20px;
border: 1px solid #e9ecef;
}
.retrieval-results-section h3 {
margin: 0 0 20px 0;
color: #495057;
font-size: 1.1rem;
display: flex;
align-items: center;
gap: 8px;
}
.retrieval-results-section h3::before {
content: "🔍";
}
.retrieved-chunks {
display: flex;
flex-direction: column;
gap: 16px;
}
.retrieved-chunk {
background: #f8f9fa;
border-radius: 8px;
border: 1px solid #e9ecef;
overflow: hidden;
transition: box-shadow 0.2s ease;
}
.retrieved-chunk:hover {
box-shadow: 0 2px 8px rgba(0, 0, 0, 0.1);
}
.chunk-header {
background: #e9ecef;
padding: 12px 16px;
display: flex;
justify-content: space-between;
align-items: center;
flex-wrap: wrap;
gap: 8px;
}
.chunk-rank {
background: #007bff;
color: white;
padding: 4px 8px;
border-radius: 12px;
font-size: 0.85rem;
font-weight: 600;
}
.chunk-score {
background: #28a745;
color: white;
padding: 4px 8px;
border-radius: 12px;
font-size: 0.85rem;
font-weight: 500;
}
.chunk-source {
color: #495057;
font-size: 0.9rem;
font-weight: 500;
}
.chunk-content {
padding: 16px;
}
.chunk-content p {
margin: 0 0 12px 0;
line-height: 1.6;
color: #495057;
}
.expand-button {
background: none;
border: none;
color: #007bff;
cursor: pointer;
font-size: 0.9rem;
text-decoration: underline;
padding: 0;
}
.expand-button:hover {
color: #0056b3;
}
.chunk-metadata {
padding: 12px 16px;
background: #f1f3f4;
border-top: 1px solid #e9ecef;
display: flex;
gap: 20px;
font-size: 0.85rem;
color: #6c757d;
}
/* LLM回答区域 */
.llm-answer-section {
background: white;
border-radius: 8px;
padding: 20px;
margin-bottom: 20px;
border: 1px solid #e9ecef;
}
.llm-answer-section h3 {
margin: 0 0 20px 0;
color: #495057;
font-size: 1.1rem;
display: flex;
align-items: center;
gap: 8px;
}
.llm-answer-section h3::before {
content: "🤖";
}
.llm-answer {
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
border-radius: 12px;
padding: 24px;
color: white;
position: relative;
overflow: hidden;
}
.llm-answer::before {
content: '';
position: absolute;
top: 0;
left: 0;
right: 0;
bottom: 0;
background: rgba(255, 255, 255, 0.05);
backdrop-filter: blur(10px);
pointer-events: none;
}
.answer-content {
position: relative;
z-index: 1;
}
.answer-content p {
margin: 0 0 16px 0;
line-height: 1.7;
font-size: 1rem;
}
.answer-content p:last-child {
margin-bottom: 0;
}
.answer-footer {
margin-top: 20px;
padding-top: 16px;
border-top: 1px solid rgba(255, 255, 255, 0.2);
position: relative;
z-index: 1;
}
.answer-source {
font-size: 0.9rem;
opacity: 0.9;
font-style: italic;
}
/* 加载状态 */
.loading-overlay {
position: fixed;
top: 0;
left: 0;
right: 0;
bottom: 0;
background: rgba(0, 0, 0, 0.5);
display: flex;
flex-direction: column;
justify-content: center;
align-items: center;
z-index: 1000;
color: white;
}
.loading-spinner {
width: 50px;
height: 50px;
border: 4px solid rgba(255, 255, 255, 0.3);
border-top: 4px solid #007bff;
border-radius: 50%;
animation: spin 1s linear infinite;
margin-bottom: 16px;
}
@keyframes spin {
0% { transform: rotate(0deg); }
100% { transform: rotate(360deg); }
}
.loading-overlay p {
margin: 0;
font-size: 1.1rem;
font-weight: 500;
}
/* 响应式设计 */
@media (max-width: 768px) {
.rag-query-view {
padding: 15px;
}
.config-controls {
flex-direction: column;
align-items: flex-start;
gap: 15px;
}
.query-input-container {
flex-direction: column;
}
.query-button {
align-self: flex-start;
}
.chunk-header {
flex-direction: column;
align-items: flex-start;
}
.chunk-metadata {
flex-direction: column;
gap: 8px;
}
}
/* 深色主题支持 */
/* 强制应用深色主题到RAG查询页面 */
.rag-query-view {
color: #e9ecef !important;
background: #1a1a1a !important;
}
.rag-query-header h2 {
color: #ffffff !important;
}
.subtitle {
color: #b8b8b8 !important;
}
.query-config-section {
background: #2c3e50 !important;
border-color: #495057 !important;
}
.query-config-section h3 {
color: #ffffff !important;
}
.config-item label {
color: #ffffff !important;
}
.config-item input[type="number"] {
background: #495057 !important;
border-color: #6c757d !important;
color: #ffffff !important;
}
.checkbox-label {
color: #ffffff !important;
}
.query-input-section,
.retrieval-results-section,
.llm-answer-section {
background: #2c3e50 !important;
border-color: #495057 !important;
}
.query-input-section h3,
.retrieval-results-section h3,
.llm-answer-section h3 {
color: #ffffff !important;
}
.query-input {
background: #495057 !important;
border-color: #6c757d !important;
color: #ffffff !important;
}
.query-input::placeholder {
color: #adb5bd !important;
}
.query-input:focus {
border-color: #007bff !important;
}
.input-hint {
color: #ffc107 !important;
}
.retrieved-chunk {
background: #495057 !important;
border-color: #6c757d !important;
}
.chunk-header {
background: #6c757d !important;
}
.chunk-source {
color: #ffffff !important;
}
.chunk-content p {
color: #ffffff !important;
}
.chunk-metadata {
background: #6c757d !important;
border-color: #868e96 !important;
color: #ffffff !important;
}
.expand-button {
color: #66b3ff !important;
}
.expand-button:hover {
color: #4da6ff !important;
}
/* 备用的系统主题检测 */
@media (prefers-color-scheme: dark) {
.rag-query-view {
color: #e9ecef;
background: #1a1a1a;
}
.rag-query-header h2 {
color: #ffffff;
}
.subtitle {
color: #b8b8b8;
}
.query-config-section {
background: #2c3e50;
border-color: #495057;
}
.query-config-section h3 {
color: #ffffff;
}
.config-item label {
color: #ffffff;
}
.config-item input[type="number"] {
background: #495057;
border-color: #6c757d;
color: #ffffff;
}
.checkbox-label {
color: #ffffff;
}
.query-input-section,
.retrieval-results-section,
.llm-answer-section {
background: #2c3e50;
border-color: #495057;
}
.query-input-section h3,
.retrieval-results-section h3,
.llm-answer-section h3 {
color: #ffffff;
}
.query-input {
background: #495057;
border-color: #6c757d;
color: #ffffff;
}
.query-input::placeholder {
color: #adb5bd;
}
.query-input:focus {
border-color: #007bff;
}
.input-hint {
color: #ffc107;
}
.retrieved-chunk {
background: #495057;
border-color: #6c757d;
}
.chunk-header {
background: #6c757d;
}
.chunk-source {
color: #ffffff;
}
.chunk-content p {
color: #ffffff;
}
.chunk-metadata {
background: #6c757d;
border-color: #868e96;
color: #ffffff;
}
.expand-button {
color: #66b3ff;
}
.expand-button:hover {
color: #4da6ff;
}
} | 9,374 | RagQueryView | css | en | css | data | {"qsc_code_num_words": 1153, "qsc_code_num_chars": 9374.0, "qsc_code_mean_word_length": 5.17259324, "qsc_code_frac_words_unique": 0.18039896, "qsc_code_frac_chars_top_2grams": 0.03688799, "qsc_code_frac_chars_top_3grams": 0.03353454, "qsc_code_frac_chars_top_4grams": 0.01676727, "qsc_code_frac_chars_dupe_5grams": 0.44416499, "qsc_code_frac_chars_dupe_6grams": 0.34607646, "qsc_code_frac_chars_dupe_7grams": 0.27867203, "qsc_code_frac_chars_dupe_8grams": 0.21830986, "qsc_code_frac_chars_dupe_9grams": 0.21830986, "qsc_code_frac_chars_dupe_10grams": 0.20187793, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.08333333, "qsc_code_frac_chars_whitespace": 0.21015575, "qsc_code_size_file_byte": 9374.0, "qsc_code_num_lines": 599.0, "qsc_code_num_chars_line_max": 65.0, "qsc_code_num_chars_line_mean": 15.64941569, "qsc_code_frac_chars_alphabet": 0.72190708, "qsc_code_frac_chars_comments": 0.0, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.50898204, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.00298667, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0} | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 1, "qsc_code_mean_word_length": 0, "qsc_code_frac_words_unique": 1, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0} |
000haoji/deep-student | src/components/SummaryBox.tsx | import React, { useState, useEffect } from 'react';
import { ChatMessage } from '../types';
interface SummaryBoxProps {
chatHistory: ChatMessage[];
isVisible: boolean;
onClose?: () => void;
subject?: string;
mistakeId?: string; // 用于错题库详情
reviewSessionId?: string; // 用于批量分析详情
// 新增：与AI调用一致的接口
onGenerateSummary?: (summaryPrompt: string) => void;
currentStreamId?: string;
isGenerating?: boolean;
// 新增：从父组件传递的流式内容
summaryStreamContent?: string;
summaryStreamComplete?: boolean;
}
export const SummaryBox: React.FC<SummaryBoxProps> = ({
chatHistory,
isVisible,
onClose,
subject = '数学',
mistakeId: _mistakeId,
reviewSessionId: _reviewSessionId,
onGenerateSummary,
isGenerating = false,
summaryStreamContent = '',
summaryStreamComplete = false
}) => {
const [isExpanded, setIsExpanded] = useState(true);
const [summaryRequested, setSummaryRequested] = useState(false);
const [summaryContent, setSummaryContent] = useState('');
const [isStreaming, setIsStreaming] = useState(false);
// 监听流式内容更新
useEffect(() => {
if (summaryStreamContent !== undefined) {
setSummaryContent(summaryStreamContent);
setIsStreaming(!summaryStreamComplete);
if (summaryStreamContent && !summaryRequested) {
setSummaryRequested(true);
}
}
}, [summaryStreamContent, summaryStreamComplete, summaryRequested]);
// 🎯 新增：当父组件传入的总结内容发生变化时，重置内部状态 - 配合保活机制
useEffect(() => {
// 当切换到不同错题时，重置总结请求状态
// 这确保了在保活模式下，SummaryBox能正确响应新错题的总结状态
if (summaryStreamContent === '' && summaryRequested) {
console.log('🔄 [SummaryBox] 检测到新错题无总结内容，重置请求状态');
setSummaryRequested(false);
}
}, [summaryStreamContent, summaryStreamComplete]);
// 监听生成状态
useEffect(() => {
if (isGenerating) {
setIsStreaming(true);
} else if (summaryStreamComplete) {
setIsStreaming(false);
}
}, [isGenerating, summaryStreamComplete]);
// 如果不可见就不渲染
if (!isVisible) return null;
const generateSummary = () => {
if (chatHistory.length === 0) {
return;
}
if (!onGenerateSummary) {
console.warn('⚠️ onGenerateSummary回调未提供');
return;
}
// 构建总结提示词
const chatHistoryText = chatHistory.map(msg => {
const roleDisplay = msg.role === 'user' ? '用户' : '助手';
const contentStr = typeof msg.content === 'string' ? msg.content : JSON.stringify(msg.content);
return `${roleDisplay}: ${contentStr}`;
}).join('\\n\\n');
const summaryPrompt = `请基于以下对话记录，生成简洁的学习总结：
对话记录：
${chatHistoryText}
请生成：
1. 题目核心知识点：题目所涉及的知识点具体分类与定位
2. 错误分析：根据聊天上下文，学生存在的主要问题以及误区
3. 学生分析：根据聊天上下文，学生可能的薄弱点位置，需要重点注意的细节
4. 解题方法: 根据聊天上下文，学生应重点掌握的具体解题方法，
要求：
- 严禁使用markdown和latex语法，尤其是**
- 严禁使用markdown和latex语法，尤其是**
- 严禁使用markdown和latex语法，尤其是**
- 内容简洁明了，不长篇大论，不啰嗦，一针见血
- 重点突出学习要点`;
console.log('📝 准备通过回调生成总结，提示词长度:', summaryPrompt.length);
setSummaryRequested(true);
onGenerateSummary(summaryPrompt);
};
return (
<div className="summary-box" style={{
border: '1px solid #e0e0e0',
borderRadius: '8px',
margin: '8px 0',
backgroundColor: '#f9f9f9',
fontSize: '14px'
}}>
{/* 头部 */}
<div
className="summary-header"
style={{
padding: '8px 12px',
backgroundColor: '#f0f0f0',
borderRadius: '8px 8px 0 0',
cursor: 'pointer',
display: 'flex',
justifyContent: 'space-between',
alignItems: 'center',
borderBottom: isExpanded ? '1px solid #e0e0e0' : 'none'
}}
onClick={() => setIsExpanded(!isExpanded)}
>
<div style={{ display: 'flex', alignItems: 'center', gap: '8px' }}>
<span style={{
fontSize: '12px',
color: '#666',
transform: isExpanded ? 'rotate(90deg)' : 'rotate(0deg)',
transition: 'transform 0.2s',
width: '12px',
textAlign: 'center'
}}>
▶
</span>
<span style={{ fontWeight: '500', color: '#333' }}>
学习总结
</span>
{summaryContent && (
<span style={{
fontSize: '11px',
color: '#999',
backgroundColor: '#e8f4fd',
padding: '2px 6px',
borderRadius: '10px'
}}>
已生成
</span>
)}
</div>
<div style={{ display: 'flex', gap: '4px' }}>
{!isGenerating && (
<button
onClick={(e) => {
e.stopPropagation();
generateSummary();
}}
style={{
padding: '4px 8px',
fontSize: '11px',
backgroundColor: '#4CAF50',
color: 'white',
border: 'none',
borderRadius: '4px',
cursor: 'pointer'
}}
title="生成总结"
>
{summaryRequested ? '重新生成总结' : '生成学习总结'}
</button>
)}
{onClose && (
<button
onClick={(e) => {
e.stopPropagation();
onClose();
}}
style={{
padding: '4px 6px',
fontSize: '11px',
backgroundColor: '#f44336',
color: 'white',
border: 'none',
borderRadius: '4px',
cursor: 'pointer'
}}
title="关闭总结框"
>
✕
</button>
)}
</div>
</div>
{/* 总结内容显示区域 */}
{isExpanded && (
<div
className="summary-content"
style={{
padding: '12px',
minHeight: '40px',
maxHeight: '300px',
overflowY: 'auto',
backgroundColor: '#f8f9fa'
}}
>
{isGenerating && (
<div style={{
color: '#666',
fontStyle: 'italic',
display: 'flex',
alignItems: 'center',
gap: '8px',
marginBottom: summaryContent ? '8px' : '0'
}}>
<div
style={{
width: '16px',
height: '16px',
border: '2px solid #e0e0e0',
borderTop: '2px solid #4CAF50',
borderRadius: '50%',
animation: 'spin 1s linear infinite'
}}
/>
正在生成学习总结...
</div>
)}
{summaryContent ? (
<div style={{
lineHeight: '1.5',
color: '#333',
whiteSpace: 'pre-wrap',
fontSize: '14px'
}}>
{summaryContent}
{isStreaming && (
<span
style={{
opacity: 0.7,
animation: 'blink 1s infinite'
}}
>
|
</span>
)}
</div>
) : !isGenerating && (
<div style={{
color: '#999',
fontStyle: 'italic',
textAlign: 'center',
padding: '20px',
fontSize: '12px'
}}>
💡 点击"生成学习总结"按钮，AI将基于当前对话生成学习要点总结
</div>
)}
</div>
)}
{/* CSS动画 */}
<style>{`
@keyframes spin {
0% { transform: rotate(0deg); }
100% { transform: rotate(360deg); }
}
@keyframes blink {
0%, 50% { opacity: 1; }
51%, 100% { opacity: 0; }
}
.summary-box:hover {
box-shadow: 0 2px 8px rgba(0,0,0,0.1);
}
.summary-header:hover {
background-color: #e8e8e8;
}
`}</style>
</div>
);
}; | 7,987 | SummaryBox | tsx | en | tsx | code | {"qsc_code_num_words": 550, "qsc_code_num_chars": 7987.0, "qsc_code_mean_word_length": 6.98727273, "qsc_code_frac_words_unique": 0.41818182, "qsc_code_frac_chars_top_2grams": 0.01249024, "qsc_code_frac_chars_top_3grams": 0.01483216, "qsc_code_frac_chars_top_4grams": 0.02393963, "qsc_code_frac_chars_dupe_5grams": 0.0603695, "qsc_code_frac_chars_dupe_6grams": 0.0447567, "qsc_code_frac_chars_dupe_7grams": 0.02758262, "qsc_code_frac_chars_dupe_8grams": 0.02758262, "qsc_code_frac_chars_dupe_9grams": 0.02758262, "qsc_code_frac_chars_dupe_10grams": 0.0, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.03172021, "qsc_code_frac_chars_whitespace": 0.38424941, "qsc_code_size_file_byte": 7987.0, "qsc_code_num_lines": 295.0, "qsc_code_num_chars_line_max": 102.0, "qsc_code_num_chars_line_mean": 27.07457627, "qsc_code_frac_chars_alphabet": 0.74806832, "qsc_code_frac_chars_comments": 0.02842118, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.35361217, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.08439634, "qsc_code_frac_chars_long_word_length": 0.00283469, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0} |
000haoji/deep-student | src/components/TemplateManagementPage.tsx | import React, { useState, useEffect } from 'react';
import { CustomAnkiTemplate, CreateTemplateRequest, FieldExtractionRule } from '../types';
import { templateManager } from '../data/ankiTemplates';
import { IframePreview, renderCardPreview } from './SharedPreview';
import './TemplateManagementPage.css';
interface TemplateManagementPageProps {
isSelectingMode?: boolean;
onTemplateSelected?: (template: CustomAnkiTemplate) => void;
onCancel?: () => void;
}
const TemplateManagementPage: React.FC<TemplateManagementPageProps> = ({
isSelectingMode = false,
onTemplateSelected,
onCancel
}) => {
const [templates, setTemplates] = useState<CustomAnkiTemplate[]>([]);
const [activeTab, setActiveTab] = useState<'browse' | 'edit' | 'create'>('browse');
const [selectedTemplate, setSelectedTemplate] = useState<CustomAnkiTemplate | null>(null);
const [editingTemplate, setEditingTemplate] = useState<CustomAnkiTemplate | null>(null);
const [isLoading, setIsLoading] = useState(false);
const [error, setError] = useState<string | null>(null);
const [searchTerm, setSearchTerm] = useState('');
const [defaultTemplateId, setDefaultTemplateId] = useState<string | null>(null);
// 加载模板
useEffect(() => {
loadTemplates();
loadDefaultTemplateId();
// 订阅模板变化
const unsubscribe = templateManager.subscribe(setTemplates);
return unsubscribe;
}, []);
const loadDefaultTemplateId = async () => {
try {
await templateManager.loadUserDefaultTemplate();
setDefaultTemplateId(templateManager.getDefaultTemplateId());
} catch (err) {
console.warn('Failed to load default template ID:', err);
}
};
const loadTemplates = async () => {
setIsLoading(true);
try {
await templateManager.refresh();
setTemplates(templateManager.getAllTemplates());
} catch (err) {
setError(`加载模板失败: ${err}`);
} finally {
setIsLoading(false);
}
};
// 过滤模板
const filteredTemplates = templates.filter(template =>
template.name.toLowerCase().includes(searchTerm.toLowerCase()) ||
template.description.toLowerCase().includes(searchTerm.toLowerCase())
);
// 选择模板
const handleSelectTemplate = (template: CustomAnkiTemplate) => {
setSelectedTemplate(template);
};
// 设置默认模板
const handleSetDefaultTemplate = async (template: CustomAnkiTemplate) => {
try {
await templateManager.setDefaultTemplate(template.id);
setDefaultTemplateId(template.id); // 立即更新本地状态
setError(null);
console.log(`✅ 已将"${template.name}"设置为默认模板`);
} catch (err) {
setError(`设置默认模板失败: ${err}`);
}
};
// 编辑模板
const handleEditTemplate = (template: CustomAnkiTemplate) => {
setEditingTemplate({ ...template });
setActiveTab('edit');
};
// 复制模板
const handleDuplicateTemplate = (template: CustomAnkiTemplate) => {
const duplicated: CustomAnkiTemplate = {
...template,
id: `${template.id}-copy-${Date.now()}`,
name: `${template.name} - 副本`,
author: '用户创建',
is_built_in: false,
created_at: new Date().toISOString(),
updated_at: new Date().toISOString()
};
setEditingTemplate(duplicated);
setActiveTab('create');
};
// 使用统一的预览渲染函数
const renderTemplatePreview = (template: string, templateData: CustomAnkiTemplate) => {
return renderCardPreview(template, templateData);
};
// 删除模板
const handleDeleteTemplate = async (template: CustomAnkiTemplate) => {
if (template.is_built_in) {
setError('不能删除内置模板');
return;
}
if (!confirm(`确定要删除模板 "${template.name}" 吗？此操作不可撤销。`)) {
return;
}
try {
await templateManager.deleteTemplate(template.id);
setError(null);
} catch (err) {
setError(`删除模板失败: ${err}`);
}
};
return (
<>
{/* 页面头部 */}
<div className={`page-header ${isSelectingMode ? 'selecting-mode' : 'management-mode'}`}>
<div className="header-content">
<div className="header-main">
{isSelectingMode && onCancel && (
<button className="back-button" onClick={onCancel}>
<span className="back-icon">←</span>
返回
</button>
)}
<div className="title-section">
<h1 className="page-title">
<svg style={{ width: '32px', height: '32px', marginRight: '12px', color: '#667eea' }} fill="none" stroke="currentColor" viewBox="0 0 24 24" strokeWidth={2}>
<path d="M12 22a1 1 0 0 1 0-20 10 9 0 0 1 10 9 5 5 0 0 1-5 5h-2.25a1.75 1.75 0 0 0-1.4 2.8l.3.4a1.75 1.75 0 0 1-1.4 2.8z" />
<circle cx="13.5" cy="6.5" r=".5" fill="currentColor" />
<circle cx="17.5" cy="10.5" r=".5" fill="currentColor" />
<circle cx="6.5" cy="12.5" r=".5" fill="currentColor" />
<circle cx="8.5" cy="7.5" r=".5" fill="currentColor" />
</svg>
{isSelectingMode ? '选择模板' : '模板管理'}
</h1>
<div className={`mode-indicator ${isSelectingMode ? 'selecting' : 'management'}`}>
<span className="mode-icon">{isSelectingMode ? '🎯' : '⚙️'}</span>
<span className="mode-text">
{isSelectingMode ? '选择模式' : '管理模式'}
</span>
</div>
</div>
</div>
<p className="page-description">
{isSelectingMode
? '请选择一个模板用于生成ANKI卡片，点击"使用此模板"按钮完成选择'
: '管理和编辑ANKI卡片模板，自定义卡片样式和字段，创建符合需求的模板'
}
</p>
</div>
</div>
{/* 标签页导航 */}
{!isSelectingMode && (
<div className="page-tabs">
<button
className={`tab-button ${activeTab === 'browse' ? 'active' : ''}`}
onClick={() => setActiveTab('browse')}
>
<span className="tab-icon">📋</span>
浏览模板
</button>
<button
className={`tab-button ${activeTab === 'create' ? 'active' : ''}`}
onClick={() => setActiveTab('create')}
>
<span className="tab-icon">➕</span>
创建模板
</button>
{editingTemplate && (
<button
className={`tab-button ${activeTab === 'edit' ? 'active' : ''}`}
onClick={() => setActiveTab('edit')}
>
<span className="tab-icon">✏️</span>
编辑模板
</button>
)}
</div>
)}
{/* 错误提示 */}
{error && (
<div className="error-alert">
<div className="alert-content">
<span className="alert-icon">⚠️</span>
<span className="alert-message">{error}</span>
<button className="alert-close" onClick={() => setError(null)}>✕</button>
</div>
</div>
)}
{/* 内容区域 */}
<div className="page-content">
{(isSelectingMode || activeTab === 'browse') && (
<TemplateBrowser
templates={filteredTemplates}
selectedTemplate={selectedTemplate}
searchTerm={searchTerm}
onSearchChange={setSearchTerm}
onSelectTemplate={handleSelectTemplate}
onEditTemplate={handleEditTemplate}
onDuplicateTemplate={handleDuplicateTemplate}
onDeleteTemplate={handleDeleteTemplate}
onSetDefaultTemplate={handleSetDefaultTemplate}
defaultTemplateId={defaultTemplateId}
isLoading={isLoading}
isSelectingMode={isSelectingMode}
onTemplateSelected={onTemplateSelected}
renderPreview={renderTemplatePreview}
/>
)}
{!isSelectingMode && activeTab === 'create' && (
<TemplateEditor
template={editingTemplate}
mode="create"
onSave={async (templateData) => {
try {
await templateManager.createTemplate(templateData);
setActiveTab('browse');
setEditingTemplate(null);
setError(null);
} catch (err) {
setError(`创建模板失败: ${err}`);
}
}}
onCancel={() => {
setActiveTab('browse');
setEditingTemplate(null);
}}
/>
)}
{!isSelectingMode && activeTab === 'edit' && editingTemplate && (
<TemplateEditor
template={editingTemplate}
mode="edit"
onSave={async (_templateData) => {
try {
// TODO: 实现模板更新
setActiveTab('browse');
setEditingTemplate(null);
setError(null);
} catch (err) {
setError(`更新模板失败: ${err}`);
}
}}
onCancel={() => {
setActiveTab('browse');
setEditingTemplate(null);
}}
/>
)}
</div>
</>
);
};
// 模板浏览器组件
interface TemplateBrowserProps {
templates: CustomAnkiTemplate[];
selectedTemplate: CustomAnkiTemplate | null;
searchTerm: string;
onSearchChange: (term: string) => void;
onSelectTemplate: (template: CustomAnkiTemplate) => void;
onEditTemplate: (template: CustomAnkiTemplate) => void;
onDuplicateTemplate: (template: CustomAnkiTemplate) => void;
onDeleteTemplate: (template: CustomAnkiTemplate) => void;
onSetDefaultTemplate: (template: CustomAnkiTemplate) => void;
defaultTemplateId: string | null;
isLoading: boolean;
isSelectingMode?: boolean;
onTemplateSelected?: (template: CustomAnkiTemplate) => void;
renderPreview: (template: string, templateData: CustomAnkiTemplate) => string;
}
const TemplateBrowser: React.FC<TemplateBrowserProps> = ({
templates,
selectedTemplate,
searchTerm,
onSearchChange,
onSelectTemplate,
onEditTemplate,
onDuplicateTemplate,
onDeleteTemplate,
onSetDefaultTemplate,
defaultTemplateId,
isLoading,
isSelectingMode = false,
onTemplateSelected,
renderPreview
}) => {
return (
<div className="template-browser">
{/* 搜索和工具栏 */}
<div className="browser-toolbar">
<div className="search-container">
<div className="search-input-wrapper">
<span className="search-icon">🔍</span>
<input
type="text"
placeholder="搜索模板名称或描述..."
value={searchTerm}
onChange={(e) => onSearchChange(e.target.value)}
className="search-input"
/>
</div>
</div>
<div className="toolbar-stats">
<span className="stats-text">共 {templates.length} 个模板</span>
{isSelectingMode && (
<div className="mode-hint">
<span className="hint-icon">💡</span>
<span className="hint-text">点击"使用此模板"选择模板</span>
</div>
)}
</div>
</div>
{/* 模板网格 */}
{isLoading ? (
<div className="loading-container">
<div className="loading-spinner"></div>
<span className="loading-text">加载模板中...</span>
</div>
) : (
<div className="templates-grid">
{templates.map(template => (
<TemplateCard
key={template.id}
template={template}
isSelected={selectedTemplate?.id === template.id}
onSelect={() => onSelectTemplate(template)}
onEdit={() => onEditTemplate(template)}
onDuplicate={() => onDuplicateTemplate(template)}
onDelete={() => onDeleteTemplate(template)}
onSetDefaultTemplate={() => onSetDefaultTemplate(template)}
defaultTemplateId={defaultTemplateId}
isSelectingMode={isSelectingMode}
onTemplateSelected={onTemplateSelected}
renderPreview={renderPreview}
/>
))}
</div>
)}
{templates.length === 0 && !isLoading && (
<div className="empty-state">
<div className="empty-icon">📝</div>
<h3 className="empty-title">没有找到模板</h3>
<p className="empty-description">试试调整搜索条件，或创建一个新模板。</p>
</div>
)}
</div>
);
};
// 模板卡片组件
interface TemplateCardProps {
template: CustomAnkiTemplate;
isSelected: boolean;
onSelect: () => void;
onEdit: () => void;
onDuplicate: () => void;
onDelete: () => void;
onSetDefaultTemplate: () => void;
defaultTemplateId: string | null;
isSelectingMode?: boolean;
onTemplateSelected?: (template: CustomAnkiTemplate) => void;
renderPreview: (template: string, templateData: CustomAnkiTemplate) => string;
}
const TemplateCard: React.FC<TemplateCardProps> = ({
template,
isSelected,
onSelect,
onEdit,
onDuplicate,
onDelete,
onSetDefaultTemplate,
defaultTemplateId,
isSelectingMode = false,
onTemplateSelected,
renderPreview
}) => {
// 检查是否为默认模板
const isDefault = defaultTemplateId === template.id;
return (
<div className={`template-card template-card-${template.id.replace(/[^a-zA-Z0-9]/g, '_')} ${isSelected ? 'selected' : ''} ${!template.is_active ? 'inactive' : ''} ${isSelectingMode ? 'selecting-mode' : 'management-mode'} ${isDefault ? 'default-template' : ''}`}>
{/* 卡片头部 */}
<div className="card-header">
<h4 className="template-name">{template.name}</h4>
<div className="template-badges">
{isDefault && <span className="badge default">默认</span>}
{template.is_built_in && <span className="badge built-in">内置</span>}
{!template.is_active && <span className="badge inactive">停用</span>}
<span className="badge version">v{template.version}</span>
</div>
</div>
{/* 预览区域 */}
<div className="card-preview">
<div className="preview-section">
<div className="preview-label">正面</div>
<div className="preview-content">
<IframePreview
htmlContent={renderPreview(template.front_template || template.preview_front || '', template)}
cssContent={template.css_style || ''}
/>
</div>
</div>
<div className="preview-section">
<div className="preview-label">背面</div>
<div className="preview-content">
<IframePreview
htmlContent={renderPreview(template.back_template || template.preview_back || '', template)}
cssContent={template.css_style || ''}
/>
</div>
</div>
</div>
{/* 卡片信息 */}
<div className="card-info">
<p className="template-description">{template.description}</p>
<div className="template-meta">
<span className="meta-item">
<span className="meta-icon">👤</span>
{template.author || '未知'}
</span>
<span className="meta-item">
<span className="meta-icon">📝</span>
{template.fields.length} 个字段
</span>
</div>
<div className="template-fields">
{template.fields.slice(0, 3).map(field => (
<span key={field} className="field-tag">{field}</span>
))}
{template.fields.length > 3 && (
<span className="field-tag more">+{template.fields.length - 3}</span>
)}
</div>
</div>
{/* 模式提示 */}
{isSelectingMode && (
<div className="mode-banner">
<span className="banner-icon">🎯</span>
<span className="banner-text">点击下方按钮选择此模板</span>
</div>
)}
{/* 操作按钮 */}
<div className="card-actions">
{isSelectingMode ? (
<button
className="btn-select primary"
onClick={() => {
console.log('🎯 点击使用模板:', template.name, template);
console.log('🔧 onTemplateSelected回调:', onTemplateSelected);
if (onTemplateSelected) {
onTemplateSelected(template);
} else {
console.error('❌ onTemplateSelected回调函数不存在');
}
}}
>
<span className="btn-icon">✨</span>
使用此模板
</button>
) : (
<>
<button
className={`btn-select ${isDefault ? 'default' : ''}`}
onClick={isDefault ? undefined : onSetDefaultTemplate}
disabled={isDefault}
>
{isDefault ? '⭐ 默认模板' : '设为默认'}
</button>
<div className="action-buttons">
<button className="action-btn" onClick={onEdit} title="编辑">
<span>✏️</span>
</button>
<button className="action-btn" onClick={onDuplicate} title="复制">
<span>📋</span>
</button>
{!template.is_built_in && (
<button className="action-btn danger" onClick={onDelete} title="删除">
<span>🗑️</span>
</button>
)}
</div>
</>
)}
</div>
</div>
);
};
// 模板编辑器组件
interface TemplateEditorProps {
template: CustomAnkiTemplate | null;
mode: 'create' | 'edit';
onSave: (templateData: CreateTemplateRequest) => Promise<void>;
onCancel: () => void;
}
const TemplateEditor: React.FC<TemplateEditorProps> = ({
template,
mode,
onSave,
onCancel
}) => {
const [formData, setFormData] = useState({
name: template?.name || '',
description: template?.description || '',
author: template?.author || '',
preview_front: template?.preview_front || '',
preview_back: template?.preview_back || '',
note_type: template?.note_type || 'Basic',
fields: template?.fields.join(',') || 'Front,Back,Notes',
generation_prompt: template?.generation_prompt || '',
front_template: template?.front_template || '<div class="card">' + '{{Front}}' + '</div>',
back_template: template?.back_template || '<div class="card">' + '{{Front}}' + '<hr>' + '{{Back}}' + '</div>',
css_style: template?.css_style || '.card { padding: 20px; background: white; border-radius: 8px; }'
});
const [isSubmitting, setIsSubmitting] = useState(false);
const [activeEditorTab, setActiveEditorTab] = useState<'basic' | 'templates' | 'styles' | 'advanced'>('basic');
const handleSubmit = async (e: React.FormEvent) => {
e.preventDefault();
setIsSubmitting(true);
try {
const fields = formData.fields.split(',').map(f => f.trim()).filter(f => f);
const fieldExtractionRules: Record<string, FieldExtractionRule> = {};
fields.forEach(field => {
fieldExtractionRules[field] = {
field_type: field.toLowerCase() === 'tags' ? 'Array' : 'Text',
is_required: field.toLowerCase() === 'front' || field.toLowerCase() === 'back',
default_value: field.toLowerCase() === 'tags' ? '[]' : '',
description: `${field} 字段`
};
});
const templateData: CreateTemplateRequest = {
name: formData.name,
description: formData.description,
author: formData.author || undefined,
preview_front: formData.preview_front,
preview_back: formData.preview_back,
note_type: formData.note_type,
fields,
generation_prompt: formData.generation_prompt,
front_template: formData.front_template,
back_template: formData.back_template,
css_style: formData.css_style,
field_extraction_rules: fieldExtractionRules
};
await onSave(templateData);
} finally {
setIsSubmitting(false);
}
};
return (
<div className="template-editor">
<div className="editor-header">
<h3 className="editor-title">{mode === 'create' ? '创建新模板' : '编辑模板'}</h3>
</div>
{/* 编辑器标签页 */}
<div className="editor-tabs">
<button
className={`editor-tab ${activeEditorTab === 'basic' ? 'active' : ''}`}
onClick={() => setActiveEditorTab('basic')}
>
<span className="tab-icon">📝</span>
基本信息
</button>
<button
className={`editor-tab ${activeEditorTab === 'templates' ? 'active' : ''}`}
onClick={() => setActiveEditorTab('templates')}
>
<span className="tab-icon">🎨</span>
模板代码
</button>
<button
className={`editor-tab ${activeEditorTab === 'styles' ? 'active' : ''}`}
onClick={() => setActiveEditorTab('styles')}
>
<span className="tab-icon">💄</span>
样式设计
</button>
<button
className={`editor-tab ${activeEditorTab === 'advanced' ? 'active' : ''}`}
onClick={() => setActiveEditorTab('advanced')}
>
<span className="tab-icon">⚙️</span>
高级设置
</button>
</div>
<form onSubmit={handleSubmit} className="editor-form">
{/* 基本信息标签页 */}
{activeEditorTab === 'basic' && (
<div className="editor-section">
<div className="form-grid">
<div className="form-group">
<label className="form-label">模板名称 *</label>
<input
type="text"
value={formData.name}
onChange={(e) => setFormData({...formData, name: e.target.value})}
required
className="form-input"
placeholder="请输入模板名称"
/>
</div>
<div className="form-group">
<label className="form-label">作者</label>
<input
type="text"
value={formData.author}
onChange={(e) => setFormData({...formData, author: e.target.value})}
className="form-input"
placeholder="可选"
/>
</div>
<div className="form-group full-width">
<label className="form-label">描述</label>
<textarea
value={formData.description}
onChange={(e) => setFormData({...formData, description: e.target.value})}
className="form-textarea"
rows={3}
placeholder="请描述这个模板的用途和特点..."
/>
</div>
<div className="form-group">
<label className="form-label">笔记类型</label>
<input
type="text"
value={formData.note_type}
onChange={(e) => setFormData({...formData, note_type: e.target.value})}
className="form-input"
placeholder="Basic"
/>
</div>
<div className="form-group">
<label className="form-label">字段列表 *</label>
<input
type="text"
value={formData.fields}
onChange={(e) => setFormData({...formData, fields: e.target.value})}
required
className="form-input"
placeholder="Front,Back,Notes"
/>
<small className="form-help">用逗号分隔，至少需要包含 Front 和 Back 字段</small>
</div>
<div className="form-group">
<label className="form-label">预览正面 *</label>
<input
type="text"
value={formData.preview_front}
onChange={(e) => setFormData({...formData, preview_front: e.target.value})}
required
className="form-input"
placeholder="示例问题"
/>
</div>
<div className="form-group">
<label className="form-label">预览背面 *</label>
<input
type="text"
value={formData.preview_back}
onChange={(e) => setFormData({...formData, preview_back: e.target.value})}
required
className="form-input"
placeholder="示例答案"
/>
</div>
</div>
</div>
)}
{/* 模板代码标签页 */}
{activeEditorTab === 'templates' && (
<div className="editor-section">
<div className="template-code-editor">
<div className="code-group">
<label className="form-label">正面模板 *</label>
<textarea
value={formData.front_template}
onChange={(e) => setFormData({...formData, front_template: e.target.value})}
required
className="code-textarea"
rows={8}
placeholder="<div class="card">{{Front}}</div>"
/>
<small className="form-help">使用 Mustache 语法，如 {`{{Front}}`}、{`{{Back}}`} 等</small>
</div>
<div className="code-group">
<label className="form-label">背面模板 *</label>
<textarea
value={formData.back_template}
onChange={(e) => setFormData({...formData, back_template: e.target.value})}
required
className="code-textarea"
rows={8}
placeholder="<div class="card">{{Front}}<hr>{{Back}}</div>"
/>
</div>
</div>
</div>
)}
{/* 样式设计标签页 */}
{activeEditorTab === 'styles' && (
<div className="editor-section">
<div className="styles-editor">
<label className="form-label">CSS 样式</label>
<textarea
value={formData.css_style}
onChange={(e) => setFormData({...formData, css_style: e.target.value})}
className="css-textarea"
rows={12}
placeholder=".card { padding: 20px; background: white; border-radius: 8px; }"
/>
<small className="form-help">自定义CSS样式来美化卡片外观</small>
</div>
</div>
)}
{/* 高级设置标签页 */}
{activeEditorTab === 'advanced' && (
<div className="editor-section">
<div className="advanced-settings">
<label className="form-label">AI生成提示词 *</label>
<textarea
value={formData.generation_prompt}
onChange={(e) => setFormData({...formData, generation_prompt: e.target.value})}
required
className="prompt-textarea"
rows={8}
placeholder="请输入AI生成卡片时使用的提示词..."
/>
<small className="form-help">指导AI如何生成符合此模板的卡片内容</small>
</div>
</div>
)}
{/* 操作按钮 */}
<div className="editor-actions">
<button
type="submit"
disabled={isSubmitting}
className="btn-primary"
>
{isSubmitting ? '保存中...' : mode === 'create' ? '创建模板' : '保存修改'}
</button>
<button
type="button"
onClick={onCancel}
className="btn-secondary"
>
取消
</button>
</div>
</form>
</div>
);
};
export default TemplateManagementPage; | 27,511 | TemplateManagementPage | tsx | en | tsx | code | {"qsc_code_num_words": 2177, "qsc_code_num_chars": 27511.0, "qsc_code_mean_word_length": 6.71336702, "qsc_code_frac_words_unique": 0.20578778, "qsc_code_frac_chars_top_2grams": 0.04680123, "qsc_code_frac_chars_top_3grams": 0.01334246, "qsc_code_frac_chars_top_4grams": 0.01731098, "qsc_code_frac_chars_dupe_5grams": 0.23284297, "qsc_code_frac_chars_dupe_6grams": 0.17119398, "qsc_code_frac_chars_dupe_7grams": 0.13157715, "qsc_code_frac_chars_dupe_8grams": 0.11522408, "qsc_code_frac_chars_dupe_9grams": 0.06835443, "qsc_code_frac_chars_dupe_10grams": 0.03284297, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.00863171, "qsc_code_frac_chars_whitespace": 0.31780015, "qsc_code_size_file_byte": 27511.0, "qsc_code_num_lines": 802.0, "qsc_code_num_chars_line_max": 267.0, "qsc_code_num_chars_line_mean": 34.30299252, "qsc_code_frac_chars_alphabet": 0.76832907, "qsc_code_frac_chars_comments": 0.0119225, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.41882674, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.00409277, "qsc_code_frac_chars_string_length": 0.11172013, "qsc_code_frac_chars_long_word_length": 0.01140377, "qsc_code_frac_lines_string_concat": 0.00272851, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.00124688, "qsc_code_frac_lines_assert": 0.0} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0} |
00000O00000/ask-ai-screenshot | core.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
AI截图分析核心功能模块
包含截图、OCR、AI客户端等核心功能
"""
import os
import io
import base64
import json
import logging
import smtplib
import time
import hashlib
import hmac
from datetime import datetime
from email.mime.text import MIMEText
from email.mime.multipart import MIMEMultipart
from typing import Optional
import requests
from PIL import Image, ImageGrab
from PyQt6.QtCore import QObject, pyqtSignal, QThread, QTimer
from pynput import keyboard
from screenshot_overlay import AdvancedScreenshotManager
class ScreenshotManager(QObject):
"""截图管理器"""
screenshot_taken = pyqtSignal(object) # 截图完成信号
screenshot_failed = pyqtSignal(str) # 截图失败信号
screenshot_cancelled = pyqtSignal() # 截图取消信号
hotkey_triggered = pyqtSignal() # 快捷键触发信号
def __init__(self, config_manager):
super().__init__()
self.config_manager = config_manager
self.advanced_manager = AdvancedScreenshotManager(config_manager)
self.hotkey_listener = None
# 连接快捷键信号到截图方法
self.hotkey_triggered.connect(self.start_screenshot)
# 连接高级截图管理器信号
self.advanced_manager.overlay = None # 初始化overlay属性
# 注意：信号连接需要在overlay创建后进行
def setup_hotkey(self):
"""设置全局快捷键"""
try:
if self.hotkey_listener:
self.hotkey_listener.stop()
# 使用固定的快捷键 Alt+Shift+D
hotkey_combination = {keyboard.Key.alt, keyboard.Key.shift, keyboard.KeyCode.from_char('d')}
def on_hotkey():
# 使用信号来避免在快捷键回调中直接调用UI操作
self.hotkey_triggered.emit()
self.hotkey_listener = keyboard.GlobalHotKeys({
'<alt>+<shift>+d': on_hotkey
})
self.hotkey_listener.start()
logging.info("全局快捷键设置成功: Alt+Shift+D")
except Exception as e:
logging.error(f"设置全局快捷键失败: {e}")
def start_screenshot(self):
"""开始截图"""
try:
# 先断开之前的连接（如果存在）
if self.advanced_manager.overlay:
try:
self.advanced_manager.overlay.screenshot_confirmed.disconnect()
self.advanced_manager.overlay.screenshot_cancelled.disconnect()
except:
pass
# 启动截图
self.advanced_manager.start_screenshot()
# 连接信号（在overlay创建后）
if self.advanced_manager.overlay:
self.advanced_manager.overlay.screenshot_confirmed.connect(self.on_screenshot_confirmed)
self.advanced_manager.overlay.screenshot_cancelled.connect(self.on_screenshot_cancelled)
logging.info("截图信号连接成功")
else:
logging.error("截图overlay创建失败")
self.screenshot_failed.emit("截图overlay创建失败")
except Exception as e:
logging.error(f"启动截图失败: {e}")
self.screenshot_failed.emit(str(e))
def screenshot_from_clipboard(self):
"""从剪贴板获取图片"""
try:
image = ImageGrab.grabclipboard()
if image and isinstance(image, Image.Image):
return image
return None
except Exception as e:
logging.error(f"从剪贴板获取图片失败: {e}")
return None
def on_screenshot_confirmed(self, image):
"""截图确认处理"""
self.screenshot_taken.emit(image)
def on_screenshot_cancelled(self):
"""截图取消处理"""
self.screenshot_cancelled.emit()
def cleanup(self):
"""清理资源"""
if self.hotkey_listener:
self.hotkey_listener.stop()
class OCRManager(QObject):
"""OCR管理器"""
ocr_completed = pyqtSignal(str) # OCR完成信号
ocr_failed = pyqtSignal(str) # OCR失败信号
def __init__(self, config_manager):
super().__init__()
self.config_manager = config_manager
def recognize_image(self, image: Image.Image) -> str:
"""识别图片中的文字"""
try:
engine = self.config_manager.get_config("ocr.engine")
if engine == "tencent":
return self._tencent_ocr(image)
elif engine == "xinyew":
return self._xinyew_ocr(image)
elif engine == "vision_model":
return self._vision_model_ocr(image)
else:
# 默认使用新野OCR
return self._xinyew_ocr(image)
except Exception as e:
error_msg = f"OCR识别失败: {e}"
logging.error(error_msg)
# 在WorkerThread中不发射信号，直接抛出异常
raise Exception(error_msg)
def _tencent_ocr(self, image: Image.Image) -> str:
"""腾讯云OCR"""
try:
# 获取配置
secret_id = self.config_manager.get_config("ocr.tencent.secret_id")
secret_key = self.config_manager.get_config("ocr.tencent.secret_key")
if not secret_id or not secret_key:
raise ValueError("腾讯云OCR配置不完整")
# 将图片转换为base64
buffer = io.BytesIO()
image.save(buffer, format='PNG')
image_base64 = base64.b64encode(buffer.getvalue()).decode('utf-8')
# 构建请求
url = "https://ocr.tencentcloudapi.com/"
headers = {
"Content-Type": "application/json; charset=utf-8",
"Host": "ocr.tencentcloudapi.com",
"X-TC-Action": "GeneralBasicOCR",
"X-TC-Version": "2018-11-19",
"X-TC-Region": "ap-beijing",
"X-TC-Timestamp": str(int(time.time()))
}
payload = {
"ImageBase64": image_base64
}
# 计算签名
signature = self._calculate_tencent_signature(
secret_id, secret_key, headers, json.dumps(payload)
)
headers["Authorization"] = signature
# 发送请求
response = requests.post(url, headers=headers, json=payload, timeout=10)
response.raise_for_status()
result = response.json()
if "Response" in result and "TextDetections" in result["Response"]:
texts = [item["DetectedText"] for item in result["Response"]["TextDetections"]]
ocr_text = "\n".join(texts)
return ocr_text
else:
raise ValueError("OCR响应格式错误")
except Exception as e:
raise Exception(f"腾讯云OCR失败: {e}")
def _calculate_tencent_signature(self, secret_id: str, secret_key: str, headers: dict, payload: str) -> str:
"""计算腾讯云签名"""
# 这里是简化的签名计算，实际项目中需要完整的腾讯云签名算法
# 由于篇幅限制，这里只是示例
algorithm = "TC3-HMAC-SHA256"
service = "ocr"
host = "ocr.tencentcloudapi.com"
# 构建规范请求串
http_request_method = "POST"
canonical_uri = "/"
canonical_querystring = ""
canonical_headers = f"content-type:application/json; charset=utf-8\nhost:{host}\n"
signed_headers = "content-type;host"
hashed_request_payload = hashlib.sha256(payload.encode('utf-8')).hexdigest()
canonical_request = f"{http_request_method}\n{canonical_uri}\n{canonical_querystring}\n{canonical_headers}\n{signed_headers}\n{hashed_request_payload}"
# 构建待签名字符串
timestamp = headers["X-TC-Timestamp"]
date = datetime.fromtimestamp(int(timestamp)).strftime('%Y-%m-%d')
credential_scope = f"{date}/{service}/tc3_request"
hashed_canonical_request = hashlib.sha256(canonical_request.encode('utf-8')).hexdigest()
string_to_sign = f"{algorithm}\n{timestamp}\n{credential_scope}\n{hashed_canonical_request}"
# 计算签名
secret_date = hmac.new(("TC3" + secret_key).encode('utf-8'), date.encode('utf-8'), hashlib.sha256).digest()
secret_service = hmac.new(secret_date, service.encode('utf-8'), hashlib.sha256).digest()
secret_signing = hmac.new(secret_service, "tc3_request".encode('utf-8'), hashlib.sha256).digest()
signature = hmac.new(secret_signing, string_to_sign.encode('utf-8'), hashlib.sha256).hexdigest()
return f"{algorithm} Credential={secret_id}/{credential_scope}, SignedHeaders={signed_headers}, Signature={signature}"
def _xinyew_ocr(self, image: Image.Image) -> str:
"""新野图床+云智OCR识别（免费公益接口）"""
try:
# 1. 上传图片到新野图床
upload_url = "https://api.xinyew.cn/api/360tc"
buffer = io.BytesIO()
image.save(buffer, format='PNG')
buffer.seek(0)
files = {'file': ('image.png', buffer, 'image/png')}
upload_response = requests.post(upload_url, files=files, timeout=10)
upload_response.raise_for_status()
upload_result = upload_response.json()
if upload_result.get("errno") != 0:
raise ValueError(f"图片上传失败: {upload_result.get('error')}")
image_url = upload_result.get("data", {}).get("url")
if not image_url:
raise ValueError("获取图片URL失败")
# 2. 调用云智OCR接口
ocr_url = "https://api.jkyai.top/API/ocrwzsb.php"
ocr_response = requests.get(
ocr_url,
params={"url": image_url, "type": "json"},
timeout=10
)
ocr_response.raise_for_status()
ocr_result = ocr_response.json()
# 3. 解析结果
words_result = ocr_result.get("words_result", [])
if not words_result:
ocr_text = "未识别到文字内容"
else:
# 合并所有识别的文字
text_lines = [item.get("words", "") for item in words_result]
ocr_text = "\n".join(text_lines)
return ocr_text
except Exception as e:
raise Exception(f"新野OCR识别失败: {e}")
def _vision_model_ocr(self, image: Image.Image) -> str:
"""视觉模型OCR"""
try:
# 获取OCR专用视觉模型配置
vision_model = self.config_manager.get_config("ocr.vision_model")
if not vision_model:
raise ValueError("未配置OCR专用视觉模型")
# 检查必要配置
if not vision_model.get('model_id') or not vision_model.get('api_endpoint') or not vision_model.get('api_key'):
raise ValueError("OCR视觉模型配置不完整")
# 将图片转换为base64
buffer = io.BytesIO()
image.save(buffer, format='PNG')
image_base64 = base64.b64encode(buffer.getvalue()).decode('utf-8')
# 获取OCR提示词
ocr_prompt = vision_model.get('prompt', '请识别图片中的文字内容，并格式化后给我。只返回识别到的文字，不要添加任何解释或说明。')
# 构建请求
messages = [
{
"role": "user",
"content": [
{"type": "text", "text": ocr_prompt},
{
"type": "image_url",
"image_url": {
"url": f"data:image/png;base64,{image_base64}"
}
}
]
}
]
request_data = {
"model": vision_model.get('model_id', ''),
"messages": messages,
"max_tokens": vision_model.get('max_tokens', 1000),
"temperature": vision_model.get('temperature', 0.1)
}
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {vision_model.get('api_key', '')}"
}
response = requests.post(
vision_model.get('api_endpoint', ''),
headers=headers,
json=request_data,
timeout=120
)
if response.status_code != 200:
raise Exception(f"API请求失败: {response.status_code} - {response.text}")
result = response.json()
if 'choices' not in result or not result['choices']:
raise Exception("API响应格式错误")
ocr_text = result['choices'][0]['message']['content'].strip()
return ocr_text
except Exception as e:
raise Exception(f"视觉模型OCR失败: {e}")
class AIRequestThread(QThread):
"""AI请求线程"""
response_completed = pyqtSignal(str) # 响应完成信号
request_failed = pyqtSignal(str) # 请求失败信号
streaming_response = pyqtSignal(str, str) # 流式响应信号 (类型, 内容)
reasoning_content = pyqtSignal(str) # 推理内容信号
def __init__(self, ai_config, prompt, image=None, ocr_text=None):
super().__init__()
self.ai_config = ai_config
self.prompt = prompt
self.image = image
self.ocr_text = ocr_text
self.should_stop = False
def stop_request(self):
"""停止请求"""
self.should_stop = True
def run(self):
"""执行AI请求"""
try:
response = self._send_ai_request()
if not self.should_stop:
self.response_completed.emit(response)
except Exception as e:
if not self.should_stop:
self.request_failed.emit(str(e))
def _send_ai_request(self):
"""发送AI请求"""
# 构建请求消息
messages = []
if self.image and self.ai_config.get('vision_support', False):
# 支持视觉的模型
# 将图片转换为base64
img_byte_arr = io.BytesIO()
self.image.save(img_byte_arr, format='PNG')
img_base64 = base64.b64encode(img_byte_arr.getvalue()).decode('utf-8')
messages.append({
"role": "user",
"content": [
{"type": "text", "text": self.prompt},
{
"type": "image_url",
"image_url": {
"url": f"data:image/png;base64,{img_base64}"
}
}
]
})
else:
# 文本模型或包含OCR文本
content = self.prompt
if self.ocr_text:
content += f"\n\n以下是图片中识别的文字内容：\n{self.ocr_text}"
messages.append({
"role": "user",
"content": content
})
# 检查是否支持流式响应
enable_streaming = self.ai_config.get('enable_streaming', False)
# 构建请求数据
request_data = {
"model": self.ai_config.get('model_id', ''),
"messages": messages,
"max_tokens": self.ai_config.get('max_tokens', 4000),
"temperature": self.ai_config.get('temperature', 0.3),
"stream": enable_streaming
}
# 发送请求
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {self.ai_config.get('api_key', '')}"
}
if enable_streaming:
return self._handle_streaming_response(headers, request_data)
else:
return self._handle_normal_response(headers, request_data)
def _handle_normal_response(self, headers, request_data):
"""处理普通响应"""
response = requests.post(
self.ai_config.get('api_endpoint', ''),
headers=headers,
json=request_data,
timeout=60
)
if response.status_code != 200:
raise Exception(f"API请求失败: {response.status_code} - {response.text}")
result = response.json()
if 'choices' not in result or not result['choices']:
raise Exception("API响应格式错误")
content = result['choices'][0]['message']['content']
# 尝试解析推理内容和回复内容
reasoning_content, response_content = self._parse_reasoning_and_response(content)
if reasoning_content:
self.reasoning_content.emit(reasoning_content)
return response_content or content
def _handle_streaming_response(self, headers, request_data):
"""处理流式响应"""
response = requests.post(
self.ai_config.get('api_endpoint', ''),
headers=headers,
json=request_data,
timeout=60,
stream=True
)
if response.status_code != 200:
raise Exception(f"API请求失败: {response.status_code} - {response.text}")
full_content = ""
for line in response.iter_lines():
if self.should_stop:
break
if line:
line = line.decode('utf-8')
if line.startswith('data: '):
data = line[6:]
if data == '[DONE]':
break
try:
chunk = json.loads(data)
if 'choices' in chunk and chunk['choices']:
delta = chunk['choices'][0].get('delta', {})
# 处理推理内容（只依据API返回的reasoning_content字段）
if 'reasoning_content' in delta and delta['reasoning_content']:
reasoning_content = delta['reasoning_content']
self.reasoning_content.emit(reasoning_content)
# 处理普通响应内容
if 'content' in delta and delta['content']:
content = delta['content']
full_content += content
self.streaming_response.emit("content", content)
except json.JSONDecodeError:
continue
return full_content
def _parse_reasoning_and_response(self, content):
"""解析推理内容和回复内容"""
reasoning_content = ""
response_content = content
# 查找 <thinking> 标签
import re
thinking_pattern = r'<thinking>(.*?)</thinking>'
matches = re.findall(thinking_pattern, content, re.DOTALL)
if matches:
reasoning_content = '\n'.join(matches).strip()
# 移除推理内容，保留回复内容
response_content = re.sub(thinking_pattern, '', content, flags=re.DOTALL).strip()
return reasoning_content, response_content
class AIClientManager(QObject):
"""AI客户端管理器"""
response_completed = pyqtSignal(str) # 响应完成信号
request_failed = pyqtSignal(str) # 请求失败信号
streaming_response = pyqtSignal(str, str) # 流式响应信号
reasoning_content = pyqtSignal(str) # 推理内容信号
def __init__(self, config_manager):
super().__init__()
self.config_manager = config_manager
self.current_thread = None
def send_request(self, model_name, prompt, image=None, ocr_text=None):
"""发送AI请求"""
try:
# 获取AI配置
ai_config = self.config_manager.get_config("ai_model")
if not ai_config:
self.request_failed.emit("AI模型配置不存在")
return
# 停止之前的请求
self.stop_request()
# 创建新的请求线程
self.current_thread = AIRequestThread(ai_config, prompt, image, ocr_text)
self.current_thread.response_completed.connect(self.response_completed)
self.current_thread.request_failed.connect(self.request_failed)
self.current_thread.streaming_response.connect(self.streaming_response)
self.current_thread.reasoning_content.connect(self.reasoning_content)
# 启动线程
self.current_thread.start()
except Exception as e:
self.request_failed.emit(str(e))
def stop_request(self):
"""停止当前请求"""
if self.current_thread and self.current_thread.isRunning():
self.current_thread.stop_request()
self.current_thread.wait()
def cleanup(self):
"""清理资源"""
self.stop_request()
class EmailManager(QObject):
"""邮件管理器"""
email_sent = pyqtSignal()
email_failed = pyqtSignal(str)
def __init__(self, config_manager):
super().__init__()
self.config_manager = config_manager
def send_email(self, subject: str, content: str):
"""发送邮件"""
try:
import smtplib
from email.mime.multipart import MIMEMultipart
from email.mime.text import MIMEText
smtp_config = self.config_manager.get_config("notification.smtp")
if not smtp_config or not all([
smtp_config.get("server"),
smtp_config.get("username"),
smtp_config.get("password"),
smtp_config.get("to_email")
]):
raise ValueError("SMTP配置不完整")
# 创建邮件
msg = MIMEMultipart()
msg['From'] = smtp_config["username"]
msg['To'] = smtp_config["to_email"]
msg['Subject'] = subject
# 添加邮件内容
msg.attach(MIMEText(content, 'plain', 'utf-8'))
# 发送邮件
server = smtplib.SMTP(smtp_config["server"], smtp_config.get("port", 587))
server.starttls()
server.login(smtp_config["username"], smtp_config["password"])
server.send_message(msg)
server.quit()
self.email_sent.emit()
logging.info("邮件发送成功")
except Exception as e:
error_msg = f"邮件发送失败: {e}"
logging.error(error_msg)
self.email_failed.emit(error_msg) | 22,366 | core | py | en | python | code | {"qsc_code_num_words": 2110, "qsc_code_num_chars": 22366.0, "qsc_code_mean_word_length": 5.40616114, "qsc_code_frac_words_unique": 0.19620853, "qsc_code_frac_chars_top_2grams": 0.02165337, "qsc_code_frac_chars_top_3grams": 0.02086438, "qsc_code_frac_chars_top_4grams": 0.01577978, "qsc_code_frac_chars_dupe_5grams": 0.32287192, "qsc_code_frac_chars_dupe_6grams": 0.27816253, "qsc_code_frac_chars_dupe_7grams": 0.22065398, "qsc_code_frac_chars_dupe_8grams": 0.17331463, "qsc_code_frac_chars_dupe_9grams": 0.1289559, "qsc_code_frac_chars_dupe_10grams": 0.12457263, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.00966627, "qsc_code_frac_chars_whitespace": 0.36631494, "qsc_code_size_file_byte": 22366.0, "qsc_code_num_lines": 635.0, "qsc_code_num_chars_line_max": 160.0, "qsc_code_num_chars_line_mean": 35.22204724, "qsc_code_frac_chars_alphabet": 0.79517392, "qsc_code_frac_chars_comments": 0.04269874, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.32400932, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.002331, "qsc_code_frac_chars_string_length": 0.11881188, "qsc_code_frac_chars_long_word_length": 0.03743517, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codepython_cate_ast": 1.0, "qsc_codepython_frac_lines_func_ratio": 0.06293706, "qsc_codepython_cate_var_zero": false, "qsc_codepython_frac_lines_pass": 0.00699301, "qsc_codepython_frac_lines_import": 0.05128205, "qsc_codepython_frac_lines_simplefunc": 0.0, "qsc_codepython_score_lines_no_logic": 0.2027972, "qsc_codepython_frac_lines_print": 0.0} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codepython_cate_ast": 0, "qsc_codepython_frac_lines_func_ratio": 0, "qsc_codepython_cate_var_zero": 0, "qsc_codepython_frac_lines_pass": 0, "qsc_codepython_frac_lines_import": 0, "qsc_codepython_frac_lines_simplefunc": 0, "qsc_codepython_score_lines_no_logic": 0, "qsc_codepython_frac_lines_print": 0} |
0011001011/vizuka | README.md | Data visualization
==================
This is a collection of tools to represent and navigate through high-dimensional datasets.
