tesla.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "f94a7c0e-b67d-4891-836f-abe2d3da287e",
   "metadata": {},
   "source": [
    "---\n",
    "title: \"Final Project\"\n",
    "author: \"Kaya Lee\"\n",
    "date: \"November 1, 2022\"\n",
    "format: \n",
    "    pdf:\n",
    "        fig-dpi: 300\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a94e52d3-e23f-4149-a3c7-4b60e4182ecc",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import re\n",
    "import numpy as np\n",
    "import matplotlib\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plots\n",
    "plots.style.use('fivethirtyeight')\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "plt.style.use('fivethirtyeight')\n",
    "import seaborn as sns\n",
    "%matplotlib inline\n",
    "#pip install pytinytex\n",
    "\n",
    "from matplotlib.colors import ListedColormap\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt #if using matplotlib\n",
    "#import plotly.express as px #if using plotly\n",
    "import geopandas as gpd\n",
    "import plotly\n",
    "import plotly.express as px\n",
    "\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import matplotlib\n",
    "\n",
    "import pandas as pd\n",
    "\n",
    "import plotly\n",
    "\n",
    "import plotly.graph_objs as go\n",
    "\n",
    "\n",
    "import plotly.offline as offline\n",
    "\n",
    "from plotly.graph_objs import *\n",
    "\n",
    "from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot\n",
    "\n",
    "from matplotlib.pyplot import figure\n",
    "\n",
    "\n",
    "from matplotlib.patches import Patch\n",
    "from matplotlib.lines import Line2D\n",
    "\n",
    "from datetime import datetime\n",
    "\n",
    "from matplotlib.patches import Patch\n",
    "from matplotlib.lines import Line2D"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "20174974-e576-4955-ada9-be4efba88036",
   "metadata": {},
   "source": [
    "## Tweets DFs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "631e08c2-2289-4a0c-81ff-6b0670b6fe23",
   "metadata": {},
   "outputs": [],
   "source": [
    "# https://www.kaggle.com/datasets/andradaolteanu/all-elon-musks-tweets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "95864bc3-25e9-426f-a2da-023cf9123198",
   "metadata": {},
   "outputs": [],
   "source": [
    "tesla_stock = pd.read_csv(\"TSLA.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "0d01b4da-cd77-4773-995a-317503ec31ad",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Date: 2022-12-08\n",
      "Time: 12:34:46.795145\n",
      "Date-time: 2022-12-08 12:34:46.795145\n"
     ]
    }
   ],
   "source": [
    "import datetime\n",
    "date_time_str = str(datetime.datetime.now())\n",
    "date_time_obj = datetime.datetime.strptime(date_time_str, '%Y-%m-%d %H:%M:%S.%f')\n",
    "date_time_obj\n",
    "print('Date:', date_time_obj.date())\n",
    "print('Time:', date_time_obj.time())\n",
    "print('Date-time:', date_time_obj)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "5cf2e166-0d4f-4eac-a056-14a41415cbef",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010-06-29</td>\n",
       "      <td>1.266667</td>\n",
       "      <td>1.666667</td>\n",
       "      <td>1.169333</td>\n",
       "      <td>1.592667</td>\n",
       "      <td>1.592667</td>\n",
       "      <td>281494500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010-06-30</td>\n",
       "      <td>1.719333</td>\n",
       "      <td>2.028000</td>\n",
       "      <td>1.553333</td>\n",
       "      <td>1.588667</td>\n",
       "      <td>1.588667</td>\n",
       "      <td>257806500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010-07-01</td>\n",
       "      <td>1.666667</td>\n",
       "      <td>1.728000</td>\n",
       "      <td>1.351333</td>\n",
       "      <td>1.464000</td>\n",
       "      <td>1.464000</td>\n",
       "      <td>123282000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010-07-02</td>\n",
       "      <td>1.533333</td>\n",
       "      <td>1.540000</td>\n",
       "      <td>1.247333</td>\n",
       "      <td>1.280000</td>\n",
       "      <td>1.280000</td>\n",
       "      <td>77097000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010-07-06</td>\n",
       "      <td>1.333333</td>\n",
       "      <td>1.333333</td>\n",
       "      <td>1.055333</td>\n",
       "      <td>1.074000</td>\n",
       "      <td>1.074000</td>\n",
       "      <td>103003500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3125</th>\n",
       "      <td>2022-11-25</td>\n",
       "      <td>185.059998</td>\n",
       "      <td>185.199997</td>\n",
       "      <td>180.630005</td>\n",
       "      <td>182.860001</td>\n",
       "      <td>182.860001</td>\n",
       "      <td>50672700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3126</th>\n",
       "      <td>2022-11-28</td>\n",
       "      <td>179.960007</td>\n",
       "      <td>188.500000</td>\n",
       "      <td>179.000000</td>\n",
       "      <td>182.919998</td>\n",
       "      <td>182.919998</td>\n",
       "      <td>92905200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3127</th>\n",
       "      <td>2022-11-29</td>\n",
       "      <td>184.990005</td>\n",
       "      <td>186.380005</td>\n",
       "      <td>178.750000</td>\n",
       "      <td>180.830002</td>\n",
       "      <td>180.830002</td>\n",
       "      <td>83357100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3128</th>\n",
       "      <td>2022-11-30</td>\n",
       "      <td>182.429993</td>\n",
       "      <td>194.759995</td>\n",
       "      <td>180.630005</td>\n",
       "      <td>194.699997</td>\n",
       "      <td>194.699997</td>\n",
       "      <td>109186400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3129</th>\n",
       "      <td>2022-12-01</td>\n",
       "      <td>197.080002</td>\n",
       "      <td>198.919998</td>\n",
       "      <td>191.800003</td>\n",
       "      <td>194.699997</td>\n",
       "      <td>194.699997</td>\n",
       "      <td>80046200</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3130 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Date        Open        High         Low       Close   Adj Close  \\\n",
       "0     2010-06-29    1.266667    1.666667    1.169333    1.592667    1.592667   \n",
       "1     2010-06-30    1.719333    2.028000    1.553333    1.588667    1.588667   \n",
       "2     2010-07-01    1.666667    1.728000    1.351333    1.464000    1.464000   \n",
       "3     2010-07-02    1.533333    1.540000    1.247333    1.280000    1.280000   \n",
       "4     2010-07-06    1.333333    1.333333    1.055333    1.074000    1.074000   \n",
       "...          ...         ...         ...         ...         ...         ...   \n",
       "3125  2022-11-25  185.059998  185.199997  180.630005  182.860001  182.860001   \n",
       "3126  2022-11-28  179.960007  188.500000  179.000000  182.919998  182.919998   \n",
       "3127  2022-11-29  184.990005  186.380005  178.750000  180.830002  180.830002   \n",
       "3128  2022-11-30  182.429993  194.759995  180.630005  194.699997  194.699997   \n",
       "3129  2022-12-01  197.080002  198.919998  191.800003  194.699997  194.699997   \n",
       "\n",
       "         Volume  \n",
       "0     281494500  \n",
       "1     257806500  \n",
       "2     123282000  \n",
       "3      77097000  \n",
       "4     103003500  \n",
       "...         ...  \n",
       "3125   50672700  \n",
       "3126   92905200  \n",
       "3127   83357100  \n",
       "3128  109186400  \n",
       "3129   80046200  \n",
       "\n",
       "[3130 rows x 7 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tesla_stock"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "e1858322-1801-46ec-9c10-18e53d62574a",
   "metadata": {},
   "outputs": [],
   "source": [
    "tesla_stock[\"date\"] = tesla_stock[\"Date\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "5e267232-5b65-4534-a94f-f3fa170f78b7",
   "metadata": {},
   "outputs": [],
   "source": [
    "tesla_stock[\"Date\"] = pd.to_datetime(tesla_stock['Date'], format='%Y-%m-%d %H:%M:%S')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "94cc5da0-13ed-418d-ad24-612b0daa3283",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "numpy.datetime64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(tesla_stock[\"Date\"].values[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "ef138d91-75f2-4ff0-a9a0-ceae6a2b2bac",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "numpy.float64"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(tesla_stock[\"Open\"][0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "5f9fa09b-ecb8-4788-a88b-6efccd3e8099",
   "metadata": {},
   "outputs": [],
   "source": [
    "#pd.to_datetime(date) - timedelta(days=days)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "ee29ba7d-cf73-4411-bd7c-cc7a7796e599",
   "metadata": {},
   "outputs": [],
   "source": [
    "from datetime import timedelta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "0f010510-e27c-4c2d-b81d-79283336fe75",
   "metadata": {},
   "outputs": [],
   "source": [
    "tesla_stock[\"full_day\"] = tesla_stock[\"date\"].str.split(\"-\").str[1] + \"-\"+ tesla_stock[\"date\"].str.split(\"-\").str[2] + \"-\" + tesla_stock[\"date\"].str.split(\"-\").str[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "8169de7c-4198-4fb0-8464-1ed00e1575db",
   "metadata": {},
   "outputs": [],
   "source": [
    "tesla_stock[\"day\"] = tesla_stock[\"date\"].str.split(\"-\", 1).str[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "c36ec6e5-0e5a-4cc1-b119-07f108f7b596",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>date</th>\n",
       "      <th>full_day</th>\n",
       "      <th>day</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010-06-29</td>\n",
       "      <td>1.266667</td>\n",
       "      <td>1.666667</td>\n",
       "      <td>1.169333</td>\n",
       "      <td>1.592667</td>\n",
       "      <td>1.592667</td>\n",
       "      <td>281494500</td>\n",
       "      <td>2010-06-29</td>\n",
       "      <td>06-29-2010</td>\n",
       "      <td>06-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010-06-30</td>\n",
       "      <td>1.719333</td>\n",
       "      <td>2.028000</td>\n",
       "      <td>1.553333</td>\n",
       "      <td>1.588667</td>\n",
       "      <td>1.588667</td>\n",
       "      <td>257806500</td>\n",
       "      <td>2010-06-30</td>\n",
       "      <td>06-30-2010</td>\n",
       "      <td>06-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010-07-01</td>\n",
       "      <td>1.666667</td>\n",
       "      <td>1.728000</td>\n",
       "      <td>1.351333</td>\n",
       "      <td>1.464000</td>\n",
       "      <td>1.464000</td>\n",
       "      <td>123282000</td>\n",
       "      <td>2010-07-01</td>\n",
       "      <td>07-01-2010</td>\n",
       "      <td>07-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010-07-02</td>\n",
       "      <td>1.533333</td>\n",
       "      <td>1.540000</td>\n",
       "      <td>1.247333</td>\n",
       "      <td>1.280000</td>\n",
       "      <td>1.280000</td>\n",
       "      <td>77097000</td>\n",
       "      <td>2010-07-02</td>\n",
       "      <td>07-02-2010</td>\n",
       "      <td>07-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010-07-06</td>\n",
       "      <td>1.333333</td>\n",
       "      <td>1.333333</td>\n",
       "      <td>1.055333</td>\n",
       "      <td>1.074000</td>\n",
       "      <td>1.074000</td>\n",
       "      <td>103003500</td>\n",
       "      <td>2010-07-06</td>\n",
       "      <td>07-06-2010</td>\n",
       "      <td>07-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3125</th>\n",
       "      <td>2022-11-25</td>\n",
       "      <td>185.059998</td>\n",
       "      <td>185.199997</td>\n",
       "      <td>180.630005</td>\n",
       "      <td>182.860001</td>\n",
       "      <td>182.860001</td>\n",
       "      <td>50672700</td>\n",
       "      <td>2022-11-25</td>\n",
       "      <td>11-25-2022</td>\n",
       "      <td>11-25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3126</th>\n",
       "      <td>2022-11-28</td>\n",
       "      <td>179.960007</td>\n",
       "      <td>188.500000</td>\n",
       "      <td>179.000000</td>\n",
       "      <td>182.919998</td>\n",
       "      <td>182.919998</td>\n",
       "      <td>92905200</td>\n",
       "      <td>2022-11-28</td>\n",
       "      <td>11-28-2022</td>\n",
       "      <td>11-28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3127</th>\n",
       "      <td>2022-11-29</td>\n",
       "      <td>184.990005</td>\n",
       "      <td>186.380005</td>\n",
       "      <td>178.750000</td>\n",
       "      <td>180.830002</td>\n",
       "      <td>180.830002</td>\n",
       "      <td>83357100</td>\n",
       "      <td>2022-11-29</td>\n",
       "      <td>11-29-2022</td>\n",
       "      <td>11-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3128</th>\n",
       "      <td>2022-11-30</td>\n",
       "      <td>182.429993</td>\n",
       "      <td>194.759995</td>\n",
       "      <td>180.630005</td>\n",
       "      <td>194.699997</td>\n",
       "      <td>194.699997</td>\n",
       "      <td>109186400</td>\n",
       "      <td>2022-11-30</td>\n",
       "      <td>11-30-2022</td>\n",
       "      <td>11-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3129</th>\n",
       "      <td>2022-12-01</td>\n",
       "      <td>197.080002</td>\n",
       "      <td>198.919998</td>\n",
       "      <td>191.800003</td>\n",
       "      <td>194.699997</td>\n",
       "      <td>194.699997</td>\n",
       "      <td>80046200</td>\n",
       "      <td>2022-12-01</td>\n",
       "      <td>12-01-2022</td>\n",
       "      <td>12-01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3130 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Date        Open        High         Low       Close   Adj Close  \\\n",
       "0    2010-06-29    1.266667    1.666667    1.169333    1.592667    1.592667   \n",
       "1    2010-06-30    1.719333    2.028000    1.553333    1.588667    1.588667   \n",
       "2    2010-07-01    1.666667    1.728000    1.351333    1.464000    1.464000   \n",
       "3    2010-07-02    1.533333    1.540000    1.247333    1.280000    1.280000   \n",
       "4    2010-07-06    1.333333    1.333333    1.055333    1.074000    1.074000   \n",
       "...         ...         ...         ...         ...         ...         ...   \n",
       "3125 2022-11-25  185.059998  185.199997  180.630005  182.860001  182.860001   \n",
       "3126 2022-11-28  179.960007  188.500000  179.000000  182.919998  182.919998   \n",
       "3127 2022-11-29  184.990005  186.380005  178.750000  180.830002  180.830002   \n",
       "3128 2022-11-30  182.429993  194.759995  180.630005  194.699997  194.699997   \n",
       "3129 2022-12-01  197.080002  198.919998  191.800003  194.699997  194.699997   \n",
       "\n",
       "         Volume        date    full_day    day  \n",
       "0     281494500  2010-06-29  06-29-2010  06-29  \n",
       "1     257806500  2010-06-30  06-30-2010  06-30  \n",
       "2     123282000  2010-07-01  07-01-2010  07-01  \n",
       "3      77097000  2010-07-02  07-02-2010  07-02  \n",
       "4     103003500  2010-07-06  07-06-2010  07-06  \n",
       "...         ...         ...         ...    ...  \n",
       "3125   50672700  2022-11-25  11-25-2022  11-25  \n",
       "3126   92905200  2022-11-28  11-28-2022  11-28  \n",
       "3127   83357100  2022-11-29  11-29-2022  11-29  \n",
       "3128  109186400  2022-11-30  11-30-2022  11-30  \n",
       "3129   80046200  2022-12-01  12-01-2022  12-01  \n",
       "\n",
       "[3130 rows x 10 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tesla_stock"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "34d1173a-b691-448e-b8a7-dbff88e8a290",
   "metadata": {},
   "source": [
    "## August 7th visualization (SEC involvement)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2489ebea-c81f-47e6-85ac-e8f386af7a38",
   "metadata": {},
   "source": [
    "### Long Term (50 days after)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "c1a20676-fe08-49db-be17-cf10bf96a8cf",
   "metadata": {},
   "outputs": [],
   "source": [
    "## tesla stock 20 days before and 50 days after\n",
    "#August 7th, 2018 tweet \n",
    "# datetime.datetime.strptime(date_time_str, '%Y-%m-%d %H:%M:%S.%f')\n",
    "start_date = datetime.datetime.strptime(\"2018-08-07\", \"%Y-%m-%d\") - timedelta(days = 20)\n",
    "end_date = datetime.datetime.strptime(\"2018-08-07\", \"%Y-%m-%d\") + timedelta(days = 50)\n",
    "august_tweet_lt = tesla_stock[(tesla_stock[\"Date\"] > start_date) & (tesla_stock[\"Date\"] <= end_date)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "72e2ef81-d8ee-48c6-a796-6326251556f7",
   "metadata": {},
   "outputs": [],
   "source": [
    "bar_colors = []\n",
    "for date in august_tweet_lt[\"date\"]:\n",
    "    if date == \"2018-08-07\": \n",
    "        bar_colors.append(\"#1DA1F2\")\n",
    "    else:\n",
    "        bar_colors.append(\"#909191\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "76bd956a-73ac-4359-aee3-4389459ad11b",
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'august_tweet_lt' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m/var/folders/wz/7k6v05bx5gvffw4vkwfkmkn40000gn/T/ipykernel_68569/2939378550.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0maugust_tweet_lt\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"day\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0mdate_labels_aug\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0mi\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mdate\u001b[0m \u001b[0;32min\u001b[0m \u001b[0maugust_tweet_lt\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"day\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mNameError\u001b[0m: name 'august_tweet_lt' is not defined"
     ]
    }
   ],
   "source": [
    "august_tweet_lt[\"day\"].values\n",
    "\n",
    "date_labels_aug = [] \n",
    "i = 0\n",
    "for date in august_tweet_lt[\"day\"].values: \n",
    "    if (i % 2) == 1:\n",
    "        date_labels_aug.append(date)\n",
    "    elif date == \"08-07\":\n",
    "        date_labels_aug.append(date)\n",
    "    else: \n",
    "        date_labels_aug.append(\"\")\n",
    "    i += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "57e137af-8f22-4732-8616-7a24a681db48",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "No handles with labels found to put in legend.\n"
     ]
    },
    {
     "data": {
      "image/png": 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58uXD3t4+zYdCSM5c6dixI3/88QfBwcGULFkSNzc3Tp48yeDBg1MFtsLCwujcuTPTpk3j5s2bFC1alIIFC3LmzBlGjhzJp59+SkJCgtk6s2fPZsCAAfj6+qLVatHr9RiNRvbs2UPv3r0tfg4vSnrnJzvXCyQXluzSpQvz58/HwcGBAgUKEBYWxvTp0xkzZgzTpk3jyy+/VM9vXFwce/bsUYszZsRoNBIWFgZgNlpPSp6enkDy2/z0XL16Vf3+mlL3Lbly5QoPHjxIlbbv7u7OzJkzWb58ucW33WlJr1ilKYBjKWvBz88PT09PSpYsaTa9d+/e7Nq1K8PgiEnp0qXVwM7QoUN59OgRkByEmTNnDqdOncLR0ZGOHTtmanvwz/cwrc8E/gl2mJY1MRqNaXZ7MJ0PU+A1JT8/P+zs7NTReqytrWncuDFdu3ZNs2jk3r17AcyCIdeuXVOnxcfHs2rVKr744gs+/PBDfvjhBzWYYsmRI0dISkpKdW0UL16cJUuW8Oeff6rXY0ZM2SVr1641y/oJDQ1lzJgxAHTt2lXt+iKEEP8mMlqHEOJfoVGjRrRs2ZJdu3Zx9epVvv32W6ytralQoQK1a9emXr16Fvto54QrV67g7+8PYNZHuF27dly9epX169czePDgTO978ODBHDlyhMjISNatW8e6devIkycPNWrUoE6dOvj4+FCmTJlU6zVu3JjGjRvTrFkzwsPD+frrr83e1K1fv57Zs2djY2PDqFGjePvtt9FoNBgMBubPn89vv/3G2LFjKVmypPoj+9GjRwwZMoSoqCjee+89hg0bhpOTE4qisGjRIn799VdGjRpF3bp103wgmT9/Pn/88QeOjo7MmTOHqlWrZvbUZkpISIiaZdK4ceNU88+ePcvw4cP58MMP1WNKS0JCAoMHD+bevXs0bdqUX375RQ1kmUYEmTlzJj4+PtSoUQODwcDAgQMJDg6mWbNmjBkzhvz58wPJbzkHDRqEr68vEyZM4PvvvwcgMjKSqVOnYmdnx7x589SHKoPBwJw5c/j999/57bffePvtt1/KkIFpnZ/sXC8mJ06cwMPDg9WrV1OpUiUAZsyYwdSpU1m5ciWKojB8+HB69eqFRqNRg4oPHjxg06ZNaQ4haxIZGak+3Lu5uVlcxpTd8PjxY4xGY5rdvRYuXIjRaFQzONJiymh5NmOhYMGCWapbYvqehIWFERsbazHDwPSG/PHjx2bT79+/j7+/v8UAxJtvvpnpNpjMmDGDr7/+msOHD9O0aVO8vLx48OABDx48oHTp0vz888/qm/zMMF07aX0mKeeZglCm85GQkEBgYKDF7AnT+TB1BTFJTEzk2LFj1KpVy2zkpvQcPHhQ/SxTnjNTBsfTp0/p1KmTWcbbkSNHWLlyJf369bOYaWXK3nj2e5BW5kZ6fHx8GDt2LBMmTODLL7/kf//7Hy4uLgQGBgLJQwd/++23Wd6uEEK8DiRzQgjxr6DRaJg0aRJ9+/ZVu3gkJSVx/vx55s6dS+/evalfvz7jxo2zmFHxPEx936tUqWI2/GC7du3QaDRERESwZ8+eTG+vePHirFixwuxB6fHjx+zdu5dff/2Vdu3a0a5dO7Zu3Zqldk6fPh2AQYMG8c4776DRaIDkAnh9+vShR48eKIrC5MmT1XVWrlxJREQE3t7ejB49Wh3KT6PR8OGHH9KkSRP1TbolK1as4H//+58amKhRo0aW2pwWo9HIo0eP2LFjB3369CEhIQFPT0+z4oImBQsWNHvYTS9rZseOHQQGBuLp6cnkyZPNlm3bti1du3YF/smU2blzJ5cvX8bLy4vJkyergQlIzlyZPHkyWq2WZcuW8fDhQyA5uycxMZGSJUuqgQlI/hw+++wzWrZsyRtvvJHlPuXTp09Hr9en+e/nn3+2uF5a5yc710tK3377rRqYgOQ3+1ZWVhiNRtq0acOHH36obtPLy4sWLVoAltPZnxUfH6/+tylz6Fmm6YqipMpcMXn06JHaVcdSvYOUfH19cXV1fe6snwoVKuDh4YHBYFCLR6Z0/vx5jh07BpCq6GFaAZLssrW1xdvbG3t7e+Li4rh69SoPHjwAoECBAlkO5pq61KX1mcA/wz+bls2XL596nZgKY6Z0+/Zt9TN69nycOXOGmJiYTJ+Pmzdvqg/2tWrVMuvCYeoS9sMPPxAZGcnvv//OmTNnOHLkCIMHD0ar1TJjxgzWrVuXaruHDh1Cp9PlWHHdokWLUqpUKSD5+AMCAkhMTMTBwYH8+fOjKEqO7EcIIV41EpwQQvxr2NraMmTIEA4ePMhPP/1Es2bNzNL3o6KiWLBgAe3atVNTwp+XwWBQfzinzJqA5LRyU5ZAZro+pOTl5cVff/3F2rVr+eyzz1IV+rx+/TpfffUV3377baZ+qN64cYPQ0FC0Wq36gP0s0wPq+fPn1Qfp/fv3A9C5c2f1QTKln376id27d/PJJ5+kmrd582ZGjRqFlZUVs2bNSvetdEaefdAuX7489erVY9CgQQQFBVG0aFFmzZplsbuGt7d3mm/Nn2U63nbt2ll8wBowYADbt2/nhx9+AP5JD2/ZsqXFN7c6nQ6dTkdiYiJHjx4Fkq8LKysrrl69ysSJEwkNDTVbZ/r06fz6668Wu6ikp3DhwlSvXj3NfykDZylZOj/ZvV5SMhUpNbG3t1cDH8++YQbUwE7KuiFpycznmbKLgKVrF5K/l6bAlqmIrSWxsbGcOXOGevXqPXc6vbW1tfr2ffbs2UyfPp0HDx4QHx/Pvn37GDBggJpdYKo/Y2KpIGd2PXnyhB49evDHH39Qs2ZN1q9fz4ULF9i9ezc9evTgyJEjdO/enTNnzmR6m1n5XFJ+Jl9++SUajYZNmzYxevRobt26RUJCAidOnKBPnz5qBpGl8wGWr6dn3bx5kw8//JCIiAg8PDyYOHGiWRtMAa/IyEhmzJhB27ZtcXR0xN3dnU8//ZQ+ffoAyfVJUnbJCQwMJCwsLMcCRmvWrOHjjz/G39+fn376iWPHjnH27FlmzZpFnjx5+P333xkyZIgEKIQQ/0rSrUMI8a/j7u5O165d6dq1KwaDgUuXLnHw4EHWr19PaGgod+7c4csvv8xywMASPz8/7t+/j1artVhIr3379pw5c4bDhw8THh6e6X7HJhUrVqRixYp89dVXREVFcezYMfbu3cvmzZuJj49nw4YNeHt7061bt3S3ExQUBCS/kUtrJIJixYrh4uJCVFQUQUFB5MuXT31wLlu2rMV10kr5jo6OZujQoeqDyLPp6VlVvXp1s/+3srLCycmJIkWKUKtWLVq0aJHmW14PD49M7yej43V3dzfLpjClfm/fvj3Nwot37twBUNOyPTw86NGjBwsXLmTOnDnMmTMHLy8vfHx8aNy4MfXq1Us1+kRmvP322wwcODDL61k6P9m9Xkzs7OwspvabPiNL2SvPPnimJ2VXiPj4eIu1BUzZElqtNs1rY/v27UByVkx6D9bHjh0jMTExxx5A33vvPUJCQpgzZw7Tpk1j2rRp6ryKFSvywQcf8P3335sF21IW5EyrlkJWzJ07lytXrqDT6Zg1a5Z6zRUrVowRI0Zga2vLvHnzGD16tMVsAUtMn0vKzJZnmbIfUgb/GjZsyMiRI/n555/566+/+Ouvv9R5xYsXZ/To0QwaNChV8NHPz48CBQpk2H3i/PnzfPrppzx69Ag3Nzfmzp2b6t5lb29PbGwsDRo0sFhktU+fPsyePZu7d+9y6dIlNYPm0KFDQM5ks0RERPDzzz9jNBr5+eef1RFnIHmEkQoVKtChQwd27NjBnj171GwjIYT4t5DghBDiX83KyooqVapQpUoVPvvsM8aNG8eSJUu4cOECV65coXz58s+1fVN6v9FoTPWmOCWj0ciaNWss9lfOLBcXF1q0aEGLFi3o378/n3zyCTdv3mTlypUZBidMb6NN3TLS4ujoSFRUlLq8qWtBRus9KykpCVtbW5o2bcq+ffsYPXo09erVy/ZD1bJly7K1HpDpvujwz/FmNNKBiamLUGhoaKoMiGdFRUWp/z18+HAqVqzI33//zdmzZwkKCiIoKIilS5eSN29eBg8ezHvvvZfpdj8PS+cnu9eLSUa1MtLKZMgsJycnbGxsSExM5PHjx2bdaUxMn6Wbm5vF/d29e1cdttc0uk5asvKGPrNMNWFMQVM3NzcaNWpEhw4d1PtKysDRpUuXePToUYbf9cwyDVPau3dvi8GwTz/9lIULF3L58mWCg4MpUaIEgwYN4v79+6mWbdy4MZ999pkakEovGGmqNZE3b16z6d26daNmzZqsWrWKGzdu4OTkRJ06dejcubM6aknK8/Ho0SMuX75Mp06d0j3OAwcO8MUXX/D06VPy58/P/PnzLRYudXFxITY2Ns1Ah7OzM4ULFyY8PJywsDA1OOHn54e9vf1zZYaZHDp0iJiYGIoVK2YWmDApWLAgnTt3ZsGCBWzfvl2CE0KIfx0JTgghXnuBgYF8+eWXREVFsXPnzjTfwFpbWzN06FA2b95MREQEQUFBzxWciI6OVmtJuLu7p/m2Ozo6mpiYGNauXcuAAQPSfUO7YMECli9fTuPGjfnuu+/SXM7T05MhQ4bQv3//DEcjgH8etjOqt2F6gDYtb29vT3R0tDr0XmZZWVkxbdo06tWrR4cOHQgODmb8+PFqtflXlelt7tOnTzO1vOkhfOrUqbRu3TpL+3rzzTd58803efjwIUePHuXQoUPs27ePR48eMXLkSNzd3XPt4SO718vLotVq8fLy4tq1a4SFhVksomga6cI0DOWzDhw4gKIoeHp6mtXGsMTPz4+SJUtmOfMpIzVq1LBYh8VUdyPlg3JO15swnR9TbYNn5cmTB3d3d+7fv8+tW7coUaIEFy9etDhihukcm7ZlaZln92vpc9Hr9YwYMSLVdNP5SJnRdOjQIRRFSfd8bNq0iWHDhpGUlESxYsWYP38+xYsXt7hsyZIlLQ6pmpLp3m261yckJHDs2DFq1qyZpSBoWjL6TCC5y1/KZYUQ4t9Eak4IIV57bm5uXL16lfDwcE6fPp3usjY2NmoV//QqymfG9u3biYuLw9bWlu3bt3Pw4EGL/8aPHw8kFzYzVXVPi6IoBAUFsXfv3jSH1TMxpdFn5jhMww6Gh4enqnhvEhgYqAYhTA8Oph/CKSvXp7Rv3z66deumFk80cXFxoUmTJtjZ2fHjjz8CyUOqHj9+PMO25ibT8ZpGB3jW5cuX6dq1Kz/99BPwz3lK6/xActG+gIAAtQDg06dPuXz5srpOvnz5aNeuHb/88gsHDhygfv36AGzcuDFHjik7snu9vEymgMK5c+cszjcN/ZhWAUtTLYU6deqku5/Q0FCCgoJyLCigKAqrVq1i5syZFgt1Koqijj5Tu3Ztdbqfnx958uShcuXKOdIOUxcJS5kQkNw1wzT6himDZu/evfj7+6f6N27cOOCfz+Tq1asWu3Y8fPiQsLAwtFqt2XFs2bKFP//802LtEki+z4D5Z+Xn54dWq02z/sbOnTsZOnQoSUlJlCtXjmXLlqUZmIB/rpOLFy9anJ+QkKCO6GGq33L69GliY2Np2LBhmtvNCtN5TuszgX+CEukNhyyEEK8rCU4IIV57efPmVX+gTpo0Kc3K/JD8Bi44OBgXF5fn/pFvSr1u2rSpGvCwpEmTJmo6ckZ1Llq1aoW1tTWhoaEsXbo03WVN/eWfTTU3pbCnLJhWunRpihcvjtFoZPny5Ra3Z+rnrdPp1PaaHshMx/qsTZs2cfLkyXTTuBs0aEC7du1QFIWRI0em2x89t5keMrZu3WrxOtq2bRtnzpxR37A2adIESB6xxdJxhYaG0r17dzp06KA+DC9ZsoROnTrxyy+/pFre1tZWfZOeUXDqRcru9fIymQpYbtiwIdVnFR0dzbZt2wDo0KGDxfVNb+MzGn3DlLGQUw+gGo2GRYsWMWXKFLVIakrbtm0jNDQULy8v6tatCyQfz9mzZ3OkIKeJKfCR1j1p48aNGAwGXFxcKFeuXKa2WbRoUSpUqEBCQoLF4NqqVauA5G4gKe+ZGzduZNKkSezcuTPVOufOneP48ePkyZPHrKvDoUOHqFixosX6JdeuXePrr7/GYDBQpUoVlixZkuE1atr2yZMn1e4+Ka1YsULNwDCdj5zOZjEFXy5fvmyxDfHx8ep9P+VIP0II8W8hwQkhxL/CkCFDsLe358yZM7z//vscO3bM7OEuKSmJnTt30qdPHxRF4fPPP7f45ikxMZEnT56k+89oNBIeHs6JEycAMuzzbG1trS6zb9++NN8OQvKP+169egHw66+/Mnbs2FTpu48ePWLChAksXLgQFxcX+vbtazbflGL/7Hr9+/cHkrsgrFmzRg1eGAwG5s6dqwZDBg8erK7TrVs3XF1dOXHiBL/88ov6AK4oCkuWLGHLli3Y2Nhk2A9++PDhuLi4EBQUxIwZM9JdNjd16NABT09PQkJCGDp0qFmdiB07drBgwQIAPvzwQyC54KmXlxfBwcEMHDjQ7I1nUFAQ/fr1IykpSR1dBKBNmzZYWVnh5+fHnDlzSEpKUtcJCAhgxYoVQOrRLl627FwvL1OTJk3Q6/WEhYUxbNgwtStOVFQUX375JZGRkdSvX99iENJgMKjZMRk9ePv5+WFjY5OjD4Om4rm//PKLWRcIX19fNdPoiy++UAMRR48ezdGCnJBc4NHa2pq9e/cyfvx4s65b27dvV7Mh+vbtm6UhRU33o3HjxqlDogLs2bOHGTNmoNFoUo3uYzofU6dOxd/fX51+4cIFvvjiC3W7pnv21atXuX//fpo1QExBUA8PD2bNmpVmUdeUypcvT9u2bTEajQwYMIBLly6p844ePcqUKVMA+Oyzz9Tpfn5+FCxYkDJlymS4/cwoU6aMGnQbOHCgWVbQo0eP+PLLLwkODiZ//vxpjqIjhBCvM6k5IYT4V6hcuTIzZsxg2LBhXLx4kZ49e+Lm5kaRIkVQFIXQ0FCio6PRarX07duX3r17W9zO5s2b2bx5c7r72rNnDxs3bkRRFPLly5epN6rvvvsuc+bMITExkXXr1lkcetPkm2++ISkpiSVLlqj/PD09yZcvH1FRUQQHB2M0GvHw8OD3339PlVKv1+sJCAhg3LhxrF27lu7du9O5c2c6duxIQEAA8+bN47vvvuP333+nUKFChIaGEhkZiZWVFd988w1NmzZVt1WgQAEmTZrEwIEDWbRoEWvXrqVEiRLcvn2bhw8fYmVlxejRo9XuEGnx8PDgq6++YvTo0cybN4+2bdtm+m3sy2Rvb8/06dPp3bs3W7duZe/evZQuXZqHDx+qo24MGjRIfetsa2vLjBkz6N27NwcOHKBJkyaUKVOGxMREgoKCMBgMFCpUiJkzZ6r7KFasGMOHD2fs2LFMnDiROXPmULRoUWJiYggODkZRFJo0aULnzp1z5RyYZOd6eZmsrKwYP348PXv2ZMuWLfj6+lKsWDG1u0mRIkXULlXPioiIUEeNSG/I1qSkJI4ePUqNGjVytK5G3759OXDgAOfOnaN169aUKlWKmJgYdYjjr776yixL4EUU5KxUqRJjx45l5MiRzJs3j2XLllGyZElu376tdufo1KmTOoRmZrVp0wZfX1/WrFlDz549KVOmDElJSeoIMF999VWq4pEdO3Zkz5497Ny5k06dOlGqVCkMBgM3b94Ekkc3SXnPNHWPs3TvPXv2rJqlpNVqGTBgQJpt9fDwYOrUqer/jxkzhjt37nD69Gk6d+5M6dKlURTFrB3vvPMOAA8ePODq1as5/j395ZdfuHPnDhcuXOC9996jRIkS2NraEhgYSFJSEnnz5uWPP/7IkRFbhBDiVSPBCSHEv4aPjw/bt29n9erV+Pr6cuPGDW7evIlWq6VAgQJ06NCBd999l4oVKz73vkwpy+3bt8/UEIjFixendu3aHDt2jNWrV6cbnNBoNHz33Xd07tyZDRs2cPToUe7evcuVK1dwdnbG29ub5s2b06VLF4tvBIcNG0ZsbCxHjx4lMDBQHcIS4Ntvv8XHx4fFixdz9uxZrl69SoECBWjSpAk9evSwWBiwYcOGbNiwgdmzZ3Po0CH8/f1xcnKiRYsW9O3bF29v78ycMt5//33Wr1/P+fPnGTFiBCtWrMixFPWcVKFCBTZs2MDcuXPZt28fAQEB2Nvb06BBAz788MNUGQ1lypRhw4YNLFy4kD179qhBieLFi9O0aVP69OmTKvW8R48eFClShOXLl3Px4kX1nNasWZO33nqLt99+O93CqS9Ldq6Xl6lcuXKsW7eO6dOn4+vri7+/P/ny5aNDhw4MHDgwzVR+00geWq3W4kgfJmfPniU6OjpHgwKQXPtm4cKF/Pnnn2zfvp2bN29ib2+Pj48PPXv2pHHjxmbL+/n5UapUKYoUKZKj7ejUqRPly5dn3rx5HDt2jICAABwdHalfvz7vvfeexeGRM+Pnn3+mRo0aLF++nGvXrqEoCtWqVaNHjx60a9fO4jqTJk1i0aJFbNiwgaCgIKytralZsyZdu3ZN1TXHz88PJycnqlatmmo7KYf0vXv3brpFLp8tcOrs7MySJUtYtmwZ69ev5+bNm2o7PvjgA7O2+/n5ZViQMztcXV35+++/WbZsGZs2beLGjRskJSVRtGhRGjduTO/evSlYsGCO7lMIIV4VGiVlp2QhhBBCCCGEEEKIlyz3X8sIIYQQQgghhBDiP02CE0IIIYQQQgghhMhVEpwQQgghhBBCCCFErpLghBBCCCGEEEIIIXKVBCeEEEIIIYQQQgiRqyQ4IYQQQgghhBBCiFwlwQkhhBBCCCGEEELkKglOCCGEEEIIIYQQIldJcEKIV8y6devQ6/Xo9Xrmzp2bqXW2bt3KW2+9hbe3N7Vr12bUqFHqvJCQEBITE19Qa19NRqORwMBAs2nHjh1Dr9dTp06dXGrVP44cOUKXLl2oVq0aNWrU4LPPPkt3+bVr16rXRGb/PXnyRF2/R48e6PV6li5d+qIPLcuaNWumtrlfv36ZWuezzz5T15k2bdoLbmFqw4YNQ6/X87///S/DZcPCwtS2Hjt2LEfbkfLcZfZfjx49crQNL1NW7mWma37YsGFm0y19FqbP82WfG9M9Kav/1q5dm+V9ZfUekJVr/GXJzn3wRXzvLDHtKyAg4IXtI73rpXz58nh7e9O0aVO++uorTpw4keXtT5s2Db1ez6BBg15A6zPnxo0bz72NlNeJEOL1Y53bDRBCmFu/fr3636tXr+aTTz5Jd/kTJ07w1VdfAVCoUCHy5ctHkSJFSExMZMaMGcybN4+jR49iY2PzIpv9yrhw4QI//vgjderUYejQobndnFRCQkLo06cPiYmJuLu7U6RIEYoWLZqpdW1tbalUqVKmlrWysnqeZuaKQ4cOERsbi6OjY5rLREdHc+jQoZfYqldXpUqVKFiwoNm06Oho9QGpevXqqdbR6XQvpW056d96L3NxcbH4GQUHB/Pw4UPy5ctHiRIlUs3Ply/fy2jeKydfvnwWz1dAQADR0dEULlyYwoULp5rv4uLyMpr3Uj17HhRF4enTp4SEhLB161a2bt3K119/TZ8+fXKphVkTFBTEqFGjcHV1ZerUqbndHCFELpLghBCvkDt37nD8+HGKFSuGVqslMDCQkydPUrNmzTTX2b59OwC1atVi0aJF6kNpWFgYf/zxx0tp96vkr7/+4tKlS69EhoQlu3fvJjExkeLFi7N582bs7Owyva6HhwfLli17ga3LPdbW1sTFxXHw4EHeeOONNJfbu3cvCQkJL7Flz0ej0Vj875xg6Uf8sWPH6NmzJ8C/5lq5e/dutu9lmTnnOf25ZFaFChUsfkbDhg1j3bp1NGrUiHHjxuVCy2Dw4MH06dOHvHnz5sr+LWncuDGNGzdONb1Hjx4cP36ct99+m4EDB+ZCy16+tL7bsbGxjBkzhrVr1zJp0iR8fHwoX758prbZrVs32rZti7Ozc042NVM2bdrEkSNHaN269XNvK7e+z0KInCHdOoR4hWzYsAGj0UjVqlVp0qQJAKtWrUp3nUePHgFQrVq11/Jt+X+N6fOqXLlylgIT/3a1a9cGYNeuXekut2PHDgDKlSv3wtuUEzw8PNTvpaW3uuLFKFSoEJC5c27KPilSpMgLbdPrpECBApQuXRp3d/fcborIAkdHR8aMGUPhwoUxGo0sX7480+u6u7tTunTpVNlYrxvTd1++z0K8niQ4IcQrZMOGDQD4+PjQqlUrIDkzIioqKs11DAYDkJzyL1598nlZ1rJlSzQaDfv3708zMyImJgZfX18qVKhgMd39VWRra0vx4sVxcnLKdPcd8fzKli0LkKl+51lZVohXnbW1NY0aNQKSuzn+15QpUwaQ77MQrysJTgjxirhw4QI3btzAysqKRo0aUb16dQoUKEBcXBybNm1KtbypeJXpTfL06dPR6/U0a9aMYcOG0bx5c3XZ6tWro9frCQsLM9vG7t276d27N3Xq1KFy5cq0aNGCsWPHcu/evTT3N2/ePP7++28aNWpElSpVaN++PcHBwWoRqp9//pkHDx7www8/4OPjQ5UqVWjbti1LliwBkvvGLl++nDfffJMqVapQt25dvv76a4v7BDh58iRff/01zZo1w9vbG29vb1q0aMHIkSMJDg5WlzMVHly3bh0A8+fPt1gQD5IfcqdMmULr1q2pXLkyPj4+fPPNN4SEhGT0MaUSFBTEDz/8QLNmzahUqRK1a9fmo48+Ytu2bWbLmc7P/PnzAfPCp7kps+030ev1VKtWDUVRWLVqFZ07d6Zq1arUqFGDjz76KNv1IAoXLkzlypWJjo7myJEjFpfZv38/8fHxaXb7SFl8MiYmJtX8gICANM/5sWPH6N+/Py1atKBSpUrUq1eP3r17s3Xr1kwfw8OHD2ndujV6vZ5evXoRFxcHJD/86nQ6s3TjhIQEFixYQNeuXalXrx5VqlShRYsWjBgxIkeKwlmiKAo+Pj7o9XqOHj2aav4XX3yBXq/ngw8+SDXP398fvV5PixYtzKZHR0czffp0OnTogLe3N9WrV6dr166sXLlSDcRZktl7T2bvZc8yPaBkpsaGpWVN97uFCxcSHBzMkCFDqFevHt7e3nTq1InNmzcDyfUw/vzzT1q3bk2lSpXw8fHhp59+Ijo6OsP9Po+rV68yYsQIWrduTbVq1ahcuTJNmjRhyJAhXLp0KdPbuXnzJvXr10ev1/PNN99gNBoBywUxTQUZP/30U2JjY5k0aRItW7akcuXKNGjQgK+//jpVIWKTx48fM2XKFN544w2qVKlCo0aNGDNmDJGRkWqxzhdZuPLhw4f873//o3Xr1lSpUoVatWrRq1cvtVvks0z3tx49euDj42N2fs+fP5/p/RoMBjZs2EDfvn3x8fGhUqVKVK9enbfeeoupU6em++LheZi6ZqS8D5o+023btjFt2jTq1KlD1apV6dy5M9HR0akKYh45ckQtIp1WIdo1a9ag1+t59913zaZn5frU6/VMnz4dSM6Ms1ScNiv3GQ8PD9zc3F7L+jpCCKk5IcQrw5Q1UbduXTWV9o033mDx4sWsXr061QND4cKFqV69Ojdv3iQyMlItBubh4YGXlxeVKlXi4sWLQHKXD41Go3YjUBSFH374gZUrVwLJf8zLli1LYGAgS5YsYfPmzcyZM4fKlSunaufOnTs5e/YsRYoUwdPTk9jYWIoVK8apU6cAuHXrFh07diQiIoLSpUuj0Wi4ceMGY8eO5enTpwQGBrJ27Vo8PDwoWbIkAQEBbNq0icuXL7NhwwazYnczZ85kypQpahvLlClDREQEYWFhrFy5kq1bt7Jq1SpKlSqFnZ0d1atXV4vJFSxYEE9PT7y8vMzan5CQwAcffMDVq1fV+YGBgWzcuJF9+/axbt06ihUrlqnPbPfu3QwZMoS4uDgcHR3R6/VERERw+PBhDh8+zO7duxk/fjxWVlZqMbfw8HDu3r2bZrG7lykr7X/WyJEjWbVqFXny5KFUqVIEBgZy+PBhjhw5wtSpU9XMn6xo3bo158+fZ+fOnRb7lpsCca1bt87SA1hGNm3axLfffovRaKRQoULo9XoePHiAn58ffn5+XLhwIcPiqo8fP+ajjz4iKCiI2rVrM2vWLOzt7QFSjSiiKAoDBgzgwIEDWFtbU6JECQoVKkRQUBCrVq1i8+bNLFq0CG9v7xw7Rkjui924cWNWr17NkSNHqFu3rlmbjh8/DsD58+eJi4tT2w/g6+sLQNOmTdVpYWFhfPzxxwQHB2NtbY2XlxdGo5EzZ85w5swZdu7cycyZM82yhLJ678noXpaWZs2a4e/vn6nzotfr01z20qVLTJkyhaSkJEqXLs2dO3e4fPkyQ4YMISkpiY0bN3Lo0CE8PT0pUaIE169f5++//yYwMJCFCxdmav9ZtW7dOr7//nsMBgN58+alZMmSREdHExYWxubNm9mxYwcLFiygVq1a6W4nPDycjz/+mIcPH9K+fXvGjRuHVpvxO6uYmBg++OADrly5QqFChShdurR6Hz948CBr1qwxu4fevXuXDz/8kJs3b2JjY4NOpyMyMpKlS5fi6+v7wgucXrp0iT59+vDw4UNsbW0pWbIkT58+5ejRoxw9epTOnTvzyy+/mAUPf/zxR1asWIFGo6FEiRIUKFBAPb/btm1j6tSpqQJ1z0pMTOTzzz9XvzvFixenYMGC3Llzh6tXr3L16lV2797N6tWrczyTzhRot9StaeHChZw9exYvLy+SkpKwt7e3WGeibt26FC5cmNu3b3Po0CG1q2lKW7ZsAeCtt95Sp2X1+qxevTq3b9/m9u3buLm5UapUKbPAQnbuMy9jhBYhxAuiCCFyXWJiolK3bl1Fp9Mpq1evVqefPXtW0el0ik6nUy5dumRx3YEDByo6nU6ZOnWq2fTQ0FB13ejoaLN58+fPV3Q6neLj46McPnxYnR4TE6OMGjVK0el0SuPGjZWoqCh13tSpU9Xt/fzzz4rRaFQURVEePnyoKIqirFmzRp3fpk0bJTg4WFEURTEajcr333+v6HQ6pVy5ckqlSpWULVu2qNs9ffq0UrFiRUWn0ym7d+9Wp1+5ckUpV66cUr58eWXTpk1m7b9y5YrSqFEjRafTKT/++KPZvKFDhyo6nU4ZN26c2fSjR4+q7atdu7Zy4MABdd6NGzeUBg0aKDqdTvnhhx8snudn3bx5U6lcubKi0+mUMWPGKLGxseq8AwcOKDVr1lR0Op3y+++/m603btw4RafTKUOHDs3UfhTln3PbtGnTTK+TUvfu3RWdTqcsWbLkudtvOofly5dXlixZohgMBkVRFCUqKkrdT9u2bTPdtqZNmyo6nU7Zu3evEhISouh0OqVu3bpKUlKS2XKxsbGKt7e38tZbbymKYvm6T++aVxRF8ff3V+ebGAwGpX79+opOpzO7LhVFUdatW6fo9XqlXLlySmhoqDr92WssOjpaee+99xSdTqd88MEHSkxMTLrHvG/fPkWn0ymtWrVSbt++rU6PiopS+vXrp+h0OqVnz54ZnDnLUl7nluzcuVPR6XTKO++8Yzb9ypUr6no6nU45cuSI2fyePXsqOp1OOXTokKIoipKUlKR07NhR0el0ymeffabcv39fXfbatWtKmzZtFJ1Op4wdO9ZsO9m592T0uWaFaTtHjx5Nd7mU97v3339fefDggaIoihIfH6988skn6v2sdu3aZsexfft2db0rV65kq42m68vSPeL+/fuKt7e3otPplHnz5pl9T0JCQpQ333xT0el0yieffGK23rP3gHv37iktW7ZUdDqdMmjQoFTfN0v30ZTXVoMGDcyO+/r16+o9dNSoUWbb6tu3r3rN3bp1S52+Y8cOpUqVKpn+TNJiOrZn/wYqiqI8efJEady4saLT6ZTvv//