INTERMEDIATE LEVEL Task 1 - Exploratory Data Analysis - Terrorism.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# INTERMEDIATE LEVEL Task 1 - Exploratory Data Analysis - Terrorism"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Author: Laiba Memon"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# LGMVIP September 2021"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# IMPORTING THE REQUIRED LIBRARIES"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "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",
   "metadata": {},
   "source": [
    "# IMPORTING THE DATASET"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "df=pd.read_csv('globalterrorism.csv', encoding = 'latin1')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    .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>eventid</th>\n",
       "      <th>iyear</th>\n",
       "      <th>imonth</th>\n",
       "      <th>iday</th>\n",
       "      <th>approxdate</th>\n",
       "      <th>extended</th>\n",
       "      <th>resolution</th>\n",
       "      <th>country</th>\n",
       "      <th>country_txt</th>\n",
       "      <th>region</th>\n",
       "      <th>...</th>\n",
       "      <th>addnotes</th>\n",
       "      <th>scite1</th>\n",
       "      <th>scite2</th>\n",
       "      <th>scite3</th>\n",
       "      <th>dbsource</th>\n",
       "      <th>INT_LOG</th>\n",
       "      <th>INT_IDEO</th>\n",
       "      <th>INT_MISC</th>\n",
       "      <th>INT_ANY</th>\n",
       "      <th>related</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>197000000001</td>\n",
       "      <td>1970</td>\n",
       "      <td>7</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58</td>\n",
       "      <td>Dominican Republic</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>PGIS</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>197000000002</td>\n",
       "      <td>1970</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>130</td>\n",
       "      <td>Mexico</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>PGIS</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>197001000001</td>\n",
       "      <td>1970</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>160</td>\n",
       "      <td>Philippines</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>PGIS</td>\n",
       "      <td>-9</td>\n",
       "      <td>-9</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>197001000002</td>\n",
       "      <td>1970</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>78</td>\n",
       "      <td>Greece</td>\n",
       "      <td>8</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>PGIS</td>\n",
       "      <td>-9</td>\n",
       "      <td>-9</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>197001000003</td>\n",
       "      <td>1970</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>101</td>\n",
       "      <td>Japan</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>PGIS</td>\n",
       "      <td>-9</td>\n",
       "      <td>-9</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 135 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        eventid  iyear  imonth  iday approxdate  extended resolution  country  \\\n",
       "0  197000000001   1970       7     2        NaN         0        NaN       58   \n",
       "1  197000000002   1970       0     0        NaN         0        NaN      130   \n",
       "2  197001000001   1970       1     0        NaN         0        NaN      160   \n",
       "3  197001000002   1970       1     0        NaN         0        NaN       78   \n",
       "4  197001000003   1970       1     0        NaN         0        NaN      101   \n",
       "\n",
       "          country_txt  region  ... addnotes scite1 scite2  scite3  dbsource  \\\n",
       "0  Dominican Republic       2  ...      NaN    NaN    NaN     NaN      PGIS   \n",
       "1              Mexico       1  ...      NaN    NaN    NaN     NaN      PGIS   \n",
       "2         Philippines       5  ...      NaN    NaN    NaN     NaN      PGIS   \n",
       "3              Greece       8  ...      NaN    NaN    NaN     NaN      PGIS   \n",
       "4               Japan       4  ...      NaN    NaN    NaN     NaN      PGIS   \n",
       "\n",
       "   INT_LOG  INT_IDEO INT_MISC INT_ANY  related  \n",
       "0        0         0        0       0      NaN  \n",
       "1        0         1        1       1      NaN  \n",
       "2       -9        -9        1       1      NaN  \n",
       "3       -9        -9        1       1      NaN  \n",
       "4       -9        -9        1       1      NaN  \n",
       "\n",
       "[5 rows x 135 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# DATA ANALYSIS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(181691, 135)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 181691 entries, 0 to 181690\n",
      "Columns: 135 entries, eventid to related\n",
      "dtypes: float64(55), int64(22), object(58)\n",
      "memory usage: 187.1+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['eventid', 'iyear', 'imonth', 'iday', 'approxdate', 'extended',\n",
       "       'resolution', 'country', 'country_txt', 'region',\n",
       "       ...\n",
       "       'addnotes', 'scite1', 'scite2', 'scite3', 'dbsource', 'INT_LOG',\n",
       "       'INT_IDEO', 'INT_MISC', 'INT_ANY', 'related'],\n",
       "      dtype='object', length=135)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>eventid</th>\n",
       "      <th>iyear</th>\n",
       "      <th>imonth</th>\n",
       "      <th>iday</th>\n",
       "      <th>approxdate</th>\n",
       "      <th>extended</th>\n",
       "      <th>resolution</th>\n",
       "      <th>country</th>\n",
       "      <th>country_txt</th>\n",
       "      <th>region</th>\n",
       "      <th>...</th>\n",
       "      <th>addnotes</th>\n",
       "      <th>scite1</th>\n",
       "      <th>scite2</th>\n",
       "      <th>scite3</th>\n",
       "      <th>dbsource</th>\n",
       "      <th>INT_LOG</th>\n",
       "      <th>INT_IDEO</th>\n",
       "      <th>INT_MISC</th>\n",
       "      <th>INT_ANY</th>\n",
       "      <th>related</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>181686</th>\n",
       "      <td>201712310022</td>\n",
       "      <td>2017</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>182</td>\n",
       "      <td>Somalia</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>\"Somalia: Al-Shabaab Militants Attack Army Che...</td>\n",
       "      <td>\"Highlights: Somalia Daily Media Highlights 2 ...</td>\n",
       "      <td>\"Highlights: Somalia Daily Media Highlights 1 ...</td>\n",
       "      <td>START Primary Collection</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>181687</th>\n",
       "      <td>201712310029</td>\n",
       "      <td>2017</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>200</td>\n",
       "      <td>Syria</td>\n",
       "      <td>10</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>\"Putin's 'victory' in Syria has turned into a ...</td>\n",
       "      <td>\"Two Russian soldiers killed at Hmeymim base i...</td>\n",
       "      <td>\"Two Russian servicemen killed in Syria mortar...</td>\n",
       "      <td>START Primary Collection</td>\n",
       "      <td>-9</td>\n",
       "      <td>-9</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181688</th>\n",
       "      <td>201712310030</td>\n",
       "      <td>2017</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>160</td>\n",
       "      <td>Philippines</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>\"Maguindanao clashes trap tribe members,\" Phil...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>START Primary Collection</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181689</th>\n",
       "      <td>201712310031</td>\n",
       "      <td>2017</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>92</td>\n",
       "      <td>India</td>\n",
       "      <td>6</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>\"Trader escapes grenade attack in Imphal,\" Bus...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>START Primary Collection</td>\n",
       "      <td>-9</td>\n",
       "      <td>-9</td>\n",
       "      <td>0</td>\n",
       "      <td>-9</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181690</th>\n",
       "      <td>201712310032</td>\n",
       "      <td>2017</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>160</td>\n",
       "      <td>Philippines</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>\"Security tightened in Cotabato following IED ...</td>\n",
       "      <td>\"Security tightened in Cotabato City,\" Manila ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>START Primary Collection</td>\n",
       "      <td>-9</td>\n",
       "      <td>-9</td>\n",
       "      <td>0</td>\n",
       "      <td>-9</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 135 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             eventid  iyear  imonth  iday approxdate  extended resolution  \\\n",
       "181686  201712310022   2017      12    31        NaN         0        NaN   \n",
       "181687  201712310029   2017      12    31        NaN         0        NaN   \n",
       "181688  201712310030   2017      12    31        NaN         0        NaN   \n",
       "181689  201712310031   2017      12    31        NaN         0        NaN   \n",
       "181690  201712310032   2017      12    31        NaN         0        NaN   \n",
       "\n",
       "        country  country_txt  region  ... addnotes  \\\n",
       "181686      182      Somalia      11  ...      NaN   \n",
       "181687      200        Syria      10  ...      NaN   \n",
       "181688      160  Philippines       5  ...      NaN   \n",
       "181689       92        India       6  ...      NaN   \n",
       "181690      160  Philippines       5  ...      NaN   \n",
       "\n",
       "                                                   scite1  \\\n",
       "181686  \"Somalia: Al-Shabaab Militants Attack Army Che...   \n",
       "181687  \"Putin's 'victory' in Syria has turned into a ...   \n",
       "181688  \"Maguindanao clashes trap tribe members,\" Phil...   \n",
       "181689  \"Trader escapes grenade attack in Imphal,\" Bus...   \n",
       "181690  \"Security tightened in Cotabato following IED ...   \n",
       "\n",
       "                                                   scite2  \\\n",
       "181686  \"Highlights: Somalia Daily Media Highlights 2 ...   \n",
       "181687  \"Two Russian soldiers killed at Hmeymim base i...   \n",
       "181688                                                NaN   \n",
       "181689                                                NaN   \n",
       "181690  \"Security tightened in Cotabato City,\" Manila ...   \n",
       "\n",
       "                                                   scite3  \\\n",
       "181686  \"Highlights: Somalia Daily Media Highlights 1 ...   \n",
       "181687  \"Two Russian servicemen killed in Syria mortar...   \n",
       "181688                                                NaN   \n",
       "181689                                                NaN   \n",
       "181690                                                NaN   \n",
       "\n",
       "                        dbsource  INT_LOG  INT_IDEO INT_MISC INT_ANY  related  \n",
       "181686  START Primary Collection        0         0        0       0      NaN  \n",
       "181687  START Primary Collection       -9        -9        1       1      NaN  \n",
       "181688  START Primary Collection        0         0        0       0      NaN  \n",
       "181689  START Primary Collection       -9        -9        0      -9      NaN  \n",
       "181690  START Primary Collection       -9        -9        0      -9      NaN  \n",
       "\n",
       "[5 rows x 135 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<bound method DataFrame.value_counts of              eventid  iyear  imonth  iday approxdate  extended resolution  \\\n",
       "0       197000000001   1970       7     2        NaN         0        NaN   \n",
       "1       197000000002   1970       0     0        NaN         0        NaN   \n",
       "2       197001000001   1970       1     0        NaN         0        NaN   \n",
       "3       197001000002   1970       1     0        NaN         0        NaN   \n",
       "4       197001000003   1970       1     0        NaN         0        NaN   \n",
       "...              ...    ...     ...   ...        ...       ...        ...   \n",
       "181686  201712310022   2017      12    31        NaN         0        NaN   \n",
       "181687  201712310029   2017      12    31        NaN         0        NaN   \n",
       "181688  201712310030   2017      12    31        NaN         0        NaN   \n",
       "181689  201712310031   2017      12    31        NaN         0        NaN   \n",
       "181690  201712310032   2017      12    31        NaN         0        NaN   \n",
       "\n",
       "        country         country_txt  region  ... addnotes  \\\n",
       "0            58  Dominican Republic       2  ...      NaN   \n",
       "1           130              Mexico       1  ...      NaN   \n",
       "2           160         Philippines       5  ...      NaN   \n",
       "3            78              Greece       8  ...      NaN   \n",
       "4           101               Japan       4  ...      NaN   \n",
       "...         ...                 ...     ...  ...      ...   \n",
       "181686      182             Somalia      11  ...      NaN   \n",
       "181687      200               Syria      10  ...      NaN   \n",
       "181688      160         Philippines       5  ...      NaN   \n",
       "181689       92               India       6  ...      NaN   \n",
       "181690      160         Philippines       5  ...      NaN   \n",
       "\n",
       "                                                   scite1  \\\n",
       "0                                                     NaN   \n",
       "1                                                     NaN   \n",
       "2                                                     NaN   \n",
       "3                                                     NaN   \n",
       "4                                                     NaN   \n",
       "...                                                   ...   \n",
       "181686  \"Somalia: Al-Shabaab Militants Attack Army Che...   \n",
       "181687  \"Putin's 'victory' in Syria has turned into a ...   \n",
       "181688  \"Maguindanao clashes trap tribe members,\" Phil...   \n",
       "181689  \"Trader escapes grenade attack in Imphal,\" Bus...   \n",
       "181690  \"Security tightened in Cotabato following IED ...   \n",
       "\n",
       "                                                   scite2  \\\n",
       "0                                                     NaN   \n",
       "1                                                     NaN   \n",
       "2                                                     NaN   \n",
       "3                                                     NaN   \n",
       "4                                                     NaN   \n",
       "...                                                   ...   \n",
       "181686  \"Highlights: Somalia Daily Media Highlights 2 ...   \n",
       "181687  \"Two Russian soldiers killed at Hmeymim base i...   \n",
       "181688                                                NaN   \n",
       "181689                                                NaN   \n",
       "181690  \"Security tightened in Cotabato City,\" Manila ...   \n",
       "\n",
       "                                                   scite3  \\\n",
       "0                                                     NaN   \n",
       "1                                                     NaN   \n",
       "2                                                     NaN   \n",
       "3                                                     NaN   \n",
       "4                                                     NaN   \n",
       "...                                                   ...   \n",
       "181686  \"Highlights: Somalia Daily Media Highlights 1 ...   \n",
       "181687  \"Two Russian servicemen killed in Syria mortar...   \n",
       "181688                                                NaN   \n",
       "181689                                                NaN   \n",
       "181690                                                NaN   \n",
       "\n",
       "                        dbsource  INT_LOG  INT_IDEO INT_MISC INT_ANY  related  \n",
       "0                           PGIS        0         0        0       0      NaN  \n",
       "1                           PGIS        0         1        1       1      NaN  \n",
       "2                           PGIS       -9        -9        1       1      NaN  \n",
       "3                           PGIS       -9        -9        1       1      NaN  \n",
       "4                           PGIS       -9        -9        1       1      NaN  \n",
       "...                          ...      ...       ...      ...     ...      ...  \n",
       "181686  START Primary Collection        0         0        0       0      NaN  \n",
       "181687  START Primary Collection       -9        -9        1       1      NaN  \n",
       "181688  START Primary Collection        0         0        0       0      NaN  \n",
       "181689  START Primary Collection       -9        -9        0      -9      NaN  \n",
       "181690  START Primary Collection       -9        -9        0      -9      NaN  \n",
       "\n",
       "[181691 rows x 135 columns]>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.value_counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Countries Wise Number of Terrorism\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Iraq                   24636\n",
       "Pakistan               14368\n",
       "Afghanistan            12731\n",
       "India                  11960\n",
       "Colombia                8306\n",
       "                       ...  \n",
       "Vatican City               1\n",
       "Antigua and Barbuda        1\n",
       "St. Lucia                  1\n",
       "Wallis and Futuna          1\n",
       "Falkland Islands           1\n",
       "Name: country_txt, Length: 205, dtype: int64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"Countries Wise Number of Terrorism\")\n",
    "df['country_txt'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Country with the most terrorism acts is:  Iraq\n"
     ]
    }
   ],
   "source": [
    "print(\"Country with the most terrorism acts is: \", df['natlty1_txt'].value_counts().index[0])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Country with the least terrorism acts is:  Man, Isle of\n"
     ]
    }
   ],
   "source": [
    "print(\"Country with the least terrorism acts is: \", df['natlty1_txt'].value_counts().index[-1])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Most common type of attack is:  Bombing/Explosion\n"
     ]
    }
   ],
   "source": [
