Normal_Disribution.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-09-19T05:03:57.008491Z",
     "start_time": "2022-09-19T05:03:55.822742Z"
    }
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-09-19T05:04:03.699494Z",
     "start_time": "2022-09-19T05:04:03.604854Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Last</th>\n",
       "      <th>Close</th>\n",
       "      <th>Total Trade Quantity</th>\n",
       "      <th>Turnover (Lacs)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>1121.0</td>\n",
       "      <td>1151.00</td>\n",
       "      <td>1121.00</td>\n",
       "      <td>1134.0</td>\n",
       "      <td>1135.60</td>\n",
       "      <td>101651.0</td>\n",
       "      <td>1157.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010-01-05</td>\n",
       "      <td>1146.8</td>\n",
       "      <td>1149.00</td>\n",
       "      <td>1128.75</td>\n",
       "      <td>1135.0</td>\n",
       "      <td>1134.60</td>\n",
       "      <td>59504.0</td>\n",
       "      <td>676.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010-01-06</td>\n",
       "      <td>1140.0</td>\n",
       "      <td>1164.25</td>\n",
       "      <td>1130.05</td>\n",
       "      <td>1137.0</td>\n",
       "      <td>1139.60</td>\n",
       "      <td>128908.0</td>\n",
       "      <td>1482.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010-01-07</td>\n",
       "      <td>1142.0</td>\n",
       "      <td>1159.40</td>\n",
       "      <td>1119.20</td>\n",
       "      <td>1141.0</td>\n",
       "      <td>1144.15</td>\n",
       "      <td>117871.0</td>\n",
       "      <td>1352.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010-01-08</td>\n",
       "      <td>1156.0</td>\n",
       "      <td>1172.00</td>\n",
       "      <td>1140.00</td>\n",
       "      <td>1141.2</td>\n",
       "      <td>1144.05</td>\n",
       "      <td>170063.0</td>\n",
       "      <td>1971.42</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Date    Open     High      Low    Last    Close  \\\n",
       "0  2010-01-04  1121.0  1151.00  1121.00  1134.0  1135.60   \n",
       "1  2010-01-05  1146.8  1149.00  1128.75  1135.0  1134.60   \n",
       "2  2010-01-06  1140.0  1164.25  1130.05  1137.0  1139.60   \n",
       "3  2010-01-07  1142.0  1159.40  1119.20  1141.0  1144.15   \n",
       "4  2010-01-08  1156.0  1172.00  1140.00  1141.2  1144.05   \n",
       "\n",
       "   Total Trade Quantity  Turnover (Lacs)  \n",
       "0              101651.0          1157.18  \n",
       "1               59504.0           676.47  \n",
       "2              128908.0          1482.84  \n",
       "3              117871.0          1352.98  \n",
       "4              170063.0          1971.42  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "beml_df = pd.read_csv(\"BEML.csv\")\n",
    "beml_df[0:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-09-19T05:04:19.211945Z",
     "start_time": "2022-09-19T05:04:19.143263Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Last</th>\n",
       "      <th>Close</th>\n",
       "      <th>Total Trade Quantity</th>\n",
       "      <th>Turnover (Lacs)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>1613.00</td>\n",
       "      <td>1629.10</td>\n",
       "      <td>1602.00</td>\n",
       "      <td>1629.0</td>\n",
       "      <td>1625.65</td>\n",
       "      <td>9365.0</td>\n",
       "      <td>151.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010-01-05</td>\n",
       "      <td>1639.95</td>\n",
       "      <td>1639.95</td>\n",
       "      <td>1611.05</td>\n",
       "      <td>1620.0</td>\n",
       "      <td>1616.80</td>\n",
       "      <td>38148.0</td>\n",
       "      <td>622.58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010-01-06</td>\n",
       "      <td>1618.00</td>\n",
       "      <td>1644.00</td>\n",
       "      <td>1617.00</td>\n",
       "      <td>1639.0</td>\n",
       "      <td>1638.50</td>\n",
       "      <td>36519.0</td>\n",
       "      <td>595.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010-01-07</td>\n",
       "      <td>1645.00</td>\n",
       "      <td>1654.00</td>\n",
       "      <td>1636.00</td>\n",
       "      <td>1648.0</td>\n",
       "      <td>1648.70</td>\n",
       "      <td>12809.0</td>\n",
       "      <td>211.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010-01-08</td>\n",
       "      <td>1650.00</td>\n",
       "      <td>1650.00</td>\n",
       "      <td>1626.55</td>\n",
       "      <td>1640.0</td>\n",
       "      <td>1639.80</td>\n",
       "      <td>28035.0</td>\n",
       "      <td>459.11</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Date     Open     High      Low    Last    Close  \\\n",
       "0  2010-01-04  1613.00  1629.10  1602.00  1629.0  1625.65   \n",
       "1  2010-01-05  1639.95  1639.95  1611.05  1620.0  1616.80   \n",
       "2  2010-01-06  1618.00  1644.00  1617.00  1639.0  1638.50   \n",
       "3  2010-01-07  1645.00  1654.00  1636.00  1648.0  1648.70   \n",
       "4  2010-01-08  1650.00  1650.00  1626.55  1640.0  1639.80   \n",
       "\n",
       "   Total Trade Quantity  Turnover (Lacs)  \n",
       "0                9365.0           151.74  \n",
       "1               38148.0           622.58  \n",
       "2               36519.0           595.09  \n",
       "3               12809.0           211.00  \n",
       "4               28035.0           459.11  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "glaxo_df = pd.read_csv(\"GLAXO.csv\")\n",
    "glaxo_df[0:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-09-19T05:04:59.694264Z",
     "start_time": "2022-09-19T05:04:59.676452Z"
    }
   },
   "outputs": [],
   "source": [
    "beml_df = beml_df[['Date', 'Close']]\n",
    "glaxo_df = glaxo_df[['Date', 'Close']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-09-19T05:06:24.549333Z",
     "start_time": "2022-09-19T05:06:24.520364Z"
    }
   },
   "outputs": [],
   "source": [
    "'''The DataFrames have a date column, so we can\n",
    "create a DatetimeIndex index from this column Date. It will ensure that the rows are sorted by time in\n",
    "ascending order.'''\n",
    "glaxo_df = glaxo_df.set_index(pd.DatetimeIndex(glaxo_df['Date']))\n",
