{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "30d6db93",
   "metadata": {
    "id": "30d6db93"
   },
   "outputs": [],
   "source": [
    "#importing the necessary libraries\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import nltk\n",
    "\n",
    "import seaborn as sns\n",
    "\n",
    "from nltk.corpus import stopwords\n",
    "\n",
    "import string\n",
    "\n",
    "from nltk.stem import PorterStemmer\n",
    "\n",
    "from wordcloud import WordCloud\n",
    "\n",
    "from collections import Counter\n",
    "\n",
    "from sklearn.feature_extraction.text import CountVectorizer, TfidfVectorizer\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "from sklearn.naive_bayes import GaussianNB, MultinomialNB, BernoulliNB\n",
    "\n",
    "from sklearn.metrics import accuracy_score, precision_score, confusion_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "1e527796",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 423
    },
    "id": "1e527796",
    "outputId": "43bc2e29-5869-41f1-b9b9-fd73891bda48"
   },
   "outputs": [
    {
     "data": {
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>v1</th>\n",
       "      <th>v2</th>\n",
       "      <th>Unnamed: 2</th>\n",
       "      <th>Unnamed: 3</th>\n",
       "      <th>Unnamed: 4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ham</td>\n",
       "      <td>Go until jurong point, crazy.. Available only ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ham</td>\n",
       "      <td>Ok lar... Joking wif u oni...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>spam</td>\n",
       "      <td>Free entry in 2 a wkly comp to win FA Cup fina...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ham</td>\n",
       "      <td>U dun say so early hor... U c already then say...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ham</td>\n",
       "      <td>Nah I don't think he goes to usf, he lives aro...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5567</th>\n",
       "      <td>spam</td>\n",
       "      <td>This is the 2nd time we have tried 2 contact u...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5568</th>\n",
       "      <td>ham</td>\n",
       "      <td>Will Ì_ b going to esplanade fr home?</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5569</th>\n",
       "      <td>ham</td>\n",
       "      <td>Pity, * was in mood for that. So...any other s...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5570</th>\n",
       "      <td>ham</td>\n",
       "      <td>The guy did some bitching but I acted like i'd...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5571</th>\n",
       "      <td>ham</td>\n",
       "      <td>Rofl. Its true to its name</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5572 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        v1                                                 v2 Unnamed: 2  \\\n",
       "0      ham  Go until jurong point, crazy.. Available only ...        NaN   \n",
       "1      ham                      Ok lar... Joking wif u oni...        NaN   \n",
       "2     spam  Free entry in 2 a wkly comp to win FA Cup fina...        NaN   \n",
       "3      ham  U dun say so early hor... U c already then say...        NaN   \n",
       "4      ham  Nah I don't think he goes to usf, he lives aro...        NaN   \n",
       "...    ...                                                ...        ...   \n",
       "5567  spam  This is the 2nd time we have tried 2 contact u...        NaN   \n",
       "5568   ham              Will Ì_ b going to esplanade fr home?        NaN   \n",
       "5569   ham  Pity, * was in mood for that. So...any other s...        NaN   \n",
       "5570   ham  The guy did some bitching but I acted like i'd...        NaN   \n",
       "5571   ham                         Rofl. Its true to its name        NaN   \n",
       "\n",
       "     Unnamed: 3 Unnamed: 4  \n",
       "0           NaN        NaN  \n",
       "1           NaN        NaN  \n",
       "2           NaN        NaN  \n",
       "3           NaN        NaN  \n",
       "4           NaN        NaN  \n",
       "...         ...        ...  \n",
       "5567        NaN        NaN  \n",
       "5568        NaN        NaN  \n",
       "5569        NaN        NaN  \n",
       "5570        NaN        NaN  \n",
       "5571        NaN        NaN  \n",
       "\n",
       "[5572 rows x 5 columns]"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#reading the CSV file\n",
    "x = pd.read_csv(\"sms-spam.csv\")\n",
    "\n",
    "#displaying the dataframe\n",
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "78693fdd",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "78693fdd",
    "outputId": "3ab31c99-767b-464a-eb10-c25ae42d9eec"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5572, 5)"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#dataset size - 5572 rows x 5 columns\n",
    "x.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6719610c",
   "metadata": {
    "id": "6719610c"
   },
   "source": [
    "## Data Cleaning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "226dc4bb",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "226dc4bb",
    "outputId": "179f2bef-bb32-4bb0-8d7c-e4e63402679e"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 5572 entries, 0 to 5571\n",
      "Data columns (total 5 columns):\n",
      " #   Column      Non-Null Count  Dtype \n",
      "---  ------      --------------  ----- \n",
      " 0   v1          5572 non-null   object\n",
      " 1   v2          5572 non-null   object\n",
      " 2   Unnamed: 2  50 non-null     object\n",
      " 3   Unnamed: 3  12 non-null     object\n",
      " 4   Unnamed: 4  6 non-null      object\n",
      "dtypes: object(5)\n",
      "memory usage: 217.8+ KB\n"
     ]
    }
   ],
   "source": [
    "#printing the concise summary of the dataset\n",
    "x.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "1205abf7",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 423
    },
    "id": "1205abf7",
    "outputId": "e1e68c4e-9cad-4d88-fe66-1bf8225706b9"
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>v1</th>\n",
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       "      <td>Ok lar... Joking wif u oni...</td>\n",
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       "      <th>2</th>\n",
       "      <td>spam</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ham</td>\n",
       "      <td>U dun say so early hor... U c already then say...</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ham</td>\n",
       "      <td>Nah I don't think he goes to usf, he lives aro...</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <th>5567</th>\n",
       "      <td>spam</td>\n",
       "      <td>This is the 2nd time we have tried 2 contact u...</td>\n",
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       "    <tr>\n",
       "      <th>5568</th>\n",
       "      <td>ham</td>\n",
       "      <td>Will Ì_ b going to esplanade fr home?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5569</th>\n",
       "      <td>ham</td>\n",
       "      <td>Pity, * was in mood for that. So...any other s...</td>\n",
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       "    <tr>\n",
       "      <th>5570</th>\n",
       "      <td>ham</td>\n",
       "      <td>The guy did some bitching but I acted like i'd...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5571</th>\n",
       "      <td>ham</td>\n",
       "      <td>Rofl. Its true to its name</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5572 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        v1                                                 v2\n",
       "0      ham  Go until jurong point, crazy.. Available only ...\n",
       "1      ham                      Ok lar... Joking wif u oni...\n",
       "2     spam  Free entry in 2 a wkly comp to win FA Cup fina...\n",
       "3      ham  U dun say so early hor... U c already then say...\n",
       "4      ham  Nah I don't think he goes to usf, he lives aro...\n",
       "...    ...                                                ...\n",
       "5567  spam  This is the 2nd time we have tried 2 contact u...\n",
       "5568   ham              Will Ì_ b going to esplanade fr home?\n",
       "5569   ham  Pity, * was in mood for that. So...any other s...\n",
       "5570   ham  The guy did some bitching but I acted like i'd...\n",
       "5571   ham                         Rofl. Its true to its name\n",
       "\n",
       "[5572 rows x 2 columns]"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#column 2, 3, 4 have majority missing values, so it is better to drop them.\n",
    "x.drop(columns=['Unnamed: 2', 'Unnamed: 3', 'Unnamed: 4'], inplace = True)\n",
    "\n",
    "#displaying the edited dataframe\n",
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "7a5f0034",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 423
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    "id": "7a5f0034",
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   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>result</th>\n",
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       "      <th>...</th>\n",
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       "      <th>5568</th>\n",
       "      <td>ham</td>\n",
       "      <td>Will Ì_ b going to esplanade fr home?</td>\n",
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       "    <tr>\n",
       "      <th>5569</th>\n",
       "      <td>ham</td>\n",
       "      <td>Pity, * was in mood for that. So...any other s...</td>\n",
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       "    <tr>\n",
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       "      <td>ham</td>\n",
       "      <td>The guy did some bitching but I acted like i'd...</td>\n",
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       "    <tr>\n",
       "      <th>5571</th>\n",
       "      <td>ham</td>\n",
       "      <td>Rofl. Its true to its name</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5572 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     result                                              input\n",
       "0       ham  Go until jurong point, crazy.. Available only ...\n",
       "1       ham                      Ok lar... Joking wif u oni...\n",
       "2      spam  Free entry in 2 a wkly comp to win FA Cup fina...\n",
       "3       ham  U dun say so early hor... U c already then say...\n",
       "4       ham  Nah I don't think he goes to usf, he lives aro...\n",
       "...     ...                                                ...\n",
       "5567   spam  This is the 2nd time we have tried 2 contact u...\n",
       "5568    ham              Will Ì_ b going to esplanade fr home?\n",
       "5569    ham  Pity, * was in mood for that. So...any other s...\n",
       "5570    ham  The guy did some bitching but I acted like i'd...\n",
       "5571    ham                         Rofl. Its true to its name\n",
       "\n",
       "[5572 rows x 2 columns]"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#renaming the column names to a better and meaningful column name\n",
    "x.rename(columns = {'v1':'result', 'v2':'input'}, inplace=True)\n",
    "\n",
    "#displaying the edited dataframe\n",
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "3cd46be7",
   "metadata": {
    "id": "3cd46be7"
   },
   "outputs": [],
   "source": [
    "#result has categorical labels, we need to convert it into numerical values - enbcoding\n",
    "#for that we will be using 'LabelEncoder' from sklearn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "6a001e3b",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 206
    },
    "id": "6a001e3b",
    "outputId": "e0e9b7d4-ffd8-4001-b490-c2a3a85c7562"
   },
   "outputs": [
    {
     "data": {
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      ],
      "text/plain": [
       "   result                                              input\n",
       "0       0  Go until jurong point, crazy.. Available only ...\n",
       "1       0                      Ok lar... Joking wif u oni...\n",
       "2       1  Free entry in 2 a wkly comp to win FA Cup fina...\n",
       "3       0  U dun say so early hor... U c already then say...\n",
       "4       0  Nah I don't think he goes to usf, he lives aro..."
      ]
     },
     "execution_count": 75,
     "metadata": {},
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   ],
   "source": [
    "encoder = LabelEncoder()\n",
    "x['result'] = encoder.fit_transform(x['result'])\n",
    "\n",
    "#displaying the edited dataframe\n",
    "x.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "215b7f36",
   "metadata": {
    "id": "215b7f36"
   },
   "outputs": [],
   "source": [
    "#so 0 means no SPAM, 1 means SPAM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "fa8ba1ab",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "fa8ba1ab",
    "outputId": "868c5eb2-cfb7-48ab-c7d3-58117b0d5c05"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "result    0\n",
       "input     0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#check if there is any NULL value\n",
    "x.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "c95877ee",
   "metadata": {
    "id": "c95877ee"
   },
   "outputs": [],
   "source": [
    "#the dataset has NO null values, so don't need to handle them"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "7aad25e1",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "7aad25e1",
    "outputId": "9f648247-0a9e-43dc-82d9-50ab76814b40"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "403"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#check if there is any DUPLICATE values\n",
    "x.duplicated().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "c1a5defd",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 423
    },
    "id": "c1a5defd",
    "outputId": "65d3ba84-d195-4ef9-b5d5-f738d51d41b1"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>result</th>\n",
       "      <th>input</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>Go until jurong point, crazy.. Available only ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>Ok lar... Joking wif u oni...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>Free entry in 2 a wkly comp to win FA Cup fina...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>U dun say so early hor... U c already then say...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>Nah I don't think he goes to usf, he lives aro...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5567</th>\n",
       "      <td>1</td>\n",
       "      <td>This is the 2nd time we have tried 2 contact u...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5568</th>\n",
       "      <td>0</td>\n",
       "      <td>Will Ì_ b going to esplanade fr home?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5569</th>\n",
       "      <td>0</td>\n",
       "      <td>Pity, * was in mood for that. So...any other s...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5570</th>\n",
       "      <td>0</td>\n",
       "      <td>The guy did some bitching but I acted like i'd...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5571</th>\n",
       "      <td>0</td>\n",
       "      <td>Rofl. Its true to its name</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5169 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      result                                              input\n",
       "0          0  Go until jurong point, crazy.. Available only ...\n",
       "1          0                      Ok lar... Joking wif u oni...\n",
       "2          1  Free entry in 2 a wkly comp to win FA Cup fina...\n",
       "3          0  U dun say so early hor... U c already then say...\n",
       "4          0  Nah I don't think he goes to usf, he lives aro...\n",
       "...      ...                                                ...\n",
       "5567       1  This is the 2nd time we have tried 2 contact u...\n",
       "5568       0              Will Ì_ b going to esplanade fr home?\n",
       "5569       0  Pity, * was in mood for that. So...any other s...\n",
       "5570       0  The guy did some bitching but I acted like i'd...\n",
       "5571       0                         Rofl. Its true to its name\n",
       "\n",
       "[5169 rows x 2 columns]"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#the dataset has DUPLICATE values, so we will have to REMOVE them\n",
    "x = x.drop_duplicates(keep='first')\n",
    "\n",
    "#displaying the edited dataframe\n",
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "1a120833",
   "metadata": {
    "id": "1a120833"
   },
   "outputs": [],
   "source": [
    "#rows reduced from 5572 to 5169 after DUPLICATED values have been deleted"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6d9d382c",
   "metadata": {
    "id": "6d9d382c"
   },
   "source": [
    "## EDA - Exploratory Data Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "bf35d200",
   "metadata": {
    "id": "bf35d200"
   },
   "outputs": [],
   "source": [
    "#the given problem is a classification problem, so we need to understand the data first by performing EDA.\n",
    "#the dataset has only 2 columns, so less analysis required."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "f1758d20",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "f1758d20",
    "outputId": "274a9092-b9bc-4a6f-c7f5-cec747a5c889"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    4516\n",
       "1     653\n",
       "Name: result, dtype: int64"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#checking the number of SPAM vs not SPAM messages\n",
    "x['result'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "8f0e68d4",
   "metadata": {
    "id": "8f0e68d4"
   },
   "outputs": [],
   "source": [
    "#out of 5169 datavalues, 653 are SPAM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "06cd5547",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "06cd5547",
    "outputId": "aab9df1b-d0e1-44ac-bc7a-2bab464dd905"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "12.633004449603405"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "653*100.0/5169"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "fde6542b",
   "metadata": {
    "id": "fde6542b"
   },
   "outputs": [],
   "source": [
    "#12.63% is SPAM and 87.37% is not SPAM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "ea0827b7",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 406
    },
    "id": "ea0827b7",
