AdaBoosting.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "fdc518a6",
   "metadata": {},
   "source": [
    "This mini project aims to utilize the power of machine learning and boosting to create a model that will predict and provide guidelines for employees when picking mushrooms. Using the feature, the model will indicate if a particular mushroom is good or bad."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f100e378",
   "metadata": {},
   "source": [
    "# Library and data import"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "678d834a",
   "metadata": {},
   "source": [
    "Import required libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e3d2f2a6",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd \n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e4aa9023",
   "metadata": {},
   "source": [
    "Data import"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "aad9054c",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>class</th>\n",
       "      <th>cap-shape</th>\n",
       "      <th>cap-surface</th>\n",
       "      <th>cap-color</th>\n",
       "      <th>bruises</th>\n",
       "      <th>odor</th>\n",
       "      <th>gill-attachment</th>\n",
       "      <th>gill-spacing</th>\n",
       "      <th>gill-size</th>\n",
       "      <th>gill-color</th>\n",
       "      <th>...</th>\n",
       "      <th>stalk-surface-below-ring</th>\n",
       "      <th>stalk-color-above-ring</th>\n",
       "      <th>stalk-color-below-ring</th>\n",
       "      <th>veil-type</th>\n",
       "      <th>veil-color</th>\n",
       "      <th>ring-number</th>\n",
       "      <th>ring-type</th>\n",
       "      <th>spore-print-color</th>\n",
       "      <th>population</th>\n",
       "      <th>habitat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>p</td>\n",
       "      <td>x</td>\n",
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       "      <td>p</td>\n",
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       "      <td>k</td>\n",
       "      <td>...</td>\n",
       "      <td>s</td>\n",
       "      <td>w</td>\n",
       "      <td>w</td>\n",
       "      <td>p</td>\n",
       "      <td>w</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>k</td>\n",
       "      <td>s</td>\n",
       "      <td>u</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>e</td>\n",
       "      <td>x</td>\n",
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       "      <td>y</td>\n",
       "      <td>t</td>\n",
       "      <td>a</td>\n",
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       "      <td>c</td>\n",
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       "      <td>k</td>\n",
       "      <td>...</td>\n",
       "      <td>s</td>\n",
       "      <td>w</td>\n",
       "      <td>w</td>\n",
       "      <td>p</td>\n",
       "      <td>w</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>n</td>\n",
       "      <td>n</td>\n",
       "      <td>g</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>e</td>\n",
       "      <td>b</td>\n",
       "      <td>s</td>\n",
       "      <td>w</td>\n",
       "      <td>t</td>\n",
       "      <td>l</td>\n",
       "      <td>f</td>\n",
       "      <td>c</td>\n",
       "      <td>b</td>\n",
       "      <td>n</td>\n",
       "      <td>...</td>\n",
       "      <td>s</td>\n",
       "      <td>w</td>\n",
       "      <td>w</td>\n",
       "      <td>p</td>\n",
       "      <td>w</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>n</td>\n",
       "      <td>n</td>\n",
       "      <td>m</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>p</td>\n",
       "      <td>x</td>\n",
       "      <td>y</td>\n",
       "      <td>w</td>\n",
       "      <td>t</td>\n",
       "      <td>p</td>\n",
       "      <td>f</td>\n",
       "      <td>c</td>\n",
       "      <td>n</td>\n",
       "      <td>n</td>\n",
       "      <td>...</td>\n",
       "      <td>s</td>\n",
       "      <td>w</td>\n",
       "      <td>w</td>\n",
       "      <td>p</td>\n",
       "      <td>w</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>k</td>\n",
       "      <td>s</td>\n",
       "      <td>u</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>e</td>\n",
       "      <td>x</td>\n",
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       "      <td>f</td>\n",
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       "      <td>b</td>\n",
       "      <td>k</td>\n",
       "      <td>...</td>\n",
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       "      <td>w</td>\n",
       "      <td>p</td>\n",
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       "      <td>e</td>\n",
       "      <td>n</td>\n",
       "      <td>a</td>\n",
       "      <td>g</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  class cap-shape cap-surface cap-color bruises odor gill-attachment  \\\n",
       "0     p         x           s         n       t    p               f   \n",
       "1     e         x           s         y       t    a               f   \n",
       "2     e         b           s         w       t    l               f   \n",
       "3     p         x           y         w       t    p               f   \n",
       "4     e         x           s         g       f    n               f   \n",
       "\n",
       "  gill-spacing gill-size gill-color  ... stalk-surface-below-ring  \\\n",
       "0            c         n          k  ...                        s   \n",
       "1            c         b          k  ...                        s   \n",
       "2            c         b          n  ...                        s   \n",
       "3            c         n          n  ...                        s   \n",
       "4            w         b          k  ...                        s   \n",
       "\n",
       "  stalk-color-above-ring stalk-color-below-ring veil-type veil-color  \\\n",
       "0                      w                      w         p          w   \n",
       "1                      w                      w         p          w   \n",
       "2                      w                      w         p          w   \n",
       "3                      w                      w         p          w   \n",
       "4                      w                      w         p          w   \n",
       "\n",
       "  ring-number ring-type spore-print-color population habitat  \n",
       "0           o         p                 k          s       u  \n",
       "1           o         p                 n          n       g  \n",
       "2           o         p                 n          n       m  \n",
       "3           o         p                 k          s       u  \n",
       "4           o         e                 n          a       g  \n",
       "\n",
       "[5 rows x 23 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filePath = 'data/mushrooms.csv'\n",
    "data = pd.read_csv(filePath)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b9ad5f2",
   "metadata": {},
   "source": [
    "# Data Exploration Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "063aa6e2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(8124, 23)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get the shape of the data\n",
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "6b05806b",
   "metadata": {},
   "outputs": [
    {
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       "      <td>3656</td>\n",
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       "      <td>6812</td>\n",
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       "    <tr>\n",
       "      <th>gill-size</th>\n",
       "      <td>8124</td>\n",
       "      <td>2</td>\n",
       "      <td>b</td>\n",
       "      <td>5612</td>\n",
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       "      <th>gill-color</th>\n",
       "      <td>8124</td>\n",
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       "      <td>1728</td>\n",
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       "    <tr>\n",
       "      <th>stalk-shape</th>\n",
       "      <td>8124</td>\n",
       "      <td>2</td>\n",
       "      <td>t</td>\n",
       "      <td>4608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stalk-root</th>\n",
       "      <td>8124</td>\n",
       "      <td>5</td>\n",
       "      <td>b</td>\n",
       "      <td>3776</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stalk-surface-above-ring</th>\n",
       "      <td>8124</td>\n",
       "      <td>4</td>\n",
       "      <td>s</td>\n",
       "      <td>5176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stalk-surface-below-ring</th>\n",
       "      <td>8124</td>\n",
       "      <td>4</td>\n",
       "      <td>s</td>\n",
       "      <td>4936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stalk-color-above-ring</th>\n",
       "      <td>8124</td>\n",
       "      <td>9</td>\n",
       "      <td>w</td>\n",
       "      <td>4464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stalk-color-below-ring</th>\n",
       "      <td>8124</td>\n",
       "      <td>9</td>\n",
       "      <td>w</td>\n",
       "      <td>4384</td>\n",
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       "    <tr>\n",
       "      <th>veil-type</th>\n",
       "      <td>8124</td>\n",
       "      <td>1</td>\n",
       "      <td>p</td>\n",
       "      <td>8124</td>\n",
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       "    <tr>\n",
       "      <th>veil-color</th>\n",
       "      <td>8124</td>\n",
       "      <td>4</td>\n",
       "      <td>w</td>\n",
       "      <td>7924</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ring-number</th>\n",
       "      <td>8124</td>\n",
       "      <td>3</td>\n",
       "      <td>o</td>\n",
       "      <td>7488</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ring-type</th>\n",
       "      <td>8124</td>\n",
       "      <td>5</td>\n",
       "      <td>p</td>\n",
       "      <td>3968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>spore-print-color</th>\n",
       "      <td>8124</td>\n",
       "      <td>9</td>\n",
       "      <td>w</td>\n",
       "      <td>2388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>population</th>\n",
       "      <td>8124</td>\n",
       "      <td>6</td>\n",
       "      <td>v</td>\n",
       "      <td>4040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>habitat</th>\n",
       "      <td>8124</td>\n",
       "      <td>7</td>\n",
       "      <td>d</td>\n",
       "      <td>3148</td>\n",
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       "  </tbody>\n",
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      ],
      "text/plain": [
       "                         count unique top  freq\n",
       "class                     8124      2   e  4208\n",
       "cap-shape                 8124      6   x  3656\n",
       "cap-surface               8124      4   y  3244\n",
       "cap-color                 8124     10   n  2284\n",
       "bruises                   8124      2   f  4748\n",
       "odor                      8124      9   n  3528\n",
       "gill-attachment           8124      2   f  7914\n",
       "gill-spacing              8124      2   c  6812\n",
       "gill-size                 8124      2   b  5612\n",
       "gill-color                8124     12   b  1728\n",
       "stalk-shape               8124      2   t  4608\n",
       "stalk-root                8124      5   b  3776\n",
       "stalk-surface-above-ring  8124      4   s  5176\n",
       "stalk-surface-below-ring  8124      4   s  4936\n",
       "stalk-color-above-ring    8124      9   w  4464\n",
       "stalk-color-below-ring    8124      9   w  4384\n",
       "veil-type                 8124      1   p  8124\n",
       "veil-color                8124      4   w  7924\n",
       "ring-number               8124      3   o  7488\n",
