linear-regression-scikit.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "id": "initial_id",
   "metadata": {
    "collapsed": true,
    "ExecuteTime": {
     "end_time": "2024-08-20T07:04:54.878835Z",
     "start_time": "2024-08-20T07:04:54.870869Z"
    }
   },
   "source": [
    "from sklearn.linear_model import LinearRegression\n",
    "from itertools import product\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.style\n",
    "import matplotlib.pyplot as plt\n",
    "import yfinance as yf\n",
    "\n",
    "pd.options.display.float_format = '{:.6f}'.format\n",
    "plt.style.use(\"seaborn-v0_8\")\n",
    "from itertools import product"
   ],
   "outputs": [],
   "execution_count": 42
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-20T07:04:54.902893Z",
     "start_time": "2024-08-20T07:04:54.895845Z"
    }
   },
   "cell_type": "code",
   "source": [
    "symbol = \"EURUSD=X\"\n",
    "start = \"2024-06-22\"\n",
    "end = \"2024-08-10\"\n",
    "interval = '15m'"
   ],
   "id": "30916ab50580ddbe",
   "outputs": [],
   "execution_count": 43
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-20T07:04:55.002698Z",
     "start_time": "2024-08-20T07:04:54.953452Z"
    }
   },
   "cell_type": "code",
   "source": [
    "df = yf.download(symbol, start, end, interval=interval).Close.to_frame()\n",
    "df.rename(columns={\"Close\": \"price\"}, inplace=True)\n",
    "df['returns'] = np.log(df['price'].div(df['price'].shift(1)))\n",
    "df"
   ],
   "id": "aedcd33cdd2b8ab7",
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[*********************100%%**********************]  1 of 1 completed\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "                       price   returns\n",
       "Datetime                              \n",
       "2024-06-24 00:00:00 1.069747       NaN\n",
       "2024-06-24 00:15:00 1.069404 -0.000321\n",
       "2024-06-24 00:30:00 1.069290 -0.000107\n",
       "2024-06-24 00:45:00 1.069061 -0.000214\n",
       "2024-06-24 01:00:00 1.068833 -0.000214\n",
       "...                      ...       ...\n",
       "2024-08-09 21:15:00 1.092061  0.000109\n",
       "2024-08-09 21:30:00 1.091941 -0.000109\n",
       "2024-08-09 21:45:00 1.091822 -0.000109\n",
       "2024-08-09 22:00:00 1.091703 -0.000109\n",
       "2024-08-09 22:15:00 1.091703  0.000000\n",
       "\n",
       "[3319 rows x 2 columns]"
      ],
      "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>price</th>\n",
       "      <th>returns</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Datetime</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2024-06-24 00:00:00</th>\n",
       "      <td>1.069747</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-06-24 00:15:00</th>\n",
       "      <td>1.069404</td>\n",
       "      <td>-0.000321</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-06-24 00:30:00</th>\n",
       "      <td>1.069290</td>\n",
       "      <td>-0.000107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-06-24 00:45:00</th>\n",
       "      <td>1.069061</td>\n",
       "      <td>-0.000214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-06-24 01:00:00</th>\n",
       "      <td>1.068833</td>\n",
       "      <td>-0.000214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-08-09 21:15:00</th>\n",
       "      <td>1.092061</td>\n",
       "      <td>0.000109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-08-09 21:30:00</th>\n",
       "      <td>1.091941</td>\n",
       "      <td>-0.000109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-08-09 21:45:00</th>\n",
       "      <td>1.091822</td>\n",
       "      <td>-0.000109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-08-09 22:00:00</th>\n",
       "      <td>1.091703</td>\n",
       "      <td>-0.000109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-08-09 22:15:00</th>\n",
       "      <td>1.091703</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3319 rows × 2 columns</p>\n",
       "</div>"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 44
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-20T07:04:55.305548Z",
     "start_time": "2024-08-20T07:04:55.142757Z"
    }
   },
   "cell_type": "code",
   "source": [
    "df.price.plot()\n",
    "plt.show()"
   ],
   "id": "2e4830b4b7ab5435",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 800x550 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 45
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-20T07:04:55.363654Z",
     "start_time": "2024-08-20T07:04:55.349248Z"
    }
   },
   "cell_type": "code",
   "source": [
    "df['lag1'] = df.returns.shift(1)\n",
    "df.dropna(inplace=True)\n",
    "df"
   ],
   "id": "30425b580ed2bb8",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "                       price   returns      lag1\n",
       "Datetime                                        \n",
       "2024-06-24 00:30:00 1.069290 -0.000107 -0.000321\n",
       "2024-06-24 00:45:00 1.069061 -0.000214 -0.000107\n",
       "2024-06-24 01:00:00 1.068833 -0.000214 -0.000214\n",
       "2024-06-24 01:15:00 1.069061  0.000214 -0.000214\n",
       "2024-06-24 01:30:00 1.069404  0.000321  0.000214\n",
       "...                      ...       ...       ...\n",
       "2024-08-09 21:15:00 1.092061  0.000109 -0.000218\n",
       "2024-08-09 21:30:00 1.091941 -0.000109  0.000109\n",
       "2024-08-09 21:45:00 1.091822 -0.000109 -0.000109\n",
       "2024-08-09 22:00:00 1.091703 -0.000109 -0.000109\n",
       "2024-08-09 22:15:00 1.091703  0.000000 -0.000109\n",
       "\n",
       "[3317 rows x 3 columns]"
      ],
      "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>price</th>\n",
       "      <th>returns</th>\n",
       "      <th>lag1</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Datetime</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2024-06-24 00:30:00</th>\n",
       "      <td>1.069290</td>\n",
       "      <td>-0.000107</td>\n",
       "      <td>-0.000321</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-06-24 00:45:00</th>\n",
       "      <td>1.069061</td>\n",
       "      <td>-0.000214</td>\n",
       "      <td>-0.000107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-06-24 01:00:00</th>\n",
       "      <td>1.068833</td>\n",
       "      <td>-0.000214</td>\n",
       "      <td>-0.000214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-06-24 01:15:00</th>\n",
       "      <td>1.069061</td>\n",
       "      <td>0.000214</td>\n",
       "      <td>-0.000214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-06-24 01:30:00</th>\n",
       "      <td>1.069404</td>\n",
       "      <td>0.000321</td>\n",
       "      <td>0.000214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-08-09 21:15:00</th>\n",
       "      <td>1.092061</td>\n",
       "      <td>0.000109</td>\n",
       "      <td>-0.000218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-08-09 21:30:00</th>\n",
       "      <td>1.091941</td>\n",
       "      <td>-0.000109</td>\n",
       "      <td>0.000109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-08-09 21:45:00</th>\n",
       "      <td>1.091822</td>\n",
       "      <td>-0.000109</td>\n",
       "      <td>-0.000109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-08-09 22:00:00</th>\n",
       "      <td>1.091703</td>\n",
       "      <td>-0.000109</td>\n",
       "      <td>-0.000109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-08-09 22:15:00</th>\n",
       "      <td>1.091703</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.000109</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3317 rows × 3 columns</p>\n",
       "</div>"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 46
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-20T07:04:55.469770Z",
     "start_time": "2024-08-20T07:04:55.460440Z"
    }
   },
   "cell_type": "code",
   "source": "df.info()",
   "id": "d25f53ec256f76d1",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 3317 entries, 2024-06-24 00:30:00 to 2024-08-09 22:15:00\n",
      "Data columns (total 3 columns):\n",
      " #   Column   Non-Null Count  Dtype  \n",
      "---  ------   --------------  -----  \n",
      " 0   price    3317 non-null   float64\n",
      " 1   returns  3317 non-null   float64\n",
      " 2   lag1     3317 non-null   float64\n",
      "dtypes: float64(3)\n",
      "memory usage: 103.7 KB\n"
     ]
    }
   ],
   "execution_count": 47
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-20T07:04:55.662691Z",
     "start_time": "2024-08-20T07:04:55.552878Z"
    }
   },
   "cell_type": "code",
   "source": [
    "df.plot(kind='scatter', x='lag1', y='returns')\n",
    "plt.xlim(-0.005, 0.005)\n",
    "plt.ylim(-0.005, 0.005)\n",
    "plt.show()"
   ],
   "id": "c9b469acadbf595c",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 800x550 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 48
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-20T07:04:55.776560Z",
     "start_time": "2024-08-20T07:04:55.755906Z"
    }
   },
   "cell_type": "code",
   "source": [
    "lm = LinearRegression(fit_intercept=True)\n",
    "lm.fit(df.lag1.to_frame(), df.returns)\n",
    "slope = lm.coef_\n",
    "slope"
   ],
   "id": "97c8791bd47a13c5",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-0.03298108])"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 49
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-20T07:04:55.801927Z",
     "start_time": "2024-08-20T07:04:55.794573Z"
    }
   },
   "cell_type": "code",
   "source": [
    "intercept = lm.intercept_\n",
    "intercept"
   ],
   "id": "cab56d15b18b688f",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.float64(6.42361927923654e-06)"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 50
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-20T07:04:55.877184Z",
     "start_time": "2024-08-20T07:04:55.865086Z"
    }
   },
   "cell_type": "code",
   "source": [
    "df['pred'] = lm.predict(df.lag1.to_frame())\n",
    "df"
   ],
   "id": "ae85fa8aa4ca9f69",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "                       price   returns      lag1      pred\n",
       "Datetime                                                  \n",
       "2024-06-24 00:30:00 1.069290 -0.000107 -0.000321  0.000017\n",
       "2024-06-24 00:45:00 1.069061 -0.000214 -0.000107  0.000010\n",
       "2024-06-24 01:00:00 1.068833 -0.000214 -0.000214  0.000013\n",
       "2024-06-24 01:15:00 1.069061  0.000214 -0.000214  0.000013\n",
       "2024-06-24 01:30:00 1.069404  0.000321  0.000214 -0.000001\n",
       "...                      ...       ...       ...       ...\n",
       "2024-08-09 21:15:00 1.092061  0.000109 -0.000218  0.000014\n",
       "2024-08-09 21:30:00 1.091941 -0.000109  0.000109  0.000003\n",
       "2024-08-09 21:45:00 1.091822 -0.000109 -0.000109  0.000010\n",
       "2024-08-09 22:00:00 1.091703 -0.000109 -0.000109  0.000010\n",
       "2024-08-09 22:15:00 1.091703  0.000000 -0.000109  0.000010\n",
       "\n",
       "[3317 rows x 4 columns]"
      ],
      "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>price</th>\n",
       "      <th>returns</th>\n",
       "      <th>lag1</th>\n",
       "      <th>pred</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Datetime</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2024-06-24 00:30:00</th>\n",
       "      <td>1.069290</td>\n",
       "      <td>-0.000107</td>\n",
       "      <td>-0.000321</td>\n",
       "      <td>0.000017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-06-24 00:45:00</th>\n",
       "      <td>1.069061</td>\n",
       "      <td>-0.000214</td>\n",
       "      <td>-0.000107</td>\n",
       "      <td>0.000010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-06-24 01:00:00</th>\n",
       "      <td>1.068833</td>\n",
       "      <td>-0.000214</td>\n",
       "      <td>-0.000214</td>\n",
       "      <td>0.000013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-06-24 01:15:00</th>\n",
       "      <td>1.069061</td>\n",
       "      <td>0.000214</td>\n",
       "      <td>-0.000214</td>\n",
       "      <td>0.000013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-06-24 01:30:00</th>\n",
       "      <td>1.069404</td>\n",
       "      <td>0.000321</td>\n",
       "      <td>0.000214</td>\n",
       "      <td>-0.000001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-08-09 21:15:00</th>\n",
       "      <td>1.092061</td>\n",
       "      <td>0.000109</td>\n",
       "      <td>-0.000218</td>\n",
       "      <td>0.000014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-08-09 21:30:00</th>\n",
       "      <td>1.091941</td>\n",
       "      <td>-0.000109</td>\n",
       "      <td>0.000109</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-08-09 21:45:00</th>\n",
       "      <td>1.091822</td>\n",
       "      <td>-0.000109</td>\n",
       "      <td>-0.000109</td>\n",
       "      <td>0.000010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-08-09 22:00:00</th>\n",
       "      <td>1.091703</td>\n",
       "      <td>-0.000109</td>\n",
       "      <td>-0.000109</td>\n",
       "      <td>0.000010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-08-09 22:15:00</th>\n",
       "      <td>1.091703</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.000109</td>\n",
       "      <td>0.000010</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3317 rows × 4 columns</p>\n",
       "</div>"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 51
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-20T07:07:00.453258Z",
     "start_time": "2024-08-20T07:07:00.295669Z"
    }
   },
   "cell_type": "code",
   "source": [
    "plt.figure(figsize=(12,8))\n",
    "plt.scatter(x=df.lag1, y=df.returns, label=\"DATA\")\n",
    "plt.plot(df.lag1, df.pred, c=\"red\", label = \"Linear Regression\")\n",
    "plt.xlim(-0.005, 0.005)\n",
    "plt.ylim(-0.005, 0.005)\n",
    "plt.xlabel(\"Lag1 Returns\")\n",
    "plt.ylabel(\"Returns\")"
   ],
   "id": "bc5ef544dc0096c5",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Returns')"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ],
      "image/png": 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XKJ/Pn+ghAQBgSxT3AwAAAADAxkj8AQAAAACwMRJ/AAAAAABsjMQfAAAAAAAbI/EHAAAAAMDGSPwBAAAAALAxEn8AAAAAAGwsPdEDAAAAiKfaeo+Wr65Uo9enHHe6ykpHqDA/K9HDAgAgZkj8AQBASmjz+7Vk2Sat316rhqbW4OOrNlSpeFShZs8oUpqTxZAAAPsh8QcAAClhybJNWlGxt8vjDU2t7Y87HJozc1wCRgYAQGxxWhsAANhebb1H67fXhoxZv71GtfWeOI0IAID4IfEHAAC2t3x1Zafl/d1paGzV8tU74zQiAADih8QfAADYXqPXZxTX5A19cgAAgL6IxB8AANhejtusrFG22xXjkQAAEH8k/gAAwPbKSkcoLzt0Up+X41JZ6fA4jQgAgPgh8QcAALZXmJ+l4lGFIWOKRxaqMD8rTiMCACB+kjrxb25u1u23367S0lJNnz5dTz75ZI+xGzdu1De+8Q2VlJTokksuUUVFRafnly5dqnPOOUclJSW64YYbtH///uBzDQ0Nmjt3rk4//XSddtppuvXWW9XQ0BCz4wIAAPE3e0aRphUfo7yczlf+83JcmjZhqGbPKErQyAAAiK2kTvznzZuniooKPfXUU7rzzjv16KOP6vXXX+8S19TUpO9973sqLS3Vyy+/rEmTJum6665TU1OTJGndunWaO3eubrzxRr3wwgtqaGjQbbfdFvz3d955pzZt2qQFCxZo0aJF2rZtm/7rv/4rbscJAABiL83p1JyZ4/Tzq0p17pThml48VF+dMkJ3XD1Fcy44WWnOpP5aBABAr5lVukmApqYmvfjii3riiSc0fvx4jR8/Xlu2bNGzzz6r8847r1PssmXLlJmZqVtuuUUOh0Nz587VP//5T73++uu6+OKL9cwzz+j888/XrFmzJLWfUPjKV76iyspKFRYW6o033tBzzz2nCRMmSJJuv/12XXHFFWpublZmZma8Dx0AAMRQYX6WLjv7pEQPAwCAuEnaU9ubNm2Sz+fTpEmTgo9NnjxZa9euld/v7xS7du1aTZ48WQ6HQ5LkcDh0yimnaM2aNcHnS0tLg/HHHHOMhg0bprVr18rpdOqxxx7TuHHjOm2zra1NjY2NMTo6AECqqK336Pm3N2vRaxv1/NubVVvvSfSQAABAiknaK/7V1dUqKChQRkZG8LGBAwequblZBw4c0IABAzrFjh49utO/Lyws1JYtWyRJ+/bt0+DBg7s8v3fvXrndbp1xxhmdnnv66ac1duzYTvsAACASbX6/lizbpPXba9XQdLg3/KoNVSoeVajZM4pYWg4AAOIiaRN/j8fTKemXFPx7S0uLUWwgzuv1hny+o2eeeUZ/+ctftHDhwojG63Q65HQ6Ivo36L20NGen3wE7Yp73bU+++pFWVOzt8nhDU6tWVOyV0+nQd78+PqZjqK336PV/V6rJ26pst0vnnToi6arWM8+RCpjnSAXM8+SWtIl/ZmZml8Q88He3220UG4jr6fmsrM5ffp599ln98pe/1G233abp06dHNN4BA3KCtxogfvLykusLLBALzPO+p7quSRXb94eMWb9jv3xyaFBBdtT339bm1yMvrlH5R/t04FBz8PF/b6zS5HGD9YNvTEy6L2bMc6QC5jlSAfM8OSVt4j9kyBDV1dXJ5/MpPb19mNXV1XK73crLy+sSW1NT0+mxmpqa4PL+np4fNGhQ8O+LFi3SvHnzdMstt+jqq6+OeLz79zdyxT+O0tKcysvLUkODR21t/vD/AOiDmOd91wtvbu6UcHfnwMFm/X75x/qPsugXmVvw6ga9s25P130eatbb71eqpdkX89UGppjnSAXMc6QC5nliFBTkGMUlbeI/btw4paena82aNcHCfOXl5SouLpbziHsiS0pK9MQTT8iyLDkcDlmWpQ8++EDXX3998Pny8nJdfPHFkqQ9e/Zoz549KikpkST98Y9/1Lx583Tbbbdp9uzZvRqv32/J77d6ebTorbY2v3w+Plhgb8zzvueQp+utZN3GNbVE/WdbW+/Ruq01IWPWbqtRVW1jUi37Z54jFTDPkQqY58kpudb5dZCVlaVZs2bpF7/4hdatW6e33npLTz75pK666ipJ7Vf/vV6vJOm8885TQ0OD7r33Xm3dulX33nuvPB6Pzj//fEnS5Zdfrj/96U968cUXtWnTJt1yyy0688wzNWLECB04cEB33323LrroIs2cOVPV1dXBX21tbQk7fgBA35XjNjuvnu12RX3fy1dXdiom2J2GxlYtX70z6vsGAADJKWkTf0m67bbbNH78eF199dW666679IMf/EDnnnuuJGn69OlatmyZJKlfv356/PHHg1f1165dqwULFig7u/2+yUmTJunuu+/W/Pnzdfnllys/P1/333+/JGnFihVqamrSH//4R02fPr3Trz17ui6TBAAgnLLSEcrLDp3U5+W4VFY6POr7bvT6jOKavKFPDgAAAPtwWJbF+vQoqK4+mOghpJT0dKcKCnJUV9fIUiLYFvO8b1u0dGO3Vf0Dpk0YqjkXnBz1/T7/9ma9+X74q/nnThmhy84eE/X9R4p5jlTAPEcqYJ4nxqBBuUZxSX3FHwCAvmr2jCJNKz5GeTmdr/zn5bg0bcJQzZ5RFJP9JnK1AQAASE5JW9wPAIC+LM3p1JyZ41Rb79Hy1ZVq8vqU43apbMoIDchzh99ALxXmZ6l4VGHI1QbFIwuTqrAfAACILRJ/AABiqDA/S5edHf2WfaHMnlEkORxav71GDY2H7+XPy3GpeGRhzFYbAACA5ETiDwCAzSRqtQEAAEhOJP4AANhUIlYbJFrgZEej16ccd7rKSkdwWwMAIOWR+AMAgD6vze/XkmWbtH57rRqaDt/esGpDlYpHtd/ekOakpjEAIDWR+AMAgD5vybJN3RY0bGhqbX/c4dCcmeMSMDIAABKPU98AAKBPq633aP322pAx67fXqLbeE6cRAQCQXEj8AQBAn7Z8dWWn5f3daWhs1fLVO+M0IgAAkguJPwAA6NMavT6juCZv6JMDAADYFYk/AADo03LcZiWLst2uGI8EAIDkROIPAAD6tLLSEcrLDp3U5+W4VFY6PE4jAgAguZD4AwCAPq0wP0vFowpDxhSPLFRhflacRgQAQHKhnR8AAOjzZs8okhwOrd9eo4bGw/fy5+W4VDyysP15AABSFIk/AADo89KcTs2ZOU619R4tX12pJq9POW6XyqaM0IA8d6KHBwBAQpH4AwAA2yjMz9JlZ5+U6GEAAJBUuMcfAAAAAAAb44o/AAAdBJaKN3p9ynGnq6x0BEXhgKPAewoAEo/EHwAASW1+v5Ys26T122vV0HS4ONyqDVUqHtVeHC7NyUK5aKqt9+it8l3yWZbSHQ6dM/lYEkIb4T0FAMmDxB8AAElLlm3Sioq9XR5vaGptf9zh0JyZ4xIwMvvpKSF8t2IPCaGN8J4CgOTB/6oAgJRXW+/R+u21IWPWb69Rbb0nTiOyt0BC2DHplw4nhEv+8nGCRoZo4T0FAMmFxB8AkPKWr67skoQeqaGxVctX74zTiOyLhDA18J4CgORC4g8ASHmNXp9RXJM3dCKD8EgIUwPvKQBILiT+AICUl+M2K3mT7XbFeCT2R0KYGnhPAUByobgfACDllZWO0KoNVSGvROfluFRWOjyOozp6ydhGjYQwNdj1PQUAfRWJPwAg5RXmZ6l4VGG3FcgDikcWJjxpNhVpG7V4niAgIUwNdntPAUBfR+IPAICk2TOKJIdD67fXqKHxcFKal+NS8cj2ZLmvMG2jlogTBH0pIUzGFRN9iZ3eUwDQ15H4AwAgKc3p1JyZ44LJXpPXpxy3S2VTRmhAnjvRwzMWSdX8V/61IyYnCMJJ9oQw2sebquzyngIAOyDxBwCgg8L8LF129kmJHkavmVbNf3XFJ1E/QWCqY0L4VvkutVlSulM6Z/LwpEgITVdMwExff08BgB2Q+AMAYCOmVfO37ao3PEGww/gEQW+W/V9x7kkqKMhRXV2jfD5/RP8+FiJZMcGyfwBAX8E6NQAAbMS0ar7lMNvett0NRicIlq/eabbBJGe6YsIuxwsASA1c8QcAwEZMq+aPHpanPTVNYbdnWWb7bfKGTpa7E1jq77MspTscOmfysQm/im66YqI3x4vUcWRhyPNPO14FBTmJHhaAFEbiDwCAjZhWzf/6tJFau7U2/AmCY/O1pzb8CYJst8t4jD0Vz3u3Yk/C2w2arpiI5HiROnosDLmxSlNOHqory8YkcHQAUhmJPwAANmNSNT/N6TQ8QXCC3t2wV762ni/9u9IcKisdbjy+WLUbjAbTFRORHC9SR49zu7FVf32/Ui3NPn1nBoUhAcQfiT8AADZj2kbN5ATBgYPNMiwHYCQW7QajyXTFRKJvSUDyCTe3LUlrt1EYEkBikPgDAGBT4dqomZwgWL66Uq0hrvZLUmubpeWrd+qys8MvY45Fu8FoJ1EmJ0SAI0VSGNLkvQIA0UTiDwBAigt1giDaxe6i3W4wFkmU6YoJoCMKQwJIZiT+AACgR9EudhftdoOxTKLCrZgAOqIwJIBkRuIPAEAfY1rlPhrV8KNd7C7a7QZJopAsKAwJIJmR+AMA0EeYVrmPZjX8aBe7i3a7QTsmUfFsX4joCTe3HZK+cOJAfpYAEoLEHwCAPsK0DZ5pnKloF7uLZrtBOyVRiWhfiOgKNbennDxUV5aNkeVP4AABpCwSfwAA+gDTNnhbd9ZFvRp+tIvdddzeW+W71GZJ6U7pnMnDI243aCfRPmGD+OvpvXLeacdp9AkDVVfXKJ+fzB9A/DksywrdowdGqqsPJnoIKSU93amCgpz2/0B9/AcKe2Keo6Pn396sN9/fGTbuuCH99FnVobBx504ZkRQtxUzmeSpU16+t9+iep1aHvbXh51eV2mqVQ6rg8xypgHmeGIMG5RrFccUfAIA+wLRVmLfZfi3FUqG6Pj3gAQCxROIPAEAfYNoqzJ2Z+JZiFKeLHD3gAQCxROIPAEAfYNoq7MqyMXr05YqEVMOnOF14PZ0UoQc8ACCWSPwBAOgDTNvgjR5ekLBq+BSn61m4kyJfm3YCPeABADFD4g8AQB9hWuX+2+edpC07D6j6gFcdK/g6JA3q79a3z4v+/fKmXQci6SZgJyYnRVKtfSEAIH5I/AEA6CNM2+r99vXN2nfA2+XfW5L2HfDqt29sifqVd4rT9cz0pMjcb09OqfaFAID4IfEHAKCPCVXlPlFX3ilO1zPTkyJvl+8yOrEDAECkSPwBALCRRF15pzhdzyI9KZIK7QsBAPFF4g8AgI305sp7NNrvmXYd6Ficrrbeo7fKd8lnWUp3OHTO5GOPehVCMrYS5KQIACDRSPwBALCRSJLMQKX5tdtqdMhz+ITByoq9KjlxYETt90y7DhTmZ/W43xXrd3e7X5NkPpJWgvE+OdCbkyIAAEQTiT8AADYSSZK5eNlHWllR1eX5Qx6fVlTslSVL114w3njfpl0HTPcbSTJvUjV/9vljjbcXTZGcFAEAIBZI/AEAsBHTJFOS3v9oX8htvf/RPl30pVHGCalJ14Haeo/xfl/5146wyXxgfyYFDR97pVXlm2vCbi8WTE+KAAAQCyT+AADYjEmS+fTrH6u1zQq5ndY2S6+u+ETfmRFZMhyqON2rKz4x2u+Lf9+qTZ8eCBkX6E5gWtBwXQK6HQSYtmIEACAWSPwBALAZkyRz6656o21tM4wzZbrfDTvqwhYqDHQnMC1o2OoLfcIhFt0OjkTFfgBAIpD4AwBgUyGTTIfhRkzjTBlur80KnaQHNHlbjQsamm4PAAC7IfEHACDGEtViLtR+Rw/L056aprDbOHFYXlTHZLrfAf0ytLvZEzYu291eqDBcQcOMdKdafH6j7XWUjO0Be8tOxxJtvDYA7I7EHwCAGImkKn289/v1aSP17oYq+ULcb5+e5tDXp42M6thM9zv7/CI9/Id1OuRt6zGuX1aaykqHqzA/SxNGDei2U0DAhFGF2rrzgHFLvUT97GLBTscSbbw2AFIFn2QAAMRIoMXckclmoIr8kr98nLD9FuZnqaBfRsjtFPTLiPpVz8L8LE0pGhQyZkrRII0eXhDy5IAk+XzW4fGFuTPAnZGmCaMGhIyZMHJAcHuJ+tnFgp2OJdp4bQCkChJ/AABiwLTFXG19+OXssdjv1p118raGXvre3OqP+vgkyRHmRn+Hw2k8vq0761Rb71HFjv0hYyt21MrbHK4IYPu4EvWziwU7HUu08doASCUk/gAAxIBpi7nlq3cmZL/PLt+ig+HimqI/PtMk/anXw19ptSQ9u3yL8TGvN9hvJO0Bo/3axIKdjiXaeG0ApBLu8QcAIAZMW8xFu4q88X7DXv3+PC7K4zNNtlrDXO0P8DT7ot7OL1E/u1iw07FEG68NgFTCFX8AAGLAtMXckVXk47bfzMSMzzTZcjrN+v5lZaZHvZ1fon52sWCnY4k2XhsAqYQr/gCAlBBJu65otPYqKx0RtsVcxyry0WK63yvKxujRlysiGp/p61L+8V499cYWtba2yeVK09VfHaPJY4dKMk+2Tj6hv97fVBMyxiHpirIxKsh1R7WdX1npcL1bsVcHPT2fpMjNTo/6zy4WEjUP+wJeGwCphMQfAGBrkbTrimZrr8L8LE0YOUArN4RoMXfCgJhUzTfZ7+jhBSoeVagVFXt7jCseWajC/Czj18XT0qqfPLKiU1G+5la/5v9xo9yuTXroB9NUVjpCK9fvCdum75tfGaMdew6qpr45xLFmavTwArX4fGpp7Xl7kvSFEwv18Wd1IZP59DSHzjrlWBXmZykrMz1kbFZGep/o816Yn2X8c041vDYAUglL/QEAthZJu66ot/YKt1rdbDV75Az3O3tGkaYVH6O8nM5LmfNyXJo2YahmzyiSZP66HJn0d+Rt9esnj6xUYX6WWsO06Wv9vE1f+Or/7c/fsfC9kB0A3K40XXfheGWFub3B12bpzys/VW29R56W0CcSvC1tfabau+nPORXx2gBIFVzxBwDYVqTtukxjTa4A1tZ7VLE9XBX5/cbbMxXpfufMHBdcwt/k9SnH7VLZlBEakOcObs/kdfn7h5+Fbb/nbW3T0pXb1GzQpu/vH36m6npvyLiaA179/cPPtO9A6Ljm1jat2bJPhwyKtK3bWiOnQ8YdDy47e0zYbSZamtMZ9uecqnhtAKQKh2VZoU+7w0h19cFEDyGlpKc7VVCQo7q6RvkM7tkE+iLm+dF7/u3NevP98K24zp0yQpJlHGuS7EWy72gmj9Her+n2XOmOsFXzJcnhkEy+eaSnOeQLszIgkv3mZrvCJvMBxxRma09tU9i46cVDdc3Mk422idTG5zlSAfM8MQYNyjWK44o/AMC2ImnXZXoW3LS1V9K384vycbQZJOmSWdIvySjpj2S/4WoAdOQwvAWDau8AgL6CxB8A0GeFqzIfWbsuswTSNNmLVauwrTvr9MzyLfI0+5SVma4ry8Zo9PCCmO3XdHtpaQ75Da68mzJdGWC63wxXWthbDAJOHJanQ02tCa32Ho3OEgAABJD4AwD6HNMq85G264q0tVeoJLw3rcJq6z16dcUn2rqrXnJIo4fl6evTRqowP0stPp/uWPhel/vZ73vmQxXmZere752qjPT2BPHdDVUhl7XnZUd2HCat7S760gl6+o2tPcYEjBqare17wy+jHzs8V5sqw99Gd/nZJ4bdr0PSVV8doyV/+ViNIboJSFI/d7q+Pm2k/H5FVO09Wol6NDtLAAAQQOIPAOhzAlXmjxSoMi+HQ3Nmjou4XdeEUQO0siJEG7yRA8Im4YP7u3X3tVMj2neb36/Fyz7S+x/t61Txfk9Nk97dUKWpRYO1ZVe9qnsoYlfb0Kwf/c87euTHZ6gwP0vujLSQiX9mRlpEx5HhSpNCJP6ZrjSdOek4o8T//7uoRLf837sh11c4JM25YIJu/r93w27vzEnH6bV3P1NtQ0uPMQPyMjR57FB9uLk2ZJtDScp2p6t/bqYsy5IrzdGlA4ErzaEp4wYHq71HO1E3ndsAAESCU8YAgD4l0kr9EbXrCrti/HD7uJ4qye874NUdC9+PaN9Llm3Syoqqbtvc+dosrdxQ1WPSH+Bt9et/Xlyr2nqP6hpCx9Y1eFVb7zE6jtp6j2obmkNur6a+WeUf93yCo9O+D3rlSg99E70r3aH126uNtvf3Dz/ToRAnJSQFn/e2hq9X4G1p02OvVGjlhu5/Hq1tlhwOZzCZj2YLyEjnNgAAprjiDwDoU5avrgy5fF6SGhoPt1ozbddVW+9RxY5wbfBqVf7x3rDt46oPeLR1Z51GDy8wape3dluN4dGHtuGTOv3+b1sVrpiyzy898+Ymo+N49OW1Rvt+4s8fGcUt+PNGtYS5J7/VZ+nZN8OvHpCkZ97cKn+YEzaB9oDrw7Q5lNoT9nUJagEZ6dwGAMAUiT8AoE/pbdX6wvwsXXb2ST3GmyZdT7+xJey+LUnPLt+iO78zNey+l6+uDHvF2pRlSRs/qTOK3fDJgfDbk/RpVfj78SWFTeYDautDrx4I7NewWH/YpD/gube3GbX9kxQ2LpB8S1ZUE/VEdYIAANgfiT8AoE+JVbV806TLtC2cp9lse6b7NeU37JdnGhdtidmreds/U7FoARmruQ0AAIk/AKBP6U21fBOmSZdpW7iszPbtRavloKkBuZna1Rz+Kn1WRlrYCvex4M5wyNsSPmV2pUmG51iMmLb9czrMVhH0tgVktDtBJEqkXQxoTwgAiUVxPwBAnxKolh/Kka3WTJSVjlBedugrqXk5Ll311fBLth2S/uOc0Vq0dKPueWq13nx/p1as36s339+pe55arUVLN6rN337y4KxThis9LXSxO1N52S5dfd5YOcNszumQZp8/1mib500dZhR38RnHG8WZVqT/3tdPNoq76qujjeIu+dIJys0Kf5Ll5BMKjOZBWelwlZWOUG642M9bJ7b4fLr1sZW675kP9VnVIVUf8OqzqkO675kPdetjK9Xi88VsbkdTm99vNK97Gw8AiA0SfwBAnxNRpX5DpknX5LFDNbi/O2TcoP5u/XPtXqNq739e8Yl8BsvQv3jy4LAJfUtrm0YOy5crPfR/7650pyaPHRp2n5L0zbPMXssLTj/RKM50v6ZxZ046zijulXc+C67CCCUvJ9M4+e6fm6nWMMsS3BnpKszPinoniESJtItBNLseAAB6j6X+AIA+x7RSf6RmzyiSHA6t316jhsbDiUpejkvFIwuDSdfd107VHQvfV/UBT6fF3g61J/0//EaJfv3sByH3tX57jbburAtbFV6SThlTqFlnjFLFjv06GKIQoLfVrwd+90HYWxFaWv166i8VYfcrSQ//vtwo7t4l7xrF/WLhCqO4x19ZYxT3+79uMorztrbJ1xD+3oH122r1X1dPNpoHj71SIW+Y19rT0hr1ThCJEkm7wcL8rIjjAQCx47CsBFX3sZnq6oOJHkJKSU93qqAgR3V1jfKF61sF9FHM88QxTboC92t7m33KznTpynPHaNSx/fX825v15vs7w+7nuCH99FnVobBx504ZIcky2iaO3rlTRuiys8eEbcN4+xOrjDoF5Ga7dDBM9X9JOn5Iv2AniGRkOq8Dr1+k8XbG5zlSAfM8MQYNyjWK44o/AABHCNf6L2D08AL9optEzbRSv9ew8n8kFeRx9AJV+MO1YTRtDxjtThCJEmm7QdoTAkDyIPEHACDKTCv1uw3uOZciqyCPo2fSLi+SNoyRdoJIVpG2G6Q9IQAkj+T+HwYAAEOJaBfW0z5N2rLluNtbuT36coVx+7a/fbjL+CpzKA5JrnSpxSB3TZMU/6Z/sZHulMKtPs3NOvx6//3Dz/TbN7YGT7kMyM3Q9ReO1+jhBebtH9OduuqrYzT/jxtDxjkkXVHWvty9tt6jV1fs0NbdDZIljT42X1+fdkKX+WwaFy2RthvsS+0JAcDuSPwBAH1am9+vJcs2af322k4JxqoNVSoe1V6ILc0Z3SY2JvssHlWoFRV7e9xGo9enhUs/0viRA/Tuhqoe49yuNPXPzVSb3y+HHAp35T83O11OSfVNPWf1aU7pP785Ub/63ZqQ25Kkn105Sfc/82HIvTokffuro/X0G1vDbm/iqHyt2V4fNu7UogH696b9YeNuuOhkPfHnj9QS5oRImkOaevIQrazo+bWWpAmjCpSZmaZrfvXXLs/tP9ii+575UIX5bv3nN0vCJrXt2yvUxDGDlenaFPKq/8D+bo0clq+Ff96g9zbt69TpYU9tk1Zt2Ksp4wbrOzPa2yEufu2jsHHRnveBzheh5nXHdoORxgMAYod2fgCAPi0R7cJM9hloy+YI0YJv3wGvtu6sD9kecN8Br5b85WPdsfA9tRgUS8rKSA9Z+V9qv+r9r/WhE+CA0cMLwt5kYMm8rd5N35xsFHfdrIlGcZPHDlWrQTvENktGd0ts3dWgH/3POyFjauu9+p8X14Vt+ydJ7ow0LVkWOumXJMuytGTZJq3cUNVte8fWNksrK6q05C8fG8fFQqTtBpO9PSEApAqq+kcJVf3ji6qhSAXM8/Bq6z2656nVYZcS//yq0qhdVYxkn3UHvbrvmQ/DbjMnM02NzT0vqHdnOORtScx/1zkZUmNLQnZtJM8tNYTulBcz3581Tk/8eVPIEw+5WS41t7Ya3VaRYXD7RY47XW3+trDzITfLpTtmR2/eHynSdoPJ2J4wnvg8RypgnicGVf0BALa3fHVl2KXWDY2tWr56Z9TahUWyz02f1RltM1TSLylhSb+U3Em/lLikX5J+++bWsKsNDnrMK9abnBwwLSp40BPdeX8k084XvY0HAEQXS/0BAH1WItqFRbLPZG/PhqNj2qYvUWiTBwAI4Io/AKSYRFS/j5VEtAuLZJ/J3p4NR8e0TV+i0CYPABDANxIASBGJqH4fa5G2C4vGSY9I9lk6dqDRPf5pTofa/D0vGece/54l8h7/q746Rr99Y0vIuZDIe/z7Spu8rTvr9MzyLfI0+5SV2d7mcvTwgkQPCwBspW99wwMA9Foiqt/HWqBdWCjFIwvVPzdTi5Zu1D1Prdab7+/UivV79eb7O3XPU6u1aOlGtfnNr9oW5mdpwqgBIWMmjBygwvwsjRyWL7cr9H+1bpczZNIvSZPGDA5Z+b+j0ycMUYhGAkHTJgw12t4j/3mWUdyTtyYm7jc/MouTpKlFA8PGZKQ7jF6/Qf3dOnlkoQ6GbedXoClF4V/rTJfTKG7i6IGafNKQsHHFowYk/UqeFp9Ptz62Uvc986E+qzqk6gNefVZ1SPc986FufWylWnzcKgMA0dKrxL+lpUWPPfaYPv30U0nS3LlzNWnSJM2ZM0d1dWaFjAAA8VNb79H67bUhY9Zvr1FtvSdOI4oek3ZhUT/pEfbie3vquGTZJnlDLAXPSJNcrrSwu9v0aZ3uvnaqBhkl/w6TrnX6+vQTDKLUJ+dET97bVBM2psVnKT8n/BJ5y2/pJ4+sCPtab93VoK9PPyFkW0dJ8vstfX36CTp9wlC50roGu9IcOn3CEM2eUaTZM4rCzwWTsxcJdsfC97TvQPfLNfYd8OqOhe/HeUQAYF+9aud333336U9/+pOefPJJ1dbW6vrrr9dNN92kv//97xo5cqTuv//+WIw1qdHOL75oF4JUEM15/vzbm/Xm+zvDxp07ZUTMqoDHWk/twqLd8s90ezdeNEGPvlwRMs6V7lCrz+y/4duvnKSCXLd+vmhVVJb9u5xSEt+ebislJw7Q2m37w8Z96QvH6Dszxqm23qNXV+zQtt0NkiWNHt5fX592QrD9XSLaWEbb1p11YW+DcUi67cpJtlj2z/cWpALmeWLEtJ3f66+/rv/+7//W+PHjdeedd2rq1Km6/vrrNX36dH33u9/tzSYBADGUiOr38dZTu7Bot/wz3d4zy0Pf+y3JOOmXpGeXb9HY4/pH7V5/kv742fCJ2WrIbbvqJbXP5e/MOLnHuES0sYy2Z5ZvCRtjqX3e3/mdqbEfEADYXK+W+h84cEAnnniiJGnFihWaNm2aJKl///7yehPYUBcA0K1EVL9PFtE+6WG6PW+UW/l5mn3G+0ZyscLUcAgyXJ5vhxN5pq0uaYkJANHRqyv+xx13nNavX6/a2lrt3LlTX/rSlyRJb731loYP7xsVZAEglURa/d5Oon3Sw3R77ii38svKTDfeN5JLZmaamrxtYeNOHJYnKXz3CTucyDNtddldnJ1akgJAvPTqG8S1116r//zP/5TT6dRpp52moqIizZ8/X/Pnz9d9990X7TECAI5SoPr9ioq9PcYUjyy05ZfnaJ/0MN3elWVjwt7jn5fj0rDCbG36rD7sfi8/e7Ref7/SaIwmEtkGL9XMPu8k/d+fPlKoqkrpaQ5dcPoJWrR0Y9iWm2WlI/RuxV4d9PR8NTw3Oz2pT+RdWTbGqNVlXk6G2vx+pTmdtmxJCgDx0qtPx1mzZunFF1/UQw89pAULFkiSiouLtWjRIs2aNSua4wMARIlJ9Xs7Mm35Z3rSw3R7o4cXGMX95LJJcoZZ4u12OfWvdXu1ZkvozgySeZs+0zZ4iWrTF+24SIT7eUQa9+GW/SGTfkkq6JepV9/5xKj7RGF+Vtgr5lkZ6Ul9Im/08AKjFpXrt+8PHrcdW5ICQLz0qqo/uqKqf3xRNRSpIFbzvKfq93bW5vdryV8+1vrtNWpoPJw05OW4VDwy8iuFptsziTtwsFl3P7U6ZD/4bHea/G2StzX8cnF3ukQpgL4nOzNNDofUGOKWgEClfklh50xetks/vzp5q/pLUovPp9sf/7f2H2wOGWfaJSOZOxnwvQWpgHmeGKZV/XuV+FdXV+s3v/mNPvjgA7W2turITbz99tuRbrLPI/GPLz5YkAqY59EX7ZMeptsLFWfaahGQ2ltuSpZt2nOazv/jh/TTp1WHwsYl6zHzeY5UwDxPjJi28/v5z3+uiooKzZw5U7m5ZjsCACDRemr5F+vthYqjUj8i0eRtlekVm2Su6h9g3KHAsLp/XzhmAEiEXiX+q1at0sKFC1VaWhrt8QAAkFKo1I9ItFfqN0v9k7mqf4BxhwLDLgB94ZgBIBF69W0jOztbhYWhCxYBANAdu7TiMj2O8o/36qk3tqi5xSdfm6XsTKcK87N1ZdkYjR5eYNQlIMedpjbu8bc1h6P9Pv9w9/gHKvXHqj1nvN+fpl0yrjDskpHMnQz6Irt8XgPoZeJ/4YUXauHChbr77ruVlpYW7TEBAGzILq24TI/D09KqnzyyQt7Wzvc5Nnr9avQe0n3PfKjB/d2685opynSlSeo5oZkwqlDpTmfIdoyS5EqT/venZ+maX/017HE88P99UTf/37th475cMlj/WLsvbJxpe8AMp9RicOunadyg3DRVHwx/QiQShXmZqm0IXXBOaq/q749SieSxw3NVmJ8T8mfsdqWpf26m0pxOTRg1QCsrqnqMnTByQEQJWqLen6atRgNdMlKxJWki2OXzGsBhvXrHHjhwQK+++qrOOOMMXXbZZbrqqqs6/QIA4Eh2acVlehzdJf1H2nfAq588slLV9aEz5jWba4zaLRosCAgyTZCuPn+CUZxpe8DHbolu3K9v+LJRXCRMkn7JPOkflJ8ZNmZT5UHNnlGkwf17/rnsO+A9/D4Ju2/DXoOfS+T707TVaKq2JE0Eu3xeAzis1zcWXnDBBdEcBwDAxmrrPVq/PXQP+vXba1Rb70nqK3amx/H3Dz8Lm/QHmCzfb/b5tfDVdUbbm/vYv4ziTFYF2CkukQr7pam6PnzcS3/fLG9L6Ps01m+v0daddarYsT9kXMWOWuP3U6Lfn2lOp+bMHBe2S4ZpHI5OoucDgNjoVTu/pUuX6ktf+pLy8/NjMaY+iXZ+8UW7EKQCO81z05ZdydqKK8D0OFzpDrX6orQGHDhCtFvb2eX9mcz60uc58wG91ZfmuZ3EtJ3f3Xffrd/97nck/gDsweNR/neuUMZf34ron1kOh6zsHCk7W1ZOjqzsHFnZ2Yd/7/hYzuePf/6YsrM7xwafa/+zMsMvDe5LjFt2JXkrLtPjaGsj6UfsRLu1nV3en4gO5gNgT71K/E844QRt3rxZo0ePjvZ4OmlubtZdd92lN998U263W9dcc42uueaabmM3btyoO++8Mziuu+66SxMmHL4vcenSpfrNb36j6upqTZ8+Xffcc48GDBggSbIsSw899JD+8Ic/yO/369JLL9VPf/pTOSlaAqQE1werI076JclhWXI0HpIaD0nVMRjY5wqivD0rLU1WTr/PTzJkm5+8CPw9J0fqIU6u7ltpGbfsSvJWXKbHkZbmkJ8r/oiRaLe2s8v7E9HBfADsqVeJf1FRkX76059q4cKFOuGEE5R5xJWp+++/PyqDmzdvnioqKvTUU09p9+7d+tnPfqZhw4bpvPPO6xTX1NSk733ve/ra176mX/3qV3ruued03XXXafny5crOzta6des0d+5c3XXXXSoqKtK9996r2267TY8//rgkafHixVq6dKkeffRR+Xw+3XzzzSosLNScOXOichwAklvrlFPl+Y9vK+t3v030UOLC0dYmR0O91GBw03GU/ODzX0fDysj4/CRDv04nHVoy3NrjlbzpmbJycnTs8UPkLsjr4eTF4cfUcYWFYYca09Zjs6Yfr6ff2HqUR9zZqUUD9O9Noe/rlqRj+ru05wBX4pLJuBH99FFl+KX5500dppUV1VFvbReuJZvpvKZVXmpgPgD21KvEf8eOHZo8ebIkqbo6Npe5mpqa9OKLL+qJJ57Q+PHjNX78eG3ZskXPPvtsl8R/2bJlyszM1C233CKHw6G5c+fqn//8p15//XVdfPHFeuaZZ3T++edr1qxZktpPKHzlK19RZWWlRowYoaefflo33XSTSktLJUk//elP9T//8z8k/kCqyMjQod/M16HfzO/9Nvx+qalJjqYmOZoaj/i9SY7GQ10eUzePHY5rf9zZ1CR5PNE71j7M0dIiR0uLdOBAp8czJMXrLtNBkp41jP3G5783p2fI63LL68pUs8stb7pbngy3ml2Z8rrc8mW41ZiWGYzxZrTHBJ73utzyZWXpuzNP1yer9rZvw5WpZlemLEfXlWl3f2+avjvv72HH9+StZm3/7BIXC6bt/P7z8lKjn8k3zypSQ2ObVm4I0abvhAFGre3crjTl5ri0aOnGsC3ZTFvqUcgtNTAfAHvqVeL/29/G/qrYpk2b5PP5NGnSpOBjkydP1mOPPSa/399pGf7atWs1efJkORztrWscDodOOeUUrVmzRhdffLHWrl2r7373u8H4Y445RsOGDdPatWuVkZGhPXv2aMqUKZ32s2vXLu3bt0+DBw+O+bECsAGnU+rXT1a/fuG7bBmKS5Ecn08OT+BERKMcjUeetAj9mD5/rHZ3rdoaDiqz1St3a7PcPq9cbWb3idpdpq9Fmb4W5R/t+ZtnpIUmcf8t/TnGcS1pLh1y99OhzBwdcvdTY2aOcj/9nb637ZAaM/vpkDtHhzL7aW//oTrozv38hEaWvOmZUuQ1hZPWlKJB+vdH4S+ALFm2KWzMwPyM9j+E68L3+fOzZxRpy84D2neg+1aQ+w54dcfC97p9PtCSTQ6H5swcF9yeHA6t316jhsbDJwnyclwqHllIq7wUw3wA7KdXif/u3btDPj9s2LBeDaaj6upqFRQUKCMjI/jYwIED1dzcrAMHDgTvzw/EHllvoLCwUFu2bJGkbhP4wsJC7d27N7hioePzAwcOlCTt3buXxB+AvaWny8rNk5Wb1+tN1NZ7dM9Tq8MuC/35VaUqzM+KSiuu2up6PfTkCrU2HGo/0dDqDf7K/Pzv/Z2tmjlhoHL8LZ1WUbSftAicuOhmxUVb+PZ6qS6jrVUDGus0oLHu8IM7yvU1k3/8SOxOTLQ5nGp2ZcrjcgdXRnhd7s8fy+qwiiJTzZ+vvAg873W55U3//ARFYHWGK1Pe9M9XXaSlS47OWblJ0i8p5JXTgJr6FpV/vFcV28O16duv2vr2s0jeltBztbqHkwIBHVuy0SoPHTEfAPvpVeJ/1llnBa+ud+ejjz7q9YACPB5Pp6RfUvDvLS0tRrGBOK/X2+PzXq+307ZD7ScUp9MhpzPcaXpES1qas9PvgB31lXn+VvmukEm/JDU0turtD3bpP8pO0pDCHF351aO7WvTW+mrttdxSbugvoE2lx+k/yk46qn0d6dk3N+uN9z6L/B9allxtrcpq9R5eGdHqVY6/Weleb6eTF+7W5g4xnmBs5hEnOTrGOaO21qTvSrP8ym7xKLulb90e0+pMV7MrU81PuDUhvf2kQ/cnL9pPQtTuWK7WjCxN3t0UvB2k40kNrysr+O8sZ8/1Kzq+LwOi8f5EV33l8/xIzAdEoq/O81TRq8T/6aef7vT3trY27dixQ0uWLNGtt94alYFlZmZ2SbwDf3e73Uaxgbiens/KyuqU5AeKFAZis7LM710aMCAn5MkQxEZeHveXwf6SfZ77DJdu+/xSQUFOn91npPvuwuFQa3qGWtMzpKzDKyxM7xNPFKe/TVktHvVrblROc6P6eQ+1/2puVM7nv/drbn8sx9v+5/a4RtXl9Fd13qAOJyyOOJHhMz/Bbmcuv0+uZp/6NTea/YN32387M2YjMpSZKfXrJ31eLLPLr+6eM33Mpp2Vkv3zHIgG5nly6lXiP3Xq1C6PffGLX9SIESP0yCOP6KyzzjrqgQ0ZMkR1dXXy+XxKT28fZnV1tdxut/Ly8rrE1tTUdHqspqYmuEy/p+cHDRqkIUOGBLc9fPjw4J8ladCgQcbj3b+/kSv+cZSW5lReXpYaGjxqa4vRvc9AgnWc5/v2N+r1f1eqyduqbLdL5506otvCSrX1HqO4aEo3POmZ7pTq6gwTmxjss7beo+ff3qKK7fvltywV9MvQtV87WaOHR9Yw0XTfppK99Z/fmaZGdz81uvsleigRcfrb2usrtHqV1eJVps/b+baQFq/cvsCKic+fa/HK7fN2s7qi84qLjDa6JkiSmpvbf9XWJnokEenayrSfrJwOf8/O+bx1aXbn1qWBv3foFBLsDpLTT8rK6nI7SADfW5AKmOeJYXqBo1eJf09OOOEEbdoUvoCNiXHjxik9PV1r1qwJVtsvLy9XcXFxp8J+klRSUqInnnhClmXJ4XDIsix98MEHuv7664PPl5eX6+KLL5Yk7dmzR3v27FFJSYmGDBmiYcOGqby8PJj4l5eXa9iwYRHd3+/3W/In8yUbm2pr88eu6BmQBNra/Pq/P67Xuq01nZbTv1uxp1NV7ja/X0uWbepSvfvIuFg4Z/KxerdiT9h7/M8+5diovV9N9ulKc+grk4apucWnJ1/7SKs2VnWqK+dp9ujuJeUalJ+pe757qjLSzf5LNNl3bpZLLa2tajaob/itr4zSM8u3Ge0b5vzONHkysuTJyNKB6C76iJnrv16kha9UKLPl85MMHU9WtHg/r13h00WnDJGaGvX3dzYro7n9ZEVmxzhf97eLpPupXyHpcGcV1YSNjbbeVlOxHI4OJyq6b1F6+M8dTl4ET2Zkd/43HduZZmb2eMIC6A2+nyenqBX3O3TokB5//PFg8ny0srKyNGvWLP3iF7/Qfffdp3379unJJ5/U/fffL6n9qnxubq7cbrfOO+88PfTQQ7r33nt12WWX6fnnn5fH49H5558vSbr88sv17W9/WxMnTlRxcbHuvfdenXnmmRoxYkTw+QcffFBDhw6VJD300EO65ppronIcAHA0Hnlxjd5Zt6fL40dW5V6ybFO3BcS6q94dbYlo/WSyz9Y2S6+u+FSyLL0boj1adX2z7lj4vn51/Rejtu8vnFgYsuJ6wOD+bu3YE51VEIe3maV9B8Lf457s7ff6Qju/wf3dYX/GkvntHC//8xP5nOnyhVhhMW3CUKVdcLIWLd2oFb5Tjmp80yYM1ZwLTg4/sHAsS2pp6bGFqTo+1hi+1amj8VDn9qh+EgiHZbW/Lo2HpNh00o4JKy2tfUVFl1UWYU5eBP6ek9N51UXwuX6Sy5XowwP6FIdlRX6zYlFRUZf72S3LUnZ2th544AGdffbZURmcx+PRL37xC7355pvq16+f5syZo9mzZ0uSxo4dq/vvvz94FX/dunW68847tW3bNo0dO1Z33XWXTj758H9mL7/8sh5++GHV19dr2rRpuueee1RQ0L68s62tTfPmzdPLL7+stLQ0XXrppfrJT34S0T371dUHo3LMMBOXNmdAgtU3Nuuuxat14FBzjzF5OS7deNEEPfpyhXFV/Vho8/u15C8fh2z9FO0VB/vqmvTzhf9Wa1vP/43luNPktyRPc/grnbdfOcl42X+44/369BP0y6fLdTDEz8ThkG6+rET/84e1amblOAzd+h8TVZifFbaThivNobvmTNFr71bG9X0ZS5F2EAnLsiSvt4cTEJ1bmaqn9qaNTXI0Herw5w7/Bn2WlZFxxEmJwycv1O2JitCPqeMKi7SeC272dXw/T4xBg3KN4nqV+L/33ntdHnO5XDrppJOUk9NH1tNFGYl/fPHBglTwwl+3GlWPP25IP31WdShs3LlTRuiys8dEY2g9imfrp+ff3qw3398Zte0dP6Sf7vxO1xo2ofR0vKZjO35IP31q8LMDAo4f0k9jj+tvNL8C73m7tGQzfV/F47MuUlH93uL3d14R0dNJiQ6PKWRchxMf3vArWJC8rKysbldHWEfc7hHpyQtlZxsV3OT7eWKYJv69Wur/3nvvac6cOV2q3h86dEj33nuv5s6d25vNAgA6aPKaXQb2mtxIHsH2jkZhfpYuOzu67fN60ug1O25THsPXsaOejtd0bE292CdSm6fZZz6/Pn/Px/N9GUuRHrdtOZ1Sv36y+vXrW008fT45PJ/XV2gMfaIi9MmLblZoRNCC284cHo8cHk/CC25GVjJXPdafaK9X0fXkhcKusmiPl9tN/YoOjBP/bdu2af/+/ZKk+fPnq6ioSPn5+Z1iNm/erN///vck/gAQBdlus/sX3ZlmH+Wm2+srctxRrU+rLMPX0YTp2LKjuE+khqzMdPP5laLvebsdt22kp8vKzZOV29sShwnS2trtSQkFHmvscEIixMkLHbnKoqlRDh8nfyV9/ro0Kt4FLJp++BM1zr0zrvtMJONvHJWVlbr++uuD973feOON3cZdcskl0RkZAKS4804doX9vrAp7j/+VZWOM7vEvK41O8dVkUVY6Qqs2VIU87kju8b+iLPKlwYEl1I1en3Lc6SorbW+faDK2vByXrigbo4de+JB7/GHsirIxKsh1G82vSN/zPc3n3sZFm+n7ym6fdfGWqJ9v0nK5ZOX3l5XfP9EjMWdZUnNz1xMNjY0dTlwc8VhjBCcvIr9TPCll/d8javzJz9pXBqQA48T/zDPP1F//+lf5/X6dc845evHFFzVgwIDg8w6HQ9nZ2erfv38sxgkAKacwP0uTxw3W2+9X9hhTPLJQo4cXxL2qfjIwqa4/cfQgSQoZI7VXPzct7Cepx/aJqzZUBdsnhhtbS0ubjhuaq9KxQ8OOTzKvDD9tgtn25v/nl3TDf/8rbFyyV+tPZFV/k9fa6ZAy0p3ytoa/39WkS8DfPtyta2aOCzu/3K409c/NDLtPyWw+h2obemRcrCSig0gqSfTPF1HkcEhutyy3W9aAwrjt9qjv8bcsyePp9kSF0cmLkCsvmrrsrmHBkpRJ+qUI7/EfNmyYJOntt9/WsGHDIqp6DwCI3A++MVEtzT6t3dZzVW5J7b87HCGrd9uR6XH7ZWnVhip1d5FiUH6m7r42sqJ+Ju0TZ88oUvnH+3pM+Lytft2x8H3d+71T9d5He9UaZlHCb344XTf95p2wY5s9o8go8f/JIyvDxiA0k9fab0kP/WCa0UmWu6+dqu8/9C/5Q1xNe3dDlZxOp2bPKNKWnfU9tm7cd8CrJX/52KiNp2k70ES2DQ1I1c+6eEiGny9SnMPx+f372bI0MNGjsZ1eVfWXpH/84x9auHChduzYoRdeeEEvv/yyjjvuOF144YXRHmOfQFX/+KJqKFJBx3leVdtoVJXbLtW7I2