mirror of
https://github.com/microsoft/autogen.git
synced 2025-07-21 07:51:55 +00:00
3e7aac6e8b
* simplify the initiation of chat * version update * include openai * completion * load config list from json * initiate_chat * oai config list * oai config list * config list * config_list * raise_error * retry_time * raise condition * oai config list * catch file not found * catch openml error * handle openml error * handle openml error * handle openml error * handle openml error * handle openml error * handle openml error * close #1139 * use property * termination msg * AIUserProxyAgent * smaller dev container * update notebooks * match * document code execution and AIUserProxyAgent * gpt 3.5 config list * rate limit * variable visibility * remove unnecessary import * quote * notebook comments * remove mathchat from init import * two users * import location * expose config * return str not tuple * rate limit * ipython user proxy * message * None result * rate limit * rate limit * rate limit * rate limit * make auto_reply a common method for all agents * abs path * refactor and doc * set mathchat_termination * code format * modified * emove import * code quality * sender -> messages * system message * clean agent hierarchy * dict check * invalid oai msg * return * openml error * docstr --------- Co-authored-by: kevin666aa <yrwu000627@gmail.com>
1061 lines
305 KiB
Plaintext
1061 lines
305 KiB
Plaintext
{
|
||
"cells": [
|
||
{
|
||
"attachments": {},
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"<a href=\"https://colab.research.google.com/github/microsoft/FLAML/blob/main/notebook/autogen_agent_auto_feedback_from_code_execution.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
|
||
]
|
||
},
|
||
{
|
||
"attachments": {},
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"slideshow": {
|
||
"slide_type": "slide"
|
||
}
|
||
},
|
||
"source": [
|
||
"# Interactive LLM Agent with Auto Feedback from Code Execution\n",
|
||
"\n",
|
||
"FLAML offers an experimental feature of interactive LLM agents, which can be used to solve various tasks with human or automatic feedback, including tasks that require using tools via code.\n",
|
||
"Please find documentation about this feature [here](https://microsoft.github.io/FLAML/docs/Use-Cases/Auto-Generation#agents-experimental).\n",
|
||
"\n",
|
||
"In this notebook, we demonstrate how to use `AssistantAgent` and `UserProxyAgent` to write code and execute the code. Here `AssistantAgent` is an LLM-based agent that can write Python code (in a Python coding block) for a user to execute for a given task. `UserProxyAgent` is an agent which serves as a proxy for the human user to execute the code written by `AssistantAgent`, or automatically execute the code. Depending on the setting of `human_input_mode` and `max_consecutive_auto_reply`, the `UserProxyAgent` either solicits feedback from the human user or uses auto-feedback based on the result of code execution. For example, when `human_input_mode` is set to \"ALWAYS\", the `UserProxyAgent` will always prompt the user for feedback. When user feedback is provided, the `UserProxyAgent` will directly pass the feedback to `AssistantAgent` without doing any additional steps. When no user feedback is provided, the `UserProxyAgent` will execute the code written by `AssistantAgent` directly and return the execution results (success or failure and corresponding outputs) to `AssistantAgent`.\n",
|
||
"\n",
|
||
"## Requirements\n",
|
||
"\n",
|
||
"FLAML requires `Python>=3.8`. To run this notebook example, please install flaml with the [autogen] option:\n",
|
||
"```bash\n",
|
||
"pip install flaml[autogen]\n",
|
||
"```"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 1,
|
||
"metadata": {
|
||
"execution": {
|
||
"iopub.execute_input": "2023-02-13T23:40:52.317406Z",
|
||
"iopub.status.busy": "2023-02-13T23:40:52.316561Z",
|
||
"iopub.status.idle": "2023-02-13T23:40:52.321193Z",
|
||
"shell.execute_reply": "2023-02-13T23:40:52.320628Z"
|
||
}
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"# %pip install flaml[autogen]~=2.0.0rc4"
|
||
]
|
||
},
|
||
{
|
||
"attachments": {},
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Set your API Endpoint\n",
|
||
"\n",
|
||
"The [`config_list_from_json`](https://microsoft.github.io/FLAML/docs/reference/autogen/oai/openai_utils#config_list_from_json) function loads a list of configurations from an environment variable or a json file.\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 2,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"from flaml import oai\n",
|
||
"\n",
|
||
"config_list = oai.config_list_from_json(\n",
|
||
" \"OAI_CONFIG_LIST\",\n",
|
||
" filter_dict={\n",
|
||
" \"model\": [\"gpt-4\", \"gpt4\", \"gpt-4-32k\", \"gpt-4-32k-0314\"],\n",
|
||
" },\n",
|
||
")"
|
||
]
|
||
},
|
||
{
|
||
"attachments": {},
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"It first looks for environment variable \"OAI_CONFIG_LIST\" which needs to be a valid json string. If that variable is not found, it then looks for a json file named \"OAI_CONFIG_LIST\". It filters the configs by models (you can filter by other keys as well). Only the gpt-4 models are kept in the list based on the filter condition.\n",
|
||
"\n",
|
||
"The config list looks like the following:\n",
|
||
"```python\n",
|
||
"config_list = [\n",
|
||
" {\n",
|
||
" 'model': 'gpt-4',\n",
|
||
" 'api_key': '<your OpenAI API key here>',\n",
|
||
" },\n",
|
||
" {\n",
|
||
" 'model': 'gpt-4',\n",
|
||
" 'api_key': '<your Azure OpenAI API key here>',\n",
|
||
" 'api_base': '<your Azure OpenAI API base here>',\n",
|
||
" 'api_type': 'azure',\n",
|
||
" 'api_version': '2023-06-01-preview',\n",
|
||
" },\n",
|
||
" {\n",
|
||
" 'model': 'gpt-4-32k',\n",
|
||
" 'api_key': '<your Azure OpenAI API key here>',\n",
|
||
" 'api_base': '<your Azure OpenAI API base here>',\n",
|
||
" 'api_type': 'azure',\n",
|
||
" 'api_version': '2023-06-01-preview',\n",
|
||
" },\n",
|
||
"]\n",
|
||
"```\n",
|
||
"\n",
|
||
"If you open this notebook in colab, you can upload your files by clicking the file icon on the left panel and then choose \"upload file\" icon.\n",
|
||
"\n",
|
||
"You can set the value of config_list in other ways you prefer, e.g., loading from a YAML file."
|
||
]
|
||
},
|
||
{
|
||
"attachments": {},
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Example Task: Check Stock Price Change\n",
|
||
"\n",
|
||
"In the example below, let's see how to use the agents in FLAML to write a python script and execute the script. This process involves constructing a `AssistantAgent` to serve as the assistant, along with a `UserProxyAgent` that acts as a proxy for the human user. In this example demonstrated below, when constructing the `UserProxyAgent`, we select the `human_input_mode` to \"NEVER\". This means that the `UserProxyAgent` will not solicit feedback from the human user. It stops replying when the limit defined by `max_consecutive_auto_reply` is reached, or when `is_termination_msg()` returns true for the received message."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 3,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"user (to assistant):\n",
|
||
"\n",
|
||
"What date is today? Compare the year-to-date gain for META and TESLA.\n",
|
||
"\n",
|
||
"--------------------------------------------------------------------------------\n",
|
||
"assistant (to user):\n",
|
||
"\n",
|
||
"# filename: stock_comparison.py\n",
|
||
"```python\n",
|
||
"import datetime\n",
|
||
"import yfinance as yf\n",
|
||
"\n",
|
||
"# Get today's date\n",
|
||
"today = datetime.date.today()\n",
|
||
"print(\"Today's date:\", today)\n",
|
||
"\n",
|
||
"# Get the start of the year\n",
|
||
"start_of_year = datetime.date(today.year, 1, 1)\n",
|
||
"\n",
|
||
"# Download the historical data for META and TESLA\n",
|
||
"meta_data = yf.download('META', start=start_of_year, end=today)\n",
|
||
"tesla_data = yf.download('TSLA', start=start_of_year, end=today)\n",
|
||
"\n",
|
||
"# Calculate the year-to-date gain for META and TESLA\n",
|
||
"meta_gain = (meta_data['Close'][-1] - meta_data['Close'][0]) / meta_data['Close'][0]\n",
|
||
"tesla_gain = (tesla_data['Close'][-1] - tesla_data['Close'][0]) / tesla_data['Close'][0]\n",
|
||
"\n",
|
||
"# Print the year-to-date gain for META and TESLA\n",
|
||
"print(\"Year-to-date gain for META:\", round(meta_gain * 100, 2), \"%\")\n",
|
||
"print(\"Year-to-date gain for TESLA:\", round(tesla_gain * 100, 2), \"%\")\n",
|
||
"```\n",
|
||
"Please save this code in a file named `stock_comparison.py` and run it. This script will print today's date and compare the year-to-date gain for META and TESLA. It uses the `yfinance` library to download the historical data for the stocks. If you haven't installed `yfinance`, please install it by running `pip install yfinance`.\n",
|
||
"\n",
|
||
"--------------------------------------------------------------------------------\n",
|
||
"\n",
|
||
">>>>>>>> USING AUTO REPLY FOR THE USER...\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"user (to assistant):\n",
|
||
"\n",
|
||
"exitcode: 0 (execution succeeded)\n",
|
||
"Code output: \n",
|
||
"Today's date: 2023-07-24\n",
|
||
"[*********************100%***********************] 1 of 1 completed\n",
|
||
"[*********************100%***********************] 1 of 1 completed\n",
|
||
"Year-to-date gain for META: 135.9 %\n",
|
||
"Year-to-date gain for TESLA: 140.54 %\n",
|
||
"\n",
|
||
"\n",
|
||
"--------------------------------------------------------------------------------\n",
|
||
"assistant (to user):\n",
|
||
"\n",
|
||
"Great! The script has successfully executed and provided the year-to-date gain for both META and TESLA stocks. As of today's date (July 24, 2023), the year-to-date gain for META is 135.9%, and for TESLA, it's 140.54%. \n",
|
||
"\n",
|
||
"Please let me know if you need help with anything else. \n",
|
||
"\n",
|
||
"TERMINATE\n",
|
||
"\n",
|
||
"--------------------------------------------------------------------------------\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"from flaml.autogen.agent import AssistantAgent, UserProxyAgent\n",
|
||
"\n",
|
||
"# create an AssistantAgent named \"assistant\"\n",
|
||
"assistant = AssistantAgent(\n",
|
||
" \"assistant\",\n",
|
||
" oai_config={\n",
|
||
" \"seed\": 42,\n",
|
||
" \"config_list\": config_list,\n",
|
||
" \"temperature\": 0,\n",
|
||
" }\n",
|
||
")\n",
|
||
"# create a UserProxyAgent instance named \"user\"\n",
|
||
"user = UserProxyAgent(\n",
|
||
" \"user\",\n",
|
||
" human_input_mode=\"NEVER\",\n",
|
||
" max_consecutive_auto_reply=10,\n",
|
||
" is_termination_msg=lambda x: x.get(\"content\", \"\").rstrip().endswith(\"TERMINATE\") or x.get(\"content\", \"\").rstrip().endswith('\"TERMINATE\".'),\n",
|
||
" code_execution_config={\n",
|
||
" \"work_dir\": \"coding\",\n",
|
||
" \"use_docker\": False, # set to True or image name like \"python:3\" to use docker\n",
|
||
" },\n",
|
||
")\n",
|
||
"# the assistant receives a message from the user, which contains the task description\n",
|
||
"user.initiate_chat(\n",
|
||
" assistant,\n",
|
||
" message=\"\"\"What date is today? Compare the year-to-date gain for META and TESLA.\"\"\",\n",
|
||
")"
|
||
]
|
||
},
|
||
{
|
||
"attachments": {},
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"The example above involves code execution. In FLAML, code execution is triggered automatically by the `UserProxyAgent` when it detects an executable code block in a received message and no human user input is provided. This process occurs in a designated working directory, using a Docker container by default. Unless a specific directory is specified, FLAML defaults to the `flaml/autogen/extensions` directory. Users have the option to specify a different working directory by setting the `work_dir` argument when constructing a new instance of the `UserProxyAgent`.\n"
|
||
]
|
||
},
|
||
{
|
||
"attachments": {},
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"All the feedback is auto generated."
|
||
]
|
||
},
|
||
{
|
||
"attachments": {},
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Example Task: Plot Chart"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 4,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"user (to assistant):\n",
|
||
"\n",
|
||
"Plot a chart of their stock price change YTD and save to stock_price_ytd.png.\n",
|
||
"\n",
|
||
"--------------------------------------------------------------------------------\n",
|
||
"assistant (to user):\n",
|
||
"\n",
|
||
"# filename: stock_plot.py\n",
|
||
"```python\n",
|
||
"import matplotlib.pyplot as plt\n",
|
||
"\n",
|
||
"# Plot the close price of META and TESLA\n",
|
||
"plt.figure(figsize=(14,7))\n",
|
||
"plt.plot(meta_data['Close'], label='META')\n",
|
||
"plt.plot(tesla_data['Close'], label='TESLA')\n",
|
||
"\n",
|
||
"# Set the title and labels\n",
|
||
"plt.title('Year-to-date stock price change for META and TESLA')\n",
|
||
"plt.xlabel('Date')\n",
|
||
"plt.ylabel('Close Price')\n",
|
||
"\n",
|
||
"# Show the legend\n",
|
||
"plt.legend()\n",
|
||
"\n",
|
||
"# Save the plot as a PNG file\n",
|
||
"plt.savefig('stock_price_ytd.png')\n",
|
||
"```\n",
|
||
"Please save this code in a file named `stock_plot.py` and run it. This script will plot the year-to-date stock price change for META and TESLA and save the plot as a PNG file named `stock_price_ytd.png`. It uses the `matplotlib` library to create the plot. If you haven't installed `matplotlib`, please install it by running `pip install matplotlib`.\n",
|
||
"\n",
|
||
"--------------------------------------------------------------------------------\n",
|
||
"\n",
|
||
">>>>>>>> USING AUTO REPLY FOR THE USER...\n",
|
||
"user (to assistant):\n",
|
||
"\n",
|
||
"exitcode: 1 (execution failed)\n",
|
||
"Code output: \n",
|
||
"Traceback (most recent call last):\n",
|
||
" File \"/workspaces/FLAML/notebook/coding/tmp_code_0e68902a38546d82fddf9b82f39278e3.py\", line 5, in <module>\n",
|
||
" plt.plot(meta_data['Close'], label='META')\n",
|
||
"NameError: name 'meta_data' is not defined\n",
|
||
"\n",
|
||
"\n",
|
||
"--------------------------------------------------------------------------------\n",
|
||
"assistant (to user):\n",
|
||
"\n",
|
||
"I apologize for the oversight. The error occurred because the `meta_data` and `tesla_data` variables, which hold the stock data, were not defined in this script. We need to fetch the stock data again in this script. Here is the corrected code:\n",
|
||
"\n",
|
||
"# filename: stock_plot.py\n",
|
||
"```python\n",
|
||
"import datetime\n",
|
||
"import yfinance as yf\n",
|
||
"import matplotlib.pyplot as plt\n",
|
||
"\n",
|
||
"# Get today's date\n",
|
||
"today = datetime.date.today()\n",
|
||
"\n",
|
||
"# Get the start of the year\n",
|
||
"start_of_year = datetime.date(today.year, 1, 1)\n",
|
||
"\n",
|
||
"# Download the historical data for META and TESLA\n",
|
||
"meta_data = yf.download('META', start=start_of_year, end=today)\n",
|
||
"tesla_data = yf.download('TSLA', start=start_of_year, end=today)\n",
|
||
"\n",
|
||
"# Plot the close price of META and TESLA\n",
|
||
"plt.figure(figsize=(14,7))\n",
|
||
"plt.plot(meta_data['Close'], label='META')\n",
|
||
"plt.plot(tesla_data['Close'], label='TESLA')\n",
|
||
"\n",
|
||
"# Set the title and labels\n",
|
||
"plt.title('Year-to-date stock price change for META and TESLA')\n",
|
||
"plt.xlabel('Date')\n",
|
||
"plt.ylabel('Close Price')\n",
|
||
"\n",
|
||
"# Show the legend\n",
|
||
"plt.legend()\n",
|
||
"\n",
|
||
"# Save the plot as a PNG file\n",
|
||
"plt.savefig('stock_price_ytd.png')\n",
|
||
"```\n",
|
||
"Please save this code in a file named `stock_plot.py` and run it. This script will plot the year-to-date stock price change for META and TESLA and save the plot as a PNG file named `stock_price_ytd.png`.\n",
|
||
"\n",
|
||