* The algorithm t-SNE is set as default to construct the 2D space.
* The module should be agnostic of the data provided.
* It ships with MNIST for quick testing.
For commercial use, and user support, please contact Sofian Medbouhi (sofian.medbouhi@free.fr) who propose a business version with additional features.
Usage
-----
### How to install ?
```sh
$ pip install vizuka
```
or clone the repo :)
build-essential is required for the wordcloud
```sh
# apt-get install build-essential
```
### How to run?
```sh
$ vizuka # launch the visualization tool
# For a quick working example with MNIST run :
$ vizuka --mnist
# Similar to downloading MNIST, fit a basic logistic and project in 2D with tSNE
$ vizuka --show-required-files
# To show the format of files you need to launch a data viz
```
But you don't want to use MNIST toy-dataset right ? Here is a complete working example:
```sh
# EXAMPLE :
# you have your preprocessed data in ~/data/set/preprocessed_MYDATASET01.npz
# and predictions in ~/data/set/predict_MYDATASET01.npz
# optionnaly the raw dataset in ~/data/set/raw_data_MYDATASET01.npz
# Run :
$ vizuka-reduce --path ~/data --version MYDATASET01 # projects in 2D
$ vizuka --path ~/data --version MYDATASET01
```
It will search in \_\_package\_\_/data/ the datas but you can force your own with __--path__ argument
* Note that if you are effectively doing big data you should install **MulticoreTSNE** in vizuka/dimension\_reduction/tSNE.py unless you want to discover t-SNE crashed with a segfault. Instructions for installation can be found in requirements/requirements.apt
Plugin structure
----------------
Add your plugins in vizuka/plugins/
You can define your own:
* dimension reduction algorithm
* heatmaps
* clustering engines
* cluster delimiter (frontiers)
* cluster viewer (cf last image)
Only thing to do : use the *vizuka/plugin/dimension\_reduction/* (for e.g) and follow the instruction from *How\_to\_add\_dimension\_reduction\_plugin.py*
Your plugin will be available in all vizuka, in IHM and cmdline without further adjustment
What will I get ?
-----------------
A nice tool to draw clusters, find details about inside distribution and zoom in.
Example with MNIST toy dataset (vizuka --mnist): (**for real life example please scroll down**)
### How to use ?
Navigate inside the 2D space and look at the data, selecting it in the main window (the big one). Data is grouped by cluster, you can select cluster individually (left click).
Main window represents all the data in 2D space. Blue are good-predicted transactions, Red are the bad ones, Green are the special class (by default the label 0).
Below are three subplots :
* a summary of the data inside the selected buckets (see navigation)
* a heatmap of the red/blue/green representation
* a heatmap of the cross-entropy of each bucket empirical distribution with empirical global empirical distribution.
Data viz navigation :
* left click selects a bucket of data
* right click reset all in-memory buckets
Other options:
* clusterize with an algo, a simple grid, or kMeans, DBSCAN...
* visualize the distribution of classes inside selected clusters
* visualize the distribution of features inside selected clusters
* filter by predicted class or by real class.
* filter by any feature you may have in your raw (non-preprocessed) dataset
* export x : export the data you selected in an output.csv
* cluster borders : draw borders between clusters based on bhattacharyya similarity measure, or just all
* choose a different set of predictions to display
What does it needs to be executed ?
-----------------------------------
```sh
$ vizuka --show-required-files
VERSION: string that identifies your dataset (default is MNIST_example)
PATH : data/ is located in /home/sofian/data_viz/manakin-ml-analytics/vizuka, change with --path
FORMAT : all are .npz file
REQUIRED:
=========
+ data/set/preprocessed_inputs_VERSION.npz
------------------------------------------
x: preprocessed inputs, your feature space
y: outputs to be predicted, the "true" class
NB: this is the only mandatory file, the following is highly recommended:
OPTIONAL BUT USEFUL:
===================
+ data/models/predict_VERSION.npz -> optional but recommended
-------------------------------------------------------------
y: predictions returned by your algorithm
NB: should be same formatting as in preprocessed_inputs_VERSION["y"])
if you don't have one, use --force-no-predict
+ data/set/raw_data_VERSION.npz -> optional
--------------------------
x: array of inputs BEFORE preprocessing
probably human-readable, thus useful for visualization
columns: the name of the columns variable in x
NB: this file is used if you run vizuka with
--feature-name-to-display COLUMN_NAME:PLOTTER COLUMN_NAME2:PLOTTER2 or
(see help for details)
GENERATED BY VIZUKA:
====================
+ data/reduced/algoname#VERSION#PARAM1_NAME::VALUE#PARAM2_NAME::VALUE.npz
------------------------------------------------------------------------
x2D: projections of the preprocessed inputs x in a 2D space
NB: you can change default projection parameters and works with several ones
see vizuka-reduce
```
Typical use-case :
------------------
You have your preprocessed data ? Cool, this is the only mandatory file you need. Place it in the folder *data/set/preprocessed_inputs\_VERSION.npz*, VERSION being a string specific to this specific dataset. It must contains at least the key 'x' representing the vectors you learn from. If you have both the correct output and your own predicitons (inside *data/models/* and prediction under npz key "y", default loaded is predict_VERSION.npz, cf --show-requiredfiles).
Optionally you can add a *raw_data_VERSION.npz* file containing raw data non-preprocessed. The vector should be the key "x" and the name of the human-readable "features" in the key "columns".
Now you may want to launch Vizuka ! First project your preprocessed space in 2D with vizuka-reduce, then visualize with vizuka.
And take some coffee.
Or two.
Or three, Vizuka is busy reducing the dimension.
...
Congratulations ! Now you may want to display your 2D-data, as your able to browse your embedded space. Maybe you want to look for a specific cluster. Explore the data with graph options, zoom in and zoom out, and use the filters provided to find an interesting area.
When you are satisfied, click to select clusters. This is quite unefficient you will select small rectangular tiles one by one on a grid, you may want to *Clusterize* using KMeans or DBSCAN.
Great now you can select whole clusters of data at once. But what's in there ? Use the menu Cluster exploration for that. When you are done click on the *export* button to find out in a nicely formatted csv (assuming you provided "raw" data) containing the data in the clusters you selected.
You finished your session but still want to dive in the clusters later ? Just select *Save clusterization* to save your session.
Default parameters
------------------
See config.py
Real life example
=================
| 7,558 | README | md | en | markdown | text | {"qsc_doc_frac_chars_curly_bracket": 0.0, "qsc_doc_frac_words_redpajama_stop": 0.29617193, "qsc_doc_num_sentences": 75.0, "qsc_doc_num_words": 1120, "qsc_doc_num_chars": 7558.0, "qsc_doc_num_lines": 189.0, "qsc_doc_mean_word_length": 4.83928571, "qsc_doc_frac_words_full_bracket": 0.0, "qsc_doc_frac_lines_end_with_readmore": 0.01058201, "qsc_doc_frac_lines_start_with_bullet": 0.0, "qsc_doc_frac_words_unique": 0.35089286, "qsc_doc_entropy_unigram": 5.36897986, "qsc_doc_frac_words_all_caps": 0.03290799, "qsc_doc_frac_lines_dupe_lines": 0.11940299, "qsc_doc_frac_chars_dupe_lines": 0.02827728, "qsc_doc_frac_chars_top_2grams": 0.00645756, "qsc_doc_frac_chars_top_3grams": 0.00830258, "qsc_doc_frac_chars_top_4grams": 0.00664207, "qsc_doc_frac_chars_dupe_5grams": 0.05885609, "qsc_doc_frac_chars_dupe_6grams": 0.04335793, "qsc_doc_frac_chars_dupe_7grams": 0.0, "qsc_doc_frac_chars_dupe_8grams": 0.0, "qsc_doc_frac_chars_dupe_9grams": 0.0, "qsc_doc_frac_chars_dupe_10grams": 0.0, "qsc_doc_frac_chars_replacement_symbols": 0.0, "qsc_doc_cate_code_related_file_name": 1.0, "qsc_doc_num_chars_sentence_length_mean": 26.9962963, "qsc_doc_frac_chars_hyperlink_html_tag": 0.0, "qsc_doc_frac_chars_alphabet": 0.85420294, "qsc_doc_frac_chars_digital": 0.00379927, "qsc_doc_frac_chars_whitespace": 0.16419688, "qsc_doc_frac_chars_hex_words": 0.0} | 1 | {"qsc_doc_frac_chars_replacement_symbols": 0, "qsc_doc_entropy_unigram": 0, "qsc_doc_frac_chars_top_2grams": 0, "qsc_doc_frac_chars_top_3grams": 0, "qsc_doc_frac_chars_top_4grams": 0, "qsc_doc_frac_chars_dupe_5grams": 0, "qsc_doc_frac_chars_dupe_6grams": 0, "qsc_doc_frac_chars_dupe_7grams": 0, "qsc_doc_frac_chars_dupe_8grams": 0, "qsc_doc_frac_chars_dupe_9grams": 0, "qsc_doc_frac_chars_dupe_10grams": 0, "qsc_doc_frac_chars_dupe_lines": 0, "qsc_doc_frac_lines_dupe_lines": 0, "qsc_doc_frac_lines_end_with_readmore": 0, "qsc_doc_frac_lines_start_with_bullet": 0, "qsc_doc_frac_words_all_caps": 0, "qsc_doc_mean_word_length": 0, "qsc_doc_num_chars": 0, "qsc_doc_num_lines": 0, "qsc_doc_num_sentences": 0, "qsc_doc_num_words": 0, "qsc_doc_frac_chars_hex_words": 0, "qsc_doc_frac_chars_hyperlink_html_tag": 0, "qsc_doc_frac_chars_alphabet": 0, "qsc_doc_frac_chars_digital": 0, "qsc_doc_frac_chars_whitespace": 0} |
0011001011/vizuka | setup.py | from setuptools import setup, find_packages
import os
data = {
'vizuka': [
'data/set/.gitkeep',
'data/models/.gitkeep',
'data/cache/.gitkeep',
'data/saved_clusters/.gitkeep',
'data/reduced/.gitkeep',
'example/tsne#MNIST_example#learning_rate::1000#n_iter::12000#perplexity::50.npz',
],
}
setup(
name='Vizuka',
version='0.36.1',
packages=find_packages(), #['vizuka/'],
package_data=data,
entry_points={
'console_scripts': [
'vizuka=vizuka.launch_viz:main',
'vizuka-reduce=vizuka.launch_reduce:main',
],
},
description=
'Represents your high-dimensional datas in a 2D space and play with it',
long_description=open(
os.path.join(os.path.dirname(__file__), 'README.md')).read(),
install_requires=open(
os.path.join(
os.path.dirname(__file__),
'vizuka/requirements/requirements.txt')).read(),
license='GPL V3',
author='Sofian Medbouhi',
author_email='sof.m.sk@free.fr',
)
| 1,059 | setup | py | en | python | code | {"qsc_code_num_words": 123, "qsc_code_num_chars": 1059.0, "qsc_code_mean_word_length": 5.06504065, "qsc_code_frac_words_unique": 0.65853659, "qsc_code_frac_chars_top_2grams": 0.070626, "qsc_code_frac_chars_top_3grams": 0.03210273, "qsc_code_frac_chars_top_4grams": 0.04494382, "qsc_code_frac_chars_dupe_5grams": 0.09951846, "qsc_code_frac_chars_dupe_6grams": 0.09951846, "qsc_code_frac_chars_dupe_7grams": 0.09951846, "qsc_code_frac_chars_dupe_8grams": 0.09951846, "qsc_code_frac_chars_dupe_9grams": 0.0, "qsc_code_frac_chars_dupe_10grams": 0.0, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.0210136, "qsc_code_frac_chars_whitespace": 0.23607177, "qsc_code_size_file_byte": 1059.0, "qsc_code_num_lines": 37.0, "qsc_code_num_chars_line_max": 91.0, "qsc_code_num_chars_line_mean": 28.62162162, "qsc_code_frac_chars_alphabet": 0.74907293, "qsc_code_frac_chars_comments": 0.01133144, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.05714286, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.416826, "qsc_code_frac_chars_long_word_length": 0.22179732, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codepython_cate_ast": 1.0, "qsc_codepython_frac_lines_func_ratio": 0.0, "qsc_codepython_cate_var_zero": false, "qsc_codepython_frac_lines_pass": 0.0, "qsc_codepython_frac_lines_import": 0.05714286, "qsc_codepython_frac_lines_simplefunc": 0.0, "qsc_codepython_score_lines_no_logic": 0.05714286, "qsc_codepython_frac_lines_print": 0.0} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codepython_cate_ast": 0, "qsc_codepython_frac_lines_func_ratio": 0, "qsc_codepython_cate_var_zero": 0, "qsc_codepython_frac_lines_pass": 0, "qsc_codepython_frac_lines_import": 0, "qsc_codepython_frac_lines_simplefunc": 0, "qsc_codepython_score_lines_no_logic": 0, "qsc_codepython_frac_lines_print": 0} |
0011001011/vizuka | vizuka/launch_viz.py | """
This is the main script to launch everything
Is able to reduce the data and launch a vizualization
from it.
"""
import logging
import os
import argparse
import matplotlib
matplotlib.use('Qt5Agg') # noqa
import numpy as np
from pyfiglet import Figlet
from vizuka import data_loader
from vizuka import vizualization
from vizuka import launch_reduce
from vizuka import cluster_viewer
from vizuka import heatmap
logger = logging.getLogger()
logger.setLevel(logging.WARN)
def main():
"""
See --help if you want help
"""
from vizuka.config import (
BASE_PATH,
DATA_PATH,
VERSION,
REDUCED_DATA_PATH,
MODEL_PATH,
INPUT_FILE_BASE_NAME,
PROJECTION_DEFAULT_PARAMS,
DEFAULT_PROJECTOR,
path_builder,
)
print(Figlet().renderText('Vizuka'))
plotters_builtin, plotters_extra = cluster_viewer.list_plotter()
plotters_available = {**plotters_builtin, **plotters_extra}
heatmaps_builtin, heatmaps_extra = heatmap.list_heatmap()
heatmaps_available = {**heatmaps_builtin, **heatmaps_extra}
parser = argparse.ArgumentParser()
parser.add_argument(
'--mnist', action='store_true',
help='download, fit, and vizualize MNIST dataset.')
parser.add_argument(
'--show-required-files', action='store_true',
help='show all the required files for optimal use',
)
parser.add_argument(
'-p', '--path',
help='change the location of your data/ folder, and auto-creates data/set/ data/reduced/ data/graph/ data/models/')
parser.add_argument(
'-s', '--feature_to_show', action='append',
help='(available later in IHM) Usage: -s MY_COLUMN_NAME:PLOTTER with COLUMN_NAME with value in'
' data/set/raw_data.npz["columns"] (see --show-required-files)'
' and PLOTTER being a value in {}. Adds this non-preprocessed/human-readable feature to the cluster view'.format(list(plotters_available.keys())))
parser.add_argument(
'-h1', '--heatmap1',
help='Specify the 1st heatmap to show, heatmaps available:{}'.format(list(heatmaps_available.keys())))
parser.add_argument(
'-h2', '--heatmap2',
help='Specify the 2nd heatmap to show')
parser.add_argument(
'-v', '--version', type=str,
help='(optional) specify a version of the files to load/generate (see vizuka --show-required-files), currently: '+VERSION)
parser.add_argument(
'--force-no-predict', action="store_true",
help='(not recommended) do not load a predictions file : vizualize as if you predicted with 100percent accuracy')
parser.add_argument(
'--no-vizualize', action="store_true",
help='(for debug) do not prepare a nice data vizualization')
parser.add_argument(
'--no-plot', action="store_true",
help='(for debug) do not show a nice data vizualization (but prepare it nonetheless)')
parser.add_argument(
'--verbose', action="store_true",
help="verbose mode")
parser.set_defaults(
heatmap1 ='accuracy',
heatmap2 ='entropy',
no_plot =False,
no_vizualize =False,
show_required_files =False,
force_no_predict =False,
mnist =False,
version =VERSION,
path =os.path.join(os.path.dirname(__file__),BASE_PATH),
feature_to_show =[],
verbose = False,
)
args = parser.parse_args()
path = args.path
(
DATA_PATH,
REDUCED_DATA_PATH,
MODEL_PATH,
_,
_,
_,
) = path_builder(path)
no_vizualize = args.no_vizualize
no_plot = args.no_plot
version = args.version
features_name_to_display = args.feature_to_show
force_no_predict = args.force_no_predict
show_required_files=args.show_required_files
heatmap1 = args.heatmap1
heatmap2 = args.heatmap2
verbose = args.verbose
print(
'Generate 2D projections with cmd "vizuka-reduce"\n'
"VERSION: Loading dataset labeled {} (cf --version)".format(version)
)
if verbose:
logger.setLevel(logging.DEBUG)
if args.show_required_files:
print(
'\n\nVizuka needs the following files :\n\n'
'\nVERSION: string that identifies your dataset (default is MNIST_example)\n'
'PATH\t: data/ is located in '+str(os.path.dirname(__file__))+', change with --path\n'
'FORMAT\t: all are .npz file\n\n'
'REQUIRED:\n'
'=========\n'
'\t + data/set/preprocessed_inputs_VERSION.npz\n'
'\t ------------------------------------------\n'
'\t\t x:\t preprocessed inputs, your feature space\n'
'\t\t y:\t outputs to be predicted, the "true" class\n'
'\t\t NB:\t this is the only mandatory file, the following is highly recommended:\n'
'\n\n'
'OPTIONAL BUT USEFUL:\n'
'===================\n'
'\t + data/models/predict_VERSION.npz -> optional but recommended\n'
'\t -------------------------------------------------------------\n'
'\t\t y:\t predictions returned by your algorithm\n'
'\t\t NB:\t should be same formatting as in preprocessed_inputs_VERSION["y"])\n'
"\t\t\t if you don't have one, use --force-no-predict\n"
'\n\n'
'\t + data/set/raw_data.npz -> optional\n'
'\t --------------------------\n'
'\t\t x:\t\t array of inputs BEFORE preprocessing\n'
'\t\t columns:\t the name of the columns variable in x\n'
'\t\t NB:\t this file is used if you run vizuka with\n'
'\t\t\t --feature-name-to-display COLUMN_NAME:PLOTTER or\n'
'\t\t\t in IHM -> Cluster exploration / Add cluster info\n'
'\t\t\t (see help for details)\n'
'\n\n'
'GENERATED BY VIZUKA:\n'
'====================\n'
'\t + data/reduced/algoname#VERSION#PARAM1_NAME::VALUE#PARAM2_NAME::VALUE.npz\n'
'\t ------------------------------------------------------------------------\n'
'\t\t x2D:\t projections of the preprocessed inputs x in a 2D space\n'
'\t\t NB:\t you can change default projection parameters and works with several ones\n' '\t\t\t see vizuka-reduce'
'\n\nSee '+str(os.path.join(os.path.dirname(__file__), 'data'))+' for real example, if you doubt\n'
)
return
if args.mnist:
from vizuka.example import load_mnist
version = load_mnist.version
features_name_to_display = ['image:images']
new_fntd = {}
error_msg = 'Argument should be COLUMN_NAME:PLOTTER with plotter in {}'.format(list(plotters_available.keys()))
e = Exception(error_msg)
for feature_name in features_name_to_display:
if ':' not in feature_name:
raise e
k,v = feature_name.split(':')
# TODO if v not in cluster_diving.plotter.keys():
# raise e
plotters = new_fntd.get(k, [])
plotters.append(v)
new_fntd[k] = plotters
features_name_to_display = new_fntd
logger.info("Starting script")
logger.info("preprocessed_dataset=loading")
(
x,
y,
class_encoder,
class_decoder,
loaded,
preprocessed_filename,
) = data_loader.load_preprocessed(
file_base_name = INPUT_FILE_BASE_NAME,
path = DATA_PATH,
version = version,
)
if not loaded:
logging.warn("No data found\nCorresponding file not found: {}\nPlease check --show-required-files".format(preprocessed_filename))
if version=='MNIST_example':
print(
'\n\nIf you are trying to load the MNIST example, you need to launch'
' "vizuka --mnist" in order to download the test data (code in vizuka/example/)'
)
return
logger.info('preprocessed_dataset=loaded')
projections_available = data_loader.list_projections(REDUCED_DATA_PATH, version=version)
if len(projections_available)==0:
logger.warn("2D_dataset=No reduced data found! Please use vizuka-reduce to generate some")
return
choice_list, choice_dict = "", {}
for i,(method, version_, params), in enumerate(projections_available):
param_str = ''.join(["\t\t\t{}: {}\n".format(name, value) for name, value in params.items()])
choice_list+="\t [{}]: \t{}\n\t\tparameters:\n{}\n".format(i, method, param_str)
choice_dict[i]=method
choice = input( "Projections datasets available: (generate more with vizuka-reduce)"
")\n"+choice_list+"Which dataset number to load?\n\n\t[?] > ")
try:
choice_int=int(choice)
except ValueError:
logging.warn("Please enter a valid dataset number! (e.g: 0)\nABORTING")
return
try:
selected_method = choice_dict[choice_int]
_, _, selected_params = projections_available[choice_int]
except KeyError:
logging.warn("Don't be silly, enter a valid int number (between 0 and {})".format(len(choice_dict)-1))
logging.warn("ABORTING")
return
x_2D = data_loader.load_projection(
algorithm_name = selected_method,
parameters = selected_params,
version = version,
path = REDUCED_DATA_PATH,
)
###############
# PREDICT
if force_no_predict:
x_predicted = y
else:
try:
logger.info('predictions=loading')
x_predicted = data_loader.load_predict(
path=MODEL_PATH,
version=version,
)
logger.info('predictions=ready')
except FileNotFoundError:
logger.warn((
"Nothing found in {}, no predictions to vizualize\n"
"if this is intended you can force the vizualization"
"with --force_no_predict :\n{}\n"
).format(MODEL_PATH, os.listdir(MODEL_PATH)))
return
raw = data_loader.load_raw(version, DATA_PATH)
if raw:
logger.info("loading raw transactions for analysis..")
raw_data, raw_columns = raw
else:
logger.info('no raw data provided, all cluster vizualization disabled! (-s and -f options)')
raw_data = np.array([])
raw_columns = []
features_name_to_display = {}
if not no_vizualize:
f = vizualization.Vizualization(
projected_input=x_2D,
predicted_outputs=x_predicted,
raw_inputs=raw_data,
raw_inputs_columns=raw_columns,
correct_outputs=y,
resolution=200,
class_decoder=class_decoder,
class_encoder=class_encoder,
special_class='x',
nb_of_clusters=120,
features_name_to_display = features_name_to_display,
heatmaps_requested = [heatmap1, heatmap2],
output_path=os.path.join('output.csv'),
base_path=path,
version=version,
)
if not no_plot:
f.plot()
f.show()
return f
if __name__ == '__main__':
main()
| 11,475 | launch_viz | py | en | python | code | {"qsc_code_num_words": 1375, "qsc_code_num_chars": 11475.0, "qsc_code_mean_word_length": 4.73018182, "qsc_code_frac_words_unique": 0.22109091, "qsc_code_frac_chars_top_2grams": 0.00768758, "qsc_code_frac_chars_top_3grams": 0.00691882, "qsc_code_frac_chars_top_4grams": 0.02260148, "qsc_code_frac_chars_dupe_5grams": 0.09501845, "qsc_code_frac_chars_dupe_6grams": 0.03305658, "qsc_code_frac_chars_dupe_7grams": 0.0202952, "qsc_code_frac_chars_dupe_8grams": 0.0098401, "qsc_code_frac_chars_dupe_9grams": 0.0, "qsc_code_frac_chars_dupe_10grams": 0.0, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.00438329, "qsc_code_frac_chars_whitespace": 0.28427015, "qsc_code_size_file_byte": 11475.0, "qsc_code_num_lines": 316.0, "qsc_code_num_chars_line_max": 160.0, "qsc_code_num_chars_line_mean": 36.31329114, "qsc_code_frac_chars_alphabet": 0.78753196, "qsc_code_frac_chars_comments": 0.01812636, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.15589354, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.02281369, "qsc_code_frac_chars_string_length": 0.35034741, "qsc_code_frac_chars_long_word_length": 0.06529485, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.00316456, "qsc_code_frac_lines_assert": 0.0, "qsc_codepython_cate_ast": 1.0, "qsc_codepython_frac_lines_func_ratio": 0.00380228, "qsc_codepython_cate_var_zero": false, "qsc_codepython_frac_lines_pass": 0.0, "qsc_codepython_frac_lines_import": 0.04942966, "qsc_codepython_frac_lines_simplefunc": 0.0, "qsc_codepython_score_lines_no_logic": 0.07984791, "qsc_codepython_frac_lines_print": 0.01520913} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codepython_cate_ast": 0, "qsc_codepython_frac_lines_func_ratio": 0, "qsc_codepython_cate_var_zero": 0, "qsc_codepython_frac_lines_pass": 0, "qsc_codepython_frac_lines_import": 0, "qsc_codepython_frac_lines_simplefunc": 0, "qsc_codepython_score_lines_no_logic": 0, "qsc_codepython_frac_lines_print": 0} |
0011001011/vizuka | vizuka/data_loader.py | import logging
import os
import itertools
import numpy as np
from vizuka import dimension_reduction
from vizuka.dimension_reduction.projector import Projector
from vizuka.config import (
MODEL_PATH,
VERSION,
DEFAULT_PREDICTOR,
PROJECTION_DEFAULT_PARAMS,
REDUCED_DATA_PATH,
INPUT_FILE_BASE_NAME,
DATA_PATH,
RAW_NAME,
)
def load_predict(path=MODEL_PATH, version=VERSION, namePredictor=DEFAULT_PREDICTOR):
"""
Simply load the predictions associated with the VERSION data
"""
logging.info("trying to load {}".format(path + namePredictor +'_'+ version + '.npz'))
return np.load(path + namePredictor + version + '.npz')['y']
def load_predict_byname(filename, path=MODEL_PATH):
"""
Simply load the predictions associated with the VERSION data
"""
full_path = os.path.join(path, filename)
logging.info("trying to load {}".format(full_path))
return np.load(os.path.join(path, filename))['y']
def list_projections(reduced_path, version):
"""
Returns a list containing [(algo_name, parameters),..] found in :param reduced_path:
"""
files = [filename for filename in os.listdir(reduced_path) if (".npz" in filename) and (version in filename)]
return [Projector.get_param_from_name(filename[:-4]) for filename in files]
def load_projection(algorithm_name, parameters, version, path):
logging.info("data_loader=loading projection:\n\talgorithm:{}\n\tparameters:{}".format(
algorithm_name,
parameters,
))
algo_builder = dimension_reduction.make_projector(algorithm_name)
algo = algo_builder(**parameters)
projection = algo.load_projection(version=version, path=path)
logging.info("data_loader=ready")
return projection
def load_raw(version, path):
raw_filename = os.path.join(path, RAW_NAME + version + '.npz')
if os.path.exists(raw_filename):
raw_ = np.load(raw_filename)
return raw_["x"], raw_["columns"]
else:
return None
def load_preprocessed(
file_base_name=INPUT_FILE_BASE_NAME,
path=DATA_PATH,
version=VERSION,
):
"""
Loads and returns the data for tSNE
One-hotted and regular ML-encoding
File to load should :
- be in path
- has name "(INPUT_FILE_BASE_NAME)_x_y_(VERSION).npz"
(VERSION) is for e.g "_20170614"
(FILE_BASE_NAME) if for e.g 'processed_predictions' or 'one_hot'
- contains entry x with input data
- contains entry y with output data (possible_outputs_list to predict)
- optionnaly an encoder to translate machine-readable possible_outputs_list to human-readable possible_outputs_list
(actually it is the opposite e.g: {604600:[False, True, False, .., False]})
:return: (input for t-SNE, classes, encoder (humantomachine class possible_outputs_list),
decoder (machinetohuman possible_outputs_list), loaded, path_of_filename)
Note that encoder/decoder are assumed trivial if no encoder are found in npz
"""
full_path = os.path.join(path, INPUT_FILE_BASE_NAME + version + '.npz')
if not os.path.exists(full_path):
loaded = False
return np.array([]), np.array([]), lambda x:x, lambda x:x, loaded, full_path
else:
xy = np.load(full_path)
loaded = True
x, y = xy['x'], xy['y']
class_encoder = {y: y for y in set(y)}
class_decoder = lambda x: x # noqa
x = xy['x']
if 'y' in xy.keys():
y = xy['y']
del xy
return (np.array(x), np.array(y), class_encoder, class_decoder, loaded, full_path)
elif 'y' + '_decoded' in xy.keys():
y_decoded = xy['y' + '_decoded']
del xy
return (np.array(x), np.array(y_decoded), class_encoder, class_decoder, loaded, full_path)
| 3,904 | data_loader | py | en | python | code | {"qsc_code_num_words": 516, "qsc_code_num_chars": 3904.0, "qsc_code_mean_word_length": 4.78100775, "qsc_code_frac_words_unique": 0.26937984, "qsc_code_frac_chars_top_2grams": 0.02594244, "qsc_code_frac_chars_top_3grams": 0.02918525, "qsc_code_frac_chars_top_4grams": 0.02756384, "qsc_code_frac_chars_dupe_5grams": 0.20105391, "qsc_code_frac_chars_dupe_6grams": 0.13619781, "qsc_code_frac_chars_dupe_7grams": 0.09485205, "qsc_code_frac_chars_dupe_8grams": 0.0640454, "qsc_code_frac_chars_dupe_9grams": 0.0640454, "qsc_code_frac_chars_dupe_10grams": 0.0, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.00502681, "qsc_code_frac_chars_whitespace": 0.23565574, "qsc_code_size_file_byte": 3904.0, "qsc_code_num_lines": 110.0, "qsc_code_num_chars_line_max": 124.0, "qsc_code_num_chars_line_mean": 35.49090909, "qsc_code_frac_chars_alphabet": 0.82171582, "qsc_code_frac_chars_comments": 0.27356557, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.05970149, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.06210952, "qsc_code_frac_chars_long_word_length": 0.01617053, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codepython_cate_ast": 1.0, "qsc_codepython_frac_lines_func_ratio": 0.08955224, "qsc_codepython_cate_var_zero": false, "qsc_codepython_frac_lines_pass": 0.0, "qsc_codepython_frac_lines_import": 0.10447761, "qsc_codepython_frac_lines_simplefunc": 0.0, "qsc_codepython_score_lines_no_logic": 0.32835821, "qsc_codepython_frac_lines_print": 0.0} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codepython_cate_ast": 0, "qsc_codepython_frac_lines_func_ratio": 0, "qsc_codepython_cate_var_zero": 0, "qsc_codepython_frac_lines_pass": 0, "qsc_codepython_frac_lines_import": 0, "qsc_codepython_frac_lines_simplefunc": 0, "qsc_codepython_score_lines_no_logic": 0, "qsc_codepython_frac_lines_print": 0} |
0011001011/vizuka | vizuka/vizualization.py | """
Module built around the class Vizualization
It is the main module that draws a nice IHM interface to explore your data
See class Vizualization
"""
import sys
import os
import logging
from collections import Counter
import pickle
import csv
from scipy import stats
import numpy as np
import matplotlib
matplotlib.use('Qt5Agg') # noqa
from matplotlib.gridspec import GridSpec
from matplotlib import pyplot as plt
from vizuka.helpers import viz_helper
from vizuka.graphics import drawing
from vizuka import clustering
from vizuka import frontier
from vizuka import data_loader
from vizuka import heatmap
from vizuka.graphics.qt_handler import Cluster_viewer
from vizuka.graphics.qt_handler import Viz_handler
from vizuka.config import (
path_builder,
BASE_PATH,
)
class Vizualization:
"""
This class contains all the tools for the vizualiation
It is created with only the vector of predictions (containing possible_outputs_list) with its decoder function
Resolution is the size of the grid of the viz, used for heatmap and clustering
Mouse control and keyboard shortcuts are used (later: QtButtons) ..seealso:: self.controls
"""
def __init__(
self,
raw_inputs,
raw_inputs_columns,
projected_input,
predicted_outputs,
correct_outputs,
resolution=100,
special_class='0',
nb_of_clusters=120,
features_name_to_filter=[],
features_name_to_display={},
heatmaps_requested = ['entropy', 'accuracy'],
color_mode = 'by_prediction',
class_decoder=(lambda x: x), class_encoder=(lambda x: x),
output_path='output.csv',
base_path=BASE_PATH,
version='',
):
"""
Central function, draw heatmap + scatter plot + zoom + annotations on tSNE data
:param predicted_outputs: vector of predicted possible_outputs_list
:param correct_outputs: vector of true possible_outputs_list
:param projected_input: vector of t-SNE projected data (i.e project_input[index] = (x, y)
:param class_dn_jobs=4, ecoder: function to decode possible_outputs_list machinetohuman
:param class_encoder: dict to encode possible_outputs_list humantomachine
"""
logging.info("Vizualization=generating")
self.last_time = {}
self.manual_cluster_color = 'cyan'
(
self.data_path,
self.reduced_data_path,
self.model_path,
self.graph_path,
self.cache_path,
self.saved_clusters_path,
) = path_builder(base_path)
self.predictors = [name for name in os.listdir(self.model_path) if version in name]
self.output_path = output_path
self.saved_clusters = [f for f in os.listdir(self.saved_clusters_path) if version in f]
self.version = version
def str_with_default_value(value):
if not value:
return str(special_class)
return str(value)
self.correct_outputs = [str_with_default_value(correct_output) for correct_output in correct_outputs]
self.correct_outputs_original = self.correct_outputs
self.prediction_outputs = [str_with_default_value(predicted_output) for predicted_output in predicted_outputs]
self.prediction_outputs_original = self.prediction_outputs
self.projected_input = projected_input
self.projected_input_original = self.projected_input
self.x_raw = raw_inputs
self.x_raw_original = self.x_raw
self.x_raw_columns = raw_inputs_columns
self.nb_of_clusters = nb_of_clusters
self.class_decoder = class_decoder
self.special_class = str(special_class)
self.heatmaps_requested = heatmaps_requested
self.features_name_to_filter = features_name_to_filter
self.correct_class_to_display = {}
self.predicted_class_to_display = {}
self.feature_to_display_by_col = {}
self.features_to_display = features_name_to_display
self.color_mode = color_mode
self.cluster_view_selected_indexes = []
self.left_clicks = set()
self.selected_clusters = set()
#self.possible_outputs_list = list({self.class_decoder(y_encoded) for y_encoded in self.correct_outputs})
self.possible_outputs_set = set(self.correct_outputs).union(set(self.prediction_outputs))
self.possible_outputs_set.discard(None)
self.filters = {
'PREDICTIONS':self.possible_outputs_set,
'GROUND_TRUTH':self.possible_outputs_set,
**{k:set() for k in features_name_to_filter},
}
self.possible_outputs_list = list(self.possible_outputs_set)
self.possible_outputs_list.sort()
# logging.info("correct outputs : %", self.correct_outputs)
self.projection_points_list_by_correct_output = {y: [] for y in self.correct_outputs}
self.index_by_true_output = {class_:[] for class_ in self.possible_outputs_list}
self.nb_of_individual_by_true_output = {}
for index, projected_input in enumerate(self.projected_input):
self.projection_points_list_by_correct_output[self.correct_outputs[index]].append(projected_input)
self.index_by_true_output[self.correct_outputs[index]].append(index)
# convert dict values to np.array
for possible_output in self.projection_points_list_by_correct_output:
self.projection_points_list_by_correct_output[possible_output] = np.array(
self.projection_points_list_by_correct_output[possible_output])
self.nb_of_individual_by_true_output[possible_output] = len(
self.projection_points_list_by_correct_output[possible_output])
self.projection_points_list_by_correct_output_original = self.projection_points_list_by_correct_output
self.resolution = resolution # counts of tiles per row/column
self.shift_held = False
self.ctrl_held = False
self.local_effectif = {}
self.local_accuracy = {}
self.local_confusion_by_class = {
class_:
{
class__:0 for class__ in self.possible_outputs_list} for class_ in self.possible_outputs_list
}
self.local_bad_count_by_class = {class_:0 for class_ in self.possible_outputs_list}
self.local_classes = set()
self.local_sum = 0
self.cursor_ids = [0]
# Get the real possible_outputs_list found in true y
self.amplitude = viz_helper.find_amplitude(self.projected_input_original)
mesh = np.meshgrid(
np.arange(
-self.amplitude,
self.amplitude,
self.amplitude/(self.resolution/2)
),
np.arange(
-self.amplitude,
self.amplitude,
self.amplitude/(self.resolution/2)
),
)
self.size_centroid = 2 * self.amplitude / self.resolution
self.mesh_centroids = np.c_[mesh[0].ravel(), mesh[1].ravel()]
self.calculate_prediction_projection_arrays()
logging.info('clustering engine=fitting')
self.clusterizer = clustering.make_clusterizer(
xs=self.projected_input_original,
nb_of_clusters=self.nb_of_clusters,
mesh=self.mesh_centroids,
method='grid',
)
logging.info('clustering engine=ready')
self.normalize_frontier = True
def calculate_prediction_projection_arrays(self):
"""
Update all the sets which use true/false flags from predictions
When to use ? -> if you change (or first load) your predictor
"""
(
self.index_bad_predicted,
self.index_good_predicted,
self.index_not_predicted,
) = viz_helper.separate_prediction(
self.prediction_outputs,
self.correct_outputs,
self.special_class,
)
(
self.well_predicted_projected_points_array,
self.mispredicted_projected_points_array,
self.not_predicted_projected_points_array,
) = viz_helper.get_projections_from_index(
self.index_good_predicted,
self.index_bad_predicted,
self.index_not_predicted,
self.projected_input,
)
self.accuracy_by_class = viz_helper.get_accuracy_by_class(
self.index_by_true_output,
self.correct_outputs,
self.prediction_outputs,
self.possible_outputs_list)
def reload_predict(self, filename):
"""
Call this function if the predictor set has changed
filename: the name of the predictions file to load, should
be located in the self.model_path folder
"""
old_left_clicks = self.left_clicks
self.prediction_outputs = data_loader.load_predict_byname(filename, path=self.model_path)
self.prediction_outputs_original = self.prediction_outputs
self.correct_outputs = self.correct_outputs_original
self.projected_input = self.projected_input_original
self.calculate_prediction_projection_arrays()
self.print_global_summary(self.global_summary_axe)
self.init_clusters()
self.update_all_heatmaps()
self.reset_summary()
self.reset_viz()
self.conciliate_filters(self.filters)
for click in old_left_clicks:
self.do_left_click(click)
self.refresh_graph()
def filter_by_feature(self, feature_col, selected_features):
"""
Updates the list of index to display, filter with :
feature_col: the column of the feature in "originals"
selected_feature_list: list of checked/unchecked feature to display
"""
featured_data_to_display = {
widget.class_ for widget in selected_features[feature_col] if widget.isChecked()
}
self.filters[feature_col] = featured_data_to_display
self.conciliate_filters(self.filters)
def filter_by_feature_old(self, feature_col, selected_feature_list):
"""
Updates the list of index to display, filter with :
feature_col: the column of the feature in "originals"
selected_feature_list: list of checked/unchecked feature to display
"""
featured_data_to_display = [
item for item, selected in selected_feature_list.items() if selected
]
self.feature_to_display_by_col[feature_col] = featured_data_to_display
self.filters[feature_col] = featured_data_to_display
# self.display_by_filter()
self.conciliate_filters(self.filters)
def filter_by_correct_class(self, selected_outputs_class_list):
"""
Filter by class, on the TRUE class of each point
"""
self.correct_class_to_display = {
widget.class_ for widget in selected_outputs_class_list if widget.isChecked()
}
self.filters["GROUND_TRUTH"] = self.correct_class_to_display
# self.display_by_filter()
self.conciliate_filters(self.filters)
def filter_by_predicted_class(self, selected_outputs_class_list):
"""
Filter by class, on the PREDICTED class of each point
"""
self.predicted_class_to_display = {
widget.class_ for widget in selected_outputs_class_list if widget.isChecked()
}
self.filters["PREDICTIONS"] = self.predicted_class_to_display
# self.display_by_filter()
self.conciliate_filters(self.filters)
def load_only_some_indexes(self, indexes):
self.prediction_outputs = [self.prediction_outputs_original[i] for i in indexes]
self.projected_input = [self.projected_input_original[i] for i in indexes]
self.correct_outputs = [self.correct_outputs_original[i] for i in indexes]
self.x_raw = [self.x_raw_original[i] for i in indexes]
self.projection_points_list_by_correct_output = {y: [] for y in self.correct_outputs}
self.index_by_true_output = {class_:[] for class_ in self.possible_outputs_list}
for index, projected_input in enumerate(self.projected_input):
self.projection_points_list_by_correct_output[self.correct_outputs[index]].append(projected_input)
self.index_by_true_output[self.correct_outputs[index]].append(index)
# convert dict values to np.array
for possible_output in self.projection_points_list_by_correct_output:
self.projection_points_list_by_correct_output[possible_output] = np.array(
self.projection_points_list_by_correct_output[possible_output])
self.nb_of_individual_by_true_output[possible_output] = len(
self.projection_points_list_by_correct_output[possible_output])
self.calculate_prediction_projection_arrays()
self.init_clusters()
self.print_global_summary(self.global_summary_axe)
self.update_all_heatmaps()
self.update_summary()
self.print_summary(self.summary_axe)
self.update_cluster_view()
def filters_active(self):
"""
True if some filters are active
"""
additional_filters_active = False
other_filters = {k:v for k,v in self.filters.items() if k!="PREDICTIONS" and k!="GROUND_TRUTH"}
for col in other_filters: # other filters are column number identifying features
additional_filters_active = additional_filters_active or other_filters[col]
return self.filters["GROUND_TRUTH"] or self.filters["PREDICTIONS"] or additional_filters_active
def conciliate_filters(self, filters):
saved_zoom = (self.ax.get_xbound(), self.ax.get_ybound())
to_display = set(range(len(self.projected_input_original)))
filtered = filters["GROUND_TRUTH"]
to_display = to_display.intersection(set([
idx for idx, class_ in enumerate(self.correct_outputs_original) if class_ in filtered]))
filtered = filters["PREDICTIONS"]
to_display = to_display.intersection(set([
idx for idx, class_ in enumerate(self.prediction_outputs_original) if class_ in filtered]))
other_filters = {k:v for k,v in filters.items() if k!="PREDICTIONS" and k!="GROUND_TRUTH"}
for col in other_filters: # other filters are column number identified features
filtered_by_feature = {idx for idx, x in enumerate(self.x_raw_original) if x[col] in other_filters[col]}
to_display = to_display.intersection(filtered_by_feature)
viz_helper.remove_pathCollection(self.ax)
self.load_only_some_indexes(to_display)
drawing.draw_scatterplot(
self,
self.ax,
color_mode = self.color_mode,
)
self.ax.set_xbound(saved_zoom[0])
self.ax.set_ybound(saved_zoom[1])
self.refresh_graph()
#######################################
# Similarity functions to draw clusters
def onclick(self, event):
"""
Mouse event handler
Actions on mouse button pressed
1 : select a tile (and a class)
2 : find similar tiles
3 : reset vizualization (graph+summary)
"""
x = event.xdata
y = event.ydata
button = event.button
left_click, right_click = ((button == 1), (button == 3))
self.summary_axe.clear()
self.summary_axe.axis('off')
if left_click:
self.do_left_click((x,y))
elif right_click:
self.do_right_click((x,y))
self.refresh_graph()
def do_left_click(self, xy):
x, y = xy
if (x is None) or (y is None): # clicks out of the screen
return
# Register this click for replay
self.left_clicks.add((x,y))
# find associated cluster and gather data
clicked_cluster = self.clusterizer.predict([(x,y)])[0]
self.selected_clusters.add(clicked_cluster)
self.delimit_cluster(clicked_cluster, color=self.manual_cluster_color)
self.update_summary()
self.print_summary(self.summary_axe)
# shows additional info if requested (argument -s)
self.update_cluster_view()
# self.cluster_view.update_cluster_view(
# clicked_cluster,
# self.index_by_cluster_label,
# indexs_good = self.index_good_predicted,
# indexes_bad = self.index_bad_predicted,
# )
def do_right_click(self, xy):
logging.info("Cleaning state, unselecting clusters, redrawing")
# reboot vizualization
self.left_clicks = set()
self.selected_clusters = set()
self.reset_summary()
self.clear_cluster_view()
self.reset_viz()
def reset_viz(self):
"""
Reset (graphically) the vizualization
..note:: does not touch the summary array, for this use self.reset_summary()
"""
logging.info("scatterplot: removing specific objects")
self.left_clicks = set()
self.selected_clusters = set()
for ax in self.axes_needing_borders:
for i in ax.get_children():
if isinstance(i, matplotlib.collections.PathCollection):
i.remove()
elif isinstance(i, matplotlib.lines.Line2D):
if i.get_color() == self.manual_cluster_color:
i.remove()
logging.info("scatterplot: drawing observations")
if self.cluster_view:
self.clear_cluster_view()
drawing.draw_scatterplot(
self,
self.ax,
color_mode = self.color_mode,
)
logging.info("scatterplot: ready")
def reset_summary(self):
"""
Reset the local summary
"""
self.local_effectif = {}
self.local_accuracy = {}
self.local_confusion_by_class = {
output_class: {
other_output_class:0 for other_output_class in self.possible_outputs_list
}
for output_class in self.possible_outputs_list
}
self.local_bad_count_by_class = {
output_class:0 for output_class in self.possible_outputs_list
}
self.local_classes = set()
self.local_sum = 0
self.selected_clusters = set()
self.summary_axe.clear()
self.summary_axe.axis('off')
def init_clusters(self):
"""
Clusterize the data and retrieve some countings
"""
(
self.index_by_cluster_label,
self.all_cluster_labels,
self.nb_of_points_by_class_by_cluster,
self.cluster_by_idx,
) = viz_helper.cluster_label_mesh(
self.clusterizer,
self.projected_input,
self.projection_points_list_by_correct_output_original,
self.correct_outputs,
)
(
self.nb_good_point_by_cluster,
self.nb_bad_point_by_cluster,
self.nb_good_point_by_class_by_cluster,
self.nb_bad_point_by_class_by_cluster,
self.nb_null_point_by_cluster,
) = viz_helper.get_count_by_cluster(
self.all_cluster_labels,
self.index_by_cluster_label,
self.correct_outputs,
self.index_good_predicted,
self.index_bad_predicted,
self.index_not_predicted,
)
def calculate_centroid_coordinates(self, x, y):
return x + self.resolution * y
def draw_the_line(self, x_list, y_list, color='b'):
for axe in self.axes_needing_borders:
axe.add_artist(matplotlib.lines.Line2D(xdata=x_list, ydata=y_list, color=color))
def line(self, float_point):
return (float_point - self.size_centroid / 2, float_point + self.size_centroid / 2)
def lower_bound(self, float_point, plus_one=None):
if plus_one:
return (float_point + self.size_centroid / 2,)
return (float_point - self.size_centroid / 2,)
def delimit_cluster(self, cluster, color='b', **kwargs):
"""
Delimits one cluster by drawing lines around it
"""
centroids_cluster_by_index = self.clusterizer.predict(self.mesh_centroids)
cluster_y_list_by_x = [[] for x in range(self.resolution)]
cluster_x_list_by_y = [[] for y in range(self.resolution)]
iter_all_coordinates = ((x, y) for x in range(0, self.resolution) for y in range(0, self.resolution))
for idx, (x, y) in enumerate(iter_all_coordinates):
if centroids_cluster_by_index[idx] == cluster:
cluster_y_list_by_x[x].append(y)
cluster_x_list_by_y[y].append(x)
calculate_coordinates = self.calculate_centroid_coordinates
def draw_all_lines(self, list_points, swapped_coordinates=False):
for a in range(0, self.resolution):
a_line_b_list = list_points[a]
if not a_line_b_list:
continue
min_b = min(a_line_b_list)
max_b = max(a_line_b_list)
no_hole = (max_b - min_b + 1) == len(a_line_b_list)
if no_hole:
if swapped_coordinates: # swaped if a is y and b is x, not swapt if a is and b is y
b_float_position, a_float_position= self.mesh_centroids[calculate_coordinates(min_b, a)]
self.draw_the_line(
self.lower_bound(b_float_position),
self.line(a_float_position),
color=color)
b_float_position, a_float_position = self.mesh_centroids[calculate_coordinates(max_b, a)]
self.draw_the_line(
self.lower_bound(b_float_position, plus_one=True),
self.line(a_float_position),
color=color)
else:
a_float_position, b_float_position= self.mesh_centroids[calculate_coordinates(a, min_b)]
self.draw_the_line(
self.line(a_float_position),
self.lower_bound(b_float_position),
color=color)
a_float_position, b_float_position = self.mesh_centroids[calculate_coordinates(a, max_b)]
self.draw_the_line(
self.line(a_float_position),
self.lower_bound(b_float_position, plus_one=True),
color=color)
else: # case not convex, which is not often so it's gonna be dirty
for b in a_line_b_list:
if swapped_coordinates:
if (b - 1) not in a_line_b_list:
b_float_position, a_float_position = self.mesh_centroids[calculate_coordinates(b, a)]
self.draw_the_line(
self.lower_bound(b_float_position),
self.line(a_float_position),
color=color)
if (b + 1) not in a_line_b_list:
b_float_position, a_float_position = self.mesh_centroids[calculate_coordinates(b, a)]
self.draw_the_line(
self.lower_bound(b_float_position, plus_one=True),
self.line(a_float_position),
color=color)
else:
if (b - 1) not in a_line_b_list:
a_float_position, b_float_position = self.mesh_centroids[calculate_coordinates(a, b)]
self.draw_the_line(
self.line(a_float_position),
self.lower_bound(b_float_position),
color=color)
if (b + 1) not in a_line_b_list:
a_float_position, b_float_position = self.mesh_centroids[calculate_coordinates(a, b)]
self.draw_the_line(
self.line(a_float_position),
self.lower_bound(b_float_position, plus_one=True),
color=color)
draw_all_lines(self, cluster_y_list_by_x, swapped_coordinates=True)
draw_all_lines(self, cluster_x_list_by_y, swapped_coordinates=False)
def get_coordinates_from_index(self, index):
return (self.resolution - index // self.resolution -1, index % self.resolution)
# check it's the same
# return (self.resolution - int(((index - index % self.resolution) / self.resolution)) - 1,
# index % self.resolution)
def request_color_mode(self, mode):
self.color_mode = mode
try:
drawing.draw_scatterplot(
self,
self.ax,
color_mode=self.color_mode
)
self.refresh_graph()
except:
pass
def request_new_frontiers(self, method):
"""
Init new frontiers based on a similarity mesure between clusters
"""
method = method.lower()
logging.info('frontiers : requiring new delimitations '+method)
for axe in self.axes_needing_borders:
for child in axe.get_children():
if isinstance(child, matplotlib.collections.LineCollection):
child.remove()
logging.info("removing a line collection")
similarity = frontier.make_frontier(method)
self.similarity_measure = similarity.compare
if method == 'bhattacharyya':
self.normalize_frontier=True
elif method =='all':
self.normalize_frontier=False
elif method == 'none':
self.normalize_frontier=False
self.refresh_graph()
return
drawing.apply_borders(
self,
self.normalize_frontier,
self.similarity_measure,
self.axes_needing_borders
)
self.refresh_graph()
logging.info('frontiers : applied '+method)
def request_clusterizer(self, method, params):
"""
Creates the clustering engine depending on the method you require
Actually different engine use different initialisations
:param params: the parameters as a dict, of the clustering
:param method: the name of the clustering engine
"""
logging.info("cluster: requesting a new " + method + " engine")
self.clusterizer = clustering.make_clusterizer(
method = method,
mesh = self.mesh_centroids,
**params,
)
if (not self.filters_active()) and self.clusterizer.loadable(self.version, self.cache_path):
logging.info("cluster: found cached clustering, loading..")