    "beml_df = beml_df.set_index(pd.DatetimeIndex(beml_df['Date']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-09-19T05:07:47.507791Z",
     "start_time": "2022-09-19T05:07:47.483128Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Close</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2010-01-04</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>1625.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-05</th>\n",
       "      <td>2010-01-05</td>\n",
       "      <td>1616.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-06</th>\n",
       "      <td>2010-01-06</td>\n",
       "      <td>1638.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-07</th>\n",
       "      <td>2010-01-07</td>\n",
       "      <td>1648.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-08</th>\n",
       "      <td>2010-01-08</td>\n",
       "      <td>1639.80</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Date    Close\n",
       "Date                           \n",
       "2010-01-04  2010-01-04  1625.65\n",
       "2010-01-05  2010-01-05  1616.80\n",
       "2010-01-06  2010-01-06  1638.50\n",
       "2010-01-07  2010-01-07  1648.70\n",
       "2010-01-08  2010-01-08  1639.80"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "glaxo_df.head() \n",
    "# Date is used as a index of dataframe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-09-19T05:17:06.510435Z",
     "start_time": "2022-09-19T05:17:06.178825Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sn\n",
    "%matplotlib inline\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "plt.plot(glaxo_df.Close);\n",
    "plt.xlabel('Time');\n",
    "plt.ylabel('Close Price');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-09-19T05:08:36.840863Z",
     "start_time": "2022-09-19T05:08:36.487910Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(beml_df.Close);\n",
    "plt.xlabel('Time');\n",
    "plt.ylabel('Close');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-09-19T05:10:02.800554Z",
     "start_time": "2022-09-19T05:10:02.768121Z"
    }
   },
   "outputs": [],
   "source": [
    "glaxo_df['gain'] = glaxo_df[\"Close\"].pct_change(periods = 1)\n",
    "beml_df['gain'] = beml_df[\"Close\"].pct_change(periods = 1)\n",
    "\n",
    "#period is 1, since we are computing gain on daily basis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-09-19T05:10:10.784100Z",
     "start_time": "2022-09-19T05:10:10.763661Z"
    }
   },
   "outputs": [],
   "source": [
    "#drop first row since it is NaN\n",
    "glaxo_df = glaxo_df.dropna()\n",
    "beml_df = beml_df.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-09-19T05:14:20.203416Z",
     "start_time": "2022-09-19T05:14:19.551943Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Plot the gains\n",
    "#The figsize attribute allows us to specify the width and height of a figure in unit inches.\n",
    "# by default the figure has the dimensions as (6.4, 4.8)\n",
    "\n",
    "plt.figure(figsize = (8, 6)); \n",
    "plt.plot(glaxo_df.gain);\n",
    "plt.xlabel('Time');\n",
    "plt.ylabel('gain');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-09-19T05:14:41.614983Z",
     "start_time": "2022-09-19T05:14:41.154919Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgAAAAFzCAYAAABIJrEIAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/YYfK9AAAACXBIWXMAAAsTAAALEwEAmpwYAABrBklEQVR4nO2dd/wcRf3/X+9PS/mE9BDSG4EQQg+B0DuEiAjqT4pSlBIEUcBCUeErChEVREUxIIgoTUBqQgwlBKQmQAokISEJSUjv/dNufn/c7d7s3uzu7O7s7d3n3s/H4/P43O3tzs7uzs68592GhBBgGIZhGKayqEq7AgzDMAzDFB8WABiGYRimAmEBgGEYhmEqEBYAGIZhGKYCYQGAYRiGYSoQFgAYhmEYpgKpSbsCxaR79+5i4MCBaVeDYRiGYYrCjBkz1gkheqh+qygBYODAgZg+fXra1WAYhmGYokBEn3v9xiYAhmEYhqlAWABgGIZhmAqEBQCGYRiGqUBYAGAYhmGYCoQFAIZhGIapQFgAYBiGYZgKhAUAhmEYhqlAWABgGIZhmAokVQGAiE4jovlEtJCIrlf8fj4Rzcr9vUVEB+geyzAMwzCMN6kJAERUDeAeAGMADAdwLhENd+22GMCxQoj9AdwKYEKIYxmGYRiG8SBNDcAoAAuFEIuEEI0AHgNwpryDEOItIcTG3Nd3APTVPZZhGIZhGG/SFAD6AFgmfV+e2+bFdwBMCnssEV1GRNOJaPratWtjVJdhmEpn3bYGbNjemHY1GMYIaQoApNgmlDsSHY+sAPCTsMcKISYIIUYKIUb26KFcEIlhGEaLkb98GQffOiXtajCMEdJcDXA5gH7S974AVrh3IqL9AdwPYIwQYn2YYxmGYRiGUZOmBuB9AEOJaBAR1QE4B8Bz8g5E1B/A0wC+JYT4NMyxDMMwDMN4k5oGQAjRTERXAZgMoBrAA0KIj4loXO73ewH8HEA3AH8mIgBozqnzlcemciEMwzAMU4akaQKAEGIigImubfdKny8BcInusQzDMAzD6MGZABmGYRimAmEBgGEYhmEqEBYAGIZhGKYCYQGAYRiGYSoQFgAYhmEYpgJhAYBhGIZhKhAWABiGYRimAmEBgGEYhmEqEBYAGIZhGKYCYQGAYRiGYSoQFgAYhmEYpgJhAYBhGIZhKhAWABiGYRimAmEBgGEYxsVX7vkfnv5gedrVYJhEYQGAYRjGxUfLNuHaJ2amXQ2GSRQWABiGYRimAmEBgGEYhmEqEBYAGIZhGKYCYQGAYRimhHhi+jJs2dWUdjWYCoAFAIZhmBJh9vLN+PGTs/CTJ2elXRWmAmABgGEYpkTY2dQCAFi3rSHlmjCVAAsADMMwDFOBsADAMAzDMBUICwAMw5QsU+evwcI1W9OuBsO0SmrSrgDDMIwXFz34PgBgyfixKdeEYVofrAFgGIZhmAqEBQCGYRiGqUBYAGAYhmGYCoQFAIZhGIapQFgAYBiGKRGEEGlXgakgWABgGIZhmAqEBQCGYRiJNGfhRJTauZnKgwUAhmEYhqlAWABgGIYpEdgHgCkmLAAwDMNI8BjMVAqpCgBEdBoRzSeihUR0veL3YUT0NhE1ENEPXb8tIaLZRPQREU0vXq0ZhmGSgX0AmGKS2loARFQN4B4AJwNYDuB9InpOCPGJtNsGAFcD+IpHMccLIdYlWlGGYZgiwSYAppikqQEYBWChEGKREKIRwGMAzpR3EEKsEUK8D6ApjQoyDFN58BDMVAppCgB9ACyTvi/PbdNFAPgvEc0gosuM1oxhGCYF2ATAFJM0lwNWtfQwwveRQogVRLQ7gClENE8IMa3gJFnh4DIA6N+/f7SaMgzDMEwrI00NwHIA/aTvfQGs0D1YCLEi938NgP8ga1JQ7TdBCDFSCDGyR48eMarLMEwlkKYdnn0AmGKSpgDwPoChRDSIiOoAnAPgOZ0DiaieiHazPgM4BcCcxGrKMAzDMK2M1EwAQohmIroKwGQA1QAeEEJ8TETjcr/fS0R7AJgOoCOADBH9AMBwAN0B/CdnL6sB8IgQ4qUULoNhGMYY7APAFJM0fQAghJgIYKJr273S51XImgbcbAFwQLK1YximEmElPFMpcCZAhmGYEoF9AJhiwgIAwzAMw1QgLAAwDMNIpDkJZx8AppiwAMAwDFMisAmAKSYsADAMwzBMBcICAMMwjIRIMQ6ATQBMMWEBgGEYhmEqEBYAGIZhSgT2AWCKCQsADMMwEjwGM5UCCwAMwzAlAvsAMMWEBQCGYZgSgU0ATDFhAYBhGKbEILAmgEkeFgAYhmFKjDRDEZnKgQUAhmGYEoF9AJhiwgIAwzCMRJpmePYBYIoJCwAMwzAlBvsAMMWABQCGYZgSg30AmGLAAgDDMIwED75MpcACAMMwTInBJgCmGLAAwDAMo0ExHfRYC8EUAxYAGIapGLY1NAfuk6YjPocBMsWEBQCGKRN+M3keLnrwvbSrUbY8+9EXGHHzZHyyYkuk44shGHAYIFNMWABgmDLhntc+w9T5a9OuRsnz349XoaG5pWC7de/mrYooAMSqVTjYB4ApBiwAMAyTKh8u3YgH3lxspKy3P1uPyx6egd9Onh+5DK+Bnn0AmNZGTdoVYBimsjnrz28BAL591KDYZW3Y3ggAWL5xZ+yy3PCQzLQ2WAPAMEyrwZo5J+FLV0zzPJsAmGLAAgDDMK0Ga5CO403vpepntTzT2mABgGGYVkMmN3iX+/yZhQ2mGLAAwDBMqyOJeHqO0GNaGywAMAzTarBNAHHKMFKTeLAPAFMMWABgGKbVYKnOq8rcCZBNAEwxYAGAYZhWQyaT/Z+ICaDMBuWdjS2cWZDxhQUAhmFaDdZwF8sE4DFmllMY4NL1O7DPz1/Co+8tM1QjpjXCAgDDMK0GYcIJoBXw2bptAIDJH69KuSZMKcMCAMMwrQZrkl6lMAHEVYcXU5ke29zAmn9GAxYAGIZpNQgTeQA8TQA8qjKti1QFACI6jYjmE9FCIrpe8fswInqbiBqI6IdhjmUYpvLIZwIs/C2uYyCvBsi0NlITAIioGsA9AMYAGA7gXCIa7tptA4CrAfw2wrEMw1QYeSfAyk4ElOSaCEzrIU0NwCgAC4UQi4QQjQAeA3CmvIMQYo0Q4n0ATWGPZRim8rAG6aokejaDAsCaLbvw0pyVPqcKd7I7p3yK1+aviVstpsJIUwDoA0COUVme22b0WCK6jIimE9H0tWvXRqoowzDlQUbEDwT0GnxN5gE47/53Me6fH2BXU4uR8v7wygJc/OD7RspiKoc0BQDVG6r7hmkfK4SYIIQYKYQY2aNHD+3KMQxTXNxOdlGc7uzhv8RV38s27ADgbVYwZcIo8dvApEyaAsByAP2k730BrCjCsQzDlCBGbOw+UQC6AsWEaYv8ijZCqQsoTGWQpgDwPoChRDSIiOoAnAPguSIcyzBMCWJk/M/9V+UB0OXPUz/zLZthWgs1aZ1YCNFMRFcBmAygGsADQoiPiWhc7vd7iWgPANMBdASQIaIfABguhNiiOjaVC2EYxgjZGTpJ36OUkf2fSBhgGYUBlFFVmRRJTQAAACHERAATXdvulT6vQla9r3UswzDlixkLQHwTgGfZsY72KjPZkTqJRZGY1gNnAmQYpiRwj89RhsaMrQEo7TwAQU5+5bbyIFOesADAMIwRGppb8KU/voH3l2yIdLyJQc8vCqCSZsNsAmB0YAGAYZjYvLtoPT5dtQ1zvtiCnz0zJ1IZBRoAxSh23n3v4Lz73vEpwzIBJKABSGBWnnQYIMP4kaoPAMMw5c8HSzfiGxPewfF7J59n463P1mvtl8hkn8MAmVYGawAYhonF2q0NAIBPV2+LVY4ZHwADqwF68MnKLQmUmiwsZzB+sADAMEwsTA0yRnwA7LUAzA99FyWQapdN9UyasAmAYZhYWM519uw7on670AcgQhlWnZTl+xd47RMfYfG67eFPGoGkZ+YsWDA6sADAMEwsrMl2XM9zg5mAI42wT3/whYEalBbsa8D4wSYAhmFiYQ0ycVX4BYsBRSgv4xMFUIphgOWUXTANxj08A6/MXZ12NVotLAAwDBPIum0N+MmTs3yXry0FDYCFygWglAZbk8JIKV2XaV76eBW+89D0tKvRamEBgGGYQG57cS4en74ME2evLPgt7wMQrswPl27Eum0N9neRcf4ebS0Ayw8h/LFpYNTs4djWeoUCxhzsA8AwTCB+wwlp7VXIWX9+C707tZWONhcFUD4mAANlxC+CqVBYA8AwjBHyg68+KzbvKjg+Dvm1AOKXlSQmq8ezfSYqLAAwDBOLqtxoG3cYMqIOh3coYkkOlAaFHnWxzvvw8ier8dKcQjNOKVKSz6uVwSYAhmFiYY21mZgddkEUQCQfgFydYtWkvAhjOrnkH1mHuiXjxyZVHWPw+J88rAFgGCYWlr29FKIAym01QJN+DwwTFhYAGIaJhZ0HILYGwPU9wuDotxpgSamUDSVPMlVGKdJKL6ukYAGAYZhYWENtfB8Ag1EARZjs//X1z/DWZ+uSP1EAcU0vpUpJCWytFBYAGIaJh2s2G3nwNbIWgPdqgKZNALdPmofz7ns3VhnuS3R//9ubi/Hh0o2ex59y1+t4/P1lnr+XoNVDGx7+k4cFAIZhAvGbjeV9AGKaAAK+a5XhsxpgOc4ob33hE5z157c8f/909Tb84oVPilij4hHmcW3c3ojbJs5Fc0smeGfGhgUAhonBXj+dhEseMr9MbKmidq7L/o9tAijQAOiVOHv5Zvx28nwA4bMRpo37Go0trWzoPnyxaScGXv8ips5fY6bAEIQxCd36wieYMG0RJn/M6waEgQWAVkZzSwa/nTwfm3c0pV2ViqCxOYOX5xa/cywlbB+A2FEA7sWA9DjjT2/iT68tdJQRJgpgV1MLPl6xWbuecXlr4Tps3dUMIHk1d1yB4qOlmwDA18xQCuz0WaOC8YbzALQyXp23Bn96bSFWbNqJO79xYNrVYSoAS90ePw+A63tIba4Qwh5Rw0QB/OSpWXj2oxXhThaDnzw9y/O3UlNgkMFohbCEOWdLTvVTzVPaUPDtMsSuphbc8tzH2LIr3Zm3lZUt7XowlYO5KAD39whhgLn/qtUALdyKgOlLvJ3skqBKqkAZuiWUJJbwWV3FQ1oY+G4Z4rH3luLvby3BH19ZkGo96mqyj7ShmZ1hmOJALgkgque5e4Ye1p4vBJDJBK8GaGLQHXj9i5GPdQgASMYHwJQuIf9oiy+plIoG4MkZy3HFP2eYL7gEYAHAEI0579O0Jfo2lgDQxAIAUywSMgFEKM/OBFjCqwH6Cic+x23Y3oirH/0QW4uo3UvVBBBC6Gixoj8SeMY//PdMTJqzyni5pQALAIawok+q/XSPRSCvAWCnmNbMS3NWYltDc9rVABBtxq8a3N2bQmsApDJUdfISKIodHugYpHxO7a7XH19dgOdmrsAT05crf08GMws9RSHM5WVsDUBpCHnlAgsAhsjboNJtgNb52QTQepm3agvG/fMD3PD07LSr4iC2BqAgCiBceUII39UASwVf/wTpc4tLAmrKzTLqqvXXXoh7G0r4NjqwTQDlUuESgQUAQ7SUiARq9RmNLABg884m/O3NxWWZAMaP7bmZ/xcbdxTtnH530Lq9Ye6y6pEUmgBCFAjgogff9z0mjlBgcgldpw+AN24NSHNOz11TJFf3TTsacfnDWdt3OiYAfaz+V5UAivGGBQBD2A0wZQnUGuyKoQGY8fkG7GwsXVPDz5+dg1tf+ARvf7Y+7aoYJU15RmVbt7rqMPVS7VoQBRDyOt9cuM5X2PM0AWiU/a93l4arjA/kEwUgf3VrVCw/o9qcAKAjlMVhwZptHjUrDmEE95YS0cCGZd22Bhw5/lUsWL01lfOzAGCIUtMAJO0DsHzjDnz1L2/jpmdKSw0tsymXDKmhlaUHzYe6Fb+t6ajl1UKCqxylD4A7CiC6E6Bv6mJX9YotUOl2Ee7rb7I0AFX6qZd1noUXcj3LRgNQZiaAV+auxhebdmLCtEWpnJ8TARmidCTQnAYg4SiADdsbAQCfpiS5hqJ1WQCKuuKdhd+pTA0OhXkAIpShcVCUZYeDzAfPzVyB0YO7ocdubQLL0g0DdJsA4nQtP3tmDrp1qLO/b2toRlNzBl3q6zyPSduPIpQTYMn0v+GII6CZgDUAhsiUiAQqbA1AsgKA5WNQx6m3ik4Y1eik2SsTTwoVaaBWbXNHAURI7B9Wa/DMh19g9ZaGwP383ur12xpw9aMfaq8JoTuzdjsBWg5u1vYwV/rwO5/j9y/nc5Qcc8drOOjWKQH11PNVSIwoeQDKTAOQNtx7G6JUUlHaToAJq71tAaCGm1BaBM0ePl+/HVf86wNc89hHxalQCNQDX/xhRqcEeYzQzXHvN6405166lZt3aZXlV5hc/4KFgkg/30LQHpYGzw+noFLaajS3sFRupFV77r0NYZkA0tcAFKcpNdgCQHVRzsfksZ9wQFOzFkhZlnC0QJQmp1K7x40CkI/xO1b+rUNbPSuo361uDjn4OAZWn/28TACWAJD0q56WBmD+qq3IZISWacbCviflZu9LWWGRqgBARKcR0XwiWkhE1yt+JyL6Q+73WUR0sPTbEiKaTUQfEdH04ta8kFJJRFEsQdgSANqUoAZg/qqteHGWubCtUsPq7IJaWrHsi5Ey9qnCAF3fo+UV8HP+K7wfHdroCQB+gn1DTtDSlf391NTWL+8t2VCwwl21vehS9nvSg10ac5mZyzbh1N9Pw1+nLYqUCrhcSUvBklrvTUTVAO4BMAbAcADnEtFw125jAAzN/V0G4C+u348XQhwohBiZdH2DKBUnwGJJwJaJoRRNAKf+fhqufOSDtKuROOVi7nz8/aVYsm574H5+IXG6ZDLWscFRBgBQ30ZPg+V3ry1hWFfgci4G5KyT/O3Xk+a56hDCBGDAUTSNRYtWbNoJICsIhDmlLRSVtxxQdNLsvUcBWCiEWCSEaATwGIAzXfucCeAfIss7ADoTUa9iV9SPgde/iBv/M7tkUgEXSwNm+QC0KbLTQyYjcOpd0wpm+M0tGbwwa0XJ2yqNEPISTdwS35hzn99aMgI/eWo2vnbv2xrnMBEGGO6Yek0NgJ++xXoXdAdbRyZgn+oud5lurFfN0ja2RhOALOSEygNQ5hqAtIT5NAWAPgBkD5zluW26+wgA/yWiGUR0WWK11OCRd5fmTQApT8uK9R6k5QTY2JLB/NVbce0THzm2/3XaIlz1yId4oRWr/i108wAk0RR1Zrnyea18FNsanJEISWQClI9RHas0AdRp+gD4XLbscHvuhHdw87NzcOxvXsOOxsK1Gm54ejbeXbzB+zw+dahyRQEkjSxMqQbjtxauw+UPTzcqdOf9HKLlAZCP+e6/ZuC+lOLrw5LWvCXNPADeKcX09jlSCLGCiHYHMIWI5gkhphWcJCscXAYA/fv3j1NfX2wnwAoxAVgde6n4AKzKeWBv3BHs3ezHum0NGPnLl/HIpYfhiCHdTVTNCHInm0YeAC+WbdiBLTu9wwytfBRtXM6iek6AUTQAPr8pymtXp2kC8PnNukYC8Pai9Xh7UTbz5NyVW3DIgK6Ofad9ulbrfKaI00a8bv/9byzClp1NmPDGIuxqymBXU0b7PgZhCTlhnn1Dcwu+yJkOZCbOXoWJs1fh0mMGG6lbEqT9CqfZey8H0E/63hfACt19hBDW/zUA/oOsSaEAIcQEIcRIIcTIHj16GKp6IawBKC5RL3Puyi1Ys9U7XOuDzzcCAB54c0nEMySD/FxLydP56Dtew2UPe6+VvisnKPq1E7Jnfd72cF101iWQX1HdZDd+2pbGFssJ0LmPEMCWXU2OZFlVAa9LmGtOetboZYL55Ytz8YdXF9r3JO4iUDLW/cmaAPSOufHpOfbnZz78Amu3Bud1iMMXm3aiuZVkF01TAHgfwFAiGkREdQDOAfCca5/nAFyQiwY4HMBmIcRKIqonot0AgIjqAZwCYA5SxIQToBBCKz43qIxikJYAEPfyxtz9Bk747eva+5fKkrtKDYDm/CFui9jZ2IJnP3LL5nrkNQDOdqLzHJPyAZCL1X1ffE0AuXdBVda4h2fglLum2QNGHDOHuwoFWQQNzz2c96nw9yQEAKtNZ00AeuW+/dk6+/Pf31qCb/9dLyFTFNbncvf/8sW5RstNS6hPTQAQQjQDuArAZABzATwhhPiYiMYR0bjcbhMBLAKwEMB9AL6b294TwJtENBPAewBeFEK8VNQLcGHFAscxAfzj7c9x8K1T8NnabcE7e1CsZpRfmlSt+hNC4JMVW4yfN6izmfLJavuzV4eoN6gLvDRnFUbcPBkzl23Sr2BCqDQ7xVI2rdxcqF7VxStcVL4c6zKKlQcgyjl0ogDcz0gAmPPFZgDAso07cf8biwqyG/qlAg6LfKzpAUVVnnU+Ha3j4nXbbTOdL2SdD9qdmfv8budJk2zOmbumzl8T6fgVm3Zi3qp8v5h2uuVU1wIQQkxEdpCXt90rfRYArlQctwjAAYlXMAQmTACv5RrV5+u3Y0iPDpHKKFoioJwAUFOtvt5H3luKm/4zBw9/ZxSOHmrO9OJ1dVYH9c6ieCv/yS/kq/OywsTclVtwQL/OscpVcfvEuTiofxecNmKPwH0dDlkhzxO3i4mj5dnVZJkAXD4AUjslIkAUJn6JpAHQWSBHuiG65/DTtlhluMvKZATa1lZjy65mjJ80F5M/Xq063EEcE4BqMImTCyLo3lin07nnx/92KgBgyfixvvvJPgC698K9p7VschLEHbCPGP8qgOD7UCx4MSBD5Fejil9WnJe2WN6kQYsNffD5JgAh0qNqYndKHtfZpHj5ow0k0uy1NhlF2V9zHso6nYFKba3bGcVtEmFvn1wrHQ2A13miZRi0/nsf7LiXugX73GrLHOw3E964Q+0oGeYa3bvqeEzHQa5bRvG6W9pOk1EJVbZQEV2L06SqrGGMd7MpufWUhgt3K8CEHczE4F0sJ8DmjLfdE4AdAlWvGWali9c98p+hRTuXNXttahFYrJHIJkmiDFqmBgTnucPdTOse+kWL2CYAn/Pq4neMSmDS1wB4k4/L93Zi9FrYSOfsupMK3fwCusj3RvXc7bBEo2GA4f0K3HsmqgGwzmnoFPKjPeaO1/D3/y02U7AmLAAYIsoKXW7sY2OF7qhr0NDckoh5wKvI7Y3Zjr+9T6a1nz0zBw+/83nI83l1pIXbrV2jzlCs2euPn5xlqzDTwnF9uY/Fsh7KnXFtyMRPDR7Oouo8AP72cR388uSr2o7uK+EXBZDPQ+9ddtj1AmQswaXACdBVeVOpn3c1tWB7Q7NTgFFU347Zd024MxmBO16ah9Vbwmv/5IgQ3efvfoaqey2EwFMzltu+S0DWj0m+hy0ZERimaZs9EpiyL92wA7c8/4nxcv3QepuJ6EgimkJEnxLRIiJaTETlkWGhSJgUOuO8xqpqbNrRiL1/