       "ring-type                 8124      5   p  3968\n",
       "spore-print-color         8124      9   w  2388\n",
       "population                8124      6   v  4040\n",
       "habitat                   8124      7   d  3148"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Describe the data\n",
    "data.describe().transpose()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "71864dc0",
   "metadata": {},
   "outputs": [
    {
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       "      <td>4608</td>\n",
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       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>ring-number</td>\n",
       "      <td>8124</td>\n",
       "      <td>3</td>\n",
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       "      <td>7488</td>\n",
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       "      <th>2</th>\n",
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       "      <td>8124</td>\n",
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       "      <td>3244</td>\n",
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       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>veil-color</td>\n",
       "      <td>8124</td>\n",
       "      <td>4</td>\n",
       "      <td>w</td>\n",
       "      <td>7924</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>stalk-surface-below-ring</td>\n",
       "      <td>8124</td>\n",
       "      <td>4</td>\n",
       "      <td>s</td>\n",
       "      <td>4936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>stalk-surface-above-ring</td>\n",
       "      <td>8124</td>\n",
       "      <td>4</td>\n",
       "      <td>s</td>\n",
       "      <td>5176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>ring-type</td>\n",
       "      <td>8124</td>\n",
       "      <td>5</td>\n",
       "      <td>p</td>\n",
       "      <td>3968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>stalk-root</td>\n",
       "      <td>8124</td>\n",
       "      <td>5</td>\n",
       "      <td>b</td>\n",
       "      <td>3776</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>cap-shape</td>\n",
       "      <td>8124</td>\n",
       "      <td>6</td>\n",
       "      <td>x</td>\n",
       "      <td>3656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>population</td>\n",
       "      <td>8124</td>\n",
       "      <td>6</td>\n",
       "      <td>v</td>\n",
       "      <td>4040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>habitat</td>\n",
       "      <td>8124</td>\n",
       "      <td>7</td>\n",
       "      <td>d</td>\n",
       "      <td>3148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>stalk-color-above-ring</td>\n",
       "      <td>8124</td>\n",
       "      <td>9</td>\n",
       "      <td>w</td>\n",
       "      <td>4464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>stalk-color-below-ring</td>\n",
       "      <td>8124</td>\n",
       "      <td>9</td>\n",
       "      <td>w</td>\n",
       "      <td>4384</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>odor</td>\n",
       "      <td>8124</td>\n",
       "      <td>9</td>\n",
       "      <td>n</td>\n",
       "      <td>3528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>spore-print-color</td>\n",
       "      <td>8124</td>\n",
       "      <td>9</td>\n",
       "      <td>w</td>\n",
       "      <td>2388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>cap-color</td>\n",
       "      <td>8124</td>\n",
       "      <td>10</td>\n",
       "      <td>n</td>\n",
       "      <td>2284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>gill-color</td>\n",
       "      <td>8124</td>\n",
       "      <td>12</td>\n",
       "      <td>b</td>\n",
       "      <td>1728</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       index count unique top  freq\n",
       "16                 veil-type  8124      1   p  8124\n",
       "0                      class  8124      2   e  4208\n",
       "4                    bruises  8124      2   f  4748\n",
       "6            gill-attachment  8124      2   f  7914\n",
       "7               gill-spacing  8124      2   c  6812\n",
       "8                  gill-size  8124      2   b  5612\n",
       "10               stalk-shape  8124      2   t  4608\n",
       "18               ring-number  8124      3   o  7488\n",
       "2                cap-surface  8124      4   y  3244\n",
       "17                veil-color  8124      4   w  7924\n",
       "13  stalk-surface-below-ring  8124      4   s  4936\n",
       "12  stalk-surface-above-ring  8124      4   s  5176\n",
       "19                 ring-type  8124      5   p  3968\n",
       "11                stalk-root  8124      5   b  3776\n",
       "1                  cap-shape  8124      6   x  3656\n",
       "21                population  8124      6   v  4040\n",
       "22                   habitat  8124      7   d  3148\n",
       "14    stalk-color-above-ring  8124      9   w  4464\n",
       "15    stalk-color-below-ring  8124      9   w  4384\n",
       "5                       odor  8124      9   n  3528\n",
       "20         spore-print-color  8124      9   w  2388\n",
       "3                  cap-color  8124     10   n  2284\n",
       "9                 gill-color  8124     12   b  1728"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Reset index\n",
    "data.describe().transpose().reset_index().sort_values('unique')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "7acaad40",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='class', ylabel='count'>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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": [
    "sns.countplot(data=data, x='class')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "e3cc07a5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 8124 entries, 0 to 8123\n",
      "Data columns (total 23 columns):\n",
      " #   Column                    Non-Null Count  Dtype \n",
      "---  ------                    --------------  ----- \n",
      " 0   class                     8124 non-null   object\n",
      " 1   cap-shape                 8124 non-null   object\n",
      " 2   cap-surface               8124 non-null   object\n",
      " 3   cap-color                 8124 non-null   object\n",
      " 4   bruises                   8124 non-null   object\n",
      " 5   odor                      8124 non-null   object\n",
      " 6   gill-attachment           8124 non-null   object\n",
      " 7   gill-spacing              8124 non-null   object\n",
      " 8   gill-size                 8124 non-null   object\n",
      " 9   gill-color                8124 non-null   object\n",
      " 10  stalk-shape               8124 non-null   object\n",
      " 11  stalk-root                8124 non-null   object\n",
      " 12  stalk-surface-above-ring  8124 non-null   object\n",
      " 13  stalk-surface-below-ring  8124 non-null   object\n",
      " 14  stalk-color-above-ring    8124 non-null   object\n",
      " 15  stalk-color-below-ring    8124 non-null   object\n",
      " 16  veil-type                 8124 non-null   object\n",
      " 17  veil-color                8124 non-null   object\n",
      " 18  ring-number               8124 non-null   object\n",
      " 19  ring-type                 8124 non-null   object\n",
      " 20  spore-print-color         8124 non-null   object\n",
      " 21  population                8124 non-null   object\n",
      " 22  habitat                   8124 non-null   object\n",
      "dtypes: object(23)\n",
      "memory usage: 1.4+ MB\n"
     ]
    }
   ],
   "source": [
    "# Check the info of the data\n",
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "d9aaaa23",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 2800x1600 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(14,8), dpi=200)\n",
    "sns.barplot(data=data.describe().transpose().reset_index().sort_values('unique'),x='index', y='unique')\n",
    "plt.xticks(rotation=90);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bcb66aad",
   "metadata": {},
   "source": [
    "# Train Test Split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "eed32c73",
   "metadata": {},
   "outputs": [],
   "source": [
    "X = data.drop(['class'], axis=1)\n",
    "y = data['class']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "c5f01d1d",
   "metadata": {},
   "outputs": [],
   "source": [
    "X = pd.get_dummies(data=X, drop_first=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "989a4fe2",
   "metadata": {},
   "outputs": [],
   "source": [
    "# X"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "8fbbf747",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "92b8bb2c",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.15, random_state=101)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d3096980",
   "metadata": {},
   "source": [
    "# Model Creation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "a532533a",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.ensemble import AdaBoostClassifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "03a0cbe6",
   "metadata": {},
   "outputs": [],
   "source": [
    "model = AdaBoostClassifier(n_estimators=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "8b7d57f2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AdaBoostClassifier(n_estimators=1)"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d2e61ac7",
   "metadata": {},
   "source": [
    "# Model Evaluation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "22cd1faf",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import confusion_matrix, classification_report, accuracy_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "74834ef7",
   "metadata": {},
   "outputs": [],
   "source": [
    "prediction = model.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "4d3fe188",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['p', 'e', 'p', ..., 'p', 'p', 'e'], dtype=object)"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "09c77170",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8777686628383922"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "accuracy_score(y_test,prediction)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "6e9137f7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           e       0.96      0.81      0.88       655\n",
      "           p       0.81      0.96      0.88       564\n",
      "\n",
      "    accuracy                           0.88      1219\n",
      "   macro avg       0.88      0.88      0.88      1219\n",
      "weighted avg       0.89      0.88      0.88      1219\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(classification_report(y_test,prediction))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "b36ddabf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.feature_importances_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "b9ad716a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "22"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.feature_importances_.argmax()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "500f2ece",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'odor_n'"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X.columns[22]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "521b0f1a",
   "metadata": {},
   "source": [
    "# Analyzing the performance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "cafbbf10",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Creating an elbow method\n",
    "error_rates = []\n",
    "\n",
    "for n in range(1,96):\n",
    "    model = AdaBoostClassifier()\n",
    "    model.fit(X_train,y_train)\n",
    "    pred = model.predict(X_test)\n",
    "    err = 1-accuracy_score(y_test,pred)\n",
    "    \n",
    "    error_rates.append(err)\n",
