HW2_Problem3.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load Data\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.font_manager as fm\n",
    "import sklearn\n",
    "from sklearn.neighbors import KernelDensity"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Loading full and 2012 data\n",
    "df = pd.read_csv('hour.csv')\n",
    "df_2012 = df[df['yr']==1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "    }\n",
       "\n",
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       "        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>instant</th>\n",
       "      <th>dteday</th>\n",
       "      <th>season</th>\n",
       "      <th>yr</th>\n",
       "      <th>mnth</th>\n",
       "      <th>hr</th>\n",
       "      <th>holiday</th>\n",
       "      <th>weekday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>weathersit</th>\n",
       "      <th>temp</th>\n",
       "      <th>atemp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>casual</th>\n",
       "      <th>registered</th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8645</th>\n",
       "      <td>8646</td>\n",
       "      <td>2012-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.3788</td>\n",
       "      <td>0.66</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>5</td>\n",
       "      <td>43</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8646</th>\n",
       "      <td>8647</td>\n",
       "      <td>2012-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.3485</td>\n",
       "      <td>0.66</td>\n",
       "      <td>0.1343</td>\n",
       "      <td>15</td>\n",
       "      <td>78</td>\n",
       "      <td>93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8647</th>\n",
       "      <td>8648</td>\n",
       "      <td>2012-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.32</td>\n",
       "      <td>0.3485</td>\n",
       "      <td>0.76</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>16</td>\n",
       "      <td>59</td>\n",
       "      <td>75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8648</th>\n",
       "      <td>8649</td>\n",
       "      <td>2012-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.3333</td>\n",
       "      <td>0.81</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>11</td>\n",
       "      <td>41</td>\n",
       "      <td>52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8649</th>\n",
       "      <td>8650</td>\n",
       "      <td>2012-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.28</td>\n",
       "      <td>0.3030</td>\n",
       "      <td>0.81</td>\n",
       "      <td>0.0896</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17374</th>\n",
       "      <td>17375</td>\n",
       "      <td>2012-12-31</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.2576</td>\n",
       "      <td>0.60</td>\n",
       "      <td>0.1642</td>\n",
       "      <td>11</td>\n",
       "      <td>108</td>\n",
       "      <td>119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17375</th>\n",
       "      <td>17376</td>\n",
       "      <td>2012-12-31</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.2576</td>\n",
       "      <td>0.60</td>\n",
       "      <td>0.1642</td>\n",
       "      <td>8</td>\n",
       "      <td>81</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17376</th>\n",
       "      <td>17377</td>\n",
       "      <td>2012-12-31</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.2576</td>\n",
       "      <td>0.60</td>\n",
       "      <td>0.1642</td>\n",
       "      <td>7</td>\n",
       "      <td>83</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17377</th>\n",
       "      <td>17378</td>\n",
       "      <td>2012-12-31</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>22</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.2727</td>\n",
       "      <td>0.56</td>\n",
       "      <td>0.1343</td>\n",
       "      <td>13</td>\n",
       "      <td>48</td>\n",
       "      <td>61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17378</th>\n",
       "      <td>17379</td>\n",
       "      <td>2012-12-31</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.2727</td>\n",
       "      <td>0.65</td>\n",
       "      <td>0.1343</td>\n",
       "      <td>12</td>\n",
       "      <td>37</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8734 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       instant      dteday  season  yr  mnth  hr  holiday  weekday  \\\n",
       "8645      8646  2012-01-01       1   1     1   0        0        0   \n",
       "8646      8647  2012-01-01       1   1     1   1        0        0   \n",
       "8647      8648  2012-01-01       1   1     1   2        0        0   \n",
       "8648      8649  2012-01-01       1   1     1   3        0        0   \n",
       "8649      8650  2012-01-01       1   1     1   4        0        0   \n",
       "...        ...         ...     ...  ..   ...  ..      ...      ...   \n",
       "17374    17375  2012-12-31       1   1    12  19        0        1   \n",
       "17375    17376  2012-12-31       1   1    12  20        0        1   \n",
       "17376    17377  2012-12-31       1   1    12  21        0        1   \n",
       "17377    17378  2012-12-31       1   1    12  22        0        1   \n",
       "17378    17379  2012-12-31       1   1    12  23        0        1   \n",
       "\n",
       "       workingday  weathersit  temp   atemp   hum  windspeed  casual  \\\n",
       "8645            0           1  0.36  0.3788  0.66     0.0000       5   \n",
       "8646            0           1  0.36  0.3485  0.66     0.1343      15   \n",
       "8647            0           1  0.32  0.3485  0.76     0.0000      16   \n",
       "8648            0           1  0.30  0.3333  0.81     0.0000      11   \n",
       "8649            0           1  0.28  0.3030  0.81     0.0896       0   \n",
       "...           ...         ...   ...     ...   ...        ...     ...   \n",
       "17374           1           2  0.26  0.2576  0.60     0.1642      11   \n",
       "17375           1           2  0.26  0.2576  0.60     0.1642       8   \n",
       "17376           1           1  0.26  0.2576  0.60     0.1642       7   \n",
       "17377           1           1  0.26  0.2727  0.56     0.1343      13   \n",
       "17378           1           1  0.26  0.2727  0.65     0.1343      12   \n",
       "\n",
       "       registered  cnt  \n",
       "8645           43   48  \n",
       "8646           78   93  \n",
       "8647           59   75  \n",
       "8648           41   52  \n",
       "8649            8    8  \n",
       "...           ...  ...  \n",
       "17374         108  119  \n",
       "17375          81   89  \n",
       "17376          83   90  \n",
       "17377          48   61  \n",
       "17378          37   49  \n",
       "\n",
       "[8734 rows x 17 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2012"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Averaging hourly demand for 2012\n",
    "hr = np.linspace(0,23,24)\n",
    "Avg_hr_demand = []\n",
    "for h in hr:\n",
    "    avg = sum(df_2012[df_2012['hr']==h].cnt)/len(df_2012[df_2012['hr']==h].cnt)\n",
    "    Avg_hr_demand.append(avg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 7200x1080 with 0 Axes>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 7200x1080 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting average hourly demand for year 2012\n",
    "plt.figure(figsize=(15,15))\n",
    "plt.bar(hr,Avg_hr_demand,align='center',color='b')\n",
    "from matplotlib import rcParams\n",
    "rcParams[\"font.family\"] = \"Times New Roman\"\n",
    "rcParams.update({'font.size': 14})\n",
    "position=np.linspace(0,23,24)\n",
    "plt.xticks(position, np.linspace(0,23,24), rotation=90)\n",
    "plt.xlabel('Hour of the day')\n",
    "plt.ylabel('No. of avg. hourly trips')\n",
    "plt.title('Hourly Bike Trip Demand Distribution')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Hourly demand histogram')"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "X = df_2012.cnt[:, np.newaxis]\n",
    "X_plot = np.linspace(1,1000,1000)[:, np.newaxis]\n",
    "plt.figure(figsize=(15,15))\n",
    "plt.hist(X,bins=50,density=True)\n",
    "plt.xlabel('Hourly demand values')\n",
    "plt.title(\"Hourly demand histogram\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "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"
    },
    {
     "data": {
      "image/png": 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546BiZmZ546BiZmZ546BiZmZ546BiZmZ546BiZmZ546BiZmZ546BiZmZ546BiZmZ546BiZmZ546BiZmZ5U9KdB5NUAVwA1AJDgDMjYl0L5Y4EjiIJevdGxE3tycs4xmeA1cC8iPh3FzXHzMyydGtQAS4H7oyI30k6ArgSOCazgKQpwHnA9IhokvSgpLkR8WyuvHTfIcC1wGkR8WK3tszMzLqv+0vSGOBY4NY06R7gfZJqsoqeThJ4mtLtu4CvtSMP4PfA/zigmJkVRneOqcwAVkTERoCIaAAWAAdnlTskTW82L903Z56k9wK7APtI+qukCySV5bcJZmaWS3d2f40FVmal1QJj2iiXWSZX3rHAv4CLgWuAJwAB38iuiKRTgVMBJkyY0LFWmJlZq7rzTCWATVlp/YD6NspllsmVtwfwj4ioj4iVwC+BT7RYkYirImJ6REwfPnx4hxtiZmYt686g8irJjK9MA4DFbZTLLJMrr4Rtz7yeBoZuR33NzKyDujOo3AeMSaf8IqkUmAA8kFXubmDXjO0p6b5t5T2dldcAzMlLzc3MrF26LahExFLgNuCdadKhwM0R8aqkr0tqDghXAIcDSBLJ4PzF7cj7OXCkpH7p9gEZeWZm1g26+zqVzwEXSNoTGEU6WE5yrcpCkosVn5V0qaSL0rwLI2I2QBt5/5L0beBiSfOAjRFxdTe1y8zMAEVEoetQUNOnT4+ZM2d2budzBrWSvrbzFTIz6wEkzYqI6dnpXvvLzMzyxkHFzMzyxkHFzMzyxkHFzMzyxkHFzMzyxkHFzMzyxkHFzMzyxkHFzMzyxkHFzMzyxkHFzMzyxkHFzMzyxkHFzMzyxkHFzMzyxkHFzMzyxkHFzMzyxkHFzMzypt1BRdJVkqq6sjJmZtazdeR2wsXAeem94W+OiAe7qE5mZtZDtTuoRMSnACSVAx+S9EtgEXBtRCzqovqZmVkP0u6gIqkkIhpIusyGAocAAgam3WK3R8TtXVNNMzPrCTrS/XW5pFrgJGA2cAZwS0Q0AUj6rqR9I+L7XVBPMzPrAToy++sUYCxweEQcFBE3NweU1Crgy3mtnZmZ9SgdOVP5XERcmZkgqTQi6tPNvwIv5a1mZmbW43TkTGVMC2ljJX0bICLmR8Rf8lMtMzPrido8U5H0aWA08A5JjVnZQ4FPAOd2Qd3MzKyHaU/317XA5cBgYGJW3hbguHxXyszMeqY2g0pEbEnPVt4REfd2Q516nC1RzPcbTqCcLXyr5AaKC10hM7MCaTWoSCqPiM0AERFAiwFF0okRcU3XVK9n+FPjgVzf+C4A9iyaz3sLXB8zs0LJNVA/R9InmzckLZLUmPVoAv6366u5Y7uh8RCm6GXGaRk3NL6z0NUxMyuYXN1f7wAWZ2z/HHgUeBmINK2IPj6msjH68UxM4rPFtxKIqxqPYn1dA/37dWS2tplZ79DqmUpELIyILRlJlwAPp+kvpY8FwEVdXssd2JNNk2mkmOlFz7F/0WwaKOGxhasKXS0zs4LINaYyoZX0bTaBTwJ9dmmWZyOZELdX0QuUs4ViGpm1cDXv2HVEgWtmZtb9cvXR3AHsRhI4cgn6cFCZH2OoZi1DtB6AyVrMnCWjC1wrM7PCyDVQ/2Ng14goau1Bco+VU7qnqjumF5tGM0lbh55210v8Z8m6AtbIzKxwco2pXBcRL+TaOZ1q/Ie816oHmR9jmFy05PXt3YteYsnazazesCXHXmZmvVOuMZX9gf9ExNp0+79aKgZ8iD66OvH6KGcVA9lJS19P213JmppzlqzjgJ2rC1U1M7OCyDWmcjlwHnBTun0hMAVYw9YpxQJG0UeDypIYBsAYrXw9bdei5CaY816rdVAxsz6n1aASEXtnJf0Y+FtE1GYmSjqiKyrWEyxOg8pobZ1CXM06BpSXsGDFhkJVy8ysYNq99H16U65aSaWSRmSk39k1VdvxLYmhAIzOOFORYNLw/ry43EHFzPqedgcVSeMl3QlsApZKWi7pG11XtR3f4hiGaGIkq7dJn1Rd5TMVM+uTOnKTrhuAgcDbgEpgGtAo6fNdUbGeYClDGcEaSrNuMzOpuopX12xi05bs28+YmfVuHQkqbwI+GRGzImJzRCyJiIuAPjsavSSGMUpvXJJl4vAqAJ+tmFmf05Ggch4wuYX0fdr7BJIqJF0i6XxJv5A0sJVyR0q6VNLlkj7c3ryMMh+TdH9769VZi2PYNjO/mk2q7g84qJhZ35PrOpW/AP0zk4DPS1qYkVYJzO3A8S4H7oyI36Wzxq4Ejsk67hSSADY9IpokPShpbkQ8mysvY/8xwNlAl6/q+FoM4aCiZ96QXlNdCcCLy9d3dRXMzHYoua5TeZYkkDwHNOUod1d7DpR+2B8LfCFNuge4WVJNRCzMKHo6SeBpPuZdwNeAk9rIa3YmcAXw0fbUq7M21zeynkqGa+0b8irLShg9qNxnKmbW5+QKKj8BiIjVrRWQVMO2ZzO5zABWRMTG9HkbJC0ADgYWZpQ7pPnYqXlsXV8sVx6SPkUyoWBqO+vUaSvTZViqeWNQAagZVsWClQ4qZta35Lr4cZtgImk08HGSINK8cnEF8AHa9yE+FsgegKgFxrRRLrNMq3mSJgNDI+IRSTnrI+lU4FSACRNaXOG/TStq6wAYppYXj6ypruLOZ5e0mGdm1lt15PaEN5J8iFcDc9K03YFr27l/kFzjkqkfUN9GucwyLeZJKiLpVjujXRWJuAq4CmD69OnRRvEWrdzQHFRaPlOZWF3J6o31rN1Yz6DK0s4cwsysx+lIULk/Ir4raRrJGcH96TjJ6e3c/1VgSFbaALa9ZXFL5TLLtJb3dpIzjxPSm4j1A8olrYiILpnyvGJ9c/dXK2cqw9JpxSs3sFfl4K6ogpnZDqcjU4pHSHo7yWyvI9M7Q44BTmzn/vcBYyRVAEgqBSYAD2SVuxvYNWN7SrpvrrxHSW4otlf6+G9gZvp7l1ixPnf318TqJKgs9GC9mfUhHQkqvwF+RnJdyi9IgsEjwJ/bs3NELAVuA96ZJh0K3BwRr0r6uqTmYHEFcDiAktOOQ4CLc+VFRF1EvNL8AFYDdenvXWLl+i1UsplK1bWYP35oJZKvVTGzvqXd3V8R8TDwloykiZKGRkRHrgf5HHCBpD1Jlsw/NU0/hmQG2Lz0epRLJV2U5l0YEbPTOrSa191WrK9r9SwFoLy0mDGDKnjJM8DMrA9pd1CRVEYyfvIeYChJN9gFwL/b+xzpjLJPt5C+b9b29cD1rTxHq3kZZa4BrmlvvTpj5fotrU4nblZTXcmClRu7shpmZjuUjnR//RL4KnALSXD5PfANSYd2RcV2dMmZShtBZViVx1TMrE/pyOyvDwDvjYgHM9JulHQeydXxfcoJ+9cw5LaHcpaZWF3F2k31rN6whSFVZd1UMzOzwunImcqtJLcSzjaihbRe79i3TeDI4sdylsmcVmxm1hfkWlDybKA4I2kR8D+SMqcAVwHju6huPV5NxrTifSZkX6JjZtb75Or+2oPkOpSX2Lqg5CJgYla5s7ugXr3ChKGVFMnXqphZ35ErqHwPWJteX2KdUFZSxNghFZ4BZmZ9RqtjKhExLzugpDe/+rukeZL+kt4TxXLwDDAz60s6cp3KmSRTiW8gmVYs4DhJE9IFGq3ZOYNe/3Vi/Ync0ngg8d1B6Hu5pyCbmfV0HZlSfCBQExGZqwRfkk4ptlbUaCm1VLKSgXTJypZmZjuQjkwpfiIroDTbJV+V6Y0mKulBXBijClwTM7Ou15GggqRTJO0uaU9Jx0i6B/AodA41rweVkQWuiZlZ1+tIUPkBMBl4GHgC+BUwm2SRSGvFOC2nmEYWNvlMxcx6v46MqRxBsv7X2cBwYHlENOXexUrVyHgtZ4G7v8ysD+jImcqvgGkR0RQRrzUHlPRmW5bDTlrqMRUz6xM6ElROJJlG/Lr0Rllfz2eFeqOJaVCJiEJXxcysS3Wk++sKYLykzE9GAQH8MK+16mVqtJQNVLB8fR0jBpQXujpmZl2mzaCSno1MI7ml72Mk6381BxYBp3RZ7XqJ5mnFC5ZvcFAxs14tZ1CRtBNwOzA1TXoIeHdEbMwo8/2uq17vMKXoFQCee62Wt00aVuDamJl1nbbGVC4CFgAfBj4C1JE1hhIRW7qmar3HKFYxkA3MXVpb6KqYmXWptrq/BkTEYc0bkm4FfppZQFJFK1faW0qC3bSIeUvHFboqZmZdqq0zldcyNyKiHpifVeb9ea1RL7Vr0cvMW1rrGWBm1qu1dabyHkkPZqWNlvShjP33AG7Me816mV31MrV1Dby6ZhPjhlQWujpmZl2iraCyEHgAaMixf0U+K9Rb7Vb0MgDzltY6qJhZr9VWUDktIh7IVUDS3/NYn15ripKgMndpLe+c6sUlzax3yjmm0lZAScvcn7fa9GIDtYmxgyuY5xlgZtaLdWjpe9s+U0cPYPZi3/3RzHovB5VuNG3cYF5csYHazfWFroqZWZdwUOlG08YNIgKeedVnK2bWOzmodKM9xw0G4OlXHFTMrHdyUOlGQ6rKmDC0kqdeXlPoqpiZdQkHlW625/jBDipm1ms5qHSzvccPZvHazSxZ6+XSzKz3cVDpZm+dOBSAR15cVeCamJnln4NKN5s6eiADykt4ZMHKQlfFzCzvHFS6WXGReGvNUJ+pmFmv5KBSAG+bNJQXV2zgtXWbC10VM7O8clApgAMmVwPw4HPLC1wTM7P8clApgD3GDGTUwHLunbus0FUxM8srB5UCkMQhU0fw4HPL2dLQVOjqmJnljYNKgbxztxFs2NLoWWBm1qs4qBTIAZOrqSor5ranlhS6KmZmeeOgUiAVZcUc+ebR3P7MEjbXNxa6OmZmedHW7YQtn84ZtM3m0Y27c1P9t7lr9lLev9fYAlXKzCx/ujWoSKoALgBqgSHAmRGxroVyRwJHkZxJ3RsRN7WVJ2kQ8CvgcGA+8LmI+HfXtmj77Fc0h7Es5zePLOq5QSUrUG5N9/L+Zn1Rd3d/XQ48HBFnAX8GrswuIGkKcB7w5Yj4PPBlSW9qKw84E/gj8A5gMfBnSVVd3aDtUaTgpJI7eXTBKma9tLrQ1TEz227dFlQkjQGOBW5Nk+4B3iepJqvo6cCdEdE81/Yu4GvtyLsnIn4bEbPS4wwFds93O/LtmOJ7GVxZymX3vVDoqpiZbbfuPFOZAayIiI0AEdEALAAOzip3SJrebF66b868iLi3OTEi1gLrgFdaqoikUyXNlDRz+fLCXtVepTo+fdAk7p27jPvm+WJIM+vZujOojAWyL8qoBca0US6zTK6816XdZPdHRIvzdSPiqoiYHhHThw8f3v4WdJFTDprI5OFVfOdPz7Juc32hq2Nm1mndOVAfQPadqfoB2Z+i2eUyy+TKy/QF4Budrmk363fuUH7cNIWPb/k2X/j+hfy69CeUqnGHH+yub2zin43TeDYmArCHFvD2otlJ3c2sT+rOoPIqyYyvTANIBtVzlcsskysPAEmHkpylvLi9Fe5O04ue47ySX3Nmw6l8sv5MLi69lOpCV6oVdQ2N/PaRRVx2/3yW139zm7wJeo2zSm7giALVzcwKqzuDyn3ALyVVRMQmSaXABOCBrHJ3A7tmbE9J920rD0lTgUkRcVW+K98dPlZyP8Vq5Kz6U5hRdxGf+Osc3jl1JLuM6M+gilIkWF/XwOoN9SxfX8eydZtZVlvHa+s2s2rDFspLixlaVcbOI/qz66gB7DS0kpLi1ns4I4K6hiZKi4soLlKb9atvbOKPj7/CxX9/gVfXbOJtE4fyw83ncUDRbAAebJrGzxqO5rP1X+VDv3+K771/D/r386VQZn2JIqL7DibdCFwfEbel15scHxHHSvo6cGtEzEunCP8qIvaTJOBB4LMRMbuNvEnAl4Cfp4cbBBwQEb/IVafp06fHzJkzO9eg1q7R2E4vNI3hwoaPcjdvo7Fp6/tTJGhq4e0qLhJDKsuoW7+KWrbOoi6lgRotZbyWUcEWGihidQxgDf1Z3X9n1m6sZ0tjMpGuX0kRYwZXMHHVQ9RoKTtpGRP0GpWqY21U8cTbL+cvTy7m1TWb2HPcIL522K4ctEs1+t7gbepSH8Vc0vBBLm06mvFDK7n443hY+y8AABWCSURBVHuz5/hty5hZzydpVkRMf0N6NweVISQXPy4ERgHfioj1kmYBP8y4kPE4YJ90twci4s8Zz/GGPEmjgUeA8VmH/HhE/C5XnXbEoNJszRnLmfXSahas2MD6ugYam4KB5aUM/ttXqNY6Rmg1I7SaYdRSpOR93BylPB/jmNs0nvkxhvkxhsUxjDpKKSIYzHqGqJYh+36IwZVlDKwoob4h2LClgVdWb+TFZx9hYYxiM/22qUuR4O07V3PC/jUcOnUESUxv/TV49JMLOO3GJ1hWW8dX3zWFTx04kfLSYl8sadZL7BBBZUe0IweVLtXah/g5g4iA5QzmpRhJXZRSpU1MOftRqlrqysoRJNZurOesW57h9meWMHxAP94zbTR7PvoNBlNLEUEJjZSqkcGsZ9I5s9vVBWdmOwYHlVb02aDS1TKC1r/mr+R/H36RB59f0er9YypKizlk6ghOfnsN++40tLtqaWad1FpQ8Siqdbn9Jw9j/8nDqGto5OXvv4laKmikmAaKaIgSljGYWfv8iNufWcLtTy/hqGmjOe8Db2JwZVmhq25mHeSgYt2mX0kxOxdlzyBPHP3BN3P2UVP55YMLuPS+53n8pdX84rh92cuD/GY9iu+nYjuGcwZRef4wvvLwdP5YfBYl6xZxzGV/5765XrrGrCfxmIrHVHZIy2MgJ205kzmaxIUfmcYH9x5X6CqZWYbWxlR8pmI7pOFax41lP+CtNUM5/fdPccMjiwpdJTNrB4+p2A6rvzZz9avv4XM6jbNugY23nsEpJXckmb6uxWyH5DMV26GVq54rSy/iyKJHOLfheC5p+AB9vMfWbIfmMxXb4ZWpkUtKL+GM+i38tOGjbIhyzozYelW/me0wHFSsRyhRExeWXkFFQx1XNL6PTX+ZzXffuwdFvgrfbIfioGI9RpGCc0t+TQV1/OpfR1Fb18D5H3xzsqaYme0QPKZiPYoEZ5f8hq8eOoU/Pv4q77/0H8xbWlvoaplZykHFehwJvnLoLlx78ltZuaGO9176MBf//XnqGnzHSbNCc1CxnumcQRx8w87cUX8y72r6Bxfd/RxHfedXPPLiykLXzKxPc1CxHm241nFZ2SVcXXoBm6IfH7vq35x24xMsXrOp0FUz65McVKxXeEfxk9zd7ww+P2Myf312KYf89H4u+ts8NtQ1FLpqZn2Kg4r1GpWq44wjduPvpx/MoVNHcvG9LzDjwvu58oH51G6uL3T1zPoELyjpBSV7rVlNu3BRw0f4R9ObGFhewif224nj9tuJsYMrCl01sx7PC0pan7Nv0fP8pux8/lz2bQ6YXM2VD8znoB/fy2f/bxb/nL+Cvv6Fyqwr+OJH6/X2LHqRK47fl5dXbeQ3jyzid48t4s7ZS9llRH9OOKCGo/ceS1U//yuY5YO7v9z91edsjlJubdyfaxsP59mYyAA28qHiBzm++G4mFy1JCnkVZLOcfI96s1S56vlIyYN8uPhBnoidua7hMH7TeCjXNB7BQUVP88niv/GOpqDY64qZdZjPVHymYiR3mryx8RCubziU1xjK+KEVHL/fTnx0+ngGV5YVunpmO5zWzlQcVBxULEN9FHN3075cM+77PLpgFf1KinjfnmP44D5jedvEYT57MUu5+8usHUrVyLuLH+Xdn9mfOUvWcd2/XuLPT77KH2a9wvAB/TjqzaN5z7TR7DNhSNcsu9/aFxWP8VgP4aBi1pJzBjEV+CHw3yrj3tK9uXXD/tzw6H5c88+FjBlUzlHTRvPePcfw5rGDOnXDsLUb65m/Yj0vLt/Ai8vXs2jVRrZs+SpVbGZS0RIOKJrNXnqBYvXt3gTrWRxUzNpQoS0cVfwIRxU/Qm1UcI/24bba/bnmoWn88qEF7KSlHH7QAew9fjA7j+jP0KoySkuK2NLQxNpN9by2bjPL1tXx6ppNLFyxgQUrNvDiig2s2rDl9WOUFIlxQyooj5Gsi0puaTqInwKjWcnJJXdwTF0D/T3t2XoAj6l4TMU6aU1UcVfjW7i1aX8e0TTqG9v+XxrBaiZqCZPecgQTqyuZVN2fScOrGD+0ktLiotf/ptZGJfc37cmNjYfwr6Y9GFZVxumHTeFj08dTUuxrlq3wPFDfCgcVy4e6KGFuTGBhjGRVDKSRYsqoZ4A2MpLVjNRqRmkVVarr8HM/2TSZ88dexqMLVrHryAGcfdRU/mvK8C5ohVn7Oai0wkHFeoIIuLPpLfyw4VgWxUjeXvQsZ3zuM+w5fnChq2Z9lNf+MuvBJDiy+DHuLvsG3y25lrlN43n/Zf/g+P99hDufXcrmet/10nYMHvkz60H6qYGTSu7iI8UPcO2Mf3D9v1/is9fPory0iLdOHMbUUQOYNLyK6v79GFxZxpDKUoZUljG4srRTM9TMOspBxawH6q/NfOEdO/OZ/5rEQy+s4IF5y/n3iyv59/yVbGlsekP5MuoZMWQgIweWM3ZwBbuM6M8uI/uzy8gB1Ayr8kWdljcOKmY91TmDKAHekT4AGkvE4uJqVjKQ1dGfNfRnVQxgWQzmtbVDeW3tEGa9NIK/sHWgv7y0iF1HDWSPMclj99ED2W3UQCrKigvRKuvhHFTMepFiBeO1nPEsz1luQ/RjfozhuRjHnLddwOzFa7ntqcXc8MgiAIoENdVJN9qgilIGlJdQWVZMRWkxFf/8KRWqo4I6KqmjXFuopI6KT/6BgeWlDB/Qj2H9y5Ip0tbnePaXZ3+ZAckMs1eimv9EDbObduK5GM+qGMA6KqmNSjbRj02UsYnydj3fkMokwFQv/zdDqWWw1jOY9QzWBkZqFVO/dBM1w6p83U0P5bW/zCwnCcZrBeNZweHFrX/RioDNlLGJfmykH5sj/f3Ev7N2Uz0r1m9heW0dy9dvTn4uK+M/7MSapqQ7rql50ulFD1JVVsz+k4dx0C7DOXCXaiZVV3lCQQ/noGJmHSJBBVuoYAtDqYXmGHDdpJZ36Lf116YQ6ynnlRjOnPffweOLVvPQ8yu4Z84yAMYMKufAXap5+87V7D95GCMGtO+syHYcDipm1m2KFAxkE7trEbvfugcfStNfKhvBQ01v5uHaN3Pnswfw+5mvADB8QD+mjh7I1NEDmDJiAFNGDmDyiCoqy/zRtaPymIrHVMx2KI0hnolJzGyawpymCcyJnXg+xlGffgeWYNyQiiTIjBrAtLGDmDZ+MGMGlbvrrBt5TMXMeoRiBXtpPnsVzX89rSGKWBijeD7G8lyM47k143hh9VgemDuGhvRjrJq17Fk0n2lF85mmF9n5q3cyoLyEspIiNm1pZOOWRpbV1vHaus28tm4zS9dtZvm6OlZs2MKK2jpWLlnIagbQSBGBKKGBwWxg6KgJDOtfxtjBFYwbUsm4IVt/jhxY7mt8svhMxWcqZj3W5ihlbkzgqabJPNU0iadjEvNjDNGOFajKqGc4a6jWOqq1lmFayxBqKaEJEdRTwhr6szr6szwG82pUs4wh2zxHabEYN6SS8UMr2WloJROGVjJhWCU7Datk/JBKqnrx7Qp2iDMVSRXABUAtMAQ4MyLWtVDuSOAokrXJ7o2Im7Y3z8x6n3LVv+GspjYqeKZpIq+87/esr2tgS2MTlWXFlJcWM3xAP0b+5p2M0mqGUEtHe8s2RymLYxivxHBejuG8EsNZtGoki1aO4MkYyTqqtilf3b8fE4ZWsNOwqtcDT011JTsNq2JYVVmv7K7r7jB6OXBnRPxO0hHAlcAxmQUkTQHOA6ZHRJOkByXNjYhnO5vXzW00swIaoE0cUPwfuP1NLRfYjstiylXPJC1lEktbzF8bVbwUI1gUI3gpRrJo00gWvTKCRxeN4E8M2+YMqopN7DR6JJNH9Gfy8Cp2HtGfycP7M7G6ivLSnruaQbcFFUljgGOBL6RJ9wA3S6qJiIUZRU8nCTzNCxjdBXwNOGk78szMutwgbWCaFjCNBW/I2xLFvBLDeSlG8lKMZGGMYsGA43ny5dXc9vRimkciJBg/pJJRg8oZWF7CwPJSykq2jYQREMTrvwM0D2SUlRQxoF8J/fuV0L88+TmgvJSB5cnPAeUl6eONz5sP3XmmMgNYEREbASKiQdIC4GBgYUa5Q4CfZGzPA07Zzjwzs4IqU+Mbz3IWXQfAprIyFsQo5scYXmgay/w1Y1i+ehCLqWQuldTHGz+qRbx+iZDYOja+hVJqqaCOsjbrNPt7h+d93Kc7g8pYYGVWWi0wpo1ymWU6m7cNSacCp6ab6yXNa0f9W1INrOjkvj1VX2tzX2svuM0FsgLo1t766v4/3q4279RSYncGlQA2ZaX1A+rbKJdZprN52x4g4irgqvZWvDWSZrY0+6E362tt7mvtBbe5r+iqNnfnSm6vQtZ8PBgALG6jXGaZzuaZmVk36M6gch8wJp1WjKRSYALwQFa5u4FdM7anpPtuT56ZmXWDbgsqEbEUuA14Z5p0KHBzRLwq6euSmgPCFcDhAEomcR8CXLydeV1lu7vQeqC+1ua+1l5wm/uKLmlzt15RL2kIycWPC4FRwLciYr2kWcAPmy9WlHQcsE+62wMR8eeM5+hUnpmZdb0+v0yLmZnlj2+5ZmZmeeOgYmZmedN7l9DsQu1dGLMnkXQ08FNgIHA98LV01YNW29pbXgdJZcBjwFci4v6+0GYASfsBBwIvAA8DG+il7ZY0FfgiSVt3Aa6KiCd723st6V3AucDHmpe/6mwbO93+iPCjgw/g6vRNAzgC+G2h67Sd7ZkAXAfsC5xA8uHy9bba2lteB+BsYC0wow+1+STg3Ky0XttuYCYwNv19AjCnt7UZGAl8kORC8JrtfV872/6CvxA97UGy9EsdUJlul6QfwjWFrNd2tukgoCRj+wLg9lxt7S2vA3AAcDLJjMQZfaTNB5Ms6KqMtF7d7rS+u6W/Dye5MLrXtZlkSOP1oNLZNm5P+z2m0nEzyFoYE2heGLNHioiH0nY0exVYRO625srrESRVAR+OiF9nJM+gF7c5dREwB7hE0p2S3k7vb/dNwK8kDQCOA75EL2xzbF2lvdkMOtfGXHk5Oah0XHsXxuzJ3kJyMWmutvaG1+FM4EdZab26zelFxnsDv4yILwJ/B+4ExtOL2w18HthMMna2PiJuppe/16nOtrHT7XdQ6bj2LozZI0naGVgeEU+Ru609+nWQdDgwMyKWZWX12jan9gBWRcTT6falgOj97a4AfgvcAPxM0qH0/jZD59vY6fZ79lfHtXdhzB5HUjHwGeCbaVKutkaOvJ7g68DeGbdzHQL8maRrqLe2GZL/+df/7yNik6TngWJ6d7uvBz4eEWskBUmAOY3e3Wbo/P9w59tf6IGlnvYgWV5mPVCRbpeSDGiNLXTd8tC2M4GR7WlrT38dSAZrx2U8XgY+QjIzqFe2Oa3zbukHRub7/Bjwyd7abpJ7pSzJ2BYwn2Q6da9rM9sO1Hfqf3h72u/urw6KHAtjFq5W20/SWcATQIWkSZJOBvrTSlt7+usQEcsj4pXmB9BI0u23iF7aZoCImAvcAXwYQNJgoAz4Db233auAzZLGZqStBJ6ml7VZW0+9Bbk/rzqb12Yd0ihkHdDawpgFrdR2kPRt4AdZyXMjYmqutvam10HSQuDESC5+7NVtllQN/Jzk2o0JJIP2/+nN7Za0J8lg/SyS6zkejIgHelObM2a2XQ58H7g0IpZ3to2dbb+DipmZ5Y27v8zMLG8cVMzMLG8cVMzMLG8cVMzMLG8cVMzMLG8cVMzMLG8cVMy6iKRpkv4g6TuFrktXkjRY0nmSbi10XazwHFSsT5D0Nkn3SmqQ9HlJQyWVSfqEpDWSnpF0WJ4P+wIwiGRdrY7UtUbSzySFpH9IukLS1ZLuSeu+o/3fimQ9sQGFrogVni9+tD5D0qeA70fE2Kz0B4GHI+KsLjjmtcCCiDing/vtDDwP7BIRL6Rpu5AsUz8zIj6W77puj3RZnxMiYkah62KFtaN94zHrSo0ki+1la0ofXaGz39oashMi4nngGOCjkj64XbXKv656/ayHcVAxyyJpjKSLJZ2bdpm9O00/TNIKSScq8YW0i6pG0r6Sbpb0A0l/lfSvrOccLOmOtPyhadoESXMlvau9dYuIR0kWQjwufY7+kr4t6QJJj0n6r4wxjlmSDpb0pKQFknaVdKakVyQ9KmlQ+hx7SPpfSWel3W1vltRP0mmSXk7HhmZJWippekabDpN0laQfAJ/e7hfeegUHFetrBkr6UeYDmJRV5mbgsoj4NnAGcIukmoj4GzAbIJJ+48sz9vkPyarOM4CvZeUREWuAE4CNwPI0eQVwb0Tc3cE2zAV2SX//CfB/EXEG8EvgRpJ7if8H2Ckts3e6zy9IVp6tIVnKvLkL7XvAAxFxPvAkcCrJzZgeIrktwF7AfiT3m/kqJIEX+B/gixHxHZIVrs18ky7rc9ZFxDczEyTtl/H7viTjGPMAImKmpDkk9xv5HhndWRERzSuNR3Kzq6XAwoiYQ3IP+G2kK8ZeC3yR5Jv90cAfOtGGAIrTZc6PBual9RhCchYzjORmSusj4oG0XTOB8RExO91+hmTlWYDzgAWSJpMEnGUR0SRpVVrv69J9HiPpfgP4AvCPiNiSbs8E3tSJtlgv46Bitq1dSL7FZ5pP8o29LUHbYyg/A56UdDZwMMlZQUdNITljGkEyu+znkTXjRtJuWfs0Zm03sbWn4mWSG7Q9AjxOcr96eGNbGtg6k20a8Fwn6m69nLu/zLa1iKSLLHOGmIB56e9NdHCKcKaIeA64F/gxsCg7GLRF0l4k3VlXk3SfFQHvzcjfRdLQDlbrj8DfIuJPvDH4tGYdMLWDx7E+wEHF+pJt7s+eoYytgeJfwFPAKQCSiknODK5P818D9pNUIen4NG1UxrUj2QFH6SPTRSTdaf/XRl23fSJpHHADcGVE3BERjSTdZ1dLOjkd8D8tIla1ctzWtvcGhqc3ZdqX9O6fpJ8PktTCPn8ADpd0SLo9EaiWlH2WZ32Mu7+sT5D0FpKB6RGSTgOuI7kH90dJunL6S7ovIv4m6UPAryQNJ/nm/vn09qqQnGHcCUwnCQyLSQbng2Qwey9Jt0TE42kX1H7AZEnXp1OCiYh7Jf0xIha2Utca4Cvp5oWS5gJVJB/c50fE9RnFvwhcSTJo/jRwgqSBwEdIgt1RJGdZh6Rtn04S+PYDdk7HeC4iGeT/E8lg/Dkk9ylvvpXspyXdARwO7C7pbRHxJ0n/DfxW0qPASyRnTjOAjk48sF7EFz+adTNJBwITIyLXmYpZj+QzFbNuIunDJF1t7yc5yzHrdRxUzLrP0STdTp+IiM2FroxZV3D3l5mZ5Y1nf5mZWd44qJiZWd44qJiZWd44qJiZWd44qJiZWd78P0oM2Suc5UMdAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "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": [
    "for bwidth in range (10,31,5):\n",
    "    \n",
    "    X = df_2012.cnt[:, np.newaxis]\n",
    "    X_plot = np.linspace(1,1000,1000)[:, np.newaxis]\n",
    "    kde = KernelDensity(kernel='gaussian', bandwidth= bwidth).fit(X)\n",
    "    log_dens = kde.score_samples(X_plot)\n",
    "    fig, ax = plt.subplots()\n",
    "    ax.plot(X_plot[:, 0], np.exp(log_dens))\n",
    "    plt.hist(X,bins=50,density=True)\n",
    "    plt.xlabel('Hourly Demand')\n",
    "    plt.ylabel('Probability')\n",
    "    plt.title(\"Kernel: Gaussian Bandwidth:{:.0f}\".format(bwidth))\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3(b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>instant</th>\n",
       "      <th>season</th>\n",
       "      <th>yr</th>\n",
       "      <th>mnth</th>\n",
       "      <th>hr</th>\n",
       "      <th>holiday</th>\n",
       "      <th>weekday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>weathersit</th>\n",
       "      <th>temp</th>\n",
       "      <th>atemp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>casual</th>\n",
       "      <th>registered</th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>8734.000000</td>\n",
       "      <td>8734.000000</td>\n",
       "      <td>8734.0</td>\n",
       "      <td>8734.000000</td>\n",
       "      <td>8734.000000</td>\n",
       "      <td>8734.000000</td>\n",
       "      <td>8734.000000</td>\n",
       "      <td>8734.000000</td>\n",
       "      <td>8734.000000</td>\n",
       "      <td>8734.000000</td>\n",
       "      <td>8734.000000</td>\n",
       "      <td>8734.000000</td>\n",
       "      <td>8734.000000</td>\n",
       "      <td>8734.000000</td>\n",
       "      <td>8734.000000</td>\n",
       "      <td>8734.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>13012.500000</td>\n",
       "      <td>2.489810</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.501946</td>\n",
       "      <td>11.520151</td>\n",
       "      <td>0.029883</td>\n",
       "      <td>2.994733</td>\n",
       "      <td>0.681704</td>\n",
       "      <td>1.413098</td>\n",
       "      <td>0.504825</td>\n",
       "      <td>0.482481</td>\n",
       "      <td>0.611193</td>\n",
       "      <td>0.189034</td>\n",
       "      <td>42.679757</td>\n",
       "      <td>191.986604</td>\n",
       "      <td>234.666361</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>2521.432959</td>\n",
       "      <td>1.108279</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.449086</td>\n",
       "      <td>6.921208</td>\n",
       "      <td>0.170275</td>\n",
       "      <td>2.005254</td>\n",
       "      <td>0.465842</td>\n",
       "      <td>0.624470</td>\n",
       "      <td>0.186752</td>\n",
       "      <td>0.166587</td>\n",
       "      <td>0.188184</td>\n",
       "      <td>0.121490</td>\n",
       "      <td>56.970413</td>\n",
       "      <td>175.481637</td>\n",
       "      <td>208.910941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>8646.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>0.015200</td>\n",
       "      <td>0.160000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>10829.250000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.340000</td>\n",
       "      <td>0.333300</td>\n",
       "      <td>0.460000</td>\n",
       "      <td>0.104500</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>46.000000</td>\n",
       "      <td>53.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>13012.500000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.520000</td>\n",
       "      <td>0.484800</td>\n",
       "      <td>0.610000</td>\n",
       "      <td>0.164200</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>156.000000</td>\n",
       "      <td>191.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>15195.750000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.660000</td>\n",
       "      <td>0.621200</td>\n",
       "      <td>0.770000</td>\n",
       "      <td>0.253700</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>275.000000</td>\n",
       "      <td>347.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>17379.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.924200</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.806000</td>\n",
       "      <td>367.000000</td>\n",
       "      <td>886.000000</td>\n",
       "      <td>977.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            instant       season      yr         mnth           hr  \\\n",
       "count   8734.000000  8734.000000  8734.0  8734.000000  8734.000000   \n",
       "mean   13012.500000     2.489810     1.0     6.501946    11.520151   \n",
       "std     2521.432959     1.108279     0.0     3.449086     6.921208   \n",
       "min     8646.000000     1.000000     1.0     1.000000     0.000000   \n",