self.clusterizer = self.clusterizer.load_cluster(self.version, self.cache_path)
logging.info("cluster: ready")
else:
logging.info("cluster: fitting the clusters")
self.clusterizer.fit(self.projected_input_original)
if not self.filters_active():
logging.info("cluster: saving the clusters")
self.clusterizer.save_cluster(self.version, self.cache_path)
logging.info("cluster: ready")
def request_new_clustering(self, method, params):
"""
Init and fit a new clustering engin, then update the heatmaps
:param method: clustering engine to use ..seealso:clustering module
:param params: a dict with the parameters
"""
saved_zoom = (self.ax.get_xbound(), self.ax.get_ybound())
method = method.lower()
self.request_clusterizer(method, params)
self.init_clusters()
self.update_all_heatmaps()
drawing.apply_borders(
self,
self.normalize_frontier,
self.similarity_measure,
self.axes_needing_borders)
logging.info('borders: done')
self.reset_summary()
self.reset_viz()
self.ax.set_xbound(saved_zoom[0])
self.ax.set_ybound(saved_zoom[1])
self.refresh_graph()
def update_all_heatmaps(self):
"""
Get all heatmaps registered by request_heatmap and draw them from scratch
"""
for (this_heatmap, axe, title) in self.heatmaps:
axe.clear()
axe.axis('off')
this_heatmap.update_colors(vizualization=self)
heatmap_color = this_heatmap.get_all_colors()
im = axe.imshow(
heatmap_color,
interpolation='nearest',
vmin=0, vmax=1,
extent=(
-self.amplitude-self.size_centroid/2,
self.amplitude-self.size_centroid/2,
-self.amplitude-self.size_centroid/2,
self.amplitude-self.size_centroid/2
),
aspect='auto')
axe.set_xlim(-self.amplitude / 2, self.amplitude / 2)
axe.set_ylim(-self.amplitude / 2, self.amplitude / 2)
axe.axis('off')
axe.set_title(title)
self.refresh_graph()
def update_summary(self):
"""
Updates the local variables (the variables containing info about currently
selected clusters).
Three objects are important inside the object Vizualization and need to be updated :
- self.local_classes contains possible_outputs_list inside current_cluster
- self.local_effectif contains the effetif of each label inside current_cluster
- self.local_accuracy is the ratio of good/total predicted inside cluster, by label
- self.local_confusion_by_class is the error made by the predictor, indexed by true output
"""
effectif_by_class = {}
logging.info("local_variables=updating")
# Get effectif
for clr in self.selected_clusters:
for cls, effectif in self.nb_of_points_by_class_by_cluster.get(clr,{}).items():
effectif_by_class[cls] = effectif_by_class.get(cls,0) + effectif
effectif_by_class = {cls:e for cls, e in effectif_by_class.items() if e>0}
# Set 3 first local variables
self.local_classes = list(effectif_by_class.keys())
self.local_sum = sum (effectif_by_class.values())
self.local_effectif = effectif_by_class
# Counts the good/bad predictions in these clusters
logging.info("local_variables=counting good/bad")
nb_good_by_class = {cls:sum([self.nb_good_point_by_class_by_cluster.get(clr,{}).get(cls,0) for clr in self.selected_clusters]) for cls in self.local_classes}
nb_bad_by_class = {cls:sum([self.nb_bad_point_by_class_by_cluster.get(clr,{}).get(cls, 0) for clr in self.selected_clusters]) for cls in self.local_classes}
self.local_bad_count_by_class = nb_bad_by_class
self.local_good_count_by_class = nb_good_by_class
# Gets accuracy
logging.info("local_variables=counting accuracy")
for cls in self.local_classes:
self.local_accuracy[cls] = (
nb_good_by_class.get(cls,0) /
(
nb_good_by_class.get(cls,0)
+ nb_bad_by_class.get(cls,0)
))
# Get confusion matrix
logging.info("local_variables=calculating confusion")
confusion = {}
for clr in self.selected_clusters:
for idx in self.index_by_cluster_label.get(clr,{}):
if idx in self.index_bad_predicted:
correct = self.correct_outputs[idx]
prediction = self.prediction_outputs[idx]
confusion[correct] = confusion.get(correct, []) + [prediction]
self.local_confusion_by_class_sorted = {cls:[] for cls in confusion}
for cls, errors in confusion.items():
self.local_confusion_by_class_sorted[cls] = Counter(errors).most_common(2)
logging.info("local_variables=ready")
def print_summary(self, axe, max_row=15):
"""
Print a short summary with basic stats (occurrence, classification rate) on an axe
This method gets its data mainly from self.local_accuracy and self.local_effectif,
these objects are self-updated when needed and contain the data of the user-selected clusters
:param max_row: max nb of row to add in table summary
:param axe: the matplotlib axe in which the stats will be plotted
"""
logging.info("local_summary=printing")
row_labels = list(self.local_classes)
values = [
[
(
'{0:.0f} ({1:.1f}%)'.format(
self.local_effectif[c],
self.local_effectif[c] / self.nb_of_individual_by_true_output[c] * 100)
),
(
'{0:.2f}% ({1:+.1f}%) - {0:.1f}'.format(
self.local_accuracy[c]*100,
(self.local_accuracy[c]-self.accuracy_by_class[c])*100,
stats.binom_test(
self.local_effectif[c]*self.local_accuracy[c],
self.local_effectif[c],
self.accuracy_by_class[c],
alternative='two-sided'
),
)
),
(
'{0:.0f} ({1:.1f}%)'.format(
self.nb_of_individual_by_true_output[c],
self.nb_of_individual_by_true_output[c] / float(len(self.projected_input)) * 100,
)
),
(
' '.join([
'{:.6}'.format(class_mistaken)+ ' ({0:.1f}%)'.format(
error_count/float(self.local_bad_count_by_class[c])*100
)
for class_mistaken, error_count in self.local_confusion_by_class_sorted.get(c,[]) if error_count != 0
])
),
]
for c in row_labels
]
arg_sort = np.argsort([self.local_effectif[c] for c in row_labels])
values = [values[i] for i in arg_sort[::-1]]
row_labels = [row_labels[i][:6] for i in arg_sort[::-1]]
# add row "all" for recap :
max_row = min(max_row, min(len(values), len(row_labels)))
values = values[:max_row]
row_labels = row_labels[:max_row]
values.append([self.local_sum, '-', '{} (100%)'.format(len(self.projected_input)), ' '])
row_labels.append('all')
self.rows = row_labels
cols = [
'#class (in cluster)\n'
'(#class (in cluster) /#class)',
'accuracy (in cluster)\n'
'(delta with accuracy (general)) - p-value',
'#class\n'
'(#class /#all_class)',
'common mistakes'
]
axe.clear()
summary = axe.table(
cellText=values,
rowLabels=row_labels,
colLabels=cols,
loc='center',
)
cells = summary.get_celld()
for i in range(0,4):
cells[(0,i)].set_height(cells[(1,0)].get_height()*2)
summary.auto_set_font_size(False)
summary.set_fontsize(8)
axe.axis('off')
logging.info("local_summary=ready")
def print_global_summary(self, ax, max_row=9):
"""
Prints a global summary with the most frequent class and
their classification accuracy
"""
logging.info("global_summary=calculating")
ax.clear()
ax.axis('off')
cols = ['accuracy', 'effectif']
most_common_classes = Counter(
{
c:len(self.index_by_true_output.get(c,[])) for c in self.possible_outputs_list
}
).most_common(max_row)
row_labels = np.array(most_common_classes)[:,0]
values = []
for c in row_labels:
accuracy = self.accuracy_by_class.get(c,0)*100
effectif = self.nb_of_individual_by_true_output.get(c,0)
if len(self.projected_input) == 0:
proportion_effectif = 0
else:
proportion_effectif = effectif / float(len(self.projected_input)) * 100
values.append(['{0:.2f}'.format(accuracy)+"%", '{0:.0f} ({1:.2f}%)'.format(effectif, proportion_effectif)])
summary = ax.table(
cellText=values,
rowLabels=[' '+str(r[:6])+' ' for r in row_labels],
colLabels=cols,
loc='center',
)
summary.auto_set_font_size(False)
summary.set_fontsize(8)
logging.info("global_summary=ready")
def request_heatmap(self, method, axe, title):
"""
Draw a heatmap based on a heatmap_builder on an axe
:param heatmap_builder: a Vizualization parameterless method which returns patches
:param axe: matplotlib axe object in which the heatmap will be plotted
"""
heatmap_constructor = heatmap.make_heatmap(
method=method,
)
this_heatmap = heatmap_constructor(
vizualization=self,
)
self.heatmaps.append((this_heatmap, axe, title))
def export(self, output_path, format='csv'):
"""
Export your selected data in a .csv file for analysis
"""
logging.info('exporting:...')
if output_path == "":
logging.warn("No export name specified, aborting")
return
columns = [
'prediction',
'projected coordinates',
'is_correct',
]
rows = [
[
self.projected_input[idx],
self.prediction_outputs[idx],
int(idx in self.index_good_predicted),
]
for idx,c in enumerate(self.cluster_by_idx)
if c in self.selected_clusters
]
if self.x_raw.any():
columns = [*self.x_raw_columns, *columns]
rows = [
[
*self.x_raw[idx],
self.prediction_outputs[idx],
self.projected_input[idx],
int(idx in self.index_good_predicted),
]
for idx,c in enumerate(self.cluster_by_idx)
if c in self.selected_clusters
]
to_export = [columns, *rows]
if format=='csv':
wr = csv.writer(open(output_path, 'w'))
wr.writerows(to_export)
logging.info('exporting: done')
else:
logging.warn('exporting: format not available')
def make_clusterization_name(self, name_clusters):
"""
Filename containing the saved session
"""
return name_clusters + '#' + self.version + '.pkl'
def save_clusterization(self, name_clusters='clusters'):
"""
Basically saves a clusterizer and replays a sequence of leftclicks
"""
if (' ' in name_clusters) or ('.' in name_clusters):
self.viz_handler.pop_dialog("Please do not use space or '.' in name!")
return
filename = self.make_clusterization_name(name_clusters)
session = (self.version, self.clusterizer, self.left_clicks)
full_path = os.path.join(self.saved_clusters_path, filename)
logging.info("user clusters: saving in {}".format(full_path))
pickle.dump(
session,
open(full_path, 'wb')
)
self.viz_handler.user_cluster_menulist.add_items([filename])
return filename
def load_clusterization(self, name_clusters):
"""
Basically loads clustering engine and sequence of left_clicks
"""
full_path = os.path.join(self.saved_clusters_path, name_clusters)
version_to_load, clusterizer, left_clicks_to_reproduce = pickle.load(
open(full_path, 'rb'),
)
if version_to_load != self.version:
self.viz_handler.pop_dialog(
"Impossible to load clusters : bad VERSION (dataset do not match)")
return
self.reset_viz()
self.left_clicks = set()
self.clusterizer = clusterizer
self.init_clusters()
self.reset_summary()
for left_click in left_clicks_to_reproduce:
self.do_left_click(left_click)
self.update_summary()
self.print_summary(self.summary_axe)
self.print_global_summary(self.global_summary_axe)
self.update_all_heatmaps()
self.request_new_frontiers('none')
self.refresh_graph()
def clear_cluster_view(self):
for clr_view in self.cluster_view:
clr_view.clear()
def add_cluster_view(self, feature_to_display, plotter_names):
logging.info(
"cluster_view=adding a feature to display, {}:{}".format(
feature_to_display, plotter_names)
)
self.cluster_view.append(
Cluster_viewer(
{feature_to_display:plotter_names},
self.x_raw,
self.x_raw_columns,
show_dichotomy=True,
)
)
self.additional_figures.append(self.cluster_view[-1])
self.viz_handler.add_figure(
self.additional_figures[-1],
"Cluster view: {}".format(plotter_names[0])
)
logging.info("cluster_view=ready")
if self.selected_clusters:
self.update_cluster_view()
def update_cluster_view(self):
if self.cluster_view:
logging.info('cluster_viewer=sorting indexes')
index_selected = [
idx for clr in self.selected_clusters for idx in self.index_by_cluster_label.get(clr,[])]
index_good = [idx for idx in index_selected if idx in self.index_good_predicted]
index_bad = [idx for idx in index_selected if idx in self.index_bad_predicted ]
for clr_view in self.cluster_view:
logging.info('cluster_viewer=plotting sorted indexes')
clr_view.update_cluster_view(
index_good = index_good,
index_bad = index_bad,
data_by_index = self.x_raw,
)
logging.info('cluster_viewer=ready')
def plot(self):
"""
Plot the Vizualization, define axes, add scatterplot, buttons, etc..
"""
self.init_clusters()
self.main_fig = matplotlib.figure.Figure()
#self.cluster_view = matplotlib.figure.Figure()
self.cluster_view = []
self.additional_figures = []
gs=GridSpec(3,4)
#self.view_details = View_details(self.x_raw)
self.viz_handler = Viz_handler(
viz_engine = self,
figure = self.main_fig,
onclick = self.onclick,
additional_figures = self.additional_figures,
)
for feature_to_display,plotter_name in self.features_to_display.items():
self.add_cluster_view(feature_to_display, plotter_name)
# main subplot with the scatter plot
self.ax = self.main_fig.add_subplot(gs[:2,:3])
self.ax_base_title = 'Correct VS incorrect predictions'
self.ax.set_title(self.ax_base_title)
# summary_subplot with table of local stats
self.summary_axe = self.main_fig.add_subplot(gs[2,:3])
self.summary_axe.axis('off')
self.global_summary_axe = self.main_fig.add_subplot(gs[2,3])
self.global_summary_axe.axis('off')
self.print_global_summary(self.global_summary_axe)
# heatmap subplots
# contain accuracy of correct prediction and entropy
self.axes_needing_borders = [self.ax]
# draw heatmap
logging.info("heatmap=calculating")
# self.cluster_view = self.main_fig.add_subplot(gs[1,3])
self.heatmaps = []
self.heatmap0 = self.main_fig.add_subplot(
gs[1,3],
sharex=self.ax,
sharey=self.ax)
self.request_heatmap(
method=self.heatmaps_requested[0],
axe=self.heatmap0,
title='Heatmap: accuracy correct predictions')
self.axes_needing_borders.append(self.heatmap0)
self.heatmap1 = self.main_fig.add_subplot(
gs[0,3],
sharex=self.ax,
sharey=self.ax)
self.request_heatmap(
method=self.heatmaps_requested[1],
axe=self.heatmap1,
title='Heatmap: cross-entropy Cluster-All')
self.axes_needing_borders.append(self.heatmap1)
self.update_all_heatmaps()
logging.info("heatmap=ready")
# draw scatter plot
self.reset_viz()
self.request_new_frontiers('none')
logging.info('Vizualization=ready')
self.viz_handler.is_ready()
def show(self):
logging.info('showing main window')
self.viz_handler.show()
logging.info('showing cluster diving window')
#self.cluster_diver.show()
logging.info("showing done")
sys.exit(self.viz_handler.app.exec_())
def refresh_graph(self):
logging.info('refreshing main window')
self.viz_handler.refresh()
logging.info("refreshing done")
| 47,857 | vizualization | py | en | python | code | {"qsc_code_num_words": 5431, "qsc_code_num_chars": 47857.0, "qsc_code_mean_word_length": 4.88178973, "qsc_code_frac_words_unique": 0.1112134, "qsc_code_frac_chars_top_2grams": 0.0178403, "qsc_code_frac_chars_top_3grams": 0.01493607, "qsc_code_frac_chars_top_4grams": 0.01357824, "qsc_code_frac_chars_dupe_5grams": 0.45208011, "qsc_code_frac_chars_dupe_6grams": 0.38758345, "qsc_code_frac_chars_dupe_7grams": 0.33481688, "qsc_code_frac_chars_dupe_8grams": 0.28823596, "qsc_code_frac_chars_dupe_9grams": 0.257006, "qsc_code_frac_chars_dupe_10grams": 0.23833591, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.00497108, "qsc_code_frac_chars_whitespace": 0.33165472, "qsc_code_size_file_byte": 47857.0, "qsc_code_num_lines": 1224.0, "qsc_code_num_chars_line_max": 166.0, "qsc_code_num_chars_line_mean": 39.09885621, "qsc_code_frac_chars_alphabet": 0.82394873, "qsc_code_frac_chars_comments": 0.12121529, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.33529412, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.04843582, "qsc_code_frac_chars_long_word_length": 0.00577429, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codepython_cate_ast": 1.0, "qsc_codepython_frac_lines_func_ratio": 0.05058824, "qsc_codepython_cate_var_zero": false, "qsc_codepython_frac_lines_pass": 0.00117647, "qsc_codepython_frac_lines_import": 0.02352941, "qsc_codepython_frac_lines_simplefunc": 0.0035294117647058825, "qsc_codepython_score_lines_no_logic": 0.09294118, "qsc_codepython_frac_lines_print": 0.01176471} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codepython_cate_ast": 0, "qsc_codepython_frac_lines_func_ratio": 0, "qsc_codepython_cate_var_zero": 0, "qsc_codepython_frac_lines_pass": 0, "qsc_codepython_frac_lines_import": 0, "qsc_codepython_frac_lines_simplefunc": 0, "qsc_codepython_score_lines_no_logic": 0, "qsc_codepython_frac_lines_print": 0} |
0011001011/vizuka | vizuka/launch_reduce.py | import argparse
import logging
from pyfiglet import Figlet
from vizuka import dimension_reduction
from vizuka import data_loader
from vizuka import config
from vizuka.config import (
VERSION,
INPUT_FILE_BASE_NAME,
DATA_PATH,
BASE_PATH,
PROJECTION_DEFAULT_PARAMS,
)
logger = logging.getLogger()
logger.setLevel(logging.WARN)
def do_reduce(algorithm_name, parameters, version, data_path, reduced_path):
"""
Project the data in :param data_path: (version :param version:)
with algorithm :param algorithm_name: using parameters in :param parameters
and save it in :param reduced_path:
"""
algo_builder = dimension_reduction.make_projector(algorithm_name)
algo = algo_builder(**parameters)
(x, _ ,_ ,_, loaded, preprocessed_filename ) = data_loader.load_preprocessed(
file_base_name = INPUT_FILE_BASE_NAME,
path = data_path,
version = version,
)
if not loaded:
logging.warn("\nNo data found\nCorresponding file not found: {}\nPlease check --show-required-files".format(preprocessed_filename))
return
logging.warn("Projecting the preprocessed data in 2D.. this may take a while!")
algo.project(x) # do the dimension projection
algo.save_projection(version=version, path=reduced_path) # save the result
logging.warn("Projecting done")
def main():
"""
Loads parameters and run do_reduce
"""
print(Figlet().renderText('Vizuka'))
builtin_projectors, extra_projectors = dimension_reduction.list_projectors()
parser = argparse.ArgumentParser()
parser.add_argument(
'-a', '--algorithm',
help=(
'algorithm name to reduce dimensions, available are :\n'
+ 'builtin: {}\n'.format(list(builtin_projectors.keys()))
+ 'extra plugins: {}'.format(list(extra_projectors.keys()))
)
)
parser.add_argument(
'-p', '--parameters', action='append',
help='specify parameters, e.g: "-p perplexity:50 -p learning_rate:0.1" '
'It will load default values in config.py if not specified'
)
parser.add_argument(
'-v', '--version',
help='specify a version of the files to load/generate (see vizuka --show_required_files), currently: '+VERSION)
parser.add_argument(
'--path',
help='change the location of your data/ folder containing reduced/ (the projections)'
' and set/ (the raw and preprocessed data).'
' Default to {}'.format(BASE_PATH)
)
parser.add_argument(
'--verbose', action="store_true",
help="verbose mode")
parser.set_defaults(
algorithm = 'manual',
parameters = {},
path = BASE_PATH,
version = VERSION,
)
args = parser.parse_args()
(data_path, reduced_path, _, _, _, _) = config.path_builder(args.path)
algorithm_name = args.algorithm
parameters = args.parameters
version = args.version
verbose = args.verbose
print("VERSION: Loading dataset labeled {} (cf --version)".format(version))
if verbose:
logger.setLevel(logging.DEBUG)
if algorithm_name == 'manual':
choice_list, choice_dict = "", {}
for i,method in enumerate([*builtin_projectors, *extra_projectors]):
choice_list+="\t\t [{}]: {}\n".format(i, method)
choice_dict[i]=method
choice = input("No algorithm specified (-a or --algorithm)\n\tChoices available are:\n"+choice_list+"\t[?] > ")
try:
choice_int=int(choice)
except:
logger.warn("Please enter a valid integer !")
return
algorithm_name = choice_dict[choice_int]
for raw_param in parameters:
if ':' not in raw_param:
raise TypeError('parameter -p not used correctly! see --help')
param_name, param_value = raw_param.split(':')
parameters[param_name:param_value]
default_params = PROJECTION_DEFAULT_PARAMS.get(algorithm_name, {})
for default_param_name, default_param_value in default_params.items():
if default_param_name not in parameters:
parameters[default_param_name] = default_param_value
logger.info('parameter {} not specified, using default value: {}'.format(
default_param_name, default_param_value)
)
do_reduce(algorithm_name, parameters, version, data_path, reduced_path)
cmd_to_launch = "vizuka"
cmd_to_launch+= (' --version {}'.format(version) if version!=VERSION else '')
cmd_to_launch+= ('--path {}'.format(args.path) if args.path != BASE_PATH else '')
print('"Projection done, you can now launch "vizuka"')
if __name__=='__main__':
main()
| 4,952 | launch_reduce | py | en | python | code | {"qsc_code_num_words": 558, "qsc_code_num_chars": 4952.0, "qsc_code_mean_word_length": 5.33154122, "qsc_code_frac_words_unique": 0.29749104, "qsc_code_frac_chars_top_2grams": 0.03932773, "qsc_code_frac_chars_top_3grams": 0.02857143, "qsc_code_frac_chars_top_4grams": 0.01915966, "qsc_code_frac_chars_dupe_5grams": 0.07159664, "qsc_code_frac_chars_dupe_6grams": 0.07159664, "qsc_code_frac_chars_dupe_7grams": 0.03831933, "qsc_code_frac_chars_dupe_8grams": 0.03831933, "qsc_code_frac_chars_dupe_9grams": 0.03831933, "qsc_code_frac_chars_dupe_10grams": 0.03831933, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.00137703, "qsc_code_frac_chars_whitespace": 0.2667609, "qsc_code_size_file_byte": 4952.0, "qsc_code_num_lines": 137.0, "qsc_code_num_chars_line_max": 140.0, "qsc_code_num_chars_line_mean": 36.1459854, "qsc_code_frac_chars_alphabet": 0.81795649, "qsc_code_frac_chars_comments": 0.05149435, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.06666667, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.22482285, "qsc_code_frac_chars_long_word_length": 0.01438694, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codepython_cate_ast": 1.0, "qsc_codepython_frac_lines_func_ratio": 0.01904762, "qsc_codepython_cate_var_zero": false, "qsc_codepython_frac_lines_pass": 0.0, "qsc_codepython_frac_lines_import": 0.06666667, "qsc_codepython_frac_lines_simplefunc": 0.0, "qsc_codepython_score_lines_no_logic": 0.1047619, "qsc_codepython_frac_lines_print": 0.02857143} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codepython_cate_ast": 0, "qsc_codepython_frac_lines_func_ratio": 0, "qsc_codepython_cate_var_zero": 0, "qsc_codepython_frac_lines_pass": 0, "qsc_codepython_frac_lines_import": 0, "qsc_codepython_frac_lines_simplefunc": 0, "qsc_codepython_score_lines_no_logic": 0, "qsc_codepython_frac_lines_print": 0} |
0011001011/vizuka | vizuka/config.py | """
Here are the default parameters used in all the package
There are 1.path 2.filenames 3.learning parameters
"""
import os
#
# ALL DEFAULT PATH
#
def path_builder(base_path):
folders = [
os.path.join(base_path, relative) for relative in [
'set/',
'reduced/',
'models/',
'graph/',
'cache/',
'saved_clusters/',
]
]
for folder in folders:
if not os.path.exists(folder):
os.makedirs(folder)
return folders
# Build all path from one base
BASE_PATH = os.path.join(os.path.dirname(__file__), 'data/')
(
DATA_PATH,
REDUCED_DATA_PATH,
MODEL_PATH,
GRAPH_PATH,
CACHE_PATH,
SAVED_CLUSTERS_PATH,
) = path_builder(BASE_PATH)
#
# ALL DEFAULT FILENAME
#
# File containing data to be t-SNEed
INPUT_FILE_BASE_NAME = 'preprocessed_inputs_'
RAW_NAME = 'raw_data_'
# default RN for predictions
DEFAULT_PREDICTOR = 'predict_'
# PROJECTIONS DATA will have a named generated from the algo projector parameters
# A version is a string added to the end of each filename
VERSION = 'MNIST_example'
#
# LEARNING PARAMETERS
#
# Dimension reduction default parameters :
DEFAULT_PROJECTOR = 'tsne'
PROJECTION_DEFAULT_PARAMS = {
'tsne': {
'perplexity': 50,
'learning_rate': 1000,
'n_iter': 12000,
},
'pca': {
'nb_dimension': 2,
'min_ratio_variance_explained': -1,
},
}
NAME_VALUE_SEPARATOR = '@@'
PARAMETERS_SEPARATOR = '#'
| 1,512 | config | py | en | python | code | {"qsc_code_num_words": 184, "qsc_code_num_chars": 1512.0, "qsc_code_mean_word_length": 5.01630435, "qsc_code_frac_words_unique": 0.52717391, "qsc_code_frac_chars_top_2grams": 0.03466956, "qsc_code_frac_chars_top_3grams": 0.03250271, "qsc_code_frac_chars_top_4grams": 0.0411701, "qsc_code_frac_chars_dupe_5grams": 0.0, "qsc_code_frac_chars_dupe_6grams": 0.0, "qsc_code_frac_chars_dupe_7grams": 0.0, "qsc_code_frac_chars_dupe_8grams": 0.0, "qsc_code_frac_chars_dupe_9grams": 0.0, "qsc_code_frac_chars_dupe_10grams": 0.0, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.01427297, "qsc_code_frac_chars_whitespace": 0.25859788, "qsc_code_size_file_byte": 1512.0, "qsc_code_num_lines": 76.0, "qsc_code_num_chars_line_max": 82.0, "qsc_code_num_chars_line_mean": 19.89473684, "qsc_code_frac_chars_alphabet": 0.80909902, "qsc_code_frac_chars_comments": 0.28703704, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.0, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.17424242, "qsc_code_frac_chars_long_word_length": 0.02651515, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codepython_cate_ast": 1.0, "qsc_codepython_frac_lines_func_ratio": 0.02325581, "qsc_codepython_cate_var_zero": false, "qsc_codepython_frac_lines_pass": 0.0, "qsc_codepython_frac_lines_import": 0.02325581, "qsc_codepython_frac_lines_simplefunc": 0.0, "qsc_codepython_score_lines_no_logic": 0.06976744, "qsc_codepython_frac_lines_print": 0.0} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codepython_cate_ast": 0, "qsc_codepython_frac_lines_func_ratio": 0, "qsc_codepython_cate_var_zero": 0, "qsc_codepython_frac_lines_pass": 0, "qsc_codepython_frac_lines_import": 0, "qsc_codepython_frac_lines_simplefunc": 0, "qsc_codepython_score_lines_no_logic": 0, "qsc_codepython_frac_lines_print": 0} |
0015/T-Glass-Applications | image_capture_app/main/rtc_pcf85063.c | #include "rtc_pcf85063.h"
#include "driver/i2c.h"
#include "esp_log.h"
#include <stdio.h>
#include <string.h>
#define I2C_MASTER_SCL_IO 8
#define I2C_MASTER_SDA_IO 9
#define I2C_MASTER_NUM I2C_NUM_0
#define I2C_MASTER_FREQ_HZ 100000
#define I2C_MASTER_TX_BUF_DISABLE 0
#define I2C_MASTER_RX_BUF_DISABLE 0
#define PCF85063_ADDR 0x51
#define PCF85063_CTRL1_REG 0x00
#define PCF85063_SEC_REG 0x04
#define DEC2BCD(val) (((val) / 10) << 4 | ((val) % 10))
#define BCD2DEC(val) (((val) >> 4) * 10 + ((val) & 0x0F))
static const char *TAG = "RTC_PCF85063";
// Array of day names
static const char *DAY_NAMES[] = {
"Sunday", "Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday"};
// Array of month abbreviations
static const char *MONTH_NAMES[] = {
"Jan", "Feb", "Mar", "Apr", "May", "Jun",
"Jul", "Aug", "Sep", "Oct", "Nov", "Dec"};
// Static buffer for formatted date
static char formatted_date[20];
static esp_err_t write_register(uint8_t reg, uint8_t *data, size_t len)
{
i2c_cmd_handle_t cmd = i2c_cmd_link_create();
i2c_master_start(cmd);
i2c_master_write_byte(cmd, (PCF85063_ADDR << 1) | I2C_MASTER_WRITE, true);
i2c_master_write_byte(cmd, reg, true);
i2c_master_write(cmd, data, len, true);
i2c_master_stop(cmd);
esp_err_t ret = i2c_master_cmd_begin(I2C_MASTER_NUM, cmd, pdMS_TO_TICKS(1000));
i2c_cmd_link_delete(cmd);
return ret;
}
static esp_err_t read_register(uint8_t reg, uint8_t *data, size_t len)
{
i2c_cmd_handle_t cmd = i2c_cmd_link_create();
i2c_master_start(cmd);
i2c_master_write_byte(cmd, (PCF85063_ADDR << 1) | I2C_MASTER_WRITE, true);
i2c_master_write_byte(cmd, reg, true);
i2c_master_start(cmd);
i2c_master_write_byte(cmd, (PCF85063_ADDR << 1) | I2C_MASTER_READ, true);
i2c_master_read(cmd, data, len, I2C_MASTER_LAST_NACK);
i2c_master_stop(cmd);
esp_err_t ret = i2c_master_cmd_begin(I2C_MASTER_NUM, cmd, pdMS_TO_TICKS(1000));
i2c_cmd_link_delete(cmd);
return ret;
}
esp_err_t initialize_rtc(void)
{
i2c_config_t conf = {
.mode = I2C_MODE_MASTER,
.sda_io_num = I2C_MASTER_SDA_IO,
.scl_io_num = I2C_MASTER_SCL_IO,
.sda_pullup_en = GPIO_PULLUP_ENABLE,
.scl_pullup_en = GPIO_PULLUP_ENABLE,
.master.clk_speed = I2C_MASTER_FREQ_HZ,
};
ESP_ERROR_CHECK(i2c_param_config(I2C_MASTER_NUM, &conf));
return i2c_driver_install(I2C_MASTER_NUM, conf.mode, I2C_MASTER_RX_BUF_DISABLE, I2C_MASTER_TX_BUF_DISABLE, 0);
}
esp_err_t rtc_set_datetime(RTC_DateTime datetime)
{
uint8_t buffer[7];
buffer[0] = DEC2BCD(datetime.second) & 0x7F;
buffer[1] = DEC2BCD(datetime.minute);
buffer[2] = DEC2BCD(datetime.hour);
buffer[3] = DEC2BCD(datetime.day);
buffer[4] = datetime.week;
buffer[5] = DEC2BCD(datetime.month);
buffer[6] = DEC2BCD(datetime.year % 100);
esp_err_t err = write_register(PCF85063_SEC_REG, buffer, 7);
if (err == ESP_OK)
{
ESP_LOGI(TAG, "RTC Date-Time set: %04d-%02d-%02d %02d:%02d:%02d",
datetime.year, datetime.month, datetime.day,
datetime.hour, datetime.minute, datetime.second);
}
return err;
}
RTC_DateTime rtc_get_datetime(void)
{
RTC_DateTime datetime;
uint8_t buffer[7] = {0};
esp_err_t err = read_register(PCF85063_SEC_REG, buffer, 7);
if (err == ESP_OK)
{
datetime.available = (buffer[0] & 0x80) == 0x00;
datetime.second = BCD2DEC(buffer[0] & 0x7F);
datetime.minute = BCD2DEC(buffer[1] & 0x7F);
datetime.hour = BCD2DEC(buffer[2] & 0x3F);
datetime.day = BCD2DEC(buffer[3] & 0x3F);
datetime.week = BCD2DEC(buffer[4] & 0x07);
datetime.month = BCD2DEC(buffer[5] & 0x1F);
datetime.year = BCD2DEC(buffer[6]) + 2000;
// ESP_LOGI(TAG, "RTC Date-Time retrieved: %04d-%02d-%02d %02d:%02d:%02d",
// datetime.year, datetime.month, datetime.day,
// datetime.hour, datetime.minute, datetime.second);
}
return datetime;
}
const char *rtc_get_formatted_date(RTC_DateTime datetime)
{
// Validate week and month values to avoid buffer overflows
if (datetime.week > 6 || datetime.month > 12 || datetime.month == 0)
{
return "Invalid Date";
}
snprintf(formatted_date, sizeof(formatted_date), "%s, %s %d",
DAY_NAMES[datetime.week],
MONTH_NAMES[datetime.month - 1],
datetime.day);
return formatted_date;
} | 4,486 | rtc_pcf85063 | c | en | c | code | {"qsc_code_num_words": 647, "qsc_code_num_chars": 4486.0, "qsc_code_mean_word_length": 4.34930448, "qsc_code_frac_words_unique": 0.23956723, "qsc_code_frac_chars_top_2grams": 0.10554371, "qsc_code_frac_chars_top_3grams": 0.0199005, "qsc_code_frac_chars_top_4grams": 0.03198294, "qsc_code_frac_chars_dupe_5grams": 0.39694385, "qsc_code_frac_chars_dupe_6grams": 0.36496091, "qsc_code_frac_chars_dupe_7grams": 0.33439943, "qsc_code_frac_chars_dupe_8grams": 0.31165601, "qsc_code_frac_chars_dupe_9grams": 0.31165601, "qsc_code_frac_chars_dupe_10grams": 0.31165601, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.06620306, "qsc_code_frac_chars_whitespace": 0.19861792, "qsc_code_size_file_byte": 4486.0, "qsc_code_num_lines": 135.0, "qsc_code_num_chars_line_max": 115.0, "qsc_code_num_chars_line_mean": 33.22962963, "qsc_code_frac_chars_alphabet": 0.71655076, "qsc_code_frac_chars_comments": 0.07668301, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.17117117, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.04875694, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.01255129, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codec_frac_lines_func_ratio": 0.08108108, "qsc_codec_cate_bitsstdc": 0.0, "qsc_codec_nums_lines_main": 0, "qsc_codec_frac_lines_goto": 0.0, "qsc_codec_cate_var_zero": 0.0, "qsc_codec_score_lines_no_logic": 0.18018018, "qsc_codec_frac_lines_print": 0.00900901, "qsc_codec_frac_lines_preprocessor_directives": 0.14414414} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codec_frac_lines_func_ratio": 0, "qsc_codec_nums_lines_main": 0, "qsc_codec_score_lines_no_logic": 0, "qsc_codec_frac_lines_preprocessor_directives": 0, "qsc_codec_frac_lines_print": 0} |
0015/esp_rlottie | rlottie/src/vector/vtaskqueue.h | /*
* Copyright (c) 2020 Samsung Electronics Co., Ltd. All rights reserved.
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#ifndef VTASKQUEUE_H
#define VTASKQUEUE_H
#include <deque>
template <typename Task>
class TaskQueue {
using lock_t = std::unique_lock<std::mutex>;
std::deque<Task> _q;
bool _done{false};
std::mutex _mutex;
std::condition_variable _ready;
public:
bool try_pop(Task &task)
{
lock_t lock{_mutex, std::try_to_lock};
if (!lock || _q.empty()) return false;
task = std::move(_q.front());
_q.pop_front();
return true;
}
bool try_push(Task &&task)
{
{
lock_t lock{_mutex, std::try_to_lock};
if (!lock) return false;
_q.push_back(std::move(task));
}
_ready.notify_one();
return true;
}
void done()
{
{
lock_t lock{_mutex};
_done = true;
}
_ready.notify_all();
}
bool pop(Task &task)
{
lock_t lock{_mutex};
while (_q.empty() && !_done) _ready.wait(lock);
if (_q.empty()) return false;
task = std::move(_q.front());
_q.pop_front();
return true;
}
void push(Task &&task)
{
{
lock_t lock{_mutex};
_q.push_back(std::move(task));
}
_ready.notify_one();
}
};
#endif // VTASKQUEUE_H
| 2,494 | vtaskqueue | h | en | c | code | {"qsc_code_num_words": 327, "qsc_code_num_chars": 2494.0, "qsc_code_mean_word_length": 4.60550459, "qsc_code_frac_words_unique": 0.42507645, "qsc_code_frac_chars_top_2grams": 0.05843293, "qsc_code_frac_chars_top_3grams": 0.02988048, "qsc_code_frac_chars_top_4grams": 0.04648074, "qsc_code_frac_chars_dupe_5grams": 0.20717131, "qsc_code_frac_chars_dupe_6grams": 0.20717131, "qsc_code_frac_chars_dupe_7grams": 0.20717131, "qsc_code_frac_chars_dupe_8grams": 0.1686587, "qsc_code_frac_chars_dupe_9grams": 0.1686587, "qsc_code_frac_chars_dupe_10grams": 0.12350598, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.00223214, "qsc_code_frac_chars_whitespace": 0.28147554, "qsc_code_size_file_byte": 2494.0, "qsc_code_num_lines": 87.0, "qsc_code_num_chars_line_max": 82.0, "qsc_code_num_chars_line_mean": 28.66666667, "qsc_code_frac_chars_alphabet": 0.83816964, "qsc_code_frac_chars_comments": 0.46672013, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.28571429, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.0, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codec_frac_lines_func_ratio": 0.08928571, "qsc_codec_cate_bitsstdc": 0.0, "qsc_codec_nums_lines_main": 0, "qsc_codec_frac_lines_goto": 0.0, "qsc_codec_cate_var_zero": 0.0, "qsc_codec_score_lines_no_logic": 0.17857143, "qsc_codec_frac_lines_print": 0.0, "qsc_codec_frac_lines_preprocessor_directives": null} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codec_frac_lines_func_ratio": 0, "qsc_codec_nums_lines_main": 0, "qsc_codec_score_lines_no_logic": 0, "qsc_codec_frac_lines_preprocessor_directives": 0, "qsc_codec_frac_lines_print": 0} |
0015/esp_rlottie | rlottie/src/vector/vdebug.h | /*
* Copyright (c) 2020 Samsung Electronics Co., Ltd. All rights reserved.