e7Lo6efKk4uPjo+h0OmXBggXq9ICAAPU+FBAQoE6Pj49Xr9HmzZub7cd0DP7+/uq0xYsXKzqdTqlfv36qa2Hr1q1K+fLlLd530pLRd9skODhYqVSpkqLT6ZT58+er002f6bPHa/obbrrmBw4cqM6bOHGiotPplK+//jrVfu7fv6+UL19eqVChgrqN7F6flvatKNm/zwghXl/SrUOIV8CBAwd49OgRNjY2tGzZUp3u7e2tvoHKqDBmZsXHxzNr1iwAJkyYQL169dR5jo6O/Pjjj3h7e3P79m3WrFmTan0bGxu++OIL9S2TpYJpY8aMoXjx4kDy21rTcKhGo5FevXrRtm1bddlq1aqpo5FcuXJFnX748GGsra154403aN++vdn2y5UrR5cuXYDsjYs+fPhwtU8uQKlSpejVqxcAZ86cydQ25syZQ3x8PA0bNmTEiBE4ODio8xo1asSvv/4KwIIFC4iIiMhyGy0JDw9Pc5z7lP/Wrl37wtv/7rvv0r17d/VNq7OzM1988QUA169fz1Zae7FixShfvjyPHj1SM3FM9u/fz9OnT9MdySM7Hj58yIMHD8iTJw9t2rQxm9exY0fee+892rVrl+bxxMfH069fP86ePUu1atWYPXt2ukOhAupQn40aNVKLt0HyORw+fDgNGjRQ6yDktPr162NjY8OlS5fMUspNXWlMQxSeOHFCnRcbG8upU6dwdnZW33bu3LmTy5cv4+XlxeTJk8mfP7+6fJkyZZg8eTJarZZly5bx8OFD4PnvPbnBysqKiRMnqsN32tra8uGHHwLJ97Mvv/zS7Dhat26t3vuuXr2a4+0xZbdUrVqVjz/+2CyrqVixYnz88cdA+vfFyMhI9U10q1at+O2337JcTPm7774zO+7SpUur2X1nz55Vp1++fJn9+/fj6OjIjBkzzN7kt2rVim+++SZL+82qFStWcPv2bWrXrs2YMWPMMgRq1KjB2LFjAZg9e7badcH0/axWrZrZ99DW1pZvv/2WBg0aULduXYtdx1I6evQoVlZWDBw4MFUB3zZt2qhFgHOiG5fRaOTRo0fs2LGDPn36kJCQgKenZ6ruFpBcANY0og9Y/htuYsqI2LNnD/Hx8Wbztm3bhsFgoGHDhuo2cuL6TCk79xkhxOtNghNCvAJMXToaNWqEq6ur2bx27doBsHnzZrUP+/M4ffo0kZGR5M+f3yytOyVT8ODgwYOp5ul0OpycnNLcvouLS6ox2FNWzW7QoEGqdUw//FP+2Pv44485f/58mkPpmR6mnz59mmZb0mIpHdfU7zwyMjJT2zCdG0v98037KFKkCHFxcRb792eHra0t1atXz/Cf6Xy+yPZb6nZRqlQp9b+z2+fe1B1k586dZtNTdunISXnz5sXFxYXHjx/z3Xffce3aNbP5o0ePZuLEiRZHB0lKSuKLL77g6NGjVKhQgblz56b73TAxBRzXrFnDqlWrzK65okWLMn/+fEaMGPF8B5YGJycnatasicFgMEt9NgUn+vTpA/zzkGGal5iYiI+Pj5qCv3fvXiC5kKmlLhY6nQ6dTkdiYqJ6/TzvvSc3lC5dOlXV/5T/7+Pjk2odS/eznNK2bVvOnj3L4sWLLc7P6L4YExNDnz59CAgIoGHDhkyaNAlr66z18NVoNGbBXZOSJUsC5t9903XSpEkTChQokGqdd95554UWBzbtv23bthaHmGzUqBF58uTh4cOHalcx0/fzwIEDzJ07l7t376rLOzg4MH/+fMaOHZvhd33GjBmcO3eOd955J9U8g8Ggrp+dv2HPBqTLly9PvXr1GDRoEEFBQRQtWpRZs2ZZ7K7h7e2dqe47kPx3sWLFisTExLB//36zeaYuHW+++aY67Xmvz2dl5z4jhHi9Sc0JIXLZkydP2LdvH/BPICKldu3aMWvWLJ48ecL27dvp2LHjc+3v+vXrQPLb0Pfff9/iMo8fPwawWNzMw8Mj3e17eHik+hGY8senpbc0afU5Nm3nyJEjXL9+ndDQUIKDg7l8+bJaOM9UwC2zHB0dLf5gM73tfvbtkCXR0dHcv38fgAoVKqS5XPny5bl16xZBQUFZamNaPDw80hzfPityov2WhptL+eMxvWKI6WndujVTpkxh9+7d6gN6fHw8Bw4coFy5cuoDUE6xtrZm0KBB/Pzzz6xdu5a1a9dSuHBhGjRoQOPGjWnYsKFZVklKK1euVAOGpiFiM6N58+Z4e3tz7tw5RowYwQ8//KAWZm3atKnFWi85qUmTJhw5coTDhw/TokULkpKSOHnyJF5eXjRs2BBHR0fOnTtHQkICtra2FutNmN58bt++PVWWi8mdO3eAf+4jz3vvyQ2WrvOU96u8efOmOV9RlBfWLhsbG06dOkVAQAAhISGEhIRw9epVtVBoWvfFmTNnqtfsw4cPM/2QmlJa91BTjZKU3/2bN28CaY+cYG9vT8mSJTNdHySrTNfpkiVL2Lhxo8VlTBkTgYGBVK1alSpVqtCyZUt27drFhAkTmDBhAnq9Xv1+1qhRI9PnzcbGhsePH3Py5Elu3rxJWFgYN2/e5PLly2oQJzvXybMvAKysrHBycqJIkSLUqlWLFi1apBn0yehv+LPeeustLl26xJYtW9TgcFhYGGfOnMHZ2dmsYK1Jdq/PZ2XnPiOEeL1JcEKIXLZ161Z16MTBgwczePDgNJddvXr1cwcnTD+IYmNjOX36dKaWTSmjQnRpPciZWHp7lZYVK1YwY8YMszdXNjY2lC9fHr1erz40ZUVOvKVL+UY0vbdnpoDHi3iD+jxyov0ZFbHL7oNZ6dKlKVOmDNevX+f8+fNUqVKFgwcPEhsbm+NdOkx69uxJiRIlWLhwIcePH+f27dusXr2a1atX4+TkxCeffEK/fv1SrRcXF0e5cuWIi4sjKCiIiRMnMmrUqAz3Z2try+LFi5k/fz7r168nODiYc+fOce7cOWbMmEHZsmX56aefqFGjxgs42uSsl19//ZXDhw8DyQUwY2JiaN++PTY2NlSvXh0/Pz/Onz9PzZo18fX1RavVmr0tN90bQkNDCQ0NTXd/pu4jz3vvyQ0ZddHJyv0sp+zcuZPffvvNLGio1WopW7YsrVq1SpV1lFJcXBx169bl6tWrXL58mfnz56vZMpmVlQKWpqyg9P4uZCbbKLtM11FmuhGk7OY0ZcoUli1bxqpVq7h69Sr+/v74+/szb948PD09+e677zIsiBkfH8+kSZNYsWKFWaaAk5MT1apV48GDB9nu+vM8QeqM/oY/q3379owfP54DBw4QExODk5OTmjXRunXrVNt7nuvzWdm5zwghXm8SnBAil61fvx5I7m+e1o+0hIQEIiIiOHHiBIGBgc/19tj0I7Fp06Zq/+9X0cqVK/nhhx+A5Dc3jRs3pmzZsnh5eWFra8uKFSuyFZzICSkfWKKjo3FxcbG4nOmHVUYPOC/bq97+Vq1acf36dXbt2kWVKlXU4f6y0qXDUnAkvW5RjRs3pnHjxkRFRXHs2DEOHz7Mvn37uHXrFlOmTMHJyUmtS2Ki0+lYuHAhV65c4aOPPmL58uV06NAhU0EFe3t7+vXrR79+/QgMDOTIkSMcOnQIX19frl27xieffML27dstvrl/XiVLlqREiRIEBgZy9+5dNR3a1NWiTp06+Pn5cezYMdzd3QkLC6NatWpmWU+m+8jUqVMz/bm8LveeV5mfnx+DBg1CURSaNm2qDl1bsmRJHBwc8PPzS/fhr06dOvz5559s2rSJESNGMH36dLM6GTnN9JmnF6B9kcFbBwcHoqKiWLNmDZUqVcr0elZWVnTv3p3u3btz+/Zt9fu5f/9+wsPDGTRoECtXrkx3m9999x2bN2/G0dGRTz/9lGrVqlG6dGmKFi2KVqtlyJAhL6QuSU7Lly8fDRo04MCBA+zdu5cOHTqoQ+mm7NIBz399Pis79xkhxOtNak4IkYtCQ0PVAoyTJk3i4MGDFv9t3bpVfVu1evXq59qnaWjN9N4khYWFcfbs2VwtMDVv3jwABg4cyPjx42nXrh06nU7NfDClcuYGFxcXNTX28uXLFpdRFEWdl9tDhj7rVW+/6Ufo7t27SUhIYP/+/ej1erOaFpak7DtvykZKydQVKKWEhAQCAgLUYqwuLi60aNGCH374gT179tCpUycAiynhPj4+5M2bl/r169O+fXsURWHkyJEW951SREQEp06dUruClCxZkg8++IAZM2awa9cuPDw8iI2NZffu3elu53mYsiCOHDmiFr80FegzBSmOHz+u1n5o1qyZ2fqmayK9+8iZM2cICAhQg0Kvy73nVTZ//nwURaFz587MmjWLTp06UaFCBfUhLqP7YqtWrbC3t+edd96hRo0axMXFMXLkyBfWXlMtH1ORyWclJCQQHBz8wvafmev02LFj3LhxQ/3eRkdHc/78ecLDw4Hk4Tg7d+7Mb7/9xv79+9HpdBgMBjV7wJK7d++q8//8808GDx5M06ZNKV68uNolJDf/hmWVqTDmrl27uHHjBgEBARQuXJg6deqYLfe81+ezsnOfEUK83iQ4IUQuMmVNeHh4WCysZuLu7q4+HKxfv56kpKQMt52yT2zKt8g1a9bE0dGRkJAQNa37Wd9//z1dunRJsxjly2D6YVi+fPlU8+Li4tQffs/WNjClWb/I/t7wz8NdWum1u3fv5u7du1hbW6f6AfcqeJXbX65cOUqUKMHNmzf566+/iI6OzlSXjpTFZC31PzYVV0tp165ddOjQgSFDhqS6ZrRarfqgnlEf6eHDh+Pq6sqNGzf4448/0l3266+/5oMPPrAYaCxYsKAahMlu3Y7MaNKkCQC+vr6cPXuW0qVLq5XwK1asiLOzM2fPnmXPnj2Aeb2JlOuvX7/eYp2W0NBQunfvTocOHdQAbHbvPWndy/6L0rsvKorCunXrgIyvHY1Gw6hRo7CxseHo0aPPHfROi6kewYEDBywGnHKq0HNaTNfpypUrLV47J0+epGfPnrRr145bt24BMH78eN59913+/PPPVMu7uLio2RLp3RPCw8PV/Vmq63Pjxg11VJPM/D3Pbc2bN8fZ2Rk/Pz81a6JDhw6pujVl9/pM6+92du4zQojXmwQnhMhFprexHTp0yHAoN9OQYA8ePFALaKYnZSq+6UcXJHcfMQ2F9/XXX5s9JMTFxfHLL7+oQ6A9m8b+Mpnesi5dutSs/3lISAifffaZ+rbt2R8spq4xKY/5Rejduzf29vb4+voyduxYsz7FBw8e5PvvvwegV69eZsOfvSpe9fabRu2YOnUqkLkuHY6Ojmrhvd9//13tg5yUlMTixYvVH8YpNWnSBCcnJ27cuMEvv/xidh5u3bqlZvBYGp0gpfz586v1YubMmZNq1I+UOnToAMAff/yBn5+f2bxt27Zx6tQptFqtxZFtckrt2rVxdHRkx44dxMbGmgWgrKysqFWrFnFxcRw/fhxPT89UQ5u2b98eLy8vgoODGThwoFpgFSAoKIh+/fqRlJSkjiIA2b/3pHUv+y8y3RdXrVrFgwcP1On37t1jyJAhnDx5EshcYV+dTqd+HuPHjzfbXk6pUqUKPj4+xMbGMmDAALP6QYcOHeKXX37J8X2m9MEHH5A3b15OnjzJd999Z1aX4MKFC3z11VdA8sO36dyavp+rV69mw4YNZg/Mx48fV7uZpXdPKFGihBpU+/PPP80exo8dO0afPn3UoERmPqvcZm9vT+vWrYmJiWHhwoVA6i4dkP3rM62/29m5zwghXm9Sc0KIXHLy5ElCQkIAMlXkskGDBnh6ehIeHs6qVato2bJlusu7ublRqFAh7ty5Q/fu3SlWrBjjxo2jbNmy9O/fn5s3b7J9+3Y++ugjPD09cXNzIzg4WA0E/PTTT1nqo5vTBg0axKBBgzh8+DANGzakZMmSxMTEEBwcjKIo1K1bl6NHj/LgwQMURVHfvJgeTnfs2EGHDh2oXbv2C0lbLl26NBMmTODrr79myZIlrFmzhtKlS/Po0SP17VGbNm3UH7854f79+2mOcvCsnj170qZNmzTn50b7s6JVq1bMmTOH2NhYdDodpUuXztR6gwYNYuDAgZw4cYLGjRvj5eXF7du3efToEb169WLt2rVmDyhOTk6MHz+eAQMGsHjxYtasWUPx4sXVdPOkpCQqVqyYqaKBXbp0Yd26deooHMuWLbNY1f+tt95i79697Nixg969e1OoUCHy58/PvXv31K4ngwcPzvQxZ4etrS316tVTMyOezY6pU6eOGgR9tkuHaf0ZM2bQu3dvDhw4QJMmTShTpgyJiYkEBQVhMBgoVKgQM2fONFsvO/ee9O5l/zWff/45hw4dIiAggGbNmlGyZEmSkpIICgoiKSmJ2rVrc+rUKRISEoiMjMTNzS3d7fXv35+tW7cSHh7OmDFjmDJlSo63+ZdffuH999/n9OnTNG/eHJ1OR3R0NMHBwej1em7evEliYmKGAfrsyJcvH9OmTaNfv36sXbuWLVu2UKZMGXX/kPw349dff1XXqVWrFh999BELFizg22+/5X//+x+FCxcmIiJCvTd26dIl3eBhvnz56NatG0uWLGH27NmsWbOGwoULq99xa2tratWqxYkTJyx2N3sVvfXWW6xZs4bY2FgqVKhg8fuX3evT9Hf74sWLap2KqVOnZvs+I4R4fUnmhBC5xJQ1YRp5IiNarZbOnTsDyUWnMtN3c+rUqVSuXJm4uDhCQ0PVYIi1tTWTJ0/m999/p0GDBsTExODv74+dnR0tW7bkr7/+UjM1ckurVq3466+/8PHxwcnJCX9/f6KiomjQoAHTpk1j0aJFFChQgKioKLXPPECnTp348MMPyZcvH0FBQS+04FirVq1Yv34977zzDm5ubly9epX4+HgaNmzItGnTmDx5cpYq22ckISGB06dPZ+pfyjeUr0r7s6JKlSp4enoCWSuE2aJFCxYtWkTDhg3RarXcvHmTokWLMn78eL777rs011m6dCmtWrXCycmJa9eucffuXSpUqMDQoUNZvny5xaETn6XVahk9ejTW1tacPXuWpUuXWlxOo9Hw22+/8f3331O1alWio6O5evUqiqLQsmVLFi5cyKeffprpY84uU8q0RqNR602YpAxWmJZ7VpkyZdiwYQOff/45pUqVIigoiJCQEIoXL87HH3/MunXrKFKkiNk62b33pHUv+6+pWrUq69ato1WrVuTLl4/r16/z4MEDqlWrxs8//8yiRYvUoWgzk2Hn4OCgFh7evn27xa5Pz6tgwYKsXbuWXr16UaBAAQICAoiPj+fDDz/kr7/+UpczDUWa02rVqsWmTZvo2bMnhQsX5vr169y5cwedTsfAgQNZtmyZWZcwgKFDhzJu3Dhq166NwWDg6tWrxMbG0rBhQ6ZOncro0aMz3O/333/P//73P6pUqUJSUhL+/v7Y2NjQoUMHVq5cqW7jxIkTr8zoNOmpXbu2+n22lDUB2b8+69evz+DBgylUqBDh4eFcunRJ7TaTnfuMEOL1pVH+6x04hRBCCCHESxcXF4e3tzeQ3J3sRYxOI4QQ4vUhmRNCCCGEECLHHThwgJYtWzJq1CiL803DQbu7u0tgQgghhAQnhBBCCCFEzqtQoQLh4eGsWLEi1dCb58+f56effgKga9euudE8IYQQrxjp1iGEEEIIIV6ImTNnqoU2PTw8KFiwoFlxyUaNGjFjxgxsbW1zs5lCCCFeARKcEEIIIYQQL8yJEydYtGgRV69e5e7du7i4uFC6dGk6depEx44dLY5qI4QQ4r9HghNCCCGEEEIIIYTIVRKqFkIIIYQQQgghRK6S4IQQQgghhBBCCCFylXVuN0AIIYR4HYSFhdGiRQsURaFx48bMnj07t5uUK27cuEHp0qUztaxer8/0dvfs2UPRokXV/4+OjiYmJsZsiMlp06Yxffp0WrduzdSpUzPf6GwyGAysXLmSDRs2cO3aNeLj4ylYsCA+Pj707dsXT09Pi+vdvn2bqVOn4uvrS2RkJAUKFKB58+b069ePvHnzZmrf48aNY8GCBWzatAmdTpfmcgcPHmThwoVcuHCBp0+fUrhwYZo3b07fvn1xd3fP1nELIYQQuUGCE0IIIUQmbNiwAVOZJj8/P+7cuUOhQoVyuVUvT1BQEKNGjcLV1TXTgYHq1aunOz8wMJCIiAjc3NxwdXVVp2/evJlx48YxZswYs+DEy5SQkEDfvn05cuQIAAULFqRIkSIEBgayfPlytm3bxpw5c/D29jZbLywsjC5duvDgwQPc3NzQ6XQEBgayePFidu3axYoVKzI8pgMHDrB48eIM2zh79mx+++03APLly0ehQoUIDAxkwYIF7Nixg7/++osiRYpk8wwIIYQQL5cEJ4QQQohM2LhxIwA+Pj74+fmxZs0a+vfvn8utenk2bdrEkSNHaN26dabXWbZsWZrzgoKC6NSpExqNhgkTJpgFJyZNmsT9+/efq73Pa8qUKRw5coQCBQowadIkatWqBUBkZCTff/89u3fvZuDAgezYsQMHBwd1vS+++IIHDx7wzjvv8OOPP2Jra8uTJ08YPHgwvr6+DB8+nPnz56e53/379/PFF19gMBjSbd/Vq1eZNGkSAEOHDuWjjz5Co9Fw584d+vfvz8WLF/n+++9ZsGBBDpwNIYQQ4sWTmhNCCCFEBs6cOUNQUBAFCxbk/fffB2DNmjXIgFfZk5iYyJAhQ4iNjeX999+nUaNGud0kM/Hx8Wpg5ccff1QDEwBubm5MnDiRIkWKcPfuXbZv367O8/Pz4+LFi3h6ejJq1ChsbW0BcHV1ZfLkybi5uXHo0CHOnz+fap8JCQlMmTKFzz//nLi4uAzbuHHjRhRFwcfHh48//hiNRgNAoUKFGDduHACHDx/m7t272T8RQgghxEskwQkhhBAiAxs2bACSsyZ8fHxwdHQkPDycw4cP53LLXk9Lly7l4sWLeHh4MGTIkNxuTioXL14kJiYGGxsbmjVrlmq+g4MDdevWBeDSpUvq9PXr1wPQvn17bGxszNZxdnambdu2AGzbts1s3t27d2nTpg0zZ87EysqK0aNHZ9hGU9DBUj2KsmXLYmdnByTXvxBCCCFeB//Z4MTatWvR6/WcPHkyR7Z348YNvvrqK+rVq0fFihVp1KgRI0aMkB8FQgjxHIxGI6tXr6Zbt27UqFGDypUr06pVK37++WeLb4SnTZuGXq9n3rx5hIWF8e233+Lj40OlSpVo0aIFEyZMICoqKkttSEhIUB8mmzVrhr29PU2aNAFg1apVaa6n1+vR6/UEBASkmhcTE6PODwsLSzV/+/btdO/enTp16lC9enU+/vhjTp48qf7tGjZsmLrssWPH0Ov11KlTx2I79u3bh16vt/iQvWvXLj755BOaNm1KpUqV8PHxoV+/fvj5+aU6lunTpwOwY8cO9Ho9PXr0SPPY0/P48WP++OMPILkLhLOzszrPdHzh4eEAfPbZZ+j1etauXZtqO2FhYQwfPhwfHx8qV65My5YtmThxIjExMdlqV0olS5Zk+vTpjBkzBq3W8k+l2NhYALPuF6aMiGrVqllcx1Sf4tSpU2bTHz16RFhYGNWqVWPNmjV06dIlwzaa6p1cvXo11byQkBDi4+MBKFy4cIbbEkIIIV4F/8ngxJkzZxgzZkyObe/8+fO88847bN26lfz589O0aVPs7OxYtWoVnTp1IjAwMMf2JYQQ/xVxcXF89NFHfP/995w8eZJ8+fJRtmxZ7ty5w+LFi+nQoUOaAeZr167RsWNHNm/ejIuLC56enoSGhjJ37lx69epFUlJSptuxf/9+IiMjcXZ2pmHDhgC0a9cOgN27d/Po0aPnP9gUxo4dyxdffMGJEydwdnamRIkSHDt2jB49erBz584c28/s2bMZMGAAvr6+aLVa9Ho9RqORPXv20Lt3b5YuXaouW716dfUh183NjerVq6c7gkR6Zs2axePHj/Hy8qJz585m8/Lly0f16tXV7hBlypShevXq5MuXz2y5Gzdu0LlzZ9avX0/evHkpUKAAISEhzJkzhx49epCYmJittpm4u7vTsmVLOnXqZHF+dHQ0x44dU9sIyYE0U6Ap5agjKZlG9wgODk61v5kzZ7J8+fJMj3DSqVMnbGxsOHz4MIsWLVK7GD18+JDhw4cD0KJFi1wrKCqEEEJk1X8uOLFz50569+6tvvHICaNGjSI2Npbhw4ezadMmpk+fzvbt2+natSsRERH873//y7F9CSHEf8VPP/3E0aNHKViwICtWrGDnzp2sXbsWPz8/2rVrx+PHjxkwYIDFwonr1q2jdOnSbN++nW3btrFjxw6mT5+ORqPh0qVL7Nq1K9PtMKXqt2jRQk2Vb9SoES4uLiQmJqqFMnPC9u3bWbJkCfb29syYMYM9e/awbt06du3aRcWKFdm3b1+O7CcyMpKpU6diZ2fH0qVL2bNnD2vWrMHX15evvvoKgN9++42nT58CyYUt3377bQDq1KnDsmXLGDlyZJb3Gx0dzYoVKwD4+OOPsbKyMpvfuHFjli1bhoeHBwBff/01y5Yto3HjxmbLXb9+nSJFirBt2zY2bdrEnj17mDFjRrY+3+yYNWsWERER2NnZ0bJlSyD5nJqyKNzc3CyulydPHiA5e8RoNKrTCxYsSPPmzbPUhjJlyjBt2jQKFCjAL7/8go+PD2+99RZNmzbl1KlTtG/fnvHjx2fj6IQQQojc8Z8JTty5c4dvv/2WgQMHYjQayZ8/f45sNzIykkuXLuHm5saHH36oTreysuKLL74A4MSJEzmyLyGE+K8ICwtTgwLTpk2jatWq6jxXV1cmTJhAxYoViYiIYOHChanWt7a2ZurUqRQvXlyd1rJlS7VOwNmzZzPVjoiICA4ePAig1gsAsLW1VR9K0+vakVUzZ84EYMiQIbRo0UKdXqRIEWbOnImjo2OO7CcoKIjExERKlixpVuzRysqKzz77jJYtW/LGG28QGRmZI/szWbduHTExMbi7u9OxY8dsb8fKyorp06fj5eWlTmvRooWa2XL69OnnbGnatm3bxty5cwHo3bs3BQoUAFC7UQDY29tbXNc0XVEUEhISnrst+fPnp1y5cgA8ePCAq1evEh8fj62tLQULFpSCrUIIIV4r/5ngxOTJk9mwYQOVKlVixYoVlCpVKt3lz507R//+/albty6VK1emdevW/P7770RHR5stZ3rrExMTk6ofc0REBPDPmxIhhBCZ4+vri9FopGLFimo//ZSsrKz44IMPgORuF8/S6/UW09lLliwJkOpenpatW7eSmJhI3rx5adCggdm89u3bA8lv8c+cOZOp7aXn1q1b+Pv7Y21trWYppFSgQAE1IPK8PD09sbKy4urVq0ycOJHQ0FCz+dOnT+fXX3/N8XoFf//9NwBdu3ZVs1Cyo1y5cha7Tpi6WOR0UMVk586dfPPNNyiKQu3atc2Gkk2rNkVKKbMlTKNrZJevry8ffPABhw8fZvDgwfj5+XHhwgWWLFlCmTJlmDdvHn369MnUyB9CCCHEq+A/E5woVaoU//vf/1i1alWG/TnXrl3L+++/z969eylWrBhNmzYlPj6eWbNm8f7775v96HFxcaFq1aokJiYycOBAAgICiIuL4/z582oF8t69e7/IQxNCiH+doKAgAMqXL5/mMhUrVjRbNiXT2+xnmd5cp3xITI8pe6NVq1ZYW1ubzatbt65aCyEnsidu3LgBJNcrcHJysrhMhQoVnns/AB4eHmpByzlz5tCiRQtat27NmDFjOHjw4HPXbLAkICCAmzdvAv8EdrIrrc/XlFmSE1kJz1q1ahVffvkliYmJVKpUiZkzZ5pdEymzWlJmUaRkapdWq1XramRHYmIiP/74IwkJCXzxxRd8+umneHh4YGtrS+3atVm8eDHFixfn9OnTajcaIYQQ4lX3nwlO9O3bl44dO2b4ZuPGjRv88MMPODo6snTpUlatWsXUqVPZtWsXXbp0ISAgIFUxzQkTJlCqVCmOHDlChw4d8Pb25t133yUkJITffvuNbt26vchDE0KIfx3TiAtpPaTDPw+DSUlJqR4GM3rwy0y6e2BgoDr6wooVK9TRNUz/KlSowMOHD4HkVP/MZmOkxRT4dnBwSHOZ9M5HVg0fPpwJEyZQrVo1NBoNQUFBLF26lD59+tCwYUNWrlyZY/sC1HoZOp2O0qVLP9e2nufBPjumT5/OiBEjMBgMVKtWjYULF+Li4mK2jJOTkzp86OPHjy1ux/QZu7m5PVfmxMWLFwkPD8fOzo6PPvoo1XxnZ2d69uwJJNcxEUIIIV4H/5ngRGYtWrSIxMREBg0aRI0aNdTpNjY2jBgxgoIFC7J161azIewKFCigVs02DddWtGhRYmJimD9/vsVh4oQQQqTNFHhI74Hf1JXO2tr6uboIpMWUNWHqv5/WP0geVnLr1q0Wt2MpEGIp1d4UlEhvKMzsDJNpKmppyZtvvsny5cs5dOgQkyZN4u2338bd3Z2IiAhGjhzJ7t27s7y/tJiCE61bt86xbb5oiqIwevRopk2bBiQXQl2wYEGqwAQkZ0OYamCk9Xf/1q1bAJQoUeK52mXaTrFixdSAyLNMbTEtK4QQQrzqJDjxDNPQYJbGizelSxqNRnX4uoSEBD766CMmT57M+PHj2bhxI3/88Qe7du2if//+XLp0iY8//viFpJgKIcS/lak2xJUrV9Jc5tKlS0DyA1pOUxSFTZs2AdCzZ08OHjyY5j9T15Nnu3aYahJZuv9bGmHEVC8hPDw8zaBMQEBAqmnp7SetfT19+pTLly+rXUny5ctHu3bt+OWXXzhw4AD169cHyLGRSBITE9XPy9Lf11fVr7/+yl9//QUkB3L++OOPdDNbKlWqBCTXrbLEVIi1SpUqz9UuZ2dnILkIZlpdlExBCdOyQgghxKtOghPPuHPnDpD8I+TZFF69Xq/+WL19+zYAa9as4fTp03Tp0sWskrtWq2XQoEHUrVuX4ODgNN+oCSGESK1hw4ZotVouX75scWQNg8HA8uXLAfDx8cnx/R8/fpzw8HCADEeVePfddwE4f/48/v7+6nRXV1cguXvIs/bs2ZNqmpeXF2XKlMFgMLBhw4ZU8x8/fmwxk8FUdDk2Nlb9G5bS3r17U01bsmQJnTp14pdffkk1z9bWVs0ctFTAMTsjQNy4cYOEhAS0Wq1aKyQ9z7OvnLJq1SoWLVoEQJcuXRg/fnyquiPPMhUs3bBhQ6pgUXR0NNu2bQOgQ4cOz9W2atWqYWNjQ2RkpMXPV1EUNbCUcjQWIYQQ4lUmwYlnmMYob9++PR06dEjznykl8/jx4wCpqribNGrUCEj/7Z8QQghzRYsWVYMCX3zxhVmA4smTJ3zzzTdcvnyZPHny8Mknn+T4/k1dOipWrEjZsmXTXbZDhw5qoc2U2RPVqlUD4I8//uDevXtA8kPjli1bmD17tsVt9evXD4CJEyeajULy4MEDBg4caLGWQalSpXBzcwNg3Lhxav2N+Ph4fvvtN44ePZpqnTZt2mBlZYWfnx9z5swhKSlJnRcQEKAWUTT9DYN/6l1kp5vA1atXAShevHimhkM1LZNTXRLu3bvHjRs3Mr29iIgIfv31VwDq16/PTz/9lKkaEU2aNEGv1xMWFsawYcPULjVRUVF8+eWXREZGUr9+fSpXrpz9gyE58GWqZzVixAgOHDigzouNjeWHH37g5MmTODg48PHHHz/XvoQQQoiXJf1XAP9BBQoUIDw8nG+++YZChQpluPyTJ0+Af9Jqn2Wa/iIqnwshxL/ZyJEjCQ8P59ixY3Tp0gUvLy+cnJy4fv068fHxuLm5MXny5Ezdq7MiLi6OnTt3AtCpU6cMl3d1daVVq1Zs3LiRTZs28e2332Jra8vnn3/OoUOHuHnzJi1atKB06dI8fPiQu3fv0qpVK4KCglJ102jXrh3Hjh1jxYoVfPrppxQrVgxXV1d1OZ1OR0BAgNnfHCsrKwYMGMDYsWPZtm0bR44cwdPTk5CQEKKiohg4cKBaM8GkWLFiDB8+nLFjxzJx4kTmzJmj1koKDg5GURSaNGlC586d1XVMI11dvHiR1q1bo9frmTp1aqbOqSk4k9mhSfV6PQEBAYwbN461a9fSvXt3s7Zk1aRJk1i3bh21a9dmyZIlGS6/atUqtb7HvXv31GFrLWncuDGfffYZkPxZjB8/np49e7JlyxZ8fX0pVqwYgYGBxMbGUqRIEcaPH5/t40hpyJAhBAUFsX//fvr27UvhwoXJkycPgYGBxMfH4+DgwKRJkyhevHiO7E8IIYR40SRz4hk1a9YEMHsLkVLv3r3p0qWLWsG9VKlS6S5/+PBhIHlMdiGEEJnn6OjI/PnzGT16NNWrV+fBgwfcuHEDT09P+vTpw8aNG6lXr16O73f37t1ER0djY2NDu3btMrXOe++9BySPxmAKbFSpUoWVK1fSunVrHBwcuHHjBnny5OH7779nypQpaY4eNXr0aMaNG4e3tzcPHz4kKCiIunXrsmzZMjUbw5SpYdKjRw+mT59OzZo1SUhIICgoiPLlyzN79mx11IZn9ejRg5kzZ9KoUSOsrKzw9/cnIiKCmjVrMnbsWP744w+zbgz169dn8ODBFCpUiPDwcC5dupTpIVlNo1SYCohmZNiwYTRv3hxbW1sCAwMtdo15kU6dOqX+9/Xr1zl9+nSa/54dyrZcuXKsW7eOzp07Y2dnh7+/Py4uLnTp0oWVK1fi4eGRI220tbXljz/+4Ndff6VWrVpER0dz48YN8ufPz7vvvsu6deto1qxZjuxLCCGEeBk0Sm526MxFPXr04Pjx4/z1119qQALgwoULvPfee7i6ujJjxgx1nqIozJgxg2nTppE/f3727duHra0t/v7+6hClkydPVvubAixcuJBff/0Vd3d3du3aJUWphBBCPJcvv/ySbdu28eWXX/L555/ndnNeK1OmTOHixYvMmTMnt5sihBBCCAukW8czKleuzNChQxk3bhzdu3enQoUKeHp6EhAQQFBQEPb29kyZMkUdY12v1zNixAjGjh3LgAEDKF++PEWLFuXatWsEBQXh6OjIlClTJDAhhBAiQ23atCFPnjz89ttveHp6ms2Lj49X6xxVqFAhN5r3Wjt58mSminEKIYQQIndItw4LPvzwQxYvXkzTpk25desW+/fvx2g00qlTJ9avX2+WaQHQrVs3li5dSvPmzblz5w779u0jNjaWTp06qX1chRBCiIwUL16cM2fOMHHiRLPhRCMiIvj22295+PAhJUqUeCHdWf7NZs2aRUBAAN27d8/tpgghhBAiDf/Zbh1CCCHEq8bf35/u3bvz5MkTHBwcKFGiBAaDgZCQEOLj48mfPz9//vknlSpVyu2mvlaCgoJwcHDIdM0LIYQQQrx8EpwQQgghXiH3799n0aJFHDx4kFu3bmEwGChSpAhNmzalZ8+eFChQILebKIQQQgiR4yQ4IYQQQgghhBBCiFwlNSeEEEIIIYQQQgiRq/4To3U8efIUgyFzY7ELIYQQQgghhBAvmpWVFldXh9xuxivjPxGcMBiMJCVJcEIIIYQQQgghxOvLYDCwbNky1q1bx82bNzEYDBQrVoy2bdvyySefYGdnZ7Z8bGwsc+fOZdu2bYSFheHg4ED16tXp378/lStXzqWjsOw/UXMiIiJGghNCCCGEEEIIIV4Z1tZa8uZ1yvTyBoOBfv36sX//fhwdHfH29sba2ppz587x5MkTvL29WbRoEQ4OydkYkZGR9OzZE39/fwoWLEiVKlUICQnB398fW1tb/vrrL6pUqfKiDi/LpOaEEEIIIYQQQgjxilu1ahX79+9Hr9ezfft2Fi5cyNy5c9mxYwfVqlXj3LlzzJw5U13+119/xd/fn3bt2rF7926mT5/Oxo0b+fbbb0lISGDEiBG5eDSpSXBCCCGEEEIIIYR4xa1btw6A7777joIFC6rT3d3dGTVqFABbtmwB4NatW2zYsIFixYoxbtw4bG1t1eV79+5NxYoVefr0KY8ePXp5B5CB/0TNCSGEEEIIIYQQ4nWWN29eSpUqZbErhpeXFwD37t0DYOfOnSiKQrdu3cwCEyZr1659oW3NDglOCCGEEEIIIYQQr7hZs2alOe/ChQsAFCpUCIDLly8DULlyZWJiYti6dSsXL17E2tqaevXq0bx5czQazYtvdBZIcEIIIYQQQgghhMglt2/fxmAwmE1zdXXF1dU1U+srisLUqVMBaNWqFQAhISFAclHMDh06EB4eri6/dOlS6tWrx/Tp03F2ds6JQ8gRUnNCCCGEEEIIIYTIJd26daN58+Zm/xYtWpTp9SdNmsTx48fJnz8/n3zyCQBRUVEADB8+HDc3N5YvX86pU6f4+++/0ev1HDlyhB9//PGFHE92yVCiQgghhBBCCCHES2YaSvR5MiemTJnCzJkzsbW1Zf78+dSqVQuAFi1aEBoaSr58+di+fbvZtu7fv0/r1q2JiYlh+/btlCxZMmcPLJukW4cQQgghhBBCCJFLChcunOV1kpKSGD16NCtWrMDOzo5p06apgQkABwcHANq3b58qyOHh4UGzZs3YtGkTJ06ckOCEEEIIIYQQQgghsiYmJoYvvvgCX19fXF1dmTlzpllgApKHFwXw9PS0uA3T9IiIiBfb2CyQmhNCCCGEEEIIIcRr4PHjx/To0QNfX18KFy7MX3/9lSowAaDT6YB/hhZ91v3794F/ghivAglOCCFEJl3QnGWh9k8CuILCv75cjxBCCCGEeIUkJCTQt29fLl26RJkyZVi+fLkahHhWo0aNANi9ezdJSUmptnPs2DEAatSo8WIbnQUSnBBCiGckWVkRTep/lzSXidA8YovVelZpVxBGpNn8JCur3G66EEIIIYT4l5o6dSpnz56lcOHCLFmyhEKFCqW5bP369SlXrhxBQUH88ssvasFNo9HI+PHjCQsLo0GDBpQqVeplNT9DMlqHEEI8IxorNl4173+naAzcKzcHh4iKWCfkIbrAMRRNEk4Pq+F0vwYaxYY3y+XFGUMaWxVCCCGEEOIfptE6MiMyMpLGjRsTFxdHxYoV0w0qTJw4EYAbN27Qq1cv7t+/j6enJ+XLlycgIICQkBAKFy7M0qVLKVq0aI4cS06Q4IQQQjzDUnAiwfEWESXXkSekDfZRpTBYxRJd6DBxbv5oE5xxudOQdz2r44Lca4QQQgghRMayEpw4ePAgffr0ydSy/v7+6n8/ePCAWbNmsXfvXu7du4eHhwdNmzbl888/x8PDI1vtflEkOCGEEM+wFJyIzn+SmILH8LjaG63BXp2e4HiLqMIHSLJ/RDGlDC2MLXAj78tushBCCCGEeM1kJTjxXyA1J4QQIhMSncKxjstnFpgAsI0tgvuN93C+04A7hLBYO4cjGl+SSMyllgohhBBCCPH6keCEEEJkQMFAguMdbGKKWJyvwQqnh1V51/g5ZRQ9R7V+LNbO5SbXX3JLhRBCCCGEeD1JcEIIITKQ6HAftEnYxloOTpg44UJb5S3eMXyAFVZssFrFRu1qHhP5choqhBBCCCHEa0qCE0IIkYFEp3AAbNPInHhWMUrQ3dgbH2NTgglisXYOxzSHSCIp45WFEEIIIYT4D7LO7QYIIcSrLsHxFlZxedEaHDO9jhVW1FLqUk6pwAHtHg5rD3JZuUAzYytK8OqMJy2EEEIIIcSrIMvBiYSEBE6fPs2JEycIDw/n0aNHPHnyBDs7O/Lnz4+XlxfVqlWjZs2a2NvbZ7xBIYR4hSkYSXS8jf1jXbbWd8GV9sZOBHGTfdqdrLVaQRlFTwvjGziQ+WCHEEIIIYQQ/2aZDk4cOXKEZcuWsX//fhITk6vQWxqFVKPRAGBvb0/z5s3p1asXlStXzqHmCiHEy5Vkfx/FKhHbGM/n2o4Xpehh/IRTmmMc0xxiv2Y3bZQ3c6iVQgghhBBCvN4yDE6cOHGCCRMmcOHCBRRFwdramgoVKlC2bFmKFy+Os7MzDg4OREVFERkZyd27dzl79izBwcFs3ryZLVu2UK9ePfr160fNmjVfxjEJIUSOSXC6BYBNBsUwM8Maa+ooDYgnnlOaY9RW6pOP/M+9XSGEEEIIIV53aQYnHj9+zJgxY9iyZQt2dna0bduW9u3bU6dOHRwdM05FfvToEYcOHWLdunUcPXqUI0eO0LlzZ4YPH46zs3OOHoQQQrwoCY63sIrPg1WSU45ts5ZSl/OaMxzV+NFO6Zhj2xVCCCGEEOJ1lWZwol27dsTExPDpp5/y4Ycf4ubmlqUNu7u706FDBzp06MCdO3dYtGgRf//9N35+fhw4cOB52y2EEC+cgpFEp9vYPymdo9t1wJFqSk2Oaw9Tx1Cf/BTI0e0LIYQQQgjxuklzKNFmzZqxe/duvvzyyywHJp5VqFAhhg4dyo4dO2jYsOFzbUsIIV6WJPuHKFbx2GRyCNGsqKHUxlax44jWN8e3LYQQQgghxOsmzeDE6NGjyZcvX47urFChQowdOzZHtymEEC9KomNyvQnbHKg38Sx7HKiu1OK6JoC73Mnx7QshhBBCCPE6STM4IYQQ/3UJTrfQJrhglegCQNRDW0IvumJhoKJsqa7Uwk6xl+wJIYQQQgjxn5fpoURTio+PJzIykoIFC6rT9u7dy8aNGzEajTRq1IjOnTuj1UrsQwjxelJQSHC8hV2Ulzrt7nUnHoY5YkjSUML7Mf8/cnK22WFPTaUOh7QHuE04hXm+4UqFEEIIIYR4XWU5evDXX39Rv359pk6dqk5btWoV/fv3Z8eOHezcuZORI0fSv3//HG2oEEK8TAa7RyjWcWZdOqIjbNFaGbl7w5k713Nm9I6qSk0cFAfJnhBCCCGEEP9pWQpOHDp0iDFjxhATE0NUVBQASUlJTJo0CYB69eoxcOBA8ufPz/79+1mzZk3Ot1gIIV6CBKfkehOmYpiJ8VriY6zxLB9F3iJPCTmfh0fh9s+9H1tsqanUI1gTSDihz709IYQQQgghXkdZCk78/fffaDQaBg8erGZOHDlyhIiICNzd3fnzzz/p378/8+bNA2D9+vU53mAhhHgZEhzD0SY6Y5XoCkDMIxsAnN0TKF0rAif3RG6cyEv0/09/Ht5KdRwVJ8meEEIIIYQQ/1lZCk6cO3eOfPny0adPH3XagQMHAGjatCk2Nsk/0nU6HcWLFycgICAHmyqEEC+HgkKi0y1sY4qgIbmwRHSELaDglDcRK2sFfb2H2NgZ8T+cj7gYq+fanw021FLqEaoJJpTgHDgCIYQQQgghXi9ZCk48fvyYwoULo0lRBc7X1xeNRkP9+vXNlnV2diYmJiZnWimEEC/RYx5htH6KTcp6E49scXBNwso6eagOG3sj+gYPUYwa/A/lIynh+apjVlGq4ay4cFh7EIUcGg5ECCGEEEKI10SWghMeHh5ERkaq/x8aGkpwcDAajYa6deuq0w0GA2FhYeTJkyfHGiqEEC/LbU1y9oJtTPLoGYoCMRG2OLsnmC3n4JqErt5D4qOtuXY0H0mG7O/TGmtqK/W5pQkjmMDsb0gIIYQQQojXUJaCE6VKlSIsLIxTp04BsHLlSgC8vb1xd3dXl1uwYAGPHz+mUqVKOdhUIYR4OW4TjDbREauE5ABrfIwVSQnaVMEJAFePBErVjODJfTvWb7FFeY6kh4pKFVwUV8meEEIIIYQQ/znWWVm4S5cu+Pn50bt3b0qWLMnVq1fRaDR069YNgJs3b/Lrr7/i5+eHRqOha9euL6TRQgjxoigo3NGEYBObot7EI1sAnPKmDk4A5C/+lLiYJ5y54EqhvLa80dDychmxxpo6SgN2a7cRyHVKUTZ7ByGEEEIIIcRrJkuZEy1btmTw4MEYDAauXLmCVqulV69etG/fHoD4+Hh8fX3RarV8//33NG3a9IU0WgghXpTHRBKjiVK7dEBylw6tlRFH16Q01/MsF0W1KklsO2jHiQtZivuaqaBUJo/ixhGtr2RPCCGEEEKI/4ws/4Lu27cvXbp0ISgoCE9PT/Lnz6/OK1myJIMHD6ZNmzYUK1YsRxsqhBAvQ5gmBADb2MLqtOhHtjjlTUSTTjhXo4GObROIfgzLNtvj5vqUsiWyXoTCCivqKj7s0G7mOgGURZ/lbQghhBBCCPG6yVLmhEmePHnw9vY2C0wA2Nvb07dvXwlMCCFeW2GEYK84YhWfXEfHaISYSJs0u3SkZG0FH7/zlPzuRuatduDOg2zdYimnVCSv4i7ZE0IIIYQQ4j8je7+chRDiXypcE0ohiqv1Jp4+tkExaiwWw7TE0R4+7fIUKyuF2SsciIrJ+hCjWrTUVXx4qLlPgOZKltcXQgghhBDidZPlbh3nz59n5syZnDlzhpiYGAyGtNOWNRoNly9ffq4GCiHEy/KExzzRPKaisQ43/3+aqRimc97ETG8nn5tC33efMm2pI3NWOjCgeyy2Nllri04pz3HlMEc1fpRVyqGVWLIQQgghhPgXy9Kv3YsXL9KjRw8OHDjA48ePSUpKQlGUNP8ZjcYX1W4hhMhxpnoThZUS6rToCBus7QzYOmatfkQJTyM9O8YRckvLkg32GLPYO0OLlrrGhjzSPOSq5lLWVhZCCCGEEOI1k6XMiT/++IP4+HjKlClD3759KVmyJPb29i+qbUII8VKFEYKdYo87BYBIIDlzwtk9AU3We2dQRZ9Ex5bxrNtlz8Y9Ch1bxGdp/bLo8VAKcFTjh16pgBVWWW+EEEIIIYQQr4EsBSdOnjyJnZ0dCxcuTFUMUwghXnfhmlA8KabWm0hK1BAXZU3+Yk+zvc3GtRJ5EKFl3zFb8rkZaVgz891DNGioZ2zERqvVXNFcpJLine12CCGEEEII8SrLUreOuLg4SpcuLYEJIcS/TjRRRGoiKKoUV6fFRNgCGpwyWQzTEo0GOreMp2KZJNbstOPStaxlP5SiDAWVQhzTHMJA1ocmFUIIIYQQ4nWQpeBE8eLFuXfv3otqi0WRkZH4+Pig1+tf6n6FEP8tpnoTRZV/hkKOfpRcxdI5E8OIpkerhV6dnuJZ0MjCdQ6E3cn8rdeUPfFE85iLmnPP1Q4hhBBCCCFeVVkKTrz55ps8ePCA7du3v6j2pPLTTz9x//79l7Y/IcR/Uxih2Cp2eFBQnRbzyBZ750SsbbNYzdICO1vo+95THB0U/lzhQOSTzBex8KIUhRVPjmsOk0TSc7dFCCGEEEKIV02WghMff/wxPj4+fPfdd8ybN49r167x5MkTnj59mua/57F582a2bt36XNsQQojMCNeE4ElRdchORYHoCFuc3TNfIyIjeVwUPu3ylKdxGrYcsMv0eho01Dc2IloTxQXNmRxrjxBCCCGEEK+KLBXE7NixIwaDgdjYWCZOnMjEiRPTXV6j0XD58uVsNezu3buMGTOGatWqcf78eQwG6WsthHgxYojhkeYhFYxV1GkJT61IjLPC6Tm7dDyrSAEjdb0TOXzWhg5NNbg6Zy4roxglKKoU57jmCJWUqthgk6PtEkIIIYQQIjdlKXPi2rVr3Lx5EwBFUTL8ZzQas92w77//nvj4eP73v/9lextCCJEZ4aSuNxET8f/1Jp6jGKZFipE3Sm7CaADfE5nv2pFce6IhsZoYzmtO52ybhBBCCCGEyGVZypzYs2fPi2qHmb///htfX19GjhxJiRIlXso+hRD/XWGaEGwUGwpQSJ0W/cgWjVbBMU/OdesAsH4aSMmkNVQvVILDJ/W8VXY9xoKNMNq4Z7huUYpTXPHihOYIlZVq2GKbo20TQgghhBAit2QpOOHp6fmi2qEKCQlhwoQJ1K1bl27dur3w/QkhRJgmlMJ4YsU/w3xGP7LFMU8i2qyN/JkhuydnUdDS2MeRU6tdOHU2geYlvyc+Tw2e5mtBkoNXuuvXMzZkhdUSzmpOUlupn7ONE0IIIYQQIpdkKTiRkqIoXLp0iaCgIGJiYnB0dKREiRJUrFgRK6vs/Zo3GAx8++23aDQafv31VzSazKc8P3nyhCdPnphNs7W1pUCBAtlqixDiv+EpsTzU3EdvLK9OMxqTu3V4eMXm7M4UBduosyQ66SleohjFChvYHNqTujW0OEb6Yv/4BImOZYjN14IEF2/QpO55V4SieCmlOKk5hrdSAzsyX1hTCCGEEEKIV1W2ghNr1qxh6tSp3Lt3L9U8Nzc3vvjiC7p27Zrl7c6dO5czZ84wduxYihQpkqV1Fy1axPTp082mVa9enWXLlpE3r1OW2yKE+G+4lBAC0VApTzk8bFwACL2WiNGgJV8hI06Ome86YW9vjYeLY9oLxIRBwj0w1qaAizVvtbBi+hIrAqw+onr9LnD7ADbh28kTOgvsC0DRN6BQY7B2MNtM26Q3mPlkJv7O52ju0Dxbxy2EEEIIIcSrJMvBiYkTJzJv3jwURcHW1pZSpUrh6OhIVFQUgYGBRERE8NNPPxEcHMzQoUMzvd2rV68ybdo0GjduzLvvvpvVZtGrVy86depkNs3WNvmhIiIihqSk7BfnFEL8e13W+GOlscYuMg/3iQLgRlDyvcPa6SkxsUmZ3lZcXBL34+LTnO943w+naFCW7eFpoyRKvdUJNxcnNuw0UqyAAex9oFR9bKPO4vhwNzbXF2O8uYq4vD48dW+G0Ta5LoUdeSitLcuB2IO4RufDi9LPcQaEEEIIIURusLbWyov0FLIUnDhy5Ahz587F1taWIUOG0KVLF+zt7dX5T58+ZcWKFUyaNImFCxfStGlTateunalt//777yQmJpKUlMTXX39tNs806odp+nfffYe7u3nxOFdXV1xdXbNyOEIIQbgmlCJ4Yp3idhh2S4uVjRF758wHJjLD9slZku4WxFp5gv2pU8S89SaNaiWwca89YXe0FC1kBI2WBNfqJLhWxzo2EIeHe9R/8a7Vk+tSOJakmfEN1mtXsl67ihZKGyop3jnaViGEEEIIIV6mLAUnFi9ejEajYcyYMbz11lup5js4OPDhhx/i5ubGsGHD+PvvvzMdnIiNTe7bfejQoTSX2bRpEwBffvllquCEEEJkVRxx3OMudRUfs+mh4VY4500gC2VvMqRNeIhNXAhJYV4o2mi00dHYXr5CvWqV2OFnx/7jtnR/M85snSTHkkQ5fkJMQmccHu3FPsIP+ycnSXQojW3+Frzn8j6brTawS7uVJ8bH1FMaoiEHGy2EEEIIIcRLkqXgxNmzZ/Hw8LAYmEipY8eO/Pbbb5w9ezbT216yZEma8ypUqIDBYMDf3z/T2xNCiIzcIhQ0UNRYXJ0WnwD37msopE/I0X3ZRZ0FA1gFRRBXqyZ2l69gf/w4jpUrUdc7Ed9TNrRvosHNVUm1rtHWnZhC7xDr0R77yMM4PNxDntA/cbIrSseSg9ltvZ9j2kNEGZ/QQmljNuqIEEIIIYQQr4MsBSeioqKoUKFCppYtXLgwV65cyVajhBDiZQjThGKlWFGYfwrwht21wqhocHZPzNF92T45i+GRB1bx0SRUrITi6ITDwYNooqNpVEvDwZM2+J6yoUPTtIMiipU9T/M146l7E+weH8clfCGud9fSskh3XIyuHNX6Ea1E0d7YWUbxEEIIIYQQOSI2NpYTJ05w8uRJ7t69S2RkJBqNBhcXF0qVKkXVqlWpW7cuWm3qkeayIkvBCXd3d4KDgzEajenu2GAwEBwcTN68eZ+rcUII8SKFaUIoRBGssVGnBYcn39uc8+Zc5oQmKQqb2Gsk3tahtXpKol6HwSM/jvv2YXf6NPkbNaKKPolDp21p1SABu4wGCNFoiXeri3VcOI4Pd5Lg4k09l4a4GvOwW7ONldqldDK+hzMuOXYMQgghhBDiv+Xp06fMnj2bpUuXEh0drU5XlORMX02KPtB58+blo48+olevXurAFFmVpdBGrVq1ePLkCfPmzUt3uXnz5vH48WNq1aqVrUYJIcSLlkA897iDp1LMbHrILSvc8hixsc+5EX7sos6jQUEbFEtiqVIo9vYYihQhsWhR7I+fAKBpnQSexmk4ft4mg639I6bAmyTZFcXl1hI0SVFUVKrQ0fguT4hkmXYRD0g93LMQQgghhBAZuXfvHt26dWPWrFlERUVhZWWFXq+nadOmdOjQgTfeeIMGDRpQuHBhFEXh0aNHTJo0iW7duvHo0aNs7TNLmRO9e/dm+/bt/P7779y+fZv333+fsmXLqvMDAgJYtmwZK1aswMrKio8++ihbjXrW5cuXc2Q7QghhcoswFI1iVm8CIPiWFcWK5OzQw7ZPzmCIz4v1nQdE166vTo+vXQvnteuwunWbkkUL4+VpYP9xWxpUTyRTWXFaG54U/Yi8N3/F5dZfPCn2KSU0pXjX2J312pWs0C6lg7EzxfHK0eMRQgghhBD/XgaDgc8//5zLly+TJ08eBg4cSMeOHXF2dra4/L1791izZg3z5s3j4sWL9OvXj+XLl2d5v1nKnKhQoQLfffcdiqKwbNky3nzzTSpXrkydOnWoXLkyb731ltqI7777jkqVKmW5QUII8TKEaULRKlqK4KlOexKt4dFjLUVzMDihMcRhG3OFpHvJdS0SypdX58XVqIFiZYX9ieMANKmTwIMILRevZT5ubLAvSkyBN7GLOoPd46MAFKAg7xt74YIL67QruKy5kGPH86xIHuGr2cc2zQZuE/7C9iOEEEIIIZIDB0uXLuXtt9+mWrVqVKlShXbt2jFjxgzi4+MzXP+TTz5Br9dz7NixNJfZsGEDly5domjRoqxbt47u3bunGZgAKFCgAJ9//jkbNmygUKFCnDt3jh07dmT52LJcsaJbt24sXLiQ2rVrY2VlRWJiIo8fPyYxMRErKyvq1KnDwoUL6datW5YbI4QQL0uYJoSCFMKGf/rEhdxOviUW9cy54IRN9CU0ShKaEDC4uWEoXEidpzg7k1ChAvYnToLBQBV9Eu55jOw/lvmuHQBP87UkwbEMzreXo01ITqNzwZX3jD3wpBg7tJs5pjmEQuqRQLLDgIEArrBau4wFVn9ySnOMQM0NllstZp12hQQphBBCCCFeAIPBQL9+/RgzZgw3b97E29ub2rVrc+/ePaZOnUqPHj14+vRpmuv//fff+Pr6ZrifrVu3otFoGDt2LEWKFMlweRNPT09GjhyJoihs2bIl0+uZZKlbh0mdOnWoU6cOsbGxhIaGEhMTg6OjI8WLF8fR0TE7mxRCiJcmkQTucpvqSm2z6cHhVmg1CkUKGjl/M2f2ZRd1BiOOWN+4RXy1apCicBBAXJ3a2F24gO1VfxIqVqBRrQTW77Yn+JaWEpnN4NBoifL8iLw3RuNyayGPS3wJGi322NPJ2IWdmi0c1h7kifEJzZXWaLMelwaSsyQuaM5xSXOep5pYXJU81Dc2oqJSBVvsOKc5xUnNMZZbLcZLKUVdow+FU2SmCCGEEEKI7Fu1ahX79+9Hr9czZ84cChYsCMCjR4/o168fZ86cYebMmQwZMiTVuiEhIUyYMCFT+7l27Rqurq7UrVs3y21s3LgxDg4O2SrN8FxjfTg6OqLX66levTrlypWTwIQQ4rVwi3CMGiNFFfN6EyG3rSjsYSSbBYZTMyZhG3WBxCel0cbFmXXpMEkoXx6jkxN2x5O7dtSrmoi9ncL+41lrhNE2PzGF3sM2xh+Hh3vV6VZY8YbSgdrG+lzUnmWDdhUJZH4kEgMG/DXmWRJFKEonw3t8ZPyMOkoDnHHBFltqKfXobeyHj7EJd7gtmRRCCCGEEDlo3bp1QHIJBVNgApJH1Rw1ahSAxYwFo9HIt99+i42NjVnNyLQ8efIkSxkTKVlZWVG0aFEePnyY5XXTzJz466+/AHjrrbfU/iWmaVkh3TuEEK+acE0oGkVDEYqq04xKcjHMauUTc2w/NrH+aI1xKOEOKFotiXpd6oWsrYmrWQMHv0NEx8Rg7+REvaqJHDhuQ4emGtzzZL4rRpxbA2yjzuF0bx0JzhUw2Cf/UdGgoYHSGBejK3s1O1il/YuOxndxIu2+g+llSaQaotSYiDYpEqNNfmw1yUEKb6WGZFIIIYQQQuSgvHnzUqpUKapUqZJqnpeXF5BcnPJZc+bM4cyZM0ycOJE1a9Zw7dq1dPcTFxeHg4NDttvp5OREXFxcltdLMzgxZswYNBoN9evXV4MTpmlZIcEJIcSrJkwTQgEKYoedOu3BIw1P4zQUz8FimHZPzqJo7bC+8UAdQtSS+Nq1cTxwELszZ4jz8aFRrQQOHLfB96QtbzXPuLCRSqMhqkgP3K//hEv4fCJLDgPtP7f5Kko1XBQXNmvXs1y7mI7G98hHfnW+AQPXNQFc0JwlVBOERtFQmrJUNlSlOCUtdgfRJj7GNWQaNnGhJNkWIN61BvF5amBrV5RaSJBCCCGEECKnzJo1K815Fy4kF0AvVKiQ2fSrV68ybdo0WrduTYcOHVizZk2G+1EUJcvP/SlpMzXsXGppBidq1aoFYBYxMU0TQojXVRJJ3OEWVZUaZtODb1kBUKKIAcj+zVilGLGNOkuCosPu1nWi3+yQdps8PUkqUgT748eJ8/HBPY+Cd/kkDp+xobVPPPZ2aa6aerfWrkQV6U6e0Fk43t9CbMG3zOaXpAzvGruxQbuKFdolvGl8B2ec0siS8MY5newKq/g75AmeitYQTYzHm9jEXsfxwQ6cHmwjybYg8a41sMpTg1p2dfHWSJBCCCGEEOJFUBSFqVOnAtCqVSt1ekJCAt9++y2urq5qt49XWZrBiSVLlmRqmhBCvE7ucAuDxoCn0bzeRPAtK2xtFArlNxKL1XPvx/ppIFZJT0i4kw+4brHehEqjIa52LZzXb8Dqzh0MhQrRtHYCZy7bcPScDU1qZ62rSYJrNeLc6uH4YBsJLpVJcixlNr8Qhelq7Mk67QrWaP/GqDGmyJKoRglKoskgQGMde5M8IdMBLZFeg0ly8Eo+lKRo7J6cwe7JKRwfbMPpwdbkQEWemtR1rYG3XXXOaU9LkEIIIYQQ4v/dvn0bg8FgNs3V1RVXV9dMrT9p0iSOHz9O/vz5+eSTT9TpU6ZMwd/fnxkzZuDu7p6jbX4RsjVahxBCvK7CNCGggCfFzKaH3LKieGED2cxCS8XuyRkUjRXaoBgMefJgKFw43eXjatTEaeMm7I+fIObNDpTwNFKyaBIHjtvSqGZiltsVXagLNjH+uIQvIKL0CNCap1/kwY2uxp4c0OzBTcmbYZZESrZR53ANnYPRxo3IEl9gtPVQ5ynWzsS5NyTOvSGapCfYPTmL3ZOTON7fitP9LSTZFaaxaw2qu3bitMMtCVIIIYQQ4j+vW7duhIebFxAfMGAAAwcOzHDdKVOmMHv2bGxtbZk8ebIahDh16hTz58/nzTffpEWLFlluU0BAAD179szyeqZ1s0OCE0KI/5QwTQgeFMSef+o/JCVB2F0tTWpnfhSLdCkKdlFnSbTXYRNwnfhqVVMNIZpqFVcXEiqUx+7kSWLatwOtlqZ1Epm/xoHz/tZULZ+UtSZYORDl+SF5gn7H+c4aoot8kGoZexxorbTP0nbtH/nifPsvkuyL87jEABTrtCP6irUrce6NiHNv9P+BijPYPT6J4/0tON3fTCu7Ivwfe/cdH0d1Lv7/M7N9V733XtzlKtu4g7Gxacb0XkJIcAglCUngXm7yS+7lmxBIAoFAqKYa40IxxWBw773J3ZLVbfW6fef8/lhbIGzJWsnd552XYnnmzDlnZCHtPnPO84wMHcjaCAsbDLv4UPcOE7RJx225kSRJkiRJupC9//77J1w50Rmv18uf/vQnZs+ejclk4l//+ldbGga73c7vf/97oqOjeeqpp7o1p+bmZtYfrSbXHd3JWdFhcGLkyJHdnsgxiqKwevXqHvcjSZJ0KvjwUUk5/cTAdsfLj6j4fKcuGabOVYHOXY3LNQij81DnWzp+wDksn9CdBRj27sXTuzf9c7xEhmksWWcMODgB4LHl4oi8DGvtt7iCB+AJ7hdwH22EwFr9Obbqz3EF9aMp6aegO3GCzxNerg/BGTEOZ8Q4FE8jpqbNmJo2E1b1FVOqBGPNibyfGs5q4zJ6iT6Y6X6GaEmSJEmSpPNJ/ElW2P5Ya2srjzzyCCtWrCAkJIR///vf7fJDzpo1i5KSEnJzc/nTn/7U7toDBw4A/uSac+bM4ZZbbmHo0KHt2jz00EPdvJOe6TA4UV9f3+POe5LhU5Ik6VQ7TCVexUvSCfJNwLFkmD1natqCQIEScbSEaG6XrnP364tmtWJevwFP796oKozPdzPvGzNFZSrpSYEHT1pjpmFs2UVwxTvUZ/4PQt+1rRvtCB9BFR9gaViJM2wkzQl3gtL9vBzCEIozcgLOyAmonkaMTZsxNW3kquJ9vJidwHplDWPFpd3uX5IkSZIk6ULV2NjIvffeS0FBAfHx8bz66qvk5LQvV2+32wHYu3cve/fuPWE/xxYRXHLJJed+cOKdd945k/OQJEk67cqVEgCSfpRvorhCR0iQRliwOCXjGJu34rVkYNx7EE96GppJBdGFLSM6cA4eiGXdelocDoTFwvA8D18uM7F0vZH0pMDrRaMaaE68l7CivxBU+QHNST896RaTdjQ3IaWvYmrZQWvUFOwx1wZ2/cm6/0GgIqxyNgMbdrA1bCODxFCC6VoSKEmSJEmSpIuB2+3mgQceoKCggKysLN54443jSocC/PKXv+wwX8U999zDmjVreOeddxg+fPjpnnJAOgxO5Ofnn8l5SJIknXZlSgmRIgoL1nbHSyp0pCb4Tsl7btVdg8FZSqvlSmwVizkwbDDFOwu6fH1wZDj5Hi+mLVtxXjISkxEuGexm8VojtQ0KkWGBB1C8lhTs0Vdhq/oUd+NAXGFd+/mueFsILXkRveMQzfG34YwYF/DYgXBETWLioZXsCLOxWlkecD4MSZIkSZKkC9kLL7zA1q1biY+P59133z0nKnDs2bOH4uJiwsLC6N+/P1ar9eQXdUAmxJQk6aLgw0cFZfQR/dsdtzugqk5l2IDAynV2xNS0FQBR7s/HUJOcFND1zVGReONiMa9fj/MSf+6fsUM9LFlnZNkGI9Mvd3VrXvaoyRibdxBUOQuPLRvNEN5pe9VdQ2jxC+g8dTQl/xx3yMBujRsIzRBOkC2fkTW7WRm1gyEinyhiTvu4kiRJkiRJ57qGhgbeffddACIiInj66ac7bPvss8+ekjGPHDnCu+++y86dO/nnP/9JWFhY27mKigoeffRRduzY0XYsODiYGTNmcM8993RrvA6DE88880y3OvwhRVF4/PHHe9yPJElST1VzBI/iIVG0zzdRUnlq800Ym7fgNSVg2F+OLzSU1vCwwDpQFJz5Qwj67Et0VVX4YmIICxEM6uNl7VYDU8a4sHQ9D+UP+tXRlHgvEYX/S3D52zSmPgzKieuT6h0lhJT8C0V4aUh7FK81C58PGpoV6ptUGpoU6htV6pu+/3uQTXD3NCdB1p5tjbFHXcG4wrVsjAxlpbqUadpNPepPkiRJkiTpQrB9+3acTv8W34KCAgoKOl6ZeyqCExs2bGDGjBm0tLQAUFNT0xacaGlp4bbbbuPIkSMIIQgPDyc0NJTi4mL++te/Ul9fz2OPPRbwmB0GJ958880eJbQUQsjghCRJ54yyY/kmxPH5JhQEKfE9D06o3iYM9oPYI67AsnctroEDupWfwTlkMLYFX2HasAH7lVcCMCHfzaadBtZsNXDpiO6t8tBMMbTE3kBw5fuY65bijPQnnRQCmlsVGpoUmqrKcZRuo9Z5I4fJp26N1X+8RfEn+fwBm0UjLEQQHiLYd0jHq7Mt/OJ2OyZjt6bnn6MxGl3QEMZV7efruIOUUkwyqd3vUJIkSZIk6QIwduzYDpNbBmLmzJknbdPc3MwjjzxCc3MzGRkZXHXVVcTEfL+a9aWXXuLw4cMoisKdd97J7373O/R6Pbt37+anP/0pr7/+OldccQW9u1ix7pgOgxPTpk2T1TYkSbpglCklhIsIbLSvVlFSoSMmSuveaoQfsTZvQ0Gg1cWgOp24e3etSsePaaEhuHv1wrx+A/YpU0BVSY7XyErxsmyDkXH5HnQnXvRwUs7wMRibt+E5tJjvCkaxYW841bUqXt+xn/c5QA4GvUZ4CISFavTK0AgPPRaI0AgPEYSFaO2CEDv26nljnpm35ln46U0OdN0v5oE96gpGFm5gdXQEK9Ql3KrdjYL8fSRJkiRJknQmzJo1i7q6OsaOHcu//vUvTCZT2zmPx8PcuXNRFIXk5GSeeOIJVNX/wrR37978z//8Dw8//DBz587lqaeeCmjcDoMTf/nLX7p5K5IkSaeGFy8blbUcVPa3O6504f+/b+v/+xEO00f0a3dOCDhUodIn89Rs6bA1bcFniES3pxahqrhzs+HAwW715cofhuntdzDsP4An118eavxwN6/PsbJtt57Bfb0B9+n1wc79BtZteYzdhSYEKhlJXsYOcxOj20WCdzGhEUEYsqdjDTIHtOijf66Xm6e4+PBLM+9/buaOa5yo3Ywn+MwJiOCBTKws4uMkL/uUPeSKwCLvkiRJkiRJUvcsW7YMVVX57//+73aBCYD169fT3NyMoihMmzatLTBxzGWXXUZQUFBbqdJAyISYkiSdk0op5jt1IfVKHYkiGSPt9woIRBc+//6zRJLoJ/La9VHfpNDSqpIS34UynydhEE4srbtwhI/DuGc3nox0hLn7yzFc/fujWcyY169vC070zfYRHaGxeJ2RQX28XQ4elB9RWbfNwMadelodKqFBGpOHlHJ5+POEpA9B8Tmw1i3GGTKU5sQbQTV0a84jB3lotit8sdREsFUwbaKr2xVQ7FFTGFL4f6yMjWWVfilZIgcdPViOIUmSJEmSJHVJcXEx0dHRpKSkHHduzZo1bZ+PGTPmuPM6nY7k5GSKi4sDHrfD4MSyZcsAGD58OOajL7CPHQvEuHGnt/ScJEkXFgd2VihLKFC3EyLCuM53M2lknJaxisv9b3bTEnu+ciJN7EURXjxkYy1fTcvVPSyDaTDgGjQY84YNtNx4A8JsRlVgfL6bOQvNFJbpyEzueN6tDti008C67QbKDuvQ6QT9c7wMH+CkV4YPVY0guCwFc/UXANgjL6M19oYOk2R21eWXuGluVVi63kiwTTDxku4FfryWFDxB/biiopx3U0PZoWxhoBjao7lJkiRJkiRJJ9fQ0ECfPn1OeG79+vUABAUF0a9fvxO2URQFIQJPkt5hcOJnP/sZqqryxRdfkJ6e3nYskDwUiqKwa9eugCclSdLFRyDYoxSwTPkWFy6GaSMZLkZhoHtP8buiuEKHXieIj9F63FcmO/HpglEP+bMou3uf+Ad6IJzD87GsXo1p61acI0YAMKy/hy+WmVi6znBccELTYG+RjnXbDGzfp8fnU0iM9XH9JCdD+nqw/ajsdEv8rajeRtzBeTgiL+vxfMGf//O6y1202BUWLDERZNMYkRf4FhQAe/RUehU9Q4o7ibWGVfQW/TFhOvmFkiRJkiRJUreFhIRgt9uPO97S0sKuXbtQFIX8/PwTxgaEEJSXlxMe3nnZ+hPpMDiRkJDgb6DXH3dMkiTpVGqgju/UrylRDhEvEpioTSGKmJNf2EMlFSpJcRr6Hu4W0AkvaWI39uBhGNfswRcaii8hHuheVY1jvKmpeGOiMa3f0BacMBlh1CA33642Ul2nEB0hqK5TWLfNwIYdBhqaVawWwahBHobneUiK6zjwInRWGtN+1aM5noiqwO1XO7E7FGZ/YSbI4qBfTuCrU7zWTDy2XKaUVfCfjGA2Keu4RIw95fOVJEmSJEmSvpeRkcG2bdtoaWkhKOj7ZPKLFy/G6/WiKEqHOyQ2bNhAY2Mj/fv3D3jcDoMTixcv7tIxSZKk7vLhY6OylnXKKnTouVSbzAAx6IxUZvBpUHpYx8iBPQsgACRxABMu6m0Dse19H1feQP8SgsBXs7WnKDjz8wn6/AvUmhq0qCgAxgz1sHitkTkLzXh9cLBEj6IIemX4mHa5i/7ZXvRnOaOQXgf3Xe/gxfeszPzYwoO3OTrdhtIRe9RUUov/QS9nGptN68kTg4+ruCJJkiRJkiSdOpdeeikbN27k2Wef5Y9//CMAbrebN998EwCDwcDll19+3HVut5tnnnkGRVEYOzbwB0o921wsSZLUTeWU8b76JqvV5WSIbO7WfkqeGHzGSkYerlZxexRSEnqebyJT7MSNCVFtQXU4cQdY07kzrmHDEIqCecOGtmOhwYIh/bzsLdLT1KJy1XgXf3yolZ/f4mBQ77MfmDjGZISf3ewgPETw2kcWKqoC/5XjseXisaRzRVkxPnysVVaehplKkiRJkiRJx9x6663ExcUxe/ZsbrzxRv7whz9wzTXXsHfvXhRF4d577223bUPTNDZu3Mjdd9/Nzp07iYqK4vrrrw943HPkJawkSRcLJ05WKkvYoW4lWIRwre8GMsg+4/Morjg1yTAVoZEpCjik9CJmz16EqrZV1zgVtLAwPDk5mNdvwD55Mhwt13TDZCfjhrlJjNW6XRHjTAiyCR68zc4/Z1p5ZZaFR++xExEawJISRcEefSUxJS8y0JXDFtNWBolhRBB5+iYtSZIkSZJ0EbNYLLz++us88MAD7Nixgx07drSdu/zyy/nlL3/Zrv3ll19ORUUFQgjMZjN//etfsdlsAY/bYXDiiSeeCLizH1MUhaeffrrH/UiSdG5TVQ2fr/OkhwLBPmUvy9QlOHAwWBvCKGUserpfbrMnisv9uRkiw3q29yKeYqy0cJC+pO7egCc9HWGxnKJZ+jnz8wl5910MhYV4srIA/6qEzvJJnEsiQgU/v9XBC+9aefkDK4/cZSfI1vWvuzuoHx5zMhNLD7IjK5RV6jKu1qafxhlLkiRJkiRd3LKysli4cCFffvklBQUF6PV6Ro4cecLtGkFBQQghGDlyJL/+9a87rOJxMh0GJz7++OO27JvdKQMCMjghSRcLn8/Ljp0FHZ53GO3sTdpFbUgNwfYQhpaOIMQRiq6fyhnaxXGc4kodqfG+Hq86yBQ78aGjyp6IqfxjWq7qYQnRE3AN6I9mMmFet74tOHG+SYjR+OlNDl7+wMJ/Zlt46A47JmMXL1YU7FFTCCt7leGOvqy07qWCMhJIOq1zliRJkiRJupgZjUamTZvGtGnTOm33/PPPExYWRlhYWI/G69K2jj59+nRYKkSSJKkjGhql0cUUxu9HEQrZZb1Irkk9Y3klOuJy+3NO5OW6e9aREGSKnZSSRUJpGQDuPqcu30QboxHX4EGYN22m+YbrwXR+ltPMTPZxz3UO3phr4Y25Fh642dHlSinukEF4jXGMK9vH5uxQVqhLuEm746x/L0mSJEmSJF3s0tLSTkk/HQYnbr/9dhYtWkRVVRW7du3i8OHDXH755VxxxRUMHz4cVZW5NCVJ6piGxubs9TTaGohqjCG3rDdmz6nd7tBdpZU6hOh5MswoKgmljo3KBNJK9uMNDcV3mkouO4flY1mzFtO2bbjy80/LGGdCvxwfN1/pZNbnFt5fYObOa52oXYkvKCr26CmElL/FaEce31gLKOQAmWchX4kkSZIkSZJ06nUYnHjqqad46qmn2Lx5MwsXLmTRokXMnj2bjz76iPDwcBmokCSpU61GO422BrR1o3Ef7EdZsJ3wkFZCg+zodT2tsdkzxRX+n1mp8T3L2ZApdiJQKBK9GV22GMeggZyu7JTejHR8UVGY1284r4MTACPyvLS0uliwxESQVTD9cleXvmyu0GH4qhYworyADVkRrFSXkK5losrCU5IkSZIkSafMXXfd1aV2Op0Os9lMdHQ0ubm5TJgwgYQePKg76baOwYMHM3jwYJ588km2bdvGwoUL+eabb9oCFWFhYW2BihEjRshAhSRJANQo/i0TDXv6UFaShCb8PxsUBCFBDsKDWymrs5AQoxAfrREVoaE7Qz8+iit0RIZpASVlPJFMsZNKUgk9Uo/J7aShT5/T9zZZUXDmD8P25VeodXVoERGna6SAqA0NmDZsRF9VhSc1FU9WJr7Y2JMGaS4b6aa5VWHpeiPBNsGkUV3YYqPosEdNJrjyfcbah/GpbQMFynb6i4Gn5mYkSZIkSZIk1q9fH1D7Y+kf/vKXv3DHHXfw+OOPdysuEFAp0by8PPLy8vjd737Hjh072lZUfPTRR8yZM4fQ0FAmTZrE5MmTGTFiBDpdFzcTS5J0wanTOxBCYVx6NVH9S2lstVDfZKWh2UZ9s5X6JhvfrLIghP+HmU4niIvUiIvWiI/WiI/2ER+jER4qurbsPwDFFToyknq2pSNE1BFNJcuVq0gr2Y+mqDhyexF40aSucw7zByfMG46WFT1bPB5MO3diXrcOw569KEKgWa2Yj/4i02w2PBkZeDIz8WRm4E1MhB/9PlAUuHaiixa7whdLTQRbBSMHeU46tDNsJNbqLxhYuZX1mQmsUVbQS/TFgOG03KokSZIkSdLF5qGHHupSOyEEdrud6upqCgoKKCoqYubMmTQ3N/O///u/AY8bUHDih/r370///v15/PHH2b17NwsXLmThwoXtAhUTJ07s1qQkSTr/tZpb8NZFEG51oaqC8GA74cF2oKatTW5uX6rrzFRWq/6PKh2FpTo2FXz/RtNoEGSleLl5qouwkJ5vB2lsVmhoUklN7FkyzEzhr/d8UOnHlaWzqYhLPlpCtGdBj85oERG4s7Mxr9+AfdKk07aF5ISEQF9WhnndOkybNqPa7fjCwrBPnIgrPx9fdBRqTQ3GgwcxHCzEcPAgpqM1sTWTCW96mj9YkZGJJzUFDAZUBW67ykmrXWH2VyZsVsGA3M5L0qIacERNIujwR4y3j2KWbSlblA3ki0vOwBdBkqSLQVfKY5+ITqdH0+QKYkmSzn9dDU782Pr16/nVr37FvHnzmDZtGkOHDg3o+m4HJ36od+/e9O7dm4ceeoj333+fF154gYaGBubNmyeDE5J0kfIEN6BVx2DQd5zXwWiApDiNpLj2bRxOOFyjUlmto7q4lNV7k3j2VYX7JxeQ0SsBzRDW7XmVVPif4Kf2MBlmpiigmni8diMxNYdZNXwipycVZnvO/GGEvP8B+sIivJkZp308pbkZ88ZNmNetQ19ZidDrcQ3oj3P4cDw5OfCDJXtadDTO6GicI0YA/i0fhsLCtmCF7YsvARA6HZ60VH+gIjOD+65M58V5Ebz9sZkHb3OQldL5v40jfAzW6q/IPbKBjPQsNihr6S8GYsF6+r4QkiRdNE5WHrsj/fv1RVG6WiNZkiTpwpOfn8+f/vQnZsyYwYcffnjmgxNOp5Nly5bxzTffsHz5clpaWhBCoKoqgwcP7mn3kiSdh3yKDxHSgOFgDnRjd5fFDOlJGukJLiItz3J5chr/WnUP//xsGDcfmM3k/tvwhvTHHdQfryUVlK4/qSquUFFVQWJs95NhWkUzCRxinTKRtNL9ABxKyTkjwQlXXh5izlzMG9bTcrqCEz4fxl27MK9bh7FgF4qm4UlNofnGG3ANHoywdi0IoIWF4Ro8GNfR3wVKayuGwiIMBw9iKDyI9bvvUBYtIlRR+GNCEmtcuXz04RTuvddAfHQn/z6qEXvkRIKqPmacfTwzrQdZp6xmvJh4Ku5ekiRJkiRJ6qYJEyYQFBTErl27Ar62W8GJpqYmFi9ezKJFi1i1ahUulwshBHq9npEjRzJp0iQuv/xyIiMju9O9JEnnuVZjK4oqsDiCIaj7/Ziat6D6mgnNvZRH+9n4cEELH+66lb2NA3kw7++EG79A0wXjDu6HK6g/nqA+CF3n5UqLK3QkxGgYe5CiIF3sQkFwUOnHsJIVtNiCqYmM7X6HgTCZcA0ciGnzFlqmTwfjqXtKp6uoxLxuHeaNG1FbWtCCg3GMH4czPx9ffHyP+xc2G+7+/XD37+c/4HJhOHTIH6w4WMi4w0uIcFbxyqxf8tg99k638TgjxmGt+ZqUqlX0TR3ANmUTg8RQQgnr8TwlSZIkSZKk7lEUhZSUFIqLiwO+tsvBiZqaGhYtWsSiRYtYv349Pp8PIQQGg4GxY8cyadIkLrvsMsLCwgKehCRJF5Ya1QVAqMcKdD+3g6VuGT5jNB5bL0yKwl3XQ/pGJx9/24snW1/m55M3kWFeg7F5G+aGNQhUPLZs3EH9cQf3x2dsXzVCE1BSqWNI35MnXuxMlthJIxHUajGklB7kYEafM5r/wZk/DPP69Zi278A1dEj3OhECfD4UuwPTtm3+5JalpQidDnffvjiH5+Pu3fu4RJanlMmEJzcXT24uAJZFixjw+RckNR3glQ8zefguO1ZzB9PXWXBETsBW/QWjnBPZYylgtbKMKeLa0zdfSZIkSZIkqUuUbrw27jQ4UVZWxqJFi/jmm2/Ytm0bQgiEEJjNZsaPH8+kSZO49NJLCQrqwaNRSZIuOA16J8KnEqUY6G5wQucsx2A/QEvs9W3bNhQFxg7zkBzv4615Fv46L5+bpgwgv78Lvb0IU8sOjM3bCToyF47MxWeMxnU0UOGxZlNdZ8LpUnqUb8IonCSxn+3KJcQfKcfsdnIoJbvb/XWHJzMTX0QE1u++Q3f4MIrHjeLxoHi84PGgeD0oHo//c4/36Lljf/egeI+2E9+vTPAmJtBy3XU4hw5BnKWf6Y5x47AsX8EvDHN4qOYJ3phj4cFbHeg7+E3liLgUa+23xFYvZ1DyMDaoaxjsG04scWd24pIkSZIkSRIAmqZRXl5OdHR0wNd2GJy47rrr2LNnD+AvEWK1Whk3bhyTJ09m3LhxWCydL52WJOni1WpuwVMXSYTN2e0+LHXLEIoeZ9jxVRjSkzQev9/O2x+beX+BhaIyHdMnZeG1ZdEaex2quxZjyw6MzTuw1K/AWrcYTTWxo/JaYBpZITtQ3dFohsiAVzykiT3o8XFQ6Ufq0RKiJUmnPzFlO6qKY8wYgj79FN3hwwiDAfR6hMGAMBrAYEDoDQiDAc1m8//96AcG/fef6/3tPVlZeJOSzuw9nIjRiH3yZELnzOHRSRt5bms+731m5q7rnCcsJyv0QTjCx2GpXUR+9CR2WLawUl3C9dqtZ37ukiRJkiRJEt988w2NjY2MHj064Gs7DE7s3r3b30CvZ/jw4YwePRqj0UhtbS3z58/v8gC33357wJOSJOn85g5uQKtIxGjo3goFxefE1LgWV8hQhP7ET/GDbYIHb3Pw5TIj3642UVqp497rHUSGCTRjJM6I8TgjxoPmxti6B2PzToq2x2LWO8hpfR51v0DT2fCaU/FYUvEe/dD04dBJvCKTndixUUka40q+pjIuGbfpzAdrHZdOwDF+XLtqGRcC58gRWJYuJW/HZ0yb0I9PllgJCRJcd7nrhHEke+RELHWLiahZwvCkUSxTv6OYQlI5wwEjSZIkSZKki9y6dev4wx/+gKIoXHtt4FttO93WoSgKXq+X1atXs3r16m5NUAYnJOni4lO9iOBGDM19oZtJJ02N61A1F46I8Z2206lw9QQ3aQka7y8w8+ybNu661kHvzB8ERVQj7uABuIMHsK/VSnKiRmPmE+gdxf4PZzHWmq9R8FeH0HTB2CxpjNBiOaIkc4Qk7EqIfzzhIU3sYZ+Sh8XRSkxNJauGn8UKERdYYAIAnQ77lVMJmfk2V+jWUJ8/hmXrjYSFaFw64vhcIcIQijN8NOa65QyMnsIWcyjfqV8zUAwlTWQQTgRKZ9EmSZIkSZIkqZ0XX3yxy209Hg+1tbXs3r2bXbt2IYRg6tSpjB07NuBxOwxODBs2LODOJEmSWoytKApY7cEQ2o0OhMBStwyPORmvJa1Ll/TP9fLr6FbenGfhPx9amDzGzeQx7nZbATxeqDiiMmGEt22VRBvNjd5Zjt5xCIOzGL2jhGFiJ+rRnAwthHCEJJyKDSOuo1s6DgCc8XwTFwNXXh6epCRsC79i2pODaWpW+PQ7M6HBgiF9vce1t0dOxly3nJDab7k8fiqL1a9Zpn7LMiBYhJAqMkgT6SSThpkOMmxKkiRJkiRJgD84EUhCS3H0NbOqqtx666389re/7da4HQYn3n333W51KEnSxa1W588zEeq1AIHnnNDbD6J3ldOccGdA+SCiIwSP3WNnzkIzC1eYKC7Xcee1DmxW//nyIyo+TSElXjv+YtWI15qO15qOE2hBx5e7jxBNObGijBjKiBVlhIvd2LFRSjaTSubTYg2mJlImXzzlVJXWq68m7OWXsa1axe3XjKO5VeH9z8wEWR3kprffLqQZI3CGjcRcv5LUqKncY/gZjTRQrBRRrBSyT9nNTnUrilCII4FUkU6ayCCWeFQuwNUnkiRJkiRJPdDVhQqqqmKxWIiOjiYnJ4fx48eTnJzc7XG7XEpUkiSpKxr0DoRXR7TSvR8vlvplaKoFZ2jgq7eMBrjtKifpST7mfm3ib2/YuPd6B6kJGofK/SUx0xK7lgfDqxipJJ1KJb3tmEE4UdHQhEJK6QEOZvQ+oyVELyae3Bzc2dlYv/kG54jh/ORGeOEdK2/MtfDIXXYSY9sHmexRV2BuWI219lta464nlDAGiEEMEIPw4eMwFRQrhRQrRaxVVrJWXYlJmEkRaaSRQapIJ5iQs3S3kiRJkiRJ546ztVBBBickSTqlWs0teGqiCQ8KfNWE4m3C1LQJR/g4UE0AqLW1GAsKEDYbWnBw24ewWk+Yc0FR4JJBHpJifbw138Lz71i5fpKL4godocEaocHiuGu6yqP4twQkHC4+KyVELyqKQuvVVxP+979jWbIEMWUKP7/FwT9mWnnlQwuP3WMnIvT7f0vNFIMrdBiW+mXYoya3S6SqQ0ciySSKZC4R43Bgp0Q5RDFFHFIK2a/4K1NFiCjSRDqpIoMkktF3N2mKJEmSJEmSFDAZnJAk6ZRyBzfgK07HZDw+N8DJmOtXowgfzojvE+gEzZuPqaDguLZCVdGCghDBQd8HLYKOBS+CyAwO5skrgpm9Kpp5X4YhVB39cgKf04l8X0I085T0J52YNzUF18A8LEuW4hg9mrCQYH5+q4Pn37Hyyiz/Copj23bg6OqJxvVY6hZjj7mmw34tWMkVfcilD0IIaqlpW1WxTdnMZnUDOqHnCu0qcuh9Bu5UkiRJkiTp/FRXV0dZWRlms5mMjAz0+u6HGGRwQpKkU8areiGoBUNzGAHnHRQalvrluG25+EzxwNFVE7t2YZ8wAeeI4ajNzW0fSnMLasv3fzdUVaE2t6B4vq/oEAY8dvTzJiWIZmMWps0DcPXtCyZTt+8zrWQ/lbFJZ6WE6MWmdepUwrfvwPrNIlqvn058tMb9Nzr49wcWXptjZcZtdoxHFzj4zIm4ggdirf4SY/N2PLYcPLZcPNZshM56wv4VFKKIJkpEM0QMx4uHMkpZqS5hmfodGVo2evmrUpIkSZKki4zD4WDWrFls3bqVF1544bjzRUVF/H//3//HunXr2o5ZrVZuueUWHnnkEYxGY8BjyldckiSdMi2mZgCsjmAwnyDxZCeMLQXoPLW0xF7fdsyyeg0AjnFj0cLD8cWdJPmkECguF0pbEKOlLXghqhuI27cL3dtbEQYD7j59cA0aiKtPn4ACFVZ7MzE1lazOvyyg+5O6xxcbi3P4cCyrVuEYPw4tMpKsFB93Xetk5nwz73xi5r7rnW07fJoT7sRSl4ShdR+WumVYa79DoOA1Jx8NVuR0GqzQYyCNDFRNZZ5uFjuULQwSsnqVJEmSJEkXj9LSUu677z7KysoAaGpqIiQkpN35W265haamJoQQmEwmPB4Pra2tvPnmm2zdupW33nor4ACFDE5IknTK1Ov9eSbCPBagNaBrzXVL8elDcIcM9B/wejGvXYu7b1+08PCudaIoCLMZYTajRUcfd7pO0zAUFmHauhXjtm2Ytm3zByr69sE5cBDuPr1PGqg4VkK0KDUnkNuTesB+xWTMGzdi++ormu+4A4CBvb1Mn+Ri3jdm5n4tuPEKF4oCQh+EPeZq/4WaB4OjCEPr3qPBiqVYa7/9QbAi9wfBivarYFJII1mksl5ZQz+Rh4HAo/+SJEmSJEnnoyeffJLS0lLCw8O58cYbjysr+n//9380NjaSlpbGM888w4ABA3C73XzzzTc8/fTTbN68mbfeeouf/exnAY17TgYnfD4f77//PnPnzqWoqAiLxUK/fv246667GD9+/NmeniRJHajXO9A8BiJVXUDXqe4ajC0F2KOnguK/1rRtG2pLC47Ro07dBFUVT1YmnqxMmH4dhsJCTFu3Ytq6DdPWbQijEVefPmgDB6PXJ+A1HP+GNK1kvywheoZpYWE4xo7BsngJ9gmX4ktMAGDsMA8NzQrfrTERFiKYNMrd/kLV0LZawt+RB4OjEEPrvqPBiiVYaxd1GKwYqY3lI927bFU2M0yMOMN3LUmSJEmSdObt2bOHDRs2kJCQwNy5c4mIiGh3vq6ujuXLl6MoCs899xx9+/YFwGg0ctVVVxEXF8cdd9zBggULLozgxBNPPMGnn35KUFAQI0eOxOPxsH79elatWsXDDz/ML37xi7M9RUmSTqDV3IKnOobwYEdA11nqlwMKzvAxbcfMq1bhi4rCk5t7imd5lKriycrCk5VFy/TpGA4ePBqk2Ers1q08oDdQlJrL/sy+HErJxmswomg+WUL0LLFPnIh59Rpsn39O088eaDt+1QQ3Dc0qXyw1ERqkMTyvk6SnquFoAOLo95TmPrqy4kTBihT0CbeRZstgo7KWAWIQJrqfp0SSJEmSJOlcV1FRweeffw7AiBEjKCws5ODBg+3abNiwAU3TSE1NxeFwsGHDhuP6iY6OpqSkhI0bNyKEYNiwrm2R7TA4UVFREch9dCghISGg9l9++SWffvop6enpvPfee0RFRQGwf/9+br31Vl588UWuvPJK0tLSTsn8JEk6ddzBjWgHs7CYPCdvfIzmwVy/CnfwADSDf/uGrqIC48FCWq695oTlQk85VcWTnY0nO5uW66fjPVhE9ZK1ZBXuIufgTjxHAxU1kTGyhOhZIqxW7JddRtDnn2M4eBBPpr9SiqrAbVc5aW5V+PALMyFBDnpn+rrWqWrsIFixF3P9CoIqPmBkxj3M0r/NFmUDI8To03R3kiRJkiRJZ9/8+fN5/fXXURSF+fPnM3/+/OPaKIqCoigUFxdzx9HttieiKAp33HEHiqKwe/fuLo3fYXDisst6nuxNURR27doV0DWfffYZAL/5zW/aAhMA2dnZXH311XzwwQesWrVKBick6Rzj0bnB2oq+KRxsXb/O1LQZ1deCI2Jc2zHLqtUIvR7n8OGnYaYnoao4s3NY4otm6eipJFYUk32woC1QIUuInj2OcWOxLF+ObcHnNDzycNvqFb0OfnK9gxfetfLmPAu/vMNOSkJgCVmBdsEKzRBBcMW7JLfUkRmawyZlPQPFEMzICi2SJEmSJF2YHnroIWJjY3nqqad45JFHePDBB9ud93q9XHrppVRXV/PBBx8wePDg4/oQQjBx4kTq6+vZtGnTcfkqOtPhI0khRJc+goKCiI+PJyIiot3x0NDQ4/andMULL7zAggULGDt27HHnWlv9CfZ0usD2s0uSdPq1mFqAo5U6AmCpX4bXGIPH1gsAxenEtGEDrkGDELYAohyngVB1lCVlsGTc1bx+92+Yf/XdfDr1dllC9GwxGrFfMRlDURHGgoJ2p8wm+NnNDoKsghfftzJnoYmKqu6vunGGjsBnCMdW/SWX+EbjxsUmZX1P70CSJEmSJOmcNmTIEAA++OADqqqq2p176623qKqqIj4+nkGDBp3w+nfffZfy8nLy8vICCkxAJysnNm/efNwxj8fDL37xC7Zt28YDDzzADTfcQHx8fNv5xsZG5s+fzwsvvEB6ejpvvPFGQJMBfyKNnJzjs+AvWbKEhQsXYrVamThxYsD9SpJ0etUb/Hkm/JU6uratQ+csx2A/SEvsDaD430iaNm5CdblObSLMU0CoOkrliomzzjliBJYlS7Et+Bx3nz7ttv2EBgt+cbudhStMrN1qYOUmI+lJPkYNdpPXy4vREMBAqh575GSCD39IvL2BnKDebFE2MEgMw8qJy5BKkiRJkiSd7zIyMrjkkktYvXo1V199NdOnTycyMpItW7awZMkSFEXh5z//ebvAQ2NjI1u2bGH+/PksWrQIRVG46aabAh67w+CE1Xr8i68XX3yRTZs28eyzz3LllVcedz40NJR7772XtLQ0HnzwQZ5//nmeeOKJgCd1jNPp5Le//S0HDhzg4MGDJCQk8Mwzz7Tb7iFJ0rmhQedEc5mI0Hc9QmqpX4lQDDjDLvEfEALLypV4kpLwpqaepplK5zWdjtYrryR05kxMGzfiys9vdzoqXHDHNU6umwjrdxhYtdnIe59ZmL9IkD/Aw6hBbmIiRZeGcoaPwlrzJdbqLxhpu5v9yh42KmsYK3q+7VGSJEmSJOlc9cwzz/CTn/yEvXv3MnPmTMC/swJg+vTpxwUe3n//ff71r3+1tbvtttuYMmVKwOMGVK3jk08+IT4+/oSBiR+aMGECKSkpfPXVVz0KTlRUVPD111+3O7Z3794TZvtsamqiqamp3TGj0UhMTEy3x5ckqetaLc24A6jUocONuWE9rtChCL1/+4a+qAh9ZSXNN98sq2FIHXLnDcCTnIzty69wDR4M+uN/ldmsMGG4h/H5HvYX61i12cDyDQaWrjOSneZl1GAP/XO86DvbJagacUROIujIXGLsDfS29WOrspnBIp8gAtu+JEmSJEmSdL6Iiopi3rx5fPrpp6xatYrGxkbi4uKYPHnyCdMv9O7dG51OR//+/bnnnnuYPHlyt8YNKDhRXV1NZmbXljVbrVaqq6u7Nalj4uLiWLt2Laqqsnr1av7v//6PP//5z9jtdh544IF2bd9++21efPHFdscGDx7MrFmzCA8/u/vWJelC19jYiCe4AV95X6LDQVGMJ70m1rsH1evGnDEFc8jRN3ofrQeLheDJ4wg2n72yjd5mNzbrye/hx8xmPdHB3686a2pq6mY/BkJC5JvfTt1xE/y/54jeuhGmXN5p05gYGDUMGppg2Tr4brWemfP1hAbD+BFw6QiIjuzg4oipUPc14Y1fMzXpp+xpLGCHdSPX2K459fckSdI5Qf7sliRJAr1ez/XXX8/1119/0rZjx45l27ZtPc4NGVBwIiEhgf3793PkyBFiY2M7bHfw4EH27dtHdnbPyu1Zrda27SVTpkwhPj6eW265hf/85z/cfffdmEzfv3m5++67ue6669pdbzT6f7HU17fi9XYjc7skSV3SIhoRZieGplDsuLtwhSBa2YbHkkyDMwZczSgtLUSu3YBj1CW0NruhuSv9nB5OdLTaAx/f6fRS7XS1/V0ITzf78eByNQd83UUlLpnQnBz08xdQ128gwmzu0mWXDIQRA2BPoX81xWff6vlsEfTK9Oem6JPlQ/ejPJqW8MsIqvoEpbycvtYBrHeup699MCGEnvr7kiTprJM/uyVJOlP0evWCeJB+qgpWBJTKfOrUqXg8HmbMmEFZWdkJ2+zZs4cZM2YghDguWNBTAwcOJCUlhZaWFkpLS9udCwkJISkpqd2H3NIhSWdGnVILdL1SRxiHCVLqcYSPadu+YV67FsXnwznq3EqEKZ27Wq+6CrW1FcviJQFdp6rQJ8vHT29y8oeHWpk02k35EZXX51j504s2Fq4w0tD0/bYiZ8R4NNWKtforhotRKCisU1ad6tuRJEmSJEm6qAW0cuLee+/lm2++oaCggCuuuIK8vDwyMzOxWq3Y7XZ2797Nzp07EUIwfPhwbr/99oAmI4Tgb3/7G5WVlfztb39Df4J9xMdWQ3i93oD6liTp9Cn31IIOQr1WwHXS9olKAR5hxBk6BAVA07CsWo07KwtfXNzpnq50gfCmpuAamId1yRIcY0YjggNfTh0eIpg6zs3k0W527tezeouBr5ab+HqFkXuvdzIg14vQWXBEXoqt+nPCnFfT3zKIbcomhokRhBF4yWxJkiRJkiTpeAGtnAgKCmLmzJlMmTIFr9fLpk2b+Oijj3j77bf56KOP2LFjB6qqcscdd/Dyyy9jMARStw0UReG7777jyy+/ZNWq459KlZaWUlRUhNVqJT09PaC+JUk6fSrctfjsFiINJ6+CYMRODIVUkguqP9ho3L0HXV0djtGjT/dUpQtM65VXgteL9ZtvetSPTgd5vbw8eKuDp2a0EBIsWLft+wC5I+JSNNWMtfor8sVIdOhYo6zs6fQlSZIkSZKkowJaOQEQGRnJP/7xDx5//HFWrlzJoUOHaGlpISQkhPT0dCZMmEBERPefJN10000888wz/O///i+5ubnEHX2KeuTIEX71q1/h9Xq555572uWbkCTp7KpTavFUxxIedPJKHfHsQVU0yrW+HEuva165El9ICO4B/U/vRKULji8mBueI4VhWrcYxbhzaKSg1HRUu6JPpZVOBAZ8GOhWE3oYzYjyWmq8JcV1NnnkIm5R15ItLiESWt5YkSZIkSeqpgIMTxyQkJBxX3/RUuOuuu1i3bh3Lli1jypQpDB48GJ/Px7Zt27Db7YwbN45HHnnklI8rSVL3CASt5mq8NQOwWU62pUMjUdlFnUjEThgAam0txt27sU+63P/4WpICZJ88GfOGjdi+WkjznXf0rDMhUBsauEQ9whZnP0oqVNKT/AmV7ZETsdR+h7X6K4Yl3cx2ZQtrlBVcJU5tfiVJkiRJkqSLUbeDEz6fj4KCAgoLC2lpaeGOO+7A4/FQWVlJSkpKtydkMBh4+eWX+eCDD5g/fz4bNmxAVVVycnKYPn06N910E6oa0G4USZJOoxaaEQYXhuYwlLDO20ZSikVp4YA2su2YZfVqAJwjR3Z0mSR1SgsLwzF2LJbFi7Ffeim+xIQuX6vY7ehLSjAUl6AvKUZfUoquqYlI4FrrFewtuob0JH/WfqEPxhExFkvtEmwxVzHYNIx16iqqfEeIoeMKVpIkSZIkSdLJdSs48c477/Dqq69SW1vbduyOO+6gtLSUq666iokTJ/L0008TFBTUrUnpdDruvPNO7rzzzm5dL0nSmVNLDQBWezCE2Tttm6TsxCWsVJPmP+D1Yl67Dne/fmjh4ad5ptKFzD7xMsyrV2P7/HOafvbAiRt5POjLyzEUF6MvLkFfUoK+urrttDc2Bk9uDvaUVMzr1jG4dhf/KbqOK8Z834UjchKWumVYaxYyOOFGtopNrFGXc61242m+Q0mSJEmSJP8igVmzZvHxxx9TWFiIz+cjOTmZqVOncv/99x+X/mDZsmW888477NixA7vdTnR0NGPGjGHGjBltKRR6qqqqim+//RZN0xg1alS380MGHJz4r//6L+bPn48QgtDQUNxuN06nE4Camho0TWPRokWUlpbywQcfYLFYujUxSZLOD5XeatBBmMcKdBycMNNEJKUUMQSBf/uGadsO1JYWHKNl+VCpZ4TVin3iZQQt+BzDwYN40tPRVVWhLy4+uiqiBH15OYrm36LhCw3Fm5KCc3g+3pRUvMlJCKu1rT/VYSfxy4VUlzpwucHkz92KZgjDGTYKc8NKrFFXMsSUz2p1OYepII6ur9iQJEmSJEkKlM/nY8aMGSxduhSr1UpeXh56vZ5t27bxwgsvsGzZMt5+++229+Cvvvoqzz33HKqqMmDAACIjI9m9ezezZ89m0aJFvPfee2RmZp5k1O9t376df/zjH2RnZ/Pkk08CsHnzZu6//34cDn/uOVVVefTRR/npT38a8P0FFJz4+uuvmTdvHjExMfzf//0fY8aM4bbbbmPLli0A5Ofn89577/GrX/2KPXv2MHPmTB588MGAJyVJ0vmjwlODzxNEhEnrtF2isguBQoXo3XbMsmoN3qgoPDk5p3ua0kXAMXYsluUrCHnjTfB6UV3+HCia2Yw3JQXHpZfiSU3Bm5KCFhbWaV/unBxsX35FL+deDpT0oW+Wr+2cPeoKzPUrsNZ+zaD46WwRG1ilLGW6dkNA89Xp9Gia3KYoSZIkSVLXzJkzh6VLl5Kbm8trr71GbKx/W2ldXR0zZsxgy5Yt/Pvf/+bXv/41Bw4c4J///CdWq5U333yTQYMGAeDxeHj66af54IMPePLJJ5k9e3aXxi4sLOTuu+/G6XS2S7Pwhz/8AbvdTlRUFJmZmWzatIm///3v5OXlkZ+fH9D9BRScmDVrFoqi8Pzzz7fd3I8NHTqUl156iRtvvJGFCxfK4IQkXeBqlRrcVTGEBXe8akLFSwJ7qCENF/7tXra6eoyFh2i59lqQeWSkU8FopGX6dKxLl+JNSsSTkoI3NRVfdHTA32PelBQ0k4kB3l3sLRrQLjihGSNwho3EXL8Sc9RUhhryWaFbxvKDKwhv7Xq1qv79+qIoxoDmJUmSJEnSxevjjz8G4Mknn2wLTABERETwxz/+kWuvvZYvvviCX//613z66af4fD7uvffedu/dDQYDTz75JAsXLmTr1q2Ul5eTmJh40rHfeustHA4HEydO5IknngBg586d7N+/H7PZzPz584mJieGrr77iscce47333gs4OBHQq7Vdu3aRkpLSYWDimP79+5OamkpxcXFAk5Ek6fwiENhN1fhqYgmyOjtsF0MhRsVJmejbdixp916EQY9zeGA/tCSpM+6BeTQ8+ggtN9yAKz8fX2xs94JfOh2erCzyfLvZV3R8FRl79BQQPiy1ixgg8jB6TBTG70cgTsFdSJIkSZIkHS88PJyMjAwGDBhw3Lm0tDTAn/8B/EGI3Nxchg0bdlxbg8FAUlJSu/Yns3btWmw2G88880xbMGPJkiUAjBkzhpiYGACmTJlCTExM2+6KQAT0is3lcnU5h0R3k2FKknT+aKIRofdgcUSjKh23S1QKsItQ6vH/INO5PcQdOIhzYB7CZjtDs5WkwHhycoh0VeE5XE9TS/tvcM0YjSs0H0vdMoxeJ2lHMmgIqqc+qLaD3iRJkiRJknrmlVde4auvvsL6gzxZx+zYsQOgLcnlww8/zGeffcbIE1TEs9vtHDhwoF37k6mqqiI1NbXd2CtXrkRRFEaNap8/LiYmhvr6+q7d1A8EFJyIj4+nqKgIu73zjPwtLS0cOHDglGX/lCTp3FSLv9JBuBbZYZsgaghTjlAm+gD+N3hxBw6i93hxjJblQ6Vzl/toLpS+7t3sO9TR6gkP1rqlJNYmY3KbOShXT0iSJEmSdIYJIXjhhRcAmDRp0knbv/baa9jtdvr37098fHyXxrDZbLjd7ra/NzY2tgVEfhwAqamp6VZhjICCExMmTMDlcvGXv/yl03ZPP/00brebcePGBTwhSZLOH4d9/jKiCfqOgxOJyi58Qkcluf4DQpC0ey9NkRF4U5LPxDQlqVt88XH4goPJ8+1mb9HxKZp8pnhcIYOx1C3HKDykH86kydZIbUj1CXqTJEmSJEk6scrKSsrKytp9NDU1dfn6v//976xfv56oqCjuv//+TtsuW7aM//znP6iqyuOPP97lMVJTUzl06FDbNpBvvvkGTdNISUkhNTW1rd2qVas4fPhwQFVAjgkoIeZPf/pTPv30U+bMmUNxcTFTp06lsbERgN27d3PgwAE++ugjNm7cSEhICPfdd1/AE5Ik6fxR4anB6wwhIVwPnuPP63ATxz6OkIUXMwChR6oIqm9g15hLiFI62QsiSWebouDJyaHf9t28XagiBPz4W9YePRVz0yaS2YG7bjDFsYUcjNtPZFM0CvL7W5IkSZKkk7v99tspLy9vd+yhhx7il7/85Umvff7553n11VcxGo3885//JCKi4+TcS5cu5eGHH8bn8/HrX/+a4cOHd3mOkyZNYsuWLdxzzz2MGTOGefPmoSgK1113HeCvGDJv3jxeeeUVFEXhqquu6nLfxwQUnIiIiOC1117jF7/4BevWrWP9+vVt56ZPnw74l5SEh4fzr3/9q10GUUmSLjx1SjWeqljionwcqTz+fDz70CteyrT2iTA9RgNHMtKIOoNzlaTu8ORkE7xpE8ENlVTVhhMb1b5krs+chCuoP8nNOygRA0g/nMWu1B1Uhx4hplFubZQkSZIk6eTef/99fD5fu2MhISGdXuP1evnTn/7E7NmzMZlM/Otf/zph8stj5s6dyx/+8Ae8Xi+/+MUveOCBBwKa4x133MGaNWtYvnw5hYWFAOTl5bUtSDh06BDPPfccAJMnT+bWW28NqH8IMDgB0LdvXz7//HM+/PBDlixZwoEDB2htbcVisZCamsr48eO57bbbOo3YSJJ0/tPQsJtq8NZkEZminSA4IUhUCmgS0TTjz95rcDiIKSqmvHcumsFwxucsSYFy5/i3I/Vz72Zv0ZjjghMArdGTiWjZQZIowFs/kEOxhRTGHSC6MVaunpAkSZIk6aS6mvfhmNbWVh555BFWrFhBSEgI//73vzsNTPzzn//k5ZdfRlEUnnjiCe65556A52gwGHj11VdZtmwZe/fuJSUlhcsuuwzD0df0GRkZjB49mquuuopp06YF3D8EGJzYsmULOTk5BAUFcf/99590P4skSReuRuoROh9mRwy6E2SvsdJAkFLPHm1M27GEvQdQNY2y3rlncKaS1H1aRDjeqCgGOXbx+aHxjB12/P4lryWVWpFMirKNUtGPjMpsdqZv5Uh4JXH1CWdh1pIkSZIkXagaGxu59957KSgoID4+nldffZWco0m8f0wIwX//938zd+5cjEYjf/3rX5k6dWqPxh83btwJc0uGhYXx+uuv96jvgBJi/v73v2fcuHE0NDT0aFBJks5/tfiTYUZoJ96cEUH50XZHk15qGol79lIXH4c9LPSMzFGSTgVPbg65zr0UHgLf8QsnACgSgzEqThLZTUxjLEGOYArjDqDRwQUXMYHAh+/kDSVJkiRJasftdvPAAw9QUFBAVlYWH374YYeBCYC//OUvzJ07l6CgIN54440eByZ+qKamho0bN7JkyRIANE2jpaWlR30GFJyorKwkMTGRsLCwHg0qSdL574jmr0gQbzhxcCJcKcMhgnHi3y8XWVaOpaWV8j5y1YR0fnHn5GD0uUhoLaak4sS/NhuJp14kkKpsRYePjMpsHCY7hyMqzvBsz11u3GxTNvGO+hovqs+yUFnAEQ6f7WlJkiRJ0nnjhRdeYOvWrcTHx/Puu+8SF9dxfqvly5czc+ZM9Ho9//nPf8jPzz8lc/juu++YPn06Y8aM4c477+QXv/gFAGVlZYwdO5a//vWveL3ebvUd0LaO2NhYamtr8fl86HTH13yXJOniUempxdMSTkKEHnC3O6egEU4FVWS0HUvavReX1UJ1asoZnqkk9YwnOxuhKPR372JfUTLpSe4TtisSQxisLiBe7MXX1IeQ1lCK4g4QV5eAGtizgAtKA/VsUzZRoGzHpbiIFXH0Ef3Zq+xit7qTBJHEYG0YmeRc1F8nSZIkSepMQ0MD7777LuAvVPH000932PbZZ5/lxRdfBCAyMpIPP/yQDz/88IRtH3zwwS6X/XzxxRd56aWXEEKgKAo6na4tkWd5eTl2u52ZM2eyb98+Xn311YBjBgEFJ37729/y2GOP8Zvf/IZHH320XT1TSZIuLrVKNZ7qWOJOkCAwmGoMipt6LQkAc3MzkaXlFA3KQ6jyzYd0fhE2G97ERAbX7+KtQ1OZPObE7epJoEHEkqpsoUL0Iu1IJtszNlMddoTYhsASXZ3vBIJSitmibqSQ/aioZItcBmpDiScRBYUx4lIKlO1sVTbyue5jgkUIA8UQ+ok8zFjO9i1IkiRJ0jll+/btOJ1OAAoKCigoKOiw7Z///Gd27NgBwJEjR1iwYEGHbW+88cYuBSfWrFnDiy++SFBQEL/5zW+YOnUqP//5z9myZQsAw4cP5y9/+Qt//vOfWb16NbNmzeKOO+4I5BYDC06sW7eOXr16sXDhQhYuXEhoaCjR0dGYTKYTtlcUhTlz5gQ0IUmSzn0+fNhNtXiqexOddnxwIvxovok6EgFI3L0PoShU9Mo+o/OUpFPFk5ND6pJlVJZ4cbnBZDxRK4VDYggD1S+JE/vRmnKxuKyURhdfNMEJDx52KzvZqmykVqnBIizki0vIE4MJIrhdWzNmhoh8BomhFLKfLepGVqhLWCNW0kf0Y5AYRgSRZ+lOJEmSJOncMnbsWPbu3dvl9rt37z6l47/99tsoisLf/vY3JkyYcNx5VVWZNm0aUVFR3H///Xz22WenNzjx3nvvtft7Q0NDp8kxFUWWUJOkC1E9daBqWOzR6HUgRPvzEUo5zSICDxYUn4+EffupSUnGZbOdnQlLUg+5c3OwLl5Mlms/B0oy6Zt14oSOtSTTJKJJUzZzWOSQXJ3KvqTdNFobCLWHndlJn0FNNLJN2cwOZSsuxUm0iGWSdiW5og/6k7zUUFHJIpcsLZcqjrBV2UiBsp3t6hZSRTqDtGGkkSHLskqSJEnSWbR161bi4uJOGJj4odGjR5OQkMCBAwcCHiOg4MT/+3//L+ABJEm68NQq/kod4Vr0cedUvIRymHL6ABBTVIzR6aJclg+VzmOejAyETscA7272FeV2GJwAhSIxmDz1a2LEATx1GRyM309pdDGhxWGdjqGqGj5f4AmkdDo9mtb5dqk6atmj7MRKEMEihGBCCCYYM5Zuv+kXCMopZYu6kYPsAyCLXAb6hpJIUrf6jSGWSeJKRovxbFe2sE3ZzCe6jwgXEQwSQ+kt+mPkhMtWJEmSJEk6jVpbW0lI6FqJ9IiICGpqagIeI6DgxHXXXRfwAJIkXXiqtWoECvHGCKD9solQjqBTfNQdzTeRtGsP9pAQ6hIvjmXt0gXKaMSTns6gil18d+j6TpvWkEaLiCBd2cIRLZvE2iRKo4txVuRi9pg7vM7n87JjZ8f7RzvSv19fFKXzN+yL1a8pVYqPO64XeoIJIYgQQkQIQQT7Axc/CGAYab9104uXPUoBW5WNVCtVmIWZIWI4eWIwIZyaMsFWbIwQoxkmRrJP2c0WZQOL1W9YJZbRTwxkoBhyysaSJEmSJOnkYmJiKCoqwuv1otd3HEZwu90UFRURHX38Q8yTCSg4IUmSBFDpqcFrjyAhUge0f9IbrpShCYUG4gmqrSOsqpp9w4eC3ObVLafzaboUGE9ODvEHvqTlsJ2mFoWQINFBS//qif7qt8SIQhw1KZREH6IsqoSsyo5rkZ8u5ZRRqhQzRruUXqIvLTTRTBPNShPNNLd9fkgppJUWfrzgwSTMBB8NWpiFhUPKQRyKg0gRzURtCr1EXwwYTsvcdejoLfrRS/SlknK2KBvZrKxns7KeTHLIEFlEiWgiiUJ/muYgSZIkSRKMGjWKOXPm8Morr/DQQw912O6ll16itbWVqVOnBjxGh8GJTz75JODOTmTatGmnpJ+L2QJ1Pi00Y8CAHj16DOiF/0/Dsb//4E/DD85/38rQtoRXknqqVqnBXXXiSh0RlNNEDD6MJO7ei0+nozI76yzM8sJwOp+mS4Fx5+Zg+/JL+rj3sO9QP4b26zhoVEUGrSKMNGUzVe4biG6MpSKylPTDmejEmS3FvU5diUVYyRODMGAkiCDiSGi/6Ono5z58tNLyg+DFsUBGMy00cUQ5TAJJDPINI4mUM5YHQkEhgSQSRBLNoulofostHFD9icEUoRBGOFHEECWi/R/EEEqYzFUhSZIkSafAAw88wIIFC3jppZcoLy/nyiuvbKse0tTUxIEDB/jwww9ZsGABJpOJ++67L+AxOgxO/P73vz8lCS1lcKJnBIIgEYxHcePFi51WPHjxKh68ePHiwYMHoXT0BO97NhHEfdqDJ01OJkmd8eLFYarDU9Of6PT2wQkdLkKo5hCDUb1e4g4UciQjDa/5xBV9JOl84k1ORjObGajtYkvRwE6DE6BSJvqSq67CLJpJrk6lOuwIh8MrSKxLPmNzPkwFxUoRo7XxGLqQq0GHjhBC/VsmThC8OBcEE8IobTxZ9eNQgutoNFRTo1RRq1RTzRH2K3vg6KIhgzAQSRRRIoYootv+tGA9uzchSZIkSeeZpKQkXnjhBR577DE+/vjjdosZhg8fDoAQApPJxF//+lfS09MDHqPDd6l9+vQ5YXCioaGB8vLytgnm5uYSEhKC0+nk4MGD7Nu3D0VRyMvL63LCDKljCgoTxOUnfWHow4fXH7bAw/eBi2N/1im1LFO/Y7eyk/5i4BmZu3RhqqcWFIG5NRbjj1ZRh1OBogjqtETCDh9B7/VyJCPwH0ySdE7S6fBkZTHgwC5mF+kQovPdSvVHS+mGU4GjNZdgewil0cUk1HUvWWR3rFVXYRZm8sTgMzLe6VZZrbJll54tuwxU1alYzcGMHBTP2KEewkL8vyg9uKmlhhqlmhqqqFGqOajsY6eyra0fq7ARfXSVRZxIIJMcdJzZFS2SJEmSdL4ZM2YMn376Ka+//jpLly6lsrKy7VxERATjxo3j/vvvJzMzs1v9dxicmD9//nHHqquruemmm4iPj+cvf/lLW4TkhwoKCvjVr35FcXExf/vb37o1KSlwuqP/6+j5dKrIYLfYyWZlPf1EnlzmKnVbjVINQLgWedy5CKUcn9DTSCyZ5VvQVJWGuJgzPUVJOm08OdmE79yJoaGWqjoLsZEdR45bCcctzIQrFVSKXiRXp7IrdQd1QbVEtkSd9rlWcZgi5QCXaGPRCxNlR1RUFfR6gUHP0Q+BXg+6czg9SVWtwpZdBjbv1nO4WoeiCLJSfIwa4qaoVMfitUaWrDMyqI+XCflukuONxJFAnDj6gET4VyHaaW0LVtRQTY1SzVZlEz51PTYRxEAxhAFikNz+KEmSJEmdSExM5A9/+AN/+MMfaG1tpaWlBavVSnBwcI/7Dmh9/9///neOHDnC/Pnz6dWr1wnb9O3bl5dffpmrrrqKv/3tb7zwwgs9nqTUcwoKg0U+C9UFFHGQDGQOAKl7akQNwqeSYIoA2pdTDKecBuIQ6AivqKQxJhrNIJPUSRcOd66/JG5f9272FeUTG+nppLVCPQmEUwEIYhviOZCwl9Lo4jMSnFinrsIkTAwUQ5jzlYnVWzre1qGq/oDFDwMXer3A2O6Y/8+ocI2kOI2kOB8RoeK05LqtbfAHJLbs0lN2xL+iISPZy/WTnAzs7W1LRjo+30Ntg8KyDUbWbjWwaaeBrBQv44e76ZvtQz06NwUFG0HYCCJVZPgPCtDQKKGITep6VqnLWCdW01f0Z5AYRjgRp/7GJEmSJOk853Q6Wbx4MVOnTsVms2Gz2QCYPXs2LpeLadOmERIS0q2+AwpOLFu2jKysrA4DE8dkZGSQk5PDunXrujUp6RTTvFjqFjPQ18rK+GA2q+vJ0GRwQuqeSm8NnsYo4iPbvyMx0kqQUk+lloPB6SS4to7CIQPPziQl6TTxxcbiCwlhiNjFN0UjGTO0s+AE1IsEYtVCzKIZpwghsSaFovgDtJpaTus8a6jigLKP4dooDpdbWbPFQP4AD32zvHi84PUqeLz86HPlxOd84HAqNHsVXB6Frbv1aML/37/FLEiK9ZEYp5EU6yM5TiMmUkPtxkqMhiaFLbv9WzaKK/wBidQEH9MmOhnU29u2bePHIsME0y93MWWMizVbDSzfYOT1OVaiwjXG57vJH+DB1EFcRkUljUzStExqqGKzsoGdyja2KZvJJJvBWj6JJMvVhpIkSZIErF69mscee4ympiaGDBlCbGxs27mvvvqKdevW8corr/Dcc88xcuTIgPsPKDjhdDrx+XwnbwjY7XaEOIcyaF2kDK37CKr8AL3Lvx9oSOR0lpk2U8VhYog7y7OTzke1Sg2e6qTjKnWE489FU08S4RWHUYC6hPizMENJOo0UBU92Nr237+bfh1R8Gm1P50+kAf/WgnAqqCSExNpkDsUepDSqhBEcvzXyVFmnrMYgjAzUhvHy12aCbYLrJznpSW5axdtE2KF/4NaMFDsHU9jUi+KGJEqrg1i1yYDH648AGPSChBj/yoqko0GL+BgNwwlecTS1+IMdW3brKSz1N0iK9XH1BBeD+niIDPvR6wihoXMfQe8oQe8qx2uMwx0yEKGzYjHDpSM8jMv3sH2PniXrjMz92syXy0xcMtjNmCGeDgMcAFHEMElcySgxjm3KZrYpmzmo20+MiGOIyCdb9JJ5KSTpAiPLdUtS123fvp0HHngAr9dLTk4OHk/7BzRTp07F6XSydetWZsyYwbx588jIyAhojICCExkZGRQUFLBp0yaGDBnSYbvvvvuOkpIShg0bFtBkpOMJAeu26clI8RET0fVgj+JtIujwPMyNa/EZImlK/AnBFe+QX13FmkQjm5T1TBHXnMaZSxciD26cxnrc1YOJyWgfnIhQyvEIE81EklhxAK/BQHP06V+6Lklnmjs3h5BNm4iyV1BaGUFqJ7mf/XknLG15J0xeE3H1CVRGlOMUTixdqKARqFpq2KfsZpgYybZtIZRU6rjjGkePAhMIHyFlr6NzV6O3ZpHr+4re4fMhHLRMCy5TOqXuPA419eJQfTxlVWY2FRhYtdkfuVFVQVzU99tBdCps3aPnQLEOIRTion1MHesPSMQcy+MhfOiclegdJRicxegdpeidpSjC7T+NgoJAVL6H29YHV+hQ3MF56HQWBvXxMrC3l0PlKkvWGflujZHFa40M7uNlfL6b5PjjyyAfYyOIS8RYhomR7Fb8uZq+Uj9jhVjCIDGUfmIgZsw9+GJKknSukOW6JanrXnvtNbxeL/feey+/+93vjjt/0003cdNNN/Hss8/y+uuv85///Ie//vWvAY0RUHDilltu4b//+7+ZMWMGTzzxBFOnTsVo/P4/zNbWVubPn8/f//53FEXh7rvvDmgy0vE0AV8tN+HyKNw73UFu+klWrggNc/1KbFUfo2guWqOmYI+eCqoRY+suwho20C9+KlvVbYwW4wmme/uBpItTLbUAmFpi2i+TFoJwyqknAVAJr6ikPj4O0Z213ZJ0jvPk5ADQz72LvUXjOw1OfJ93ohx/2SWF5JpUKiPLKfDtYCijTvn81iur0WOgtz2f55YYyUj2nqTs6cnZjnyCsXUvTYn34Aob+f0KBnsRBkcRekcR2b7Z5Ng0sIEvIxqXOZ3Dnr4UNeVQUh9D2WEDuw7qWL/dn4cmJkJj0ig3g/p4iY90oXeV+1dEVJSid5agd5ahCP+8hWrCa07GET4aryUFrzkFnykOvaMEU9MmTE0bMZXvQCh63EH9cIUOxRXUn/QkM+lJTmrqFZZvMLJ2m4GNHeSl+DEDBgaIQfQXAyniIJvV9axQl7BWrKSvyGOQGEoY4T36ukqSJEnS+WLTpk1ERETwm9/8ptN2jz76KHPmzGH16tUBjxFQcOKGG25g9erVfPnllzzxxBM89dRTJCYmYrVaaW1tpby8HJ/PhxCCn/zkJ0ycODHgCUnt6VR4+C47r31k4ZVZFqZPcnW4x1nnKCW48n0MjiLc1hxaEm7DZ/p+Wb0jfBzmhjWMaFDYEiHYomxkrLj0TN2KdAGoPVqpI0KLbndc56nBorRQrA3C3NyMtamZ0r69z8YUJem008LD8cZEM9Sxi1lFlzHpJPEFf96Jg1hEEw5CCXaEENYcwdagLQzWRqJy6oJ49dSxV9nFYJHP0uXh2B0K109y9ShppbFpC9bab3CEj/UHJgAUFZ8pHp8pHlf4Jf5jmguDoxi9owiDvQiTfR8Z3vVkGEDE6vGmJuM2Z1ArcrFr4SRYDmJwlWBoKkFXVYGCfzWDplrxWpJxREz4PhBhjEFxudEdPoyu+AjmI5vQVVfjGD2K1l430Bo7Hb2jCFPjRkxNmzE1b0UoBtzB/XGGDCUqtD/TJwmmjPXnpVh2NC9FdITGZSPdjMjzdPg1UlDIIIsMLYsqjrBZWc92ZTPblE1kksNgLZ8EEmVeCkmSJOmC1tzcTG5uLjpd51sc9Xo9ycnJ7N27N+AxAgpOADz33HMMGzaM119/nfLycg4dOtTufHZ2Ng8//DCXX355wJORTiwyTPDo3Xbe+cTC3K/NHK5RmX65i2PfF4rPibXqMyx1ixG6IJoS78UVOpwfv9LyWtLwmFOIq1lLdngeO5StDBejMHVYgFSS2qsRNQivnnhLKPD9k1hDq/+HTx2JRJT785vUy3wT0gXMk51D1tqNlJQKXO7O29YfzTsRRgUOQgFIqU5le/AWDrCPHDpPMh2I9cpqVHQkVI1g/iYDowd7SIrreAvDyehcRwgun4nHkkZL3E2dN1ZNeGw5eGw5OI4d8tQfDVYUoncUYW1Yjk185z/ZBJouGK8lBVdU/7ZAhHCb0R85gq7wCPrDZZgPb/IHJRob24YSOh3CaMRw4AD1j/8GLTISrzUTrzWT1rgbMdgP+ldTNG3G1LQZoRhxBQ/AGDqUS/P7MS7fw7Y9epasNfLhF2YqqlSuu9zVaf4QgBhiuUJczWgxnq3KJrYrWzig20uciGecNpEEkrr9tZYkSZKkc1lMTAylpaX4fL5OAxSaplFeXk5YWFjAYwQcnFAUhVtvvZVbb72VQ4cOUVxcTHNzMyEhIaSnp5OcnBzwJKSTM5vg/hsdLFhiYvFaI1W1KvdeZyfMs5mgwx+hehtxho+hNXYaQmc7cSeKgjNiHMEV7zLcfgX7gnZToGxjsMg/szcjnbcO+6rx1EUTF9n+uLFlL05hw0EomRXbcFkttIaFnp1JStIZ4M7NwbJqFemuQxwsje20rZ0wXG15J/wriqKaYggRoWxRN5CjnZrgRCMN7FZ2kieG8OVXkVgtginjXN3vUHMRUvoKKDqakn4GauBlgTVDOG5DOO6Qwf4DwofeWY7qacDnCUOtcaIrPoL+8GEsR1ahPzwfteX7SibCaMQbG4snJxtHbBy+uFh8sXH4IiNQ6+sJf/ZZQma+TcMjD4P+6EsaRcVjy8Zjy6Yl7mYM9v1tKyrMTRvRVDPu4AGMSB7KoNw+fLIkiKXrjNgdCrdd5WwL/CMECA+K5kTxOVE1p/9zzUWk5mSiT2Wc1psd5sOssVUzV/c+U7RryT6FwSZJkiRJOleMGDGC+fPn8/LLL/PQQw912O6tt96ivr6eK6+8MuAxAg5O/FBaWhppaWk96UIKgKrCtZe5iIvyMftLM8+/7uHx4Z9hjQqmKfnneK3pJ+3DGToM2+G5pNfuINGWzBZlIwPF0FO6rFi6cNUqNbirMtpX6hAaRvt+DpMIAsIrDlOblHDcyh1JupB4srIQikJ/7y72FSWR2WnxI4UGEgingmN5JxQUBmqDWK5bymEqiaPnK402KGtQUTHuHsXBUj03T3Vis3SzMyEIrngPnauSxtSH0YwRPZ4fgL6sAsvyFRh3FqDa7W3HNYsZX2wcrn79jgYgYvHGxaGFhdFRXVItKormW28j9M03sX36Ga3XTz++kaLiseXiseXSEn8Lhta9mBo3YWregrlxPZpq4a6sLCKdw5m37VJ8dft4aMRrmGjxByI4+aqTccAQnY530+P43PIx48RlMugvSZIkXXDuvvtuFixYwEsvvURRURHTp08nOzsbq9WKw+HgwIEDfPrpp3z22Wfo9Xruv//+gMfodnCitbWVlpYWNE3rtGRoQkKnmcKkQGkeJsR/Ttaog/xj3SM8tfwv3HO9m1xrFyt5qCacYSOx1C9jqPdnfGr4kv3KHnJFn9M7b+m858KJy9CEpzqGuKzvX7DrnWWovlbqRRJBdfUYnU7qEuV/99KFTdhseJOSGFK/i38duvIkwYnj804A9BX9WCtWs0XZ0OPqSU00UqBsp7c3j4VfR5Mc72NE3onzE3WFuW4p5sb1tMZcgyeoh78ffD5M27djWbYcQ1ERmsmEa2Ae3qRkfLGx+OJi0UJCuhXQdOcNwD5uLNZly/FkZuIemNdxY0WHJ6gPnqA+tIjbMLTsxty0Eb2jlGv6LMZmdPLuhin8ddXjPHT5IixmHUI1I3Rm/5+qGaGaTnhM9dRxb/GzzE0wsyzkO5q1JsaKy2QeCkmSJOmCkZOTw5/+9Cf+53/+hy+++IIvv/zyuDZCCPR6PX/+85/p3Tvw/HMBBye+/fZbnn/+eQ4cOHDStoqisGvXroAnJZ2YoWU3QZUfoHdXkZY+hF/1bubVj6288qGt00SZP+aMGIu1bjF9astZHhvBJmU9OaK3fBEldaqWGgAMLTHtShIaWvcA/nwTceWHAKhPOMk7NUm6AHhyckhevITaw14cTgMWc8c/g4/lnQj/Qd4JEyb6igFsUzYzRkzA1oP8PxuVtQA0rx1HU4vKT25o7WjBwUnp7QcJOjIHV1B/7FFTuj0npaUFy+o1mFeuRNfYiC8qipbrrsM5PB9h6e6SjuO1XnMNhkOHCJ41i/qkRLSoLpQwVnR4gvvhCe7XdmhIBiiJTt79LIFnFt3Jz291EGzrWuBfM0bRmvprbi56loWxGmsiN9CsNXOFuBp9zxapSpIkSdI5Y9q0aeTl5fHmm2+ybNkyqqqq2s6Fh4czevRofvKTn9CrV/e2OAb0G3P16tX88pe/7HSlxA91tZ3UOdXTiO3wHMxNG/AZo2lIfQRPUB8ioNNEmR3xmeJx23Kx1q9gUPQNLNZ9QzmlJJFyRu5HOj/VKv7gRIRo/8Lf2LoHrzEWt9NGeEUlraGhuGwd5D2RpAuIOzcH63ff0duzj4qaMDKTqjts6887YSVcKadCfP8kYaAYyhZlI9uVzYwUI7s1jxZa2KlsI90xgKXLohme5yYtsXtJMBVvEyGlr6Lpw2lOug+UwCMc+rIyzMuXY960GcXrxZ2bS8tNN+Hu07vDLRo9otfTdPfdhP/tWULemknDo4+AIfD8GACD+3oxmxy8Oc/CC+9YefA2OxGhXQ1QRNOc9iumHHqOMI/gq7g9tIoWrtVuwMypC8ZIkiRJ0tmUnp7On//8ZwDcbjf19fVYLBZCQkJ63HdAwYnXX38dIQTDhg3j0UcfJT09HbPZ3ONJSJ0QPsIKn0b1tdAafRX2qCvaJSU7YaLM6Q6sJ3kd5AgfR2jZqwxsVlkdamGTup4kTQYnpI7VUI3mNhBnDgGOPiHWvBha9+MIG47S6iP88BEqcrLO6jwl6UzxpKcj9HoGartYVT2+0+AEKNSTQNgP8k4AhBFOBtlsV7YwjKHdmscmdQMaGqVfj8dogKsnnKR8SEeEj5Cy1/3btNJ/h9BZu36tz4dxxw4sy5djPFiIMBpxjhiBY8xofHGnfyWVFhlJ8+23E/r66wR98iktN97Q7b76ZPl48DYHr8228PzbVmbc5iA2qmvBHp8plqa0XzHq0HMEezXmJVbwofoO12k3E0pYt+ckSZIkSecio9FIbGznicEDEVBwYvv27dhsNl555RVs8snomaHoaIm7CZ85CZ/pxP/wP06U+feZNn56k53YyI6f9rhDBuLThxBct5K8kMGsU1ZRTy3hRHZ4jXRxO+ytwVMdQ/wPFk4YHEUowo3blktoVTU6r5e6RFlCVLpIGI140tPJq9jNnJppCNF52oQGkUCcegCLaMTxgzeqg7VhzNXtZ4+yBwJMTuzSu9iubCe2oT9rd8Rw/SRnl7ci/JjtyCcYW/fSlHgPPkvXKm8pLS2Y16zFsnIluoYGfJGRtEy7Fufw4QhrAMGNU8Ddvx/2CROwLlmCJzMD1+DB3e4rM9nHL++08/IsC8+/a+HBWxwkx3c1QBFHQ+pjDDj0d4K9jbyXqudD9R2maTcSewoSn0qSJEnS6fb+++8DcO211xIUFNTuWCBuv/32gNoHFJzw+XxkZGTIwMQZ5g4d0qV2w/O8REU4eGOumX/MtHHPdQ56ZfhO3FjR4Qwfg7X6Swa7prHRvJbNygYuE1ecwplLF5I6tQZ3dU67J4iG1j0IFDy2bCIqdiAUhYYz8JRUks4VnpwcYvd/gc7ipqnVQmiQo8O2de3yToS1HU8ihSgRwxZ1M3kMCSj/T0n0ITR8HPjsUuJjfIwa0r0kmMamLVhrv8ERPhZX2Mm3l+jKy7EsX4F50yYUjwd3Tg4tN9yAu2+f07N1o4tar74KQ1ERQR/O9ifcjInudl+JsRoP32Xn5Q+s/Os9Kz+9yUF2age/U3/EZ06gIe1R0g/9nQcK63g7PY456vtcqU0jHbm6TJIkSTq3/fnPf0ZRFC655JK24MSxY4E4rcGJ9PR0ysrKAhpAOrMyk338+l47r31k4T8fWjpNlOkMH421+ksi6zfQO64fBcoOLhFjsXBmn3ZJ5z4Hdtz6FjzVscRlfv/i3Ni6B68lFaGzEl5eSVNUJF6T8SzOVJLOLHdONrYvoI97D+XV4Z0GJxyEHs07UUHFDyokKSgMFsP4Rv2C+qA6Ilq6toLNrXNTHlVC0JE+FBXH8Ms77Oi6ERfQuY4QXD4TjyWNlribOm1r3LkTy5IlGA8cRBgMOIcNwzF2DL74c2RFgE5H0z13E/7M3wiZ+Rb1jz4Kxu7/TIqJEDxyl38FxSuzLNwz3UH/nK4GKJJoTH2U2EP/4OcHDzMzM41P1blcJq6gvxjY7TlJkiRJ0uk2bNgwACw/SGB97NjpFFBw4tZbb+Wpp57igw8+4Lbbbjtdc5J6KDJMtEuUWVmtcv2k4xNlaoYI3MF5mOtXMTj6cXYatrFN2cwIMfrsTFw6Zx2r1KFvisZ2LHblc6K3F+KImoTidBJSXUNxXr+OO5GkC5A3ORnNbGaQtoMvq6+lT3plJ639eSfC2/JOfC9X9GGFWExp9KEuBydKow/hU33s/3Qig/t6yOriU/12NBchpa+AoqMp6Wftchq1m7ndTtDceZg3bcIXEUHLtdfiHHHmt250hRYeTvMddxD66qsEffwxLTff3KP+wkIED99p5z+zrbw518KtVznJH+Dt0rVeSwqNaY8QeuifPHCgmPcye/Gt7iuatSZGijGySpYkSZJ0Tnr33Xe7dOxUCyg4ceONN7J9+3aefvppDhw4wNixY4mNjcXQSVbsrCy5fLFHNI3QF19EmMy4+/TB3ac3WuTJX7j+OFFmdZ3KPdMd2H6UKNMRMQ5T81YSmopJj8hkm7KJoWKELH0mtVOr+BP9RWjfL5E22vejoOG29cJwoBBVCOoSEs7WFCXp7NDp8GRl0m//bt6ouRtN63xXQ/0P8k78kB49A0Qe60LWYje2YnV3vn3So/NQGl2MKMxBq4vh2ptaA5+7EARXvIfOVUlj6sNoxogTNjMcPEjwe++hNjTSOnUq9omXcdKyUGeZu28f7JddhvW77/BkZuEa2rXtkR2xWWHGbXbemGvh/QUW7E4n4/O7toXGa0mjMfURQov/yd379zIvazDr9Kto1pqYKKag49z+WkqSJJ1rBIItygYSRBJxyNeeZ8rvf/97EhMTue+++05bmoeA3oEOPppcyufzMWvWLGbNmtVpe0VR2LVrV/dnJ4Gi4MnOwbxhA6ajX0tvbAzu3n1w9+mDJzMD9Cf+Z/xxoswX3rHy2D12zKbv23hsvfAZo7HUL2Nw2E3M081it7JTLjmV2qmhBs1lIs4aBPgrARha9yAUPR5rJrZ9n+LT6WiM7f7+bkk6X7lzswjfWUCYq56axmBiwps7bFv/g7wTPzZAG8h6dR2l0cXklvc57vwPlUYfwqfzUbFoMleMthMWEngSTHPdUsyN62mNuRZP0AnG8/mwLlyIddG3aJGRNDzyMN60tIDHOVtar5yKoaiI4Nmz8SYn4ethNnGzCX52s4O3PzHz8SIzdofClLHuTpOgHuO1ptOY+kvCil/gxgNbCc4awxr9BlpEM1dp0zFhOnknkiRJEgBrlZWsVVcySbuSOCGDE2fK4sWL0ev1zJgx47SNEdDuVLvdjt1uRwjRpQ9N616ddekHFAX7lCuoe+q/qfuvJ2m57jq08HAsK1YQ9u9/E/nkfxHy+huYV69Gra8/YRfD87z87BYHR2pVPvzCjPjha1hFxRE+DoP9IGlOHTEils3KegTdy/YuXZiO+KpxV8USF/X994WxdQ8eayaoRoz7DtAQF4s4x5+mStLp4M72rxDs695FRXVYp20dhOI8mnfix2zYiG2IpzKiHI+u46fyXtVDaVQx7v25WFtDGZfvDHjOevtBgo7MwRU8wF+i+kd0VdWE/fN5bN8swpk/jPrHf3NeBSYAf/6Ju+9CGAyEvDUT3N0ssfoDej3cM93J8AEevl5pYt43JrQu/rr0WrNoTHkIvaeOKQdXMclzKWWUMEd9jxY6DmhJkiRJ39ut7GStupI+Wn/6iP5nezoXFY/HQ1xcHLrT+Ho/oJUTe/bsOV3zkE5GUfDFxOCIicExfhy4XBj378e4axfGXbsx7dgBgDc+Hnef3v5VFenpbUtvc9N9XDXezYIlJtKTfYwb9v0LX2fYSGxVn2CtW85gSz4L1QUc4qDMKC4B/qVzdWoNnqp+xEX7A46Ktxm9s4zWmGtRGxvRHz5CXX7Plk1L0vnKFxuD02phiNjOe9V5DMwp7aS1QsPRvBONQvDjlAPJ1akcjqigMqKMlOr0E/ZQGl2CV++lZulEJvQ/iF4X2FMjxdtESOmraPpwmhPvBeUHzymEwLxuHUHz5iP0ehrvvQf3wIEB9X8u0cLCaLrzDkL/8ypB8+bTcustPe5Tp8KtVzmxWgRL1hmxOxVuv8rZpZ0uHlsOjSm/ILTkRUYXfkNQ+vUsMHx1tNToTUQhV59JkiR1pIwSFilfkiRSmCimyLw9Z9j48eNZtGgR27dvZ8CAAadlDJlY4HxlMuHu1w93v34gBLojR9oCFZYlS7F+txjNbMbTKxdX7z54evfispGhFJWpfPKtiZR4H+lJ/jeaQh+EK3QYpsZ15MZey0pDMJvU9aRrMjghgZ1WPDoH7uoY4rL93zPG1r0A/nwTBfsBqEs4R7L1S9KZpijUJ8TT69A+qmuD8HhVDPqOVw4eyzuhc1ehmZPbnQtxhBLWEk5pVAnJ1WnHvfDyql5Kog7h2J9DvDCRFFMPgey3FT5Cyl5H9bVSn/47hO77hJZKayvBsz/CtG0b7uxsmu+4HS0srOt9n6M8vXtjv3witm8W4cnKxHUKso0rin/bpM0i+HypCYdT4d7pDowdp+D6fj5BvWhMmUFoyUvkHZqPNf0OPtYv4CP1Xa7WrieZ1B7PT5Ik6UJTTy0L1HmEEMrV2nSZr+cs+NWvfkVlZSV33nknl19+OYMGDSI6OhqTqeOtiePGjQtoDBmcuBAoCr64OBxxcTguvRTF6cSwdx/G3UdXVWzdBoArL4/bb72HZ98MYuZ8C4//xE6Qzb8e1RE+DnPDGqyNGxkUOZQV6hKqOEwMcWfzzqRzwLFKHbqmaIKs/u8XQ+seNNWM15KKZd8aNJuVlsgTJ9OTpItBXWIC8QcKSfRUcqQu9GjQ4MTqSQTAYN+P60fBCfCvntiRvpXq0CpiGtvnSSiPKsFr8NC0Yjzj+hYGPE/bkU8wtu6lKfEefJbvxzbs20fwe++jtrTQcs01OCaM7zyz53nGfsUVGAoLCf5oDt7kZHxxPf/dpihw+Sg3FrNg7kITL71v5f4bHQTbTr7PwxPUh6bkBwkpfZnsQ7O4NfU+5hs+5WN1NldoV5ND7x7PT5Ik6ULhwM4n6hwUVKZpN2HGcvKLpFNu0qRJAAgh+OKLL/jiiy86bd+d/JMBBSeeeOKJgDpXFIWnn346oGuknhNmM+68AbjzBvhXVVRUYFm1Csuq1YSOK+S+67P5x0wrb39q5sFbHKiqP5u4x5yMpW4Z/cJ/y1plFZuU9UwR15zt25HOspofVOo4lvjN2LoHjy0XUDHs3effc9+VrHCSdIGqT/C/2R3gLeBQdd9OgxMOQnAKG8bW/bgiLj3ufHRjLGaXhdLoQ+2CEz7FR1FUMY6D2fSyQbAtsFwTxqYtWGu/wRE+FlfYSP9BrxfbF19iWbIEX3Q0DT+9H2/y8QGT855OR/NddxH+zN8IeWsm9b96DDp50tNVSlMTEz27GB5WyOzifP4xM48HbnYQF3XynFvu4H40JT9ASOl/SC5+i1tSf8Ynhs/5Qv0Eh7CTJ+RWOUmSJC9ePlPn0UwTN2i3EUb42Z7SRSs+/vSvkg4oOPHxxx+jKApCnPipgPKDNydCCBmcOBcoCr7ERFqmTcO0ZSvm5StIujeTG65w8eEXZhauMDJ1nBsUBWfEeIIr3iXIXk6/oDy2KZsYLcYTTMjZvotTxouHBhpopIFGpZ5GGlBQ6CX6Eku83Lt2ArXUoDksxNusgBvVXYPOXY0j4lJ0VVXoGhtpzZFbgKSLm8tmozU0hEG+HayuHg0UddJaoZ4EYlr3gxDHBfYUFJJqUjiQuJcmSyMhjlAAyiJL8RlduNaPYkBOWUDz07mOEFw+E48ljZa4m/zHDh8m+N33MJSV4Rh1CS3TpoHRGFC/5xMtNJSmu+4i9OWXCZ47l+bbbw+8EyHQl5dj3LkTY8EuDCUlAAQZDDzq3cA76l388+0x3He9g5w030m7cwfn0ZT0U0JKXyW25DWuT5nBF4aFLFa/oVVrZaQYI38vncdUVcPn8wZ8nU6nR9MunJVLktRdAsE3yhdUKGVM1aaRQNLZntJFbfHixad9jICCE/fee2+H55xOJ9XV1WzYsIGmpibuv/9+Bp7HSbQuOEYjzhHDsSxdRmtDAyMHhlFUquPrlSbSEn30yfLhDB2G7fBcLPVLGWS7ga3KRrYoGxkrjn+yd64SCBw4aKSehqPBh0Ya2j5vVVratTcKIz40tqgbiRBR9BX96S36YSPoLN3BuadKq8FdFUt8tD8oaWz1J8Z123ph2LDP/3lONhw+fNbmKEnngrrEeLL2HKSx0YzDacBi7rjiRoNIIN63H537CD7T8VsMEuqSKIo7QGl0MX1LBuBTfBRGFuM4lM6QMA96XWDVsKxVnwHQlPQzUPSYV64k6JNPEUYjjfffj7t/v8Bu9jzlyc3BPnkStoVf487MwjVi+Mkvcrsx7tuPscAfkNA1NiIUBW9qCq1XXomrb198UZGEvvkWd+95m9BYBy/PmsTNU52MyDv5G1N3yCCaku4npOx1Ikv+w9WpM/hWt5h16irsWiuXismogRVXk84RPp+XHTsLAr6uf7++KMqFGyiUpK5ao6xgr7qLUdp4coXc7nYxCCg48bvf/e6kbVpaWnjkkUd4//33ueGGG7o1KZ/Px6xZs/j4448pLCzE5/ORnJzM1KlTuf/++ztNuiF1zDFqFJYlSzGvWo39yqnccIWT0sMq735m4fGftBIRasIZNgJL/XLCvDeRbejFTmUrI8QojOdYDXY3bg5TQb1Sd3QVRAON+AMQbqV9ubggEUwoYaSKdMJEOKGEESrCCCMcMxbcuNin7KFA2c4KdQkrxVLSyKSv1p8Msi/qhDsCQZ1SjbtqYNsyZUPrHnz6EHymeGx7v8IXGYkWFSmDE9JFrz4hnuRde8nyFFJRE0ZmUnXHbY8msTS07j1hcMLgMxBfl0h5ZClZFbmU26rRLA4M24aRmlIb0LxUTwOmps04Ii9DuAyEzHwdU0EB7l69aLr9NkTIhbM6rivskydjKCwieO5cvCkp+E6QzFdtaMBYUICxYBfGfftQPB40kwlPr1609uuLu3dvRHBwu2saf3o/Ie+8y7RtHxGaaOe1BdOorXczZZwb9SSLH9yhQ2jGR3DZm4QX/5vLU3+BFRsb1DU4hIMp2jXoZZowSZIuIgXKdtapq+in5TFMjDjuvNMFBj1dqpQkdZ/b7ea7775jx44dtLa2Eh8fz7hx4+jd+/QEi075b7qgoCD++te/MmHCBP71r3/x3HPPBXS9z+djxowZLF26FKvVSl5eHnq9nm3btvHCCy+wbNky3n77bSwWmQglUFpUFO4+fbCsXo198iSMBj33Xe/g2TdtvDXPwiN32XFGjMNatwRz/SqGROezT93NTmUbg0X+WZ27HTsVlFKu+D+qOIJQ/E/ydULnDzgQRqJI8QceRBihhBNKKHo6T59uwkx/MZD+YiB11LJL2cEuZQdFugOYhYVeog99xQCiib3olte20IxX58JTHeuv1CEExta9uG29QNMwHNiPS66QkiQA6uPjEIpCnm8nW2su6TQ44SAEnz4MQ+tenBEnzmSdXJ1KWXQJpdGHKA6qxlmSwiWR7oDTu5jrVwACb1USER89g+Jw0DL9OhxjxlxQSS+7TFVpuvNOwv/2N0JmvkX9r38NBgP60lJ/QGJnAYbycgB8kZE4Ro7E3a8vnsxM0Hfyskmvp+nuuwiaPZsJ6z4nLMXB31beSk29ym1XOzGc5BWXKzQfBASXv0lYyb8ZnfIQVmwsU7/lY3U212jXY8J8Cr8QkiRJ56ZSivlW+YpkkcalYvJxr79LK1VefN/KFWNcTBje8SpFqWc2bNjAb3/7Ww7/6AHk888/z+WXX87TTz9NUNCpXW1+WsLwUVFRZGVlsXbt2oCvnTNnDkuXLiU3N5fXXnuN2Fh/MrC6ujpmzJjBli1b+Pe//82vf/3rUz3ti4Jj7BhMLxdg2roV19ChREcIbrvKyZvzLHz8rYkbr4jHbc3BUr+CuKjJJIpktigbGSiGnrFlpQJBE43+QARlVCil1Cn+J4U6oSOOBIaJkXA4lThdFOkRNtRTlIwxgkhGi/FcIsZSQhEFyg52KFvZqm4iSsTQV/Snl+iHFevJO7sA1OJ/c6U0xBASJNC5KlC9TXhsvdCXlqI6nHhycs7yLCXp3OA1mWiKimBg606+qJ56onQSP6DgsWVjbNlzwrwTAFa3jajGaIpjikCBiHXjCI8ILAkmmhdz/XK8JSmELPwQb3w8TTMexJcQQPnRC5AICab5rjsJfenfhD3/ArqmJtTmZoSi4MlIp+Waq3H37YsvNjawZL86HS233IIwmxm07Dv+nG7nfwruo77Jyv03ONoqZHXEFZYPCILL3yK05EUGpzyEFStfK58zR32fadrNBMlth5IkXcDqqGWBOp8wwrlKu+64FcxHalRe/tCCxSQY1DvwnC5S15SVlfHAAw/gcDhQFIXU1FSCg4MpKSmhsbGRRYsW0drayhtvvHFKxz1tawQbGxtpaWk5ecMf+fjjjwF48skn2wITABEREfzxj3/k2muv5YsvvpDBiW7y5OTgjYnGsnwFrqFDAcjr5eXSEW4WrzWSnuTjkuTxhJa9irGlgCHB+Xymm8d+ZQ+5os9pmZNAUEvN0WCEf2VEi9IMgEmYSCCJ3lp/EkUyscShR8/WPXremudfPRNi08hO85GT5iUn3UdE6MnLuJ2MikoamaSJTJzCwV5lNwXKdpap37FCLCGdLPpq/Ukj84Le9lGr+MuIRmhRKEr7fBPmDZv9n8vghCS1qU9IIHl7Ab5WQVOrhdAgR4dt3dZszI0b0LkP4zMdv7VA08C8rx8MW4KnIpEhIYHlmQAwNW9B52mCLUF4EhNpeOxRMHS+muxi4cnOpvXqq7F+9x3u3BzcfY9u17DZetaxqtJ63XUIi4XMhV/zXIaTJyt/xt9nWvnZLXZiI08WoBiOP0Axk9CSF+mV8hAW9UYWqPOZrb7LdO1mwpGlmyVJuvDYsfOx+hG6tpKh7VeL1TUq/HuWBUWBGbfZCQvp+Wt+6cTeeustHA4H/fr145lnniEjI6Pt3Keffsqf/vQnVq9ezcaNGxl69D3lqXBaghNvv/02FRUV5HTjTUt4eDgZGRkMGDDguHNpaWkAVFVV9XSKFy9VxTFmDMHz5qMvLsGbmgLAVRNcFJerzP7STOI9g+mrD8Fct5SM4IcIE+FsUtaTI3qfkm0NPnxUcbhti0Y5ZbgU/9NAmwgiUSSTKJJIFMlEEn3cio2GJoXZX5pJjvMxaoiHfYd07D2kY1OB/wV3VLjmD1Sk+chO8xFk7dkPLjMW8sRg8sRgaqhml7KD3cpODur2YRVWeol+9BX9iSKmR+Oci2qoRmsNIiHYDLj8+SaM0WjGSAz79uFJTEQEBYFwn7QvSboY1CXEk7ZtB708+yivDus8OGHLBo7lnfg+OFHbaGN/aSwHy2Jwug1Eun30VS0YLYH/LLPULcHbEIn+SD32GyfKwMSPOC67FMdlpyHps6JgnzIFYbYQ98kn/D39ef7b+Qv+OdPGfTc4yE7tvJKHK8y/v/pYgCI15SFu4DY+UT9itvou12k3EcvpL+kmSZJ0pnjx8Jk6l1ZauFG7jVDC2p1vblV4+QMrTpfCL++wE3OSQK/UM2vWrMFgMPDSSy+1WzAAcO2119LY2MjTTz/NihUrzl5w4pFHHunwnBACt9tNUVERJSUlKIrCddddF/CEXnnllQ7P7dixA4C4uOOTh0ld58rPx/b5F1hWrqA51V9KTafC3dc5+dsbVt6cb+OpK8cT0bQAnbuWwaZ8FqtfU04ZSSR3a8xGGjikFFKsFFHKobakleEigmyRS8LRYEQoYZ0GQDQB739uxuuFO6c5iI0UjBzoQQiorFbZd0jHviI9mwoMrN7iz3SdGOMjO92/siIrxYepBwmwo4hmrLiUUWIcxRRSoO5gq7KRzep6xmmXnfXcHKdatajBdSSWuGgNhA9D6z5cocPA7cZQWIhj7NhTNpYsuSZdCBpjY/DpdAwWO/iu+gr6pFd22FYzROIzhGNo3ccRwwQ2FZhZsWEwdU1BqIpGSlwtWUlVJFls6NTAX4TpHSUY7AfxFPVCGCpwDR7Uk1uTusExYTzCbCZ09myeSf47f7Y8zMsfBHHLlU7yB3T+8659gOIlSPkFN3Mn89XZzFE/4GptOqmkn4G7kCRJOr0Egq+VL6hUyrnKdx3xJLY773DCK7Ms1DcpPHibg6S4wFcSSoE5fPgwqampxwUmjpk4cSJPP/00hYWFp3TcgIITX3/9dZfbTpo0ibvuuivgCXVECMELL7zQ1rfUfcJsxjVsGOa1a2m59lr/k28gNFhw93VOXnrfwpvrrubXvRZgqV9Bn9irWC2Ws1ldR5LWteCEBzellFCsFHJIKaRBqQcgRISSK/qQoqWTSDI2Als+u3yDgX1Fem6ax/N+3AAA3UNJREFU4my3NFZRICFGIyFGY3y+B58GJRUq+w7p2XdIx4qNBpauM6KqgrREHzlp/o/URB/6buzK0AmVbJeNvs1WvK3wabSdlcGLSRFpF8wKCn+ljho81UOJi9LQO4pRNSduW28MhYUoPh/u3FO3pUOWXJMuBJpeR2NsDP3rd/FezS1ogg4rNbi9CiuPXMWavcnsqLIhhEJ0eBMj++8nI7Eas7Fne2nNdUsRPiO6nUdwDRiAsF4cuXLONc6RI9DMZkLefZc/xj3LP+Mf5f0F4dTUu5gytvMEp+0DFP+GlBnczJ18rM7mE/UjrhDXyPJ6kiSd91Ypy9in7maMNoFserU75/bAa3MsVFSr3H+jg8z/n733Do+jStO376rOQd3KOUfnnHMAB0ywCSYYTA5jTJ5vZ3Z35jdhd4fdgRkYhmFMDh7AJjoCjtjY4JwlJ0Ur59y5u+r7o22BsSSrZTnXfV261Oo6dc6panV31XPe93kTOo88U+gZXC5Xp2aXp0SL5ubmHh03IHFi4cKFnW5XqVRYLBaGDBnS4+VF/vrXv7Jz507Cw8N56KGHztje3Nx8xsnRarVERl4ZN4o9jWP8OAxbt6Lftg3Htde2PZ+R5OP6SW5Wfmvia8t9zFR/iibiegYKQ9ghfE8DdYQQdkZ/MjK1VFMkFHJCKKCcUnyCD7WsJp5EBkpDSZZTCSG026kh5dUiKzfq6JfhZczgzp15VSKkxEukxLuZPs7/wVZQovJHVhSpWbNFyzdbBLQamUG9vdxxnfPspYgkLxp7LtqWg+haDqLy+P0YPPpEbqo18Q+Dl2/Ez7mTR64IH4pmmvCJHtzV0URlSGhtRwDwmLIwHt+IrFLh+Un+mYKCgp/6uBjSy/eiN9moawwiIqSlbZssQ2W9lbySSD5cE4LTNZMwQy3Xjqhn6CCR6opDPTIHwWtD37QTT3UmWmcBztFnlmFTuHC4Bw+iWafF8s67POf5M+9nPc2arVHUNojceX3nlTz8AoVMUNn7bQLFbdzNCvEzvhKW4cDGILnnQmoVFBQULiTZwgF2idvoLw1iqDzytG0+H7z3hYGCYhX3zHbSN10RJi4UPp8PVSc3R6e2eb09a0rao+LE+eJvf/sbb7zxBlqtlpdffpnQ0DONoN5//31effXV054bMmQIH3/8MSEh52hudSUSEQR9e2Petg3z7TedViT49hugvAaW7JlKpmELGZlHmBI6gT2NOzhs3M9s02wAbJKNPE8euZ5ccj25tMj+C/BoVTRjNGPI0GSQpE5CI5x7jrPbAy++A0YDPD5fjfVn9eW7QlwsjD/5mddqhyN5sP+wwLfbNZhNGh6c244pu6cF6vZD3V6oPwg+B4gaCO4H4TdB2GA0ulCCPa3cfOQ3LI5v5IDue6abZp3zMV9sat2l0ApCUySZaWaEA3lgTiI8Jgby8yEznYj4cMAvDpqMgUcv6PUaLJagHuujp/C2uLs5FzURQT+uTl9p50WhfX7+GjlSE2HXXvq6j1LTGENynIvGFh1HiyI4WhROs02PRu1jaD8vU4fZ6F3zFGLmvTQHjcLW1EOvdfFmkD1oc2WICCd41KCrs2zopcTEkRAZjPrFV3jgyF9Imvgc72yJotWh4ZkHwNJZEY6IaRCkR3v0dSIq34B+z/GI+BBLW5fyrWcd6L1cY7gGoYcqV13t9NTnrvL5felzObxGVd4qzKIZk3jl3c/kefLY0PINGeoM5gbdgkr48X5EkmDRR5CTB/ffCteOM1zEmSpcKM5btY6ewOv18sc//pGlS5ei0+n4+9//zvDhw9tte++9957hcaHV+j9sGhpseL1KbtLP0Y4eg/Wtt2n6dhvugQNP23brNCgqNfG3Xc/wh/BFSOIAegl92ePci+xQUSwUUkUlCKCX9STKKYwmlSQ5BbMvCE76IzbiBAIsfdcOX67TUVKh5ZHb7bidPmrOvUuSY/w/KlHL+h90WExOJo9wo3JXtkVHqO35CMj41BbcQUNxBw3Abe4N4skvsmYAvygTY7mbofXv813I90TbU4kl/twneREpEEpAhBBvOLXVdYQ3HccROhl7YQVhJ4qxz5yBvcZ/7LLswWYP3BTT6fTgcvVcHz2FE1U35+Klxulq+/tKOy8K7fPz18hmCsKj1TKUg3xQ0J/8UivVDVZAJjaikcGZRSTF1DJkUG8ENMhNIbiqDuLUDO2Z11qWCC1Zg8+TivZoIbbrZmKvs/XAkSqcM+GxqB9/HOs/FzF53f9imL6Q17em8pu/yDx6+1kM3lSD0cXOJ6j8Azx7/0xT4i+4VrwBUdDwrfNbauz1TJVnXLCy31cyPfW5q3x+X/pcyq+RhMQO4Xu2C1sxYGCKNIPMn6U8XM7UUsNS8UNCCONa1/XUu+xt22QZvlirY+tuLbMmuhiU5aam5iJO9jyiVovKQvpP6FCcKC8v75EBYrtZS91ms/HUU0+xZcsWLBYLr732WofCBIDFYsFisXR3mlcl7r598YWEYNiy9QxxwmiAB25x8NJ7Ft7YMouHk8oYYhxBjnCQ3cJ2oolltDyeZCmVSKLP68XQ0QIVm3ZqGT/UfV7CuWZNdFBbZWP5+hBSnR8wLHwTAB59AvaI63AHDcCrTwSh82P0mLKYUjWIAs9R1qg+Zx6/QMvl64VQRw1Si4XoYC0aezaC7MVj6oUmNw9BlpUSogoKHSGKNMRE07fyCM2tBsQgmWG9C0iPr8Zk+NlFsCDgMWaibc32X42d89ASqsZ9qDx1eApTkYVKHMMHIZ+loo5iLHvh8CYk0PjkE1hf+yejV79M8M2/4OWtvXjpfRP3zXGQmezr0IfCFTIGkAkqX4y15J80JSzgGnEmJsnEDvEHHLKD66QbUdNxxKKMjBsXdmzYsGPHhkOwtf1lF2zYsaFDxzXSTIJQrq0UFC40Nlr5WlxBiXCCXlIfGoR6Vqu+JE/qzWR5GgYubw8hGzaWi5+iRs1s6TZ0PysZ+s0WLd/t1jJppJtrxyoV4a4mOhQnpk6des6dC4LA4cOHA96vqamJ+++/n5ycHGJiYnjjjTe6VZZU4SyIIo5xYzGvXIWqvAJf7OllyeKjJW69toUl3wxg3bd7uGZWHPdKD2PAdEbd4fOFzQ4frdQTFebjxqmus+8QIIa6DRirV/Jkb4n/qvt/vLb9Xv6/m7OITE5G0gReR94bMYc5lf/Lu/E2tkprmMINPT7nC0WNXIuzKprocAmt7SgyIm5jOubjK5B0OryJiRd7igoKlywNcTFknSjm3hEbUEVrOzU9dJsy0TdtR+WqPOdxfT4vFH+FUzLCrgLq42I4UFYOZZ0vOFzpxrKXWjUgX3Q0jU89SfA/XqP3p6/ymzse5uWdA3jtIyNmk0RqvI/UBB+p8T7io6XTPJFcIWMBTgoUr9GUsIAx4kQMkolNwjq+EJcyQB7sFxrwCw2nBIdTz/mEdoR+GQwYMWLCiJFyylgifsAc6XbCiejxc6CgoNA+JyjkG3EFbtxMk2bRVx6AT/axW9jOdmErJUIx10gzSSPjYk81YGRkmmniK3EZdmzcJt2NBetpbTbt1PDNFh0jB3iYPdXV6fenwvnl+PHjZy1w0VkbQRB4//33AxqzQ3FC7oEVnO704Xa7eeSRR8jJySE9PZ23335bKR16HnGOHo3pmzUYtm6hde7cM7aPGqKiJPcwq/YPJi6zmd4ZZ5phdhXB24qu5QDa5n0gqGiJvQdZ3XGSrSzD0q/1tNoFHrndgfbcrStOw1C7DnPVZ7jNfXDFTeS+ZCt/fU/Dq9+M59n77Vg03XgPiBpCQx9kbO2rbI3IJtXXh2TSenbiFwAJiQaxFk9NBlHhPjStR/EaU0GlR3v8OJ6MDM7uIKqgcPVSf1LsTWospCwmq9O2HpN/u9Z+HAg/p3FVrirChFLKy3oRaztB7siOIw6vJi7FakBSWBiNTz2J9bV/kvjhIv5j3n38wGAKSlUUlKg4eMz/padRyyTF+doEi+Q4H4SMRQDMPxEoBovDMGLkG2ElZWIJAKIsYsCICRNGTITJEX7xQT4pQsimNjHCgPG0KMgaqvhS/IRPxH9xo3QL8SiCtILC+URCYruwlR3C94QSzi3SXW3CoAoVI+WxpMjprBFXsUL1GX2k/kySrzkj6uBS4ZQQUU0lVUIlVUIF1VTiFJwgww3SLURz+sLozoNqvlynZ0CWh9tnORVh4iLT0tLCzp07u92mOz5IHYoTGzZs6HAnWZa55ppr6N+/Py+//HLAg3bGK6+8wv79+4mJiWHx4sXtml8q9ByyyYRzyGD0u3Zju/76M0rNCQLcOtNLyQclLF4ewy8fdhNq7fpNu+hpQtuyD13zPjS24whI+DRhiN4mgov+SmPy08jq9kNGdxxUc+CohhunuHq8nrGhbiPmqs9wmofQGjEP2WgmGHh4roNXFht561MDC++2d0sQ8eljGWObwnHn96zTfMk9PI6ey8vEp4kGJMGHpzqK6FQb6qpi7BGzEOvqUNXW4pgw/mJPUUHhksZuteA0Ggkpr6Csd+fihKQNx6cJQ2PL41zFCUPDFiRZRHNcwqPTUZPUtfLPChcHyWr1p3gsep3wxe8wed5djLnRX3mjqUWg8KRQUVCiYv0PWiRZQEAmNlIiJWEKWaExDLS/hZV/0pTwC7LEPsTJCbhwYcKEDn23K2RFEMUd0ny+FJfyhbiEGdKNV1S+u4LCpUQrrXxzMo2jj9SfKfI0NO2kBkcSxV3SfWwXtrJL2EaxUMQ06TqSuLjV09oXIqpwCg7AL5SGE0G6nEWUHEOcnEDYz77vDh1T8/EqPZnJXubPdqJSMg0vKherEEaH4kRcXNxZd9ZqtV1q11UaGxtZvHgxAKGhofzpT3/qsO2LL77YY+Ne7TjHj8ewYyf6nTtxTJp0xnbRkszC8Yv43donePdzA0/Nt6PuxEpVdNeia96HrmUfansBAjJebRT28Om4LUPw6hPQ2I5iLX6N4MIXaUp+BkkTcloftQ0CX6zVk57oZfLIns0109d9i7lyKS7jQMTVPkJP/DdNjy/Am5hIQozE3Tc6eedzAx+v0jN/dvdUW0/oFOZUHOKtOAffSsuZKdzRo8dwvqnFXyZVqo8kWn0EARmPqRfag8cBcGd1frOloHDVIwjUx8UQUVyK6PUhqTuPNPKYMtG2HAJGQjdvJgWfE33jDqqdKUQWlVHWKxNZiXC65JFNJpoeX4DlzTexLP4X9tIybDdcjzVIxaDeXgb19qejuNxQVOYXKgpLVew6pGGreyDwd8IMtaRHVZCQmUxqopXoCKlHLuwtWLlduofl4mesFr/EJl/LYKVsqYJCj/JjGoenLY2jDVkiuOgv+NRWWmPmIatNqFAxVp5ImpzBGnEVX6iW0l8azAR5Mlp0532+MjItNFPFSRFCqKSKytOEiDAiSJcziZSjiZKjCScSdSd1GHKLVLz3pZ6EGIkHb3V0Wl5Z4cJwyYkTF4ODBw/idPrLMOTk5JCT03EIpiJO9BzehAQ8KSnot2zFMWHCmeXmBAFrYj8eG/xPXtr5LK9+aOSemxyEBf8YQaFyVaJt3oeueS8aZ7G/X3089ogbcFkG49OfbozqMfemMekprMV/J7jwRRqTn0HS+hVUnwSLlxsQBZh3o7NHq9/p678jqHIJLvMA5C0WdMd2I5nNWP+5iMaFC/HFxTKwl5cbJrtY+a2OyDCJmRO6IY4IIuaI+5lc8yLrowpJ9WWTRb+eO5DziBcvecIxAEKkcPSOr5FFHR5DCvrjP+CzWPBFRV3kWSooXPpUZqQRm5tP3NFjlPTr02lbtzETfeM2TNRjo3vpc7qmHYiSE1eeFVEqpzzr8stHvlqR9XqaHnsM8/LlGL/9Fk1hAc333ov0k+hRnRayUnxkpfj9InwSlFeJFJaqKMr3cLwshh1Ffsd3jVomJkIiLspHXJREXJREbKQPfTfuW/QYuEW6g6/FFWwS19EqtTBOntTtiAwFBQU/P0/juFWac0Y0gdpRgMaehwbQOApojn8IrzEdgGhimSfdzw/Cd+wRdnJCKGS6NOu8pGC10kKBkEeBkEcFZeckRPyc4nKRNz81EB4i8ejt9m59Tl1t+Hw+Pv74Y7788ksKCgrw+XwkJCRw3XXX8dBDD6HTnX4SCwsL+fvf/86ePXtobGwkMTGR22+/nbvuugvxEiszfkmJExMmTODYsWMXexpXJY7x47B8sBjt0aO4+5x5Ee0MHsHQ+M94VP8V7++YyQtvmbjz2jJGx2xG17wPtctvtuYxpNAadTMuyxAkbecGWl5TOk3Jz2A98TeCi16kKekZfLoo1m7VUlSm4t7ZjoBSSM6GvmErQRUf4jL3x5uTjGnXOmwzZuAcMZzgV/5O8Guv0fjkE/iiopg62k1Vncg3W/wCxdC+gRupSZpgBmtnc8y2ko2G1cTJSZi5dOuWy8jkk8tmcQPNQiPuQ8OJCVajaT2C25gBiGiP5+Lu3QslCVBB4ew0xMZQHxtD8v5DlGdl4NN0nCfmMflNn0Mo7544IcsY6r/Fo08g9HglzWGhtIYpaZGXFRoNrbfeijs9naCPlxDywou03HUn7v79222uEiEhRiIhRmLCcDO6ui248r8h2zaVPPckyqp1HDiqZdv+Hy88w0Mk4qN8xEb5hYv4KAlrkHzWj3Q1GmZJc9gkrGO3uJ1WqYVp8ixUKJE5ClcGXtFLs7GRJlMTTcZGmo1N6D16IhujiWqMxuDu2eoYrbTytbicUqGYvtIAJsvXtpvGoW/ahSxoaEp6gqCyDwgu/Av2yBuwh88AQUSNhgnyVNLkTNaIq/hU9SGDpWGMlSeh6aRqz9mQkamhmgIhlwIhlyrBb9hskYNJkzOIkqOJkmMCFiJ+TmWtyKIlBkwGmV/c6cB0eRchuSD4fD4WLFjApk2bMBqNDBw4ELVazYEDB3jllVfYvHkz77//PgaDP6X86NGjzJs3j9bWVoYMGUL//v3ZsWMH//Vf/8X+/fsvuQX/S0qcULh4uAYOxGdZjn7L1nbFCUQdzuDRTJA/JvkmG29vGMY7q1LIT4zjrlFFED0et2XwGekZZ8NrSKYx+VmCi17GWvQi+zX/ztqtiQzt52FINwSBjtA1/IC5/F+4zX1xVQzBsuYTnCNGYJ8xHQSBpscXEPzK37H+wy9QSOHh3D7TSV2DwEcr9YQF20mOC9z3wmsZxg1VB3nTUME6+VNmC/dfkqtNddSySVxHsVBEmBzOja47eeXL/gwZ34jaXYUzZDyqigrE1lalhKiCQgDkDxvM8BVfkZB9hKLBAzps5/edCCXEXU6p3P7NaGdo7MdRuypoFWYRVLeRY2NGnsu0FS4i7kGDaIiPx/Lue1jfehv7pInYbriBTvMpAVfYePSCzOSKD5nMUoj3G0vXO0MpakrmRFMKJ5qTKC5NZP/RyLb9zDobiSFVJITUkBhaR0JYPVEhrYi6YByhU5FVfrM9EZHJ8jTMUhDfi5uxyzaul25GdwHCyBUUehIZmQbqqRDKKBdKKMoqoFXf6s+ok8HkNBPeEo5NZyM/9jj5sccJsluIbIwisjEao9t0TuN3msZx2kR96Jr24AoagMeURUPabzCXf4ipejka21Fa4h5E0vgrXcSRwD3Sg2wVNrFP3E2RXMA0aRaxxHd5Xl68lFJ8UpDIo0VoBhliiGOsNJFUOYMwwnvsOra+SeCfHxkQRVhwl51gS9cXJAVvMxrHCTyGZGT1pbvwdz749NNP2bRpE1lZWbz55ptEnYxmrq+vZ8GCBezbt4/XXnuN5557DlmW+bd/+zdaW1v585//zE033dTW9r777mPlypVce+21TJ8+/WIe0mko4oSCH7Ua55jRGNesRaypQYo4M+rBGToRQ/0mEt3L+fX0XD4/Opdv9k7kSOsE5s92kKDpnmmlT59AY8ov0ea+xuKvDQQHebhtes+VDdU1bieo/AM8pl7Y7VOxLn0bd2YmLbfPbYsA8EVG0rhgAcGvvkrwP/5B4xNPog4N4YFbnfz1XSNvfmrgufvt3Yrk0IffxfTq51kVXcUh7w4GCKN67NjOFRdOtgtb2S/sQYOGSdI1DJCHUFbtV9vjzEUAuH/iN+FRxAkFhS7THBlBTWI8iYeyKe2ThVfX8Y2c25hBsPsAIBOo74Sh7lsklQnxkB2fSqQyLeXcJq5wUZHCw2l85mlMy5dj3LQZTWGhP80jrPOoGmfoBLz6OFSuSgTZiyC50cseesleekvNCPJekHbidMuU1YdQXBdGcX0EJQ2RbDw+BI/P/9mvFj30CT/MU2P/B3fCrbiDBgIgIDBCHoNJMrNe+JpPxQ+ZLc3FTMeVtxQULjYuXFRSToVQ5v+hHJfgTyPXyjrMniBSGqOx2oOx2K1ofD9GHDg0DqqDK6kOriQ/Npf82FzMjiAcQguZ9CUkgEg3fxrHFnYIPxDWQRrHT9HYjiH6WnBZ/T4vsspAS/yDeBp7Ya5YQkj+f9ESdx/uIH/asAYtk+VppPkyWSuu5hPxXwyVRzJaHt9hdIMDO4VCPvlCLicoxCO4UcsakkhhlDSOFDkdE+cmxrRHi03gtY+MuNwCT9xjJyK0k+trWUb01PnTW+y5aGx5qN3+SI6W6Ntxhk3p8fldynz55ZcA/Md//EebMAF+v8bf//733HTTTaxevZrnnnuO77//nmPHjjFixIg2YeJU29/97nfcddddLF68WBEnFC5NnGPGYFy7DsPWrdjmzDlju08XQ0Pa/0PSWJFVJmakQFpvB4tX6HnpPSM3THExcYQHsRuCqk8Xwzv5f6TGZuY/J7xAkDQTL+d+ca1r2klQ2Xt4TJm0qucQ/O5r+KKiaH7g/jNWoXyxMTT94jGs//gH1n/8g6Ynn8BstfLI7Q5efs/IG0sNPH1v4LlwskpPL9M9HGv5gO9Mm0iQMwnh4oZby8gcFg6xVfgWO3b6yYMYK0/EiD+errLWHwacqDuIpDLj08ehOf4V3qhIpODgizhzBYXLj4Khgxn55UoSD+ZQMHxIh+08pgwMTTswy/W0BnDBK3rq0bbsxxF8Dfq9e6hOTupUBFG4TFCrsd1yC570dII+/vjHNI8BHUfgAHiNaXiNZy9hHZUCUcCpYrM+yUlNnZvSKpHichWbdw1k2dEbuFN+DZdlCK3Rd7St0vaVB2CSTawSv2Sp+AFzpNsJ7aZXioJCT3IqKqJcKKXipCBRR01bVEQY4WTIWcTIccTIcYTIQWQXHO6wP4PHQFJNCkk1KTg1DqqDq6i2VvKD6nt+4HvC5Qgy5F5kyr07fQ+00sLX4oqfpHFMO2vaha5pN5Kox23+STSdIOAMGYfHkIql9C2sxX/HHnYttsjZIPqvaxNJ5h7pIb4TNrBb3E6hnMd06XqiiGk7PwVCLvlCLhWUIQsyJtlML7kvqVI6iSShPoeUkM6wOaCyVsXna3Q0NgssuMtBXNTPFjdlCZWr0i9EnBQkVJ4GACTRiMeYhlM/DDHbgdeSztX20RMSEkJqaioD2vkuSE5OBqC6uhqALVu2AHDNNdec0Xbo0KGEhYWxZ88eWltbMZsvDZFZEScU2pCsVlyDBqLfsQPbdddBOxe3Pze2zEj28auHbHy8Ws+y9XqOFai56wYnFnNgEQYHjqrZnm3g2pGNZEWXI5x4iebEhW152N1B17SboNJ38BgzaLHcTfDL//Cbjj36CLKh/dKe3oQEmh57DOtr/8T62j9pfGIh0eFm7rvZwetLDLy/zMDDtzkCNun0GdOZUTuQNw1HWCcv4VbxsdPqyV9IKijjW3EdVUIFMXIcs6W5RJ2sM11ZI7L3sJpdhzRo1DJx4k7cpizwSWjz83GOVELFFRQCpTUslMrUZBJyjlDatzduY/ufP35vFwimPCBxwtDwPQC+skhEu4PyzPRzn7TCJYN74EAa4uKwvPc+1rffwT5xArYbbzxrmkegqESIjpCIjpAY1s+LwyWwOnsKg/t6yWr5kJDWI9iibsYZMg4EkWTSuE2axzLxE5aKH3CTdFtAIeQKCj2JDx/HhMPsFXZRI1QBoJP1xBBLptyLGCmWaGLRoT9tP5mum57rPQYSa5JJrEkmuV8ieWIBucJRtolb2MYWwuQIMuQsMuXep0VEnKCAr8WVePAwXbqePl1J3ZM86Jr34g4aBOKZQoFPH0tD6q8xV36GsW4dGnsuzfEPtfm96dBxrXwd6b4s1olf8bH4Pplyb6qEChoF/41+hBzFCHkMqVIGUUT3WLqGLEOrXaCyVqSyRqSqVvQ/rhVpsfmvfVWizMNzHaQm+ED2oXYU/xgZYc9D9Nn8x6m24jGmYw/LwGPKwKeJRr9jF6bVqxFsNryRaXgTet4A9FJm0aJFHW47dOgQANHR0QDk5eUBkNlB1HNKSgp1dXXk5+czcODAHp5p91DECYXTcIwfj37vPvS7d+McO7ZL+5iM8OCtTr7f62PZeh3/95aRu29w0jvN16X9m1oElnylJyHax4zJKhqlX2ItegnriVdoSnwcj7l3wMehbd5LUOnbeI1pNEc+SPA/3kBwOv1+EiGd+2J4k5NpfuRhrIte95tkLlxIr1Qjt0x38ek3epZv0DHn2sDTTtRhs7m+5jifxTSxx/Mtw8WpAfdxLthoZauwicPiIUyymRnSDfSS+1JdJ7LmsIa9R9RU1qgQkElL8nHblGq0Uj0tpploik4guN24MxX3fwWF7lAwdBCRhSdIOnCI3NEj2m0jaUNxyEGECF33nRDxYmj4AXfQQHSbc/CFBNMQG9OTU1e4BJDCw2l8+ilMK1Zg3PwdmoJCmu+7Fym845Dwc2X2VCc5eSY+2HYNz96RhqXyQ4IqPkTftIOW2Lvx6WKIIobbpfl8KS7lM/FjZkmzSUP5nlC4cDiwc1DYxwFhLzahlVA5nMnSNBLkJEIJO28+X0EEMUQezhB5OK20kCscI1c4ynZhK9vFrYTK/ggNHz52C9sJI5xZZ0nj+Cna1hxEyYHTOrzjRqKW1ti7cJt7EVT2ASH5/01r7N24frJPCmnMlx5ik7CePOEYcSQwRBpOipyOBes5nQNZhuZWoU14+KkQYXP8uACn18lEh0v0SfcSHS4RE+okKbiIcI6gKcpD4yhAkPzX1V5tJK6ggXiMfjFC0oS3pWBr8vIJ+uIlNGVleFJSaH3sUbwJCed0DFcSsizzyiuvADBt2jTgxwiKiHbS9X/6fG1t7QWYYdfoUJyYOrXzGydBEMjOzu60nSAIrF+/vvuzU7jgeFNS8MTHY9iyFeeYMV2uyiAIMG6oh9QEHx8s07NoiZFJI9zcMNnV6eKOJMOHK/V4PHDPbAdqFUiqYBpTniO46G9Yi1+lOeFR3EGdh7H+FG3zfiwlb+I1JNMUtwDL2x+gqqik6ZGH8cV3bVXHk55O00MPYn3jTayLFtG0YAHjhkJVncimnVoiwyTGDvF0eU4ACCqSrQ/Qv/Ef/GDdSZKvD5HC+b+J8OFjv7Cb7cJWvHgZJo0ivWEs2TlmVh5WU1btFyRSE3zcMs3JoN5eLGYZff0eqPD7Tei370YWBDzpyoqsgkJ3cFitVGakEX/kGMX9++Iyt5/D20AsERTRVd+JSAoQfa04haFYjn+MfdpUpZrOlYpaje3mm/1pHh+dTPO4807cg87PapfJCHOucfGvFQa25MQzbsgz6Bq3Ya76jJD8/8IePhN7+AyCxRBul+azXPyEleLnTJGnM0AefF7mpKBwinrq2Cvs4ohwCK/gJUlOYZpvFkmkXHDjcTNBDJaHMVgeRiut5J0UKnYI34MA/aSBTJKvDah6hq5pN5LK3KUFOrdlCA36RCylb2MpfQtH61FaY24H0V/9Q4+BGfINyPL1XT43Hi/Y7AI2h4DdefL3yb9rGwQqa1VU1Yo4XD/2Z9TLREf4GNjLS1S45BcighsJV59A4ypG5SxF7SxB7a6GGpAR8OnjcAaPxm3MxGtMb0sd+ylifT2mFSvQ79uPLziY5nvn4xo8+Ir7rquoqMDnO31h12KxYLFYurT/X//6V3bu3El4eDgPPfQQAA6Hv+SrXq9vd59Tz9vt9i6N0dTUhNXaNVHL5XLx8ssv86tf/apL7U/R4W1jWVlZlwbtrJ1whf3TXBUIAs7x4wj6eAma/PyAb0ZjIyWevd/Oig06Nu3UkndCxfw5DqLC2k/z+G6XhmOFam6b4Tytjay20Jj8LNYTf8NS/E+a4x/CbR161vG1LQexlL6B15BEU+ITmD5dgfboMVruuANP78AiMDy9etH8wP1Y3n4Hyxtv0PToo8y+BmrqRT77Rkd4iNRWb76r+HRRTLFPosj7PWtZyh3CwnMqwXQ2TlDAJnE99UIdce40zAdnsGNvNJ9V+su/Jcf5mHOtk0G9vGe4JGtbj+LThCJpI9Aez8WbmIhsVGo8KSh0l8LBA4nOKyBl3wGOjh/TbpsGOZZY8RhmuY7WLqywxQvZeLVRqLPrAXCMHA7l5T06b4VLC/eAAf40j/ffx/ruuzjGj6d19k09nuYBMKyfl50Hvaz6Vkf/TC/WkDG4g/phrvwUU80qdE27aY29G6Mpg1ulu1gtLmOD+A2tUguj5fGXZHUqhcsXGZkSTrBX3EmhkI9KVtFb7sdgaTjhdF6+/kJhxswgeSiD5KHYaKVVshElRp19x58iudC1HMAZPAqErpXrlbThNKb8ElP1Cgy1a9A48mmOfxifPg6X2x/h0GJTYXPgFxocQtvvnz62nfzxeDt+75qN/vSvof08RJ8UIaLCvFg1NWhcJWicxaidJaicJagqmtv282nC8RoScQWPxqtPxGNMRVZ1cl3pcmHcsBHjxo0A2GbMwD51CmjPLLl6JTBv3rwz7qsXLlzIE088cdZ9//a3v/HGG2+g1Wp5+eWXCQ31e9uJJ/PQO7onl2X5tN9nY/78+bz//vsEn8V/7ocffuB3v/sdpaWlPSdOPP/88wF1pHDl4BwyBNPyFRi+29KtlXKtBm6d4SIr1cvHq/S8+LaJm6e5GDXQc5rIWV4tsnKjjn4Z3najEGS1iabkZ7AW/x1L6Zu0yB5cwR1XutC0ZGMpeR2vLp6mpCcxrN+KYft2bNOm4RzdvQoZ7n79aJl/D0Hvf4D1rbdpeuRh7psDL71v5N0vDDxzn61D4aUjxODJ3FB7iI+i7Wxzr2a86qaz7xQgjTTwnbiBfCEXrSMU+bu7+X6Hv0RsYoyPm6b6IyQ6rD4iS2jsx3AFDUZwuVCfOIH9mgubhqKgcKXhDDJT1iuTuCPHODGgX7ttGvD7+oRQflZxwkIVVqGalpBbMe7chicjAyk0RBEnrgKksDAan3wS08qVGDdtRl1U1LNpHi4XCAKCVsttM5383xsmvlin4/6bnchqCy3xD+K0jiSo4iOCi17EETIeW9TN3MitbBC+YYf4Pa1SC1PlGajo2s2VgkJHePG2+UnUCtUYZSOjpHEMlIdgPA+VJHqKA3tDWPp1DHqdjNkoE2SSMRslgkynHp/8bZIJMvp/Gw0yhpYDCLL7tPSMnyPJYLcLNNsEmltP/Whpbr2DlsZZ2BvqaHRYaHAbcHnav90TRf94JoOMUS8TYpWIiwbTqec6+K1VeVG5KlCfFCE0zhJUpaWIkr8CioyITxeLx9wXhz4B78kfWdW+39IZyDK6vXsxrViJqrER55DB2G640f/9dgXz4Ycfths50Rler5c//vGPLF26FJ1Ox9///neGD//x/8Z4clHR6XS2u7/L5Tqt3dk4duwY8+fP57333msTQH5KU1MTzz//PMuXL0eWZYKCAi/z2qE4Maedag0KVwlaLc7RozB8uwmxoeGsHg0d0T/TR8JDdv61Qs+S1XqOFaiYe50To94fLvbBcj16vcwds5wdRmbJKgONiU9iLXmNoLL3EGSv34zrZ2haD2Mt+SdeXQxNyU+h3ZuD6auvcA4fhv26md2a/ylcgweDx4Plw4+wvPMuPPgAj8x18Nd3jbyx1Miz99kwBRJQIAhEhzzAiPoX2RWSQ4qvP/FC6jnNEfwrClVUku05SrZ2F7JXRf3mGTTvGEN8hMANk10M7uMhLPjsYoraWYzos+Mx9UKTl4cgSUoJUQWFHqBo0ABij+WSunc/jB19xnYXQdhlC8FCOSVy5+ls8UIOXlmDrzocVX09tutnnadZK1ySqNXY5szBk55B0Ecf+dM87rgD9+BBne/ncqFqaEBsbEJsbETV1IjY2IjY0IiqsRGxqQnRbkcyGGh8+ikio6OZPs7N6s06cnI99M3wXzx7gvpRb/odpuqVGOrWo205QGv0HVxjmYGZILaLW7HJrcyS5qDlylzpVDi/2LFzUNjLAWEvdsFGmBzBtdJ19JL7nteo057A5oCVm3TER/tIS/DRYhNosQvUNogUlgnY7AKyfObFryjImHUjsep6YQiJwnxSxPB4oMUm0nRSiGixCUjSmfvrtDJWcwhBJjOJpjwGq/disprRxwzEHKTBbPxRZNBp28mM8DlReZsQf/rjaUL0NCM6mhC9jajc1Qiy/3NAFnV4dfG4gkedFCES8epi2jXx7Arq4mLMX3yJprAQT3w8LfPvwZN29upDVwIxMYGlettsNp566im2bNmCxWLhtddeO02YAIiMjOTIkSPU1taS1s55rKmpATr2pPg5gwYNYv/+/W0CRfhPBPHVq1fzpz/9ifr6emRZZsaMGfzHf/xHQMcEiiGmQgc4xo7FsPFb9N//gP0cLniDLTIL7nKwYZuWrzZrOVFu4p6bnBw4pqaiWsUjt9sJMp3lZlmlpylxIZaS1wkqXwyS+7SaxprWo1iLX8Oni6Yp6WnU+WUEfbwEd0YGLXfc0SM5aa4RI2jxeAj65FMsHyyGe+fz0G0O/v4vI+98buAXd/n9MrqKrA5irDibPPdK1qo+526eREvgpf9aaeWEUMAJCikWCnEIDmRRwHZoINr91zI+ycigR5xEdlY/+ozJSehPuv+7TVkYj21A1mjwnCxPpHB5IooSPp834P1UKjWSdHEqy1yJuI0GSvr1JulANvXlFUhxSWe0aSSWCArpzHdCg4Mo8iijDxG7DyAZDLj6d81EU+HKwt2/Hw3/3y/91Tzeew9H7lhc/fuhamxCbPSLEKrGkwJEUyOi48wVNMlsxhcSgi88DE96Gj6rFeOmzVjefY+GZ59hymjYc1jNZ2v0pCfZ0J3SGkQdtuhbcVlHYC5fjLX0DVxBAxgbcydmbRAbhG9YI67iemmOkuKh0GXqqD3pJ5GNT/CSLKcyxDeCRJIvm/+jNVt0OJxw1zznmaUyAUkCu8MvWLTafvzd2urFU76TeimNRo9AcblIi01Ao5GxmmSCzDIxERIWs4TV7P/bYpaxmv0RGbqf6oByPIa6I5iqPkLShNAaeSeyoPYLDi0nRYefCxHSmYbvsqBGUluR1BZ82ijcQQPahAifNgKEc79GEJqbMa1ahX7nLmSTiZY77sA5cgQBl8e7SmhqauL+++8nJyeHmJgY3njjjXYrcmRkZLB582by8vIY+bOKe7IsU1BQgEqlale4aI93332XBQsWsG3bNubPn88HH3yA1+vl97//PZs3b0aWZRISEvh//+//MX78+G4dW4fixK9+9SueffZZoqICzJPqhJKSEl5++WX+8pe/9FifCucHKSwMd7++GH74Afv0aaDpfr1jUYRrx7rJSPbywTIDryw2IMsC44a66ZveRc8GUUtzwmNYSt8iqHIpguzBET4dje041uJX8WkjaEx6BrGmBcs77+CLiKD5gft7NAfXOXYsgseD+ctlBH34ESl3z+Ou650sXm7gk6913DnLFZgOEjSYG2v38X5kJVs8nzNVdddZd/HipZxSioQCTgiF1Ap+F16jbCKkJZ2yb3sR1JDKwzPVRM+TIIASWQCip5GgsnfR2o7iCB6DrLGiPX4cT1rqOf0PKFx8fD4vh7JzAt6vf7++CIKy6tmTnOjfj/jDxzB/tZbmhx8+Y7vfd+Jop74TsRxBFCQqHBnEH1jvT13TakEO7D2vcGUghYbS+OQTmFatxvjttxi+9wvMsiAgBQUhBQfji4zEnZmBFByMZA1GCgnGFxyMZLW2+13pTUzE+s9FBH32OS3z7uL2mS7+9oGRr7/TMfua029gvIZEGlN/jaFuI6bqFYTk/Z4RkbNxhk1kq2oTh4VD9D1LJJDC1Y0XL8UUcUDcQ5FQgEpW0+ekn0RXK1xcKlTVCWzZo2H0IE+7wgT4r43NJ1M6fmqXoW/YSlDkYhpS/x2voWsmhR0iiDjCp+MxZmApfQtr8aunbZZE3UnRwYpXn+h/rLG2PXfqR1YZz5/5pNeLYfNmjGvWIni9OCZPxj59GnIHBo4K4Ha7eeSRR8jJySE9PZ233367rXTozxk/fjxvvfUWGzZsYN68eadt27t3L/X19YwYMQKz2dylsQ0GA6+//jrPPPMMGzZsYO7cuTQ1NWGz2VCr1Tz44IMsWLAAnS7wBddTdHjntnPnTqZNm8Zdd93FAw880OVwj/YoKiri/fff59NPP+3w5ClcejjGj0d3KBvd/v24hndSyqiLJMdJ/NtDNj5fq6euUeCmqQGW4xQ1NCc8QlDZu5irvkDlqkLfvBufNpzG5GcQbD6si15H1mhpevSR82Le6Jg0CcHtwbR6NbJWw7Dbb/eX4tyqw2SAG6a4EAP4/A4JvZtxdf/LlvATpHgOkSqevvIpI9NIPUVCISeEAkooxit4EGWRWOIZJ00iSU6lriCGtz4xEhUmsWCeA7Ox/S/DztA2HyCo/H0EyUNL7D04g8ciNjWhrqykdUT7pQ8VFBQCx6vXcWJAX9L27Ed94gTepNOjJ87mOyEgES8cpk6Ow5LfgOD14vzZiojCVYhajW32TTiHD0NwufwihMXSbZHek5WFfdo0TGvW4E5PI3XkSMYMdrN5p4Zh/TzER//se0ZQ4Qi/FpdlMEEVH2GuXMrUpmSKUqPZJK4jXk7ESvC5H6fCFUMLzRQK+RQKeRRzAq/gwSibGCNNoL88GCOXpwn3ig16NGqYOSFwsVjXtBuvNhKv/syouu7iNabSkPZbNLZjyCojktqKT20F1UUUAGQZbXY25mXLUdXW4urXF9tNs/FFXhrGppcyr7zyCvv37ycmJobFixe36/1wihEjRpCRkcH333/PJ598wty5cwGor6/nD3/4AwD3339/QONrtVpeeeUVfv3rX7Ny5UoABg4cyJ/+9KcuR2B0RoffWCtXruR///d/ee+991i8eDGTJ0/m+uuvZ8yYMV0yt6ioqGDr1q18+eWX7Nu3D4A777yTX/7yl+c8aYULgyczE29UJIbvtvSIOAGg18G8G9o3ZekSgoqWuAeQBQ2Gxu/xaqNoTHoGvFosb7yKaLfT+OQTSJ28Uc8V+7RrwePBtHYtskbDjDk3Y3MIbNyupbFZYN4Nzq5fC4pahuvvJtexmPXa1dwtp6IS1JRw4mR0RAHNQhMAwXIIfeX+JEmpJJDUlsN7tEDFW58YiAqTeHyePTD/CwDJjbnyMwwNm/HoE2iJfwifzi8iao7nAuDJVOrWKyj0JCV9+5ByNBfT6q9oWvCL07a5MGOXLYR04DsRzgn0QivHpLGkHM/BExuDt4tlkhWufHxxcT3Wl33GdDQFBQR9+hnehERumBzDoeNqlnyl59n77O1GXEvacJoSn0DXvAtzxcfMLfLyaqqRb8SV3CbNQ0QJ075akZCooKxNkKgV/PnuFtlKX7k/KVIaCSRfdD8JA030Eb6lUs6gjL4B7XusUEV2rpobJruwmAMzTBc8TWhsR7GHz+zxSAVZZcBtGdSjfXYLSUKTl4dx/Qa0x47hjYqi8bFHA66od7XS2NjI4sWLAQgNDeVPf/pTh21ffPFFRFHkT3/6E/feey+//e1v+eyzz4iMjGTnzp00NTUxd+5cpkyZ0mEfHaFSqXjhhRcwm818/PHH1NTUdFiuNFA6fPebzWb++7//m7lz5/LCCy+wbt061q9fjyiKpKSkkJ6eTkJCAkFBQej1elpaWmhsbKSqqooDBw5QXe0PN5dlmYkTJ/L4448zYIAS0ndZIQg4xo8n6LPP213du2gIIq2x9+Ax98FtykIWTFjffhN1eTnNDz2ENyHhvE/Bft1MBLcb46ZNoNFw6/U3EGqVWbFRR1OrwEO3OjB21ZTYkMr1Df15V3eUD4VF2AUvkiChkbUkkMQwaSRJcirBnGlMeiRfxVufdl+YUDlLsZS+hdpVgT3sWmyRN51mYqQ9fgzJaMTbgxe7CgoK4NNqsF0zmaDlq9Dk5uLJOF0AbCCWSAoACX52MxcvZOOQzTjrgrDU1tEy58Yrrt67wiWCKNI8/x5C//wClvfexffcc9w8Tc37XxrYskfDxOFnVtoCQBBwWUcgCzrCS15jRtNYVgSXslvYzgi5/TK6ClcmDuwUCQUUkkeRUIhLcLZFf46XppAipxFK2CXjJRFCGf2FtWgEFybqqZQz8HXR0FWS4Mv1OsKCJSaO6EbURPMeBOROq3RcrqgqK9Hv2oVu9x5UjY1IRiOtN8/BMW4cqJSKPl3l4MGDbZU3cnJyyMnpOF33xRdfBGDAgAF8+umnvPLKK+zYsYPc3FySkpJ49tlnue222zrc/6mnnurSnPR6PRUVFdx1110MGjTotG2CIPDyyy93qZ9TnFWaHDBgAIsXL2bv3r18/PHHbNy4kby8PPLy8tqtmXqqTqrZbObaa6/l3nvvpVevXgFNSuHSwTV8OKaVqzB8t4WWey4RcQJAEP0f3rKMeeknaI8cpeX2ubj79rlA4wvYZt+E4HFj3LARWatl6owZBFskPlyp5+UPjDx2h6PjUp0/Iyh4NjNqX+CgqYWBHisJ2tFE6oZ3WoLtnIQJWUZf/y3mqs+RVUYak57CY+5zRhvN8VzcmZmKIZGCwnnAMXY0xk1bMK3+isannjxtW6McS5x4FLNcf1pqh4l6QoUy8qSRxBwvQBJFnMMGX+ipK1xFyBYLzfPvwfraPwn65FMGz5vHzjQNqzfpGJDlJcTS8fec2zIQp3UUI4q3ccw0jm3qLSTJqUShpPheqcjI1FB1MjoinwrKQACjbCRNziBFSiOJFHRcep4CsRwmS9iKAytHpQn0F9eRIB+iiKFd2n/7fg0V1Sruv9mBphvBH/qm3Xh1cfj0sYHv3BUk6YJezwktLej37kW3azeakhJkUcTdqxe2m27E1a+f3ydJISAmTJjAsWPHAt4vPT2dV155JaB91qxZE1D7qqqqM/ZpTys4G11+6wwZMoQhQ4bg8/nIzs5m586dlJWVUV9fT0tLCzqdjtDQUFJSUhg4cCCDBg1Cq/zTXbaccvaXdSLOEcMw/LCdlptmIp8lpedCO/sb1q/HsG0b9mum4hxzgVdjBIHWW29F8Hgwff0Nst7A0EkTsZodvPWZgZfeNfLI7Q4SYrrg/yCIZAUvZFDtOgz1mxGlo3iMW7CHTcMd1P8MJ+Q2YSJc4vG7AhMmBG8zQWXvo2vNxmXuT0vcfGT1mXWUVdXVqBobsWcpJUQVFM4LWg32adMI+vRTtIeP4OqT3rbpR9+JstPEiXghB5+sosKXwci8VdQkJSKYTJfImqPClYonMxP7jOmYvv4GT3o6t80YzfOvm/h8jY6Hbus8VbM1Zi4htqPMKcrj7+mhfCOuYJ50P2oUk+UrBQ9uTlDYJkjYhFYAouQYRsnjSJHSiCKm0+gIlxvWbNXS3Cqi1firTvh/y2g1nPa7vec0GgLy/PopAhIZwg8kCNnUyglky9fgQ0eNfJxE4SAlcv+zRk84nLB6s5a0BC8DewVeGUt016Fx5NMaObt7B9EOQnML2rxcNLm5aHLzUNXV4Y2Lw5OSjDclBU9yMlJISM9G3nk86LKz0e3ajfbIEX8p+vh4WufMxjlkKLLl7NYACpcGCxcuvCjjBqzrqVQqBg4cyMCBA8/HfBQuEX7q7G+MimC0z0fzslUUDe48NedCOvvrdu/GvGo1ziFDsM3qfrnTc0IUabnzTgSnC9OyZfhCQ0gfMICn59tZtMTAK4uN3H+zgz5dqEoiq0zYo2bjCJ+BvnErhroNWEtew6uNxhF+LU7rSBA15yRMaFpzsJS9h+Cz0xJ9B87QSR1+KWmOHwfwR04oKCicF5yjRmLcuBHj6tW4ej3R9vyPvhMVlMj+71sVLqI5RhXpBBfXonW5KM9KR0m6UrgQ2KdNQ5NfgPnzz4l8JpGZE5JYsVHPgaOd34zJKhOtsXdjLX6VG+vT+DishC3Ct0yWp13A2Sv0NHbsFAi55AvHOUERPsGLVtaRJKeQIqeRLKdhwtSlvk6Ui3ywzEBdg0CIVcbtAbdHwO0J7KZZq5HRamQiQiUeuMXZJc8HwWdnoPA1YUIJxfIAcuVRnEqlK5SHMkL8gng5hxN0HqG27gctNrvAnDsCrNx2El3TLoBzSukQbDY0eXloc/PQ5OairqwEQNLr8aSl4e7XD3VpKYbtOxC+2wKAz2rFm5yMJznZL1okJARuoivLqAsK/Wkb+/chOpz4rFYckyfhHDYcX2xMt49J4eJx2YgTClcf9mArdXExxB05xomB/ZAvRoi/LCPW1aHJy0ebn48mPx9VXR3utDRa5t11cdMORJHme+4m+NVXsXywmMYnFhKdlMQz99l5Y6mBNz8xMHemi9GDO8jN/RmySo8j7BocoZPRNe3BULeWoPLFmKqXs8t2J2+tnUB0uMSCQIQJyYOpehnGuvV4dbE0Jz2NT9/5LY322HF8oaFIYWFdHERBQSFg1GpsM2dg+deH6A5mg/rHVK6f+07EcBy14KVU6kfqsQM4TSbqY2MUcULhwiCKNN9zDyEv+P0nJj/9HHuyNXy+VkdWihd9J5Xj3EH9cQSPoV/ZVoYGXcse7R5SfekkkXrh5q9wzjTSQP5JQaKcUmRBxiJbGSAPIk3KJJb4TtNRf44kw7fbtazapMVikll4j4P0RN9p2z0ecLkF3D/73d5zbo+A0wW7Dml49ws9j89z/PQj9QxEVzXW4lcRqeGINJFyTjdlbCGSWjmBROEApXI/fB1E+9Q2CGzaqWX4AG/XomXbQde8G48hBUnb9bKpgtOJJi//ZGRELurycgRZRtZq8aSm0jp8GJ6MTLzxcaf7Ovh8qCsqUBcWoiksQlNUhO7AAQBklQpvQjye5JS2CAvJam13fLGmBv2u3eh370ZVV4es1eIaOADn8OF+HyUlJfiK5uDBg2f4Sa5btw5RFJk8eTJiN19/RZxQ6BKlfXozcN1GIk4UU52SfP4HlGVU1dVo8vLQ5BegyctD1eSvWiGZTHjS0nBMmIBz1Mhul0nrUbRamh56mJCXX8b6xps0PPsM1rAwnrjHzntfGFjylZ6GZoGZE9xdV9QFFa7gEbisw9HYjpJ3MI/XNo8mPqiYp6/5DpV6PBJnFw5UrkqCSt9C4yzBETqJ1qhbQDxLdIvPhyYvF9egQYrRnoLCecY1dCje9RswfbUW4frpbQJww0nfiSC5jhbCiReyaZKjcLcaCSst80eyKRd/ChcQ2RJEy73zsb76D6yffcLtM+/lpfdNrN6k45bpnZcHt0Xfhrb1CNcVHaIwI5Y14mrukR7EcJmWi7waOOUfkSccJ1/IpVbwm91HyJGMlMeSJmUSQWS3zCwbmwX+tVJPbpGaQb083H6d8wwjcVEAndaftnFqRl0hPcnHB8sMfLFWx9yZ7f9famzHsJS8Dsjsk2fR2IHMWygPZbi4jDg5h2IGtdtmxUYdKhGun9T5e6AjVK5KNM4SWqPndt7Q5UJTWIj2lBhRUoogSchqNZ6UFOwzZ+DOyMCbmNj5tbFKhTc+Hm98PM7x4wEQmpvbhApNURGGrVv9pu+ALyQET3Iy3pRkPElJqEvL0O/ahaaoCFkQ8GRkYJs5A9eAAaDrRKVUuCI4fvw4Tz75JMXFxWzduvW0UqZLlizhhx9+ICUlhZdeeomsrKyA+78E7uoULgdqE+JwmM3E5xw9P+KEJKGqqESTn482Pw9NXj5iqz9n0Wex4ElLxZ6Wjic9DV9U1CV5QS5bgmh69BGCX3oZ6+tv0Pj0U+iNRh6e6+CTr3Ws2aqjvknkjlnOTpX8MxAEDlb1463vhhMd7uTZKV8TZtsKuWtwWYfiCJuG15DYzoRk9I3fY65YiixqaEpYgNvStXQsdWkposOJR0npUFA4/4gitutmYn3nXaLzCqjI9HtPNJ70nQimHA1OTEIT2dJQYnLzEYDyjPROOlVQOD940tOxXzcT0+qvyMpIZ9ywyWzZrWFYPw9JcR2vGssqIy1x9xB84hVursngnYgGNohrmCXNvmQqNSj4y32WUXJSkDhOi9CMIAvEEs9EaSqpcka71cMC4dAxNR+v1uHxCtwxy8mogZ4eXQcZ2tdLWZWLDdt0xEdJjBlyeuSqvv47zBUf49NF0ZTwMI3Hqzvsq5lo6uR4koQDlMp9kX4WPZFXrOLAUQ3XTXBhDQqsdOgpdE07kRFwWYa1u13/wzb0u3ahPnECwedDFkW8SUnYr70GT0YGnuRk0Jybh4tsseAeOAD3wJMr4V4v6rIyNIWFqIuK0BQWot+3r629Nzqa1htvwDV0KFJw8DmNrXD5UFhYyJ133onNZiM4OJjm5ubTxIlBgwZRWFhIQUEB9913H8uWLSMqKiqgMRRxQqFriCKlfbLI2LmHtJ178Oh0SGoVPrX6x98qNRqjCXRGZI0GWav1/2g0/g/Nn37z+Hz+D738fH9IWkEBot3u3xQcjLtXLzzpaXjS0vBFRFw2q/e+qCiaH3oQ62v/xPL2OzT94jFUajV3zHIRapX56jt/qdEHbnZg6KJR9SmPiehwiQXzvMiGedR7ZmKo24C+YQv6pl24Tb2xh0/DY+oNgoDgtRFU8S90zXtxm3rREnc/kia4S+OJ9Q0Y164DFL8JhdM5ZZQbKBfaKPdyxD1gAJ6EOFL2HqAyLQVZpTrpO2ElRCgnhHLcsoFqOZVRx5dTHxONUzEWU7hI2K+5Bk1+PubPv2DOwkQOHsti6Vd6nnvA3mlVQI+5L46QcaRUbmGc9Qa+0x3kiJBNH7n/hZu8whl48HCCQvKF4xQIuTgFJypZRRIpjJbGkyKnY+yBCBe3B5at1/H9Xi3xUT7mz7ETFda9G/qzcf0kN+VVKj5boyM6QiI1wQeyD1PlZxjrN+Iy96Ml/iEkUQV0LE6AP3pimLicOPkwJfy4yCPJ8OU6HcFBEpNHBV46FABZRte0G48pE0lzZvqE5vhxgpYuxRsTg2PSJNwZ6XhSU89/hIJajTcpCW/Sj5X6xMZG1CeKkcJC/SXmL5Nrc4WeY9GiRdhsNmbNmsXzzz9/RvGLJ554gkcffZTf/OY3rFixgkWLFvG73/0uoDEUcUKhy5RnZhB/+CjJB7M7bvTNug43nRIqZK0WwW5HdPnD33zh4bj6928TIy53jwNPejotd96J5V//ImjJElrmzUMQBKaPdxNilfh4tZ6/LTby2O0OgjspwQZwOE/FW58ZiAmXWDDPjulkyKOkCcUWfRv2iFno67/DUL+R4BN/w6uPx2kdhaFuA6K3idaom3GEXXtGtY/2EOvqMK5bj37nTgBs065FNpvP+XwoXDn81Cg3EC6kUe5liyBgu24Gwa+/TeyxXMr6+EtwNxBLNLmIeCliCNaKWowtrRQOGXRx56twdXPKf+LPLxD+r/eYe9OveHNlKJt3aZgyqnN/JVvUrWhbDzOlcAf5mel8K6wlTk7ASvCFmbtCGxISG4RvOCrk4BW86GQ9qXI6aVImSaSgPUuFikAoqxL5YJmeyloVk0e6uX6S67xm5YoizJ/t4C/vmnjncz2/vLeOpObX0bYexh42FVvUrf5rI/nsokITMdTLcSQJByiT+yKdvH3adVBNaaWKe25yoO1m4ILaWYLaXUVL2LVnbvR4MH/yKb7wcBqefeail96UgoNxK1ESVzXbtm3DYrHwP//zPx1W5dRqtfz+979n/fr1bN68OeAxFHFCoct49Tp+uONWvzmlz4fK60X0elF5f3ycHh+P4JEQ3B4Ejwc8bgS3++TfJ3+73SfNelL8YsQV+EHnGj4MW30dpq++xhcWhn3mTABGDPBiMTt453MDf33PyKO3O4iLaj8Mtk2YiDhpfmk4s42sMuKImIEjbCq6pp0Y69ZhrvoMrzaSxtRf4TUkn3WuYk0NxnXr0O/aDYKAc/Ro7FOnIoWeW9imgoJCYLh7ZdIYFUnKvoNUZKYjqdUnfSeOIMkCZXIf0o7vw6PVUJ2SdPYOFRTOI7LZ3OY/MXrvR2zPeISvv9MxsJeXsOCOhXdZZaAldj7BJ15mTnVv3oiCNeIqbpXuQkSJsLqQbBO2kC0eoJ80kCypD3EkBGRo2RVkGb7brWHFBh0Gvcwv7rTTK/XsFcx6AqMBHr7NwV/fNfD+Ege/HZtPS8I9OEPGBdxXoTyUoeIKYuUjlNIflxtWbdKRFOtjSN/AIwpP4U/pEHFZhpw5//XrUdfU0PiLX1x0YUJBAaChoYGsrCz0+s7Dv41GI8nJyRw/WfkvEBRxQiFwBAFJrUZqR/J298pUVkhPYp82DVVtHaZv1uALC8M1YgQAvVJ9PDXfzutL/aVGH7jFQVbK6V/UOXkq3j6LMHEaogZXyFhcwaNROcvw6SJB7DzkT1VVhXH9OnS794JKxDFuNPYpk5CCT4YVdrKaoITpKyicBwSB/OFDGLrqG+IPH6V4QD8aTvpO1JCC160lsvAEFRlp7X7+KihcaDxpadiuuw7zqlU8cMNGfn1iOp9+o+fR2x2dRnx7zL1xhEwgpnozU6238rVhF7uFHYyQR1+4yV/lFJLPTvEH+kkDuVa+7ryM0WIT+GilnsP5avqke7nreidBpvOTxtERCcYjLBi2nZe2LWRR3ovc2V/bLYeTRmJpkGNIEvZRLvdmwzYDza0iD9xiQ+xudoMsoWvejdvcF1l9etlVVVUVxnXrcQ4diqdX4KaCCgrng/DwcCpPlqg9G3V1dVgsloDH6JGrG5vNhsnUtVrGCgpXDYJAy+1zERsbCfp4CVJwcJvBZFyUxLP32Vm0xMCiJQbunOVkxAC/8h6wMHHamCI+Q0KnTVSVlRjXrkO3dy+o1RT36UXxgL64jUYoLfX/nAUlTF9B4fzQGB1FXXwsyQeyKeuViVtrIlu6hkaiiSooQuXzUZ6VcbGnqaDQhmPqFDQFBUR+9QV3TUvl3T2Z7DuiZkifzleTbVG3oG3NYdSJzeRlDmKb8B3JcgqRRPf4HMspZZe4jX7SINK4Ot8/P/UMaqGZb1QrCJcjmCRNRKbnFyOO5Kv4cKUeh1PglmlOxg/rWdPLrnDK+HJwYhQzhXq+/iGM2Hgnk0Z0rbT7zymUhzFEXInRVsq3OwwM6eMhJb57pUMB1PYCVJ4GbJFzTt8gy5g//QxZq6V19uxu96+g0NMMHDiQNWvW8MknnzB3bsfVZVasWEFVVRVTpkwJeIxuiROVlZW89957fPfdd5w4cQJZljl8+DBVVVU899xzPPDAA92ajILCFYdaTfP99xH8t1ewvPMOjU8/jS/af+EVbJF5ar6ddz438OFKAw3NLuKjfd0XJs6Cqrwc49q16PYfAI0Gx5TJ2CaNI+/EiZ4bREFB4ZzJHzqYEctXk5h9mMIhg6jCX5Uj9lguLSEhtIRf3r48ClcYokjLvLsIeeFFJu98i60xv+WLtSZ6pXoxdhL5K6v0tMTdS3DRX7mh0sXrMUa+FlcwT7ofNedWeeAUDdSzVdxEnnAMALtoI026OsWJU55BkiCxJ30HHr2HjGO92FBehd2hI8jkwGJ0otedLiIEuhjh9cLKTTo27dASHeFjwV0OYiO7fwPfLdoxvpyWpqG01sPy9TpiIqQzIla7QgOxNMrR7Djqj2S4YUr3SoeeQt+0E1nQ4A46vZKabtcutLm5tMy9DVkxPla4hLjnnntYs2YNf/zjHyktLeXmm28mOTm5bXtJSQnLli3jzTffRBAE7rvvvoDHCFic2LJlC88++yytra3Isj80Szj5KVZaWsru3bvZs2cPjz/+OAsXLgx4QgoKVxqy0fiTEqOv0/DMM8gnw5wMenj0DgdLVuv5arMOAZm4aInH77KfUe+7u6hKSzGtWYvu4EEknQ77NdfgmDQR2WxG7oIRlIKCwoWlJSKc6uREEg8dpqRPL7x6Pab6Bqw1tRwfNVxxSFe45JDNZprvnU/w31/l6fB3WWhbyMqNOm6/rvObN48pC0foJMJrN3Gd9W4+NW1li7CJyXI75oABYMfODmErB4V9qFAzRpqAhMR2cSuNNJxzKczLmbyYYzSbmuhXOIj60njWbD+9UopG5SXI5CTI6CTI5KDJpSM8RCQ8RCLUKndajaWqVuT9ZXrKqlSMH+rmxqmubhtFdgfBa0PlrsBUs/oM40sRuPtGJy+9b+S9Lw388gFbp94oHYzA93XT2F46kplDjhNqjen+ZGUfuua9uIIGIKt+VPEEmw3zsuV4kpNxjlbSnBQuLYYOHcozzzzDX//6V958803efPNNNBoNBoMBh8OBx+OPSpJlmaeffpoRJ1PaAyEgcaK4uJgnn3wSh8PBzJkzmTVrFq+99hpHjhwBIDk5mTlz5vDll1/yj3/8g379+jFp0qSAJ6WgcKUhhYbS/MjDBL/yd6xvvEnjEwvbykCpVTDvBicRIRJF5SruudHRI8KEurgY45q16LKzkQx6bNOn45g4AVlJwVJQuOQpGDqIiKJikg9kkzdyGDHH85BEkcq01Is9NQWFdvGmpmK7/npCVqxgQb/1/GPfNIb39/pLOHZCa9TNaFuyGVD8DbmZ49iv2k2qL50kUgKegwcP+4Rd7BK24cFDf3kQo+TxmDDRTBPb2cox4TAj5bHdPczLmmprJSWRJ4ivScJSncCX+7IIDrIxeegRWh16Wmx6Wux6mm0GmmwGSqtDyM7/UY0QBJkQi0x4iERYsER4iExYiER4sERJhYov1+vQqGUeus1O/8zzZHopy4jeRlSuCtSuSlSuClSuStSuCkRfi78JIi2xZxpf6nXw0K3+Ch5vfWrg6XvtAYknsgxrc8Zg0TVzc9Ii7NJvQexehrzGdgzR14LLOvy0500rViI4HLTcPtdfckRB4RLjkUceYcCAAbzxxhvs3LkTt9uN2+1f7BRFkUGDBvHoo48yceLEbvUf0Dvq9ddfx+Fw8PTTT/PYY48B8M4777RtDwsL4/nnnyctLY0XX3yRjz76SBEnFBRO4k1IoPne+VjeehvLB4tpfvCBti8eQYDp43sgikGWURcV+T0lDh9GMhqxXTcTx/jxyMZzr1GuoKBwYbCFhFCZnkr84aOU9ulFTF4BtYkJeAydO2QrKFxMHJMnocnPZ8yRz9gak87Sr5L4/x6yo+6sAISooyXuPqxFf2FGRT3FcWGsEVcxX3oIPV1T6iUkjgjZ/CB8R6vQQpqcwThpMqH8mAJlwUqsHM9RIYcR8hiEbtkiXr400sDhxGwsNivpZVls2J+J26NmxqhDhFrshFrsZ+wjy5CY3J/6Rh21DQK1DSJ1jSK1DSKHjqtptZ9+85yZ7OXuG51Yg3rA9FL2oXLXojopQKjdPwoRouRsayaJRny6aFxBA/DpovHpYvDqE5A0we12GxEqc+9sB68vNfDRKj33zu76tVdBWQQ1DRZmDvoBk1yJ1LS9W5U/AHRNu5BEPW5zv7bnNPn5GLZvxz51Cr7Y2G71q6BwIRg1ahSjRo3C4XBQUVFBY2MjBoOBhIQEzGbzOfUdkDjx/fffY7Vaefjhhzttd//99/PWW29x8ODBc5qcwuXNT82XAuFKrgTh7teP1ptvJujzzzF9uQzbLTf3SL9iYyO63bvR79qNurISyWSi9fpZOMePRz5LuR8FBYVLk8IhA4nKL2TgmvVonU7Ks9Iv9pQUFDrnJ/4TTzYv4gnn71mxUceca1ydV+8wZeAInYylfiPXB9/Pv0ybWS98wyx59llFhCIK2CJ+S61QTbQcw0zfTcTTvjF0L7kvG8U11FJNBFHncqSXFV68rFatRPAJ9CsaxLHCeEqqwhjVL49Qq63D/QQBgoMkQiw+0hLP3O500SZYyMCALG/XKlfIMoLkRPQ2I3qbEbzNiN4mRG8zKnc1alcFKnc1gvzjNaRPHewXIYJH4dXF+EUIbTSy2hJwqlvvNB83THaxYqOeuEgD0daz7+P1iuw6kkKYtYWYBA8efSLGmq9xBo8GIcDyq5IHXfM+3JbBIGpODYB56Sf4QkOwTZ8eWH8KChcJg8FAamoqbrcbbQ+Vuw1InKirqyMrKwtVZwlngEqlIj4+nqNHj57T5BQub06ZLwXKlV4JwjlhPKq6WoybNiOFheGY1L2wJ1wudAcPod+5E01uLoIs40lJoWXubTiHDWtLG1FQULg8cVgslGdlEH/0OE6jkbo4ZSVN4dJHNplovu9egv/2Cv8R8Ta/2bEQnUZm1qTOV6htUXPQtmaTUbKCMRkz2Kr+niNSNn3k/u22r6GK78SNFAtFWOVgrpNmkyn36lTMyJR7sUlex1HhMBHy1SNObBLWUSPUMLB4CI66MHbmpBIfWUeflPJz6levg/hoifjok4aXkhvR09wmOpwSHE7/uwXR24Qgn1kxQ0bEpw3Hp4vGbe7XJkL4dNHIqi7mu7rdCG438llWb6eM8lBapeKrzQauGRlKYlR9p+0PFcRjc+iZOPgYgiBgi5hJcMnr6Bp34AoZ07W5nUTbmoMoOXD+JKXDuPFb1FVVND3yiHL9pnDJU1dXx3vvvcemTZsoLCzE5/OhUqlITExk3LhxPPjgg0RFde8zNiBxwmKxUF7etQ+yqqoqgoODuzMnBYUrHttNN6Gqb8C0bBm+sFDc/du/+DoDSUKTn49+5050+w8guN34QkOxT5uGc/gwpIiI8ztxBQWFC0rR4AFE5xX4y4cq+ccKlwne5GRsN95A6rLlPJa1hkXfz0CthunjOhEoRK2/ekfhi0ysKKYwPoFvhXXEy4lY+HFpu4Vmvhc2c0TIRo+eidJUBshDUHfhktaAkUSSOSYcZpw86apI7TgiZHNI3M8waQSmhnCW7+mNVuNlwuDjPeOtK8sYar/BWLsWUTozNQRAUpmR1BYktRWPMfLkY0vbc6ceyyoTCAF8znm9qMvKUZcUoy4pRVNSjKqiEkSRhl8+hy+mY8NKQYA7ZzmprjWwaU8vbpywj2Czo922NqeWg7kJJMfUEBPeBIDb3BePPgFj7de4gkcGFD2ha9qFpDLjMfUCQKytxbh2La5BA3H37dP141dQuAjs2bOHJ554goaGhrbiGABer5eCggIKCwtZsWIFr7zyyvk3xBw0aBAbN27km2++YcaMGR22++qrr6ipqWHq1KkBT0hB4