       "25%    10829.250000     2.000000     1.0     4.000000     6.000000   \n",
       "50%    13012.500000     2.000000     1.0     7.000000    12.000000   \n",
       "75%    15195.750000     3.000000     1.0     9.000000    18.000000   \n",
       "max    17379.000000     4.000000     1.0    12.000000    23.000000   \n",
       "\n",
       "           holiday      weekday   workingday   weathersit         temp  \\\n",
       "count  8734.000000  8734.000000  8734.000000  8734.000000  8734.000000   \n",
       "mean      0.029883     2.994733     0.681704     1.413098     0.504825   \n",
       "std       0.170275     2.005254     0.465842     0.624470     0.186752   \n",
       "min       0.000000     0.000000     0.000000     1.000000     0.020000   \n",
       "25%       0.000000     1.000000     0.000000     1.000000     0.340000   \n",
       "50%       0.000000     3.000000     1.000000     1.000000     0.520000   \n",
       "75%       0.000000     5.000000     1.000000     2.000000     0.660000   \n",
       "max       1.000000     6.000000     1.000000     4.000000     1.000000   \n",
       "\n",
       "             atemp          hum    windspeed       casual   registered  \\\n",
       "count  8734.000000  8734.000000  8734.000000  8734.000000  8734.000000   \n",
       "mean      0.482481     0.611193     0.189034    42.679757   191.986604   \n",
       "std       0.166587     0.188184     0.121490    56.970413   175.481637   \n",
       "min       0.015200     0.160000     0.000000     0.000000     0.000000   \n",
       "25%       0.333300     0.460000     0.104500     5.000000    46.000000   \n",
       "50%       0.484800     0.610000     0.164200    20.000000   156.000000   \n",
       "75%       0.621200     0.770000     0.253700    60.000000   275.000000   \n",
       "max       0.924200     1.000000     0.806000   367.000000   886.000000   \n",
       "\n",
       "               cnt  \n",
       "count  8734.000000  \n",
       "mean    234.666361  \n",
       "std     208.910941  \n",
       "min       1.000000  \n",
       "25%      53.000000  \n",
       "50%     191.000000  \n",
       "75%     347.000000  \n",
       "max     977.000000  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn import neighbors\n",
    "df_2012.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(8734, 17)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2012.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def find_outliers(x):\n",
    "    Q1=np.percentile(x,25)\n",
    "    Q3=np.percentile(x,75)\n",
    "    IQR=Q3-Q1\n",
    "    lower=Q1-1.5*IQR\n",
    "    upper=Q3+1.5*IQR\n",
    "    outlier_ind=list(x.index[(x<lower)|(x>upper)])\n",
    "    outlier_value=list(x[outlier_ind])\n",
    "    return outlier_ind,outlier_value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "find_outliers(df_2012['temp'])[0]\n",
    "df_2012=df_2012.drop(find_outliers(df_2012['temp'])[0],axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "find_outliers(df_2012['atemp'])[0]\n",
    "df_2012=df_2012.drop(find_outliers(df_2012['temp'])[0],axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "find_outliers(df_2012['hum'])[0]\n",
    "df_2012=df_2012.drop(find_outliers(df_2012['temp'])[0],axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "find_outliers(df_2012['windspeed'])[0]\n",
    "df_2012=df_2012.drop(find_outliers(df_2012['temp'])[0],axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "find_outliers(df_2012['casual'])[0]\n",
    "df_2012=df_2012.drop(find_outliers(df_2012['temp'])[0],axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "find_outliers(df_2012['registered'])[0]\n",
    "df_2012=df_2012.drop(find_outliers(df_2012['temp'])[0],axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>instant</th>\n",
       "      <th>dteday</th>\n",
       "      <th>season</th>\n",
       "      <th>yr</th>\n",
       "      <th>mnth</th>\n",
       "      <th>hr</th>\n",
       "      <th>holiday</th>\n",
       "      <th>weekday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>weathersit</th>\n",
       "      <th>temp</th>\n",
       "      <th>atemp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>casual</th>\n",
       "      <th>registered</th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8645</th>\n",
       "      <td>8646</td>\n",
       "      <td>2012-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.3788</td>\n",
       "      <td>0.66</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>5</td>\n",
       "      <td>43</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8646</th>\n",
       "      <td>8647</td>\n",
       "      <td>2012-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.3485</td>\n",
       "      <td>0.66</td>\n",
       "      <td>0.1343</td>\n",
       "      <td>15</td>\n",
       "      <td>78</td>\n",
       "      <td>93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8647</th>\n",
       "      <td>8648</td>\n",
       "      <td>2012-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.32</td>\n",
       "      <td>0.3485</td>\n",
       "      <td>0.76</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>16</td>\n",
       "      <td>59</td>\n",
       "      <td>75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8648</th>\n",
       "      <td>8649</td>\n",
       "      <td>2012-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.3333</td>\n",
       "      <td>0.81</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>11</td>\n",
       "      <td>41</td>\n",
       "      <td>52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8649</th>\n",
       "      <td>8650</td>\n",
       "      <td>2012-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.28</td>\n",
       "      <td>0.3030</td>\n",
       "      <td>0.81</td>\n",
       "      <td>0.0896</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17374</th>\n",
       "      <td>17375</td>\n",
       "      <td>2012-12-31</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.2576</td>\n",
       "      <td>0.60</td>\n",
       "      <td>0.1642</td>\n",
       "      <td>11</td>\n",
       "      <td>108</td>\n",
       "      <td>119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17375</th>\n",
       "      <td>17376</td>\n",
       "      <td>2012-12-31</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.2576</td>\n",
       "      <td>0.60</td>\n",
       "      <td>0.1642</td>\n",
       "      <td>8</td>\n",
       "      <td>81</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17376</th>\n",
       "      <td>17377</td>\n",
       "      <td>2012-12-31</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.2576</td>\n",
       "      <td>0.60</td>\n",
       "      <td>0.1642</td>\n",
       "      <td>7</td>\n",
       "      <td>83</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17377</th>\n",
       "      <td>17378</td>\n",
       "      <td>2012-12-31</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>22</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.2727</td>\n",
       "      <td>0.56</td>\n",
       "      <td>0.1343</td>\n",
       "      <td>13</td>\n",
       "      <td>48</td>\n",
       "      <td>61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17378</th>\n",
       "      <td>17379</td>\n",
       "      <td>2012-12-31</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.2727</td>\n",
       "      <td>0.65</td>\n",
       "      <td>0.1343</td>\n",
       "      <td>12</td>\n",
       "      <td>37</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8734 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       instant      dteday  season  yr  mnth  hr  holiday  weekday  \\\n",
       "8645      8646  2012-01-01       1   1     1   0        0        0   \n",
       "8646      8647  2012-01-01       1   1     1   1        0        0   \n",
       "8647      8648  2012-01-01       1   1     1   2        0        0   \n",
       "8648      8649  2012-01-01       1   1     1   3        0        0   \n",
       "8649      8650  2012-01-01       1   1     1   4        0        0   \n",
       "...        ...         ...     ...  ..   ...  ..      ...      ...   \n",
       "17374    17375  2012-12-31       1   1    12  19        0        1   \n",
       "17375    17376  2012-12-31       1   1    12  20        0        1   \n",
       "17376    17377  2012-12-31       1   1    12  21        0        1   \n",
       "17377    17378  2012-12-31       1   1    12  22        0        1   \n",
       "17378    17379  2012-12-31       1   1    12  23        0        1   \n",
       "\n",
       "       workingday  weathersit  temp   atemp   hum  windspeed  casual  \\\n",
       "8645            0           1  0.36  0.3788  0.66     0.0000       5   \n",
       "8646            0           1  0.36  0.3485  0.66     0.1343      15   \n",
       "8647            0           1  0.32  0.3485  0.76     0.0000      16   \n",
       "8648            0           1  0.30  0.3333  0.81     0.0000      11   \n",
       "8649            0           1  0.28  0.3030  0.81     0.0896       0   \n",
       "...           ...         ...   ...     ...   ...        ...     ...   \n",
       "17374           1           2  0.26  0.2576  0.60     0.1642      11   \n",
       "17375           1           2  0.26  0.2576  0.60     0.1642       8   \n",
       "17376           1           1  0.26  0.2576  0.60     0.1642       7   \n",
       "17377           1           1  0.26  0.2727  0.56     0.1343      13   \n",
       "17378           1           1  0.26  0.2727  0.65     0.1343      12   \n",
       "\n",
       "       registered  cnt  \n",
       "8645           43   48  \n",
       "8646           78   93  \n",
       "8647           59   75  \n",
       "8648           41   52  \n",
       "8649            8    8  \n",
       "...           ...  ...  \n",
       "17374         108  119  \n",
       "17375          81   89  \n",
       "17376          83   90  \n",
       "17377          48   61  \n",
       "17378          37   49  \n",
       "\n",
       "[8734 rows x 17 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2012"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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LhmEw6JZhzJ/xo4Nr7zgBveMoSc+mrMCyn0rLKNx3hIB4+/iylm62/r80J5/SnAKKLH07PeFPgi/tQeiIXrgF+OIe7M+R/y2usxjORqOTxN+oBvG7+nvjERViXV90IBXfdk5/HgaAJr3aU5CRwzHL59QsLSNrfypNerWvsvzJPu+cbPk5oFvvrhzed9j6fH/iAeK6d6j0d9CWWcVJhsFjBnHVxCv5bv3/uGrilbVSV0eK6dWewir2fUwD2feR8e0pTM+h1Cb+3H2pRMRXHT9llePMq/D3vVHLSLJ2HqqV+jpSQ45dBGo+x8VvgCewHrC9oL9yqk/qxJHMXAJ97Yd7+3p5kJqZa7esZVQIz906nKkfzaF7qxheum0UXjYJi8zcAr5bvpkvF60j1uaLXH0KiAwmd9GJH8uFeQW4e7rjF+RPdmqmXbmCnHxrMqG8bCEBEUFnvK6i5l1bs/i/9nM7xHRoxvD/uwZPXy+8/H1Oeua2NgRFBrPFrm0KrW2TZdM2gdYYj9mULSAgIrhG79ft0ov4+a1vz77iNRQQGUxeRo7dsqIq6l9e7kSfL8wrJCA86LTrUhIPMvPeN7jp9XtIXPUXH9zxCiVFlYcIt+rZgcRVfzksrjMVEBlEfoX2KN+fQZXK2bZbUV6BNeZTCWkagU+gL3vX7yKiVWPHVNrBAiODyTtJ3892UN+/ZMJQFs2aT9kx573VmUdUMMcy7I/zpbkFeJwiPu+WUWQt20LJkfJ2Kth5kG1TXqPd2/eRteIv/pr4ImVOmrCqyPMM4veqEH/m7xuImnAZqV//QVlRMX6dW8I5coLDPzKYwgrxF+cW4hsRWE81qnuhkaFk/37iTHF+bj4enh4EBAeQfiT9FK+09+QdT+Pt48WwcUO5/dHJFBcV88Osn2qjyg7hFxlMQQPe9z6RwRRViL8krxCfM4w/olc7UlZsc0TVal1Djl0Ean6pSBjQ1TTNG03TvOX4A7j+VC8yDOM2wzDWGIax5v1PPj/jykplBuDpYZ9/Kj5Wiptr5V17rLSMV28fzb7UTB5+/ydKSk98Kff18qBH6ybENYvkbzN+IDm97n6En5RpUlJ04ku0uyXRUlrxx4RpWs9AnyjrVp6QONN1Nrwb+RAUGcymCvM7ZBxKY9V3fxDaNIKbXrrzjEI8U6ZpUmzTNm6WPlCxbUyTSjG6ebhXivFUXFxdCGsaQUpSPWTkK/QBOF7/ChOhmtiVc/NwO9EWp1oHuLq58v5tLxHaLJJbpv9fpTP3AJ0u7WG9pKg+mSYUV0isVLk/TewSMG4e7pU/NxUYhkHfmy7l9w9+dlh9a0N1+z5V9H33avT9xu2aUlJU7LSXiFiZWM+6Hefi4Y55iv0cdcvl7H7qE/vXuLuydcILeDePpN27f8M4xdlqZ2KaVEqyVCf+PTbxJz40g5x1u2j/8UPE3DMGv26tKagwWtFZmaZpPeN+nKuHO2U1OLaf80yTIps2cPe0fEeo+PehGgryC/n6g295/YnpXDV5rMOqWCsa+r43zUrHvrOJv+llPdg3b40jalb7GnLszqis7Px8OLGaJi4eAvpXsdz/VC8yTXOGaZo9TNPsMemmcTV8SzmV8EA/si1zQByXV1hMWKCf3bI1O/azZW8y8e2b88H917L9wBFm2fwQd3dzpWPzSP49cQQRgX5s3HOYunbRmL68vn2W9ZGbno1PoxNxePp6U1xYTH6WfbY5MyUd70a+dss8fb3JSsk443W2Bk0ayf+ernw1VF5mLut+XsF///6W9br52tJrTD/e2v6p9ZGTno2vTd29LG2TZ3N5C1TdNl6+3mSlVP9sVJuLOtjdbaQuZaak41NpH3lV2keZyfblbGM81bpWPdvTtEss25ds4o1r/0XjDs0YOGl4pXo07RTLvg2JDovrTGVV0R5evl5kn6Y9qmqzilr0aEvvcYN4evU7PLN2BmOfnEDL7m14Zu0MxwVwBnqO6cf07Z9aH7kn6fv51ej7ntXo+wNvGc4Vfx/Py2s/4OW1H9Cqe1uue/JWrnuy6gnQ6kvx4TTcAuzjc/Xzpji56vgC+3Yia9kWCveduMwmIL4Dfl1bkbl4IxvH/AO/uOY0vmNkrdbbUWoaf4Al/iKb+I9l5pL44DtsueYpUj5diHfrxqR+fW5cKpObnIFnhfg9/LzIPc3n/Fw2ZOxg5u/62frITM/CP+DEdwQfXx+KCovIqfAdoSZ+/nwuAUGNHFHdWpObnIFXA9v3tvKTM/AItI/f3c+L/DOMP6RLC46uT3JE1WpdQ45dBGp+qcgNQHvDMPbZLDOA9kCkw2ol1XZhm6Y89VkChcUleHm4U1JaSnJGDt1bx9iVS1i3g9bR5Vf0hAf6cdeoi0lYu4NbLrXfnquLC+2ahBMeYJ/4qAsbF6xh77ATPw47DepOdNsT1xuHt4xi16qtmBWu2du3KYmi/EJCYsKs17OHt4jip1e/PON1x/UZN4g13y8hL/PkX4T2bUwk8yRflh1lw4I1PDVsl/V550E9aNz2xOz3ES2j2Llqa6Xrd/daYgyNCeeoZS6PiBZRfG8T4+l0u+wiltbTrSB3Lt9CwHO34+7pTklRCS5urgRHh7KrQiJl+5KNhMdGW5+HtYxi54qtp13XdVgvDm3fD0D2kQzmvPwlXYf1gnd+sJZv0rEF+zc7x2RtO5dv4brnbrNrj6Aq22MT4bFR1ufhLaPYuWLLKbe9d8Munhn0N+vzbsN70XV4Lz668zXHBlFDGxasYY9N3+8yqAfRNej7ITHh1nlsIlpE8eNp+v7Xz3xiV+b2tx5gzZxlLP/qdwdE4ziZS7fQ+uUgXLw8KCssxnBzxbNxKFnLKycZvVs3xqtZBMmz7CdcDR0ZT95f5X/Oi1My2PPvzwkd2Rumf1cnMZyNrKVb8Kgi/uxTxJ8y6+QTzjb521Vk/bGJjIXrarPaDrNv+VYujZiIm6c7xyzHAv/oEA6cx8O+l81fzqT1J+4cEz8knhZtm1ufx7SMYcOKTWc9Wfb2jTtPX6ge7V++lcERE3H1dKe0gex7W8nLtuITMRFXL3dKC0sw3FzxjQ45o0seQjo1J33THsdXspY05NhFoOYjLrYD04FPKJ+Qc6bl/0sdXK9acXyCopNOVHQOCg3wpV/HlqzaXv7lc+W2fQzq2pqIQH9mJqxmj+XsYtuYMLbZTGjnahh0bF6ea9p16CjZllm5s/MLKS0z6dIymrpWmFNASuIh62PF14to3rWVdeh+XP+uLHyv/LrTRmGBDL//agBKS0pZ+sVCOg68AIDIVo3JTE5j99qdZ7wOoPc1l1CUV0hxUTEhMWF0HtKD2B5tcXF1oVmXWGu9Ow68gN8+rN3h9QU5+SQnHrI+ln/9Oy26trZOQtaxfzfmv1c+kWBAWCCj7r/G0jbH+OOLhXSyxBjVKoaM5DSS1u6w276BUeUt4gCadGjOvs31k5HPSc1i869radOnEwBtL+7E+nkryUrJYODkEYS3LP9xvvTTBXa3ym0TH8eij+aedt3BrXuJiWtuXVdWWlZpZEWnSy9koxNcJgLl7bGlQntsmLeKrJQMLrFpj2WfJtDOJubW8R1Z/NE8u20ZBna3AS0tPkZWcrr1kZ+VxzHLsvpUmJNvd1w43vdPHBe6kWDp+43CAhlp0/eXVLPv2zZEfnYemcnp1kdJcQn5WXnkZ9uP6KhvJamZpCesJbBveV8I7NeZo3NWUJycTuMpo/C2JOu8moYTdcMQMhZtwLNJGL4dmhF1c3nGOnfzHvw6nrjdq1laRu465/7Rdtzx+AMs8Qf060yaJf5om/g9m4YTecMQMi3x+3RoRuTN9hn7kBG98Ovckh33/KfO4zhT+alZJC1cR9OLy+921eziOHbOXU1uSgY9bhtGUMso+xcYnPQYD6de5yzycvLYl7jf+vjlq/l06NbO+nfwogEXMnvGVwAEhwcz4YGbKm/EMOxv/e3nw9BrL8fNvfw83tWTx/LRyx/XdihnJT81i902+77pxXHsmruavJQMulex743T7PuT3g/aSRWkZnFgwTqiLPFH941j78+ryU/OIO72YTSKrdz3TxZj08t7sHfuuXNHjYYcuwjUfMTFS8ARs8ItCAzDcN5ZjCzy8vL5cf6vAHz3cwLjx44kOOj8mMjosXGDefXbxWw/kEpadh7/GD8EgHlrthEdEkDziGCuiO9EcnoOH/6ykkA/b5Izcph0WU8APvhlJSv+2suALq0I8ffhifFDnOJLTG5aNrP/+SFX/2MCBTn5bFu6ib/+2AhASJMwel7Zn/lvfUdJUQlzXvuKK6fewOV3X0lgZDDvTXnFup0zWdfzyn6Mf/52uzvR5Gfn8XD3SQREBHHb2w+Qm5HD9qWbObLnMItn2U/cWdty0rL5/J8fcq2lbf5auomt1rYJJ/7K/sx96ztKior54bXZXD31RobffSWBkSG8M+Vl63ZcXF3oMTyeRmGB9Bjem9R9KaQfPGpd36xTS/bWU9LiuNmPvc/oqdfTuH0z/MMC+WJq+aUL3Uf1If1AKkeSDnN4x34Wz5zHmMdvBODX934i2XKt+qnWrZj9G0HRIQyeMpq89BwCo0NIeNN+EtLYi9ox97Wv6irc05r92AeMmjqe6PZNaWTXHr1t2uMAf8z8hSusMf9ojRmgSaeWtOoVh19II2J7tidxZf1PPFpdOWnZfGHT922PC6FNwul1ZX/mWfr+j6/N5qqpNzLM0vffrdD3u9v0/aMV+v65YNfDM2j+xI34dmiGR3ggOx98F4CwK/pQtP8Ix3Ly6fTNv/CKCaPx7Sduh/vX7eXHuZTPf8UrJpSYu6+gJD0Hz8Yh7H/9m3qJ5Uwk2sTvHh7IrpPE7xkTRrRN/Nst8Qf06Yhfl5YYHu5sHvvkOTMx6XEJj31E/0fHEda+Kb5hgcx/5AMA2o2OJ/tAKhlJ5Zd8RnRuQZP4DvgE+xPTsx0HVpafnXX39aLDmD4AxF3dl3UfJ1CQnlP1mzmhzLRMXn9iOnc/eSd5OXmsXbqONYvLL4GNjIngsrFD+OzNLyguLMbV1YX+I/oTHBbEJSMGcHjvYVIOHsHTy4Pr7riaG+4Zz/oVG5jz2c/8tc75Ry4sfOwj+lr2vU9YIAss+75tFfs+Jr4D3sH+NO7ZjoM2+769zb5ff47t++VTP6LHY+MI7tAU77BAlj1UHn+LK+LJPZBKdmJ5/CGdWxDZuwNeIf5VTkQZcVFb1r/8dZ3X/2w05NhFjJqMPjDKf80+BNwGNAZ2AG+bpvl2dbdRcjTp/BnuUEPHNpx8mGpD8MDEhh1/CQ226wPgXeMBXucXg/pPBtaXQhrIpHEncUNhw/7sN+xPPiz38Dp9ofPUT2XJ9V2FejXapWFfRR3UsA/9Dd6Eg7PO6y8+RYkrzss/7p6xvZx2v53JiItBwBtAIuWDkHoahjHVNM3nHF05EREREREREWnYapq4aAp0M+2HafxoGMa/HFgnERERERERERGg5iM4t1ZIWmAYhivQ3XFVEhEREREREREpV9MRF3mGYUwDlgHuQAfgJmCOoysmIiIiIiIi4nTO8tbLUnM1SlyYpvmCYRi3A88DrYF9wDvAa7VQNxERERERERFp4Go64gLTNN8F3q2FuoiIiIiIiIiI2KnRHBeGYTxrGMZDhmGEGobR2zCMPYZh7DUMY1BtVVBEREREREREGq6ajrjoB1wGlACfAb8C9wIPAwsdWzURERERERERJ2Nqjou6VtO7inxtmmYeMAXwBO41TTOXM7jkRERERERERETkdGqauDAMw3gTmAbcBeQbhjEWuNPhNRMRERERERGRBq+mdxV5xTCMDsCLpmnuMQwjGjgKjKqV2omIiIiIiIhIg3YmdxXZavP/Q4ZheACXAoscWTERERERERERp1NWWt81aHBqlLgwDOM6YCrgBxiWxd6W/89wbNVEREREREREpKGr6YiLicDTwAXAUiAXGAAsd2y1RERERERERERqPjnnfNM0/we8AESbprkIeIbyURgiIiIiIiIiIg5V08RFW8Mw3gfCgCDDMP4JvAZ0cnjNRERERERERKTBq2ni4j5gHZADvGx5fVPgJgfXS0RERERERMT5mGXn58OJ1ShxYZpmHvAFEGaaZikwCxhrmmlYKWcAACAASURBVObPtVE5EREREREREWnYapS4MAzjSmAv8G/LoiPAfwzD6OLoiomIiIiIiIiI1PRSkUeAMcAiANM0sygfgfGxY6slIiIiIiIiIlLz26HOM00zwTCMDjbLulA+z4WIiIiIiIjI+a3MueeDOB/VNHGRbRhGb8DFMIxI4GrgWWCmw2smIiIiIiIiIg1eTS8VeQ3oB9wOJFJ+l5FXgP9zcL1ERERERERERGqcuHgKKAP6ApcC7pTfCrWvg+slIiIiIiIiIlLjS0X6AZcBJZTfCnUhcC/wsOX/IiIiIiIiIucvU3Nc1LWajrj42jTNPGAK4AXca5pmLjVPgIiIiIiIiIiInFZNExeGYRhvAtOAu4B8wzDGAnc6vGYiIiIiIiIi0uDVaKSEaZqvWG6F+qJpmnsMw4gGjgKjaqV2IiIiIiIiItKg1fgSD9M0t9r8/xBwyKE1EhEREREREXFWZZrjoq7V9FIREREREREREZE6o8SFiIiIiIiIiDgtJS5ERERERERExGkpcSEiIiIiIiIiTqvGk3OerWMbFtT1WzoNty6D67sK9azh7nsAb+UJG7RCSuu7CvXGv+7/1DiVLe6u9V0FqUc+Zn3XoP54G+71XYV6lebSsCfvKzH0vUfOX6bZcL/X1RcdUURERERERETEaSlxISIiIiIiIiJOS4kLEREREREREXFaDfvCYxEREREREZGaMBv2HDb1QSMuRERERERERMRpKXEhIiIiIiIiIk5LiQsRERERERERcVqa40JERERERESkuso0x0Vd04gLEREREREREXFaSlyIiIiIiIiIiNNS4kJEREREREREnJbmuBARERERERGpLlNzXNQ1jbgQEREREREREaelxIWIiIiIiIiIOC0lLkRERERERETEaSlxISIiIiIiIiJOS5NzioiIiIiIiFRXWWl916DB0YgLEREREREREXFaSlyIiIiIiIiIiNNS4kJEREREREREnJbmuBARERERERGpLrOsvmvQ4GjEhYiIiIiIiIg4LSUuRERERERERMRpKXEhIiIiIiIiIk5Lc1yIiIiIiIiIVFeZ5rioaxpxISIiIiIiIiJOS4kLEREREREREXFaSlyIiIiIiIiIiNPSHBciIiIiIiIi1WVqjou6phEXIiIiIiIiIuK0lLgQEREREREREaelxIWIiIiIiIiIOK3zYo6LwuISXvt2MT5eHuTkF3HfFX3x8/asVO79eSsxTRPDMCgsLuGukX0wDINjpWVM+yyBhHU7iA5uxNM3X067JhH1EEntWrZqLf957xNeemoqjaPO7fgiYxvT/+bLSd2bTHjzSJZ8voADW/fWaBu+Qf6M+vt1FGTn4+rmyrfPf0rZsVLr+gmv3sNFY/oCsCFhNe9OftGhMdSEu6c7o6beQFFeAT4Bvvzw/GcU5hZUKtd+QFfiLumG4eLCzmWbWT935WnXtR/QlSkfT7Xbzt71u3j5iscAGHLnFRguLphlZXh4ezLn5S9rMdLKajN2OHl8p2sXZ9KscywXXzeI4oIiUvem8Psn86osZxgGo/8+DgD/kAB+fOVLMlPS7bYz+sHrmPvmt+xcubVO6l4Tbp7ujJh6PUV5BXgH+DLn+c8pqqIvtBvQhfaW/b1r2WY2zl0FgIurC2OfnUSXYT1JP3CULx58m0Nb9gDg5e/N1c/fRtt+nUnbd4SvH/+Afet21WV4Nebq5U6vR8dRkleIZ4APK579kpIq2sMz0Jcutw/Hw9+bJY/PrHJbsSN7EnfjYH645pnarrbDNOT4Xb3cibeJffkpYu92+3Dc/b354ySxt7LE/v05ErutNl3acNl1l1FUWMThPYf5ceaPpyx7099v4svpX7JpxSbr8riL4rjn2XsIjQplRcIK3nzsTQryKrdlfXLzdOeyqeMpzivEK8CX+Sc59rUe0IW2l3TDcDFIWraFLZZjH4BXIx8eXPoGXv4+AHx6+yv89csaAPrfORrDxcAsM3H39mDBy1/VTWAO4ObpTv9Hx1GcW4hXgA+Lnv+S4iraxivAl4ssx4EFT1T9WXBW1Y2xxYDOxA7siuHiwt5lW9jx82oAXNxc6f/ItRwrKsEn2J/df2yq1joRZ3NejLh49ouFdIttzL2j+zKgcyzTPk+oVGbxpkQOpmUxeWgvJl3ek9SsXOb/uR2AOau2MrZvZ37810Qigvx5fvavdR1CrTuankF+QQGbtm6v76o4xM2v3s28N7/h1w/m8Mvb33HrG/fVeBuT37qf5bN/47vnP+XI7sOM/Ns11nVB0SHkpGXx+vVP8/r1TzP7Hx86svo1dvW0SSSt2cZPL37BpoQ1XPvs5EplwlpEMeLB6/j6yY/56okP6DdhKFFtmpx2Xaue7fngjpd5ZczjvDLmcX566Us2LfgTgLiBFxDSJJz5078h4a3vCIgIotuI+LoLnNqN/VTxnapdnIlPgB+3vnoP/5v2CV89PZNWF7ajQ78uVZYdfu9YCrLz+O6Fz0iY8QOT37zfus7T1wtvfx9aX9QBw6ir2tfM2Gm3snvNNua++CVbEv7kqmcnVSoT2iKSyx+8lu+enMk3T3zIxRMuJ7JNDAAXjLmYFZ8t5Ln+/0fW4TTGPHmz9XWX3DGKTb+s5u1x08hOyeCWGQ/iUUUC3Jn0feYWkldvZ9W/Z7Nn/lr6PX9rleUaNYsguG0M7j5Vx+MTEcgF94yuzarWioYcfz9L7Cv/PZvd89cy4CSxBzSLIOg0sXc/x2I/zi/Qjwdfe5D3nn6PGf+aQdxFcVzQ/4Iqy3r7euPj70PHnh3tlnt6ezJqwihee+g1Xrr/Jbr3786ERybUQe1rZtS0W9m7ZjsJL37JtoQ1jH52YqUyIS0iGfLgNcx5ciY/PvER8RMuI9xy7APocd1Avn7wHT66/lk+uv5ZtiWU/z1rO7AbQU3C+H36dyx663v8I4LoOKJXncV2toZMu4WDq7fzx4uz2ZWwlsuerfqzENgsgtA2Mbg7+XG9KtWJMahFJP3+fg0L/vlfEh7/mO4TLiPUsv/j7xlNfnoOf7z4FfMf/5je91xRrXVyGmVl5+fDiZ114sIwjB6OqMiZOpKZy9w12+jXORaAnu2a8fvG8iSFraTkdPILi63PPd3dyLE8v7R7Wzo1jyLY34er+3bB1Tgv8jl2QoODGNi3bn9w1qbIVo3x8vMGoKSw2HoGobqad2tNeMto9qwvP6O6ccEa+t881PpDZeDEEST9uZ2dK7awfekmMg6nOTaAGmgUHkSPUX3YbPnRvH3JJjoO7k5wTJhduUsmDeevResxTROAbYs3cMnkEaddt+S/89kwbxV71u1kz7qdhDaLYOO88hEJEa0a42lpZyhva+8atvXZqO3YTxXfqdrFmfQdP5h9m3dTlF8IlPfly6dcUamcq7sbgyeNZN0v5WfgkhMP4h8SQOueHQAoyitk29JN5KZl113la6BReBDdRvVh64K1AOxcsom4wRcQFBNqV67/pOFsX7TBur+3L95I/8nDAdjw0wr2b0gkLz2H5Z8uoKzMtL5u55LNrP9hGQc37+bT+/6DT6AvEa0b11F0NecTEUjr0fHsTVgHwIE/NtN8SDf8K7QHQOqGJI5uOfmItG5TRrJ11rmVsG/I8ftEBNJmdDx7qhH7kdPEfsGUkWw+h2K3NXT8UHZt3kWh5di3MmEl19x5TZVlC/IKWL9kPVkVvhs2btGY/zz6H7at3caK+SuY9eosusRXnfitL/7hgXQe1ZvtlmNf4pLNtBt8AYEV9nefScPYuWij9di3c/FGLrYc+1w93GjVtxNHth8gcelmEpduxrQc/8JaNcajwt/Bmn6nqi9+4YG0Hx3PrgXln4U9SzYTO6Qbjar4LCRvTOJIDUfmOoPqxnjhpKEk/b4RLPt/9+KNXDh5GACdrulP6rb9AJilZST9vpELbzv9OhFnU+1f6IZhXGAYxseGYfxiGMZCwzB+NQzjN2BOLdbvtNbs3E+grzfeHu4AuLm60DgkgD93HrAr169jSxZtTCRh7Q6y8wvJzC1gxEXtAayvBdidks7doy+uuwDqkIvL+ZOQWTd3Jdc/fweevl5cNKYfs//5EQBNO7Vk+P9dzcTp/8dt7zyAl793la9vG9+RtP1HrM+zUjIAaNa5Je5eHnQa1J2Jb97PtGVv0bZ3xyq3UVda9+pAbkYOJZZEW1lpGWn7U2nVs71duTbxcXYxHUk6ROteHU67LuPQiaSM4WIQ3iKK5F0HAdiycC2dBnen69CeeDfyxTfYn9XfLK6dQKtQ27GfKr5TtYszaRffkaM28aUkHaLlBW1xcXO1K9esU0u8/X1IO5BqV7atpS2OK3PS23vF9mpPXoW+kL4/ldie9vVvFR9H+v4TMaYmHSLWEmOJTfI6PDaauS98YX2+a/kW6/8LcwoozC0g8/CJy2icTXR8ewozcjhmicksLSNnfypRvdpX/QKbJI2tdtf2Z+d3yzhWUFRbVa0VDTn+xvHtKagQe/b+VKJrGHv7a/uz4xyL3VbXPl1J2Z9ifX4g6QAdunfAtcKxz5ZZoS2StiaRm5lrfZ6WnMaRQ0cqvqxetejVgfwKx76M/am0qPB3sGV8HBk2fwuOJh2mhaVPtB3YjZiusdz/+yvc+OHf8Qnyt5bbvnAt7QZfQNzQi/Cy/B1c/80fdRDZ2WtSxWcha38qTXpW/VmouP/PBdWNsWnvDmTZ7P/0pMM0iW8HgKefN/6RwdZ12QePEtauyWnXiTibmvyS/REoBGYDnwAzgY+BhY6vVvUdycwl0NfLbpmvlwepNn+IAFpGhfDcrcN54pO5TP1wDv+66XK8bBIWmbkFfJywmi8XrSP3HP0j3pB88fj7HCsq5uEfnqMor5D181bi5efN4NtGMue1r/jg7tfwDw1g6N1jq3x9YGQweRn2faQor4CAiGBKCot5csC9PNrzDjb/uo67Pn6U6Lb1dxAPiAwmLyPHbtnxulYudyKmwrxCAsKDTrvOVqueHUhc9Zf1eUriQWbe+wbXv3wnN79xD58++DYlRSUOias6ajv26sZXsV2cSWCFNirMK8Td0x0/my+mx8sV5ORTWnLMpmzltnRWFfcjlNe/UURQhXJBldqjkU1f9wn0Y8BtI+hz06UnPasY2iKSxBVbyUnNdGAEjuUbEUxhhfYozi3ENyKw2tto1Cwcz0A/jqxPdHT1al1Djt83IpiiCrGXNJDYbYVEhJCdcWKEWH5uPu6e7jQKbnTG22zbrS1zPqnX83GVNIoMJr/S95VC/Csc+xpFBtmVK8orxN9y7Ns6bzXTOk3i/WueIjAmjBvefwDDck1gauIhZt87nbEv38E1b9zFNw++y7E6/Dt/NvwjgymoeBzIK8SvBp8FZ1fdGP0igyiw+e1TnFuIn2X/7168iW43DsLdxxPD1YXITi0wXIzTrhNxNjVJXBw2TfMO0zQ/ME1z5vEH8EhtVa46DMDTw36O0eJjpbi5Vg7tWGkZr94+mn2pmTz8/k+UlJ6YiNHXy4MerZsQ1yySv834geR05xwuLeXcvTxY88NSVn+/hKv+cTNt+3Si48AL8A3055Jbh3HJrcNOeXbcNE1Kiortlrl5uNv9qMtOzeSzqe+y9ufl9L/58lqL5bSqUdfyctiVc/Nwo/T4ZKOnWmej06U92PDLKrtlrm6uvH/bS4Q2i+SW6f9X6Ux+raqD2KsTX1Xt4ixM06S4QnxA5f1r2o84AHD3cKe0pHI/cEamaXKsGn3BNLEr5+bhbtcWRXkFJK7Yyv6NSUx4928ERFVO3PS56VJ+evYzB0fgaKb1DNxxrh7udhMMn5JhEHfzEDa+P7cW6lYXGnL8Zx97x5uHsOGcjP0EE5Nim3Zwt5yMOtNjmm8jX0IjQ1m5wLkuCaz6+4pbpTjNavyd37NqGx+On0ZobDQx3VpZl7u6ufLpba8Q3CySa6ffW7d/58+CaVb+LLjV5LNwDqh2jCZ25WzLzH/0Qw5vSGLMe/fT686RRHZpSdquQ6ddJ6dR33NRaI6LU7rVMIwrq1h+6eleaBjGbYZhrDEMY80HPzl2mHl4oB/Z+fYjJPIKiwkL9LNbtmbHfrbsTSa+fXM+uP9ath84wqyFJybac3dzpWPzSP49cQQRgX5s3HPYofUUx5rw2j2sm7eSuW98zfy3v+fWN+4jvEUUafuP8NuHP/Pbhz/z6SPv8u1zswhuHMrr22dZHxeN6UtWSjo+jXzttunh7Wm9ZMTW7x/PJTi68vWSdSWzirp6+npVqmtmsn05L19vsix3jDjVOltNO8Wyb8OJM3CteranaZdYti/ZxBvX/ovGHZoxcNJwh8RVHbUde3Xjq9gu9annmH5M3/6p9ZGbno1vhfiKC4vJz8qze11mSjreldqy6n7gjLJSMqqovxfZFfpCVrJ9nBXLlJaUsn9jEv+9+3Uyk9Np1q213etb9+lI4oqtpO93ruHiFeUlZ+AZUOEY5udFXhXHsKpEXtiGDuMv4aa1b3Lzhrfp89RNRPRozc0b3q6N6jpcQ44/t4rY3WsQe9SFbYgbfwkT1r7JLRvepu9TNxHZozW3OHnsA68cyPc7v7c+stKy8As48V3Px8+HosIicrNyT7GVk7vytiuZ8a8Zjqquw+RUcez28PUmp8L+zq507KtcBiDvaDabflpBQHQIAM17tqNxl5YkLtnMB9c+RVSHZvSZdG7McZCbnIFXxeOArxe51fwsnAuqG2PFch5+J8oUZuXxyyMfMPv659n4xe+EtIpm67dLT7tOxNmc9HaohmHsASqOjzcMw7C9QMwATOD9U72JaZozgBkABQtnOPQCswvbNOWpzxIoLC7By8OdktJSkjNy6N7afkbchHU7aG358Rke6Mddoy4mYe0ObqmQdnF1caFdk3DCA+wTH+I8fIP8iWnfjILsfADm/udrel3VH9M06TjwAtw93a3D/Zt3bcW+zbt5dthD1tdnHckgvHkUF48fYl0WEhNGackx9m6q/OPULDPZv3l3LUd1cjuXbyHgudutcbm4uRIcHcquCrer3L5kI+Gx0dbnYS2j2Lli62nXHdekY4tKcXYd1otD28snbco+ksGcl7+k67Be8M4PDo3xZGo79urEV1W71KcNC9awZ9iJ23R2GdTD7lKmiJZR7Fy1FbNC1nzvpiSK8gsJiQkn7UD5j/KIFlH8+Grd3t72TCUu30Kj5ybj5unOMUtfCIoOJXGl/SU8O5dsIqzC/t61YkvFzWGWmRzasoes5BOJm/DYaIKbhrPyc+efrPDgsq30//dEXL3cKS0sbw+/6BAOr9hWrdcfWZ/IFwNOHBdjR1xEyxE9SbjjP7VVZYdqyPEfXLYV3wqx+0eHcKiasaesT+SzCrG3GtGTX5w89hUJK9ixYYf1ec/BPWnetrn1eeOWjdm8cjNlZ3DGcOj4ofz+3e/kZOacvnAdS1q+ldHPBdkd+wKjQ9hd4diXuGQzobFR1uchLSPZvaLq21qbpWUkWyaq7DisFynb9wGQcySTBS/PJm5YT/545+S3lnUW+5Zv5bLnJ9q1jX90CPur+Vk4F1Q3xj1LNhHc8sT+D2oRyb7llS9xjb/3CvYu3ULSbxtqtE7EGZxqxMUzwDigFdDS8mhh8/+WQKylXL0JDfClX8eWrLIcdFdu28egrq2JCPRnZsJq9ljOJraNCWObzRk0V8OgY/NIAHYdOkq2ZVbq7PxCSstMurSM5nxzfKbp4/+eq/IzcykpKiHA5vrOvIxcVvzvdzx8PJny4SO079eFPtcNIiK2MWXHSklJPGR9FOYUsG9TEtmpGdbbYnYY0JXfZ86jtKSUiNhoOg3uDoCruys9x/Zn/rvf10usADmpWWz+dS1t+nQCoO3FnVg/byVZKRkMnDyCcMsfqqWfLqC9zW0w28THseijuaddd1ynSy9kY4XLIQ5u3UtMXHPr87LSsjodeVDbsVcnvqrapT4V5uTb9eflX/9Oi66trUN74/p3I+G98i+cjcICGXl/+Sz7pSXHWPLFQjoNLL9dYFSrGDKS00hau8Nu+wYGzng/1JzULLb+upbWfcony21zcUc2zltFdkoG/ScPJ8zSF5Z/uoC2/TpbX9cqPo4lH/0CQGSbGLwalc9r4dXIB8PVhb1rdwIQ3CScXuMHseOPjQTFhBLVvinxNwyuyxBrpCA1i70L19G4TxwAjS+OI2nuavKSM+hy+zACbL7AAuWnGTixX8uKj5GXnG59FGXlWZedCxpy/AWpWexZuI4YS+wxF8eRaIm96+3DCDyD2EvPgdjzc/I5kHjA+ljwvwW07dbWOhln9wHd+WbGNwAEhQdxw99uqLwRA+vcDsddeu2lFOQXUFRYRESTCHpd2ou4C+NqPZ7qyk3NYvuv64i1HPtiL+7IlnmryEnJoM/k4YRa9veqTxfQ2ubY1zI+juUfzQMgbuhFBDUJByA0NpqCzFyOJpWPLD68dQ9RFf4OHnSSEYank5eaReLCdTSzfBaaXRzHjnmryU3J4MLbhtn9kAeq3P/Orroxrp/1Ky1s9n/T3nH8afnbd1ybYRcS2bEFc+5/p9L7nGqdiLM46YgL4EPAxTTNEgDDMEaZpml3mtUwjLZAQi3Wr1oeGzeYV79dzPYDqaRl5/EPy5n0eWu2ER0SQPOIYK6I70Ryeg4f/rKSQD9vkjNymHRZTwA++GUlK/7ay4AurQjx9+GJ8UPOuQPb6eTl5fPj/PKziN/9nMD4sSMJDjo3Jy8yTZN3b3uRYfddxb5NSTQKDeTb5/5LxqE03p38Atc+NZGJ/7mPZbN/49tnZ510Ox/c/RrD7r2KtAOpePp68cOLnwMQGBHMDc/fwdEDR9izbie/vPkthTkFdRVelWY/9j6jp15P4/bN8A8L5Iup5cNZu4/qQ/qBVI4kHebwjv0snjmPMY/fCMCv7/1EsuXuOqdad1zsRe2Y+9pXdstWzP6NoOgQBk8ZTV56DoHRISS8+W1th2unNmOvTnxVtYszyUnL5ot/fsi1/5hAQU4+25Zu4q8/NgIQ2iScXlf2Z95b31FSVMyPr83mqqk3MuzuKwmMDOHdKS9bt+Pi6kL34fE0Cgukx/DeHN2XQvrBo/UVVpW+eexDhk8dT7SlL/xv6nsAdBvVm4wDqaQmHSZ5xwGWzpzPyMfLf7Qseu8nUiz7e+Cdo2lzcSc2J/xJ7tEs6+v9wwKZ8sUTBDUOpd/EE0Ok/3v363UcYc0sfvQj4h8dR2iHpniHBbLo4Q8AaDUqnpz9qWRZfpiEdW5BdO8OeAf7E9WrXbVHJTi7hhx/xdh/t4k9e38qmTaxN7bEHt2rXbVHZZwLstKyePsfb3P7k7eTl5PHhiUbWLu4/JahETERDBo7iNlvzaa4sBgXVxf6juhLcFgw/Ub2I3lfMkcOHmHQ2EHc98J9dnddy83KZVy3cfUVVpV+eOxDLp86jsj2TfELC+T7qeUDnTuP6k3mgVSOJh3myI4DrJg5n6GWY9+S9+ZwZGf5XF8tenXgin9PJmnZFnav+ItfX/vauu21sxcRGB1KvykjyUvPISA6hEVv1t/Jmpqa/9hHDHh0HGEdmuIbFsgvj5R/FtqPiifrQCrpls9CZKcWNI3vgE+IP016tmP/ynPns1CdGI/uOMDaTxK45InrAVg9Yw5plv3ftHcHIju1wNXDjS+ue8Zu8tVTrZNTM83zZy6Vc4VxurPvhmE0tfz3YeB5bNP2EAzMNk2zTXXf0NGXipxL3Lo479m7unBfj3qdx7XeuXF+JcOkZopw7gmPapP/KXPk579WpefGRHdSOxruJx9+JO30hc5j3V0r372rIWlk1mQqPTnfPLR31nn9xbdg8cfn5W9a734TnHa/VefbZGfgLSAGmFJhXTFw8lPaIiIiIiIiIiJn4bSJC9M0fzIMYz0wzjTNF+ugTiIiIiIiIiIiQPVGXGCa5gGgyqSFYRiXmqY536G1EhEREREREXFGZ3AHIzk71b7w2DCMYcBUIBI4fsGuCxABeDu+aiIiIiIiIiLS0NVkxrRZwAvAauCYZZkBjHZ0pUREREREREREoGaJi3XAq6ZpFtkuNAxjp2OrJCIiIiIiIiJSrib3KXoS+D/DMJoYhtHU8mgG3FI7VRMRERERERGRhq4mIy5mAG2B5yosN4FpDquRiIiIiIiIiLMyNTlnXavJiIsXgDDTNF2OPyifpPO+2qmaiIiIiIiIiDR0NRlxkQx8bxhGJCcSHgbldxmZ7uiKiYiIiIiIiIjUJHHxCeWXiawDjo+NMYDxjq6UiIiIiIiIiAjULHGRZJrmKxUXGoaxzYH1EREREREREXFeZZrjoq7VZI6LKYZhXFXF8lGOqoyIiIiIiIiIiK2aJC76AO8bhlFq8ygD3q6luomIiIiIiIhIA1eTS0WeAm4D1gCllmUGcKOjKyUiIiIiIiIiAjVLXMwFvjdNs8h2oWEY7zm2SiIiIiIiIiJOytQcF3WtJomLL4CphmH8arPMAK4E7nNorUREREREREREqFni4gmgNTABMC3LDCASJS5EREREREREpBbUJHHxIjDXNM0c24WGYQx1bJVERERERERERMpVO3Fhmubskyyf67jqiIiIiIiIiDixMs1xUddqcjtUEREREREREZE6pcSFiIiIiIiIiDgtJS5ERERERERExGnVZHJOERERERERkYbN1BwXdU0jLkRERERERETEaSlxISIiIiIiIiJOS4kLEREREREREXFaSlyIiIiIiIiIiNPS5JwiIiIiIiIi1VWmyTnrmkZciIiIiIiIiIjTUuJCRERERERERJyWEhciIiIiIiIi4rQ0x4WIiIiIiIhIdTXgOS4Mw/AGXgBygCDgYdM0s6so9yjlAyXKAB/gCdM0zTN93zpPXDwwcUFdv6UTacixw+trnq/vKtSr+3tMre8q1Ksyzvg4dV5wb8AD3DIpqe8q1CtX07W+qyD16Imc1fVdhXozzf/CyOToegAAIABJREFU+q5Cvep+LLe+q1CvQkPz6rsK9crNs7S+qyBSW94C5pmm+aVhGJcD7wLjbAsYhjECaGGa5mTL8w+Ba4Avz/RNG+43aRERERERERGpFsMwooHxwI+WRQuAUYZhNK9QtD3gb/O8AAg4m/dW4kJERERERERETmcAcNQ0zXwA0zSPAbuB/hXK/UR5QuMqwzCCgFDgv2fzxprjQkRERERERKS6zAY7x0VjIK3Cshwg2naBaZp/GYYxDvgMWAyMNU2z4GzeWCMuRERERERERBo4wzD+n737Do+i2sM4/p30HpKQhNBJ6L0KKE1AFBBEQUG813YRFbtiQSzXa8PeUbF3sKGCSlWkg0gv0ntIIKSSTjL3jw2b7CaEELIl5v08zz4wM2cm57dn5szsmTNnxhuGsabEZ7xdEhPLYx8l+UKZA5p5AyOApsAMwzC8zyVvargQERERERERqeFM05xmmmbXEp9pdkkOY3mTSEnBQHzJGYZh9AW6maY5H8tjJB2Be88lb2q4EBEREREREZEz+R2oW/RKVIp6UTQE/rBLdyWwB8A0zXjgEaD3ufxhjXEhIiIiIiIiUlGFNXOMC9M0EwzDmA0MwDIA50DgO9M0DxuGMRGYZZrmdmA90LXEqgXA6nP522q4EBEREREREZGKuBV43jCMDkAd4NQ4GFcD+4DtwIdAQ8MwHgKSgAbAM+fyR9VwISIiIiIiIiJnZJpmCnBTGfO7lPh/IfBYVf5djXEhIiIiIiIiIm5LDRciIiIiIiIi4rb0qIiIiIiIiIhIRZk1c3BOV1KPCxERERERERFxW2q4EBERERERERG3pYYLEREREREREXFbGuNCREREREREpKIKNcaFs6nHhYiIiIiIiIi4LTVciIiIiIiIiIjbUsOFiIiIiIiIiLgtjXEhIiIiIiIiUlGmxrhwNvW4EBERERERERG3pYYLEREREREREXFbargQEREREREREbelMS5EREREREREKqpQY1w4m3pciIiIiIiIiIjbUsOFiIiIiIiIiLgtNVyIiIiIiIiIiNtSw4WIiIiIiIiIuC0NzikiIiIiIiJSURqc0+nU40JERERERERE3JYaLkRERERERETEbanhQkRERERERETclsa4EBEREREREako03R1DmqcatFw0ah9HOeP6U9edh5J+xP449O5ZaYzDIPh948BIDgilFkvzyAtMeWclsV1a8nVT99EWJ0INi5Yw/RH3yc3MweAmOYNuO6l24hsXIdNC/7i8wff5mTeScd9ESXUiatH3+su4dj+BKIa12HpVws4tHX/WW0jMCyY4fePITs9C08vT2ZO+YLCkwXW5de/cgfnXd4bgA3z/+Tdm16o0hicbfnqtbzx3qe8+L9J1IuJdnV2zoq3rzcjJv2LnMxsAkID+XHKl+ScyC6VrnW/jrS5sBOGhwc7lm9m/a+rKrQsIDSQgTcPxy/In68f+9A638PLk8seHMvJ3DyCwkPYtmSjzXrO5Oh64NTfGDZxNHPfmsnOVdvK3P5tH0/ir9nLWfntH1UZng1Hl/fplrXu15EJH0+y+Rv71u/ixRGTARg0YQSGhwdmYSE+/r7MfmmGI8I/o8bt4+g9ZgB52Xkc3Z/A75/OKTOdYRhcfv/VgKW8f3x5BqmJyQA069aKfz09nrA64WxYsIbPH33PWreXdNfHk/lz9jKWf7vIYfFUlqefN90nX03eiRx8QwNY/cwM8svYT3xrBdL+lqF4B/mz/JFPytxOq2v6k5uWRdqeeI6u3e2M7J+zqojfJySAq1e9hk+wPwDzx73KvjlrnJL/qtCxczv+de0osrNy2Lf3AB+890WZ6Vq2asab70whNrYxc379jbtvf5i8vHyb7Tz8yF28+tK7LF/2p7OyX2meft70mHw1+Sdy8AkNYFU5Zd/hlqH4BPmztIyyv6ZE2c+tRmVv+PlQf/J1FJ7IxjM0kEPPfEqhffyeHjR6bgLhQ88n99BR9t79Gtlb9hYvrhVEnVtG4BkUwIFHpjk5gqpj+PoQdvdNFGZl4xEcRMpr72NmZp02fcCgvoRcNYyEcROdmMsq5OtDrdtvpjArC4/gYNLemlZuvP4D+xF0xXCOTbgXACMwkLDJE/Hr0ZWTh+JJff5V8jaXfb0j4m7c/lGRgNBArnvldr5/6lO+e/IT4rq1pFWfDmWmHXznSLLSs/jx+a9YMG0W496655yW+fj70u+6wXzx0Dt8ct+btO7TgcseGAuA4WHQaXB33rz+Gd7491O0HdCZ8y7v48BvwtZ1r9zOnLe+57cPfmbu2z9w4+t3nfU2bpp6Dyu+/p0fpnzB0b1HGHbvVdZlYXUjyDiexmvXPMlr1zxp82O2OkpKTiErO5tNW7e7OiuVMvqpcexe8zezXpjOxvlrGPPMTaXSRDWJYdjEMXz734/5+tEP6Hf9YGKaNzjjMoDajeoQ06w+PgG+Ntu85I4ryEzJYNaLM5jx6AdccudIm/WcxRn1gG+gH37BATQ9rzUYRpnbPn90f+q3aVK1wZXBkeVd3rKm3Vvx/i0v8eLlj/Di5Y8w68UZbFrwFwBt+3cmokEUc9/8nnlTfyA0OozOl/Z0+HdhLzA0iP+8cidfP/UpM578mGbdWtHmNPvCpXeOIis9i++f/5J5037ilrcsF24+/r70v24wnzz0Nh/e9yZt+nRk5APXlFq/9+gBNGzT2JHhnJMLnr6BhNXbWfPc1+yft5ZeU24sM11wo2jCmtfH2+74BvAJDWDA1DvYP38tO79dUm0aLaBq4m859kL+uOddfh7zLD+PeZb98/5ydLarTK2wUKa++zyPT36ORx9+lu49u3DhgF6l0nl4eHDp8EGMGXkTo0bcwKCL+3HVmMusywODAgkJCaLH+d1OW/e5m95FZb+6qOz7nKbsQ4rK3quMsm819kJ+v+ddZo95ltnVrOwbPX0zJ1Zv5fBzn5M6bzWNptxaKk3EFf1I+nwumy64hbz4JBo+aXse8W1UB//mDfEI8HNWth0i/OE7yVm3mdQ3PiR70XIiHrn7tGk9IyOoNW6sE3NX9cIeuJvcDZtIf/sDshcvI+yhe0+b1qN2BMHX257bgq8dQ/aiJRybcC8FSceJeOFJDL/qvQ9IzVHhhgvDMJ4xDKO/IzNTll5jB3Jw815ys3IB2LTgLy6+9bJS6Ty9PRkw7lI2zF0NQMLuwwRHhNKse6tKL4tqUoevJk9j79qdbJy/hp9f/YbmPdsAljt5c6fO5MTxdPat38X2ZZspdOJrceo0rYdfkOUuQX5OHn7BAWe1fuNOzYiKrcu+9bsA2LhgDX2vG4yPv+Xk3v8/l7Lnr+3sXLmF7cs2kXLkeNUG4GS1w8Po39v5P7KqQmhUGF2GX2D9Abl96SbaDexCeP1Im3T9xw1l6x/rMYu6rm1bvIEBN116xmUABzbu5tDWfaX+ds8r+3F4m6UnT2FBIVsXrWPA+EtLpXM0R9cDALmZOWxftokTx9PLzEPthtEER4SQuPuwI0K0cnR5l7dsyWfzWD9nNfvW7WTfup1ENopmwxxLb4zoEnUOWOod/7Osd6pCn7EDObB5D7lZlt4RGxasYfCtl5dK5+ntxaBxw1g315L/I0Xl3bx7a6KbxPD55GnsWbuD9fP/5KdXv6ZFz7Y260c2jCYoIoSE3fGOD6oSAqJr0XRET/bPXwfA4SWbaTSoE0H1a5dKm7RhD8dP0yNvwNt3sOn9X8k4cMyh+a1qVRG/h48X9fq0JXn7QeKXbiF+6RbMwurT9ffa669i44YtZBbdbZ376+/ceff4UukMw+C1l6eRlJTM2r82smTxCgoKiq9XMk9ksnjRCo4nJTst7+fCvuwPlVP2x8op+/pFZX946RYOV6Oy944OI3xEH9LmW3rGpC/ZQK1B5+FTP8omXcqspWSu38nJ5HSOfTa31KsbszbsImvrXqozz8gIggZfSPbilQBkr1pLQL8eeNUtu1dt6A2jyfh2tjOzWKU8akcQMKg/OUtWAJD751/49e6J52l6EQdfO4bMmbNs5uWuXkv2vN/I/3snyY8+jUdICF5NGjk87yJV4Wx6XIwCSl3RG4YRU3XZKa1Fz7YcP3jUOp24J54mnVvg4eVpk65Ruzj8gwM4fsg2bbMebSq97NDW/WSlZVrnpyYmkxKfBFh+xBXkWx6rMAyD/Nw81vy4tGqDL8e6X1dxzZRb8A3047zL+/D14x8B0LBdLEPvvpL/vHk349+5D79g/zLXt/9eT3WXb9Q+Fm8/H9oN6MJ/3rqHp5ZPpcX5bcvcRnXj4eH2HYzK1KxHazJTMsjPyQMs+97xg8esP7hPad6zTaljpWmP1mdcdopZxrN6fkEB1IqJsE4nH06ibouG5x7UWXJ0PVCSaZZugDQMgwtvGML8abNKLatqji7v8palxBc3UBoeBpFNYkjYZWmo2bxwLe0GdqHj4O74hwQSGB7M6u8XV2XoFdKyZzuSSuQ/YU88cZ1b4Gm3LzQuKu+kQ8ds0rbo0YaDW/eRmXbCOj81MZnkorodLOU98IahzJv2kwMjOTcxPVuRk5JBQdF+YhYUknHgGDE9WpWZvqwfZQ0HdiK0SR1qt23MxZ9O5LzJY/Dw9ixjbfdTVfFHdWrK6CUvcfEnE/ENC3Jonqtarz49OLD/kHV61669dOveCS8v26eACwoKyM+3PBZiGAY5OXl8903pusyZN1/ORd2isj9pV/Z1z6LsGxWV/dVLXuKSTybiV43KPrhnO06mpFNYFD8FheQdSCTY7lxmXQ74Na3H4Smfl95YNWmsOR2/ru0pSE3HzLHc1KCgkJOHE/Dt0r5U2qARl3Dil9+K01ZDvp07UJiajplbHG9BfAK+nUr3OgwYNpjsuQtLxZv71zrr/83MTAozMyk4Wr0art1GYeE/8+PGzuaX3NPAWMMw+hqG0afocyHwooPyBkBonXBOpGRYp3Mys/H29SYoLLhUuuyMLGtjgiVtDqHRYZVeZq9xx2Ys/myezbz6rRsx/t2JhETWOuteD+di+iPvczI3jwd/epbczBzWz1mFX5A/A8cP4+dXv+GD218luHYog28fWeb6teqEk5lywmZebmY2odHh5Ofk8d9+d/Jw91vY/Ns6bvv4Yeq2cP7jAWIRWieczBLHABSXVel0J0qkySE0KuyMy8qzbfEGev97ED4Bvnh4etCwbSyGh/O7Eju6HjiTftdfwpLP59mMAeMoji7viu4LTbu3Zvfq4udeE3cf5qM7X+ffL03g+tfv4POJb5Ofm19qPUerVcF9oZa1vE/apK1VRnk36diMRZ8Vj5PR//rBLPp8LgVOKO/KCqwTTo5dHZ6fmUNAdK0KbyNuxPkk/rWLzR/OY9Gd7xA3vAddH7zqzCu6gaqIf98vf/JJq5uYNfJJguvX5uKP7q02j0oAxMREk5ycap0+kZGJr68PERFl12lt27Xk48/fJCq6NiEhwWWmqQ6qouz3/vInH7W6iZ+qYdl71wnnpN05oiAzG2+7cwSAZ61gom8ZQdT1Q/AMCXRWFp3GM6o2ham291QLM7PxioywmedVPwaP0GDyNv/tzOxVOc+oSArS0mzmFWZl4WkXr2e9uniEhpC3pfx4vRrUJ3ftBgqPV4/eViJn03AxAbgB+KTE50PgCgfkq5hpkp9b3Grs7eMNUPqC0jStdyiL03pZfqRUdlkJ/iEBhNUJZ9NC22cgU+KPs/qHJdRuGM21L06oVIiV4e3nw5qflvHnj0sZ9dh1tLigHW37dyawVjAX3jiEC28cYr1TWhbT7nsF8PLxtrnITz+WypeT3mXtLyvoe90lDotFzqACZWVJh006Lx+v4h/a5S0rx/TJ77F//S7GT7ufi24dQaMOcSSWs185jKPrgXLUa9mQ/Nx8Ehz8iIiVo8u7gvtC+0FdrY/VnOLp5cl7418kslEdbnzz7lI9XpzinPYF79PU7RFsKKrb67dsRH5uPkecVd6VZJqmtbfBKZ4+3mfVuBbWoh6Ja3ZgniwgN/UEf3+5iKYjzq/inDpGVcR/SsKq7fw8+hlCm9YlqlNcVWXR4UzTJKfE3VRfXx8A8u3riiKHDyXw3TezaNS4AW+8PcUpeXQE0zStvS1O8ahk2R9ZtZ3Zo5+hVtO6RFeXsjdNm94UAIaPN+bJ0uVemJlNxorNZG7YRdx7D+EdU/pxmmrNNIt7HxQp9V0YBsGjh5P++XdOzpwDmCbYXR8Y3j6YJfd9wyBo1GWc+OqbM24u8MrLSHv93arOpYjDnM1bRZ4HFpqmmVpypmEY951pRcMwxgPjAfqGd6F1cOxp0553eW+umXKzdXrv2h0EhBR34fMN9CcvJ4+sNNvW9tTEZPztWpN9A/1JS9xT6WUlDRg3jG+fLD0ae2bqCdb9spITyelM+PCh08ZV1a5/9Q4+vONVstOzwIQbX7+LPz6dw/GDR/n9w19s0obXq83jv71qnf7ioXdJS0wmuontUz4+/r42b1g4ZdHHvzL07isdE4icUWpiMgGl9lG/UmWVmmCbzrIfJ59xWXmy0jL5apJltPHgyFCG3DWSH5/7stKxVJSz64HyXHjDENoP6sbwiZa3kfgHB9CwbSwN28by9X8/qlR85XF0eVd0X2jYLo7vniiu85p2b0WjDnH8OOVLXhv9BBN/eIr+44ay4B3HPk7R4/I+XDflFuv0brt9wS/Qj7ycXDJLPNYHkFJGefsF+pFq9z0OGjecGU8Wl+OAG4bQadB5XD7R8jYS/+AAGrWNpVHbWL76r/sMUpyVkIJvqG183kF+ZJVRh5+Oh6cnHp7F9y+Stx3At1b1uCtbFfGXlJ2Uzp6fVhJUL4Kja3dVRRar3JWjL+Pl15+0Tq9ZvZ5atUKs00FBgWRn55CamlbW6qSkpPLTD3NISkrmy6+r74+VzDLK3uccy353UdknumnZl5SfkIyXXfyeQf7klxG/mX+SrA272HPri7RdPJWgzs1J+TmpVLrqquDocTzseg95BAZQcKz4sUffjm0IHjmUoEsvAiwNG4aPDw1+/5aDF45yan7PVcGxJIwQ28eajEB/Co4Vl6lPh7YEjriUgCGDLMu9vTF8fYiZO5MjFxePB+XbrTO5f22gIP6IczIvUgXOpuEiDFhfNKaF/XovlbeiaZrTgGkAExpfVe4DdRsXrGH/kOJRzdsN6GLzTH1UbAy7Vm8t9czigU2Wwdoi6kdyvOiZ5qgmMcx+ZUall51ywdUDWPPjUjJTbX8k2fz9jbtJTXBOV6vAsGDqt2pkabQAfn3jO3qM6otpmrTt3xlvX29rF+7GHZtyYPNenhnygHX9tKMpRDWOodfYi6zzIupHUpB/kv2bSo8obxaaHNxcvQdwqs52rNjC2Gdvtparh5cnYXVrs3PVVpt0fy/dSFRcXet0VGwMO1ZuPeOyihp8x0j+XraJrYvWn0M0FePseqA83z39GbNf+do6PW7qvaz9eQUrvll0rmGWydHlXZF9oUHbJhyyO+Y7DelB/PaDgKUOmf3SDDoN6eHwhosNC9bwxJDi19Z1GNCVeiX2hejYuuxYvQ3T7rnM/UXlXbt+FElF45pEN6nLDyXKu8/VA1n94xKbuv2bpz/lpxJpbpl6H2t+XsGyb36v8tjORfzyrfR+/j94+nlTkJOP4eVJUN0IjqyseFfo5G0HCI0rbsAuPFlI6i73HIzUXlXEb88sLOT4lgNVmMuqNefXhazrtck6ffHgC2nVqpl1Oq5pY1Yu//OMY1VsWLeZhCOJDsuno8Uv30pgibL3KCr7+HMs+yQ3LvuS0pdvotHzEzD8fDBz8jC8PPGpG0nGys2nX6mwkKwte8hLqN4DrdvL+XM9no/dg+Hrg5mbB16eeNWJJOevjdY0uZu3c3hE8VtnAgf1IeCivhy7/8myNunWctesw3PSfeDrY+l54emJV3QUueuK483b8jeJo6+zTvv374f/wL4kP/yEdZ5X44Z41Ysh84efnZn9fx43Hw/in+hsHhV5GXgIaA3EFn3igMlVmaGcjGwSd8dbPyu/+4PGHZtauyS36duRhe9ZRgQOiazF0HssPQEK8gtYNn0hbft3Bixv3UhNOM7etTsrvQzg/KsuJDczh7zcPCLqR9L+oq7EdW2Bh6cHjToUdyts279zqZ4OjpKVeoL83HybZ/MzU06w8ttF+AT4cuuHD9GqTwcuGDOA6Lh6FJ4ssPlOczKyObBpD+nHUqyvQWzdryOLPplDQX4B0XF1aTewC2B5S0P3kX2Z9+6PTonNkU4NPlnWIJTuLONYGpt/W0uLC9oB0LJXOzbMWUVaYgoDbrqUqFjLD4+lXyyweUVo855tWPTRr2dcZmUYGKd5xrfj4O40aBfLZ/e+VZWhnZaz6wFbtt9DdnomqQnJ1s/JvHyy0k6QnZ6JIzi6vCuyL7Qf1I31do+JHNq6nwYlXg1aWFDIvg2Of3VmdkYWCbvjrZ/l3y2iScdm1sE42/btyLz3LAMNhkbWYvg9ljEaCvJPsmT6AtoVlXdM0/qkJBxnz9odAPS6qj85RXV77fpRdLyoG027tiQrPZOUhGTr52TeSTLTTpDloPKurOxjaRxYsI56F1gG5KvXuw17f/2TrIQU2t08hNBYu3GzDUo9w7/5g7k0uLADHj6WexHRXZux5UPbcZzcVVXE32RoN4IbWt7WExoXQ25qJml73PfuY0b6CXbt3GP9zPhyJp27drAOxtl/YG+mvmnpPRQdHckDk+4AwNPTk06d21m3c9HFfXn37U9Lbd8o5xzgTrKPpbHfruz3FJV9+zLK3jhD2deqBmVf0sljqaQtWEPIBZYBKIN7dyDl1xXkJyQTffNl+MZaGqb9WjS0jmvhGRKI4elB5l92r4Q3ij7VVMHxFLIXr8TvvE4A+HfvTObCpRQcPU7ItaPwalQf8vMpOJpk/RSmn7DOq24Kk1PIWbYCv66W85rfeV3I/n0JhceSCLrmKrwaNigdb0YG5BXH61k3hsARl5Kzag2eMdF4N4sl8IrhrgxLpMLOpsfFfOAH0zRzSs40DOOLqs2SrRPH0/n68Q+58rHryc7I4u9lm9i2xNKyGNEgku5X9GXe1B/Iz83n51e/4YpJ/+KS26+gVp1w3rv1Zet2KrOs+xV9GDvlZpu3UWSlZ/Jgl3GERocx/u37OJGSwfZlmzm67wiLP3fOBZ9pmrw7/gWG3DWKA5v2EFK7FjOf/YyU+OO8e9PzjP7ff/jPG3ex/OvfmflMGaNIF/ng9lcZcucojh86hm+gHz+98BUAtaLD+deUW0g6dJR963Yy962Z5GRkOyU2R8nMzGLWvN8A+OGX+YwdOYzwsIoP5OVq0ye/z4hJ11CvVSNCImvxZdHjG12GX8DxQ8c4uucIR3YcZPEnc7jikX8DsPC92STstIw4X94ysLyNpnmPNgRFhNC0eyt2rbIMyti8ZxsatIvFy8eb18c84ZLBGME59YCHpwedh/YkJLIWnYf2JOlAIsmHXXNh48jyPtO+AND0vJb88qrt87Erv/6d8LoRXHTrZZxIziCsbgTz3prpuC/hNDKOp/PV4x8w+rEbyM7IYtuyTWxdsgGAiAZR9LyiL79O/YH83Dx+fPVrrpz0b4bePpKwOuG8fatlLOmeV/Tl2im3lKrb7+nyH6fHcy6WPvwR3SdfTXjrhgRE1WLJAx8AEHdZT04cOmb9IVa7fRPq9myNX0QwdXq0JKHozvTRtbtY88K3nP+/a0nbfYST2bns+Nr5b4qprHONP6ZnK3o/P4745Vs5smIbf730vctiqYykpGQmPfAkT095mPT0DBb/sYJFvy0DoEHDelx19Qhef2UaEbXD+eizN0hOTmHxHyvYs3s/H71f/Mifp6cnw0dcQlR0JJddPpj9+w5y6KB797xZ8vBH9Jh8NRFFZb+4qOybXtaTjNOUfUyPltYeOXV7tqJvUdnHr9jGmmpW9vsffof6k68joHVjvKLC2P/AVADCL+tD3qGj5O6JJ+b2kYT07kDqvNXkH0u1pjkloH0cwT3b4RURQlCPNpxYucUVoZyz40+/Ttg9N+HTIg7PiDCO/+8VAAIvuZCT8Ymc3H/oDFuoXlKee5XQ22/Gu1kcnhHhpDxr6fQeMKg/BUcSOHng4GnX9YgIJ/Ltl/GqE03w1cWPyRyf/D+H51ukKhinu/tsGEYfu1lhQC/A/h1ao0zTvLOif/BMj4rIP9dra6rvYGBV4Z6uk1ydBZcqpGYf+h7V+bbWOcrBfd/O4QzdT/q5OgviQg9n/OnqLLjMU8HdXJ0Fl+rC6R8xrglq13avnmrO5uVbs8999Vf99o++8Mn+4tF/5IWt/zVPum25ldfjYgrQAUgCSj7EU3IkGwOIBirccCEiIiIiIiIiUlHlNVw8Chw0TXNHeRswDEMPRomIiIiIiEjNYGpwTmc7bcOFaZoLK7IB0zQdO6S8iIiIiIiIiNRYZ/NWERERERERERERp1LDhYiIiIiIiIi4rbN5HaqIiIiIiIhIzVaoMS6cTT0uRERERERERMRtqeFCRERERERERNyWGi5ERERERERExG1pjAsRERERERGRijJNV+egxlGPCxERERERERFxW2q4EBERERERERG3pYYLEREREREREXFbGuNCREREREREpKIKC12dgxpHPS5ERERERERExG2p4UJERERERERE3JYaLkRERERERETEbanhQkRERERERETclgbnFBEREREREakoDc7pdOpxISIiIiIiIiJuSw0XIiIiIiIiIuK21HAhIiIiIiIiIm5LY1yIiIiIiIiIVJSpMS6cTT0uRERERERERMRtqeFCRERERERERNyWGi5ERERERERExG1pjAsRERERERGRCjILTVdnocZRjwsRERERERERcVtquBARERERERERt6WGCxERERERERFxWxrjQkRERERERKSiCgtdnYMaRz0uRERERERERMRtqeFCRERERERERNzf6rkzAAAgAElEQVSW0x8VyafmvjrGv4a3E93TdZKrs+BSr6x51tVZcKmhnSa4OgsutSs70dVZcJneQbGuzoJLLffKdnUWxIVGh3V0dRZcZgv5rs6CS/2Nn6uz4FKJKYars+BS3kbNvu7/xNUZkH+cmn1EiYiIiIiIiIhb0+CcIiIiIiIiIhVlanBOZ1OPCxERERERERFxW2q4EBERERERERG3pYYLEREREREREXFbGuNCREREREREpKIKa+6bMl1FPS5ERERERERExG2p4UJERERERERE3JYaLkRERERERETEbWmMCxEREREREZGKKix0dQ5qHPW4EBERERERERG3pYYLEREREREREXFbargQEREREREREbelMS5EREREREREKkpjXDidelyIiIiIiIiIiNtSw4WIiIiIiIiIuC01XIiIiIiIiIiI21LDhYiIiIiIiIi4LQ3OKSIiIiIiIlJRpunqHNQ46nEhIiIiIiIiIm5LDRciIiIiIiIi4rbUcCEiIiIiIiIibktjXIiIiIiIiIhUVGGhq3NQ46jHhYiIiIiIiIi4LTVciIiIiIiIiIjbUsOFiIiIiIiIiLgtjXEhIiIiIiIiUlGFpqtzUOOox4WIiIiIiIiIuC01XIiIiIiIiIiI21LDhYiIiIiIiIi4LY1xISIiIiIiIlJRZqGrc1DjqMeFiIiIiIiIiLitat/jonH7OHqNGUBedi7H9ify+6dzykxnGAYj7r8agJCIUH58eQapick22xkxcQy/vDWTHau2WuePf/Meul16vs22vnjkPRZ9Ps8B0Zyet683wyf9i9zMbAJCA/lpypfknMgula5Vv460ubAThocHO5dvZv2vq864rFW/jtz68SSb7exfv4uXRkwG4KIJIzA8PDALC/Hx9+Xnl2Y4MNKyeft6M2LSv8gpiv/H08TfukSMO+ziL29ZQGggA28ejl+QP18/9qF1voeXJ5c9OJaTuXkEhYewbclGm/Wqk+Wr1/LGe5/y4v8mUS8m2tXZqVLNOzRn8JhLyM3JIX7fEX76ZFa5aa+//zq+enM6m1Zuss5v3KIR9788kbpN6rJy/ipevv8V8vPynZH9c9a+U2uu+tfl5GTnsH/vIT77oOxjtFuPTjz54mRi6kaxYM4fPPbAs2SeyLJJE9esCQMv6cv+vQfZsHYzR+ITnRHCWWnSPo6+YwaSl53L0f2JLPj01zLTGYbBqPvHAhAcEcrMl6eTUqLeP+W+jyezavZyln77OwDNu7Xi+qdvJqxOOOsWrOHTR6eRk5njuIDOUpP2cfQZM5DcovPewnLiH2kX/6nzXr3mDRj30h1EN45h/YI/+fDBqZzMO2ldt8/oAdzw3AQA0pPSuO/88TbLXckZ8QPExNWj00XdSNyXwN4NO0k+ctyxgdlx5HnPL9ifsVNuoVWf9iQdSGTGIx+wb91O6zoT7K4J9q3fxYtF1wTO4srrHv+QAJ5Y9hZ+wQEAvH/zi2yc+6ejQj0jb19vhk26hpzMHAJCA5k15Utyy/guWvbrSOsLO2F4GOxavoUNdtc5F948DL8gf7577CObdW7++CGb7exfv4tXRzziuIAqKbZ9Uy4sOvaPHkhg3ienP/avuv8aAEJqh/LtS1/Z1P39xgxk/HO3AZCWlMYdPcdZj//ylrmao899p/7GyIljmfXWd2wv8XtIxB1U64aLgNAgbnzlDp4e9hC5WTnc9MbdHN13hC2LN5RKe+mdI8lOz2TOOz9SJ64eN791D8+NehQA30A//IMDaHZea5g6s3j7IYHkZuXwwpjHOZlr+QFz5SPXsWHhX84JsIQrnxrHtj/Ws272Clr17cDoZ27ikztft0kT2SSGSyeO4cVhkzBNkztn/JfE3fEc2XGw3GVNu7fig1teIi0xBYDmF7SzbrNN/85ENIhi+qRpAIx9/hY6XdqTdbNXOC94YPRT49j6x3rWFsU/5pmb+Ngu/qgmMQybOIbni2K8u0SM5S0DqN2oDjHN6pOZdsJmm5fccQWZKRnMm/oDHp4ePDB7is161UVScgpZ2dls2rrd1VmpcsG1gnjw1fu5begd5GTl8PBbD3F4Xzx//VH6OPUP9CcwOJB23dsy/U3DOt/Dw4Neg3sx+dpHqNOgDs98/jQDrhjAnOllN4S6k9BaIbw09SkuG3gNWZnZvPbeFPbtOcCS322PUf8AP64dN4ZJd/+PiMhwnnn5Ue5/5A7++9Bz1jR9+p/PxZf259GJz1BY6J5dIANDgxj/yl38d9gD5GblcOsb95Cw7wibF68vlfayO0eRmZ7JL+/8QExcPW576z6eGmX746vv6AE0bNOEVbOXA+Dj78tF1w3hg4emEhIRyo3P3sqVD/yLzx5/3ynxnUlgaBA3vXIXTxTFf8sb95B4mviH3zmKrBLxT3jrPp4ZNRnDw4Oug3vw8vVPEdkgmvs+fZTzL+/L4hkLres26dCUF655AoD042luc+HurPjb9u1Il4t78Okj0zBddCw48rx30S2XsWHuKua//QND772K8dMm8t8+d5KXnUvT7q14/5aXSC26JmhR4prAmVx13QPQc8wAPp84lZwTlgbLnSs2Oyfo0xj51H/4+48NrJ+9gpZ9O3DVM+P47M43bNJENolh6MTRvDzsYUzT5PYZj5O4+zAJOw4BENEomjrN6pOVlmmzXtPurfjolpdJK/pha/9duIvA0CAmvHIXk4fdT25WDne8cS8Je4+wsYxj//I7ryQrPZNZ78ykbtP63Dl1Ik+MfNi6PK59U54Z+zgAaXb1W3nLXMnR5z4Av0A//IMDaXFeK2ZPNew3K+Jy1fpRkT5jB3Jg815ysywnlo0L1nDJrSNKpfP09uKiccNYN3c1AAm7DxMcEUrz7q0ByM3MYduyTWQcT7dZz8ffl08fepcdK7eyZ91ODm7dT0H+SVKcfNclJCqMrsMvYPMCyw+x7Us30XZgF8LrR9qku3DcULb9sR7TtLxX+O/FG7jwpkvPuGzpZ/PYMGc1+9btZN+6ndRuFM3GOZZW+uim9fAN8rf+jfycPPyL7kA4S2hUGF2GX8CmEvG3KyP+/uOGsrVEjNsWb2BAUYzlLQM4sHE3h7buK/W3e17Zj8Pb9gNQWFDI1kXrGDD+0lLp3F3t8DD69+7p6mw4xJCxQ9i5eRc5RfXAyvmrGD3hqjLTZmdms27pOtKOp9kuMGD6WzNIPZ7G3+u3s27ZegoLCxyd9Spx9bUj2bLxb7IyLXfffpv7B7fcdUOpdI1jG/LIxKdZt2YjC35dxOvPv0OPXt2sy5s0bcR9k2/jiYeec9tGC4B+Yy9i/+Y91np//YI1XHrr5aXSeXp7ccm44fw111KXHSmq91sU1fsAUQ2jCY4I4cjuw9Z5dZrE8PHkd9m9dgfr5v/JzFdn0KpnWwdHVXF9y4h/yGniv9gu/pCi+A0DZk+dScbxdPas38nWZZtsyrzToPPISs9iz4adbF22kUN/73dOcBXgjPjrxNZl5MSxfPHf913WaOHo8972pZv466flHNy8l4/vep3AWkHUaVYfgCWfzWN9iWuCyEbRbJjj3J6Grrzu8fLxomXv9hzZfpAdyzaxY9kmzELTKXGXJaRoX9hS9F3sWLqJNgO7EGb3XfQbN4Rtf2ywibdfieucgxv3cHhr6WN56Wfz2DhnNfvX7WL/ul1ENIpm45zVDoyocvqPHcTeLcXH/tqFaxg24YpS6Ty9vRhy02X8WXTsx+86RGhEKC27twGg66DzyMrIYveGnWxetpGDJeq38pa5mqPPfQA5mTlsXbax1O8hEXdR4YYLwzCc20ewAlr2bEvSwaPW6YQ98cR1boGnl6dNusbtYvEPDiDp0DHrvMQ98bTo0domnWk3yEpqYrLNRUubvh3YUkbLpqM169GaEykZ5OfkAZYf0McPHqNp91Y26Zr3bMPxEt/H0T3xNCuKsbxlKfHFDTGGh0FUkxgSdlkqsy0L19JuYBc6Du6Of0gggeHB/Pn9YscEehrNerQms4z4m50h/sQ98TQ9Tfwll51y6mRfkl9QALViIqzTyYeTqNui4bkH5QIeHtW6nfK0Ol7QgYSDCdbpg3sO0bpLq1L1QEmFdhehhQWFnMy33FUxDIP83Dx+/2GRQ/Jb1Xr27sbB/cUXH3t27adztw54edl2qNu2eQdpqcUXIwkJx4g/VPy93T/5Dvbs3Mc9kybw2XfvMHBwP4fnvTJa92zLsRLH8pE98TQto95v0i6uVL2fsOcwrXpYLl4Nw+CiG4by67SfbNY7sHWfTc+rlMRkjscfw120sos/4SziP7LnMC17tKGwoJACu/195Y9LrOl6XtabQTcO5fW/PuSiG4c6OKKz44z4R95/DUd2H+bye69m4ueP0+mibjibo897O1Zssc7Pycgm50Q2qUU3ZeyvCSJLXBM4iyuve9r070zjjk15dNFr3PzhgwSGBTsmyApqWsZ3kVzGd9G0Z1uSS8R7bM+RCl3npJbxXSQ6ubwros357WyO/fjdh2neuWWpYz+2fRwBwQEcO1Qi7Z54WhfV/ReM6MvgGy/l7b8+5pIbbW9ElbfM1Rx97iupsIz9RMpQaP4zP27sbH7J9DAM433DMB41DKOxg/JzVsLqhJOZkmGdzsnMwdvXmyC7k0ytOuFkZ2RZL1QsabMJjQ4/q7/XadB5rHVBK3SoXZwAuWXk35Ku+II7JzOH0KiwMy4rqWn31uxevc06nbj7MJ/c+TrXvDSB616/gy8mvk1+rnOf+69s/LnlxJ97mvjtbVu8gd7/HoRPgC8enh40bBuL4aHuc+4kIro2GSX2j+wT2fj4+hAaHnrW24ptHcvj7z1KWGQYgU7uWVRZ0TFRpKYU9yA5cSITX18fwiJqlbtex85t+fyjrwEIDArgwkG9mfX9HJ574jW+/ORb3v74RVq0aurQvFdGWJ0ITtjU+9ll1vthZdb7OdQqqjcGXj+E3z6fS8HJ8nvWxHVsxsLP5lZhBOemovGXfd4rjh+gQevG3P7uA4RG1rLpSTf1tpe4veP1fDPlc6588N/0u2aQAyM6O46O3y/Qjw79u7Dqp6V8M+UzFn05j9vfuZ/6Tm6wduZ5L6pJDDtXbiX9WGqpZfbXBM7iyuueDXNW80C7G3jtqv8SXj+S8e/fj2G47rwfWieMrDK+i5DosFLpMu2OjYpc55QU172VS8q7IsLrhJd57AeHh9imi44gy/7YP5FNWNG+89qEF7ipw7VMn/IZVz90LQOuudiarrxlrubsc5+IOzqbhourTNMcB3wEXG0YxjuGYfzLMAz/M63oKKZpkpebZ5328rHcYbQ/GE0Ta0t1cVpvCvIrftB6eHoQ2TCaxD3x55DjSjJN8nPLyr/dc3cmNum8fLyKv4vylpXQblBXNsy1bZzx9PLk/fEvUrtRHW548248yrmT7RDnEH9hOfEXVqDSnj75Pfav38X4afdz0a0jaNQhzi3vRNRsJrk5udYpbx9vAGsPirNxLP4YC2f+TkzDGCa+fF+V5dCRTNMkp0T8vj4+QPnxB4cEUaduNL/NtfSeahzbEF9fH1YuWwPArz8t4NCBeIZdcYkDc145pl19cKq8S9f7Jnml6n0vCvILaNCyEfm5eaW6ydoLCAkgvE4E6xeuqaLcnzv7+L1OEz9lxO9dFP8pyfFJrPhhMZENoxn34h02aXOzcpj/0c98/vj7DHKjO4+Ojj+6cQzevt78vdLSI2HNLytIOnSM7sN7OSKc03Piea/3tYOY+cznZWajfRnXBE7h4usegN2rt/Hm2CeJiqtHo06ua8Q1TUrdMCrzGtYunZeP91n/OG03qBubXDgIaXlME/JKnOusx77dPmFilr7m97X9LnKzcpjz0Ww+fuw9Bv9nmE3a8pa5kjPPfSLuqsKDc5qmmV307yHDMDYDlwBjgYGGYSQBn5imuamsdQ3DGA+MB+gV3pmWwbGVymyPy/tw7ZSbrdO71+4gMCTQOu0X6E9eTh6ZdgMPpSYm418i3am0aYm7K/y3m5/X2uZtI86UmphMgF3+fQP9rINKWdMl2KazxJh8xmUlNWwXx/dPfGKdbtq9FQ07xPHTlC95ffQT3PfDU/QfN5QF75y+i1lVq2z8vuXE73ua+O1lpWXyVdHApMGRoQy5ayQ/PvdlpWORczfgigHc89xd1umta7cRFBpknfYP8ic3J5cTdgOtVkRGagZLfl5C2vE0nvrkf1WS36o24sqhPPvKo9bptWs2EhpafMclMCiAnOwcm8dC7I2bcC1PPfKiddrT09PmX4C/t+6kViV6rVS18y/vyw1TbrFO7167w64u8yMvJ7dUvZ9SRr3hF+hPSuJuLrphKF0GnceoiZZR1/2DA2jcNo7GbWP5/L8fWNNfMm44Xzz5Ea7U0y7+XVUQ/ymZqSdY88sKMpLTuefDhynLkhkLGfXANVURSqU4O/5TDfMeXsX3dQ7+vb/UXU1Hc9Z5r8UF7di5cqvNIxUlNWwXx3clrgmcxZXXPSVlJKWxbvZywurWZt/anZWO51yklXEN6xvoR7rdd5FWqrxLf19n0qBdLDNdUN5l6XV5X8ZNmWCd3rluO4F25/q8nFxO2B/7CaX3Hf9AP/aWUfaLZixgzIP/KvPvl7fMGVx57hNxVxVuuDAM4wkgCbgN8AXeAIaZppluGEYA8LxhGOtM0yy155umOQ2YBnBT4ysr/fDMhgVr+N+QXdbp9gO6Uq9FA+t0dGwMO1dvLTWY1v5NlsFsatePIqnombfoJjH8+ErFX+vZ6eLzWPbtospm/ZzsXLGF0GdvxtvXm/zcfDy8PAmvW5tddg0p25duJCqurnU6MtbS/fNMy05p0LYJBzfvtZnXcUgP4rdb3qCRfjSFn1+aQcchPcCJDRc7VmxhrF38YXVrs9Mu/r/tYoyKjWFHUYzlLauowXeM5O9lm9i6yPnjnEixFfNXsGND8dtRegzsQeMWjazT9WPrsWnV5nMaYHLHxh0kJSSdUz4dZeGcPxi6rvj59AGX9KF5y+K7gU3iGrF6xdrTxj/m2iv46btfbR4v2b1zL3l5+cQ2bcyGtZbR8wtOFrBr+x4HRVFx6xb8yd4S9X7HAV2pX6LerxNbl+2rt5Wq9/eVUe/XaVKX71+Zzm+fz2XmK9OtaW+fOpHVPy9nyTfFr4Trd/VFrPhxCZmpZ98AVpXWL/iTx84Q/44Kxh/dpK5N3Na0G3eTknD6htz9m123Hzg7/iO7DnEyL5+Y2HrsWW/5oVp4soD4nYeqPLbyOOO8Fx1Xj9oNo1j2VfHbVEpq0LYJh+yuCZzFldc99goLCjlcxuDdzrJrxRZCnx1fal/YXeq72ERUXIx1Oio2hl0rt9hv7rTqu7C8y/LXgj/ZM+Re63Tngd2o37z4ka2YJnX5e1Xpa/49m3aTk5VDZIMo65gQdZrU5duXSx/7AHs3nf4mZnnLHM1V5z6pOFcN3lyTnc2jIo9i6WHxKBBnmubLpmmmA5immQVsBqZUfRaLZWdkkbA73vpZ8d0imnRsZh2Ypm3fTsx7bxYAoZG1GH6P5c0CBfknWTJ9Ie36dwYgpml9UhKOs2ftDpvtGxinfY6xQevGHHDRxVvGsTQ2/7bW+oqqFr3asX7OKtISU+h/06VExVpOVMu+WECrPh2s6zXv2YY/Pvr1jMtOaTeoGxvtukse3rqf+m0aW6cLCwo5sMG5Ffmp+E+9kq1lr3ZsKIp/QIn4l5YR46KiGMtbZmWcvvw7Du5Og3axfHbvW1UZmlOdGpSrrMG5qpOsjCwO7j5k/cz/dj4tOxUP0NW1X1e+m/YdAOFR4fz73tJ3TAzD8jnFw9ODFh2bW6e7DziPmR/84NhAKikj4wR7du2zfr6fPouOXdpaB+PsM+B83p/6GQCR0bW5+8HiOzZXXTOCrMwscnJyqN+wLgMH96Nr945knsji689nMnj4QMAykGuTuEbM/Ppn5wdoJzsjiyO7D1s/S7/7ndiOza3l3a5vJ+a8Z2lIDY2sxeX3jAYs9f6i6Qvo2L8LAHWL6v3da3eQlZ5JSkKy9ZOfl09mWiZZ6ZY7V32uGkBOZjb5uXnUrh9Fp4u60axrSxdEf+q8d9j6WXaG+EeUiP+P6QvoUEb8Hp4eNOlQ3NjVoX9n5n04GwC/IH96X9kfT2/L/jToP5cy8zQX/M7g7PhzMnNYPGMhXQdb3sJkeHgQHVuX5d//4bSYwfHnvYgGUVwwdgDblmwkvH4k9Vo1ote/LrLJQ/tB3VjvisdEcO11T8fB3YloEAVAVFxdslJPcHTPkaoPsoIyjqWx5be1NCv6Lpr3aseGOatJS0yh302XEln0XSz/Yj4tSsTbrGdblnxk+0pv+3NfSWV9F66UnZFF/O7D1s/ib3+naYlr/vZ9O/Hzez8CUCsqjJH3jAEsx/7vX82nU9GxX69ZfZITjrNz7Xb8g/zpe9UAa/02eNwwvnn5K4Byl7mCK859pxiUs6OIuJBR0R8xhmE8Y5pm2X1JLcs7A91N03y7vO2cS4+LsrTq1Z5Og7qRnZFF0qFjLPlqAQCxnZtz02t38djAe8jPzcPL15srJ/2b9KRUatWJYPZr35BWNBCVh6cHXYf25PoXbmPZN7/z69szST5cfLe1UbtYelzehxn/+/ic8up/Dm+f9Q8J5LJJ15B86BjBkbWY9fyX5GXlcv+sZ5k/9QfW/2p57VHXEb1o0LYJALtWbWPT/OJns8tbBnDH9Md4c+yTNq/9MgyDwXePsjyCk5xBrboRzH9rZqXea30u7ZL+IYGMKIo/JLIWPxbF/8CsZ5lXIv5uJWLcaRdjecsatovlikeuJSgihOmT32PXKsvgVM17tqFBu1i8fLz57b1Z5zQw6Strnq30uucqMzOLWfN+46kX3+KWG8YyduQwwsPKH7yxqg3tNOHMiSqpc+9OnH/x+WRmZJJ4MJFfvrRcnLbq3IpJbzzIuAHjycvJw8PTgz6X9mHiS/cy9+t5zHjra44ePkpk3UhenfkyaclprFu2nvi98fz8xS9Vmsdd2YlVur2SevXtzkVDLiQj/QSHDsYz/dPvAejUtT2vvvsMgy4YyZDhF/HCm0/YvF0mPS2Dbi37k59/Eh9fH5547iH27T5ArfBQfpu7mD9XrquS/PUOqtzjgafTpld7Og86z1rvL/pqPgBxnZtz62t3M2ng3eTn5uHt683oSdeSnpRKWJ0Ifnjta2u9X9JD059g6beLWPrt71xwRV/GvXi7zfeUmZ7JHV1uLP18fQVV9ft8WtvF/0eJ+G9+7W4mF8XvVSL+WnUi+Kko/vC6tZn87dNkpKSzbdkmEvcdYdGXlm2E1A7lwen/w8vbi79XbmHxjAXstmvkdzVHxg+W5+H//cQ4EvcdIbBWMOsXrmHnn5UfsDCw4p1bbTjqvBcSWYuJPzxNeL3aNn/vw9tfZe3sFdbpu6Y/xut21wRn61z2fVdd94x64ga6Xt6bncu3sHPlFpZ8MrfSDf6eVM2PP/+QQIZNGmvdF2Y//xV5WbncO+sZFk79kQ1F30WXEb2oXxTv7lVb2Tz/L+s2GrSL5bJH/k1QRAjfTH6f3ats9+nbpj/G1HMsb3uJZu6ZE52Ftr060PXi7mSnZ3Ls0FF+Kzr2m3VuwW2v38P9A+601v1jH76OtKRUwqMj+P71r0k9mkJI7VAenfEUXt5ebF25mUXTF7BzraUHZ3nLKsvbqNra35HnPrD8Hjpv6PmMe+F2lnzzG7Pfnsnxw5V/q9Yn+777R7d+ZD57XfW+E3gagZM+cdtyq3DDRZkrW94uMqjoUZAKqeqGi+rkXBou/glqeocqVzZcuANHNlxUB45suHB3Vd1wUd3U7JpfKttw8U9Q0/f9qmq4qK6quuGiuqnqhovqRg0X1ZM7N1yczRgXo4HJQCBYa2L/ov9XuOFCREREREREpNqqwt5JUjFncxtgHPA/oDOwDDgB9ANWlLOOiIiIiIiIiEilnU0fpnmmaX4LPA/UNU3zD+BpYJJDciYiIiIiIiIiNd7ZNFy0MAzjfSASCDMM43HgVaCdQ3ImIiIiIiIiIjXe2TRc3AWsAzKAl4rWbQhc64B8iYiIiIiIiLgfs/Cf+XFjFR7jwjTNTOCtErMeNwzDC+hb5bkSEREREREREaGchgvDMH4Cgs6wfm0gCVhYlZkSEREREREREYHye1xsLFq+HSgEbsLyqMiaEmmaAOEOy52IiIiIiIiI1GjlNVy8ABimaaYCGIYRZ5rmY/aJDMP40VGZExEREREREZGa7bQNF6ZpptnNijYMw9M0zYJTMwzD6Aec56C8iYiIiIiIiLiXQtPVOahxKjw4J/AtsMEwjKVY3izSCrgYKNULQ0RERERERESkKlT4daimac4HBmEZjLMFkAqMMk3zWQflTURERERERERquLPpcYFpmvHAIyXnGYbR0DTNA1WaKxERERERERERyn8d6kTgF9M0txZNTwY87ZMBFwL9HJVBEREREREREbdRWOjqHNQ45fW4aALUKjHdGQgEEoBTo5EYQB3HZE1EREREREREarry3ipym92sp4HNpmnmlZxpGEZrR2RMRERERERERKTCY1yYprn2XLchIiIiIiIiInI2yhvj4m3A9wzrG0APLK9GFREREREREflnKzTPnEaqVHm9JTyBk0A8xWNa2DOAplWdKRERERERERERKL/h4mngqGma2eVtwDCMD6o2SyIiIiIiIiIiFuUNzrnffp5hGIHAFUB9YDvws2maBx2XPRERERERERGpySo8sKZhGN2AnwEPYB+Wx0SeNAzjStM0tzomeyIiIiIiIiJuxCx0dQ5qHI+zSPsccCsQaZpmV9M0uwAXALc4JGciIiIiIiIiUuOdzatMV5qm+V3JGaZpphqGkVvFeRIRERERERERAc6ux0WQYRjBpyYMw/A2DOPfWF6HKiIiIiIiIiJS5c6mx8VUYIVhGFmANxAHZADDHJExEZKp5gAAACAASURBVBEREREREZEKN1yYpvm3YRhdgKFAU+AA8BNwJbDWMdkTERERERERcSOFpqtzUOOczVtF/gM8CsRg6XFRsrQ+qeJ8iYiIiIiIiIic1aMirwDjgT+Bk0XzDGBMVWdKRERERERERATOruFiPvCDaZo5JWcahvFF1WZJRERERERERMTitA0XhmH0sZv1KfCkYRiz7OaPAu6s6oyJiIiIiIiIuBuzsNDVWahxyutxMQXoACQBJUtmVIn/G0A0argQEREREREREQcor+HiUeCgaZo7ytuAYRjDqzZLIiIiIiIiIiIWp224ME1zYUU2YJrmT1WXHRERERERERGRYmczOGeV8MfD2X9S3EQhNft9x0M7TXB1Flzq53VTXZ0Fl/pv10dcnQWXSSTP1VlwqXC8XZ0FlzpZw+v+dOuL2GoeA8PVWXCpeqaPq7PgUj6Gn6uz4FJeNXz//8crrNnnNldwesOFiIiIiIiIiFQ/hmH4A88DGUAY8KBpmunlpL0ZSAG2m6a5srJ/Vw0XIiIiIiIiIlIRU4E5pmnOMAzjEuBd4Gr7RIZhhAGfAHebprnnXP+ontsQERERERERkXIZhlEXGAvMKpq1ABhuGEbjMpJ/DbxSFY0WoB4XIiIiIiIiIhVXc8e46AckmaaZBWCa5knDMPYCfYF9pxIZhjEMaAZ0NgzjfmAz8IhpmpUe+EwNFyIiIiIiIiJyJvWA43bzMoC6dvPGAiuA14GPgXWAAdxf2T+sR0VEREREREREajjDMMYbhrGmxGe8XRITyLab5wvk281rAywzTTPfNM3jwHvANeeSN/W4EBEREREREanhTNOcBkwrJ8lhLG8SKSkYiLeb54VtW8NGIPxc8qYeFyIiIiIiIiJyJr8DdYtec4phGN5AQ+APu3QbgRYlpk8C287lD6vhQkRERERERKSizMJ/5udMYZtmAjAbGFA0ayDwnWmahw3DmGgYxqnGiteAwYZh+BZNn49lvItK06MiIiIiIiIiIlIRtwL/Z+++w6Oq8j+Ov08KIQRSgCR0CKH3KlVAQJQighXBtaygrrvWhd0fq+5aEF0VLKvYxYaCXUEBAQWlBEQ6oSWhlwikkg65vz8yGWYmQ0hgJhnk83qeeWDmnpk533vPPefmO/ee+6wxpiNQByieB+Mmiu4sssOyrFXGmEeAl40xO4Bsy7Jmns+XKnEhIiIiIiIiImdlWVYqMMHN611dnn8EfOSp79WlIiIiIiIiIiLis3TGhYiIiIiIiEhZFVqVXYOLjs64EBERERERERGfpcSFiIiIiIiIiPgsJS5ERERERERExGdpjgsRERERERGRMrI0x0WF0xkXIiIiIiIiIuKzlLgQEREREREREZ+lxIWIiIiIiIiI+CzNcSEiIiIiIiJSVprjosLpjAsRERERERER8VlKXIiIiIiIiIiIz1LiQkRERERERER8lhIXIiIiIiIiIuKzNDmniIiIiIiISFkVFlZ2DS46OuNCRERERERERHyWEhciIiIiIiIi4rOUuBARERERERERn6U5LkRERERERETKqtCq7BpcdHTGhYiIiIiIiIj4LCUuRERERERERMRnXTCXigQGBTJy8s3kZeVQLSyEb5/5mNwTOSXKtR7QibaXdcb4+bFr5RY2zF9dpmWX3zMK4+eHVVhIleAgvps2x/6ev7w32ek79m5IYNqoh70UqXsXe/zFGneIpfeYgeTn5HNs7xGWfbDQbTljDCMnjQGgRq0w5k6fQ3py6lmXFX/HVRNvZOGrX7Fr9Ta3n//X9ybz27yVxH2+zJPhnbMWHVswdMyV5OXmcmjPYb59f26pZW+bdCufvDKbzXGb7a83admYSdMnUi+mHnGLVjN90gsU5BdURPW9buWadfzvrQ94/onJ1K8bXdnVOS8BQYFcOXkseVm5BIeFsPCZT8hz0xe0GNCRlpd1xvgZElduZev8NfZlVUOrMWnFy1StUQ2AWXdNJ37hWvz8/bh66h20G9aDtAPH+HziaxzeurfCYiurJh1iuXTMIPJz8vl97xF++mCB23LGGEZPugko2te/mT6HtOQUAJp3b83NT91JRJ2abFy8lo8efYu8rNyzLqtMAUGBDJ88jrysHILDQvj+DNu+5YCOtLL19Ykrt7DZtu39/P24Zup4OgzrQeqBY8yZ+BqHtu6xv++ye652GgcWTvu0okIrk8CgQEZMHmdv+/Oe+dht/K0GdKKNre3vWrmVTbaxrmqNYG545i5a9evAsX3JfPHIO+xdn2B/z53v/Z/T5+zbkMCLox7xfmDl5O327+j+9x7m13krWPn5Uq/FUx5NOsTSd8wg8nPyOLo3udTYR9liD3WJvfhzRk0cw/evfsXO1fH21+985UG6j+jt9FmzHnmLpR/94IVoyi4gKJDL/3UT+SdyqRoWwuJnZrtt+80GdKTFwE4YP8PulfHEf7+mxOd0GzeInPQsjicd5sD6BJoN6MjN7//DqdzBDYm8dfW/vRpTeQQEBTLMoe+bf459X3tb3/epQ9/nF+DP0H/exMm8fEJqhrLrl0329/kKb477AMFhIVx61wiCqgcz99/vVUhMIufigjnj4vop40lau515z81m86K13Dh1QokykTF1GTFxDF889h6fPfoO/W4bSt0WDc+6rO3ALtRqGMUPr3zJohlfExYdQecRvQBo1qM179w9jemjH2H66EeY9/wcNi/+reICt7nY4weoFhbCrS/8jS+nfMAXT75PbPdWtO7X0W3ZofddS3ZGNt88+wmL35zL+FcfLNOyoJCqVK1RjWaXtAFj3H527xsH0qBtjGeDOw81wqvzzxcn8caTb/L642/S7pK2dO3f1W3Z4JBgQmqE0L5HOwyn4/Pz86Pv0L48fMsjTB77L3oMuoRB1wyqqBC86lhKKtk5OWyO31HZVfGIkVP+zN61O1j03By2LVrL1VPvKFGmVkwdLp94A/Mee59vH51Jr9uuIKpFA/vybmMG8sXE13l33FTeHTeVbYuK9umOo/vy68c/Mq3/g6QfPs6Ix26rqLDKLCSsOne8cB+fTvmAOU++R/PurWl7hn5gxH3XkZ2RzZfPfswPb37L3a8+BECV4CAG3jqU9//vNd79+yu07deJa/8x7qzLKtvoKX9mz9rtLHhuDlsX/ca1U8eXKFM7pg5XTryRbx97n68ffZc+t11JtG3bdx7dl9UfL+G//R8g7fBxrn7sVvv7Wg/sTM2GUfz4ylf8NOMbQqMj6DiiZ4XFVhbXTrmD3Wt38P1zs9m6aC3Xu4k/MqYuwybeyFePvccXj77LpbddSR1b/APvvprNC9cw46YnyUhO5c9vTqRKcBAAsT1a897d03lp9CO8NPoRvn9+Dlsqaawrjbfbv6NLbxxEo7ZNvBlOuVQLq86fX7iXz6Z8wKdPvk+z7q1Kif1acjKy+OrZj1n45rfc5TLOB9eoRvNL2uAwDFItNIS87FyeG/Mfnh79L54e/S8SftvBxiWV3w6GT7mdfb/uZMlzn7Jj0W+MmPrnEmVqxdRh0KTrmf+fD/jukffo4dLvVw2txvWv3suORb+x8YtfOGBL2jXp0Yo5d7/I26P+w9uj/sOPz3/GjsXrKiy2siju+xY+N4f4Rb9xzRn6visc+r7eLn1f3MdLeNbW94106PsG3TuarNRMFj7/KV8/+i4D77vG/j5f4c1xH6Bm42iimjegSrWgConnD6PQ+mM+fNgFkbgIjYqg28g+9oOIHcs3025wV2o2iHQqd9n44WxbtgHLKlrp23/eyGUTRpx1WXSz+gRVD7Z/TkFuPsG2jOTyD39g44I17Fm/iz3rd1G7cTSbFqymIl3s8RfrO3Yw+7fsJi87D4DNi3/jir9cXaKcf6A/g8aPYOPCokzzkcSD1KgVRvMerUtdBpCXlcuOFZs5cTzDbR1qN4qmRq1QkhMPeiPEczJs7DB2bUkgN7vo17K4Rau58Z4b3JbNycph/fL1pB9Pd15gYParc0g7ns72DTtYv2IDhYWnvF31ClG7ZgQDL+1V2dXwiBpR4XQc2ZvttoPKxOVbaD24C+ENajuV6zt+GDuXbbLv7wk/b6LvhOEA+FcJoPml7UnecYDEFVtIXLEFyzZQbZkXx4GNiWSnZLJm1hKswsIKjK5s+o0dzL4tSeTZ2vvGxWsZ+pfRJcr5BwYwZPxVrF9Y1F8dtu3rLXq0ITqmLh89/CZJ63ayYdGvfPvip7Ts1Q6g1GWVKTQqgs4j+xBv2/YJyzfTZnAXIly2fb/xw9mxbKN92+/8eRP9bNt+07w49m9MJCslk7hZi+3bHSCqWX2Cqle1Py/Izbf/MucLQqMi6DKyD1tt4+DO5ZtpO7grES7jYP/xw9juEP+OnzcywDbW7Vy+mfXfruTAlt18dP//qBZenejm9QFY8eEPbFqwhr3rE9i7PoHajaPZvMC3fnUF77f/YpGNoqleK5QjiYe8H1QZFcW+2x77psVrufIvo0qU8w8M4PLxV7HeZZxv0aMNUDTOb1uxmUyXcb5KcBAf/N8b7IyLJ2n9LvbH7+VUwUlSDx/3cmSlqxEVTvure7PTtu8nLd9Cy8tL9vu9xg8jYalzv99rwjD78utn3MeqdxaQuv+o0/t+/XAx2+b/yoH1CRxYn0BEoyi2LfjVy1GVXY2oCDqN7MO2s/R9l56l7ztg6/tWu/R93a4fwJFt+wAoPFXIjqUb6HfniIoIrUy8Pe4DHNyUxOF43zu7UsRVmRMXxpibvVmR0jTv2YYTqZkU5OYDRR3L8f1HaWb7Y7NYi15tOb7/d/vz35MO0bxnm7Mu27pkHe0Hd6XT0B4Eh4YQUrMGv375MwCph04PWMbPEBVTlyMJFftH68Uef7GWvdo5xZCcdIiYLi3xC/B3Kte4fSzBNapx/IBz2eY925