    "    \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "d0c64577",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.  , 0.  , 0.  , 0.  , 0.  , 0.  , 0.  , 0.  , 0.02, 0.  , 0.  ,\n",
       "       0.02, 0.  , 0.  , 0.  , 0.02, 0.  , 0.04, 0.04, 0.04, 0.  , 0.  ,\n",
       "       0.04, 0.02, 0.  , 0.  , 0.  , 0.12, 0.08, 0.  , 0.  , 0.  , 0.  ,\n",
       "       0.  , 0.  , 0.  , 0.  , 0.  , 0.  , 0.  , 0.  , 0.  , 0.  , 0.  ,\n",
       "       0.  , 0.06, 0.  , 0.  , 0.  , 0.  , 0.02, 0.  , 0.  , 0.  , 0.  ,\n",
       "       0.  , 0.  , 0.  , 0.  , 0.  , 0.  , 0.  , 0.08, 0.  , 0.  , 0.  ,\n",
       "       0.  , 0.  , 0.  , 0.  , 0.  , 0.02, 0.  , 0.  , 0.  , 0.  , 0.  ,\n",
       "       0.  , 0.  , 0.  , 0.04, 0.  , 0.18, 0.  , 0.08, 0.  , 0.  , 0.06,\n",
       "       0.  , 0.  , 0.  , 0.  , 0.  , 0.  , 0.02])"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.feature_importances_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "645a47e4",
   "metadata": {},
   "outputs": [],
   "source": [
    "features = pd.DataFrame(data=model.feature_importances_, index=X.columns,columns=['Importance'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "68c01008",
   "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>Importance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>cap-shape_c</th>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cap-shape_f</th>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cap-shape_k</th>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cap-shape_s</th>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cap-shape_x</th>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>habitat_l</th>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>habitat_m</th>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>habitat_p</th>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>habitat_u</th>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>habitat_w</th>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>95 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             Importance\n",
       "cap-shape_c        0.00\n",
       "cap-shape_f        0.00\n",
       "cap-shape_k        0.00\n",
       "cap-shape_s        0.00\n",
       "cap-shape_x        0.00\n",
       "...                 ...\n",
       "habitat_l          0.00\n",
       "habitat_m          0.00\n",
       "habitat_p          0.00\n",
       "habitat_u          0.00\n",
       "habitat_w          0.02\n",
       "\n",
       "[95 rows x 1 columns]"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "b7142ad7",
   "metadata": {},
   "outputs": [],
   "source": [
    "imp_features = features[features['Importance']>0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "5dab016f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "        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>Importance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>cap-color_c</th>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cap-color_n</th>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cap-color_w</th>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bruises_t</th>\n",
       "      <td>0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>odor_c</th>\n",
       "      <td>0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>odor_f</th>\n",
       "      <td>0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>odor_n</th>\n",
       "      <td>0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>odor_p</th>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gill-spacing_w</th>\n",
       "      <td>0.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gill-size_n</th>\n",
       "      <td>0.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stalk-surface-above-ring_k</th>\n",
       "      <td>0.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stalk-surface-below-ring_y</th>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stalk-color-below-ring_n</th>\n",
       "      <td>0.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ring-number_t</th>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>spore-print-color_r</th>\n",
       "      <td>0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>spore-print-color_w</th>\n",
       "      <td>0.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>population_c</th>\n",
       "      <td>0.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>population_v</th>\n",
       "      <td>0.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>habitat_w</th>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            Importance\n",
       "cap-color_c                       0.02\n",
       "cap-color_n                       0.02\n",
       "cap-color_w                       0.02\n",
       "bruises_t                         0.04\n",
       "odor_c                            0.04\n",
       "odor_f                            0.04\n",
       "odor_n                            0.04\n",
       "odor_p                            0.02\n",
       "gill-spacing_w                    0.12\n",
       "gill-size_n                       0.08\n",
       "stalk-surface-above-ring_k        0.06\n",
       "stalk-surface-below-ring_y        0.02\n",
       "stalk-color-below-ring_n          0.08\n",
       "ring-number_t                     0.02\n",
       "spore-print-color_r               0.04\n",
       "spore-print-color_w               0.18\n",
       "population_c                      0.08\n",
       "population_v                      0.06\n",
       "habitat_w                         0.02"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imp_features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "60283f5f",
   "metadata": {},
   "outputs": [
    {
     "data": {
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v9CBluglTyru3SgALuJYyx/iVQw20oSQ9H3gDpaLC5JFo/wAOBn5u+/IawpsvSdq5x12eB7wZOLL6mpLtg+Y+qoD/jsA8lvI7T0WEGkl6DKXt4vGU0tUfpbTl3Tdpu0WBPSmVQxanXDuebDsl+OeRpCUoUx8sRWnfu7TeiJppiralfW2fX19EzdR2HkSS+DNKUj9iGtXNy1GUkcXTvVlaD13HAC+bfBMUoyUj0HonaUVKr9zdKBUpYOLv/gLgR8DPbN/exbHWoySmH7a90Ezbx5wkvZDSuAPwKeAg27MmbbMUZe7MfYAFgDfYPnqogY6xSTebSeLXoG0UJpRzcQel090JwImUKVhykzsEkpajjDLYEPgm5fPp0twLzb+S1J97kp4LHAHcBbzD9u9rDin6IAnl+uVzad5U1+rvU8osq8Nmpnx+7d2qtBaDIWl9SiL/tZTOFjBxXm6iVFj4ue3GlZPth0kJmn5x2o7mnaQnUUqN/4BSIeTXVM8OdDEnsu2rBhpgw0jahjJiv3VdvQc4mzkHsm0ILEb5jHoQ2N72McOPdjxVA3eOApahtN8dkmlKh2uKtiUDFzHRtnSi7VtqCK1RJl27jwH+RDkHadubQpL6ETOoepK+C/gfYOUOm10NfBn4dj5oRl8ahXon6UFKcrjV2HAHpezyj2yf3eOxVqeU58/vv0eSWuWtV6ZMDdK64byCUjLKwPKUeQHbp0KYbn7YNFD3aNLNZutm/wRysz80VeJsy+prU0pDA0yclzsoJexOIA8CAyPp4fYf6a0BNY2jIyr3SXOn7Rq9EhNTct1GuQ7P1FCda/EIy3uifjkH/VElD15MmTpnmWr1zcC5wO8yGnxwqmfgnSjJ/DVaq6vl3cBvKFMeHGP74UceIbo1KUHTL/ns6YNJz9F5dhgBkraifPa0OhhNPietz6n/UKanOGFIoY09Sf+qvl0MWI6J9r2b6e7ZYfUBhtcYklZmom1pS6D999o6JxeTdr+BknQsZXqWtO11IUn9iC5Vyf11mfoB+IJ8oMw/0ijUu7YH49Mp01AcanvGntQdjvUYYEcA2z/pT4TNMMVDcDc6bd8aaZ73QY8k/QjYgombfbctc7M/ZNVcsBsz8RD2HGZ4ELB97lCDHFPz2Giaz54RlfukuTMP1+hci0dc3hP1yzmI+d2kSl8AD1FGov0cOHJun63jkSStMojjZjqXeZdnh9FUVandGXgJU7d5/5ZSmfP+eiIcT3k/jKZqSrUt276e0vbyI5L8tg8faoBjTNJCTLTtbUEXbXs0NMmfpH7EkGQe99GRRqHeSfoqZVT+JXXH0mRtc8T2le2t+n3MJqhu9rei3GxuycTNfpL8NaqS/BsxZ5J/cdrOS0Z59IekT8zL/rb37Vcs0T+5T5o783qNzrV4dOU9Ub+cg9GQaezmXlvy5gxKIv+Xtm+qMaSIoZO0y7zsn0EhMU4kHTAv+9verV+xRGfVdLRbtn21qqaK3A8N1KQBPK0k/+LVy63n7tuBk22/bOgB1ihJ/YghyQPw6EijUP2qZOhnKOdg97rjieiH6ma/leTfiqmT/BfZXqeG8Bqn6ky3OfACYHfgcWREbMSMcp8UMae8J+qXczAach7mnqSPU0a6/mvGjWO+kDaNiAmSVgX2J1NKxRiS9FRKYnkr4EXAY0nb0tC1DeDZHtgbWKJ6qXHnIYnFiOHrthxnxDhbCtiVkuTMA3CMBdvXAQdXX60k/9uAd1FuNgWsVVuAY65K4m/GRA/qDZi4122/9qa86YhKVaOIiIgYR7Y/1c/jJYE2EtKmUTNJSwAvA7B9UM3hNN3ilGfwjB6tiaQFgZUBbF9VczjztbYk/paUQTsrtL/c9v0/hxdVc03T1tc+rVGjJKkfERHRUKkg0n/T3Pw39mZzUHpI4t8NnE41BQJw5rBijJ6tRjlPs8lzSjRcrtERETGNJNAi4AnAgZRnhyT1o+meTvXsQJ6le9JDEv9ySpvSCcAJtq8dToTN0uOAnVZbX6PkDR4RERFJNs+lHm7+/8HEzX/MI0mnUkZ0T3VjfxdwGhNJ/LNsPzTUAGNe5TMpYkLeDxERERGd5V4pYkLeDz2Q9B86t+P9nYl2vBOr6pwxAJJeQJneYEumH7DT3tZ3ZlPb+pLUj4iIiOiBpD0oN5vTJfEvY84evLn5769N276/EziViRv7s20/XEdQERERERERERExX1ix7ftLmDOJf0MtETXTH3lkhdO7mLOt76y09RVJ6kdERET05vs88mbzUua8+b++hria5PdM3NifY3t2veFERERERERERMR85DtMtOPdVHMsTTd5wM45SeJPLUn9iIiIiN5N7sF7Y73hNIvt7ft5vGrOrg2rY5/Uz2NHRERERERERMRosf2Ofh5P0hLAy6pjH9TPY4+5jYFzM2CnO0nqR0RERPRmOds31x1E9NVqlA4as8n9cURERERERERE9OYJwIGUtqUk9btk++x+Hk/SqsD+5dDeup/HHgVptIyIiIjoQb8T+pLWoJo/yvbq/Tx29EwzbxIxWiQdV337U9sH9OGQ1wC79eE4EREREREREU2TtqV6LQ5sSZk6dewkqR8RERFRr4WBVRnTm82IGLjNgQWAT/fjYLZvB37Sj2NFRDNJ+nj17Rm2/9iHQ95KGe2Ue6WIiIiIiGisJPUjYuRJmk0pW/NR21/qwyH/Tim1HBERETG/uxFYAbit5jgixlUSyr37JOX39Yp+HMz2tcCu/ThWRERERETE/CpJ/YiYHzwALASc3I+D2X4I+Hc/jhURERFRswsoSf2nAufVHEvEfEPS6sAywJW2b+i0XRLKc+UWYGngqroDiYiIiIiIGBcL1B1AREQXrq2WD9caRURERMTo+RFlzr631R1IxCiQtKykvauvJaZ4/SmSzgEuA04D/iPpV5KWHHasY+wf1XKFWqOIiIiIiIgYI0nqR8T84KRquX6tUURERESMGNuHAz8DtpC0v6TF644pomY7AvsB77R9e/sLkhYBjgbWpXSGEaVd5BXAkUONcrz9kvK7fU3dgTSZpOOqr936dMhrgN2AN/fpeBERERER0YOU34/oIPO4j5RvATsB/yPpYNt31B1QzLO7KZ01MjdpRETEPJC0M/Bn4FnALsDLJP0W+CtlLvBpKx3ZPmjgQUYM17aUe8xfT/HarsDq1etHUd472wAvBTaX9Brbhw4pznH2Hcrn0c6STrT9k7oDaqjNKZ1WPt2Pg1WdZHIuI4q0aURMuBU4iLwfIiIGLkn9iM4yj/uIsH2OpHdSRtycKOnttk+rO66Ye7avBLasOYyIiIhxcCBzNqAtBbypy31NaYCLGCdPq5ZnTvHa66vlcbZfXn3/LUl/oiT3Xw8kqT/vVgDeAvwY2F/SG4CD6b6z0VUDj7AZbqSci9tqjiP6Lwm0mqVNI2KC7WspHScjImLAktSP6OxaYBUyj3vtJO1ffft3YB3gZElX012jkG3vPuAQI4ZC0nHVtz+1fUAfDtkqoRkR0bNUNRopmuHnGLBco0fKstXy2vaVkh4NbEpJgv1g0j77U5L6me6rP65kItkoYOvqqxsmbVX9cgElqf9U4LyaY4k+SgItAmxfRKYW7gtJj6U8hz0WWHCm7W2fNNM2MXRXAFvVHUREDF4elCI6O4kyyml9ph7lEcOzKxONQqY0DD0JeOIM+6naPkn9eSRpbju33AfcDlwO/AU4qHrwirmTEpoRMUpS1Wg0pCPEaMg1enQsWS1nT1r/bMpn1mzg2EmvXVEtlxtcWI2jDt/H8PwIeCHwNuCXNccSbZJAG760aUQ8kqQ9gL0p03h1K53vBkDSkymdT1cAFgO+a/vmbve3fQ9w4oDCi4gRkg/giM4yj/vouIqUlavb3DbEPbr6WgHYjPJ++hHwLtv39yu4BkkJzYgYJalqNAJspyPEaMg1enTcBSxBOR/ttqyWF9u+ddJrD1bLhwYYV5OkysQIsH24pJ8Bb6yq373T9t11x9VkSaDVKm0aNWuratQL88iOFX+0PbnjXvRA0oLAr4GXtlbVGE6jSVoP+Abl86Xdr4Gb27Z7O/AJynvhmbYfJCIaKTeFER1kHvfRYXvVumMI9q2WLwI2rr6/ADgbuKn6eVlgQ8oUCQbOAv4IPA5YC3geZXTUW4ClgVcPI/AxkxKaETFKUtUoYkKu0aPjUmATygjl37et35FyjzrVKKZWB4AbBhtaM9hOlYkRIGln4M+UBPIuwMsk/ZbuprHD9kEDD7IhkkAbCWnTqN+WTFTfnDxwp/We6Gb9DZLeb/uQvkfYHG8Ddqi+vwE4ADgHmMUjKx3FgEh6CfArYGHmvC5MNbDtJ8AXgMcD2wNHDDzAiBhJSepHdJB53CMm2N5X0kcoD79nAnva/utU20pahzJP6UbA72y/t1q/EnAgZb7SV0p6oe0/DCP+MZISmhExSlLVKGJCrtGj43eUUvt7SrqEMkXIrsAzKY2kh0+xz/rV8pphBBgxJAcyZ2JgKUpnvG4YSFK/f5JAq1naNEbCSZTPlhUpnSCpfv4Xc3aseDITif/LKO+Zx1X7tKom/EzSE21/aWjRj5edq+XFwOZTVDCKAZO0AnAIsAhwEfA/wCnAnVNtb/suSUdSnr9fRJL6EY0lOxWtI6YiaTZzPgB36jX6iF0pSf0Z50WLmF9I2pIyyuNiYCPb982w/aKURoqnA9vZPrZt/V+B1YFDbb9+gGGPJUkHAW+kNCakhOYYkLQm8Ddy7ehadY2eDXy0Hw05kh4FrAwpZd4rSW+lVDW6EEhVo5pVIwFfTmlsXosyigxK0uBCyjziR9rOlAkDkGv0aJC0BOWedUUe+Tx3mu3J5U2RdAZldObnbO8zlEAjBqy6X5pbuS/to+ozZiOSQKtN2jRGg6QXAL+gXJ/3BX42+f0gqdUB6eOUa/cbbP+hemZ7BfBV4AmUwVbr2L54iP+FsSDpDmBxYCfb6YxaA0lfBD4A/BtYz/Zt1fpWPmLtyX/bknYHfgicZ3uD4UYcMTiSPl59e4btP/bheCsBn6Pcz47dtGBJ6kd0IOlK5mEed9ur9S+amEySKA3ViwHXpnF6sCQdQRlZsFu3ZRgl7UIZgfBb2y9rW/8e4GvAv/M+6U1VQlPAe4G1KfP2poTmkEl6UvXtf7r97JG0AKXhAdtXTXptWcrcmtje95F7x2SS7qOUvtzM9ul1x9NUbVWNNmZiBGyqGtVE0gspo8pWbl9dLdvvaa+hjE6b54flmJBr9GiR9Azgp0yMwIcyYv/1tq+dtO06lCkTDGxl+6ShBdoQkpanlF2eqrPRCbYz7cEASFplXvZPR8f+SQKtfmnTqJ+k1YFzgQeBTW1fPsP2awCnU0qTb2j7smr9qtVxlgC+a/sdg4x7HLV9Jm1g+/yaw2kkSedTnhnebXu/tvXTJfU3o1S8uNX244cYbsRAtf3dv8L2UXXHM+qS1I+I+UY1+mxnYDdKL/eFKR/4z2q/0ZG0PWWus9ttf7aOWMeNpP9QSpxtZPvcLvdZnzI/3fW2V2pb37oJvdf24oOId1x1qCDS7YXctjPtTh+0jRJ/1uSHrGn2WR24HJid8zDvJP0LWIXSGJS53GuSqkajQ9KbKI3OYuI8XAlcX/28POU903ptNrCL7Z8PN9LxlWv0aJK0GuUe9jrbV3bYZh1g3erHn9t+aDjRjT9JK1ISX6+k8/SPD1Pmk32/7euGFVvEMCWBVr+0adRP0neBtwIftP2VLvf5IGUe8R/Z3rNt/eeBDwGX2F5zEPGOM0nnUO59XmD7uJrDaSRJtwOPYVKbxgxJ/VZH1AdtLzLMeMeVpLn5+zdwH3A7pZ3vL8AfbWc6nbkk6SZKx9/cJ3UhDQcRMV+QtBxwJLAJEw3SnVwBHAVY0u9yMeiL1oiax/WwT2vbpSatb80PlV5lc2fy3/9M74cYjLn9ved89cdJlJKM61PmxIx6XEU+y2tXjcT8AbAAcDfweUrD542TtlsWeAvwEUoD0g8lnTy5ekjMk1yjR4ztKyjPBtNtcwFwwXAiao6q4flYynPEdO+FRwGvBbaRtLXtvw0jvoghu5ySQFt6hu1icNKmUb9tKb+zk3vY58Rquc2k9cdRkvorE3PjF8B6wPaU32UM30LV8sEe9lmyWmaKr/7ZkvK5NFWH7E6DFqZaf4Ok99s+pO8RNsM/KBUgV6g7kPlBkvoRMfKqstVHUT7cZwOHURI6+