    "print(\"Most common type of attack is: \", df['attacktype1_txt'].value_counts().index[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "# Exploratory Data Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Anaconda\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "image/png": 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WLTNN0zQB84svvjBN0zTfeOMNc8SIEaZpmmbr1q3NvXv3mqZpmj///LMZFBSUJd6BAweaCxYsyHVMa9euNTt27Gg7TktLM1u2bGkuXrzY9Pb2NmNiYkzTNM3XX3/dFvf9ILvvMhBn3oZcq2RRJ7ciIiIiIlJ0TNPklVdeYf369ZQoUYKjR49y/PhxAOrWrUvTpk0BiImJ4cknn8Te3h6Azp07Z9ueYRj079+fL774gkGDBrFp0ybmzp0LQIkSJejduzcAzzzzDN27d+f8+fNs3LiRXr162dq4dOlSgcdVokQJIiIicHd3Z+jQoTRv3rzAbUrulFyKiIiIiNzHIiMjOXHiBPHx8ZQqVQpHR0dSUlIAKF++vK1cxoRX/gwaNIjOnTtTtmxZevXqRcmS2acdhmGQnp5O5cqVsVqtBRpHdvbt24eDg8NteR5UbqRnLkVERERE7jMVKlTg3LlzAJw9e5YHHniAUqVKsXbtWg4fPpxtnRYtWvDtt9+SkpLC+fPn+e6777JtD6B27drUrl2bf/3rX4SEhNjOp6en23Z9/fLLL2nRogUVK1akXr16LFiwAMhIYrdt21agMV0d1wsvvMD69es5deqUrd/ry0nhUXIpIiIiInKfqVatGs2bN8fV1RWr1UpcXBw+Pj5ERkbSuHHjbOv4+vrSpUsXPDw86N69Oz4+PlSqVAmAkJAQhg0bhsViITk5GYB+/frx8MMP4+zsbGujfPny7Ny5E29vb9asWcOkSZOAjNnTTz/9FA8PD1xcXGybCm3evJmHHnqIBQsWMHToUFxcXHIck7u7OyVLlsTDw4Pp06czZswYhg8fTsOGDfn000+ZOHEif/75J507d+abb77Rhj63gXEz09v3Ah8fHzMuLq6owxARERGRYmz37t04OTkVdRjFzvnz53FwcODixYsEBATw0Ucf4eXllW3ZkSNH4unpybPPPms75+DgwPnz5+9UuEL232XDMOJN0/Qp7L70zKWIiIiIiOTLkCFD2LVrFykpKQwcODDHxNLb25vy5cvzn//85w5HKEVJyaWIiIiIiOTLl19+ma9y8fHx2Z4vjFnL7du3079//yznypQpwy+//FLgtqVglFyKiIiIiMhdw83N7bbsLCsFpw19REREREREpMCUXIqIiIiIiEiBKbkUERERERGRAlNyKSIiIiKSB/uyNQv1Jz/s7OywWCy4urrSq1cvLl68mG05f3//WxpTYmJivjfoudYff/xBnz59ePTRR3F2dqZDhw7s3buXpKQkevbsCYDVauX777+31Vm2bBlTp069pTgL4uOPP6ZRo0a4uLjw3//+N8dyYWFh1KlTx3a/ly1bdgejvPF+3a2UXIqIiIiIFEP29vZYrVZ27NhB6dKlmT17dpbraWlpAGzcuPGW2r+V5NI0Tbp160ZgYCAHDhxg165d/Pvf/+b48ePUrl2bhQsXAjcmS126dGHixIm3FOetSk1N5dVXX2Xz5s3s2LGDDh065Fp+zJgxWK1WFixYQGhoKOnp6Te0d7viVHIpIiIiIiJ3RMuWLdm/fz/R0dEEBQXx9NNP4+bmBoCDgwMAvXv3zpKghISEsGjRIhITE2nZsiVeXl54eXnZktGJEyeyYcMGLBYL06dPJy0tjfHjx+Pr64u7uzsffvjhDXGsXbuWUqVKMWzYMNs5i8VCy5YtSUxMxNXVlcuXLzNp0iSioqKwWCxERUURERHByJEjbeWv/tjb27Nu3TouXLhAaGgovr6+eHp6snTpUgAiIiLo3r077du3p0GDBrz00ktARmIdEhKCq6srbm5uTJ8+Pdv7lpqayqlTpzAMA0dHx3zdaycnJ0qWLMnJkycJDAzklVdeoVWrVrz77rusXr0aT09P3NzcCA0N5dKlSwA4OjoyYcIE/Pz88PPzY//+/QCcOHGCHj164Ovri6+vLz/99BOQMVM6ZMgQgoODGTBgwA33q0GDBpw4cQKA9PR0HnvsMU6ePJmv+IuSXkUiIiIiIlKMpaam8sMPP9C+fXsAYmNj2bFjB/Xq1ctSrk+fPkRFRdGhQwcuX77M6tWr+eCDDzBNk5UrV1K2bFn27dtH3759iYuLY+rUqYSHh7N8+XIAPvroIypVqsTmzZu5dOkSzZs3Jzg4OEs/O3bswNvbO9d4S5cuzeTJk4mLi+O9994DMpLEq66+RuTbb79l2rRp+Pv78/rrr9O6dWvmzJnDmTNn8PPzo23btrbyW7dupUyZMjRq1IhRo0bx559/cvToUXbs2AHAmTNnsr1v7u7udO3albVr11K1atV83e9ffvmFEiVKUKNGDVvb69atIyUlhQYNGrB69WoaNmzIgAED+OCDD3jxxRcBqFixIrGxscydO5cXX3yR5cuX88ILLzBmzBhatGjBkSNHaNeuHbt37wYy3gUaExODvb09ERERWe7Xnj17iIyM5MUXX2TVqlV4eHhQvXr1fMVflDRzKSIiIiJSDCUnJ2OxWPDx8eGRRx7h2WefBcDPz++GxBLgiSeeYM2aNVy6dIkffviBgIAA7O3tuXLlCs899xxubm706tWLXbt2ZdvfihUrmDt3LhaLhSZNmnDq1Cn27dt3W8a2b98+xo8fT1RUFKVKlWLFihVMnToVi8VCYGAgKSkpHDlyBIA2bdpQqVIlypYti7OzM4cPH6Z+/focPHiQUaNG8eOPP1KxYsUb+nj55Zfp378///jHP+jcuTMXL17k66+/Zvz48dnGNH36dCwWC+PGjSMqKgrDMICMGWGAX3/9lXr16tGwYUMABg4cyPr16231+/bta/vvpk2bAFi1ahUjR47EYrHQpUsX/v77b86dOwdkLBW2t7fPNpbQ0FDmzp0LwJw5cxg0aNDN3eAioplLEREREZFi6Oozl9crX758tuXLli1LYGAg//vf/4iKirIlO9OnT6dmzZps27aN9PR0ypYtm2190zSZNWsW7dq1yzEmFxcX23OVt+rChQs89dRTfPzxx9SuXdvW96JFi2jUqFGWsr/88gtlypSxHdvZ2ZGamkqVKlXYtm0b//vf/3j//ff5+uuvmTNnTpa6//vf/3jhhRdwdHTkzz//pFevXpQvXz7H5HLMmDGMGzfuhvNX77dpmrmO62oyeu3n9PR0Nm3alG0SmdPvEeDhhx+mZs2arFmzhl9++YXIyMhc+y4uNHMpIiIiInKP6NOnD5999hkbNmywJYlnz56lVq1alChRgnnz5tk2AqpQoYJtFg2gXbt2fPDBB1y5cgWAvXv3cuHChSztt27dmkuXLvHxxx/bzm3evJl169ZlKXd929caNGgQgwYNomXLlln6njVrli2B27p1a67jPHnyJOnp6fTo0YM333yTLVu23FDG09PTNvs3duxYzp07x86dO/Nc1puTxo0bk5iYaHuect68ebRq1cp2PSoqyvbfZs2aARAcHGxb6gpk+48FkP39Gjx4MM888wxPPfUUdnZ2txTznabkUkREREQkD8kpxwv153YJDg5m/fr1tG3bltKlSwMwfPhwPv/8c5o2bcrevXttM2bu7u6ULFkSDw8Ppk+fzuDBg3F2dsbLywtXV1eGDh16ww6phmHwzTffsHLlSh599FFcXFwICwuzzUBeFRQUxK5du2wb1Fx1+PBhFi5cyJw5c2yb+sTFxfHaa69x5coV3N3dcXV15bXXXst1nEePHiUwMBCLxUJISAhvvfXWDWVmzJiB1WrFxcUFPz8/2rVrh6+vL2PGjLmle1u2bFk+++wzevXqhZubGyVKlMiysdGlS5do0qQJ7777rm2DoZkzZxIXF4e7uzvOzs437Ph7VXb3q0uXLpw/f/6uWRILYOQ1vXuv8fHxMePi4oo6DBEREREpxnbv3o2Tk1NRhyF3CUdHR+Li4gp10524uDjGjBnDhg0bCtROdt9lwzDiTdP0KVDD2dAzlyIiIiIiIsXI1KlT+eCDD+6aZy2v0rJYERERERGRAkhMTCzUWcuJEydy+PBhWrRoUWht3glKLkVERERERKTAlFyKiIiIiIhIgSm5FBERERERkQJTcikiIiIiIiIFpt1iRURERETy8EBl90Jt788zCXmWOX78OGPGjOHnn3+mSpUqlC5dmpdeeolu3boVaixFbcaMGQwZMoRy5cple71nz55MmzaN+vXr4+joSIUKFQBIS0uje/fuvPbaa5QpU4akpCRGjx7NwoULc+3PwcGB8+fPF/o4roqOjqZ06dL4+/sDMHv2bMqVK8eAAQOyLX/ixAn69+/Pjz/+eNtiulM0cykiIiIiUsyYpknXrl0JCAjg4MGDxMfH89VXX/H777/ftj5TU1NvW9u5mTFjBhcvXsz22s6dO0lLS6N+/fq2c2vXrmX79u3ExsZy8OBBhgwZAkDt2rXzTCzvhOjoaDZu3Gg7HjZsWI6JJUCNGjWoVasWP/30050I77ZScikiIiIiUsysWbOG0qVLM2zYMNu5unXrMmrUKABSUlIYNGgQbm5ueHp6snbtWgCaNGnCzp07bXUCAwOJj4/nwoULhIaG4uvri6enJ0uXLgUgIiKCXr160blzZ4KDg4mIiKB79+60b9+eBg0a8NJLL9nacnBwYMKECXh7e9O2bVtiY2MJDAykfv36LFu2DMiYTRw/fjy+vr64u7vz4YcfAhkJV2BgID179qRx48b069cP0zSZOXMmSUlJBAUFERQUdMN9iIyM5Mknn8z2Hjk4ODB79myWLFnC6dOnSUxMxNXV1TauJ598kvbt29OoUSPeeOONG+qbpsn48eNxdXXFzc2NqKgoW6ytWrXiqaeeomHDhkycOJHIyEj8/Pxwc3PjwIEDAHz77bc0adIET09P2rZty/Hjx0lMTGT27NlMnz4di8XChg0bCAsLIzw8HID9+/fTtm1bPDw88PLysrXVtWvXu+6dltlRcikiIiIiUszs3LkTLy+vHK+///77AGzfvp358+czcOBAUlJS6NOnD19//TUAx44dIykpCW9vb6ZMmULr1q3ZvHkza9euZfz48Vy4cAGATZs28fnnn7NmzRoArFYrUVFRbN++naioKH777TcALly4YEtWK1SowD//+U9WrlzJN998w6RJkwD49NNPqVSpEps3b2bz5s18/PHHHDp0CICtW7cyY8YMdu3axcGDB/npp58YPXo0tWvXZu3atbYE+Vo//fQT3t7eOd6HihUrUq9ePfbt23fDtdjYWCIjI7FarSxYsIC4uLgs1xcvXozVamXbtm2sWrWK8ePHc+zYMQC2bdvGu+++y/bt25k3bx579+4lNjaWwYMHM2vWLABatGjBzz//zNatW+nTpw/Tpk3D0dGRYcOGMWbMGKxWKy1btszSZ79+/RgxYgTbtm1j48aN1KpVCwAfHx82bNiQ4zjvFkouRURERESKuREjRuDh4YGvry8AMTEx9O/fH4DGjRtTt25d9u7dy1NPPcWCBQsA+Prrr+nVqxcAK1asYOrUqVgsFgIDA0lJSeHIkSMAPP7441StWtXWV5s2bahUqRJly5bF2dmZw4cPA1C6dGnat28PgJubG61ataJUqVK4ubmRmJho62fu3LlYLBaaNGnCqVOnbImfn58fDz30ECVKlMBisdjq5ObYsWPUqFEj1zKmaWZ7/vHHH6datWrY29vTvXt3YmJislyPiYmhb9++2NnZUbNmTVq1asXmzZsB8PX1pVatWpQpU4ZHH32U4OBg27ivxv3777/Trl073NzceOedd7LMGGfn3LlzHD161PbMbNmyZW3PmT7wwAMkJSXlfjPuAkouRURERESKGRcXF7Zs2WI7fv/991m9ejUnTpwAck6o6tSpQ7Vq1UhISCAqKoo+ffrYyi9atAir1YrVauXIkSM4OTkBUL58+SxtlClTxvbZzs7O9ixmqVKlMAwDgBIlStjKlShRwlbGNE1mzZpl6+fQoUO2xCyndnNjb29PSkpKjtfPnTtHYmIiDRs2vOHa1VhzOs7pHl4fa05jHTVqFCNHjmT79u18+OGHucaZV38pKSnY29vnWv9uoORSRERERKSYad26NSkpKXzwwQe2c9duehMQEGB7Rm/v3r0cOXKERo0aAdiWaJ49exY3NzcA2rVrx6xZs2wJztatW29L3O3ateODDz7gypUrttiuLr/NSYUKFTh37ly215ycnNi/f3+2186fP8/w4cPp2rUrVapUueH6ypUrOX36NMnJySxZsoTmzZtnuR4QEEBUVBRpaWmcOHGC9evX4+fnl59hAnD27Fnq1KkDwOeff57neCpWrMhDDz3EkiVLALh06ZLtd7p3717b86J3M72KREREREQkD/l5dUhhMgyDJUuWMGbMGKZNm0aNGjUoX748b7/9NgDDhw9n2LBhuLm5UbJkSSIiImyzaz179uSFF17gtddes7X32muv8eKLL+Lu7o5pmjg6OrJ8+fJCj3vw4MEkJibi5eWFaZrUqFHDlkzlZMiQITzxxBPUqlXrhucuO3bsSHR0NG3btrWdCwoKwjRN0tPT6datW5ZxXqtFixb079+f/fv38/TTT+Pj45Plerdu3di0aRMeHh4YhsG0adN48MEH2bNnT77GGhYWRq9evahTpw5Nmza1PVvauXNnevbsydKlS23PZ141b948hg4dyqRJkyhVqhQLFiygfv36rF27lo4dO+ar3+LMyG169l7k4+NjXv8wr4iIiIjItXbv3m1bNipFJzk5maCgIH766Sfs7OzyXS8iIoK4uDjee++92xhd4QkICGDp0qXZzsAWVHbfZcMw4k3T9Mmhyi3TslgRERERESmW7O3teeONNzh69GhRh3LbnDhxgrFjx96WxPJO08yliIiIiMh1NHMp94o7OXOpZy5F7lP2ZWtmOU5OOV5EkYiIiIjIvUDLYkVERERERKTAlFyKiIiIiIhIgSm5FBERERERkQK7bc9cGobxMDAXeBBIBz4yTfNdwzCqAlGAI5AIPGWa5l+ZdV4GngXSgNGmaf4v87w3EAHYA98DL5imaRqGUSazD2/gFNDbNM3E2zUmEREREbk/NazxeKG2t/fEyjzLODg4cP78+ULtNz+io6MJDw9n+fLlLFu2jF27djFx4sRsy1qtVpKSkujQoUO+2z958iS9evXi1KlTlC1bljVr1uDg4JBtWcMweOaZZ5g3bx4Aqamp1KpViyZNmtzUezoDAwMJDw/Hx8eHDh068OWXX1K5cuV815f8uZ0zl6nAP0zTdAKaAiMMw3AGJgKrTdNsAKzOPCbzWh/ABWgP/NcwjKsvs/kAGAI0yPxpn3n+WeAv0zQfA6YDb9/G8YiIiIiI3FXS0tIKVL9Lly45JpaQkVx+//33N9XmBx98QEBAAAkJCSxZsoTSpUvnWLZ8+fLs2LGD5ORkAFauXEmdOnVuqr/rff/990osb5PbllyapnnMNM0tmZ/PAbuBOsCTwOeZxT4HumZ+fhL4yjTNS6ZpHgL2A36GYdQCKpqmucnMeG/K3OvqXG1rIdDGMAzjdo1JREREROROMk2T8ePH4+rqipubG1FRUUDG7GKnTp1s5UaOHElERAQAjo6OTJ48mRYtWrBgwQIcHR15/fXX8fLyws3NjT179gAQGxuLv78/np6e+Pv78+uvv97Qf0REBCNHjgRgwYIFuLq64uHhQUBAAJcvX2bSpElERUVhsViIiopi3bp1WCwWLBYLnp6enDt37oY2S5cuze+//w5A7dq1c00uAZ544gm+++47AObPn0/fvn1t1y5cuEBoaCi+vr54enqydOlSAJKTk+nTpw/u7u707t3blpxevT8nT54EoGvXrnh7e+Pi4sJHH32UaxyStzvyKhLDMBwBT+AXoKZpmscgIwE1DOOBzGJ1gJ+vqfZ75rkrmZ+vP3+1zm+ZbaUahnEWqAacvK7/IWTMfPLII48U2rhERERERG6nxYsXY7Va2bZtGydPnsTX15eAgIA865UtW5aYmBgAJk6cSPXq1dmyZQv//e9/CQ8P55NPPqFx48asX7+ekiVLsmrVKl555RUWLVqUY5uTJ0/mf//7H3Xq1OHMmTOULl2ayZMnExcXx3vvvQdA586def/992nevDnnz5+nbNmyN7Tz6KOP8tZbb+Hr68uwYcPyHEufPn2YPHkynTp1IiEhgdDQUDZs2ADAlClTaN26NXPmzOHMmTP4+fnRtm1bPvzwQ8qVK0dCQgIJCQl4eXll2/acOXOoWrUqycnJ+Pr60qNHD6pVq5ZnTJK9276hj2EYDsAi4EXTNP/OrWg258xczudWJ+sJ0/zINE0f0zR9atSokVfIIiIiIiLFQkxMDH379sXOzo6aNWvSqlUrNm/enGe93r17Zznu3r07AN7e3iQmJgJw9uxZevXqhaurK2PGjGHnzp25ttm8eXNCQkL4+OOPc1xu27x5c8aOHcvMmTM5c+YMJUtmncs6evQoU6ZM4ddff+WTTz6xJbPu7u78/Xf2qYK7uzuJiYnMnz//hmc7V6xYwdSpU7FYLAQGBpKSksKRI0dYv349zzzzjK2+u7t7tm3PnDkTDw8PmjZtym+//ca+fftyvQeSu9s6c2kYRikyEstI0zQXZ54+bhhGrcxZy1rAn5nnfwcevqb6Q0BS5vmHsjl/bZ3fDcMoCVQCTt+WwYiIiIiI3GEZT4XdqGTJkqSnp9uOU1JSslwvX758luMyZcoAYGdnR2pqKgCvvfYaQUFBfPPNNyQmJhIYGJhrLLNnz+aXX37hu+++w2KxYLVabygzceJEOnbsyPfff0/Tpk1ZtWoVjRs3tl3/6aef8PDwoGbNmnz33Xe0adOG48eP4+joSMWKFXPsu0uXLowbN47o6GhOnTplO2+aJosWLaJRo0Y31Mnrabno6GhWrVrFpk2bKFeunC05lVt322YuM599/BTYbZrm/11zaRkwMPPzQGDpNef7GIZRxjCMemRs3BObuYT2nGEYTTPbHHBdnatt9QTWmDn9CRQRERERucsEBAQQFRVFWloaJ06cYP369fj5+VG3bl127drFpUuXOHv2LKtXr77pts+ePWvbHOfq85q5OXDgAE2aNGHy5MlUr16d3377jQoVKmR5rvLAgQO4ubkxYcIEfHx8bM93XuXu7s7atWtJSkqiZs2aTJ8+nREjRvD000/n2ndoaCiTJk3Czc0ty/l27doxa9YsWxK+detWIOO+RUZGArBjxw4SEhKyHX+VKlUoV64ce/bs4eeff76hjNyc2zlz2RzoD2w3DMOaee4VYCrwtWEYzwJHgF4ApmnuNAzja2AXGTvNjjBN8+p8+/P8/1eR/JD5AxnJ6zzDMPaTMWPZ5zaOR0RERETuU/l5dUhhSk1NpUyZMnTr1o1Nmzbh4eGBYRhMmzaNBx98EICnnnoKd3d3GjRogKen50338dJLLzFw4ED+7//+j9atW+dZfvz48ezbtw/TNGnTpg0eHh488sgjtmWpL7/8MjExMaxduxY7OzucnZ154oknsrTRuHFjpkyZQrt27ShVqhQ1a9bkq6++YuLEiXh5edGwYcNs+37ooYd44YUXbjj/2muv8eKLL+Lu7o5pmjg6OrJ8+XKef/55Bg0ahLu7OxaLBT8/vxvqtm/fntmzZ+Pu7k6jRo1o2rRpPu+c5MS43yb6fHx8zLi4uKIOQ6TI2ZetmeU4OeV4EUUiIiJS/OzevRsnJ6ci63/btm0899xzxMbGFlkMcm/I7rtsGEa8aZo+hd3Xbd/QR0RERERE8m/27Nn07duXf/3rX0UdishNuSOvIhERERERkfwZNmxYvl7RIVLcaOZSRERERERECkzJpYiIiIiIiBSYkksREREREREpMCWXIiIiIiIiUmDa0EdEREREJA9NavQu1PZ+ORGVZxk7Ozvc3NxITU3FycmJzz//nHLlymVbNiIigri4ON577z1mz55NuXLlGDBgQKHGLJIXzVyKiIiIiBRD9vb2WK1WduzYQenSpZk9e3a+6g0bNkyJpRQJJZciIiIiIsVcy5Yt2b9/P6dPn6Zr1664u7vTtGlTEhISbigbFhZGeHg4APv376dt27Z4eHjg5eXFgQMHAHjnnXfw9fXF3d2d119//Y6ORe5dSi5FRERERIqx1NRUfvjhB9zc3Hj99dfx9PQkISGBf//733nOUPbr148RI0awbds2Nm7cSK1atVixYgX79u0jNjYWq9VKfHw869evv0OjkXuZnrkUERERESmGkpOTsVgsQMbM5bPPPkuTJk1YtGgRAK1bt+bUqVOcPXs22/rnzp3j6NGjdOvWDYCyZcsCsGLFClasWIGnpycA58+fZ9++fQQEBNzmEcm9TsmliIiIiEgxdPWZy2uZpnlDOcMwsq2fXdmr519++WWGDh1a4BhFrqVlsSIiIiIid4mAgAAiIyMBiI6Opnr16lSsWDHbshUrVuShhx5iyZIlAFy6dImLFy/Srl075syZw/nz5wE4evQof/755x2JX+5tmrkUEREREclDfl4dcieEhYUxaNAg3N3dKVeuHJ9//nmu5efNm8fQoUOZNGkSpUqVYsGCBQQHB7N7926aNWsGgIODA1988QUPPPDAnRiC3MOMnKbL71U+Pj5mXFxcUYchUuTsy9bMcpyccryIIhERESl+du/ejZOTU1GHIVJg2X2XDcOIN03Tp7D70rJYERERERERKTAllyIiIiIiIlJgSi5FRERERESkwJRcioiIiIiISIEpuRQREREREZECU3IpIiIiIiIiBab3XIqIiIiI5CH4wYGF2t6KP3J/PyVAYmIinTp1YseOHbZzYWFhODg4UL16dYKDg6lduzYAgwcPZuzYsTg7O+Po6EhcXBzVq1fH39+fjRs3kpiYyMaNG3n66acBiIuLY+7cucycObNQxyX3N81cioiIiIjcZSIiIkhKSrIdf/LJJzg7O99QbuPGjUBGovrll1/azvv4+CixlEKn5FJERERE5C4TFxdHv379sFgsJCcnExgYSFxc3A3lHBwcAJg4cSIbNmzAYrEwffp0oqOj6dSpEwAXLlwgNDQUX19fPD09Wbp0KQA7d+7Ez88Pi8WCu7s7+/btu3MDlLuSkksRERERkbuMj48PkZGRWK1W7O3t8yw/depUWrZsidVqZcyYMVmuTZkyhdatW7N582bWrl3L+PHjuXDhArNnz+aFF17AarUSFxfHQw89dLuGI/cIPXMpIiIiIlIMGYZxU+dv1YoVK1i2bBnh4eEApKSkcOTIEZo1a8aUKVP4/fff6d69Ow0aNCjUfuXeo+RSRERERKQYqlatGn/99VeWc6dPn6ZevXqF2o9pmixatIhGjRplOe/k5ESTJk347rvvaNeuHZ988gmtW7cu1L7l3qJlsSIiIiIixZCDgwO1atVi9erVQEZi+eOPP9KiRQsqVKjAuXPn8t1WbuXbtWvHrFmzME0TgK1btwJw8OBB6tevz+jRo+nSpQsJCQkFHJHc6zRzKSIiIiKSh/y8OuR2mDt3LiNGjOAf//gHAK+//jqPPvooISEhDBs2DHt7ezZt2pRnO+7u7pQsWRIPDw9CQkLw9PS0XXvttdd48cUXcXd3xzRNHB0dWb58OVFRUXzxxReUKlWKBx98kEmTJt22ccq9wbj6LxT3Cx8fHzO7nbRE7jf2ZWtmOU5OOV5EkYiIiBQ/u3fvxsnJqajDECmw7L7LhmHEm6bpU9h9aVmsiIiIiIiIFJiSSxERERERESkwJZciIiIiIiJSYEouRUREREREpMCUXIqIiIiIiEiBKbkUERERERGRAtN7LkVERERE8tDrkWcLtb0FRz7Ns4xhGDzzzDPMmzcPgNTUVGrVqkWTJk1Yvnw5y5YtY9euXUycOJGwsDAcHBwYN24ckyZNIiAggLZt2zJjxgyGDBlCuXLlCjV+kewouRQRERERKYbKly/Pjh07SE5Oxt7enpUrV1KnTh3b9S5dutClS5cb6k2ePNn2ecaMGTzzzDM3lVympaVhZ2dXsODlvqRlsSIiIiIixdQTTzzBd999B8D8+fPp27ev7VpERAQjR468oU5ISAgLFy5k5syZJCUlERQURFBQEADPP/88Pj4+uLi48Prrr9vqODo6MnnyZFq0aMHUqVPx8vKyXdu3bx/e3t63a4hyD1FyKSIiIiJSTPXp04evvvqKlJQUEhISaNKkSb7rjh49mtq1a7N27VrWrl0LwJQpU4iLiyMhIYF169aRkJBgK1+2bFliYmJ49dVXqVSpElarFYDPPvuMkJCQwhyW3KOUXIqIiIiIFFPu7u4kJiYyf/58OnToUOD2vv76a7y8vPD09GTnzp3s2rXLdq137962z4MHD+azzz4jLS2NqKgonn766QL3Lfc+JZciIiIiIsVYly5dGDduXJYlsbfi0KFDhIeHs3r1ahISEujYsSMpKSm26+XLl7d97tGjBz/88APLly/H29ubatWqFahvuT8ouRQRERERKcZCQ0OZNGkSbm5uN123QoUKnDt3DoC///6b8uXLU6lSJY4fP84PP/yQY72yZcvSrl07nn/+eQYNGnTLscv9RbvFioiIiIjkIT+vDrldHnroIV544YVbqjtkyBCeeOIJatWqxdq1a/H09MTFxYX69evTvHnzXOv269ePxYsXExwcfEt9y/3HME2zqGO4o3x8fMy4uLiiDkOkyNmXrZnlODnleBFFIiIiUvzs3r0bJyenog6jSIWHh3P27FnefPPNog5FCiC777JhGPGmafoUdl+auRQRERERkSy6devGgQMHWLNmTVGHIncRJZciIiIiIpLFN998U9QhyF1IG/qIiIiIiIhIgSm5FBERERERkQJTcikiIiIiIiIFpuRSRERERERECkwb+oiIiIiI5OHZRwcXanufHvikUNsTKQ40cykiIiIiUgwdP36cp59+mvr16+Pt7U2zZs3uyV1cZ8yYwcWLF3O83rNnTw4ePAjA+fPnef7553n00Ufx9PTE29ubjz/++E6FeoPo6Gg6deoEwPLly3n99deLLJbiQMmliIiIiEgxY5omXbt2JSAggIMHDxIfH89XX33F77//ftv6TE1NvW1t5ya35HLnzp2kpaVRv359AAYPHkyVKlXYt28fW7du5ccff+T06dO3Nb783peOHTuybNmyXBPle52SSxERERGRYmbNmjWULl2aYcOG2c7VrVuXUaNGAZCSksKgQYNwc3PD09OTtWvXAtCkSRN27txpqxMYGEh8fDwXLlwgNDQUX19fPD09Wbp0KQARERH06tWLzp07ExwcTEREBN27d6d9+/Y0aNCAl156ydaWg4MDEyZMwNvbm7Zt2xIbG0tgYCD169dn2bJlAKSlpTF+/Hh8fX1xd3fnww8/BDJm+AIDA+nZsyeNGzemX79+mKbJzJkzSUpKIigoiKCgoBvuQ2RkJE8++SQABw4cIDY2ln/961+UKJGRxtSoUYMJEybYyr/zzju2vq/OIiYmJuLk5MRzzz2Hi4sLwcHBJCcn29ps37493t7etGzZkj179gAQEhLC2LFjCQoKYsKECcTGxuLv74+npyf+/v78+uuvN8RqGAaBgYEsX748/7/oe4ySSxERERGRYmbnzp14eXnleP39998HYPv27cyfP5+BAweSkpJCnz59+PrrrwE4duwYSUlJeHt7M2XKFFq3bs3mzZtZu3Yt48eP58KFCwBs2rSJzz//nDVr1gBgtVqJiopi+/btREVF8dtvvwFw4cIFW7JaoUIF/vnPf7Jy5Uq++eYbJk2aBMCnn35KpUqV2Lx5M5s3b+bjjz/m0KFDAGzdupUZM2awa9cuDh48yE8//cTo0aOpXbs2a9eutSXI1/rpp5/w9va23RMPDw9bYnm9FStWsG/fPmJjY7FarcTHx7N+/XoA9u3bx4gRI9i5cyeVK1dm0aJFAAwZMoRZs2YRHx9PeHg4w4cPt7W3d+9eVq1axX/+8x8aN27M+vXr2bp1K5MnT+aVV17JNgYfHx82bNiQ4+/tXqcNfUREREREirkRI0YQExND6dKl2bx5MzExMbZZzMaNG1O3bl327t3LU089xeOPP84bb7zB119/Ta9evYCMxGvZsmWEh4cDGTOfR44cAeDxxx+natWqtr7atGlDpUqVAHB2dubw4cM8/PDDlC5dmvbt2wPg5uZGmTJlKFWqFG5ubiQmJtr6SUhIYOHChQCcPXuWffv2Ubp0afz8/HjooYcAsFgsJCYm0qJFi1zHfezYMWrUqJHttSlTprBgwQL+/PNPkpKSWLFiBStWrMDT0xPIeD5z3759PPLII9SrVw+LxQKAt7c3iYmJnD9/no0bN9ruEcClS5dsn3v16oWdnZ1tHAMHDmTfvn0YhsGVK1eyjemBBx4gKSkp1zHdy5RcioiIiIgUMy4uLrbZNciYqTx58iQ+Pj5AxjOZ2alTpw7VqlUjISGBqKgo27JU0zRZtGgRjRo1ylL+l19+oXz58lnOlSlTxvbZzs7O9sxhqVKlMAwDgBIlStjKlShRwlbGNE1mzZpFu3btsrQZHR2dY7u5sbe3JyUlBchIdLdt20Z6ejolSpTg1Vdf5dVXX8XBwcHW98svv8zQoUOztJGYmHhD38nJyaSnp1O5cmWsVmu2fV97X1577TWCgoL45ptvSExMJDAwMNs6KSkp2Nvb5zmue5WSSxERERGRPNzpV4e0bt2aV155hQ8++IDnn38eIMtGMQEBAURGRtK6dWv27t3LkSNHbIljnz59mDZtGmfPnsXNzQ2Adu3aMWvWLGbNmoVhGGzdutU2w1eY2rVrxwcffEDr1q0pVaoUe/fupU6dOrnWqVChAufOnaN69eo3XHNycmL//v04Ojry2GOP4ePjwz//+U/efPNN7OzsSElJsSXa7dq147XXXqNfv344ODhw9OhRSpUqlWO/FStWpF69eixYsIBevXphmiYJCQl4eHjcUPbs2bO2cUREROTY5t69e3F1dc11vPcyPXMpIiIiIlLMGIbBkiVLWLduHfXq1cPPz4+BAwfy9ttvAzB8+HDS0tJwc3Ojd+/eRERE2GbnevbsyVdffcVTTz1la++1117jypUruLu74+rqymuvvXZb4h48eDDOzs54eXnh6urK0KFD85yhHDJkCE888US2G/p07NiR6Oho2/Enn3zCqVOneOyxx2wbC129J8HBwTz99NM0a9YMNzc3evbsyblz53LtOzIykk8//RQPDw9cXFxsGx1d76WXXuLll1+mefPmpKWl5dje2rVr6dixY6593suMnKbU71U+Pj5mXFxcUYchUuTsy9bMcpyccryIIhERESl+du/ejZOTU1GHcd9LTk4mKCiIn376yfb8Y3F19b2kq1evLupQssjuu2wYRrxpmj6F3ZdmLkVEREREpFiyt7fnjTfe4OjRo0UdSp6OHDnCf/7zn6IOo0jpmUsRERERESm2rt8cqLjy9fUt6hCKnGYuRUREREREpMCUXIqIiIiIiEiBKbkUERERERGRAtMzlyIiIiIieRjnMqRQ2wvf+VG+yn3zzTd0796d3bt307hxYwCSkpIYPXo0CxcuLNSYrpoxYwZDhgyhXLly+a7z8ccfEx4eTsmSJRkxYgTDhw/PtbyHhwfOzs7Mnz/fdm7SpEkEBATQtm3bW449J+PHj+f777+nQ4cOuLi4EBwcTO3atQu9n/udkksRERERkWJq/vz5tGjRgq+++oqwsDAAateunW1imZqaSsmSBfvrfVpaGjNmzOCZZ57Jd3KZmprKq6++yv79+6lQoQKHDx/Otfzu3btJT09n/fr1XLhwgfLlywMwefLkHGPK6zUkeY39ww8/5MSJE5QpU4bAwEBcXV2VXN4GWhYrIiIiIlIMnT9/np9++olPP/2Ur776ynY+MTERV1dXACIiIujVqxedO3cmODiY6OhoAgIC6NatG87OzgwbNoz09HQgI1F1c3PD1dWVCRMm2NpzcHBg0qRJNGnShClTppCUlERQUBBBQUGkpaUREhKCq6srbm5uTJ8+PdtYU1NTOXXqFIZh4OjomOu4vvzyS/r3709wcDDLli2znQ8JCbElzY6OjkyePJkWLVqwYMECfvzxR7y8vPDw8KBNmzYAhIWFMWTIEIKDgxkwYACJiYm0bNkSLy8vvLy82LhxIwBdunThwoULNGnShKioKOLi4ujXrx8Wi4Xk5OSb/K1IbjRzKSIiIiJSDC1ZsoT27dvTsGFDqlatypYtW/Dy8rqh3KZNm0hISKBq1apER0cTGxvLrl27qFu3Lu3bt2fx4sX4+/szYcIE4uPjqVKlCsHBwSxZsoSuXbty4cIFXF1dbTOHc+bMYe3atVSvXp34+HiOHj3Kjh07ADhz5swN/aempuLu7k7Xrl1Zu3YtVatWzXVcUVFRrFy5kl9//ZX33nuPvn37ZluubNmyxMTEcOLECby8vFi/fj316tXj9OnTtjLx8fHExMRgb2/PxYsXWblyJWXLlmXfvn307duXuLg4li1bhoODA1arFYAPPviA8PBwfHx88vNrkJugmUsRERERkWJo/vz59OnTB4A+ffpkeT7xWo8//niWhM7Pz4/69etjZ2dH3759iYmJYfPmzQQGBlKjRg1KlixJv379WL9+PQB2dnb06NEj27br16/PwYMHGTVqFD/++CMVK1a8oczLL79M//79+cc//kHnzp25ePEiX3/9NePHj7+h7ObNm6lRowZ169alTZs2bNmyhb/++ivbvnv37g3Azz//TEBAAPXq1QPIMtYuXbpgb28PwJUrV3juuedwc3OjV69e7Nq1K9t25fbRzKWIiIiISDFz6tQp1qxZw44dOzAMg7S0NAzDYNq0aTeUvfrM4lWGYdxwbJpmjn2VLVs2x2caq1SpwrZt2/jf//7H+++/z9dff82cOXOylPnf//7HCy+8gKOjI3/++Se9evWifPny2SaX8+fPZ8+ePbals3///TeLFi1i8ODBOY7LNM0bxnR9GYDp06dTs2ZNtm3bRnp6OmXLls1xzHJ7aOZSRERERKSYWbhwIQMGDODw4cMkJiby22+/Ua9ePWJiYvKsGxsby6FDh0hPTycqKooWLVrQpEkT1q1bx8mTJ0lLS2P+/Pm0atUq2/oVKlTg3LlzAJw8eZL09HR69OjBm2++yZYtW24o7+npydy5cwEYO3Ys586dY+fOnXh7e2cpl56ezoIFC0hISCAxMZHExESWLl2a44zsVc2aNWPdunUcOnQIIMuy2GudPXuWWrVqUaJECebNm0daWlqe45PCpZlLEREREZE85PfVIYVl/vz5TJw4Mcu5Hj168OWXX2bZjCc7zZo1Y+LEiWzfvt22uU+JEiV46623CAoKwjRNOnTowJNPPplt/SFDhvDEE09Qq1YtZsyYwaBBg2ybAr311ls3lJ8xYwZDhw7FxcUFe3t7unXrxr59+xgzZgzvvvuurdz69eupU6cOderUsZ0LCAhg165dHDt2LMfx1KhRg48++oju3buTnp7OAw88wMqVK28oN3z4cHr06MGCBQsICgq6YUb3qpCQEIYNG4a9vT2bNm2yLauVgjNymyK/F/n4+JhxcXFFHYZIkbMvWzPLcXLK8SKKREREpPjZvXs3Tk5ORR3GTYuOjiY8PJzly5cXdShSTGT3XTYMI940zULf0UjLYkVERERERKTAtCxWREREROQeERgYSGBgYFGHIfcpzVyKiIiIiIhIgSm5FBERERERkQJTcikiIiIiIiIFpuRSRERERERECkwb+oiIiIiI5OFf3kMKtb1/xuf93kw7Ozvc3NwwTRM7Ozvee+89/P39b7qv2bNnU65cOQYMGHAroYrkm5JLEREREZFiyN7eHqvVCsD//vc/Xn75ZdatW3fT7QwbNqyQIxPJnpbFioiIiIgUc3///TdVqlQBIDo6mk6dOtmujRw5koiICAAmTpyIs7Mz7u7ujBs3DoCwsDDCw8OBjFeVTJgwAT8/Pxo2bMiGDRsASEtLY/z48fj6+uLu7s6HH34IwLFjxwgICMBiseDq6sqGDRtIS0sjJCQEV1dX3NzcmD59+p26DVLMaeZSRERERKQYSk5OxmKxkJKSwrFjx1izZk2u5U+fPs0333zDnj17MAyDM2fOZFsuNTWV2NhYvv/+e9544w1WrVrFp59+SqVKldi8eTOXLl2iefPmBAcHs3jxYtq1a8err75KWloaFy9exGq1cvToUXbs2AGQYz9y/1FyKSIiIiJSDF27LHbTpk0MGDDAltBlp2LFipQtW5bBgwfTsWPHLLOb1+revTsA3t7eJCYmArBixQoSEhJYuHAhAGfPnmXfvn34+voSGhrKlStX6Nq1KxaLhfr163Pw4EFGjRpFx44dCQ4OLrxBy11Ny2JFRERERIq5Zs2acfLkSU6cOEHJkiVJT0+3XUtJSQGgZMmSxMbG0qNHD5YsWUL79u2zbatMmTJAxoZBqampAJimyaxZs7BarVitVg4dOkRwcDABAQGsX7+eOnXq0L9/f+bOnUuVKlXYtm0bgYGBvP/++wwePPg2j17uFpq5FBEREREp5vbs2UNaWhrVqlWjbt267Nq1i0uXLpGSksLq1atp0aIF58+f5+LFi3To0IGmTZvy2GOP5bv9du3a8cEHH9C6dWtKlSrF3r17qVOnDidPnqROnTo899xzXLhwgS1bttChQwdKly5Njx49ePTRRwkJCbl9A5e7ipJLEREREZE85OfVIYXt6jOXkDGz+Pnnn2NnZ8fDDz/MU089hbu7Ow0aNMDT0xOAc+fO8eSTT5KSkoJpmje10c7gwYNJTEzEy8sL0zSpUaMGS5YsITo6mnfeeYdSpUrh4ODA3LlzOXr0KIMGDbLNnr711luFPna5OxmmaRZ1DHeUj4+PGRcXV9RhiBQ5+7I1sxwnpxwvokhERESKn927d+Pk5FTUYYgUWHbfZcMw4k3T9CnsvvTMpYiIiIiIiBSYkksREREREREpMCWXIiIiIiIiUmBKLkVERERERKTAlFyKiIiIiIhIgSm5FBERERERkQLTey5FRERERPLwXvPBhdreyJ8+ybOMnZ0dbm5utuM+ffowceLELGWio6MJDw9n+fLlhRZbdHQ0pUuXxt/fH4DZs2dTrlw5BgwYUGh9JCYm0qlTJ3bs2JGv8/kRERFBcHAwtWvXBjLe3Tl27FicnZ3597//zSuvvFKgNiRvSi5FRERERIohe3t7rFbrHe83OjoaBwcHW3I5bNiwOx7DrYiIiMDV1dWWGH7yyf9P4G8mucypDcmblsWKiIiIiNxFfvzxRxo3bkyLFi1YvHix7XxYWBjh4eG2Y1dXVxITEwGYO3cu7u7ueHh40L9/fwC+/fZbmjRpgqenJ23btuX48eMkJiYye/Zspk+fjsViYcOGDVnatVqtNG3aFHd3d7p168Zff/0FQGBgIBMmTMDPz4+GDRuyYcMGIGMmsmXLlnh5eeHl5cXGjRvzPc6IiAi6d+9O+/btadCgAS+99BIAaWlphISE4OrqipubG9OnT2fhwoXExcXRr18/LBYLycnJBAYGEhcXx8SJE0lOTsZisdCvXz8SExNxdXW19RMeHk5YWFiubQDMnz8fNzc3XF1dmTBhgq2+g4MDr776Kh4eHjRt2pTjx4/ne4z3GiWXIiIiIiLF0NWE6OpPVFQUKSkpPPfcc3z77bds2LCBP/74I892du7cyZQpU1izZg3btm3j3XffBaBFixb8/PPPbN26lT59+jBt2jQcHR0ZNmwYY8aMwWq10rJlyyxtDRgwgLfffpuEhATc3Nx44403bNdSU1OJjY1lxowZtvMPPPAAK1euZMuWLURFRTF69OibugdWq5WoqCi2b99OVFQUv/32G1arlaNHj7Jjxw62b9/OoEGD6NmzJz4+PkRGRmK1WrG3t7e1MXXqVNsscGRkZI595dZGUlISEyZMYM2aNVitVjZv3sySJUsAuHDhAk2bNmXbtm0EBATw8ccf39QY7yVaFisiIiIiUgxltyzWarVSr149GjRoAMAzzzzDRx99lGs7a9asoWfPnlSvXh2AqlWrAvD777/Tu3dvjh07xuXLl6lXr16u7Zw9e5YzZ87QqlUrAAYOHEivXr1s17t37w6At7e3bcb0ypUrjBw5EqvVip2dHXv37s3f4DO1adOGSpUqAeDs7Mzhw4dxcXHh4MGDjBo1io4dOxIcHHxTbd6KzZs3ExgYSI0aNQDo168f69evp2vXrpQuXZpOnToBGWNfuXLlbY+nuNLMpYiIiIjIXcQwjGzPlyxZkvT0dNtxSkoKAKZpZltn1KhRjBw5ku3bt/Phhx/ayt+qMmXKABkbEaWmpgIwffp0atasybZt24iLi+Py5cu31Oa17VapUoVt27YRGBjI+++/z+DBN7fZUk73KTemaeZ4rVSpUrb7e+3Y70dKLkVERERE7hKNGzfm0KFDHDhwAMh4DvAqR0dHtmzZAsCWLVs4dOgQkDH79/XXX3Pq1CkATp8+DWTMRNapUweAzz//3NZOhQoVOHfu3A19V6pUiSpVqtiep5w3b55tFjMnZ8+epVatWpQoUYJ58+aRlpZ2S+O+1smTJ0lPT6dHjx68+eabtjHnFDdkJIBXrlwBoGbNmvz555+cOnWKS5cuZdlpN6c2mjRpwrp16zh58iRpaWnMnz8/z7Hfj7QsVkREREQkD/l5dUhhu/rM5VXt27dn6tSpfPTRR3Ts2JHq1avTokUL22s7evTowdy5c7FYLPj6+tKwYUMAXFxcePXVV2nVqhV2dnZ4enoSERFBWFgYvXr1ok6dOjRt2tSWjHbu3JmePXuydOlSZs2alSWmzz//nGHDhnHx4kXq16/PZ599lusYhg8fTo8ePViwYAFBQUGUL1++wPfl6NGjDBo0yDb7+NZbbwEQEhLCsGHDsLe3Z9OmTVnqDBkyBHd3d7y8vIiMjGTSpEk0adKEevXq0bhxY1u5nNqoVasWb731FkFBQZimSYcOHXjyyScLPJZ7jZHbFO+9yMfHx7y645PI/cy+bM0sx8kp9+/OZiIiItfbvXs3Tk5ORR2GSIFl9102DCPeNE2fwu5Ly2JFRERERESkwJRcioiIiIiISIEpuRQREREREZECU3IpIiIiIiIiBabkUkRERERERApMyaWIiIiIiIgUmN5zKSIiIiKShy/aDCrU9p5Znfv7IQMDA3n55Zdp166d7dyMGTPYu3cv7du3Z9euXUycODHH+mFhYTg4ODBu3Libji0xMZGNGzfy9NNPZ3vNycmJRo0acfnyZQICAvjvf/9LiRLZz1ldG8ekSZMICAigbdu2zJgxgyFDhlCuXDkAOnTowJdffknlypVvKtaIiAji4uJ47733bjg/fvx46tSpw+XLlxkzZgzPPffcTbUbHBxM7dq1byqe+51mLkVEREREipm+ffvy1VdfZTn31Vdf0bdvX7p06ZJrYllQiYmJfPnllzlef/TRR7FarSQkJLBr1y6WLFmSr3YnT55M27ZtgYxE+eLFi7Zr33///U0nlnnp3bs3VquV6OhoXnnlFY4fz987vdPS0oiIiCApKalQ47kfKLkUERERESlmevbsyfLly7l06RKQkfAlJSXRokULIiIiGDlyJACHDx+mTZs2uLu706ZNG44cOXJDWwcOHKB9+/Z4e3vTsmVL9uzZA0BISAijR4/G39+f+vXrs3DhQgAmTpzIhg0bsFgsTJ8+PccYS5Ysib+/P/v3789XHCEhISxcuJCZM2eSlJREUFAQQUFBADg6OnLy5EkA5s6di7u7Ox4eHvTv3x+Ab7/9liZNmuDp6Unbtm3znSgCPPDAAzz66KMcPnyY559/Hh8fH1xcXHj99ddtZRwdHZk8eTItWrRg/vz5xMXF0a9fPywWC9999x3dunWzlV25ciXdu3fPd//3EyWXIiIiIiLFTLVq1fDz8+PHH38EMmYte/fujWEYWcqNHDmSAQMGkJCQQL9+/Rg9evQNbQ0ZMoRZs2YRHx9PeHg4w4cPt107duwYMTExLF++3DYbOnXqVFq2bInVamXMmDE5xnjx4kVWr16Nm5tbvuK4avTo0dSuXZu1a9eydu3aLNd27tzJlClTWLNmDdu2bePdd98FoEWLFvz8889s3bqVPn36MG3atDzu4P938OBBDh48yGOPPcaUKVOIi4sjISGBdevWkZCQYCtXtmxZYmJieOaZZ/Dx8SEyMhKr1UqHDh3YvXs3J06cAOCzzz5j0KDCXSZ9r9AzlyIiIiIixdDVpbFPPvkkX331FXPmzLmhzKZNm1i8eDEA/fv356WXXspy/fz582zcuJFevXrZzl2dDQXo2rUrJUqUwNnZOd+zgQcOHMBisWAYBk8++SRPPPEE/fv3zzWO/FqzZg09e/akevXqAFStWhWA33//nd69e3Ps2DEuX75MvXr18mwrKiqKmJgYypQpw4cffkjVqlWZPXs2H330EampqRw7doxdu3bh7u4OZCyjzY5hGPTv358vvviCQYMGsWnTJubOnXtL47vXKbkUERERESmGunbtytixY9myZQvJycl4eXnlWef6mc309HQqV66M1WrNtnyZMmVsn03TzFdcV5+5vJk48ss0zWzrjho1irFjx9KlSxeio6MJCwvLs63evXtn2ejn0KFDhIeHs3nzZqpUqUJISAgpKSm26+XLl8+xrUGDBtG5c2fKli1Lr169KFlSaVR2tCxWRERERKQYcnBwIDAwkNDQUPr27ZttGX9/f9vGP5GRkbRo0SLL9YoVK1KvXj0WLFgAZCRv27Zty7XfChUqcO7cuZuKNa848ttHmzZt+Prrrzl16hQAp0+fBuDs2bPUqVMHgM8///ymYrvq77//pnz58lSqVInjx4/zww8/5Du+2rVrU7t2bf71r38REhJyS/3fD5Ryi4iIiIjkIa9Xh9wuffv2pXv37jfsHHvVzJkzCQ0N5Z133qFGjRp89tmNcUZGRvL888/zr3/9iytXrtCnTx88PDxy7NPd3Z2SJUvi4eFBSEhIrs9d3kwc1xoyZAhPPPEEtWrVyvLcpYuLC6+++iqtWrXCzs4OT09PIiIiCAsLo1evXtSpU4emTZty6NChPGO6noeHB56enri4uFC/fn2aN2+eY9mQkBCGDRuGvb09mzZtwt7enn79+nHixAmcnZ1vuu/7hZHf6e97hY+PjxkXF1fUYYgUOfuyNbMcJ6fkf9c1ERGRe93u3btxcnIq6jCkGBk5ciSenp48++yzRR3KTcnuu2wYRrxpmj6F3ddtWxZrGMYcwzD+NAxjxzXnogzDsGb+JBqGYc0872gYRvI112ZfU8fbMIzthmHsNwxjppG5CNswjDKZ7e03DOMXwzAcb9dYRERERETk/uXt7U1CQgLPPPNMUYdSrN3OZbERwHuAbSsl0zRtWzAZhvEf4Ow15Q+YpmnJpp0PgCHAz8D3QHvgB+BZ4C/TNB8zDKMP8DaQ/RZPIiIiIiIityg+Pr6oQ7gr3LaZS9M01wOns7uWOfv4FDA/tzYMw6gFVDRNc5OZsX53LtA18/KTwNWneRcCbYzstpYSERERERGR266odottCRw3TXPfNefqGYax1TCMdYZhtMw8Vwf4/Zoyv2eeu3rtNwDTNFPJmAWtll1nhmEMMQwjzjCMuKsvPxUREREREZHCU1TJZV+yzloeAx4xTdMTGAt8aRhGRSC7mcirOxDldi3rSdP8yDRNH9M0fWrUqFGAsEVERERERCQ7d/xVJIZhlAS6A95Xz5mmeQm4lPk53jCMA0BDMmYqH7qm+kNAUubn34GHgd8z26xEDstwRURERERE5PYqivdctgX2mKZpW+5qGEYN4LRpmmmGYdQHGgAHTdM8bRjGOcMwmgK/AAOAWZnVlgEDgU1AT2CNeb+9V0VERERE7ohvOxfuLqGdv/0izzJ2dna4ubmRmppKvXr1mDdvHpUrV86xfFhYGA4ODowbN45JkyYREBBA27Ztcyy/bNkydu3axcSJE29lCHkKDAzk2LFj2NvbA/DPf/6TH3/8kbFjxxbZuyLfeustHnnkEfbt22e7VzfjzJkzfPnllwwfPhyApKQkRo8ezcKFC7FarSQlJdGhQ4dbbuNudztfRTKfjMSvkWEYvxuGcfWFMH24cSOfACDBMIxtZGzOM8w0zauzkM8DnwD7gQNk7BQL8ClQzTCM/WQspb09fypERERERIqAvb09VquVHTt2ULVqVd5///181508eXKuiSVAly5dbltieVVkZCRWqxWr1UrPnj355JNPCiWxTEtLu6V6K1asIDg4+Jb7PXPmDP/9739tx7Vr17YlhVarle+//75AbdztbudusX1N06xlmmYp0zQfMk3z08zzIaZpzr6u7CLTNF1M0/QwTdPLNM1vr7kWZ5qmq2maj5qmOfLq7KRpmimmafYyTfMx0zT9TNM8eLvGIiIiIiJSlJo1a8bRo0cBOHDgAO3bt8fb25uWLVuyZ8+eG8qHhITYEpbvv/+exo0b06JFC0aPHk2nTp0AiIiIYOTIkQAcPnyYNm3a4O7uTps2bThy5MgN7QA4ODgAcOzYMQICArBYLLi6urJhw4Z8jSMwMJC4uDgAPv30Uxo2bEhgYCDPPfecLZac+oyOjiYoKIinn34aNzc30tLSGD9+PL6+vri7u/Phhx/mGtvff//N5cuXuX4PlsDAQCZMmICfnx8NGza0ld+5cyd+fn5YLBbc3d3Zt28fEydO5MCBA1gsFsaPH09iYiKurq5cvnyZSZMmERUVhcViISoqirCwMMLDw239uLq6kpiYmGMbACkpKQwaNAg3Nzc8PT1Zu3at7XfVvXt32rdvT4MGDXjppZeAjCQ7JCQEV1dX3NzcmD59er5+D7dLUSyLFRERERGRfEpLS2P16tU8+2zGQsAhQ4Ywe/ZsGjRowC+//MLw4cNZs2ZNtnVTUlIYOnQo69evp169evTt2zfbciNHjmTAgAEMHDiQOXPmMHr0aJYsWZJjTF9++SXt2rXj1VdfJS0tjYsXL2Zbrl+/frZlsatXr7adT0pK4s0332TLli1UqFCB1q1b4+Hhkee9iI2NZceOHdSrV4+PPvqISpUqsXnzZi5dukTz5s0JDg5m8eLF2ca2atUq2rRpk227qampxMbG8v333/PGG2+watUqZs+ezQsvvEC/fv24fPkyaWlpTJ06lR07dmC1WgFITEwEoHTp0kyePJm4uDjee+89IGOZcnZyagOwzU5v376dPXv2EBwczN69e4GMmdGtW7dSpkwZGjVqxKhRo/jzzz85evQoO3bsADJmRYuSkksRERERkWIoOTkZi8VCYmIi3t7ePP7445w/f56NGzfSq1cvW7lLly7l2MaePXuoX78+9erVA6Bv37589NFHN5TbtGkTixcvBqB///62mbGc+Pr6EhoaypUrV+jatSsWiyXbcpGRkfj4+NxwPjY2llatWlG1alUAevXqZUuicuPn52cby4oVK0hISLDNcp49e5Z9+/blGNuPP/7IoEGDsm23e/fuAHh7e9uSvWbNmjFlyhR+//13unfvToMGDfKMr6BiYmIYNWoUAI0bN6Zu3bq2+9KmTRsqVaoEgLOzM4cPH8bFxYWDBw8yatQoOnbsWKAlv4WhqF5FIiIiIiIiubj6zOXhw4e5fPky77//Punp6VSuXNn2HKPVamX37t05tnGr+10aRsZb/0qWLEl6erqtrcuXLwMQEBDA+vXrqVOnDv3792fu3Lk31X5uceXUJ0D58uWztDFr1izbfTh06BDBwcE5xhYbG4ufn1+2fZYpUwbI2EQpNTUVgKeffpply5Zhb29Pu3btcpwdzs84IGMWOS+53ZerMV4bZ5UqVdi2bRuBgYG8//77DB48+KZiLGxKLkVEREREirFKlSoxc+ZMwsPDsbe3p169eixYsADISEa2bduWY93GjRtz8OBB22xcVFRUtuX8/f356quvgIzZxhYtWgDg6OhIfHw8AEuXLuXKlStAxjOaDzzwAM899xzPPvssW7Zsuakx+fn5sW7dOv766y9SU1NZtGiR7VpOfV6vXbt2fPDBB7bre/fu5cKFC9nGtnPnTho3boydnV2+Yzx48CD169dn9OjRdOnShYSEBCpUqMC5c+eyLX/9NUdHR9t92bJlC4cOHcq23LUCAgKIjIy0jefIkSM0atQoxxhPnjxJeno6PXr0sC0zLkpaFisiIiIikof8vDrkdvL09MTDw4OvvvqKyMhInn/+ef71r39x5coV+vTpk+Pzivb29vz3v/+lffv2VK9ePceZu5kzZxIaGso777xDjRo1+OyzzwB47rnnePLJJ/Hz86NNmza2mcPo6GjeeecdSpUqhYODw03PXNapU4dXXnmFJk2aULt2bZydnW1LPnPq83qDBw8mMTERLy8vTNOkRo0aLFmyJNvYFi1aRPv27W8qxqioKL744gtKlSrFgw8+yKRJk6hatSrNmzfH1dWVJ554ghEjRtjKBwUFMXXqVCwWCy+//DI9evRg7ty5WCwWfH19adiwIQDVqlXLsY3hw4czbNgw3NzcKFmyJBEREVlmLK939OhRBg0aZJshfeutt25qjIXNuN9eDenj42Ne3aFK5H5mX7ZmluPklONFFImIiEjxs3v3bpycnIo6jEJx/vx5HBwcME2TESNG0KBBA8aMGVPUYdniSk1NpVu3boSGhtKtW7fb0tfjjz/O3LlzqVWr1m1pvzjL7rtsGEa8aZo3PgxbQFoWKyIiIiJyD/v444+xWCy4uLhw9uxZhg4dWtQhARm7qV59XUi9evXo2rXrbetr5cqV92Vieadp5lLkPqWZSxERkZzdSzOXcn/TzKWIiIiIiIjcVZRcioiIiIiISIEpuRQREREREZECU3IpIiIiIiIiBab3XIqIiIiI5GFdn96F2l6rr6LyLJOYmEinTp3YsWOH7VxYWBgODg6MGzcu2zoRERHExcXx3nvvFVqsIvmlmUsREREREREpMCWXIiIiIiJ3mcDAQCZMmICfnx8NGzZkw4YNN5T57rvvaNasGSdPniQkJITRo0fj7+9P/fr1WbhwIQCmaTJ+/HhcXV1xc3MjKipjRnX48OEsW7YMgG7duhEaGgrAp59+yj//+U8SExNxcnLiueeew8XFheDgYJKTk+/Q6KW4UnIpIiIiInIXSk1NJTY2lhkzZvDGG29kufbNN98wdepUvv/+e6pXrw7AsWPHiImJYfny5UycOBGAxYsXY7Va2bZtG6tWrWL8+PEcO3aMgIAAW8J69OhRdu3aBUBMTAwtW7YEYN++fYwYMYKdO3dSuXJlFi1adKeGLsWUkksRERERkWLIMIxcz3fv3h0Ab29vEhMTbdfXrl3L22+/zXfffUeVKlVs57t27UqJEiVwdnbm+PHjQEay2LdvX+zs7KhZsyatWrVi8+bNtGzZkg0bNrBr1y6cnZ2pWbMmx44dY9OmTfj7+wNQr149LBZLtjHI/UnJpYiIiIhIMVStWjX++uuvLOdOnz5tm4ksU6YMAHZ2dqSmptrK1K9fn3PnzrF3794sda+Wh4zlsNf+93p16tThr7/+4scffyQgIICWLVvy9ddf4+DgQIUKFW5o7/oY5P6k5FJEREREpBhycHCgVq1arF69GshILH/88UdatGiRa726deuyePFiBgwYwM6dO3MtGxAQQFRUFGlpaZw4cYL169fj5+cHQLNmzZgxY4YtuQwPD7ctiRXJjl5FIiIiIiKSh/y8OuR2mDt3LiNGjOAf//gHAK+//jqPPvponvUaNWpEZGQkvXr14ttvv82xXLdu3di0aRMeHh4YhsG0adN48MEHAWjZsiUrVqzgscceo27dupw+fVrJpeTKyGkq/F7l4+NjxsXFFXUYIkXOvmzNLMfJKceLKBIREZHiZ/fu3Tg5ORV1GCIFlt132TCMeNM0fQq7Ly2LFRERERERkQJTcikiIiIiIiIFpuRSRERERERECkzJpYiIiIiIiBSYkksREREREREpMCWXIiIiIiIiUmB6z6WIiIiISB42h3Yu1PZ85+T87kmAU6dO0aZNGwD++OMP7OzsqFGjBgCxsbGULl26UOMpCKvVSlJSEh06dLipcsuWLWPXrl1MnDjxToQpd4CSSxERERGRYqZatWpYrVYAwsLCcHBwYNy4cbbrqamplCxZ9H+VT01NxWq1EhcXl6/k8tpyXbp0oUuXLnciTLlDiv4bKSIiIiIieQoJCaFq1aps3boVLy8vevfuzYsvvkhycjL29vZ89tlnNGrUiIiICJYtW8bFixc5cOAA3bp1Y9q0aaSlpfHss88SFxeHYRiEhoYyZswYAgMDsVgsxMbG8vfffzNnzhz8/Pw4ffo0oaGhHDx4kHLlyvHRRx/h7u5OWFgYSUlJJCYmUr16dWJiYkhOTiYmJoaXX36ZevXq3RBXvXr1mDRpUpZyycnJxMXF8d5773H48GFCQ0M5ceIENWrU4LPPPuORRx4hJCSEihUrEhcXxx9//MG0adPo2bNnUf8qJAdKLkVERERE7hJ79+5l1apV2NnZ8ffff7N+/XpKlizJqlWreOWVV1i0aBGQMUu4detWypQpQ6NGjRg1ahR//vknR48eZceOHQCcOXPG1u6FCxfYuHEj69evJzQ0lB07dvD666/j6enJkiVLWLNmDQMGDLDNpsbHxxMTE4O9vT0RERG2JBHIMa7JkydnKRcREWHrf+TIkQwYMICBAwcyZ84cRo8ezZIlSwA4duwYMTEx7Nmzhy5duii5LMaUXIqIiIiI3CV69eqFnZ0dAGfPnmXgwIHs27cPwzC4cuWKrVybNm2oVKkSAM7Ozhw+fBgXFxcOHjzIqFGj6NixI8HBwbbyffv2BSAgIIC///6bM2fOEBMTY0tWW7duzalTpzh79iyQsaTV3t4+2xhziysnmzZtYvHixQD079+fl156yXata9eulChRAmdnZ44fP57veyV3nnaLFRERERG5S5QvX972+bXXXiMoKIgdO3bw7bffkpKSYrtWpkwZ22c7OztSU1OpUqUK27ZtIzAwkPfff5/BgwfbyhiGkaUfwzAwTfOG/q+WuzaO6+UWV35dG8+1Y8kuJik+lFyKiIiIiNyFzp49S506dYCsS0xzcvLkSdLT0+nRowdvvvkmW7ZssV2LiooCICYmhkqVKlGpUiUCAgKIjIwEIDo6murVq1OxYsUb2q1QoQLnzp3LM67ry13L39+fr776CoDIyEhatGiR53ik+NGyWBERERGRPOT16pCi8NJLLzFw4ED+7//+j9atW+dZ/ujRowwaNIj09HQA3nrrLdu1KlWq4O/vb9vQBzJ2qR00aBDu7u6UK1eOzz//PNt2g4KCmDp1KhaLhZdffjnHuK4vd62ZM2cSGhrKO++8Y9vQR+4+xv02tezj42PGxcUVdRgiRc6+bM0sx8kpeoZBRETkqt27d+Pk5FTUYdwRgYGBhIeH4+PjU9ShyG2Q3XfZMIx40zQL/ReuZbEiIiIiIiJSYFoWKyIiIiJyH4uOji7qEOQeoZlLERERERERKTAllyIiIiIiIlJgSi5FRERERESkwJRcioiIiIiISIFpQx8RERERkTxsH92mUNtzm7k61+unTp2iTZuMPv/44w/s7OyoUaMGALGxsZQuXfqm+4yLi2Pu3LnMnDkz2+uJiYls3LiRp59++qbbFgEllyIiIiIixU61atWwWq0AhIWF4eDgwLhx4265vdTUVHx8fHJ9l2ViYiJffvmlkku5ZVoWKyIiIiJyF1i9ejWenp64ubkRGhrKpUuXAHB0dOTkyZNAxuxkYGAgkJGUDhkyhODgYAYMGEB0dDSdOnUCYN26dVgsFiwWC56enpw7d46JEyeyYcMGLBYL06dPZ+fOnfj5+WGxWHB3d2ffvn1FMm65eyi5FBEREREp5lJSUggJCSEqKort27eTmprKBx98kGe9+Ph4li5dypdffpnlfHh4OO+//z5Wq5UNGzZgb2/P1KlTadmyJVarlTFjxjB79mxeeOEFrFYrcXFxPPTQQ7dreHKPUHIpIiIiIlLMpaWlUa9ePRo2bAjAwIEDWb9+fZ71unTpgr29/Q3nmzdvztixY5k5cyZnzpyhZMkbn5Zr1qwZ//73v3n77bc5fPhwtu2IXEvJpYiIiIhIMVe+fPkcr5UsWZL09HQgY4YzP/UmTpzIJ598QnJyMk2bNmXPnj03lHn66adZtmwZ9vb2tGvXjjVr1hRgBHI/UHIpIiIiIlLMpaSkkJiYyP79+wGYN28erVq1AjKeuYyPjwdg0aJF+WrvwIEDuLm5MWHCBHx8fNizZw8VKlTg3LlztjIHDx6kfv36jB49mi5dupCQkFDIo5J7jXaLFRERERHJQ16vDrndypYty2effUavXr1ITU3F19eXYcOGAfD666/z7LPP8u9//5smTZrkq70ZM2awdu1a7OzscHZ25oknnqBEiRKULFkSDw8PQkJCSElJ4YsvvqBUqVI8+OCDTJo06XYOUe4BhmmaRR3DHeXj42PGxcUVdRgiRc6+bM0sx8kpx4soEhERkeJn9+7dODk5FXUYIgWW3XfZMIx40zRzfi/NLdKyWBERERERESkwJZciIiIiIiJSYEouRUREREREpMCUXIqIiIiIiEiBKbkUERERERGRAlNyKSIiIiIiIgWm91yKiIiIiOTh11fz9/7I/Go05Zc8yxiGwdixY/nPf/4DQHh4OOfPnycsLAyAL774gmnTppGWlkbJkiXx9fUlPDycypUrc/nyZV566SW+/fZbSpQogbOzM++//z4PPfRQoY5D5FqauRQRERERKYbKlCnD4sWLOXny5A3XfvzxR6ZPn84PP/zAzp072bJlC/7+/hw/nvHe6ldeeYVz586xd+9e9u3bR9euXenevTv32zvu5c5ScikiIiIiUgyVLFmSIUOGMH369BuuTZkyhfDwcOrUqQOAnZ0doaGhNGrUiIsXL/LZZ58xffp07OzsABg0aBBlypRhzZo1d3QMcn9RcikiIiIiUkyNGDGCyMhIzp49m+X8zp078fLyyrbO/v37eeSRR6hYsWKW8z4+PuzcufO2xSqi5FJEREREpJiqWLEiAwYMYObMmTmW2b59OxaLhUcffZSoqChM08QwjBvK5XRepLAouRQRERERKcZefPFFPv30Uy5cuGA75+LiwpYtWwBwc3PDarXyxBNPkJyczGOPPcbhw4c5d+5clna2bNmCs7PzHY1d7i9KLkVEREREirGqVavy1FNP8emnn9rOvfzyy4wbN47ff//ddi45ORmA8uXLM3DgQMaOHUtaWhoAc+fO5eLFi7Ru3frOBi/3Fb2KREREREQkD/l5dcjt9I9//IP33nvPdtyhQwdOnDjBE088QVpaGpUrV8bV1ZV27doB8NZbbzFu3DgaNmxIiRIlaNy4Md98842WxcptZdxv2xH7+PiYcXFxRR2GSJGzL1szy3FyyvEiikRERKT42b17N05OTkUdhkiBZfddNgwj3jRNn8LuS8tiRUREREREpMCUXIqIiIiIiEiBKbkUERERERGRAlNyKSIiIiIiIgWm5FJEREREREQKTMmliIiIiIiIFJjecykiIiIikof9U10Ktb3HJu7M9fqpU6do06YNAH/88Qd2dnbUqFEDgNjYWEqXLm0rGxISQqdOnejZs2ehxlhUkpKSGD16NAsXLrzpuhEREQQHB1O7dm0ABg8ezNixY3F2di7sMCUbSi5FRERERIqZatWqYbVaAQgLC8PBwYFx48YVbVB3SO3atW8psYSM5NLV1dWWXH7yySeFGZrkQctiRURERETuAvHx8bRq1Qpvb2/atWvHsWPH8l1m//79tG3bFg8PD7y8vDhw4ACmaTJ+/HhcXV1xc3MjKioKgOjoaFq1asVTTz1Fw4YNmThxIpGRkfj5+eHm5saBAweAjBnT559/nqCgIOrXr8+6desIDQ3FycmJkJAQW0wODg62zwsXLrRdCwkJYfTo0fj7+1O/fn1bQpmYmIirqysAaWlpjBs3Djc3N9zd3Zk1axYAkydPxtfXF1dXV4YMGYJpmixcuJC4uDj69euHxWIhOTmZwMBA4uLiAJg/fz5ubm64uroyYcKELPG9+uqreHh40LRpU44fP14Yv677kpJLEREREZFizjRNRo0axcKFC4mPjyc0NJRXX301S5krV67kWKZfv36MGDGCbdu2sXHjRmrVqsXixYuxWq1s27aNVatWMX78eFsyum3bNt599122b9/OvHnz2Lt3L7GxsQwePNiW4AH89ddfrFmzhunTp9O5c2fGjBnDzp072b59u23mNTfHjh0jJiaG5cuXM3HixBuuf/TRRxw6dIitW7eSkJBAv379ABg5ciSbN29mx44dJCcns3z5cnr27ImPjw+RkZFYrVbs7e1t7SQlJTFhwgTWrFmD1Wpl8+bNLFmyBIALFy7QtGlTtm3bRkBAAB9//PFN/W7k/9OyWBERERGRYu7SpUvs2LGDxx9/HMiY0atVq1aWMr/++mu2Zc6dO8fRo0fp1q0bAGXLlgUgJiaGvn37YmdnR82aNWnVqhWbN2+mYsWK+Pr62tp/9NFHCQ4OBsDNzY21a9fa+uzcuTOGYeDm5kbNmjVxc3MDwMXFhcTERCwWS67j6tq1KyVKlMDZ2TnbGcNVq1YxbNgwSpbMSFuqVq0KwNq1a5k2bRoXL17k9OnTuLi40Llz5xz72bx5M4GBgbbnVvv168f69evp2rUrpUuXplOnTgB4e3uzcuXKXGOWnCm5FBEREREp5kzTxMXFhU2bNt10mb///jvH8jkpU6aM7XOJEiVsxyVKlCA1NfWGcteWub6cYRi28ykpKTn2k108pmlmqX+1jeHDhxMXF8fDDz9MWFjYDe1m105OSpUqZevDzs4uy/jk5mhZrIiIiIhIMVemTBlOnDhhSxyvXLnCzp1Zd5xt1KhRtmUqVqzIQw89ZFsGeunSJS5evEhAQABRUVGkpaVx4sQJ1q9fj5+fX6HHXrNmTXbv3k16ejrffPPNTdUNDg5m9uzZtoTv9OnTtkSyevXqnD9/PsvmPxUqVODcuXM3tNOkSRPWrVvHyZMnSUtLY/78+bRq1aoAo5LsaOZSRERERCQPeb065HYrUaIECxcuZPTo0Zw9e5bU1FRefPFFXFz+/ytSSpcunWOZefPmMXToUCZNmkSpUqVYsGAB3bp1Y9OmTXh4eGAYBtOmTePBBx9kz549hRr71KlT6dSpEw8//DCurq6cP38+33UHDx7M3r17cXd3p1SpUjz33HOMHDmS5557Djc3NxwdHfH19bWVDwkJYdiwYdjb22eZwa1VqxZvvfUWQUFBmKZJhw4dePLJJwt1nAJGblPE9yIfHx/z6o5RIvcz+7I1sxwnp2hnNBERkat2796Nk5NTUYchUmDZfZcNw4g3TdOnsPvSslgREREREREpMCWXIiIiIiIiUmBKLkVERERERKTAlFyKiIiIiIhIgSm5FBERERERkQJTcikiIiIiIiIFpvdcioiIiIjk4eAHDQu1vfrP782zjJ2dHW5ubrbjJUuW4OjoeMt9JiYm0qlTJ3bs2HHLbVz17rvvcujQIWbMmAHA0KFDOXDgAKtWrQJg1qxZ7Nu3j5kzZ2Zbf8mSJTRs2BBnZ+dbjuHixYs899xzJCQkYJomlStX5scff8TBweGW27xeYd6z+4GSSxERERGRYsje3h6r1VrUYQCQlpaGnZ2d7djf35/IyEjbsdVqJT093VZu48aNdO3aNcf2lixZQqdOnW4quUxNTaVkyf+fvrz77rvUrFmT7du3A/Drr79SqlSpmxiVFDYtixURERERuUtYrVaaNm2Ku7s73bp146+//sr1fHx8PB4eHjRr1oz3338/2zZN02T8+PG4urri5uZGVFQUANHR0QQFBfH0009nmUEF8PT0ZO/evSQnJ3P27FnKlSuHxWKxJXobN27E39+fjz/+GF9fXzw8POjRowcXL15k48aNLFu2jPHjx2OxWDhw4AAHDhygffv2eHt707JlS/bs2QNASEgIY8eOJSgoiAkTJmSJ4dixY9SpU8d23KhRI8qUKUNiYiKurq628+Hh4YSFhQEQGBjIiy++iL+/P66ursTGxgIQFhZG//79ad26NQ0aNODjjz++4T61bNkyS7LfvHlzEhIScv+F3WeUXIqIiIiIFEPJyclYLBYsFgvdunUDYMCAAbz99tskJCTg5ubGG2+8kev5QYMGMXPmTDZt2pRjP4sXL8ZqtbJt2zZWrVrF+PHjOXbsGACxsbFMmTKFXbt2ZalTsmRJLBYLmzdv5ueff6ZJkyY0bdqUjRs3kpSUhGmaPPzww3Tv3p3Nmzezbds2nJyc+PTTT/H396dLly688847WK1WHn30UYYMGcKsWbOIj48nPDyc4cOH2/rau3cvq1at4j//+U+WGEJDQ3n77bdp1qwZ//znP9m3b1++7uuFCxfYuHEj//3vfwkNDbWdT0hI4LvvvmPTpk1MnjyZpKSkLPUGDx5MRESELaZLly7h7u6erz7vF0ouRURERESKoavLYq1WK9988w1nz57lzJkztGrVCoCBAweyfv36fJ/v379/tv3ExMTQt29f7OzsqFmzJq1atWLz5s0A+Pn5Ua9evWzrNW/enI0bN7Jx40aaNWtGs2bN2LhxIz/99BP+/v4A7Nixg5YtW+Lm5kZkZCQ7d+68oZ3z58+zceNGevXqhcViYejQobbkFqBXr15ZluReZbFYOHjwIOPHj+f06dP4+vqye/fuPO9r3759AQgICODvv//mzJkzADz55JPY29tTvXp1goKCbLOa18axfPlyrly5wpw5cwgJCcmzr/uNnrkUEREREbkHmaaJYRj5KpeT8uXL53jN39+fDz/8kJSUFEaMGEGNGjXYtWsXNWrUoHnz5kDGstYlS5bg4eFBREQE0dHRN7STnp5O5cqVc3y+NLcYHBwc6N69O927d6dEiRJ8//339O7dm/T0dFuZlJSULHWuvydXj3M6f1W5cuV4/PHHWbp0KV9//TVxcXE5xnW/0syliIiIiMhdoFKlSlSpUoUNGzYAMG/ePFq1apXj+cqVK1OpUiViYmIAsmzAc62AgACioqJIS0vjxIkTrF+/Hj8/vzzj8ff35+eff+bEiRM88MADGIZBjRo1WLp0qW3m8ty5c9SqVYsrV65k6b9ChQqcO3cOgIoVK1KvXj0WLFgAZCS727Zty7P/n376yfZs6eXLl9m1axd169alZs2a/Pnnn5w6dYpLly6xfPnyLPWuPlMaExNDpUqVqFSpEgBLly4lJSWFU6dOER0dja+v7w19Dh48mNGjR+Pr60vVqlXzjPF+o5lLEREREZE85OfVIXfC559/zrBhw7h48SL169fns88+y/X8Z599RmhoKOXKlaNdu3bZttmtWzc2bdqEh4cHhmEwbdo0HnzwQdumOjmpUqUKNWrUwMXFxXauWbNm/PTTT3h4eADw5ptv0qRJE+rWrYubm5stoezTpw/PPfccM2fOZOHChURGRvL888/zr3/9iytXrtCnTx9bGzk5cOAAzz//PKZpkp6eTseOHenRoweGYTBp0iSaNGlCvXr1aNy48Q1x+/v78/fffzNnzhzbeT8/Pzp27MiRI0d47bXXqF27NomJiVnqent7U7FiRQYNGpRrbPcrI7dp8HuRj4+PqSlsEbAvWzPLcXLK8SKKREREpPjZvXs3Tk5ORR2GFLLAwEDCw8Px8fHJcj4sLAwHBwfGjRuXa/2kpCQCAwPZs2cPJUrcHYtAs/suG4YRb5qmTw5VbtndcUdERERERESK0Ny5c2nSpAlTpky5axLLO00zlyL3Kc1cioiI5Ewzl3Kv0MyliIiIiIiI3FWUXIqIiIiIiEiBKbkUERERERGRAlNyKSIiIiIiIgWm91yKiIiIiOQhMapw9z5x7J37BpOnTp2iTZs2APzxxx/Y2dlRo0YNAGJjYyldunShxgMwadIkAgICaNu2bbbXlyxZQsOGDXF2ds61nStXrtC0aVPi4+MxDIOxY8fyn//8B4Dw8HDOnz9PWFhYgeP99ddfGTp0KGfOnOHSpUu0bNmSjz76CKvVSlJSEh06dMi1fn7LXSsxMZF69erxz3/+kzfffBOAkydPUqtWLYYOHcp7773H7NmzKVeuHAMGDCAkJIROnTrRs2dPBg8ezNixY3F2dubf//43r7zyiq1df39/Nm7ceGs3ohjRzKWIiIiISDFTrVo1rFYrVquVYcOGMWbMGNtxbollampqrsc5SUtLY/LkyTkmlpCRXO7atSvPtmJiYvD39wegTJkyLF68mJMnT+YrjpsxevRo233ZvXs3o0aNAjKSxu+//z7P+vktd7369euzfPly2/GCBQtwcXGxHQ8bNowBAwbcUO+TTz6xJeb//ve/s1y7FxJLUHIpIiIiInJXiI+Pp1WrVnh7e9OuXTuOHTsGQGBgIK+88gqtWrXi3XffveF49erVeHp64ubmRmhoKJcuXQLA0dGRyZMn06JFCxYsWEBISAgLFy4EYOLEiTg7O+Pu7s64cePYuHEjy5YtY/z48VgsFg4cOMDMmTNtZfr06WOL88cff+SJJ54AoGTJkgwZMoTp06ffMJ7Dhw/Tpk0b3N3dadOmDUeOHAEgJCSE0aNH4+/vT/369W0xXe/YsWM89NBDtmM3NzcuX77MpEmTiIqKwmKxEBUVRWxsLP7+/nh6euLv78+vv/6abbkLFy4QGhqKr68vnp6eLF26NNt+7e3tcXJy4urrDaOionjqqads18PCwggPD7+hXmBgIHFxcUycOJHk5GQsFgv9+vUDwMHBAYDz58/Tpk0bvLy8cHNzyzGG4krLYkVEREREijnTNBk1ahRLly6lRo0aREVF8eqrrzJnzhwAzpw5w7p16wD49ttvbccpKSk0aNCA1atX07BhQwYMGMAHH3zAiy++CEDZsmWJiYkBMpJCgNOnT/PNN9+wZ88eDMPgzJkzVK5cmS5dutiWeAJMnTqVQ4cOUaZMGc6cOWOLde3atbz++uu24xEjRuDu7s5LL72UZUwjR45kwIABDBw4kDlz5jD6/7F332F2VWXfx783SSC00AxdigjSnwChinRpShcTBOlGBR6EB6SJoAiKoiAIFjqKhCi9WAABEUQwgShNmgaJ8EJACL0E7vePtWc4GUII2TOzp3w/15Ur5+xTZs05Z/bZv73WuteBB3LFFVcAJTjeeuut/OMf/2Dbbbdt/5mtDj74YDbZZBPWW289Nt98c/baay/mnXdejjvuOMaOHcvpp58OwAsvvMAtt9zCwIEDueGGGzjqqKO49NJL33W/o446ik022YRzzz2X559/nrXWWovNNtuMOeec810/e+TIkVx88cUsvPDCDBgwgEUXXZQnnnhiht7LE088kdNPP53x48e/67bBgwdz+eWXM2TIEJ555hnWWWcdtt12WyJihp67afZcSpIkST3c66+/zr333ssnP/lJhg0bxvHHH8/EiRPbbx8xYsRU92+7/uCDD7L00kuz3HLLAbDHHntwyy23vOfjAIYMGcLgwYPZd999ueyyy5hjjjmm2aZVV12VXXfdlQsvvJCBA0uf1RNPPMH8888/1WOGDBnC7rvvzmmnnTbV42+//XY+97nPAfD5z3++PeQCbL/99swyyyysuOKKPPXUU9P8+XvttRcPPPAAO++8MzfffDPrrLNOe69sq8mTJ7Pzzjuz8sorc/DBB3PfffdN8/muu+46TjzxRIYNG8ZGG23Ea6+91t6b2tGWW27J9ddfz+jRo6f5Gs6szOSoo45i1VVXZbPNNuM///nPe/7+PZHhUpIkSerhMpOVVlqpfd7lPffcw3XXXdd+e8fetbbrmTnd551Wr9zAgQO588472WmnnbjiiivYcsstp/nYa6+9lv33359x48axxhprMGXKFH7729+yxRZbvOu+Bx10EOeccw4vv/zye7altXduttlma7/c9jt87WtfY9iwYQwbNqz9tkUXXZS9996bK6+8koEDB3Lvvfe+63m//vWvs/HGG3Pvvfdy9dVX89prr03z52cml156aftr/O9//5sVVlhhmvedddZZWWONNfjBD37ATjvt9J6/0wf1y1/+kkmTJjFu3DjGjx/PQgst9J7t7YkMl5IkSVIPN9tsszFp0iRuv/12oFRkfa8euFbLL788EyZM4JFHHgHgF7/4BRtuuOF0H/PSSy8xefJktt56a374wx+2D9+ce+65efHFFwF4++23efzxx9l444353ve+x/PPP89LL7001XzLVvPPPz+f/exnOeecc9q3rbfeelx88cVACVXrr7/+dNt1wgkntAc/KMN433zzTaBU1H322WdZbLHFpmonlJ7LxRZbDIDzzz+/fXvH+22xxRb86Ec/ag+zd99993Tbc8ghh/Dd736XBRZYYLr3m5ZBgwa1t73V5MmTWXDBBRk0aBA33XQTjz322Ad+7iY551KSJEl6H++3dEhXm2WWWbjkkks48MADmTx5MlOmTOGggw6aqkrptAwePJjzzjuPnXfemSlTprDmmmvypS99abqPefHFF9luu+147bXXyMz2YjwjR47kC1/4AqeddhoXX3wx++yzD5MnTyYzOfjgg5l77rl5+OGHWX755af5vIccckj7/EaA0047jb333puTTjqJoUOHct55532g1+S6667jK1/5CoMHDwbgpJNOYuGFF2bjjTduH9565JFHcthhh7HHHntw8skns8kmm7Q/vuP9vv71r3PQQQex6qqrkpkstdRSU1WF7WillVZ639f/vYwaNYpVV12V1VdfnV/+8pft23fddVe22WYbhg8fzrBhw97zteyp4v26yvua4cOHZ1tlJ6k/m33wQlNdf/W13jOeX5KkrvbAAw+855BITdutt97KhRdeyE9/+tOmm6IW0/osR8S4zOzcxVux51KSJElSJ1h//fXfd2ir+jbnXEqSJEmSajNcSpIkSZJqM1xKkiRJkmozXEqSJEmSajNcSpIkSZJqs1qsJEmS9D4eu2HrTn2+JTf7zfveZ+LEiey///7cf//9vP3223z605/mpJNO4v777+eJJ55g661Lm77xjW8w11xzceihh3ZqG6UPyp5LSZIkqYfJTHbccUe23357Hn74YR566CFeeuklvva1rzF+/Hh+85v3D6cz6q233uq051L/1mXhMiLOjYinI+Lelm3fiIj/RMT46t/WLbcdGRGPRMSDEbFFy/Y1IuKe6rbTIiKq7bNFxJhq+x0RsVRX/S6SJElSd7rxxhsZPHgwe+21FwADBgzglFNO4eyzz+awww5jzJgxDBs2jDFjxgBw//33s9FGG/GRj3yE0047rf15LrzwQtZaay2GDRvGF7/4xfYgOddcc3HMMcew9tprc/vtt3f/L6g+qSt7Ls8HtpzG9lMyc1j17zcAEbEiMBJYqXrMjyNiQHX/nwCjgGWrf23PuQ/wXGZ+FDgF+G5X/SKSJElSd7rvvvtYY401pto2ZMgQllpqKY4++mhGjBjB+PHjGTFiBAD/+Mc/+P3vf8+dd97JN7/5Td58800eeOABxowZw2233cb48eMZMGAAv/zlLwF4+eWXWXnllbnjjjtYf/31u/33U9/UZXMuM/OWD9CbuB1wcWa+DvwrIh4B1oqICcCQzLwdICJ+DmwP/LZ6zDeqx18CnB4RkZnZab+EJEmS1IDMpBqwN0PbP/WpTzHbbLMx22yzseCCC/LUU0/xhz/8gXHjxrHmmmsC8Oqrr7LgggsCpSd0p5126tpfQv1OEwV9DoiI3YGxwCGZ+RywGPCXlvtMrLa9WV3uuJ3q/8cBMnNKREwGFgCe6fgDI2IUpfeTJZZYolN/GUmSJKmzrbTSSlx66aVTbXvhhRd4/PHHGTBgwLvuP9tss7VfHjBgAFOmTCEz2WOPPfjOd77zrvsPHjx4ms8j1dHdBX1+AiwDDAOeBH5QbX/36RfI6Wyf3mPevTHzzMwcnpnDhw4d+oEaLEmSJHW3TTfdlFdeeYWf//znQCm6c8ghh7Dnnnuy0EIL8eKLL87Qc1xyySU8/fTTAPz3v//lscce69J2q3/r1p7LzHyq7XJEnAVcU12dCHy45a6LA09U2xefxvbWx0yMiIHAPMB/u6blkiRJ6s9mZOmQzhQRXH755ey3335861vf4u2332brrbfm29/+Ni+//DInnngiw4YN48gjj3zP51hxxRU5/vjj2XzzzXn77bcZNGgQZ5xxBksuuWQ3/ibqT7o1XEbEIpn5ZHV1B6CtkuxVwEURcTKwKKVwz52Z+VZEvBgR6wB3ALsDP2p5zB7A7cBngBudbylJkqS+4sMf/jBXX331u7bPNtts/PWvf33Px917b/tiDYwYMaK96E+rl156qXMaKbXosnAZEaOBjYAPRcRE4Fhgo4gYRhm+OgH4IkBm3hcRvwLuB6YA+2dm24I7X6ZUnp2dUsjnt9X2c4BfVMV//kupNitJkiRJakBXVovdZRqbz5nO/U8ATpjG9rHAytPY/hqwc502SpIkSZI6R3cX9JEkSZIk9UGGS0mSJElSbYZLSZIkSVJthktJkiRJUm3duhSJJEmS1Bs9dvcXOvX5llztrPe9T0Sw22678Ytf/AKAKVOmsMgii7D22mtzzTXXvM+j3/HEE09w4IEHcskllzB+/HieeOIJtt56awCuuuoq7r//fo444oiZ+0WkFvZcSpIkST3QnHPOyb333surr74KwPXXX89iiy32gZ5jypQpLLroolxyySUAjB8/nt/85jftt2+77bYGS3Uaw6UkSZLUQ2211VZce+21AIwePZpddnlntb8777yT9dZbj9VWW4311luPBx98EIDzzz+fnXfemW222YbNN9+cCRMmsPLKK/PGG29wzDHHMGbMGIYNG8aYMWM4//zzOeCAAwDYc889+fKXv8zGG2/MRz7yEf74xz+y9957s8IKK7Dnnnu2/9zrrruOddddl9VXX52dd96Zl156qfteEPVohktJkiSphxo5ciQXX3wxr732Gn//+99Ze+21229bfvnlueWWW7j77rs57rjjOOqoo9pvu/3227ngggu48cYb27fNOuusHHfccYwYMYLx48czYsSId/285557jhtvvJFTTjmFbbbZhoMPPpj77ruPe+65h/Hjx/PMM89w/PHHc8MNN3DXXXcxfPhwTj755K59EdRrOOdSkiRJ6qFWXXVVJkyYwOjRo9vnSbaZPHkye+yxBw8//DARwZtvvtl+2yc/+Unmn3/+D/zzttlmGyKCVVZZhYUWWohVVlkFgJVWWokJEyYwceJE7r//fj7+8Y8D8MYbb7DuuuvW+A3VlxguJUmSpB5s22235dBDD+Xmm2/m2Wefbd/+9a9/nY033pjLL7+cCRMmsNFGG7XfNuecc87Uz5ptttkAmGWWWdovt12fMmUKAwYM4JOf/CSjR4+euV9GfZrDYiVJkqQebO+99+aYY45p70VsM3ny5PYCP+eff/4MPdfcc8/Niy++ONNtWWeddbjtttt45JFHAHjllVd46KGHZvr51LfYcylJkiS9jxlZOqSrLL744nzlK1951/bDDjuMPfbYg5NPPplNNtlkhp5r44035sQTT2TYsGEceeSRH7gtQ4cO5fzzz2eXXXbh9ddfB+D4449nueWW+8DPpb4nMrPpNnSr4cOH59ixY5tuhtS42QcvNNX1V197qqGWSJLU8zzwwAOssMIKTTdDqm1an+WIGJeZwzv7ZzksVpIkSZJUm+FSkiRJklSb4VKSJEmSVJvhUpIkSZJUm+FSkiRJklSb4VKSJEmSVJvrXEqSJEnv4/HHv9upz/fhDx8+Q/e7/PLL2XHHHXnggQdYfvnlAbj55pv5/ve/zzXXXDPTP/+HP/who0aNYo455gBg66235qKLLmLeeeed6ecE+MY3vsFZZ53F0KFDeeONN/j617/OLrvsMt3HzDXXXLz00kvvefvzzz/PRRddxH777feB2zLXXHNx6KGHfqDHaebZcylJkiT1UKNHj2b99dfn4osv7rTnfOutt/jhD3/IK6+80r7tN7/5Te1g2ebggw9m/PjxXHnllXzxi1/kzTffrPV8zz//PD/+8Y87pW3qWoZLSZIkqQd66aWXuO222zjnnHPeFS5feOEFdthhB1ZccUW+9KUv8fbbbwMljK6yyiqsvPLKHH74O72jc801F8cccwxrr702J5xwAk888QQbb7wxG2+8MQBLLbUUzzzzDAAnn3wyK6+8MiuvvDI//OEPAZgwYQIrrLACX/jCF1hppZXYfPPNefXVV6fb/mWXXZY55piD5557DoCTTjqJNddck1VXXZVjjz12mr/vpptuyuqrr84qq6zClVdeCcARRxzBo48+yrBhw/jqV7863ec64YQT+NjHPsZmm23Ggw8+OMOvtTqHw2IlSZKkHuiKK65gyy23ZLnllmP++efnrrvuYvXVVwfgzjvv5P7772fJJZdkyy235LLLLmO99dbj8MMPZ9y4ccw333xsvvnmXHHFFWy//fa8/PLLrLzyyhx33HEAnHvuudx000186EMfmupnjhs3jvPOO4877riDzGTttddmww03ZL755uPhhx9m9OjRnHXWWXz2s5/l0ksvZbfddnvP9t91110su+yyLLjgglx33XU8/PDD3HnnnWQm2267LbfccgsbbLBB+/0HDx7M5ZdfzpAhQ3jmmWdYZ5112HbbbTnxxBO59957GT9+PMB7Ptecc87JxRdfzN13382UKVNYffXVWWONNTr5XdH0GC4lSZKkHmj06NEcdNBBAIwcOZLRo0e3h8u11lqLj3zkIwDssssu3HrrrQwaNIiNNtqIoUOHArDrrrtyyy23sP322zNgwAB22mmn9/2Zt956KzvssANzzjknADvuuCN/+tOf2HbbbVl66aUZNmwYAGussQYTJkyY5nOccsopnHXWWfzzn//kd7/7HVAC4XXXXcdqq60GlF7Khx9+eKpwmZkcddRR3HLLLcwyyyz85z//4amnnnrX87/Xc7344ovssMMO7fNIt9122/f9fdW5DJeSJElSD/Pss89y4403cu+99xIRvPXWW0QE3/ve9wCIiKnuHxFk5ns+3+DBgxkwYMD7/tzpPcdss83WfnnAgAHvOSz24IMP5tBDD+Wyyy5j991359FHHyUzOfLII/niF7/4ns//y1/+kkmTJjFu3DgGDRrEUkstxWuvvTbNNk7ruX74wx++63VR93LOpSRJktTDXHLJJey+++489thjTJgwgccff5yll16aW2+9FSjDYv/1r3/x9ttvM2bMGNZff33WXntt/vjHP/LMM8/w1ltvMXr0aDbccMNpPv/cc8/Niy+++K7tG2ywAVdccQWvvPIKL7/8Mpdffjmf+MQnZup32HHHHRk+fDgXXHABW2yxBeeee257Vdj//Oc/PP3001Pdf/LkySy44IIMGjSIm266iccee2yabX2v59pggw24/PLLefXVV3nxxRe5+uqrZ6rdmnn2XEqSJEnvY0aXDukso0eP5ogjjphq20477cRFF13EiBEjWHfddTniiCO455572GCDDdhhhx2YZZZZ+M53vsPGG29MZrL11luz3XbbTfP5R40axVZbbcUiiyzCTTfd1L599dVXZ88992SttdYCYN9992W11VZ7zyGw7+eYY47hc5/7HA888AAPPPAA6667LlAKDF144YUsuOCC7ffddddd2WabbRg+fDjDhg1rX3plgQUW4OMf/zgrr7wyW221FSeddNI0n2v11VdnxIgRDBs2jCWXXHKmQ7FmXkyv67svGj58eI4dO7bpZkiNm33wQlNdf/W1d89pkCSpv3rggQdYYYUVmm6GVNu0PssRMS4zh3f2z3JYrCRJkiSpNsOlJEmSJKk2w6UkSZI0Df1t+pj6nu7+DBsuJUmSpA4GDx7Ms88+a8BUr5WZPPvsswwePLjbfqbVYiVJkqQOFl98cSZOnMikSZOaboo00wYPHsziiy/ebT/PcClJkiR1MGjQIJZeeummmyH1Kg6LlSRJkiTVZriUJEmSJNVmuJQkSZIk1Wa4lCRJkiTVZriUJEmSJNVmuJQkSZIk1Wa4lCRJkiTVZriUJEmSJNVmuJQkSZIk1Wa4lCRJkiTVZriUJEmSJNVmuJQkSZIk1Wa4lCRJkiTVZriUJEmSJNVmuJQkSZIk1Wa4lCRJkiTVZriUJEmSJNVmuJQkSZIk1Wa4lCRJkiTVZriUJEmSJNVmuJQkSZIk1Wa4lCRJkiTVZriUJEmSJNVmuJQkSZIk1Wa4lCRJkiTVZriUJEmSJNVmuJQkSZIk1Wa4lCRJkiTVZriUJEmSJNVmuJQkSZIk1Wa4lCRJkiTVZriUJEmSJNVmuJQkSZIk1Wa4lCRJkiTVZriUJEmSJNVmuJQkSZIk1Wa4lCRJkiTVZriUJEmSJNVmuJQkSZIk1Wa4lCRJkiTVZriUJEmSJNVmuJQkSZIk1Wa4lCRJkiTVZriUJEmSJNVmuJQkSZIk1Wa4lCRJkiTVZriUJEmSJNVmuJQkSZIk1Wa4lCRJkiTVZriUJEmSJNVmuJQkSZIk1Wa4lCRJkiTVZriUJEmSJNVmuJQkSZIk1Wa4lCRJkiTVZriUJEmSJNVmuJQkSZIk1Wa4lCRJkiTVZriUJEmSJNVmuJQkSZIk1Wa4lCRJkiTVZriUJEmSJNVmuJQkSZIk1Wa4lCRJkiTVZriUJEmSJNVmuJQkSZIk1Wa4lCRJkiTVZriUJEmSJNVmuJQkSZIk1Wa4lCRJkiTVZriUJEmSJNVmuJQkSZIk1Wa4lCRJkiTVZriUJEmSJNVmuJQkSZIk1Wa4lCRJkiTVZriUJEmSJNVmuJQkSZIk1Wa4lCRJkiTVZriUJEmSJNVmuJQkSZIk1Wa4lCRJkiTVZriUJEmSJNVmuJQkSZIk1Wa4lCRJkiTVZriUJEmSJNXWZeEyIs6NiKcj4t6WbSdFxD8i4u8RcXlEzFttXyoiXo2I8dW/n7Y8Zo2IuCciHomI0yIiqu2zRcSYavsdEbFUV/0ukiRJkqTp68qey/OBLTtsux5YOTNXBR4Cjmy57dHMHFb9+1LL9p8Ao4Blq39tz7kP8FxmfhQ4Bfhu5/8KkiRJkqQZ0WXhMjNvAf7bYdt1mTmluvoXYPHpPUdELAIMyczbMzOBnwPbVzdvB1xQXb4E2LStV1OSJEmS1L2anHO5N/DblutLR8TdEfHHiPhEtW0xYGLLfSZW29puexygCqyTgQWm9YMiYlREjI2IsZMmTerM30GSJEmSREPhMiK+BkwBflltehJYIjNXA/4PuCgihgDT6onMtqeZzm1Tb8w8MzOHZ+bwoUOH1mu8JEmSJOldBnb3D4yIPYBPA5tWQ13JzNeB16vL4yLiUWA5Sk9l69DZxYEnqssTgQ8DEyNiIDAPHYbhSpIkSZK6R7f2XEbElsDhwLaZ+UrL9qERMaC6/BFK4Z5/ZuaTwIsRsU41n3J34MrqYVcBe1SXPwPc2BZWJUmSJEndq8t6LiNiNLAR8KGImAgcS6kOOxtwfVV75y9VZdgNgOMiYgrwFvClzGzrhfwypfLs7JQ5mm3zNM8BfhERj1B6LEd21e8iSZIkSZq+6G+dfcOHD8+xY8c23QypcbMPXmiq66++9lRDLZEkSVJ3iohxmTm8s5+3yWqxkiRJkqQ+wnApSZIkSarNcClJkiRJqs1wKUmSJEmqzXApSZIkSarNcClJkiRJqs1wKUmSJEmqzXApSZIkSarNcClJkiRJqs1wKUmSJEmqzXApSZIkSarNcClJkiRJqs1wKUmSJEmqzXApSZIkSarNcClJkiRJqs1wKUmSJEmqzXApSZIkSarNcClJkiRJqs1wKUmSJEmqbWDTDZDU9x2/xqiprh897syGWiJJkqSuYs+lJEmSJKk2w6UkSZIkqTbDpSRJkiSpNsOlJEmSJKk2w6UkSZIkqTbDpSRJkiSpNpcikTTTdl5in6mu//rf5zTUEkmSJDXNnktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJtA5tugCRJPdnOS+wz1fVf//uchloiSVLPZs+lJEmSJKk2w6UkSZIkqTbDpSRJkiSpNsOlJEmSJKk2w6UkSZIkqTbDpSRJkiSpNsOlJEmSJKk2w6UkSZIkqTbDpSRJkiSpNsOlJEmSJKk2w6UkSZIkqTbDpSRJkiSptoFNN0CSpK4y++CFprr+6mtPNdQSSZL6PnsuJUmSJEm1GS4lSZIkSbXNULiMiD/MyDZJkiRJUv803TmXETEYmAP4UETMB0R10xBg0S5umyRJkiSpl3i/gj5fBA6iBMlxvBMuXwDO6LpmSZIkSZJ6k+mGy8w8FTg1Iv43M3/UTW2SJEmSJPUyM7QUSWb+KCLWA5ZqfUxm/ryL2iVJkiRJ6kVmKFxGxC+AZYDxwFvV5gQMl5IkSZKkGQuXwHBgxczMrmyMJEmSJKl3mtF1Lu8FFu7KhkiSJEmSeq8Z7bn8EHB/RNwJvN62MTO37ZJWSZIkSZJ6lRkNl9/oykZIkiRJknq3Ga0W+8eubogkSZIkqfea0WqxL1KqwwLMCgwCXs7MIV3VMEmSJElS7zGjPZdzt16PiO2BtbqiQZIkSZKk3mdGq8VOJTOvADbp3KZIkiRJknqrGR0Wu2PL1Vko61665qUkSZIkCZjxarHbtFyeAkwAtuv01kiSJEmSeqUZnXO5V1c3RJIkSZLUe83QnMuIWDwiLo+IpyPiqYi4NCIW7+rGSZIkSZJ6hxkt6HMecBWwKLAYcHW1TZIkSZKkGQ6XQzPzvMycUv07Hxjahe2SJEmSJPUiMxoun4mI3SJiQPVvN+DZrmyYJEmSJKn3mNFwuTfwWeD/AU8CnwEs8iNJkiRJAmZ8KZJvAXtk5nMAETE/8H1K6JQkSZIk9XMz2nO5aluwBMjM/wKrdU2TJEmSJEm9zYyGy1kiYr62K1XP5Yz2ekqSJEmS+rgZDYg/AP4cEZcASZl/eUKXtUqSJEmS1KvMULjMzJ9HxFhgEyCAHTPz/i5tmSRJkiSp15jhoa1VmDRQSpIkSZLeZUbnXEqSJEmS9J4Ml5IkSZKk2gyXkiRJkqTaDJeSJEmSpNoMl5IkSZKk2gyXkiRJkqTaZngpEkn919pDR7RfvmPSmAZbIkmSpJ7KnktJkiRJUm2GS0mSJElSbV0WLiPi3Ih4OiLubdk2f0RcHxEPV//P13LbkRHxSEQ8GBFbtGxfIyLuqW47LSKi2j5bRIyptt8REUt11e8iSZIkSZq+ruy5PB/YssO2I4A/ZOaywB+q60TEisBIYKXqMT+OiAHVY34CjAKWrf61Pec+wHOZ+VHgFOC7XfabSJIkSZKmq8vCZWbeAvy3w+btgAuqyxcA27dsvzgzX8/MfwGPAGtFxCLAkMy8PTMT+HmHx7Q91yXApm29mpIkSZKk7tXdcy4XyswnAar/F6y2LwY83nK/idW2xarLHbdP9ZjMnAJMBhaY1g+NiFERMTYixk6aNKmTfhVJkiRJUpueUtBnWj2OOZ3t03vMuzdmnpmZwzNz+NChQ2eyiZIkSZKk99Ld4fKpaqgr1f9PV9snAh9uud/iwBPV9sWnsX2qx0TEQGAe3j0MV5IkSZLUDbo7XF4F7FFd3gO4smX7yKoC7NKUwj13VkNnX4yIdar5lLt3eEzbc30GuLGalylJkiRJ6mYDu+qJI2I0sBHwoYiYCBwLnAj8KiL2Af4N7AyQmfdFxK+A+4EpwP6Z+Vb1VF+mVJ6dHfht9Q/gHOAXEfEIpcdyZFf9LpIkSZKk6euycJmZu7zHTZu+x/1PAE6YxvaxwMrT2P4aVTiVJEmSJDWrpxT0kSRJkiT1YoZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbQObboAkST3B2kNHtF++Y9KYBlsiSVLvZM+lJEmSJKk2w6UkSZIkqTbDpSRJkiSpNsOlJEmSJKk2w6UkSZIkqTbDpSRJkiSpNsOlJEmSJKk2w6UkSZIkqTbDpSRJkiSpNsOlJEmSJKk2w6UkSZIkqTbDpSRJkiSpNsOlJEmSJKk2w6UkSZIkqTbDpSRJkiSpNsOlJEmSJKk2w6UkSZIkqTbDpSRJkiSpNsOlJEmSJKk2w6UkSZIkqTbDpSRJkiSpNsOlJEmSJKk2w6UkSZIkqTbDpSRJkiSpNsOlJEmSJKk2w6UkSZIkqTbDpSRJkiSpNsOlJEmSJKk2w6UkSZIkqTbDpSRJkiSpNsOlJEmSJKk2w6UkSZIkqTbDpSRJkiSptoFNN0BS37HPMvu2Xz7n0bMbbIkkSZK6mz2XkiRJkqTaDJeSJEmSpNoMl5IkSZKk2gyXkiRJkqTaDJeSJEmSpNoMl5IkSZKk2gyXkiRJkqTaDJeSJEmSpNoMl5IkSZKk2gyXkiRJkqTaDJeSJEmSpNoMl5IkSZKk2gyXkiRJkqTaDJeSJEmSpNoMl5IkSZKk2gyXkiRJkqTaDJeSJEmSpNoMl5IkSZKk2gyXkiRJkqTaDJeSJEmSpNoMl5IkSZKk2gyXkiRJkqTaDJeSJEmSpNoMl5IkSZKk2gyXkiRJkqTaDJeSJEmSpNoMl5IkSZKk2gyXkiRJkqTaDJeSJEmSpNoMl5IkSZKk2gyXkiRJkqTaDJeSJEmSpNoMl5IkSZKk2ro9XEbExyJifMu/FyLioIj4RkT8p2X71i2POTIiHomIByNii5bta0TEPdVtp0VEdPfvI0mSJElqIFxm5oOZOSwzhwFrAK8Al1c3n9J2W2b+BiAiVgRGAisBWwI/jogB1f1/AowClq3+bdl9v4kkSZIkqU3Tw2I3BR7NzMemc5/tgIsz8/XM/BfwCLBWRCwCDMnM2zMzgZ8D23d5iyVJkiRJ79J0uBwJjG65fkBE/D0izo2I+aptiwGPt9xnYrVtsepyx+3vEhGjImJsRIydNGlS57VekiRJkgQ0GC4jYlZgW+DX1aafAMsAw4AngR+03XUaD8/pbH/3xswzM3N4Zg4fOnRonWZLkiRJkqahyZ7LrYC7MvMpgMx8KjPfysy3gbOAtar7TQQ+3PK4xYEnqu2LT2O7JEmSJKmbNRkud6FlSGw1h7LNDsC91eWrgJERMVtELE0p3HNnZj4JvBgR61RVYncHruyepkuSJEmSWg1s4odGxBzAJ4Evtmz+XkQMowxtndB2W2beFxG/Au4HpgD7Z+Zb1WO+DJwPzA78tvonSZIkSepmjYTLzHwFWKDDts9P5/4nACdMY/tYYOVOb6AkSZIk6QNpulqsJEmSJKkPMFxKkiRJkmozXEqSJEmSajNcSpIkSZJqM1xKkiRJkmozXEqSJEmSajNcSpIkSZJqM1xKkiRJkmozXEqSJEmSajNcSpIkSZJqM1xKkiRJkmozXEqSJEmSajNcSpIkSZJqM1xKkiRJkmozXEqSJEmSajNcSpIkSZJqM1xKkiRJkmozXEqSJEmSajNcSpIkSZJqM1xKkiRJkmozXEqSJEmSajNcSpIkSZJqM1xKkiRJkmozXEqSJEmSajNcSpIkSZJqM1xKkiRJkmozXEqSJEmSajNcSpIkSZJqM1xKkiRJkmozXEqSJEmSajNcSpIkSZJqM1xKkiRJkmozXEqSJEmSajNcSpIkSZJqM1xKkiRJkmozXEqSJEmSajNcSpIkSZJqM1xKkiRJkmozXEqSJEmSajNcSpIkSZJqM1xKkiRJkmozXEqSJEmSajNcSpIkSZJqM1xKkiRJkmozXEqSJEmSajNcSpIkSZJqM1xKkiRJkmozXEqSJEmSajNcSpIkSZJqM1xKkiRJkmozXEqSJEmSajNcSpIkSZJqM1xKkiRJkmozXEqSJEmSajNcSpIkSZJqM1xKkiRJkmozXEqSJEmSajNcSpIkSZJqM1xKkiRJkmozXEqSJEmSajNcSpIkSZJqM1xKkiRJkmozXEqSJEmSajNcSpIkSZJqM1xKkiRJkmozXEqSJEmSajNcSpIkSZJqM1xKkiRJkmozXEqSJEmSajNcSpIkSZJqM1xKkiRJkmozXEqSJEmSahvYdAP6i32W2bf98jmPnt1gSyRJkiSp89lzKUmSJEmqzXApSZIkSarNcClJkiRJqs1wKUmSJEmqzXApSZIkSarNcClJkiRJqs1wKUmSJEmqzXApSZIkSarNcClJkiRJqs1wKUmSJEmqzXApSZIkSarNcClJkiRJqs1wKUmSJEmqzXApSZIkSarNcClJkiRJqs1wKUmSJEmqzXApSZIkSarNcClJkiRJqs1wKUmSJEmqzXApSZIkSarNcClJkiRJqs1wKUmSJEmqzXApSZIkSarNcClJkiRJqs1wKUmSJEmqzXApSZIkSaptYNMNkNS7bL7wHu2X55nVXYgkSZIKey4lSZIkSbUZLiVJkiRJtRkuJUmSJEm1OWFKUo/1x5Ej2i9vePGYBlsiSZKk92PPpSRJkiSpNsOlJEmSJKk2w6UkSZIkqTbDpSRJkiSpNsOlJEmSJKk2w6UkSZIkqTbDpSRJkiSpNsOlJEmSJKk2w6UkSZIkqTbDpSRJkiSpNsOlJEmSJKk2w6UkSZIkqTbDpSRJkiSpNsOlJEmSJKk2w6UkSZIkqbZGwmVETIiIeyJifESMrbbNHxHXR8TD1f/ztdz/yIh4JCIejIgtWravUT3PIxFxWkREE7+PJEmSJPV3TfZcbpyZwzJzeHX9COAPmbks8IfqOhGxIjASWAnYEvhxRAyoHvMTYBSwbPVvy25svyRJkiSp0pOGxW4HXFBdvgDYvmX7xZn5emb+C3gEWCsiFgGGZObtmZnAz1seI0mSJEnqRk2FywSui4hxETGq2rZQZj4JUP2/YLV9MeDxlsdOrLYtVl3uuP1dImJURIyNiLGTJk3qxF9DkiRJkgQwsKGf+/HMfCIiFgSuj4h/TOe+05pHmdPZ/u6NmWcCZwIMHz58mveRJEmSJM28RnouM/OJ6v+ngcuBtYCnqqGuVP8/Xd19IvDhlocvDjxRbV98GtslSZIkSd2s28NlRMwZEXO3XQY2B+4FrgL2qO62B3BldfkqYGREzBYRS1MK99xZDZ19MSLWqarE7t7yGEmSJElSN2piWOxCwOXVqiEDgYsy83cR8VfgVxGxD/BvYGeAzLwvIn4F3A9MAfbPzLeq5/oycD4wO/Db6p8kSZIkqZt1e7jMzH8C/zON7c8Cm77HY04ATpjG9rHAyp3dRkmSJEnSB9OTliKRJEmSJPVShktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm0Dm26AJM2Iv+69zVTX1zz36oZaIkmSpGmx51KSJEmSVJvhUpIkSZJUm+FSkiRJklSb4VKSJEmSVJsFfaZh9sELTXX91deeaqgl/YevuSRJktS72XMpSZIkSarNcClJkiRJqs1wKUmSJEmqzXApSZIkSarNcClJkiRJqs1wKUmSJEmqzXApSZIkSarNcClJkiRJqs1wKUmSJEmqzXApSZIkSarNcClJkiRJqs1wKUmSJEmqzXApSZIkSarNcClJkiRJqs1wKUmSJEmqzXApSZIkSarNcClJkiRJqs1wKUmSJEmqzXApSZIkSarNcClJkiRJqs1wKUmSJEmqzXApSZIkSarNcClJkiRJqs1wKUmSJEmqzXApSZIkSarNcClJkiRJqs1wKUmSJEmqzXApSZIkSarNcClJkiRJqs1wKUmSJEmqzXApSZIkSarNcClJkiRJqs1wKUmSJEmqzXApSZIkSarNcClJkiRJqs1wKUmSJEmqzXApSZIkSarNcClJkiRJqs1wKUmSJEmqbWDTDZAkqTfZZ5l92y+f8+jZDbZEkqSexZ5LSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm0Dm26AJKnzHb/GqKmuHz3uzIZaIkmS+gt7LiVJkiRJtRkuJUmSJEm1GS4lSZIkSbUZLiVJkiRJtRkuJUmSJEm1GS4lSZIkSbW5FElNaw8d0X75jkljGmyJJEmSJDXHnktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbd0eLiPiwxFxU0Q8EBH3RcRXqu3fiIj/RMT46t/WLY85MiIeiYgHI2KLlu1rRMQ91W2nRUR09+8jSZIkSYKBDfzMKcAhmXlXRMwNjIuI66vbTsnM77feOSJWBEYCKwGLAjdExHKZ+RbwE2AU8BfgN8CWwG+76feQJEmSJFW6vecyM5/MzLuqyy8CDwCLTech2wEXZ+brmfkv4BFgrYhYBBiSmbdnZgI/B7bv2tZLkiRJkqal0TmXEbEUsBpwR7XpgIj4e0ScGxHzVdsWAx5vedjEatti1eWO26f1c0ZFxNiIGDtp0qTO/BUkSZIkSTQYLiNiLuBS4KDMfIEyxHUZYBjwJPCDtrtO4+E5ne3v3ph5ZmYOz8zhQ4cOrdt0SZIkSVIHjYTLiBhECZa/zMzLADLzqcx8KzPfBs4C1qruPhH4cMvDFweeqLYvPo3tkiRJkqRu1kS12ADOAR7IzJNbti/ScrcdgHury1cBIyNitohYGlgWuDMznwRejIh1qufcHbiyW34JSZIkSdJUmqgW+3Hg88A9ETG+2nYUsEtEDKMMbZ0AfBEgM++LiF8B91Mqze5fVYoF+DJwPjA7pUqslWIlSZIkqQHdHi4z81amPV/yN9N5zAnACdPYPhZYufNaJ0mSJEmaGU30XEqS1Occv8aoqa4fPe7MhloiSVIzGl2KRJIkSZLUNxguJUmSJEm1GS4lSZIkSbUZLiVJkiRJtRkuJUmSJEm1GS4lSZIkSbUZLiVJkiRJtbnOpaRud/rH922/fMBtZzfYEkkSwM5L7DPV9V//+5yGWiKpN7PnUpIkSZJUm+FSkiRJklSb4VKSJEmSVJvhUpIkSZJUm+FSkiRJklSb4VKSJEmSVJtLkUjqUa7eZrf2y0PmbLAhkiRJ+kDsuZQkSZIk1Wa4lCRJkiTVZriUJEmSJNVmuJQkSZIk1Wa4lCRJkiTVZriUJEmSJNVmuJQkSZIk1Wa4lCRJkiTVZriUJEmSJNVmuJQkSZIk1Taw6QZIkiRp5s0+eKGprr/62lMNtURSf2fPpSRJkiSpNsOlJEmSJKk2w6UkSZIkqTbDpSRJkiSpNsOlJEmSJKk2w6UkSZIkqTbDpSRJkiSpNsOlJEmSJKk2w6UkSZIkqTbDpSRJkiSptoFNN0BSz7DgvKu2X376+b832BJJkiT1RvZcSpIkSZJqM1xKkiRJkmpzWKz6rH2W2bf98jmPnt1gS6Ri9sELTXX91deeaqglkiRJnc9w2UV2XmKfqa4PGRQNtUSSJEmSup7DYiVJkiRJtdlzqX7n+DVGTXX96HFnNtQSSZIkqe+w51KSJEmSVJvhUpIkSZJUm+FSkiRJklSb4VKSJEmSVJvhUpIkSZJUm9ViJUnqIf669zZTXV/z3KsbaokkSR+cPZeSJEmSpNrsuZSkXmyfZfZtv3zOo2c32BJJktTf2XMpSZIkSarNcClJkiRJqs1wKUmSJEmqzXApSZIkSarNcClJkiRJqs1wKUmSJEmqzaVIJEmS+om1h45ov3zHpDENtkRSX2TPpSRJkiSpNnsuJfUbE8YMn+r6UiPGNtQSSZKkvseeS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm2GS0mSJElSbYZLSZIkSVJthktJkiRJUm0Dm25Af3f8GqOmun70uDMbaokkSZIkzTx7LiVJkiRJtRkuJUmSJEm1GS4lSZIkSbUZLiVJkiRJtVnQR5Kkbnb1Nru1X97m6gsbbIkkSZ3HnktJkiRJUm2GS0mSJElSbYZLSZIkSVJtzrmU1CUOXWlU++V5BzfYEEmSJHULey4lSZIkSbXZc/kBLTf0k1Ndn4/5G2qJ1HX8nEu914Qxw6e6vtSIsQ21RJLU3xgu1WfsvMQ+U10fMigaaokkSZLU/xgu1eusPXRE++U7Jo1psCWSJEmS2jjnUpIkSZJUmz2XApyjI0mSJKkew6Uk9XNXb7Nb++Vtrr6wwZZ0vQXnXbX98tPP/73BlkiS1PcYLnuwCzfda6rru/3hvIZaIkmSJEnTZ7iU1Kc8cuJKU13/6BH3NdSSnuX0j+/bfvmA286eocf8de9tprq+5rlXd2qbJElS32K4lCSpC8xMoJckqTezWqwkSZIkqTbDpSRJkiSpNofFSlIPtPbQEe2X75g0psGWSJIkzRh7LiVJkiRJtdlzKalRHZfcmWeOhhoiSZKkWgyX6vGWG/rJqa7Px/wNtUSSJEnSezFc9iJXb7Nb++Vtrr6wwZZIkiRJ0tQMl5IkdTGHf6u32WeZd9ZpPefRd9ZpPX6NUVPd7+hxZ3ZbmyT1fBb0kSRJkiTVZs/lDFhw3lXbL887aKEGWyJJkiRJPZPhUpLUL1ksTJKkzmW47GFO//g7cxzmHdxgQyRJkjRNsw+eeiTbq6891VBLpJ7FcKl+rzXQH3Db2dO5pyRJkqT3YrhUj9Sb57k++LW12y9/7IQ7GmyJ+qKdl9hnqutDBkVDLZEkSZqa4VKSGtJ6EuXp5//+nvfbfOE92i/PM6u7bUmS1DN5lCJJquWRE1ea6vpHj7ivoZZIkqQmGS6l6bh6m93aL29z9YUNtkSSBHDoSqPaL3//vjMbbIkkqSPDpSRJkqReq+PSUg9Nur6hlshwKanXay2iNGDuBhsidSGLhUmSejrDZS/1x5Ej2i9vePGYBlsi9Wz//Mly7ZdnmX9Igy2Zvo5nXedj/oZaIkk934Qxw6e6vtSIsQ21RH3R8WuMmur60eMcgj+jDJdSQ/xirOeeAzdtvzyrvZW93uOPf3eq6x/+8OENtUSSJM0sw6UkSQ1qHYkyxxwNNkSSpJoMl5IkSZJ6tNkHLzTV9Vdfe6qhlmh6DJdSiws33Wuq6/PYi9BvPHb3F9ovL7naWQ22RD3B5gvv0X55nln9qlTvsuC8q7Zffvr5vzfYkmn7697bTHV9zXOvbqglPcs+y+zbfvmcR89usCXSzPMbU+oEzv+T+qfWNRfnHdxgQ6SZ0NUnUVwrWup/DJd9nKXru0bHs66D52qoIarlsRu2fufKAos115BOMqNBxx763qOzT1x1Rw+9Q9d6FitRN2/toe/Mq75j0jsV/ndeYp+p7jdkUHRbm6Su0uvDZURsCZwKDADOzswTG25St3N4iaTu5tqi6gk6Y7kAv0PrOf3j7wzlnHfwW1Pd1nriysJVM6/j53zewW+3Xz7gtv47fLZ1+Pe8gxaazj3fm0ORO1+vDpcRMQA4A/gkMBH4a0RclZn3N9syqR7n/zXLZTHqaV1b9CNffqjBlvRdj5y40lTXZ5nnzXcu9+D1XPujvrA/d/j3B9MTe4v720mU9+ot7ok67s8/esR9DbWkc/TqcAmsBTySmf8EiIiLge2Afh0u+9P8v+4suuFZV/UHnf05dz3X5jU9/HtmistMb7jgfINn6ZyGqUfqrdN5OqMXrTM4z3X6ZnYocmsPfcfe4vd6zftboG8Tmdl0G2ZaRHwG2DIz962ufx5YOzMP6HC/UUDbabePAQ92a0M7z4eAZ5puRD/ja979fM27n6959/M1736+5t3P17z7+Zp3v976mi+ZmUM7+0l7e8/ltE43vCstZ+aZwAefiNHDRMTYzBz+/vdUZ/E1736+5t3P17z7+Zp3P1/z7udr3v18zbufr/nUevvYkonAh1uuLw480VBbJEmSJKnf6u3h8q/AshGxdETMCowErmq4TZIkSZLU7/TqYbGZOSUiDgB+T1mK5NzM7N0llqav1w/t7YV8zbufr3n38zXvfr7m3c/XvPv5mnc/X/Pu52veolcX9JEkSZIk9Qy9fVisJEmSJKkHMFxKkiRJkmozXEqSJEl6TxExreX/pHcxXEqSeqyImKXlcq8uQteZOrwuCzbZFkl9W0TMkpkZEbM33Rb1fIbLfsizT31DRAyLiLWabofUlTLzbYCIOALYpuHm9CSfiIhPRsQawFcjYu6mG9QXtIZ2SRARSwI7R8Rg4JsRsXrTbVLXiYgdImJQRMw5s8/hTrQfMEz2PRExD7AWcGpEfCsi9oiIhZpuV2/Q8eDRv4+eKSLmioijWzbNCTxT3eZ3F0wCjgR+C9yQmS/as1tPRETLyYytIuITfta6VkQM6HDd/XHP8xywBvAgsGRm3gW+V31RRAwFdgW+SzmR8KmZeR53mv1AVuvNRMSXIuJM4PCIGN5ws1RDZk7OzDOBTwITgOWAU3xf31/LweOxEXEicFBELNFws/RuQ4CtIuLiiJgN+C/lc976Hva777CIOCoiRmXm/cALwGPAlhGxYGZOqe4za6ON7KVavis/B5wEnAhsUucMvt5bFebfqi6fHhHnAaMiYoWGmyYgIpaNiJ9l5gvA3dXmWduOM6phsoOaa6E6W2ZOyszPUNbt/Cvwg4j4zgd9nn73xdzftJ0VjIiVgD2B8cBswP9GxPaNNUwzre2AujqYfCkzzwHOA+4ADoiIYU22rydrO9MaEVsAWwKPAwsDx0bEmk22Te+oDjqfAD5FOWt+NfAhYLmI2Cki9omIbwPrN9nOhvwVOCkiDsnM7YHNq+2nR8TCEbEM8AV7MWdOdab+i8DewH3ALsCnHHbc+VrC/J7AosCfgGWBPSLiEw02TcXjwMYRcW1mjgY+BlxL6dHaobrPARGxeGMtVKeIiIXavjMi4jPAvzNzDLAZ5eTlGR/k+QyXfVxmvhURSwOnASdk5o+BC4Gbge0i4pAm26cPpppU/3b1nl4YEVsBZOYjwJXAP4DVmmxjT1adad0I+F/gC5l5BuXv4X7Kl+SIBpsnygmx6n0KYD7g/4Abgf0pJ8jmpfRgJuVkWb8QxSyZeT2wEvDliPhVZj4HHAPcA1wG/AF4qK0XUzOmen0HAFsAV2bmnZk5Cvg7cAowwh7MzhcRmwEHAQdm5rnAxZQe+R0iYmSTbevPImJQZr6WmcsBr0TEQ8DCmXk28AvK/uce4GOZObHRxqqW6rv2f4ArqtEDm2XmKxExsHpvNwMGR8QuM/qchss+qsNY+NeAFYGjATLzUcrZp98D8/bHoWW9UUuwXAw4hDIH7ZCI2B8gMycAtwF7RcQGzbW0x0tga8prSGa2HZSPBRwe26DWYXLA5cBOwNuZeSKlJ+lx4PnMPDwzv5aZL3Scs9VXZfF2RKyUmRMz86PAAhHx1+rmbwEHAvtWAVQzoO27snp93wL+DAyLiGWr7acCfwR2pIx2UE0tI0jmA56gDIE/DSAzx1IC5rNAv/jb7oky882ImL+6vDNwEXBXRGycmRcD+wI/yMwvNdlO1Vft+64DJlO+c/9Y3fRWddz5LHAFJYDOkKhGJagPaQsh1eUh1Xh5IuJaytCTjTJzcjXM583MfK3B5uoDioi/AGcBt1B6MHYF/kbpmc5qWNdQ4Odtn4P+rOoJe6s6iTIwM9+IiEUoO9DxmfnZ6n4fAv5bHcBHunNsTEQcBqxVzf1o3b4J5SB0JHBff3qPqs/vfJTw8+vMPLra/lPK8OHPZOYdDTax1+nwXbkU8BLwMqWn8hHgX8CblBMblwEbAF/OzDcbaXAfEmVJi2MoB63/AX5c3bR7Zj4fEfNk5uSm2qcyDxZYHvhcZj5d9VydDnw3M7/XbOvUGTrsAz8DLETZ3/0qM79bbV8VeAA4Gzg7M//0vs/bj76b+4XWg+KI+CYwjFJV8I+Z+YuIOAnYB9gkM8c31lDNlIiYCzifsrN/IyKGUM4gjgRuAo4H3gY+nJn/aKyhPUSHHecPgSWBR4HfUYYPXgMsDazuSZaeIyK+BkzMzAvaDjKrz/pbwKDMfL7ZFnaf1s9wdX0F4CeU8HNAZr4WEV8HhmXmTk21s7fp8F05GpiHcrJuT8oQ41GUM/XzUYZkrw9snpkzPDRMU+uwPx4AHEXpODk+ShGq71OK1O3g91f3m9ZJ1ShFIJcDDs7Mu6PUJrgCWNvhsL1by4n3BYGVKdMpJkbEOpSCZn+j5IdFMvNLETEvMEtm/vf9ntvhkH1My5fll4FNgcMohV5WiYgDMvOrwA8poVM9XIfhzWTmS8CrwK8iYoGqV/p3wO2UM07LZ+bLfjEXLQcypwILUqo/PkoZ4rZVZn6KMm/PKrsN6vg5p/Qg7QilMnK17QzKSbHnu7Fpjat60gdFxIiIWCQzHwC2ooxOuCUiPloNif3M9J9JrVq+Kz8NzJqZW1Pm/l0O7JSZ387MEZTP4UrAfsCXG2pun9CyPz6YMo/rZGDziDghM9/IzAOBcwDnCzeg5W9io3inIuwo4Hrg8oj4bGb+lbIcicGyF6tO9LwVpdrv74GvAPdExG6Z+RfK98mclH3fodXDXpiRYAn2XPYZbUOmqrHRRMRRwGOZ+ctq+MlmwJeA3bIUgFAv0HYmMSI2BRagDOVMykHOlpQhKv8HfItyZv3RzPxJU+3tKaoeXjLzpWrneQZwcmb+o5rnMxJYLzM/3/IYh8I2oOXs6VBKRdhXM3NCRFxFOSHwI2BDYPEqAPQ7EbE5Zfj73cBvMvOhavuDwMPAjpn5RoNN7DWqHrIPZ+ajEbEG8HXKfvOQ6vYVKSfs7spSjZdq//v/MvO+hprdZ0TEx4CrKD3FR1LmXB4LnJiZVzXZNkFELEqpz/E88PvM/GO1/UfA7sDHM/Pe5lqozlRNQZkrM4+pvmdOBC7NzBOq2wdXo2MG5Dv1EN6XPZd9x8HAai3Fef4FHBwRa2bmq5l5dbV9lWaapw+qOrOUVXGeMyjDX08CNgYuoATLlYBTKQupb04/qp75Po4DFqt2iG9SikN8PyI+XJ1cORtYKCI+2vYAg2X3ayvgE2Udy19Rqvh+NyL2ycxtgZ8DywBPUQoNvGvR9b5oGiMWrqP06CwNfCYiVq/mCN8MHGOw/EB2ABavPkf/oMwl+khEbFoNwb6fsuTC39sekJl/MFjWF2X5rAeBnSnF5zam/H0vCBxdnfhTN2s5biTLElAnU+YafyreWXLk/wFHGyz7joj4JKU69qIRMWv1PTMC2CYiLqz2ka9DWXniAz23x1N9Q7VzSMpcnIsolS+/QBn+eh9lmMlIYF0PonuPiFiIEiK/kZn3RcR+wKqU9/fSzHyumot2MjDOXsuiek0S+B7ltXmBsnbdMpQlW9an9IR9trFGql1EXAj8hRKWrgZupVSG/X7rMJwPeva0t4uIfYC5gaAsar0YsAflpNJKlMIaZzfXwt6n6iF/lrJvuD0zL62Gaf4PpUftL9UBdtv9B6bLutQWER8Gvgk8SZnG8QywFKWXeAVgy8w8trEG9lMtI0eWoBRyeYpSLHAC5RhyDcqcy6czc5vGGqpOF6Wo546Uec43Atdm5lMRMQewYWb+dqaf25zRu0XEHJn5SttlytjodSiB5J+UAiZ7U+aZ/dhx8j1fROyamb+sLn+e8l4elpk/q7Z9hnLm9/rMPLsa9rlyZt7dWKN7iJYvyqCUsT8XGEip/vgaZW7l1pS/ja9l5pSOBVPU9VpDYjUMawvKSbHfUwpWTaQMh72LUkzlhf72HlV/5/9HGa1wJKXn4AhKb9tiwNKZeUtzLexdWkNiRCxAOdm6KnBnZp4TETsDnwfGABd5Era+jieDolSdXIryuZ4FeIMyXeE3zbRQUNa0BG6gnNj7GGWE26mZOToiFq6u35qZrzbYTNUU7yxntwHwUUqxslOAz1Jyw2PAda2jNGZ2utDATmqzGlCddfhsRDxAmYz7UGZ+PSJ2B75KGVL288z8vfPJer6W92ilqid6cJYKv0OAnavbf5qZl0TEU8CDUNajoszF6tfaJqhXV78KXJiZu0fEMZRhsj/KzPMi4nwow2D7W09YT1DNeVsxIu4HdqPMGbyYskzShMw8vxqOcxdwevazAj4AUdaX25VyEunTlIp9twE/pXyOf03p2dUMagmWPwN+TVkIfjNgs2qI8amUAP+435X1tRQMmY0yp3JJSnj5E+Vk0pHAtsBREfE7quX2Gmtw/3Y45b05m/L+nAnsFxEfqebe/b8mG6f6WoLlspRlf/6Xss+bLTO/HRHPUU64PUUZ7QjM/HQhey57uYjYFvgZ5eBj/XxnTcsNKTv0u4GjMvP15lqpDyoitgKuBYZn5l1RKhruCTySmUe03M+TBh1ExLmUfdteLds+TSnccR7wM1+z5lRnwveh9BqtCWycmY9FWXt0HDCaMkzu762f9b6utde9OvGxAmW+yxjKwfhclED0z9bPtqYvIhanjOg5JjNfiIgTgcsy886IGAx8nBJyBgL/l5mvu1/tPBFxBfAQcC9l+N0/gW9Vo0aWBZ7NGaxAqc7R8fMdpcjSRMq87tsy80cR8UvgI8CozLynoaaqE0XEQMrUuSt5Z23Z7auhsAMpJ4AmdMYJdwv69FJtBR+yVFf7JaWy1xeqcfNkqfC1B2X+iMGyl6nGuu8P3BgRu2TmNZQ5QstHxEYt9/MAqEUVyj+amXtFxNIRcVyUReb/Tjk7+y9fs+ZUAer/UYZgrQP8FZg9IubOzCerbVOAG9qCZcfiNn1Rh173Y6oegwco63o+WB18f4xSfObAptrZS81Fmbd6RkQsRalOOhQgM1/LzD8Al1KGwrYVr3Af0Qmq0DJHZh6WmT8HjgHWrf4nMx82WDYnInaOiG2yFFl6lfK30TYKKihrWxose7GIWC8ijopS9XUKpbbB0pSQeUgVLPcATqAcH73VGd+59lz2Qi1nuD8ETKYcgMxPGcrwBPBdyjjqizLzsuZaqhnVMmRhVUqPzt8z8+8RsRZwDXBGZn4zIuZLl5J5T9X8vWMoPV/3AG8DTwNPZeZZTbatv4uIpSn7qSeA7SjDPD9DWZ/16sy8Nsraak9n5r+rx/SrYcsRMRp4PjO/XF0PylzUeSlFNfauThzqA4iIJSknW/+HclJ9CmVkyDLAEsBpmTmuuq+9lp2k+vyOBq6jFKCbHBGrAXtReoktlNTNWkZGbAt8g7I83f3VbXsDh1CGRv4zM/dtrqWqq+qN3IYyYmASZRjsGpTRMGdU0+iWo6zte0Bm3tRpP9t9aO/SEkIWAi6kTMB9mjK/8p+UUDkPMDQzt2iupZpRLe/pcpRqhX+jHEyOpewMBlGKeByXmSdVj/EAiKlOtMxD+dxPphxArgyMzlJN9yeUA/Yjm2xrf1bNIf44JVRuAfwpM/erth9KORnwAmWe4arZUq2zv6hGJByemVtFWWtxF2BxyhDijwJvZeajzbWwd2nZN8xHWSP4VeBTlPWeF6DMOVqQ8rqe11xL+46W13xBYEhmPhKlMNVGlNEjd1DWUPxXZh7WYFP7tSj1Oi6j/C08BmxPWYLia5Sh+PNk5t/f8wnUq0TElyjfu/8CjgdWpCxndzvl5NoFWYqaddpxpeGyl4qI6yhzLeeh9NT8nnIwfXNVDOJlh8P2HlWRk58B12Qpjb8mpZDHW5l5XHUGuHXoXL/XEsoXpOwoh1B6K/8MXFHNrzoa2CQzN6keYyhvUEScA2wK/AD4bWY+Um3fBpiDMqd4XPSTCr4tvQhB6UW7jFKo67+Ug75hlCqNpzXXyt6n5XWdhRJoflodPA2hrK24C/Dn1te1v/WSd7aW/fHKlAJdk4DnMnPHas77ZpRKsRMy86DmWto/te5Tq7+LCylDxp8FXqr+rQV8Oq0K2+u17AN3AA6grIH+YcoUuu9S3vf5KAV9/tH6mM74+c657IWiFOv5HWWoyX6