a6zJFllfyDzRjDZbcPY9GbZ74MozJ06tORI/uP2J/vTzpAm66t8XdZL44KXTKqhacKOVlwEiiKsyAvn5++XuqV+lYGP78LIkd7VjE925Dt0hek7j9KjEtf0LRXW1Id9pWjSYeJ6VlUptXAzjToFMtDS6dzy7uTqBZRw16u+HMBasfW44dn53gznHPSqld7jjnEdiTpELFdWpZo701s+/qxA0edyrbs2Zb98XvISj9hfz0tOYWUQ8cASl1WmZr2bE2Wy7ZP2X+UprY/xorF9mpLisMfJkeTDhFr6+sdt29UbD3mPzvb/nzbknW0GdyV9kMvsY8Dv335izdDKpdmPdu4jT/Wpe0369WOFKex7rA9/oRVW+2v52bmkHsih7TDRZcPpLmMdZExdUmupLGuNN5u/1A0Bgy+fTg/vPmtFyMpv1a92pUx9qYlYk9OOkTLns77ius4n5ac4pSsbdu/I1t/3uDJEM5Jk14l+/20/Udp7NL2Y3q3cUpKHE86TJNeRWVaDOpMrSZ1qNuuCePem8Tlk2/CP7BovaW7tP1aTetydJfvtP3YM/R9MW76Psf4jyUdoqmbvi8yth4LHPq+qtWDCatb0/487eAx6rRs6JVYzoW3x/1ixQkPEV9WnqP5e40x7xhjbjXGVOjPMGF1apKVmun0Wl5WDmHRNd2UOz0Y52blEhYVcdZlyYkHef++lxk37R5uffleZk18jYK8ktf2N+vRhsQ17uc88KaLPf5iYXVqcsJhPeRm5RAYFEh1lw44rE5NcjKzOVVwyqFsLmHREaUuO5sBt13JLx/9QOFJ3zoToVZ0bTId1kvOiRyqBFUhrGZYuT+raZum/OetR4mIjCDEh35tlSKhdWqS7bAfQ9GvhzVc2m9onQincnlZuYTa9vetC37lyfbjeeuGJwhvEMnNb/8d43BZVHB4dfreOYKet1zuU7+4FwsvYz8Qbt/XTzqVDXezr8d0as7SD91fK1/asooU5nbb5xDqEk9YnQiyHdaP47YHqBZenf53jqD3LUPsZ9YB/J54iI/v+x83TvsLN738Nz6d+Don3YwDlSWsTsQZxsGS8Wc5xZ9jH+scRcbUJTEunsyjaSWWxfZoTVIljnWlqYj2P/C2oSz9aCGnfGysi3A5FsrNyi1X7K7HTGfTecglrPOBs25q1Ikgpwz9fo06EeSkObT9EznUsLX99lf3Zv+6XayeuZAvH3iNdlf1ZOCkkmdmNu7Rmr2rt3shinPnftxz3/dlnaXv62fr+xzHtp0/b6Lnny6nSrUg/Pz9qN8uBuNDP3ZUxLgvcqEoz545zLKsO4AE4CljzAvGmL5eqpczy6IgL9/ppYAqgU6DUlE5nMoFVAk4PfCWtgzwD/Dn7Tufp3bjOtz+ygMlfsUHaD+km/0Sgwp1scdfzGU9BFYJBCh5cGVZTtn1orIBRcmK0paVon6rRhTkFXDEhy4ROc0iLzfP/qx4vZx0bR9lcPTQUZZ89RN1G9Vl4vS/e6yG4iFu+4IACl3ar2XByVL2d4A9a7bzztgpRMbWo0HnZvbX87Ny2B0Xz8FNSYx740GnX6J8wnn1A4El9vXg0GpE1Knl9jr20pZVNKuM44BVoq8PdFo3eVk5JMbFs39TEre88ZDT9vUP8Of9O6dTu3E04165z+04UFmK4nJOpAS42Z64lHONv1ifW4bw7dRZbr+r3ZDubF7oO6fKO/Fy+2/QqjEFeQUc9sGxzrIs8l36NSgZu2VRIna3baUUfv5+RDaKJjnJBy6VcbMtA6oEUHjSzTFgrnPbL/6hJapFA/b/tpPCk6fISTvBb7N/osOoPiW+qtWQrmz3tbZ/hr6v0E3f5zju+bvp+5Li4jng0vd9+fDbHNiQyC1v/p0Bf7mahh2b8bsvnW1VAeO+nBvLsv6QD19W5sSFZVnHbf+uAGYC9YGlxphPjTGTjTGRZ3qvMeZOY8xaY8zaLZmJ5a5kWnIK1UJDnF4LCqnqdCcIgLQjzuWqhgSTbptFurRlzXq0plHHWHYs38zLNz5O/TaNGTh+eIl6NGofy76N5a//+bpY479k9KW8tOMj++NESgbVQqvblweFBJOfm092unMmOi05heAS6yuY9OTUUpeV5rLbhzFy0k08u+5tnl33NrFdW3LDY3/mhsduP88oy2/QNYOYt+tb+yPteDrVw06vl+DqweTl5nHCZb2URWZaJr989wvP/306HXp28GS1xQMy3LTfKiHBZLi034wjKVR1KBcUEkymmzaedSyDzfPiCK9Xy/7aqYJTHNyUxOy/vUz6kRQadm7u4SjKp+fofry242P7I9OlH6gaUpX83Dyy0rOc3pfqZl1VDalKmst6GDJ+JHOenOn2u0tbVtEyklPd9F1V3W77YKdt71zmVMEpDmxKYtbfXiL9SAqNbNu3aY/WNOgYy67lm3n9xiep16YJ/cYPw1eku+27S8af7jLWuRsrm/dpR2JcvNMlJY4atm9aKWO9OxXd/gfdPoxrJo3lhXXv8sK6d4nt2pKxj93BTY+VnAzS23qO7seMHbPsj8yUDEJcjmPyc/NLxO5unHc85imLFpe0cbrbSGXKOJJKcFjJfj8zOc2lXIpTuSrVq9r7fb8Af/z8Tycik7ftL/GZAPU6NOXgxiRPVv+8pXu578tJz+KLyW/x9s1TWTPnR6Ka1WP9V8u9GFH5VMS4L3KhKPPtUI0xtwPHgHuBHsD7QEvLshKNMQ2BacaYOZZlfef6Xsuy3gTeBLivyY3lTuXsWrWVsKfvIjAokIK8AvwC/KlZrzYJLoPKjuWbiIqtZ38e2bQuu+Liz7qs07CeHNqxH4CM31P5btocOg3rCa+fvr6zYbsY9m/ZXd6qe8TFGv+mxWvZO+z0wWP7QV2p17KR/XlU07okrIl3mmAIYN/moonLajWI5LjtGteomLrMe2FOqctK88VTHzLvhdO3Bhw/4yHWfbeKVZ8tPd8wy23VolXs3Hj6Dhk9B/ekScvG9ucNmtZn8+otFJ7HxIo7N+3k2JHKv65fnCWtimfU0xEEBAVy0tYXhNerxR6X2/YmLt9CZGxd+/PaTeuQFOf+INw6Veh2Ui6r0OLw1j1kHCn7wb43bFy8lseHTbQ/7zioG/Ud+oHopvXYuWZbiYlE99r29doNojhmm9MmOqYeXzvs6/1uGsyab34hK61kkq+0ZZUhYdVWrn16gsu2r02Sy7bfuXwzkQ59fe2mdUmM2+r6cViFFgcdtm/7YT044jAOLJz2KR2G9WDp674xp0/Cqq3c8PSdTuNgRL3aJLqMg0Xxn277kS7xR8XWo1ajaOI+WeL2exq0i+FAJY317lR0+//sqQ/41qHM3TP+ztrvVrHis588HtvZbFy8lieGJdifdxjUjfoOcw9EN63LrjXxZYy9Lt+cZZx31PmKS1jhI7eA3bMqnhrPjHfa98Pq1WJPnPO+n7R8C7Wanm77tWLqsntV0f6RvG2f07LCU6c46jLxat12TTjsQ22/WGIZ+75dLn1fZNO6JJ2h7zt0hrFt0L3XkLBiCzuWVv7cJsUqctwX8XXluVTkHeAVYBHQyLKs+yzLSgSwLGs/8CO25ISnZR5NZ8uP62jRpz0ALfu2Z8OC1aQnpzJwwgiibJ3xilmLnW6P2aJXW5bNnH/WZQfj99LA4ZZfhacKS/za0n5IdzZV0mUSF2v8uZk5JCcesj/ivlhGk07N7Kcvt+3fiSVvzQMgNDKc4Q9eDxRl1VfMXkK7gV0AqNOsPmlHjrN73a5SlzkzTtf/5WRkkXYkxf44mV9AdvoJcjKyqGjZmdnsTzxgfyz6fBGtOreyT1DWbUA3vnjzCwBqRtXkTw+VnFfXGOe7vfr5+9GyUwv78x6DLuGrd772biAVqPjUN18/Be5sThxNZ8eP64ntU3QHgGZ927F1wRoyklPpO2E4tW19wepZi2nW7/QZM017tWXVzKJr2NsOvYSIhlFA0QSc2WknOJZ0GCg6nbhqaNG1v1VDq+Hn78e+EvtGxcrJzOZI4iH7Y+UXS4np1Nze3tv178QPbxX9cR0WGc7IB4uu2z5VcJJfZi+mvW1fr9usAalHjpO0bicAfW8YSG5WLvl5+dRuEEWny7vTrFursy6rLCeOprPtx3U0t2375n3bsdm27ftNGE6kbdvHzVpMC4dt36xXW1bMXAhAtJvtu9e2fQ/H76W+yziw30fOOoCicTD+x3U0t42DLfq2Z9OCNaQnpzJgwgh7/CtnLaKVw1jXvFc7fra1/ZoNo+g1djA7ftlERINI6rVuRO+bL3f6nqLLRCp/XoNiFd3+szOySD2SYn+czD9JVvoJsithrHONfVWJ2DuXEvuSM8ZezLiM844atmnCvi2+cebBiaPp7Fyynqa2fb9p33ZsW/Armcmp9L5zmD0hsfajJU79fkzvNqy27ftxMxfQfEBH/G2X1zTs2ty+rFirK7qxbcHaigipXE4cTWf7j+todoa+r/YZ+r7YUvo+49D3FWs/9BIatI9hzkMzKiKsMvP2uF/MGJwPDEV8kCnrgbwx5j3gTsuy8s+wfBAw2LKsyaV9zrmccQEQHBrC1ZPHkXLgKDUiw5n77MfkZ+cxae7TLJrxNRvmF93yq9uovjRsFwNAwuptbF50uhM+0zJjDEMfuK7olMOUTMLr1WLRq19xMv/09XP3zv43r4x9ssSv+xXljxD/Sc5/3bXq256OQy4hJzOb4wd+Z4XtV7OYLs25/aX7eXLwgxTkFRAQFMg1k28m41g64XVq8v1Ln5Nhm4SttGV+/n50Gd6LPz13D6s++4kfXvualIMlzzx4YPZ/iPt8KXGfLytz3RNOub/Fqid0ubQzva/oTVZmFsn7k/n+46KkVOsurZn8v38yftCd5Ofm4+fvR78R/Zg47SEWfvoDc179lN8P/k5kvUhe/Go66SnprF+xgUO7D/HdrO89Wsfv1lfOwUBWVjZzf/iRKc+/yt23j2XstVdRMyK8wuvxWLdHPPI5VUNDuHLyTaQdOEr1yHB+eHY2+dl53DP3KZbN+Iat84v+6Oo4qg/1bPv7ntXb7Pdsv+rx2+g4ug9JK7eyO24bce//YE/oXP/iX2nWtx3bFv3GiWPprJy5gOyUTPcVKYdk3A4b56xN3w50cugHfv5kMQBNu7Rgwkv38+/BD1KQl09AUCDXT/4TGcfSiahTk7kvfUb60TR6XdOf25//q9PdZrIzsniw6x1cclWfMy4rMa9QGdUk8PwCtgkODWHY5LGk2saB+c9+Qn52HvfNfYqfZnzDZtu27zyqL/XbNQEgafU24m3b/qYX/0rzvu3Zatu+y2fOJ8u2fY0xXP7AtUWX36VkElavFj+++jWn8s8tZkee6PuhKP6rJo+1j4Pf2eJ/cO5Ulsz4hk22cbDrqL7Ut7X9xNXxbF30GzUiw3ng6ylE1He+heAHf3uJDfNW2Z/fM/vfvObhsT6D81+HjrzZ/l3b+KTZj7Pi859YeY5nHxg8+4dQ674d6DykOzmZ2Rw7cJRfzhp7GuF1ajHPFjsUjfPdhvfituf+yorPfmL+a185jfON2zel5+h+zHnivfOub32rynl/BhT9sX35v8ba+v0wlvx3DvnZedw5bwrLZ3xL/PdF+36H0X2oa9v398RtZ8ei0/PzdBjdh0bdW3I86TABVavwyyvfOH3HbbMf5v2xUz3a9nOMZ26pXdz3Fe/7C2z7/r1zn2JpGfq+Mba+L37Rb2QeS2eFQ98X26st9dvHEFAlkJ/fmufRSYkDPNT+vTnuA9RvH8PQR24mpFYo3zz8Dns8NEHrU3s+/kNnQjLuuuLC/jXsDELfWOiz2608iYsAy7JOurzWBGhvWVaZzyU918SFXPg8dfB6ofJm4uJCUFmJC1/hqcTFhcjTiYsLjacSFxeqi73v93Ti4kLi6cTFhcZTiYsLlacSFxcqTyUuLlR/+MTFhCF/yMEt9K0ffHa7lXmOC6CvMeZBoDrY98RgIAao4+mKiYiIiIiIiIiUJ3HxBPAt0AaIA/KAPsCzXqiXiIiIiIiIiEi5Jueca1nW88C/qAjeGwAAIABJREFUgBOWZb0P3A/c4pWaiYiIiIiIiMhFrzxnXLQ2xjxC0d1FWhhjbgUigQHeqJiIiIiIiIiIz6mkGzZczMpzxsXDQBgQAvwXGEjR2RaTvFAvEREREREREZGyn3FhWdZhnJMUtxpj/IFOHq+ViIiIiIiIiAilJC6MMa8BQWd5fyRwChjlyUqJiIiIiIiIiEDpZ1wUUpS4SLD9fyRwCFjrUMYPLvIbtIuIiIiIiMhFw9IcFxWutMTFFKDAsqxjAMaY6pZllZjPwhjzibcqJyIiIiIiIiIXtzMmLmxzWjiq4lrGGNMGuMzTlRIRERERERERgfLdDnWNMWYZMB/IBFoDfwJmeqNiIiIiIiIiIiLluavILGNMPPB3oAOQAfwbeMVLdRMRERERERHxLZrjosKVOXFhjIm2LGs9cLPL612B3zxdMRERERERERERv3KUHef6gjEmAnjJc9URERERERERETmtPImLfxpjuhc/McZcCmwAeni8ViIiIiIiIiIilC9x0R0Yaoy5zBjzNLAAeBlo7pWaiYiIiIiIiMhFrzyTc+4DnjDGPANcCfSwLGuLMWYosMdL9RMRERERERHxHYWVXYGLzxkTF8aYX4Fa7hYBgcC3xhgDRAPVvFM9EREREREREbmYlXbGxdfAIYrOpjhTTskPuMnDdRIRERERERERAUpPXLwIFFiWlV/8gjHGD6htWdbvxphwy7LSjDGbvF5LEREREREREbkonXFyTsuyslySFpcC+4H3bC/VNsb8D6ju1RqKiIiIiIiI+Air0PpDPnxZee4qMg14DFgDYFlWAvAN8IHnqyUiIiIiIiIiUr7ExU+WZb0FpDq81hDo4NkqiYiIiIiIiIgUKU/iIsMY0xCwAIwxI4DngIXeqJiIiIiIiIiISGmTc7p6kaJExTXGmGcAf+Az4G/eqJiIiIiIiIiIz/Hx+SD+iMqcuLAsKwu4B7jHGBMFHLMs60y3SRUREREREREROW9lvlTEGFPPGDPHGDPTsqzfgW7GmIeMMUFerJ+IiIiIiIiIXMTKM8fFB8BJIAPAsqw1wAHgDS/US0RERERERESkXHNc7LYsa4Ix5n6H17KBqz1cJxERERERERHfpAkTKlx5zrg4ZIwxnL6rSDTwBLDNGxUTERERERERESnPGRfvA58DjY0xw4C+QDLwJ29UTERERERERESkPImLh4GbgY5AI+ApIM6yrAJvVExEREREREREpDyJiwJgou09yyzL+sU7VRIRERERERERKVLmxIVlWXcX/98Y098Y8xxF813MsixrY1k/x2DKV8M/mFxOVXYVKk1guaZU+eNJyEmu7CpUqse6PVLZVahUj62dUtlVqDT/6Pavyq5CpapykY97F3v8+fhXdhUqTRYnK7sKleq1tN8quwqVakqNbpVdhUqVFKDZG//IrEKrsqtw0Slz4sIY096yrM3GmEHArcBoYBdwCChz4uJidjEnLURERERERETORXkuFZlrjPEHwoH/AT0sy4r3TrVERERERERERMp3O9R9wDjgGuAU0MMYU9UrtRIRERERERERoXxnXNxqWdZuAGPML8D9wF5jzEzLsv7PK7UTERERERER8SWawqTClSdx0dsY0xG4ERgOxANTgdneqJiIiIiIiIiISHkSFx8CO4BPgEcty0rwTpVERERERERERIqUJ3HxmGVZT3itJiIiIiIiIiIiLsqcuFDSQkRERERERC52VqFV2VW46JTnriIiIiIiIiIiIhVKiQsRERERERER8VlKXIiIiIiIiIiIzyrP5JwiIiIiIiIiF7fCyq7AxUdnXIiIiIiIiIiIz1LiQkRERERERER8lhIXIiIiIiIiIuKzlLgQEREREREREZ+lyTlFREREREREysjS5JwVTmdciIiIiIiIiIjPUuJCRERERERERHyWEhciIiIiIiIi4rM0x4WIiIiIiIhIWWmOiwqnMy5ERERERERExGcpcSEiIiIiIiIiPkuJCxERERERERHxWZrjQkRERERERKSMLM1xUeF0xoWIiIiIiIiI+CwlLkRERERERETEZylxISIiIiIiIiI+S3NciIiIiIiIiJSV5riocDrjQkRERERERER8lhIXIiIiIiIiIuKzlLgQEREREREREZ+lxIWIiIiIiIiI+KwLdnLOwKBARk4eR15WLsFhIXz7zMfkncgpUa71gE60uawzfn6GnSu3snH+avuyamEhDLzrKqpWD+bzf890+z2dR/Siz82X88qYJ7wWi6c07hBL3zGDyM/J4+jeZJZ+sMBtOWMMV0+6CYAatcKYO30OackpTp9z9cQxzH/1K3atjq+QursKDApk1OSbyc3KoVpYCN888zG5brZvmwGdaHtZZ4yfHztXbmGDw/Y9l2VtBnTinvcmO33Hng0JPD/qYQCG3DMK4+eHVVhIleAg5k2b443wy61D5zbccPNocnNy2bv7AB++475e3Xt25snnH6ZuvSgWL1jGv//xNFknsp3KxDaPYfCV/dm7ez8b123h8KHkigihzAKCArly8lj7vr/wmU/c7vstBnSk5WWdMX6GxJVb2Tp/jX1Z1dBqTFrxMlVrVANg1l3TiV+4Fj9/P66eegfthvUg7cAxPp/4Goe37q2w2Lxl5Zp1/O+tD3j+icnUrxtd2dXxmMCgQK6aPI7crFyqhYUw9wzjQCvbOGD8DAkO40DVGsHc+MxdtOrXgWP7kvn8kXfYuz6hosMos4CgQK6YPJb8rFyqhoXwwxnafnOHtp/kpu1PdGn72xauBaD/PVdj/AxWoUVgcBUWT/usYgIrI2/G33xAR259759On3NgQyKvj3rUu0GVwtvjYHBoNZ5Y8SrBtnXx5l3Ps2nhr2ddVpliOsTSb8xg8mzHOUs+mO+2nDGGayeNBYqOc76aPtt+nFO/RUPGT7uX6CZ12bD4V9795wxO5p8s8RkPvvcwa+atZMXnP3kvIA/q1KUd4265npzsHPbs3s+7b81yW65V6+a8/PozNG3amIXzf+TBvz1Mfn5BBdf2/PhXDaTHwzeRfyKXoLBqrJk6hwI3+0ZQeAgd7h5OYPVgVj7yvtOyKqHVuGn1S1SpEQzAovEvsmfB2gqpf3kFBAUy1OG4Z0Epxz2tHI57tjj0fcXaj+hJz5sH89aYKSW+o8e4QeSkZ3E06TD7fXgs9BWWJuescBds4uL6KXewbdlG1s9bRav+Hblx6ng+uO9/TmUiY+oyfOKNTLvqX1iWxb1z/sPviQc5vPMAALUbR1OneQOy07PcfkdoVARD/jqKrDMs9yXVwqrz5xfuZepV/0dedi7j//cAv+85TPzPG0uUHX7fteRkZLHw9W+oE1ufCa8+yHPXFR2cBYVUJbhGNZpf0oYFM76q6DDsbpwynvhlG1g3bxWt+3dkzNQJvHffy05lomLqctXEMTx71WQsy+KBOY+RnHiIwzv3n/OyZj1a8/bd00hLTgWgZZ/29u9rN7ALtRpG8cnkNwEY9+zddBnRi3XzVlXcinEjLDyUaTOmcPXgcWRn5fDSW8+wJ2kfv/zkXK/galW5ZfwYJj/wBLUiazJ1+qNMeuReHvu//9rL9BvYmytGDOTRiVMpLPTNHnnklD+za9lGNs+Lo3n/Dlw99Q4+ve8VpzK1Yupw+cQbmHHVI1iWxfg5j3I08RC/2/b9bmMG8sXE18k7kQtA0qqtAHQc3ZdfP/6Rhf+dzXXP382Ix27jresfr9gAPexYSirZOTlsjt9R2VXxuGun3MH2ZRvZYBsHbpg6ng/PMA5Mt40Df5vzH5ITD3Jk5wEG3n01mxauYclr3zD0oeu5482JTOl3P/k5eZUUUelGTvkzO5dtZEsZ2v5rZ2n7+S5tv+XAzkQ0jOTryW8DMPrZO2k3oidb5sVVYISl82b8MT1a8/HdL5Bh6/ub9WlXgZG5581xEKD3mEF8OHGGvR/cuWqL/XNLW1ZZQsKqM+GF+3n8qn+Ql53L3f97kOQ9h9ny84YSZUfedx3ZGVl8//rX1I2tzz2v/p2p1z2M8fOj29CeTL9tCpENo/n7B4/Se3R/fp6zxOn9/W4cROO2MayZt7Kiwjsv4RFhvPLGswwZcB3ZWdm88e40kpL2snTJcqdyfn5+DB85hLHXTqBR4wbM/vJtrh9zNbM++LySan5u+jx1OweWbiRp7moaDOhA32f+zE9/e7VEuRqNo4lo0YC8tBMllrUaexnLHnyDfFsC4PDKyvmhriyutvV9m+fF0aJ/B0ZPvYPZLn1f7Zg6DJl4A6/a+r47bX1fsq3vA6gRFc5lfx1FTrrz+qgaGsL10+5m3hMfkrr/9wqJSeRclPlSEWPMzd6sSHmERkXQdWQftiz+DYCdyzfTbnBXajaIdCp32fhhbF+2EcuyANj+80YumzDCvnzfpiQOxp/519TBfxnJilmLvRCB5106djD7tuwmL7voIGPT4rVc+ZdRJcr5BwYwePxVrF9YlIU9kniQGrXCaN6jDQB5WblsX7GZE8czKq7yLsJs23ezbfvuWL6Z9m6278Dxw4lftsG+fbf9vJFBtu17rst++fAHNixYw571u9izfheRjaPZuKDoF6roZvWpWj3Y/v0Fufn2X6Mq0023XMvWTdvJzioafH9cuIy777+9RLkmTRvxyMSnWL92E4vnL+XlZ1+nZ9/u9uUxzRrz94f/yuP/91+fTVrUiAqn48jebF+8DoDE5VtoPbgL4Q1qO5XrO34YO5dtsm/jhJ830XfCcAD8qwTQ/NL2JO84QOKKLSSu2IJVWFRuy7w4DmxMJDslkzWzlmD56Hooj9o1Ixh4aa/KrobHFY8DWx3GgbaDuxLh0k8MGD+MbS7jwADb/r5z+WbWf7uSA1t28+H9/6NaeHWim9ev2EDKqEZUOB1G9maHQ9tv5abt9xk/jF0ObX+XS9tvdml7fnfT9iOb1aeKS/9W1Qf6t2Lejn/1h4uIX/ArB9YncGB9AjUbR7N1QeWdYeDtcTCgSgCtL+3A4R372bFiMztWbLavi9KWVab+Yy9n75Yk+3HOhsVrGfaX0SXK+QcGcMX4kfy2sGjsPpx4kNBaYbTs0QZjYN6Mr8g8nkHShl3Er9hcYryLbBRNjVqhHE486P2gPORPt93A5o3xZGcVnUH5w/yfuO+BCSXKGWN4efqbHDuWwrrfNvHLz3GcOnVhjXPVosNpNqoXexetB+DgL1toPKQz1V36AoBjG5M47uY4369KAPX7tSNlx34OLd/KoeVbfaKNu1MjKpxODsc9CWU87tnp0PcV6/+Xkaxx83fN2FfvY8W785W0EJ9Xnjku7jXGvGOMudUYU6lHM817tuFEaiYFufkAFJ4qJGX/UWJ7tHYu16sdxx12wt+TDtOsZxunMsU7uKueN1zGb9+sIN/2Hb6uVa92HHOINTnpEE27tMQvwN+pXOP2TQmuUY3jB446lW3psl4KK/H8p+Y925Dlsn2P7z9Kc5ft26JXW6ftm5x0yL59z3VZ6qHj9teNnyEypi5HEooOXrYsWUf7wV3pNLQHwaEhhNSswZovf/Zk6Oek16Xd2b/39AFWUsJeunTvSECA8wlV27bsJD3tdELqyJGjHDpwxP580sP3krRrDw9OvocPv3idwUMHeL3u5RXTsw3ZLm0jdf9RYlzaRtNebZ0G4KNJh4npWVSm1cDONOgUy0NLp3PLu5OoFlHDXq7AYX+vHVuPH571jUuBzpef3x9vOqNmZxgHmrm0hWa92pHi0haK9/cE26/tALmZOeSeyCH9cAq+6Fzb/jGHtt/S1vYfXDqdP7m0/R1L1tFqcBfaDr2Eqrb+bcOXv1RAZGXj7fjTXfr+WjF1OJpQeX+4enscbDewC407NeM/S1/i7nf/SYjDuihtWWVq3asdRx3iOZJ0iGZdWuLvcpwT0z6W4BrVOOZwnHM46SCteral8FQhpwqKLgsxxlCQl0/cN6fbuTGGy28fzoI3v/VyNJ7Vt19P9u09/ct6QsIeuvXoXOI44NSpUxQUFF0WYowhLzePLz+bW6F1PV91e7UmNzWTU7Z9wzpVSOa+o9Tt2dpteXcJiUaDOxPVuRk3/jKNK96fSFBEda/W+Xw0ddMXpOw/SlOXviDWTd/X1GGddLthABvd/F3TalAXasfUoV7bJtw28x9c+X834R/ovE+J+IryHM0OsyzrDiABeMoY84Ixpq+X6lWqsDoRZKdmOr2Wm5VDWHREiXJZDuXysnIIi3Iu406tRtFUCw9h74YL5/qu8Do1nWLNzcolMCiQ6i4HHOF1apKTmW0fuIvK5hAWXbPC6no2YS6xgG3budSxqNwJhzK59u17rsscNevRhsQ12+zPkxMPMvO+l/nTtHu47eV7+WjiaxTkVf51odF1o0hLTbc/P3Eii6CgKkTUCi/1fZ26tOOjmZ8CEFK9GpcNuZS5Xy7gv4+/xMfvf85r7z1Py9bNvFr38gqtU5PsVOdTHPOycqnhsu+H1olwKpeXlUuobRtvXfArT7Yfz1s3PEF4g0hufvvvGGPsZYPDq9P3zhH0vOVyn/rFWZy5GwfysnIIPcs4kHuGcSAypi4JcfFkHE3zToXP0/m0/Rq2eOMX/MqU9uN5203bP5p4iE/ve4Vrp93NDS//lS8nvsFJH+jfink7fkdNerRmz5rtXoii7Lw9Dm5YsIZJ7W/nhRseo1aDSO56e5J9XZS2rDJF1KnFCZd9uezHObmEO6y7hm2a8Lc3/kFYZLjTmZODbxvGTx8t5NTJU16MxPPq1I0iJeV033Uis+g4oGYt98e8bdu3YuZH/yMqujahob6RmCqrkDo1yXXpCwqycqkWXfoxj6M93//K+60nMPfaJ6nRoDZXzHwIfKCNu+Ou78sv53FPzUZRBIdXZ/+GxBKf3+nq3uxbt4uV7y3k0wdn0PGqXgyZeKMXIvnjsQr/mA9fVubEhWVZx23/rgBmAvWBpcaYT40xk40xkaV+gAdZFuS7HFAFVAnkVIHLQGPh9IdlQJXAsw5GxhguvWUIS9/53mP1rQiWZZGfdzqLGlClKMteIl7L+VdlgEB3664yWRYFec51LNq+LpNnWTiVC6gSQGFxvOe6zEGHId3YuNB5YiP/AH/euvN5IhvX4c+vPFDijJbKYFkWubmnr8kPqlIFgJOu68tBjdDq1KkXzY8Li84YadK0EUFBVYhbUTQx1fxvF3Ng3yGuuuZKL9b8HLhtGwEUurRfy4KTLtvYdV/Ys2Y774ydQmRsPRp0Pp2gyc/KYXdcPAc3JTHujQcJq+s7ST05zXLp3+H8xoG+twxh7lT3k9n5AusMbd81XstN/+au7b87dgq1Xdq+f4A/s+6cTs3Gdbjxlft8on8rVhHxF2s9pBvxCyt5kj5vj4M2iWu28fLYJ4mOrU8Tl3VR2rLK4NoGAqoEAu6Oc6wSvyoHurSVlEPHWPX1z0Q2imb88/cC0KBVYwry8i+oS0TsLIvc3Fz706CgonVzssB98vHQgSN88dlcGjdpyEuvPV0hVfQUy7LsZ1sU868S6PY47myOrN7BdzdOJaxZPaI6x3qqip5lWU7HM1B02Zu74x53fZ8xhl63DGHFGf6uiWregL1rd1J48hTZaSf4dfZPdBrVx/NxiHhAeea4uN0Yc5Ux5gfgF+AI0NKyrBuAj4BpxpjhZ3jvncaYtcaYtVsyS2b7yis9OYVqoSFOr1UNqWqfVKtY2hHnckEhVUl3KeMqpltLet80iCd/fZ2n1r3JtY/dRtOuLXhq3ZvnXW9P6jG6H6/smGV/nEjJIMQh1qohweTn5peYeDQtOYVgl3UXFBJMerLvnB6d5mb7utt2Jbfv6TjOdZmjRu1j2bvxdHtt1qM1jTvGsn35Zl668XEatGnMwPFum7xXjbp+ONsOxNkfKcdTCQs7/YtJSPVq5ObkOl0W4mr8Pbcw5ZHn7c/9/f2d/gXYHr+L8JphXojg3GW4ab9VQoJL7PsZR1Ko6rKNM93s+1nHMtg8L47werXsr50qOMXBTUnM/tvLpB9JoWHn5h6OQjwh3W1fVnIcSC/DONCiTzsS4uKdTqv3NZlnaPuu7TrjiHO5s7X9MFvbb9KjFfU7NiVx+RbeufEJ6rZpTJ/xw7wQybnxdvyO6reP4eDG8z9WOR/eHgcdZR5LZ928lUTUKzlHQGnLvK3X6P68ueMT+yMzJcMpnqohVcnPzSsxgXqq22PEYFIdYs9KO8Ha71fxzqRXaWmb4+vy24dz7aRxvLxuJi+vm0mzrq0Y99gdjHvsDi9GeW6uu3Eke5M32h/Hj6USHn56vA6pHkJOTi5pZzgOSE1NY+7XC7n/nn/Ru093t2V8VfaRVILCnLdvYPWqZJ/l+P5Mco5lkPRtHNXrl+wLfIG7456gMxz3uOv7GndrQfebBvKvX1/jkXVvMPKxW2nctQWPrHsDAL8AP/wCTv85eHj7PoLDnb9PxFeU564i7wD7gVeA6y3Lsp+bblnWfmPMj8CbFJ2J4cSyrDdty7i/yZjznv1m16qtjHn6TgKDAinIK8AvwJ+IerVJcLl1547lm4mKrWt/HtW0Lrvitrp+nJO9GxN4atBD9uedh/ek0/CezLznxfOttkdtXLyWPcNOX8rScVA36rVsaH8e3bQuu9bEl5hccO/moomtajWI4viBooP06Ji6zH3Bd67l37lqK2OfvqvE9nW9Nev25ZuIiq1nfx7VtC474+LPa1mxhu1iOLBlt9NrnYf15NCOotnY039PZd60OXQe1pPFr1fstbBLFixj+PrT7XjQlf1o0er0r2ExsY1Zs2rdGSfYHHPLNXz7xXyny0sSd+0mP7+Aps2asHFd0ezxp06eImFHkpeiODdJq+IZ9XQEAUGBnLS1jfB6tdizeptTucTlW4h02PdrN61DUpz7GcOtU4UcdjN5l1VocXjrHjKO+E5ST05LWLWVMDfjQGIZxoEEh3EgKrYetRpFs+oT57sK+JqkVfFc7abt73bT9ms7xFuraR12l9L2j9jafrthPUnesQ+AzN/TWDztU9oO68Evr/vG9e/ejr9YvXYxHNqyx+P1Ly9vj4OuCk8VciB+T7mXedOGxb/yb4fjnE6DutHA4TinTtN67FyzrcRxzh7bcU7tBlEcsx/n1OOrF2aX+I49mxJJtfXxc556n68dytwzYyK/freS5Z/53u1QF87/kQ19N9ufDxl6Ga1at7A/j20WQ9zKtWedaHvD+i0cPuy7CVt3Dq2M59Jn78C/aiCncgswAf5Ur1eLw3HnfnmXVVjI8a37PFhLz0lcFc/oMvR9CW6OexLj4tm/MZHpgybaX28/vAcdhvdk1j0vAXBk+35qNz3dTxSePMXRhENejkrk3JRnjosPgOaWZT3nmLRwsN9Wxusyj6az9cd1tLDdqrJl3/ZsXLCG9ORULpswgqimRTvuylmLaNWvo/19zXu14+eZC5w+yxjny9pO5Z8k/UiK/ZGdnsVJ22u+JDczm+TEQ/bHqi+WEtOpuf3U3rb9O7PoraIDztDIcK568AYAThWcZPnsJbQf2AWAus0akHrkOEnrdjp9vsFU2vV+mUfT2fLjOvutSFv1bc/GBatJT05lkMP2XT5rMa0dtm+LXm1ZOnP+eS0r1mFIdza4XCZyIH4vDds2sT8vPFXInkr4VS4z8wRJCXvsjy9nz6VT13b2Sbj6DerN2zM+BCAyujYP/PNu+3tvGDeK7KxscnNzadCoHoOHDqBbj05kncjm04++YujIwUDRZI4xsY356tPvKjy+0pw4ms6OH9cTa7tVYbO+7di6YA0Zyan0nTCc2ra2sXrWYpr162B/X9NebVll2/fbDr2EiIZRQNEEnNlpJziWdBiAqBYNqBpadL1z1dBq+Pn7sW/drgqLz1uKJyE+02TEF6LicaC5rZ9o4TAODJgwgkiHcaClyzjwi60t1GoYRe+xg9n+yyYiGkRSr3Ujet98ecUHUwaubT/W1vYzk1Pp49D218xaTPMytv0ch7Z/OH4PdV36t8o+68CRt+MvVnSZSOXdTaSYt8fBTkN7UMu2LqJt/eDvtnVR2rKKlJOZzZHEg/bHii9+ommnFvbJONv378yCt4p+OAiLDGfUg0XX5Z8qOMmy2YvpOLArAPVsxzmJ63bi5+9HTMfTif6OA7vww7vzAMjOyCL1SIr9cTK/gKz0LLIznM/o8AWZGSdI2LXb/vj046/p0q2D/Thg4OC+vPbKTACioiOZNLnochh/f386dzl9m/fLr+jPm6+9X/EBnIeco+nsW7ye+n3aAlD/0rbsnv8r2UdSaX/XMMKa1nV+g6HE8WzM8O7UaFR0hXtYbF3y0rJIr4Q2XhYnjqaz/cf19ls0N+vbji22455LXY57XPu+lTMXcCr/JBlHUuyPnPQsTuYX2H+UWTlzAS0HdMTfdol5464tWPnewgqO8sJU2XNRXIxzXJiyHsgaYwIsyzrp8loToL1lWWX+ScYTZ1wABIeGMHLyWFIOHCU0Mpy5z35CfnYeE+dOZdGMb9g4v+g2WN1G9aVBuxgAElbHs2XRb/bPaNi+KaMe+RPVa4Xy6cNvk+iSvQS45Lr+XHJdf14Z88R51zkX784j0bpvBzoN6U5OZjbHDxzll0+KbnnUtEsL7njpfh4b/CAFefkEBAVy3eQ/kXEsjfA6tZj30mf2Cen8/P3oOrwXtz73V1Z+9hMLXvuKlIPHPFK/wHLkyYJDQxg1eZx9+37z7MfkZ+fxj7lP88OMr9lg277dR/WloW377lq9jc2LTl+XfK7LAO6f/W9eHvuk02zUxhiGPXAd+bn5nEjJJKJeLX549StO5p95LglH35/YefZC56hv/x5cPuwyMjNOcGD/IWZ/8CUAnbt14MU3pjKkz7UMG3k5z73yuNMdJjLSM+neaiAFBSepElSFx//7f+xJ3Ed4zTB+XPgzv8at91gdb6rufsbv8qoaGsKVk28i7cBRqkeG88Ozs8n3fHUUAAAgAElEQVTPzuOeuU+xbMY3bJ1flHDqOKoP9WzbeM/qbWyz7ftXPX4bHUf3IWnlVnbHbSPu/R/sf9Bf/+Jfada3HdsW/caJY+msnLmA7JRM9xUpp8fWTvHI55RXVlY2c3/4kSnPv8rdt49l7LVXUTOi7JOYecI/uv3LK58bHBrCVQ7jwDzbOPDQ3KkscRgHujqMA4m2cSA0MpwHvp5CRH3nU+Df/9tLbJi3yqP1DCnXbwRnVtz2U21tf5Gt7f9l7lP8fIa2v3v1Nrbb2v4Il7a/2qHtG2MY+MC1FOTmkZWSSVi9Wix79RtOlbF/qwjejL/YHbMf4d2xT3n01ohp5zj2e3McvP7x2+k++lJ2rtzKrrit/Pz+wtP9YCnLyisLz7afNn070GXIJeRkZnPswFGWfbIIgNguLbjrpQd4ePAD9uOcGyffYj/O+falT0k/mkbNerV5+POnyEzNYNuKzSTvOczSjxe5/a5/zn6c5Z8vZcXn537GxfeppZ/l60n9LuvN0OGDyMw4wf59B/nwvaLJt7t178Rr7zzPpZcMp1btmsxd+DEpKan8siyOpMS9fDjTe2fcTqnRzSufWyWsGj0evonM/UepFhXOmqfncDI7j1HfP8nGV79l93dFycfaHWLo+e9xVK1Vg+WTZ3LEdlZG7ym30Gx0Hw6tjOfwqm1snbmoaJIID0sK8MxfgVVDQxhq6/tqRIaz0Nb3/W3uUyyd8Q1bbH1fp1F9qG/b35McjnscdbmuH12v68dbY04fk3Qa1Ycml7TiWOJhAqoGsvTVbzxS76f3fOybM556SPJl/f84vwY5iP5pmc9ut/IkLgYADwLVKcpfAgQDMZZl1SnrF3oqcXEh8nbiwteVJ3HxR+TNxMWFwFOJiwtVZSUufIG3EhcXCk8lLuTCdK6Jiz8CTycuLjQVmbjwRd5KXFwoPJW4uFApcXFh8uXERXnmuHgC+BZoA8QBeUAf4Fkv1EtEREREREREpFyJi7mWZT1vjKkDDLQs62NjzKfAx8BX3qmeiIiIiIiIiA+xfPbEhD+s8py/2toY8whFl4m0MMbcCvwVGOCNiomIiIiIiIiIlCdx8TAQBoQA/wUGArcAk7xQLxERERERERGRsl8qYlnWYZyTFLcaY/yBTh6vlYiIiIiIiIgIpSQujDGvAUFneX8kcAoY5clKiYiIiIiIiIhA6WdcFFKUuEiw/X8kcAhY61DGD/hD3gpGRERERERExJV1cd/ttlKUlriYAhRYlnUMwBhT3bKsEvNZGGM+8VblREREREREROTidsbEhW1OC0dVXMsYY9oAl3m6UiIiIiIiIiIiUI7JOYE1xphlwHwgE2gN/AmY6Y2KiYiIiIiIiIiU564is4wx24CHgA5ABvBv4BUv1U1ERERERETEp1iFprKrcNEpc+LCGNPRsqx1wM0urwcbY1oAWyzLOuXpCoqIiIiIiIjIxcuvHGWfMcaMN8bca4xp5PD6KqAP8KgxppZnqyciIiIiIiIiF7PyzHFxBdAd2A3cb4y5BkgD2gNvAmHAM8AET1dSRERERERERC5O5UlcfAz82bKsfGNMIHAb8AtQaFnWSeC4Maa3F+ooIiIiIiIi4hOswsquwcWnPJeKxFmWlW/7fzgQQdEtUrMBjDEGiPZs9URERERERETkYlaeMy6CjTGbgBygGfAaMB1IM8b0BOoDCZ6vooiIiIiIiIhcrMpzO9TnjDHrgc7AEsuy1hljegDHKZr74hngLu9UU0REREREREQuRuU54wLLshYDix2erzbGtLYs6xPgE09XTkRERERERMSXWJap7CpcdMqcuLDdAnUCUAfwL34ZuARo6/mqiYiIiIiIiMjFrjxnXPwI7ALWAicdXm/k0RqJiIiIiIiIiNiUJ3FxEhhmWZbl+KIxJtazVRIRERERERERKVKe26H+BbjazettPFQXEREREREREREn5Tnj4lkgxhgz3eE1PyAaCPZorURERERERER8kFVY2TW4+JQncTEX2ASkAcWXi/gD13m6UiIiIiIiIiIiUL7ExYvACctyzi8ZY3Z5tkoiIvL/7N13fBTV+sfxz0nvFZLQewep0ps0lSqCotgVUa9d8Xr9Wa6912vHioqCvaOCitKR3luC9ARIQhLSy/z+2LDZTRZIJJtd4Pt+vVaZmTO7z7Nn5szk7MwZERERERGxOWrHhTHmQmChZVm7S2eNsc12ematAYYDE9wWoYiIiIiIiIicto51xcVlQCZwpOPicqAesJ+yW0UMGpxTREREREREThNWiTl+IalWR+24sCxrVLlZT2C7AiPPcaYxpoc7AhMRERERERERqcrjULeX77QoFVJdwYiIiIiIiIiIOKpKx8UV5WcYY5oBr1ZfOCIiIiIiIiIiZaryVJHLjDErLMv6FsAYcwm2Tot8t0QmIiIiIiIi4mUs6/hlpHpV5YqLM4G6xpgrjTGfAC8B1wBt3BKZiIiIiIiIiJz2Kn3FhWVZacAbxpgbgEigvWVZycaYq4D3Kvs+eRRXPcpTRHiVLnA59Ryi0NMheFS/sKaeDsGjUijwdAge9e9u/+fpEDzm6WWPezoEjxrd+UZPhyAe9Hb90/fC1Cf21fZ0CB7VKqyep0PwqM/MQU+H4FEFRUWeDkHklHLUv6SNMTuA+q4Wlf5/jzHGYHs0aqU7LkREREREREREKutYlwA8DWwBtgElRynjg+12EREREREREZFTnlVijl9IqtWxOi7eBEosyyoBMMZ8DMy0LOsbx0LGmNP7GmARERERERERcZujDs5pWVbRkU6LUs2xXX1RXt1qj0pEREREREREvIoxJtgY87Ix5nFjzOvGmIjjlJ9gjJl7op9bldEipwMPGGN+xDauBYAvcDEw7EQDERERERERERGv9hrwk2VZM40x52C7U+NiVwWNMXWBe4G0E/3QqnRcjMR2dUU8ZR0XAG1PNAgRERERERER8V6lHRETgSOPTJsDfGGMaWxZ1t8uVrkbeAO48EQ/uyodF08ASyzLynacaYw560SDEBERERERETkZnMaDcw4EDlqWlQO24SWMMduBAcDfjgWNMdcAHwNtquODK91xYVnWb8aYhsaYO7A9JnUz8KFlWb9XRyAiIiIiIiIi4rXqAanl5mVRbtxLY0wzIMayrCXGmGrpuDjq4JzlGWPOxfZ41POBWKAP8Ksxpm91BCIiIiIiIiIinmGMmWyMWebwmlyuiAXklpsXCBQ6vIcPtltJXqjO2Kpyq8gUoI9lWcsdgvIFngXmV2dQIiIiIiIiIlJzLMuaCkw9RpE9QHS5eeHAXofpPsBk4HJjDNg6NoKMMQcty6r1T2OrSsfFQsdOCwDLsopLOy9ERERERERETnmWdfwyp6jfgbeMMcGWZeUaY/yBhsAfDmWWAq0dpi/ANjjnBSfywZW+VQSIMMY0PzJhjKljjLkfaHciAYiIiIiIiIiId7MsKxn4HhhcOmsI8IVlWXuMMVOMMa0sy8q3LGv3kReQDuSX/vsfq8oVF09ie9RJc8AfiABWA+NPJAAREREREREROSncADxtjOkIJGC7LQTgYmxPFtnsjg+tSsfFo8AgoC3QAthpWdYidwQlIiIiIiIiIt7Fsqx04FoX87sepfz7wPsn+rlV6bgoBO4qXecPdVqIiIiIiIjI6cYqMZ4O4bRT6Y4Ly7KuP/JvY8wAY8wz2B6HMt2yrNXuCE5ERERERERETm+V7rgwxnSwLGutMWYwcAUwFtiK7dEn6rgQERERERERkWpXlVtFvit99GkU8DLQw7KsDe4JS0RERERERESkah0XO4H7gECgP9DDGJNkWVaeWyITERERERER8TKWpTEuappPFcpeYVnWn5ZlzQYeA+KAHcaYJ90TmoiIiIiIiIic7qpyxUXv0me1TgBGABuAx4EZ7ghMRERERERERKQqHRcfApuBT4D7Lcva5p6QRERERERERERsqtJx8aBlWQ+7LRIRERERERERL2eVeDqC00+lx7hQp4WIiIiIiIiI1LSqDM4pIiIiIiIiIlKj1HEhIiIiIiIiIl5LHRciIiIiIiIi4rWqMjiniIiIiIiIyGmtxDKeDuG0oysuRERERERERMRrqeNCRERERERERLyWOi5ERERERERExGtpjAsRERERERGRSrI0xkWNO+k7Lhqd0Yy+Fw2mIDefAztSmPvBTy7LGWMYc9fFAITHRvLd8zM5lJLm9D5jplzErFe/YuuSDS7f4+b3/49l3y9k0edzqz2PqvIL9GfkPZeQn51LcGQoPzz5CfmHcyuUaz2wI23O6ozx8WHbwnWsmbUUAB9fH8Y9PomOw3uQtvsgM6a8zt71fwMQFB7MBU9OplX/M0jduZ8v7nuHnSu31WR6ldL4jGb0u2gwBbkF7N+RzO/HqPuxDnX/jUPdtzizDZc+NpnohBhWz1nGR/e/RX52XoX3uPX9e/nr+wUs9IK6P6LJGc0YcNEQCnLz2b8jhTkfzHJZzhjD+LsmArb8v3p+BukO2/4Rd75/L0u+X8j8z38HoOWZbbjyseuITohh5ZxlfHD/VPJcfDee4u76r+y24Un+gf6MuucS8rLzCIkM5bsnPz5KO9CJtmd1xvgYti1cz+pZSwDbvj7hyeto3f8MDu5M4fP73mGHF+7rJ2rh0hW8/NYHPPvwPdSrE+/pcKpdy44tOfuis8nPy2ff3/v4btp3xyx7+V2XM/OVmaxdvNY+PzAokNFXjaZlp5Y8dt1jNRF2tTkt8w8MIPLG67BycjDh4WS+OhUrJ+eoxYMHDyT0/NEcvPEO2wxfH6LuvoPgQQMo3pdM+iNPUbjFu/Z9/0B/zrvnUvKycwmJDOWbJz8mz0X71nZgJ9qVnudsWbiOVaXt27GWBYUHM/HJ62lT2vbNvO8d/l65tcLn97lkKLkZh0lJ2ldhuTdo3bEVIycOJy83j71/7+XL9785ZtlJ/76KD1/+mNWL1zgtG3HxcO5+9k4A0g+mM/7MiyksKHRr7CeqZceWnHvROeTn5bH37318e5z9/sq7ruCTV2Y47feNWzXiruenULdJXRbPXsLzd73g9Xkf0apjK0ZcfC75ufns3bGXr45R9606tuKau65i+iuu6v5c7nqmrO4v7D7xpPkO5PRzUt8qEhIZxtUv3Mznj37AZ49Mo/mZrWnbv6PLsiNuGUduZjZfP/0xs6d+y7Wv3m5fFhgaRHB4CC26t8UcpfOsz4RBNGjXxB1p/CPjHr2a7cs2MeuZmayfvZzxj0+qUKZWkwTOmTKBrx+cxpf3v0vfK88hoWV9ALqM7cvij3/liQG3kbEvlbEPXmFf76zrR7P25794/eJHyUxJ56qpUwgIDqyx3CojNDKMa164hU8f/YCZj7xPizPb0O4odT/ylvHkZObw5dMf88vUb7n+VduJW0BwIIOuOJdp/3mdd+98hXb9OzHu35dUWL/fhME0bNfYnelUWWhkGJNfuJVPHp3Gx4+8T4szW9O+fyeXZcfcMp7szGw+e3o6s6Z+w42v3lmhzIAJg2nosH0HBAcy9IrhvPOf15h658t06N+JC/59qdvyqSp3139ltw1PG/foNSQt28yPz8xg3exlXOiiHajdpA4jpkzgqwff54v736WfQzsw6PoxrPl5Ka9e/AiZKelc44X7+ok6mJZOTm4uazds9nQobhEWFcaUF6fw1iNvMfWhqbTr3o4uA7q4LBscGkxIeAjte7SvsKxuk7rEN4gnIjrC3SFXq9M1/6gpt1Gwei2Zb7xD3rwFRN19x1HL+tSKJfxK5/Yr5OyhZH/9PSnjL6U45QCRd9zs7pCrbMKjk0hctonvnpnBmtnLuOjxayuUiWtSh1FTLuLzB9/n0/vfYeCV51KnZYPjLht6/RhW/7yE/138MBkp6Uwu1/YFR4Ry9Su3sXb2MpZ88adXdlqER4Vz7//+w6sPvc4rD75Oh+4dOHNAN5dlg0ODCY0IpWOPMzAuTnTbdGrF7RfdVfr6t9f/4RoeFcbdL97Fm49M5Y2HptK+ezu6DujqsmxwaDCh4aF06NEeQ1nuPj4+9D23L/defh/3TPw/egzuzuDzB9dUCickPCqce1+6m9cffoNXH3qdDme2P2bdh4WH0rFnB5d136pjK+686N+218XeX/dyejupOy76TRzCznXbyc+x/Qq6Zs4yzrnhvArlfP39GDJpFCt/tl1tkJy4h/DYSFr0aAtAfnYemxas5XBqpsvPqdUwnvDYCJIT97gpk6qJiIum8+g+bJizAoCt89fSbkgXouvXcio3YNIINv+xGsuyANj85xoGXDsCgNXfL2bX6kSy07JYNH0OJSWWfb2t89ex6tuF7Fm3nem3vkxIVCjxLerVUHaV03/iEHauS7LX/eo5yzj3hrEVyvn6+zFs0ihW/mz7lWVfad237NGW+CZ1+OjeqSSt2MKq2X/x7Yuf0qqX8wlt7YbxhMVGkJy41/1JVcHAiUPZ4ZD/qjnLGHmU/M+ZNJrl5fJvVbrtA8SVbt/7HLbvhCZ1eP/eN0lcsYWVs//iqxdn0qZXxZN9T3F3/Vdm2/C0iLhouo7uw/o5ywHYMn8t7YZ0Jbp+badyAycNZ6NDO7Dpz9UMvHakfZ2V3y5k97rtfHjry4REhXndvn6iasVEM6hfL0+H4TbnTjyXbeu2kVe6LyyZvYQL/3Why7K52bmsmr+KjNSMCsu2b9zOltVb3BqrO5yO+fvUiiVk2CDy5i8CIP+v5QT164VvguuricIvvYjsr5x/jc79dS6FGzZRciiD7K+/g5ISt8ddFZGl7dva0vZt8/y1dBjSlZhy7dugSSPY8Mcqe/u28c/VDC5t3461bPP8tSz/diG71m3n/Vv/R2hUGAkt6tvf95pXb+O3d38kddd+t+f6T42+ZARb1m4lt3TbXzh7EZfcdLHLsrnZuSyft4JDaYcqLOt7dh8OZ2azceUmls9bQdLGJLfGXR2GTxzOVof9fvHsJUw4xn6/cv7Kivu9gRmvzuRQagabVm1m5YJVlJQUuzv0ajHqkhFsWbetrO7nLGLijRe5LJubncvy+Ss45KLd63t2b7Kzstm4ahPL568gaeN2t8YtcqIq3XFhjOnnYl4rY0zz6g2p8lr3as9Bh4NKStJemnZphY+fr1O5Rh2aEhweQuruA05lW/Vs61SuxKp44DbGMPiq4fwy9eiXoNW0Zj3bkJ2eRWFeAQAlxSWk7TpAsx7O+TTv1Y60XWU5H0jaS7PSnI+sCxDXrC6znp5hn962aL3933lZueQdzuXQvoq3FnhS614dnOo+OWkvzbq0wrdc3Tfu0Izg8BAOOtR9ctJeWvVsx64Nf5Odcdg+/1BKGml7D9qnjTEMuWoEv0z91o2Z/DNte7XngEP++5L20txF/k1c5r+HNj3bAbYch141glnlctxZ7rtJT0kjde8BvIW76/9424Y3aN6zLYddtAPNe7RxLterPWkO39WBpH00L20HXO3rGV62r1cHH5+Tuo/+mDr16UTKrhT79O6k3bTt2rbCvuDIcuiodlTiZX+8VsbpmH9gl46UZGRi5efbZhSXULw3mcAuFa86Cxl1Ljm//IqVl+80374u4NeoIZlvvO3WmKuqRc+2Fc5zUncdoEW59q1lr3ZOnQspSXvt7duxlm1xeZ6TCkD7wV2o3SSBBu2acMN7/2HMfy7B1//o25OndOnTmX27ku3TOxN30f44236Ji21/6PmDuWDS+Xyz+gsumHS+W2Ktbp36dCTZIfddSbtp27VNlXIvKS6hqLAIsJ0LFeYX8PvXc90Sb3Xr3LsT+3bus0/vStxNu+O2exXbtyFjBzP+mvP5etXnjL/m5Kh7b2KVmFPy5c2qcjZ3rot5KcBn1RRLlUUlxJCdnmWfzsvOwz/Qn7Do8ArlcrNyKC5toGxlc4mMjznuZ5x15bn88dEvlBR5Ty9sZEIM2emHneblZecSER9drlx0he8nIq6sTEhUGAMnj6TP5cMICg9x+Vm1miSQuHgDWQcq9tJ7UlRCDIedcsutUt1HlfuuAJp0asHcD8vGSRh05bnM/ehnir2o7o+IToitVP7RLvPPI6p02x9y5XB+q0SOzTq14NcPf67GDE5MTdR/ZZd5SmRCNDkO3wFAfqXagVwi4yrmX7tJHbYt3kCml+3rcmyx8bFkppddLZhzOAf/QH8iYk6OWx5O1OmYv2/t2pRkOP96auXk4FMr1rlcvbr4RERQuGGTy/fxiYgg7JIJhI47DxMa5rZ4/4nIcud3YGvfyp+3lT8fys/Os7dvx1rmKK5JHbY6tH3dxvRl+4qtzH1/Fh/c/gpdR/Vm1BTXv2Z7Uq2EWs7bfnYOAYEBRMVEVul9/nvdw4xsdx5vPv4W1/3ftYy+bGR1h1rtYuNrkeWwfeQeziUgMIDIKuYO0LRtU/771v1E144m9Cjnwt6mQt0fzvlH+T94/SOMbj+WN594i8n/N4nRl3p/3cvp7bgdF8aYm4wxh4C7jTHFji8gFVvnhUdYlkVBftmVA34BtrFGK/wRZjlfYQDgH+BPceGx/1ir17ohhfkFXnOLyBGWZVGU75yPX4C/0x9ntnI4lfML8Hf6bvKzc0lcvIFda5K48s07iKxTsSOnz+XD+P7xj6s5g2pgWRQ65OYf4A+4qnurUnUfHBFCdEIsq3+1XZZav3UjCvMLnW6f8CZWJfO3LIuCvPLbih/FhcU0aN2IwvyC4+YYEhFCTEIsq35dVk3RVwM3139ll3mSZUFhvvO9qH6u2rVy5cq3A0f0vXwY3z0+3S2xivtYOO/j9n3hOMe3U8Vpmb9lYZU7ByAgABz3a2MIGzeGwzOO/ttSSU4O+StWUbhxE7FPPoRvXO2jlq1x5dp4cH2eY2vfnM8D7T80HWuZg36XD+Orxz+yT9dpUZ+kZZspKSom+9BhFs74lTPP61sNSVUvy7LId7iSxj8gAMB+FUFV5Obk8fk7X/LifS9z4bXjqy1G9ymfu22//ye5H9h7gF+/+p06Desw5fmKY4B5Jcsi37HdCzzS7v2zuv/ina946f5XGH/tuGoLUcQdjvtUEcuyXjHG/AlcAfyv3OICy7L2uVjNiTFmMjAZoF9MF9qEN/0nsdJjbH8ue/I6+3TSii2ERoTap4NCgynIKyAnI9tpvUMpaQQ7lAMIDA0mIyXxmJ836KoRdBp2JudNsd0zGBweQqP2TWnUvikzHnz3H+VQHTJS0l3kE0RmSrpzuWTnvMuXKS4sZteaJD686SXu/v0FGnVuwZp9ZaNxt+jTnsTFG5wuM/eUnmP7c8WT19unE1dsISSi7BeioNAgCvLyyS5X9+ku6j4oNIhD5b6rYZNGM/OR9+zTg68aTudh3Rnrou4/8UDd9x47gKsq5O+47R89/5AK+QeTnpLI0KtG0HVYd8ZPsT1xJDg8hMbtm9G4fVM+evAde/lzJo1musN34wk1Xf+VXeZJGS7bNdftQEi5diCjXJmWfdqzbfEGr76fW2wGnT+IW5+61T69ccVGwiLL9oWQsBDy8/I5nHHY1eonvdM9f4DiAwfxCXe+QsInJJjig2W3swWc0Z6QMSMJPncYAMbfHxMYQMKsr0g+t3Q8oKIiCjduJu3+R4if+QH+7dtS/NsfNZbHsRxycexy1XYdqtC+BZNR+tSoYy07olWfDmwt1/b5+Pk63XK8Z9NOQqI8f0XKsHFDuOvpsj+s16/YQHhk2VWGIaHB5Ofmk3UC2/4Pn8xi8j0VB3n2tMHnD+Z2h/1+Q7n9Pjgs+B/v91mHspj3wzwyUjN4dNrD1RJvdRs6bgh3PVU2AK+t7h3avVBbu3cidf/jJ7OY/J9rTihOEXer1ONQLctaY4z5j2VZFYaaNcY0tCxr53HWnwpMBbiu8QWuby6thNVzlvH38LLHdXUc3I26rRrYp+Ob1mHr0g0V7uPasdY2iF9s/ThSd9sOTvFN6vDdCzOP+XlfPPaBU5nrXruTZT8sZNFnc/9pCtUicdF6Ip64Fr9Af4ryC/Hx8yW6bi0Sl2x0Krd1/lpqN6trn67dtA7bFq8v/3ZYJRZ71/9NRnLZAT2uWV1iGsax5JPf3JdIFayes4yHhk+xT3cc3I16rRrap+Ob1mXL0o1Hrfta9eM4aK/7unztUK/9Lx7C0m/mkX2orMH/7LEP+NahzPWv3cmyHxax4LPfqz23ylg55y+2O2z7nQZ3o77Dtp/QtC6bXeT/t4v8E5rU5csXZvDbRz/z1QtlY5vc9NoUlv6wkHkOOQ68eCiLyn03nlDT9V+ZZZ62bdF6Ip+YjH+gP4VO7YDz45w3z19LXLM69um4cu1AXLO6xDaMZ9Env9ZY7PLPLZ692GkQyR5DetC4VWP7dL2m9Vi3ZN1JM15DVZ3u+QPkL1+Jz3/uhMAAyC8AX1984+PIX1n2mMOCDZtIuajsaWHBgwcSMmgAqfc+VPENS0oo3LKVkgPeM47PlkXrmfjEdRXat/KPq980fw1xDuc5cU3rsGXxhuMuA4hvVo9aDeNYUK7t27tpJ/FNy9rMkqJikrd5/urLBb8sYtOqyfbp3kN70bR12dPAGjStz+ola05429+yxvsGqV00exFbVpc9GarnkJ40btXIPl2/aT3WnuB+v2XNFg4me88+4GjhL4uYtKrsh9teQ3vRxKHdq9+0PqsXrz3hut+8xvuenuPNrH/8F638U0e9VcQYM8UY4zja47+NMQ+Ue/0X+MD9YdrkZeWQkrjX/lr0xVyadGph7xlvN6Azs9+yDaIZUTuKUbfbRhguLixi/oxf6TDI9oi0Os3rk56cStIK58bZYHB8HmpOZjaHktPsr8KCQnIyssnJdP5Vt6ZlHchgw28raNHH9pSDln3bs+anpWSmpDPg2hHULj3gLpo+h1b9z7Cv17xXO+a/ZxunIKFlfYIibPfyBUWEYHx92LHC1mDFNIij58TBbJm3huj6tajTpiG9Lh1SkylWkJuVQ6pO8cgAACAASURBVHLiXvtrYWndHxmIqP2ATvxSWveRtaMY7VD382bMOWrd971wEHnZeRTkF1Crfhydhp5J826tycnMJj05zf4qKigiO+Owx+o+NyuHfYl77K/5X/xO004t7fl3GNCZn96yDbAZWTuKsbdPAGz5z50xh06DbI8Jq1uaf+KKLRVyLCwoJNth++5/4WDysnMpLP1uOg89kxbdWnsg+5qv/+Mt8wZZBzJY/9sKWvTpAEDLvh1Y/dNSMlLSGXjtSHs7sHD6bFo5PCq2Ra/2zHvPNl5HbIM4ek8cwqZ5a4iuX5u6bRrS+9KhNZ+Mmx15qoB1Cpxl5GTlsDtxt/015/M5tOpcNjBt14Fd+XLqlwBEx0Vz6R0uHmNscPlYPGOMy/ne5HTPH6AkLZ28BYsI6mZr1wLP7Eru3HmUHDhI2MQL8WvYAAoLKTlw0P6yMrOwSucB+DVtjAmzXY1gwkLB15eCtRV/2PCUrAMZrPttBa1K27fWfTuw+qclZKSkM/jakcSVtm/zp8+hjUP71rJXO+a+N+u4y2IbxNFn4mA2zltDTP3a1GvTiL6lbd/c936k7cBO9tuPm3ZtyR/ve36Mo+ysbHYm7rK/fvrsF9p0bm3f9nucdSYz37TdGhQbF8NVd15R4T3Kb+MhYSEMn3AOfv62XC+cPJ53nn3f/clUUU5WDrsSd9tfsz+fTWuH3LsN7MYXU78AICYuhstc7PfG+RQfH18fWnVqaZ/uMbg7X73ztXsT+YfK1/3Pn/1CW4f8uw88k0+n2uo+Ji6GK++8vOKbGIPD02AJCQvhXIe6v+Dacbz33PvuTkXkhBzriosmQJTDdBcgFEgGjpz9GSDBPaEdX1ZqJjP++y4THriS3KwcNi1Yy8Z5tl8cajWIo+f5A/jpta8pzC/guxc/Zfw9lzH8pvOJSojlzRues7+Pj68PXUf0IqJ2FN1G9ObgzhTS9nhnr+sRX977LiPumUjdNo0Irx3F5/e8BUDn0b1J332AA0n7SN6ymwXTfmHUfbYG/I+3vidl624ABv1rDC37dmDd7OUcPphhXz+8dhQ3zLif6Hq16H/NcPvnfXjTSzWc4bFlpWbyyX/fYcIDV5GblcPGBWvZMG81YDsh6XX+AGaV1v03L37KBfdcxoibxhGdEMPrNzwLQK/zB3D5k9c7PXEgJzOb27t6/6VyWamZfPTft5lYmv+GBWtZV5p/rQZx9Dl/AN+/9hWF+QV8/eJMJtxzOaNvGkd0Qiwv3/DMcd+/z/m2W1Mcv5vszGxu7nq123KqCnfX/8mybXx+7zuMumcidds0JKJ2FJ/eMxWALuXagfnTfmbMfZcB8Ptb35G8dTcRtaO4ccYDRNerxQCHfX2al+3rJyo7O4fvfrFdOfb1j7OZOG4UMdFRx1nr5JGRmsHrD7zOdQ9eR3ZWNqvnr2bFn7ZHZcfXj2fwuMF8+tqnFOQV4OPrQ7+R/YipHUP/Uf1J3pnM/j22K5EatmhI98HdadC8Ad0Hd2fpr0s9mValna75H3rmRSJvvA6/5s3wjY3h0JO2c5rgoYMo2pdM0c5dx1w//PKJBJ7Zlbx5CylOS7ev701m3Ps2591zCfXaNCKidhQfl7ZvXUf3IXX3AfYn7WPfll38Oe0nzi9t335963uSS89zjrYsonYUt874LzH1ajHomhH2z3v3phcB2L5iK98/O5PxD17F/sS9FOQWsNjDV9q6cij1EC/d9wq3PHQjh7OyWT5/JX/9aRuLKaFBAueMH8r0Vz+hIK8AX18fBo4cQEztaM4aNYC9O/aSsmc/gUGBXHzDhVx2yyWsWrSa7z/5kY0rXQ/m6k0OpWbw6gOvccOD15Odlc2q+atY7rDfDx03hJkO+33/kf2Jrh1N/1H92Ve638fGx/LAm/eTkZbBygWr2Lt9L9998L2HM6ucQ6mHeOn+V7jpwX+RnZXNigUrWXak7uvHc/a4oXz86gx73Q84UvcjB7Jvx77Sug/gousv4NKbJ7Jq8Wp++PjkqHs5vZnK/gJljOkCrLMsq6Dc/LaWZW04ymoVnMitIie78MrdmXPKOkSFO41OK4Wctps+AP54/y+Z7nQ67/9PL3vc0yF41OjON3o6BPGgt+vnH7/QKeqJfV404KcHrCn07h/B3C3Ix9/TIXhUgVX1wTJPJXN3zzmlT/w2thh+Sp7Yt9n6o9fWW6XPpC3LWuE4bYwZiK3jwzM3/YuIiIiIiIjIKa/SHRfGmF3A+8BLwM3AFOBHY0x/y7JcjPYkIiIiIiIicmqxSrz2woRT1lEH53ThW8uy7sc2zsV/gCsty7oA8L7h9kVERERERETklFCVjosdxjYU8XPAPMuyPiud37f6wxIRERERERERqcKtIsASYDa2zo7LjTGNsN0u0skdgYmIiIiIiIiIVKXjIgK4zrKsRId5N5e+RERERERERE55JZbGuKhpVblV5G2gQ/mZxpjT+1lHIiIiIiIiIuI2Vem4uBJw6loqHfNiSnUGJCIiIiIiIiJyRFVuFXkDqG/rq7AzgAU8UZ1BiYiIiIiIiIhA1Tou/gf8BezE1lkBto6LSdUdlIiIiIiIiIg3sjTGRY2ryq0iLwMbgXDLsnYA/sAe4GF3BCYiIiIiIiIiUpWOi5HAduCp0ukD2Doz2lR3UCIiIiIiIiIiULWOi/8AY4E/ACzLygBmAO9Xf1giIiIiIiIiIlUb4+Iny7JmG2PaOszrCDSs5phEREREREREvJJlHb+MVK+qdFxkGmN6Az7GmARgPPA4MM0tkYmIiIiIiIjIaa8qt4q8CPQHrgOSgNuBF0r/LyIiIiIiIiJS7Sp9xYVlWUXAk6UvO2NMA2BXNcclIiIiIiIiIlL5jgtjTDgwDqhTup4pfQ0EznJHcCIiIiIiIiJyeqvKGBe/AUHAKqDIYX6tao1IRERERERExEuVWMbTIZx2qtJxEQc0tSyr2HGmMaZj9YYkIiIiIiIiImJTlcE57wa6uZgfWU2xiIiIiIiIiIg4OeoVF8aYb4GwcrMbGGPKD8TZBtu4FyIiIiIiIiIi1epYt4qsBfyBjUDJUcoYYHR1ByUiIiIiIiLijSyNcVHjjtVx8QyAZVmHAIwx7S3LWudYwBjTApjtvvBERERERERE5HR21DEuLMs6dKTTotREF8WSgI+rPSoRERERERERESrxVBFjzE3AzUCcMeaicosjgJ3uCExERERERERE5LgdF5ZlvWKM2QxcCrxbbnEBsNodgYmIiIiIiIh4G8vydASnn+N2XABYljXbGLPcsqw0x/nGmMZAXWBb9YcmIiIiIiIiIqe7SnVclAo0xtyO7RGpR4ZRDQbOw/ZIVBERERERERGRalWVjosZQBZQC9sjUgHaAtOqOygREREREREREahax8Vcy7L+a4w5A4ixLGuuMaYucIebYhMRERERERHxKiWWOX4hqVZHfRyqC3HGmD7AJuBcY0xDbONbXOmOwEREREREREREqtJx8THwItAFeB34A1gCfOuGuEREREREREREKn+riGVZ84AzHWY1McbElH/SiIiIiIiIiIhIdal0x0XpeBYvALmWZV1pjOkO9DXGvGpZVn5l3+fSvNP3obfr/X09HYJH+Vqnd/4L/XI9HYJHxeDv6RA8KoDT917I0Z1v9HQIHvXtylc9HYJnFVb6FOGUdH6PuzwdgsfE+BR5OgSP+qLt6Z3/7s1hng7Bo6Jjiz0dgsgppSqDc34ApAAZAJZlLTXGNAbeRONciIiIiIiIyGnA0uCcNa4qY1xstyzrEiDJYV4OMKZ6QxIRERERERERsalKx8VeY4wBLABjTDzwMLDRHYGJiIiIiIiIiFTlVpFpwOdAI2PMcKAvtltHLnNHYCIiIiIiIiIiVem4uBe4FOgINAQeAxZbllXojsBEREREREREvE2JxriocVXpuCgEppSu80fp41FFRERERERERNym0h0XlmVdf+TfxpgBxphnsI13Md2yrNXuCE5ERERERERETm+V7rgwxnSwLGutMWYwcAUwFtgK7AXUcSEiIiIiIiIi1a4qt4p8Z4zxBaKAl4EelmVtcE9YIiIiIiIiIt7H8nQAp6GqPA51J3AJcD5QDPQwxgS5JSoREREREREREarWcXGFZVl/WpY1G9sTReKAHcaYJ90TmoiIiIiIiIic7qpyq0hvY0xHYAIwAtgAPA7McEdgIiIiIiIiIiJV6bj4ENgMfALcb1nWNveEJCIiIiIiIuKdSizj6RBOO1XpuHjQsqyH3RaJiIiIiIiIiEg5lR7jQp0WIiIiIiIiIlLTqjI4p4iIiIiIiIhIjVLHhYiIiIiIiIh4raqMcSEiIiIiIiJyWrM0OGeN0xUXIiIiIiIiIuK11HEhIiIiIiIiIl5LHRciIiIiIiIi4rU0xoWIiIiIiIhIJZV4OoDTkK64EBERERERERGvpY4LEREREREREfFa6rgQEREREREREa+lMS5EREREREREKsnCeDqE046uuBARERERERERr6WOCxERERERERHxWuq4EBERERERERGvpTEuRERERERERCqpxPJ0BKcfXXEhIiIiIiIiIl5LHRciIiIiIiIi4rVOiVtFfIICaHL/pRQdzsM/KpTtj3xE8eFcpzK+4SG0eP4Gogd2JO/vFLbdPZWsFVvtyxvccj74GCix8AkOYMdTM2o6jX/MN8ifnv93MYXZeQRGhrD48ZkUlssfIDAqlI7XjSAgPJj5901z+V7NRvWg3WVD+PbCx9wddrXxDfKnx70XU3DYlv/SY+R/xvUj8A8LZqGL/H2D/GlzySDyM3LISNrL/hWJNRH+P9bkjGb0v2gI+bn5HNiRwq8fzHJZzhjDuLsmAhAeG8lXz8/gUEoaAPVaNmDSczcT37gOq+b8xbt3v0ZRQZF93f4TBnPVU/8CIPNgBnf2nuy03BP8Av0Zcc8l5GfnEhwZyo9PfkK+i/puNbAjrc/qjPHxIXHhOtbOWgqAj68P5z8+iTOG9yB990FmTnmdvev/tq931r/GYHx8sEpKCAgO5OfnPq2p1CrFL9Cfs++ZSEF2HkGRofxylPxbDOxIq7M6Y3wMSQvXs740f4CgiBCmLPgfQeEhAEy/7nk2/rwMgAH/GoPxMVglFv7BAcx57rOaSewEtOzYkrMvOpv8vHz2/b2P76Z9d8yyl991OTNfmcnaxWvt8wODAhl91WhadmrJY9edPO1fZSxcuoKX3/qAZx++h3p14j0dTrXJy8/n+TemERISTGZWNndcdzlhoSFOZQqLinhx6gcEBASQfiiD3t06M2xgb/vyqR99hlViYXwMeXkF3HzNRIzx7kfctTijBcMuHkZ+bj77diTzw7TvXZYzxnDZvy8HIDI2kunPTSctJRWA+s3rc/5149i/Zz91GtXhg6emkZpsW/bvV/9Nv1H9nd7r9Xtf48cPf3RjVpXT5IxmDLhoCAW5+ezfkcKcYxz3xpc77qWXHvcc3fn+vSz5fiHzP//d6TPGTZnId69+weYlG9yTyIkKCCDs2huwcnMwYeFkv/0GVk7OUYsHDjiLoFFjyJhyW4X3CR4xmpLDWRTv3kXRRi/NtxwTGEC9/7uC4uxcfCPD2PvENErKHwd9fWj4xL+IGtGHgt372XHHi+Su3378ZScZExhA9G3XUpKTi094GOkvvY2VffRtIWTYACIuHEXypCk1GKVI9Tglrrho9uQkMpZuYscTH5P60180f+a6CmXq33QeqT8sZu24BylISaPttLvxCQkEIGZoVwIbxrHrxS/Y9b8vCUiIodaY3hXew1v1e+wqkv/azNKnPuXvX1bQ/8mrXZaLaBRPTKv6+JfmXV5IfBRdbh7jzlDdos9jV5G8dDPLnvqUHb+soO9R8g9vFE90S9f5B0SGMPi1m9kxewVbP5/n9Z0WoZFhXPvCrcx4dBozHnmfFme2pn3/Ti7Ljr5lPDmZ2Xz+9HR+mvoN/3r1TgCMjw/dzu3J81c+yrOXPUzHwd3oPXaA07pNOjbnmUsesr0ufcjjnRYAYx+9mr+XbeKnZ2ayfvZyxj0+qUKZWk0SOGfKBL59cBpf3/8ufa48h/iW9QHoPLYvSz7+lacG3MahfamMefAK+3ptBnUmpkEcv73yFb+/9g0R8dF0HNmzxnKrjNGPXs2OZZuZ/cxMNs1expjHr6lQJrZJAkOnXMgPD07ju/vfo9eVZxNXmj9At4sG8cWUN3jvksd575LH2TR7OQCtBnUmukFt5r7yNX+89g3h8dG097L8ywuLCmPKi1N465G3mPrQVNp1b0eXAV1clg0ODSYkPIT2PdpXWFa3SV3iG8QTER3h7pBr1MG0dHJyc1m7YbOnQ6l2j77wJp07tOW2ay9jUJ/uPPTc6xXKvPnhZ0RFRnDrpEu577breePDT9matAOAuQv/Ys++/Vx3+YVMvvQC9qem8dPvC2o6jSoJiwzjjhfv4J1H3uHth9+m7Zlt6dzf9fY+4daLyM48zAdPTeOrqV9y9+t3A+Dr58u9b93HR89+xIwXP+HHD37gP2/cA0BoZCh5Ofncc+E9TBlzJ1PG3MnGZRtZOmepy8+oSaGRYUx+4VY+eXQaHx/nuDfmlvFkZ2bz2dPTmTX1G24sPe45GjBhMA3bNXGaFxQaRHB4KK26t/HqDqzwW+6gcN0ast99i/yF8wm77eh/hPrExhIy8bIK801YGBH3PUj+ogXkz/75pOm0AGjw2PUcXraRfU9/RMYvS2j4xL8qlIkZO5CD039mQ7/rKNh7kPoPT67UspNNzP/dQt7KdRx6+V1y5y4k9r7bjlrWt3YsUZMm1mB0ItXrpO+4CIiPJm5sP9J+sf1amP7nGmLP7kZgg9pO5Q79uYYDXy/g8JokNt3wEn5RYYSUnsgHt6iHX1iwvWxJXgF+4c6/2nirkPgoWozpxY7ZKwHYPW8djYd2Jrx+rQplD6xO4uD6HUd9r843jGLDR7+5LVZ3CImPovl5ZfnvmbeORsM6E+Yi/4Ork0jd4Dr/wa/fzNq3Z5G184Bb460uAyYOZce6JPJz8gBYNWcZw28YW6Gcr78fZ08azfKflwCwL3EPEbGRtOrRFmPg+9e+Iis1k6RVW9mwYC0lJSX2dTsP605OZg5Jq7eyYcEadm86+rZTUyLiouk8ug8b5qwAYNv8tbQd0oXocvXdf9IINv+xGsuyjZy05c819L92BABrvl/MrtWJZKdlsXj6HCyH0ZXimtcjMCzIPl2YV2C/KsEbhMdFccbo3mwuzT9x/jpaD+lCVLn8+0waztY/1tjz3/rnGvqW5u8b4Efzfh3Yv3k3iQvWkbhgnf07qN28HgEObaG35e/KuRPPZdu6beSV7gtLZi/hwn9d6LJsbnYuq+avIiM1o8Ky7Ru3s2X1FrfG6gm1YqIZ1K+Xp8OodvsPpvHDr38ysPeZAPTs2pG5C5eyZ1+KU7mvfpxDy6aNAfDz86Vf9y68P/NrAJJ27iY7p+xX2qDAAA5nZ9dMAv/QOZecQ+K6RPv2vnTOUsb/a3yFcn7+foy9diyLfloEwO5tu4mKjaJ9j/a069Ge8Khw+9UXm1duJr5+PO17diAwKIhX7n6ZdYvXsnnlZrZv2E5RYREH9x2suSSPYqCL497Ioxz3zil33AsvPe4dEdcwnvDYCPYl7nFaNy87jw0L1pCVmunGTE6MT2wsgWcNJn/xQgAKVywnsGdvfOITXJYPnjCR3O+/rTA/4r6HyP3iM0qS97k13urmFx9D9Jj+ZMy2daZlzV9NxNDuBNSPcyqX/v18clZvpSgtk4PTf8IqLqnUspOJb+1Yws49i9w/FwOQu2QFIQN74lfX9ZV1kVdNIOtz11doSdWVYE7JlzerUseFMaaBMeZqY8wdxpiRxhiP32oS2bsdhWmZlOQW2GYUl5C3cz+Rvdo6lctYsM7+7+KsHIqzcsnfaztop81eTsywbtQa2RO/yFD8Y8LZ//mfNZbDiajbqw156VkU5dnyt4pLyNp1gDo927he4ShD4LaeMICtXy+kKDffXaG6RZ3S/Isd89959PwtF/k3HNKZyCYJ1GrfmLM/mEL3ey/Cx9/XrXGfqDa92nNg1377dHLSXpp3aYWvn3PcTTo0Izg8hIO7yzpk9iXtoXXPdpQUl1BcaLuCwhhDYX4Bi7+ZZy/Xa0w/hl09gv8tf5ehV49wc0aV07RnG7LTsygsre+S4hLSdh2gaQ/n/b1Zr3ak7SrL+UDSXpr1tJU5si5AXLO6zHq67Lawjb+uoO2QrnQ4tzvBEaGExoSz/Muy78TTmvRsS065/NN3HaBJD+ftvWmvdqQ7bB8Hk/bRpHSfaDWoM/U7NeP2uc9z2bt3ERIdbi+3+dcVtB7ShXbndieoNP9VXpS/K536dCJlV9kfq7uTdtO2a9sK+4IjV+0A4NRxdyrx8Tnpf6Oo4K9Va4mOjCA4yHYFnZ+fL/US4lm2er1TueycXFIOpNqn6yTUZut2WyfsgF7dmLtwKb/MXUhG1mHSMzIZNWxgjeXwT5zR+wyn7X1P0m7adG1TYXtvfkZzQsJD2L97v1PZ9r06EBIWQlhUGIFBZVcf7t+zn8atG5GWkuq0H3QZ0IUVf65wY0aV17bccW9fFY57yUl7aNOzHWA73g29agSzplb8Y/6IEst7Hxfgf0ZnSjIzIL/0fK2kmOLkffif0bFC2aBzhpP/2xys/Dyn+QE9e+Nbrx5+LVoQ8dhThE66Hvw8fkpfKeE921OUnomVV3beX7ArhbDS+j3CcjjWBzWrz76nP6zUspNJULczKD6UiZVXui0Ul1C0J5nArmdUKBt23jkc/vG3srIiJ6FKn80YY64AtgAvAJcBTwFrjDHtjrmimwXUiaEo/bDTvOLDuQTExxx1neCmdchYuJ7C/YcAyN26h003vEjL/91Eq9dvY8ttr1Li0Kh5s9D4GPLK5V9wOI/Q+KhKv0dEozgCo8LYv8q7b49wJTShYv6F2XmEVCH/Zuf1JmX5Nta9+wtzb3mDZqN70u1u17/YeovohFgOp2fZp/Oyc/EP9CfM4Y9QgKiEGHKzcuwdFLayeUQ57B8N2jbmpjf/TWTtKIIdfl1/7cbnuKnTlXz25EdccPdlDLxkmBszqpzIhBhyytV3fnYuEfHR5cpFk+Pw/eRn5xERV1YmJCqMAZNH0vvyYU4570/cy8e3vMyE527g4v/dxKdT3qAov9BN2VRdhMv88wgvl39EQrRTufzsPMJL89/w01882mESb1/4MFH1a3Pp23faL4k+kLiXT295hXHPXc+F/7uRL6e86VX5uxIbH0tmetmvozmHc/AP9Cci5tS65UOcpRxMIzLCub0LDQlmf6rzOAZ9zuzEjG9mkZOTS1FRMRs2J1JS2nHVrFEDnr7/Tu598iXufuR5Hr37FoICXd9K6S1iE2LJdGjbcg/nutzeYxNiycnKocih7c85nEtsfAyblm8kPzef8ybbrlaIjoumdr3aGBcdXD3P7smiWQvdlE3VVPa4F32c496QK4fz20c/U1xUXDOBVzOfWrWwMp2vCLFyc/GJdb7yzqdOXUx4BEWbNlZ4j8BBQyjcuIHcr74g68nHCDxrEKFXVbzt0hv5J8RS7LAdAJQczsXfxXm/b1Q4cdeNpfYVw/END630spOFb1wtSg45bwsl2bn41Y51mudXvw4+keEUrNtUk+GJVLuq/AzzFPAsEGdZVmfLstoBQ4Gb3BJZZVnYf20/wifAH+sYB6Q6V53D9oc/cF7H35cNVz5NcOMEWr95B+YYv9Z5F8t+tcURvgH+lFT2gGwM7a4Yypq3XQ9w5e0sy6pQ/1XKH4huVY+UZVuwiorJP3SYTR/Ppfl53j3GiWVZFOaX5e0X4A9Q8UTMsigo9/34B/hRXFhWLm3vQRZ9/Se1G8Yz6dmbncrm5+Qx+70f+Oi/bzPs6pHVnEXVlc8bbLk7nqDaylHh+3H8bvKzc0lcvIFda5K4/M07iKxTdsLj6+fLtMnPU6tRPJe8cgs+XtQWuM7fuT5t5crn71dh2/h76SbenfgotZrVpX7n5vb5vn6+TJ/8PDGNEpjgZfm7YuG8jfsf2RcKT84/SqRyDIagwACneQWFhfj5Ov9q/MAdN9ChdQtuue8J3vn4C9Zu2krTRmXjvRQVFfPSo/ewc88+pjz0DIVFnh/H51gsCwocfjE92vZuWZBf7pdV/wB/igqLOXTwEA9f+RDte7bnzpemMHj8YGLiYti9dZdTeR9fHxIa1WFPkvPtFJ5Svv3zP8pxz3Jx3DvSTjZo3YjC/IIKt4icVCwLK7/cr+b+/uC47RpD8Oix5H7henBlv0aNKVy/FoqLsbIyyfvxewIHD3Vj0NXIsir8uGgC/LFctPkl2bkcXrSW7DXbaDL1Hvzr1KrUspOGi23BBPhjldsWwieMJvOjL2o4OJHqV5WOixTgKcuy7HuIZVl7AHtXrjHG5c3QxpjJxphlxphl3+Yk/eNgXSnYl4pfZLle1LBgCpIrjh4NENWvAxkL15O3s+xyw8hebQnr1JxDf65hzdgHCGvXmHrXj6rWON0lOzmdwHL5B4QFkZ2SXqn1E85sSduJZ3H5ile5YvXr9Hn4cuK7teCK1RUHOfNGOS7y9w8LIqeS+QP4+Pri41u2K6Rt3ElglHf1vvcaO4Cpmz+xv7LSMgmJKIsxKDSIgrx8sjOc789OT0lzKmcrG+w0unr2ocMs+3ER79z1qtM9wI7mzfy1wq9anpCZkk5wuXwCQ4PILFffmclpTuXKlykuLGb3miSm3/QSGclpNOzcAoCmPdpQv2Mzts5fyxsTHqFu28b0nzTcjRlVTVZKWoX8A0KDyTpu/hXLAGQfzGTt94uJrGv7daZxj9bU69iUxPnreGfCw9Rp24g+XpQ/wKDzB/HN1m/sr4zUDMIiw+zLQ8JCyM/L53DG4WO8i5zs4mvHkJnl3N5l5+QSV6vc1VcR4Tx01428/fzDUD2jhAAAIABJREFUjBsxlO07djNyqG0Q4r9WrWPd5q307taJ9196jE3btvPBp0e/fcATzjr/LL7Y8qX9VX57Dw4Ldrm9pyanEhYR5jQvOCzYPq7F+qXruX/ifTx367MUFxWTmpLK6oWrncq379GedQ5P3qlpvccO4K3Nn9hf1XHcG3rVCC646xJeWfEer6x4jxZdW3Ppg9dw6YMVBzn2ViWpBzHhzsdjExJCSWrZLVH+7ToQPGIksZ9+Sezn3xB24634t+tA7Off2Ar4+mJ8yjqli5IS8Qn3/DG+MgqTU/Etd97nExZMoYunxliFReSs2cbf/3qGwuSDhHZpWallJ4vi/an4lLvyzCc0hGKH2+MCO7UjfNwIGsz5lAa/f07M3TcS2LEdDX7/vKbDPeVYmFPy5c2qckPbncBNxpiPHebVAZobYxpg6wS5Enio/IqWZU0FpgLMSxhfrTcOHlqwnhbPReMTFEBJXgHGz5fAerXIWFRxdOTgFvUIahRP8kdznObXGtWL7I07AShISefvpz6h1qje8MrX1RmqW+xZuIEBT12Db5A/xXmF+Pj5ElY3ln2LK3c52P5VicwY+G/7dLOR3Wk6sgezr3/ZXSFXq70LN9Dv6bL8TRXzB1tHRWSzOvbpkqISDm3b645w/7FVc/7igeHb7NOdBnejfqsG9umEpnXZsnQjVrl79P9eaxvIrFb9OA6W3usc36QuX71Q8XG/f69JJP0oHX4AO9ZVb6fjP7Ft0XrGPXEtfoH+FOXbtveourVIWuJ8KeyW+Wup3ayufbpW0zokLl5f/u2wSiz2rP+bzNK8OwzvQfJm26+OmfvT+fm5TzljeA/mvnH0x2vWpKRFGxjzRHS5/GPZXi7/xPnrqOWwTcc2TWD7YtcjxlvFJSSXDlrbfnhPUjbb2sKs/YeY89yntBveg3lekj/A4tmLnQbR7DGkB41bNbZP12taj3VL1p2y41WITfdOHfjvwdfIy88nKDCQwqIi9u0/QLeOFZ8Yc8QbH35Kz64d6dejKwC/zF1Ii6aNAIirFcMt11zCz3MXcs3E82skh8pYMnsJW1eXPbr9zCHdadSqkX26bpN6rF+yvsL2nrh2G7k5ucQ3iLePiVGvST2mPzfdqVxwWDDnTR7L2w+9TUm5AQp7nt2LXz93Pl+qSSvn/MX24xz3NlfyuJfQpC5fvjCD3z762en4d9NrU1j6w0LmffY7J4uCVSsJv30KBARAQQH4+uJbO47CNavsZQo3byTt6svt04H9BxI44CwyH/kvYOuo8G3QsOxNi4sp2rmzxnI4EVmL1tIg/kZMYABWfgH4+RJQtzaHF687+kolJeSs306hq3OcYy3zcnl/rcL3gdudvgu/hNrkLV9jL5O/bjN7zit72l7osP6EDB3Agbse8UTIIiekKldcvAg8Dvzt8FqE7VaRHcB24IFqja4SCg8cIm32CqL6dQAgqv8ZHPxhMQXJadS7YTTBpX+8BDWMo86lQ0n/YzWBDWoT2rYRda6w3bN/eN3fhLUveySWVVzC4ZVbK36YF8o9kMGOX1dSr49tqJF6fduRNOsvspPT6XjdcCKb1nFewdj/A0BJQRHZyWn2V35Gtn3eySD3QAY75zjk368d22f9RU5yOh2Oln+5R5yte+dnGpzVEZ8AWz9efLcWrH/3l5oIv9Jys3JITtxjfy344neadmppH5Ssw4DO/PSW7ZfCyNpRnHf7BACKC4v4Y8YcOg6ynajXbV6f9ORUEldswcfXhyYdy24R6DioC7+8axttOigsmH4XDMLX3/adDLtmJF89X7Gzo6YdPpDBxt9W0KKP7Y+TFn3bs/anpWSmpNP/2hHULq3vxdPn0LJ/2eBUzXu1Y8F7PwMQ37I+QRG2i8OCIkLw8fVhxwrb/r5vww7qtWtsX6+kuIRdq71n7JfDBzLY/NtKmpXm36xve9b/tJSslHT6XDuCWqX5L50+hxYO+Tft1Y5F7/0EQLtzuxPdwDb6eq1mdck9dJiDSbZR5fdt+Js65fLf40X5A+Rk5bA7cbf9NefzObTqXDZAX9eBXfly6peA7d79S++4tOKbGFw+6tAY49WPQPynjjxdxvLiAQerqlZsNAN6dWNx6Qn64uWrGdq/F/G1Y3lvxtds3+l8K8AvcxeyYXMij//frfY6btW8CRu3lnXI+vj40KFNi5pLohLKb++/ff4rrRza/q4Du/D11K8A2/Y+8Q7bow6LCov45ZOf6TbI9tSVBi0acDD5IJtXlHXq+/j6cNuztzHro1nM+67igORN2zUlca3n9v/crBz2Je6xv+Yf57g31uG4N3fGHDq5OO7lZGaTnpxmfxUWFJKdkU1OpvNVG8bWSNRgtpVnpaeRv3gRAZ1t+QV06Ub+/D8pST1I8PgJ+NZvAIWFlBw8UPY6nIVVWEDJQduApblffUHAmd1tt5gAfu3ak/v1yXErQdGBQ2T+uozwvrZjXETfjhyatZDClDTiJp9HYNN6AAS1bIhv6ZU3vhGhGB8fspdvOu6yk0lxajq5fy4mqHtnAIJ7dCH71/kU708l4vLx+DWqD4WFFO8/aH+VZB7+f/buOzyKcu3j+HfSew8phBJ6RxCpUgTLsVAUjwh2pVrwBUEU9XjsHAtiA8WKYsGKYqEqIB1p0qQkgATSE9J75v1jQ5JNAiSSZBf4fa5rlZ15Zve+M7M7M/c+80zpNJFzTU16XLwOfG+aZnxVMw3LkcDEWomqhg5Om0vTJ27Ds10TXBr4cWDKOwAED+tD3tEECjOy6fjtU7hFBNNwXNl1+nvHzQQg/vNfcYsIIuL+YRSkZODaMJCjr31ri1T+kdXTP6TX9JEEtWuMe7Afq6a9D0CLIb3IOJpIWslJSXCnSMJ7t8M9wJuwnm1q1CvBnq2Z/iE9HhtJQLvGeDTw4/eHLfk3H9qLzJiy/IM6RRLeqx1ugd6E9mxDXEn+CVsP8sdLX9P76dtJi4qlMCeP/V/a911lMpLTmf/ke4z8z13kZGSzZ+1Odv9u6eYb1KgBvW/oz0+zv6MgL5+FsxYw4tHbGXz/cPxCA3lrwksA+IUEcP+cqWSkprN37U7iD8fy23zLyb2Lmwv/GjeU6+4fzl8bdrN6wXKit9tHMe+7xz7gmkdHEda2Cd7Bfnzz6LsAXDSkN6kxiSRGxxK/P4Z185Zy3eOWk9ZV7/5I/IEYAAbeO5SWl3Zk97ItZCallS4PsPnLlfiFBzJgwhCyUzLwDQ/k17fsq+fVD499wL8eHUlo28Z4Bfvx/aPvAdBpSG9OxCSSFB1Lwv4YNsxbytUl+a959ycSDlhO5CJ7tmPY/8YQvW43hzbs5ddZZQerW79chV94EP0mDCarJP9Vb31f/0nWQFpyGnP+M4dx/x1HVkYWO9bsKL0LQkhECIOGD+LL2V+Sn5uPg6MDfa/rS0BwAP0G9yPu7zgSjll+kW3csjHdB3WnUYtGdB/UnU0rNtkyrVqTlZXNoqWW21wv/HkZo4YPJsC/+oMX27MnJo9n5tvz2Bd1mOSUVP770L0A/PLrahqGNiCycUM2bv2T3fujKMgv4INZz1gNvnnDNYOIS0jkvU+/wc/Xh7jEJMbeUvnWovYkLTmNd558hzFPjiErI5sda3ew7XfL7cAbRIQw8IaBfP3W1+Tn5fPZq59x1/S7uemBEQSGBjJj/AuApZdFt8suoWXnliz9YilbVm6p9D4tOrXg4M6Dlabb0sn93qhy+71d5fZ7fW7oz48V9ntD7h+Of2ggb5Ts987EwdGB7tf2xjfYjx7X9ibx73iSj9nfbdIzX5+J55gJODVvjoN/IBmvvgyA62WDKIqPoyjm6GmXL9y7m6yP3sfr3omWtnm55C05d8Y6O/rYHMKn34l720icg/04+shsAPyH9iU/JoG86GOE3Hcj3n07k7ZsE4WJJzj6yFuly59u3rkm+bnX8Z80BpfWzXEM9Cf56VcB8PzXZRQej6fwSIyNIxSpPcbZ/gJjGMZo0zTfK/m3s2mapx2CvrYvFTmX7HZ2s3UINuV4wa55i3VOObYOwaaCcTlzo/OYi51fN1iXthRVf8yZ89EP287dg+JaUXBh337vhh5TbR2CzQQ42PddWurayy0v7F+1Y/adH0XSf8o/INvWIdhU0+3LzusDn2UhI87LM5sr4hfY7Xqrye1Q7zYM45hhGIWGYRSVPIqBd062OVPRQkRERERERESkJmpyqcgrwD3ANuDkSEhGyTQRERERERERkVpXk8LFFixjXFjdKNkwjHPj9hMiIiIiIiIics6pSeFiDHC3YRhLyk0zgDuAp2s1KhERERERERE7ZF7AY5fZSk0KFxOAyVQeF8NEhQsRERERERERqQPVHpwTuBvoDTiZpulw8gGMr5vQRERERERERORCV5PCxQLgL9M0iytMX1SL8YiIiIiIiIiIlKrJpSLbgJcMw1hbbpoBXA3cXKtRiYiIiIiIiIhQs8LFSCAMaI1lXAuwFC7a1XZQIiIiIiIiIvao4iUIUvdqUrh4AVhjmmZu+YmGYfSo3ZBERERERERERCxqUrj4DRhrGIa7aZozDcPoDviYprm8jmITERERERERkQtcTQbnnAM8DHQBME1zE9DVMIyH6iIwEREREREREZGaFC4igFbAH+Wm/YGlmCEiIiIiIiJy3is+Tx/2rCaFi3WmaRZQNjAnwFggvXZDEhERERERERGxqMkYFxsNw3gTCDQMwwO4EegMjKiTyERERERERETkgleTHhfhwEvADqAx8D3QASiog7hERERERERERM7c48IwjL6AAVwBHALWlTwA2gBvAIvqKkARERERERERe2Fi2DqEC051LhU5AXwMRAJ9KszLB96r7aBERERERERERKAahQvTNHcahtEfuMk0TRUpRERERERERKTeVGtwTtM001HPChERERERERGpZzW5q4iIiIiIiIjIBa1YQ1zUu5rcVUREREREREREpF6pcCEiIiIiIiIidkuFCxERERERERGxWypciIiIiIiIiIjd0uCcIiIiIiIiItVUjEbnrG/qcSEiIiIiIiIidkuFCxERERERERGxWypciIiIiIiIiIjd0hgXIiIiIiIiItVk2jqAC5B6XIiIiIiIiIiI3VLhQkRERERERETslgoXIiIiIiIiImK36n2MC1VKRC5MhRf41YAuut/3hasgz9YR2Jazq60jsClX48I98skyC2wdgk2ZxbaOQGzJvLAPe857+njXvwt3byoiIiIiIiIidk+FCxERERERERGxWypciIiIiIiIiIjdqvcxLkRERERERETOVcWGxi6rb+pxISIiIiIiIiJ2S4ULEREREREREbFbKlyIiIiIiIiIiN1S4UJEREREREREzsgwDHfDMN4wDON5wzDmGIbhU0UbX8MwvjIMI90wjG2GYfQ82/dV4UJERERERESkmszz9FFNs4E1pmlOB74H3qmizTTgW+Ay4DjwvWEYntV/i8pUuBARERERERGR0zIMIxwYBSwqmbQcGGIYRtMKTZebpvm5aZpbStoHAO3O5r1VuBARERERERGRMxkAJJmmmQ1gmmYhcAjoX76RaZq/lvt3GpAOxJzNG6twISIiIiIiInKBMwxjrGEYf5R7jK3QpCGQXGFaBhB+mtdsBaw0TTP2bGJzOpuFRURERERERC4kxbYOoI6YpjkXmHu6JkBOhWmuQMFplrkPmHqWoanHhYiIiIiIiIic0THAv8I0bywDcFZiGMblWHpbRJ/tG6twISIiIiIiIiJn8hsQbhiGO4BhGM5AY2BVxYaGYbQFmpmm+V1tvLEKFyIiIiIiIiJyWqZpxgE/AoNKJl0OfGOa5jHDMKYYhtEawDCMZsBYYKlhGE0Nw+hsGMaEs3lvjXEhIiIiIiIiUk3Fhq0jsKkJwIuGYXQGQrEUKABGAocNw0gHVgKNgP8rt9zNZ/OmKlyIiIiIiIiIyBmZppkKjKli+sXlnjau7ffVpSIiIiIiIiIiYrdUuBARERERERERu6VLRURERERERESqqZgLe5ALW1CPCxERERERERGxWypciIiIiIiIiIjdUuFCREREREREROyWChciIiIiIiIiYrc0OKeIiIiIiIhINZm2DuACpB4XIiIiIiIiImK3VLgQEREREREREbulwoWIiIiIiIiI2C2NcSEiIiIiIiJSTcWGrSO48KjHhYiIiIiIiIjYLRUuRERERERERMRuqXAhIiIiIiIiInbrvBjjwsHNhSZP3EpRZi5Ofp4ceWY+RZk5Vm0cvT1oMXMCfgM6k3s4nqhpc8ncegAAw8mRJo/fQnFuAc6BPpxYtYPkHzfYIpV/xNHNmZ7TR1KQlYurrwcbnl9AQYX8AVz9POk87lpcvN1Z8/i8Kl+r+eAetL/tcn646bm6DrvWOLo50+OxkeRnWvLfdJr8O42/Fmcvd9ZVyN/Fx4ORG1/DxdsdgGWjZ3F48R/1Ev8/FdmpOf1uvpy8nDwSj8Sz4uNfqmxnGAbDp44CwDvQl+9mfsGJ+BQAGrZqxOhXHiCkaRjbl2/mg2mzKcwvtFo+rHlDulxxCfGH4zi04wApscl1m9gZOLs6c92jt5CXlYu7ryc/zviMvCrWd5sBF9Husi4YDgYH1u3mz182AuDm7c5NM8bRpl8nkv6O55vH3+fItoOly4z96BGr1/l7+0FmDXu87hOrJidXZ656dBT5Wbm4+XqydMbnVebfckBnWpfkH71uN7t/2VQ6z83HgylrX8fN2wOAT8fNZO+SP2g5oDN3fDTN6nVitkfx9rAn6japs9Sqcyuuuvkq8nLziD0cy6J5i07b9vapt7PgzQXs3LCzdLqrmytD7hpCq4ta8dy4c+P7Lzcvj5lvz8PDw530jCwmj7sdL08PqzYFhYXMmvsxLi4upJ5Io3e3Llw5oHfp/Lnzv8IsNjEcDHJz83ngnlEYxvlz4e66TVt5492PefnpR2kYFmLrcGpF804tGHTzleTn5BH3dxyL5/1UZTvDMBg59TYAfIN8WfDKp6SUfPdPenMqfQb3tWr/7uNzWPLJL6edZ2t1nXvDFhEMHXcDiTEJhDYJ5dMXPyElzrb7vCq5uOA1dgJmTjaGlzdZ776NmZ19yuauAy7DffBQTjz0f5Vex/26IZiZGRQePUrh3j11HHjtMFxdaDj9DoqycnD09eL4C/MorrgfdHSg8Qv34ndtH/JjEjgyeRY5uw8B4ODtQeMX78enXxfyjsRx9LE5ZG/bb4NMzp7h6oL/pDGYWTk4+HiRMus9zKxTbwueV/XH+9+DiRs9pR6jPD8V2zqAC9B5UbhoNmM0J37bTtL36/C77CKavzSO/RNmWbVpeP8wkn/aQMwb39H44RG0nTeNLT3uozg7j4hJwylIzuDYG9+BowMXLX2RnIPHyP7rqI0yqpm+z93F0ZU7iFq0kUYDOtFvxt2suP+tSu18moQQ0DqCvBOZVb6OR4gfXR8YSt6JrLoOuVb1ee4uYlbuIHrRRiIGdOLSGXfzWxX5ezcJwb9V1fm3GXUZqya9Q37Jji92nX3vvD19vRjz6oM8Nfhh8rJzGf/GJOIPx7Jr9fZKbYdMvJHs9Cx+fnshYc0bcu9bD/H8jY9hODjQ7eqezLzzWYIbhfDQx0/Q+/r+rF6wonTZDv0v4uKrevLx43Mxi+3jK3r4s/fw16odbP9xPW36d+bfz49m/sQ3rNoER4ZxzZQRvDp4OqZpct+CJ0mIOkbc/hgGjh/KziWb+HXO9/xr8r+5e+4Unuv3IPk5eTTv0ZaPxs8kreQAt2WfjrZI8bSGPHs3+1ftYNePG2jZvxNDn7+HLye+adUmMDKUK6bcxJzBj2OaJqMXPEFi1HES9scA0O3mgXwz5W3yM3MBiF6/G4DIHm35bPyrpMenAtCiT4d6zOyf8fLzYsqsKUy8diK52bk88tYjHDt8jK2rtlZq6+7pjoe3Bx16dGDBmwus5oVHhhPSKAQff5/6Cv2sPfvqO/Tp3pWrB17Kmo1beeqVObz0n4es2rzzyVf4+fow5pYbKSws4qZxDxHZuCEtmzVh5brNHItN4Kmp9wHw+P/eYPFva7l64KW2SKfWJaWkkp2Tw849+2wdSq3x8vVi4quTmTZ4MrnZuUx6Ywqxh46zY/W2Sm1vnDiC7PRMFr79LQ1bRDB59jQeHz4NTx9P8nLyeHLEdPLzCgC484m7+WP55tPOs7W6zt3RyZGH507nqZGPkxKfQssurZky5xGmXz+1vlM9I+8HJ5O/eSN5K3/D5ZLueE+aQvpzT1fZ1iEwEM9bbqM4Pd1quuHlhc+06WTMfoPi2Nj6CLvWNHpuPOmrtnJi0Rq8+3eh8Qv3cviBV6zaBFw/gKRPl3B8xsc0fuVBIp4ey4HhjwIQMuEG0n5ZT/zsbwibPIpm7z3GnkvHUpyTZ4t0zkrgYxPJWbuZrCWrcO/djaAn/o/ER56vsq1jcCB+o0dRlJZRz1GK1I5z/lIRlxB/gq/vS8pSy6/jJ1b/ScBV3XBtFGzVLm31nyQtXEvWn9Hsn/AaTn5eeLSKACDk5oFk7z1iaVhUTOqv2wifMKRe8/inPEL8aDm0F0eWWXbcMb/voukVXfCOCKrUNnFHNEm7j5zytbpMGMye+b/WWax1wSPEjxbDyvI/9vsumlzZBa8q8k/aEU3ynsr5O7g40bBfB1L2HeX4mt0cX7Mbs9is89jPRv9RV3BkVzR52ZYTz+3L/+CaCddXaufo7MRVo4ewZYmlt0Fs1DF8An1p3aMdhgE/zv6OjOR0orcfYM/anRSXK06ENgtn+JRRfPrf9+ymaOHTwJ+uQ/qwe/kWAPav2Un7yy/GP8L6895/9DX8tWoHpmlZj/tW72DAmOtKl9n2wzpidh1i/oNv4OHnRUjLhgCs/WQpfy7exJFtBzmy7SBBTULYuXgT9sK7gR+dhvRm33LLSXnUml20ubwrfhW29z6jr+HAqj9L8z+w+k8uHXMtAI4uTrTo25GEfTFErd1F1Npdpdv7xk+WsWfxZmK2HSRm20ECmoSwe7HtT1hO5+pRV3Nw10FySz4LG5dt5KZ7b6qybU5WDtvXbCctOa3SvEN7D7F/x7nzi1tCUgo/rVjNgN6XANDz4s6sXLeJY7HxVu2++3k5rZo1BcDJyZG+3bvy0YKFAET/HUNWdtmvlG6uLmRmnVuF69MJCvBnYN9etg6jVl0+6iqid0eVbu9/rNjM9fcOr9TOydmJwWOGsXGJpffosYMx+Ab60q5He1zdXXl72pvs3rCLA9v2cWTPIQrzC0mOTTrtPFur69zb9WiPl593ac+MA9v2ERzRgPY97auA6xAYiNvAQeStXwdA/pYtuPbqjUNIaJXtPW4eRc6iHypN9/3PU2R/89U5V7RwCgnAf2g/0pZZ9s0Za3bgc0V3XCIaWLVL/XEN2TsOUJiSTtKnizGLyo5jMtbsIPWH38nZGcXhia/g5OeFW8tG9ZpHbXAMDsTr6svIXmXZ1nM2bsVjQE+cwqvuXeZ71wjSv/qxPkMUqVU1LlwYhnGTYRgfG4bxg2EYLxuG0aouAqsun97tKUhJpzgn3zKhqJjcvxPw6dXOql3a2l2l/y7KyKYoI4e845buf47e7riEBZbOz4tJxLNN47oPvhaE92pLbmoGhbmW/M2iYjKOJhLWs23VC5zihLzNiP4cWLiOwnOs2hxWkn9R+fz/PnX+VRUkGl/ehQZdWjDi91e4at4UXP296jTm2tC2VwcSjyaUPo+LPk6Lrq1xdHK0ahfZsTnu3h4kxSSWTouNPkabnu0pLiqmqMByWYhhGBTk5bPh+99L2w2feguxUce4fvJIpsx/ki5XXFLHWZ1Zi57tyErNoKBkfRcXFZNyNJHmPazXd4teHUgp9/dJiI6leU/Ld8LBkt4FALkZOeRm5nAi1nKgeuJ4WZdgw8EgODKM+IPH6iyfmors2Y7sCvmnHk0kskL+zXq1J7Vc/knRsUSWfCZaD+xCxEXNmbRyJrd9MBUPf+/SdmkV8g+MDCXRjvKvykV9LiL+aNnJekx0DO0ublfps1DeqQqTxXZSoKuOzdt34u/rg7ubK2ApSjQMDeGPHbut2mVl5xCfWLZew0KDOXDIUsDt36sbK9dtYunKdaRlZJKals7gKwfUWw71wcHhnP99xkrH3p1IKLe9H486RuuubStt7807tcDD24PEmLLvgePRx2jfsyMp8SlW23rn/l3YXtJr4XTzbK2uc3f38sDLzwsXN5fS+UnHEmjcpkldpfSPOHfuQnF6GuSVHK8VF1EUF4tL586V2rpdfQ25K5Zj5uVaTXfp1RvHhg1xatkS3+f/h+fY8eB0bnTC9u7ZgcLUdMzcsuP+/KPxePVsb9WudD7g1jyC2Bc/KX2eua7sMsHijGyKMrPJt8dLgs7ArVsnik6kY+aWbAtFxRQei8Pt4k6V2npd/y+yfvm1rK3IOahGe3TDMF4HPgdCgSjAHfjCMIwb6yC2anENC6Aw1brrf1FmDi4hAadcxq1ZGGnrdlOQcAKAEyt3EHbnVTh4uIGjA16dmsE5crDjGRJAboX88zNz8Qzxq/Zr+DRpgKufFwnbo2o7vDrnGVo5/4KsXDxqkP/hnzczr+0YFg1/Bu+IIK76cDLY+TXe/qGBZKaWdfXLzcrB2dUZr3InoQB+oQHkZGSXFigsbXPxK/f5aNSuKfe/8zC+wX64l4x54ObpRueBF7PxhzV8NeMTVn62lPvfnkpEa9sW9HxD/clKte7imJeVg2+I/2nb5WXl4NvAug1YLimJ2rCHjMQTleY179GW6E17ayny2uETGkB2he09LysX7wr5+4T6W7XLy8rFuyT/PYs382zH0bx309P4RQRz63sPVTmmQdMebTm86a86yKJ2BYYEkp5a1gU6OzMbZ1dnfALOnUs+/on4pBR8faw/754e7iQkp1hN63PJRXzx/S9kZ+dQWFjEnn1RFJcUbpo3acQJbsrTAAAgAElEQVSLTzzEYzNeY9ozM3l22kTcXF3rLQepuYDQQDLKfbfllHz3e1fY3gNCAsnOyKaw3Hd/TmYO/lUcG3W/sicbF6+v8v1ON6++1XXu+7b8RX5OHkPGWnov+jXwJ6hhMIZhX8eDjkFBmBUu+zBzcnAItO555xgWjoO3D4V/Vd6PuQ28nII9e8j59hvSZzyH24CBeN49uk7jri3OoYEUVTgOKM7MwbmK9evo502DcdcTfMc1OHp7Vvl6rpHhZK7fRWFCap3EW5ecGgRRfMJ6WyjOysExONC6XUQYjj7e5O20/336ucQ8Tx/2rKbfxrcD15qmeaVpmpNM07wPuBjoUfuhVY9pQnG5qiqAg4szZmHRKZcJu+tfHH7649LnUQ/PJWPbQdp+9DARD1yPV5eW5ByIqbOYa5dZ2tviJEcXZ4pPk78Vw6D9HVfw53u2H3TrnzBNs7S3xUk1yr+cuI37+GnE8/i2CKdBl+a1FWKdME2TgryyvJ1cnAEoqpi3aZJf4e/j7OJEUUFZu5TjSaxfuJrgxiGMfvkBAEKahuHs6sxfGyy/3v7x83qSYhLpMcS2176bJhSUXJd8kpOLs1U+lobW7ZxcnCv/bYA+t1/JD89/WuV7dbjyEnYusa/LJCqudwCnCuvT0o4K24dTpfwPb/qLD0Y9S1DzcCK6tKj0Xm2v7MaeJfY9QC2AifU27nzys1BxmzjPGBi4ubpYTcsvKMDJ0fpX0/9MnkDHNi2Z+PgLvP/ZN+z86wDNmkSUzi8sLOK1Zx/l72OxTHnqJQoKrQfnFftimqfa3q3XW8XPBVgGNq74PeDg6EBok1COR1fuWXW6ebZQ17mnJZ3g+bueoV2P9jz42mQGDB+If4MAjh20r/HOTNPEzKvwq7mzM2b5z65h4D7serK//qrK13Bq2pSCXTuhqAgzPZ2cn3/EbdAVdRh1LTLNSsf9hoszZhXf+cVZOWSu30nWnweJnPsozmGVLyMOuuMajj3/UV1FW6dM06S4wrZguFTeFnxuHkLa/G/qOTqR2lfTfmG/AVZ9Bk3TNA3DKD3LNwyjkWmaVt/yhmGMBcYCTPXuwlCPZv8w3MryY5Nx8rWuojp6uZMfl1Jle9++HUlbt5u8v8u6EBaeyCRqytsAOAf70eihf3Pkufm1FmNdyopLxbVC/i5ebmTFV69yHHpJK9qNuoxWwy0npI4uTji6OnPHjjnM6zyh1uOtbdlV5O/s5UZ2NfOvKCcpnegfNuDVMJCErQdrI8Ra0ev6/tw1Y3zp84Nb9+PhU5a3m6cb+bl5ZKVZX5+eGp9i1c7S1p3U+LLeNVknMvnj5/VkpKQz6YPpADiUdL11cCqrbR7960ilHh31LS0+BfcK+bh6upUOJlnaLs46b1dPN9IqtGnZpwNRG/ZYXVJSXqOOzVj4VNV337GVjCryd/F0J6NCbulx1u1cq2gDkJWUzs4fN+AbHsjRkrssndSwYyQ/P/VxpWVsbeANA3nwfw+WPt+7dS9evmWXd3l4eZCXm0dmWtWDEJ8vQoIDSM+w/rxnZefQIKhC7yMf79LBN5OSU5kzbwGTxlrutrB5+y527TvA5HF38NFrzzFywlQ+/vIH7hl1Q/0kIWfU7/oBjJ9xf+nz/dv+stre3bzcyaviuz8lLhnPKr/7rY+N2vXowO6Nu6jK6ebVB1vkvnfTbp6+5T8ADBk7jJT4ZHau+7NW8qktxUlJGN7W+2LD3YPi5LJLHZw7dMTt2utwu+LKkgkuGC4uBH37PUk3DAVHR8ujRGF0FA4+tt2/V1dBXDKOFY77HLzcKYivfNxvFhSS/edBDt/7Eu1WzcazaytO/FQ2Xov3pZ3JXL+L/L/jKy17LihKSMaxwnpz8PCgqNzlga4Xtcd7+LV4XWcpTBkuzhguLjRe+TV/D7BZh3mRf6SmhYslwOuGYZS//1QYcKlhGKmAAQwGrD4JpmnOBeYCrA29sVZ7oaSt3Y3LK/44uLlQnJuP4eSIa8Mg0tdXviuEe8uGuDUJIX7+8lO+XqPJN5L2+05SV9jHNZ1ncmzdHvr/7x4c3Zwpyi3AwckRr/BAYjdUrztYwvYovhjwcOnz5td1p9l1PVg2/o3TLGU/jq/bQ98Xy/I3aph/VcziYpJ3/12LUZ697cs3859rygopFw3qRkTrsoGkQpuFs3/T3kqDaB7eaRnAMyiiAUkl1/uGRIbz3atfVHqPw39GkVpS8Is9GENhfgFhzRoSvd1yQltcWMRxG/dEOrh+Nze9MBZnV2cK8izbu394EFEbrT/v+9fsJLh5WOnz4GZhRG0ou/a/QfNwAhuHsOHzFVQlokMkMbsO1U0SZyF6/R6GvuCPk6szhSX5+4UHcmijdVfgqDW7CCqXf2CzUA5tqPpOOWZRMXEVBq0N7xDJ8V2Haz3+2rBh2QarQTR7XN6Dpq2blj5v2KwhuzbuOqfGq/gnul/UkSeTZpObl4ebqysFhYXEJiTSrfOpBxJ8+5Mv6XlxZ/r2uBiApSvX0bKZ5fr9BkEBTLznFpasXKfChR35Y/kmplxTVqjrdnl3GrcqG3MhPDKcvRt3V9reo3dGkZudQ4NGIaXjQoRHhrNgpnUPs+5X9WTlV1V/D55uXn2wZe7uXu4MHjOMj55+n+Ii+/ouKdi+DYfAKeDiAvn54OiIY4MGFPxZdlexgr/2knLn7aXPXfsPwG3AZaQ99SRgKVQ4Nip36WdREYVH7Ou451Qy1u+kUch9GK4umHn54OSIS3gwmRtOU2QrLiZ79yEKyv2o6doiApfGISR/trQeoq4buZu34xg8yepv4RQWTO6WsmJb3q59xAy9u/S555X98LyyPwlTnrFFyCJnpaaXilwPtAHuKvf4F+BV7nnfUy5dBwoST5CybCu+fS23LfTt14nknzaQH5dC+IQhuDcPB8C1cQNCb72CE6t24NooGI92TQi940qr1wq8ridenZqx/4Fz46QdICcxjSMrttGwj2VQooaXtif6l81kxaXSedw1+DYLs17AKP0PAMX5hWTFpZQ+8tKySqedC3IS0/h7ebn8+7bn0C+byY5LpeOp8q9wPX/ktZfg3dhyVwrf5mHkncgiLdq+RtnOycgmLupY6WPtN7/R7KJWpYOSdezfhcXvWkYN9w32Y9ikEYClC+2qL5bTeaDlRCW8RQSpcclEbd2Pg6MDkZ3LLhHoPLArSz+wjDadm5XL6gUr6Ha1ZUR+w8GBkGbhrPt2Vb3lXJWMxDT2/Lq19DalrS7tyJ+LN5EWn8qAMdcRXLK+1326jDb9ygYqa9mrA6s/XAxAQKMG9Bp1Oft+/xP/iGDC2zam963WXWQtl4nYz91ETspMTGPfr9toXnKb0uaXdmD34k1kxKfSZ8y1BJXkv+nT5bTsVzY4V7Ne7Vlfkn/7q7vj38gy+npQ83ByTmSSVGF7t1wmYl+XyZyUnZFNTFRM6WP518tp3aVsYNqLB1zMt3O/BcC/gT+3Tr618osYVDmuh2EYVU63R0GB/vTv1Y0NJQeoG7bs4Ip+vQgJDuTDLxZy6G/r7v1LV65jz74onp/+YGmOrVtEsvdAdGkbBwcHOrZtWX9J1IOTd9Y5+f9zTXZGNsejjpU+Vn79Ky3Lffdf1L8ri9613CXGr4E/N00aCUBhQSHLP19K14HdAIho2YjkuGT2b7W+NWxku0iid1U9vtXp5tUHW+Xu4OjAfS8/yNL5i1m76PdK822tODWF/A3rcelq2a+7XNyNvN9XU5yUhPu/R+AY0QgKCihOSix9mJkZmPn5FCdZBurO/vYbXLt3B2fL5TbO7TuQ8925cSlBYeIJ0lf8gfelln2cz6WdOfHLOgriU2gwdhiuzSx3CXNr1RjHkp43jj6eGA4OZG2x/Kjl0jiEoFFXkbF6Oy4RDXBv25SgW/9lm4TOQlFyKtmrN+DWowsA7j26krV8DUUJyfjcfiPOTSKgoICihKTSR3F6Jma+ZZrIuaamPS5eBFabpml1kblhGF6maWaW/Pua2gquuqKmzaXpE7fh2a4Jzg38ODjlHQCCh/Uh72gChRnZdPz2KVwjggkfd13pcvvGzQTAt08HvDo3w3BxZtfw/1a6ds7erZ7+Ib2mjySoXWPcg/1YNe19AFoM6UXG0cTSk/DgTpGE926He4A3YT3bnFWvBHuyZvqH9HhsJAHtGuPRwI/fH7bk33xoLzJjyvIP6hRJeK92uAV6E9qzDXEl+Yf1akvfF0dzfN0eYtfvZcsr39osl+rKSE5n/pPvMfI/d5GTkc2etTvZ/fsOAIIaNaD3Df35afZ3FOTls3DWAkY8ejuD7x+OX2ggb014CQC/kADunzOVjNR09q7dSfzhWH6bv6T0PT5/9iNue2o014wfhqefN/P/8x5ZdtD9