apAFGm+526CX30Vy/sf0PjEE3iT2omZPImqqgrdrt3od+1C1diIpNfjHDoE1/DheFJSlJsWBYUrFJfJxA+334JXd+VGkylcmTgmTUKTl8/4I19QMiSd1ZvTUatkpo4+c8X8FF5jOo6wazDVreN668O8G1TFN+JKbpXuwoObXcJ29gq7AJmh8khGyGPQE1jqYi+5L9+IKymnjDjiz/EoL23qqGW98A1xcgJjpLG8meOmscXE9FGHMOg6fh26jOQmqOwD9M27cJn74zGmIZ8hOgQFnvbQHl4v6ooK1CUlqItL/L8rKhB8fuNNyWTCmxCPu3cf9Nu2EbT0ExqffKLT6yOtBh68tYX/e9PE+p19uXH8PrSaM4089xxJRpIFhvcp/PFJQcAecT3Wkn+ia9qFK3hU147D50TXcgBn8Bj/eZFlgj79DFkUab25Z1J9FRTOF9XV1SxYsICmpib69u3LXXfdRd++fTEajbS0tJCTk8OSJUs4fPgwTz/9NMuWLSMyMjKgMQISJ+677z42bNjAb3/7W5xOJzNnzjxtu9frZdmyZfzP//wPgiAwb968gCajoHBVodXS9NDDhLz8MtY33qDh2WeQwn407xJsNnR796HftQvNiRPIgoC7Vy9sN92Iq18/6KHcLgUFhUsbxQRT4bJEEGi5605C/vwCtxe+SW2v/2TFRgsqFUwa0fGNsS3yRrQtB4kv+5zJGbeyRr2W1eIyyijGITjoJfVlrDzxtGiKQEiTM1DJao4JOcTJl7440V3/Lp9KYhVfoEXDddJsDufqOFIUQb/UUuIjG859Xp4GLMWvoXaW0Bo5B0f49J4rc+zznSlElJf/KEQYDHgTEnBMnoQnIQFvQgJSaGjb+N6oSCwffoT+h204x3VemSXEKjFl2BG+3tafTXt7ce2InNMOo7bRTG5JFP3TSrGYnKft6w4agFcXj7HmK1zWEV2K+tC1HESQPW1VOnT79qE9epSWW25Gsnbvf1pB4ULx1ltv0dTUxKxZs3jhhRcQfyb+9e3bl1tvvZVf/vKXfP3113z44Yc888wzAY0RkDgxfPhwnnzySV555RX+/d//nf/8z/9EOPkOvvHGGykpKcHpdCLLMvfffz9jxgSWg6WgcLUhW4JoevQRgl96Gevrb9D4xEI0RUXod+5Cm5OD4PPhjYmh9aabcA0donxxKSicRDHcVVC49JFNJprnzyf41Vd5xLYYR+bDfLlOj1oF44Z2IFCIWlri7iO48M8Mr8ghPz6LPOEYCXIS431TiCL6nOakRUeanMFx4SgT5WtQ0QOr+ueR7vh3yciUDyimXqjjFulOfC1BfLzKSKillWG9C8/ewVlQ2wuxlLyGILloTvwF7qCB3etIlhFaWlFXVqCqrERdUYm6rBR1WTmC1//5Lhn0eOMTcEyaiDchAU9Cgn8hpxMhxDV8OO5duzGtXIm7f7+zXjvFhDcxql8+2w5lsPdYEkN7nTg1PXbkpKLXehiUWXzmjoKILXIW1pLX0TXv9gsUZ0HXvAufOgSPMQ3Bbsf8xZd4EhJwjute1Q8FhQvJ5s2b0ev1/OEPfzhDmDiFKIr84Q9/YMOGDaxfv/78ihMACxYsID09nb/97W/k5+e3PX/8+HEA4uLiWLBgAbfcckugXSsoXJX4oqJofuhBrK/9k7D/9zsESUIKCsIxfjzOEcPxxcVd7CkqKFxyKIa7CgqXB960VOwzZ2Ba/RWPzd3MP6TJfPqNHrVaZtTA9gVGrzEVR9i1GOvWcqPlcSrNo4kkusc8IrLkPhwXj1BCEcmk9UifgVARUobGqyWsJfy8+F6Uh5VyVDzCaGk88XIy/1ypx+0RmDHqCCrVuZX51DVuJ6h8MZI6mMaUp/Hpu3aNIrS2oq74UYRQVVairqxEtP1YLUQyGPDGxeGYMP50ISLQ1FVBoGXubYT+358xf/4FzQ/cf9ZdeidXUNdkZv/xJEItNlJiaymqCKeyLpgxA3LbTfcAcAcNwquL9UdPWIZ1Gj0heG1oW3NwhE4BQcS0ajVCayutjz6ipOcqXBZUVFSQmZl51nKhQUFBpKenU1BQEPAYAYsTANOmTWPatGmUlJSQl5dHa2srBoOB5ORk0tOVUmcKCoHiSU+n+d756A5l4xo8GHevLDhLVRwFBQUFBYXLAfs116DJzcP65ec8/HQSi6RUlqzSo1Y5GdavfYHCFnkj2tZDhJR9COm/Q1b13E18MqnoZB1HhcMkyxdWnGjVt3A46RAAFpuV1Mp0QntQpGg2NHE87ghJUjIj5bF8u0PD8UI1t89sxaxp3/CxS8gSpqovMdatxW3MpDnhUWT1mTcogs12UnyoQF1ZiaripAjR2trWRtLr8UVH4xrQH190NN7oGHwx0UiWwMuCdoQUEYFt+jTMq1ajPZSNu3+/TtsLAozpn0dji5Hv9mVhNjrZdTiF4CAbWYkVnewoYo+4DkvpW2ib9+G2Du2wqa5lH4Lsw2UdhrqoCP0PP+CYMAFvQvulbxUULjW0Wi0tLS1datva2opaHbjU0C1x4hQJCQkkKG8oBYUewT1wIO6B3QyNVFBQUFBQuFQRRVrunkfIn18gdPH7PPjUs7zxhZV/rdCjUjkZ3LsdgULU+NM7Cv6PoLL3cFkGg6BBFjTIogYE9U8en3pe3fYYQdXhja4aNelyFseFo3hlD2o05/kE/Ehh2Akkt4aWTdegHr+Z/Wl7sNqCSalIJ7Q17JxECo/KQ3byfjReDTPEmZRWqlj1rY4BWR5GDXLRjWAzAASfg6DSt9G1HsIRMoHWmDtOM7nUHDuOcf161BUViD+5cZF0Or8I0bcvvphovNHR+GJi/GkWPeVP0QmOKVPQ79mL+bPPaMhIR9Z37t+jUslMHX6E5ZsHs3rrIHySyIxRB88a1OCyDMWrXYWpZhVuy+AOoyd0TbvwaiPxauIJWfpXJKsV+3Uz222roHApkpWVxd69ezl48CADBgzosN2BAwc4ceIEQ4d2LNZ1RLfFicrKSmw222klRNpDiaRQUFBQUFBQULi6kaxWmu+eR/Ci1wld+SUPz72dRUsMfLBMj1p00j/rTIHCa0jGHjELU81KdC0HAhpPRvALGOIpsUKDLWoOLuswwF+1I0c8SAH5ZNKrR47xbLjUTqrDymndPQLfoaHk7RxNr2nrcQ7ayf703Vhbg0mtzED2zz4gZGSOJGTj1DoZkjsCMd7I+8sMBJlk7pjl7LYWoHLXYC15E5WripaYO3GGTvrJoDKGzd9hWrYMKTQUV5/e+KJj8MZE44uKRgoJviAiRIeoVLTccTvBL/8N4+qvsN1y9moYRr2bqSMOs/r7gSRE1REX2Xj2cQQRe8QsLGVvo23Zj9sy5MwmniY0tmPYI67D8N13qMvLaXrwgbMKJgoKlxJz5sxhz549PPXUU7zyyiv079//jDYHDx7kqaeeQhAEZs+eHfAYAYsTixYt4r333qOpqemsbQVB4PDhwwFPSkFBQaG7KEaJCgoKCpcmnt69sU+dinHDBiyZmTx6+2Be+8jIu1/oefA2B33Tz8zrt0dejyN0AoLkQpA8CLIXZM/Jx56Tj70/eXzqee/Jx26QvGhbszHUbWwTJ+JJxCibOCbmkCldGHGiJKIYWZAQsocwZ9IedmSncfSbGUTtHk7vmWupiDvOvvRdVMsVjJYmkEBSAH2foCa4ioyyLILtIXy5zkRtvcDCux2YDH5zx0AJoYyQwg8Agaakp/CYf3KevF7Mn3yCYcdOXAMG0Hz3PNDpAh/kPONNTsY5biyGLVtwDRuKN+ns5zQypIVbJ+/GoHd3eRyXdRjemlWYalbjDhp8hiijb96DgIzHl4H163dx9euHu5OVZwWFS5FbbrmFlStXsmPHDubOnUufPn3o06cPJpOJ1tZWDh8+zJEjR5BlmVGjRnXLgzIgceK9997j5Zdf7nL7s0VVKCgoKPQ0ilGigoKCwqWLbdZ1aPLzMS9Ziuf/S+CxO8N57UMj73xm4OG5DnqlnilQyGoL53pFaaxejalmBaKnEUkTjIhIltybg8I+nDjRc35XsL2il9KwEuxH+pIS5Eatkhk7MI+o0Ga+P5jB9qW3MGF4DmRlUxZXwmeqj4iXExnlG33WvhuNDeTFHiOiMZKEmmQKy8PZfkDPtLEu0pPaN3I8G3HkkCl8j6SOpClxIZI2om2b0NyM9e130BQVYZsxHfv06Ze0oaPt+uvRHjxE0NKlNDz3XJc8vYJ+Vjb0rAgi9oiZWMreQ9tyALdl0Gmb/SkdcRhWbgWgVSkcoHAZIggCb7zxBr///e9Zvnw5OTk55OTkIAhC232/KIrMmTOH3/72tx1W9OiMgMSJJUuWIAgCd999Nw899BBhYWHdMrpQUFBQUFBQUFC4MggoYk2EpnvuIPTFv2F9/32kp57iF3faefVDI299auCxOxzdvqHuDJdlMKaaFWhb9relJmTJfdgn7iZfOE5f+fyuYleEluFTe2jePp603j8aLKYnVBMW3MrG3b1Z+/0gBteGcO8cA4fVOewUtvGZeikhaaGkVmYQbAs5o1+3yk128gH0bj29S/pjs+vZeiCDpFgPM8Z3feX/FAI+MoXviRcOUyMnQfLjoP6xFKe6pATLW28j2u003X8f7kGDunU+LiSyXk/rrbdgffsdDJs24Zg69byM47KOwFezGmPNan951ZPRE6K7Fo2jAEf9aAw5+2m96Sak0DNfSwWFywGdTsfzzz/PwoUL2bJlC0VFRdhsNoxGIykpKYwfP564c6g0GJCyUFZWRnR0NP/5n//Z7QEVFBQUFBQUFBSuHLoTsRYxZiQDNmzCtHIVzJnNgrscvPovA68vNfCLOx2kJvSsQOHTx+LVRqNr3tsmTkQTi1UO5qiQc17FCQmJ4ogivGXxhDosmA1Fp20PCbJz4/h9/HAwg33HkrEvdXPPTSPobxrEAXazTf8DezJ2ENocRmplOla7/8ZWRiYn6SButYthuaNQeTVs2tsLWRa456YWVKrAFhDVOBkgrCVEKKdIHkS+PIL+KkOb/4Vuzx6CPl6CZDbT8NST+OLje+DsXBjcAwbgGjAA09ff4Bo4ECk8vMf6/qk4ZwufhqX8QzQt+3AH+SuE6Jq2gxu06/LwxMZgnzAKZLeSTqpw2VFeXo5OpyMsLIy4uDjuuOOODtvm5+dTXFzM5MmTAxojoHdEcHDwWeuaKigoKCgoKCgoKHRGTUoS9nGjMW7ahDYnhyCTzIK7HFiDZBYtMXCirOdv2lyWwWhsuQhef1lLAYFech9KOIGN1rPs3X1qrNU4dQ7qv59AWnx1u200aokJg48xbuBx8os1vPCWkRMleobIQxl7eCLpZVm0GFrYnbmDfam7aTI2UhRVQL2llsyy3lgcVg4cT6Sq3sqY/nmEh0gBzdFEPSOEz7FQRY40hXx5FG23CZKEaeVKLB8sxpOYQMNzz15WwsQpWm+5GVkUCfrk0+6ZcHTAKXHuUHYOu0uNOOQghOIvOJSdzaHsHOSqH3DttiI2tbJ/2GAOHTnKoeycbvljKShcTKZMmcJTTz3Vpba/+tWv+Pd///eAxwjok3/y5MkUFhZSVlYW8EAKCgoKCgoKCgoKp2i96Xq8cbEEffgRYmMj1iCZhfPsmI0y/1xipKSiZwUKt2UIAhK6lv1tz2XJfZEFmePCkR4d6xQyMsWRhQgtFpy5vUiOremwrSBAVlIlT9/XhEYDry42sHG7HlFSkVSTwtgjE0gvz6TF2MTuzO0UxOQSVR9DXF0CVfUW9h1PIi2uivSE9gWQjginiGHCl4j42CvfSCWZP87J6cTy5lsY12/AMWYMTQsWIAcFdft8XEyk4GBsN1yP9tgxdHv2nJcxZFQUyYOxCjWEUoKRBoJq69HmuCnrnUVzZMTZO1FQuATw+Xw4HI62H7vd3va80+k8bdvP2+Xl5VFSUoLTGaB3CwGmdTz99NNs3ryZJ598kr/85S8kJycHPKCCgoKCgoKCgoICGg3N995LyIt/IWjxYpoef5xgi8jCu+288oGR1z428sTddmIjA4sC6AivPgGfJgxt8z6cIeMACCOcCDmSY8JhBsvDe2Scn9JkaqTZ1ETz2utIjGxApzl7ukp8lI9fPmDj49V6Vmw0kRjVlwmDj6HTQlJ1KnG1iZSGF9NiaKZXaV88HjWb9vbCbHAyZkBeF2cmEUQdkUIBSeyjhQgOytNx8WOEtKGpmZCXXkVVU0vLbbfiHDeum2fh0sE5diz63bsxf/El7t69kY2aHh+jgiyS5b2kCnuol+KQt2jx6PXkDT+zxKiCwqVKeXk5s2bNwuPxtD0nCAL79+9n8ODBXeqjvVKjZyMgcSI0NJS//OUvzJ8/n5kzZxITE0NISAhCBzWMBUHg008/DXhSCgoKCgoKCgoKVz6+qChabrsVy4cfYVyzBvvMmYRaZb9AsdjIPz408MQ9DqLDJXwSeL3g84HXJ+D1+f/2+oSTz4HXe/L5U21OtvdJAv0yvJgsQzDUb0TwOZBVBsBvjLlV3EQjDQTTs0aFxRGFiG4tDXtGMHhQbpf3M+jh/pudbN7lZvn6EJZ9N4QpQw8TEdKKWlKTXJ0K+LMTthzMwObQMWvsfrQdiR+yjyCqCaGcYKGCYCrQCH7DzEo5nSPyRCR+vFEPLS2n38bNiBo1TQt+gScjo/sn4VJCFGm5/XZCXngR87LlNN91a48PIaPihDyYXuIWzIcbEGpVHJsyEp9WqQjWHZQS8ReHhIQEHnjgARYtWtT23E+rcpyN6OhofvOb3wQ8bkDiRHZ2Ng8//DCyLCPLMuXl5ZSXl3fYviPRQkFBQUFBQUFBQQHANWIEztzjGNesxZ2WjCcjjbBgWHCXh1f/ZeV/3zACIMvndl15JN/DY7MGY6xbh7blIK7gkcBJcYJNHBeOMEIec66H00YDDdRYqxH2j0CDQEJkfUD7CwJMHO7E6zzOxt29WbV1ECP7FdA7ufxUIQjySiMpKItkSK8iokJbftxZ9qF2FKCxHUdjz0VjzyNS9IdY22Ur1aTRIMXQSOxp0RLIMgk5R8jYsRtbsBXnwseQw6PP9VRcUvhiY7FPnYpp3TocwwadlzHK6UVK0x50uyVa461UpySdl3GuBpQS8RePhQsXcttttwEgyzLXXHMN/fv35+WXX+5wH1EUMRqNWK3WDtt0RkDixEsvvYTD4SA6OpqbbrqJuLg4NJqeD4dSUFBQUFBQULjUUFbwzh8tt9yE79hxjO9+wI45N+Ix6AGYPlJPbon/5lglSqhECVGU/Y9VEkmJsajVatQqGbUK/4/a/1ilwv+8Gr7bpWXTDg3lU9KwqIPRNe9tEycsWImV4zkq5PSoOLFP3IMgi5RtnkRqbA0qVfdMGCNDWpg9cS+b92ax7VA6lXUWxg3MxenWsO1gOlGhTQzKKMRKNcFUECKUE3L0HUTZHxnh1cXgtA6joE5PAzG4MbU7juDz0WvrNmJz86lOSuDwxPH0CQvlSlxqtE+7Ft2+fQR98jni9TOQ1IFVNukUSSLuyHHUuwVkIGfMuLayogoKlxNqtfq0sqBz5swhJSXlnEqFnnXMQBofOnQIg8HAp59+SkSEYuiioKCgoKCgcPWgrOCdP2SdjuwpExm2YjV9Nm/lwPSpIAhYzU6G9S7qcL/+/cK7dN83ZZSb73Zr2LRTR+qgQegbvgfJBaIOgF5yHzaKa6mlmjCCz/l4HNjJEXIwlaTibg4mrX/Hx9AV9Fov00bmcDAvgT1HkqlrMqNXu1CJXh4f+iop4jFUgl84a5VDcQaPxGPqjceUgay2IMtuquo6/t/V2h30X/8twdU1FAweSOGQgVf2DbVWS+vcuQS/9hrJ+w9SMKxn/CDMdfX02roNa00tdXGxHBs7EofF0iN9KyhcbJ5//vnzPkZAMr7P5yMlJeWCCxNffPEFWVlZ7N69+4KOq6CgoKCgoKDQk4iihCy7A/4RxZ4xhbyUaQ0LJW/kcMJLy0g8FLgIBB2f3yCTi2H9XOw8qKFWPRhB9qBtOdC2PUvIQpAFjgqHe+RYDgh78QleGreNw2xwEhXafM59CgIMzCjhhjG7wOuhuimERwYtIspYSTm9OChN5zvpXnbIc2mNmYvbOhRZffYb46CaWoYvW0VQfQOHpk6kcOigK1uYOIknKxPH8KEkHcjGVN9wTn2JHg/pO3YzfNkqDC2tZE8ez/4Z1yjChMIVQ0VFRbt+E7m5uTz//PM89thj/PrXv2bVqlX4fGc3/u2IgCIn+vbty7Fjx/B4PBcsnWPfvn3813/91wUZS0FBQUFBQUHhfKJEX3ROae8sQsoqSNu1l8boqIBLL546v4IkYapvwFpTi6WmFnNdPSMzh7LDewefbA7niV56HCWbyZH917P9+/UlSZXCMeEwYxh9Tsfgxct+YQ/xnhS+P5bBgIySHrvXt1DF2Ii1TJ+sYVvTdFwRfdkpd3/VPyqvgN5bfsBt0LP7hpm0hoX2zEQvE1pvuh7VoWx6bd3GnhtmdkuU0R4+wqjPl2NotVGWlUHe8KF49bqA+1HSxhQuRT788EMWLVpEXV0dGzZsICYmpm3b0qVL+eMf/4gkSW3CxfLly3n33XdZtGhRtwIaAhInHn30UR566CFeeOEF/uM//iPgwQJl7dq1/PrXv26rq6qgoKCgoKCgoHAF38gIAkcmjGHElyvp9+137Jhzw9mrHMgyYn09mhMnUBcVMvToMYJq61CdXL1z63UIkkxW4UHiI6eRUxhHeUYa8arjCPiQUQF+Y8w14ioq6NjsvSscEbJxCHb0x8YgI5AWX31O/fmRiSOHTOEHXJg4rr0GXUQIgf8H+NHa7GT9sIPIE8U0REdyaOokPAZDD8zz8kI2m8gdOZy+m7cSd+QYZX16dXlfsakJ0xdfot+/n9ZgK7uvn0FTdFS356IIlwqXGn/+8595991324SHpqamNnHi8OHD/OEPf0CSJAwGA7fddhvh4eGsXbuW7OxsFi5cyJIlSwIukBGQOBEWFsbtt9/O4sWL2bJlC+PGjSMqKgpDJx9m8+bNC2hCAJWVlfz1r39l+fLlGAwGwsPDqa2tDbgfBQUFBQUFBYUrkSv5Rsar05EzeQJDVn1D7y0/kD1l4mkr2mqXC8vJiAjrDzvQFJcitrYCIGvUuENDKeudRVNEOM2R4TjNZlL37CPpQDZDB+exvHoEm0umcm9KDqFyKXX4KymkyZmoZDXHxKOE070KFTIye4WdRMpRHNuWSZi1hZCgc1tkE/HQS/iOGCGXWjmRHHkqXgJfmfdPUCbu6HHSd+5BkCRyhw+lpH8fZPESFqzOM5XpqUTn5ZO+ay+1SQm4TO0bhrYhyxi2/oBp1TcIXi+t101nZ1QEskp1YSasoHAByMnJ4d1330UQBBYsWMDcuXOJivpRfHvxxReRJAlBEFi0aBEjR/oNhh966CF+8Ytf8N1337Fq1SpuuOGGgMYNSJyYPXt2W33TwsJCioqKzrpPd8SJl19+meXLl9OvXz/+9Kc/8d///d+KOHEVc8WuDikoKCgoKCi0S1NUJAXDBpO+ay+2fQfx6LR+MaK6FmOz379BBnzRUbj69sGbmIQ3OQlPdBiHjhw9o7/axARS9h+ir/0wWyx92JHfnzuTdEQKBdTJfnFCh45U0skVjhNKJGJg1mwAFJJHvVDHmKab2FmhYUTf4nM6Dyp3DcOELzFTT740nCKGQDfrZxgbm+i95QeCq6qpj43m6NjROKyKJwKCwLGxoxj5+Qoyt+3k0DWTO2xqrqun1/fbCaquwZ2ZScvc2/CFW5G7IRQqKFzKfP755wA8++yzPPTQQ6dtq6mpYfv27QiCwIQJE9qECfCXEv23f/s3Nm/ezOrVq8+vODF8+PCAOu8uqamp/N///R833ngj4lWs5Cr4uZJXhxQUrkYUwVFBQaErnBjQj5DySlL37gfAZTTQFBFOeVY6zRHhNIeH0WfI4NO/60+Wz/w5zRHhuAx6IkpK6J9RyuZ9vdhaPZXxURs4yo/mbb2kPuSqjtIQVE9YS3jAc94j7sQsB1G7tz+CIJMaVxNwH6fQNh8gqOxdfEjsl2dRT0L3OvJ6Ma5fz8g16/Fp1ByeMIaKjPSrwvSyqzgsFgqHDCR9117CTxRTm5R42nbR6yVl7wESD+Xg1WlpuvsO3MNG+s9hB/9zCgqXMzt27ECn0zF//vwztm3durUtamLGjBlnbE9LSyMmJoajR88Uis9GQOLE4sWLAx6gOzzyyCMXZBwFBQUFhQuPIjgqKCh0CUHg0NSJBFdW0RoWevZw+7P0VZcQT0TRCdImVLHrSApr86YyJforguUKYAAAyaShlXVUhZQHLE5UUUWpUMx43xS+OqQnM9mDSd+NG1fZh6n6S4y13+DRJ7LTPh4nQYH3A6iLigj6eAnqykqqUpM5PmoEbuPl7y1xPkTu4v59icovJOv7HTTERLd5nYSWlNHr++0YWlspz0wnd8RQeg8bEnAuvYLC5UR1dTUxMTFo2/H82bFjR9vjMWPGtLt/RETE+RcnLmWam5tpbj69TJNWqyUyMvIizUhBoX2UVWMFBQUFBYWu4dNqqUvsZsTAz6hNjCf2eB6h1ZX0TS1j1+FU8hvSiAwuaGujRk26nM4x61GyBB8ques+AnvF3WhlLZaywdQ1ikwf7wp4jhocBJ94Da39OI6Q8bREzcF5+HjA/QhOJ6avVmLYshXJaqXx4fvIbqcM4MWgJ66DzofILYsiR8eNZtiKr0jbvY+iQQPI2L6T6IIibFYLe2ZNpzGme14kCgqXG263G0sHpXB37twJQGJi4mk+FD+ltbW1U1/KjrhixIn333+fV1999bTnhgwZwscff0xIyDko7Vcpzc3NmIyBr1Dq9RoslqAe66Mn+7lUaG5uJjc3N+D9+vTp0+PHcym9RpfSXLwt7m72oSYiyNijc7mUzsuVOJeeQDkvlz5X4mt0Kb3Wl8t5caYnI20UiSkvZ8ioOvYfT2J5wa0sHPp3nDoVFqu/nwGN/Tks5dAa0UBsa2yX5mFX2zkuHmOsfizHcsPQamDEAJmC/K4fk1mqJMP9FRqHC7IewRAzCU83zktwYTFhny9HbGyCayejuv1mRI8H0+HDAfUD5+//5Vyvg87X/4svOY7KgX2JP5BDTF4BotdLycihlA8diKxWYWqnnyvxPX0poZyXi0NYWBjV1WdWGiosLKS8vBxBEDqMmmhtbaW4uJjExMR2t3dGQOLE1KlTA+pcEATWr18f0D7d5d5772XOnDmnPXcqDKWhwYbXK12QeVwpyLIHmz3wUESn04PL1dJjffRkP5cKl9LxXEqv0aU0Fyeqbvbhpcb540rZlXZersS59ATKebn0uRJfo0vptb6czkt9bAzWghN4hw4hM7GCPYX9aemtR2w4To27NwCRcgxaWcsJYwnW6q6ldhyPzUWQBdKbB/LFXpl+GV7o8jGdXia0IeUZfOo0qGkJ6Lxo7Y62lX5vdBRNTz2JNyUFWr3K/0s7fXTUz7GBA7EUleAyGTk2ZhT2YCu4ff6fCzyX7vRzpXGlnxe1WrwkF9IHDRrE119/zdGjR+nV68cSuytXrmx73JE2sGzZMrxeL4MHDw543IDEibKysi61O1XR40JisVg6DD1RUFBQUFBQUFBQqE2Mp9cPOzA2NdM3tYzDhbF8XTCTm+MP4DX5xQkRkcjGGMrDSvCKHtSSptM+PSoP5WGlZMiZlOWHYHcIDOvn6dJ82isT2tuQEFg9DlkmJjePjB27UXm85A8dRNCdcxE0xrPvq3AGPq2G7bfOVgxDFa5qbrrpJr766iuee+45Xn75ZTIyMti+fTvvv/8+giAQGxvbbuREdnY2f/vb3xAEgWnTpgU8bkDixKJFizrc5nA4qKmpYcOGDezYsYMnnniiXXdPBQUFBQUFBQUFhYtBXUI8sIPw4hLsA6wkx9SysWgqs/v9BqLlthvS6IYYSiNOUB1cRWx9fKd9loeW4lP5GOodxtfZGkxGiV6pvk73ATDQRH9hzTmVCTU0N9Nr63ZCyytojIrkyLjR2EOC6a/u+cztq8ozSxEmFK5yJk6cyMyZM/n666+58cYb0Wq1uN1uZFlGFEX++Mc/nlZVc82aNW3lQ10uF2PHjmXixIkBjxvQJ9ekSZPO2mb+/Pn85S9/4dVXX2XgwIGMGzcu4EkpKCgoKCgoKCgo9DTOIDMtoSGEF5dSPKAf/dNKKSwfwua8QYxJPYHXkAyAxW5F7zJQFVzRqTghCRIlEUWEtIQSJESTnatm1CAPKhV0FkQcThF9hI2A0K0yoYLPR0LOEVL37PcbOY4dRVmvzPN6U61UWlJQuLp48cUXiYuL48MPP8ThcAAQFRXFb3/7W8aOHXta2xdeeIGysjJkWWbQoEG89NJL3RrzvBhiPvHEEyxZsoS33npLEScUFBQUFBQUFBQuGWoT40k6kI3a6SIiBGLC6vkmfwYTGr9uEycEBKIbYiiKKsCldqHz6trtqyq4EpfWRa+Sfhxs1OLxnj2lI4XdpIq7aZYjOCRP63KZUJXHQ1hJGRFFJwgvKUPt8VCTlMCxMSPPrcyqgoKCQjuoVCp++ctf8vjjj1NUVIRarSY1NRWV6swqRgMHDiQ9PZ3rrruOWbNmtdumK5wXcUKr1ZKYmEh2dvb56F5BQUFBQaFHuKrClBUUFACoTUwgZf8hwkrLqEpPpW9aOet39uPAYYms6B/DHaIaYyiKLqA6uJKE2qQz+pGRKY4oxOQwE9YSzpZsHeEhEkmxHZuwh1JCqribCjmTo/IEpLNcigs2GzHH84goOkFoWTkqn4Rbr6cqNZmq1BQaYqOVFAQFhauYL774gn//93/nww8/ZNiwYWds379/P//85z/Zt28fdrud6OhopkyZwuOPP47Vau3SGP9/e/cdVmX9/3H8eQ5ThuIABRQVByjuEbgz7WtDSy0zLSu3ZtkwbXyzLG0vK9M0zdK0vk23v0pz75UoOHEgDhBliGzO/fvDPEXgPnAO+Hpcl9cl93zd9zn3zeF9PvfnU6ZMGerVq3fZZT744IPryv9vRVKcyM7OJi4urtg7xRQREbkWaqZcOBVtpDRL9a1Etrs7lWKPEV87mKDKZ6lcLo2le9tRr/UJ8tx9AfDK9MYrw4v48icLLU4keZ0lzeMc9WIbkJ7hxsGjznRpl33JWoGJPEJMa0k3yl62MGFOScFt1z7cIiNxOXgQX4uFTE9PjoeGcLpGEMmV/cCs60zkZrdjxw7Gjx9/yfnLli3jqaeeIjc3l0aNGuHr68uuXbv4+uuvWblyJd999x0VKlQoxsRXZvPiRHx8PO+88w4pKSm0bNnSJtucPXu2Tbbj6PRhUEREHIGKNlKqmUwkBlXF98hRTBYLmM3cGp7J/34L5uj+ZVRt5GtdtHJSADEB+8lwTadMdv7RL2L9DuOa40rlJH+ij/thYKL5ZR7pqM6feJhS2GG5u0BhokxKKr5HY/E7Eku5hNMA5Pr5kd7pVqI8PThXsYJaSIiI1W+//cYLL7xAenp6ofNzc3N59dVXsVgsfPrpp9aRM7KysnjqqadYsWIFn332GWPHji3O2Fd0TcWJVq1aXXKeYRhkZ2dbO8swmUw8+uijN5buJqMPgyIiIiJFLzGoKgH7D1LuVALJAVVo3tjEklXnWbY9gMca/b1c5eQqxATsJ97nJDUSalmnp7mf40zZRIJP1sHJcOJgnB/VA3Lwq1B4q2F3Uqlh2k68EXyh80vDwOtsEr5HYvE9Eot3UhIAqZUqknZXF7IbNyWvShUMI5tz1/HZUERKp1OnTvHhhx8yf/58ypQpQ6VKlUhMTCyw3L59+0hMTKR+/fr5hvR0c3Pj8ccfZ8WKFWzZsqU4o1+VaypOJP1147yScuXK8eSTT9K5c+frCiXiqNS6RUREpOQ7GxiAxWymUuwxkgOq4OoCHRrEsmhbfU6fPGRdrky2B+XSfIgvn784Eet7BLPFTNXEapxN9eBsqhcdI85fcn91TeswMHHAaE213dFUjd6LR+o5DCC5ih/7I1pyunoQmd5e+tJJRC5p4sSJzJ8/nwYNGvDmm28yYcKEQosTF4f5PHPmDLm5uTj/Y3jhi3/TX22fE8XpmooTs2bNuux8JycnypUrR3BwcL5xT0VKC7VuERERKfnyXFxICqiCb2wcByMuPIbcOtyLX3dks3qDhbp1/162crI/+6vuIc39HF6Z3mQ5Z3Kq/AkCz1TDJc+VmDg/TCaDpvWyAJcC+6rEEXxNRzlgicD5bA51N24h2c+Xo40akBhUjWyPMsV01CJS0gUHB/POO+9wzz33XPbv7dq1a+Pv78/JkycZM2YMTz/9NL6+vvz555+89tprmM1m+vfvX4zJr841FSduueWWosohIiIiIlJsEoOqEbJ+Ex7JKQB4lvehdY0/Wb+/KdWqn6aM24X+IyonV+FA4F7ifU7idcqbuEqxGCaDaqerYxgQc9yPQN+zeBUymqeZHOqa1pFmlOcYDakbvZk8Jyd2/uc2ct3di/NwRcSBnTx5kry8vHzTypYtS9myZfNNGzJkyFVtz8XFhU8++YQnnniCxYsXs3jxYus8Pz8/vvjiC9q2bXvjwW1MzRtEREREbkJmswXDyL7mf2bzpYfKLEkSq1UFoFJsnHXabS3OkmNxYf/hitZprrlulD9XkVPlT5JrziWu0jF8Uyrjke3JqTPlOJ/hTu2qCYXuo4ZpB2VM59hntMMpKxf/g4eIr1VThQkRyeehhx6iU6dO+f59/fXXN7TNoKAgunXrhpOTE40aNaJjx474+vqSkJDAjBkzSE5Otk14G7pky4l33333hjduMpkYPXr0DW9HRERERGzrZn9UMdPbi3MVylMp9hgXx9ioGFSbppW3E32kHmF1EnB2ulCIqZLkT3T1XeyrGkWucw5BCTUAOBjnh4tTLtWrnAH88m3fKSuB6vzJSaMOyQRQbX8UTrm5HAurV3wHKSIlwpw5cwptOXG9kpKS6Nu3L/Hx8cycOZPw8HAAsrOzef311/nhhx8YMWIEc+bMuaHctnbJ4sSXX36J6QaGLDIMQ8UJO1CHjSIi4gj0+0hKgsRqVakeuZsz6eng6UqeW2XurP8bO1Y04+CxyoTWOAmAb0plzJYoTlU4SbnzPviklyc3z8SRE75U9z+Ds/O/WpMYBt6nfsCCMweNVmCxUDV6L8mV/UirWMEORyoijszf39+m25sxYwaHDh1i9OjR1sIEgKurK6+++ipbt261/mvRooVN930jLlmc6N69+w0VJ8Q+bvZvQW4m+uAvIo5Mv4+kJEisXo2aO3fhumcf2S0ufICvEexNze2H2B0TQEj1k5hM4GxxpmKqL6d94q2tJo7FVyQ715naVeMLbNc1dTuu5/eyz2hDNh5UjDuGx7k0Ylo2L87Dk5uMPhvKRZs3bwagTZs2Bea5uLjQunVrDh8+THR0dMkoTrz99tvFmUNErpE++IuIiNyYVN9KZLu74xa1x1qcyCrXhLvrLGbS1ic5Fl+BoCpnAagRH4xbjhu+KZUBiInzo4xbFv6+yfm2acrLxOvU9+S4V+V4ehgA1aL2kunhwekaQcV3cHLT0WdDuSg1NRW4MJpmYS5Oz8nJKXS+vdikRJadnW2LzYiIiIiIFB+TicSgqrju2Qd/Pe+d5+ZPA/+9lC+TxK6YqtZFy2aUI+R4fUyYyMp25lhCBYIDT2P+V0Njj9OLcMpN5lyVBzAw45GcQsXjJzhery7GZYb+E3EUN3tnuaVBcHAwAKtWrSowLy8vj40bNwIQGhparLmu5JqGEr3ozJkzfPXVV6xcuZLDhw+Tl5eHk5MTQUFBtG3bloEDB1K5cmVbZxURERERsanEalUJ2H8Ql0OHyKlTB0wmzpprcGfwEuZGPcTpJC98y6flW+fwiUpYLOYCo3Q4ZR6nzJnlZPi0JdejJhBF1ei9WMxmjofWLcajErl+aoFR8vXu3Zvly5fz+eef06xZM5o3v/BIWW5uLu+99x779++nTp06RERE2DlpftdcnNi2bRtPPvkkSUlJGIZhnZ6bm8uhQ4c4fPgwCxYs4JNPPuGWW26xaVgREREREVs6WzUAw8kJ191RF4oTQIJRk9tqLOWnfb3YFVOV21rszbfOwbjK+Hidp2K5fxQtDAOvk3MxnMpwvnIPAJyys/E/cJD44BrklClTbMckIje3Dh06MGTIEKZNm8ZDDz1EkyZNqFChAnv27OHEiRNUqlSJiRMnXvKxD3u5puJEQkICjz/+OCkpKYSFhdG3b1/CwsLw8PDg3LlzREVF8d133xEdHc3TTz/NvHnz8PPzu/KGRYqYOggSERGRwuS5uJBdpxau0VGc79EdgHP4YnJ2ok2NjayIace59MN4e2RdmJfuRvzZcjQPPcw/+453T9mMa/pBzgX0w3D2AiMb/wMxOOdo+FARKX6jRo2iWbNmzJ49m127drF79278/Px4+OGHGTp0qEP+nX5NxYnp06eTkpLC3XffzXvvvYf5X8/NhYWFcf/99/Pcc8+xdOlS5syZwzPPPGPTwCLXQ83TRERE5FKyw+rj/dM8nBISyPX1AUycpib3BP/Eipi2RB0KJKLBIQAOHb/wgb7WPx7pcCYLr/j55JSpSaZP6wsT/xo+NMW3Eud8KxXzEYnYl74YLB6zZ8++7PyOHTvSsWPHYkpz466pOLFq1Src3d157bXXChQmLjKbzbz22mssX76cZcuWqTghIiIiIg4tK6we3j/Nw3V3FLkdLwy9l2AE08JjF/UDDrH/aA2ahhzF1TmPg8f8qFwhxdqSAiDYtBlTXhpp/iPBdOEzsuu+A3impLL71nZ2OSYRe9IXg3I9rqksdfLkSWrXro2Xl9dll/P29qZ27dqcOHHihsKJiIiIiBQ1S4Xy5Pr74xq12zothcpkGWW4o/av5OQ5s++oP2dSPUlO88zXEaY3p6lKNBnl25Fb5u+hQsusWUdWGXcSalYv1mMRESmprqk44erqyrlz565q2bS0NJydr2swEBERERGRYpXVoAEuhw5jSk//a4qZ09Sksc8m/CslEXUokAOxVTCbLNQMOP3XMgYhpjVk4855v7ut2zInJuK6Zx/HQ0MwHKzDORERR3VNxYmQkBBiY2OJjIy87HI7d+7k6NGj1K2rIZNERERExPFlNwjDZLHgumefdVqCEYyzKZc2tbaRnunGnsMBVKt8FjfXC8/SB7CHcqYEDhqtMJw8rOuVWbMGTCYNHyoicg2uqTjRo0cPDMPgqaeeYteuXYUuExkZyVNPPYXJZKJ79+62yCgiIiIiUqRyg4KweHnhFrXHOi0Zf3IMN8Irr8XH6zwGJmtHmC5kUNu0iSTDn1PU+XtDWVm4b9pEVuOGZHt6/Hs3IiJyCdf03MV9993HwoUL2bRpEw888AD169enfv36eHp6kpaWRnR0NHv27MEwDCIiIrjvvvuKKreIiIiIiO2YzWTXr4/rrl2YmjTEMJsxcOI0NfAzHaZFvUPsPFidapXPAFDLtAkncthntAP+HlPUfctWzBmZpLdvA+fP2+lgRERKnmsqTphMJqZNm8a4ceOYP38+UVFRREVFYTKZMAwDuDBaR48ePRg7duwlR/QQEREREXE0WQ3CcN+8mXLxCST7VwEuPNoRYN5HU/+dVPdPAqAcpwg07eWo0ZjzVPh7A4ZBmTVryKlaldwa1SEq2h6HISJSIl2yOPH888/To0cPIiIi8k13c3Pjrbfe4oknnmDNmjUcOXKE8+fP4+HhQc2aNWnXrh2BgYFFHlxERERExJZyQi50YFkp9pi1OHGWquQaLviZDnHWCMKEhRDTGjINTw4bLfKt73LgAM6nTpHatw+YTIXtQkRELuGSxYn58+ezYMEC/P396d69O927dyco6O/hkQIDA3nwwQeLJaSIiIjcnMxmC3l5ude8npOTMxaLWnDKtTHc3cmuXYtKsXEcDG95YRpOJFIdX46wFwuBROFtOsMuy+3k4ZJv/TKr12Dx9CSrWTPAsMMRiIiUXJcsTnTu3JnVq1dz4sQJpkyZwpQpU2jWrBk9evTgzjvvxNPTszhzioiIyE0oLy+XXbujrnm9hg3CMJlciyCRlHbZDerhvW8/ZVJSyChXDoDTRk2qmA9S2ThELdMWzhhVSSA433rms0m47t5NRqdO4OICRrY94ouIlFiX/Eph0qRJrF+/ngkTJtCyZUtMJhPbtm1j7NixtG3bljFjxrBhw4bizCoiIiIiUqSywuoDUCk2zjotkSDyDGfqmVZgJpd9Rlv+2QkmQJm1G8BkIqNtm+KMKyJSaly2vaOXlxf3338/s2bNYsWKFYwePZrQ0FAyMjJYsGABAwYMoGPHjkycOJGjR48WV2YRERERkSJhqVCec+XL4/uP4oQFF85QDSdTHkdpSgY++dYx5+ZSZuNmshs2xFK+fDEnFhEpHa76YczKlSszcOBAfvnlFxYvXszQoUMJCAjg5MmTTJ06lTvuuIO+ffvyww8/kJaWVpSZRURERESKzJmgqpQ7FY9zVpZ12jGjIQlGMEeMpgWWrxxzGHN6Ohnt2xVnTBGRUuW6eoqqVasWzzzzDMuXL2fu3Ln07t0bHx8ftm/fziuvvELbtm157rnnWLduna3zioiIiIgUqdNBVTEbBhXjTlinJRPALuM/WP7dZZthUC1qD7n+VcipVauYk4qIlB433I11s2bNGDduHGvWrGH69On07t2bsmXLsmjRIgYPHmyLjCIiIiIixSbVtxLZ7u5Uij12xWV94hPwPptEevs2Gj5UROQG2GyMLWdnZ/z9/QkMDMTf3x8Aw9AQSiIiIiJSwpjNJFYLpGLccUwWy2UXrRq1hxw3VzKbF3zcQ0RErt4lhxK9WkeOHGHJkiUsWbKEmJgY4EJRomHDhnTv3v1GNy8iIiIiUuwSg6oRcCCGcvEJJPtXKXQZt/Pn8T0Sy7EG9SnjqqFrRURuxHUVJ44fP86SJUtYunQpe/bsAS4UJKpUqUK3bt3o3r07tfTMnYiIiIiUUGcDA7CYzVSKjbtkcSJwzz5MhkFc/RDqFHM+EZHS5qqLEwkJCSxdupQlS5YQGRkJXChIlClThs6dO9OjRw9atWqFSc/aiYiIiEgJl+fqQpJ/FSrFHuNgeIsC8825eQTuPUBiUDUyvb3tkFBEpHS5bHHi7Nmz/PrrryxZsoRt27ZhGAaGYWAymWjRogU9evSgS5cueHp6FldeEREREZFikRhUlZANmymTkkpGubL55vkdPoJrZibHwkLtlE5EpHS5ZHFi4MCBbNq0iby8PGvHltWrV+fee++le/fuBAQEFFtIEREREZHilhhUjZANm6kUe4xjDcP+nvHX8KHnfcqRFOBvv4AiIqXIJYsT69atA6Bs2bLccccd9OjRg6ZN1QuxiIiIiNwcMr29SCvvQ6XYuHzFibKnEymbeIa9rcM1fKiIiI1csjjRoUMHunfvTqdOnXBV78MiIiIichNKDKpGUORunLOyyXW78Jm4WtQecl1cOFVHHcCLiNjKJYsTU6dOLc4cIiIiIiIO53RQVWrs3EXFuOPE16qJa3oGfoePElcvhDwXF3vHExEpNcz2DiAiIiIi4qhSfSuR7e5GpdhjAATu3YfZYiGuvjrCFBGxJRUnREREREQuxWwmsVpVKsYdx5ybS+Ce/SRWDSwweoeIiNwYFSdERERERC4jMagaLlnZ1Nm0FbeMDOI0fKiIiM2pOCEiIiIichlnAwOwmM1U3bOP9LJlOVM10N6RRERKHRUnREREREQuI8/VhST/ygDE1Q/R8KEiIkVAxQkRERERkSs4Wac2GV6enKhb295RRERKpUsOJSoiIiIiIhfE1w4mvnawvWOIiJRaajkhIiIiIiIiInal4oSIiIiIiIiI2JWKEyIiIiIiIiJiVypOiIiIiIiIiIhdqTghIiIiIiIiInal4oSIiIiIiIiI2JXDFifWr1/PI488Qnh4OM2aNaNfv36sWbPG3rFERERERERExMYcsjjx888/079/f3bs2EGjRo1o2rQpO3bsYNCgQfzvf/+zdzwRERERERERsSFnewf4t4SEBF599VW8vb2ZO3cudevWBSAyMpL+/fvzxhtvcOutt1K5cmU7JxURERERERERW3C4lhPffPMN2dnZPPbYY9bCBECjRo0YNGgQWVlZaj0hIiIiIiIiUoo4XHHiYr8SnTt3LjDv9ttvB2D16tXFmklEREREREREio5DFScMw+DgwYOYzWaCg4MLzK9RowZms5mDBw9iGIYdEoqIiIiIiIiIrTlUnxMpKSlkZ2dToUIFXF1dC8x3dnamfPnynDlzhvPnz+Pl5WWdl5qaSmpqar7lXV1d8fPzw8nJoWowl2QYzpQr533N6zk7O2MymW22DWVRlps9ixtm/L0L3oOuxM3ZjDN/F05L23lRFmVRFmVRFmVRFmUpaVkcWUn5O7W4mAwHaoJw8uRJbr31VgIDA/njjz8KXea2227j+PHjrF69Ol+nmJ9++imTJk3Kt+yDDz7Ia6+9VqSZRUREREREROTGOFTLCbP5ypWjS9VSHn30UXr06FFgenp6Oh4eHjecTURERERERESKhkMVJy4WEbKysi65zMV5ZcqUyTe9bNmylC1btujCiYiIiIiIiEiRcKiHXLy8vPDw8CApKYnc3NwC83Nzc0lKSsLNzU2FCBEREREREZFSwqGKEyaTidq1a5OXl8eRI0cKzD98+DAWi4W6desWfzgRERERERERKRIOVZwAaNeuHQDLli0rMO/itA4dOhRrJhEREREREREpOg5XnOjZsydubm588cUX7N692zp9165dTJ8+HXd3d/r27WvHhCIiIiIiIiJiSw41lOhFc+bM4fXXX8fFxYWIiAgMw2DTpk3k5ubyzjvvcO+999o7ooiIiIiIiIjYiEMWJwBWrFjB9OnTiY6OxtXVlZCQEIYPH06rVq3sHU1EREREREREbMhhixMiIiIiIiIicnNwuD4nREREREREROTmouKEiIiIiIiIiNiVihMiIiIiIiIiYlfO9g4gtpeens7Bgwc5c+YM6enpGIZBmTJl8PX1pXbt2nh4eNg7Itu2bePYsWN07969WPaXlJRE+fLl8007evQomzdvJikpiQoVKtCiRQtq1KhRLHlKwmvkKHbu3El0dDS5ubmEhYXRrFmzItnPpEmTqFevHp06dSqS7V8vi8XC7t27iYmJ4ezZs2RnZ+Ps7EzZsmXx9/enQYMGVKhQwa4Zi+s1upLIyEh2795NZmYmVapUITw8nIoVKxbJvhz1/VIS6Jp2/GvaUeiaLhl0TeuavlrFeU1LyaQOMUuR33//nVmzZrF9+3YsFkuhyzg5OdG8eXMGDBhAhw4dijnh30aPHs2iRYvYs2dPke5n9+7dvPzyy2RkZPDrr78CFwoDr7zyCosXLy6wfJs2bXj99dcJCAgokjwl6TUqLhaLhV9++YU1a9bg5OTEvffeS/v27cnKyuLJJ59kzZo1+ZZv3LgxEydOpEqVKjbNERoaislkon///jz77LM4O9u3dmsYBnPnzuWzzz4jKSmpwDyTyQSAyWSiRYsWjBw5khYtWhRJFkd5jR566CHatm3L8OHD800/cuQIzz33HFFRUfmmOzs788ADDzBmzBjc3NxsmsXR3i+OxFHeL472GjnSNe0odE2XDLqmC6druiBHuqalZFJxohQwDIPnn3+ehQsXYhgGFStWpGbNmvj6+uLu7o5hGGRlZXH69GkOHTrE2bNnMZlMPPDAA4wbN85687SFLVu2XNVyU6ZMYcOGDcyePZt/vgVbtmxpsyy7d+/moYceIisri7CwMH766ScA+vfvz4YNG/D09OS2224jICCAxMRENm3aRFxcHAEBAfzwww82reQ60mvkSCwWC0OHDmXt2rXW94HJZGLs2LEcPnyY2bNn4+vry6233oqrqysbNmzg0KFDVK9enZ9++gkvLy+bZQkNDbXuv27durz22ms0adLEZtu/Vi+++CLz5s2jfPnyNGjQACcnJ6KiokhISKBHjx7UqFGDQ4cOsWnTJk6dOoXJZGL06NEMGDDApjkc7TW65557ePfdd63TEhIS6NmzJ4mJiVSuXJmIiAgqVapEXFwc69at4/z587Ro0YKvvvoKJycnm2YBx3m/OApHe79c3L8jvEaOck07El3Tjk/X9KXpmi7Ika5pKZlUFi4F5s6dy4IFCwgJCeHVV1+9YnO6bdu28dprr/H999/ToEEDevXqZbMs/fr1u6Y/pPv162f9v8lkIjo62mZZPvvsM7Kysnj++efp378/AMuWLWPDhg2EhoYyffp0KlWqZF0+JyeHd955h2+++YYpU6bw8ssv2yyLI71Gn3/++Q2tP2zYMBslgTlz5rBmzRoaNGjAoEGDSEtL4/PPP+f999/HbDbTuHFjpk+fjre3NwC5ubmMGzeOH3/8kRkzZvDUU0/ZLAtA586d8fT0ZP78+fTp04e77rqLxx9/nFq1atl0P1eyePFifvnlF7p27crrr79ufcwnOzubCRMmsHjxYubNm0e1atUAWLFiBa+++irvvfce9evXJyIiwmZZHO01+rdJkyaRmJhI165dmTBhAu7u7tZ5Z8+e5cUXX2T16tXMmjXLeh+wFUd5v+iavjRHeY0c6Zp2pPdLYXRNQ5cuXW5o/YstRW1B13ThdE1fPXte01LyqOVEKXDPPfcQHx/P//3f/xXoV+FSzp49y5133klgYCA///yzzbIMGjSItWvXYjKZqF27dr4//v/pwIEDnDlzpsDNeebMmTbLEh4ejr+/P/PmzbNOmzBhAnPmzGHu3Lk0bdq0wDqGYdClSxdyc3P5448/bJbFkV6jRo0akZOTY/35n00PL+ficrZ8FKdnz56cPHmS33//3frtypEjR7jrrrswDINvv/22wLci2dnZ3HbbbZQtW5YlS5bYLMs/q/0LFy7knXfeITExEbPZzG233cagQYOK7Ruavn37EhcXx7Jly3B1dc03Lycnh9tvv51bbrkl3zcThw4d4p577qF169ZMmzbNZlkc9TW6qF27dlgsFpYvX57vA89F6enpdOrUCT8/P+bPn18kWez9ftE1XThHeo0c6Zp2pPeLrunCPfLII2zevBmTycS1fkzXNd3kituxBV3ThXOka1pKJrWcKAViY2Np3779Vf/RC1ChQgVuueUW1q1bZ9Ms06dPZ+7cubz33nskJCQwbNgw7r777gLLXexzwpbFiH/LyMggKCgo37Tc3FwAQkJCCl3nYlPB1atX2zSLI71G8+bN44knnuDQoUNUq1aNe++916bbvxaHDx+mVatW+Zp91qhRg0aNGrFz507q1atXYB1XV1caNmxo8/PyT926daNTp05MmTKFb775hmXLlrF8+XKqVq3KXXfdxe233079+vUxm4tmwKMDBw7QsmXLAh94AFxcXKhfv36B4w8ODiY8PNymrY/AcV+ji86dO0dEREShH3gAPDw8aNGiBWvXri2yDPZ+v+iavjJ7v0aOdE070vulMLqmYdasWbzzzjvMnDmToKAgPv/8c7s9j69runC6pq+eI1zTUnKoOFEK+Pj4cObMmWteLyEhodCb6o3q27cvbdu2ZcyYMTz33HP8/vvvjBs3Dh8fH5vv63KqVq1KZGQkubm51k6TwsLCADh48CCNGjUqsI7FYiE6OhpfX1+bZnGk1yg4OJhvvvmGPn36EBsbS2hoKJ07d7bpPq6W2WwmLS2twPQWLVoQFxdHcnIylStXLjA/OTm5yD+oeXh4MGrUKAYNGsTcuXOZO3cux44dY9q0aUybNg13d3fq169PtWrVqFKlCk8//bTN9m2xWDh58uQl5589e7bQ8+bs7My5c+dslgMc+zUCqF69er5vjAqTlJRUZB9QL7Ln+0XX9NXRNX2BI71fCqNr+oLnn3+e1NRUfv75Z7777jteeuklm27/aumaLpyu6avnKNe0lAx6F5QCzZo1Y/v27SxatOiq1/nhhx/YuXMn4eHhRZIpKCiIb7/9lqeffprly5fTtWtXmz4mcTXuuOMOTp06xQsvvGC9Kd599934+/szfvz4Ar80LBYLb7zxBidPnuS2226zaRZHe40qVKjAp59+iru7O6+//joZGRk238fVCAsLY9u2bURGRuab/txzz7F27dpCP/Bs3ryZP//8k4YNGxZLxnLlyjF8+HBWrVrF119/Td++falatSoZGRls27aNefPmMXXqVJvus379+uzdu5dly5YVmBcZGUlkZGSB52tjY2PZvHmzzZ+7dbTXaP/+/SxevJjDhw8DcO+997J582ZOnDhR6PLbt29n+/bt1K9f3+ZZCmOP9wvomr4WN/s1DY7zfgFd05fz6quvUrNmTebMmcPBgweLZB9Xomu6cLqmL83Rr2lxbGo5UQqMHDmSVatWMXr0aH788Uc6depEnTp18PX1pUyZMphMJjIzM0lMTOTgwYMsW7aM9evX4+npyciRI4ssl8lkYujQoXTo0IExY8YwYsQI7r33Xpt2NHk5gwcPZtmyZSxatIhdu3bRt29fGjZsyEsvvcRLL73EHXfcQdeuXQkMDCQhIYHff/+do0ePUqlSpQJDIN0oR3yN6taty8CBA5k0aRIzZ87k8ccfL5L9XM7AgQPZvHkzjz76KL1792bIkCGXHAv8wIEDzJ8/n1mzZgEUe6dJZrOZ8PBwa7EoOTmZXbt2ERcXx9mzZ226r0cffZQtW7bw7LPPMnDgQDp27Iinpydbt27lo48+wjAM+vbtC0B8fDzfffcdc+fOJTMzM18ns7bgaK/R3r17ee6554AL35rVqFGDnJwchg0bxqxZs6wttA4cOMDSpUuZOXMmhmHw8MMP2zzL5RTn++UiXdPX5ma9pi9yhPcL6Jq+HFdXV1544QWGDBnCpEmTmDhxYpHs53J0TRdO1/SllZRrWhyTOsQsJfbu3cuYMWPYv3//FTvBMQyDOnXq8MYbbxT6aENRyMnJYeLEicycORM/Pz98fHzYt2+fTTvhKUxKSgpvvvkmCxYsKDDvnx0GXbwMQkND+eCDD4qkqu2Ir1FmZiZLly7Fx8eHjh07Ftl+LufHH39k3Lhx5OXl8fvvv1O1atVCl3vuuedYtGgRJpOJp59+mqFDh9o0R2GdONnThx9+yLRp0wq8VwzD4IEHHuD1118HYP369QwYMABnZ2eeeeYZBg4caPMsjvIanTp1iujoaKKjo9mzZw979uyxfhNjMplYtmwZgYGBwIWC4G+//QZc+ID8/PPP2zSLo71fLtI1/TdHe40c6Zq+yN7vF13TJYOu6cLpmi7Ika5pKZlUnChl1q1bx5o1azhw4ACnT58mIyMDs9mMh4cHfn5+1KlTh3bt2nHLLbdc05CftrJt2zZeeOEFjh07ZvMegi/n5MmT/Pbbb0RHR3P06FHS0tLIysqiTJkyVKhQgbp169K+fXtat25d5M+8OfprZA/x8fEsXbqUxx577JLLfP/99+zevZtevXoVSVPRfv360bZtW5t/mLoRGzZs4IcffmD//v1YLBZq1qxJjx498j1LGh8fz8qVK2nfvj3+/v5FlsURXqPCpKSkWD8E9e/f33rNTJo0if3799O7d2/atGlj8/064vvFkTjC+8URXyNHuqYdla5px6RrunC6pq/MXte0lEwqTkixy8jIYO7cuWRkZPDEE0/YO46IiIiIiIjYmYoTIg4iOzubY8eOkZubS82aNYtkJJXLOX/+POnp6RiGgYeHR75hw4qbsjh+FhEpvfT7yDGziIiUduoQs5TIyspi8uTJLF68mISEBKpUqUKXLl0YMGAA5cuXL3Sd0aNHs3jxYpuPt6wslxYbG8vatWtxdnamc+fO1k6lpk+fztSpU60jiJQpU4aHH36YkSNHWodBtbWEhAS+//57Vq9ezYEDB8jMzMw3383Njbp169KhQwf69OlzyQ6wlOXmyCKOzZHudcri+FlAv48cOcv27dtvaP1mzZrZKImUFI50f3GkLFLyqOVEKZCdnc0jjzzCzp07+efLaTKZqFSpEhMnTqR58+YF1hs9ejSLFi2yab8PynJpU6ZMYdKkSVgsFgA8PT35/PPP2bdvH+PHj8dkMhEUFISrqyuHDx8mLy+PDh068Pnnn9s0B1wYpvSNN94gKysLwzAwm82UL1/eOiZ5VlYWSUlJ1qxlypRh/PjxdO3aVVluwizi2BzpXqcsjp8F9PvI0bOEhoZed59TJpNJf+DdZBzp/uJIWaRkUsuJUmD69On8+eefNGnShHHjxlGzZk0iIyP55JNP2LJlCwMGDOCzzz6jbdu2ymKnLKtWreLjjz/G29ubbt26kZaWxq+//sqYMWMA8PX1ZdKkSTRu3BiAY8eO8eyzz7Jq1Sp++OEHevXqZbMsa9euZezYsXh5eTFs2DBuv/12atSogZOTU77l8vLyOHz4ML///jszZsxgzJgx+Pr6WofoUpabI4sjfYOnLIVzpHudsjh+Fv0+cvwsb775JhMmTCA9PZ1KlSpRs2ZNm237WjnSvU5ZCudI9xdHyiIlk1pOlAJdu3bl9OnT/Prrr9axgy/64IMP+OKLL3B3d2fGjBn5qpVFUaVUlsINHDiQLVu28Msvv1iHKV2xYgXDhw/HZDIxceJEunTpkm+d+Ph47rzzTurWrct3331nsyyPPPIIO3bs4Ntvv6VBgwZXtc6uXbvo06cPLVu2ZObMmcpyE2VxpG/wlKVwjnSvUxbHz6LfR46fBWDHjh0MGjQIi8XC999/T506dWy6/avlSPc6ZSmcI91fHCmLlExqOVEKHDt2jPDw8AI3AYBRo0bh7OzMlClTePzxx5k7d671w4iyFF+W3bt307Jly3z76NixI7Vq1eLQoUO0bt26wDqVK1emcePG/PnnnzbNEhUVRXh4+FV/+AJo2LAhERER7N69W1lusiyO9A2eshTOke51yuL4WfT7yPGzADRt2pS33nqLkSNH8t///pfvv//e5vu4Go50r1OWwjnS/cWRskjJpOJEKWA2m8nNzb3k/KeeeoozZ87w/fffM3jwYL777jv8/PyUpRizZGRk4OLiUmB6rVq1iImJsT6/+m9OTk7YunGTi4tLgWaqV8NkMpGdna0sN1mWnj17UrNmTQYNGsT58+d55ZVX7PYNnrIUzpHudcri+Fn0+8jxs1z0n//8h3vuuYeFCxcyf/587r333iLZz+U40r1OWQrnSPcXR8oiJZPZ3gHkxtWqVYudO3dy+vTpSy7z6quv0rZtW06cOMHAgQNJSkpSlmLMUqNGDbZt28bZs2fzTX/vvfdYunSptbOtf4qPj2fbtm0EBwfbNEvdunXZuHEjMTExV71OVFQUGzZsICwsTFlusizw9zd4GRkZ/Pe//7X59pXlxjjSvU5ZHD+Lfh85fpZ/GjVqFN27dychIaHI9nEljnKvU5bCOdL9xZGySMmk4kQp0L17d86fP8+QIUPYsmVLgWGv4MI3Hp988gn169fnwIED3Hfffdf0C1hZbsz999/PuXPn6NevH3/88Qc5OTnAhSHJatasibu7u3VZi8XC6tWreeSRR8jMzOS+++6zaZZhw4aRlZVFnz59mDx5Mvv27Su0ym2xWIiJiWHatGk89thj5OXlMWjQIGW5ybJcdPEbvF27djF//vwi2YeyXB9Hutcpi+Nn0e8jx8/yT5UrV+att95i8ODBRbaPq+EI9zplKZwj3V8cKYuUTOoQsxSwWCwMHz6cVatWYTKZqFWrFosWLSp02dTUVAYPHszOnTutHfnYsvMZZbl0lhdeeIEFCxZgMplYuHAhtWvXLnTZZ599lqVLl2IYBrfeeitTpky57k6XLuXnn39m3Lhx1g+lZrMZHx8f3N3dMZlMZGZmkpycTF5eHoZh4ObmxvPPP0/fvn1tmkNZSkaWi+Lj45k4cSLBwcF2/6CsLH9ztHudsjh+Fv0+cvwsjsje9zplKZyj3V8cJYuUTCpOlBIXe3OeN28ePj4+lx2LPCcnh48//phvvvmGrKwsm98IlOXSlixZwsKFC/n0009xdi68y5d3332X5cuX07t3bx555JFLLnejTp8+zezZs1m7di0HDx4s8Mysh4cHtWvXpl27dvTs2ZPAwMAiyaEsJSOLODZHutcpi+NnAf0+KglZLufQoUOcOXOGli1b2mX/4lgc6f7iSFmk5FFx4iaWkpJCZGQk7dq1s3cUZXEAKSkpZGRkYDKZ8PT0xMvLS1mURUoxR7rXKYvjZylOjnSvc6Qs/6ShF+VGOdL9xZGyiH2pOHGTcKQKu7Ioi7Ioi7Ioi7Ioi7JcP0cqTjjSeVEWZZGSTR1i3iSmTJnCI488Yu8YgLJcirIUTlkKpyyFU5bCKUvhlKVwylI4R8riSBzpvChL4ZRFSgoVJ0RERERERETErlScEBERERERERG7UnFCRERERKQECQ4OpkWLFvaOISJiUypOiIiIiIiUIMOHD2f27Nn2jiEiYlNFM2C1OJxatWo5TIVdWQrnSFkc6RsZZSmcshROWQqnLIVTlsIpS+HskcVisbB7925iYmI4e/Ys2dnZODs7U7ZsWfz9/WnQoAEVKlQo1kz/drO/RpeiLIVzpCzieDSUqIiIiIiIAzEMg7lz5/LZZ5+RlJRUYJ7JZALAZDLRokULRo4cqT/4RKTEU3GiFJg0aRL16tWjU6dO9o6iLCUgy9XYtm0be/bsIScnh9DQUCIiIqwfhJRFWZRFWZRFWWzNkVoIOEKWF198kXnz5lG+fHkaNGiAk5MTUVFRJCQk0KNHD2rUqMGhQ4fYtGkTp06dwmQyMXr0aAYMGFBkmRzhvCiLskjppuJEKRAaGorJZKJ///48++yzODvb72kdZXH8LABJSUl89tlnbN26FR8fH/r370+HDh1ISUnhiSeeYOvWrfmWr1OnDhMnTiQ4OFhZlEVZlEVZlMVmHKmFgKNkWbx4MaNGjaJr1668/vrreHh4AJCdnc2ECRNYvHgx8+bNo1q1agCsWLGCV199ldOnTzNz5kwiIiJsmsdRzouyKIuUfipOlAKhoaHAhYu8bt26vPbaazRp0kRZlKVQqamp9OrVi9jYWC5e/k5OTnzxxRfMmDGDdevWUbNmTVq3bo2TkxMbN25k//79+Pr68ssvv1CpUiVlURZlURZlURabcKQWAo6SpW/fvsTFxbFs2TJcXV3zzcvJyeH222/nlltu4d1337VOP3ToEPfccw+tW7dm2rRpNs3jKOdFWZRFbgKGlHghISHGiBEjjDFjxhghISFGaGio8eyzzxoHDx5UFmUp4M033zRCQkKMYcOGGZGRkcbKlSuN2267zWjfvr0RGhpqjB071sjJybEun5eXZ11nwoQJyqIsyqIsyqIsNrFo0SIjJCTEGDVqlHH+/Hnr9KysLGPs2LFGs2bNjNjYWOv0P/74w2jXrp0RGhpqbNiwodRmadGihTF8+PBLzh8+fLjRunXrAtMHDBhgtGnTxqZZHOm8KIuySOmn4kQpEBISYowePdowDMNYsGCB0aZNGyMkJMSoV6+eMWLECGPHjh3KoixWnTt3Ntq3b29kZWVZp61fv94ICQkx2rVrZ2RnZxdYJzc31+jYsaPRqVMnZVEWZVEWZVEWm+jTp4/Rrl27fFkuys7ONjp06GD93XlRTEyMERYWZgwePLjUZmnWrJnRvXv3S87v3bu30ahRowLThwwZUuj0G+FI50VZlEVKP7O9W26IbXXr1o3ffvuNwYMH4+bmxrJly+jTpw+33347H330Ebt378ZisSjLTZzl5MmTNGzYMF9T0aZNmwIQFhaGi4tLgXWcnJyoV68e8fHxyqIsyqIsyqIsNnHgwAEaNGhQ4NEFABcXF+rXr8+6devyTQ8ODiY8PJzo6OhSm6V+/frs3buXZcuWFZgXGRlJZGQktWrVyjc9NjaWzZs3F5h+oxzpvCiLskjpZ99e+aRIeHh4MGrUKAYNGsTcuXOZO3cux44dY9q0aUybNg13d3fq169PtWrVqFKlCk8//bSy3ERZPD09OX36dL5pF3/+d8dF/3TmzBlrp1zKoizKoizKoiw3ymKxcPLkyUvOP3v2LGlpaQWmOzs7c+7cuVKb5dFHH2XLli08++yzDBw4kI4dO+Lp6cnWrVv56KOPMAyDvn37AhAfH893333H3LlzyczMpF+/fjbN4kjnRVmURUo/tZwoxcqVK8fw4cNZtWoVX3/9NX379qVq1apkZGSwbds25s2bx9SpU5XlJsvSpEkTIiMjrd/IWCwWJk6cCMDu3bsL9NIOsH37dnbu3EmDBg2URVmURVmURVlswpFaCDhSls6dOzNkyBCys7P5/PPP6d27N127dmXcuHEkJydz//33c//99wMQExPDlClTOH/+PM899xw9evSwaRZHOi/KoixS+qnlxE3AbDYTHh5OeHg4AMnJyezatYu4uDjOnj2rLDdZluHDh7Nu3TqeeuopQkJCOHv2LPHx8VSuXJlu3boxbNgwRowYQatWrXB2dmbVqlV8/vnnADzyyCPKoizKoizKoiw24UgtBBwpC8Czzz5Lq1at+P777zlw4AAWi4WaNWvSo0cPOnfubF2uVq1avPbaa7Rv3x5/f3+b53Ck86IsyiKln4YSLQVCQ0O555578g0ppSzKcjnLli3j1Vdf5cyZMwD4+/vzySefEBQUxIMPPsiRI0fyLW8YBkOHDuWZZ55RFmVRFmVRFmWxmQ8//JBp06ZhMpkK7LNXr16MHz8egPXr1zNgwACcnZ155plnGDhwYKnOUpjz58+Tnp6OYRh4eHjg5eVVLPt1pPOiLMoipZuKE6VAv379aNu2LUOHDrV3FGUpAVkuysvLY9++fZjNZmrXro2z84WGVMnJyUyfPp3Nmzdz7tw5goODeeCBB+jQoYOyKIuyKIuyKIvNbdiw4YotBOLj41m5cmWRtRBwxCwJCQl8//33rF69mgMHDpCZmZlvvpubG3Xr1qVDhw706dOHChUqFFkWRzovyqIsUnqpOFGK2avCrizKoizKoizKoizKoizX74cffuCNN94gKysLwzAwm82UL18eNzc3ALKyskhKSrKO7lWmTBnGjx9P165diyWfXiNlKalZxLGpOFGKOFKFXVlKR5aQkBDat2+vLMqiLMqiLMpi1yyO9LuxqLOsXbuWQYMG4eXlxaBBg7j99tupUaMGTk5O+ZbLy8vj8OHD/P7778yYMYP09HRmzpxp7b/KlhzhvCiLskjpp+JEKeFIFXZlURZlURZlURZlURZluT6PPPIIO3bs4Ntvv73qEVJ27dpFnz59aNmyJTNnzrRpHkc5L8qiLHITMKTEW7NmjRESEmI0b97cmDJlinHw4EEjNze3wHK5ubnGgQMHjMmTJxvNmzc36tWrZ2zcuFFZlEVZlEVZlEVZlEVZHCRLs2bNjIEDB17zegMHDjTCw8NtmsWRzouyKIuUfipOlAL9+vUzGjRoYOzateuq14mMjDTCwsKMxx57TFmURVmURVmURVmURVkcJEt4eLgxZMiQa15v0KBBRtOmTW2axZHOi7Ioi5R+Znu33JAbFxUVRXh4+FU3/QNo2LAhERER7NmzR1mURVmURVmURVmURVkcJEvdunXZuHEjMTExV71OVFQUGzZsICwszKZZHOm8KIuySOmn4kQp4OLiUqCTpKthMpnIzs5WFmVRFmVRFmVRFmVRFgfJMmzYMLKysujTpw+TJ09m37595ObmFljOYrEQExPDtGnTeOyxx8jLy2PQoEE2zeJI50VZlEVKPxUnSgFHqrAri7Ioi7Ioi7Ioi7Ioy/Vr3bo1b775JpmZmXz66ad0796dxo0b06ZNGzp16kTnzp1p27YtjRo1omvXrnz44YdkZ2czduxYOnToYNMsjnRelEVZ5CZg7+dK5MatW7fOCAkJMVq2bGl89tlnxt69e42cnJwCy+Xl5RkHDx40pk6darRo0cIIDQ01Vq5cqSzKoizKoizKoizKoiwOkuWihIQE44MPPjB69OhhNGzY0AgJCcn3r2nTpkavXr2MTz75xIiLiyuSDI50XpRFWaT001CipcTPP//MuHHjyMnJAcBsNuPj44O7uzsmk4nMzEySk5PJy8vDMAzc3Nx4/vnn6du3r7Ioi7Ioi7Ioi7Ioi7I4UJbCpKSkkJGRgclkwtPTEy8vr2LZryOdF2VRFindVJwoRU6fPs3s2bNZu3YtBw8eLPDsloeHB7Vr16Zdu3b07NmTwMBAZVEWZVEWZVEWZVEWZXHALI7Ekc6LsiiLlF4qTpRi9qqwK4uyKIuyKIuyKIuyKEvp5UjnRVmURUoPFSdERERERERExK40WoeIiIiIiIiI2JWKEyIiIiIiIiJiV872DiAiIiK2ExcXR6dOnQqd5+LigoeHB1WrVqVdu3Y8+OCD+Pv723T/MTEx1KpVy6bbFBERkdJPfU6IiIiUIv8sTjRo0ABXV1frvJycHM6ePcuJEycwDANPT0/efPNN7rjjjhve7+nTp3njjTc4duwYP/300w1vT0RERG4uajkhIiJSSn388cdUrVq1wPRTp07x7rvvsnjxYp577jnKlStHq1atbmhfa9asYenSpYSFhd3QdkREROTmpD4nREREbjJVqlThgw8+oEuXLuTk5PDf//6XnJwce8cSERGRm5iKEyIiIjchk8nEq6++ipubG8ePH2fRokX2jiQiIiI3MT3WISIicpOqWLEiHTt25P/+