Vy3LX1Hr34t62q+KROlmVpQL9MfWdGkUYd2z/ifZm0FPv2uWM0/48bQ27LIenbXx2tp9/YGjbuq1OH6fX3docd34lDs7Rtb/fJIKKrINuhuqbwX6MmjsrXmu31YePOM/wZ57jT9cNLi6PSxtN0PidD29CO+tpnXbJ/b4l6q0SkpGSf53YV03Z+K1as0PXXX6+ZM2dq2bJleu211/SHP/xBTzzxhO677z7NmjUr0k32eST+8cUHC1IB8zw5mbYU65ft0qEQX6IDXOkOtfrscb8k4se0FWS41nam8zmZ2ob2Rcn+ed6XWyUieST7PLcr08S/VzfqPPLII/rJT36iX/3qV0pLS5Mk/fjHP9aPf/xjLVq0qDebBACgTzBtKeYLt3b/c21tJP2InGkryHCt7UznczK1DUX00SoRsL9eJf4ff/yxzjrrrC6Pn3feefrss8+OelAAACQr05Zi6a40o7i0NOrlIHKmrSDDtbYznc+p2jY0VdAqEbC/XiX+ubm52rdvX5fHt27dqvz8/KMeFACg76mt9+j5tzdr0Wsb9fzbm1Vbb8/7zMtKRygvO/SX37wcl67+avjlsA5Jl599olHceVOHGY3vxKHcfxsvBdlmJ20mjjL7bmT6M85xp+uKsjFG8zDQ2q623qPFyzZq7sJVmvvEKi1e9pFq6z1G8znHnaYrI9xfQKp8LvR1pp9rtEoE+q5eJf5f+9rXdN9992nTpk1yOBxqbGzUP//5T91zzz2aMWNGtMcIAEhibX6/Fi3dqHueWq0339+pFev36s33d+qep1Zr0dKNavPb6z6//rmZcmeEvppfPLJQk8cO1aD+oYuNDezv1pmTjjOK++ZZRQqXZjok3XrVqWGi2rldZl8Bnry16wq/vhgXC/Nu/LJR3A2XTgob43RI3zyrSAPzMsLGThw9MNjGM5TikYXqn5uphX/eoNsWrNK/1u3Vnpom7alt0r/W7dHtC1bpj//argkjB4TcTkurX/9YsydsXMdWeqn2udDXBVolhkKrRKBv61Xi/6Mf/UgjR47UrFmz1NTUpIsuukjf+973dNJJJ+nHP/5xtMcIAEhigRZQR1aDDrSAWvKXjxM0sthYsmxTyF7rg/u7gy3FRg/LC7mt0cfmRxQXlkN6/E8bjELnXj3ZbJuGtu6sM4pbunKbUdzfPzS7dbD84/CtC2NlybJNYWOcDrO4KUXtrascYfqkZ7qcndp4Tis+Rnk5na/U5uW4NG3CUM2eUaQlyzZp5YYq+bqpJdHaZmllRZXkkKYVH6P0Hm47aW2zPm/nprD7C0i1zwU7MJlPAPquXrfzk6RPP/1UH330kfx+v0466SQNGzZMv/nNb3T77bdHc4x9AlX944uqoUgFfWGep1oLqEiOV1JU26SdM3mYXv7np70fPBLGKSncOzg3y6WrzjNrAXnblZM0enhB8LGeWtvV1nv0i8XvqdEbutBkbpZLP7hkgh5+ab0OeXou8tZxbodqpZdqnwsm+sLneUBfa5WI5NGX5rmdRL2dX3Nzs37961/rtddek8vl0oUXXqif/OQncn5+Zvqdd97RnXfeqT179mjjxtD/adkRiX988cGCVNAX5nmqtYCK5HglyyjWtC2bwyH1/lQ9+gLTFpDHD+mnO78zNWyc6XwNbDMa7QEj2a9dPhdM9IXPc+BoMc8TwzTxNyvhKWnevHn6/e9/r69//evKyMjQc889p379+um6667TL3/5Sz333HM67rjj9NRTT/V60ACAviXVWkBFcrymObppWzaSfvszbQHpMZwzpvNVil57wEj2a5fPBQDoC4wT/7/+9a+aO3euLr/8cknSmWeeqXvvvVd79uzRH/7wB11zzTX64Q9/qIyM8EVpAAD2EOsWUIElp41en3Lc6SorHZHQpcGRHa9Zpm7alo0r/vaX7kqTWsNfJcsynDOm81WKXnvASPZrt9ZwyfZ5BQAdGf+PUFNTo+nTpwf//qUvfUm7du3S8uXLtXjxYp16qlkVYQCAfZSVjtCqDVVh7+WNtAVUm9+vJcs2af322k7bXrWhSsWjCjV7RpHSwhRBi4VIjzdcrCvNof84Z7QefblCB0PcW52bna6y0mON7vFPc0ptBissc93SwZ5rFCKKjO/x/6rZPf5XlHVeHt9TwllWOkLvrN+jJoN7/K8oG2NUa8LkvWzyPslxp9mmNZzJ51V67+ppA0DUGH8Ktba2Kjs7O/j3tLQ0ZWZmau7cuST9AJCiYtUCKlkrgkdyvCaxrW2W/rmuKuwV3KyMdF1w+olGYzzt5KFGcV8Yc4xRXLK36UtkO7/BYdowBnxxQvifSfGoAcYtIAOF/cK1zOufm6l+BlfVv3BioXF7QJP3ssncb2n165V/7bBFW79k/bwCgI7M14D14Atf+EI0xgEA6KNmzyiSHA6t316jhsbDX3zzclwqHlkYcQuo2nqP1m+vDRmzfnuNaus9CVlGG8nxfm3aCXrvoyq1dtNKLWDNln1yOLpvoxbgbWkzblv3pS8M1UFPi9Zt2x8ybsX6PUbbe/j35UZxP3n4b0Zx1/zqr0ZxP/qNWZzpfiPhchqtuFdNiLaOHZWMLtDmnQdUHSr+8ykw+ti8kHGjjz3c+jGQcB4pkHA2t7aFrQeQnubQ16adICm67+XAtv69cW+PrQTbWwQ6NGfmOOPtJptIPq8KCnLiNCoA6CqixL+7LybhvqwAAOwtzenUnJnjotYCavnqypBLhCWpobFVy1fvTEhF8EiO968f7AyZ9EsK22pNak/knn5ji9H4nnt7q8Ye1z9s4m9qzfZ6o7i6pugWIGgwvA0h2vuVzJJ+Kfzy/YAlf9ms9LTQiywrduzX1p112rCjLmTchk/qVFvvkaSwCee6bbVqCVNZ29dm6a8f7NJlZ4+J6ns5zenUrOknaO3W6pAtAhN5Ei8aTD+v3nivUqNPGBinUQFAVxEl/r/85S+VmZkZ/Htra6seeOAB5eR0PoN5//33R2d0AIA+ozA/S5edfdJRb6evVAQ3Od5IqqqH0xJBxfdo7hdHz9PcJkuhf34Nja16ZvkW45NekhU2NlzSH3Dkeyla7+XlqytDJv1SYk/iRYPpe63RQwcDAIllnPhPmTJF1dXVnR6bNGmS6urqVFcX+uw0AACm7FQRPJKq6uFkuNLUbFjxPZr7Rfx4I2ipF811DrF6L/WVk3hHw/S9lpOV/J9XAOzN+JvBb3/721iOAwAASZFXzjdtoRWrVluhtmta3dzhcIS8MpqX49K3zzWv+F6Q6w67X8TPgNwM1R5sCRvnjqilnlnq70p3qNXXc2xvum6YMk2KHQ6Hnn97c59sg2f6efXVqSPiOCoAoaRq600uCQAAkkqgInh3RcsCikcWqn9uphYt3Ri25V+sWgOabLcwP0tjhuerfHNNj9v5wqhCfbCl5+clafwJAzRxzGC5XZvkDXHVf9DnFd8PeVvCJv0nHZurzbsOhoyRpC+XDNY/1u4LG3dMf5f2HAh/oiHPbXb//olDs7Rtryds3MVnHG/U5jASg/Nd2lcf/ljGHJurLQav4XUXjjdqlXdlhC313q3YG7YN5EnD+4ecf73pumHKJCl2pTn0weZ9nWpdJLptZyRMP69SIakAkl2ytgqOF/seGQCgz5o9o0jTio9RXk7n5bF5OS5NmzBUs2cUGbfQilWrrXDbXbxskxYt3ajNO7svjpebna5pE4Zq6+6GsEv4t+6s15JloZN+t8upu6+dKkn60f+8E3b8N18xOWyMJF19/gSjuHuv/5JR3G9+ZNZ+b+7sLxrFmbY5dLucKszLMIq1HGlhYzJdTg0qyA4bNyg/07hVXiQt9Qrzs4zaQF4/a0LY91KsmLa0PLLAZV9rg2fyeQUg8VK99SZX/AEASSdcdXHTFlpbd9bFpDWgyf7f+6iq2zZmAWOPK9CXJx4T8kphQHW9V03e6pAxGRlpOtjYqvXbd8tvsAr8mTdC3zYQ8Pgra4ziTNv+/WLhCqO4uY/9yyjugWffM4o7ZWyBVlaE/pkFhGy79zmns/1KdTieFr9q6z3GrfJM42rrPfK0hC4Y6G1p04GDzVHtuhGpno4nN8slT4sv5Hukr1T8j3ZnEwDRl+ytguPBYVlW9PvgpKDq6vBL/RA96elOFRTkqK6uUT7DqsVAX8M879nzb2/Wm+/vDBt33JB++qzqUNi4c6eMiKiquOn+Q8nLcSk3y6VdNU1HtZ2Ozp0yQn/7cGfIe7oRfx3nl2lyGC7OdA5GOrdj5cjjaWpu1b/WhT/plSzjP1p8niMVJPM872ufmZEYNCjXKI4r/gCAPse0WngkVdJjsf9QGhpb1RrlL0ZN3la1hbiCisToOL9MW+WFi+trFfOPPJ5Fr5mtOEmW8QPo2/raZ2YskPgDAPoc02rhkVVJj/7+w3E6HFHZTkC226W0NIf8XPFPKpHOL5OK03297WVfHz+AvoXPHIr7AQD6oLLSEcrLDv2fc6BKuklcpO3MykpHKMcdvgBcOCefUGAcm5MZen+B47j8bLNid18uGWwUd2rRAKO4iaPyjeKOG5hpFHdMf7MvX+NG9DOKMz1eU1mZaXJnhD9xk5tlPr/a/H4tWrpR9zy1Wm++v1Mr1u/Vm+/v1O1PrNL8l9epzX94hYjpeyBWrfqk9hMUz7+9WYte26jn396s2vrwXRgCkmH8AFIHnzkk/gCAPsikWnikVdJNtfn9euVfO9QSphK/Ky10UpiX49I3vzJag/uHL/41KD9TE8cMChkTOI4zJx0XdnuSebX+62ZNNIq76ZtmXQJ+ce00ozjTLgE3XzHVKO7ysiKj11pq7wAQziljBmnySUPCxhWfOMB4fvVUcbrVZ6l8c43mLvh3MPk3fQ/EokhVTyco7nlqtRYt3djpBEVPEjl+AKmHzxwSfwBAH2XaQivarbYCyVlrD/fSu9IcmjZhqKaMC32FOfAF4+5rpyozTKI5ekR/4+Oorfco3HVoh6Tyj8MXVlMEcVt31iktzLeKNGf7+MKcEwluJz3M9tI/XwQxpWhg2PHdsfB93X3tVLnCLNT4womFcoUJSk9z6GvTTtDsGUUalB/uZILZ7RwmFaf3HfDo8T9tCP49UW3kotUSizZ4AOIp1T9zuMcfANAnmbbQimarLZPkzJ2RrllfGqn+uZlyOJxh27IdbGxVpitNzSFWEGzYsd+4LdurK3Yo3B3+lqT//aNZcbX5hnGP/alCbWEu9Lb5pUVLKxSu/mCbX/r9XzcpXO1DX5v09w8/08YddWHHt++AR+u31Sgr06XWpp6LN236tE4tYXbsa7P01w92qax0uJpbQ7fUq9hRa9Qeavnqyi6JdHfWbTu8vUS0kYtmSyza4AGIp1T/zKGdX5TQzi++krldCBAtzPPk05t2QPFuyzZ34SrtiWKLQFMOKewJB0lyOKRofvNwpTuM2xfmZrt00CC5NjG9eKiy3elR+9ktem2jVqw3W12RyHZTdm6JFUt8niMVMM8Tg3Z+AABEWW/aAcW9LVuSn86P9uWGSNoXtoa5Oh+JbLdLjYY/E5OfXSSdIhLZboqWWADQN5H4AwBgKBbtgHqzzVDt3kYfm689teGv+JteoTeVlZmmpubwiXV6mkO+CJL1cCJpX+hypckbpiijFH4VQaDy8/LVlUb7DfzsQv3cykpH6G8f7jJavWCyvVihJVZ8JeJnDMCeSPwBpDy+WMWHHV7nstIRWrWhKuS92JG2AyorHaF3K/bqoKfnK6m52ekqKx2uNr9fS5Zt0vrttZ3GsGpDlYpHtdcN+Pq0E7RqQ8/FB6X2AoRfm3acXv7np2HHd97UYXr9vd1h474zY6wWvPpR2P1efs6JevqNrVHb7+Vnn6iX/r5DjQYnHa766hg9/caWkMv987JdGjM8X+Wba3qMCRRmNJ0PZ08+VouWbgz5cyvMz9IXRhWG3G8k20tzdq2MGI33YCzeA+jK5L3e3c8YAHpC4g8gZfHFKj7s9DoH2gGtqOj5XuxI2wEV5mcpKzM9ZOKflZGuwvwsLVq6sdt9B6qpy+HQnJnjNGXcYK2sqOpxe1PGDdYFp59olPh/86wilW/er+oD3h5jBvV3a/LYoerfb5uq65t7jOvfL0NnTjrOKPH/5llFevP93fKHuADudDh05qTjtG3XoZA/E0kamJ+pyWOH6vd/2x4y8c/MSNP1syZoyV8+DluY0XQ+vPrOJ0Y/t+tnTdDtC1aFfK0njBxgvL2AaL4HY/EeQFeBzglH6ulnDADhkPgDSFl8sYoPu73Os2cUSQ5H2KTQVG29R56W0FervS1t2rqzzria+ndmjJPD4dS6rTU66Dk8xtwsl75wYvsYa+s9SnMqZCX+QPu90cfmhUxGRx+bp9p6T8ikX5Kq65sjaiOYleFUY3PPA8zKdKi23qPZM4q0+uN9ITsjOBztsXUNPR+HJNU1eI07KEjh58PXpp2g+35bHnKfHavgjzk2P+Rr3dzSpi076423J0X/PRjt9wA6i2bnBAAIIPEHkJL4YhUfdnydo90OaPnqyrCV5huaWvXs8i1h2701NLZq+eqduuzsMWHH+OqKHUbt937/ty36+LPQieaGT+rU6Pko9MY+t+g1s7in39gSMumXpEavX8tX71Tp2IEhk35Jqjng1TNvGLQI9EuvrvhE35kxLmxhRin8fHj+7c3GP7ey0uGq2LE/ZOz67fvDthvsOA9i8R5M9ZZYsWbS2rHjzxgATJD4A0hJfLGKDzu/ziZJoQnjKunN0e0osHV3g9H2Nn5yIOwYGxpbtfHT0CcHArwtZoX4Wgwr8Dd5W/XM8i1h4yxJGz49YLTNbbvMjqWjnl7rSKrgm7xfwiX9HbcnxfY9GK33ADqjcwKAWCDxB5CS+GIVH7zO4RlXSc+McjV1w8L6/lA32fcizrSbQIYrLexVfKn9eD2GJ0X8pr0EHWZhAaGK5kVSBd+0PaDp9iTeg30RnRMAxELfqKYEAFHGF6v44HUOr6x0hPKyQx9/Xo5LV5SNMYozraY++th8ozjTpdtZhicmCvMzw8Y41F6B3/R4TfedlZFmFHfisLzgn2vrPXr+7c1a9NpGPf/2ZtXWe4LPtfn9WrR0o+55arXefH+nVqzfqzff36nbn1il+S+vU5vfb/zzLSsdbvx+caWHPjPRcR7wHux7IpkzAGCKxB9ASuKLVXzwOocXqJIeSvHIQo0eXmAUZ3qf9tennSBXWugE0pXm0NXnnWT0M5x9vtmS7+997WQN7h/6ZEKgS8D4EwpCxo0/vkCF+Vm64pzRYffrkHTVueGXsqenOfT1aSN7TOrveWq1Fi3dGKyUv6Jib5el9K0+S+WbazR3wb/VPzfT+Odm+n75QgTzgPdg32P6mdBX6qIASA4k/gBSEl+s4oPX2czsGUWaVnyM8nI6J2h5OS5NmzA0WCXdNM5EYX6WpowbHDJmyrjBxiccJo8dqkEGCf3o4QW685opcru6v/rudjl15zVTJElbwtxrH3j+n2vDdwoY1N+tl/75Sdi4qUWDVZif1WNSH6iE//ifNoQtmrfvgEeP/2mD8c/N9P1y/awJxvOA92DfFM33OgBI3OMPIIXRkio+eJ3DM62SHu1q6iZt/yTzn+E9107VHQvf174DHh1pcH+37r52qiTpd29ukbeH4n3eVr9+t3yrvlwyVDVh2gPWfN4eMFwC7nBIF33pBD3+500h4yTpjJJjjCrhr9tWa1Rob9222qi2B5w9oyjiecB7sO+hcwKAaHNYlmmlG4RSXX0w0UNIKenpThUU5KiurlE+wwrHQE+S9YuV3eZ5sr7OMP/ZmMZt3VmnZ5ZvkbfZp+xMl648d4xGHds/uI17nlodstJ8Xo5LWa40VYXoZx+Q7U5Tkzd8B4DcbFfYtomSdPyQfhp7XH+9+f7OsLGmzp0yIuKK+bF4v/AeTBy7fZ4D3WGeJ8agQblGcST+UULiH198sCAVMM9hR8+/vdkoqU5zOtRm0CnA6ZBMGgpkupxGXQIG93drzIj+WrE+/O0DpqYXD9U1M0+O2vbQ9/B5jlTAPE8M08Sfe/wBAEDcmLaXM+2o53SaRWb0UFPgSFmZ6caV8B2Gg6RiPgAg0bjHHwAAGAnVr96UaVJdmJ+pqrrwS/3Hn1CgHXsOhr114NvnjtH8P24MuS2HpCvKxqgg161VG6rCbvO4QTmq+ORAyG1SMT82ojEXASCVkPgDAICQAq3r1m+v7ZQMr9pQpeJRhwvOmSgrHaF3K/bqoKfnK/+52emaM3Oc7n/2Q4W6IdHhkK48d6xe+dcOrajoeWl+oOvA4P7btS9E3YBA1wFJKh5VGHabs2cUae6Cf3dbzLBjHAlp9ERzLgJAKuGTEQAAhBSutd2Sv3xsvK3C/CxlZYa+7pCVka7Rwwt02slDQsaddvIQFeZnGbc+u/vaqRrcP6vLbQQOde46IJm1U0tzOnXv905V6dhBykh39hiH6InmXASAVMIVfwAA0COT1nbrt9eott5jdGW7tt4jT0voKvzeljbV1nt0zcxxcjqdWrOlulNtgBx3uiaOHhhMqk1bn2Wkp+tX138xZNeBgEhaLH7/omIq5sdBtOciAKQSqvpHCVX944uqoUgFzHMkA9Mq/KYt63qzPZJqSNGfi/HE5zlSAfM8MUyr+nPFHwAA9Mi0Cn+Tt+dCeEe7vcL8LF129klG/w72Fe25CACphMQfAAD0yLQKf8eWdaEqrvdme6ao9G5vsZw7AGB3JP4AAKBHZaUjjFrblZUOD1ZcX7O1Wo3ew/fxr1i/RxNHD9LsGUUqKx2hlRV7dShUVf+s9Iha4FHpPTVEMhcBAJ3xvyAAAOhRYX6WJowcEDJmwgkDVJifpcWvfaQVFXs7Jf2S1Oht04qKvVq8bJMK87PC3vvZ6rMiulJPpffUUJifpeJRhSFjaJ8IAN0j8QcAAKEd2f+um+dr6z16b9O+kGHvf1Sl8o/3ytsaOvH3trZp6846o6FFUukdfZ9p60YAQGcs9QcAAD2qrfeoYvv+kDEVO/ar1dcmX1voRkGtbZYWG159f3b5Ft35nalh45avrgy59FuSGhpbtXz1zqSr9I7ImbZZBAB0RuIPAAB6ZJpYb/jkgNH2vM1t4YMkeZrNKrhT6T010ekBACLDUn8AANAj08Ta8oe+2h/gdIa7b6BdVqbZtQkqvQMAEB6JPwAA6JFpYj0gL9MobvwJBWFjHJKuKDNbll9WOkJ52aGT+u4qvdfWe/T825u16LWNev7tzdQAAADYGkv9AQBHjf7p9mXaQu3q88bq/mc/lBXiwr/DIV157ljtee5D7Tvg7TFuUH+3Rg8Pf4JAOlzpfUXF3h5jOlZ6N2k52LH1H3MbAGAHJP4AgF6jf7r9mSbWBblupTkdIQv8pX2+zP/ua6fqjoXvq/qARx2jHWpP+u++NnxRv45mzyiSHA6t316jhsbD8zAvx6XikYWdKr0vfu0jrdxQ1WUbgZaDlqRrLziZuQ0AsBUSfwBArwX6px8p0D9dDofmzByXgJEhmkwS6xf/tjVsVX9fmxWsrv+r67+orTvr9OzyLWrx+ZXpStOVZWM06tj+EY/PtNK7acvBi740Uq/8awdzGwBgGyT+AIBeiaR/Okuj+zaTxLo31fVHDy/QPd89TQUFOaqra5TP5z+qcYar9P7qih1GLQd//7ct+viz+pBxzG0AQF9C4g8A6BX6p6eeUIl1X6iuv3V3g1Hcxk8OhD2RwdwGAPQl3JwGAOgV+qejo95W148rs46D8hu2JmRuAwD6Cq74AwB6pS9c4UX8RFpdPxFGH5uvPbVNYeMG5Lm1q6YxbFxfmtt0JwCA1EbiDwDoFdM2bwm9wou4iqS6fiJ8fdoJWrVhr1pD3OfvSnPo6vNO0qMvV9hibtOdAAAgkfgDAHqpL1zhRXyZVtdPlML8LE0ZN1grK7q28wuYMm6wRg8vsM3cpvMGAEAi8QcAHIVkv8KLxAhXXT+RvjNjnBwOp9ZtrdFBz+E5m5vl0hdOPDxn7TC36bwBAAgg8QcA9FqyX+EFjmQ6Z+0wt+m8AQAIIPEHABy1ZL7CC3THdM725blN5w0AQACJPwAASIjaeo/eKt8ln2Up3eHQOZOPZcl5FNF5AwAQQOIPAADiqqdK8+9W7KHSfBTReQMAEEDiDwBAiot3j3cqzccHnTcAAAEk/gAApKhE9Hin0nx82aE7AQDg6JH4AwCQohJx5Z1K8/Flh+4EAICjR+IPAEAKStSVdyrNJ0Zf7k4AADh6VM4BACAFRXLlPZqoNA8AQPxxxR8AAJsKVbQvUVfek6XSfLwLGgIAkEgk/gAA2IxJ0b5EXXnvTaX5aCbpiShoCABAopH4AwBgMyZF+2ZNPyFhV95NK83HIkmnlSAAIBWR+AMAYCOmRftmTT8hYT3eO1aaf6t8l9osKd0pnTN5eKdK89FO0mklCABIVST+AADYSCRF+xLd470wP0tXnHuSCgpyVFfXKJ/PH3wuFkk6rQQBAKmKxB8AABuJpGhfMvd4j0WSTitBAECqIvEHAMBGelO0Lxl7vMciSaeVIAAgVVG2FgAAGykrHaG87NCJazza5R2tWCTpdnltAACIFIk/AAA2EmiXF0qsivZFUyySdLu8NgAARIrEHwAAm5k9o0jTio9RXk7nxDkvx6VpE4bGvGhfNMQqSbfDawMAQKS4xx8AAJtJ5qJ9kYhF1wG7vDYAAETCYVmWlehB2EF19cFEDyGlpKc7u23/BNgJ8xypwGSek6Sjr+PzHKmAeZ4YgwblGsVxxR8AACS1ZOw6AABAX8I9/gAAAAAA2BiJPwAAAAAANsZSfwAAgB4E6gs0en3KcaerrHQE7f4AAH0OiT8AAMAR2vx+LVm2Seu316qh6XBHgVUbqlQ8qr2jQJqThZMAgL6BxB8AAOAIS5Zt0oqKvV0eb2hqbX/c4dCcmeMSMDIAACLHqWoAAIAOaus9Wr+9NmTM+u01qq33xGlEAAAcHRJ/AACADpavruy0vL87DY2tWr56Z5xGBADA0SHxBwAA6KDR6zOKa/KGPjkAAECy4B5/AACQ1OJdWT/Hbfb1KNvtitkYAACIJhJ/AACQlBJVWb+sdIRWbagKudw/L8elstLhUd83AACxwFJ/AACQlAKV9Y9MwAOV9Zf85eOY7LcwP0vFowpDxhSPLIzpqgMAAKKJK/4AACDpRFJZPxYJ+OwZRZLDofXba9TQePjEQ16OS8Uj21cbAADQV5D4AwCApBNJZf3Lzh4T9f2nOZ2aM3NcsL5Ak9enHLdLZVNGaECeO+r7AwAglkj8AQBA0kmWyvqF+Vm67OyTYroPAABijXv8AQBA0qGyPgAA0cMVfwAAkBC19R69Vb5LPstSusOhcyYfG7xfn8r6AABED4k/AACIq57a9L1bsSfYpi9QWX9Fxd4et0NlfQAAzCTtUn/LsvTggw/qtNNO09SpUzVv3jz5/f4e4ysrKzV79mxNnDhRM2bM0DvvvNPp+ZUrV+qCCy5QSUmJrrrqKlVWVgafa2lp0a9//WudccYZmjJlim644Qbt3dvzFw0AANB7pm36Zs8o0rTiY5SX03k5f16OS9MmDKWyPgAAhpI28V+8eLGWLl2qRx99VA8//LD+/Oc/a/Hixd3GWpalG264QQMHDtRLL72kCy+8UDfeeKN2794tSdq9e7duuOEGXXzxxfrDH/6gAQMG6Pvf/74sy5IkPfzww3rrrbf04IMP6rnnnpPP59ONN94YfB4AAERHJG36ApX1f35Vqc6dMlzTi4fqq1NG6I6rp2jOBScrzZm0X2MAAEgqSfs/5tNPP62bbrpJpaWlOu200/TTn/5Uzz77bLexq1atUmVlpe6++26deOKJuu666zRx4kS99NJLkqQXX3xREyZM0DXXXKMxY8bo/vvv165du/Tee+9Jkv74xz/qxz/+saZOnarRo0frnnvu0fr16/Xpp5/G7XgBAEgFkbTpCwhU1r9m5sn61tljaKcHAECEkjLxr6qq0p49ezRlypTgY5MnT9auXbu0b9++LvFr167VySefrOzs7E7xa9asCT5fWloafC4rK0vjx4/XmjVr5Pf79cADD+j000/vst2DBw9G8agAAECytOkDACCVJGVxv+rqaknS4MGDg48NHDhQkrR3795Ojwfij3yssLAweJ9+qOedTmeXpP/pp59WQUGBxo4dazxmp9Mhp9NhHI+jk5bm7PQ7YEfMc9hRv6wMs7jsDKWnM/dhD3yeIxUwz5NbwhJ/r9erqqqqbp9ramqSJGVkHP5yEPhzS0tLl3iPx9MpNhAfiA33fEdvvfWWnnzySd11111d/k0oAwbkyOEg8Y+3vDyqOcP+mOewk2+dO1b/3lilA4eae4zpn5upb5aNVUFBdo8xQF/E5zlSAfM8OSUs8V+7dq2uuuqqbp+7+eabJbUn+ZmZmcE/S+3L9I+UmZmpAwcOdHqspaVFbrc7+PyRSX5LS4vy8vI6PfbWW2/pRz/6ka688kp94xvfiOh49u9v5Ip/HKWlOZWXl6WGBo/a2nru9gD0Zcxz2FG6pAmjBuiddXt6jJkwcoDSZamurjF+AwNiiM9zpALmeWIUFOQYxSUs8T/11FP18ccfd/tcVVWVHnjgAVVXV2v48OGSDi//HzRoUJf4IUOGaOvWrZ0eq6mpCS7vHzJkiGpqaro8P27cuODfX3vtNd1yyy267LLLdPvtt0d8PH6/Jb+fLgDx1tbml8/HBwvsjXkOu7n6vLGyrPbq/Q2Nh+/lz8txqXhkoa4+byxzHrbE5zlSAfM8OSXlPf5DhgzRsGHDVF5eHkz8y8vLNWzYsC736ktSSUmJFixYIK/XG7zKX15ersmTJwefLy8vD8Z7PB5t3LhRN954oyTp3Xff1S233KIrrriiV0k/AAAwF2jTV1vv0Vvlu9RmSelO6ZzJw6nYDwBADCRl4i9Jl19+uR588EENHTpUkvTQQw/pmmuuCT6/f/9+ZWZmKicnR1OnTtUxxxyj2267Td///vf1t7/9TevWrdP9998vSbrkkku0aNEiLViwQF/5ylc0f/58DR8+XKeeeqp8Pp9uv/12TZkyRd/97neDKwskKT8/P6L7/AEAgLnC/Cxdce5JKijIUV1dI1eIAACIkaRN/OfMmaPa2lrdeOONSktL06WXXqrZs2cHn7/00kt10UUX6Qc/+IHS0tL0v//7v5o7d64uvvhiHX/88Zo/f76GDRsmSRo+fLgeeeQR3XfffZo/f74mTZqk+fPny+FwqKKiQrt379bu3bs1ffr0TmN4+umndeqpp8bzsAEAAAAAiCqHZVncmB4F1dUHEz2ElJKe7uQKEWyPeY5UwDxHKmCeIxUwzxNj0KBcoziaLAIAAAAAYGMk/gAAAAAA2BiJPwAAAAAANkbiDwAAAACAjZH4AwAAAABgYyT+AAAAAADYGIk/AAAAAAA2RuIPAAAAAICNkfgDAAAAAGBjJP4AAAAAANgYiT8AAAAAADZG4g8AAAAAgI2R+AMAAAAAYGPpiR4AAADoG2rrPVq+ulKNXp9y3OkqKx2hwvysRA8LAACEQeIPAABCavP7tWTZJq3fXquGptbg46s2VKl4VKFmzyhSmpNFhAAAJCsSfwAAENKSZZu0omJvl8cbmlrbH3c4NGfmuASMDAAAmOD0PAAA6FFtvUfrt9eGjFm/vUa19Z44jQgAAESKxB8AAPRo+erKTsv7u9PQ2Krlq3fGaUQAACBSJP4AAKBHjV6fUVyTN/TJAQAAkDgk/gAAoEc5brNyQNluV4xHAgAAeovEHwAA9KisdITyskMn9Xk5LpWVDo/TiAAAQKRI/AEAQI8K87NUPKowZEzxyEIV5mfFaUQAACBStPMDAAAhzZ5RJDkcWr+9Rg2Nh+/lz8txqXhkYfvzAAAgaZH4AwCAkNKcTs2ZOU619R4tX12pJq9POW6XyqaM0IA8d6KHBwAAwiDxBwAARgrzs3TZ2SclehgAACBC3OMPAAAAAICNkfgDAAAAAGBjJP4AAAAAANgYiT8AAAAAADZG4g8AAAAAgI2R+AMAAAAAYGMk/gAAAAAA2BiJPwAAAAAANkbiDwAAAACAjZH4AwAAAABgYyT+AAAAAADYGIk/AAAAAAA2RuIPAAAAAICNkfgDAAAAAGBjJP4AAAAAANgYiT8AAAAAADZG4g8AAAAAgI2R+AMAAAAAYGMk/gAAAAAA2BiJPwAAAAAANkbiDwAAAACAjZH4AwAAAABgYyT+AAAAAADYGIk/AAAAAAA2RuIPAAAAAICNkfgDAAAAAGBjJP4AAAAAANgYiT8AAAAAADZG4g8AAAAAgI2R+AMAAAAAYGMk/gAAAAAA2BiJPwAAAAAANkbiDwAAAACAjZH4AwAAAABgYyT+AAAAAADYGIk/AAAAAAA2RuIPAAAAAICNkfgDAAAAAGBjJP4AAAAAANgYiT8AAAAAADZG4g8AAAAAgI2R+AMAAAAAYGMk/gAAAAAA2BiJPwAAAAAANkbiDwAAAACAjZH4AwAAAABgYyT+AAAAAADYGIk/AAAAAAA2RuIPAAAAAICNkfgDAAAAAGBjJP4AAAAAANgYiT8AAAAAADZG4g8AAAAAgI2R+AMAAAAAYGMk/gAAAAAA2BiJPwAAAAAANkbiDwAAAACAjZH4AwAAAABgYyT+AAAAAADYGIk/AAAAAAA2RuIPAAAAAICNkfgDAAAAAGBjJP4AAAAAANgYiT8AAAAAADZG4g8AAAAAgI2R+AMAAAAAYGMk/gAAAAAA2BiJPwAAAAAANkbiDwAAAACAjZH4AwAAAABgYyT+AAAAAADYGIk/AAAAAAA2RuIPAAAAAICNkfgDAAAAAGBjJP4AAAAAANgYiT8AAAAAADZG4g8AAAAAgI2R+AMAAAAAYGMk/gAAAAAA2BiJPwAAAAAANkbiDwAAAACAjZH4AwAAAABgYyT+AAAAAADYGIk/AAAAAAA2RuIPAAAAAICNkfgDAAAAAGBjSZv4W5alBx98UKeddpqmTp2qefPmye/39xhfWVmp2bNna+LEiZoxY4beeeedTs+vXLlSF1xwgUpKSnTVVVepsrKy2+0sXLhQZ511VlSPBQAAAACAREnaxH/x4sVaunSpHn30UT388MP685//rMWLF3cba1mWbrjhBg0cOFAvvfSSLrzwQt14443avXu3JGn37t264YYbdPHFF+sPf/iDBgwYoO9///uyLKvTdiorK/Xoo4/G/NgAAAAAAIiXpE38n376ad10000qLS3Vaaedpp/+9Kd69tlnu41dtWqVKisrdffdd+vEE0/Uddddp4kTJ+qll16SJL344ouaMGGCrrnmGo0ZM0b333+/du3apffee6/Tdu68806NGzcu5scGAAAAAEC8JGXiX1VVpT179mjKlCnBxyZPnqxdu3Zp3759XeLXrl2rk08+WdnZ2Z3i16xZE3y+tLQ0+FxWVpbGjx8ffF6SXnnlFXk8Hl166aXRPyAAAAAAABIkPdED6E51dbUkafDgwcHHBg4cKEnau3dvp8cD8Uc+VlhYqL179xo9v3//fj344INavHix1q9f36sxO50OOZ2OXv1bRC4tzdnpd8COmOdIBcxzpALmOVIB8zy5JSzx93q9qqqq6va5pqYmSVJGRkbwscCfW1pausR7PJ5OsYH4QGy45++77z5ddNFFGjNmTK8T/wEDcuRwkPjHW15eVqKHAMQc8xypgHmOVMA8RypgnienhCX+a9eu1VVXXdXtczfffLOk9iQ/MzMz+GepfZn+kTIzM3XgwIFOj7W0tMjtdgefP/KEQUtLi/Ly8vSvf/1La9as0S9/+cujOp79+xu54h9HaWlO5eVlqaHBo7a2nrs9AH0Z8xypgHmOVMA8RypgnidGQUGOUVzCEv9TTz1VH3/8cbfPVVVV6YEHHlB1dbWGDx8u6fDy/0GDBnWJHzJkiLZu3drpsZqamuDy/iFDhqimpqbL8+PGjdOyZcu0d+9effGLX5Qk+Xw+tba2atKkSXriiSc61QYIxe+35Pdb4QMRVW1tfvl8fLDA3pjnSAXMc6QC5jlSAfM8OSXlDRhDhgzRsGHDVF5eHnysvLxcw4YN63KvviSVlJRow4YN8nq9neJLSkqCz3fclsfj0caNG1VSUqKf/vSneu211/TKK6/olVde0U033aTBgwfrlVde0YQJE2J4lAAAAAAAxF5SFveTpMsvv1wPPvighg4dKkl66KGHdM011wSf379/vzIzM5WTk6OpU6fqmGOO0W233abvf//7+tvf/qZ169bp/vvvlyRdcsklWrRokRYsWKCvfOUrmj9/voYPH65TTz1VDodDhYWFwe0WFhYqPT1dxx9/fHwPGAAAAACAGEjKK/6SNGfOHM2YMUM33nijfvjDH+rCCy/U7Nmzg89feumlevLJJyVJaWlp+t///V9VV1fr4osv1quvvqr58+dr2LBhkqThw4frkUce0UsvvaRLL71UBw4c0Pz58ynGBwAAAACwPYdlWdyYHgXV1QcTPYSUkp7uVEFBjurqGrmHCLbFPEcqYJ4jFTDPkQqY54kxaFCuUVzSXvEHAAAAAABHj8QfAAAAAAAbI/EHAAAAAMDGSPwBAAAAALAxEn8AAAAAAGyMxB8AAAAAABsj8QcAAAAAwMZI/AEAAAAAsDESfwAAAAAAbIzEHwAAAAAAGyPxBwAAAADAxkj8AQAAAACwMRJ/AAAAAABsjMQfAAAAAAAbI/EHAAAAAMDGSPwBAAAAALAxEn8AAAAAAGyMxB8AAAAAABsj8QcAAAAAwMZI/AEAAAAAsDESfwAAAAAAbIzEHwAAAAAAGyPxBwAAAADAxkj8AQAAAACwMRJ/AAAAAABsjMQfAAAAAAAbI/EHAAAAAMDGSPwBAAAAALAxEn8AAAAAAGyMxB8AAAAAABsj8QcAAAAAwMZI/AEAAAAAsDESfwAAAAAAbIzEHwAAAAAAGyPxBwAAAADAxkj8AQAAAACwMRJ/AAAAAABsjMQfAAAAAAAbI/EHAAAAAMDGSPwBAAAAALAxEn8AAAAAAGyMxB8AAAAAABsj8QcAAAAAwMZI/AEAAAAAsDESfwAAAAAAbIzEHwAAAAAAGyPxBwAAAADAxkj8AQAAAACwMRJ/AAAAAABsjMQfAAAAAAAbI/EHAAAAAMDGSPwBAAAAALAxEn8AAAAAAGyMxB8AAAAAABsj8QcAAAAAwMYclmVZiR4EAAAAAACIDa74AwAAAABgYyT+AAAAAADYGIk/AAAAAAA2RuIPAAAAAICNkfgDAAAAAGBjJP4AAAAAANgYiT8AAAAAADZG4g8AAAAAgI2R+AMAAAAAYGMk/kgalmXpwQcf1GmnnaapU6dq3rx58vv9PcZXVlZq9uzZmjhxombMmKF33nmn0/MrV67UBRdcoJKSEl111VWqrKzsdjsLFy7UWWedFdVjAXoSz3ne0tKiX//61zrjjDM0ZcoU3XDDDdq7d2/Mjg2pq7m5WbfffrtKS0s1ffp0Pfnkkz3Gbty4Ud/4xjdUUlKiSy65RBUVFZ2eX7p0qc455xyVlJTohhtu0P79+4PPRfr+AaIpXvO8oaFBc+fO1emnn67TTjtNt956qxoaGmJ2XMCR4jXXO7rrrrv07W9/O6rHgc5I/JE0Fi9erKVLl+rRRx/Vww8/rD//+c9avHhxt7GWZemGG27QwIED9dJLL+nCCy/UjTfeqN27d0uSdu/erRtuuEEXX3yx/vCHP2jAgAH6/ve/L8uyOm2nsrJSjz76aMyPDQiI5zx/+OGH9dZbb+nBBx/Uc889J5/PpxtvvLHL+wA4WvPmzVNFRYWeeuop3XnnnXr00Uf1+uuvd4lramrS9773PZWWlurll1/WpEmTdN1116mpqUmStG7dOs2dO1c33nijXnjhBTU0NOi2224L/vtI3j9AtMVrnt95553atGmTFixYoEWLFmnbtm36r//6r7gdJxCvuR7wwQcf6Lnnnov5caU8C0gSX/7yl62XXnop+PdXXnnF+spXvtJt7MqVK62JEydajY2Nwceuvvpq6+GHH7Ysy7J+85vfWFdeeWXwuaamJmvSpEnWqlWrOm3nO9/5jnXZZZf1uB8g2uI5z08//XTrtddeCz5fVVVlnXTSSdaOHTuieUhIcY2NjVZxcXGnz9f58+d3mpsBL774onXWWWdZfr/fsizL8vv9VllZWfA9cfPNN1s/+9nPgvG7d++2xo4da3322WeWZUX2/gGiKV7zvLGx0Ro3bpy1Zs2a4PMffPCBNW7cOMvr9cbq8ICgeH6mW5ZlNTc3WzNnzrS+9a1vdbsPRA9X/JEUqqqqtGfPHk2ZMiX42OTJk7Vr1y7t27evS/zatWt18sknKzs7u1P8mjVrgs+XlpYGn8vKytL48eODz0vSK6+8Io/Ho0svvTT6BwR0I57z3O/364EHHtDpp5/eZbsHDx6M4lEh1W3atEk+n0+TJk0KPjZ58mStXbu2yzL8tWvXavLkyXI4HJIkh8OhU045pcc5fcwxx2jYsGFau3ZtxO8fIJriNc+dTqcee+wxjRs3rtM229ra1NjYGKOjAw6L11wPWLBggcaOHatp06bF8KggsdQfSaK6ulqSNHjw4OBjAwcOlKRu70murq7uFCtJhYWFwdhwz+/fv18PPvig7r777uCHFRBr8ZznTqdTp59+uvr37x987umnn1ZBQYHGjh0bleMBpPZ5WFBQoIyMjOBjAwcOVHNzsw4cONAlNtSc3rdvX4/PR/r+AaIpXvPc7XbrjDPO6LSfp59+WmPHjtWAAQOifFRAV/Ga65K0bds2Pffcc90u/0f0pSd6AEgdXq9XVVVV3T4XuBeo44dM4M8tLS1d4j0eT6fYQHwgNtzz9913ny666CKNGTNG69ev7+URAV0l0zzv6K233tKTTz6pu+66q8u/AY5GT/NQ6jqvw81Zr9fb4/Ner7fTtkPtB4i2eM3zIz3zzDP6y1/+ooULFx71MQAm4jXXLcvSHXfcoR/84AfBk7iILRJ/xM3atWt11VVXdfvczTffLKn9AyUzMzP4Z6l9+fKRMjMzu5x1bGlpkdvtDj5/5IdTS0uL8vLy9K9//Utr1qzRL3/5y6M6HqA7yTLPO3rrrbf0ox/9SFdeeaW+8Y1vRH5QQAg9zUNJwbkaLjbcnM7Kyur0xdPk/QNEU7zmeUfPPvusfvnLX+q2227T9OnTo3IcQDjxmusvvPCC2tra9K1vfSvah4AekPgjbk499VR9/PHH3T5XVVWlBx54QNXV1Ro+fLikw8uiBw0a1CV+yJAh2rp1a6fHampqgsuJhgwZopqami7Pjxs3TsuWLdPevXv1xS9+UZLk8/nU2tqqSZMm6Yknnuh0LxIQqWSZ5wGvvfaabrnlFl122WW6/fbbe39gQA+GDBmiuro6+Xw+pae3f62orq6W2+3uchKqpzkbbk4PGjRIQ4YMCW7b5P0DRFO85nnAokWLNG/ePN1yyy26+uqrY3FIQLfiNddfeOEFVVRU6JRTTpEktba2qq2tTZMmTdJrr72mYcOGxeoQUxb3+CMpDBkyRMOGDVN5eXnwsfLycg0bNqzLvUGSVFJSog0bNgSXfgbiS0pKgs933JbH49HGjRtVUlKin/70p3rttdf0yiuv6JVXXtFNN92kwYMH65VXXtGECRNieJRIdfGc55L07rvv6pZbbtEVV1yhn//857E6LKS4cePGKT09vVPx1PLychUXF8vp7Pw1o6SkRB9++GGwpaRlWfrggw96nNN79uzRnj17VFJSEvH7B4imeM1zSfrjH/+oefPm6bbbbtOcOXNifGRAZ/Ga6w8++GCn7+OXXXaZJkyYoFdeeYXP9FhJYEcBoJPHH3/cmj59urVq1Spr1apV1vTp060nn3wy+Hxtba116NAhy7Isy+fzWTNmzLB+9KMfWZs3b7Yef/xxa+LEidauXbssy7KsyspKq7i42Hr88cetzZs3Wz/84Q+tr33ta8F2Ix299NJLtINC3MRrnre2tlpnnnmmdfXVV1v79u3r9Ku5uTkhxw77+vnPf27NnDnTWrt2rbV8+XLrlFNOsd544w3Lsixr3759lsfjsSzLsg4ePGiddtpp1j333GNt2bLFuueee6xp06YFW1Z+8MEH1vjx463f//731kcffWRdeeWV1nXXXRfcT7j3DxBL8ZjndXV11sSJE62f/exnXT67fT5fYg4cKSden+kdPfzww7TzizESfyQNn89n3XfffVZpaal16qmnWg888ECnRP0rX/lKsH+5ZVnWJ598Yl1xxRXWhAkTrJkzZ1orVqzotL2///3v1rnnnmt94QtfsK6++upOPUM7IvFHPMVrnn/44YfWSSed1O2vjr15gWhoamqybrnlFmvixInW9OnTrcWLFwefO+mkk4I9nS3LstauXWvNmjXLKi4uti699FJrw4YNnbb10ksvWV/+8petiRMnWjfccIO1f//+4HPh3j9ALMVjni9durTHz+7Kysq4HCcQr8/0jkj8Y89hWZ+vzQAAAAAAALbDPf4AAAAAANgYiT8AAAAAADZG4g8AAAAAgI2R+AMAAAAAYGMk/gAAAAAA2BiJPwAAAAAANkbiDwAAAACAjZH4AwBgI2eddZYeeeSRuO3v008/1cSJE7Vz586QcbfeeqvGjh3b6df48eM1ffp03Xzzzdq/f39E+y0vL9fq1auPZugAAKQMEn8AANAr27Zt0zXXXCOPx2MUP2nSJL3zzjvBX6+//rpuueUW/e1vf9PPfvaziPb9H//xH/rss896M2wAAFJOeqIHAAAA+p7HH39cjz32mEaOHBn2an+Ay+XSoEGDOj02YsQIffbZZ3rkkUd08OBB5ebmxmK4AACkNK74AwCQQlpaWvTrX/9aZ511liZMmKCpU6fqhz/8Yael9p999pm++93vatKkSfrSl76kxYsXq6ysTC+//HIw5q233tL9998f8ZX67mRmZsrhcCgtLU2SZFmWnnjiCZ199tkqKSnRhRdeqFdffTUYP3bsWEnSbbfdpltvvVU7d+7U2LFj9e9//zsYc+Rjt956q2666SZdc801OuWUU/TEE0/okUce0ezZs7VgwQKdccYZKi4u1pVXXqlt27YFt/OPf/xDF198sUpKSvTFL35Rt956q+rr64/6mAEAiCcSfwAAUsi8efP05ptv6le/+pXeeOMN/epXv9KqVav0f//3f5Ikj8ej2bNny+/367nnntP/+3//Ty+//LIqKys7befFF1/Ueeedd1RjsSxLH3zwgZ566imde+65ys7OliT9v//3//Tcc8/p5z//uf785z/rqquu0i9+8Qs9++yzkqR33nlHknT77bdr7ty5xvt74403dPrpp+ull17SBRdcIElavXq1ysvLtWDBAv3ud79TbW2t7rrrLknS/v37deONN+qSSy7RsmXL9Oijj+r999/XvHnzjuq4AQCIN5b6AwCQQoqLi3XeeeeptLRUknTsscfq9NNP1+bNmyVJy5Yt0/79+/Xyyy+rf//+kqQHHnhAF1544VHve/Xq1Zo0aVLw783NzRowYIBmzJihH/3oR5KkpqYmLVmyRP/93/+tM888U5J03HHHadeuXVq0aJGuuOKK4O0Cubm5ys3NNb4Cn5+fr2uvvbbTYz6fT/PmzVN+fr4k6bLLLtMDDzwgSaqqqlJLS4uGDRumY489Vscee6wee+wxtbW1Hc3LAABA3JH4AwCQQi688EKtXLlSDz74oD755BNt375dO3bsCJ4I2Lhxo0aOHBlM+iWpqKgoKvfeT5gwQQ8++KCk9sKA99xzj4qKivTDH/4weLV/69atam5u1k9+8hM5nYcXJvp8PrW0tMjr9crtdvdq/8cff3yXxwYOHBhM+qX2kwmtra2SpHHjxumCCy7Q9ddfr0GDBmnatGk688wzVVZW1qv9AwCQKCT+AACkkDvuuENvvPGGZs2apbPOOks33HCDFi1apKqqKklSWlqa/H5/TPbt/v/buX+Q1Ls4juMfI8PCCJeihBRrKBqiGm5BNDQXQpBEY4MFQUNY4BCFhER/IDHISAehpOZAWopyiBobbLOUIigIhYJ06pmuEE/wXJ7i/vG+X/BbDpzz+/7Gz/me3zGZiuHbZrOpsbFRw8PDmp6eVigUksFg0NvbmyRpfX1dDofjX2tUVFT80Ls+6sp/tGHwX+utra1pcnJSiURCZ2dnmpmZUVdXl6LR6A/VAQDA74B//AEA+Etks1nt7+9rfn5eXq9XQ0NDam1t1fX1dTFwt7S0KJPJKJfLFeelUik9Pz9/eT3Nzc3yeDw6OTnR3t6eJMnhcKi8vFz39/ey2WzF5/T0VJFI5N0pgO+MRqMk6eXlpTiWTqc/Xd/l5aX8fr8cDkfxEkC/36/z83M9PT19en0AAH4WOv4AAJSYTCajRCLxbsxkMqmjo0PV1dU6OjpSW1ub8vm8dnZ2lEwm1d7eLkkaGBhQMBiUx+ORx+NRPp+Xz+eTJBkMhi+vdXR0VPF4XKurq+rv71ddXZ1GRkYUCARkNpvV2dmpi4sLraysaHx8vDivqqpKqVRK2WxWtbW1slqtikajstvtyuVyCgQCn67XbDYrFovJaDTK5XKpUCgoHo/LbrfLYrF89tMBAPhpCP4AAJSYg4MDHRwcvBuzWq06Pj5WIBDQ0tKSBgcHVVNTo2/fvml6elpbW1t6fX1VZWWlwuGwfD6fXC6XampqNDExoWQyWeysfyWDwaDFxUU5nU4tLCxoc3NTXq9XFotFgUBAj4+Pqq+v19TU1LuL+cbGxhQOh5VKpRQKhbS8vCy/3y+n0ymbzSav1yu32/2p2pqamhQMBrWxsaFYLKaysjJ1d3dre3v7w5MHAAD8rgxv38/2AQCAv97d3Z3S6bR6e3uLYw8PD+rr69Pu7m7xEkAAAPDnYLsaAAAUFQoFud1uRSIR3d7e6urqSnNzc7Lb7cXfAQAAwJ+Fjj8AAHjn8PBQoVBINzc3MplM6unp0ezsrBoaGn51aQAA4H8g+AMAAAAAUMI46g8AAAAAQAkj+AMAAAAAUMII/gAAAAAAlDCCPwAAAAAAJYzgDwAAAABACSP4AwAAAABQwgj+AAAAAACUMII/AAAAAAAljOAPAAAAAEAJ+wfLA/C/zW4/mAAAAABJRU5ErkJggg=="
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 52
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-20T07:08:00.287340Z",
     "start_time": "2024-08-20T07:08:00.095696Z"
    }
   },
   "cell_type": "code",
   "source": [
    "df[['returns', 'pred']].plot(figsize=(12,8))\n",
    "plt.show()"
   ],
   "id": "dc86615b444e6739",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ],
      "image/png": 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GjRuHsrIyTJgwwfW//Px8ZGRkYMKECa6RAUREpE3MQ09ERESpTrFpBlevXo3Zs2fjiiuuwB133IEbb7wR5557LgBg+fLlWL9+PQAgJycHjz/+uKsXvqamBk888QSysrIAAAsWLMCdd96Jhx9+GJdccgny8/Nxzz33KPWziIgojpiHnoiIiGiEIEns4wilra3P42+DQYeCgmx0dQ3wGRBSFI/F1JTK+33P4S787rntAIBT5lXgu1+qVLhEiZPK+z2Vcb9TMuHxnLq476NTUpIbchkmAiQiIk3yk02UiIiIKKUwoCciIiIiIiLSIAb0RERERERERBrEgJ6IiIiIiIhIgxjQExGRJnFKVyIiIkp1DOiJiEgzOA8eERER0QgG9EREpBnslCciIiIawYCeiIg0iWnriIiIKNUxoCciIiIiIiLSIAb0RERERERERBrEgJ6IiIiIiIhIgxjQExEREREREWkQA3oiItIk5qEnIiKiVMeAnoiINIMT2xMRERGNYEBPRESawU55IiIiohEM6ImISJOYh56IiIhSHQN6IiIiIiIiIg1iQE9ERERERESkQQzoiYiIiIiIiDSIAT0REWkS09YRERFRqmNAT0REmsF58IiIiIhGMKAnIiIiIiIi0iAG9EREpBkcZU9EREQ0ggE9ERFpEvPQExERUapjQE9ERERERESkQQzoiYiIiIiIiDSIAT0RERERERGRBjGgJyIiTWIeeiIiIkp1DOiJiEgzOA8eERER0QgG9EREREREREQaxICeiIg0g6PsiYiIiEYwoCciIk1iHnoiIiJKdQzoiYiIiIiIiDSIAT0RERERERGRBjGgJyIiTWLaOiIiIkp1DOiJiEgz+Ng8ERER0QgG9EREREREREQaxICeiIiIiIiISIMY0BMRkWbwsXkiIiKiEQzoiYhIk5iHnoiIiFIdA3oiIiIiIiIiDWJAT0RERERERKRBDOiJiEiTmIeeiIiIUh0DeiIi0gw+Nk9EREQ0ggE9ERERERERkQYxoCciIiIiIiLSIAb0RESkGXxsnoiIiGgEA3oiItIk5qEnIiKiVMeAnoiIiIiIiEiDGNATEZEmMW0dERERpToG9EREpBkcZU9EREQ0ggE9ERERERERkQYxoCciIiIiIiLSIAb0RESkGXxsnoiIiGgEA3oiItIkpq0jIiKiVMeAnoiIiIiIiEiDGNATERERERERaRADeiIi0iTmoSciIqJUx4CeiIg0g4/NExEREY1gQE9ERERERESkQYoF9GazGbfeeisWL16M5cuXY926dQGX3b17Ny6++GJUVVXhoosuQm1trcf7r7/+Os4++2xUVVXh+uuvR2dnp+u9jo4O/PCHP8SiRYtw8skn43e/+x1sNlvcfhcRERERERFRIigW0K9duxa1tbV4+umncdttt+Ghhx7CW2+95bPc4OAgrrnmGixevBgvv/wyFixYgGuvvRaDg4MAgJ07d2LNmjW44YYb8MILL6C3txerV692ff6mm25Cf38/XnjhBTzwwAN444038Je//CVhv5OIiOTDx+aJiIiIRhiU+NLBwUG89NJLePLJJzF79mzMnj0b+/fvx7PPPosVK1Z4LLt+/Xqkp6fj5ptvhiAIWLNmDTZs2IC33noLq1atwjPPPIPzzz8fK1euBOC4UXDGGWegsbERZWVlKCoqwo033ogJEyYAAM477zxUV1cn+icTEZHMmIeeiIiIUp0iPfR1dXWw2WxYsGCB67VFixahpqYGoih6LFtTU4NFixZBGG65CYKAhQsXYseOHa73Fy9e7Fq+oqICo0ePRk1NDYxGI+6//35XML9//368//77WLp0aZx/IREREREREVF8KdJD39bWhoKCAhiNRtdrxcXFMJvN6O7uRmFhoceyU6dO9fh8UVER9u/fDwBobW1FaWmpz/vNzc0er1122WXYsmULZs+ejUsvvTSi8up0AnS6ka4gvV7n8V8ipfBYTE2pvN/1+pG6WBAEGAypsw1Seb+nMu53SiY8nlMX9338KBLQm0wmj2AegOtvi8US1rLO5YaGhoK+7/TLX/4SPT09+M1vfoOf/vSneOyxx8Iub2FhtmuEgLu8vMyw10EUTzwWU1Mq7vfcjkHXv41GAwoKshUsjTJScb8T9zslFx7PqYv7Xn6KBPTp6ek+Abfz74yMjLCWdS4X6P3MTM+DZebMmQCA3/72t/j617+Oo0ePYuzYsWGVt7NzwKeHPi8vE729JtjtYpBPEsUXj8XUlMr7vb9vyPVvi8WGrq4BBUuTWKm831MZ9zslEx7PqYv7PjrhdFwoEtCXlZWhq6sLNpsNBoOjCG1tbcjIyEBeXp7Psu3t7R6vtbe3u4bZB3q/pKQE/f392LBhA1asWAGdzjG8wzl8v6urK+yAXhQliKLv3Mp2uwibjQckKY/HYmpKxf1ut4/UxaIopdzvB1JzvxP3OyUXHs+pi/tefoo8xFBZWQmDweCa2A4AqqurMXfuXFfg7VRVVYXt27dDkhyNOEmSsG3bNlRVVbned5+1vqmpCU1NTaiqqoLJZMJPfvIT1NTUuN7ftWsX9Ho9Jk2aFMdfSERERERERBRfigT0mZmZWLlyJW6//Xbs3LkT7777LtatW4fLL78cgKO3fmjIMaxyxYoV6O3txd13340DBw7g7rvvhslkwvnnnw8AuOSSS/Dqq6/ipZdeQl1dHW6++WacfvrpGDduHEpKSnDuuefirrvuwu7du7F161asWbMGl112GXJycpT46UREFAPmoSciIiIaodg0g6tXr8bs2bNxxRVX4I477sCNN96Ic889FwCwfPlyrF+/HgCQk5ODxx9/HNXV1Vi1ahVqamrwxBNPICsrCwCwYMEC3HnnnXj44YdxySWXID8/H/fcc4/re377299ixowZ+O53v4vrr78ep59+Om666abE/2AiIpIV89ATERFRqhMk51h2Cqitrc/jb4NBh4KCbHR1DfAZEFIUj8XUlMr7fc/hLvzuue0AgFOrKvCd8ysVLlHipPJ+T2Xc75RMeDynLu776JSU5IZchokAiYhIk3g7moiIiFIdA3oiItIMjrInIiIiGsGAnoiIiIiIiEiDGNATERERERERaRADeiIiIiIiSjpWm4gd+9vRN2hRuihEcWNQugBERETh4jx4REQUrpc+OIB3q4+iOD8Da7+/TOniEMUFe+iJiEiTmIeeiIiCebf6KACgvWdI4ZIQxQ8DeiIiIiIiIiINYkBPRESaxDz0RERElOoY0BMRkWZwlD0RERHRCAb0RERERERERBrEgJ6IiIiIiIhIgxjQExEREREREWkQA3oiItIMzoNHRERENIIBPRERaRLz0BMREVGqY0BPRESaxLR1RERElOoY0BMRkWawU56IiIhoBAN6IiIiIiIiIg1iQE9ERERERESkQQzoiYiIiIiIiDSIAT0RERERERGRBjGgJyIizeDE9kREREQjGNATEZEmMQ89ERERpToG9EREpEnMQ09ERESpjgE9ERFpBjvliYiIiEYwoCciIiIioqQmcVgXJSkG9ERERERElNQYzlOyYkBPRERERERJjT30lKwY0BMRkWawOUZERNEQRaVLQBQfDOiJiEiTmLaOiIiIUh0DeiKNauoYwK//8jle/uCA0kUhUgRHTxIREVGqY0BPpFHvVx9DQ3MfXvmIAT2lDnbKExEREY1gQE+kUfVNvQAAu53dlERERETBsb1EyYkBPZEG2ewiGlv7lC4GEREREREpiAE9kQY1tvbDxp55IiIiIqKUxoCeSIMODQ+3d2BgT0RERBQMJ1KlZMWAnkiDDh3vDb0QURJie4yIiIhoBAN6Ig2qb2JAT8Q89ERERJTqGNATaYzJbENzx6DSxSBSHIdPEhERUapjQE+kMQ3NfR7DjhnUUCphpzwREUWDzSVKVgzoiTTmEIfbExERERERGNATaQ4nxCMiIiIiIoABPZHmcEI8IiIiIiICGNATaUp3vxldfWYAQGFeOgA+E0ZEREQUEhtMlKQY0BNpiPvz85PK8xQsCZEy2B4jIiIiGsGAnkhDnAG9MU2HiuJshUtDRERERERKYkBPpCHOCfEmluVCr2MCL0o9POqJiCgaEsd4UZJiQE+kEZIk4VBTHwBg0ui8kcCGieiJiIiIiFISA3oijWjtMmHQbAMATKrg8/NERERERKmOAT2RRrinq2NAT0REREREDOiJNML5/HxOZhqK8zMULg0RERGRdvAJRUpWDOiJNMI5w/3k0XkQhJGpwXh9IiIiIiJKTQzoiTTAZhdxuKUfgNtwew1P9y1JEp5/bz/+8fZeiLxlThHg0UJEREQ0wqB0AYgotGNtA7DZRQDApIpchUsTu10NnXh7SyMAYOb4AiyZWapwiYiIiIiItIc99EQa4D4h3sQkmBCvo2fI9e+2bpOCJSGt0fDAFCIiIiLZMaAn0gDnhHjF+RnIyzJ6vMcR60REREREqYkBPZEGHGoemRDPScs9lbwHQUREREQUOwb0RCpnMttwvG0AADCxXPvD7YmIiIgSjSMaKVkxoCdSuSMtfa4ebfceeiIiIiIiSm0M6IlUzjkhniAAE8r8zXCv7VvOWn50gIiIiIhISYoF9GazGbfeeisWL16M5cuXY926dQGX3b17Ny6++GJUVVXhoosuQm1trcf7r7/+Os4++2xUVVXh+uuvR2dnp+u93t5erFmzBsuWLcOJJ56IW265Bb29vd5fQaRah5r6AABjinOQbtSPvCEwFCYiIiIiSmWKBfRr165FbW0tnn76adx222146KGH8NZbb/ksNzg4iGuuuQaLFy/Gyy+/jAULFuDaa6/F4OAgAGDnzp1Ys2YNbrjhBrzwwgvo7e3F6tWrXZ+/7bbbUFdXhyeeeAJPPfUUDh48iF/+8pcJ+51EsXLOcD95tPbzz7toe1ABERERaQ4bH5ScDEp86eDgIF566SU8+eSTmD17NmbPno39+/fj2WefxYoVKzyWXb9+PdLT03HzzTdDEASsWbMGGzZswFtvvYVVq1bhmWeewfnnn4+VK1cCcNwoOOOMM9DY2IiioiL873//w3PPPYc5c+YAAG699VZceumlMJvNSE9PT/RPJ4pIz4AFHb2OnO3JkH+eiIiIiIjko0gPfV1dHWw2GxYsWOB6bdGiRaipqYEoih7L1tTUYNGiRRCGhxcLgoCFCxdix44drvcXL17sWr6iogKjR49GTU0NdDodHnvsMVRWVnqs0263Y2BgIE6/jkg+h5pGHg+ZHCCg1+SsrXxagIiIiIgoZor00Le1taGgoABGo9H1WnFxMcxmM7q7u1FYWOix7NSpUz0+X1RUhP379wMAWltbUVpa6vN+c3MzMjIycOqpp3q89/e//x0zZszw+I5QdDoBOt1IBKLX6zz+SxQvh5sdz88bDTqML8+Fwe2Y0/s5JrVC5/b8v04nwGDQVvmVlsp1kF6fusdOKu/3VMb9TslEyeNZr9el1DVDbViXxY8iAb3JZPII5gG4/rZYLGEt61xuaGgo6PvunnnmGbz55pv4y1/+ElF5CwuzXSME3OXlZUa0HqJINbY7RpJMGTsKJcWez9BnZo4c91o7FrOyRx53ycoyoqAgW8HSaJfW9rsccjtMrn8bjYaUPHZScb8T9zslFyWO51GjspCTZQy9IMUV6zL5KRLQp6en+wTczr8zMjLCWta5XKD3MzM9D5Znn30Wv/nNb7B69WosX748ovJ2dg749NDn5WWit9cEu10M8kmi6EmShL2HuwAA40uz0dXl+ZiIyTRy3GvtWBwcMI/8e9Di89souFSug/r6RgJ6i8WWUsdOKu/3VMb9TslEyeO5u3sQVrM1od8pl6aOAbz52RGcNn80pozJV7o4UWFdFp1wOi4UCejLysrQ1dUFm80Gg8FRhLa2NmRkZCAvL89n2fb2do/X2tvbXcPsA71fUlLi+vupp57C2rVrcfPNN+OKK66IuLyiKEEUfR9UtttF2Gw8ICk+WrsGMWByXHgmlOf6HGvOY1KC9o5F9/NJFCVNlV1NtLbf5WC389hJxf1O3O+UXJQ4nm0aPod+8/RW9A1a8eH2Y1h3y5lKFycmrMvkp8hDDJWVlTAYDK6J7QCguroac+fOhU7nWaSqqips374d0vDMX5IkYdu2baiqqnK9X11d7Vq+qakJTU1NrvdfeeUVrF27FqtXr8ZVV10V519GJJ/6EBPiJU0a+mT5HURERKRampxEeFjfoDZHFlBiKBLQZ2ZmYuXKlbj99tuxc+dOvPvuu1i3bh0uv/xyAI7e+qEhR6quFStWoLe3F3fffTcOHDiAu+++GyaTCeeffz4A4JJLLsGrr76Kl156CXV1dbj55ptx+umnY9y4ceju7sadd96Jr33ta7jgggvQ1tbm+p/dblfip5MGbNzZhJ89/Am272tTtBwNTY4J8bIzDCgZlVzPG2n4mkpEREREpBqKTTO4evVqzJ49G1dccQXuuOMO3HjjjTj33HMBAMuXL8f69esBADk5OXj88cdRXV2NVatWoaamBk888QSysrIAAAsWLMCdd96Jhx9+GJdccgny8/Nxzz33AAA++eQTDA4O4pVXXsHy5cs9/tfU1KTMDyfVW7d+D7r6zPjzy18oWg5nD/2kijy/kzISEREREVFqU+QZesDRS3/ffffhvvvu83lv7969Hn/PmzcPr7zySsB1rVq1CqtWrfJ5/YILLsAFF1wQe2GJEsxmF3FkOGXdpAD55520OISMtyeIiIiIiGLHRIBEKnS8fQCW4QlDJo0OHtBrkQbvQRARERERqQ4DeiIVOuQ2IV6oHnqtE9hfT0REREQUFQb0RCrkDOiL8jKQn21UuDTxJbG/noiIiIgoKgzoiVSo/rjz+fnc0Atr8SF6IiIiogSS2F6iJMWAnkhlzBY7jrX3Awj+/HyyzHzPIfdERERERNFhQE+kModb+lyd7pOT/Pl5IiIiIiKKHgN6IpVxPj8vCMCE8jCG3GsRh70REREREcWMAT2RyjgD+tFF2cgwGkIuz9CYiIiIKDi2lyhZMaAnUpn6446APlS6Ok0/eZ4kz/8TERERESmJAT2RivQOWtDeMwQg+IR4msch90RJjzNKExERxR8DeiIVaWjqc/2bE+IRkVb97c06/OzhT9DUMaB0UYiIHHiPkZIUA3oiFXE+P2/Q6zCmJDusz2ixE0yDRSaiCGyoOY7ufgueeG230kUhIiJKagzoiVTEGdBPKMuBQR/i9ORj6ESkcr2DFqWLQERElNQY0BOphCRJYU+Ip3W8F0FEREREFDsG9EQq0dEzhH6TFUCST4gHDrknIiKixGLbg5IVA3oilagfHm4PRDohHi9RRERERESpiAE9kUo4n5/PSjegtCAz5PICB64TkcoxdR0REVF8MaAnUolDrufncyEIDNaJSPsYzhORavAGIyUpBvREKmAXRTS0OHLQJ/vz895474KixaYZERERpToG9EQq0NQ+CItVBBD5DPe84UxERERElJoY0BOpgPuEeMmeso5ILhzcoU58bp6IiChxGNATqYBzQryC3HSMyklXuDRERDJhbE9EKsHqiJIVA3oiFXBOiBdZujrtYgceUfLi6U1ERJQ4DOiJFGax2nG0bQBAdBPiab3xzGHTRERERETRYUBPpLAjLf0Qh7usI3l+Pllmh9f6DQki8sKTmoiIKGEY0BMpzDkhngBgYnmusoUhIpIRY3siUotkedxvYMiqdBFIZRjQEynMOSFeeVEWMtMNCpcm8ZJkoAEpIEnaZsktWVrQCvrb+j34wdr30NI5qHRRiEgFfvfcdqWLQCrDgJ5IYTFPiMcGMxGpiMRbLbJp6hjA+9uOobGlHzsPdihdHCJSgSMt/UoXgVSGAT2RgvpNVrR2mwBEPiEee7Yp1fEcoGS3eU+r698ib94SEZEfDOiJFNQwPNweiGxCPCIitWLcKQ9JkrB5T4vb3woWhoiIVIsBPZGCnBPiGfQCxpbkKFwaIiJ5MQaN3rG2ATR18Ll5IiIKjgE9kYKcz8+PK81FmiG605ENZiKi5LO5rsXrFdb2RETkiwE9kUIkScKh5j4AUU6IlyyJ6ImIyINjuH1r6AWJKGwSn1uhJMWAnkghnb1m9A5YAACTRqdW/nleVEkOPIrUj6d6dI609KO1y+TxGrclERH5w4CeSCGHOCGeA0caUAR4uKgfA8/YOSfD0+t4wBPJ5eUN9UoXgSguGNCT5omihC/qO9DZO6R0USLinBAvM12PssKsqNfj3ni22UX84YUdePiVL+LWC97ebcIL7+9HY2v0eVAFRmUUJQaLlOwkScKWOsdw+7mTi6BjfUkki021zUoXgSguGNCT5n2w/Rj++GINbnpkk9JFiYgzZd3E8ryoGmz+PvFxzXHUHupE9d42fFHfEWMJ/bvvn9vxv82NuG3d5qjXwSH3JAeGOWrF8zsW9U29aO9x3KBeUlmqcGmIiEjtGNCT5r284aDSRYiYKLpNiDdavuH2PcPP5APAgMkm23rddWhsJAQRkZZsGZ4ML82gw/ypxa7HTHgflIiI/GFAT6SApo4BmC12AI4eeiKiZMHAM3qi23D7eZOLkJluULhERESkdgzoiRRQ7zYhnpw99EREpF0Hjvagq88MwHe4vcRHGYiIyA8G9EQKONTkGG4/KseIgtz06FaSJA8QJ8nPICI/OF9GZJzD7Y1pOlRNKfZ8k5uSiNywfiUnjuUiUoAzZV1Kp6sbxssRRYvHjjpxv0RHFCVs3esI6KumFCPdqAfAVI1E5OtQUy8eevkLWG0isjMM+O6XKjF93Cili0UKYQ89aZ7WblBabXYcHU75xuH2RJFhcEPJam9jt2ti06V+ZrfX2KWOUtTOgx14+OUv0NQxoHRRktofX6xBV58Z/SYrWrpMuPfZbUoXiRTEHnqiBDvS0g+76GiaTZSph97fsCutPG/J+IwiobUbeCmJ+ygqW/a0AADSjXrMnVzkel2AAG5U0oo/vVQDANh/rAd/unG5wqVJXv0mq9JFIBVhDz1pntZ67NwnxJtUnhv1evz9bEEjG4NNU5KDNo52otDsooite9sAAAumFcOYpvdZhjezSEt63dLoUuyMaQzZKDAeHaR5WmvkNAwH9OWFWcjKSFO4NERE8tLK6CA12XO4y9XjtnRmmeebvHNFRERBMKAnSrD64RnuOSEeESU7rd1wVcrm4dntM9MNmD2pMMBS3JhEqUrgnT0KggE9UQINDFnR0jkIAJhUEf1we29s5hGRWjCIj4zNLmLb8HD7hdOLkWbwbJqxGU9ERMEwoCdKoIbh3nkAmBTjDPehnpfXTKOarVWKklYOcaJgdh3qxKDZBgBYWlkWcDnN1OlEJDs+ykTBMKAnSiBn/nm9TsD40hzZ18/YmJKd+32sti6TcgWhsLAJGppzuH1OZhoqJxT4LsCKnYiIgmBAT5RAzoB+XGkO0gy+sxinAkmSUFvfqXQxSKPceyn3NnajvZtBPWmX1WbH9v3O4fYlMOjZLKPofLzzOJ56YzcGhpjOLBnxGXoKhlcOogSRJAn1xx0BvewT4mmoG2zXoU58Ud+hdDEoSXy6u0XpIlBQGqqcFPBFfSeGLHYAwNLKUr/LsCFPoUiShL+ur8MnXzTj+ff2K10cIkowBvSUVCQVP2TY1WdGz3Be1lSe4f6T2mali0BEcaTialh1Nu9x3JDKy0rDjPGj/C7jfMxEzdc3Uo+9R7qVLgLFAZ+hp2AY0BMliHO4PRD7hHhERKRtZqsdNQcco5UWzSyFXscmGUWHoR5RauPVg5KKmi9qh4ZnuM8w6lFRmBWfL9HAyEz2MhElO57j4dh5sANm6/Bw+5n+h9u741YlSl189IaCYUBPlCDOHvqJ5bnQ6eStmDkUi4jUiPfvAnMOtx+VY8S0caOULQwlDZ5zRKmHAT0lF5VeyERJcgX0cj0/HyINvWYkyc8gIgqbyWzDzoOO4faLZ5ZCF6RCd72l0usbqYAU8A8iSgEM6CmpqLWnurlj0DWTcSpPiEcUq2S5kZXM1FkLq0vNgXZYbSIAYGllmcKloWSi1vOPj9uF70hLH9at34MjLX1KF4U0ggF9kusdsMBktildjJTnPiHe5ARNiMdrJyUjHtfawt3l3+Y9rQCAorx0TAlxTXA+O8ttSYGotTMDcIxQXPvPbbj1yc8xOMT2aDhu/+sWbNzZhNv/ukXpopBGMKBPYh09Q/jJQxtxy+OfwmqzK12cuHG/jKm1se8M6POzjSjITVe4NMpS6z4iInnwHA9ucMiK2kOO4fZLZpZB4LATkpHazr8DR3tQd6QbLZ2DWP/ZYaWLQ5SUGNAnsdc/bYAkAX2DVuxr7FG6OCnN/fl5uRpv7mtR2wWciIj8276/HTa7o9JeUhl6dnswDz1pmMWtQ4kjRoniQ7GA3mw249Zbb8XixYuxfPlyrFu3LuCyu3fvxsUXX4yqqipcdNFFqK2t9Xj/9ddfx9lnn42qqipcf/316Ozs9FmHJEm48sor8fLLL8v+W7RAzcOxkp3VJuJISz8AYFJFbly/yyPIV+k+V2epiIgSwzncvmRUBiaWx/eaQKlB1fd63MvGwShEcaFYQL927VrU1tbi6aefxm233YaHHnoIb731ls9yg4ODuOaaa7B48WK8/PLLWLBgAa699loMDg4CAHbu3Ik1a9bghhtuwAsvvIDe3l6sXr3aYx2iKOI3v/kNPvnkk4T8NlKOGi9qR9v6YRcdBZuUoOfniYhUQYV1spL6TVbsbnB0OiytDG+4PWMgioTaRnIwnieKP0UC+sHBQbz00ktYs2YNZs+ejXPOOQdXX301nn32WZ9l169fj/T0dNx8882YMmUK1qxZg+zsbFfw/8wzz+D888/HypUrMXPmTKxduxYfffQRGhsbAQAtLS244oor8P777yMvj8EUJV798ZEJ8SaW8xhU5V0XIooLtY4UUsq2fW2uG7xLZoYx3J4oQmo743jJJ4o/gxJfWldXB5vNhgULFrheW7RoER577DGIogidbuQ+Q01NDRYtWuS6iy0IAhYuXIgdO3Zg1apVqKmpwfe+9z3X8hUVFRg9ejRqamowbtw47Nq1CxUVFXjggQfw9a9/Pary6nQCdLqR+4p6vc7jv2rlntdWr9PBYFB3eaPlfsdXbxBk/Z1yrKuh2ZF2pKwwC6NknBDP/fjT63UQAM/jNAH7PJr1CzrPe/Q6vbz7LBVopQ6KB73e8/jR61Ln+NHKfvfeR6myf8Kxpc4x3L6iKAuTRoc3p4p7+4fbkvzyOozUcpwYDDqP+kCnExSvx9SybcIVSXnV/tuU3vfJTJGAvq2tDQUFBTAaja7XiouLYTab0d3djcLCQo9lp06d6vH5oqIi7N+/HwDQ2tqK0tJSn/ebm5sBAGeeeSbOPPPMmMpbWJjt96Kbl5cZ03rjzZg+sntzcjNQUJCtYGnix33XjBqVjfQ0vWzrlmObHR7OIzpzQqGs+yAra+T8yc3NRJpBh8zMkdeys41x3+fRrD/Na/9kZ6Un7bEZb+51kCRJaGofQEWx//oqWeR2mDz+zshMS7njR+3XHl3ayLVHEISU2z+BdPeZsWd4uP1pC8ehsDAnrM85T2djuoHbkvyy2kTXv9V0zhUUZCM7eySXekZGmqv+ClWPSZIEQRDQP2hBdmaabNc1tWybcDnLa7aGzlalld+m9muYFikS0JtMJo9gHoDrb4vFEtayzuWGhoaCvi+Hzs4Bnx76vLxM9PaaYLeLQT6pLIvbbKL9fUPo6hpQsDSBHWnpQ362Efk50fVeuw/n6u4agFHGgD7WbTY4ZMPRVseEeGNLsmTdB4ODI8d4X58JAoChIavrtf4Bc9z3eTTrt1o8L0qDgxbVHptq5a8OeumDA/jvJw340kkT8M2zpilcwvjp7fMM6IdM1pQ5frRy7ekdGKmbJElKmf0TynvVRzE82h5VkwvC3i7Oa5x5yMZtSX65B/SSqJ5zrqtrAH39Q66/LWYbentNIeuxD7cfwwvv7cfSWWXYsOM45k8rxo8urpKtTFrS1TXgkSkg1LJqppVrmNqEc6NGkYA+PT3dJ+B2/p2RkRHWss7lAr2fmSnf3R9RlCCKvg8B2e0ibDb1HpCiW6RrF9VZ1r1HunDfP7cDAJ74+ekwRDEMx33PWG2ix6MGsYp1mx082u3694SyXFn3gd3tmLTbRUDyfE20S3Hf59Gs3/tcEsX4lzNZuddB//2kAQCw/tPD+PppUxQsVXzZ7Z7Hjz0Fjx+1X3ts7g01KfZ6NFl8VusYOTimJBtlBVkRbxdRSr1jncLjflxIKjpObDbRo84WRckVyAWrx9a9sQcA8MG2YwCA6r1tsv0mtWybcNlsIszm8AJ6rfw2tV/DtEiRhxjKysrQ1dUFm22kB7mtrQ0ZGRk+E9eVlZWhvb3d47X29nbXMPtA75eUlMSp9CSn/25qcP27q88c+wpVNvlK/XD+eb1OwPjS8IZXhot56IlIlVgf+ejqM2NfYzcAYGmEk+G57lGzoqeAVHxsuBUtmR8HI1KSIgF9ZWUlDAYDduzY4Xqturoac+fO9ZgQDwCqqqqwfft2VxoOSZKwbds2VFVVud6vrq52Ld/U1ISmpibX+0RKOtTkeHZsTEm2rI8CaJmKmx1ERHGxdW+rq+5bWlmmaFkouantGuue6YLxPFF8KBLQZ2ZmYuXKlbj99tuxc+dOvPvuu1i3bh0uv/xyAI7e+qEhxzM3K1asQG9vL+6++24cOHAAd999N0wmE84//3wAwCWXXIJXX30VL730Eurq6nDzzTfj9NNPx7hx45T4aaqSivWm2lIkHRruoZ9cwXR1RJQa1FULq8OWPY7Z7ceX5aCsMCuqdXC7UiCqHryh5rIRJQnF8gasXr0as2fPxhVXXIE77rgDN954I84991wAwPLly7F+/XoAQE5ODh5//HFUV1e70tQ98cQTyMpyXBAXLFiAO++8Ew8//DAuueQS5Ofn45577lHqZ1GEVH0RilFXn9n1GMGkBAX0HsPwE/KNkZOSeacTkQee7UBn7xAOHOsBwN55ij+1XWJVVhyipKTIpHiAo5f+vvvuw3333efz3t69ez3+njdvHl555ZWA61q1ahVWrVoV8jvff//9yAtKmqKmC1nDcO88AEwaHYeA3i16lyBBSMkxGZTqeNSrmyQBVpsdaYbUfeTImXseAJZE+Pw84PbcsYqub6ReartpLnk8Q69cObRMZbuUVEixHnoiILkrd+eEeOlpeowu0kZuUCKtYTtHhdxanza7iBv/9DH2HulSsEDK2jw83H5SRR5KRqVW/uWWzkH88919ONrWH/ZnRFHCe9VH8UV9RxxLlly0Ug+qoeNBbTc8lCZJEh79Ty3u/NsWmNzSXZO2MKAnxXy+uwW7G5Rv5B1p6cMT/93let5dLs71TSjPhU6XmItYMt8gIQLArgoNsthE/PHFGqWLoYi2bpPrWrC0MvLeeWBkFIoWj/zf/H0r3t16FL9+anPYn9mw8ziefWcf/vhiDQaGrHEsHSWGexe9cqVwqjvSrXQRVOVISz+21LWiobkPr3/aoHRxKEoM6EkRg0M2PP7aLo/Xoq7n3a4V0bT1b//rFny2qwV3Pb012hL4ECUJDcMz3HNCPE+Mx4iSm79T3JKiOYdjHW6vdQNDkff47dg/koq4d8AiZ3GSl4qvq5K64nmYLeHldE8VZuvI9ujt5/mmVQzoSRHJPqyntcuEweHfGJfn5+F1YVTxxZyIKFVt3tMCAJg6Nh+FeRnRrcT1CD0regqNN82JUg8D+lShsgreX8Mk6iKqMLI9dNxtQryKXAVLQkSUWAwoHFo6B3GkxfHs+NIU7J0nZajt9PMojxq66NVQhoglZq+q7dih8DGgJ2XIWWtIfv+pKOeEeLlZaSiKtlcmRfC5fyJKRs7eeQHA4hgCelcVqZYLHKmOmkdvuE9Cp4ZJ8cgT22DJgQF9MlPxWerv0qPe0kbOOQnSpIq8kZRDRESUMjYPPz8/Y/wojMpJj3o9vIZQZNQb3PNQVjeOrtIuBvSkfe752FVQGdnsomuYZTwnxHNv5KngZ4eNKWNITmwfkhodax/AsbYBAMCSyjJZ1smakwKRYpwcOJWk2jXjWFs/uvrMYS3bZ7Kg36SezBJsL4aPAT0pQtZTVGXn+9G2ftjsjhmd4zUhnrcjLX2qrfgkSUJz5yBElZbP6WhbP1764ADau01KF4UioO6jilLVluHh9jpBwKIZJQqXRhlHW8PPPU+R23GgHc++vc8nAFOiTjza1o//fnIIvYO+s6S7X/ur97YlslhJI9p9eri5D796ajN+9vAnfmf3lyQJv39+h+vv2vpO/PCBj/HqxkNRfqM8jrb248p738dV933genSJgjMoXQBKUTIEd69tPISNXzR5pNxQA/cJ8SaWJ2ZCvLv+thUXnTY57t/zcc3xiD/z1udH8NKHB7F8bgWuvKBStQGYM0/ylrpWrP3+MoVLQ4Go9fihEWq9uZgokiRh8x7HcPvKCaOQl2WUab2yrCZhfr0u/NzzFLkH/7UTANAzYMZ3v1Q58oYCx4nz+hkqx3tz5yCGLMmd5UhN/rfliOvfR9v6MWVMvsf73f0WvylFX914CF9dPinu5QvkoVe+cP37sVd3YalMo5ySGXvoSRFyXG/+s/EQ2nuGPNerghaPc0K8klEZyJWpIReOf39U7/F3PLbFX9+si/gzL314EACw8YsmuYsTF97HFKlbqg2fJPVrbO1Hc+cgAHmG2/MYp2B2HGhXugguew53+b7o1RRhHvjE8WgG+qlI1NBm9qe9m+2wSDGgJ2Wosw6RRUNTHwDHhHiJxsmTiIiUtWV4Mjy9TsDC6XIOt0/iCydFzTsmU9uM9+oqjTYn5os27g6VYUCl8Tz0eg3uJIUxoCdF+K1DZDh/la6bTGYbjrc7JkKK54R4RERakirNM8dwe8czn7MnFSInMy32labKxqOoqTUwA6B8w4wAaOtGhoEBfcQY0JMi/A7zkaPSV/jCcbi5z1WERE2IpzWqbngQEcWgobkPbcPDRZfEkHveH9adFBaVHycqL15SEd02tr+AXm2jOZz0OoankeIWI5KRM/+8ThAwviwxE+IFos5q2hfvwxIlF7+BZ4qc6FuGJ8Mz6AUsmCbPcHt/Q2WJPKn3iq++oFF751PUz7qHGHKvVuyhjxwD+hShturUryQYcu8M6MeUZCM9TZ/w79dCFeh9cVd6n1FyUutkP1oyMGSNajvaRN9ZkyVJvn0iSRLae0yq28eSJGFLnWO4/dzJRcjKkDeRkLp+bWKobBerku8z9OrCfRibPj+pAAMxmR0ZBCRJwq6GTjR3jqThTdSQ+yGLDceGHz2NlkEvT3hqF0W0dg3Ksi61Y0CfImrrO2XNA97RMxTTCeu3KDIUr63LFNPJ6wzIY/18IibE81c3d/WZXf9+67MjaJQpD3BXnxm19R2yrEsL5DxX4kmSJDz9Vp0rfVEq8renNu9pwY1/+hgfbj+W8PIki+q9rfjhAx/j7//bG9HnRFHC6sc/8/ve57vlySf8+qYG3Pzop3jlY2VzJXs7eLwXHb2OOnhJpXzD7bX07Kscdh4cudZIkoT9R7vxvbUf4Mp738eV976Phubwr9MHj/dgzZOf4b3qo/Eoqir43CSP4Pr1300NePBfOzE4ZIVdFPGP/+3Fa5+o67yKxn83NeD59/aj9pBvu0Vr59NPH/oE/SZrWMv++d+OtkD13jb8/vkdONoWog0Yh6bO7X/dgl/95XNU722Leh16mQL6x/6zC7c8/llUKZe1hgF9inhnayM2yHRADw5Z8fNHN+FXf/kcR6MMGOMUz+O3z1Tjlsc/Q2dvdCkv7np6a9Tf3dNvdjXmJiv0/Py7bo2W1m4TbpMhD7BdFPGzhz/BH16siXldAHx2tBqvrVuHZ6lWu4PHevHRjuOqSlsUb+HUE4+9uguDZlvEwSiNePiVWkgS8NGOyK4bh4IEWy9+cCDWYgGAK5B/fVODLOuTi3MyPKNBh/lTi+X/Ao3caJSTBOCeZ7bB7vYw8B9eCP9a9Nt/VKOpYxDPvrMvDqVTj2iODJPZhlc21GPHgXa8+MFBbKhpwgfbj+E/Hx+SrTMA8D1s433Nb2juxSsb6vH2lka/x4oa2xzB2EUJn+4K72Zo3ZFuAMDbWxp93vOXBSkeNUprl2NUwN/e3BP1OnQy7aTqfY6bCtGkXNYaBvQp5L+fNMiyngPHRhpskTb2XOLcMHGexIl0aDhdHQBMLFf2+Xk5mcyplzO2222kg5qFe9c+mWmtcZb0glTtyZxWU5Qk143AeVOKkGGUd7h9qvLXVIik3kvBeyBh/2b3kWiHW/pwvG1k1GVXn3bzgHf0aLfscvE3b0Giq99kru/ViAE9qYbWr7v1w8PtjQYdxpRkK1wa+cj9nKrP2ljpR42bjkgd9jd2o7vf8azr0sqyuHyH1q+R0VDbPAlqFc1m0rldQOx2EYJbROBnGoyo8Tolh9jPA3+7IZ5nVyy97LwZEDkG9ClEriEsclQBfteg8Qt3w3BAP6E8NzEpN5KlvtP4ficiN8lSL0Vo83DvfHqaHnOnFMm6blfjNgWrSl4ewiDDNrKLkkeAr5V5ZPwJWXQN1lER7w6/mUbi/8Pdj5tYgnIN7iLFMaBPKXE4RaJdpXavFX5JkpTQCfESSfZdpYWGAu8OE1GY7KKI6uGAfv60YkUynFDq8r6iRnOJtdlFz4Be1MB1miLit1NP7hGY7utjMyqhGNAnMe9zSU0xSrwmxYvPykJr7TZhYMiRLkSpCfE0S00HppMWbjoQqZCWch3LZe+RbvQOOp7rXjpTvtntnZxbNBVrJS33FGuJXZQ8htzHc6tzj0ZOK6eB+6MaMV0JUu8yEjMG9ClEJ1PgJEfF4ve5OI1UWP4cOj4yUeDEJOuhl5sad3OyNRrtcj4AmeTE4dE1Vpu2J3882taPgSHPycIONfWivccU4BPhs9nDP57icX/OLorYtq8Nrd3R/RabXURTxwAkSUJz56DsvY+b9zh65zPT9ZgzWd7h9sF09Ay58k7709w5CIs1vONaFCWf7StJEsxhft61HkmK6HgJxW4PvK/MlsjPWS1OJNpvskY0l4C/CdH8Lue2mM0upUwP/Z7DXbIeo4lQd6RL1vUNWWyo3tsq26THPf1m1B3uQv3xHtdrwYbct/cMYceB9piPs5auQZ900+3dJuw90pVy829wGtYk9oFXDubWbhOuvPd9XHbudJy5cCwkScIbnx6GTifgSydOiOo73qs+iuVzKzBBhlndDxzrQVlhVszrAeQLGte9sQeXr5gBQ4icmM4Z7nMy01CSnyHTtwcXbk+YJEn490f16OwdwqXnTkd2Rhr6Bi14ZUM95k4uwoLpJXEu6Yj3qo9id4O8F6a2bhN+//wOVE4swBUrZkb8eZPZhtv/Gnt6PzX58YMbcf/1Jyfn0F+Zr9HrPz2MlzfUo3JCAX5+yQJ5V54gtfUd+MOLNchKN+DBH58CnSBg75Eu3PfP7QCAR392WkzHwj3PbMOvrlgsV3Ej9l71MTz/3n4AwLpbzoz48w+8VINdDV0YXZyN4+0DOGl2Gb534WxZymazi6je6wjoF0wrQZohDv0kzkfo3Wclb+7DHX/bgvxsI35//cnQeY2nrd7bhodf+QLjS3Nw+5VLQ37FE//dhc17WnH5ihk4ff4YAMCjr+5CzYF23HzJAkwZkx9yHTa7iGt+9yEA4JqvzArzxwX322eq/b7+zpZGPP/+fnzzrGk4Z/G4sNb1n4/r8donDa42kBbUHurAn17ciUUzSvD9lXMCLjdkcbuxE0Udafcaci9nMBRLPvJohCr5m58dgclsx+XnzUhIeeRQfzxwOtBoPP7qLtQc7EBetlGW9d30yCaP1JJA8Ju7P/3zRgDAN86civOWjvd5P5zWrclsw+rHPwMArPn2IkwZkw+bXcTNj30KALjxornhFT5JsIc+SdUdDhw0PfP2PvQOWLCroRMvb6jHvz48iD1Blg/ljr9tifqz7p56Y4/q7qht/KIJ/9t8JORy7s/Pq212zpYuE9Z/dhif7W7Bu1sdeeqffmsvPtxxHH9++YvQK5Bxl8QjF/Df3qxDa7cJH+04HlXP9P82H0Fbt1eaG5Xtw0gNDNmwcWeT0sXQhJc31ANATHWg0l5435HffdBsg9XqOAfeGT7XgZG8wNHy7gGJVrSnVaz55ncN30Q83u5IyxVuTudw7Dnc5Xrcamml/MPtA3npQ8c+7xmwoKPXN03X46/tAgAcCTOfuHOUwd/f2ut6bWtdK6w2EQ+Fc50AsHX4xgYAPPHa7rA+E63n3tsPSQKee3d/2J95bTh17zNvaycn/R9eqIEoSdhS1xp0uQ+3j6QQjqQv38kuSh7np5yj1nYcaJdtXeEIpx35oVeHV7IJtQVqDnYAAHoHLLJ8n3cwD4QXlP9n46Gov7PRrW5z7k/3EThvfR667Z5MGNAnqYNuw1786TdZPXKOOhs6iRKovpXtEiLjxShUQ99mF3G4xdFDP6lCffnn3YclHhkuZ02CL7Dx1BljzvihKIZtaoHVpq0hhRQ9j9pO8PiP432V3CiNeg5VlZTfn817HDcHsjMMmDWxMC7fofTtxXDrSNY5yol1CLkEeIzy4FNb2ub3qdYEV6OJ7NyK+7xcGsCAPkVJgEd3iVoaTGoph7tQVdKxtgFXQybZZrjXBLdjRoWHD1HcedSbzn8K7u/L/B1BaHxwS0SsNhHb9jluji6cXhLy0SytUuN1mWLnvlclKXnS1lFiBTpWYrsWhP6w4Ocal0KXHx/JefWh0CTP4VWJrroDTdoi1zVE1t8TolZyH46ayIA+3Moy1guz2i/rai9fPKVS8EThcZ7vch8a4Z5nqTTL/a5Dna5J6ZZWlsXvi4ZPdKViLAZ3KUBC3IbckzrEa48GmtgurGtBgEKF07bxXH9yTbQdDQb0KUqC56z3UgQzTcpxjgQccq/Bi4gzoC/Oz5BtghE5uVe2UW1ete8T987JKIrq7zOpE5JQMpD8nAPuwx3DnfU6+HcoVw+otQraXOcYbp+blYaZE0Yl9LtDbxP5NhqHX6uP9/kYzc1d91WIkueQe7Wec+HQctnlk7gx94GuDXHvcPDXKZnCvRwM6FOVz91Y5YriTosNB/cJ8dTI32QlkYj3sRFr9esZrMhTWJWcDiGx4UKA19DZ4b/8DUeM6TsUPNbUeJhbrHZs3+8Ybr9oRin0uvg1p5TOQ6/FG+3JTu49IkmSR4+nltPWyXEDk8IXsN0eQ3AtR1ieascBA/okFWoyCgny9+DIQWvDvIYsNhwbnlAwWQP6SEXb+LPa7CE/azLb0DNggSRJGBzOue2vd5IcWrtNQfNUB9LTb47qc+5EScLB4z2w2UW0d5siOrf9ldtmF1F7qMM1saNTV58ZdlHE3iNdIfNSd/WZ8e7WxoCTgG7b14bDzX1+31OzDrdc85IEDA5ZXbOWO18Lx+HmPuxp6PT7Xt+gFVvqWvFpbTPag+SDD3bp6eg1473qo2ho7sXbm4+4zuHQRn7Ap7uaw/xMcP0mK3bsb4fVFt2kmF/Ud7iOt6UzEze7vT/uu/d4+wD+u6kBtiD520Np6hjwyBiilWq1b9DiUz8kLa+dEuujLpJXD31L52DArDF2UURHj29mBX+6+2ObtDYcZqvnOTw4FN6166nXd6OlczAeRVLUfz6ux/F2398Vy3ksSRI+rW1GbX2H6zW7KOLNzw/jrr9v9fsZneDYF+9vO4rWLv/b2Wy14+//24uf/Hkjnnt3Pz7f3YJ/vrMvrOwcHkd8GM/QJ/uNSeahT1HvbGnE5DFuAWiI43z9Z4excWcTrv3KbLxffTT4wkHUHe7C2ue2B3z/0f/U4saL5iLNMJIzualjAM+8vQ8nzS7H8nkVAIBOP2l63IU6b1/ecBCvbzqMygkFIcu865D/Bi7gaAA7v0uNM9wDcOVvBhzpY2565JOwg/w3Pz+MVzYETiuy+vFP8aOLq1BemAUA+LS2Gc+9tx/fOHMqTp5bEXYZj7T04Z5nt2HWhALceNE8v8v8+6ODeOPTw66/BQDf/VKlxzLRVNfvbG2M4lPqECx4qj/egxc/OIBROUbcf/3JHo/YBNPWbcIvHvsUOZlp+P31J0edV/sXj25CR+9IY27ZnHJc/eXQuakPHOvBb/9R7VPuJ/+722/qpg+2H0OaQYe3tzRi2th8rL5skd/12kURP3v4E9ffD/7oFORkpnks40zP9fBPTkVmunYuj+7BmyhJ+MvrezzeD+eGbe+AxZWC9JZLF/q8/9t/VHukR4smHzzgmbpyb2N3wPM9kCf/K086tB8+8DEA4JR5FT71SDicN0zys42YPm6ULGUKxHXqBriwbdzZhFWnTsbgkA2//MvnMX/fmic/x7Sx+TGvJ5FEScJNj2yC1SbixxfPw7wpxUoXSXaNrf0YV5oDQP7HaCRIcIvn8W71UbxXfRR/+cUZPh1ED79cix0H2vGDlXOweGYpPvkicIrUnz70ScD3Atl/tDvsZf/zcT1e33QYV14wE8vmVOCD7cfCTkv4SW0zPqltjrouUytnekYfMRwyNQc78OTrjrr3/h8sQ2FeBt6vPoaXPjgY9HN/e6sOW+taIQB4KsB2dqaci7gtFmoeMK8Xq/e2YbHCN1/jiT30KWrjF00RzWj6rw8PorlzEH98cQdqgwS4oQQL5gGg9lAn3vTKHfngv3Ziz+EurFs/0kh96o093h8NW1efGa9vcgSG4eaeDnTX/1CT43VBACaUqzOgb/S609nZG/4d85c+OBg0HU5LlwmPvVrr+vvJ13ej32SNeP88+d/dMFtGhrD64x7MA466et36PZ5t3OS+ARuRrXvbAADd/RaP3Kyh/Hc453e/yYqDx4Knvwymw+s421QbXs/qC8M3oLr7LegfHCl3sDzMb29xNAT2Hw1c3gGvXpvDQXryYk2FqCRJAnYe7PB6MfTn3LfHZ7t987T7y3Ueq2Dnu7t4dqx8vDNwMBKI2WJHzUFH2RfPLPXo2UwU9xjr9eFztqlDvvSzwc4lNTJb7K5sM//6sF7h0sRH0NzpsT+75hO4SwAsflIROvPKP/Ifx7U/lvaYPw/+a2fYy772SYPHTcx//G+vrGUhh51uqY6bOhy97R/VHA/6GZ0gYOvwdTseVbj7qJRwet+37W+LQynUgwF9kgqnbvfMUxzeensHww8MotXc4Tk0p6XLd3in+8zykRqyRD6U2HtIl3c5xhRnI8OonR49OYU79C4Y9+0b+WMXnr2Tcki2aVUi+T2K//Y4Zd/QewVdiv/OOPHXsNH6SEO1Fb/mYDssVkegs7QycT0+nmnG/Lyvtg0VpeyMWK+lSbIhvITa/zGtL/bVyWYoxKNTFB3Z9vHwxTNkEB3ni6y/QYfBjulwRylqFQP6VOYxaZJ6qvNwSpLo8zLQ82lqnxAvHGrY9x4TNEb4zL/ypVe/UHNqqIngWTHJuF6vvwUh8LGvgnMiWn4DvTDOEvfPxXK0xOVYU9nucA63L8hNx5Qx8R+aHu421docNHLSUBVHIXBfxkcsbb1oPpnI3ej6ae6PkXgVmgE9JS2PtHUqageEU+mEmgAmEZP89Q5a0D7cO61EQC9X3aT4rhe8JmiM8GDkpHhJJk499N7rEpCcAZAsPfQx1C3J3WRyTMzpfKRhyczSxDYSQ+xHNdycpTgKEqxEdRR6r8PfShQ4pLR0AzoVhbt3Au1HueopwU9bIdiak/2wYkCfwjzT1mmrIaCGE7PBbdi/lnvoFY/ovZ7di21WfqV/TKKFdyJoqaEfr1PbpwEsJOcNoOjrcvVuDLVkYQGAHfvbXfOKLK0sS8h3hntOJOPxHK5U+O1K/MS4nHvKjtSmKETziE+gdrpc56q/jj3PdXt+kRJznSQSA/pkFcZxK6i2h16OlciwjhDqjzsC+jSDDmNKsuP/hXGihps57vVswJymAXjO1Ev+qGAXR0XOcnvf1BAEIeDjHRrdXAACNbwSN+Q+Lq1xFe2QzXscEwYW52ckPLNJqM2gos2kqGTdDsGClWjOu3C2kxLXDvbQx4d8gfTw+kItF6iHXp5ieK00jJG9SX5cpeYsXknKZLYhw6gP+6D1HK7iezIMWWwwme0oyE0P67vlSvMUz95Euyi6ZsKNiJ9N6pzhfkJZLgz65Ls3FizXtLuotqcbk8Xmccw6bzC0dZswOGTDhPLcoMdEd7/F9W/vxURRwhf1HRhXmoOu4ZnLJ43OQ219Jzp7hwJmJjjWPoBHXvkC/3fmVBTnZ0b70+JqyGzDlj2+s5H7E+qcMplt2HWoE7MmFqDLLW/wxzub0NDch6WVpXh14yGcuXAsjncM4HBzH6x2ERedOgVZXhNYHW3rR++AxfsrAABWmx1pBj1sdhFfHOzA6JJsHG3tx4zxBcjJTMOuhk7XjTK5fLDtKOZOLoIxTe/x+ssfHYTRqPf7mdc3NeCqC2ZFnbJPSZ/6ySYQTpXqvsjRMHIAuzOZbXh14yEcax/AibMi67X+7yeH8OVlE32uW299fgQSJJx/woSgDcB9jd2oO9KFk2aXo2RUfM/VgSGrK8vLksrSxDUQ/XxNe49n/XyoqTfged7db8am2mYsnlmK0uFt1Nw5iC17WnBK1WiMygl9jQ+l/ngv3tsaPKXtp7uaMbYkx5V6TU51R0Yy1hxrG8D+o92udKr+/PPdfdAJAi46bbJHmlw1c+ZMP9zc5zMxsHdvpXuKu3D5O5qtdhHuZ1XfoGfdbjJHPsmw8yg92taP/25swKgcI768bCIy0w2wi2LASYi31LUiP9sIs9UOAcC4Ms/r9+6G6DMwka+XPjwAACgvyILfMDzEheVws2cmmRv/tAEnzC7HhChGtD737n58edkE5GYZXa+5nwMjj9AHfiyloakXL314AOcuGY/8bCOSDQP6JFFzoB0PvfwFTplXgctXzAzrM54pHzzfs4si1jz5Obr6zPjN1SeEXNf1f9yAP9xwctCGweBQeBW/e1Hk7D22iyJ++ZfNrotiJLwvdJIkuSqTiQrlnw81j0C4/DUCN9Qcx9/erAvr8xabCEmSom7cvvTBQY8RDqIkYXDIhl889ikA4FdXLA772PH2/raj+Oe7+z1e+8rJEwPnaR22YTgdy9a9barNUfvnF3dgw47gaWOcQj3F8MRru1BzsAPTx+Zjn1u6qk93NePTXcCLHzgu7N4pvj7Ydsxj+5jMNvz6qc0Bv+eF9w/gsnNn4PVNDR77YFxpDi5fMQO/f36Hx/LOYzOS/e/dGPzH2/tgTNPhvuuWeby+L0hars17WjGmOBsXnjwp7O9Vi/9sPOTzWqS1aLBt488L7x9wnTO7Ikxr+srHh1BelI0lbvmB9xzuch1zE8qC16/3PrsNAPDu1qN48EenRPTdTkdb+zE2jOBn27421yNBS2cmZri9O/e6uq3bM7vIXU9vxc++Md/v5/7wQg2OtvXjjU8b8PBPTgMArHnyM0gSsG1fO2777pKYyjVkseE3f98acrkn/+vIYy13ndrZO4Q///sLj9fueWYbSgsC3+B5d/jmgzFNh1WnTpG1PPGyt7EboiThjr9tCbnsbes2488/PgXZGWmBF/K69vvLYvSvDw/iyi9Vuv7+0YMbPd7/w4s7QpbFH7PVjlsf/8z1977Gbqy5fDH+/VHglIOP/qfW42/vJsf9XtcPis2bn42kkJ45ftTIG8MbPtLrysCQDe9XB7/pF8g7WxshCMA3z5rmeu3v7ikKwyhMQ3MfGpr7cPBYL265dGFU5VAz7XU/kF8P/Gsn7KKED8Ns4ANePfReJ0NT+6CrR/PfHx0Ma33O/NWB7GvsDq9gbmXpljEf9N4j3VEF8/609Qy5cntP1vLz8/Af7IUbzDuZzLGlmfFIoShKOOKWE/uD7cfwxqcNYa3H++bEKx/7Ng5CBfNasWFHkJzEXkL10NcMT/IVaSDnrTnE+fX+NkeZvfdBY2s/qvcGzhHbb/Lf4+/PgMm3UWqxihGP/NlxoCP0QioQ1u+KtIs+Qp98EXkud3cNXr2NR9tGRggcaxsIq/j9fvZ7uA639IVeCMCW4dntSwsyMb5M/l7mQMJ+hj7ATnRuT/d62rlNw/3twfT0h39+Or5b3lF4R1r8jyhp9ZPy1tvbmxtlLUu8BXpMyN/99Kb2yNo7jX5G5mzcGfzcPngs8hFVkiShp9+zbXdweGTWW58f8feRAOuJ+KtTWizzIbT7S0+c4O2/yc/oMyc/k9wHLF7YsYjGMKBPUuH03urCnFk83ErTFmLodbgXcfelZH2GVr5VeU6IN1rbAb0cGybWkRSeQ+49iyQgdA+zk/diyZ6mJFxabfg4yx1J+eXKRJdM8+fEe/fHenwF+7gUconE6Bu0YHeDY1j30kQOt4+AUud5pPW/3MWMJVARkulE96LXh8oG5PV3Ag8gfRJvd7WKZff6m2Ml0ZOVBqtynceumiZQTTQG9Cks3Enxwr1Yh5qdPNwGkPtFJdpA0d+n9LE0wLw+6nzONzvD4HomUavkeKwh0tzx3nzy0LuVyTEbeXQRvRob3UrQxCz3QSZzi+QYDXRBj3gbaOTQkWtiq1gaQjE3okJ8XA2Hb/W+NtdxmOjh9tFcOxMp4q+VP6KPWjLHlWoOmpN9xvHk43uSJbq6CeuIkQL8OwUwoCcAwRvM4QZrIZcLs/72zCseaHhZ5BeDUHerI+F8fn5SRZ5yQaOKrofONE7Rch9R4nssCmFfOHx66NloAADEtneU4yy3Ej30mrkZFOdgXa4yBP+45wqEAP9WknO4fUVRlmJZTUIdwzHeV41apDcS5D4eY1lbMo/iChXQK3qjLMWCrWSixlPGNZpP2WIoigF9Cgs2G6S7cHvHbKF66MNai6doLzj+GhhyBXd2UXTN3jlR48/PA/L06sQc0Lv30Eu+zb3we+g9l2M876CJHno/XMPoIumhD7BspEGEVi6O4fyusDafNg+RhOgZsLhmUV9aWabamz1SlBF9rPVDpB8Ptbzc6wtGrfsykEC/1d/PiLTNk6jLhCSpI11uqolpyL3f9SW6iz708ezZQZ9ax5hW2iwUZ8FOzHB76O0xBnX+yhKo0o/mGizX8LPj7YOwDM8XoPUJ8QB52vE2u4zP0Iue1bAgRP8MvdYaa/GSyIZa1J8NMqQvoh76QK8naw99GOK9/2NdvdwBnty21rW6yrC0sjT4wnEUqoEa6rG3gOuNcftqOTjT3k3f8Le1muswDR8yKcnf/kr0LgxvyH3qHlhMW5eE3tna6Er5E4z7rPTu50BXnxlvfHbY9Xfdke6wvnf7/na8vKEey+eWIyczDX95fQ9soogrzpuJovyMsIPw5s5BbKlrxZ6GTpgsnrOn3/G3LRBFCX1+0qu4qz/ei+5+M7bva4MgCOgZsGDr3tbwCuDH7oYu2GwiZowv8Mh9OUmhlHVycuYBj8Whpl60euWt37G/HTPcU52E+LzT57tbsH1/+0j52vp9cu4G0tQ+4JE6UY6bOBar3SeHudbc+sRn+Nopk3DBsomuIaaiJOHF9w/g7S2xzfIsShJ0w+fYf/xkFfC2+vFP/b7+Pz+zTTtv7u072h1+gQJcz7sizJixt7EbXX1mFOTGnqNbTjX72vDiu3ux82D4s/Afbu7Fxp3HcdKcciyYVuLz/sadTVi3fk9E5bjxTxtQmBd+vR4Ouyjimbf3YfOeFtdrz723P8gnPF157/sYX5qDr58xBZt3t6JkVAZe+fhQyM899cYePPXGHhTmpWPJzFJ8/fQp0OtG+ju2DJdnbEkOKooSP9zefRu/vqkhYJ7uR7zSevnzy798juPtAx6vhROQX3f/h1j7/WXI85O/OdI29GOv7gIAfHnZBEwsz8Nbnx/Bix8cwMzxozB7UiEGI8xt3tQxEHqhQAQBXX1mvPnZYSyaURLztTDeAm3r1zcd9nntmbf3YmxJDiZW5OKEyjK8vaUR+TlGZKQZcKSlD18c8qxDag60+6wDcKQFfHtLo0f2mVgcPNYD0+Fun9fvDCMdXzx8uOMYTp8/RpHvTiRnaskfrJwT8Wfdr5/3/XM7Ll8xI+Gxc8+ABWv/uQ3fPm8GPt3V4vGeJEl449MG/Nctg06g7BfJigF9Enru3fAaQO4pSkS3VvBv/r414sav0+ubGvD6pgYY9DrXMOyfP7ppOO9seC2/li6TT75RJ+dQ91C272/3CApj9coGR6By73UnuSbEK8pLR36Oco19udrR9/1ze8x5gZ96wzcYePDfO1FRlBXxurxTmkWSFud3z+/w+C1yPB+58YsmnLlwbMzrUdorHx9C8ahMnDS7HABQW98RczAPAJu+aMbyeRV45JUvsD+MtHctYaSScnJ2OD7z9r6wP3PgmP8yhBPseHv8tV2qy1f7y8c3RfwZZ1C7bV87/vKLMzzes4tixME84MgpPDAkb4Pp451N+CiC1Kv+HGntxx9eqInqs529ZvxvcyOK8jJw9uJxABwNWedxrWTvPADsb+zBxzWxpQj0DuaB8IbOWmwinnx9t99c95EObd22r83130d+eqqrA6LuSHfYHQjuXt4Q+kZiMI/+pxYHjvXg3eqjMV8L5WS2+N64iWRL727ocmVmaO8eCrmdAq37pkcir3OCeejlL/y+3hBm+05uf39rL5bPrYBBr45Byx3+UsTJKJprobe/v7XX7829eKs70o01T37u83rvoAX//ii2ekDr1HH0kvK8euhj5f+Zau0Phak/1uPqLU6G5+fjrakjsjy4cpPjGapwRwdogXvA3dIZfmAdzO6GTp91yyWaZ/Rauvwfc70DkeXKBpIvX62/nthYM1TIKdK82fHifs5vqWt11SJKBfTOG5PNnfHZPuEeArsOdfr/fAxP25nM/kcbJIwkBbwJqDSzzc+2ifJ03VAT242yZBft4yrx0GeK/FqlBGuIVNWJNKh0PaICDOgJQGImt1BRfRk1m13CsTZHD0cyPD+f7OQ4rNWc+idibhtECxkAott/6v9daqKGRw7VUIZAnMPtJ5TnorQg8hFHcoj3s9CxXv/VdFMoUmouuf/nlqMrsZoCVjVS08SxKipKUGo6720qurmgFAb0BCBBwbZ6zv2oHW3rd/VyTWJAr3ryBPTJU026bw4NxPNRNRg08LNUJQmq5bhp7zHh4PAjVkoOt4/33Gax1pP2GLro1RRIqY6M20auSYuTlZoOQ61MMqmmm0SxZlpKBsnTUqWYJOKimgwpJJyTwghw9NgoipFLGGI/5pKph979NNdED30U+0/FEzurkhoCKrVeG7bUjUykumSmkgE9e+hTkb/NGu2uijUTTbJTQTXooqayBKOmm0QM6BnQ07CEVCAaqaSCOTw8a2ZFcTYy0zmnpNrJ0c7UQuAbDTkmDIw35iuOPzVtXrUF9pv3OAL6KaPzUJyfqVg54l0FxVpP2mM4iJQ+/pT+/kRRU2+qOqln+6jhJms41FRK3rBiQE/D+Ax9eEzD6XSSIV0dhUcLgW/4JD//Ui9RkmDnhTquVNF4VEERvLV0DbqyqiypLFO0LMncQ6+2mzhq4m+/RLurYnksIhWoqX2qhipZa9hDDwiSKq7m6tbW5plKw2DQoaAgG11dA6qZiOHKe99XugghGfRC0txF+/a503GGwqnMPtvdjCde2y3LuvKzjcjLNnqkMtSq7AwDBoYiy2Mcyj3XnIiyQmUmxPLnjy/W4Iv68POQU/TUlMbqSGs/bl+3WeliJL2C3HScsWAMXt5QDwHA/defjIJc5VKU3vfPbdgbRTq3cFUUZUWckWTR9BJUD6efSyZqOt87eobw80flTRlH/j34o1OQk5mmdDEAAHuPdOG+f25XuhhJ73tfnoWT5pQrXYywlJSE7kRkDz0lTLIE8wAwabTyE+IJMj5E3zNgSYpgHoDswTwAPPjvnbKvM1qHmnoZzKcoBvOJ0dVndg23nzY2X9FgHoj/KKFo0osmYzCvNuxvSxw1PdqlptECitFbAV18U9E9+bo8HWJqwYCeKEIGvQ5jS3KULgYlUDQN3ngZMFmVLgIpRgJ08t+wIl9H2xw3OJUebg9wosdUxbgucVQUz/NGjsGCjKqPkDFvA693EWBATxSh8WU5MOh56pAykmnWfYqMcfo2ZCx8H0J2d0K+T190HOmzPk3Y96mNIACLFZzdfqQcGjrnBREMReWRuoGdAo+yqmhbByyKzg5Agr74KAwV9UjW88xQ2gjBYINgNEM/qjX0BwgAA3pKJjobhIz4DxvXRv55CfGt7JPwQpI2BCF9QOlShKTTCUgbvwdpU2qGG8+pScjqBdLMShcjYURJhH5UGwSdCOPkxDwCYpyyE7qcHqRXfp6Q71ObmeMLkJ9tVLoYmumhF9IHkbHgAxhnbEVSXiMSTLkYU84vjmxdhtEHkbHoXegKml2v6fJboS9plLlcntQ0zN3f8H8hsw8ZC953nF+Ta5E2bh8Mow8CBguMMzbDMHZfdF+m9jaETuXlUxHFAnqz2Yxbb70VixcvxvLly7Fu3bqAy+7evRsXX3wxqqqqcNFFF6G2ttbj/ddffx1nn302qqqqcP3116Ozs9P1niRJuP/++3HiiSdi6dKlWLt2LUTO9ikDaTh4jrYWlEbWobdAX3oYgjHKYc2CCCGjH+kzNyNj3kbo8gM826e3QEgP9R0ShMw+BPtdk1US0Hs28tzKmzaEzKX/Q8bityGkD3r8ZsE4CBgiDYI8t0XalB3ImP9h9PvLVRgRQmYvBKMJ+rKGKMolI50NGfM+RkbVx6oP6tutzTCUH4ahqAn6kqNBloxDC8UQzjkU/3LoRrUgY84mZMzdqP4GiUys4sjQQ0Hv9myhzgZD+aHhemv4/Yx+xzOIAASjCYLRFNN3C7ro63l9SSN0Hr0ssd5sjPfNyhFLKpXvnQdCPUMv17aQXP91XpcjlTZuLwSDFfr8DgjGoZH1ZfUi0l5XIX0QhvJDgMEC6K3QlzVAyFB33Sy30HtWCvDvKL9JEGGcvhWZS/8H44wt4a9Tb4Vxxhakz/3Yo1MlbWItMha+B33xUehLGqEvPeKqlwJJG7sfgl5E+rQdjhcMZqTP2AbjpF3QFzYH/Ww4dDldjuNKxdcNf1kjDGWHIejtENJGzsu0sQdgnFQLfX4n0kbXO86VcBksMFZ+hoyF70GX0xXmhyQIWT1xf7Yd4khoapxcG2RBcqdYIu21a9eitrYWTz/9NI4fP45f/OIXGD16NFasWOGx3ODgIK655hpceOGFuPfee/Hcc8/h2muvxTvvvIOsrCzs3LkTa9aswR133IGZM2fi7rvvxurVq/H4448DAP7617/i9ddfx0MPPQSbzYaf//znKCoqwlVXXaXEz46fNMfFU9CJkMzO2bglGCrqIVnToS9shmRNd5yIkg66jAGY9y+AoLNDMmcHWbGEtIm7oC9qguXAfOiLj8FQ5FmpDn1xMiRTiBkY04ZgnLAb+sJgw2f2wHJwHqCzwd4xGhADHJ5pQ9AXtEDQidDldENf2OLxdvqMapi2nANI+pEXBTvS52yCYByCtX4exMFcSKYcQJAgpA1BsmTCMOYA0sYcdH3EenwSxL5CQNJBNOUAVsfESGqYEM+dkNWDjDmfwtY6FtaGOchc8KHjdZ2EjKoNAABJ1EFwu9Np2noOIOr9rEyEkD4IachxTGQs+Z/rxoGloRL2jgrX/s+YvwGmLecCki7wOtLM0Be0wN5ZASHNjPTKzbB3l8B2dBoMY/fBUNw08rkJdTBVnwXY/c80K2T1QJfVB3t3qeNibM0ABDuEdNNwecPvxhKMg4De5jhXRD0M5YddQZKh/DCsh2eFva5EM4kjDSbjxN0Y6h8FXW4nDGWHocswwdYyHrrcTuiy+mFtmghb80SkVRyCvasMYn8+9MXHIPYXjJyzggjDmAOALQ225kkAhhs9Yw7A1joOgsEKCBLsXaWuYwsAxMEcmPcuduyH4fWMHDsCIIjQFx2HcXItxKEsmHeeCuhs0Bcfh9hTBAiSY/t7Hz8BSdAXH4NkTUf6dMcMwILBiswlb8NyYB4kazqEzAHY20cDOhGG8gbYOyrc6iYJQsYAJGs60ibsgWRyHOOiKRdid6mj7FZj4HpHYRa7e2NtpMGXNm4vDGWNSMNemLaci7SJu2AoOQbJaoQ4lAV9brfj84dmwd42PvAXpA0BkgDY0qHL6YSQMej7vnNfuzOYAUHyeE+X1+G49lgyYCg5BgAw710Esa8AGfM/gmRLg3nXSV7nugQhs99x/Eg6198AHPtKb4Muqw/GGdUQdCLEwVzYWsYjbew+2NrGwXZ0GgABurx2CGkWxzXEud6MAeiLmiCkmR3nts7maBiLOkiWLAhGE3R5HZBsRojdjiBeJwhYNL0k8PZKIGcdrMvphKG8AdamKZBMOchc/A4AwFI/F7rhESuSKQfiQB4kS8bwsR+iXtTZYJyyE/oC32uz9cgMSJYMx/XSdV7boS85CrGv0LH+tCHHtcRu8LgWC0YToLNDX3wMaaMPAcBwm8Pm+Kwl0+2bhs/NoWxAkFzHMADoC5ugy+kdXq4Opq1nQ19yFIbSRlgOVEGyGT2PvdxOCEYT7D0lSJuwG9JQNsS+Qoh9BYDBAn1hC3TZ3ZAsGcPHzHD9Y7BAl9mP+p4G6AU9dIIeekEHg04PvaCH3vlfQQe9zuD4r6CP6+MQziH3urwORzvFnAUYrBDSzDBO2uX3M9amibC3j3G0b7z2vZDZB11OF+ztY4bbRxKMU3dAV9AC865lSBu/B/o8R3Cnz+9w1Ilmx3UcEgDb8OSQgui47lrSIRgsSJu4G/p8x0StxunbYGueCEPxMehyehyvuQdlE3djaOdySEM5juO54hDsnRXQ5XTDUHbEo7y6US0wFB93/W2cWgNbexus9fOGy2F3HLd6G+xtY+C+L/WFzbB3lo2U2WCBvrAJxol7hrdFP2zHpkBf2gh721hVPd7g7KEXjIOOa7M9ze0GmSf38zZz4fsQ+/MhmnJg7y5xHPMADMXHIQ5lQ+x21Gf6wiYYp46M8kqf9TkshysBUQdBb4WuoA329gpAJ0LsLnXFFPriY8PX80yYa092XCuH2w/6Ua2wNU0CDFZIg7nQ5fRAN6oV1kNzAUF0HY+6Ua0wlByFrX00xK4yAAKEzF7oi5oh9hUgbcwB13Hj+o2lhyF2l0CyhJFpSGeHvugYBIPVUcenWSBZMqDLGIC9swz2zooI2hzaokjausHBQZx44ol48sknccIJJwAAHnnkEXz66af4xz/+4bHsv/71Lzz66KN49913IQgCJEnCeeedh+uuuw6rVq3CzTffDJ1Oh3vvvRcA0NTUhDPOOAPvvPMOxo0bh9NPPx0//OEPsWrVKgDAq6++igceeADvvx9+mje1p61rN3Xitk/vVboYKcHeU4TZEwuhE3QQBMc8847/uv0NYfjffv7r8ZpzWZ3X3/6W9f3vsbZ+1PR/qvQmSQnmvYtwyyVLIUkiJEiQJAz/V4IICZLkqAckSBAlyZFb2fWe/78lYPjf4shrbut1/Z/k+d997Uewp8d/Y47kJQ7mYNaYCj/nH9zOecHPua/zOJ91zncF3791buuFAOjc1wu4/j1kN+P9xo+V3SApwto0EWV5eTh5boXSRQEAfLy7Ad0Ze5UuBvmhg2442Ne5Bf466AUD9Dqd6+aAwW0ZnaCHXqeDQXDcJNANv2cY/oxu+PVBkw2ftn+i9E9MCfML52PcKOUnwASA2qbDOGSqU7oYKeGOk25BcWah0sUIKZy0dYp0RdTV1cFms2HBggWu1xYtWoTHHnsMoihCpxu5e1JTU4NFixa57oIKgoCFCxdix44dWLVqFWpqavC9733PtXxFRQVGjx6NmpoaGI1GNDU1YcmSJR7fc+zYMbS2tqK0NLzhdDqdAJ3bRFT64QnR9GqZGI3PmCSMPr8DdV1MGZZq0mdU44/bqpUuBiWYLqsfdV37lS4GJVhaRQM6Afy3XiXpKv0MjCB1ECFCFEUw94i27ejcgR2doZej5PLWvk34zqKvKF0MWSgS0Le1taGgoABG48hkM8XFxTCbzeju7kZhYaHHslOnTvX4fFFREfbvdzSy/AXmRUVFaG5uRlub41lq9/eLi4sBAM3NzWEH9IWF2X6HVeXlZfpZOvEKCiZBsus9n6uk+JAELBg929VT6xgaNdwr696T6t0b6/aaT09toPfc3nf2Art6dSURA9bYnosl9RPcenWd/4YEWEU2HxOlqmw2dDq4zkefcz3g+S8CEtzO55HzV3SNyoDj9TDrhEGe8wmTrk9XzWR0Q7bUmfxRaebdS+F4tEByPNrl9l/B+bdu5HXBYzm3ZXWizzr8LTuynP9lhTTW9Yki2fXQCQIMeh30euVOfovN6rh+UNzp+iagoCDYY8faoUhAbzKZPIJ5AK6/LRZLWMs6lxsaGgr4/tDQkMe6g31PMJ2dAz499Hl5mejtNcFuV8dJN7T9DKSN3Q99YTNEUw50WX0ek2d4kyzpsDZNgnGCY1iPtXE6xL4CSHYDhHQTdJl90Be0QpfTA3tXKURTtus5OHEwB7osz9nkJVGANJgHe08xxN5CSNZ0GEbXQ5cxAGvjdEi2NEg2I9Iq6mEoP+JTHneWA/MgGM3Q5XYBOrtjXcPPUYn9+RAy+2HvLHc9Y+ePvbMM1qZJ0Od2OSbyMlghpJsAUQ8hzQxxIN/nea1grEemQzRnoVQ3Cdedd3LYn4un1W8+jE79oYg+Iw7kQcjs85jkynJ4puN5U0GEoLdBMA45tnlpI4SsXtczuMFY6udAsmRCX9IIQ5Hj2TV7bxGkwVykzwo9Q7a1cRrSxu2HJAmw1s+FkD4IXU4P9KPaYN4/3zGz9xTf3jLJlgZpKMv1zJV530LHs1qSABgcz06ljdsH/ag2QGeDOJAPe8do1/OH4mAOxL7CgMeCJAGWvYsh2dLw7fNmYMb4Qo+h1TrBMUpHgABdkMcjgv1X5xpu7Tn8OtCzmUfb+nHr4586npuvaHD8Nn9lt6RDMDoCAVvrWEjWdIg9RZBs6YDeBtj10GX3OiYqsqZDyBiALqsftuYJMJQf9tw/R6Yjbfw+iIM5kOwG1zEhWYww710C2PWAToQuvx2GoibHfjFn+WxXSYLjWTi7AbrMAYimHAhpZujzO2A5PBOG4uOQRB106SZIoh7W+jmQ7GmAIME4eadPveNk3j/fNYmSefcJMM7Y6rrBae8qhZDZD+uRGdDldiOtIvQ5I5qyIfYUwXp8Kk7++lJUTS0O+ZlE+N5978Ni7IKhpBFCusnxHOtgrsezy/5u7loOznXsc0GCNJDvqOcNFse8AwYrBOOQ49lGtzktRFM2dJmBJyGzNU9wzDmgtzv2YdFxCDoJtvYKz7kx3EiS74zt9p4i2I5PhmRPg2Q1OtaV1wkhsx+6nC6IPSWOa8dY/yMlbC3joC9thO3YNMdz24IE69HpMBQfhTiYB31hs99rhTiUBd3wPAHWY1McQZrViIx0HW46exUmVxQE/O2Jdu3bN7n+bTk4FwAcc0nM3Op6XRzIha1tHNLG7oNg8MzdPLTrJKSN3QtBb4etowL6UW2QzJnQF7TCcnAeRFMODMXHkDYu8GgUe3cJrA2zHPMaiHqIJscz9UKaGYLeBl1uF3SjWoNeL6xNEwFJB2koC0KaxTHPw0A+dNk9MJQ3QOwvgL2zHOkzt4S9bSRLOiwH58FQdsTjPLB3lsHWPDHg9cfZjjHvnw/JnAVddjfEgXysmDcXJaPU0Vnz9uZGtIoNSJ++DYDj+m09MtNR95c3eOxne2+B6/l3AJBsBliPTR2eq0BybHODFbqcbohD2Y461pIB49Qa12csh2bBOGm3RxlsbWNgax0PXWafY0JUUe9xnFgOzvN7bXYShzKhy/C8EWnvLYD18Cykz97kaovYu0og9o8CBAm63E7o8wN3l0uWdEAQYe9x1MvO+kbsz3fUi0Havv6Y6xZD7PWs47Mz03D6/NE4c9HYhB8PG3cexz+a/yD7eu2dZZDsetjbxzjqxbLGsD4nWdNgbZzhmgtBHMqErWkSJFPw9p1ozgBsadBlez62LEmC44ZVhCS7HrbWcRB7iyBZjTCUNsJQ6pgY2No0CWJfAYT0QVdc430ttHcXA6LeMb9AbxEkmxGGJZno6lL/ZJvh3HRQJKBPT0/3Caidf2dkZIS1rHO5QO9nZmZ6BO/p6eke35OZGf4JKoqS31kn7XZRFc/QAwBEA6xHKmE9UjnyWtqQaxIrR4A7GRAFSNYMwObYNqa2sRAMVo8JaqThSaJsTVM8vsJ2dIbr30JGP3TZPY4Jc/oL/E4y4Zq4xP21I7NgPeKYcMxQcRCGikOui5JzohSX4Qm6Aq3L1jLeMZmZ0eS6kFkbp0EyZzomvoAA28AoPxtreJ3DE58JWT0wTtsOsbsU4kCexwQuQzWnuk0yCOhLdOrZ515sbWNg76jwaOQN7ToR0sAo/5PHGcyOyYzcJgGTrHDtA/eJ4QTjIHSj2iHobUgbN5IexbT5vJH1ARB7i2AdmVfQsUz1mUgbvxdibyHsHaOhK2gZmcEWww3Rpik+x5s3k2uSKz+cs7va3G7uDR/T1kNzfYZDmtrGefxtbZwOXXYv0ibucjSa6ud5/C4AqKsTcfqM8qBljMrI5NJu83cHnsnbbhMBCBD7imDpK3JMdJTdA0g6GKfshGjOgGXPCV6TTvlnH8pxmzxshEc9MszWPDm89bVMHFlPhJMLun/Wm7l2ueMfeisyF703Uq720RC7ymHaPDKh6tC2M6EvaoLYP8qjThG7y2BrHKnHXNKGHBO0+Zkosra+A7MnquMZO0kCpIF8WAfyfd/0dw4YLCMTSHqvy+u/9s4KWOurPJbQFx2HZE+D2DcKsAdP32Y9NNf1b1vLRGTM9pzfw943CpZ9C0OuR7JmwDbo+/tsbWMc1xmb0TEZVvFxx03ooRxYD8/2XX64PhF7SmA9NMc16ZpgNDluavmbFBTAr79/EorzM1Vbz9s7xrj+bao+09Gj65z4C4C91W3iQ9eEdWmw7F06sszweWZtGFnU1jQZ9q4yrwlG3SarG37Nu16RbEZIgKMd0DQZEOyOoLGvENDbXOeqvbMMtsaZ/n+TKRf29rFuv+ss1+eGvjgZkjnTEcCmOybasx6uBGzpjknbLBmApIOlr8jvuk2bz4O+6DjEoRxIA/kQ0gcgmTPhneTJPuiY7HbhtBJMGePn/FJA/fFeNO8shWn76a79CABiXyFsx6c6Ji+tqIetbRzE7lJkLn0LgCMAG9p+ls/6JADi8HZyHt1DO/Khy+uEvaMCkPQwm3KANItrwjInu1ud432tNnWMhpDZh7QJe2BrnuCatBQAzDtPAyAhc+n/XK9Z6hyjIIa2nhfwt+uLjsE45QvP7/Ge7HiYZ73lIGT2QZ/fDntPMTLmes5DYN6zZHjCuJFj4KxFYzG6KAvvbTuG4+0DGDBZ8canh7H+08OomlqMsxaPxawJBXGdBNHJahVhaxnnCrgth2ZB7CtExryNIT/r3o7W5bc6bpBk945MCDrcVhf7imBrngjJkgldfpvHPpNsabAervRpG5jczlHXa87rrnNSXGs6dJn9ELJ6He1wW6D63rdu8STCOH0b9KPaYd63AGK37/wG1oZ8WA/PctTpbpN7m1rHj0zQa7A6JkjsKvV7HdQJgmrr+kgpEtCXlZWhq6sLNpsNBoOjCG1tbcjIyEBeXp7Psu3t7R6vtbe3u4bLB3q/pKQEZWVlrnWPHTvW9W8AKClRx+y1cWXNgHn3CUCa2adydhENkCyRHwbSUA7s7sF3FFxBnN463CiJLN+vNJgPa/08xwzF8zYAdgNsLRMinqVaGsyHueb0kRfcAnr3YB4A9GoZg+nFFbhDhGjOhC7dhKHakyA5G8aS3vNmCeDRCAxFsmS5GoriYC7SZ1RD7M9HWDPL240ejX2xq9yzFziKO7U+Ijx2fIgGiH2FMH9xSsBFtu9vx+CQDVkZys6C7r21JFMu7MMzuQ8N5EU4c7wGSZ7HnPWInyBB0nsECCH5m7192O6GcFP6xJ89WLJkf+dATOeF4BE8RkLyuuHgfeMvKu77SNLD7nVTLjjBVf+FmilZiLWccSBIOkiCCHuPV9Aa4uZIsOPaz7f4XiP8vhaCpHcFjbCnDTf4JUS0//18znZ8qs9i3tdn/zyP4+BZfZCQgC1croGhAfaj2F8Ay/5Frr/NexfBUHIU1mO+2yoQyZIFe/vIdhT7o7t5KZlyhwN1RzYD46Qv3MohYKh2GXQ53cOz0YfexvaOMRgayB+e2d+RkcJfMB+sPLbh66KtfbTHbPmin5s/mel6nLFwLE5fMAZ1h7vw3rZj2L6/DZIE7DjQjh0H2lFRlIUzF47FsjnlyEyPXzvALkmwNs5wzEzfW+TK1OKdrWio5hRkVH08/J4A27Fpnjewexxxkr9gGBg5F8TusujOU4+V6VzfLfYXAP2hRjiFqlt0sOxbHN73ep/TbmWBzeh5k9OLQcFHK+SmSMu0srISBoMBO3bswOLFjh1WXV2NuXPnekyIBwBVVVV48sknIUmSa5b7bdu24brrrnO9X11d7ZrFvqmpCU1NTaiqqkJZWRlGjx6N6upqV0BfXV2N0aNHh/38vNaJIU8qFQiQpixckiUTQzWnOYIYGVJOeVf+7twfvVAnHcy1yxyjLsJq7ERO7CnB0M5TIJmjn6nJ2jjDFdBLMe7/RLHaRGzd24pTq4KMFFBYxI1vLXK7WSFJQuw3c0JobO1H74AFednx/Z5wBA3oVcZ6bAoMFfXDN/PUXm+OUFE85zJ98Cuo7dwFW1sEN6lUJdqNmvidoab9H+nNBbGnBJYe5TurxK4yDHWVwn3/SYN5rlEQ4XJdzyK6MeV3Ta5/mfcvCLDMyMTblRMLUTmxEO09Jny4/Tg21BxHv8mKpo5BPPvOPvz7o4M4eU4Fzlw0BhVF8j9/LYoSIBp8RqzZmic68s0Dw22w7OHUwcNzPsR8I19FB3+CGNQyubkMFAnoMzMzsXLlStx+++347W9/i9bWVqxbtw733HMPAEcvem5uLjIyMrBixQr8/ve/x913341vfvObeP7552EymXD++ecDAC655BJ8+9vfxvz58zF37lzcfffdOP300zFu3DjX+/fffz/Kyx1DZX//+9/jyiuvVOJnUzzFXOG7raphFsSBfEeubC9qCugzpQIAw88D29yCYnta3INkZ5766Fegg72zFLq8TlgP+Q6XVatNXzQpH9BrJ6aLDynx52DdkS4srVRHSiOtsB2bBtvxyRH1qpF/mRgV8pEkkodORRG9mkYLRE49ZXfv1YbV/41Zf0274vxMfP30Kfjq8on4fHcr3qs+isMtfRiy2PHetqN4b9tRzJ5YgDMXjUXVlGLZ2oeBbtzajk8GRB3E/oKRNpgziFfgupgMGNDLYPXq1bj99ttxxRVXICcnBzfeeCPOPfdcAMDy5ctxzz33YNWqVcjJycHjjz+O2267DS+++CJmzJiBJ554AllZjt7HBQsW4M4778SDDz6Inp4enHzyybjrrrtc33PVVVeho6MDN9xwA/R6Pb7+9a/jO9/5jhI/mbRCNMDeMsHvW2oK6Mvts3G45zikoeyQwwjVyHJggUx3leNvXGkOGlv7se9oD1q7TShVyaRJlBi7GzoZ0EdDg8G8GoMoFRYpaalpW6uoKJpm7y1yTZjomMwxMmkGPZbPq8DJc8tx8Hgv3q8+ii11rbCLEnY1dGFXQxeK8zNwxsIxOGXeaORkxtah4m/OLscbBr+PnlD09Cpq08dKsYA+MzMT9913H+677z6f9/bu3evx97x58/DKK68EXNeqVatcQ+696fV6rF69GqtXr46twCrW0jWodBFSRkaaehqoOqTBenC+0sWIgaCZu8rL5pTjxfcPQALwWW0zvrJ8UsjPxEuqd9Ar0cxV03P0lHrUeJMhWalpW6uoKJpmbx8Dq3EI4kBewHknwhmZIQgCpo7Jx9Qx+fjGmVPx0Y7j+GDHMfT0W9DeM4SXPjiI/3x8CCfOKsNZi8ZifFluVOUNGNCT7NTUSRcr9XeNUUjNHQzoE+XSc6YrXQQXXuz9O3GW/D2ppy8Yg1kTHfNRbKpthiTxgptK2nuG0NqtfA54nvLxp8Z6NZl6kdROTftfjRM0apKoh+3odIhdQbLURLip83PS8ZXlk/C77y/DdV+djWljHROBWm0iPt7ZhNv/ugX3PFONzXtaYIswvbWNAX3CTCyP7qaLGjGgTwL+ngEpyA1/BvMT/ARAhXnhfz4RHv3Zafj5JYEmM/F123eW4JZLF8pahtu/uwRlhfGZaE4rTprte6w8+KNT8IcbTsbjN50e0T4K5qlfnBH1Z0+bPxoP/HA5fnn5Ytz0zfmylCc9TY9lcyoAAK3dJhw81ivLepX06M9Ok2X7/OGGk/HLy0dmo412uOEdVy4NvZA3P+2evCz55o9Ye91Jrn/vbgicFzlRnL2HM8aNwt3fOyHhjZHffX8ZfvoN3xRRsbrtO0tkWU9ZQeyPwqgxhJJjJubrvzYHP1g5R4bSJDc19dCr7WA8ZV6F0kUI6eLTo5trItr9btDrsLSyDKsvW4Tbv7sEp1ZVwGhwtMn3H+3BY6/uws8f3YTXNh5CT785rHXaI7wBkErkbterJUWlHBjQJwF/F/vcCBrV/hrgGUZlU3N5S0/TIzM9/OHu+TlGZMucXizDqJ7h9krJyvA9VnIy0zAqJx1pBp1sz5bH0qiSJCA3y4jJo/NkTTG3cHoJ0ocfufiktkm29UZKrtEB6Wl6jMrxvHE3vizyWfJH5aSjeNTIpJRphsgvK4V56agoivxmmb90NIV58k2QWTwq0xUk7lHBsHtp+A7GwhklqCjKxtQEN0aK8jMwZ5L/fN+xmCDTjYlJFZHNou2PqgK6YXoZJm5aNKMUMydoIOuNwtQ0GEJth6KcdWu8lETZBpFjU48vy8V3zq/E/defjP87YyqK8x3bq6ffgv9sPISbHtmEx1/bhQPHeoJex60M6AOaPm4UxpWmQDafKKgraqOo+OuhFyK4Kvl7doh3CH2praGnxKjvUJtADc8jxWuzpBv1WDyjBJ/UNmPznlZ86+xpSDNo+yaPXPsr1pmhdYIQ0bDiodpl0OV2+s1FLvdpOmtiIVq6jmHP4S6IkqSKWbBVUITkpcJtK995KstqkpqarvNqG3KvhUfNoj1X5NztOZlpWHHCeJy7ZBx2HuzAe9uOYtehTthFCZ/vbsHnu1swoSwXZy0ai6WVpTB6zc1kt6t/OytJDddgNWIPfRLwF9BHcsD7W1SN+Y4juZbE43RXWxWixMU1VANDFQ3GOG6XZXMdQw5NZht2HOiI2/ckilz7K9brq04QImpIS4N5jhy9or8bKvIehJXDvZr9JisaW/plXXes1FdLa58aqjBv8j1Dr8Zfpy5qihXUVBatiHabxeNGjk4nYP60YvzsG/Nx9/dOwFmLxrpGeh5u6cO69Xtw0yOb8NKHB9DeMzJHS6TP3KcaHSNXv9hDnwT8DbmP9YBXY0CvNDXduQcAUYV3yyMZGRIv8dwqM8aPQmFeOjp7zdj0RROWzCyN47fFn1x3umPtSVLDcRPIzAkFEOA4rvYc7pJteHhU1HfKJx211fOAjOep+n6a6qhpE6mtJ1KFTQ4f0V6L4r2pK4qycek507Hq1MnYVNuM97cdRVPHIPpNVrz52RG89fkRzJ9ajLMWjWVAH4IaRoKqEQP6JOB3yH2MtZPmA/o41M4qu7ZCVKDODznkXgUbKZ5Hrk4QcNLscrzx6WF8Ud+J3gEL8rL9p8GJFzkbVd4XRjkaQ9GMHJHz+iz3IZiTmYYJ5bloaO7D7oZOrDjB97n9xBv+kRqvpik8bL+mJhVcTj1IGqhwou6hT9CtnMx0A85aNBZnLhyDPYe78F71Uew40A5JArbvb8f2/e2qaEepGbePfxy4kAT8TdY2PoJJI/ydG6OjmKAq3iKd4CwzXd77VWrruSnKT3wmglAVqRwVbayTD6a53eBKk2EyKW/L5jhS34iShM92t8i+/kSS65iOdb97T86nNpXDKQv3NXbDalNP70k0ExBScCqr5gH4v2kfDS08A604FR0AGTK3YWIld5sqHqLdfXoZMklEQhAEzJpYiBsvmof7rj0J55843jWRsxpHX6qJ95wD5MDWQBLIz0lHkVeauVWnRpa6Y9WpkwEAedlGXP+1ObjyS5WYMiayGYN/fskCTB2bj68NrwsATp5bjqwoLwI/WDkH86YU4caL5gIAygqycO4S30mw/BHgmJH1nMXhLa9FXzpxQtSfLcpLx8zxo3DO4nGYOiYfP764yjUja1AhJ8WLukguztR3F5wU/u+bN6UIo4uzMXtigSsfLACMLs52/Xv2xIKIU6plphvw44s903RVFGW7ZtPepOBs93KQa+iaRw89gGsunBXR5684fyYAxz7PyUzDFStmIC/biOXzKnDjRXMjyljh7xfNmVQYUXkA4KvLJ7n+PWui4/MWm4j64z0Rr0su3s28L0Vwjrhzr6PLo0jFecFJE2TrJXEvixqoJ5wbsWB6SUyfv/Sc6QAcWUoq3Wa6v+g0dW37aP1g5Rx886xpsqxLTfv/7EVjY17H+NIcn3Ms3BuB7mk7AeDEWeWy3VyKh5PnlEMfZSNEyZR8xaMycfHpU/H760/Gd780M6psM0qY7tbWSgRnnOKsz2L13eF2R7JQ/+02Csuq06bgyf/uBgB85eSJEfVmCxDw5WUT8eVlEz1eX/Ptxbj/+e3YHUa6pvlTi1E5oQCVExYBAC50W5dthYhrfvdh2OVxWjyzFIu9nlG+6LTJeHtLY9jruOTsabjk7Gn45zv78G710YjLoGYZRgOuuqAST72xx/XaqBwjuvstIT97+5VLke2Vgm7N5Yvxkz9vBABMHZOPA8d8A5dQjZ1YJ28aUzwSLF902hRcdJrjxtSnu5pdx7fTqlMn4+UN9QAcgfddVy316XEWBAHrbjkTkiRBEARIkoSr7vsgaBl+9o35mDWxAIIgBJzV/OS55TjU1IsjLf042tqPsRpNoyLfpHieK3IGwO5+8a0FuO+f231ef+oXZ7g+f9FpU7Dq1MkQBAGnVI12bfsHf1Qccr8F8tjPToMxTY8r730/rOUf+empsNhE5GWNPEoxbUw+DHodbHYRuxq6MGO8sum/nJs70htUt1y6EGNLspGVkYZzF4+DxWZHTmYarv/jBgxZ7ACA808cjzc/OxJ0PRedNgVfPmkiHnp5J3YNXx9+e82JKMhNx4P/2ok9h0NfM665cBamjR2FIj83Eu//wTLc9MimiH5bpVdKtp9/cz6mjs3Htfd/5PH62JJsHG0bCLImNYV0DhPKc/HPu87Ht371ZsSfffRnp7nSbQLATd+cD6tNhCAAaQY9/v1RfVjrqSjKwl1XnYCr10Z3Hnpb8+1FjrpeAK6O4NyuKMpCU8egx2vjy3KweGYp+gYteOPTw2Gv66ffqMLM8QW4/7nt2HfUcb1T097PTDdgaWUpNu9pjfizsyYW4GffmO+qWysnFOC3/6gGACyaUYLvfXkW/v1RPdZ/Fnh7FeVnYHxpDo60OiYDTTPo8MvLF+H2v26J4teMWHnKJPzn40NRf37dLWdiX2M37n12m+u1c5eMwzfPmoa9R0bqnkkVufjl5YshIfQxpoZUzcY0PU6ZNxrL51ZEfb2Lhz/duByDZhtufeIzj9dvuGgefvjAx2GtQxAc14jVj3uu43tfnoUnX98d4FOenDFKeWEWHv7JqRgcsiE70wCLVYRdlJBh1OP6P24IuZ6nfnEGTGab3zTMWqbeW22kCuGO/Ak2lE/eEWxhrsxrMbUNl4+XcH9n1FsjxAcTuZ29vyrYdzvfC6d8OmFkuUC9kEsry1w3Lzbtag6nuKrk00Mf9QzBbn9I/tcTaNv7uwkDeG77iI4rr0UjHZ6XYTR4BPPOdThHfuxp6IxofWqiEwRXIybdqEdulhGCIHjsv3B73tONeo8RAzqdgPQ0PfLDnFOiKD/DbzAPRJfv2vtQTkvT+00rGeqaptZLRbTDndO9jn9BEGAMsG2C0ekEWSejcq4v0pEe/sowUr9HVgaDTgeDXqfqSbZiuaa6f9Z7Ld7nfThUvJlc9G4jCOx2x418rT1zHa92lL8JtMORl23EqBzfej2SYmYY9cj0c9Mkz896w5GZbkBRfobjep1tREFuuk9dF4jgdh1MJgzoKe63pOWcbCT6lCSyFUFVon/SKsrJz0KlrYvxih/t70n07s3JTEPV1GIAjtEDYgInkZRzYiK5Gjre6/G3Vq2fg7OGn6M/1NSHwSGbwqWJjj3ATJpy1NGCzz9CLS/zARHmAabVp1M1fvrElXPXR/rosd/PcUMHpKaOkUBFcQ9aNT+5s4rE/qiFEP9YQz2HpyIY0FNQ4U6iE2wpJU4y76+UI3BJpgmF4nVjJG53whO56cP8Dc7J8Xr6Ldit0V5bn/0V5Xb2fobeX8MvUbMIx+t7Kic4HiMQJQl7G0MPKY+naH9hoBtP0Z62/qrEcFcld1UR7upC1eOqbRSqtmDRkXXir6jrLcHn44mqp+LNe/NGs4nUFMB7C7SfDG7P0DOgl4+/xykjvoHm70UZd5Gaj9dEYEBPcSfnScYeek+JvscQyXaMJrjX0k2TeVOKXM8wb6pN3LB7edPWybOesM5xjZ+DE8tzXcOe94Qxr4jc5Dg37AHWIUcdHfEa5D4e5JoPQqUHqjpLFT0p2mQRfg7hQMd1KK7D3u3zydpWcOf8ieH81nhckWVpEwbqoTe4B/TqyUiidakeLGsBA3oKSm3xVbiNrUDP5Sa7cH9m9Jsj/A8m9LlEGb8q3FUZ9DqcUFkGANi2rw0ms/aGYcv1DH04EnY0xOmLdDrBNfHa7jAmfYurKH+j3D30/oVZR8u8o2Rbn0ovFcl2CZOzh95ujzKgV+vOVik1H4POshncrmmJfBSOQkuVdrhSGNAniYnlua5/+5thOphpQVJPhFsdzp9WHNF3Rk3GHvp5U4oiWkckmQMSZWxptsff86aEtx/8NWQy3CYUmRtg23h/Ktis9ksrSwO+J4cxxSMzy48rCX+W+VAzg0dyzVk21zHs3mITsXVv5DMRK817FMW4khxMHRNbKprJFXlI8/e8XRJcy50B/fH2AXT1mRUuTeT87hcApaMyo1pfvtuERs7JqJRqs4U7GZ/3hIfe1HqYKt0YLi/wTW84tiTbz5Lh8TfJX25WdBNVGYd7ZYPdIygZ5TvRonOTlrr9NkOYKd0SJdqROWPDuiaGPqYmVYy0LfU6QbZ2UKyHc6Dz3X1SPJuGA/pwJ3iLRLQppAOJpM/G3/6KNSsSeVJXzUVRqyjKxo++Pg/XfXU2po8bFdZnZo4fhW+dPQ3zpwYJAsO4mJyzeBxOnTc6zJKG56ffqPL7erSnv3dj6MvLJuJ7F87C6ssW4tJzpuOEWWVBPusojxrSmnibNnaUx98Xnz4lvA/62ZDpRj1uXDUXK5dPwoql433SQAG+F+HbvrPEZ5mf/F8Vzj9hPC45O3Be4DMWjvH7erhtl6+dMgnzpxXjotMm45R5FThnybjwPghH+jRnUP/ji+fh+q/NCfuz3iaW56KiyNEY/DSBw+7l4n1efO3Uybj2K7OjWte3z5uBBdOKccWKGUg36vGNM6d6fpfXQTdnUiF+8a0FUX1XMIHqiO99eVbAAOTGVXORn23Ed0LkpXVOjAcAdQnupZejaTrDzzkNAN+7cBbGFGfj/BPGR7S+b5wxFRVFWThpdjkKctMBRP8M/cVnTIHRoMN1X3Ucf185eaLrvR9fXIXiADPiO339DP913+XnzfD4+0snTXDleZ42Nh+3XrYoaLm07OffnC/bui471zf38/Wr5mL62PyAeaFnjh8V8PVxbqk+r/5yJaaPG4WffzN0feB9Hpy7ZByKh29IBZsw9MovVfq+OLyv/+/MqZgxbhRWnDA+5A0frVh5yiTPF6KsQC4+YyqWVpbikrOnIc2gR3F+Jr5y8kQsnlGCk2aX4cTZgdtOwfzhx6dFV6BhJaMyMdWtM8p5ffGYFC/KkRtq8DMZzt3lcys8/r7honke9WosLj5jStgzxedlG/GDlXN86tafX7JA1kl+w3HjRXMT+n2JpL4IhaJW5RWY63VC0ElBzlkyDgumlQRdZzin2lmLxsg+vLooQNqiaHsp3Iv3tVMm4cKTHRe7aWNHYdrYUag/3uP3c+tuOTOq71NKtKmNnBZML8GC6Y5jYkJ5rk8+ae/tX1bo22szd3IR5k4uCtqzcO7icfhg27Goynjhsomu/XfBSRMj/vyYkhw8+KNTovpub4IgYNmccvz7o3rUHelGe48JxfnR9XaGS+7HYEpHZaK12wTAcQc/3Rhdz8AZC8bgjAUjN2rOWzoeL7x/wPW396n702/Mj+p7/CnOz0B7z1DQZU6aU46T5pT7zUe/YHoJ5k8rDlm/lBdmoSA3HV19Zuxu6MRJwxMjJlq0Q4UDzWtRWpCFu64+AQDw748Ohr2+/Jx03P29E70LF9CSmaXYUud/JMv5J0zAuUvGQT88scPKUybjwpMnutJO3XvtSUFzoAcKxE5fMAb7jnbjs10tAIBMowG3f3epxzKFeeno7HWOuEiOiF7Oa9cPL5qH/Jx0n9fLCrJwy/ANkWff2efxXla6ATd/a6HH+fbd82filCrfm//L5lRg2ZwKn9dDufj0KTj/xAkhl1t3y5l+r0fO8yEnMw2/uHRhxN+faL+8fDEOHuvBc+/tD7rc9748K0RbQHD7/w7fOnsa/vmu73qzM9Jw3Vc9b3qvPGWyx9/OcytcAoCpXp0R3ionFGDa2Hy89klDwGXOXTwOB472jKwUnrOxB2v/zp9ajB0H2sMsceJNHZOPMSXZONY2EPU6rrygEhu/aPJcZ3F20G0arvNPcJx3X10+Ca9uPBRwuW+cORXnLhkHQRAwMGR1vV5emIXp40ah9lBHzGWJRKiYR8vYQ5/CZAsM4tClEevwQu+Puzdk/aXf0PDIrKiEtXXDmME62G4Knhc+7K9MuEiPvZNml7u2ixZ76d3vkCdD76Rco3gCLTPL7Tl6LU3imCixPJes95qlUa/TuerueM7J4b7mZDgH5KaPMn91PHicc97FCnI6+s28oZ6fFb