"--------------------------------------------------------------------------------\n",
|
||
"\n",
|
||
">>>>>>>> USING AUTO REPLY FOR THE USER...\n",
|
||
"user (to assistant):\n",
|
||
"\n",
|
||
"exitcode: 0 (execution succeeded)\n",
|
||
"Code output: \n",
|
||
"[*********************100%***********************] 1 of 1 completed\n",
|
||
"[*********************100%***********************] 1 of 1 completed\n",
|
||
"\n",
|
||
"\n",
|
||
"--------------------------------------------------------------------------------\n",
|
||
"assistant (to user):\n",
|
||
"\n",
|
||
"Great! The script has successfully executed and the plot of the year-to-date stock price change for META and TESLA has been saved as a PNG file named `stock_price_ytd.png`. You can find this file in the same directory where you ran the script.\n",
|
||
"\n",
|
||
"Please let me know if you need help with anything else.\n",
|
||
"\n",
|
||
"TERMINATE\n",
|
||
"\n",
|
||
"--------------------------------------------------------------------------------\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# followup of the previous question\n",
|
||
"user.send(\n",
|
||
" recipient=assistant,\n",
|
||
" message=\"\"\"Plot a chart of their stock price change YTD and save to stock_price_ytd.png.\"\"\",\n",
|
||
")"
|
||
]
|
||
},
|
||
{
|
||
"attachments": {},
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"Let's display the generated figure."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 5,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": "iVBORw0KGgoAAAANSUhEUgAABXgAAAK8CAYAAABV1dcbAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8pXeV/AAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOzdd1yVdf/H8ffhsPcQBAURcCLulZZaampqpWbDsrRlw+67Xb+22bC677tdtsyWNixbVpqVI7fm3gu3iIAMQea5fn9ccpJABQQOB17Px4PHubiu61zX5xyQ8u2Hz9diGIYhAAAAAAAAAIDTcXF0AQAAAAAAAACAyiHgBQAAAAAAAAAnRcALAAAAAAAAAE6KgBcAAAAAAAAAnBQBLwAAAAAAAAA4KQJeAAAAAAAAAHBSBLwAAAAAAAAA4KQIeAEAAAAAAADASRHwAgAAAAAAAICTIuAFAAAAAAAAACdFwAsAAAAAAAAAToqAFwAAAAAAAACcFAEvAAAAAAAAADgpAl4AAAAAAAAAcFIEvAAAAAAAAADgpAh4AQAAAAAAAMBJEfACAAAAAAAAgJMi4AUAAAAAAAAAJ0XACwAAAAAAAABOioAXAAAAAAAAAJwUAS8AAAAAAAAAOCkCXgAAAAAAAABwUgS8AAAAAAAAAOCkCHgBAAAAAAAAwEkR8AIAAAAAAACAkyLgBQAAAAAAAAAnRcALAAAAAAAAAE6KgBcAAAAAAAAAnBQBLwAAAAAAAAA4KQJeAAAAAAAAAHBSBLwAAAAAAAAA4KQIeAEAAAAAAADASRHwAgAAAAAAAICTIuAFAAAAAAAAACdFwAsAAAAAAAAAToqAFwAAAAAAAACcFAEvAAAAAAAAADgpAl4AAAAAAAAAcFIEvAAAAAAAAADgpAh4AQAAAAAAAMBJEfACAAAAAAAAgJMi4AUAAAAAAAAAJ0XACwAAAAAAAABOioAXAAAAAAAAAJwUAS8AAAAAAAAAOCkCXgAAAAAAAABwUgS8AAAAAAAAAOCkCHgBAAAAAAAAwEkR8AIAAAAAAACAkyLgBQAAAAAAAAAnRcALAAAAAAAAAE6KgBcAAAAAAAAAnBQBLwAAAAAAAAA4KQJeAAAAAAAAAHBSBLwAAAAAAAAA4KQIeAEAAAAAAADASRHwAgAAAAAAAICTIuAFAAAAAAAAACdFwAsAAAAAAAAAToqAFwAAAAAAAACcFAEvAAAAAAAAADgpAl4AAFBnXXjhhbrwwgsdXUatNHbsWPn6+jrs/nv27JHFYtFHH33ksBpOp2nTpho6dKijy6h2n376qVq1aiU3NzcFBgY6uhz8w9ixY9W0aVNHlwEAAJwAAS8AAHXEJZdcoqCgIB05cqTUsYyMDEVERKh79+6y2WwOqE5asmSJJkyYoPT0dIfcvyJycnI0YcIEzZ8/v8bvvXnzZk2YMEF79uyp8Xuj/ti6davGjh2ruLg4vf/++3rvvfeq9X4TJkyQxWKRi4uL9u/fX+p4ZmamvLy8ZLFYdNddd9n3F/9DwOk+XnjhBX300UdnPKf4459habdu3WSxWDR58uRqfe3VpaKvu/hrcLqPpKQk+7WPHj2qu+++W61atZKXl5fCwsLUrVs3Pfzwwzp+/Lj9vIr+Q1F6ero8PT1lsVi0ZcuWKnsvAACo71wdXQAAAKgab7/9thISEnTvvfdq+vTpJY49+uijSklJ0ezZs+Xi4ph/312yZImefvppjR07ttZ3C+bk5Ojpp5+WpBrvAN68ebOefvppXXjhhXW6ey86OlonTpyQm5ubo0upl+bPny+bzabXXntNzZo1q7H7enh46PPPP9dDDz1UYv/MmTPP+LxRo0Zp8ODBpfZ37NhRXl5e+vTTT0vsv+WWW9StWzeNGzfOvu/UIHLHjh1auXKlmjZtqmnTpumOO+6ozMtxqN69e1f4dUvS5MmTywxli38up6WlqUuXLsrMzNRNN92kVq1aKTU1VevXr9fkyZN1xx13VLr7f8aMGbJYLAoPD9e0adP07LPPVuo6AACgJAJeAADqiJiYGD311FN6+OGHNXbsWA0YMECStHLlSr3zzjt64IEH1L59+2qtITc3V+7u7g4LkVH7FRYWymazyd3dXZ6eno4up95KTk6WpCr9x5acnBx5e3uf8ZzBgweXGfBOnz5dQ4YM0TfffFPm8zp16qTRo0ef9rqxsbElPr/99tsVGxt72ud89tlnCgsL0//+9z+NHDlSe/bscbp/UImNja3w65akkSNHqkGDBqc9PmXKFO3bt0+LFy9Wz549SxzLzMyUu7t7pWv+7LPPNHjwYEVHR2v69OkEvAAAVBH+9gUAQB1y3333qV27drrzzjuVm5uroqIi3X777YqOjtZTTz2lrVu3auTIkQoODpanp6e6dOmiH374ocQ10tLS9MADD6ht27by9fWVv7+/LrnkEq1bt67EefPnz5fFYtEXX3yhxx9/XI0bN5a3t7cyMzNL1TVhwgQ9+OCDkswguvhXgovHEBQWFuqZZ55RXFycPDw81LRpUz366KPKy8sr92t/7733FBcXJy8vL3Xr1k1//vlnqXPy8/P15JNPqnPnzgoICJCPj4969eqlefPm2c/Zs2ePQkNDJUlPP/20vdYJEybYzynP+3g6X3zxhTp37iw/Pz/5+/urbdu2eu211ySZv3J95ZVXSpIuuugi+71PHRXx9ttvq02bNvLw8FCjRo00fvz4MsdeLF++XIMHD1ZQUJB8fHzUrl07+31OZ+3atQoNDdWFF15Y4tew/6n417J3796tgQMHysfHR40aNdLEiRNlGIb9vOJfr//vf/+rV1991f713bx582ln8G7dulVXXXWVQkND5eXlpZYtW+qxxx4rcc7Bgwd10003qWHDhvLw8FCbNm304YcfnvG1neqzzz5Tt27d5O3traCgIPXu3Vu//vprqfMWLVqkbt26ydPTU7Gxsfrkk09KHK/on5WvvvpKzz33nCIjI+Xp6al+/fpp586dpe771ltvKTY2tsT3clnzpPPy8vTUU0+pWbNm8vDwUFRUlB566KGz/rlp2rSpnnrqKUlSaGhoqe/v8nyPXXjhhUpISNBff/2l3r17y9vbW48++ugZ7ytJ1157rdauXautW7fa9yUlJemPP/7Qtddee9bnV5Xp06dr5MiRGjp0qAICAkr91sPplOdniFTye7/4Z5OHh4e6du2qlStXlrrud999p4SEBHl6eiohIUHffvttlbzOyti1a5esVqvOO++8Usf8/f0r/Q8z+/bt059//qlrrrlG11xzjRITE7VkyZJzLRcAAIgOXgAA6hRXV1e999576tmzp5555hmFhYVp9erVmj17thITE3X++eercePG+r//+z/5+Pjoq6++0rBhw/TNN99o+PDhkqTdu3fru+++05VXXqmYmBgdOXJE7777rvr06aPNmzerUaNGJe75zDPPyN3dXQ888IDy8vLK7O4aMWKEtm/frs8//1yvvPKKvXusOEi95ZZb9PHHH2vkyJG6//77tXz5ck2aNElbtmwpV9AxZcoU3XbbberZs6fuuece7d69W5dddpmCg4MVFRVlPy8zM1MffPCBRo0apVtvvVVZWVmaMmWKBg4cqBUrVqhDhw4KDQ21/xry8OHDNWLECElSu3btJEmbNm0q1/tYlrlz52rUqFHq16+fXnzxRUnSli1btHjxYt19993q3bu3/v3vf+v111/Xo48+qtatW0uS/XHChAl6+umn1b9/f91xxx3atm2bJk+erJUrV2rx4sX2cQdz587V0KFDFRERobvvvlvh4eHasmWLZs2apbvvvrvM2lauXKmBAweqS5cu+v777+Xl5XXG97yoqEiDBg3Seeedp5deekmzZ8/WU089pcLCQk2cOLHEuVOnTlVubq7GjRsnDw8PBQcHlzkLev369erVq5fc3Nw0btw4NW3aVLt27dKPP/6o5557TpJ05MgRnXfeefZZraGhofrll1908803KzMzU/fcc88Z63766ac1YcIE9ezZUxMnTpS7u7uWL1+uP/74w971Lkk7d+7UyJEjdfPNN2vMmDH68MMPNXbsWHXu3Flt2rSRVPE/Ky+88IJcXFz0wAMPKCMjQy+99JKuu+46LV++3H7O5MmTddddd6lXr1669957tWfPHg0bNkxBQUGKjIy0n2ez2XTZZZdp0aJFGjdunFq3bq0NGzbolVde0fbt2/Xdd9+d9j149dVX9cknn+jbb7+1/7p+8fd3eb/HJCk1NVWXXHKJrrnmGo0ePVoNGzY843svmWMFIiMjNX36dPv3yZdffilfX18NGTLktM/LyclRSkpKqf2BgYFyda3YX2mWL1+unTt3aurUqXJ3d9eIESM0bdq0cgXU5fkZcqrp06crKytLt912mywWi1566SWNGDFCu3fvtr+Xv/76q6644grFx8dr0qRJSk1N1Y033lji612V0tLSSu1zdXW1d3NHR0erqKhIn376qcaMGVNl9/3888/l4+OjoUOHysvLS3FxcZo2bVqpLmEAAFAJBgAAqHPuuusuw83NzfD19TVGjRplGIZh9OvXz2jbtq2Rm5trP89msxk9e/Y0mjdvbt+Xm5trFBUVlbheYmKi4eHhYUycONG+b968eYYkIzY21sjJyTlrTf/5z38MSUZiYmKJ/WvXrjUkGbfcckuJ/Q888IAhyfjjjz/OeN38/HwjLCzM6NChg5GXl2ff/9577xmSjD59+tj3FRYWljjHMAzj2LFjRsOGDY2bbrrJvu/o0aOGJOOpp54qdb/yvo9lufvuuw1/f3+jsLDwtOfMmDHDkGTMmzevxP7k5GTD3d3dGDBgQImvz5tvvmlIMj788EP7a4yJiTGio6ONY8eOlbiGzWazb48ZM8bw8fExDMMwFi1aZPj7+xtDhgwp8bpOZ8yYMYYk41//+leJaw8ZMsRwd3c3jh49ahiG+X0jyfD39zeSk5NLXKP42NSpU+37evfubfj5+Rl79+49bd0333yzERERYaSkpJQ455prrjECAgLO+L24Y8cOw8XFxRg+fHip7/FT7xEdHW1IMhYuXGjfl5ycbHh4eBj333+/fV9F/6y0bt26xPffa6+9ZkgyNmzYYBiGYeTl5RkhISFG165djYKCAvt5H330Uanv5U8//dRwcXEx/vzzzxL3f+eddwxJxuLFi0/7PhiGYTz11FOGJPvXqvg1lud7zDAMo0+fPoYk45133jnjfcq63wMPPGA0a9bMfqxr167GjTfeaBiGYUgyxo8fbz9W/H1yuo+lS5eWeT8fHx9jzJgxZR676667jKioKPvX/NdffzUkGWvWrDnr6yjvz5DiukNCQoy0tDT7/u+//96QZPz444/2fR06dDAiIiKM9PR0+77imqKjo89a06nO9LqLvwZlfbRs2dJ+XlJSkhEaGmpIMlq1amXcfvvtxvTp00vUV+zUnyNn07ZtW+O6666zf/7oo48aDRo0KPG9DgAAKocRDQAA1EHPPfecQkJC5OLioldeeUVpaWn6448/dNVVVykrK0spKSlKSUlRamqqBg4cqB07dujgwYOSzEWQimfoFhUVKTU1Vb6+vmrZsqVWr15d6l5jxow5a7fnmfz888+SzPESp7r//vslST/99NMZn79q1SolJyfr9ttvL9E9PHbsWAUEBJQ412q12s+x2WxKS0tTYWGhunTpUuZr+6eKvI9lCQwMVHZ2tubOnXvWe/3Tb7/9pvz8fN1zzz0lZhzfeuut8vf3t79Pa9asUWJiou65555S81UtFkup686bN08DBw5Uv379NHPmTHl4eJS7prvuuqvEte+66y7l5+frt99+K3HeFVdcYe/WPp2jR49q4cKFuummm9SkSZMy6zYMQ998840uvfRSGYZhf/9TUlI0cOBAZWRknPHr+N1338lms+nJJ58sNSf6n+9NfHy8evXqZf88NDRULVu21O7du+37Kvpn5cYbbyzxPVp8/eJrrlq1Sqmpqbr11ltLdKVed911CgoKKnGtGTNmqHXr1mrVqlWJ96Fv376SVGpkQHmU93vs1Nd/4403Vvg+1157rXbu3KmVK1faH882nmHcuHGaO3duqY/4+PgK3buwsFBffvmlrr76avvXvG/fvgoLC9O0adPO+vyK/gy5+uqrS3zt/vk1P3z4sNauXasxY8aU+Hl18cUXV/i1ldc333xT6n2cOnWq/XjDhg21bt063X777Tp27JjeeecdXXvttQoLC9MzzzxTYgxLea1fv14bNmzQqFGj7PtGjRqllJQUzZkzp0peFwAA9RkjGgAAqIP8/f3VsmVLpaSkqGHDhlqxYoUMw9ATTzyhJ554osznJCcnq3HjxrLZbHrttdf09ttvKzExUUVFRfZzQkJCSj0vJibGvl1UVKSjR4+WOB4cHHzGRXn27t0rFxcXNWvWrMT+8PBwBQYGau/evZKkEydOKCMjo9Q5xcebN29e4pibm1upBYgk6eOPP9b//vc/bd26VQUFBWW+jtPZuXNnud/Hstx555366quvdMkll6hx48YaMGCArrrqKg0aNOis9y5+nS1btiyx393dXbGxsfbju3btkiQlJCSc9Zq5ubkaMmSIOnfurK+++qpCv+ru4uJS6v1t0aKFJNlnKxcrz3tbHHidqe6jR48qPT1d7733nt57770yzylePKwsu3btkouLS7mCs3+GzJIUFBSkY8eO2T+v6J+Vf16zOPgrvmbx1/CffxZcXV1LLQC2Y8cObdmy5bTB+Zneh9Mp7/dYscaNG1dqwa2OHTuqVatWmj59ugIDAxUeHm4Ppk+nefPm6t+/f4Xv9U+//vqrjh49qm7dupWYf3zRRRfp888/14svvnjWRSIr8jOkvF/zf/78knTafyg4V7179z7jImuSFBERocmTJ+vtt9/Wjh07NGfOHL344ot68sknFRERoVtuuaVC9/zss8/k4+Oj2NhY+/vu6emppk2batq0aWcczwEAAM6OgBcAgHqgeN7pAw88oIEDB5Z5TnGo9Pzzz+uJJ57QTTfdpGeeeUbBwcFycXHRPffcU+bc1FO7d/fv318q5Jg3b16pxaHKUlZ36am+/PLLUt2CFe0k++yzzzR27FgNGzZMDz74oMLCwmS1WjVp0iR7MHomFXkfyxIWFqa1a9dqzpw5+uWXX/TLL79o6tSpuuGGG/Txxx9X6LVUBQ8PDw0ePFjff/+9Zs+eraFDh1bLfc6lw/tUxe//6NGjTzsbtHiW7LmyWq1l7j/1e66if1bKc83ystlsatu2rV5++eUyj586e7q6nMvX9dprr9XkyZPl5+enq6+++qyhalUp7tK96qqryjy+YMECXXTRRad9fkV/hlTl19wRLBaLWrRooRYtWmjIkCFq3ry5pk2bVqGA1zAMff7558rOzi7zH1eSk5N1/Phx+fr6VmXpAADUKwS8AADUA8Wdlm5ubmftgvv666910UUXacqUKSX2p6enn7XrKzw8vNT4gfbt20s6fYAbHR0tm82mHTt22BcTk8zFtNLT0xUdHS1JGjhwYJmjDYqP79ixo0QXYEFBgRITE+33L35tsbGxmjlzZol6nnrqqRLXPF2tFXkfT8fd3V2XXnqpLr30UtlsNt15551699139cQTT6hZs2ZnfJ8kadu2bSU6Z/Pz85WYmGivJy4uTpK0cePGs9ZosVg0bdo0XX755bryyiv1yy+/lCuMl8yAcffu3fauXUnavn27JJXqNi2P4te0cePG054TGhoqPz8/FRUVVer9j4uLk81m0+bNm0sthlUZ5/JnpSzFX+OdO3eWCBkLCwu1Z8+eEuF1XFyc1q1bp379+p31H0cqev+zfY9VhWuvvVZPPvmkDh8+rE8//bTKrnsm2dnZ+v7773X11Vdr5MiRpY7/+9//1rRp084Y8Jb3Z0h5nfrz65+2bdtWqWtWl9jYWAUFBenw4cMVet6CBQt04MABTZw4scTPeMnsZB43bpy+++47jR49uirLBQCgXmEGLwAA9UBYWJguvPBCvfvuu2X+5fzUsQpWq7VUd9mMGTPOOFu2mKenp/r371/io/hXkn18fCSZ4depBg8eLEl69dVXS+wv7kws/tXdiIiIUteWpC5duig0NFTvvPOO8vPz7c//6KOPSt2ruJvu1Ne3fPlyLV26tMR53t7eZdZakfexLKmpqSU+d3FxsYd2eXl5kk7/PvXv31/u7u56/fXXS9Q/ZcoUZWRk2N+nTp06KSYmRq+++mqpa5TVNeju7q6ZM2eqa9euuvTSS7VixYozvoZTvfnmmyWu/eabb8rNzU39+vUr9zWKhYaGqnfv3vrwww+1b9++Muu2Wq264oor9M0335QZBJ/t/R82bJhcXFw0ceLEUh22lemoPJc/K2Xp0qWLQkJC9P7776uwsNC+f9q0aSVGQ0hmB+rBgwf1/vvvl7rOiRMnlJ2dXeH7l/d7rCrExcXp1Vdf1aRJk9StW7cqu+6ZfPvtt8rOztb48eM1cuTIUh9Dhw7VN998Y/+zWJby/gwpr4iICHXo0EEff/xxiRE0c+fO1ebNmyt1zXO1fPnyMr9/VqxYodTU1FIjPM6meDzDgw8+WOo9v/XWW+1dwQAAoPLo4AUAoJ546623dMEFF6ht27a69dZbFRsbqyNHjmjp0qU6cOCA1q1bJ0kaOnSoJk6cqBtvvFE9e/bUhg0bNG3atDLn2VZE586dJUmPPfaYrrnmGrm5uenSSy9V+/btNWbMGL333ntKT09Xnz59tGLFCn388ccaNmzYGbvpJLOb9tlnn9Vtt92mvn376uqrr1ZiYqKmTp1aquahQ4dq5syZGj58uIYMGaLExES98847io+P1/Hjx+3neXl5KT4+Xl9++aVatGih4OBgJSQkKCEhodzvY1luueUWpaWlqW/fvoqMjNTevXv1xhtvqEOHDvbOtg4dOshqterFF19URkaGPDw87ItAPfLII3r66ac1aNAgXXbZZdq2bZvefvttde3a1d795uLiosmTJ+vSSy9Vhw4ddOONNyoiIkJbt27Vpk2bylzQyMvLS7NmzVLfvn11ySWXaMGCBWed4evp6anZs2drzJgx6t69u3755Rf99NNPevTRR8+6oNrpvP7667rgggvUqVMnjRs3TjExMdqzZ49++uknrV27VpL0wgsvaN68eerevbtuvfVWxcfHKy0tTatXr9Zvv/2mtLS0016/WbNmeuyxx/TMM8+oV69eGjFihDw8PLRy5Uo1atRIkyZNqlC9Vf1nxd3dXRMmTNC//vUv9e3bV1dddZX27Nmjjz76SHFxcSU6Rq+//np99dVXuv322zVv3jydf/75Kioq0tatW/XVV19pzpw56tKlS4XuHxoaWq7vsapy9913l/vc1atX67PPPiu1Py4uTj169CjXNaZNm6aQkBD17NmzzOOXXXaZ3n//ff30008aMWJEmeeU92dIRUyaNElDhgzRBRdcoJtuuklpaWl644031KZNm0pf80y+/vrrMschXHzxxWrYsKE+/fRTTZs2TcOHD1fnzp3l7u6uLVu26MMPP5Snp6ceffTREs8rKCjQs88+W+p6wcHBuvnmm/XNN9/o4osvlqenZ5n1XHbZZXrttdeUnJyssLCwqnmRAADUNwYAAKiT+vTpY7Rp06bEvl27dhk33HCDER4ebri5uRmNGzc2hg4danz99df2c3Jzc43777/fiIiIMLy8vIzzzz/fWLp0qdGnTx+jT58+9vPmzZtnSDJmzJhR7pqeeeYZo3HjxoaLi4shyUhMTDQMwzAKCgqMp59+2oiJiTHc3NyMqKgo45FHHjFyc3PLfe23337biImJMTw8PIwuXboYCxcuLFWzzWYznn/+eSM6Otrw8PAwOnbsaMyaNcsYM2aMER0dXeJ6S5YsMTp37my4u7sbkoynnnqqQu9jWb7++mtjwIABRlhYmOHu7m40adLEuO2224zDhw+XOO/99983YmNjDavVakgy5s2bZz/25ptvGq1atTLc3NyMhg0bGnfccYdx7NixUvdatGiRcfHFFxt+fn6Gj4+P0a5dO+ONN96wHx8zZozh4+NT4jkpKSlGfHy8ER4ebuzYseO0r6P4ubt27TIGDBhgeHt7Gw0bNjSeeuopo6ioyH5eYmKiIcn4z3/+U+oaxcemTp1aYv/GjRuN4cOHG4GBgYanp6fRsmVL44knnihxzpEjR4zx48cbUVFRhpubmxEeHm7069fPeO+9905b86k+/PBDo2PHjoaHh4cRFBRk9OnTx5g7d679eHR0tDFkyJBSz/vn99O5/lk53Xvw+uuv279Hu3XrZixevNjo3LmzMWjQoBLn5efnGy+++KLRpk0b+2vp3Lmz8fTTTxsZGRlnfA+eeuopQ5Jx9OjRUsfK8z1W1s+Xyt7vVJKM8ePH2z8vfo9O9zFmzJgyr+Pj41Pi2JEjRwxXV1fj+uuvP+29c3JyDG9vb2P48OGnPae8P0PO9L3/z58nhmEY33zzjdG6dWvDw8PDiI+PN2bOnFnmz6Wz+efrPlXx1+B0H8U/Z9avX288+OCDRqdOnYzg4GDD1dXViIiIMK688kpj9erVJa45ZsyY014vLi7O+OabbwxJxpQpU05b8/z58w1JxmuvvVah1woAAP5mMQwnmfAPAACAWmHs2LH6+uuvq6W7EKXZbDaFhoZqxIgRZY5kAAAAQP3GDF4AAACglsjNzS011/eTTz5RWlpauRfAAwAAQP3CDF4AAACglli2bJnuvfdeXXnllQoJCdHq1as1ZcoUJSQk6Morr3R0eQAAAKiFCHgBAACAWqJp06aKiorS66+/rrS0NAUHB+uGG27QCy+8IHd3d0eXBwAAgFqIGbwAAAAAAAAA4KSYwQsAAAAAAAAAToqAFwAAAAAAAACcFDN44ZRsNpsOHTokPz8/WSwWR5cDAAAAAABQJQzDUFZWlho1aiQXF3ozcXYEvHBKhw4dUlRUlKPLAAAAAAAAqBb79+9XZGSko8uAEyDghVPy8/OTZP6w8/f3d3A1AAAAAAAAVSMzM1NRUVH27AM4GwJeOKXisQz+/v4EvAAAAAAAoM5hJCXKi0EeAAAAAAAAAOCkCHgBAAAAAAAAwEkR8AIAAAAAAACAk2IGL+q0oqIiFRQUOLqMOs/NzU1Wq9XRZQAAAAAAANQ7BLyokwzDUFJSktLT0x1dSr0RGBio8PBwhsADAAAAAADUIAJe1EnF4W5YWJi8vb0JHauRYRjKyclRcnKyJCkiIsLBFQEAAAAAANQfBLyoc4qKiuzhbkhIiKPLqRe8vLwkScnJyQoLC2NcAwAAAAAAQA1hkTXUOcUzd729vR1cSf1S/H4z8xgAAAAAAKDmEPCizmIsQ83i/QYAAAAAAKh5BLwAAAAAAAAA4KQIeAEAAAAAAADASRHwArXI2LFjZbFYdPvtt5c6Nn78eFksFo0dO7bEuf/8GDRokObPn1/msVM/5s+fL0k6cOCA3N3dlZCQUIOvFAAAAAAAAFXB1dEFACgpKipKX3zxhV555RV5eXlJknJzczV9+nQ1adKkxLmDBg3S1KlTS+zz8PCQj4+PDh8+bN939913KzMzs8S5wcHBkqSPPvpIV111lRYuXKjly5ere/fu1fXSAAAAAAAAUMUIeIFaplOnTtq1a5dmzpyp6667TpI0c+ZMNWnSRDExMSXO9fDwUHh4eJnXOXW/l5eX8vLySp1rGIamTp2qt99+W5GRkZoyZQoBLwAAAAAAgBMh4EW9YBiGThQU1fh9vdysslgsFX7eTTfdpKlTp9oD3g8//FA33nijfaxCVZk3b55ycnLUv39/NW7cWD179tQrr7wiHx+fKr0PAAAAAAAAqgcBL+qFEwVFin9yTo3fd/PEgfJ2r/gfs9GjR+uRRx7R3r17JUmLFy/WF198USrgnTVrlnx9fUvse/TRR/Xoo4+W6z5TpkzRNddcI6vVqoSEBMXGxmrGjBn2Ob8AAAAAAACo3Qh4gVooNDRUQ4YM0UcffSTDMDRkyBA1aNCg1HkXXXSRJk+eXGJf8Wzds0lPT9fMmTO1aNEi+77Ro0drypQpBLwAAAAAAABOgoAX9YKXm1WbJw50yH0r66abbtJdd90lSXrrrbfKPMfHx0fNmjWr1PWnT5+u3NzcEjN3DcOQzWbT9u3b1aJFi0pdFwAAAAAAADWHgBf1gsViqdSoBEcaNGiQ8vPzZbFYNHBg1YfTU6ZM0f3331+qW/fOO+/Uhx9+qBdeeKHK7wkAAAAAAICq5VyJF1CPWK1Wbdmyxb5dlry8PCUlJZXY5+rqWuY4h1OtXbtWq1ev1rRp09SqVasSx0aNGqWJEyfq2WeflasrPyIAAAAAAABqMxdHFwDg9Pz9/eXv73/a47Nnz1ZERESJjwsuuOCs150yZYri4+NLhbuSNHz4cCUnJ+vnn38+p9oBAAAAAKgKRTZDX6zYp82HMh1dClArWQzDMBxdBFBRmZmZCggIUEZGRqkANDc3V4mJiYqJiZGnp6eDKqx/eN8BAAAAANXh06V79MT3m9S2cYB+/NfZm5qc3ZkyD6AsdPACAAAAAACgVsrJL9Rrv++UJG07kqUiG32KwD8R8AIAAAAAAKBWmrp4j1KO50mS8gttOnjshIMrAmofAl4AAAAAAADUOsey8/XO/F2SJFcXiyRp19HjjiwJqJUIeAEAAAAAAFDrvLNgl7LyCtUq3E8XxzeURMALlIWAFwAAAAAAAOWy6VCG1u1Pr/b7HM44oY+W7JEkPTyolZqH+Uoi4AXK4uroAgAAAAAAAFD7Hc44oRFvL5HNMPTH/RcqKti72u71+u87lFdoU7emwbqwZagycwskSbuOZlfbPQFnRQcvAAAAAAAAzuqNP3Yqr9CmgiJD7/+5u9rus+vocX216oAk6aFBLWWxWBQXanbw7qaDFyiFgBcAAAAAAABntC81R1+t3G///KtV+5V6PK9a7vXyr9tVZDPUv3WYujQNliTFNPCRJKUcz1d6Tn613BdwVgS8AAAAAAAAOKNXf9+uQpuh3i1C1S4yQLkFNn28dG+V3iO3oEiTft6inzYclsUiPTCwpf2Yj4erGgV4SmJMA/BPBLxALWCxWM74MWHCBO3Zs+e0x5ctWyZJKioq0gsvvKBWrVrJy8tLwcHB6t69uz744AP7vcaOHathw4adtaYDBw7I3d1dCQkJ1fWyAQAAAABOYGdylr5bc1CS9MCAFrq9T5wk6ZOle5STX1gl99hwIEOXvrFI7y40Rz/c3idOrcL9S5wTx0JrQJlYZA2oBQ4fPmzf/vLLL/Xkk09q27Zt9n2+vr5KSUmRJP32229q06ZNieeHhIRIkp5++mm9++67evPNN9WlSxdlZmZq1apVOnbsWIVr+uijj3TVVVdp4cKFWr58ubp3716ZlwYAAAAAcHKvzN0hmyENbNNQ7SID1aZRgJqGeGtPao6+WLFfN10QU+lrFxTZ9OYfO/XWvJ0qtBlq4Ouu54e31YA24aXOjQv11Z87Ugh4gX8g4AVqgfDwv//DFRAQIIvFUmKfJHvAGxISUupYsR9++EF33nmnrrzySvu+9u3bV7gewzA0depUvf3224qMjNSUKVMIeAEAAACgHtp0KMM+MuHei1tIkqwuFt3aO1aPfbtRUxYl6voe0XKzlv+XxAuLbFq7P10Ld6Tolw2HtSPZDGwHtw3Xs8PaKtjHvcznxYaac3h3JTOiATgVAS9Qh4SHh+uPP/7QnXfeqdDQ0EpfZ968ecrJyVH//v3VuHFj9ezZU6+88op8fHyqsFoAAAAAQG33ytztkqRL2zUqMTLhik6RemXudh1MP6FZ6w9peMfIM17nwLEcLdyeooXbj2rxrhRl5f492iHAy03PDEvQpe0iZLFYTnuNuFBzRMNuOniBEgh4UT8YhlSQU/P3dfOWzvAfp8ro2bOnXFxK/svo8ePmf9xefvlljRw5UuHh4WrTpo169uypyy+/XJdcckmF7jFlyhRdc801slqtSkhIUGxsrGbMmKGxY8dW1csAAAAAANRya/Yd029bkmV1seie/s1LHPN0s+rG82P0nznb9O6C3RrWoXGJcDYnv1DLd6dpwfajWrjjqHb/Y2G0AC83XdC8gfo0D1X/+Ian7do9VXHAuzctR/mFNrm7srQUIBHwor4oyJGeb1Tz9330kORetV2vX375pVq3bl3msfj4eG3cuFF//fWXFi9erIULF+rSSy/V2LFjSyy0dibp6emaOXOmFi1aZN83evRoTZkyhYAXAAAAAOqRl092717RqbFiT4arpxrdPVpvz9uprUlZmr/tqMIDPLXwZKC7MvGY8ots9nNdLFLHJkHq3TxUvVs0ULvIQFldKtYQ1dDfQz7uVmXnF2lfWraahfmd2wsE6ggCXsDJREVFqVmzZqc97uLioq5du6pr166655579Nlnn+n666/XY489ppiYsw++nz59unJzc0vM3DUMQzabTdu3b1eLFi2q5HUAAAAAAGqv43mFWrTTXAvmroual3lOgLebRnVrog8WJermj1fKZpQ83jjQS71bNFDv5qHq2ayBArzczqkmi8WiuDBfrT+QoZ3JBLxAMQJe1A9u3mY3rSPu62Dx8fGSpOzs8g2hnzJliu6///5S3bp33nmnPvzwQ73wwgtVXSIAAAAAoJbZcjhThiFFBHiqScjp/257c68Yfbpsr/IKbfJ0c9F5sSEnu3RDFRfqc8aZupURF2oGvLtTmMMLFCPgRf1gsVT5qARHSU1NVVJSUol9gYGB8vT01MiRI3X++eerZ8+eCg8PV2Jioh555BG1aNFCrVq1sp+fkZGhtWvXlrhGSEiIUlNTtXr1ak2bNq3E+ZI0atQoTZw4Uc8++6xcXfnRAQAAAAB12aaDGZKkNo38z3heRICXfrjrAqVm56lTkyB5ulmrta64UPPv9ruSy9fEBNQHpDSAk+nfv3+pfZ9//rmuueYaDRw4UJ9//rkmTZqkjIwMhYeHq2/fvpowYUKJUHb+/Pnq2LFjiWvcfPPN8vLyUnx8fKlwV5KGDx+uu+66Sz///LMuu+yyqn9hAAAAAIBaY/PhTElSfMSZA15JahnuJ6lmxiUUL7S26ygdvEAxi2EYxtlPA2qXzMxMBQQEKCMjQ/7+Jf9jk5ubq8TERMXExMjT09NBFdY/vO8AAAAAUHcMef1PbTqUqXdGd9aghHBHl2O3/UiWBryyUH6erlr/1IAqHwFRG5wp8wDK4uLoAgAAAAAAAFB75BfatP1IlqSzj2ioadEh3nKxSFm5hTp6PM/R5QC1AgEvAAAAAAAA7HYmH1dBkSF/T1dFBnk5upwSPFytigo2F31jDi9gIuAFAAAAAACA3aZD5gJr8Y38a+UIBObwAiUR8AIAAAAAAMBu0yFzgbU2jQIcXEnZ4kJ9JBHwAsUIeAEAAAAAAGC3+WTAGx9Ru+bvFvu7g5cRDYBEwIs6zDAMR5dQr/B+AwAAAIDzs9kMbT58soO3cS0NeMNOBrzJdPACEgEv6iA3NzdJUk5OjoMrqV+K3+/i9x8AAAAA4Hz2H8vR8bxCubu62Dtla5viug6mn9CJ/CIHVwM4nqujCwCqmtVqVWBgoJKTkyVJ3t7etXIofF1hGIZycnKUnJyswMBAWa1WR5cEAAAAAKik4vm7LRv6yc1aO/sCg33cFeTtpmM5BdqdcrzWzgoGagoBL+qk8PBwSbKHvKh+gYGB9vcdAAAAAOCcNtsXWKud4xmKxYX6atXeY9p9NJuAF/UeAS/qJIvFooiICIWFhamgoMDR5dR5bm5udO4CAAAAQB2w6VCGJOcJeHcdZQ4vQMCLOs1qtRI8AgAAAABQTsUjGuJreVdsbKiPJGnX0WwHVwI4Xu0cpgIAAAAAAIAadTQrT8lZebJYpFbhfo4u54xaNDTr23gww8GVAI5HwAsAAAAAAABtPmx278Y08JGPR+3+pe/OTYPkYpESU7J1OOOEo8sBHIqAFxUyefJktWvXTv7+/vL391ePHj30yy+/2I/n5uZq/PjxCgkJka+vr6644godOXKkxDX27dunIUOGyNvbW2FhYXrwwQdVWFhY0y8FAAAAAACc4u/5u7V7PIMk+Xu6KaGxWefSXakOrgZwLAJeVEhkZKReeOEF/fXXX1q1apX69u2ryy+/XJs2bZIk3Xvvvfrxxx81Y8YMLViwQIcOHdKIESPszy8qKtKQIUOUn5+vJUuW6OOPP9ZHH32kJ5980lEvCQAAAAAA6JT5uxG1e4G1Yj1iQyQR8AIWwzAMRxcB5xYcHKz//Oc/GjlypEJDQzV9+nSNHDlSkrR161a1bt1aS5cu1XnnnadffvlFQ4cO1aFDh9SwYUNJ0jvvvKOHH35YR48elbu7e7numZmZqYCAAGVkZMjf3zn+wwMAAAAAQG120X/nKzElW5/c1E29W4Q6upyzmr8tWWOnrlRkkJcWPdzX0eVUGTIPVBQdvKi0oqIiffHFF8rOzlaPHj30119/qaCgQP3797ef06pVKzVp0kRLly6VJC1dulRt27a1h7uSNHDgQGVmZtq7gMuSl5enzMzMEh8AAAAAAKBqHM8r1J7UbElSfCPnCBW7Ng2Wq4tFB46d0P60HEeXAzgMAS8qbMOGDfL19ZWHh4duv/12ffvtt4qPj1dSUpLc3d0VGBhY4vyGDRsqKSlJkpSUlFQi3C0+XnzsdCZNmqSAgAD7R1RUVNW+KAAAAAAA6rGthzNlGFJDfw818PVwdDnl4uPhqnaRJ+fw7mZMA+ovAl5UWMuWLbV27VotX75cd9xxh8aMGaPNmzdX6z0feeQRZWRk2D/2799frfcDAAAAAKA+KZ6/6wwLrJ2qRxxzeAECXlSYu7u7mjVrps6dO2vSpElq3769XnvtNYWHhys/P1/p6eklzj9y5IjCw8MlSeHh4Tpy5Eip48XHTsfDw0P+/v4lPgAAAAAAQNXYbA94nevv2z1iG0gyA16WmUJ9RcCLc2az2ZSXl6fOnTvLzc1Nv//+u/3Ytm3btG/fPvXo0UOS1KNHD23YsEHJycn2c+bOnSt/f3/Fx8fXeO0AAAAAAEDadDhDkvMFvJ2jg+RudVFSZq72pDKHF/WTq6MLgHN55JFHdMkll6hJkybKysrS9OnTNX/+fM2ZM0cBAQG6+eabdd999yk4OFj+/v7617/+pR49eui8886TJA0YMEDx8fG6/vrr9dJLLykpKUmPP/64xo8fLw8P55jxAwAAAABAXbLlcKY2HsyUxSK1iwx0dDkV4uVuVYcmgVqRmKalu1IV08DH0SUBNY6AFxWSnJysG264QYcPH1ZAQIDatWunOXPm6OKLL5YkvfLKK3JxcdEVV1yhvLw8DRw4UG+//bb9+VarVbNmzdIdd9yhHj16yMfHR2PGjNHEiRMd9ZIAAAAAAKjXXv99hyRpcNsINQr0cnA1FdcjNsQMeHen6truTRxdDlDjLAYDSuCEMjMzFRAQoIyMDObxAgAAAABQSZsPZWrw63/KYpHm3NNbLRr6ObqkClu2O1XXvLdMDXw9tPKxfrJYLI4u6ZyQeaCimMELAAAAAABQTxV37w5pG+GU4a4kdWwSKA9XF6Ucz9PO5OOOLgeocQS8AAAAAAAA9dCmQxmavSlJFot0d7/mji6n0jxcrerSNEiStHR3qoOrAWoeAS8AAAAAAEA9VNy9O7RdIzV30u7dYj1iQyRJS3cR8KL+IeAFAAAAAACoZzYdytCcTUdOdu82c3Q556xHnBnwLtudKpuN5aZQvxDwAgAAAAAA1DOv/WZ2717arpGahTl3964ktYsMlLe7VcdyCrQ1KcvR5QA1ioAXAAAAAACgltiXmqP3F+5WVm5Btd1j48EM/brZ7N79txPP3j2Vm9VFXZoGS2IOL+ofAl4AAAAAAIBawDAM/evz1Xru5y0a98lfyi+0Vfk9dh89rse/2yhJuqx9IzUL863yezhKzzjm8KJ+IuAFAAAAAACoBf7Ymqx1BzIkmV2oD369rsrmyabn5Gvij5s14JWFWrs/XV5u1trbvVuYJxkVf909YkPUKMBTkUFe1VAUUHu5OroAAAAAAACA+s4wDL16ci5ur+YNtHRXqr5fe0gRAV76v0taVfq6BUU2fbZsr177fYfSc8yxD31bhenRwa0UF1oLu3cPr5c+uVxq0EK69gvJK6jcT20XGaDF/9dXFoulGgsEah8CXgAAAAAAAAf7bUuyNhzMkLe7Va9d01F/bE3WAzPW6Z0Fu9Qo0FM39GhaoesZhqE/tibruZ+3aPfRbElSy4Z+enxoa/VqHloNr6AKFJyQvrlFOpEm7V9mBr3Xfyd5B5fr6QS7qK8IeAEAAAAAABzI7N7dLkka07Opgn3cNbJzpA6nn9D/5m7XUz9sUpifpwYlhJfreluTMvXsrC1atDNFkhTi4677BrTQ1V2i5GqtxdM65z4lpWyTfMIkGdLhddInl0k3/FDukBeoj2rxn2oAAAAAAIC679fNR7TpUKZ83K0a1yvWvv+uvs00qluUDEO6+4s1+n7tQRlnmE17NCtPj8zcoMGv/alFO1PkbnXRbX1iNe/BC3Vd9+jaHe7u+E1a8a65PWyyNGaWGfQmbZA+vlTKZuE04HTo4AUAAAAAAHAQm+3v2btjz2+qIB93+zGLxaJnLk9Qcmaeft+arLu/WKtfNx/Rc8MSFOj993m5BUX6cHGi3p63S8fzCiVJQ9pG6P8uaaWoYO+afUGVkZ0qfX+nud1tnNS8v7k9dpYZ7h7ZaD6O+UHyaeC4OoFaqhb/0w0AAAAAAEDd9uvmJG05nClfD1fdekr3bjFXq4veub6z7unfXFYXi35af1gDX12ohduPyjAMzVp/SP1fXqCXZm/T8bxCtYsM0Izbe+it6zo5R7hrGNKP/5aOH5EatJT6P/33sdCW0tifJN9wKXmT9OPdjqsTqMXo4AUAAAAAAHCAU7t3bzy/aYmu3FO5WV10T/8WuqhlmO79cq12p2Trhg9XKDbUx76AWri/px4a1FLDOjSWi4sTLTa25jNp6yzJxU264n3J/R+hdIPm0vDJ0qfDzU5eAKXQwQsAAAAAAOAAszclaWtSlvw8XHXLBaW7d/+pfVSgfvp3L43pES1J2n00W15uVt3bv4X+eKCPRnSKdK5wN2239MvD5nbfx6WI9mWf5x9pPuYcq5m6ACdDBy8AAAAAAEANs9kMvVbcvXtBjAK83cr1PC93q56+PEED2oRr+e5UXds9WuEBntVZavUoKpRmjpMKsqXoC6Se/zr9ud7B5mNehvk8K3EWcCr+RAAAAAAAANSwnzce1rYjWfLzdNXNF8RU+PnnN2ug85s58YJjf/5POrBS8giQhr8juVhPf65n4N/bJ45JvqHVXh7gTBjRAAAAAAAAarXDGSeUnpPv6DKqTNEp3bs3nR+jAK/yde/WGQdWSQteNLeH/E8KjDrz+VZXyTPA3D6RVr21AU6IgBcAAAAAANRau48eV9//LtCQ1xfpeF6ho8upEj9tOKwdycfl5+mqmyrRvevU8o5LM2+VjCIpYaTU7sryPc/r5JiGHAJe4J8IeAEAAAAAQK310uxtOlFQpIPpJ/TK3O2OLuecmd275uu45YLY+te9O+dRc3E1/0hpyH/L/7ziObx08AKlEPACAAAAAIBa6a+9aZq9KUkWi/n51MWJ2nQow7FFnaNZ6w9p19Fs+Xu66sYLmjq6nJq19Sdp9ceSLNLwyZJXUPmfSwcvcFoEvAAAAAAAoNYxDEPP/7xVknRN1ygNaRshmyE9/t1G2WzGOV1786HMSo97yMwtUEGRrVLPLbIZeu13c/burb1i5e9Zj7p3s45IP/zL3O75Lymmd8WeTwcvcFquji4AAAAAAADgn+ZsOqK/9h6Tl5tV9/RvIcOQ5m9L1pp96fpi5X5d271Jpa67fHeqrn5vmRoHemnK2C5qFe5f7uf+tvmIbvlklawuFjUJ9lZsAx/FhvooNtT35LavGvi6y1LccvwPP6w7qN1HsxXo7aax5zetVP1OyTCk78dLOalSw7ZS38crfg06eIHTIuAFAAAAAAC1SkGRTS/NNrt3b+kVo4b+npKk+we01MRZm/XCL1s0oE1DNfD1qPC1/9iWLEk6mH5CV7y9RK+P6qh+rRuW67nv/7lbktmJm5iSrcSUbP2+teQ5fp6uig31Vdyp4W+oj6KCvPX67zslmd27fvWpe3flB9LOuZLVQ7rifcm14l83OniB0yPgBQAAAAAAtcoXK/drd0q2QnzcNa53rH3/DT2i9fVfB7T5cKae/3mLXr6qQ4WvvXy3GRCG+nnoaFaebvlklR4b3Fo3XxBz2s5bSdqTkq3liWmyWKTv7jxfx/MKtfvoce06mq3dKdnaffS4DqafUFZuodbtT9e6/ellXifI201jejatcN1O6+g26deTHbsXT5TCWlfuOsXzeungBUoh4AUAAAAAALXG8bxCvfbbdknS3f2bl+h0dbW66LnhCRoxeYlmrj6oKztHqUdcSLmvnZ1XqA0HzUXaZtzWQ+8u3KXPV+zXsz9t0Y4jx/XMsAS5u5a9XNFXq/ZLkno3D1X7qEBJ0vnNGpQ4J7egSHtSs7X7qBn47j6arV0nw9+sXHPm7/iLmsnXo57EMYX50sxbpcJcKa6v1G1c5a9l7+A9VjW1AXVIPfmJAgAAAAAAnMH7C3cr5Xi+Yhr4aFS30nN2OzYJ0rXdmmja8n164vuN+vnfvU4byv7TX3uPqchmqHGgl5o28NHzw9uqWZifnvtps75ctV8FNluZXcGFRTZ9/dcBSdLVXaNOe31PN6tahfuXmutrGIZSjucrPSdfzcJ8y1VrnTD/eenwOnN+7uVvSy7l+zqViRm8wGmdw58sAAAAAACAqnMw/YR9zu2DA1vKzVp2bPHQwFZq4OuuncnH7eeXx4pEMxzsHmuGhRaLRTdfEKP3b+gii0Waufqg1uwr3SG6cMdRJWflKdjHXf3LOa/3VBaLRaF+Hmre0O+MYyDqlD2LpUWvmtuXvib5R5zb9ZjBC5wWAS8AAAAAAKg2uQVF+m7NQY3+YLnu+Owv5RYUlXmeYRh6dOYG5eQXqWvTIF2SEH7aawZ4u+mxIeYs19d/36H9aTnlqmV5YqokqXtMcIn9/Vo31IiOkZKkZ3/aIsMwShz/cqU5nmFYh8bl7hau13IzpG9vk2RIHUdL8Zed+zVP7eD9x9cHqO/4qQQAAAAAAKrc9iNZevrHTer+/O+658u1WrQzRb9sTNJT328q8/xv1xzUgu1H5e7qoheuaHfWTtdhHRqrR2yI8gptevL7jaVC2X/KLSjSuv3m/N3uMaXn9j44sKU83Vz0195j+mVjkn3/0aw8/b4lWdKZxzPgFD8/KGXsl4KaSoNeqJprFnfw2gqk/ONVc02gjiDgBQAAAAAAVSInv1BfrdqvEW8v1oBXFmrq4j3KOFGgxoFeGtMjWi4W6ctV+/X5in0lnnc0K08TZ22WJN3dr7niQs8+p9ZiseiZYQlys1o0b9tRzdmUdMbzV+87pvwimxr6eyg6xLvU8fAAT43rHSdJeuGXrcorNDuNv11zQIU2Q+2jAtUy3K9c70O9tuFraf2XksVFGvG+5FFF75mbt2T1MLeZwwuUwCJrAAAAAADgnGw8mKEvVu7T92sOKSuvUJJkdbGof+swjerWRL2ah8rqYlHDAE+9NHubnvp+k+Ij/NU+KlCSNOHHTUrPKVB8hL/G9Y4t932bhfnqtt5xenPeTj3942b1ah4qH4+yow77/N2YkNN2B9/WO1afr9infWk5+mTJXt3SK0ZfrTq5uFoXunfPKuOA9NN95nbvB6WoblV3bYvF7OLNOmzO4Q2KrrprA06OgBcAAAAAAFTY8bxC/bD2kL5YuU/rD2TY9zcJ9tbVXaN0ZedIhfl7lnjOHX3itHZfun7dfER3fPaXZv27l1buSdNP6w/L6mLRSyPbnXZhtdO5q28zfb/uoPanndCrv23XY0Piyzxv+W4z4O32j/m7p/LxcNUDA1ro4W826I0/dig21Ec7k4/Ly82qS9uf4yJh5ZW8Rdq/XOpwnWR1q5l7VgWbTfr2dnP+buPOZsBb1bxOBrx08AIlEPACAAAAAIByMQxD6w5k6IsV+/TDukPKyTfHGLhZLRrYJlyjujVRj9gQubiU3SFrsVj036va6/I3FysxJVvjp63WrqPmPNVxvWOV0DigwjV5ulk18bIE3fjRSn24eI9GdIpU6wj/EufkFRZp9b5jkqTzYk8f8ErSyM5Rmrp4j7YmZelfn6+RJA1uGyE/z2oOWwtOSAtekpa8LtkKpRPHpAvurd57VqVlb0l7/jRHKYx4v3rC6eI5vCeOVf21ASdGwAsAAAAAQD336m/bNWPVAfVvHaZrujUpFZBmnCjQ92sPavryfdqalGXfH9vAR6O6NdGITo0V4utRrnv5e7rpndGdNeytxVq6O9V+nbv7Na90/Re1CtMlCeH6ZWOSHvt2g76+vWeJkHn9gQzlFdrUwNf9rPN9rS4WPT4kXqOnLLcH2Fd1iax0beWya540617pWOLf+9Z9KZ1/jzmaoLZL2iD9PtHcHjRJComrnvt4BZmPdPACJRDwAgAAAABQjxXZDH24KFGZuYX6eOlefbx0r9pHBWpU1yg1beCjr1bt188bDiu3wCZJcnd10ZC2Ebqma5S6xQSfdp7tmbQM99OLI9vp3yc7ZF8c2U6ebtZzeh1PXhqvhduPavW+dH25ar9GdWtiP1Y8f7e89V7QvIEuahmqeduOKqaBzxnHOpyT7FTp18ekdZ+bn/s1kvpPkH64Szq6RTqyUQpvWz33riqF+dLMcVJRvtRysNRpTPXdy97BS8ALnIqAFwAAAACAemxrUqYycwvl425V7xahmrv5iNbtT9e6/eklzmvZ0E/XdIvS8I6NFejtfs73vax9I7lYJDeri7o2PfcANSLAS/de3ELP/rRFL/yyVQPiG9q7iped7BTuVoH7TLw8QU//uEnXnRddqRD7jAxDWveFNOfRk2GlRep2q9T3CcnTX9ryg7R1lrRhRu0PeJe9JSVvlrwbSJe9Ub0dx14nv3508AIlEPACAAAAAFCPLTu5+FjXmGBNHt1ZR7Py9M3qA/pq5X4dyczV4LYRGtW9iTpGBVZ50Dm0XaMqvd7Ynk31zeqD2nI4U5N+2ar/XtleBUU2/bXXnNnaPTak3NeKCvbWB2O6Vml9kqTUXeY4hsQF5udh8dKlr0tRp9yr3VUnA95vpH4TJJeKLTxXY9L3m3ODJWnAs5JPg+q9Hx28QJkIeAEAAAAAqMeWn+xuPe9k+Bnq56Hb+8Tp9j7VNEe1GrlaXfTc8ARdMXmJvv7rgK7sHCl3Vxfl5Bcp0NtNLRv6Oa64okJzAbUFL0qFuZKrp9TnYannv0ovSNZ8oOThL2UekPYtkZpe4Jiaz2bOI1JBjtSkp9T+muq/Hx28QJlq6T8BAQAAAACA6mazGVqxxwzLulfXnNka1qlJkK7pas7fffy7jVq8M0WS1LVpcImF12rcn/+Vfn/aDHdj+kh3LJF63Vc63JUkN0+p9WXm9oYZNVtnee34Tdryo2SxSkP+WzOLwdHBC5SJgBcAAAAAgHpq25EspecUyMfdqoTGAY4up8o8PKilQnzctSP5uN6ct1OSgwNsm01a/Ym53f9p6YbvpZCzdEi3u9J83PSduZBZbVKQK/38gLnd/XapYZuauS8dvECZCHgBAAAAAKinihcf69w0WG7WuhMRBHq769HBrSVJuQU2SVL3mPLP361y+5dJmQfNsQvdby9ft2vTXpJvuJSbLu38rdpLrJAlr0vHEs36Lvy/mruvvYP3WM3dE3ACdeenNwAAAAAAqJBl9vm7dWM8w6lGdGps79r183BVfCN/xxVTPGah9aXm+IXycLFKCVecfP5X1VNXZRzbI/35P3N74HOSZw2+r8UdvHmZUlFBzd0XqOUIeAEAAAAAqIdsNkMrEovn7zqwu7WaWCwWPT+irSKDvHTteU1kddT83aICc8yC9HdgW17FYxq2/SLlZlZpWZX2y/+Zc4Sb9qr46zlXXoGSTn4d6eIF7Ah4AQAAAACoh7YnZ+lYToG83KxqF1l35u+eKi7UV4se7qtHLmntuCJ2zTMXBfMJNRdXq4iIDlJIMzNQ3fpTtZRXIam7pO2/nFxY7X81s7DaqVyskufJ71Xm8AJ2BLwAAAAAANRDy3ebAVmXpkF1av5urbPxa/OxzXDJ6lqx51osUturzO3aMKZh/cka4i6SQls6pgb7HF4CXqAYP8EBAAAAAKiH/p6/W/fGM9Qa+TnSllnmdtsrK3eNtiPNx93zpawjVVJWpRiGtP5Lc7s4dHYELxZaA/6JgBcAAAAAgHrGMAwtt8/frXsLrNUa22dLBdlSYBMpsmvlrhESJzXuIhk26ZubzdDYEQ7+JR1LlNy8pVZDHFOD9HcHLyMaADsCXgAAAAAA6pkdyceVlp0vTzcXtYsMdHQ5ddeGk+MZEkae27zaS16S3P2kPX9K069yTMhbPJ6h5WDJw7fm71/MixENwD8R8AIAAAAAUM8sPzmeoXN0kNxdiQaqxYlj0s655nbxmIXKiuwsjf5Gcvc1Q97Pr67ZkLeoUNo009xu58DxDBIdvEAZ+CkOAAAAAEA9s+zkAmvnxTB/t9ps+VEqypfC4qWGbc79ek26S6NnmiFv4kLp82tqLuTdPV/KPip5h0hxfWvmnqdDBy9QCgEvAAAAAAD1iDl/1+zg7V6TC6xt+vbvkQX1gX08wxVVd80m3f/u5E1cIH0xSsrLqrrrn86Gk+MZ2oyQrG7Vf78z8Q4yH+ngBewIeAEAAAAAqEd2HT2ulOP58nB1UfuogJq56b5l0oyx0sxbpezUmrmnI2UlmV220rmPZ/inJudJ131thry750vvXSQd2Vy19zhVfra0ZZa57ejxDNIpHbzHHFsHUIsQ8AIAAAAAUI8Uj2fo1CRIHq7W6r9hUaH00/3mtmGT0nZV/z0dbdO3kgwpsqsU1LTqrx/dQ7rhe8mvkZS6Q3q/r7Tui6q/jyRt+0UqyDZfR2TX6rlHRTCDFyiFgBcAAAAAgHqisMimnzccliSdV1PjGVa+Lx3Z+Pfnabtr5r6OtGGG+dj2yuq7R2QX6fY/pdiLpMIT0re3ST/8WyrIrdr7rP/SfGx7pWSxVO21K4MZvEApro4uAAAAAACAmrQ3NVsHj50otT8i0EvRwd5ycakFIVY1yC+06e4v1mjJrlS5ulg0MKFh9d80K0n64zlz2ydMyk6u+wFv2m7p4F+SxUVqM7x67+XTwJzJu/A/0vwXpNUfS4fWSFd9LAXHnvv1s1Oknb+b221rwXgGqWQHr2HUjtAZcDACXgAAAABAvbE/LUf9X16ggiKjzOO+Hq6Kj/BXfCN/JTQOUJtG/moW5is3q3P/AmxuQZHGT1ut37cmy93qoreu66RW4f7Vf+NfH5fys6TGnaXWl0q/Taj7Ae+Gb8zHmD6Sb1j138/FKl34f+b4hJm3SknrpXcvlIa9LbUeem7X3vStZBRJEe2l0BZVUu45K+7gtRVI+cclDz/H1gPUAgS8AAAAAIB644+tySooMuTn6aqIAE/7/iKbof3HTuh4XqFW7EnTij1///q3u6uLWof7Kb5RgBIa+6tNowC1CveTp1sNzK+tAifyizTu01X6c0eKPFxd9N4NXdSnRWj13zjxz5OjCizSkP9JGQfM/XU54DWMU8YzVPHiamfTrJ9025/S1zdK+5dLX14n9bhL6j9BsrpV/Hq2ImntNHO7tnTvSpK7t+TqKRXmml28BLwAAS8AAAAAoP5YtDNFknR7nziNv6hZiWMFRTbtOnpcmw5matOhTG08lKEthzKVlVeodQcytO5Ahv1cq4tFzUJ91eZk4Bsb6qOoIC9FBnnXmuC3yGboUPoJ3T9jnVYkpsnb3aopY7qqR1wNzN4tKpB+fsDc7nqz1KijZHU3P6/LAe+RjVLKNsnqYXYs17SAxtLYn8xO6aVvmh8HVklXTpX8G5X/Ojab9OO/zXEPVo+aD6vPxitIyjpszuENinZ0NYDDEfACAAAAAOqFwiKblu1KlSRd0KxBqeNuVhe1CvdXq3B/XdHZ3GezGdqXlmMPfDcdytSmgxlKzc7XtiNZ2nYkSzNXHyxxnVA/D0UHe+u+i1uoZxn3qS5bkzL1ydK92puarf1pJ3Qo/YQKbeYoCj8PV310U1d1jg6umWKWvS0d3Sp5N5D6Pm7uC2pqPp44ZnZeetdQLTVpw9fmY/OLJc8Ax9RgdZMGPidFdZe+Hy/tXya900u64gMp7qKzP98wpNn/J635zJwjPOI9yS+8+uuuCK9gM+DNYaE1QCLgBQAAAADUE+sPZigrr1ABXm5KaFy+8M3FxaKmDXzUtIGPhrSLkCQZhqEjmXnadChDGw9mavPhDO1NzdGBkyMejmbl6WhWnv776zbNrKGAd9WeNI2dulLH8wpL7HezWtSioZ8mjWirdpGBNVKLMg5K8180ty+eaHZbSpK7j+QbLh1Pko4l1r2A12aTNp6cv9v2SsfWIknxl0kN20hfjZGObJA+HS5d9KjU6wHJ5TQzpQ1D+v1pacW75ufDJktthtVYyeVW/L1z4phj6wBqCQJeAAAAAEC9sGiHOZ6hZ1yIrC6WSl/HYrEoPMBT4QGe6te6oX2/YRhKzynQ5sOZuu6D5Vq7P10ZOQUK8K7E/NMKWLIrRbd8vEo5+UXq2jRI13Rtoqhgb0UFe6mhn6dczuG1VsqcR6SCbCnqPKn9qJLHgmPNgDct0Vx4rS45sELK2C+5+0ktBjq6GlNInHTLXOnnB6U1n0rznpP2LZNGvC/5lDGq48//SoteMbeHvCy1v6Zm6y2v4n80oIMXkETACwAAAACoJ4rn755fTV21FotFQT7uOr9ZAzUL89XO5ONatDPF3vlbHRZsP6pxn6xSXqFNvZo30HvXd5GXuwNnAO/8Xdr8vWSxmgur/bNTNDhW2rekbs7hLV5crfVQyc3LsbWcys1LuvxNqUkP6af7pV2/S+/2kga9ILlYpeyj5kfqLmnd5+ZzBjxnzk6urewdvAS8gETACwAAAACoB7LzCrVmn/nr3GXN361qfVqEamfycS3cfrTaAt65m49o/LTVyi+yqV+rML11XSfHLvBWmGd2ikpS99uk8ITS5wTHmI91LeAtKpA2fWduJ9SyBcmKdbxOatRB+vJ6KW2X9NX1ZZ930WNSz7tqtLQK8zoZ8NLBC0gi4AUAAAAA1AMr9qSpoMhQZJCXokO8q/1+fVqEasqiRC3YflSGYchiqdoxCT9vOKx/f75GhTZDlySE67VrOsrd9TRzVWvKktfN4NC3oXTh/5V9TnCs+VjXAt7dC6ScFHNRudg+jq7m9Bq2kcbNN8do7FkkeYdIPqGSTwPzsXFnqdVQR1d5dnTwAiUQ8AIAAAAA6rzi+bsXNGtQ5WFrWbrFBMvD1UVJmbnafuS4Wob7Vdm1v1tzUPd9tVY2Q7q8QyP978r2crU6ONw9tlda+D9ze8BzkudpFrGrqwHvxq/NxzbDJGv1zlw+Z57+0uVvObqKc0MHL1CCg/8LAAAAAABA9VtczfN3/8nTzarzYs1FrBZuP1pl1/1y5T7dezLcvbJzpF6+qoPjw11Jmv1/UuEJqWkvqe0ZRhQUj2jIPirlZtZMbdWt4IS05Udzu+2Vjq2lvqCDFyihFvxXAAAAAACA6pOclautSVmSpJ5xITV23z4tQiWZC6FVhU+W7tHD32yQYUijz2uiF69oJ6tL9Xcjn9W22dK2nyUXV2nwf6UzdUh7BphjDCTpWGLN1Ffdts+R8o9LAVFSZDdHV1M/0MELlEDACwAAAACo05buSpUktWnkrxBfjxq7b++TAe+KxDTl5Bee07U++HO3nvx+kyTp5gti9MzlCXKpDeFuwQnpl4fM7R7jpbBWZ3+OfUxDHQl4N8wwHxOukFyIWWqEvYP3mGPrAGoJfvIAAAAAAOq0U+fv1qS4UB81DvRSfpFNy3dXvtPwzT926NmftkiSxl8Up8eHtK6ROcLl8ufLUvpeyb+x1Puh8j2nLs3hPZEu7Zhrbp9pNAWqVnEHb16mVFTg2FqAWoCAFwAAAABQZxmGoUU1PH+3mMViUZ+WlR/TYBiG/vfrNv331+2SpPsubqEHB7aqPeFu6i5p8avm9sDnJQ/f8j2vLgW8W2dJRXlSaCupYYKjq6k/vAIlnfxzQBcvQMALAAAAAKi7dqdk63BGrtytLuraNLjG79+7uRnwVnShNcMwNOmXrXrjj52SpEcuaaV/92te5fVVmmGYoxmK8qW4vlL85eV/bl0a0bDha/MxYeSZZw+jarlYzXnOEnN4ARHwAgAAAADqsMUnu3e7NA2Sl7u1xu/fs1mIXF0s2p2SrX2pOeV6js1maMIPm/TeQrPDdcKl8bqtT1x1lllxW36Udv4mWd3PvrDaPwXHmI/O3sGbdURKXGBut73CsbXUR/Y5vAS8AAEvAAAAAKDOKp6/W9PjGYr5e7qpU5MgSdKCHWfv4j2eV6hHv92gj5fulcUiTRrRVmPPj6nuMismP1ua/Yi5ff7dUkgFw+fiDt6sQ1J++ULvWmnzd5Jhkxp3/vs1oeYUz+GlgxeQq6MLAAAAAACgOuQX2rR0d6qkml9g7VR9WoZqxZ40Ldx+VNefF23ffyK/SH9sTdbmwxnalpSlrUlZOnDshCTJxSL9Z2R7XdE50lFln96Cl6TMA1JAE+mC+yr+fK8g89frczOkY3ukhvEljx9aI7l5S6Etq6TcarNhhvnY9krH1lFf0cEL2BHwAgAAAADqnCKbofu+Wqus3EKF+LgroXGAw2rp0yJU/5mzTUt2pii/0Kac/EJ9snSvPlqyR2nZ+aXObxzopceGtNbgthEOqPYsjm6Tlr5pbl/youTuXfFrWCxmx+uhNeaYhlMD3rTd0gcXSx5+0v1bJVePqqm7qqUlSgdWShYXqc1wR1dTP9HBC9gR8AIAAAAA6hSbzdDD36zXrPWH5Wa16L9XtZfVxXELYMVH+CvEx12p2fm6+4s1WrD9qHLyiyRJkUFe6tU8VK3C/dQy3E8tG/opyMfdYbWekWFIP90v2QqlFoOkVoMrf61TA95TrZoq2QrMrswDq6Sm559bzdVl4zfmY9Nekl+4Y2upr+jgBewIeAEAAAAAdYZhGJrw4yZ9/dcBuVik16/pqItahjm0JhcXi3q3CNW3aw7ql41JkqTWEf6648I4DU4Il6vVSZbH2fiNtOdPydXT7N49F8Uza08NeAvzpDWf/f357vm1P+BtO9KxddRndPACdgS8AAAAAIA6wTAMvTB7qz45uUDZ/65qr0tqyZiDUd2aaM6mJLWLDNAdFzZT7+YNZLE4rqu4wnIzpTmPmdu97peCmp7b9coKeDd/X7IbM3GBpMfO7T7V4cgmKXmzZHWXWl/q6GrqL29z8UKdOObYOoBagIAXAAAAAOAUbDZDx/MLdTy3UFm5hcrKLVBW3t/bGw9m6vMV+yRJzw5L0PCOtWeBsm4xwdo8cZCjy6i8+S9Ix5OkoBip57/P/Xr2gDfx732rPjQfO442O3kP/iXlZZnzeGuTDV+bj80uNheMg2P4hJqPh9dLecclD1/H1gM4EAEvAAAAAMAh9qflaHlimhnU5hbqeF6hfbs4tD1uD3DN4+Xx+JDWuq57dDVXX48c2SQtf8fcHvxfyc3z3K9ZHPBm7DdHM6TulPYtlSxW6aLHpT2LpGN7pL1LpBYDz/1+VcUwpI0nA17GMzhW7IWSXyMpY5/0y0PSsLcdXRHgMAS8AAAAAIAaZxiGRr2/TAeOnajwc92sFvl5usnP01W+Hq4nH93k7+mqPi1DdXmHxtVQcT1VvLCaUWSOI2jev2qu6xMquftK+celY3vNxdUkqdUQyT9CiuljBry7F9SugPfASil9n1l7CyfuyK4LPAOkK96XPr5UWjtNir1Ianelo6sCHIKAFwAAAABQ4/al5ejAsRNys1o0oE24/O1h7anBrbltfrjZw1wPVxfnml/rzNZ9bnbWunlLg16ouutaLFJwjJS0QTqyQVr3hbm/y03mY+yF0uqPzYXWapPiTuZWQyR3b8fWAqnpBVLvB6UFL0qz7pUiO//dHQ7UIwS8AAAAAIAa99dec2Gkto0D9Na1nRxcDcp0Il369Qlzu89DUkAVzzQOjjUD3oX/k/KzpOA4s3NXkmJ6m4/Jm6TjRyXf0Kq9d2Uc3SZtnGlu9/yXY2vB33o/JCX+Ke1bIn19k3TTr5Kru6OrAmqUi6MLAAAAAADUP6v3mQFvpyYsUlVrzXteykmRGrSQzhtf9dcv7rRM3mQ+drlRcjkZU/g0kBq2NbcTF1T9vStj4X8lGVKroVJ4W0dXg2JWV3NUg2egdGiN9MdER1cE1DgCXgAAAABAjftrb7okqXM0AW+tlJUk/XVyLu4lL1VPR2RQzN/bVg+pw3Ulj8ee7OatDQFvys6