+hL+8vpnMUrWPx8AbM852rX1WSzo4Xc+x8+eCRe8EUVlGkbwcaivA8wcxUQVBlgs/6GoTbslIyQNgKsdSIXmO1XXLoY1AO7zZffX1AD4mQByZbgFTQHhGeLodX7huC/OgT/IBGBKIjzpztex782TXZEnhfUnDw3Ah8s24s9TP8M1j38U+tx5DUCY5x+84/OzVuK6f8/En1/L9oGbdzZh6E2T8Oep+T5xwrRFuOCB92zfHxWm19d46oPlAFKzAGhrAP4G4E4ARwE4FMDI3H8mh4n0nCZm6KoyLDv8cxFDufzPp95uCQCmJWWvjlT1Ylr3IoqKUiCf7MhdXhqowwDDHxuFjOLcQWzd1YQhN07EXS9/CkDlAxA8G49iVmvWsP86bNuap9AxARTUV/oax06uu8Kocq+AQ1X1Wr4xG/URdJ/yGgDnj9ZXS/sThkhOgBo7btuV7Y+siBYrV8BTM5bb+3y+Pmvm+2LjTkfuBpm846Nm5QJ467N4Tstx0RUANgshJgkh1ggh1lt/idaszDDpCBPH01TVMJsCPPbjnMfrNd2RMwGYHjO9ilPVI++dHe1cu1wagBE3T8Zpvy9INlkUHBoASwAoUipgh/CheczRd7wGAFi0Ntup+vsAOOe4zS0ZPDF9WSQBQOUE6od+GKD3zbTffe/x37N/0Do9Of4BAP7+v8V4a6GzC47yvF+blw9nO/NPb+LOKZ8q66Z6Fl6pifN28vDPz5EKWPN4nb1qc31fQftQ+E3cPmkeTrlrGpZt8A4nTHEuYBRdD63XiOg3AJ4GYKdZEkK0/iXXNLFmmWlnaVP1M5YAEGS/nTh7JQ4Z0AU9O7bVPp8QwMcrNmNnYwtGDsynPbWcAE0mCZHL07nP1mTQywHLD0KhBmB7YwvmrVLPDMISunNU7F4sHwBVBIL7swMibHJ5vbsjKdQ2+uz/+99cjPGT5uEbI/sV7hRAU4u/c2quejZGnACFuiz5q6cAUCA0KFTt9m95VLZiWQtm7fvirJX42iHeMevbpfUKZi7fjJnLN9vf5fdGrQFQmwC8TDphCJMJUOddsnxQmjQy+FmTl007mtDPmck5VOgjANw+aS6O2rN7YCh0WtpFXQHgsNx/edldAeAEs9UpX6IMMl7E8wEorEdjc3abnwDQ2JzBd//1AQZ2a4+pPzpe4zz5/2P/8CYAZzjb9obsS2Q8KsFV3qYdjfh8vVpSd8dnh3lGWRNAcj4AYe9LRjELD5rxBURMhjh3YZlAOK1XXbVPGKBrwFiXU89GWdehUeOZRYqo0HACVCZrQnRPeWtQ0DUB7GxqwZJ12zGwe71j+798HG392rhcY78BqvC9stT42W9h2ondr4S4XXoaAH8B4OZn5+Dx6csc21Rpm8O+U399fRH++vqiwFDftBYz1DIBCCGOV/zx4C/RbMAHwAR+GgB3JyxjCQ7uRTU2eXTCQvGmbpcy7FnnNK8BcH4/9753ceY9//PYN7tzi5eNVoFzJbvkBICwJiN1Z+w/MJi6884kRP6zQi+qq6rw1sJ1+MZf30ZLRr3Ua1DnqjO4N3mk3PXCiBOgR/uS75X38w7XJoP47yerCrZ1bl/nub/fPZWvR2kCyHUnbq97twZAZ9ZtYbeBMGGASm2Sc6OnACCyAsxDbxcKSW7BK8lZuslQyjD4CgBE9M3c/2tVf8WpYnlQKnkAVI00bwIIp1v438J1OPAXUxx2Qvd55LPte/NkW2AIqyrTxa3hmLvSO92wWzUb5iUTIu/B7oXbRBCG0AJABDu8qVsv+9U5HcP0T0AEXP3YR3h38Qas3+ZcrMVqlTf9Z7bjHHLpTS0Z7PXTSfZ3K8Wumw+WbtKqi4WJ99Z2AXCr8zXulc7pdTUAgDoEzi+PgK+QK9dfsZvXoGqfLndx4QSAvDYl6N4IITB+0jw7Pa+M+zZYfV9jzgdAvqVeqdcLBQD/MNM4TFX0scUgSANg6ZJ28/hjcpjIA2BhOrxra84Ddre2tZ77qBr0h0s3AgCmf164frnw6PTW5xYzshf1MDyJ9ups1fs6VbNh6+LVOc74fAN+9eIn2Pun0Zef0PFWl1E7AfofE8UfpaklU6D1ca4LL9cphAAAwFJAtbg8vK3rWLBmW8H5LNzP4kt/fNP3fH41E4p7GYTfIOqVClj+pv24lWYE538/VEmJ/ELX/DUA8ufCilkaRXcZlrkkrwEIbwLQyQOwvbEF93qENrvraw3mTc2FGqKtHmuDqJ55kPNzVKy8KcXG1wdACPHX3P//K051yhcTUQAmGpXqRbVsqZ3bBwsAup2jVVfPxUwC4p+j4qVRUN1+a1sYE4CMV+f41b+8HaocFWGFEed9zs1igo6xzTT65/n+Yx9i4uxVDpule9C/9YVPcMHoAeha761adkOUXyejJSMgBwW4Byh1W4zfjtSZADWP9cs06WUCEPk8AF4Cn9bpQzjVqSbbfksQ+wkAXoKfhaUBcAtn7mx5UUwAOhoAv3VXCnMyeNSFvNuWe2E3AVlA8a9buaCbCKgtEV1JRH8mogesv6QrV04ksSRmFFTVsDyyO7fzEQBCCh9BM/GqCAKAECJwpT6ruOaMcLzMaptydtvkj7N2UdkE4LWed1Tty8rNO0OtQx5WA6ASzHSdAMMwcXahDVkuZ96qrfjbm4txxT8/8OwEVdUSIt+hCuHtV+BF2A7XqvPCNdvs9KrKNqLZ7v3udd7U5C47j98YuGVXE1Zs8l5xMYwJoEXZrryP9zNjBWl7LM/6G56e7TybK1teKAHAmliI4Ceju94DkK+/qi5ebUvlA6AriC5YvbUkVhENQjcPwMMA9gBwKoDXAfQFYCYeqpXQrFC9bdjeGGppXxMyhNyYrWQWlo2svo23wifsub0ctogIn6/f7ljXW5f73liEETdPxpqt3ilE5Y7om/e/a39WaWCsXd9YsA4L12yDkN79IAe/sI9i9O2v4tBfvay9f1inH5XnepCgGEej5AwBK/ycESJ05IsjbtxH06QabKJqAL5yz/9wy/OfOFXiithvP16dtxqPvb/M83fP5Wc1zCVCACf+7nV7lTjVXlZ9vTICypj0AQhyArTs6ktd8fLkigIIlZsht+uyDTsCnT79np37/bKef6NdF+naPNqx6rbpmiBPvmuap3NyKaErAOwphPgZgO1CiIcAjAWwX3LVKg+EqleWOPF3U3Hi714PXW4cHwC5Tlb4j2UCENI+7y/Z4NjXK5+553lsSd25ffqSDTj2N1Oxs8kKA9R/+a3Z57IN3rMhubh3F+d9E9QmgPzGLbucjkJhZiUm2d7QDCFEaJOR6j4GtRMrPDMKcgfqMD5oDGoqBIBqa/W4gs45//nNBeuUnWtoDUCu1pZGya1BeebDL3DD07O0BIsr//Wh7+//lrLJqeoAeGucBISn5igoFbAKVbvy0yDs9HF0lUv6bG3hYlheYcVytjwhhFb0hoVV/e2NLbj+6VkB+3rfEa+cDPnopPxvusK4s4dMzgZQzJwAugKA1XtuIqIRADoBGJhIjcoIEdCIvJYA1SnvuN+8hm/97V3vnb3KkD5bdbJMAFb5/56xHF+/9208P2ul8jg3ypmmrQFwHunuKMJ03JZKcconq/FPj9hlr5detV0+d3OL06koDRvehu2N2PfmyfjTqwtDr1jmNQiHPVaXFg8NwII1ecVfWC1GfqlXZ6txaHX+9q5ScxG3U3Qf/YPHP8Kj7y3TagdRBXIh8oN3nPam8kb3QiUAqOrfp3M7AMAOH5Ob+567Iy/8wooB4JOVW7DvzZNxqmb2zOaWDJ6b+YX9/cOAiA6/W+qVntgSAOT75HU/P1y2Ec9+lK9PdtLkf0wYvDQPftom0+gKABOIqAuAnwJ4DsAnAH6dWK3KBPnxmViC0l7kBcCS9TvwxoJ14cuQWqY16XBL+UtziXOufvRDWzoXISfEdqftumy3ujFMx211KPe+/hl+6rFIkFdpqtPI525uyTgFNk+1X3L59SzTxguzVob2GXGGAWY/h7ENh8XZQeY//09KPxvmEoSQTQD+moT81+gCW4E93sMEsHVXsJBu4j57tTfZZL92a4NSMxXm9GoTgMr5Mbvf9sYWzPh8ozKc1v183dkdgzQAQD6rnsXA61+0c+67+dubi/HEdLU2RYVf+3PfBtsHoNmZn4TgPam45vGZ+P5jH9nfz7vvXbyeWy3QxPxh1G2vKLe/GaHfj4quANAJwMXIZgK8B9nBv5mIDkyoXmWB3Kk0hkxA4kssE0D+s1vCzA8c+W3uRXvC5t927+3ua8IMdO4lY5XnDaUByG9rct+LgHqZeI7XPzULA69/Uflb2OVh5frYNtcExv+813rwDCmcCUDkTQAZf22MqtS4ERzuMErrOq2FsvyIept1BE75ug791csFDnVAYfSC353Q1QBY593R2Iyv/uUtjLn7DcU+PieC9/saJEQf+5upBSY5ANpOtOu3NeDCB94ryCcho4rIAPI+AE4BVOu0APLvnqr/eH7mCgy8/kVs1tD8rtm6C+s86l/MdPK6AsAhAMYB6AOgN4BLARwH4D4i+nEyVSt9HGrMXCt6bf4az9hUi627mnyd1uLgZ9uyvsrhLVETW+RVYc4D3bONMM7uOomKvOr5rGKlQ6cJION4Xqqc/o++txSPvLc0sA66eKny5q/eilue+zhUWfJ13/HS/JDH6j9c1QIvXh2kpxbF4zHml3rVE750BlAv3AKAu1Pt0aENAGCVhgAQVQKQz+hlLnFHvcgCifXc3Ke/9QXvNeObMwJzV27B0x/kVddqDUD2v5WyW0VQu5E1ALJ5QEdjYeUmkXGH3Xnx0FtL8Pqna/GwT4rjIBNAkIMjoF7Aynb2Vux//5uLAQCL1gU7fi9Yre8cniS6AkA3AAcLIa4TQlyHrCagB4BjAFyUUN1KHpUa89mPVmD8pHmex+xqasF+t/zX9yWOFQbo8m59Ze5qvCc5ywHO+Flr77BOgF6Cg3u2Ek4DUB24T5hxQO4E3J7IFzzwXsH+Nzw9G1M+8V4LPC7ycw1r3lE6AcauUSFWH+xlApAJawJwaAB8j/XX5uhQuJRz/jMR7BwGazRmnVFNAE5znLr+qix2btZsbdCOJspkBMbc/Yatqga8EtrkNQBeBN3xupp8wXJiJp3bpdpF9zbXeCQgkvE0ASicAMMIyM0+mt6aqkLh2eJLf3zDESXk156L6AOoLQD0ByCnB2sCMEAIsRPS6oCVhp8a0+vF3pmzif3nwy8KfjPx3N2OibKUbC8uImsAfCRav/p4mgB86hOElgYgxF2SX7JdTS2+L7ppz9tFIcI/dVDVLs6y0V6Y0AB4ll2V1wD4ti3FjzqqepkCDYCrTEsY8fLOl4l6m3Xuj+49fFtz3XiVackvAVIcDcCSdc7wv7zGIviGqe6prqBVqyEAuDUufk6AXlpKVXWabRNC4b2pVrw7FnO+2OIwcZRKIiFdAeARAO8Q0c1EdDOA/wF4lIjqkXUIrEj8HJm8YoOtvfzauvxbUGKcwjo5Zx2qFLLyixYmta7zRHrHhZm5tdHRAIQwKcidwHafmQ4AbNnp/D1soh43J0QI//RDVwPwzIdf4LonZkY+j2qJV6/hOsyzfW3+GjsxSnap1+AZkLzH1+8Nl33RHd/uzmpnnUMnkiGqmLW1oRkrAgSX2R5rGrjRFVDViYAKkX0AvM/p+u5qB28vcgolg26YCEBXA1C4k58FQB5U83n9fTQAHj4/Ta4BnIg827Gqjm5fIpkqKdV1EGWlARBC3Iqs3X8TgM0AxgkhfiGE2C6EOD/B+pUNbpvWFxvVsexeS3xOmr3SVtUvXpf3kr3kofcd+2VDZVZ4q2Ud53J7j2eRnXfdzn/uY7zwSgXsln7DSLoqm5vXeXVokdT+2xuaAxKoODsT2ds9LnGWil6xaSc2bm9UdgpEWRu2LGz+4PGP8NQHTk/qMGe3TQDSvQvrBKjqx+Ulm91RALrlhsHPCRDI3xOdGXhUE8BLcwqzKrr5y1RvfyGH8K55TlUwkup9ttqkfyIgzZO60LlbYTUA5973jv1ZRwPgvmR3m3Kuc6BfR3stgdz36Us24N2cIFSTkwB02pSvAFyCToAQQswQQtwthPi9EGJ6kpUqF/z6KfeyuvYxuf9W21q4ZhvWbNmFK/71gb2P7Ak8fclGx/ET3liEqx/9EM/NzDu9zVq+CXdO+RSAc7Bx21pVGgDVIkZ3vbzA+8JyWOOl+x786bWFzv2kHdZta8DDby+JpW4Pc6isDt3W0BI6ftoUg2+cGPnYI8a/ioNuneLoAGUOv/0VHPXr17BgtXdiTvnaVm3e5ettrdQAeAoAfjX3Jki7YpuXYrSTQh+AfFlE+e9J5gFYuCaeGSij8QzcqDQA972xuGCbVZ6fsOUOH9atg879Wrl5F755/7u2E+ak2SvthcRUyH5MNZYGIIwJwLWr897qt7OXcmnFG5oyeHLGcnzt3rfxjQnZd9MycelE+Pi9AsXUAPguBsT44yepbVA05pc/WY2tDVnfAOslOenO131VX+4zrNmS7by//9hH+PIBvUFE+PKfsiknf3Di0ALPY1XOdZUAIL8QT81YjmtP3sv+rnqhrbL+/tYS78rD+XKN/OXL9jVdMHqg777e5QXuYiO/iH4JT9z7liKqQVt+jiffNc21gE/+euRljQ+/PRt7LO/rKNN2ZMr3UOrUvNGFpiAt9ZO5zHpBPg4L12zFnrurFyV1q4ebWwSeyUWKOEwAAdfw1IzloRN6WYRZG0LFckmLmBEC/1CsWe9GNx+JtQKe37P44b+jmpKCJYCv5NLk/nnqQlx78l6OCVAQtgbAzwRQMOP3/h5mTQuLxpZMwf2xXJh0NH6+JoDAo82hrQFgCtGdUVod8CX/mI5rHrcaTaEdXoVfQ2lozjgyVTW6kt1kMqLgBV+2YQdemZf3dLc1ACFbne7+qmvzyvClU2QY9bDs4LW9sdlXYJukoa5Nmo9XbMbA619UCo8q/Doo+b77OXq5sYRRRx4Az3NE66qaMxmt9hMkEJ505zS89Zk6mqKhydnw/zptkbNszW72un/PjCzo+KXZ1UFuB//3vJ6rVdi6hsnmqLtnGI2JEOrJkopT78pmFKzV0AAU+gDkPy9au81xn7zuQZglej9esdnW+uo8A79dkoxEcsMCQAz8HrP8gFVhgboviRDA6NtfwYRphbbC+99Y5MhU1dCUcXTKBRoAAYy5+w2HfVsV/ifn8vZCt59RDRJZQcW5/bH3lmrNcMJ0b/IgtmF7I378ZGFu8btfXoC3Fq7zDcssFlbufrffhy6yGUDuhMIMROoogMK7Pn/1Vtw1JdhUpMKdCCgO592nTpftnh2u2ZJ3xrv2iZmhowrKBT8nNRVhhLh7p36G1VuC71sYuTAjhFYoJJBtc0De1u6vASg8j8UJv3sdf3wlb6o0EQE09g9v4tNcbH9cH4BiwiaAGPg9RLnBfbZ2W0FGuCryX4pTZuXmXbht4jxcfOQgh9fup65kEu7yCqIAUBhVYL1DssRsCQCWZKzuJPQasOplaGzOFLyg1ysyoKkIpQGQTjL5Y7VUfdfLn2qXVyw2aXaIbhXAyXflc67r3qctu5qwZN12fLp6G/bq2cFWu7e4G46Cl+dGm6nozlLjdJHu2aF7YFQlomkNTJPi/3WQm0ldTZXvrPrtRes9U3RHRUAvF4KMZQLwW9AryBn5vSVZnwK/VMBReWXemsB9SsXiyAJADPyeodwAVd6tBMK2EJ1QbTXhin/OwMtz843rxdkrHfvscmkA3OFW97gc9AC1Q5YV/mLZgVXvme47M+PzjbjkaOe2huZM5JculA9AQIx3saVwXa2PbtSAX7y1rk/DhQ+8pzTJBGkA4hCcCCg+7vJ1w+MqGo1n8kpEoc/zlCE0ABZWwp2mZr0JmOq7fX6ECy3W4UmP1SF16lNsWACIgd8zlCVpVSw/UbgY/y7t6xyDP1Ao5TY0Oz3d3aFsqpmX1fjlBunOB6/qPHUb8KQ5qwpC8Bqb/T3yvXh+5opQM7egMbBUHf90q7Xdp/3I7e+EYbt77uflj6GTCMiLIOe9rGkqWeav3ooZn2+0v5tYrKu1UUXuUMN4tmu5JF2EALaEFACs0v1MAHL/MviGF3HpMYM9901jMGYBoDXg8wxlu6vcEVlUEYUazLrW1wWmLW1ozoTuWC01v6o9WrHgSg1AiHPse/Nkx3e3BsAvhO2FWStw15RP8d9rjsX3Hv0wxFmD8YuBLiZCCMegqasit0KSVMie/1ba2zDopAKOSlYDoGMnjXeeyx+eYX8uVWEvTWqqqhyDqInHHDbnRUYIe5XB2moqSNmtwl7YRzMMMCOAyT5OvmmMxSUy/rMTYBz8JGYdxytLA1CtsQiGTife0NwSWrK0ZvcOJ8Dcfz8NQJwG7PbQ9lv/+upHP8Rna7f7vuxR2RnCyzdJ3AP+F5t2YuD1L2qnf1Uhtz/Vs8pGiHg/xDgagCCaW4qT6kRebW3BGm8hs2JxdTsmnklzSPOOEHlBXKedTft0rZ0vIEwYoB+sAWAi4fcMdwUMLl9s2mn7ALSvrbbjcr3o3L42sD67mvTCq2RalCYA56ptliCwZssu1LepQX2bmngOWi0ZHPXr1+zvXgLQ65+uTdRZxi8NajFpEQI1KFTJyiGeYZGFGwGBv0z9DIO619vbTvjdVF9nQ+eM2bAGQLORvh7Soc2PZRvUibkqmcL1EuI/5+ZMBi/MWhm8o3VOyBON4PPLi3j5TQp2uEJfvUrOOgEGntY4paKQYg1ADFRrWlvs0vDwt5ICea2rLTNxdnCc+tT5a0K/xD/890w0NhcKDlt3NdkaCksQGHXbK3YCj7hZ2uTZmZfJ+ELpZU9isA67zkJSWB3fxUcOAgD069oOAPC0YsEoXXY0OjUAv35pHsb9M68SX7J+h616VbFxRyNuee5j7GpqCd1ZLdugXgfDohhOgEw6PPH+Mtz9in54aEaIyA6afgLAh0udZlf/kObiN0YOAyxzMhmB8+9XxyADzg7Yi/mrsmF8plZ1U6X8DGLphh2Y9ulaDOze3t62eN127HfLf+3vE2evwqPvZdX0C2KmNwWAnY3OF5dABbNfN4f88mXvHyMSJkFOGMLaQd3JmNrVZhdFimP2uObxj+zPUTqb37+8AIvXbceQHvXoWt8m1LF+4VmANeMrjQ6QyWPiidyimbDI4qOlm7Bvn06RzuXXzqwwvyC27GpKZTAukfGfNQBReX7WCkeqTjde3tUyH6/QWwksaX4zeb7S0c8ibJhOECrv9SSWtg1iq48GJyqzlm9S5v5/ac5KO++5m7VbG3DC76badmor0Ukc5LUoovQ1VnioO7RUhyD/l0xGYJKGRospLmkMSovWbcfz0romOtRo5Nz3etfcrN7SkIooWio+AKkKAER0GhHNJ6KFRHS94ncioj/kfp9FRAfrHps0M5fFH7ytXOGyOjwN5q/eilnLNxXtfKoBIsnFeLzwU4G78Qulk7HWZXAz7p8fOOyXMpPmrMKitdvxxoJsWlvTnUOU4qy1zRtbwkeWBC3r3JwR+N2U0kvAxJQHOj4kYSJ84qzWGZWK9wEgomoA9wAYA2A4gHOJaLhrtzEAhub+LgPwlxDHJoq1IlUc5q0qHc/kuHnL4/D5+u3BOyXAxh16OciB/KyjGJgOWYsiUFiOmQ3NhWmbgzh3VH/f3zkpDxMHnea4y72SoY8YO8G1TkQxWLm5NJxS09QAjAKwUAixSAjRCOAxAGe69jkTwD9ElncAdCaiXprHJkoKGutEcb8wxSSthXjCaACSFNjdbcmkNqRbfV2kulsCgMpBNIggYem2iYVrYzDFp7X1YTLunCl+bXhFCutC/PHVwqysaZCmANAHgBwAvjy3TWcfnWMBAER0GRFNJ6Lpa9eaCysq5oywGOg4LcqUiAkrFioNwG5t1X6xSV6vO6VvkBNdGDq3r40kvVjpq5tawvsAbAihWWHSo41G9FFroTX0V0mQZgtQjaDux+S1j86x2Y1CTBBCjBRCjOzRo0fIKnpTbcBRq5TYsrM0QuKKwZcP6A0A+Ne7Swt+00nKZBr3TMzPuTQsVUSRVt6rqY6uAXhEcV+Z0qOuunh9WDHPVWxG9OmYdhUik+ZTWQ6gn/S9LwC3O6jXPjrHJsq1J+9VzNMljmlP/1Lm6KHdPdWfqoWbgGTjdqfOD149LCpE0RY7sZwAo2SXZMqDugBnTZO0rW29AsCpw/cwWt4DF400Wp4faT6V9wEMJaJBRFQH4BwAz7n2eQ7ABblogMMBbBZCrNQ8tlXwizP31d63Z8dw8doyYQQAIcyt554GRGQPcG56dIh+D6PyziK9mOWw/HTsPvh09TbHmgFHD+2udezM5dkol6YWTtrTWunTuW3RztWmtnjChookBfh2dWavbbe2wVlfTZGaACCEaAZwFYDJAOYCeEII8TERjSOicbndJgJYBGAhgPsAfNfv2CJfQlEI4xDmtzxsEGFW5PLLwV1MgrzN/ahSqPrv/eYhGNyjXrF3eaatUYUunn/YgFBlNDZnylrYqxTGjAg/Cz1scLcEaqKmNZsATAs3xTRCppoJUAgxEdlBXt52r/RZALhS99jWSLHi49ds1feELZVFdGojhmIS1Fn29um1G56fWXwTQFLUKjrd00bsgfMO649H3l2KXp3aYmWAB3R25cbC7bvv1iZwdUqmeOisoufmzQXr0KFNTcmkxE6SJN/edqYFgCJKAK1XLCsCT3/3CBy/t79j4bA9dot1jmItY7pkvX/+dpmDbp2C/y2MvlKdKUxkzJOpIiqu+J0wXmtM1Oa0Hzqqy8aWvBOgvCJlz47FUx8zwWxrCO/D05IRRRts5MyUaZCk/G7ev6F4nRALADE4uH8XXHbMEN99Tt+vl+/vB/Xv7Pu7nwbgD+cepNye9EtdKpPhqA77fvfH66cSueRQeIWqWmmXdUJZGyUnQNlBkgWA0mLrrvCz+OZMRjvqpRzDnm87az/7s+4KlF4cPrir52+sAahggt6LoHZ36EDvhgX4CwBWOJub1mxvk1HZ8ZMq70TNVMClRK2HBsDqYHR8Rhqa86mA5UGAIwNKiygCQEboa9FMZD4tNvVt8gNzc0smVr/4z+8chuvHDFP+1tZDALj7nAMjaQeKeacrY6RIkKBBKKij9Go8FromgB+cNNT+rLO8cGsg6oviJWF7lTdsj91w1sF9I54tPbwiHayBX2emsaOhxfZ/sGaLFx850GiyorgM7NY+eCcfbjtrP09hulyIsrBVcybjGCT9MG1u06VL++ge8XKio8bmTCxVfU11FcYdOwS771YYJeTXh0dxzC7mwmiVMVIkSNCjcgsAN52+Dx68+FBb9d8h4AXUzZv+g5P2sjv0oMVYkkC2DwdxyvCeZk4a1QTgcWAVkfLla19XXXYq0I5ta1DfRu3ja02EdITL6iqytVjWrRnRu1OspYpNM6i7OnJDl/MO64+zD1YmEi15rGcSRQNw1oF9UF+n5weeRoIsALhhzD64+5wDIx0rT4S2N7agvea1+qHKE+KnWSj1dMssAMQkSFpzCwDnHtYfx++9OwZ0zc5aOrTxl3CDJlrTfnQ8nrpitGNbXULqOj+vez9nx1OG98RJ++RV6OceFj18T8YraY/M2AAfDBm/4kwLAGcfFH7ACWNrvPjIQZ6/nXfYAPTv2h6na4SOZYSw27A1CBCZTVcclnqX86IJjddRe3bH5ccOxoCY2oRi07ldtv+I4iz85QP7oIOHkAg484pEjbjx44C+nQL3qa0hnHlgH09/Jz/qqs23k2LIQcVcGZUFgJioGsR9F+QzOcmz8SXjx9ov3K6mbAcapIIL0gD079YehwzI+hFYssa44/wdEy1+9/UDPH/7rqKM4b29X9izD+6L5686SvnbScN7Ym9ZQNBo3zoDrtce8kD+x3MP0s7a6BcEYHoG9NuvH4Anx40O3lEiyKFURnX/LBXooO71mPbj4zFk9w6B5cipgGWTQpSwM1Ps08uZejWqxuuSowbh8csOB5BV8d4wZh88lvteLnRsVziBuELz/a8i//7n3RtPsgfNJEwAXhoqGUvOjGIKcA/4JvwYVBO+FiHwW4++NMoZi+lfwwJATFSzULmxeq0jby2/26FNDe78f4WNx7JfqST7G08fhhe+px5sAeCkffRU7Hv7zNp/fFqhw8s1kp+Bm5oqsnNiuyX7ap/Mexbue/DMlUfiqStGo39X7xlZB4+Fe564PD+wVlVRQTy812zJyzRALtPAtw4Pl0xHRVUVBfp/FBwTojepdnV2+/fthLm/OM2xzerUj93LGcoqP6oWSQNQlaIGQLbRD+3pbLeqfAc6/PRLwwuS4fTq1E5p5y1VVFqh9prtqopIaxAGkjEBeGm0ZJNOJveuRrGluwWAWk0h5vJjB9ufbxgzDBcdMdD+rurGMkJ4+hdEsec3F1G4ZgEgJqrn27l93h5eRYROCindEgDa1VVjvz6FM2vrhcsoBqvLjhmCEYpjwhKkQn/uqiMd1+c3YFVVZQfJ5646Ev/4zmGO32qqKXDxpP1dQkP3Dm1wyICu2M9DTfjj0/a275vsf3DowC4FNuHC5XbVg5duH3frV0bo7RhA2E41TF9yxv7ZAdPKK15TVejfYJ2/TU0VTts3bw6Q20VLRhRoAAhUdAHgyD3zA7V74GhXZ7