7/9YsWIFPXr0sM47duwYs2bNYuPGjRw/fpzs7Gx8fHxo3Lgx/fr1IyIiwrrsbbfdxvHjxwGIiooiJCSEwMBA/vjjD+sy2dnZzJ07l4ULF3Lo0CEMw6BmzZp07dqVhx9+GDc3t+I7cBEREXE4Kk6IiIjcxJo2bcr//d//sXXrVuu0tWvXMmLECDIzM/H29iYoKIisrCyOHTvGsmXLWL58Oe+//z5du3YFLnS86eLiwpEjR/Dw8CA0NBRfX1/r9pKTkxk8eDCRkZGYzWaqVauGu7s7+/btIzo6msWLFzNjxgzKly9f7McvIiIijkGPdYiIiNzEAgMDAThz5gw5OTlkZ2fz4osvkpmZyWOPPcb69euZN28eS5cuZeXKlbRu3RrDMJg8ebJ1G5988glDhw4FoGbNmnz77bd88skn1vkvvPACkZGRNG3alF9//ZXffvuNBQsWsHz5clq0aEFUVBT//e9/i/fARURExKGoOCEiInIT8/T0tP4/JSWF3bt3k56eTuXKlRkzZky+oUgrVarEiBEjADh8+DAWi+WK29+1axcrVqzAx8eHyZMnExQUZJ3n7+/PJ598gqenJ8uXL2fv3r02PDIREREpSVScEBERuYn9c5QOk8lEs2bN2LZtG7/99htOTk4Fli9TpgwAFouFrKysK25/+fLlALRu3ZoKFSoUmF+xYkVr/xWrV6++rmMQERGRkk99ToiIiNzE0tLSrP/39va2/t/d3Z2oqCiio6OJjY0lNjaW/fv3c/jwYesyV9NyIiYmBoCtW7fSp0+fQpeJi4sDyLdtERERubmoOCEiInITO3ToEABVq1a1PsKxZcsW3nrrLaKioqzLmUwmqlevTrdu3ViwYMFVb/9i8SMhIYGEhITLLnvu3LlrjS8iIiKlhIoTIiIiN7EdO3YA0KRJEwD279/PgAEDyM7OpkWLFtx7772EhIRQq1YtvLy8OHz48DUVJy4+BvL8888zYMAAm+cXERGR0kHFCRERkZvUyZMn2bBhAwB33nknALNnzyY7O5tWrVoxY8aMAv1OnDp16pr2Ub16deDvxzsKEx0djclkolq1anh5eV3T9kVERKR0UIeYIiIiN6nx48djsVioXbs2HTt2BOD48eMAhISEFNoh5o8//mj9f15envX/ZnPhHyluvfVWAH777TfOnj1bYP65c+d47LHH6N69O0uXLr3uYxEREZGSTcUJERGRm8yRI0cYOXIky5cvx8XFhfHjx1sLETVq1ABgyZIlHD161LpOSkoKb775JosWLbJO++doHR4eHsCFviWys7Ot08PDw2nZsiWpqakMHTo03zbj4+N5/PHHSUlJwdfXl27duhXJ8YqIiIjjMxmGYdg7hIiIiNhGXFwcnTp1AqBBgwbWTi7hQjEhISGB06dPA+Dl5cV7773HbbfdZl3m2LFj9OzZk9TUVJydnQkODgYuFDSys7MJDQ3l1KlTJCcn8/PPPxMWFgZcGGnjzjvvxDAMAgICqFKlCt9++y1woQgxcOBADhw4gMlkonbt2pjNZg4dOkROTg5eXl5888031KtXr1jOkYiIiDgeFSdERERKkX8WJ/7N2dkZb29vgoODadeuHb1796ZChQoFljt+/DiffvopW7du5dSpU7i7u1OzZk3uvvtu+vbtywsvvMDixYt58skneeKJJ6zr/fjjj0ydOpWTJ0/i4+PDvHnzqFSpEgAZGRnMmTOHpUuXWosSfn5+tG3bliFDhlC1atWiOSEiIiJSIqg4ISIiIiIiIiJ2pT4nRERERERERMSuVJwQEREREREREbtScUJERERERERE7ErFCRERERERERGxKxUnRERERERERMSuVJwQEREREREREbtScUJERERERERE7ErFCRERERERERGxKxUnRERERERERMSuVJwQEREREREREbtScUJERERERERE7ErFCRERERERERGxKxUnRERERERERMSuVJwQEREREREREbtScUJERERERERE7ErFCRERERERERGxKxUnRERERERERMSuVJwQEREREREREbtScUJERERERERE7ErFCRERERERERGxKxUnRERERERERMSuVJwQEREREREREbtScUJERERERERE7ErFCRERERERERGxKxUnRERERERERMSuVJwQEREREREREbtScUJERERERERE7ErFCRERERERERGxKxUnRERERERERMSuVJwQEREREREREbtScUJERERERERE7ErFCRERERERERGxK2d7BxAR+8vKyuLMmTOkpp4jLy/P3nFERESkBHNycqJsWW8qVqyIm5ubveOISAlhMgzDsHcIEbGfrKwsjhw5gru7Fx4enjg5OWMymewdS0REREogwzDIy8slPf08mZlp1KhRQwUKEbkqKk6I3OROnDhBTo5B2bI+9o4iIiIipUhqajIuLiYCAgLsHUVESgD1OSFyk0tNPYeHh6e9Y4iIiEgp4+HhSWrqOXvHEJESQsUJkZtcXl4eTk7qfkZERERsy8nJWX1ZichVU3FCRNTHhIiIiNicPl+IyLVQcUJERERERERE7ErFCRERERERERGxKxUnRERErtEXX3xORESzAv/atLmF//ynI8OHD2bp0sVXvb3XX3+ViIhm7N+/rwhTX1pERDO6d7/b5tv94YfviIhoxqJFC6zThg8fTEREM86dK9pO8rKzs/nuuzlFug8RERGxHfWCJyIicp3at7+VOnXqWn+2WCwkJyexbNlvvPbaWOLiYhk8ePgVt9Ohw634+/tTsWLFoozrEO6+uxvNmjXH1dW1SPfz+OODOXLkMA8++FCR7kdERERsQ8UJERGR69S+/a107XpPgel9+vTj0Uf78NVXM+nWrTtVqvhfdjsdOnSkQ4eORRXToRR2vopCYmJisexHREREbEOPdYiIiNhYUFAQ7dvfSl5eLhs3rrd3HBERERGHp5YTIiIiRcDX1w+A5ORkABYtWsCECeOYMOFtfvnlRyIjd1KxYkUmT57O9OlTWbJkIbNmfUvduiHWbaxevZLvvpvL/v17cXJypm7dEAYOHEyTJs3y7Wvr1s18/fVMoqOjyMvLpXbtOvTt24/bbut83fkjIppx113d6N69J1OmTGLv3micnZ255ZYIRox4ioCAgHzLr169klmzZnLw4AHKli1Hjx734eHhUWC7w4cPZseObfz++yq8vb2t0xctms/PP//EkSOHKFPGg7CwBgwePCzfYzPp6el8++03rFz5B8ePx5Gbm4ufX2U6dLiVgQOH4uHhwYkTJ+jZs2uB43jlldcAiI8/xYwZX7Bhw1qSkpKoVKkS7dt3ZMCAQfj4lM+X8+TJE4waNYb33nublJQU2rfvwPjxb133ORUREZFLU3FCRESkCMTFHQPAz69yvukffPAuvr5+PPBAH06cOF7gj/yLZs6cztSpkylfvgIdO3bGzc2V3377P0aMGMaHH35MeHgrAObP/4W3355A+fIV6Nz5djw8PFm9eiUvvTSGYcNG8NhjA6/7GPbt28OIEUNo3LgJPXv2Ijp6N8uX/86BA/v53/9+xmQyATBv3s/WDHfeeTcWi4VZs2bi6el5Vft5883xLFjwC/7+Adx5591kZ+fw22//x9atm5k69Uvq1KlLbm4uTz45jOjoKMLDWxEe3or09HTWrFnFnDmziYuL4513PsDb25uBA4fwv//NJTs7m379HrMWfI4ePcLQoQNITk4mPDyC4ODa7N27h++//5Y1a1bxxRczqVTJ15orNTWFV155iQ4dOuLh4UnNmjWv+1yKiIjI5ak4ISIiYmN79kSzZs1q3NzciIhonW+ei4sL06bNwN29zCXXP3r0CNOnT6NGjZp89tk0a0eZvXo9yKOP9mXSpAvFiYSEeD744B1q1KjJ55/PoFy5cgAMGzaCkSOHM23aFNq3v5Xg4FrXdRwxMQd54omnePjhRwEwDIOnnx7Bpk0b2bZtCy1a3EJqaiqffjoRP7/KTJ/+lbUYc//9vRk06NEr7mPLlk0sWPALTZs25/33J1oLGnff3ZVhwwbxxRef8+67H7JixXKionbz6KMDGD78Cev6I0aMpHfvHqxdu5rMzAy8vb0ZPHgYixcvJC3tHIMHD7Mu+/bbb5CcnMzLL4/L1/fFrFkzmTz5U95//x3efvt96/T09HT69HmYp5569rrOn4iIiFw9FSdERESu0+rVKzl58oT159zcXI4di2XdujXk5eXy1FPPUqFChXzrtGrV+rKFCYDly5eRl5fLwIFD8o3gUb16DZ566lmysrLIzc3l//5vCdnZ2QwePNxamABwc3Nj4MChjBw5nMWLF/Dkk89c1/G5ubnTu3df688mk4lWrdqwadNGYmNjadHiFtavX8v582kMGDAoXyuROnXqctddXfnll58uu4/ffvsVgBEjnszX0qJJk2Y8/viTlCvnA0BISCgvvfQK7dt3yLe+p6cnoaH1Wbt2NampqZc8t6dOnWTHjm00bdq8QKecDz/8KIsXL2TVqhWkpKTkO5cdO3a6bH4RERGxDRUnRERErtPq1StZvXql9WdnZ2d8fHy45ZYIeva8n1at2hRYJyAg8IrbjYk5AEBYWIMC83r0uN/6/7179wAXWh9cXOeijIwMAPbv33/lA7mEKlWq4OLikm+al5cXADk52QAcOLAPgNDQ+gXWb9iw8RWLEzExB3Bycip0/Uce6W/9f1BQdYKCqpOVlcXu3buIjT3KsWOx7Nu3l23btgKQl5d3yf0cOHDhPDRp0rTAPLPZTIMGDTl69AgxMQdp1qy5dd6lHrsRERER21JxQkRE5Dr9+/GAq+Hm5nbFZVJTUwGu2GfDuXPnAPjllx8vs62Ua0iXn6urayFTL/QzYRgGAGlpaQB4ehbs/LJs2bJX3Edqaipubm44O1/+I4nFYuHrr7/k22+/sZ6fChUq0rBhIwIDAzl0KIa/IhXq/Pnzf+Us/Jxe7GsiMzMz33Q3N/crHoOIiIjcOBUnREREHMzFUS7On0+3PtZwUWZmJq6urpjNZutyP/20gMDAqsUdEwBv7wsFiItFin9KSjp7xfU9PDw4efIEubm5BQoUmZkZ1sc05s6dzdSpk2natDn9+j1G/fr1raNrjBo1kkOHYq6wnwtFicTE04XOv1jo+ecjHSIiIlJ8zPYOICIiIvnVqlUbgOjo3QXmvf/+29x6a2tOnDhO7dp1gL8f7/in2NhYPvnkI9asWVWkWUND6wEQGbmzwLx9+/Zecf1atWqTl5dX6LKjRj1F587tyczM4Ndfl+Lk5MT7739E69ZtrIUJwzA4cuTIX2v83XTi4kgiF9WpU+eSOQH+/HM7zs7OBAVVv2JmERERsT0VJ0RERBzMf/5zB2azma++mkFKSrJ1elzcMf74YzkBAYEEBARyxx134eTkxNSpkzlz5ox1udzcXD788B3mzp1NSsr1P9ZxNVq3bkv58uX5/vtviY09ap1+6FAMCxcuuOL6d9xxFwBTp07O90hFZORO/vxzBw0bNsbdvQxubm7k5eWRlJSUb/2ZM6dz/HgccOG4L3Jycsr3s79/AE2bNic6Oor583/Jt405c2Zx6FAMbdu2x9vb+xqOXkRERGxFj3WIiIg4mBo1ajJo0FCmTZvCww8/SNu27QGD33//lZycbF5+eRwA1aoF8cQTT/Hxxx/St28v2rfvgJeXNxs2rOPIkcO0adPO+sd/UfHw8ODFF8fy4otjGDCgHx07dgYMli9fhq9vJeLi4i67fnh4K7p1u5eFC+fTr9+DtGrVhrS0NJYv/w1PT09Gj34BgDvuuJvdu3cxZMgAOnW6HRcXF7Zt28K+fXspX74CSUln/yrkXGj54OdXmbi4Y7z22lhatgznrru68uKLLzN06ADeems8K1Yso2bNWuzbt5ft27fi7x/AqFHPF+m5EhERkUtTcUJERMQBDRgwmKCg6nz33RyWLl2EyWSiYcPGDBkyjAYNGlqX69PnYapXr8HcubP544/lWCx5BAZWZeTIZ7n//geu2NGkLbRvfyuTJk1h+vSpLF/+G25u7vTo0ZN69cJ4+eUXrrj+Sy+9QmhofebN+4l5837C1dWVVq3aMGzYCOvoJvfd1wvDsPDzzz+yYME8vL29qFatOuPHv4WbmxtjxjzL+vXraNiwMQAjRozkjTdeY9my30hMTOSuu7oSFFSdmTO/YcaMaWzYsI5t27bi6+tH3779ePTRAepvQkRExI5MhnG5vq1FpLSLioomIEDPWIuIiIjtnThxlLCwgkMFi4j8m/qcEBERERERERG7UnFCREREREREROxKxQkRERERERERsSsVJ0RERERERETErlScEBERERERERG7UnFCREREREREROxKxQkRERERERERsSsVJ0RERERERETErlScEBERERERERG7UnFCREREREREROxKxQkRERERERERsSsVJ0RERERERETErlScEBERERERERG7UnFCROQfDh8+xDvvvMH9999Lhw6tueOO2xg48BHmzv2GtLRz9o4nJcDevXt4++0J9O7dkw4dWnPbbe0YPPgxfvzxf+Tm5uZbdtu2rURENOOjj96zU1pxNIsWLSAiohlffPH5ZZeLiGhG9+53A3DixAkiIpoxZsyz17XPL774nIiIZqxateK61pfid/E1W7Rogb2jiIjYjLO9A4iIOIo5c2YxefKnALRsGU6HDh3JyMggMvJPPvnkQ+bOncXbb79PgwaN7JxUHJHFYmH69KnMnDkdFxcXWrVqQ9u27Th3Lo3Nmzfy/vvvsHz5Mj766FPc3d3tHVdKEW9vbwYOHEKNGjXtHUVEROS6qTghIgL8+OP/+PTTidSsGcybb75LzZrB+eb//vuvTJgwjhEjhjJz5jcEB9eyU1JxVF999SVffvkFDRo05M0338PPz886Lycnh7feGs+SJYsYP/5V3njjHTsmldLG29ubwYOH2TuGiIjIDdFjHSJy00tMPM0nn3yEj48Pn346pUBhAuD227vw0kuvkJWVxYQJ44o/pDi02NijfPnlNCpUqMjEiZPyFSYAXFxceOmlsfj7B/DHH8s4fPiQnZKKiIiIOCa1nBCRAkw5yZQ58SMu5/djzkmyd5zLsriUJ8ezLhkB92O4+FzXNn755Seys7Pp1+9RKlXyveRyXbrcyZw5s4iOjmLv3mhCQ+sDF5797tLlTrp2vYdJkz7myJHDVKhQkS5d7qR//0G4ubnl286xY7FMnz6VzZs3kZZ2joCAQO66qysPPdQPZ2cX63LDhw/m5MkTTJv2JZMmfczGjRvIysqiXr16DB48nObNW1zX8RaH5HMm5v3uyoGjZpJTHbsO7lPWQp3qFnrcnk05b+O6trFkySJyc3Pp1as3Xl7ehS7j7OzCqFFjSE5Oxsen/GW3Fx9/ihkzvmDDhrUkJSVRqVIl2rfvyIABg/Ktm5ubw8yZM1i58g/i4uJwc3OlXr369O37COHhEfm2ef58Gl999SV//LGMhIR4fHx8aNu2A4MHD6NChQrXddzFIc04x0r+II6jnMOx+33xxpuqVOdWbsPLVPj7oCicOHGCnj270r79rbz77ofW6XFxx5g6dTJbt24hMzODJk2aMXLkM4we/TS+vpWZMuWLfNvJzs5m6tTJLF26mLNnz+DvH8B99z1Ar169MZlMxXY818qUnEKZefNxOXAQc3KyveNclsXHh5w6tcnocS9GuXLFss/U1FS+/PILVq1awenTCZQr50NERCsGDRqKv38AAC++OJoVK5bz888LCQgItK77wgvPsXLlH7zyyuvcdVdX6/Q5c2bx6acT+eyzqTRv3rJYjkNESj/H/sQoIsXOnHWasvsn4Ja8yeELEwDmnCTckjdRdv8EzFmnr2sbW7ZsBiAiovUVl+3QoSMAq1atzDf94MEDPPvsSDw8PLnvvgfw9i7LV1/NYNSokVgsFutye/fuoX//h/njj2W0aNGSBx98iHLlfJgyZRLPPfdMvmUBMjIyGDp0IAcO7Oeuu7rSocOtREbu5OmnR3DixPHrOt6ilphk4p1p7mzZ5ezwhQmA5FQzW3Y58840dxKTru8PsI0b1wMQHt7qssu1bduerl3voXz5Sxcnjh49wqOP9mXBgl8IDq5Fr14P4u8fyPfff0v//v1ITPz7ff7ee28zY8Y0ypYtR69evenU6XaionbzzDNPsHXrZutyaWnnGDJkALNnf0VAQCC9e/elYcPGLFjwCwMG5N+mI0k2kpnFDPaw2+ELEwDnOMcedjOLL0k2ku2aJTY2lsGDH2P58t9p1KgxPXvez4kTxxk6dCApKSmFrvPhh+/xyy8/0rp1W7p1u5ezZ8/w4Yfv8r//zS3m9FfPnHiGsu+8h9uWrQ5fmAAwJyfjtmUrZd95D3PimSLf39mzZxkw4GG++24OlSr50qvXg4SGhrJkySIee+xhYmIOAtC6dRsAtm7dYl3XMAx27NgOwI4d2/Jtd+PGDXh6etG4cZMiPwYRuXmo5YSI5OOesARzbuEfXB2ZOTcF94SlpFd75JrXjY09AkBQUI0rLhsUVB2gQGEgJuYg99//AM899wIAubm5vPLKS/zxxzKWLFlE1673YBgG48e/Sk5OLjNmzKJu3RDr+p988hFz587ml19+4r77elmnp6Qk07hxE9588x1rq4rg4Fp8/vlnLFq0gCFDhl/z8Ra1X9e4kJrm+EWJf0tJM/PrGhceuif7mteNj48HoFq1oBvO8fbbb5CcnMzLL4+ja9d7rNNnzZrJ5Mmf8v777/D22++TlnaOhQvn07Rps3zfgN9zTw/693+Yn376gRYtbgFgypRJxMQc5PnnX6JHj/uty65du5rnnnuajz563yH7wdjIWs5z3t4xrtl50tjEOrpw93VvY/v2bVccseNyJk58n6SkJCZMeJvOnf8DwNChI3jyyWHs3Plnoeu4uLgwc+ZsKlasBEC3bt3p3/9hFi6cz4MPPnTdWYqS+6+/Yk5NtXeMa2ZOScX9199If6hPke5n0qSPiYuLY9CgoQwaNNQ6/ffff2Xs2Bd5/fVX+PrrubRq1QaTycTWrZu5557uAOzfv4+UlGQ8PDzyFScyMzPZuXMH7dp1yNfaT0TkRqk4ISL5uKTusneE6+aSGnld66WlpQHg6el5xWXLlr3QDDc5OX+rEg8PD4YMedz6s7OzM0888TQrVizn11+X0rXrPURF7fqriNE7X2ECYPDgYfzww3csWjQ/X3ECoG/fh/N9AGzdui2ff/4ZsbFHr+1Ai0nUASd7R7hu15v94jCzZcqUuaH9nzp1kh07ttG0afN8hQmAhx9+lMWLF7Jq1QpSUlJwcjJjGAYnT57k1KmTVKniD0C9evX56acFVK5cGbhQKFu6dDG1atXOV5iACy05GjVqwsqVf3D+fBqenl43lN/WDhFj7wjXLYaDN7T+jh3bCnxbfbWSkpLYuHE9jRo1sRYmAFxdXRkx4imGDOlf6Hrdu/e0FiYAQkPrUblyFU6ePHFdOYqDS1S0vSNcN5eoqCLdfnZ2NsuX/46/fwADBw7JN+/227uwYME8tmzZxP79+6hbN4Q6dULytZzYunULTk5OdO16L99//y2nT5/G19eX7du3kZ2dTevWbYs0v4jcfFScEJGbnre3N0lJSWRlZeHsfPnbYkZGOgDlyuVvll+rVh3Kli2bb1pAQAA+PuU5eHA/cOGRDrjwHHhh34h6eHhy4MB+DMPI93x3tWrV8y3n5XXhD8icnJyrOTwpBuXKlSMxMZFz585d9pGNKzlw4MJ7pUmTpgXmmc1mGjRoyNGjR4iJOUizZs25/fY7+O23pdx33700atSI8PBWtGnTjjp16lrXi409Snp6Orm5uYW+77Kzs8jLy+PgwYNqou1ABg4cctkROCIiml1y3r59e7BYLDRs2LDAvLCwBjg5FX6fq1q1WoFpPj4+nDp18ioSi6OJjT1KVlYmjRs3KbTPkMaNm7BlyyYOHNhP3bohtG7dhq++mkFMzEFq1arNtm1bqFs3hIiIVnz//bfs2LGN//znDjZtWo/ZbFZxQkRsTsUJEcknp2xD3M6utXeM65JTttF1rRcQEEhSUhLHjh21dnJ5KUeOHAbA398/3/R/j85wUcWKFTl69AgA585d+HZ948b11j4KCpOenp6vFYerq+u/lrjwIdMwrq/zxqIWVieP9TtK3mMdcCH79QgIqEpiYiJxcbGXLU6kpZ0jOzvnkh1Qnj9/4RGGS7Xiudhha2ZmJgCvvDKO0NB6LFo0nx07trNjx3Y+//wz6tYN5eWXX6Vu3RDr++7o0SPMmDHtktlSUx3vca5garGLnfaOcV1qUdtu+07+q++FChUqFpjn5OREhQqFv0f/3XlvSZATVh+39RvtHeO65ISFFen2r/V+0rp1W776agZbt26mevUa/PnnDnr06Enjxk1wcnJix47t/Oc/d7Bx4wbq1w+7oUKsiEhhVJwQkXwy/e7CJXVXiet3wuJcjky/O69r3fbtbyUqajerVq28YnFi9epV1nX+6eKHu39LS0vDx8cHuPDoB8B///sK3bp1v66sJUGXdjlEHXAipYT1O1HOy0KXdtfXGiUiojWRkX+yadNGGjZsfMnlfv75RyZP/pQBAwYX2l+Ih8eFPyIu1UHlxUJDub96+Xd2dqFv34fp2/dhTp06yebNm1i+/Dc2bdrIqFFP8csvC63vuzvvvJtXXx1/XcdnLxG05RAxnCfN3lGuiSdehNPGfvv/64/Ri3+c/tv58+nFGadIZXbpgktUNOaUktXvhKVcWTK7/OfKC96Ai9d+YmJiofPPnbtwzi7eT8LCGlC2bDm2bNlMWFhD0tPP07Rpczw9vQgJCWXHjm2cOnWSo0eP5HuMUUTEVkrWJ0cRKXIWN19S675Mlk84FhfH/1bE4lKeLJ9wUuu+jMXt0sOAXs6dd3bFw8OTH3747rLPVq9YsZzo6N3UrRtKWFiDfPP27t1TYKSNhIQE4uNPUb/+hWVr165rXfbfcnNz+PjjD/n++++u6xgcSaXyBs8PyaRlw1x8ylquvIKd+ZS10LJhLs8PyaRS+etrjdKlyx24uLjw44//s/Y/8W8ZGRksWDAPgFtuCS90mTp16gAQGVl4a4E//9yOs7MzQUHVOX48js8++4S1a1cDUKWKP/fc052PP55MixYtOX06gRMnTlC9eg1cXV3Zt29voa1tvvtuDl9+OZ2UlORrPOqi52Py4REGUI8GeFN8Q3NeL2+8qUcDHmEAPiYfu+UICamHyWQiKqpgH0KHDx8iPb3kdTJ6KZZKFUl9fjRZLVtg+asQ7MgsPj5ktWxB6vOjsVQq2LLFlqpXr4GbmxvR0VGFPgb4558XRuIIDq4FXGhVEx4ewZ9/bmf79q2YzWYaN77wiFnTps05cuQwS5YsBqBt23ZFml1Ebk5qOSEiBRguPqRXH2TvGMXGz8+PkSOf4e23J/Dkk8N5990PrR/WLlq58g9ef/0VXF1deeWV1wps48yZRL75ZhaPPPIYcLHY8AGGYdCt273AhX4EAgOrsmDBPO68sysNGvz9PPisWV/x7bffcNdd3YruQItROW+Dx3pm2TtGsQkMrMqDDz7E7Nlf8fTTT/D22+9bm0zDhcc5xo8fR1zcMTp06EiTJoX3F+DvH0DTps3ZsWMb8+f/wr339rDOmzNnFocOxXDrrbfh7e1NdnYWc+bMYtOmDdxyS4T18Z+cnBwSExNxdXWlYsWKuLq60rlzF5YsWcj//jc336gL27Zt5dNPJ1K5chUee2xAEZ2dG+Nl8qYr99o7Roni5+fHLbeEs2XLZtavX2vtGyA7O5tJkybaN1wRMMqVI/2xax+pqbRzdXWlU6f/sGTJQmbMmMawYSOs85Yv/53169cREhKa7/dd69Zt+P33X/n55x+oU6cu3t4XioLNm7dkzpxZzJ07C19fvwKdOouI2IKKEyIiXOil3mKx8MEH79KvXx9uuSWc2rXrkJOTzZ9/7mDv3j1UrFiJ119/k9q16xRY38PDk2nTJrNt22Zq1gxm69YtHDx4gDvvvJu2bdsDF76VGjv2NZ555gmGDh1Ihw63EhAQyN690WzduoWAgEAef/yJ4j50sZFhw0aQlHSWRYsW0LNnN9q0aUdgYFUSE0+zadMGkpKSaNSoCWPHjrvsdl588WWGDh3AW2+NZ8WKZdSsWYt9+/ayfftW/P0DGDXqeQAqVqzEgw8+xNy5s+nbtxdt2rTFZDKzceN6jhw5zIABg62jbzz55NNERv7JxIkfsGrVCurXDyMhIYGVK//A2dmZ//73VcxmNaYsTZ59dgyDBj3K6NHP0KFDR3x9fdm4cYO1hYyTk17v0mD27K9YvHhhofN69er917W/g6++msH27dsIC2tAbOxR1q9fS9my5Rg7Nn+xPSKiDWazmVOnTnHrrZ2s0y/0O+FMWlpavhFgRERsScUJEZG/9Ox5P7fcEs6PP/6PLVs2s3PnDpydXahatRpPPvk0Xbvea302998CAwN5+ulRfPTR+/z55w78/QN45pnneOCB/GPYN2nSlC+/nM3MmdPZsmUza9euxs/Pjwce6MOjjw6gYsWibeYrRcfJyYmXXx7H7bd34eeff+TAgX2sX78WJydnateuw5Ahw7nnnh44OV1+uNKgoOrMnPkNM2ZMY8OGdWzbthVfXz/69u3Ho48OyPceHDFiJFWrVmP+/J9ZvHgheXl51KxZi7FjX+Puu/9uhVO+fHlmzJjF119/yapVK9i9exc+PuVp27Y9AwYMzje6h5QO1avXYNq0mUye/CmbN28kNzeX5s1b8sYb7/Dww71xc3O3d0SxgaNHj1g7Xf63Dh1utV77M2dOZ+XKFURH76ZChYrce28PHntsoHUI4ovKly9PaGh9oqN306xZc+t0T09PQkNDiYraTZs2eqRDRIqGyXDU7t5FpFhERUUTEFD9ygvKJUVENKNOnbrMnl3y+4sQkZLPYrFw/Hgc/v7+ODu75Jt34sRxevbsRs+evRgz5kU7JZSbyYkTRwkLu3xn0yIioA4xRUREREoVk8nEo4/25aGHehfoCPGbb2YB0Lx5C3tEExERuSQ91iEiIiJSiphMJrp3v4+5c2fz8MO9adWqNWazE5GRf7J79y4iIlpx222d7R1TREQkHxUnREREREqZJ554iho1alr7I8nNzf2r092R9O37ECaTyd4RRURE8lGfEyI3OfU5ISIiIkVFfU6IyNVSnxMiIiIiIiIiYlcqToiIiIiIiIiIXak4ISIiIiIiIiJ2peKEiKCuZ0RERMTW9PlCRK6FihMiNzknJyfy8nLtHUNERERKmby8XJycnOwdQ0RKCBUnRG5yZct6k55+3t4xREREpJRJTz9P2bLe9o4hIiWEihMiN7mKFSuSmZlGamoyubk5aoIpIiIi180wDHJzc0hNTSYzM42KFSvaO5KIlBAmQ3+JiNz0srKyOHPmDKmp58jLy7N3HBERESnBnJycKFvWm4oVK+Lm5mbvOCJSQqg4ISIiIiIiIiJ2pcc6RERERERERMSuVJwQEREREREREbtScUJERERERERE7ErFCRERERERERGxKxUnRERERERERMSu/h+16tKLB3kBywAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1080x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#sns.set(rc={'figure.figsize':(15, 10)})\n",
    "sns.set(font_scale=2)\n",
    "ax1 = sns.set_style(style=None, rc=None )\n",
    "fig, ax1 = plt.subplots(figsize=(15,6))\n",
    "\n",
    "#sns.lineplot(data = df['y_var_1'], marker='o', sort = False, ax=ax1)\n",
    "\n",
    "\n",
    "\n",
    "ax1 = sns.barplot(x = august_tweet_lt[\"Date\"], y = august_tweet_lt[\"Volume\"], alpha=0.5, palette = bar_colors)\n",
    "plt.xticks(ticks = ax1.get_xticks(), labels = august_tweet_lt[\"day\"].values, rotation = 90)\n",
    "plt.ylabel(\"Volume (Hundred Millions)\")\n",
    "#plt.yticks(ax1.get_xticks(), labels = )\n",
    "\n",
    "\n",
    "ax2 = ax1.twinx()\n",
    "\n",
    "sns.lineplot(x = august_tweet_lt[\"day\"], y = tesla_stock[\"Open\"],  ax = ax2, color = \"#ffbf59\")\n",
    "sns.lineplot(x = august_tweet_lt[\"day\"], y = tesla_stock[\"Close\"], ax = ax2, color = \"#596fff\")\n",
    "sns.lineplot(x = august_tweet_lt[\"day\"], y = tesla_stock[\"High\"], dashes = True, ax = ax2, color = \"#79ed79\")\n",
    "sns.lineplot(x = august_tweet_lt[\"day\"], y = tesla_stock[\"Low\"], dashes = True, ax = ax2, color = \"#ff5962\")\n",
    "\n",
    "plt.xticks(ticks = ax2.get_xticks(), labels = date_labels_aug, rotation = 45)\n",
    "plt.ylabel(\"Stock Prices $USD\")\n",
    "#plt.yticks(ticks = np.arange(18, 28, 2), labels = [str(x) for x in np.arange(18, 28, 2)])\n",
    "\n",
    "plt.legend()\n",
    "\n",
    "legend_elements = [Line2D([0], [0], lw=8, label='Open', color = \"#ffbf59\"), \n",
    "                   Line2D([0], [0], lw=8, label='Close', color = \"#596fff\"),\n",
    "                  Line2D([0], [0], lw=8, label='High', color = \"#79ed79\"),\n",
    "                  Line2D([0], [0], lw=8, label='Low', color = \"#ff5962\"),]\n",
    "\n",
    "#ax2.set_yticks(np.linspace(ax2.get_yticks()[0], ax2.get_yticks()[-1], len(ax1.get_yticks())))\n",
    "plt.xticks(ticks = ax2.get_xticks(), labels = date_labels_aug, rotation = 45)\n",
    "\n",
    "legend = plt.legend(handles=legend_elements, \n",
    "           fontsize = \"small\",\n",
    "           loc='lower center', \n",
    "           title = \"Price Indicator\", \n",
    "           bbox_to_anchor = (0.5, -0.6), \n",
    "            ncol = 4)\n",
    "           #borderpad = 2, )\n",
    "plt.setp(legend.get_title(),fontsize='small')\n",
    "\n",
    "plt.title(\"TSLA Stock Prices From 07/19/18-09/26/18 \\n Aftermath of Elon Musk's Tweet 'I'm Taking Tesla Private' \\n on August 7th, 2018\")\n",
    "\n",
    "#ax2.get_xticklabels()[13].set_color(\"#1DA1F2\") \n",
    "\n",
    "ax2.grid(False)\n",
    "\n",
    "\n",
    "\n",
    "#sns.barplot(x = august_tweet_st[\"Date\"], y = tesla_stock[\"Volume\"])\n",
    "\n",
    "#plt.plot(tesla_stock[\"Date\"], tesla_stock[\"Open\"])\n",
    "\n",
    "# WHY DID THE TESLA STOCK DROP ????\n",
    "\n",
    "# put small twitter logo under date of blue bar "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2c73da07-04c2-4395-b46d-a17f6252729b",
   "metadata": {},
   "source": [
    "## May 5th tweet - tesla stock too high"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "109fc2e2-1471-4f30-bcaa-f04c1d117d80",
   "metadata": {},
   "source": [
    "### Short term"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "f967c0cf-c392-445d-8250-3c10cdb8009d",
   "metadata": {},
   "outputs": [],
   "source": [
    "## tesla stock 20 days before and 50 days after\n",
    "#May 5th tweet --> tesla stock is too high \n",
    "# datetime.datetime.strptime(date_time_str, '%Y-%m-%d %H:%M:%S.%f')\n",
    "start_date = datetime.datetime.strptime(\"2020-05-01\", \"%Y-%m-%d\") - timedelta(days = 20)\n",
    "end_date = datetime.datetime.strptime(\"2020-05-01\", \"%Y-%m-%d\") + timedelta(days = 50)\n",
    "may_tweet_lt = tesla_stock[(tesla_stock[\"Date\"] > start_date) & (tesla_stock[\"Date\"] <= end_date)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "91a7207a-9356-480a-bae3-0a37ab368b32",
   "metadata": {},
   "outputs": [],
   "source": [
    "bar_colors = []\n",
    "for date in may_tweet_lt[\"date\"]:\n",
    "    if date == \"2020-05-01\": \n",
    "        bar_colors.append(\"#1DA1F2\")\n",
    "    else:\n",
    "        bar_colors.append(\"#b0b0b0\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "1396d473-dbcf-47db-bbe4-790e8d6369d4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['04-13',\n",
       " '',\n",
       " '04-15',\n",
       " '',\n",
       " '04-17',\n",
       " '',\n",
       " '04-21',\n",
       " '',\n",
       " '04-23',\n",
       " '',\n",
       " '04-27',\n",
       " '',\n",
       " '04-29',\n",
       " '',\n",
       " '05-01',\n",
       " '',\n",
       " '05-05',\n",
       " '',\n",
       " '05-07',\n",
       " '',\n",
       " '05-11',\n",
       " '',\n",
       " '05-13',\n",
       " '',\n",
       " '05-15',\n",
       " '',\n",
       " '05-19',\n",
       " '',\n",
       " '05-21',\n",
       " '',\n",
       " '05-26',\n",
       " '',\n",
       " '05-28',\n",
       " '',\n",
       " '06-01',\n",
       " '',\n",
       " '06-03',\n",
       " '',\n",
       " '06-05',\n",
       " '',\n",
       " '06-09',\n",
       " '',\n",
       " '06-11',\n",
       " '',\n",
       " '06-15',\n",
       " '',\n",
       " '06-17',\n",
       " '',\n",
       " '06-19']"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "august_tweet_lt[\"day\"].values\n",
    "\n",
    "date_labels_may = [] \n",
    "i = 0\n",
    "for date in may_tweet_lt[\"day\"].values: \n",
    "    if (i % 2) == 0:\n",
    "        date_labels_may.append(date)\n",
    "    elif date == \"05-01\":\n",
    "        date_labels_may.append(date)\n",
    "    else: \n",
    "        date_labels_may.append(\"\")\n",
    "    i += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "bd0e5823-dcab-4bec-91bd-f5e460826320",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "No handles with labels found to put in legend.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#sns.set(rc={'figure.figsize':(15, 10)})\n",
    "sns.set(font_scale=2)\n",
    "ax1 = sns.set_style(style=None, rc=None )\n",
    "fig, ax1 = plt.subplots(figsize=(15,6))\n",
    "\n",
    "#sns.lineplot(data = df['y_var_1'], marker='o', sort = False, ax=ax1)\n",
    "\n",
    "\n",
    "\n",
    "ax1 = sns.barplot(x = may_tweet_lt[\"Date\"], y = may_tweet_lt[\"Volume\"], alpha=0.5, palette = bar_colors)\n",
    "plt.xticks(ticks = ax1.get_xticks(), labels = may_tweet_lt[\"day\"].values, rotation = 90)\n",
    "plt.ylabel(\"Volume (Hundred Millions)\")\n",
    "#plt.yticks(ax1.get_xticks(), labels = )\n",
    "\n",
    "\n",
    "ax2 = ax1.twinx()\n",
    "\n",
    "sns.lineplot(x = may_tweet_lt[\"day\"], y = may_tweet_lt[\"Open\"],  ax = ax2, color = \"#ffbf59\")\n",
    "sns.lineplot(x = may_tweet_lt[\"day\"], y = may_tweet_lt[\"Close\"], ax = ax2, color = \"#596fff\")\n",
    "sns.lineplot(x = may_tweet_lt[\"day\"], y = may_tweet_lt[\"High\"], dashes = True, ax = ax2, color = \"#79ed79\")\n",
    "sns.lineplot(x = may_tweet_lt[\"day\"], y = may_tweet_lt[\"Low\"], dashes = True, ax = ax2, color = \"#ff5962\")\n",
    "\n",
    "plt.xticks(ticks = ax2.get_xticks(), labels =date_labels_may, rotation = 45)\n",
    "plt.ylabel(\"Stock Prices $USD\")\n",
    "#plt.yticks(ticks = np.arange(18, 28, 2), labels = [str(x) for x in np.arange(18, 28, 2)])\n",
    "\n",
    "plt.legend()\n",
    "\n",
    "legend_elements = [Line2D([0], [0], lw=8, label='Open', color = \"#ffbf59\"), \n",
    "                   Line2D([0], [0], lw=8, label='Close', color = \"#596fff\"),\n",
    "                  Line2D([0], [0], lw=8, label='High', color = \"#79ed79\"),\n",
    "                  Line2D([0], [0], lw=8, label='Low', color = \"#ff5962\"),]\n",
    "\n",
    "#ax2.set_yticks(np.linspace(ax2.get_yticks()[0], ax2.get_yticks()[-1], len(ax1.get_yticks())))\n",
    "plt.xticks(ticks = ax2.get_xticks(), labels =date_labels_may, rotation = 45)\n",
    "\n",
    "legend = plt.legend(handles=legend_elements, \n",
    "           fontsize = \"small\",\n",
    "           loc='lower center', \n",
    "           title = \"Price Indicator\", \n",
    "           bbox_to_anchor = (0.5, -0.6), \n",
    "            ncol = 4)\n",
    "           #borderpad = 2, )\n",
    "plt.setp(legend.get_title(),fontsize='small')\n",
    "\n",
    "plt.title(\"TSLA Stock Exchange Prices From 04/13/20-06/19/20 \\n Stock Price Continues to Rise After Elon Musk Tweets \\n 'Tesla stock price is too high imo' on May 1st, 2020\")\n",
    "\n",
    "ax2.grid(False)\n",
    "\n",
    "\n",
    "\n",
    "#sns.barplot(x = august_tweet_st[\"Date\"], y = tesla_stock[\"Volume\"])\n",
    "\n",
    "#plt.plot(tesla_stock[\"Date\"], tesla_stock[\"Open\"])\n",
    "\n",
    "# WHY DID THE TESLA STOCK DROP ????\n",
    "\n",
    "# put small twitter logo under date of blue bar "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "bed33d6e-25a7-425d-8a4d-d0dd3e634c1d",
   "metadata": {},
   "outputs": [],
   "source": [
    "## tesla stock 20 days before and 50 days after\n",
    "#May 5th tweet --> tesla stock is too high \n",
    "# datetime.datetime.strptime(date_time_str, '%Y-%m-%d %H:%M:%S.%f')\n",
    "start_date = datetime.datetime.strptime(\"2022-10-03\", \"%Y-%m-%d\") - timedelta(days = 20)\n",
    "end_date = datetime.datetime.strptime(\"2022-10-03\", \"%Y-%m-%d\") + timedelta(days = 50)\n",
    "may_tweet_lt = tesla_stock[(tesla_stock[\"Date\"] > start_date) & (tesla_stock[\"Date\"] <= end_date)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "922eb282-552e-45ef-a8d3-592857a9773b",
   "metadata": {},
   "outputs": [],
   "source": [
    "bar_colors = []\n",
    "for date in may_tweet_lt[\"date\"]:\n",
    "    if date == \"2022-10-03\": \n",
    "        bar_colors.append(\"#1DA1F2\")\n",
    "    else:\n",
    "        bar_colors.append(\"#b0b0b0\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "01d5fbf9-7006-42b5-a7c7-30b168ec98d0",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "No handles with labels found to put in legend.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#sns.set(rc={'figure.figsize':(15, 10)})\n",
    "sns.set(font_scale=2)\n",
    "ax1 = sns.set_style(style=None, rc=None )\n",
    "fig, ax1 = plt.subplots(figsize=(15,6))\n",
    "\n",
    "#sns.lineplot(data = df['y_var_1'], marker='o', sort = False, ax=ax1)\n",
    "\n",
    "\n",
    "\n",
    "ax1 = sns.barplot(x = may_tweet_lt[\"Date\"], y = may_tweet_lt[\"Volume\"], alpha=0.5, palette = bar_colors)\n",
    "plt.xticks(ticks = ax1.get_xticks(), labels = may_tweet_lt[\"day\"].values, rotation = 90)\n",
    "plt.ylabel(\"Volume (Hundred Millions)\")\n",
    "#plt.yticks(ax1.get_xticks(), labels = )\n",
    "\n",
    "\n",
    "ax2 = ax1.twinx()\n",
    "\n",
    "sns.lineplot(x = may_tweet_lt[\"day\"], y = may_tweet_lt[\"Open\"],  ax = ax2, color = \"#ffbf59\")\n",
    "sns.lineplot(x = may_tweet_lt[\"day\"], y = may_tweet_lt[\"Close\"], ax = ax2, color = \"#596fff\")\n",
    "sns.lineplot(x = may_tweet_lt[\"day\"], y = may_tweet_lt[\"High\"], dashes = True, ax = ax2, color = \"#79ed79\")\n",
    "sns.lineplot(x = may_tweet_lt[\"day\"], y = may_tweet_lt[\"Low\"], dashes = True, ax = ax2, color = \"#ff5962\")\n",
    "\n",
    "plt.xticks(ticks = ax2.get_xticks(), labels = may_tweet_lt[\"day\"].values, rotation = 45)\n",
    "plt.ylabel(\"Stock Prices $USD\")\n",
    "#plt.yticks(ticks = np.arange(18, 28, 2), labels = [str(x) for x in np.arange(18, 28, 2)])\n",
    "\n",
    "plt.legend()\n",
    "\n",
    "legend_elements = [Line2D([0], [0], lw=8, label='Open', color = \"#ffbf59\"), \n",
    "                   Line2D([0], [0], lw=8, label='Close', color = \"#596fff\"),\n",
    "                  Line2D([0], [0], lw=8, label='High', color = \"#79ed79\"),\n",
    "                  Line2D([0], [0], lw=8, label='Low', color = \"#ff5962\"),]\n",
    "\n",
    "#ax2.set_yticks(np.linspace(ax2.get_yticks()[0], ax2.get_yticks()[-1], len(ax1.get_yticks())))\n",
    "plt.xticks(ticks = ax2.get_xticks(), labels = may_tweet_lt[\"day\"].values, rotation = 45)\n",
    "\n",
    "legend = plt.legend(handles=legend_elements, \n",
    "           fontsize = \"small\",\n",
    "           loc='lower center', \n",
    "           title = \"Price Indicator\", \n",
    "           bbox_to_anchor = (0.5, -0.6), \n",
    "            ncol = 4)\n",
    "           #borderpad = 2, )\n",
    "plt.setp(legend.get_title(),fontsize='small')\n",
    "\n",
    "plt.title(\"TSLA Stock Exchange Prices From 04/13/20-06/19/20 \\n Stock Price Continues to Rise After Elon Musk Tweets \\n 'Tesla stock price is too high imo' on May 1st, 2020\")\n",
    "\n",
    "ax2.get_xticklabels()[13].set_color(\"#1DA1F2\") \n",
    "\n",
    "ax2.grid(False)\n",
    "\n",
    "\n",
    "\n",
    "#sns.barplot(x = august_tweet_st[\"Date\"], y = tesla_stock[\"Volume\"])\n",
    "\n",
    "#plt.plot(tesla_stock[\"Date\"], tesla_stock[\"Open\"])\n",
    "\n",
    "# WHY DID THE TESLA STOCK DROP ????\n",
    "\n",
    "# put small twitter logo under date of blue bar "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b4ce648a-fd88-4ec4-83e7-c686d8ae9a08",
   "metadata": {},
   "source": [
    "## Volatility of Tesla Stock"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "eca7d7c5-e99d-4fb7-8e25-18bf940e5544",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>date</th>\n",
       "      <th>full_day</th>\n",
       "      <th>day</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>620</th>\n",
       "      <td>2012-12-13</td>\n",
       "      <td>2.350667</td>\n",
       "      <td>2.353333</td>\n",
       "      <td>2.183333</td>\n",
       "      <td>2.240667</td>\n",
       "      <td>2.240667</td>\n",
       "      <td>32269500</td>\n",
       "      <td>2012-12-13</td>\n",
       "      <td>12-13-2012</td>\n",
       "      <td>12-13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>621</th>\n",
       "      <td>2012-12-14</td>\n",
       "      <td>2.252000</td>\n",
       "      <td>2.293333</td>\n",
       "      <td>2.239333</td>\n",
       "      <td>2.254000</td>\n",
       "      <td>2.254000</td>\n",
       "      <td>15345000</td>\n",
       "      <td>2012-12-14</td>\n",
       "      <td>12-14-2012</td>\n",
       "      <td>12-14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>622</th>\n",
       "      <td>2012-12-17</td>\n",
       "      <td>2.251333</td>\n",
       "      <td>2.300000</td>\n",
       "      <td>2.250000</td>\n",
       "      <td>2.293333</td>\n",
       "      <td>2.293333</td>\n",
       "      <td>12373500</td>\n",
       "      <td>2012-12-17</td>\n",
       "      <td>12-17-2012</td>\n",
       "      <td>12-17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>623</th>\n",
       "      <td>2012-12-18</td>\n",
       "      <td>2.284000</td>\n",
       "      <td>2.338000</td>\n",
       "      <td>2.284000</td>\n",
       "      <td>2.306000</td>\n",
       "      <td>2.306000</td>\n",
       "      <td>23308500</td>\n",
       "      <td>2012-12-18</td>\n",
       "      <td>12-18-2012</td>\n",
       "      <td>12-18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>624</th>\n",
       "      <td>2012-12-19</td>\n",
       "      <td>2.316667</td>\n",
       "      <td>2.350667</td>\n",
       "      <td>2.301333</td>\n",
       "      <td>2.307333</td>\n",
       "      <td>2.307333</td>\n",
       "      <td>19482000</td>\n",
       "      <td>2012-12-19</td>\n",
       "      <td>12-19-2012</td>\n",
       "      <td>12-19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3125</th>\n",
       "      <td>2022-11-25</td>\n",
       "      <td>185.059998</td>\n",
       "      <td>185.199997</td>\n",
       "      <td>180.630005</td>\n",
       "      <td>182.860001</td>\n",
       "      <td>182.860001</td>\n",
       "      <td>50672700</td>\n",
       "      <td>2022-11-25</td>\n",
       "      <td>11-25-2022</td>\n",
       "      <td>11-25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3126</th>\n",
       "      <td>2022-11-28</td>\n",
       "      <td>179.960007</td>\n",
       "      <td>188.500000</td>\n",
       "      <td>179.000000</td>\n",
       "      <td>182.919998</td>\n",
       "      <td>182.919998</td>\n",
       "      <td>92905200</td>\n",
       "      <td>2022-11-28</td>\n",
       "      <td>11-28-2022</td>\n",
       "      <td>11-28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3127</th>\n",
       "      <td>2022-11-29</td>\n",
       "      <td>184.990005</td>\n",
       "      <td>186.380005</td>\n",
       "      <td>178.750000</td>\n",
       "      <td>180.830002</td>\n",
       "      <td>180.830002</td>\n",
       "      <td>83357100</td>\n",
       "      <td>2022-11-29</td>\n",
       "      <td>11-29-2022</td>\n",
       "      <td>11-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3128</th>\n",
       "      <td>2022-11-30</td>\n",
       "      <td>182.429993</td>\n",
       "      <td>194.759995</td>\n",
       "      <td>180.630005</td>\n",
       "      <td>194.699997</td>\n",
       "      <td>194.699997</td>\n",
       "      <td>109186400</td>\n",
       "      <td>2022-11-30</td>\n",
       "      <td>11-30-2022</td>\n",
       "      <td>11-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3129</th>\n",
       "      <td>2022-12-01</td>\n",
       "      <td>197.080002</td>\n",
       "      <td>198.919998</td>\n",
       "      <td>191.800003</td>\n",
       "      <td>194.699997</td>\n",
       "      <td>194.699997</td>\n",
       "      <td>80046200</td>\n",
       "      <td>2022-12-01</td>\n",
       "      <td>12-01-2022</td>\n",
       "      <td>12-01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2510 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Date        Open        High         Low       Close   Adj Close  \\\n",
       "620  2012-12-13    2.350667    2.353333    2.183333    2.240667    2.240667   \n",
       "621  2012-12-14    2.252000    2.293333    2.239333    2.254000    2.254000   \n",
       "622  2012-12-17    2.251333    2.300000    2.250000    2.293333    2.293333   \n",
       "623  2012-12-18    2.284000    2.338000    2.284000    2.306000    2.306000   \n",
       "624  2012-12-19    2.316667    2.350667    2.301333    2.307333    2.307333   \n",
       "...         ...         ...         ...         ...         ...         ...   \n",
       "3125 2022-11-25  185.059998  185.199997  180.630005  182.860001  182.860001   \n",
       "3126 2022-11-28  179.960007  188.500000  179.000000  182.919998  182.919998   \n",
       "3127 2022-11-29  184.990005  186.380005  178.750000  180.830002  180.830002   \n",
       "3128 2022-11-30  182.429993  194.759995  180.630005  194.699997  194.699997   \n",
       "3129 2022-12-01  197.080002  198.919998  191.800003  194.699997  194.699997   \n",
       "\n",