    "outputId": "9e82e8c7-89e8-4326-8e91-b17ae9e61137"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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wj3Tg74gaulvZbuC43vXA1aZz2EXrmdU/m71XZMno9l6d+Ng6ZsXTrFin2aaHYsq4Gm6cnSSZhq1rN35Y9tvxtXy6OsN5Mxv5v9P9T8sbPktz3sz1NKVhyFb+oa+tahUnPrqOhSsyRBTs0CfCb6Pd2L5X3sVOAQOoTwTzOkZZYS71wcArpnPYR2uv+uo5e0Q+GmU6SR7+Tn3iUNMhChXK3e+s1wjwpP3ypdT4pusPWZgZNMd0kjzMNB2gGEJb6uzx6sC/fypHmkjke02xgxZnBgZtT8iKn4fQljrrAdMBbJUhUnFE0y8P/DCz7aums+ToLeoTS0yHKIZQlzoei74KvGM6h60yRCq+23Tz/v/ODHjNdJYcTDcdoFhCXeqs35sOYLM0FZWHNv1q30/01nNNZ9mCJHC/6RDFIqWGB5HrlnWpFJVV45JTRyzTfct1Jt/j1CdWbmkBpdQ1Sql3lFJvKqUalFIHKqVmKaUWKqXmK6XmKKWGtlj+KaXUq622Ua+U0kqpnVs8d3n2uf2K9c2EvtTxWHQl8LjpHLZrprJ6bHLqXp/rPuV4ssRvtvSiUupgYDywj9Z6L+Bw4OPsy6drrb+Nv/t+c3b5PsA+QB+l1I6tNvcWcGqLr08C3i30G2gp9KXOusN0gDBooqpmTPK24ct173I6YWIu9YmOPqXfDlihtU4CaK1XaK1bzw9/CdgwAp8IPA08wqYFBngSOA5AKTUE/zTgot7iR0oNxGPROcDfTecIgyTV3UYnb9t9pe75L9NZsqblsMxzwGCl1CKl1J1KqfYuEHEM/igMMBH4Y/YxsdVyq4CPlVLDs6/NyC/25kmpN5piOkBYNFJTOyp5+9CvdN18w1EWA492tJDWeg2wL3A+/qg6Qyl1dvblh5RSDcBI4CdKqW3wR+zZWutFQCpb4JY2jOATgCcK/zY2JaXOiseiLwKzTOcIi/XUdB+VnLbT17rHmwZjXE19IqfTurTWaa31LK31fwOX4O9ig/+eeoTWeoLW+mPgFGArYIlSKg44tN0Ffxo4E/i31npVEb6PTUipNyWjdQmtpbZuZPL2HVfp7m91vHTRzaU+8adcFlRKDVVK7dLiqRFs/vrxE4GjtNaO1trBH+E3KbXWej1wJXB9Z0PnQkrdQjwWnYWM1iW1ltqehyRv32G1ri31JKArO7FsHTBdKfWuUupNYHegvvVCSikH+Bb+eQUAaK2XAKuUUge2XFZr/YjWel4euTsU2rO0Nsdxvb2AeUCF6Sxh0os1iVdrfvxpD9W4Wwn+uD9Tnzi6BH+OETJStxKPRd8Efm06R9isoq73Icnbt1una97r4j8qQ+dG6cCRUrfv5wT4titBlaCuz8jktAHrdXVX3nDhbuoTJt7Dl4yUuh3xWHQ1cIXpHGH0Fb36jkpO69uoqxZ3weY/BCZ3wXbLipR6M+Kx6Azgr6ZzhNFKevcblZzWO6mrPijiZjVwDvWJtUXcZlmSUm/ZucDXpkOE0Qr69B+TnNozqSuLdY7zNOoTnb4wYhBJqbcgHot+DEwynSOsPqfvgHHJqbVNuqLQe4ovJEQXmZRSdyAeiz4K3Gs6R1gtY+ttv5O8tbpZV+R7a9k08APqE+uLmaucSalzcwkbJ+uLEvuE/tsd2nRLRbOuWJrH6j+hPvF60UOVMZl8kiPH9YYCc4FeprOElaOWffy36smRSpXZPsdV7qE+cX6XhipDMlLnKB6LLsSfxN9sOktYxfV2g49o+mUqrSO5XNp5FnBxF0cqS1LqTojHon8Dfmg6R5h9qAfucFRTLJnW6vMtLPYBcBL1iVD+ApZSd1I8Fp1OO5P5Rem8rwc5RzfduC6t1RftvJwAjunommM2k1LnIR6LTgHuM50jzBbqb+14TNP1qzNatbwU0HrgBOoTC0zlKgdS6vydTw5XzRBd513t7HRc03VfZ7RaiX9F2AnUJ14wncs0KXWe4rFoCjgNucuHUW/pIbuc2FS/LK3VBOoTz5nOUw7kkFaBHNdTwF3IzDNT1gET4rGozNPPklIXieN6twGXms4RMgngmHgs+rLpIOVEdr+LJB6LXoY/vzhjOEpYLAYOlkK3JSN1kTmuNx54CJl51pWeB06Ox6Jfmg5SjmSkLrJ4LPoMcCDQlVfvCLM7gKOk0JsnI3UXcVyvN/AwYO0F7kpsPXBZPBb9nekg5U5G6i4Sj0X9mU3+5XOaDMcJujeAfaTQuZGRugSylx1+ENjLdJaASQM3ANfFY9FQzuPOh5S6RBzXq8L/dPwaoMpwnCB4HzgzHouG6lzoYpBSl5jjesOB24DDDEcpV2uAG4Fb47Foo+kwQSSlNiR76OtmYJjpLGVCA/cDV8dj0c8MZwk0KbVBjutV4p8YUg/0N5vGqJfxP9nukntLhY2Uugw4rtcL/yodPwK2MxynlF4EfpG9+IQoEil1GXFcrxr/zK//BFrfqNwWGeBJ4JZ4LPqK4SxWklKXKcf1jsQ/QeQI7LgD56f402d/G49FPzQdxmZS6jLnuN4A4BT8Efwgw3E6aw3wOP4x+hfisaic7FICUuoAcVxvR/xyHw/sTXnOCFyOf8LFM8AT8Vh0neE8oSOlDijH9foBhwPfAcZg7tBYI/6n13/NPubHY1H5oTJISm0Jx/X644/ee7R47E5xTwH9BP9OJW9mH28BC2QKZ3mRUlvOcb1BwED84+AbHv2yjwr8SR+Z7H81/nzrr4GVwAr8D7iWAkuzJ6mIMielFsIy5fhBixCiAFJqISwjpRbCMlJqISwjpRbCMlJqISwjpRbCMlJqISwjpRbCMlJqISwjpRbCMlJqISwjpRbCMlJqISwjpRbCMlJqISwjpRbCMlJqISwjpRbCMlJqISwjpRbCMlJqISwjpRbCMlJqISwjpRbCMlJqISwjpRbCMlJqISwjpRbCMlJqISwjpRbCMlJqISwjpRbCMlJqISwjpRbCMlJqISwjpRbCMlJqISwjpRbCMlJqISwjpRbCMlJqISwjpRbCMlJqISwjpRbCMv8P5STHgoaT1o0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#for better representation, we can use PIE CHART to represent it.\n",
    "#PIE CHARTS can be created using matplotlib library\n",
    "\n",
    "plt.pie(x['result'].value_counts(),  labels = ['NOT SPAM', 'SPAM'], autopct = '%0.2f', radius = 0.8)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "d07846e7",
   "metadata": {
    "id": "d07846e7"
   },
   "outputs": [],
   "source": [
    "#hence, highly IMBALANCED DATA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "d774e6d0",
   "metadata": {
    "id": "d774e6d0"
   },
   "outputs": [],
   "source": [
    "#now we will be analysing the number of alphabets/words/sentences being used in the TEXT\n",
    "#for this, will create 3 new columns: (1) no. of characters (2) no. of words (3) no. of sentences in SMS\n",
    "\n",
    "#using 'nltk' library for this. \n",
    "#Natural Language Toolkit for text processing \n",
    "#(pip install nltk)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "ffd4ce2b",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "ffd4ce2b",
    "outputId": "d4453103-26a3-4f32-bd9c-2b001fc36f2d"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[nltk_data] Error loading punkt: <urlopen error [WinError 10061] No\n",
      "[nltk_data]     connection could be made because the target machine\n",
      "[nltk_data]     actively refused it>\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#downloading the dependencies \n",
    "#punkt package includes pre-trained models for tokenizing text in many languages\n",
    "\n",
    "nltk.download('punkt')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "e0b0ae5a",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "e0b0ae5a",
    "outputId": "96c083c2-d244-4a39-df41-e0b92819682f"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\codes\\AppData\\Local\\Temp\\ipykernel_37516\\3785843795.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  x['countCharacters'] = x['input'].apply(len)\n",
      "C:\\Users\\codes\\AppData\\Local\\Temp\\ipykernel_37516\\3785843795.py:5: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  x['countWords'] = x['input'].apply(lambda i:len(nltk.word_tokenize(i)))\n",
      "C:\\Users\\codes\\AppData\\Local\\Temp\\ipykernel_37516\\3785843795.py:9: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  x['countSentences'] = x['input'].apply(lambda i:len(nltk.sent_tokenize(i)))\n"
     ]
    }
   ],
   "source": [
    "#creating a new column with count of characters\n",
    "x['countCharacters'] = x['input'].apply(len)\n",
    "\n",
    "#creating a new column with count of words\n",
    "x['countWords'] = x['input'].apply(lambda i:len(nltk.word_tokenize(i)))\n",
    "#'word_tokenize' function takes a string of text as input and returns a list of words\n",
    "\n",
    "#creating a new column with count of sentences\n",
    "x['countSentences'] = x['input'].apply(lambda i:len(nltk.sent_tokenize(i)))\n",
    "#'sent_tokenize' function takes a string of text as input and returns a list of sentences"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "b2deabf7",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 206
    },
    "id": "b2deabf7",
    "outputId": "604524c7-35e5-470f-d30f-0ac90811361a",
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>result</th>\n",
       "      <th>input</th>\n",
       "      <th>countCharacters</th>\n",
       "      <th>countWords</th>\n",
       "      <th>countSentences</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>Go until jurong point, crazy.. Available only ...</td>\n",
       "      <td>111</td>\n",
       "      <td>24</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>Ok lar... Joking wif u oni...</td>\n",
       "      <td>29</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>Free entry in 2 a wkly comp to win FA Cup fina...</td>\n",
       "      <td>155</td>\n",
       "      <td>37</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>U dun say so early hor... U c already then say...</td>\n",
       "      <td>49</td>\n",
       "      <td>13</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>Nah I don't think he goes to usf, he lives aro...</td>\n",
       "      <td>61</td>\n",
       "      <td>15</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   result                                              input  countCharacters  \\\n",
       "0       0  Go until jurong point, crazy.. Available only ...              111   \n",
       "1       0                      Ok lar... Joking wif u oni...               29   \n",
       "2       1  Free entry in 2 a wkly comp to win FA Cup fina...              155   \n",
       "3       0  U dun say so early hor... U c already then say...               49   \n",
       "4       0  Nah I don't think he goes to usf, he lives aro...               61   \n",
       "\n",
       "   countWords  countSentences  \n",
       "0          24               2  \n",
       "1           8               2  \n",
       "2          37               2  \n",
       "3          13               1  \n",
       "4          15               1  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#displaying the edited dataframe with the 3 new columns added\n",
    "x.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "e9a255a1",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 300
    },
    "id": "e9a255a1",
    "outputId": "4485798e-cde1-4583-a3c5-99dc370fd1d6"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>countCharacters</th>\n",
       "      <th>countWords</th>\n",
       "      <th>countSentences</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>5169.000000</td>\n",
       "      <td>5169.000000</td>\n",
       "      <td>5169.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>78.977945</td>\n",
       "      <td>18.453279</td>\n",
       "      <td>1.947185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>58.236293</td>\n",
       "      <td>13.324793</td>\n",
       "      <td>1.362406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>36.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>60.000000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>117.000000</td>\n",
       "      <td>26.000000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>910.000000</td>\n",
       "      <td>220.000000</td>\n",
       "      <td>28.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       countCharacters   countWords  countSentences\n",
       "count      5169.000000  5169.000000     5169.000000\n",
       "mean         78.977945    18.453279        1.947185\n",
       "std          58.236293    13.324793        1.362406\n",
       "min           2.000000     1.000000        1.000000\n",
       "25%          36.000000     9.000000        1.000000\n",
       "50%          60.000000    15.000000        1.000000\n",
       "75%         117.000000    26.000000        2.000000\n",
       "max         910.000000   220.000000       28.000000"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#extracting the 5 number summary of the 3 new column values\n",
    "x[['countCharacters', 'countWords', 'countSentences']].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "8bd14494",
   "metadata": {
    "id": "8bd14494"
   },
   "outputs": [],
   "source": [
    "#extracting the same summaries, classified on the basis of SPAM and not SPAM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "8a1db23a",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 300
    },
    "id": "8a1db23a",
    "outputId": "bf0e2cd6-c3da-46e4-c71b-1cd876ce81af"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>countCharacters</th>\n",
       "      <th>countWords</th>\n",
       "      <th>countSentences</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>4516.000000</td>\n",
       "      <td>4516.000000</td>\n",
       "      <td>4516.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>70.459256</td>\n",
       "      <td>17.120903</td>\n",
       "      <td>1.799601</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>56.358207</td>\n",
       "      <td>13.493725</td>\n",
       "      <td>1.278465</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>34.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>52.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>90.000000</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>910.000000</td>\n",
       "      <td>220.000000</td>\n",
       "      <td>28.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       countCharacters   countWords  countSentences\n",
       "count      4516.000000  4516.000000     4516.000000\n",
       "mean         70.459256    17.120903        1.799601\n",
       "std          56.358207    13.493725        1.278465\n",
       "min           2.000000     1.000000        1.000000\n",
       "25%          34.000000     8.000000        1.000000\n",
       "50%          52.000000    13.000000        1.000000\n",
       "75%          90.000000    22.000000        2.000000\n",
       "max         910.000000   220.000000       28.000000"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#for not SPAM\n",
    "x[x['result'] == 0][['countCharacters', 'countWords', 'countSentences']].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "415a82ca",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 300
    },
    "id": "415a82ca",
    "outputId": "89c51256-c060-467a-c8ee-4d2cd2829d83",
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "        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>countCharacters</th>\n",
       "      <th>countWords</th>\n",
       "      <th>countSentences</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>653.000000</td>\n",
       "      <td>653.000000</td>\n",
       "      <td>653.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>137.891271</td>\n",
       "      <td>27.667688</td>\n",
       "      <td>2.967841</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>30.137753</td>\n",
       "      <td>7.008418</td>\n",
       "      <td>1.483201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>13.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>132.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>149.000000</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>157.000000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>4.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>224.000000</td>\n",
       "      <td>46.000000</td>\n",
       "      <td>8.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       countCharacters  countWords  countSentences\n",
       "count       653.000000  653.000000      653.000000\n",
       "mean        137.891271   27.667688        2.967841\n",
       "std          30.137753    7.008418        1.483201\n",
       "min          13.000000    2.000000        1.000000\n",
       "25%         132.000000   25.000000        2.000000\n",
       "50%         149.000000   29.000000        3.000000\n",
       "75%         157.000000   32.000000        4.000000\n",
       "max         224.000000   46.000000        8.000000"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#for SPAM\n",
    "x[x['result'] == 1][['countCharacters', 'countWords', 'countSentences']].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "cbff4800",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 437
    },
    "id": "cbff4800",
    "outputId": "684e5cbe-0452-4b9a-e677-e64535e204a6"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='countCharacters', ylabel='Count'>"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#for better visualization, we will plot a histogram using 'seaborn'\n",
    "plt.figure(figsize = (15, 5))\n",
    "sns.histplot(x[x['result'] == 0]['countCharacters'], color = \"yellow\")\n",
    "sns.histplot(x[x['result'] == 1]['countCharacters'], color = \"black\")\n",
    "\n",
    "#black -> SPAM, yellow -> not SPAM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "d4ac0dad",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 437
    },
    "id": "d4ac0dad",
    "outputId": "02ca722c-b74c-4a2a-8fe9-4c9d3dd7d131"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='countWords', ylabel='Count'>"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (15, 5))\n",
    "sns.histplot(x[x['result'] == 0]['countWords'], color = \"yellow\")\n",
    "sns.histplot(x[x['result'] == 1]['countWords'], color = \"black\")\n",
    "\n",
    "#black -> SPAM, yellow -> not SPAM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "158938fd",
   "metadata": {
    "id": "158938fd"
   },
   "outputs": [],
   "source": [
    "#observation : SPAM messages have more no of characters used, mean is 137.89 for SPAM and 70.45 for not SPAM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "2b4bb03f",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 775
    },
    "id": "2b4bb03f",
    "outputId": "16b52004-4892-493a-af41-2d80d5c2ff0c"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x22e85fb2f70>"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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wwDlEVplULcSINS5zYLJxysQsslxHf5m9GFlKMhzsXURmTnEq2UNQokEMrUSX3UeVUqm7byil0pRSX0nguK8B/1FKrQZmAT8H7gBOV0ptAU6P30ZrvQ54hFjS9CLw1WSsMIPdk6oHrjLr6pFiVUKMRFPyPNzx6ek440Phc4pTueXsydgtMnFZ7N+kXDe/u2QWnvgE4yl5Hn524bRDnuMlRq5Ep5h/UWvdO0SmtW5TSn0R+NP+DtJarwTmDXLXoJOxtda3A7cnGNMhG2xStd1ipK5dKp8KMRLZLSYunV/MseUZeIMR8lPtMj9CJMRiMnLBrALmFKfRHQiTl2IjdRgMs4qjL9GEyKCUUlrr3YUZjcCIvWIGXXZvlmX3Qox0xRlSU0UcGqltJBJNiF4CHlFK/YXYyq8vERvWGpFCEY3ZOHAvs04ZMhNCCCHGpEQTopuJrTj7MrGVZi8Df0tWUMk22KRqp9UkG94JIYQQY1SilaqjwJ/jPyNeKDJwDpHTIsvuhRBCiLEq0UrVFcAvgClAb6UqrXVZkuJKqlBEY9xrlZnTapIhMyGEEGKMSnTZ/X3EeofCwMnAP4F/JSuoZNvXXmb+YISI7EAthBBCjDmJJkR2rfVrgNJaV2utbwNOSV5YyTXYkJlBKRwWmUckhBBCjEWJTqruUUoZgC1KqRuBXcCI3fkuNEhhRoiVNu/wh0hzjtiKAkIIIYQ4BIn2EH2D2CavNwFzgSvZs/3GiBOK6AE9RAAumUckhBBCjEkH7CGKF2G8WGv9XaAbuDbpUSVZeJA5RBBbadYhQ2ZCCCHEmHPAhEhrHVFKze1bqXqkC0f1oENmTqtJEiIhkkBrzaqadp5bXUd3IML5M/OZU5yK1Sx7jY0GDZ09vL+1mdc3NTK7KI2TJ2VRmuka6rCEOCiJziH6BHhaKfUo4N3dqLV+IilRJdlgk6ohVq263ScJkRBH2uqaDi7+y4cEI1EAHly6g39edwwnTBixUxFFXCAc4Q+vb+FfH+4A4L+r6nhsuYd/XHsM2R7bAY4WYvhIdA5ROtBCbGXZefGfc5MVVDJpreN1iAafQ9TmlQ1ehTjSXtvY0JsM7faXt7YTDEeGKCJxpOxo8fGfj3b0a1tf18nmhu4hikiIQ5NopeoRP29ot3A0lgwZ1MCEyG0z09wdGIKohBjZWroDbKzvorMnRFmmk3SnGZfVgt0SGxILhQeOtgfDUUbHIPzoVtvuZ1N9F5FolAk57gEb6Ea0ZrDybZFodGCjEMNYopWqbcDngan0r1R9XZLiSppQJIp5kOEyAI/dTFWzd9D7hBCDa+js4ZYnVvPGxiYArCYDPzh7Mm9tbuLrp1UwozCVUydn89e3t/X74PziCWUyh2iY297UzRf/+THbmmLvi5kuC/+6bgGT8z29jylJd3LujDyeXV3X21aYZmdCjvuoxyvE4Uh0yOxfQC5wJvAWUAh0JSuoZAqFB59QDeCxmaSHSIiDtHZXR28yBBAIR3lg6Q5sZiNX3buUHS1eZhWl8vANi7jhhFJOn5LN7y+bTX27nzte2MDHVa2EI9KbMBy9sampNxkCaO4O8sDSavqurwlHokzLT+Hzx5UyqyiVz84t5MoFJbR6A/z7w2pufWI1z62uk/dWMewlOql6vNb6s0qpC7TW9yulHgBeSmZgyRLcTw+R22amVeYQCXFQBvugq2z2csKELNp9IbY3eVFKsW5XB1sbvSwqz2B1TTv3vFMJwN1vb+eh6xcyvzTjaIcuDmBDXeeAtpU7OwiGo729ezvbfNzx4kbSnRam5Hn4qLIVs9HAdx7bxYa62PfmB5fu5EsnlvHtMyZiNib6PfzghCJRVuxo48kVu4hqzUVzCpldnIbFlJznE6NPolfK7qVX7UqpaUAKMC4pESXZvqpUA6TYzbT5JCES4mCUDbK8+viKTD6uasNmNpDptnDLE6u57b/reW1jIz97bgOrazo4c2oOAFEN//ygf6+DGB5Onpg1oO3C2QX9hjptZiMWo4FWb5B3tzazo9VHtsfamwzt9rd3KtnR6ktarJ/saOOyuz/koWU7eeTjGi6950NW7GhL2vOJ0SfRhOhupVQa8P+AZ4D1wC+TFlUS7WvJPYDbZqLNF5I3ZiEOwrQCD/970Qzc1liH84LSdGYWpVKR4+KmUypYU9PJe1tb+h3zUWUrk/P2zEPp7gnLBOthaEFpBjedMh6L0YBBwWXzizltcjbvbG7iB0+u4a5XN+MPRfjemRP7Hbf7WugronVSN89+5OOafnPUtI6VdxAiUYmuMvtb/Ne3gLLkhZN8+0uIzEYDNpOBTn+YFIf5KEcmxMhkt5i45Jgiji3PoNMfwh+KUNPmY3N9F798aRNfP7XigOe46tgSDIOUwhBDK9Nt5aZTK/jUnAK0hoI0O69taOQr/1nR+5i/vVPJg9cv4J/XzWdTQydFaQ7KMp1kua00de0ZTj1vZj7F6Y6kxTrYPLRwRLJskbhEV5lZgYuIDZP1HqO1/klywkqe4H4mVQOkOS00dQckIRLiIBX1+bCzW4x84+FVQGw+0YzCFFbXdFCa6eSsablkuCykOSwsKsvguuNKWSDzh4Ytk9HQW3W6wx/kN69s7nd/VyDM6poOLl9QwgkT9gyx/fO6+fznw2qW72jjvBn5nDczH9thrCrc2eqj1Rsky20lP9U+4P5LjiniqZW1/dquWFB8yM8nxp5EJ1U/DXQAy4ERvVRgfz1EAGkOM42dPYzPlrLzYuyqbffTE4qQm2LDYUn0bWKPvt/Mn1lVy5dPLOfs6Xl094S4551KAuEoFdku7rp0FlPyU45k6CKJItFYZep5JWksLM/AH4zw3Oo6goP0xEzO8/CTC6bRE44c0jW0m9aa1zc28q1HVtHhD5HpsnDXpbNZPD6z3+PmlqTxwBcX8O8PqokCVy4oYW5J2iE/rxh7Er1KC7XWS5IayVGyv0nVAKkOCw1dPUcxIiGGj0AowkvrG/jR02tp84U4ZVIWPzhnCuVZB/cFYVymk0Xl6XywrRWAP7+1jZ+cP5U7XtjY+5gtjd384oWN/OVzc3EexgemOHrSnRZ+fN5UHli6gz++sRWXxcRVi0qYV5I66OMNBnVYyRDEehi/8p8VBMKxIbHm7iBffWAFz37tOArT9vRKWkxGji3P5NjyzH2dSoj9SnRS9ftKqemH8gRKKaNS6hOl1LPx2+lKqVeUUlvi/6b1eeytSqmtSqlNSqkzD+X5DiS4j53ud0uxm2nsHNGdYEIcsvV1ndz04Ce0xff0e31jE795eROB0MFtsZFiN/OLT83gm6dVMDXfw5dOLBu0Z/adLc20dsvKzpEiGtV8sL2FVzc0onVsuOyPb26jwx9O2nPWtvt7k6Hd2n0h6jvki6s4svabECml1iilVgPHASviicrqPu2J+Dqwoc/tW4DXtNYVwGvx2yilpgCXEquGvQT4k1LqiJexDUX0fofMUuxm6uQPTYxRfYvw7fbC2nqaDqGo3rhMJ18/bQKPf/lYbl4yqd8co92m5nvw2KV3aKRo8QYHzNOBWHHOZMl0WwfsPWkzG0h3WpL2nGJsOlAP0bnENnI9CxgPnMGejV3PO9DJlVKFwDnA3/o0XwDcH//9fuDCPu0Paa0DWutKYCswP6FXcRBC4f33EKU5LDR0SkIkxqbBPmRKM539hj06/EF2tfvxBcJ4e8Jsqu/knc1NbGnoGnRZtc1sRCnF1HwPl80v6m13WU38+PyppNjlg22kcFqNVGS7cFiMnDQhiznFqQDkpQy+q32nP8Sudj+Bw9jEtzzTxW3nT2H39pNGg+KOT8+gNNO5/wOFOEgH+mqWDWRqrV/o26iUOg+oBaoPcPzvgO8BfTe1ydFa1wForeuUUtnx9gLgwz6Pq4m39aOUuh64HqC4+OBXEBxoDlGaw0y9JERiPw73GhzOpuV7OHliFm9sim3FYTYqfnz+VNKdFrTWfFTZyt/e2cax5