/uvH3mfwo6MIb9sY72A/vnx0LgBdhvQmJSaRxOhY4vbHsGbeEoY8bukS/9u7i4g/EIN3sB/3ffEf/BsG0f+esq+qj+9/zeo9mnVvw5JZVV8bbGs/PPYB/3p0JKFtG+MV7Mf3j74HQKchvTkRk0hSdCwJ+2PYMG8pVz9uOWlf8+5PJBywnMhG9mzHsP+NIXrdbg5t2MuvsyofrDbt3ppfZ31df0mdhbTkNOb8Zw7j/juOrIwsdqzZwdbVltvFhkSEMGj4IL6c/SX5ufk4ODrQ97q+BAQH0G9wP+L+jiPhmKUnUuOWjek+qDuNWjSi+6DubFphf4Wrip6YPJ6Zb89jX9RhklNS+e9D9wLwy6+raRjagMjGDdm49U9274+iIL+AD2Y9YzX45g3XDCIuIZH3Pv0GP18f4hKTGHvL+dN1OCsrm0VLLbf4XvjzMkYNH0yAf/UHbrZH6clpvP/kXO56cjTZ6dnsXPsnO363/NLeIKIB/YcPZOHsb8jPy+fLWZ9z2/S7GP7ATQSEBPLyhBlWr9W8YwuidlZdmDjdPFup69zdvdzpelk3mnduyYovlrJt5dZ6y62mMmbNxGvsBJyaNcchIJCMmS8D4DZwEMXxcRTFnH5cjsI9u8n88H28759I4dGjmLm55C45d8Y6O/rYHMKn34l720icg/04+shsAPyH9iU/JoG86GOE3Hcj3n07k7ZsE4WJJzj6yFsAODXwp+WC53BpGEyD0UNKX/PQfS/ZJJezlfzs6wRMGoNLq+Y4BvmT9PSrAHhdfRmFx+MpOHKujNl37ik+N37nOK8YNf0VwjCMFljuKnKyt4YBjDBN897qLF/bl4qcS3Y6u9k6BJtyvGDXvMU6pxxbh2BT/jjbOgSb8qj53afPG1uKzr3R2mvTD5tm2joE23K+sO9UMvLi/7N1CGIjs1uk2ToEmzp24NwuFJ4tP/9sW4dgU5E7lp3Xp/bvR9x6Xp7Z3BMz327XW416XBiG8S6WO4vEAeUv+gsFqlW4EBERERERERGprppeKnID0MQ0zbjyEw3D+HfthSQiIiIiIiIiYlHTwsUPQG4V0zfUQiwiIiIiIiIids2+7jd0Yahp4WIy8JxhGBvLTTOA6wD1uhARERERERGRWlXTwsXXQHugI1BUbnrbWotIRERERERERKRETQsXLYEWJ299epJhGH1qLyQREREREREREYuaFi5mYLmDyMEK0y/s+z2JiIiIiIjIBUFjXNS/mhYuOgE3G4ZRvnBhAJcAHWotKhERERERERERal64cAP2AHGAWTLNAFrUZlAiIiIiIiIiIlDzwsXzwCHTNAvKTzQM48PaC0lERERERERExKKmhYtMYL5hGDmmad5pGEZ34FLgrdoPTURERERERMS+mIatI7jwONSw/cdAISWDcZqmuQmIAd6p5bhERERERERERGpcuDhkmuYtQHS5adnA0NoLSURERERERETEoqaFi+OGYRiUDMxpGEYI8DSwt7YDExERERERERGp6RgX84CvgSaGYVyDZXyLeOC22g5MRERERERERKRGhQvTNKMNw/g30B1oDDwHbKh4lxERERERERGR81GxrQO4ANXoUhHDMJ4yTbPYNM0Npml+aZrm70C4YRiP11F8IiIiIiIiInIBq1aPC8MwxgBhwGWGYRRVmB0A3AI8W8uxiYiIiIiIiMgFrrqXiswDZgN+QGSFecVojAsRERERERERqQPVKlyYpplf0uviMmAb4AUYJbNDgAnA4jqJUERERERERMROaIyL+lftwTlN0zQNw7gaWE7J7VDL2VmrUYmIiIiIiIiIUPPboTYCGgB9gc2macYYhnE54FzrkYmIiIiIiIjIBa9GdxUBdpmmmQQsAm4vmbYaeLVWoxIRERERERERoeY9LpwNwziIZTDOA4Zh/Ab4UPMCiIiIiIiIiMg5p+K4CVL3alS4ME3zScMwvgQOmKa53jCMJKAL8HWdRCciIiIiIiIiF7Sa9rjANM3d5f79G/BbrUYkIiIiIiIiIlJCl3iIiIiIiIiIiN2qcY8LERERERERkQtVsWHrCC486nEhIiIiIiIiInZLhQsRERERERERsVsqXIiIiIiIiIiI3VLhQkRERERERETslgbnFBEREREREammYlsHcAGq98LFehe3+n5Lu+Fh2joC23oiY7OtQ7CpEf4X2ToEm0qn0NYh2FQ+jrYOwWbei8izdQg2dUOPqbYOwaZcjQu7c+fnW2bZOgSbCWp6ha1DsKnw2Fxbh2BTwR6+tg7Bpk4kZtk6BJvKsXUAct65sI8mRERERERERMSuqXAhIiIiIiIiInZLY1yIiIiIiIiIVJPGuKh/6nEhIiIiIiIiInZLhQsRERERERERsVsqXIiIiIiIiIiI3dIYFyIiIiIiIiLVZNo6gAuQelyIiIiIiIiIiN1S4UJERERERERE7JYKFyIiIiIiIiJitzTGhYiIiIiIiEg1FRu2juDCox4XIiIiIiIiImK3VLgQEREREREREbulwoWIiIiIiIiI2C0VLkRERERERETEbmlwThEREREREZFqKrZ1ABcg9bgQEREREREREbulwoWIiIiIiIiI2C0VLkRERERERETEbmmMCxEREREREZFqMm0dwAVIPS5ERERERERExG6pcCEiIiIiIiIidkuFCxERERERERGxWxrjQkRERERERKSaijXKRb1TjwsRERERERERsVsqXIiIiIiIiIiI3VLhQkRERERERETslsa4EBEREREREammYlsHcAFSjwsRERERERERsVsqXIiIiIiIiIiI3VLhQkRERERERETslgoXIiIiIiIiImK3zpvBOZ1cnek3fST5Wbm4+Xqw+oUF5GfmVGrn5uvJJeOvxcXLnRVPzLOa16RvBy6dciOL7nuT9Jik+gr9rDm6OdNr+kgKsnJx9fVg/fMLKKgid1c/T7qMuxZnb3d+f3xeFa8ELQb3oP1tl/P9Tc/Vddi17qKuHbn19hvJyc7l8KG/ef/dT6ts16ZtS958ewbNmjVl8S+/8n/3Tyc/v8DqdaY//iCzXnmHdWs311f4p+Xs6sywR28lNysHD19Pvp/xGblVrON2Ay6i/WVdMBwc2L9uF9t/2XjGeW7e7oyaMZ62/TqR9Hc8Cx5/n8PbDpQuc+9Hj1q9x+HtB3l52GN1mG31NO3UnL43DyI/J5+EI3H89vHiKtsZhsH1U0cC4B3oy/czF3AiPgWAlpe05dbnxuIfGsCO5X8w/4l3ycvKrfQaD370GJt/XMu6r1fWWT6nUpfrHsDdx4On176Fu7cHAHPHvcyfSzafcZ5dcHXB975xmNnZGN7epL81FzM7+5TN3QcNwPOGISTdN9kywdEBv2mTcR/Yn6LYOFKf+R8F+w/WU/D/XMtOLbly5JXk5eQReySOn+b9WGU7wzC47eHbAfAN9OXTVz4lJT4ZgIgWEdwwbjgJxxIIaxLGx/+bR3KcZd7Dbz1M38H9rF5rzmOz+fmTn+swq+pr3qkFg26+kvycPOL+jmPxvJ+qbGcYBiOn3gaAb5AvC175lJSSz/6kN6fSZ3Bfq/bvPj6HJZ/8ctp555p1m7byxrsf8/LTj9IwLMTW4dS6rl07cvudI8jOzuHQob95951PqmzXtl0r3n7nJZo1b8IvP6/g/nsfJT8/H4Bevbvx6mvPEB4exi8/L+ehSU+SmZlVn2n8Y90u7szdd48iJzuHqOjDzJ7zUZXt2rdvzQfvz6Jli0gW/biUMWOnlOYfFhbCo49M5ODBQzRt2ogff1zGr7+tqccs/pnOXTpwy+03kpOTw+FDR/nw3c+qbNej18X8b+aThIWHsHTxbzzy0NNkZVr2Ey1bNWPCxLuJOXqcppGNeOHpWcQej6/PNP6xiy/uxJ133kxOTg7R0X/z9ttVH9e3a9eKd9+dSYsWTfnpp+WMH/9w6bovb+HCeXz99SLmz/+6rkM/b5i2DuACdN4ULi5/7i4OrdrBvkUbadq/E1e8cDc/PfBWpXZ+TUIIbBVB7olMq+keQT44e7gR1qVFfYVca/o9dxdHV+7g4KKNNBrQiQEz7mbZ/ZVz920Sgn/rCPIq5H6SR4gfFz8wlNwT58YOuzw/f19mv/MiVwwYTlZWNnM/mEl09BF+W2G983VwcOC6IVdy8/AxNG4SwZffvs9NNw9l/seWL2pPL098fLzo2fsSmDnXFqlUacSzo9mzajtbf1xP2/6dufn5MXw08XWrNg0iwxg85WZeHPwopmnyfwv+S3zUcWL3Hz3tvCvGD2XHko0sm7OQayffxNi5U/hvv4nk5+TRokdb3hv/CifiUwFo3aejLdKvxNPXi3tencizg6eRl53L2DcmkXA4lt2rd1Rqe93EG8lOz2bx2wsJa96Q8W9NZsaNj+Pi7srAO65m3iNz8An05fYXxjP84Vv47Mn3rZbvO2IQjds3ZfOPa+srPSt1ue4Bet88iE+mzCYv01Kw2b9+V+nrnm6ePfCb8n/kbdhEzoqVuPa8BL9pk0l98tkq2zoEBeJ95y0Up2eUTvO46gqyFv5I+ux38X98Gr6THyBp/IP1Ff4/4uXrxeRZk5l03SRys3OZ+ubDHD90nG2rt1ZqO+LBm8lKz+SbOd8Q0SKCaXOmMe2Gh3F0cuSxdx/nsZsfIyU+mdZdWvPI248yddgUPH09yc3O49GbHqUgz3Jwe88To9m0fFN9p1olL18vJr46mWmDJ5ObncukN6YQe+g4O1Zvq9T2xokjyE7PZOHb39KwRQSTZ0/j8eHT8PTxJC8njydHTCc/z1K0vvOJu/lj+ebTzjvXJKWkkp2Tw849+2wdSp3w9/flnfdeYUDfYWRlZfPBR68RffAwK1b8btXOwcGBIUOvYvgNd9OkSQTfLvyIm0cO4+N5X+Lh4c648bfzwH3TCQ4O5PU3n+fJp6Yw9aGnbJRV9fn7+/HRR6/To+fVZGVl8+n82Rw8eIily1ZZtXNwcOCG66/husG3Etm0MT//9Cm33jKcDz78HIBZrz7Da6/NZd36P3B1deXAvnU0b9mTgoKCqt7WLvj5+fLmOzO46rKbyM7KZs77L3Mo6ggrf7XeT7t7uHP32Ft4aOITBAUH8vJrTzH9P5N47OHncHJy4oNP3+DfQ+4iLjaBrt068e68WVx3xUgbZVV9/v6+vP/+q/TpM5isrGw+/vgNDh48xPLlq63aOTg4MGzY1QwbdgdNmzbihx8+ZtSoG/jooy+s2t1558107tyOr79eVJ9piNTYeXGpiGeIH22G9iJqmeXA5ciaXbS4ogs+EUGV2sb9GU3i7iOVpmcnpXNw6ZY6j7W2eYT40WpoLw6X5B7z+y6aXtEF7ypyT9gRTVIVuZ/UdcJgds3/tc5irUu333kTf+7YTVaWpYq+5JffmPh/Yyu1MwyD12bOJSkpha1b/uT31espKiq7oVFWZharV64nOSml3mI/E98G/lw8pA87l1u2z31rdtLx8osJiAi2ajdw9LXsWbUd07TUgPeu3sGgMdedcd6+NTvZ8sM6ju46xEcPvo6nnxehLSMA+P2TpWxfvInD2w5weNsBgpuEsGPxRmyt36jL+XtXNHnZlhPqHcv/4OoJ11dq5+jsxJWjB7NtiSXm2KhjeAf60qpHO0Iiw5j/2Fyit+5n+7LN/DDrS1r36mC1fHDjELwCfYiLOl73SVWhrte9k4sTbft2InbfUfat3cm+tTsxi80zzrMHDkGBeFw5kNw16wHI27wFt769cAyt+ldl71tvJus764OynBUrKdjzF8Un0shauAiK7f/mZv+65V9E7Yoit2Tb37R8Ezfee2Oldk7OTlw/5nrWL7b8fWIOxuAX6EeHHh1o36MD3n7epb0v9m3bR0hECB16dsTVzY03p73Brg072bdtH4f2HKKwoJCkWPvohXj5qKuI3l2W/x8rNnP9vcMrtXNydmLwmGFsXLIBgGMHY/AN9KVdj/a4urvy9rQ32b1hFwe27ePInkMU5heSHJt02nnnmqAAfwb27WXrMOrMnXfdzI7tZfv9X35ewf89NL5SO8MwmPny2yQlJrPljx2sXrWOoqIiAJo3b8qkB59g86Zt/PzTcmY8/xp9+/Ws1zz+qTGjb2Hbtp2l+f/40zIennp/pXaGYTDjf2+SmJjMps3b+PW3NaX5A7Rp0wJvby8A8vPzcXFxwdXVpX6S+IduvfPf/LljD9kluS9bvJL7J42u1K5Z8yZMm/QUWzbvYMnPv/LyjLfo07cHAD17d8Pf35e42AQAtv7xJ40aN6TXpZfUXyL/0D33jGJ7uW3/559XMGXKvZXaGYbBSy/NJjExmc2bt7Ny5TqrdQ8QGdmYoKAA9u+PqpfYRc7GWRcuDMOo/E1Rzxr1bEtOagaFuZZfh8yiYtKOJtKoZ9sq2588gK9iRl2FWGca9qqce/rRRMJPkTunOPFoO6I/+xeuozAnr65CrVOX9uvJ30diSp8fPHiIS3p0wcnJulNRUVFR6a8IhmGQm5vPN19VrjAX29EJTMue7chKzaCgZB0XFxWTfDSRlj2s13GrXu1JPppQ+jw++jgterY747z9630nHswAACAASURBVHeXTs/NyCE3M4cTsZYTmtTjyaXzDAeD4Mgw4g4eq+UMa65Nr44klcsnLvo4zbu2xtHJ0apd047Ncff2ICkm0apt657tObrnMFlpZb2PTsSnkHK87OTEMAwuv+tals79oQ4zOb26XvcdBnalyUUteHLla4z/YBqe/t6l7U43zx64du1McVo6Zl7Jd1ZRMUXH43Dt2rlSW4/BV5O9dAVmrvX3W+mygFOTxqS//V6dxlwbOvXuRPzRsq7Mx6JjaHtx20rbfotOLfDw9iAhJsGqbYdeHfHw8sDLzwtXN9fSeQnHEmjapgkp8clW339d+3dlaxW9OWylY+9OJJTL/3jUMVp3rZx/85L8E8vlfzz6GO17diQlPsUqx879u7C9pMfG6eadixwczovfp6rUr38vjpTf7x84RI9q7ffz+OpLy35/5869pKamlbY9fjyemKOx9RD92btsQB8OHz5a+nz/vih69bq4Wvl//sXC0vnffvsTM2c+TUhIMDfccC3PPT/L7i+VubRfD44eKTsWiTpwiG7dK6/73Tv/4sSJsvUbF5vAsRjL+vX28cTP3xd3d7fS+TFHj9O2Xas6jv7s9e/f23rd74+iZ8+u1Vr3CxZ8XzrfMAzuv/9uZs2ynx7GIqdT7T2aYRh3G4ZxzDCMQsMwikoexcA7dRhftXiHBpCban35Q35mLp4hfjaKqP54hgSQVyH3ghrm7tOkAa5+XiRsP3errWFhIaSknCh9npmRhaurC4GB/lW279CxDR/Nf5MGIUH4+NjXCVlFvqEBZKVmWE3Ly8rBNySginaZ5drk4tvA/4zzymsQGcaBDXtITzxRaV6LHu2I2rT3rHKpLX6hAWSW+5vkZuXg7OqMV4WTa7/QAHIysikqKLRq6xdSOffIi1qy8pOycTIG3nk1K+cvoaiwqFLb+lLX63774k1M7XgXr970XwIjghn33lQMwzjjPHvgGBxMcVqa1TQzOxuHoEDrdg3DcfDxoWDPX1W+joOPD163jMBz+DAMT686i7e2BIYGkl5um8jJtGz7PgE+ldplZ2RTWG7bz87MITAkgL+27CUvJ49hYy29lPwb+BPcMBijipPcnlf1ZP0v6+oom5oLCA0ko3z+JZ997wr5B4RUzj8nMwf/Cp8dgO5X9mRjSc+UmswT2woLDyElObX0eUZmJq6urqfc73fs2Jb5n80hJCQYH9+q9/vdunXmvXfn10m8tS28YSjJVvln4erqSlBQ5W0coHPn9nz91XuEhjTAt1z+zzz7Kn/8sZ21vy+ibZsWvPHm+1Uub09Cw0JITS13zJdpOeYLCDz9sW/Xizvx0fuWS2Q2b9xOTnYu4++/E4AGIUE0jAjDwcF+9nOnEh4eSkpKuXWfcfp136lTOxYseIeQkGCrdX/vvXcyd+58CgsLq1xOTq/4PH3Ys5qU4l8BHgBaAs3KPZ6vg7hqxDTN0h4HJzm6OFNcYLsTjvpzityre7JlGHS44wp2vHfuDTpWnmma5Jb7NfVkN8eCgqq/jI/FxPHNV4to0rQRb8yZUS8x/mOmWXqt+UlOLs5WJ+OWdli1c3JxKtsOTjevnL63X8l3z1d90Nbpym7sWGIf17lX/Js4uzgDVC4ymGZpb4XybYsqfDe4+3jgHxrIjhWWSzIi2jShIK+A2Cgb9y6pp3UftWkvr496hpDmDWlaYZyf082zKdPErPC3wcUFyudmGHgNH0rmF1+d8mWKs7PJ27qdgr1/ETjjKRwbBJ+yrT0wTcgv911Xuu1X2KZNE/Iq9DBxdnGmsKCIE0knePrOp+jQswMPvTaFQTcOIqBBADEHjlq1d3B0ILRJGMeibd/L6iTTNMnPreKzX+EzYWLdDiwD3Vb8jrDkGMrxKnI83TyxPdOE3NyywZRdXUr2+6c4CYs5FstXX35P06aNmPP2i5Xm+/p6E94wjMW/nBuXzJqmSU5OufxLj3uqHpvi6NHjfPb5d0RGNuaD914tne7i4sL69Vt4YcbrPDLtAW65pfKlV/amYu4uJbkXnuKYD8DH15uwhiEsW7wSgKTEZG4bMZ6efS7hrbkvctPIYYSEBnNgX3Sdxl4barruY2KO88UXC4mMbMzcua8A0KFDG3Jz89i3z/4HpBY5qSaDc24BvjdN02qvbxjGG2da0DCMscBYgOH+3enp1bJGQZ5JZlwqrr6eVtNcvNzIjE89xRLnj6pyd/ZyI6uauYdd0or2oy6j9fBLAXB0ccLR1Zm7dszhw84Taj3e2vLvEUOZ+fozpc//2LQdP7+yX9y8vDzJycm16iJYXmrqCX5YuJikpBQ++9LmnYZO60R8Ch4+1uvY1dONtArr+EScdTtXT3fSSkbQP928k1r36ciBDXusLisor3HH5nzzVNWjVte1ntf3444ZZdcuR23dj4dP2a/jbp5u5OfmkZVm3b01NT4F9wp/OzdPt9LBRk+6cvQQFjzzYenzQXddQ5cru3P9FMsgXe7eHjTp0IwmHZrx+X8/qLW8zqS+1j1ARlIaW39ch394EIe2Hqj2PFspSkzC4f/Zu+/4KKr1j+OfSUhCGgkJSSiBEDqhF2lKB710EJRiuaIU9YcFRa+AvXC5VlRExYIFCyo2kA7SewtVSkJvpkF6gczvjw2bbApJIMmu8H2/XqPMzNnZ59kzuzs5e84Zb9seEk4e7lyKzh7u49q0MR4D+uLe61YADBcXDDdXKi/8hbO9suZEuXiRjP0HiH3uFYLmfIVL4zAurbCd3M6eut7elXFTH7Gu/7X9L7x8svN293InLTWNxAu2Pe9izsbgVcH29XH3cid2l2X4197Ne3luxLMADBoziJhzMYSvt53ctnHbxuzZuLtE8ymuToO68ODU7HH7B3fY5l8+K//c7/3YszF45nnvuxOX69wPa9uYvZvyn3T2Svuk7A0dNpD3pmf/VrZ58w58fX2s617eXpbv/bgCvvdjz/PrLwuJjo7lh5/yDgsb9+goJj6T/+S+juCuuwbz8YfZDS4bN26nYsXs/L29PElJSbEZ+pJTbGwcc+fOJzoqht9/+8q6/b13X2XauzPZt+8gaenpzPzoDVat2sDJk/aZ2yk/Q4b24413X7aub9uy07burdd88QUe48Fx9/HCRNsfqjau38bQgQ9k7bdM0rl2tf3n8cpt+PBBzJiRHfumTbbnvnfWuV9w3Z/n558XEBUVyy+/WK51/u//7qdfv1t58cWnAEvDXYsWTWjZsglPPPFCKWYjcvWK03AxGrjfMIzFObYZwL+Bl/N/iIVpmjOBmQBv1ri7xCeSOL5hH7cGPUA5NxcupmXgVM4Z76r+nNyYf9fg68mp9fvw/N8DOJd34VJqdu6ni5j7uZ0RfNvlaet67b5tqNO3LYsfLLQ9yq4WLVzOjluyL6hv69WVhg2zG8Rq16nJxvVbCp2rInzHHs6ecexbXx3csJcR/x2Li5sLGVnnd8WqlTi0aZ9Nub/W7iKwdlXremCtKhzcuK/QfQBBtatRqUYg675bnm8M1RuHcnLPkZJMq1jCl23lpd4TrOvNuremWv0a1vWgWlU5uHk/Zq76PrbbMoFnpeBAorPGugeFVuXXd+ZYy3Qa3oPNv60hKcfddn587St+z1HmwRlPsvWPDaz78c8Sz+1KyqLuc8q8lMnJfUeLvc8e0rbtwOmZJ8HNFdLSwdkZ56BA0nbsspZJ3/cX54b927ru3r0LHt06EzM5nzsGZGaScfAQmVGONQnjpqWbOBSe3Vh0U482hNQPsa5XDa3G3k1783zWRew+TEpyCkHVg6xzYlQLrcY3b9neJtrdy52BYwbx6UufknnJ9hjtbmvP8p+WlXRKxbJ12WYm9M6+00vrHm2oUS9n/lXZn0/+kbsjSE1OIbB6kHVOjKqhVZnztm3+bW5rx8of8//cu9I+KXsLFyzjlg7Z7+9evbrbzEdQp05N1q/bXOj3/o7tu/Pc8vK+kcP48YffiYvNO0zSUcybt4StW3da1/v26UmjRg2s63Xr1mLNmk2F5r91WzinTp+1rt95R3/GPTIJgNmzf+K+e4fSpk0Lh2q4WLzwT3Zuv9263vNfXWkQlt0DsFadmmxav7XA3O/+9x388uMfBf5h7+XtaWnYmDQ1z+SVjuCPP5bRtm1v63qfPj0Iszn3Q1m7tvC63759F6ez6n7ixFd59dW3rfu++eZD5s6dz9dfF9xDUcTeijNU5CHgQ+BojuUIYPdmueSoC0Qu30GNWxoBEHJLIw4t3ELiuThaj+lNxVpVbB9gcMWx2o40jrswKVEXOLp8B8E3W3IPvqUREQu3kHQ2juZje+ObT+5Z/wEgM/0iSWdjrUvahSQuZW1zZAnxiRw+FGld5nz7Cy1bN7NOTNStR0dmTLe0KgcFBfD0RMsvls7OzrRomX1Lz563debjD7/Kc3zDMBzmPEiIusCeFduttyJtcEsTwhdt4sK5OLqP7ktgVh2v/WYZDTtlT0xYr30jVs5aWOg+/+qB3DyiO/vX7MIvOIBqDUO45e6eNjE0vfUmdtpxmEhKQjJnI05bl/VzVxLavK51Qr7GnZuz5BPLZGs+Ab70H38nYOk+vub7ZTTp1hKAKnWCiTsbQ+T2gwDccmc3UpNSSU9Lp1JwIM173kSd1g1Ijk8i7mysdbmYfpGkC4kkx5fthGWlXffNe7XFv3ogAEG1q5J8PpG/I88Uus8RZMbGkbpuA+VbW+rW7aZWpKxcQ2ZUNF4j7qRcjeqQkUFmVLR1MeMTMLO2AZSrVRPDy/KrvOHlCc7OpO/eW+Bz2kNyQjInI05alxU/Lad+83rWc79Vl5b8OvMXwDJXxYgnRgCWLtNLvltM626WGfKr161O9NloDmzPbtR2cnbi8TcfZ+HshayZt5rcajWqRcRu+859lJyQzOmIU9Zl5U8rqJsj/+adWzLvE8tEg76BFblzvKWX1MWMiyz7bgktu7UGILhudWLOxnBwu+2tQUPDQonck3+OV9r3T3F5MvICJyX/B4mPT+TQwUjr8u23P9P6puzv/R49OzP9Pcv8DEFBAUycbGnwcnZ2pmWrptbj3Pavrnw4I7uH3T333kFiYhKpKamEhATTu08P2rVvVYaZFU18fAIHDkRYl6++/pE2OSakvO22rrwzzdKDtHLlQF54/knAkv9NrZtbj9O7dw/eey+7x0l4+F5aNM++o1Zqaio7dzpWTyPLNd8R6/LDd7/SslVTa+5du9/CR9O/ACxzVUyYmN1La/g9t5OUlExKairVQ6pxW+9utGnX0rrf2dmZaR+8xlez5vDbz445bDo+PoGDByOsy+zZP3HTTc2t+d96a2feffcTwFL3zz47HrDk1rp19vd/r17dmD7d0mv0/Pl4Tp06a13S0tKIi7twxV4rYivTuD4XR1acHhf3Ax2AraZpWpv0DMMYXeJRXYWlk2fRedJwAhrWwDPAlyXPWL68GgxoT/zJKOKyLriDmoZSvX0YHn7eBLdtwMlNlos4F8/yhA26GYBGd3RkxxdLSYlNyP/JHMzqSbNoP2k4lcJq4B7gy8r/WHKv07898SeiOJ+Ve0DTUKp1CMPdz5uq7RoUuVfGP0F0dCwTn36F16ZOIj4+gdWrNljv5129RjXuHD6Q996ZiX8lP2Z9/T6xsXGsXrWByIhjzPr0W+txnJ2d6T/wXwQGBTBgUC+OHT3ByRP2/9Xh+8mfMnDiXVRrGEKFAF++nWiZAbpV/5uJORnF35FnOHPwBKu/XMTtz94DwPJP5nP2kGXG9YL2VQjw5bHvX8CvWiW6PdDH+nyfj5tm8/x12jRgwTTHaYVPiInnuxc+Y+jzI0lJSGb/ut3sW2Pp5u5fPZD2t3dm4YxfyUhL57dpP3DHxHvoM24wFSv78eFDbwLQ/vbO3Dv1QZtZ95Pjkxjf6gG75FSQ0qp7sNy1ZMT/xnJw/V4ObdzLgmk/WZ/3Svscxfk3puHzf2MpV6c2zv5+nJ9qGbvr3rMbF8+c5eLxE1d8vPe9I3C7qRWpa9ZzKTbO+nhHdiHmAh+/8DGjXxhNUkIy4evC2bHGcteLwOAgut3ejZ8++In0tHS+fedbRk66nzsfGYp/ZX+mPvhfwNLLonXXm6jbrC5Lvl/CtpV5bwVep2kdDu92vLHP8TEX+OyFmYx8YRTJ8cnsXreL8DWWX6EDgwPpPLgbv86YS3paOj9M+457Jo1k8CN34hfkz5sP2XYTr92kToENM1fa90+RlJTMvCWW+Rp+XbCUEYP74Vfx+pm0PDoqhqeffImprz9L/IUEVq1cz4oVawGoERLM8OGDeOetj6hUyY+vv5lBbEwsq1ZuICLiKJ9+Yul5M2z4IN6bPsXme+D8+XjqhLaxS07FERUVw+OPP8vbb71EfHwCK1asZekySwNkzZDq3H3XEP73+gcEBPjxw5xPiI6J5c8Vazl0+AgffZw97POef49j0sTHaNo0jAoVvPhs1ndERh6zV1pFEhMdy+SnX+Pl/z5DQnwia1dtZNWflkmEq9eoxh3D+jP9nU/oN/A23nz3ZZv6vXAhniZ1OuLl7Un3np1o3rIJ3341lxXL1tgrnWKLiorhiSde4I03XiA+Pp4//1zH8uWW+ENCgrnrrsG8+eYMAgL8+e67j4iOjmPlynUcPnyEmTO/tnP0IlfPKGorvGEYHwATTdOMz7W9smmaZwt4WB6lMVTkn8Ljhs3c4oX4LfYOwa6GVmxeeKHrWCqO1/2yLJXHufBC16mJVaIKL3Qde/CUh71DsCs34/q9JWdRfLdtWuGFrlOVavYsvNB1LCk9tfBC17EAD5/CC13Hzqc59m1lS1tKyjEH//3+2jxf867r8i+7l49+47D1VpweFzuANwzDWJdjmwH0AoaVaFQiIiIiIiIiIhSv4WI4UAWoD1xuYTKAsJIOSkRERERERMQRZXJddrhwaMVpuPgvsNY0TZt+b4ZhtC3ZkERERERERERELIo88NQ0zWX5NFpUBlqUeFQiIiIiIiIiIhSjx4VhGJmQb5+YQ8BHJRaRiIiIiIiIiEiW4gwVeQWYhe38FkOBtSUdlIiIiIiIiIgIFK/hYqppmik5NxiGMR34A+hSkkGJiIiIiIiIOCJNzVn2itNwcZNh2NzW1RloDzQt0YhERERERERERLIUp+FiCXCW7AamTOAcMKykgxIRERERERERgeI1XPzbNM05uTcahvHvEoxHRERERERERMSqOA0X3oZhHAWq5PO4L0ssIhEREREREREHlWnvAG5AxWm4eBsYA2wBLmZtM9BQEREREREREREpJcVpuFgK/GqaZmrOjYZhfFOyIYmIiIiIiIiIWBTYcGEYRqdcm74CXjEMY16u7UOAR0s6MBERERERERGRK/W4mAo0A6KxHcYzJMe/DSAINVyIiIiIiIjIDSDTeqNNKStXarh4DjhhmubBKx3AMIz+JRuSiIiIiIiIiIhFgQ0XpmkuL8oBTNP8veTCERERERERERHJ5mTvAEREREREREREClKcu4qIiIiIiIiI3NA0w0XZU48LEREREREREXFYargQEREREREREYelhgsRERERERERcVhquBARERERERERh6XJOUVERERERESKKNPeAdyA1ONCRERERERERByWGi5ERERERERExGGp4UJEREREREREHJbmuBAREREREREpokxMe4dww1GPCxERERERERFxWGq4EBERERERERGHpYYLEREREREREXFYmuNCREREREREpIg0w0XZU48LEREREREREXFYargQEREREREREYdV5kNF5meeLeundBjuhou9Q7CrV71vsncIdrWXDHuHYFcGhr1DsKskLto7BLv575kAe4dgV35ON27dAySZN/ZnX6WaPe0dgt1EH11q7xDsanrL5+0dgl2l3dhf+7hoLIFIidIcFyIiIiIiIiJFlGnvAG5AGioiIiIiIiIiIg5LDRciIiIiIiIi4rDUcCEiIiIiIiIiDksNFyIiIiIiIiLisDQ5p4iIiIiIiEgRmei2MWVNPS5ERERERERExGGp4UJEREREREREHJYaLkRERERERETEYWmOCxEREREREZEiyrR3AHZkGIY78DqQAFQE/mOaZnw+5XoBfbB0llhhmuZP1/K8argQERERERERkaKYASwyTXOOYRj/Aj4GhucsYBhGPeA1oLVpmpmGYaw2DOMv0zT3XO2TaqiIiIiIiIiIiFyRYRhVgRHAvKxNy4D+hmHUzFX0CSyNG5c7pywGnryW51bDhYiIiIiIiIgUpgsQbZpmMoBpmheBI0DnXOW6ZW2/7EDWY6+ahoqIiIiIiIiIFFEmpr1DKBWGYYwBxuTYNNM0zZk51qsBMbkelgBUzbUtd7n8yhSLGi5EREREREREbnBZjRQzr1QESMm1zQ3IKKRcfmWKRUNFRERERERERKQwp7DcSSQnb+B0IeXyK1MsargQERERERERkcL8CVTNuiUqhmG4ADWAVbnKLQXq51ivl/XYq6aGCxEREREREZEiMq/TpdC8TfMsMB/onrWpBzDXNM1ThmFMMAzjcmPFR8BtAIZhGFgm63yvCE9RIM1xISIiIiIiIiJF8RDwumEYzYDKZE/mORw4ChwwTXOPYRjTDcN4O2vfm6Zp7r2WJ1XDhYiIiIiIiIgUyjTNOGB0Pttb5VqfDcwuqefVUBERERERERERcVhquBARERERERERh6WhIiIiIiIiIiJFlFmkqSylJKnHhYiIiIiIiIg4LDVciIiIiIiIiIjDUsOFiIiIiIiIiDgszXEhIiIiIiIiUkSZ9g7gBqQeFyIiIiIiIiLisNRwISIiIiIiIiIOSw0XIiIiIiIiIuKwNMeFiIiIiIiISBGZmPYO4YajHhciIiIiIiIi4rCuqx4X9ZvVp8/wXqSlpHH62Gl++eK3K5Z94KmRfDP9W8I37rLZ12d4L55640kA4qLjuLPNCDLSM0o19pJQr1k9bht2G2mpaZw5eoZ5X867Ytl7n7qXOdPnsHvjbuv2Rm0a8ciUR6hUpRIbl27kg8kfkJKUUhbhXzXn8i60mzycjMRUXH082DRlDhmJeWN28/Wk2YN9cPVyZ+2zX9rsc63gwV2b3sXV2x2AxaOmcXTR1jKJvyhc3FzoP/Fu0pJS8PDx5Pep35KaT44NuzSnUdcWGE5OHFq/h50LNxW6r2GX5jz0xUSb4xzbeZi3Bk4GwL2CBy+t+4Dy3h4AfDr2TXYt3lJaqRZZzaa1uWVYd9JT0og6do4/v1qUbznDMBj41HAAKvj78Nvbczh/LtbmOAMnDGPBB79wcNM+6/Yx08dzU98ONsf65tlPWDl7SSlkU3yhTWvTaVgP0rLyX/7VwnzLGYbB4KdGAODt78Mvb39vzb9aveqMeusRgmpWYeeyLXz+nxlcTL+Y5xjjv5jM5vnrWffTn6WXUAFc3FwYOPFuUrPO/d8KOPfDcpzfB3Od+wXtK+/tzoipD9KwU1Oij59jzrOfcXTHoTzPf/NdPUm5kMi5yDN59ttDaNPadB7Wg/SUNP4+do5lV6j7IbnqPi7HuX/Zk19MZtP89azNUb+hTWszeMII5n0wlwM53heOoHbTOnQfdivpKWmcPX6WRV/+kW85wzAY/tQ9APhU8mHOW98Qm5X/+OlPcXO/jjblP3n2QxZ/vZBqdYIZMPZ2ok7+TeWQynzz+tfEno0p3aSuUsuWTbj3vqEkJ6dw5MhxPvn463zLNQyrx0cfv0Gt2iEsXLCccQ9PJD09HYD2HVrzzruvULVqFRYuWMaT418gMTGpLNMoNes3b+f9T77izZcnUq1KkL3DKTHObi50nDScjKRU3Hw8WPvfOaTnd93j40nrrOueP5+zve6p0bExHSYMYcH/TSf+ZHRZhX5Vyrm50HXScNISUynv48HKqfnnW6tLU2p3a47h5MSx9Xs5sMByreJUzpkuzwzlYloGHn7eHFmz27oPwK2CBw+vfxe3rGvAn8dM4+Bix7kGzK2cmwudJg0nPav+1xRQ/+Wz6t/Ny53lueo/pGNjbp4whPn/gPoXuey6abjw9vVm8rv/YWzvh0lJTuX5DyZz8sgptqzK+8Hj7umOl7cnzdo14dsPjDz76zerz5PDngYgLibuH9Fo4eXrxYRpE3i0z6OkJqfyzAfPcOroKbav2p6nrLunOx7eHjRu25g50+dYt7u5u9H/vv5Me3oavpV8eex/j3HfM/fx4XMflmUqxdbxtZGcWBlOxLxNVO/SlE5T72f5uA/ylKsQEkTFesGknU/Ms6/hiK78Of5ja4PH6fWOdaF+x6uj2L9qJzvmb6Bh52YMnTKaLx99z6ZMQGgV+k4Yxpv9JmKaJo/OeZFzEac5c/DEFffVaduQzx58iwvn4gCod3MTm+O2H9ad2RNmkJqYCsChDXvKJukr8PDx4v53HuG1fs+QlpzK6Pcf5++jZ9i7OjxP2b6PDiYlPolFH/1G5drVGPvBeP435DkA3DzL4+7tQd02YTDjl+zjV/AkLTmVN4a9wMU0y/v/jmf/TfjybWWTYCE8fbwY/c5jvNTvadKSU3nw/fGcO3qGPat35inb/9EhJMcnseCjX6lSuxoPf/AkU4ZMxnByonWvdrx936sEVA/iya+eo8Ogzqyes9zm8Z2GdiekUSib568vq/RsDH11FPtW7WR71rk/bMpovsh17geGVqHfhGG8nnV+P57j/L7Svp4PDiB88SaWfvgrfZ64kzEzJ/Bip0dJT0kDwL2CJ/e+9TA/vfwlMSf+tkf6eXj6eDHmncd4MavuH3p/PGcLqPsBjw4hKUfd/98HT/LqkMk2ZToP7U6NRqFsylG/5T3L4+7tSf02DZk/I+93pD15+Xjx6DtP8J9+T5CanMr49ydw5shpwlfvyFN2yKNDSY5P5NePfqZanWCemPEfnh38HzwreJKWksYLQyeRnvX+vu+5+9m6bAvO5Zx5euYkXhr+LLHnYqnboj4TPnyGSYOeeGK8KQAAIABJREFUKutUC1Wxog8ff/oWXToOJCkpmc+/eJfIw0dZvnyNTTknJyf6D7iNwbffT0hIMD//+gXDhg/kqy9/wMPDnbEP3ssj/zeJgAB/3ps+hRdemsBTT75kp6xKTnRsHMkpKezed8DeoZS47q+N5OiqcA7O20RI56Z0/+/9LHwk73WPb0gQ/vWCSc113eNRqQIuHuWp0qJOWYV8TW59dSSRq8L5a/4mQjs35V9T7uf3R23zrRhamU5P3ckXfZ8D0+SuH54l5vAZog+epMMjA0iOTWDjjHkYzk6MnP+KdR9As+Fd+ePJj0nLugY8vsGxrgFzu1z/B+ZtombnpvT87/38kU/9+4QEUaleMCn/8PoXuey6GSrS764+HNxzmJRkyx9X65dtYMT/Dcu3bEpSCtvWbud8zIU8+265rQNJCUns3/kX29ZuJ3L/kVKNu6T0GtGLw3sOk5qV/6alm7jz4TvzLZuSlMLOtTu5kCv/aqHVeH/S+/y1/S82LtnI7Hdm06x9s1KP/Vp4BPlSZ2B7ji21XLSeXLOHkFtb4BVcKU/ZqPBIYvYdy7PdybUcwZ0aE3vgBKfW7uXU2r2YmY4zbq1CYEVa97+ZPcssfzQfWLubxj1a4RccYFOu66g+7F+1E9O0xP7X6nC6ju5b6L61Xy8hfNFmju44xNEdh6gUEsSuRZZfpMu5lqNBx6acOXCCg+t2c3Ddbod4bTqN6MHxPUdIyzrfdy3byr8eGpinnLNLOXqO6seOxZsBOBtxCm9/H+q1DQMgLSmV/et2kxATb/M4V3c3vnrmYw5u3EfkjkOc2HeMSxkXiTvjGL+6dh7Rk2N7Iq3571y2ld4PDcpTztmlHLeN6s+2xZb6PBNxigr+PtRvG4ZhwPwZv5AQE0/kzkPsW7ebzEzbu5IH1AjC278CZyJOlX5S+fAJrEir/jezO8e53ySfc7/bqD7sy3F+718dTves8/tK+w6s3c2239dzYs8RvnjsPTx9vahcN9h63Ac+eJwVny9wmEYLgC751H3fAur+X7nq3jur7i8LLKB+U5NS2bduV573hSPoMeI2IvdGWL/rti7fwqCHB+cpV86lHP1GD2TT4o0AnDp8Eh9/H8LaNsLN3Y2P/jOdvRv3cGjHAY7tO8LF9IvEnIkmrG0jvHy9rT0zDu04QEBwII3aNS67JIvovpHDCN+5l6SkZAAWLljO408+mKecYRi8/eZHREfFsG1rOKtXrefSpUsA1K5dk/GPPceWzTtY8Mcypk55l46d2pVpHqWlkl9FunVsb+8wSpxnkC/1B7QnMuu65/jaPdTu2YIK+Vz3nNsVSdTevNc9ydHxRCxxjIb4wngF+hI2oD2Hl1nyPbp2D3V6tsAnV75tRvUicuUuyPqsj1y9izajewPQ9M7ORP11AgDzUiYRK3fRdoxln7NrOUI7NibqwAmOrdvLsXWOdQ2Ym2eQLw0GtCciq/6PFVL/fxdQ/4f/IfXvyDKv08WRXVPDhWEYlQ3DyPstaQctOjTnzPEz1vUTESdp1CoM53LOBT7GzMxbPT0GdWfIA7fz686fGPLA7aUSa2lofnNzzp04Z10/GXmSsELzt/1gjtwXSWKOVtmYszH8fdpxLtjzU7V9Q1LjEriYaunyal7KJOF4FFXbNcy3fH5fRiE9WhDYog7D17zFv76cQPmKXqUac3HVbRdGYlwCGVk5Zl7KJOZEFHXa2uZYr30jmz+w/o48Td12YYXuizud/ce44WQQGFqFs4ctf8g06taSms3r8NzKdxn7+X/wrOhdOkkWU4P2jYnOkc/ZyNPUblk/z/les0kt3L09iD4ZZd12LvI09duF2ZQzTdvPgvPnYm0+Hxp1bsbefH7RtpeG7RsTlSv/OvnkH9qkdp78z0SeokG7RmReyuRShmVYiGEYZKSls/G37F9qDcOg58g+LJr5eylnU7C67cJIyufcr1vIuX8u8jR1Cjj3c+47uGGvdXtqQgqpiSmcz2qcaty9JQGhlaneKJSHZj3DgGfuwtml4M/TshKWq+7PFKPuz0aeomG7RkB2/S68Qv1mmo538d6kQ1P+zvFddzriFPVbNsyTf+2mdfDw9iDqZPZrdTryFI3aNSH2XKxNI12zzi3YmdVjw93LAy9fL1zLu1r3R5/6mxoNQkorpavWqXN7jh07aV0/fOgIbdu2oFw52860ly5dIiPD0rPEMAxSU9P48QfLUNLdu/cTF5f9I8bp0+c4eeIM1wsnp+vm9zmr4HZ5r3sunIgiuKDrnoLexw74/s5PjfYNSckn3+q5vgdCOoRxIcdnY2zkGWq0bwCAq5c73pX9rPviT0UT0KA6AHW6t6Bq8zqMXfUWQ2ZNwN3BrgFzq94u/9fjeq1/kZwK/EQ3DOOoYRiXrrQAp4DHyy7cglWqXIn4uOxfh5ITk3F1c8XHz6dYx3nxwVfo33gQH//3E8ZMGkX/u/uWdKilwj/IP0/+Lm4uVPCrcNXHrN+iPn98lf/YYUfhWdmP1DjbLnAZSal4BPkW+RhHFmxhVsPR/D74FbyDK3HbrCfAcJzu0T6V/UiKS7DZlpaUgk+QXz7lsl+L1KRUfAIrFrovpzptw4jYvN+6Hr5oM083Gcm7d76IX3AAYz59CsMBXpuKuV6T1KRUXNxc8MrVsOJb2Y+UhGTrH+iWsnlfu8K0uLUN2xdtvragS1DFyv4k2uSfUoz8U/HNkX/1sJqM+/hpfAJ8cc+axwSgx329+XP2Yi5dvFSKmVzZ1Z77aVc499MKOPcDQ6twaOM+4qPOA9B6wC0c2X6IlV8s5Kvx02nVrwP9JuTfi68sFbXuKxZS9z3u680KO9fv1fCr7E9CjvxTsvL3zvVd5xfkT3JCMhdz5J+SmELFfN77bW5tx6ZFGwA4sO0v0lPS6D/G0ovFN7AilaoFYBiO9wdwlapBxMbEWdcTEhNxc3PD3z/v+Q3QpElDZn/7IUFBAVTwyb8RunXrZnz6yexSiVdKhldlP1JyXfekJ6biWYzrnn+SfPNNSsUrV75elSvaDIlIT0zFK+uz/sjq3bS8pzsuHm4Yzk5UbhKK4WS5ljmwcAvvNB7NN3e8gk9wJQZ/5ljXgLl55XPdm56Y9/UQuR5d6Zv4VWAoUAeoDcwF7gRq5Vh6AF+VcoxFY5qkZbU+gmVCNcDmoq2oUpJTmfvZL7z73HSGjM7bBdURmZik58zf9XL+V3dR6lnBk0qVK7Fp2abCC9uRaZrWVufLnFxdyLyKi/Ezmw4wf+gUfOtUJahF7ZIK8dqZJhlptjmWc3XJe26b2JQr51ou+4+SK+3LocmtrQlfnPcP9IjN+5k+4hUCa1cjxAHGRJqmSXqufIA8OZkm1l/rs8u6FOt94eTsRECNIM5Fnr6GiEuWmeucKHf5/Z67Tk3bzwUAF9dyNvnHno5mw6+rCagRxKg3HwEguEEIGWnpdhsiYnUN537mFc79/D4fOt57K79Myf6DrUrdYCK3HiDz4iWSziey/vvl3DTwlhJI6trkrnuXAurezKfuy2XVfXVHqd+rkDuv7O8623Mi93ciWK4Lcr9OTs5OVA6pzOlIy2txIfo8U0a+QljbRjz27hN0GdyNioF+nDp8ojTSuSamCampqdZ1N1dLL5GMi/lf95w8dYYff/iNmjWr8+FHr+fZ7+PjTdVqVVi0cEXpBCwlI5/rHmdXFzKv8nrP4RWUb57vO2zK5SyzeNLnnA6PZPAn42n/cD+qNKtF9GHb7/QTmw/w3fAp+NeuSlVHugbM7Uarf5EcrjQ55+eAk2maFwEMwwg3TXNurjLHDMN4DZhypScxDGMMMAagrm8DqnpWu4aQLXoO7sFT/3vCur53+z68fbK7d3l4epCWmkbChbwTMRbVgu8WMuaZB64pztLS7fZuPPa/x6zr+7fvxytn/l6W/BOvMv/bx9zOzJdmXnOcpS3pbBxuPp4221y9ypN8Lq6AR1xZSnQ8Eb9vxKuaP+e2Hy6JEK/Z+XOxeFSwzdHNs7x1Mk1rubO25cp7unMha5z2lfblVKNJbX5+6cs82wESoi+wY/56KlatxNHtZXtnhXaDOnHv1LHW9YjtB/HMlU96ajpJF2xnwj9/Lhb3XK+dJfeIIj93vTZhNncbsYf2gzozcmr2qLzD2w/mqs/ypKem5ck/Lp9zp7ynO3E58k86n8jWBRtIiI1n/OeTAOg5sg8tb23D7RMsd6Rw9/YgpHFtajauxTcvflbi+RXkas99tyuc+275nPv1b27CoY37bIaUOJVzxinH8INTfx3Hw7fsuxB3yFX3ESVQ9z1H9qHVrW0YkqN+a2bV7+wyrN+i6DSoCw9OHWddP7jjL5vvuvJe7qTlk3/s2Ribzwi4nL9t3Ye1bczeTbYTDu/fvJeX73oegP5jBhJ7Lobd623vPmYPQ4cN5L3p2ZdbmzfvwNc3u1epl7cXKSmpnI/LO38XQFzseX79ZSHR0bH88NOnefaPe3QUE595teQDlxKVeDaO8vlc9yRe5XWPo0vIL1/PvPnmLpfzNUm9kMSiZyyfbZ4BPtz82CBW/m8OuSVHx7N/3kYqVPXntINcA+aWWMB17/Va/47MRMNtylqBDRemZdB3zoHftQzDqGea5kEAwzDKAZOAwMKexDTNmcBMgC7BPUqkltcv2cCondl/yLTv2Z7Q+jWt68G1ggnfmHeyueI6sMv+t77Lz8alGzkYftC63rZHW2rmyL9arWrs2bTnqvLvNaIXK39dScL5hMIL29np9fvwfP0BnMu7cCk1A6dyznhV9ef0xr+u+phmZibRe4+XYJTX5tCGvfj8dywubi5kpFly9KtaicO5/pg+sHYXgbWrWtcDalm6vhe277LqjUM5sefKk9FmXsrk1L6j15hR8YUv28rLvbMvIpp2b021+tWt60G1qnBo874889Yc222ZxLBScCDRWWPdg0Kr8Ns7eS9YCtLitjas+2nltSVwjXYu28LzOfJv3r01wTnyr1yrKgc378+T/9F886/KL+98n+c5ju6KIO6s5Y+6Oa99ya85yjw8YwJb/ljP2h/L9naoBzfsZUSuc79i1UocynXu/5Xr/A6sVYWDWef3lfYBBNWuRqUagaz7zvZuKqf/Ok5QrSrW9cyLl6xzv5SlHcu2cKSQuj9QxLqvHFqVn9/5nhWzF9ucA+NmTGDzH+tZU8b1WxRbl21mQu/sRvrWPdpQo172fBNVQ6uyf9PePN91kbsjSE1OIbB6kHVOjKqhVZnz9jc25drc1o6VP9rW/WXuXu70Gz2QL17+jMxL9p+ybOGCZdzSIbsBpVev7jQMq2ddr1OnJuvXbS70e3/H9t2cOX3OZtt9I4fx4w+/Exd7vmSDlhJ3YsM+egQ9gLObC5eyPhe9q/pz8hquexzZ8Q378Jr6AOXcXLiYlW+Fqv4cz5Xv0bW78cvxme0XWpljG/bnPhwdHh3I0XV7ifwz713IwHIN+Pc+x7kGzO34hn30DLJ9Pa7n+hfJqTiDNl8BZhuG8ZdhGFuAc8BTwCOlElkhkhKSOB5xwros/nEJYS0aWCfoatPlJn6Y+SMAfoF+3PfkvXkPYhiQYxibh5cHvYb+i3IulvacO0YPZtZbX5R2KlclOSGZkxEnrcuyn5ZRv0X2BG2turTi55k/A1AxsCJ3P3F33oMY5Jmv4Naht5KSnEJaahpB1YNod2s7Gt3UqNTzuVopURc4tmwH1W62xFitYyMiF24h+WwcTcf2xifHlxhkDVvMlXNon5vwrmG5S4Fv7SqknU/iQqTjTE6WEHWBPSu2W29TWv+WJuxctIkL5+LoNrovgVk5rvtmGQ07Zd8Fpl77RqyatbDQfZc1ufUmduUaJtK8V1v8q1vaJgNrVyX5fCJ/2+G1SUlI5mzEaeuyYe5KQpvXtZ7vjTu3YMknlsnmfAJ86T/eckedSxkXWfP9cpp0awlAlTrBxJ2NIXL7QZvjGxgFzt1RPawmx/dEllZqRWLJ/5R1WTf3T2o1r2fNv0nnFiz6xDLJok+ALwPHDwUs+a/6fhnNurUCoGpW/hHbD+Lk7ERos+xhP826tWTJ5/MBSI5PIu5srHW5mJ5B0oUkkuNtf9UubZfP/fpZ536DW5oQnnXud89x7q/N5/xemXV+X2mff/VAbh7Rnf1rduEXHEC1hiHccndPAFbOWkBYl+bWYUi1WtVj1ReLSj/pXFISkjkTccq6rC2k7gflqPuV3y+jeT51n7t+MwqoX8PyJVGG2eaVnJDM6YhT1mXlTyuomyP/5p1bMu+TXwHLfBR3jh8OwMWMiyz7bgktu7UGILhudWLOxnBwu+2tMUPDQonck7cHlpOzE//35mMsmb2IdfPW5NlvD/HxiRw6GGldvv32Z1rf1Mw6GWePnp2Z/p7lV+WgoAAmTrY0+Dg7O9OyVVPrcW77V1c+nDHLun7PvXeQmJhEakoqISHB9O7Tg3btW5VhZqXn8sSEBU5Q+A+UHHWBI8t3UOMWy3VPjVsacXjhFpLOxdFqTG8q5nPdc8W5qRx4PgeApKgLHF6+g5Cs67yatzTiwKItJJ6Lo82Y3tbGih2zVxDaKfs8D+nQiG2zFtscq37vm6jcOJT54z+y2eZT3XIN6Fe7Cqnnk4h1oGvA3JKjLhCZq/4PLbS8Hq2vw/oXyelKQ0VsmKZ5FGhjGEYPoCkQD/xhmqZDvLvPx5zn3eemM+7Fh0lKSGL7uh1sXW251U/l4CBuG9yTbz/4nvTUdJydnejctzN+ARXp2rcLZ46d4dypv3Er78qwB+/g7kdGsHNjOH98u4D9O/4ZLZgXYi7w4fMfMvbFsSQlJBG+Npztq7cDEBQcRPfB3flhxg+kp6bj5OxEx74d8Qvwo1O/Tpw9fpa/T/1N98Hdeez1x2xm4U68kMjwFsPtlVaRrJk0i3aTh+MfVgOPQF9WP225cKszoD0JJ6OsjRCVmoZStX0Y5f29qdKuAWeyWqertm9I59dHcXr9Pk5v2M/Wt362Wy4F+WHypwyYeBfVGobgHeDL9xMtw3ha9b+Z2JNR/B15hjMHT7D6y0UMevYeAFZ8Mp+zhywzzl9p32W12zRg4bQfbbbVaRfGsP+N5dD6vRzauJeF034q7VSLJCEmnu9e+Jyhz99HSkIy+9ftZt8ayy+R/tUDaX97ZxbO+JWMtHR+n/YDd0y8hz7jbse3sj8fPfSW9ThOzk607tOeCgG+tO7Tgajj54g9FW3dH9KkFsfs3GiRn4SYeGa/8CnDnx9JSkIy+9btZu8ay69HlaoH0uH2zvwx4xcy0tL5ddochk68l37jBuNb2Z8PHnoDAN8gP8Z9+BQJcfHsX7ebc0fP8OfsxVd6Wrv4fvKnDMw69ysE+PJtjnM/Jte5f3vW+b08n3M/974KAb489v0L+FWrRLcH+lif7/Nx0wA4sv0Q89+cw5AXR/J3xGnSU9LZ+OPKMsw8f5frfkSOut+To+5vvr0z83PVff9xg6lY2Z/3s+q+ME7OTrTp0wGfAF/aZr0vYk5FFf7AMhAfc4HPXpjJyBdGkRyfzO51uwhfY7njT2BwIJ0Hd+PXGXNJT0vnh2nfcc+kkQx+5E78gvx586GpNseq3aQOEbttGy3cvdxp2bU1tZvVZfn3S9ixcnuZ5VZc0VExPP3kS0x9/VniLySwauV6VqxYC0CNkGCGDx/EO299RKVKfnz9zQxiY2JZtXIDERFH+fQTS8+TYcMH8d70KTbf++fPx1MntI1dcipJSUnJzFtima/j1wVLGTG4H34Vr48JDJdPnkXHScMJaFgDjwBflmUNg6g/oD3xJ6OIy7ruCWoaSnD7MNz9vKnWtgGnNlmue1w8y9Nw0M0ANLqjIzu/WEpKrOP2sl08eRZdJw0nMKwGXgG+1mEfYf3bc+FkFLGRZ4g+eJLtXy2l23N3AbB55h9EH7L0kgvpEEZQk1DKuZbju2GvcTEtw3rsGu0a0mvqKI5t2MfxDftZ847jXQPmtmzyLDpl1b9ngC9Ls16PBgMsr0fO+q+eVf/BbRtwMkf9h2XVf+M7OrLDwetf5DKjOK3QhmH0AvxM0/zGMIw2QKJpmsUa/F1SQ0X+idwNF3uHYFcDTX97h2BXe8tlFF7oOpbi8HeHLl0Xb+D8PYveRn5dSqD4k0RfT5LMG/uzb2nM3sILXaeijy61dwh2Nb3l8/YOwa7SbvAf811u2L94LJ48Pvu6PgNG1hx8XdbwrKNzHbbeijxUJGsSzh+BQQCmaW4G7jUMY0QpxSYiIiIiIiLiUDKv08WRFWeOiw5AMJBzsOdCYGr+xUVERERERERErk1xGi6WmqZ5Hmzu/TKkhOMREREREREREbEqzsDjSMMwJgNVDcMYBtyBZdiIXe4qIiIiIiIiIiLXv+LcVeR7wzDaAfcB9wJngFtN01xWSrGJiIiIiIiIOJTM6+g2y/8UxZ3q/RDwgWmauw3DqAscLfmQREREREREREQsinNXkduBY8D/sjb9DbxvGEaz0ghMRERERERERKQ4k3M+g2VOi1UApmleAL4Hvij5sEREREREREREijdUZJFpmksNwwjLsa0ZUKOEYxIRERERERFxSJrhouwVp+Ei3jCMDoCTYRiVsdwKdQrwZalEJiIiIiIiIiI3vOIMFZkGdALGApHAeOCdrP+LiIiIiIiIiJS44twO9SIwNWsRERERERERESl1RW64MAyjIvAa0BfwBQ4CM0zT/LyUYhMRERERERFxKJma5aLMFWeOi++BRsAMYC/gCnQxDKOGaZovlkJsIiIiIiIiInKDK07DRTuguWmaR3Js+9EwjEklHJOIiIiIiIiICFC8yTnfAfzy2Z5x+R+GYbS65ohERERERERERLIUp8dFEDDTMIzwHNuqAFUMw2gIGEBbIKwE4xMRERERERGRG1hxGi7cgPVAdI5tx3L82wDqlURQIiIiIiIiIo7I1OScZa44DRdTgUOmaRZYS4Zh/HLtIYmIiIiIiIiIWBRnjov7gKcMw6hkGEYHwzCOGoZxzDCM7pcLmKYZXvDDRURERERERESKpzgNF52AD4B44FtgBZbbo3Yp+bBERERERERERIo3VGSuaZpJhmE8hmW+i0dN00w0DKM4xxARERERERH5x8q0dwA3oOL0uDAMw/gAeBX4PyDZMIzBwMOlEpmIiIiIiIiI3PCK3FvCNM23DcMIA94wTfOoYRhVsdxhZECpRSciIiIiIiIiN7Ti9LjANM19pmkezfr3aeAA0KAU4hIRERERERERKbjHhWEYR4HqRTjGIeCjkgpIRERERERExFFlYto7hBvOlYaKvAqcB7YBJvA6MAfYmqNMLaB9qUUnIiIiIiIiIje0KzVcfA44maZ5EcAwjHDTNOfmKnPMMIzXgCmlFaCIiIiIiIiI3LgKnOPCNM3My40WWWoZhlHv8ophGOUMw3geCCzNAEVERERERETkxlXku4oArwA/GIZRAUjAMkzEFRhaGoGJiIiIiIiIOBpTc1yUueLcDvUo0MYwjJ5AEyAe+MM0zTOlFJuIiIiIiIiI3OCK0+MCANM0lwJLL68bhnGfaZpflGRQIiIiIiIiIiJwhTkucjMMY7RhGCcNw8gwDONS1pIJfFaK8YmIiIiIiIjIDaw