/F1fr/aBja0FpAZHS5W+Z20vekHb85th6gBpGwAsAAAAAqFHH8wq1LSlTktSJgLd2WvGeVJQvRXWX4i6qnnucOiu1zXDJO7jk8eJxDbtrQcD75/8kw2YurNaog6OrQVlaD5W63mJuz7pHKipwaDlATWIGLwAAAACgRq3bny6bITUO9FJDf09Hl4N/yjsurZxiblfnrNlTA96uN5c+Ht1TcnGV0vdKaYnmomyOkLZbWv+lud37IcfUgPIZ8KyUnSL1fkCyujm6GqDGEPACAAAAAGpU8QJrjGeoAcf2SLvmSe2ulty9y/ectdOk3HQzgG05uPpqC2gs9fy3uR3ZtfRxD19z/76l5pgGRwW8f74sGUVSs/5SZGfH1IDycfOSrvrY0VUANY4RDQAAAACAGvX3AmuBji2kPvjpfvPX1T8dLp04dvbziwqlpSdnmfYYL7lYq7U8DXjG/LBYyj7u6DENx/ZK6z43t/s87JgaAOAsCHgBAAAAADXGZjO02t7BG3yWs3FOigqkvUvN7f3LpKmDpcxDZ37O1h/NkQjeIVL7a6u/xrOxL7S2ULLZav7+i16RbIVS7IVSVLeavz8AlAMBLwAAAACgxuw6elyZuYXycrOqVYSfo8up25LWSwXZkruf5BsuJW+WpgyUUnaWfb5hSItfN7e73lr+kQ7VqXEXyc1Hykkx669JSRukNZ+Z233+r2bvDQAVQMALAAAAAKgxxeMZ2kUGyM3KX0mrVXH3bnRP6eY5UnCclLFP+nCAdHB16fP3LZUOrZZcPaWut9Rsrafj6m7WL0m759fMPfOypF8fl967ULIVSE17SdE9aubeAFAJ/NcUAAAAAFBjWGCtBu0rDnh7SEFNpZvmSBHtpZxU6aOh0pzHpLTdf5+/5A3zsf0oyTe0xss9LfuYhmqew2sY0oavpTe7mu+FrdBcZO6KD6r3vgBwjlwdXQAAAAAAoP5YvS9dktSpCQFvtTIMad8yc7vJyQ5Y31BpzCzpq+vNbtilb5oLqjUfILUeKm37WZLFXFytNom90HxM/FPKzZA8A6r+HrmZ0pej/w6Rg5pKl7wktRhY9fcCgCpGBy8AAAAAoEak5+RrZ/JxSVInOnirV+pOc26t1UNq1OHv/Z7+0uhvpWtnSM0ulmRIO+ZIP/zLPN5ysNSguSMqPr2GCVJoa6nwhLT+q+q5x8r3zXDX1VO66DHpzuWEuwCcBgEvAAAAAKBGrDnZvRvbwEfBPu6OLaau27vEfIzsIrl6lDzm4iK1GCCN/lr612rpvDsljwDJxU3qdV/N13o2FovU5SZze9WHZndyVdvwtfl4yUtSn4ckN8+qvwcAVBMCXgAAAABAjSheYK0j4xmqX/H83SZnWRwsJE4aNEm6f6t07yYzEK6N2l0luXpJyZul/cur9tpHNpvXdXGT4i+r2msDQA0g4AUAAAAA1AgWWKtB5Q14i7l7S34Nq6+ec+UVKLW9wtxe9WHVXnvjye7d5hdLXnxvAnA+BLwAAAAAgGpXWGTTuv3pkqRO0YEOraXOyzwsHdsjWVykqG6OrqbqFI9p2PSdlJNWNdc0jL/HM7QdWTXXBIAaRsALAAAAAKh2245kKTu/SH4ermoe5ufocuq2fSfn7zZMMBdVqysadZIi2ktFedLa6VVzzQOrpPS9kpuP1OKSqrkmANQwAl4AAAAAQLVbfXI8Q4cmgbK6WBxcTR23b5n5WN7xDM6iOhZbKx7P0GqwOaYCAJwQAS8AAAAAoNqt3pcuSerEAmvVb+/J+bvRdSzglaSEkZK7n5S2S0pceG7XshVJG2f+fV0AcFIEvAAAAACAapWTX6g/d6RIkjqxwFr1OpEuHdlobte1Dl5J8vCV2l9tbp/rYmuJC6XsZHNhtbi+514bADgIAS8AAAAAoFq98cdOpRzPU2SQl7rHBDu6nLrtwEpJhhQUI/mFO7qa6tH5RvNx6ywp60jlr1M8niH+csnV/dzrAgAHIeAFAAAAAFSbncnH9cGfuyVJEy5tI083q4MrquP2nlxgLbqnY+uoTuEJUmQ3yVYorfm0ctcozJM2/2huM54BgJMj4EWFTJo0SV27dpWfn5/CwsI0bNgwbdu2rcQ5F154oSwWS4mP22+/vcQ5+/bt05AhQ+Tt7a2wsDA9+OCDKiwsrMmXAgAAAKCaGYahJ7/fqIIiQ/1ahal/fENHl1T37Ts5f7cujmc4VfFia399bM7Sragdc6W8DMmvUd0OwwHUCwS8qJAFCxZo/PjxWrZsmebOnauCggINGDBA2dnZJc679dZbdfjwYfvHSy+9ZD9WVFSkIUOGKD8/X0uWLNHHH3+sjz76SE8++WRNvxwAAAAA1WjW+sNasitVHq4umnBZG0eXU/cV5EoH/zK363rA22aY5BkoZeyTdv5e8ecXj2dIGCG50FUOwLm5OroAOJfZs2eX+Pyjjz5SWFiY/vrrL/Xu3du+39vbW+HhZc97+vXXX7V582b99ttvatiwoTp06KBnnnlGDz/8sCZMmCB3d2YfAQAAAM7ueF6hnv1psyRp/EXNFBXs7eCK6oFDa6SifMknVAqJc3Q11cvNS+pwnbTsLemvqVKLAeV/bl6WtO3k320Trqie+gCgBtHBi3OSkZEhSQoOLrlQwrRp09SgQQMlJCTokUceUU5Ojv3Y0qVL1bZtWzVs+PevZw0cOFCZmZnatGlTmffJy8tTZmZmiQ8AAAAAtderc7frSGaeokO8Na53rKPLqR/2LjYfm/SQLBbH1lITupxcbG37bCnjQPmft/N3qfCEFBwrNepYPbUBQA0i4EWl2Ww23XPPPTr//POVkJBg33/ttdfqs88+07x58/TII4/o008/1ejRo+3Hk5KSSoS7kuyfJyUllXmvSZMmKSAgwP4RFRVVDa8IAAAAQFXYlpSlqUv2SJKevoyF1WrE1p+kP/9nbjft5dhaakqD5uZrNWzS6k/K/7x9y8zHuL71IwgHUOcxogGVNn78eG3cuFGLFi0qsX/cuHH27bZt2yoiIkL9+vXTrl27FBdXuV8TeuSRR3TffffZP8/MzCTkBQAAAGqh3IIiPfTNehXZDA1qE64LW4Y5uqS6b9lkafYjkgwztOw4+qxPqTO63Cjt+dNcbK33g5LV7ezP2X8y4I06r3prA4AaQgcvKuWuu+7SrFmzNG/ePEVGRp7x3O7du0uSdu7cKUkKDw/XkSNHSpxT/Pnp5vZ6eHjI39+/xAcAAACAmmcYxhmPPfj1eq3bny5/T1c9cWl8DVZWDxUVSj8/KM3+P0mG1HmsdO1Xkns9mnfc6lLJu4F0PMkc1XA2+dnS4fXmdpPu1VsbANQQAl5UiGEYuuuuu/Ttt9/qjz/+UExMzFmfs3btWklSRESEJKlHjx7asGGDkpOT7efMnTtX/v7+io/nfwABAACA2ia/0KYf1h3SyMlL1OmZufp2TdnzTl/5bYd+XHdIri4WvXN9ZzUO9KrhSuuRvOPSF9dKK94zP794ojT01fJ1sNYlru5Sp+vN7VUfnv38g6slo0jyayQF8FuhAOoGRjSgQsaPH6/p06fr+++/l5+fn31mbkBAgLy8vLRr1y5Nnz5dgwcPVkhIiNavX697771XvXv3Vrt27SRJAwYMUHx8vK6//nq99NJLSkpK0uOPP67x48fLw8PDkS8PAAAAwCmSs3I1ffk+TV++T8lZefb99365Tst2pWnCZW3k5W7O1/12zQG9/vsOSdLzI9qqZ1wDh9RcL2QekqZfLSWtl1w9peHvSm2GOboqx+k0Rlr0qrTrDyltt7l42ukUj2do0p35uwDqDAJeVMjkyZMlSRdeeGGJ/VOnTtXYsWPl7u6u3377Ta+++qqys7MVFRWlK664Qo8//rj9XKvVqlmzZumOO+5Qjx495OPjozFjxmjixIk1+VIAAAAAlMEwDK3Zn66Pl+zRzxsOq6DIHMkQ5ueh67pHq8gw9MYfO/Tlqv1auz9db13XSWnZ+Xr46w2SpDsujNNVXeiMrDZJG6RpV0lZh8zRBKO+kKK6OroqxwqOkZr1k3b+Jv31kdnNfDr7V5iPUYxnAFB3WIwzDVACaqnMzEwFBAQoIyODebwAAADAaaQez9M3qw9oYJtwRYf4nPHc3IIizVp/WB8v2aMNBzPs+7tEB+mGnk01qE243F3NKX9Ldqbo31+sVcrxPHm7W+VmdVHGiQJdkhCut67tJBcXOiOrxY650oyxUv5xqUEL6boZUlBTR1dVO2z9yRxZ4d1Aum+z5FrGb4fabNJLTaXcDOnWeVLjTjVeJlAeZB6oKDp4AQAAAKCOevDr9fpja7L+O2e7brygqe66qJn8PEvOaD2UfkKfLdurL1buV1p2viTJ3dVFl7dvpDE9myqhcUCp6/Zs1kA/332B7vlirZbsSpVUpPaRAXr5qg6Eu9Vl5QfSzw+Z82Ob9pKu/lTyCnJ0VbVH84HmXN2sQ9KWH6W2I0ufk7LNDHfdvKXwtjVfIwBUEwJeAAAAAKiDNh7M0B9bzYWN84tsenfBbn3z10E9NLClrugcqZV70vTxkj36dfMRFdnMX+xsFOCp0T2idU3XJgr2cT/j9cP8PPXpzd313sLd2ngwQ09dFm+fx4sqZLNJc5+Qlr5pft7hOnMxNdczf33qHaur1HmMNH+StGpq2QHvvpPzdxt3rn+L0QGo0wh4AQAAAKAOenv+TknSZe0b6fIOjfTsT1uUmJKth75Zr+d+3qKMEwX2c3vEhmhMz6bq3zpMrlaXct/D6mLRHRfGVXntOCk/R5p5q7R1lvl538elXg+wONjpdLxeWvCitHeRdHSbFNqy5HHm7wKoowh4AQAAAKCO2ZmcpV82JkmSxl/UTC3D/dSreag+XrJHr/++QxknCuTlZtWITo11Q4+mahnu5+CKUUrWEenza6RDqyWruzRsctldqfhbQGOpxSXStp/MLt5LXih5fP/JDt4m59V8bQBQjQh4AQAAAKCOeXveLhmGNCC+oT28dXd10a29YzWiU2NtPJSpDlGBCvDi19RrpeQt0rSrpIx9klewdM10KbqHo6tyDl1uMgPeddOlfk9K7t7m/uPJUtpuSRYpsqtDSwSAqlb+370BAAAAANR6+1Jz9P26Q5Kku/o2K3U8xNdDfVqEEu7WVofXS1MGmOFucJx0y2+EuxUR11cKbGIuprbp27/3719uPoa1lrwCHVIaAFQXAl4AAAAAqEMmL9ilIpuh3i1C1S4y0NHloKJWvCvlZUqR3cxwN4QZxxXi4iJ1vtHcXvXh3/uLA17m7wKogwh4AQAAAKCOSMrI1Td/HZAk3XVR6e5dOIH9K83HXvdL3sGOrcVZdRwtubhJB1eZHdGStI+AF0DdRcALAAAAwOEMw9DKPWm6/dO/NOq9ZUrLznd0SU7pvYW7lV9kU7eYYHWLIRx0OifSpZRt5nZkF4eW4tR8w6TWl5rbf02VCnKlw2vNz5sQ8AKoe1hkDQAAAIDDFNkMzdmUpPcW7tba/en2/a//vkMTLmvjuMKcUMrxPE1fsVcS3btO6+Aq8zE4VvJp4NhanF2XG6VNM6X1X0ktB0tF+ZJPmBQU4+jKAKDKEfACAAAAqHE5+YX6+q8D+uDPRO1Ly5Ekubu66MIWofp18xFNW75XN18Qo6hgbwdX6jzeXbBLuQU2tY8MUK/mhINO6cDJgDeyq2PrqAua9pJCmkmpO6U5j5r7mnSXLBbH1gUA1YCAFwAAAECNOZqVp0+W7tGny/YqPadAkhTo7aYbzovW9T2aKtTPQ6M/WK5FO1P08tzteuXqDo4t2EkkpmTroyV7JEn3XNxCFkIs57R/hflIwHvuLBapy01muJuy3dwXdZ5jawKAakLACwAAAKDa7UzO0gd/JmrmmoPKL7RJkqJDvHXLBTG6onOkvN3//qvJw4NaadGbi/Td2oMa1ztWrSP8HVW203jupy0qKDLUp0WoLmoZ5uhyUBk2298jGgh4q0b7UdJvT0tFeebnLLAGoI4i4AUAAABQLQzD0PLENL2/cLd+35ps39+xSaBu6x2ri+PDZXUp3WnaNjJAQ9pF6Kf1h/WfOdv04VjCrjNZtCNFv205IquLRU8Mbe3oclBZqTuk3AzJ1UtqmODoauoG72ApYYS07nPJ1VOKaO/oigCgWhDwAgAAAKhShUU2zd6UpPcX7ta6AxmSzN+Wvrh1Q43rHasuTYPPeo37L26h2RuT9MfWZK1ITFO3mLM/pz4qLLLpmVmbJUnXnxetZmF+Dq4IlXZgpfnYuJNk5a/qVab77dLGmVKLQZKru6OrAYBqwX81AAAAAFSZ1ON5uuOz1VqxJ02S5OHqopGdI3XzBTGKDfUt93ViQ311ddcoTV++Ty/O3qqvb+/BXNkyfL5yv7YdyVKgt5vu6d/c0eXgXNjn73ZxbB11TaMO0n2bJQ/+8QNA3UXACwAAAKBKbD+SpZs/Xqn9aSfk6+GqW3rF6PrzohXi61Gp693dr7lmrj6gv/Ye029bknVxfMMqrti5ZeQU6OVft0mS7ru4hQK96U50ageK5+92c2wddZFPA0dXAADVysXRBQAAAABwfvO2JWvE20u0P+2EmgR767vxPXVP/xaVDnclqaG/p248P0aS9J85W1VQZKuqcuuE137foWM5BWoe5qtruzVxdDk4F7mZUrI5aoMF1gAAFUUHLwAAAIBKMwxDHy7eo+d+2iybIXWPCdY7ozsryKdquklv7xOn6cv3afuR47r/q3V65eoOZS7MVpdtPpSpyQt2KTuvUK4uFrlZXeRqtein9YclSU8MjZerld4dp3ZotSRDCmwi+dGpDgCoGAJeAAAAAJX26bK99kW+ru4SpWeGJcjdterCxgAvN716dQfd+skq/bDukLzdrZo0om29mcf7w7pDeujrdcotKLt7uV+rMPVuEVrDVaHKFS+wRvcuAKASCHgBAAAAVNofW5MlSbdcEKPHhrSuluD1olZheu2ajvrX56v1xcr98nK36smh8XU65C0ssumlOdv03sLdkqRezRtoaLsIFdoMFRYZKiiyyepi0bAOjR1cKarEfgJeAEDlEfACAAAAqLT0nAJJUreY4GoNXIe0i9CJgvZ6YMY6TV28R74errp/QMtqu58jHcvO178+X6NFO1MkmWMqHhzYst6Npqg3DOOUDl4WWAMAVBwBLwAAAIBKS8/JlyQFelfNzN0zGdk5Ujn5hXry+01644+d8vFw1e194qr9vjVp86FM3fbZKu1POyEvN6v+c2U7DW3XyNFloTql7ZZOpElWDym8raOrAQA4ISbxAwAAAKi09BNmB2+Qt1uN3O+GHk31f5e0kiS98MtWLdudWiP3rQk/rDukEZMXa3/aCTUJ9tbMO3sS7tYHxd27jTpIrtX/DyUAgLqHgBcAAABApRTZDGWcDHgDaijglcyRBaO6RUmSnvp+kwqKyl6AzFkUFtk06ect+vfna5RbYFOv5g30w13nq3WEv6NLQ03Yv8J8ZP4uAKCSCHgBAAAAVEpWboEMw9wO9KrZzsOHB7VSkLebth3J0idL99bovc+myGZo1vpD2pl8/KznHsvO19ipK/XuycXUbusTq49u7FYjIy9QSxxggTUAwLkh4AUAAABQKcdOLrDm426Vu2vN/tUi0NtdDw8yRzW8One7kjNza/T+Z/Lqb9t11/Q1uuzNRVq0I+W0520+lKnL3lqkRTtT5OVm1RujOuqRS1qzmFp9kp8tHdlkbhPwAgAqiYAXAAAAQKXU5AJrZbmqS5TaRwUqK69Qk37Z6pAa/umPrUf0xh87JUk5+UW66aOV+nVTUqnzfjxl3m5UsJdm3tlTl7Zn3m69c2iNZBRJfo2kgMaOrgYA4KQIeAEAAABUSvECa4E1OH/3VC4uFj1zeRtZLNK3aw5qRWKaQ+ooti81R/d8sVaSdG33JhrUJlz5RTbdMW21vl1zQJI5vmHSz1v0r1Pm7f541wXM262v7OMZuji2DgCAUyPgBQAAAFApxR28QQ6cF9suMlCjujWRJD35/UYVOmjBtdyCIt3+2V/KzC1UxyaBmnBpG715bUdd0SlSRTZD9365Tu8u2KWxU1f8PW+3d6ymju3KvN367OBq85GAFwBwDgh4AQAAAFRK+skZvAEO6uAt9uCAlgr0dtPWJMctuPbk9xu1+XCmQnzc9fZ1neTu6iJXq4v+M7KdxvSIliRN+mWr/txxyrzdwa3lauWvZPXaobXmY6OODi0DAODcXB1dAAAAAADnVLzIWpCDA94gH3c9NLCVHv12g57/eYuW7k7V5R0aqV+rhvJyt57xuYZhKDu/SMey83UsJ19p9scCHcvOV1ZugbLzi5STX6jjeUXKyStUgJebmoR4q2mIj5qEeGtX8nF9teqAXCzS66M6KiLAy359FxeLJlzWRn6ebnpz3k5FBXvp3dFdFN+IkQz1XnaKlLHP3I7o4NBSAADOjYAXAAAAQKVkFC+y5uX4EQNXd43S/G3J+nXzEc09+eHjbtXANuFKaByg9BNmYJuWk28+ngxyj2UXKL+KxjrcP6Clzm/WoNR+i8WiBwa21LCOjdQo0Eve7vw1DDIXWJOkkOaSJ4E/AKDy+D8LAAAAAJVS3MHrqEXWTmV1sei9G7poW1KWflh3UN+vPaQDx05o5pqDmrnm4Fmf7+HqohAfdwX5uCvYx12B3u4K8nZTgJebvN1d5eNhlY+7q7zcrTqWk6+9qTnam5qtvak5OnDshC6Ob6g7+sSd8R7Nwvyq6uWiLigOeBnPAAA4RwS8AAAAACol/URxwOv4Dt5iLcP99GB4Kz0woKXW7E/Xj+sOKTkzT0E+bgr2/jvADfI++ejjrmBv97OOcgCqXPECa407ObYOAIDTI+AFAAAAUCnp9hENju/g/SeLxaJOTYLUqUmQo0sBykYHLwCgirBkKwAAAIBKSS9eZM2n9gW8QK2WeVg6niRZXKTwto6uBgDg5Ah4AQAAAFTKsZMdvAG1YJE1wKkcOjmeIbS15O7j2FoAAE6PgBcAAABAhRUW2ZSVWyhJCqoFi6wBToXxDACAKkTACwAAAKDCMk4usCZJAbVwBi9Qq9kD3g4OLQMAUDcQ8AIAAACosPSTAa+fp6tcrfy1Aig3wzgl4O3k2FoAAHUC/ycGAAAAoMKKF1gLZDwDUDHp+6ScVMnFTQpPcHQ1AIA6gIAXAAAAQIWln1xgLcibBdaACinu3m0YL7l6OLYWAECdQMALAAAAoMKKO3iZvwtUEAusAQCqGAEvAAAAgAo7RgcvUDmHVpuPzN8FAFQRAl4AAAAAFZZxghm8QIXZbNKhdeY2HbwAgCpCwFuP7Ny5U3PmzNGJEyckSYZhOLgiAAAAOKviDt5AOniB8juWKOVlSFYPKay1o6sBANQRBLz1QGpqqvr3768WLVpo8ODBOnz4sCTp5ptv1v333+/g6gAAAOCMimfwBjKDFyi/gyfHM4S3laz82QEAVA0C3nrg3nvvlaurq/bt2ydvb2/7/quvvlqzZ892YGUAAABwVvaAlxENQPkVL7DWmPm7AICq4+roAlD9fv31V82ZM0eRkZEl9jdv3lx79+51UFUAAABwZuknWGQNqLDigJf5uwCAKkQHbz2QnZ1donO3WFpamjw8PBxQEQAAAJzdsWyzgzeADl6gfGxF0mEWWAMAVD0C3nqgV69e+uSTT+yfWywW2Ww2vfTSS7roooscWBkAAACcVcYJM+Clgxcop5TtUkG25OYjNWjh6GoAAHUIIxrqgZdeekn9+vXTqlWrlJ+fr4ceekibNm1SWlqaFi9e7OjyAAAA4GTyC206nlcoiUXWgHLbu8R8jGgvuVgdWwsAoE6hg7ceSEhI0Pbt23XBBRfo8ssvV3Z2tkaMGKE1a9YoLi7O0eUBAADAyRR371oskj8BL3B2OWnS/BfM7eYXO7YWAECdQwdvPREQEKDHHnvM0WUAAACgDsg4ucCav6ebrC4WB1cDOIFfn5Cyk83RDD3GO7oaAEAdQwdvPTB16lTNmDGj1P4ZM2bo448/dkBFAAAAcGbHcorn79K9C5zVrnnS2s8kWaTL3pRcWegaAFC1CHjrgUmTJqlBgwal9oeFhen55593QEUAAABwZuknA94AFlgDziw/W/rxbnO7261Sk+6OrQcAUCcR8NYD+/btU0xMTKn90dHR2rdvnwMqAgAAgDM7lmOOaKCDFziLec9L6Xsl/0ip35OOrgYAUEcR8NYDYWFhWr9+fan969atU0hIiAMqAgAAgDPLONnBG8gCa8DpHfhLWva2uX3pq5KHn0PLAQDUXSyyVg+MGjVK//73v+Xn56fevXtLkhYsWKC7775b11xzjYOrAwAAcF47jmTp/T93yyKLru4WpY5RgbJY6v6iY8UdvIGMaADKVpgv/XCXZNiktldJzS92dEUAgDqMgLceeOaZZ7Rnzx7169dPrq7ml9xms+mGG25gBi8AAEAlJGXk6tXftuurVftlM8x9X67ar4TG/rrhvKa6tH0jeblbHVtkNUo/cbKDlxENQNmWvS0lb5a8Q6RBLzi6GgBAHUfAWw+4u7vryy+/1DPPPKN169bJy8tLbdu2VXR0tKNLAwAAcCqZuQV6Z/4ufbg4UbkFNknSgPiG8vV01az1h7XxYKYe+ma9nvt5i67sHKnR50WraQMfB1dd9dLtM3jp4AVKOZ4sLfyvuX3xM5IPY/EAANWLgLceadGihVq0aOHoMgAAAJxSbkGRhr25WLtTsiVJXaKD9MjgVuocHSxJenxIvL5cuV+fLdurg+kn9MGiRH2wKFF9WoTqhh7RurBlmKwudWN8Q3oOHbzAac17TsrPkiI6SO1HOboaAEA9QMBbR91333165pln5OPjo/vuu++M57788ss1VBUAAIDz+nNHinanZCvI200vXtFOF8c3LDFvN9jHXXdcGKdxvWM1f1uyPlm6Vwu2H7V/RAZ56bru0bq6a5SCfZy78/XYyYA3gEXWgJKSNkqrPzG3B02SXFjXHABQ/Qh466g1a9aooMD8H+/Vq1efdrGP+rAICAAAQFX4ecNhSdLwjpEa0Cb8tOdZXSzq17qh+rVuqD0p2Zq2fK++WnVAB46d0Iuzt+qV37ZraLsIXX9etDo46aJsGYxoAEozDGnOo+bCavHDpOiejq4IAFBPEPDWUfPmzbNvz58/33GFAAAA1AF5hUX6bfMRSdLgtqcPd/+paQMfPTYkXvdd3FI/rjukT5bt0caDmZq5+qBmrj6oto0DNLanuSibu6vzdPodY0QDUNr22VLiAsnqLl38tKOrAQDUI87zf5GolIKCArm6umrjxo2OLgUAAMBp/bk9RVl5hQr391SnJkEVfr6Xu1VXdY3Sj3ddoG/v7KkRHRvL3eqiDQczdP+Mderzn3n64M/dOp5XWA3VV63cgiKdKCiSJAXSwQuYCvOlXx83t3uMl4KaOrQcAED9QsBbx7m5ualJkyYqKipydCkAAABO6+eN5niGQQnhcjmHhdIsFos6NgnSy1d30NJH+urBgS3VwNdDhzNy9exPW9Rj0u96afZWpWXnV1XpVS7zhNm962KR/Dz4hUBAkrTyAyl1p+QTJl1w5jVQAACoagS89cBjjz2mRx99VGlpaY4uBQAAwOnkFRZp7snxDEPaRVTZdUN8PTT+omZa9PBFmjSirWIb+Cgrt1Bvz9+lYW8tVlJGbpXdqyr9PZ7B/ZzCbqDOSN0lLXjB3O77uOTp79h6AAD1Dv/kXg+8+eab2rlzpxo1aqTo6Gj5+PiUOL569WoHVQYAAFD7Ld6ZoqzcQoX5eahzJcYznI2nm1WjujXRVV2iNHfzET3702btS8vRtR8s05fjeijUz6PK73ku0k8usBboxfxd1HO5mdLC/0jLJku2AqlhW6njaEdXBQCohwh464HLL7/cKVdnBgAAqA1+3pAkSbrkHMcznI3VxaJBCeFq08hfV7+7VLuPZuv6Kcv1xbjzatWsWxZYQ71nK5LWTpN+nyhlHzX3NbtYGvqy5GJ1bG0AgHqJgLcemDBhgqNLAAAAOCd5hUXycK354CS/0KZfN5kB7+C2VTee4Uyigr017dbzdNW7S7U1KUs3fLhCn93SXf6etSNQzThxsoO3FoXOQI3Zu1Sa/bB0eJ35eUhzaeDzUosBjq0LAFCvEfDWYdnZ2XrggQf0ww8/KD8/X/369dMbb7yh0NBQR5cGAABQbk9+v1GfLN2rMD8PNW/oq2ahvmoW5qu4MPMx1Nej2n5bafGuFGXmFirUz0NdmgZXyz3KEtPAR9Nv6a6r31um9QcydNPUlfrk5m7ydnf8/77TwYt6KX2/NPdJadNM83OPAOnCh6Wut0qu/GMHAMCxHP9/iKg2TzzxhD799FNdd9118vT01Oeff65x48bp22+/dXRpAAAA5bI/LUfTlu+TJCVn5Sk5K0+Ld6aWOMff01XNToa9zcJ81TzMT83CfNU40OucRyr8vP6wJGlQm3BZa3hBseYN/fTJTd107fvLtGrvMd05bbWmjOla43X8U3pxwOtFqIV6ID9HWvya+VF4QpJF6jzWXEzNp4GjqwMAQBIBb5327bffaurUqbryyislSTfccIPOO+88FRYWytWVLz0AAKj9PlycqCKboZ5xIXpgYEvtTD6u/2fvvsOjqrM/jr9nJr0XEkICoffeO6KiIArY197Fumtf177FXdv6W1117Q17AwVUFJDepfcOCSUJSUjvmfn98c2kQICUSSbl83qeee535t6594wGwpw5c87epCz2JGWx51gW8ak5ZOQVsS4ujXVxaRWe6+NppUOLgArJ306RAbQL98fLw3rGaxcW2/l1WyJQf+0ZTtQrJpiPSpK8C3ce4+Vfd/LnCd3cEouTc8haqCp4pSlzOGDLd6ZqN+OweaztKJjwHLTq497YRERETqAsXxN26NAhRo4cWXp/4MCBeHp6cuTIEWJjY90YmYiIiDR3DoeDz1bF8duOJJ66qAftW/ifdEx6TiFfrYkH4M6zOjIgNpQBsaEVjskrLGZ/crZJ+JYkffcmZbHvWDZ5hXa2Hc1g29GMCs+xWS30aBXEtUNjmdIvBl+vynv7Lt+bQnpuIS0CvBjSvv7aM5xoQGwoL1zWh/u+3MD/Fu6lV0yw2xLOUK6CVwleaaoOr4M5j0H8SnM/JBbOfxa6TwYNrxYRkQZICd4mzG634+lZ8R/eHh4eFBcXuykiEZE6lLwHVrwOY/8CgVHujkZETiOnoIjHpm/mhw1HAEjNLuC7u0ac1Hrg01UHySkopltUIKM7V/5VaB9PG91bBdG9VVCFx4uK7cQfzy1L/JZL/mblF7H5cDp/mb6Z537ewVVD2nD9sLa0DvUrfX5BkZ2ZJfGNd0N7hhNN6RfDlsPpvLtkPw9/s5GOEQF0jQp0SyzHczRkTZqozESY/3fY8BngAE9/GP0ADL8XPH3dHZ2IiMgpKcHbhDkcDs4999wK7RhycnKYNGkSXl5l/yBft26dO8ITEXGt2ffDgSXgEwzn/c3d0YjIKRxIzubOT9eyIyETm9WCl83Khvg0Ply2n9tGdyg9Lr+omI+WHwBg6pgO1R6i5mGz0r6FP+1b+HNej5aljzscDhIy8pi98SjTVh4gPjWXtxft493F++gcGUhmXiFpuYXkFJR9IH6hG6tly3t0Qje2Hc1g2Z4Upn7yOzPvGUWwG6po03NVwStNUMZReGsk5JT0+O5zFYx7BoKi3RuXiIhIFSjB24Q988wzJz02ZcoUN0QiIlLHkrab5C5A0jb3xiIipzR/eyL3f7WBzLwiWgR488Y1/dmXnM1j0zfz7193cn6PKGLDTRXtD+uPcCwzn6ggHyb1dV2CxWKx0CrYl9vHdOCWUe35bUcSHy8/wNI9yexMzDzhWBjWPtyt7RnK87BZee3qAUx6bSkHU3K476v1bhm6VlrBqyFr0pRs+sokd8M6wCXvQJvB7o5IRESkypTgbcIqS/CKiDRJq98tWydtd18cIlLqeHYBOxIy2ZGQwY6jZrvxUDoAA2JD+N+1A4kK9mFI+zBmbjjCin0p/GX6Jj67bSgOB7yzZB8At4xqh6ftzAPRasJmtXBej5ac16Ml+45lEZeaQ4ifFyG+noT4eRLk44nVza0ZThTm78U7NwzksjeXs3DnMUa/8BuRQT60CPAi3N+bsAAvvD2seFgt2KzOrQUPW8n2xMfL7ff38mBg21A8zvDfWz14pUnaPtNsh9+j5K6IiDQ6SvCKiEjjlpcOG78su58eD3kZ4BN06ueIiMsUFNnZl5zFjqOZbC+XzE3MyK/0+BuGt+XJC3vg5WGSiBaLhecv6834VxazfG8KX/8eT0SgN3uSsgj09uDqIfUzGLZDRAAdIgLq5Vq11TM6mBcv78tDX2/gSHoeR9LzXHbuB8/rwp/O7XzK/bkFxeQX2QEleKUJSYuHw2sBC3Sb5O5oREREqk0JXhERadw2fAGF2RDRzSR7M4/CsR3QZoi7IxNpklbuS2FDfBo7jmawIyGTvceyKCx2VHpsmzBfukUF0T0qkG6tgugVHVzagqG8tuH+PHx+V579cTvP/ridduH+AFw9NJZAHyURKzO5bzTDO4QTl5pDSlY+KdkFpdvCYjvFdgdFxQ6ztTu39or3i8sez8ovYldiFp+sPMhdYzuesmo6Lde0Z/CwWgjw1lsJaSK2zzLb2OEQ2PL0x4qIiDRA+leZiIg0XnY7rClpzzDkdtjxk0nwJm5VglekDryzeC//+mnHSY8HenvQrVUg3aKCSrddowKrlQC8eWR7Zm06ysb4NDYfTsfDauHmke1cGH3TExHoTUSgt0vOVVBkZ8Tz8zmWmc/87YlM6FX5YLny7RmqO/hOpMFytmfoMdm9cYiIiNSQErwiItJ47VsAKXvAO8hMu07dD3vnqw+vSB1Izynktd/2AHBOt0gGtg2lW1QgXaMCiQnxrXWyz2a18OJlfbjotSUUFjuY3C+aVsG+rghdqsDLw8oVg9rw5sK9fL46/pQJ3tIBa34asCZNRGYCxK006+5qzyAiIo2TErzNTF5eHj4+Pu4OQ0TENZzD1fpdA94BENnD3E/a5r6YRJqod5fsIzOviG5Rgbx3w6A6GT7WNSqQv07uyZer47nvNH1gpW5cPTiWNxfuZcnuY8Sn5tAm7OR2GunOCl5ftc6QJmL7LMABMYMguLW7oxEREamRuhlJLA2K3W7nH//4BzExMQQEBLBvn5lK/dRTT/H++++7OToRkRo6fgB2zTHrwbeZbWR3s1UFr4hLpWTl88Gy/QA8cF6XOknuOl07tC2z/jiKtiV9eKX+xIb7MbpzCxwO+GJ1XKXHHC9t0aAKXmkitv1gtj2muDcOERGRWlCCtxl49tln+eijj3jxxRfx8ir7x3ivXr1477333BiZiEgt/P4B4IAOZ0OLkkq/iG6ABXKSIeuYO6MTaVLeXryPnIJiescEc34PDSBqyq4ZEgvA178forDYftJ+55C1ED9V8EoTkJ0MB5eZtfrviohII6YEbzMwbdo03nnnHa699lpsNlvp43379mXHjpMHpYiINHiFubBumlkPmVr2uJcfhLU3a7VpEHGJpIw8pq04AMCD53XRYK0mblyPlkQEepOclc+8bYkn7XcOWQtVgleagh2zwWGHVn0htJ27oxEREakxJXibgcOHD9OpU6eTHrfb7RQWFrohIhGRWtoyHXKPQ3AsdBlfcV9pH161aRBxhf8t3EteoZ0BsSGM7Rrh7nCkjnnarFw5yPQh/fyENg3JWfks2mm+HaEWDdIkbJtptt1VvSsiIo2bErzNQI8ePViyZMlJj3/77bf079/fDRGJiNTSweVm2+dKsNoq7ivtw6sKXpHaOpKWy+erTJLvofO7qnq3mbhqcCwWCyzZnczBlGwA9h3L4pL/LWNnYiahfp5M6hPt5ihFain3OOxfZNbqvysiIo2ch7sDkLr39NNPc+ONN3L48GHsdjvTp09n586dTJs2jdmzZ7s7PBGR6kvda7bOZG55Zxq0FrcK1k+DsY9DcEzdxCfSRLy+YA8FxXaGdQhjRMdwd4cj9aRNmB+jO0eweNcxvlwTz7jukdz28e8czykkNsyPj24eTGy4n7vDFKmdnT+Dvch888fZy19ERKSRUgVvMzBlyhRmzZrFvHnz8Pf35+mnn2b79u3MmjWL8847z93hiYhUX0pJgjesw8n7yrdocDhO3j/nUVj/KXx1HRTl112Mda2ooPLXJ+IicSk5fL0mHlD1bnPkHLb26cqDXPPuKo7nFNK3TQjT7x5Bh4gAN0cn4gLbfjBbtWcQEZEmQBW8zcTo0aOZO3euu8MQkebiwDKI6Ar+LVx/7vxMyE4y6/COJ+8P6whWTyjIhPR4CIkt25e6H46sN+sj6+CXx+HCl10fY13LSoL3xoGHN1z9ZeX/HURqIaegiLs/X0uR3cHozi0Y3C7M7Eg/BAufg+F/hMhu7g1S6tS53SOJDPQmKdN8EDaueyT/vbo/fl56+yBNQG4a7P3NrNWeQUREmgBV8DYD8fHxHDp0qPT+6tWruf/++3nnnXfcGJWINFk7foSPJsLMP9bN+VP3ma1fC/AJPnm/h1fZVy1PbNOw7XuzDW5jtmveg03f1EmYdWre3yDtICTvgg/Gw5EN7o5ImhC73cGDX21ky+EMwvy9+OfFvct2rnrLVMB/f5cqyJs4T5uVW0e1B+D6YW1567qBSu5K07Hk31BcABHdK2/3JCIi0sgowdsMXHPNNSxYsACAhIQExo0bx+rVq3niiSf4+9//7uboRKTJWf+Z2R5YCna7689/uvYMTqVtGk4YtLb1e7Md/RCMecSsZ/3p1P16G6JDa2HDp2Yd3gmyj8FHF8H+xe6NS5qMl37dyZytCXjZrLx9/cCKvVYTS/5MHVkHu/XNoKZu6pgOrHvqPP5xcS88bHrbIE3EsV2w8k2zPu/voPYzIiLSBOhfas3Ali1bGDJkCABff/01vXv3Zvny5Xz22Wd89NFH7g1ORJqW3DTYU5L0yc+A4/tdfw3ngLXTtSWobNBa6j44ugEsNug+CcY+Bu3PgsIc+Op60/qhobPb4eeSxHTfq+H236DdaNOO4tPLyvoJSpOzMyGTxIy8Or/ON7/H8+ZC82fs+ct6l7VmcCr/Z2rR86ribeIsFgth/l7uDkPEdRwO+OUxM1yt83jocr67IxIREXEJJXibgcLCQry9vQGYN28ekyebQQLdunXj6NGj7gxNRJqa7bPMVx6dnP1uXSmlpEVD2OkSvJVU8Dqrd9uPMb2BrTa47H0IjIaU3TDzTw0/WbXxCzi8FrwCYNxfTYuKa781CeviAvj6Rlj7sbujFBey2x38Z+4uxr+ymFEv/MYTMzZzJC23Tq61al8Kj8/YDMC9Z3fi0gGtKx6Qexwyj5i1h4/5Wdwzv05iERGpE7t+gT3zTK/+Cc+5OxoRERGXUYK3GejZsydvvfUWS5YsYe7cuUyYMAGAI0eOEB4e7uboRKRJ2VzSz9az5CvddZHgLa3gPV2LhpIK3mO7oLjIrLfOMNuel5QdFxABV3wEVg/YOh1WN+De5HnpMO+vZn3WnyEwyqw9feCKj2HgTYADZj8A8WvcFKS4Uk5BEfd8vo5X5+8GoLDYwWer4jjrpQU8+b1rE72Hjudwx6drKSx2cGHvVjx4XpeTD3JW7wa3gcG3mfXC5xr+ByMiIgBF+TDnL2Y9/B4NKBURkSZFCd5m4IUXXuDtt99m7NixXH311fTt2xeAmTNnlrZuEBGptcxEOLDErIffa7Z1MfyrtAfvad6YhbQ1SebifNMmImUvJGwqa89QXuxQOO8fZv3LEw03ObroRchOMn13h95VcZ/VBhe9Ar0uB0cxfHcr5GW4JczGatbGIzzzwxYKi+ugb3QNHDqew2VvruDnLQl42iy8eHkfvpo6jOEdwiksdvDpyjjGvrSQp77fwtH02id6X/9tD2k5hfRpHcy/r+iL1VpJT0pnRXxkdxjxp5Iq3t9hr6p4RaQRWPGG+TdBQBSMedjd0YiIiLiUErzNwNixY0lOTiY5OZkPPvig9PGpU6fy1ltvuTEyEWlSts4Ahx1aD4aeF5vHjm507aC1vHTISTbr0w1Zs1ohoptZJ20rq97tMBb8wk4+fthd0ONisBfCNzdCdrLrYnaFYzthVcnf1xNeAI9KemJaLHDR/0FwLKQdhJ8eqd8YG7HCYjuPz9jMxysOsmBHkrvDYc2BVKa8voztRzNoEeDFF7cP48pBbRjaIZwvpg7jy6nDGNo+jIJiO5+sPMhZLy7kmR+2kJBesx69xzLzmb7+MABPX9QDXy9b5Qc6K3gje0BgSxh0q7m/8AVV8YpIw5ZxBBb/26zP+zt4B7o3HhERERdTgreZsNlsFBUVsXTpUpYuXcqxY8do164dkZGR7g5NRJoKZ3uG3ldAi67g4WuGfzlbKrhCakn/Xf8I8Ak6/bHOPryJ28r675Zvz1CexQKTXzPVsRmH4bvbwF7skpBrzeEwXym1F0GXC6DzuFMf6xMMl70LFits+hI2f1t/cTZivx84TmaeaeWxNu64W2OJT83huvdWkZJdQI9WQfxw7ygGnTDobFiHcL66Yzhf3D6MISWJ3o9XHGTMSwv468yt1R7G9smKAxQU2enXJoSBbUNPfWD5BC/AyPtMFe+h1bBvQbWuKSJSr+Y+A4XZ0HoI9LnS3dGIiIi4nBK8zUB2dja33HILrVq1YsyYMYwZM4bo6GhuvfVWcnJy3B2eiDQFqfvNV7UtVpNEtXlAVG+zz5V9eKvSnsHJ2Yd3x2xI3Gz67Ha78NTH+wTBlZ+Y1g77FpiWCA3Bzp9g729g84Lx/zzz8bHDYMyfzXr2A3D8YN3G1wQs2FlWtbv+YJr7AgHeXryX/CI7A9uG8u1dw4kJ8T3lscM7hvPV1GF8fvtQhrQLo6DIzkfLDzD6RZPoTapCoje3oJhPVpqfkdtHd8BiqaQ1A5gPGsq3aABTxTvwZrNe+LyqeEWkYdrxE2z+GrDAxBfNh7oiIiJNjBK8zcCDDz7IokWLmDVrFmlpaaSlpfHDDz+waNEiHnroIXeHJyJNwZbvzLb9GAgo+WZAdH+zdWWC11nBW5XBKC2dFbxbzLbD2ZW3ZzjxORf9x6wXvQC759UsTlcpzIU5j5n18HurPhBmzCPQZijkZ8D0qWWD5qRSv5Vry7DxUBoFRe7pw3ssM5+vfz8EwEPnd8HPy+OMz7FYLIzo2IKv7hjGZ7cNZVDb0AqJ3r/NOn2i97t1hzieU0ibMF/G92x56gtlJkDucfMhTotyA9hG3W+qeONXwb6FVXylIiL15PgB+P5Osx52d9m/TURERJoYJXibge+++47333+fCy64gKCgIIKCgpg4cSLvvvsu336rr++KiAs4WwH0urzsseh+ZuvKQWulFbyn6b/r5PwauZOzL/CZ9L2qpCrRAdNvg7T46kToWstfN/10A6NhdDU+kLN5wKXvgHcQxK+Epf9XdzE2cvGpOexJysJmtRDo40F+kZ1tR90zoO7DZftLWyUM7xBeredaLBZGdmrBN3cO59NbhzKwbSj5RXY+XGYSve8v3X/Sc+x2R+njt4xsj4ftNP8sdFbvhnUET5+yxwOjYOBNZr1IvXhFpAEpyoevbzT9+1sPhnF/dXdEIiIidUYJ3mYgJyeHli1PrsqJjIxUiwYRqb3ErXBsu2kh0H1S2ePOKpmjG13Xz9bZz7cqlawBLcG3pJ+o1fP07RlONOF5aNXPVCx+c6N5k1jf0g/BkpfN+vx/gHdA9Z4f2g4uKGkzsfJNJd5OwVm9O7BtKINLet2uPVg3fXhTswtIyymodF9GXiGfrDCtEu4a2/HUrRLOwGKxMKpzC769czif3DqEAbEh5BfZ+cfsbby3ZF+FY+dtT2R/cjZBPh5cOajN6U/s7L/bssfJ+0beDzZviFsB+xfXKG4REZf75Qk4usH8W+DyDysfUCoiItJEKMHbDAwfPpxnnnmGvLyyr2jm5ubyt7/9jeHDh7sxMhFpEpzVu53PB9+QssdbdDH9bAuzIXm3a65VnR68FktZFW/Hs8uSvVXh6QNXTgOfEDi81rxJrI39S+Ddc+DtMZBXxerQX5+ColyIHQ69LqvZdXtebL5Sn5tqvmIvJ3EmeM/pFlk6YGxdHQxaS80u4NyXF3L2vxeyOzHzpP2frYwjM7+ITpEBnNf9NK0SqshisTC6cwTf3TWCB8aZlgrP/ridj5cfKD3mvSWmevfaYW3x9z5DO4gTB6yVF9QKBt5o1urFKyINwZbvYM27Zn3puxByhg+xREREGjkleJuBV199lWXLltG6dWvOPfdczj33XNq0acPy5ct59dVXq3Wu5557jsGDBxMYGEhkZCQXX3wxO3furHBMXl4e99xzD+Hh4QQEBHDZZZeRmJhY4Zi4uDguvPBC/Pz8iIyM5JFHHqGoSD0iRRodhwO2ONsznJCEtNogqo9ZH91Q+2vlHjeJSqhaiwaArhMBCwyZWv3rhbY1bQ7AvEnc9E31z5G6H766Dj6+yCSKj26ETV+d+XkHlsLW6SY5e0EtBsJ4+pYlw5O21uwcTVhOQREr9qUAJsE7ILYkwVsHFbwfLtvP8ZxCjucUcuMHq0lIL/vQNa+wuLRVwp1ndcRqdd0AIIvFwp/O7cQ9Z5ufg2dmbuXzVXFsiE9j9YFUPG0WbhrR7swnOnHA2olGPWCq+OOWw4ElrgleRKQmknfDzD+Z9eiHoPN57o1HRESkHijB2wz06tWL3bt389xzz9GvXz/69evH888/z+7du+nZs2e1zrVo0SLuueceVq5cydy5cyksLOT8888nOzu79JgHHniAWbNm8c0337Bo0SKOHDnCpZdeWrq/uLiYCy+8kIKCApYvX87HH3/MRx99xNNPP+2y1ywi9SRuBaTFgVcAdJlw8n5XDlpzDlgLaFn1dgXD74HHD9f8zV2X8TD6YbOedR8k7aja8/IzYd7f4I0hsH2WSdTGDDL7fv/g9BWOxUXw05/NeuDN0KpPzWJ3alny93yiErwnWr4nhYIiOzEhvnSODKBvm2BsVgtH0/M4kpbrsutk5BXyUUnlbLCvJ0fS87jpw9Wk5xYC8O3aQyRn5RMd7MOUftEuu66TxWLh4fO7cvvo9gA8PmMzD369AYBJfaNpGeRzmmcDdjscK/nZr6yCFyAoGgY4q3hfcEHUIiI1kJMKX98ABVnQdhSMfdzdEYmIiNSLM49nlibBz8+P22+/vdbnmTNnToX7H330EZGRkaxdu5YxY8aQnp7O+++/z+eff84555wDwIcffkj37t1ZuXIlw4YN49dff2Xbtm3MmzePli1b0q9fP/7xj3/w6KOP8te//hUvL/XHEmk0lr9mtj0vAS+/k/eXJng31P5aKSUJ3qq0Z3CyWMDLv3bXPftxOLQG9i8ybxpv/+30CebiIvjoorKq5fZnmZ6+QdHwcjdTCRm/GmKHVv78tR+aalufEDjnydrFDibBu+17SNxW+3M1Mb/tLGvPYLFY8PPyoHurQLYczmDtweNEh/i65DqfrDhIZl4RnSMDeP/GwVz21nJ2JGRyxye/88FNg3lnsfnZvn1MBzxPN+isFiwWC49P7E5hsYOPlh9g3zHzwezto6tQDZ92AApzTJ/d0PanPm7UA7DuYzi41LQlaT/aNcGLiFRFZiJ8crH5PesfCZe/b4aOioiINAP6jddEzZw5s8rHTp48ucbXSU9PByAsrGQwzdq1FBYWMm7cuNJjunXrRmxsLCtWrGDYsGGsWLGC3r17Vxj8Nn78eO666y62bt1K//79axyPiNSjxG2w8yfAAiPvq/yY6H5mm7DJJD5r80ardMBaFdszuIrVBpe9b/rnJu+EWX8y90/VNmH12ya56xMCF//PtIlwHtv7Mlj/qanirSzBm50Cvz1r1uc8CX5htY/fWXGpFg0VOBwOFpTrv+s0MDaULYczWBd3nEl9a19Nm1NQVDrc7J6zOxEb7sdHNw/mD2+vZOW+VCa/voy41BzC/L24anBsra93OhaLhWcm9aCg2M7nq+IY2zWC7q2CzvxEZ//diK6n/zMcHAMDboA178GiF5TgFZH6kxYH06aYb/sERMENP0BglLujEhERqTdK8DZRF198cZWOs1gsFBfXbLq93W7n/vvvZ+TIkfTq1QuAhIQEvLy8CAkJqXBsy5YtSUhIKD2mfHLXud+5rzL5+fnk55dNsc/IqOKQIhGpO8tKenh3nwQtOld+THgn076hIAuSd0HLU3y9uyqqM2DN1QIi4IoP4aMLzeCWNsNgaCV9fTOOwoLnzPq8v0O3CyvuH3iLSfBunQETnjs5gbvgWchLg5a9THsGV3C2aDi2E4oLwebpmvM2cjsSMjmanoePp5XhHcNLHx/QNpSPVxx0WR/ez1fFcTynkLbhflzUpxUAPaODefv6gdz04Wr2JGUBcNOIdvh62VxyzdOxWCw8O6UXk/pE06MqyV0o13+3Cn9+Rz0Aaz82fXgPLIN2I2serIhIVaTshY8nQ8YhCImFG2ZC2Gm+bSAiItIEqQdvE2W326t0q2lyF+Cee+5hy5YtfPnlly6MvHLPPfccwcHBpbc2bTQJV8St0uJgc8nQsVEPnPo4qw1a9TXr2g5aK63gdUOCFyB2mEnaAvzyOMSvOfmYuU9BQabpt9v/+pP3xwwwg+eK82HD5xX3Hd0Iv39o1he86LqvlYa0BU9/KC4oS5ILv5VU747o2AIfz7LE6sC2ZtDa1iMZ5BbU/HckmOFpb5e0X7h7bEc8yrVfGNmpBf++wvzZCPT24Mbh7Wp1reqwWi0M7xhOsF8Vk/3OCt5TDVgrL7g1DCj52V/0fM0CFBGpqsSt8MEEk9wN7ww3z1FyV0REmiUleKVG7r33XmbPns2CBQto3bp16eNRUVEUFBSQlpZW4fjExESioqJKj0lMTDxpv3NfZR577DHS09NLb/Hx8S58NSJSbctfB0cxdBhrkpan06qf2dZ20Jo7K3idht0NPaaAvRC+ucm0VHDav7gk6W2BC18GayW/Yi0WGHSLWa/9sGzYmsNRMljNAb0uc23Vo9ValphTm4ZSzvYMZ5drzwAQE+JLZKA3RXYHmw6l1eoa3/wez7FMMzztkv6tT9o/pV8M3901nO/uHlH1ZKs7JFajghdg1INg9TR/Jg4ur7u4RKR5O7zOfLMmOwla9oabfzatYkRERJohJXibsN9++40ePXpU2s4gPT2dnj17snjx4mqd0+FwcO+99zJjxgx+++032rev+An5wIED8fT0ZP78+aWP7dy5k7i4OIYPHw7A8OHD2bx5M0lJSaXHzJ07l6CgIHr0qPzNo7e3N0FBQRVuIuIm2cmwbppZn65618kVg9ZyUk3rAnBvZY7FApNfN60nMg7B9NvAXmxaH/z4sDlm8K1lvYcr0/ty8AqElD3ma+wAm7+F+JXg6VdWJexKzjYNiUrwAhzPLmBdnGnBcM4JCV6LxVJaxbs2ruZtGgqL7by1yFTv3jm2I14elf+Ta2DbMLq0DKzxdepcUQGk7DbrqlTwAoS0gf7XmfVCVfGKSB04uNy0Zcg9br41c9Ms005JRESkmVKCtwl75ZVXuP322ytNhgYHB3PHHXfwn//8p1rnvOeee/j000/5/PPPCQwMJCEhgYSEBHJzc0vPe+utt/Lggw+yYMEC1q5dy80338zw4cMZNmwYAOeffz49evTg+uuvZ+PGjfzyyy88+eST3HPPPXh7e9f+hYtI3Vr1NhTlmsRt+7POfLwzwesctFYTzurdwFbg5V+zc7iKTxBcOQ08fGHvb7D4JVj5phnA5tfCDEc7He9A6HOFWf/+AeRnmdYOAKMfNF9xd7XSBO8215+7EVq8+xh2B3RtGUhMiO9J+50J3nUH02p8jRnrD3M4LZcWAd5cOagRtxVK2QP2IvAOqt7P5mhnFe8iOLii7uITkeZnzzz45FLTEqndaLjhe/ANdXdUIiIibqUEbxO2ceNGJkyYcMr9559/PmvXrq3WOd98803S09MZO3YsrVq1Kr199dVXpcf85z//4aKLLuKyyy5jzJgxREVFMX369NL9NpuN2bNnY7PZGD58ONdddx033HADf/97HVStiYhr5WfC6nfMetQDpqL1TMI6mIrVojw4tqNm103dV3IuN7ZnKK9lT5j0ilkvfB4W/Musz/t71d5kOts0bJ8Fc/4CmUchtB0M/2NdRFuW4D1Vi4bsZPjgAvj+bsg6VjcxNCDzt5tvkIztVnm11wBngjfuOA5nG40q2pOUxf/N3cULP5uf9alj2pf1+D2yHhI21zBqNykdsNa9an/enUJiod81Zq1evCLiKttnwRdXmw+aO58P135jPjgVERFp5lw0wUUaosTERDw9T93Tz8PDg2PHqvdGvipvdH18fHjjjTd44403TnlM27Zt+emnn6p1bRFpANZ+bFolhHeCbhdV7TlWq2lZcGCJGbQW1av61y0dsNah+s+tK32vgriVppduUS60GQp9r67ac6N6Q+vBcGgNrP/EPDb+OfD0qZtYnb1T0+IgL8NUIZe38QuIW25uO36E8/9hhsRVJ6HXSOw7lsVPm48CML5n5X3fe0YH4WWzkppdwIGUHNq3OH3V+JG0XGZtPMIPG46w7WhZW6T2Lfy5dmhbcycvAz680Pw3fWAr+Ia45PXUueoMWDvR6Idgw2ewbyHErYLYoS4NTUSamY1fwfd3mRkAPS6GS98FDy93RyUiItIgqIK3CYuJiWHLli2n3L9p0yZatWpVjxGJSKNWmAsrXjfrkfeD1Vb157bqa7YbPodDv5cNF6uqhjBgrTITnofWQ8DT/9SD1U5l4M1l647nQtcLXB+fk1+YaW8BZQm78nb+bLY+ISaBP/OP8NFFkLy77mJyk+d+3kGR3cHZXSMYEFt5tbW3h43erYMBWHuw8j68KVn5fLLyIFe8tZwRz//Gcz/vYNvRDDysFs7pFskrf+jH7D+Owt+75LP05N1QmA0FWbDrlzp5bXWiNMFbxQFr5YW2VRWviLjG7x/AjDtMcrfftXDZ+0ruioiIlKMEbxM2ceJEnnrqKfLy8k7al5ubyzPPPMNFF1WxAk9EmreCHPjiKtNKIDAa+lxZvee3G222B5fBe+fCawNMW4PkPVV7fmkFbwNL8Hr6wM0/wUPbTVVudfS8BAJagoePSRTXdbXsqdo05KRCXEmP1KkL4PxnzbC3g0vhzRGw8AUoyq/b2OrJ8r3JzN2WiM1q4YkLT1+ROrBcmwanzLxCvlt7iBs/WM2Qf83nqe+3sObAcSwWGNo+jH9e0os1T4zjg5sGc3H/mLLkLpT9DANs+8Glr6tOOX9ealLBC6aK1+ph+lXHr3ZdXCLSfCx/DWY/ADhgyFQz7NSmL6KKiIiUp9+MTdiTTz7J9OnT6dKlC/feey9du3YFYMeOHbzxxhsUFxfzxBNPuDlKEWnw8rPg8z+YhJ+nP1z+PnhUcyBi1wlw/QxTwbvjR9NTd9EL5hY9wCSMe10GAZEnP9fhgJQG1oO3PJsn2IKr/zwvP5i60PQmDquH1hORPcxgmsQTEry7fgGHHVr2NnGM+CN0nww/PgR75sLCf8GW72DSq9B2eN3HWUeK7Q6enW2qUa8dGkunyNP3bHRW967Zn8qcLUeZufEI87cnkV9kLz2md0wwk/tGc1HfVrQKPnlYWwUp5T7M2DPP9LNu6H0jC7Lh+AGzrkkFL5je0n2vNq1IFj4P108/41NERADz+3/h82XfABj1AJz7TJNsHyQiIlJbSvA2YS1btmT58uXcddddPPbYY6X9cy0WC+PHj+eNN96gZcuWbo5SRBq0vAz47HKIXwXeQXDttzXvo9nxHHPLz4KdP8Gmr01V35F15vbLE9BhrEn2drsIvAPM83JSID/drEPbueJVNRxB0fV3LWcFb+K2io/vLOmHXr5FRGhbM7hm63T4+VFI3gkfToCBN8G4vzbKaeXfrTvEtqMZBPp4cP+4Lmc8fkDbEAB2J2Vx56frSh/vEOHPlL4xTOrbig4RAVUPIKVcBW9xPuz+1Xyo0ZA5hyL6R4J/i5qfZ/RD5sOdvfNNi5bWg1wTn4g0XQ4H/PpkWWuoc56CMQ+7NyYREZEGTAneJs45zOz48ePs2bMHh8NB586dCQ1tfG/ORaSe5R6HTy+Dw2vBJxiumwGtB9b+vN4BJonb50rIOmaSiJu+hsO/mwTQ3vng4QvdLjTHeJUMuAqKMVWvUjPlWzQ4HKYCqjAP9sw3j5/YA9hiMQnIjufA3Gdg3cew9iPY8RNc8Dz0vLTRVFFl5xfx0i87AfjTOZ0J8z9z38bIQB96xQSx5XAGrYJ9mNw3mkl9o+kZHYSlJq/bWcEb0c0kTrf90LATvMWFsP4zs65pewansPaminfDp6Ya77pvax+fiDRd9mL48UHzOwdgwgsw7E63hiQiItLQKcHbTISGhjJ48GB3hyEijUX6IfjiakjYZKo1r/8eovu5/joBETD0DnNL2QubvzHJ3tS9sOVbc7N6mmPro41BU9aiC1hskJcOGYchuDUcWGoGfwW2glb9Kn+ebyhM/i/0vQpm3QfJu+DbW2Djl2awXEhsvb6Mmnh70V6OZeYTG+bHDSPaVvl5024ZytH0XLpHBWG11iKZ7XCYtiRgvmI84w7YPde0QHB+gNGQHN0EP9wNCZvN/e6Tan/OMQ/Bxi9M248DS6HdqNqfU0SanuIi+P4u2Pw1WKww6b8w4Hp3RyUiItLgaciaiIhUtHsuvDXaJHf9WsCNs+smuXui8I4w9i/wx7Vw+28w9E7wjwB7odlf2yrC5s7DG1p0Nmtnm4by7RmsZ/gnQdsRcOdSGPsY2LxMi4E3hsLy180b8gbqSFou7ywxydXHLuiGt4etys8N8/eiZ3Rw7ZK7ANnHID8DsECPi01SvDDH9OJtSIoKYMFz8O7ZJrnrGwaXfwCDb6v9ucM6QL+rzfrLa8uSxyIiTkX58M2NJrlr9YDL3ldyV0REpIqU4BUREaO4COb/3fTczU2FVn3htnkQ1at+47BYIGYgXPACPLgDrvsOzn7S9PGU2jmxTcPOn839rhOr9nwPb5OEv3MZtB1pkpS/PgHvnVOxx2wD8t/5u8krtDOkXRgTekW5Jwjnf5uQNuDpAz2mmPvbfnBPPJXJTIR3zzHDjOxFpmr3nlWmjYSrWnFMeB5aD4G8NJh2MRzb6ZrzikjjV5BtBrrumA02b/jDZ9DrUndHJSIi0mgowSsiIpCZANOmwJKXzf3Bt8Etv5reme5k84BO4+CsRyDQTcm5piSyh9kmboWjGyHzCHj6Q7vR1TtPRBdT2T35NdOf+ehG+LFhJuBX7EsB4O6zO9asd64rOPvvhncy2x4Xm+2uX0wf5IZg0fOQWK5q98pPICDStdfwDjTD+1r1hZxk+HhyWesKEWm+8tJNz/99C8zvpGu/ga4T3B2ViIhIo6IEr4hIc7dvEbw1Cg4uBa8A85XIC182lYbStDgreBO3lbVn6HROzf5fW60w4Aa4taTNwP5FkJXkmjhdJK+wmPjUHAB6RAe5LxBngjeso9lGDzBDAwuyYO9v7ovLKTsFNnxu1ldOc23V7ol8Q8zAxojukJUAH0+BtPi6uZaINA5f3whxK8A7GG74Hjqc5e6IREREGh0leEVEmiu7HRa9CJ9cbHqERvaEqQuh9+XujkzqijPBm7wLts0066q2ZziViC6mpYbD3rBaDgD7k7OxOyDIx4OIAG/3BZJa0qLBWcFrtUL3yWbdEP6b/f4BFOWZytr6GH7mHw43/GAS3ulxMG2ySTKLSPOTdcxU7gLcOBPaDHFvPCIiIo2UErwiIs1RdjJ8dhks+KdJzPW/3vTbdQ7hkqYpuA14B5nBdce2mwnlnc+v/Xl7XWa2W76r/blcaE9SFgCdIgPc154Bynrwhncse8zZh3fnz2a4mVP8Gvj6Bvj1KSgurPvYCvNg9TtmPfyPdVe5e6LAliaZExJr2jT8/kH9XFdEGpa4FWYb2bN+BrqKiIg0UUrwiog0NwdXwFujzVfDPXzh4jdhyuvg5XfGp649eJyE9AbSM1Sqz2KByO5l99sMBf8WtT9vz0sAi3mj3oC+bl8+wes2dntZn9nyCd42QyGgJeSnm/YWh9fBZ1fA++NMVe/y/5r7eenVv6bDYZLKG76A2Q/Ae+fBmvcrP3bzN5CdZFpG9Ly4+teqjeDWZcMTd82p32uLSMNwcLnZth3h3jhEREQaOQ93ByAiIvXEbocVr8G8v4GjGFp0gSs+hpY9qvT01ftTufLtFfRpHczMe+vha9xSN1r2hPhVZl3b9gxOQdHmzfnBZbB1Boz8k2vOW0t7jjWABG/GYdP+wOoJwbFlj1ut0H0SrHkPvr/LtEkBsNigx2QzgG3fAvhgAlzzNYS0OfU18rPg8Fo4tBoO/Q6H1kDOCS0PDq0xFdxdylVsOxyw4g2zHnon2Dxd85qro/N4sz281vRwdvVgNxFp2A4uM1sleEVERGpFCV4RkeYgJxW+vxt2/Wzu974CLnoFvKue+PpidRwAmw6lk5SZR2SghrA1SpHlEvquSvAC9LrUvFHf8l2DSfDubQgVvM7+u6HtwHbCP7t6TDEJ3uxjpl1Gnz/AmEdMpe+RDfD5HyBpG7x3Llz9JcQMKKvOPbTaJG3j10DSVtNqpTybF7TqZ/pZZhw2iffvboPbf4MWJb2A98w3rTq8AszAPHcIamXiPLoBdv8K/a9zTxwiUv/y0iFhs1krwSsiIlIrSvCKiDR1h9bCNzeZYUY2b7jgBRh4U7V6bWbkFfLzlqOl91fsTWFKvxjXxyp1r81Qs23ZuyzR5wo9Loaf/mwSdSl7K7YjcINiu4N9ydkAdIoIdF8gKXvMNryS/9ZtR8KQqVCYCyPvq9gDO7of3D4fPrvSJHA/nGgGoB1eC7mpJ58rqDW0GQyth5ikblRv8CgZLFdUABlHIX4lfHmN6bftE2Qq+sEkd31DXPmqq6fLBPNzs2uOErwizUncKsBhBi4GRrk7GhERkUZNCV4RkabK4TDDk355wgzVCm0PV34MrfpW+1Q/bTpKXmFZheDKfUrwNlqt+sDNc8xwK1fybwEdxsLe+aaK96w/u/b81RSfmkNBkR1vDysxob7uCySlkv67TlYbTHzp1M8Nbg23zIFvb4Y982DPXPO4zdskgFsPNsnc1oNNm4xT8fCCK6fBO2dB8k7TEuKsR2HfQlM5PPTOmr461+gyHhY9D3sXQFF+WWJaRJq20vYMw90bh4iISBOgBK+ISFNUmGeGK2383NzvPtkMUvMJrtHpvll7CICh7cNYtT+V5XtTzvAMadDq6s10r8tMgnfzt6bVQDWqxF3NOWCtQ0QANqv74iir4K1hRbNPEFz9FWz6EvIySqpz+5ikbXUEtoQ/fAofXgA7ZptevWDaRIS2rVlsrtKqHwREQVYCHFgKnc51bzwiUj9KB6yNdG8cIiIiTYDV3QGIiIiLZRyFjyaa5K7FCuf/01Tv1TC5u/dYFmsPHsdmtfDcpb2xWS0cTMnhcFquiwOXRq/bhab3a/JO0zvWjRrEgDUoS/CG1aJlhc3DtC4Yfje0HlT95K5T60Fw0X/MOivBbIffW/O4XMVqLRv+tusX98YiIvWjIAeOrDNr9d8VERGpNSV4RUSaiC9Wx/HDrO9xvDPW9On0CYHrpsOIe2tVSfltSfXuWV0i6BARQO8YkyheoSpeOZFvCHQuSdRt+c6toTgreDtFuDHBW1wIaQfNurIevO7Q/zoYfLtZx44wSd+GoMsEs901x7SXEZGGa9mr8M5Y02+9pg7/DvYiCIqBEDd/i0BERKQJUIJXRKQJyCssZvXMt5jw+61YshJwRHSHqQug49m1Om+x3cH0dSbBe8XA1gCM6BgOwPK9ybULWpqmXpea7Zbv3JqoK03wurOCNy3OJDA8fCGwlfviONGE501V/xUfujuSMh3Gmt7CaQfh2E53RyMip7L3N5j7NBxZDzPuAHtxzc5T2p5hhFvb+YiIiDQVSvCKiDQBmamJvGB7C29LEb8UD+J/Hd+EsA61Pu+S3cdIzMgnxM+Tc7pHAjCiYwvAVPA6VGknJ+oyATz94PgBOLzOLSE4HA72NoQEr7O6LbyjaUPQUNg8TO/dhjS13ssf2o8x610/uzcWEalcdjLMKDeU8dAaWP7fmp2rdMCa2jOIiIi4QgN6tyEiIjVl3/kLXpZidtjbcGfh/by08AjvL91f6/M6h6td3C8Gbw8bAAPbhuJls3I0PY8DKTm1voY0MV7+0PUCs978jVtCSMrMJzO/CKsF2rXwc0sMQO0HrDU3XcabrfrwijQ8Dgd8fzdkJUJEN5j4b/P4gn9BYjV7rhcVQPwas9aANREREZdQgldEpAnw2mcSIis8h/Hged0A+MfsbXy9Jr7G50zLKWDu1kQALi9pzwDg62WjX2yIuZ768Eplel9htlu+heKier/87kRTvds23L/0gwm3SC2p4K3NgLXmxJngjV8FOanujaU+2O0mybXgOdi30N3RiJzeqrdh9y+mlcrlH8Dg28w3NooLTKuG4sKqn+voBijKBb9waNGlzkIWERFpTpTgFRFp7ArzCDq0CIC1viO495xOTB1j2jP8Zfom3lm8l0W7jrHpUBrxqTlk5hVWqbXCzI1HKCi2071VEL1KBqs5qQ+vnFanceDXArKPwd759X75PUmZAHR054A1KFfB20AGrDV0IbHQshc47LBnXv1eOy8DPp4E75wNhXl1dx17MexfAj89Av/pCe+Pg0XPw+d/gKOb6u66IrWRsBnmPmXW5z8LLXuavrmTXgXfUEjYBIv/XfXzOdszxA5X/10REREX8XB3ACIiUksHlmAryiHBEUqSfzcsFguPXdCNjNxCvlwTz79+2nHSUzxtFoJ9vQj18yTUz4tQf7MN8St77LOVcUDZcLXyRnRswSvzdpf24bXoDZqUZ/M0Vbyr3oSNX5RVZtaTPccaQP9dgJR9ZqsWDVXXZTwkboGdP0OfK+vnmoV58OU1cGCJub9nLnSf5LrzFxXA/sWw/QfY8RPklPtgzCsQAiJNtffX18PUReAb4rpri9RWQQ58e4up1O1yAQy5vWxfYBRc+LLZv/gl6DoBovuf+ZylA9bUnkFERMRVlOAVEWnsdvwIwLziAQT6egJgsVj45yW9aRXsy8p9KRzPKSAtp5DjOQXkF9kpLHaQnJVPclb+aU/tabNwcf+Ykx7v1yYEH08rKdkF7ErMomtUoOtflzRufa8yCd4dP0FuWr0mrfY0hAFrhbmQXtIiRRW8VddlAix5GfbMN1/5tnnW7fWKi+C7W8uSuwBbZ5w6wWsvhum3m+r0ATeaYXWVxViYa17D9lkmWZ2fXrbPNxS6Xgg9JkOHsVCQDe+cZQYTfn8X/OGzhjWUT5q3Xx6D5F0QEAVT3ji54rbXZebnfOsMM4Bt6iLw9Dn1+ezFELfSrDVgTURExGWU4BURaczsdtg1B4C59kGE+pT9tW6zWrhvXGfuo3OFp+QWFHM8p6BC0vd4TiHHsys+lp5byIW9WxHm73XSZb08rAxuF8aS3cms2JusBG8TsHxPMsdzCgnw8SDQx4NAbw8CfDwI8PbA38sDq7WaVdqt+kJEdzi23bzxH3Rz3QReiT1J2YCbE7yp+wEHeAebPpNSNTEDTXuPnGR4/3zzFe7Wg6D1YAhu7dqvczscMOs+2DHb9BU95wmY+zTsnGOqFr0qGdC39zfY8p1Z718Mvz4Jg26FgTeZpNbuX2HbTNg9Fwqzy54X0BK6XWSSum1HVkwKe3jDldPM6935Eyx/FUY94LrXKVJT22bC2o8AC1z6Nvif4u+yiS/DgaVwbIf5MzTxxVOfM3EL5GeY6vWo3nURtYiISLOkBK+ISGN2dANkHqXA6scKew/+4HPmajdfLxu+Xr5Eh/jW6tLDO4azZHcyy/emcNPI9rU6l7jX2oOpXPPeqtMeE+BtEr8B5RK/JhHsSaCPB+0j/OneKohuUYH4eXmYRFy/q2Hu06St/IQPUkewPyWHO8/qQM/o4NNeqzbScwpLK9Pdm+AtGbAW3lE9JqvDaoMB18PS/8CRdebm5BtqkuU+IaYi3Ce43PoUj/kEg3dQ5RWxc5+GDZ+CxQpXfAhdJ8Lq9yA9zrRp6DHl5Oes+9hsYwZCWjxkHoUFz8LiFwELFJf7VkRwG+g+2VQDtxliXtupRPeHC16E2ffD/L9DzCBoP7oa/+FEXCz9EMz8o1mPvM9Um5+Kfzhc/CZ8djmsfhs6nAXdLqz8WGd7hthhp/8zISIiItWiBK+ISGO28ycAdgcNpSDHJNrqy4iOLYCdrNyXQrHdga26FZ7SYKzanwpAiwBvIgK9ycovJDOviKy8IorsZiBfVn4RWflFZzyXxQLtW/jTPtyf9KTWfOWwEJK8lu8PLyPO0ZLNh9KYc/8YfDzr5o39nmNmwFqrYB8CvN34zxwNWKu5cX+F/tfDod/h0BpzS9gMucfNrbosVpPkLZ/0tVhh3wKzf/JrZcmonhfD8v+aqvMTE7xZSabdAsDk183/223fw6q34fDv5vGwjqZKt/tkk7StTnJ/4E0Qv8r0rf72FrhzielxKlLf7MUwfSrkpUH0ADjnyTM/p/N5MPxeWPE6/HCP+RZH8Mk9/Dmw1GzVnkFERMSllOAVEWnMSpING/yGAxDkW8f9KsvpFR1EgLcHGXlFbD+aQa+YuqvKlLq19XAGALeNbs+dZ5UNBHM4HOQX2U2yN7+IzLxCsvKKyMw3yV9n0vd4dgG7krLYfjSDY5n57DuWzb5j2YAPyzx7Mca2mSdiNvBU+mQOpOTw6vzdPDqhW528lhr33934FRxabSbEe9auuh2AlHIVvFJ94R3Nre8fzP2CHEjdB3npJumUm2a2eell69y0k/cX5YHDXnJs2snXOf9Z6H9d2f2el5gE765fTG9cL/+yfRs+B3uRaRfRsod5rM+V5pa0HbBARNeaV2xbLHDh/8HRTZC01fQzvX6GKsCl/i15GQ4uA68AuPz9qvfCPvcZ87wj6+G72+HGWWArebtZVADznjEtUQDaqUJdRETElZTgFRFprI4fML3sLDZWew4Gcuu1gtfDZmVo+zDm70hi+d5kJXgbsc2HzQCoXie0TrBYLPh42vDxtBER6F2lcx3LzGf70Qz2J2fTNtyPgRl3w493Mb5oAUz5C3d8up53Fu/joj6t6qRVgzPB2zGiGgnelL2m4sxeCEExMPrB2gdSmuBVBa9LePlBVK/qP68w74Skb7l1i07Q8ZyKx0f3h9B25u/XXb9Ar0vN4w4HrJtm1gNuOPk6kd2rH1tlvPxMP943R5gK450/Q7eJrjm3SFXErYKFz5v1hS9DWIeqP9fDCy57H94+C+KWw+KX4OzHzJ+nb24ua7ky8j7TW1tERERcRiN6RUQaq51muBqxw0ksNBWHgVXowetKwzuagStLdifX63XFddJzColLzQGgV0xQrc8XEejNmC4R3DiiHWO7RuLf92JTBZYWx/jAA0zsHUWx3cFfvttMUbG91tc70UkVvPuXwJzHTULvVH59yiR3AZa9UrM2AOVlp0DyTrOuTnJEXM/TBwJbmsra2KHQ5XxTcTt06snJXTDVsj0vMeutM8oeP7jM9FX2CoCel9ZtzC06wfC7zfrXJ03lo0h9yE2D724DRzH0vhL6XlX9c4R3hEmvmPXiF2HBc/DWGJPc9QmBq76A8/6uynQREREXU4JXRKSx2vmj2XabSGae6Y1anxW8AGO7RgKwfG8KSZl59XptcY2tR031butQX0L8vFx/AS8/6HGxWW/8gr9O7kmQjwebD6fz4bIDLr/cnmMnJHh//jOsfMNU6DocJz9h30LzZ8lig5BYU+G5/LWaXTw7GeY+A6/0hpwUsHqogrcxciZ4d/8K+ebnqbR6t9dl4F0Pw/tGPQj+ESap/Pv7dX89EYfDDPlLjzNV7Be+XPNz9b4c+l1n2qMseh7y001rkzuXqCJdRESkjijBKyLSGOUehwPLzLrrBaUJ3qB6TvB2igygf2wIxXYHM9Ydrtdri2s4+++e2J7BpZxVYFu/J9LHwRMXmq+zvzx3J3EpOS67TF5hMYeO5wIlCd6cVEjaZnbumG2GYZVnLzbVvQCDb4Pxz5n1yjchM7HqF85KMpWWr/Q2FcCF2RDVB675GnxqXxUt9Syqj6m8LsqDXXPM37fbfjD7BtxYPzH4BMHZT5j1wufNz7JIXVr/qalat3qYNgu1/btr4osQUdK6ZMSf4OafzYdoIiIiUieU4BURaYz2zDdfoYzoDmEdyMwzXy+v7xYNAFcOagPAN2sP4aisQlIatC1HSvrvuqA9wym1HQnBsZCfATt+5MpBbRjeIZy8QjuPz9jssp+bvceycDggxM+TcH8viFthdlhL/lz8+iQcXlv2hHUfm2FWPiEw9i/Q7UKIGQiFOWbI0JlkJpgE8St9TNVvYY7p4Xr1V3DHYuh0rktel9SzE9s0bPrGJHtb9oKYAfUXx4AbILKn6Rm86MX6u640P8m7zbcdAM5+3DX9cb384fbf4L5NcP4/qj6oTURERGpECV4RkcZoR0l7hq4X4HA43NaiAeCiPq3w8bSyJymL9fFp9X59qZ3SAWt1OSTPajVf2QXY+TMWi4XnLu2Nt4eVpXuSXdaqobT/bkQAFosFDi43O/pdA90nmT6739xUNmzrt2fN/rGPgV+YSeyd+7R57PcP4PjByi+UcQR+fhRe7WvaPxTlmsTwNd/A7Qug6wT1l2zsnH12d8+FNe+a9YAb6vf/q9UG4/9p1mveNUk4EVcryodvbzEfULUbDSPvd925vfwgtK3rziciIiKnpASviEhjU1wEe+aZddeJ5BYWU2Q3FZDuqOAN9PFkYq9WAHzze3y9X19qLiu/iP3J2QD0rMsWDQAdzjLb+FUAtGvhz8PndwXg77O3ueRnZ++JA9acFbxtR8Lk1yGkLaTFmX68i140fXJbdIHBt5aLcyy0P8skgxe9UPEC6Yfgx4fh1X6w6i1T1dl6CFz3Hdw23wzwUmK3aWjZE8I7Q3E+JO8Cm7cZzlbfOp4NnceDvcgMAxRxtfl/h4RN4BsGl75jPlgQERGRRkcJXhGRxuboBvNVd58QiBlQWr1rtYC/l3vemF1R0qZh1saj5BQUuSUGqb7tRzNwOCAqyIeIQO+6vVjMIDPILD3eJEqB20a356YR7QB49LtNzNx4pFqnTMnKZ962RF76ZQdXv7OSd5fsB0oSvPlZcGSDObDtcPANgSs+Mu0adsyGFa+bfeP/dfJXh51VvBu/gKQdkBYPsx+A//Y3lZTF+RA7HK7/Hm79FTqNU2K3qSnfpgGgxxTwDXVPLOc/a/qi7vrZDAUUcZXd88r+LpzyOgRFuzceERERqbH6/y6viIjUzv5FZttuFFhtZOaZIVWBPp7ma+luMLR9GLFhfsSl5jBnSwKXDmjtljikerYcrof+u07eARDVC45uhLiV0PtyLBYLz0zqQX5RMV+sjueBrzbgZbMyoVfUSU8vLLaz42gm6+OPs+7gcdbHp3GwkgFtLQK8GNs1Eg6tMX2qg1qXDfaJGWCSZXMeNfc7jYPO550ca+tB0O0ikwj+/ErTksFu+lzTdiSc9Si0H6OkblPX8xJYXNL7dsAN7osjogsMuhVWvw3L/muqzEVqKysJvr/TrAffZnqQi4iISKOlBK+ISGOzf7HZtjdfec9wY/9dJ6vVwhUDW/Py3F18/Xu8EryNxJbDGUA9tGdwih1uErzxq0p78losFv55cW/yC+1MX3+YP36xjneuH0TP6CDWxR1nfVwa6+PS2HQ4jbxC+0mn7BwZwIDYUPrHhtA/NpROkQHYrBbY6mzPMKLiE4beYWLYOx8mPH/qWM950vS6Tivpw9tutBnE1m6UK/5LSGMQ2d30Iy3Kc///956XmARvyh73xiFNg8MBs+6H7GMQ2cN88CUiIiKNmhK8IiKNSVG+qX4EU0EI5QasuXdC9WUDW/N/83axcl8qB1OyaRvu75Lz7knK5N3F+0nPLaSg2E5hsZ2CIju+XjbuH9eFfm1CXHKd5shZwdu7LgeslddmqOld6/wZLmG1Wnjx8j7kF9n5cfNRbvl4DQ7HyU8P8vGgf2xoaUK3b5sQgn1P8XPvHLDWdnjFxy0WuOTNM8ca2R0ueMEkowffdnKiWJo+iwXO+5u7ozCCSz40yzgM9mL1SZXa2ToDdv5oWtZc+i54+ro7IhEREaklJXhFRBqTQ7+bajL/SIgwA6oy88xXx91ZwQsQHeLLqE4tWLI7mW/XHuKhkgFatbFwZxJ//Hw9mfmV9/Vdd/A4X985nG5R9dBioInJLShmd1ImAL3qK8EbO8xsE7dAfiZ4B5bu8rBZeeWqfhQU25m7LRGrBbq0DCxJ6Jrq3A4t/LFaq9AWoajAtGgAiK1FYnboHeYm4m6BrUwPa3sRZCZAcIy7I5LGKicVfv6zWY9+0LTOERERkUZPCV4RkcaktD3D6NL+n84K3iA3J3gBrhzUhiW7k/lu7SHuH9fFfFW+BhwOBx8tP8A/Zm/D7oDB7UKZ0i8GL5sVTw8LnjYrHy07wO8Hj3PjB6v57q4RtA71c/Gradp2JGRgd5ietS2D6njAmlNQtOmHmxZnErAdz6mw29Nm5a3rBrL9aAbtWvgT4F3Dn+mjG8wHIX7hpR+EiDRqNg8IioH0ODOkUAleqalfHjetGSK6weiH3B2NiIiIuIj7swEiIk2Rw1E3A5hKE7xjSh8qq+B1b4sGgPN6tCTIx4Mj6Xks25PMmC4R1T5HYbGdZ2Zu5fNVcQBcMbA1z17SC2+Pil9JHt0pgiveXs6uxCxu+GA13945gjB/L5e8juZgy5Gy/rv1OpyvzTCT4I1bdVKCF8BmtdS+otjZniF2uAahSdMR3LokwRsPDHV3NNIY7Z4HG78ALDD5dfCopw/3REREpM5Z3R2AiEiTs+Bf8O8ukLDZtectyCn72nmFBK/7h6w5+XjauLi/qSz7bNXBaj8/LaeAGz9Yzeer4rBY4PGJ3Xjx8j4nJXcBgv08mXbLUGJCfNl3LJubP1pDTkHlrRzkZFtL+u/2iqnn9haxJYmp+JWnP642yid4RZqKkDZmmx7v3jikccrPhNn3m/Wwu6DNYLeGIyIiIq6lBK+IiKtt/R6yk+DnR6l0UlRNxa8EeyEEtYbQ9qUPN6QEL8C1Q9tiscAvWxNZF3e8ys/beyyLS/63nOV7U/D3svHu9YOYOqbjaatLo4J9+PiWIYT4ebIxPo27Pl1HYbHdFS+jydtc3wPWnJxJ1/g1UFwHCXm7vSx5rMFo0pQ4B62lKcErNTD/H+bDgZBYOOdJd0cjIiIiLqYEr4iIKzkcZdVVB5fBjh9dd+7y7RnKJT0zchtOiwaArlGBXD7AJCL++eN2HFVIci/dncwlbyxjf3I2MSG+fHvXCMb1aFml63WKDODDmwbj62lj0a5jvLN4X63ibw7yi4rZlWgGrPWMrucEb0R38A6GwmwzbM3VkrZBXjp4BUBUH9efX8RdglXBKzUUtwpWv2PWk14FL3/3xiMiIiIupwSviIgr5R6Hwpyy+3OfgqIC15y7kv67ABmlQ9YaRoIX4OHxXfH1tLH24HF+3pJw2mM/WXmQGz9cTUZeEQNiQ/j+npF0b1W9tgH9Y0P5+5SeAHy47AD5RcU1jr052J2YRWGxg2BfT1qH+tbvxa3Wsq8Gx69y/fnjVpht68FmMJVIU1HaouGQe+OQxqUgG76/E3BAv2sr7X0uIiIijZ8SvCIirpRmBoPhEwL+kZC6D9a8V/vz5qXDkfVm3X50hV1lQ9YaTjKrZZAPU8d0AOD5n3dUmnAtKrbz15lbeer7LRTbHVzSP4bPbx9GRGDNhr5c3D+GqCAfkrPymbnhSK3ib+q2lOu/W68D1pxih5mtMxnrSgeXmW3bka4/t4g7OSt40+Jd2/5HmrZfnzT/FgmKgfH/cnc0IiIiUkeU4BURcSVnZVVYh7Ied4tegJzU2p334Apw2M15nX0YSzS0HrxOU8d0ICLQm7jUHD5ZUXHgWnpuITd/tIaPlh8A4JHxXfm/K/vi43nyMLWq8rRZuWlkOwDeX7q/Sq0hmqvNpQneem7P4NTGmeBd5dpElcNh/qwAtNWANWlinH/3F2SaD/1EzmTXr/D7B2Z98ZvgG+LWcERERKTuKMErIuJKzt6IIW2g/3UQ2RPy0mDxS7U77ynaMwBk5jesHrxO/t4ePHx+FwD+O383aTmmVcWB5Gwu/d8yluxOxtfTxlvXDeCeszu5pJL06sGx+HnZ2JGQybI9KbU+X2NT1aT2liMZAPSq7/67TjEDweoBmUdc20/0+H7ISgCrp7mGSFPi5Q++YWatPrxyJtkp8MM9Zj3sbuhwlnvjERERkTqlBK+IiCs5K3iD24DVBuOfNfdXvwMpe2t+3tMleEt78DasCl6Aywe2oVtUIBl5Rfx3/h5W7kvh4v8tY++xbFoF+/DNncOZ0KuVy64X7OfJlYPM15jfW9q8hq2l5RRwzsuLuPC/S9h+NOOUxxUW20v3u62C18sPWvU167iVrjvvweVmGzMQPOu5t7BIfQgp16ZB5FQcDph9H2QnQUQ3OPdpd0ckIiIidUwJXhERV3L24HX2Sux4DnQ+H+xFMLeGb7CyUyBxs1m3q9h/1+FwlGvR0LAqeAFsVguPT+wOwLQVB7juvVWk5RTSt00IP9wzsk4SjDePbIfFAgt3HmN3YqbLz99QfbfuMPuTs9l6JIMpbyzjo2Unt6lIycrn2dnbKCiyE+DtQdswPzdFS7k2DTVM8OZnweG1sOFz82frsyth7jNmn9ozSFMVrEFrUgUbv4Tts8y3GS59Rx94iYiINAMNr9xLRKQxK63gLdcn97x/wJ75sGM2HFgK7UZV75wHl5ptRHcIiKywK7ewmGK7SeI1tB68TmO6RHBWlwgW7ToGwEV9WvHvK2rXb/d02ob7c36PlvyyNZH3l+7n+cv61Ml1GhKHw8FXa8yHC7FhfsSl5vDXWdtYsjuZFy/vg5eHlfeW7Oe9JfvILjAD764ZGovV6oYBa06xQ2HlGxC/6vTH5aXDsV1wbEe5285Tf0Xd5gXdJrk+XpGGoDTBG+feOKThSouDnx4x67F/Kfu2hIiIiDRpDTMbICLSWJXvwesU2Q0G3gS/vw+/PA63LwRrNb5AUYX2DDarBT+vukmYusLfp/TkL99tZkyXCO48q4NL+u2ezu2jO/DL1kSmrz/Mw+O70iLAu06v524b4tPYlZiFj6eVWX8cxffrD/PPn7Yzf0cSE15dQlGxneM5pldz75hgHhnfldGdW7g3aGcFb+JWk8T1CYasJPMhyKE1kLTdJHIzj5z6HP6RENHVfAU5slvJtgf4hdXPaxCpbyGq4JUzWP6aGcTXegiMvN/d0YiIiEg9UYJXRMRVCnMh21SpllZZOY19DDZ/A0c3wqavoN/VVT/vvkVmW0mCNyPXJO0CvD3qPGlaG23D/fli6rB6u97AtqH0bRPCxvg0Pl15kPvHdSndl55bSHxqDmH+XrQI8MbLo/F3K/pqjflgYWKvVgT7enLjiHYMaR/GH79Yz56kLAA6tPDn4fFduaBXVMP4WQlsCaHtzWC072432+Rdpzi2VUkit3tZQjeiqxK50vwEqwevnIbDAbt+MetRD4BNb/VERESaC/3WFxFxlfTDZuvpD76hFfcFRMDoh2DeMzD/79Bjihk0dSbJeyBlN1g9oN3Ik3ZnOAes+eqv8/IsFgu3jWrPH79YzycrDhLk48mmQ2lsOpTOvuTsCseG+HkSGehNRKA3EQHeRAb5EBFg7jsfjwz0Ici3YSbRs/KLmLnRVLn+YXDZBwvdWwUx695RfLBsPy2DfLi4XzQetgaWzI4dZhK7u38pe6xlL2g7AqJ6m0Ruiy7gG+K2EEUaFGf7H1XwSmVS9kDaQdOqppIPhUVERKTpUkZARMRVnD0Rg1tDZYnAoXfCmvfNcSteh7P+fOZz7phltu3HnJw0BjLzTAVvoHfDG7Dmbhf0iiImxJfDabn8ffa2CvvC/b1Izy2kyO4gLaeQtJxCdiVmnfZ8XjarSQKXuzkTwB1aBDC0fdhpe9qmZOWTX2QnOsS1w25+3HSEnIJi2rfwZ0j7ihWtvl427jm7k0uv51Ij/gS5aRDW3vSmjh2uqlyR0wmJNdusBCjKB4+m3X6m0TuyHoJjwT+8fq63+1ezbTsCvAPq55oiIiLSICjBKyLiKs6KqpA2le/39IHz/grf3gJLX4EBN0Bg1OnPub0kwdu98qFRzh68DXXAmjt52Kw8PrE7L8/dSftwf/q2CaFP62D6tg4h1N8Lu91Bem4hSZn5HMvM51hWHkkZznW+WWflk5SRR0ZeEQXFdg6n5XI4LbfS63WODOD2MR2Y0i8ab4+yfshbDqfzwdL9zNp0BIcDnrqoBzcMb+uyamBne4YrB7VpkBXGp9WyB1zzpbujEGk8/MLBwxeKcs3vnPCO7o6o6crLMD3BDywxg8r6XlW952+bCV9fD1F9YOqi6vXer6ndc82203l1fy0RERFpUJQREBFxFWdPROdXaCvT81JY+aYZIvXbszDl9VMfm34IDq8FLND1wkoPKUvwqoK3Mhf2acWFfVpVus9qtRDq70WovxddowJPe568wmKSs/LLksGZ5dd5rNyXyu6kLP787Sb+/ctObhrZjnbh/ny0/ACr96dWONczM7eyIT6Nf13SG99aDsbblZjJurg0bFYLlw2MqdW5RKQRsFjM75iU3Urwupq9GI5ugD2/wd7f4NBqsBeV7fcKgO4XVe1cBTkw5zGzTtgE22ZAr8tcHnLFa2bDwWVm3fn8ur2WiIiINDhK8IqIuIqzgvfEAWvlWSww/l/w/nmw/lMYeofpNVqZ7bPNNnaYGUhVCWeLhiBV8NYpH08brUP9aB1aed/kjLxCvlgVx4fLDpCQkceLc3aW7vOwWriwTytuHtme3w+k8tzPO5ix/jDbj2bw9vUDaRvuX+O4nNW753aLJDLQp8bnEZFGJKRNSYJXg9ZqLf2QSebu/Q32LYTc4xX3h3UwQx4PLoMZd0KL+WbA45ks/T/IOARYAAcsfB56XAzW2n2od1r7F0NxgWnj0aJz3V1HREREGiRlBEREXMX5ZtvZI/FU2gwxlbxbp8MvT8ANP1Tes/cM7RlALRoaiiAfT+44qyM3j2zPrI1H+GDZflKzC7h0QAzXD2tHVLBJvvZrE0KvmGDu/XwdOxIyuei1pTx9UQ/6tgkhNswPH8+qv/nPLypmxnoz2O+qIaf5UEFEmhYNWqu5gmw4sKwsqZu8s+J+7yDT877jOeYW1h6KC+GTS0yrhi+vhdvng0/wqa+RsheWvWrWU96AX5+A5F2w+Zvqt3mojvLtGRpbux4RERGpNWUERERcJb0KLRqcxv0VdvwI+xeZoShdxlfcn3UM4pabdbdTfyW0dMiaWjQ0CF4eVi4b2JrLBp76Z2BYh3Bm/3E0d322lvVxaTzy7abSfS2DvIkN8yM2zJ/YMD/ahvvRpmQb7u9VocfuvG1JpGYX0DLImzGdI+r0dYlIAxJc8iFimip4q2zzt7DuY4hbaapcnSxWiBlYktA916xtJ7w9snnC5R/CO2NN5fSMO+EPn526p+4vj5trdDwH+l0DWYkw/2+mirfXZeZ8ruZwwJ6SBK/aM4iIiDRLSvCKiLiC3Q7ppprytC0anELbwrC7YNkr8OuT5o1g+Td9O38Ch90Mdglte8rTqIK3cYoK9uGrqcN5df4uFu48RlxKDpn5RSRm5JOYkc+aA8dPeo6/l6002Rsb5seKfSkAXDGwDR62ehjeIyINQ2kFb5x742gsctNg+lRwFJv7wW3M79xO55pqXd/QM58jIAL+8Al8MMH8fl78Eox99OTjds6BXXPA6gkXvGgqaYdMhRVvwPH9sOFzGHijS18eYCqE0+LA5gXtR7v+/CIiItLgKSMgIuIKWYlgLwSLzfTrq4rRD8L6T8wbs7UfwZDby/aVtmeYfNpTZKiCt9Hy8rDyyPhuPDK+Gw6Hg7ScQuJScziYmkN8ag4HU7KJS80hLiWHoxl5ZBcUsyMhkx0JmRXOc+UgtWcQaVZCSv7Mq0VD1cSvMsndkFi4boYZTFeTFgYxA+Ci/8APd8PCf0FwDPS6HDxL+p8X5sGcv5j18LvL+uB6B5jf9788bhLDfa8CD2/XvDYnZ3uGtiPBq+Z93UVERKTxUoJXRMQVnO0ZgqJP/nrnqfgEw9mPw48PwcLnoPcV4BsCeelm2AtUIcFrKniDfPXXeWNmsVgI9fci1N+Lvm1CTtqfX1TMoeO5pQnfuJIk8OB2YcSGVz74TUSaqOByCV67/dStAsQ4WNLuqP0YaNGpdufqfy0cWQ9r3oUf7oEfH4YOZ0Hn8+D4AVOlG9gKxjxS8XmDboHlr5l/K6ybVvEDXVdQewYREZFmTxkBERFXqE7/3fIG3ASr3jGDXpa8DOf/A3b9aqqBW3SFiC6nfXpZiwZV8DZl3h42OkYE0DEiwN2hiIi7BUWb3rHFBZB9DAJbujuihi1updnGjnDN+cb/y1Ttbv4OMo+Ylgy75pTtP/9Z8A6s+BxPXxj9EPz0MCz+N/S/zjzmCvlZZUnszue55pwiIiLS6OgjfxERV3AOu6lK/93ybB7mzSDAqrcgdT9sn2nud590xqeXDVnT53UiIs2CzbOsFVC6Bq2dVmEeHFln1m2Hu+acHl7m9/aD2+DOZXDuMyZ5bLFB5/FmkFplBtxg/o2QlQCzH4QDy6Aov/bx7F9skv2h7SC8lhXKIiIi0mgpIyAi4grOXojVreAFU3HT4WzYtwDmPAb7F5nHq5TgLWnRoASviEjzEdwaMg6bwVqtB7k7mobr8FqT/AxoCaHtXXtuiwWiepnb6AdNstbqeer+vh7ecNajMPNe2Pi5uXn4Quww0z6i/VlmsGpV2zw5OdszdDqvZr2FRUREpElQRkBExBWcVVQhNRh4ZbHA+H/CW6Ng18/mseBY80bvNBwOB1n5atEgItLsBLcxw8M0aO304kpaF8QOr/vkZ1UGp/W/zgxB2/GjqbzNTjIf7u5bYPZ7B0O7kSUJ3zEQ0f30PZYdjrIBa2rPICIi0qwpwSsi4go1bdHg1LKneeO3bpq5333SGd+M5hQUU2x3AGrRICLSrDg/TFSLhtM7uMJs27qo/25tWSzQ61Jzczjg2A6T6N2/GA4sMUNWd/5kbgB+LaD96LIK37AO5hwOB+SlwdGN5mfA5g3tRrv1pYmIiIh7KSMgIuIKpS0aapjgBTj7SdgyHQqyoMeUMx7ubM9gs1rw9bTV/LoiItK4ONsBqYL31OzFEL/arGNd1H/XlSwWiOxubkPvMPEe3ViW8I1bATnJsHWGuYFpNeFwQE4KOIrLztVuFHj5ued1iIiISIOgBK+ISG3lpUN+ulnXpAevU2BLuP57SDsIsUPPeHj5AWsW9d0TEWk+gmPNNk0VvKeUuAUKMsE7yHxLpqGz2iBmgLmNuh+KCkwP4f2LTMI3fjVkJVZ8jlcgBEbByD+5JWQRERFpOJTgFRGpLWcFlW8oeAfU7lxtBptbFWTkOfvv6q9yEZFmpbSCVwneU3K2Z2gzxCRPGxsPL2g73NzG/gUKckzS2sMH/FuAbxh4+rg7ShEREWkglBUQEamt0v67tajerYGMkgreIA1YExFpXpw9ePPSID8TvAPN/SPr4ZcnIKo3DLzJfP2/uSo/YK0p8PIzyWoRERGRSpxmLKuIiFSJs4LK+ZXZepKpCl4RkebJOxB8Qsza+SHj4bUwbQocXAar3oL/DYP3x8PGL6Ew122huoXD0fAGrImIiIjUISV4RURqy5ngDanFgLUaKOvBqwpeEZFmxznUM/0QHFoL0y4xPeFbD4FuF4HFBvErYcYd8HI3+PkvcGxn/cW36CV4PhamT4UDy0zStb6k7oPsJLB5QfSA+ruuiIiIiJuo7EtEpLacPXjruUWDKnhFRJqxkDaQuBm2/QDbZ0J+BsSOgGu/NhW+GUdh/aew7mPzQeSqN80tdoRp39BjSt31cE2Lh8UvQnEBbPrK3MI7wYAboO81EBBRN9d1iiup3o0eoD61IiIi0iyogldEpLZKe/C6p4JXPXhFRJoh54eKGz41yd22I+Hab8r68Qa1grMegfs2wrXfQtcLTVVv3HKYMRX+rxvMeRyO7XJ9bItfMsndmEEmqevpDyl7YO7T5rpfXQ975oG92PXXhnLtGZpI/10RERGRM1DZl4hIbZVW8NZ3glcVvCIizVb53zltR5nKXS//k4+z2qDzeeaWccRU9a79GDIOwco3zK3tSBh4M/SYDB7etYsrdT9s+Mysz3/WJFnH/wu2TDfVxIfXmorj7TNN7/r+15lbcEztrlte6YA19d8VERGR5kEVvCIitVFUAJlHzbree/AqwSsi0mzFllSntj/r1MndEwVFw1l/hvs3wTXfQNeJYLGawWzTbzO9erdMr11ci18CexF0PKesgtY7EAbeCLf/BncugyF3gE8wpMfBwn/BK73gsytg+2woLqzd9TMTTQ9eLNBmSO3OJSIiItJIKCsgIlIbGYcBB9i8wa9FvV5aQ9ZERJqxNoPhkX3gFwYWS/Wea7VBl/PNLf1wSa/eaaaq99ubzQeXw++pfkzJe2DjF2Z99pOVHxPVCya+COf9DbbPMtXEB5fC7l/NLaAl9LvGtHYI61D9GJz9d1v2BN+Q6j9fREREpBFSBa+ISG2UH7Bmrd+/UjNUwSsi0rz5h1c/uXui4BgY+6jp1TvkDvPYL4/DL0+A3V69cy16ARx26DIBWg88/bGevtDnSrj5R7h3LYy8D/wjICsRlv4HXhsEi/9d/T69zgRvrPrvioiISPOhBK+ISG2kOwesta73S2fkasiaiIi4iM0DLngBxv3V3F/xuhnGVlRQtecn7YDN35j12Meqd+0WneC8v8MD2+DKaabthKMYfvsHTJtiegefSUE27PoFds0x9zVgTURERJoRlX2JiNSGs4K3nvvvgnrwioiIi1ksMOoBCGwFP9xjErZZSXDV5+AdcPrnLnwOcEC3iyC6X82u7+EFPaZA98mw4XP46RE4sATeHAFT3oBuF5rjHA7ISYGUvXBoNeyZBweXQ3FJMtpiM4PjRERERJoJZQVERGojLc5sg92R4FUPXhERqQN9rwL/FvDVDbB/ESx/Dc4+TVVuwhbY9r1ZV7d6tzIWC/S/FtoMhe9ugaMb4ctroMPZkJcGKfsgP/3k5wXHQqdzofflEBhV+zhEREREGgkleEVEaqO0RUP9JngdDgdZ+aaCN0gVvCIi4mqdxsHEl+CHu2HH7NMneJe9arY9LzFD1FylRSe4dR7M/5tpGbFvQcX9Qa0hsrtJ6nYaB+Gdat+TWERERKQRUlZARKQ2jh8029B29XrZ7IJi7A6zVgWviIjUia4XmHYHiVvM77vQticfU5gHO38y62H3uD4GDy8Y/0/TuuHQ7xASC+Edze9dT1/XX09ERESkEVKCV0SkpoqLyip46znB62zP4GG14OOpeZkiIlIH/MIgdhgcXGaGlw294+Rj9v4GBVkQFAMxA+suljZDzE1ERERETqKsgIhITWUcBnsR2LzMQJp6VH7AmkVfRxURkbrS9QKz3flz5fu3/WC23SeDVW8tRERERNxB/woTEamp4wfMNqRtvb+p1YA1ERGpF10nmu2BpZB3wmCzooKyxG+PyfUbl4iIiIiUUoJXRKSmnAneem7PAJBRroJXRESkzoR3hBZdwF4Ie+ZX3Ld/EeSnQ0BLaDPUPfGJiIiIiBK8IiI15sYEb6YSvCIiUl9O1aZh2/dm230SWG31GpKIiIiIlFGCV0SkptxZwZtrWjQEqUWDiIjUtS4lCd7dv5oBowDFhbDjR7PurvYMIiIiIu6kBK+ISE01iApeJXhFRKSOtRkCvmGQlwbxK81jB5ZC7nHwC4e2I90anoiIiEhzpwSviEhNuTXB6xyyphYNIiJSx6w26DLBrJ1tGrbPNNtuF4JNv4tERERE3EkJXhGRmshLh9xUsw5tW++Xd1bwBinBKyIi9cHZh3fHj2Avhu2zzP0eU9wXk4iIiIgASvCKiNTM8YNm69cCvAPr/fJlFbxq0SAiIvWg4zlg84Lj+2Hdx5B9DHxCoP1Z7o5MREREpNlTgldEpCbc2J4ByvfgVQWviIjUA+8AaD/GrOf+1Wy7TgSbPmgUERERcTcleEVEaqLBJHj1xlpEROqJs01DfrrZqj2DiIiISIOgBK+ISE24OcGboSFrIiJS37pcULb2CoSOZ7svFhEREREppQSviEhNNJgKXiV4RUSkngTHQKu+Zt11Anh4uzceEREREQGU4BURqZkGUsEb5KsWDSIiUo9GPQhhHWH4ve6ORERERERKqPRLRKS67MWQFmfWbkjw7kzILK3gDff3qvfri4hIM9bzYnMTERERkQZDFbwiItWVcQTshWD1hKDoer/8q/N3ATCxdxQhfkrwioiIiIiIiDRnSvCKiFSXsz1DSCxYbSfvzi5g6e5kiu0Ol19625EMftqcgMUC953bxeXnFxEREREREZHGRQleqZbFixczadIkoqOjsVgsfP/99xX233TTTVgslgq3CRMmVDgmNTWVa6+9lqCgIEJCQrj11lvJysqqx1chUkun6b/rcDi46cPVXPf+Km74YBVJmXkuvfQr80z17kV9oukaFejSc4uIiIiIiIhI46MEr1RLdnY2ffv25Y033jjlMRMmTODo0aOlty+++KLC/muvvZatW7cyd+5cZs+ezeLFi5k6dWpdhy7iOqdJ8C7adYyNh9IBWLYnhYmvLmHp7mSXXHbL4XR+3ZaI1QL3ndvZJecUERERERERkcZNQ9akWi644AIuuOCC0x7j7e1NVFRUpfu2b9/OnDlzWLNmDYMGDQLgtddeY+LEifz73/8mOrr++5mKVNtpErz/W7gXgAv7tGJvUhY7EjK5/oNV3DO2E/eP64yHreafqzmrdyf3jaZTZECNzyMiIiIiIiIiTYcqeMXlFi5cSGRkJF27duWuu+4iJSWldN+KFSsICQkpTe4CjBs3DqvVyqpVq9wRrkj1nSLB+/uBVFbvT8XTZuGpC3vw/T0juWZoLA4HvL5gD1e/u5Kj6bk1uuTG+DTmbU/CaoE/qXpXREREREREREoowSsuNWHCBKZNm8b8+fN54YUXWLRoERdccAHFxcUAJCQkEBkZWeE5Hh4ehIWFkZCQcMrz5ufnk5GRUeEm4janSPA6q3cvG9CaqGAffDxt/OuS3rx2dX8CvD1Yc+A4E19dwvztidW+5H9Kqncv6d+aDhGq3hURERERERERQy0axKWuuuqq0nXv3r3p06cPHTt2ZOHChZx77rk1Pu9zzz3H3/72N1eEKFI7+ZmQU9JTN7Rt6cPbj2bw2w5TYXvHWR0rPGVS32h6xwTzxy/Ws/lwOrd+/Du3jWrPnyd0w8vjzJ+zrYs7zsKdx7BZLfzp3E4ufTkiIiIiIiIi0ripglfqVIcOHWjRogV79uwBICoqiqSkpArHFBUVkZqaesq+vQCPPfYY6enppbf4+Pg6jVvklI4fNFvfMPAJLn34zZLq3Ym9W9G+hf9JT2vXwp9v7xrOLSPbA/De0v1c8dZy4lNzTnu5vMJinv9pBwCXDYihbfjJ5xYRERERERGR5ksJXqlThw4dIiUlhVatWgEwfPhw0tLSWLt2bekxv/32G3a7naFDh57yPN7e3gQFBVW4ibhFJe0ZDiRnM3vTEQDuGtvx5OeU8Paw8fSkHrxz/UCCfT3ZeCidif9dwk+bj1Z6fEZeITd+sJrVB1Lx9rDyx3PUe1dEREREREREKlKCV6olKyuLDRs2sGHDBgD279/Phg0biIuLIysri0ceeYSVK1dy4MAB5s+fz5QpU+jUqRPjx48HoHv37kyYMIHbb7+d1atXs2zZMu69916uuuoqoqOj3fjKRKqokgTv24v3YXfA2K4R9IwOrvRp5Z3fM4qf7hvNgNgQMvOKuPuzdTz1/RbyCotLj0nKyOMPb69k1f5UArw9+PDmwbQJ83PxixERERERERGRxk4JXqmW33//nf79+9O/f38AHnzwQfr378/TTz+NzWZj06ZNTJ48mS5dunDrrbcycOBAlixZgre3d+k5PvvsM7p168a5557LxIkTGTVqFO+88467XpJI9ZyQ4E3MyOO7tYcAuOfsqvfHjQnx5as7hpdW/H6y8iCX/G85+45lsT85m8veWs72oxm0CPDmy6nDGNGxhStfhYiIiIiIiIg0ERqyJtUyduxYHA7HKff/8ssvZzxHWFgYn3/+uSvDEqk/JyR4P1i6n4JiO4PbhTK4XVi1TuVps/LohG4MbR/GQ19vZPvRDC56bSk+njZSswtoG+7HtFuGqO+uiIiIiIiIiJySKnhFRKqjXIK3sNjOtyXVu1PHnLr37pmM7RrJT/eNZliHMHIKiknNLqBndBDf3jlCyV0REREREREROS1V8IqIVJXdDmkHzTq0HYt3HSMlu4AWAV6c3TWiVqduGeTDZ7cN48Nl+4lPzeHh8V0J9PF0QdAiIiIiIiIi0pQpwSsiUlWZR6G4AKweEBTD9J83ATCpbzQettp/IcJmtXDb6A61Po+IiIiIiIiINB9q0SAiUlXO9gzBbcgodDBvWyIAl/Zv7b6YRERERERERKRZU4JXRKSqyvXfnbM5gfwiO50iA+gVE+TWsERERERERESk+VKCV0SkqsoleKevN8PVLukfg8VicV9MIiIiIiIiItKsqQeviMipFBfB0Y1wYDHsXwwHVwCQ7hvDyn2pAEzpF+3OCEVERERERESkmVOCV0Tk+EFY/Q5kH4PcNMhLM9uMI1CQWfHYwGh+zOsLFDK0fRitQ/3qP14RERERERERkRJK8IpI82a3U/j1zXgeXVv5fu9gaDcK2o+B9mNwRHTjg1eWAIVcOiCmXkMVERERERERETmRErwi0mwV2x2s/u4/DD+6liyHD68VXUIaAaQ7/EnHn1SCGDNwJH+e2BNPm2lZvuVQOnuSsvD2sHJB71ZufgUiIiIiIiIi0twpwSsizdKWw+m8MH0ZryW/DBb41Pc6tkf+gYzcQjLyCsnMK+JYZj47l8Wx8UgWr1/Tn8hAH2asPwzAuB4tCfLxdPOrEBEREREREZHmTgleEWlWsvKL+M/cXXy4bD/P294mxCOb1MCu3H7f89zpUTFhO2fLUR7+ZhOr96dy0X+X8t+r+zNz4xEALumn9gwiIiIiIiIi4n5K8IpIs+BwOPhlawJ/nbmNhIw8Bll2cKXHIgDCrnwdPE6uxp3QqxWdWwZy16dr2ZWYxVXvrDTH+3txVteIeo1fRERERERERKQyVncHICJS1+JTc7j149+589N1JGTk0T7Ui48ivzQ7B9wAbYac8rkdIwKYcfdIJvWNLn1sUp9WpT15RURERERERETcSRW8ItJkFRbbeW/Jfl6dv4u8QjueNgt3ntWRP/nOwXP+LvANg3F/O+N5/L09+O9V/RjcLpQ5WxK4bXSHeoheREREREREROTMlOAVkSZpzYFUnpixmV2JWQAM6xDGsxf3ppN3Orz+gjnovL+DX1iVzmexWLhheDtuGN6ujiIWEREREREREak+JXhFpEk5nl3A8z/v4Kvf4wEI9/fiiQu7c0n/GCwWC3x1FxRmQ5uh0O9aN0crIiIiIiIiIlI7SvCKSJPgcDj4du0h/vXTdo7nFAJw9ZA2PDqhGyF+Xuag3XNh+0yw2ODC/wOr+uiKiIiIiIiISOOmBK+INAlvL97H8z/vAKBbVCD/vKQXA9uWa79QmAs/PWzWw+6CqF5uiFJERERERERExLWU4BWRRm9PUhb/N3cXAH86tzN/PKcTnrYTqnOX/geOH4DAaBj7l/oPUkRERERERESkDijBKyKNWrHdwaPfbaKgyM5ZXSJ4YFxn02u3vJS9JsELMOE58A6s/0BFREREREREROqAGlCKSKM2bcUB1h48jr+XjX9d2vvk5K7DAT8+BMUF0PFc6DHFPYGKiIiIiIiIiNQBJXhFpNGKT83hxTk7AfjLxO7EhPiefNDWGbBvAdi8YeJLcGICWERERERERESkEVOLBhGplsy8QuJTc4k/nkN8ag6H03IJ9PagR3QwPaODaB3qe3IVbR1wOBz8ZfomcguLGdI+jGuHxJ58UF4GzHnMrEc/COEd6zwuEREREREREZH6pASviFRJdn4RV769gq1HMk57XLCvJz2jg+gZHUSvGJP0bd8iAJvVtUnfr9bEs2xPCj6eVl68rA/Wys6/8DnISoDQ9jDyfpdeX0RERERERESkIVCCV0Sq5J3F+0qTu6F+nrQJ86NNqB8xob4czy5g65EMdidlkp5byPK9KSzfm1L6XF9PG91aBdKrpMq3Z3QwXaIC8Paw1SiWhPQ8/vnjdgAeOq8r7Vr4n3zQ0U2w6i2zvvDf4OlTo2uJiIiIiIiIiDRkSvCKyBklZeTxzuJ9ALx2dX8m9Y2u9Lj8omJ2J2ax9Ug6W49ksOVwOtuPZpJbWMz6uDTWx6WVHuthtdC5ZWCFat/urYII8D79X0sOh4PHpm8iM7+Ivm1CuGVU+5MPstvNYDWHHXpcDJ3G1fSli4iIiIiIiIg0aErwisgZ/WfeLnILi+kfG8JFfVqd8jhvDxu9YoLpFRNc+lix3cH+5OzSpK9zm5ZTyPajGWw/msG3a82xFgu0D/fn7rM7cfnA1pVe45u1h1iw8xheNiv/vrxP5a0f1n8Ch1aDVwBMeK5Wr11EREREREREpCFTgldETmtXYiZfrYkH4ImJ3as9QM1mtdApMoBOkQFM6RcDmCrcw2m5JQnfDLYdSWfL4QwSMvLYl5zNI99uxNvDelKl8JG0XP4xaxsAD57fhc4tA0++YHYKzHvGrM9+HIIqrzYWEREREREREWkKlOAVkdN6/ucd2B0wvmdLBrULc8k5LRYLrUP9aB3qx/ieUaWPp2Tl8595u/h0ZRwPfb2RcH8vRnRqAZik8KPfmdYM/WNDuH10h8pPPu9pyD0OLXvBkDtcEq+IiIiIiIiISENldXcAItJwLd+bzG87kvCwWnh0Qrc6v154gDd/m9yLib2jKCi2M/WTtWw9kg7Al2viWbI7GW8PK/++om/lrRniVsL6T836wpfBps+wRERERERERKRpU4JXRCpltzv410/bAbhmaCwdIgLq5bo2q4X/u7IfQ9uHkZVfxE0frmHF3hSenW1aMzwyvisdK4uluBBmP2jW/a+H2GH1Eq+IiIiIiIiIiDspwSsipOUUsP1oBnEpOSRn5ZNbUMwPGw+z5XAGAd4e3Hdu53qNx8fTxjs3DKJbVCDHMvO5+t2VZBcUM6htKDePbF/5kzZ8DklbwTcUxv2tXuMVEREREREREXEXfX9ZpJk7nl3Aef9ZTHJWfqX77xrbkfAA73qOCoJ9Pfn4liFc+r/lHE7LxcfTykunas0AsPkbsx15H/iH11+gIiIiIiIiIiJupApekWbuxV92kpyVj7eHFT8vW4V97Vv4c8upKmbrQcsgH6bdOoTxPVvy6lX9ad/Cv/IDMxPgwFKz7nVZ/QUoIiIiIiIiIuJmquAVacY2HUrjyzVxAEy7ZQhDO4RjtzvILSwmO7+IED8vvDzc+zlQx4gA3r5+0OkP2jYTcEDrwRASWy9xiYiIiIiIiIg0BKrgFWmm7HYHT/2wFYcDLu4XzdAOpq2B1WrB39uDyCCf+k/u5qTC3KfLqnGrausMs+15ietjEhERERERERFpwJTgFWmmvlkbz8b4NAK8PXh8Ynd3hwP5WfDZFbDsVbNN3Fa152UcgbgVZt1jSt3FJyIiIiIiIiLSACnBK9IMpeUU8MKcnQDcP64zkUE+7g2oKB++uhYO/27uF+bAV9dBXsaZn+tsz9BmKAS3rtMwRUREREREREQaGiV4RRqh3IJidiZkkpSZR1GxvdrPf/nXXaRmF9ClZQA3jmjn+gCrw14M02+HfQvB0x+u+QaCWkPqXvjhbnA4Tv98tWcQERERERERkWZMQ9ZEGpn8omIuf2s5W4+Y6laLBUJ8PWkR4E14gBctArzN2t+LFoFmGx7gTUTJ/v3J2Xy26iAAf5vcC0+bGz/ncThg9v2w7QewecFVn0HHs+HKj+GDCbB9Fix/DUb+qfLnpx+G+JWARe0ZRERERERERKRZUoJXpJF5Zd5uth7JwGa14HA4sDvgeE4hx3MK2Z105udbLCavOqlvNMM7htd9wKcz76+wbhpYrHDZeya5C9B6EFzwPPz4kDkmZgC0G3Xy87f9YLaxwyEour6iFhERERERERFpMJTgFWlE1h5M5e1FewH437UDGNe9JcdzCkjJKiAlK59jWflmnZ1PcmbJttz93MJiHA4I8fPkCXcPVlv2Kix7xawveuXkCtxBt0L8Gtj0JXxzM9yxGIJaVTxm63SzVXsGEREREREREWmmlOAVaSRyCop46OuN2B1w6YAYxveMAihtyQCBVTpHcmYBwX6eBPt61nHEp7FuGsx92qzH/Q0G3njyMRYLXPQfSNgMSVvhwwvgymnQqo/ZnxYHh9Zg2jNMrrfQRUREREREREQaEg1ZE2kknv95BwdScmgV7MMzk3rW6Bx+Xh7Ehvu5N7m7bSbMus+sR94Ho+4/9bFefnDVpxDcBo7vh/fPg3WflJynpD1D25EQGFWnIYuIiIiIiIiINFRK8Io0Akt3JzNthRmM9uLlfdyboK2NvQvgu1vBYYcBN5jq3TMJ62DaM3Q+H4ryYOa98P09sPkbs7+X2jOIiIiIiIiISPOlFg0iDchzP21n+vrDdG0ZSO/WwfSJCaZTZACPfLsRgOuHtWV05wg3R1lDh9bCl9dCcQF0n2z67losVXuuXxhc/RUs/T9Y8E/Y8Kl53GI15xIRERERERERaaaU4BVpIL5YHcfbi/cBcCwzn6V7kivsbxfux2MTu7kjtNo7thM+uwwKs6HDWLjsPbDaqncOqxXGPAytB5sq4Oxj0G4UBETWScgiIiIiIiIiIo2BErwiDcDag8d5+octANwxpgNtw/3ZfDiNTYfS2ZmQic1q4eUr++Ln1Qj/yKbFwbSLIfc4xAyEP3wGHt41P1+Hs+COJfD7+9D7CpeFKSIiIiIiIiLSGDXCbJFI05KUkcddn66lsNjBhJ5R/OWCblgsFiAWgLzCYvKL7I2z727WMZPczTwCEd3g2m/BO6D25w1qBec8WfvziIiIiIiIiIg0ckrwirhRQZGduz5bR1JmPp0jA/j3lX1LkrtlfDxt+HhWs51BQ5CXDp9eCql7ITgWrp9heumKiIiIiIiIiIjLWN0dgEhz9tdZW1l78DiBPh68c8MgArybyGcuhbnwxdWQsAn8WsAN30NQtLujEhERERERERFpcpTgFXGTL1bH8fmqOCwW+O/V/Wnfwt/dIblGcSF8czMcXAbeQXD9dAjv6O6oRERERERERESaJCV4RdygoMjO24v2AvDw+V05u2ukmyNyEbsdfrgXdv0MHj5w9ZfQqq+7oxIRERERERERabKayPfBRRoXLw8r3901gs9XxXH32CZS3epwwC+Pw6YvwWKDKz6CdiPdHZWIiIiIiIiISJOmBK+Im4QHePPHczu7O4xTy0mFw+sgeSccK7ml7IawDnDOk9BhbMXjF78Eq94064vfhK4X1HvIIiIiIiIiIiLNjRK8InKynFR4fRDkpFSyLwWmTYHO58N5f4fI7rD6XVjwT7N/wgvQ9w/1G6+IiIiIiIiISDOlBK+InGz1OyaR6xsG7UZBRFeI6Aah7WHz17DmPdj9K+yZB53Hw6455nlnPQrD7nRv7CIiIiIiIiIizYgSvCJSUX4mrCxptTDxJeh9ecX9rQfCkKkw76+wfaYZqAbmsbGP1WuoIiIiIiIiIiLNnRK8IlLR7x9AXhqEdYSel1R+THhH+MMnELcKlrwMLTrDef8Ai6VeQxURERERERERae6U4BWRMoW5sPx1sx79IFhtpz8+dihc+3XdxyUiIiIiIiIiIpWyujsAEWlA1n8K2UkQ3Ab6aFCaiIiIiIiIiEhDpwSviBhFBbDsVbMeeR/YPN0bj4iIiIiIiIiInJESvCLNjcNhbifa9BWkx0NAS+h/Xf3HJSIiIiIiIiIi1aYEr0hzkp0C75wF/+4Mvz0LmQnmcXsxLP2PWQ+/Fzx93RejiIiIiIiIiIhUmYasiTQXeRnw6aVwdKO5v/glWPoK9LoUwjtB6l7wDYVBt7g1TBERERERERERqToleEWag4Ic+OIqOLoB/MLhnCdh09cQt8K0ZnAaehd4B7gtTBERERERERERqR4leEWauqIC+PoGOLgMvIPguukQ3c9U6h5eB6vegi3TTeJ36FR3RysiIiIiIiIiItVgcTgqm7Yk0rBlZGQQHBxMeno6QUFB7g6n4bIXw3e3wtYZ4OEL18+AtsNPPi73OGAB35D6jlBEREREREREylHOQ6pLFbwiTZXDAbPvN8ldqydc9WnlyV0wvXdFRERERERERKTRsbo7ABGpAw4H/PokrJsGFitc/j50GufuqERERERERERExMWU4BVpiha/BCteN+vJr0OPKe6NR0RERERERERE6oQSvCJNzco3YcE/zXrC89D/WvfGIyIiIiIiIiIidUYJXpGmZP2nMOcvZj32cRh2l3vjERERERERERGROqUEr0hTse0HmPlHsx5+L5z1Z/fGIyIiIiIiIiIidU4JXpGmYM88+PZWcNih//Vw/rNgsbg7KhERERERERERqWNK8Io0dgdXwJfXgb0Qel4Ck15VcldEREREREREpJlQglekMTuyAT6/EopyodN5cMk7YLW5OyoREREREREREaknSvCKNCSH18Lif0Nh3pmPPbYLPr0U8jOg7Ui4chp4eNV9jCIiIiIiIiIi0mB4uDsAESnhcJg+usf3Q+5xGP/PUx97/CBMmwI5KdCqH1z9JXj51VuoIiIiIiIiIiLSMKiCV6ShOLjcJHcBVv4Pjqyv/Lj8TPjscsg8AhHd4Lrp4BNUf3GKiIiIiIiIiEiDoQSvSEOx/lOztXmBww4z/wTFRRWPcTjgh3sheRcERsP1M8A/vP5jFRERERERERGRBkEJXpGGID8Ttn1v1pd/AD4hkLAJVr5R8biVb5rjrJ6m525QdD0HKiIiIiIiIiIiDYkSvCINwdbvoTAHwjtDt4vK+u8ueA5SS9o2HFwBc58y6/H/gjaD3RKqiIiIiIiIiIg0HErwijQEGz4z237XgMUC/a6F9mOgKBdm3w+ZifDNTWAvgl6Xw5Db3RmtiIiIiIiIiIg0EErwirhbyl6IWwEWK/S92jxmscBFr4CHD+xbCO+eA1kJ0KIrTHrV7BcRERERERERkWZPCV4Rd3NW73Y8F4JalT0e3hHOetSsMw6BVwD84VPwDqj/GEVEREREREREpEFSglfEnezFsOELs+5/3cn7R/wRWvUFLDD5NYjoUq/hiYiIiIiIiIhIw+bh7gBEmrW9CyDzCPiGQtcLTt5v84QbZ0NWErToVP/xiYiIiIiIiIhIg6YEr4g7bfjUbHtfCR7elR/jE2RuIiIiIiIiIiIiJ1CLBhF3yUmFHT+adf9r3RuLiIiIiIiIiIg0SkrwirjLlu+guABa9i7psysiIiIiIiIiIlI9SvCKuMv6kvYMqt4VEREREREREZEaUoJXxB0cDjjrUeg+yfTfFRERERERERERqQENWRNxB4sFuk00NxERERERERERkRpSBa+IiIiIiIiIiIhII6UEr4iIiIiIiIiIiEgjpQSviIiIiIiIiIiISCOlBK+IiIiIiIiIiIhII6UEr4iIiIiIiIiIiEgjpQSviIiIiIiIiIiISCOlBK+IiIiIiIiIiIhII6UEr4iIiIiIiIiIiEgjpQSviIiIiIiIiIiISCOlBK+IiIiIiIiIiIhII6UEr4iIiIiIiIiIiEgjpQSviIiIiIiIiIiISCOlBK9Uy+LFi5k0aRLR0dFYLBa+//77CvsdDgdPP/00rVq1wtfXl3HjxrF79+4Kx6SmpnLttdcSFBRESEgIt956K1lZWfX4KkRERERERERERJoGJXilWrKzs+nbty9vvPFGpftffPFF/vvf//LWW2+xatUq/P39GT9+PHl5eaXHXHvttWzdupW5c+cye/ZsFi9ezNSpU+vrJYiIiIiIiIiIiDQZFofD4XB3ENI4WSwWZsyYwcUXXwyY6t3o6GgeeughHn74YQDS09Np2bIlH330EVdddRXbt2+nR48erFmzhkGDBgEwZ84cJk6cyKFDh4iOjq7StTMyMggODiY9PZ2goKA6eX0iIiIiIiIiIvVNOQ+pLlXwisvs37+fhIQExo0bV/pYcHAwQ4cOZcWKFQCsWLGCkJCQ0uQuwLhx47BaraxatareYxYREREREREREWnMPNwdgDQdCQkJALRs2bLC4y1btizdl5CQQGRkZIX9Hh4ehIWFlR5Tmfz8fPLz80vvZ2RkuCpsERERERERERGRRksVvNIoPPfccwQHB5fe2rRp4+6QRERERERERERE3E4JXnGZqKgoABITEys8npiYWLovKiqKpKSkCvuLiopITU0tPaYyjz32GOnp6aW3+Ph4F0cvIiIiIiIiIiLS+CjBKy7Tvn17oqKimD9/fuljGRkZrFq1iuHDhwMwfPhw0tLSWLt2bekxv/32G3a7naFDh57y3N7e3gQFBVW4iYiIiIiIiIiINHfqwSvVkpWVxZ49e0rv79+/nw0bNhAWFkbs/7d37zFV138cx18Hf4aQhopyFeR08dLN6EZQLUlLKlOba+k0spGN1Jlpl3XVWqVdxJJW2ipsZjddk1apLZVu0paEKealTFQSscswSQXhvH9/NM/CK8KB4weej+384fl+/Hw/n89e44/XOTvfxERNmjRJTz/9tM455xx5vV49/vjjiouL07BhwyRJffv2VUZGhsaOHas5c+bo4MGDmjBhgkaMGKG4uLgg7QoAAAAAAABwEwUvTsrq1auVnp7u//fkyZMlSXfccYfmzZunBx98UP/884/uvvtuVVZW6qqrrtLSpUvVoUMH//9ZsGCBJkyYoAEDBigkJETDhw/X7NmzT2odZiaJh60BAAAAAIDW5VDXPBlsaQAAEFZJREFUcaj7AE7EY6QFDiorK+NBawAAAAAAoNXasWOHevToEexlwAEUvHCSz+fTzp071alTJ3k8nmAvp56///5bCQkJ2rFjB78VjGZDztBQZAXNjYwh0MgUWgI5Q6CRKQSSmWnv3r2Ki4tTSAiPz8KJ8RMNcFJISMgp/ykWD4NDSyBnaCiyguZGxhBoZAotgZwh0MgUAiUiIiLYS4BD+BgAAAAAAAAAABxFwQsAAAAAAAAAjqLgBQIsNDRUU6dOVWhoaLCXglaMnKGhyAqaGxlDoJEptARyhkAjUwCCiYesAQAAAAAAAICj+AYvAAAAAAAAADiKghcAAAAAAAAAHEXBCwAAAAAAAACOouAFAAAAAAAAAEdR8KLNmD59ui677DJ16tRJUVFRGjZsmDZt2lRvzIEDBzR+/HhFRkaqY8eOGj58uCoqKvzXf/zxR40cOVIJCQkKCwtT37599fLLL9eb45tvvtGVV16pyMhIhYWFqU+fPpo1a9YJ12dmeuKJJxQbG6uwsDANHDhQP//8c70xzzzzjNLS0hQeHq7OnTs3/jDQLFzPWGlpqbKysuT1ehUWFqazzjpLU6dOVU1NTRNPBodzPSuSNGTIECUmJqpDhw6KjY3V7bffrp07dzbhVBBorSFnh1RXV+uiiy6Sx+PRmjVrTv4wEBCtIVNJSUnyeDz1XjNmzGjCqSCQWkPGJOnTTz9VSkqKwsLC1KVLFw0bNqxxB4Imcz1TBQUFR/zNOvT6/vvvm3g6AFoVA9qIQYMGWV5enpWUlNiaNWvsxhtvtMTERKuqqvKPyc7OtoSEBFu+fLmtXr3arrjiCktLS/Nff/PNN23ixIlWUFBgW7Zssfnz51tYWJjl5ub6x/zwww/27rvvWklJiW3dutXmz59v4eHhNnfu3OOub8aMGRYREWGLFy+2H3/80YYMGWJer9f279/vH/PEE09YTk6OTZ482SIiIgJ3OAgI1zO2ZMkSGzNmjC1btsy2bNli+fn5FhUVZVOmTAnwScH1rJiZ5eTkWGFhoZWWltq3335rqamplpqaGsBTQlO1hpwdMnHiRLvhhhtMkhUXFzf9cNAorSFTPXv2tKeeesrKy8v9r/+uH8HVGjK2aNEi69Kli7322mu2adMmW79+vX3wwQcBPCWcDNczVV1dXe/vVXl5ud11113m9XrN5/MF+LQAuIyCF23W7t27TZJ9+eWXZmZWWVlp7du3t4ULF/rHbNiwwSRZYWHhMecZN26cpaenH/det9xyi40ePfqY130+n8XExNgLL7zgf6+ystJCQ0PtvffeO2J8Xl4eBa8DXM7YIc8//7x5vd7j3htN1xqykp+fbx6Px2pqao57fwSPqzn77LPPrE+fPrZ+/XoK3lOMi5nq2bOnzZo160RbwynCtYwdPHjQ4uPj7Y033mjQ/tDyXMvU4Wpqaqx79+721FNPHffeANoefqIBbdaePXskSV27dpUkFRUV6eDBgxo4cKB/TJ8+fZSYmKjCwsLjznNojqMpLi7WqlWrdM011xxzzNatW7Vr1656946IiFBKSspx741TW2vI2InujcBwPSt//fWXFixYoLS0NLVv3/6YcyO4XMxZRUWFxo4dq/nz5ys8PPzEm0SLcjFTkjRjxgxFRkYqOTlZL7zwgmpra4+/UQSNaxn74Ycf9NtvvykkJETJycmKjY3VDTfcoJKSkoZtGM3OtUwd7uOPP9aff/6pO++885jzAmib/hfsBQDB4PP5NGnSJF155ZU6//zzJUm7du3SaaeddsRv20ZHR2vXrl1HnWfVqlX64IMP9Omnnx5xrUePHvr9999VW1uradOm6a677jrmeg7NHx0d3eB749TWGjL2yy+/KDc3Vy+++OIx50XTuZyVhx56SK+88or27dunK664Qp988skJ94vgcDFnZqYxY8YoOztbl156qUpLSxu6XbQAFzMlSRMnTtTFF1+srl27atWqVXr44YdVXl6unJycBu0bLcfFjP3666+SpGnTpiknJ0dJSUmaOXOm+vfvr82bN/OheZC5mKnDvfnmmxo0aJB69OhxzHkBtE18gxdt0vjx41VSUqL333+/0XOUlJRo6NChmjp1qq6//vojrn/99ddavXq15syZo5deeknvvfeeJGnBggXq2LGj//X11183eg04dbmesd9++00ZGRm69dZbNXbs2EbvASfmclYeeOABFRcX6/PPP1e7du2UmZkpM2v0PtB8XMxZbm6u9u7dq4cffrjRa0bzcTFTkjR58mT1799fF154obKzszVz5kzl5uaqurq60ftA83AxYz6fT5L06KOPavjw4brkkkuUl5cnj8ejhQsXNnofCAwXM/VfZWVlWrZsmbKyshq9fgCtF9/gRZszYcIEffLJJ/rqq6/qffIZExOjmpoaVVZW1vsEt6KiQjExMfXm+OmnnzRgwADdfffdeuyxx456H6/XK0m64IILVFFRoWnTpmnkyJEaMmSIUlJS/OPi4+NVXl7uv1dsbGy9e1900UVN3TJamOsZ27lzp9LT05WWlqbXX3+9UWeAhnE9K926dVO3bt3Uq1cv9e3bVwkJCfruu++UmpraqPNA83A1ZytWrFBhYaFCQ0Pr3efSSy/VqFGj9Pbbb5/8YSAgXM3U0aSkpKi2tlalpaXq3bt3g88AzcvVjB16/9xzz/VfDw0N1Zlnnqnt27c34iQQKK5m6r/y8vIUGRmpIUOGnPT+AbQBwf4RYKCl+Hw+Gz9+vMXFxdnmzZuPuH7oB/YXLVrkf2/jxo1H/MB+SUmJRUVF2QMPPNDgez/55JPWs2fP464tJibGXnzxRf97e/bs4SFrjmkNGSsrK7NzzjnHRowYYbW1tQ2+P05Oa8jK4bZt22aSbOXKlQ1eC5qX6znbtm2brVu3zv9atmyZSbJFixbZjh07GrwWBI7rmTqad955x0JCQuyvv/5q8FrQfFzP2KF///chazU1NRYVFWVz585t8FoQOK5n6r9jvV6vTZkypcH3B9C2UPCizbjnnnssIiLCCgoKrLy83P/at2+ff0x2drYlJibaihUrbPXq1Zaammqpqan+6+vWrbPu3bvb6NGj682xe/du/5hXXnnFPv74Y9u8ebNt3rzZ3njjDevUqZM9+uijx13fjBkzrHPnzpafn29r1661oUOHmtfrtf379/vHbNu2zYqLi+3JJ5+0jh07WnFxsRUXF9vevXsDeFJoLNczVlZWZmeffbYNGDDAysrK6t0fgeV6Vr777jvLzc214uJiKy0tteXLl1taWpqdddZZduDAgQCfFhrL9ZwdbuvWrSbJiouLm3YwaDTXM7Vq1SqbNWuWrVmzxrZs2WLvvPOOde/e3TIzMwN8Umgs1zNmZnbvvfdafHy8LVu2zDZu3GhZWVkWFRXFhwhB0hoyZWb2xRdfmCTbsGFDgE4GQGtDwYs2Q9JRX3l5ef4x+/fvt3HjxlmXLl0sPDzcbrnllnrl1tSpU486x38/mZ09e7add955Fh4ebmeccYYlJyfbq6++anV1dcddn8/ns8cff9yio6MtNDTUBgwYYJs2bao35o477jjq/fnG3KnB9Yzl5eUdcw8ILNezsnbtWktPT7euXbtaaGioJSUlWXZ2tpWVlQXsjNB0rufscBS8wed6poqKiiwlJcUiIiKsQ4cO1rdvX3v22Wf5YOoU4nrGzP79xu6UKVMsKirKOnXqZAMHDrSSkpKAnA9OXmvIlJnZyJEjLS0trcnnAaD18pjxNBQAAAAAAAAAcFFIsBcAAAAAAAAAAGgcCl4AAAAAAAAAcBQFLwAAAAAAAAA4ioIXAAAAAAAAABxFwQsAAAAAAAAAjqLgBQAAAAAAAABHUfACAAAAAAAAgKMoeAEAAAAAAADAURS8AAAAaBPGjBkjj8cjj8ej9u3bKzo6Wtddd53eeust+Xy+Bs8zb948de7cufkWCgAAAJwECl4AAAC0GRkZGSovL1dpaamWLFmi9PR03XvvvRo8eLBqa2uDvTwAAADgpFHwAgAAoM0IDQ1VTEyM4uPjdfHFF+uRRx5Rfn6+lixZonnz5kmScnJydMEFF+j0009XQkKCxo0bp6qqKklSQUGB7rzzTu3Zs8f/beBp06ZJkqqrq3X//fcrPj5ep59+ulJSUlRQUBCcjQIAAKDNoOAFAABAm3bttdeqX79++uijjyRJISEhmj17ttavX6+3335bK1as0IMPPihJSktL00svvaQzzjhD5eXlKi8v1/333y9JmjBhggoLC/X+++9r7dq1uvXWW5WRkaGff/45aHsDAABA6+cxMwv2IgAAAIDmNmbMGFVWVmrx4sVHXBsxYoTWrl2rn3766YhrixYtUnZ2tv744w9J//4G76RJk1RZWekfs337dp155pnavn274uLi/O8PHDhQl19+uZ599tmA7wcAAACQpP8FewEAAABAsJmZPB6PJOmLL77Q9OnTtXHjRv3999+qra3VgQMHtG/fPoWHhx/1/69bt051dXXq1atXvferq6sVGRnZ7OsHAABA20XBCwAAgDZvw4YN8nq9Ki0t1eDBg3XPPffomWeeUdeuXfXNN98oKytLNTU1xyx4q6qq1K5dOxUVFaldu3b1rnXs2LEltgAAAIA2ioIXAAAAbdqKFSu0bt063XfffSoqKpLP59PMmTMVEvLv4yo+/PDDeuNPO+001dXV1XsvOTlZdXV12r17t66++uoWWzsAAABAwQsAAIA2o7q6Wrt27VJdXZ0qKiq0dOlSTZ8+XYMHD1ZmZqZKSkp08OBB5ebm6uabb9a3336rOXPm1JsjKSlJVVVVWr58ufr166fw8HD16tVLo0aNUmZmpmbOnKnk5GT9/vvvWr58uS688ELddNNNQdoxAAAAWruQYC8AAAAAaClLly5VbGyskpKSlJGRoZUrV2r27NnKz89Xu3bt1K9fP+Xk5Oi5557T+eefrwULFmj69On15khLS1N2drZuu+02de/eXc8//7wkKS8vT5mZmZoyZYp69+6tYcOG6fvvv1diYmIwtgoAAIA2wmNmFuxFAAAAAAAAAABOHt/gBQAAAAAAAABHUfACAAAAAAAAgKMoeAEAAAAAAADAURS8AAAAAAAAAOAoCl4AAAAAAAAAcBQFLwAAAAAAAAA4ioIXAAAAAAAAABxFwQsAAAAAAAAAjqLgBQAAAAAAAABHUfACAAAAAAAAgKMoeAEAAAAAAADAURS8AAAAAAAAAOAoCl4AAAAAAAAAcBQFLwAAAAAAAAA4ioIXAAAAAAAAABxFwQsAAAAAAAAAjqLgBQAAAAAAAABHUfACAAAAAAAAgKMoeAEAAAAAAADAURS8AAAAAAAAAOAoCl4AAAAAAAAAcBQFLwAAAAAAAAA4ioIXAAAAAAAAABxFwQsAAAAAAAAAjqLgBQAAAAAAAABHUfACAAAAAAAAgKMoeAEAAAAAAADAURS8AAAAAAAAAOAoCl4AAAAAAAAAcBQFLwAAAAAAAAA4ioIXAAAAAAAAABxFwQsAAAAAAAAAjqLgBQAAAAAAAABHUfACAAAAAAAAgKMoeAEAAAAAAADAURS8AAAAAAAAAOCo/wPmcdVgJyD5tQAAAABJRU5ErkJggg==",
|
||
"text/plain": [
|
||
"<IPython.core.display.Image object>"
|
||
]
|
||
},
|
||
"execution_count": 5,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"from IPython.display import Image\n",
|
||
"\n",
|
||
"Image(filename='coding/stock_price_ytd.png')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Use a Different Code Execution Environment\n",
|
||
"\n",
|
||
"The code execution happened in a separate process, so the plot is not directly displayed in the notebook. Is it possible to change the code execution environment into IPython?\n",
|
||
"\n",
|
||
"Yes! In the following we demonstrate how to extend the `UserProxyAgent` to use a different code execution environment."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 6,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"from typing import Dict, Union\n",
|
||
"from IPython import get_ipython\n",
|
||
"\n",
|
||
"class IPythonUserProxyAgent(UserProxyAgent):\n",
|
||
" def __init__(self, name: str, **kwargs):\n",
|
||
" super().__init__(name, **kwargs)\n",
|
||
" self._ipython = get_ipython()\n",
|
||
"\n",
|
||
" def generate_init_message(self, *args, **kwargs) -> Union[str, Dict]:\n",
