Salary data.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "38974ec7",
   "metadata": {},
   "source": [
    "## 1. Importing Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "fdd042e8",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from sklearn import preprocessing\n",
    "from sklearn import metrics\n",
    "import seaborn as sns\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.model_selection import train_test_split\n",
    "from matplotlib import pyplot as plt\n",
    "from sklearn.decomposition import PCA\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "from sklearn import preprocessing\n",
    "from mlxtend.plotting import plot_decision_regions"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5bc0093d",
   "metadata": {},
   "source": [
    "## 2. Importing Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a30e0801",
   "metadata": {},
   "outputs": [],
   "source": [
    "test_tmp= pd.read_csv(\"SalaryData_Test(1).csv\")\n",
    "train_tmp= pd.read_csv(\"SalaryData_Train(1).csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c3720292",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_tmp= test_tmp.append(train_tmp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "1d8f40bd",
   "metadata": {},
   "outputs": [],
   "source": [
    "test= test_tmp.copy()\n",
    "train= train_tmp.copy()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "860e7c7e",
   "metadata": {},
   "source": [
    "## 3. Understanding Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "18cd6893",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>workclass</th>\n",
       "      <th>education</th>\n",
       "      <th>educationno</th>\n",
       "      <th>maritalstatus</th>\n",
       "      <th>occupation</th>\n",
       "      <th>relationship</th>\n",
       "      <th>race</th>\n",
       "      <th>sex</th>\n",
       "      <th>capitalgain</th>\n",
       "      <th>capitalloss</th>\n",
       "      <th>hoursperweek</th>\n",
       "      <th>native</th>\n",
       "      <th>Salary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>25</td>\n",
       "      <td>Private</td>\n",
       "      <td>11th</td>\n",
       "      <td>7</td>\n",
       "      <td>Never-married</td>\n",
       "      <td>Machine-op-inspct</td>\n",
       "      <td>Own-child</td>\n",
       "      <td>Black</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>38</td>\n",
       "      <td>Private</td>\n",
       "      <td>HS-grad</td>\n",
       "      <td>9</td>\n",
       "      <td>Married-civ-spouse</td>\n",
       "      <td>Farming-fishing</td>\n",
       "      <td>Husband</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>50</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>28</td>\n",
       "      <td>Local-gov</td>\n",
       "      <td>Assoc-acdm</td>\n",
       "      <td>12</td>\n",
       "      <td>Married-civ-spouse</td>\n",
       "      <td>Protective-serv</td>\n",
       "      <td>Husband</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&gt;50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>44</td>\n",
       "      <td>Private</td>\n",
       "      <td>Some-college</td>\n",
       "      <td>10</td>\n",
       "      <td>Married-civ-spouse</td>\n",
       "      <td>Machine-op-inspct</td>\n",
       "      <td>Husband</td>\n",
       "      <td>Black</td>\n",
       "      <td>Male</td>\n",
       "      <td>7688</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&gt;50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>34</td>\n",
       "      <td>Private</td>\n",
       "      <td>10th</td>\n",
       "      <td>6</td>\n",
       "      <td>Never-married</td>\n",
       "      <td>Other-service</td>\n",
       "      <td>Not-in-family</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   age   workclass      education  educationno        maritalstatus  \\\n",
       "0   25     Private           11th            7        Never-married   \n",
       "1   38     Private        HS-grad            9   Married-civ-spouse   \n",
       "2   28   Local-gov     Assoc-acdm           12   Married-civ-spouse   \n",
       "3   44     Private   Some-college           10   Married-civ-spouse   \n",
       "4   34     Private           10th            6        Never-married   \n",
       "\n",
       "           occupation    relationship    race    sex  capitalgain  \\\n",
       "0   Machine-op-inspct       Own-child   Black   Male            0   \n",
       "1     Farming-fishing         Husband   White   Male            0   \n",
       "2     Protective-serv         Husband   White   Male            0   \n",
       "3   Machine-op-inspct         Husband   Black   Male         7688   \n",
       "4       Other-service   Not-in-family   White   Male            0   \n",
       "\n",
       "   capitalloss  hoursperweek          native  Salary  \n",
       "0            0            40   United-States   <=50K  \n",
       "1            0            50   United-States   <=50K  \n",
       "2            0            40   United-States    >50K  \n",
       "3            0            40   United-States    >50K  \n",
       "4            0            30   United-States   <=50K  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "666548a4",
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>workclass</th>\n",
       "      <th>education</th>\n",
       "      <th>educationno</th>\n",
       "      <th>maritalstatus</th>\n",
       "      <th>occupation</th>\n",
       "      <th>relationship</th>\n",
       "      <th>race</th>\n",
       "      <th>sex</th>\n",
       "      <th>capitalgain</th>\n",
       "      <th>capitalloss</th>\n",
       "      <th>hoursperweek</th>\n",
       "      <th>native</th>\n",
       "      <th>Salary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>39</td>\n",
       "      <td>State-gov</td>\n",
       "      <td>Bachelors</td>\n",
       "      <td>13</td>\n",
       "      <td>Never-married</td>\n",
       "      <td>Adm-clerical</td>\n",
       "      <td>Not-in-family</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>2174</td>\n",
       "      <td>0</td>\n",
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       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
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       "      <th>1</th>\n",
       "      <td>50</td>\n",
       "      <td>Self-emp-not-inc</td>\n",
       "      <td>Bachelors</td>\n",
       "      <td>13</td>\n",
       "      <td>Married-civ-spouse</td>\n",
       "      <td>Exec-managerial</td>\n",
       "      <td>Husband</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>38</td>\n",
       "      <td>Private</td>\n",
       "      <td>HS-grad</td>\n",
       "      <td>9</td>\n",
       "      <td>Divorced</td>\n",
       "      <td>Handlers-cleaners</td>\n",
       "      <td>Not-in-family</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>53</td>\n",
       "      <td>Private</td>\n",
       "      <td>11th</td>\n",
       "      <td>7</td>\n",
       "      <td>Married-civ-spouse</td>\n",
       "      <td>Handlers-cleaners</td>\n",
       "      <td>Husband</td>\n",
       "      <td>Black</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>28</td>\n",
       "      <td>Private</td>\n",
       "      <td>Bachelors</td>\n",
       "      <td>13</td>\n",
       "      <td>Married-civ-spouse</td>\n",
       "      <td>Prof-specialty</td>\n",
       "      <td>Wife</td>\n",
       "      <td>Black</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>Cuba</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   age          workclass   education  educationno        maritalstatus  \\\n",
       "0   39          State-gov   Bachelors           13        Never-married   \n",
       "1   50   Self-emp-not-inc   Bachelors           13   Married-civ-spouse   \n",
       "2   38            Private     HS-grad            9             Divorced   \n",
       "3   53            Private        11th            7   Married-civ-spouse   \n",
       "4   28            Private   Bachelors           13   Married-civ-spouse   \n",
       "\n",
       "           occupation    relationship    race      sex  capitalgain  \\\n",
       "0        Adm-clerical   Not-in-family   White     Male         2174   \n",
       "1     Exec-managerial         Husband   White     Male            0   \n",
       "2   Handlers-cleaners   Not-in-family   White     Male            0   \n",
       "3   Handlers-cleaners         Husband   Black     Male            0   \n",
       "4      Prof-specialty            Wife   Black   Female            0   \n",
       "\n",
       "   capitalloss  hoursperweek          native  Salary  \n",
       "0            0            40   United-States   <=50K  \n",
       "1            0            13   United-States   <=50K  \n",
       "2            0            40   United-States   <=50K  \n",
       "3            0            40   United-States   <=50K  \n",
       "4            0            40            Cuba   <=50K  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "aaab8eb5",
   "metadata": {},
   "outputs": [],
   "source": [
    "str_c= [\"workclass\",\"education\",\"maritalstatus\",\"occupation\",\"relationship\",\"race\",\"sex\",\"native\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "78bf5c38",
   "metadata": {},
   "outputs": [],
   "source": [
    "number= LabelEncoder()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "77f41816",
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in str_c:\n",
    "    train[i]= number.fit_transform(train[i])\n",
    "    test[i]=number.fit_transform(test[i])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "96f5a433",
   "metadata": {},
   "outputs": [
    {
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       "      <th>age</th>\n",
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       "      <th>capitalgain</th>\n",
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       "      <th>Salary</th>\n",
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       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>37</td>\n",
       "      <td>&gt;50K</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>44</td>\n",
       "      <td>2</td>\n",
       "      <td>15</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>7688</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>37</td>\n",
       "      <td>&gt;50K</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>34</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>37</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   age  workclass  education  educationno  maritalstatus  occupation  \\\n",
       "0   25          2          1            7              4           6   \n",
       "1   38          2         11            9              2           4   \n",
       "2   28          1          7           12              2          10   \n",
       "3   44          2         15           10              2           6   \n",
       "4   34          2          0            6              4           7   \n",
       "\n",
       "   relationship  race  sex  capitalgain  capitalloss  hoursperweek  native  \\\n",
       "0             3     2    1            0            0            40      37   \n",
       "1             0     4    1            0            0            50      37   \n",
       "2             0     4    1            0            0            40      37   \n",
       "3             0     2    1         7688            0            40      37   \n",
       "4             1     4    1            0            0            30      37   \n",
       "\n",
       "   Salary  \n",
       "0   <=50K  \n",
       "1   <=50K  \n",
       "2    >50K  \n",
       "3    >50K  \n",
       "4   <=50K  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "bf1e1200",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>workclass</th>\n",
       "      <th>education</th>\n",
       "      <th>educationno</th>\n",
       "      <th>maritalstatus</th>\n",
       "      <th>occupation</th>\n",
       "      <th>relationship</th>\n",
       "      <th>race</th>\n",
       "      <th>sex</th>\n",
       "      <th>capitalgain</th>\n",
       "      <th>capitalloss</th>\n",
       "      <th>hoursperweek</th>\n",
       "      <th>native</th>\n",
       "      <th>Salary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>39</td>\n",
       "      <td>5</td>\n",
       "      <td>9</td>\n",
       "      <td>13</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>2174</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>37</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "      <td>13</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>37</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>38</td>\n",
       "      <td>2</td>\n",
       "      <td>11</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>37</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>53</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>37</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>28</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>13</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>4</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   age  workclass  education  educationno  maritalstatus  occupation  \\\n",
       "0   39          5          9           13              4           0   \n",
       "1   50          4          9           13              2           3   \n",
       "2   38          2         11            9              0           5   \n",
       "3   53          2          1            7              2           5   \n",
       "4   28          2          9           13              2           9   \n",
       "\n",
       "   relationship  race  sex  capitalgain  capitalloss  hoursperweek  native  \\\n",
       "0             1     4    1         2174            0            40      37   \n",
       "1             0     4    1            0            0            13      37   \n",
       "2             1     4    1            0            0            40      37   \n",
       "3             0     2    1            0            0            40      37   \n",
       "4             5     2    0            0            0            40       4   \n",
       "\n",
       "   Salary  \n",
       "0   <=50K  \n",
       "1   <=50K  \n",
       "2   <=50K  \n",
       "3   <=50K  \n",
       "4   <=50K  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "5c406d62",
   "metadata": {},
   "outputs": [],
   "source": [
    "mapping= {' >50K': 1, ' <=50K': 2}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "9bf95902",
   "metadata": {},
   "outputs": [],
   "source": [
    "train= train.replace({'Salary': mapping})\n",
    "test= test.replace({'Salary': mapping})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "40afb5bf",
   "metadata": {},
   "outputs": [],
   "source": [