Yb8+p+93YJHi9e7S2EFwtVG9IdPojgawKQ+f05BxqPhGnrkYdir555zZQlrEexpbtt8zoagKG7d8ANY/bBU1eMxtPfPQKXHzsEt3w5n45d1WdmMiKyFkqlNWUNQBmhahCdJQ0AEfDSD47G3y8+1LHPLksA8BhUrRe7RQh0zM10X73uWLx304meddF5SZaMH2vb9oIGoP37dsYPT9nb/u4nAFiDw/59OxcIPFVEBS+f+9xewohXDc/Yv7d9jFxUFVFBWe7L9NQABNShporwvRP29KhReML6FYSZBfXLaU6svOKq+2u3sYxwPA+5WplMft0HOeIlDRPAo5cejpevPdau3/BeHXH9mGEYtkdxVmPb3bXWho4PStKoxgrd8SOMBmC/Pp3wt4sODd4xBEF9H5CP348kABSYAJyCrorf5FT5hwzoioP7dyn4XfXKZoQzGdBhg/Kh3UHVlic4loBZrORvAAsAsVFqAKQBsIoIvTq1w3F7O6VnSwBoW1utlNhrpM7Zolt9G+y+m14Clhe+d5QjNNBRZ1cYmPsaekgqUNkXwG/9cLcWduGvxqB3p2xda6rIOdNQ3DMvG6NXJ5vVOOSKk/YZ2K2+wNzg1j6otCrZc+XvxRXHDUGfzu0cvy+87XRcJwlEfrx7o7egZlFThHwNGZ8ZVI0kZMqDu3w/MwJ2KmCrumk5AY4e0g177t7BvpaeHdtg3LFDjKunVQPo907YE3845yD8/EvD7W0lMP47uOsbB2jb/4Fs/XUFgCRo76EBkN/XKCaAl689Bo9ddnhBf1VbRQWmMTe7eZgVLVT9EZFzcuS4rhBtpFducSav/ikJWACIiaphyh27VydhOQG2q61WdjjWSyDbg4IWZdkz59RVV1OFEX06eXYGVp0s4UKWxF/43lGYcs0x0r75C/A1AbgutKa6Cg25ULG2ddUFKxW6c+t7WQh8Y/YVzmn/d+a+IFdZXzvEGcOv4wOwd8/d8PuI4UeAf1jk+LOzGcpCawByu59/WH+M3T/vEOgWVGSsS1VpN6zOv3O7WpcWJf+5RRSaAIDiCwDys7Guxfrvvo3De5nXCPTq1A5d6uvw7aPy0RWqd79zjLj1KBwj+W+cdVBf/OS0YdqLNxFRYBhy2wRziniZMeUx2uqjBnbXj87Yc/fdcPjgbgW+IbXVVYG+SIFaHennwT3qcc1Je+GQ/l08J0d7ajjaWlh1Yw1AGRHkV+LVnH511ggM79URvTu3U9p8VBqAIO45/2A8/J1R6J5b0jZIrd6hTQ0O6NcZf5RCbAb3qHf4MAB5lZZfIg3VLMzScrSvrUY7VwzuQJedPrQGgMju5uRTt62tLjimU7ta24wCZO+prMq3jncLDnHw62j6dMkO2OF9ALL7CwBfl4QavyWjhZ3Gt/C3Qwd2wS+/MgK/+MoIxz2TP2cyhU6AQH4xJV0bclzkQc19a93CzaOXmvfkV90/1TbT9yMo9PNHpxZqpNzdycybT8GDCvU9ITgR2VNXHIEfnbp34H5hkjFdfWJWM/k1KbnWyAF5dbtcfavt9erkLeR6oYoCcL9zHV0z/qBXUn43ute3wfdPGurr0PvAhYdq5zGojtDnx4UFgJgESYxePx89tAcmfv9o1NVUeWgA8upZu6wAfVLHtrU4emh+RuApAEjbn73ySJwoRQ2ojnnsssOx+PbTfR1dVIOZ5ejYvq6mQEJ+7NLDcYOUWtM9/ndsl30xva6YKN85uAcA1Uss79OcEY7v9ozSdUwcXxy/DJHWc9TVAFhRJVYsthACx+29O/bp1RF3n3Og4/m5yQtJKtUl4ZuHD0DHtrWeAoDc/qqkmbflA2A66+RzVx2p3C73ibYJy/7upJPGLNxPa6JC1b5Vr5dps8AFo/0jTqqrCGcd1Ae3nJE3Tbibbad2teii0EgRBUdQDO25G648PtjvZd8QTsnXnrwXlowf63hHekvPQ9Z6+s2G9+3tr+kpiAKorip4D9zveFB/7vXKtvXoG7vU1/m+nzKWn1SzZvI3E7AAEJOgPlwnDESlAbDWpT+wX+co1QJQWLf7c/kJrMHWT/MgY4XBhdUAWO9uu7rqAgl5945tcXIuIyCRUwOwZPxYO2uXp2MeybZptwAQ3FmrZ3T5jX4zzrhY5elqAO45/2DcdPo+trOb9dgmff9onHmgf0Khbh2yHX9Q1Ig1Dow/ez/H9W7a0YTVW7JLBldLgpJlAtDJr/78VUfh/ZtOwme3nR647/59O+M7kprdWudenhXZGhuyvod7QN3q6/DSD44OdYxqBtqlvX72y6j8RBGO6+aubxyIi+TET7rvNcjYuiG/+LK3FkoHuS9qlMxLXrPhPp2DwzULogCqCEN7OlXyYT3uvSZhbXz6xg5tapQaGDc//9K+OPugPtph3CZIzwOk1ZCMJ9DJw3vi1jNHYEC39hjQrT3ufmWhZ9y7Z81cHeNJ1oALayZZeIzfoOSrAfDphNvVVftKteRzvLcPAHmqt4PGAyG8hQRy7JesKk43uUqvTu1wxJDuePS9paHPMWyPjvjPd4/QEADyGid3WtkZn28E4NTSfGv0ADz4vyWorQlu/4N71IdyNvvqwX3xtzcXA8gLMHJHnX902Q9hO8zendvZ0RFqCp973y6FAoAqtWyUeHU/TC14pdLUEHkvGBWWbh3i5U6QXzU5zbSXlkwnY6M7e2F1FeGyowdj/z6dcMSe3QEAw3/+kmc9VMjdhjVJA5waANWk5XifEMonLh+Ndxetxx6d2uLObxzoXwHDsAYgJnFXA1TtU1dThW8eNgADu9eDiHDCsJ549sojI3k7jz97Pwzs1t5hK7Tap6pqfhoLv/P7dVTta6sdwsPB/bo4zkVEgb4UBeej/H0rDPvzv08ZIYI1AAqVsyms0mSP5KtzPgkqtaY883bXTcYdp25xUP8ugape69pVHsjWb3Iq4J9/aTgW/GqM1r0JayaQH1+1ol7uKJZO7Wtx4+nBM2WLoEH1wH5dCrb1DmkySJNOCs2EWgMQf+VQlSd/FLOQLOD165q918fs1QMXSkl4ZHT6VXdfNmnOKlRVkT34u8+r+u5V5vVjhjnyA7SVclGEnTiMGtQV3zvRO8lakrAAEJOgwUanMbhj5MeM2MOY5H/OqP6Y+qPjHXa8/EBibobrJxxkTQD5pua20RLCpxolIltNX6jeD7531ovsFzYV9u4M6aG5KE2uenKnfFB/Sygq3N0SFKzfVJ3UZ7edjonfD6fWdpzDxwHJrWonZE1Cuhn44qyjYD0nOe2AbQLwOc4vnCsoH8wfzj3QEWXRpqbKcwats63YXKjwG/B6VnUaGhw/Jn3/6AInN7djncUNY4bZg7sbuU3/dOxwPHjRofjHt0d5OteZSpbjbu5B5Vpt76g9uzvqptKOugWQ4/fuUbBP2rAAEBP3YLNHR2ecvo5D57A9dsMtZwzHz6QY4ySxPPDbhExFCwB/Ou8g5XZ/00GV0klGPqKdR0ywF1UEWFYFHSdA+b0WQuRnvEJIpoR4nWF1FTkWPfLC6ozle2bnNFAMa3IGPkAtmFRXFXo4hyF/Pwp/s0rNa2zClR02HapDA6DKiKlRD79Y6qD71L6uxs4yefkxgzH/l2MCalxaqPJLKLPgUeGCOUG8ePVReP1Hx9nfB3SrL/BDcT/vRy45DP8eNxqXHzsEb/z4BMdvVsim/Lja1lb7qsy9zhOFccc6JwBB/bXcb4St14MXjwpXuSLAAkBM3M/actqz1LE6MblEhIuOHISu9cWJIb77nINw3wUjQ3tCA96DpJ8PABEpnWTsQS/Ce0woDAPMl1dYYEHeAcsM4hpX4nYq937zkIKc+26sGbE8M67yGdTs3RR1NoWfdmHm8s3y6YsGkSQAOKIRCvd1V9vPezyMoBf2VpeAAsDBvy7JpuVWadgIFHqVv317d8KAbv6aLvfzOWLP7jh0YFflvtfkFuoKq40UEY5R4V4obI9O/onWbjx9H/Tr2g5Dd/deR6WcYAEgJm4b2F05Jw67Q40Q0ZF0J9KpXa3tgR8Wr7oFzaq8wmSyZYa/YqrKO2aNyuUp8LNnOjUA+UFA7kTIY39V9VSLFBEINdVVgdoMqzOWhY18ffL7dcuFbtmL8Fh1Cz0sBWOtC++nrs9rKQrRjQNXrTLpeT7pnEHhsGdIiwUB/jM0HU2JjpksaXW/ifKtBb9UAz1R9DDOV687Fq/98Djlb2EELOtRhA19T8JBV16t1YvRQ7rhjR+fEFpjqeK/UsK1tGABICZyKFCvTm3thkEaqqLWRGD8rEcYUlQI2WVhX/vhcbj8mOyg4jd4CddnkjoeS2tDRN5CgIsXrz6qwPFMt99TDUAqF4gWl2nCFhgSaFLfPX4IrjhuCM49rL/nPn5aitFDuhVuVHDp0YMD97GeQhWR0gmwsSWbX0IeNNxOen4aAC0BIOWp/BkH9MbD3z4seEdNvNJOR11JcXCPDgWLblmEEwCi9ZNCmDEBpIlOJEPScBhgTKqqCLefvR9ueHq2y3M8POUsK6g61ak/PA4bdzR6HmO/vz43y51C2MLqOAZ1r8fyjTuy2/wEAOnmyhqAjBB48OJRWLxuu+fAoNq6W9ta9Oyoty6DG9VszNYASKO75ZBXEAUQ6az+tK+rCYw5N9HdhumznSaA/PZ3F20AAEz5ZLXnsabeJb9yVAKsqUFJzs4ZB6s2KuG4Y9tarNq8S3nccTEc1sL4844c2AWDe9TjupP3xtT5a7WPaymDzjKoJZiOLooCawAMoJKErZcgSjstZclWrtrB/TvbfgQqJ6OB3ett73bfMhVlW3z/xL1w5/87wLce+Zzw3vdNHkDkMEAhsiYRVcKlJFTtgIcGQOm3kP1vpSi2FQBF6vzcy1S74++d6LVZnbYt+3JYA9GRUuiWZWbzEg6D0BHcSqFzNol7pn/FcUNQV5Nfr8PN32M4rIXRAOzWthavXnec57LfXmxz5ar4zdf2D3V8KVAK3TwLAAZQzd5GDcyqRIu9OEgxaWzJ2LPU2rCB/BLWizDr5lMw65ZTHL/V1VTh7IP7FhwjdzJkb/M+h6xiFMhrC3RUj6ZfVJVDlqrufzj3QBzcvzM65Ozz1jLL3WMmXdHlt193Cl4mBNNQGgBkl2VdMn4sDpFyxffr2h4vXn0Unhx3RKQ6+K2dYJ9bw9qiuhYra2IxuEojRa/1zKqrCE9dcYSdZdHSCIRZrEaXYiyTvHlnk/35/gtG4usj+yn3u+2s/ezP/xczW6EuuldfAuM/CwAmULX3G08fhinXHGOvy94aaWoWtq1VGWYUgDv0bbe2tejom6HNH3fHc75kz3Z05EIE+mhEmWPrDpCqe2Uv9COd+IRhPfH0d4+0hZUThu2O3379APxQsQBMEvRxZb/L1zq6BkIrR4PGvvv27hTp3TpkQBdlBj8vwipbdjS2hKyRPlZa5KgcMqCLHQJsebt3aleLTw2HORpenVnJll1NwTsBOO+w/uiVu9bj9w4OLTRJUNMpBU0v+wAYQPUYa6qrMNQjM5sXZWDWgny1TS0ZtOTCHHQEgGk/Ol7pPRvlPXBoACSVscWS8WOdB7jurZf3sbUSotda5X7oXobKHqvnmEYFSxsnSU0Vob6uGttzg5oqUuHIPbtj6XtL7cWbLF6+9hicdOe0gjLDPOpiDCRxIACzbjkF+9/y30TP8+fzD0aX9nUYPaQbBl7/or1dK8TY9f38Uf3RqV0tvrRfPtGR6XEoTj4KXazl1HWwFq7ySlt9zUl7YZVBzU0JjOvasABgANXsrRJoaA5nAujv8nr1WoVPB4cPgO017r2/3FkK5L3G3eFrPz5tb/Tr2g6n7bsH3lm0PnKd/FD7AIQ6VVGoriL07dIe81dvBSAvIpXf5xdn7otxxw7GS3NWOY7d0yNOOox6OIkZUvh4c//942isdDldGqzDUpAls4rwZVfIpOm7XAwTAJDViLw6b02gGcOepHj0Ud8/yWwaXqtNBC3lXAqvPAsABkgwOqukaZJ8AKKYACyidPTyEVYn7dfxuPMAHL/37njkksNw+GBn+Frb2mpcLK+sBvMOYaqQLNXsOgoPXnSoMefFKiLb7wDI3wfZbFJbXRWYGEbG/Yi6d2iDddsalPuYGkfa1VbbS1ProuesmN3nvRtPxKjbXlHuc+nRg3DfG4tDnVsXUxMO0wN2Uqrt5686Cqu37MIl/5gOAPj6yH4444DenumCLexJSow+Kgw3jd0H+/TqiBMDshmWgqaAfQAMYOo5Wu9zCbQLT+RG29iSyfsARHACjHOdcqdlzUj1nQCzn4/Ys7t/6GDIOum+0HFy4wdx/LDdccIwM8uJVpErp76PoKt77e79fBMP