Us02vAN+LiFGUXhqDZe+yJWUuyicBMvOvwCWUxWyXy+KtaFnsuL9rCR9nUP4eNqUUhFkFWCdK4ZjXKQeSbQePBstuFBELR8ScUZZJgrIEwX6UpTR2j4hVqu2zAFdWwTL6SbAcUH35rwrsWQXtL1PC5TGZ+W3KWnOzN9jMXqnl7/xHlLoD51TbX6Cs53YWsGaUIlJtjzFYzqS2v9koS1ocApyQmRsDAyPibsp6ogdR9sUHN9jUfqlDsPwSpcd+f8r+5ReZ+b+U0W9R/VMv1hIsZwN2B47IzEN4Z53ZHwCbZ+a/uiJYguGyV6rm3JxOORN4U5Y1EcdQ5jLd0R8OzHq7aUyYvp7yhz8kIg6rdgqPArMBb7bdyfcWImKllstDKF+G4zLzNcq6ls9SvjifBn5QTVi317ebtcy3uhs4OiIOzMzJWda0Ow+YFdgrIiYAq1fvX78oplJ9kb8VEUMp++7JAJl5W2YeXX1mTwKGZeZ3G21s7/YMZT5R274CyuduHLBfZj7ZGcUr+rMOB6WHU5YUegQgM7elFO96MiLWz8xX+8Pfd0/TEizPokxPeDozn8vMAzPzxoj4BPAr4HtZrZuu3ikivggsX119o/r3GYAs61deRZkWsHzr4zr779Jw2Qu0fflFxEYRsUuUindQDp6/XA05ORb4fWb+raFm6gNo+0OOiM9XQzf3AW6i7OCHUeZd/pxyBvhf9lgW1d/CyRFxXUTMW/VE/BnYNSJWrQLkqZR92/xtX6qG8kYMoHym36QcYO4UEedExDco78/3KUVVjsrMYxtrZQNavsi/Q1mL+LKI2DQiTomIb0fEAsDLlHVANfOSMqJn1mpfAeXgalhmvgj942RGV2r5LluYMi3hJWCLKJViycyvUoblqUHVceLHMvPzwMIR8dWI+EE1cmJR4JTM/F2zrVQn+FdmPhARm1NOvH8LWCAiDqpuH0TpiDoFuq4au3Mue7iWeQxrU+aVTaD0zFyTmaMjYldgR+ChtGBJr9AyZGFzShD6NmVi/V8ow7jmAEZR1l07NTMfbqyxPVQ1d28VSgXIyZSeyoUpJ1yGU3rwj26uhQKIso7gFcC1WdZOO4h3hvHfQNmPtfUs9bs5bxGxG7A1Ze7LI5R9+0LA8Zn5nybb1tvEO8VkVqIsNfKvLOunngB8lrKv/STw72oYoGqIsrTBa9XlrShDu0dExHrAFyjFQ35LGVXiyb2GRcRHgSOADwGPA3MC/w+4PzMvbLJtqq/D0Oclgd9QOiguphQ5/Ayl0GHbEjM3d2UNCsNlLxClQM9PKEMWxkXEF4C1KdVELwH+6867d4mysPeRwPWZeUWUktE/BZbIzM0jYg1KZcOPAodlWRuwX4sORV4i4khgT8qBzD8oO9B1gccy84LqPhbwaUjLwf4mwOaUsvdtQ/pHA/tSlkt64b2fpe+IUg16CUroebTatgSwITA4M8+q9vU3Antl5t3v/Wxq1fJZW5YyzPh2ylpu11JOym5KKZj0Smb+tHpMvyga1RWqkTTfBP6TmT+NiBWAb2bmZ6vbPwocBAwGvp2Z/2yssf1URGxNWU6kbU7dnMAngE2AkzPz/0XEGcAz/W3kSF8WERtTRnMtSRkddD9wZmb+sxpN8HJmTuzq/Z/hsoeKiF2ruZRExAhK8DguM9u6srcDRgK3Aj/2ALp3aOm13J8yFHYs5X2dWN1+DWUtu6cjYnlgzqzWX+vPYuplBdalVBV9qDpjfgblAObsDo/x4LEHqN6ziykh6ieZeXC1vb2iZ394nyLiEkrhrnso4eeXlF60SdXtgym9uddm5ncaa2gv07JvGEiZX3kK8BplfdDfUUYz/Ky1J7g/9pJ3poiYl9IbPAx4CLgF2DEzj255P5YA1s3MMc21tH+KsoblFZQTVa9TTuw92xryq5OzWwIbefzYu7V8l36ectJ2j8ycUM0zP5Uyz/yUzBzbXW0a2F0/SB/YCtWX5RyZOSbKukQjI+KtzDwtM6+MiEmUs+DuGHq4tgPotvcqM8+IiMcoc6o+FRH3Us7yLg+8Vd3nH401uAeJqYvxXEZZAP2ViJhIOTO3DXB9RCyWmd9se1x/CCw9XfWl91xE7EkptnRVtX1gVguo96P36RTK/NNjKXPQtgM2j4gfUA7Q5wd+mZk/aa6JvUtEfJyyP7iD8vr9HLiXUiBtZ0pV4lMoVUu/ldUSCwbLejLz+Yi4iDKsciPKKJxNqtD50Yh4hTKCxMqwzbiZcvLqQmBVSpXeZSJiPGU/vDjwIrCrx4+9XxUsF6dMD9qtCpaDqlFBe0XEyZQCoN0WLu257GFah/FFxAaUncQnMvO2ao7ePsBEylBJvyB7gQ7v6TGUOYLPUYYGrkkZPrQ0pYLhOZn519aDbxURcRzwRmYeHxGrAesAH83MQyJiIWCudJH5HqNlvnhbMarDgWUyc98m29WU6mThFZSD7v2r4UtXUuZa/5cyhO2oBpvY60TETpQ1npcGJlYnMlYGjs3Mnauwcy6lFP9DDTa1T5hWj29EDAf2oizM/jvgasr322uZ+Vz3t1IAEXEgsDewfma+FBFjKWtB3wosQhl63++n2/QVUQp9/hj4QodRGqtk5j3d3R4rUPZQETFnZt5C6eK+NiL2zMzrKNUFl6KchVAv0BIsjwdWogxTORg4jbJQ+kGUBW7/C7xZnXEyWLaIsh7iSGA5gGo+2k3A6hGxemY+lZmPRrisQBMiYkD1/8IRsUpEzJ0tlXqryxdSlobod6oTTFOAXYGMiO0pxbv2zczNgeMoc9g0AyJivojYMDMvBeYGvgd8vipk8U9g1Yi4mtKDeb3Bsr7qM/xWdfn0iDgjIk4D7qIcl1xHGXmzSGY+abBsVmaeRjl5tVNE/JRy8mU54ETgQINl79b2ndviccoalutGxFzVfbanLAPW7WslGy57kHhnUe0tgbMjYv7MPJdSTfDEiPhuZo6nzMn7faON1QdSnU1fNjNHUKqcjgdeoAzZWgI4ijKsaw/K+HhVquIQ/wYOowy5+ia0DxuenVL9jmqbQzG6Wduw5SgL0v+ecrb8n1HWTmu7z8DMfDwzj2h7TEPNbUS1Xw9KldwnKUVmLs7MX1V3eSAzX2+sgb3P+sCLUQogPUMZarwapQdtAWB14BrKPCOHGddU/f22nSTdg1J18heU76xbKVM5fkQZ3v1yU+1U0XKS9TbKiex1MnP7atsjaQX6Xq3DiZ6REbELpUL2WZTRjd+JiB9SViI4JTNf7e4T7w6L7WEi4iOUCrCHZOZNEbFgluIu8wIPAj9NK3v1Ch2Gwy5IOcO+NHBoZm5ZTbo/FPh1lmUa5gAWzcxHmmt1z1ENI5yfUizic5l5V0SsS3nNVqYUK5iUmcc02ExVohSsGU0Z5nkrsF5mPtlsq5oREYtm5hPV5akqFldf8pcCd1VDvK1o/AFExFqZeWd1+VRKwZ4fU/avR1BGhlyUmX9teUy/KBrVFSJiVsoB628pyz3tCVySmTdUt3+LMr/1C5n5p6ba2Z9FxJDMfGFa+5KI+CqlcM9WmflGMy1UZ+lwXPlNYHvKKK7Ngc9Tps1tBMwL3JOZf25i/9evzh73EltQ1qeZEBG7A7+PiDOBgZm5EHBCo63TDGnphZ6rOjHwQjUf8E3eObO7FPDnzPwRQGa+YrB856xrZk7JzKcpJ1vmq24eSwmXN1OKEvy8ekzHISLqYtM4E3oLpUjE5cD+mflkROweEVt0f+uaU/XKnh0RV0XE7C29lu37BeBkYOWIWNxgOeOq+X2HRsSB1Wt6DaWn8iBKgcLDgJeAUVHWhjZY1rcSpVd4N0qwXAP4RPW9RmZ+ndJruWND7evXoqyVe39ErNrhJFbb8f2PKSdgNm2ifepcLcFyLcq+7xOZeRBlWsUYYJvMHJOZP8vMP1eP6fb9nz2XDev4xRcR6wCjKIVezqP0Vm4F3NIyhEo9WEy9mO2NlEVr/0LpabuRsgzB65QzSxtn5jMeABURMTQzJ1Vh8SxKYPk8JZAfQnktn6PsVLelVNzcOzMfbKjJ/V6URepfpBSLGAF8IzN/ERGDgDuBozPz2ibb2IRqzh+UoP3vDmec5wO2yMyLm2th71O9bptQliN6mjJvfUnKUGyAq7IUv/sa8LHM3L2ZlvYtEfE/lPD4ImX43VqUwj2/zMynmmybICIOo8znPmpa+9oo1bovy36ypnBfFRGfBe4GHqHMJx8C/C8wLjOnVCfUrqKMjvtFcy11KZJGVQcbbSHkVGBCZp4SEW8Cr2fmvVGWIGk7I6FeoOU9PZiyaPwYSgjaFhiQmWtFxDKU3sxnwjXXAKh66leoDgwXoBQ7mhP4F+8cPL5FmZM6AjifMrTQYNmQKBWtl8tSmXM+YG1gnShrtK5HGfLdb4JlvFMhdwFKYZnNgLERsVPbkMHq7/05ytqf+gCq1+3SKNWiPwcsBPyQsiTRAcBuEXEH8DfKGoyaSVWv+kSAzPxbRLxAKar2X8roqk9Qet+/kZn/brCp/VKHIbAvAJOAqyPiiMz8XnWfAZn5Vmae31Q71TkiYhhlZOOylDn7Iyn7vb2A/0bEo5l5R0SslJmNF86z57IHqMbEbwaMzFJK/UNV6Pgo8BPKoto/bLSRel9t8x6qy58BzqT0Tvw1IhYDPkUZUvQAcHpaEbZddcbtTGCfzBwbpVryyy23n0Y5S35HRCydmf9qrLH9XNtBTTUs7gTKF94WWar1zk6ZnzUZeCszL2p9TGON7kZVr/sfgbMy84KI2J9ScOarmXlBs63rfSJiYeA7mblXdX014BxKr+WClOkFZwP3A0tl5j8iYh5gSus+RDMuIpagfIaPz8xzWrbPSzmYXYJSofebwLczc0IDzRQQEUdQClxtW/1/NnBTZn6x0Yap00VZ13cbygiui4D7gB9Q5kKfCtzZdlzZ9Gg451w2LCIGU+Y07EmphHksZfz8fpS5I6cYLHu+agjg7yPi6GrTDcCfgHMj4iNZ1h26kDI89h6D5TsiYlHKgs8HVsFyOOV1mzsiZqvuNj9lkjqUkttqSBUs58nM5yknv24FDo5SaOXVzDw9M3/REixn6S/BsjKQ8hm9CyAzzwCOAc6LsvacPoAsSya8GBE3RVlq5BTghKo35lrKELGvAUtUwXKWzJxssJx5VU/kl4B9o6wv3Lb9+cw8hXLMsmhmjjJY9gg3Z1ny6RbK3MqdI+J3Ld+f6sVa6lDcRum1fIVykmfDzPwKZaTG14HBbY9pepqV4bIBMXUZ/jco88kupZzdfpgyx2xbypnX33R/C/VBZeablPftMxHxnepLeDtKMZpLI2KzLAV7zsvMPzTb2h5nLWAQZT4PlKEeN2Xmi/nO8gxXUob9YDDvEX4QETdR5oQfRZn/tldEbNfxjk1/yXW1joWNqs/sM5QKmm2upRwU3NWNTeszMvNAyomMfwF/y8xLq97w+yjfnT/Oai3Lvv556y5ZljvbizLM/fwON89CmbqgbhbvXsbpXmD9iBgCkJmPAz8F/pIub9QntJ6czcwHgJ9RTmBuFxG7Zua3KbUnXmqqjR05LLabtY2Br3osl6UspfD/qu7uRzLzqYjYgTJJdzO/KHu+KGuATYmydMZplIn1fwe2rYY57wF8l1Kq/erpPVd/U/XkPEMpcPR5yjypn2Xmd1rmr+0APJGZd1SP6TdDLHuKjq951VP/U8qSMJ8BngX2Bz5KGf7Z7wpHVEPh56HMC/4NcBnwD8pwzV2Ak9KibLVExIqU4Zp7ZeY107jdfUMni4gPUXqLV6b0wO8G/Dczv9xow/qhluPHRSiFrRYCTqcMjVyeUql7ODAoMz/fXEvVWToUgpsFygm0agrK54ANgZMzc3xzrXw3w2U36vAhuYJS9XJWytnsC6p5lnsBXwF2cF5Z71H90f+JcsD9J8pctNWAnTPzvohYDxifma802MwepZqbNgKYjbKkyKaU4W03ZuY3q/scQDkw39Aey+ZVB/ePtQ05rIovfY5y1vSOiFisGgLer0TEVpQFqw+mVITeBLiDUvn7LcrJ5zOaa2HfURVLup2yluU3Gm5OvxERh1KqU76amd9puj39VXWs8UfgXMoSPPdl5ueiVISdjzL/7oT+eIKvL2k5ub4I8CowuJoi0DFLDOtpwRIMl42IiO8DCZwE/JnyRTmZMkF+VmBIZjp8qoerCkuMr+agLUEZqvD5rCp1RcS5lF7MrTLzxmqbS460iIgVKH8H51VD3VanzPV5hXJwvj+we2b+09eu+3X4ElseGE1ZN+1XwIvVl9+vKcWqhrUNTexPImJOyutyGLAKJWhvVfXuvp1Wgu50ETEr8HtKAbB/Nt0eqbtExOGUed2nUpajODoz/xARc3jyum9o6aH+CKUexW8pSxLuW00FaL9Py2N61KgN51x2s4iYC3gIOBo4g7KW5Q8pXds/Ap41WPZ81QHllsDcVWXTf1NKtLcuVPwD4GagPRAZjqZWzR84FtgnIjaoPvs/oLxmFwDHGiwbtUJEzB4RG1Mqc36VMgz2gOo6lDk/e/THYAlQ9eL+iVLFb3/eWTbnKMr0BnWyzHwjMzeu9g3x/o+Q+oy7KFNJLqeMePtDdaL7tIiY37+H3q8KloOAXwDHUTLDQOA/1XY6nrTsScESXOeyW7R0b3+MUvjiPMrcnNcz84TqPn+nLLXwXINN1QyIsp7fksDJlDlmp0bEFygnC86OiKUoa9x9CTgtM2/uaWeVeoKIWJkyl3JcRJxN6fW5JTMfjIhTgF9k5t3Va2ew7GZRlnPYjPK+bAbsl5m/jYgJwInA8VWP/astw5j7/EmAjmeMK89RCs7slJlPRsQngc9STkCpC7lfVV82jWOH/1Cm3/wjM39a9eKfDFyZmf9tpJHqFC3fp5Mo04WuB8ZS5vAfmpnPR8S2EfFYZv6tyba+H4fFdrGWYDmc0iNzUHXAPCelhP89wBScgN1rRMR5wENV0ZklKXPO1qUUO3iOd3orXnJO0NRa/h5WowwjvJ2yXtMgSs/91dlhLUCDefdreZ+WBq6hnCk/EJiQmZOjlLjfhPIF+NvMfL0/BMtWEXE6Zb2x/1KmNGxH2Qf8hXLS6ajMvLmxBkrq1dq++yJic8qIiEcp1ZGfBa4DxgPzUuZd/l9T7VR9EbEQpXDWrZQw+Xj1/yeAz2XmFdXx5tWU6VeGy/6uGgp7A3BkZt5UHbAtRBnecAzwWmYe32QbNeMi4v+AuVt6a+anDIkbAZydmZd1uH+/Ouh+Ly1flMMo1XNfB+amnJ07G5iLMo/kJ+kSPI1p/bxGxJaUM+WfApahBMnLImIZYGBmPljdb1q9eX1WRGwKHEFZNucTlEqaB1PWJp4dmDUzH2muhZJ6s5bvyyGUJc2upSxd9yngHErIWA4YkJn3NNdSdZaI2IzSWfEQZSTMUMqx0iuUddKPAUZn5umNNXIGGS67SIdCGCtSei2/D6xBORj5MHBhZn7fnpneISKWyswJEfFp4BOZeXi8swzJfJTey68A12XmD3xf3y3Kci2XUAr4XFmdkd0WGEA5a7cSsATw03SNrkZVQ5PnyswvVNf3B9amDPn+CvDpLIs69wsdenM3BZ7OzKsiYkHKPNRPAZdk5nn+7UuaWS0FXQYAGwGrVceKc1COH/cBJgCHu5/p/VqOI9cGvgGsSVnK6hzKyd2DKEU/n8nMn1SP6dHfMc657AIdguWywCPA7yilo79PGV62KLCzvVq9Q1Up88KIOIkyFG6xiJg1M98AyLKe5Tjgm5SF5Z0LNG1BKau9NEBmXlcVIPg2sBOlxPqjBstmRcSOwNqZuV7btsw8IyIeBBanrDN4W0//gussLQd7wyj78VmBxyPizizrFP8ceJGyX/dvX9JMqY4J20aB/JqyvMhyEfHnzPxzRNxACRp7UHq2nm6oqeokVbBcgjKCa0fKyfb9KScRzsnMQ1vv3xtygz2XXSgiTgAWAfbPzFcjYp5qvtLClN6bszrOL1PPExFDMvOFiBhJ+WN/FFiPMg/tGWABSmh6m1L05KH+ctD9fjoMsZw1M9+ohlpuQxlieU01rPh8yhpqP8nMMc21WAAR8Tlgncw8sKXHblZg/qzW2qru128+59X0htMp4fKvlMJsLwHfz8x/RMSgzHyzyTZK6hsi4n+BJTPz0OpYclXK/uf6an/s0iN9SFWX5fvAlpn5WlWX5VLKFLqvZuYNjTbwA3Ipki5SnfnfEPhiFSzXBJavPjDHADcZLHu+ahjKIRGxYGZeDHyNskjxIMoJgl9QKmceCnw9q+UY+ssB9/tpCZb7AD+IiN2B2ygBfcfqLOxNwLcoAXP5qidT3ajtNa8+71AKRXwsIjZvOUP6XUoF5HZ9/XMeZcHyNhsC21OKr70K7EYJl6dHxFoGS0mdISIWp5zIblt24muUOZZHAl+sRlIYLHuxDt8tAOMox0U7R8QiWZa4Oo0yEm5sd7evLnsuu0g1P2l+4GFKKf9PUw7YTgWeysz/NNc6fRDVWcPFgAOrHsyhlPfxSeDHmflodb+2Cfj9pjdnelqGEn6aMuz1B5QTK+cBP6MMLVwNeIIypPAaYERmjm+mxf1bNR/2WuAqyvCcL1GW3FmEsh/bEli3vxTu6TC94WzK67I+MBw4OTOvqW77GnBZljVbJekDaxkhsh2lNsc/KHPtLsnM71X32RFYJDPPaK6lqqvDd8s6lFFbN1Dm8u8CvAA8RVnO6ouZeWdvGArbynDZSSLiJ5QJ1g9l5uURsQYwknIwchxlofFjgKsy8+rGGqoPLCJmB75OKRF9YzVkYSClAM3/AF9oq5qpqUXEYsAJwK8y8zcRsQhwASWYH5mZT0TEYMpwn6sy86oGm9vvdDwREhFbAMdT5vr8gjKHcAtgEnBNljUc+1tl2JHAFpm5V5S1P7ejzA++zoM8SZ2l6rE8ibI+9u0RsRHwBUrQONreyr4lIo6kZISngY9RpgvNDXySspzVn6vCh72uw8JhsZ2gGkr2EWBrylC/WygHZTdn5rqZ+VtgRUoQ6TfVFfuQ1yhrDo0EVo+IuTNzSmb+L6U89MONtq6HiYj9qrNxUCroLg18Nkq13Sczc3PKDvTrAJn5GnCwwbL7tZw9Xbf6XP+esqTOpylrNz6amd/OzLOqYDlLPwuWS1B6DwYCZOZkSg/mmZR9/cbNtU5SX1ENk9yPUim0bWmRv1DC5oeAYxtqmrpAlEr5O1CmWkym9F5OABavvm8Pz8wrm2thPfZcdpKIGEFZFP6TlK7t5YAvAxdTqsX+HzAyM+9qrJH6wDoMXzicUsjnCuDhzLy15X79qjfnvUTEIGDVzBwXEZ/NzF9FxPqUoR7/Bn6T1ZpcETF7NR+5Vw336Guq92cEcB9wZRUi56quPwJsn5kvNtnGpkTEh4BNKHOdLs1qPeLq9Vk4XctS0kzqcHwxiNIBcRKlJ+vgamTPAGApyjIUkxtrrGrrUODwfygdF2sAn8/MrSLiZ5Se6i2AG3pbb2Urw2UnirIu3CuZ+bWIuIhSTviflHlLl2TmZY02UO9rWsMPWoNjRGxDmXO1OKU67Lcpc2gdrtIiylqAPwHuB46iDPnYDUjK8MpbeuNQj76iZX7w1sDHKYUEVgUeo7w/D0fE94FHMvOnTba1O3Wc3tCy/eOUXoVnKIW7XmimhZL6gg7Bchlgjsy8J8pqAv9HGfHz/cy8o8l2qnO01KCYF1i5rXOiGhr7ZpZ1TL9AmVN7XJNt7QyGy07QcqC2OqXC10BghczcoLp9/sz8b6ON1AcSEasCL2XmP6vrrQFzbkqw3J0yD/M+e96mOX/vo5QD8oUovfpQvjQvyMy/N9BEMVXhiIUpJwD2q3orP0WpiLoY5eTJPzLzi62Paa7VXa+a3nA5MJjSy/5RSi/CE5n5lyhr3e5HKUS1X19/PSR1vaog2JrAHMB/qrndAynfldsAuwKPeyK29+pwIuEGylzKY6rrn6P0VL4IbABslJn/jYiBmTmlsUbXZLjsZBHxHeBwypmJ+x0u2Xu0HHRvSClCMx74UVuxnv5wgD0zqmE7A7KsYflZSnXkuSlLV8xBGXK5DvAd4K+9eYfZV1RB6kTKMKzDM/Mv1fYVKCcDVsnMH1Xb+s3nvsP0ho0oc+W/DFwE/Jmy9MhdmflsU22U1DdExLaUIfefAH5MmX/3HPDxzHwmIlZ3KlXfERHHAktn5p4t2+akvO/zAndk5ti+8J1rQZ9OlplHUpZcWD3KovEGy16gOrP0dtX7fCzwW8rZxL0jYp2+8MfehQ4CNo6IdSmVke8ClqD8HcxDKQzzR2Adg2VzImKhiFigurompVjE/6O8d8sDZOYDmXlzS7Ac0J8+95k5BrgFOKSaxrAiZXTC25Szyy8YLCV1kjeBvSlTRoZm5oKUffJTVQE8g2UvVn3nrtayaTJVUc8oVfKh5LCrM/OMKlhGX/jOteeyC0TEZ4BPAfv0hQ9Jf1H1wJ1DGbJwZpRlM46m9MR9A7jFcDS1qsLdNylrIb4E/CszT61uOxLYk1Ix9tUsC89Pc16rulZEzEopNLYqJST9LTMPjoi1gS9ShoH+ltKz3C/3WTMwvWFoZk5qtJGSeq1pjWSr9s2nAHdm5gUR8b/Aclmq0asXi4gvAzdRCjS9TumhPoWyZvr11X1uBn6emec21c6uYLjsIhExV2a+1HQ79MFUgWhR4Nhq3PsASk/GfcB3MvNfjTawB+lQ+Wx3ylItbwNfzWpB+Yi4GPi2cyybVxVZ+gWl8uB+WS39EhFLUobyA3wjM59upoU9xzSmNzhyQdJM6zDv7jDgLeBPmXlnFShXogyJ3RDYysqwfUNEzE+ZInQbcCnl5O5XgAeBuYCXM3Of5lrYNQyX6rc6hKO5MvOliFgROBj4DXA3ZdjKGZSd/uTMPKip9vYk0zrYjoiVKfNH/g48BPwHuATYODMf7f5WCqaaSzwPsDJlLuFclAqxP6/myq5DqVZ4Y4NN7VEi4iTgb8CvMvONptsjqXfqcKzxE2AZ4GbKyJ5jKcub7U2pEHtpZt7eSEPVKVpGwSxImb//IWB1ylSUG4AplLWkH8/MK6rH9Kn6LAObboDUlJad/bHAR6sqsJ+lBKIdKJUhPwQcQClQs6NDOouW1+77lJ7eSZTKo4cBXwM+TymAsndmPmrPTzNayp+vBxwDfA4YR6lAuDowV0R8Grg2M0+pHuNnvLiDMr3hoqYbIql3incvZfZmZm5eXf8zpZDP0pn57QabqU7S4fvzIMpyXqdGxGaU46L5KCcsf9TymFn6UrAEC/qon6qGuxIRm1IOIE+gTLa+n7IEw5coi9nuTFno9jvAaR50v6OaqL4KcBZlbcAfUIb2HAhcD/w6M2+Ad8KoulcVLBcCLgBOzbIk0iDgPODXlGU3JrYFy+oxfsaBzLwE+F8/u5JmRjWfclRE/E91zLE/8PGI+Hi11MTNwLbAnlWtDvViHYY+n045PhoLUB0LfQ9YjvKZmLPtcX3xO8Zhsep3qiq+b0RZh/FQ4P7MPK267Yhq21cy85fVtsOABzLz6sYa3UO0DLFcEtiEsg85txpyuQWl6t2NmfnDJtupd0TEdsD6mfnViNiPsj7r/JThyv9peU979bpaktSTVCdgv0SpAHsR8BglYMxf/X9/Zk6JiNky8/XmWqrOFBFbUaag7ANcmZmHt9y2EKUy8L1Nta87GC7Vr0TESOC5zPx9RAwDjgdephSd+Vt1n52BfTNzi+Za2vO0DLFcmrLY/GuUXrCRmflwRMwGbAwMz8zjm2xrf9ZxWGtELEepWPck5X07n3dOqpzVSCMlqR+IiP8BPgPMCVyWmbdGxDeBYZSpJH/IzDcbbKI6Qcs8yzWBb2XmltWx0mWUKRYH9KeTt4ZL9RsREZSlBe6PiAOBa4BXKEtpPAdcRVkg/bWWHYW9OS0iYiClwNE1mXl1RJwBLAR8PzP/Ui1NktVr5zzLbtZhWM4GwFOU4kpzA4tXn/35KEUFDm8btixJ6hwRsXhmTmy5vgSwC7AYpSfrDxHxVWBt4HMWDOsbqg6LU4ErWmoYzEGZgjIU2KS/rCLhnEv1C1WvW1YH14sBS1KKzywGHEIpC/4FYIMqIAFgsHyXrSlnYRcByMz9gbuAkyPi05n5dlu4MVg2pxr++k3KOq1nA2tXn/15KfNhxxgsJalzVUHyTxHRvrxEZv4b+CnwMLBvNTXnJErBO4NlL1Z1WrR5lLLCwC4RsQBAZr6SmZ+ifOf2i2AJhkv1Ey3V2g4D5gV+Rinesx+wAeUg/AHgmdaA1N912HEC/IESWnaJiFEAVZW7cyjzStSgqsd4deDzmbkx8CqlgMBnImIE8BJwaGZ+D6b5/kqSZtL/b+/O4y2bzvyPf75FGWpQyhCziJh+5jY1MSsaEUQibYwyRDUSCSFiKEPoEBFzgiSGhE4pU0w/QojQ5iExD4WYJXQQUyFIffuPtQ4n1YWqW/fefc+t7/v18qqz91m77nqpe+8+z37Wep4aSO5GCSIPbzv/Wq0QOozSyxLgjQamGN2klbRQMbftN2yvT6nIfnVtbQeA7WNb1zQ1396UViTRr9X2IpvYHltPLQWMsf2cpPGUCrFfBhZtfeCO/0vSOsBClCdzl1KewO4oaT7bh9o+o7nZRdt+2MHAAsBetcXIEpS2OidR+re+Z/vX9ZosW46I6Ga1psPTwEmSfmF7x7a3Z2gbl4fYHapuQWm1DzkDmFnSK8AZtneXtDdwnaSdbP+mdV1/aznyUZK5jP5ueUrZ5wPq8XhKFS9sPw+cT8nGvdjI7Pqwtn2nmwI/owQqP6D0An2GsrdghZRQb1brJlefiJ4OPADcQclY/tL2S8CNwE2UfcZAli1HRPQU249Q+gpPJ+luSZtKOg94zPY1DU8vplJbbYMjgb8D36X8e+8raYu653KP+t40JwV9ol+TNBOlWfzulGWb7wHPUqp3DQUWBa63/XgdnwbybSQNAc4ETrX9+7rMY1/gBdsHSlqwLgOKBkhamPJv8VbdZznM9lH1vS9RHp4cQ8nOb1Kr+iZjGRHRSyTtC8wCvN36/Rydr1aD3Qf4DmVP7XPAy8C3gOMpvaWnyc+TCS6jX2otE6yvBwCLU54ibQ0YOAVYpA7f1fbbjUy0D6o9K2e2/UI9PpHyC/NY2+NrQaRfAFvafq2OSVDeyyStQWmlsxHlIcm9wOm2R7WN2QBYjVLu/uYElhEREV0jaVdgdts/qMdDKYUhj7G9aT13I3CK7XObm2mzsucy+p329iGSVgSG2L5B0iGUJ0trUvpN3dd2zQfB6LRM0u7AFyj7B35t+8fAbylVYteSdCvlF+mswAdBSgLLRmxGKUq1MaUY1UbAxZKetX0EQF1+9cESrASWERERU07SucC7wLyStgBWt/2GpL8BC9b2MsOAR1qB5bT64D2Zy+hXJC0NzG37Wkk/pixFmYdSlW0r2+/VjdabAjsAf84H7kLSupQ9lfsAMwMbAIe49P0cBawMLEwpSHC47Wum1V+cfUFdkvNTyrLvjW3fKWkR4CrgNtvbNzrBiIiIfqBW/l3e9mb1+DLgOkrC4lbKZ6PdgYHADrbfnpZXCiW4jH5D0rzA1cAoSmXTkbY3knQBsBwlYFrT9lOSFmntswyQ9CngeUqT3xvrU7kzgeuB2YDtKEWPPg0MsP1oAstmSZoTuITy73IfcIHtByVND9wPXGV77wanGBER0dEkLQT8HjjM9i8lfRf4D8q+yg2Be20fVMfOXAPLaXo1XILL6Dck3QJcavtoSetTlgpuByxhe2dJ1wHrUNqO/KnBqfZJko6ltGrZg1J19BzbZ0k6CdgEWNH2qw1OcZrX1nJkgO0JkuYGBgG7UrL0Y2zf3D62yflGRER0Kkmz2H5d0r9T7rNPU5IVm9n+S10tdBGldscdeehepBVJ9AuSzgHmBTaQtKjtaynVYRfkwz1nVwIHJ7CcNNv7ULKVjwP32z6rnv8mcA+lum40ZKK+WqdIGk3Zb/kscCrlpreHpM3qmAmS1MBUIyIiOpqkQcA+kj5l+3zgQOBTlJVBrwHUFXBvUeOpBJZFgsvoeLWH5SDbC1H2m10oacP6QfxxYD1JZ1Gyb0fXa6Zrar59Wf0FujSwbStIkbQXZR/rs03ObVrX1ldrL8pDk9eAFSn7ZN+ilEK/DRjXGp8bXURExJSz/Ral8OkPawbzTsq2q6HA8ZI+Lel84BbbtzU5174my2Kjo9XMzEhgrO136rltgf2BY4ExwJaUPZhjbT85LW+ynlySZqdsUn+EUv1sK9svZKll72v/fpW0J7AKsHMtTrUqpTjV3MDxth9ocKoRERH9hqSZgYOBm4DraoHD6YATKAmL221vU8fms2WVViTR0Wpm5hfw4Q+27TGSngV+SNlfObo1Pj/8k8f2y7Xy7mXA6BpYDkhg2bvqTewASRfYHkfp0bodJfA/xfZtksYDX6FknBNcRkREdI93KFtPtgZelXS/7TeAPSXdBFwIqXEwsWQuo9+StCgl8DzE9u8ank5HS1DejFrF9xhKpeMf2P6jpI2A8ylNm4+o4+ay/WKDU42IiOg32ovz1Aqxn6NUaH/M9k1t4xJYTiTBZXSsiatyTapKV6ssdO/PLmLqSNqcshx529qb9fPACbavqBXqrgQetf2FRicaERHR4T7iM+QHgaOkTYGVgPmBCcCRwIt1b2a0SXAZHaetHcPslEIms9l+vul5RXQ3SccA79o+SNKOwI7Af9k+XdIMwMWUfq4vNTjNiIiIfkHSssCbtp+ox+0B5lBKYLkDZR/mg1nV9X8luIyO0tbfb1bgAuAuYHHg2FZ/v4hO13qCWr/P9wIusn2/pI2Bb1P2XH6v7YaXZTkRERFd0PbZcm3g+5T2ayfXWgfZGjSF0ookOkrbD/dYyn7KO4HPAs9ISoGq6BdqYLmY7VeBvwKHShpk+zfAt4C1KG1IWuMTWEZEREyh+jB3gqQVgEOB3wArAztLWjWB5ZRLcBkdpy5LuIdSyXRP4Ijag3HVupwhoqNJ+iwliMT2T4BHgR9JGm77IWBD23c0OceIiIhOVx/mTgd8k9Ky7vvAF4EhlK4D6yR5MWUSXEZHkTRjLQM9J/AccIXtCyUNB04Ghjc6wYju8TqwnKTD6/H3KeXQF67H7zcyq4iIiH6mrv4ZBywjaTbbf6EEm9NR2pAs0OT8Ok2Cy+jzJKn+uTZwkKTBlPYMFwJLSFofOA+41PYNzc00omskDah/Dqw3tr8CI4F5JC1pezzwEjBa0tAsg42IiOia1j23vh5SX14KzASsLWkhYG7KtpSB1JVEMXkSXEafVte6W9IylB/u7wBnUZrJnwg8BWwCXGX7sNY1zcw2omvqfg8BOwOnStqWUpHufWD1OubnwCPA8k3NMyIiotO19lBKOpRyz70EeJyStNgQ+Dnw/ymJjPOAQa1ER3yyVIuNPq9WzLwW2Bt4DDgaGAocafuuicamamZ0DEnzU1rp3CfpYOBF4BnKg5SbgG2AuYCv2r6quZlGRER0vrZ2diOAoyhtRQ6gPMgdYfvpmrmcHhgGnE65Bz/Q1Jw7TTI80QnmAV6m9BN6wfZISlbnHEkrw4dLZxNYRoeZHrhA0u3AYrZ/VoPILYGzgYOBK4DlGpxjREREx5M0Qw0sFwG+Qukb/Uj9XHk68AdJ29l+yvbjwAjgkASWUybBZfQ5k1h68DilmMkIScPquSOBPwPnSfqMk4KPDiJpiKQ1bD8FHE5ppzOo9b7t8baftX0xcAiwlaSlmpltREREZ5O0NbBuPRwCzA+sLmk5ANs/AHanZDKp535o+/LenmunS3AZfU4rUJS0sqQVgcHAr4CvAXtK2hM4Ffg6cAkwe0NTjeiqFYFhkmahVKhbEZhF0h2SBgJI2knSTJSqyHOS39cRERFTrCYt7rN9taRvUiqyfw14FdhG0uckzWT7AmCjek3aj3RRPqxEn9JWGXZH4CRgC8qywOeB3YC/U9oxHEUp6vMFSjWviI5Qn5LeYvsKSnGqLYBnbG9A6d/6hKRTgK1svwPMDGxr+/6m5hwREdGJ6h5L235I0nzAp4H9gPmAfYB/ALsCa7UXhLSdll9dlOAy+pRaGXZZYF9gM0qPIYCrgWVsH2N7b+C/KVW99rb9dDOzjZgykpYH/hPYWtKMlBvcYsBpkua1PQrYn7IM/Cv1srdt39jEfCMiIjpZqxaHpP2AWYGfAg8BewBrAaOBh4GXbE/INqupl2qx0SfUliMTJM0MLF5Pz0apCLuqpCOAA4Hdbf+sXrOU7QcbmnLEFJE0v+3nJG1FybjfA5wBvAOcAAwHjrF9lyTVBy2pfhwRETGFJA0FNrE9th7/Ejio3ofnA9anBJf32T6xwan2O8lcRuMkLQisK2kwJZMzHrgXWAI4vw57gpLRGdO6LoFldApJnwK2r5XqzgOOA5alLMmZx/ZulCenx0uas/XkNIFlRERElywPjJJ0QD0eDywNYPt5yufL31FagEU3SuYyGlX3WP4/YHvgi8Adtnes730V+HfgVsp6+BG2n0g2JzpN3ccxGzAv8CXgZGAmSm+t9ynl0O+StKTth5qbaUREROerBfFWoFSAfQF4j7Ll5HZKr/RFgetryxFaK4Yamm6/ksxlNKbtB3kcpW/l7MBLkhYHsH0OcA3wP8CoGlgOSGAZnUTS9HUfx0uUhsxzAt+gFOrZj1Kt7sD2wHIS7XgiIiLiE0iaDqAWxLuN0rpuJkqS4nuUeh67AutQikVSxyew7CbJXEZj2vaVrUTZf7YCsAZlz+UY2zdI2g643PbrDU41oktaWXZJCwG72D5Y0sqUCrEDgQtt3y5pM9uXNTrZiIiIDlYf5r5fX68IDKmfJYcDo4A1gQNt39d2TVbDdbNkLqMRNQNpSesD5wIL276D0rfyYWAnSeOAFRJYRqeqgeWMwFjqvg7bd1IK+bwC7CZpvVZg2V4GPSIiIiaPpKUp2Ugk/Rj4FjBa0q+BN20fTdljeYKk+Vv32wSW3S+Zy2iMpDmBG4HtbP9B0irAYErxntmAf7V9Wh2btfDRkSTtAKxi+xttN7MJkoZR9hRfYju9WiMiIrpA0ryUlnWjgIWAkbY3knQBsBxlG8qatp+StEhrn2X0jOmbnkBM04YCdwEDJZ0ILAysBIy2fQZwN2TJQnS894ClJQ2x/SZA7eU6v+2f1+M8PImIiOiaCymF8W6tnQd2qX0t37C9mKTrgCckLZrAsudlCVb0momX/Nl+glLB6zDgbtubUprariZphrZxCSyj47QV5bmI0rB5m7r3EuBEYI7W2ASWERERU07SOZRK7BvU4PFaymfLBSlFIQGuBA62/aeGpjlNSeYyekXNzEyorw+gLH8dBhxq+5V6fingUGB/2+82NtmILqp7iSdI2hBYUdIcwIGUG9sawL51L/EDts9ucq4RERGdrH6eHGR7IUn7AhdK2s/21ZIeB9aT9G+UpbIb1GuyGq6HZc9l9Iq2D91fp+wzOxoYAewAbFmreZ0PXGf7tCwTjE7TVv14SeACYEdK1nIcpbDAw8BiwD/a+moNaD10iYiIiMlTVweNBMbWtiNI2hbYHzgWGANsSQksx9p+Mvfc3pHgMnqcpFltvyppIKVK5jm2r6nv7QhsY3tDSXPbfqGeT3AZHUPSkcDNwG+A84BfUZbl/BD4I7AVsIfti9uuyfd4RETEVGoPGiWtSbn3/s726EmNiZ6VPZfRoySNBH4kaQnb7wF/AVZvGzIGeFXSXAksoxNJ2omy3Ob39cb1H8BvgaMoAeVelKzlvpIGta7L93hERMTUaw8abd9IWRW3rqQRkxoTPSt7LqOnPUXZVL2npJ8APwWukzQEOI6yZGEu4KXWBfnQHZ2i7q0cDSxr+y1JWwGDgF9SvveXlTQBeBo4to7Jw5OIiIgumvg+OvGx7cckrW/77WZmOG1L5jJ6lO0bgFOB+YDDKYHkMsBnge8Dm1D6Ef1D0nSNTTSiaxYCPgPMI2kB4LvAQ/UJ6R3AesClwI22H0hgGRER0TVtnxNnkzSzpPlg0kmJBJbNyZ7L6HaSVgNesT2uHm9OCSTPBJYErrT96/reoJrNSfWu6EiSvgScBQjYtD5QoWbnBwNz2b6vwSlGRER0tLbCkLNSiubdBSxOWRV0c6OTi3+SzGX0hDWAhyWtKmleSnuRbW0fB1wLbCTpiNrL8h1IL8voXPVBycrAy8DmbW+9ZfvFVmDZ1vcyIiIipkDbnsmxwC+AOymr4J6RlG1+fUj+MaLb2T5G0mPA1ZRszmZtmZtLKQHlu+llGf2F7UclLQ1cL+laYIOJiwdkOWxERETXSRoK3ANcVv87wvazktaQ9HpWCfUNyVxGj7B9CR9mczZrO/+27UtsXwnJ5kT/YXu87ZWBvwO3SRqQ7++IiIipJ2lG228AcwLPAVfYvlDScOBkYHijE4wPZM9l9ChJg4Hrgdco2Zx8w0W/J2k+2883PY+IiIhO1SqCJ2ltYARwNLAA8B3AlCWy+wG32D6ssYnGP0lwGb1C0hXAHMBqlBWC+caLfitVYSMiIrqurYDPMsD3gI2By4GDgRkpq+JmB56tNT0+uKapOUeR4DJ6TbI5ERERETE5amXYa4G9gccomcuhwJG275pobLoO9BHZcxm96c9NTyAiIiIiOsI8lNodD9p+wfZIYAJwjqSV4cPaHQks+44El9FrskwwIiIiIiZlEkXwHgeeBUZIGlbPHUlJVpwn6TP5bNn3pBVJREREREQ0qhUo1qzkBOBPwK+A/YHFJb0GbA+MBEZR9lw+2cxs46MkcxkREREREY1pZS0l7QicBGwBXAE8D+xGafO1MHAUpVLsF4C/NjHX+HjJXEZERERERGNqy5FlgX2BdYFv17euBr5l+xgASbMBNwB72366kcnGx0rmMiIiIiIiep2kAfXPmSlxyfbAMsC6tlcH/gu4WNIoANuvAFvbvqKhKccnSHAZERERERG9StKCwLqSBgP7AeOBe4ElgPPrsCcoey7HtK6z/WAvTzWmQJbFRkREREREr6l7LIcAI4CTgTtsP1bfewPYWNJMwK7ACNtvppdlZ0hwGRERERERvUKS6h7LcZSqsLMDL0la3PY42+dIGg68BYyy/YSkAQksO4PSHiYiIiIiInpDW3C5EnAPsAKwBrA4MMb2DZK2Ay63/XqDU40uyJ7LiIiIiIjocTUDaUnrA+cCC9u+A7gEeBjYqWY0V0hg2ZmSuYyIiIiIiF4haU7gRmA723+QtAowmFK8ZzbgX22fVsfKCVY6SvZcRkREREREbxkK3AUMlHQisDCwEjDa9hnA3QAp4NOZsiw2IiIiIiJ6RKuXZYvtJ4AXgMOAu21vCuwBrCZphrZxCSw7UDKXERERERHR7eqy1gn19QGU5a/DgENtv1LPLwUcCuxv+93GJhvdIpnLiIiIiIjoCQKQ9HVgI+AW4F1gnKS165hDgdNsX1X7X0YHS0GfiIiIiIjoVpJmtf2qpIHAGcA5tq+p7+0IbGN7Q0lz236hnk8Bdpn12wAABJJJREFUnw6XzGVERERERHQbSSOBH0lawvZ7wF+A1duGjAFelTRXAsv+JXsuIyIiIiKiOz0FLAjsKeknwE+B6yQNAY4DtgTmAl5qXZDAsn/IstiIiIiIiOhWkuYATgfeB44FHgDOBl4F5gVG2X46LUf6l2QuIyIiIiJiqkhaDXjF9rh6anVgEeBMYBfgSttb1LGDbL+VwLL/yZ7LiIiIiIiYWmsAD0taVdK8lCqw29o+DrgW2EjSEbWX5TuQXpb9UTKXERERERExVWwfI+kx4GpKC5LNbN9X376UElC+m16W/Vv2XEZERERERLeQtBglwLzY9rc/Ykwqw/ZTCS4jIiIiIqLbSBoMXA+8BmyQQHLakT2XERERERHRbWyPt70y8HfgNkkDJKnpeUXPS+YyIiIiIiJ6hKT5bD/f9DyidyS4jIiIiIiIHpH9ldOWBJcREREREREx1bLnMiIiIiIiIqZagsuIiIiIiIiYagkuIyIiIiIiYqoluIyIiAAkbSHJkpZoO7e8pM+3Ha8j6XNT8TXe/Jj3Zpd0T/3vBUnPtx3P0NWvGRER0VsSXEZERBTbADcBW7edWx74fNvxOkCXg8uPY/tl28vbXh44DTi+dWz73Z74mhEREd0pwWVEREzzJA0BVgd2oQaXNVt4OLBVzR5+F9gN2LserylpU0m3S7pb0rWS5mr9fZLOknS/pPskfXmirzeHpFslbfIJ8xoq6UlJA+vxLJKekjRQ0vWSTpB0i6QHJK1SxwyWdKakO+u8Nu/m/10RERGTNH3TE4iIiOgDvghcZftRSa9IWsH2HyUdAqxk+xsAkmYG3rT9o3o8HFjVtiV9DdgP2Ac4GHjN9jJt46iv5wIuA0bbvubjJmX7DUnXA5sAl1AC34tsvycJYLDtz0laCzgTWBo4CLjO9s6SZgXukHSt7fHd8P8pIiLiIyVzGRERUZbEjq2vx9bjyTE/cLWk+4HvAEvV8+sDP2kNsv23+nIg8Dtgv08KLNucDuxUX+8EnNX23rn17/9vYJYaTP4bsL+ke4DrgZmABSfza0VERHRZMpcRETFNkzQ7sB6wtCQD0wGWtN9kXH4ycJztyyStAxzW+msBT2L8+8AfgA2BGyZnfrZvlrSQpLWB6Ww/0P72xMPr1/6y7XGT8/dHRER0l2QuIyJiWrclcLbtT9teyPYCwJPAGsAbwNC2sRMfDwOer69Htp3/LfCN1kHbslgDOwNLSNp/CuZ4NiVLedZE57eqf/8alGW4rwFXA3uqrpuV9C9T8HUiIiK6LMFlRERM67YBLp7o3EXAtsDvgSVrAZ+tgMuBLVoFfSiZygsk3Qi81Hb9fwLDa6Gde4F1W2/Y/gdl7+S6kvaYzDn+ChhOXQbb5m+SbqFUl92lnjuCsvz2PkkP1OOIiIgeJ3tSq3YiIiKir5C0JbC57a+2nbse2Nf2XY1NLCIiok32XEZERPRhkk4GNuaf+21GRET0OclcRkRERERExFTLnsuIiIiIiIiYagkuIyIiIiIiYqoluIyIiIiIiIipluAyIiIiIiIiplqCy4iIiIiIiJhq/wsdgJUdaa4KngAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1080x1440 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplots(figsize=(15,20))\n",