    "df= train.append(test) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "5967e914",
   "metadata": {},
   "outputs": [],
   "source": [
    "df1= df.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "f14154eb",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   age  workclass  education  educationno  maritalstatus  occupation  \\\n",
       "0   39          5          9           13              4           0   \n",
       "1   50          4          9           13              2           3   \n",
       "2   38          2         11            9              0           5   \n",
       "3   53          2          1            7              2           5   \n",
       "4   28          2          9           13              2           9   \n",
       "\n",
       "   relationship  race  sex  capitalgain  capitalloss  hoursperweek  native  \\\n",
       "0             1     4    1         2174            0            40      37   \n",
       "1             0     4    1            0            0            13      37   \n",
       "2             1     4    1            0            0            40      37   \n",
       "3             0     2    1            0            0            40      37   \n",
       "4             5     2    0            0            0            40       4   \n",
       "\n",
       "   Salary  \n",
       "0       2  \n",
       "1       2  \n",
       "2       2  \n",
       "3       2  \n",
       "4       2  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "762becde",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(45221, 14)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "d9acff54",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>workclass</th>\n",
       "      <th>education</th>\n",
       "      <th>educationno</th>\n",
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       "      <th>native</th>\n",
       "      <th>Salary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>45221.000000</td>\n",
       "      <td>45221.000000</td>\n",
       "      <td>45221.000000</td>\n",
       "      <td>45221.000000</td>\n",
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       "      <td>45221.000000</td>\n",
       "      <td>45221.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>38.548086</td>\n",
       "      <td>2.204507</td>\n",
       "      <td>10.313217</td>\n",
       "      <td>10.118463</td>\n",
       "      <td>2.585148</td>\n",
       "      <td>5.969572</td>\n",
       "      <td>1.412684</td>\n",
       "      <td>3.680281</td>\n",
       "      <td>0.675062</td>\n",
       "      <td>1101.454700</td>\n",
       "      <td>88.548617</td>\n",
       "      <td>40.938038</td>\n",
       "      <td>35.431503</td>\n",
       "      <td>1.752151</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>13.217981</td>\n",
       "      <td>0.958132</td>\n",
       "      <td>3.816992</td>\n",
       "      <td>2.552909</td>\n",
       "      <td>1.500460</td>\n",
       "      <td>4.026444</td>\n",
       "      <td>1.597242</td>\n",
       "      <td>0.832361</td>\n",
       "      <td>0.468357</td>\n",
       "      <td>7506.511295</td>\n",
       "      <td>404.838249</td>\n",
       "      <td>12.007640</td>\n",
       "      <td>5.931380</td>\n",
       "      <td>0.431769</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>17.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>28.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>37.000000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>37.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>37.000000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>47.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>45.000000</td>\n",
       "      <td>37.000000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>90.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>99999.000000</td>\n",
       "      <td>4356.000000</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>39.000000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                age     workclass     education   educationno  maritalstatus  \\\n",
       "count  45221.000000  45221.000000  45221.000000  45221.000000   45221.000000   \n",
       "mean      38.548086      2.204507     10.313217     10.118463       2.585148   \n",
       "std       13.217981      0.958132      3.816992      2.552909       1.500460   \n",
       "min       17.000000      0.000000      0.000000      1.000000       0.000000   \n",
       "25%       28.000000      2.000000      9.000000      9.000000       2.000000   \n",
       "50%       37.000000      2.000000     11.000000     10.000000       2.000000   \n",
       "75%       47.000000      2.000000     12.000000     13.000000       4.000000   \n",
       "max       90.000000      6.000000     15.000000     16.000000       6.000000   \n",
       "\n",
       "         occupation  relationship          race           sex   capitalgain  \\\n",
       "count  45221.000000  45221.000000  45221.000000  45221.000000  45221.000000   \n",
       "mean       5.969572      1.412684      3.680281      0.675062   1101.454700   \n",
       "std        4.026444      1.597242      0.832361      0.468357   7506.511295   \n",
       "min        0.000000      0.000000      0.000000      0.000000      0.000000   \n",
       "25%        2.000000      0.000000      4.000000      0.000000      0.000000   \n",
       "50%        6.000000      1.000000      4.000000      1.000000      0.000000   \n",
       "75%        9.000000      3.000000      4.000000      1.000000      0.000000   \n",
       "max       13.000000      5.000000      4.000000      1.000000  99999.000000   \n",
       "\n",
       "        capitalloss  hoursperweek        native        Salary  \n",
       "count  45221.000000  45221.000000  45221.000000  45221.000000  \n",
       "mean      88.548617     40.938038     35.431503      1.752151  \n",
       "std      404.838249     12.007640      5.931380      0.431769  \n",
       "min        0.000000      1.000000      0.000000      1.000000  \n",
       "25%        0.000000     40.000000     37.000000      2.000000  \n",
       "50%        0.000000     40.000000     37.000000      2.000000  \n",
       "75%        0.000000     45.000000     37.000000      2.000000  \n",
       "max     4356.000000     99.000000     39.000000      2.000000  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.describe(include='all')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "458c9bfc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "age              0\n",
       "workclass        0\n",
       "education        0\n",
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       "occupation       0\n",
       "relationship     0\n",
       "race             0\n",
       "sex              0\n",
       "capitalgain      0\n",
       "capitalloss      0\n",
       "hoursperweek     0\n",
       "native           0\n",
       "Salary           0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3f334b8e",
   "metadata": {},
   "source": [
    "### Finding Correlation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "1e24d56f",
   "metadata": {},
   "outputs": [],
   "source": [
    "corr = df1.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "388a896c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,10))\n",
    "sns.heatmap(corr,annot=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "15db675c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Skew: -0.31062061074424\n",
      "Kurtosis: 0.6350448194491634\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16,5))\n",
    "print(\"Skew: {}\".format(df1['educationno'].skew()))\n",
    "print(\"Kurtosis: {}\".format(df1['educationno'].kurtosis()))\n",
    "ax = sns.kdeplot(df1['educationno'],shade=True,color='g')\n",
    "plt.xticks([i for i in range(0,20,1)])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "322e7618",
   "metadata": {},
   "source": [
    "#### >> The Data is negatively skewed and has low kurtosis value\n",
    "#### >>Most of people have eduction Number of years of education 9 - 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "09fab3d0",
   "metadata": {},
   "outputs": [],
   "source": [
    "dfa= df_tmp[df_tmp.columns[0:13]]\n",
    "obj_colum= dfa.select_dtypes(include='object').columns.tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "4193dd3f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-27-9e26c651d4f9>:3: MatplotlibDeprecationWarning: Adding an axes using the same arguments as a previous axes currently reuses the earlier instance.  In a future version, a new instance will always be created and returned.  Meanwhile, this warning can be suppressed, and the future behavior ensured, by passing a unique label to each axes instance.\n",
      "  plt.subplot(2,2,i)\n"
     ]
    },
    {
     "ename": "ValueError",
     "evalue": "num must be 1 <= num <= 4, not 5",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-27-9e26c651d4f9>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      3\u001b[0m     \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msubplot\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m2\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m2\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m     \u001b[0msns\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcountplot\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mdfa\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mcol\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 5\u001b[1;33m     \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msubplot\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m2\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m2\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m+\u001b[0m\u001b[1;36m2\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      6\u001b[0m     \u001b[0mdf_tmp\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mcol\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mvalue_counts\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnormalize\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mTrue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mbar\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      7\u001b[0m     \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mylabel\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcol\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\matplotlib\\pyplot.py\u001b[0m in \u001b[0;36msubplot\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m   1140\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1141\u001b[0m     \u001b[0mfig\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mgcf\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1142\u001b[1;33m     \u001b[0max\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mfig\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0madd_subplot\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1143\u001b[0m     \u001b[0mbbox\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0max\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mbbox\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1144\u001b[0m     \u001b[0maxes_to_delete\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\matplotlib\\figure.py\u001b[0m in \u001b[0;36madd_subplot\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m   1400\u001b[0m                     \u001b[1;31m# more similar to add_axes.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1401\u001b[0m                     \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_axstack\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mremove\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0max\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1402\u001b[1;33m             \u001b[0max\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0msubplot_class_factory\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mprojection_class\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1403\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1404\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_add_axes_internal\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0max\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\matplotlib\\axes\\_subplots.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, fig, *args, **kwargs)\u001b[0m\n\u001b[0;32m     37\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     38\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfigure\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mfig\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 39\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_subplotspec\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mSubplotSpec\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_from_subplot_args\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfig\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0margs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     40\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mupdate_params\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     41\u001b[0m         \u001b[1;31m# _axes_class is set in the subplot_class_factory\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\matplotlib\\gridspec.py\u001b[0m in \u001b[0;36m_from_subplot_args\u001b[1;34m(figure, args)\u001b[0m\n\u001b[0;32m    687\u001b[0m                     \u001b[0mnum\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnum\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    688\u001b[0m                 \u001b[1;32mif\u001b[0m \u001b[0mnum\u001b[0m \u001b[1;33m<\u001b[0m \u001b[1;36m1\u001b[0m \u001b[1;32mor\u001b[0m \u001b[0mnum\u001b[0m \u001b[1;33m>\u001b[0m \u001b[0mrows\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0mcols\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 689\u001b[1;33m                     raise ValueError(\n\u001b[0m\u001b[0;32m    690\u001b[0m                         f\"num must be 1 <= num <= {rows*cols}, not {num}\")\n\u001b[0;32m    691\u001b[0m                 \u001b[1;32mreturn\u001b[0m \u001b[0mgs\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mnum\u001b[0m \u001b[1;33m-\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m   \u001b[1;31m# -1 due to MATLAB indexing.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mValueError\u001b[0m: num must be 1 <= num <= 4, not 5"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x720 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16,10))\n",
    "for i,col in enumerate(obj_colum,1):\n",
    "    plt.subplot(2,2,i)\n",
    "    sns.countplot(data=dfa,y=col)\n",
    "    plt.subplot(2,2,i+2)\n",
    "    df_tmp[col].value_counts(normalize=True).plot.bar()\n",
    "    plt.ylabel(col)\n",
    "    plt.xlabel('% distribution per category')\n",
    "plt.tight_layout()\n",
    "plt.show() "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "18f5ba8a",
   "metadata": {},
   "source": [