6RUZyNxb85kZww5O/mGAWXb3iSr41uEDQ53PNDrCa1UVaSdy0iFq875hzDAcPlidMRAA9uvbyV7R1IpQkQf/752wJ37nclwFIPkpFWe4q29Tg0uPGRy4nksp+ACwAGAAU7O3ckBusk3NGXv1unhOgOHo3qHO8XJZSWL8Xqg7vpbvGMI+J69ioz5vPxtpKTUhdwpnq9ZxwhDdKaPVdtmcSScBQUm37qbOTARcoFicp9SwMgaaIKoPwOXHDsFjl40O3O+Dn52MJy4v3O+6U/bGVxU+Ml1zGTWTFLzLFRYADFACglwqNLUIPHjRKDw5bnTkjGIAQve27j7cmt37dTxfO6SvvSRyUoOs32zrrevzi6Co7lW5tyFdM0lNdRVm3pwP9fRPEZ0eOs9D95m5sx+2VayLkRgx/FISPmVkutbXhUrF++ilh+OOr+4faCqoRFgAMEC+8zM0tJTJYNDYkkGn9rUY6bHQRxBhbOuXHTMYB/XvDKAwdM9OmBNQnN+CNypGDuyCU/ftiVu/MsK3PK/vr1x3rL1dTlVbThMR6xkN6VEvLb6kCmPMfz52L/8scrJfQb0i97pVVhzb9PNXHaXcnoba1X1KvzUrgpBnsSYFWZN+AKWg2pbp17U9/t+h6jwBlQ4LAAbIZ2hLtx7FwOTLHcYEcOPp++COr2azfblD99w58z3P52fEVtCmphp//dZIDOkRLVmK1dG7ayXfwynXHIOpHouqlAS5qn7vhKFayyafO6o/7r9wpHbxfouvxGlrYTPLFZw7999/MaDg+qly1gtkBdooPHPlkaH2jxOZEpVihAEyZmABwAAlJvCWHbodvVf2vvzAFHSe3P7hqueJe2zwOr3f9Q3tuZudnMXi7xcfij+dd1DM2pnBqjlRfmVLv8fVrrY6lDmovo2PCSDF98oO7VX8dvc5B2Kf3Dr2XnTvUIeLjhiIvl3aKdvFjafvE6le8nn9JhxVIYRrwH8577BU+vjvdytNJ12KC4cBGsBUmFixcryXCvLgooPVSblvk5XZbXhv/1lf0v3SaSPU8do657XakBACxxU5Y5kfsvCS0RS0wqA0AeT+l+pAcuaBfXDmgX189xncvQNuyaWeLWjfRXjNq6sImRb9E5l0uCxWHoByJOryy0mRigBARF0BPA5gIIAlAP6fEGKjYr/TANwNoBrA/UKI8bnttwC4FIC1fNSNQoiJiVfcA3vhH0PllfJCJCP6+M98QhF2luKhAejduR2euHx0weI1BaezTTWG4uSlTvNvF47ECa643zDx7KXaZ+ZV4VKYqsHK+poAQr4Hd59zoOP7xKuPxrLcSpFRidpU5NXqTL7Pckl++R6yg7DQflZmNQAl2piZAtISR64H8IoQYiiAV3LfHRBRNYB7AIwBMBzAuUQ0XNrlLiHEgbm/1AZ/oLQHbNP06tQOE68+2miZcU0AADBqUNdAz+D8LDtkBT04bd98bvbd2tZ6Xke5tY+XfnC0vQJj3mwitHwAwiQh6t6hjYcTYC4MMORtc8/Mh/fuiFP3jZY/P+4YJrdRd1lBd+jSowd5/lZVRThAw78hrB3eqAZAGlUqURYIet8H99BPnJU0aZkAzgRwXO7zQwCmAviJa59RABYKIRYBABE9ljvuk+JUUR9TM8s0DQC//up+dh78IEy91NaLEtZO6XYC1D6fYR+Aupoq3HPewbjykQ8wRPFS2wJBmXWCw/boiGF7ZDU9ctWt+666nLBagZevPRbd6uvwyHtLPfdJ05s8H9ej11r6dmmHLTubsCW3TK3zvll5KnKaFJ9+4t/jRuPQgKia00b0wszlm30bcpX9rujV32SOHFlAtBx3mTxPjTsCSzfE00yZIi0BoKcQYiUACCFWEpHK6NkHwDLp+3IAh0nfryKiCwBMB3CdyoQAAER0GYDLAKB///6qXWJTZXhgSaPf+8ah+vfGdP10y7NNLREFrVGDsh1rUJhaGMbu3wtj9x/ru0+Zjf8O5HUubA2AgcHCyt+uWtEvrG9IIoRM7jXtR8cDAG56ZjYefW8ZLpLSSffo0AZnHNAblx8zGE9MX4avKpa3tmhqCV7kRue+2ItdaUrLUTJ5emFpHx64aKSxrJStiS71dehSrzfZSprEBAAiehmASv92k24Rim1Wa/4LgFtz328F8DsA31YVIoSYAGACAIwcOTKhSXY5d/HhSUulHVcDsH/fzlj4qzFFSwkaZiCzZk2lFkIl+wDYGgDNNRd0OGP/XqgmwpWPfFDwWznZki0V+u1n74/bz3bOemuqq/DHc7NRHSMkP5VB3euxeN12x77NIRz3/Pbs3L4OW3Y1az8Po3kAcv8rzKfZpoyabXICgBDiJK/fiGg1EfXKzf57AVij2G05ADl7Q18AK3Jlr5bKug/AC2ZqHY1yeuAmMHW9efWqpqOSjw+ALsUa/GV0BKa9enbA5ccMxvmHlVjaWEm71a9rNplR53aFK+BFbRJEhLH798KVj+S35Z0NIxbqQ/jVAJNjyjXH4JcvzsXf31pib2vOaGgANMr+1yWHYconq7VnmiblzkpdHbUcScsJ8DkAF+Y+XwjgWcU+7wMYSkSDiKgOwDm545ATGizOAjAnwboGYkziLZMXxlhfoZnBz8KaZZVLxxJmACMi3HD6PgVLJqeNHJ7407HDMeFbh+Cg/l0SPaeOs2HSFGMWW1NdZa9Qd9Se3QEAIwJCWWX8hJl+Xdvj20d5OxO6MaF5uvjIgQDMm0SZ5EhLABgP4GQiWgDg5Nx3EFFvIpoIAEKIZgBXAZgMYC6AJ4QQH+eOv4OIZhPRLADHA7im2Bcgk18MyEyTL3WFgjkNQDhMhioVkzKttgOB7Mprp3h41cd1hP3L+Qfj5WuzqZP9nA3joutYWKxnZtXnqKHdsWT8WN+VBfPHmK+HiSiAn39pOJaMH2tfUxxNXTlTTq97Kk6AQoj1AE5UbF8B4HTp+0QABSF+QohvJVrBkLSGDj4cZi5YhOzoS80+HkTYKIdSxG7bAX256hrfvbHgFfdkzH55pZ6QvObTJ9lBLM4lmhxfTQjX1sCf155UpgBQTnAmQAMYywRYJkoz0z4A2iaA0hgRQmN1jF3r67Bhe2PKtQlHnDveU2M2q8LSACTxvK87eS+t/Yrt6BpmrEyibklkAuTxv/RhAcAApuPLSx3T3Y9uh1Z2GgBXGoB3bjixbIQ8C8uJTPfem7g66x6ZFABOGd4T//1kNY7I2dpLhhiXaLIlmTSv5VfdNFZkWVFqqyH6wQKAAcroeRvBVAPXXcbXoszG/zy5epdaHnAdvnX4ADS3CIzdX73OgYXJTk9n0aGw/PVbh4Tav9grfIYRDJPob2qqE9AAlJmwW4mwAGAAMqQC6FrfBoBz7fhSxFRXES4IsLwka0DKA5BqLeLRr2t7/PyM4cE7GiSfOc/krDRcWcWKZY+jzjdZN6N5ACpcA1BOsABgAFNhLyftszvu/ebBOHGf0s6eZT4TYDkPkcG09uuTMTsomSur1EnbXm4yPUY+DwBLAKUOCwAGMOWUQ0SeS8qWEqaut3entvj2kYNw7qh+wTvnuPH0YThiSInZcb2wfAAqYCAzeY2ZEooCSFqNHecaTdaNMwGaowSarTYsABigFDqqYmJsMSCi0Orly44ZYubkRaTCmkdsRIJRALoU2wcgDElolEze67xGtARvHuOg/LySShDT68wzrYNyWwbYBCY6fVsDELuk6BTr2ZVKHgBrcSYT2ImAgrMaMynDAoABKq2jrzSNR1wqwQfA5BXm1wJI/74VS6QPM3lI4q4cs1cPTPr+0UbKqrSwaDcl0Gy1YQHAAJXW4EuhYy4n+G6FI78WQIqVKFoq4OIco8M+vToaKceaEFVqKuByggUAA1Ra5ise0PQIm+mwnDEpFA7sVg8Aqa6MWGxHtijnKVWToy24lWb1GAl2AjRABfTvDiphQDOC3QG2/hv2tUP64uMVm3HdyXvHLqtbhzZYMn6sgVpFxw5lS3wtAOs8rQdrQlSpGoBy0pCyAGCAMnreRqg0n4e4VEL7aFtbjdvP3j/tahijV6fsOgYmneNUtMa2wYmAygcWAAxQrNlCqdAaO60kCJvpkCkdjtyzO564fDRGDuhSlPOFWwyotKm0/rCcYQHAAKUcM5wEpd4BlQph1zpgSotRg7omfo5YYYDGamEW1gCUD+wEaICK698r7oKjYTsB8g1jAgi3GFBptye7dpUyIypjWAAwQH71q8ogzQxt5QRrAJgghvfuBCBaCF6pjq+V1h+WMywAGKDSOvgKu9zIcAfIBHHaiD3w2g+Pw6n77qF9zAnDdgcAfH1k36SqFQvbBMA2gJKHfQAMUGkq3lJXQZYKogRS2jKlz6Du9aH279e1fephkn6wBqB8YA2AAezxsEJaPA9oeuRNAHzHmMqBnQDLBxYADJBPBVwZLZ7HMz2s+9Smhl8zpnL40v69AQBHDy2TZbsrGDYBGKDiTAAVdr1R6dO5Ha4+cSi+enCftKvCMEXjkAFdStpEweRhAcAgpeqVaxwe/7UgIlx78l5pV4NhGEYJ6yYNYC1+kXTa0FKBTQAMwzDlD2sADFBTXYV/fHsU9u1tZjnNUofHf4ZpnXRuX4tNO5rSrgZTJFgAMMQxe/VIuwpFg73aGaZ1MvWHx2Hrrua0q8EUCRYAmNDw8M8wrZPO7evQuX1d2tVgigT7ADChYQUAwzBM+cMCABMaDgNkGIYpf1gAYELDGgCGYZjyhwUAhmEYhqlAWABgQsMaAIZhmPKHBQAmNOwDwDAMU/6wAMCEhjUADMMw5Q8LAExoePxnGIYpf1IRAIioKxFNIaIFuf9dPPZ7gIjWENGcKMczycCZABmGYcqftDQA1wN4RQgxFMArue8q/g7gtBjHMwnAwz/DMEz5k5YAcCaAh3KfHwLwFdVOQohpADZEPZ5JBlYAMAzDlD9pCQA9hRArASD3f/ciH8/EgE0ADMMw5U9iiwER0csA9lD8dFNS5/Sox2UALgOA/v37F/PUDMMwDFOyJCYACCFO8vqNiFYTUS8hxEoi6gVgTcjitY8XQkwAMAEARo4cKUKeh2EYhmFaJWmZAJ4DcGHu84UAni3y8QzDMAxT0aQlAIwHcDIRLQBwcu47iKg3EU20diKiRwG8DWBvIlpORN/xO55hGIZhGD0SMwH4IYRYD+BExfYVAE6Xvp8b5niGYRiGYfTgTIAMwzAMU4GwAMAwDMMwFQgLAAzDMAxTgbAAwDAMwzAVCAsADMMwDFOBsADAMAzDMBUICwAMwzAMU4GwAMAwDMMwFQgLAAzDMAxTgbAAwDAMwzAVCAsADMMwDFOBsADAMAzDMBUICwAMwzAMU4GwAMAwDMMwFQgLAAzDMAwTkyuOG4LqKkq7GqFgAYBhGIZhYvKT04bhs9tOT7saoWABgGEYhmEqEBYAGIZhGKYCYQGAYRiGYSoQFgAYhmEYpgJhAYBhGIZhKhAWABiGYRimAmEBgGEYhmEqEBYAGIZhGKYCYQGAYRiGYSqQmrQrwJQnN58xHHvu3iHtajAMwzARYQGAicTFRw5KuwoMwzBMDNgEwDAMwzAVCAsADMMwDFOBsADAMAzDMBUICwAMwzAMU4GwAMAwDMMwFQgLAAzDMAxTgbAAwDAMwzAVCAsADMMwDFOBsADAMAzDMBVIKgIAEXUloilEtCD3v4vHfg8Q0RoimuPafgsRfUFEH+X+Ti9OzRmGYRimdZCWBuB6AK8IIYYCeCX3XcXfAZzm8dtdQogDc38TE6gjwzAMw7Ra0hIAzgTwUO7zQwC+otpJCDENwIYi1YlhGIZhKoa0BICeQoiVAJD7v3uEMq4iolk5M4HShAAARHQZEU0noulr166NWl+GYRiGaVWQECKZgoleBrCH4qebADwkhOgs7btRCOHlBzAQwAtCiBHStp4A1gEQAG4F0EsI8W2NOq0F8HmIywiie64erR2+ztYFX2frgq+zdWH6OgcIIXqofkhsOWAhxElevxHRaiLqJYRYSUS9AKwJWfZqqaz7ALygeZzyJkSFiKYLIUaaLLMU4etsXfB1ti74OlsXxbzOtEwAzwG4MPf5QgDPhjk4JzRYnAVgjte+DMMwDMMUkpYAMB7AyUS0AMDJue8got5EZHv0E9GjAN4GsDcRLSei7+R+uoOIZhPRLADHA7imuNVnGIZhmPImMROAH0KI9QBOVGxfAeB06fu5Hsd/K7nahWJC2hUoEnydrQu+ztYFX2fromjXmZgTIMMwDMMwpQunAmYYhmGYCoQFAAki6kdErxHRXCL6mIi+n9uuTF1MRN1y+28joj+5yjok56ewkIj+QESUxjWpMHydvyKiZUS0LY1r8cPUdRJReyJ6kYjm5coZn9Y1qTD8PF8iopm5cu4louo0rkmFyeuUynyOXKnG08bw85xKRPMpnzY9Ss6VRDB8nXVENIGIPs29p19N45pUGOyHdpOe40dEtI6Ifh+rckII/sv9AegF4ODc590AfApgOIA7AFyf2349gF/nPtcDOArAOAB/cpX1HoDRAAjAJABj0r6+hK7z8Fx529K+rqSuE0B7AMfnPtcBeKMVP8+Ouf8E4CkA56R9fUlcZ+73swE8AmBO2teW4POcCmBk2tdUhOv8PwC/zH2uAtA97etLqt1K5c4AcEycurEGQEIIsVII8UHu81YAcwH0gUfqYiHEdiHEmwB2yeVQNkyxoxDibZF9Uv+AR7rjNDB1nbnf3hG5rI6lhqnrFELsEEK8lvvcCOADAH2LcQ06GH6eW3Ifa5AVdkrGScjkdRJRBwDXAvhl8jUPh8nrLGUMX+e3Adye2y8jhCiZhEFJPE8iGopsBt034tSNBQAPKJuB8CAA7yJ86uI+AJZL35fntpUcMa+zbDB1nUTUGcAZyC5iVXKYuE4imoxscq6tAJ5MpqbxMHCdtwL4HYAdSdXRBIba7YM5lfHPiErHFCkT5zpz7yQA3EpEHxDRvymbLbbkMNjfngvg8dwEMzIsACjIzQ6eAvADaUYUqgjFtpKZSVkYuM6ywNR1ElENgEcB/EEIschU/Uxh6jqFEKciq7ZsA+AEQ9UzRtzrJKIDAewphPiP6bqZxNDzPF8IsR+Ao3N/pRJCbWPgOmuQ1cj9TwhxMLK5Y35rsIpGMNzfnoNsXxQLFgBcEFEtsg/pX0KIp3ObV+fU+pZ6Pyh18XI4VcR9AawwXdc4GLrOksfwdU4AsEAI8XvjFY2J6ecphNiFbMbOM03XNQ6GrnM0gEOIaAmANwHsRURTk6lxNEw9TyHEF7n/W5H1dxiVTI2jYeg61yOrybEEun8DODiB6kbG5PtJRAcAqBFCzIhbLxYAJHLqsb8BmCuEuFP6KVTq4pw6ZysRHZ4r84KgY4qJqessdUxeJxH9EkAnAD8wXM3YmLpOIuogdUg1yCblmme+xtEw+H7+RQjRWwgxEFlnq0+FEMeZr3E0DD7PGiLqnvtcC+BLKKG06QafpwDwPIDjcptOBPCJ0crGIIH+9lwYmP0D4CgA+Q/ZzkAAmAXgo9zf6QC6IWvzXZD731U6ZgmADQC2ITvzH57bPhLZl+0zAH9CLulSKfwZvs47ct8zuf+3pH19pq8TWQ2OQNZ5xyrnkrSvL4Hr7Ang/Vw5HwP4I7IzjdSv0XS7lX4fiNKLAjD1POuR9RS3nufdAKrTvr4knieAAQCm5cp6BUD/tK8vqXYLYBGAYSbqxpkAGYZhGKYCYRMAwzAMw1QgLAAwDMMwTAXCAgDDMAzDVCAsADAMwzBMBcICAMMwDMNUICwAMAwTmtyKZdaqZKuI6Ivc521E9Oe068cwTDAcBsgwTCyI6BZkV4MsufSrDMN4wxoAhmGMQUTHEdELuc+3ENFDRPRfIlpCRGcT0R1ENJuIXsplpwMRHUJErxPRDCKabGUjZBgmWVgAYBgmSYYAGIvsmgL/BPCayC5OsxPA2JwQ8EcAXxNCHALgAQC/SquyDFNJ1KRdAYZhWjWThBBNRDQbQDWAl3LbZyObhndvACMATMmtVFsNYGUK9WSYioMFAIZhkqQBAIQQGSJqEnmnowyy/Q8B+FgIMTqtCjJMpcImAIZh0mQ+gB5ENBrIrlpHRPumXCeGqQhYAGAYJjWEEI0Avgbg10Q0E9mV0o5ItVIMUyFwGCDDMAzDVCCsAWAYhmGYCoQFAIZhGIapQFgAYBiGYZgKhAUAhmEYhqlAWABgGIZhmAqEBQCGYRiGqUBYAGAYhmGYCoQFAIZhGIapQP4/FK1LMeQHaeQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (8, 6));\n",
    "plt.plot(beml_df.index, beml_df.gain);\n",
    "plt.xlabel('Time');\n",
    "plt.ylabel('gain');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-09-19T05:17:11.276064Z",
     "start_time": "2022-09-19T05:17:10.688723Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sn.distplot(glaxo_df.gain, label = 'Glaxo');\n",
    "plt.xlabel('gain');\n",
    "plt.ylabel('Density');\n",
    "plt.legend();\n",
    "#Following almost Normal distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-09-19T05:17:14.232303Z",
     "start_time": "2022-09-19T05:17:13.632592Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sn.distplot(beml_df.gain, label = 'BEML');\n",
    "plt.xlabel('gain');\n",
    "plt.ylabel('Density');\n",
    "plt.legend();\n",
    "#Following almost Normal distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-09-19T05:26:22.010752Z",
     "start_time": "2022-09-19T05:26:21.988475Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean of Gain: 0.0004\n",
      "Return(gain) on daily basis is: 0.04 % \n",
      "\n",
      "Standard Deviation:  0.0134\n",
      "Risk involved is: 1.34 %\n"
     ]
    }
   ],
   "source": [
    "print('Mean of Gain:', round(glaxo_df.gain.mean(), 4)) #round up mean to 4 digits\n",
    "print(\"Return(gain) on daily basis is:\", round(glaxo_df.gain.mean(), 4)*100 ,\"%\", \"\\n\")\n",
    "\n",
    "print('Standard Deviation: ', round(glaxo_df.gain.std(), 4))\n",
    "print(\"Risk involved is:\", round(glaxo_df.gain.std(), 4)*100, \"%\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-09-19T05:27:14.120651Z",
     "start_time": "2022-09-19T05:27:14.100646Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean of Gain:  0.0003\n",
      "Return(gain) on daily basis is: 0.03 % \n",
      "\n",
      "Standard Deviation:  0.0264\n",
      "Risk involved is: 2.64 %\n"
     ]
    }
   ],
   "source": [
    "print('Mean of Gain: ', round(beml_df.gain.mean(), 4))\n",
    "print(\"Return(gain) on daily basis is:\", round(beml_df.gain.mean(), 4)*100 ,\"%\", \"\\n\")\n",
    "\n",
    "print('Standard Deviation: ', round(beml_df.gain.std(), 4))\n",
    "print(\"Risk involved is:\", round(beml_df.gain.std(), 4)*100, \"%\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-09-19T05:30:22.705437Z",
     "start_time": "2022-09-19T05:30:22.688756Z"
    }
   },
   "source": [
    "### Compute 2% loss or gain for Glaxo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-09-19T05:27:47.636356Z",
     "start_time": "2022-09-19T05:27:47.623592Z"
    }
   },
   "outputs": [],
   "source": [
    "from scipy import stats"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "prob=stats.norms.cdf(x,mean,sd)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-09-19T05:28:28.312651Z",
     "start_time": "2022-09-19T05:28:28.294794Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.06352488667177397"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Probability of making 2% loss or higher in Glaxo\n",
    "stats.norm.cdf( -0.02,loc=glaxo_df.gain.mean(),scale=glaxo_df.gain.std())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-09-19T05:29:50.702458Z",
     "start_time": "2022-09-19T05:29:50.674100Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.07104511457618568"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Probability of making 2% gain or higher in Glaxo\n",
    "1 - stats.norm.cdf(0.02,loc=glaxo_df.gain.mean(),scale=glaxo_df.gain.std())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Compute 2% loss or gain for BEML"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-09-19T05:52:15.518168Z",
     "start_time": "2022-09-19T05:52:15.508185Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.22155987503755292"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Probability of making 2% loss or higher in BEML\n",
    "stats.norm.cdf( -0.02,loc=beml_df.gain.mean(),scale=beml_df.gain.std())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-09-19T05:52:54.489662Z",
     "start_time": "2022-09-19T05:52:54.476361Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.22769829484075343"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Probability of making 2% gain or higher in BEML\n",
    "1 - stats.norm.cdf(0.02,loc=beml_df.gain.mean(),scale=beml_df.gain.std())"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}