021ve2LJJ0OPJsy39b5w4l0rF0PPIny+zyhy31eWS0nj7hpPUzfNO9hNU5K+82/2kfHxrz7FrAT8D+SDrZ9R90BNZHtVeuOIQB4N7AIcBfwvE6dGW3fBHxe0u8pjamLV/u+f0hxjrtcoyMqkhYHfge0SsMeS5kD9gzKcwWURruNKZ2NtgWWAX4n6em27xluxBEDlwRa/dKmUb+VZt6ko8mJnlbn1YxWnjvfBN4A7CXpCNu9dLSI/rieUkltNcro+25sWi2vGUhEzXQSJTm/IvDUap2BfzHxGb8s8GQmEv+XATdQOn49FXg05TPqZ5KeaPtLQ4t+fPySMpDzNcAfao5l5C1QdwAR8xtJj5K0bPWVjjHDsTOlwedB4CW2X2f7OzPs81vKxXazQQfXEH+k/D73kvSKmTaW9EpgL8rNzuSL8QbVMjehPbL973n5qjv+hluxWt457VbRFdvnAO+kPASfKOk5NYcUUafWqKcvd1OdqBqV/BXKdX27wYbWHLlGjyZJC0h6vqSPSfqWpB9XJeHbt1lY0mKSkhjon3dQkjezgT1sb2v7MNtX2X6g+rrK9q9sv5CS2DdlxOXba4x7bElaUNKOkr4r6WRJF1VfJ1frdqymu4vB+CbwV8rz9OZ1B9NQadOo3+3Vspf3wPMm7dvSmvbglnmKqKFs3095hjgHOEbSlyStK2nRmkNrklOr5YyfRwCSFgPeRvlMOmlQQTWN7S2Bz1ES97Mond6Xsb2G7edUX2tQOp++B7i12vbzttcDlqBUnLqGco35rKRnDv0/Mv/7DqVy2s6Sdqk7mFEnO5WCImYi6RnA3pRyT2swZ5mVy4FjgO91O7dy9EbSHym/+2/bflfb+unmGdoOOBq41vYThhnvOJL0JOAiYLFq1eHAQZQHgFYP6eWADSmdMF5BeZ/cBazVXtpX0pmUh+DP2P7EUP4DEX3U9tmzlu1LZth2IWB14BuUh+YzbG863T4xM0n7V99uDDyTcj6upjSW3kqZn7cT2959sBFGDE/bPL2b2T69y302pTQk3WW7lzK0EfMNSS+hJNJWnfTSHM8OkvaiVAC7C1jJdkqaziNJp1FG2xxg+y1d7vMj4M3AX2yns14fSXohZZqW9jLVU5WOvQbY0/YfhxVbk1RTCh5OeWb+JnAwcKnt+2oNrCHSplE/Sb+m/F5nAZvY/ucM2z+FUuFlSeBI2zu2vbYH8H3gPNsbTH2E6ERS+/PyVGXHp2PbGeQ2jyRtA/yJ0gHyxbb/VK1/RFu3pMdQKr68uHptQ9vdju6PaUhaHTiXMpBwU9uXz7D9GsDpwMKU83BZtX7V6jhLAN+1/Y5Bxj1uqmv0ssCPgbWBP1Puk7pp46NpUwomqR8xA0mfB/6HUtmi01yAplyEv2z7o8OKrSkk3UDpEbed7WPb1k+X1F+P8nB2v+1HDzPecSXpBcARlIfgmS4eAu4BXj7pnK0O/Kj68b3djCiMqNukB17oPK9WNz5o+6vzGFLjtX3+/3dVtezms8m2MxJtgKpKRq25R2+1/VCd8Yw7SXcDi1IaIc7scp+Ngb8A99h+zCDji6iDpLdQGvtb14ebKc8Tj3h2kLQwpbTyksAutn823GjHj6SbKdeBOZ7fZthna0pn+Vm2lxlkfE0i6U3AAZT3Quv9cCWl7K+A5SmVj9qnitrF9s+HG+l4SwJtNKRNo15VlYoTqh9nAZ8Efmb79knbLQm8EfgEZRqX2cAWtk9t2+Y3lOksvmP7nYOOfdxUz9NzK8/TfSLpcODlwAOUKQYPozyjGdiCkmjeljJCvzUFxUG2dxt6sGNK0neBt1La6r7S5T4fBL4A/Mj2nm3rPw98CLjE9pqDiHdcTWrjy33SDJLUj5iGpG9RRui3HnAvYWIewNYDcGuUIJQPnP1sv3vIoY41SfcDjwLWs/3XtvXTJfVbjdX32l6c6IvqAfZrwEvoPIXLbMocmu+bqed1zL2qPObLKVUs1mJiXr9ZwIWUuUuPtD1tb8aY2Tw+8LY7FHhDzsm8k3Qlc9epAgDbmfu6z1LVqD6SLqNUBHm/7W90uc97KNfzf9h+6gybR49yja5XNbLvIsrzw/HAO2xfOsOzww8oJeB/ZnvnYcc8biTdBywEbGT73C73WR84m3TK7htJqwCXUuacvhv4PKUB+sZJ2y1L+fv/CPAY4D7g6U0b9TRISaCNjrRp1EvSx4BPM/EsNxu4gjmrJazGnAOrPmb7823HWB34e7XN9rZ/P4TQx4qkeaowYXvffsXSZFVJ/f8DtmT69o3We+HPlL/5+wccWmNI+ielqtdzbJ/R5T6bUEbrX2n7yW3rX0CZ6uUO20v2P9rxlfuk3jSqB0NELyQ9lzKfn4GLKWXoTuuw7abA9yjlQd4h6Zedto250pqv5vE97PO0anlT/8NpruqB9mWSVqLcdK5F22hMSgPq8bavrSfCZuiihOZzgD2BaySlhOa8m/zA+gnK7/l7TDQ+TMWURtHrgNPSINQ/tletO4aYMENVI1GuyU+lzGGaqkb9dzzwFODDkg6d6Ros6QnAhymfUccNIb5GyTV6JLyHklC+kFLO9IEu9jmZktRcd3BhNcpNwErAMyilSLvxjGp580AiaqZ3UxL6dwHP6zSi2PZNwOcl/Z7yXli82vf9Q4qzCZIAGxFp06iX7c9K+hfwdUoCf0HKfezq1SbtzxI3Au+x/YtJx/gnyWnMkyTlR4Pte6oy/O8F3ges2GHTWcBXgC/Z7tegkyhWmod9V5j0c6t9cJF5OGZTpfpEDzJSP6IDSQdRyj39C9hgcjmoKbZfglLufTXg5xnh0T+SjqOUHfqk7U+3rZ9utM3RlBJFc8y7FTG/SwnN+k332RPRNKlqVD9JawHnU37f11IahA6fPAq8Gj2+I/BVSsL5YUoVpAuHGvAYyzV6NEi6hNKRaA/b+7etn+7Z4TnAKWRkTV9IOozyeXMeZd7kaadhkbQQ5dqxDuXz69WDj3L8SbqQ0llijufoGfb5OKUk9sW21xpgeBHRYNXUN68AtmbqjhV/Bo7IiORoimoKu42BDZno8HIL5V7qlLwXBkPS9ZSBhB/qofz+B4AvAjfYXrFtfet54lrbTxhEvBGQpH5ER5KuAJ4EvNX2j2bavtpnD8rcjf9Oad/+aSsRewOwpu1Z1fopG+Yk7Qb8uHot82LG2EgJzdEgaZfq2yNs31FrMBE1qqoanUy53l5C91WNDGyeqkb9I+kjwGeZKNt4G6UB6IZq3QrAepQ5w1sJ5Y/a/sJQAx1juUaPDkl3AY9mUun3GZL661DeMw/ZXniY8Y4jSS8FfkP5fR8L7NZp1KuklYH9gRdU2+9g+3fDinWcSbqDMup+M9und7nPpsCpwF22HzfI+CIiIiLqJOnXlA5GsygdUaetsFlN83UG5bl6joGEbXmh82xvMLCgo/FSqiais1YJlfN62KfVaLR8n2Npuu9TyvquCBwjaWfbF03eSNITgQ8CezExh+/Bwww0YsBSQnME2P5J3THE1Kre7f8d5THTyMCYZ2+tllcAz52uqpHt0yU9j4mqRm8DktTvE9ufl3Q78CVgMcr7YKtJm7WS+fcAH7D93SGG2AS5Ro+OVueWydOBTGfZapnOen1g+7eSjgReDmwD/EvSMZRG0PbORptQkvkLVbsekYR+X7XmF3142q3m1Nq201zjERExZqqKOetTqiYsXa2eRZnK6FzbD9YVW8SAfYNyv7oU8BdJnwR+NrltQ9KSlIrOn6i2nU0ZgNhue8o9bto5YqCS1I/o7D5gYUpDW7ceUy1TEqePbN8r6RWUeV/XBf4q6e9tm3yvGvX01OpnAXcCr8pcQ/0n6fHApsCTgccy0VjUke1PDTquhtiWcoP45U7Jgna2L5D0FUoJze1IwiDGkKRnUMq/bwOsQdvc1ZIuB44BvpepEgZic8pn0hdmmqYIwPbtkr5I6ay3+aCDaxrb35F0KGU+um2YulHuWOAA25mzuv9yjR4d11Lm530qpSNRN7aollcOIqCGej1wEPBqynP1i6uvyVrX7cOATGHXX/+hzFP9HODMLvd5TrXMfOIDlARavdKmEVFIWgzYB9iDic7xk90q6QfAZ2zfM7Tgxpyk1hRRVwKfnTx1Wod9VgI+A9j27gMMrzFsn1xNPfRpyvX4m8A3qgrOrYpry1EGJizAxH3rPrZPbR1H0urAS6rXjx5S+GNL0vLAlkx9n3SC7RtqCm0kpPx+RAeSzqXM6fd12//T5T5focxjmjIrAyBpbeBnlNK9LVONxLkEeG3miO0vScsBXwdeRY+dwmzP+JAcM0sJzdEkaSnK9WIZSrnfaUcG2j5oGHE1gaTPUyq5tD9cTWZKL+ov2/7osGJrAkn3UhI1G9vuKnEmaQPgLOA+24sNMr6IYco1enRI+iGwO/A72y9tW99p6q5lgIuBxwNftf3BIYc81iS9hNL5bgtKJZF29wAnAt+2/fthxzbuJH2fkqi5EVi/0xQIbds/ATibUrnih7bfNvgom6XbBBqQBNoApE1jtEh6LCVR1m3HipMGHlSDSHoSpcPv6sxc3cjAP4CtbV8z6NiaoO2+FOAEysC0W2fYZ03gb5Skfj6T+kjS6ynXh+XaVk+Vc7gReI/tXwwrtiaRtCKlAsIr6Xydfhj4FfB+29cNK7ZRkqR+RAeSPgN8FHgAeIntP8+w/dbA7ykfOJ+zvc/go2ymqmHoZcCGlIvtgsAtlKkSjgJ+nRH6/VUlLc+gu5v9R7Cd8o19IOluYFFgU9tdjbaRtDHwF+Ae24+ZafvonqQtgX2BzXrYzbZTKakPJH2LkiRofSZdQvmcur5atzywMfDM6nUD+9l+95BDHVuSbgUeB2zVbSObpC2A44HbbXdqzI6Y7+QaPTokbUS5Hhh4i+0DqvWPSOpXSczDKc8VDwHPtP2PWgIfc5IWpIyKbR9t869uRqbF3JG0FnA+5b7oWsoAhMMn/86rc7Mj8FVgZUpj6XrpJN9fSaDVK20ao6Oad3pv4Fk97Jbn6D6qqoWcDzyjWnUpcABTP0/vysQz9UWU60OmuZtHbfelqpb/BHawfek0+ySpP0CSFgZeAWxNGSH+36kdKX/7f6ZMFZUKzQMgaR3KfdLSdHefdAvlPulvg45t1CSpH9FBNWLjH5Qeow8DPwT2p4zCn11tswCwHmUkyFsoCf3bgafYvqWOuCMGoSqX/IHqxz9Res2dA8xyLiRDI+kySiPE+21/o8t93kM5X/+w/dQZNo8uSdoL+BblRrOXRqE8fPWBpOdS5qI2JZm/p+0p5y2rRsJ+j1LlxcDmnbaN3qSqUcSEXKNHi6TvAG+jfO4fTint/ovq5zdUy22B11E6YwB8yfZHhh9txOBI+gjwWSZGm91G6Qx/Q7VuBUqbxpJM3NN+1PYXhhromEsCrX5p06hf1YHo10Crik6eo2tStWd8m3Id+BzwiU6Do6q2708C/6/a/u22vzekUMdWW1L/AMrn/gLAHcDrbP+hwz5J6sdYkrQ48HdgpWrVsZRcXOs+Cco968aUHNy21bprgKc3rbJRkvoR05C0LWXk98JMPAQ/QBlVYEqJxoVbm1evbW/72CGHGjFQki6lzFX9O9s71B1PU6WE5mio5nD/K+Wh62/Ax4EHgd9Rrg1PofTo3RDYkzJf5inAWymjMf9dQ9hjRdJBwBuBfwEbzDSfu6QlKI12qwE/t505e/sgVY0iJuQaPVqqxMH+wJuYeI6bctNqeSCwexI7MY4k7Q18iYnpDyb/nbfeB/cAH7D93WHF1hRJoNUvbRr1k/R2Ssd4KB2LDqDqWEGZLm1atk8cXHTNIuk4yrQ4R9resct9fk0ZxXy87a0HGV8TtFeQolQy+jkTAws/ZPtrU+yTpH6MJUkfAj5PuRa81faPZ9j+zZSkP8CHbX95wCGOlCT1I2YgaV3KfGYbzrDpWZSRghcMPKiIIZN0D7AI8GLbf6w7nqZKCc3R0Db67yZKZZY7Oz1cSRLwBcqokONsb1NHzONG0hXAkyg3+z/qcp89gO8D/7a92iDja4pUNRouSYMoUZ1Spn2Sa/RokrQj8BFKB7upXEyZtzrzYsZYq67ZuwHbUErKtk+DcCFlRNQBtm+uJ8LxlgRa/dKmUT9JZwAbUa69m880f3gMjqQbKQPVdrD9uy73eTHwf8DNtpebafuY3uRpoapnid8Cq1TrDwTeZvvBtn2S1I+xJOk0YBPKvehbutznR8Cbgb/Yfs4g4xs1SepHdKmam7HjA7Dts+qKrUmqxohdmL4x4idpjOivthv+DWyfX3M4jZYSmvWTdBHwdODjtj9brZv24UrSscBWwB629x9mvONI0r2USjkb2z6ny302oHTAu8/2YjNtH91JVaPhqRp++i0NQn2Ua/TokrQSpZP2csCClDkYz7P9z1oDm89JGsQ9jW3vPoDjRtQmCbT6pU2jfpLuABYHdrL9y7rjaTJJ91M6W29o+7wu91mPUlnhAduLzrR9TG9yUr9a93jgCGCz6rXTgFfavql6PUn9AZP0WEqFx8dSnhmmZfukgQfVAJJuplQ83a7btqKqEuQxlGl0lhlkfKMmozIiulQl7ZO4r1E17+inmSgb2D7/1sqUeVe2BT4p6f/Z/t/hRjjW/gZsSekxen6tkTSc7c9Lup2JEppLUZLF7VJCc7CeUC3PbVv3316SkhZq701d+QHwfErJ+CT15919lETx4j3s85hqeX//w2ku23+S9GzmrGq0CLDiFJunqtG82XeG11/CxDm4CDiTkkwWJZG5EaVDpCll338/mDCbK9fo0VVNh3BU3XGMoV2ZfnqDXqk6XpL6MW6WqJbTTs0yyXXV8nF9jqWp0qYxOv5edwDBLMrzwWqUDqjdeHLbvjEAtm+pEpXfo1TXeQ5wpqQdbP+t3ujGW1XZcW/gWT3sZpJf7ZdWe10vny+tai+9tAuOhfzRRcR8QdLXgHcz0RB6GxMjn1qN1etSGk8XB74maRXb7xt6sOPp+5RG6TcBv6k5lsaz/R1Jh5ISmnVp9Upvb5S7u+37pShzKrf7R7V85qCCapgrgHWAHYBue0a/tFr+ayARNVg12mnjVDUaLNsdk/qS9qEk9C+gdJyY8nctaUMmOmD8n+1PDyLWJss1OhrmKvqb1I8YV0mg1S9tGvW7nNJut/QM28XgnQu8CHg7cHiX+7ydcs3v9jMs5kI1QGT3qkLkFykdkU6V9CYm2pWiT6qp0X7NRHuRptk8BucmymDNZzDnAKrpPKNaNu6ZOuX3I2LkSXohE6PJrgHeDxxh+6FJ2y0IvBL4MmWuZQMvsv2nIYY7tiT9HHgd8LGUiY0mk3QdpVFuc9unVesWA+6sNtnC9imT9tkW+AMpVdcXkj4DfJRSyv0ltv88w/ZbU64jjwI+Z3ufwUcZMRxtZecuo5SUvXuG7RenPCg/hR7K20WME0nrAK8ClqF0FPtZNZo/IqLvJP2OkkA73vbWXe5zHLAF8AfbLxlkfE2RNo16SfoAJUn5jQzAqZekNwIHUdpNfwK8s9MzRPXs8C0mqvO8yfbBQwp1bE1Vfn+KbV4EHEKp2DIb+BmwMym/3zeS3k75+4YycPAAyjQTsyi/82nZPnFw0TWHpMOAHSmdhjaZnPOZYvuFgDMog30Ot/3qwUc5OpLUj8aT9KRBHNf2VYM4bhO1PQBfC2xk+7oZtl+BUlZ2RfIA3BeSnkeZS+jTwKaUG5yDgUsp5WOnlTmGYpxIOh54HvBm2z9pW38psAbwVdsfnLTPfpRSXv+x/cRhxjuOJC1D6aX+WOBh4IeUaQ3Osz272mYBytzVuwNvoST0bweeYvuWOuKOGARJvwG2B3a3fWCX++wG/Bj4re2XDTC8iKGrqoZ8G3gIeLHt2ya9/tbq9faROHdR5iydtpNYxCiS9PAADmvbqe7ZJ0mg1S9tGvWTtAglCfM0YFvbJ9ccUmNJEnAypby7KSNdD6WcnxuqdSsAmwCvBpal3DedYvt5dcQ8brpJ6lfbPQP4LaV6i6mmKkpSvz8knUGZpu5iysCdW2fYJQZA0kspVXRMqWq3W6cO15JWprT/vaDafgfbvxtWrKMgSf1ovDwAjz5JNwKPB95l+9td7tPqaXez7eUGGV8TtN1szo28H2KsSPo08DFK6eTd29Z/DvgwZfT43sAvKXMq7wJ8jtKI9DPbuww96DFUVT84CliYic+nByg9qk25bizc2rx6bfuMSo5xI+k/lEa3jWx3VapO0vqUDpDX215pkPFFDJukTwH/Dzh6cudeSatREjgLTbHrrcDTMi1CzG+qZ7V+S8Kgj5JAq1/aNEaDpOUo5d43BL5J1bHC9n21BtZAkpYCfgc8u1rV6f3R6gR5OuV5OknPPug2qV9tuzSlRPwW1apco/tE0h2UaXx3sv3LuuNpMkmHAy+nvC8epFQjnOo+6QWUZzlRRum/qo5465SkfjReHoBHn6S7KXNYb2L77C732RA4E7jX9uKDjK8J5vF9kvdDjBVJm1AeaGcBT2g1QEh6PPB3YKmpdgPuBTa0fcmwYh13ktZlYn7w6ZxFmWf8goEHNYZS1Wi0SbqX0oFlG9vHd7nPlsBxwP22Hz246CKGT9JJwHOBd9veb9JrX6ZM5XUv8Abgz8B2lJGziwKfsP2Z4UYcMW8kfWKGTV7CxL3SRZTn5Bso96fLUUaorUVpMD2bauo72/sOIt6mSgKtXmnTqN+kQVWit04W6VgxAFV1u70ogxKe0WGzSygVjr7XqooX805SK0F/pu17u9j+UcA+lOlmsb3bAMNrjLak/ga2z685nEarqrkcROncCDPfJx0G7Gz7/kHHNmpyMYyAXARH3zWUeV8X6WGf1rb/6X84jbRV3QE0SSqIjDbbZ1Slqx9FSeBfV62/RdJ2lFE3q03a7UbKzWYS+n1UPXRtXJVa3obSIL109fIs4ELgWNtn1RPh2LhiAMc0eRbpl2uBVSlz0HWV1KfMJQ7V51d0L9fo+cLK1fLCKV57OeXz5/u2j6zW/UrSpsB7KVN+JanfR9Xost2Y5jpNqX40q54I53/TJd8l7UNJ6F9A6eA45T1R1Sm+1VHy/2x/ehCxNpntWyVtRhJodUmbRv00w88xZNVnzLeBb0takSmu0zNNgRpzp9e52Ks5xmfqxBe9uxxYl4m/+6hJlZx/raSDKPdJW1Cqn7a7BzgR+Lbt3w85xJGRkfoRMfIkfQ14N/B52/+vy30+C3wE+F/b7x1kfBH9lgoi8zdJCwHPB9akJC0vB/5oe8a5GiNGUT6TRpukb1MSBA8Db7B96Azbvwo4BFgA+K7tdww+yvGR98Poaxtxs57tv7atXxm4mpLU38z26W2vbQccDcyyvcyQQx5bkt4KfIWJBrnJCZxWg9Q9wPtt/2BYsTWBpK0ppUsvo4xAm3IO97btFwfOpXSo3y5TFg1WEmjRNF1UFZlWqodERL9J+gDwReAbtt9XdzwxQdKCwJOZ8z7pX7YH0cl+vpKkfkSMPEkrAecBjwVeYPvUGbZ/DmXEx53A+rYzWj/mKymhGRGjRNIugziu7Z8M4rhNUyUqL6LcJwH8FjiQMu3EjZRrwfKUa8MuwA6U68UdwJq5T+pNrtGjT9J9lHkWN7d9Wtv611Hm7r0bWLK9QaiazuVc4EHbvVQHiw4kfRj4LBOJ/Nspz3TXV+uWB9YDlqheN/AR218acqhjS9JvgO2B3W0f2OU+uwE/Bn5r+2UDDC8iIiKiVlXJ9zOApwHb2j655pAiZpSkfkTMFyRtQJkrZSXge5TG6r+2ytFJErAOpbF6L0op2lfZPreWgCMGpCqhuS/dl9BcB/hkSmj2j6TnVd+e1c3cZ9U+iwIbA9g+aVCxRUQzVXMyHkVJ7M/0gCdKx8cdei37GNPLNXo0SLqa8sywq+2ftq3/MaUM/J9tv2DSPs8GTgNutr3cMOMdR5LWoiTwF6RM8/EB4DDbD07a7lGUeTO/TDlnD1EqLFw03IjHk6T/ACsAG3X7XCxpfUqHo+ttrzTI+CIiIsadpI+3vrf9qanWz432Y8W8kbQccDilY/Y3KZ2AL7V9X62BRXSQpH5El6pyyusz9TyA505uoIjeSfrXDJssRhnh1PrgeoByDgw8Hli4dSjKyLR7KOVMV+9/tBHDlxKao6EqvTwbeJbti7vcZ3VKGf7ZmTe5e5KeNIjj2r5qEMeNqJOkVYCvUUbidyrl/jDwG0qZ638PK7YmyDV6dEg6AngZcBLwfNuzJT0e+AfwOOBjtr8waZ83AD8FLrK99rBjHjeSvgfsCdxESShPe92V9ERKdZFlgR/Y3mvwUY4/SfdSnpG3sX18l/tsCRwH3G/70YOLLiIiBi0J5fpV7UcGaJ9uq3393MjUXf0hqb2Uu+jtnDjte1GH/NFFzEDSYsA+wB7AUh02u1XSD4DPZM7kebJql9u1SjguAqzYYZvWCJv0XOqBpP2rb2179ynWz405jhXz5F2Uv+kvzJQsALB9t6QvUEpovpMyLUX0x+Q5YQe9X1NdMYBjmtwDxxiqkvQ7SloB2ApYm3LvKkonyL8Bx9u+vr4ox1qu0aPjIEpSf3PgFEmnAS+llHl/EPj5FPs8p1peNpQIx9/zKe+Hz3fTkc721ZK+CHwV2HrQwTXItZRn7B2BrpL6wKuqZeZ1nwtJoNUvbRoRc/gkE+2in+qwfm7kM6k3ndqB0j5Uv8nnIOdkgObxWtxJ467RGakfMY1qhOCxwOrM/KFuyuiPrW1fM+jYxpGkAwZxXNu7DeK442gAPUhVDpUepP2QEpqjoe39sHYPI/XXAP4OPGR74Zm2j6L6XfdbPpMGJFWNoslyjR4tkg5lIjlpJp7lPmt7n0nbLghcQ+kU/E7b3xlaoGNK0t3AosCmts/scp+Ngb8A99h+zCDjawpJ36ZMTfcw8Abbh86w/auAQ4AFgO/afsfgoxwvGZFZv7Rp1E/Szq3vbR801fq50X6s6E7787TtBaZaPzfajxUxP5P0iXnZ3/a+/YqlCeb1fmiqQ9LAa3RGKUV0UDVMH00piQlwKXAAcAZwPeVDY3nKHMm7As8E1gCOlrSe7YeGHfP8Lsn3kXAVU19cO62P4WolyZboYZ/HVctOlUZiOFatlrfXGcR8KNeF+UCqGo0eScszRecK2zfUF9XYyzV6tLwO2JsyX/sKlFHHP7E9VSfi11Ge66BMoRDzrlXKtJc2p9a2g+jQ11SfA94APBY4RNJOwIGUqQ5upDzfLQ9sBOxCmb5FwB3A52uId1xkRGa90qZRvwMpv2tTqudMXj83Jh8rutAp+Z6kfESRpPzQ5VrcBxmpH9GBpL2Ab1M+aD4HfML2lA0MkhaglC76f9X2b7f9vSGFGhENIemflORw1yNnJO1HadS+0vaTBxje2JpiXvcrKZ/12wKXz7D7IpRqL5+mjGA+2faWfQ4xojapajQ6JIkyh/U7KJ1Np3Ix8C3gh86DYF/lGh0xQdKFwDOAT9r+dJf77APsC1xse61BxtckkrYAjqIk9mf63BdwJ7CD7RMHHVtEjKe2UeBzjJ6cx9HhjRuJGRERMZUk9SM6kHQcsAVwpO0du9zn18ArKPOVZi7AiOirlNCsh6SHJ6+qlnNzE7WH7UHMIRUxdFVVo/MpiRvorqoRwEVAqhr1kaSlgN8Cm7ZWddi09bl1GvBS27cNOLTGyDU6YoKkrwPvpiSIN7P9txm2fxZwCrA48L+23zf4KJtD0irA1ygj8TslxR4GfgO83/a/hxVbRIyf6jMHgPbPk/b1cyOfTREREUnqR3Qk6Ubg8ZRe6r/rcp8XA/8H3Gx7uUHGFzFMbXOf/d32GbUG02CSVqYkwx5brfot3ZfQXNP2f4Yc8ljo07zu9wHftP3hPhwrYiSkqtFoqEbonwhsVq26BTiUqTtXvAZYhnIOTrG9xdADHlO5RkdMqBI3lwILA3cBnwEOsH3zpO2WAd4MfJQyHcV9wNNtXzXciJtB0grAVsDalGk/RJme5W+UgQnX1xhexEClTSNiQjWQzcCbu+0sIWkl4GeUqgkZyDaPqg7ya1Q//tP2/ZNeXxT4LBPPb1cA37G931ADjYiRk6R+RAeS7qfM67eh7fO63Gc94BzgAduLDjK+ppL0eMootCdTGk1nLL9l+1ODjmvcVUlNA6+faeRZDFZKaA6fpF0mrTqA8rvfB5guCWNK4/R1wHm27xpMhFE9EK/PFHOIA+fafrCu2MZZqhqNBklvAH5K+cw5GNjb9p0dtn0MpSPGm6rt32j7kGHFOu5yjY6YUCXQDmhbZcoURjdU369AmbJC1ZeBXW3/dKiBRgxBEmj1S5tG/dqmtbvL9qxag2m4tvfD2rYv7nKf1SnTD2YqhD6Q9BpK1a6bgSfafmDS60dTpnxsr8BmYD/b7x5aoGOirWMXtg+aav3caD9WxLAkqR/RgaTrgOWAV9s+vMt9dgQOA663vdIg42uaalTB14AdKZ0tupabzXkn6VbK6JmuO7nE4KSEZr3m5gE4BkPSYpTOFXtQRpxN5VbgB8BnbN8zrNiaIFWNRoOk3wEvAk6w/fwu9zme0iHjaNsvGWR8TZNr9PBI+lf1rW2vPsX6uTHHsWLeSHoJ8D1g5bbVrUao9kbqa4E9bf9+WLE1laTlmaITpO0b6otq/CWBVr+0adSv7X3wTtvfqTueJstnUv0k/RjYDfi+7b0mvfYSStUvUwaSnEWpurZytW4z26cPN+L5W9vfvG0/aor1c2OOY0V/SFqa8t7YhqkH7hxLqQDW2M5h+aOL6OxcSgPp24GukvrVtgbygNBHkpalzP26Cp3niI3BugJYh85JsxiiKgGwY0po1maranlFrVE0XDXS41hgdaa/NiwNfIjyntna9jXDiK8hlqiW1/awz3XV8nF9jqXJ1qcatdHDPt+iJPXXG0hEDZZr9FCtWi0nN8StytzLqIc+sv07SatRKrRM1zB3hO2H6oly/FXTtOwJvAN4ZodtLqZcG37ojP6J8ZQ2jfrdCyxKSVDG/GfxanlfrVGMj9Yz3ElTvLZbtbwM2Nj2nZKWoLSNPx14C5Ckfu86tRsl1zAiJL0V+AqwWGtV28srAytRKlh8UtL7bf9gyCGOhCT1Izo7hJLU31LS/pSepHdPtaGkxSkPwFtSLsg/H1aQDbEvE41zhwHfBS4AbkuDw9AcAawLvBQ4rt5QoqVKCBxSfcWQpExy/apy+0cDT6lWXUop8TvVHOK7Uhqw1wCOlrReEgd9M4tS1Wg1uu/Q+OS2faM/WgmyXjoatbZdetqtYq7lGj0UP+lxfdSguuYeVn3FkElaijLab9PWqg6bPpPynP0mSS+1fdsQwovpJYHWX2nTqN9/KB2yM8p7/vSiaplO8v3Rqlo3R4UpSQtQOkK2Su3fCWD7dkn7UaZSe84wAx0Tq/W4PoZM0oeBzzJxr3o7pZ2pvY1vPcrgksWB70pa0vaXagi3Vim/H9FB1Zv9ZMqF0pQ5bg6lJAza5wHcBHg1sCzlA+YU28+rI+ZxJekqSm+sn9reteZwGknS4ygdKVYEXmw7D8EjIiU0o4kk7UV5mDXwOeATtmd32HYB4JPA/6u2f7vt7w0p1LHWVvb9+G7neq3mlN0C+EPKvvfHXE6D0CrpmGkQBijX6IioU9WmcSKwWbXqFibaNCZ3gnwNsAzlXukU21sMPeAxNpelrj8EfB643PbTBhlfE6RNo35VQnIv4EO2v1J3PE1SDVZrtyvlM+k3wG0z7L4IpTPGRtXPP7a9Zz/jayJJ91MG3K5v+4K29esDZ1POz+q2r2x7bXPKdf0e248ZbsQRgyNpLUoCf0FKdccPAIfZfnDSdo+i5OG+TBm1/xCwnu2LhhtxvZLUj5hG1av9d8Czq1Wd3jCtHkSnA9vbvnXQsTWJpHuBhYGtbE9VliiGQNJTgF8Ba1JGxB4M/BW4NRUThqubEppASmjOI0k7t763fdBU6+dG+7Fi7rQlho+0vWOX+/yaUv636wR0TE/SG4GDKPdHP6G7qka7Vtu/yfbBQwp1rLW9H46w/aou92m9H06w/fxBxtc0uUZHxKiQ9Abgp5Tr7sHA3q0Rf1Ns+xhKh8k3Vdu/0XYqjcylJNBGU9o06iVpDUrS5i5gA9v/qTmkxphi3vBWO3a3f/et7WcBG9nOVITzSNKdlBLj29r+c9v69wBfA662vcqkfdalTBd8v+1HDy/aiMGS9D3KM/RNlM+Yq2bY/omUqVyWBX5ge6/BRzk6ktSPmEE1wm8vYG/gGR02u4TyAPy9TiMFY+5J+iel/P7Gts+pOZxGkvRw+4/0Nt+obWe6lz7poYRm6xydBqSE5lxoe/Cd4294igfiXuT90AdzOTL5xcD/kZHJfZOqRqNB0t7AfpTf96eBfTs1TFfn7BPAx6vt32H7u8OKddzlGh1RSHoq8AfK6JktbV87w/YrU0aeCXi+7X8PPsrx11ZRp+sOXJKOp3QUOzoVdeZeEmijJ20ao0HSDsDPKGWVPwT8yvYD9UY1/iRdyZx/86tUP18HPDjVPhVTpgC5jnLf+t2ZrunRHUl/o3QA3sf259rW/5kyve/Btt80aZ/nA8cC19h+0hDDjRgoSZdROjS+3/Y3utznvcBXgX/YfuoAwxs5SepH9EDSikxdQvO6+qIaf5IOAHYGdrd9YM3hNFLVKDG3bDtzpvVBSmgOV9vf/Rx/w3k/1K+tVN2Gtruay13SesA5wAO2Fx1kfE2Sqkb1k7QQpZzs0ym//4uBA5m6c8UulNFponRKXaea7zrmUa7RERMk7QPsS5lq5cVd7vN7YDvgo7a/OMj4mkLSdZQ5e19t+/Au93klZSTz9bZXGmR84ywJtNGTZ7j6VdWloLwfVqP8vT8AXA7cCjzcYVco5yDV1vpkbqYEif6S9E1KZa8bKB0aL6k6vRxRbfKIijmS3gV8AzjL9ibDjHdcSXos8N7qxx/Yvn6G7VcE9qh+/LLtewcZX1NIuhtYFNjU9pld7rMx8BcaOB1FehlG9KBK3ieBP3xfAV4HvF/SL2zfV3dADbRv3QEEADtRkgUzldA8SNKHmSihuZmk16eEZs9W63F9DM8sSiP1apQSjt14ctu+0Se2b5W0GalqVBvbD0p6EXAc5T3xTOBL0+wi4F/Ai5LQ76tco0eEpHmqBJLpvvpiO8p74bc97PMb4IXAi4Ek9fujNRihl1HerW2XnnarmJbtVdt/bksob5sEWm3SplG/LXlkBYtFKIOnOjG9V1aImZ1E+Z1OOXVaDMW3KOXGlwMulHQrsBTl7/0a4NdT7LMt5bydPawgG+DlwCeBy21/qovtrwfeADwFuJTSiTvmXatTVy/56ta2jWtfSlI/Ikae7YskvZkyX+8fJe1h+7K642oS23kAHg07VcsTJ5fhmsz2XcAukp5EKaH5RiAJgx50Kv2akrAj4VxKOdm3A12NPKu2Nd13AoguVUn6bwPfTlWjetj+t6RnURokdgeW7LDpbcCPgE9V14non1yjR8cJzMM0OaSdpB9aJWH/2sM+F07aN+bd7ZTpilai+/uf1uj8OwYSUXMlgVaztGmMhNb7IGpme8u6Y2g625dLehOwP7A4E8/PtwGvnzwthaQVgBdUPx4zrDgb4JWUz6WukvO2LekXwD6UKQaT1O+PqygDRLamVCrqRqt6y1UDiWiE5WE1ogNJi1JKY0KZT+6mGbZflpJggDLvTUY+9ZHtQyRdTinxe7GkvwKXAffMvKt3H3iAEcOxPuVmc78e9vkWJWGw3kAiiqjHIZRr7paS9gfeaXvKRlJJi1PeB1tS3j8/H1aQTZSqRvWp3gMfkPQxYAOm6FwBnJN5Swcm1+jRopk3iQFarlr20nmote0KfY6lyS6kfMbsRnmO7sab2/aNPkkCLSLvg4jJbB8m6UTgJZT7n+uAo2xPVV3wWZRqYFAqtEV/PL1adptIhjKlIJQKedEfx1B+n/8j6Ujbf5tu42pAwwcoz99/GkJ8I0V2OshFTKVtLrn/AKvNlKSX9ChKqbqVgJfZ/r/BR9kckp5KGVn23F52I3OfxRjJPOIRRTV39cnAcyg38TczMXf15DnEXw0sS7kmnGJ7nsoyR0RMJdfo0SFpiy42Wxx4GvB6YENKQ94+wGzbJw4wvEaQdAOwDPBi23/scp/tgKOBW20/fpDxNYWkvSkdjQx8GtjXHRoBq3urTwAfr7Z/h+3vDivWiIiIiGGTdCewGLCB7fO73GddSvXIO2wvObDgGkTSKpTpDBamdPT9DHCA7ZsnbbcMpQPqR4HHAfcBT7fdqNH6Gakf0dmrq+Uvuxl1b/shSYcA/0MZ4Z+kfp9UpUlPYiIpA6Uc4O00cN6UUSJpJcqFNhURhiMlNEeQpA2AbZh6VOyxts+pK7ZxVZU8eyll1NmzKdeHvauvyVrXjdOBlw0nwmZIVaOIOeQaPSJ6SMr/Hvi6pA8DnwP2sL3TDPtEdy6nJPVfCHSV1Gfi+vDPgUTUTD8E3kEZhbYPsKOkA5m6E+QuwJrVfpdW+0aMvbRpRJNJWpgyP/jLgXUo1+5Hz7CbbSenFOOilVdYrId9WtvmfdAn1XSCbwUOAB4DfAH4vKQrmfOedVVKG5+qdW9tWkIf8ocXMZ21KR8OJ/Wwz8mUpP46A4mouT5OKeE4G/gK8J3MaT0ylgJ2pbxX8gA8eCmhOUIkbUiZR3zDaTb7nKSzgbfbPns4kTWD7VslbQbsRUnmP6PDppdQztP3qrnfo39eDBxIqWp08PSbAnAr8FlKInMW6QAZ4yXX6PmU7S9I2hh4raTf2j6k7pjGwB8p1XT2lPQD25dMt7GkNYE9KM8UfxhCfI1g+0FJL6KU6V2NUtb0S9PsIuBfwIvS8W4wkkAbSWnTqJmkJag6X9s+qOZwGqOqiHokpXJRpi0aEVVH+L0AbH+q5nCa4DpgDSYqd3Wj1QZ4/UAiaijbB0m6BfgesDLlc+nJlHtYmPNz6lpgT9u/H26Uo2GBugOIGGFPqJZX97DPNdVy5T7H0nRbUx6w/tf2h5LQjwb7FeUm5hWSPlmVyZySik8Cr6C8fw4bTojNIOk1wKmUm/lWL9EHKT1Ib6y+b63fCDhV0qunPlrMLduzbX/b9pqUa+92lFLKr6++X9n2mra/k4T+QPRc1Qg4hPK+eM0Mm0fMb3KNnr8dSDl/e9Ycx7j4LnA3sChwXFVdZ0qSdgCOpSQ276V0xIs+qZ6dnwV8lVJRRB2+bqd0oF+3iSOehqFKoJ1PmVbwpcCTKKP9Op2T9q+IcfYEynV4/5rjaAxJi1OmvHk65V70SCYqtLSmbNkP+EvbutOAfYEkmgdrOeCTlClxYvBOplxn95a00EwbV9vsTXlPnDLg2BrH9u8oSfzXUj6TTgcuq75Or9a9Fli1qQl9AHWYTiui8STdRWlYeK7tv8y0fbXPJpQPmPts91K2JaYh6R5gEWBz2932moshqEbV/I0yemDBuuMZd9XN4wVMPHhdTHn4na6EpigjldfJiJv+kPR0SmnlRYCHKDeV+wPn23642mZByuib3Skjzx4F3A+sZ/vSOuKO6DdJF1IqJLzC9lFd7vNS4DfA32ynslGMjVyj529tc2PeYnvZmsMZC5LeAPyU8rcPcAWl4fS6at1KwOaUhrtWCc1dbf90+NE2QzVKfAOmnjLqHNsP1BXbuKsSaH+l/L3PBo4CbmKiQsVnKCPGN6RMLWVK29IxALb3HX7UzZA2jfrlHAyfpPcDXwYeBrazfVyn81DdI/2Mco/7Htv71RByY+T9MFySnkNJzhs4HNjF9j0dtl0MOAh4ZbX983uY9iuib1K+KaKzGyjzdKzFRM/EmaxdLaedUzZ6dh3lXKSRIRotJTRHxocoCf37gBfbPmHyBlVy/1zgXEmHUnrBLwJ8kIlyyxHzu1Q1iqjkGj3fW75aLl5rFGPE9s+rTo7foYxGbi+f2dIagXw3sJftnw0xxMapkvanV18xXG+j/P1PTqDtAWD7vyMy2xJozwZ+kQRaRAzASylJyUNtHzfdhrbPl7QVpfPq1ySdbvucYQQZMWi2T5P0C+B1lGT9JpJ+SJmOub0j6vOAt1DaQAz8Kgn9qEvK70d0dhqlkWGPHvZ5K+WDvdtOANGdY6rlRrVGETECUkJzJLSmBPnGVAn9yaob/W9Qzss2A42sISQtKmnn6mvGEZWSlm3bPp1a+6f1u1ykh30WrpapaBRjJ9fo+drbq2XORx9VcyOvAXyRMuoMJt4Hpoxc/izwlCT0Y8z1lEADtqJM6fU1SRsMPryIaJhnVssjpnpx8jRStm8CvkZ5/nvHYEOLGLo3U6aCEmXwwScpHbUvAS6tvv8k8MRqm2MpldciapGkfkRnB1fLDSX9bxfzYv4vpZRd+77RH1+hjN74kKSlZ9o4YtzZvtv2ByhlfJ9L6VD0kerrrdW6FWx/0PZd9UU6tlpJ5F7mb/rdpH1j3ryYUtb6s8CtXWx/a7XtAcALBxdW49xQLdfqYZ9UNYqxlmv0/EPSUpJeIOn3wPZMlN2MPrJ9ne2PVFOuLEJ5b6wALGp7Xdv72L5h+qNEzPeSQIuIUbJktfx327r7275/zBT7nFottxhEQBF1sX0fsB3wXuBaOnfMvhp4F/DCap/oE0lPlfQvSZdJWqmL7VeW9A9J/5S0yjBiHCUZqRTRge2jJR0HPJ/yEPUcSd9kovwKwIqU8ivvpCT0DZxk+zc1hDy2bP9D0iuAQ4FTJb3L9jEz7RdDcStlPiHPtGH0X0po1uYmSu/dXm7iWw/IN/c/nEZ6dbX8ZTdlq20/JOkQ4H+A1wD/N8jgGuQ0SinZPYAfdblPqhpFI+QaXR9JD8/lrpdTRpTHgFTX7BvrjiOiBktWy+kSaHdO2icJtOFIm0Y00T3AY5nz7/62tu+fBFw0aZ/WtisMLqyIetg28L9V7mddYD1gmerlmynTa15QbRf991rK1Mt/sH3tTBvb/o+kyyidMV5Hw57hktSPmN5rgBMoI9DWp4wK7ESUkoI7Djyqhqk6V0C5iD4N+IOk2ygNb/fMsLttbz3A8BqtutDuWnccEUN2KuX6sBFwdpf7bFwtTxlIRM2zNlVHuh72OZmS1F9nIBE108HAG6iqGgHv6fSQW41A+wYTnSBT1SgiBqVjhbUOHgJ+RfkMu30A8UREJIE2otKmMRIeoEx/M7vuQBrkCsqUUf8dEWv7ZkmzgKUolaUmfya1qtM+MJQIm+tuSjtHksc1qNozzqu+Yni2o/zN/7aHfX5DqcT5YpLUj4gW27MkbQJ8jjIKrdP8r3cD3wf2sX3vsOJrkC2Z82ZGlJvMjafcujATczVGRPTT1ygduD4q6VdVecyOJC1HKbv8IPD1IcTXBE+ollf3sM811XLlPsfSWKlqFBEjat8utplNGRV7BXCq7VTSGQJJa1I6ws+2nfaoaJIk0CI6sH05ZYRmDM/ZlM+kDYGj2tb/mVIV7wOSfm37FgBJqwIfojzLnT/USBvG9pWUdvCIJnlStfxrD/tcOGnfxshDVMQMqiT9eyXtC2zF1OVXjs+ojoFKD8WaSfolcCJwgu2L644nok62z5L0VuB7wBmS3gccZXuOkQWSFgBeSukEsCywl+0zhx7weGrdwy7Swz4LV8tOHfRi7qSqUUSMFNvdJPWjXr1WU4iY3yWBNmIkPRnYlFIJYTHgu+ngFQ1yDLA7sAPw8bb136R8Jj0ZuKzqwL0YsBkT1UZ+MNxQI6IBlquWd/WwT2vbxlU0UqaBiIiImUiazUTHipspHS1aSf4LO+4YMR+TtP8Mm6xHKeVuylyM51HmiTWwPGUerqWrbS+gNMjZ9u4DCLdRJP2TMprjrba7mstd0lsoDRBX215lgOE1jqRHk6pGERExg7aR+ra9YN3xRAyLpNcAvwD+anvdtvXPpUwRZUo5/qkSaG+ynWmL+kTSepQpoTab9NLa7QMYJL0d+ARwO/BM2w8OLcgxJWkv4MQMFKmfpMWA3wMLArva/mfba59kItHfagdsdcbb3/ZbhhVnxDBVUwauS2nnWwZ4NDN0RLX9qcFHNv4k3UD5nb/Y9h+73Gc74GjgVtuPH2R8oyZJ/YiImJGk8ymjMBeoVrVfPGYxZ5K/l1I5ESNrUmeWaTetlpO3nXJ9GrHnnaSfUuZyP8v2Jl3ucxZlJPmvbL92kPE1laQlSVWjiKhZdf2eDXzU9pfqjicmJKkfTZUE2miQ9BLgV5QKXu2JGvPIpP5jKNNJLQa8yvYRw4x1HLU9X7cGipxASfJnoMiIkbQ18BZgTUqVvMuBg2z/utbA5kOSnjeI49o+aRDHbSpJu1A6cvU0ACT3s/0h6RRK9Zxv2n5vl/t8A3gXcLbt6aZoHjtJ6kf0SNKywF6Q3ljRLFWyZgvK3E5bUMoHTpXkv405k/znDyvGiH6SdCUDmPrD9mr9PmbTSHoR8DvK+dkPeI873NRWva2/QZnT3cArM597RMT4knQfsBCwme3T644nJiSpHzG1JNAGT9IKwGXAY4CLgP8BTgHuZIqkfrXPT4GdgB/b3nO4EY+fKqnfMtVAkRMoSf4MFImx0cNgkV7YdqbV7hNJnwU+THfTQ7l9O9sLTLNtdEnSPsC+wL3AhrYvmWH7NYEzgUWBz9r++HTbj5sk9SN6lIaIiKJK8j+PiST/OnRI8jetDE5EDJ6kY4HnUz5vzqXM/3cSZUQNwIqUz6h3AhtU606yvdWQQ42IiCGS9C/KKJtNbZ9ZdzwxIc/SEVEXSV8EPgD8G1jP9m3V+lbCbaqk/u7AD4HzbG9AzJNJA0W2BNZm6jakWynTUpxASfKfP6QQI/puUmeWfsl9VJ9I2gQ4nfIZdCzlOrEApY3JlI52SwEbUgZ5vozSIezVtm+oI+ZxJGkZ4ApKdZwbgT1t/7bDtjtQpnZcHrgHWL1p5yJJ/YgepSFi+Oa1VFFKEg2HpCUoCbStgV2AJaqX8l6JiL6TtDSloWctZu75Lsq1eyvbswYcWuOlqlFE1EnSgcCbgLfb/l7N4USbPEtHRF2qKQXXBt5te7+29dMl9TejdBpu3Hy9wzBpoMiWzFkNEiae8W6ndM5++fCii+gPSVsM4ri2TxzEcZumem7YGbgSeKrth6a7X5W0F/Bt4AJgE9sPDDfi8SXpDcBPmfjsv4LSweu6at1KwObAapQ2PlOmNPrp8KOtV5L6ET1KQ8TwzWOpopQkGrCqtPV6TDyIbQ48jrb5xPNeiYhBkPRo4HPAHpQevVO5m9KLdx/b9w4rtibLvVJE1EnSBpQRN1cB69u+o+aQolLNK74RpDE6IoZL0u2U0vtzVHGZIam/DnAe8KDtRYYZbxO1DRTZsvqaoxpknisiot8kXQasDrzf9jeqddO2Z0g6DHhl+z7RH5J2Br7DRPve5HxQK9dwN7CX7Z8NK7ZRkkRXRMwvupnXJoZgmiQ+TJyneymNqScAxw81wIhojCpJ/15J+wJbUT6blqlevplSMu1427fXFGJERAyZ7XMkvRPYDzhR0tttn1Z3XAG27wGSzI+IOixULR/sYZ8lq+Xd/Q0lOrgD+E/1dS2wBrA4aQ+ca9WURP1m26sP4LgRdVixWl7Utu6/UyZIWsj25OvGT4EdgdcC3xhodA1j+yBJxwDvAl5MqczZugbMpnS2+C2wX9NK7rdLUj8i5gfdzH+8OPA04PWUeW5OA/ah7UIcc0/SepTzsCWwGROl9adK4p8AnDHFTU/E2JK0IGWerUczQ6OD7auGElSDVHNiHlF9RUREg0nav/r275RRfidLuhr4K2We3oen2d22dx9wiGNP0nGUkTVvtv3vLvdZCfgZ5RxsPcj4IgYlCbSRdj2wCqVs73ld7rNptbxmIBE1XI8DRjJYZO6sOoBjpuxzjJNWh68b29bd1fb9spRORu2urpZPGVRQTWb7OuAjwEckPQpYunpplu2H6otsdCSpHxEjr4fSjL8Hvi7pw1TlmG3vNLjIGuUcJm7cRZL4EUhaBngn8HLgmcw5/18nJvdfERERg7QrE/etpty7Pgl44gz7teZmTFJ/3m1J+V0u3sM+j27bL2J+teoAjpn3RH+cSknqvwI4fKaNq+lC3kb5/Z802NCaYYokfgaMDN5P6g4gYsTdRJmr/XFt626gdAJeAHgGj0zqt0b3P3bg0TVclcS/ccYNGyaNyhG9u5tyQ58HqxFl+wuSNgZeK+m3tg+pO6Yx8xvgi5SHq7wPopEkPYfSGLQsKQc4MiQtC+wFYPtTNYcTERH1uIo8q0VEPZJAG10/Ad4AvF7ST23/qdOGkh4D/ILSIczAj4cT4ti7hSTxh8r2bnXH0HSSPj6I46a9o28uoiT1nw6cDGD7AUkXAWtTSuz/edI+b6iWk5P9EUOh5GMiYhxJ2gE4EjjRdjfl+2Maku4BFq1+bF047qB0cDmR8vB1XpL80QSSHg9cCjyeUpbrR8BtwCcp74+3UErxbwi8jPLeOZWqMch2GvsGRNKalDm2bHvBuuNpqpyHiIhmkzSbck+0tu2Lu9znWcD5wL22exnhHxHRFUmHU6qsPQB8CzgM+Avl82oL4EFgW8oI/RWq3Q5KYrQ/2q4NAEcBXwdOTxI/xtmkv/u+yXN2f0j6GPBp4Bft1X4lfQT4LGVa388BvwQWA3YB9qac0+/ZfvvQg26Qtral2bYzQL2SpH5EjCVJ6wLnArfYXrbmcOZ7khYCNmaiTNqmlJsZmDPJfzITPayT5I+xJOkTwCeA+4ENbV/UKYkpaQXgYEoj0Vdsf6iOmJsiyeTRIGlV4EDKeUjHuoiIhpnLpP6HgM8Dl9t+2iDji4hmqkrq/x8zT/XRGkX+Z2B72/cPOLRGqK4NLWZioMgJlMEiaUOKsTPp775vbHcz/WPMoK0N6S7gCbbvqNYvBlxImVZn8ueSgFnAuravGV60zZM2vqklqR/RA0nLA2sBS1erZgEX2r6hvqhiKpK2A44G7rO92EzbR28kPYpHJvlbI2paF5bbgVOA421/fcghRgyMpL8AG9HWK3e6G01JjwYuAFYHXmD7uCGH3Bi54Y+IiE6q+9elqh9vreZojD6QtP+kVbtSngl+Q6lmNJ1FKPdIG1U//9j2nv2MLyKiRdICwHuB9zExL/Jks4CvAF+yPZCEXBNJei4ZKBIRI0bSFpRpys+zPatt/SrAz4DnTtrlQuBNti8YXpTNlDa+qSWpHzGD6ob/rZTSKs/ssNnFwHeA7+eGfzRIOgrYHrjM9tPrjmfcVY2kGzHxgPZc2h7QcuGNcSLpZkpS4FW2j6jWPZNyY29gYdsPT9pnL+DbwK9sv2bIITdGbvgjIqJddV14G7ANsAYToy8NXA4cS3mGu7CeCMfDFKVl23/PXR2iWs4CNrJ9Rb9ii4iYSttAhQ2B5YAFKXO+nwecktH5gzXFQJHnMEOS3/a5Qw1yjEl63rzsb/ukfsUSMeokPQ1Yk5L4v9z2eTWH1Bhp45takvoR06hG5v8OWK+1qsOmrTfSucBLbV8/6NjikSS15rB+L/BCynn5ou2P1hpYA1RliTZj4oFsA8rNjsiFN8aMpAcojT4btRoWJD0Z+Aflc+fxtm+btM9GwBnA1bZXGW7EzZEb/vqlqlFEjIKqY/bXgLcDCzD9c9xsYD/g/emgPXckXcmcCfxVqp+vo8xR3YmB+6rtTgO+a/vaAYUZUZsk0CKmN8VAkedQqkG2ri3OfMr9M4/zvOdcRMRQpI1vavkAjuhA0qLAccDTKY1ANwGHAmcCN1TrlqPcdL6m+n4D4FhJG6RXb/9IenjmraZ0OfDFfsYSxTRJ/P9uUi3voTTQRYyTu4AlmPNvflbb96sC50/aZ9FqudzAooqoSTdVjSSlqlFEDNMvgB2ZuCe9iKmf49aidNR7F7AS8NqhRzoGbK/a/nPb/LHb2r54+BFFjJwTmIcEGmm/jTFXTYlzuqQLKAOm/gbsDjyOzh3zYt7k9xoRMR/KTWFEZ+8FnkF5gPox8B7bd0+x3U8lfRj4OrBHtc97gS8MK9AG6PVG8yHgV5RzdvsA4mmcGZL47efnbkoS/0RKw8WZma80xtA/KO+BJ1ESBNi+TdL1wPLAVjwyqf+cajnVdST6527gJOa+0TR61ENVo2dSRsK+WVKqGkXEwEjaCXgV5VpwAbCn7bM6bLsh8H3KZ9irJL3O9i+GFuz4al2Lc98TMSEJtBpJOosyN/Ivcx86Onpoa7pnqIGNv6262GZx4GnA6ylVUU8D9qFUOIoYS5IWAtZniuqDwLm2p6tAFTEUKb8f0YGk84G1gWNsv7DLff4AbAv81fa6g4uuWSR9oovNZgN3AlcAp9q+ebBRNYuk+5n6weou4FQmkvhnJ4kf407Stygjkr9i+0Nt6/cHdqWMAtzC9mXV+o2Bo4ElgT/ZftGwY44YhKqq0Tn0VtUI4GIgVY0iYiAkHQ9sAfwd2LBDx+z27RcHzqY0XJ9ou5uG7oiIrknaoovNOibQbJ84wPAaoa3c+GzgeODnwOG276w1sIbpccDI6ZR2phMpA0aSTKtJNZjtc8AvbO9UdzzzE0nHVd/a9tZTrJ8bcxwr5p2kx1CuubsDS3XY7FbKwM/P5NoxHNU1YyOA3AtNSFI/ogNJdwGPBl5h+6gu99kBOBK42/ZjBxhexFC1ldC8gzmT+OfYntvpESLmS5K2B44C/ml7jbb1a1FKBS4IPEwZHbgY8NRqnYGX2P7D0IOOGABJHwE+S/nb3p/OVY1aD2OtqkYGPmY7VY0iou8k3ULpSLe77QO73GdXyufYbbaXnmHziIiBSgKt/yRdRKmsCRNVve4D/o+S4P99BigMlqRTKR1WOg0YOY2JJP5ZOR+jRdLhwMuAN9o+pO545hdt7alzzAne1tGolyoure0zv3gfSXoG8AfgCcx8PgxcDWxn+++Dji1iKknqR3TQ1hi0oe3zutxnPcqItVttP36A4UUMlaT/oTxcnZu5kKPpqnJcP6Qk6j9u+4q213YHvsvUUxx9wvanhxNl81Rl4B9RIs32DfVFNd5S1SgiRpGkOymd6jayfW6X+6xPGa2fztkDIulxwGMp90/Tsn3V4COKGG1JoPWfpHWANwCvoyRvYCLBfxul4tTBtk8efnTjry25CaXS5qlMJPHPzoCR0dY2kC1VjXog6QSqz5n231v7+rmRc9AfkpYELgJWrFZdCPyEqasP7kJp/wD4D7BWpv3tj6pyhYE32/53l/usRJlWp3GVK5LUj+ig6kH6bOZupP7ptp87wPAiImJESXoapQz/mpTk/uXAT22fXWdc40jSAsBbKdMhPLPDZhcD3wG+n05J/ZWqRhExiiRdSBmNuY3t47vcZ0vgOOBi22sNLrpmkfQCyjV6czqXMp3MtqfqHBnRKEmgDVY1JcIbgB2Z+HxqNZJfQxm9f7DtC2sIbyxJ+j8mkvjn5Nls/iJpXUplwltsL1tzOBF9IenzwIcon/8fBz7nDglTSQI+Anym2v6Ltj86rFjHWVvlirVtX9zlPqtT2lsbV7ligboDiBhhB1J6Y72th33eRvkAOmgQAUVExOiz/XfbH7G9g+0X2353Evr9V43MPxPYj5LQV4evZ1bbnCFphXqiHVv3V8ure9inte0DfY4lIqLl15TP/x172OdVlOe4IwYSUQNJ+iallOkOlCo6na7TU31FBLQqVqSj0QDYPtH2nsAKwCuAwyj3tgKeSEnyXCDpr5I+WF+k48P29ra/YvusJPTnS8tXy8VrjSKiv15OeQb4pe3PdkroQ8kc2/4c8EvKteIVwwkxYk4ZqR/RQdX76veUErHfB95n+74O2y4CfJUyCuGPtl80tEAbRNKjgJdQRno8me7KNzauBMswSNoA2IYpSl0Dx9o+p67YImL8SVqUMt3N0ykPUzdRymVOVSLtNdX3UEbtb2D7/snHjN6lqlFEjCJJS1CuEasAb7B96Azbvwo4BPg35RqRMprzSNJOlHKYUOasPpJyTmYBMyZybP9kYMFFzCckbQccDdxne7G642kCSY+ldAjbCdiKifamxo0CjJhM0lHA9sBltp9edzwR/SDpHmAR4MW2/9jlPrk+99lcjtR/FnA+cK/tRnU2SkmziM42B75GSVi+FXi5pEOBs4AbKR80y1MSBq+m9O49C/iqpOd1OqjtkwYc91iStBnwU+BJ7aun2cXV6+m51EeS1gZ+AGw8zWafk3QG8FbbfxtOZBH1qRp/VqP7eWJzHZh376WUVjbwY+A9tu+eYrufSvow8HVgj2qf9wJfGFagY+5AYFNKpaKukvqkqlFEDJjt2yVtQxlFc0iVYD6QqZ/jdqGMJD8beE0S+n3z1mp5NfB82/+sM5iI+dTbq+VV024VfWP7TuBAST8BXk+p9rVkrUGNMUkLAesz9WCRc20/WFdsUUhaCtiQ8gz9Qso91OG1BjUmJD1p5q0ewZTOkrfbTuW7/riTktS/sYd9Wtve1f9wogetQbXX1BpFDTJSP6KDth5C/ZT5AeeCpKdTGtoeTUnUP0CZM6XbkR6Zf64PqsbR3wILM9Gh4kHglurnpYGF2na5H9je9p+HGWfEsEjag1Kh5Vk97JbrQB9IOh9YGzjG9gu73OcPlOo7f7W97uCia45UNYqIOkl6uJvNmPmZrn2bXKf7QNKtwOOAPWzvX3c8EfOLDgm0zNk7JJLWp4zSfx2wYms1GanfV5IWA/ahdLpeqsNmt1IGlHzG9j3Diq0puryHesRuwGXAJukEOe/m8hy0uwb4C3Cg7aP7EFIjSTqWUpnl9TNV92rb5zXAL4DjUx147kia/HywK+We5zfAbTPsvgiwOqWDNsCPq+l0GiNJ/YgOqqR+v+VBYC5IOgh4I/Aw8Angm7bTG26IJC1D6UixBKUjxf7AD4HzbD9UbbMgsB7lwezNlBHLtwFr2L6lhrAjBqL6W/818NLWqh52z3WgDyTdRenoNTdl3++2/dgBhtcYVWWiRYDPUBqgb6BMgzBdVaOzgY9ROuhNKdUsIqIbeV4bXW3X6Q1tn1d3PBF1SwJtdElanZLI3wl4amt1tbwTOAL4ue1jaghv7FSjk4+lJGRmeo428A9ga9uNG4k5SHNxD/UQ8CtKhbxeRjRHB326j20l9o4FXmf71j4cs1EkvZpS3esvwGa2pz0vkhYATqVUsN3J9i8HH+X4mWIwbet60G2yurX9LGAj21f0K7b5QXqgR3SW0d2j4/mUD/X/tf25uoNpqHdTEvoPAC+bap4h2w9TkjVnS/o1ZVT/EtW+Hx9irBGD9jZKqV4oScwD6GGe2OiL+ynJgqt72Ke1bcrU9c8JzPnQtTzwzhn22RCYbq46k2eUiOjOvnUHEB1dSZny5jE1xxExKnrpBAxzJtCS0O8zScsBr6Uk8ltTC7ZXI/wj8HPgN52qUEXvqnL7RwNPqVZdSnmWPgO4nnIOlqeck12BZwJrAEdLWq81oCT6opt7qNmUji1XAKfavnmwITXObtXybcAmlLL6f6S0q95UvbYs5fl5O0pn+jMpFSweR5m24mXAMsA2lAEMWwwn9PFh+zBJL6ScjyMl7Wn7+qm2lbQ8pULhJsABSejPk6uYsy1plern6yjX4U5aU1BcB5wGfNf2tYMKclRlpH5EjDxJ91HKuj/P9ql1x9NEks4F1gG+bvt/utznK8D7KKP5NxhkfBHDJOkMysjji4HN0xt6+CSdCjybuRupf7rt5w4wvMbIKNmIiJiKpE9RqrJ82vYnaw4nonaSPtHFZkmgDZCkxYFXAm+gDBxp3W+2kvmnAT8DDrU9a/gRjj9JewHfpiRlPgd8otOo2Go07CeB/1dt/3bb3xtSqBFDIel7lGqnRwFv7VQFoeqI9ANKtcgDbL+lWr8o8D1gZ8r7JCPHeyRp5+rbt1Pa+e4D/sTU1Qe3pXSuOJvyWdaR7YMGFPJYahu5v7bti+uOZ9QlqR8RI0/S1cBKlHIq59YdTxO1zYu5VbdlkauyzCcAt9vuNE9axHxH0h3A4uSBqTaS9qD0kP6D7Rd3uc/vKT3c97b9/UHG1xSSBjISwPaJgzhuREQMh6QlgPMpcyU/2/al9UYUEU3XNi0ITCTyL6GMyD/Y9pV1xNUkko6jjCQ+0vaOXe7za+AVZO7qGDOSXg4cTulQtLlnSNJJEnAKZXDDf+d/rzrAnEmZDvUo268YZNzjpkMZ+E7nYrrX2tl2qg/2QNIJlN/trrb/XXM4Iy9/XBExPzgFeA2ltFCS+vVYtFre3cM+91TLRfocS8So+HvdATTYjygjbbaT9B3gfZ1KY0paBPgq8ELgj0no90+S7xERMRXbt1elTI8CTpW0D3BIqhtFRI0Wq5bXAr8Afm77vBrjaaK1quX+PezzY0pSf+3+hxNRq72ZmGp2xkSxbUv6BmX+9z2BQ6v1syX9EPgupVR/9G7yFDnTTZnT63Q60QXbW9Ydw/wkSf2ImB98DdgReLekgzOPVi2uB55E6fl5Tpf7rFctbxhIRBH1uRxYF1i65jiabHPKtWFp4K3AyyUdytQl0l4NrFC99tWqisiUuq1EEhEREZ1J+lf17WKU0frfAr4p6WYmOv52YturDzK+iGikAynl9Y/vJoEWA7FEtexl/uPrquXj+hxLtKnmCt+S0vGi1c4xC7gQOMF22vX671nV8h897NPadnInl79Wy8fPU0TNtFrdAUT0Kkn9iC5IWh3YgTKn+DKUkl3T9cxyykL1j+2zJL0P+F/gcElvzvxyQ3cy8Ebgw5IOtX3HdBtLehzwIUpi7eQhxBcxTL+gdFrZHjiu5lia6gTmLHu2PPDOGfbZEPjjNK+b3BtHRET0w6qTflb1tVwX+ybZFmMvCbThs/3mumMIZlGuA6sB3VZJeHLbvtFnkp4IfAV4OZ2fhR+WdATwAdtXDSu2Bmh1VFm2h31a2z520vp7q+WD8xRRA6XU++iqcguPBRacadumfTal4TJiGpIWA74NvImpS7FMbnBobZOGiD6S9PHq2zMoSbR/SzoGuJSZR3pg+1MDDK8pvk9J6q8GnCRpD9tnTbWhpI2BH1AevlztGzFOvgm8AdhL0hG203GlHil7FhERMZp+UncAEaMoCbRouHOBFwFvp8wl3o23U9qVMlVCn0naHPgtJWk23bP1o4BXUaa+2972KcOIrwGuBp5CaVv6U5f7vKlaTr42tDpN3tSHuCJqI+kFlKkpNqdU++pG4wboKBWHIqYmScAfgG0oNzc3A9dQSi6bMs/7UsDTgIWqdZdRypRje6uhBz2mJM1mzo4SU3Wo6Mj2jD26YmaS9mNizieAiykdLW6o1q0AbAI8s7UL8G3bM42ejZjvSFqO0hCxISXJfzBwaad53aO/JG0xiONmjvi5l6pGEREREZ31kECD8nx9J5AE2gBIWpDSsWIbpq6WcCxwpO2HawlwTEl6I3AQ5e/7J8A7bd/dYdvFKVO37Fpt/ybbBw8p1LEnaWXgIiZGix8N7A+cycQUmq3p7N4MvLhadzuwpu1eplCIKUj6MvB+yt/3+21/Y4bt3wt8tdr+q7Y/2PbaPsC+lOlF8owd8yVJ36R05ILeBvG4abmfJPUjOpD0GkqJZQOfAj5NSVb+lbYPi+pG8y3V6/cCO+ahq7+qpP5cs71Av2JpsqqjyxeB9wGt32mnahWzKTebH858dTG/ktRNI05PnYwo149G9SCN8TYvVY2a9uAVERERzZQE2uiQ9EJKZcGV21dXy/b71muAPW1PN31X9KBqUzoZeA7ld30zcChTDxZ5NaXUuIBTbD+vjpjHlaRvUZJnDwO72f7ZDNvvROmQ0Rq8867BRzneJD0euAR4fLXqXMrv+BzgxmrdcpSBJG8C1qf8/m8Enml7VtuxLgKeDnzM9heG8h8YE5IWAtaofvyn7fsnvb4o8FngNZTBC1cA37G931ADHXPVZ0zrc+g+4EjKe2EWJccwLduNqhKWpH5EB5KOpIw4O832ZtW6NYG/MUVDtKSNgBOBu4B189AV40rSWsBelF7ta0x6+XJKr/bv2r5w2LFF9NO8dijqIInMGBupahQRERExsyTQRoOkNwEHUH6vrUT+lZR7U1E6VqzS9tpsYBfbPx9upONL0lLA74BnV6s6JSZa5+B0SsWKWwcdW5NI+iewKvB923t3uc93gLcBV9hefYDhNYakdSjP08sz82ARUT6rXmj7r23HeDKwT/Xj52xfPohYx1U1qPMQSlvGE20/MOn1o4FtmXMAg4H9bL97aIGOOUknUkruXw083/Y/aw5ppCWpH9GBpGuAFYE3t3r7TJfUr17/KvBe4Eu2PzzMeCPqIGlhJua4uXXyzU/E/EzSJwZxXNv7DuK4EcOWqkYRERERM0sCrX6SVgEuBRYB7gY+D/zI9o2TtluWct/6EeAxlBGDT7c9eQ7rmEuSFqAMFNkbeEaHzS6hVAP7nu1BdLZvNEn3AgsD29g+vst9tgL+DNxv+9GDjK9JJC1JKZ2/M7BEh81up3T0+mQ6uPSXpB8Du1Guz3tNeu0llGlzDPwHOAvYmFLpxcBmtk8fbsTjSdKtlGpGe9jev+54Rl2S+hEdSLqPMqpsS9snV+ueSnkIMPAY2/dO2uf5lFHKF9tea8ghR0RERAxNqhpFRDSbpP+WQ7Z90lTr50b7sSLGQRJo9ZP0NeA9lPvQ59k+f4bt16GUil8c+Ibt9w86xiaStCKwFrB0tWoWcKHt6+qLavxJupZqyg/b53a5z/rA2cD1tlcaZHxNJGkRYAPK++G/g6coU7ecPbksfPSHpPOAZwFvtH3IpNd+BbwS+Duwse07JS0BnEaZ7uBA27sPO+ZxJOku4NHAhrbPqzueUZc5XSM6e4iS1L+zbV379ytQ5lFpd3u1fOIA44qKpAWp5kFLr+mIiGaStDolsbwOZY6zR/PIud3b2fbWw4itATakdHT8YTcb2z5L0ncpVY3eBaSqUUTE/O0EynXAzNm+1Fo/NyYfK2Ic3EpJoN0+04ZtWttmVGZ/bEv5fPnyTAl9ANsXSPoK8ElgOyBJ/QGokvdJ4A/f2cBLgLUpc7l3Y+22faPPqqT9adVXDM9y1fJf7SuriiLbMFFq/04A27dL2o9SSeQ5wwx0zF1JqdzymJrjmC8sUHcAESOsNXps2bZ111PKxgKsP8U+T6mWaYQYjqdTPvT/NcN2ERExZiQtJukASq/prwBvAl4EbFl9bTHpa8u2r+iPZapl+3X4wdY3kqYaVfa7arn9oIKKiIihap+beqr1c/MVMW5aSbC1p91qTkmg9deTquWxPexzzKR9I8bFNynX2w9KWmymjattPkRJcH5rwLFFDFOrTeO+SevXpZSDh4k2jJYLq2UGdfbP4dUyA3C6kMRjRGcXAKtTHqSOgTK0T9IZlOTA3sCvWxtLehRl5BnA5cMNtfHS8NMnko4bwGEzKjYi+kqSgCMoPacF3AxcQ3nwMqVU5lLA0yhVd0xJ/l9fQ7jjLFWNIiKabase10c01TcpHRo/KOkw2/dMt3ESaAPRmhbq4R72aW2bQXExVmwfK2lf4BPACZL27FTBopqK4geUZ+t9bR8z1XYR86kHKDnSZSatb00ldY3tKye91mrzWJDol69SBuq8R9IvbF9ad0CjLEn9iM6OA3YEXgh8rW39/lQj/SSdCBwKLAa8DliP8tB16FAjjeifLSl/w/3oKNE6ztyW3oyI6OTVwAsony/7Ap8Gngn8FcD2FgCSFgfeUr2+NLCH7VPqCHhMXUvpADlVVaNFKVWNJif1U9UoImJM2D6xl/URTZUE2kj4D+W+9TnAmV3u0yqtfO20W8UcJH18EMe1/alBHLeJqnNkSiWQDYFzJP0NOAu4sXpteWAjJlUNme785hzFfOhKSlvSJsCf29a/lPI+OGmKfZauljcNNLIGqaY1eCFwFHCqpH2AQ2xnCqIpyE6uJWIqklag3PTPBp5m+19tr/2ekuyf/AYScB7wXNuTy7ZEn0laE/gbZSR4esf1gaQTGEAS3nZG60RE30g6EtgBOM32ZtW6jtcESRsBJwJ3AevaTsNcH0g6DHgl8AHbX2tbfxylqtEJ7ZVaqqpGpwAbA3+1ve5wI46IiIgYvrYk2PaUBJop960zJdAml/ydQxJo3ZP0fWAPyu97/ZmeByQ9gXIOlgV+aPttg49yPEiazWDaldLu1ydTnKPpBuR0PVgn5yjmN5K+CbwDuAF4vu1LJO1AqQwJ8Ebb/7+9+46WrKoWNf7NJik5NkkBBa9Kzogg3QoqGQlmyYoIzxyuz2tCvb6LGRFF8JJERIIoWZCMcEGSgMSLCCpZggISe74/1i66+nBCVXdV7TpV32+MGqtq7bVqTM6hT9Xec681fz5izkeA7wG/z8yNehnvoIqIRt5tfmAq5W9OUnblHHd3I8o1wJW7GF7fMakvjSMiplD+nTw/on8+4PPA3pStZQEeBX4G/Edm/qOXcQ4rk/qSNJwi4q/AssBemXl01TfuZ0JEfJtSJucbmfnZXsY7qCLiQ8AhwG8z8y1N/e8DjqGchF3K6LsafSEzv97zoCVJXVclC2YAn8vMb9Qdj1Q3E2j1i4jVgesoP997gE8Avxzlet9clF07vw0sT9mCf53MvBG1pPr/veMy0zIIHeLvSCoi4lWU60jzVF2PUEo5BqXE4yqZ+cyIOacDWwGHZub+PQx3YM3h36ShywuZ1JfmUEQsTtlC9sH0H1RPmdSXpOEUEU9RTrqmZ+YlVd+/AbdQLoIumJn/GjHnTcBvgZsyc/UehzyQ3NVIkjSaps/pTTPz8rrjkepmAq0/RMT/Bf6Tmd9PH6V8L72/6luGcgPqoswsSfi5zPyvngYqSeqZiHg7pdzyAk3djwLbZebvRoxdBriLkgvaOTN/1aMwB1pEHDkn8zNzz07FMhlYy1KaQ5n5cN0xSJI0ZJ6jJAv+2dTX/HwZXlzL/bGqfXkX4xoqmXlfRMzDKLsaATsy/q5GJvQlaXDdA6xIWeEqDT2T7/0hM/9fRDwGfIOyi9RiwMhSgY1k/pOUElM/6mGIkqQey8wTI+IiYBvKtYt7gVPHyPmsCRxXPT+/RyEOvGFLys8pV+pLY4iIhSjb9AIclpn3TTB+WUp9LoBvjlwhqM6ravMuD5CZd9UcztCJiAAWp5wM3zNKQkeSuiIibgNWBrbMzHOrvgAeB14CvCMzTx4x553Az4F/ZeYCqGfc1UiShktEHAXsCuyfmYfWHI4kzSIilgT2BLYAVqdc1wB4GLiRsrvXkZn5UD0RSpIkjc6kvjSGiNgVOBq4PTNf3cL4oGz7uwrw7sw8ocshSj1X1ZfbjXICvAEwL2WbujUz86amcdsCmwGPZeZ/1hGrpMEVEScCO1FWz3ynqf98YBpwYWZu3tQ/N6W2+4bA9Zm5dm8jliRpeETEesDlwN3Aupn5j5pDkiRJkqRJz+2fpLHtRElWtpScr1aeHU/ZquvtXYxLqkVETAUuAX4CbArMR/n/PUYZfifwKeArEbF2r2KUNDTOp/zt2XJE/xFV//SIuCgi9o+ITwNXUBL6LX+ua2IRsVBEfLF6LNPC+GWbxr+0FzFKknovM68GPkzZgv+iiHh9zSFJkvpIRKwSEV+JiHMj4oaI+N+IWGXEmNUjYuuImFZXnMMgIhaPiE9GxFkR8ZeIeKJ6/KXq+2S185o0NCJiqca1i7pjkUZypb40hoi4Gfg3YNvMPKvFOVsCZwI3Z+Zq3YxP6qWImAJcRkmKzQBOAi4GfkBJkq3RvFK/mvM74HXA1zLzS72NWNIgqxLIf6P8PXp1Zv6p6diZlGT/yC+5AVwLbGI9985wVyNJ0mgi4ojq6YbAqpTP5L8A1wOPAOOV7crM3Lu7EUr1qZJjrWz9PlotX2lSq64tHQh8jLLYsLFI5EXXlSJiK+AM4DngFZn5t95GO/gi4oPAtyhlNeHFi3Ya59RPAp/MzMN6FZtUp4hYDbiB8r10rrrjGRQRsVnjeWZePFr/7Gh+r2Ewd90BSH3sZVV7bxtz7qva5Tscy1CLiNmt1f4U8BhwO/A/wDGZ+ceOBTZcdqNclHsW2D4zfwMQET8YZ85pwMaUVf2S1DGZeV9EzEO5QXXkZ8SOwOeBvYHG6vFHgZ8B/2FCv6Pa3tUoIo4HvkDZ1cikviQNpj2YmQhISpJgBeDlE8yLarxJfQ2kCRJoywPLAW8BvhwRJtC6JCKWBHZn/Bsrjs7Mh+qJcKD9GNiL8v/+3yilWnYZbWBmnhURfwJeUY05qFdBDoOI+Czwn8z8O/QY5Sb4+6q+pYF1gEWABYAfRcSimfmNGsKVNBgupHzXT2bNTTf6Z8fI9xp4Q/UfK7VpRtXOP+6oWTXG+m+rs0bb3r0VL60ey1ASy5+KiJ8AH8nMpzsV3JB4N+VD8seNhH4Lrq3aCVdvSlK7MnPGGP1PU5LGX6hWQs0NPJhuT9UNr6nay9qYc3nVrtrhWCRJ/eNuZv/CnDSQTKD1h4j4GPBVWrux4vOZaSK5QyJiOuWmrQS+DnwpM5+PiFHP6yonAv8OvBGT+h0TEatT/h0EZTHbp4ETM/PZEePmptyM/U3Kv42vRcQZLpiSNAfGyvPMbv5n6Jh4lMZ2L/AqYH1av1i9ftXeN+4oteuAqt2Ksloc4A/AVcCD1eulKD//tSgnCL8HfgMsTLnzejNgHuD9lLuw396LwAfI2lV7ahtzHqjaJTobiiS1xm1Lu85djSRJL5KZK9Udg9RPTKD1h4j4DvBRZiYOHqXcWHF/1TeVcu1jMcqNFd+JiBUz8xM9D3Yw7Vu1Z2bm51ucc2XVWuK0s/4PMBflmurGmXn3aIMy8zng5xFxKeU661LV3A/1KlBJA+WNbfZrFCb1pbFdAvwbsF9E/GjkydZI1TbA+1ESypf2IL6hkZkHRMT/pST0rwT2yczrRxsbEWsBhwEbAGdk5ser/uWAoyjbq+0UEVtm5tm9iH9ALFq1D4w3aIR5qna8u64lqW0RsRDw8erlYZk57s10EbEs8IHq5Tcz81/djG+IuKuRJEnSxEyg1SwitqTUcQf4K/BJ4JTqZ948bi5KialvUsqGfDQizs7Mc3oY7qDamHLN9L/bmPPXql1m3FFq15sov4v/N9bfo2aZ+ZeIOBD4NrB5t4OTNJgy86J2+jW6KXUHIPWxI6v2VcBxETHmBevq2M8pNwE0z1UHVFt0fQ34IzB9rIQ+QGb+AZgG3ELZLm2Lqv8eYHvgf6uhu3cx5EH0SNW2s+q+se3+g+OOkqT2vQ34MvDeiRL6lfuA9wJfArbrXlhDp7FCf/1xR83KXY0kSdKwaTuBBhxIWT1uAq0zPly19wAbZeaJIxP6AJn5fGaeCLyuGgtldb/m3NSqvbONOY3f0TzjjlK7GrumtVNG7XdVu1yHY5EktcGkvjSGzLwMOJ5yErUTcEtEfCEipkXEv0XEq6rnXwBuBnaknKSd5N1FHdc4gfpmZj410eBqzDcov7sPj+j/YdX/ui7EOchuqtpN25jzHsq/ias7H46kIbcT5e/LCa0Mzsxk5me65Vc65xLKz3S/aseicbmrkSQNt4iYOyKWqh7u2KJhYgKtfhsw88aKCUtHVTcO/z/Kd90NuhzbsGjsltbOLl8rVO0j445Su56v2nY+ixtj3Y1Tw+AJ4OLqoS6LiBkR8VxEfKbuWCYDk/rS+PYCfkv5Er88ZVXg+ZQk/i3V8y8DL6/G/BZXgHfDhlV7YxtzbqjakSdfV1XtVNSOU5mZuFl8osERsSfw1urlKd0MTNJQek3VtnNh9PKqXbXDsQwzdzWSJI0rIlaLiIMj4mbgKcpOLfcBT0XEzdWx1euNUuo6E2j1W6Bqr2hjTmPsAuOOUqsaK/TXaWPOtlV707ij1K7GjiHt7ATSGDvhbiPSZJeZf87M6ZlprffeeIaSd7ik7kAmA5P60jiqld1vpdTtvYfyx2W0x1+AjwBbtrKSXG1rJJEXbmNOY+xiI/r/WbU5RxENnx9T/g1MBc6NiNVGGxQRL4+Ig4HDKT/j24HjehalpGHxsqqdcJVNk8Z278uPO0otc1cjSdJYImJKRHwPuI6yS8urKdegGufQU6q+/YBrI+K7EeE1Kg0