       "         Volume        date    full_day    day  \n",
       "620    32269500  2012-12-13  12-13-2012  12-13  \n",
       "621    15345000  2012-12-14  12-14-2012  12-14  \n",
       "622    12373500  2012-12-17  12-17-2012  12-17  \n",
       "623    23308500  2012-12-18  12-18-2012  12-18  \n",
       "624    19482000  2012-12-19  12-19-2012  12-19  \n",
       "...         ...         ...         ...    ...  \n",
       "3125   50672700  2022-11-25  11-25-2022  11-25  \n",
       "3126   92905200  2022-11-28  11-28-2022  11-28  \n",
       "3127   83357100  2022-11-29  11-29-2022  11-29  \n",
       "3128  109186400  2022-11-30  11-30-2022  11-30  \n",
       "3129   80046200  2022-12-01  12-01-2022  12-01  \n",
       "\n",
       "[2510 rows x 10 columns]"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## volatility of tesla stock \n",
    "# 2013 - present\n",
    "# datetime.datetime.strptime(date_time_str, '%Y-%m-%d %H:%M:%S.%f')\n",
    "start_date = datetime.datetime.strptime(\"2013-01-01\", \"%Y-%m-%d\") - timedelta(days = 20)\n",
    "end_date = datetime.datetime.strptime(\"2022-12-01\", \"%Y-%m-%d\") + timedelta(days = 20)\n",
    "volatility = tesla_stock[(tesla_stock[\"Date\"] > start_date) & (tesla_stock[\"Date\"] <= end_date)]\n",
    "\n",
    "volatility"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "6294d4aa-814e-4b8e-81e3-f75d8c28381e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import plotly.express as px\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "476c9c59-0589-42ec-920f-526d736d3efb",
   "metadata": {},
   "outputs": [],
   "source": [
    "## look into tweets that include tesla and their respective volumes "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "37c109d4-e2dd-441e-b8e2-97c708b8a29e",
   "metadata": {},
   "source": [
    "# Controversial tweet volume analysis "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "3b5d4af2-ed73-426b-8878-b85d27c90ca7",
   "metadata": {},
   "outputs": [],
   "source": [
    "## tesla stock 20 days before and 50 days after\n",
    "#August 7th, 2018 tweet \n",
    "# datetime.datetime.strptime(date_time_str, '%Y-%m-%d %H:%M:%S.%f')\n",
    "start_date = datetime.datetime.strptime(\"2020-05-18\", \"%Y-%m-%d\") - timedelta(days = 20)\n",
    "end_date = datetime.datetime.strptime(\"2020-05-18\", \"%Y-%m-%d\") + timedelta(days = 20)\n",
    "democrats = tesla_stock[(tesla_stock[\"Date\"] > start_date) & (tesla_stock[\"Date\"] <= end_date)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "001c9d67-1814-4527-a733-812a9cad8723",
   "metadata": {},
   "outputs": [],
   "source": [
    "bar_colors = []\n",
    "for date in democrats[\"date\"]:\n",
    "    if date == \"2020-05-18\": \n",
    "        bar_colors.append(\"#1DA1F2\")\n",
    "    else:\n",
    "        bar_colors.append(\"#b0b0b0\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "e2a4ef5a-1580-4688-8fc4-8716456314da",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'TSLA Trade Volume (Hundred Millions)')"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(rc={'figure.figsize':(15, 10)})\n",
    "sns.set(font_scale=2)\n",
    "sns.set_style(style=None, rc=None )\n",
    "ax1 = sns.barplot(x = democrats[\"Date\"], y = democrats[\"Volume\"], alpha=0.8, palette = bar_colors)\n",
    "plt.xticks(ticks = ax1.get_xticks(), labels = democrats[\"day\"].values, rotation = 90)\n",
    "plt.title(\"May 18th, 2020 Tweet\")\n",
    "plt.ylabel(\"TSLA Trade Volume (Hundred Millions)\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "57bfa593-77ee-4b0a-9ee9-69b979225afd",
   "metadata": {},
   "outputs": [],
   "source": [
    "## tesla stock 20 days before and 50 days after\n",
    "#August 7th, 2018 tweet \n",
    "# datetime.datetime.strptime(date_time_str, '%Y-%m-%d %H:%M:%S.%f')\n",
    "start_date = datetime.datetime.strptime(\"2022-10-03\", \"%Y-%m-%d\") - timedelta(days = 20)\n",
    "end_date = datetime.datetime.strptime(\"2022-10-03\", \"%Y-%m-%d\") + timedelta(days = 20)\n",
    "ukraine = tesla_stock[(tesla_stock[\"Date\"] > start_date) & (tesla_stock[\"Date\"] <= end_date)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "bec480e0-610f-4227-b383-b503ee501573",
   "metadata": {},
   "outputs": [],
   "source": [
    "bar_colors = []\n",
    "for date in ukraine[\"date\"]:\n",
    "    if date == \"2022-10-03\": \n",
    "        bar_colors.append(\"#1DA1F2\")\n",
    "    else:\n",
    "        bar_colors.append(\"#b0b0b0\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "2187d00e-0310-4a14-a604-5c6210b6b4e4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'October 3rd, 2022 Tweet')"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Yly5d0rhx41SkSBEtXrxYQUFBkqTw8HANHDhQEydOVLt27VSmTBmrY1y9elX//e9/ZRiGZs6cqU6dOkmSDMPQ7Nmz9cknn+j111/X+vXr5e7unuusAAAAAAA4smzv9F+8eFFTpkzRgAEDdO3atXT7zp07p//85z/q3bu3XnrpJQ0YMEDt2rXT/Pnzcx1o4cKFSkpK0oABAyyFX5Lq1aunwYMHKzExMdu7/evXr1dcXJx69uxpKfzS7QUGhw4dqtq1a+vcuXPau3dvrnMCAAAAAODosiz9u3btUvfu3TVv3jzt3LlTV65cseyLjY1V3759deDAARmGoWLFiqlKlSq6efOmJk+erKlTp+Yq0NatWyUpXVlP07lzZ0nSli1bshzDbDardu3aatasWab7q1SpIun2rAIAAAAAAJyV1dJ/8+ZNjRw5Ujdv3lS1atU0YsQIlS5d2rJ/5syZunDhgiSpf//+2rp1q3755RetWLFCJUqU0Ny5c3XkyBGbwhiGoRMnTsjFxUXVq1fPsL9q1apycXHRiRMnsnyVYN++fbVy5Ur17t07wz6z2axDhw5JksqWLWtTPgAAAAAAChOrpX/JkiW6evWq2rRpo5UrV+r555+Xv7+/JCk5OVnff/+9TCaTKlWqpDFjxsjN7fbyALVq1dI777yj1NRUff/99zaFuX79upKSklSsWDF5eHhk2O/m5qaAgAAlJCQoLi7OprHTrFixQmfOnFHp0qVVv379XI0BAAAAAEBhYLX0b968WS4uLho7dqw8PT3T7QsLC9PNmzclSSEhIXJxST9Mx44d5efnp9DQUJvCJCQkSJK8vb2tHuPl5SVJuSr9Bw8e1MSJEyVJr7zyiuWDCgAAAAAAnJHV1nv69GmVKlVKlStXzrBv+/btln9v3bp1hv2urq6qVKmSTp8+bVOYf394kJmspvVnJTw8XM8++6zi4+P1+OOPKyQkxOYxSpTws/x7YmKi3NwK5o2Hrq4uKlWqSIbtjpDBUXI4QgZHyeEIGe7GHI6QoTDkcIQMjpLDETJIUkxCitzcXQskh4uLSSUc+Htxt+VwhAyFIYcjZHCUHI6QwVFyOEKGuzGHI2QoLDn+yWrpv3btmmrXrp3pvrCwMEmSn5+f6tatm+kxJpPJ5oKe9qq/xMREq8ek7ctqNsC/bd68WS+99JLi4+PVp08fjRs3zqZcaaKjY2U23/6afH3dlJJiztU4tkpNNevy5ZsZtjtCBkfJ4QgZHCWHI2S4G3M4QobCkMMRMjhKDkfIIEkuPl5KSU4tkBxms+HQ34u7LYcjZCgMORwhg6PkcIQMjpLDETLcjTkcIYMj5nBxMaW7Qf1vVj+C8Pf3V3x8fIbtsbGxOnz4sEwmk5o0aSKTyZThGMMw9PfffysgIMCm0H5+fvLx8VFMTIxSUlIy7E9JSVFMTIw8PT0t6wtk59tvv9Vzzz2n+Ph4DRw4UJMmTcrRjAIAAAAAAAo7q+23evXqOn36tGJjY9Nt37Rpk6WQt23bNtNzd+3apevXr2e6An9WTCaTAgMDlZqaqsjIyAz7IyIiZDabFRQUlKPxPvvsM40bN06GYWjMmDF64403Mv2QAgAAAAAAZ2S19Hfo0EHJycmaMmWKZVtSUpK++uorSZK7u7s6d+6c4bykpCR9+OGHMplMatOmjc2B0tYI2LhxY4Z9adusfdjwTwsWLNCMGTPk7u6ujz/+WAMGDLA5CwAAAAAAhZnV0v/EE0+obNmyWrp0qR599FGNGzdOPXv21NGjR2UymTRw4MB00/fNZrP+/PNPPf300zp48KBKliyphx9+2OZAffr0kaenp+bMmaODBw9ath84cEBz586Vl5eX+vbta9l+7tw5nTx5UlevXrVsO3r0qCZPnixJmjx5sh566CGbcwAAAAAAUNhZXcjP29tbc+fO1ZAhQ3TgwAEdOHDAsq9z584aMWJEuuM7d+6sc+fOyTAMeXl5afLkyfL19bU5UMWKFTV69GiNHz9ejz/+uJo1aybDMLRz506lpKRo8uTJKlGihOX40aNHKywsTMOHD7dkmjVrlpKTk+Xv76/ffvtNv/32W6bXevzxx9WoUSObMwIAAAAAUBhk+aL6wMBA/fLLL1q7dq0OHTokNzc3NW/ePNNp+35+fjIMQ82bN9crr7xidVX/nOjXr5/Kly+vuXPnavfu3fLw8FDDhg313HPPqXnz5tmen/Z2gRs3bmj16tVWj2vRogWlHwAAAADgtLIs/ZLk4eGhkJCQbN9rP23aNBUrVkzFihWzS7D27durffv22R63YMGCDNv++OMPu2QAAAAAAKAws1r6z507J09Pz3RT6bNStWpVe2UCAAAAAAB2kOXq/SNHjizILAAAAAAAwI6sln5JMgyjoHIAAAAAAAA7y7L0AwAAAACAwovSDwAAAACAk6L0AwAAAADgpLJ8ZV90dLR++OGHPF0gu1f9AQAAAACA/JFl6T99+rTGjBmT68FNJhOlHwAAAACAOyTL0u/h4aESJUoUVBYAAAAAAGBHWZb+unXratGiRQWVBQAAAAAA2BEL+QEAAAAA4KQo/QAAAAAAOClKPwAAAAAATorSDwAAAACAk7K6kN/w4cNVrly5gswCAAAAAADsKMvSDwAAAAAACi+m9wMAAAAA4KQo/QAAAAAAOClKPwAAAAAATorSDwAAAACAk6L0AwAAAADgpCj9AAAAAAA4KUo/AAAAAABOitIPAAAAAICTovQDAAAAAOCkKP0AAAAAADgpSj8AAAAAAE6K0g8AAAAAgJOi9AMAAAAA4KQo/QAAAAAAOClKPwAAAAAATorSDwAAAACAk6L0AwAAAADgpCj9AAAAAAA4KUo/AAAAAABOitIPAAAAAICTovQDAAAAAOCkKP0AAAAAADgpSj8AAAAAAE6K0g8AAAAAgJOi9AMAAAAA4KQo/QAAAAAAOClKPwAAAAAATorSDwAAAACAk6L0AwAAAADgpCj9AAAAAAA4KUo/AAAAAABOitIPAAAAAICTovQDAAAAAOCkKP0AAAAAADgpSj8AAAAAAE6K0g8AAAAAgJOi9AMAAAAA4KQo/QAAAAAAOClKPwAAAAAATorSDwAAAACAk6L0AwAAAADgpCj9AAAAAAA4KUo/AAAAAABOitIPAAAAAICTovQDAAAAAOCkKP0AAAAAADgpSj8AAAAAAE6K0g8AAAAAgJOi9AMAAAAA4KQo/QAAAAAAOClKPwAAAAAATorSDwAAAACAk6L0AwAAAADgpCj9AAAAAAA4KUo/AAAAAABOyu1OB7AmNDRUs2bN0tGjR5WcnKw6depoyJAhat26dY7HuHjxombOnKk//vhDly9fVrly5dSzZ089++yz8vDwyMf0AAAAAADceQ55p3/FihUaOHCg9u7dq3r16qlBgwbau3evBg8erKVLl+ZojAsXLug///mPli5dKn9/f7Vr105xcXGaPn26nnnmGSUnJ+fzVwEAAAAAwJ3lcHf6L126pHHjxqlIkSJavHixgoKCJEnh4eEaOHCgJk6cqHbt2qlMmTJZjvPf//5XFy5c0MiRI/X8889LkuLj4/XCCy8oNDRUCxYs0KBBg/L96wEAAAAA4E5xuDv9CxcuVFJSkgYMGGAp/JJUr149DR48WImJidne7T916pR+//13Va5cWcOGDbNs9/Hx0cSJE+Xq6qqFCxfm29cAAAAAAIAjcLjSv3XrVklSp06dMuzr3LmzJGnLli1ZjrFt2zYZhqH27dvLxSX9l1i+fHnVrl1bf//9t06cOGGn1AAAAAAAOB6HKv2GYejEiRNycXFR9erVM+yvWrWqXFxcdOLECRmGYXWctDJfo0aNTPenjX3s2DE7pAYAAAAAwDE5VOm/fv26kpKSVKxYsUxX13dzc1NAQIASEhIUFxdndZxLly5JkkqXLp3p/lKlSkmSrly5YofUAAAAAAA4JodayC8hIUGS5O3tbfUYLy8vSVJcXJz8/PyyHCftWGtjxMfH25TPxcVk+XeTyWR1fHszmUzpru1IGRwlhyNkcJQcjpDhbszhCBkKQw5HyOAoORwhgyS5mKSSPgXz44CLKe3/pOco34u7LYcjZCgMORwhg6PkcIQMjpLDETLcjTkcIYMj5rCWxXKckdU8+QJ28eJFtWnTRhUqVNCmTZsyPaZ9+/Y6d+6ctmzZYnUF/4EDB1pW6G/SpEmG/dOnT9fMmTP10ksv6bnnnrPr1wAAAAAAgKNwqOn9Pj4+kqTExESrx6Tty2o2QNo4t27dyvUYAAAAAAAUdg5V+v38/OTj46OYmBilpKRk2J+SkqKYmBh5enrK39/f6jhpz/Jbe2b/8uXL6Y4DAAAAAMAZOVTpN5lMCgwMVGpqqiIjIzPsj4iIkNlsVlBQUJbjpK3ab+2VfCdPnpSkbMcBAAAAAKAwc6jSL0mtW7eWJG3cuDHDvrRtbdu2zdEYmzZtktlsTrfv3LlzOnLkiCpUqKDAwEB7RAYAAAAAwCE5XOnv06ePPD09NWfOHB08eNCy/cCBA5o7d668vLzUt29fy/Zz587p5MmTunr1qmVbpUqV1Lp1a0VERGjatGmW7fHx8Ro7dqxSU1M1cODAgvmCAAAAAAC4Qxxq9f40ixYt0vjx4+Xu7q5mzZrJMAzt3LlTKSkpmjx5snr16mU5tn///goLC9Pw4cM1YsQIy/aoqCg98cQTunz5soKCglStWjXt2bNHly9fVps2bfTFF1/Izc2h3lgIAAAAAIBdOWTr7devn8qXL6+5c+dq9+7d8vDwUMOGDfXcc8+pefPmORqjUqVKWrZsmaZPn64tW7bo9OnTqlSpkp566ik9/fTTFH4AAAAAgNNzyDv9AAAAAAAg7xzumX4AAAAAAGAflH4AAAAAAJwUpR8AAAAAACfFanYFaPfu3YqKilJISMgduX54eLgOHjyoW7duqWzZsmratKlKlCiRb9eLiYlRQEBAum2nT59WWFiYYmJiVLx4cTVq1EhVq1bNtwySZDabdfDgQcurHZOSkuTm5iZ/f3+VK1dOdevWVfHixfM1g3T7lZEnTpxQdHS04uPjZRiGvL29VapUKQUGBsrHxyffMziC8+fP69KlSypbtqzKlCmT5bGnTp1SdHS0GjduXEDppP379+vw4cNKSUlRnTp11LBhw3y71p38PfLZZ5+pVq1a6tixo93Htrfdu3fryJEjSk5OVnBwsJo1ayaTyZQv13KUPy8k/swAAAD2wUJ+Bei1117TTz/9pCNHjuTL+P369VOrVq303HPPpdseGRmpV199VYcOHUq33c3NTf/5z3/0+uuvy9PT0245Dh48qLFjxyohIUHr1q2TdPuH13feeUdr1qzJcHzLli01fvx4lS9f3m4ZJMkwDC1evFgzZ85UTExMhn1ppcFkMqlRo0Z68cUX1ahRI7tmkKQNGzbom2++0Z49e2Q2mzM9xtXVVffff78GDRqktm3b2j2DI4iIiNCYMWO0f/9+y7Z69erptddes/p9z4/fM2azWStXrtTWrVvl6uqqXr16qU2bNkpMTNSIESO0devWdMffd999+vTTT1W2bFm7ZXCE3yPBwcEymUwaOHCgXn755Tv6RpOYmBjNnDlTf/75p4oVK6aBAweqbdu2un79uoYPH64///wz3fE1atTQp59+qurVq9stg6P8eSHxZwYAALAvSr8d7Nq1K0fHffHFF9q+fbsWLFigf37b7XUXMzg4WD179tSHH35o2Xbp0iX16dNHV65cUZkyZdSsWTOVLFlSZ8+e1R9//KG4uDg1atRI8+fPl6ura54zHDx4UP369VNiYqLq1Kmj5cuXS5IGDhyo7du3y9fXVx06dFD58uV15coV7dy5U2fPnlX58uW1bNkyu848GDNmjH744QcFBASobt26cnV11aFDh3Tp0iX17t1bVatW1alTp7Rz505duHBBJpNJr732mgYNGmSX6xuGodGjR2v16tUyDEMlSpRQtWrVVKpUKXl5eckwDCUmJury5cs6deqUrl69KpPJpP/85z/673//m293Mu+Eixcvqnfv3rp69aqKFy+uihUr6sSJE4qPj5erq6tefvllPfPMMxnOs3fpN5vNGjp0qLZt22b5PWgymfT2228rIiJCCxYsUKlSpdSuXTt5eHho+/btOnXqlKpUqaLly5fLz88vzxkc5fdIcHCwpNtff1BQkN59913Vr1/fLmPb4saNG3r00Ud15swZy38TV1dXzZkzR/PmzdMff/yhatWqqUWLFnJ1ddWOHTt07NgxlSpVSitXrlTJkiXtkuNO/3khFb4/MwpyVkxWmEXHDCFmxdzmyDPpHOXPCyl//8xw1N8jmWEW3d315wXT++2gf//+Nv0m6d+/v+XfTSaTDh8+nB+xJN3+w+fKlSvq3r273nvvPXl5eVn2Xb16VWPGjNGWLVv0zTffaODAgXm+3syZM5WYmKjRo0dbxtu4caO2b9+u4OBgzZ07N90P6cnJyZo8ebIWLlyoL774QmPHjs1zBklas2aNVq5cqe7du2v8+PGW38BJSUl67733tGbNGv3www+qVKmSJOm3337TuHHj9NFHH6l27dpq1qxZnjMsXrxYq1atUs2aNTVu3Lhs/4LbvXu33n33XX333XeqW7euHn300TxnkKRZs2bl6fxhw4blOcPnn3+uq1evql+/fhozZozc3NyUkJCg2bNna/bs2ZoyZYoSEhI0fPjwPF8rK4sWLdLWrVtVt25dDR48WLGxsZo1a5amTJkiFxcX3XfffZo7d+7/a+/e42LM+z+OvydFB1YOhdWixIzKqkTLSpvDOmyxrF2rB5acT+1aymkdbse1e1vn483NYmNjbVYOq0IUFnUrcqiEijStlEOHSfP9/dGvYUwRXemz0+f5eHg87Mw1M68ue13Nd67vdQ1q1aoFAHj69CnmzZuHvXv3YsuWLfj666/L3UBlGwGAbt26wczMDPv378egQYPQu3dvjB8/Hs2bN5fsNV5l7dq1uH37Njw8PDB+/HhkZmZi/vz5mDFjBpRKJb744gvMmTNHMxNBrVZj6dKl+Pnnn7Fx40bMmjWr3A0U9hcAnX1GMQqzYspi9+7dCA4OrrBBP8+ie2bNmjVkZggBPCum2JvMpFu/fr3kH6r/E/YXQMXuMyhtIzyLTltV31/wkX4JjBw5EhEREZDJZLC1tS31yFNCQgLu37+v8wZx69atknSUdKTfzc0NarUaYWFhWgP+Yjk5OejatSssLS2xf//+cje4urqiUaNGCAoK0ty2cOFC/PLLLwgICICTk5POY4QQ6NGjB54+fYpjx46VuwEAvL29kZqaitDQUFSvXl3rvoKCAnTv3h3t27fXWldJSUno06cPOnbsiE2bNpW7oU+fPkhPT8eRI0d0jsqUJjMzE7169ULjxo2xb9++cjcARb/4CwoKNP/9/E72ZYqXk+INQZcuXQAU7XBfnFESHh4OX19fqFQqzJw5U+tDMamP9Pfv3x9paWkICQnRHLW/desWevfuDSEEdu3apXO0W6VSoUuXLnjnnXdw6NChcjdQ2Uae318cOHAAS5cuxd9//w0DAwN06dIFI0eOfCtH/rt37w6VSoWQkBDNtnrmzBkMHz4clpaWCAsLg5GRkdZjCgsL0b17dxgYGCA0NLTcDRT2FwCdfQZAY1YMz6J7hmcIafunzYqpSBRm0lHYXwA09hlUthGeRfcM7y+K8JF+CWzevBkBAQH48ccfoVQqMXbsWHzyySc6yxXvYKUa5JfFo0eP8MEHH5Q44AcAU1NTuLi4ICIiQpLXy83NRZMmTbRue/r0KQBALpeX+JjiHePJkyclaQCKPmBp166dzht4ADAyMoKdnR0iIyO1brexsYGrq6tkMy+Sk5PRuXPnMr95B4C6deuiffv2Om3lERQUhIkTJyIpKQnvvfce+vbtK9lzl5VSqcRHH31U4ptfd3d3rFy5EhMnTsSSJUtgaWmJHj16VEjHzZs30aFDB603GM2aNcP777+PmJgYtGrVSucx1atXR+vWrSX7N6GyjTzPy8sLXbt2xfr167Fz506EhoYiLCwMVlZW6N27N7p37w47OzsYGEj/hS9paWmaN4LFij/4sLe31xnwA0VvXFq1aiXZ+qCwvwDo7DMAGrNieBbdMzxDSBuFWTHl/T1VPFujvCjMpKOwvwDo7DMobCM8i+4ZCvsLoPJn3vKgXyLe3t7o1KkT/P39MXXqVISEhGDevHkwNzev1K6mTZtqHeUtyYMHDyR7M29lZYXY2Fg8ffpUsyOxt7cHACQmJuL999/XeYxarcaVK1dgYWEhSUPxc6alpZV6f2ZmJh4/fqxzu6GhIR49eiRJg7m5Oe7fv//aj1MqlSUOPt6UjY0Ndu7ciUGDBiE5ORkKhQLdunWT7PnLwszMDH///Xep93/00UeYN28evvvuO/j7+6NevXoVMr3LwMCgxH93FxcXpKamIisrq8TzILOysiSbpktlG3mRqakppkyZgpEjRyIgIAABAQFISUnRvHE0NjaGnZ0d3nvvPTRs2BDffPONJK9rZmaGjIwMrduK//vFqYDPu3//vmTn3VHYXwB09hkA8Pvvv6NOnTrYtm2b5kMyFxcXzayYGTNmaN7AA0XrYs6cOThx4gT+/PNPSd7Ed+rUqVyz6CrS8ePHUa9ePZ0BP1D0Qczy5cvRtWtXBAUFSTLoj46OhkKh0Hqus2fPQiaTYe7cuTrrxsjICLNmzcLJkydx7NgxSQf9pqamWLp0KTp16oSlS5fi4MGDOHz48FudIfTrr7+idu3a2LZtW5k+JGvbti22bduGXr16YdeuXZK8iW/QoAHOnTsHmUyG1500K+WRw1OnTuHdd9/FzJkzNR+sm5iY4Ouvv4ajoyN8fX2xdu1a1K5dW2uQKyUK+wuAzj6DwjZy7NgxNGjQACtXrtT8fli4cKFmFt3s2bO1Tj0wMDCAv78/QkJCcPz4cUkG/b/88gssLS2xePFird9R1atXx+zZs3Hy5EmsXr1aM4vKw8MDTZs2RZ8+ffDf//5Xsn8fCvsLoOgDuvLMvC3voF/6wzZVWJMmTbBr1y588803CAsLg6enp2RTccsqPj4eBw8exM2bNwEAffv2xblz53D37t0Sl4+OjkZ0dDTs7Owkef2ePXvi3r17mD59uuZ/7E8++QSNGjXCggULdN44q9VqLFq0CGlpaZop4FKws7PDtWvXSpz6Gxsbi9jYWJ1PXJOTk3Hu3DnJPol1dnZGdHQ0goODy/yYPXv2ICYmBq6urpI0FKtbty5Wr14NY2NjzJ8/H7m5uZI+/6s4ODjg0qVLiI2NLXWZAQMGYOzYscjPz8f48eMRHR0teYe9vT2ioqJ0OqZOnYqIiIgSB/znzp3DxYsX0bp1a0kaqGwjpalduzbGjRuH8PBw/Pzzz/D29oaVlRVyc3MRFRWFoKAgbNy4UbLXc3R0RGxsrGZbVavVWLFiBYCiKc0vnnMIFO23YmJi4ODgIEkDhf0FQGufcfPmTTg5OZU4KwbAS2fFpKamStKwefNmzJkzB8bGxlAqlRgwYAC2bt2q86dDhw4AoHN7RXr06BFat279yll0ycnJkrxeeWYIvewD1/Lw8vLC0aNHMWrUKNSoUQOhoaEYNGgQunfvjuXLl+Py5culnjdbXsnJyXB1dX2jWTG3bt2SpKF4FocQAk2aNMGhQ4cQFhZWpj9SnJZUTKlUws7O7qUz6apVq4YlS5ZINrvgRRT2FwC9fUZlbiNpaWlo3br1G82iS09Pl6QhISEBDg4OJGbRVfb+AiiaeWttbQ0hBKysrDBx4kRMmDDhlX+KlysvPtIvMZlMhjFjxsDd3R3+/v6YMGEC+vbtK+mn7C9z7do1TJ06FUDRm45mzZqhoKAAY8eOxfbt2zUzDxISEnD48GFs3boVQggMHjxYktcfNWoUQkNDERwcjEuXLsHb2xutW7fGzJkzMXPmTPTs2ROenp5o3LgxlEolQkJCcPv2bdSvX1/nIknl8dVXX+H8+fOac9k8PDxgZmaGCxcuYPny5RBCwNvbG0DR+XC7d+9GQEAA8vLyJPsk3NfXF+Hh4fDz88PevXvRtWtXtGjRAhYWFjAxMYFMJkNeXh7+/vtvJCYmIjQ0FKdPn4aZmRl8fX0laXhey5YtMWLECKxZswZbt27F+PHjJX+N0gwdOhSRkZEYPnw4hg8fDhcXlxI/wf3mm2+QkZGB3377DUOHDpXsnLJiI0aMwLlz5/DVV19h4MCBGD16dKlXi01ISMD+/fuxfft2AJDkaB1AZxt5FQMDA7i6umoGk1lZWbh06RJSU1ORmZkp2euMGzcOkZGR+PrrryGXy5GZmYn09HQ0aNAAXl5eGDt2LCZMmIAOHTrA0NAQ4eHhmilyQ4cOlaSBwv4CoLXPoDArBuBZdMV4hpA2KrNipk2bhocPH2Lfvn3YvXs3Zs6cKdlzlxWFmXRU9hcAvX0Gz6LjWXTFKn3mrWAVRqVSiR9++EG0atVKuLu7i759+wqFQlFhr5eWlibCwsLE6tWrxfjx44WHh4eQy+VCLpcLhUIhUlNTNctOmjRJc9/3338vaUdWVpbw9/cXCoVC509xS/Hf5XK56Nu3r0hMTJS0QQghli1bpvV6z7/u7NmzNctFRkYKuVwu7O3txebNmyVtuHr1qvDy8iqxo6QuT09PERMTI2nD83Jzc8W+ffvEsWPHKuw1SrNx40ZhZ2cnFAqF6Nu370uXXbx4sdb/u1Las2ePsLe3FwqFQqSkpJS63JQpUzSvv2HDBkkbKGwjcrlc+Pn5SfqcbyokJER07NhR8/N+9NFHIjY2VmRlZYmePXuWuI5++uknSRso7C+EoLPPGDJkiLCzs3ut5/7rr7+EQqEQw4cPl7xHrVaLDRs2CAcHB/Hhhx+KsLAwzX1Tp06t0N+txdtgcHCwSEpKEkIIsWXLFuHg4CDu3LlT4mOioqJEq1atxODBgyVpWLlypZDL5WLKlClCpVIJIYR48uSJ8PDwEAMGDBCPHj3SWr6wsFDMnz9fKBQKsXDhQkkahHj1fqOwsFCcPXtWzJ8/X3Tr1k2zTUu9L588ebJQKBTiwIEDZX5MYGCgkMvlwtfXV7IOIYTIz88XvXr1EnZ2diIhIUHS5y4LHx+fMm2ry5cvF3K5XLRr105ERUVJut1Q218IUXn7DCrbyOjRo4VCoRAhISGa1/322281v7/Onz+v85ioqCihUCiEj4+PJA2DBw/WanheTEyMaNWqlejXr5/W7bdv3xaOjo46t5cHpf2FEEJcv35dODo6Cjc3N5GTkyP585eGr97/FkRFRWH69OlISUmR7GroZZWdnY0rV67g6tWrGD58uObckTVr1iA+Ph4DBw7Ehx9+WCGvnZaWhqNHj+LKlSu4ffs2Hj9+jPz8fJiYmKBu3bpo2bIlOnfujI4dO1bIBcKAoquA79mzB/Hx8VCr1bC2tka/fv20PllLT0/HiRMn0LlzZzRq1KhCOiIjI3Hq1CkkJCQgIyMDubm5MDAwgKmpKSwtLdGiRQu4ubmhffv2enOV0JLcuHED+/fvh5GRESZNmvTSZU+ePIk1a9bg8uXLkl+QKz09HYcPH8awYcNKXSYwMBCXL1/G559/LtnU/hdV5jYyZMgQdOrUCWPGjJH0ed9UYWEhrl+/DgMDA9ja2mqOZmZlZWHz5s04f/48Hj58CBsbG3zxxRcV8lU6VPYXQOXvM8LDwzFmzBiYmJi81qyYgoICbNq0CW5ubpI3AUWz2fz9/ZGQkKCZRfevf/1L0m/5eNHzV+MGns2ii4uLQ8uWLUudRZeXl4cVK1ZIcmHS3NxcDBw4EPHx8WjatKlmhlBmZiZmzpyJ6tWrlzpDaP/+/ZJ9/3VJ32TwMi/OEJJiiipQ9K0rn332GXJycuDq6lrmWTGmpqYIDAyU/IJqJ0+exOjRo9GzZ0/N6UlvS/G2amZm9tKZdAAwa9Ys/PbbbzA0NET9+vWRnp4uyXZDdX8BvP19BpVt5OLFixg8eDCEEFqz6CwtLeHl5YXdu3eXOIuu+CKMUvyODQ0NxcSJE1G9evUSZ9FlZ2djwYIFGDBggNYsuocPH2Lx4sXo16+fBGuC3v4CKBqHrVmzBr6+vm9t5i0P+t+S3NxcBAQEvJXvImdMn+Tl5ZV63ixjrOLs3bsX8+bNQ2FhIUJCQmBlZVXiclOnTkVwcDBkMhm++eabCv8gqaCgACtWrMDWrVthaWkJc3NzXL9+vcIG/ffu3cOVK1c0H6BfvXpVc50cmUyG0NBQNG7cGEDRKRpHjx4FUHRK0LRp0yTryM7OxuLFi/HHH3/o3CeeuyBU8ds6hUKBZcuWSfqG9XUHNBWpeDAXHx//yg++hBBo0aIFFi1aVOKpEP90mzZtwsqVK6FWqyGXy7W+EvZFS5Yswc8//wwAkh6Iorq/AN7uPoPSNhIaGoq5c+dqprY3atQIq1atQpMmTfDll1/qnK8uhMCYMWMwefJkyRp++uknbNq0SWcbFULgiy++wPz58wEAp0+fho+PDwwNDTF58uQSv2ayPKjtL/Ly8nD48GGYm5vDw8OjQl7jRTzoZ4wxxv4hVCoVUlJS8PTpU1hbW0t+1f4XUZkVUxKeRcczhIDKnxVDBYWZdJT3F8Db2WdQ20Z4Fp22qry/4EE/YxUoPz8f69atw8GDB6FUKtGwYUP06NEDPj4+pV5F1M/PDwcPHpT0FzGFDgoNVDooNHAHvYZiycnJiIiIgKGhIbp166aZJrt582Zs3LhRc+EjExMTDB48GL6+vlpfvVSV8Cw6xt5cVZxJx/sMVlXxoJ+xCqJSqTB06FDExMRofYevTCZD/fr1sWLFCrRt21bncX5+fpKea0ahg0IDlQ4KDdxBr6HY+vXrsWbNGs3XOJmZmWHDhg24fv06FixYAJlMhiZNmqB69eq4efMmCgsL4e7urvlGg4r25MkT5OTkQAgBU1NTra/oelsoNFDpoNBAqYMxxljJquahAYmV9/vEnZ2d9aaDQgOVjs2bN+PixYtwdHTEvHnzYG1tjdjYWKxatQrnz5+Hj48P1q5di06dOpX7tah3UGig0kGhgTvoNQBFF8NauXIlatWqBS8vLzx+/Bh//vkn/P39AQAWFhZYs2YN2rRpAwBISUnBt99+i/DwcOzZsweff/655E1KpRKBgYE4efIkEhISkJeXp3V/jRo10LJlS7i7u2PQoEGSXTDudRvkcjk6d+5cYQ1l7aCwLiq6gVJHZaLwPoMxVjZUZvNVZgcf6ZeAQqF44/M+ZDKZZP8zUeig0EClw9PTExkZGfjzzz91vh922bJl+M9//gNjY2Ns2bJF6yii1EcPKXRQaKDSQaGBO+g1AMCIESNw/vx5/P7775qLrx0/fhzjxo2DTCYr8Urw6enp6NWrF1q2bIndu3dL0lFsz549WLRoEfLz8yGEgIGBAerUqaP5Xu38/Hw8ePBAMyvBxMQECxYsgKenp141UOmg0ECpo7JReJ/BGHs1KrP5KruDj/RLYPHixVi4cCFycnJQv359WFtbV9kOCg1UOlJSUuDq6qoziACAKVOmwNDQEOvXr8f48eMREBBQIV8JQqWDQgOVDgoN3EGvAQAuX76Mdu3aaT2/h4cHmjdvjqSkJHTs2FHnMQ0aNECbNm1w8eJFSVsiIiIwe/Zs1KxZE2PHjkX37t3RrFkzVKtWTWu5wsJC3Lx5EyEhIdiyZQv8/f1hYWEBV1dXvWig0kGhgVIHhaPsFN5nADTWBYUGKh0UGqh0UGgA6Mzmq+wOHvRLoH///rC2tsbIkSPx5MkTzJkzBy1atKiSHRQaqHQYGBjg6dOnpd7/9ddf4/79+wgMDMSoUaOwe/duWFpa6mUHhQYqHRQauINeA1B0gSkjIyOd25s3b44bN25ojpy+qFq1apB60t6mTZtgZGSEbdu2wcHBodTlqlWrBltbW9ja2qJTp04YNGgQNmzYIMngjkIDlQ4KDZQ6vL29K/0oO4X3GQCNdUGhgUoHhQYqHRQaAODQoUOoXbs2NmzYoPlwv127dtixY4dmNt/EiRN1ZvNJrbI7eNAvEScnJyxZsgS+vr6YNWsWAgMDq2wHhQYKHc2bN0dMTAwyMjJgYWFR4jJz587F3bt3ERERgREjRmD79u162UGhgUoHhQbuoNcAAM2aNUNUVBQyMzO1zoH+8ccfMXnyZM306eelp6cjKioKNjY2krbExcXB1dX1pQO7F7Vu3RoffPABLl++rDcNVDooNFDqoHKUvbLfZwA01gWFBiodFBqodFBoAOjM5qv0DsEk5efnJxQKhQgKCqryHRQaKrNjx44dQi6Xi08//VScO3dO5ObmlrjckydPRL9+/YRcLhceHh6iX79+QqFQ6FUHhQYqHRQauINegxBC/Pzzz0Iul4vevXuLsLAwoVKpSl22sLBQhIeHi48//lgoFAqxc+dOyTqEEMLV1VWMHj36tR83cuRI4eTkpDcNVDooNFDqEEKI6Oho4ezsLBwdHUV8fLykz/26Kvv9DoV1QaGBSgeFBiodFBocHR3F8OHDX7rM7NmzNb/b09PThRBCTJ06VdLf8ZXdYSDtRwhsypQp+PTTT6FUKqt8B4WGyuzw9vaGu7s7rl69iqFDh2LAgAElLmdqaopt27ahTZs2uHv3rqRf/0Wlg0IDlQ4KDdxBrwEABg8ejD59+uDGjRuYMGECbt++XeqyU6dOxZgxY3D79m24u7vD29tb0paWLVvi7NmzuHHjRpkfExcXhzNnzsDe3l5vGqh0UGig1AE8O8qem5uLWbNmSfrcr6uy3+9QWBcUGqh0UGig0kGh4fnZfKWZO3cuOnXqhLt372LEiBF48OCB/nWU+2MDxlipCgsLxa5du8TAgQPFmDFjXrqsSqUSP/74o2jTpo2knyxS6aDQQKWDQgN30GsodvDgQTF27FhRUFBQ6jJLly4VH3/8sdiyZctLl3tTkZGRQi6Xi3bt2om1a9eKa9eulfg6hYWFIjExUWzcuFG4uLgIhUIhTpw4oTcNVDooNFDqeF5lH2WnhMK6oNBApYNCA5WOymygMpuvsjv4K/sYIyY7OxuxsbFwc3Or8h0UGqh0UGjgDnoNFWnfvn2YN28eCgoKABRd8NDc3BzGxsaQyWTIy8tDVlYWCgsLIYRAjRo1MG3aNElnHVBooNJBoYFSR7H09HSsWLECNjY2GDVqVIW8xj8FhXVBoYFKB4UGKh2V2aBWqzFu3DiEh4dDJpOhefPmCA4OLnHZhw8fYtSoUYiJidFchFCqWX2V3cGD/rckKSkJ9+/fR7t27ap8B4UGKh0UGqh0UGig0kGhgTvoNVRGR0ZGBnbs2IGIiAgkJiZCpVJp3W9qagpbW1u4ubmhf//+aNy4sV42UOmg0ECpgzoq+w3Gqjq1Wo3AwEAEBQXB3NwcGzZsKHXZgoICrFy5Ejt37kR+fr6kp/JVZgcP+t8SPz8/BAcHS34O6D+xg0IDlQ4KDVQ6KDRQ6aDQwB30Gih0ZGdnIzc3FzKZDGZmZqhZs2aVbKDSQaGBUgc1lb29MsbeHJXZfFJ18IX8GGOMMVYmtWvXRsOGDdGgQQMolUqcP3++SjZQ6aDQQKnjeUlJSSQ6KKCwLig0UOmg0EClg0JDaR21a9d+6wP+iuzgQT9jjDHGXtv69esxdOjQKt9ApYNCA3fQRGFdUGig0kGhgUoHhYaq0sGDfsYYY4wxxhhjTE/xoJ8xxhhjjDHGGNNTPOh/S2xsbODi4lLZGSQ6KDRQ6aDQQKWDQgOVDgoN3EGvgVIHY+zVeHtljFHBg/63ZNy4cdixY0dlZ5DooNBApYNCA5UOCg1UOig0cAe9BkodjLFX4+2VMUaFYWUH6Bu1Wo3Lly/jxo0byMzMhEqlgqGhId555x00atQIDg4OqFu3bpXooNBApYNCA5UOCg1UOig0cAe9BkodL0PhKCaFBiodFBqqckdOTg4SExNx//595OTkQAgBExMTWFhYwNbWFqampm+t5UUU/k0oNFDpoNBApYNCQ1XpkAkhRIU8cxUjhEBAQADWrl2LBw8e6Nwnk8kAADKZDC4uLvD19a2Qf1QKHRQaqHRQaKDSQaGBSgeFBu6g10CpgzFWNiEhIdi+fTuio6OhVqtLXKZatWpo27YtfHx84O7u/pYLGWOMB/2SmTFjBoKCglCnTh04ODigWrVqiIuLg1KpRL9+/dCsWTMkJSXhr7/+wr179yCTyeDn5wcfHx+966DQQKWDQgOVDgoNVDooNHAHvQZKHS+icBSTQgOVDgoNVb1DCIFp06bhwIEDEEKgXr16sLa2hoWFBYyNjSGEQH5+PjIyMpCUlITMzEzIZDJ88cUXmDdvnuYDPKlR+Deh0EClg0IDlQ4KDVW6Q7ByCw4OFnK5XEyZMkU8efJEc3t+fr6YPXu2cHZ2FsnJyZrbjx07Jtzc3IRCoRBnzpzRqw4KDVQ6KDRQ6aDQQKWDQgN30Gug1PG8o0ePisGDBws7OzuhUChK/GNvby+GDh0qTpw4obcNVDooNHBHkZ07dwq5XC769OkjoqKiXrn8hQsXhJeXl1AoFCIwMFDSFiFo/JtQaKDSQaGBSgeFBu4Qgo/0S8Db2xupqakIDQ1F9erVte4rKChA9+7d0b59e/zwww+a25OSktCnTx907NgRmzZt0psOCg1UOig0UOmg0EClg0IDd9BroNQB0DiKSaGBSgeFBu7Q1qdPH6Snp+PIkSOoU6dOmR6TmZmJXr16oXHjxti3b1+5GwAa64JCA5UOCg1UOig0cId2ACsnFxcXMW7cuFLvHzdunOjYsaPO7T4+PuLDDz/Uqw4KDVQ6KDRQ6aDQQKWDQgN30Gug1CEEjaOYFBqodFBo4A5tbdq0EZMmTXrtx02cOFE4OTlJ0iAEjXVBoYFKB4UGKh0UGrjjGf7KPgmo1WqkpaWVen9mZiYeP36sc7uhoSEePXqkVx0UGqh0UGig0kGhgUoHhQbuoNdAqQMAfv31V9SuXRvbtm2Ds7PzK5dv27Yttm3bhnfeeQe7du3SmwYqHRQauEObubk57t+//9qPUyqVOjN5yoPCuqDQQKWDQgOVDgoN3PEMD/olYGdnh2vXriE0NFTnvtjYWMTGxqJ58+ZatycnJ+PcuXM6t//TOyg0UOmg0EClg0IDlQ4KDdxBr4FSR/Hzurq6lnnaMgDUrVsX7du3x61bt/SmgUoHhQbu0Obs7Izo6GgEBweX+TF79uxBTEwMXF1dJWkAaKwLCg1UOig0UOmg0MAdzxiW+xkYvvrqK5w/fx7ffvstRowYAQ8PD5iZmeHChQtYvnw5hBDw9vYGAKSnp2P37t0ICAhAXl4ehgwZolcdFBqodFBooNJBoYFKB4UG7qDXQKkDoHEUk0IDlQ4KDdyhzdfXF+Hh4fDz88PevXvRtWtXtGjRAhYWFjAxMYFMJkNeXh7+/vtvJCYmIjQ0FKdPn4aZmRl8fX0laQBorAsKDVQ6KDRQ6aDQwB3PKfcJAkwIIcSyZcuEXC7XufqiXC4X3333nWa5yMhIIZfLhb29vdi8ebNedlBooNJBoYFKB4UGKh0UGriDXgOljsmTJwuFQiEOHDhQ5scEBgYKuVwufH199aaBSgeFBu7QdfXqVeHl5VXiNlvSNuzp6SliYmIke30haKwLCg1UOig0UOmg0MAdz/DV+yV05swZBAYGIiEhAWq1GtbW1ujXrx+6deumWSY9PR0nTpxA586d0ahRI73toNBApYNCA5UOCg1UOig0cAe9Biodt27dwmeffYacnBy4urqW+SimqakpAgMDJTndgEIDlQ4KDdxRusjISJw6dQoJCQnIyMhAbm4uDAwMYGpqCktLS7Ro0QJubm5o3769ZFcCL0ZhXVBooNJBoYFKB4UG7niGB/0V6MmTJ8jJyYEQAqampqhZs2aV7aDQQKWDQgOVDgoNVDooNHAHvYbK7Lh27Rr8/f0RHx//yoGKEAItWrTAokWL8P777+tVA5UOCg3cQROFdUGhgUoHhQYqHRQauKMID/olpFQqERgYiJMnTyIhIQF5eXla99eoUQMtW7aEu7s7Bg0ahLp16+ptB4UGKh0UGqh0UGig0kGhgTvoNVDqKFaZRzEpNVDpoNDAHTRRWBcUGqh0UGig0kGhoap38KBfInv27MGiRYuQn58PIQQMDAxQp04d1KhRAwCQn5+PBw8eQK1WAwBMTEywYMECeHp66l0HhQYqHRQaqHRQaKDSQaGBO+g1UOpgjDHGmB4p91UBmDh16pSQy+Wibdu2Yv369SIxMVE8ffpUZ7mnT5+KhIQEsW7dOtG2bVvRqlUrcfbsWb3qoNBApYNCA5UOCg1UOig0cAe9BkodjLFXi4qKKtcfxhh7m3jQL4EhQ4YIBwcHcenSpTI/JjY2Vtjb24thw4bpVQeFBiodFBqodFBooNJBoYE76DVQ6mCMvVpZrthf2p9WrVpVdj5jrIoxrOyZBvogLi4Orq6ucHBwKPNjWrdujQ8++ACXL1/Wqw4KDVQ6KDRQ6aDQQKWDQgN30Gug1AEA0dHR5Xq8s7OzXjRQ6aDQwB3aFi9ejIULFyInJwf169eHtbV1uZ/zTVBYFxQaqHRQaKDSQaGBO57hQb8EjIyMUK1atdd+nEwmg0ql0qsOCg1UOig0UOmg0EClg0IDd9BroNQBAN7e3m988SCZTIYrV67oRQOVDgoN3KGtf//+sLa2xsiRI/HkyRPMmTMHLVq0KPfzvi4K64JCA5UOCg1UOig0cMczPOiXQMuWLXH27FncuHGjzN+hGBcXhzNnzsDJyUmvOig0UOmg0EClg0IDlQ4KDdxBr4FSB0DjKCaFBiodFBq4Q5eTkxOWLFkCX19fzJo1C4GBgW+9gcK6oNBApYNCA5UOCg3c8ZzKPr9AH0RGRgq5XC7atWsn1q5dK65duyYKCgp0lissLBSJiYli48aNwsXFRSgUCnHixAm96qDQQKWDQgOVDgoNVDooNHAHvQZKHcWio6OFs7OzcHR0FPHx8ZI//z+lgUoHhQbuKJmfn59QKBQiKCioUl6fwrqg0EClg0IDlQ4KDdxRhL+yTyL79u3DvHnzUFBQAAAwMDCAubk5jI2NIZPJkJeXh6ysLBQWFkIIgRo1amDatGnw9vbWuw4KDVQ6KDRQ6aDQQKWDQgN30Gug1FHs6NGj8PX1xfvvv18pRzGpNFDpoNDAHbrS09OxYsUK2NjYYNSoUZXSQGFdUGig0kGhgUoHhQbuAHjQL6GMjAzs2LEDERERSExM1DnH0tTUFLa2tnBzc0P//v3RuHFjve2g0EClg0IDlQ4KDVQ6KDRwB70GSh3F/P39ceDAAXz//ffo27dvhb4W5QYqHRQauIMmCuuCQgOVDgoNVDooNFT1Dh70V6Ds7Gzk5uZCJpPBzMwMNWvWrLIdFBqodFBooNJBoYFKB4UG7qDXQKGDwlFMCg1UOig0cAdNFNYFhQYqHRQaqHRQaKjqHTzoZ4wxxhhjjDHG9JRBZQcwxhhjjDHGGGOsYvCgnzHGGGOMMcYY01OGlR3AGGOMMZpSU1PRtWvXEu8zMjKCqakprKys4Obmhi+//BKNGjWS9PVv3LiB5s2bS/qcjDHGWFXD5/QzxhhjrETPD/odHBxQvXp1zX0FBQXIzMzE3bt3IYSAmZkZFi9ejJ49e5b7dTMyMrBo0SKkpKTgt99+K/fzMcYYY1UZH+lnjDHG2CutXLkSVlZWOrffu3cPP/zwAw4ePIipU6eidu3a6NChQ7le69SpUzh8+DDs7e3L9TyMMcYY43P6GWOMMVYODRs2xLJly9CjRw8UFBRg1qxZKCgoqOwsxhhjjP0/HvQzxhhjrFxkMhnmzp2LGjVq4M6dOwgODq7sJMYYY4z9P57ezxhjjLFyq1evHjw8PHDkyBEcP34c/fr109yXkpKC7du34+zZs7hz5w5UKhXMzc3Rpk0bDBkyBB988IFm2S5duuDOnTsAgLi4OMjlcjRu3BjHjh3TLKNSqRAQEIADBw4gKSkJQghYW1vD09MTgwcPRo0aNd7eD84YY4wRx4N+xhhjjEnCyckJR44cwYULFzS3RUREYMKECcjLy0OtWrXQpEkT5OfnIyUlBaGhoQgLC8O///1veHp6Aii6YKCRkRFu3boFU1NTKBQKWFhYaJ4vKysLo0aNQmxsLAwMDPDee+/B2NgY169fx5UrV3Dw4EFs2bIFderUees/P2OMMUYRT+9njDHGmCQaN24MALh//z4KCgqgUqkwY8YM5OXlYdiwYTh9+jSCgoJw+PBhnDhxAh07doQQAuvWrdM8x6pVqzBmzBgAgLW1NXbt2oVVq1Zp7p8+fTpiY2Ph5OSEP//8E0ePHsUff/yBsLAwuLi4IC4uDrNmzXq7PzhjjDFGGA/6GWOMMSYJMzMzzd+zs7Nx+fJl5OTkoEGDBvD399f6yr/69etjwoQJAICbN29CrVa/8vkvXbqE48ePw9zcHOvWrUOTJk009zVq1AirVq2CmZkZwsLCcO3aNQl/MsYYY+yfiwf9jDHGGJPE81ftl8lkcHZ2RlRUFI4ePYpq1arpLG9iYgIAUKvVyM/Pf+Xzh4WFAQA6duyIunXr6txfr149zfUBTp48+UY/A2OMMaZv+Jx+xhhjjEni8ePHmr/XqlVL83djY2PExcXhypUrSE5ORnJyMuLj43Hz5k3NMmU50n/jxg0AwIULFzBo0KASl0lNTQUAredmjDHGqjIe9DPGGGNMEklJSQAAKysrzVT+8+fPY8mSJYiLi9MsJ5PJ0LRpU3h5eeGPP/4o8/MXf6igVCqhVCpfuuyjR49eN58xxhjTSzzoZ4wxxpgk/ve//wEAHB0dAQDx8fHw8fGBSqWCi4sL+vbtC7lcjubNm6NmzZq4efPmaw36i08HmDZtGnx8fCTvZ4wxxvQRD/oZY4wxVm5paWk4c+YMAKBXr14AgB07dkClUqFDhw7YsmWLznn99+7de63XaNq0KYBn0/xLcuXKFchkMrz33nuoWbPmaz0/Y4wxpo/4Qn6MMcYYK7cFCxZArVbD1tYWHh4eAIA7d+4AAORyeYkX8tu7d6/m74WFhZq/GxiU/Pbko48+AgAcPXoUmZmZOvc/evQIw4YNw6efforDhw+/8c/CGGOM6RMe9DPGGGPsjd26dQu+vr4ICwuDkZERFixYoBngN2vWDABw6NAh3L59W/OY7OxsLF68GMHBwZrbnr96v6mpKYCic/dVKpXmdldXV7Rr1w4PHz7EmDFjtJ4zPT0d48ePR3Z2NiwsLODl5VUhPy9jjDH2TyMTQojKjmCMMcYYPampqejatSsAwMHBQXNxPqBokK5UKpGRkQEAqFmzJn788Ud06dJFs0xKSgr69++Phw8fwtDQEDY2NgCKPihQqVRQKBS4d+8esrKysG/fPtjb2wMouvJ+r169IITAu+++i4YNG2LXrl0Aigb3I0aMQEJCAmQyGWxtbWFgYICkpCQUFBSgZs2a2LlzJ1q1avVW1hFjjDFGHQ/6GWOMMVai5wf9LzI0NEStWrVgY2MDNzc3DBw4EHXr1tVZ7s6dO1i9ejUuXLiAe/fuwdjYGNbW1vjkk0/g7e2N6dOn4+DBg5g0aRImTpyoedzevXuxceNGpKWlwdzcHEFBQahfvz4AIDc3F7/88gsOHz6sGexbWlqiU6dOGD16NKysrCpmhTDGGGP/QDzoZ4wxxhhjjDHG9BSf088YY4wxxhhjjOkpHvQzxhhjjDHGGGN6igf9jDHGGGOMMcaYnuJBP2OMMcYYY4wxpqd40M8YY4wxxhhjjOkpHvQzxhhjjDHGGGN6igf9jDHGGGOMMcaYnuJBP2OMMcYYY4wxpqd40M8YY4wxxhhjjOkpHvQzxhhjjDHGGGN6igf9jDHGGGOMMcaYnvo/8IpJW9Q1U3gAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(rc={'figure.figsize':(15, 10)})\n",
    "sns.set(font_scale=2)\n",
    "sns.set_style(style=None, rc=None )\n",
    "ax1 = sns.barplot(x = ukraine[\"Date\"], y = ukraine[\"Volume\"], alpha=0.8, palette = bar_colors)\n",
    "plt.xticks(ticks = ax1.get_xticks(), labels = ukraine[\"day\"].values, rotation = 90)\n",
    "plt.ylabel(\"TSLA Trade Volume (Hundred Millions)\")\n",
    "plt.title(\"October 3rd, 2022 Tweet\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "9ff6c4bb-914f-4b66-85b7-34e12eb868b1",
   "metadata": {},
   "outputs": [],
   "source": [
    "## tesla stock 20 days before and 50 days after\n",
    "#August 7th, 2018 tweet \n",
    "# datetime.datetime.strptime(date_time_str, '%Y-%m-%d %H:%M:%S.%f')\n",
    "start_date = datetime.datetime.strptime(\"2020-12-16\", \"%Y-%m-%d\") - timedelta(days = 20)\n",
    "end_date = datetime.datetime.strptime(\"2020-12-16\", \"%Y-%m-%d\") + timedelta(days = 20)\n",
    "pronouns_nightmare = tesla_stock[(tesla_stock[\"Date\"] > start_date) & (tesla_stock[\"Date\"] <= end_date)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "29ec388c-b4e7-4f9c-9af5-f7536a23d865",
   "metadata": {},
   "outputs": [],
   "source": [
    "bar_colors = []\n",
    "for date in pronouns_nightmare[\"date\"]:\n",
    "    if date == \"2020-12-16\": \n",
    "        bar_colors.append(\"#1DA1F2\")\n",
    "    else:\n",
    "        bar_colors.append(\"#b0b0b0\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "d3c4ee00-0cf7-4545-ada5-b27c4be218da",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'December 16th, 2020 Tweet')"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(rc={'figure.figsize':(15, 10)})\n",
    "sns.set(font_scale=2)\n",
    "sns.set_style(style=None, rc=None )\n",
    "ax1 = sns.barplot(x = pronouns_nightmare[\"Date\"], y = pronouns_nightmare[\"Volume\"], alpha=0.8, palette = bar_colors)\n",
    "plt.xticks(ticks = ax1.get_xticks(), labels = pronouns_nightmare[\"day\"].values, rotation = 90)\n",
    "plt.ylabel(\"TSLA Trade Volume (Hundred Millions)\")\n",
    "plt.title(\"December 16th, 2020 Tweet\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "1fca3f0a-50ac-4087-8930-d8a14f6ac5cf",
   "metadata": {},
   "outputs": [],
   "source": [
    "## tesla stock 20 days before and 50 days after\n",
    "#August 7th, 2018 tweet \n",
    "# datetime.datetime.strptime(date_time_str, '%Y-%m-%d %H:%M:%S.%f')\n",
    "start_date = datetime.datetime.strptime(\"2020-07-24\", \"%Y-%m-%d\") - timedelta(days = 20)\n",
    "end_date = datetime.datetime.strptime(\"2020-07-24\", \"%Y-%m-%d\") + timedelta(days = 20)\n",
    "pronouns_suck = tesla_stock[(tesla_stock[\"Date\"] > start_date) & (tesla_stock[\"Date\"] <= end_date)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "390152da-e584-4946-801e-193ff3fb77ab",
   "metadata": {},
   "outputs": [],
   "source": [
    "bar_colors = []\n",
    "for date in pronouns_suck[\"date\"]:\n",
    "    if date == \"2020-07-24\": \n",
    "        bar_colors.append(\"#1DA1F2\")\n",
    "    else:\n",
    "        bar_colors.append(\"#b0b0b0\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "82c69007-e94d-4fd9-affd-982f6c91adb1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'July 24th, 2020 Tweet')"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(rc={'figure.figsize':(15, 10)})\n",
    "sns.set(font_scale=2)\n",
    "sns.set_style(style=None, rc=None )\n",
    "ax1 = sns.barplot(x = pronouns_suck[\"Date\"], y = pronouns_suck[\"Volume\"], alpha=0.8, palette = bar_colors)\n",
    "plt.ylabel(\"TSLA Trade Volume (Hundred Millions)\")\n",
    "plt.xticks(ticks = ax1.get_xticks(), labels = pronouns_suck[\"day\"].values, rotation = 90)\n",
    "plt.title(\"July 24th, 2020 Tweet\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "be3cff16-9208-40c9-b44f-d34ceb2ead82",
   "metadata": {},
   "source": [
    "# Stock and Volatility Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "277310fb-527d-4da2-a07f-d702cb3b53bd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: cufflinks in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (0.17.3)\n",
      "Requirement already satisfied: setuptools>=34.4.1 in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from cufflinks) (58.0.4)\n",
      "Requirement already satisfied: pandas>=0.19.2 in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from cufflinks) (1.3.4)\n",
      "Requirement already satisfied: plotly>=4.1.1 in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from cufflinks) (5.11.0)\n",
      "Requirement already satisfied: ipywidgets>=7.0.0 in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from cufflinks) (7.6.5)\n",
      "Requirement already satisfied: ipython>=5.3.0 in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from cufflinks) (7.29.0)\n",
      "Requirement already satisfied: six>=1.9.0 in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from cufflinks) (1.16.0)\n",
      "Requirement already satisfied: colorlover>=0.2.1 in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from cufflinks) (0.3.0)\n",
      "Requirement already satisfied: numpy>=1.9.2 in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from cufflinks) (1.20.3)\n",
      "Requirement already satisfied: decorator in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from ipython>=5.3.0->cufflinks) (5.1.0)\n",
      "Requirement already satisfied: backcall in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from ipython>=5.3.0->cufflinks) (0.2.0)\n",
      "Requirement already satisfied: pygments in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from ipython>=5.3.0->cufflinks) (2.10.0)\n",
      "Requirement already satisfied: prompt-toolkit!=3.0.0,!=3.0.1,<3.1.0,>=2.0.0 in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from ipython>=5.3.0->cufflinks) (3.0.20)\n",
      "Requirement already satisfied: appnope in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from ipython>=5.3.0->cufflinks) (0.1.2)\n",