Zm8sbGJ7mCYkydms7SylaWVrfz2kpmcPT0PNcjmyelOK98/ezKfmVtIV0+YcRlOxsmH2kEbyuvPYTHx9VMreH9bM29saiLNYeH2C6cxJW/gvmUfV7Xy0+fWs7Gui9On5PCN0ybsc7FKlz+EwaBwDlK/yGwycPHcIuYUpdHQ1UN+ip3ybNeg15gQh+NACdGvgGsGad8A3A2csq8DlVLnAo1a6+VKqZMSiGWwq3vA102t9d3x52bevHkHXWQieKBVZk6LzCES+3W41+Bwlu2x8avPzGBDXRcd8Z3rJ8Y36dzc0M3V9y7lW6dP4GfPbegtgvfJjna+dfoElle38d3HVjMl39O7THtvbpuZuSXpR+vljEpDef0FwhGWV7dx12tbe9ve39bM3Z+bx/icPYU2tzV2c9W9S0l3WphTnMY7W5qp7+zhvquPwW3fU9Kk3RfktQ2N/OWtbTitJm46ZTyLx2cO2PTXajYytSCFqciKRJE8Bxoyy9BaV+3dqLXeChyocMhi4HylVBXwEHCKUurfQINSKg8g/m9j/PE1QFGf4wuJ9UIdUaGIHjAe3Ve600JTV0CqVYsxK9NtY0FZOulOC//32hau/9dy3t7cRHVLNx6bmeoWH3uPjL20rp7vnz2JdKeFFpkkPWo1dvbwwF7Vn0MRzcb6TvzBWEHODn+IymYvXz6pnMXjMwlFolw8r4iJOW5q2v39jn1zUxPffnQVWxq7Wbmznevu/1i22xBD5kAJ0cDqV3vst69ba32r1rpQaz2O2GTp17XWVxLb+uPq+MOuJlbjiHj7pUopq1KqFKgAlh4gvoMWOsAqM6vJiM1skE1exZi2Ykc7V/ztI15c18BrGxu56t6lBCOaqI5iHmSzTKvJyDtbmjljSg4pdilqOlpZTIZBiytazUa+/chKTvrVm3zu7x/itBp58KMdPLxsJx9Xt3HPO9tp9QZxWPYc2xOKcN/7lQPO9eqGxgFtQhwNB0qIXlVK3a72GqxVSv0YeP0Qn/MO4HSl1Bbg9PhttNbrgEeI7ZP2IvBVrfWhz8Tbh1Akut8eIoAMl1VWmokx7alPdg3YW+zJFbs4Y2oOuR4r9r0+FM+ansvrGxu5970qPtkp3/BHK4NSfHZuYb82j82EQcHza+sJRzWrazrZVN9F7V7voS+tqyfYZ/m8USnSHQMn1KfJLgFiiBxoDtG3ia0Q26qUWhlvmwl8DHwx0SfRWr8JvBn/vQU4dR+Pux24PdHzHopgeP+TqgEynBbqO3qYViDj1WJsGuxLg8VoYFKum0BY88vPzGDtrg46/SHGZTp57OMawvFxtAc/2smFswqwmI541QwxxNKdVgBuWTKJDfWdeGxmFpalc/Pja/o9rt0fGnCsUqrfRGizycANJ5bz9pbm3tWJLquJkydlDzhWiKNhvwmR1toLXKaUKiNWHwhgndZ6e9IjS5LYHKL9PybdaaFOVpqJMexTswt4aNnO3g8qpWIbsKY6LLy9uYn3tjYzszCVrkCInz+/sd+x5VnOA37pECOH1pqaNj9RrclPtbNkWi53vLCR9XWdRKOa4yti84T6avUGKc9y9qtr9bmFJRSn95+FMa8kjUe/tIgPt7VgMxtZWJbBlHwPQgyFRCui3aO17tero5R6be+2kSA2ZLb/N+sUu5m6vSb/CTGWlGQ4uOuSWbyxqZGohjOn5lCe5STbY6csy0l9ew9aQU8wwl+d22mJz7lzWox8btE42bl+lGj1Bnho2U5+/9pWwtEoVy0q4YvHl/Obi2exq92HxWSkIMXGrWdN4ucvbGRafgrbm7vo7gnxx8vn8NbmJj7Z0cbpU3M5bnwmRoOByuZuQhFNQZodp8XEnOI05hTLnmNi6O03IVJK2YhNns6Mb7Gx+13OA+QnObakCB6gMCNAhsvCLkmIxCgXjkRZXdPBm5ubAM34bDeBUIS5JWlsrOuksStAc3eApu4gmS4LgVCUTLeVskwn3mCE+g4/eak2Hr5hIRvqYkUZJ+d5mJg7sCaNGJk+qmylssnLDSeWoXVsKOyVDfV8buE4xmfv+f98fEUmt1unsby6jXNm5DKvJI1JeR4m5e3p7enwhbj77W387tUtBMJRTp+cww/OmSy1qMSwcaAeohuAbxBLfpazJyHqBP6YvLCSJ5GEKN1pZXm1TAwVo08kqqls9tLiDRAKR7n6vmW9w2JWk4Fvnj6Ba/+xjO+fNYlVNe0cMy4DpWJzit7Z2sxjy2uYnOfm5InZ/OnNbRgU3H7hdD4zrxDzgcaixbCitaa61UdDZw/ZbhvjMhwDih12+EKsr+vk0eU1ABSm2SnPLCMYjvTOEfMHwtz/QTX//GBPnd4ZhSn87pKZlGXtSZo+2dnG/764qff2KxsaGJfp4NazJh+wR7G5O8Dqmg52tfkoyXAyozCF1EEmZAtxOA40h+gu4C6l1Ne01r8/SjElVSAcwXSAN+4Mp4UGKc4oRplgOMozq3bxgyfXMiXPQ4rD3G+rjUA4SmWzl2A4SlcgTLbbxp0v7/kAO7Y8g3Om5/HcmjoWlWWQ5jDT5gvxw2fWMrckjQnSMzRiaK15bUMjX3/oE7zBCHazkV9fPJMlU3P7JSetviDrajt7b9e0+dlU34WxT+K0tq6D/3zUvzbR6poONtR19UuIVu1sHxDHc6vr+NKJ5WS4rPuMtbsnzJ0vbeKhZTt7275yUjlfP60Cq0zcF0dQQl/ptNa/V0odq5S6XCl11e6fZAeXDIFwFPN+KlVDbFJ1Q2ePFGcUo8q2pm6+99hqAuEoNrMRX3BgVQtfIBxbUq/hnx9U9bvv/W0tvUnP9iYvBWmxCbKhiKbZK18gRpLqFl9vMgTgD0X45sMrqWzuv7nvloauAceu2tVOIBRlZ6uX+k4/obAedA+74F471A82NDatIAXXINt19LW1qbtfMgTwl7e2UTnIRsRCHI6EEiKl1L+AO4nten9M/GdeEuNKmlhCtP+XbTMbMRsNtPsGLh0VYqSqbff3VpheXt3GiROyBjxmUXkGTd0BitId3HBiGd88rYKL5+0pIB+Jxj7kpuR7ej+QHBYj+Sn7q+EqhpuGrp7eZGi3QDg6YB/Hwa6RM6fmcu/7lfzpjW3c+dJmjIbYHKK+stxWyrL6J0BzS9I4ZtyeydMeu4kbTxk/YJuOvXkD4QFtUc2gCb0QhyPRVWbzgCl6FHSZBMKRhOY6ZLmt1Hb4SRtk928hRqLcFBtKgdaxPf3e3dLM986cyAtr6zCbDJwzLY+Ptrfwu0tmcftz61m9KzZUMq3Aw9XHjuPx5TVENVw4Ox9/KII3GCHNYea3l8yiJMMxxK9OHIwsV6y4pj+0J6mwGA1kOC2srmmnwx+iON3BgrIMLp5XyKPLa9AaTp2UxbT8FN7a3MRrGxtJc1iYkufmxpPHMz7bxdubm5iSl8Jn5hVSku6k0x+iqydEpstKYZqDP10xl031nfSEoozPdiU0obo000mW20pT155eyPIsp1xz4ohLNCFaC+QCdUmM5agIhve/uetu6fHijFPzpTijGB3GZ7n42QXT+NEz6whHNVsau7hlyQRMRsV7W1u448WNhCKaF9c18NWTx/cmRGt3dXL29Dx+e/FMijMcFKc7aPUFuXBWAZkua+/QmRg5SjOd/PrimXzz4ZUEwlGsJgN3fHo6r25o4M6XNwOxCtS/v2w2Mwo8nD9zPuhYMcVX1jfwj/erAGjsCvDT5zZw+4XTmJrn5viKTLw9ER5fXkMkGuWuV7ewoa6L06Zk863TJzA+202We2Cv0/7kp9q575pj+NVLm1he3cbi8Rl887QJ+513JMShSDQhygTWK6WWAr1putb6/KRElUSBcBRzAkXj0hxm2b5DjFi+YDi2fUK7n7wUOxNz3TitJk6YkMnD1y8kEIkQDGsqm33874ubBkyuDkf7z//o7gmzYkc7p0/NBaDAYqIgVb6hjxRaazY1dFHZ5MVtNzE518OSqblMvOl46jt7yPFYafcG+eYjq3qP6ewJ8/K6etJdVn7xwnJCEc0Pz53Cc2vq9jo3NHT2cM87lb3DWCdPzKapK8Cqmg4Anl9TT2NXYMBu9/vS6Q9R39mDy2oiP9XOtIIU/nzlHDr8IdIcZmzmRD+6hEhcolfVbckM4mgKhAffnHJvaU4LtVKLSIwwdR1+FLEPoJ88u763/ZazJlGYauPWJ9bSFQhz+4XTaOoO0N0T5qxpubT5gny0vbV3+429i5eWZjopz3LiC4bZ2thNmzdIUbqDsizX0Xx54hC9v62Fa+9bRjBeUfq0ydn84tMzKM92UZ4d+3/4xIoabGYDZ0/PI8dtY2lVKzkpdn7zyube87yztYkMp2XAl8Wopl+16jc2NfKp2fn89IKpWM1GWr1B7n23kpp2P5P3SojqO/1sb/RiMirGZ7tp6urh+0+sZfmONlIdZn524TTOmJKDw2LCYZFESCRPQleX1vqtZAdytATDUcwJVNFNd0hxRjFytHQHeGx5DX98YyvXn1DG717d0u/+X720ia+dMh6P3cznFpUQjmoynBYsJgMfV7ViMhr43pJJPLGiBqXAaY4lRHazka+cXE62x8Kzq+t4bWMjf3xjGxCbTH3PVfNYPD5zQDxi+GjzBvnh02t7kyGI7Sh/xa6OfvuG5XqsfOeMifz7w2p2tfu5YkEx25u6+53rjY1N/PC8yfzw6XW9E/RzPVY0sdWGu9nMBpwWEy+ta2BLYxcLSzP4yQVT2fu76Ob6Lr74z2VUt8bea284sYyVO9pZviNWB67dF+JrD37C019dzIzC1CP3H0WIQSSUECmluoDdV7sFMANerfWI23QmNofowD1E6U4LnwxSN0OI4eitzU384oXYnmI94WhvT89ukajGbFRcfEwRf35zK98+fQJ2i5Ff9imU93F1G3ddOguH2YjdYuRPV8xmZ6ufFLuJlTs6SHdZuPOlPb0FvmCEmx9fzZNfOZYst+3ovFBx0LzB8IDl9AAte5VKCEU0v3hhY+/w6dMra7n0mCKWTMtlcq6bqI6tVKxq9vLoDYtYU9uJ22picp6bHzy5tt+5Pr+4lJufWE1zd2xLl80N3dS0+fnOGRN6HxONah5cuqM3GQIwGw18VNna71xaQ1WzVxIikXSJ9hD1q7imlLoQmJ+MgJItGDlwHSKADKeVeplDJEaAaFTzcJ86LWaD4hunVRCOapq6Ajz1yS5sZiMzClP5xkMr6QlFcVpNPL2ydsC53t3STLM3gNtq5tnVtVy1aBxuq4um7iA5noGTWGva/LT5QpIQDWNZLitnTs3lhbX1/dpLM510B0K0eUOkOszUtfdw7vRcTp+aSygcRRPbm+6Tne38Nt7jOCnXzXfPnMjEXDdzx6X3nuu286fy+9e28NaWJibluqnIcfUmQ7u9vqmRLxxf2nu7Jxzhg+0t/R7T2h0kL8U2YEhOJlCLo+GQBmS11k8ppW450sEcDcEE6hBBbD+z+nhxxr3L2QsxnBgMioocFx9VtrKoLI3x2S42N3RjNhpQCn547hTC0Sg3P76GG08Zzx0vbOTl9Q24bAP//JVSlGY4eWtzE1EN/3i/itsvnEaOx4p1kLl3E3PdZMmH1bBmNRv5zhkT6eoJ8e7WFlLsZn503hTsZiPX3fcxS6tamVucxs1LJtLsDfDtR1YRCEcpy3Ry2/lTmZwb26pFo2n1hvhwewvH7TVMOrMolT9cMYf6jh7SHGbe29YyIA6zUeGx77nmHBYTZ07NYWP9nuKP/11Vy+2fms63HlnZ28v56dkFTMmTKugi+RIdMvt0n5sGYnWJRmRNomAClaohVpzRZjLQ4g2SKW/4Ypi79JhiXlhTzxULx/Gt+AcawEkTsnCaTfiCYWrb/Wyq7+QPl8+msTNAltvKGxsbe+eCWE0GZham4Labufe9qt5z+0MRjAbFceMz+cWnpnPbf9cRCEfJT7Hxy4umS62uEaA008n/nDOF+s4e7BYjuR4bl979YW9PzPIdbaysae9dcg+wvdnL1sYuMlxW/KEIWseW4hem26nv6GFrUzcOi5Gp+R48dgs2s7G3rtCsohSm5HlYX7dn249rF49jYm7/WRafml3Ix1VtvLetBaXg3Jl5LChL579fO47KZi/pDjOT8jyyb5k4KhLtITqvz+9hoAq44IhHcxQEI4nNIYJ4ccZ2vyREYtibVpDCP6+bzzcfWdmbDAG8ubmJOSVpnDgxk4vnF/LAhzv54j+XA1CS4eB3l87mw23NGA2Kkydl8/LaerI8/Ye/ZhSmMKsoFYvJyKRcDwvK0unwhyhItZPtkaGykeC9bc1ce9+y3l6XH547ZcCwVKe/f0Voj91EhsvKvS9toqYtNs8n1WHmx+dP5c9vbCbdbaerJ8xTK3fx9ZPG0xGMUNvuJ91pYXZxGn++cg5vbW5iY30Xi8oyOLY8Y0Dv/LhMJ3+5ci672n0YDQaK0u3YzCZyPDYm5424KapihEt0DtG1yQ7kaAlFEhsyA8h0xRIimcwnRoJWX5Atjd0D2qNas76uk6I0R++u5RDbz+qWx1fz1ZPL+cd71aQ7rTz0cQ03L5kIgMmguPXsSUwrSOnd2dxgULLUfoRp9Qb50dNr+0207+wJYVDQd+59UXr/Apvjs1xsqu/qTYYgturrtQ2NnD8jj7++sx2As6blsqmpm1ueWENDZwCnxcgPzpnM+TPzuGrRuP3G1u4L8uamJu5+extOq4mvnjyeRWUZB9zOQ4hkSHQvs0Kl1JNKqUalVINS6nGlVGGyg0uGRDZ33S3daWFXu0ysFsNYOABNG6FpE7Vtfo4rH7gEfmKOm/e2tgy6SMAXjNATitLUHUApuG5xKedOz+eRGxby3E3Hc9WicVL7ZYTzBcNUtfj6tb2yvoEvHl/Wr81tM3H+zPze21rrQUuPVDZ70UpjNcWG3orSHNz50iYaOmOr1rzBCP/v6XWs2dU54Ni9vbW5iW88vJL1dV0sq2rjmvuW8cmO9kN4lUIcvkTf6e4DHgA+G799Zbzt9GQElSxaa0IJVqqGWEJU0+Y78AOFGAqddfDOr+Hjv9M85RocZTdxxcJiugJhVu5sx2U18c3TKvjzW9tYXdPB7OJUbGYDPaE9Q2qlmU7qO3rw2EwsKE1ncny+RpHsEzVqZLmtXLWgmOwUO/5QBJPRQFNXgBkFsRVj/lAEm8lIuy9EizfAN0+fQDhes6go3TFgNeI5M/L4zqNr6PDHNr9+eX0DN51awbq6PSUcIlHNzjY/i/YTV08owr3vVQ5of3VDAwvLMw7/hQtxkBJNiLK01vf1uf0PpdQ3khBPUoWjGoNSGBIozAiQ7baxcmdbkqMS4hBtex2W3UP7xEu4resCnn10PQYFF88r4qZTxtPSHeCZ1XWsjm+f8ODSnXz3zInc914VNW1+puencM3icWxu7OKBLy5kWoHs2zcaBfzdHFPs4MZHN7J7e+6ZhR6umGrlqw/umUT9t6vnsXJHO+9t3bNC7KcXTOXrp47nr29vJxLVXD6/mHZvsDcZglive3cgjNVk6Dd/Ldtt5e63t/HJjnZOm5LDceMzyekz58ygIHWQbTxSEtjaQ4hkSDQhalZKXQk8GL99GTBwXeUwFwhHsZgSX0Kf47FS3SI9RGJ46u5oZsfxf6AxdTbPPlrNgtJ0FpSlY1CK2jYf47JctPSpBdPUFeDXL2/mZxdOI9tlxWUzUZHt5qK5hTR3Bahr95PjsSX8hUGMDF3dXn7+cnVvMgSwqqaT6vb+w6vd/jDfOmMC725poabNx/EVmVQ2ezllUjbHlmeiAatJ8a1HVg94jjSHBYsxlhApBV89qZwtDZ38/PlYr9ELa+u5dvE4bj1rUu98NIvJyA0nlPPOlubeuUwOi7Ff9WwhjqZEE6LrgD8AvyW23P59YL8TrZVSRcA/gVwgCtyttb5LKZUOPAyMI7Za7WKtdVv8mFuBzwMR4Cat9UsH+Xr2K9EaRLvleGzUtPuJRrV8SIhhZUNdB7+rXkiBI8zUFDc/uWAq0aim2RvEYjTQ4guRHQrzheNL+VafDTsjUY3WcOcrm9nV5uffX5jPhroufvHCBrp7wlx3XClXLCghN0VWj40Wfm2loXPg/DFldXP7hdPoDoRxWk0UpNr445tbcVlNlGW5eGZVLV8/tYK3Nzfzt3e3E9XwmTn5fPH4Ur7fpzK13WxkVmEK914zjx1tfrJcVlJsRi740wf9nu+fH1RzxYISxmfvmZQ/vzSdR790LO9uacJuMbJ4fCZT86WnUgyNRBOinwJX90lc0oE7iSVK+xIGvq21XqGUcgPLlVKvANcAr2mt74gXd7wFuFkpNQW4FJgK5AOvKqUmaK0jh/LCBnOwCZHNbMRtNVHf2UN+qv3ABwiRZJGoprKpm67mOn5VuhzPyntYN/dpfvN2I69tbOx93JdPLKeqyUdnT4i/XT2P2nY/1c1e5oxL5/UNDayMb0uztLKNH/93Xe8KpN+/HvtAvOHE8qF4eSIJbDYbZ03P47+raslyW+nuCTMhx8XHOzu55509c3g+t6iEn14wlcoWH81dAS6aU0A4EpsgvZs3GOWTHe38+rMz8IeimIyKSCRKZYuXS44p5ph4Ieo3+lyLu0W1Ruv+5etMRgNzS9KYW5KWnBcvxEFINCGasTsZAtBatyqlZu/vAK11HVAX/71LKbUBKCBWv+ik+MPuB94Ebo63P6S1DgCVSqmtxLYH6f814zAkWpSxr9wUG1XNXkmIxJDq7gmxvLqNt7c04zAbWZLbgefN/yGcOYVtHYpl1a2cPiWHNm+Q5Tva+OcHVfz+8tn87pUt/OGNbaQ6zHzt5PH89pXNbO2zNL/DH8RoUP2WZD+4dAeXHlNEihTDGxXafCHmlaSyqCydVTUdZLmtLCpL55r7lvV73L8+qObUSdksq2yJfXFUUNnYf6WY02piXKaTp1bW8s6WZuxmI1cuLKE8y8k7mxt4b1srE3LcTMn3UJhqo6bPKt3Pzi2kWCbri2Es0YTIoJRK26uHKOG1uEqpccBs4CMgJ54sobWuU0rtHjAuAD7sc1hNvG3vc10PXA9QXFycaAgABMIRzINsP7A/hWl2NtR3cey+dvTubgKrG8wyxDBWHM41eKieXlXbbwPN5zJs3L/45/TkzGWKzc83TyzkkVUtZLut/L9zprBmVzt/fmMbq3fFJlS3+0L87PkNfOv0Cfw6Xo3YaFCMz3b1mwgLUJzukDoww9jBXn92s5EOf5jfvLJnAvVTK+xcu7iUh5ftpCzTSVWLl4jWRKKadn+YXW1+0pxWTp+YTonNx3GeRgw6Qq0twrsNPt7Z0gzEqpjf8852fn/ZbJq7ApRnuQhHNfe8tZ2/XDmP59bUsbSqlQtm5XPa5BysJrmuxPCVaFLza+B9pdRjxOYQXQzcnsiBSikX8DjwDa115372BRvsjgHbg2it7wbuBpg3b95BbR8SOIgl97sVpTtYs6t93w+4czzMuw7O/e1BnVeMXIdzDR6KunY///vixn5t21t6WJW2hGl2P89sC/Ob16sA2FDXxYfbW/nj5bP5Qrwi9Z64wWU1UZrpJN1p4caTyxmX6ez3Td5iNPC1UyqwSUI0bB3s9ReMRLn//ap+bTXtfsrSLbywaAM59W/RNH4xG/I/zY0PfoI3GJulsKmhi88vLuaavBY2dbuIaEWFO8htb7QOeI5tTd08vryGnW1+rCYDt541iVAkws1nTSIS1RhlDqYYARKtVP1PpdTHwCnEEpdPa63XH+g4pZSZWDL0H631E/HmBqVUXrx3KA/YPdhcAxT1ObwQGLgd92EIHkSV6t3GZTh5e3PT4Hd2x9trVx5eYELsS3cj4bZ2/MGBU+lCUU1tNJOJ+RH+dEUaOhqlOxihtr0Ho0ENumt4KBJlWr6Hzp4w//6wmt9fPod/f3Eh63Z1EAhHmZTrli0TRhmtNd2B8IB2e6AVT/NKdhWcSVrjMny2es6ekUdRmoNQJIrNbOS/K3eR7pzKgx/vxGRQTMo1MTHHSVN3oN+53DYTF082M9HeQ1PYwR/e3sadn53F25ubaOoKMC7TwZQ8D3Yp8imGsYSvzngCdMAkaDcV6wr6O7BBa/2bPnc9A1wN3BH/9+k+7Q8opX5DbFJ1BbA00edLRE8wguUgh8yK0hzsbPXTHQjjsu71n6tpI3jyob36CEYpxiRvM7RuB5MVMirA4oCWSnj//8jNnckjF01mW2uQhoCZM4qhzO4HvZ12Sy4fN/r464oeZpekk+ux4guEafeH+PKJ5fzk2fW984NOn5LD8uo2XlrXAMQ2c23zhRiX4WRchnMoX71IIrfNyFULi6luaGFJcZTGHiMPbQyTW1jMNeu+wMer25lVOIXvzSujeVslH2xrIdttY0N9B99fMokTckPckNYAkRANtlJWR8dhNUQ4uzhMZ1DxQYuD+ZlBClztRI02lA5wfGaQpa2dvLulkXn5Nn76QSeXHlPMqRMz2LSrlZ5QhPG5KYzLlQKMYvhIZrq+GPgcsEYptTLe9n1iidAjSqnPAzuIV7/WWq9TSj1CLOkKA189kivMIDbebT3IhMhiMjAhx8X7W5s5Y2pu/zvbKiF7Kmx/I7aFgkk2gRWHoGkjPP4FqF8Tu33Rfej0EmirRpUsxLxzKbOXf5vZJ91CJLMYw7r/ojb+F4D0grmcdNKPWHBCF8uN4+gOG6jIdvPvD6uYV5rOTadWkO604LAYeWFtfW8yBDCnOJVUmxTBG+2MYR9Xjg/gcXxCvU5jriPAORefzGf/s5b6+HL8lTWdfO+Jtdx61mTe3NzErjY/Xzy+jAJjG4VLf4tx4zMA5BfOJ+v0n3OG5+8Y338SLG6uPPl/CNiOwbDhVTrsRbh76jCVncpp6SEuslajvI1cfnIR2xxFfPmBVXy8IzavzWM38a+rZjKzNHefsQtxNCUtIdJav8vg84IATt3HMbeT4NykQ+E7hB4iiO0k/trGxkESompwZYMjHbobIPXoTLAVo0gkDB/dvScZmv8ldOcuVNP6WJJdMI9IxRIi48/CGPaifC29yRCA2rUc4/bXuE9dxr3vrSfTbeVbp1Vw1bHj6A5E+NqDn/D/zp2MLxjGadkzLyjTZeHWsyfjtMkQxmhnIkJ3Tw9/b13EFHeApoCBjFoTuSm23oQI4IJZhfy/p9fR6o0V8/xkRzvvnlnXmwwBqJqlmDc8hdr5UWxSWqAT80u3UHXJ2/xfx0W8usLH1Jx5/CAnQpmzA/XUl0BHMdhSWHfyK73JEECnP8z/vbWTP+WnYbXKl0kx9A4+OxjB/KEIVvPBv+RFZRk8v6aOrp5Q/zvaq8GZBbY08O5jnpEQ+9PTAVtfif2eNg5ypqLSS8GRAasfgkevwrj0L1haNmJ8/y4MlW8NOIWp8nW21rbQFQhT2ezlpodXEolqOnxBCtPsdAci/OvDarLdVu6/9hj+84UFPP3V45hRmHpUX6oYGg4doCVo4HuBP3Hph+fzta1fYEH4Iy6Z3f8LnsmgepMhiK2wte58b8D5VPW7kD2593bHpEu5+dU2/ruxC38owsc1Xq56MUx9yA46voJRGaiubx5wrg11nbR2D9xAVoihMLYSomAEy0FOqgbIcFmZVZTKPW9v739HRw04M8GeEpsDIsTBsnmg9MTY74u+BmseAYsL6tbAjEuhZHHs5+UfQOMGyBhYMLE173jWNO75INMaqlt8LK1sZf64dBo6/CgUeSl2SjKcLB6fSUGa1NUaK3xYmb7tblxbnowlKJ21lL9+A8e7+69ZSXf2Hz7d1e6nJXPOgPPpgrnQvGcJf03mYlbUdPV7TFcgzA5fnzpW/jZmpgzcBum4ikwM+1553CsYjrKxvpO3NzexpaGLSDTpizvFGDSm+st9h5gQAVwyr4gfPLWW06bk7Plm3VkLjkywuME3cCmqEAdkNMOir0D1e2C0xpKiSACa1sO69TDp3FiybbZDyBfrURp3HFS9C4DOmszqzHPZ8UF7v9MaDIpTJ2eT5bbx3rYWvn3GBCbmuhiXKZOnxxpPtAP7lqdiN0w2iARBR0n1VfKdM46lJxybWzkzLUSG00JLvJfIF4zQkj6X4rKTUNvfBEBnT8U/8VM4Vj3Ye36rxTpgY1cAd6S93+3ZLc9z40lf5J53qwmEoxxfkcnxFZk491qs0u4LsrSqlXc2N1Oe7eK48RmsqG7n1ifXEIlqLEYDv71kFmdPz2U/ZVyEOGhjKiHyhw5tDhHEeomuW1zKF+7/mAevX0h5phO66mNDGxYX+NsOfBIhBpM9Ba59Ed20EVW3Et6+EwKxCsG19gpWpp5D7ayzmOz0MrPyHlyONPTZd9Jjz2FrJJftXZkYVHvvBpnlWU5K0h24lI82v5E/vrGVyxcUc8GsAXVOxRjgNbig/CzWFF7BOq+bDEuEWeGVpNpSqa/1k+q00NjZQ0l2Hf85oZ1nmvPY0G7gwpIwxVYfypYCJ90KOorq3EVPyw7ePvZBSqI7CSgbn/iK+fopafzy5S29z7lkSg45qi220CQcAGcmkSkXUup18+0zJhDV4LQYSbOCy7knSdda88jHNfz8+Q29bSXpds6YmtvbKxSMRPnuY6uYku+mNHPPvmhCHK4xlRB5A+HDqpQ6vzQdfyjMp//0PhWZNrb7/o+vbTRwrcUJvpYjGKkYa+p6THzclMVcYwH58WSoecYNfKd6Ae+/s7P3cbed+C2u3vZNWmfewGMN+QTCUbLdJn71mZlUtngZl+FkfLqVFEM3D631U5ge+wZ9QsU+Kq2LUa9Fu3m34ja+8cRmIHZtTcyawW8mTmRZ1RbCUTAozYbyUhb0/JPv7fhJbLFItYlQVwWsfzr2E5desJ4VOb/lS+97MRsV1x3r4jMTzOgzJ+INhLFbjGit2ekuZO2iR3FHO6hTmRi7CylMsxGNBAlEoCLdxIyS/jvb72r387tXN/drq271Dyh54gtGaOkOUiqXtTiCxlRC5A8e2qTqvk6ckM3U/BRqdmznos5X+dmyT3HRMSl4pIdIHKJ2f5Dbnt+G19vNaSfumduzMfUE3l/af8LpLz/oYuLF/+HGR6v42ikGfvHCngrWp0/OZnFpKuWV/+YV96coy3bR0BngplMrOKY0/ai9HjG8GJTiF6/2r5W2qcnPivoQp0/NY1tjN6WZTl6vDmGfeiPpeadjCnYQzphI6pYn2Hvveb+7jOJMDzedaieq4ZV1DRSn2fnVS5tQKjaHDeCvV8xkTSAbiymX1q4gbyzdzB+vmMtnF+x74+BIVBPca+gNBm5Z4LGbyPHIdkniyBpTCZE3GMZjP/w/okyXlUx3F7giTLEbeaOzgAtsnxyBCMVYtK2hm7V1XTwybyP21e/AhDNh80v4omZiJbn28AUjtGsXLd4gFpOBr58ynk92tvdupjmp8Tk+si7iW4+v4+9Xz2NBaTpF6U7ZOmEMC4Q1bd7QgPbuQIQ/vL619/aisgyOL08lw9eCmRCdrfX4c08ixXH3nh5ws4OaCZ9j2aZ2nl5V13vsluZYL07fithdQc3d8YUoJoPiB+dMZkL2/oe48lPtXLmwhH/02WrEYzMxrySt9/weu4nfXzqbonTZKFYcWWMqIYoVZjxCezT5msDqYbrTwJstGVyQJj1E4tAEfF18eaaJgqU/BzTVn32Funm/Jc1kxmlZ0bu3FMDi8RlUt/jIT7ERjmhmFKViUlGK0ix4jAHuqpzJhqYgx5ZnMH9cOm67FF4c61zmCBfNLeDBpXuGXs1GRTSqOXVyNpNyPWxu6OL1jY1cf1wRd1dmsb7NwOdnmAmpfDbPvY+phiqMOswWVUqnLqfdX9fvOXJTbPhDe65Tj91EcaqFH547mTZfiPxUG8eMS8N1gOvRbDRw/QllFKbZeXxFDZNzPVy7eBzTC1N57mvH0ewNku22SjIkkmJMJUS+wKFPqh6guxGsbkpTDLxfbQd7x4GPEWJvrZU47A4mpBvpnnwJG2fewn+W1fLc6tWUZDr4zSWz+Ps7lWxp7OK48ZmUZjnZUN/JaZNzsJgMuCxG3tzSytraTgLhKJfPL2JWkYOLjymSZEgAkGIIcMaUXKIaXl3fQF6qjWsXl+KyGHljUyN/enMrMwtTue28KTR0h5lfaOczk+GxzWFmlEZoMhSwyptFOKrJS7HhDkXYVN/Ze/45xalUZDs5Y0oOH2xvYWKOmyXTcvF2dnDR3HF09YTJclmxJrhhcH6qnS8cX8Zl84uxmgyY4iuDSzKdlMgqSZFEYyoh6glFsB3JhMiVQ6HbQGW3mbCra2z9xxSHr70Gb8NWcqNWunPLeKjnBipXNfDkJ7sA2NLQzZf/vZz7r51PVyDMkytq+P3rW/nLlXNBa2xmI29sbGD5jnYAxmU4uHxBCRNz3Qe9ibEYvRpCDn750mp8wQhLpuXS1BVgzc4OXlpf37v578qd7dS0+fjXlVPYuM3PBzs1ZxUbKcjw81SH4rnVdUR1rEcp12PjT1fMYXNDN2ajgUkZRn7wzAZCmDh3eh5VLT5+88pmHvtcBSl2Cyl2ywEiHNzey/GFSLYxdcXFtu44QkNm3fWQNQmbSZFhgyqvhfFH5sxiLGjaBI9eg7NxPeGpV/Jm3o247E5eXLuj38OiGpbvaOMf71fy3TMmcckxRdjMRhxmI12BECWZLv5w2WycViOT8jzkpUjBRdFfWMPG+q54wc7Y9fW1U8b3JkO7NXcHWd8S5duv7Ont/tVZNhYUZdEdyMNkULyyvpHjxmeyvbGbW56IbTdTlGbjngvz+L/3mnl0eQ1Tc+z8/YIc/NEx9fEiRoEx9TWy5xA2d92n7kawpwFQ6DGwpcdzZM4rRj+t0Svuh8b1YHWzZsYPeG97O1UtXgpSB076T3dY6PSH+fdH1eSm2Fi7q4NgJMLyqjb+9NY28lJtnDwpR5IhMSi31ciisv67yhsNir3n2SsFJoOBkyZkcckxRZRkOLj9rWZy7Zq/vVPJX97ajstq5NTJ2bT49lRG39nWw6oWM1+eY+WJi7P50XF2HlnTThdyPYqRZUyl8P5QBNthLrsHYpWEg16wxpKgbIeRqpYsCPWAWZaCigMIelHb3gCg/qRf09YT5aJjStjZHuTKRePYUNfJ/e9XEdUwPttJJKqJamjzhqhr78FqNtLqC/F/b2wDwHakej3FqNQdiHLNohKuXFhMQ2cAp8VEXoqVzy0q4f739yzH/+zcQjx2E509IdbXdXLKpGzcNhNhDHzjtAq0hnAkitEAy6vb+z+J2cqnHm0hHIktkD99cjYmWdkoRpixlRAdqSGzrgawp4MhllxlOxXbVVFsWwVJiMQBBLuaoPRkLD0dfGSZT4rNwt/f2U6Kw8LSylY8dhN3XTqLrp4wuR4b1//rYwDOmZGL3WKkON3OxrrY3lFXLiymNEsmmop9MxggAtz04ErC8WrPC8vS+ebpFUzMcWMxGQiEIpRlurjmH8t6t+B4aNlOPjOngM6Qid+9uqcKtS8UoW9loCl5blIdZr59+gS8wVgv/Ma6rkH3KFtf18lbm5po8wU4eWI2s4vTsCU42VqIZBszCZHWmq5AGKf1CPzxddbGtuyIy3UaWKPzYgmRO+fwzy9Gteq2HtwTL6Vj0pcoM7nY1OBFo1hX28nZ0/MIR6JsrO/mkx2tjM9xc/7MAtKcFtp9QXa0+vjBU2u541PTuftzc5lTnIbDMmb+jMUhMBsUd7ywsTcZAlha2UogFGXtrg7e3drCwrJ08tMcAzZNfXJlLZ+dW9SvbVlVK989YyKT8jwYlcJsNOAPRvj961vxxUtEnDUtlwk57n7Hbarv5NK/fkBnT6xW0d1vV/K3q+dx2mR5zxTDw5h5J/XGN3Y1GY7AkFnnLnDsqfyb61RURzOhp/3wzy1GnbW7OvhwewtRrZlbnMojK4NcOr+Q7kAUb3eA/3l6LT2h2LfyymYvn5lbSIYBclPsrN7ZzqXHFPPrVzbT1BWgON2Bw2xkQVmGbNQqEuILRtnZ2n+n+U/PKeTnz29gY303ADtafXxc1cpn5xX2q1fksZkwGvv39Mwfl85Pn9vA1sbu3rY7PzODv109j+1NXvJSbEwvSCHN2X912UeVrb3J0G6/e3UzC0vTcdmkRIQYemNmUnW7L4jbdoTyv/YdsV3u4zLsivaIHX+XFGcU/a3a2c5Ff36fnz23gT+9sY12X4iLjynEoAzc/0EV21u8vcnQbs+srGVynoep+R4cFhPPrKqlqSuAx27CYjJw91XzJBkSCXNaDJwyKQezUTE130Neio38VFtvMrTb9mYfxen9r6trji0lEN5TcHFyrpspeZ5+yRDEEqpjyzO5cmEJp07OIXuQbTV6+hRu3M0biAzolRJiqIyZHqJ2X+jIJUQdO6D0xN6bBqXINfuobgoy6cg8gxglnlq5i0A4Slmmg99cPJM3NjaxuCKLysZulGLAppUADqsRm8nIc6tr+fqpE7j3vSquO66UJVNzGJfhHPTDRoj9ueGEUhaUpfP+1hZmFaYwuyht0Mflpli56dTxdPWEyXRZcVqM5Hps/OOaYwhHo7htJp5YsWvAcYkk6PNL0zEaVL8E6IYTykhxHFqdIiGOtDGTEHX4Q0eo0JeGjhpw9R/3zrX2UNmsJCES/TR3BTAY4PeXzGL1rg6mF6VQ0+plW5MXg1LsbPVRlG5nZ+ueTVy/cWoFSsHNSybz3pZmLp9fxLHjM3Db5INDHLyIhlc3NPLX+L5iAI1dAT41J592b5jJeW42NXRhNijGpTtYu6uDDl+QXI+NiTluguEo1/xjWe+xv/jUdLY2dbO8uh2zUXHZ/GKm5h247Mj0glT+84UF/PnNrTR3B7lucSmnTMo+4HFCHC1jJiFq9x2hhKi7CQwmsPT/RpRjCVHZLstMRX+fnlPIvJJUokBDV5CybDd/e6eSpZWtTMn3sLAsg4vmFOKwmNjV5mNuSRqPfLyTi+cV8cnOdqrbfPzfG1t5/qbjmJIvCZE4eMFIlAeX9i/4+faWZu7+3Fz++MY2/vLWNmYXp3HtseMIRaN4bGYKUx2sq+vgwaU7+P1ls/sd+8SKGu749HTW13XhMBspz3ZRlrX/TVshVvtoYVkGs4tTiUS1LAYQw86YuSLb/UGcliOwwqx1O7jzBzTn2KNsbZflo6K/BaXppDvMNHYHmF7g4dYn17C9yQvA2l2d7GzdwqXHFJHltnLOjDwu/uuHTM714LSY6OoJ886WZkwGdeT24BNjjkKx9zSdz84r4tYn1lAbr1a9vLqNHS0+fn3xTH7bZ4k9QFT3P/jiY4qoyPFQkXNoxWiP2AbbQhxhY+Zdtt0XwnkkvpE0bQLPwISo0KXY2C1zO0R/Ld1+DIbY0mRfKNqbDO3W4Q9htxjJT7Gzq92Px27i1rMm8t/Vu4hENa3eIF86sYySdJlELQ6Ny2rg2sXj+rVluSy9ydBuTd0BOvzBfm0nVGRiMxlYUJrO7KJUfvHp6Swu71/1WojRYtj1ECmllgB3AUbgb1rrO47Eedt9IRxHYsiscT0Uzh3QXJxqZttmD+FItHd3ZiHCgR421Pnp8Ifo7AljMqh+9WAAJud5cFmMVLeG+PtV89AaLphVwIrqdv521TzmlKRilh4icYh8wSiZLgs3nTqepZWt5HrsTMhxY1AM6DlyW82kOcy0+ULML03jnBl5KAW/v3wW0agiN0W+9InRa1glREopI/BH4HSgBlimlHpGa73+cM/d4g2Q4bQe3knCPdCyFaZdNOAuu8NJpqGLbU1eJua6BzlYjEUtQSPrajt5bk0d6U4LVy4s4R/vV/Xe/5k5hRSn2fl4RxsTsl28s6WZi+YWUpLh5ORJUrBOHD4N/PLFTUQ1TC9MYXVNO9uauvn8caXc805l7+OuXTyO3BQbF84uwGU1sbWhG4/NjNNqJtst+5KJ0W9YJUTAfGCr1no7gFLqIeAC4LATop2tPibmHGaiUvMxpBUPvj2HxU0p61hV0y4Jkei1q81HTziKyWBgc0M3GU4r3zljIv5QhJIMB8Vpdl5cV8+EHDdbG7s5b2Y+JRkyPCaOIAVGo8LrD7O0srW3+cZTxjOzMJWm7gAZTgsFqTai0TDlWU60BrvZgDcYpiDNMYTBC3H0DLd++AJgZ5/bNfG2w1bT5ifnsOq3aFj3FOTNHvxus40pqoo31g+s0SHGrpp2P5XN3VxyTGz7gw+2t3Dny5v494fVlKQ7yHSauHReIadMyuaqY0upONykXYi92EwGvnJieb+2TJeFVLuJ8mwH0wo8VGS7MBoMuGxWrCYjLd4gMwpTWTItb4iiFuLoG249RIOtW+83yq2Uuh64HqC4uDihk4YiUZq7A2S4DmPZ8prHINgNuTMGv18pZjtbeHBrK4FwRFZSjGIHcw2m2s2cNjmXug4/3z1zIhtqOynOcHDc+Ez+82EVXzmlgrw06RESiTvY90CnWTG1wMNPzp/KR5Wt5KfaOLY8EwOaYBh8gTBmo4EZhSkYDAaKpYdSjFHDrYeoBui7k2AhUNv3AVrru7XW87TW87KyshI6aW27n3Sn5dD3Mdv0PGx4FmZd3rvD/WBS3Q4mpER5aK+aH2J0OZhrcGZhCjtbvWxv6kZHo3xmXgGLytIJRaJ84/SJTMo9tKXLYuw62PfAnFQXDrOJquZuzp2RR2Gandp2HzkeOzOLUjlxYg6zitIwHIl9HoUYwYZbD9EyoEIpVQrsAi4FLj/ck1a3+Mh2H+Jw2a7l8Mm/YP4NYE/d/2MdmVyUVs8vX7UwqyiNmUUHeLwY9aYVppHltlHX0UMkqnFZTVTkuDEYpIinOHrmjksnzWGmqTtIQaqdCTkubFIYUYh+htVfhNY6rJS6EXiJ2LL7e7XW6w73vMuqWilNdDPMtsrY5GlnJoT8sOKfMOuKfrvb75M7l9L2tXz+uBO56t6lXH9CGTecUCbL8Me4nBQ7OSmySkcMrbJsN2WyU4YQ+zSsEiIArfXzwPNH8pxvbW7ivBkDiykCEPZDZy1YPVD9Hqx6CPJmQu0nsfvnXAUphYk9UVoZbHyOeSe6KblgKn9/t5JnV9dy61mTmVmUSocvRGdPiPxUO+lO2YZBCCGEGC6GXUJ0pG2s76Sq2cuEvVfv+Ntg/VOw6QWwpcQmTLtzY0NjzkOsxGpPAU8BbHmJrEnncvOSSby3rYWfPLue2nY/LqsJp9VEY2cPpVlOzpiSS5rDzKb6LjbUd9ETilCQamdReQYnT8ymJMOBUgqtNUrJEIsQQgiRLErvtU/NSDJv3jz98ccfD3rfR/Hlzcuq2pju9nKKfSuEfOBvjQ2FAZiskD1lwEath6WnA+rXxH535cRqFmkgGgZlAJOFiDKzzjqbta0G/KEwuSl2xmU4sJqMNHT2sLa2g55QdNDT56XYiEY1DV2Bfu02s4Fstw2jQRGNl59VCsJRjS8YwRcME4lq7GYjqQ4LLqsJq9mAzWTEZjZgNhowGhRKxfY+6kuj0Tq2p1EwHKUnFCUUicbv67/XkQJMRgM2sxGryYBpH+c8kN3PGY7GnjMQjhDVYDEasJpi8SrFfs+9+xyRqCbQ5xxmo8JmMmIyKkozXXz91Arsg+9zd8Cg93cNCnEE7PcalOtPJNmY+iY+ohMipVQTUD3YfaknXJWbsujiAsKB6Gmm1f0WUAQj6I6AikQ0SXnxZoNWGfb9975tbCG0qd3k3d9jlMlsQEe1jka10ZVusWQW96uQFu5uDepwMGqwuUxGm2vU9/Ylg45GdO09X1obbq8LDnJ3s9Z6yf6O3981uJdMoPlQYhyB5LUeOfu9BhO4/kb6/4uRHP9Ijh1i8W880HvgaDKiE6KDoZT6WGs9b6jj2E3i2bfhFMuRMhpf077Iax0+hnt8BzKS4x/JscPIj/9QyPInIYQQQox5khAJIYQQYswbSwnR3UMdwF4knn0bTrEcKaPxNe2LvNbhY7jHdyAjOf6RHDuM/PgP2piZQySEEEIIsS9jqYdICCGEEGJQkhAJIYQQYswb0QnRkiVLNLHagPIjP8n4OSC5BuUnyT/7Jdef/CT5Z0wZ0QlRc/NIrnklRgO5BsVQkutPiCNnRCdEQgghhBBHgiREQgghhBjzZP8rcciauwKsr+uk3R+kLNPFpFw3JqPk2EIIMdz4Q2E21nWxo9VHttvKlLwUUhzmoQ5rWJGESBySpq4evv/kWl5Z3wCAQcHdV83jtMk5QxyZEEKIvqJRzVMrarn1yTW9bdcuHse3T5+IyyZpwG7ydV4ckg11Xb3JEEBUw/97ai2NXT1DGJUQQoi9Vbd6+fGz6/q13fdeFVsau4YoouFJEiJxSNq8wQFtdR09+AKRIYhmZGrzBtnR4hvqMIQQo1x3T5ieUHRAe7svNATRDF+SEIlDUpblRKn+badOyibHYxuagEag/3lqLSf86o2hDkMIMcrlp9opz3L2a7ObjZRkOIYoouFJEiJxSCblefjLFXPJclsBOGliFreePRm7xTjEkY0cNnPszy8SHXP1z4QQR1GGy8r/XTab2UWpAJRkOLj3mnmUZbmGNrBhRmZTiUNiNho4c1ous4pT8QXC5KTYcFjkcjoYwXCsC3t9bSfTC1OGOBohxGg2NT+F+6+bT3N3gBS7mQyXdahDGnbkE0wcFhkiO3QNXQGcFiPVrV5JiIQQSeexm/HYZan9vsiQmRBDpLGzh6J0B20ysVEIIYacJERCDJHm7iCFaXbaB1mxJ4QQ4uiShEiIIeAPRgiGo+R4bLRIQiSEEENOEiIhhkCbL4jbbsJtM9EqCZEQQgw5SYiEGAL+UASbyYjLaqbNJwmREEIMtaQlREqpIqXUG0qpDUqpdUqpr8fb05VSryiltsT/TetzzK1Kqa1KqU1KqTOTFZsQQ60nFMFqMuC2mQat+i2EEOLoSmYPURj4ttZ6MrAQ+KpSagpwC/Ca1roCeC1+m/h9lwJTgSXAn5RSUuVPjEq7EyKX1US7X1aZCSHEUEtaQqS1rtNar4j/3gVsAAqAC4D74w+7H7gw/vsFwENa64DWuhLYCsxPVnxiZAlFomg9eio6+4NRLPEeog5JiIQYIBiJjKq/eTH8HZXCjEqpccBs4CMgR2tdB7GkSSmVHX9YAfBhn8Nq4m17n+t64HqA4uLiJEYthoOmrh7e2NTIQ0trmJDj4ooFxUwvTB3SmI7ENeiP9xA5LSa8gTDRqMZgUAc+UIx5o/09sKHDz6sbGnlseQ3TCjxcOr+YqflSuFQkX9InVSulXMDjwDe01p37e+ggbQO+Hmit79Zaz9Naz8vKyjpSYYphSGvNIx/X8L3H1rBiRxsPLdvJZfd8xJaGrqGO67CvQX8ogsVkxGBQWE1GvMHwEY5SjFaj+T0wHIny9/eq+MFTa/lkZzv/+nAHV/ztIyqbvUMdmhgDkpoQKaXMxJKh/2itn4g3Nyil8uL35wGN8fYaoKjP4YVAbTLjE8NbfUcPf3pja7+27kCY9XX7y6tHhp5gBIsp9ufnsBrpDkhCJMSudj//eK+qX1u7L8Sm+pH/Ny+Gv2SuMlPA34ENWuvf9LnrGeDq+O9XA0/3ab9UKWVVSpUCFcDSZMUnhj+lFCbjwEvUOAqGlvyhCBZj7HU4LSa6eyQhEsKgFIZBPpUMauT/zYvhL5k9RIuBzwGnKKVWxn/OBu4ATldKbQFOj99Ga70OeARYD7wIfFVrHUlifGKYy02x8e0zJvRry3BaRsV8gt1DZgB2i5FOSYiEoCDVzo0nj9+rzcbkPM8QRSTGkqRNqtZav8vg84IATt3HMbcDtycrJjHyXDCzgFyPjRfW1lOe5eT0KTmUZjqHOqzD5g9GMMd7iBxmGTITAsBgUFy+oJiyTBcvr69nYq6H06dkU5TuGOrQxBhwVFaZCXGoUhxmzpiayxlTc4c6lCOqbw+RzWKUITMh4tKdVs6ekcfZM/KGOhQxxsjWHUIMAX8wgiU+P8puNtIdkFpEQggxlCQhEmII+IJhrKY9CVGX9BAJIcSQkoRIiCEQGzKL/fnZzAaZQySEEENMEiIhhoA/GOntIbJJD5EQQgw5SYiEGAJ9e4jsFiOdsp+ZEEIMKUmIhBgCPcEo1vgqM4fZJD1EQggxxGTZvRgTvMEwtW1+rCYDRekO1BBXvg2E99QhslsMdMkqM5Fk3T0hajt6sJuNUtdHiEFIQiRGvcqmbn767Hpe39SEw2Lk5iUTuWhOES7b0F3+wUgUs3HPHCJvjxRlF8mzpaGL/3lqLR9VtuK2mvjheVM4b2YeNrN8BAixmwyZiVEtFIlyzzuVvL6pCQBfMMKPnlnP6pr2IY0rGI5i2t1DZDbSLbvdiyTpCUX41Uub+KiyFYCuQJjvPraadbWyYaoQfUlCJEa1Vm+Q59bUDWjf1NA1BNHs0beHyG424pVl9yJJmrsDvLKhYUB7ZbN3CKIRYviShEiMai6riUm57gHteSm2IYhmj1BEYzLEeohsFkmIRPI4rSbKswbu/5fhsg5BNEIMX5IQiVHNaTVx85JJOCzG3rZjyzOYWZQ6dEERG8oz9e0hCkbQWg9pTGJ0SnNY+OkF03rrXgEsmZbDtHzZQV6IvmRGnRj15pSk8d8bj2NbUzcOq5FJOR4y3UP77TgYjvauMjMbDRgUBMJRbGbjAY4U4uAtLMvgvzceR2VzNx67mQm5bjKc0kMkRF+SEIkxoTzbRXm2a6jD6BWKRDEb9nxjd1hMeANhSYhEUiilmJDrZsIgw8dCiBgZMhPiKAtHogAYDHtqIdktRtnPTAghhpAkROKI6fAFqW33E4p/4IvBhSK6d4XZbnazJERC7I+3J0xtux9/UGp2ieSQITNx2CJRzQfbmvnJs+vZ2ernU3MKuOGEMkoyBq5sEbvnD/VPiBwWI92yfYcQg1pT087PX9jAiup2Fpdn8N0lk5icJ5PCxZElCZE4bBvqOrnmvmWEo7FVUg98tIOeYIRfXDS9d78usUcgsmfbjt1sZiNeKc4oxAC72vxc+49lNHcHAXh9UxPbW7w8dsOxQ744QowuMmQmDtvWxu7eZGi3p1buoqEjMEQRDW+xKtX9//RsZoNs8CrEIKpavL3JUG9bs4/qVt8QRSRGK0mIxGFzD7InWIbLis0il9dgguEolr16iGQOkRCDc1kHvr8YFDit0vssjiz5xBIHpabNx6sbGnh1fT074t/QpuZ7mFOc2u9xt503lWz30FaDHq5CET1ID5HMIRJiMOXZLq5cWNyv7caTx1N6BOcotnmDfLCtmefX1LG+tqN3JagYW2QOkUjY1sYurrl3KTXtPQBke6z867r5TMz18IfL57B2Vwdt3iAVOW6mShXcfRpsUrXNbJQhMyEG4bKa+NbpEzhjSg672nsoTrczrSAF6xGq2dXmDfKz5zbw+IoaAIwGxV+vnMtpU3KOyPnFyCEJkUjYC2vqe5MhgMbOAE98sotbz/KQn2onP9U+hNGNHMFIpHcfs90cFiOdPaEhikiI4S3daeWECdlJOfeGus7eZAhiq2a//+QaphemkOORXu6xJGlDZkqpe5VSjUqptX3ablNK7VJKrYz/nN3nvluVUluVUpuUUmcmKy5x6Nbs6hjQtnJHO9Go7MF1MAJ9tu3YzW6WhEiIodDiDQ5oa+wKSI/tGJTMOUT/AJYM0v5brfWs+M/zAEqpKcClwNT4MX9SSsmMuWHmrGm5A9ounJ3fr+KyOLDB5hDZpQ6REEOiNNPJ3m9h88elk+uRJf1jTUIJkVKqXClljf9+klLqJqVU6v6O0Vq/DbQmGMcFwENa64DWuhLYCsxP8FhxlBxXkcmXTyrDbFSYDIrrFo/j5InJ6cYezYLh/vuYQWwvs05JiIQ46ibmuvnjFXPIcFoAmFuSxk8vnIrLZh7iyMTRlugcoseBeUqp8cDfgWeAB4Cz93vU4G5USl0FfAx8W2vdBhQAH/Z5TE28bQCl1PXA9QDFxcWDPUQkSZbbxrdPn8gl84rRQGGafcDk4LHgcK/BYDiKcbBl95IQiQTIe+CRZTYaOGtaHrOKUunuCZObYsMtydCYlOinWVRrHQY+BfxOa/1NIO8Qnu/PQDkwC6gDfh1vH2zMZdCJKVrru7XW87TW87Kysg4hBHE4TEYD4zKdlGY6x2QyBId/DQYjEcyDTKqWOkQiEfIemBx5KXYqctySDI1hiX6ihZRSlwFXA8/G2w76qtFaN2itI1rrKHAPe4bFaoCiPg8tBGoP9vxCjASDVaqW3e6FEGJoJZoQXQssAm7XWlcqpUqBfx/skyml+vYqfQrYvQLtGeBSpZQ1fu4KYOnBnl+IkSAY0YMuu/dKQiSEEEMmoTlEWuv1wE19blcCd+zvGKXUg8BJQKZSqgb4EXCSUmoWseGwKuCG+PnWKaUeAdYDYeCrWuvIQb4WIUaEYDiKca+EyGI0EI5oQpGBRRuFEEIk334TIqXUGvYxlwdAaz1jP/ddNkjz3/fz+NuB2/cXjxCjQTAcHdBDpJTCaY1Vq06Pr3YRQghx9Byoh+jc+L9fjf/7r/i/VwCy1bAQhyAUGTiHCMBpNdHpD0lCJIQQQ2C/CZHWuhpAKbVYa724z123KKXeA36SzOCEGI0G6yGC2J5NUq1aCCGGRqKTFZxKqeN231BKHQscua2GhRhD9pUQOSxGOvySEAkhxFBItDDjdcB9SqkUYnOKOuJtQoiDFIxE9jNkJivNhBBiKBwwIYrvKXai1nqmUsoDKK31wF0+hRAJCYY1VtPAhEh6iIQQYugccMgsvvz9gvjvnZIMCXF4gvuYVG03S0IkhBBDJdEhs/eUUn8AHga8uxu11iuSEpUQo1hoX3OIrCY6/MEhiEgIIUSiCdGx8X/7rirTwClHNhwhRr9YD9HAhMhpMdLukx4iIYQYColWqj452YEIMVaEIlFMhsEnVdd19AxBREIIIRJadq+USlFK/UYp9XH859fxFWdCiIMU2Oeye5PMIRJCiCGSaB2ie4Eu4OL4TydwX7KCEmI0C+1jyMxlNcmQmRBCDJFE5xCVa60v6nP7x0qplUmIRySBNximuydMusOCeZDl3uLoCkX0oKvM3DYT7dJDJEYRbzBMtz9MussimxaLYS/RhMivlDpOa/0uxLbyAPzJC0scKat2tnPnS5tYvauD06fk8OUTyyjPdg91WGPavlaZuWSVmRhFPtnRxq9e2sS62k6WTMvlhhPKKMtyDXVYQuxTognRl4H74/OGFNAKXJ20qMQh6+oJxTcItdLY1cPn7v2ot/rxY8trqG7x8fer5+Gxm4c40rErNql68K07ekJRguEoFunJEyNYZVM3V/19KV2B2HvPw8t2sqvNz18+NweX9dDee7oDITp8IdKcFhyWRD+6hEjcfq8qpdTvgPeA9/tUqkZr3XkUYhMHacWONm5/dgNrdnVw4oQsrl08Dl8g0u8xy6paqWnzMcUuc+KHyr4KMyql8NhMtPuDZLttQxCZEEfGtiZvbzK027tbm6lp9TMp7+ATotU17dz+3AY+2dHOovIMbjlrEpPzPEcqXCGAA/cQbQU+BfxKKQXwPrEije8Dq7TW0STHJxJU3eLlmvuW9vYGvbKhgZ1tXr5z5kS6esLsaPHy0roGxmU4aPEG+dmz67GaDJw+NZeZhSnE//+KoyAU0YP2EAG4bWbafSFJiMSI0tTVw4fbW3l3SxPTC1OZkONCKdB6z2NsZgM2s/Ggz13T5uPa+5bR4o0NJ7+1uYmqFi+PfWkRWXv9nWitqW2PzebIT7XL+5o4KPtNiLTWfwD+AKCUygMWEyvS+C0gC5AUfZiobPYO2Bh0Y303JoPij29sZWKOm1vPnkSex8pV9y7tfaO6551KHrlhEbOKU49+0GPUvobMIDaxutUr84jEyBEMR/jzm9u4970qAB7+uIbp+SncfOZE7nhxU+/jvnPGRIrTHQd9/uoWX28y1LdtR6u/X0LU4g3w8LKd/OH1rWgNXz25nEvnF5Ppsh7aCxMjhlLqGmCe1vpGpdSFwGat9fqDPc8BJyqomBnE9jO7ADgR2AL8+mCfTCSP2zYwt7UYDb2rljY1dPG7V7fQ2B3s960tGInywrq6oxWmYPey+8H/9GJL7yUhEiNHdYuPf7xf1a9tTW0HE3M9/PXKOfzw3Cn85wsLuGReEYZ9fBHYH5d14Hub0aBwWvv3Nr23pYVfvrgJXzCCPxThzpc3886W5oN+PnH0xPOLIz1h8kJgyqEcuN9AlFKvAB8CXwUCwM+11nO11ku01j8+lCcUyVGR7eaiOYX92q5cWMwLa+p7b3f4QwRCA0c5fXuN9Yvkii27H/yDwWU10Sa1iMQIoOPfrCJaE9UD7zcoOHNaHtcdV8ri8Zm4D3Ehx/gcF1cvKunXduPJ4ynLdPZre2rlrgHHPrGi5pCeUySPUmqcUmqDUupPwArg/ymllimlViulfhx/jFMp9ZxSapVSaq1S6pJ4e5VSKjP++zyl1Jt7nftY4Hxi03xWKqXKDya2A80h2g7MBCqAFqBZKdWktZa0e5jx2M3cevYkzpuZR227n3SnhX99UM22pu5+jyvPdg449pwZ+UcrTMH+h8xcVhkyE8Nbhz/I+9taePCjHeSn2vncwmLOnpbL82v3fPnKS7Ex/giV93BaTHz9tApOnZxDbYefojQH0ws8WEz9e4gm5bp5fWNjvzaZeD1sTQSuBZ4CPgPMJ7aC/Rml1AnEpuTUaq3PgdhuGYmcVGv9vlLqGeBZrfVjBxvUgeYQ3RAPxgMsJDZ/6KtKqSxgrdZalt4PI5kuK8dXZPHbVzZx33tVnDAhi/e2tfTe/8XjS5lVmMrdn5vL39+txGo28MXjy5gj84eOqnBED7qXGcQS26Yu2c9MDF+vrG/gO4+u7r395Ce7ePiGhUwrSOG5NXUcMy6dy+YXUZBmP2LPme60csKErP0+5ryZ+Ty0bGfvF4o0h5lPzZYve8NUtdb6Q6XUncAZwCfxdhexDph3gDuVUv9LLLl552gElWgxhwDgI1aMMQAUApZkBSUO3a42H/e8U0kgHCXVYeY7Z0ykJxxhSp6bxeVZpDjMnDE1l5Mmxt5c9v6WJZJLa73fHiKP3UxVs/coRyVEYtp9QX7/+tZ+bYFwlDU1nXzl5PFce1wpVqPhkOYKHa7JeR4e//KxbKjrRAOTc91SCHL42v0mp4BfaK3/uvcDlFJzgbOBXyilXtZa/wQIs2eqzxFfinugOkS/JdYrNIFYBvc+8Ffgaq11+5EORhw+pRS7V5ouq2pjWVUbAL+5eCYvra8nL8XGtPwU0pySzw6FSFRjUGqfHxgem4nm7sBRjkqIxCjAMOhSds3SyhaqWnxku61MK0gZktVdpZlOSjMHTgsQw9ZLwE+VUv/RWncrpQqAELHcpFVr/W+lVDdwTfzxVcBc4AXgokHOB7F9Vw9pvPZAs7sriU2oztRan6K1/h+t9fOJJENKqXuVUo1KqbV92tKVUq8opbbE/03rc9+tSqmtSqlNSqkzD+XFCChItfPlk/rPI8tyW9nc0MX3HlvN5/6+lN+9uhmvTKQeEsF9bOy6W4rdPGCJsRDDRYrDwtdPrejX5rAYyfHYuPivH/K9x1ZzzX3L+Nmz62W1pDggrfXLwAPAB0qpNcBjxJKZ6cDS+J6pPwB+Fj/kx8BdSql3gMjAMwLwEPBdpdQnR3RStdb6/wCUUq8Bp/a9Tyn1mtb61EEPjPkHsRpG/+zTdgvwmtb6DqXULfHbNyulpgCXAlOBfOBVpdQErfW+XrDYB4NBccWCEkoznDy7uo4JuS5sJiP3vVfFeTPyiGjNIx/X8Om5hcwsTB3qcMecUHjfK8wgNmQmk6rFcNPlDxHVmhSHhdMmZ/P3q+fxxIpd5KXYOGNKDl978JN+j39qZS2XLyhmfmnGEEUshiutdRUwrc/tu4C79nrYNmK9R3sf+w6xEau92/9BLOdAa/0eh7js/kBDZjbAAWTGe3N2v5N7iCUu+6S1flspNW6v5guAk+K/3w+8Cdwcb39Iax0AKpVSW4nNOv8g0Rci9sh0WTl/VgHnzypgdU1sc9crF5bw31W1GA2KG08ZTyAkueZQCEaiWPaz67fbZqLDHyIS1RiHYB6GEH35gmHe3tzMXa9upicc5csnlnPG1BxOnRz7AVi3q4OGrgBKxXo4u3rCRKKarh7phRYjy4EmVd8AfINY8rOcPQlRJ/DHQ3i+HK11HYDWuk4plR1vLyBW72i3mnib2Mv62g6WVbURiWqOGZdGQaoNjSJjH+P1eSk2FpVn8L99Ksb+6qVN/O2qeUcrZNFHbEL1vhMik8GA02qk3Rfc5/9TIY6WFdVtfOnfy3tvf+/x1djMszhvZj5NXQEsJgOFaXauObaEDJeVhs4AmS4Lbd6gzOURI86BhszuIjZe9zWt9e+TGMfgs/QGe6BS1wPXAxQXFycxpOFndU07l/z1Q/zx3h2rycD/nDOZP7+5ja+dOp6zpuWR6ug/WTrdaeWtzU0DzvX82jpOm5JzVOIebQ7nGgwdYA4RQKrdQnO3JERicEfzPbBvbaHd7v+gimA4wi9e2ES608KPz5+K22bm1y9v7n3M4vIMUg6xEKMQQyWhktla698rpY5VSl2ulLpq988hPF9DfE+03Xuj7a6iVQMU9XlcIVC7j1ju1lrP01rPy8raf12K0ea/q+p6kyGILXd9f1tLrCjjE2t5v0/Nod0MCnI8A1cn5sjmoYfscK7BhBIih5mmLllpJgZ3NN8DswZJyjOcVv790U5avEG2NHbz3rYW/vLWtn6PeW9bC5sbugccK8RwllBCpJT6F3AncBxwTPznUMZcngF2F3O8Gni6T/ulSimrUqqUWGGmpYdw/lGtsU/BvsI0O988rYJZRalcNr+Y6QUpPLxsx4BjlFJctaik37wVh8XIWdNzj0rMor9AeP9DZgCpdjNN3VKcUQy906fk9NtLzGxUnDQhiwWl6dx06ni+eVoF4zIchCIDO/R7ZJ6iGGESLcw4D5iitR50GGswSqkHiU2gzlRK1QA/Au4AHlFKfR7YAXwWQGu9Tin1CLCeWOGlr471FWaBUIRPdrbz4tp63DYTp0/J4cJZBTy9spYsl5UrFhTzm1c2974RXbt4HBnOwbuo5xSn8fiXF7G0qhWTwcAx49KYkp9QJXRxhAXDUcwH6CGKVauWHiIx9KYVpPDolxaxrKqVYDjKnOI0Kpu7eXR5Te9qyOMrMvn2GRP6DZmlOcyUZ8kcIjGyJJoQrQVygYS3RddaX7aPuwZdqq+1vh24PdHzjwaRqGZzQxc7WnykuyxMzHXjscWSmg8rW7j63mW9j7377e089uVF/OGy2VS3ePnzm9v6fSu7770q/vOF+YM+j1KK6YWpTJdl9kMulhDtv4coxW6moVMSIjE8TM7z9O4J1hOK8Mc3tvYrDfHOlmbOnZHHp2YX8P62ZibmuDl7eh5Gg2J5dSvNXUGK0h1MyHFhGuTa31DXyca6TswmA1PyPFJdWhwRSqklxJbzG4G/aa3vONAxiSZEmcB6pdRSYlt3AKC1Pv9QAhUxb2xq5Ev/Wk44vlX01YvG8a0zKrCZjPzlze39HhsIR3ljYxNLpuZgMxvoHGRJqzcwpjvVRoTgfrbt2C3FbmZHq+8oRSRE4jr9IVbXdAxoX1/Xxfambk6oyKKqxcvTq2rZ1NDFfe9VAWA0KP5w+WzOmpbX77hlVa18+d/Lae6OJVgTsl38+pKZTC9ITfZLEaOYUspIbCX86cTmKC9TSj2jtV6/v+MSTYhuO7zwxN7qO/zc+via3mQIYqs3zpmRx4zCFPyhMEaDYmZhKoFwhHW1nfSEIrT6grT7Q+R6bNR37plnYjIonJZE/3eKoRKbVH2AOUQOCx9Xtx2liIRIjNYapWBBWTrPru4/WJDlsrKqpoNV8WTpW6dP4Dev7BlCi0Q1tz6xhhkFqb2bvobCUR74qLo3GQLY3NjNe1tbJCEaY8bd8tzlwM+BYmLTab5fdcc5DxzGKecDW7XW2wGUUg8Rq3d4+AmR1vqtwwhMDKLTH6ZpkD2rmrsD2MxGvn5qBZvqu3lvWzOZLgufnlPAnOI0wpEoNW1+bjixjL++tZ36zh48NhNfPqmcdr9UOB7uEplDlCpziMQwEYpEWVHdxr8+rMYfjHDFwhJOmZRNTZuflTvbMRkUVy4sIRju3zutB6ma0u4L0eEP9SZE3mCIDXVdAx63pWFgmxi94snQPcSKQAOUAPeMu+U5DiMpKgB29rldAyw40EEJJURKqS721AWyAGbAq7X2HGSQIi7HY2Vavoe1tZ29bQYFJemxa6InFOWOFzf23vfaxkYeuX4hxekOXlnfwKqadk6bkkOqw0wgFOXed6v46+fmHvXXIQ5OIqvM0pwWSYjEsLBqZzuX3fMhuzuyX9vYyB8vn824DAcnTMhEa9ja0M3F8yqwW0w8u7qWBaXpHFuewf+9tpVInx7w8iwneSl7yn2kOqycMimbjfX9E6AFZbLdxxjzc/YkQ7s54u2HmhAlXNuwr0R7iPrtHKuUupBYl5Q4RCkOC//7mRl8+5FVbKzvItVh5mcXTKMix01PKMILa+u48ZTxGBRUNnl5bk0db25u4ttnTOT8Wfms2dXJAx/tYM2uDlxWE//v3MlMzj+kDX7FURQMH7gOkdNiJBiJ4guGccgwqBhCL6ytJ7rXx8gDH+3kpxdOZc2uDhwWI5cdU0x+mp0p+R6uXTwOq8lAJKr58xVzuOWJNbR6g4zPdvLbi2fhsprY0tBFIBylON3BeTPy2N7czUvrGmK9TQtKWDAufdBYatp8tHqDZLmt5KXYj8KrF0fJvqqLHk7V0YRrG/Z1SO+2Wuun4puzisPgtpm5YFY+pwUj+IMRtjZ1U1jXgT8YJttt469vxVaSTSvw8O0zJtLVE6Klu4dQRGNQ8MXjSylMc5DpslKcsXeCLYajRCZVK6XIcFpo6AxQmikJkRg6g12qRiOEo5pwRBOKaMJ9qrHYzEYAolpjNxv47hkT6QqESXOYAc3vXtvMX9/aTjiqWVCazi8+PZ1fXjSdLx5fjskAk3LdWM39r3mtNa9vbOTbj66i3Rciy2Xlrktncez4zGS+dHH07CA2TDZY+6FaBlTE6xruIrZ5/OUHOijRIbNP97lpIFaXKOGaRGJwL6+rp74zgNtmwmY2Up7l5M1NTRSnOwhHNRajgVAkwtpdneSl2DlnWi5vb27mW4+uYvd70OziVP50+ZyhfSEiYYksuwdId1po6OyR/aDEkDppYjb3vVfVb/HHpccUc97v30VrCEejlGQ4uf+6YzAZDNR19JDmMBMMR7nnnUre3tLce9zNSyby9Mra3nN9VNnK/R9U8cNzpzK3ZN/b1FQ2e/nqAyvoCUUBaOoO8JUHVvDs146jME2+CI4C36f/HCIAX7z9kGitw0qpG4GXiC27v1drve5AxyX69fO8Pr+HgSpiM7bFIeoJRSjLdLK2toOtDV2cNS2Xxq4Af35zG4FwlCy3le+cOZH/fXEjPaEoH21vYcm0XH790ib6lsf8ZEc762o7MBoUq2o6qGnzUZ7lYmZhKikO2UtouAmGowntYp/miCVEQgyl7p4Q//uZ6TR3BYlqyHBaiESifP3UCrp6wphNsWt5S30X3308NjxmMxv4n3OmsKu9//X7+9e38rmFJfz17T0lRV5e18BNp1Tsd9++Xe3+3mRot3ZfiPqOHkmIRoGqO855YNwtz8GRXWWG1vp54PmDOSbROUTXHlJEYlANnX6eWLGLf3+4gyy3hUuOKSYQivDTZzf0PqapK8A/3q/ivBn5PLq8hom5bnpCYRoGmWyrlOKnz67nv32Wwn7ztAq+cvL4hHojxNGTaEIUK84oCZEYWm3+EK3dQZ5auYtgOMqFswooy3Jy58ubeucW5afYMBsNvcUae0JRfvj0Wr5+2gR+22fpvS8YwWLq/340uzgVl23/H0NZLisGRb+5TDazgXSnZd8HiRElnvwcVgJ0JCS6l1mhUupJpVSjUqpBKfW4Uqow2cGNVo8v38X/vriJXe1+Vu7s4H+eWjvoh2R1i4+cFBupDjNnT8+j3Rfm7Gn99yAzGhRGpfolQxD7NlbV7E3q6xAHLxQ58CoziG3wWtvuPwoRCbFvWmt++dImNjd0U9XiY31dJ/e8s71fclLb0UNgr3ISUQ2RaP9enVlFKRSm7pkMnemy8NWTx2M1GfcbQ1mWk9vOn4qKn95oUPziU9MZlyHDyeLISnTI7D5i2dtn47evjLednoygRrPGzh7ufa+yX1skqvHYY8NbWS4r4WiUNl+IvBQbi8szmFucxqaGLuo7/Xz++FJcNjNPrKihMM3O/zt3yqDrC8NRjV82Vxx2ehKoQwSxHcU31A+sCCzE0bSiur3f7RSHubdSdY7Hij8YobMnTCAUxWY2ku020+IN0BOKMr0ghR+eO4U2X5Bsl5WwjjIl38PD1y+kJxShPNuV0JCXxWTkknlFzC1Jo6Gjh/xUO+XZLgwJ9LQKcTASTYiytNb39bn9D6XUN5IQz6jR6Q/R2RMiw2nFbtnzDchqMpDqsPRWZ51bksYx49JId5r53SWzWFrZisVkoDDNxvSCFNbVddHQ0cOi8gwunldIutPK1PwUbjxlPA6zkTSnhZ2tPtKdln77C80o9FCcLuPrw00wHEloGDPDZaG2XYbMxJETCkdp7OrBbjGS7tz3nJ2+cjz9H/fulmauWzyOKLC9yYvbZiLFbmZavgeP3URls5e8FDuTc91UNnWzqqaTonQ7L69v4KRJWXhspkPaU9FqNjI1P4Wpsim1SKJEE6JmpdSVwIPx25cBLckJaeRbUd3Gj59dx7pdnZw4IYvvLZnIxNxYDUuP3cxt503hw8pWphek8OLaetbWtDOtIIVvPbKytyvabjbyrTMmcPdb23HbTNz9znb+ePkczp6eh9looKBP13NRuoP7rz2GO1/ezCc72zh1YjZfOWU8qQ4ZYx9uAuFo79Lk/clwWqjvkIRIHBm7N4R+YsUu8tNs/OjcqSwsS6eqxUdtu5/cFBvjs1wEw1G2NHbR7g8zLsPBnOI0XFYT3YHY3ondgRA5KTa+/tDK3nOnOszc8anp/OH1rRSlO3hlXQMVOS6uP6GMl9c3sLWxq7cnyHKA4TGIDdNtb/JS3eojzWGmItuFyyYLRETyJZoQXQf8AfgtseX27wMy0XoQVc1err53KV3xN5DXNjZS2+HngS8sJM1p4d2tzXzh/o85aWI2uR4bHrsJg7LT1BVgYVkG72+L5ZkGFRs+O3tGHi3dAT47r5Dn19RybHnGoInO9MJU/nzlHDp7QqQ5LAcclxdDIxCO4rYe+M09zWGhwx8iGI4OmIgqxMEIhaP88Y2tPPJxDQBVzT5ue2Yd159Yxv97ai1RDUrBT86fSnNXgLte3wrEvpT970XT+ebpFfiCEcIRzeQ8d789yiC24quzJ8SXTixnY30Xp0zKxqhiiz1mF6ezs83HpFw3TV09dPpD5KXuv6ji+9ta+Pz9y3pXll177Di+cdoEWTUrki7RhOinwNVa6zYApVQ6cCexREn0UdXi7U2GdttQ10VNm4+ecIQNdZ184fgy5o9L45uPrOod5np8xS6+dsp4NtZ30eoN8sUTyvjRM+vo8IcAeHZ1Hd85YwLhSHTAc+7msJiksvEwl0ilagCDQfXWIiqSoU9xGBq7enhixa5+befNyucn/13f2yOtNfz4v+v5ysnlvY/xhyK8v62ZReWZ7Gz1YzSAyWDoV5MIYEZhCsur23g4nnAB3HTqeH79cmwyNsCLa+v57NxCwnrf718Q28vx1idW91tmf9/7VZw5LZeFsqWHOAhKqXuBc4FGrfW0RI5J9KvnjN3JEIDWuhWYffAhjn6DLSG1mgy4bCZeWd/Az5/fyB/f2MonO9v7zfkBeGjZTs6alovRoAhHdW8ytNvDH+/EkMAKJTF8BRPYy2y3LLeVmjZZaSYOj81sJMdjG9AeCPdPTsJRTd/vW0aD4viKLO56dQt3vryJ37yymVufXMP3zpzY77iTJmbx6PKafm0GpXqTod2e/GQX+/k+B8TmXu5oHXjNSwkKcQj+ASw5mAMS/XQ1KKXSdt+I9xBJV8QgJmS7+czc/hUJvnPGRMIRzc+e3UB5lpMFpYPv1RMMR8lLsTG3OI20QYbFguEo0b03FhIjSjCS2CoziCVEO9t8SY5IjHYZLmu/ZesAHpsJj73/W7jDYkT3qfo6vSCFDfVdbG/2Mr0ghTnFqbR6g7y+sZHfXzqLiTluTqjIZP649AH7nelB3qYiWmMz7/8jJ9NlZXZR6oD2EuklHd1uS7mc21KquC0lGv/3gNtsHIjW+m2g9WCOSTSp+TXwvlLqMWJziC4Gbj+48MYGj93MrWdN4uK5hXQFwjitJibnuNnU2MW3z5jAutpOGjp7qMh2YTcb+y2N/8zcQho6/Fw2v4gstxWrydDvW9xXThpPpjux1SFieIoNmSX2PSTTZaW6RWpJicN34oQsnvzysWxt7MbjMDOjIIWKbBffe2wNTd0BMpwW7rhoOh3+EDazgZ5QlJJ0O95AiP85ZzIfbG8hGI7y3TMnsrGuk+MnZDEp34PFoMh021gyNYcX1zX0Pp8CctzWfoVkL5iZf8CVrx67mZ99aho3PfgJ25q82M1GfnTeFCbleZL1n0YMtVjy03frjhLgHm5Lgds6jmqxxkQrVf9TKfUxcAqxa/3TWuv1SY1shKls9rKhrhMNlGY4eHJlLQ8v24FSiisWFHP29Dz+8PrW3vlFWxq7+eVnZvDy+np2tPhYMi2XDKeFyhYvKXYzNz++mpuXTOL9bf+fvbsOj/O4Gj78m2cZxMxkWWamxA7HoYY5adI0SZumSSlt8zZtv77t2zZlbkpJk4bTBhpmZjOzbIuZl3m+P3a1liyZJNmSpbmvS5e1jxZm5Ue7Z2fOnNNOhyvAFQsKOGdG1ug+SWXYAodZhwggM8FEdbuaIVKGz6jXmFOYwpzC6ER/jyfAYytq+cysHOxmPR5/iIc/qeFnl8zggRsW4PKHyEuyUN/t48uPrY3PAH1Y2c5vrpjFD57bzIubmjHpNb56+iTuPLuCWQXJvLK5iQVFqZw3M5tzZmbzn9V1rK7u5MLZuZw3Mwez4dBvOdNzk3jqSyfQ0O0lwWygKM2KEKrm0Dj2M/r3MSN2+Wcc4+rVh73sFQuAVBA0iO1NDj77z5V0ugMkmPRct6SIJ1bFGvVKycOf1lCaYeuXbN3pDvC9/27m+5+ZwplTsmh3+3EHwpxQmsbjK2pp6Pbx45e2MSs/iWSLgVan97Brhyhj1+E2dwXISjTzYZ/mmIoyUva2u3lrR+uA42/vaOVHL0Zf5i+clU2CxThgOeyZdQ3x1t7+UITfvLGLyVkJ3HbqJG5aWoJJr8UDmP89f9phl5roK9VuIvUg/c2UcaXwCI8fNSoPaAS8sLExniA9JSeBdbXx/HMSLXpuO3Xw8vSaJqjv8nLPu3sA+PoZ5TzyaQ093n2BU29V2DmFyUfxGSjHSiAcQX+YFXYzE0zUdqoZImXkaQeYcUm2Gvnm8skEwhFK0qxsqOse9Hpmg8Y5M7Jx+oJ8uqeDbY0Olk/Lwh8Ko9NEfBZUCHFYwZDbH0TTNCxHGDgp40It0WWywY4fU2rL0gjY0eSMf1/f5aUiyx5PYPzJRTOi5e29QVL2q6Nx6yml8STDvGQLLn+I93a1cdOy4n7XM+o0Tp+SeVSfg3JsHMkMUZLFQERK2l0DG/oqynAUpFo4uTy937FvLZ/Mw59W8/u3dnHfB3v51lObOKk8Y0AAf/m8PKblJFLb4SYckXz/M1NZWJzCr17fyZV//5TvPL2JrY2H13am2xPgufUNXPH3T/nc/St5b2crftVyaKL5HrD/Jz9P7PiQCSGeAD4FKoQQ9UKImw91GzVDNAzeYIjtjQ6WT8vk3Z2tzM5P4ryZOUSk5FvLJ6PTBFVtbv74diVWo47bT5tEfZeHLneAM6dm8c7OVkJhyc8vnUmLw8c97+xmVn4SC4pTefTmRfx3fQOJZgMXzcll9hDK3StjTyB8eHWIIPrpujDVyq4WJ+lq+UAZQc09Pkoz7EzNSWRns5PyrASyEs3Myk/m5MkZeAJhki0GXt3UyP03LODFTU34gmEumZuH0xfEZtJz8uQMjHqNTleATnsAm1HPSZMzSDAbeHJ1HTct01N0iAas7+9q4xv/2RC//Pl/rebfX1zCkjJVc2jC+FHP4/woCaI5Q4VEZ4a+N9yEainlNUd6GxUQDcOqvZ08vKKGs6ZmcftpZZj0On7+6o74z6fnJsY/hXkCYX79+k5yksx8YVkpek1wSnkGP3t1BxfOyaW5R/KjC6ezuDiVdLuJZeUZLCvPGK2nphwlRzJDBNGZw8oWFyeWpR/6yopyEJUtTqrb3SRYDBg0ePCTahJMeorSraxb08WvL5vNir0d7GjeN+N9x/LJmPQaOiFIshhIseip6/Lymzd2xnOLcpLM/L/PTOUv7+6O75o9oSyN2g4PvmCYTneA3GTLgODIFwwPaHQN8Nb2FhUQTTTR4OeYJlAPZlQCIiFENeAEwkBISrkgVtvoP0AxUA1c2bcY5FjhCYTYUNfNqqpOilKtvL29lfJMO1aDjgc/qe533a2NDi6YndPvWFOPjx5fgLAMM78wlW8un8z3n91CjzeIThN899wp5KVaVMXpccoXDB9RK47cZAvbmhxHcUTKRLBybztfeWIDbU4/QsAXlpVw8ZxcntvQyJaG6PnlDoTY0+bi7OnZZCeZ+XRPOw99Us30nET+s6YOgAtm5fDUmrp+idZNPT6aenz0XVn7dE8H1y0u5MYHVxOKSBLNev5x/XxO6BPYawKSLQPbcSQNckxRjoXRzCE6TUo5R0q5IHb5LuBtKWU58Hbs8pjz+tZmrr1vJX94q5KqDjeXz8/HZtQzpzB5QGVpANt+gc0V8/OpyErEH5S8X9mGlJKMWG2hcETy05e3s6vPJzRlfPGHIhiPYIaoLMPGhtruozcgZdxrd/r4xWs7aYvVBJIS7vuwijOmZrG4JBWjTmN+UQoI+O65U6nr9PDs+nqm5SRx9cICrCYdv71iNr++fBYGnUaPZ+DrnMsXYv9ajL5gJN7mw+ELccd/NvarOG3U6/jSyWX9AimrUcdpKl9SGSVjaRriIuDU2PcPAe8B3xmtwQym1enj6TX1fOW0MjLsJipyEvnZy9t5em09cwqSOWdGNi9vaopf36jTCEck914/n3d3trKgKIVn1zdy++PrgGhi49ULC7lsXh6/fG1n/HaNPT7mHOsnpxx1UsojbtZanGajptONyx/CbhpLf67K8aLF6Wf9IEH1rhYnJr3G55cWs6vFSYJJz11PbyYQ66/x3IYGfnzRdH73xi7W1EQn68vSbXzvvCnc9vj6+P0IAZmJJjyBfcnQiRY9ne4A58/KoSDFyvq6Llbs7aTD5e/XRmRRSSpP3XoCH1W2YzHqWDopnem5SUfpN6EoBzdaM0QSeEMIsVYIcUvsWJaUsgkg9u+gHxOEELcIIdYIIda0tbUdo+FGdbsDLChOITvJTH6SkS63j1MqMvjeeVOYlpNAYYqFaxcVkGI1MDs/iT9cPZuwlHS7fJw0KY1uT5CPdu+rK1PX6WVnsxOdEJj6vEnmHqIbtDK6hnoO+mP5Qwfa8jwYvU6jNN3O+toxt3qsjJIjPf9sBh3zC5PRaYKyDDtptmhboIJUC05fgFn5ifiDYXY1O+PBEIDdpKex2xsPhgD2tLtZVd3JHcvLybCbmJRp565zplCYauGiObkkWQycUJrK76+cg8Wo0dzj452drVgNOv73/GnYTXpW7O3gvZ2t1HV60Os05hel8vUzJ3PLyWUqGFJG1Wh95FwqpWwUQmQCbwohdhzyFjFSynuBewEWLFhwzBp7bW3o4dn1DVRkJ9Du9DEp3cKmqm4Wl6TiD4bpdAXIT7VyQrKFy+bls76ui3d3tFKelYg7FMEG1AxSU2Zro4PTKjIIxurTfO+8qVRk2Y/V01KGYKjn4JHmD/WanpvI29tbOUkl2Ssc+fkXkpLvnVPG6joXG+t6yEw0s7AoiYIUK+fPzuOVzc2cWpFJbrKZRLOe82flkmIz0ur0DVopfU1NF3+/uICz83LRE6K9uxlf2M41C/O5fkkhAkFlq4vmHj9zC1Oo7fQwJTuBZIue7z+3JV5sNM1m5KGbFjEjTwVBytgwKgGRlLIx9m+rEOJZYBHQIoTIkVI2CSFygIFlVEfJzmYn19y3glBE8vJ1eYQy03inysVDn9Zwz7t7uGhOLpfPy6emw8X7le1sa+zhrOnZvL2jjf+ub+S7506hut1D9iAdpxcUp2A1aNx22iTMeo1zZmRhUQnV45IvGOk3E3i45hel8Od3dvPDC6apFgbKEUvR+XmrxsEvXq+MH3tlk4mvnTGJn7y0PXp5czM/vXA6P7tkBp2eIDohKEy1EAhFeG1rM5My7Rh0gh3NTk4pz+ChtR08sKqFBLOe/7csgbKMCD95fTfrarspSrPy/fOm8sbWZt7ZGZ3Bent7C989byrZiWbuOLOcsJSEI/DAx3v5+aWzBi1cqyjH2jF/5xVC2ABNSumMfX8W8GPgBeAG4Bexf58/1mM7kKp2F587sZjrCruRlS+xufjz/bbX/3ddA6lWI7PyEylKtaAJwW9e38nnl5bwl3d3s762mwXFKWys6+Hyefk8s74eKWFeYTJLJ6Vx+xMb4smHZ0zNIjd5lJ6oclR5g+EhBUSFqVY0Ef1kvrA49SiMTBnPOnzwtw+q+x1rc/np9ga5bF4eOckWWhw+kiwG3IEw2xodNPX4mFOQzImlqfz2ilm8u7ONQCjC9YuLSLMb+dKj0er63Z4gH7VauG/jLna2uACo6fDwtX+v53dXziY32UKyzUirw4fNqGNHs5On1tYDkGjWc+c5U3D5QpjsKiBSRt9oTEVkAc/GPunqgcellK8JIVYDT8aqSdYCV4zC2AZo6PLw+tZm6todXJ3cQ/XkL7CtZmA+xwsbGylJt0a7RKdZcAfC9G4m6m3X8NyGBn53xSwmZ9spTbfx3IZGvv7vDcjYpHdpupVM1c1+3BrqkpkQglMrMnnok2oVEClHTAodaTYDXzq5lFSbkUA4wvYmB1OyE3h2fQPPrGugKNXKudOzWVvZRU6yhYwEE3qdoMsb5DvPbI5/YHtjWwv/e/5UdJogHDuWn2rhuQ0N/R7TF4zgDYR5Y1sLrU4/s/OSmJWfzOaGfRWsHb4Q72xv4bK5ecful6EoB3HMAyIp5V5g9iDHO4AzjvV4DuX5DY08u76RH55TwtuhQp5+bSenTxmYy1GSbiXXJlndHcQYa8eRnxitp3H+rBx++eoOkiwGZhrqyZk/G6PJjDcY4f2dbTj9IQpSLfzuqjmkqYrE49ZQAyKAUysyuOM/G6jr9FCQun9jaEU5sCJdB//vvKlsqO/hmXX15CRZOH9WDj99aXs8r7Gm08NrW5tpdfp58JMaAHSa4GeXzMBs0OHq05j6re2t3LS0GItRRygsseh1WI26frvMILpbtjW21b+my0Nj98B8pJ3NTrzBMNbD2EHZ1O2lyxMg3W4ic5D0A0UZLpWschAuX5Bn10c/+aTbzezpDrK5oYevnDaJ8kw7la0upufYmZRq4LzZhcwNruHfbfkUp9v43KIcDIS459q5fFzZxillSVyX00D5yzfBrR+DrYgLZucyuyCZHk+A7CQzGQnqj3w8G+qSGYDVqOf0KZn8/f093H3JzBEemTKedWtJfLK3jX9+1FsVuov3drZy07IS/vDWvryi/BQrT66pj18ORyR/fKuSC2fnUNvuwKgTfFzl4NwZ2by9owWjDOIOwhXzsvnf07O467XG+G2vnZVInsnbbxz5KQMD+WXlGRwqK05KyUeV7XzzqY20Of3kJpn549VzWViiZkuVkaUCokH4g2GqOtzogNIMG5WtLiLhAE5fdEtqY4+Xz8zM5rrCTpI2P4ihfRuhrovxZ8/j8mk29FYTN82yEooEydx4N9Nm30ZPRzvTX/8cpJWDcd8ussJUK6hP/BOCPxjBqBt6rsTZ07P5n2c28Y0zJ8eLeSrKobT5DTyxqn/jcIcvFF+q79V3y32vZBPcUdZIUs/f0cJeGs+9mRqTgx8VbaGw8lH81iz85hsx7fgXk8+5mppgIpl6H9OaHqZLdwE/OzWRDJ2HnR4Lek1w09JiHltZiz8U4eTydGbmJRxydqi6w8OXHl0bn4Fq7PFx66NrefGry1SJEmVEqYBoPy0OH398q5InVtdyx5nlLChO5dK5udhNRspwA+ANhLk2t4X0Z68DX3RNXN+8Cd2Cm5k5/5vUOvw4/UFmPncWhLx8lHIJaZoLdAY47zdgU316JiJfMIxBP/RdYslWI0tKUnl0RQ13LJ88giNTxjOdFl3+2l+63djvckWWHSHoFyjdc1KAjOeuiR8srF9BzgX3YPj4LggHsACW6rfgtO8z760bmNf3cWdczLXvfBYCLpYn5eOYei8f7NS4aWkJBr1ga0MPM02tmGUWcOAPhQ1dngHLcR3uAI3dXhUQKSNqNFt3jEmf7ung8VW1SAlz8pOZm5+IJxChutNFms3AP66bh9WoI8VVGQ+Geon1D5MeaiEiJTZ3HSDxT7+K1T1JTCoqhFveh5KTR+eJKaPOFwofUduOwSyfls2jK2oIDvJpXlEGk2nRuO20MgBMeg1NQKrNiN2s5y/XzuVXl8/kL9fOZV1NJ3+4dHI8ULp8dgaFzW+y/1SSYeNjUHjCvgPhIJGQHwz7gpNA2lTaZQIEojvP6Kkn4dXb+HlFNYtNVUwTNXyvYCtzVtwBwYG5RX2l2kzsH8+Z9BopVuPgN1CUIVIzRPtxeIOcOTWTKdl2kix6ujzRHj3/eH8vtZ1edJrgP1fmoY8M0oBQZ8QV0rj6wc3kJJn500Xv4fP7uSavlLTshGP+XJSxxRs4srYdgylItZKVaObt7a2cMyN7hEamjGeuUIQ8u+DTz1owtm5BWtMIZM/l9YYgv3tzF05/CJtRx1dPLyffFualOavwWLLJ9n2KThv4FiH1ZkSof36QNCVTc+LPyGx4i87UOawyLmaGs38VbdFVTYJjN6d++Jt9B5d+A2zpHExZho3vnjeVu1+O1kwSAn580QxK0m1D+4UoygGogCimqcfLf9fV8+iKWu48u4JQOEKjw0+23UhtV4gL5+Sh1wRpsosZn96BKD0Bkguhe9/afOTEr7OyIRi7Px//924b3zm7gskqGFKILZkNZ4Zo73tQt5KTy67jiVW1KiBSDosnADPdK8h58TawpkLATSSlFHvFb7lhaTEAAnhyTS2LL55MQv407AEPIv803Oiwr30QQtHdYgiBnH8j4ukb9j2AOQl35hx+8L6gw1WO0aFx4excwrKz/0Bs6QTzFmKwpoHfAdMvjaYReLrAmnLA8ZsMOq5bXMji4lSaHT5yky2UZ9rRBlkGVJThUAER0V0MT6+pZ1eLk2+cMYnCVCvbGntIMOmpbHPz69d3ctPSEvyhCF3CxqbpdzJ7268xzboKgl5wNhGZfA6E/Dy6et8npy0NDtJV8qsS4wuFMeiG+CIe9sOKv4I9k8WJn/BoTQmtDp/afqwcUrpwYKt7jU9Oe5LVXVZyLBEWats5LbmFZc874hXUv3L6JPzBMP/qmkF2ooWtO7vIsJuYc/JjlHd/hC7spTrjNDa35HPyuY+RUvcWPlM6W+1LaG3NwKB1cmpFJg1dXn7x6g7+fH4xU3oHoTdRd/JvkUE7hTMujW4sqXwT2nbB0q8f8jlYjHpmFSQz66j+ppSJTgVEQKvDh9WkY3uzk9U1nXzzzAoSLQZMBh1PrqnnhhOLeXxVLW2xmhoA9533fyz/8ArQmcCWAZM/gwC8+8p1MC0nkZwklfSnRPkCYQxD3WXWvBns2VC+HPOOl1lc8j88s66eL586aWQHqYw7yboAL+fcyh2vdgMOAIpTJ/GXc5LxBVuAaOPhe97ZzeNfWITFEKK+y8O03GT0QnDtUwGyEk9Cr2k0rPQyt8BBU0kpr+y5ELc/RIfbx11nellR1cHbO6Idl4SAxLRsVp/1LDpvG8GEQrwJxSz75Cao+4T4la55EkwDZ9Cr293UdnpIthqYlGE/rDpFijJc6iwD6rq88fXpH5w/jV+8toNOdwCAc2dkYzPq+gVDAL9eE2JR+WUkbXsUSk8lbM3A8NwXWFhyP2vqINlq4CcXzyBZJf4pMZ5hFGakeQukFkNyAXg7ObnQwAOr6rj1lDLV30w5qHZp5Wef9M/5qe70s92bBLTEj51QmsazG5p4dEW0MGOiWc+PLpzO4pIUVlbtq85/9oxs3tneQm2sqKMQMD9DYjHocPvD6DTBN88oo0zfxubkqTgt5WTYTczOTUaf+luoej+6TFZ6CuQtGDDelXs7uPmhNfFikLedWsatp5SRaBkkb1NRRtCEDYhqOtzsbXOTaNGztdFBREarAb+0qSkeDE3NSSAUjgyo1wHQ7Q0TtOfCrKug8EQifgey+GQun2Jm2ZR8CnOyVEVhpR+Pf+iFGWnfBTmzQWiQWkJ5uIqITFL9zZRD8ocFDl9wwPEmN1iNOvJTLDR0eVlUksqvXt8Z/7nDF+Kv7+3hr5dPwlfTBpEwvqRJeC0JhNydVHWYSLXo+M5CPSVaCw9clEWd10CmOcL0rb8gmHYpp8/Zb5HLNg2yph1wrB0uP9/976Z+lbH/+t4eTpmcweJSVa5EObomZEC0sa6bzz2wih5vkK+fUY5JrzGvMIVL5uaxqb4HTyDE7adOYmVVJ95gmIrshH69ewBump9EetEcWLUKXvo6xqseR8y5lrIVv6Tssn+CRQVDSn8OXzBaiHMoumtg8jnR7xPzEO07OXnyZ3hiZa0KiJSDMpltXLkgn0dW7NsAYtJrzMlP5qalxexqcXHm1CzKMu0Dbru71YWh7hMmv/0FACJJRew47R98KfAEV81IwuRvJ9xqwZVzE7OeOodZfmf0htY0Ok6884jH2uMNsrd94Db8ZofviO9LUY7UhAuIPIEQv31jJz3eIPkpFuxmHXMLUthQ183PX9nO5KwEvn5GOV97YkO8cuuqqk7+fM1c/vXRHlqcQW6YbuAC91Pw34dhye1Q9R7C70R6OhBn/BAsyaP7JJUxyekLYTEOIYfI74CgD8xJ0csJudCwmmUnp/M/T2/CEwhhNU64P2XlMPX4JcunZWHS63htazO5yRa+eFIJz22INnaFaNPWZZPSOGdGNpvquslMNLO9ycGMHBvptc/G70vrqWFSw/PsrPgynrYq0JuxpuYxiRbc06/FtudlfFnz6Jx3O5VOG6cc4VjTbEZm5iWyucHR73jBIG0/FGWkTbhXUacvxJ42F3edM4WqDheLi1P5z5o6puUmkploxukN8smejn5l7Gs7Pfx7VS2/PVlH4vanSN72MrhjNTYEkDcP9rwD8z8POarPlDI4py84tMClpx7smdFkDYCEHOisJtlqYHJ2Am9ua+GiOapjuDI4TQge+bSGzQ0OTihLo83pZ1ujIx4M9fpodwf3Xj+PnEQzVR1uvn1WBYtzBAlP/Lff9Yz1n1JRegpufStGbxtUf8BHGVfynOMKli+6jjXNIR55sImnbjnyhP8kq5G7L5nJlx9dR0O3F5Ne43vnTWFKjipdohx9Ey4gSrUa+caZk/nlqzv4+/XzaOrxUZBsJSvJjNWoJxiOkGI1oNcEoT5LZL5QBHw9JG95cN+dWVMhpQTm3QBCj+j9BK8og3D5Q1gMQ5ghcjRGdzL2MtkBCd4uFhSl8OLGJhUQKQcUDofY3uzk2sWFBMMRitNt5MdaXmQkmCjPtLOnzUWLw8+uFhf/+qQagPd2tvGN00uZWbAUUfNB/P46is7Dk7KAysY1BEUhLfY8Cm3JvLSlipe2RK9zydxcyrMTB4ylqdvL9qboVv/yLDvlWQMDnVn5yTx724k0dHtJNBsoTrcN2npEUUbahAuIwjJCeYaN31w5m398UMWNJxbjCYZ5ZEUN03KTSLIY+PeqWm47rYw/vb07fruLZueSrW8Eaxp4OiAhG866G6wZ0F0dLT/vbjvwAysTntMXwjqUJbOeumjw3UsISMyFzioWFM3mkRU1eAPhoS3HKeNekiHCLSeX8uMXt8U/5J1Qmso918xldU0Xm+u7WT4tm6JUK7tanP1u+48Pa7jopt9R8vAikBHck86nreg83t7Swa/figBeYDd/v24eT35pCTUdHjITTEzPSxqww7au08Otj6xla1N0Ocxi0PH4Fxczt3BgUcbMRLOqsaUccxMqIKrr9PD+zlbyU63c/NAazp2Rze/f2sXq6uiW0nW13UzPTWRhSSo6ITh/ZjbtrgAXz81jdmoI4zPfInzC19hpnk2WOUiaPhQtljfnatj4BHz8e/jiu9FgSVH24/YPNSCqj85E9mXLhJ467HnzKU23sWJvB6dNyRyZgSrjih8j//q4qt+Md6rNxEOfVvd77ZuVl8SkrP6J1RKJS5fMp2e/hJBhus15ZBot3P/p1n7X29zQw51nT2FRyYF3gq2u7owHQwDeYJg/vl3J3z47XwXzypgwoZq7vrO9hclZCbyzoxW7Sc/Fc/LiLwi9tjY6KEy1sqfNzZzCZGbmJ1Hf1sWkj79JKLGAFdo8bnobgolFEHBD/kJ47suw6/Xo0obfPUrPThnLpJS4/UOcxemp779kBtHLnVVAdInhre0tg9xQUcAdjFDT0X/n1qRM+4DXvk0NPQP6g129sBC7xYzflovPXkC6Rc/WFl+8NEmv3MMoQNvQ5R1wbFezE08gNMi1FeXYmzAzRP5AGKtJz952F+dMz+Lyefk0Ow+8lfOkSWm8sKGBc6cksbgwhQ+rvs5bjXqeftXJX66aSbapG567FWSfruNlZ0Kimh1SBvIGw+h1Ar12hJ9BZBhcLWDb75N3Qna09QEwKz+JP7+ze5AbKwqYDRpnTc9mbU0XS0pSaXP5OVAtz9J0G1fMz6e+28vCohRm5SXi9IUobH6TiKanoPktIgt/hdWowxMIAzAzL/Gwkp7nFCYPOHbJvDxSbap4rTI2TJgZIqc/SIvDR1mGnWBY8vyGBt7e3spJ5f07LS8oSiEvxUJmopkbTyzhtNAnGENOwumTWTa1gOduX8pp0/Mgcwpc+TDYs6I3LD0dzr4bjKoDszKQa6j5Q85mMCWCbr83DXsWOOpBRihMteILhqluV7OTykAacNncPC6dm8eWRgeaECwsSuHUydFZR6tRhxCwuCSVBJOeOYXJXDE/H6tRx70f7iVBHyExPYeU5BR2zLyTh1a38vBNi/jJRdP51eUz+e55U6kYJIF6f3MLkvnJRdNJMOnRBFw+P5+rFxaqSuvKmDFhZogCoQhbGhwsKkllW5MDvU6jKNVEht3IjNwk9rS5mJWfxNyCZHSaQB9yM/vTWzHUf4Lzyqc5M8eCSCvtc48aTL0gWno+4I5+YjcNLGymKBCt+msbSj+m7pp9QXdfBnO0QaazCZGYx6z8JN7b2crn00sGXleZ0EJS8taOVv6zug6AqnY3a2u6uO9zCzh7RjY1HR4KUiwY9QKdTuP7z0a3ipn0Gr+4ZBpJOJj3Hw0wAo2cVpHB9NxE0uwmjDqNvJTD69doNxu4/oRiTpuSSSgsyUk2Y9Kr3CFl7JgQAdHm+m5SLTquXVzArY+ui69/6zXB986byh/e2sWPLpzOgx9XM68omdy2jyh86xYI+UFnJCEpDfoFQ30k5hzDZ6Icr1xDTaju3Dt4QATRc6+zChLzmJ2fzFvbW/n8UhUQKf0FQpLn1vevOTQjL4lXtzTxxKq6+LHzZmZz7aICvrl8MsFwBE0IfvVGJVOv39d+Qwi44YRiLEY9JelDe/vIV0UWlTFq3AdEtR1u/vz2Lm5cVsramu5+yYChiOTNbS1Mz00CCT+8YBrpsp3CN26CSBg0HZz/h2gPKUUZhm5PANtQijK27YKMKYP/zJ4NHXugeBkz85P4x4d7cfuHOBOljFsmvYbdpMcf2vfad1J5On98u7Lf9V7Z3MwV8/P53Zu74scSLXpCGLn91DJ8oTDnTM9mziDb5BVlPBj3r5wN3V5uPqmM7z+3mXmFA3s+dbj9LC1LpzjdikEHq+oFuVf9By3kRZdWCumTo4GRogxDq8NPsvUIu3XLSLSp66Tlg/88IQdaossbVqOeKdkJvLuzlfNn5Q5ztMp4IoTgttPK+MlL2+PHjDpt0KbVXZ7+u8e+cuokbCYdd55zgKBcUcaRMRcQCSHOAf4I6IB/Sil/MZz7k1Kyrq6b3a1uLp9XMODnl8/LZ15xCtXtHjrcfhYVJGAoOl0FQcqIanH4SLYcYUDUVR3NFbIcoAJ6Yi5sfx6QgGBBUSovbGhUAZHSTyAU5pPd7XznnApqOjykWI3kJpspSbNS1Wc7fn6yhUnpdr591mTaXX6K0mxMzU7AqPJ8lAliTAVEQggd8BdgOVAPrBZCvCCl3DaU+/P4AwigzeUH4OXNTXznnAqeXluP2x/m80uLKUy1sLvVRZbdhNmoMa0wE450a7SiHEJTj29A5d5Dqv0U0g/yyby3VYyrFexZLC5J5YlVtXS5A6SorcxKjEEX7VP29o42MhJMuHwhQpEI931uAU+tqeOTPR0sLErhxmXF6DTB9NxE/KEIFoOOTo+fJWXph34QRRkHxto7/yJgt5Ryr5QyAPwbuGiod9bi8PPp3k7yk60IEa2m+ud3djM9N4n/u2g6nkCAYASKU620OHx8/d8bqO30HPqOFeUINfV4STmSgEiGo3WGDpa/JgQkF0LbTgBsJj1zC5P577r6YY5WGU8EGtctKQKgzenHGwyjCYFBJ7hsXh5/uGoOVy8qxB0IYzAIujxB9ra70es0Tpl8gIR+RRmHxtQMEZAH1PW5XA8sHuqdCWBLrPrq986dyoubGnH5QswtSMZq0JiclUROogmnL8Rdsa2mofAgC+uKMkwtDj8ptiNYMtv7PpgSIOkQTVuT8qF1G5ScDMCZU7P450d7uXFpCZpqiKkAUkB+kpmvnT6JZzc0UJhi4+pFBfgCYTrdATzBMGa9jmm5iUzOSmJylmpSrUxMYy0gGuwVvF+EIoS4BbgFoLCw8KB3lpdqY2l5Ot5AhBc3NZKRYKIo1UqH289CWwp2g8Y97+7h7Z3RpqznzcymMFVtCVUO7kjOwV5tTv/hzxD5emDNAzDrqkNfN7kYdr4Sv1ieaces1/HGtmbOmaFKQoxHR3r+5SWayU6x8MrWZuYXptLp9rGxrovzZuawrDydNleANLsRi2GsvR0oyrE11v4C6oG+mc/5QGPfK0gp7wXuBViwYMFBp3MMOo2lpWmsqenixLI0chItlGbayLHpMBoEXp2J9EQT5Zl2LpyTy0Vz8lSTQeWQjuQcBHD4grj8oUPnEAW9UP0BbH4a8uZBStGhB5NUAJ528HaCJRUhBBfOzuX3b1ayfFo2OjVLNO4c6flnsxgpTDRz09ISajs9JJhTmJKdwLyi6K7b/JSx9jagKKNjrP0lrAbKhRAlQANwNXDtcO5wSm4SU3KTaOr2IARkJ/WfAbr74pn4gmHs5iPcAaQoh2lLfXTZ9qDBScdueOcn0Yrnk5ZDRsXh3bmmResUVX8crZwOzC9K4dUtzTz8aTU3qkKNCjC9MIXpQF2nG5tJT6rNNNpDUpQxZ0wFRFLKkBDiK8DrRLfdPyCl3DoS952TPPhSmF6nYdeNtdxyZTzZUNdNcfogPe4iIWhYB61bYdfrMPVCyJ5x5A+QOw+2vwAV54GmQwjBF5aV8OOXtpFsNXDR7DyVT6QAUJCqei0qyoGMqYAIQEr5CvDKIa+oKMeJd3e2snT/rctdVfDeL6JNW1OKYNEtYBvi9ubU0mgfvbX/goU3A4KcZAvfOXcK97yzmx+/uI0ZeUksnZTOeTNyKEwb+OGgw+Wn2xukMNWKQX1AUBRlAhpzAZGijCfv72qjpsPD185IgbAfumqg5hPY+RpUnAt5c4f/IELAzCth3cPRpbdpF0P2TIrTbPz04pl0uPzsbYs29PzH+3uwGHRMzU1kUka0GfHHe9qpaneTaDbg9oc4tSKT8kw73d4g7U4/Rr3GlJxE5hYmk5dswRsI09TjwxcMk2w1kJNkwWbSodMEBp120IBKSok/FAGiLSVUp3NFUcYKIQer336cEEK0ATWHefV0oP0oDudIqfEc2FgZS7uU8pyDXeFA56CldIE984ofxROBponqfj8PRZDBCCP6xycAs35gbTFPiMiubp0veh0hdPZUo2ay9ts9EOxs8EoZkTpLokFnTVIJdcdQ13v/qnWsfKbtAD8+6Dl4GK+BY+VvaaiO5/Efz2OH6Ph3HOo1cDw5rgOiIyGEWCOlXDDa4+ilxnNgY2ksI2U8PqcDUc917Bjr4zuU43n8x/PY4fgf/1CoZAFFURRFUSY8FRApiqIoijLhTaSA6N7RHsB+1HgObCyNZaSMx+d0IOq5jh1jfXyHcjyP/3geOxz/4z9iEyaHSFEURVEU5UAm0gyRoiiKoijKoFRApCiKoijKhKcCIkVRFEVRJrzjOiA655xzJKC+1NfR+jokdQ6qr6P8dVDq/FNfR/lrQjmuA6L29uO5CKgyHqhzUBlN6vxTlJFzXAdEiqIoiqIoI0EFRMqw+ENhuj2B0R6Goox5vkCYHq/6W1GUsUp1u1eGbF1NF395dzeVrS6uWJDPpXPzyEuxjvawFGVMCUckq6s6+dM7lTT1+PjcCUV8ZmYOmYnm0R6aoih9qIBIGZJdLU4++8+VeINhAH77xi7anH5+cP40DDo18agovbY29HDd/SsJRaI5qv/34jb8oQi3nlI2yiNTFKUv9c6lDMmuFmc8GOr1+Mpamrp9ozQiRRmbtjT2xIOhXvd/WEWbU/2tKMpYogIiZUhM+oGnjtWkQ68TozAaRRm7LEbdgGOJFv2ozKTWdXr4w1u7jvnjKsrxQAVEypBMy0miLMPW79h3zp5CbrJllEakKGPT7PxkMhJM/Y7defYUkq3GYz6WqnY37+9sO+aPqyjHA5VDpAxJXoqF+29YyMqqTuo7PSwsSWVeYfJoD0tRxpzSDDuPf2ExK6s6aXP6OaEsjTkFyaMylkAoQiAcGZXHVpSxTgVEypAVp9soTrcd+oqKMsGVZyVQnpUw2sMgEI7gD6mASFEGo5bMFEVRJohAKEJABUSKMigVECmKokwQ/lBYBUSKcgAqIFIURZkgVA6RohyYCogURVEmCL9aMlOUA1IBkaIoygQRCKsZIkU5EBUQKYqiTBCBUIRgKIKU8tBXVpQJRgVEiqIoE4QvGEbCgFYiiqKogEhRFGXC6M0fUnlEijLQMQ+IhBAFQoh3hRDbhRBbhRBfjx3/kRCiQQixIfZ13rEem6IoynjmVwGRohzQaFSqDgHfklKuE0IkAGuFEG/GfvZ7KeVvRmFMiqIo4148IFKJ1YoywDEPiKSUTUBT7HunEGI7kHesx6EoijLRqCUzRTmwUc0hEkIUA3OBlbFDXxFCbBJCPCCESBm9kSmKoow/vlAYUDNEijKYUQuIhBB24BngG1JKB/A3oAyYQ3QG6bcHuN0tQog1Qog1bW1tx2q4ihKnzkFlNA3n/FMzRIpyYKMSEAkhDESDoceklP8FkFK2SCnDUsoIcB+waLDbSinvlVIukFIuyMjIOHaDVpQYdQ4qo2k4558KiBTlwEZjl5kA7ge2Syl/1+d4Tp+rXQJsOdZjUxRFGc8CKqlaUQ5oNHaZLQWuBzYLITbEjn0PuEYIMQeQQDXwpVEYm6IoyrjlD0Uw6TU1Q6QogxiNXWYfAWKQH71yrMeiKIoykQRCESxGnQqIFGUQqlK1oijKBBEIR7AadPF6RIqi7KMCIkVRlAkiPkOkcogUZQAVECmKokwQwbBaMlOUA1EBkaIoygThD0WwGPQqIFKUQaiASFEUZYIIRSKYDRqBWMVqRVH2UQGRoijKBBGJgEGnEYrI0R6Koow5KiBSFEWZIMJSotcEEakCIkXZnwqIFEVRJohwRGLQCTVDpCiDUAGRoijKBBGJSHSaRkQFRIoygAqIFEVRJoBIRCIBvaZmiBRlMCogUhRFmQDCUqITAiGEmiFSlEGogEhRFGUCCEckmgY6NUOkKINSAZGiKMoEEJESnSbQBCogUpRBDCsgEkIsFULYYt9fJ4T4nRCiaGSGpiiKooyUUESiCYEmBGEVECnKAMOdIfob4BFCzAb+B6gBHh72qBRFUZQRFYkFRDpNEI6o1h2Ksr/hBkQhKaUELgL+KKX8I5Aw/GEpiqIoIykc2bdkpprdK8pA+mHe3imE+C5wPXCSEEIHGIY/LEVRFGUkhSMSTYCmCYJBFREpyv6GO0N0FeAHbpJSNgN5wK+HPSpFURRlRIWlRNOiOUQqqVpRBhpWQBQLgp4BTLFD7cCzB7uNEKJACPGuEGK7EGKrEOLrseOpQog3hRCVsX9ThjM2RVEUZZ9wJFqHKJpUrWaIFGV/w91l9kXgaeAfsUN5wHOHuFkI+JaUciqwBLhdCDENuAt4W0pZDrwdu6woiqKMgGgdIoFOi84WKYrS33CXzG4HlgIOACllJZB5sBtIKZuklOti3zuB7UQDqYuAh2JXewi4eJhjUxRFUWKiM0REZ4jCKiBSlP0NNyDySykDvReEEHrgsP/ShBDFwFxgJZAlpWyCaNDEAQIrIcQtQog1Qog1bW1twxm7ogyJOgeV0TTU8y/SJ4dIzRApykDDDYjeF0J8D7AIIZYDTwEvHs4NhRB2ovlH35BSOg73AaWU90opF0gpF2RkZAxp0IoyHOocVEbTUM+/voUZVVK1ogw03IDoLqAN2Ax8CXgF+H+HupEQwkA0GHpMSvnf2OEWIURO7Oc5QOswx6YoiqLEhHsDIg3V3FVRBjHcOkQW4AEp5X0AsTpEFsBzoBsIIQRwP7BdSvm7Pj96AbgB+EXs3+eHOTZFURQlJhKJNnbVqdYdijKo4c4QvU00AOplAd46xG2WEi3keLoQYkPs6zyigdByIUQlsDx2WVEURRkBoUgkWphRLZkpyqCGO0NkllK6ei9IKV1CCOvBbiCl/AgQB/jxGcMcj6IoijKIiFRLZopyMMOdIXILIeb1XhBCzAe8w7xPRVEUZYSFY0tmaoZIUQY33BmibwBPCSEaY5dziLbzUBRFUcaQvktmatu9ogw0rIBISrlaCDEFqCC6DLZDShkckZEpiqIoIyYSASEEOk2oJTNFGcRwZ4gAFgLFsfuaK4RASvnwCNyvoiiKMkLCUsaXzNQuM0UZaFgBkRDiEaAM2ACEY4cloAIiRVGUMSQcicQKM6ICIkUZxHBniBYA06RUC9KKoihjWThCNIdIUzlEijKY4e4y2wJkj8RAFEVRlKMnHFFLZopyMMOdIUoHtgkhVgH+3oNSyguHeb+KoijKCApHZDypWgVEijLQcAOiH43EIBRFUZSjKyxlbNu9yiFSlMEMd9v9+0KIIqBcSvlWrEq1bmSGpiiKooyUSESii3W7V/GQogw0rBwiIcQXgaeBf8QO5QHPDXNMiqIoyggLqSUzRTmo4SZV3060WasDQEpZCWQOd1CKoijKyIpEJJqmlswU5UCGm0Pkl1IGhIj2ahVC6InWIVLGqbpODzubnUgkFVkJFKbZRntIigJAu8vPjmYHDm+Q0nQ7k7MS0LQD9ZGeeMKy75KZeplWlP0NNyB6XwjxPcAihFgO3Aa8OPxhKWNRZYuTG/+1ivpuHwCZiSYevnERU3ISR3lkykTX5vTxvWe38Oa2FgAMOsG/Pr+QZeUZozyysSMU6e12r5q7KspghrtkdhfQBmwGvgS8IqX8/rBHpYxJr21pjgdDAK0OP8+ubxjFESlK1NZGRzwYAgiGJf/7/BY63f6D3GpiiUQkItbcVfUyU5SBhjtD9FUp5R+B+3oPCCG+HjumjDObG3oGHNtQ1x3LTVBLE8ro6XAFBhyr6vDg8odJVau6QDRvSBMCnep2ryiDGu4M0Q2DHPv8MO9TGaPOnTGwKPklc/NUMKSMutKMgVHPWdOyyEwwjcJoxqZwfMlMJVUrymCGFBAJIa4RQrwIlAghXujz9S7QcRi3f0AI0SqE2NLn2I+EEA1CiA2xr/OGMjbl6FlWns5tp5Zh1GnoNcHNy4o5rULlaCijb1pOIn+4ag7JVgMAyyalcefZUzAbVFm0XvsKM6qkakUZzFCXzD4Bmoi27vhtn+NOYNNh3P5B4B7g4f2O/15K+Zshjkk5yjISzHxz+WSuXFiAlJCfYsGgG+4ko6IMn8mg4+K5eSwsScEbCJOTaMFmHm5GwPgSji1tq15mijK4Ib1iSClrgBrghCHe/gMhRPFQbquMLr1Oo1httVfGqLxk62gPYczqu2QWiYz2aBRl7BlupepLhRCVQogeIYRDCOEUQjiGcZdfEUJsii2ppQxnbIqiKMo+4T67zMJSItWymaL0M9z1jl8BF0opk6SUiVLKBCnlUIvS/A0oA+YQXY777WBXEkLcIoRYI4RY09bWNsSHUpShU+egMpqGev6F+/QyE6D6mSnKfoYbELVIKbePxECklC1SyrCUMkJ0G/+iA1zvXinlAinlgowMldCrHHvqHFRG01DPv1AkghbrKqCpfmaKMsBwsw7XCCH+Q7Sha7wCmpTyv0d6R0KIHCllU+ziJcCWg11fURRFOXyRSLSPGYBOUzvNFGV/ww2IEgEPcFafYxI4aEAkhHgCOBVIF0LUAz8EThVCzIndvppo5WtFURRlBITlvgKqOoFq36Eo+xlWQCSlvHGIt7tmkMP3D2csiqIoyoGFwmrJTFEOZri7zCYLId7uLbAohJglhPh/IzM0RVEUZaT0brsHou07VECkKP0MN6n6PuC7QBBASrkJuHq4g1IURVFGVlhKeuuoquKMijLQcHOIrFLKVUL062UVGuZ9KiOk2xNgU30PVe1uClItzMpLJl31dlJGQYfbz6b6Hmo6PBSnWZmVn0SqTZ2Lx1IoLNGMsRkilVStKAMMNyBqF0KUEU2ERghxOdEaQsoo8wfD3PfhXv7y7p74scvn5/PDC6aRYDaM4siUicbjD/Gntyp56NOa+LGbl5Xw7bMmYzGq9hrHSrSXWSyHSAiVVK0o+xnuktntwD+AKUKIBuAbwK3DHZQyfFUdbv723p5+x55eW8/uVtcojUiZqPa0ufsFQwAPfFzF3nb3KI1oYgqHJbreXWY6QTisAiJF6Wu4u8z2AmcKIWyAJqV0jsywlOHyBsKDVqL1BMLHfjDKhOYJDFxFl1Kdi8daKNInIBKCUKyh2ROravH4Q9x8UuloDk9RRt2QZoiEEBcIIYr6HPoW8JEQ4gUhRMnIDE0ZjqJUK5Oz7P2OZdhNqjGrcswVpVvJT7H0O1aYaqEoVTViPZb6VqrWafuWzKra3Gq2TlEY+pLZ3UAbgBDifOA64CbgBeDvIzM0ZThS7Sb+fM08PjMzh0SzntMqMvjXjQvJ2++NSVGOtuxEC/dev4CzpmaRaNZz9vQs/nH9AjITzaM9tAkl3HeGSBOEYktm3d4gTp/aC6MoQ10yk1JKT+z7S4H7pZRrgbVCiNtGZmjKcFVkJ/C7q2bT5Q6QZDFiMepGe0jKBDUtN5E/XjOXHm+AZKsBs0ElUx9roYhEi30Ejs4QRZfMHL4gvqBavlSUob4qCSGEnWjbjjOAv/b5mfrYN4aY9Dqyk9SskDL6LEYdFqM6F0dLKBztdg+9OUTRGSKHN0ggFBnNoSnKmDDUgOgPwAbAAWyXUq4BEELMRW27VxRFGXP2XzLrLczo9IVUQKQoDDEgklI+IIR4HcgENvb5UTPw+REYl6IoijKC+idVQzAcDYKcviABtQVfUYZeh0hK2QD8RkoZ6XOsCXhwBMY1ZoXCEZp6vHR7Akf9sTrdAZq6vUSOoICayx+ksduLL3jskyR7PNHx9r7QKkdXtydAU4+X0FH8fftDYRq7vTh9wRG7z2Mx7l5OX/TvwR9SOTL9Z4i0fjNEbr9KqlaUIc0QCSHMgBVIF0KkAL29OxKB3BEa25hT2+nh/g/38tTaenKTzfzg/OksLUtDrxtufcv+AqEw7+9q5+5XttHm8PPZJUXccEIReSkH36a8vraLu1/Zzub6Hk6tyOBbZ1UwOSthRMc2mHBE8umedn7y8nZqOzxcMjePL51SSpHa4n9UhMIRPt7TwU9e2kpjt48r5udz80mlFI7wNvbdrU7+8FYlb25rYVpOIv/v/KnML0od8v2FI5KPd7fz45e20tDl4/L5eXzxpFIKj9J5srami7tf3sbWRgdnTs3iG8vLKc88+n8PY9XAOkTRgMjlDxGKSKSU7NeGSVEmlKG+k38JWAtMif3b+/U88JeRGdrYEgxH+Pv7e3jo0xo8gTC7W93c9OBqtjU5RvyxNjc4uOWRNVS3e3AHwtz7wV4eW1l70Jmimg43n//XatZUd+EPRXh9awt3/GfDMZnJ2t7k4PP/Ws3OZifeYJjHV9Xyx7cq1afyo2Rbk4ObHlzN7lY3nkCYhz6t4e/v7xnRmTmHN8hd/93MS5ua8IcirK/r5nP3r2Jv29ArnW9r7OHG2Li9wTCPrKjlr+/tIXgU8leq2lzc8MAq1tV24w9FeHlzE995ehM93pGb6Tre9O12r2nRJOtAKBIPlPwqj0iZ4IYUEEkp/yilLAG+LaUslVKWxL5mSynvGeExjgktDh9PranrdywckVS2jHwrjG2NPezfd/GJVbW0ufwHvE11u3vAi/3WRgd1nZ4D3GLk7G51DeiL9NyGBlocBx6vMnSVLa4BncqfWlNHi8M3Yo/R0OVlTXVXv2PuQJiqYRTwq2wdOO6n19bT4hy5cfeqanfj2m8ZaF1tNw1dR//vYawamFQdwekLYjPpsBl1OEZwWVRRjkfDbd3xZyHEiUBx3/uSUj48zHGNORaDjswEMw3d3n7HE8wjX08l2WoccCw7yYLZcOA6QrZBxmHUaViPQfPMwX4HaXYTZsPILiUqUYP9vjMTzFgOcn4cKYtRh9mg4Qv2nzWwmYZ+Pg027owEE2b9yNfHGuzvwaTXRvR3dLwJRSSxeAhNCIJhidMXwmbUowmB0xdiAq8oKsrwmrsKIR4BfgMsAxbGvhaMwLjGnDS7iR9dOI2MBBMl6TaEgJl5SczISxrxx5qdn8ykjH1tN3Sa4LvnTiHJcuAu9eWZCVw6N6/fsTuWl1OUdvTbI0zPTWReYXK/Yz+6YDqZCaok1dEwIy+JmX3OOyHghxdMI81uGrHHKEy1ctc5U/odO3dGNhXDyEmbnpvErPz+4/7RBdNITxi5cfeqyErgMzOz+x37zjkVEzqvbbBt995gGLNBh9Wow6WqVSsT3HCnDxYA06Tcf4Hn4IQQDwDnA61SyhmxY6nAf4jONlUDV0opuw50H6MhJ8nC1QsLaHb4+NbyyczKTyI3eXiF5qraXby/s42tjQ5OmZzBktI0CtOs/OvGhWxu6MHlC1KRncj03MSD3k+SxcD3zpvKBbNzaXb4KEy1MisvacQTvgeTnWThnmvnsbm+my5PkPIsOzNyRyZQdHgDrKrq4q3tLRSl2ThjSiaTsyfGx9htjT28tb2FFoefs6dnMb8oFZtJT26yhb9fN4/NDT30eIKUZycw4xDnx4E0dXv5ZE87K/Z2Mq8ohWWT0ilItaJpgssXFFCRnUB1h4fMBBMz85JIsQ2cvTxcuckW/vbZPuPOSmBG3tDGfSjJViM/vHA6l83Pp8XhpzjNysy8ZDRt6EnDkYhkY303r29tJhiWnD09i7mFKRiOwd/YSAhH+hRmjPUy84ciGHQCvaYRULtDlQluuAHRFiCbIy/G+CBwD9B3ae0u4G0p5S+EEHfFLn9nmOMbMTubnVz7zxU4vNFPUU+tqeeea+YOa4dMc4+XLz+6lh3N0Tykp9bW8+VTS/nm8goKUq0UHOGuofQEE6dNyRzyeIYjN9ky7OBwMC9ubOL7z22JX37goyqeuvUEitPH9yf9nc0Orr53BY7Yp/bHVtbyl2vn8plZ0U2ceSnWQ+46PBR3IMQvX9vBcxsagej5t2xSGvdcO49kqxG7Sc8JZemcUDa859LXSIz7cGUmmDl9ysjNUm6o6+aqez8lGKvZ86+Pq3j8i0tYUpo2Yo9xNIUikXhAqAlBKBwhEIpg0GnoNKGKMyoT3nA/2qQD24QQr8c63b8ghHjhUDeSUn4AdO53+CLgodj3DwEXD3NsI2pDXVc8GOr1u7d2DWsX164WVzwY6vXPD6uOSSL08aDF4ePXb+zsd6zN5WdrY88ojejYWV/bHQ+Gev3urV30jOCuweo2dzwY6vXR7g52t478RoHx4KVNjfFgCCAi4aFPqo+oTthoCoX3LZnp4zNEYQw6DYNOUwGRMuENd4boRyMxiJisWGFHpJRNQohBpzqEELcAtwAUFhaO4MMfXHCQSq7+YGRYL4aDFaYLReSAnTgTVTgiB32R3n9H27F2LM7BwbbQ+4OREX3uB7qv0f79jlXeQRqgevxhjvVva6jnX79t92Lf35deE+h1atu9ogxrhkhK+f5gXyM1uAM85r1SygVSygUZGRlH86H6mVOQhHG/XIEvn1pK6jASWSdnJZCZ2P/2l83LH/ECe8ernCQzt57Sf73GZtQxNfvo5J0crmNxDs4tTBnkfCsb0cTp4nQrJ5T2L7RYkWWnLGN8L0cO1YWz8wYcu+HEovisy7Ey1POvb1K1pgmC4Ug0h0ivqRwiRWGYM0RCCCfEPyAZAQPgllIO5R2rRQiRE5sdygFahzO2kTY9N4knblnMAx9V09jj5folRZxacfgvRnvaXOxpdWE16qjITiQjwUR2kpm/XDuP/66tZ3NjDxfMyuX8WTmYDrE1WErJrhYXVe0ukiwGKrITSLWN/E6d0SaE4OpFBWTYjTyxuo5JGXY+d2LxhEiqnp6byONfXMwDH1XR5PDxuSVFnFoxtPywqnY3u1ucmAw6pmQnkJkYzatJshj5+aWzeG5DA29ua+Gk8nQun19AxkF2BzZ1e9na6KDD7ack3cbsvCRMx6C0w1gwrzCZh29axD8/2kswFOHmZaUsPk7yhwDCsn+l6t4ZIoMm0DSBf5AZMEWZSIZbh6jfO5MQ4mJg0RDv7gXgBuAXsX+fH87YRpoQgvlFqczOTyYiJcYjqJ2yvraL6/65Encg+oKzpDSV3105h62NPdz66DqK02wUpFrodPmxmw68tb7XJ3s6uPFfq+Of6M6bmc2PL5xxVLYvj7bMBDPXLC7i0nn56GPJnxOBEIIFxanMKTjy862vzfXdfPb+lfH8t9n5Sdxz7VwKUqOzQMXpNr5x5mRuPaUMk147aOuGxm4Pv3xtJ8/H8o50muB3V87mojkDZ07GI5NBx8mTMzihNA0pJEbd8VXTqO8uM61PDpFep6EJ1AyRMuGN6H5RKeVzwOmHup4Q4gngU6BCCFEvhLiZaCC0XAhRCSyPXR5z9DrtiN6cPIEQv31jVzwYAlixt5PV1Z18/9nNhCOSPW0u3tvZxj8+rGJHy8FbgXS6A/zv81v6vXi9srl53Ccamwy6CRMM9XWk51tf/lCYv763p99mgI31PayqHljNwmzQHbKP1dZGRzwYgugb7E9f3s6eNueQxne8Mui14y4Ygv69zKK7zPbNEKmkakUZ/pLZpX0uakTrEh0yx1BKec0BfnTGcMYzFrn8IbYP0u+socuL2z9wirrDdfBdRC5/iL2DtE9oP8TtlInHEwizZZBAuaptaO032p0Dz7E2p59ujyrodzwIRyRa7CNwtA5RNIdIr9MQAhUQKRPecGeILujzdTbgJLp9XolJs5k4f1bOgOPTcxOZlGnvd0wTUHyIytIZdhNnDFJrqEQlwir7SbYYuGiQROD5RSlDur/idBv7T9LNzEskP0VVJB/rpJT9dpnpxL6kar1OzRApCgw/h+jGkRrIaJJSUtfpwRuMkJdiPqw8nmAwRH17Dz1+STgSpjjFTFrKwOrMOk1w49ISGrt9vLm9BYtBx51nT2ZeYQo/v2wW//PURrY0Oki1Gbn7khmU79caocsdoMXhI9FiIDfZgsWo4zvnTqHHG2J1dSeJZj3/e8F0puWM7s4rZXi8gTD1XR4MOo3CWKXoQXXVQsAF5mTwdRE0pdAQSsTpC6HTRDwPqCDVikGnceWCfKraXbyypRmjTuMbZ5Yzr/DwA6JOd4DW2Pk3pyCJX10+i7tf3k6XJ8i0nER+eMF0shJHviCnMrIiMvqBSxukUrVeE2hCbbtXlOEumeUDfwaWEl0q+wj4upSyfgTGdky4/SGe29DAz17ejjsQZumkNH584XTKDtLlsLWzm02NbppdIf78TmW8NcBvLpnCgkkDZ4OK02388Zo5NHR5Meqjb3hCCKZZDDz2hcU0O/wkmPUDKj1vru/h209vZGezk3S7kV9cOovTpmRSnpnAA59fQFOPD6tRR/4xqvyrHB01HW5+8eoOXt3SjEkfDVquWVTYv8lv0A87XoBX74KT7oAN/6Y180ReTP4s7QEHD31ajScQZnFJKksnpeH0hfjiSaUUptn4zRVzuGO5B4OmxdtyHI7Bzr9L5uYzKz8JhzdEfqqFbBUMHRdCkUi/HDydFs0h8gejhRmFCogUZdhLZv8iujssF8gDXowdO25sbejh+89uiSc9f7y7gz+/sxt/6MBbUDc3OGhwBLn75e20OPwAVHd4uP3JrTR3Dp4UbTXqKc9KoCjN1i95NclqpCI7YUAw1OHy843/rGdnczRhtd0V4NZH17K7NXo5wWxgclaCCoaOc1JK/rO6jle3NAPgD0X45Ws7WV/b3f+KrVvhmS9A8TLY9CR07uajxM/g12z87f09eGLn78qqTrY3OflkTwcf724Hop3rJ2UmUJRuO+xg6GDn3+SsRBYUp6pg6DjStwYR7Gvdsa9StTjoa56iTATDDYgypJT/klKGYl8PAseuWuIIGCxB+bWtzQdNbm71RGhz+QdUrm1x+GnsOPguscPV4vCxZ7/k11BEUtOh2nqMJ92eIC9sbBxwfF3tfjvBOvdE/02fBE0bIb2CN+v1OHzBAbf9eHc7C4pTeX1by5DH1azOv3El1GfLPQze3NUfVDNEysQ23ICoXQhxnRBCF/u6DugYiYEdKxmD1O6pyErAbjrwaqLdEO0uv/8uZbNBI9k+MgmmiRYDiZaBY0izD73buDL2WE06ZuYNzD0r2b95rS2WSO/tBnsWOBqYkRbGOkhRxNIMO3WdHmbnJw95XInmwc+/8VjraiIIh+WAJbNgOIIvGN1lZtAJ/GE1Q6RMbMMNiG4CrgSaiXa8vxw4rhKtZ+Ql9du1ZTZo/L/PTCPRMnhidSAcpiwziUy7iRtPLO73sx+eN5nirP6VawOhMIGDvNCEwhE63X6c3iDBUIRAbNo6P8XKzy+Z2W9XzxdOKqEilnTtC4YJR2T834OJROSgfZiU0WfS67jt1LJ+wcfcwmQWlvRvqUHWDJh9LeG23YTP/hXkLeAzaS24fAEW9Nk1ZjXquGhOLjXtbpZPy8QTCCHlwc+PQCiMNxDCGwjji50n6Qkm/nzVHE4oTePEsjQMOsEtJ5UyOdNOeITOp0A4HD/flaMrFNk/IIoeC4QiGFVzV0UBht/c9SfADVLKLgAhRCrwG6KB0nEhK9HMry6fxc4WJy5fiNIMG5MGSaj2B8OsrenivV2tpNmMXJTn4tSUNVxwYRFNpJOXmYY7EKau00NRug1PIMSKPR3c9+FeNKFxy8klLC5Nw9ynLceKvR089Ek19V1ezpmRTXmmjYc/qeG6E4pYNimDs6Zn89JXl1HT6SHDbqIiKwF3IMxzGxr59+paitNsnFiWxrZGB1cuLGDWIDMCO5sdPLGyjtU1nZw3M4cLZ+dSoHqljSkz85N54fZlVLa6MBs0KrITyNy/fYYtjS3zf4zNU09u1TPoHPUUujbwxWkVrCwo5ppFhWgC7CY9Pd4gP7hgKpUtTu74z0aWladz+bx8yvYr8+D2h/hodzv3f1iFXic4b0YOQoBBJ3D4QySY9GgimpD7y8tmMT03gZpOD498WsPmhh4umZvHeTNzBuS/HYo/GGZFVQf3fVBFKBLhC8tKOaEsDdtBZmWV4YnWIOobEGmE45Wqo8dVQKRMdMN9BZrVGwwBSCk7hRBzh3mfx1ya3cSJh2iaubmhh3s/3Es4Irm0XE/6y7eg79rNXGAuEClaSuDk73HL8y3cc+181tV0cdNDa+K3/3hPO499YTFLJ6UDsLWxh8//axW+2Lr95oYebl5WwomT0rn10XX8/bp5nDMjh2m5SUzLjS6pRCKSf35UxR/frgRgS4ODd3e0csvJpVx730qeve3Eftv2G7q83Pjgahq7fbHHdLCloYffXjl70KUWZfQUp9so3n+ZrI+qNhc9Xe1UfPwVDK1bANCaN5NUvZJViT/k4Y3R3LW7zp3Cr1/fyakVGdhMOmYXJPO39/bw4a42HrppUb/msJ/s6eBLj6yNX/50bwffPXcqnkAIpzfIM3s72N4UTapeWdXFb66YxS9e2UG7O5pft7XRQVW7mx9eMO2IqmmvrenihgdWxy+v2NvJA59fwOlTsg77PpQjE4pE+ucQCaK7zEIRDDoNJGqXmTLhDXfJTBNCxOfrYzNE4/Kddm+bm/d2tjGvMIXsYB36rt39fq7VfIzRWQtEt1E/urJmwH08vXZfNYLN9T3xYKjvz3tnb+7/qGrAckKTw8e9H+ztd8wdCBOR0QrWO5r7J3TvbnXGg6Fer25pVomxx6GmbjdWZ3U8GOplbFrN6Zn7/t8/2d3O7Pwk3tnRSnGajTRbNOdsS6Oj3waCUDjCvz6u6ndfUsKWhh421nXT4vRx2n7NZF/c2ERhWv+g7d+r66jv8h7Rc3l2Q8OAYw9/UkPkEEu/ytDtv8tMp2nxStUGnYZBr5bMFGW4wctvgU+EEE8TrUN0JXD3sEc1Buk1gU4TSCQRMfinYaEZ4kmKVuPA6/Q9ZtANjEVNei36rrTfdXvphMCo1wbkb/R+8NNr/e9TP8hj6DSBfgL2BDveCSFAG/y8C6MHou0zTAYdHe4AOiGISND3OQX6/r8LIQadJTQZNFx+QTgSzTHpy2LQ0eH29zvW+3dxJGyGgY9rM+kHbFJQRs7+OURanxwig06oGSJFYZgzRFLKh4HLgBagDbhUSvnISAxsrCnPsnPRnFw+2NlGk6EIb97S6A+EAKERmX4pHms+JelWitOsXLekqN8LkF4TXDpvXxuFOQXJ8U/vva5bUsS2ZieaBl88uWzAMkR2kplvnzW537HMBBP+YITsJBPTcvtXqy7PsjMrv/8OphtOKKLoEO1BlLEnP9WOy16Ct3j5voNC4Jp0Ic/URPONdBosLklla6ODS+bmUd/poardjRBw1tRMSjP25RDpNMHNy4r7BSFGncakDDuLSlKZkpXAW1ub4j/TBHxmVg6e/frv3X5aGQVHWAvrwjm50TfhPvf9uROKDtlcVhm68P7b7uOtO6J1iPQqqVpREIfagTKWLViwQK5Zs+bQVzwCdZ0etjU6MOgELl+QKQk+qruCaJYEunwR/MEwRalWkgwhqjp9eHwBpiRLii0e/MLEiu4k0hMsJJsN+EIR3tzRgt2k54TSNHY0OwmEwlRkJ7KkJIWtTU7e3t5CfZeXk8ozQEIwEsFm1GEz6kiwGNnZ7MQdCDE5K4HFxSlUd3rY2uhg5d4O8lIs5KdY6XYHObkifdBk8JoONx/samNDXTdzC1OYkmXHqNdR2epCp0V32Q12OwWAQ75DH41zEGBns5Ot9e3MTvaT7txByJDAJm0qdZ0eChM1rHpJgWwkybkbvzWTLfqZ7O4Kk2CKVjzvcAdIMutxB8M0dUcrmmckmChOs8arsAfDET7Z08Hb21ow6jWWTkrDGwyTYjHS4wvS1ONDCEgw6bGb9VRkJxCJwLs729je1MOColRK063YzQZ2tTgJRaAiy443GGZ3q4vsRDMz85PIiCWI72lzsaWhh0AoQn6KhXU1XfT4Qpw1LYs5BcmDzmgqBz8HD/f829bo4PbH1/GzS2YCsKm+m3d3ttLm9PPFk0oB+OdHVbz1zVNGYMjKODKhPqWMy3yfoarr9HDTg6u5aE4e93+0lwcvyeYnb3YwrSibV7dUUtsZzb257dQyXtzYSF0sd0KvCR76jI0Zie1MDTdz1eOSuy+ZQUTCd8+dyuqqDr782DranNHlBqNO4+/XzeP0qVnMyk/mv+vquOPJDb2rZSwqSeWWk0u548kN8XwfTcA9187jpy9to9nhoyjNRmB3O/ffsJApB+ljlp1opssdYH1tNy9ubOJ/zqngt2/sii+7JVsNPPHFJUxVvdDGjC0N3Vx970p+fGYWuVt+jKVnL/9e/Ax3PbeerEQT1ywq4CxrJTlv3QA6A6tOfpKbXtlM7wpXaYaNX1w6ky0NDn780rb4/c7OT2J+YQqfXVJEWaadLfU93PrIWtLsRkJhydPr6vnCslLe3L6XmblJPLoymhOXn2LhkZsXU5xmwxcM0+MNsK6mm+fWN3LH8snc9+Feuj3RApEWg45vnTWZn768HYALZufyk4un0+Lwc+29K+iIJWSb9BqPf3HJkBvNKkdmYA5RtHWHLxjBqNeISLXLTFHUR7I+NtV30+WJNlOtyDDT7XTxSZ0Xk0GLB0MGXTRnoq5PImkoIvntehD1q0g3BFhaaOHDynYeW1FDu8PHiqrOeDAEEAhHeODjKnq8AXa3OvnBc1vpO1G3rqaTxm5vv+TniIQ/vV3J9ScUEpFQ1e6modvHw58OTN7uq6rdzR/ermRvu5vyLDurq7v65SB1e4K8OYyKxsrI+++6Blz+EIttzViq32bvst/w27eiCdAXzM6lobWDSVv+BJEQPZOv4Gerw/RN99nb5qa6w82f36nsd78b63tIshn5eHc7kYjkoRXVeINh6ru8NDt8dHuCNDt8NHb5yEjct+2/vsvLir0d8fv+8zu72dvuJsVqpKnHFw+GALzBMKuru5geW759cWMje9vcvL+zNR4MQTRf5f4P9xIKqzfhY2HgLrNopWpPIITFoMMQK9SoKBOZCoj6cPhCJFkMdLoDZFo1PIEwek302w1m0uvwBEIDbtvoCBHAgNAZybULGru9mA0aISn7BUO9mh1+PP4QnkA43kdt32PocfoGPkar00+qtX95gKp210F35/TuQoPobNBgY6nrUrvOxpK9sZYZ+qALAK8xJZ7MbDHoSDKEMbqjO7W8lmyanQPbzDh9YZz+gedQOBKh1eUnJCPUDrLbsMPlJ8lqIByJDDgO0dpFvcF7osUQP95Xm9NHSp/GtP5gmIZBdqLVdHoIqDfhY2JgHSJBOCLxBMKYDToMei1elFNRJioVEPVRkZ1AdYebabmJvFftJic1moSaYt3XpsPlD5E+SM2iz84wYbTaCXkdvFjp56zp2WQkmEmxGVlSmjbg+hfPySUn2UpJuo2lZf1/HpYRJmXaBuy6uWhOLv9d33/L8tWLCg/asLMw1UppejTpdX1tN8vKB47lnOnZB7y9cuxdsSAfgC5rMRgsFO95nHNnRP+PNtR10xK00TL5WgAy9/6Xa2b03wovBJSl2zh9v23zRp2GTtM4oTQNo07H1YsKBzz2jLwk6jrdA3ZBLiiOVs4uSrdSkBotxFjV7hq07ciy8vR4L7ZEs56cJAunT80ccL3rlhSpeljHSLSX2b7Lep2GNxAmGI5g0muY9JraZaZMeGMuqVoIUQ04gTAQklIuONB1RyKhVUrJ7lYX1R1uzHodOk3Ep5EzdA463QH+s8XNhXML2d7kQAhYVmCg1in41Rt76PIGuGF+JldOCmPRC9Y4kojorSRZDbEt9IKMBBM7mp009vhYVdXBlOxEzp2RzcxYZektDd3888MqjHqN8iw7uUkWpJSEIvDHtyvpcPm5ZG4eVyzIZ3ODgz+8tYsEs55vn1WBTgiSrAYmZdjp9ARodwXISTJj0mvUdHpIMhvQhOA3r+/kw93t3LysBLtZz30f7MWg0/jmWZM5d3o2CQdoVTLBHbOk6g6Xn92tLjpcAXJTLASCIUzSzxRDM13ShhYKsMdno86lsTQnTIavBp27BV39ShosU3nQs4R/r20hM8HE/5w1idw0O/5AhN1tLsIRSYrNiNWoIQAhNMwGjYJUK89vaIyfC184qYRUm4H8FCvNPT6q2t2EIpLJmQksKUuNJ0dvqu/mlc2NWI0GshJNpNqM/PD5rfhDEW45uZRQJMI97+xh6aQ0vnxKGcGIJN1mZFNDD795fSfeYJhbTynj0nl58ftUDmhEkqo/3t3OL1/bwXfPnQpAq8PHD57fQigiuf+GhYTCET7/4Gr2/Oy8kRm1Ml6opOox4DQpZfvRfhApJR/vbufnr+5ga2O0uN2XTy2l2x3kidV1ACwpSeGbZ07ma//ZSLPDR6JFT/b5U6iqq+OJpc1o3dVk7X4S9mo4L/wnP3ilmjaXH03AZxcXMSs/ie89tyWeD3TF/Hxyksy8s6MViLZtmJGXzO2nTeKbT27gyTXR4o2nVmRw5pRM/n79PGQEJmXY0es1itPtpNsM9HhD3PnUJpz+EEadxnfOqeDptfVsb3ZiN+n55vLJ/OmdShzeIN86q4KfXzYTfyhCktWAzajn0rl5aEKoZp1jQFWbkw93d3D3y9vxh6K7DP9+aRFTfKuptU/D1vQmv26azTPb6vjWYhtpu+/DWPkSAOHsOTiWXM1skUFIGOhyB1lfWUupZmKdI5U/vb07WpdIE1y/pAiLQaPZ4efZ9Q1cu6iQO8+ezImlaTy3sYF73t2NwxvkCyeVsrmhh0/3dJCVaOLLp0ziq0+s45eXziYsJW9ua2FPq4c3t0dzz6Zk27nz7Ao2NfQwLSeRRaWpXDYvn80NPVz/wCo8gTAmvcbvr5rNc7cvRRJtmaMcO/vXIbKa9Dh8oXjpD50moh/CwhG120+ZsCb0mV/X5eGVzc3xYAjAatTHgyEAs1HPb9+qpNkRrfh8ydx8fv5qJecm15H75q1kr/4FomsvonM31tX3UJgcjTEjEh5ZUYM/GOmXHP3U2nq6PEEC4QjPrm8gEpFIKXlufQObG/aN472dbTQ5/OxodDIlJxF9rMLejiYHn+zt5Oev7ojniATCEe5+ZTvnxJZVXP4Qf36nkkvn5hGR8OvXd7K33U1usgVbbIkiM9GsgqExIBSOUNXh4ScvbYsvWXiCYYp826lPmk9S1Sus16bzzDYnZoPGZxIqMceCIQBd8wbSq1/ixQ2N1HR4eG5DA39f3UV3xMRjK2vjiczhiOTBT6qxmvQUp1nRaYLHV9Wyo9nJD57fwgMfVdPtCRKRcO8Hezkxtozb4vDz3IYG7CYDr2xp4o0tzWhCxIMhgB3NLj6obOeDXW3c9tg6mnt8BEIRvvmfjXhi+XH+UISv/3sD3d6gCoZGQSjcP6naGuupaIkVgBVCYNJr+GLn4JaGHlyD5KApyng2FgMiCbwhhFgrhLjlaD5QjyfIpobu+GW9JnDv9yIwJz+ZNTXxdm0kmPX4wmFSXP1bdwDoaz5kUU7/YoqtLt+A63W6A1R3uKnv8uLyh/AGw7yzs3XA9araXexuc/U71tDtxWbS99uxA9EALNgnubrLE8TSJz+jsfvI2isox4bDF6LV4ScY3vd/ZzXoSHZX4QlrZPZsZEtX9P8xN8lCWsfaAfeR0fw+evxMyd5XT6o7YmVXi2vAdf2hCI09PlJjSc893iAb63sGvV6vjfXdTM5K4O3trXR6/fEdl31til3H6Q/R5vTT6vQPSOoOhiUtPQP/HpSjL9DbsyxG0wQ2o65fs2mjXhdPrP7B81t4S+0+VSaYsRgQLZVSzgPOBW4XQpzc94dCiFuEEGuEEGva2tqG9UDJViOz+iSFhiJyQMftTQ09zC9Kjl92+0OYdBpdtrIB9xcqXMrq5v6JiRmDJGCn2owUp9nIT7FgM+mxGHScOnlg0mlxmo2yjP4dynOTLHj8IVL3q3Ktif7tQJKthn67RnKTjqwjuXJgI3kOJpj1ZCaa+1Vu9gTD9NhKsOgitCXNYkZK9P+xscdLZ9q8AffRnn0yIWFiV4szfixJ8zI5yz7guia9Rk6SmS5PNKBOshiYlT+wBpWpT8+PWXlJVLa6OG1KJslWE4WpAytTz8pPZleLC7tJT0aCiYwEEwn7/S0ZdIKsJDU7NFxDOf98oXC/cwzAbtZjMez7fzbpo4nWAFVtbmo63CjKRDLmcoiklI2xf1uFEM8Ci4AP+vz8XuBeiCYUDuex7CYdl8zNZ1NDD1saHCydlMac/CT++bn5NPV4Kc+0YzUa8IVCvLChieJ0GznWCJ+dWsia6gRyp19PUqQbEnOR7XvwLPwa1Y9FU580AdcuKsRi0FGQaqGu04tJH831mZWXTDAcJsGip6HLQyAY5ryZ2XxQ2RZfvls6KY3cZDMz85JocfiQUpJsNTA1J5GNdV3cdmoZf3irEpc/hEEnuPPsKTy7PrrUZzPq+Nrp5fz5nUo0AXecOZlpOYm0OX1oQvTreK4cuZE8B0NhSV6SmZ9cNIMfvrCVuQXJfPu0QvQJGgXhLtwzrmRyTwd3nlFMWlICTlsBoWmXoTeaQW8i0F7FmpRzuWRSPk+tqUcT8PVTi7Anp/P989L5n2c20+KI5rRdt6QIly9IssXI9ScUUZxqISPBxP9dOJ3bH1tPY48PTcBNS0v4dE+07lBGgolL5+Xxwa42zpqWFZ2+3drEqRUZvLcz+mZcnmWnLMMGUnLVJTMoSLGiaYLfXTWHrz2xHm8wmkP0i0tnUppuO8hvQzkcQzn//MGBuUE2o77fDFF0p1mYHk+Qbm+wXzNgRZkIxlRAJISwAZqU0hn7/izgx0fjsVZVdfCXd3eztqaLL59axv+eP43HVtby5cfWU5ph4ztnV1DX5eOVzVWcWpHBjLwkZulqKN30W8zNayiZciGRWZcg3/spYu/7yOmXoQ+5+eG5k7AbIhgNJvZ2h/AEQtxz9Vy6PUF84Qi/f3Mnf3i7krOnZXNyeTqbG5qYkpPIy5samVOQzHVLishONJNo0bO6qpOr7v0Us0HHNQsL6PYGuWx+PtefUExNp4cZeYk4vKHYLjMbp1Vk0O7yk5NkwaATTMtJJMlqIN1m5Ol19dzz7m70muBbyydzttpZNuo21Xfzuzd3sbvFyfNXpTH35ul0hwxk+ipJ/fDnmFo3Yyo9m8i8r2BzW/nre3uYlannV9NOR//JLyHoRSz5KsnJ6Xz1ua0Up1l56MaFvLurjasf2EBOkoWfXDQDc6wSsdWoIxSR/OHtXWxrdLJsUjr+sOSZtfXcde4U9DqNSETS4fKRbDVwyuQMJmXaMQhBoEzy2X+uRKcJvnb6JL61fDI3Ly1BrxOk2Yzsbffw4sZGbnlkDVctKOSGE4s4c2omL39tGS0OH+kJJkrT7UfcCFYZGf5QBON+M0Q20/5LZhq+YISqDjeagJp2VZ9MmVjGVEAEZAHPxpo86oHHpZSvjfSD7Gp2cOfTm+LJznlJFv70diUf7Y5+Kt5U38OWRge/eG0Hd55VQU2Hh0mmHqZtuhlc0XV1XWoxuievhXB06UFb9y/M3g4KJn2ZhzaE+c6kWu54NytaTNFm5PdXzua2x9YRjuX5PLW2nmBYsrA4mR+/tI0vnVzKL1/bCcDVCwuYkZfIL2KXAX79xi7uOmcKtz26lie/dCKTsxKA/j3I0uxmyrP2HcuLNd18fkMDP3xha/z4t5/eRIrNyBlTs0by16ocgVaHj9sfW0ddl5f/XJWHad39OGZ8G52nkcLXrwdfNwCm7U+T3VPDTtsPqevy8LclAayv3B6/H8Pb/0vOMgveYBGra7q47bH1fO7EYhy+EA6fk9seW8cfr57L7Y+v45GbFnH7E+tweKO5Pa9tbaa+20N5VgJ3PLmR31wxi+fXN/Lern3LMNHdYXO4O9aKA+C7z27hvs/NZ/m0aBL/pvpubn9837l934d7icgI3ztvGqUZ9n5NZZXR4Q+FB8wQWY16TH0aSBt10eKMDd1epmQnUtOpZoiUiWVM5RBJKfdKKWfHvqZLKe8+Go9T3eHpt/MrJ9kSD4Ygmlzd7Qli1Gn0eIPYzXpKdC3xYAiIBkLh/onN2o6XKLe4eH67A38Izp8UXZrqdAeo7fTG3zB6vbK5CacvzOKSVHq80ccDeGlTU792CL12tToJhCXVR7C2H45IHl85sL3HixsbD/s+lJFX0+mJt38pEi00pCzAEdQwdu+NB0O9dI2rOTXLS2GqlbzWdwfcV9Hex1lWHA06nP4Qfd/3QhFJS2yHZH23Nx4M9drS4KA0w0Y4Iml3BfoFQxCdWRgsifq59fvOn53NzgHn9uMr6+KPq4w+fzAyoNim1ajrlytmiM0QtTn9FKVZcXhDqrWKMqGMqYDoWLGZ9P2qQGsimnfTKywlJoNGMBzBbNCh0zT8Yr+kZN0gy02WZPxST7LViJ4gzX3eRyzGgb/qdLsRkHR5gpgNOkKxdgnpduOAKtUAKVYjLl8Qu+nwJ/Z0mqAwbWDeRsEgibHKsWM16uL/xyGdFXPIhV5IpHGQHBudEVfEgNMXwmvJGfBjjzWfNs++BHqd1v9c610W6XuO9zLqNHrf88x6bUAidO9Y91eYtu/8sZsH3iYjwdjvzVYZXb5QtA1RXxajDvN+SdW+YJguTwC7SY/NpMMxSAshRRmvJuQr1rQcOw/cMI83vr6M1796IoXJZv7vgmksn5bFhbNzKEqxMC8/masXFKDXBHtanewM59A99dp9d9LTgMyb3+9+I8u+xbsdyfzfSXZc5lxer4zu+rlgVg4FKRYqsvsvcX3uhGKyEk0093jxxnqOCQG3nFxKfrI1PmMEkGYzkmQxcNWiQkoyjiwx9bOLo8ndvRIt+ngrCGV0lKbbeP2ry3jlq0sx5c8me85ZTM60k1g0D++SO/Zd0ZqK/8yf8Uq9mU53gM3WJWBN3fdzvYmq8s+zuTE6a3h6RQY7m/fVs6rIspNk0bOgKIWcJBOnT8noN47PLinktS3NlGXYSLMZ+cJJJf1+PrcgmcwEU//zx6zn/Fn7ArOZeUlU9NnRJgT84PzpKnl/DOntat/X4pI05hWmxC8bdBreYJgud/RDl92kp8c7cKZaUcarMde640gcaduEDbVd9PiCBEMRajo9bGt0sLg0jbxkCz2eALvbXNR3eVlckoLL48fvcbCsJBGfMNMR0JMmnBT6dmL31hNOm0y3Lg1Dxy7MwU5CaRVsl8Xs7pYYRLQX2fbGHvLTEtDpDbT0+MhJNtPi8NPpDpCbbMFq1GE16ghHJHXdHlzeMCk2AzajjvKsBHzBCJvqu6OVfRPMmA0a0/OS+jXOPFzbmxxsbuhBJwQz85NiOUjKIYxo645QOMKW+h6CkQhNPV5W7WljQb4NvcEAmgGTXuPTqi6EjHDG5BRSdR7eqQ7S4AyzoDiVdLuRuk4PZ2d0kNKxnrAUtCZM5YHdiRSm28lJMpNsMeAOhNjZ7MJs0ChMtbK7zYU/FCEn0UyiWY8nGH38ojQb/mAYVyBEXpIFhy9Iqs1EMByhusOD3aQj1WrEbNAwGXTUdHjQhGBGXtKA4L6u082m+h66PUGm5CQyMy8Ro37gzJJyxEakdcf3n92MUadx1kH6Fv7jgz18ZmYO7+xoZVKmnde2NPPrK2YzpyD5iAetjBsTahfEWEuqPmq2NvawurqTFoePFXs72dIY7Uu2fFoWK/Z28NqWZipbo4XsnlxTz/VLCllZ5eIfqzp54ooc/ufVdv5ycoAacylzqh7h08h0bny5AbCh1+yY9H5uOy1MVauTmi4vwbDk5PJ0CnXRvmF2s56Pd3fw5VPL+MNbu4jIaH5PstXALy+dxXef2cK1iwp4Zl03O5qdfO2Mcr52+iRmDNI8cyim5iQyNWdgvRnl2FlT04UA1tZ28avXdlKQasFkMtHc4+Lk8nS++dTmePf3f31ayy8uncmv36lESnhsVR3fO29KtAaQ30VXaz1frTuNT2q6gGjh0Atm5aDXCU6fkkWECD96cQcAnz+xmPd3tRGKRDhrWjaN3V78gTDlmQm8t6OF/65vJBTLATp1cgZ/uHrOoAn3i0oGNgbuVZBqoyBVbakfq3zBcLxK/YEYddFK1b1LZnazmiFSJpYJs2T2/s42bGY96QlmtsRq/cwtSKGx24teE/FgqNd/Vtdz5tQsOtwBdjQ7+NzcBHY5TZREqvFj5M8b982shSISdyBMpzvAGztaObEsnQ113SRYDDy1pp6FJam8vrWFM6dm8XRsd1lvEmq3J0h1h5uiVCtPra2PvxH9/b098aRb5fgnpeTFDY10eQLc+8FeAM6dkcMTq2o5sSyVNTVd8WAIopXH39jWwuxYA2CInpNCgHQ0sMc6h09q+p+zL21uojDVRn2Xh9wkSzxH6d+razl7ehZ1nV4SzXpe3dLMrMJkKludPLm2IR4MAby3q409bQMrXCvHN38oguEQOV16nYY/GK1DZDPpsRn1dHsCB72NoownEyYg8gTDhMP9lwdNBo1gRBIZZNUwGInEa6YEwmA3QEAKRCRIWG/FNcgHp0Aogr5PQquU4AqE6V2VNBn2VYLd/3YWoxZrwLjv8XuTrJXjn5QQikSQkngFcYNOIxCKoGmiX1XxXm5/qF9isi8YPZdkOEhQDvzT7T3PogGOiM91B8Mynmjde65HxzP4cnkwdPwuoyuD8w9SqXp/Rl30POz2Bkkw6bEadTjUDJEygUyYgOiU8gx0IrqdPivW1HRtdReFqVaE6N3xtc/Z07JZWdWJSa8xJdPKX1Y7mWLz0Ggswd69g1tn9v/V6TRBXoqFiiw7O5qd5KdYcPmCXDE/nz1tLmbnJ/HO9lYumpPb73ZGncakLDs7ml2cPiWTVVWdAFwyJ4/CFLUTbLzQNMEZU7NIshr47OIiAN7b2cr5s3LZ2uBgQXHKgNucNzOHdbX7+uhdOCcXvaahpRRRFthJYUr/pOVFJanUd3ooSLHS5QnEg5/zZmTzUWUbiWY9ESmZW5DM7lYXRalWFu73uJMy7ZQeYdK+Mvb5Btl2v7/epOreUiMWo04tmSkTyoRJqu52++jx+nF4IzT0+HD7Q6TbTSSYdTh9YZp7fEjgw8o2yjPtLCxJpbHbh0kvKEk2sKfTj91sQK9pTLZ0Y2n4lA+CU7l/U5AUq4FrFxVg1An2dHiobndzxtQsXP4wuUlmtjU5CIYle9td6LVoL6kXNjaSlWDm2iWFvLGlicxEMznJFh75tIbL5uWzrDydpm4vep1GRXaC6hA+OkY0qXprbRcRTeDxB2no8WMz6jEZNAw6gdsf3e4cCksE0ZowiWaNXS1uXtvawmXz8inLsKEnjC8YwqRFMBv0PLe5ndU1PZw8OZ0lpWmEpSTRrOfljY2srunmrGlZaJqgssXFiWVpNDm8zC1IocXhY2pOIskWA5sbeqjt9JCbbGFmXlK/4p7KqBuRpOor/v4JZ03LPmhO4kubGtFpgsdW1PLIzYt4eXMTZoOOH5w/7chHrYwXKql6vAmFIrQ5fXR6wvzslW1srI/mEKXajNx98Qy+/Ni6+HW/d+4UStJt/O/z2+K5FJkJJr54cinfeHIzt582ibddLpaVnUIoJKjIjr6ZfPnx9eQmW/jHeclcJVfyxbensKLOQ2GqhZ9dOpOaNjd6DRaVpPD39/aQnWSm2xPkvZ2tfOusChLMBkwGHRfPyaOmw8P196+k3RVdv5+Rl8hfrp1H0SD1hJTjw8q9HYTDEWo63Xzvua3x5a0vnVxKKBLh/o+qgWgtmO+eO4Ufv7wNXzDCiWVpXD4/n9+8vhN3IExZho2zp2dT2epi+bRMaru8FKZZeWVzM69ubuLOsyv48qPr+Ou1cynPSuCTvZ1cODsHTUCLw0ckLLn5oegbaFGqlRuXFvN/L22Lj+e7scRtk0HtEBtPAqGB2+73l2g2sK62i0SLHiEENqOedrf/GI1QUUbfhFgy29LUgyck2d7siAdDEK0g/dyGBmbk7dt99cvYG0/fxNJWp5/dLU7KMmzc98FekhLs7O0Os7HBxVNr61lZ1UlEQn2Xl1fqjCSsvYcvTY0GM7WdXj6qbOeP7+wmFIYfvbCNTQ0O3t7eytqaLh5dUUtVhwerSY9OE5gNOh7+tDoeDEG0mvDHu9uPwW9KORranT66PQEC4Qj/99J2+k7K3vvhXhIt+5Zr/aEID31aw3kzo3V+PtnTgcMXwhPLMdrT5iYQjrCyqoNwBD6o7ODNbS00dHup7/axucFBdqKZ7/x3M9PzkpiancBXHl/P796sRK/T+Ov7e+OPdcGcXH7+6o5+4/nlqzvY06ZaNow3/tChl8zS7UY21HWTGZuNtpv1dLpVUrUycUyIgMjjD4GEqkFe6CtbXNGtzDHhiBz0RWBrk4OCFGt8J1AwHKF6kG7Qa+uckFRAYqQ7fmxbo4PcZAvJNiOtzoGfuNpd+475gmHW13YPuM72JseAY8rxodsTRKdpeIJhfMH+ifJSRs+lvqra3eQm76uM7vAG+yVX13V6yEow0zXIebqxvpv8FAvdniBOX6jfpoHAIG0Y/KH+xyISOtSswLgTDYgOvvqRbjfhD0XIjOVYJlkMdPb5YBY5QBK+oowXEyIgSrWb0GuCWX22MPc6oSyNDX0CkASTnqzEgRV2Ty7PYHNDDylWA95AGJNex8xB7u+8qcnQUUk9mfFjyyalU9niZE+ri+m5/WsBCQFFfeq32Ex6LpzdP/Ea4MSy9EM/UWVMyk22EAyHSTAb4m82vfq2Tui1pDSVTXXd8cupNmO/QGpKdiI1HR5yUywDbnvm1Cy2NzkoSY9WnpZyX+sNvSb6VT/3+EMDNhNYjTryVTL/uBPdZXbwl/tUmxER+xeiAVF7LOj2BsKc/Ot3aehWpUCU8WtiBEQWLbqbK9PGbaeWxT8pLZ+W1a+FRXaimT9cPYfcRDNXLYy27RACLpqdi1mvcf0JRfzy8lmcUJLCxaURPlvq4d+fm8a5M7LQa3D1glxOSHay5YKX+agzGYNOcM2iAhYXJ/Lv6yuYmqbjjjPLmZoTTVpNtOj589VzyUsxs6vFSVNP9MXmwjm5XDg7FyHAoBPcfloZi0pSBz4x5bB5A2F2tzqpG6RR6dHmDwcoSrWSlWDit1fOpiAWyGTYTfzi0lnkJJri/elm5ydx9cICPtzdjtmg8f3zplCQYuaucyZz32XFPHNFJjYtxG2nlSHDEX57xSxuPaWUghQLV8zPJyfJzKXz8rj74umsq+nEYtD4y7VzKUi18OTqOr5z7hTSYm94q6o6+N2Vs8mPjSczwcTfr5tPcdrECYh6vMHo3944f6M/nBwivU4j1W4kI9ZyJdFsiM9CvrGtmfour2oKrYxr4z6pekNtFw5fkPV13fztvT2UpFu59/oF7G138db2Vr773838/NKZtLv8bKjr5s6nN3HF/Hwum5tHfool+kKiCcxGPX94axfuQJizpqQzqXgnxe99lfTcxRjn/ZAvnLiAFOHk0kf20u1pY1FJCo/cvIin19Rz0d9WkWozctdZk/jre7spz0zg6oWFzC9KQacJbnxwNRvresiwm/jZpTM4rSKTX142i6+cPgm9JihMtaI/xKc75cCq2t38/JXtvLGtBbtJz3fOreCSuflH1CR3qLbXdVHV7SMUjvDf9Q2s2NvB766YQ5PDS02Hh9+8sZNvLp/MTy6azt52N7UdHna3ufjpxdMxaNGWGT95aTttLj+zc238fL6Tm7pfpnPB1/nfD1t5fWszFoOOL59Sxoy8RL782DrK0u0sn5rJoytrqWx1U5hq4acXzSA7yUyazci5M7Lp8QbITDCj1wm+d95UdjQ76HQHeXVzE8Xptn7LyOPV9iYHd/13Exvreki3G/n5pTM5rSJzXP6tHU4OEURbBOUkRXOIzAaNsJR4AiFe39rMktJUXt/azK2nlB3t4SrKqBh/f/l9ODwBPt7TTmO3j9+/WYkvGKEw1cYf3trFT17azqd7Oqjr8nLjg6tp6vHzyIpaOt0B/vHBXipbXfzp7Ur+/M5uNJ3G3a9sxx0rqvjGjnYeaCohlDEdY+NKpm/4GZ/sqMfW8DFp1uib7KqqLv789m5aYjlDne4A33luG6dPyeaFjY388IWtfFjZxl3PRF+QAdpcfm59dB27WpxYjDomZyVQmmEfly/Qx0ooHOH+D/fyxrYWAFz+ED94biub6ruPyeM3ugI8v76e93e1897ONuYUJPPv1bX85KXtPPxpDfVdXr755EYae3z8+Z3dPL+xkXve2UO3J0Szw883n9xIWyzHbGOjm7vW2HGHdVi2P8Xm+h6kBE8gzG/f3EVlq4vL5uWztcnBD1/czoy8ZCCa2P+1f28gIiXpCWZyky1MzUkizW5iXW03tz22jj+9vZtHV9TwxOo6nl5Tx/FcjuNw9HgD/f722l2B+N/eeHQ4OUQAd55dEW/xI4Qg2WKgwxVge5OT0yoy2d3qGvfnhjJxjet32jannxSrgW1NPfFj5VkJbKzv6Xe9iARfqH+l4FXVnZSm2zAbNLoGKV//YqWXzsKzATDVf0SewYk7rOesEkP8Oh/v6eiXtyT3exxPIDxgLOGIpLrj2C/rjFcd7gAvbW4acHxn87F542vo8pKXYuW1LdExzC9K5cNBdgx696tUXd/lISL3tXjptanJQ1PqQhJ2PcvpRYb9buMlO/bpfneri7w+OUY93uCgy4VrqrsGHHtuQyPd47wgX3OPf8L87XkCIQT0yx87ELNBhxD7Aqcki4GmHh8NXV6m5iSiCTHoxhBFGQ/GdUBkNgp6PEHykvdN//d4gmQkDEya3v/FojTdRpPDhz8UIWGQpZWKdBO2nl3RC4m5dIZMmAmwq8/7S36Khbb9Xjz6Po5BJ+L5HH0NdkwZGrtRT3nmwEKDx6rQZYrNQLvLz6RMOwBNPV6KB6kntf/5lxbbCLC/VJuRRH8LvrTpVHb13yGWYjXgjwVWiRZ9v3YgOk2QYht43pekDxzL9NzEeCL2eJVg1k+Yv71Whz+aMC0Op8aehA1PwCOXwqv/Q5IJVuztIDvJjEGnUZhqobJF9bpTxqdxHRDlpdiZmZ/M9NxEpmZH3xRf2NjIF08qifcpA7h4Ti57+9QdKk6zMj03EYc3hJTRmab5Rcnxn1sMOu6cE8S25xXQdOxe9FMmZ1jwJ0/inT3R7fEGneDbZ1fEZwYAzpqWybbY9nmTXmNJaRo/vWQGfd/3rllUyJRs1ZV+pNjMer5zTgWWPoUGl5SmMqcg+Zg8fmmGjem5idx6Shlmg8Yrm5u4bklhvwDotIoM6rv2zUxMyU7AGwizsa6by+fnx49rAu4+2ULu7idwLvgKm5v3JQJPz02kNMPOcxsaEQLuPKuC5zfsS4D92hmTmJ4zMDBcVJLarw5XolnPl08tw6Qf3wFRbrJlwvzttTh88Z1jA/TUwjs/gRe+Biv+Bq9/H2o+gmXfAGs6+Z0reWJldbydS26yhR3N0dewHc0OvvHv9QRCqueiMj6MudYdQohzgD8COuCfUspfHOi6h1O2PhyRbGnoJhyRNPf4cPnD8V01dV0erEY9WQlGhKZR1eZCr9MoSbPR5fEjEbQ6fGQnGkm1Gqjt8hGMQEGijvJQJTp3C25bPk5DJmmak2Ytm0aXpMMdJCfZjDcQxm7S097jIs0QICfVTqPXiMsfojTDzuQsO6GIZFeLk+p2N+l2ExXZCSRbx9+n1NFW2eJkd5sLu1HPlJzEQWcJBzEirTu2N3bT5Qli0GnUdkaLcCaa9DQ7fOh1GilWAxaDnuoONzajjmSrgdpOD9lJFuxGHS6vF5fHQ3EC5AVr6NJn0G4qQBNQ1e5BJwSFqSZkwENNT4TcJDOZ5jB1XgOtTj85SWZm5CaRah/8OTf3+NjR7MAfjFCebac03X44v5vjXjAcif/tpdlNTBmbf3vDbt3xwsZG/rO6lq+cVg51q6DydTAngdBB1QdQdhok5kF3DRiskDMHdHqQkm3rPuQnjQv45qRmFuaZeT84lVqn5C/XzuPsP3yA0xfis4sL+crp5SP5nJWxY0K17hhTAZEQQgfsApYD9cBq4Bop5bbBrn8kfaQUZQhGtJeZogzBsAOif364l/W13VyXsRfW3A+TlkPIC5EgZM8GS/IBbxsKR7hnRSe3pm/EHOikobWd33Edf71hGbc9sZ4vn1LGfR9W8f6dpx7mkpxynJlQ/6ljbdv9ImC3lHIvgBDi38BFwKABkaIoinJwzQ4fiThh1T9gwU2QkH3oG8XodRrfWJoOnAFAjqMZ5wdBfnbfo5xscVG2+UXC/jNZV93J7MIUfv7qDpp7fPz04hmkjMN8LGV8G2s5RHlAXZ/L9bFjcUKIW4QQa4QQa9ra2o7p4BQF1DmojK4jPf9aO7pJ3vMiVJx7RMHQYLTEbD47K4FGUwnnzMhFJBewXKziTw89xo/+9TyrKhvxBQJ87d/rCYUjSCmpbncP2FyiKGPRWFsyuwI4W0r5hdjl64FFUsqvDnZ9tVyhHGVqyUwZbUNfMtv+Imx7nlvW5mO0JXPCpKwRG5TsM7BABP601UQ4HOZ27Vks+Pl1+GoiCLyYiMQ+dxcbujkjrROvZqU9ZMFugAJbBJNewxHS4Q0L7MmZJGYWEIpIuj0BgmFJksWA1ajD6QvR6vQhEGQlmUm1GtDrNIQAgUASLVMRCEUIRyQ6TWDUa+g0gTjIr1ES7fcXDEUIhiMIASa9Lnq72H0f7yQSKaNLoIFwBCnBqNfQ6zSm5SQyvyjlQDc9/p/8ERhrAdEJwI+klGfHLn8XQEr58wNcvw2oOcy7TwfGUst4NZ4DGytjaZdSnnOwKxzBOThWntOxoJ7ryDnoOXig80+vQdd3EubajUL7e/AzPBQ8U5qk7ygOs8+YgIjOIGqI9mScLOrwShN1ffo7KmNHyNHmb/jbjVsG+VE6sONQr4HjyVgLiPREk6rPABqIJlVfK6XcOgL3vUZKuWC49zNS1HgObCyNZaSMx+d0IOq5jh1jfXyHcjyP/3geOxz/4x+KMZVULaUMCSG+ArxOdNv9AyMRDCmKoiiKohzMmAqIAKSUrwCvjPY4FEVRFEWZOMbaLrOj6d7RHsB+1HgObCyNZaSMx+d0IOq5jh1jfXyHcjyP/3geOxz/4z9iYyqHSFEURVEUZTRMpBkiRVEURVGUQU2IgEgIcY4QYqcQYrcQ4q5j8HgFQoh3hRDbhRBbhRBfjx3/kRCiQQixIfZ1Xp/bfDc2vp1CiLOPwpiqhRCbY4+7JnYsVQjxphCiMvZvSp/rH5XxCCEq+jz/DUIIhxDiG6P5uznajvX5d7QJIR4QQrQKIbb0OXbMz6Vj4SB/y2P6+R5v59yRnlNjzVDOk7FCCGEWQqwSQmyMjf3/YsfH/NhHnJRyXH8R3a22BygFjMBGYNpRfswcYF7s+wSipQSmAT8Cvj3I9afFxmUCSmLj1Y3wmKqB9P2O/Qq4K/b9XcAvj9V4+vzfNANFo/m7GW/n3zF4TicD84AtY+VcOorP9UB/y2P2+R6P59yRnFNj8etIz5Ox9EW0dJQ99r0BWAksOR7GPtJfE2GGKN4fTUoZAHr7ox01UsomKeW62PdOYDv7tSDZz0XAv6WUfillFbA7Nu6j7SLgodj3DwEXH+PxnAHskVIerLDhaP1uRsoxP/+ONinlB0DnfodH+1w6Kg7ytzyWn+9xd84d4Tk15gzhPBkzZJQrdtEQ+5IcB2MfaRMhIDpkf7SjSQhRDMwlGnUDfEUIsSk2Rdw7BXksxiiBN4QQa4UQt8SOZUkpmyD6Bw3xUrLH6nd2NfBEn8uj9bs5mo738R+u0T6Xjrr9/pbH8vMdC2MYCQf6HY9ph3mejClCCJ0QYgPQCrwppTxuxj6SJkJANFgvlmOytU4IYQeeAb4hpXQAfwPKgDlAE/DbYzjGpVLKecC5wO1CiJMPct2jPh4hhBG4EHgqdmg0fzdH0/E+/uEaF89/kL/lA151kGPH+vmOhTFMSEdwnowpUsqwlHIOkA8sEkLMGOUhjYqJEBDVAwV9LucDjUf7Qf