4PS7eBMYCW4DLk3YawLDiPOEAp8rFKX5diXHKtHcIdtXqYqK9Q7Crvyhv7xDsqprpau8Q7OrD89vsHYLd1PeqZu8Q7Gpu2MXCC13HzBv7q4+qZ1LtHYLdTG/5vL1DsKtx21+2dwh2Ff/vkfYOwa7cu9crvJCIFFlxGi6WA/NN07T569MwjK9LNiQRERERERERx3SDt8nbRXEaLr4CphiG8VOObQYwBHikRKMSEREREREREaF4DReTgNpAf7De/8UJqIwaLkRERERERESkFBSn4eI1YIFpmhk5NxqG8a+SDUlERERERERExKLIDRemaf5WwK7YEopFRERERERExKGZpll4ISlRBTZcGIbxG/ChaZqLstbnAZ65iwENsQwXEREREREREREpUVfqcfEtsCfHegRwDjhD9hwXBtC3dEITERERERERkRtdgQ0XpmnOybXJG3g2n9uhLiiNwEREREREREREijM5ZwYw3jCMcsAq0zRXAJim+XepRCYiIiIiIiLiYDLRHBdlrTiTcz54+d+GYXQ2DOMNLENGvjFNM7w0ghMRERERERGRG1uRGy4Mw2himuZuwzC6A/8GBgGHgNOAGi5EREREREREpMQVZ6jIPMMwnAFf4H2grWma+0onLBERERERERGR4jVcHAeeBdyATkBbwzAiTdNMLZXIRERERERERBxMpr0DuAE5FaPsv03TXG2a5lLgNSAQOGYYxtTSCU1EREREREREbnTF6XHRwTCMZsBQoA+wD5gCfF8agYmIiIiIiIiIFKfh4mvgAPAd8JxpmodLJyQREREREREREYviNFy8aJrmy6UWiYiIiIiIiIhILkVuuFCjhYiIiIiIiNzoTEx7h3DDKc7knCIiIiIiIiIiZUoNFyIiIiIiIiLisNRwISIiIiIiIiIOqziTc4qIiIiIiIjc0DI1x0WZU48LEREREREREXFYargQEREREREREYelhgsRERERERERcVia40JERERERESkiExTc1yUNfW4EBERERERERGHpYYLEREREREREXFYargQEREREREREYelOS5EREREREREiijT3gHcgNTjQkREREREREQclhouRERERERERMRhqeFCRERERERERBzWdTPHhbObCx0nDScjKRU3Hw/W/ncO6Ykpecq5+XjS+sE+uHq58+dzX9rsq9GxMR0mDGHB/00n/mR0WYV+Vcq5uXDbxBGkJ6VS3seTJVO/Iy2ffOt2aUb9ri0wnAwi1+9l78LN1n3lK3gwYd17lPf2AOCbsW+zf/FWADo/PADDycDMNHFxd2XZWz+WTWJXwSjvSvDkf5OZmIKzjycnp3xFZu7XwtmJkP+fg75XAAAgAElEQVQ9jF+fDqSd/Jsjj79Lyt4j2bt9vaj84ECcvTw4/uzMMs6geFzcXOg38S5Sk1Lx8PFk3tRv8637Bl2aE5ZV94fX7yV84SbrPg8fT7qO7Ud5L3fmPj/L5jFjv3jG5jjHdh5m2sBnSy+hYirn5kLPScNJT7Sc+8umfp9v/nW6NKNet+YYTgZH1u9j34LNeY7T+q7upFxIIibyDCd3HKZOl2bc/eXTNuVO7YzgkwHPl2pOJa15y8bcde8dpCSncPTICT7/5Jt8yzVoWJf3PppKrVohLF64gvHjJpOenlHG0V67Bs3q03dEb1JTUjl99DQ/f/HbFcuOenokX7//LeEbd9ns6zO8N/9580kA4qLjGHLTcDIc+fVwdcVr9EOYKckYXt4kffoRZnJygcXdOnelfL8BXJjweJ7juPfpT2ZiApdOnuDi/n2lHHgJcXXFa0yO/D8pJP8uXXHvN4DzT+aTf9/+mIkJXDzxD8ofaN2qGfffP4KU5BQiIo8y48Mv8i3XqFF9Pv9sGnXrhDJv/hJGj5lAeno6AFWqBDHxmUc5fPgINWtWZ/78paz4c20ZZlF8N9o139Vav3k773/yFW++PJFqVYLsHU7JcXXF4/6HMJOTcfLyJnnWR5gpBb/3XTt2pXzvAcRPzH7vu995NxgGmCa4uZHy9WdlEfm1K+eCS8chkJ4K5T3IWDPX8u8CypZr0gkzLRkz7hyZZyItm9v0tuZulHMlY/2vZZiAyNW7bhouur82kqOrwjk4bxMhnZvS/b/3s/CRD/KU8w0Jwr9eMKnnE222e1SqgItHeaq0qFNWIV+T/q/ez8FV4eyZv5G6nZsyYMoD/PDodJsy/qGV6TnhTj7s9yymaTJqznNERZzm74MnAWg9rBtzJ3xEeqLlAy9yw14A6ndrQcXqAfw68VMABr0+hsZ927Fn/sYyzLDoQl4by4WV24mbt44KXVoQMvUhjox726aM/+1diJ69mFNTvqLmO49S45XRHLh9knW/W0hl3OvV4GKu88IRDX71Af5aFc7O+Rto0LkZd04ZxdePvm9TJiC0Cn0mDOXtfpMwTZNxc17gXMQpzmbVvX9IEJXrBpN8IcnmcXXaNmTWg29z4VwsAPVublI2SRVDn1dHcnjVLvbO30idzk3pO+V+5j5q+173D61M96fuYGbf5zBNk5E/PEf04exzv3wFDwa9/SCLXvqauBNR1sfVbNuAOQ9OI+FsHAC1bmlcdomVEN+KPkz/+HVu7TKE5KRkPv78LSIjj7Fyue0fIk5OTvTpfysjBo+mRkgw3//8KXcMG8A3X/1kp8ivjrevN5Pfe4YxvR4iJTmVF2Y8y4kjp9iyamuesu6e7nhW8KRZ26bMnv5dnv0Nm9dn/LCnAIiLPu/YjRaA96NPkL5lE2mr/sSldRu8Hp9AwpSX8y3r5O+Px4h7yEyIt9lueHnh/fQkEme8T+bZM2URdonxfiwr/5V/4npTG7zHTyD+tYLz97zrHjLj8+Zf4T+TSJjxPpln/ln5V6zoyxdfvEfbdr1ISkrmm9kzOHz4CEuWrrIp5+TkxO2DetO3392E1qzBgj++4e67BvP5LMt7YNo7r/DuuzNZv2Erbm5uHDqwntp125GR4bjn/412zXc1omPjSE5JYfe+A/YOpcR5PvwEGds2kb7mT1xatcHzkQkkvp7/e9/w88d96D2YOT77XG5qj1NQFZLef8NyvMf+g2vHrqSv+bNM4r8Wrt3u4tLRPVw6uBWnmo1w7XEP6Qs+yVvQzQPXf40kY+UczAvZDXNOoU1x8vEnfenXluPd+m+c67Xm0sG835lyZSamvUO44VwXQ0U8g3ypP6A9kUt3AHB87R5q92xBheBKecqe2xVJ1N5jebYnR8cTsWRbqcdaErwDfWnavwMHlm0HIGLtHhr0aIlvrnxvHtWbQ6t2YZqWN9ah1bu4ZXQfAJxdy1GnYxP+PnCSiHV7iFi3BzPTUi6gTjVcvdytx8lITbf2ynA0LkEV8RvYiQtLtwAQvyYc31vb4BocaFMubt5aknYe4mJsPFFfL4ZM27mAk8MPk7zvCI6uQmBFWvW/mb3LLOfqwbW7adSjFRWDA2zKdRnVm/2rwq11/9fqcLqM7mvdf2JXJKf25X0frP16CbsWbebYjsMc23EY/5Agdi3anKecvXgH+tJkQAcOZp37kWv3UL9n3nO//ajeHF6Zfe4fXr2L9qN7W/ffMeNRNny2yKbRAmDL18vYv3ALJ3cc5uSOw1SsEcj+RVtKOauSdc99d7I7fB/JSZZfn5Ys/JNHHx+dp5xhGLz39kyio2PZvm0Xa1Zv5NKlf94c2f3v6sPB3YdISbY0wK5fuoG7xg3Pt2xKUgrb1mznfOz5PPtuue1mEuOT2L/jL7at2U7k/shSjftaOfn749a1O2kb1wOQsX0bbu064BRUOd/y7kNHkDL/9zzbKzz7Eilzf/zHNVo4+ftTvlt30jZY8k/ftg239gXn7zFsBCnz8ubv8/xLJM/98R/XaAEwetRd7Nixm6Ss9/r8P5by9FPj8pQzDIOp/5tOVFQMm7fsYMWfa7l06ZJ1f4MGdfD29gIgPT0dV1dX3NxcyyaJq3CjXfNdrUp+FenWsb29wyhxhp8/bl26k74567NvxzZc23bAKbCAz74hI0hdaPved64eguGefZ1LehqGp1epxVxSDE8fnBu04VKkpbdg5rH9ONduhlHBP09Zt75jubh9mU2jBYCTf2VwKW9dNy9mgJt77oeLOKQSabgwDGNsSRznagW3a0hqXAIXUy3dHs1LmVw4EUVwu4b5lr/8x0w+O0orxBIV2i6M5LgEMrLyzbyUSdyJKELb2uZbq30j4k78bV2PjjxDaNZrUr9bC4Kb12b8yre55/On8KjobS13YPl2/p+9+w6Pqsr/OP4+mfReIAmhBpBeBJGiVLEi9rZgW/0BdndtuwKu7roW7Lp20RVWXSuWRREFsdBRepMWOgTSSJ3UOb8/JiSZJEACKQN8Xs9znydz77mT75m5986d75z7vZ3O7k3XC/oSGB5CSHQYKz6f2wA9q72wAd0pzsjCVfpaUOKicMc+wvp39WhXthwIbN+c3ZPer/pkLu9//9v370JOpfc+fWcK7Su99+0HdCO9wnufkrSX9v27eLSpbj84sCet7G/jY4hNbMa+zbvrsgvHpM2Aqtv+gZ0ptK7U/8QzungkJdKS9tJmgLtNh+G9iGkTT7Nubbh2ygOcM34UDj8HAJmV+h/Tthkpm7yn/zUxcHB/dmzfVfZ48+Zt9OnXC19fzwF2JSUlZb+oGmMoyC/g80+nN2isdaH3mb3YuzO57PGOLTvpdloXHL6OQ67jqmZfP+fy4Vw15nK+WjmNq8ZcXi+x1iW/Hr1wZWVCQYF7hquEkuS9+PXoWaVt4PkjKJgzG1vgOZzYv/8ZOJo3x/eUUwh//ClCxtwKvsfHQEy/ntX3379nNf2/YAT5P1TT/wHl/Y944ilCxh0//QcYNvRMtm3bWfZ444YtDBhw2hH39fz8Aj78qHxo+Oeff8Pzzz9KXFxTLr/8Qh5/4kVycjxH43mTk+2c71j4+JwQv0968OveC5tZzbGve9V9P+DcERT+PBsq7ftFvy7Ev9+Z+J85BBMaigmPoGDOdw0R/jHxadkRm58DxaXntNaFzUzFp0UHj3aOtj0wkbH4xLYi4LK78Rt0Bfi4PxNLklbhaNcTxym9ISAYExRKyXrvHFEtUtlhj2jGmO3GmJIjTC7gtQaKt1qh8dE4MzyHARbm5BMSF9lIEdWv8Pho8ir1tyA3n7C4qErtojzaFeTmExbrbrNu5q881n0Mb1/9KJEtmnLd2/dhjAEgZcsePrn7Fa547lau/tcdfH7/mxQXeOeQUb/4aIozsj3mleQ68YuLrtLWERlG3K2XEvvHETjCQxoqxDoVER9FXqX+FuQ6Ca/03kfER5FboV1+rpOIWM82R9KuX2e2LFl/9MHWg7D4qCr7enXbflh8FM4D5f0vyHGWbfvdLzmDncs2sfjd7/j8z6/T7aL+nPXA1VX+V+t+ndm++Pd66EX9im8WS3qFEQU52bkEBPgTHVP9+9+1eyfeff9lYuOaEB4eVm0bb9YkvglZGeVDgPNy8/AP8CcyOqJWz/PILY8ysuulvPnEZG6ZMJaLrx955JUakU+TJthKlz1YpxOfGM9fnX2aJWDCwin+veq+HHDW2RStX4fzi2lkT3qcgGFnEXLTmHqNu644ath/R7MEfA7R/8CzzqZo3Tqcn08ja9LjBA49i5Cbj4/+AyQ0jyctLaPscXZOLgEBATRpUvXzD6Bnz6589unbxMfFEhFRvq//87EX+O23FcyfO53Ondrz8ivefa3/yXbOJ558YppUueTNOp2Y6ErHvvgETGg4xRuq7vslO7eT/cyjhN47ntAHHibnxUlQWFilnbcxoZHg9Ewq2sJ8TIjntu/o1A/X3iSKl8+h4Nt3cHQ8Hb+Bl7nbpydTOGMy/uffTMCIMRR+NwWKvfMcX6SyI6VinwXOBtoBbQ8xtQP+UY8xHpm1ZZn3gxz+friKSg6xwvHNWktRgWd/ff19KanUX2vxaOfr70tJsWebbUt+59+jH6NJuwRaVLjW0+Hr4INxzxPdOp5rXrkbn8P8etmorPUYTQFg/P2wxcVVmrpynWQvXEPuys20m/wgfs2qDiv1du731PMDxtffr8p7T6V2vv5+Vd77I+l+7ums/s7LLpOwtmy0xUG+/r64Kr/fForyPfvvKu1/bIcW7Fy6EVdxCc4DOSz96Ed6XHpmlX/V6dzT+N3b+l8T1pKfX/7rUkCAHwDFh7hefc+uZKZ9Op3WbVry0utPNkiIdclaS0F+QdljP3/3EPfioqrHgCNx5uXz2Tuf8+JDL3P12CvrLMZ6YS22oMBznp8fVNwXjCHo4stwTqu+uLJv6zYUrV0NJSXY7CzyZ3xNwPBz6jHoumMP0X9buf+XXkbeZ4fof5s2FK0p7X9WFs4ZXxN4nPQf3K+B01lxX3dv+4eqTbFz5x7+++EXJCa24t9vv1A239/fn4ULl/LkpH/x4F/v4tprr6jfwI/VSXbOJ5VZbKHnvm/8/KDEc98PHHkZ+V8eurC8cfiS/c+HcDRrTthf/w4OLz3PrciCLa50zuvwBZfntu8Tk4Brz2b3/PxcilfPxdGpX4UGDgq+ehUTGUvAhePKRmNI7biwJ+TkzY6UuHjdWvujtXabtXZ7dRNQADxzuCcxxowzxvxmjPltYc6mOgv+oJzkDAIjPH9B9w8NJGdfxiHWOL5l70snqNKIAf+QILIr9Tcr2bNdQDVtAHJTs1j99SIiEtzXyLXp14nmPduyZd4a3rnmUZp1ac2ZY0ZUWc8bFCWn41vpvXeEBlFUTT9tUTF5KzeTdNuzFO5NI7R3hyptvF1mNe99QEggWZX6m5mcTrDHex9IZi33h5bd27Jj5ZajD7YeZCVnEFR5Xw8JInvfgUrt0j3a+YcGlm37Pr4OfCqcoOxbv7PKcwIk9GjL7pXeXecA4MprLmb7vpVlU1pqBpGR5aMNQkJDcDrzOXAgq9r1MzIOMP3L7/jT7RM448zTGyrso3buFWcza8u3ZdOB9EzCKvx6HBwSRIGzgOzMoy+0+82H3xIeFV4X4dYbV1oqJsxzhIwJDsaVVn65k1/X7gRdOJKYTz4n5rOvCL3jT/h17U7MZ6V3XXE4MBVOWIuTtuATdnyMunGlVtP/oEr979adwAtH0uSzz2ny+VeE3vkn/Lp1p8nn5f2v+GWlOGkLPl486ujaa68gJ2tL2ZSakk5UVPm+HhYagtPpJCMjs9r109MzmDbta8aMvZfBg8trH/zrpcf4Ze5C3vn3f7n19r/y1hvP0KJFQr3352idbOd84smVlopP6OH3fd8u3Qk8fyRR739O1H+/IuSWP+HbpTtR/3Xv+77deuLboRNFK34j88G7cbRtT+BlVUdeehubcwATWOl8xT8Qm1upbpOPD5jyr3g2dVfZej4tOuATn4hrx3oKPnkGE9sS39OOn4StnNwOm7iw1lb5ycoY08sYM8gYM9gYMxjoDRy2DL219i1rbR9rbZ8BoaccW8TV2LlwHSFxUThKf1n08XUQlhDDrkXH3zDvmkhauI6wuCh8K/Q3MiGGrYs9h8NtmbeGJu2alT2OaRvP1kXV3+bNlrhILi3W2G1EfzJ2uOsjZO8/wOznPqH16R3royvHLGvBavziojGB7l+ajK8D/4SmZC9ac+iVXC7y1iZRmJx26DZeavPCtUTEReFX4b2PSmjClsWe7+uGeauJrfDex7ZtxuZFa2v8f1p0S2TXGu8rVrqtmm0/IiGGbYs8t/2keWuIaVth209sxtaF7tdo3/odHstcJSWkbNnjsX6zbm3Y64X9r853385h+MBLy6bZs36mXfvEsuXt2ieyaMFvuFyHL7y5Yvka9u7df9g23mD+9wv5v3PHlU2LflhMq3Yty5a3bNuClYtXHbG/R7Jx1cZjDbVeFa5YjiMmBkpHmOBw4GgaS9GqFWVtijasJ/3mG8i4dQwZt44hb+q/Kd64gYxb3ZdDFCdtwdGyVfmTlpRQvGNHQ3bjqBWtWI5P5f7HVur/7+tJ/+MNpI8bQ/q4MeROcfc/fdxh+r/de/s/ffr3nHb6uWXTtzN/oEOHdmXLTzmlLXPnLj7itv/b0pXs3lNeF+bqqy5m8+ZtALz//mcsXLiUvn171Usf6sLJds4nnopWLccn2nPf94mNpXhN+b5fvGE9B265gcy7xpB51xjyPvg3xZs2kHmXe98PGDiUkr3uz32bnobzvbfx69qjwftSWyU7f8eERICve9vHx4EJi8a1y/PzypWyCxNdXqzUulzYdHcBYkeH07AH3DXAbG4mRfO/xNG87r+bidSHWlXtMca8D/wEfAFMLZ3+A9R+TG4dykvJZOsPy2k10F2QsdXArmz+9ldy92Vw2rgRRFX4kgLuWxcfrOdQrcMt8wI5KZlsmLOcdme6b9XYbmA31s5cQva+DM4ceyFNSvu75IPZnDK4/EDcdkBXFr47E4CuF/QlqqX7zhtN2iXgPJBDapL7oLZ33TaadW1Ttp6rxMVuL/vl/aDilANkzv6N8DPd/Qwb1JOMbxdSlJxO3C2XENDW/atRYMdWZXUtHOEhGIcPuUsr3SLMlE5eLDslk7VzlnFK6W1KOwzszsqZS8jcl8HQsSNpWvreL/hgFh0HlxeqOmVAN+aWvvcHufeD6v9P93NPZ9V33nM3kYNyUjLZ+MNy2pZu+20HdmP9zF/J3pfBGeNGlCUkfnv/B9pX2PYTz+jC4nfdhbcWvTuTU4b2xOHvLmDX8rRTypYd1Om8PqyfeXzcGiw7K4fNm7aWTZ/890t69+lRVqDvrLMH8vor7wIQG9eUB8bfBYDD4aBX7/Lb3Z5z3hDeen1qw3eglnKzc9mxZWfZNPPT7+ncq1NZMc5+w07n4zfdw4NjYqO56b4bqzyHMcbjMyA4NJgR15yPr5/7Nbt63JW88+yU+u/MMbAZ6RQsWoh/r9MA8O/dh4J5v+BKSyXoymtwtGgJRUW4UlPKp5xsbFEhrlT3Savzi2n4n97XfYkJ4Nu1G84vpzVan2rDlZFO4aKF+Pcu7f9pfSiY+wuu1FSCrqq+/zYnG1tY3v+8z6cR0Le8/35du+H8wnv7n5WVzYYNW8qm/7z3KX37lhfePe+8Ybzw4psAxMfH8sjD9wHuff30PqeWPc+IEWfzr3+9XfZ45cq19Dq1/NbP+fn5rFhxmOR/IzvZzvmOxcHCpIcsUHocshnpFC5ZiF9P977vd2ofCue7j32Bl1+DT/OWUFyEKy2lbLI52VBUiCvNve8XJ23Gt135l3XrclG88ThIfOVlUZK0Cp+W7kK0Pq06U7J5GTbnAL6nnYuJigOgePkPONp0A4f72OBIaEfR8h8AcO3fiYmtkLC1LkqSj48fakRqWz7bCUQB5wDbrLUbjDF9gepLOTegHya+y6AJo2jauRXBTSOZ/aC7uFTHSwaQtSuFjNIv5XE9EmkxoAtB0WE079eJ3aXF9/xCAul8mfs6965XDWLFlFk407Or/2de4H8T/83540cR37kVoU0j+Wq8+ySkx8VncGBXCqlJe9m/cReLpn7PBQ9dB8C8yd+wv/QOCYn9u3DpU2NJWrCWrYvWM+fF8pO1ZZ/8TGRCEwbfdhG56dlEJMTw86tfNXwna2j7hDdoMfFGgru0wTc2iu1/cdeKjb5kMIW79lOQtIdmd15B+KCeHPh+CUUpB8raHBTcox1hA7rjGxNOaP+u5NRidEJD+2ziO1w0fjQJnVsR3jSST8a/BUDvi88gY1cKKUl7Sd64i3lTv+OSh64H4MfJ00neVH6niZbd29K+f1dCY8LdRTgrjdZp27cTM1889LWhjenrif/mnAmjievSitCmEUx/0L3td7v4DA7sSiWtdNtf8p/vOe9v1wKw4K0ZZXcH2bVsM3Oe+5QL/n4DaUl7KXIWsuLTXzz+R+vTO/LTC977BeZwUlPTmfCXx/jnpPFkZ+Uw9+dF/DxnPgCtWjXn6lGX8PILbxHTJJp33vsX6ekZzP15EUlbtjPl7Q8bOfraO5B2gJceeoW7/3EHOdm5LJ23nF9/cd/mML5lPOdfeQ4fvPohhfmFOBw+DB05hOimUQy7aAh7tu9h3+79BAQGMOq2q7n+7mtZsXAlX384g/XLvf8kNudfzxMy9jZ827XDJyqG7BeeBSBg2HBK9iVTsmvnYdcvXr+W3CnvEHr73e62BfkUfPdtQ4ReJ7JffJ7Qcbfh27YdPtExZD/v7n/gWcNx1aT/69aS8+47hN15N8U7d2Lz88k/jvqfkpLGn//8EM8/9w+ysrKZM2ces2a7j2VtWrfkumuv5KmnX6Vp02g++XgyqWnp/DhnHps2b+WNN8uTlNffeCcTxv+JHj26EB4eyjvvfkhSUtVbiHqTk+2c72jk5uYx/fs5AHw5Yxajr7iI6KgTo4Bp7mvPE3yTe983UTHkvFx67Bvi3vcLdx9+3y+YNQOf2DgCrxqNzczEp2kszo+ruducFyr84QP8B1+Bq2kLTEgEhbPeA8C3U19sViolGftw7U2iaMGX+A37AzZ9H7aokJK17tvHlqyZj094NL6nn4915uATFk3RkhmN2aXj1omUEDxemNq86MaYJ6y1E0r/ftRa+7AxJhxYba1tXZPneKHVdSftu5zmc2xDl493lxbnNXYIjeoD38AjNzqBRdiTu/jT6weWNnYIjaZjaPPGDqFRTevSqIMSG509uT/6SJi7ubFDaDTPxA9r7BAa1Z3LHm3sEBpV1o03NXYIjSpo+PFXS60uBd87+cQdzgQMb3HuCfmd9odd33vt+1bbERe7jDH5wHnAj8aYDUAIkHz41UREREREREREaq9WiQtr7WvGmPestdkAxpiLga7ArPoITkRERERERERObrUdccHBpEXp3xuMMZnAtcAbdRmYiIiIiIiIiLdxcUJeKeLVapW4MMa4oNp3aRNKXIiIiIiIiIhIHavtiIt/Au9SnrwwwDXAvLoMSkREREREREQEap+4mGStdVacYYx5BfgGGFpXQYmIiIiIiIiIQO0TF6cb43GHFAcwAOhRZxGJiIiIiIiIiJSqbeLie9y3Pj14qYgL2AeMqsugRERERERERLyRVXHOBlfbxMWN1tqP6yUSEREREREREZFKapu4+MIY42+tLTTGOIDrcRfofM9aW1z34YmIiIiIiIjIycynlu0zgAeMMTHAa8BTQFfgiboOTERERERERESktiMuXrbWPm6M6QaMAYZba38yxtxbD7GJiIiIiIiIeBWXVY2LhlbbERc5xpgmwCvAtNKkhQMYWfehiYiIiIiIiMjJrraJiy9wXyKSBIwzxrQGnsVd50JEREREREREpE7V6lIRa+1a4OoKsw4YY14Ecus0KhERERERERERapm4MMYEA+cBoZSPsggG/gj0r9PIRERERERERLyMKlw0vNoW55wGtAQCgF2l81oCM+oyKBERERERERERqH3iYq219gJjzBlAvrV2mTGmI3BpPcQmIiIiIiIiIie52hbn9DXGNLfWLgCuMsYEAnnAn+s+NBERERERERE52dV2xMUvwHJjzFXAx7jvLhJZOl9ERERERETkhOZSlYsGV9vExRJgCrDUWptTmsDoB7xQ14GJiIiIiIiIiNT2UpH3gb6AH4C1dj5QADxYx3GJiIiIiIiIiNQ6cfGrtXaotTajwrylwL11GJOIiIiIiIiICFD7xEWxMSbg4ANjTBAwHthXp1GJiIiIiIiIiFD7GhdTgLnGmO2APzAQMMDFdRyXiIiIiIiIiNdRcc6GV6vEhbV2gzFmCO5ERWvgE+Aba+2B+ghORERERERERE5utR1xgbXWiftWqCIiIiIiIiIi9aq2NS5ERERERERERBpMrUdciIiIiIiIiJysrFWNi4amERciIiIiIiIi4rWUuBARERERERERr6XEhYiIiIiIiIh4LdW4EBEREREREakhF6px0dAaPHERVdLQ/9F7FJmTe4BLkya5jR1Co9qXYRo7hEblbwIbO4RG9VhYn8YOodF8alIbO4RGtWtDaGOHII2oaXBEY4fQaApO7o89sm68qbFDaFThU99t7BAalc0/uc97Rerayf1NWkRERERERES8mhIXIiIiIiIiIuK1VONCREREREREpIasalw0OI24EBERERERERGvpcSFiIiIiIiIiHgtJS5ERERERERExGspcSEiIiIiIiIiXkvFOUVERERERERqyFoV52xoGnEhIiIiIiIiIl5LiQsRERERERER8VpKXIiIiIiIiIiI11KNCxEREREREZEacqEaFw1NIy5ERERERERE5KgZY5oYY940xjxljHneGON3iHYtjDGzjDHZxphfjDEda/L8SlyIiIiIiIiIyF/f/B0AACAASURBVLH4FPi3tfavwEbg0UO0ewj4F3AuEABMq8mTK3EhIiIiIiIiIkfFGNMf6GitXVw6azpwlzEmpFI7P+B9a+10a+1C4CagqzGm6ZH+h2pciIiIiIiIiNSQtapxUclZwNaDD6y1u40xAH2AnyvMLwLmVVhvN5ANHDjSP9CICxEREREREZGTnDFmnDHmtwrTuBqu2hxIqzQvG0g4wnr9gMmlCY3D0ogLERERERERkZOctfYt4K3qlhljngS6H2LVocA3leYFAEdKSFwH/KkmsSlxISIiIiIiIiKHZK0df6hlxpjxwLAKjw0QAuw5zDrXA69bazNq8v+VuBARERERERGpIReqcVHJLODWCo/bAIXAb9U1NsYMAnJKC3TWiGpciIiIiIiIiMhRsdb+Buw1xnQrnXU+8LK1ttC4PWqMiQcwxvQBhgPLjTFtjDH9jDE3HOl/aMSFiIiIiIiIiByLa4CHjTHbgFBgYun8QOB6YIYxpgkwG4gAHqmwbv8jPbkSFyIiIiIiIiJy1Ky124H/q2a+E0isMCvyaJ5fl4qIiIiIiIiIiNfSiAsRERERERGRGrIqztngNOJCRERERERERLyWEhciIiIiIiIi4rWUuBARERERERERr6UaFyIiIiIiIiI15LKqcdHQNOJCRERERERERLyWEhciIiIiIiIi4rWUuBARERERERERr3VC1LhwBPrRZ+IoinLz8Y8IZunjH1OU46zSzj8yhG63XohfWBCLJ04tm998WA/Oef8vHm1Tlm/hm5GP1Hvs9cE3wI8hE0ZRmJNPYEQwP0/6mMJqXo/AiBD63nIh/mFBzP7b1Gqe6fhjAvyJ+vNYXHlOfMJCyXjpbWxu3iHbB587hPCrLyJ5zP0NGGXdaNujPcP+cDYFzgL270jm+6nfVtvOGMPVD1wLQHiTCD577kMy9qWXLR/6h7MZ99QdAGSmZnLXgDEUFxYfcVlj8Q3wY8T4aynIdRIUEcK3kz6koJrtu+PQnnQa1gvj48OWBWtY/e0SAHwcPlz+xBi6j+hHxq5UPrn/dfas3eZe5uvggr+OorigkJDocDbNXVW2njdyBPrRb6J7Xw+ICGbJE9Uf+wIiQ+hx64X4hQax4CHPfd0/PJhRi1/CPywIgFljXmTbzN8aJP660qFnBy74w/kU5OezZ9te/jd1+mHb/vGBG/nwlY9YvWh12fw2HVvzwPP3k5CYwKJZi3n+gRcoKixqiPCPmgnwp/mEGynJdeKICGXPk1NxVX7/HT60evJ2Ii88k8Jd+9l+74s412498rLjwLH23ycsmFZP30n44F4UbE9m58TXyVu+sRF6cvR69urGtTdcidPpZNvWnbw7+b/Vtus34DSeev4RmiXE8f3MH3nwvkfJzXF/Np7SoS233X0zu3buoU1iS5589EX27tnXkN2oEd8AP4ZNGEVB6bnNT4c4t2k7tAftzjoV4+PD9gVr2TDjV8B9fB/64DUUFxQRHB3G1rmry5YBBIQHc/uClwgoPRZ+Pu5FNn7npcdCf3+Cb74Nm5eHT2gYee++gXUe+lzHf9AwAkdcQtb4P5fNC7r6OjAGrIWAAJzvvdMQkTeYBUuW8fLk//Dso+Np3iyuscOpM/kFBTz/1vuEBAWSlZPLPWOvIzQk2KNNUXExL07+gAB/P9IzszjjtJ6cO2QAAHMXL+P2CU94tO/WsT0fvjapwfpworCoxkVDOyESF/2fuIndP61k2/8W03xoDwY8dTO/3PFqlXZhreOI7NiCwgM5HvPj+3fmx7EvkZfs/jLXbFC3Bom7vpzz2E1s/Xklv3+9mMQhPTjviZuZfnfV1yOydRxNOrTAWen1OJ5FT7gb5/xfyfv+Z4LO6EPMQ38mdfwT1bZ1NI0hcsxoXFnZDRzlsQuJCOX2F/7ExIseoCAvn7tevpfkrXtZ9cuKKm0vu/sq8rJymf7GFyS0b8Hdr93PP66YULa8XY/2PDHanaTLTMv0SEwcblljueyxm9nw80pWfb2IDkN6cvkTY/jw7pc92jRJjOe8+6/h5YsmYq3llo8fZv+WPezbuItelw1k0X9/4NunPuSqZ2/j4r/fyBtX/QOA4XddRm5GNj+99hU+Dh/u+vqJsvW80ZmP38Sun1aSNH0xLYb2YOCkm/nxzuqPfVEdWlBQzb7eafQwfr7nzbIvAHsXrKv3uOtSWGQof33xAe648C7y8/KZ8OqD7N62h6U/L63SNigkiJCwELr368ZHr5iy+T4+Pgy8YCATb3iI+JbxPPH+4wy/fDgzP5rZkF2ptZaP30rWz8s4MH0eYUN60erJ29l213MebaIvG0rqB9+xZ9J/aPXcn2jx6Dg2XTH+iMuOB8fa/7jbLifz24Xse20aze4dTdu3J7Ju4DhczoLG6E6tRUZG8Mqbkzhv2NXk5ebx+jvPsnXLdn6aM9+jXVBwEDePu5b77v4bTZrG8OxL/2DCw/cw8S+P4+vry78/eJmrLr6J5L376d2nB5OnvsjIc0Y1Uq8O7dzHbiKpwrnN+U/czP8qndtEJcYz+IGrmTLyb2At137yEGmb95K6cRdn3HUJeenZLHptOsbhw01f/7NsGUDPUcP45r43yxLhOxZ677Ew5PZ7KVq6mMK5P+J3Wl9C7rqfnKcfrbatiY4h6JrrsdlZZfP8Th+AT1wzcl9+xv18f/or/oOGUTj3xwaJv76lpmeQ53Syet2Gxg6lzj320tsMPP1Uzh92JvOWLOfRF97k6Yfu8Wjz1vvTiIoIY8zoyykuKeGaW/9CYqvmnJLYit9WreP5R+4ntkk0AIuWrWqMbogclWO6VMS4hddVMEcjKC6StpcOYOf3ywHYM3cNLc/tRWiLJlXapq1MIn3t9irzf586m+0zfiVl2RZSlm0hrHUc2ytk4Y8nobGRdL5kAJtnu1+PbfPW0O6cXoRX83okr0pi/7qqr8fxytE0htALhuH8ZREAzsXLCB7aH9+E6jPtETddQ/ZnXzdkiHXmrNHnsnVtEgV5+QAs++E3Lrr98irtHH6+jBh7Cb9+txiAPZt3ERETQad+XQHoc25f8rLz2LJyE2vmr2Ln7+Xbw+GWNZaw2ChOvfhM1s9eBsDmeavpcnZvoipt34PGXMiGn1diSys+b/xlFYPHXgjAqq8XsWvlFnLTs1n8wWysqzxj3ueqoSSv3wGAq8TFhp9WMHjcyIboWq0Fx0XS/tIBbJ/l3td3z11D60Mc+1JXJpFWzb7u4+9L88HdSN+wkz3z1rJn3lqP1+N4MGL0CDat2Ux+6b6waNZirrn96mrbOnOdLJ+3nMy0TM8FBj569WMOpGXy+4oNLJ+/AperpL5DPya+cdFEXTKYzFnuEUHZ81YSfk5f/FvEerTL+HoeeSs3UZyeReoHM7Elrhot83Z10f/seSvJ+N9cnKu3sO3u5/CNDCXwlJYN2o9jcd0fr2LVynXklY4qnDXzJ+68Z0yVdm3bteav9/yDpb+u5LsZc3h20qucOagfAP3P6ENUVATJe/cDsOy3VbRs1ZwBA09vuI7UQGhsJF0qndu0P6cXEZWOd33HXEDST6vcowiApF9W0XfsCAB6XD2ElN93AmBLXGz5aRX9xrmXOfx9SRzUjZQNO9k+fy3b53vvsdBExxAwdDiFSxYAULR8Kf79zsAnNr7a9kFXjib/2/95zHO0bI0JCiqfUViACQmtt5gbWpPoKM4aNKCxw6hz+1PTmTFnLkMG9AGg/2k9+Gnhb+xO3u/R7ouZc+jQtjUAvg4HA/v2Yson7m3gDxefxzmD+9OzSwd6dunAzj37OHtgv4btiMhROmTiwhgz+EgTcAXwl0M9R0OIH9CZ/PRsSvILAfeHUc6OFOIGdK5+hWo+iHL3pJX9bXwM4W3jydy0p17irW8tB3TGmZFNcYXXI3NnCi37Vf96eOsH89EI7NODkgNZ2PzSX8tKXBTvTibgtB5V2oZeej45M+aUtz3OdD2jOyk7yz+o9mzZTYfenXD4Ojzate3RjuCwYFJ2VWibtIcu/d2JizMvHcIFN4/k9aVTOP9mzy/oh1vWWNr170xuRjZFpdu3q8RF+s4UEvt18Ww3oCsZO1PKHqcm7aFtf3ebg+sCNG2XwMynPyp7HBgaRESz6LLHB3anEt/RO7/INBvQmfwMz2Nf9o4UmvWv+b7e6uxexPZqzzVzn+O8qfcTEHX8nbieemZPkncmlz3embSLLqd1rrIvVOSq9Fq4SlwUF7lHExljKCoo5Mcvf6qXeOtKWP9uFGdkYQ9uzyUuCnfuI7R03z7IVtjeA9u1YO/T79Vomberi/7nLCi/VMiVnUdJTh6FyWkcLwYO7sfO7bvLHm/ZtJU+fXvh6+s5mHbt6t85cKA8WZe8dz+7d+0FICw8hMioCIKCAsuW79q5h85dOtRz9LXTqobnNq3P6EJmhc/G9KS9tBrQCQD/0CDC4suP71m7U2nayX18bz+8FwmntueWn5/jynfvJ8iLj4V+3XthMzOhoPT8xVVCSfJe/Lr3rNI24NwRFP48GwryPeYX/boQ/35n4n/mEExoKCY8goI53zVE+A3Gx+fEK+P368q1RIWHExQYALiTEs3jY/ltpefooNw8J8kp5ceyhLimbNrq/lGmWVzTsvklJSVs37WHdm288zxHpLLD7dVPAjOA94CpwBfAnNK/D05vABfWc4yHFRwfTUGG5/Dnotx8guMij+r54vp3Yt+i3+sitEYRFh+Ns9LrUZibT+hRvh7HE0dsE1wHsjzmuXKd+DaN8Zjn26IZPhFhFK45ft/n6PhocjLKL3HJz3XiF+BHWLTnAKjouBjysvMoKSq/xCM/x0lUnPvk7aXbn2Fszxv4aNJ7jHrwBoZfe15Zu8Mtayzh8dHkVdq+C3KdhMdFecyLiI8it8LrU5CbT3hseZvgyFAGjxvJGTecS2BY+bWhG39ZRf/rz8E/OAAfhw/NuyVivPTkJyQ+mvxjPPZtm/ErUzuPZfoV/ySsRRPOe/de9zXPx5GYuCZkV3ivnTlO/AP8iYiOqPVzte3Slkcm/42oplGEhAUfeYVG5BcfQ0mG52VurhwnfnHRVdo6IsOIveUymt44AkdYSI2XebO66v9BAYkJ5CxcQ/H+jHqJtz7EN4sjI+NA2eOcnFwCAvyJjjn8MaD3aT2Y8s6HAPy6eAXOvHxuvfOPAMTGNaF5i2b4+HjXcSC0huc2ofFRHpe/FubkE1p67N/6y2p6Xz8cv+AAjMOH+O6JmNJ+bvj2V17oNpYPrvonES2acMU73nss9Ilpgivb81zHOp2YaM/RJz7xCZjQcIo3rK/yHCU7t5P9zKOE3jue0AceJufFSVBYWKWdeJf9qelEhHsm1YKDgkhJS/eYd0afnnz8v+/IczopLilh3cYkrK06om7pqvWc1qNLlflSMy5rT8jJmx3ujPxvQC9rbWtrbSLuxEWCtTbx4AR0Ag5dBa0hWFv2i+NBDn8/XEVHN8y31Xl92HGcFaaryFpb9ovEQb7+friKvXvYc52wFlvgOYLC+PthiyvUZTCGsGsuJuv9aQ0cXN2yFgorjBbx9fcD8EhQgLtwUFHl7SHAj5IK20NBXj4z3/2aKQ9P5oL/u8ij7eGWNQprKSqoZvuu3G8LxRXaOfwr9TnXSdKidexalcQNb95bNsri84lvs2vFFm546z6G3nYJLXu2Z//m3Xgje6hj31Hs68mLN/DNNU8Q0T6B2F7t6irEBmIpqLAv+JXuC8VFta/HkrInhR+++JFmrZpx//P31VmE9cJaXJXef+Pvh63ms8+V6yRn4WpyV20m8a3x+DVrUqNlXq2O+n9QkxtHsPuJKfUVbb2w1uJ0lv+S7h/gDxx+2w+PCKNZ8zhmzfwJgNSUNK6/5lb6n3k6r771NFePupS4+KZs2pBUr7HXWjXnNtUe7ywe7Sq2+W7Cv9mzMokrJt/DgNsvolnPtqRu9hxdu3PJBj4c9QQx7RJI8NpjocUWVjrX8fODEs9zncCRl5H/5aeHfBbj8CX7nw/haNacsL/+HRyHHqUm3sEYCCzdzw8qKirCt9IIw4f/PI7undpz98NP886HX7D6900ktmpR5fnmzF/C8IF96zVmkbp0yMSFtXaOtXZThVnbrLX7KzXLBK450j8xxowzxvxmjPntp9xNR2peK3nJGfhHev6C4hcaSN6+o/vVJKZnIqkrvOwDuxZykjMIjPB8PfxDAsk5ytfjeFKyPw2f8DCPeT4hwZRUGC4XcGpXwq64kJazP6Hlj58R/dc7COjZlZY/ftbQ4dbKwMuGMGXDx2VTVnomIRHlWfeg0CAK8wvIycz1WC8jOZ3gcM/tISgk0OOuIgf99PFswqLCqsw/0rKGlLkvg6BK/QkICSSr0vadlZzu0a5ym5KiEnatSuKDO18iMzmdVr1OAcCZmcu08ZN5+7onWPLxHGLbJ7D8i3n12KOjl5ecQUBE3R37nKlZJP1vEaHNY47cuBENv3w4X2/6X9l0IC2T0Er7QkF+ATmZtS86nH0gm7nfzOXZ+56nR/+ql5h5k6LkNByV3n+f0CCKqtm3bVExeas2s+32ZyhKTiWkd4caLfNmddV/gLCBPclZuIbCHd53J42KrrzmIrYmLy+b0tLSiYwsH1kUGhqC05nPgUojDyu69c4/8sh4z7sHLFqwlGsu/T/uGPcXiotLSN67n3m/LK63fhyN7Bqe21Ru5x9a3iY/M5eZD77DR9dOYuVHPxHTPoG1X3gWMgXIS81i/fRFhCd457HQlZaKT6jn57EJCsaVVn6u49ulO4HnjyTq/c+J+u9XhNzyJ3y7dCfqv1+5l3friW+HThSt+I3MB+/G0bY9gZdVXxtIvEdskxiysj3P83KdTprGeI40iwgP4+/33cbbzzzCFSOGs3XHbkaePbjK863duIVuHdvXa8widak2dxWJN8aMAb4GsoHOwD+BlMOuBVhr3wLeApjS/Lo6HYOSvGAdwXH/hyPQj5L8Ioyvg5CEmKO63COmexvSV2+ry/Aa3I6F6zhv0v/hG+BHcUERPr4OwhJi2HkcX/5SU/m/rsDx8D2YAH9sQSH4OvCNb0r+0vKKyQVrNrD70pvLHoecO5jgc4aQ8sA/GyPkGls6+1eSRtxb9rj32afTokOrssfNEhP4ffE6rMtzKGDS6i3k5+XTtGVsWU2M+MQEPnv+I6qzdfWWQ8ZwuGUNZcvCtVzx5FiP7TsyoQlJiz2Hwm6at5qm7RLKHjdt24ykRWurPJ91Wfas3UZWctUvO8PvupzN89ew4aeqd2rxBnsWrGPQ057HvtCEGPYew75uXS7S1u6owyjr3sJZC9m4srxSfP+z+9OmY+uyxy3aNmf14jW4XEdfaHLjqo2kJqceU5z1LXvhalrG3eFxvPNPaErOojWHXsnlIm/tVoqq2d4Pu8wL1VX/A9q3wL9VHGn//b4Boj423337IyuWlRdhPuf8YXTqUv6lo237Nixe8Nsht/3rbryKLz79hoyMzGqXh4aFuBMbEyZRUuJdozR3LFxHaKVzm/CEGHZUOt5tm7ea6LbNyh5HJ8azfWHVSyXOuPtSts1fS9KPK6v9f9blYv867zwWFq1ajs9d94O/v/vyDocDn9hYiteUf1YVb1jPgVtuKHvsP2go/gOHkfOk+y5hAQOHUrzN/SOdTU/D+d7b+A8cSv5nHzZsZ6RW+p7alb+nZZBfUEBgQABFxcXs3Z9Kn8Nc7vHGe5/Rr3d3BvXt5TF/7cYtdD6lLcZLL4kSqU5tLt6+D+gCbAWygCVALHDD4Vaqb86UTHbNXk6zge6CXAmDurJ9xq/kJWfQ9ZYRhLdr5rmC4ZDXLbY6vw/bvz0+7yZyUG5KJlt+WE7rM92vR+uBXdk481dy9mVw+rgRHh/oABhOmINWSVoGzl8WEVh6cA7q15vcH+ZRsj+N8BuuxLd1CygqomR/atnkysopm+fNnNl57Nmyu2z65bMfaX/qKWUFCHsM6cU3k92/pETGRnHFPX8A3JeO/PjhLHqddRoAzU9pQXpyGpuWbSAoNIghVw/H4efOX14w5iI+fd590nK4ZY0pJyWT3+cso/2Z7lsWnzKwG6tnLiFrXwaDx15Ik9Lte9EHs+kwuPwX83YDujL/XXfhsbgOLQgMd9cvCAwPxjh82L7McyRY9wv60qJ7Ih/f+1pDdOuoOFMy2TF7Oc1L9/Xmg7qy9Vv3sa/7LSOIqGZfr3zsS7zwdMJauQt1RbRrRsGBXDKT9jZE+EctLzuPnVt2lU2zPptFp17lhWn7DO3DtLfcl4JFx0Zz/b3XVXkOYzxfCh+HDx1PLf8Vvt/wvnzxzpf125FjVJxygKwffiNsoHs7Dx/YkwPfLqBoXzqx4y4loG1zAAI7tMJROvrIER6C8fEhd+nvR1zm7eqi//6t4mgy+jyyf1mBf4tYgjq3ocl15zdOh2ogOyuHzZu2lk2ffPglvU/rUVaMc9jwgbzxyhTAXavi/vF3lq076vrLyc3Nw5mfT8vWzTlvxFn07d+7bLnD4eDFVx/nP+9+zFeff9ug/aqJ3JRMNlc4t2kzsCsbSs9t+lY4t1n+/hwSKxz7W5/RlaXvehad7DjidOK7JfL1PW94zIto6T4WRrdrRv6BXNK99FhoM9IpXLIQv57uz3W/U/tQOP8XXGmpBF5+DT7NW0JxEa60lLLJ5mRDUSGuNPdvjcVJm/Ftd0r5c7pcFG88Pvb9mjp4VzHr5dfs10aT6CiG9O/N4mXuwsKLlq7i7EH9iWsaw5RPvmLrTs9LW7//eSHrNyXxxIN3VTnXnzN/ie4mIsedGo+4sNYWAPcaY/4GdASyrLWb6y2yWlg4/l36TBxFdJdWBDWNZMFf3gEg8dIB5OxKIWuL+8Mnpkci8Wd0ITAmrNoinHF9O7LiueO79gHA9xPfZeiEUTTt0oqQppF896D79eh88QAyd6WUfRjHd0+k1YAuBMeE0bJfJ3YuPv4/tNIe/xdR94zFv2M7HDFRpD36AgAh5w+jeM8+irfvauQI60ZWWiZTHnmb6x/5P5xZuaydv4rVc92/HDVtEcugK4byv9c+p6igkGkvfsToCTdy6V1XEh0Xw0u3ue/b7hfoz8hbLuXSO69k3aI1/PTRbLas2HTEZY3ti4n/ZsT40TTr3JqwppF8Pn4yAD0vPoOMXSmkJu1l38ZdLJj6PSMfcn9p/WXy1+zb5H7vh91+CacM7M66WUvJTs0sWx/cCY7m3RPx9ffjzT/8k+KCoobvYC3Mm/Au/UqPfcGxkcwtPfa1u8R97DuYhGjSI5GEAe5jX3z/TiSXHvuaDejMoKfHsGfBOvYuXM/S5z5vtL4crQNpmbz68Gvc9vdbyc3OZcW8FSz9xX273LgWcZxzxdl8/NonFOYX4uPwYfDIwUQ1jWLwRYPZuyOZ/bv3ExMXw8Nv/o3M9EyWz1/Bnq17mP4f779V8s6Jr5Mw4Y8EdU7Er2kkOx90J9qiLhlE4a79FCTtJu6OKwkb1JPMWUsoTjnAzgdfLVv/cMuOB8fSf9/YKE75+HH8mzcldszFZc+59Y5nGqUvRyMtNZ2Jf3mcR598kOysHOb9vIiff3TfIrNlq+Zc9YeLeeWFyVx06Xk8+9KjHndZyMzMonv7QYSGhTD8nMGc2rs7//3PNObMnttY3Tmi7ya+y7AJo4jt0orQppHMLD236VLh3CZ14y6W/WcWZ/3tWgCWvPUNqZvcX+Zan9GFuO6J+Pr78uEfHvc4vrfq35kLJo1h+8J17Fi4nrkvePexMPe15wm+6TZ827bDRMWQ8/KzAAQMGY5rXzKFu3cedv2CWTPwiY0j8KrR2MxMfJrG4vz4/YYIvUHk5uYx/fs5AHw5Yxajr7iI6KgTo0j9Q38exwtvvceGpO2kph/g7/feAsCMOfNJiIslsWVzFi9fzbqNSRQWFfHOc38nMCCgyvMsW72e22/Q5UHHwnLiJMWOF6ammUhjTBjwEGCttQ8aY/oCHa21tbp/Wl1fKnI82V+bC3NOQFdHeff1w/VtQob33l6tIbQ0gUdudAJrX3zyFj771Hj3iKb69pSpetIoJ48RWd6R9G0Mf4rofeRGJ7Cx3Q6fQDjRhU99t7FDaFQ2P/fIjU5g/i26nxhDug+hU+zpJ+R32t/3/+q171ttLhWZApwJRANYa5cAAcaY4+fnCRERERERERE5rtQmcVFkrR0IVKxwtwO4+RDtRURERERERESOSW0uXjhYltkCGGMCgL8Auw+5hoiIiIiIiMgJxHUCFX49XtQmcfG1MeZDINoY0wUYCYQAFx9+NRERERERERGRo1ObxMVq4BZgBNAKGA/MsNam1UdgIiIiIiIiIiK1SVysBSZZa9+pr2BERERERERERCqqTeLiZ2BR5ZnGmEHWWu+98beIiIiIiIhIHbGoxkVDq03iohj42BjzK5S9Uw5gKNC6juMSEREREREREalV4sIfmA/sBY8UU7s6jUhEREREREREpFRtEhdPAtuttYUVZ5beaUREREREREREpM7VJnGRC7xnjHFaa/9ojOkLDARerZ/QRERERERERLyLy6rGRUPzqUXb/+Cuc5EJYK1dAuwC3qyHuEREREREREREapW42GqtvRZIqjAvD7ikbkMSEREREREREXGrTeJijzHGUFqY0xgTBzwKrK+PwEREREREREREalPjYirwGdDaGDMCd32LfcD19RGYiIiIiIiIiEiNExfW2iRjzFVAX6AV8DiwyFpbVF/BiYiIiIiIiHgTi4pzNrQaXypijPmHtdZlrV1krf3EWjsXSDDGPFSP8YmIiIiIiIjISeyIIy6MMWOBZsAwY0xJpcXRwLXAY/UQm4iIiIiIiIic5GpyqchU4DUgEkistKwQuK6ugxIRERERERERgRokLqy1haWjLoZZa+c0QEwiIiIiIiIiXslaV2OHcNKpUY0La60FfI0x5xpjmhhj4owxU4wxU40x1QURbAAAIABJREFULes5RhERERERERE5SdW4OCfwNpBrrU3FfVvUzsCnwJ/rIzARERERERERkRrfDhV4zVo73xgzEugDdLbWbjPGdKun2ERERERERETkJFebxEWQMeZK4BngqdKkRXPg/4BJ9RKdiIiIiIiIiBdxYRs7hJNObS4VeRqIBR4B/mGMaY37Vqjv10dgIiIiIiIiIiI1HnFhrc3FfVvUg7YDTxtjWtV5VCIiIiIiIiIiHCZxYYy5H5hhrV1X+ngi4KjcDBgGDK2vAEVERERERETk5HW4EReJQGSFx72BECAZyi7qMUB8/YQmIiIiIiIi4l2sVY2LhnbIxIW19o5Ksx4H1lhrCyvONMZ0qY/ARERERERERERqU5yzU+WkRSmHMeZPxpjEugpKRERERERERARql7i4zxjzvjFmmjHmagBjjB8wB/gBuNQY07M+ghQRERERERGRk1ON7yoC9AT2AuuBq40xBcBqIAZYC2wEPgMurusgRUREREREROTkVJvExT+stf88+MAYcx0QCBRbd3WSQmNM17oOUERERERERMRbuFBxzoZWm0tFAo0xUcaYIGPMSKAPEApkARhjgoGweohRRERERERERE5StRlx8QuwHfctUXcA9wNTgY3GmNtx3z51YZ1HKCcM34CSxg6hUfmZ2uQJTzy+mMYOoVEl+boaO4RGU1hc3NghNKqomJP72Hey3zHuQEpuY4fQaPxO8vc+aHiHxg6hUdn8k3fbBzCBIY0dgsgJpcaJC2vtd8aYVsApuG+L6jTGzABKcCctJgAP1E+YIiIiIiIiInIyqs2IC4DmQERp0qI3sMNamwpsAG6s8+hEREREREREvIg92YcTNoIaj103xtwBrALuKZ21Evi7MWZ4fQQmIiIiIiIiIlKbi+6vAzoB3wNYa0uAT4DX6yEuEREREREREZFaJS6+sdZuAo97v5wFhNdtSCIiIiIiIiIibrWpcZFmjBkNNDXG9AeuAu4GnqyXyERERERERES8jEs1LhpcbRIXLYFs4HTgCmAvcBvwTj3EJSIiIiIiIiJSq8TFlcBoa+35FWcaY5rhTmKIiIiIiIiIiNSp2iQuHgdGG2NCKK9z4QDGANfWdWAiIiIiIiIiIrVJXNwOdAAux7NAZ3ydRiQiIiIiIiLipSyqcdHQapO4eBqYY63NqDjTGHNF3YYkIiIiIiIiIuJW48SFtXZabeaLiIiIiIiIiBwrn8YOQERERERERETkUJS4EBERERERERGvVZsaFyIiIiIiIiInNWtVnLOhacSFiIiIiIiIiHgtJS5ERERERERExGspcSEiIiIiIiIiXks1LkRERERERERqyIVqXDQ0jbgQEREREREREa+lxIWIiIiIiIiIeC0lLkRERERERETEa6nGhYiIiIiIiEgNWasaFw1NIy5ERERERERExGspcSEiIiIiIiIiXkuJCxERERERERHxWqpxISIiIiIiIlJDLtW4aHAacSEiIiIiIiIiXkuJCxERERERERHxWkpciIiIiIiIiIjXUuJCRERERERERLyWinOKiIiIiIiI1JBVcc4Gd0IkLhyBfvSZOIqi3Hz8I4JZ+vjHFOU4q7Tzjwyh260X4hcWxOKJU8vmNx/Wg3Pe/4tH25TlW/hm5CP1HvvR8g3wY8iEURTm5BMYEczPkz6msJo+Jw7tQbuzTsX4+LB9wVo2zvgVAB9fB0MevIbigiKCo8PYOnd1jZZ5pQB/Iu+8BVdeHj5hYWS++hY2N++QzYPOHkro5ReTcvu9AJiQEKIm3k9g/z4U79rDgadfpHDN+oaK/qgl9mjHkD+cTaGzgP3b9zH7P99W284Yw5UPjAYgLCaCL57/iIx96VXa3TdlIou/XsC8z370+B9X3D+a6a9OY8PidfXTkVryDfDj/PGjKcjNJygihO8mfUhBNdt+h6E96TisF8bHsGXBWtZ+u6RsWWB4MA/M/xeBYcEAfHDL86z77jcAgiJCGHTLSAJCg5j+8JQG6VNt+Ab4cUGF/s88TP87Vej/mgr9P6j7yP70v+5sJv/hsSr/o9+1w3Fm5pKStJedyzfXW3/qQseeHblw1AUUOAvYs30PX0z56rBt/++Bm/jglf+yctEqj2UXjrqAB565D4CM1Ayu7juaosKieo29rpgAf6L+PBZXnhOfsFAyXnr7sMfB4HOHEH71RSSPub8Bo6w/JsCfqHvGYnOd+ISHkv7i4fsfct4Qwq46/vt/2mk9+OMf/4DT6SQpaQdvvDG12nZdunRg8uTnad++Dd98M5tbb/0LhYWFVdp9+eVUPvtsOu+//1l9h35MfAP8GDxhFIW5+QREBDP3yerPgQIjQuhz64UEhAbxw988X5vWg7px5v1X8vUdr5C1K7WhQq8bvn74DboSCvMhMJiiudPcfx+irW/3wdiCPGzGPlx7k9yz+44AY8BajK8/RQu+bMAOHJv8ggKef+t9QoICycrJ5Z6x1xEaEuzRpqi4mBcnf0CAvx/pmVmccVpPzh0yAIC5i5dx+4QnPNp369ieD1+b1GB9qG8Llizj5cn/4dlHx9O8WVxjhyNSJ06IxEX/J25i908r2fa/xTQf2oMBT93ML3e8WqVdWOs4Iju2oPBAjsf8+P6d+XHsS+Qlu7/MNRvUrUHiPhbnPHYTW39eye9fLyZxSA/Oe+Jmpt/t2eeoxHgGP3A1U0f+Daxl1CcP8f/tnXd8VUX2wL8nvZBQEiAgBAIKCAKidFFQAQtKUVfFtRd01XVt666dVXTXdXfVn2UVV2XVtddVUVxELBSlSVNBidKkBBIIpJf5/THzkvdeXkIC7+W9kPP9fPLJu3Pn3jln7tRzZ87N/XELO9ZuYthvJ1CYu4evnngPiY7iovfvrde5SKT1LddTvOBrimbPJX7oIFr/8UZy75wWMG5UehopF/8ak7+nKizlwnMpmvsFe55/idQpl5D24L1snXQ+priWQUAEkNyyBVMe+h1TT7+FksJifvPoDWz9eQurPv+mRtwJ151FQX4BM598hw7dD+Gax29i2lm3+8QZec6JZPbJ4qv351eFJSQnkJiSTM/Bh/P+ExJynerL+GmX8sNny1n5/kIOG9mPCfdfxmvXPeYTJy0rgzE3n80Tp9+BMYbLX72TnHW/sN2V4YHnnsCbNz9JyV77jLMXrK66tk2X9rQ7rBNFu33biUhhwrRLWev07zGyH5Puv4xX/PRPz8pg7M1n87jTf4rTf5tXHU5p14rjr5lYQ8+E1GR+9fereP+eF8jbuL1RdDoQUlqlcPsjf+DKU6+mqLCYux6/nU0/bWbRZ4trxE1MTqRFSjL9h/blpcdrlume/Xty07nWiJ23M6/JGC0A2tx2HUXzFlH48WckDh9I2h3Xs+PW+wPGjW6bRqvLz6PSqx1s6qTdbvUvmGX1T7/zenL+WLf+Fbubtv6tW7fkmWce4phjTqegoJDnn3+UH3/8idmzP/eJFxUVxcSJpzBx4kV07dqZ//73ec477wxmzHjFJ97FF59L//69eeON9xpTjf3ixPsu4efPlrPmva/oOrIfY/58KR/8tua4r2WX9qT36ESR37gvKT2V2KQEOgw4tLFEDipxJ/yaip9XUbF2MVFd+xA3+gJKZz5dM2J8EnEnX0LZ3Fcxu6uNM1FZ/YhqmUbp/16w9xt7EdE9BlKxtma7GYlMe+RfjBh0JCcffwxffr2Mex56ir/ecYNPnOkvvknrlilcft4ZlFdUcM5Vt5CVeQiHZWWyeMW3/OPum2mX3gaAhUtXBEqmybIjN4/CoiJWfrsm3KIoSlA5YB8XIhJW40di+1Z0mziMjR8vA+CXL1bReewAWnRKrxF35/JsclevrxH+/b9ns37mInKWriNn6TpSurRnfQSvMGjRrhWHTxjGj7Otzj9/uYruYwaQ6qfzoMtPIXvuCnBLmX76fAWDrjgVgL5njyTn+40AmIpKsueuYNCUfZ+LNKLS00gaewLFXywAoGTREhKOHUZ0LdbllAvPpeBt30FZyddLKfp4DmXf/0DunfcRlZpKTFaXkMt+IIw6bwzrV2VTUmgn3t/MXsxpv5lUI150bAwnXz6eJbO+AmDLus2kpLWk55DeVXHaZbYnJS2VLes2+1xbXFDMt/NWsGdnfgg1aRgp7VrRf/xwvp+9FIB1X67i8NFH0cqv7I+4/FTWfraiahnfj5+vYMQV4wCIjovhsGP7sm3NJtbNW8W6easwldXL/TavyGbLtzXbiUggpV0rjvTS/8d66r/WS38PI38znq//M7tGGuc9fh3znv2wSRgtAE7/9TjWrvqRIlcX5s9ewHnXnBswblFBEUu+XMqunbtrnBtx0nAK9hTw3Tffs+TLpWR/91NI5Q4m0W3TaHHK8RR9vhCAoq+WkjRqKDEdA7eDLS85hz1vvN+YIoYUj/6Fn9Vf//zXm77+l112Ht98s5oCt7Jk5sxPuPnmq2vEExEefPAJcnJ2smjRN8ydO5+KigqfOFlZmaSnt2Ht2nWNIvuBkNy+Fb0mDGPd/+wYaH0tYyCAbSuy2R5g3Fe4I58fP14ScllDgSS3JLrXYCqy7WS7cv13RHfvj6Sm1Ygbf9qVlC+d7WO0AIhKy4DYhKpjU14G8YmhFTxIbN+Ry8w5XzBy2EAAhh7dj7kLFrN5q2+f9fZHc+jRzY7lYqKjGTF4ADNe+y8A544/iTHHDaV/7x70792Djb9sY/SIIY2rSAhJb9OaE44dFm4xFCXoNMhwISJ/ChDcSUTuCJI8DSZj2OEU5+6hotgueTQVlezdkEP7YYcHvqCy5n6kgl92Vv2WKCG1Wwa7f/glJPIGg87DDqcobw/lXjrv3phD5yG+OmcO781ur8lHbvYWOg/rBUB8i0RSMtpUncvfvIO2vTrv81ykEX9Ufyp35WNKSmxARSUVv2wlfkD/GnGTTj+FolmfYIpLfMJLliyr+m0KCqgsKKBie05I5T5Qeg87ghyvZ7sl+xcOPaon0THRPvGy+nYnMSWJHZuq9dmavZnDh/YB7IB2zCXj+HD6f2tNqzKC9vBlDe1NYd4eylzZr6yoJG9jDll+Zb/bsD4+E++c7C1kDbVxep0wgE5HdufGuf/gwmd/T1LrlBrpROq+xW5De1Pgp3/uxhy6+enf3U//Hdlb6Da0Os7As0ex/N15lBb7LhXvdeJRpGdl0LFPVy5+7hZO/uNkomN9y1SkMWD4kWzZsKXqeOO6TfQ5uneNuuCNqaysETZ60omcddkZvPPNG5x12RkhkTVUJAzsR8Wu/Oq2raKS8s1biT+6X424LSaezN6Zc2q0g02Z2vRPCKT/pJMp+PDg0H/kyOH8/PPGquO1a9cxdOhRxMT4vk+qqKigrMyuHhIRiotLePXV6u1UIsK1117Kww9PbxzBD5DOQwOPgToNDTzuq7U9j9B2fl9Ede6JKd4L5a79NpWY3TuI6tTDJ150t35Iq3ZEtcskftJ1xB57JkTZdrEiewXR3fsTfdhREJ+EJLag4ruFja3KfrFo+Wpap6aSmBAPWKPEIRntWLzcdztrQWERW3Oqx/cd27flh582ANChfduq8IqKCtZv+oXuXSNznLu/REXp9xdCTSXmoPyLZOpVqkXkChG5CzheRO7y/gOuB34XUinrICmjDSV5vksAywqKSWrfar/u135oL7Yt/D4YooWMlIw2FPnpXFpQTAs/nVtktPZZHlm6t5gW7VoD8NPnKxlwwYnEJsUj0VFk9M1ComSf5yKN6HZtqdjt+/a0srCQ6La+bx6iD+lIVMtUSlfX/WxjOneiZOlyKnfW9AERSbTOSGNvXvUy5+KCImLjY2nhNwlvndGGoj2FVJSVe8UtplV7a5gaffGpzHlxFhXlvm/fIpXUjDYU+pX9koJiUtq39ovX2ideSUExqa7sr/5oEff2vZynz76HVp3acv6/bkIkMsu3P4H0L22g/m0y25HYqgUbv6n5ZvXICcPZsPQH5s+YxWs3PEH/04cx9uZzQqBJ8EjPSCc/r3pVUOHeQuLi42jZpmWD7jP1qnsZf8Qknvrz00y57XLGn39asEUNGdHt0qnc5bsyqrKgiBi/djCmUweiWqZQuiqy+7iGElOL/v79QEynDkSnplCy8uDQv2PHDHJz86qO9+wpID4+nvT0NgHj9+vXm1dffYr27dvSsmV1X3H11RczffqLlJeXB7wu0miR0YZi/3Zwb80x0MGKtGgFRQU+Yaa0GEn21T+61xAqt2RTvmwOJR8+Q3TPQcSOsCszTe5WSmc+TdzJlxJ/6uWUzpoB5U1ja9z2Hbm0TG3hE5aUmEiO37ht+MD+vPrfWRQWFVFeUcG3a7MxpqbResmK7zi6X+8a4YqiRB71Ncf9G8gEWgFZfn+JwPkhka4+GFO12sJDdFwslWX7NxHLPGkgGz6K7D1+xpiqNw0eYuJiqfSffBp84nnH+fi2Z9myPJtJT9/A0KtPJ6N/N3b++Ms+z0UcxkCJb15IbBzGOy9EaHHWBPa+/Po+b5f8qwns/r+ngi1l0DHGUOald2xcLEANA4QxpsZb9Zi4GCrKKujcqwtlJaU1tohENH56g9XHv74bA+UlpT5x/PPm56+/55nzptG2e0c6NZV9zsb46AV260sg/csC6C8iDLtwLPOemRnw9u0O68T6xWupLK+gcNdeFr3yKUdOPCb4egQTYyjxKuOx8a4ulDV8ElZUWMybz7zNI3c+xllXnBk0EUOOMdWrzhwSF4vxnoiKkHLOePJffLORhQs9xhgq66F/6rnj2X0Q6W+Moaio2hdTfHwcQNXqCn82bfqFV155h6ysTKZP/zsARxzRi+LiEtasiWwHvD4EGAMdyLivyWHAlPuNe6JjoNJX/6i0jlT+8qMNLy6gfOUXRPfy2g4RFU3Ju48jrdoRP25K1WqMSEcEElxZ91BWVkaM3yq7u66fQt9eh3LdXX/lmZffZuX3P5CV2anG/ebM+5oTRwwOqcyKogSHevmnMMaUisgVwPHGmDn+50WkRYDLvM9PAaYAXNRyMKOSD9sfWQNSuDWPuFbJPmGxLRIo3JZXyxV1k9Y/i6/vfiEYooWMvVvzSGjpq3NccgJ7/XT2jxfXojpO8e4CZv3xGQCS27Zk+O8m8fkDr+7zXKRRkbMD8bO8S3IiFTnV+znj+h9B8sTTSDp1rD0fG4vEx9Fh1ttsOanaL0T8oKMoWbKcil+2EGkMnzSSS/5yVdXxuqVrSUqtfrYJyQmUFpdQsNv3LUzetlyfeDZuInnb1jHmknEcPXYwZ91svziSmJJE1yO60/WIbrw49ZkQarP/5G/LJTHVv+wnku9X9vO35pLgFS8+OZE9AdqEgh35rHx/Ia06prFx6Q+hETqIBNI/vhb9EwPo32VgDwZNPoEBZxwLWINGTHwsdyx9imlHXUlUTBRRMdX27C3fbyDRr30NN2POHM3vH7ix6nj10m9JaVndBiQlJ1FSXMKeA3CuOvPlD5nyx8sOSM7GpGL7TqJSfVdbRSUnUeG1TDr+yD6knDmOFqeNAezEXuLi6PzpG2w8/qxGlTfYVGzfSbS//kn10z9z7htsGNU09J88eRJPeH314KuvltGqVfXKopSUFhQVFZOXV9OHC0Bu7i7eemsmOTm5vP32cwBcc82lnH76WKZO/T0ALVumMGBAX446qi833hiZX1bbuzWPeP8xUIuaY6CDFbN3F5Lg1y7HJWAKdvmGRUWBVLfnZsemquuiOvUgKiOLsi/epOS1B4k/7zZijh5D+aKPQi3+AdMuPY38Pb5jnYKiItqm+a40apmawtSbfgNYZ5VPPv86119R8z3r6rXr+MM1l4ROYEVRgka9HWsau0lwjoh0BzIAj2lTgDOB6+q4djowHWDGIecHdfPM1vnfktT+MqITYqkoLkNioknumLZf2z3S+nYld+XPwRQvJGxY8C0n/eUyYuJjKS8pIyommpSOaWz00/nnL1fSpluHquPWWRlsWFDzM5/DrpvI+nmryf50eYPORQIli5cRfetNEB9nV15ERxPTvh0ly6o9RJeu/p5t51xUdZx4wigSR48k97Zqly0xXTOJOaQDBe980Jji15tlsxfx06nVb8SOPHEgnXpW78fM6NaRNV9/V2Pv/s8rrQPP9E7t2LHJ+jzIyOrIWw+9wpwXZ/H2Q9Ve5a994ma+/mA+X7z+KZFK9oJvmfjn1j5lv1XHNH7+yrdcr/tyFW27V5f99G4ZZC8M/DlXU1EZsc44/Vm34FsmBdD/Jz/9fwyg/7qF37Jx+Tr+cWL15x/7jhtCv3FD+c/VjwCw9fuNpHfrWHW+sryCnAhbbTX/4wVc/s2VVcfDxgwjq2fXquNO3TqxfOFKKgP4sWgIa1ZEviHLQ/Gib4i+6wYkPg5TUgox0cRktKV4SXU7WLJqDZsnXlp1nDz2OJLGjCTn9/eGQ+SgUrzoG6Lb+unfoab+myb46p88diTbb246+n/wwWyGDKl2lD1u3Gh69672a3DooVl8+eVX+yz7S5eu4JdftgJw663TmDbtH1Xn/vOff/Lmm+/zwgv7XqEYLjYs+JYx7WuOgTZF+DbfYFGx8Xviki+AmFi7vSMqGklpQ+WmtT7xKnM2IW0yqo5NZSUm176Yie5xNCbHrrY0Bbspm/cOMT0GNgnDxeAj+zB1Zx7FJSUkxMdTVl7Olu07GFjHdo8nX3iDIUf15djBA3zCV69dx+GHdWsy20WVyCJS/aEdzDTUOedzwPfAK9jtI/8GZgBhezVVlLObTbOX0WGEdTbY8dg+rJ+5iMKtefS58lRSvQbvgDWz1NJAZZ48kPUfRu7XRDwU5Oxm3SfL6HKM1bnLiD6s/WgRe7flMWjKqVXGim9enEPWcdXOyTKH92HJc7N87tXj1EFkHJHFBzc8WSOdus5FCpW5eRTPW0DCwKMASBh8NEWffkFlzg5a/PpsYjI7Q1kZFdt3VP1V7tkDpTYMILpjB5InnkbxV4uJ7tCe2MO6kXzG+HCqVYOiPYVsWbe56u/LNz+l25E9qhwQ9h05gI+etg42W7ZtxaQbrF+CirJy5r4ymyNPOBqAjod2Im/rTtYtXUthfgF5W3Or/spKyyjYXUBhvu+bDEFqrTONzd6c3ayZs4zux9hPFh864ghWf/Q1+dvyGHHFONJd2f/qP7M51KvsdxvWhwXP2QFZn1MG07pzOwDSu3ekcNdedmT7rrKROtqJcLI3Zzffz1nGoV76r3L6H+un/2F++s9/7iMqSsvJ35pb9Ve0u4Dy0jLy3aeg5z/3ET1H9Sc6ztq0uxzdg/kzZhFJFOwpYMO6jVV/s17/mN4DelXVhcGjBvHadDvpatOuDRffdGHNm4jYvsCR1CKJU845mZhYq/evrjiT5/4+I9SqBI2KnXkUfb6QBDcoTxxyFAWffEnF9p2kXngWMV061WwH8/dWhTV1KnbmUfj5QhKGeOk/u1r/2Fr0N6VNS//8/D2sXbuu6u/FF99g0KAjq5xxjh07kkcesZ/EzMhoxx3u85DR0dEMHFjtsPqUU07gsceeBWDXrnw2b95a9VdSUkJe3m527Yqcr0n5U5izm+xPlpHpxn2ZI/rww4d2DDRwyqm07uY77hOh7olpBLb1dVKYT0X2CqI6W2ekUZmHU/HjUszeXcQcPRZpbb+mU77sE6K7HgHRtnxEd+xO2bJPAKjcvhFpl1l9T1NJxdam8SWl9DatGTn0KL5auhKAhUtWMPrYobRvm8aM197lp42+218//mwB3/2Qzf1//G2NcjBn3tcH1ddEvPFMqnVyrRxMNPRTpuOBrsYYn1ZBRML6rcwFtz7HwNsn06Z3JoltWzH/FrvMPWviMPZuyiF/nZ2UpPXLImN4bxLSUgI64Ww/uCff/L1p7H/9+PbnGHXbZNr2ziS5bauqrR2Hjx/G7k055GZvYcfaTSx9/n8cf+evAVg0/QN2/mAfXebw3mT0zSI6LoZXzr2P8pLqPbF1nYtE8h54mJbXXknsYd2JTmtD3p/t3t2ksSdQsWUr5Rs21nptVFob2v7zH8RktCdlcvVy4Z233xNyuQ+EPTvzefHuf3HeXZdQtKeQb+etZNUXdlVMeud2HHPGSN5/4m3KSkp55+FXOefWCxl/7Zm0zkjj0d88WK80oqKjGDxuOC3btmLIuOHkbNjGzs3h/9rKu7c/y8m3TqbD4Zm0aNuKd279FwD9xg8nb1MOO7K3sH3tJhb++2NOucMuC/3y6Q/Y7sp+t6G9mfTAFWTPX81PC79jzsO+df6QvllkDe1NcloqXYf04uevIust3ju3P8spt04m4/BMUtq24m2nf38v/bet3cSCf3/MOKf/F17618WGpT/w8d9e4/SpF7Fj3RZKi0pY8vpnIdXnQNm1cxeP3PkY1069moI9BSydt4zFn9vPHGZ0as9JZ47hpcdfobS4lOjoKEaeNpI2bVtz/Gmj2LJ+C9s2byc+IY5zr/oV5//2PL5ZuJwPXprJd8si67nvi533/R+tb7iCuJ7diU5rzc57HgIg+eTjKf9lG+XrN4VZwtCyc9r/0eaGK4jr0Z3o9NbscPq3OMXqX3YQ6p+Ts5Mbb7ybBx+8m/z8fD79dB6ffPIFAF26dOLXvz6Tv/3tCdq2TePll59kx4485s6dx48//sT06ZG9JXZfzL79OY67bTJtD7djoP+5MVCvCXYMlOeM0e37ZdF5WG8S26TQaUgvNrn2PDY5gd6TrP+eI351LMtm/I+i3D2BE4tASj/5D3HHnUll205IcktK/2efZ0yvwZj8HVTkbaNySzZl898h9vhzMbnbMGWlVKyeD0DFqnlEpbYhZtDJmKK9RKW0oezrwL6PIpE7rp/CQ9NfYE32enbk7mLqjXYV3sw58+jYvh1ZnQ/hq2Ur+XZtNqVlZTzz96kkxMfXuM/Sld9x9YVnN7b4IaegoJD3PrY7+9+Z+T/OO/N02rRuHs5rlYMbaYglTkTrMibVAAAZr0lEQVT+DDxtjMn2Cz/UGFMvz07B3irSlNjeUDPRQcZ5GZG15LyxuX1b631HOojpRM1BQ3PiwDYuNG0WlG/fd6SDmBnpTeyNbpBp7i/8eq9du+9IBynT2h4bbhHCym+uTwy3CGEl5uxad5E3C2r4ImlmxKZ3O6g7v9Tkbgdl75ZfkB2xz62hU+ki4GkR8X4FJ8DxwKhgCaUoiqIoiqIoiqIokUhlc7fKh4GGGi76AXuAboDnaUUBHWq9QlEURVEURVEURVEUZT9pqOHiYWAScLcxZq+IDAfaAw8EXTJFURRFURRFURRFUZo9DfqqCDANOBqIBTDGzAc6AhODLJeiKIqiKIqiKIqiKEqDDReLjDGjjDF5XmFLgBuCKJOiKIqiKIqiKIqiKArQ8K0i5SISb4wpARCRROBWYFvQJVMURVEURVEURVGUCMOgzjkbm4YaLmYAX4jIeiAOGIH9qsj4IMulKIqiKIqiKIqiKIrSMMOFMWaNiIzEGiq6AK8BHxhjdoVCOEVRFEVRFEVRFEVRmjcNXXGBMaYIeDUEsiiKoiiKoiiKoiiKovjQYMOFoiiKoiiKoiiKojRXKo36uGhsGvpVEUVRFEVRFEVRFEVRlEZDDReKoiiKoiiKoiiKokQsarhQFEVRFEVRFEVRFCViUR8XiqIoiqIoiqIoilJPjPq4aHR0xYWiKIqiKIqiKIqiKBGLGi4URVEURVEURVEURYlY1HChKIqiKIqiKIqiKErEoj4uFEVRFEVRFEVRFKWeGNTHRWOjKy4URVEURVEURVEURYlY1HChKIqiKIqiKIqiKErEooYLRVEURVEURVEURVEiFjVcKIqiKIqiKIqiKIoSsahzTkVRFEVRFEVRFEWpJ8aoc87GRldcKIqiKIqiKIqiKIoSsajhQlEURVEURVEURVGUiEUNF4qiKIqiKIqiKIqiRCzq40JRFEVRFEVRFEVR6on6uGh8dMWFoiiKoiiKoiiKoigRixouFEVRFEVRFEVRFEWJWNRwoSiKoiiKoiiKoihKxKI+LhRFURRFURRFURSlnqiHi8ZHV1woiqIoiqIoiqIoihKxqOFCURRFURRFURRFUZSIRQ0XiqIoiqIoiqIoiqJELNLcvkErIlOMMdPDLUe4UP2br/7NWXdQ/VX/5qt/c9YdVH/VX/Vvrvo3Z91B9VcOPprjiosp4RYgzKj+zZfmrDuo/qp/86U56w6qv+rfvGnO+jdn3UH1Vw4ymqPhQlEURVEURVEURVGUJoIaLhRFURRFURRFURRFiViao+Giue/1Uv2bL81Zd1D9Vf/mS3PWHVR/1b9505z1b866g+qvHGQ0O+eciqIoiqIoiqIoiqI0HZrjigtFURRFURRFURRFUZoIarhQABCRGBGZIiLrwy1LMBCR0SKyQERGhVuW/WF/5BeRriLytIg85RX2hIjcEiBuKxG5T0TeC5LIEYeItBCRO0RkcT3idnR59dS+4kYCIhIrIteKyIY64rwvIucGMc2mlketReT+UJbx2uqXooSSpt6/7QsRObeh9VZEokXkinCNYcKdfjBx/ct1dfUvkUAktL8icqKIzD9Y66KiRBox4RZAiRiigN1AZrgFCRIbgf7hFuIA2B/5t7v/8V5hLwG7AsQVbP1PabhoTYYy4BcgvZ5xWwGlIZUoeFQCa4HOdcR5AlgVxDSbWh4BxBLaMl5b/VKUUNLU+7d9MR/Ib+A1Udi6GK4xTLjTDyYV2L6jrv4lEoiE9vdgr4uKElHoiotmjoicLiJdjTGlwKJwyxMsjDFrgB3hlmN/2R/5jTGF2Im6d9iXxpgak1djTB6w5oCEjHCMMSXAz/WMmwP8GFKBgogxpoJ9yGuMmWmMCdobs6aSRyLyW6gq49+FMi3/+uVJO9SISD8RGdkYaUUyIhIvIlPCLUdj09T7t31hjNlgjJnZwGvKgCUhEini0w8mxphK4Kdwy7EvahvfeBPqNsIYsxbYGar7h4Lm2m4qBwdquGjGiEgn7FtZD5XhkiVENHV99kf+hnjbber5Ux8aomNTy49wyBvReSQiYwBv40GjySsi/YBpjZBOS+B57KqpZouIRGH7r47hliVMRHRdDBPhzpNwpx9Mmrzn/kZsI5rMc9d2U2nqNCnDhYjcJCI3isg8EfmL24f3exG5V0QWiciZLl4LEXlGRG4RkdkiMrm2e7gwEZE/iMg9IvKGiPzD7VfsICJ/9+wVF5ENIrLUDRzDioicIyKLRWSCiLwsIrtE5HcicrSIfC0iO0XkVBG5VES+F5HjRGSOiOSJyGnuNucBnYA/iMhEr3v3F5ElIrJFRAaGRcHg0VpE3hKRPW7/6Vkufy4WkR88ZSCC8ZEfQEQOF5FHReTPIvKpiAwOdKErC2+JyJ1eYWNFZLqI3Atc4RUesM64NIyLj4gkufpwZ40EDwARudulc4GIdBORL0RkvYj0d+efEpHnRKS7q6f/EpFPnPHN25/FX11bcFyANDJFZLuI3CwiHVzY+SLyfyLyN2C8V9yOLr1bnCwnuPbm307Oy1y8dFeeLgySfh2dPNNcfT3VnT/RPZfrnX6v+N2/jYhku7zp7hX/IhFp6dJf7PRY4+J29br+FrF7mv/j5JwlIgNClUdBeN7HisiT7tznInKIiKQBFwDtxfYP/bzSmyy2/V4irv2WAP2H2DdRN7u4p7ryMkFERontI54Qkc3u+qr6JSLxwMVAqks7lKshzgaygCkiconYOn2niHwo1sdNrIiMceXnCifzThH5m8vrT0Rkt4hcLpYrRWS1u2aFiGwTkYtDKP9+4Z71nSLyqiuLxwODgdFS3T7VKC8i0tOVyadE5BoR2Si23WwjIjNEJFdEnnHXjxaRj0XkNyLyjsunR0UkUo1E/v3buSJS4sprkssLA9aoV58yEUphG1DvHxGR913YRFc/J4nI2yKSLyJXet0zS0SeFdsnPeiXnv+Ysae7/5Mi8id3r4/Fth0B2wSve00WkdtFZK6I3F+f9IOUZ72c7H8Tkc9EpLOInOHy6O8i8pGItHBxj3B15AERKRKRhLrKhLvmarH9/L/Etv8hnxdIgHGYk+NOEVkoItd6xT1ZrK+iu0SkQkSWie2TfMY3YscA94jIra6On0z924gerlw8JXYctM7l3UARmSq2zXlLqvuOBBF53Mn0DBDWOUGAMnKsiLzp6ttfxLZx/3bRa+SJojQpjDFN4g/oAzzhfqcAfwRuBUa4sLFAAdAWuBZ41oX/ClhZ2z3c76uA+93vKGC5u3cMcAOQDYzG7pdeBVwRAfmRivVJcQ+QCJzjjs92OtyE3SfaFms5v9XFuxWY53UfA3R1v7u647PcPZ4Cng+3rgeQRz8DfweSgMnABqANdk/kw7jGO9xyNlD+BGA10MrFOQvIAVLc8VRghvsdD8wCprrjju7aOHf8GDDX/Q5YZ9zxV8DvvI6fBaJCoO8a4Az3eySw2ZMOcDeQDLwFRLuwl4DX3e9/Al3c7ynYLTMxwCjgZ697DPVK7yjgC6/j973y7m/AXe7374H3vPJ0IzDB67rngqRfErAA6OnCBgIlrl62AL4FXgf6ApM89dXF/Q0w0SutROw2iYtdPkwCcoEzgGjgI+A+F3c0sMpLv1xgSqjz6ACf92LgOPf7A+Am97vqebvji4F1wDCq2+9L3blA/Ud7J4sBznT5dSjwiZcc93np6V2/qp5HI7UNo1yaj7uwOBd+jdfzfxrrl2QIdt/6lS4fzgR+cddlOH1vw/Yr04BiXH2KhD/gCCDb/fb0aWnADK/8jw5UXtxzegr4EujhdNyGbTPaAB2wflt6uDxc4a7rAJyCfZt6brjzoJYy4NM/uPD1wCj3O4vqNqLeZSLEcu+r3qe6sjjXq1znYvurVKfrZndOsFtcD3fHZ3npG2jMGO3uswwYBHR36T/p4tU2phwG3OHCW7vwcXWlH6S8SnL3T3LHn2ONIzuATBe2GjjT/X4daOd+3wkk7KNMpLqyH+XyJh842p3rGkxd/PTyH4ddAJzvzvVwda6vy+s9QLo79wHwkvvt3/5eA5ztfh8LnOx+z2DfbUQCMB3bx/bFvtRpCbziJfM84EH3+yGq+8j22Ho0qrHqfj3KyEPAu8Cn2P6rE1AOHOafJ/qnf03tryk55ywELhSRtdgBx7PAF0Cp2FUBCe64I7Zh+p+ItMYOvFvUcQ+wDd6tYPf2ichz2Inan0VkF3ZAMBtARL7BDvTCijEm38k2xxhTJPbLCanGmNcARGQZVi/PPtiXXbxFQJ1vVYwxb7h7LMIaRJoy7xljCp0uHYwxuSKyG3jXGPN1uIWrBz7yYwdLRcYYj0Oqt7CD8jOAf3tfaIwpEZGtXkHXYI1WHueKi7ETAs99AtUZsIPje0Xk/7Ad4Hpj98AGm5ewhre3sIPVVsCJIjIbO/nuB3QBfiv2BehOoKXYgzOANS68NXbyUeWUU0QeAD42xiz0Su8m4EOv48XYwRrYQUyB2JUZvXH54fL0Uayh510RGYEdKARDv8OxA4s1Lq3FIvIdcJEx5k8ikgPMNMasBFaKWzEhIlcDxcaYdzwJubq+3f0ud21FvjHmLXfNYmx5Avu8i7z0y8ZOckKdR/v1vN211wFLxL6pTce3vPqz0RizwOn9jZfeF1Oz/8jAGggB3jLGGHddFPCaiNwEPOKlp3f9CgeTgXQRud4dzwMSvZ7/PGPMLve8o4BZxpgy1z9kABhjtrr8fcn1K9Ow+TsG+FdjK1QLPwAXiEgsdlICNZ/5YAKUF6/nFG/sfnTcGOArY0yuO94KZBhj1opILvCBMWYLsEVEPgFOA14h8vDvH8B3iX/V74aUiRBTZ713ZXCLl9ylIrIHeMOdW+Ql52jsM/b4svH+glSN8Z4xpkJEdgDLjTGLwH6ZAmv4hcBtQkcXXulVz2ZhJ991pR8MxmPHn4XueBLWSfJMY8wGETkGO4H31IW9wOtuxcI/qXakXFuZyBeRk1zYWOzktq62NCj4j8Pcm//FfvnbAdsPtcD1T1jDW3d3D//2dy/wVxEpwhrY2wZIurY2otiVuUVe/etkIM1Lpu/AruzAlpduTo5tIrLxALPkQKitjDwKLDPG/AjVbRy2LVWUJkuTMVwYY34Su3z1MewqiF9jvTe/bIzxOCT0bP2IwVpwd2EHcpPruMd24DDsGwcP64BDPEn7iVKOtdpGAt6yVfidq8S+xTDiu8q1IfKX04TKyD7w1sXQ9PZveuT3KavO0PYz1qAQCG89+2G/RBGI7QSoM443sW95TscaOl5ouPj14iVgmYgkYd/EPQpciO2EP8PW953GmIe9LxKR9tgJ7SOeiabXuV7Y/DoFmxefeJ3uB3gbMrzZBPwB28kvxL6l8jAduNNNms8C7giSfv7tENi2yPNsayu347HP7Vm/8ICDVYd3O/AJcKvLx1zsgPy/7lwo82i/nrdjC3AvduXId9Tf34N3O1Bb/9EVql9JOi4CnsPWn78Ad7nwcLcjmdhJWKA88p6gVPj1A5XUkmduEJ+NnVBGBG6Scgi2vHkMtP7y11Ve/J9TwP6yluRXY99aRjL17av3q0wEmX3Vex85AxyXU/2s+mHfyNegjvGeP6upLuu1tQmZwAvGmJdc+MMu/Kba0g8SXbDGHQCMMTtdurucMf51bDvseW43Ytve5Vij4zXs2/+CYNvSF7ErLhprW5R3f5YJ/MkYM98de/I3CWtIPhHbJ2UBr/rdw8MLWGPC61gD0q8CpLmvNsL4xf0pwHjjaKyxKJTPvSHUVkYiee6iKPtNk/Fx4QYt72CXkX2K7fy2YAfFnjitRKQHdlCZZIx5CmuFreseYBvG3t7JUfsEr7kRqXt7mysbgG5i99R7EOr3hZB87Fv9QASsM1D1BYtHgZux24qyGyx1PTDG/IBdqnkd1qP5C9i3B6cDc7D1/Rj3hh8AERmCXVUU5eJ5wg8TkTbusAw4H7hOfH0P1JUfT2K3HLyI3a7hLecu7OTpDkCMMXsDXL8/+m3A+kg4xOuy+jzbS4ExInJBfeQIINcSrLOuS9y9zjDG/OROhyyP9vd5uxU2nwL/NMbM2Q+VPW1abf1HIKKMMSdijXs3i8gJ+5FuKNgCnCleM1BXJw6UOCKoD3T5fbUxZpoxpra3m7W1DwdKROVFPagkgico9aj3DSEf2x/G+Z+oY7znj/fzra1N8Al354bUlX6Q2AyMEJFkr3SPAWYC9xhj/Fd4tDTG/Aq7EmQStr2CWsqEiPTEtuN3GmO+D4H89cU/32NE5Gi3iuAmrD+GC4EXjTG1rXzKNMbcjR3LxwMP1JJOfduILcA4EUn0i+v5TG9t/WJjU1sZUZSDkiZjuMC+jZxojMnHeo0X4GXgL2Id1h0P/BW7l28A0NYtKx0FJIpIt1ruAbbhvtDFB7v385/udxQ1J++RMpkX/GTxHsC6wyivuAT4XYZ18NXL/14B4jY1asjulT8RO7DzIlDev4s1LJwLdmCFXU75gdc1/s/ac/w6cJLXpCsLu8w8ltrrjIenXZx5B6jTvngJO1B52RizGvs237itKQuxe9Nniv2M7znAsc6w8jrwnFhntGOA690ycMFOnFdgjTMviHPE5q65QEQ822WysHkQQ3V+JAHHUDM/HsZuT3kriPotwL4puxxARKKxg+4Xva73LrfeE/ArgcdE5FC/8544tbZjIjIUGIrdEvI5kOdVT0KdRw1+3tgVIV1c2odgB6qetEuxxp8YN+Goq02rrf/A5Yt3Xt+MFexVl0/idS/P71J3nac9DSWl2C1RrwH9gVfEOmT9A9XbaWr0D/7Hfv2Fx2HtIdjy8lEI5N5fBmC3hcWLyGgX1g47IWstIlnUXl6gHnnhd+zJCwGGY99iRxq19W/bgGFil7R7+omOXtc0pEyEirrqvUcmbzlqtF9Ozg+whofbXHCWO9eR2sd7UL2tBmx/5/m6Wm1twsvAJBF5TKyTywewfi7qSj8YePr1l0VkmNgtIEOxdT/NGR46A0liV4pdLyIxzqDr/eWh2srEEditGKlinXy3dL87ea4NcXnwtLEvY18s/Mm9XHgE2Oj6lmnY8rIEWOFnJPIuJ+eISCf3YuUefNvl+rQR3vKANQ4lA++LyElinaP3wn4SfBl2+2yciKRjfai08+szGotAZaQ9dc9dqvIkhEY3RQkNJgIcbdTnD9u57MFaUe/D7r9NwBod8rAD/gEu7jjskufPgJOxywOvCnQPFz8K+Ae2oboXuB1bwdthB93bsY1bf6xzt89wDi3DmB+nYhufR7F7MO/CLnO7CtspP419C/pbF34Xdsn5wy7c47joGWxDPNLpbrDODbtgO5McYHC4n/9+5M8Ep+djTpdbnW6/d+EvA4eEW879kP8SrNPGeVjfE48BR7hrMrEO6NYAR2Kdk63BTka7uji3Yzvu99y1c11dClhn/GR6HkgOsd4ZwF+9jm/01Gt33Bc7+Njt5El04Z5J3G7svuQsrO+Dp7GOBse5sAqs09pB2KXV/+d0fRW7QuC/7twV7l7vYp3WbcfL2aRL8w2sUSSY+nXHvh18DDt48zigPMHVxdlYY0Yytg0zwGVYR4U5wPfYZbVDsStRXnfl55+uPE3ALnufg91i0Qc7wN+AbRsr3D1XuDRCmkcH8Lyfc+X1H9hJwxqvfPnGlYHOwNvY8j4KWyc87XcXAvQf2Dd1nny9HesXAawjxHexBow/uTCf+oXtMz529+oR4npyN3aJ+ATsm8p17vn/3p33PP/XsP3DFKfTVJfn09yxx8GcwZa532F95vQNdxvop28X7OR2LbYur8A6mDsVu0/d4yS2Rnlxz+ZL7Fv+fsAIV1bfdPc9G1s3nsROQOZiJwM3YNvYs8Otf4D8qKt/ONmV6c+x45a1wNUNLRMhlr/Weo+ddL3pntFQ7Da/MuBxbJ326OpxsjsO60B9IXaFl0ff4wk83pvqys8fsHX8HqqdgwYcU7pzv8XWuU04R5L7SL9BfUMdeXWcK7s73f2jsT4gtrm8eAz4Gjtenev+bsY6T/Y44q6tTKRiDQIbXdl5D2uYTca2MQbrzyEounjpdBZe4zDsGHyae+Y/ej2reKxBPxe71cG4fOhPzfZ3KrYdvA3rnLKLl+77aiN6YsdUG4GRXnKOxPYZedi2wFNODsWOI35wci8H7sc5TQ9De+BfRvq4Z/w5tl8ch/UT4nFw65Mn+qd/TelPjAn3Fl1FUSIdtwzxXmPMjeGWJRIQu+f5AmPMfeGW5UARkfOwWz7mu+M47KRmnjFm2QHc96DJo4Mdsfuhs4wxP4dblnAjInOxX86ZEWZRlBAgIlOxhvyLwyyKsg/cyrXRxpjH3HE0dlJ+ojHmobAKpyhKWDhYHC8qihICxDqiGoR9SxGJy6UbFbdMvRN2D/FNYRYnWPwFuElEooxdqp2CfXu3an9udpDm0UGL11LwprwtMJgE2k6hHDzo82063AbkiEiyMaYAu9pkNHb1m6IozZCm5ONCUZTGZwh2me1yY8zycAsTAYwG/gy8ZozZFm5hgsRV2KXFO8R+fvWvwKPGmLL9vN/BmEcHJW51ze/c4cVuD3yzRUTGYX2mnC4iXcItjxJcRORI7NbIISIyKNzyKPvkfuxWxvUi8hN26/anxph14RVLUZRwoVtFFEVRFEVRFEVRFEWJWHTFhaIoiqIoiqIoiqIoEYsaLhRFURRFURRFURRFiVjUcKEoiqIoiqIoiqIoSsSihgtFURRFURRFURRFUSIWNVwoiqIoiqIoiqIoihKxqOFCURRFURRFURRFUZSI5f8B43fTIP5h4q4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1440x1440 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "corr_data =df_2012.iloc[:,[2,4,5,6,7,8,9,10,11,12,13,14,15,16]]\n",
    "\n",
    "cor_mat=corr_data.corr()\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(20,20)) \n",
    "sns.heatmap(cor_mat,annot = True)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_2012_feat_pre=df_2012[['season','hr','weathersit','temp','hum','windspeed','casual','registered','cnt']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<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>season</th>\n",
       "      <th>hr</th>\n",
       "      <th>weathersit</th>\n",
       "      <th>temp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>casual</th>\n",
       "      <th>registered</th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8645</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.66</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>5</td>\n",
       "      <td>43</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8646</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.66</td>\n",
       "      <td>0.1343</td>\n",
       "      <td>15</td>\n",
       "      <td>78</td>\n",
       "      <td>93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8647</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0.32</td>\n",
       "      <td>0.76</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>16</td>\n",
       "      <td>59</td>\n",
       "      <td>75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8648</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.81</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>11</td>\n",
       "      <td>41</td>\n",
       "      <td>52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8649</th>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0.28</td>\n",
       "      <td>0.81</td>\n",
       "      <td>0.0896</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17374</th>\n",
       "      <td>1</td>\n",
       "      <td>19</td>\n",
       "      <td>2</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.60</td>\n",
       "      <td>0.1642</td>\n",
       "      <td>11</td>\n",
       "      <td>108</td>\n",
       "      <td>119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17375</th>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>2</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.60</td>\n",
       "      <td>0.1642</td>\n",
       "      <td>8</td>\n",
       "      <td>81</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17376</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>1</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.60</td>\n",
       "      <td>0.1642</td>\n",
       "      <td>7</td>\n",
       "      <td>83</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17377</th>\n",
       "      <td>1</td>\n",
       "      <td>22</td>\n",
       "      <td>1</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.56</td>\n",
       "      <td>0.1343</td>\n",
       "      <td>13</td>\n",
       "      <td>48</td>\n",
       "      <td>61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17378</th>\n",
       "      <td>1</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.65</td>\n",
       "      <td>0.1343</td>\n",
       "      <td>12</td>\n",
       "      <td>37</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8734 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       season  hr  weathersit  temp   hum  windspeed  casual  registered  cnt\n",
       "8645        1   0           1  0.36  0.66     0.0000       5          43   48\n",
       "8646        1   1           1  0.36  0.66     0.1343      15          78   93\n",
       "8647        1   2           1  0.32  0.76     0.0000      16          59   75\n",
       "8648        1   3           1  0.30  0.81     0.0000      11          41   52\n",
       "8649        1   4           1  0.28  0.81     0.0896       0           8    8\n",
       "...       ...  ..         ...   ...   ...        ...     ...         ...  ...\n",
       "17374       1  19           2  0.26  0.60     0.1642      11         108  119\n",
       "17375       1  20           2  0.26  0.60     0.1642       8          81   89\n",
       "17376       1  21           1  0.26  0.60     0.1642       7          83   90\n",
       "17377       1  22           1  0.26  0.56     0.1343      13          48   61\n",
       "17378       1  23           1  0.26  0.65     0.1343      12          37   49\n",
       "\n",
       "[8734 rows x 9 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2012_feat_pre"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "X=df_2012_feat_pre.iloc[:,:-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "y=df_2012_feat_pre.iloc[:,-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_mod = pd.get_dummies(X, columns=['weathersit'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_mod = pd.get_dummies(X_mod, columns=['hr'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_mod = pd.get_dummies(X_mod, columns=['season'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['temp', 'hum', 'windspeed', 'casual', 'registered', 'weathersit_1',\n",
       "       'weathersit_2', 'weathersit_3', 'weathersit_4', 'hr_0', 'hr_1', 'hr_2',\n",
       "       'hr_3', 'hr_4', 'hr_5', 'hr_6', 'hr_7', 'hr_8', 'hr_9', 'hr_10',\n",
       "       'hr_11', 'hr_12', 'hr_13', 'hr_14', 'hr_15', 'hr_16', 'hr_17', 'hr_18',\n",
       "       'hr_19', 'hr_20', 'hr_21', 'hr_22', 'hr_23', 'season_1', 'season_2',\n",
       "       'season_3', 'season_4'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_mod.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "#splitting into fit and test data\n",
    "from sklearn.model_selection import train_test_split\n",
    "X_train, X_test, y_train, y_test = train_test_split(X_mod, y, test_size = 0.3, random_state = 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(6113, 37)"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "from math import sqrt\n",
    "from sklearn.metrics import mean_squared_error"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "K: 1\n",
      "training RMSE for knn regression: 0.0\n",
      "testing RMSE for knn regression: 4.4845318959541185\n",
      "\n",
      "K: 3\n",
      "training RMSE for knn regression: 1.9393300763667352\n",
      "testing RMSE for knn regression: 4.264715629209586\n",
      "\n",
      "K: 5\n",
      "training RMSE for knn regression: 2.3634423291849025\n",
      "testing RMSE for knn regression: 4.3649780289753615\n",
      "\n",
      "K: 7\n",
      "training RMSE for knn regression: 2.6657770900493816\n",
      "testing RMSE for knn regression: 4.27573464266204\n",
      "\n",
      "K: 9\n",
      "training RMSE for knn regression: 2.8559942366283186\n",
      "testing RMSE for knn regression: 4.163565055840469\n",
      "\n",
      "K: 11\n",
      "training RMSE for knn regression: 3.0676474877609072\n",
      "testing RMSE for knn regression: 4.434262414410805\n",
      "\n",
      "K: 13\n",
      "training RMSE for knn regression: 3.2778891659501492\n",
      "testing RMSE for knn regression: 4.526324524179744\n",
      "\n",
      "K: 15\n",
      "training RMSE for knn regression: 3.527125818099893\n",
      "testing RMSE for knn regression: 4.632421908660346\n",
      "\n",
      "K: 17\n",
      "training RMSE for knn regression: 3.7500893531979727\n",
      "testing RMSE for knn regression: 4.787315675795072\n",
      "\n",
      "K: 19\n",
      "training RMSE for knn regression: 3.963821457053139\n",
      "testing RMSE for knn regression: 5.061796497423346\n",
      "\n",
      "K: 21\n",
      "training RMSE for knn regression: 4.1265056457336735\n",
      "testing RMSE for knn regression: 5.238158826670223\n",
      "\n",
      "K: 23\n",
      "training RMSE for knn regression: 4.30193143744033\n",
      "testing RMSE for knn regression: 5.303005489524041\n",
      "\n",
      "K: 25\n",
      "training RMSE for knn regression: 4.441319219292374\n",
      "testing RMSE for knn regression: 5.471929380098573\n",
      "\n",
      "K: 27\n",
      "training RMSE for knn regression: 4.613592158002663\n",
      "testing RMSE for knn regression: 5.633620746339742\n",
      "\n",
      "K: 29\n",
      "training RMSE for knn regression: 4.730281044944662\n",
      "testing RMSE for knn regression: 5.743309441277013\n",
      "\n"
     ]
    }
   ],
   "source": [
    "Training_RMSE_knn=[]\n",
    "Testing_RMSE_knn=[]\n",
    "for K in range(1,30,2):\n",
    "    print(\"K:\",K)\n",
    "    \n",
    "    knn = neighbors.KNeighborsRegressor(n_neighbors = K)\n",
    "    knn.fit(X_train,y_train)\n",
    "     \n",
    "    y_training_pred_knn = knn.predict(X_train)\n",
    "    \n",
    "   #training\n",
    "    error_train_knn = sqrt(mean_squared_error(y_train,y_training_pred_knn))\n",
    "    print(\"training RMSE for knn regression:\",error_train_knn)\n",
    "    Training_RMSE_knn.append(error_train_knn)\n",
    "     \n",
    "    y_test_pred_knn = knn.predict(X_test)\n",
    "    #testing \n",
    "    error_test_knn = sqrt(mean_squared_error(y_test,y_test_pred_knn))\n",
    "    print(\"testing RMSE for knn regression:\",error_test_knn)\n",
    "    Testing_RMSE_knn.append(error_test_knn)\n",
    "    print(\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "no_neighbor=range(1,30,2)\n",
    "Training_RMSE_knn=np.array(Training_RMSE_knn) \n",
    "Testing_RMSE_knn=np.array(Testing_RMSE_knn) \n",
    "plt.figure(figsize=(15,10))\n",
    "TA_inter,=plt.plot(no_neighbor,Training_RMSE_knn,label=\"Training_RMSE_knn\",color=\"red\")\n",
    "VA_inter,=plt.plot(no_neighbor,Testing_RMSE_knn,label=\"Testing_RMSE_knn\",color=\"green\")\n",
    "plt.legend([TA_inter,VA_inter],['Training_RMSE_knn','Testing_RMSE_knn'],fontsize=14)\n",
    "plt.xlabel(\"Number of k nearest neighbors\")\n",
    "plt.ylabel(\"RMSE\")\n",
    "rcParams['font.family'] = 'Times New Roman'\n",
    "rcParams.update({'font.size': 14})\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "training RMSE: 2.8559942366283186\n",
      "testing RMSE: 4.163565055840469\n"
     ]
    }
   ],
   "source": [
    "knn = neighbors.KNeighborsRegressor(n_neighbors = 9)\n",
    "knn.fit(X_train,y_train)\n",
    "     \n",
    "y_training_pred = knn.predict(X_train)\n",
    "    \n",
    "#training\n",
    "error_train = sqrt(mean_squared_error(y_train,y_training_pred))\n",
    "print(\"training RMSE:\",error_train)\n",
    "\n",
    "y_test_pred = knn.predict(X_test)\n",
    "#testing \n",
    "error_test = sqrt(mean_squared_error(y_test,y_test_pred))\n",
    "print(\"testing RMSE:\",error_test)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "14645    224\n",
       "14653    792\n",
       "11361    114\n",
       "11728    223\n",
       "12755    335\n",
       "        ... \n",
       "12374    645\n",
       "14025    579\n",
       "8905      49\n",
       "14608    296\n",
       "15324    900\n",
       "Name: cnt, Length: 2621, dtype: int64"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_test"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}