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#ifndef VDEBUG_H
#define VDEBUG_H
#include "config.h"
#ifdef LOTTIE_LOGGING_SUPPORT
#include <cstdint>
#include <iosfwd>
#include <memory>
#include <string>
#include <type_traits>
enum class LogLevel : uint8_t { INFO, WARN, CRIT, OFF };
class VDebug {
public:
VDebug();
VDebug& debug() { return *this; }
VDebug(LogLevel level, char const* file, char const* function,
uint32_t line);
~VDebug();
VDebug(VDebug&&) = default;
VDebug& operator=(VDebug&&) = default;
void stringify(std::ostream& os);
VDebug& operator<<(char arg);
VDebug& operator<<(int32_t arg);
VDebug& operator<<(uint32_t arg);
// VDebug& operator<<(int64_t arg);
// VDebug& operator<<(uint64_t arg);
VDebug& operator<<(long arg);
VDebug& operator<<(unsigned long arg);
VDebug& operator<<(double arg);
VDebug& operator<<(std::string const& arg);
template <size_t N>
VDebug& operator<<(const char (&arg)[N])
{
encode(string_literal_t(arg));
return *this;
}
template <typename Arg>
typename std::enable_if<std::is_same<Arg, char const*>::value,
VDebug&>::type
operator<<(Arg const& arg)
{
encode(arg);
return *this;
}
template <typename Arg>
typename std::enable_if<std::is_same<Arg, char*>::value, VDebug&>::type
operator<<(Arg const& arg)
{
encode(arg);
return *this;
}
struct string_literal_t {
explicit string_literal_t(char const* s) : m_s(s) {}
char const* m_s;
};
private:
char* buffer();
template <typename Arg>
void encode(Arg arg);
template <typename Arg>
void encode(Arg arg, uint8_t type_id);
void encode(char* arg);
void encode(char const* arg);
void encode(string_literal_t arg);
void encode_c_string(char const* arg, size_t length);
void resize_buffer_if_needed(size_t additional_bytes);
void stringify(std::ostream& os, char* start, char const* const end);
private:
size_t m_bytes_used{0};
size_t m_buffer_size{0};
std::unique_ptr<char[]> m_heap_buffer;
bool m_logAll;
char m_stack_buffer[256 - sizeof(bool) - 2 * sizeof(size_t) -
sizeof(decltype(m_heap_buffer)) - 8 /* Reserved */];
};
struct VDebugServer {
/*
* Ideally this should have been operator+=
* Could not get that to compile, so here we are...
*/
bool operator==(VDebug&);
};
void set_log_level(LogLevel level);
bool is_logged(LogLevel level);
/*
* Non guaranteed logging. Uses a ring buffer to hold log lines.
* When the ring gets full, the previous log line in the slot will be dropped.
* Does not block producer even if the ring buffer is full.
* ring_buffer_size_mb - LogLines are pushed into a mpsc ring buffer whose size
* is determined by this parameter. Since each LogLine is 256 bytes,
* ring_buffer_size = ring_buffer_size_mb * 1024 * 1024 / 256
*/
struct NonGuaranteedLogger {
NonGuaranteedLogger(uint32_t ring_buffer_size_mb_)
: ring_buffer_size_mb(ring_buffer_size_mb_)
{
}
uint32_t ring_buffer_size_mb;
};
/*
* Provides a guarantee log lines will not be dropped.
*/
struct GuaranteedLogger {
};
/*
* Ensure initialize() is called prior to any log statements.
* log_directory - where to create the logs. For example - "/tmp/"
* log_file_name - root of the file name. For example - "nanolog"
* This will create log files of the form -
* /tmp/nanolog.1.txt
* /tmp/nanolog.2.txt
* etc.
* log_file_roll_size_mb - mega bytes after which we roll to next log file.
*/
void initialize(GuaranteedLogger gl, std::string const& log_directory,
std::string const& log_file_name,
uint32_t log_file_roll_size_mb);
void initialize(NonGuaranteedLogger ngl, std::string const& log_directory,
std::string const& log_file_name,
uint32_t log_file_roll_size_mb);
#define VDEBUG_LOG(LEVEL) \
VDebugServer() == VDebug(LEVEL, __FILE__, __func__, __LINE__).debug()
#define vDebug is_logged(LogLevel::INFO) && VDEBUG_LOG(LogLevel::INFO)
#define vWarning is_logged(LogLevel::WARN) && VDEBUG_LOG(LogLevel::WARN)
#define vCritical is_logged(LogLevel::CRIT) && VDEBUG_LOG(LogLevel::CRIT)
#else
struct VDebug
{
template<typename Args>
VDebug& operator<<(const Args &){return *this;}
};
#define vDebug VDebug()
#define vWarning VDebug()
#define vCritical VDebug()
#endif //LOTTIE_LOGGING_SUPPORT
#endif // VDEBUG_H
| 5,749 | vdebug | h | en | c | code | {"qsc_code_num_words": 784, "qsc_code_num_chars": 5749.0, "qsc_code_mean_word_length": 4.81760204, "qsc_code_frac_words_unique": 0.33673469, "qsc_code_frac_chars_top_2grams": 0.04447975, "qsc_code_frac_chars_top_3grams": 0.03600741, "qsc_code_frac_chars_top_4grams": 0.025417, "qsc_code_frac_chars_dupe_5grams": 0.16812285, "qsc_code_frac_chars_dupe_6grams": 0.13899921, "qsc_code_frac_chars_dupe_7grams": 0.13105639, "qsc_code_frac_chars_dupe_8grams": 0.11252317, "qsc_code_frac_chars_dupe_9grams": 0.09981467, "qsc_code_frac_chars_dupe_10grams": 0.09981467, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.01048873, "qsc_code_frac_chars_whitespace": 0.2205601, "qsc_code_size_file_byte": 5749.0, "qsc_code_num_lines": 187.0, "qsc_code_num_chars_line_max": 82.0, "qsc_code_num_chars_line_mean": 30.74331551, "qsc_code_frac_chars_alphabet": 0.83240348, "qsc_code_frac_chars_comments": 0.38980692, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.23148148, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.0022805, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codec_frac_lines_func_ratio": 0.2037037, "qsc_codec_cate_bitsstdc": 0.0, "qsc_codec_nums_lines_main": 0, "qsc_codec_frac_lines_goto": 0.0, "qsc_codec_cate_var_zero": 0.0, "qsc_codec_score_lines_no_logic": 0.27777778, "qsc_codec_frac_lines_print": 0.0, "qsc_codec_frac_lines_preprocessor_directives": null} | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codec_frac_lines_func_ratio": 1, "qsc_codec_nums_lines_main": 0, "qsc_codec_score_lines_no_logic": 0, "qsc_codec_frac_lines_preprocessor_directives": 0, "qsc_codec_frac_lines_print": 0} |
0015/esp_rlottie | rlottie/src/vector/vraster.h | /*
* Copyright (c) 2020 Samsung Electronics Co., Ltd. All rights reserved.
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#ifndef VRASTER_H
#define VRASTER_H
#include <future>
#include "vglobal.h"
#include "vrect.h"
V_BEGIN_NAMESPACE
class VPath;
class VRle;
class VRasterizer
{
public:
void rasterize(VPath path, FillRule fillRule = FillRule::Winding, const VRect &clip = VRect());
void rasterize(VPath path, CapStyle cap, JoinStyle join, float width,
float miterLimit, const VRect &clip = VRect());
VRle rle();
private:
struct VRasterizerImpl;
void init();
void updateRequest();
std::shared_ptr<VRasterizerImpl> d{nullptr};
};
V_END_NAMESPACE
#endif // VRASTER_H
| 1,746 | vraster | h | en | c | code | {"qsc_code_num_words": 246, "qsc_code_num_chars": 1746.0, "qsc_code_mean_word_length": 5.23577236, "qsc_code_frac_words_unique": 0.57317073, "qsc_code_frac_chars_top_2grams": 0.06832298, "qsc_code_frac_chars_top_3grams": 0.02018634, "qsc_code_frac_chars_top_4grams": 0.03416149, "qsc_code_frac_chars_dupe_5grams": 0.0, "qsc_code_frac_chars_dupe_6grams": 0.0, "qsc_code_frac_chars_dupe_7grams": 0.0, "qsc_code_frac_chars_dupe_8grams": 0.0, "qsc_code_frac_chars_dupe_9grams": 0.0, "qsc_code_frac_chars_dupe_10grams": 0.0, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.00281889, "qsc_code_frac_chars_whitespace": 0.18728522, "qsc_code_size_file_byte": 1746.0, "qsc_code_num_lines": 50.0, "qsc_code_num_chars_line_max": 100.0, "qsc_code_num_chars_line_mean": 34.92, "qsc_code_frac_chars_alphabet": 0.90486258, "qsc_code_frac_chars_comments": 0.66494845, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.0, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.02735043, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codec_frac_lines_func_ratio": 0.2173913, "qsc_codec_cate_bitsstdc": 0.0, "qsc_codec_nums_lines_main": 0, "qsc_codec_frac_lines_goto": 0.0, "qsc_codec_cate_var_zero": 0.0, "qsc_codec_score_lines_no_logic": 0.39130435, "qsc_codec_frac_lines_print": 0.0, "qsc_codec_frac_lines_preprocessor_directives": null} | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codec_frac_lines_func_ratio": 1, "qsc_codec_nums_lines_main": 0, "qsc_codec_score_lines_no_logic": 0, "qsc_codec_frac_lines_preprocessor_directives": 0, "qsc_codec_frac_lines_print": 0} |
0015/T-Glass-Applications | image_capture_app/t_glass_ble_app/lib/main.dart | import 'dart:async';
import 'dart:io';
import 'dart:typed_data';
import 'package:image/image.dart' as img;
import 'package:shared_preferences/shared_preferences.dart';
import 'package:flutter/foundation.dart';
import 'package:bitsdojo_window/bitsdojo_window.dart';
import 'package:flutter/material.dart';
import 'package:path_provider/path_provider.dart';
import 'package:screen_capturer/screen_capturer.dart';
import 'package:system_tray/system_tray.dart';
import 'package:flutter_blue_plus/flutter_blue_plus.dart';
void main() async {
WidgetsFlutterBinding.ensureInitialized();
runApp(
const MyApp(),
);
doWhenWindowReady(() {
final win = appWindow;
const initialSize = Size(600, 450);
win.minSize = initialSize;
win.size = initialSize;
win.alignment = Alignment.center;
win.title = "T-Glass BLE APP";
win.show();
});
}
String getTrayImagePath(String imageName) {
return Platform.isWindows ? 'assets/$imageName.ico' : 'assets/$imageName.png';
}
String getImagePath(String imageName) {
return Platform.isWindows ? 'assets/$imageName.bmp' : 'assets/$imageName.png';
}
class MyApp extends StatefulWidget {
const MyApp({Key? key}) : super(key: key);
@override
State<MyApp> createState() => _MyAppState();
}
class _MyAppState extends State<MyApp> {
//SCREENSHOT
Directory? _screenshotsDirectory;
CapturedData? _lastCapturedData;
//BLE
bool _isScanning = false;
bool _isConnected = false;
String _buttonText = "Start Scanning";
final String ServiceUUID = "00ff";
final String charUUID = "ff01";
final int desiredMtu = 215; // [[[You need to check the set MTU size.]]]
String _targetDeviceName = ""; // Target device name entered by user
final AppWindow _appWindow = AppWindow();
final SystemTray _systemTray = SystemTray();
final Menu _trayMenu = Menu();
bool _isDarkMode = false;
BluetoothDevice? _connectedDevice;
BluetoothCharacteristic? _targetCharacteristic;
/// Load saved theme preference
Future<void> _loadThemePreference() async {
SharedPreferences prefs = await SharedPreferences.getInstance();
setState(() {
_isDarkMode = prefs.getBool('isDarkMode') ?? false;
});
}
/// Toggle theme and save preference
Future<void> _toggleTheme() async {
setState(() {
_isDarkMode = !_isDarkMode;
});
SharedPreferences prefs = await SharedPreferences.getInstance();
await prefs.setBool('isDarkMode', _isDarkMode);
}
Future<void> _handleClickCapture(CaptureMode mode) async {
Directory directory =
_screenshotsDirectory ?? await getApplicationDocumentsDirectory();
String imageName =
'Screenshot-${DateTime.now().millisecondsSinceEpoch}.png';
String imagePath =
'${directory.path}/screen_capturer_example/Screenshots/$imageName';
_lastCapturedData = await screenCapturer.capture(
mode: mode,
imagePath: imagePath,
copyToClipboard: false,
silent: true,
);
if (_lastCapturedData != null) {
// ignore: avoid_print
// print(_lastCapturedData!.toJson());
} else {
// ignore: avoid_print
print('User canceled capture');
}
setState(() {});
}
@override
void initState() {
super.initState();
_loadThemePreference();
_initSystemTray();
}
@override
void dispose() {
super.dispose();
}
Future<Uint8List> convertPngToRgb565(String imagePath) async {
// Load the image file
File file = File(imagePath);
Uint8List imageBytes = await file.readAsBytes();
// Decode the PNG image
img.Image? image = img.decodeImage(imageBytes);
if (image == null) {
throw Exception("Failed to decode image.");
}
// Define target size
const int targetSize = 126;
// Resize while maintaining aspect ratio
img.Image resizedImage = img.copyResize(image,
width: targetSize, height: targetSize, maintainAspect: true);
// Create a blank 126x126 image with a black background (or any color you want)
Uint8List blankImageBytes =
Uint8List(targetSize * targetSize * 4); // 4 bytes per pixel (RGBA)
ByteBuffer buffer =
Uint8List.fromList(blankImageBytes).buffer; // Convert to ByteBuffer
// Create a blank 126x126 image with a black background (or any color you want)
img.Image finalImage = img.Image.fromBytes(
width: targetSize, height: targetSize, bytes: buffer);
// Draw the resized image centered onto the final canvas
int offsetX = (targetSize - resizedImage.width) ~/ 2;
int offsetY = (targetSize - resizedImage.height) ~/ 2;
img.compositeImage(finalImage, resizedImage, dstX: offsetX, dstY: offsetY);
// Prepare RGB565 buffer
Uint8List rgb565Data = Uint8List(targetSize * targetSize * 2);
ByteData byteData = ByteData.view(rgb565Data.buffer);
int index = 0;
for (int y = 0; y < finalImage.height; y++) {
for (int x = 0; x < finalImage.width; x++) {
img.Pixel pixel = finalImage.getPixel(x, y);
// Extract RGB components and cast to int
int r = pixel.r.toInt();
int g = pixel.g.toInt();
int b = pixel.b.toInt();
// Convert to RGB565 format
int rgb565 = ((r >> 3) << 11) | ((g >> 2) << 5) | (b >> 3);
// Store as two bytes (Little Endian format)
byteData.setUint16(index, rgb565, Endian.little);
index += 2;
}
}
return rgb565Data;
}
/// Function to send data chunk over BLE
Future<void> _sendChunkToBLE(Uint8List chunk) async {
// Replace with your actual BLE characteristic write function
if (_targetCharacteristic != null) {
try {
await _targetCharacteristic!.write(chunk,
withoutResponse: true, allowLongWrite: false, timeout: 60);
debugPrint("Data written to characteristic.");
} catch (e) {
debugPrint("Failed to write data: $e");
}
}
}
void _sendImageOverBLE() async {
if (_lastCapturedData == null || _lastCapturedData!.imagePath == null) {
print("No image to send.");
return;
}
try {
Uint8List rgb565Data =
await convertPngToRgb565(_lastCapturedData!.imagePath!);
// Send over BLE or use for display
print("RGB565 Data Length: ${rgb565Data.length}");
// Send in chunks (assuming BLE characteristic write method)
int chunkSize = desiredMtu; // Adjust based on BLE MTU size
for (int i = 0; i < rgb565Data.length; i += chunkSize) {
int end = (i + chunkSize < rgb565Data.length)
? i + chunkSize
: rgb565Data.length;
Uint8List chunk = rgb565Data.sublist(i, end);
// Send the chunk over BLE (example method, replace with your actual BLE library)
await _sendChunkToBLE(chunk);
}
} catch (e) {
print("Error: $e");
}
print("Image sent over BLE successfully!");
}
void _toggleScanOrDisconnect() async {
if (_isConnected) {
// Disconnect
await _connectedDevice?.disconnect();
debugPrint("Disconnected from device.");
// Wait for clean disconnection
await Future.delayed(const Duration(seconds: 1));
setState(() {
_isConnected = false;
_buttonText = "Start Scanning";
});
} else {
if (_isScanning) {
await FlutterBluePlus.stopScan();
debugPrint("Scanning stopped.");
setState(() {
_isScanning = false;
_buttonText = "Start Scanning";
});
} else {
if (_targetDeviceName.isEmpty) {
debugPrint("Please enter a device name.");
return;
}
// Ensure Bluetooth is ON before scanning
await FlutterBluePlus.adapterState
.firstWhere((state) => state == BluetoothAdapterState.on);
await FlutterBluePlus.stopScan(); // Stop any previous scan
debugPrint("Reset BLE state.");
// Start scanning
FlutterBluePlus.startScan(timeout: const Duration(seconds: 10));
setState(() {
_isScanning = true;
_buttonText = "Stop Scanning";
});
// Listen for scan results
FlutterBluePlus.scanResults.listen((results) async {
for (ScanResult r in results) {
if (r.device.advName == _targetDeviceName) {
debugPrint("Found target device: $_targetDeviceName");
// Stop scanning
await FlutterBluePlus.stopScan();
setState(() {
_isScanning = false;
_buttonText = "Connecting...";
});
// Connect to the device
try {
await r.device.connect();
_connectedDevice = r.device;
debugPrint("Connected to $_targetDeviceName");
setState(() {
_isConnected = true;
_buttonText = "Disconnect";
});
// Discover services and characteristics
List<BluetoothService> services =
await r.device.discoverServices();
for (BluetoothService service in services) {
for (BluetoothCharacteristic characteristic
in service.characteristics) {
// Find the characteristic with the target UUID
if (characteristic.uuid.toString() == charUUID) {
_targetCharacteristic = characteristic;
debugPrint(
"Found target characteristic: ${characteristic.uuid.toString()}");
}
}
}
} catch (e) {
debugPrint("Failed to connect: $e");
setState(() {
_buttonText = "Start Scanning";
});
}
return; // Exit after connecting
}
}
});
}
}
}
Future<void> _initSystemTray() async {
// We first init the systray menu and then add the menu entries
await _systemTray.initSystemTray(iconPath: getTrayImagePath('app_icon'));
_systemTray.setTitle("T-Glass");
_systemTray.setToolTip("T-Glass BT App");
// handle system tray event
_systemTray.registerSystemTrayEventHandler((eventName) {
debugPrint("eventName: $eventName");
if (eventName == kSystemTrayEventClick) {
Platform.isWindows ? _appWindow.show() : _systemTray.popUpContextMenu();
} else if (eventName == kSystemTrayEventRightClick) {
Platform.isWindows ? _systemTray.popUpContextMenu() : _appWindow.show();
}
});
await _trayMenu.buildFrom([
MenuItemLabel(
label: 'Capture & Send',
image: getImagePath('app_icon'),
onClicked: (menuItem) async {
if (_isConnected) {
await _handleClickCapture(CaptureMode.region);
_sendImageOverBLE();
}
},
),
MenuSeparator(),
MenuItemLabel(label: 'Show', onClicked: (menuItem) => _appWindow.show()),
MenuItemLabel(label: 'Hide', onClicked: (menuItem) => _appWindow.hide()),
MenuItemLabel(
label: 'Exit',
onClicked: (menuItem) => _appWindow.close(),
),
]);
_systemTray.setContextMenu(_trayMenu);
}
@override
Widget build(BuildContext context) {
return MaterialApp(
debugShowCheckedModeBanner: false,
theme: _isDarkMode ? ThemeData.dark() : ThemeData.light(),
home: Scaffold(
body: WindowBorder(
color: const Color(0xFF805306),
width: 1,
child: Column(
children: [
const TitleBar(
appName: 'Capture Tool for T-Glass',
),
Align(
alignment: Alignment.topRight,
child: IconButton(
icon: Icon(_isDarkMode ? Icons.light_mode : Icons.dark_mode),
onPressed: _toggleTheme,
tooltip: "Toggle Dark Mode",
),
),
Expanded(
child: Padding(
padding: const EdgeInsets.all(20.0),
child: Column(
mainAxisAlignment: MainAxisAlignment.center,
children: [
Row(
crossAxisAlignment: CrossAxisAlignment.center,
children: [
Expanded(
child: TextField(
decoration: const InputDecoration(
labelText: "Enter Target Device Name",
border: OutlineInputBorder(),
),
onChanged: (value) {
setState(() {
_targetDeviceName = value;
});
},
readOnly: _isConnected,
),
),
const SizedBox(width: 10),
ElevatedButton(
style: ElevatedButton.styleFrom(
shape: RoundedRectangleBorder(
borderRadius: BorderRadius.circular(8),
),
padding: const EdgeInsets.symmetric(
horizontal: 16, vertical: 14),
textStyle: const TextStyle(
fontSize: 16, fontWeight: FontWeight.bold),
),
onPressed: _toggleScanOrDisconnect,
child: Text(_buttonText),
),
],
),
const SizedBox(height: 20),
// Image display section
if (_isConnected &&
_lastCapturedData != null &&
_lastCapturedData?.imagePath != null)
Expanded(
child: Container(
width: double.infinity,
decoration: BoxDecoration(
border: Border.all(color: Colors.grey, width: 2),
borderRadius: BorderRadius.circular(8),
),
child: ClipRRect(
borderRadius: BorderRadius.circular(6),
child: Image.file(
File(_lastCapturedData!.imagePath!),
fit: BoxFit.contain, // Prevent overflow
),
),
),
),
if (_isConnected &&
_lastCapturedData != null &&
_lastCapturedData?.imagePath != null)
SizedBox(
width: double.infinity, // Full width button
child: FilledButton(
onPressed: () {
_sendImageOverBLE();
},
child: const Text('Send'),
),
),
if (_isConnected) const SizedBox(height: 20),
if (_isConnected)
SizedBox(
width: double.infinity, // Full width button
child: FilledButton(
onPressed: () {
_handleClickCapture(CaptureMode.region);
},
child: const Text('Capture Region'),
),
),
],
),
),
),
],
),
),
),
);
}
}
class TitleBar extends StatelessWidget {
const TitleBar({Key? key, required this.appName}) : super(key: key);
final String appName;
@override
Widget build(BuildContext context) {
return WindowTitleBarBox(
child: Row(
children: [
const Spacer(),
Padding(
padding: const EdgeInsets.only(left: 8.0),
child: Text(appName),
),
Expanded(
child: MoveWindow(),
),
const WindowButtons()
],
),
);
}
}
final buttonColors = WindowButtonColors(
iconNormal: const Color(0xFF805306),
mouseOver: const Color(0xFFF6A00C),
mouseDown: const Color(0xFF805306),
iconMouseOver: const Color(0xFF805306),
iconMouseDown: const Color(0xFFFFD500));
final closeButtonColors = WindowButtonColors(
mouseOver: const Color(0xFFD32F2F),
mouseDown: const Color(0xFFB71C1C),
iconNormal: const Color(0xFF805306),
iconMouseOver: Colors.white);
class WindowButtons extends StatelessWidget {
const WindowButtons({Key? key}) : super(key: key);
@override
Widget build(BuildContext context) {
return Row(
children: [
MinimizeWindowButton(colors: buttonColors),
MaximizeWindowButton(colors: buttonColors),
CloseWindowButton(
colors: closeButtonColors,
onPressed: () {
showDialog<void>(
context: context,
barrierDismissible: false,
builder: (BuildContext context) {
return AlertDialog(
title: const Text('Exit Program?'),
content: const Text(
('The window will be hidden, to exit the program you can use the system menu.')),
actions: <Widget>[
TextButton(
child: const Text('OK'),
onPressed: () {
Navigator.of(context).pop();
appWindow.hide();
},
),
],
);
},
);
},
),
],
);
}
}
| 18,363 | main | dart | en | dart | code | {"qsc_code_num_words": 1434, "qsc_code_num_chars": 18363.0, "qsc_code_mean_word_length": 6.80195258, "qsc_code_frac_words_unique": 0.33263598, "qsc_code_frac_chars_top_2grams": 0.01199508, "qsc_code_frac_chars_top_3grams": 0.01220012, "qsc_code_frac_chars_top_4grams": 0.00738159, "qsc_code_frac_chars_dupe_5grams": 0.10098421, "qsc_code_frac_chars_dupe_6grams": 0.07484109, "qsc_code_frac_chars_dupe_7grams": 0.05003076, "qsc_code_frac_chars_dupe_8grams": 0.02645069, "qsc_code_frac_chars_dupe_9grams": 0.02645069, "qsc_code_frac_chars_dupe_10grams": 0.02645069, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.0156183, "qsc_code_frac_chars_whitespace": 0.3654087, "qsc_code_size_file_byte": 18363.0, "qsc_code_num_lines": 555.0, "qsc_code_num_chars_line_max": 104.0, "qsc_code_num_chars_line_mean": 33.08648649, "qsc_code_frac_chars_alphabet": 0.82141938, "qsc_code_frac_chars_comments": 0.08380983, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.2967033, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.08368997, "qsc_code_frac_chars_long_word_length": 0.03459344, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0053495, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0} |
0015/T-Glass-Applications | image_capture_app/t_glass_ble_app/macos/Podfile | platform :osx, '10.14'
# CocoaPods analytics sends network stats synchronously affecting flutter build latency.
ENV['COCOAPODS_DISABLE_STATS'] = 'true'
project 'Runner', {
'Debug' => :debug,
'Profile' => :release,
'Release' => :release,
}
def flutter_root
generated_xcode_build_settings_path = File.expand_path(File.join('..', 'Flutter', 'ephemeral', 'Flutter-Generated.xcconfig'), __FILE__)
unless File.exist?(generated_xcode_build_settings_path)
raise "#{generated_xcode_build_settings_path} must exist. If you're running pod install manually, make sure \"flutter pub get\" is executed first"
end
File.foreach(generated_xcode_build_settings_path) do |line|
matches = line.match(/FLUTTER_ROOT\=(.*)/)
return matches[1].strip if matches
end
raise "FLUTTER_ROOT not found in #{generated_xcode_build_settings_path}. Try deleting Flutter-Generated.xcconfig, then run \"flutter pub get\""
end
require File.expand_path(File.join('packages', 'flutter_tools', 'bin', 'podhelper'), flutter_root)
flutter_macos_podfile_setup
target 'Runner' do
use_frameworks!
use_modular_headers!
flutter_install_all_macos_pods File.dirname(File.realpath(__FILE__))
target 'RunnerTests' do
inherit! :search_paths
end
end
post_install do |installer|
installer.pods_project.targets.each do |target|
flutter_additional_macos_build_settings(target)
end
end
| 1,389 | Podfile | en | ruby | code | {"qsc_code_num_words": 183, "qsc_code_num_chars": 1389.0, "qsc_code_mean_word_length": 5.50819672, "qsc_code_frac_words_unique": 0.50819672, "qsc_code_frac_chars_top_2grams": 0.07738095, "qsc_code_frac_chars_top_3grams": 0.09424603, "qsc_code_frac_chars_top_4grams": 0.13392857, "qsc_code_frac_chars_dupe_5grams": 0.19742063, "qsc_code_frac_chars_dupe_6grams": 0.0, "qsc_code_frac_chars_dupe_7grams": 0.0, "qsc_code_frac_chars_dupe_8grams": 0.0, "qsc_code_frac_chars_dupe_9grams": 0.0, "qsc_code_frac_chars_dupe_10grams": 0.0, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.00412541, "qsc_code_frac_chars_whitespace": 0.12742981, "qsc_code_size_file_byte": 1389.0, "qsc_code_num_lines": 43.0, "qsc_code_num_chars_line_max": 151.0, "qsc_code_num_chars_line_mean": 32.30232558, "qsc_code_frac_chars_alphabet": 0.82755776, "qsc_code_frac_chars_comments": 0.06335493, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.21212121, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.29823213, "qsc_code_frac_chars_long_word_length": 0.11760184, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0} | |
0015/T-Glass-Applications | image_capture_app/t_glass_ble_app/windows/runner/flutter_window.cpp | #include "flutter_window.h"
#include <optional>
#include "flutter/generated_plugin_registrant.h"
FlutterWindow::FlutterWindow(const flutter::DartProject& project)
: project_(project) {}
FlutterWindow::~FlutterWindow() {}
bool FlutterWindow::OnCreate() {
if (!Win32Window::OnCreate()) {
return false;
}
RECT frame = GetClientArea();
// The size here must match the window dimensions to avoid unnecessary surface
// creation / destruction in the startup path.
flutter_controller_ = std::make_unique<flutter::FlutterViewController>(
frame.right - frame.left, frame.bottom - frame.top, project_);
// Ensure that basic setup of the controller was successful.
if (!flutter_controller_->engine() || !flutter_controller_->view()) {
return false;
}
RegisterPlugins(flutter_controller_->engine());
SetChildContent(flutter_controller_->view()->GetNativeWindow());
flutter_controller_->engine()->SetNextFrameCallback([&]() {
this->Show();
});
// Flutter can complete the first frame before the "show window" callback is
// registered. The following call ensures a frame is pending to ensure the
// window is shown. It is a no-op if the first frame hasn't completed yet.
flutter_controller_->ForceRedraw();
return true;
}
void FlutterWindow::OnDestroy() {
if (flutter_controller_) {
flutter_controller_ = nullptr;
}
Win32Window::OnDestroy();
}
LRESULT
FlutterWindow::MessageHandler(HWND hwnd, UINT const message,
WPARAM const wparam,
LPARAM const lparam) noexcept {
// Give Flutter, including plugins, an opportunity to handle window messages.
if (flutter_controller_) {
std::optional<LRESULT> result =
flutter_controller_->HandleTopLevelWindowProc(hwnd, message, wparam,
lparam);
if (result) {
return *result;
}
}
switch (message) {
case WM_FONTCHANGE:
flutter_controller_->engine()->ReloadSystemFonts();
break;
}
return Win32Window::MessageHandler(hwnd, message, wparam, lparam);
}
| 2,122 | flutter_window | cpp | en | cpp | code | {"qsc_code_num_words": 216, "qsc_code_num_chars": 2122.0, "qsc_code_mean_word_length": 6.55092593, "qsc_code_frac_words_unique": 0.5, "qsc_code_frac_chars_top_2grams": 0.14416961, "qsc_code_frac_chars_top_3grams": 0.06501767, "qsc_code_frac_chars_top_4grams": 0.03250883, "qsc_code_frac_chars_dupe_5grams": 0.0, "qsc_code_frac_chars_dupe_6grams": 0.0, "qsc_code_frac_chars_dupe_7grams": 0.0, "qsc_code_frac_chars_dupe_8grams": 0.0, "qsc_code_frac_chars_dupe_9grams": 0.0, "qsc_code_frac_chars_dupe_10grams": 0.0, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.00357995, "qsc_code_frac_chars_whitespace": 0.21017908, "qsc_code_size_file_byte": 2122.0, "qsc_code_num_lines": 71.0, "qsc_code_num_chars_line_max": 81.0, "qsc_code_num_chars_line_mean": 29.88732394, "qsc_code_frac_chars_alphabet": 0.84069212, "qsc_code_frac_chars_comments": 0.23185674, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.08163265, "qsc_code_cate_autogen": 1.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.03251534, "qsc_code_frac_chars_long_word_length": 0.02269939, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codecpp_frac_lines_preprocessor_directives": 0.06122449, "qsc_codecpp_frac_lines_func_ratio": 0.0, "qsc_codecpp_cate_bitsstdc": 0.0, "qsc_codecpp_nums_lines_main": 0.0, "qsc_codecpp_frac_lines_goto": 0.0, "qsc_codecpp_cate_var_zero": 0.0, "qsc_codecpp_score_lines_no_logic": 0.12244898, "qsc_codecpp_frac_lines_print": 0.0} | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 1, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codecpp_frac_lines_func_ratio": 0, "qsc_codecpp_nums_lines_main": 0, "qsc_codecpp_score_lines_no_logic": 0, "qsc_codecpp_frac_lines_preprocessor_directives": 0, "qsc_codecpp_frac_lines_print": 0} |
0015/T-Glass-Applications | image_capture_app/t_glass_ble_app/windows/runner/main.cpp | #include <flutter/dart_project.h>
#include <flutter/flutter_view_controller.h>
#include <windows.h>
#include "flutter_window.h"
#include "utils.h"
int APIENTRY wWinMain(_In_ HINSTANCE instance, _In_opt_ HINSTANCE prev,
_In_ wchar_t *command_line, _In_ int show_command) {
// Attach to console when present (e.g., 'flutter run') or create a
// new console when running with a debugger.
if (!::AttachConsole(ATTACH_PARENT_PROCESS) && ::IsDebuggerPresent()) {
CreateAndAttachConsole();
}
// Initialize COM, so that it is available for use in the library and/or
// plugins.
::CoInitializeEx(nullptr, COINIT_APARTMENTTHREADED);
flutter::DartProject project(L"data");
std::vector<std::string> command_line_arguments =
GetCommandLineArguments();
project.set_dart_entrypoint_arguments(std::move(command_line_arguments));
FlutterWindow window(project);
Win32Window::Point origin(10, 10);
Win32Window::Size size(1280, 720);
if (!window.Create(L"t_glass_ble_app", origin, size)) {
return EXIT_FAILURE;
}
window.SetQuitOnClose(true);
::MSG msg;
while (::GetMessage(&msg, nullptr, 0, 0)) {
::TranslateMessage(&msg);
::DispatchMessage(&msg);
}
::CoUninitialize();
return EXIT_SUCCESS;
}
| 1,268 | main | cpp | en | cpp | code | {"qsc_code_num_words": 153, "qsc_code_num_chars": 1268.0, "qsc_code_mean_word_length": 5.68627451, "qsc_code_frac_words_unique": 0.62745098, "qsc_code_frac_chars_top_2grams": 0.03678161, "qsc_code_frac_chars_top_3grams": 0.03448276, "qsc_code_frac_chars_top_4grams": 0.0, "qsc_code_frac_chars_dupe_5grams": 0.0, "qsc_code_frac_chars_dupe_6grams": 0.0, "qsc_code_frac_chars_dupe_7grams": 0.0, "qsc_code_frac_chars_dupe_8grams": 0.0, "qsc_code_frac_chars_dupe_9grams": 0.0, "qsc_code_frac_chars_dupe_10grams": 0.0, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.01597744, "qsc_code_frac_chars_whitespace": 0.16088328, "qsc_code_size_file_byte": 1268.0, "qsc_code_num_lines": 43.0, "qsc_code_num_chars_line_max": 76.0, "qsc_code_num_chars_line_mean": 29.48837209, "qsc_code_frac_chars_alphabet": 0.80169173, "qsc_code_frac_chars_comments": 0.15615142, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.0, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.03925234, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codecpp_frac_lines_preprocessor_directives": 0.16666667, "qsc_codecpp_frac_lines_func_ratio": 0.16666667, "qsc_codecpp_cate_bitsstdc": 0.0, "qsc_codecpp_nums_lines_main": 0.0, "qsc_codecpp_frac_lines_goto": 0.0, "qsc_codecpp_cate_var_zero": 0.0, "qsc_codecpp_score_lines_no_logic": 0.4, "qsc_codecpp_frac_lines_print": 0.0} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codecpp_frac_lines_func_ratio": 0, "qsc_codecpp_nums_lines_main": 0, "qsc_codecpp_score_lines_no_logic": 0, "qsc_codecpp_frac_lines_preprocessor_directives": 0, "qsc_codecpp_frac_lines_print": 0} |
0000cd/wolf-set | themes/bluf/layouts/_default/met.html | <!DOCTYPE html>
<html>
<head>
<meta charset="utf-8" />
<title>Meting Music</title>
<meta name="robots" content="noindex, nofollow">
<link rel="stylesheet" href="/css/APlayer.min.css">
<script src="/js/APlayer.min.js"></script>
<script src="/js/Meting.min.js"></script>
<style>
body {
background-color: #020202;
}
.aplayer {
margin: 0px;
}
.loading {
text-align: center;
padding: 10px;
}
.loading::after {
content: "";
display: inline-block;
width: 24px;
height: 24px;
border: 2px solid #f3f3f3;
border-top: 2px solid {{ .Site.Params.lightColor }};
border-radius: 50%;
animation: spin 1s linear infinite;
margin-left: 10px;
}
@keyframes spin {
0% { transform: rotate(0deg); }
100% { transform: rotate(360deg); }
}
.hide {
display: none !important;
}
</style>
</head>
<body>
<div id="player-container">
<div id="loading" class="loading"></div>
</div>
<script>
const defaultConfig = {
server: 'netease',
type: 'album',
id: '137470856',
autoplay: 'true',
theme: '{{ .Site.Params.lightColor }}',
loop: 'all',
order: 'random',
preload: 'auto',
'list-max-height': '400px'
};
function createPlayer() {
const metingJs = document.createElement('meting-js');
const params = new URLSearchParams(window.location.search);
Object.keys(defaultConfig).forEach(key => {
metingJs.setAttribute(key, params.get(key) || defaultConfig[key]);
});
document.getElementById('player-container').appendChild(metingJs);
new MutationObserver((mutations, obs) => {
const aplayer = document.querySelector('.aplayer');
if (aplayer?.classList.contains('aplayer-withlist')) {
document.getElementById('loading').classList.add('hide');
obs.disconnect();
}
}).observe(document.getElementById('player-container'), {
childList: true,
subtree: true,
attributes: true,
attributeFilter: ['class']
});
}
window.addEventListener('load', createPlayer);
</script>
</body>
</html> | 2,917 | met | html | en | html | code | {"qsc_code_num_words": 216, "qsc_code_num_chars": 2917.0, "qsc_code_mean_word_length": 5.99074074, "qsc_code_frac_words_unique": 0.60185185, "qsc_code_frac_chars_top_2grams": 0.03477589, "qsc_code_frac_chars_top_3grams": 0.01700155, "qsc_code_frac_chars_top_4grams": 0.05718702, "qsc_code_frac_chars_dupe_5grams": 0.0, "qsc_code_frac_chars_dupe_6grams": 0.0, "qsc_code_frac_chars_dupe_7grams": 0.0, "qsc_code_frac_chars_dupe_8grams": 0.0, "qsc_code_frac_chars_dupe_9grams": 0.0, "qsc_code_frac_chars_dupe_10grams": 0.0, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.02657005, "qsc_code_frac_chars_whitespace": 0.43229345, "qsc_code_size_file_byte": 2917.0, "qsc_code_num_lines": 86.0, "qsc_code_num_chars_line_max": 87.0, "qsc_code_num_chars_line_mean": 33.91860465, "qsc_code_frac_chars_alphabet": 0.75483092, "qsc_code_frac_chars_comments": 0.0, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.025, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.10109664, "qsc_code_frac_chars_long_word_length": 0.00788211, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codehtml_cate_ast": 1.0, "qsc_codehtml_frac_words_text": 0.00994172, "qsc_codehtml_num_chars_text": 29.0} | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_cate_xml_start": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_cate_autogen": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_codehtml_cate_ast": 0, "qsc_codehtml_frac_words_text": 1, "qsc_codehtml_num_chars_text": 1} |
0000cd/wolf-set | themes/bluf/layouts/partials/getColorCategory.html | {{- $hex := . -}}
{{- if eq (substr $hex 0 1) "#" -}} {{/* 检查是否以 "#" 开头 */}}
{{- $hex = substr $hex 1 -}} {{/* 去掉 "#" */}}
{{- end -}}
{{/* 将 HEX 转换为 RGB */}}
{{- $r := printf "0x%s" (substr $hex 0 2) | int -}}
{{- $g := printf "0x%s" (substr $hex 2 2) | int -}}
{{- $b := printf "0x%s" (substr $hex 4 2) | int -}}
{{/* 将 RGB 归一化到 [0, 1] */}}
{{- $rf := div (float $r) 255 -}}
{{- $gf := div (float $g) 255 -}}
{{- $bf := div (float $b) 255 -}}
{{/* 模拟 max 和 min 函数 */}}
{{- $max := $rf -}}
{{- if gt $gf $max }} {{- $max = $gf -}} {{- end -}}
{{- if gt $bf $max }} {{- $max = $bf -}} {{- end -}}
{{- $min := $rf -}}
{{- if lt $gf $min }} {{- $min = $gf -}} {{- end -}}
{{- if lt $bf $min }} {{- $min = $bf -}} {{- end -}}
{{/* 计算 HSV 值 */}}
{{- $delta := sub $max $min -}}
{{- $hue := 0.0 -}}
{{- if gt $delta 0.0 -}}
{{- if eq $max $rf -}}
{{- $hue = mod (add (mul 60 (div (sub $gf $bf) $delta)) 360) 360 -}}
{{- else if eq $max $gf -}}
{{- $hue = add (mul 60 (div (sub $bf $rf) $delta)) 120 -}}
{{- else -}}
{{- $hue = add (mul 60 (div (sub $rf $gf) $delta)) 240 -}}
{{- end -}}
{{- end -}}
{{- $saturation := 0.0 -}}
{{- if gt $max 0.0 -}}
{{- $saturation = div $delta $max -}}
{{- end -}}
{{- $value := $max -}}
{{/* 优先判断灰色（包括黑和白） */}}
{{- $result := "unknown" -}}
{{- if le $saturation 0.2 -}}
{{- $result = "gray" -}}
{{- else -}}
{{/* 根据 Hue 值分类颜色 */}}
{{- if or (and (ge $hue 0) (lt $hue 15)) (and (ge $hue 345) (lt $hue 360)) -}}
{{- $result = "red" -}}
{{- else if and (ge $hue 15) (lt $hue 45) -}}
{{- $result = "orange" -}}
{{- else if and (ge $hue 45) (lt $hue 75) -}}
{{- $result = "yellow" -}}
{{- else if and (ge $hue 75) (lt $hue 165) -}}
{{- $result = "green" -}}
{{- else if and (ge $hue 165) (lt $hue 195) -}}
{{- $result = "cyan" -}}
{{- else if and (ge $hue 195) (lt $hue 255) -}}
{{- $result = "blue" -}}
{{- else if and (ge $hue 255) (lt $hue 315) -}}
{{- $result = "purple" -}}
{{- else if and (ge $hue 315) (lt $hue 345) -}}
{{- $result = "pink" -}}
{{- end -}}
{{- end -}}
{{/* 输出最终颜色分类 */}}
{{- $result -}} | 2,132 | getColorCategory | html | en | html | code | {"qsc_code_num_words": 291, "qsc_code_num_chars": 2132.0, "qsc_code_mean_word_length": 2.95189003, "qsc_code_frac_words_unique": 0.27147766, "qsc_code_frac_chars_top_2grams": 0.0523865, "qsc_code_frac_chars_top_3grams": 0.08381839, "qsc_code_frac_chars_top_4grams": 0.08963912, "qsc_code_frac_chars_dupe_5grams": 0.23282887, "qsc_code_frac_chars_dupe_6grams": 0.03958091, "qsc_code_frac_chars_dupe_7grams": 0.0, "qsc_code_frac_chars_dupe_8grams": 0.0, "qsc_code_frac_chars_dupe_9grams": 0.0, "qsc_code_frac_chars_dupe_10grams": 0.0, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.06174411, "qsc_code_frac_chars_whitespace": 0.26313321, "qsc_code_size_file_byte": 2132.0, "qsc_code_num_lines": 74.0, "qsc_code_num_chars_line_max": 81.0, "qsc_code_num_chars_line_mean": 28.81081081, "qsc_code_frac_chars_alphabet": 0.48504137, "qsc_code_frac_chars_comments": 0.0, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.12903226, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.03000469, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codehtml_cate_ast": 1.0, "qsc_codehtml_frac_words_text": 1.0, "qsc_codehtml_num_chars_text": 2132.0} | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 1, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_cate_xml_start": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_cate_autogen": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_codehtml_cate_ast": 0, "qsc_codehtml_frac_words_text": 0, "qsc_codehtml_num_chars_text": 0} |
000haoji/deep-student | src/components/KnowledgeBaseManagement.tsx | import React, { useState, useEffect, useCallback } from 'react';
import { TauriAPI } from '../utils/tauriApi';
import { useNotification } from '../hooks/useNotification';
import type {
RagDocument,
KnowledgeBaseStatusPayload,
RagProcessingEvent,
RagDocumentStatusEvent
} from '../types';
import { listen } from '@tauri-apps/api/event';
import './KnowledgeBaseManagement.css';
import {
BarChart3, FolderOpen, Target, RefreshCcw, Trash2, Upload,
FileText, CheckCircle, BookOpen, Sparkles, Rocket,
Calendar, Scale, Puzzle, Settings, File, Clock
} from 'lucide-react';
interface KnowledgeBaseManagementProps {
className?: string;
}
export const KnowledgeBaseManagement: React.FC<KnowledgeBaseManagementProps> = ({
className = ''
}) => {
const [documents, setDocuments] = useState<RagDocument[]>([]);
const [status, setStatus] = useState<KnowledgeBaseStatusPayload | null>(null);
const [loading, setLoading] = useState(false);
const [uploading, setUploading] = useState(false);
const [processingDocuments, setProcessingDocuments] = useState<Map<string, RagDocumentStatusEvent>>(new Map());
const [selectedFiles, setSelectedFiles] = useState<File[]>([]);
const { showSuccess, showError, showWarning } = useNotification();
// 拖拽状态
const [isDragOver, setIsDragOver] = useState(false);
// 加载知识库状态
const loadKnowledgeBaseStatus = useCallback(async () => {
try {
setLoading(true);
const [statusData, documentsData] = await Promise.all([
TauriAPI.ragGetKnowledgeBaseStatus(),
TauriAPI.ragGetAllDocuments()
]);
setStatus(statusData);
setDocuments(documentsData);
} catch (error) {
console.error('加载知识库状态失败:', error);
showError(`加载知识库状态失败: ${error}`);
} finally {
setLoading(false);
}
}, [showError]);
// 初始加载
useEffect(() => {
loadKnowledgeBaseStatus();
}, [loadKnowledgeBaseStatus]);
// 监听RAG处理事件
useEffect(() => {
const setupEventListeners = async () => {
try {
// 监听整体处理状态
const unlistenProcessing = await listen<RagProcessingEvent>('rag_processing_status', (event) => {
const data = event.payload;
if (data.status === 'completed') {
showSuccess(data.message);
loadKnowledgeBaseStatus(); // 重新加载状态
} else if (data.status === 'error') {
showError(`处理失败: ${data.message}`);
// 清空处理状态，让用户能够重试
setProcessingDocuments(new Map());
} else if (data.status === 'progress') {
// 可以显示整体进度信息
console.log(`整体处理进度: ${Math.round(data.progress * 100)}%`);
}
});
// 监听文档处理状态
const unlistenDocument = await listen<RagDocumentStatusEvent>('rag_document_status', (event) => {
const data = event.payload;
setProcessingDocuments(prev => {
const newMap = new Map(prev);
newMap.set(data.document_id, data);
return newMap;
});
if (data.status === 'Completed') {
showSuccess(`文档 "${data.file_name}" 处理完成，共生成 ${data.total_chunks} 个文本块`);
setTimeout(() => {
setProcessingDocuments(prev => {
const newMap = new Map(prev);
newMap.delete(data.document_id);
return newMap;
});
}, 3000);
} else if (data.status === 'Failed') {
const errorMsg = data.error_message || '未知错误';
showError(`文档 "${data.file_name}" 处理失败: ${errorMsg}`);
// 提供一些常见错误的解决建议
if (errorMsg.includes('Unsupported file format')) {
showWarning('请确保文件格式为 .txt, .md, .pdf 或 .docx');
} else if (errorMsg.includes('File not found')) {
showWarning('文件可能已被移动或删除，请重新选择文件');
} else if (errorMsg.includes('Permission denied')) {
showWarning('没有文件访问权限，请检查文件权限设置');
}
// 保持失败状态显示一段时间，然后清除
setTimeout(() => {
setProcessingDocuments(prev => {
const newMap = new Map(prev);
newMap.delete(data.document_id);
return newMap;
});
}, 8000);
}
});
return () => {
};
} catch (error) {
console.error('设置事件监听器失败:', error);
}
};
setupEventListeners();
}, [showSuccess, showError, loadKnowledgeBaseStatus]);
// 监听文件拖拽事件
useEffect(() => {
const setupFileDragListeners = async () => {
try {
// 尝试使用 Tauri v2 API
const { listen } = await import('@tauri-apps/api/event');
// 监听文件拖拽进入
const unlistenDragEnter = await listen('tauri://file-drop-hover', () => {
setIsDragOver(true);
console.log('文件拖拽进入');
});
// 监听文件拖拽离开
const unlistenDragLeave = await listen('tauri://file-drop-cancelled', () => {
setIsDragOver(false);
console.log('文件拖拽离开');
});
// 监听文件拖拽放下
const unlistenDrop = await listen<string[]>('tauri://file-drop', async (event) => {
setIsDragOver(false);
const filePaths = event.payload;
console.log('拖拽文件路径:', filePaths);
// 过滤支持的文件格式