9/e+cfbFVVxfHPl4cQ4PMxgDUwlaBBjRQyMmQhGhVDZpNpo4lhgj9KrQGpBpsJdKaypoRQsR8aWBiRGipINoWGgAkoFPKeYDTID52SgEpIpFJo9cded97hzbuPy+u+c+/jrs/MmbvPOfusvfa56+6z9jrnniXpBNIPY6GZPQxgZrvd8P4LzKU5lN7hOprZy/65B1jsbe+W1N/17U+aHeSiD8kx22Bmu12vip2bDqaz618qlbSlDqW13zLV3d9q0KEcFDvHVckx2klVYmb7gJXAeXQy3ctBLThE64HBkgZ5VGI8sLQjG5Qk4B7gj2Y2O7O9f6baRUDhHxVLgfGSuksaBAwG1pVRn16S6gtlYJy3vRSY6NUmAo/koY9zGZnbZZU6NzmQu/1ViEraUodR7LdMdff3eLG5Yue46miHnVQNkk6W1NvLPYCxwBY6ge5lp9JPdeexAOeTnvrfBkzPob3RpBB1E7DRl/OBBcBzvn0p0D9zzHTX70/AR8usz6mkf5o0ApsL5wDoCywHtvpnn5z06Qn8HWjIbKvIuTke7S+H/txHuq35BikacXWlbCmHvhb7LVd1fzubzR2rTVXb0h47qZYFGAY867pvAm727VWve7mXeFN1EARBEAQ1Ty3cMguCQFnMowAABupJREFUIAiCIGiTcIiCIAiCIKh5wiEKgiAIgqDmCYcoCIIgCIKaJxyiIAiCIAhqnnCIOglKGeF7ZtZPlHS3pG2eofhJSWdJGpjNGF0J3YIAjrQLSTdIuj2z725Jv82sT5Y0p53t5G7zQWVoZRy8StJznvJnk6R25WxzG/p0+TQNOiPhEHUeppLe31NgHikZ4mAzGwpMAvr9v41I6loG3Uppp64d7QSdi6k028UaYFRm33CgIWMHo4DVpQhtp40GxwdTcZuS9FbSO59Gm9kwUob2pnbKHQiEQ1TjhENURiRd4TOVRkkLJJ0iablvWy7p7V5vvqSLM8cd8M8xklZKelDSFkkLlZgCDABWSFoh6TTgLGCGpVQXWMps/SsXWSdprkeOHvO3jyLps5LWu34PZWbv8yXNlrQC+I6k90paI+lZ/3yn16uTNCszI5vcUjevN07SWkkbJC1Syu+DpJ2Sbpb0FHCJpCmSnndZ93fw1xO0Ql42S3rx2xBJPSQ1AAdJL697j4scBayRNFzS097+YnmSX2/jW5JWATdIGuE6rwW+kNFrqKR1kja6jMEdfQ6DI8nRpt4MvAocADCzA2a2w2WcJuk3SsmsfyfpXZk25/i4tj3T/reBc9xuvuhj3UwfL5skXduWbr5vpMttdBusb0NOf6Wo/kalyNY5Hf7FBEen0m+GPF4WYCjpzbT9fL0P8Etgoq9fBSzx8nzg4syxB/xzDLCflHuoC7CWNPsB2JmRfQGwuIgeA4FDwHBf/wVwuZf7ZurdAkzO6PMoUOfrJwFdvTwWeMjL15Ny9RT29WlFt37Ak0AvX/8KzW8+3QncmNHhZaC7l3tX+justSVPm/X1lcC5wEdIF6Crgc+TLnIveZ0m4ANe/jpwe+bYH2RkZevNBDZ5+U5ggpe7AT0qfZ5racnTpoA6YBnwEvAT4OMZWctJ0XNIk8cnMm0ucrmnAy9k2nw0c/znSBNOgO7A74FBxXRzW9sOjPRjTgK6tiHnyzRnDKgD6iv93cViROi5fHwIeNDM/gZgZv+Q9H7gk75/AXBrCXLWmdmfASRtJDk4Tx2jLjvMbKOX/+AyAN4t6RagN3AiaTApsMjMDnu5AbjXZ9cGnODbxwJ3mdkhSH1spe33kQaa1T5x6kYaNAo8kCk3AQslLQGWHEsHg7KQt82uJkWCepBsYivwVWAvKTrUQHKMV3n9e0kXrwIPeBst6y0gJQvG5U5Xup3ysJltLUH/oHzkZlNmdljSecBI4MPAbZJGALNIdrbIxyBIzkiBJZYi689LekuR9scBwzIRpAZSXrrXi+i2H9hlZutdt3/6/mJy1gM/VkoIuyQzXgcVJByi8iGS89AWhf2H8NuVHm7tlqnzn0z5MK1/R5uBMyR18R92S1rK6OHl+cCFZtYoaRJptlPgtUz5G8AKM7tI0kDS7BxK66OAx83ssiL7s+18jBQxuAC4SdLQgrMV5EKeNgvpOaJrgTcB3yc5Qqf7ZynPDxVsp6jeZvZzSc+QbGuZpGvM7IkSZAflIVebMjMjJc9dJ+lxUqRoNrDPzIYXaT8rW0XqiBRBX3bERmlMEd2K9btVOS7rXJKdLpA008x+WkSXICfiGaLysRz4lKS+AJL6kC4A433/BJpnODuBEV7+BM0RmLZ4FagHMLNtpNDr1zL3rwfr6P+wqAd2+axkQhv1GoC/eHlSZvtjwHXyh1q9j0foBjwNnC3pHV6np6QhLRuQ1AV4m5mtAG6kOWoV5EduNuusIUUQTzazPX4x2+vy1pjZfuCVzPMUnwFW0QIz2wfslzQ6oyfeh1OB7WY2h5QkeFgJegblIzebkjRA0pmZfcOBFz06s0PSJV5Pks4oVa6zDLjex0okDZHUq43jtwADJI30+vU+TrYqR9IpwB4zmwvcA5xZTHCQHxEhKhNmtlnSN4FVkg6THiKdQgqLTiMN/Fd69bnAI5LWkQaQ11qT2YIfAb+WtMvMPghcA3wXeEHSQVL2+GlHkXET8AzwIimzfH2RereSbpl9CcjOrucBQ4AmSW94P77XUjePPt0nqRCmnkHKvJ2lDviZ3/4QcJtf6IKcyNtmzewVSXtJEc4Ca4GzgUZfnwjcpfTA//ZM+y250vU8yJG3fi8FLnf7/CvpOaQgJ/K0KdJkbZakAcC/XfZ1Xm8C8ENJM0iO1v0021hrNAGHJDWSIul3kG6FbfBJ517gwjb6/bqkS4E7lf7E8i/SIwbzisgZA0xzOz0AXFFC34MOJrLdB0EQBEFQ88QtsyAIgiAIap5wiIIgCIIgqHnCIQqCIAiCoOYJhygIgiAIgponHKIgCIIgCGqecIiCIAiCIKh5wiEKgiAIgqDmCYcoCIIgCIKa539tcG4FQ9VtWQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 582.375x540 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#finding relationship between the columns\n",
    "sns.pairplot(x, hue='result')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "d9ade1fe",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 229
    },
    "id": "d9ade1fe",
    "outputId": "6cd30f7c-26a2-4d56-8351-11dafe3819e8"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>result</th>\n",
       "      <th>countCharacters</th>\n",
       "      <th>countWords</th>\n",
       "      <th>countSentences</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>result</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.384717</td>\n",
       "      <td>0.262984</td>\n",
       "      <td>0.284901</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>countCharacters</th>\n",
       "      <td>0.384717</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.965770</td>\n",
       "      <td>0.638143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>countWords</th>\n",
       "      <td>0.262984</td>\n",
       "      <td>0.965770</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.684541</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>countSentences</th>\n",
       "      <td>0.284901</td>\n",
       "      <td>0.638143</td>\n",
       "      <td>0.684541</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   result  countCharacters  countWords  countSentences\n",
       "result           1.000000         0.384717    0.262984        0.284901\n",
       "countCharacters  0.384717         1.000000    0.965770        0.638143\n",
       "countWords       0.262984         0.965770    1.000000        0.684541\n",
       "countSentences   0.284901         0.638143    0.684541        1.000000"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#find pearson's correlation coefficient\n",
    "x.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "bfc6551d",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 507
    },
    "id": "bfc6551d",
    "outputId": "c7cd5b83-1da0-499c-a38f-c0248c8ab5f8"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 102,
     "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": [
    "#converting it into a heatmap\n",
    "sns.heatmap(x.corr(), annot=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "28ca076e",
   "metadata": {
    "id": "28ca076e"
   },
   "outputs": [],
   "source": [
    "#multi-collinearity in the dataset\n",
    "#all new 3 columns are highly correlated with each other but countCharacters is correlated more with the 'result' than any other column"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b916c85d",
   "metadata": {
    "id": "b916c85d"
   },
   "source": [
    "## Data Preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "78770422",
   "metadata": {
    "id": "78770422"
   },
   "outputs": [],
   "source": [
    "#peforming preprocessing such as tokenization (converting the text into tokens or words), removing special characters,\n",
    "#removing stop words and punctuation and finallying stemming the data.\n",
    "#also, converting to lower case first and then pre-processing the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "727bd8e8",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "727bd8e8",
    "outputId": "7b9c142f-b729-44b6-9e44-40feaa21031e"
   },
   "outputs": [],
   "source": [
    "#downloading the package which contains the stopwords\n",
    "nltk.download('stopwords')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "fb37349b",
   "metadata": {
    "id": "fb37349b"
   },
   "outputs": [],
   "source": [
    "def transform_text (text):\n",
    "    \n",
    "    #converting to lower case\n",
    "    text = text.lower()\n",
    "    \n",
    "    #tokenization\n",
    "    text = nltk.word_tokenize(text)\n",
    "    \n",
    "    #removing special characters\n",
    "    removedSC = list()\n",
    "    for i in text:\n",
    "        if i.isalnum():\n",
    "            removedSC.append(i)\n",
    "            \n",
    "    #updating the text after removed special characters\n",
    "    text = removedSC[:]\n",
    "    \n",
    "    #removing stop words and punctuation characters\n",
    "    removedSWPC = list()\n",
    "    for i in text:\n",
    "        #stopwords.words('english') is a function of 'nltk', returns list of english stop words\n",
    "        #string.punctuation is a part of 'string' module, containing the ASCII punctuation characters\n",
    "        if i not in stopwords.words('english') and i not in string.punctuation:\n",
    "            removedSWPC.append(i)\n",
    "            \n",
    "    #updating the text after removed stop words and punctuation characters\n",
    "    text = removedSWPC[:]\n",
    "    \n",
    "    #stemming the data using 'PorterStemmer' algorithm.\n",
    "    #nltk module provides this class to use.\n",
    "    ps = PorterStemmer()\n",
    "    stemmed = list()\n",
    "    for i in text:\n",
    "        stemmed.append(ps.stem(i))\n",
    "    \n",
    "    text = stemmed[:]\n",
    "    \n",
    "    return \" \".join(text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "6589a86c",
   "metadata": {
    "id": "6589a86c"
   },
   "outputs": [],
   "source": [
    "#function for transforming the text is ready"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "2096abcc",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 310
    },
    "id": "2096abcc",
    "outputId": "f2545dda-3cec-4297-8411-738065335a30",
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\codes\\AppData\\Local\\Temp\\ipykernel_37516\\2432381459.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  x['processed'] = x['input'].apply(transform_text)\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>result</th>\n",
       "      <th>input</th>\n",
       "      <th>countCharacters</th>\n",
       "      <th>countWords</th>\n",
       "      <th>countSentences</th>\n",
       "      <th>processed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>Go until jurong point, crazy.. Available only ...</td>\n",
       "      <td>111</td>\n",
       "      <td>24</td>\n",
       "      <td>2</td>\n",
       "      <td>go jurong point crazi avail bugi n great world...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>Ok lar... Joking wif u oni...</td>\n",
       "      <td>29</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>ok lar joke wif u oni</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>Free entry in 2 a wkly comp to win FA Cup fina...</td>\n",
       "      <td>155</td>\n",
       "      <td>37</td>\n",
       "      <td>2</td>\n",
       "      <td>free entri 2 wkli comp win fa cup final tkt 21...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>U dun say so early hor... U c already then say...</td>\n",
       "      <td>49</td>\n",
       "      <td>13</td>\n",
       "      <td>1</td>\n",
       "      <td>u dun say earli hor u c alreadi say</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>Nah I don't think he goes to usf, he lives aro...</td>\n",
       "      <td>61</td>\n",
       "      <td>15</td>\n",
       "      <td>1</td>\n",
       "      <td>nah think goe usf live around though</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   result                                              input  countCharacters  \\\n",
       "0       0  Go until jurong point, crazy.. Available only ...              111   \n",
       "1       0                      Ok lar... Joking wif u oni...               29   \n",
       "2       1  Free entry in 2 a wkly comp to win FA Cup fina...              155   \n",
       "3       0  U dun say so early hor... U c already then say...               49   \n",
       "4       0  Nah I don't think he goes to usf, he lives aro...               61   \n",
       "\n",
       "   countWords  countSentences  \\\n",
       "0          24               2   \n",
       "1           8               2   \n",
       "2          37               2   \n",
       "3          13               1   \n",
       "4          15               1   \n",
       "\n",
       "                                           processed  \n",
       "0  go jurong point crazi avail bugi n great world...  \n",
       "1                              ok lar joke wif u oni  \n",
       "2  free entri 2 wkli comp win fa cup final tkt 21...  \n",
       "3                u dun say earli hor u c alreadi say  \n",
       "4               nah think goe usf live around though  "
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#will create a new column to store the transformed text -> 'processed'\n",
    "x['processed'] = x['input'].apply(transform_text)\n",
    "\n",
    "#displaying the edited dataframe with a new column 'processed'\n",
    "x.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "52148949",
   "metadata": {
    "id": "52148949"
   },
   "outputs": [],
   "source": [
    "#will be creating word cloud for data visualization to display the most frequently occurring words in the processed dataset.\n",
    "#using 'WordCloud' class\n",
    "\n",
    "wc = WordCloud(width=500, height=500, min_font_size=10, background_color='white')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "475f1006",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 544
    },
    "id": "475f1006",
    "outputId": "4549babd-62f6-46e0-f39d-55bd50eb6f32"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7ff800663550>"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#creating a wordcloud for the SPAM messages\n",
    "spamWC = wc.generate(x[x['result'] == 1]['processed'].str.cat(sep=\" \"))\n",
    "\n",
    "#creating figure and displaying\n",
    "plt.figure(figsize=(12, 6))\n",
    "plt.imshow(spamWC)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "KKjzvZxw9fA7",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 544
    },
    "id": "KKjzvZxw9fA7",
    "outputId": "a2b023fb-f675-4209-c84b-22895c8d2088"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7ff8005bc0d0>"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#creating a wordcloud for the not SPAM messages\n",
    "spamWC = wc.generate(x[x['result'] == 0]['processed'].str.cat(sep=\" \"))\n",
    "\n",
    "#creating figure and displaying\n",
    "plt.figure(figsize=(12, 6))\n",
    "plt.imshow(spamWC)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "kjNkfXx793fG",
   "metadata": {
    "id": "kjNkfXx793fG"
   },
   "outputs": [],
   "source": [
    "#extracting the most common words used in both SPAM and not SPAM messages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "0GM55U9i-rfk",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "0GM55U9i-rfk",
    "outputId": "5071b249-15f8-4def-8882-0fb5d763bea0"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['free',\n",
       " 'entri',\n",
       " '2',\n",
       " 'wkli',\n",
       " 'comp',\n",
       " 'win',\n",
       " 'fa',\n",
       " 'cup',\n",
       " 'final',\n",
       " 'tkt',\n",
       " '21st',\n",
       " 'may',\n",
       " 'text',\n",
       " 'fa',\n",
       " '87121',\n",
       " 'receiv',\n",
       " 'entri',\n",
       " 'question',\n",
       " 'std',\n",
       " 'txt',\n",
       " 'rate',\n",
       " 'c',\n",
       " 'appli',\n",
       " '08452810075over18',\n",
       " 'freemsg',\n",
       " 'hey',\n",
       " 'darl',\n",
       " '3',\n",
       " 'week',\n",
       " 'word',\n",
       " 'back',\n",
       " 'like',\n",
       " 'fun',\n",
       " 'still',\n",
       " 'tb',\n",
       " 'ok',\n",
       " 'xxx',\n",
       " 'std',\n",
       " 'chg',\n",
       " 'send',\n",
       " 'rcv',\n",
       " 'winner',\n",
       " 'valu',\n",
       " 'network',\n",
       " 'custom',\n",
       " 'select',\n",
       " 'receivea',\n",
       " 'prize',\n",
       " 'reward',\n",
       " 'claim',\n",
       " 'call',\n",
       " 'claim',\n",
       " 'code',\n",
       " 'kl341',\n",
       " 'valid',\n",
       " '12',\n",
       " 'hour',\n",
       " 'mobil',\n",
       " '11',\n",
       " 'month',\n",
       " 'u',\n",
       " 'r',\n",
       " 'entitl',\n",
       " 'updat',\n",
       " 'latest',\n",
       " 'colour',\n",
       " 'mobil',\n",
       " 'camera',\n",
       " 'free',\n",
       " 'call',\n",
       " 'mobil',\n",
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       " 'tone',\n",
       " 'help',\n",
       " '0845',\n",
       " '2814032',\n",
       " '16',\n",
       " '1st',\n",
       " 'free',\n",
       " 'tone',\n",
       " 'txt',\n",
       " 'stop',\n",
       " '100',\n",
       " 'date',\n",
       " 'servic',\n",
       " 'cal',\n",
       " 'l',\n",
       " '09064012103',\n",
       " 'box334sk38ch',\n",
       " 'free',\n",
       " 'entri',\n",
       " 'weekli',\n",
       " 'competit',\n",
       " 'text',\n",
       " 'word',\n",
       " 'win',\n",
       " '80086',\n",
       " '18',\n",
       " 'c',\n",
       " 'send',\n",
       " 'logo',\n",
       " '2',\n",
       " 'ur',\n",
       " 'lover',\n",
       " '2',\n",
       " 'name',\n",
       " 'join',\n",
       " 'heart',\n",
       " 'txt',\n",
       " 'love',\n",
       " 'name1',\n",
       " 'name2',\n",
       " 'mobno',\n",
       " 'eg',\n",
       " 'love',\n",
       " 'adam',\n",
       " 'eve',\n",
       " '07123456789',\n",
       " '87077',\n",
       " 'yahoo',\n",
       " 'pobox36504w45wq',\n",
       " 'txtno',\n",
       " '4',\n",
       " 'ad',\n",
       " '150p',\n",
       " 'someon',\n",
       " 'contact',\n",
       " 'date',\n",
       " 'servic',\n",
       " 'enter',\n",
       " 'phone',\n",
       " 'fanci',\n",
       " 'find',\n",
       " 'call',\n",
       " 'landlin',\n",
       " '09111032124',\n",
       " 'pobox12n146tf150p',\n",
       " 'urgent',\n",
       " 'mobil',\n",
       " 'number',\n",
       " 'award',\n",
       " 'prize',\n",
       " 'guarante',\n",
       " 'call',\n",
       " '09058094455',\n",
       " 'land',\n",
       " 'line',\n",
       " 'claim',\n",
       " 'valid',\n",
       " '12hr',\n",
       " 'congrat',\n",
       " 'nokia',\n",
       " '3650',\n",
       " 'video',\n",
       " 'camera',\n",
       " ...]"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#extracting all the words used in SPAM messages\n",
    "spamWords = list()\n",
    "\n",
    "for msg in x[x['result'] == 1]['processed'].tolist():\n",
    "  for word in msg.split():\n",
    "    spamWords.append(word)\n",
    "\n",
    "spamWords"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "Us_mXRt5-ySp",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "Us_mXRt5-ySp",
    "outputId": "672e4846-6246-4585-a7e7-2ff600e21de9"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('call', 320),\n",
       " ('free', 191),\n",
       " ('2', 155),\n",
       " ('txt', 141),\n",
       " ('text', 122),\n",
       " ('u', 119),\n",
       " ('ur', 119),\n",
       " ('mobil', 114),\n",
       " ('stop', 104),\n",
       " ('repli', 103),\n",
       " ('claim', 98),\n",
       " ('4', 97),\n",
       " ('prize', 82),\n",
       " ('get', 74),\n",
       " ('new', 64),\n",
       " ('servic', 64),\n",
       " ('tone', 63),\n",
       " ('send', 60),\n",
       " ('urgent', 57),\n",
       " ('nokia', 57),\n",
       " ('contact', 56),\n",
       " ('award', 55),\n",
       " ('phone', 52),\n",
       " ('cash', 51),\n",
       " ('pleas', 51),\n",
       " ('week', 49),\n",
       " ('win', 48),\n",
       " ('c', 45),\n",
       " ('collect', 45),\n",
       " ('min', 45),\n",
       " ('custom', 42),\n",
       " ('messag', 42),\n",
       " ('guarante', 42),\n",
       " ('per', 41),\n",
       " ('chat', 38),\n",
       " ('tri', 37),\n",
       " ('msg', 35),\n",
       " ('draw', 35),\n",
       " ('number', 35),\n",
       " ('cs', 35)]"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#to count the frequency of the words, we will be using the Counter class to create a dictionary\n",
    "spamWordsDictionary = Counter(spamWords)\n",
    "\n",
    "#to extract the most common words\n",
    "spamWordsDictionary.most_common(40)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "fDKbm3uH_Nph",
   "metadata": {
    "id": "fDKbm3uH_Nph"
   },
   "outputs": [],
   "source": [
    "#converting this dictionary to a dataframe\n",