qE2j1a9Rmn6+NOY2xf+twLMPqHMrf/31a+XsfEesBu1LOH87ucmzD5lzK7+JTEbHGRIMjYk3g05TfxTldjk3S8GmUu3l+3FEC2rtDVBpK1Za9B0XE94G1KXeULlkdfgi4BvhDNU7dcR9ly60dgQtbnLNT1Y5M+DRuELDOexsy818RsSNld4q1gesj4tamIYdGxFLMXIEZlBsodslMVxZI6rTG35V2tm5sjPX7b2ftRfletAUzdzUaTVTtubirkSQNg+OBnZn59/+PwJXA/VXfVMquaqsDc1Fukl8OeGfPI5W671zKblGfiohfZeYN4w02gdYVZ1BKO27FzNIGE9m6aa7m3A8of+vXAA6PiH0z89nRBkbEzsChwLzAY8BhPYtyOHwP2BdYELg0Ir4GHJmZDzUPioglKed7n6vGPlXNlaROuphyE9e6lPMFjSPMQ0rqdxFxKLAP8Bzwzswcdzv3iNgJ+AVl9cePM3O/pmOfAr4B/C4z39C9qAdTdQfvsZSTsIbGB0k09d1M+V21UzJBkloSEbdQtnz/eGZ+v8U5H6FcgPhTZq7SxfCGTkQE5QLdpxh7J4S/AN8EDvFGSEkabBHxHso5QwLXA/tk5u/HGLs+ZVewdarx783M43sVq9QLEbEipYTjvMDjQCsJtIUpCbTXZKar9edQRCwHXAssBLw5M8dN7EfE6yklNv8JrJuZrtbvgIjYm5k7O94DnEZJLiflXG1+ys3Cr6RcY0rgXZl5Yh3xDrKI2I1ZS6Il8GfKzXcJLAOsxMwddhLYIzN/2tNApQ6IiM268b6ZeXE33nfYVDuzXE7ZnWjdzPxHzSH1NZP6kvpeRKxAWdnRWGX5S+AY4GrggapvKrA+sBtlRX9QTpZXbz4BjogrgfWAr2Xml3ryHzCAImIbYAfKz3wqZXXN3yknyacCJ7tCX1K3RMThwN7AbcAaY63waBo/D3AD5UaAn2bmHl0PcghVyf21cVcjSRpqEXEBMA24FVg/M5+YYPwCwFWU7fgvsn6pBpEJtPpVSYMTKbuCHAocBVzfuHZRfZddi7Kr1IcoSeddMvOaWgIeUBGxF/B9yjW+0c4PGgtGngb2zcyjexXbsKmu7R3KrDdmj7Zw5x7KDXpn9io2qZMiYgadL8WbmelOkB0SER+k7OhyI7B/Ve5RozCpL2lSiIg3A6cw9pf+WYYDTwJvy8zfNr3HysBPqpcfz8zruhCqJKnLqpUzl1I+D34J7J6ZT44xdn7KjWA7VePfZD13SZK6JyL+DiwK7J2ZR7U4Zw/gCODRzFx8guHSpGQCrfsi4k8TDJmfsjCh8XN/Bni4er0EZTcFKL+PByjXljIzV+58tMMrIl4GfAzYHhi5i9rfKItFvpmZf+5tZMMnIuamLI7aglISp/EZ/DAlufZb4JTMfK6eCKU5VyX1Oy0zc64uvO/QiYgjqqcbUsoVJWW3x+uBR4Dnx5membl3dyPsLyb1JU0aVVL+O8A2lK31RzODUu/sE5l5R69ikyT1VkQcB7yL8mX/b5RtHC8G7q36lgM2A94PvKyadlJmWqtXkqQuioh/UhJnG7S6wjUi1qWs1n8iMxfqZnxSnUygdZeJm8knIhamaQfIkWUpJGlORcS0bryvC0Y6Y5SdFBo3OraysHPoPqNN6kuadKpaaNMpJ8CLVd2PULbovyAz76kpNElSj0TESygrOLZg/C/6jZOBc4EdMvOpbscmSdIwi4gbgdcCW2TmBS3OmQ6cD9yUmat3LzpJgywijpx4VPsyc89uvK/UT6qbjl64zurNRZJ6ISL+zByUR8jMV3Qumv5nzQdJk06VtD+u7jiGVUQsSakxN97KgqO9u1pSN2XmUxHxVuAjwKeYdRvTZn8BvgkcYk13SZJ64mTgC8DOQEtJfWAXysW8U7oVlNRvTKB1nsl3qT0RsRqwL+Ua36toWiEbEbdTrvH9ODNvrClESQMuM1eqO4bJxJX6kqSWRcTHgK9SttOEWev+wcy76p4EPp+ZB/UoNElDLCICWBtYB1iy6n4IuAb4g8l8SZJ6JyIWAa4GVgTem5knTDB+F+DnwF3Aepn5WPejlOoxXgINMIGmoRER6zHOYpHMvLqu2IZBREyhlDjdn1LidOT1vYaklDr9AfDJzOxGiQtJUotM6kuSWhIR3wE+yswv+o8C1wL3V31TKUm1xkqDBA7KzE/0NFBJkiRJtYqIlYBfAOsDpwFHAb8HHqCcJywNbEDZAWx74CrgHZl5Vw3hSl1nAk0qImJ94BDK58N4rgL2z8yruh/V8ImIEyg76jT+Fv0RuJJZr/FtQLnpAsrfppMy8509DlWS1MSkvqRJJSKWADYGXgksBMw10ZzM/Eq34xp0EbElcGb18q/AJ4FTRm4PGBFzATtRtrpegfKlf6vMPKeH4UqSJEmqSUQ83/ySiWtktjImM9MSkpq0TKBJEBHvAH5KKQnc+LfwDGWFflAWiczbNOVZ4H2ZeWIv4xx0EfEe4FjK35nrgX0y8/djjF0f+DFlV7yk7MBzfK9ilTohIr7Yjfc159BdlikanUl9SZNCREwFvkuptdjWxZzMnDDxr/FFxBnAVsA9wAaZee8E45eh3FW9LHB2Zm7T/SglSZIk1S0iurGyOD2v02RlAq3/RMRiwFqU0l0vZeydEwDIzGN6Edcgi4jXUHZ7nA94DjgcOAK4LjOfr8bMRfm97A18gHL972lgncy8pY64B1FEXABMA24F1s/MJyYYvwDlGt+rgYsy843dj1LqnOq7accToX437TzLFE3MpL6kvledbF0BrMwEJ1qjycwpHQ9qyETEA8ASwEcy85AW5+wPHAw8lJlTuxmfJEmSpP4QEV/qxvtm5gHdeF+p20yg9Y+ImA4cAGzaxjR3CumAiDiSUnLlKWDrzLxwgvHTgLMoNwEcnZl7dT3IIRERfwcWBfbOzKNanLMH5SaMRzNz8a4FJ3VBl244NefQQZYpap1fSCRNBp8FVqmen0P5A3818HB6Z1KvLFC1V7QxpzF2gXFHSZIkSRoYJt+lF1mTchH6wIkS+gCZ+UREHEhJoK3V7eCGRUR8iLLwIJiNBSOaY5tT/h18b6KEPkBmXhQR36NcE9yiu6ENnUaJg+vbmNMYO0+HY5G6zuT7pHA8rZcpmgv4CLAcMHRlikzqS5oMdqB88T8jM7evO5gh9VfKjRXztTGnMfZvnQ9HkiRJkqRJwQRazSLitcD3KYmBG4AvUuq1n0G53rQKpW7v+sA+wLrApcAHgSdrCHkQLVW1Z7Yx5wxKUn+piQaqLXcBrwUWaWPOwk1zJaljqjJFu1A+j/9A62WKdomIdw1bmSLvUJE0GaxQtS1t+66uOKNqt2pjztYj5kqSJEmSNGwaSTATaPX5MGVl30PAGzLzVODuxsHMvDMzr8nMwygrAb9J2aL/4Mz0d9AZD1btU23MebpqH+pwLMPuZMoNLju3MaeRcDulKxFJGmYfqNrbgE3HSugDZOZVwGaUkkZBufluqJjUlzQZPF6199caxXD7FuUk6hMRsclEgyPi9cDHKSdt3+pybJIkSZL6XEQsFxFHRMR/1x2L1GMm0Oo3jfLz/H5m/nO8gVn8O3A+8MaIsJZ7Z/yuajdoY86GVXtph2MZdt8B/gR8MCLeMdHgiNiFkji7E6/xSeq8tssUAQdWL4euTJFJfUmTwQ1Vu2KtUQyxzLyHsvL+PuC8iPheRKwdES98jkSxdkR8l3Lyex+wVWa6/b4kSZKkxYA9qoc0TEyg1e9lVXtNU182nkTEaGUODqPcjPG+LsY1TL4DPA98LiIm3E4/IqYC/5dSJuG7XY5tqGTmY8AWlH8PP4+IX0XE2yJi+YiYJyLmrp6/LSJOAX5Rjd28mitJnWSZojbMXXcAktSCHwNvBHYFfl1zLAMtIv40wZD5KR+0H64ez0TEw5ST4SWY+SEc1diTIiIzc+UuhSxJkiRJUt/KzMciYgtKYuznVe3Yo4DfAw9QzqeXpqxg3h3YHrgKeIcJtI55SdXe09TXvBpwMcrvotn/Vu2q3QpqmGTm7yPig8ChwBUR8Qng1Myc0TyuWjyyHeUmgKWAD2XmlT0PeIBFxPPNLyk/7+3GmwKsD/wpIsYak5lprkl9KSLOr55mZm4+Sv/smOW9NEfuAl6LZYpa4h9aSX0vM0+IiB2Ad0XEZzPzv+qOaYCt1OK4xrf4+YBlxxgztWpzjOOSJEmSJA00E2h94WHKNYoFmvoeZOb1in/jxUn9Jat20a5GNmAi4ogJhtxE2S75ZOCRiLiWWW9uWRtYvBr7B2DTiNgkM/fuTsRDaeQfljH/0LQ5RupX06t25DXq6VVfO/9/N8Z7vbtzTga+QClTdEGLc4a2TJFf/iT1vYjYDPgJZfv9/4yInYDjgFuAJyean5kXdzfCgXJ03QFIkiRJkjRATKDV7xZKUv9VwGUAmflkRNxe9W3Pi+u2b1+1D/YqyAGxBxMnuxpJscWBN404Fk1j1mJmvWST+p1zQN0BSD12MaP/XRqrX731HeC9lDJFF2fmCeMNHvYyRZHp/7OS+ltEzGD2P2C9e12SJEmSahYRqwE3UM7R5qo7HqlXIuJL3XjfzDQx16KI+CrwH8CRzSu+I+LrwGeBZ4D9KCUS5qeUQfg6MBdwbGbu3vOgJ6mI+DNdSJJl5is6/Z6SpP4QEStRPoPXB06j9TJFQ7f9vkl9SX2vSurPLi8YSZIkSVLNTOpLqktEbARcTtmG/2WZ+VTVvwRwK7DYaNOAfwHrZ+bNvYpVkqRhMkqZoomS1q2MGdiFngP5HyVp4Lyx7gAkSZIkSXPkEeAY3OZUUo9l5hURsSflWvhiwL1V/98j4q3ACcDIleAPALuZ0JckqassU9QGV+pLkmZbRCwFfAggM79ScziSJEmSJEltiYh5KLXdV6Mk/m8HfpOZT9YamCSpayJihdmYlsBTwGOZ+UyHQxpKlilqj0l9SdJscwtNSZIkSZIkzY6ImJ9SQ5nMvLjmcCQNkRHbvs+OvwL/AxyVmWd1ICRpQib1JUmzzaS+JEmSpPFExCuBjYFlgPmBH2XmQ/VGJUnqB03XlWYMav1jSf0pImZ04G0aCdbfAu/KzEc68J7SmPyglCRJkiRJUkdFxDrA94BNRxw6GXioadz+wJeAx4BVM/PZXsUoabhZUrCvDG19ZEm12bNq9wU2omyr/xvgKuDB6thSlN1E3grMB1wJHAYsDKwO7AAsCWwB/AqY1pvQNaxcqS+pb0TEEdXTzMy9R+mfHbO8lzrLlfqSJEmSRoqIbYCTgHmZNVGTwBqZeVPT2AWBeymr+HfJzFN6Gauk4eU1jfr5O5BUp4g4FPgAcCrwwcx8YIxxUynJ/O2AIzPz/VX/S4BDgd0o33Pfk5m/6EXsgy4ilgO+hvmdWZjUl9Q3qi1vEqD5i3xzf7tviScFXeXJlyRJkqRmEbEMcBuwIPBH4FPApcA/GSWpX835KfAe4L8zc5/eRixpWHlNo37+DiTVJSLeBvwSuAx4Q06QLI2IoHynfR3w7sw8oeqfQlnBvw5wambu2M24h4WfD6Nz+31J/eRuRk/ej9UvSZIkSeovH6ck9O+iXCB9FKBcBx3ThcB7gfW6HJskSZIEsB8l53DQRAl9KJnliPge8AtgH+CEqn9GRBwO/IiyVb/UNSb1JfWNzFypnX71hSeAi/GmC0mSJEnFWynnB99uJPRbcGvVrtSNgCRJkqQR1qza/21jTmPsGiP6r6/aJeYoImkCJvUl9b2I2K16emtmXlFrMJpFZv4ZmF5zGJIkSZL6xyuq9so25vyzahfscCySpD4QEZtVT+/NzNtrDUaSioWrdqk25jTGLjSi/19V++wcRSRNYErdAUhSC44CjgRWrDkOSZIkSdL45qnadi5qLlq1T3Q2FElSn7gQuADYpLkzM/+YmVOslyypBn+p2ve2MWfXqr17RP/Uqn1wjiKSJmBSX9Jk8FjVeidvn4iIl0TEJhGxc0TsGhELTzxLkiRJ0hC4r2pfMe6oWW1ctX/tcCySNJ5GScGL6w5kCDxetTfUGoUkzXQqEMD7IuJjEw2OiI9TbgDIam6zjar2rk4GKI3k9vuSJoM7gbWAxeoOZNhFxMuBrwHvZOYKHCh1hG5qGrc38EHKDRlvyczsZZySJEmSavM7yi5rOwK/nGhwRMwP7Eu5QGpiTVLPWFKwp+4GXgvMX3cgklT5L2B3YAng2xHxXuAY4GrggWrMVGB9ygr9dau+B6u5zd5F+S57bpdjHiaPUH4f5hWamNSXNBmcAqwNbAecX28owysiNgTOpNxcEU2HRvtgPRU4hJL4fwvwm64HKEmSJKkfHE1ZxfTuiPhpZp4z1sCIWBA4HliBcl7x370JUZLUY2dQkvpbAJfUHIskkZl/j4g3A2cDS1OS9uuOMyUoO1JtmZkPv9AZ8UrgyupxcvciHi6ZeQ+wR91x9Jtw8aSkfldt7f4HYFlg68w0sd9jEbEIcAvlC869wFcpJ2E3UC6+rZGZN42YcwqwPXBIZn6ktxFLkiRJqktE/BJ4G/AMcDBwIvA/lHOHacCzlJt/9wWWqaYdk5l79jxYSUMnIl4CrEf5+zM/8OvM/Ee9UQ22iFiGcg1pXmCTzLyx5pAkCYCIWBQ4ANgNWGSMYY9RVo1/OTMf6VFo0ouY1Jc0KUTEKsBJwGrAkcBxwPXAI27t3n0R8XngK8BDwPqZeXfVP4Oxk/r7AT8ArszM1/U4ZEmSJEk1qbbUP52yrfV452uNHcDOA7bNzKe7HJqkITZeScHmaxqWFOyOiNiIsop1IeBA4LiqBIIk1S4i5qPc8LU6M8sAPwL8EbjK76m9Ue18sDEzb7z7UWY+VG9U/cOkvqS+FxHPN7+kvToqmZmWGplDEXEFpX7Qf2TmfzX1j5fUnwZcAPw9M5fqZbySJEmS6hURU4CPA5+g7Lo2moeBbwHfyMwZvYpN0vCZoKTgyKT+UsBfKIn/rTPTkoJzKCL+VD1dEFiSmdf2HgceBZ4fZVpDZubK3YtOklS3iFgH+B6w6YhDIz+j9we+RLnxbtXMfLZnQfYBE12SJoOY4LW671VVe3Ebcx6t2oU7G4okSZKkflcl6b8dEQcBG1JuEp4KzAX8HbgWuNRVT5K6rSop+GtgcV5cUvBFMvPBiDiLUlJwG8Ck/pxbacTrxrW9harHeFyVKEkDLCK2oezSPC8vvvFupKOB/wKWALYFTul6gH3EpL6kyeCAugMQL63aJ9qYs2DVPtXhWCRJkiT1qYjYrXp6a2ZekZnPAZdVD0mqw4eBpSklBTduKik43pxzgR0oNyVpzh1ddwCSpP4TEcsAPwfmo5Q6+BRwKfDP0cZn5uMR8SvgPcBWmNSXpP6SmSb16/cgsDzwcuAPLc5Zr2rv7UpEkiRJkvrRUZRVNe8Grqg3FEkCYDvK36XvNBL6Lfhj1brtewdk5p51xyBJ6ksfpywOvAt4Q2Y+ChPeeHch8F5m5h+GxpS6A5AkTQpXVu1WrQyOiLmAfSgnzZd2KyhJkiRJfeexqr291igkaSZLCkqS1J/eSskhfLuR0G/BrVW7UjcC6mcm9SVJrfg5pZ7NXhGxzngDI2IKcCiwatV1bJdjkyRJktQ/7qzaxWqNQpJmsqSgJEn96RVVe+W4o2bV2Jp/wXFHDSCT+pKkCWXmyZQamPMB50XE/hExtXlIRCwdEbsCVwF7Ue6wOzszL+x5wJIkSZLqcgrlhuDt6g5EkioPVu3L25hjScEuq64jbR4Rb68em0fE0nXHJUnqqXmq9tk25ixate3crDcQTOpLklr1NuAWyofm9ykntlkduwa4h1I/cy3KRbwbKbVtJEmSJA2Pgyg1MT8UEW+qOxhJwpKCfSOKD0bEDZTrSOcAx1ePc4B7IuKGiNgnJiioLEkaCPdV7SvGHTWrjav2rx2Ope+Z1JcktSQzHwLWBw4BnqYk7huP+ZqePwccBry+jTo4kiRJkgZAZv4DeDPlhuDfRMRhETE9IhY3QSOpJpYU7AMRsRhwCfBDys83xnisCvwIuDgiFq0lWElSr/yuandsZXBEzA/sS7nx7uJuBdWvIjMnHiVJUpOIWAJ4KyXJPxWYC/g7cC1wVmbeU2N4kiRJkmoSEc83v2Tm7l6tyMycu8MhSRIRcSnweuBR4AvAiZTVgQmsDjwMvAX4OGUHQiglBbfpebADqLqp6yJg06rr78AJwBWU30MASwMbAu8AlqTaKSEzp/U8YElST0TEFpSdWmYAW2fmOVX/DMrnwBqZeVPVtyBlZ5etq2PrZ+a1tQReE5P6kiRJkiRJ6ojqAtzsysycq2PBSFIlIpakrOh7DS++2egZYN7m4cANwDR3IOyMiHgv8FPKz/44YL/M/OcYYxek7BK5azX+fZn5817FKknqrYj4JaX07zPAwZQb7/6H8hkwDXiWcuPdvsAy1bRjMnPPngdbM5P6kiRJkiRJ6oiI+NKczM/MAzoViyQ1q7bsPRDYG3jJGMOeBY4EPpmZT/QqtkEXEWcAWwEXZuabWpxzASWZc5Y7JkjS4Ko+n08HpjP+Ll+NUl7nAdtm5tNdDq3vmNSXJEmSJEmSJA0FSwr2XkTcS/lZvz0zf9ninJ2Ak4D7MnO5bsYnSapXREyhlMD5BLDsGMMeBr4FfCMz52R3sEnLpL4kaUIRsQ5wFWULnFUy828TjF8euAOYG1izUfdGkiRJkiRJwyUinqZcI2q5/nF1Lepq4JnMHGtnBUnSAImIuYENGf3Gu0uHcXV+s7nrDkCSNCm8k7K9zekTJfQBMvNvEXEqsAvwLuCLXY5PkiRJkiRJ/ekxYAlgOUpiphWN1fn/6EpEkqTaRcRu1dNbM/OKzHwOuKx6aIQpdQcgSZoUplPq2ZzVxpwzqnaLjkcjSZIkaVKIiHkiYqOI2DsiPl099q765qk7PklST9xYtXu2MWevEXMlSYPnKOBIYMWa45gUXKkvSWrFy6u2nW30b63al3U4FkmSJEl9LiLmB74AfABYbIxhj0TEYcDXMvPJngUnaahYUrAvnERZMLJjRHwZOCDHqAscEQF8CdiRssDkxB7FKEnqvceAhYHb6w5kMnClviSpFUtU7VNtzGnUt5na4VgkSZIk9bGIWAG4DvgMsDillNdoj8WBfweujQhvBpbULW2XFAROpVw7f1eXYxsWhwO3UH4PXwCuj4hPRsSmEfGqiFilev5J4A/VGKo5h9cTsiSpB+6s2rFuAlYTk/qSpFY8UrUrtDGncVHO2meSJEnSkKi21D8LWIWSvLmFkrifDrwGeG31/DOUncACeBVwVkS4o6SkbpiOJQVrlZnPAltRkjcBrAp8A7iI8jlxa/X8G8Bq1Zg/AVtV9ZUlSYPpFMrf/O3qDmQyMKkvSWpFY6u57duYs2PV3jruKEmSJEmD5P2UxH0C/wmsnpnfzMyLM/O2zLy1ev4tYE3ga9W8Vau5ktRplhTsA5l5F+Xv/rcp2y2PtYvLY8C3gLUz8+56opUk9chBwF3AhyLiTXUH0+9ijNI1kiS9oNr+7JvAc8DmmXnJBOM3A86j3Dz2ucw8sPtRSpIkSapbRJwPTAN+lZk7tzjnZMpNwRdk5ubdjE/S8ImIp4B5gPUy87oW56wDXA08k5kv6WJ4Qyki5gXWA1anlGIBeBi4Ebg6M5+pKzZJUm9FxCrASZSdWo4EjgOuBx5Jk9izMKkvSZpQRCxI2fZsCeBJ4HPA4Zn51IhxLwH2oazIWYByQvbKzHQLfkmSJGkIRMQDlPOG7TPzjInGV3O2Bk4HHsrMqd2MT9LwiYh7ganAjpl5aotztgN+jX+XJEnqmoh4vvklZbevVmVmDlX5rqH6j5UkzZ7MfDwi3gOcCcwPfA/4ekRcBdxL+bBdDli/Oh7As8C7TehLkiRJQ2WRqr2njTn3Vu3CHY5FkqBsuz+VUlKwpaQ+lhSUJKkXYoLXamJSX5LUksz8bUS8FTgWWJayEn+zEcMaH7p/A3bNzAt7F6EkSZKkPvAwJXn2CuDaFue8smmuJHXamcAbgd0i4ugWSwruSlnAcHoP4pMkaVgdUHcAk4nb70uS2lJtsb8bsA2wDrBkdegh4BrgNODYzHy6ngglSZIk1SUizgC2Ai7IzM1bnHM+MA04OzO36WZ8koaPJQV7JyJ268b7ZuYx3XhfSZImE5P6kiRJkiRJ6oiIeB9wDGWF69HAhzPziTHGLgAcDOxRjd81M4/rUaiShkhEbEFZsT9X1fUkMFFJwW0z89zeRzt5RcQM2quH3Iqhq5ksSdJoTOpLkiRJkiSpIyIigEuA11MSOw8BJwBXAPdXfcsAGwFvB5aiJNAuzcyR5b0kqWMi4o3MLCkIL04+W1JwDlVJ/U7LzJxr4mGSJA02k/qSJEmSJEnqmIhYDDgDeF3VNdbFp0YC7XLKithHIZfb6QAAJlpJREFUuh2bpOFmScHuiogVu/G+mXlXN95XktRfImIeYF1gdWDxqvth4Ebgmsx8tq7Y+oFJfUmSJEmSJHVUREwBPgTsB7x2jGE3A4cAh2ZmN1Z3SpIkSepzETE/8AXgA8BiYwx7BDgM+FpmPtmr2PqJSX1JUssiYl7gvcDbgLUod7S/dIJp1j6TJEmShlhELMsoq20y8976opIkSZJUt4hYAfgtsDIzd/IaSwL/C2yemX/tdmz9xqS+JKklEfFvwK+AVzPxh2sza59JkiRJkiRJkqQXVNvtX8fMnb1uAY4ErgDuo+QhlgY2BPYAVq3G/RFYJzOf62G4tTOpL0maUEQsAFwPvAKYAZwKPEjZDieBr1G2xVmfUjczKXUxzwXIzAN6H7UkSZIkSZL6TUSsB2zB6DWTf5uZV9cVmySpdyLiQ5RyXAl8HfjSWGW5qvJeXwY+X43fPzMP7VGofcGkviRpQhHxSeCbwPPAWzPz/IhYDbiBESvxI2Jt4FjgNcDHMvMHNYQsSZIkqQ9ExNLAdEZP3FyYmffXFJqkIWNJwfpFxBqUesgbTjD0CuCDmXlD96OSJNUlIs4HpgG/ysydW5xzMrAjcEFmbt7N+PqNSX1J0oQi4kLgDcDxmfneqm/UpH51bCngD5QT5I29w1qSJEkaLhHxcuBblOTZWAmx54FTgE9n5t09Ck3SELKkYP0iYgvgNGBeZv4OngX+Xr1eHJinacrTwLaZeV4v45Qk9U5EPAAsAWyfmWe0OGdr4HTgocyc2s34+s2UugOQJE0KjVo1p4x2MCJmOSHOzAeB71Au3v2f7oYmSZIkqZ9ExBsoNwDvQknQxBiPuasx10fEpvVEK2nQVSUFz6LsKJiU5P7h1eEEvgr8APifpr7LgAOAr/Qy1kEVEUsCJwLzUX6+PwE2AhbIzOUyc1lgfsoK/sMpN33NB5wYEUvUE7UkqQcWqdp72phzb9Uu3OFY+p5JfUlSKxat2rua+p5uer7gKHN+V7XTuhGQJEmSpP4TEctTVmIuTEncnwW8HVgReEn1WJGSzD+zGrMwcFpELFdHzJIG3r7AKyiJ4rdk5k7A9xsHM/NLmfmRzHw9sC5wM/A64O+ZeUAdAQ+gj1ISN88A22TmPpn5+8x8rjEgM5/PzKsy84PANpRV/ItUcyVJg+nhqn1FG3NeOWLu0DCpL0lqxZNV21yz5dGm5yuMMqcxdpluBCRJkiSpL32WkqR/HtgtM7fJzJMz8y+Z+Uz1+Etm/jIztwXeB8yo5ny2xrglDa7tKNcoTsjM88cbmJnXAW8EHgC+ExHrdT+8obAN5Xfwg8z8zUSDM/Mc4GDKjV/bdDk2SVJ9rqH8rd+/jTn7Uz5Tru1KRH3MpL4kqRV3Vu0LK2cy8yFm3g23yShzGie+z3QxLkmSJEn9ZWvKRbbDM/PYiQZn5nHAYZi4kdQ9lhSsX2MF5qltzGmMfeW4oyRJk9nPq3Z6RBxRlcwZVUQsEBFHANOrrp91O7h+Y1JfktSKq6p2/RH951Euvn26ucZZRKwE/DvlYt51PYhPkiRJUn9o3Ah8YhtzGmPdfl9SNyxatZYUrM9LqvaJNuY0do2cr8OxSJL6x8+Ayyg5ht2BP0XEwRHxvoh4c0RsUT0/GLijGgPwu+rm4KFiUl+S1IpzKR+s24/ob9SgeyVwW0ScGBFnAH8AXlYdO6w3IUqSJEnqA49U7WNtzGmMfWTcUZI0eywpWL/7qnadNuY0xt7f4VgkSX0iM5NSJud/KPmHpYD9gKOBs4HfVM/3A6ZWYy4Hdqgj3rqZ1JckteJ04GLgnxGxcqMzM38HfIXyYboYsBOwJbBQNeTIYbxjTpIkSRpijV2+1mhjTmPsVeOOkqTZY0nB+l1CuXb02YhYeKLB1ZjGDpCXdDk2SVKNMvMRYFPgw8DNlM+L0R43U8rivKGaM3Si3AQhSdLsi4jNgfcDq1Fqzt0OHJOZJ9camCRJkqSeiogtgHMoF902yMwnJxg/PyWZ/2pgy8w8t/tRShomEXE4sBfwn5n5xab+XwBvp2zn+7rM/HvVvxJlYcPywCWZOb3XMQ+aiNiEkpxP4AbgA5n5+zHGbkjZ9XHNavxm1aISSdIQiIhlgdWBxauuh4EbM/Pe+qLqDyb1JUkvaNwtnZn/qDsWSZIkSZNTRHwJ+BIlWb9PZl43xri1KImb9YEDMvMrPQtS0tCIiHcAxwPXZ+baTf3NieZHgfOB+SmrBReq+nd1B8LOiIgfULZPbiQkbgKuoGyvn5RSBxsBqzamAIdk5od7HKokSX3JpL4k6QURMQOYAayZmTc19e9WPf2VCX9JkiRJY4mIxirYbSnJ+saqzN8DD1SvlwY2YNZt988Y731N+EuaXdWOIGcCcwF7ZOYdTce+DDT+bjUulEfVHpGZ7+9VnIMuIgI4EPgEM8sCj0xONH72M4BvA59NExiSJAEm9SVJTaqkfgJrjEjqj9ovSZIkSc2azh1e6OLFSZtWjs0iM+eaw9AkaVSWFOytiFgd+BCwBfCqEYdvB34L/Cgzb+x1bJKkekXE0sB0Rtl+H7gwM++vKbS+YFJfkvSCiHiWcrf0es1bZJrUlyRJktSK6tyh4zJzysSjJA0zSwpOPhExL7BY9fKRzHymzngkSfWIiJcD3wLeRrnBbjTPA6cAn87Mu3sUWl8Z6wcjSRpODwFTKfXLrqs3FEmSJEmTjcl3STV6FJgREZYUnCSqJP5Qr7qUpGEXEW8ATgMWYmYZltHMDewCvDUits3MS3sRXz8xqS9JanY55W64AyNiEeA24Nmm4xtExJLtvmlmXtyZ8CRJkiRJksY0WjLgKMrug1cB7j4oSVKfiIjlKQn9hauus4AjgCuZedPX0sAGwF7A1tXY0yJitcy8p7cR18vt9yVJL4iITYALKVvwz3KoamfnQyMz05vIJEmSJL0gIuYDFgUezMyubNkvabhYUrB/VQtEvlG9/PxESZgqyfNVyu/tE5n5WJdDlCTVICIOBvanbK2/Z2YeO8H49wDHUPIVh2TmR7ofZf9wSzRJ0gsy83fATsAdlA/GxqMhZvMhSZIkaQhExIIRsXX1WHCU40tGxMnAP4B7gEci4ltVXWVJmhMPVe2qtUah0ewC7AGs3cqqysz8G7BWNWenrkYmSarT1pQbuA6fKKEPkJnHAYdRcg7bdDm2vuPKSUnSLDLzNMr2NS8HlgdeApxP+XDdG7izxvAkSZIk9bedgSOBu4FXNh+IiCmULTXXZebNvwsBHwdWAN7RuzAlDSBLCvavHSjXlU5qY84JwDqUpP6R3QhKklS75ar2xDbmnAjs2zR3aJjUlySNKjP/AvwFIOKFxfZXulWdJEmSpHG8tWpPHmVb/XcC61ESO9cAFwHTKEn+nSNiy8w8u2eRSho03wa2o1zk/8GIY0Gp0duuxGvonbBK1V7ZxpyrqvZVHY5FktQ/HgGWBtops9IY+0jnw+lvbr8vSWrF0dVj6D4oJUmSJLVldUoS7PJRju1atVcDr8vMTwIbMzPJs1v3w5M0qCwp2NcaqykfbGNOo5zC8h2ORZLUPxo3cK3RxpzG2KvGHTWAvMtQktSOTWlvKxxJkiRJw2Wpqr2ruTMi5qGsyk/gh5n5HEBmPhsRhwIbAhv1MlBJg8eSgn3racrvYpE25ixctdn5cCRJfeL7wLbAZyLixMx8crzBETE/8O+Uz4aDexBfXzGpL0lqRWPFzC9qjUKSJElSv1u8ap8d0b8+8FLKBbizRhy7rWqX6WJckoaIJQX7zl8pCf2NgYtbnLNJ1f6tKxFJkmqXmb+NiAOALwEXRsQ+mXndaGMjYi3gMODVwAGZeW7vIu0PJvUlSa14kLLi5v66A5EkSZLU1/4FLARMHdE/rWrvyMyR5xX/6npUkobZ0ZQbiiwpWJ8LKeVZPhwRP8rMf4w3OCIWBv4P5fd2YdejkyTVIiK+SPlbfxXlJuCrI+IG4PfAA9WxpYENGLHtfjV3VJn5lS6GXRuT+pKkVtxEuQi3InBdvaFIkiRJ6mN3AGsD04Fzmvp3pFyUu2iUOY0t+x/oZmCShp4lBevzY2A/YFngjIh4e2beN9rAiFiG8ntaDphRzZUkDaYvM7PMSgJBSd6vMcrYqMasXz3GM5BJ/Sl1ByBJmhSOpXxo7l53IJIkSZL62rmUc4f9ImKriFgwIj5MWV0DcNooc9as2nt6EaCkobMb5XrGuKvD1T2Z+UdK3eQAXg/cHhH/HRG7R8RbIuLN1fP/Bm6vxiRwyFjbMEuSBkY0PUa+bvXYaGMHTmTmxKMkSUMtSgG6c4A3Ue5y+0r6ASJJkiRphIhYFriZsgX/LIcoO4CtMfJcIiIuADYDvpuZn+pJoJKGRkTcR9kRZD0TxPWJiCnA4cCeVddY15UayZifAB/0+pMkSYVJfUnShCJiM+ClwIGUrW9uA34BXE+pSff8ePMz8+JuxyhJkiSpP0TEG4DjKdssN/wJ2DYzbxkxdmXgVkoSZ+vM/E3PApU0FCLifEpJwZ0y89d1xzPsImIH4N+BjXjxasoELgMOzMzTex2bJEn9zKS+JGlCETGDse+gnkhm5tydjEeSJElSf4uIeYFNgGWAe4FLM/O5UcZtCmxevTwwM5/qXZSShkFE7EVZ9f2rzNyp7nhURMTiwNrAklXXQ8C1mflIbUFJkvpSRMwHLAo8mJkzag6nNib1JUkTqpL6syszc66OBSNJkiRJktQiSwpKktSfImJBShkugIsz8/ERx5cEfgxsC8wNPE4p5fK5zHyml7H2A5P6kqQJRcS0OZmfmRd1KhZJkiRJkqRWWVJQkqT+FBG7A0cCdwOvbF6FHxFTgCuAdZm1XEsCJ2fmO3oZaz8wqS9JkiRJkiRJGkiWFOxfEbEScATl57z5BMMlSQMmIo4D3gV8NzM/OeLYu4GfUT7DrwUuAqZRkvwJbJOZZ/c24nr5hUSSJEmSJEmSNMhi4iGqwQLAdGb/pgtJ0uS2OuUz4PJRju1atVcDr8/M5yJiHuASYANgN8CkviRJkiRJkiRJA+CNdQcgSZJGtVTV3tXcWSXvp1ES/j/MzOcAMvPZiDgU2BDYqJeB9gOT+pIkSZIkSZKkgZSZF9UdgyRJGtXiVfvsiP71gZdSkvpnjTh2W9Uu08W4+pJJfUnShCLi/DmYbl00SZIkSZIkSZLU7F/AQsDUEf3TqvaOzLx/lDlDyaS+JKkV0yl3xY1Xg25k/bMYo1+SJEmSJEmSJA23O4C1KfmHc5r6d6TkFUbbbaexZf8D3QysH5nUlyS14mImTs4vALwKWKQaextwb5fjkiRJkiRJkiRJk8+5wDrAfhFxCXAJsCewASXHcNooc9as2nt6EmEfMakvSZpQZk5vZVxEBLANcBClHs77M/PSLoYmSZIkSZI0JksK9rUHgAPqDkKSVJuDgH0pW/CfPuLYzYye1N+GkvC/vLuh9Z/IdFdkSVJnRcSywDWUm8fWzsy/1RySJEmSJEkaQhExgzkoKZiZc3UlMEmSRES8ATgeWLap+0/Atpl5y4ixKwO3Uj6nt87M3/Qs0D5gUl+S1BUR8WngQODgzPxo3fFIkiRJkqThExEX0n5JwdupSgpm5hu7Gd8wiIjNM/O82Zz7w8zcr9MxSZL6R0TMC2wCLEP5/L00M58bZdymQGMHnQMz86neRVk/k/qSpK6IiI2B3wF/ysxV6o5HkiRJkiRpLCNKCi4E7GRJwc6IiH8Am2fm79ucdxiwt7slSJIEU+oOQJI0sJ6p2uVqjUKSJEmSJGkCWZwObAo8D5wSEcvXHNagWBA4MyJe2+qEiPgJ8P7uhSRJ0uRiUl+S1C2bVu2TtUYhSZIkSZLUosy8F/gOsATwmZrDGRS3UX6e50TEChMNjoijgD2rlz/rYlySJE0aJvUlSR1Xbb3/RUoduitrDkeSJEmSJKkdjW33t6k1isHxZuCvwPLAuRExdbRBUfwU2A0I4Ghg955FKUlSH5u77gAkSf0vIr7YwrApwGLA+sBG1esEvtvF0CRJkiRJkjrNkoIdlJl/iYg3A5cAqwC/iYjpmflYY0xETAGOBd5VdR0BfCAzs+cBS5LUh0zqS5Ja8WVKgr5VATwHfCYzz+1KRJIkSZIkSd1hScEOy8xbI2Ir4HxgTeD0iHhzZj5VJfR/Dry9Gv6TzNynrlglSepHbr8vSWpVTPAA+CdwPfB9YO3M/F7vw5QkSZIkSZo9lhTsnsy8GtgBeBp4PXByRLwUOImZCf0fm9CXJOnFwt1rJEmSJEmSJEmDaA5LCm7pDoSdFxE7UBL5U4AHgaUoC0Z+lJn71xmbJEn9yqS+JEmSJEmSJGkgRcQMZr+k4Pe6EpSIiN2BI5i5++MPMvMjNYYkSVJfM6kvSZIkSZIkSRpIVVJ/IkkpKXgncBFwWGbe1NXABlBErNDmlI9Vj5OAT401KDPvnv2oJEkaDCb1JUkdExErA0sCf87M++uOR5IkSZIkSb0REc934W0zM+fuwvtKkjSp+GEoSZpQRCwFvL16+bPMfGzE8VWAXwBrV10ZEb8C3p+Zj/YoTEmSJEmSJNUnJh4iSZJmhyv1JUkTioh9gR8Ct2bma0ccmw+4EXgls568JXBJZk7vVZySJEmSJEmqR0Ts3o33zcyju/G+kiRNJq7UlyS14i2UJP3JoxzbA1i5On4qcB6wBbAd8IaIeEdmntCjOCVJkiRJktpmScE5Z/JdkqTumVJ3AJKkSeHVVXvlKMfeXbXnZ+bbMvPgzNwB+C1l5f67R5kjSZIkSZLUdRGxVETsVz0WGeX4KhFxNXAbcBnwt4g4KSIW7XWskiRJYzGpL0lqxVJVe09zZ0S8FNiYskr/sBFzjqjadbsbmiRJkiRJ0ph2Bn4AfDgzH2s+UJUUPAtYm7IwISjXzHcEftXTKCVJksZhUl+S1IpFq3bGiP7XAfNQkvq/HXHszqqd2r2wJEmSJEmSxtVKSUEoJQU/CpxGSe6/ISLe0YsAJUmSJjJ33QFIkiaFx4FFgGVG9E+v2psy85ERx56t2ue6GJckSZIkSdJ4Wi4pWD0/OCLOAbaojp/Q3fAGR0R8sRvvm5lf6cb7SpI0mZjUlyS14hZgI2BL4Mym/p0pd7tfNMqcxg0A93c3NEmSJEmSpDHNbknBLbCkYLu+TPl5dppJfUnS0DOpL0lqxRmUrfb3iYibgUsoW9StSjlZ++Uocxonvn/tRYCSJEmSJEmjWLRqxyopOANLCnZS1B2AJEmDyKS+JKkVPwD2A5atnje7PDMvGGXOdpSE/yVdjk2SJEmSJGkslhTskcycUncMkiQNKj9kJUkTyszHKNvOXUO547rxuAR4x8jxEbEWsEH18twehSlJkiRJkjTSLVW75Yh+SwpKkqRJw5X6kqSWZObNwPoR8QrKye29mfnncabsWbWXdTs2SZIkSZKkMVhSUJIkTXqRmXXHIEmSJEmSJElSx0XEIsBNlJKCzRfDA7gsMzcdZc4VwPrA1zPzCz0JVJIkaRxuvy9JkiRJkiRJGkiWFJQkSYPAlfqSpNkWESsBRwCZmZvXHI4kSZIkSdKYWikpWCX1165e/iwzn+tNdMMhIt4IvA1YC1gSeCnlJouxZGau3IPQJEnqayb1JUmzLSJWA26gnGDNVXc8kiRJkiRJ6j8RMRU4HpjW6BpjaI445jUnSZKAuesOQJIkSZIkSZIkDaaImAc4i7IDQgDXAvcA21CS+McCiwHrAstVfdcAN9YQriRJfWlK3QFIkiRJkiRJktRLEbFSRJwfEefVHcsQ2ANYp3q+Z2auB3y2cTAzd8/M7TPzZcCOwL3AqsDpmblnr4OVJKkfmdSXJEmSJEmSJA2bBYDp1UPdtXPVnp2ZR483MDN/Tdmi/xngqIh4VbeDkyRpMjCpL0mSJEmSJEmSumUtZm6z/yIREc2vM/MO4CDKjRcf7Xp0kiRNAib1JUmSJEmSJElStyxetXc29T3T9Hz+UeY0yiK8uSsRSZI0ycxddwCSpEntAeCAuoOQJEmSJElS33qGkotoTuT/o+n58sBtI+Y81XRMkqShZ1JfkjTbMvNBTOpLkiRJkiRpbHcDrwGWbnRk5v0R8U9gQWAjXpzUX60xtCcRSpLU59x+X5I0oYjYfA7m/rCTsUiSJEmSJGlSuaZq1xnRfzEQwEcjYr5GZ0QsAnyGktC/qScRSpLU50zqS5JacUpEbNDupIg4DPhgF+KRJEmSJEmaE42Sgl+pO5AhcB4leb/NiP5Dq3Yd4IaI+GZEHALcQFnZD3BMb0KUJKm/Raa710iSxhcRM4C/A5tl5s0tzvkJsBeQmTlXN+OTJEmSJElSf4qIRYHrKIn9N2XmHU3HGtePYOZW+1G1vwG2ycwZvYlUkqT+5Up9SVIrbgOWAM6JiBUmGhwRRwF7Vi9/1sW4JEmSJEmSxmRJwfpl5qOZuVJmrtic0K+OvR/4AHAF8ATwNGWl/qeB7UzoS5JUuFJfkjShiHg58DvgZcDtwBsy84FRxgVlW7T3Vl1HA3ulHzaSJEmSJKkGEfEPYPPM/H2b8w4D9nb3QUmS1A9cqS9JmlBm/gV4M/AQsArwm4hYpHlMREyhrMpvJPSPwIS+JEmSJEmq14LAmRHx2lYnVFvCv797IUmSJLXHpL4kqSWZeSuwFfA4sCZwekS8BF5I6P8ceFc1/CeZ+X4T+pIkSZIkqWaWFKxZRJwfEedFxIptzFmuMa+bsUmSNFm4/b4kqS0RMR04E5gPOBvYhXKS+7ZqyI8z80N1xCZJkiRJktTMkoL1i4gZQAJrZOZNLc5ZmfL7SksgSJLkSn1JUpsy80Lg3cAMYEvgTmCH6vCPTOhLkiRJkqR+YUlBSZI0CEzqS5Lalpm/ZmZtualAAD/IzP3ri0qSJEmSJOnFLCk4KS1QtU/VGoUkSX1i7roDkCT1j1ZqyzW5ADgI+BhwEvCtseZn5t1zHp0kSZIkSdLsycyrI2IHSknB1wMnR4QlBfvXVlX711qjkCSpT4Q3HEqSGiLi+S68bWamN5FJkiRJkqTaVYn9kyi72D4ILEXZgfBH7kDYGRFxxIiuPYAEfg08OsH0+YCVgQ2q1/+dmft0Mj5JkiYjk/qSpBdExIwuvG1m5lxdeF9JkiRJkqS2RcTuwBGUZD6UkoIfqTGkgVJdX2pOPDR+zq0mIxrjHwY2yMw7OxWbJEmTlSsnJUnN9qw7AEmSJEmSpHZZUrCv3M2sCfwVq9f3As+OMy+Bp6pxl1F2T7inW0FKkjSZuFJfkiRJkiRJkjSpWVKwfzWt3F8jM2+qOx5JkiYjv5BIkiRJkiRJkia7mHiIanIxJan/RN2BSJI0WZnUlyRJkiRJkiRNdpYU7FOZOb2VcRExH7Ao8GBmzuhmTJIkTTZuvy9JkiRJkiRJkroiIhYENqteXpyZj484viTwY2BbykLEx4HDgc9l5jO9jFWSpH5lUl+S9IKI+GI33jczv9KN95UkSZIkSVJ/i4jdgSOBu4FXNq/Cj4gpwBXAusxaQiGBkzPzHb2MVZKkfmVSX5L0goiYQTlp6qjMnKvT7ylJkiRJkqT+FxHHAe8CvpuZnxxx7N3AzyjXo64FLgKmUZL8CWyTmWf3NmJJkvrP3HUHIEnqOzHxEEmSJEmSJKklq1MS9JePcmzXqr0aeH1mPhcR8wCXABsAuwEm9SVJQ8+kviTpBZk5pe4YJEmSJEmS2mVJwb62VNXe1dxZJe+nURL+P8zM5wAy89mIOBTYENiol4FKktSv3H5fkiRJkiRJkjSpWVKwf0XE05QFhutl5nVN/RsDv6P83pbLzPubjr0euBT4V2Yu0NuIJUnqP67UlyRJkiRJkiQNAksK9qd/AQsBU0f0T6vaO5oT+k1zJElSxW2WJUmSJEmSJEmTWmZO6caj7v+uAXFH1U4f0b8jZZX+RaPMaWzZ/0CXYpIkaVLxS4kkSZIkSZIkSeqWcym7KOwXEVtFxIIR8WFgg+r4aaPMWbNq7+lFgJIk9bvI7HiZIUnSAIuINwJvA9YClgReyvjb22VmrtyD0CRJkiRJktRnImJZ4GbKFvyzHAJuAtbIEYmKiLgA2Az4bmZ+qieBSpLUx+auOwBJ0uQQEVOB45lZ72ysRH6OOObdY5IkSZIkSUMqM++NiO0o15WWbTr0J2CXURL6KwNvqF6e25soJUnqbyb1JUkTioh5gLOAtSkJ+2sp259tQ0naHwssBqwLLFf1XQPcWEO4kiRJkiRJ6iOZeUlEvALYBFgGuBe4NDOfG2X4ssBXq+cX9ShESZL6mtvvS5ImFBEfAH5MSdbvlZlHR8RqwA2U7fXnahq7A3AIJcm/W2aeXEfMkiRJkiRJzSwpKEmSJiuT+pKkCUXE2cBbgLMyc5uqb9SkfnVsZeAqyo4w62bm7T0OWZIkSZIkCZizkoIjr3lIkiTVYUrdAUiSJoW1mLnN/otExCwnw5l5B3AQsADw0a5HJ0mSJEmSNIqmkoLTKAn764AzqsMJ/BQ4nVJmMKq+q4GjgWN6HK4kSdKoTOpLklqxeNXe2dT3TNPz+UeZc17VvrkrEUmSJEmSJE1sD2Cd6vmembke8NnGwczcPTO3z8yXATtSar2vCpyemXv2OlhJkqTRmNSXJLXimREtwD+ani8/ypynxjkmSZIkSZLUCztX7dmZefR4AzPz15QV/c8AR0XEq7odnCRJUitM6kuSWnF31S7d6MjM+4F/Vi83GmXOao2hXYxLkiRJkiRpPJYUlCRJk55JfUlSK66p2nVG9F9MqTf30YiYr9EZEYsAn6GcNN/UkwglSZIkSZJezJKCkiRp0jOpL0lqxXmU5P02I/oPrdp1gBsi4psRcQhwA/Ca6tgxvQlRkiRJkiTpRSwpKEmSJj2T+pKkVvyKsgX/yyJi5UZnZp4BHEFJ+K8CfALYF3hZNeQc4Ec9jVSSJEmSJGkmSwpKkqRJz6S+JGlCmfloZq6UmStWteWaj70f+ABwBfAE8DRlpf6nge0yc0bPA5YkSZIkSSosKShJkia9yPRmQ0mSJEmSJEnS4ImIPSi7DF6emZs09W8DnEZJ3t8B/BqYH9iOsgNhAh/JzEN6HbMkSdJIJvUlSZIkSZIkSQMpIhYFrqOsyn9T8w6EEfETYK/qZeNCeVTtb4Bt3IFQkiT1A5P6kqQJRcT5lJPbvTLzrhbnLAccC2Rmbt7N+CRJkiRJkmZHROwNvB9YDZgbuB04BjgoM5+rMzZJkqQGk/qSpAlFxAxKUn+NzGypnlxErEw5Ec7MnKub8UmSJEmSJEmSJA2qKXUHIEmSJEmSJEmSJEmSRmdSX5LULQtU7VO1RiFJkiRJkoZWRJwfEedFxIptzFmuMa+bsUmSJLVq7roDkCQNrK2q9q+1RiFJkiRJkobZdEpJwQUmGNfspU3zJEmSamdSX5L0IhFxxBiHvhYRj04wfT5gZWADysnvRR0MTZIkSZIkSZIkaahEpjcbSpJmFREzmPVu9KjaVj80GuMfBjbIzDs7FZskSZIkSVKrmq5xrJGZN7U4Z03gOuBfmdnOCn9JkqSucKW+JGk0dzNrAn/F6vW9wLPjzEvgqWrcZcCPMvOebgUpSZIkSZLUBZYUlCRJfcWkviTpRTJzpebX1V3tAG9p9a52SZIkSZKkXrOkoCRJGkRuvy9JmlBEXEg5md0jM++qORxJkiRJkqRRWVJQkiQNIpP6kqSOiYj5gEWBBzNzxgTDJUmSJEmSOioi/owlBSVJ0oAxqS9JmlBELAhsVr28ODMfH3F8SeDHwLaU0i6PA4cDn8vMZ3oZqyRJkiRJUkPTyv01LCkoSZImq7nrDkCSNCnsDBwJ3A28svlAREwBzgLWZeYWdQsBHwdWAN7RuzAlSZIkSZJmcTElqf9E3YFIkiTNLpP6kqRWvLVqTx5lW/13AutRTpCvAS4CplGS/DtHxJaZeXbPIpUkSZIkSapk5vRWxllSUJIk9bMpdQcgSZoUVqck7S8f5diuVXs18LrM/CSwMXBl1b9b98OTJEmSJEl6sYhYMCK2rh4LjnJ8yYg4GfgHcA/wSER8KyLm7XmwkiRJYzCpL0lqxVJVe1dzZ0TMQ1mVn8APM/M5gMx8FjiUsh3/Rj2MU5IkSZIkqdnOwOnAD4Enmw80lRR8GzAP5TpGo6TgsT2NUpIkaRwm9SVJrVi8ap8d0b8+8NLq+Vkjjt1Wtct0KyhJkiRJkqQJtFJSEEpJwe9WbVCVFOxNiJIkSeObu+4AJEmTwr8od6pPHdE/rWrvyMz7R5kjSZIkSZJUp1ZLCr4+M5+rdiW8BNiAUlLw7J5EKUmSNA5X6kuSWnFH1U4f0b8j5cT4olHmNLbsf6BLMUmSJEmSJE3EkoKSJGnSM6kvSWrFuZST2f0iYquIWDAiPky5ax3gtFHmrFm19/QiQEmSJEmSpFFYUlCSJE16br8vSWrFQcC+lC34Tx9x7GZGT+pvw9jb20mSJEmSJPWCJQUlSdKk50p9SdKEMvNeYDvgPsqK/cbjT8AumZnN4yNiZeAN1ctzexiqJEmSJElSM0sKSpKkSc+V+pKklmTmJRHxCmATyvZz9wKXNmrOjbAs8NXq+Wgnx5IkSZIkSb1wLrAOpaTgJcAlwJ6UkoKJJQUlSdIkECMWV0qSJEmSJEmSNBAiYllK6cCFRh4CbgLWGGUHwguAzYDvZuanehKoJEnSONx+X5IkSZIkSZI0kCwpKEmSBoEr9SVJkiRJkiRJAy0i5qWFkoIRsSmwefXywMx8qndRSpIkjc6kviRJkiRJkiRJkiRJfcrt9yVJkiRJkiRJkiRJ6lMm9SVJkiRJkiRJkiRJ6lMm9SVJkiRJkiRJkiRJ6lMm9SVJkiRJkiRJkiRJ6lMm9SVJkiRJkiRJkiRJ6lMm9SVJkiRJkiRJkiRJ6lMm9SVJkiRJkiRJkiRJ6lMm9SVJkiRJkiRJkiRJ6lMm9SVJkiRJkiRJkiRJ6lMm9SVJkiRJkiRJkiRJ6lMm9SVJkiRJkiRJkiRJ6lMm9SVJkiRJkiRJkiRJ6lMm9SVJkiRJkiRJkiRJ6lMm9SVJkiRJkiRJkiRJ6lMm9SVJkiRJkiRJkiRJ6lMm9SVJkiRJkiRJkiRJ6lMm9SVJkiRJkiRJkiRJ6lP/H+g7T61lh2L0AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 2400x800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,4),dpi=200)\n",
    "sns.barplot(data=imp_features.sort_values('Importance'), x=imp_features.sort_values('Importance').index, y='Importance')\n",
    "plt.xticks(rotation=90);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f28e1af3",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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