const supportedExtensions = ['.txt', '.md', '.markdown', '.pdf', '.docx'];
const validFiles = filePaths.filter(path => {
const extension = path.toLowerCase().substring(path.lastIndexOf('.'));
return supportedExtensions.includes(extension);
});
if (validFiles.length === 0) {
showWarning('没有支持的文件格式。支持的格式：.txt, .md, .pdf, .docx');
return;
}
if (validFiles.length !== filePaths.length) {
showWarning(`已过滤不支持的文件，将上传 ${validFiles.length} 个支持的文件`);
}
try {
setUploading(true);
showSuccess(`开始处理 ${validFiles.length} 个文件...`);
await TauriAPI.ragAddDocuments(validFiles);
showSuccess(`成功拖拽上传 ${validFiles.length} 个文件到知识库！`);
// 重新加载知识库状态
await loadKnowledgeBaseStatus();
} catch (error) {
console.error('拖拽上传失败:', error);
let errorMessage = '拖拽上传失败';
if (typeof error === 'string') {
errorMessage = `拖拽上传失败: ${error}`;
} else if (error instanceof Error) {
errorMessage = `拖拽上传失败: ${error.message}`;
}
// 提供更有用的错误信息和建议
if (errorMessage.includes('系统找不到指定的文件') || errorMessage.includes('文件不存在')) {
errorMessage += '\n\n建议：\n• 确保文件未被移动或删除\n• 尝试使用"选择文件"按钮代替拖拽\n• 检查文件名是否包含特殊字符';
}
showError(errorMessage);
} finally {
setUploading(false);
}
});
console.log('文件拖拽监听器设置完成');
return () => {
// 清理拖拽监听器
};
} catch (error) {
console.error('设置文件拖拽监听器失败:', error);
showWarning('文件拖拽功能暂时不可用，请等待应用完全加载');
}
};
setupFileDragListeners();
}, [showSuccess, showError, showWarning, loadKnowledgeBaseStatus]);
// 处理文件选择
const handleFileSelect = (event: React.ChangeEvent<HTMLInputElement>) => {
const files = Array.from(event.target.files || []);
const supportedTypes = ['.txt', '.md', '.markdown', '.pdf', '.docx'];
const validFiles = files.filter(file => {
const extension = file.name.toLowerCase().substring(file.name.lastIndexOf('.'));
return supportedTypes.includes(extension);
});
if (validFiles.length !== files.length) {
showWarning(`只支持 ${supportedTypes.join(', ')} 格式的文件`);
}
setSelectedFiles(validFiles);
};
// 上传文档
const handleUploadDocuments = async () => {
if (selectedFiles.length === 0) {
showWarning('请先选择要上传的文件');
return;
}
try {
setUploading(true);
const documents: Array<{ file_name: string; base64_content: string }> = [];
// 读取文件内容，像Anki组件一样处理
for (const file of selectedFiles) {
try {
const content = await new Promise<string>((resolve, reject) => {
const reader = new FileReader();
reader.onload = (e) => {
const result = e.target?.result as string;
resolve(result);
};
reader.onerror = (e) => reject(e);
// 根据文件类型选择读取方式
if (file.type === 'text/plain' || file.name.endsWith('.txt') || file.name.endsWith('.md')) {
reader.readAsText(file);
} else {
// 对于PDF、DOCX等二进制文件，读取为ArrayBuffer然后转换为base64
reader.onload = (e) => {
const arrayBuffer = e.target?.result as ArrayBuffer;
const base64 = btoa(String.fromCharCode(...new Uint8Array(arrayBuffer)));
resolve(base64);
};
reader.readAsArrayBuffer(file);
}
});
documents.push({
file_name: file.name,
base64_content: content
});
} catch (fileError) {
console.error(`处理文件 ${file.name} 失败:`, fileError);
showError(`处理文件 ${file.name} 失败`);
}
}
if (documents.length === 0) {
showError('没有文件被成功处理');
return;
}
showSuccess(`开始处理 ${documents.length} 个文件...`);
await TauriAPI.ragAddDocumentsFromContent(documents);
showSuccess(`成功上传 ${documents.length} 个文件到知识库！`);
// 清空选择的文件
setSelectedFiles([]);
// 重新加载知识库状态
await loadKnowledgeBaseStatus();
} catch (error) {
console.error('上传文件失败:', error);
let errorMessage = '上传文件失败';
if (typeof error === 'string') {
errorMessage = `上传失败: ${error}`;
} else if (error instanceof Error) {
errorMessage = `上传失败: ${error.message}`;
} else if (error && typeof error === 'object' && 'message' in error) {
errorMessage = `上传失败: ${(error as any).message}`;
}
showError(errorMessage);
// 提供重试建议
showWarning('请检查文件格式是否正确');
} finally {
setUploading(false);
}
};
// 删除文档
const handleDeleteDocument = async (documentId: string, documentName: string) => {
if (!confirm(`确定要删除文档 "${documentName}" 吗？此操作不可撤销。`)) {
return;
}
try {
console.log('开始删除文档:', documentId, documentName);
await TauriAPI.ragDeleteDocument(documentId);
console.log('文档删除成功，开始刷新数据');
showSuccess(`文档 "${documentName}" 已删除`);
// 重新加载知识库状态和文档列表
await loadKnowledgeBaseStatus();
} catch (error) {
console.error('删除文档失败:', error);
showError(`删除文档失败: ${error}`);
}
};
// 清空知识库
const handleClearKnowledgeBase = async () => {
if (!confirm('确定要清空整个知识库吗？此操作将删除所有文档和向量数据，不可撤销。')) {
return;
}
try {
await TauriAPI.ragClearKnowledgeBase();
showSuccess('知识库已清空');
loadKnowledgeBaseStatus();
} catch (error) {
console.error('清空知识库失败:', error);
showError(`清空知识库失败: ${error}`);
}
};
// 格式化文件大小
const formatFileSize = (bytes?: number) => {
if (!bytes) return '未知';
if (bytes < 1024) return `${bytes} B`;
if (bytes < 1024 * 1024) return `${(bytes / 1024).toFixed(1)} KB`;
return `${(bytes / (1024 * 1024)).toFixed(1)} MB`;
};
// 格式化日期
const formatDate = (dateString: string) => {
return new Date(dateString).toLocaleString('zh-CN');
};
// 获取处理状态显示
const getProcessingStatusDisplay = (docId: string) => {
const processing = processingDocuments.get(docId);
if (!processing) return null;
const getStatusText = (status: string) => {
const statusMap: Record<string, string> = {
'Reading': '读取文件',
'Preprocessing': '预处理',
'Chunking': '文本分块',
'Embedding': '生成向量',
'Storing': '存储数据',
'Completed': '处理完成',
'Failed': '处理失败'
};
return statusMap[status] || status;
};
const getStatusClass = (status: string) => {
const classMap: Record<string, string> = {
'Pending': 'pending',
'Reading': 'reading',
'Preprocessing': 'reading',
'Chunking': 'reading',
'Embedding': 'reading',
'Storing': 'reading',
'Completed': 'completed',
'Failed': 'failed'
};
return classMap[status] || 'reading';
};
return (
<div className={`kb-processing-status ${getStatusClass(processing.status)}`}>
<div className="kb-processing-header">
<span className="kb-processing-title">
{getStatusText(processing.status)}
</span>
<span className="kb-processing-percentage">
{Math.round(processing.progress * 100)}%
</span>
</div>
{processing.status !== 'Completed' && processing.status !== 'Failed' && (
<div className="kb-processing-bar">
<div
className="kb-processing-progress"
style={{ width: `${processing.progress * 100}%` }}
/>
</div>
)}
{processing.chunks_processed > 0 && (
<div className="kb-processing-chunks">
<div className="kb-chunks-info" style={{ display: 'flex', alignItems: 'center', gap: '8px' }}>
<BarChart3 size={16} />
已处理 {processing.chunks_processed} / {processing.total_chunks} 个文本块
</div>
{processing.total_chunks > 0 && (
<div className="kb-chunks-progress">
<div
className="kb-chunks-progress-bar"
style={{
width: `${(processing.chunks_processed / processing.total_chunks) * 100}%`
}}
/>
</div>
)}
</div>
)}
</div>
);
};
return (
<div className={`knowledge-base-container ${className} ${isDragOver ? 'drag-over' : ''}`}>
{isDragOver && (
<div className="kb-drag-overlay">
<div className="kb-drag-overlay-content">
<div className="kb-drag-icon" style={{ display: 'flex', justifyContent: 'center', marginBottom: '16px' }}>
<FolderOpen size={48} color="#667eea" />
</div>
<h2 className="kb-drag-title">松开鼠标上传文档</h2>
<p className="kb-drag-subtitle">
支持 .txt, .md, .pdf, .docx 格式的文档
</p>
</div>
</div>
)}
<div className="knowledge-base-content">
{/* 页面标题 */}
<div style={{
background: 'white',
borderBottom: '1px solid #e5e7eb',
padding: '24px 32px',
position: 'relative'
}}>
<div style={{
position: 'absolute',
top: 0,
left: 0,
right: 0,
height: '4px',
background: 'linear-gradient(90deg, #667eea, #764ba2)'
}}></div>
<div style={{ position: 'relative', zIndex: 1 }}>
<div style={{ display: 'flex', alignItems: 'center', marginBottom: '8px' }}>
<svg xmlns="http://www.w3.org/2000/svg" width="32" height="32" viewBox="0 0 24 24" fill="none" stroke="#667eea" strokeWidth="2" strokeLinecap="round" strokeLinejoin="round" style={{ marginRight: '12px' }}>
<path d="M12 5a3 3 0 1 0-5.997.125 4 4 0 0 0-2.526 5.77 4 4 0 0 0 .556 6.588A4 4 0 1 0 12 18Z"/>
<path d="M12 5a3 3 0 1 1 5.997.125 4 4 0 0 1 2.526 5.77 4 4 0 0 1-.556 6.588A4 4 0 1 1 12 18Z"/>
<path d="M15 13a4.5 4.5 0 0 1-3-4 4.5 4.5 0 0 1-3 4"/>
<path d="M17.599 6.5a3 3 0 0 0 .399-1.375"/>
<path d="M6.003 5.125A3 3 0 0 0 6.401 6.5"/>
<path d="M3.477 10.896a4 4 0 0 1 .585-.396"/>
<path d="M19.938 10.5a4 4 0 0 1 .585.396"/>
<path d="M6 18a4 4 0 0 1-1.967-.516"/>
<path d="M19.967 17.484A4 4 0 0 1 18 18"/>
</svg>
<h1 style={{ fontSize: '28px', fontWeight: '700', margin: 0, color: '#1f2937' }}>RAG 知识库管理</h1>
</div>
<p style={{ fontSize: '16px', color: '#6b7280', margin: 0, lineHeight: '1.5' }}>
智能文档管理系统，为AI提供丰富的知识背景，让分析更加精准和深入
</p>
</div>
</div>
{/* 知识库状态 */}
<div className="kb-stats-grid">
<div className="kb-stat-card">
<div className="kb-stat-header">
<div className="kb-stat-icon blue">
<svg style={{ width: '24px', height: '24px' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M12 6.253v13m0-13C10.832 5.477 9.246 5 7.5 5S4.168 5.477 3 6.253v13C4.168 18.477 5.754 18 7.5 18s3.332.477 4.5 1.253m0-13C13.168 5.477 14.754 5 16.5 5c1.746 0 3.332.477 4.5 1.253v13C19.832 18.477 18.246 18 16.5 18c-1.746 0-3.332.477-4.5 1.253" />
</svg>
</div>
<div>
<div className="kb-stat-label">Total Documents</div>
<div className="kb-stat-value">
{loading ? '...' : (status?.total_documents || 0)}
</div>
</div>
</div>
<div className="kb-stat-label">文档总数</div>
<div className="kb-stat-progress">
<div
className="kb-stat-progress-bar"
style={{width: loading ? '0%' : `${Math.min((status?.total_documents || 0) * 10, 100)}%`}}
/>
</div>
</div>
<div className="kb-stat-card">
<div className="kb-stat-header">
<div className="kb-stat-icon green">
<svg style={{ width: '24px', height: '24px' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M8 7v8a2 2 0 002 2h6M8 7V5a2 2 0 012-2h4.586a1 1 0 01.707.293l4.414 4.414a1 1 0 01.293.707V15a2 2 0 01-2 2v0a2 2 0 01-2-2v-5a2 2 0 00-2-2H8z" />
</svg>
</div>
<div>
<div className="kb-stat-label">Text Chunks</div>
<div className="kb-stat-value">
{loading ? '...' : (status?.total_chunks || 0)}
</div>
</div>
</div>
<div className="kb-stat-label">文本块总数</div>
<div className="kb-stat-progress">
<div
className="kb-stat-progress-bar"
style={{width: loading ? '0%' : `${Math.min((status?.total_chunks || 0) * 2, 100)}%`}}
/>
</div>
</div>
<div className="kb-stat-card">
<div className="kb-stat-header">
<div className="kb-stat-icon purple">
<svg style={{ width: '24px', height: '24px' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M4 7v10c0 2.21 3.582 4 8 4s8-1.79 8-4V7M4 7c0 2.21 3.582 4 8 4s8-1.79 8-4M4 7c0-2.21 3.582-4 8-4s8 1.79 8 4m0 5c0 2.21-3.582 4-8 4s-8-1.79-8-4" />
</svg>
</div>
<div>
<div className="kb-stat-label">Vector Store</div>
<div className="kb-stat-value" style={{fontSize: '1.5rem'}}>
{loading ? '...' : (status?.vector_store_type || 'SQLite')}
</div>
</div>
</div>
<div className="kb-stat-label">向量存储</div>
<div className="kb-stat-status">
<div className="kb-status-dot green"></div>
<span>运行中</span>
</div>
</div>
<div className="kb-stat-card">
<div className="kb-stat-header">
<div className="kb-stat-icon orange">
<svg style={{ width: '24px', height: '24px' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M9.663 17h4.673M12 3v1m6.364 1.636l-.707.707M21 12h-1M4 12H3m3.343-5.657l-.707-.707m2.828 9.9a5 5 0 117.072 0l-.548.547A3.374 3.374 0 0014 18.469V19a2 2 0 11-4 0v-.531c0-.895-.356-1.754-.988-2.386l-.548-.547z" />
</svg>
</div>
<div>
<div className="kb-stat-label">AI Model</div>
<div className="kb-stat-value" style={{fontSize: '1rem'}}>
{loading ? '...' : (status?.embedding_model_name || '未配置')}
</div>
</div>
</div>
<div className="kb-stat-label">嵌入模型</div>
<div className="kb-stat-status">
<div className={`kb-status-dot ${status?.embedding_model_name ? 'green' : 'red'}`}></div>
<span>{status?.embedding_model_name ? '已配置' : '待配置'}</span>
</div>
</div>
</div>
{/* 文件上传区域 */}
<div className="kb-upload-section">
<div className="kb-upload-header">
<div className="kb-upload-icon">
<svg style={{ width: '24px', height: '24px', color: '#667eea' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M7 16a4 4 0 01-.88-7.903A5 5 0 1115.9 6L16 6a5 5 0 011 9.9M9 19l3 3m0 0l3-3m-3 3V10" />
</svg>
</div>
<div>
<div className="kb-upload-title">上传文档</div>
<div className="kb-upload-subtitle">支持多种格式，智能解析文档内容</div>
</div>
</div>
<div>
<div>
<label htmlFor="file-upload" style={{fontSize: '1.1rem', fontWeight: '600', color: '#2d3748', marginBottom: '1rem', display: 'flex', alignItems: 'center', gap: '8px'}}>
<svg style={{ width: '20px', height: '20px', color: '#667eea' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M3 7v10a2 2 0 002 2h14a2 2 0 002-2V9a2 2 0 00-2-2h-6l-2-2H5a2 2 0 00-2 2z" />
</svg>
选择文档文件
</label>
<div style={{marginBottom: '1.5rem'}}>
<div style={{fontSize: '0.9rem', color: '#666', marginBottom: '0.75rem', display: 'flex', alignItems: 'center', gap: '8px'}}>
<Sparkles size={16} />
支持格式:
</div>
<div className="kb-format-tags">
<span className="kb-format-tag txt">
<svg style={{ width: '16px', height: '16px', marginRight: '4px' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M9 12h6m-6 4h6m2 5H7a2 2 0 01-2-2V5a2 2 0 012-2h5.586a1 1 0 01.707.293l5.414 5.414a1 1 0 01.293.707V19a2 2 0 01-2 2z" />
</svg>
.txt
</span>
<span className="kb-format-tag md">
<svg style={{ width: '16px', height: '16px', marginRight: '4px' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M11 5H6a2 2 0 00-2 2v11a2 2 0 002 2h11a2 2 0 002-2v-5m-1.414-9.414a2 2 0 112.828 2.828L11.828 15H9v-2.828l8.586-8.586z" />
</svg>
.md
</span>
<span className="kb-format-tag pdf">
<svg style={{ width: '16px', height: '16px', marginRight: '4px' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M12 6.253v13m0-13C10.832 5.477 9.246 5 7.5 5S4.168 5.477 3 6.253v13C4.168 18.477 5.754 18 7.5 18s3.332.477 4.5 1.253m0-13C13.168 5.477 14.754 5 16.5 5c1.746 0 3.332.477 4.5 1.253v13C19.832 18.477 18.246 18 16.5 18c-1.746 0-3.332.477-4.5 1.253" />
</svg>
.pdf
</span>
<span className="kb-format-tag docx">
<svg style={{ width: '16px', height: '16px', marginRight: '4px' }} fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M9 12h6m-6 4h6m2 5H7a2 2 0 01-2-2V5a2 2 0 012-2h5.586a1 1 0 01.707.293l5.414 5.414a1 1 0 01.293.707V19a2 2 0 01-2 2z" />
</svg>
.docx
</span>
</div>
</div>
<div style={{position: 'relative'}}>
<input
id="file-upload"
type="file"
multiple
accept=".txt,.md,.markdown,.pdf,.docx"
onChange={handleFileSelect}
style={{position: 'absolute', inset: '0', width: '100%', height: '100%', opacity: 0, cursor: 'pointer', zIndex: 10}}
/>
<div className="kb-upload-zone">
<div className="kb-upload-zone-icon" style={{ display: 'flex', justifyContent: 'center', marginBottom: '16px' }}>
<FolderOpen size={32} color="#667eea" />
</div>
<h3 className="kb-upload-zone-title">拖拽文件到窗口任意位置</h3>
<p className="kb-upload-zone-subtitle">支持 .txt、.md、.pdf、.docx 格式文档</p>
<div className="kb-upload-zone-button" style={{ display: 'flex', alignItems: 'center', gap: '8px', justifyContent: 'center' }}>
<Target size={16} />
推荐使用拖拽上传
</div>
</div>
</div>
</div>
{selectedFiles.length > 0 && (
<div className="kb-selected-files">
<div className="kb-selected-header">
<div className="kb-selected-icon" style={{ display: 'flex', alignItems: 'center' }}>
<CheckCircle size={20} color="green" />
</div>
<h3 className="kb-selected-title">
已选择 {selectedFiles.length} 个文件
</h3>
<div className="kb-selected-badge">
准备就绪
</div>
</div>
<div className="kb-file-list">
{selectedFiles.map((file, index) => (
<div key={index} className="kb-file-item">
<div className="kb-file-icon" style={{ display: 'flex', alignItems: 'center' }}>
<FileText size={20} color="#667eea" />
</div>
<div className="kb-file-info">
<div className="kb-file-name">{file.name}</div>
<div className="kb-file-meta">
<span className="kb-file-size">{formatFileSize(file.size)}</span>
<span className="kb-file-status">等待上传</span>
</div>
</div>
<div className="kb-file-check" style={{ display: 'flex', alignItems: 'center' }}>
<CheckCircle size={16} color="green" />
</div>
</div>
))}
</div>
</div>
)}
<div className="kb-action-buttons">
<button
onClick={handleUploadDocuments}
disabled={uploading || selectedFiles.length === 0}
className="kb-button primary"
>
{uploading ? (
<>
<div style={{
width: '20px',
height: '20px',
border: '2px solid transparent',
borderTop: '2px solid white',
borderRadius: '50%',
animation: 'spin 1s linear infinite'
}} />
<span>处理中...</span>
</>
) : (
<>
<Upload size={16} />
<span>处理文件 ({selectedFiles.length})</span>
</>
)}
</button>
<button
onClick={loadKnowledgeBaseStatus}
disabled={loading}
className="kb-button secondary"
>
<RefreshCcw size={16} />
<span>刷新状态</span>
</button>
</div>
</div>
</div>
{/* 文档列表 */}
<div className="kb-documents-section">
<div className="kb-documents-header">
<div className="kb-documents-title-group">
<div className="kb-documents-icon" style={{ display: 'flex', alignItems: 'center' }}>
<BookOpen size={24} color="#667eea" />
</div>
<div>
<div className="kb-documents-title">文档库</div>
<div className="kb-documents-subtitle">管理您的知识库文档</div>
</div>
</div>
<button
onClick={handleClearKnowledgeBase}
disabled={!documents.length || loading}
className="kb-button danger"
style={{ display: 'flex', alignItems: 'center', gap: '8px' }}
>
<Trash2 size={16} />
<span>清空知识库</span>
</button>
</div>
<div style={{
overflowX: 'auto',
overflowY: 'visible',
maxHeight: '70vh',
position: 'relative'
}}>
{loading ? (
<div className="kb-loading">
<div className="kb-loading-icon">
<div className="kb-loading-spinner"></div>
<div className="kb-loading-inner" style={{ display: 'flex', alignItems: 'center', justifyContent: 'center' }}>
<BookOpen size={24} color="#667eea" />
</div>
</div>
<h3 className="kb-loading-title">正在加载文档...</h3>
<p className="kb-loading-subtitle">请稍候，正在获取您的知识库内容</p>
<div className="kb-loading-dots">
<div className="kb-loading-dot"></div>
<div className="kb-loading-dot"></div>
<div className="kb-loading-dot"></div>
</div>
</div>
) : documents.length === 0 ? (
<div className="kb-empty">
<div className="kb-empty-icon">
<div className="kb-empty-circle" style={{ display: 'flex', alignItems: 'center', justifyContent: 'center' }}>
<BookOpen size={48} color="#667eea" />
</div>
</div>
<h3 className="kb-empty-title">
知识库等待您的第一份文档
</h3>
<p className="kb-empty-subtitle" style={{ display: 'flex', alignItems: 'center', gap: '8px', justifyContent: 'center' }}>
<Rocket size={16} />
上传一些文档开始使用RAG功能，让AI拥有丰富的知识背景，为您提供更加精准的分析结果
</p>
<div className="kb-empty-formats">
<div className="kb-format-tag pdf" style={{ display: 'flex', alignItems: 'center', gap: '4px' }}>
<File size={16} />
支持 PDF
</div>
<div className="kb-format-tag docx" style={{ display: 'flex', alignItems: 'center', gap: '4px' }}>
<File size={16} />
支持 Word
</div>
<div className="kb-format-tag md" style={{ display: 'flex', alignItems: 'center', gap: '4px' }}>
<File size={16} />
支持 Markdown
</div>
<div className="kb-format-tag txt" style={{ display: 'flex', alignItems: 'center', gap: '4px' }}>
<File size={16} />
支持 TXT
</div>
</div>
<div className="kb-empty-cta" style={{ display: 'flex', alignItems: 'center', gap: '8px', justifyContent: 'center' }}>
<Upload size={16} />
立即上传文档
</div>
</div>
) : (
<div className="kb-table-container">
<table className="kb-table">
<thead>
<tr>
<th>
<div style={{display: 'flex', alignItems: 'center', gap: '0.5rem'}}>
<FileText size={18} />
文档信息
</div>
</th>
<th>
<div style={{display: 'flex', alignItems: 'center', justifyContent: 'center', gap: '0.5rem'}}>
<Scale size={18} />
大小
</div>
</th>
<th>
<div style={{display: 'flex', alignItems: 'center', justifyContent: 'center', gap: '0.5rem'}}>
<Puzzle size={18} />
文本块
</div>
</th>
<th>
<div style={{display: 'flex', alignItems: 'center', justifyContent: 'center', gap: '0.5rem'}}>
<Clock size={18} />
上传时间
</div>
</th>
<th>
<div style={{display: 'flex', alignItems: 'center', justifyContent: 'center', gap: '0.5rem'}}>
<Settings size={18} />
操作
</div>
</th>
</tr>
</thead>
<tbody>
{documents.map((doc, index) => (
<tr key={doc.id}>
<td>
<div className="kb-doc-cell">
<div className="kb-doc-icon-wrapper">
<div className="kb-doc-icon" style={{ display: 'flex', alignItems: 'center', justifyContent: 'center' }}>
<FileText size={20} color="#667eea" />
</div>
<div className="kb-doc-number">{index + 1}</div>
</div>
<div className="kb-doc-info">
<div className="kb-doc-name">
{doc.file_name}
</div>
<div className="kb-doc-meta">
<span className="kb-doc-id">
ID: {doc.id.substring(0, 8)}...
</span>
<span className="kb-doc-status">
已处理
</span>
</div>
{processingDocuments.has(doc.id) && (
<div>
{getProcessingStatusDisplay(doc.id)}
</div>
)}
</div>
</div>
</td>
<td className="kb-cell-center">
<div className="kb-file-size-display">
{formatFileSize(doc.file_size)}
</div>
<div className="kb-file-size-label">
文件大小
</div>
</td>
<td className="kb-cell-center">
<div className="kb-chunks-badge">
<div className="kb-chunks-dot"></div>
{doc.total_chunks} 块
</div>
</td>
<td className="kb-cell-center">
<div className="kb-date-display">
{formatDate(doc.created_at)}
</div>
<div className="kb-date-label">
上传时间
</div>
</td>
<td className="kb-cell-center">
<button
onClick={() => handleDeleteDocument(doc.id, doc.file_name)}
className="kb-delete-button"
style={{ display: 'flex', alignItems: 'center', gap: '8px' }}
>
<div className="kb-delete-content">
<Trash2 size={16} />
<span>删除</span>
</div>
</button>
</td>
</tr>
))}
</tbody>
</table>
</div>
)}
</div>
</div>
</div>
</div>
);
};
export default KnowledgeBaseManagement; | 37,889 | KnowledgeBaseManagement | tsx | en | tsx | code | {"qsc_code_num_words": 3496, "qsc_code_num_chars": 37889.0, "qsc_code_mean_word_length": 5.12156751, "qsc_code_frac_words_unique": 0.2076659, "qsc_code_frac_chars_top_2grams": 0.08048031, "qsc_code_frac_chars_top_3grams": 0.07975426, "qsc_code_frac_chars_top_4grams": 0.03987713, "qsc_code_frac_chars_dupe_5grams": 0.39346551, "qsc_code_frac_chars_dupe_6grams": 0.32929349, "qsc_code_frac_chars_dupe_7grams": 0.28483664, "qsc_code_frac_chars_dupe_8grams": 0.24864563, "qsc_code_frac_chars_dupe_9grams": 0.22105557, "qsc_code_frac_chars_dupe_10grams": 0.19558782, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.06608548, "qsc_code_frac_chars_whitespace": 0.37937132, "qsc_code_size_file_byte": 37889.0, "qsc_code_num_lines": 932.0, "qsc_code_num_chars_line_max": 339.0, "qsc_code_num_chars_line_mean": 40.65343348, "qsc_code_frac_chars_alphabet": 0.69521582, "qsc_code_frac_chars_comments": 0.01264219, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.4223301, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0157767, "qsc_code_frac_chars_string_length": 0.17150036, "qsc_code_frac_chars_long_word_length": 0.01662613, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0} |
000haoji/deep-student | src/components/TagManagement.tsx | import React, { useState, useEffect } from 'react';
import { invoke } from '@tauri-apps/api/core';
import {
Tag,
TagType,
CreateTagRequest,
TagHierarchy
} from '../types/cogni-graph';
import './TagManagement.css';
interface TagManagementProps {
isInitialized: boolean;
}
const TagManagement: React.FC<TagManagementProps> = ({ isInitialized }) => {
const [tags, setTags] = useState<Tag[]>([]);
const [tagHierarchy, setTagHierarchy] = useState<TagHierarchy[]>([]);
const [loading, setLoading] = useState(false);
const [error, setError] = useState<string | null>(null);
const [showCreateForm, setShowCreateForm] = useState(false);
const [selectedTagType, setSelectedTagType] = useState<TagType>('KnowledgeArea');
const [newTag, setNewTag] = useState<CreateTagRequest>({
name: '',
tag_type: 'Concept',
parent_id: undefined,
description: ''
});
useEffect(() => {
if (isInitialized) {
loadTags();
loadTagHierarchy();
}
}, [isInitialized]);
const loadTags = async () => {
try {
setLoading(true);
const allTags = await invoke<Tag[]>('get_tags_by_type', {
tagType: selectedTagType
});
setTags(allTags);
} catch (err) {
setError(`加载标签失败: ${err}`);
} finally {
setLoading(false);
}
};
const loadTagHierarchy = async () => {
try {
const hierarchy = await invoke<TagHierarchy[]>('get_tag_hierarchy', {
rootTagId: null
});
setTagHierarchy(hierarchy);
} catch (err) {
console.error('加载标签层次失败:', err);
}
};
const createTag = async () => {
if (!newTag.name.trim()) {
setError('标签名称不能为空');
return;
}
try {
setLoading(true);
setError(null);
const tagId = await invoke<string>('create_tag', {
request: {
...newTag,
description: newTag.description || undefined
}
});
// Reset form
setNewTag({
name: '',
tag_type: 'Concept',
parent_id: undefined,
description: ''
});
setShowCreateForm(false);
// Reload tags
await loadTags();
await loadTagHierarchy();
console.log('标签创建成功:', tagId);
} catch (err) {
setError(`创建标签失败: ${err}`);
} finally {
setLoading(false);
}
};
const initializeDefaultHierarchy = async () => {
try {
setLoading(true);
setError(null);
const result = await invoke<string>('initialize_default_tag_hierarchy');
// Reload data
await loadTags();
await loadTagHierarchy();
alert(`默认标签层次初始化成功: ${result}`);
} catch (err) {
setError(`初始化默认层次失败: ${err}`);
} finally {
setLoading(false);
}
};
const renderTagHierarchy = (hierarchies: TagHierarchy[], level: number = 0): JSX.Element[] => {
return hierarchies.map((hierarchy) => (
<div key={hierarchy.tag.id} className={`tag-node level-${level}`}>
<div className="tag-info">
<span className={`tag-type ${hierarchy.tag.tag_type.toLowerCase()}`}>
{hierarchy.tag.tag_type}
</span>
<span className="tag-name">{hierarchy.tag.name}</span>
<span className="tag-level">Level {hierarchy.tag.level}</span>
</div>
{hierarchy.tag.description && (
<div className="tag-description">{hierarchy.tag.description}</div>
)}
{hierarchy.children.length > 0 && (
<div className="tag-children">
{renderTagHierarchy(hierarchy.children, level + 1)}
</div>
)}
</div>
));
};
const getAvailableParents = (): Tag[] => {
return tags.filter(tag => {
// Can only be parent if it's a higher level type
const parentTypes: TagType[] = [];
switch (newTag.tag_type) {
case 'Topic':
parentTypes.push('KnowledgeArea');
break;
case 'Concept':
parentTypes.push('KnowledgeArea', 'Topic');
break;
case 'Method':
parentTypes.push('Topic', 'Concept');
break;
case 'Difficulty':
return []; // Difficulty tags usually standalone
default:
return [];
}
return parentTypes.includes(tag.tag_type);
});
};
if (!isInitialized) {
return (
<div className="tag-management-container">
<div className="not-initialized">
<p>图谱未初始化，请先完成Neo4j连接配置</p>
</div>
</div>
);
}
return (
<div className="tag-management-container">
<div className="tag-management-header">
<h3>标签管理</h3>
<div className="header-actions">
<button
onClick={() => setShowCreateForm(!showCreateForm)}
className="create-tag-btn"
disabled={loading}
>
➕ 创建标签
</button>
<button
onClick={initializeDefaultHierarchy}
className="init-hierarchy-btn"
disabled={loading}
>
🏗️ 初始化默认层次
</button>
</div>
</div>
{error && (
<div className="error-message">
{error}
<button onClick={() => setError(null)}>✕</button>
</div>
)}
{showCreateForm && (
<div className="create-tag-form">
<h4>创建新标签</h4>
<div className="form-group">
<label>标签名称:</label>
<input
type="text"
value={newTag.name}
onChange={(e) => setNewTag({ ...newTag, name: e.target.value })}
placeholder="输入标签名称"
/>
</div>
<div className="form-group">
<label>标签类型:</label>
<select
value={newTag.tag_type}
onChange={(e) => setNewTag({ ...newTag, tag_type: e.target.value as TagType })}
>
<option value="KnowledgeArea">知识领域</option>
<option value="Topic">主题</option>
<option value="Concept">概念</option>
<option value="Method">方法</option>
<option value="Difficulty">难度</option>
</select>
</div>
<div className="form-group">
<label>父标签 (可选):</label>
<select
value={newTag.parent_id || ''}
onChange={(e) => setNewTag({
...newTag,
parent_id: e.target.value || undefined
})}
>
<option value="">无父标签</option>
{getAvailableParents().map(tag => (
<option key={tag.id} value={tag.id}>
{tag.name} ({tag.tag_type})
</option>
))}
</select>
</div>
<div className="form-group">
<label>描述 (可选):</label>
<textarea
value={newTag.description}
onChange={(e) => setNewTag({ ...newTag, description: e.target.value })}
placeholder="输入标签描述"
rows={3}
/>
</div>
<div className="form-actions">
<button onClick={createTag} disabled={loading}>
✅ 创建
</button>
<button onClick={() => setShowCreateForm(false)} disabled={loading}>
❌ 取消
</button>
</div>
</div>
)}
<div className="tag-content">
<div className="tag-list-section">
<div className="section-header">
<h4>标签列表</h4>
<div className="filter-controls">
<label>筛选类型:</label>
<select
value={selectedTagType}
onChange={(e) => {
setSelectedTagType(e.target.value as TagType);
loadTags();
}}
>
<option value="KnowledgeArea">知识领域</option>
<option value="Topic">主题</option>
<option value="Concept">概念</option>
<option value="Method">方法</option>
<option value="Difficulty">难度</option>
</select>
</div>
</div>
{loading ? (
<div className="loading">加载中...</div>
) : (
<div className="tag-list">
{tags.map(tag => (
<div key={tag.id} className="tag-item">
<div className="tag-header">
<span className={`tag-type ${tag.tag_type.toLowerCase()}`}>
{tag.tag_type}
</span>
<span className="tag-name">{tag.name}</span>
<span className="tag-level">L{tag.level}</span>
</div>
{tag.description && (
<div className="tag-description">{tag.description}</div>
)}
<div className="tag-meta">
<span>创建时间: {new Date(tag.created_at).toLocaleDateString()}</span>
</div>
</div>
))}
{tags.length === 0 && (
<div className="no-tags">
暂无 {selectedTagType} 类型的标签
</div>
)}
</div>
)}
</div>
<div className="tag-hierarchy-section">
<h4>标签层次结构</h4>
{tagHierarchy.length > 0 ? (
<div className="hierarchy-tree">
{renderTagHierarchy(tagHierarchy)}
</div>
) : (
<div className="no-hierarchy">
暂无标签层次结构，请先创建标签或初始化默认层次
</div>
)}
</div>
</div>
</div>
);
};
export default TagManagement; | 9,811 | TagManagement | tsx | en | tsx | code | {"qsc_code_num_words": 809, "qsc_code_num_chars": 9811.0, "qsc_code_mean_word_length": 5.94066749, "qsc_code_frac_words_unique": 0.25463535, "qsc_code_frac_chars_top_2grams": 0.06991261, "qsc_code_frac_chars_top_3grams": 0.04057428, "qsc_code_frac_chars_top_4grams": 0.01664586, "qsc_code_frac_chars_dupe_5grams": 0.2224303, "qsc_code_frac_chars_dupe_6grams": 0.18081565, "qsc_code_frac_chars_dupe_7grams": 0.14398668, "qsc_code_frac_chars_dupe_8grams": 0.13067, "qsc_code_frac_chars_dupe_9grams": 0.06242197, "qsc_code_frac_chars_dupe_10grams": 0.06242197, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.00238892, "qsc_code_frac_chars_whitespace": 0.36000408, "qsc_code_size_file_byte": 9811.0, "qsc_code_num_lines": 343.0, "qsc_code_num_chars_line_max": 98.0, "qsc_code_num_chars_line_mean": 28.60349854, "qsc_code_frac_chars_alphabet": 0.76206402, "qsc_code_frac_chars_comments": 0.01294465, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.42763158, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.08301497, "qsc_code_frac_chars_long_word_length": 0.0125968, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0} |
0000cd/wolf-set | themes/bluf/layouts/partials/head.html | <meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<meta name="author" content="{{ .Site.Params.author }}">
<meta name="template" content="bluf">
<meta name="theme-color" content="#0000cd">
<meta name="license" content="{{ .Site.Params.license }}">
<link rel="apple-touch-icon" sizes="180x180" href="/apple-touch-icon.png">
<link rel="icon" type="image/png" sizes="32x32" href="/favicon-32x32.png">
<link rel="icon" type="image/png" sizes="16x16" href="/favicon-16x16.png">
<link rel="manifest" href="/site.webmanifest">
{{/* {{ $style := resources.Get "css/style.css" }}
{{ $secureCSS := $style | resources.Minify | resources.Fingerprint }}
<link rel="stylesheet" href="{{ $secureCSS.RelPermalink }}" integrity="{{ $secureCSS.Data.Integrity }}"> */}}
{{ $style := resources.Get "css/style.css" | resources.ExecuteAsTemplate "css/style.css" . }}
{{ $secureCSS := $style | resources.Minify | resources.Fingerprint }}
<link rel="stylesheet" href="{{ $secureCSS.RelPermalink }}" integrity="{{ $secureCSS.Data.Integrity }}">
{{ if .Site.Params.enableUmami }}
<script defer src="{{ .Site.Params.UmamiLink }}" data-website-id="{{ .Site.Params.UmamiID }}"></script>
{{ end }}
<script>
(function() {
const savedTheme = localStorage.getItem('theme');
if (savedTheme) {
document.documentElement.setAttribute('data-theme', savedTheme);
} else {
const prefersDark = window.matchMedia('(prefers-color-scheme: dark)').matches;
if (prefersDark) {
document.documentElement.setAttribute('data-theme', 'dark');
}
}
})();
</script> | 1,667 | head | html | en | html | code | {"qsc_code_num_words": 183, "qsc_code_num_chars": 1667.0, "qsc_code_mean_word_length": 5.8852459, "qsc_code_frac_words_unique": 0.41530055, "qsc_code_frac_chars_top_2grams": 0.03899721, "qsc_code_frac_chars_top_3grams": 0.02785515, "qsc_code_frac_chars_top_4grams": 0.02599814, "qsc_code_frac_chars_dupe_5grams": 0.42804085, "qsc_code_frac_chars_dupe_6grams": 0.3463324, "qsc_code_frac_chars_dupe_7grams": 0.30454968, "qsc_code_frac_chars_dupe_8grams": 0.30454968, "qsc_code_frac_chars_dupe_9grams": 0.24698236, "qsc_code_frac_chars_dupe_10grams": 0.24698236, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.02040816, "qsc_code_frac_chars_whitespace": 0.14757049, "qsc_code_size_file_byte": 1667.0, "qsc_code_num_lines": 37.0, "qsc_code_num_chars_line_max": 111.0, "qsc_code_num_chars_line_mean": 45.05405405, "qsc_code_frac_chars_alphabet": 0.7375088, "qsc_code_frac_chars_comments": 0.0, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.0625, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.34472422, "qsc_code_frac_chars_long_word_length": 0.09652278, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codehtml_cate_ast": 1.0, "qsc_codehtml_frac_words_text": 0.21175765, "qsc_codehtml_num_chars_text": 353.0} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_cate_xml_start": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_cate_autogen": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_codehtml_cate_ast": 0, "qsc_codehtml_frac_words_text": 0, "qsc_codehtml_num_chars_text": 0} |
000haoji/deep-student | src/components/AnkiCardGeneration.css | .anki-card-generation {
padding: 20px;
max-width: 1400px;
margin: 0 auto;
background: #f8fafc;
min-height: 100vh;
}
/* 文档处理状态样式 */
.document-processing-status {
background: white;
padding: 20px;
border-radius: 12px;
margin-bottom: 20px;
box-shadow: 0 2px 8px rgba(0, 0, 0, 0.1);
border-left: 4px solid #3b82f6;
}
.document-info {
display: flex;
gap: 20px;
margin-bottom: 15px;
font-size: 0.875rem;
font-weight: 500;
color: #64748b;
}
.tasks-list {
margin-top: 15px;
}
.task-item {
background: white;
border: 1px solid #ddd;
border-radius: 6px;
padding: 12px;
margin-bottom: 8px;
cursor: pointer;
transition: all 0.2s ease;
}
.task-item:hover {
border-color: #2196f3;
box-shadow: 0 2px 4px rgba(0,0,0,0.1);
}
.task-item.selected {
border-color: #2196f3;
background: #f3f8ff;
}
.task-header {
display: flex;
justify-content: space-between;
align-items: center;
margin-bottom: 8px;
}
.task-id {
font-weight: 600;
color: #333;
}
.task-status {
font-size: 0.75rem;
padding: 2px 6px;
border-radius: 3px;
font-weight: 500;
}
.status-pending { background: #fff3cd; color: #856404; }
.status-processing { background: #d1ecf1; color: #0c5460; }
.status-completed { background: #d4edda; color: #155724; }
.status-failed { background: #f8d7da; color: #721c24; }
.status-truncated { background: #ffeaa7; color: #8b6914; }
.task-status-info {
display: flex;
gap: 8px;
align-items: center;
}
.error-indicator {
background: #f8d7da;
color: #721c24;
font-size: 0.75rem;
padding: 2px 6px;
border-radius: 3px;
font-weight: 500;
}
.error-count {
color: #dc3545;
font-size: 0.75rem;
margin-left: 4px;
}
.error-summary {
background: #f8d7da;
color: #721c24;
padding: 2px 6px;
border-radius: 3px;
font-size: 0.75rem;
font-weight: 500;
}
.completion-indicator {
background: #d4edda;
color: #155724;
padding: 2px 6px;
border-radius: 3px;
font-size: 0.75rem;
font-weight: 500;
}
.generation-status {
text-align: left;
}
.status-main {
font-weight: 500;
margin-bottom: 4px;
}
.status-detail {
font-size: 0.75rem;
color: #64748b;
font-weight: 500;
}
.task-preview {
font-size: 0.875rem;
color: #64748b;
margin-bottom: 8px;
overflow: hidden;
text-overflow: ellipsis;
white-space: nowrap;
}
.task-progress {
display: flex;
align-items: center;
gap: 10px;
}
.progress-bar {
flex: 1;
height: 6px;
background: #e9ecef;
border-radius: 3px;
overflow: hidden;
}
.progress-fill {
height: 100%;
background: linear-gradient(90deg, #28a745, #20c997);
transition: width 0.3s ease;
}
.progress-text {
font-size: 0.75rem;
color: #64748b;
white-space: nowrap;
}
.anki-card-generation h2 {
color: #1e293b;
margin-bottom: 20px;
text-align: center;
font-size: 1.5rem;
font-weight: 600;
padding: 20px;
background: white;
border-radius: 12px;
box-shadow: 0 2px 8px rgba(0, 0, 0, 0.1);
}
/* 输入区域样式 */
.input-section {
background: white;
padding: 20px;
border-radius: 12px;
margin-bottom: 20px;
box-shadow: 0 2px 8px rgba(0, 0, 0, 0.1);
}
.form-group {
margin-bottom: 15px;
}
.form-group label {
display: block;
margin-bottom: 8px;
font-weight: 500;
color: #374151;
}
.form-control {
width: 100%;
padding: 10px 12px;
border: 1px solid #d1d5db;
border-radius: 6px;
font-size: 0.875rem;
transition: border-color 0.2s ease;
}
.form-control:focus {
outline: none;
border-color: #3b82f6;
box-shadow: 0 0 0 3px rgba(59, 130, 246, 0.1);
}
.form-row {
display: flex;
gap: 20px;
}
.form-row .form-group {
flex: 1;
}
/* 选项区域 */
.options-section {
border-top: 1px solid #e2e8f0;
padding-top: 20px;
margin-top: 20px;
}
.options-section h4 {
margin-bottom: 15px;
color: #1e293b;
font-size: 1.125rem;
font-weight: 600;
}
/* 按钮样式 */
.btn {
padding: 8px 16px;
border: none;
border-radius: 6px;
cursor: pointer;
font-size: 0.875rem;
font-weight: 500;
text-decoration: none;
display: inline-flex;
align-items: center;
gap: 6px;
transition: all 0.2s ease;
}
.btn:disabled {
opacity: 0.5;
cursor: not-allowed;
}
.btn-primary {
background: #3b82f6;
color: white;
}
.btn-primary:hover:not(:disabled) {
background: #2563eb;
}
.btn-secondary {
background: #64748b;
color: white;
}
.btn-secondary:hover:not(:disabled) {
background: #475569;
}
.btn-outline {
background-color: transparent;
border: 1px solid #6c757d;
color: #6c757d;
}
.btn-outline:hover:not(:disabled) {
background-color: #6c757d;
color: white;
}
.btn-success {
background: #10b981;
color: white;
margin-right: 10px;
}
.btn-success:hover:not(:disabled) {
background: #059669;
}
.btn-info {
background-color: #17a2b8;
color: white;
}
.btn-info:hover:not(:disabled) {
background-color: #117a8b;
}
.btn-danger {
background-color: #dc3545;
color: white;
}
.btn-danger:hover:not(:disabled) {
background-color: #c82333;
}
.btn-sm {
padding: 4px 8px;
font-size: 0.75rem;
}
/* 错误信息 */
.error-message {
background-color: #f8d7da;
color: #721c24;
padding: 12px;
border-radius: 4px;
border: 1px solid #f5c6cb;
margin-bottom: 20px;
}
/* 卡片预览区域 */
.cards-preview {
background: white;
border-radius: 12px;
box-shadow: 0 2px 8px rgba(0, 0, 0, 0.1);
padding: 20px;
}
.cards-header {
display: flex;
justify-content: space-between;
align-items: center;
margin-bottom: 20px;
padding-bottom: 15px;
border-bottom: 1px solid #e2e8f0;
}
.cards-header h3 {
margin: 0;
color: #1e293b;
font-size: 1.25rem;
font-weight: 600;
}
.card-controls {
display: flex;
align-items: center;
gap: 15px;
}
.selected-count {
color: #64748b;
font-size: 0.875rem;
}
/* 卡片列表 */
.cards-list {
max-height: 600px;
overflow-y: auto;
margin-bottom: 20px;
}
.card-item {
border: 1px solid #e2e8f0;
border-radius: 8px;
margin-bottom: 15px;
transition: all 0.2s ease;
background: #f8fafc;
}
.card-item.selected {
border-color: #3b82f6;
box-shadow: 0 4px 12px rgba(0, 0, 0, 0.1);
}
.card-item.error-card {
border-color: #dc3545;
background: #fff5f5;
}
.card-item.error-card .card-number {
color: #dc3545;
font-weight: 600;
}
.error-content {
background: #f8d7da;
border: 1px solid #f5c6cb;
border-radius: 4px;
padding: 10px;
margin: 10px 15px;
}
.error-content label {
color: #721c24;
font-weight: 600;
margin-bottom: 5px;
display: block;
}
.error-text {
color: #721c24;
font-size: 0.875rem;
}
.card-header {
display: flex;
align-items: center;
gap: 10px;
padding: 12px 15px;
background-color: #f1f5f9;
border-bottom: 1px solid #e2e8f0;
}
.card-number {
font-weight: 600;
color: #1e293b;
flex-grow: 1;
}
.card-content {
padding: 15px;
}
.card-field {
margin-bottom: 15px;
}
.card-field:last-child {
margin-bottom: 0;
}
.card-field label {
display: block;
margin-bottom: 8px;
font-weight: 500;
color: #374151;
font-size: 0.875rem;
}
/* 标签样式 */
.tags {
display: flex;
flex-wrap: wrap;
gap: 8px;
}
.tag {
background-color: #e2e8f0;
color: #1e293b;
padding: 4px 8px;
border-radius: 12px;
font-size: 0.75rem;
font-weight: 500;
}
/* 输出操作区域 - 增强版 */
.output-actions {
border-top: 1px solid #e2e8f0;
padding-top: 20px;
}
.export-options, .anki-connect-actions {
background: #f8fafc;
border: 1px solid #e2e8f0;
border-radius: 8px;
padding: 15px;
margin-bottom: 15px;
}
.export-options h5, .anki-connect-actions h5 {
margin: 0 0 10px 0;
color: #1e293b;
font-size: 1.125rem;
font-weight: 600;
}
.export-buttons {
display: flex;
gap: 8px;
flex-wrap: wrap;
}
.export-buttons .btn {
flex: 0 0 auto;
}
/* 响应式设计 */
@media (max-width: 1200px) {
.advanced-options .form-row {
flex-wrap: wrap;
}
.advanced-options .form-group {
min-width: 250px;
flex-basis: calc(50% - 10px);
}
}
@media (max-width: 768px) {
.anki-card-generation {
padding: 15px;
}
.form-row {
flex-direction: column;
}
.cards-header {
flex-direction: column;
align-items: flex-start;
gap: 10px;
}
.card-controls {
width: 100%;
justify-content: space-between;
}
.output-actions {
display: flex;
flex-direction: column;
gap: 10px;
}
.btn {
width: 100%;
}
}
/* 滚动条样式 */
.cards-list::-webkit-scrollbar {
width: 8px;
}
.cards-list::-webkit-scrollbar-track {
background: #f1f1f1;
border-radius: 4px;
}
.cards-list::-webkit-scrollbar-thumb {
background: #c1c1c1;
border-radius: 4px;
}
.cards-list::-webkit-scrollbar-thumb:hover {
background: #a8a8a8;
}
/* AnkiConnect状态样式 */
.anki-status {
margin-bottom: 15px;
padding: 15px;
background-color: #f8fafc;
border: 1px solid #e2e8f0;
border-radius: 8px;
}
.status-indicator {
display: flex;
align-items: center;
margin-bottom: 5px;
}
.status-label {
font-weight: 500;
color: #374151;
margin-right: 8px;
}
.status-checking {
color: #64748b;
font-style: italic;
}
.status-available {
color: #10b981;
font-weight: 600;
}
.status-unavailable {
color: #dc3545;
font-weight: 600;
}
.connection-error {
margin-top: 8px;
padding: 8px 12px;
background-color: #f8d7da;
color: #721c24;
border-radius: 4px;
font-size: 0.875rem;
border: 1px solid #f5c6cb;
}
/* 按钮增强样式 */
.btn:disabled {
opacity: 0.65;
cursor: not-allowed;
}
.btn-info:disabled {
background-color: #6c757d;
border-color: #6c757d;
}
.btn-info:disabled:hover {
background-color: #6c757d;
border-color: #6c757d;
}
/* 高级选项样式 */
.advanced-options {
margin-top: 20px;
padding: 15px;
background-color: #f8fafc;
border: 1px solid #e2e8f0;
border-radius: 8px;
}
.advanced-options h5 {
margin: 0 0 15px 0;
color: #1e293b;
font-size: 1.125rem;
font-weight: 600;
border-bottom: 1px solid #e2e8f0;
padding-bottom: 8px;
}
.form-help {
display: block;
color: #64748b;
font-size: 0.75rem;
margin-top: 4px;
line-height: 1.3;
word-wrap: break-word;
overflow-wrap: break-word;
max-width: 100%;