    "mostCommonSPAM = pd.DataFrame(spamWordsDictionary.most_common(40))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "jBblxZIk_30g",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 591
    },
    "id": "jBblxZIk_30g",
    "outputId": "35d21f65-22df-42ee-e307-d6ca39b06c7e"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plotting a bar plot of the mostCommonSPAM dataframe\n",
    "plt.figure(figsize=(12, 6))\n",
    "sns.barplot(data = mostCommonSPAM, x=0, y=1)\n",
    "plt.xticks(rotation='vertical')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "iHYyTWYDAO2p",
   "metadata": {
    "id": "iHYyTWYDAO2p"
   },
   "outputs": [],
   "source": [
    "#words like 'CALL', 'FREE', '2', 'TXT', 'TEXT', 'UR', 'MOBIL' are the most common words in SPAM texts"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "hD1ryYyPDoUS",
   "metadata": {
    "id": "hD1ryYyPDoUS"
   },
   "source": [
    "## Model Building"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "g4CYS7lVD02K",
   "metadata": {
    "id": "g4CYS7lVD02K"
   },
   "outputs": [],
   "source": [
    "#NaiveBayes classifier works BEST on textual data, so will firstly perform it on the dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "-WxWmcFCEAFI",
   "metadata": {
    "id": "-WxWmcFCEAFI"
   },
   "outputs": [],
   "source": [
    "#we need to give numerical inputs to the classifier model, so will have to convert the 'processed' column into vectors.\n",
    "#using 'bag of words'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "id": "GXzUN--UEznA",
   "metadata": {
    "id": "GXzUN--UEznA"
   },
   "outputs": [],
   "source": [
    "#converting the collection of text into a matrix of token counts\n",
    "cv = CountVectorizer()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "zdPlxYWXE-vm",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "zdPlxYWXE-vm",
    "outputId": "72f25fec-fdb9-416e-e396-d42079ea16ea"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5169, 6708)"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#transforming the data of processed column\n",
    "X = cv.fit_transform(x['processed']).toarray()\n",
    "\n",
    "#printing size of X\n",
    "X.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "id": "UaAee-QhFDdf",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "UaAee-QhFDdf",
    "outputId": "a345bad7-d8e7-42c6-d819-afc691eb5e5a"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 1, ..., 0, 0, 0])"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#storing the values of the 'result' column\n",
    "y = x['result'].values\n",
    "y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "id": "2LZrgCI0FY8y",
   "metadata": {
    "id": "2LZrgCI0FY8y"
   },
   "outputs": [],
   "source": [
    "#splitting the training and testing dataset\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.2, random_state = 49)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "id": "0_3FTO2RHQuv",
   "metadata": {
    "id": "0_3FTO2RHQuv"
   },
   "outputs": [],
   "source": [
    "#creating the objects for the models\n",
    "gnb = GaussianNB()\n",
    "mnb = MultinomialNB()\n",
    "bnb = BernoulliNB()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "id": "A3-_9K4ZH3nO",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "A3-_9K4ZH3nO",
    "outputId": "d328caf1-48cc-404f-ac19-4ed4ab7da539"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.8617021276595744\n",
      "[[774 125]\n",
      " [ 18 117]]\n",
      "0.4834710743801653\n"
     ]
    }
   ],
   "source": [
    "#training the dataset for GaussianNB\n",
    "gnb.fit(X_train, y_train)\n",
    "y_pred1 = gnb.predict(X_test)\n",
    "print(accuracy_score(y_test, y_pred1))\n",
    "print(confusion_matrix(y_test, y_pred1))\n",
    "print(precision_score(y_test, y_pred1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "id": "nt9Ox6u6IDeC",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "nt9Ox6u6IDeC",
    "outputId": "01abc5e4-75b1-4040-f49c-cc79ce0ec76b"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.9700193423597679\n",
      "[[882  17]\n",
      " [ 14 121]]\n",
      "0.8768115942028986\n"
     ]
    }
   ],
   "source": [
    "#training the dataset for MultinomialnNB\n",
    "mnb.fit(X_train, y_train)\n",
    "y_pred2 = mnb.predict(X_test)\n",
    "print(accuracy_score(y_test, y_pred2))\n",
    "print(confusion_matrix(y_test, y_pred2))\n",
    "print(precision_score(y_test, y_pred2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "-Qiq7GWJJSLo",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "-Qiq7GWJJSLo",
    "outputId": "49278f39-e22a-4559-dd8a-2263cba8c19c"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.9642166344294004\n",
      "[[893   6]\n",
      " [ 31 104]]\n",
      "0.9454545454545454\n"
     ]
    }
   ],
   "source": [
    "#training the dataset for BernoulliNB\n",
    "bnb.fit(X_train, y_train)\n",
    "y_pred3 = bnb.predict(X_test)\n",
    "print(accuracy_score(y_test, y_pred3))\n",
    "print(confusion_matrix(y_test, y_pred3))\n",
    "print(precision_score(y_test, y_pred3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "id": "BVi02ol7JYYb",
   "metadata": {
    "id": "BVi02ol7JYYb"
   },
   "outputs": [],
   "source": [
    "#we have to focus mainly on 'precision' value\n",
    "#the max precision we got is 9.45 with 9.64 as accuracy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "id": "m3_35xosKV9Y",
   "metadata": {
    "id": "m3_35xosKV9Y"
   },
   "outputs": [],
   "source": [
    "#using 'TfidfVectorizer' for vectorization \n",
    "tf = TfidfVectorizer()\n",
    "\n",
    "#transforming the data of processed column\n",
    "X = tf.fit_transform(x['processed']).toarray()\n",
    "\n",
    "#storing the values of the 'result' column\n",
    "y = x['result'].values\n",
    "\n",
    "#splitting the training and testing dataset\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.2, random_state = 49)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "id": "2S1dzhqsKjG0",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "2S1dzhqsKjG0",
    "outputId": "2f4b100a-91da-4412-8d58-bf6d01c86c8f"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.8597678916827853\n",
      "[[775 124]\n",
      " [ 21 114]]\n",
      "0.4789915966386555\n"
     ]
    }
   ],
   "source": [
    "#training the dataset for GaussianNB\n",
    "gnb.fit(X_train, y_train)\n",
    "y_pred1 = gnb.predict(X_test)\n",
    "print(accuracy_score(y_test, y_pred1))\n",
    "print(confusion_matrix(y_test, y_pred1))\n",
    "print(precision_score(y_test, y_pred1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "id": "9DsDpIpNK0PX",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "9DsDpIpNK0PX",
    "outputId": "168910f4-2071-49dc-b4a3-340d3065b88a"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.9574468085106383\n",
      "[[899   0]\n",
      " [ 44  91]]\n",
      "1.0\n"
     ]
    }
   ],
   "source": [
    "#training the dataset for MultinomialnNB\n",
    "mnb.fit(X_train, y_train)\n",
    "y_pred2 = mnb.predict(X_test)\n",
    "print(accuracy_score(y_test, y_pred2))\n",
    "print(confusion_matrix(y_test, y_pred2))\n",
    "print(precision_score(y_test, y_pred2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "id": "0qkJKFHZK065",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "0qkJKFHZK065",
    "outputId": "53381466-a601-4735-8730-ca52ad72e152"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.9642166344294004\n",
      "[[893   6]\n",
      " [ 31 104]]\n",
      "0.9454545454545454\n"
     ]
    }
   ],
   "source": [
    "#training the dataset for BernoulliNB\n",
    "bnb.fit(X_train, y_train)\n",
    "y_pred3 = bnb.predict(X_test)\n",
    "print(accuracy_score(y_test, y_pred3))\n",
    "print(confusion_matrix(y_test, y_pred3))\n",
    "print(precision_score(y_test, y_pred3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "id": "S5O70rceK3pQ",
   "metadata": {
    "id": "S5O70rceK3pQ"
   },
   "outputs": [],
   "source": [
    "#as data is IMBALANCED, precision score matters more than accuracy.\n",
    "#using TfidfVectorizer method, we get precision score = 1 for MultinomialNB\n",
    "#so we will use this only"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "id": "gq-hSXHwLjkn",
   "metadata": {
    "id": "gq-hSXHwLjkn"
   },
   "outputs": [],
   "source": [
    "#trying out different CLASSIFIER model for the BEST predictions\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.naive_bayes import MultinomialNB\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.ensemble import AdaBoostClassifier\n",
    "from sklearn.ensemble import BaggingClassifier\n",
    "from sklearn.ensemble import ExtraTreesClassifier\n",
    "from sklearn.ensemble import GradientBoostingClassifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "id": "HspGQxShLn_B",
   "metadata": {
    "id": "HspGQxShLn_B"
   },
   "outputs": [],
   "source": [
    "#creating objects of the classifier models\n",
    "svc = SVC(kernel='sigmoid', gamma=1.0)\n",
    "knc = KNeighborsClassifier()\n",
    "mnb = MultinomialNB()\n",
    "dtc = DecisionTreeClassifier(max_depth=5)\n",
    "lrc = LogisticRegression(solver='liblinear', penalty='l1')\n",
    "rfc = RandomForestClassifier(n_estimators=50, random_state=2)\n",
    "abc = AdaBoostClassifier(n_estimators=50, random_state=2)\n",
    "bc = BaggingClassifier(n_estimators=50, random_state=2)\n",
    "etc = ExtraTreesClassifier(n_estimators=50, random_state=2)\n",
    "gbdt = GradientBoostingClassifier(n_estimators=50,random_state=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "id": "VJbaA2c8LqQV",
   "metadata": {
    "id": "VJbaA2c8LqQV"
   },
   "outputs": [],
   "source": [
    "#creating a dictionary that maps short names to the corresponding classification models.\n",
    "clfs = {\n",
    "    'SVC' : svc,\n",
    "    'KN' : knc, \n",
    "    'NB': mnb, \n",
    "    'DT': dtc, \n",
    "    'LR': lrc, \n",
    "    'RF': rfc, \n",
    "    'AdaBoost': abc, \n",
    "    'BgC': bc, \n",
    "    'ETC': etc,\n",
    "    'GBDT':gbdt,\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "id": "yt0KfuNYL7dq",
   "metadata": {
    "id": "yt0KfuNYL7dq"
   },
   "outputs": [],
   "source": [
    "#creating a function which uses train test split data and performing on model and returning the scores\n",
    "def train_classifier(clf,X_train,y_train,X_test,y_test):\n",
    "    clf.fit(X_train,y_train)\n",
    "    y_pred = clf.predict(X_test)\n",
    "    accuracy = accuracy_score(y_test,y_pred)\n",
    "    precision = precision_score(y_test,y_pred)\n",
    "    \n",
    "    return accuracy,precision"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "id": "pL97j-a4MJ2o",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 744
    },
    "id": "pL97j-a4MJ2o",
    "outputId": "05d730d3-5625-4952-f6c7-7deb6c8a8303"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For  SVC\n",
      "Accuracy -  0.960348162475822\n",
      "Precision -  0.9519230769230769\n",
      "For  KN\n",
      "Accuracy -  0.8974854932301741\n",
      "Precision -  1.0\n",
      "For  NB\n",
      "Accuracy -  0.9574468085106383\n",
      "Precision -  1.0\n",
      "For  DT\n",
      "Accuracy -  0.9410058027079303\n",
      "Precision -  0.8245614035087719\n",
      "For  LR\n",
      "Accuracy -  0.9458413926499033\n",
      "Precision -  0.9072164948453608\n",
      "For  RF\n",
      "Accuracy -  0.9642166344294004\n",
      "Precision -  1.0\n",
      "For  AdaBoost\n",
      "Accuracy -  0.9545454545454546\n",
      "Precision -  0.9\n",
      "For  BgC\n",
      "Accuracy -  0.960348162475822\n",
      "Precision -  0.873015873015873\n",
      "For  ETC\n",
      "Accuracy -  0.9709864603481625\n",
      "Precision -  1.0\n",
      "For  GBDT\n",
      "Accuracy -  0.9497098646034816\n",
      "Precision -  0.9191919191919192\n"
     ]
    }
   ],
   "source": [
    "#taking each classifier algorithm, training and testing data, storing the score values and then printing for each\n",
    "accuracy_scores = []\n",
    "precision_scores = []\n",
    "\n",
    "for name,clf in clfs.items():\n",
    "    \n",
    "    #calling the previously defined function\n",
    "    current_accuracy,current_precision = train_classifier(clf, X_train,y_train,X_test,y_test)\n",
    "    \n",
    "    print(\"For \",name)\n",
    "    print(\"Accuracy - \",current_accuracy)\n",
    "    print(\"Precision - \",current_precision)\n",
    "    \n",
    "    accuracy_scores.append(current_accuracy)\n",
    "    precision_scores.append(current_precision)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "id": "iD0iWdnNMaZj",
   "metadata": {
    "id": "iD0iWdnNMaZj"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Algorithm</th>\n",
       "      <th>Accuracy</th>\n",
       "      <th>Precision</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>KN</td>\n",
       "      <td>0.897485</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NB</td>\n",
       "      <td>0.957447</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>RF</td>\n",
       "      <td>0.964217</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>ETC</td>\n",
       "      <td>0.970986</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>SVC</td>\n",
       "      <td>0.960348</td>\n",
       "      <td>0.951923</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>GBDT</td>\n",
       "      <td>0.949710</td>\n",
       "      <td>0.919192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>LR</td>\n",
       "      <td>0.945841</td>\n",
       "      <td>0.907216</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>AdaBoost</td>\n",
       "      <td>0.954545</td>\n",
       "      <td>0.900000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>BgC</td>\n",
       "      <td>0.960348</td>\n",
       "      <td>0.873016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>DT</td>\n",
       "      <td>0.941006</td>\n",
       "      <td>0.824561</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Algorithm  Accuracy  Precision\n",
       "1        KN  0.897485   1.000000\n",
       "2        NB  0.957447   1.000000\n",
       "5        RF  0.964217   1.000000\n",
       "8       ETC  0.970986   1.000000\n",
       "0       SVC  0.960348   0.951923\n",
       "9      GBDT  0.949710   0.919192\n",
       "4        LR  0.945841   0.907216\n",
       "6  AdaBoost  0.954545   0.900000\n",
       "7       BgC  0.960348   0.873016\n",
       "3        DT  0.941006   0.824561"
      ]
     },
     "execution_count": 161,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#converting the accuracy and precision score values to a dataframe\n",
    "#sorting on the basis of precision value\n",
    "performance = pd.DataFrame({'Algorithm':clfs.keys(),'Accuracy':accuracy_scores,'Precision':precision_scores}).sort_values('Precision',ascending=False)\n",
    "performance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "id": "WV78j7NgMqid",
   "metadata": {
    "id": "WV78j7NgMqid"
   },
   "outputs": [],
   "source": [
    "#precision is 1, we need to maximize the accuracy score.\n",
    "#try using the Voting classifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "id": "84f7456c",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Voting classifier of NB, RF and ETC\n",
    "\n",
    "#creating the objects for the classifier classes\n",
    "mnb = MultinomialNB()\n",
    "etc = ExtraTreesClassifier(n_estimators=50, random_state=2)\n",
    "rfc = RandomForestClassifier(n_estimators=50, random_state=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "id": "ea9192cf",
   "metadata": {},
   "outputs": [],
   "source": [
    "#creating voting object\n",
    "from sklearn.ensemble import VotingClassifier\n",
    "voting = VotingClassifier(estimators=[('rf', rfc), ('nb', mnb), ('et', etc)],voting='soft')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "id": "ba480c35",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "VotingClassifier(estimators=[('rf',\n",
       "                              RandomForestClassifier(n_estimators=50,\n",
       "                                                     random_state=2)),\n",
       "                             ('nb', MultinomialNB()),\n",
       "                             ('et',\n",
       "                              ExtraTreesClassifier(n_estimators=50,\n",
       "                                                   random_state=2))],\n",
       "                 voting='soft')"
      ]
     },
     "execution_count": 166,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#training the data\n",
    "voting.fit(X_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "id": "cded7e12",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy 0.965183752417795\n",
      "Precision 1.0\n"
     ]
    }
   ],
   "source": [
    "y_pred = voting.predict(X_test)\n",
    "print(\"Accuracy\",accuracy_score(y_test,y_pred))\n",
    "print(\"Precision\",precision_score(y_test,y_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "id": "e555ef92",
   "metadata": {},
   "outputs": [],
   "source": [
    "#precision is still 1 but accuracy dropped down."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "id": "5e02d431",
   "metadata": {},
   "outputs": [],
   "source": [
    "#let's try STACKING"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "id": "a2dea307",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Stacking of NB, RF and ETC\n",
    "estimators=[('rf', rfc), ('nb', mnb), ('et', etc)]\n",
    "\n",
    "#most weightage to ETC\n",
    "final_estimator=ExtraTreesClassifier()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "id": "ed9c5b65",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.ensemble import StackingClassifier\n",
    "clf = StackingClassifier(estimators=estimators, final_estimator=final_estimator)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "id": "cf82c7e7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy 0.9854932301740812\n",
      "Precision 0.9838709677419355\n"
     ]
    }
   ],
   "source": [
    "#training the dataset\n",
    "clf.fit(X_train,y_train)\n",
    "y_pred = clf.predict(X_test)\n",
    "\n",
    "#printing the scores\n",
    "print(\"Accuracy\",accuracy_score(y_test,y_pred))\n",
    "print(\"Precision\",precision_score(y_test,y_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "id": "bd87901b",
   "metadata": {},
   "outputs": [],
   "source": [
    "#precision dropped so can't consider it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "id": "c897ef2c",
   "metadata": {},
   "outputs": [],
   "source": [
    "#finally, ETC is giving the best results, so we will be using the ETC classifier."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "id": "74aa58ec",
   "metadata": {},
   "outputs": [],
   "source": [
    "#model is PREPARED.\n",
    "#now we have to host the website, for that pipeling needs to be done\n",
    "#the text which we will get, has to be transformed first, then vectorized and then apply the algorithm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "id": "75dd2f73",
   "metadata": {},
   "outputs": [],
   "source": [
    "#we will pickle 2 files\n",
    "import pickle\n",
    "pickle.dump(tf,open('vectorizer.pkl','wb'))\n",
    "pickle.dump(etc,open('model.pkl','wb'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ba83f737",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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