      "Requirement already satisfied: matplotlib-inline in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from ipython>=5.3.0->cufflinks) (0.1.2)\n",
      "Requirement already satisfied: jedi>=0.16 in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from ipython>=5.3.0->cufflinks) (0.18.0)\n",
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      "Requirement already satisfied: ipython-genutils~=0.2.0 in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from ipywidgets>=7.0.0->cufflinks) (0.2.0)\n",
      "Requirement already satisfied: nbformat>=4.2.0 in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from ipywidgets>=7.0.0->cufflinks) (5.1.3)\n",
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      "Requirement already satisfied: Send2Trash>=1.5.0 in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.0.0->cufflinks) (1.8.0)\n",
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      "Requirement already satisfied: nbconvert in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.0.0->cufflinks) (6.1.0)\n",
      "Requirement already satisfied: cffi>=1.0.0 in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from argon2-cffi->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.0.0->cufflinks) (1.14.6)\n",
      "Requirement already satisfied: pycparser in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from cffi>=1.0.0->argon2-cffi->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.0.0->cufflinks) (2.20)\n",
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      "Requirement already satisfied: bleach in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.0.0->cufflinks) (4.0.0)\n",
      "Requirement already satisfied: testpath in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.0.0->cufflinks) (0.5.0)\n",
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      "Requirement already satisfied: mistune<2,>=0.8.1 in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.0.0->cufflinks) (0.8.4)\n",
      "Requirement already satisfied: entrypoints>=0.2.2 in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.0.0->cufflinks) (0.3)\n",
      "Requirement already satisfied: defusedxml in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.0.0->cufflinks) (0.7.1)\n",
      "Requirement already satisfied: jupyterlab-pygments in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.0.0->cufflinks) (0.1.2)\n",
      "Requirement already satisfied: nest-asyncio in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from nbclient<0.6.0,>=0.5.0->nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.0.0->cufflinks) (1.5.1)\n",
      "Requirement already satisfied: async-generator in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from nbclient<0.6.0,>=0.5.0->nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.0.0->cufflinks) (1.10)\n",
      "Requirement already satisfied: packaging in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from bleach->nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.0.0->cufflinks) (21.0)\n",
      "Requirement already satisfied: webencodings in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from bleach->nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.0.0->cufflinks) (0.5.1)\n",
      "Requirement already satisfied: pyparsing>=2.0.2 in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from packaging->bleach->nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.0.0->cufflinks) (3.0.4)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "pip install cufflinks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "7be58bd9-eb70-480a-ba9a-b5226bcb13ae",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: yfinance in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (0.1.87)\n",
      "Requirement already satisfied: requests>=2.26 in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from yfinance) (2.26.0)\n",
      "Requirement already satisfied: numpy>=1.15 in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from yfinance) (1.20.3)\n",
      "Requirement already satisfied: multitasking>=0.0.7 in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from yfinance) (0.0.11)\n",
      "Requirement already satisfied: pandas>=0.24.0 in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from yfinance) (1.3.4)\n",
      "Requirement already satisfied: lxml>=4.5.1 in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from yfinance) (4.6.3)\n",
      "Requirement already satisfied: appdirs>=1.4.4 in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from yfinance) (1.4.4)\n",
      "Requirement already satisfied: python-dateutil>=2.7.3 in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from pandas>=0.24.0->yfinance) (2.8.2)\n",
      "Requirement already satisfied: pytz>=2017.3 in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from pandas>=0.24.0->yfinance) (2021.3)\n",
      "Requirement already satisfied: six>=1.5 in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from python-dateutil>=2.7.3->pandas>=0.24.0->yfinance) (1.16.0)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from requests>=2.26->yfinance) (2021.10.8)\n",
      "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from requests>=2.26->yfinance) (1.26.7)\n",
      "Requirement already satisfied: idna<4,>=2.5 in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from requests>=2.26->yfinance) (3.2)\n",
      "Requirement already satisfied: charset-normalizer~=2.0.0 in /Users/Kaya/opt/anaconda3/lib/python3.9/site-packages (from requests>=2.26->yfinance) (2.0.4)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "pip install yfinance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "7bd6c222-cad2-4b4b-8275-1d6bf90d2dbd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "        <script type=\"text/javascript\">\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
       "        if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
       "        if (typeof require !== 'undefined') {\n",
       "        require.undef(\"plotly\");\n",
       "        requirejs.config({\n",
       "            paths: {\n",
       "                'plotly': ['https://cdn.plot.ly/plotly-2.16.1.min']\n",
       "            }\n",
       "        });\n",
       "        require(['plotly'], function(Plotly) {\n",
       "            window._Plotly = Plotly;\n",
       "        });\n",
       "        }\n",
       "        </script>\n",
       "        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import cufflinks as cf\n",
    "import numpy as np\n",
    "import yfinance as yf\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "cf.set_config_file(theme='pearl', world_readable=False)\n",
    "cf.go_offline()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "8a180762-8213-4f3f-9c14-e758a0779abe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>date</th>\n",
       "      <th>full_day</th>\n",
       "      <th>day</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010-06-29</td>\n",
       "      <td>1.266667</td>\n",
       "      <td>1.666667</td>\n",
       "      <td>1.169333</td>\n",
       "      <td>1.592667</td>\n",
       "      <td>1.592667</td>\n",
       "      <td>281494500</td>\n",
       "      <td>2010-06-29</td>\n",
       "      <td>06-29-2010</td>\n",
       "      <td>06-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010-06-30</td>\n",
       "      <td>1.719333</td>\n",
       "      <td>2.028000</td>\n",
       "      <td>1.553333</td>\n",
       "      <td>1.588667</td>\n",
       "      <td>1.588667</td>\n",
       "      <td>257806500</td>\n",
       "      <td>2010-06-30</td>\n",
       "      <td>06-30-2010</td>\n",
       "      <td>06-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010-07-01</td>\n",
       "      <td>1.666667</td>\n",
       "      <td>1.728000</td>\n",
       "      <td>1.351333</td>\n",
       "      <td>1.464000</td>\n",
       "      <td>1.464000</td>\n",
       "      <td>123282000</td>\n",
       "      <td>2010-07-01</td>\n",
       "      <td>07-01-2010</td>\n",
       "      <td>07-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010-07-02</td>\n",
       "      <td>1.533333</td>\n",
       "      <td>1.540000</td>\n",
       "      <td>1.247333</td>\n",
       "      <td>1.280000</td>\n",
       "      <td>1.280000</td>\n",
       "      <td>77097000</td>\n",
       "      <td>2010-07-02</td>\n",
       "      <td>07-02-2010</td>\n",
       "      <td>07-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010-07-06</td>\n",
       "      <td>1.333333</td>\n",
       "      <td>1.333333</td>\n",
       "      <td>1.055333</td>\n",
       "      <td>1.074000</td>\n",
       "      <td>1.074000</td>\n",
       "      <td>103003500</td>\n",
       "      <td>2010-07-06</td>\n",
       "      <td>07-06-2010</td>\n",
       "      <td>07-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3125</th>\n",
       "      <td>2022-11-25</td>\n",
       "      <td>185.059998</td>\n",
       "      <td>185.199997</td>\n",
       "      <td>180.630005</td>\n",
       "      <td>182.860001</td>\n",
       "      <td>182.860001</td>\n",
       "      <td>50672700</td>\n",
       "      <td>2022-11-25</td>\n",
       "      <td>11-25-2022</td>\n",
       "      <td>11-25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3126</th>\n",
       "      <td>2022-11-28</td>\n",
       "      <td>179.960007</td>\n",
       "      <td>188.500000</td>\n",
       "      <td>179.000000</td>\n",
       "      <td>182.919998</td>\n",
       "      <td>182.919998</td>\n",
       "      <td>92905200</td>\n",
       "      <td>2022-11-28</td>\n",
       "      <td>11-28-2022</td>\n",
       "      <td>11-28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3127</th>\n",
       "      <td>2022-11-29</td>\n",
       "      <td>184.990005</td>\n",
       "      <td>186.380005</td>\n",
       "      <td>178.750000</td>\n",
       "      <td>180.830002</td>\n",
       "      <td>180.830002</td>\n",
       "      <td>83357100</td>\n",
       "      <td>2022-11-29</td>\n",
       "      <td>11-29-2022</td>\n",
       "      <td>11-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3128</th>\n",
       "      <td>2022-11-30</td>\n",
       "      <td>182.429993</td>\n",
       "      <td>194.759995</td>\n",
       "      <td>180.630005</td>\n",
       "      <td>194.699997</td>\n",
       "      <td>194.699997</td>\n",
       "      <td>109186400</td>\n",
       "      <td>2022-11-30</td>\n",
       "      <td>11-30-2022</td>\n",
       "      <td>11-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3129</th>\n",
       "      <td>2022-12-01</td>\n",
       "      <td>197.080002</td>\n",
       "      <td>198.919998</td>\n",
       "      <td>191.800003</td>\n",
       "      <td>194.699997</td>\n",
       "      <td>194.699997</td>\n",
       "      <td>80046200</td>\n",
       "      <td>2022-12-01</td>\n",
       "      <td>12-01-2022</td>\n",
       "      <td>12-01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3130 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Date        Open        High         Low       Close   Adj Close  \\\n",
       "0    2010-06-29    1.266667    1.666667    1.169333    1.592667    1.592667   \n",
       "1    2010-06-30    1.719333    2.028000    1.553333    1.588667    1.588667   \n",
       "2    2010-07-01    1.666667    1.728000    1.351333    1.464000    1.464000   \n",
       "3    2010-07-02    1.533333    1.540000    1.247333    1.280000    1.280000   \n",
       "4    2010-07-06    1.333333    1.333333    1.055333    1.074000    1.074000   \n",
       "...         ...         ...         ...         ...         ...         ...   \n",
       "3125 2022-11-25  185.059998  185.199997  180.630005  182.860001  182.860001   \n",
       "3126 2022-11-28  179.960007  188.500000  179.000000  182.919998  182.919998   \n",
       "3127 2022-11-29  184.990005  186.380005  178.750000  180.830002  180.830002   \n",
       "3128 2022-11-30  182.429993  194.759995  180.630005  194.699997  194.699997   \n",
       "3129 2022-12-01  197.080002  198.919998  191.800003  194.699997  194.699997   \n",
       "\n",
       "         Volume        date    full_day    day  \n",
       "0     281494500  2010-06-29  06-29-2010  06-29  \n",
       "1     257806500  2010-06-30  06-30-2010  06-30  \n",
       "2     123282000  2010-07-01  07-01-2010  07-01  \n",
       "3      77097000  2010-07-02  07-02-2010  07-02  \n",
       "4     103003500  2010-07-06  07-06-2010  07-06  \n",
       "...         ...         ...         ...    ...  \n",
       "3125   50672700  2022-11-25  11-25-2022  11-25  \n",
       "3126   92905200  2022-11-28  11-28-2022  11-28  \n",
       "3127   83357100  2022-11-29  11-29-2022  11-29  \n",
       "3128  109186400  2022-11-30  11-30-2022  11-30  \n",
       "3129   80046200  2022-12-01  12-01-2022  12-01  \n",
       "\n",
       "[3130 rows x 10 columns]"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tesla_stock "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "210c8d67-171d-43de-8a71-d2231640d118",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  1 of 1 completed\n"
     ]
    }
   ],
   "source": [
    "single_stock = yf.download('tsla', start=\"2010-06-29\", end=\"2022-12-05\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "483cc1b5-265d-4af9-a6cf-4e94ced000e3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2010-06-29</th>\n",
       "      <td>1.266667</td>\n",
       "      <td>1.666667</td>\n",
       "      <td>1.169333</td>\n",
       "      <td>1.592667</td>\n",
       "      <td>1.592667</td>\n",
       "      <td>281494500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-06-30</th>\n",
       "      <td>1.719333</td>\n",
       "      <td>2.028000</td>\n",
       "      <td>1.553333</td>\n",
       "      <td>1.588667</td>\n",
       "      <td>1.588667</td>\n",
       "      <td>257806500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-07-01</th>\n",
       "      <td>1.666667</td>\n",
       "      <td>1.728000</td>\n",
       "      <td>1.351333</td>\n",
       "      <td>1.464000</td>\n",
       "      <td>1.464000</td>\n",
       "      <td>123282000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-07-02</th>\n",
       "      <td>1.533333</td>\n",
       "      <td>1.540000</td>\n",
       "      <td>1.247333</td>\n",
       "      <td>1.280000</td>\n",
       "      <td>1.280000</td>\n",
       "      <td>77097000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-07-06</th>\n",
       "      <td>1.333333</td>\n",
       "      <td>1.333333</td>\n",
       "      <td>1.055333</td>\n",
       "      <td>1.074000</td>\n",
       "      <td>1.074000</td>\n",
       "      <td>103003500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-28</th>\n",
       "      <td>179.960007</td>\n",
       "      <td>188.500000</td>\n",
       "      <td>179.000000</td>\n",
       "      <td>182.919998</td>\n",
       "      <td>182.919998</td>\n",
       "      <td>92905200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-29</th>\n",
       "      <td>184.990005</td>\n",
       "      <td>186.380005</td>\n",
       "      <td>178.750000</td>\n",
       "      <td>180.830002</td>\n",
       "      <td>180.830002</td>\n",
       "      <td>83357100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-30</th>\n",
       "      <td>182.429993</td>\n",
       "      <td>194.759995</td>\n",
       "      <td>180.630005</td>\n",
       "      <td>194.699997</td>\n",
       "      <td>194.699997</td>\n",
       "      <td>109186400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-01</th>\n",
       "      <td>197.080002</td>\n",
       "      <td>198.919998</td>\n",
       "      <td>191.800003</td>\n",
       "      <td>194.699997</td>\n",
       "      <td>194.699997</td>\n",
       "      <td>80046200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-02</th>\n",
       "      <td>191.779999</td>\n",
       "      <td>196.250000</td>\n",
       "      <td>191.110001</td>\n",
       "      <td>194.860001</td>\n",
       "      <td>194.860001</td>\n",
       "      <td>73533400</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3131 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Open        High         Low       Close   Adj Close  \\\n",
       "Date                                                                     \n",
       "2010-06-29    1.266667    1.666667    1.169333    1.592667    1.592667   \n",
       "2010-06-30    1.719333    2.028000    1.553333    1.588667    1.588667   \n",
       "2010-07-01    1.666667    1.728000    1.351333    1.464000    1.464000   \n",
       "2010-07-02    1.533333    1.540000    1.247333    1.280000    1.280000   \n",
       "2010-07-06    1.333333    1.333333    1.055333    1.074000    1.074000   \n",
       "...                ...         ...         ...         ...         ...   \n",
       "2022-11-28  179.960007  188.500000  179.000000  182.919998  182.919998   \n",
       "2022-11-29  184.990005  186.380005  178.750000  180.830002  180.830002   \n",
       "2022-11-30  182.429993  194.759995  180.630005  194.699997  194.699997   \n",
       "2022-12-01  197.080002  198.919998  191.800003  194.699997  194.699997   \n",
       "2022-12-02  191.779999  196.250000  191.110001  194.860001  194.860001   \n",
       "\n",
       "               Volume  \n",
       "Date                   \n",
       "2010-06-29  281494500  \n",
       "2010-06-30  257806500  \n",
       "2010-07-01  123282000  \n",
       "2010-07-02   77097000  \n",
       "2010-07-06  103003500  \n",
       "...               ...  \n",
       "2022-11-28   92905200  \n",
       "2022-11-29   83357100  \n",
       "2022-11-30  109186400  \n",
       "2022-12-01   80046200  \n",
       "2022-12-02   73533400  \n",
       "\n",
       "[3131 rows x 6 columns]"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "single_stock"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "52b998b9-a3f3-4c09-93f5-2529abffded3",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
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       "\n",
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       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
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       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
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       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
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       "            if (entry.contentBoxSize) {\n",
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       "                    // Chrome 84 implements new version of spec.\n",
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       "                    // Firefox implements old version of spec.\n",
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       "                // Chrome <84 implements even older version of spec.\n",
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       "\n",
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       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
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       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\n",
       "                /* FIXME: We get \"Resource interpreted as Image but\n",
       "                 * transferred with MIME type text/plain:\" errors on\n",
       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "                 * to be part of the websocket stream */\n",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(data);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div id='e68343f5-7ac8-428c-a324-df292412be00'></div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fcb75bffd00>]"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "\n",
    "plt.plot(single_stock.index, single_stock[\"High\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "id": "e517b2f0-a0d3-4801-936f-cf4921014061",
   "metadata": {},
   "outputs": [],
   "source": [
    "single_stock.reset_index(inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "id": "27367ace-b8a9-4428-8c6f-543990d35da3",
   "metadata": {},
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "Can only use .str accessor with string values!",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[0;32m/var/folders/wz/7k6v05bx5gvffw4vkwfkmkn40000gn/T/ipykernel_49319/3289808602.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0msingle_stock\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0msingle_stock\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"Date\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcontains\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"2018\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36m__getattr__\u001b[0;34m(self, name)\u001b[0m\n\u001b[1;32m   5485\u001b[0m         ):\n\u001b[1;32m   5486\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 5487\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mobject\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__getattribute__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   5488\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   5489\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__setattr__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/pandas/core/accessor.py\u001b[0m in \u001b[0;36m__get__\u001b[0;34m(self, obj, cls)\u001b[0m\n\u001b[1;32m    179\u001b[0m             \u001b[0;31m# we're accessing the attribute of the class, i.e., Dataset.geo\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    180\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_accessor\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 181\u001b[0;31m         \u001b[0maccessor_obj\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_accessor\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    182\u001b[0m         \u001b[0;31m# Replace the property with the accessor object. Inspired by:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    183\u001b[0m         \u001b[0;31m# https://www.pydanny.com/cached-property.html\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/pandas/core/strings/accessor.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, data)\u001b[0m\n\u001b[1;32m    166\u001b[0m         \u001b[0;32mfrom\u001b[0m \u001b[0mpandas\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcore\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marrays\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstring_\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mStringDtype\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    167\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 168\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_inferred_dtype\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_validate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    169\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_is_categorical\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mis_categorical_dtype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    170\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_is_string\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mStringDtype\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/pandas/core/strings/accessor.py\u001b[0m in \u001b[0;36m_validate\u001b[0;34m(data)\u001b[0m\n\u001b[1;32m    223\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    224\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0minferred_dtype\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mallowed_types\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 225\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mAttributeError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Can only use .str accessor with string values!\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    226\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0minferred_dtype\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    227\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mAttributeError\u001b[0m: Can only use .str accessor with string values!"
     ]
    }
   ],
   "source": [
    "single_stock[single_stock[\"Date\"].str.contains(\"2018\")]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c971a060-515e-441b-8070-db7fd9d54d5b",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "\n",
    "plt.plot(single_stock.index, single_stock[\"High\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "id": "db19a489-2e87-44dd-bb5e-c5df3254d633",
   "metadata": {},
   "outputs": [],
   "source": [
    "## tesla stock 20 days before and 50 days after\n",
    "#August 7th, 2018 tweet \n",
    "# datetime.datetime.strptime(date_time_str, '%Y-%m-%d %H:%M:%S.%f')\n",
    "start_date = datetime.datetime.strptime(\"2018-01-01\", \"%Y-%m-%d\")\n",
    "end_date = datetime.datetime.strptime(\"2022-12-05\", \"%Y-%m-%d\")\n",
    "volatility = tesla_stock[(single_stock[\"Date\"] >= start_date) & (single_stock[\"Date\"] <= end_date)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "id": "d8845dfc-769d-4ff0-8bc6-b10b49f3b070",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>date</th>\n",
       "      <th>full_day</th>\n",
       "      <th>day</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1891</th>\n",
       "      <td>2018-01-02</td>\n",
       "      <td>20.799999</td>\n",
       "      <td>21.474001</td>\n",
       "      <td>20.733334</td>\n",
       "      <td>21.368668</td>\n",
       "      <td>21.368668</td>\n",
       "      <td>65283000</td>\n",
       "      <td>2018-01-02</td>\n",
       "      <td>01-02-2018</td>\n",
       "      <td>01-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1892</th>\n",
       "      <td>2018-01-03</td>\n",
       "      <td>21.400000</td>\n",
       "      <td>21.683332</td>\n",
       "      <td>21.036667</td>\n",
       "      <td>21.150000</td>\n",
       "      <td>21.150000</td>\n",
       "      <td>67822500</td>\n",
       "      <td>2018-01-03</td>\n",
       "      <td>01-03-2018</td>\n",
       "      <td>01-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1893</th>\n",
       "      <td>2018-01-04</td>\n",
       "      <td>20.858000</td>\n",
       "      <td>21.236668</td>\n",
       "      <td>20.378668</td>\n",
       "      <td>20.974667</td>\n",
       "      <td>20.974667</td>\n",
       "      <td>149194500</td>\n",
       "      <td>2018-01-04</td>\n",
       "      <td>01-04-2018</td>\n",
       "      <td>01-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1894</th>\n",
       "      <td>2018-01-05</td>\n",
       "      <td>21.108000</td>\n",
       "      <td>21.149332</td>\n",
       "      <td>20.799999</td>\n",
       "      <td>21.105333</td>\n",
       "      <td>21.105333</td>\n",
       "      <td>68868000</td>\n",
       "      <td>2018-01-05</td>\n",
       "      <td>01-05-2018</td>\n",
       "      <td>01-05</td>\n",
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       "      <th>1895</th>\n",
       "      <td>2018-01-08</td>\n",
       "      <td>21.066668</td>\n",
       "      <td>22.468000</td>\n",
       "      <td>21.033333</td>\n",
       "      <td>22.427334</td>\n",
       "      <td>22.427334</td>\n",
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       "      <td>2018-01-08</td>\n",
       "      <td>01-08-2018</td>\n",
       "      <td>01-08</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
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       "      <th>3125</th>\n",
       "      <td>2022-11-25</td>\n",
       "      <td>185.059998</td>\n",
       "      <td>185.199997</td>\n",
       "      <td>180.630005</td>\n",
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       "      <td>182.860001</td>\n",
       "      <td>50672700</td>\n",
       "      <td>2022-11-25</td>\n",
       "      <td>11-25-2022</td>\n",
       "      <td>11-25</td>\n",
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       "      <th>3126</th>\n",
       "      <td>2022-11-28</td>\n",
       "      <td>179.960007</td>\n",
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       "      <td>2022-11-28</td>\n",
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       "      <th>3127</th>\n",
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       "      <td>2022-11-29</td>\n",
       "      <td>11-29-2022</td>\n",
       "      <td>11-29</td>\n",
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       "    <tr>\n",
       "      <th>3128</th>\n",
       "      <td>2022-11-30</td>\n",
       "      <td>182.429993</td>\n",
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       "      <td>2022-11-30</td>\n",
       "      <td>11-30-2022</td>\n",
       "      <td>11-30</td>\n",
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       "      <th>3129</th>\n",
       "      <td>2022-12-01</td>\n",
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       "      <td>2022-12-01</td>\n",
       "      <td>12-01-2022</td>\n",
       "      <td>12-01</td>\n",
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       "<p>1239 rows × 10 columns</p>\n",
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       "           Date        Open        High         Low       Close   Adj Close  \\\n",
       "1891 2018-01-02   20.799999   21.474001   20.733334   21.368668   21.368668   \n",
       "1892 2018-01-03   21.400000   21.683332   21.036667   21.150000   21.150000   \n",
       "1893 2018-01-04   20.858000   21.236668   20.378668   20.974667   20.974667   \n",
       "1894 2018-01-05   21.108000   21.149332   20.799999   21.105333   21.105333   \n",
       "1895 2018-01-08   21.066668   22.468000   21.033333   22.427334   22.427334   \n",
       "...         ...         ...         ...         ...         ...         ...   \n",
       "3125 2022-11-25  185.059998  185.199997  180.630005  182.860001  182.860001   \n",
       "3126 2022-11-28  179.960007  188.500000  179.000000  182.919998  182.919998   \n",
       "3127 2022-11-29  184.990005  186.380005  178.750000  180.830002  180.830002   \n",
       "3128 2022-11-30  182.429993  194.759995  180.630005  194.699997  194.699997   \n",
       "3129 2022-12-01  197.080002  198.919998  191.800003  194.699997  194.699997   \n",
       "\n",
       "         Volume        date    full_day    day  \n",
       "1891   65283000  2018-01-02  01-02-2018  01-02  \n",
       "1892   67822500  2018-01-03  01-03-2018  01-03  \n",
       "1893  149194500  2018-01-04  01-04-2018  01-04  \n",
       "1894   68868000  2018-01-05  01-05-2018  01-05  \n",
       "1895  147891000  2018-01-08  01-08-2018  01-08  \n",
       "...         ...         ...         ...    ...  \n",
       "3125   50672700  2022-11-25  11-25-2022  11-25  \n",
       "3126   92905200  2022-11-28  11-28-2022  11-28  \n",
       "3127   83357100  2022-11-29  11-29-2022  11-29  \n",
       "3128  109186400  2022-11-30  11-30-2022  11-30  \n",
       "3129   80046200  2022-12-01  12-01-2022  12-01  \n",
       "\n",
       "[1239 rows x 10 columns]"
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     },
     "execution_count": 127,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "volatility"
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   "cell_type": "code",
   "execution_count": 134,
   "id": "5ca2bd19-dd41-4583-93c4-239301be36bc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  1 of 1 completed\n"
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   "source": [
    "single_stock = yf.download('tsla', start=\"2010-06-29\", end=\"2022-12-05\")"
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   "cell_type": "code",
   "execution_count": 137,
   "id": "df56ea9d-846d-443a-94a7-600eadbd7fab",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  1 of 1 completed\n"
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   "source": [
    "stk = yf.download('tsla', start=\"2022-05-27\", end=\"2022-12-05\")"
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   "cell_type": "code",
   "execution_count": 138,
   "id": "9e25d215-306a-447f-80ad-4fd509ecfd10",
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",
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      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
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      "\u001b[0;31mAttributeError\u001b[0m: 'NoneType' object has no attribute 'write_html'"
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    "\n",
    "#plotly-opensource"
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