4wymyzRz4ZXELnvAlDpHWrs/TuPfRaf4Y+HntE7kxEoYbNCxg591jPxhcD+hQWToUZTnWoiYPIrfLQ+wnoU61hLle2gKgr5SSqzQvzMjBzOMjbVNusuWPJo30cx/0St5SG8M4jHd9jyzlHSVefGc2dg3H9Lg9aOaziPjFnbPwP8Uye+igeogn2ErF/Y53UTmuT4glCePVouOna3Feltklso005p9dzlvtg5D4vI7vZp63zTWs0EYtRfIQVd4SzTBzO0VhX6XPj3u13GPxUQFq/kxu50FvYb8PXO3uA3Ds/wEGZ6OesIuXMSd/SZUL98d64flc8t0U8G+HJcg9npttz6LsVSF8HqHtbBiuaUmdxqM3lvj3VvG2VYlBZ720gkR5fWtzX4ZTZXw99qOuGXmUbI+I22XDx3W94MA+9L7lv2hsiyH3rWc8O/8FdJBsG9CksnLQx4QQPWrjL7V6x+xtyr7FO1ZhFXad7b6hoe/qj/HpAnY2wRTNKYExzHFeJzEkvB/ddGs9e9ESJ9y8oyE3H6GLH5Hrec0xQCO75vlV63VBruZQkW+8tN23MwgnIQgWy/lahtiH3dlEK+VtDNdtSrV0XDmV76N3KIW8xCAzok1qoE1euyi4uMUDM6/RcgegR0PvpoWfN7yOcTRL1iPtA3xnl+uQUzfGcYTRg0XRHmr7Ne1pgtcVxqJ/sGykxz9DHN+1WYo8c53P0ew53JWx0j9pHqTgpnV4tGh5F1l7x4857boNw+H1mXeaN6/MVEZ4iWryBGU6Jo3mGPpGbIpyvirRNFumxpY1H4+TfKYl+hl6VPTBJigF9Erv6y7OCvh9WA1GmOi8vzBzBOkFAeWEWSoLkRQ4vv6on94uDvwpNE3W7jKKtY9MMnjOgh2q8Oyt7n1QpAT52+nz/6ewmVeS5/u18hlltnDnpB4ZsqFHR7LmLZozM6urM8+x+EXZmNQAiD8bmTA5/X7jnLI8m77l7PmRv7iklJ48eOVbGFEefJzuYyuH0dSazDQ3NfXH5DqUESg8X7rYsKwy8b+Ndzbpn3Ygk5/LUMe7pr7QvVIq/SI3KCX399k5/O3+abzrccNoceSFy0QebE29saYTnuwZ29sTykfosNzMN5X4yy3hzP56d3LOvOFPSqvnmWzg3SieUjbQF50zyvRad6iejQqpyjiCUe5f7G/EaiL/vjjarDvli2roktrSyDGOKs/Grpzb7fT+cINZ9kV98awHu++d2n2XCuSjc9p0l+NnDn4Rc7vfXL0NmuiHoXcRfXr4I3f1mPPCvnWjq8D8pVbAi+Rta5u9u8GM/iy1PqppF01Py4I9OwcadTaEXdPO7HyzDsfYBVE4owPrPjoTsOTh78Vi/r1cUZePHF8+DxSpi+rhREZUhHJNH58X87Hvl+AJXSrNNtc1YPLNUptJ58j5ST55bjv1He9DaZfK7/BUrZqI4PwNzJxehOD8DH+04juXzRlJEXXTqFGQY9X4bgYAjTWDlhAK88P4BHG7xDF6vuTD8nPV5WUbcedVSfLqr2SO9Xbiu/9pcvPZJAz75oslnSGl2hgGXnjMdja19+MrJkzB93Ch8vrsFXzt1coC1OcydXIRzl46LuCwzxhVAJwgQJQl7Dnd63ESIl3Dq6zuvWopfB6jvvfOxB7J8XgX2HO5C36DV45GCG78+L6zPn71oHDbubPKpmy9fMQO76jtdf8cjljj/hPFobO1H6ahM12MR3vxtx0vOng67KGHG+AJVBzmBTB+bj33D6bsmj84LeTPf3S2XLsS9z27z+97k0Xk4eW4FCt3SyN555VK8vbURZy30rKu/86WZ+PGDG11/f+0U33MvnN7BWy5bhFuf+Czc4ns4cXY5jrYOICcrDf/60Df94g9WzsEj/6l1/R1JMKKUsxePRUfPEEoLMlE8yvG/dKMeZovd7/IrT5mEGeMLfF4vyE3HD1bOQWfvkN90m2rs1Ah1tJQWZOEn/1cFk9nmMbfJ7d9dgrrDXR4pEn+wcg7+8sZuWKyONoggCLhx1Vys//wwLj59ajyKH7NYqqKbhvPYrzp1Mj7acQzXrZwzvE7flRbkpmNsSQ66+oZwdDhN3tmLxmL34S5cds70oN/j3jmQn2PEqOx0jCnJdj166Dn4yfe7p47Jx8LpJejqMyMrXY9dfualmTImD986O3g5nK75yiz843/7YDLbwlo+mTCgT3JjgvRmhzXLvdsiFcXZKMpLR4crX2/4MsK8C+cv1603Y5oepQVZKB2VGTCgD8Zfo8Lf3WBjWhLfOYziQpGTGbznxJ9ROekYNbxPJ5bn4sCxnuGv91+AYA2seVN8e3zkUlaQFXNAr9MJOGl2OdZ/dhhf1Hegd9ASMDe2nMaX5uK8JePx63WOQM47v25OZhq+ceY0198Xn+HZeEk36rHq1CkB1+8MiidW5PoE9JEeE2NLcqJuPBXmZeA7589EZ98Qat0CQwCAIOCsRSMBRtXUYlRNDX28/OT/qqIqS1aGAZMqcnHweC92N3ThgpMmRrUeuQUbvbTAT4+pP3qdDtd9dQ5augax+vGRwCrcURVpBp0rN/0PH/gY/SZH7uGF00s8Avp4MKbpccOquX7eCV7h5WT65trWkhnjC1z54CMV7AbpLy9f7PPa2NIcXPmlSp/Xveu6dD/Xz3ACeu8e6Kx0AwbdGuceV2qv9ekEAf93pqN+8RfQL55Z6nHzVguT/Rn0Olx6rmcwc/UFlXj4lVqfZb+/cg6WBLmR7H2TWf2/PrS5k4t8XhtflovxZZ4juhbPLEV+jhH3POO4eSVJEhZML/EYoZYMTplXge+6nZ9fXjYRX1420WOZi06bjH9/VO/6e96UIlyxYmZU3+eeVWDZ7HJcfMZUvLu1MfRcQsMHnyAIrjr7oZe/8Lvomm/71kOBnDirHCfO8rxhdeW974f9eS1T/+1JiptI78gK8J+vPZy7iPGYcEXOnhRtPE+VWHJvEq08AxwLZ8+HXZSweXdLfL4k+TdjUGqZtKxy+NGP/Ud7YLH67y2Ll0T0Isv9DQJS/tBNKf4OUbkP22hWZ7e7zadjYBNYCUqNglHLtSOeEl3Hut8Uc46cC1gGwe8/R15L/t0TV6zNUlh4k46EMct9GGdhom+ER1oxpFp2k3A2j1bTo8Uqlov+mOJsTCx39AwkdLZ7FW9Puanl2Jk9/By9zS5i//DIE1VTeMN5Xye0OLSdYhPNPg/6kSgOIffc5FoYch9Xaj8F1V4+NQrnUVop+N+RcO+hD/VIZajdyd0dmxSvzVJbOCexe6ArDD8z6i2ck1DtjbdU66FX+/7QMmdO+obmPhxrH5B9/akw0kELJo/Oh3G4h293Q3yHknuL5uxV4oxPtXqVglPDZcd9/o2QM3RrTCznmxpPVdn3TnLtbr8SXee6p61znVvuRYhkm6uhgtAwBvQpLKwT3yOgh/+7f+EMuU/wierdyxrq2xOVekpTUmqTyPdjT5hV5moobqqNbBJBOSR7EOWvLlGiGZBm0LmeP97jZyIf1Yl0I8lcZ+sEz2MzkfuM7cTE85vrXI4dEeMx5DHkXqM99LKlHJZnNXEhAbKfuGr+vXIJpykrZwvBY8i9PfiaPeJ8P/s2ye6vJZw2azOSRTgX1/S0kUNEAJDjJ6VMeD30ERQsTKNyQ0+gF65w0+pR9DQzKiDGYuZmGTFvimOins92tSTkZpFGtmzScaZQPNzc55r8LV60f59GCPonJT+559KJ5priPuTevXcx1XHkV7KIYsx9DDyG3IvBh9zzEIsvBvQp4MaL5rpyUDoV5WXghFllIT97xfkzkWHUo3JCAbIy0nDthbN9ZrYO56IqCALOXuQ/JVm0Vp06GQWBgvoIr9OXhJkSI5XIXfdefu4M6HUCxpflIDcBs78ryTnsvqvPjD1H5O299XctLnLLO316FCnhvE0Z40jDVjXFdwZhp7KCyHPJyyHW+0L+8hVHy5nPWQJQd1jdvfRKhy7xvJ9XGuJYnOE2k3uhjDeClbJohvpn5vY3F4kcx8D5J05w/TtYushpYx1pOL3bPifNGUnZmeiRg3KRrdhx+P1Z6eEnz5o10Te9nruTwmijRsTt52ohtpwSIJVsMLYQveRyy3frDHNmWXFPc1nk9m/3G3oTyj2zELh/Pl4mVcQ/vaySmLYuBSyYVoKHf3Iq9DodrDa7KwAPZ7hZRVE2/nTjcqQNPys6tjQHf/rhclx93wcRl+Nb50zHt86ZLlsKiZzMNNz+3SX4kVvu22gV5KbjqV+cgaui+F1a8O3zZuAf/9sr6zovOzeymyBjS3PwhxtORmYEF3ytmjelGNkZBgwM2bDpi2bMnihfEOlPhtGAu67+//buOz6qKv//+HsmvVfSSAgQQkmoUqVbKLIKiLir4rKIdYXFXddVset+XVRwLVhWbD9196vfB2LBvqKrogisoICEXkNJCJBIQkJCMvP7I2RIIIFJMuXO3Nfz8eDBZObOnXPnc+be87n33HMGqqS08qyNJGf86fJeyttZrNwmkt++XdromotaNs2Nt113SY4+Xb5bvZ2cxu1MMpIjFRkWpLKK2jnbT50WykiaezXTHamOK3sZDO2ZqgFdk7Ry44HTpmU61ZCeqSo5WqX4qBAlOjn9nhHddmVvrdlySJcMaa/stjF668utknznlgJn6+DD1w/U3S+uaPS14b3SaseusJy5gT5jUg8t/7lAvU+ZluziczMVGRqoDmc4GeCrWvX7ctFvMyUhXJePzNKm/BK9t3RHo8vUVYM/TO6p1RuLlNMhXlvyS7Rm20F9t+7kYLKJsWEalJOs5S6aMcbXRrmfPCJLVcdrlJUWrX/+e7NTIWpsukh3ahMbpstHZmn/4XKN6pchSTqnc6JG9E6TRQ2nSw0KtOrKC7O1s7BMVzUyv/2YAe20/1C5vl/v2gGFr/1VN63aVKSrRmWffWEf5v8ta0iqnVtYkoICm/9jP3U+dl84q92iQaN8YLtaqjlnzR1aOEXhmdRdmT/baKi+LijQqgHdkvWfH/dq1eYDurqys9tPZLRNjFDbxAiXrCs8NOiMyel5fdoqPLR5c9C7U3PqZXR4sGOu6tayWizqlhmn/2484IGB8XzhmlJD9ROMU2PU2r3tNRd1lcViUfdG5qE+ldVi0SVnSfp9Qc+sROVk1p5ki6p3ZcyQt2M0eg+9c29tU++kS2PH5UG5Kac9d6ro8GCNHtDutOeDgwIafd6M3NXi6dIuTgFWa5MJfZ2I0CDHVK/9uiYpNTGiQUIvyadPwLVWeGigrrs4R5L0z39vduo9Gclnv8rt6t1F/V4zUu1vtql57S8alKm4uAgVFx9VdXXDdmBQoFXXX5KjwuJybd93xGXlG9IjVUN6pJ59QR9Hl3vABFx1f5whG44GVdftvuq4Tas3F3m5NP7DaCfeup3oEVFYXKFDvxzzyGca7CtwymlXx1q5EUarB2io8XmmiZkrNHUcbs1x3lWH9ta0ERrUDje0NcxQ/fxt5gY4j4QePq2pBoIZdtzuZqZBctyxpR3TopUcHy7JtXPS+/so9mdjtJ92Tr3bKfJ2ue8qfWvD3tx9ojumjDJ73TU7jsvG4tZ4tGDd1I/WI6E3LxJ6tJoRG2kGLJJfMMMB13XjDVkcV+k37ir22NVbv2ewOpgUG6bEE4MSGnn6Oq/MQ1/v8antTIOFES7W2LHC2Sv0ZjjOuIXPtHuaE2DXbZQZ6pVTM0n4TD1Bc5DQo9WMuG84NaE3Yhk9ykVfACdKmufc3NpReu2Slue5dqAXszJim6xuIMK8XcUeOsHZolFCXF6Ks2sw8zD7YTcxZqLS2DzThiwoXKr2V06kXcvZfSdX6M2LhB6tFtKCgfbczdXz3ZpRaoJrBlhrjFnadYkxYeraLlaS9N26AkP2ZvE1jV3l8/a9uXXd7o8crdLeg0fd8hkerzku/kpPGxTPJPsAnOTsYdnXRiM3ilYNcu/qY9MZQtjUb7+x/bgri2WGekXb17xI6NFqIcHNS+gfnD5AF7h4Tvr64qJCHNPsmcGcm4coIylS113crcllWnJMHNE7zTHP9u8ndpdEI7wl6kbxLThcrh37S922/vouPPH7Gtk7zeWf1xx1I4uPH9LeZetsrA4O7+Xd7eyaeXKqwDyDdrs3wm+3bm5wqXaE6+Y607zjZlP/u3BmpP8zSYgOaW1xTtNYfUtPcu8802aRkRR5cuq3ST0UHGRVZFiQzsluc+Y3nmJE77YKDrQqNDhAA7q5eM73M2jN/nrisA4uLIn/iY1w/W/Z07ju0TJMW4dWCQ5qfuKckRSpKaM664tVe9xQopOji9dngLas23TPStTDNww6bQqQ1goMsOovV/Zx6ToNy40HkH5dkvSvf29WVbVNy37e3+qkpP7B7s6rz1Fk2OmJ0RUXZmtoz1Slt/FuA3risA4a2jPVcY+5O9w4PlcDunl3/vfo8GBlJEUq/0CZNuw8rNH9M9z6eUZIzpvLYqmdZ/hoRbVSE8IVXW/aNWfdPLG7Plm+W/29HG8jSI4L15+v6K2q4zXq1Dbm7G84g7un9tO6bYeU2yFetz23zEUlPJ3TJ3F8sH57UnJ8uO77XX9JUmZKlObdPEQBVkuzL65EhgVp3owhslrksmlV645PZ7oa3tRv/2xhv/6SHJ3rxJSFzvDH2z+6d4xXlxM9As/k9OYOGbQ/IKEHYAj+d3itFRYSqHO6tNHy9YVakVeoKy7IVmCAa3qQNJbMS7WNlXbJUS75jNawWCwN5pR2h35d23i9y71Uex99/oEybcwvUXWNzWUxdmhBm6vuJENLuKJ7aoN56GVRQIBFvz6/U4vXFx8dqimjO7e6XP4it94MC60RGxmiYV7u5dIUA/y0DSkz5eT+vanjgDNa8153amx319r7w+vXJX+sV9PGdjXEsRDeYZ5+yXALM9yT5Bc4AetVdb1Gjh6r1tpth1q1LrOH8tQGi1H2Qd0ya5Oryqoa7dh/xK2f5ewWG+ObOcFQhYG7tSavoKr4vhbFv5H3uKv7tT8mvi2/f95o34XZWzktQ0IPwOMaTcKMckxxQzlyMuMVE1nbzfC7dftd/wEmclp4DFJvOmfEOK4gGXn6Ok9qOMY9zMQoJ9rgWa1Jxc5WY1qbhNc/OeCPY8c5exvB6QMgkkD7AxJ6tI6Xd4qN7b8YUANGY7VaHPf+rd12SKXlVS1fWb0K7o9XGc7KoPOZhwYHKuvE+Ah5Ow+7fP12Dze6XF21TFlX0SLUFe/w92/d5ufHTka4NzcSesAEPJ0MnI3xyuN+dd3ua2x2rdxwwAOf6J9ObbIYqWFWN33dtn1HdKyq2n0f5Ct97o31M4cnuajuebsKm4q3v+zGpq1z4U6kfkLvj8mvH24SmoGEHq1y8bmZLX5vclzrB8sKdXJU1/qjImedYUTgupFexw5s17qCGUxKfIQuOMd9UwW6gr930UxvE6nMEwPVLfu5oMXr8VY35qjwk4MnBQc1bzRlVwqwGvewVZfQ19js2pz/i0vX3dqeR/Rcgif5994cHtNgYM1WrsrPu9wb6eR2a3CsahnjtoxgaI/cOEi/n9hdYwa0PPG993f9Wj0tWoDVqkdvOves8223T4nWHVf10X3T+ikuqul5Oh++fqBmTuqhScM7tqpcRtGjY4KuvCBbHdOiNXlklq64IFv3Tevn7WIpwGrVBX3TlZoQ7u2ieFTdVfod+49o/6GjXi5N81w0MFPtkiLVu1Oio2u5Nxh5HuL2qVGOqaPc0e3eGYNya+eTDgkO0Pn1TuK1ZIpRmM+0i7pKksumguzftXY9N4zPccn64D4uOal+IhlrKim7eHD7M3x+vdW4Iauz+3uXeye3qXNGbIvWXzf9bNs2ES16P9yLaevQIklx4UqKa10yFh4apG6Zca0uS5vYMHVrH6+vftp3xuW6tDv7Z8VGhuiczm1aXSaj+NW5mY6dd0hwgNvnx26OKaNqp5+a/siXXi5JQ+7sKTAwJ1n/9+VW2ex2Lfu5QJeNyHLbZ7laWEigHpg+wNvFUHy0++a0b63AAKu6ZsRqzbZD2rDLfQPjnamOTh3TRbnt49UtM06xkSEKDwlUSnx4q6bRO9NJUPiX4b3S1DUzTomt/J3VJUw3TsjVb87vZOjfLVyvqa7yZ7pY4u4U22arn9C7+cO8wNltymkfr3NzU/T9+ub1FJx9dV/9sPGAy072wbU4ZQ+/Y7T7s+EcfzzAnio6Ilg9OtZ2y172c0GDe/qc1eAdJvjOfE1dt/v8A2U6crQVgx+2UGhwoIb0SFV8dKisVov6dU1SelJkq9YZ1MKTAeyLfVNSbJjL7jG2Wiwk8z7CpcdgF/30XbkHadjl3v8Ons3ZpKE9Ux2PnW2GxEWFaFT/DMVEcoLXiEjoAcCDhvSoPZAWl1Zqkxuv4sI7urU/2RPInVfp3c0lXVLJ59Fafph4+bNWncRrLNT176FvZVXw9y73nOE3NxJ6AC3CwCUt06tTgsJPDL7YosHxXDhIEFyvbWKEoiOCJUkbdrnnPnq/bIsC8BstaR6c/Xa31u34bH4/KJ5n3wdjIaGHX2B/hNZwxwA8TQkKDHDcg/bDpiJVVtV47LPhfhaLRTknxgZZv6PYZXWLE2gAfIYB91cNrtD7Y0bfQkY7thisOD6DhB5Ai/jrWV1PbNfg7rXd7iuP12j15qJmvdfuyj6IcIu6bveHjhxTUUmFl0sDAB5SN8p9C9Kyxg5nrp2H/uRjqx9eBmpOc8D/th4k9PC6y8/LUlhIgGZO6uGaFXJ6zyNcfVa3bnojM8hqG62kuDBJ0nc/7/dyaeBqOZnxjsd5PnwffWuxK0ZrxTEAl8e48vywq9oHdheev7Y1uIe+desyoubM0MO+2f+Q0MPrLhqYqfl/HO5X08V5U/uUKLet2x3HwFt/3UtjBmRoyujObli7MVksFsec9Bt2FuvwkWPOv5kjseElxIQq+cQJm7ydrkroGw/8uEGZks48v7O3GGmaTPiWC/qmKyE6VDeMz9HUsV0UFxWiP17ey9vF8nMtO8LfNCH3jK93y4zTgG5JZ13ubFrb/uiYFu14PLhHSivXZkD+cpKCNk6LMA89DMEfpxDxlraJEdpZUOqWdbtjP9u9Y4K6d0xww5qN7dzcFL23dIfskpbnFToSs+bgV2NcOe3jVVi8Vxt3Fctmt7t0H1d/VZeN6KjhvVLVJjbMZes/9TNaavyQ9moTG9agIQ04Y8qozrrqwmxZLBalJkRoZO+23i4SmtCj3vG7sTZCfFSIrr0456zrcffI89HhwfrrdQN1rKpa7VP8b5/UnG+PtoP/4Qo9AHhBm9gwdc6IlVQ72r2zg6dx8to35Jy4j76s4rjyC8vc9jkWi0VJceGGnIYpKDBAw3ulKb1NpLeLAh9kxDrtz1w5SnqD41kL1uuugdraJkYoKy3GPSv3Mn4v5kZCDwBeUtftft/Bo9pV2PxeFRy/jatLuzhHOzbPBdPXefpEDlULgCs0597us6wIQBNI6OF3zH4F0+zb70v6dUlSUGDtbvi7dS2Ykx6GFRkWpMwT41lscNl99LVc1kAGAAMz2pRqcD9XzmxgJl5J6O12u+bNm6dBgwZpwIABeuyxx2Sz2ZpcPj8/X9OmTVPv3r01btw4ffvttw1eX7ZsmS6++GL16tVLU6dOVX5+fqPrueeeezR//nyXbgtgVlwdbr3w0ED1yU6UJK3IK1R1TdP7wTo0cHxH3fR1m/NLdLz67LE9E+IOwOjq9lMN9ldOthXO1qbgRCbQNK8k9K+++qo+/PBDPfPMM3r66af1wQcf6NVXX210WbvdrhkzZigxMVGLFi3ShAkTNHPmTO3bt0+StG/fPs2YMUOTJk3S22+/rfj4eN18882n3Y/64osvauHChW7fNsDbPHXI86cEw5vbMqRH7Zz0ZRXHtW77Ie8VBC6X0752+rqqapu27f3Fy6VpJs7YAabS0l98Y4l2C/J50nUv8aOmnKl5JaF//fXXNWvWLPXr10+DBg3Sbbfdpn/961+NLrt8+XLl5+froYceUlZWlm688Ub17t1bixYtkiQtXLhQ3bt31/Tp05Wdna05c+Zo7969WrlypSSprKxMs2bN0osvvqjU1FSPbSM8i7bnSe7cOfM1u15O+zjFRARLqh0c7+zqz6VLRIwsu22MAgNqD7MunY+esANwsfPOadlMAgEBJ3dI/bsl1T5w0ZzvdL8GnOPxaesKCwu1f/9+9e/f3/Fc3759tXfvXh04cEBJSUkNll+zZo1ycnIUHh7eYPmffvrJ8Xq/fv0cr4WFhSk3N1c//fSTBg4cqD179qiyslLvvPOOZs+e3aIyW60WWa0n90gBJxpodf/D+6z1YmG1WhQYaI7YNFYX6yd5gYFWl34Xlga/A//5ni2n/L49uV2BsmpwjxR9sny31mw9qGPHaxQZFtTk8vVjHWCiut4UI29/YKBVnTNilLezWBt2FbeqrPUbzZ7YxwXW+zxZjP09+ztfbHNQX3zP5ed10mcrT96y6mwMAwOtunPKOdpVWKoL+2UoMNDaoK5arQ2PqU3V51M/LzDQ2mC6z4BAjndn0pzvpv7xxJPtCGf2ZadeqCDmzvF4Ql9UVCRJDRL3xMTae0gLCgpOS+iLiopOey4hIUEFBQVOvd61a1e98MILrSpzfHxEo1fCoqNdO+8vWi4yIsTxOCQkSHFxEV4sjefVr4shISd/1pGRoS79LsLDg08+Dgv2m+85OCjA8Tg62rXfmTMuGtJRnyzfreoau9btLNa4wR2aXDYi4uRo+K6Ory8y+vb3y0lR3s5i7dj3i4JDgxVxhpM1ZxIQfPJ9YR747VkCT+5HAqxWw3/PZuBLbQ7qi+9rTgyHxEVoSL2/I4vKHY9DQgIbXdep9bnBPifAori4CAXXa89Ecbw7o+Z8N1GHKhyPg4Mbj487nWlfdmqyT8yd45aE/tixYyosLGz0tfLy2h95cPDJxKDucVVV1WnLV1RUNFi2bvm6Zc/2uiscPnz0tCv00dFhOnKkQjVODGIF9zt6tNLx+Nix4youPurF0nhOY3WxsrLa8Xpp6TGXfhcVFSd/V+UVVX7zPVcdr3E8PnLEtd+ZM2LDAtUuOVK7C8v07+W7dG63pCaXLSs7WdfLjlaqONDc/a+NXgc7ptTOwW6zS8vX7tU5ndu0aD2l5Sd/e8cq3L+PO3L05OfV2GyG/579mS+2Oagvvq81MTxSejJhrKqsbrCupupzg31OjV3FxUcbtGfKyiqpV2fQnO+mrOyY43HlKfFxJ2f2ZdXVNQ3+JubOndRwS0K/Zs0aTZ06tdHX/vKXv0iqTd5DQkIcj6Xa7vKnCgkJUUlJSYPnqqqqFBoa6nj91OS9qqpK0dHRrdqG+mw2u2y20+/jqamxqbqVIxfDNWpqTsbHbrObLi7162L9ASFtNtfWUVu977mmxn++Z7vNfd+Zswbnpmh34VZt2/uL9hwoU0p8eKPL1R8J38Y+yPDbn54YqfCQQJVXVmvdtkPq2TGhReupv52eqKMN1m83/vdsBr7U5vCVcqJprYlhgzaZvfG2wqn1uf6xzX7i8+u3vX2p/ntDc76bBseTJuLjTmeM5SnpFjF3jltuTBg4cKA2bdrU6L9LLrlE0smu9/Uft2lz+pWL5ORkHTx4sMFzBw8edHSzb+r1xtYFAEY1MCfZcb+gc4PjwRdYrRZ1zaydvm6DqwbG88RgiObu+AHAVVo3Kp5LVgP4O4+PNJCcnKy0tDStWrXK8dyqVauUlpZ22r3wktSrVy+tX79ex44da7B8r169HK/XX1dFRYXy8vIcrwOAL4iJDFH3jrXTnH3/c4Fs/jQvoMl1O5HQ7zt4VMWllWdZGgB8W0tGp2+Qrzd6/COjB5rilaEDr7zySs2bN08rVqzQihUr9Pjjjzfoon/48GEdPVp7z8SAAQOUmpqq2bNna8uWLVqwYIHWrl2ryZMnS5Iuu+wyrV69WgsWLNCWLVs0e/Zspaena+DAgd7YNMDrIkJPDp4V6OJRkeOjQx2P46JCzrCkbzFK6jy4e4ok6dCRY9q8u6Txhbhi4XNy2sc5Hm/YdbhF6zBKHQWAs6p/nHLyLUzD6jlG/qo51rWMVxL6a6+9VuPGjdPMmTN1yy23aMKECZo2bZrj9cmTJ+uVV16RJAUEBOi5555TUVGRJk2apMWLF+vZZ59VWlqaJCk9PV3z58/XokWLNHnyZJWUlOjZZ59lx2BiZp+39JIh7ZUcF6bcDvFqnxLl0nWf06WNhvVM1fBeaeqTnejSdRuFxYtXAXp3SlTYiVF96XbvP1Liwx0nwDbsbH23e0/UUI6ggPlcdWG2JCm9TetGFk9LPPn+Xp1a3lYwe3vOXernSFbyJb/g8WnrpNokffbs2U3OC//ll182+DszM1P//Oc/m1zfiBEjNGLEiLN+7htvvNG8gsJnsD86KTIsSH+7YZBbTmpZLRZdM66by9eLWsFBAerfNUnfrNmn/246oCmjOyuk3pR6UsMGjjdPPsB5FotFOZlx+u7nAuXtKpbdbm/+79Ob7VqqGWAKF/RNV1bbGKUltC6hj48O1Z9/01ul5VXqceJWspaov9ujnec6WW2jlRwXppKjVZowtOlpcr1t/JD23i6Cz/DKFXoA7kUPFd9V1+2+sqpGP24uOsvS8BU57WsbtcWllSo4XH6WpQ2Gi2SAKVgsFnVIjVZIcMDZFz6L3A7xGpSb4nR75GyL0apxnQCrVX+9bqD+PmOI4W6frD98Qt8uTU/hi4ZI6OF3GEsMviw7PUaJMbVjFTTa7Z767ZO61buPPq+V3e49Msg9JwUBwG8FBlgdt/gZFUch55HQA4CBzgJZLBbHVfr1Ow+feVR0jnY+IzYyxHFfad7O5g+M59UaSj0D4GaN7maMc2iGN3DscRoJPQAYTF1Cb7dLy/MaXqWnfeO7ck5MX7dxd4lsNiIJAI1pdO9Icgc0iYQefoH9PPxJUly4stNjJEnL1hXI3kQPAuq9b6nrdl9RWa2dBaVeLg0AGMnpRzROe5obbRznkdDDL2S1jXE8Pjc3xYslAVyj7ir93oNHtbuwzMulgSt0yYhzTBHU7G73BrotBABcrdFhO+zM6gI4g4QefiE6Ilh/vW6g7pnaT5kunnsd/m/8iWlbwkIC1baV8++6Sv+uSQoMqN1F1x8cz848PkpNCPd2EVokPDRQHdJq908bdrV8YDwGrAMA+Kd6jRyOdU4joYffaJsYoY5p0d4uBnxQeptIzf39YM39/WBHEu1t4aFB6pOdKKn2PvrqGpuXS2Qct1zeSwO6JWnWZT29XZRm65ZZO33dlj0lqjxe4+XSNI12FAAAvsEYLVcA8LKEmFCFhxprCpe6bvel5cf18466Ltp0vU6KDdNNE7qr94kTHr4k98R99NU1dm3d84vT7yPqAMymwX6Pk4wN3HV1X28Xwe0IufNI6AHAoLp3jFd0eJCkxuek52DnezqmxSg4qPbQm7er+dPXScQdgP9p0CvoRCZf/xYz9nsNBQWSwuEkagMAGFSA1apBJwZ5/GnLQR09dpyx0XxcUKBVndNjJUl5O52/j97TcafxDMCTGPQOUsNeGdz65TwSegAwsLpu99U1Nv1344EGr3Gw80057Wvvo99dUKqyiuNeLg0AAPBlJPQAYGAZSZFKPzHy/rJ1p3e7h+/JOXEfvV3SxpaMds+JHAD+pt5+ze64Tmtv7GUApyChBwADs1gsGtw9VZK0de8vKiwu93KJ0FrpSZGKDKsdGyGvFdPXuRfNZwCe09geJzYyxPE4NMRYg9YCRkJCDwAGNyg32dG9vrHB8eBbrBaLumXWXqXfsLNlA+MBgL+7aGCmOmfEalBustqnRHm7OPAwC/cVOo2EHgAMLjYyRLkdau+73n/o5BV6Dna+q9uJbveFxRU6+EtFs95L1AH4m8YOZyHBAbpzyjm64ZJcjncmRMSdR0IPAD6gbnA8+Ie6gfEkaYMTo93bPTzMPW1nAIDHMZNPi5DQA4AP6JPdRqHBAd4uBlwkKTZMiTGhkqQNhr2PHgA8hbOIOAVVwmkk9ADgA0KCAtSva1KD5zjW+ba60e7zdh5u3hV4Lp8D8DPs1oCWI6EHAB8xhG73fqWu2/2R8uPaW3TUy6UBAGPw8B1GMJD6oeccj/NI6AHAR2RnxDq6aUviaOfjup4Y6V5q3vR1ng471QwAAOMioQcAH2G1WHRubkqDv+G7osODlZEUKam22/2ZePOKFRfLAAAeRxvHaST0AOBDzu+brsyUKA3plaboiGBvFwetVHcf/ab8ElXX2LxcmpNoRwHwJPY5QMuR0AOAD4mJCNZfrxuoO6f293ZR4ALdMmvvo6+sqtGO/Ueceo+nG760swG4m4U9TbONGZAhSWoTG3qWJX1H/QFiqRHOC/R2AQAAMKvOGTEKsFpUY7Mrb2exstNjG13OTsd3AEA9l43IUrfMeHVMi/Z2UeBlXKEHAMBLQoMDldU2RpK04Sz30XsSV8sAeBS7nGYLDLCqZ1aCIsOCvF0Ut6BKOI+EHgAAL8o5Mdr9tn1HdKyq2sulAQDPI3kDWo6EHgAAL6qbj77GZtfm/JLGF6LHPQDATDjL4zQSegAAvKh9apRCgwMkSXk7nZ+P3q1oSAHwIAvD3AMtRkIPAIAXBQZY1SUjVpJzCT0NXxhRTCTTaKJ16vZsk0Z09Go5YAyM5eI8RrkHAMDLctrHa822Q9pTVKYjR6sUHdEwOaLHPYzutiv66H8/36yhPVO9XRT4qL//YaiKiiuU1ZZR2+trlxSp3QfKvF0Mj+PctfO4Qg8AgJd1ax/neLxhl/e73dOOQnO1TYzQX67so3NzU7xdFPiomIhgdUqPoRfSKWZN7qnz+rQ97UQvUIeEHgAAL2ubGOForOU1Mn1d/Sv0NHUBwDzio0P12zFd1Dk9xttFgUGR0AMA4GUWi0U5J67S5+0slt1OJ3sAgLlw6GsZEnoAAAyg24n56A8dOaaikoqmF/TAJXp6vAIAvIlbL5xHQg8AgAHkZMY7Hp822j2XLQAAQCNI6AEAMICEmFAlx4dLkvIMMDAeAACexKnrliGhBwDAIHJOdLvfsPOwbE1clffM3Lx0dQQAwBeQ0AMAYBB1A+MdPVat/MKT8w5z1QIAYCbcQu88EnoAAAyiS7s4x7XxvF2nT1/nKTSkAADwDST0AAAYRGRYkDJToiQ1MjDeCSTbAAB/x6HOeST0AAAYSE772tHut+SX6Hi1rfZJ+twDAIBGkNADAGAg3U7cR19VbdO2vb94uTQAAHhI/cFg6Y7mNBJ6AAAMJLttjAIDag/P3ryPHgAAbyGddx4JPQAABhIcFKDs9BhJ0oYT99HT4x4AADSGhB4AAIOpm75u+/4jKj9W3eA1T/RCpKcjAMCrOA45jYQeAACDqRsYz26XNu0ult3uxWv0ZPcA4HUpCeGOx2GhgV4sifvQG61l/LM2AADgwzKToxQeEqjyymrl7Spu0JDzOG+eTAAASJJ+dW577TtYrpT4cCXFhnm7OG7HqWTncYUeAACDsVot6ppZ2+0+b+epA+O5v5ljoSkFAIYSEhSgmZN6aPLILG8XBQZDQg8AgAHV3Ue//1C5SkorvVcQutwDADyhwax1HHucRUIPAIABdTtxhV6S8nYVe68gdLkHAMCwSOgBADCglPhwxUWFSJLydp5M6LlmAQAA6pDQAwBgQBaLxdHtfmfBEW8WxHufDQAAzoiEHgAAg8rJPDl9nUfVy+GT4/x/NGUAgPfZ691Ez7lk55HQAwBgUN3ax532nCcaOVaLRb86N1MdUqM1dUwX938gAABoEeahBwDAoGIjQ5SWGKF9B496/LMvG5Gly0Z4/GMBAGC8mGbgCj0AAAaWk3n6VXoAAACJhB4AAEPLaR/v7SIAAOBhXKN3Fgk9AAAG1qVdrKyMDgQAMBEOe84joQcAwMDCQgLVIS3K8beFVg4AwA95fEYXP+GVhN5ut2vevHkaNGiQBgwYoMcee0w2m63J5fPz8zVt2jT17t1b48aN07ffftvg9WXLluniiy9Wr169NHXqVOXn5zteq6qq0qOPPqrhw4erf//+mjFjhgoKCty2bQAAuFrd9HUAAAD1eSWhf/XVV/Xhhx/qmWee0dNPP60PPvhAr776aqPL2u12zZgxQ4mJiVq0aJEmTJigmTNnat++fZKkffv2acaMGZo0aZLefvttxcfH6+abb5b9xCmep59+WkuWLNG8efP05ptvqrq6WjNnznS8DgCA0eXUm74uMIDOdQAAoJZXWgWvv/66Zs2apX79+mnQoEG67bbb9K9//avRZZcvX678/Hw99NBDysrK0o033qjevXtr0aJFkqSFCxeqe/fumj59urKzszVnzhzt3btXK1eulCS9++67+tOf/qQBAwaoU6dO+utf/6p169Zp165dHtteAABaIzsjVhf0Tdfw3m2V1Tba28UBAMCtuLvMeR6fh76wsFD79+9X//79Hc/17dtXe/fu1YEDB5SUlNRg+TVr1ignJ0fh4eENlv/pp58cr/fr18/xWlhYmHJzc/XTTz+pf//+mjt3rnJyck4rR2lpqdNltlotslpP1qqAE1dHArhKAi+jLpoTcTen6RfnKDo6TEeOVKimpunb1OBf+L3Dn1CfzcuZ2NcfIyYw0KrAQOqJMzye0BcVFUlSg8Q9MTFRklRQUHBaQl9UVHTacwkJCY774M/0utVq1eDBgxu89vrrrysuLk5dunRxuszx8RGNDkIUHR3m9DoAd6IumhNxNyfibk7EHf6E+mxeZ4p9/QuocbERCg3xeKrqk9zyLR07dkyFhYWNvlZeXi5JCg4OdjxX97iqquq05SsqKhosW7d83bJne72+JUuW6JVXXtGDDz542nvO5PDho6ddoecqCYyAumhOxN2ciLs5EXf4E+qzeTkT+/rPl5SUKyQ4wFPFM6y4uIizLuOWhH7NmjWaOnVqo6/95S9/kVSbvIeEhDgeS7Xd5U8VEhKikpKSBs9VVVUpNDTU8fqpyXtVVZWioxveY7hkyRL98Y9/1NVXX63LL7+8Wdtjs9lls50+iF5NjU3V1eyM4H3URXMi7uZE3M2JuMOfUJ/N60yxrz9meXWNTQHV3EjvDLck9AMHDtSmTZsafa2wsFBz585VUVGR0tPTJZ3sht+mTZvTlk9OTtbWrVsbPHfw4EFHN/vk5GQdPHjwtNe7devm+Pujjz7S