|
||
" return super().generate_init_message(*args, **kwargs) + \"\"\"\n",
|
||
"If you suggest code, the code will be executed in IPython.\"\"\"\n",
|
||
"\n",
|
||
" def run_code(self, code, **kwargs):\n",
|
||
" result = self._ipython.run_cell(code)\n",
|
||
" log = str(result.result)\n",
|
||
" exitcode = 0 if result.success else 1\n",
|
||
" if result.error_before_exec is not None:\n",
|
||
" log += f\"\\n{result.error_before_exec}\"\n",
|
||
" exitcode = 1\n",
|
||
" if result.error_in_exec is not None:\n",
|
||
" log += f\"\\n{result.error_in_exec}\"\n",
|
||
" exitcode = 1\n",
|
||
" return exitcode, bytes(log, \"utf-8\"), None"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"The implementation overrides three functions in `UserProxyAgent`:\n",
|
||
"* constructor. We get the ipython instance as the code execution environment.\n",
|
||
"* `generate_init_message`. We generate a modified initial message to send to the assistant agent, by adding the info that the execution will be performed in IPython.\n",
|
||
"* `run_code`. We execute the code with the ipython instance.\n",
|
||
"\n",
|
||
"With the new `IPythonUserProxyAgent`, we are able to run the code within the current notebook environment and display plot directly."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 7,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"ipython_user (to assistant):\n",
|
||
"\n",
|
||
"Plot a chart of META and TESLA stock price change YTD\n",
|
||
"If you suggest code, the code will be executed in IPython.\n",
|
||
"\n",
|
||
"--------------------------------------------------------------------------------\n",
|
||
"assistant (to ipython_user):\n",
|
||
"\n",
|
||
"Sure, we can use the `yfinance` library in Python to download the stock price data and `matplotlib` to plot the data. If you don't have `yfinance` installed, you can install it using pip:\n",
|
||
"\n",
|
||
"```python\n",
|
||
"!pip install yfinance\n",
|
||
"```\n",
|
||
"\n",
|
||
"Here is the Python code to plot the YTD stock price change for META (Facebook) and TESLA.\n",
|
||
"\n",
|
||
"```python\n",
|
||
"# Python code\n",
|
||
"import yfinance as yf\n",
|
||
"import matplotlib.pyplot as plt\n",
|
||
"from datetime import datetime\n",
|
||
"\n",
|
||
"# Define the ticker symbol\n",
|
||
"tickerSymbols = ['META', 'TSLA']\n",
|
||
"\n",
|
||
"# Get data on this ticker\n",
|
||
"start_date = datetime(datetime.now().year, 1, 1)\n",
|
||
"end_date = datetime.now()\n",
|
||
"\n",
|
||
"# Fetch the data\n",
|
||
"data = yf.download(tickerSymbols, start=start_date, end=end_date)\n",
|
||
"\n",
|
||
"# Plot the close prices\n",
|
||
"plt.figure(figsize=(14,7))\n",
|
||
"plt.plot(data['Close'])\n",
|
||
"plt.title('YTD Stock Price Change for META and TESLA')\n",
|
||
"plt.xlabel('Date')\n",
|
||
"plt.ylabel('Price (USD)')\n",
|
||
"plt.legend(tickerSymbols)\n",
|
||
"plt.grid(True)\n",
|
||
"plt.show()\n",
|
||
"```\n",
|
||
"\n",
|
||
"This code will plot the closing prices of META and TESLA stocks from the start of this year to the current date. The prices are in USD.\n",
|
||
"\n",
|
||
"--------------------------------------------------------------------------------\n",
|
||
"\n",
|
||
">>>>>>>> USING AUTO REPLY FOR THE USER...\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Defaulting to user installation because normal site-packages is not writeable\n",
|
||
"Requirement already satisfied: yfinance in /home/vscode/.local/lib/python3.9/site-packages (0.2.26)\n",
|
||
"Requirement already satisfied: pandas>=1.3.0 in /home/vscode/.local/lib/python3.9/site-packages (from yfinance) (2.0.3)\n",
|
||
"Requirement already satisfied: lxml>=4.9.1 in /home/vscode/.local/lib/python3.9/site-packages (from yfinance) (4.9.3)\n",
|
||
"Requirement already satisfied: appdirs>=1.4.4 in /home/vscode/.local/lib/python3.9/site-packages (from yfinance) (1.4.4)\n",
|
||
"Requirement already satisfied: numpy>=1.16.5 in /home/vscode/.local/lib/python3.9/site-packages (from yfinance) (1.25.1)\n",
|
||
"Requirement already satisfied: html5lib>=1.1 in /home/vscode/.local/lib/python3.9/site-packages (from yfinance) (1.1)\n",
|
||
"Requirement already satisfied: pytz>=2022.5 in /home/vscode/.local/lib/python3.9/site-packages (from yfinance) (2023.3)\n",
|
||
"Requirement already satisfied: beautifulsoup4>=4.11.1 in /home/vscode/.local/lib/python3.9/site-packages (from yfinance) (4.12.2)\n",
|
||
"Requirement already satisfied: frozendict>=2.3.4 in /home/vscode/.local/lib/python3.9/site-packages (from yfinance) (2.3.8)\n",
|
||
"Requirement already satisfied: requests>=2.31 in /usr/local/lib/python3.9/site-packages (from yfinance) (2.31.0)\n",
|
||
"Requirement already satisfied: multitasking>=0.0.7 in /home/vscode/.local/lib/python3.9/site-packages (from yfinance) (0.0.11)\n",
|
||
"Requirement already satisfied: soupsieve>1.2 in /home/vscode/.local/lib/python3.9/site-packages (from beautifulsoup4>=4.11.1->yfinance) (2.4.1)\n",
|
||
"Requirement already satisfied: webencodings in /home/vscode/.local/lib/python3.9/site-packages (from html5lib>=1.1->yfinance) (0.5.1)\n",
|
||
"Requirement already satisfied: six>=1.9 in /usr/local/lib/python3.9/site-packages (from html5lib>=1.1->yfinance) (1.16.0)\n",
|
||
"Requirement already satisfied: tzdata>=2022.1 in /home/vscode/.local/lib/python3.9/site-packages (from pandas>=1.3.0->yfinance) (2023.3)\n",
|
||
"Requirement already satisfied: python-dateutil>=2.8.2 in /home/vscode/.local/lib/python3.9/site-packages (from pandas>=1.3.0->yfinance) (2.8.2)\n",
|
||
"Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.9/site-packages (from requests>=2.31->yfinance) (3.2.0)\n",
|
||
"Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.9/site-packages (from requests>=2.31->yfinance) (2023.5.7)\n",
|
||
"Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.9/site-packages (from requests>=2.31->yfinance) (3.4)\n",
|
||
"Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.9/site-packages (from requests>=2.31->yfinance) (2.0.3)\n",
|
||
"\n",
|
||
"\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.0.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.2\u001b[0m\n",
|
||
"\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n",
|
||
"[*********************100%***********************] 2 of 2 completed\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 1400x700 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"ipython_user (to assistant):\n",
|
||
"\n",
|
||
"exitcode: 0 (execution succeeded)\n",
|
||
"Code output: \n",
|
||
"None\n",
|
||
"None\n",
|
||
"\n",
|
||
"--------------------------------------------------------------------------------\n",
|
||
"assistant (to ipython_user):\n",
|
||
"\n",
|
||
"It seems like the code executed successfully but didn't produce any output. This could be due to the fact that the IPython environment you're using might not support matplotlib's interactive mode. \n",
|
||
"\n",
|
||
"Let's try a different approach using pandas' built-in plotting function, which should work in any environment. \n",
|
||
"\n",
|
||
"```python\n",
|
||
"# Python code\n",
|
||
"import yfinance as yf\n",
|
||
"import pandas as pd\n",
|
||
"from datetime import datetime\n",
|
||
"\n",
|
||
"# Define the ticker symbol\n",
|
||
"tickerSymbols = ['META', 'TSLA']\n",
|
||
"\n",
|
||
"# Get data on this ticker\n",
|
||
"start_date = datetime(datetime.now().year, 1, 1)\n",
|
||
"end_date = datetime.now()\n",
|
||
"\n",
|
||
"# Fetch the data\n",
|
||
"data = yf.download(tickerSymbols, start=start_date, end=end_date)\n",
|
||
"\n",
|
||
"# Plot the close prices\n",
|
||
"data['Close'].plot(title='YTD Stock Price Change for META and TESLA', figsize=(14,7), grid=True)\n",
|
||
"```\n",
|
||
"\n",
|
||
"This code does the same thing as the previous one, but uses pandas' built-in plot function instead of matplotlib. The plot should appear directly in your IPython environment.\n",
|
||
"\n",
|
||
"--------------------------------------------------------------------------------\n",
|
||
"\n",
|
||
">>>>>>>> USING AUTO REPLY FOR THE USER...\n",
|
||
"[*********************100%***********************] 2 of 2 completed\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<Axes: title={'center': 'YTD Stock Price Change for META and TESLA'}, xlabel='Date'>"
|
||
]
|
||
},
|
||
"execution_count": 7,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 1400x700 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"ipython_user (to assistant):\n",
|
||
"\n",
|
||
"exitcode: 0 (execution succeeded)\n",
|
||
"Code output: \n",
|
||
"Axes(0.125,0.2;0.775x0.68)\n",
|
||
"\n",
|
||
"--------------------------------------------------------------------------------\n",
|
||
"assistant (to ipython_user):\n",
|
||
"\n",
|
||
"Great! The code executed successfully. The output `Axes(0.125,0.2;0.775x0.68)` is just a representation of the plot object. The actual plot should be displayed in your IPython environment. \n",
|
||
"\n",
|
||
"The plot should show the YTD stock price change for META and TESLA. The x-axis represents the date and the y-axis represents the closing price in USD. \n",
|
||
"\n",
|
||
"If you can see the plot and it meets your requirements, then we are done here. \n",
|
||
"\n",
|
||
"TERMINATE\n",
|
||
"\n",
|
||
"--------------------------------------------------------------------------------\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"ipy_user = IPythonUserProxyAgent(\n",
|
||
" \"ipython_user\",\n",
|
||
" human_input_mode=\"NEVER\",\n",
|
||
" max_consecutive_auto_reply=10,\n",
|
||
" is_termination_msg=lambda x: x.get(\"content\", \"\").rstrip().endswith(\"TERMINATE\") or x.get(\"content\", \"\").rstrip().endswith('\"TERMINATE\".'),\n",
|
||
")\n",
|
||
"assistant.reset()\n",
|
||
"# the assistant receives a message from the user, which contains the task description\n",
|
||
"ipy_user.initiate_chat(\n",
|
||
" assistant,\n",
|
||
" message=\"\"\"Plot a chart of META and TESLA stock price change YTD\"\"\",\n",
|
||
")"
|
||
]
|
||
}
|
||
],
|
||
"metadata": {
|
||
"kernelspec": {
|
||
"display_name": "Python 3",
|
||
"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": "3.9.17"
|
||
},
|
||
"vscode": {
|
||
"interpreter": {
|
||
"hash": "949777d72b0d2535278d3dc13498b2535136f6dfe0678499012e853ee9abcab1"
|
||
}
|
||
},
|
||
"widgets": {
|
||
"application/vnd.jupyter.widget-state+json": {
|
||
"state": {
|
||
"2d910cfd2d2a4fc49fc30fbbdc5576a7": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "2.0.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "2.0.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "2.0.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border_bottom": null,
|
||
"border_left": null,
|
||
"border_right": null,
|
||
"border_top": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"454146d0f7224f038689031002906e6f": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "2.0.0",
|
||
"model_name": "HBoxModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "2.0.0",
|
||
"_model_name": "HBoxModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "2.0.0",
|
||
"_view_name": "HBoxView",
|
||
"box_style": "",
|
||
"children": [
|
||
"IPY_MODEL_e4ae2b6f5a974fd4bafb6abb9d12ff26",
|
||
"IPY_MODEL_577e1e3cc4db4942b0883577b3b52755",
|
||
"IPY_MODEL_b40bdfb1ac1d4cffb7cefcb870c64d45"
|
||
],
|
||
"layout": "IPY_MODEL_dc83c7bff2f241309537a8119dfc7555",
|
||
"tabbable": null,
|
||
"tooltip": null
|
||
}
|
||
},
|
||
"577e1e3cc4db4942b0883577b3b52755": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "2.0.0",
|
||
"model_name": "FloatProgressModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "2.0.0",
|
||
"_model_name": "FloatProgressModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "2.0.0",
|
||
"_view_name": "ProgressView",
|
||
"bar_style": "success",
|
||
"description": "",
|
||
"description_allow_html": false,
|
||
"layout": "IPY_MODEL_2d910cfd2d2a4fc49fc30fbbdc5576a7",
|
||
"max": 1,
|
||
"min": 0,
|
||
"orientation": "horizontal",
|
||
"style": "IPY_MODEL_74a6ba0c3cbc4051be0a83e152fe1e62",
|
||
"tabbable": null,
|
||
"tooltip": null,
|
||
"value": 1
|
||
}
|
||
},
|
||
"6086462a12d54bafa59d3c4566f06cb2": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "2.0.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "2.0.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "2.0.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border_bottom": null,
|
||
"border_left": null,
|
||
"border_right": null,
|
||
"border_top": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"74a6ba0c3cbc4051be0a83e152fe1e62": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "2.0.0",
|
||
"model_name": "ProgressStyleModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "2.0.0",
|
||
"_model_name": "ProgressStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "2.0.0",
|
||
"_view_name": "StyleView",
|
||
"bar_color": null,
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"7d3f3d9e15894d05a4d188ff4f466554": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "2.0.0",
|
||
"model_name": "HTMLStyleModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "2.0.0",
|
||
"_model_name": "HTMLStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "2.0.0",
|
||
"_view_name": "StyleView",
|
||
"background": null,
|
||
"description_width": "",
|
||
"font_size": null,
|
||
"text_color": null
|
||
}
|
||
},
|
||
"b40bdfb1ac1d4cffb7cefcb870c64d45": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "2.0.0",
|
||
"model_name": "HTMLModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "2.0.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "2.0.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_allow_html": false,
|
||
"layout": "IPY_MODEL_f1355871cc6f4dd4b50d9df5af20e5c8",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_ca245376fd9f4354af6b2befe4af4466",
|
||
"tabbable": null,
|
||
"tooltip": null,
|
||
"value": " 1/1 [00:00<00:00, 44.69it/s]"
|
||
}
|
||
},
|
||
"ca245376fd9f4354af6b2befe4af4466": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "2.0.0",
|
||
"model_name": "HTMLStyleModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "2.0.0",
|
||
"_model_name": "HTMLStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "2.0.0",
|
||
"_view_name": "StyleView",
|
||
"background": null,
|
||
"description_width": "",
|
||
"font_size": null,
|
||
"text_color": null
|
||
}
|
||
},
|
||
"dc83c7bff2f241309537a8119dfc7555": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "2.0.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "2.0.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "2.0.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border_bottom": null,
|
||
"border_left": null,
|
||
"border_right": null,
|
||
"border_top": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"e4ae2b6f5a974fd4bafb6abb9d12ff26": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_module_version": "2.0.0",
|
||
"model_name": "HTMLModel",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "2.0.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "2.0.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_allow_html": false,
|
||
"layout": "IPY_MODEL_6086462a12d54bafa59d3c4566f06cb2",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_7d3f3d9e15894d05a4d188ff4f466554",
|
||
"tabbable": null,
|
||
"tooltip": null,
|
||
"value": "100%"
|
||
}
|
||
},
|
||
"f1355871cc6f4dd4b50d9df5af20e5c8": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_module_version": "2.0.0",
|
||
"model_name": "LayoutModel",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "2.0.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "2.0.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border_bottom": null,
|
||
"border_left": null,
|
||
"border_right": null,
|
||
"border_top": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
}
|
||
},
|
||
"version_major": 2,
|
||
"version_minor": 0
|
||
}
|
||
}
|
||
},
|
||
"nbformat": 4,
|
||
"nbformat_minor": 2
|
||
}
|