    "sns.countplot('attacktype1_txt', data=df, palette='inferno', hue = df['targtype1_txt'])\n",
    "plt.xticks(rotation=50)\n",
    "plt.xlabel('Attack Type')\n",
    "plt.title('Attacking Methods with their targets as hue')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Anaconda\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplots(figsize=(20,8))\n",
    "sns.countplot('iyear', data=df, palette='crest', edgecolor=sns.color_palette('dark',7))\n",
    "plt.xticks(rotation=90)\n",
    "plt.xlabel('Years')\n",
    "plt.title('Number Of Terrorist Attacks per year')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Maximum Attacks mostly happened during the year of  2014\n"
     ]
    }
   ],
   "source": [
    "print(\"Maximum Attacks mostly happened during the year of \",df['iyear'].value_counts().index[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Anaconda\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplots(figsize=(15,8))\n",
    "sns.countplot('imonth',data=df,palette='YlOrBr',edgecolor=sns.color_palette('dark',7))\n",
    "plt.xticks(rotation=90)\n",
    "plt.xlabel('Months')\n",
    "plt.title('Number Of Terrorist Attacks')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Maximum Attacks mostly happened during the month of  5\n"
     ]
    }
   ],
   "source": [
    "print(\"Maximum Attacks mostly happened during the month of \",df['imonth'].value_counts().index[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0       63297\n",
       "1.0       30157\n",
       "2.0       15278\n",
       "3.0       10273\n",
       "4.0        7549\n",
       "          ...  \n",
       "312.0         1\n",
       "1362.0        1\n",
       "297.0         1\n",
       "4224.0        1\n",
       "396.0         1\n",
       "Name: affected, Length: 341, dtype: int64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_cp=df.copy()\n",
    "df_cp['affected']=df['nkill']+df['nwound']\n",
    "df_cp['affected'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1 = df_cp.sort_values(by='affected', ascending=False)[:20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "heat =df1.pivot_table(index='country_txt', columns='iyear', values='affected')\n",
    "heat.fillna(0,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Heatmap for Attacked with respect to Country and Year')"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(heat, cmap='PiYG')\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('Country')\n",
    "plt.title('Heatmap for Attacked with respect to Country and Year')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Anaconda\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "image/png": 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kNgVeBtxFuWeylx8Bh1OaC99BKbPh9BPK9rRdROyYmWdk5jERsXnN01/r8v8bpWZ1A0rw9j1KGZKZf42IT1ECzyvqA4M672lclfJ+0WcOlpHMzIjYh3LR5sSIOJVSO7wR5X2g9wF7dz/RV5Lmk+PgvR9+/PjxM5wfGu9p7NFtGeBG5r3fbXKPfvakBIj3Ud7pdg3lhPfxLdPKPvO3DqWm4yZK0HAH5eXyzxlgfmYsQnlMp8f7+Gq3NShPk7yaEhzeT3kK5smUp5k232N5cB3PtJbpDNi933mn5T2CA5UNpQnx5ynB6T8oAc9s4JfAS3sM/xRK0HEnJXAdbHpvocd7P1v6/Vjt92uNtOXqunRlLe/7KIHUV+l6ZyGltvKPdR6SxrsT6fGexq5hv9tYxzdv6adn+dY8HlXLbS5d77JsWx8pgd8bKEHnXXX5/p2yLX2M+d81+DZKrfINtRzuojSj/AiwwhDX68fyD7yc8mqdByitCX4MPHWQ4Q+vw395IbapaW3l0OjnFbWfP3Slv5xS83t7LaN/UJovfw54Wo/xvKGWzUOUdzb+H+VdqldTLiT0ytfBPcazEeWe11sp93ffWse1UT/bMov4flM/fvwsnp/I7Ov5ApIkSYu9iJhBqd3bKDP/MsbZ6Ut95cttwOWZudVg/UvSovKeRkmStESJiOdSHqBzxngOGCNiSvfDheq9oIcBj2d07n+WJGsaJUnSkiEi3k5pIv1GyisotsrMi8c2V+0i4m2UB3idBdxMuZdxO+CplHsmt87MB1tHIEnDxAfhSJKkJcVHKfe93gC8YTwHjNVFlHtCt6O8zxLKPdmHAIcaMEoaLdY0SpIkSZJaeU+jJEmSJKmVzVOB1VdfPadOnTrW2ZAkSZKkMXHJJZfckZlTenUzaASmTp3KzJkzxzobkiRJkjQmIuKmtm42T5UkSZIktTJolCRJkiS1MmiUJEmSJLUyaJQkSZIktTJolCRJkiS1MmiUJEmSJLUyaJQkSZIktTJolCRJkiS1MmiUJEmSJLUyaJQkSZIktTJolCRJkiS1MmiUJEmSJLUyaJQkSZIktZo82hOMiFnAfcAjwNzM3CIiVgVOBKYCs4DXZubdtf8Dgf1q/+/JzDNq+ubAdGBZ4BfAezMzI2IZ4Dhgc+BOYI/MnLUoeT7yzKMWZfAJ5d0vfvtYZ0GSJEnSKBqrmsbtM3OzzNyi/j8AODszNwTOrv+JiI2BPYGnAzsB34iISXWYo4D9gQ3rZ6eavh9wd2Y+BTgcOHQU5keSJEmSJqTx0jx1F+DY+vtYYNdG+gmZ+XBm3ghcDzw3ItYCVszMCzMzKTWLu/YY18nADhERIz8LkiRJkjTxjEXQmMCvI+KSiNi/pq2ZmbcC1O81avo6wM2NYWfXtHXq7+70+YbJzLnAvcBq3ZmIiP0jYmZEzJwzZ86wzJgkSZIkTTSjfk8jsE1m3hIRawBnRsSfBui3Vw1hDpA+0DDzJ2R+G/g2wBZbbLFAd0mSJEnSGNQ0ZuYt9ft24BTgucBttckp9fv22vtsYL3G4OsCt9T0dXukzzdMREwGVgLuGol5kSRJkqSJblSDxohYLiJW6PwGXgJcDZwG7FN72wc4tf4+DdgzIpaJiA0oD7y5uDZhvS8itqz3K+7dNUxnXLsB59T7HiVJkiRJfRrt5qlrAqfU59JMBn6Qmb+KiD8AJ0XEfsDfgN0BMvOaiDgJuBaYC7wzMx+p43o781658cv6ATgaOD4irqfUMO45GjMmSZIkSRPRqAaNmXkDsGmP9DuBHVqGOQQ4pEf6TGCTHukPUYNOSZIkSdKiGS+v3JAkSZIkjUMGjZIkSZKkVgaNkiRJkqRWBo2SJEmSpFYGjZIkSZKkVgaNkiRJkqRWBo2SJEmSpFYGjZIkSZKkVgaNkiRJkqRWBo2SJEmSpFYGjZIkSZKkVgaNkiRJkqRWBo2SJEmSpFYGjZIkSZKkVgaNkiRJkqRWBo2SJEmSpFYGjZIkSZKkVgaNkiRJkqRWBo2SJEmSpFYGjZIkSZKkVgaNkiRJkqRWBo2SJEmSpFYGjZIkSZKkVgaNkiRJkqRWBo2SJEmSpFaTxzoDWvJ8/MdHjHUWxo1DXvOesc6CJEmSNCBrGiVJkiRJrQwaJUmSJEmtDBolSZIkSa0MGiVJkiRJrQwaJUmSJEmtDBolSZIkSa0MGiVJkiRJrQwaJUmSJEmtDBolSZIkSa0MGiVJkiRJrQwaJUmSJEmtDBolSZIkSa0MGiVJkiRJrQwaJUmSJEmtDBolSZIkSa0MGiVJkiRJrQwaJUmSJEmtDBolSZIkSa0MGiVJkiRJrQwaJUmSJEmtDBolSZIkSa0MGiVJkiRJrQwaJUmSJEmtDBolSZIkSa0MGiVJkiRJrQwaJUmSJEmtxiRojIhJEXFZRPys/l81Is6MiL/U71Ua/R4YEddHxJ8jYsdG+uYRcVXtdkRERE1fJiJOrOkXRcTUUZ9BSZIkSZogxqqm8b3AHxv/DwDOzswNgbPrfyJiY2BP4OnATsA3ImJSHeYoYH9gw/rZqabvB9ydmU8BDgcOHdlZkSRJkqSJa9SDxohYF9gZ+G4jeRfg2Pr7WGDXRvoJmflwZt4IXA88NyLWAlbMzAszM4HjuobpjOtkYIdOLaQkSZIkqT9jUdP4VeAjwKONtDUz81aA+r1GTV8HuLnR3+yatk793Z0+3zCZORe4F1htWOdAkiRJkpYQoxo0RsTLgdsz85KhDtIjLQdIH2iY7rzsHxEzI2LmnDlzhpgdSZIkSVqyjHZN4zbAKyNiFnAC8MKI+D/gttrklPp9e+1/NrBeY/h1gVtq+ro90ucbJiImAysBd3VnJDO/nZlbZOYWU6ZMGZ65kyRJkqQJZlSDxsw8MDPXzcyplAfcnJOZrwdOA/apve0DnFp/nwbsWZ+IugHlgTcX1yas90XElvV+xb27humMa7c6jQVqGiVJkiRJg5s81hmovgicFBH7AX8DdgfIzGsi4iTgWmAu8M7MfKQO83ZgOrAs8Mv6ATgaOD4irqfUMO45WjMhSZIkSRPNmAWNmTkDmFF/3wns0NLfIcAhPdJnApv0SH+IGnRKkiRJkhbNWL2nUZIkSZK0GDBolCRJkiS1MmiUJEmSJLUyaJQkSZIktTJolCRJkiS1MmiUJEmSJLUyaJQkSZIktTJolCRJkiS1MmiUJEmSJLUyaJQkSZIktTJolCRJkiS1MmiUJEmSJLUyaJQkSZIktTJolCRJkiS1MmiUJEmSJLUyaJQkSZIktTJolCRJkiS1MmiUJEmSJLUyaJQkSZIktTJolCRJkiS1MmiUJEmSJLUyaJQkSZIktTJolCRJkiS1MmiUJEmSJLUyaJQkSZIktTJolCRJkiS1MmiUJEmSJLUyaJQkSZIktTJolCRJkiS1MmiUJEmSJLUyaJQkSZIktTJolCRJkiS1MmiUJEmSJLUyaJQkSZIktTJolCRJkiS1MmiUJEmSJLUyaJQkSZIktTJolCRJkiS1MmiUJEmSJLUyaJQkSZIktTJolCRJkiS1MmiUJEmSJLUyaJQkSZIktTJolCRJkiS1MmiUJEmSJLUyaJQkSZIktTJolCRJkiS1MmiUJEmSJLUyaJQkSZIktTJolCRJkiS1MmiUJEmSJLUyaJQkSZIktTJolCRJkiS1GtWgMSIeHxEXR8QVEXFNRHy6pq8aEWdGxF/q9yqNYQ6MiOsj4s8RsWMjffOIuKp2OyIioqYvExEn1vSLImLqaM6jJEmSJE0ko13T+DDwwszcFNgM2CkitgQOAM7OzA2Bs+t/ImJjYE/g6cBOwDciYlId11HA/sCG9bNTTd8PuDsznwIcDhw6CvMlSZIkSRPSqAaNWdxf/y5dPwnsAhxb048Fdq2/dwFOyMyHM/NG4HrguRGxFrBiZl6YmQkc1zVMZ1wnAzt0aiElSZIkSf0ZctAYEdtFxPIt3ZaPiO2GOJ5JEXE5cDtwZmZeBKyZmbcC1O81au/rADc3Bp9d09apv7vT5xsmM+cC9wKr9cjH/hExMyJmzpkzZyhZlyRJkqQlTj81jecCG7d026h2H1RmPpKZmwHrUmoNNxmg9141hDlA+kDDdOfj25m5RWZuMWXKlEFyLUmSJElLpn6CxoGaeC4DPNLPhDPzHmAG5V7E22qTU+r37bW32cB6jcHWBW6p6ev2SJ9vmIiYDKwE3NVP3iRJkiRJxeSBOtYnj/5XI2mLHk1UlwXeBPxtsIlFxBTgP5l5T0QsC7yI8qCa04B9gC/W71PrIKcBP4iIrwBrUx54c3FmPhIR99WH6FwE7A0c2RhmH+BCYDfgnHrfoyRJkiSpTwMGjZTg6yBK886kBGbNGsdOU9G5wDuHML21gGPrE1CXAk7KzJ9FxIXASRGxHyX43B0gM6+JiJOAazvTyMxOjebbgemUoPWX9QNwNHB8RFxPqWHccwj5kiRJkiT1MFjQOJ3ShDSAcyiB4bVd/TwMXJeZgzYBzcwrgWf1SL8T2KFlmEOAQ3qkzwQWuB8yMx+iBp2SJEmSpEUzYNCYmTcBNwFExPbApZl532hkTJIkSZI09garaXxMZp43khmRJEmSJI0//byn8XERcVBE/Cki/hURj3R95o5kRiVJkiRJo2/INY3Alyn3NP4S+AnlXkZJkiRJ0gTWT9C4G3BQfTCNJEmSJGkJMOTmqcDylHcfSpIkSZKWEP0EjacD241URiRJkiRJ408/zVOPBI6LiEeBXwALvJcxM28YroxJkiRJksZeP0Fjp2nqwcBBLf1MWqTcSJIkSZLGlX6CxjcBOVIZkSRJkiSNP0MOGjNz+gjmQ5IkSZI0DvXzIBxJkiRJ0hJmyDWNEXHMIL1kZu63iPmRJEmSJI0j/dzT+EIWvKdxVWAF4J76kSRJkiRNIP3c0zi1V3pEbAd8E3jdMOVJkiRJkjROLPI9jZl5PnA45T2OkiRJkqQJZLgehHMD8KxhGpckSZIkaZxY5KAxIiYD+wKzFzk3kiRJkqRxpZ+np57TI/lxwFOB1YC3DVemJEmSJEnjQz9PT12KBZ+eeh/wE+CEzJwxXJmSJEmSJI0P/Tw9ddoI5kOSJEmSNA4N14NwJEmSJEkTUF9BY0Q8IyJOjog5ETE3Im6PiJMi4hkjlUFJkiRJ0tjp50E4zwHOAx4ETgP+ATwReAWwc0Rsl5mXjEguJUmSJEljop8H4XwBuBrYITPv6yRGxArAWbX7S4Y3e5IkSZKksdRP89QtgS80A0aA+v9QYKvhzJgkSZIkaez1EzR2v26j3+6SJEmSpMVMP0HjRcDHanPUx0TEcsBHgd8PZ8YkSZIkSWOvn3saPwbMAG6KiJ8Bt1IehLMz8ATgBcOeO0mSJEnSmBpy0JiZF0fElsCngB2BVYG7gHOAz2bmVSOTRUmSJEnSWBkwaIyIpSg1iTdm5tWZeSWwW1c/zwCmAgaNkiRJkjTBDHZP4+uBHwIPDNDPfcAPI2KvYcuVJEmSJGlcGErQ+L3MvLGth8ycBRwN7DOM+ZIkSZIkjQODBY3PBn49hPGcBWyx6NmRJEmSJI0ngwWNKwB3D2E8d9d+JUmSJEkTyGBB4x3A+kMYz5Nqv5IkSZKkCWSwoPEChnav4r61X0mSJEnSBDJY0PhVYIeIODwiHtfdMSKWjoivAS8EDh+B/EmSJEmSxtCA72nMzAsj4oPAYcDrIuLXwE218/rAi4HVgA9m5u9HNKeSJEmSpFE3YNAIkJlfjYhLgQOAVwHL1k4PAjOAL2bmb0Ysh5IkSZKkMTNo0AiQmecD50fEUsDqNfnOzHxkxHImSZIkSRpzQwoaOzLzUeD2EcqLJEmSJGmcGexBOJIkSZKkJZhBoyRJkiSplUGjJEmSJKmVQaMkSZIkqZVBoyRJkiSplUGjJEmSJKmVQaMkSZIkqZVBoyRJkiSplUGjJEmSJKmVQaMkSZIkqdWoBo0RsV5EnBsRf4yIayLivTV91Yg4MyL+Ur9XaQxzYERcHxF/jogdG+mbR8RVtdsRERE1fZmIOLGmXxQRU0dzHiVJkiRpIhntmsa5wAcz87+BLYF3RsTGwAHA2Zm5IXB2/U/ttifwdGAn4BsRMamO6yhgf2DD+tmppu8H3J2ZTwEOBw4djRmTJEmSpIloVIPGzLw1My+tv+8D/gisA+wCHFt7OxbYtf7eBTghMx/OzBuB64HnRsRawIqZeWFmJnBc1zCdcZ0M7NCphZQkSZIk9WfM7mmszUafBVwErJmZt0IJLIE1am/rADc3Bptd09apv7vT5xsmM+cC9wKrjchMSJIkSdIENyZBY0QsD/wYeF9m/nOgXnuk5QDpAw3TnYf9I2JmRMycM2fOYFmWJEmSpCXSqAeNEbE0JWD8fmb+pCbfVpucUr9vr+mzgfUag68L3FLT1+2RPt8wETEZWAm4qzsfmfntzNwiM7eYMmXKcMyaJEmSJE04o/301ACOBv6YmV9pdDoN2Kf+3gc4tZG+Z30i6gaUB95cXJuw3hcRW9Zx7t01TGdcuwHn1PseJUmSJEl9mjzK09sGeANwVURcXtM+BnwROCki9gP+BuwOkJnXRMRJwLWUJ6++MzMfqcO9HZgOLAv8sn6gBKXHR8T1lBrGPUd4niRJkiRpwhrVoDEzL6D3PYcAO7QMcwhwSI/0mcAmPdIfogadkiRJkqRFM2ZPT5UkSZIkjX+j3TxV0jB76/e+MnhPS4hvvfEDY50FSZKkCceaRkmSJElSK4NGSZIkSVIrg0ZJkiRJUiuDRkmSJElSK4NGSZIkSVIrg0ZJkiRJUiuDRkmSJElSK4NGSZIkSVKryWOdAUkaT3b/2qFjnYVx40fv/ehYZ0GSJI0D1jRKkiRJkloZNEqSJEmSWhk0SpIkSZJaGTRKkiRJklr5IBxJ0oh4yWcPGessjBu//uTHxzoLkiQtNGsaJUmSJEmtDBolSZIkSa0MGiVJkiRJrQwaJUmSJEmtDBolSZIkSa0MGiVJkiRJrQwaJUmSJEmtDBolSZIkSa0MGiVJkiRJrQwaJUmSJEmtDBolSZIkSa0MGiVJkiRJrQwaJUmSJEmtDBolSZIkSa0MGiVJkiRJrQwaJUmSJEmtDBolSZIkSa0MGiVJkiRJrQwaJUmSJEmtDBolSZIkSa0MGiVJkiRJrQwaJUmSJEmtDBolSZIkSa0MGiVJkiRJrQwaJUmSJEmtJo91BiRJ0uC2+uinxzoL48aFhx401lmQpCWKNY2SJEmSpFYGjZIkSZKkVgaNkiRJkqRWBo2SJEmSpFYGjZIkSZKkVgaNkiRJkqRWBo2SJEmSpFYGjZIkSZKkVgaNkiRJkqRWBo2SJEmSpFYGjZIkSZKkVqMaNEbEMRFxe0Rc3UhbNSLOjIi/1O9VGt0OjIjrI+LPEbFjI33ziLiqdjsiIqKmLxMRJ9b0iyJi6mjOnyRJkiRNNJNHeXrTga8DxzXSDgDOzswvRsQB9f9HI2JjYE/g6cDawFkR8dTMfAQ4Ctgf+D3wC2An4JfAfsDdmfmUiNgTOBTYY1TmTJIkLTae+c5PjXUWxo0r//czY50FSePcqNY0Zub5wF1dybsAx9bfxwK7NtJPyMyHM/NG4HrguRGxFrBiZl6YmUkJQHftMa6TgR06tZCSJEmSpP6Nh3sa18zMWwHq9xo1fR3g5kZ/s2vaOvV3d/p8w2TmXOBeYLVeE42I/SNiZkTMnDNnzjDNiiRJkiRNLOMhaGzTq4YwB0gfaJgFEzO/nZlbZOYWU6ZMWcgsSpIkSdLENh6Cxttqk1Pq9+01fTawXqO/dYFbavq6PdLnGyYiJgMrsWBzWEmSJEnSEI2HoPE0YJ/6ex/g1Eb6nvWJqBsAGwIX1yas90XElvV+xb27humMazfgnHrfoyRJkiRpIYzq01Mj4ofANGD1iJgNHAR8ETgpIvYD/gbsDpCZ10TEScC1wFzgnfXJqQBvpzyJdVnKU1N/WdOPBo6PiOspNYx7jsJsSZIkSdKENapBY2bu1dJph5b+DwEO6ZE+E9ikR/pD1KBTkiRJkrToxkPzVEmSJEnSOGXQKEmSJElqZdAoSZIkSWpl0ChJkiRJamXQKEmSJElqZdAoSZIkSWpl0ChJkiRJamXQKEmSJElqZdAoSZIkSWpl0ChJkiRJamXQKEmSJElqZdAoSZIkSWpl0ChJkiRJamXQKEmSJElqZdAoSZIkSWpl0ChJkiRJamXQKEmSJElqZdAoSZIkSWpl0ChJkiRJamXQKEmSJElqZdAoSZIkSWpl0ChJkiRJamXQKEmSJElqZdAoSZIkSWo1eawzIEmSpMXX0/f++FhnYdy45rhDxjoL0oiwplGSJEmS1MqgUZIkSZLUyqBRkiRJktTKoFGSJEmS1MqgUZIkSZLUyqBRkiRJktTKoFGSJEmS1MqgUZIkSZLUyqBRkiRJktTKoFGSJEmS1GryWGdAkiRJUrHpaz461lkYN6748aFjnQVV1jRKkiRJkloZNEqSJEmSWhk0SpIkSZJaGTRKkiRJkloZNEqSJEmSWhk0SpIkSZJaGTRKkiRJkloZNEqSJEmSWhk0SpIkSZJaGTRKkiRJkloZNEqSJEmSWhk0SpIkSZJaGTRKkiRJkloZNEqSJEmSWhk0SpIkSZJaTR7rDEiSJEnSSNhix/ePdRbGjZlnHL7Qw07ImsaI2Cki/hwR10fEAWOdH0mSJElaXE24oDEiJgH/C7wU2BjYKyI2HttcSZIkSdLiacIFjcBzgesz84bM/DdwArDLGOdJkiRJkhZLEzFoXAe4ufF/dk2TJEmSJPUpMnOs8zCsImJ3YMfMfHP9/wbguZn57q7+9gf2r383Av48qhldOKsDd4x1JiYQy3P4WJbDy/IcXpbn8LEsh5flObwsz+FleQ6fxaUs18/MKb06TMSnp84G1mv8Xxe4pbunzPw28O3RytRwiIiZmbnFWOdjorA8h49lObwsz+FleQ4fy3J4WZ7Dy/IcXpbn8JkIZTkRm6f+AdgwIjaIiMcBewKnjXGeJEmSJGmxNOFqGjNzbkS8CzgDmAQck5nXjHG2JEmSJGmxNOGCRoDM/AXwi7HOxwhYrJrTLgYsz+FjWQ4vy3N4WZ7Dx7IcXpbn8LI8h5flOXwW+7KccA/CkSRJkiQNn4l4T6MkSZIkaZgsNkFjRGREHN/4Pzki5kTEz+r/V0bEAS3D3t+SPj0idqu/Z0TEkJ9qVIe9MSIur5/f9TdHEBErR8Q7Bui+ekScGxFXRsTFEbH8AP1mRBzW+P+hiDi4z/xMi4itG/8fK58hDPuqmoenNdKmRMRFEXFZRDy/xzDfjYiNe6R/PCKuqfN9eUQ8r5/5GKn5GaDfX0TEyguTx0WxuJXTwoqILSLiiIUYrq/yiYiDI+JDQxjvRnV/cXlE/DEiBmxyUsv3Z/3mf7hFxLPqstqxkbZMRJxV52WPHsN8JiJeNIRxHx4R72v8PyMivtv4f1hEfKDP/M63Xg63iJgVEVc19uF9r2OjYTxs5ws5vX0jYu2IeGJEnBARf42Ia+v+8qn1GH5HRHxhCON6W0Ts3RnnQuRlwG07Iq6IiB/2O94+89DzeLcQ49mwng9cGRFnDdLvU2t5X1/3VSdFxJp9Tu939XuB/VhEPFLXyc53z3OwQcbvdt4Q4/Bcbrgt7DF9tDTW58tHcr2OiFMj4sIhjGvclNfidE/jA8AmEbFsZj4IvBj4e6djZp7G6D8l9cOZefIiDL8y8A7gGy3d3w6cn5kH1QPlvwcY18PAqyPiC5nZ93tgImIyMA24H+g7AAb2Ai6gPK324Jq2A/CnzNynx/Qmdd6l2ZW+FfBy4NmZ+XBErA48biHyA8M/Pz1l5ssWYvyLZHEsp4UREZMzcyYws8/hhrN8uh0BHJ6Zp9ZpPWOYxttTLYO5wzCqzrLai/KgMIBnAUtn5mY9pjspMz81xHH/Dtgd+GpELEV5H9WKje5bA+/rM7/T6HO9XIiy2n5h95fDtEwGm8542c4Xxr7A1cCRwLGZuSdARGwGrAk8hfJ+5NdGxMdygHtlMvObddgZdZwLvEarrq+P9JvJiPhvygX07SJiucx8oN9xDGEaPY93C+kA4KjM/F5EbDDANB8P/Bz4QGaeXtO2B6YAtw0xz49k5kAnvg9m5mYRcX+vfcgQTWMJ3867jMdzuWGzsMf0UfbgIqzPHdMYYBlEqWh4NnB/RGyQmTe2jWhclVdmLhYfSuF/Htit/j8O+Cjws/p/X+Dr9fcGwIWU1298Fri/pgfwdeBays70F43xzQC2qL9fUoe/FPgRsHyP/EzvDNuV/lzKSnJZ/d6opj8duBi4HLgS2BA4AXiwpn25x7g+ChzdR/kcCBxS/38IOLj+Xh84u073bOBJjXn4CnAu8GPgH5RA/HLg+bX7EXU+bug1v3U8y9fhnkoJEgE2A/4GzKnjW7bm8TPARcC2XWW+Uy3vWcCclrLcp/6+CjgGWKb2NwtYvf7eoo536nDOT01fCzi/ju9q4Pk9pv9T4BLgGmD/EdweXg2c3tJthzEup2nAecBJwHXAF4HXUdb/q4An1/6mUNa7P9TPNjX9YMoN478GflDH97PGNL9Xx3Ml8JqafhRlp3oN8OlBymeBcmhM93jgHOAvwFtahr8S2LxH+lTgN5T1+FJg60Z5zABOBv4EfJ9595N/qs771XWeO+kzKPu784APAq+gbDeXAWcBazbyfEzt/wbgPS15jtr9yZQT7scDawDXA/fWZf/kWjafYt5Jw3Tm7SOfU9eJK+qyXKExz1dRLmptDTwDOLYuv1WAZYB7KMHO5nWeLqEErmvVcb+Hsl++krJfnMqC6+VQ15ehlsks6nrQlT6Deful1YFZjWPMj4DTKevIqpTt/Urg98AzB1uPgA/XvF8JfHq8budt+aTH/o3ylPLplHX4KuD9wG6U/f3N9XvZHvk/vn7+SVkPP93Ylh8G7qS8CPvXwOco69T9dT7+VfP2AOUY31lf31LzfQVlXXlCY5l8qKUcPwt8hLJf2atrPTicss//I2X9/0ldpp9r9Pd65h3bvwVMqulDOd5dAZxd03qeO/TI71HAJ4ew7rwJOK6l21Ta91XnUrajazvz0eh2PnAKZVv9ZqPb/cBhdVxnU/b5f6Ds/2+u68xv6nK8FrixLt9r6rK+tZbfMXXac4CHgJtYArbzrnyNq3O5xrIf02N6P2W4qB/qet0jve14Pejxq8e49qNUGB0EHNhI372O/wpKpVGn/DvlNaT9xIiVzWhObFEXIvBMyonX4+uCaBbkvswLGk8D9q6/38m8HdurgTMpB7m1KScy8wWNlJ3H+cByNf2jwKd65Gc6Zcd3ef18v6avCEyuv18E/Lj+PhJ4Xf39OEoQNRW4eoB53q3m8W1DLJ8VKTvIlZh/R3M6sE/9/Sbgp415+BnzDnIH0ziw1u4/olyF3Ri4vmXar6cGt3Ulfnb3Mqn/E3ht43+nzKdQDiwbUHYgV1F2TN8BXlj7fSnlROGp9f9xwPvq71m0BwHDOT8fBD5ef08CVugx/VXr97KUDX+1Edoelq/r3XWUHc8Lavrja1mOZTlNo6y3a1EChr8z74TwvcBX6+8fANvW308C/tjIzyXUE03m384P7Qxf/6/SVe6TKOvV83qVzxDK4Yq67Fav5bh2j/l+IyXQ+iXlBHnlmv4E4PH194bAzEb+7wXWrWV6YWO+V22M93jgFY1t4xvN+WTeAerNwGGNPP+ulvPqlBOxpXvkeVvmnZz+AHh1d9k2yuYjXevCbpR91g3Ac7Kxn+ua59mUg+ZbgbdRTsZfBmxD2acuXfM6pfa/B+WVSFAC2U7Qs3Jj3prr5VDXl6GWySzKvuby+nl/c79Uf3efTM5m3rp2JHBQ/f1C4PKB1iPKxchvUwL4pSj73u3G23Y+UD7psX+jXAg4szHelRvl+GVKrXz3fC1bl8vRwP6UE9qfATsDfwXmUi48rkw5Uf0J5Zg2A9ihMZ57qMez+n+1xu/PAe/uNe9debmOcjL+EuC0RvoM4NDGfusW5u3TZtd5/2/K8XXp2t83mHfuMejxrqtMe5479MjvhyjB9MsHWXe+Ary3pdtA+6oHOnmrac2g8SHgvyj72TOBRyjrZ1ICvD0oJ9bfqcOcTQm4XkHZJz9cy2+VxnpyGnBeYznNAbanbDt3swRs5135HY/nctMY+2P6M4dahov6Yd563fns0cxT/d08Xg96/OoxjbMoAf1TgSsb6VcB63SNq1leQ9pPjNRncWqeSmZeGRFTKdXnA71SYxvgNfX38ZSVEmA74IdZmrDcEhHn9Bh2S8pG9duIgHKy1NbmuFfz1JWAYyNiQ8qOdOmafiHw8YhYF/hJZv6ljr+niFgH+DiwEfDziJiTmT+OiCspG+U/u4fJzH9GxHGUqx4PNjptRQmYoZTHlxrdfpQDN+n5aWY+Clw7wL0QewFfrb9PqP8v7dHfI5SrUN22pFxRuREea770fGAX4BcRcUdnfjLzujrMsZQLAl/tHtkgFmV+/gAcExFL1/Fc3mPY90TEq+rv9SgH5Dv7zOOgMvP+iNicUk7bAyfWdveXATeOcTkB/CEzbwWIiL9SrjBC2SFuX3+/CNi4sR2sGBEr1N+nZWmG3u1FlBoFADLz7vrztRGxPyWQWYtyAWKB8snM6YPM96l1ug9GxLmUq3o/bfaQpVnYGZTagl2At0bEppRt/et1/X2EcjDouDgzZ9fyuJxywegCYPuI+AjlJG5VylXV0+swJzaGX7fOw1qUfdKNjW4/z8yHgYcj4nZK07/ZXfO1F2UZUb/fQDkR7+XEHmkbAbdm5h9qGfyzzstyjXl+AuWEeGvKCes69fe91CuiwCbAmXWZT6LUMEAJNr8fET+lq7wb+llfhlIm0H+ztTMz8676e1vqcSYzz4mI1SJipdqt13q0LeWE8rLaz/KU/cP5bRMbo+38JQPks9f+7c/Af0XEkZQWPJ1tfSAvpzSR3IFSNhtRWqasTQksHqAEJ9dSTjZ3bAz75HqP18rAcpST7I5NIuJztdvyzGuG3VNEPIfSsuWmiJhN2b+v0tivdG55uQq4prFPu6HO/7aU/cwf6nq5LHB7HWZIx7vG+tR27tDM77MpF2KeBfw6Iu6inFv8lVLbkwPNb8Ng+6obew5Vut1Q8/JDykWMzSLikTr9uRHxX8DZEfEHStnMpSzj24H/UFpazAReHBFrUPbXzW1wWUoNb+f3yhN9O+82Ts/lxvqYvjHlODEa2pqnth2vh3L8ekwt/6cAF2RmRsTciNgkM68GfgtMj4jOxbJug+4nRtJiFTRWpwH/Q4m8Vxugv7ad52A71aDsMPbqP2tAubp+bma+qga4MwAy8wcRcRHlSuoZEfFmypX7NtsAV2TmbRGxM2UnvCblatgCAWPDVykb+fcG6KdZBoPdv/Fw4/cCUW5ErEa5+rZJRCTlRDDrhtXtoZadWjTzVPuZERH7Ug4wa1CaKrSd5M5l3kOdHj/g3CzC/GTm+RGxHWUZHh8RX87M4xrDTqPsALfKzH/V+28Gy89C65QTpayuojTfvXyAQUalnHoM/2jj/6PM2+8sRSmr+Q4k9YDTtl7Ot67U/jegXI19TmbeHRHTKVfRe5XPdAYuh+79Q0bEIZRlTudAkpm3UJpGHRMRV1OCoVdQToQ3reN/qDGeZnk8Akyu9xx9g3K1++Z6ItzMT7MMjgS+kpmn1fXs4IHG3ZyBiJhEOel5ZUR8nFKGqzUO5t16lf0C5V69n3nz/E7ga5TmqVdTrrx/kNL88Jg6jmsyc6se49mZclHvlcAnI+LpPfrpZ30ZsEwGMdD60ZxOr6t+2fXdTA/gC5n5rT7yMhbbec98tu3f6ja3KSWweyfwWkotCJRjXK9j6V6U2r3OspxLaVFzVkScRzkh3RV4F+UC8VKNYQ8CXpaZV9QLipMa3aYDu9Zu+1LOEwayF/C0iJhV/69I2VY6D3Fq7re692mTKWV1bGYe2GPcQzreNfQ8d+jyIkrAeXMN3k+jNBP9RY+A8RrgBT3GAfNvt937qoHOCYYSlD6OcpHrZZSmm98CyMyD675oO0rNeFAunn2XclGkI6jbed23vjwz75vo23kPX2V8ncuN+TF9oJkbaYMcr4dy/Grag1LbfmMtmxUpgfMnMvNtUR52tjNweb2w0zSU/cSIWWrwXsadY4DPZOZVA/TzW+ZduXhdI/18YM+ImFSv2G+/wJClzfo2EfEUgIh4QkQ8tUd/bVZi3gN69u0k1qtvN2TmEZQd/TOB+yj3BfVyJeWqxtqZeRtlJ/+/lOr/VvXq2EmU9tIdv2P+8rigZfCB8tNmN8p9E+tn5tTMXI9SC7JtH+O4EHhBRGwQ5cmUW9T0lernJkqNxeTOcqHUlJxXf8+iXNGEeTXMwz4/EbE+cHtmfofSrOrZXcOuBNxdT6ieRrmiPCJqOW3YSNqMUk5/AqaOZTn1MY5fU04KgcdqmPsdZhXKDvcB4N56YeWlwBNbygfaywFgl4h4fD2ATqNcXf14Zm7WCRgjYqcotc1ExBMpF6/+Tln+t9aruW9g/pPZXjoHnDuiPBl5twH6be5X9hlkvN1eRLkAtV5dVutTakB27WMcfwLWjlIzQ0SsEOWBC815XoVyAnBXlgdo3EWp8dmKso3/GZgS5eEuRMTSEfH0KA/OWS8zz6XcW7Yy5ep893q5MOvLwpjFvPVjoGVyPvX4UgOqOxoX9BZYjyi1Xm+qy5qIWCdKTUurMdrO2/LZc/8W5eE8S2Xmj4FPMm+/eF/N5zIR8ZbGPE2jHHtfS6kh24QSbO5XT4JWoNQevq/Ob9N9lHXj1roNLtfVfYVGt9cxgLre7U5p9jY1M6dSWg70c8H4bGC3znKMiFXrcWIgjx3vOsPU9J7nDl0uo6xbK2XmnyjNfw8D/q9Hvz8Atq4XnanT2inKg7v63Vd1PLcep5einPh2guKlmLetvJ5SoziLsq6+qU57KeAldTu/g1KLuDylBqk5/T/T2M5r95Ewi3GynfeymJ7LjeQxfaz1PF73cfxq2gvYqbHf2Zy6XCPiyZl5UZaH0N1BadHQNJT9xIhZ7ILGzJydmV8bpLf3Au+M0jxipUb6KZQblq+i1Fyd1z1gZs6hLIgfRmkK+nug7dHDX475H8v7OEpzgS9ExG+Zf0e4B3B1lKZpT6NsnHdSmsFeHRFf7srHnyjNU8+IiEuBD1BWqi8MIYg9jNLGvuM9wBvr/LyBUj69nA68qs7LAq/IaLEXpVybfgz8vyEO3ynz/Sk1iacDZ0XEtZQaix0pDyBIygb0oyhX2x+lXGGF8uCTr0XEb5h3EBuJ+ZlGufJzGeVkrHs9/BUlsL2ScjXo90Oc5sJYntJE4do6vY0p9z08RLnnbizLaajeA2wR5dHx11LugxvM54BV6jZzBaXZ0RWUk6lrKBeVfku572KB8qnjaCsHKDf2/5yy7D5baxS7vYSyLV9BOUH4cGb+g3IVcp+I+D2ludeAV34z8x7KfbtXUZq0/GGA3g+mLNPfMH9TrqEYjm3035R92JF1vs+kHESb8/yE2ntzvb8KuDcz76jj2A04tI7jcsrFoEnA/9X19TLKPXD3sOB6uTDry2DObey/O60G/gd4e5RXDaw+wLAHd/JDeTBEM5hfYD3KzM5DIC6s83oyg5/Yjfp2PkA+2/Zv61BqQS+n1PR1at2m1zwtB+wU5ZUb11D2m7/NzJ93pkN5cMhulBOkoylNt86jXCxtmk6pnbyZErD9p6v7JykPnjmTErAOZDvg75n590ba+ZTmdWsNMiwAmXkt8AlKU9Er63QHHLZ5vKvbQac5eNu5Q3PYMykB4u8jotNs942U5mxTuvp9kNIM+N0R8Ze6zexLaSba176q4ULKun41JaB4XF3uj1KenPwPyjb9Tcq236nNe1sd5pt1neoEyp2mfavX8TyJsi/sbFdPYZDgf4jG+3beZrE6l2Nkj+mjadmuc/svDnC8HurxC4AoF8aeROM4maU5+D+j1DB+OcorYq6m7I+u6MrboPuJkdR5sIIkSVpEUZot3Z+Z/zPWeZE0MtzOtSRa7GoaJUmSJEmjx5pGSZIkSVIraxolSZIkSa0MGiVJkiRJrQwaJUmSJEmtDBolSWqIiH0jIhuff9dXRnw+ykueR2q6WZ/KKEnSuDJ5rDMgSdI4tTswm/KetVdR3kG4AvDuEZreVnV6kiSNKz49VZKkhojYF/gesGFmXt9IPxPYBlg+Mx8do+xJkjTqbJ4qSdLQXAosC6wOEBFPiIhDI+LG2oT1xoj4eETMd2yNiGdHxG8i4qGIuDkiPhYRn46I7OpvgeapEbFTRFwYEQ9GxL0R8dOI2KirnxkRcUFEvCgiLo2If0XE1RGxa1d/T42IUyLi9pqXv0XEjyLCVkeSpAF5oJAkaWimAvcCd9ZA6wxgY+CzwFXAlsAngVWBDwJExOrA2cAtwN7Av4H313ENKCJ2An4OnAPsASwPfAa4ICI2y8y/N3p/MvA14AvAHXX6J0fE0xq1pT8D7gHeXvtZB3gZXkCWJA3CoFGSpN4m1eCwc0/ja4D3ZeYjEfEGYFvgBZl5fu3/7IgAOCgiDs3M24EPAMsBO2bmbICIOAOYNYTpfw64AXhpZs6tw14IXEcJCj/Q6Hd1YLvM/Evt71LgVuC1wOdr8LohsEtmntYY7gf9FIgkacnk1UVJknr7E/Af4C7gaOBbmfn12m0n4CbgdxExufMBfg0sTal1pH5f2AkYATLzQUoNYquIWA54NnBiJ2Csw94I/BZ4Qdcgf+kEjLW/24HbgSfVpDspAegXI+ItEbHhEMtAkiSDRkmSWrwKeA6lCedZwDsiYu/abQ1gfUpQ2fxcXLuvVr/XogRv3W4bZNqrAEGpLez2D0oT2Ka7evT3MPB4gCxPvXsxMJPShPW6iLghIt4+SD4kSbJ5qiRJLa7u3A8YEecAVwJfjogfU2rubqQ0/+xlVv2+lRJgdltzkGnfDSTwxB7dnlin35fMvAHYO0ob2k2BdwHfiIhZmfnLfscnSVpyWNMoSdIgMvNh4MOUAPAdwK+A9YD7M3Nmj88dddDfA1tFxLqdcUXEssDOg0zvAeASYPeImNQYdn1ga+C8RZiXzMzLmXdP5CYLOy5J0pLBmkZJkoYgM0+LiD8AHwKeAryR8vCbw4ArgMdRnmL6SmDXzPwX8BXK00rPiIhPU5qMfqB+D/ai5E9S7n38WUR8g/L01E9TnuB6WD95j4hnUp6ueiJwPTAJ2BeYS3k6qyRJrQwaJUkauk9QXrXxZmBH4ABgf2AD4AHgr5RA798AmXlHROwAHAEcR2lW+k3K00737h55U2b+KiJ2Bg4CTqrjnAF8JDNv6TPf/wD+RglY1wUeorwm5OWZeUmf45IkLWGi3BsvSZJGQ21ueilwR2buMNb5kSRpMNY0SpI0giLis5QmoTdRnqr6ZuCZlKeySpI07hk0SpI0shL4FLB2/X0l5Z5Hn1gqSVos2DxVkiRJktTKV25IkiRJkloZNEqSJEmSWhk0SpIkSZJaGTRKkiRJkloZNEqSJEmSWhk0SpIkSZJa/X/Pe8cPQ2ZezAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,6))\n",