white-space: normal;
}
/* 增强form-row在高级选项中的显示 */
.advanced-options .form-row {
gap: 20px;
}
.advanced-options .form-group {
min-width: 200px;
flex: 1;
overflow: hidden; /* 防止内容溢出 */
}
.advanced-options .form-group .form-help {
word-break: break-word; /* 强制长词换行 */
hyphens: auto; /* 自动断字 */
}
/* 添加全局字体样式 */
.anki-card-generation {
font-family: inherit;
}
.anki-card-generation * {
font-family: inherit;
}
/* 数字输入框样式增强 */
.form-control[type="number"] {
text-align: right;
}
/* 文件上传区域样式 */
.upload-zone {
border: 2px dashed #cbd5e1;
border-radius: 12px;
padding: 20px;
margin-top: 10px;
text-align: center;
transition: all 0.3s ease;
background: #f8fafc;
}
.upload-zone.drag-over {
border-color: #3b82f6;
background: #eff6ff;
}
.upload-zone.uploading {
opacity: 0.7;
pointer-events: none;
}
.upload-content {
display: flex;
flex-direction: column;
align-items: center;
gap: 12px;
}
.upload-icon {
font-size: 2.5rem;
color: #64748b;
}
.upload-text {
font-size: 1rem;
font-weight: 500;
color: #334155;
}
.upload-hint {
font-size: 0.875rem;
color: #64748b;
}
/* 选中文件列表 */
.selected-files {
margin-top: 15px;
padding: 15px;
background: #f1f5f9;
border-radius: 8px;
}
.selected-files h4 {
margin: 0 0 12px 0;
color: #1e293b;
font-size: 1rem;
font-weight: 600;
}
.file-list {
display: flex;
flex-direction: column;
gap: 8px;
margin-bottom: 12px;
}
.file-item {
display: flex;
justify-content: space-between;
align-items: center;
padding: 8px 12px;
background: white;
border-radius: 6px;
border: 1px solid #e2e8f0;
}
.file-name {
flex: 1;
font-weight: 500;
color: #1e293b;
font-size: 0.875rem;
}
.file-size {
font-size: 0.75rem;
color: #64748b;
margin-right: 10px;
}
.btn-remove {
background: #fee2e2;
color: #dc2626;
border: none;
border-radius: 4px;
width: 20px;
height: 20px;
cursor: pointer;
display: flex;
align-items: center;
justify-content: center;
font-size: 0.75rem;
}
.btn-remove:hover {
background: #fecaca;
}
.upload-actions {
display: flex;
gap: 10px;
}
/* 增强的错误提示样式 */
.error-message {
display: flex;
align-items: center;
gap: 8px;
margin: 15px 0;
padding: 12px 16px;
background-color: #f8d7da;
color: #721c24;
border: 1px solid #f5c6cb;
border-radius: 6px;
font-size: 0.875rem;
line-height: 1.4;
}
.error-icon {
font-size: 1rem;
flex-shrink: 0;
}
.error-text {
flex: 1;
}
/* 加载状态指示器样式 */
.loading-indicator {
display: flex;
align-items: center;
gap: 12px;
margin: 15px 0;
padding: 12px 16px;
background-color: #e7f3ff;
color: #0066cc;
border: 1px solid #b3d9ff;
border-radius: 6px;
font-size: 0.875rem;
}
.loading-spinner {
width: 1rem;
height: 1rem;
border: 2px solid #b3d9ff;
border-top: 2px solid #0066cc;
border-radius: 50%;
animation: spin 1s linear infinite;
flex-shrink: 0;
}
.loading-text {
font-weight: 500;
}
/* 旋转动画 */
@keyframes spin {
0% { transform: rotate(0deg); }
100% { transform: rotate(360deg); }
}
/* 改进现有错误消息样式以保持一致性 */
.connection-error {
margin-top: 8px;
padding: 8px 12px;
background-color: #fff3cd;
color: #856404;
border-radius: 4px;
font-size: 0.875rem;
border: 1px solid #ffeaa7;
}
/* 成功状态样式 */
.success-message {
display: flex;
align-items: center;
gap: 8px;
margin: 15px 0;
padding: 12px 16px;
background-color: #d4edda;
color: #155724;
border: 1px solid #c3e6cb;
border-radius: 6px;
font-size: 0.875rem;
line-height: 1.4;
}
.success-message .success-icon {
font-size: 1rem;
flex-shrink: 0;
}/* Template Selector Styles */
.template-section {
margin: 20px 0;
padding: 20px;
background: #f8fafc;
border: 1px solid #e2e8f0;
border-radius: 12px;
}
.template-section h5 {
margin: 0 0 16px 0;
color: #1e293b;
font-size: 1.125rem;
font-weight: 600;
display: flex;
align-items: center;
gap: 8px;
}
.template-selector {
display: flex;
flex-direction: column;
gap: 16px;
}
.template-grid {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(280px, 1fr));
gap: 16px;
margin-bottom: 16px;
}
.template-option {
background: white;
border: 2px solid #e2e8f0;
border-radius: 12px;
padding: 16px;
cursor: pointer;
transition: all 0.2s ease;
position: relative;
overflow: hidden;
}
.template-option:hover {
border-color: #3b82f6;
box-shadow: 0 4px 12px rgba(59, 130, 246, 0.15);
transform: translateY(-2px);
}
.template-option.selected {
border-color: #3b82f6;
background: linear-gradient(135deg, #eff6ff 0%, #dbeafe 100%);
box-shadow: 0 4px 16px rgba(59, 130, 246, 0.2);
}
.template-option.selected::before {
content: "✓";
position: absolute;
top: 12px;
right: 12px;
width: 24px;
height: 24px;
background: #3b82f6;
color: white;
border-radius: 50%;
display: flex;
align-items: center;
justify-content: center;
font-size: 14px;
font-weight: bold;
}
.template-preview {
margin-bottom: 12px;
min-height: 80px;
display: flex;
flex-direction: column;
gap: 8px;
overflow: visible;
}
.preview-front, .preview-back {
padding: 8px 12px;
border-radius: 6px;
font-size: 0.875rem;
line-height: 1.4;
}
.preview-front {
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
color: white;
font-weight: 500;
}
.preview-back {
background: linear-gradient(135deg, #11998e 0%, #38ef7d 100%);
color: white;
font-weight: 500;
}
.template-info {
text-align: left;
}
.template-name {
font-size: 1rem;
font-weight: 600;
color: #1e293b;
margin-bottom: 4px;
}
.template-desc {
font-size: 0.875rem;
color: #64748b;
line-height: 1.4;
margin-bottom: 8px;
}
.template-fields {
font-size: 0.75rem;
color: #3b82f6;
background: #eff6ff;
padding: 4px 8px;
border-radius: 4px;
font-weight: 500;
}
.template-actions {
display: flex;
justify-content: center;
margin-bottom: 16px;
}
.template-preview-detail {
background: white;
border: 1px solid #e2e8f0;
border-radius: 12px;
padding: 20px;
margin-top: 16px;
}
.template-preview-detail h6 {
margin: 0 0 16px 0;
color: #1e293b;
font-size: 1.125rem;
font-weight: 600;
text-align: center;
padding-bottom: 12px;
border-bottom: 2px solid #e2e8f0;
}
.template-info-detail {
background: #f8fafc;
padding: 16px;
border-radius: 8px;
margin-bottom: 20px;
font-size: 0.875rem;
line-height: 1.5;
}
.template-description,
.template-fields-detail,
.template-usage {
margin-bottom: 12px;
}
.template-description strong,
.template-fields-detail strong,
.template-usage strong {
color: #374151;
margin-right: 8px;
}
.field-list {
display: inline-flex;
flex-wrap: wrap;
gap: 4px;
margin-left: 8px;
}
.field-tag {
background: #dbeafe;
color: #1e40af;
padding: 2px 6px;
border-radius: 4px;
font-size: 0.75rem;
font-weight: 500;
}
.preview-container {
display: grid;
grid-template-columns: 1fr 1fr;
gap: 20px;
margin-top: 20px;
}
.preview-card {
border: 1px solid #e2e8f0;
border-radius: 8px;
overflow: hidden;
background: white;
}
.preview-label {
background: #f1f5f9;
padding: 12px 16px;
font-weight: 600;
color: #374151;
font-size: 0.875rem;
text-transform: uppercase;
letter-spacing: 0.5px;
border-bottom: 1px solid #e2e8f0;
flex-shrink: 0;
}
.preview-content {
padding: 16px;
min-height: 120px;
font-size: 0.875rem;
line-height: 1.5;
word-wrap: break-word;
overflow: hidden;
display: flex;
flex-direction: column;
height: auto;
}
/* 确保模板预览区域的样式不被外部CSS干扰 */
.template-preview-detail .preview-content * {
box-sizing: border-box;
}
.template-preview-detail .preview-content .card {
margin: 0;
transform: scale(0.85);
transform-origin: top center;
width: 100%;
height: auto;
overflow: hidden;
}
/* 优化模板预览的显示效果 */
.template-preview-detail {
background: white;
border: 1px solid #e2e8f0;
border-radius: 12px;
padding: 20px;
margin-top: 16px;
overflow: hidden;
}
.preview-container {
display: grid;
grid-template-columns: 1fr 1fr;
gap: 20px;
margin-top: 20px;
align-items: start;
}
.preview-card {
border: 1px solid #e2e8f0;
border-radius: 8px;
overflow: hidden;
background: white;
box-shadow: 0 2px 4px rgba(0,0,0,0.05);
height: auto;
min-height: 200px;
display: flex;
flex-direction: column;
}
/* Responsive template grid */
@media (max-width: 768px) {
.template-grid {
grid-template-columns: 1fr;
gap: 12px;
}
.preview-container {
grid-template-columns: 1fr;
gap: 16px;
}
.template-option {
padding: 14px;
}
.template-preview {
min-height: 70px;
overflow: visible;
}
.preview-front, .preview-back {
padding: 6px 10px;
font-size: 0.8rem;
}
.template-preview-detail .preview-content .card {
transform: scale(0.75);
overflow: hidden;
}
.preview-container {
grid-template-columns: 1fr;
}
}
| 19,032 | AnkiCardGeneration | css | en | css | data | {"qsc_code_num_words": 2444, "qsc_code_num_chars": 19032.0, "qsc_code_mean_word_length": 5.05728314, "qsc_code_frac_words_unique": 0.14198036, "qsc_code_frac_chars_top_2grams": 0.03106796, "qsc_code_frac_chars_top_3grams": 0.02475728, "qsc_code_frac_chars_top_4grams": 0.02305825, "qsc_code_frac_chars_dupe_5grams": 0.44304207, "qsc_code_frac_chars_dupe_6grams": 0.3538835, "qsc_code_frac_chars_dupe_7grams": 0.27135922, "qsc_code_frac_chars_dupe_8grams": 0.22055016, "qsc_code_frac_chars_dupe_9grams": 0.19174757, "qsc_code_frac_chars_dupe_10grams": 0.17815534, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.09412149, "qsc_code_frac_chars_whitespace": 0.19556536, "qsc_code_size_file_byte": 19032.0, "qsc_code_num_lines": 1183.0, "qsc_code_num_chars_line_max": 65.0, "qsc_code_num_chars_line_mean": 16.08791209, "qsc_code_frac_chars_alphabet": 0.71312867, "qsc_code_frac_chars_comments": 0.0, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.51976285, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.0003678, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0} | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 1, "qsc_code_mean_word_length": 0, "qsc_code_frac_words_unique": 1, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0} |
000haoji/deep-student | src/components/DataStats.tsx | import { useState, useEffect } from 'react';
import { TauriAPI } from '../utils/tauriApi';
interface DataStatsProps {
className?: string;
}
export const DataStats: React.FC<DataStatsProps> = ({ className }) => {
const [mistakeCount, setMistakeCount] = useState(0);
const [loading, setLoading] = useState(true);
useEffect(() => {
const loadStats = async () => {
try {
const mistakes = await TauriAPI.getMistakes();
setMistakeCount(mistakes.length);
} catch (error) {
console.error('加载统计数据失败:', error);
} finally {
setLoading(false);
}
};
loadStats();
}, []);
if (loading) {
return <div className={className}>加载中...</div>;
}
return (
<div className={className}>
<div className="stat-item">
<span className="stat-label">错题总数:</span>
<span className="stat-value">{mistakeCount}</span>
</div>
<div className="stat-item">
<span className="stat-label">回顾分析:</span>
<span className="stat-value">0</span>
</div>
<div className="stat-item">
<span className="stat-label">存储大小:</span>
<span className="stat-value">计算中...</span>
</div>
</div>
);
}; | 1,224 | DataStats | tsx | en | tsx | code | {"qsc_code_num_words": 118, "qsc_code_num_chars": 1224.0, "qsc_code_mean_word_length": 6.05084746, "qsc_code_frac_words_unique": 0.39830508, "qsc_code_frac_chars_top_2grams": 0.16386555, "qsc_code_frac_chars_top_3grams": 0.14285714, "qsc_code_frac_chars_top_4grams": 0.08403361, "qsc_code_frac_chars_dupe_5grams": 0.30532213, "qsc_code_frac_chars_dupe_6grams": 0.19607843, "qsc_code_frac_chars_dupe_7grams": 0.19607843, "qsc_code_frac_chars_dupe_8grams": 0.19607843, "qsc_code_frac_chars_dupe_9grams": 0.1372549, "qsc_code_frac_chars_dupe_10grams": 0.1372549, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.00215285, "qsc_code_frac_chars_whitespace": 0.24101307, "qsc_code_size_file_byte": 1224.0, "qsc_code_num_lines": 47.0, "qsc_code_num_chars_line_max": 72.0, "qsc_code_num_chars_line_mean": 26.04255319, "qsc_code_frac_chars_alphabet": 0.7664155, "qsc_code_frac_chars_comments": 0.0, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.2195122, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.09632653, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0} |
000haoji/deep-student | src/components/DataImportExport.tsx | import React, { useState } from 'react';
import { TauriAPI } from '../utils/tauriApi';
import { DataStats } from './DataStats';
import { Upload, Download, BarChart3, AlertTriangle, Trash2, Lightbulb, FileText, Calendar, HardDrive, Settings } from 'lucide-react';
interface DataImportExportProps {
onClose?: () => void;
}
export const DataImportExport: React.FC<DataImportExportProps> = ({ onClose }) => {
const [isExporting, setIsExporting] = useState(false);
const [isImporting, setIsImporting] = useState(false);
const [importFile, setImportFile] = useState<File | null>(null);
const [exportFormat, setExportFormat] = useState<'json' | 'csv'>('json');
const [isExportingSettings, setIsExportingSettings] = useState(false);
const [isImportingSettings, setIsImportingSettings] = useState(false);
const [settingsImportFile, setSettingsImportFile] = useState<File | null>(null);
// 导出数据
const handleExport = async () => {
setIsExporting(true);
try {
console.log('开始导出完整数据...');
// 并行获取所有数据
const [
rawMistakes,
statistics,
apiConfigs,
modelAssignments,
subjectConfigs
] = await Promise.all([
TauriAPI.getMistakes(),
TauriAPI.getStatistics(),
TauriAPI.getApiConfigurations(),
TauriAPI.getModelAssignments(),
TauriAPI.getAllSubjectConfigs(false) // 包括禁用的配置
]);
// 新增：将图片文件转换为Base64包含在备份中
console.log('开始处理图片备份，错题数量:', rawMistakes.length);
const mistakesWithImages = await Promise.all(
rawMistakes.map(async (mistake) => {
try {
// 处理问题图片
const questionImageData = await Promise.all(
mistake.question_images.map(async (imagePath) => {
try {
const base64Data = await TauriAPI.getImageAsBase64(imagePath);
return {
path: imagePath,
data: base64Data
};
} catch (error) {
console.warn(`备份图片失败: ${imagePath}`, error);
return {
path: imagePath,
data: null
};
}
})
);
// 处理解析图片
const analysisImageData = await Promise.all(
mistake.analysis_images.map(async (imagePath) => {
try {
const base64Data = await TauriAPI.getImageAsBase64(imagePath);
return {
path: imagePath,
data: base64Data
};
} catch (error) {
console.warn(`备份解析图片失败: ${imagePath}`, error);
return {
path: imagePath,
data: null
};
}
})
);
return {
...mistake,
question_image_data: questionImageData,
analysis_image_data: analysisImageData
};
} catch (error) {
console.warn(`处理错题图片失败: ${mistake.id}`, error);
return mistake;
}
})
);
console.log('图片备份处理完成');
const mistakes = mistakesWithImages;
// 获取系统设置（尝试获取常见设置键）
const settingKeys = [
'theme', 'language', 'auto_save', 'default_subject',
'api_configs', 'model_assignments', 'model_adapter_options'
];
const settings: Record<string, any> = {};
for (const key of settingKeys) {
try {
const value = await TauriAPI.getSetting(key);
if (value !== null) {
settings[key] = value;
}
} catch (error) {
console.warn(`获取设置失败 ${key}:`, error);
}
}
const exportData = {
version: '2.0', // 升级版本号以支持完整数据
timestamp: new Date().toISOString(),
data: {
mistakes,
reviews: [], // 目前回顾数据存储在错题聊天记录中
settings: {
system_settings: settings,
api_configurations: apiConfigs,
model_assignments: modelAssignments,
subject_configurations: subjectConfigs
},
statistics
}
};
// 统计图片备份信息
const imageStats = mistakes.reduce((stats: any, mistake: any) => {
stats.totalQuestionImages += mistake.question_images?.length || 0;
stats.totalAnalysisImages += mistake.analysis_images?.length || 0;
stats.successfulQuestionImages += mistake.question_image_data?.filter((img: any) => img.data).length || 0;
stats.successfulAnalysisImages += mistake.analysis_image_data?.filter((img: any) => img.data).length || 0;
return stats;
}, {
totalQuestionImages: 0,
totalAnalysisImages: 0,
successfulQuestionImages: 0,
successfulAnalysisImages: 0
});
console.log('导出数据统计:', {
错题数量: mistakes.length,
系统设置: Object.keys(settings).length,
API配置: apiConfigs.length,
科目配置: subjectConfigs.length,
图片备份: {
问题图片总数: imageStats.totalQuestionImages,
解析图片总数: imageStats.totalAnalysisImages,
成功备份问题图片: imageStats.successfulQuestionImages,
成功备份解析图片: imageStats.successfulAnalysisImages,
图片备份成功率: imageStats.totalQuestionImages + imageStats.totalAnalysisImages > 0
? `${((imageStats.successfulQuestionImages + imageStats.successfulAnalysisImages) / (imageStats.totalQuestionImages + imageStats.totalAnalysisImages) * 100).toFixed(1)}%`
: '无图片'
}
});
if (exportFormat === 'json') {
// JSON格式导出
const dataStr = JSON.stringify(exportData, null, 2);
const dataBlob = new Blob([dataStr], { type: 'application/json' });
const link = document.createElement('a');
link.href = URL.createObjectURL(dataBlob);
link.download = `ai-mistake-manager-backup-${new Date().toISOString().split('T')[0]}.json`;
link.click();
URL.revokeObjectURL(link.href);
} else {
// CSV格式导出（仅错题数据）
const csvHeader = 'ID,科目,创建时间,问题描述,题目类型,标签,OCR文本\n';
const csvRows = mistakes.map(mistake => {
const row = [
mistake.id,
mistake.subject,
mistake.created_at,
`"${mistake.user_question.replace(/"/g, '""')}"`,
mistake.mistake_type,
`"${mistake.tags.join(', ')}"`,
`"${mistake.ocr_text.replace(/"/g, '""')}"`
];
return row.join(',');
}).join('\n');
const csvContent = csvHeader + csvRows;
const csvBlob = new Blob([csvContent], { type: 'text/csv;charset=utf-8;' });
const link = document.createElement('a');
link.href = URL.createObjectURL(csvBlob);
link.download = `ai-mistake-manager-mistakes-${new Date().toISOString().split('T')[0]}.csv`;
link.click();
URL.revokeObjectURL(link.href);
}
alert('数据导出成功！');
} catch (error) {
console.error('导出失败:', error);
alert('导出失败: ' + error);
} finally {
setIsExporting(false);
}
};
// 导出系统设置
const handleExportSettings = async () => {
setIsExportingSettings(true);
try {
console.log('开始导出系统设置...');
// 并行获取系统设置数据
const [
apiConfigs,
modelAssignments,
subjectConfigs
] = await Promise.all([
TauriAPI.getApiConfigurations(),
TauriAPI.getModelAssignments(),
TauriAPI.getAllSubjectConfigs(false) // 包括禁用的配置
]);
// 获取系统设置（尝试获取常见设置键）
const settingKeys = [
'theme', 'language', 'auto_save', 'default_subject',
'api_configs', 'model_assignments', 'model_adapter_options'
];
const systemSettings: Record<string, any> = {};
for (const key of settingKeys) {
try {
const value = await TauriAPI.getSetting(key);
if (value !== null) {
systemSettings[key] = value;
}
} catch (error) {
console.warn(`获取设置失败 ${key}:`, error);
}
}
const exportData = {
version: '2.0',
type: 'settings_only',
timestamp: new Date().toISOString(),
settings: {
system_settings: systemSettings,
api_configurations: apiConfigs,
model_assignments: modelAssignments,
subject_configurations: subjectConfigs
}
};
console.log('导出系统设置统计:', {
系统设置: Object.keys(systemSettings).length,
API配置: apiConfigs.length,
科目配置: subjectConfigs.length
});
const dataStr = JSON.stringify(exportData, null, 2);
const dataBlob = new Blob([dataStr], { type: 'application/json' });
const link = document.createElement('a');
link.href = URL.createObjectURL(dataBlob);
link.download = `ai-mistake-manager-settings-${new Date().toISOString().split('T')[0]}.json`;
link.click();
URL.revokeObjectURL(link.href);
alert('系统设置导出成功！');
} catch (error) {
console.error('系统设置导出失败:', error);
alert('系统设置导出失败: ' + error);
} finally {
setIsExportingSettings(false);
}
};
// 导入系统设置
const handleImportSettings = async () => {
if (!settingsImportFile) {
alert('请选择要导入的系统设置文件');
return;
}
setIsImportingSettings(true);
try {
const fileContent = await readFileAsText(settingsImportFile);
const importData = JSON.parse(fileContent);
if (!importData.settings || importData.type !== 'settings_only') {
throw new Error('无效的系统设置备份文件格式');
}
// 确认导入
const settingsInfo = {
系统设置: Object.keys(importData.settings.system_settings || {}).length,
API配置: (importData.settings.api_configurations || []).length,
模型分配: importData.settings.model_assignments ? 1 : 0,
科目配置: (importData.settings.subject_configurations || []).length
};
const confirmMessage = `
即将导入系统设置（备份版本: ${importData.version || '1.0'}）：
- 系统设置: ${settingsInfo.系统设置} 项
- API配置: ${settingsInfo.API配置} 个
- 模型分配: ${settingsInfo.模型分配 > 0 ? '包含' : '无'}
- 科目配置: ${settingsInfo.科目配置} 个
- 备份时间: ${new Date(importData.timestamp).toLocaleString('zh-CN')}
注意：导入将覆盖现有系统设置，是否继续？
`;
if (!confirm(confirmMessage.trim())) {
return;
}
console.log('开始导入系统设置...');
let importResults = {
settings: 0,
apiConfigs: 0,
modelAssignments: 0,
subjectConfigs: 0
};
// 导入系统设置
if (importData.settings.system_settings) {
for (const [key, value] of Object.entries(importData.settings.system_settings)) {
try {
await TauriAPI.saveSetting(key, String(value));
importResults.settings++;
} catch (error) {
console.warn(`导入设置失败 ${key}:`, error);
}
}
}
// 导入API配置
if (importData.settings.api_configurations) {
try {
await TauriAPI.saveApiConfigurations(importData.settings.api_configurations);
importResults.apiConfigs = importData.settings.api_configurations.length;
console.log('API配置导入成功');
} catch (error) {
console.warn('API配置导入失败:', error);
}
}
// 导入模型分配
if (importData.settings.model_assignments) {
try {
await TauriAPI.saveModelAssignments(importData.settings.model_assignments);
importResults.modelAssignments = 1;
console.log('模型分配导入成功');
} catch (error) {
console.warn('模型分配导入失败:', error);
}
}
// 导入科目配置
if (importData.settings.subject_configurations) {
console.log('科目配置导入功能需要后端API支持，暂时跳过');
}
const successMessage = `
系统设置导入完成！统计信息：
- 系统设置：${importResults.settings} 项
- API配置：${importResults.apiConfigs} 个
- 模型分配：${importResults.modelAssignments > 0 ? '已更新' : '无'}
页面将刷新以应用更改。
`;
alert(successMessage.trim());
window.location.reload();
} catch (error) {
console.error('系统设置导入失败:', error);
alert('系统设置导入失败: ' + error);
} finally {
setIsImportingSettings(false);
setSettingsImportFile(null);
}
};
// 导入数据
const handleImport = async () => {
if (!importFile) {
alert('请选择要导入的文件');
return;
}
setIsImporting(true);
try {
const fileContent = await readFileAsText(importFile);
if (importFile.name.endsWith('.json')) {
// JSON格式导入
const importData = JSON.parse(fileContent);
if (!importData.data || !importData.data.mistakes) {
throw new Error('无效的备份文件格式');
}
// 确认导入
const settingsInfo = importData.data.settings ? {
系统设置: Object.keys(importData.data.settings.system_settings || {}).length,
API配置: (importData.data.settings.api_configurations || []).length,
模型分配: importData.data.settings.model_assignments ? 1 : 0,
科目配置: (importData.data.settings.subject_configurations || []).length
} : {};
// 统计图片备份信息
const imageBackupStats = importData.data.mistakes.reduce((stats: any, mistake: any) => {
if (mistake.question_image_data) {
stats.totalQuestionImages += mistake.question_image_data.length;
stats.backedUpQuestionImages += mistake.question_image_data.filter((img: any) => img.data).length;
}
if (mistake.analysis_image_data) {
stats.totalAnalysisImages += mistake.analysis_image_data.length;
stats.backedUpAnalysisImages += mistake.analysis_image_data.filter((img: any) => img.data).length;
}
return stats;
}, {
totalQuestionImages: 0,
totalAnalysisImages: 0,
backedUpQuestionImages: 0,
backedUpAnalysisImages: 0
});
const totalImages = imageBackupStats.totalQuestionImages + imageBackupStats.totalAnalysisImages;
const backedUpImages = imageBackupStats.backedUpQuestionImages + imageBackupStats.backedUpAnalysisImages;
const confirmMessage = `
即将导入数据（备份版本: ${importData.version || '1.0'}）：
- 错题数量: ${importData.data.mistakes.length}
- 系统设置: ${settingsInfo.系统设置 || 0} 项
- API配置: ${settingsInfo.API配置 || 0} 个
- 模型分配: ${(settingsInfo.模型分配 || 0) > 0 ? '包含' : '无'}
- 科目配置: ${settingsInfo.科目配置 || 0} 个
- 图片备份: ${totalImages > 0 ? `${backedUpImages}/${totalImages} (${(backedUpImages/totalImages*100).toFixed(1)}%)` : '无图片'}
- 备份时间: ${new Date(importData.timestamp).toLocaleString('zh-CN')}
注意：导入将覆盖现有数据，是否继续？
`;
if (!confirm(confirmMessage.trim())) {
return;
}
console.log('开始导入完整数据...');
let importResults = {
mistakes: 0,
settings: 0,
apiConfigs: 0,
modelAssignments: 0,
subjectConfigs: 0
};
// 1. 预处理：恢复图片文件
console.log('开始恢复图片文件...');
const mistakesToImport = [];
for (const mistake of importData.data.mistakes) {
try {
const processedMistake = { ...mistake };
// 🎯 处理问题图片
if (mistake.question_image_data && mistake.question_image_data.length > 0) {
const newQuestionImages = [];
for (const imageInfo of mistake.question_image_data) {
if (imageInfo.data) {
try {
// 从备份的Base64数据恢复图片文件
const newPath = await TauriAPI.saveImageFromBase64(imageInfo.data, imageInfo.path);
newQuestionImages.push(newPath);
console.log(`恢复问题图片成功: ${imageInfo.path} -> ${newPath}`);
} catch (error) {
console.warn(`恢复问题图片失败: ${imageInfo.path}`, error);
// 如果恢复失败，使用原路径（可能不存在）
newQuestionImages.push(imageInfo.path);
}
} else {
// 没有备份数据，使用原路径
newQuestionImages.push(imageInfo.path);
}
}
processedMistake.question_images = newQuestionImages;
}
// 🎯 处理解析图片
if (mistake.analysis_image_data && mistake.analysis_image_data.length > 0) {
const newAnalysisImages = [];
for (const imageInfo of mistake.analysis_image_data) {
if (imageInfo.data) {
try {
const newPath = await TauriAPI.saveImageFromBase64(imageInfo.data, imageInfo.path);
newAnalysisImages.push(newPath);
console.log(`恢复解析图片成功: ${imageInfo.path} -> ${newPath}`);
} catch (error) {
console.warn(`恢复解析图片失败: ${imageInfo.path}`, error);
newAnalysisImages.push(imageInfo.path);
}
} else {
newAnalysisImages.push(imageInfo.path);
}
}
processedMistake.analysis_images = newAnalysisImages;
}
// 清理临时的图片数据字段，避免传递到后端
delete processedMistake.question_image_data;
delete processedMistake.analysis_image_data;
mistakesToImport.push(processedMistake);
} catch (error) {
console.warn(`处理错题失败: ${mistake.id}`, error);
mistakesToImport.push(mistake);
}
}
console.log('图片恢复完成，开始导入错题数据...');
// 2. 导入错题数据 - 使用批量操作
if (mistakesToImport.length > 0) {
try {
await TauriAPI.batchSaveMistakes(mistakesToImport);
importResults.mistakes = mistakesToImport.length;
console.log(`批量导入 ${mistakesToImport.length} 道错题成功`);
} catch (error) {
console.error('批量导入失败，尝试逐个导入:', error);
// 如果批量操作失败，回退到逐个保存
let successCount = 0;
for (const mistake of mistakesToImport) {
try {
await TauriAPI.updateMistake(mistake);
successCount++;
} catch (error) {
console.warn('导入错题失败:', mistake.id, error);
}
}
importResults.mistakes = successCount;
console.log(`逐个导入完成，成功: ${successCount}/${mistakesToImport.length}`);
}
}
// 2. 导入设置数据
if (importData.data.settings) {
// 导入系统设置
if (importData.data.settings.system_settings) {
for (const [key, value] of Object.entries(importData.data.settings.system_settings)) {
try {
await TauriAPI.saveSetting(key, String(value));
importResults.settings++;
} catch (error) {
console.warn(`导入设置失败 ${key}:`, error);
}
}
}
// 导入API配置
if (importData.data.settings.api_configurations) {
try {
await TauriAPI.saveApiConfigurations(importData.data.settings.api_configurations);
importResults.apiConfigs = importData.data.settings.api_configurations.length;
console.log('API配置导入成功');
} catch (error) {
console.warn('API配置导入失败:', error);
}
}
// 导入模型分配
if (importData.data.settings.model_assignments) {
try {
await TauriAPI.saveModelAssignments(importData.data.settings.model_assignments);
importResults.modelAssignments = 1;
console.log('模型分配导入成功');
} catch (error) {
console.warn('模型分配导入失败:', error);
}
}
// 导入科目配置（如果支持）
if (importData.data.settings.subject_configurations) {
// 注意：科目配置导入需要逐个处理，因为可能涉及创建或更新
for (const config of importData.data.settings.subject_configurations) {
try {
// 这里可能需要检查是创建还是更新
// 为简化，我们尝试更新，如果失败则跳过
console.log('科目配置导入功能需要后端API支持，暂时跳过');
} catch (error) {
console.warn('科目配置导入失败:', error);
}
}
}
}
const successMessage = `
导入完成！统计信息：
- 错题：${importResults.mistakes} 条
- 系统设置：${importResults.settings} 项
- API配置：${importResults.apiConfigs} 个
- 模型分配：${importResults.modelAssignments > 0 ? '已更新' : '无'}
页面将刷新以应用更改。
`;
alert(successMessage.trim());
window.location.reload();
} else if (importFile.name.endsWith('.csv')) {
// CSV格式导入（仅错题数据）
const lines = fileContent.split('\n');
const header = lines[0];
if (!header.includes('ID') || !header.includes('科目')) {
throw new Error('CSV文件格式不正确');
}
const mistakes = [];
for (let i = 1; i < lines.length; i++) {
const line = lines[i].trim();
if (!line) continue;
const values = parseCSVLine(line);
if (values.length >= 7) {
mistakes.push({
id: values[0],
subject: values[1],
created_at: values[2],
updated_at: values[2], // 使用创建时间作为更新时间
user_question: values[3],
mistake_type: values[4],
tags: values[5].split(', ').filter((tag: string) => tag.trim()),
ocr_text: values[6],
question_images: [],
analysis_images: [],
status: 'completed',
chat_history: []
});
}
}
if (mistakes.length === 0) {
throw new Error('CSV文件中没有有效的错题数据');
}
if (!confirm(`即将导入 ${mistakes.length} 道错题，是否继续？`)) {
return;
}
// 使用批量保存错题
try {
await TauriAPI.batchSaveMistakes(mistakes);
alert(`成功批量导入 ${mistakes.length} 道错题！`);
} catch (error) {
console.error('批量导入失败，尝试逐个导入:', error);
// 如果批量操作失败，回退到逐个保存
let successCount = 0;
for (const mistake of mistakes) {
try {
await TauriAPI.updateMistake(mistake);
successCount++;
} catch (error) {
console.warn('导入错题失败:', mistake.id, error);
}
}
alert(`成功导入 ${successCount} 道错题（使用逐个导入）！`);
}
} else {
throw new Error('不支持的文件格式，请选择 .json 或 .csv 文件');
}
} catch (error) {
console.error('导入失败:', error);
alert('导入失败: ' + error);
} finally {
setIsImporting(false);
setImportFile(null);
}
};
// 清空所有数据 - 三层验证防误触
const handleClearAllData = async () => {
// 第一层验证：基本确认
const confirmMessage = `
⚠️ 危险操作警告 ⚠️
您即将删除所有数据，包括：
- 所有错题记录
- 所有回顾分析
- 所有设置配置
此操作不可恢复！请确认您已经备份了重要数据。
确定要继续吗？
`;
if (!confirm(confirmMessage.trim())) {
return;
}
// 第二层验证：等待3秒冷静期
const waitMessage = `
正在进入数据清空流程...
请等待 3 秒冷静期，然后会进入最终确认。
如果您改变主意，请关闭此对话框。
`;
if (!confirm(waitMessage.trim())) {
return;
}
// 显示倒计时
for (let i = 3; i >= 1; i--) {
await new Promise(resolve => setTimeout(resolve, 1000));
if (!confirm(`${i} 秒后进入最终确认...\n\n点击"取消"可随时停止操作`)) {
return;
}
}
// 第三层验证：输入确认文本
const currentTime = new Date().toLocaleTimeString('zh-CN');
const finalConfirm = prompt(`
🔐 最终安全验证
当前时间: ${currentTime}
请输入以下确认文本来完成数据清空：
"我确认删除所有数据${currentTime.slice(-5)}"
注意：必须完全匹配，包括时间后缀
`);
const expectedText = `我确认删除所有数据${currentTime.slice(-5)}`;
if (finalConfirm !== expectedText) {
alert('确认文本不正确或已超时，操作已取消\n\n为了安全，请重新开始整个验证流程');
return;
}
try {
// 获取所有错题ID并批量删除
const allMistakes = await TauriAPI.getMistakes();
const mistakeIds = allMistakes.map(mistake => mistake.id);
if (mistakeIds.length === 0) {
alert('✅ 数据库已经是空的！');
return;
}
try {
await TauriAPI.batchDeleteMistakes(mistakeIds);
alert(`✅ 已批量清空 ${mistakeIds.length} 道错题！页面将刷新。`);
} catch (error) {
console.error('批量删除失败，尝试逐个删除:', error);
// 如果批量删除失败，回退到逐个删除
let deletedCount = 0;
for (const mistake of allMistakes) {
try {
await TauriAPI.deleteMistake(mistake.id);
deletedCount++;
} catch (error) {
console.warn('删除错题失败:', mistake.id, error);
}
}
alert(`✅ 已清空 ${deletedCount} 道错题（使用逐个删除）！页面将刷新。`);
}
window.location.reload();
} catch (error) {
console.error('清空数据失败:', error);
alert('清空数据失败: ' + error);
}
};
// 读取文件内容
const readFileAsText = (file: File): Promise<string> => {
return new Promise((resolve, reject) => {
const reader = new FileReader();
reader.onload = (e) => resolve(e.target?.result as string);
reader.onerror = (e) => reject(e);
reader.readAsText(file, 'utf-8');
});
};
// 解析CSV行
const parseCSVLine = (line: string): string[] => {
const result = [];
let current = '';
let inQuotes = false;
for (let i = 0; i < line.length; i++) {
const char = line[i];
if (char === '"') {
if (inQuotes && line[i + 1] === '"') {
current += '"';
i++; // 跳过下一个引号
} else {
inQuotes = !inQuotes;
}
} else if (char === ',' && !inQuotes) {
result.push(current);
current = '';
} else {
current += char;
}
}
result.push(current);
return result;
};
return (
<div style={{
width: '100%',
height: '100%',
overflow: 'auto',
background: '#f8fafc'
}}>
{/* 头部区域 - 统一白色样式 */}
<div style={{
background: 'white',
borderBottom: '1px solid #e5e7eb',
padding: '24px 32px',
position: 'relative'
}}>
<div style={{
position: 'absolute',
top: 0,
left: 0,
right: 0,
height: '4px',
background: 'linear-gradient(90deg, #667eea, #764ba2)'
}}></div>
<div style={{ position: 'relative', zIndex: 1 }}>
<div style={{ display: 'flex', alignItems: 'center', marginBottom: '8px' }}>
<svg style={{ width: '32px', height: '32px', marginRight: '12px', color: '#667eea' }} fill="none" stroke="currentColor" viewBox="0 0 24 24" strokeWidth={2}>
<path d="M11 21.73a2 2 0 0 0 2 0l7-4A2 2 0 0 0 21 16V8a2 2 0 0 0-1-1.73l-7-4a2 2 0 0 0-2 0l-7 4A2 2 0 0 0 3 8v8a2 2 0 0 0 1 1.73z" />
<path d="M12 22V12" />
<polyline points="3.29 7 12 12 20.71 7" />
<path d="m7.5 4.27 9 5.15" />
</svg>
<h1 style={{ fontSize: '28px', fontWeight: '700', margin: 0, color: '#1f2937' }}>数据管理</h1>
</div>
<p style={{ fontSize: '16px', color: '#6b7280', margin: 0, lineHeight: '1.5' }}>
备份和恢复您的学习数据，确保数据安全和迁移便利
</p>
</div>
</div>
<div className="data-import-export" style={{ padding: '24px', background: 'transparent' }}>
{/* 数据导出 */}
<div className="section" style={{
backgroundColor: 'white',
padding: '1.5rem',
borderRadius: '8px',
boxShadow: '0 2px 4px rgba(0,0,0,0.1)',
marginBottom: '1.5rem'
}}>
<h4 style={{ display: 'flex', alignItems: 'center', gap: '8px' }}>
<Upload size={20} />
数据导出
</h4>
<p>将您的错题数据导出为备份文件</p>
<div className="export-options">
<div className="format-selector">
<label>导出格式:</label>
<select
value={exportFormat}
onChange={(e) => setExportFormat(e.target.value as 'json' | 'csv')}
>
<option value="json">JSON (完整备份)</option>
<option value="csv">CSV (仅错题数据)</option>
</select>
</div>
<div className="format-description">
{exportFormat === 'json' ? (
<p style={{ display: 'flex', alignItems: 'center', gap: '8px' }}>
<Lightbulb size={16} />
JSON格式包含完整数据，可用于完整恢复
</p>
) : (
<p style={{ display: 'flex', alignItems: 'center', gap: '8px' }}>
<Lightbulb size={16} />
CSV格式仅包含错题基本信息，适合在Excel中查看
</p>
)}
</div>
</div>
<button
onClick={handleExport}
disabled={isExporting}
className="export-button"
style={{ display: 'flex', alignItems: 'center', gap: '8px' }}
>
{isExporting ? '导出中...' : (
<>
<Download size={16} />
导出数据
</>
)}
</button>
</div>
{/* 数据导入 */}
<div className="section" style={{
backgroundColor: 'white',
padding: '1.5rem',
borderRadius: '8px',
boxShadow: '0 2px 4px rgba(0,0,0,0.1)',
marginBottom: '1.5rem'
}}>
<h4 style={{ display: 'flex', alignItems: 'center', gap: '8px' }}>
<Download size={20} />
数据导入
</h4>
<p>从备份文件恢复您的错题数据</p>
<div className="import-options">
<div className="file-selector">
<input
type="file"
accept=".json,.csv"
onChange={(e) => setImportFile(e.target.files?.[0] || null)}
id="import-file"
/>
<label htmlFor="import-file" className="file-label">
{importFile ? importFile.name : '选择备份文件 (.json 或 .csv)'}
</label>
</div>
{importFile && (
<div className="file-info">
<p style={{ display: 'flex', alignItems: 'center', gap: '8px' }}>
<FileText size={16} />
文件: {importFile.name}
</p>
<p style={{ display: 'flex', alignItems: 'center', gap: '8px' }}>
<HardDrive size={16} />
大小: {(importFile.size / 1024).toFixed(2)} KB
</p>
<p style={{ display: 'flex', alignItems: 'center', gap: '8px' }}>
<Calendar size={16} />
修改时间: {new Date(importFile.lastModified).toLocaleString('zh-CN')}
</p>
</div>
)}
</div>
<button
onClick={handleImport}
disabled={isImporting || !importFile}
className="import-button"
style={{ display: 'flex', alignItems: 'center', gap: '8px' }}
>
{isImporting ? '导入中...' : (
<>
<Upload size={16} />
导入数据
</>
)}
</button>
</div>
{/* 系统设置导出/导入 */}
<div className="section" style={{
backgroundColor: 'white',
padding: '1.5rem',
borderRadius: '8px',
boxShadow: '0 2px 4px rgba(0,0,0,0.1)',
marginBottom: '1.5rem'
}}>
<h4 style={{ display: 'flex', alignItems: 'center', gap: '8px', marginBottom: '1rem' }}>
<Settings size={20} />
系统设置管理
</h4>
<p style={{ marginBottom: '1.5rem' }}>单独导出或恢复API、科目、系统配置等设置，不影响错题数据</p>
<div style={{ display: 'grid', gridTemplateColumns: '1fr 1fr', gap: '1rem' }}>
{/* 设置导出 */}
<div style={{
border: '1px solid #e5e7eb',
borderRadius: '6px',
padding: '1rem'
}}>
<h5 style={{ margin: '0 0 0.5rem 0', fontSize: '14px', fontWeight: '600' }}>导出系统设置</h5>
<p style={{ margin: '0 0 1rem 0', fontSize: '13px', color: '#6b7280' }}>
包含API配置、科目设置、模型分配等
</p>
<button
onClick={handleExportSettings}
disabled={isExportingSettings}
style={{
display: 'flex',
alignItems: 'center',
gap: '6px',
padding: '8px 16px',
backgroundColor: '#3b82f6',
color: 'white',
border: 'none',
borderRadius: '4px',
fontSize: '14px',
cursor: isExportingSettings ? 'not-allowed' : 'pointer',
opacity: isExportingSettings ? 0.6 : 1
}}
>
{isExportingSettings ? '导出中...' : (
<>
<Download size={14} />
导出设置
</>
)}
</button>
</div>
{/* 设置导入 */}
<div style={{
border: '1px solid #e5e7eb',
borderRadius: '6px',
padding: '1rem'
}}>
<h5 style={{ margin: '0 0 0.5rem 0', fontSize: '14px', fontWeight: '600' }}>恢复系统设置</h5>
<p style={{ margin: '0 0 1rem 0', fontSize: '13px', color: '#6b7280' }}>
从设置备份文件恢复配置
</p>
<div style={{ marginBottom: '0.75rem' }}>
<input
type="file"
accept=".json"
onChange={(e) => setSettingsImportFile(e.target.files?.[0] || null)}
id="settings-import-file"
style={{ display: 'none' }}
/>
<label
htmlFor="settings-import-file"
style={{
display: 'inline-block',
padding: '6px 12px',
backgroundColor: '#f3f4f6',
border: '1px solid #d1d5db',
borderRadius: '4px',
fontSize: '13px',
cursor: 'pointer',
width: '100%',
textAlign: 'center',
boxSizing: 'border-box'
}}
>
{settingsImportFile ? settingsImportFile.name : '选择设置文件'}
</label>
</div>
<button
onClick={handleImportSettings}
disabled={isImportingSettings || !settingsImportFile}
style={{
display: 'flex',
alignItems: 'center',
gap: '6px',
padding: '8px 16px',
backgroundColor: '#10b981',
color: 'white',
border: 'none',
borderRadius: '4px',
fontSize: '14px',
cursor: (isImportingSettings || !settingsImportFile) ? 'not-allowed' : 'pointer',
opacity: (isImportingSettings || !settingsImportFile) ? 0.6 : 1
}}
>
{isImportingSettings ? '恢复中...' : (
<>
<Upload size={14} />
恢复设置
</>
)}
</button>
</div>
</div>
<div style={{
marginTop: '1rem',
padding: '0.75rem',
backgroundColor: '#f8fafc',
borderRadius: '4px',
fontSize: '13px',
color: '#6b7280'
}}>
<div style={{ display: 'flex', alignItems: 'center', gap: '6px', marginBottom: '4px' }}>
<Lightbulb size={14} />
<strong>提示：</strong>
</div>
<ul style={{ margin: 0, paddingLeft: '1.2rem' }}>
<li>系统设置备份独立于错题数据，可安全操作</li>
<li>包含API密钥等敏感信息，请妥善保管备份文件</li>
<li>恢复设置会覆盖当前配置，操作前请确认</li>
</ul>
</div>
</div>
{/* 数据统计 */}
<div className="section" style={{
backgroundColor: 'white',
padding: '1.5rem',
borderRadius: '8px',
boxShadow: '0 2px 4px rgba(0,0,0,0.1)',
marginBottom: '1.5rem'
}}>
<h4 style={{ display: 'flex', alignItems: 'center', gap: '8px' }}>
<BarChart3 size={20} />
当前数据统计
</h4>
<DataStats className="data-stats" />
</div>
{/* 危险操作 */}
<div className="section danger-section" style={{
backgroundColor: 'white',
padding: '1.5rem',
borderRadius: '8px',
boxShadow: '0 2px 4px rgba(0,0,0,0.1)',
marginBottom: '1.5rem'
}}>
<h4 style={{ display: 'flex', alignItems: 'center', gap: '8px' }}>
<AlertTriangle size={20} color="#dc3545" />
危险操作
</h4>
<p>以下操作将永久删除数据，请谨慎操作</p>
<button
onClick={handleClearAllData}
className="danger-button"
style={{ display: 'flex', alignItems: 'center', gap: '8px' }}
>
<Trash2 size={16} />
清空所有数据
</button>
</div>
{/* 使用提示 */}
<div className="section" style={{
backgroundColor: 'white',
padding: '1.5rem',
borderRadius: '8px',
boxShadow: '0 2px 4px rgba(0,0,0,0.1)',
marginBottom: '1.5rem'
}}>
<h4 style={{ display: 'flex', alignItems: 'center', gap: '8px' }}>
<Lightbulb size={20} />
使用提示
</h4>
<ul style={{ margin: 0, paddingLeft: '1.2rem' }}>
<li>建议定期导出数据进行备份</li>
<li>JSON格式可完整恢复所有数据</li>
<li>CSV格式适合数据分析和查看</li>
<li>导入前请确保文件格式正确</li>
</ul>
</div>
</div>
</div>
);
}; | 38,208 | DataImportExport | tsx | en | tsx | code | {"qsc_code_num_words": 3113, "qsc_code_num_chars": 38208.0, "qsc_code_mean_word_length": 6.13556055, "qsc_code_frac_words_unique": 0.21329907, "qsc_code_frac_chars_top_2grams": 0.00397906, "qsc_code_frac_chars_top_3grams": 0.02314136, "qsc_code_frac_chars_top_4grams": 0.01979058, "qsc_code_frac_chars_dupe_5grams": 0.43298429, "qsc_code_frac_chars_dupe_6grams": 0.39183246, "qsc_code_frac_chars_dupe_7grams": 0.35094241, "qsc_code_frac_chars_dupe_8grams": 0.31403141, "qsc_code_frac_chars_dupe_9grams": 0.2665445, "qsc_code_frac_chars_dupe_10grams": 0.23057592, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.02286535, "qsc_code_frac_chars_whitespace": 0.36243719, "qsc_code_size_file_byte": 38208.0, "qsc_code_num_lines": 1171.0, "qsc_code_num_chars_line_max": 183.0, "qsc_code_num_chars_line_mean": 32.62852263, "qsc_code_frac_chars_alphabet": 0.76079639, "qsc_code_frac_chars_comments": 0.02324121, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.45783133, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.00100402, "qsc_code_frac_chars_string_length": 0.07339032, "qsc_code_frac_chars_long_word_length": 0.00844029, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0} |
0015/esp_rlottie | rlottie/src/vector/vbrush.cpp | /*
* Copyright (c) 2020 Samsung Electronics Co., Ltd. All rights reserved.
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "vbrush.h"
V_BEGIN_NAMESPACE
VGradient::VGradient(VGradient::Type type)
: mType(type)
{
if (mType == Type::Linear)
linear.x1 = linear.y1 = linear.x2 = linear.y2 = 0.0f;
else
radial.cx = radial.cy = radial.fx =
radial.fy = radial.cradius = radial.fradius = 0.0f;
}
void VGradient::setStops(const VGradientStops &stops)
{
mStops = stops;
}
VBrush::VBrush(const VColor &color) : mType(VBrush::Type::Solid), mColor(color)
{
}
VBrush::VBrush(uint8_t r, uint8_t g, uint8_t b, uint8_t a)
: mType(VBrush::Type::Solid), mColor(r, g, b, a)
{
}
VBrush::VBrush(const VGradient *gradient)
{
if (!gradient) return;
mGradient = gradient;
if (gradient->mType == VGradient::Type::Linear) {
mType = VBrush::Type::LinearGradient;
} else if (gradient->mType == VGradient::Type::Radial) {
mType = VBrush::Type::RadialGradient;
}
}
VBrush::VBrush(const VTexture *texture):mType(VBrush::Type::Texture), mTexture(texture)
{
}
V_END_NAMESPACE
| 2,168 | vbrush | cpp | en | cpp | code | {"qsc_code_num_words": 302, "qsc_code_num_chars": 2168.0, "qsc_code_mean_word_length": 5.0794702, "qsc_code_frac_words_unique": 0.48675497, "qsc_code_frac_chars_top_2grams": 0.05736636, "qsc_code_frac_chars_top_3grams": 0.04889179, "qsc_code_frac_chars_top_4grams": 0.02607562, "qsc_code_frac_chars_dupe_5grams": 0.07040417, "qsc_code_frac_chars_dupe_6grams": 0.0, "qsc_code_frac_chars_dupe_7grams": 0.0, "qsc_code_frac_chars_dupe_8grams": 0.0, "qsc_code_frac_chars_dupe_9grams": 0.0, "qsc_code_frac_chars_dupe_10grams": 0.0, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.00909091, "qsc_code_frac_chars_whitespace": 0.18819188, "qsc_code_size_file_byte": 2168.0, "qsc_code_num_lines": 69.0, "qsc_code_num_chars_line_max": 88.0, "qsc_code_num_chars_line_mean": 31.42028986, "qsc_code_frac_chars_alphabet": 0.8625, "qsc_code_frac_chars_comments": 0.5295203, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.0, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.00784314, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codecpp_frac_lines_preprocessor_directives": 0.02777778, "qsc_codecpp_frac_lines_func_ratio": 0.0, "qsc_codecpp_cate_bitsstdc": 0.0, "qsc_codecpp_nums_lines_main": 0.0, "qsc_codecpp_frac_lines_goto": 0.0, "qsc_codecpp_cate_var_zero": 1.0, "qsc_codecpp_score_lines_no_logic": 0.02777778, "qsc_codecpp_frac_lines_print": 0.0} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codecpp_frac_lines_func_ratio": 0, "qsc_codecpp_nums_lines_main": 0, "qsc_codecpp_score_lines_no_logic": 0, "qsc_codecpp_frac_lines_preprocessor_directives": 0, "qsc_codecpp_frac_lines_print": 0} |
0015/esp_rlottie | rlottie/src/vector/vbitmap.h | /*
* Copyright (c) 2020 Samsung Electronics Co., Ltd. All rights reserved.