7bffriuuuEJ33XVXyzcMAAAAAACD8PhIA8nJyUpLS9OqVascz61atUppaWmn3QsvSb169dL69et17NixBsv36tXL8Xr9dVVUVCgvL8/x+vfff6/bb79dU6ZM0b333uuuzQIAAAAAuADX5p3nlaEDr7zySs2bN08rVqzQihUr9Pjjjzfoon/48GEdPXpUkjRgwAClpqZq9uzZ2rJlixYsWKC1a9dq8uTJkqTLLrtMq1ev1oIFC7RlyxbNnj1b6enpGjhwoKqrq3XXXXepf//+uv7661VUVOT419g99gAAAAAA+AqvDB147bXX6tChQ5o5c6YCAgI0efJkTZs2zfH65MmTdemll+oPf/iDAgIC9Nxzz+nuu+/WpEmTlJmZqWeffVZpaWmSpPT0dM2fP19/+9vf9Oyzz6pPnz569tlnZbFY9PPPP2vfvn3at2+fhg4d2qAMr7/+ugYOHOjJzQYAAAAAnAXz0DvPYrfbTx/tDQ0UFTWcsz4w0Kq4uAgVFx9lQA94FXXRnIi7ORF3cyLu8CfUZ/NyJvZ/eW6ZDh2pvc36hdtGKoh56NWmTdRZl+FbAgAAAAB4GdeZW4KEHgAAAABgGHS5dx4JPQAAAAAAPoiEHgAAAAAAH0RCDwAAAACADyKhBwAAAAAYBvfQO4+EHgAAAADgVYxx3zIk9AAAAAAAw7CIS/TOIqEHAAAAAMAHkdADAAAAAIyDC/ROI6EHAAAAAHiVnZvoW4SEHgAAAABgGFygdx4JPQAAAAAAPoiEHgAAAABgGBYmoncaCT0AAAAAAD6IhB4AAAAAAB9EQg8AAAAAgA8ioQcAAAAAeJWdeetahIQeAAAAAAAfREIPAAAAAIAPIqEHAAAAAMAHkdADAAAAALzq3O4p3i6CTwr0dgEAAAAAAOY2YUgHRYUFq2NatLeL4lNI6AEAAAAAXhUcFKCxA9t5uxg+hy73AAAAAAD4IBJ6AAAAAAB8EAk9AAAAAAA+iIQeAAAAAAAfREIPAAAAAIAPIqEHAAAAAMAHkdADAAAAAOCDSOgBAAAAAPBBJPQAAAAAAPggEnoAAAAAAHwQCT0AAAAAAD6IhB4AAAAAAB9EQg8AAAAAgA8ioQcAAAAAwAeR0AMAAAAA4INI6AEAAAAA8EEk9AAAAAAA+CASegAAAAAAfBAJPQAAAAAAPoiEHgAAAAAAH0RCDwAAAACADyKhBwAAAADAB1nsdrvd24UAAAAAAADNwxV6AAAAAAB8EAk9AAAAAAA+iIQeAAAAAAAfREIPAAAAAIAPIqEHAAAAAMAHkdADAAAAAOCDSOgBAAAAAPBBJPQAAAAAAPggEnoAAAAAAHwQCT0AAAAAAD6IhB4AAAOx2WzeLgIAAPARJPSnOHz4sLeLAOiXX37xdhHgBaWlpd4uArzkp59+0nXXXafjx4/LauXQbBa0OeBPaLuYE20X7wv0dgGMoqysTA888IA2bdqktm3b6pxzztENN9zg7WLBhJYtW6Z33nlHN954o7Kzs2W322WxWLxdLLhRaWmp/vrXv2rv3r3q3Lmzhg8frvPOO082m43kzs/98ssvuvvuu/XVV1/p17/+Nb91k6DNAX9D28V8aLsYB9+2pEOHDumWW25RZWWlbrvtNnXv3l1PPvmk3nvvPW8XDSZSU1MjSdq5c6c+//xzff/997LZbBwQ/VxhYaFuuukmVVRUaPLkySoqKtK8efO0d+9eDoh+bunSpRo4cKBCQkL04Ycf6r777lNgIOfZ/R1tDvgT2i7mRNvFWGg5SCooKNCuXbv0/PPPKzs7WyNGjFBFRYUWLFigiRMnert4MImAgABJUl5enmw2m1asWKGcnBz169ePM91+qO4MdmFhoQ4fPqxHHnlEGRkZ6tSpk+68807t379fbdu29XYx4QZ1v+eYmBgFBgbqnnvuUVxcXKPLwP/Q5oA/oe1iLrRdjMmUp1AOHDig4uJiHT9+XJK0ceNGWa1WJSQkOJbp3bu3jhw5or1793qrmPBzhw8fdpzZlmp3knl5efrhhx90xx136PDhw/rmm29UVlbGAdGP1MW97gz29u3bFRsb67iX9siRIwoICFBkZKTKysok1SZ38H1FRUWSJIvFIrvdrvT0dI0YMUJvvPGGpNq68NJLL+nrr7/Wnj17vFlUuBBtDvgT2i7mRNvF2Ex1hb6qqkoPPvigvvnmG6WlpSkuLk6PPvqozj//fK1Zs0Y2m001NTUKCAjQnj17FBgYeNpVE6C1jh8/rvvvv1/Lli1Tx44d1bVrV91+++2yWq2KjIxU586ddfXVV6u8vFxff/21li9frgsvvNDbxUYrnRr3zp07684779SIESP0wgsv6J577lGbNm30/fffq3379rr55puVnJysf/zjH4qJifF28dFKJSUluvXWWzVp0iRdeumlslgsioqKUq9evfTzzz/rqaee0uLFi5WSkqI333xT1dXVeu6555Sbm+vtoqOFaHPAn9B2MSfaLr7BNFfoa2pq9OSTT2r37t168sknNWPGDO3bt08PP/yw7Ha77r33XiUkJDi6Du3YsUPt27dXWFiYl0sOf/PGG29o8+bN+p//+R+NGjVK77zzjh577DHt379f7dq105w5cyRJV199tUJDQ/XNN9+ooKBAEmc7fdmpcX/vvfc0Z84chYaG6plnntEll1yin3/+Wf/4xz+0aNEiLViwQEeOHNH9998vidj7qrq4HTx4UD/++KM+/vhjx9WLoKAgdevWTUVFRVq2bJkefvhhvfzyy/rkk0+UlZWlp59+mlHQfRRtDvgb2i7mRNvFN5gmoS8vL9dnn32myy67TH379tXw4cN16623asWKFSoqKlJQUJCja9Dx48e1Zs0a9e7dWxaLhTmB4TLHjx/X+++/rzFjxmjo0KG68sorNWfOHK1Zs0aLFi2SJEVERKiqqkrh4eG67LLLtHHjRi1dulSS6L7mo5qK+7p16/Tyyy8rKytLY8eOVf/+/dWjRw+Fh4erU6dOeuSRR/Tpp5+qsLCQ2PuouritXbtWYWFhKikp0euvv+54fdiwYSovL1dkZKS6dOmi4OBgBQcH67777tPSpUsd3fThW2hzwJ/QdjEn2i6+wzQJfWlpqWJiYhQcHOx4rl+/fiotLdXOnTslyXEQ3bRpk7Zs2aKBAwdKkqxWq7Zt26ZDhw55vNzwH3a7XUFBQcrIyFB5ebnj+fPOO08DBw7U6tWr9fXXX0s6OcjMuHHjlJGRoW+//VabN292rAe+42xxX7VqlZYvX65Dhw5p5cqVio+Pd7wvKSlJbdu21caNG71VfLjAL7/8ovfff19XXXWVRo4cqW+++Ubbtm1zvP7CCy/o5ZdfVlxcnKxWq2w2m1JTU5WWlqYdO3Z4seRoKdoc8Be0XcyJtotvMU1Cn5iYqPHjx6tz586OwTzy8/Nlt9uVkpIiSY6BHn744QfFx8fr3HPPVUFBgW655Rb96le/chyEAWecepXFYrGopqZGsbGxKiwsVGFhoeO1Sy+9VGFhYVq6dKmOHj2qgIAAVVdXS5J++9vfau/evfr4449VXV3N2U6Da07cJ02apLCwMC1ZskRpaWmKiIjQ/PnzHVP+/Pzzz4qLi1Pv3r09vBVoiaaurMbExCg6OlqTJ0/WkCFDFB0d3eAqfXJysiTpq6++UllZmaxWq5YvX67IyEj179/fI2VHyzUWd9oc8Be0XcyJtotv8auEvri4uNHn7Xa7goODddVVV6lTp06OM4g7d+5UYGCgUlNTGyx/4MABZWRk6Nlnn9Xo0aNVVlamL7/8Un379nX7NsD3LVy4UDfffLPjPtk6NptNAQEBGjJkiNavX9/gzGVGRob69++vbdu2afv27ZLkmI+6d+/ejq5MnOE2rpbGfcCAAdq+fbsOHTqk2bNn6+WXX9aUKVN033336Z577tHQoUMVGRlJ7A2sqdhLJ+dofvzxx5WRkaHevXtr6NChWr9+vb777jtJtQ2nVatW6aabbtK0adN0zz336E9/+pMGDRqkmJgYYm9QTcWdNgd8UWP7L4m2i79radxpuxiLX4xyv3r1aj366KOyWCzq3r27Jk+erK5duzrmSpRqG1V1Xd/q5sX89ttvlZ2draSkpAbL1g1eVFZWpueee05Dhw712rbBd6xYsUL33Xefdu3aJYvFoiNHjig6Otrxet1O7aKLLtKbb76pjz/+WFlZWUpPT5ckTZ48WS+99JLjntm6qz5Wq1V33XWXgoKCPLxFcIar4r5v3z6NGTNGwcHB2r59u3bt2qWnnnpKAwYM8Mp24eycjb0kBQcHq7q6WoGBgRo2bJjWrl2r//3f/9WQIUMkSX379tUrr7yizZs3a/v27Xr++ecdXbBhLGeLu0SbA77jhx9+0Pz58xUYGKhevXppwoQJyszMdMzAQNvFP7kq7rRdjMHnr9Bv375d999/v84991xNmDBBW7Zs0fPPPy+pdmdSU1Mji8WigIAAx1koi8WiyspKff31144Dp9Vq1aZNm/T999/r8ssv19y5c/XBBx9wYMVZHThwQNOnT9f111+vSy+9VM8884xyc3OVnp7u2CFWV1c7rtJI0h/+8AetWbNGX375pWNu4sjISCUnJysvL09SbZ2sa/BxQDQed8X9vPPO07XXXquHHnqIA6JBORv7U489dVeuOnTooBEjRujQoUNauHChY72DBw/WtGnT9NBDD5HMG1BL406bA0a1dOlS3X777erfv7/69u2rH374wTFafV33edou/scdcaft4l0+m9DXnQFcu3atSktLddNNN+nKK6/Ua6+9pieeeMKxXF2FfOKJJzRo0CBt2LBBkrRx40YVFxdr9OjRKikp0V133aUJEyZo586d6t+/vy655BLPbxR80vz581VTU6PPPvtMN910k5KSklRYWKh9+/Y57hmra8g/8cQTjgbguHHj9OWXX+q1115TVVWVtmzZoqqqKg0fPtybmwMnuTruI0eOdKybLmrG1tzY1z/21MV2yJAh6tGjh15//XUGP/MRrYk7bQ4YSV0bev369erUqZNmzpypm2++WaNGjVJJSYlKS0tlt9tpu/gZd8Sdtosx+FyX+4KCAqWkpDjO/pWUlKhz584KDQ2VVDuo0KFDh9SpUyf16tVLO3bs0IwZMxQcHKz58+erW7dukqSKigpFRkbqvffe05tvvqkuXbro448/VseOHb22bfAddfVQku6++25H/ZOkwsJCRUVFKSEhwdHVctOmTfrzn/+soKAgPfXUU0pNTdX06dOVmpqqv/3tb1qyZIk2b96sYcOGKSsry1ubhbPwVNwZPMh4WhP7+seeutjGx8dr8ODBioqKajASOozFVXGnzQEjqN+Gttvtys/PV0pKig4fPqz4+Hjt2LFDaWlpqqqqksVi0fbt2zVz5kwFBwfTdvFhnoo7bRfvsdh95HTK5s2bde+996q0tFSpqam6/PLLNXbsWH300Ud6+OGH9cknn2ju3LlatmyZEhISVFBQoLFjx2ratGnauHGjhg0b1qDRtGjRIt19993q1KmTbrnlFo0aNcqLWwdfcWo9/M1vfqPRo0dLkuP+2Pz8fE2cOFFvvPGGcnJyJEm7du3Sli1bNHz4cAUHBzsaf5K0bds27d69W2FhYRo0aJDXtg1NI+7m5arY11dXD+rXBxiLq+NOmwPedGp9njx5si666CJ99tlneuihh9ShQwf98ssv2rt3rxITE2Wz2TR69GhNmTKlQRuaY5hvIe7m4RNX6CsrK/X444+rU6dOuuiii/Tdd9/p/vvvV1VVlcaOHatHHnlEzz//vIKDg/Xaa68pIiJC27dv19VXX63c3FxNnDjR0Q2krlJOmDBBknTZZZd5c9PgQxqrh/fee6/Ky8s1btw4R+Pt2LFj6tKliwoKChyNvMzMTGVmZjrWVb8Rn5WVxZltAyPu5uXK2NdXVw9I5o3JlXGnzQFva6w+P/DAAzp+/LjGjx+vmJgYLVy4UMXFxfr3v/+tmpoabd68Wddff726dOmiCRMmONrQHMN8B3E3F59I6Hfs2KFVq1Zp4cKF6tChg2PQmPfee09hYWG65ZZbdM8992jYsGFKTk5WcHCw4uPjNW3aNL366quaOHFigwZU3f0hHFjRHE3Vww8++EChoaEaO3asJCk7O1tFRUXav3+/JDlGDIVvIu7mRezNyZVxp80Bb2uqPr/77rsKDQ3V6NGjlZ+fr7S0NCUmJkqSkpOT9bvf/U6vvPKKJkyYwMlHH0TczcUnBsWLjIxUampqg4GDrrvuOsXExOjTTz9VVlaWBgwYoMrKygYDMvTo0UOVlZWOqTTqUEHREk3Vw+joaH3++ecqLCx0PD9q1Ch98MEHkkTD3scRd/Mi9ubk6rjT5oA3NVWfY2Nj9emnn+rIkSPasGGDdu3aJUmOUcxzc3Nls9kYtNNHEXdzMUxCf6Zb+auqqpSQkKD169erpqZGkpSQkKDRo0eruLhYW7Zs0axZs/Tf//5Xixcv1oEDByRJP/74o3r27Kk2bdp4ZBvg+1pSD8eMGaNDhw7pq6++cizbr18/BQYGatWqVZJOjiwKYyLu5kXszYm4w5+0tD4XFRXpP//5j0aNGqXPP/9c69evd7xv1apV6tOnjxISEtxefrQMcUcdQyT01dXVjqvodZWuvo4dO6pdu3Zavny5du/e7Xh+9OjRio+P19q1a9WvXz/96U9/0uuvv67p06fruuuu0zvvvKMLL7zQY9sB39bSejhq1CglJibq559/1uHDhyVJ7dq1U3h4uL788kvZ7XbHrAwwHuJuXsTenIg7/Elr6nNycrJWrVqlLl26aOLEibr++us1a9Ys/eEPf9AXX3yhCy64wGPbgeYh7qjP60eeiooK3XrrrfrLX/4i6fQua1VVVZKka665Rps2bdJ3332nY8eOOZYdM2aMvvnmG1VWVuqGG27Q3//+d/3ud79T3759tWTJEseotMCZuKIeLl26VEFBQZKkTp06KSMjQ0lJSVyxMTDibl7E3pyIO/xJa+vz6NGj9c033yg8PFxz5szRHXfcoc6dOysjI0OLFy/WiBEjPLtBcApxx6m8PiheSEiIduzYoe3bt2vp0qUaNmyYampqZLVaZbPZHKPJdujQQRMnTtRHH32kjIwMR2Xr0aOHKioqtHXrVuXm5io7O1vZ2dne3CT4IFfUw6NHj2rPnj2OeYfvuOMO5pc2OOJuXsTenIg7/Elr63PPnj119OhRbd26Vd27d3fMxgBjI+44lVcT+urqaklSSkqKIiIi9Pe//13Dhg1znGkKCAjQ/v37dfvtt8tms2n+/PnaunWr3nzzTVksFg0fPlxffPGFunbtShKPFnNlPaw/lQcNPGMj7uZF7M2JuMOfuLI+d+7c2ZubgmYg7miMR7vc79mzR+Xl5ZLkmMZFkgoKCnTppZcqODhYCxYskFR7P8g777yjX/3qV0pKStJDDz2k+Ph4zZgxQ+3bt9eMGTP0m9/8Ro899phGjRrFARVOox6aE3E3L2JvTsQd/oT6bE7EHU6xe8CiRYvsI0eOtP/617+2jx071r5y5Up7ZWWl3W632wsKCuwzZsyw79ixwz5//nz7+eefb6+pqbHb7Xb7V199ZV+zZk2j61yzZo198eLF9v3793tiE+AHqIfmRNzNi9ibE3GHP6E+mxNxR3NY7PYzzHngAt9++63mzJmj6dOnq2vXrnrllVe0Z88e3XzzzRoxYoQqKio0atQovfXWWwoKCtLs2bNltVoVGRmpmTNnqlOnTqeegGBOVzQb9dCciLt5EXtzIu7wJ9RncyLuaC63d7n/6quvlJycrMsuu0y5ubl6/PHHVVpaqk2bNkmS9u7dq+7duys9PV12u11HjhzR8uXLVV1drU6dOp02FQMVEi1BPTQn4m5exN6ciDv8CfXZnIg7msvlCf22bdt05MgRSbUDN1RVVSklJUV2u111nQE6deqk1atXS5IiIyO1fft23XfffRo/frxiYmI0ePBgHT9+XNLpUzEAzqAemhNxNy9ib07EHf6E+mxOxB2t5bKE/quvvtLw4cP1xz/+URMnTtRnn32mwMBADR8+XBdeeKEqKysdZ4j27NmjzMxMSdLhw4clSZs3b9bcuXP18ssva+rUqfrpp5+0cOFCVxUPJkE9NCfibl7E3pyIO/wJ9dmciDtcpVXT1tXdk3Hs2DG98MIL+vWvf63x48frzTff1BtvvKFNmzZp1qxZqqmpUUBAgGw2m0pLS1VQUKAOHTpIkrp06aI5c+YoJydHYWFhkqScnBxde+21p90DAjSGemhOxN28iL05EXf4E+qzORF3uEVLR9M7fvy44/Hq1avtw4YNazBq4j//+U/7hAkT7J988kmD5X/44Qd7jx497Hv27DltnTabraXFgUlRD82JuJsXsTcn4g5/Qn02J+IOd2nRFfoXX3xRS5cuVXJysoYPH64BAwbo6NGjqqiocCwzatQo7dixQwsWLNCYMWMc8yZ+8sknatu2rdq2bStJqqio0Hfffaf+/fsrJibGBacoYBbUQ3Mi7uZF7M2JuMOfUJ/NibjDnZp1D31lZaVuv/12LV68WOPHj5fNZtNzzz2nF154QePHj9dbb73lWDYpKUljx46V1WrVa6+9Jqm2Aq5cuVIjR46UJL355psaNGiQFi1axAiMcBr10JyIu3kRe3Mi7vAn1GdzIu7whGYl9AcPHtTWrVt11113afLkyZozZ46uvvpqffTRRwoJCVF+fr7Wr1/vWL5Lly4aPHiwvv/+e5WUlCg0NFQ2m02HDh3SFVdcoSeffFIPPPCAnn/+eUVHR7t84+CfqIfmRNzNi9ibE3GHP6E+mxNxhyc0K6HfvXu38vLy1L9/f0lScHCw4uLi1LZtW2VlZen48eP64IMPHMtHRUWpa9euKi8vV3V1tYqKirR161Z99NFH6tu3r1asWKFLL73UtVsEv0c9NCfibl7E3pyIO/wJ9dmciDs8oVn30Pfs2VPnn3++du/erQ4dOshisSg4OFhbt27V6NGjVVpaqv/85z96//33NWHCBElSWlqafvrpJ1VUVCgjI0OPPPKIhg8frvj4eLdsEPwf9dCciLt5EXtzIu7wJ9RncyLu8IRmJfQRERF69NFHFR4e7nhu3bp16tixo2JiYjRu3DiVlJRo3rx5SkpKUnZ2tpYtW6Zhw4YpISFBkjRx4kSXbgDMh3poTsTdvIi9ORF3+BPqszkRd3hCs0e5j4qKavD3jz/+qJ49e0qSUlJSdNNNN6mkpET33HOPLBaLSktL9fDDDzeoyEBrUQ/NibibF7E3J+IOf0J9NifiDndr0bR1dfLz87V27VpNmjTJ8ZzdbtdDDz2kkpISrVu3TsOGDWt1IYEzoR6aE3E3L2JvTsQd/oT6bE7EHe7QrEHx6tjtdklSXl6eJOnCCy+UJC1YsEB9+/bVu+++q9jYWCok3Ip6aE7E3byIvTkRd/gT6rM5EXe4U4uu0NfNe7hlyxZ169ZNS5Ys0TPPPCObzabnn39e5513nksLCTSGemhOxN28iL05EXf4E+qzORF3uFOrutwHBAToxx9/1MaNG/X73/9eN9xwg6vKBTiNemhOxN28iL05EXf4E+qzORF3uIPFXtcHpAW+/PJLbdq0Sddee62Cg4NdWS7AadRDcyLu5kXszYm4w59Qn82JuMMdWpXQ2+12RxcSwFuoh+ZE3M2L2JsTcYc/oT6bE3GHO7QqoQcAAAAAAN7RolHuAQAAAACAd5HQAwAAAADgg0joAQAAAADwQST0AAAAAAD4IBJ6AAAAAAB8EAk9AAAAAAA+iIQeAAATOP/889WlSxfHv+7du2vkyJG6//77dfjwYafXY7fb9e677+rQoUNOv6e4uFgLFy50/P3b3/5Wd955Z7PKDwAATsc89AAAmMD555+vMWPGaPr06ZKkY8eOafPmzZo7d66sVqv+7//+T1FRUWddz8qVK/Xb3/5WX3zxhdLT05367NmzZ2vPnj164403JEklJSUKCAhw6vMAAEDTuEIPAIBJhIeHq02bNmrTpo0yMjJ0wQUX6JVXXtH+/fv10ksvObWOllwHOPU9sbGxJPMAALgACT0AACaWlpamUaNG6aOPPpIkbd68WTfeeKP69++v7t27O5J+SVqxYoWmTp0qSbrgggv0zjvvSJJWr16tKVOmqGfPnho5cqQefPBBlZWVSZLuvPNOvfvuu1q5cqW6dOkiqWGX+3feeUejRo3SW2+9pZEjR6pXr16aNWuWCgsLddttt6lPnz4aPny43n77bUeZ7Xa7XnzxRV1wwQXq1auXJkyYoMWLF3vmCwMAwEBI6AEAMLnOnTsrPz9fZWVlmj59umJjY/XWW2/pww8/1NixY/Xoo49qw4YN6tOnj+bPny9JWrhwocaNG6eNGzfqmmuu0bBhw7R48WLNmzdP69ev1/Tp02W323X33XfroosuUp8+ffTtt982+vn79u3Tp59+qgULFujpp5/WF198oUsuuUS5ublatGiRhg8frgceeEDFxcWSpCeeeEJvvvmm7r33Xn3wwQeaOnWqHnjgAf3rX//y2HcGAIARBHq7AAAAwLuio6MlSb/88oumTp2qKVOmKCIiQpI0a9YsvfTSS9q0aZO6deummJgYSVJ8fLxCQ0P18ssva8iQIbrpppskSe3bt9fjjz+uCy+8UCtXrtTAgQMVGhqqoKAgtWnTptHPr66u1r333qusrCx17txZXbt2VVBQkK655hpJ0jXXXKOFCxdq586dCgkJ0f/7f/9Pf//73zVy5EhJUrt27bR37169/PLLmjJliju/KgAADIWEHgAAkystLZVUe2/7VVddpQ8//FB5eXnavXu3Nm7cKEmy2WyNvjcvL0+7du1Snz59Tntt27ZtGjhwoFNlaNeuneNxeHi4UlNTHX+HhIRIkqqqqrR161ZVVlbqz3/+s6zWkx0Nq6urVVVVpWPHjik0NNSpzwQAwNeR0AMAYHLr169X+/btVV5ert/85jeKj4/X+eefr6FDh6pHjx4aMWJEk++12Wy65JJLHFfo64uPj3e6DEFBQQ3+rp+s11c3wN6TTz6pjh07nvZ6cHCw058JAICvI6EHAMDECgoK9MUXX+j666/Xhx9+qJKSEn322WeOBHvTpk2STibSFoulwfuzs7O1detWZWZmOp7btm2b5s6dq1tvvVVRUVGnvac1OnbsqMDAQO3bt0/nnXee4/nXX39dW7du1UMPPeSyzwIAwOgYFA8AAJMoLy9XUVGRioqKlJ+fryVLlui6665Tenq6rrnmGqWkpKiiokKffvqp9u3bp2+//Va33nqrpNru7lJtd3hJ2rhxo44eParp06crLy9PDz74oLZt26Yff/xRf/7zn7Vz5061b9/e8Z4DBw4oPz+/1dsQFRWlK664Qk899ZTef/995efn6+2339bcuXOVlJTU6vUDAOBLuEIPAIBJvPLKK44p6IKCgpSamqpx48Zp+vTpioiI0NixY7V+/Xo98sgjKisrU9u2bXX55Zfriy++0Lp163TllVeqc+fOGjFihP74xz/q1ltv1fTp0/XSSy/pqaee0qWXXqrw8HCde+65uuOOOxzd3ydOnKjPP/9cF198sf7973+3ejtmz56tuLg4PfXUUzpw4IBSU1M1a9YsXXfdda1eNwAAvsRir+tDBwAAAAAAfAZd7gEAAAAA8EEk9AAAAAAA+CASegAAAAAAfBAJPQAAAAAAPoiEHgAAAAAAH0RCDwAAAACADyKhBwAAAADAB5HQAwAAAADgg0joAQAAAADwQST0AAAAAAD4IBJ6AAAAAAB80P8HdbWbJfIW228AAAAASUVORK5CYII="
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 53
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-20T07:09:01.252087Z",
     "start_time": "2024-08-20T07:09:01.239542Z"
    }
   },
   "cell_type": "code",
   "source": [
    "df.pred = np.sign(df.pred)\n",
    "df"
   ],
   "id": "e9fbf0f826b80895",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "                       price   returns      lag1      pred\n",
       "Datetime                                                  \n",
       "2024-06-24 00:30:00 1.069290 -0.000107 -0.000321  1.000000\n",
       "2024-06-24 00:45:00 1.069061 -0.000214 -0.000107  1.000000\n",
       "2024-06-24 01:00:00 1.068833 -0.000214 -0.000214  1.000000\n",
       "2024-06-24 01:15:00 1.069061  0.000214 -0.000214  1.000000\n",
       "2024-06-24 01:30:00 1.069404  0.000321  0.000214 -1.000000\n",
       "...                      ...       ...       ...       ...\n",
       "2024-08-09 21:15:00 1.092061  0.000109 -0.000218  1.000000\n",
       "2024-08-09 21:30:00 1.091941 -0.000109  0.000109  1.000000\n",
       "2024-08-09 21:45:00 1.091822 -0.000109 -0.000109  1.000000\n",
       "2024-08-09 22:00:00 1.091703 -0.000109 -0.000109  1.000000\n",
       "2024-08-09 22:15:00 1.091703  0.000000 -0.000109  1.000000\n",
       "\n",
       "[3317 rows x 4 columns]"
      ],
      "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>price</th>\n",
       "      <th>returns</th>\n",
       "      <th>lag1</th>\n",
       "      <th>pred</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Datetime</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2024-06-24 00:30:00</th>\n",
       "      <td>1.069290</td>\n",
       "      <td>-0.000107</td>\n",
       "      <td>-0.000321</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-06-24 00:45:00</th>\n",
       "      <td>1.069061</td>\n",
       "      <td>-0.000214</td>\n",
       "      <td>-0.000107</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-06-24 01:00:00</th>\n",
       "      <td>1.068833</td>\n",
       "      <td>-0.000214</td>\n",
       "      <td>-0.000214</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-06-24 01:15:00</th>\n",
       "      <td>1.069061</td>\n",
       "      <td>0.000214</td>\n",
       "      <td>-0.000214</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-06-24 01:30:00</th>\n",
       "      <td>1.069404</td>\n",
       "      <td>0.000321</td>\n",
       "      <td>0.000214</td>\n",
       "      <td>-1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-08-09 21:15:00</th>\n",
       "      <td>1.092061</td>\n",
       "      <td>0.000109</td>\n",
       "      <td>-0.000218</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-08-09 21:30:00</th>\n",
       "      <td>1.091941</td>\n",
       "      <td>-0.000109</td>\n",
       "      <td>0.000109</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-08-09 21:45:00</th>\n",
       "      <td>1.091822</td>\n",
       "      <td>-0.000109</td>\n",
       "      <td>-0.000109</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-08-09 22:00:00</th>\n",
       "      <td>1.091703</td>\n",
       "      <td>-0.000109</td>\n",
       "      <td>-0.000109</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-08-09 22:15:00</th>\n",
       "      <td>1.091703</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.000109</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3317 rows × 4 columns</p>\n",
       "</div>"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 55
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-20T07:09:25.306879Z",
     "start_time": "2024-08-20T07:09:25.296430Z"
    }
   },
   "cell_type": "code",
   "source": "np.sign(df.returns * df.pred)",
   "id": "9d7fc3048e3a71",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Datetime\n",
       "2024-06-24 00:30:00   -1.000000\n",
       "2024-06-24 00:45:00   -1.000000\n",
       "2024-06-24 01:00:00   -1.000000\n",
       "2024-06-24 01:15:00    1.000000\n",
       "2024-06-24 01:30:00   -1.000000\n",
       "                         ...   \n",
       "2024-08-09 21:15:00    1.000000\n",
       "2024-08-09 21:30:00   -1.000000\n",
       "2024-08-09 21:45:00   -1.000000\n",
       "2024-08-09 22:00:00   -1.000000\n",
       "2024-08-09 22:15:00    0.000000\n",
       "Length: 3317, dtype: float64"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 56
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-20T07:09:44.759495Z",
     "start_time": "2024-08-20T07:09:44.739231Z"
    }
   },
   "cell_type": "code",
   "source": [
    "hits = np.sign(df.returns * df.pred).value_counts()\n",
    "hits"
   ],
   "id": "955d268caf543f88",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.000000     1393\n",
       "-1.000000    1216\n",
       "0.000000      708\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 57
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-20T07:10:20.130271Z",
     "start_time": "2024-08-20T07:10:20.110373Z"
    }
   },
   "cell_type": "code",
   "source": [
    "hit_ratio = hits[1.0] / sum(hits)\n",
    "hit_ratio"
   ],
   "id": "d06879902481d5d0",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.float64(0.4199577931866144)"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 59
  }
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