    "sns.barplot(df['region_txt'].value_counts()[:10].index,df['region_txt'].value_counts()[:10].values, palette='crest')\n",
    "plt.title('No. of Terrorist Activities by Region', fontsize=20)\n",
    "plt.xlabel('Regions', fontsize=16)\n",
    "plt.ylabel('Count', fontsize=16)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Anaconda\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "image/png": 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qWlJVSzbbbLOVhSxJkiRJa6R5TRCT3IQuOTy4qr7Ymi9uw0Zpp5e09guArUd23wq4sLVvNaZ9uX2SrANsDPxm7h+JJEmSJC1+81nFNMABwFlV9a6RTYcDe7fzewNfHmnfq1Um3Y6uGM1JbRjq1Ul2bbf5zGn7TN3Wk4Bj2jxFSZIkSdJqWmceb/t+wDOA05Oc2tpeD/wHcEiSfYBfAXsAVNWZSQ4BfkJXAfUFVXV92++fgU8C6wNHtj/oEtCDkpxN13O41zw+HkmSJEla1LKmdbgtWbKkli5desPlm61/mx6jWeYPf/x13yFIkiRJWgMkObmqlozbtiBVTCVJkiRJw2eCKEmSJEkCTBAlSZIkSY0JoiRJkiQJMEGUJEmSJDUmiJIkSZIkwARRkiRJktSYIEqSJEmSABNESZIkSVJjgihJkiRJAkwQJUmSJEmNCaIkSZIkCTBBlCRJkiQ1JoiSJEmSJMAEUZIkSZLUmCBKkiRJkgATREmSJElSY4IoSZIkSQJMECVJkiRJjQmiJEmSJAkwQZQkSZIkNSaIkiRJkiTABFGSJEmS1JggSpIkSZIAE0RJkiRJUmOCKEmSJEkCTBAlSZIkSY0JoiRJkiQJMEGUJEmSJDUmiJIkSZIkwARRkiRJktSYIEqSJEmSABNESZIkSVJjgihJkiRJAkwQJUmSJEmNCaIkSZIkCTBBlCRJkiQ1JoiSJEmSJMAEUZIkSZLUmCBKkiRJkgATREmSJElSY4IoSZIkSQJMECVJkiRJjQmiJEmSJAkwQZQkSZIkNSaIkiRJkiTABFGSJEmS1JggSpIkSZIAE0RJkiRJUmOCKEmSJEkCTBAlSZIkSY0JoiRJkiQJMEGUJEmSJDUmiJIkSZIkYB4TxCQfT3JJkjNG2vZL8n9JTm1/jxrZ9rokZyf5WZKHj7TfK8npbdv7kqS1r5fkc639xCTbztdjkSRJkqQ1wXz2IH4SeMSY9ndX1U7t7wiAJDsAewF3a/t8MMna7fofAvYF7tj+pm5zH+CKqtoeeDfw9vl6IJIkSZK0Jpi3BLGqjgd+s4pX3x34bFVdU1XnAmcDuyS5LbBRVZ1QVQV8Cnj8yD4HtvOHArtN9S5KkiRJklZfH3MQX5jktDYE9ZatbUvg/JHrXNDatmznp7cvt09VXQdcCdxq3B0m2TfJ0iRLL7300rl7JJIkSZK0iCx0gvgh4A7ATsBFwDtb+7iev5qlfbZ9Vmys2r+qllTVks0222y1ApYkSZKkNcWCJohVdXFVXV9VfwE+CuzSNl0AbD1y1a2AC1v7VmPal9snyTrAxqz6kFZJkiRJ0jQLmiC2OYVTngBMVTg9HNirVSbdjq4YzUlVdRFwdZJd2/zCZwJfHtln73b+ScAxbZ6iJEmSJOlGWGe+bjjJZ4AHAZsmuQB4E/CgJDvRDQX9JfBcgKo6M8khwE+A64AXVNX17ab+ma4i6vrAke0P4ADgoCRn0/Uc7jVfj0WSJEmS1gRZ0zrdlixZUkuXLr3h8s3Wv02P0Szzhz/+uu8QJEmSJK0BkpxcVUvGbeujiqkkSZIkaYBMECVJkiRJwDzOQdTc2vxWO/UdAgAXX35q3yFIkiRJmif2IEqSJEmSABNESZIkSVJjgihJkiRJAkwQJUmSJEmNCaIkSZIkCVjFBDHJ/ValTZIkSZI0uVa1B/H9q9gmSZIkSZpQs66DmOQ+wH2BzZK8fGTTRsDa8xmYJEmSJGlhzZogAusCG7TrbTjSfhXwpPkKSpIkSZK08GZNEKvqOOC4JJ+sqvMWKCZJkiRJUg9W1oM4Zb0k+wPbju5TVQ+Zj6AkSZIkSQtvVRPEzwMfBj4GXD9/4UiSJEmS+rKqCeJ1VfWheY1EkiRJktSrVV3m4itJnp/ktkk2mfqb18gkSZIkSQtqVXsQ926nrxppK+D2cxuOJEmSJKkvq5QgVtV28x2IJEmSJKlfq5QgJnnmuPaq+tTchiNJkiRJ6suqDjG998j5mwK7AacAJoiSJEmStEis6hDTF41eTrIxcNC8RCRJkiRJ6sWqVjGd7g/AHecyEEmSJElSv1Z1DuJX6KqWAqwN3BU4ZL6C0uS68xaP7DsEfnbhkX2HIEmSJE2kVZ2D+F8j568DzquqC+YhHkmSJElST1ZpiGlVHQf8FNgQuCXw5/kMSpIkSZK08FYpQUzyZOAkYA/gycCJSZ40n4FJkiRJkhbWqg4xfQNw76q6BCDJZsDRwKHzFZgkSZIkaWGtahXTtaaSw+by1dhXkiRJkjQBVrUH8etJvgF8pl3eEzhifkKSJEmSJPVh1gQxyfbA5lX1qiT/ANwfCHACcPACxCdJkiRJWiArGyb6HuBqgKr6YlW9vKpeRtd7+J75DU2SJEmStJBWliBuW1WnTW+sqqXAtvMSkSRJkiSpFyubg3jTWbatP5eBSAvpPls9q+8QOOGCT/YdgiRJkrSclfUg/jDJc6Y3JtkHOHl+QpIkSZIk9WFlPYgvBQ5L8jSWJYRLgHWBJ8xjXJIkSZKkBTZrglhVFwP3TfJg4O6t+WtVdcy8RyZJkiRJWlCrtA5iVR0LHDvPsUiSJEmSerSyOYiSJEmSpDWECaIkSZIkCTBBlCRJkiQ1JoiSJEmSJMAEUZIkSZLUmCBKkiRJkgATREmSJElSY4IoSZIkSQJMECVJkiRJjQmiJEmSJAkwQZQkSZIkNSaIkiRJkiTABFGSJEmS1JggSpIkSZIAE0RJkiRJUmOCKEmSJEkC5jFBTPLxJJckOWOkbZMk30zy83Z6y5Ftr0tydpKfJXn4SPu9kpzetr0vSVr7ekk+19pPTLLtfD0WSZIkSVoTzGcP4ieBR0xrey3wraq6I/CtdpkkOwB7AXdr+3wwydptnw8B+wJ3bH9Tt7kPcEVVbQ+8G3j7vD0SSZIkSVoDzFuCWFXHA7+Z1rw7cGA7fyDw+JH2z1bVNVV1LnA2sEuS2wIbVdUJVVXAp6btM3VbhwK7TfUuSpIkSZJW30LPQdy8qi4CaKe3bu1bAuePXO+C1rZlOz+9fbl9quo64ErgVuPuNMm+SZYmWXrppZfO0UORJEmSpMVlKEVqxvX81Szts+2zYmPV/lW1pKqWbLbZZjcyREmSJEla3BY6Qby4DRulnV7S2i8Ath653lbAha19qzHty+2TZB1gY1Yc0ipJkiRJWkULnSAeDuzdzu8NfHmkfa9WmXQ7umI0J7VhqFcn2bXNL3zmtH2mbutJwDFtnqIkSZIk6UZYZ75uOMlngAcBmya5AHgT8B/AIUn2AX4F7AFQVWcmOQT4CXAd8IKqur7d1D/TVURdHziy/QEcAByU5Gy6nsO95uuxSJIkSdKaYN4SxKp6ygybdpvh+m8F3jqmfSlw9zHtf6IlmJIkSZKkv95QitRIkiRJknpmgihJkiRJAkwQJUmSJEmNCaIkSZIkCTBBlCRJkiQ1JoiSJEmSJMAEUZIkSZLUmCBKkiRJkgATREmSJElSY4IoSZIkSQJMECVJkiRJjQmiJEmSJAkwQZQkSZIkNSaIkiRJkiTABFGSJEmS1JggSpIkSZIAWKfvACTN7FG3e1HfIXDEee/vOwRJkiQtEHsQJUmSJEmACaIkSZIkqTFBlCRJkiQBJoiSJEmSpMYEUZIkSZIEmCBKkiRJkhoTREmSJEkSYIIoSZIkSWpMECVJkiRJgAmiJEmSJKkxQZQkSZIkASaIkiRJkqTGBFGSJEmSBJggSpIkSZIaE0RJkiRJEmCCKEmSJElq1uk7AEmT72l3ekXfIXDw/76z7xAkSZImnj2IkiRJkiTABFGSJEmS1JggSpIkSZIAE0RJkiRJUmOCKEmSJEkCTBAlSZIkSY0JoiRJkiQJMEGUJEmSJDUmiJIkSZIkwARRkiRJktSs03cAkrQQnn+PV/cdAgAfPP0dfYcgSZI0I3sQJUmSJEmACaIkSZIkqTFBlCRJkiQBJoiSJEmSpMYEUZIkSZIEmCBKkiRJkhoTREmSJEkSYIIoSZIkSWrW6TsASdIyr7/Xa/oOAYC3nfz2vkOQJEk96KUHMckvk5ye5NQkS1vbJkm+meTn7fSWI9d/XZKzk/wsycNH2u/VbufsJO9Lkj4ejyRJkiQtBn32ID64qi4bufxa4FtV9R9JXtsuvybJDsBewN2ALYCjk9ypqq4HPgTsC/wAOAJ4BHDkQj4ISVoT/ef9Xtd3CAC86nv/3ncIkiQtKkOag7g7cGA7fyDw+JH2z1bVNVV1LnA2sEuS2wIbVdUJVVXAp0b2kSRJkiStpr4SxAKOSnJykn1b2+ZVdRFAO711a98SOH9k3wta25bt/PR2SZIkSdKN0NcQ0/tV1YVJbg18M8lPZ7nuuHmFNUv7ijfQJaH7AmyzzTarG6skSZIkrRF66UGsqgvb6SXAYcAuwMVt2Cjt9JJ29QuArUd23wq4sLVvNaZ93P3tX1VLqmrJZpttNpcPRZIkSZIWjQVPEJPcPMmGU+eBhwFnAIcDe7er7Q18uZ0/HNgryXpJtgPuCJzUhqFenWTXVr30mSP7SJIkSZJWUx9DTDcHDmsrUqwD/E9VfT3JD4FDkuwD/ArYA6CqzkxyCPAT4DrgBa2CKcA/A58E1qerXmoFU0mSJEm6kRY8Qayqc4Adx7RfDuw2wz5vBd46pn0pcPe5jlGSJEmS1kRDWuZCkiRJktQjE0RJkiRJEmCCKEmSJElq+loHUZKkeXfAbq/vOwT2+dbb+g5BkqRVZg+iJEmSJAmwB1GSpN59+TGv6zsEdv/qv/cdgiRpAOxBlCRJkiQBJoiSJEmSpMYhppIkaZUc/+RX9x0CDzjkHX2HIEmLmgmiJElaNE7f5xV9hwDAPQ54Z98hSNKN4hBTSZIkSRJggihJkiRJakwQJUmSJEmACaIkSZIkqTFBlCRJkiQBVjGVJElacOe+4mV9hwDAdu98d98hSBoYexAlSZIkSYA9iJIkSZrBhf82jJ7OLd5oT6e0UOxBlCRJkiQB9iBKkiRpwl3y4df2HQK3ft5/9B2CNCfsQZQkSZIkASaIkiRJkqTGIaaSJEnSArj8kH/tOwRu9eT/13cIGjgTREmSJEk3+O233td3CNxitxf3HcIaywRRkiRJ0sS56tRP9R0CG+30zL5DmHPOQZQkSZIkAfYgSpIkSdK8uPr8r/YdAgAbbv2YVb6uPYiSJEmSJMAEUZIkSZLUmCBKkiRJkgATREmSJElSY4IoSZIkSQJMECVJkiRJjQmiJEmSJAkwQZQkSZIkNSaIkiRJkiTABFGSJEmS1JggSpIkSZIAE0RJkiRJUmOCKEmSJEkCTBAlSZIkSY0JoiRJkiQJMEGUJEmSJDUmiJIkSZIkwARRkiRJktSYIEqSJEmSABNESZIkSVJjgihJkiRJAkwQJUmSJEmNCaIkSZIkCTBBlCRJkiQ1JoiSJEmSJMAEUZIkSZLUmCBKkiRJkoBFkCAmeUSSnyU5O8lr+45HkiRJkibVRCeISdYG/ht4JLAD8JQkO/QblSRJkiRNpolOEIFdgLOr6pyq+jPwWWD3nmOSJEmSpIk06QnilsD5I5cvaG2SJEmSpNWUquo7hhstyR7Aw6vqn9rlZwC7VNWLpl1vX2DfdvHOwM/mOJRNgcvm+Dbng3HOrUmIcxJiBOOca8Y5t4xz7kxCjGCcc80459YkxDkJMcKaHeftqmqzcRvWmeM7WmgXAFuPXN4KuHD6lapqf2D/+QoiydKqWjJftz9XjHNuTUKckxAjGOdcM865ZZxzZxJiBOOca8Y5tyYhzkmIEYxzJpM+xPSHwB2TbJdkXWAv4PCeY5IkSZKkiTTRPYhVdV2SFwLfANYGPl5VZ/YcliRJkiRNpIlOEAGq6gjgiJ7DmLfhq3PMOOfWJMQ5CTGCcc4145xbxjl3JiFGMM65ZpxzaxLinIQYwTjHmugiNZIkSZKkuTPpcxAlSZIkSXPEBFGSJEmSBCyCOYiStCZLshZwWlXdve9YFoska1fV9X3HofmX5J6zba+qUxYqFvUjyS2BOwI3nWqrquP7i2h27TN/g6q6qu9YtHiZIErqRZL7AadW1e+TPB24J/Deqjqv59AmSlX9JcmPk2xTVb/qO57ZJFkbeDSwLSPfP1X1rr5imsHZSQ4FPlFVP+k7mMUiya1Z/kf4EF6v72ynNwWWAD8GAvwNcCJw/57iGivJPwBvB25NF2eAqqqNeg1sQiX5J+AldOtonwrsCpwAPKTHsFaQ5H+A5wHXAycDGyd5V1X9Z7+RaT4l2aOqPr+ytnm5b4vU3DhJ3jfb9qp68ULFMptJ+DKZhBinJNkMeA2wA8v/0BnMl8kkxAiQ5DRgR7ofYgcBBwD/UFUP7DWwaZI8c1x7VX1qoWOZSZJjgHsDJwG/n2qvqsf1FtQYSY4A/gScDvxlqr2q3txbUGMk2ZBuXd1n003F+Djw2aEdsU+yK/B+4K7AunTLPf1+aJ+dSR5Hl4htAVwC3A44q6ru1mtgI5J8FnhrVZ3eLt8deGVVPavXwKZJcjbw2Ko6q+9YVmYSvtuTnE732fmDqtopyV2AN1fVnj2Htpwkp7b4ngbci+47/uSq+pueQ1tBkkcDd2P53x9v6S+iFSW5GfAKYJuqek6SOwJ3rqqv9hzacpKcUlX3XFnbfLAH8ca7Kd0P8M+1y3vQHdU5ta+AZvAOhv9lMgkxTjmY7n/+aLqjeXsDl/Ya0YomIUaA66qqkuxO13N4QJK9+w5qjHuPnL8psBtwCjCYBBEYVII1i62G+INmuqq6Gvgo8NEkDwA+A7y79Sr+a1Wd3WuAy3yALpH9PF3v1zOB7XuNaLx/peuZObqqdk7yYOApPcc03V2mkkOAqjojyU49xjOTiyfkuxIm47v9T1X1pyQkWa+qfprkzn0HNcZNktwEeDzwgaq6NsngeniSfBi4GfBg4GPAk+gOXA7NJ+h+s9+nXb6A7nN0EAlikkcCjwK2nNYhtRFw3ULEYIJ4490ReHBVXQs3vCmOqqqX9RvWCibhy2QSYpxyq5bIvKSqjgOOS3Jc30FNMwkxAlyd5HXAM4C/a8MPb9JzTCuoqheNXk6yMV2P52BU1XFJNmdZMntSVV3SZ0wzODLJw6rqqL4Dmc3IUNhn0w2HfSfdgZe/o1t39069BTdNVZ09MmfyE0m+33dMY1xbVZcnWSvJWlV1bJK39x3UNGcl+RjwaaCApwND/F5amuRzwJeAa6Yaq+qLvUU0s0n4br8gyS3ons9vJrkCuLDXiMb7CPBLuiHQxye5HTCoEQ3Nfavqb5KcVlVvTvJOYIivzTtU1Z5JngJQVX9Mkr6DGnEhsBR4HF0iO+VqYEHyDBPEG28LYEPgN+3yBq1taCbhy2QSYpxybTu9qA2juJBu7sKQTEKMAHsCTwX+sap+nWQbYBLmU/yB7gDRYCR5Mt1z9226YVzvT/Kqqjq018BW9APgsFZk4VoGOOSs+TlwLPCfVTWacB3aehSH4g9J1gVOTfIO4CLg5j3HNM5vk2wAHA8cnOQSFugo+Gp4NvDPdPPRoIv1Q/2FM6ON6D6DHjbSVgzzR/jgv9ur6gnt7H5JjgU2Bo7sMaSxqup9wGhP0nmtJ35o/thO/5BkC+ByYLse45nJn5OsT/feIckdGHmN9q2qfgz8uM09DXAXulh/VlV/XogYnIN4IyV5NrAf3Y8IgAcC+1XVgb0FNUaST4xprqr6xwUPZgaTEOOUJI8BvgNsTTf3ZyO6+QqH9xrYiEmIcUo7CnrHqjq6zQlYuw3vG4wkX6F9idDNR9sBOKSqXttfVMtL8mPg76d6Dds81KOrasd+I1teknPohkidXgP+8kmyQVX9ru84Vqa9fy6h63l/Gd2P2w8OaAgsAEluTjf3NMDT6OI8uKou7zUwzatJ+G5P8paq+peRy2sDn6qqp/UY1graCJG3AVtU1SOT7ADcp6oO6Dm05ST5f3S/O3YD/pvuu/NjVfX/eg1smiR/D7yR7vv8KOB+wLOq6tt9xjVdkkfR9R7/gu7zczvguVU17wcxTBD/CkluA/xtu3hiVf26z3ikSZLkOcC+wCZVdYc2SfzDVbVbz6EtJ8lo0ZzrgPOq6oK+4hknyelVdY+Ry2sBPx5tG4Ik3wAeWVV/WemVe5TkTnS9R5tX1d2T/A3wuKr6t55D0zxJV1V5P7oCOqMVdm/fV0zj+NqcW0k+Sdcr8+9J1qObh3ZKVe3Xa2DTJDmSbt7cG6pqxyTrAD8a2mf8qPZ83rSqruw7lnGS3IpubnToihRd1nNIK0jyU+AxUwf9Wk/n16rqLvN+3yaIN14mYO2cJDcF9mHFilJDOoI3CTG+uqrekeT9LOtNukENoGrtJMQ4KsmpwC50B1d2bm2nD+kLrx1N/kZVPbTvWGaT5D/pqsF+pjXtSbc24mv6i2pF7cfY7emGcI0OORvUMhdtzu6rgI+MvDbPqIGsNZnkkKp6croKjOPe64MoBJTku1V1/yRXs3ycgxta3H6IvYxuvs8Na2AOrZdz6K9NmKzvojbv7GC6ysoPBo6sqnf3G9WKkvywqu6d5Ecj//dTq2qnnkMDIMlDquqYdJVrVzCkYcUASZ4AHDOVvLZ5qA+qqi/1Gdd0SY6vqgeMXA5w3GjbfHEO4o2UCVk7h66Yxk+BhwNvoRveM7RJ45MQ41Q8S3uNYnaTEOOoa6rqz1PzwtsR0UEdsaqq65P8IcnGQz0KClBVr0ryRLphMgH2r6rDeg5rnHPb37rtb6huVlUnTatZMKQ5c1Pz5B7TaxQrUVX3b6cb9h3LKrhyIYZtzYGhvzZhAr6LkowuE/BeumF836Mr6nbPqjqln8hm9PvW4zU1Z25XYEjfSQ8EjgEeO2bbEOfIvmn0O7KqfpvkTXTzZYfkzHTLQx1C9zzuAfxwKhGfz8TbHsQbKZOzds6PqisrflqrLHUTuh6RwSSykxDjJEqyEd1R+kHN6ZvSimr8lq40/4uA5wM/qao39BnXdEkOoTsA9E2WX2NwMEfBJ026dQZrqPP82nCuFwKfr6p7JnkSsE9VPbLn0CZOG+582pB6uMZJ8h9060h+keV7tweVKPjanButIM1Mami/P1pC+37g7sAZwGbAHq2YySC09/qTquqQvmNZmanfm9PaBjWCCWacxztlXufz2oN4403K2jlTFS1/m27h31/TlW0fksHHOK1QyQpqQAuSJ1lCN1dhw+5ifktXKfTkWXdceK+lG1p8OvBcuuUDPtZrRON9rf0Nzpihe8sZ0hA+uGHx8YOATdrly4BnVtWZvQa2ohcA+wN3SfJ/dL2egylaMcv/fXBDN6vqL0l+nGSbqvpV3/HMYqqewJKRtmJ4o4LGvTaf3m9I47ViWa+hKwQyOn2k9+e0qoZYAXQ2Z9L10t2Z7n3+M7qiaYPR3usvpOvtGrqlSd7FskI6L2L55SSG4hVV9ZuVX23umSDeeJOyds7+ba7kG4HD6ZbjGFQ1KSYjxv9qp/8A3IZurSzoFnv+ZR8BzeLjwPOr6jsASe5PlzAOYl7SlFao5KPtb7Cq6sB05bC3qaqf9R3PqKmhe0neQndg5SCWVYoc4rC+/YGXV9WxAEkeRPf/v2+PMY1zy6p6aLrqm2tV1dVJHguc13dgMDFDNkfdlm6o1Eks3ws/mANrk5IwVNU5wHKvzb5jmsXBwOfo1hR9HrA3cGmvEU3TCqk8ke6g9Ghxorf0FdMMTqiqe9IligAkOQW458y79OKbSV5J938ffa/3kuTM4kV0vzM/R/edeRTdwZehObHVa/gE3fzYBRv26RDTOZCuyuHGwNdrgdYnWVVJtquqc1fW1qdJiHHK9AnDM7X1Kcn3qup+K2vrW1asGjjV+zG0qoGPpTtAsG5VbZdkJ+AtQ/pxm+TEqvrblbX1LcmPa9rSG+Pa+tZ+eO1dVae3y3sBLxva8zklya1ZvodmUD11Wb4S8A2q6riFjmU26daNnV4sbVCJQjsw/UxWTGgGN+Q9yclVda/R4XxJjquqsa+HPiT5Ot1cvunFid7ZW1Aj0lXL35LuoPRT6b4noVu+6sO1ANUsV0eScb/bBve9PilaUZqHAv9IV9Tvc8Anq+p/5/u+7UG8EabPqRjal9w0X2DFI0yHAvfqIZaZTEKMUzZLcvt2FJck29HNBejdyKT7k5J8hK6iZdFVtPx2X3HN4gDGVA0coP3oPpi/DVBVp7b/+5Bcn+RpwGfp/udPYZjP6Tnp1sk6qF1+Ot0QuaF5EnBoe07vT/eD/GGz77LwkjwOeCewBd16iLejKxBytz7jmq6qjsuYNU/7jmtUkg8DN6OrZPkxutfASb0GNd4RwA/ohuYPerkYlk0fuagl3xfSFfYbkq2q6hF9BzGLhwPPonveRqs9Xw28vo+AZlNVQ/tuHCvdcjGvZMUDLb0Pfx7Vegy/Sdcz+2C6AwXPT7f28Wur6oT5um8TxBthEuZUtKI5dwM2zvJlhzdi5OhonyYhxjFeBnw73YLf0H24PLe/cJYz/Yjnm0bOD3GowKRUDbyuqq7M8lUDh/Z8PpWuEt976WL7Xmsbmn8E3kxXCCTA8cCze41ojKo6p/Uafgk4H3hYVf2x36jG+le6AkpHt0JfD6Y7ODAoGVnzFLgDXY/Ih+kW0x6K+7YiaadV1ZuTvJPhVV6Ebl25l/cdxCr6tyQbA6+gK7CyEd136JB8P8k9pkYLDE1VHQgcmOSJVfWFvuNZmXbw5+V0UzL2Tbe+8Z2r6qs9hzbd5+k+gz7GMA+mAjes1fh04BnAxXRDYw8HdqJ7DPOWkJsg3nhDn1NxZ7oS6Ldg+bLDVwPP6SOgMSYhxuVU1dfbB97UsI6fVtU1s+2zUCZlDs2IY9Ot3zfoqoHAGUmeCqzd/vcvBr7fc0zLqapfArv3HcfKVNUVdM/fIGXFdQU3oevpOjHJYNYXHHFtVV2eZK0ka1XVsUne3ndQY7yAtuYpQFX9vA2LHZKpAwB/SLIFcDnz+OPrr3BQS7i/yvKfm0Ob48VIUnAlXc/sEN0feFYbGnkNy6Y6DOq9XlVfmIQh0HRz5U5m2bzyC+gSmaEliNdV1Yf6DmIVnEA34ubxVXXBSPvSNuph3pgg3nhv7juA2VTVl4EvJ7nPfHZB/zUmIcYZ3ItlwxJ2bD8cP9VvSMtM0ByVSaka+CLgDXQ/Hv4H+Abwb71GNE2Sm9JVhJ3+42HeSmCvjkxOFeBBrys4xm+TbEDXE3twkksY3pp4MAFrngJfbZ+d/wmcQhffEKsq/5kuxjew7DksYHBzvJLcnm5Uw33ohsOeQDeX95xZd1xYE7E8yAQNgb5DVe2Z5CkAVfXHTBt+MxBfSfJ84DCGfaDlzjMVpqmqeT0YaIJ4Iw183uGoJyQ5k+7o6NeBHYGXVtWnZ99tQU1CjAAkOYhuiNSpLBuWUMBgEkQmZI7K0Hs8W9L1PGB7uufyPlU1xB/f0B1h/CndfJW30FUxPWvWPRbWRFQBrqrzps8xH7jdgT/RDdt7Gl2xtKH1KEC3+PjrgfWT/D3dmqdf6Tmm5VTVv7azX0jyVbqhnENaiHzKy4Htq+qyvgNZBf9Dt4zAE9rlvejmxg+m2FNVnQcrFnoaoEkZAv3ndFW/CyDJHRhJwAZk73b6qpG2IR5o+fKY/PpKYCnwkar603zdsVVMV1MmaP0pgCSnVtVOSZ4APJ7uh8SxQ6oaOAkxTklyFrDDQpYaXl1JTmnlsAcpydOr6tNJxs6jqap3jWtfaEk+R1dk4Tt0R5l/WVUv7TWoGST5UZuDdlr7EXET4BtDm3CfCagCDJDkYOB1Q51jPl2SjVh+tMCgjoK3pHsfukI/oeuF/9gQPkenzX9fQVUN6kd4ksOBvarqD33HsjIZX135B1W1a18xTTdToaeqGlShp6nnMskP6A60XQ6cUVV37Dm05bQDQG+kW/vyKOB+wLOq6tt9xjWpkryXrhDiZ1rTnnRLWq0PbFRVz5iv+7YHcTXV5K0/dZN2+ijgM1X1mwH29k9CjFPOoOsBuajvQGYx9DkqN2+nQ38v7VBV9wBIcgDDHM4zZapa4G/TLUb/a7ohxkMz2CrA0wx9jjkASZ5L12P4R7rRAmGAR8Fr2GuePnaWbcXwemmuB05NcizLf74PbQoBdPPMX8uy6sp7Al9LsgkM5jtpIgo9MSFDoKvqm+mWCdqV7vPoJUPt7W7flTuw/LSMIY0GA9h52gHUr0wdVG0j7+aNCeLi95UkP6X7AfH8JJvRDUkakkmIccqmwE/aD8fRL+ch/XAc9ByVqvpIOx30PF6WJV1U1XUDPmgBsH+SW9It/Hs4sEE7PzRDrgI8auivzSmvBO421B9gU8YU/4Flw6T+raouX/ioOlU1uCq6K/Gl9jcJ9myn+7bTqQ/Rf2Q430mTUujpHa0g3g1DoBng76QsW25r6iD6Nq2S7XlDmqKR5E3Ag+gSxCPoRgl9l2FNF4LuoOoNKyYk2Ybudyh0v/XmjUNM1wDth+NVVXV9K0G8UVX9uu+4Rk1CjDAZCz4n+QXwtxPwo3GqgMGudD8WBlXAIMn1LOs9Ct2Qjj8wwOHkSdauqsGW6h6VZD0GWAV4EqVb5Psfhj7cMMk76Hq+/qc17dVOrwLuX1Wz9eLNq0kZ8j6qzfHapqp+1ncs4yS5N3D+1Hd4kr2BJ9LNN95vID2HACQ5mm5qy7/T/fC+BLh3Vd13tv0W2ripI0OcTtKGwN4TOI3uu/Lu7fytgOdV1VE9hneDdtBqR+BHVbVjks3phr339lk0TpJH0S3H8Qu653M7ujnc3waeU1Xvma/7tgdxkUrykKo6ZnR+xbQekN6HzUxCjNMNKRGcxZl0iczQDbqAQVUNaiHvlTi3JQufA44ZwtyuccbM97pDkiuB06vqkj5iGmfaXPN16YbB/35IBwWa19Gt43Yiwx5ueL+qut/I5dOTfK+q7pfk6b1F1ZmUIe8AJHksXdGndYHtkuwEvGVgo1g+AjwUIMkD6JKvF9Gt3bY/XQXOodidbvTSaKGnwYwgSHIbunVD10+yM8t6YTeiq2o6NL8E9qmqMwGS7EBXCOZf6X7TDSJBBP5Y3Zrm17U53JcwjB7t5VTVEVm2tFroDqpO9Ry/Zz7v2wRx8XogcAzj51cMZV7FJMQITFxxokmZo5KqOmjk8qeTvLC3aCbbneneRy8APp5uWYnPVtV3+w1rBfvQlbw/hu698yC6irt3SvKWaa+H3kyfa57k8XTr+A3NR+iey0FXLAY2SPK3VXUiQJJd6IZBQ8/LckzQkPcp+9G9Fr8NUFWntrm8Q7L2SC/hnsD+1S3y/oUkp/YX1oqqamqUyF+AAwGSfI+uuMoQPBx4FrAVXTGdqQTxauD1PcU0m7tMJYcAVfWTJDtX1TkDm6axtM3p/Cjduo2/Y0B1BpK8uqre0S4+rqo+P7LtbVU17/97h5gucknWmz6EK8kmQxriobnVhvOsoKoOXOhYZpPkP4DfsnwBg/XoehWHUsBg4rTh2u8Fnja0XtCWuP5TVV3cLm8OfAj4J+D46nlpiSTrzDRPZmjVFwGSfH9oQ+HGaUMOP06XFIZuaOk/0Y12eHRVHdJjeMDw1xKdMlLN8kdVtXNrO60GtLB7kjOAndrc7Z8C+1bV8VPb+n6fr0yS86tq677jGJXkiS3JHrR01b9/Q/e9Dt33+qbAM4DvVtW9+4ptSrpMdauqOr9d3pZuWtNpvQY2YnT48PShxAs1tNgexMXvi0l2n/rR04YrfI1usfdBaHOSnsiKC7sPcT2vwauqA5OsC9ypNf2sqq6dbZ+eTBUwmF6kZEgFDCZGmx+7J91k+x8CT+43orG2nUoOm0uAO7XKxUN4jZ4E3HPaUNi1gCUMb2F36KpE7ku3puAQKxYDUFU/BO7RilWkqn47srn35LAZ9FqiSY6gGyFwRpKnAmu3oWcvBr7fa3Ar+gzd2peX0Q3f/A5Aku3pihMN3WDe621I8WlTyWGSf6H7vXQeXYXQc/uMb4xn0c2ReyndwaDv0hXTuhYYxNrHVVVJvkT7HVxVv+w1oPEyw/lxl+eFCeLi9yXg0CRPBLamq3D4yl4jWtGX6b40TmaYC6pOlCQPohsq80u6D5Ktk+w9dQR3KKpqaMOiJlaSc4FT6X5sv2pk2NTQfKdV4JsaLvNE4PgkN6frTR6Kx7LsR+J1dO+lIc3xmvLUdvq6kbbBHFyZqQDM1FCzgRWA2b6q9mgHVA9M8j906zUOxSfp4jmIrvDHNXTzuL9BN79rMKrqrUm+RbdczFEjc6LXopuL2Lsx86Fv2ERXkGwo3kpXyI0kjwGeTrcMx850xUse3l9oK6qqP9INhX3nmM2/W+BwZvODJPduB6+GqGY4P+7yvHCI6RogyQuAR9BKylfVoI42TsKQk0mS5GTgqVMV7pLciW59ycH0GsMNQ7qeD9yf7gPvO8CHRyZgaxUl2aiqruo7jpVpQ3ueSDe/Z+ro8heGUlQnyQXAu1jxCG3B4BKawUvy3Kr6SLqS8isY0ry/JCdV1S5Jjqf7XPo1cFJVDSLZBmgHUv6F7vv8IEaWMfK1uXqSfGK27TWQ5U+S/LiqdmznP043Iujt7fJgqphm/FI2U2rqMQxFkp/Qzd3/JV218ql6EoMYqp1lVdRHK6jTLt+0qm4y075zxR7ERWraEdvQ9R6eCuyaZNeBfZl8P8k9qur0vgNZJG5SI+XPq+p/k8z7h8mN8Cm6ifbvb5efQvejZ4/eIpowSd5P+1IeVwBgaIWJWiJ4aPsborVZNk9u8Nr7+p+BqYWUvw18ZChDyiesAMy4tUT/pd+QVnAt3Y/G9ejiG8SBlUk0lARwFSTJBnQJwm7AB0e23XT8Lr14zJi20BXXGUwxnSxbU/CRfccymyHUDzBBXLyml+w+bIb2Ibg/8Kw2TO4aBnYkZwItTXIAXbIF3Vyak3uMZyZ3nnZU8dgkP+4tmsm0tO8AVkcb1vV24NZ07/OhVQG+aMLmPn+IbgmOqR+Nz2BZ0Z/etflSM6mqGszQyKr6WDt7HAMZojsqySPoercPB+5ZA1/7UnPmPXQH968CzqqqpQBtyYuLZt5tYVXVeVPn29IrT6WbB38uMKTiOl+ie/+cl+QLVfXEvgMaKoeYqndJbjeuffQDR6uuFf15AV3iHeB44IPTq9n2Lckn6YaU/qBd/ltg76p6fq+Bad4kORt4bFUNpvjHqNHKkJNgdPjZbG19SfKKMc03p6sWequq2mDM9l4MvVhaku/QLTR+5kqvrEUlyZZ0B9V+XFV/aW23pRst9Kteg2vaVJa96EYCXU63Ju8rq2rs77u+TKv+O1Gf9wvNBHGRS7IZ8GpWLN39kN6CmkGSW7N8jIP44NP8SHIW3RyAqf/zNnRVA/+CPcirpb3PXwPswIDf52mLo/cdx0wmbQmgJKcAe1TVL9rl2wOHDmVe0qgkGwIvoUsODwHeWVWX9BvVMkm+zrJiaddPtVfVuGIbkkYk+QtdHYF9qurs1nbOkObwwuzLR2h5DjFd/A6mO5LzGOB5wN7Apb1GNE2Sx9FVvNqCruz97egShbv1GdekWckkcQaYcD2i7wAWkan3+aMZ6Pu8WdrWyfoSyy/L8MXeIhoxSclh8yq6odnntMvbAoOaW5VkE+DldEPdD6Qb3nVFv1GNtVVV+Zm0hkjykKo6ZqZqpkP5TJogT6TrQTy2HWz5LMOcy71jkqtoxV/aeRjedIfemSAufreqqgOSvKSqjqNbm+i4voOa5l/pyjgfXVU7J3kw3TAFrZ5xk8QHZ6Ti5tXjtk/gj/QhmIT3OcBGdMUWHjbSVoA/xlZDuoXnz6+qb7W18J4LPBQ4ChjMPN4k/wn8A7A/cI+qGlKZ++kslrZmeSBwDN2SNtP5mbSaquow4LBWaffxwMuAzZN8CDisqo7qM74pQyj+MikcYrrIJflBVe2a5BvA+4AL6YYg3aHn0G6QZGlVLWkFSnauqr9MlRzvO7ZJlWRz4N7t4kkDG8r11ap6TCtKVCx/lLGGNiRlEkzC+1xzpw0tfWhV/SbJA+iO1r8I2Am4a1U9qc/4prRhZ9fQrSU5+mNjMEfrk5xBN6x9HeCOwDlYLG2NkGQt4ElVdUjfscyk9cDPaMgHVFvsewB7Dm26g1bOBHGRawurfodumYv30x3Bf3NVHd5rYCOSHE13xOnfgU3phpneu6ru22dckyrJk4H/pCt5H+Dv6BZPH+rSAvorDf19nuTVVfWO0WU5Rg1tOY6hm7Y22n8Dl1bVfu3yqVW1U4/hTZQkV9Al1mNZLG1xS3J8VT1g5dfsx7QDqdsAV7TztwB+VVXb9RedFjOHmC5SbRHy5wHbA1sCB1TVg/uNaka7A3+iG5LwNGBjYBCV4ybUG+gS7EvghgImRzOQteeSzDopvKpOWahYFouq+mo7eyUwxPf5VNXSiVqWY8DWTrJOVV1HtzbaviPb/F5fPeeaBK7RvpnklXRzuH8/1TiUnrmpBDDJh4HDq+qIdvmRdMPKpXlhD+Ii1QpBXEvXq/BI4Lyqekm/UWkhJDm9qu4xcnktuvLY95hltwWT5NhZNpdDUVZdkucA366qnycJ8HG6OV/n0S0Z8qNeA2yS7FhVY+fGJfnnqvrQQsc0yZK8AXgUcBldr8I9q6qSbA8cOORKsUOT5AK69QXHqqoZt2nytR666QY31SHJyVV1r2ltS6tqSV8xaXHzSOPitcNUQtAWTT+p53hmNAGLZ0+ar7e5aJ9pl/cEjugxnuUMuCd7Er0E+GQ7/xTgb+gW+d6Zbi7i3/UT1goOS7JHVZ082pjkzXRFIkwQV0NVvTXJt4DbAkfVsiO9a9HNRdSqWxvYgGFWXNQ8m6AhmpcleSPwabohp0+nW29Qmhf2IC5S09d3GfJ6L0NfPHtStN6Dzavqey3pvj/dj54rgIOn1krrm+XF587ofLMk/wOcWFXvbZcH855Pci/g88DTquqE1tv5IeBOwONbVVtpwQ3pfaKFM1IJ+Nft8jPplmo4D9hvKENMp7SCL28CHkCXIB4PvGVocWrxMEFcpJJcz7Lx9AHWpysvP7jeuaEvnj0pknwVeH1VnTatfQnwpqoaV857wSV5c1W9KcknxmyuqvrHBQ9qQrVqlo+mOwhwHvCQqjqzbTurqu7aZ3yjkvwNcBjwAuA5rfkpVfXn/qLSmi7Jj6pq577j0MKalErA0yXZYODLxWiRMEFUb0Z6kB4I3IaBLp49KZKcUVV3n2HbcvMStTi06qUfoRsm95Wqek5rfyDw6qp6dJ/xTRkp1b4D3fv8aOCFdMsLDKYghNY8STbx9bfmmbRKwEnuC3wM2KCqtkmyI/Dcqnp+z6FpkTJBVG9m6EGaYk/SakpydlVtv7rb+pJkPbohPdsyMh+6qqxguxqSrANsWFVXjLTdnO7zfRBHmkdKtcOyuV5TpdsHVxBC0uLW1r/cqaquS/JTYN+qOn5q20wHW/uS5ETgSXSVTHdubYOLU4uHRWrUm6p6dt8xLDI/TPKcqvroaGOSfYCTZ9inT1+mW5bhZEZ6jrV62lIHV0xr+/0MV+/FBBWCkLRm+AxwXJLLgD/SVXyfmst/ZZ+BzaSqzu+mb9/g+r5i0eJngqjeJXnfmOYrgaVV9eWFjmeCvZSuWuTTWJYQLgHWBZ7QV1Cz2KqqHtF3EJKkNcsEVgI+vw0zrSTrAi9m2fqy0pxziKl6l2R/4C50VQ6hG3Z4JrA1cE5VvbSn0CZSkgcDU8NOzqyqY/qMZybt//7+qjq971gkSRqqJJsC7wUeSjc0/yjgxc6f1XwxQVTvkhwDPKwNlZuaU3UU8PfA6VW1Q5/xaW4lOZ1u/tk6wB2Bc+iGmE7NR/ubHsObKElmLc9fVacsVCySpPmR5H5V9b2VtUlzxSGmGoItgZuzbNz/zYEtqur6JM5NW3we03cAi8g7Z9lWwEMWKpDZjFQxHcuj4JI0q/cD0w8IjmuT5oQJoobgHcCpSb5N14v0AOBtrRLj0X0GpnlxMfA8YHvgdOCAqd5jrZ6qenDfMayik1lWtXQbuqI6AW4B/AqwiI0kTZPkPsB9gc2SvHxk00Z0yxtJ82KtvgPQmivJ/drZT9N9AH6p/d2/qj5WVb+vqlf1FJ7mz4F0xXNOBx7J7L1gmkWSV4+c32PatrctfETjVdV2bSmLbwCPrapNq+pWdL3JrncqSeOtC2xA16Gz4cjfVXTLXkjzwjmI6k2Sk6vqXklOqSqHSawhkpxeVfdo59cBTvL/f+OMvnemv4+G+L6aes9Pa1taVUv6ikmShi7J7arqvL7j0JrDIabq07VJPgFsOWapi6qql/QRlObdtVNn2iLFfcYy6TLD+XGXh+CyJG+kGzVQwNOBy/sNSZKGKcl7WiX3DyRZoUenqh638FFpTWCCqD49hq5k80NYfiH3rYHXASaIi9OOSa5q5wOs3y5PVTHdqL/QJk7NcH7c5SF4CvAm4DC6+I5vbZKkFR3UTv+r1yi0xnGIqXqXZEe65OCpwJOBXwJfqKr39xmXNHRJrgd+T0u0gT9MbQJuWlU36Su22STZoKp+13cckiRpRfYgqjdJ7gTsRdeDcDnwObqDFg/qMy5pUlTVRFWxS3Jf4GN0RRe2aQeHnltVz+83MkkarlbUbz/gdnS/3adG3Ny+z7i0eNmDqN4k+QvwHWCfqjq7tZ3jB560OCU5ka7y3uFVtXNrO6Oq7t5vZJI0XEl+CryMbjrO9VPtVeUcbs0LexDVpyfS9SAem+TrwGcZZmENSXOkqs6fVpjo+pmuK0kC4MqqOrLvILTmMEFUb6rqMOCwJDcHHk93dGzzJB8CDquqo/qMT9KcO78NM60k6wIvBs7qOSZJGrpjk/wn3bqx10w1VtUp/YWkxcwhphqUJJsAewB7VtVD+o5H0txJsinwXrrqxQGOAl5cVb/pNTBJGrAkx45pLn8nab6YIEqSFkSS+1XV91bWJkmS+mOCKElaEElOqap7rqxNkgRJXj6tqYDLgO9W1bk9hKQ1hHMQJUnzKsl9gPsCm037wbMRMFFLdUjSAtpwTNu2wBuS7FdVn13geLSGMEGUJM23denWPlyH5X/wXEW37IUkaZqqevO49lav4Wi66u/SnHOIqSRpQSS5XVWd13cckjTpkvxoaj1Zaa7ZgyhJmldJ3lNVLwU+kGSFo5JV9biFj0qSJlOShwBX9B2HFi8TREnSfDuonf5Xr1FI0gRJcjpdYZpRmwAXAs9c+Ii0pnCIqSRJkjQwSW43ramAy6vq933EozWHCaIkaUEkuR+wH3A7uhEsoVvs+fZ9xiVJkpYxQZQkLYgkPwVeBpwMXD/VXlWX9xaUJElajnMQJUkL5cqqOrLvICRJ0szsQZQkLYgk/wGsDXwRuGaqvapO6S0oSZK0HBNESdKCSHLsmOaqqocseDCSJGksE0RJkiRJEuAcREnSPEvy8mlNBVwGfLeqzu0hJEmSNIO1+g5AkrTobTjtbyNgCXBkkr36DEySJC3PIaaSpF4k2QQ4uqru2XcskiSpYw+iJKkXVfUbIH3HIUmSljFBlCT1IslDgCv6jkOSJC1jkRpJ0rxKcjpdYZpRmwAXAs9c+IgkSdJMnIMoSZpXSW43ramAy6vq933EI0mSZmaCKEmSJEkCnIMoSZIkSWpMECVJkiRJgAmiJEljJblNks8m+UWSnyQ5Ismd5vD2H5TkvrNsf1yS187V/UmStCqcgyhJ0jRJAnwfOLCqPtzadgI2rKrvzNF97Af8rqr+a8y2darqurm4H0mSVocJoiRJ07Q1GverqgdMaw/wDuCRdNVY/62qPpfkQcArq+ox7XofAJZW1SeT/BI4EHgscBNgD+BPwA+A64FLgRcB+wC/AXYGTgFOB5ZU1QuTbAZ8GNimhfLSqvpekgcC721tBTygqq6e46dDkrQGcR1ESZJWdHfg5DHt/wDsBOwIbAr8MMnxq3B7l1XVPZM8ny6R/KckH2akBzHJPsCdgIdW1fVJnjWy/3uBd1fVd5NsA3wDuCvwSuAFLVncgC7xlCTpRjNBlCRp1d0f+ExVXQ9cnOQ44N7AVSvZ74vt9GS6JHMmn2+3Pd1DgR26DkwANkqyIfA94F1JDga+WFUXrOLjkCRpLIvUSJK0ojOBe41pz5g2gOtY/jv1ptO2X9NOr2f2g7O/n6F9LeA+VbVT+9uyqq6uqv8A/glYH/hBkrvMctuSJK2UCaIkSSs6BlgvyXOmGpLcG7gC2DPJ2m1e4AOAk4Dz6Hr41kuyMbDbKtzH1cCGqxjPUcALR2LZqZ3eoapOr6q3A0sBE0RJ0l/FIaaSJE1TVZXkCcB72lITfwJ+CbwU2AD4MV1RmFdX1a8BkhwCnAb8HPjRKtzNV4BDk+xOV6RmNi8G/jvJaXTf3ccDzwNemuTBdD2TPwGOXI2HKUnSCqxiKkmSJEkCHGIqSZIkSWpMECVJkiRJgAmiJEmSJKkxQZQkSZIkASaIkiRJkqTGBFGSJEmSBJggSpIkSZKa/w+RAh//ZSR4VQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplots(figsize=(15,6))\n",