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#ifndef VBITMAP_H
#define VBITMAP_H
#include "vrect.h"
#include <vsharedptr.h>
V_BEGIN_NAMESPACE
class VBitmap {
public:
enum class Format : uint8_t {
Invalid,
Alpha8,
ARGB32,
ARGB32_Premultiplied
};
VBitmap() = default;
VBitmap(size_t w, size_t h, VBitmap::Format format);
VBitmap(uint8_t *data, size_t w, size_t h, size_t bytesPerLine,
VBitmap::Format format);
void reset(uint8_t *data, size_t w, size_t h, size_t stride,
VBitmap::Format format);
void reset(size_t w, size_t h, VBitmap::Format format=Format::ARGB32_Premultiplied);
size_t stride() const;
size_t width() const;
size_t height() const;
size_t depth() const;
VBitmap::Format format() const;
bool valid() const;
uint8_t * data();
uint8_t * data() const;
VRect rect() const;
VSize size() const;
void fill(uint32_t pixel);
void updateLuma();
private:
struct Impl {
std::unique_ptr<uint8_t[]> mOwnData{nullptr};
uint8_t * mRoData{nullptr};
uint32_t mWidth{0};
uint32_t mHeight{0};
uint32_t mStride{0};
uint8_t mDepth{0};
VBitmap::Format mFormat{VBitmap::Format::Invalid};
explicit Impl(size_t width, size_t height, VBitmap::Format format)
{
reset(width, height, format);
}
explicit Impl(uint8_t *data, size_t w, size_t h, size_t bytesPerLine,
VBitmap::Format format)
{
reset(data, w, h, bytesPerLine, format);
}
VRect rect() const { return VRect(0, 0, mWidth, mHeight);}
VSize size() const { return VSize(mWidth, mHeight); }
size_t stride() const { return mStride; }
size_t width() const { return mWidth; }
size_t height() const { return mHeight; }
uint8_t * data() { return mRoData ? mRoData : mOwnData.get(); }
VBitmap::Format format() const { return mFormat; }
void reset(uint8_t *, size_t, size_t, size_t, VBitmap::Format);
void reset(size_t, size_t, VBitmap::Format);
static uint8_t depth(VBitmap::Format format);
void fill(uint32_t);
void updateLuma();
};
rc_ptr<Impl> mImpl;
};
V_END_NAMESPACE
#endif // VBITMAP_H
| 3,630 | vbitmap | h | en | c | code | {"qsc_code_num_words": 468, "qsc_code_num_chars": 3630.0, "qsc_code_mean_word_length": 4.74786325, "qsc_code_frac_words_unique": 0.34401709, "qsc_code_frac_chars_top_2grams": 0.06075608, "qsc_code_frac_chars_top_3grams": 0.0769577, "qsc_code_frac_chars_top_4grams": 0.02250225, "qsc_code_frac_chars_dupe_5grams": 0.13636364, "qsc_code_frac_chars_dupe_6grams": 0.1129613, "qsc_code_frac_chars_dupe_7grams": 0.09225923, "qsc_code_frac_chars_dupe_8grams": 0.09225923, "qsc_code_frac_chars_dupe_9grams": 0.09225923, "qsc_code_frac_chars_dupe_10grams": 0.06435644, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.0150463, "qsc_code_frac_chars_whitespace": 0.28595041, "qsc_code_size_file_byte": 3630.0, "qsc_code_num_lines": 97.0, "qsc_code_num_chars_line_max": 89.0, "qsc_code_num_chars_line_mean": 37.42268041, "qsc_code_frac_chars_alphabet": 0.84220679, "qsc_code_frac_chars_comments": 0.31983471, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.10447761, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.00283516, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codec_frac_lines_func_ratio": 0.44776119, "qsc_codec_cate_bitsstdc": 0.0, "qsc_codec_nums_lines_main": 0, "qsc_codec_frac_lines_goto": 0.0, "qsc_codec_cate_var_zero": 0.0, "qsc_codec_score_lines_no_logic": 0.49253731, "qsc_codec_frac_lines_print": 0.0, "qsc_codec_frac_lines_preprocessor_directives": null} | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codec_frac_lines_func_ratio": 1, "qsc_codec_nums_lines_main": 0, "qsc_codec_score_lines_no_logic": 0, "qsc_codec_frac_lines_preprocessor_directives": 0, "qsc_codec_frac_lines_print": 0} |
0015/T-Glass-Applications | image_capture_app/t_glass_ble_app/windows/runner/win32_window.h | #ifndef RUNNER_WIN32_WINDOW_H_
#define RUNNER_WIN32_WINDOW_H_
#include <windows.h>
#include <functional>
#include <memory>
#include <string>
// A class abstraction for a high DPI-aware Win32 Window. Intended to be
// inherited from by classes that wish to specialize with custom
// rendering and input handling
class Win32Window {
public:
struct Point {
unsigned int x;
unsigned int y;
Point(unsigned int x, unsigned int y) : x(x), y(y) {}
};
struct Size {
unsigned int width;
unsigned int height;
Size(unsigned int width, unsigned int height)
: width(width), height(height) {}
};
Win32Window();
virtual ~Win32Window();
// Creates a win32 window with |title| that is positioned and sized using
// |origin| and |size|. New windows are created on the default monitor. Window
// sizes are specified to the OS in physical pixels, hence to ensure a
// consistent size this function will scale the inputted width and height as
// as appropriate for the default monitor. The window is invisible until
// |Show| is called. Returns true if the window was created successfully.
bool Create(const std::wstring& title, const Point& origin, const Size& size);
// Show the current window. Returns true if the window was successfully shown.
bool Show();
// Release OS resources associated with window.
void Destroy();
// Inserts |content| into the window tree.
void SetChildContent(HWND content);
// Returns the backing Window handle to enable clients to set icon and other
// window properties. Returns nullptr if the window has been destroyed.
HWND GetHandle();
// If true, closing this window will quit the application.
void SetQuitOnClose(bool quit_on_close);
// Return a RECT representing the bounds of the current client area.
RECT GetClientArea();
protected:
// Processes and route salient window messages for mouse handling,
// size change and DPI. Delegates handling of these to member overloads that
// inheriting classes can handle.
virtual LRESULT MessageHandler(HWND window,
UINT const message,
WPARAM const wparam,
LPARAM const lparam) noexcept;
// Called when CreateAndShow is called, allowing subclass window-related
// setup. Subclasses should return false if setup fails.
virtual bool OnCreate();
// Called when Destroy is called.
virtual void OnDestroy();
private:
friend class WindowClassRegistrar;
// OS callback called by message pump. Handles the WM_NCCREATE message which
// is passed when the non-client area is being created and enables automatic
// non-client DPI scaling so that the non-client area automatically
// responds to changes in DPI. All other messages are handled by
// MessageHandler.
static LRESULT CALLBACK WndProc(HWND const window,
UINT const message,
WPARAM const wparam,
LPARAM const lparam) noexcept;
// Retrieves a class instance pointer for |window|
static Win32Window* GetThisFromHandle(HWND const window) noexcept;
// Update the window frame's theme to match the system theme.
static void UpdateTheme(HWND const window);
bool quit_on_close_ = false;
// window handle for top level window.
HWND window_handle_ = nullptr;
// window handle for hosted content.
HWND child_content_ = nullptr;
};
#endif // RUNNER_WIN32_WINDOW_H_
| 3,522 | win32_window | h | en | c | code | {"qsc_code_num_words": 456, "qsc_code_num_chars": 3522.0, "qsc_code_mean_word_length": 5.35526316, "qsc_code_frac_words_unique": 0.43859649, "qsc_code_frac_chars_top_2grams": 0.03603604, "qsc_code_frac_chars_top_3grams": 0.02088452, "qsc_code_frac_chars_top_4grams": 0.02211302, "qsc_code_frac_chars_dupe_5grams": 0.12694513, "qsc_code_frac_chars_dupe_6grams": 0.12694513, "qsc_code_frac_chars_dupe_7grams": 0.10647011, "qsc_code_frac_chars_dupe_8grams": 0.05241605, "qsc_code_frac_chars_dupe_9grams": 0.05241605, "qsc_code_frac_chars_dupe_10grams": 0.05241605, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.00667656, "qsc_code_frac_chars_whitespace": 0.23452584, "qsc_code_size_file_byte": 3522.0, "qsc_code_num_lines": 102.0, "qsc_code_num_chars_line_max": 81.0, "qsc_code_num_chars_line_mean": 34.52941176, "qsc_code_frac_chars_alphabet": 0.89910979, "qsc_code_frac_chars_comments": 0.54741624, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.1875, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.0, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codec_frac_lines_func_ratio": 0.27083333, "qsc_codec_cate_bitsstdc": 0.0, "qsc_codec_nums_lines_main": 0, "qsc_codec_frac_lines_goto": 0.0, "qsc_codec_cate_var_zero": 0.0, "qsc_codec_score_lines_no_logic": 0.45833333, "qsc_codec_frac_lines_print": 0.0, "qsc_codec_frac_lines_preprocessor_directives": null} | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codec_frac_lines_func_ratio": 1, "qsc_codec_nums_lines_main": 0, "qsc_codec_score_lines_no_logic": 0, "qsc_codec_frac_lines_preprocessor_directives": 0, "qsc_codec_frac_lines_print": 0} |
0015/T-Glass-Applications | image_capture_app/t_glass_ble_app/windows/runner/win32_window.cpp | #include "win32_window.h"
#include <dwmapi.h>
#include <flutter_windows.h>
#include "resource.h"
namespace {
/// Window attribute that enables dark mode window decorations.
///
/// Redefined in case the developer's machine has a Windows SDK older than
/// version 10.0.22000.0.
/// See: https://docs.microsoft.com/windows/win32/api/dwmapi/ne-dwmapi-dwmwindowattribute
#ifndef DWMWA_USE_IMMERSIVE_DARK_MODE
#define DWMWA_USE_IMMERSIVE_DARK_MODE 20
#endif
constexpr const wchar_t kWindowClassName[] = L"FLUTTER_RUNNER_WIN32_WINDOW";
/// Registry key for app theme preference.
///
/// A value of 0 indicates apps should use dark mode. A non-zero or missing
/// value indicates apps should use light mode.
constexpr const wchar_t kGetPreferredBrightnessRegKey[] =
L"Software\\Microsoft\\Windows\\CurrentVersion\\Themes\\Personalize";
constexpr const wchar_t kGetPreferredBrightnessRegValue[] = L"AppsUseLightTheme";
// The number of Win32Window objects that currently exist.
static int g_active_window_count = 0;
using EnableNonClientDpiScaling = BOOL __stdcall(HWND hwnd);
// Scale helper to convert logical scaler values to physical using passed in
// scale factor
int Scale(int source, double scale_factor) {
return static_cast<int>(source * scale_factor);
}
// Dynamically loads the |EnableNonClientDpiScaling| from the User32 module.
// This API is only needed for PerMonitor V1 awareness mode.
void EnableFullDpiSupportIfAvailable(HWND hwnd) {
HMODULE user32_module = LoadLibraryA("User32.dll");
if (!user32_module) {
return;
}
auto enable_non_client_dpi_scaling =
reinterpret_cast<EnableNonClientDpiScaling*>(
GetProcAddress(user32_module, "EnableNonClientDpiScaling"));
if (enable_non_client_dpi_scaling != nullptr) {
enable_non_client_dpi_scaling(hwnd);
}
FreeLibrary(user32_module);
}
} // namespace
// Manages the Win32Window's window class registration.
class WindowClassRegistrar {
public:
~WindowClassRegistrar() = default;
// Returns the singleton registrar instance.
static WindowClassRegistrar* GetInstance() {
if (!instance_) {
instance_ = new WindowClassRegistrar();
}
return instance_;
}
// Returns the name of the window class, registering the class if it hasn't
// previously been registered.
const wchar_t* GetWindowClass();
// Unregisters the window class. Should only be called if there are no
// instances of the window.
void UnregisterWindowClass();
private:
WindowClassRegistrar() = default;
static WindowClassRegistrar* instance_;
bool class_registered_ = false;
};
WindowClassRegistrar* WindowClassRegistrar::instance_ = nullptr;
const wchar_t* WindowClassRegistrar::GetWindowClass() {
if (!class_registered_) {
WNDCLASS window_class{};
window_class.hCursor = LoadCursor(nullptr, IDC_ARROW);
window_class.lpszClassName = kWindowClassName;
window_class.style = CS_HREDRAW | CS_VREDRAW;
window_class.cbClsExtra = 0;
window_class.cbWndExtra = 0;
window_class.hInstance = GetModuleHandle(nullptr);
window_class.hIcon =
LoadIcon(window_class.hInstance, MAKEINTRESOURCE(IDI_APP_ICON));
window_class.hbrBackground = 0;
window_class.lpszMenuName = nullptr;
window_class.lpfnWndProc = Win32Window::WndProc;
RegisterClass(&window_class);
class_registered_ = true;
}
return kWindowClassName;
}
void WindowClassRegistrar::UnregisterWindowClass() {
UnregisterClass(kWindowClassName, nullptr);
class_registered_ = false;
}
Win32Window::Win32Window() {
++g_active_window_count;
}
Win32Window::~Win32Window() {
--g_active_window_count;
Destroy();
}
bool Win32Window::Create(const std::wstring& title,
const Point& origin,
const Size& size) {
Destroy();
const wchar_t* window_class =
WindowClassRegistrar::GetInstance()->GetWindowClass();
const POINT target_point = {static_cast<LONG>(origin.x),
static_cast<LONG>(origin.y)};
HMONITOR monitor = MonitorFromPoint(target_point, MONITOR_DEFAULTTONEAREST);
UINT dpi = FlutterDesktopGetDpiForMonitor(monitor);
double scale_factor = dpi / 96.0;
HWND window = CreateWindow(
window_class, title.c_str(), WS_OVERLAPPEDWINDOW,
Scale(origin.x, scale_factor), Scale(origin.y, scale_factor),
Scale(size.width, scale_factor), Scale(size.height, scale_factor),
nullptr, nullptr, GetModuleHandle(nullptr), this);
if (!window) {
return false;
}
UpdateTheme(window);
return OnCreate();
}
bool Win32Window::Show() {
return ShowWindow(window_handle_, SW_SHOWNORMAL);
}
// static
LRESULT CALLBACK Win32Window::WndProc(HWND const window,
UINT const message,
WPARAM const wparam,
LPARAM const lparam) noexcept {
if (message == WM_NCCREATE) {
auto window_struct = reinterpret_cast<CREATESTRUCT*>(lparam);
SetWindowLongPtr(window, GWLP_USERDATA,
reinterpret_cast<LONG_PTR>(window_struct->lpCreateParams));
auto that = static_cast<Win32Window*>(window_struct->lpCreateParams);
EnableFullDpiSupportIfAvailable(window);
that->window_handle_ = window;
} else if (Win32Window* that = GetThisFromHandle(window)) {
return that->MessageHandler(window, message, wparam, lparam);
}
return DefWindowProc(window, message, wparam, lparam);
}
LRESULT
Win32Window::MessageHandler(HWND hwnd,
UINT const message,
WPARAM const wparam,
LPARAM const lparam) noexcept {
switch (message) {
case WM_DESTROY:
window_handle_ = nullptr;
Destroy();
if (quit_on_close_) {
PostQuitMessage(0);
}
return 0;
case WM_DPICHANGED: {
auto newRectSize = reinterpret_cast<RECT*>(lparam);
LONG newWidth = newRectSize->right - newRectSize->left;
LONG newHeight = newRectSize->bottom - newRectSize->top;
SetWindowPos(hwnd, nullptr, newRectSize->left, newRectSize->top, newWidth,
newHeight, SWP_NOZORDER | SWP_NOACTIVATE);
return 0;
}
case WM_SIZE: {
RECT rect = GetClientArea();
if (child_content_ != nullptr) {
// Size and position the child window.
MoveWindow(child_content_, rect.left, rect.top, rect.right - rect.left,
rect.bottom - rect.top, TRUE);
}
return 0;
}
case WM_ACTIVATE:
if (child_content_ != nullptr) {
SetFocus(child_content_);
}
return 0;
case WM_DWMCOLORIZATIONCOLORCHANGED:
UpdateTheme(hwnd);
return 0;
}
return DefWindowProc(window_handle_, message, wparam, lparam);
}
void Win32Window::Destroy() {
OnDestroy();
if (window_handle_) {
DestroyWindow(window_handle_);
window_handle_ = nullptr;
}
if (g_active_window_count == 0) {
WindowClassRegistrar::GetInstance()->UnregisterWindowClass();
}
}
Win32Window* Win32Window::GetThisFromHandle(HWND const window) noexcept {
return reinterpret_cast<Win32Window*>(
GetWindowLongPtr(window, GWLP_USERDATA));
}
void Win32Window::SetChildContent(HWND content) {
child_content_ = content;
SetParent(content, window_handle_);
RECT frame = GetClientArea();
MoveWindow(content, frame.left, frame.top, frame.right - frame.left,
frame.bottom - frame.top, true);
SetFocus(child_content_);
}
RECT Win32Window::GetClientArea() {
RECT frame;
GetClientRect(window_handle_, &frame);
return frame;
}
HWND Win32Window::GetHandle() {
return window_handle_;
}
void Win32Window::SetQuitOnClose(bool quit_on_close) {
quit_on_close_ = quit_on_close;
}
bool Win32Window::OnCreate() {
// No-op; provided for subclasses.
return true;
}
void Win32Window::OnDestroy() {
// No-op; provided for subclasses.
}
void Win32Window::UpdateTheme(HWND const window) {
DWORD light_mode;
DWORD light_mode_size = sizeof(light_mode);
LSTATUS result = RegGetValue(HKEY_CURRENT_USER, kGetPreferredBrightnessRegKey,
kGetPreferredBrightnessRegValue,
RRF_RT_REG_DWORD, nullptr, &light_mode,
&light_mode_size);
if (result == ERROR_SUCCESS) {
BOOL enable_dark_mode = light_mode == 0;
DwmSetWindowAttribute(window, DWMWA_USE_IMMERSIVE_DARK_MODE,
&enable_dark_mode, sizeof(enable_dark_mode));
}
}
| 8,534 | win32_window | cpp | en | cpp | code | {"qsc_code_num_words": 894, "qsc_code_num_chars": 8534.0, "qsc_code_mean_word_length": 6.43847875, "qsc_code_frac_words_unique": 0.32774049, "qsc_code_frac_chars_top_2grams": 0.03439889, "qsc_code_frac_chars_top_3grams": 0.0114663, "qsc_code_frac_chars_top_4grams": 0.01250869, "qsc_code_frac_chars_dupe_5grams": 0.08113273, "qsc_code_frac_chars_dupe_6grams": 0.03978457, "qsc_code_frac_chars_dupe_7grams": 0.02015288, "qsc_code_frac_chars_dupe_8grams": 0.02015288, "qsc_code_frac_chars_dupe_9grams": 0.02015288, "qsc_code_frac_chars_dupe_10grams": 0.02015288, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.01390121, "qsc_code_frac_chars_whitespace": 0.20764003, "qsc_code_size_file_byte": 8534.0, "qsc_code_num_lines": 288.0, "qsc_code_num_chars_line_max": 90.0, "qsc_code_num_chars_line_mean": 29.63194444, "qsc_code_frac_chars_alphabet": 0.83732623, "qsc_code_frac_chars_comments": 0.1358097, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.0952381, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.02277966, "qsc_code_frac_chars_long_word_length": 0.01586441, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codecpp_frac_lines_preprocessor_directives": 0.05238095, "qsc_codecpp_frac_lines_func_ratio": 0.05238095, "qsc_codecpp_cate_bitsstdc": 0.0, "qsc_codecpp_nums_lines_main": 0.0, "qsc_codecpp_frac_lines_goto": 0.0, "qsc_codecpp_cate_var_zero": 0.0, "qsc_codecpp_score_lines_no_logic": 0.13333333, "qsc_codecpp_frac_lines_print": 0.0} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codecpp_frac_lines_func_ratio": 0, "qsc_codecpp_nums_lines_main": 0, "qsc_codecpp_score_lines_no_logic": 0, "qsc_codecpp_frac_lines_preprocessor_directives": 0, "qsc_codecpp_frac_lines_print": 0} |
0015/T-Glass-Applications | image_capture_app/t_glass_ble_app/windows/runner/utils.cpp | #include "utils.h"
#include <flutter_windows.h>
#include <io.h>
#include <stdio.h>
#include <windows.h>
#include <iostream>
void CreateAndAttachConsole() {
if (::AllocConsole()) {
FILE *unused;
if (freopen_s(&unused, "CONOUT$", "w", stdout)) {
_dup2(_fileno(stdout), 1);
}
if (freopen_s(&unused, "CONOUT$", "w", stderr)) {
_dup2(_fileno(stdout), 2);
}
std::ios::sync_with_stdio();
FlutterDesktopResyncOutputStreams();
}
}
std::vector<std::string> GetCommandLineArguments() {
// Convert the UTF-16 command line arguments to UTF-8 for the Engine to use.
int argc;
wchar_t** argv = ::CommandLineToArgvW(::GetCommandLineW(), &argc);
if (argv == nullptr) {
return std::vector<std::string>();
}
std::vector<std::string> command_line_arguments;
// Skip the first argument as it's the binary name.
for (int i = 1; i < argc; i++) {
command_line_arguments.push_back(Utf8FromUtf16(argv[i]));
}
::LocalFree(argv);
return command_line_arguments;
}
std::string Utf8FromUtf16(const wchar_t* utf16_string) {
if (utf16_string == nullptr) {
return std::string();
}
unsigned int target_length = ::WideCharToMultiByte(
CP_UTF8, WC_ERR_INVALID_CHARS, utf16_string,
-1, nullptr, 0, nullptr, nullptr)
-1; // remove the trailing null character
int input_length = (int)wcslen(utf16_string);
std::string utf8_string;
if (target_length == 0 || target_length > utf8_string.max_size()) {
return utf8_string;
}
utf8_string.resize(target_length);
int converted_length = ::WideCharToMultiByte(
CP_UTF8, WC_ERR_INVALID_CHARS, utf16_string,
input_length, utf8_string.data(), target_length, nullptr, nullptr);
if (converted_length == 0) {
return std::string();
}
return utf8_string;
}
| 1,797 | utils | cpp | en | cpp | code | {"qsc_code_num_words": 225, "qsc_code_num_chars": 1797.0, "qsc_code_mean_word_length": 5.19111111, "qsc_code_frac_words_unique": 0.39555556, "qsc_code_frac_chars_top_2grams": 0.05393836, "qsc_code_frac_chars_top_3grams": 0.06849315, "qsc_code_frac_chars_top_4grams": 0.04623288, "qsc_code_frac_chars_dupe_5grams": 0.14041096, "qsc_code_frac_chars_dupe_6grams": 0.14041096, "qsc_code_frac_chars_dupe_7grams": 0.1010274, "qsc_code_frac_chars_dupe_8grams": 0.1010274, "qsc_code_frac_chars_dupe_9grams": 0.1010274, "qsc_code_frac_chars_dupe_10grams": 0.1010274, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.02511881, "qsc_code_frac_chars_whitespace": 0.1803005, "qsc_code_size_file_byte": 1797.0, "qsc_code_num_lines": 65.0, "qsc_code_num_chars_line_max": 79.0, "qsc_code_num_chars_line_mean": 27.64615385, "qsc_code_frac_chars_alphabet": 0.76782077, "qsc_code_frac_chars_comments": 0.09293267, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.11320755, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.01411043, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codecpp_frac_lines_preprocessor_directives": 0.11320755, "qsc_codecpp_frac_lines_func_ratio": 0.03773585, "qsc_codecpp_cate_bitsstdc": 0.0, "qsc_codecpp_nums_lines_main": 0.0, "qsc_codecpp_frac_lines_goto": 0.0, "qsc_codecpp_cate_var_zero": 0.0, "qsc_codecpp_score_lines_no_logic": 0.24528302, "qsc_codecpp_frac_lines_print": 0.0} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codecpp_frac_lines_func_ratio": 0, "qsc_codecpp_nums_lines_main": 0, "qsc_codecpp_score_lines_no_logic": 0, "qsc_codecpp_frac_lines_preprocessor_directives": 0, "qsc_codecpp_frac_lines_print": 0} |
0015/esp_rlottie | rlottie/src/vector/vpathmesure.h | /*
* Copyright (c) 2020 Samsung Electronics Co., Ltd. All rights reserved.
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#ifndef VPATHMESURE_H
#define VPATHMESURE_H
#include "vpath.h"
V_BEGIN_NAMESPACE
class VPathMesure {
public:
void setRange(float start, float end) {mStart = start; mEnd = end;}
void setStart(float start){mStart = start;}
void setEnd(float end){mEnd = end;}
VPath trim(const VPath &path);
private:
float mStart{0.0f};
float mEnd{1.0f};
VPath mScratchObject;
};
V_END_NAMESPACE
#endif // VPATHMESURE_H
| 1,586 | vpathmesure | h | en | c | code | {"qsc_code_num_words": 232, "qsc_code_num_chars": 1586.0, "qsc_code_mean_word_length": 5.07327586, "qsc_code_frac_words_unique": 0.54741379, "qsc_code_frac_chars_top_2grams": 0.07476636, "qsc_code_frac_chars_top_3grams": 0.02209006, "qsc_code_frac_chars_top_4grams": 0.0, "qsc_code_frac_chars_dupe_5grams": 0.0, "qsc_code_frac_chars_dupe_6grams": 0.0, "qsc_code_frac_chars_dupe_7grams": 0.0, "qsc_code_frac_chars_dupe_8grams": 0.0, "qsc_code_frac_chars_dupe_9grams": 0.0, "qsc_code_frac_chars_dupe_10grams": 0.0, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.00619675, "qsc_code_frac_chars_whitespace": 0.18600252, "qsc_code_size_file_byte": 1586.0, "qsc_code_num_lines": 44.0, "qsc_code_num_chars_line_max": 82.0, "qsc_code_num_chars_line_mean": 36.04545455, "qsc_code_frac_chars_alphabet": 0.90549961, "qsc_code_frac_chars_comments": 0.73455233, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.0, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.01662708, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codec_frac_lines_func_ratio": 0.23529412, "qsc_codec_cate_bitsstdc": 0.0, "qsc_codec_nums_lines_main": 0, "qsc_codec_frac_lines_goto": 0.0, "qsc_codec_cate_var_zero": 0.0, "qsc_codec_score_lines_no_logic": 0.35294118, "qsc_codec_frac_lines_print": 0.0, "qsc_codec_frac_lines_preprocessor_directives": null} | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codec_frac_lines_func_ratio": 1, "qsc_codec_nums_lines_main": 0, "qsc_codec_score_lines_no_logic": 0, "qsc_codec_frac_lines_preprocessor_directives": 0, "qsc_codec_frac_lines_print": 0} |
0015/esp_rlottie | rlottie/src/vector/vbezier.h | /*
* Copyright (c) 2020 Samsung Electronics Co., Ltd. All rights reserved.
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#ifndef VBEZIER_H
#define VBEZIER_H
#include <vpoint.h>
V_BEGIN_NAMESPACE
class VBezier {
public:
VBezier() = default;
VPointF pointAt(float t) const;
float angleAt(float t) const;
VBezier onInterval(float t0, float t1) const;
float length() const;
static void coefficients(float t, float &a, float &b, float &c, float &d);
static VBezier fromPoints(const VPointF &start, const VPointF &cp1,
const VPointF &cp2, const VPointF &end);
inline void parameterSplitLeft(float t, VBezier *left);
inline void split(VBezier *firstHalf, VBezier *secondHalf) const;
float tAtLength(float len) const { return tAtLength(len , length());}
float tAtLength(float len, float totalLength) const;
void splitAtLength(float len, VBezier *left, VBezier *right);
VPointF pt1() const { return {x1, y1}; }
VPointF pt2() const { return {x2, y2}; }
VPointF pt3() const { return {x3, y3}; }
VPointF pt4() const { return {x4, y4}; }
private:
VPointF derivative(float t) const;
float x1, y1, x2, y2, x3, y3, x4, y4;
};
inline void VBezier::coefficients(float t, float &a, float &b, float &c,
float &d)
{
float m_t = 1.0f - t;
b = m_t * m_t;
c = t * t;
d = c * t;
a = b * m_t;
b *= 3.0f * t;
c *= 3.0f * m_t;
}
inline VPointF VBezier::pointAt(float t) const
{
// numerically more stable:
float x, y;
float m_t = 1.0f - t;
{
float a = x1 * m_t + x2 * t;
float b = x2 * m_t + x3 * t;
float c = x3 * m_t + x4 * t;
a = a * m_t + b * t;
b = b * m_t + c * t;
x = a * m_t + b * t;
}
{
float a = y1 * m_t + y2 * t;
float b = y2 * m_t + y3 * t;
float c = y3 * m_t + y4 * t;
a = a * m_t + b * t;
b = b * m_t + c * t;
y = a * m_t + b * t;
}
return {x, y};
}
inline void VBezier::parameterSplitLeft(float t, VBezier *left)
{
left->x1 = x1;
left->y1 = y1;
left->x2 = x1 + t * (x2 - x1);
left->y2 = y1 + t * (y2 - y1);
left->x3 = x2 + t * (x3 - x2); // temporary holding spot
left->y3 = y2 + t * (y3 - y2); // temporary holding spot
x3 = x3 + t * (x4 - x3);
y3 = y3 + t * (y4 - y3);
x2 = left->x3 + t * (x3 - left->x3);
y2 = left->y3 + t * (y3 - left->y3);
left->x3 = left->x2 + t * (left->x3 - left->x2);
left->y3 = left->y2 + t * (left->y3 - left->y2);
left->x4 = x1 = left->x3 + t * (x2 - left->x3);
left->y4 = y1 = left->y3 + t * (y2 - left->y3);
}
inline void VBezier::split(VBezier *firstHalf, VBezier *secondHalf) const
{
float c = (x2 + x3) * 0.5f;
firstHalf->x2 = (x1 + x2) * 0.5f;
secondHalf->x3 = (x3 + x4) * 0.5f;
firstHalf->x1 = x1;
secondHalf->x4 = x4;
firstHalf->x3 = (firstHalf->x2 + c) * 0.5f;
secondHalf->x2 = (secondHalf->x3 + c) * 0.5f;
firstHalf->x4 = secondHalf->x1 = (firstHalf->x3 + secondHalf->x2) * 0.5f;
c = (y2 + y3) / 2;
firstHalf->y2 = (y1 + y2) * 0.5f;
secondHalf->y3 = (y3 + y4) * 0.5f;
firstHalf->y1 = y1;
secondHalf->y4 = y4;
firstHalf->y3 = (firstHalf->y2 + c) * 0.5f;
secondHalf->y2 = (secondHalf->y3 + c) * 0.5f;
firstHalf->y4 = secondHalf->y1 = (firstHalf->y3 + secondHalf->y2) * 0.5f;
}
V_END_NAMESPACE
#endif // VBEZIER_H
| 4,584 | vbezier | h | en | c | code | {"qsc_code_num_words": 673, "qsc_code_num_chars": 4584.0, "qsc_code_mean_word_length": 3.92867756, "qsc_code_frac_words_unique": 0.25557207, "qsc_code_frac_chars_top_2grams": 0.01361573, "qsc_code_frac_chars_top_3grams": 0.00567322, "qsc_code_frac_chars_top_4grams": 0.00605144, "qsc_code_frac_chars_dupe_5grams": 0.11649017, "qsc_code_frac_chars_dupe_6grams": 0.08623298, "qsc_code_frac_chars_dupe_7grams": 0.07791225, "qsc_code_frac_chars_dupe_8grams": 0.04160363, "qsc_code_frac_chars_dupe_9grams": 0.04160363, "qsc_code_frac_chars_dupe_10grams": 0.04160363, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.05033557, "qsc_code_frac_chars_whitespace": 0.28490401, "qsc_code_size_file_byte": 4584.0, "qsc_code_num_lines": 139.0, "qsc_code_num_chars_line_max": 83.0, "qsc_code_num_chars_line_mean": 32.97841727, "qsc_code_frac_chars_alphabet": 0.75625381, "qsc_code_frac_chars_comments": 0.27072426, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.06185567, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.0, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codec_frac_lines_func_ratio": 0.17525773, "qsc_codec_cate_bitsstdc": 0.0, "qsc_codec_nums_lines_main": 0, "qsc_codec_frac_lines_goto": 0.0, "qsc_codec_cate_var_zero": 0.0, "qsc_codec_score_lines_no_logic": 0.19587629, "qsc_codec_frac_lines_print": 0.0, "qsc_codec_frac_lines_preprocessor_directives": null} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codec_frac_lines_func_ratio": 0, "qsc_codec_nums_lines_main": 0, "qsc_codec_score_lines_no_logic": 0, "qsc_codec_frac_lines_preprocessor_directives": 0, "qsc_codec_frac_lines_print": 0} |
0015/esp_rlottie | rlottie/src/vector/vcowptr.h | /*
* Copyright (c) 2020 Samsung Electronics Co., Ltd. All rights reserved.
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#ifndef VCOWPTR_H
#define VCOWPTR_H
#include <cassert>
#include <atomic>
template <typename T>
class vcow_ptr {
struct model {
std::atomic<std::size_t> mRef{1};
model() = default;
template <class... Args>
explicit model(Args&&... args) : mValue(std::forward<Args>(args)...){}
explicit model(const T& other) : mValue(other){}
T mValue;
};
model* mModel;
public:
using element_type = T;
vcow_ptr()
{
static model default_s;
mModel = &default_s;
++mModel->mRef;
}
~vcow_ptr()
{
if (mModel && (--mModel->mRef == 0)) delete mModel;
}
template <class... Args>
explicit vcow_ptr(Args&&... args) : mModel(new model(std::forward<Args>(args)...))
{
}
vcow_ptr(const vcow_ptr& x) noexcept : mModel(x.mModel)
{
assert(mModel);
++mModel->mRef;
}
vcow_ptr(vcow_ptr&& x) noexcept : mModel(x.mModel)
{
assert(mModel);
x.mModel = nullptr;
}
auto operator=(const vcow_ptr& x) noexcept -> vcow_ptr&
{
*this = vcow_ptr(x);
return *this;
}
auto operator=(vcow_ptr&& x) noexcept -> vcow_ptr&
{
auto tmp = std::move(x);
swap(*this, tmp);
return *this;
}
auto operator*() const noexcept -> const element_type& { return read(); }
auto operator-> () const noexcept -> const element_type* { return &read(); }
std::size_t refCount() const noexcept
{
assert(mModel);
return mModel->mRef;
}
bool unique() const noexcept
{
assert(mModel);
return mModel->mRef == 1;
}
auto write() -> element_type&
{
if (!unique()) *this = vcow_ptr(read());
return mModel->mValue;
}
auto read() const noexcept -> const element_type&
{
assert(mModel);
return mModel->mValue;
}
friend inline void swap(vcow_ptr& x, vcow_ptr& y) noexcept
{
std::swap(x.mModel, y.mModel);
}
};
#endif // VCOWPTR_H
| 3,215 | vcowptr | h | en | c | code | {"qsc_code_num_words": 408, "qsc_code_num_chars": 3215.0, "qsc_code_mean_word_length": 4.85784314, "qsc_code_frac_words_unique": 0.37745098, "qsc_code_frac_chars_top_2grams": 0.05650858, "qsc_code_frac_chars_top_3grams": 0.02421796, "qsc_code_frac_chars_top_4grams": 0.03229062, "qsc_code_frac_chars_dupe_5grams": 0.17709384, "qsc_code_frac_chars_dupe_6grams": 0.15741675, "qsc_code_frac_chars_dupe_7grams": 0.13420787, "qsc_code_frac_chars_dupe_8grams": 0.09283552, "qsc_code_frac_chars_dupe_9grams": 0.09283552, "qsc_code_frac_chars_dupe_10grams": 0.0, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.00295359, "qsc_code_frac_chars_whitespace": 0.26283048, "qsc_code_size_file_byte": 3215.0, "qsc_code_num_lines": 126.0, "qsc_code_num_chars_line_max": 87.0, "qsc_code_num_chars_line_mean": 25.51587302, "qsc_code_frac_chars_alphabet": 0.83333333, "qsc_code_frac_chars_comments": 0.36111975, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.1875, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.0, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.075, "qsc_codec_frac_lines_func_ratio": 0.125, "qsc_codec_cate_bitsstdc": 0.0, "qsc_codec_nums_lines_main": 0, "qsc_codec_frac_lines_goto": 0.0, "qsc_codec_cate_var_zero": 0.0, "qsc_codec_score_lines_no_logic": 0.1625, "qsc_codec_frac_lines_print": 0.0, "qsc_codec_frac_lines_preprocessor_directives": null} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codec_frac_lines_func_ratio": 0, "qsc_codec_nums_lines_main": 0, "qsc_codec_score_lines_no_logic": 0, "qsc_codec_frac_lines_preprocessor_directives": 0, "qsc_codec_frac_lines_print": 0} |
0015/T-Glass-Applications | image_capture_app/main/t_glass.c | #include "t_glass.h"
#include "touch_element/touch_button.h"
#include "battery_measurement.h"
#include "esp_timer.h" // For getting timestamps
#include "esp_log.h"
#include <string.h>
#define TOUCH_BUTTON_NUM 1
#define DOUBLE_TAP_THRESHOLD_MS 300 // Define a threshold for double-tap detection (e.g., 300 ms)
#define TAG "[Glass Panel]"
// Define the variables
lv_obj_t *base_ui = NULL;
lv_timer_t *base_timer = NULL;
lv_color_t font_color;
lv_color_t bg_color;
bool time_colon_state;
lv_obj_t *time_hh;
lv_obj_t *time_mm;
lv_obj_t *time_colon;
lv_obj_t *date_label;
lv_obj_t *battery_label;
lv_obj_t *ble_label;
static lv_obj_t *canvas;
static lv_color_t *canvas_buf;
static lv_image_dsc_t img_dsc;
static bool first_press = true;
static int64_t last_call_time = 0; // Stores the timestamp of the last call
bool can_execute_function()
{
int64_t current_time = esp_timer_get_time(); // Get the current time in microseconds
if ((current_time - last_call_time) >= 500000) // Check if 0.5 second (500,000 µs) has passed
{
last_call_time = current_time; // Update the last call time
return true; // Function can be executed
}
return false; // Function should not be executed
}
/* Touch buttons handle */
static touch_button_handle_t button_handle[TOUCH_BUTTON_NUM];
/* Touch buttons channel array */
static const touch_pad_t channel_array[TOUCH_BUTTON_NUM] = {
TOUCH_PAD_NUM14,
};
/* Touch buttons channel sensitivity array */
static const float channel_sens_array[TOUCH_BUTTON_NUM] = {
0.02F,
};
esp_lcd_panel_io_handle_t io_handle = NULL;
esp_lcd_panel_handle_t panel_handle = NULL;
esp_err_t initialize_spi_bus()
{
ESP_LOGI(TAG, "Initialize SPI bus");
spi_bus_config_t buscfg = {
.sclk_io_num = BOARD_DISP_SCK,
.mosi_io_num = BOARD_DISP_MOSI,
.miso_io_num = BOARD_DISP_MISO,
.quadwp_io_num = BOARD_NONE_PIN,
.quadhd_io_num = BOARD_NONE_PIN,
//.max_transfer_sz = JD9613_HEIGHT * 80 * sizeof(uint16_t),
.max_transfer_sz = JD9613_WIDTH * JD9613_HEIGHT * 2,
.data4_io_num = 0,
.data5_io_num = 0,
.data6_io_num = 0,
.data7_io_num = 0,
.flags = 0x00,
.intr_flags = 0x00,
.isr_cpu_id = ESP_INTR_CPU_AFFINITY_AUTO,
};
return spi_bus_initialize(BOARD_DISP_HOST, &buscfg, SPI_DMA_CH_AUTO);
}
esp_err_t initialize_panel_io()
{
ESP_LOGI(TAG, "Install panel IO");
esp_lcd_panel_io_spi_config_t io_config = {
.dc_gpio_num = BOARD_DISP_DC,
.cs_gpio_num = BOARD_DISP_CS,
.pclk_hz = DEFAULT_SCK_SPEED,
.lcd_cmd_bits = 8,
.lcd_param_bits = 8,
.spi_mode = 0,
.trans_queue_depth = 10,
.on_color_trans_done = NULL,
.user_ctx = NULL,
.flags.dc_low_on_data = 0,
.flags.octal_mode = 0,
.flags.lsb_first = 0,
.flags.quad_mode = 0,
.flags.sio_mode = 0,
.flags.cs_high_active = 0};
// Attach the LCD to the SPI bus
return esp_lcd_new_panel_io_spi((esp_lcd_spi_bus_handle_t)BOARD_DISP_HOST, &io_config, &io_handle);
}
esp_err_t initialize_panel_jd9613()
{
ESP_ERROR_CHECK(initialize_spi_bus());
ESP_ERROR_CHECK(initialize_panel_io());
esp_lcd_panel_dev_config_t panel_config = {
.reset_gpio_num = BOARD_DISP_RST,
.rgb_ele_order = LCD_RGB_ELEMENT_ORDER_RGB,
.bits_per_pixel = 16,
.flags.reset_active_high = 0,
.vendor_config = NULL};
ESP_ERROR_CHECK(esp_lcd_new_panel_jd9613(io_handle, &panel_config, &panel_handle));
ESP_ERROR_CHECK(esp_lcd_panel_reset(panel_handle));
ESP_ERROR_CHECK(esp_lcd_panel_init(panel_handle));
setBrightness(panel_handle, 255);
/* Add LCD screen */
ESP_LOGI(TAG, "Add LCD screen");
const lvgl_port_display_cfg_t disp_cfg = {
.io_handle = io_handle,
.panel_handle = panel_handle,
.buffer_size = JD9613_WIDTH * JD9613_HEIGHT,
.double_buffer = false,
.hres = JD9613_WIDTH,
.vres = JD9613_HEIGHT,
.monochrome = false,
.rotation = {
.swap_xy = false,
.mirror_x = false,
.mirror_y = false,
},
.flags = {
.buff_dma = false,
.buff_spiram = false,
.sw_rotate = true,
.swap_bytes = false,
.full_refresh = true,
.direct_mode = false,
}};
const lvgl_port_cfg_t lvgl_cfg = ESP_LVGL_PORT_INIT_CONFIG();
ESP_ERROR_CHECK(lvgl_port_init(&lvgl_cfg));
lv_display_t *disp = lvgl_port_add_disp(&disp_cfg);
if (disp)
{
return ESP_OK;
}
ESP_LOGE(TAG, "[Err] LVGL Display is not setup properly");
return ESP_FAIL;
}
/* Button callback routine */
static void button_handler(touch_button_handle_t out_handle, touch_button_message_t *out_message, void *arg)
{
(void)out_handle; // Unused
static bool single_button_press = false;
if (out_message->event == TOUCH_BUTTON_EVT_ON_PRESS)
{
ESP_LOGI(TAG, "Button[%d] Press", (int)arg);
single_button_press = true;
}
else if (out_message->event == TOUCH_BUTTON_EVT_ON_RELEASE)
{
ESP_LOGI(TAG, "Button[%d] Release", (int)arg);
if (single_button_press)
{
if (first_press)
{
// On the first button press, go to the last tile
}
else
{
// On subsequent presses, go to the next tile and remove the previous one
}
}
}
else if (out_message->event == TOUCH_BUTTON_EVT_ON_LONGPRESS)
{
ESP_LOGI(TAG, "Button[%d] LongPress", (int)arg);
single_button_press = false;
}
}
esp_err_t initialize_touch_pad()
{
ESP_LOGI(TAG, "Creating button\n");
/* Initialize Touch Element library */
touch_elem_global_config_t global_config = TOUCH_ELEM_GLOBAL_DEFAULT_CONFIG();
ESP_ERROR_CHECK(touch_element_install(&global_config));
ESP_LOGI(TAG, "Touch element library installed");
touch_button_global_config_t button_global_config = TOUCH_BUTTON_GLOBAL_DEFAULT_CONFIG();
ESP_ERROR_CHECK(touch_button_install(&button_global_config));
ESP_LOGI(TAG, "Touch button installed");
for (int i = 0; i < TOUCH_BUTTON_NUM; i++)
{
touch_button_config_t button_config = {
.channel_num = channel_array[i],
.channel_sens = channel_sens_array[i]};
/* Create Touch buttons */
ESP_ERROR_CHECK(touch_button_create(&button_config, &button_handle[i]));
/* Subscribe touch button events (On Press, On Release, On LongPress) */
ESP_ERROR_CHECK(touch_button_subscribe_event(button_handle[i],
TOUCH_ELEM_EVENT_ON_PRESS | TOUCH_ELEM_EVENT_ON_RELEASE | TOUCH_ELEM_EVENT_ON_LONGPRESS,
(void *)channel_array[i]));
/* Set EVENT as the dispatch method */
ESP_ERROR_CHECK(touch_button_set_dispatch_method(button_handle[i], TOUCH_ELEM_DISP_CALLBACK));
/* Register a handler function to handle event messages */
ESP_ERROR_CHECK(touch_button_set_callback(button_handle[i], button_handler));
/* Set LongPress event trigger threshold time */
ESP_ERROR_CHECK(touch_button_set_longpress(button_handle[i], 1000));
}
return touch_element_start();
}
esp_err_t initialize_battery_measurement()
{
return battery_measurement_init();
}
void base_view(lv_obj_t *parent)
{
lvgl_port_lock(0);
lv_obj_set_scroll_dir(parent, LV_DIR_NONE);
// TIME
lv_obj_t *base_tile = lv_obj_create(parent);
lv_obj_set_size(base_tile, LV_PCT(100), LV_PCT(22));
lv_obj_set_style_bg_color(base_tile, bg_color, 0);
lv_obj_set_style_border_width(base_tile, 0, 0);
lv_obj_set_scrollbar_mode(base_tile, LV_SCROLLBAR_MODE_OFF);
lv_obj_set_scroll_dir(base_tile, LV_DIR_NONE);
battery_label = lv_label_create(base_tile);
lv_obj_set_style_text_color(battery_label, font_color, 0);
lv_obj_align(battery_label, LV_ALIGN_TOP_RIGHT, 0, 0);
lv_obj_set_style_text_font(battery_label, &lv_font_montserrat_10, 0);
ble_label = lv_label_create(base_tile);
lv_obj_set_style_text_color(ble_label, font_color, 0);
lv_label_set_text(ble_label, LV_SYMBOL_BLUETOOTH);
lv_obj_align(ble_label, LV_ALIGN_TOP_LEFT, 0, 0);
lv_obj_set_style_text_font(ble_label, &lv_font_montserrat_10, 0);
lvgl_port_unlock();
}
const char *get_battery_icon(float voltage)
{
if (voltage >= 4.0)
{
return LV_SYMBOL_BATTERY_FULL; // Full battery
}
else if (voltage >= 3.85)
{
return LV_SYMBOL_BATTERY_3; // 3 bars
}
else if (voltage >= 3.70)
{
return LV_SYMBOL_BATTERY_2; // 2 bars
}
else if (voltage >= 3.50)
{
return LV_SYMBOL_BATTERY_1; // 1 bar
}
else
{
return LV_SYMBOL_BATTERY_EMPTY; // Empty battery
}
}
void sys_timer_fn(lv_timer_t *timer)
{
lvgl_port_lock(0);
float battery_voltage = battery_measurement_read();
// Convert voltage to percentage
int battery_percentage = battery_voltage_to_percentage(battery_voltage);
// ESP_LOGI(TAG, "Battery Voltage: %.2f V, Battery Percentage: %d%%\n", battery_voltage, battery_percentage);
char battery_info[100];
snprintf(battery_info, sizeof(battery_info), "%.2fV, %d%% %s", battery_voltage, battery_percentage, get_battery_icon(battery_voltage));
lv_label_set_text(battery_label, battery_info);
lvgl_port_unlock();
}
void create_lv_canvas(lv_obj_t *parent)
{
// Allocate buffer in PSRAM for RGB565 format
canvas_buf = (lv_color_t *)heap_caps_malloc(GlassViewableWidth * GlassViewableHeight * sizeof(lv_color_t), MALLOC_CAP_SPIRAM);
if (!canvas_buf)
{
ESP_LOGE(TAG, "[Err] Failed to allocate canvas buffer\n");
return;
}
img_dsc.header.cf = LV_COLOR_FORMAT_RGB565;
img_dsc.header.w = GlassViewableWidth;
img_dsc.header.h = GlassViewableHeight;
img_dsc.data = (const uint8_t *)canvas_buf;
img_dsc.data_size = GlassViewableWidth * GlassViewableHeight * sizeof(lv_color_t);
// Create LVGL canvas
canvas = lv_image_create(parent);
lv_image_set_src(canvas, &img_dsc);
lv_obj_align(canvas, LV_ALIGN_CENTER, 0, 0);
}
esp_err_t init_tglass()
{
if (initialize_panel_jd9613() != ESP_OK)
{
ESP_LOGE(TAG, "[Err] JD9613 panel driver setup failed");
return ESP_FAIL;
}
if (initialize_battery_measurement() != ESP_OK)
{
ESP_LOGE(TAG, "[Err] Battery Measurement setup failed");
return ESP_FAIL;
}
if (initialize_touch_pad() != ESP_OK)
{
ESP_LOGE(TAG, "[Err] Touch pad setup failed");
return ESP_FAIL;
}
lvgl_port_lock(0);
font_color = lv_color_white();
bg_color = lv_color_black();
// Create a display base object
base_ui = lv_tileview_create(lv_screen_active());
lv_obj_clear_flag(base_ui, LV_OBJ_FLAG_SCROLLABLE);
lv_obj_set_style_bg_color(base_ui, lv_color_black(), 0);
lv_obj_set_style_text_color(base_ui, lv_color_hex(0xffffff), LV_PART_MAIN);
lv_obj_set_style_border_width(base_ui, 0, 0);
// lv_obj_set_pos(base_ui, 0, GlassViewable_X_Offset);
lv_obj_set_size(base_ui, GlassViewableWidth, GlassViewableHeight);
lv_obj_align(base_ui, LV_ALIGN_BOTTOM_MID, 0, 0);
create_lv_canvas(base_ui);
base_view(base_ui);
base_timer = lv_timer_create(sys_timer_fn, 1000, NULL);
lvgl_port_unlock();
return ESP_OK;
}
void lv_gui_ble_status(bool isOn)
{
lvgl_port_lock(0);
lv_obj_set_style_text_color(ble_label, isOn ? lv_palette_main(LV_PALETTE_BLUE) : font_color, 0);
lvgl_port_unlock();
}
void update_canvas_with_rgb565(uint8_t *data, size_t len)
{
if (!canvas_buf)
return;
lvgl_port_lock(0);
memcpy(canvas_buf, data, len); // Copy BLE image data into the buffer
// Update the image descriptor with new data
img_dsc.data = (const uint8_t *)canvas_buf;
// Refresh LVGL object
lv_obj_invalidate(canvas);
lvgl_port_unlock();
} | 12,194 | t_glass | c | en | c | code | {"qsc_code_num_words": 1743, "qsc_code_num_chars": 12194.0, "qsc_code_mean_word_length": 4.30636833, "qsc_code_frac_words_unique": 0.20367183, "qsc_code_frac_chars_top_2grams": 0.02331468, "qsc_code_frac_chars_top_3grams": 0.01705302, "qsc_code_frac_chars_top_4grams": 0.01731948, "qsc_code_frac_chars_dupe_5grams": 0.21302958, "qsc_code_frac_chars_dupe_6grams": 0.14401812, "qsc_code_frac_chars_dupe_7grams": 0.09645617, "qsc_code_frac_chars_dupe_8grams": 0.05555556, "qsc_code_frac_chars_dupe_9grams": 0.02264855, "qsc_code_frac_chars_dupe_10grams": 0.01278977, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.01998097, "qsc_code_frac_chars_whitespace": 0.22429063, "qsc_code_size_file_byte": 12194.0, "qsc_code_num_lines": 395.0, "qsc_code_num_chars_line_max": 142.0, "qsc_code_num_chars_line_mean": 30.87088608, "qsc_code_frac_chars_alphabet": 0.773549, "qsc_code_frac_chars_comments": 0.12030507, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.09121622, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.04297166, "qsc_code_frac_chars_long_word_length": 0.00456749, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.00149142, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codec_frac_lines_func_ratio": 0.06756757, "qsc_codec_cate_bitsstdc": 0.0, "qsc_codec_nums_lines_main": 0, "qsc_codec_frac_lines_goto": 0.0, "qsc_codec_cate_var_zero": 0.0, "qsc_codec_score_lines_no_logic": 0.11824324, "qsc_codec_frac_lines_print": 0.00337838, "qsc_codec_frac_lines_preprocessor_directives": 0.02702703} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codec_frac_lines_func_ratio": 0, "qsc_codec_nums_lines_main": 0, "qsc_codec_score_lines_no_logic": 0, "qsc_codec_frac_lines_preprocessor_directives": 0, "qsc_codec_frac_lines_print": 0} |
0015/T-Glass-Applications | image_capture_app/main/jd9613.c | #include "esp_check.h"
#include "esp_lcd_panel_interface.h"
#include "esp_lcd_panel_io.h"
#include "esp_lcd_panel_vendor.h"
#include "esp_lcd_panel_ops.h"
#include "esp_lcd_panel_commands.h"
#include "driver/gpio.h"
#include "jd9613.h"
#define TAG "jd9613"
typedef struct
{
esp_lcd_panel_t base;
esp_lcd_panel_io_handle_t io;
int reset_gpio_num;
bool reset_level;
uint8_t rotation;
uint16_t *frame_buffer;
uint16_t width;
uint16_t height;
bool flipHorizontal;
} jd9613_panel_t;
// There is only 1/2 RAM inside the JD9613 screen, and it cannot be rotated in directions 1 and 3.