    "sns.barplot(df['country_txt'].value_counts().index[:20],df['country_txt'].value_counts()[:20].values,palette='magma')\n",
    "plt.title('Countries with most acts of terrorism')\n",
    "plt.xlabel('Countries')\n",
    "plt.ylabel('Count')\n",
    "plt.xticks(rotation= 90)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Anaconda\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,6))\n",
    "sns.barplot(df['city'].value_counts()[1:11].index,df['city'].value_counts()[1:11].values, palette=\"Blues\")\n",
    "plt.title('Cities with most acts of terrorism', fontsize=20)\n",
    "plt.xlabel('Cities',fontsize=16)\n",
    "plt.ylabel('Count',fontsize=16)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Anaconda\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplots(figsize=(20,5))\n",
    "sns.countplot('targtype1_txt', data=df, palette='Blues')\n",
    "plt.xticks(rotation=90)\n",
    "plt.xlabel('Target Type')\n",
    "plt.title('Targets by Terrorists')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Anaconda\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(18,10))\n",
    "sns.barplot(df['gname'].value_counts()[1:16].values, df['gname'].value_counts()[1:16].index, orient='h', palette='magma')\n",
    "plt.title('No. of Terrorist Activities by Terrorist Group', fontsize=20)\n",
    "plt.xlabel('Groups', fontsize=16)\n",
    "plt.ylabel('Count', fontsize=16)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Number Of People Affected Analyzation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Anaconda\\lib\\site-packages\\pandas\\core\\generic.py:3887: PerformanceWarning: dropping on a non-lexsorted multi-index without a level parameter may impact performance.\n",
      "  obj = obj._drop_axis(labels, axis, level=level, errors=errors)\n"
     ]
    },
    {
     "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>gname</th>\n",
       "      <th>country_txt</th>\n",
       "      <th>nkill</th>\n",
       "      <th>nwound</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Islamic State of Iraq and the Levant (ISIL)</td>\n",
       "      <td>Iraq</td>\n",
       "      <td>31058.0</td>\n",
       "      <td>23697.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Taliban</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>29269.0</td>\n",
       "      <td>27871.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Boko Haram</td>\n",
       "      <td>Nigeria</td>\n",
       "      <td>16917.0</td>\n",
       "      <td>7671.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Shining Path (SL)</td>\n",
       "      <td>Peru</td>\n",
       "      <td>11595.0</td>\n",
       "      <td>3030.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Liberation Tigers of Tamil Eelam (LTTE)</td>\n",
       "      <td>Sri Lanka</td>\n",
       "      <td>10928.0</td>\n",
       "      <td>10991.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Al-Shabaab</td>\n",
       "      <td>Somalia</td>\n",
       "      <td>8176.0</td>\n",
       "      <td>6025.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Farabundo Marti National Liberation Front (FMLN)</td>\n",
       "      <td>El Salvador</td>\n",
       "      <td>8019.0</td>\n",
       "      <td>4049.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Islamic State of Iraq and the Levant (ISIL)</td>\n",
       "      <td>Syria</td>\n",
       "      <td>6883.0</td>\n",
       "      <td>4031.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Nicaraguan Democratic Force (FDN)</td>\n",
       "      <td>Nicaragua</td>\n",
       "      <td>6630.0</td>\n",
       "      <td>728.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Tehrik-i-Taliban Pakistan (TTP)</td>\n",
       "      <td>Pakistan</td>\n",
       "      <td>6014.0</td>\n",
       "      <td>9518.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                              gname  country_txt    nkill  \\\n",
       "0       Islamic State of Iraq and the Levant (ISIL)         Iraq  31058.0   \n",
       "1                                           Taliban  Afghanistan  29269.0   \n",
       "2                                        Boko Haram      Nigeria  16917.0   \n",
       "3                                 Shining Path (SL)         Peru  11595.0   \n",
       "4           Liberation Tigers of Tamil Eelam (LTTE)    Sri Lanka  10928.0   \n",
       "5                                        Al-Shabaab      Somalia   8176.0   \n",
       "6  Farabundo Marti National Liberation Front (FMLN)  El Salvador   8019.0   \n",
       "7       Islamic State of Iraq and the Levant (ISIL)        Syria   6883.0   \n",
       "8                 Nicaraguan Democratic Force (FDN)    Nicaragua   6630.0   \n",
       "9                   Tehrik-i-Taliban Pakistan (TTP)     Pakistan   6014.0   \n",
       "\n",
       "    nwound  \n",
       "0  23697.0  \n",
       "1  27871.0  \n",
       "2   7671.0  \n",
       "3   3030.0  \n",
       "4  10991.0  \n",
       "5   6025.0  \n",
       "6   4049.0  \n",
       "7   4031.0  \n",
       "8    728.0  \n",
       "9   9518.0  "
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2 = df[['gname','country_txt','nkill', 'nwound']]\n",
    "df2 = df2.groupby(['gname','country_txt'], axis=0).sum().sort_values(['nkill', 'nwound'], ascending=False).drop('Unknown').reset_index().head(10)\n",
    "df2\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "    }\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>country_txt</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>iyear</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1970</th>\n",
       "      <td>Dominican RepublicMexicoPhilippinesGreeceJapan...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1971</th>\n",
       "      <td>United StatesWest Germany (FRG)United StatesUn...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1972</th>\n",
       "      <td>PanamaPhilippinesKuwaitSpainArgentinaUnited Ki...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1973</th>\n",
       "      <td>ColombiaIrelandDominican RepublicUnited Kingdo...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1974</th>\n",
       "      <td>ItalyFranceItalyBoliviaUnited KingdomArgentina...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1975</th>\n",
       "      <td>PakistanSpainSpainSpainUnited KingdomNetherlan...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1976</th>\n",
       "      <td>TurkeyTurkeyPortugalWest Germany (FRG)United S...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1977</th>\n",
       "      <td>JapanJapanJapanFranceFranceSpainItalySpainItal...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1978</th>\n",
       "      <td>BrazilEl SalvadorItalyItalyItalyJapanNetherlan...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1979</th>\n",
       "      <td>JapanColombiaPhilippinesNicaraguaNicaraguaPeru...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980</th>\n",
       "      <td>West Bank and Gaza StripUnited KingdomUnited K...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981</th>\n",
       "      <td>IrelandEl SalvadorIraqPeruFranceSomaliaSomalia...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1982</th>\n",
       "      <td>CanadaGuatemalaIranColombiaColombiaColombiaGua...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1983</th>\n",
       "      <td>South AfricaUnited KingdomNetherlandsPeruPeruP...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1984</th>\n",
       "      <td>PeruEl SalvadorEl SalvadorWest Bank and Gaza S...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1985</th>\n",
       "      <td>West Germany (FRG)FranceFranceFranceFranceFran...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1986</th>\n",
       "      <td>SwedenSri LankaFranceIsraelPeruPeruPeruPeruPer...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1987</th>\n",
       "      <td>LebanonIndiaEl SalvadorPeruSouth AfricaIndiaLe...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1988</th>\n",
       "      <td>ChilePeruPeruPeruPeruPeruSri LankaPhilippinesP...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1989</th>\n",
       "      <td>ColombiaUnited StatesIndiaIndiaIndiaIndiaIndia...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1990</th>\n",
       "      <td>LebanonIndiaIndiaIndiaBoliviaNicaraguaIsraelBo...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1991</th>\n",
       "      <td>JordanPhilippinesGuatemalaPhilippinesColombiaC...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1992</th>\n",
       "      <td>SpainZaireIsraelEl SalvadorUnited KingdomUnite...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1994</th>\n",
       "      <td>United StatesMexicoMexicoMexicoMexicoMexicoMex...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995</th>\n",
       "      <td>United StatesUnited StatesUnited StatesTajikis...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1996</th>\n",
       "      <td>FranceFrancePakistanPakistanPakistanPakistanPa...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1997</th>\n",
       "      <td>NepalWest Bank and Gaza StripUnited StatesUnit...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1998</th>\n",
       "      <td>BurundiRussiaUnited KingdomIraqWest Bank and G...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999</th>\n",
       "      <td>ColombiaAngolaSouth AfricaPhilippinesAlgeriaGr...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000</th>\n",
       "      <td>NamibiaNamibiaIndiaKosovoSomaliaBangladeshIndi...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2001</th>\n",
       "      <td>ColombiaYemenColombiaTurkeyAlgeriaYemenYugosla...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002</th>\n",
       "      <td>PakistanIndiaIndiaIndonesiaIndonesiaAlgeriaPhi...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>RussiaColombiaColombiaColombiaColombiaColombia...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004</th>\n",
       "      <td>IraqIndiaIsraelColombiaIndiaIndiaIndiaPhilippi...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005</th>\n",
       "      <td>IraqPeruColombiaBosnia-HerzegovinaIndiaNepalUn...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>AfghanistanIsraelIraqIraqIraqIraqIraqSri Lanka...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>West Bank and Gaza StripThailandSri LankaAfgha...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>PhilippinesKenyaIndiaSudanNigeriaSri LankaIraq...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>SomaliaIraqIraqIraqWest Bank and Gaza StripInd...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>AfghanistanPakistanPakistanPakistanPakistanPak...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <td>EgyptIraqIraqNigeriaIraqIraqIraqIraqIraqRussia...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <td>PakistanKenyaPakistanKenyaPakistanPakistanIraq...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>PakistanIraqIraqIraqPakistanPakistanPakistanPa...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>ColombiaSomaliaPakistanPakistanSomaliaIraqIraq...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>IraqBosnia-HerzegovinaIraqSwedenLibyaIraqIraqI...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>IraqIraqIraqIndiaIndiaAfghanistanTurkeyTurkeyS...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017</th>\n",
       "      <td>AfghanistanSudanDemocratic Republic of the Con...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                             country_txt\n",
       "iyear                                                   \n",
       "1970   Dominican RepublicMexicoPhilippinesGreeceJapan...\n",
       "1971   United StatesWest Germany (FRG)United StatesUn...\n",
       "1972   PanamaPhilippinesKuwaitSpainArgentinaUnited Ki...\n",
       "1973   ColombiaIrelandDominican RepublicUnited Kingdo...\n",
       "1974   ItalyFranceItalyBoliviaUnited KingdomArgentina...\n",
       "1975   PakistanSpainSpainSpainUnited KingdomNetherlan...\n",
       "1976   TurkeyTurkeyPortugalWest Germany (FRG)United S...\n",
       "1977   JapanJapanJapanFranceFranceSpainItalySpainItal...\n",
       "1978   BrazilEl SalvadorItalyItalyItalyJapanNetherlan...\n",
       "1979   JapanColombiaPhilippinesNicaraguaNicaraguaPeru...\n",
       "1980   West Bank and Gaza StripUnited KingdomUnited K...\n",
       "1981   IrelandEl SalvadorIraqPeruFranceSomaliaSomalia...\n",
       "1982   CanadaGuatemalaIranColombiaColombiaColombiaGua...\n",
       "1983   South AfricaUnited KingdomNetherlandsPeruPeruP...\n",
       "1984   PeruEl SalvadorEl SalvadorWest Bank and Gaza S...\n",
       "1985   West Germany (FRG)FranceFranceFranceFranceFran...\n",
       "1986   SwedenSri LankaFranceIsraelPeruPeruPeruPeruPer...\n",
       "1987   LebanonIndiaEl SalvadorPeruSouth AfricaIndiaLe...\n",
       "1988   ChilePeruPeruPeruPeruPeruSri LankaPhilippinesP...\n",
       "1989   ColombiaUnited StatesIndiaIndiaIndiaIndiaIndia...\n",
       "1990   LebanonIndiaIndiaIndiaBoliviaNicaraguaIsraelBo...\n",
       "1991   JordanPhilippinesGuatemalaPhilippinesColombiaC...\n",
       "1992   SpainZaireIsraelEl SalvadorUnited KingdomUnite...\n",
       "1994   United StatesMexicoMexicoMexicoMexicoMexicoMex...\n",
       "1995   United StatesUnited StatesUnited StatesTajikis...\n",
       "1996   FranceFrancePakistanPakistanPakistanPakistanPa...\n",
       "1997   NepalWest Bank and Gaza StripUnited StatesUnit...\n",
       "1998   BurundiRussiaUnited KingdomIraqWest Bank and G...\n",
       "1999   ColombiaAngolaSouth AfricaPhilippinesAlgeriaGr...\n",
       "2000   NamibiaNamibiaIndiaKosovoSomaliaBangladeshIndi...\n",
       "2001   ColombiaYemenColombiaTurkeyAlgeriaYemenYugosla...\n",
       "2002   PakistanIndiaIndiaIndonesiaIndonesiaAlgeriaPhi...\n",
       "2003   RussiaColombiaColombiaColombiaColombiaColombia...\n",
       "2004   IraqIndiaIsraelColombiaIndiaIndiaIndiaPhilippi...\n",
       "2005   IraqPeruColombiaBosnia-HerzegovinaIndiaNepalUn...\n",
       "2006   AfghanistanIsraelIraqIraqIraqIraqIraqSri Lanka...\n",
       "2007   West Bank and Gaza StripThailandSri LankaAfgha...\n",
       "2008   PhilippinesKenyaIndiaSudanNigeriaSri LankaIraq...\n",
       "2009   SomaliaIraqIraqIraqWest Bank and Gaza StripInd...\n",
       "2010   AfghanistanPakistanPakistanPakistanPakistanPak...\n",
       "2011   EgyptIraqIraqNigeriaIraqIraqIraqIraqIraqRussia...\n",
       "2012   PakistanKenyaPakistanKenyaPakistanPakistanIraq...\n",
       "2013   PakistanIraqIraqIraqPakistanPakistanPakistanPa...\n",
       "2014   ColombiaSomaliaPakistanPakistanSomaliaIraqIraq...\n",
       "2015   IraqBosnia-HerzegovinaIraqSwedenLibyaIraqIraqI...\n",
       "2016   IraqIraqIraqIndiaIndiaAfghanistanTurkeyTurkeyS...\n",
       "2017   AfghanistanSudanDemocratic Republic of the Con..."
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df3 = df.groupby('iyear')['country_txt'].sum().to_frame()\n",
    "df3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "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>iyear</th>\n",
       "      <th>1970</th>\n",
       "      <th>1971</th>\n",
       "      <th>1972</th>\n",
       "      <th>1973</th>\n",
       "      <th>1974</th>\n",
       "      <th>1975</th>\n",
       "      <th>1976</th>\n",
       "      <th>1977</th>\n",
       "      <th>1978</th>\n",
       "      <th>1979</th>\n",
       "      <th>...</th>\n",
       "      <th>2008</th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>nkill</th>\n",
       "      <td>174.0</td>\n",
       "      <td>173.0</td>\n",
       "      <td>566.0</td>\n",
       "      <td>370.0</td>\n",
       "      <td>539.0</td>\n",
       "      <td>617.0</td>\n",
       "      <td>674.0</td>\n",
       "      <td>456.0</td>\n",
       "      <td>1459.0</td>\n",
       "      <td>2100.0</td>\n",
       "      <td>...</td>\n",
       "      <td>9157.0</td>\n",
       "      <td>9273.0</td>\n",
       "      <td>7827.0</td>\n",
       "      <td>8246.0</td>\n",
       "      <td>15497.0</td>\n",
       "      <td>22273.0</td>\n",
       "      <td>44490.0</td>\n",
       "      <td>38853.0</td>\n",
       "      <td>34871.0</td>\n",
       "      <td>26445.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nwound</th>\n",
       "      <td>212.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>409.0</td>\n",
       "      <td>495.0</td>\n",
       "      <td>865.0</td>\n",
       "      <td>617.0</td>\n",
       "      <td>756.0</td>\n",
       "      <td>518.0</td>\n",
       "      <td>1600.0</td>\n",
       "      <td>2506.0</td>\n",
       "      <td>...</td>\n",
       "      <td>18998.0</td>\n",
       "      <td>19138.0</td>\n",
       "      <td>15947.0</td>\n",
       "      <td>14659.0</td>\n",
       "      <td>25445.0</td>\n",
       "      <td>37688.0</td>\n",
       "      <td>41128.0</td>\n",
       "      <td>44043.0</td>\n",
       "      <td>40001.0</td>\n",
       "      <td>24927.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 47 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "iyear    1970   1971   1972   1973   1974   1975   1976   1977    1978  \\\n",
       "nkill   174.0  173.0  566.0  370.0  539.0  617.0  674.0  456.0  1459.0   \n",
       "nwound  212.0   82.0  409.0  495.0  865.0  617.0  756.0  518.0  1600.0   \n",
       "\n",
       "iyear     1979  ...     2008     2009     2010     2011     2012     2013  \\\n",
       "nkill   2100.0  ...   9157.0   9273.0   7827.0   8246.0  15497.0  22273.0   \n",
       "nwound  2506.0  ...  18998.0  19138.0  15947.0  14659.0  25445.0  37688.0   \n",
       "\n",
       "iyear      2014     2015     2016     2017  \n",
       "nkill   44490.0  38853.0  34871.0  26445.0  \n",
       "nwound  41128.0  44043.0  40001.0  24927.0  \n",
       "\n",
       "[2 rows x 47 columns]"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "casualties_by_year = df.pivot_table(columns='iyear', values=('nkill','nwound'), aggfunc='sum')\n",
    "casualties_by_year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df3=df['iyear'].value_counts()[:15].to_frame()\n",
    "df3.columns=['Attacks']\n",
    "data=df.groupby('iyear')['nkill'].sum().to_frame()\n",
    "df3.merge(data,left_index=True,right_index=True,how='left').plot.bar(width=0.9,color=['cyan','black'])\n",
    "fig=plt.gcf()\n",
    "fig.set_size_inches(18,6)\n",
    "plt.title('Year-wise Attacks vs Killed')\n",
    "plt.xlabel('Years')\n",
    "plt.ylabel('count')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# CONCLUSION"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Most deaths due to acts of terrorism have been caused by Islamic State of Iraq in 2014 with the numbering at around 40000"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}