esp_err_t panel_jd9613_set_rotation(esp_lcd_panel_t *panel, uint8_t r)
{
jd9613_panel_t *jd9613 = __containerof(panel, jd9613_panel_t, base);
esp_lcd_panel_io_handle_t io = jd9613->io;
uint8_t write_data = 0x00;
switch (r)
{
case 1: // jd9613 only has 1/2RAM and cannot be rotated
// write_data = LCD_CMD_MX_BIT | LCD_CMD_MV_BIT | LCD_CMD_RGB;
// jd9613->width = JD9613_HEIGHT;
// jd9613->height = JD9613_WIDTH;
write_data = LCD_CMD_RGB;
jd9613->width = JD9613_WIDTH;
jd9613->height = JD9613_HEIGHT;
break;
case 2:
write_data = LCD_CMD_MY_BIT | LCD_CMD_MX_BIT | LCD_CMD_RGB;
jd9613->width = JD9613_WIDTH;
jd9613->height = JD9613_HEIGHT;
break;
case 3: // jd9613 only has 1/2RAM and cannot be rotated
// write_data = LCD_CMD_MY_BIT | LCD_CMD_MV_BIT | LCD_CMD_RGB;
// jd9613->width = JD9613_HEIGHT;
// jd9613->height = JD9613_WIDTH;
write_data = LCD_CMD_RGB;
jd9613->width = JD9613_WIDTH;
jd9613->height = JD9613_HEIGHT;
break;
default: // case 0:
write_data = LCD_CMD_RGB;
jd9613->width = JD9613_WIDTH;
jd9613->height = JD9613_HEIGHT;
break;
}
if (jd9613->flipHorizontal)
{
write_data |= (0x01 << 1); // Flip Horizontal
}
// write_data |= 0x01; //Flip Vertical
jd9613->rotation = r;
ESP_LOGI(TAG, "set_rotation:%d write reg :0x%X , data : 0x%X Width:%d Height:%d", r, LCD_CMD_MADCTL, write_data, jd9613->width, jd9613->height);
esp_lcd_panel_io_tx_param(io, LCD_CMD_MADCTL, &write_data, 1);
return ESP_OK;
}
static esp_err_t panel_jd9613_del(esp_lcd_panel_t *panel)
{
jd9613_panel_t *jd9613 = __containerof(panel, jd9613_panel_t, base);
if (jd9613->reset_gpio_num >= 0)
{
gpio_reset_pin(jd9613->reset_gpio_num);
}
ESP_LOGI(TAG, "del jd9613 panel @%p", jd9613);
free(jd9613->frame_buffer);
free(jd9613);
return ESP_OK;
}
static esp_err_t panel_jd9613_reset(esp_lcd_panel_t *panel)
{
jd9613_panel_t *jd9613 = __containerof(panel, jd9613_panel_t, base);
esp_lcd_panel_io_handle_t io = jd9613->io;
// perform hardware reset
if (jd9613->reset_gpio_num >= 0)
{
gpio_set_level(jd9613->reset_gpio_num, jd9613->reset_level);
vTaskDelay(pdMS_TO_TICKS(10));
gpio_set_level(jd9613->reset_gpio_num, !jd9613->reset_level);
vTaskDelay(pdMS_TO_TICKS(10));
}
else
{ // perform software reset
ESP_RETURN_ON_ERROR(esp_lcd_panel_io_tx_param(io, LCD_CMD_SWRESET, NULL, 0), TAG, "send command failed");
vTaskDelay(pdMS_TO_TICKS(20)); // spec, wait at least 5ms before sending new command
}
return ESP_OK;
}
static esp_err_t panel_jd9613_init(esp_lcd_panel_t *panel)
{
jd9613_panel_t *jd9613 = __containerof(panel, jd9613_panel_t, base);
esp_lcd_panel_io_handle_t io = jd9613->io;
// vendor specific initialization, it can be different between manufacturers
// should consult the LCD supplier for initialization sequence code
int cmd = 0;
while (jd9613_cmd[cmd].len != 0xff)
{
esp_lcd_panel_io_tx_param(io, jd9613_cmd[cmd].addr, jd9613_cmd[cmd].param, (jd9613_cmd[cmd].len - 1) & 0x1F);
cmd++;
}
jd9613->flipHorizontal = 0;
jd9613->rotation = 0;
panel_jd9613_set_rotation(panel, jd9613->rotation);
esp_lcd_panel_io_tx_param(io, LCD_CMD_SLPOUT, NULL, 0);
vTaskDelay(pdMS_TO_TICKS(120));
esp_lcd_panel_io_tx_param(io, LCD_CMD_DISPON, NULL, 0);
vTaskDelay(pdMS_TO_TICKS(120));
return ESP_OK;
}
void rgb565_swap(uint16_t *color_data, uint32_t width, uint32_t height)
{
uint32_t total_pixels = width * height;
uint32_t u32_cnt = total_pixels / 2;
uint16_t *buf16 = color_data;
uint32_t *buf32 = (uint32_t *)color_data;
while (u32_cnt >= 8)
{
buf32[0] = ((buf32[0] & 0xff00ff00) >> 8) | ((buf32[0] & 0x00ff00ff) << 8);
buf32[1] = ((buf32[1] & 0xff00ff00) >> 8) | ((buf32[1] & 0x00ff00ff) << 8);
buf32[2] = ((buf32[2] & 0xff00ff00) >> 8) | ((buf32[2] & 0x00ff00ff) << 8);
buf32[3] = ((buf32[3] & 0xff00ff00) >> 8) | ((buf32[3] & 0x00ff00ff) << 8);
buf32[4] = ((buf32[4] & 0xff00ff00) >> 8) | ((buf32[4] & 0x00ff00ff) << 8);
buf32[5] = ((buf32[5] & 0xff00ff00) >> 8) | ((buf32[5] & 0x00ff00ff) << 8);
buf32[6] = ((buf32[6] & 0xff00ff00) >> 8) | ((buf32[6] & 0x00ff00ff) << 8);
buf32[7] = ((buf32[7] & 0xff00ff00) >> 8) | ((buf32[7] & 0x00ff00ff) << 8);
buf32 += 8;
u32_cnt -= 8;
}
while (u32_cnt)
{
*buf32 = ((*buf32 & 0xff00ff00) >> 8) | ((*buf32 & 0x00ff00ff) << 8);
buf32++;
u32_cnt--;
}
if (total_pixels & 0x1)
{ // Odd pixel count, swap the last pixel separately
uint32_t e = total_pixels - 1;
buf16[e] = ((buf16[e] & 0xff00) >> 8) | ((buf16[e] & 0x00ff) << 8);
}
}
static esp_err_t panel_jd9613_draw_bitmap(esp_lcd_panel_t *panel, int x_start, int y_start, int x_end, int y_end, const void *color_data)
{
jd9613_panel_t *jd9613 = __containerof(panel, jd9613_panel_t, base);
assert((x_start < x_end) && (y_start < y_end) && "start position must be smaller than end position");
esp_lcd_panel_io_handle_t io = jd9613->io;
// Swap the 2 bytes of RGB565 color
// Cannot find a way to use it in ESP_LVGL_PORT
rgb565_swap((uint16_t *)color_data, x_end - x_start + 1, y_end - y_start + 1);
uint32_t width = x_start + x_end;
uint32_t height = y_start + y_end;
uint32_t _x = x_start,
_y = y_start,
_xe = width,
_ye = height;
size_t write_colors_bytes = width * height * sizeof(uint16_t);
uint16_t *data_ptr = (uint16_t *)color_data;
bool sw_rotation = false;
switch (jd9613->rotation)
{
case 1:
case 3:
sw_rotation = true;
break;
default:
sw_rotation = false;
break;
}
if (sw_rotation)
{
_x = JD9613_WIDTH - (y_start + height);
_y = x_start;
_xe = height;
_ye = width;
}
// Direction 2 requires offset pixels
if (jd9613->rotation == 2)
{
_x += 2;
_xe += 2;
}
// define an area of frame memory where MCU can access
ESP_RETURN_ON_ERROR(esp_lcd_panel_io_tx_param(io, LCD_CMD_CASET, (uint8_t[]){
(_x >> 8) & 0xFF,
_x & 0xFF,
((_xe - 1) >> 8) & 0xFF,
(_xe - 1) & 0xFF,
},
4),
TAG, "send command failed");
ESP_RETURN_ON_ERROR(esp_lcd_panel_io_tx_param(io, LCD_CMD_RASET, (uint8_t[]){
(_y >> 8) & 0xFF,
_y & 0xFF,
((_ye - 1) >> 8) & 0xFF,
(_ye - 1) & 0xFF,
},
4),
TAG, "send command failed");
if (sw_rotation)
{
int index = 0;
uint16_t *pdat = (uint16_t *)color_data;
for (uint16_t j = 0; j < width; j++)
{
for (uint16_t i = 0; i < height; i++)
{
jd9613->frame_buffer[index++] = pdat[width * (height - i - 1) + j];
}
}
data_ptr = jd9613->frame_buffer;
}
esp_lcd_panel_io_tx_color(io, LCD_CMD_RAMWR, data_ptr, write_colors_bytes);
return ESP_OK;
}
esp_err_t esp_lcd_new_panel_jd9613(const esp_lcd_panel_io_handle_t io, const esp_lcd_panel_dev_config_t *panel_dev_config, esp_lcd_panel_handle_t *ret_panel)
{
esp_err_t ret = ESP_OK;
jd9613_panel_t *jd9613 = NULL;
gpio_config_t io_conf = {0};
ESP_GOTO_ON_FALSE(io && panel_dev_config && ret_panel, ESP_ERR_INVALID_ARG, err, TAG, "invalid argument");
jd9613 = (jd9613_panel_t *)calloc(1, sizeof(jd9613_panel_t));
ESP_GOTO_ON_FALSE(jd9613, ESP_ERR_NO_MEM, err, TAG, "no mem for jd9613 panel");
jd9613->frame_buffer = (uint16_t *)heap_caps_malloc(JD9613_WIDTH * JD9613_HEIGHT * 2, MALLOC_CAP_DMA);
if (!jd9613->frame_buffer)
{
free(jd9613);
return ESP_FAIL;
}
if (panel_dev_config->reset_gpio_num >= 0)
{
io_conf.mode = GPIO_MODE_OUTPUT;
io_conf.pin_bit_mask = 1ULL << panel_dev_config->reset_gpio_num;
ESP_GOTO_ON_ERROR(gpio_config(&io_conf), err, TAG, "configure GPIO for RST line failed");
}
switch (panel_dev_config->bits_per_pixel)
{
case 16: // RGB565
// fb_bits_per_pixel = 16;
break;
default:
ESP_GOTO_ON_FALSE(false, ESP_ERR_NOT_SUPPORTED, err, TAG, "unsupported pixel width");
break;
}
jd9613->io = io;
// jd9613->fb_bits_per_pixel = fb_bits_per_pixel;
jd9613->reset_gpio_num = panel_dev_config->reset_gpio_num;
jd9613->reset_level = panel_dev_config->flags.reset_active_high;
jd9613->base.del = panel_jd9613_del;
jd9613->base.reset = panel_jd9613_reset;
jd9613->base.init = panel_jd9613_init;
jd9613->base.draw_bitmap = panel_jd9613_draw_bitmap;
jd9613->base.invert_color = NULL;
jd9613->base.set_gap = NULL;
jd9613->base.mirror = NULL;
jd9613->base.swap_xy = NULL;
jd9613->base.disp_on_off = NULL;
*ret_panel = &(jd9613->base);
ESP_LOGI(TAG, "new jd9613 panel @%p", jd9613);
return ESP_OK;
err:
if (jd9613)
{
if (panel_dev_config->reset_gpio_num >= 0)
{
gpio_reset_pin(panel_dev_config->reset_gpio_num);
}
free(jd9613);
}
return ret;
}
void flipHorizontal(esp_lcd_panel_t *panel, bool enable)
{
assert(panel);
jd9613_panel_t *jd9613 = __containerof(panel, jd9613_panel_t, base);
jd9613->flipHorizontal = enable;
panel_jd9613_set_rotation(panel, jd9613->rotation);
}
void writeCommand(esp_lcd_panel_t *panel, uint32_t cmd, uint8_t *pdat, uint32_t length)
{
jd9613_panel_t *jd9613 = __containerof(panel, jd9613_panel_t, base);
esp_lcd_panel_io_tx_param(jd9613->io, cmd, pdat, length);
}
void setBrightness(esp_lcd_panel_t *panel, uint8_t level)
{
lcd_cmd_t t = {0x51, {level}, 1};
writeCommand(panel, t.addr, t.param, t.len);
} | 11,454 | jd9613 | c | en | c | code | {"qsc_code_num_words": 1536, "qsc_code_num_chars": 11454.0, "qsc_code_mean_word_length": 4.0625, "qsc_code_frac_words_unique": 0.16471354, "qsc_code_frac_chars_top_2grams": 0.03076923, "qsc_code_frac_chars_top_3grams": 0.05464744, "qsc_code_frac_chars_top_4grams": 0.03333333, "qsc_code_frac_chars_dupe_5grams": 0.3911859, "qsc_code_frac_chars_dupe_6grams": 0.35673077, "qsc_code_frac_chars_dupe_7grams": 0.32772436, "qsc_code_frac_chars_dupe_8grams": 0.26137821, "qsc_code_frac_chars_dupe_9grams": 0.24759615, "qsc_code_frac_chars_dupe_10grams": 0.2125, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.11105621, "qsc_code_frac_chars_whitespace": 0.29326, "qsc_code_size_file_byte": 11454.0, "qsc_code_num_lines": 340.0, "qsc_code_num_chars_line_max": 158.0, "qsc_code_num_chars_line_mean": 33.68823529, "qsc_code_frac_chars_alphabet": 0.65978999, "qsc_code_frac_chars_comments": 0.09533787, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.21691176, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.00367647, "qsc_code_frac_chars_string_length": 0.04352022, "qsc_code_frac_chars_long_word_length": 0.0068513, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0238348, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.00735294, "qsc_codec_frac_lines_func_ratio": 0.04044118, "qsc_codec_cate_bitsstdc": 0.0, "qsc_codec_nums_lines_main": 0, "qsc_codec_frac_lines_goto": 0.0, "qsc_codec_cate_var_zero": 0.0, "qsc_codec_score_lines_no_logic": 0.11029412, "qsc_codec_frac_lines_print": 0.0, "qsc_codec_frac_lines_preprocessor_directives": 0.03676471} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codec_frac_lines_func_ratio": 0, "qsc_codec_nums_lines_main": 0, "qsc_codec_score_lines_no_logic": 0, "qsc_codec_frac_lines_preprocessor_directives": 0, "qsc_codec_frac_lines_print": 0} |
0015/T-Glass-Applications | image_capture_app/main/nvs_manager.c | #include "nvs_manager.h"
#include <esp_log.h>
#include <string.h>
#define TAG "[NVS Manager]"
esp_err_t nvs_manager_init(void)
{
esp_err_t err = nvs_flash_init();
if (err == ESP_ERR_NVS_NO_FREE_PAGES || err == ESP_ERR_NVS_NEW_VERSION_FOUND)
{
ESP_LOGW(TAG, "NVS partition truncated, erasing...");
ESP_ERROR_CHECK(nvs_flash_erase());
err = nvs_flash_init();
}
if (err == ESP_OK)
{
ESP_LOGI(TAG, "NVS initialized successfully.");
}
else
{
ESP_LOGE(TAG, "Failed to initialize NVS: %s", esp_err_to_name(err));
}
return err;
}
esp_err_t nvs_manager_store_string(const char *key, const char *value)
{
nvs_handle_t nvs_handle;
esp_err_t err = nvs_open(NVS_NAMESPACE, NVS_READWRITE, &nvs_handle);
if (err == ESP_OK)
{
err = nvs_set_str(nvs_handle, key, value);
if (err == ESP_OK)
{
nvs_commit(nvs_handle);
ESP_LOGI(TAG, "String stored successfully under key '%s'.", key);
}
else
{
ESP_LOGE(TAG, "Failed to store string under key '%s': %s", key, esp_err_to_name(err));
}
nvs_close(nvs_handle);
}
else
{
ESP_LOGE(TAG, "Failed to open NVS: %s", esp_err_to_name(err));
}
return err;
}
esp_err_t nvs_manager_get_string(const char *key, char *buffer, size_t buffer_size)
{
nvs_handle_t nvs_handle;
esp_err_t err = nvs_open(NVS_NAMESPACE, NVS_READONLY, &nvs_handle);
if (err == ESP_OK)
{
err = nvs_get_str(nvs_handle, key, buffer, &buffer_size);
if (err == ESP_OK)
{
ESP_LOGI(TAG, "String retrieved from NVS using key '%s'.", key);
}
else
{
ESP_LOGW(TAG, "String not found in NVS under key '%s': %s", key, esp_err_to_name(err));
}
nvs_close(nvs_handle);
}
else
{
ESP_LOGE(TAG, "Failed to open NVS: %s", esp_err_to_name(err));
}
return err;
}
esp_err_t nvs_manager_erase_key(const char *key)
{
nvs_handle_t nvs_handle;
esp_err_t err = nvs_open(NVS_NAMESPACE, NVS_READWRITE, &nvs_handle);
if (err == ESP_OK)
{
err = nvs_erase_key(nvs_handle, key);
if (err == ESP_OK)
{
nvs_commit(nvs_handle);
ESP_LOGI(TAG, "Key '%s' erased successfully.", key);
}
else
{
ESP_LOGE(TAG, "Failed to erase key '%s': %s", key, esp_err_to_name(err));
}
nvs_close(nvs_handle);
}
else
{
ESP_LOGE(TAG, "Failed to open NVS: %s", esp_err_to_name(err));
}
return err;
}
esp_err_t nvs_manager_erase_all(void)
{
esp_err_t err = nvs_flash_erase();
if (err == ESP_OK)
{
ESP_LOGI(TAG, "NVS partition erased successfully.");
}
else
{
ESP_LOGE(TAG, "Failed to erase NVS partition: %s", esp_err_to_name(err));
}
return err;
} | 2,931 | nvs_manager | c | en | c | code | {"qsc_code_num_words": 419, "qsc_code_num_chars": 2931.0, "qsc_code_mean_word_length": 3.76133652, "qsc_code_frac_words_unique": 0.1575179, "qsc_code_frac_chars_top_2grams": 0.07614213, "qsc_code_frac_chars_top_3grams": 0.04441624, "qsc_code_frac_chars_top_4grams": 0.05076142, "qsc_code_frac_chars_dupe_5grams": 0.66307107, "qsc_code_frac_chars_dupe_6grams": 0.64086294, "qsc_code_frac_chars_dupe_7grams": 0.64086294, "qsc_code_frac_chars_dupe_8grams": 0.50190355, "qsc_code_frac_chars_dupe_9grams": 0.44098985, "qsc_code_frac_chars_dupe_10grams": 0.44098985, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.0, "qsc_code_frac_chars_whitespace": 0.29136813, "qsc_code_size_file_byte": 2931.0, "qsc_code_num_lines": 114.0, "qsc_code_num_chars_line_max": 100.0, "qsc_code_num_chars_line_mean": 25.71052632, "qsc_code_frac_chars_alphabet": 0.75878671, "qsc_code_frac_chars_comments": 0.0, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.31775701, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.16166439, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codec_frac_lines_func_ratio": 0.04672897, "qsc_codec_cate_bitsstdc": 0.0, "qsc_codec_nums_lines_main": 0, "qsc_codec_frac_lines_goto": 0.0, "qsc_codec_cate_var_zero": 0.0, "qsc_codec_score_lines_no_logic": 0.12149533, "qsc_codec_frac_lines_print": 0.0, "qsc_codec_frac_lines_preprocessor_directives": 0.04672897} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codec_frac_lines_func_ratio": 0, "qsc_codec_nums_lines_main": 0, "qsc_codec_score_lines_no_logic": 0, "qsc_codec_frac_lines_preprocessor_directives": 0, "qsc_codec_frac_lines_print": 0} |
0015/esp_rlottie | rlottie/src/vector/vpath.h | /*
* Copyright (c) 2020 Samsung Electronics Co., Ltd. All rights reserved.
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#ifndef VPATH_H
#define VPATH_H
#include <vector>
#include "vcowptr.h"
#include "vmatrix.h"
#include "vpoint.h"
#include "vrect.h"
V_BEGIN_NAMESPACE
struct VPathData;
class VPath {
public:
enum class Direction { CCW, CW };
enum class Element : uint8_t { MoveTo, LineTo, CubicTo, Close };
bool empty() const;
bool null() const;
void moveTo(const VPointF &p);
void moveTo(float x, float y);
void lineTo(const VPointF &p);
void lineTo(float x, float y);
void cubicTo(const VPointF &c1, const VPointF &c2, const VPointF &e);
void cubicTo(float c1x, float c1y, float c2x, float c2y, float ex,
float ey);
void arcTo(const VRectF &rect, float startAngle, float sweepLength,
bool forceMoveTo);
void close();
void reset();
void reserve(size_t pts, size_t elms);
size_t segments() const;
void addCircle(float cx, float cy, float radius,
VPath::Direction dir = Direction::CW);
void addOval(const VRectF &rect, VPath::Direction dir = Direction::CW);
void addRoundRect(const VRectF &rect, float rx, float ry,
VPath::Direction dir = Direction::CW);
void addRoundRect(const VRectF &rect, float roundness,
VPath::Direction dir = Direction::CW);
void addRect(const VRectF &rect, VPath::Direction dir = Direction::CW);
void addPolystar(float points, float innerRadius, float outerRadius,
float innerRoundness, float outerRoundness,
float startAngle, float cx, float cy,
VPath::Direction dir = Direction::CW);
void addPolygon(float points, float radius, float roundness,
float startAngle, float cx, float cy,
VPath::Direction dir = Direction::CW);
void addPath(const VPath &path);
void addPath(const VPath &path, const VMatrix &m);
void transform(const VMatrix &m);
float length() const;
const std::vector<VPath::Element> &elements() const;
const std::vector<VPointF> & points() const;
void clone(const VPath &srcPath);
bool unique() const { return d.unique();}
size_t refCount() const { return d.refCount();}
private:
struct VPathData {
bool empty() const { return m_elements.empty(); }
bool null() const { return empty() && !m_elements.capacity();}
void moveTo(float x, float y);
void lineTo(float x, float y);
void cubicTo(float cx1, float cy1, float cx2, float cy2, float ex, float ey);
void close();
void reset();
void reserve(size_t, size_t);
void checkNewSegment();
size_t segments() const;
void transform(const VMatrix &m);
float length() const;
void addRoundRect(const VRectF &, float, float, VPath::Direction);
void addRoundRect(const VRectF &, float, VPath::Direction);
void addRect(const VRectF &, VPath::Direction);
void arcTo(const VRectF &, float, float, bool);
void addCircle(float, float, float, VPath::Direction);
void addOval(const VRectF &, VPath::Direction);
void addPolystar(float points, float innerRadius, float outerRadius,
float innerRoundness, float outerRoundness,
float startAngle, float cx, float cy,
VPath::Direction dir = Direction::CW);
void addPolygon(float points, float radius, float roundness,
float startAngle, float cx, float cy,
VPath::Direction dir = Direction::CW);
void addPath(const VPathData &path, const VMatrix *m = nullptr);
void clone(const VPath::VPathData &o) { *this = o;}
const std::vector<VPath::Element> &elements() const
{
return m_elements;
}
const std::vector<VPointF> &points() const { return m_points; }
std::vector<VPointF> m_points;
std::vector<VPath::Element> m_elements;
size_t m_segments;
VPointF mStartPoint;
mutable float mLength{0};
mutable bool mLengthDirty{true};
bool mNewSegment;
};
vcow_ptr<VPathData> d;
};
inline bool VPath::empty() const
{
return d->empty();
}
/*
* path is empty as well as null(no memory for data allocated yet).
*/
inline bool VPath::null() const
{
return d->null();
}
inline void VPath::moveTo(const VPointF &p)
{
d.write().moveTo(p.x(), p.y());
}
inline void VPath::lineTo(const VPointF &p)
{
d.write().lineTo(p.x(), p.y());
}
inline void VPath::close()
{
d.write().close();
}
inline void VPath::reset()
{
d.write().reset();
}
inline void VPath::reserve(size_t pts, size_t elms)
{
d.write().reserve(pts, elms);
}
inline size_t VPath::segments() const
{
return d->segments();
}
inline float VPath::length() const
{
return d->length();
}
inline void VPath::cubicTo(const VPointF &c1, const VPointF &c2,
const VPointF &e)
{
d.write().cubicTo(c1.x(), c1.y(), c2.x(), c2.y(), e.x(), e.y());
}
inline void VPath::lineTo(float x, float y)
{
d.write().lineTo(x, y);
}
inline void VPath::moveTo(float x, float y)
{
d.write().moveTo(x, y);
}
inline void VPath::cubicTo(float c1x, float c1y, float c2x, float c2y, float ex,
float ey)
{
d.write().cubicTo(c1x, c1y, c2x, c2y, ex, ey);
}
inline void VPath::transform(const VMatrix &m)
{
d.write().transform(m);
}
inline void VPath::arcTo(const VRectF &rect, float startAngle,
float sweepLength, bool forceMoveTo)
{
d.write().arcTo(rect, startAngle, sweepLength, forceMoveTo);
}
inline void VPath::addRect(const VRectF &rect, VPath::Direction dir)
{
d.write().addRect(rect, dir);
}
inline void VPath::addRoundRect(const VRectF &rect, float rx, float ry,
VPath::Direction dir)
{
d.write().addRoundRect(rect, rx, ry, dir);
}
inline void VPath::addRoundRect(const VRectF &rect, float roundness,
VPath::Direction dir)
{
d.write().addRoundRect(rect, roundness, dir);
}
inline void VPath::addCircle(float cx, float cy, float radius,
VPath::Direction dir)
{
d.write().addCircle(cx, cy, radius, dir);
}
inline void VPath::addOval(const VRectF &rect, VPath::Direction dir)
{
d.write().addOval(rect, dir);
}
inline void VPath::addPolystar(float points, float innerRadius,
float outerRadius, float innerRoundness,
float outerRoundness, float startAngle, float cx,
float cy, VPath::Direction dir)
{
d.write().addPolystar(points, innerRadius, outerRadius, innerRoundness,
outerRoundness, startAngle, cx, cy, dir);
}
inline void VPath::addPolygon(float points, float radius, float roundness,
float startAngle, float cx, float cy,
VPath::Direction dir)
{
d.write().addPolygon(points, radius, roundness, startAngle, cx, cy, dir);
}
inline void VPath::addPath(const VPath &path)
{
if (path.empty()) return;
if (null()) {
*this = path;
} else {
d.write().addPath(path.d.read());
}
}
inline void VPath::addPath(const VPath &path, const VMatrix &m)
{
if (path.empty()) return;
d.write().addPath(path.d.read(), &m);
}
inline const std::vector<VPath::Element> &VPath::elements() const
{
return d->elements();
}
inline const std::vector<VPointF> &VPath::points() const
{
return d->points();
}
inline void VPath::clone(const VPath &o)
{
d.write().clone(o.d.read());
}
V_END_NAMESPACE
#endif // VPATH_H
| 9,067 | vpath | h | en | c | code | {"qsc_code_num_words": 1117, "qsc_code_num_chars": 9067.0, "qsc_code_mean_word_length": 4.99552372, "qsc_code_frac_words_unique": 0.19516562, "qsc_code_frac_chars_top_2grams": 0.05268817, "qsc_code_frac_chars_top_3grams": 0.05645161, "qsc_code_frac_chars_top_4grams": 0.04193548, "qsc_code_frac_chars_dupe_5grams": 0.52150538, "qsc_code_frac_chars_dupe_6grams": 0.44982079, "qsc_code_frac_chars_dupe_7grams": 0.41863799, "qsc_code_frac_chars_dupe_8grams": 0.3483871, "qsc_code_frac_chars_dupe_9grams": 0.28727599, "qsc_code_frac_chars_dupe_10grams": 0.25537634, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.00451739, "qsc_code_frac_chars_whitespace": 0.26756369, "qsc_code_size_file_byte": 9067.0, "qsc_code_num_lines": 285.0, "qsc_code_num_chars_line_max": 87.0, "qsc_code_num_chars_line_mean": 31.81403509, "qsc_code_frac_chars_alphabet": 0.83571751, "qsc_code_frac_chars_comments": 0.13598765, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.17857143, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.00421241, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codec_frac_lines_func_ratio": 0.22321429, "qsc_codec_cate_bitsstdc": 0.0, "qsc_codec_nums_lines_main": 0, "qsc_codec_frac_lines_goto": 0.0, "qsc_codec_cate_var_zero": 0.0, "qsc_codec_score_lines_no_logic": 0.25892857, "qsc_codec_frac_lines_print": 0.0, "qsc_codec_frac_lines_preprocessor_directives": null} | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codec_frac_lines_func_ratio": 1, "qsc_codec_nums_lines_main": 0, "qsc_codec_score_lines_no_logic": 0, "qsc_codec_frac_lines_preprocessor_directives": 0, "qsc_codec_frac_lines_print": 0} |
0015/esp_rlottie | rlottie/src/vector/vrect.cpp | /*
* Copyright (c) 2020 Samsung Electronics Co., Ltd. All rights reserved.
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "vrect.h"
#include <algorithm>
VRect VRect::operator&(const VRect &r) const
{
if (empty()) return VRect();
int l1 = x1;
int r1 = x1;
if (x2 - x1 + 1 < 0)
l1 = x2;
else
r1 = x2;
int l2 = r.x1;
int r2 = r.x1;
if (r.x2 - r.x1 + 1 < 0)
l2 = r.x2;
else
r2 = r.x2;
if (l1 > r2 || l2 > r1) return VRect();
int t1 = y1;
int b1 = y1;
if (y2 - y1 + 1 < 0)
t1 = y2;
else
b1 = y2;
int t2 = r.y1;
int b2 = r.y1;
if (r.y2 - r.y1 + 1 < 0)
t2 = r.y2;
else
b2 = r.y2;
if (t1 > b2 || t2 > b1) return VRect();
VRect tmp;
tmp.x1 = std::max(l1, l2);
tmp.x2 = std::min(r1, r2);
tmp.y1 = std::max(t1, t2);
tmp.y2 = std::min(b1, b2);
return tmp;
}
| 1,955 | vrect | cpp | en | cpp | code | {"qsc_code_num_words": 307, "qsc_code_num_chars": 1955.0, "qsc_code_mean_word_length": 4.0, "qsc_code_frac_words_unique": 0.41693811, "qsc_code_frac_chars_top_2grams": 0.07166124, "qsc_code_frac_chars_top_3grams": 0.02117264, "qsc_code_frac_chars_top_4grams": 0.0, "qsc_code_frac_chars_dupe_5grams": 0.0, "qsc_code_frac_chars_dupe_6grams": 0.0, "qsc_code_frac_chars_dupe_7grams": 0.0, "qsc_code_frac_chars_dupe_8grams": 0.0, "qsc_code_frac_chars_dupe_9grams": 0.0, "qsc_code_frac_chars_dupe_10grams": 0.0, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.05052632, "qsc_code_frac_chars_whitespace": 0.27109974, "qsc_code_size_file_byte": 1955.0, "qsc_code_num_lines": 68.0, "qsc_code_num_chars_line_max": 82.0, "qsc_code_num_chars_line_mean": 28.75, "qsc_code_frac_chars_alphabet": 0.81122807, "qsc_code_frac_chars_comments": 0.58721228, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.10526316, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.0086741, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codecpp_frac_lines_preprocessor_directives": 0.05263158, "qsc_codecpp_frac_lines_func_ratio": 0.07894737, "qsc_codecpp_cate_bitsstdc": 0.0, "qsc_codecpp_nums_lines_main": 0.0, "qsc_codecpp_frac_lines_goto": 0.0, "qsc_codecpp_cate_var_zero": 0.0, "qsc_codecpp_score_lines_no_logic": 0.15789474, "qsc_codecpp_frac_lines_print": 0.0} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codecpp_frac_lines_func_ratio": 0, "qsc_codecpp_nums_lines_main": 0, "qsc_codecpp_score_lines_no_logic": 0, "qsc_codecpp_frac_lines_preprocessor_directives": 0, "qsc_codecpp_frac_lines_print": 0} |
0015/esp_rlottie | rlottie/src/vector/vinterpolator.cpp | /* -*- Mode: C++; tab-width: 8; indent-tabs-mode: nil; c-basic-offset: 2 -*- */
/* vim: set ts=8 sts=2 et sw=2 tw=80: */
/* This Source Code Form is subject to the terms of the Mozilla Public
* License, v. 2.0. If a copy of the MPL was not distributed with this
* file, You can obtain one at http://mozilla.org/MPL/2.0/. */
#include "vinterpolator.h"
#include <cmath>
V_BEGIN_NAMESPACE
#define NEWTON_ITERATIONS 4
#define NEWTON_MIN_SLOPE 0.02
#define SUBDIVISION_PRECISION 0.0000001
#define SUBDIVISION_MAX_ITERATIONS 10
const float VInterpolator::kSampleStepSize =
1.0f / float(VInterpolator::kSplineTableSize - 1);
void VInterpolator::init(float aX1, float aY1, float aX2, float aY2)
{
mX1 = aX1;
mY1 = aY1;
mX2 = aX2;
mY2 = aY2;
if (mX1 != mY1 || mX2 != mY2) CalcSampleValues();
}
/*static*/ float VInterpolator::CalcBezier(float aT, float aA1, float aA2)
{
// use Horner's scheme to evaluate the Bezier polynomial
return ((A(aA1, aA2) * aT + B(aA1, aA2)) * aT + C(aA1)) * aT;
}
void VInterpolator::CalcSampleValues()
{
for (int i = 0; i < kSplineTableSize; ++i) {
mSampleValues[i] = CalcBezier(float(i) * kSampleStepSize, mX1, mX2);
}
}
float VInterpolator::GetSlope(float aT, float aA1, float aA2)
{
return 3.0f * A(aA1, aA2) * aT * aT + 2.0f * B(aA1, aA2) * aT + C(aA1);
}
float VInterpolator::value(float aX) const
{
if (mX1 == mY1 && mX2 == mY2) return aX;
return CalcBezier(GetTForX(aX), mY1, mY2);
}
float VInterpolator::GetTForX(float aX) const
{
// Find interval where t lies
float intervalStart = 0.0;
const float* currentSample = &mSampleValues[1];
const float* const lastSample = &mSampleValues[kSplineTableSize - 1];
for (; currentSample != lastSample && *currentSample <= aX;
++currentSample) {
intervalStart += kSampleStepSize;
}
--currentSample; // t now lies between *currentSample and *currentSample+1
// Interpolate to provide an initial guess for t
float dist =
(aX - *currentSample) / (*(currentSample + 1) - *currentSample);
float guessForT = intervalStart + dist * kSampleStepSize;
// Check the slope to see what strategy to use. If the slope is too small
// Newton-Raphson iteration won't converge on a root so we use bisection
// instead.
float initialSlope = GetSlope(guessForT, mX1, mX2);
if (initialSlope >= NEWTON_MIN_SLOPE) {
return NewtonRaphsonIterate(aX, guessForT);
} else if (initialSlope == 0.0) {
return guessForT;
} else {
return BinarySubdivide(aX, intervalStart,
intervalStart + kSampleStepSize);
}
}
float VInterpolator::NewtonRaphsonIterate(float aX, float aGuessT) const
{
// Refine guess with Newton-Raphson iteration
for (int i = 0; i < NEWTON_ITERATIONS; ++i) {
// We're trying to find where f(t) = aX,
// so we're actually looking for a root for: CalcBezier(t) - aX
float currentX = CalcBezier(aGuessT, mX1, mX2) - aX;
float currentSlope = GetSlope(aGuessT, mX1, mX2);
if (currentSlope == 0.0) return aGuessT;
aGuessT -= currentX / currentSlope;
}
return aGuessT;
}
float VInterpolator::BinarySubdivide(float aX, float aA, float aB) const
{
float currentX;
float currentT;
int i = 0;
do {
currentT = aA + (aB - aA) / 2.0f;
currentX = CalcBezier(currentT, mX1, mX2) - aX;
if (currentX > 0.0) {
aB = currentT;
} else {
aA = currentT;
}
} while (fabs(currentX) > SUBDIVISION_PRECISION &&
++i < SUBDIVISION_MAX_ITERATIONS);
return currentT;
}
V_END_NAMESPACE
| 3,730 | vinterpolator | cpp | en | cpp | code | {"qsc_code_num_words": 462, "qsc_code_num_chars": 3730.0, "qsc_code_mean_word_length": 5.09090909, "qsc_code_frac_words_unique": 0.34848485, "qsc_code_frac_chars_top_2grams": 0.06122449, "qsc_code_frac_chars_top_3grams": 0.01360544, "qsc_code_frac_chars_top_4grams": 0.00935374, "qsc_code_frac_chars_dupe_5grams": 0.05017007, "qsc_code_frac_chars_dupe_6grams": 0.03061224, "qsc_code_frac_chars_dupe_7grams": 0.0, "qsc_code_frac_chars_dupe_8grams": 0.0, "qsc_code_frac_chars_dupe_9grams": 0.0, "qsc_code_frac_chars_dupe_10grams": 0.0, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.03385602, "qsc_code_frac_chars_whitespace": 0.24772118, "qsc_code_size_file_byte": 3730.0, "qsc_code_num_lines": 124.0, "qsc_code_num_chars_line_max": 80.0, "qsc_code_num_chars_line_mean": 30.08064516, "qsc_code_frac_chars_alphabet": 0.80434783, "qsc_code_frac_chars_comments": 0.22439678, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.02298851, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.00518493, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codecpp_frac_lines_preprocessor_directives": 0.06896552, "qsc_codecpp_frac_lines_func_ratio": 0.03448276, "qsc_codecpp_cate_bitsstdc": 0.0, "qsc_codecpp_nums_lines_main": 0.0, "qsc_codecpp_frac_lines_goto": 0.0, "qsc_codecpp_cate_var_zero": 0.0, "qsc_codecpp_score_lines_no_logic": 0.11494253, "qsc_codecpp_frac_lines_print": 0.0} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codecpp_frac_lines_func_ratio": 0, "qsc_codecpp_nums_lines_main": 0, "qsc_codecpp_score_lines_no_logic": 0, "qsc_codecpp_frac_lines_preprocessor_directives": 0, "qsc_codecpp_frac_lines_print": 0} |
0015/esp_rlottie | rlottie/src/vector/vinterpolator.h | /*
* Copyright (c) 2020 Samsung Electronics Co., Ltd. All rights reserved.
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#ifndef VINTERPOLATOR_H
#define VINTERPOLATOR_H
#include "vpoint.h"
V_BEGIN_NAMESPACE
class VInterpolator {
public:
VInterpolator()
{ /* caller must call Init later */
}
VInterpolator(float aX1, float aY1, float aX2, float aY2)
{
init(aX1, aY1, aX2, aY2);
}
VInterpolator(VPointF pt1, VPointF pt2)
{
init(pt1.x(), pt1.y(), pt2.x(), pt2.y());
}
void init(float aX1, float aY1, float aX2, float aY2);
float value(float aX) const;
void GetSplineDerivativeValues(float aX, float& aDX, float& aDY) const;
private:
void CalcSampleValues();
/**
* Returns x(t) given t, x1, and x2, or y(t) given t, y1, and y2.
*/
static float CalcBezier(float aT, float aA1, float aA2);
/**
* Returns dx/dt given t, x1, and x2, or dy/dt given t, y1, and y2.
*/
static float GetSlope(float aT, float aA1, float aA2);
float GetTForX(float aX) const;
float NewtonRaphsonIterate(float aX, float aGuessT) const;
float BinarySubdivide(float aX, float aA, float aB) const;
static float A(float aA1, float aA2) { return 1.0f - 3.0f * aA2 + 3.0f * aA1; }
static float B(float aA1, float aA2) { return 3.0f * aA2 - 6.0f * aA1; }
static float C(float aA1) { return 3.0f * aA1; }
float mX1;
float mY1;
float mX2;
float mY2;
enum { kSplineTableSize = 11 };
float mSampleValues[kSplineTableSize];
static const float kSampleStepSize;
};
V_END_NAMESPACE
#endif // VINTERPOLATOR_H
| 2,680 | vinterpolator | h | en | c | code | {"qsc_code_num_words": 383, "qsc_code_num_chars": 2680.0, "qsc_code_mean_word_length": 4.79112272, "qsc_code_frac_words_unique": 0.44908616, "qsc_code_frac_chars_top_2grams": 0.0479564, "qsc_code_frac_chars_top_3grams": 0.02833787, "qsc_code_frac_chars_top_4grams": 0.03487738, "qsc_code_frac_chars_dupe_5grams": 0.12643052, "qsc_code_frac_chars_dupe_6grams": 0.10245232, "qsc_code_frac_chars_dupe_7grams": 0.06103542, "qsc_code_frac_chars_dupe_8grams": 0.03487738, "qsc_code_frac_chars_dupe_9grams": 0.0, "qsc_code_frac_chars_dupe_10grams": 0.0, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.02990835, "qsc_code_frac_chars_whitespace": 0.22649254, "qsc_code_size_file_byte": 2680.0, "qsc_code_num_lines": 88.0, "qsc_code_num_chars_line_max": 84.0, "qsc_code_num_chars_line_mean": 30.45454545, "qsc_code_frac_chars_alphabet": 0.8552822, "qsc_code_frac_chars_comments": 0.50895522, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.0, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.00607903, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codec_frac_lines_func_ratio": 0.3, "qsc_codec_cate_bitsstdc": 0.0, "qsc_codec_nums_lines_main": 0, "qsc_codec_frac_lines_goto": 0.0, "qsc_codec_cate_var_zero": 0.0, "qsc_codec_score_lines_no_logic": 0.45, "qsc_codec_frac_lines_print": 0.0, "qsc_codec_frac_lines_preprocessor_directives": null} | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codec_frac_lines_func_ratio": 1, "qsc_codec_nums_lines_main": 0, "qsc_codec_score_lines_no_logic": 0, "qsc_codec_frac_lines_preprocessor_directives": 0, "qsc_codec_frac_lines_print": 0} |
0015/T-Glass-Applications | image_capture_app/main/main.c | #include <stdio.h>
#include <string.h>
#include "freertos/FreeRTOS.h"
#include "freertos/task.h"
#include "freertos/semphr.h"
#include "freertos/task.h"
#include "freertos/queue.h"
#include "esp_log.h"
#include "nvs_manager.h"
#include "t_glass.h"
#include "ble_server.h"
#define TAG "[Glass Main]"
#define IMAGE_MAX_SIZE 31752 // 126x126x2 (Width x Height x 2 bytes)
#define DESIRED_MTU_SIZE 215 // MTU is determined by the Flutter BT Package
static uint8_t *image_buffer = NULL;
static size_t received_bytes = 0;
typedef struct {
uint8_t data[DESIRED_MTU_SIZE];
size_t length;
} ble_data_t;
static QueueHandle_t ble_queue;
void ble_disconnected(){
received_bytes = 0;
}
void ble_receive_image_chunk(uint8_t *data, size_t length) {
if (ble_queue) {
ble_data_t ble_data;
memcpy(ble_data.data, data, length);
ble_data.length = length;
xQueueSend(ble_queue, &ble_data, portMAX_DELAY);
}
}
// Function to process BLE image chunks in a separate task
void ble_process_task(void *arg) {
ble_data_t received_data;
while (1) {
if (xQueueReceive(ble_queue, &received_data, portMAX_DELAY)) {
if (image_buffer == NULL) {
ESP_LOGE("BLE", "Image buffer is NULL! PSRAM allocation failed?");
continue;
}
if ((received_bytes + received_data.length) <= IMAGE_MAX_SIZE) {
memcpy(&image_buffer[received_bytes], received_data.data, received_data.length);
received_bytes += received_data.length;
ESP_LOGI("BLE", "Received %d/%d bytes", received_bytes, IMAGE_MAX_SIZE);
} else {
ESP_LOGE("BLE", "Buffer overflow! Resetting.");
received_bytes = 0;
}
if (received_bytes >= IMAGE_MAX_SIZE) {
ESP_LOGI("BLE", "Image complete, updating LVGL.");
update_canvas_with_rgb565(image_buffer, IMAGE_MAX_SIZE);
received_bytes = 0;
}
}
}
}
// Initialize BLE queue
void ble_receive_init() {
ble_queue = xQueueCreate(10, sizeof(ble_data_t));
// Allocate in PSRAM
image_buffer = (uint8_t *)heap_caps_malloc(IMAGE_MAX_SIZE, MALLOC_CAP_SPIRAM);
if (!image_buffer) {
ESP_LOGE("BLE", "Failed to allocate image buffer in PSRAM!");
} else {
ESP_LOGI("BLE", "Image buffer allocated in PSRAM.");
}
xTaskCreatePinnedToCore(ble_process_task, "BLE_Proc_Task", 4096, NULL, 2, NULL, 1);
}
void app_main(void)
{
ESP_LOGE(TAG, "App Started!");
// Initialize NVS
if (nvs_manager_init() != ESP_OK)
{
ESP_LOGE(TAG, "[Err] Failed to initialize NVS.");
return;
}
if (init_tglass() != ESP_OK)
{
ESP_LOGE(TAG, "[Err] T-Glass Init Fail");
abort();
}
ESP_LOGI(TAG, "[Pass] T-Glass Init");
ble_receive_init();
ble_server_init();
}
| 2,957 | main | c | en | c | code | {"qsc_code_num_words": 380, "qsc_code_num_chars": 2957.0, "qsc_code_mean_word_length": 4.57368421, "qsc_code_frac_words_unique": 0.29210526, "qsc_code_frac_chars_top_2grams": 0.04602992, "qsc_code_frac_chars_top_3grams": 0.04142693, "qsc_code_frac_chars_top_4grams": 0.04315305, "qsc_code_frac_chars_dupe_5grams": 0.12658228, "qsc_code_frac_chars_dupe_6grams": 0.06214039, "qsc_code_frac_chars_dupe_7grams": 0.04142693, "qsc_code_frac_chars_dupe_8grams": 0.0, "qsc_code_frac_chars_dupe_9grams": 0.0, "qsc_code_frac_chars_dupe_10grams": 0.0, "qsc_code_frac_chars_replacement_symbols": 0.0, "qsc_code_frac_chars_digital": 0.01645338, "qsc_code_frac_chars_whitespace": 0.26006087, "qsc_code_size_file_byte": 2957.0, "qsc_code_num_lines": 105.0, "qsc_code_num_chars_line_max": 97.0, "qsc_code_num_chars_line_mean": 28.16190476, "qsc_code_frac_chars_alphabet": 0.77787934, "qsc_code_frac_chars_comments": 0.07067974, "qsc_code_cate_xml_start": 0.0, "qsc_code_frac_lines_dupe_lines": 0.08536585, "qsc_code_cate_autogen": 0.0, "qsc_code_frac_lines_long_string": 0.0, "qsc_code_frac_chars_string_length": 0.16339156, "qsc_code_frac_chars_long_word_length": 0.0, "qsc_code_frac_lines_string_concat": 0.0, "qsc_code_cate_encoded_data": 0.0, "qsc_code_frac_chars_hex_words": 0.0, "qsc_code_frac_lines_prompt_comments": 0.0, "qsc_code_frac_lines_assert": 0.0, "qsc_codec_frac_lines_func_ratio": 0.06097561, "qsc_codec_cate_bitsstdc": 0.0, "qsc_codec_nums_lines_main": 0, "qsc_codec_frac_lines_goto": 0.0, "qsc_codec_cate_var_zero": 0.0, "qsc_codec_score_lines_no_logic": 0.20731707, "qsc_codec_frac_lines_print": 0.0, "qsc_codec_frac_lines_preprocessor_directives": 0.17073171} | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc_code_frac_chars_dupe_7grams": 0, "qsc_code_frac_chars_dupe_8grams": 0, "qsc_code_frac_chars_dupe_9grams": 0, "qsc_code_frac_chars_dupe_10grams": 0, "qsc_code_size_file_byte": 0, "qsc_code_num_lines": 0, "qsc_code_num_chars_line_max": 0, "qsc_code_num_chars_line_mean": 0, "qsc_code_frac_chars_alphabet": 0, "qsc_code_frac_chars_digital": 0, "qsc_code_frac_chars_whitespace": 0, "qsc_code_frac_chars_comments": 0, "qsc_code_cate_xml_start": 0, "qsc_code_frac_lines_dupe_lines": 0, "qsc_code_cate_autogen": 0, "qsc_code_frac_lines_long_string": 0, "qsc_code_frac_chars_string_length": 0, "qsc_code_frac_chars_long_word_length": 0, "qsc_code_cate_encoded_data": 0, "qsc_code_frac_chars_hex_words": 0, "qsc_code_frac_lines_prompt_comments": 0, "qsc_code_frac_lines_assert": 0, "qsc_codec_frac_lines_func_ratio": 0, "qsc_codec_nums_lines_main": 0, "qsc_codec_score_lines_no_logic": 0, "qsc_codec_frac_lines_preprocessor_directives": 0, "qsc_codec_frac_lines_print": 0} |
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