    "#### >> Majority of the workclass is in Private Sector\n",
    "#### >> Also for education mojority of the people have HS graduation or some college degree"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "89974af1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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3n0tKiIjwcXeCT/OhM8TOBCKnyVqCUEQ0AHcBWAhgGoDLRWRar8MWAphsfi0GcLd5exjAvymljgUwD8ANvc79tVJqpvm1PFuvIR80dDTgofcfwszfzcT48vG4bvZ1docUl1fz4rPHfhb/8+r/2B0K0aChlFqulJqilDpaKfVT87Z7lFJ9lpIopa5RSj2W+yjJiZRSfVqMmSAkSl9XizFnEBIRfbwAzef2cXQJkQO5s/jYcwBsVUptBwAReQTAIgAfxhyzCMBDSikFYJWIVIhItVJqP4D9AKCUahWRjYhu7/wQBWDdwXX475f/Gy/vehnBcBAnjDoBX5/7dcyunm13aEl9asqn8IUnvoBtR7bh6Mqj7Q6HiIgSCEfCcIkLmksDEE0QBg22GBOlK2gE2WJMRGTq+vDRJS4YyXfoEVEeymaLcQ2APTG/15m3pXWMiEwAcCKAt2JuvtFsSb5fRIbGe3IRWSwia0RkTX19fT9fQu69uONFnP3g2Rg9ZDTu+dQ9ePryp/HTc36a98lBIDqL8ILJF+D2N2+3OxQiIkqi6xP+Ll6NMwiJ+kMPm1uMmSAkIuoeX6KJhkgkYnc4RJSmbCYI463YVekcIyKlAB4H8E2lVIt5890AjgYwE9Eqw7jZKKXUvUqpWqVUbVVVVZqh26Mj1IFr/n4Nbj71Zlxy7CWoKqnKm03FVi06ZhH+8sFf0BJsSX0wERHZIhAOwKf5un9nBSFR/3BJCRHRx7oqCDWXhrAK2x0OEaUpmwnCOgBjY34fA2Cf1WNExINocvBhpdQTXQcopQ4qpQylVATAfYi2Mg8Kv3jjF5gybApOqjnJ7lD6bXjxcNSOrsWDax+0OxQiIkogGA52bzAGAI+LS0qI+iNoBOH3cEkJEREQ/QDSq3mhida90ZiInCObCcLVACaLyEQR8QK4DMCyXscsA3CVuc14HoBmpdR+iZbN/QHARqXUr2JPEJHqmF8vBrA+ey8hd4yIgXveuQdXHn+l3aEM2IVTLsT/e/v/ITpakoiI8g1bjIkyQzd0bjEmIjJ1/X2huTQYEc4gJHKarCUIlVJhADcCWAFgI4ClSqkNIrJERJaYhy0HsB3AVkSrAa83bz8VwBcBnCMia82v8837bhORD0RkHYCzAXwrW68hl17e+TKGFg3FhIoJdocyYMePPB6GMvDa7tfsDoWIiOLo3WLs0TxskSTqB24xJiL6WFeHgiYal5QQOVA2txhDKbUc0SRg7G33xPysANwQ57zXEX8+IZRSX8xwmHnhofcfwjkTzrE7jIwQEZw/6XzctfounDH+DLvDISKiXnq3GHs1L1uMifqBMwiJaKBEZAGA3wDQAPxeKXVrr/vFvP98AB0ArlFKvZvsXBH5G4Cp5kNUAGhSSs3M9mvpXlLCCkIiR8pmizFZFFERPLPlGZwxYfAk0847+jw8t+U5NHQ02B0KERH1EjT6ziDUDZ2jIYjSFIqE4Hf7ETY4a4uI0iciGoC7ACwEMA3A5SIyrddhCwFMNr8WI7q0M+m5SqnPK6VmmknBxwE8gRzo+gDSJS7OICRyICYI88CGQxtQ6i3FiJIRdoeSMWW+Mpw69lQuKyEiykNdQ8S7aC4NmktDKMI5akTpYIsxEQ3QHABblVLblVI6gEcALOp1zCIAD6moVQAqzLn8Kc81qw8/B+Cv2X4hgDmD0OWFS1wwlMEPHokchgnCPPDSzpdwwsgT7A4j486ffD7ueece/sNARJRnguFoC1Asn+ZjmzFRmrpajLmkhIj6qQbAnpjf68zbrBxj5dzTARxUSm2J9+QislhE1ojImvr6+n6E31MwHIRbc8MlLrjEhYiKDPgxiSh3mCDMAy9sfwHHjzze7jAybsaIGYioCF7e+bLdoRARUYzeW4yB6KISbjImSk/IiLYYcwYhEfVTvLn7vasrEh1j5dzLkaR6UCl1r1KqVilVW1VVlTRQK7pmEAKAJhrbjIkchglCmyml8Pru1zFz1Ey7Q8k4EcGFUy7EHW/dYXcoREQUIxAO9JhBCLCCkKg/uisI2Z5PRP1TB2BszO9jAOyzeEzSc0XEDeAzAP6WwXiTiu1Q0FzcZEzkNEwQ2mx743YUuYswvHi43aFkxXlHn4eXdr6EupY6u0MhIiJTvBZjr+ZF0GAFIVE6dEOHz+2DUoobO4moP1YDmCwiE0XEC+AyAMt6HbMMwFUSNQ9As1Jqv4VzPwFgk1IqZ2/EYpegsYKQyHmYILTZO/vfwZRhU+wOI2uKPcWYf9R8/GbVb+wOhYiITLEtQF28mpcVhERpChkheFweeDQPqwiJKG1KqTCAGwGsALARwFKl1AYRWSIiS8zDlgPYDmArgPsAXJ/s3JiHvww5Wk7SJRwJQxMNQLSCkAlCImdx2x1AoXt779uYNHSS3WFk1SXTLsHXnv0a/uOM/0B5Ubnd4RARFbxgONinxdireTmDkChNekSHR/PA4/J0txsTEaVDKbUc0SRg7G33xPysANxg9dyY+67JXJTWhCNhuCRag8QKQiLnYQWhzVbvW43JwybbHUZWjSodhTk1c3Dn23faHQoREcGcQdirgtCjeVhBSJSmkBGC2+WGR/NwUQkRFTwjYkBzRSsI3S43Ry8QOQwThDZSSuH9A+8P6hbjLlcedyV+tepXaOxstDsUIqKCFzsjqAtbjKm/RGSBiGwWka0icnOc+0VE7jDvXycis1KdKyKVIvKCiGwxvw81b58jImvNr/dF5OKYc142H6vr/hHZfu26oUdbjF1MEBIRhSNhiLlcmS3GRM7DBKGNdjbthM/tQ6W/0u5Qsm5s+VicMvYU/Oy1n9kdChFRweOSEsoUEdEA3AVgIYBpAC4XkWm9DlsIYLL5tRjA3RbOvRnASqXUZAArzd8BYD2AWqXUTAALAPzO3NTZ5Qql1Ezz61BGX2wcoUi0gtDtciNkcAYhERU2Q31cQegSFxOERA7DBKGN1h9aj6OHHm13GDlz9QlX4w/v/QEfHf7I7lCIiApaZ7izbwWhixWE1C9zAGxVSm1XSukAHgGwqNcxiwA8pKJWAagQkeoU5y4C8KD584MALgIApVSHOZgfAIoAqCy9rpSMiAGlFFziYosxERGiYxdiZxAaii3GRE7CBKGNNtRvwLjycXaHkTPDi4fj89M/jxuW34DorF0iIrJDohmEXFJC/VADYE/M73XmbVaOSXbuSKXUfgAwv3e3C4vIXBHZAOADAEtiEoYA8EezvfgWEZH+v6zUQpEQPJoHIsIWYyIi9KwgdLvcrCAkchgmCG30/sH3Mb58vN1h5NQl0y7BjsYdePTDR+0OhYioYAXCAXg1b4/buKSE+ileEq73p4CJjrFybt8DlHpLKTUdwEkAvi8iXauDr1BKHQfgdPPri3EDFlksImtEZE19fX2qp0uoa/4gEH0jzAQhERW6UOTjCkK2GBM5DxOENtpwaAMmDp1odxg55Xa58Y1538A3/vENtOltdodDRFSQAuFAnxZjj4sJQuqXOgBjY34fA2CfxWOSnXvQbEOG+b3PPEGl1EYA7QBmmL/vNb+3AvgLoi3MfSil7lVK1Sqlaquqqiy8xPi6NhgDTBASEQHmFmOJVhBqLo1bjIkchglCm4QjYWw5sqXgKggB4LgRx+H4kcdzYQkRkU2C4fhbjLmkhPphNYDJIjJRRLwALgOwrNcxywBcZW4zngeg2WwbTnbuMgBXmz9fDeApADCPdZs/jwcwFcBOEXGLyHDzdg+ACxBdaJI1hjI+nrXFbZ1ERAhHwj1mEPK6SOQsTBDaZNuRbRhePBx+j9/uUGzx1RO/it+u/i32t+63OxQiooITMPq2GLtdblYQUtrM+X83AlgBYCOApUqpDSKyRESWmIctB7AdwFYA9wG4Ptm55jm3ApgvIlsAzDd/B4DTALwvImsBPAngeqVUAwAfgBUisg7AWgB7zefKGiPy8awtDuMnIupZQcgWYyLncdsdQKHa2LARE8on2B2GbapKqnDuxHPx61W/xm3zb7M7HCKighIIB+B19Z1ByCUl1B9KqeWIJgFjb7sn5mcF4Aar55q3HwZwbpzb/wTgT3FubwcwO93YByKiIj1mbbGVjogKXViF4XdFC2A0Fz84IXIaVhDaZFPDJtQM6b3kr7BcOu1S3PfufWgJttgdChFRQYnXYuxxedAZ7rQpIiLniW0xdomLb4SJqOCFDbYYEzkZE4Q2+bD+Q4wdMjb1gYNYdVk1Thh5Ah778DG7QyEiKihBI9i9fbWLV/MyQUiUBiPSM0EYURGbIyIispehei4pYYKQyFmYILTJxoaNGFc+zu4wbHfOxHPwwNoH7A6DiKigBMJ9ZxB6NS9nEBKlIfaNMFuMiYjMJSUuVhASORUThDZQSmHL4S0YW17YFYQAMG/MPHxw8APUtdTZHQoRUcHQw3rfFmPNg0CICUIiq/rMIGSLMREVuHAk3KOCkB+cEDkLE4Q2qO+oh0BQ7iu3OxTbeTUvThl3Cp7c+KTdoRARFYygEYxbQRg0uKSEyKreLcZ8I0xEhS72usgKQiLnYYLQBpsaNmF8xXiIiN2h5IXZ1bPx7JZn7Q6DiKhgxG0xdnEGIVE6YpeUaKJxBiERFbywCkNzfTx6gQlCImdhgtAGmxs2Y8yQMXaHkTdmV8/GG3veQDDMyhUiolzQDT3ukhLOICSyLrZSRkTYYkxEBa9Hi7FovC4SOQwThDbYdHgTRpeNtjuMvFFeVI6JFRPx+u7X7Q6FiKgg6EbfGYRezcsPaojSEFGRHpUybDEmokJnRGKWN7lYQUjkNEwQ2mBzw2bUDKmxO4y8cuKoE/HP7f+0OwwiooIQNIJ9Kgg9mocVhERpMJQBQXRcDJeUEBGZW4xjZrMyQUjkLEwQ2mDL4S0YU8YW41jTR0zHa7tfszsMIqKCEDJCfWYQelweLikhSgOXlBAR9dR7SQmvi0TOwgRhjhkRA7uad7GCsJdpVdPw3oH3EDJCdodCRDSoGRGjx3KFLh7NAz2s2xQVkfMYyujRYswlJURU6GKvi9xiTOQ8TBDm2O7m3RjqH4oid5HdoeSVUm8paspqsPbAWrtDISIa1EKRELwuL0Skx+1ezQs9wgQhkVV9KgjZYkxEBS62xVhzMUFI5DRMEObYliNbuME4gWlV0/CvPf+yOwwiokEtZIT6LCgBALfLzSUlRGmIqEjPGYRspSOiAhdbQSgiTBASOQwThDm25fAW1JSxvTieY6uO5SZjIqIs0w29z4ISIDqDUDdYQUhkVe8WY1YQElGhC0fC3VuMNdF4XSRyGCYIc2zz4c2oLq22O4y8NKVyCt7Z/47dYRARDWq6ocetIPRoTBASpSO2xVhEOIOQiAqeETF6JAhZQUjkLEwQ5thHhz/igpIExpWPw8H2g2gONNsdChHRoKUbOtwud5/bWUFIlJ7YZT8usMWYiCh2BqFLXEwQEjkME4Q5tr1xO1uME9BcGiZXTsa7+9+1OxQiokErWQVhKMJN8kRWRVSES0qIiGJEVOTjLcYujR+cEDkME4Q5ZEQM7G7ejeoythgnMqlyEtuMiYiyKFEFodvlhm7oUErZEBWR8xgRAy7EJAj5RpiIChwrCImcjQnCHKprqUN5UTmK3EV2h5K3JlVOwtt737Y7DCKiQSvRkhKXuNhmTJQGQxlwuVhBSETUxVAfzyBkgpDIeZggzKFtjdswZsgYu8PIa1OGTcF7B96zOwwiokErFAnFrSAEuKiEKB29Kwi5pISI+kNEFojIZhHZKiI3x7lfROQO8/51IjLLyrkicpN53wYRuS0XryW2gpBLSoicJ/47BMqKrUe2YnTpaLvDyGvjysehrqUO7Xo7SrwldodDRDToJJpBCABelxdBI4gylOU4KiLniahIdwWhiLDFmIjSJiIagLsAzAdQB2C1iCxTSn0Yc9hCAJPNr7kA7gYwN9m5InI2gEUAjldKBUVkRC5ejxExeswgZIKQyFlYQZhDW49sxcjSkXaHkdfcLjcmVkzEB4c+sDsUIqJBKdEMQiBaQRgMB3McEZEzGarXDEK2GBNR+uYA2KqU2q6U0gE8gmhiL9YiAA+pqFUAKkSkOsW5XwNwq1IqCABKqUO5eDERFeluMdZE4/IzIodhgjCHNh/ejNFlrCBM5aihR2HtgbV2h0FENCglmkEIsMWYKB1GxOi5xZgVhESUvhoAe2J+rzNvs3JMsnOnADhdRN4SkVdE5KR4Ty4ii0VkjYisqa+vH8DLiOKSEiJnY4Iwh3Y07kBNWe/rPfU2cehEvLefcwiJiLIhWQWhV4u2GBNRaoYy+EaYiAZK4tymLB6T7Fw3gKEA5gH4LoClItLneKXUvUqpWqVUbVVVlfWoEzBUzxZjfnBC5CxMEObQruZdGFU6yu4w8t6koZPw7oF37Q6DiGhQSlpByC3GRJbFziDkkhIi6qc6AGNjfh8DYJ/FY5KdWwfgCbMt+W0AEQDDMxh3XLGV1WwxJnIeJghzpLGzEUbEwBDfELtDyXtHVx6ND+s/5CdORERZoBt696f7vXEGIZF1RsSAmAU8nEFIRP20GsBkEZkoIl4AlwFY1uuYZQCuMrcZzwPQrJTan+LcvwM4BwBEZAoAL4CGbL8YQxndMwhdLlZWEzkNtxjnyPbG7RgzZAziVHZTL6XeUlT6K7H1yFZMHT7V7nCIiAaVpEtKXB62GBNZxBZjIhoopVRYRG4EsAKABuB+pdQGEVli3n8PgOUAzgewFUAHgC8lO9d86PsB3C8i6wHoAK5WSvVuXc642BmEmrDFmMhpmCDMkR1NO9henIZJQyfh/YPvM0FIRJRhISOUNEHIFmMia/osKWEFIRH1g1JqOaJJwNjb7on5WQG4weq55u06gCszG2lqERXpMYOQH5wQOUtWW4xFZIGIbBaRrSJyc5z7RUTuMO9fJyKzzNvHishLIrJRRDaIyDdizqkUkRdEZIv5fWg2X0Om7GjcgZElI+0OwzG4qISIKDuSVhCyxZj6ob9/7yU7N9HfeyIyR0TWml/vi8jFMefMFpEPzMe6I95A/kyKqEiPBCFnEBJRoQtHwh+3GLOymshxspYgFBENwF0AFgKYBuByEZnW67CFACabX4sB3G3eHgbwb0qpYxHdvHRDzLk3A1iplJoMYKX5e97bemQrKwjTcPTQo/HO/nfsDoOIaNBJlSBkBSGlYyB/76U4N9Hfe+sB1CqlZgJYAOB3ItL1H/Td5uN3PdeCjL7YXnq3GLOVjogKmVKqxwcnmmisrCZymGxWEM4BsFUptd0scX4EwKJexywC8JC5XWkVgAoRqVZK7VdKvQsASqlWABsB1MSc86D584MALsria8iYbY3bMKqMCUKrjq48GusOrrM7DCKiQSdZgtDtcnMGIaWr33/vpTg37t97SqkOpVRXSUoRAAUA5uMNUUq9abbjPYQs/43Yu8WYlTJEVMi6PjTpKt7WXNxiTOQ02UwQ1gDYE/N7HT5O8lk+RkQmADgRwFvmTSPNrU0wv4+I9+QislhE1ojImvr6+v6+hozZ2bQT1aXVdofhGCNLRiIQDuBg20G7QyEiGlRSLilhizGlZyB/7yU7N+HfeyIyV0Q2APgAwBIzYVhjnp8sjq7zM/I3oqGM7jfCnEFIRIXOiHy8wRiIVhDygxMiZ8lmgjDe3Jfem5OSHiMipQAeB/BNpVRLOk+ulLpXKVWrlKqtqqpK59SMU0qhrqWOMwjTICKYOnwq24yJiDIsaAS7B4j3xiUl1A8D+XvPyrl9D1DqLaXUdAAnAfi+iBSl81iZ+huxTysdW4yJqIAZyujx9wUThETOk80EYR2AsTG/jwGwz+oxIuJBNDn4sFLqiZhjDpptJF3tJIcyHHfG1XfUw+/2w+/x2x2Ko0waOglr9q2xOwwiokFFN3R4XJ6497k1thhT2gby916yc1P+vaeU2gigHcAM87HGpIgjo4yIAZf5p7SIcEkJERW02AUlQLTFmB+cEDlLNhOEqwFMFpGJIuIFcBmAZb2OWQbgKnO73TwAzUqp/ebWuT8A2KiU+lWcc642f74awFPZewmZsbt5N+cP9sPkYZOxeu9qu8MgIhpU2GJMGdbvv/dSnBv37z3zWLf583gAUwHsNB+vVUTmmX9HXoUs/43YZ0kJW4yJqIAZEVYQEjld/HcIGaCUCovIjQBWANAA3K+U2iAiS8z77wGwHMD5ALYC6ADwJfP0UwF8EcAHIrLWvO0HSqnlAG4FsFREvgJgN4DPZus1ZMqupl1sL+6HKcOm4N537rU7DCKiQSVZBaHm0thiTGkZyN97ic41HzrR33unAbhZREIAIgCuV0o1mPd9DcADAPwAnjO/ssaIfDyDkC3GRFTowpFw94cmAJc3ETlR1hKEAGAm9Jb3uu2emJ8VgBvinPc64s+SgVLqMIBzMxtpdu1u3o2qYnvnIDpRdWk1OkIdONh2ECNLmWAlIsqEYDgIvz/+yAuPy8MWY0pbf//eS3SueXvcv/eUUn8C8KcEj7UG0XbjnDDUxwP5XeJigpCICpqhjB4dCppLY2U1kcNks8WYTDubd6KqhAnCdIkIjh1+LN7e+7bdoRDZQkQWiMhmEdkqIjfHuX+RiKwTkbXmRs7T7IiTnEWPJK4gZIsxkXWxFYQuF1uMiaiw9a4gZIsxkfMwQZgDOxp3sMW4n44Zfgze2POG3WEQ5ZyIaADuArAQwDQAl4vItF6HrQRwglJqJoAvA/h9ToMkRwqGgwlnELo1NwJGIMcRETlTjxmEYIKQiAqbETF6LClhizGR8zBBmAO7m3ezRbafpo+Yjtd2v2Z3GER2mANgq1Jqu1JKB/AIgEWxByil2szWPQAoAaBAlEKyGYSsICSyLvbNMFuMiajQhSPhnktKuMWYyHGYIMyBPS17MKJkhN1hONKxw4/F2gNrETJCdodClGs1APbE/F5n3taDiFwsIpsAPItoFWEfIrLYbEFeU19fn5VgyTl0Q+/xB3wsr+blDEIii8Iq3HOLMd8IE1EBi53LCrDFmMiJmCDMss5QJ9qCbagoqrA7FEcq8ZZgzJAxWHtgrd2hEOVavEVNfSoElVJPKqWOAXARgP+J90BKqXuVUrVKqdqqKs5DLXShSChhBaHb5WYFIZFFERX5OEHIGYREVODCkXDPBCErCIkchwnCLNvXug9VJVU9BrZSeqZXTccru16xOwyiXKsDMDbm9zEA9iU6WCn1KoCjRWR4tgMjZ9MNHW4t/gxCj8YWYyKrYpeUaKIhoiI2R0REZB8jYvR4z+sSF8KKFYRETsKsVZZ1JQip/2aOmokV21bYHQZRrq0GMFlEJoqIF8BlAJbFHiAik8R8dyoiswB4ARzOeaTkKClnELLFmMiS2BmEAmGlDBEVNEMZPWcQCisIiZyGCcIs29u6F8P9LOgZiJmjZmJV3Srohm53KEQ5o5QKA7gRwAoAGwEsVUptEJElIrLEPOwSAOtFZC2iG48/H7O0hCgu3dATbjG2uqTk7b1vs1qKCl6PGYRsMSaiAheOhHtUEGouziAkchomCLNsb8teDPUPtTsMRxviG4Jx5ePwVt1bdodClFNKqeVKqSlKqaOVUj81b7tHKXWP+fP/KqWmK6VmKqVOVkq9bm/E5ARJKwg1D/RI6g9jFvx5AVbVrcp0aESOEolE4HJF/5TWRGOCkIgKmhFhBSGR0zFBmGV7WvZgmH+Y3WE43syRbDMmIsqEkBEaUAVhm96GxkAjVm5fmY3wiBzDUAZc+HiLMatqiaiQxasg5AcnRM7CBGGW1bXUYXgxW4wHau6YuVi2eVnqA4mIKKmkLcZa6hmEe5r3AABe2P5CxmMjchJDfTyQX4QzCImosBnK6LnFWNhiTOQ0TBBmGROEmTG9ajr2NO/pfmNKRET9oxs6PFriJSWp5r3uadmDGVUz8O7+d9EZ6sxGiESOYEQMthgTEZnCkXCPFmOXcDYrkdMwQZhl+9v2M0GYAZpLw9wxc/HMR8/YHQoRkaOFI+GkFYR6OEWCsHkPxlWMw8ShE/HO/neyESKRI0RU5OMlJeJiBSERFbTYze6A2WLM6yKRozBBmEVKKRxsO8gEYYbMHTMXT2x8wu4wiIgcLemSElfqFuPdzbsxzD8Mw/3DUd9en40QiRzBiPScQchKGSIqZH1mELLFmMhxmCDMosOdh+F3++Fz++wOZVCYVzMPq+pWobGz0e5QiIgcKxRJsqRES91ivLt5N6pKqlDiLUFToCkLERI5Q1iFu1uMXeKCUsrmiIiI7NNnBiGXlBA5DhOEWbS/le3FmeT3+DFr9CwuKyEiGoCQERrQDMLdLbtRVVyFYk8xE4RU0IyIwRZjIiJTOPLxhyZA9LrICkIiZ2GCMIsOth/EUP9Qu8MYVE4bexqWblhqdxhERI6klIJu6D0+4Y9lpYKwrrkOI0pGMEFIBS+iIt3/W2KLMREVutixC0D0uijghnciJ2GCMIsOth3E0CImCDPp5LEn49Xdr6I12Gp3KEREjmMoAyLSY8tgrFQzCJVS2Nu6FyNKRqDUW4rGAEc+UOEyIgYEAoAJQiIiQxl9/r5gmzGRszBBmEUH2g6gvKjc7jAGlVJvKY4bcRyWb1ludyhERI6TbEEJAHg1L3RDTzhLrT3UjnAkjBJPCUo8JUwQUkEzlNHdTqeJhoiK2BwREZF9ei8pAaLXRlYQEjkHE4RZdKDtACqKKuwOY9A5deypbDMmIuqHZPMHgegn/QJJODOoJdiCIb4hEBGUekvZYkwFLXYgvwjb6IiosBkRo88IE83FTcZETsIEYRbtb9vPFuMsOHXcqXhh+wsIhAN2h0JE5CipKgiBaBVhojbjlmALSrwlAMAEIRW8SCTSc0kJ2+iIqB9EZIGIbBaRrSJyc5z7RUTuMO9fJyKzUp0rIj8Skb0istb8Oj/br6P3khKA10Yip2GCMIsOtB1Apb/S7jAGnYqiChxdeTRe2fmK3aEQETmKbuhwu9xJj/FpPgTDSRKEnmiCsMRbwgQhFbSumZ6A2WIcYYsxEaVHRDQAdwFYCGAagMtFZFqvwxYCmGx+LQZwt8Vzf62Umml+ZX0+U2xVdRe3uFldTeQgTBBmEbcYZ89Jo0/Cso+W2R0GEZGj6IYOr+ZNeoxH8ySs0G4JtqDYUwwgWkHYHGjOeIxEThH7ZphVMkTUT3MAbFVKbVdK6QAeAbCo1zGLADykolYBqBCRaovn5ky8GYQul4stxkQOwgRhFtW317PFOEtOHnMynt78dMJB+kRE1JelCkK3L2mLcWyCsCXYkvEYiZzCiBg9Woy5pISI+qEGwJ6Y3+vM26wck+rcG82W5PtFJO6bUhFZLCJrRGRNfX19f18DgJ7XxC6acIsxkZMwQZglERXB4c7DrCDMkgkVExCOhLGpYZPdoRAROUYoEko9g9DltVRBWOIpQaveyqQIFSxDGZxBSEQDJXFu610BkeiYZOfeDeBoADMB7Adwe7wnV0rdq5SqVUrVVlVVWQo4kbhbjF3cYkzkJEwQZsnhjsMo9ZSmrNSg/hERzK6ejZU7VtodChGRY+iGDreW/N8lj+ZJOoPQ7/EDiP7R73f70aa3ZTxOIieIqAgrCIlooOoAjI35fQyAfRaPSXiuUuqgUspQSkUA3IdoO3JWxZtB6BK2GBM5CROEWXKw/SAqi7mgJJtmjpqJFVtX2B0GEZFjZGKLcbG7uPv3Ml8Z5xBSwerdYswqGSLqh9UAJovIRBHxArgMQO9B68sAXGVuM54HoFkptT/ZueaMwi4XA1if7RcSt4KQLcZEjsIEYZYcbDuIyiImCLPpxOoT8eruV/mpFBGRRVZmECZbUtIUaOpuMQaAUk8pNxlTwWKLMRENlFIqDOBGACsAbASwVCm1QUSWiMgS87DlALYD2IpoNeD1yc41z7lNRD4QkXUAzgbwrWy/lrgzCNliTOQo7H/NkoaOBpQXldsdxqBW6a/EyJKRWLNvDeaNmWd3OEREeS9khFImCL2aN2GLcXOwGaWe0u7fS31MEBIgIgsA/AaABuD3Sqlbe90v5v3nA+gAcI1S6t1k54pIJYC/AZgAYCeAzymlGkVkPoBbAXgB6AC+q5R60TznZQDVADrNpz5PKXUoO68aiER6thhzcRoR9YdSajmiScDY2+6J+VkBuMHquebtX8xwmCnF3WLMFmMiR2EFYZY0dDSgzFdmdxiD3nEjjsOru161OwwiIkfQDR0eLXmLsceVuIKwOdCMYi8rCOljIqIBuAvAQgDTAFwuItN6HbYQwGTzazGiw/NTnXszgJVKqckAVpq/A0ADgAuVUscBuBrAn3o91xVKqZnmV9aSg0B0BmHXvC1WEBJRoTOUAZeLLcZETsYEYZbUd9RjiHeI3WEMetNHTMfLO1+2OwwiIkew0mKcagZhbAVhsbcYzUHOICxwcwBsVUptV0rpAB4BsKjXMYsAPKSiVgGoMOdjJTt3EYAHzZ8fBHARACil3lNKdQ3w3wCgSER8WXptSRnKQLQ4kjMIiYjCkXCfJSWaS2MFIZGDMEGYJfXt9RhSxARhth0/8ni8WfcmNwcSEVmgGzrckmIGoSv5FuPYGYTF7mIuKaEaAHtifq8zb7NyTLJzR5pD+GF+HxHnuS8B8J5SKvY/2D+KyFoRuUW6sne9iMhiEVkjImvq6+uTv7okes8gVFBsMyaigpWoxZgfnhA5BxOEWXKo4xDKfZxBmG3Di4ejzFuGD+s/tDsUIqK8F4qknkGYbElJS7AFJd6S7t99bh86Qh0ZjZEcJ14SrneWLNExVs6N/6Qi0wH8L4DrYm6+wmw9Pt38ijuDSyl1r1KqVilVW1VVZeXp4jIiRne1jIjAJS5+YElEBSscCUNz9aogZIsxkaMwQZglDe0NTBDmyHEjjsPru1+3OwwiorynGzrcmoUKwgQtxq16a48KQp/GBCGhDsDYmN/HANhn8Zhk5x4025Bhfu+eJygiYwA8CeAqpdS2rtuVUnvN760A/oJoC3PWRFSkR7UM5xASUSGL12LMJSVEzsIEYZY0dHKLca5MHT4V/9rzL7vDICLKe7qh9/njvTe35k5YQdgabEWJp2cFYXuoPaMxkuOsBjBZRCaKiBfAZQCW9TpmGYCrJGoegGazbTjZucsQXUIC8/tTACAiFQCeBfB9pdQbXU8gIm4RGW7+7AFwAYD1GX+1MWJnEAJspSOiwhY7dqELr4tEzsIEYZYc7jjMCsIcmVY1DavqVtkdBhFR3rO0pMTljTuDUCmFNr0Nfo+/+zaf24d2nQnCQqaUCgO4EcAKABsBLFVKbRCRJSKyxDxsOYDtALYCuA/A9cnONc+5FcB8EdkCYL75O8zjJwG4xZw1uFZERgDwAVghIusArAWw13yurIlEIj0S7mylI6JCFjbiLynhdZHIOZK/S6B+UUrhSOcRVhDmyMSKidjXug+NnY0Y6h9qdzhERHkrZKSeQZiogjBoBCEi8Gre7tuKtCLUB/u/5IEGB6XUckSTgLG33RPzswJwg9VzzdsPAzg3zu0/AfCTBKHMth71wPWulmGlDBEVsrAKw+/y97hNE24xJnISVhBmQUeoAyKCIneR3aEUBM2l4diqY/HW3rfsDoWIKK9ZrSCMlyBsCbag1Fva47YidxFbjKlg9Z5BqLk0LikhooIVNrjFmMjpLCUIReRxEfmUiDChaEFDRwOGFrGSLZemDpuKN/e8aXcYRHHxGkr5wsoMQo/mQcCInyCMnT8IcIvxYMNrVXr6VBCCS0qICl0hX0cNZfRtMWYFIZGjWL1w3Q3gCwC2iMitInJMFmNyvIYOLijJtWOGH4M365ggpLzFayjlhaARTLnF2Kt50Rnq7HN7S7ClxwZjwKwg5AzCwYTXqjT02WLsYqUMERXudTQcCcPl6lVB6OIHJ0ROYilBqJT6p1LqCgCzAOwE8IKI/EtEvmRuiqMYDR0NXFCSY1OHTcU7+99BdMwRUX7hNZTyRcgIweNK/p+cV/MiaPRdUtKmt/VJELKCcHDhtSo9RqRnBSGXlBBRIV9Hw5E4S0pE4wcnRA5iufRZRIYBuAbAVwG8B+A3iF74XshKZA7GBGHuVZVUwe1yY2fTTrtDIYqL11DKB0EjmHIGocfliTuDsPcGYyC6pIQJwsGF1yrr+lQQioszCImoYK+jvT80AaLXRbYYEzmHpS3GIvIEgGMA/AnAhUqp/eZdfxORNdkKzqkOdx5Gma/M7jAKzjHDj8HqfasxcehEu0Mh6oHXUMoXlpaUaPGXlLTpbX2Wb/ncPnSG+7YjkzPxWpWeeAlCVsoQFbZCvo6GVRiaq2cFoUvYYkzkJJYShAB+r5RaHnuDiPiUUkGlVG0W4nK0I51H+mx6pOybXDkZq+pW4XPTP2d3KES98RpKeSFoBPsk+XrzaB4Ew/FbjP3uXhWE7qK48wrJsXitSkOfJSV8I0xEBXwdZYsxkfNZbTH+SZzbuBEigcOdh5kgtMHUYVPx1t637A6DKB5eQykvWJlB6NHitxi36+19kotFbrYYDzK8VqWhdzsdKwiJCAV8HTUifbcYu1xsMSZykqQVhCIyCkANAL+InAhAzLuGAChOeGKBO9xxGOMrxtsdRsGZOnwq3n/l/eg/Tr3K24nswGso5Rvd0C1tMU60pCRegjBeMpGchdeq9CmloKB6LilxcUkJUaHiddTcYtx7BiFYWU3kJKlajD+J6IDVMQB+FXN7K4AfpHpwEVmA6FBWDdFy61t73S/m/ecD6ABwjVLqXfO++wFcAOCQUmpGzDk/AnAtgHrzph/0LuO225HOIzhuxHF2h1FwhviGoNJfiU0NmzB9xHS7wyECBngNJco0K0tKvC5v3BbjVr21T4LQ4/JAN3R+MON8vFalKaIiEAiif8pGcUkJUUEr+OtovL8FNBdbjImcJOm7BKXUgwAeFJFLlFKPp/PAIqIBuAvAfAB1AFaLyDKl1Icxhy0EMNn8mgvgbvM7ADwA4E4AD8V5+F8rpX6ZTjy5dKTzCEp9bDG2Q9eiEiYIKR8M5BpKlA1WWoy9mvUEoYjA7/GjI9TB5VwOxmtV+gzV942wC2wxJipUvI5Gl5T0riAUEbYYEzlIqhbjK5VSfwYwQUS+3ft+pdSv4pzWZQ6ArUqp7eZjPQJgEYDYBOEiAA8ppRSAVSJSISLVSqn9SqlXRWRCmq8nLzQFmlDm5RslO0yqnIS3976Na2ZeY3coRAO9hhJlnJUtxh7NE7fFuDXYiqqSqj63d80hZILQuXitSl/v+YNAdNYWW+mIChOvowlmEHJ5E5GjpFpSUmJ+LwVQFucrmRoAe2J+rzNvS/eYeG4UkXUicr+IDI13gIgsFpE1IrKmvr4+3iFZ0xhoxBDfkJw+J0UdM/wYrKpbZXcYRF0Gcg0lyjjd0C1VEMabKxhvizHARSWDBK9VaTJUgjfCrCAkKlQFfx0NR8JwuXqmFzTRWEFI5CCpWox/Z37/7348tsS5TfXjmN7uBvA/5nH/A+B2AF/u8yBK3QvgXgCora1N9ZgZo5RCc6CZW4xtMrlyMjY1bIJu6PBqXrvDoQI3wGsoUcbphp5yVmDXXMHeWvVWJggHKV6r0hdRkT4VhJponEFIVKB4HeUHJ0SDQaoKQgCAiNwmIkNExCMiK0WkQUSuTHFaHYCxMb+PAbCvH8f0oJQ6qJQylFIRAPch2sqcN9pD7XC73ExO2cTv8WNs+VisO7jO7lCIuvXzGkqUcaFI6hmEHi1+grBNb4Pf0zdB6Hf7mSAcJHitsi5ei7GIsJWOqMAV8nU0HAn3SRBqwu3uRE5iKUEI4DylVAuiW4XrAEwB8N0U56wGMFlEJoqIF8BlAJb1OmYZgKskah6AZqXU/mQPKiLVMb9eDGC9xdeQE42dbC+225RhU/D23rftDoMoVn+uoUQZpxs63FqKLcaaN+4Mwna9PW4Foc/tY4Jw8OC1yiJWyhBRAgV7HY23xdglLrYYEzmI1QRhV7nB+QD+qpQ6kuoEpVQYwI0AVgDYCGCpUmqDiCwRkSXmYcsBbAewFdFqwOu7zheRvwJ4E8BUEakTka+Yd90mIh+IyDoAZwP4lsXXkBOcP2i/KcOm4M26N+0OgyhW2tdQomywssXY4/IgZIQQ3R/2sfZQe9wKQrYYDyq8VllkRIy4s7ZYKUNU8Ar2OpqwspofnBA5RvIygo89LSKbAHQCuF5EqgD0nWDei1JqOaJJwNjb7on5WQG4IcG5lye4/YsWY7bFkc4j3ORos2OHH4tnNj9jdxhEsfp1DSXKNCtbjEWke5Nxkbuo+/aEFYSaD+2h9ozHSrbgtcqiiIqwgpCI4inY62i8ymrNxSUlRE5iqYJQKXUzgJMB1CqlQgDaASzKZmBO1djZiCFeVhDaaWLFROxt3YvmQLPdoRAB4DWU8kcoEkqZIATMNuNwzzbjRBWEPo0txoMFr1XWGcqASM9dey5xcUkJUYEr5OtoOBKOu7yJCUIi57BaQQgAxwKYICKx5zyU4Xgc70jnEZR4S1IfSFmjuTRMHT4Vb+19C+cdfZ7d4RB14TWUbGelxRiItg13hjtRjnIAgFIK7Xp7j4rCLvk6gzAQDkATDR4t9eulHnitssCIJJhByBZjIirQ66ih4s8g5HWRyDksJQhF5E8AjgawFkDX/8IVCuBCl67GQCNKvaV2h1Hwpg6bijf3vMkEIeUFXkMpX1hpMQaim4nb9Y/bhoNGEJpLi3uuV/PmZYLw2mXXYk7NHNw09ya7Q3EMXqusM1TfWVtsMSaiQr6OsoKQyPmsVhDWApimek8spz4OdxxmgjAPTKuahld2vWJ3GERdeA2lvGC1xbjIXdRjrmCb3oZiT3HcY/OxxdiIGHhmyzMJY6aEeK2yKKIi8ROErJQhKnRpX0dFZAGA3wDQAPxeKXVrr/vFvP98AB0ArlFKvWvx3O8A+AWAKqVUQ79flQWRSPzZrEwQEjmH1S3G6wGMymYgg0VjoJEtxnlgWtU0rN67mrOAKF/wGkp5IWRYSxD6PT0rCNv19sQJQrevx7H54K29b6E12IrNhzfbHYrT8FplUbxtnawgJCKkeR0VEQ3AXQAWApgG4HIRmdbrsIUAJptfiwHcbeVcERkLYD6A3f19MekIq3CfFmPNpfG6SOQgVisIhwP4UETeBtA9tVwp9emsROVgjZ2NmDxsst1hFLxKfyXKfGXY1LAJ06p6/xtLlHO8hlJeCEVClmbyxasgjLfBGIhWELaF2jIWYyY8+9GzOGP8GdhyZIvdoTgNr1UWxdvWySUlRIT0r6NzAGxVSm0HABF5BNGlJh/GHLMIwENmVeIqEakQkWoAE1Kc+2sA/w7gqQy9tqTCkXDc62IgUhBLnIkGBasJwh9lM4jBhBWE+WPGiBl4fffrTBBSPviR3QEQRVQk7h/v8RS5i9Cmf5z0a9Pb4m4wBqIVhC3BlozFmQmv73kdCyctxBt73kAgHIi7XIXi+pHdAThFwgpCthgTFbofpXl8DYA9Mb/XAZhr4ZiaZOeKyKcB7FVKvd9743osEVmMaFUixo0bl2boPXH0ApHzWWoxVkq9AmAnAI/582oA72YxLsdqCjRxBmGe4BxCyhe8hlI+6NpgnOyNQpcirahH23CyCkKv5kVnuDNjcWZCfXs9hhcPR3VpNXY07rA7HMfgtcq6iIrA5WKLMRH11I/raLx/lHvPL0x0TNzbRaQYwA8B/KeFeO9VStUqpWqrqqpSHZ5UOMIWYyKns5QgFJFrATwG4HfmTTUA/p6lmBytJdiCUg8ThPng+BHH47Vdr9kdBhGvoZQXrLYXA+Zcwd4txkkqCPNtScmRziMo95VjzJAxbDNOA69V1iXcYsxKGaKC1o/raB2AsTG/jwGwz+IxiW4/GsBEAO+LyE7z9ndFJKszZo1I39EL3GJM5CxWl5TcAOBUAC0AoJTaAmBEtoJysuZAMysI88S48nFo09tQ11JndyhEvIaS7XRDh8dlLUFY5O5ZQdgSbEk6g7AzlD8VhEopNAYaUV5UjurSamw5zARhGvp1rRKRBSKyWUS2isjNce4XEbnDvH+diMxKda6IVIrICyKyxfw+1Lx9voi8IyIfmN/PiTlntnn7VvP5UpfL9lOiFmPOICQqeOleR1cDmCwiE0XEC+AyAMt6HbMMwFXmtXQegGal1P5E5yqlPlBKjVBKTVBKTUA0kThLKXUgg6+zj4QfnLCCkMgxrCYIg0opvesXEXGjb+kzAWgOMkGYL0QEJ4w6Aa/sZJsx2Y7XULKdbuiWNhgD0aRfbAVhS7Al8RZjzZdXLcZtehvcLje8mhcjS0die+N2u0NykrSvVVncwHkzgJVKqckAVpq/A0ADgAuVUscBuBrAn2Ke527z8buea4HlV56meG+ERYRvhIkoreuoUioM4EYAKwBsBLBUKbVBRJaIyBLzsOUAtgPYCuA+ANcnOzfzL8kaI2L0bTEWDWHFCkIip7C6pOQVEfkBAL+IzEf0ovR09sJyppARQigS4jD0PHL8yOPx/LbnccXxV9gdChU2XkPJdrqhW24xLvL0XFLSHGxOmCD0at68qiBs6GhARVEFAGCIbwhnEKanP9eqbG3gXATgLPP8BwG8DOB7Sqn3Yh53A4AiEfEBqAQwRCn1pvlYDwG4CMBzaf7fwJJ4FYSaaGwxJqK0r6NKqeWIJgFjb7sn5meFaGWipXPjHDPBUuQDEFERKKi+FYQuF1uMiRzEagXhzQDqAXwA4DpEL0L/ka2gnKo52IxST6mlAfCUG7NGzcLKHSsR/XeVyDa8hpLtupaUWNF7i3FToClxgtDtRSAcyEiMmXC483B3grDUW4rGQKO9ATlLf65VibZrWjkm2bkjzRY6mN/jtehdAuA9pVTQPC92pki8ODLGUH1nbbmEb4SJqDD/5jMiRtwuBbYYEzmLpQpCpVRERP4O4O9KqfrshuRcTYEmlPnK7A6DYowrHwfd0LG9cTuOrjza7nCoQPEaSvkg3RmE9e0f/6faGGhMuIDLp/nyKkHY0NGAIb4hAIAybxkThGno57Uq4xs4LT2pyHQA/wvgvDTi6Dp3MaKtyBg3bpyVp+uD2zqJKJ5C/ZsvHAn3qR4EWFlN5DRJKwjNQag/EpEGAJsAbBaRehFJuTK9EHFBSf4REcyqnoV/bv+n3aFQAeI1lPKJbuh9EhqJ+N3+HhWELYEWFHudMYMwNkFY6i1Fc6DZ5ojy3wCvVdnYwAkAB802ZJjfD8XEOwbAkwCuUkpti3mOMSniAAAope5VStUqpWqrqqpSvsB44i4pASsIiQpVof/NZ6j4FYTcYkzkLKlajL+J6Bamk5RSw5RSlQDmAjhVRL6V7eCcpinQhBJvid1hUC+zR8/GMx89Y3cYVJi+iQFcQy1sBr3C3Ai6TkT+JSInZPwV0KCR1gzC3i3GwabEFYTu/KogPNxxGGXeaDU/E4SWfRP9v1ZlfANnzDlXmz9fDeApABCRCgDPAvi+UuqNricwH69VROaZ24uv6jonGxJu62SlDFGh+iYK+H1zwgpCVlYTOUqqBOFVAC5XSnVP+DYHSV9p3kcxmgKJ30CRfeaMnoNXdr2CYDhodyhUePp9DbW4GXQHgDOVUscD+B8A92YwdhpkQpGQ5S3GRe6iHluMmwPNCT8A82r5NYOwvqO+e9xHqbcUTcEmewNyhn5fq7K4gfNWAPNFZAuA+ebvMI+fBOAWEVlrfnXNJ/wagN+bz7MNWVpQApgtxr1nELo4a4uogBX0+2YjYsAt8WcQsoKQyDlSvVPwKKUaet+olKoXEWtlCAWkOdicsAWL7FNeVI6JQyfi1V2vYv7R8+0OhwrLQK6hKTeDKqX+FXP8KvRsryPqQTf09BKE+scJwpZgS9ItxvmWICz3lQOIvo5wJIxgOAif22dzZHltQH/vZWMDp1LqMIBz49z+EwA/SfBYawDMSBVvJsRtMeYbYaJCVtDvm8ORMFyuvrVHrKwmcpZUFYR6P+8rSE2BJpR42GKcj2qra/HU5qx1GhElMpBrqJXNoLG+ggTVMiKyWETWiMia+vqCmZdNvQTDQctLSvxuPzpCHd2/twRbEs7Y9bg8MCJG3iRGGto/nkEoIhjiG4LmINuMU+Dfe2mKt8WYw/iJClpBX0fjXRMB87rIymoix0iVIDxBRFrifLUCOC4XATpJY2cjE4R56vTxp+PJjU8ioiJ2h0KFZSDX0HQ2cp6NaILwe/Huz8RAfnI+3dDh1byWju3dYtyqtyb8901EUOQuypsqwvqOepQXlXf/XuYtQ2MnNxmnwL/30mREjD7VMqwgJCpoBX0djbfZHYiOXuB1kcg5kvYaKaWsrTskAEBjoJFLSvLUhIoJKPIU4e29b2PemHl2h0MFYoDXUCubQSEixyM6c2uh2ZJHFFfQCFpuMfZ7Pq4gjKgI2vS2hC3GQHRRSWeoM2GVYS4d6TzS3WIMAGW+MjQFmuwLyAH491764g3kdwlnEBIVqkK/jhqRJBWErKwmcoxUFYSUhqZAU168OaL4Tht3GpZuWGp3GERWpdwMKiLjADwB4ItKqY9siJEcJJ0W4yJ3UXeCsF1vR5G7KG5lQOzxneHOjMQ5UI2djd1bjIHoopLGACsIKbPibTHWRGOlDBEVpIRbjNliTOQoTBBmUGOALcb57KzxZ+Fv6//Gf6TIESxuBv1PAMMA/Nbc5LnGpnDJAXRDh1uzVkHo03wIhoMwIgaag80pP/zyadEKwnzQFmrrUc1f6illBSFlXLxqGbbSEVGhMpQRt0uBoxeInMXaOwWypDmQ+k0U2Wfi0IkoLyrHSztfwieO+oTd4RClZGEz6FcBfDXXcZEzBQ3rFYQi0t1m3BxoTvnhl8/ty4sKQqUU2vV2+N3+7ttKvCVMEFLGxauW0URDWPGNMBEVnkQVhC5xcQY8kYOwgjCDmoPNKPYmntFE9jt34rm4/7377Q6DiCjndEO3PIMQiG4ybg+1W6og9GrevKgg7Ax3wqN5erRDl3hKuKSEMi5eizErZYioUBkRI+4oEs3F0QtETsIEYQa1BltR6mEFYT4796hz8eyWZ/lmkYgKTjBsfUkJEF1U0q63oyXYknIBl0/z5cUW49Zga59lKpxBSNkQ780wl5QQUaFKVkHIJSVEzsEEYQZZeRNF9qooqsC8mnl4YO0DdodCRJRTuqFbbjEGYioIA81JNxgD+dNi3Kq39mmHLvGW4EjnEZsiosEqHAnD1evPaM3FYfxEVJgMlWSLMa+LRI7BBGGGKKXQqvetXKD8c8GUC3DX6rs4D4OICkrQSL+CsDXYiuZg6hmEXld+tBgnqiBkgpAyLdEW41AkZFNERET2CUfCbDEmGgSYIMyQQDgAl7jg1bx2h0IpzBgxA26XG//Y+g+7QyEiyplAOACPZr2CsKq4CnUtdWgONMPv8Sc91uv25k0FYbwEIZeUUKYZEQMuV98EIStliKgQxdvsDnBJCZHTMEGYIc3BZpR5y+wOgywQEXzm2M/gF//6hd2hEBHlTLoVhCNKRmBH0w7sadmDYf5hSY/1ab68qSDsncws9hSjTW+zKSIarOLN23KJi1uMiaggJZpBqInGGYREDsIEYYY0B5o5f9BBzp5wNjbWb8R7+9+zOxQiopwIhoNpVRCOKBmBbY3bsKlhE8YMGZP0WK+WRxWE7p4VhH63nwlCyrh487ZcLi4pIaLCZKj4W4y53Z3IWZggzJCWYAtKvdxg7BQezYOLj7kYP3/953aHQkSUE8FwEF6X9TEYo0pHYUfjDmw5siVlgtDj8uRtBaHfwwQhZZ4R4QxCIqIuSbcY84MTIsdggjBDrAxxp/xywZQL8M/t/8T2xu12h0JElHVBIwi3Zr3FeFTpKGw5sgX7WvehurQ66bEezYNAODDQEAesVW9Fkbuox23FnmK0h9ptiogGq0QtxpEIZ20RUeFJNINQc2mcQUjkIEwQZkhzoJkbjB2mxFuC8yefj9v/dbvdoRARZZ1u6PC4rLcYjywZid3NuzGqdFTK1mSf24eOUMdAQxyw1mAr/O5eFYRuP9p1Jggps+IlCDWXxhmERFSQks0gZIsxkXMwQZghLcEWziB0oIuPuRgPf/AwDncctjsUIqKsCoQDaSUI/R4/hvmHpWwvBqJLSjrC9icIm4N9Ny57NS/CkTDfoFBGxZu3xTfCRFSo4s1lBbjFmMhpmCDMkOZgc5+qBcp/w4qH4fRxp+O3q39rdyhERFkVNNJbUgIA1WXVqCmrSXmcV/PmRQVhS7ClTzW/iHCTMWVcKBKKO4OQs7aIqBCFI2G4XHEqCF384ITISZggzBC2GDvXRcdchLvX3I2QwcHiRDR4pdtiDETnEFqqIHT78nZJCRAdKdEabLUhIhqs4s3b4rZOIipUiWYQusQFQ/GDEyKnYIIwQ5qCTVxS4lBHVx6N6tJqPLnpSbtDISLKmmA4/QrCG0+6EQsmLUh5XF5VELr7flhX7GYFIWWWofpuMea2TiIqVMm2GAuEbcZEDsEEYYY0dTah2MsKQqe6cOqFuPPtO+0Og4goa/pTQVheVA6v5k15nE/zoTOcBxWEemvcav5iTzFadVYQUuaEjXCfahnNpbFShogKUry5rF3YZkzkHEwQZggrCJ3tlLGnYEP9Bmw7ss3uUIiIskI39LQrCK3KlxbjeDMIAaDIU8QKQsqosOpbLcMWYyIqVOFIGK4EqQVWVxM5BxOEGdISbEGpt9TuMKifvJoX5048F3947w92h0JElBX9qSC0Kl8qCNv0trgzCP1uPxOElFFGJM4WY1YQElGBCkfCCSsI3S43r41EDsEEYYZwSYnzffLoT+Kh9x/ijAwiGpSCRhBulzsrj13kLsqLCsI2vS3uv8V+j59LSiij4s3b0oRtdESUPhFZICKbRWSriNwc534RkTvM+9eJyKxU54rI/5jHrhWR50VkdDZfgxExICJx72N1NZFzMEGYIS3BFrYYO9xRQ49CkbsIb+550+5QiIgyTg/rluYJ9odX8+ZNBWHcBCErCCnDuKSEiDJBRDQAdwFYCGAagMtFZFqvwxYCmGx+LQZwt4Vzf6GUOl4pNRPAMwD+M5uvIxzpO5e1iyYar41EDsEEYYa0BltR4mWC0MlEBGdNOAsPf/Cw3aEQEWWcHtGzVkHo0+yfQRhREQTCARS5i/rcV+Qu4pISyigjYvRdUiJsMSaitM0BsFUptV0ppQN4BMCiXscsAvCQiloFoEJEqpOdq5RqiTm/BIDK5oswVN9rYheOXyByDiYIM6RVb2UF4SBw9oSz8eiHj/JTLiIadLK5pKTIXWR7BWG73g6/x9+nqguIxscKQsqkePO2WEFIRP1QA2BPzO915m1Wjkl6roj8VET2ALgCOaggjPfvL8DxC0ROwgRhBhgRA53hzriD0clZaobUoNJfiVV1q+wOhYgoo0JGKKstxoFwICuPbVWi9mIAKPYUoznYnOOIaDCLO4PQxTY6IkpbvMF9vav9Eh2T9Fyl1A+VUmMBPAzgxrhPLrJYRNaIyJr6+nqLIfcVb3FTF354QuQcWU0QDnDg6v0ickhE1vc6p1JEXhCRLeb3odl8DVa06q0o9hQn/NSEnOXkMSfjiU1P2B0GEVHGKKWgG1lsMXb7EAwHoVRWO5iSag+1w++O/0FdkbuIS0qyKEsD9uP+vSciw0TkJRFpE5E7ez3Py+ZjrTW/RmTrNSeaQRhWrJIhorTUARgb8/sYAPssHmPlXAD4C4BL4j25UupepVStUqq2qqoqzdA/Fo6EIXHzldEPT1hBSOQMWctoDWTgqukBAAviPPTNAFYqpSYDWGn+bquWYAtKvaV2h0EZcurYU/HExidsfaNLRJRJoUgImkvL2gdZLnHBo3lsrSJs09sSVvJzi3H2ZHHAfqK/9wIAbgHwnQQhXaGUmml+HcrAS4wr4QxCVskQUXpWA5gsIhNFxAvgMgDLeh2zDMBV5oct8wA0K6X2JztXRCbHnP9pAJuy+SIMlbiCkPNZiZwjmyVvAxm4CqXUqwCOxHncRQAeNH9+EMBF2Qg+HdxgPLhMqpyEQDiATQ1Z/XeUiChndEOHx5Wd+YNd7J5D2Ka3JawgLHYXc0lJ9mRlwD4S/L2nlGpXSr2OaKLQNuFIGC5XnBZjvgkmojQopcKItv+uALARwFKl1AYRWSIiS8zDlgPYDmArgPsAXJ/sXPOcW0VkvYisA3AegG9k83WEjFDiGYSsICRyjOz0GkXFG5o618IxNQD2J3nckeYnJlBK7U/UPiIiixH9lBrjxo1LL/I0tQRbuMF4EBERzK2Zi2e3PItjq461OxwiogELhoNZmz/YpchdFN1kbNM43na9Pe4GYyBaQcglJVkzkL/3kp1r6e+9OP4oIgaAxwH8RMVpB8jE34jxNnZyzhYR9YdSajmiScDY2+6J+VkBuMHquebtcVuKsyVVBSEThETOkM0KwoEMXB2wTM1TsKI50MwKwkFmTs0cLNvcu7qfiMiZsrnBuItP86Ej1JHV50gmaQWhhxWEWZS1Afv9cIVS6jgAp5tfX4x3UCb+RkzYYswKQiIqQKFI4gpCt8uNkBHKcURE1B/ZTBAOZOBqMge72pDN71mbL2NVS7Al4eZEcqYTR52Id/e/i+YAt14SkfMFjWDWW4x9bp+tLcbtoSQVhG5WEGZRtgbsp/33nlJqr/m9FdGh/HMsv4o0xdti7BIXq2SIqCDF+9CkC1uMiZwjmwnCgQxcTWYZgKvNn68G8FQmg+4PJggHH7/Hj+NGHIcXd7xodyhERAOmG3ruWoxt0qa3ocgTP0FY7ClGu96e44gKRlYG7CPNv/dExC0iw82fPQAuALB+4C8vvkRbjNliTESFKN6HJl3cLjdCEVYQEjlB1hKEAxm4CgAi8lcAbwKYKiJ1IvIV865bAcwXkS0A5pu/26ol2JJwcyI516zqWfjH1n/YHQYR0YAFwzmoILS5xbhdb4dP88W9z+/x2xrbYJbNAftI8PeeiOwE8CsA15h/I04D4AOwwhzIvxbAXvO5ssKI9J23pbk0RFQkW09JRJS34l0Tu2iiscWYyCGyuaRkoANXL09w+2EA52YwzAFrCjSh2M0KwsGmdnQtfvTKj6CUgki8MUlERM4QNILZn0Foc4txm96WsMW4yF2ENr2N1/MsydKA/YR/7ymlJiQIZba1iAcuXrUMB/ETUaEKRULwS/yCGbfLzWsjkUNks8W4YDQHm7nFeBCaUDEBgXAAW49stTsUIqIBydWSEjtbjFv0loRLStwuNzSXhqARzHFUNFjF22LMCkIiKlSpZhCyxZjIGZggzIDmQDNnEA5CIoLa0bV4ftvzdodCRDQguWgx9mpe27cYJ6ogBKJzCLmohDIlXjsdl5QQUaEKqyQzCIVbjImcggnCDGgKNqHEwwrCwWjmqJlYsW2F3WEQEQ1IzioI7WwxDrYlnQfMBCFlkhFJsKREGYh2VBMRFY5kMwi5pITIOZggzICWALcYD1azq2fj1V2vsiKAiBwtaOSmgtDWLcahFBWEbiYIKXMSbTEWCNuMiajghCKhhBWEmovzWYmcggnCDGjRWziDcJCq9FdiZOlIrNm3xu5QiIj6TTf0wd9iHGxLOIMQiG4yZoKQMiXeDEIg+kbYUIYNERER2YdbjIkGByYIM6A12MoW40Fs5qiZnENIRI4WDAfhdrmz+hxet70JwvZQO4o8iSsImSCkTIq3xRiIvhE2IkwQElFhSXRNBLikhMhJmCDMgJYgW4wHs1mjZjFBSESOFjSCOZlB2BG2MUGotyevIHQzQUiZk6hahq10RFSIElVVA+YMQlYQEjkCE4QZ0Kq3otRbancYlCXHjzwe7x14D+16u92hEBH1Sy4qCH1uHzp0eysIkyUIi9xFTBBSxkRUJO6b4a5FJUREhSQcCSdMEPKDEyLnYIJwgIyIgUA4kHQwOjmb3+PHMcOPwWu7X7M7FCKifgmEA/Bq3qw+h0/z2d5inGyLMROElEmJ2unc4uYbYSIqOClnELLFmMgRmCAcoJZgC0q9pRARu0OhLJo5ciZWbFthdxhERP3SGe4c/AnCFC3GRe4itAZbcxgRDWbxthgDgMvl4gxCIio4oUgocQUhl5QQOQYThAPUHGzmgpICMKt6Fv657Z92h0FE1C8doY7szyB02zeDMKIiCIQD8Ll9CY9hBSFlUsIZhMItxkRUeEJGKHEFIZeUEDkGE4QD1FVBSIPbMcOPwa7mXTjUfsjuUIiI0parCsLOUGdWnyORjlAHitxFCTcoAtElJS16Sw6josEsUQUhZ20RUSEKRUIJZx1rwusikVMwQThAzYFmJggLgObScOKoE7Fy+0q7QyEiSltnqBM+LXF1XSb43Pa1GLfryecPAtF5smwxpkwxIvE3dmqiscWYiApOyAjB44rfqaC52GJM5BRMEA5Qc7AZxZ5iu8OgHJg5aiae3/a83WEQEaWtM5SDCkK3D51heyoI2/S2lP8W+z1+thhTxkRUJP4MQnGxUoaICk6yFmO3yw3d0HMcERH1BxOEA9Qc4AzCQjF79Gy8sP0FKKXsDoWIKC2d4RxUENrYYtymtyVdUAJEW4xbdVYQUmaEI+H4MwhdnEFIRIUnaYsxZxASOQYThAPUEmxBsZcVhIVg7JCxMJSBjw5/ZHcoRERpycUMwiJ3kW0txm16m6UWY1YQUqYknEHIFmMiKkChSJIWY2GCkMgpmCAcoOZgM4rdTBAWAhFBbXUt24yJyHE6Q53wurObIPS7/WgPtWf1ORKxWkHIBCFlQkRFAIAtxkREJt3Qk7YYcwYhkTMwQThATYGmlFULNHicWH0ilm9dbncYRERpCYQDWW8x9nv8tlUQtuqtqWcQuv1o1+1JYNLgEo6Ek7bSscWYiApNsusiZxASOQcThAPUHGhGiZczCAvF7OrZeGP3G/xHjogcJRctxh6XBxEVsaVKoE1vQ5G7KOkxfg9nEFJmGJH47cVAtJWOFYREVGhCRvIZhLwuEjkDE4QD1BRoQqmn1O4wKEfKi8oxrnwc/rXnX3aHQkRkWS4qCEXEtjbj1mCrpRZjVhBSJhjKgCbxW+lc4uIMQiIqOEkrqzmDkMgxmCAcoKZAU8q2JhpcZlfPxvItbDMmIucIhANZryAEgGJPsS1z/qxWENrVAk2DixExEs7aYosxERUi3dDZYkw0CDBBOEDNQbYYF5ramlr8Y+s/7A6DiMiyzlAnfO7sVhAC9iUIW/XWlPOAu7YrBsPBXIREg1g4Ek5aQchWOiIqNKlmEHJJCZEzMEE4QC3BFpR62WJcSKYNn4bdzbtxoO2A3aEQEVkSNII5qSD0e+xp420JtqSsIBQRlHhL0BJsyVFUNFgZKvkMQrYYE1EhiahI0tELnM1K5BxMEA5QS7CFLcYFRnNpqB3NKkIico5ctRgXuYvsqSAMpt5iDACl3lImCGnAjIiRsFKGFYREVGhCRggelwciEvd+t8vNGYREDsEE4QC1BFtQ4mGLcaGpHV2Lpzc/bXcYRESWBMM5qiB0+21JELboLSlbjAGgxFOC5mBzDiKiwSwcCSeuIOQMQiIqMKFI4g3GQPS6yBZjImdggnAAlFJo09s4g7AAzamZg5U7VvIfOyLKe0bEQDgS7p7Bl012JQjb9LaUW4wBsMWYMoItxkSUSSKyQEQ2i8hWEbk5zv0iIneY968TkVmpzhWRX4jIJvP4J0WkIlvxh4zkCUK3y83KaiKHYIJwADpCHfBq3qQXRBqcKv2VGF02Gm/secPuUIiIkgqEA/C5fQlbfzLJrhbjNr3NUotxsaeYCUIaMLYYE1GmiIgG4C4ACwFMA3C5iEzrddhCAJPNr8UA7rZw7gsAZiiljgfwEYDvZ+s16IYOj5b4Q0hNNLYYEzkEE4QD0Bxs5oKSAjanZg6e/ohtxkSU3zrDnSjSki/wyBSf24f2UO6XlLQGWy1VEBZ7itEcYIsxDUzSFmNhizERpWUOgK1Kqe1KKR3AIwAW9TpmEYCHVNQqABUiUp3sXKXU80qprk8rVgEYk60XkKrFmFuMiZyDCcIBaA4wQVjITh5zMpZtXmZ3GERESQXCAXjd2Z8/CNhXQdgeamcFoY2y1B5XKSIviMgW8/tQ8/ZhIvKSiLSJyJ29nme2iHxgPtYdkqWy2WTbOllBSERpqgGwJ+b3OvM2K8dYORcAvgzguXhPLiKLRWSNiKypr69PM/QoKy3GrCAkcgYmCAeAFYSFbfKwyWgKNGHL4S12h0JElFBnqBM+zZeT5ypyF6E12JqT54rVprdZWlJS7GaCMNOy2B53M4CVSqnJAFaavwNAAMAtAL4TJ5y7zcfveq4FGXiJfRgRA5orcYKQMwiJKA3xPshQFo9Jea6I/BBAGMDD8Z5cKXWvUqpWKVVbVVVlIdy+QpFQ0jnHmouzWYmcggnCAWgKNDFBWMBc4mIVIWWVhaqcY0TkTREJiki8N8tECIQDKHLnpsXY7/GjVc99grBdb7fUYuz3+NEUaMp+QIUlK+1x5vcHzZ8fBHARACil2pVSryOaKOxmPt4QpdSbSikF4KGuczItWYuxy8UKQiJKSx2AsTG/jwGwz+IxSc8VkasBXADgCvO6mBW6oSffYizcYkzkFEwQDkBToIkbjAvcyWNOxhObnrA7DBqELFblHAHwdQC/zHF45CCd4U54tcHbYmxEDASNoKUkaIm3BM1BziDMsGy1x41USu0HAPP7CAtx1KWIA8DAW+pSbjHmDEIism41gMkiMlFEvAAuA9C7+mAZgKvMcQ3zADSb18WE54rIAgDfA/BppVRHNl8AW4yJBg8mCAegKdCEEg8ThIVsVvUsrDuwDg0dDXaHQoNPyqocpdQhpdRqAPyrixLqDOUuQeh3+3OeIGwPRasHrYybK/GUcElJ5mW1PS7DcURvHGBLHVuMiShTzEUiNwJYAWAjgKVKqQ0iskRElpiHLQewHcBWAPcBuD7ZueY5dwIoA/CCiKwVkXuy9RosLSlhgpDIERL/L5lSYoKQfG4fZo+ejWc/ehZXz7za7nBocIlXWTPXpljIwQLhQO4ShDa0GLfpbZYWlADRJSVsMc64gbTHeZOce1BEqpVS+8324UMW4ojd0hkvjoxI2mLMJSVElCal1HJEk4Cxt90T87MCcIPVc83bJ2U4zIRSthhzBiGRY7CCcAAaOxvZYkyYN2YeHt/4uN1h0OCTscqaTGyoI+fqDHfC587NkhI7Kghbg62WE4Sl3lK06FxSkmFZaY8zv3d98nY1gKeSBWE+XquIzDO3F1+V6pz+SrXFmC3GRFRI2GJMNHgwQTgARwJHuKSEcMrYU/DSzpfQEcrqeA8qPFaqcizJxIY6cq5AOACvK3cVhO16e06eq0u6FYTcYpxZWWyPuxXAfBHZAmC++TsAQER2AvgVgGtEpC5mPuvXAPzefJ5tAJ7LxmtO1mKsicYKQiIqKKlajLmkhMg52GI8AE2dTagurbY7DLLZEN8QHDv8WKzYugIXH3ux3eHQ4NFdWQNgL6KVNV+wNyRyos5QJ7zu3M0gbA/lNkHYqrfC70m9wRiIziBkgjDzstQedxjAuQnOmZDg9jUAZliNu79StRizlY6IComVCkJ+cELkDKwgHIDGQCMrCAlAdJvxYxsfszsMGkSsVOWIyCgRqQPwbQD/YVbSDLEvaspHgXAAHpcnJ8/ld9tTQeh3W0wQekvQGsztjEQafJJtMXa52GJMRIXFygxCJgiJnIEVhAPAJSXU5bRxp+Hap6+Fbug5WwZAg5+FqpwD6DmUn6iPznAOtxh7cl9B2BJssfxvcbGnGG16G5RSlrYeE8VjRBLPIGSLMREVmlAklHDsAsAKQiInYQXhADQHm1lBSACAqpIqjCsfh5d2vGR3KEREPeSygrDIXYR2vR3RjtLcaAo0odhrbQahV/NCIAiEA1mOigYzthgTEX0sVYuxJhoMZeT0bwMi6h8mCAegOcAEIX3s1LGn4tEPH7U7DCKiHjpCHTmbQeh2ueHVvDmtIky3mr/UV8o5hDQgqbYYs1KGiApJqhZjEWEVIZFDMEE4AC3BFiYIqdvp40/H3zf9nZUDRJRXOkId8Gm+nD1feVE5Gjsbc/Z8RzqPoMRrPUFY4ilBc7A5ixHRYGdEkswgZIKQiApMKBJK+KFJF000hCLcZEyU75gg7KdAOAClFOfNUbfRZaMxomQEXtv9mt2hEBF1a9VbLS/xyIQhviE40nkkZ8/X2JnewrDyonIc7jicxYhosAtHwnC54v8J7Xa5+SaYiApKyEg+gxAwr40Gr41E+Y4Jwn5qCjShzFfGIefUw2njTsPSDUvtDoOIqFtbsA1+T+4ShGXestwmCAONabUYV/gqUN9Rn8WIaLBLtsXY4/JwxiURFRTd0FPOOva4PPzwhMgBmCDsp64EIVGs08edjsc3Ps42YyLKGy16C4o91pZ4ZEKZrwyNgdy1GKe7MKy8qBz17UwQUv+FjMTtdF7Ni85wZ44jIiKyj5UWY7fGGYRETsAEYT81BZo4f5D6GFs+FkOLhuKNPW/YHQoREQCgTW/LaYtxrisI0/33uMxXxgpCGpBk1TIezYNgOJjjiIiI7GOlxVgTjS3GRA6Q1QShiCwQkc0islVEbo5zv4jIHeb960RkVqpzReRHIrJXRNaaX+dn8zUkku7WRCocp487HY+sf8TuMIiIAACtwdacthiXeEpymiBsDqRZQegrx8H2g1mMiAa7oBGER2OCkIgIiFYQJttiDHA+K5FTZC1BKCIagLsALAQwDcDlIjKt12ELAUw2vxYDuNviub9WSs00v5Zn6zUk09jZyBZjiuvMCWfisQ8fY5sxEeWFdr09py3Gpb7SnC4BSbfFuKKoAofaD2UxIhrsguFgwjfDXpcXAYMzCImocCS7JnbhkhIiZ8hmBeEcAFuVUtuVUjqARwAs6nXMIgAPqahVACpEpNriubY63HmYLcYU15ghYzCseBhe3fWq3aEQEeV8i3GZtwyHO3OTIFRKoSXYkvYMQiYIaSCCRpAtxkREJj2ip24xdmmcQUjkANlMENYA2BPze515m5VjUp17o9mSfL+IDI335CKyWETWiMia+vrMzxo60nkEZV5WEFJ8Z44/Ew9/8LDdYRARoT2U2wrCMl/uEoRd22K9mtfyORW+Ci4poQEJhoNwa/GrZTwuJgiJqLCEjBDcwhZjosEgmwlCiXObsnhMsnPvBnA0gJkA9gO4Pd6TK6XuVUrVKqVqq6qqLAWcjoaOBiYIKaGzJpyFJzY+Ad3Q7Q6FiAqYUgrtentOZxAO8Q7J2QzCpkAThviGpHVORVEFGjoashQRFYKUFYQGE4REVDh0Q0/4oUkXthgTOUM2E4R1AMbG/D4GwD6LxyQ8Vyl1UCllKKUiAO5DtB055xo6GjiDkBIaVToK48vH4/ltz9sdChEVsEA4AM2lpZwNlEllvjI0djbm5Lmag81pf1hXUVSRsMJxe+N2vLLzFc6QpaQC4UDCBKFX8zJBSEQFRTd0SzMI2WJMlP+ymSBcDWCyiEwUES+AywAs63XMMgBXmduM5wFoVkrtT3auOaOwy8UA1mfxNSR0uPMwyn3ldjw1OcRZE87CQ+8/ZHcYRFTA2vS2nLYXA9EZhI2B3CQImwJNac8DLnIXQSmFjlBHj9sPtR/CzHtm4pKll+CZj57JZJg0yATCgYRbjL2aly3GRFRQQpHULcaaaGwxJnKArCUIlVJhADcCWAFgI4ClSqkNIrJERJaYhy0HsB3AVkSrAa9Pdq55zm0i8oGIrANwNoBvZes1JHOk8wgrCCmpsyachX9s/Qdagi12h0JEBapVb0WJpySnz1nmK0NToCknz9WfBKGIoNJf2WcO4V8/+CtOGXsKrjz+Svxtw98yGSYNMrqhJ0wQelxsMSaiwqKHU7cYay6NLcZEDpDVniOl1HJEk4Cxt90T87MCcIPVc83bv5jhMPvlSOeRtOceUWEpLyrHidUn4vEPH8eXTvyS3eEQUQGyo4KwxFOCzlAnQkYoYRIlU5oCTSjxpp8ArSiqQH1HPcZXjO++7YG1D+DK46/EhIoJ+MqyryAYDsLn9mUyXBokgmFuMSYi6qJHrLUYs4KQKP9ls8V4UGvsbGSCkFL6xMRP4A/v/cHuMIioQLUGW3O6oASIVujlqoqwKdDUrwrJiqIKHGo/1P37tiPbsLd1L2aOmolhxcNw1NCj8OKOFzMZKg0iASNxi7HH5eGCMiIqKJa2GAuXlBA5AROE/RBREbQEW7jFmFKaN2YeNjZsxLYj2+wOhYgKkB0VhAAwtGhojwRctjR2Nvbr9Y0qHYWPDn/U/fvKHSsxe/RsaC4NAHDs8GOxet/qjMVJg0uyCkIuKSGiQhOKhFK2GHPDO5EzMEHYD82BZhR7irvfSBAl4tE8OHfiubj/vfvtDoWIClCr3gq/O7cVhABQXVqNHU07sv48+9r2YWjR0LTPG18+Hh8c/KD79xe2vYDjRxzf/fvEoRPx/oH3MxIjDT66ocOreePe59FYQUhEhUUP6ykrCL2aF52hzhxFRET9xQRhPxzpPILyIm4wJmsWTlqI+9fej3AkbHcoRFRg2vS2nLcYA8DI0pE5qZze37ofw4qHpX3ehIoJ+OBQNEGolMJLO1/CidUndt9/1NCjuu8n6i1oBBPO2/JqXiYIiaighCKhlDMIfZoPHaGOHEVERP3FBGE/cEEJpWPi0IkYWTISz370rN2hEFGBaQ22okgryvnzjiodha2NW7P+PPvb9qPSX5n2eRMqJmBTwyYopbD+0HoUe4oxqnRU9/1jh4zF7ubdrHaguILhYMIZhJpoMCIGjIiR46iIiOxhJUHo1bzoDPPfVKJ8xwRhPxzuPMwEIaVlwaQFuGv1XXaHQUQFxq4KwtFlo7Hl8JasP8+BtgP9ShCWF5XDp/lQ11KHxz58DHNr5va436N5MK58HDY2bMxUqDSIBI0gvK74LcYiwjmERFRQdCP1FmO2GBM5AxOE/XCk8wgXlFBazp5wNtbsW4OtR7JfUUNE1KUl2IIid+4rCEeXjcaOxuzPIDzUfqhfCUIgWt29oX4DHv7gYZw98ey49687uG6gIdIgFDJCCSsIAXNRSZgJQiIqDCHDWgUhW4yJ8h8ThP1wuOMwSr2ldodBDuJz+1hFSEQ516q32lJBWF1ajV3NuxBRkY9jCbZixdYVGXuOdr0dISOEEk9Jv86fXDkZ333huwgaQRw7/Ng+948dMhbrD60faJg0CCWbQQhwkzERFZZwJJw6Qej2oiPMBCFRvmOCsB/qO+rZYkxp+/TUT+OBtQ+gTW+zOxQiKhAtwRYUu4tz/rx+jx9lvjLsb90PANh6ZCtm3D0Dlyy9BE9vfjojz3Gg7QCGFw+HiPTr/GtmXoNzJ56LL838UtzHGDNkDD46/NFAw6RBKBgOJtxiDLCCkIjSIyILRGSziGwVkZvj3C8icod5/zoRmZXqXBH5rIhsEJGIiNRmM37LS0p0JgiJ8h0ThP2wv20/hhYNtTsMcphRpaMwc9RM/PG9P9odChEViJZgiy0VhABQU1bTnWD7xj++gfOOOg8//8TP8ZVlX8lIm9GBtgP92mDcxaN5cNExF+GciefEvb+mrCYnm5gHgyy9ua0UkRdEZIv5fWjMfd83j98sIp+Muf1l87a15teIbLxe3dDhcaVoMWYFIRFZICIagLsALAQwDcDlIjKt12ELAUw2vxYDuNvCuesBfAbAq9l+DVZmEPrc3GJM5ARMEPbDwbaDqPBX2B0GOdBnjvkMfr3q19xuSEQ50RhotG1m7tyaubh7zd1YsXUF1h1Yh89O/yyOG3EcxpaPxcs7Xx7w4x9oO4DKov7NH7SiZkgNdjTt6NEmTX1l8c3tzQBWKqUmA1hp/g7z/ssATAewAMBvzcfpcoVSaqb5dSjTrxcwE4ScQUhEmTEHwFal1HallA7gEQCLeh2zCMBDKmoVgAoRqU52rlJqo1Jqcy5eQGeoEz63L+kxPs3HFmMiB2CCsB8Oth9kBSH1y4wRM1DiKcGyzcvsDoWICkBDewPKi8ptee6LjrkIL+54EV944gv41snf6m7JrK2uxTMfPTPgx9/ftj+rH9YVe4pR4inpbpOmhLLy5tb8/qD584MALoq5/RGlVFAptQPAVvNxciZVBaFH87CCkIisqgGwJ+b3OvM2K8dYOTcpEVksImtEZE19fX06p3brCHWkXIjm03zcYkzkAEwQ9kN9ez0ThNQvIoJLp1+Kn732Myil7A6HiAa5hs4GVBRV2PLcfo8fN825Cd85+TuYVd3dUYq5Y+bi2S3PDvgauL81++M+xpaPxZYjW7L6HINAtt7cjlRK7QcA83tXu3Cq5/uj2V58i/R3QGUKqSoIPS4PAuFANp6aiAafeNep3v9AJjrGyrlJKaXuVUrVKqVqq6qq0jm163wEwgH4tBQVhG4fOsNMEBLlOyYI+6G+ox5D/UwQUv+cNvY01HfU45Vdr9gdChENYkopNHY2otxnTwUhAJw54UycPPbkHrdNrJiIYDg44MTb7pbdGObv/wxCK6rLqrH1yNasPscgkOs3t8nOuUIpdRyA082vL8Z9gAFUzBgRAxEVgdajq7knj+ZhizERWVUHYGzM72MA7LN4jJVzs6oz3Amv5oXmSnxNBKKjFziDkCj/MUGYps5QJ/SwjhJPid2hkENpLg2fm/45/PiVH9sdChENYk2BJhS5i5JWOtlBRDBjxAysqls1oMd5/8D7mDh0Yoaiiq+6tJqbjFPL1pvbg2YbMszvXfMEE56jlNprfm8F8BckaD0eSMWMbujwat6k27O5pISI0rAawGQRmSgiXkRnrPaeRbQMwFXmwqd5AJrNymor52ZVu95uaRlakbuILcZEDsAEYZoOtR9CZXFl0j8MiVKZf9R8bGrYhDf3vGl3KESUZw62HcTjHz4+4Mep76i3rb04lSnDpuCtvW/1+3zd0LHlyBYcNfSoDEbV15ghY7CpYVNWn2MQyNab22UArjZ/vhrAUzG3XyYiPhGZiOjik7dFxC0iwwFARDwALkB0i2dGBY1g9zzNRDwuVhASkTVKqTCAGwGsALARwFKl1AYRWSIiS8zDlgPYjujM1fsAXJ/sXAAQkYtFpA7AyQCeFZEV2Yi/PdQOvzt1gtCn+Th6gcgBku8jpz4Oth9EpT97WxOpMHg0D75w3Bfwwxd/iBevftHucIgoT7x/4H2c+cCZcIkLxZ5iLJy8sN+Plc/zcqcOm4qH1j3U7/M3HNqAmrKalEPRB6qmrAaPbng0q8/hdEqpsIh0vUHVANzf9ebWvP8eRN/cno/om9sOAF9Kdq750LcCWCoiXwGwG8BnzXM2iMhSAB8CCAO4QSlliEgJgBVmclAD8E9E30hnVDAcTFmVyyUlRJQOpdRyRK+TsbfdE/OzAnCD1XPN258E8GRmI+3LagWhV/NyBiGRAzBBmKZD7YfytiKDnGXBpAVYumEpXt75Ms6acJbd4RBRHvjNW7/B56Z/DhOHTsRNz92EjUdt7HeLcH1HvW0bjFOZMmwKNtZv7G7XTOYvH/wFf13/V3x73rdx9sSzAQDvHXgPkysnZz3OmiE12NG0AxEVgUvYdJFIlt7cHgZwboJzfgrgp71uawcwO93Y02Xlv1lWEBJRobBcQehmBSGRE/Cv3TQdbDvIBCFlhNvlxtUnXI1vr/g2IipidzhEZLOmQBMe3/g4FkxagJPHnAyf5sPru1/v9+PVt9fbuqAkGb/Hj5ohNVh3cF3S417d9Sq+/tzXMaFiAi5deine2/8eAOCd/e9kff4gABR7ilHiKcH+1v1Zfy5yhqARhMeVooLQxQpCIioM7Xq7pWp+n+bjDEIiB2CCME2H2g/l7Rsucp6zJ54N3dDx8LqH7Q6FiGz2xMYnMKt6VvcYi5NqTsKzW57t9+PVd9RjiG9IpsLLuKnDpmL13tVJj/nRyz/CdbXX4ZJjL8H1J12Pzz76WWxq2ISnNz+NaVXTchLn2PKxA964TINHMGxhBiG3GBNRgWgPWUwQsoKQyBGYIEzT/rb9rCCkjHGJC1+r/Rq++8J30RRosjscIrLRim0rUDu6tvv3OTVzBpQgPNh+MG9bjAFgUuUkrN6XOEG4s2kn3jvwHs4cfyYA4NyjzsUZ48/AjN/OwMljT8aMETNyEufostHYcpgJQoqyUkHodrn5RpiICoLVCkKPy4NwJAwjYuQgKiLqLyYI07S3ZS+G+YfZHQYNItNHTMfcmrm4+Z832x0KEdlEKYUXd7yI2dUfj1CbOmwqDrYdxO7m3f16zENth/I6QThl2BSs2bcm4f0PrH0A50w4p0e11lUnXIXbz7sdi2ctzkWIAIBRpaNYQUjddENPvaSELcZEVCCsVhCKCIrcRVxUQpTnmCBM0+6W3RhROsLuMGiQ+eqsr+KpzU/h+W3P2x0KEdlg/aH18Lv9GFU6qvs2zaVhVvUsvLLzlX495qGOQ6jwVWQowsw7eujR2HJkS8JKq0c3PIqzJp7V5/YTRp0AzaVlN7gYY4aMwaaGTTl7PspvVrYYuzVWEBJRYWjX2+HTfJaO9bk5h5Ao3zFBmKa65jqMKGaCkDKrzFeG75zyHVz996uxr3Wf3eEQUYa8vvt1S38Mr9yxEieOOrHP7ccMP6bfi0rq2+vzeiSGz+3D+PLxcReV7G7ejX1t+zBteG7mDCYzZsgYbG7YbHcYlCestBh7NS8ThERUENpD7fC5rSUIi9xF6Ah1ZDkiIhoIJgjTEDJCONx5GMOLh9sdCg1Cs6tn4/zJ5+Piv13MNxZEDhdREVz22GVY+PBCzP/TfLQEW5Iev3LHShw/8vg+t0+vmo5/7flX2s+vlMLu5t0YUZLfH2hNHjY5bpvx8i3LMbdmbk4rBRMZVz4Ou5p3cekEATArCLnFmIgIANCmt1lOEPo0H1uMifIcE4Rp2Ne6D8OKh+XFGxYanK447gqUecvw2Uc/i3AkbHc4RNRPy7csx7v738XSS5fC5/bh1tdvTXhsREXwxu434iYIJ1VOwvam7SkTjL0daj8EgeR1BSEAHDv8WLy88+U+ty/bvAxzaubkPqA4vJoXNUNqsPkwqwjJ2gxCVhASUaFoD7WjSEs9gxCIVhCyxZgovzFBmIY9LXvyvhqDnM0lLnzv1O/hcMdhXLr0UuiGbndIRNQPP33tp7hsxmXwe/z48swv43fv/A5telvcYzfWb0SptxRVJVV97vNoHkwdNhVv7307reff1LAJ4yvGQ0T6FX+unDjqRLyy6xUopbpva9Pb8Nru13DS6JNsjKyniRUTsf7QervDoDxgpcXY4/Kw4pSICkKb3mZpSQlgziBkBSFRXmOCMA27m3dz/iBlnUfz4Edn/QjNwWbM/9N8NHY22h0SEaVh7YG12NW0C2eOPxMAUDOkBieMPAF/fO+PcY9/dderOG7kcQkf75jhx+CN3W+kFcOmhk0YVz4urXPsMKp0FDTRelTnPb/teUyvmo4yX5mNkfU0vnw8Pjj4gd1hUB6wsqTEo3lYQUhEBaFdb0eRx1qC0Kt5WUFIlOeYIEzDnuY9GFY8zO4wqAB4NS/+4/T/wMiSkTjpvpO4QZPIQR7d8CjOmnBWj3EU508+H/e/d3/c41fuWIkZVTMSPt60qml4fU96i0o+bPgQNWU1aZ1jBxHBiaNO7NFm/PjGxzFvzDz7gopjQsUErD241u4wKA8EjSDcLnfSY4o9xWmPBSAicqK0Kgg1H5eUEOU5JgjTsKt5V9wWMKJs0Fwarj/pelxy7CU47f7TsGzzMrtDIqIUlFJY+uFSnD7u9B63nzjqROxr24eN9Rt73B6OhLFyx0rUjq5N+JjTqqZh9d7ViKiI5Tg2HNrgiApCAJhZPROPffgYAKA12IrlW5bj1LGn2hxVTxOHssWYonRDT5kgrPRX4kDbgRxFRERkn/ZQO/xuv6VjuaSEKP8xQZiGnU072WJMObdw8kL8+Owf47qnr8OPX/lxj1ldRJRfPqz/EG16G44ZfkyP2zWXhnMmnIMH1j7Q4/a36t7CyJKRST98qvRXYohvSFqVxJsPb3ZMgvDM8Wdi/aH1WHtgLf5v1f9hTs2cvPswbnTZaLTr7ahrqbM7FLKZlS3Glf5KHGo/lKOIiIjs0663W64g9LrZYkyU75ggTMP2xu2oLqu2OwwqQNOqpuHO8+/Eox8+is8/9nn+40qUp/6+6e84ZewpcZeDLJi0AA+8/wBCRqj7tme3PJu0erDLtKppeHPPm5ZiqGupQ2uwFaNKR1kP3EZezYvPHPsZXPbYZbj9zdtx5XFX2h1SHy5xYVb1LKzcvtLuUMhmVlqMK4oq0NDRkFbVLxGRE7WHrCcIWUFIlP+YILQoHAljZ9NOjB0y1u5QqEANKx6GX87/JRo7G3HmA2eivr3e7pCIHCUYDuLG5Tdi+l3Tcefbd2blOZ7c9CROGXNK3PvGV4zHmCFj8PdNfwcARFQEj374KOaOmZvycadVTcOLO1+0FMMj6x/B6eNO7zEDMd9dfMzFuOK4K/Czc3+GseX5+e/s8SOPx/Pbn+9zezgSxuq9q3Gw7aANUVGudYY6Uy4p8WpelHhKcKTzSI6iIiKyR0eow3oFoeblDEKiPMcEoUXbjmzDiJIR8Ll9dodCBczn9uH7p38fxww/BnN/PxdbDm+xOyQix7j26Wvx/sH3ce3sa3Hr67fi0Q2PZvTxD7QdwJYjW3D8yOMTHvOpyZ/C/77xvwhHwnhy45Pwat6kC0q6zK6ejZXbV1oaMfDwuodx1oSz0gnddh7Ng9PHn45pVdPsDiWhWdWz8OKOF3v8/2B/636c/sfTcemjl2LKnVPw7EfP2hgh5UJ9Rz3KfeUpjxtePJxzCIlo0OvQOyzPICz1lqKhoyHLERHRQDBBaNHGho0YXz7e7jCI4BIXvnzil3HJsZfg1PtPxeu709tuSlSIXtv1Gl7Y9gJ+cNoPMHPUTNxyxi1Y8uySjFb4LNu8DHNGz0laXXTm+DPhEhe+8tRXcPM/b8blMy6P247cW82QGng0DzbUb0h63Ku7XsXe1r2YOWpmuuFTCjVlNfC7/VixbQWA6EKVT/75k5hUOQl/XPRH/Pzcn+Oqv1/FrfOD3MH2g6goqkh5XGUxF5UQ0eDXEbZeQVjpr8S+1n1ZjoiIBoIJQos21m9EzZAau8Mg6vapKZ/Cd075DhY9sgh/+eAvdodDlLeUUvj289/GV2Z9BX5P9FPuqcOn4rSxp+G2N25Lef5Tm57CjN/OwKzfzcIzHz2T8Lg/vf8nnDnhzKSPpbk03HzazWjobMCFUy/EKWPjtyPHM7t6Np7f1rfFtcvu5t34/GOfx3dO+Y6j2oudQkTw5RO/jG+v+Da2HdmGT/75k5hQMQFfnvlluMSFaVXT8Pnpn8e3VnzL7lApi+rb61FelLqCcGjRUCYIiWjQS6fFuNJfif1t+7McERENBBOEFq2vX5+3c5GocM2pmYNfzP8F/v2Ff8cPVv6AA9GJ4nh116uob6/H2RPO7nH7F477An73zu+SzvP8x9Z/4KvLvoqrTrgKn53+WVzz92vitpHuatqF9fXrMadmTsp4Kv2V+O4p38Wnp34aLrH+z3Dt6Fo8sfGJuPetPbAW834/D5+b/jlLMVD/nDr2VIwrH4c5v5+D8eXj8c153+xRAXrxMRdjw6ENeHGHtXmR5DwNHQ2WKggriiqwv5VvhIlo8AqEAxBIyrmsXSr9lZzXS5TnmCC06MP6D9liTHnpqKFH4f8t/H94butz+PRfP43mQLPdIRHllZ+//nNcMu2SPlV1I0tH4szxZ+JXb/4q7nn7WvfhyieuxC1n3oI5NXNw8piT8eOzf4yr/341tjdu73HsQ+8/hDPHnwmv5s3a65hbMxcfHf4IGw71bDN+q+4tzP/TfCyevRgXH3Nx1p6folWEN592Mx7/3OO4rva6Pglej+bBFcdfgf96+b9SPpYRMdCut2crVMqS+o56DC0amvK4oUVDsa+NrXRENHjtbdmLESUjLB9f6a/EofZDWYyIiAaKCUILdEPHlsNbMKFigt2hEMU11D8Ut33iNvg0H2bfOxsfHPzA7pCI8sIHBz/Au/vfxSeP/mTc+y+bcRnueeceNHY29rhdKYWvPfs1nD/5/B5LR6ZVTcPlMy7HpUsvRWeoEwBwpPMIfvPWb7KenPNoHpw/+fweG5jXHliLC/56Ab598rcdt5hksPrExE9gZ9NOvLrr1YTHvLLzFRx717GovK0StffWoq6lLocRUn+FI2G06W0o85WlPLbSX8kKQiIa1HY378bI0pGWj68oqkBDRwM7nojyGBOEFry7/12MGTIGpd5Su0MhSsijeXDT3Jvw+emfx1kPnIV737nX0sZTIidSSmFf6z60BluTHvfz13+Oi465KGFl36jSUThz/Jm45aVbetz+1/V/xfqD63Hl8Vf2Oeczx34Gw4uH4wuPfwH7WvfhpuduwunjT8f4iuxXmV845UI8tvEx/Hndn/H4h4/jEw99AjeedCNOHnNy1p+brNFcGq447grc/M+b416DX975Mj7zt8/g6hOuxnNXPIfa0bU49f5TM7owh7LjcMdhDPENsTQagLO2iGiw2928GyOKrVcQejUvij3F/PeOKI8xQWjB67tfx/Sq6XaHQWTJ/KPn4/ZP3o5f/uuXWPTIIs76oEFn25FtOOOBMzDtrmmovr0aX3vma2jT2/oct+HQBqzYtgKfnvrppI/3pZlfwiPrH8Gbe94EAGxu2IyvP/d1/Ptp/x43sSgi+M4p30FYhTHh/ybgQNsBfHnmlzPz4lIYVjwMPzvnZ/jPl/4T//Xyf+GWM25JuRiFcm/+UfNxqP0Qlm1e1uP2jfUbcenSS/HDM36IU8edCpe4cNmMyzC3Zi6+/NSX+aFOnjvUfshSezEAjBkyBusPrU/5IQYRkVPtat6F4cXD0zpnWPEwLnAiymNMEFrw8s6XMX0EE4TkHBMqJuDO8+9Eua8c0347Db9+89cIhAN2h0U0YFsOb8EZD5yB40ccj8c/9zge/szD2NG0A6fdf1qPdj6lFG587kZcedyVKau/y4vK8W+n/Bsu+OsFuP7Z63H6H0/HtbOuxdRhUxOe49W8+LeT/w3PfuFZ3HLGLZZaDjNl8rDJuH/R/bjz/DtxwqgTcva8ZJ3m0nD9Sdfjumeuw96WvQCAHY07sODhBfjqiV/FrOpZPY7/6qyv4oNDHyRcQkP5ob6jHkP91hKEI0tH4qTRJ+HXq36d5aiIiOyxo3EHqkqq0jqn0l/JBCFRHmOCMIWIiuBfe/7VYwYVkRN4NS++Musr+OX8X+LJTU9i/P+Nx/f/+X2sPbCWVSrkSEc6j2DBnxfg8hmX47PTPwvNpaG8qBzfO/V7qB1dizn3zcGru15FOBLGN1d8E/Xt9SmrB7ucPOZk/PzcnwMAbjnzFnxyUvyZhb1Z3dxHhWdW9SwsmroIJ//hZNy0/CbM+8M8fOaYz2DB5AV9jvVqXtw05yZ84x/fiFsNS/mhvr0e5b5yy8d/8fgv4ldv/gpXPHEFXtj2QsK5W/w3mYicaFfzLowqHZXWOZVFTBAS5TO33QHku1d3vYrhxcPTLp8myhcTh07Ej8/+MXY27cQ/tv4Dn/7rp9ER6sDJY07GqeNOxZnjz8RJNSfB7eLlgPKXbui4+G8Xo7amFhdMuaDHfSKCK4+/EmPLx+KKJ65AfXs9ZoyYgZ+f+/M+m4uTmTJsCqYMm5Lp0KmAXX7c5ZgxcgbW7l+Ln57zU0yqnJTw2JmjZmLGiBn40cs/wi/P+2UOoySrDrUfwhDfEMvH1wypwf2L7sdLO17CDctvwLDiYXjooocwedjk7mMeev8h3Lj8RnziqE/g3gvv5d+bROQYe1r2pLXFGIguKuH4I6L8xYxACve9ex/OO+o8u8MgGrAJFROwpHYJltQuwaH2Q1h/aD3e2fcO/rj2jzjUfgifnvJpXDPzGpw54UxLA9iJMqGhowEv7ngRLcEWHDv8WMypmdOnKi8cCePLT30ZERXB4lmLEz7WmePPxGljT4Nu6PB7/NkOnciS40Ych+NGHGfp2MWzF+Pap6/FVSdcxc6FPHSo/VBaFYRAtJ3ukmmX4KJjLsJTm5/Cqfefir9d+jecPfFs/GbVb3D7m7fj1k/ciue2PIevLPsK/v75v0NEsvQKiIgyQymFupa69BOE/grsa9uXpagK15t73sS979yLlmALzjv6PFx+3OVpfaBF1IVZgCRagi14ZvMz+MTRn7A7FKKMGlEyAudMPAc3zLkBv7vgd/jdBb9DqbcU1z1zHY6+42jc+vqt/HSPsupg20Fcu+xaHPWbo3Dn23fiyU1P4ivLvoKxvx6LW168BVuPbIVSCtuObMOFf7kQW45swQ9O+0HKikDNpTE5SI5V6a/EtSdei8sfv5xzY/PQwfaDKC9KL0HYRXNp+Myxn8F3T/kuLn/8ckz5f1Nw279uw23zb8O0qmm4ae5NWH9wPf624W9pPe4/tv4D4349Dqf84RSs2bemX7EREaXrcOdh+DQfij3FaZ03vnw83q57O0tRFabb3rgNn/7rp1HiLcGU4VOwdMNSjPv1OPz7C//OjdGUtqwmCEVkgYhsFpGtInJznPtFRO4w718nIrNSnSsilSLygohsMb9bmxbdD//x4n/gtPGnoaKoIltPQZQXRpSMwGenfxa/u+B3+O4p38Xru1/HlDun4PyHz8ef1/0ZjZ2N/XrcDYc24Kev/hTn/ek8TP1/U3Hsncfiwr9eiDvfvpMJSAsGcg3NV0bEwN2r78b0305Hq96KP3/mz/jx2T/Gd0/5Lu654B78/Nyf48OGD3HKH06B/6d+zL53NqrLqvGTs3/CxB8VhE9O+iRGlY7C4qcXJ5xZl29y/feeiHzfPH6ziHwy5vbZIvKBed8dkuFSvMbOxpRLj1I5qeYk/P7Tv8c3530TD170YPf8Lq/mxXdP/S5ueu4m7Gu1Vl3z5MYncdWTV+Hrc7+OM8afgQv+cgF2NO4YUHxElHtOfM98qP0QhvmHpX3e7OrZWHtwLerb6zMZTkFSSuEHK3+Ae9bcg99+6re4dNql+OTRn8QtZ96Cey64Bx8d/ghT75yKP773R866JcskW/+xiIgG4CMA8wHUAVgN4HKl1Icxx5wP4CYA5wOYC+A3Sqm5yc4VkdsAHPn/7N15nJ11fff/12eWbCSQBBKWBEiEgCHsBsS1KEoRrdhWK1QEXMptb6l63/UuaO9fra21tFJv9a4VESlYLaiImltRWcQdkYQdAk2EQAIJCQRCEsKsn98f50qcTGaSmczMdZ2Z83rmcR5zzrWdz3XmzJUz7/kumXlxcRGclpkX7qyWhQsX5uLFg/ur6g+X/5Bzvn0OX/qDL+32X4ul0ez5juf5xWO/4BeP/YI7Vt/BETOO4JS5p/DyA1/Ocfsfx6wps3boBtXV3cU9T97D9/7re1x939U8s+UZXnnQKzlmv2OYNWUW3dnNoxse5fbHb+dXq37F61/0ev7ixL/g1Qe/eli6VEXEksxcOOQD1YGhXEN3dtzduR7uSmby5OYneeSZR9jQtoHWplb2nrQ3B0w5YNt4Wo8/9zg/+u2P+Jdb/4UJzRO44MQLOGT6ITs95gudLzChZYLd7dRwtnRs4cKbLuSEA07g82/8PBNaJuzWccq4Jpb9eS8ijgCuBk4EDgBuAg7LzK6I+A3wQeDXwPXA5zLzBzurfzDXxLd9423MnzGf18597cBenN3w1Xu+ym2P38b3zvoeB089uN/tfrDsB5z97bP55Cmf3Dbj+reXfpsfLP8Bt733tgHPtizVs+7s5peP/ZL71t7Hcfsfx0tnvXS3PxPU62fE0fo78/1r7+eMa87g8jdfPsgzhr//6d/zjqPfwbuPe/eg9x2Lurq7ePCpB7lrzV088uwjbGrfxPjm8UxsnUgQdHR3EAR7jt+TOVPncPDUg3n6+ae55FeXsPK5lXz85I/3e81f9vQyPvWrT3HI9EP44pu+yEF7HVTy2ale9XdNHMkxCE8Elmfmw0UB1wBnAA/02OYM4CtZSyl/HRFTI2J/YM5O9j0DOLnY/yrgJ8BOL3aD8dTzT/F/bv0/fHHJF/mb3/sbw0E1rEmtkzj1kFM59ZBTae9q596193Lvk/fyyZ9/kmXrl9HW1caBex7ItInTaIomntnyDCueXcHMPWay8ICFvG/h+zhy5pE7jGd4yPRDeO3c17KpfRM3/vZG3rPoPXRnN2894q2cMvcUjt3vWGbuMdNQaAjX0MxcPVJFdXV3seq5VTyw7gEWP7GYX636Fbc/fjtd2cXsPWezR+sedGUXG17YwLrn17HhhQ00RRNTJ0zl2P2O5V3HvosTDjhhl9/fiLDFoBrWxNaJfPKUT/LpWz/N0V84mgtfcSGnzzud/afsX3VpfSn7894ZwDWZ2QY8EhHLgRMjYgWwZ2beWhzrK8BbgJ0GhPXmHUe9g/Et4zny347kqH2P4siZR3Lsfsdy3H7HcdBeB/HMC8/wlbu/whV3XsHfnfx328JBgD+c/4es3rSak686mavechXH7HvMdtfa9q52NrywgSTZa/xejG8ZP6jaurq7WLt5Leu3rKcpmth38r5MmzDN/6817LZ0bOHbD36bf/j5P9De1c7hex/OP//qn5k+cTofeeVH+IPD/mDQ7986Nip/Zx6Klx/4cj5722c5fd7pg54FebR5ofMF1m1ex9rNa1n3fO3rmk1rWPncSh599lFWPLuC5euXs8+kfThs78PYb/J+TGiZQGd3J+1d7SRJS9Qim00dm1i7aS1rN69lQusEXnXQq/jASz+w05+FeXvP4/Onf55r7r+Go79wNG958Vt48+Fv5tDph9La1MrG9o089fxTrN+yno1tG+nObia2TmTyuMlMap1Ed3bz7AvP8vhzj7PquVXbGgIcuNeBzN9nPofvc/i23wed8HJsGMnv4ixgZY/Hq6j9xWNX28zaxb77bv3lNzNXR0SfI6NGxPnA1tHsN0XEQwOqeioHM5F9SDo/eMkHOwa0z0BsoYWJdA7b8erJWD43GNvnN5Rza6J5adPSVmDrbwZJN+2PdD/S/QiP8E2+ObDjBNDMhE/xqfgUn9px/WbW8ByPD7Cq/ptbjD5DuYZuFxDu5vVwH4L17Mdxu9yymw6Szmfz2R3XBXTRFU/n03kztX+DUi8/f9ZhHVXUUbs+Tnwv7/3dsrXcSxft/eyxD/BUj8dlXBPL/rw3i1oLwd7H6iju916+g93+jDidubQy+e+7/75ru+Uj8f0Pmm5tvnX8rdza9/puOi645IIdn7N4zxz3d/1cup8HBjdkWLVGU72jqVYYPfV2sWX588tbmETniuYVE9/G2363bjNP8BwD/aNovX5GHJ2/M7cwgRkc8ZpPvKbvAXN3dl0srlP7/11d/tHrd8r5GUm6aV/ZvbJ75Xbfyl27j/v4Al/Y+UY9vw9NNF/VdNW4q7hqd2utxmi5Vu1KGefxJHfRTdeuNwT6uSaOZEDY158Te/dn7m+bgey7U5l5GXDZYPYZSRGxODfWX7P24TCWzw3G9vmN5XMbA4ZyDd1+wW5cDyNicXZX/96ol/eodVjHqKmj/C50ZX/eG/KxhvszYr18/wciIhbns6OjVhhd9Y6mWmF01TuafsZ2w5j8nXksfM9G089If/w+1I/Rch4jOUnJKuDAHo9nA71HXe5vm53t+2TRpJri69phrFmS6sVQrqGSVJayP+/t7Fizd1GHJNUbf2eWVDdGMiC8HZgXEXMjYhxwJrCo1zaLgHOKmZlOAjYUTaF3tu8i4Nzi/rnAd0fwHCSpKkO5hkpSWcr+vLcIODMixkfEXGAe8JvieBsj4qSoDYp3Dn5GlFT//J1ZUt0YsS7GmdkZERcAPwKagSsy8/6IeF+x/lJqM8ydDiyn1iv7XTvbtzj0xcA3IuI9wGPQcyCKulY33Z1HwFg+Nxjb5zeWz21UG8o1dJjUy3vDOrZnHduzju2VXkfZn/eKY3+D2iD8ncD7M3PreDt/DlwJTKQ2OUlZE5TUy/d/IEZTrTC66h1NtcLoqnc01TooY/h35rHwPfMc6sNYOAcYJecRtcmQJEmSJEmSJDWikexiLEmSJEmSJKnOGRBKkiRJkiRJDcyAcJhFxIERcUtELI2I+yPig8Xy6RFxY0QsK75Oq7rW3RURzRFxZ0R8r3g8ls5takRcGxEPFt/Dl42V84uI/1G8J++LiKsjYsJYOTftvog4LSIeiojlEXFRH+sjIj5XrL8nIo4fgRr6vG722ubkiNgQEXcVt78Z7jqK51kREfcWz7G4j/VlvB6H9zjPuyLiuYj4UK9tRuT1iIgrImJtRNzXY9mArhO7ei8NQx2fKq7N90TEtyNiaj/77vR7OAx1/G1EPN7jtT+9n31H+vX4eo8aVkTEXf3sO2yvh3Y0nN/nQTznoD9rRsRHihofiojf77H8JcX7Y3lxbYti+fjiPbY8Im6LiDlDrHnAnx3roNZBfRasst4Y5Ge7smvt59pVSn0RcW7xHMsiYutkHRphUcE1caBG+v1Y0jmM+PW/hHOYEBG/iYi7i3P4+Gg7hx7PP2L/t1UmM70N4w3YHzi+uD8F+C/gCOCfgYuK5RcB/1R1rUM4x/8J/CfwveLxWDq3q4D3FvfHAVPHwvkBs4BHgInF428A542Fc/M2pPdFM/Bb4EXF+/1u4Ihe25xObaD/AE4CbhuBOvq8bvba5uSt15wRfk1WAPvsZP2Ivx59fI/WAAeX8XoArwaOB+7rsWyX14mBvJeGoY5TgZbi/j/1d73a1fdwGOr4W+DDA/i+jejr0Wv9vwB/M9Kvh7eR/T4P4nkH9VmzWHc3MB6YW9TcXKz7DfCy4pr2A+ANxfL/Dlxa3D8T+PoQax7QZ8c6qXXAnwWrrJdBfrarolYG8X/KcNYHTAceLr5OK+5PG+mfzUa/UdE1cRD1jej7saRzGPHrfwnnEMDk4n4rcBu1z9Sj5hx6nMuI/d9W1c0WhMMsM1dn5h3F/Y3AUmr/gZ9B7QMHxde3VFLgEEXEbOCNwOU9Fo+Vc9uT2n8cXwbIzPbMfJYxcn7UZi2fGBEtwCTgCcbOuWn3nAgsz8yHM7MduIbae6KnM4CvZM2vgakRsf9wFrGT62Y9GvHXo5dTgN9m5qMj+BzbZObPgPW9Fg/kOjGQ99KQ6sjMGzKzs3j4a2D27h5/KHUM0Ii/HlsVf2n+E+Dq3T2+dtuwfp8Hajc+a54BXJOZbZn5CLWZUE8srl17ZuatWfst5Su99tl6rGuBU3a3VcMgPztWXetgPwtWWi+D+2xXeq2D/D9lOOv7feDGzFyfmc8ANwKnDbRu7bZKrokDVcL7ccSVdP0f6XPIzNxUPGwtbjmazgFK+b+tEgaEI6ho5n4ctVR838xcDbUfbGBmhaUNxWeAvwK6eywbK+f2ImAd8O9FU+HLI2IPxsD5ZebjwCXAY8BqYENm3sAYODcNySxgZY/Hq9gxmBvINsOm13Wzt5cV3RF+EBELRqiEBG6IiCURcX4f60t9Pai1iOgv+Cnj9YCBXSfKfl3eTe2vrH3Z1fdwOFwQta7OV0TfXa7LfD1eBTyZmcv6WV/G69Goyn7f72CAnzX7q3NWcb/38u32KYL5DcDeu1nmZxj4Z8eqax3sZ8HK6t2Nz3ZVv7ZblVFf5T+bDWo0vu7D+X4s1Qhe/0dc0TX3LmAttTB/1J0DI/9/WyUMCEdIREwGvgV8KDOfq7qe4RARbwLWZuaSqmsZIS3Ump1/ITOPAzZTaxo86hW/wJ5BrUnzAcAeEXF2tVWpDvTVCiB3Y5thsYvr5h3UutkeA/xf4DsjUQPwisw8HngD8P6IeHXvMvvYZ6Rej3HAm4Fv9rG6rNdjoMp8Xf4a6AS+1s8mu/oeDtUXgEOAY6n9Uv4vfZXZx7IReT2As9h568GRfj0aWZnf5x2ffOCfNfurc2f1D8u57cZnx8pqLQz2s2CVr+1gP9tV/druynDWV+nPZgMbS697Xb+3Rvj6P+Iysyszj6XWG+TEiDhyJ5vX3TmU9H9bJQwIR0BEtFL7gf1aZl5XLH5yaze04uvaquobglcAb46IFdSajL82Ir7K2Dg3qCX2q4q/YECtq8LxjI3zex3wSGauy8wO4Drg5YyNc9PuWwUc2OPxbGrdkwa7zZD1c93cJjOf29odITOvB1ojYp/hriMznyi+rgW+Ta27TE+lvB6FNwB3ZOaTfdRZyutRGMh1oqz3ybnAm4B3FF0xdjCA7+GQZOaTxQfbbuBL/Ry/rNejBfgj4Ov9bTPSr0eDK/N6sJ1Bftbsr85VbN9Vv2f92/Yp3md7sXvd7Qf72bHKWrceazCfBausd7Cf7ap+bbcqo77KfjYb3Gh83Yfz/ViKEq7/pcnaEA4/oTYEwGg6hzL+b6uEAeEwK8a9+DKwNDM/3WPVIuDc4v65wHfLrm2oMvMjmTk7M+dQ6/b248w8mzFwbgCZuQZYGRGHF4tOAR5gbJzfY8BJETGpeI+eQm3MirFwbtp9twPzImJu0VrtTGrviZ4WAedEzUnUujCtHs4idnLd7LnNflvHPYqIE6n9//X0MNexR0RM2Xqf2qQY9/XabMRfjx76bRlWxuvRw0CuEwN5Lw1JRJwGXAi8OTOf72ebgXwPh1pHzzEn/7Cf44/461F4HfBgZq7qa2UZr0eDK+v7vJ3d+Ky5CDgzajO+zgXmAb8prl0bI+Kk4pjn9Npn67HeSu0z36BbNezGZ8fKai3qHexnwSrrHexnu0pf2x7KqO9HwKkRMS1qLS1PLZZpZFVyTRyi4Xw/jriSrv8jfQ4zImJqcX8ixWeZ0XQOJf3fVo2scIaUsXgDXkmtWeg9wF3F7XRq42HcDCwrvk6vutYhnufJ/G62njFzbtS6jC0uvn/foTbz2Zg4P+Dj1C6+9wH/QW0WpTFxbt6G9L44ndoMaL8F/rpY9j7gfcX9AD5frL8XWDgCNfR33exZxwXA/dRmAPs18PIRqONFxfHvLp6rktejeJ5J1AK/vXosG/HXg1oguRrooPZXzff0d52g1qXt+p29l4a5juXUxm/Z+h65tHcd/X0Ph7mO/yi+9/dQ+8C3fxWvR7H8yq3viR7bjtjr4a3P782wfZ8H8ZyD/qwJ/HVR40P0mCERWEjtc8FvgX8Folg+gdrwBsupzbD4omGo+2QG8Nmx6loZ5GfBKutlkJ/tyq6VQfyfMtz1URurdnlxe1cZP5veqrkmDqK2EX0/lnQOI379L+EcjgbuLM7hPuBviuWj5hx6nc/JjMD/bVXdtl5cJUmSJEmSJDUguxhLkiRJkiRJDcyAUJIkSZIkSWpgBoSSJEmSJElSAzMglCRJkiRJkhqYAaEkSZIkSZLUwAwIJUmqIxFxXkT86zAf8y0RcUSPx38XEa8bzueQpCpFxAERcW1x/9iIOH0A+5wcEd8bwnNeHxFTd3d/SRpJQ70ujsRnUtU3A0JJksa+twDbAsLM/JvMvKm6ciRpeGXmE5n51uLhscAufxEehuc8PTOfHennkaTdUcV1UaObAaFGrYj4TkQsiYj7I+L8Ytl7IuK/IuInEfGlrX/xiIgZEfGtiLi9uL2i2uolNaqIODsifhMRd0XEFyOiOSLeVVy7fgq8ose2V0bEW3s83tTj/l9FxL0RcXdEXFws+7PiGnd3cc2bFBEvB94MfKp4zkN6HjciTomIO4tjXRER44vlKyLi4xFxR7HuxcXyvy22+0lEPBwRH+hR0/+MiPuK24dG9pWUNJZExDkRcU9x/fqPiPiDiLituD7dFBH7Ftv9bbH+xxGxLCL+rFg+p7j2jAP+Dnh7cc17e0ScGBG/Ko71q4g4vI/nnxERNxbXvC9GxKMRsU+xbofPnMXyFRGxT/HcS4vPnvdHxA0RMbGcV07SWFX1dbFXLQdHxM1FPTdHxEHF8rcVz3F3RPysWLagx2fdeyJi3si+UhouLVUXIA3BuzNzffEB7PaI+D7w/wHHAxuBHwN3F9t+Fvg/mfmL4mL2I2B+FUVLalwRMR94O/CKzOyIiH8DzgY+DrwE2ADcAty5i+O8gVqrwJdm5vMRMb1YdV1mfqnY5hPAezLz/0bEIuB7mbm1m8nW40wArgROycz/ioivAH8OfKY43lOZeXxE/Hfgw8B7i+UvBl4DTAEeiogvAEcD7wJeCgRwW0T8NDN3ei6SFBELgL+mdm18qrimJXBSZmZEvBf4K+Avi12OBk4C9gDuLD4DApCZ7RHxN8DCzLygOP6ewKszszNqwyt8EvjjXmV8DPhxZv5jRJwGnN9jXe/PnN/KzKd77T8POCsz/ywivlEc/6tDfGkkNag6uS729K/AVzLzqoh4N/A5ap9F/wb4/cx8PH435ML7gM9m5teKcLJ5yC+ISmFAqNHsAxHxh8X9A4F3Aj/NzPUAEfFN4LBi/euAI7b+UgzsGRFTMnNjmQVLaninUAsCby+uRxOBlwM/ycx1ABHxdX537erP64B/z8znAbZe94Aji2BwKjCZ2h9DduZw4JHM/K/i8VXA+/ldQHhd8XUJ8Ec99vt+ZrYBbRGxFtgXeCXw7czcXJzHdcCr2EXYKUnAa4FrM/MpqF3TIuIo4OsRsT8wDnikx/bfzcwtwJaIuAU4EbhrJ8ffC7iqaMWSQGsf27wS+MPi+X8YEc/0WNf7M+c8oHdA+Ehmbq1hCTBnJ/VI0q7Uw3Wxp5fxu8+C/wH8c3H/l8CVxR9Gtn5uvBX464iYTe2P18t2ebaqC3Yx1qgUESdT+wX5ZZl5DLVfQB/ayS5NxbbHFrdZhoOSKhDAVT2uRYcDf0vtg1lfOin+r45aojiux3H62udK4ILMPIpaq8QJA6hnZ9qKr11s/0fFth73t67b1bEkqT99XdP+L/CvxfXsv7H99az3tv1dQ7f6e+CWzDwS+AP6vjb2eQ3r5zNnX/v3dV2UpN1VD9fFnUmAzHwf8L+p/fHkrojYOzP/k9rwNluAH0XEawd5bFXEgFCj1V7AM0XXuhdTa049Cfi9iJgWES1s30T6BuCCrQ8i4tgyi5Wkws3AWyNiJkDRXeRO4OSI2DsiWoG39dh+BbUWhwBn8Lu/7t4AvDsiJvU4DtS6/K4ujvOOHsfZWKzr7UFgTkQcWjx+J/DT3Ty3nwFvidq4h3tQa4nz8908lqTGcjPwJxGxN2y7pu0FPF6sP7fX9mdExIRi+5OB23ut733N63ms8/qp4RfAnxTPfyowrce+vT9zStJIq4frYk+/As4s7r+D2jWTiDgkM2/LzL8BngIOjIgXAQ9n5ueARdS6P2sUMCDUaPVDoCUi7qH2149fU7vAfRK4DbgJeIDaeF4AHwAWFoOkPkBtXARJKlVmPkDtr6w3FNevG4H9qbUivJXateuOHrt8idofPn5DbWy/zcVxfkjtA9fiiLiL2viAUBuH9bbiuA/2OM41wP8qBqI+pEc9L1AbN/CbEXEv0A1cupvndge1Foy/KWq43PEHJQ1EZt4P/APw04i4G/g0teviNyPi59R+6ezpN8D3qX3++/vMfKLX+luoDS1zV0S8nVpXuH+MiF/S/1hYHwdOjYg7gDcAq6n9Qt3XZ05JGlF1cl3s6QPAu4pr4TuBDxbLPxW1yezuo/bH4rupjbd9X/EZ9cXAVwZ+5qpSZO6q5ak0ekTE5MzcVLQg/DZwRWZ+u+q6JEmSNHQR8bfApsy8ZJiPOx7oKgbsfxnwhcw8djifQ5JGwkhdF9V4HBtDY83fFrMwTaDWBe871ZYjSZKkUeAg4BsR0QS0A39WcT2SJJXKFoSSJEmSJElSA3MMQkmSJEmSJKmBGRBKkiRJkiRJDcyAUJIkSZIkSWpgBoSSJEmSJElSAzMglCRJkiRJkhqYAaEkSZIkSZLUwAwIJUmSJEmSpAZmQChJkiRJkiQ1MANCSZIkSZIkqYG1VF1AGfbZZ5+cM2dO1WVIGmFLlix5KjNnVF2HJEmSJEmjSUMEhHPmzGHx4sVVlyFphEXEo1XXIEmSJEnSaGMXY0mSJEmSJKmBGRBKkiRJkiRJDcyAUJIkSZIkSWpglQSEEXFaRDwUEcsj4qI+1r84Im6NiLaI+HAf65sj4s6I+F45FUuSJEmSJEljU+kBYUQ0A58H3gAcAZwVEUf02mw98AHgkn4O80Fg6YgVKUmSJEmSJDWIKloQnggsz8yHM7MduAY4o+cGmbk2M28HOnrvHBGzgTcCl5dRrCRJkiRJkjSWVREQzgJW9ni8qlg2UJ8B/gro3tlGEXF+RCyOiMXr1q0bdJGSJEmSJElSI6giIIw+luWAdox4E7A2M5fsatvMvCwzF2bmwhkzZgy2RkmSJEmSJKkhVBEQrgIO7PF4NvDEAPd9BfDmiFhBrWvyayPiq8NbniRJkiRJktQ4qggIbwfmRcTciBgHnAksGsiOmfmRzJydmXOK/X6cmWePXKmSJEmSJEnS2NZS9hNmZmdEXAD8CGgGrsjM+yPifcX6SyNiP2AxsCfQHREfAo7IzOfKrleSJEmSJEkayyJzQMP/jWoLFy7MxYsXV12GpBEWEUsyc2HVdUiSJEmSNJpU0cVYkiRJkiRJUp0wIFTlLr/jch566qGqy5AkSZIkSWpIBoSq3JV3Xcmda+6sugxJkiRJkqSGZECoyj2+8XGe73i+6jIkSZIkSZIakgGhKpWZrNm0hs3tm6suRZIkSZIkqSEZEKpSG9o28ELnC7YglCRJkiRJqogBoSq1euNqAANCSZIkSZKkihgQqlJPbHwCgE0dmyquRJIkSZIkqTEZEKpSWwNCxyCUJEmSJEmqhgGhKrV602r2HL8nmzsMCCVJkiRJkqpgQKhKrXpuFQdMOcAWhJIkSZIkSRUxIFSlntj4BLOmzHKSEkmSJEmSpIoYEKpSj298nFl7zrKLsSRJkiRJUkUMCFWpp59/mpl7zLQFoSRJkiRJUkUMCFWptq429hy3J1s6tlRdiiRJkiRJUkMyIFSlOro6mDJ+il2MJUmSJEmSKmJAqEq1d7UzedxkWxBKkiRJkiRVxIBQldoWEHYaEEqSJEmSJFXBgFCVau9qZ8q4KWzp2EJmVl2OJEmSJElSwzEgVKU6ujuY0DKBpmiivau96nIkSZIkSZIajgGhKtPV3QVAc1MzE1om8HzH8xVXJEmSJEmS1HgMCFWZtq42WptaAQwIJUmSJEmSKmJAqMq0d7XT2lwLCCe2TjQglCRJkiRJqoABoSrT3tXOuOZxQK0F4eaOzRVXJEmSJEmS1HgMCFWZtk67GEuSJEmSJFXNgFCV6dnF2IBQkiRJkiSpGgaEqkx7VzvjmmpdjMc3jzcglCRJkiRJqoABoSrT1tVGS3MLAONbxrO53TEIJUmSJEmSymZAqMq0d7VvG4PQFoSSJEmSJEnVMCBUZRyDUJIkSZIkqXoGhKpMW2cbLU21Lsatza0GhJIkSZIkSRUwIFRlenYxbokWOro7Kq5IkiRJkiSp8RgQqjI9uxg3NzXT0WVAKEmSJEmSVDYDQlWmret3XYxbmlpo72qvuCJJkiRJkqTGY0CoyrR3tW8LCJubmmnvNiCUJEmSJEkqWyUBYUScFhEPRcTyiLioj/UvjohbI6ItIj7cY/mBEXFLRCyNiPsj4oPlVq7h1HMMwtamVlsQSpIkSZIkVaCl7CeMiGbg88DrgVXA7RGxKDMf6LHZeuADwFt67d4J/GVm3hERU4AlEXFjr301SvRuQdjW2VZxRZIkSZIkSY2nihaEJwLLM/PhzGwHrgHO6LlBZq7NzNuBjl7LV2fmHcX9jcBSYFY5ZWu4tXU6BqEkSZIkSVLVqggIZwErezxexW6EfBExBzgOuG14ylLZerYgbIkWOrqdxViSJEmSJKlsVQSE0ceyHNQBIiYD3wI+lJnP9bPN+RGxOCIWr1u3bjfK1EjrOQZhS1MLHV0GhJIkSZIkSWWrIiBcBRzY4/Fs4ImB7hwRrdTCwa9l5nX9bZeZl2XmwsxcOGPGjN0uViOnrattuzEIDQglSZIkSZLKV0VAeDswLyLmRsQ44Exg0UB2jIgAvgwszcxPj2CNKkFbZxstzT3GIOx2DEJJkiRJkqSylT6LcWZ2RsQFwI+AZuCKzLw/It5XrL80IvYDFgN7At0R8SHgCOBo4J3AvRFxV3HIj2bm9SWfhoZBW1ebXYwlSZIkSZIqVnpACFAEetf3WnZpj/trqHU97u0X9D2GoUahts42xjWPA5zFWJIkSZIkqSpVdDGWgGIMwh5djJ3FWJIkSZIkqXwGhKqMsxhLkiRJkiRVz4BQlWnr7DUGoS0IJUmSJEmSSmdAqMr07GLc3NRsC0JJkiRJkqQKGBCqMu1d7YxrKiYpiRY6uzsrrkiSJEmSJKnxGBCqMu1d7bQ0OUmJJEmSJElSlQwIVZm2rjZam383BmF7V3vFFUmSJEmSJDUeA0JVxlmMJUmSJEmSqmdAqMq0d7Vvm6SkpckxCCVJkiRJkqpgQKjKtHf2akHoGISSJEmSJEmlMyBUZdq7fxcQNjc124JQkiRJkiSpAgaEqkx7V/t2k5Q4BqEkSZIkSVL5DAhVmfaudlqaHINQkiRJkiSpSgaEqkzPWYybo5mu7KI7uyuuSpIkSZIkqbEYEKoyHV0d27oYRwStTa12M5YkSZIkSSqZAaEq09Hdsa2LMTiTsSRJkiRJUhUMCFWJzNxuDEJwohJJkiRJkqQqGBCqEt3ZTVM00RS/ewvaglCSJEmSJKl8BoSqREd3By3Rst0yWxBKkiRJkiSVz4BQlejo6qCluY+A0BaEkiRJkiRJpTIgVCU6uzu3G38QbEEoSZIkSZJUBQNCVaKju4PmaN5uWWtzK+1d7RVVJEmSJEmS1JgMCFWJflsQ2sVYkiRJkiSpVAaEqkRHV4ddjCVJkiRJkuqAAaEq0dHdT0BoC0JJkiRJkqRSGRCqEn11MW6OZlsQSpIkSZIklcyAUJXo6NpxkhJbEEqSJEmSJJXPgFCV6OzupKXZMQglSZIkSZKqZkCoSnR079iCsLmp2RaEkiRJkiRJJTMgVCU6ujpobto+IGxtaqW9q72iiiRJkiRJkhqTAaEq0eckJU1OUiJJkiRJklQ2A0JVoq8uxi3hJCWSJEmSJEllMyBUJWxBKEmSJEmSVB8MCFWJjq4+WhA22YJQkiRJkiSpbAaEqkRHd8eOLQjDFoSSJEmSJEllMyBUJTq7O3eYxbi5qdkWhJIkSZIkSSWrJCCMiNMi4qGIWB4RF/Wx/sURcWtEtEXEhwezr0aH/roYt3e1V1SRJEmSJElSYyo9IIyIZuDzwBuAI4CzIuKIXputBz4AXLIb+2oU6LMFoV2MJUmSJEmSSldFC8ITgeWZ+XBmtgPXAGf03CAz12bm7UDvtGiX+2p06Oh2khJJkiRJkqR6UEVAOAtY2ePxqmLZsO4bEedHxOKIWLxu3brdKlQjp6Oro88xCO1iLEmSJEmSVK4qAsLoY1kO976ZeVlmLszMhTNmzBhwcSpHZ3fnDrMYOwahJEmSJElS+aoICFcBB/Z4PBt4ooR9VUc6ujtoiu3ffnYxliRJkiRJKl8VAeHtwLyImBsR44AzgUUl7Ks60uckJU1OUiJJkiRJklS2ll1vMrwyszMiLgB+BDQDV2Tm/RHxvmL9pRGxH7AY2BPojogPAUdk5nN97Vv2OWjoOrr6nqTkuc7nKqpIkiRJkiSpMZUeEAJk5vXA9b2WXdrj/hpq3YcHtK9Gn47uHScpaYkWOrOzoookSZIkSZIaUxVdjCU6ujpoiR0nKensMiCUJEmSJEkqkwGhKtFXC8LmpmYnKZEkSZIkSSqZAaEq0d7VTkvT9i0IDQglSZIkSZLKZ0CoSnR2d9IU27/9msNZjCVJkiRJkspmQKhK9NWCsKWphc5uxyCUJEmSJEkqkwGhKtHZ3bljF2NbEEqSJEmSJJXOgFCV6OjuoDm2n6SkpamFzrQFoSRJkiRJUpkMCFWJjq6OvicpsQWhJEmSJElSqQwIVYnO7k6am/poQegYhJIkSZIkSaUyIFQl2rvadwgIm6OZjm5bEEqSJEmSJJXJgFCV6OzupCV27GLc1d1VUUWSJEmSJEmNyYBQlejo7ui7BaFjEEqSJEmSJJXKgFCV6GuSEmcxliRJkiRJKp8BoSrR2d1Jc/RqQegsxpIkSZIkSaUzIFQlOrr7aUHoLMaSJEmSJEmlMiBUJTq7O/scg9CAUJIkSZIkqVwGhKpER9eOk5TYglCSJEmSJKl8BoSqRGd3Jy2xfRfj5iZbEEqSJEmSJJXNgFCVsIuxJEmSJElSfTAgVCX6mqTEFoSSJEmSJEnlMyBUJTq7O53FWJIkSZIkqQ4YEKoSnV2dNMf2XYybovZ27OruqqIkSZIkSZKkhmRAqEp0dO84izFAa1OrrQglSZIkSZJKZECoSnR279iCEGrjEHZ0d1RQkSRJkiRJUmMyIFQl+hqDEByHUJIkSZIkqWwGhKpEfwFhc1MzHV22IJQkSZIkSSqLAaEq0dnd6RiEkiRJkiRJdcCAUKXLTLqyyzEIJUmSJEmS6oABoUq3dYKSiNhhnWMQSpIkSZIklcuAUKXr6O7oc/xBgOZwDEJJkiRJkqQyGRCqdP1NUAK1Lsa2IJQkSZIkSSqPAaFK19HVfwvClqYWxyCUJEmSJEkqkQGhSrerLsa2IJQkSZIkSSqPAaFK19ndSXPTjjMYQ9GC0DEIJUmSJEmSSmNAqNLtrIuxYxBKkiRJkiSVy4BQpdtZF2PHIJQkSZIkSSpXJQFhRJwWEQ9FxPKIuKiP9RERnyvW3xMRx/dY9z8i4v6IuC8iro6ICeVWr6Ha6SzGjkEoSZIkSZJUqtIDwohoBj4PvAE4AjgrIo7otdkbgHnF7XzgC8W+s4APAAsz80igGTizpNI1TDq6OmiOvscgbG5qdgxCSZIkSZKkElXRgvBEYHlmPpyZ7cA1wBm9tjkD+ErW/BqYGhH7F+tagIkR0QJMAp4oq3AND2cxliRJkiRJqh9VBISzgJU9Hq8qlu1ym8x8HLgEeAxYDWzIzBv6epKIOD8iFkfE4nXr1g1b8Rq6nU1S0tLUYkAoSZIkSZJUoioCwuhjWQ5km4iYRq114VzgAGCPiDi7ryfJzMsyc2FmLpwxY8aQCtbw2lULQicpkSRJkiRJKs+QA8KI+FZEvDEiBnqsVcCBPR7PZsduwv1t8zrgkcxcl5kdwHXAy3evclWls7uT5qb+xyC0BaEkSZIkSVJ5hqMF4ReAPwWWRcTFEfHiXWx/OzAvIuZGxDhqk4ws6rXNIuCcYjbjk6h1JV5NrWvxSRExKSICOAVYOgznoBI5SYkkSZIkSVL96Luf5yBk5k3ATRGxF3AWcGNErAS+BHy1aOnXc/vOiLgA+BG1WYivyMz7I+J9xfpLgeuB04HlwPPAu4p1t0XEtcAdQCdwJ3DZUM9B5XKSEkmSJEmSpPox5IAQICL2Bs4G3kkttPsa8ErgXODk3ttn5vXUQsCeyy7tcT+B9/f1XJn5MeBjw1G3qrGzSUqamxyDUJIkSZIkqUxDDggj4jrgxcB/AH9QdAUG+HpELB7q8TX2dHR39D8GoS0IJUmSJEmSSjUcLQgvL1oEbhMR4zOzLTMXDsPxNcZ0dnf2PwZhOAahJEmSJElSmYZjkpJP9LHs1mE4rsaojq6dtCB0FmNJkiRJkqRS7XYLwojYD5gFTIyI44AoVu0JTBqG2jRGdXR30BL9T1LiGISSJEmSJEnlGUoX498HzgNmA5/usXwj8NEhHFdjnC0IJUmSJEmS6sduB4SZeRVwVUT8cWZ+axhr0hjX0b2TWYyjmfau9pIrkiRJkiRJalxD6WJ8dmZ+FZgTEf+z9/rM/HQfu0l0dnfSFH0Pf9nS1GILQkmSJEmSpBINpYvxHsXXycNRiBrHrroY24JQkiRJkiSpPEPpYvzF4uvHh68cNYKdTlLiGISSJEmSJEml6ruf5yBExD9HxJ4R0RoRN0fEUxFx9nAUp7Fppy0IHYNQkiRJkiSpVEMOCIFTM/M54E3AKuAw4H8Nw3E1RrV3tfc7SYljEEqSJEmSJJVrOALC1uLr6cDVmbl+GI6pMayju4Pm6L8FYUd3R8kVSZIkSZIkNa6hTFKy1f+LiAeBLcB/j4gZwAvDcFyNUR3d/XcxbmlqobPLFoSSJEmSJEllGXILwsy8CHgZsDAzO4DNwBlDPa7Gro6ujn67GDc32YJQkiRJkiSpTMPRghBgPjAnYrupab8yTMfWGNPe1c6Elgl9rjMglCRJkiRJKteQA8KI+A/gEOAuoKtYnBgQqh+7msW4o8uAUJIkSZIkqSzD0YJwIXBEZuYwHEsNoDM7+52kxFmMJUmSJEmSyjUcsxjfB+w3DMdRg2jvau9/DEJbEEqSJEmSJJVqOFoQ7gM8EBG/Adq2LszMNw/DsTUG7WySkpamFjrTFoSSJEmSJEllGY6A8G+H4RhqIB3dO5/FuL2rveSKJEmSJEmSGteQA8LM/GlEHAzMy8ybImIS0PcAcxI7n6SkpanFLsaSJEmSJEklGvIYhBHxZ8C1wBeLRbOA7wz1uBq7Ort3PklJR7cBoSRJkiRJUlmGY5KS9wOvAJ4DyMxlwMxhOK7GqJ11MW5paqGzyzEIJUmSJEmSyjIcAWFbZm4bNC4iWoAchuNqjNrVJCXt3Y5BKEmSJEmSVJbhCAh/GhEfBSZGxOuBbwL/bxiOqzFqVy0IHYNQkiRJkiSpPMMREF4ErAPuBf4bcD3wv4fhuBqjdjVJSWe3XYwlSZIkSZLKMhyzGHdHxHeA72TmuqGXpLGuq7trp5OUtHfZxViSJEmSJKksu92CMGr+NiKeAh4EHoqIdRHxN8NXnsaiXU5SYgtCSZIkSZKk0gyli/GHqM1efEJm7p2Z04GXAq+IiP8xHMVpbNrlGITdjkEoSZIkSZJUlqEEhOcAZ2XmI1sXZObDwNnFOqlPu5rF2ElKJEmSJEmSyjOUgLA1M5/qvbAYh7B1CMfVGNfZ3bnTMQg7ujvIzJKrkiRJkiRJakxDCQh3NpOEs0yoX53dnf3OYtwUTTRFE13ZVXJVkiRJkiRJjWkosxgfExHP9bE8gAlDOK7GuM7uzn67GAO0NrXS3tW+020kSZIkSZI0PHY7gcnMvpuASbuws0lKoMc4hHZUlyRJkiRJGnFD6WIs7ZaBtCB0JmNJkiRJkqRyVBIQRsRpEfFQRCyPiIv6WB8R8bli/T0RcXyPdVMj4tqIeDAilkbEy8qtXkPV0dXR7yQlAK3NtS7GkiRJkiRJGnmlB4QR0Qx8HngDcARwVkQc0WuzNwDzitv5wBd6rPss8MPMfDFwDLB0xIvWsOnObpKkKfp/623rYixJkiRJkqQRV0ULwhOB5Zn5cGa2A9cAZ/Ta5gzgK1nza2BqROwfEXsCrwa+DJCZ7Zn5bIm1a4g6ujpobWolIvrdpqWpxS7GkiRJkiRJJakiIJwFrOzxeFWxbCDbvAhYB/x7RNwZEZdHxB4jWayG164mKIHfzWIsSZIkSZKkkVdFQNhX07Ec4DYtwPHAFzLzOGAzsMMYhgARcX5ELI6IxevWrRtKvRpGHV27Dgibm5rtYixJkiRJklSSKgLCVcCBPR7PBp4Y4DargFWZeVux/FpqgeEOMvOyzFyYmQtnzJgxLIVr6HY1gzHUJimxi7EkSZIkSVI5qggIbwfmRcTciBgHnAks6rXNIuCcYjbjk4ANmbk6M9cAKyPi8GK7U4AHSqtcQzaQLsYtTS12MZYkSZIkSSrJzpOaEZCZnRFxAfAjoBm4IjPvj4j3FesvBa4HTgeWA88D7+pxiL8AvlaEiw/3Wqc6N6AuxmEXY0mSJEmSpLKUHhACZOb11ELAnssu7XE/gff3s+9dwMKRrE8jZ0CTlNjFWJIkSZIkqTRVdDFWAxtIC0K7GEuSJEmSJJXHgFClGsgkJXYxliRJkiRJKo8BoUrV0d1Bc1PzTrdpbbKLsSRJkiRJUlkMCFWqjq4OmmPnAWFzU7NdjCVJkiRJkkpiQKhSDWSSkuYmuxhLkiRJkiSVxYBQpRrIJCV2MZYkSZIkSSqPAaFKNZAxCO1iLEmSJEmSVB4DQpWqo6uD1qbWnW7jLMaSJEmSJEnlMSBUqdq62nYZELY0tdjFWJIkSZIkqSQGhCpVe1c7Lc07H4OwpanFLsaSJEmSJEklMSBUqdo623Y5SUlTNNnFWJIkSZIkqSQGhCpVe1f7LrsYtza12oJQkiRJkiSpJAaEKlVb165bENrFWJIkSZIkqTwGhCrVQFoQNjc1095tQChJkiRJklQGA0KVaiBjELY2tToGoSRJkiRJUkkMCFWqgcxi3NzUTFtXW0kVSZIkSZIkNTYDQpXqhc4XdtnFuKWpxRaEkiRJkiRJJTEgVKnautoGNIuxAaEkSZIkSVI5DAhVqrbOtgF1MXYWY0mSJEmSpHIYEKpUA2lB2NLU4izGkiRJkiRJJTEgVKnsYixJkiRJklRfDAhVKrsYS5IkSZIk1RcDQpWqrauNcU3jdrpNS1MLHd22IJQkSZIkSSqDAaFK1d7ZTkvTzlsQ2sVYkiRJkiSpPAaEKlVbVxutzTsfg9AuxpIkSZIkSeUxIFSp2rvaBzSLsV2MJUmSJEmSymFAqFINpAVha1MrnV2dJVUkSZIkSZLU2AwIVaqBtCBsbmqmvdsuxpIkSZIkSWUwIFSp2jvbd9mCsKWpxUlKJEmSJEmSSmJAqFK1dw9sFuPObrsYS5IkSZIklcGAUKVq62xjXPO4nW7T0tRCW1dbSRVJkiRJkiQ1NgNClaqju2OXLQjHNY+jrdOAUJIkSZIkqQwGhCpVW2fbLicpGd8y3haEkiRJkiRJJTEgVKk6ujt2OUlJczTTnd2OQyhJkiRJklQCA0KVqr2rfZctCCOC8c3j7WYsSZIkSZJUAgNClWZrq8BdjUEIML55PFs6t5RQlSRJkiRJUmOrJCCMiNMi4qGIWB4RF/WxPiLic8X6eyLi+F7rmyPizoj4XnlVa6g6ujoY1zSOiNjltuNbxvNC5wslVCVJkiRJktTYSg8II6IZ+DzwBuAI4KyIOKLXZm8A5hW384Ev9Fr/QWDpCJeqYdbW1bbL8Qe3Gtc8zoBQkiRJkiSpBFW0IDwRWJ6ZD2dmO3ANcEavbc4AvpI1vwamRsT+ABExG3gjcHmZRWvo2rvaBxwQjm+2BaEkSZIkSVIZqggIZwErezxeVSwb6DafAf4K6N7Zk0TE+RGxOCIWr1u3bkgFa3i0dbbtcoKSrca1jGNLh2MQSpIkSZIkjbQqAsK+BqDLgWwTEW8C1mbmkl09SWZelpkLM3PhjBkzdqdODbP2rnbGNY8b0La2IJQkSZIkSSpHFQHhKuDAHo9nA08McJtXAG+OiBXUuia/NiK+OnKlajg5BqEkSZIkSVL9qSIgvB2YFxFzI2IccCawqNc2i4BzitmMTwI2ZObqzPxIZs7OzDnFfj/OzLNLrV67rb2rfeBdjA0IJUmSJEmSStFS9hNmZmdEXAD8CGgGrsjM+yPifcX6S4HrgdOB5cDzwLvKrlPDr61z4C0IW5tbDQglSZIkSZJKUHpACJCZ11MLAXsuu7TH/QTev4tj/AT4yQiUpxEymBaE45vHs6XTSUokSZIkSZJGWhVdjNWgBjMGYWuTLQglSZIkSZLKYECo0gymBaFdjCVJkiRJksphQKjStHW20dI0sF7tBoSSJEmSJEnlMCBUadq72gfcxXh883i2dDgGoSRJkiRJ0kgzIFRp2roG14LQSUokSZIkSZJGngGhSjOYMQjHNY0zIJQkSZIkSSqBAaFKM5gxCMc1j7OLsSRJkiRJUgkMCFWaFzpfYFzzuAFtO75lvJOUSJIkSZIklcCAUKXZ3LGZ8c3jB7StLQglSZIkSZLKYUCo0mxq38T4lkEEhI5BKEmSJEmSNOIMCFWaTe2bmNAyYUDbjmseZxdjSZIkSZKkEhgQqjQb2zYysWXigLY1IJQkSZIkSSqHAaFKs7lj86BaENrFWJIkSZIkaeQZEKo0g+1i3NbZNsIVSZIkSZIkyYBQpdncsZkJrY5BKEmSJEmSVE8MCFWaze2bBzwG4fjm8QaEkiRJkiRJJTAgVGme73jeWYwlSZIkSZLqjAGhSjPYSUrauhyDUJIkSZIkaaQZEKo0g21B6CQlkiRJkiRJI8+AUKV5vuP5AY9B2NLUQld20dXdNcJVSZIkSZIkNTYDQpWiO7tp62xjfMv4AW0fEUOaqGRj28bd2k+SJEmSJKnRGBCqFFu7FzfFwN9yk8dNZkPbhkE/19rNa5l5yUx+verXg95XkiRJkiSp0RgQqhSb2zczsXVg3Yu32nP8njyz5ZlBP9etK29lj9Y9+NNv/akzIUuSJEmSJO2CAaFKsblj84DHH9xqyvgprN+yftDP9YvHfsEfHPYHNDc188C6Bwa9vyRJkiRJUiMxIFQpNrfvRkA4bgrPvDD4FoS/XPlLFsxcwIF7Hsjy9csHvb8kSZIkSVIjMSBUKTZ3bGZC64RB7bM7LQg7ujq4+8m7mb/PfPadvC+/Xf/bQe0vSZIkSZLUaAwIVYrN7ZuZ0DK4gHCP1j0GHRA+sO4B9pu8H3uM24MDphzAQ08/NKj9JUmSJEmSGo0BoUqxO2MQTh43edAB4SPPPsKsKbMAOGDKAXYxliRJkiRJ2gUDQpVic/tmxreMH9Q+U8ZN4ennnx7UPiueXcHMPWYCMGvKLB5+5uFB7S9JkiRJktRoDAhVik3tm5jQPPgxCJ/eMriA8OFnHt4WEM6YNIOntzzNlo4tgzqGJEmSJElSIzEgVCk2dwy+BeGe4/ccdBfjh595mH0n7wtAc1OzrQglSZIkSZJ2wYBQpdidSUp2ZwzCRzc8yn6T99v2eP8p+7Pi2RWDOoYkSZIkSVIjMSBUKTa1b2J88+BbED77wrOD2mflhpXst8fvAsJpE6axZtOaQR1DkiRJkiSpkRgQqhSbOjYNugXhlHFTeOaFZwa8/YYXNtDZ3cme4/fctmzqhKkGhJIkSZIkSTthQKhSrN20lqkTpg5qn8njJrOxbSPd2T2g7R/d8Cj7T96fiNi2bNrEaTyx8YlBPa8kSZIkSVIjMSBUKZ7Y9ATTJ00f1D7NTc1Map3Ec23PDWj7Fc+u2DZByVbTJ07niU0GhJIkSZIkSf2pJCCMiNMi4qGIWB4RF/WxPiLic8X6eyLi+GL5gRFxS0QsjYj7I+KD5Vev3fHkpieZPmFwASEMbibjR599lJl7zNxu2fQJ01m9cfWgn1eSJEmSJKlRlB4QRkQz8HngDcARwFkRcUSvzd4AzCtu5wNfKJZ3An+ZmfOBk4D397Gv6tCTm59k70l7D3q/aROn8fhzjw9o20eefYQZk2Zst2zvSXvz5OYnB/28kiRJkiRJjaKKFoQnAssz8+HMbAeuAc7otc0ZwFey5tfA1IjYPzNXZ+YdAJm5EVgKzCqzeA3elo4tvNDxAlPGTRn0vkfNPIobH74RgPau9p3OatxfF+O1m9cO+nklSZIkSZIaRRUB4SxgZY/Hq9gx5NvlNhExBzgOuK2vJ4mI8yNicUQsXrdu3VBr1hCs2bSGvSftvd3kIQN14qwT+d5/fY9Hn32UE790IidfeXK/k5Y8uuFR9t1j+4BwYstEMpONbRt3q3ZJkiRJkqSxroqAsK+UKAezTURMBr4FfCgz+5zBIjMvy8yFmblwxowZfW2ikmwNCHfHkTOPZPn65bz6ylfzsgNfRntXO9ctva7PbVduWLnDGIQRwT6T9mHNpjW79fySJEmSJEljXRUB4SrgwB6PZwO9p5ntd5uIaKUWDn4tM/tOilRXVm9azd4Tdy8gbGlq4fcO/j1OmXsKb1/wdt559Du5+BcX77DdC50vsOGFDX0GkXtP2tuAUJIkSZIkqR9VBIS3A/MiYm5EjAPOBBb12mYRcE4xm/FJwIbMXB21PqpfBpZm5qfLLVu7a82mNUydMHW39//Ll/8l5xxzDgAvOeAlLH1q6Q5dhlduWMnMyTNpih3f0tMnTDcglCRJkiRJ6kfpAWFmdgIXAD+iNsnINzLz/oh4X0S8r9jseuBhYDnwJeC/F8tfAbwTeG1E3FXcTi/3DDRYT2x8gmkTpg3LscY1j+PwvQ/n1lW3brf80Q2Pst8e+/W5z9QJU1m9afWwPL8kSZIkSdJY01LFk2bm9dRCwJ7LLu1xP4H397HfL+h7fELVsSc2PsG0icMTEAIcMeMIfv7ozzn1kFO3LXv02UeZOXlmn9tPnTCV1RsNCCVJkiRJkvpSRRdjNZjHNjzGPpP2GbbjHTXzKH766E+3W/bbZ37LjEl9T0YzfdJ0ntjYe5hLSZIkSZIkgQGhRtgLnS/wm8d/w4IZC4btmAtmLmDJ6iV0dHVsW3b3k3czd+rcPrefPnE6T2wyIJQkSZIkSeqLAaFG1E9W/IRDph/CXhP2GrZjTh43mQOmHMDdT969bdn9a+9n7rT+A0InKZEkSZIkSeqbAaFG1KKHFnHiAScO+3GP2OcIfrXyVwBsbt/Mk5ufZNaUWX1uu/fEvVm7ee2w1yBJkiRJkjQWGBBqxDz+3ON884Fv8oqDXjHsx54/Yz6/eOwXADyw7gHm7DWH5qbmPredOmEq67esp6u7a9jrkCRJkiRJGu0MCDUiOro6eON/vpE/evEfcdBeBw378RfMWLCtBeG9a+9lzrQ5/W7b0tTCnuP3ZN3z64a9DkmSJEmSpNHOgFAj4it3f4XWplbOPPLMETn+7D1n09bVxgPrHuCuNXftMoTcZ9I+jkMoSZIkSZLUBwNCDbv2rnb+7qd/xznHnkNEjMhzRARvPvzNXHTTRXzt3q/xigN33o15+sTprN64ekRqkSRJkiRJGs0MCDXsfvzIj5k6cSpHzTxqRJ/nzYe9mZsevolT5p6yyxaE0yZMswWhJEmSJElSHwwINeyuX3b9iMxc3NteE/bi4tddzHnHnrfLbadOmDrkgPDWlbdy8pUns+GFDUM6jiRJkiRJUj0xINSw+8HyH3DCrBNKea6j9z2aSa2Tdrnd9InTWfncyiE91yd+/gke2/AYb7/27UM6jiRJkiRJUj0xINSweuSZR3hmyzMcOv3QqkvZzn6T9+ORZx/Z7f0feuohblt1G/96+r9y66pbeXLTk8NYnSRJkiRJUnUMCDWsbn7kZl5ywEtoivp6a+03eT9WPLNit/f/1tJv8Zo5r2FS6ySOnnk0P3/s58NXnCRJkiRJUoXqK8XRqPezR3/GghkLqi5jB/tN3o/HnnuMzNyt/X+58pcsmFk7ryNnHsktK24ZzvIkSZIkSZIqY0A4BrV3tXPvk/fSnd2lP/cvHvvFiM9evDsmj5tMa1MrTz3/1KD3zUx+8/hvOGLGEQActe9R/HTFT4e7REmSJEmSpEoYEI5B//Krf+GkL5/EsZceO6wh4fce+h5nXXsW/++h/9fn+jWb1vD0lqc5eOrBw/acw+mAKQew4tkVg95vxbMraIomZkyaAcBhex/GimdX8OwLzw5vgZIkSZIkSRUwIBxjNrdv5tO//jSfP/3ztHe1c/PDNw/bcf/se3/G5PGTOfc75/bZEu+Xj/2So2YeVXfjD261uxOV3LrqVo6YcQQRAUBLUwuHTDuEe568Z7hLlCRJkiRJKl19Jjnabf9xz3+wYMYC5kydw+nzTuffbv+3YTnu5277HEfOOJJ3HPUOXjPnNfzdT/9uh21ufuTmuhx/cKuZe8zcrRaEt666lcP2Pmy7ZXOnzTUglCRJkiRJY4IB4Rhz3dLreM2c1wBwytxTuOnhm4alK+yVd1/JH87/QwDecfQ7uOruq9jwwobttvnh8h9ywqwThvxcI2XfPfblt+t/O+j9bn/8dg7f+/Dtls2ZOoc7V985XKVJkiRJkiRVxoBwDHm+43luXXUrLzngJQDsMW4Pjtr3qCF3M1729DLWb1nPi/d5MQDTJ07nhANO4Kv3fHXbNg8/8zAb2zbyomkvGtJzjaRZe87iwacfHNQ+Xd1d3Lv23h1aEB4y7RDuevKuYaxOkiRJkiSpGgaEY8hPVvyEw/Y+jMnjJm9bdtx+x/GD5T8Y0nEXPbSIl89++XZjC75h3hv4/O2fJzMB+NHyH7HwgIV1O/4gwPx95nPH6jvo6OoY8D4PPvUg+0zaZ7vXFGpdjB986kG6uruGu0xJkiRJkqRS1W+ao0H7/rLv85L9X7LdshNmncAPl/9wW5C3O7770Hd56eyXbrfsuP2Oozu7uW7pdXRnN5fdcRkvP/Dlu/0cZZgyfgr7T96fO9f8rmtwZrLkiSWs2bSmz32WrF7CYdMP22H55HGTmTZhGr99ZvBdliVJkiRJkuqJAeEYcv2y6zlx1onbLTt4r4Ppyi6WPrW0z31+u/63PN/xfL/H3Ni2kTtW38Fx+x233fKmaOLdx72bC2+6kE/98lO0d7XzioNeMfSTGGFHzjySnz/6c6DWffhNV7+JN/7nG3np5S/lsQ2P7bD97U/czqHTD+3zWIdOP5S71tw1kuVKkiRJkiSNOAPCMWLZ08vY3L6ZQ6Ydst3yiOBls1/Gdx/87g77XHHnFRz7xWPZ95J9+fEjP+7zuD9+5McsmLmAia0Td1h3wgEn8MqDXsm/3/Xv/LeX/Le67l681ZEzj+SWFbcA8ImffYI1G9fwtT/6Gqcecirnfee8Hbb/2YqfccTMI/o81iHTDmHJE0tGslxJkiRJkqQRV/+JjgbkB8t/wImzTiQidlj38gNfznVLr9tu2eInFnPhTRfy+dM/z/9+1f/mvO+cx3Ntz+2w7/XLrt+h2/JWEcF5x57HpW+6lKP3PXp4TmSEHb//8dz2+G2c8+1z+OKSL/KRV32E5qZm/uSIP+HBpx7ktlW3bdt27ea1PPLsI8zfZ36fxzp070O5/YnbyypdkiRJkiRpRBgQjhHfefA7LDxgYZ/rjtn3GP5r/X/xxMYngNq4e3/xg7/gXce+i4P2OoiXzn4pC2Ys4JJfXbLdfpnJD5b/gBMOOGHE6y/L1AlT+ZdT/4WHn3mYS069hH0m7QNAa3Mrb1/wdj7+049v2/amh2/i+P2Pp6Wppc9jHTb9MO5ac9eQxneUJEmSJEmqmgHhGPDwMw9z15q7eNnsl/W5vrW5ld87+Pf4zK8/A8CX7/wyz77wLKcdetq2bd5x9Dv4/O2fZ2Pbxm3Lbl11Ky1NLcyZOmckyy/dQXsdxCde+wkOmHLAdsvfMO8NLFm9hDtW3wHUWmX2Hnuxp70n7U1LUwsrn1s5ovVKkiRJkiSNJAPCUeT6Zdfzzm+/k4/e/FHWb1m/bfmliy/l1ENOZXzL+H73PeeYc7j8jsv5t9v/jQtvupC/evlfbTdm4Ow9Z/OS/V/CZ2/77LZl/37nv/O6F72uz27LY9G45nH8yRF/wkU3XcSDTz3I9cuu56TZJ+10n8P2PsxxCCVJkiRJ0qhmQDhKXLbkMt713XcxY9IM7lt7Hwv+bQHXL7ueXzz2C75855d502Fv2un++0zahwtOvIBvP/htPvTSDzF32twdtjn3mHP59K2f5omNT/DMlme4dum1vP5Frx+pU6pLbzrsTWx4YQPHXnosZx91NvtO3nen2y+YsYCbHrmppOokSZIkSZKGXzTC+GkLFy7MxYsXV13Gbvv5oz/nj77xR3zm9z/DrD1nAXD747dz+Z2X8/hzj/P/vfr/46WzXzosz/XlO77MA089wPjm8Ry414H8+cI/H5bjjiZd3V0sWb2EEw44YZetJ5evX84//uIf+e0HfltSddqZiFiSmX0PxilJkiRJkvrU9+wLqhtrNq3h7de+nQ+/7MPbwkGAE2adwAmzTiAzh7UL8HnHnscNv72BxzY8xnuPf++wHXc0aW5q5sRZJw5o2xdNexHPvfAcDz/zMC+a9qIRrkySJEmSJGn4GRBW7ImNT7B8/XJm7jGTw/Y+bLtxATe1b+It17yF0w49rd8WgsM9PmBzUzNvmPeGYT3mWNYUTSw8YCHXL7ueC068oOpyJEmSJEmSBs2AsCK/WvkrPnLzR7hnzT0cNPUg1m9ZT0dXB380/484Ze4ptHW18Q8//wcOmXYIZx99dtXlaidOO/Q0PvXLT/He49/LhJYJg9p35YaVfOa2z/Dos4/yxnlv5Lxjz2uYSWEkSZIkSVJ9cAzCkj2z5Rn+8oa/5Ppl13PesedxytxTaG1uBeCxDY/xs0d/xvL1ywF41UGv4rVzX2tgNAp87JaPcfR+R/Pe497LDb+9gUX/tYimaOLso87mXce9i5amHbP421bdxpuveTMnzzmZQ6YdwqKHFnHgXgfyzbd9k8njJldwFqOfYxBKkiRJkjR4BoQlaets44o7r+BjP/kYrzzolbznuPewx7g9Kq1Jw2ft5rV8acmXePDpBzluv+N4+YEvJzP55gPfZI9xe3Ddn1zHjD1mbNv+l4/9kjdf82Y+/LIP87IDXwZAZ3cnn/n1Z1j3/Dp+8I4fMH3i9KpOZ9QyIJQkSZIkafAqCQgj4jTgs0AzcHlmXtxrfRTrTweeB87LzDsGsm9fqgoIn2t7jsVPLOb7y77P1+75GnOnzeW8Y8/j8L0PL70WVaOru4ur7r6KHz/yY77wxi/we3N+j6/f93UuuukiLnzlhTtMhtKd3XxpyZe4a81dfPes73LY3oft1vNu/blutNanBoSSJEmSJA1e6QFhRDQD/wW8HlgF3A6clZkP9NjmdOAvqAWELwU+m5kvHci+fSkjIFy/ZT23rryV2x6/jSWrl3Df2vtYt3kd8/aex7H7Hstr5r6GOVPnjGgNql+/efw3XHX3VSx7ehlHzTyKC068gLnT5va7/aKHFnHlXVfy7uPezZ8s+BPmTZ/HlPFT+uyqvFV3dnPTwzfxhdu/wM2P3MzG9o3MmTqHP57/x7z/hPfv9PnK1tHVwZpNa2hpamG/yfsNW5BpQChJkiRJ0uBVERC+DPjbzPz94vFHADLzH3ts80XgJ5l5dfH4IeBkYM6u9u3LSASET256kl+u/CW3rLiFWx65hRXPrmDBzAUctvdhHDrtUOZOm8usKbNobmoe1ufV6NbV3TXg98TqjatZ9NAi7lxzJ49vfJznO56ntal124zXx+x3DIdOO5SWphYeeOoBvvPgdxjXPI43HfYmXnHgK5g6YSoPP/MwNz18Ez/67Y84dt9jed2LXsfsPWfTnd1s6dxCEEyfOJ1Dph/CghkLmNg6ccTOfc2mNSx6aBHXPnAtv1r5KyaPm0xHdwcAb5z3Rs495lxOnnPykH5mDAglSZIkSRq8KgLCtwKnZeZ7i8fvBF6amRf02OZ7wMWZ+Yvi8c3AhdQCwp3u25fBBISrnlvFl5Z8ia7sorO7k7bONja1b+KpLU+x6rlVLHt6GRvaNgAwvnk8R+97NMftdxzz9p6309Zd0lBlJu1d7Tz1/FOs2LCCFc+s4MnNT9Kd3ew7eV9OOOAEDt/78D5b47V1tnHb47fxwLoHePaFZ4kIxjWPA2DDCxu2vacBJo+bzD6T9qG1qZUtnVtYv2U9z3c8v8Mxg2D2nrOZvedsZuwxgynjai0ck6Sts42N7Rt5anOt1rWb1wIwfeJ0XnnQKznhgBO2TcSyZtMafvHYL/jlyl8CsN/k/Th2v2M5cM8D2Wv8Xrz7uHczf8b8Ab1GBoSSJEmSJA1eFYlWX30Je6eU/W0zkH1rB4g4Hzi/eLipaIW4a3uwD3tycJ/rngcmAd100EV7G215O7V/decFWplAR9VlDIi1DtnjPM4d3LH9wsHWGgTNTNgUm5o3san32m666STpBoImmjOyZSW1f7uUdNHFC+tzfS6i9q/PWpsZt6Zpzbgf8sNtqy7ZdMnjbGTNAM+i759dSZIkSZLUryoCwlXAgT0ezwaeGOA24wawLwCZeRlw2VCL7SkiFuezo6N1UkQszo3WOtysdWSMplolSZIkSRprmip4ztuBeRExNyLGAWdC7+ZELALOiZqTgA2ZuXqA+0qSJEmSJEkaoNJbEGZmZ0RcAPwIaAauyMz7I+J9xfpLgeupzWC8nFrH3nftbN+yz0GSJEmSJEkaKyqZVSMzr6cWAvZcdmmP+wm8f6D7lmhYuyyPMGsdGdY6MkZTrZIkSZIkjSmlz2IsSZIkSZIkqX5UMQahJEmSJEmSpDphQDhAEXFaRDwUEcsj4qKq6+kpIg6MiFsiYmlE3B8RHyyWT4+IGyNiWfF1WtW1AkREc0TcGRHfKx7Xa51TI+LaiHiweG1fVse1/o/ie39fRFwdERPqpdaIuCIi1kbEfT2W9VtbRHyk+Dl7KCJ+v4qaJUmSJElqJAaEAxARzcDngTcARwBnRcQR1Va1nU7gLzNzPnAS8P6ivouAmzNzHnBz8bgefBBY2uNxvdb5WeCHmfli4BhqNdddrRExC/gAsDAzj6Q2gc+Z1E+tVwKn9VrWZ23F+/ZMYEGxz78VP3+SJEmSJGmEGBAOzInA8sx8ODPbgWuAMyquaZvMXJ2ZdxT3N1ILsmZRq/GqYrOrgLdUUmAPETEbeCNweY/F9VjnnsCrgS8DZGZ7Zj5LHdZaaAEmRkQLMAl4gjqpNTN/Bqzvtbi/2s4ArsnMtsx8hNpM5ieWUackSZIkSY3KgHBgZgErezxeVSyrOxExBzgOuA3YNzNXQy1EBGZWWNpWnwH+Cujusawe63wRsA7496I79OURsQd1WGtmPg5cAjwGrAY2ZOYN1GGtPfRX26j5WZMkSZIkaawwIByY6GNZ3U3/HBGTgW8BH8rM56qup7eIeBOwNjOXVF3LALQAxwNfyMzjgM3UQXfivhTj950BzAUOAPaIiLOrrWq3jYqfNUmSJEmSxhIDwoFZBRzY4/Fsal0460ZEtFILB7+WmdcVi5+MiP2L9fsDa6uqr/AK4M0RsYJaN+3XRsRXqb86ofY9X5WZtxWPr6UWGNZjra8DHsnMdZnZAVwHvJz6rHWr/mqr+581SZIkSZLGGgPCgbkdmBcRcyNiHLVJFBZVXNM2ERHUxspbmpmf7rFqEXBucf9c4Ltl19ZTZn4kM2dn5hxqr+GPM/Ns6qxOgMxcA6yMiMOLRacAD1CHtVLrWnxSREwq3gunUBuHsh5r3aq/2hYBZ0bE+IiYC8wDflNBfZIkSZIkNYzItPfeQETE6dTGz2sGrsjMf6i2ot+JiFcCPwfu5Xdj+32U2jiE3wAOohYivS0ze08WUYmIOBn4cGa+KSL2pg7rjIhjqU2mMg54GHgXtVC9Hmv9OPB2ajNa3wm8F5hMHdQaEVcDJwP7AE8CHwO+019tEfHXwLupncuHMvMHZdcsSZIkSVIjMSCUJEmSJEmSGphdjCVJkiRJkqQGZkAoSZIkSZIkNTADQkmSJEmSJKmBGRBKkiRJkiRJDcyAUJIkSZIkSWpgBoQaVhExJyLuq7qOqjT6+UuSJEmSpNHHgFB1LyJaRtNxJUmSJEmSRhMDQo2E5oj4UkTcHxE3RMTEiDg2In4dEfdExLcjYhpARPwkIhYW9/eJiBXF/fMi4psR8f+AGyJi/4j4WUTcFRH3RcSriu02RcS/RMQdEXFzRMwolh8SET+MiCUR8fOIeHGx/MqI+HRE3AL8U0TcGxFTo+bpiDin2O4/IuJ1EdEcEZ+KiNuL2v/b1pOMiP/VY/nHe78IEfGiiLgzIk4Y0VdbkiRJkiRpCAwINRLmAZ/PzAXAs8AfA18BLszMo4F7gY8N4DgvA87NzNcCfwr8KDOPBY4B7iq22QO4IzOPB37a47iXAX+RmS8BPgz8W4/jHga8LjP/Evgl8ApgAfAw8Kpim5OAXwPvATZk5gnACcCfRcTciDi1OM8TgWOBl0TEq7c+QUQcDnwLeFdm3j6Ac5UkSZIkSaqEXSw1Eh7JzLuK+0uAQ4CpmfnTYtlVwDcHcJwbM3N9cf924IqIaAW+0+P43cDXi/tfBa6LiMnAy4FvRsTWY43vcdxvZmZXcf/nwKuBR4EvAOdHxCxgfWZuKoLAoyPircX2e1ELBk8tbncWyycXyx8DZgDfBf44M+8fwHlKkiRJkiRVxhaEGgltPe53AVN3sm0nv3sfTui1bvPWO5n5M2pB3uPAf2ztCtyHLI73bGYe2+M2v6/jAj+j1mrwVcBPgHXAW6kFhwBBrSXi1uPMzcwbiuX/2GP5oZn55WKfDcBKai0TJUmSJEmS6poBocqwAXhm67iBwDupdQcGWAG8pLj/VvoREQcDazPzS8CXgeOLVU099vtT4BeZ+RzwSES8rdg3IuKYvo6bmSuBfYB5mfkw8AtqXZK3BoQ/Av68aLlIRBwWEXsUy99dtFYkImZFxMxin3bgLcA5EfGnO3thJEmSJEmSqmYXY5XlXODSiJhEbay/dxXLLwG+ERHvBH68k/1PBv5XRHQAm4CtLQg3AwsiYgm1IPLtxfJ3AF+IiP8NtALXAHf3c+zbgObi/s+Bf6QWFAJcDswB7ohaf+V1wFsy84aImA/cWnRj3gScTa3FJJm5OSLeBNwYEZsz87s7OTdJkiRJkqTKRGZWXYO02yJiU2ZOrroOSZIkSZKk0couxpIkSZIkSVIDswWhJEmSJEmS1MBsQShJkiRJkiQ1MANCSZIkSZIkqYEZEEqSJEmSJEkNzIBQkiRJkiRJamAGhJIkSZIkSVIDMyCUJEmSJEmSGpgBoSRJkiRJktTADAglSZIkSZKkBmZAKEmSJEmSJDUwA0JJkiRJkiSpgbVUXYAkSZJUhX322SfnzJlTdRmSRtiSJUueyswZVddRz7weSo2jv2uiAaEkSZIa0pw5c1i8eHHVZUgaYRHxaNU11Duvh1Lj6O+aaBdjSZIkSZIkqYEZEEqSJEmSJEkNzIBQkiRJkiRJamAGhJIkSZIkSVIDMyCUJEmSJEmSGpgBoSRJkiRJktTADAglSZIkSZKkBmZAKEmSJEmSJDUwA0JJkiRJkiSpgRkQSpIkaVSJiA9GxH0RcX9EfKhYNj0iboyIZcXXaRWXqToTETvcpNEuIq6IiLURcV+v5X8REQ8V18l/rqo+SaOHAaEkSZJGjYg4Evgz4ETgGOBNETEPuAi4OTPnATcXjyWA7cLAs846q8/l0ih1JXBazwUR8RrgDODozFwAXFJBXZJGGQNCSZIkjSbzgV9n5vOZ2Qn8FPhDar8MX1VscxXwlmrKUz3LTP7zP/+TzKy6FGlYZObPgPW9Fv85cHFmthXbrC29MEmjjgGhJEmSRpP7gFdHxN4RMQk4HTgQ2DczVwMUX2f2tXNEnB8RiyNi8bp160orWtXr2XKwr8fSGHIY8KqIuC0ifhoRJ/S1kdfDsa2vYRV296bGYEAoSZKkUSMzlwL/BNwI/BC4G+gcxP6XZebCzFw4Y8aMEapS9ejqq6/myCOPpLm5mSOPPJKrr7666pKkkdICTANOAv4X8I3oI+Xxeji2ZeYubwdf+L0BbafGYEAoSZKkUSUzv5yZx2fmq6l1rVsGPBkR+wMUX+1Spx3cf//9vO1tb+P++++vuhRpJK0Crsua3wDdwD4V1ySpzhkQSpIkaVSJiJnF14OAPwKuBhYB5xabnAt8t5rqVI8WLFiw7f7Xv/71PpdLY8h3gNcCRMRhwDjgqSoLklT/WqouQJIkSRqkb0XE3kAH8P7MfCYiLqbWje49wGPA2yqtUHVl6dKltLe309raum1ZR0cHEyZMqLAqaegi4mrgZGCfiFgFfAy4ArgiIu4D2oFz036iknbBgFCSJEmjSma+qo9lTwOnVFCORoH58+cza9Ysek7EMGPGDObPn19hVdLQZWZ/s+2cXWohkkY9uxhLkiRJGtNWr17NunXrWLBgAY8++igLFixg3bp1rF69uurSJEmqCwaEkiRJksa09evXM2/ePADmzp0LwLx581i/fn2VZUmSVDfsYixJkiRpzPvpT3/K/vvvv+3x6tWrOeCAAyqsSJKk+mFAKEmSJGnM+73f+z3GjRvH0qVLmT9/Pu3t7VWXJElS3bCLsSRJkqQxbfr06SxbtgyARx55BIBly5Yxffr0KsuSJKlu2IJQkiRJ0pi2//7709zczP3338/BBx8M1GYxnjlzZsWVSZJUHwwIJUmSJI1pS5cu5YUXXqC1tXXbso6ODiZMmFBhVZIk1Q+7GEuSJEka0+bPn8/HP/5xjjzySJqbmznyyCP5+Mc/zvz586suTZKkumBAKEmSJGlMe81rXsM//dM/8e53v5uNGzfy7ne/m3/6p3/iNa95TdWlSZJUFwwIJUmSJI1pt9xyCxdeeCFXXHEFU6ZM4YorruDCCy/klltuqbo0SZLqgmMQSpIkSRrTli5dyp133sknPvGJbcs6Ojr4x3/8xwqrkiSpftiCUJIkSdKYNn/+fGbNmkVEbLvNmjXLMQglSSoYEEqSJEka01avXs26detYsGABjz76KAsWLGDdunWsXr266tIkSaoLBoSSJEmSxrT169dz6KGHAjB37lwADj30UNavX19lWZIk1Q3HIJQkSZI05v3sZz9j//333/Z49erVHHDAARVWJElS/TAglCRJkjTmGQZKktQ/uxhLkiRJaghNTU3cdNNNNDX5a5AkST3ZglCSJElSQ+ju7uZ1r3td1WVIklR3/NOZJEmSpDHvnnvuITO33e65556qS5IkqW7YglCSJEnSmHf00UdXXYIkSXXLFoSSJEmSGsa1115bdQmSJNUdA0JJkiRJDeOtb31r1SVIklR3DAglSZIkjXmOQShJUv8cg1CSJEnSmOcYhJIk9c8WhJIkSZIaxjXXXFN1CZIk1R0DQkmSJEkN48wzz6y6BEmS6o4BoSRJkqQxb8mSJduNQbhkyZKqS5IkqW44BqEkSZKkMe8lL3lJ1SVIklS3bEEoSZIkqWF84AMfqLoESZLqjgGhJEmSpIbxuc99ruoSJEmqOwaEkiRJksa8Sy65ZLsxCC+55JKqS5KGLCKuiIi1EXFfH+s+HBEZEftUUZuk0cWAUJIkSaNKRPyPiLg/Iu6LiKsjYkJETI+IGyNiWfF1WtV1qr58+MMfJiK23T784Q9XXZI0HK4ETuu9MCIOBF4PPFZ2QZJGJwNCSZIkjRoRMQv4ALAwM48EmoEzgYuAmzNzHnBz8Vjawetf//qqS5CGTWb+DFjfx6r/A/wVkOVWJGm0MiCUJEnSaNMCTIyIFmAS8ARwBnBVsf4q4C3VlKZ6d+ONN1ZdgjSiIuLNwOOZefcutjs/IhZHxOJ169aVVJ2kemVAKEmSpFEjMx8HLqHWbW41sCEzbwD2zczVxTargZl97e8vxI3rk5/85HZjEH7yk5+suiRp2EXEJOCvgb/Z1baZeVlmLszMhTNmzBj54iTVNQNCSZIkjRrF2IJnAHOBA4A9IuLsge7vL8SN66Mf/eh2YxB+9KMfrbokaSQcQu36eHdErABmA3dExH6VViWp7hkQSpIkaTR5HfBIZq7LzA7gOuDlwJMRsT9A8XVthTWqjv3xH/9x1SVIIyYz783MmZk5JzPnAKuA4zNzTcWlSapzBoSSJEkaTR4DToqISRERwCnAUmARcG6xzbnAdyuqT3XuW9/6VtUlSMMmIq4GbgUOj4hVEfGeqmuSNDoZEEqSJGnUyMzbgGuBO4B7qX2evQy4GHh9RCwDXl88lrb56le/ut0YhF/96lerLkkassw8KzP3z8zWzJydmV/utX5OZj5VVX2SRo+WqguQJEmSBiMzPwZ8rNfiNmqtCaU+nX322Zx99oCHq5QkqaHYglCSJElSw3jPe+yBKUlSbwaEkiRJkhrGl7/85V1vJElSgzEglCRJkjTmXXnllduNQXjllVdWXZIkSXXDMQglSZIkjXnnnXce5513XtVlSJJUl2xBKEmSJKlhvOpVr6q6BEmS6o4BoSRJkqSG8fOf/7zqEiRJqjsGhJIkSZLGvPe9733bjUH4vve9r+qSJEmqG45BKEmSJGnMu/TSS7n00kurLkOSpLpkC0JJkiRJDePggw+uugRJkuqOAaEkSZKkhvHoo49WXYIkSXXHgFCSJEnSmHfWWWdtNwbhWWedVXVJkiTVDQNCSZIkSWPe1VdfvdPHkiQ1MicpkSRJktQQIoKzzjrLcFDSqHXMx29gw5aOYTvenIu+PyzH2WtiK3d/7NRhOZaqYUAoSZIkaUzLTCIC2L7lYGZWVZIk7ZYNWzpYcfEbqy5jB8MVNKo6BoSSJEmSRr2tAeBw7WN4KElqJI5BKEmSJGnU6zkByc5uB1/4vQFtJ0lSIzEglCRJkiRJkhqYAaEkSZIkSZLUwAwIJUmSJEmSpAZmQChJkiRJkiQ1MANCSZIkSZIkqYEZEEqSJEmSJEkNzIBQkiRJkiRJamAGhJIkSZIkSVIDMyCUJEmSJEmSGpgBoSRJkiRJktTADAglSZIkSZKkBmZAKEmSJEmSJDUwA0JJkiRJkiSpgRkQSpIkSZI0CkXEFRGxNiLu67HsUxHxYETcExHfjoipFZYoaZQwIJQkSZIkaXS6Ejit17IbgSMz82jgv4CPlF2UpNHHgFCSJEmjRkQcHhF39bg9FxEfiojpEXFjRCwrvk6rulZJGmmZ+TNgfa9lN2RmZ/Hw18Ds0guTNOoYEEqSJGnUyMyHMvPYzDwWeAnwPPBt4CLg5sycB9xcPJakRvdu4Ad9rYiI8yNicUQsXrduXcllSao3BoSSJEkarU4BfpuZjwJnAFcVy68C3lJVUZJUDyLir4FO4Gt9rc/MyzJzYWYunDFjRrnFSao7LVUXIEmSJO2mM4Gri/v7ZuZqgMxcHREz+9ohIs4Hzgc46KCDSilSksoWEecCbwJOycysuh5J9c8WhJIkSRp1ImIc8Gbgm4PZzxYzksa6iDgNuBB4c2Y+X3U9kkYHA0JJkiSNRm8A7sjMJ4vHT0bE/gDF17WVVSZJJYmIq4FbgcMjYlVEvAf4V2AKcGMxmdOllRYpaVSwi7EkSZJGo7P4XfdigEXAucDFxdfvVlGUJJUpM8/qY/GXSy9E0qhnC0JJkiSNKhExCXg9cF2PxRcDr4+IZcW6i6uoTZIkaTSyBaEkSZJGlWJMrb17LXua2qzGkiRJGiRbEEqSJEmSJEkNzIBQkiRJkiRJamAGhJIkSZIkSVIDMyCUJEmSJEmSGpgBoSRJkiRJktTADAglSZIkSZKkBmZAKEmSJEmSJDUwA0JJkiRJkiSpgRkQSpIkSZIkSQ3MgFCSJEmSJElqYAaEkiRJkiRJUgMzIJQkSZIkSZIamAGhJEmSJEmS1MAMCCVJkiRJkqQGZkAoSZIkSZIkNTADQkmSJEmSJKmBGRBKkiRJkiRJDcyAUJIkSZIkSWpgBoSSJEmSJElSAzMglCRJkiRJkhqYAaEkSZIkSZLUwAwIJUmSJEmSpAZmQChJkiRJkiQ1MANCSZIkSZIkqYEZEEqSJEmSJEkNzIBQkiRJkiRJamAGhJIkSZIkSVIDMyCUJEmSJGkUiogrImJtRNzXY9n0iLgxIpYVX6dVWaOk0cGAUJIkSZKk0elK4LReyy4Cbs7MecDNxWNJ2ikDQkmSJEmSRqHM/BmwvtfiM4CrivtXAW8psyZJo5MBoSRJkiRJY8e+mbkaoPg6s+J6JI0CLVUXIEmSJA1GREwFLgeOBBJ4N/AQ8HVgDrAC+JPMfKaaCiWp/kXE+cD5AAcddFDF1Wigpsy/iKOuqr9e41PmA7yx6jI0BAaEkiRJGm0+C/wwM98aEeOAScBHqY25dXFEXERtzK0LqyxSkiryZETsn5mrI2J/YG1fG2XmZcBlAAsXLswyC9Tu27j0YlZcXH9B3JyLvl91CRoiuxhLkiRp1IiIPYFXA18GyMz2zHwWx9ySpK0WAecW988FvlthLZJGCQNCSZIkjSYvAtYB/x4Rd0bE5RGxBwMccysizo+IxRGxeN26deVVLUkjICKuBm4FDo+IVRHxHuBi4PURsQx4ffFYknbKLsaSJEkaTVqA44G/yMzbIuKz1LoTD4hd6iSNJZl5Vj+rTim1EEmjni0IJUmSNJqsAlZl5m3F42upBYZPFmNtsbMxtyRJkrQjA0JJkiSNGpm5BlgZEYcXi04BHsAxtyRJknabXYwlSZI02vwF8LViBuOHgXdR+8P3N4rxtx4D3lZhfZIkSaOKAaEkSZJGlcy8C1jYxyrH3JIkSdoNdjGWJEmSJEmSGpgBoSRJkiRJktTADAglSZIkSZKkBmZAKEmSJEmSJDUwA0JJkiRJkiSpgRkQSpIkSZIkSQ3MgFCSJEmSJElqYAaEkiRJkiRJUgMzIJQkSZIkSZIamAGhJEmSJEmS1MBaqi5AkiRJkiRJAzPnou9XXcIO9prYWnUJGiIDQkmSJEmSpFFgxcVvHLZjzbno+8N6PI1udjGWJEmSJEmSGpgBoSRJkiRJktTADAglSZIkSZKkBmZAKEmSJEmSJDUwA0JJkiRJkiSpgRkQSpIkSZIkSQ3MgFCSJEmSJElqYAaEkiRJkiRJUgMzIJQkSZIkSZIamAGhJEmSJEmS1MAMCCVJkiRJkqQGZkAoSZIkSZIkNTADQkmSJEmSJKmBGRBKkiRJkiRJDcyAUJIkSZKkMSYi/kdE3B8R90XE1RExoeqaJNUvA0JJkiRJksaQiJgFfABYmJlHAs3AmdVWJameGRBKkiRJkjT2tAATI6IFmAQ8UXE9kuqYAaEkSZIkSWNIZj4OXAI8BqwGNmTmDdVWJameGRBKkiRJkjSGRMQ04AxgLnAAsEdEnN1rm/MjYnFELF63bl0VZUqqIwaEkiRJGlUiYkVE3BsRd0XE4mLZ9Ii4MSKWFV+nVV2nJFXodcAjmbkuMzuA64CX99wgMy/LzIWZuXDGjBmVFCmpfhgQSpIkaTR6TWYem5kLi8cXATdn5jzg5uKxJDWqx4CTImJSRARwCrC04pok1TEDQkmSJI0FZwBXFfevAt5SXSmSVK3MvA24FrgDuJfa7/6XVVqUpLpmQChJkqTRJoEbImJJRJxfLNs3M1cDFF9n9rWjY25JahSZ+bHMfHFmHpmZ78zMtqprklS/WqouQJIkSRqkV2TmExExE7gxIh4c6I6ZeRlFK5qFCxfmSBUoSZI0mtiCUJIkSaNKZj5RfF0LfBs4EXgyIvYHKL6ura5CSZKk0cWAUJIkSaNGROwREVO23gdOBe4DFgHnFpudC3y3mgolSZJGH7sYS5IkaTTZF/h2bVJOWoD/zMwfRsTtwDci4j3UZu98W4U1SpIkjSoGhJIkSRo1MvNh4Jg+lj8NnFJ+RZIkSaOfXYwlSZIkSZKkBmZAKEmSJEmSJDUwA0JJkiRJkiSpgRkQSpIkSZIkSQ3MgFCSJEmSJElqYAaEkiRJkiRJUgNrqboASZIkSdqZYz5+Axu2dAzb8eZc9P0hH2Ovia3c/bFTh6EaSZKqZ0AoSZIkqa5t2NLBiovfWHUZ2xmOkFGSpHphF2NJkiRJkiSpgRkQSpIkSZIkSQ3MgFCSJEmSJElqYAaEkiRJkiRJUgMzIJQkSZIkSZIamAGhJEmSJEmS1MAMCCVJkiRJkqQGZkAoSZIkSZIkNTADQkmSJEmSJKmBGRBKkiRJkiRJDcyAUJIkSZIkSWpgBoSSJEmSJElSAzMglCRJkiRJkhqYAaEkSZIkSZLUwAwIJUmSJEmSpAZmQChJkiRJkiQ1MANCSZIkSZIkqYEZEEqSJEmSNMZExNSIuDYiHoyIpRHxsqprklS/WqouQJIkSZIkDbvPAj/MzLdGxDhgUtUFSapfBoSSJEmSJI0hEbEn8GrgPIDMbAfaq6xJUn2zi7EkSZIkSWPLi4B1wL9HxJ0RcXlE7FF1UZLqlwGhJEmSJEljSwtwPPCFzDwO2Axc1HODiDg/IhZHxOJ169ZVUaOkOmJAKEmSJEnS2LIKWJWZtxWPr6UWGG6TmZdl5sLMXDhjxozSC5RUXwwIJUmSNOpERHPRbe57xePpEXFjRCwrvk6rukZJqkpmrgFWRsThxaJTgAcqLElSnTMglCRJ0mj0QWBpj8cXATdn5jzgZnp1pZOkBvQXwNci4h7gWOCT1ZYjqZ4ZEEqSJGlUiYjZwBuBy3ssPgO4qrh/FfCWksuSpLqSmXcVXYiPzsy3ZOYzVdckqX4ZEEqSJGm0+QzwV0B3j2X7ZuZqgOLrzL52dFB+SZKkHRkQSpIkadSIiDcBazNzye7s76D8kiRJO2qpugBJkiRpEF4BvDkiTgcmAHtGxFeBJyNi/8xcHRH7A2srrVKSJGkUsQWhJEmSRo3M/Ehmzs7MOcCZwI8z82xgEXBusdm5wHcrKlGSJGnUMSCUJEnSWHAx8PqIWAa8vngsSZKkAbCLsSRJkkalzPwJ8JPi/tPAKVXWI0mSNFrZglCSJEmSJElqYAaEkiRJkiRJUgMzIJQkSZIkSZIamAGhJEmSJEmS1MAMCCVJkiRJkqQGZkAoSZIkSZIkNbCWqguQJEmSpJ2ZMv8ijrrqoqrL2M6U+QBvrLoMSZKGhQGhJEmSpLq2cenFrLi4vsK4ORd9v+oSJEkaNnYxliRJkiRJkhqYAaEkSZIkSZLUwAwIJUmSJEmSpAZmQChJkiRJkiQ1MANCSZIkSZIkqYEZEEqSJEmSJEkNzIBQkiRJkiRJamAGhJIkSZIkSVIDMyCUJEmS9P+39/fhdtX1nfD//gRCglLlwehFgYhVZoyBaCV1LNBWUMCx3glzD4zQqdI2hTupjXWgnSj0cdqg3FOsY6bmDJgOaDtRik7Jzz4o8mANWGxAJcbUAYsChZ9GAVHaHIL53n+clXgSDuHBkLWz9+t1Xfs6e332Wut8di6uxT7v/f1+FwAwwgSEAAAAADDCBIQAAAAAMMIEhAAAAAAwwgSEAAAAADDCBIQAAAAAMMIEhAAAAAAwwgSEAAAAADDCBIQAAAAwZKpqn6r6fFV9vO9egMEnIAQAAIDh82tJNvbdBLB3EBACAADAEKmqw5P8bJIP9N0LsHcQEAIAAMBweW+S/5xk6+PtUFXnVtW6qlq3adOmPdYYMJgEhAAAADAkquqNSb7ZWrtlV/u11i5trc1vrc2fNWvWHuoOGFQCQgAAABgexydZUFVfS/LhJCdV1Z/22xIw6ASEAADsNapqZlV9rqq+WFUbqur3uvrBVXVNVd3e/Tyo714B+tBae2dr7fDW2pFJzkxyXWvt53tuCxhwAkIAAPYm40lOaq29PMkrkry+ql6d5B1Jrm2tHZXk2m4bAIAnQUAIAMBeo034Xrc5vXu0JAuTXNHVr0hy2p7vDmCwtNZuaK29se8+gMEnIAQAYK9SVftU1ReSfDPJNa21m5O8oLV2X5J0P5/fY4sAAHsVASEAAHuV1tr3W2uvSHJ4kldV1dFP9tiqOreq1lXVuk2bNj1jPQIA7E0EhAAA7JVaaw8muSHJ65N8o6oOTZLu5zcf55hLW2vzW2vzZ82atadaBQAYaAJCAAD2GlU1q6oO7J7vn+R1Sf4hyZokZ3e7nZ3k6l4aBADYC+3bdwMAAPAUHJrkiqraJxNfdl/ZWvt4VX02yZVVtSjJXUnO6LNJAIC9iYAQAIC9RmvttiQ/PkX920leu+c7AgDY+5liDAAAAAAjTEAIAAAAACNMQAgAAAAAI8wahAAAwMA78h1/2XcLO3ju/tP7bgEAdhsBIQAAMNC+9u6f3W3nOvIdf7lbzwcAw8AUYwAAAAAYYQJCAAAAABhhAkIAAAAAGGHWIAQAAAAYIlX15Pa7+In3aa39kN2wNxAQAgAAAAwRoR5PlSnGAAAAADDCBIQAAAAAMMIEhAAAAAAwwgSEAAAAADDCBIQAAAAAMMIEhAAAAAAwwgSEAAAAADDCBIQAAAAAMMIEhAAAAAAwwgSEAAAAADDCBIQAAAAAMMIEhAAAAAAwwgSEAAAAADDCBIQAAAAAMMIEhAAAADBEquqIqrq+qjZW1Yaq+rW+e2JwVNVjHrBv3w0AAAAAu9WjSc5vrd1aVT+S5Jaquqa19uW+G6NfjxcGVlVaa3u4GwaJEYQAAAAwRFpr97XWbu2efzfJxiSH9dsVg6S1tv0BiYAQAAAAhlZVHZnkx5PcvFP93KpaV1XrNm3a1EtvwOAQEAIAAMAQqqoDknw0ydtbaw9Nfq21dmlrbX5rbf6sWbP6aRAYGNYgBAAAgCFTVdMzEQ7+WWvtY333w2BxYxJ2ZgQhAAAADJGaSH9WJdnYWntP3/0wOB5vzUFrESIgBABgr1FVR1TV9VW1sao2VNWvdfWDq+qaqrq9+3lQ370C9Oj4JG9OclJVfaF7vKHvphgMk29Q4kYlbGOKMQAAe5NHk5zfWru1qn4kyS1VdU2SX0hybWvt3VX1jiTvSLKsxz4BetNaW5vEHFLgSTOCEACAvUZr7b7W2q3d8+8m2ZjksCQLk1zR7XZFktN6aRAAYC8kIAQAYK9UVUcm+fEkNyd5QWvtvmQiREzy/B5bAwDYqwgIAQDY61TVAZm4O+fbW2sPPYXjzq2qdVW1btOmTc9cgwAAexEBIQAAe5Wqmp6JcPDPWmsf68rfqKpDu9cPTfLNqY5trV3aWpvfWps/a9asPdMwAMCAExACALDXqKpKsirJxtbaeya9tCbJ2d3zs5Ncvad7AwDYW7mLMQAAe5Pjk7w5yfqq+kJXuyDJu5NcWVWLktyV5Ix+2gMA2PsICAEA2Gu01tYmqcd5+bV7shcAgGFhijEAAAAAjDABIQAAAACMMAEhAAAAAIwwASEAAAAAjDA3KQEAAAAYEVWPvddXa62HThgkRhACAAAAjIDJ4eDRG00ihAAARSZJREFURx89ZZ3RZAQhAAAAwAiZPGJQOEgiIAQAAIbAU/kDty5+4n1MtwOG1eSRg9u2v/SlL/XUDYNCQAgAAOz1BHoAT87OYaBwkMQahAAAAAAjpapyzDHHmF7MdgJCAAAAgBEwebT15JGDRmFjijEAAADAiBAGMhUjCAEAAABghAkIAQAAAGCECQgBAAAAYIQJCAEAAABghAkIAQAAAGCECQgBAAAAYIQJCAEAAABghAkIAQAAAGCECQgBAAAAYIRVa63vHgAAYI+rqk1Jvt53H+xxz0vyrb6bYI96YWttVt9NDDLXw5HlejiaprwmCggBAICRUVXrWmvz++4DoG+uh0xmijEAAAAAjDABIQAAAACMMAEhAAAwSi7tuwGAAeF6yHbWIAQAAACAEWYEIQAAAACMMAEhAAAAAIwwASEAAADAAKuqX6iq/76bz3laVb1s0vZ/qarX7c7fwd5DQAgAAAAwek5Lsj0gbK39dmvtU/21Q58EhAAAwNCoqr+oqluqakNVndvVFlXV/6mqG6rqsm2jcKpqVlV9tKr+vnsc32/3wKiqqp+vqs9V1Req6n9U1T5V9YvdtevTSY6ftO/lVXX6pO3vTXr+n6tqfVV9sare3dXO6a5xX+yuec+qquOSLEjyX7vf+eLJ562q11bV57tz/UlVzejqX6uq36uqW7vXXtrVf7fb74aq+seqetukns6rqi91j7c/s/+SPF0CQgAAYJj8Umvt2CTzk7ytqg5L8ltJXp3k5CQvnbTvf0vyR621n0jy75N8YE83C1BVc5K8KcnxrbVXJPl+kp9P8nuZCAZPzqSRfrs4z7/NxKjAf9Nae3mS/7d76WOttZ/oahuTLGqt3ZRkTZLfaK29orX21UnnmZnk8iRvaq0dk2TfJEsm/apvtdZemWRlkl+fVH9pklOTvCrJ71TV9Ko6NskvJvk3mbgOn1NVP/5k/23Yc/btuwEAAIDd6G1V9e+650ckeXOST7fW7k+SqvrzJP+qe/11SV5WVduOfU5V/Uhr7bt7smFg5L02ybFJ/r67Hu2f5LgkN7TWNiVJVX0kP7h2PZ7XJfmfrbV/TpJt170kR1fVHyQ5MMkBST7xBOf510nubK39n277iiRvTfLebvtj3c9bkvzfk477y9baeJLxqvpmkhckOSHJ/26tPdy9j48l+akkn3+CHtjDBIQAAMBQqKrXZOIP5J9srf1zVd2Q5CtJ5jzOIdO6ff9ljzQIMLVKckVr7Z3bC1WnJfl3j7P/o+lmhNZEorjfpPO0Kfa/PMlprbUvVtUvJHnNk+hnV8a7n9/PjrnS+KTn2157onMxIEwxBgAAhsVzkzzQhYMvzcR0tmcl+ZmqOqiq9s3EVOJtPpnkV7dtVNUr9mSzAJ1rk5xeVc9Pkqo6OBMj7F5TVYdU1fQkZ0za/2uZGHGYJAuTTO+efzLJL1XVsyadJ0l+JMl93Xn+46TzfLd7bWf/kOTIqnpJt/3mJJ9+mu/tb5Oc1q17+OxMhJ6feZrn4hkkIAQAAIbF3yTZt6puS/L7Sf4uyT8luSjJzUk+leTLSb7T7f+2JPOr6raq+nKSxXu+ZWDUtda+nOQ3k3yyu35dk+TQJL+b5LOZuHbdOumQyzLxxcfnMrG238Pdef4mE+sKrquqL+QH6wP+ViaugddkIvzb5sNJfqO7GcmLJ/WzORPrBv55Va1PsjXJ2NN8b7dmYgTj57oePtBaM714AFVrU40+BQAAGA5VdUBr7XvdCML/neRPWmv/u+++AGBQGEEIAAAMu9/tRtN8KcmdSf6i124AYMAYQQgAAAAAI8wIQgAAAAAYYQJCAAAAABhhAkIAAAAAGGECQgAAAAAYYQJCAAAAABhhAkIAAAAAGGECQgAAAAAYYQJCAAAAABhhAkIAAAAAGGECQgAAAAAYYQJCAAAAABhhAkIAAAAAGGECQgAAAAAYYQJCAAAAABhhAkIAAAAAGGECQgAAAAAYYQJCAAAAABhhAkIAAAAAGGECQgAAAAAYYQJCAAAAABhhAkIAAAAAGGECQgAAAAAYYQJCAAAAABhh+/bdwJ7wvOc9rx155JF9twE8w2655ZZvtdZm9d3HIHM9hNHhmvjEXBNhNLgeAjyxkQgIjzzyyKxbt67vNoBnWFV9ve8eBp3rIYwO18Qn5poIo8H1EOCJmWIMAAAAACNMQAgAAAAAI0xACAAAAAAjTEAIAAAAACNMQAgAAAAAI0xACAAAAAAjTEAIAMDAqao/qapvVtWXJtUOrqprqur27udBk157Z1XdUVVfqapT++kaAGDvJCAEAGAQXZ7k9TvV3pHk2tbaUUmu7bZTVS9LcmaSud0x76+qffZcqwAAezcBIQAAA6e19rdJ7t+pvDDJFd3zK5KcNqn+4dbaeGvtziR3JHnVnugTAGAYPK2AcHdN+aiqY6tqfffa+6qquvqMqvpIV7+5qo6cdMzZ3e+4varOflrvGgCAvdELWmv3JUn38/ld/bAkd0/a756uBgDAk/B0RxBent0z5WNlknOTHNU9tp1zUZIHWmsvSfJHSS7uznVwkt9J8m8y8a3w70wOIiFJquoxD4BRtHr16hx99NHZZ599cvTRR2f16tV9twTPlKn+Z9+m3LHq3KpaV1XrNm3a9Ay3xSDxGREAHt/TCgh3x5SPqjo0yXNaa59trbUkH9zpmG3nuirJa7vRhacmuaa1dn9r7YEk1+SxQSUj7PE+6PkACIya1atX58ILL8yKFSuyefPmrFixIhdeeKGQkL3dN7rPkOl+frOr35PkiEn7HZ7k3qlO0Fq7tLU2v7U2f9asWc9oswwOnxEBYNd25xqET3XKx2Hd853rOxzTWns0yXeSHLKLc8EOWmvbHwCjaPny5Vm1alVOPPHETJ8+PSeeeGJWrVqV5cuX990a/DDWJNm2xMzZSa6eVD+zW6bmRZmYmfK5HvpjwPmMCABT23cP/I7Hm/Kxq6kgT+eYHX9p1bmZmL6c2bNnP3GXADBENm7cmBNOOGGH2gknnJCNGzf21BE8NVW1Oslrkjyvqu7JxDIz705yZVUtSnJXkjOSpLW2oaquTPLlJI8meWtr7fu9NM5AM2IQAKa2O0cQPtUpH/d0z3eu73BMVe2b5LmZmNJs+ggAPAlz5szJ2rVrd6itXbs2c+bM6akjeGpaa2e11g5trU1vrR3eWlvVWvt2a+21rbWjup/3T9p/eWvtxa21f91a++s+e2dwTZs2LZ/61Kcybdru/DMIAPZ+u/P/jE9pykc3Dfm7VfXqbn3Bt+x0zLZznZ7kum6dwk8kOaWqDupuTnJKV4MdWHwaGHUXXnhhFi1alOuvvz5btmzJ9ddfn0WLFuXCCy/suzWA3mzdujWve93rsnXr1r5bAYCB8rSmGO/GKR9LMnFH5P2T/HX3SJJVST5UVXdkYuTgmd257q+q30/y991+/2XyN8fQWpsyFLTODDBqzjrrrCTJ0qVLs3HjxsyZMyfLly/fXgcAANimRiE4mT9/flu3bl3fbQDPsKq6pbU2v+8+BpnrIYwO18Qn5po4OrZ9gXzJJZdk8eLFGRsby/nnn5/EF8mjwPUQ4IntiZuUAAAA9O43fuM38vKXvzy/8Ru/0XcrADBQBIQAAMBI2LYGIQCwI7fvAgAARsJBBx2U2267LQcddFDfrQDAQBEQAgAAI+E3f/M38+IXvzi/+Zu/2XcrADBQBIQAAMDQe8lLXpLzzz8/z372s3P++efnJS95Sd8tAcDAEBACAABD74477sgll1yShx9+OJdccknuuOOOvlsCgIEhIAQAAEbCH/zBH+SrX/1q/uAP/qDvVgBgoLiLMQAAMPSmTZuWBx54IPPmzdu+vXXr1p67AoDBYAQhAAAw1Pbdd98897nPzXXXXZdHHnkk1113XZ773Odm332NlwCAREAIAAAMuec85zl56KGH8vnPfz5btmzJ5z//+Tz00EN5znOe03drADAQBIQAAMBQe/DBB3PuuefmggsuyLOf/exccMEFOffcc/Pggw/23RoADAQBIQAAMNTmzJmTM844I5s3b05rLZs3b84ZZ5yROXPm9N0aAAwEi24AAABD7cILL8wb3vCGbN68eXtt5syZ+ZM/+ZMeuwKAwWEEIQAAMNQuv/zybN68OQcddFCS5KCDDsrmzZtz+eWX99sYAAwIASEAADDUrrnmmixZsiT3339/Wmu5//77s2TJklxzzTV9twYAA0FACNCDqtqnqj5fVR/vtg+uqmuq6vbu50GT9n1nVd1RVV+pqlMn1Y+tqvXda++rqurjvQDAoGutZePGjZk2bVqqKtOmTcvGjRvTWuu7NQAYCAJCgH78WpKNk7bfkeTa1tpRSa7ttlNVL0tyZpK5SV6f5P1VtU93zMok5yY5qnu8fs+0DgB7nxtuuCGLFy/Ogw8+mMWLF+eGG27ouyUAGBgCQoA9rKoOT/KzST4wqbwwyRXd8yuSnDap/uHW2nhr7c4kdyR5VVUdmuQ5rbXPtonhDx+cdAwAAAA8ae5iDLDnvTfJf07yI5NqL2it3ZckrbX7qur5Xf2wJH83ab97utqW7vnO9ceoqnMzMdIws2fP3g3tA8DeaeXKlVm5cmXfbQDAwDGCEGAPqqo3Jvlma+2WJ3vIFLW2i/pji61d2lqb31qbP2vWrCf5awFgOC1atKjvFgBg4BhBCLBnHZ9kQVW9IcnMJM+pqj9N8o2qOrQbPXhokm92+9+T5IhJxx+e5N6ufvgUdQDgcSxZsiTvete7st9++xlJCACTGEEIsAe11t7ZWju8tXZkJm4+cl1r7eeTrElydrfb2Umu7p6vSXJmVc2oqhdl4mYkn+umI3+3ql7d3b34LZOOAQCmsHLlyhx44IHCQQDYiYAQYDC8O8nJVXV7kpO77bTWNiS5MsmXk/xNkre21r7fHbMkEzc6uSPJV5P89Z5umsG2dOnSzJw5M1WVmTNnZunSpX23BNCrJUuW5MEHH8ySJUv6bgUABoopxgA9aa3dkOSG7vm3k7z2cfZbnmT5FPV1SY5+5jpkb7Z06dKMjY3l4osvzuLFizM2NpZly5YlSVasWNFzdwD9WLlyZR555JGsWrWq71YAYKAYQQgAQ+iyyy7LxRdfnPPOOy/Petazct555+Xiiy/OZZdd1ndrAL0SDgLAYwkIAWAIjY+PZ/HixTvUFi9enPHx8Z46AujfggULsmnTpixYsKDvVgBgoAgIAWAIzZgxI2NjYzvUxsbGMmPGjJ46AujfYYcdlunTp+ewww7ruxUAGCjWIASAIXTOOedsX3Nw8hqEO48qBBgVL33pS7Ny5crtdzB+6Utfmn/4h3/ouSsAGAwCQgAYQttuRHLBBRfk/PPPz4wZM7J48WI3KAFG1te+9rVcd911OeGEE7J27dq84Q1v6LslABgYphgDwJBasWJFNm/enNZaNm/eLBwERtaMGTOyefPmvPe97813vvOdvPe9783mzZstuwAAHSMIAQCAobZly5bMmDEja9asyaxZs5JMhIZbtmzpuTMAGAxGEALAkJo3b16qavtj3rx5fbcE0Ivp06dnfHx8h7sYj4+PZ/r06X23BgADQUAIAENo3rx5Wb9+/Q5/DK9fv15ICIyk8fHxzJw5M29/+9vz3Oc+N29/+9szc+bMjI+P990aAAwEU4wBYAhtCwevvvrqJMnVV1+dhQsXZs2aNT13BtCPzZs356STTuq7DQAYSEYQAsCQWrVq1S63AUbRX/zFX/TdAgAMHAEhAAypRYsW7XIbYNQsWLAgxx9/fBYsWNB3KwAwUASEADCEjjnmmKxZsyYLFy7Mt771re3Ti4855pi+WwPozba7GFtuAQB2ZA1CABhCt912Ww455JDtfwwnycEHH5zbbrut584A+nXsscfmlltu6bsNABgoRhACwBBaunRpHnrooVxyySV5+OGHc8kll+Shhx7K0qVL+24NoFe/9Vu/1XcLADBwBIQAMIQuu+yyXHzxxTnvvPPyrGc9K+edd14uvvjiXHbZZX23BtCr0047re8WAGDgCAgBYAiNj49n8eLFO9QWL16c8fHxnjoC6F9rbfsDAPgBASEADKEZM2ZkbGxsh9rY2FhmzJjRU0cA/auqzJ8/P1XVdysAMFDcpAQAhtA555yTZcuWJZkYOTg2NpZly5Y9ZlQhwChorW0PBSffoMRIQgCYYAQhAAyhFStWZPHixbngggvy7Gc/OxdccEEWL16cFStW9N0awB63evXqvOhFL8p1112XRx55JNddd11e9KIXZfXq1X23BgADQUAIAENqxYoV2bx5c1pr2bx5s3AQGFnLly/PqlWrcuKJJ2b69Ok58cQTs2rVqixfvrzv1gBgIAgIAQCAobZx48ZcdNFFmTZtWqoq06ZNy0UXXZSNGzf23RoADAQBIQAAMNT233//fOpTn8rixYvz4IMPZvHixfnUpz6V/fffv+/WAGAgCAgBAICh9vDDD+eAAw7IGWeckWc961k544wzcsABB+Thhx/uuzUAGAjuYgwAwF6lqv5Tkl9O0pKsT/KLSZ6V5CNJjkzytST/obX2QE8tMoC+973v5aSTTuq7DQAYSEYQAgCw16iqw5K8Lcn81trRSfZJcmaSdyS5trV2VJJru20AAJ6E3R4QVtV/qqoNVfWlqlpdVTOr6uCquqaqbu9+HjRp/3dW1R1V9ZWqOnVS/diqWt+99r6qqq4+o6o+0tVvrqojd/d7AABgoO2bZP+q2jcTIwfvTbIwyRXd61ckOa2f1hhkS5YsyYMPPpglS5b03QoADJTdGhA+1W90q+pl3etzk7w+yfurap/udCuTnJvkqO7x+q6+KMkDrbWXJPmjJBfvzvcAAMDgaq39U5I/THJXkvuSfKe19skkL2it3dftc1+S5091fFWdW1Xrqmrdpk2b9lTbDIiVK1fmwAMPzMqVK/tuBQAGyjMxxfipfKO7MMmHW2vjrbU7k9yR5FVVdWiS57TWPttaa0k+uNMx2851VZLXbhtdCADAcOtmoixM8qIkP5rk2VX180/2+Nbapa21+a21+bNmzXqm2mRAXXfddXnkkUdy3XXX9d0KAAyU3XqTktbaP1XVtm90/yXJJ1trn6yqHb7Rrapt3+geluTvJp3inq62pXu+c33bMXd353q0qr6T5JAk35rcS1Wdm4kRiJk9e/bue5MAAPTpdUnubK1tSpKq+liS45J8o6oO7T5rHprkm302yWBykxIAmNrunmL8VL/RnWrkX9tFfVfH7Fjw7TAAwDC6K8mrq+pZ3SyS1ybZmGRNkrO7fc5OcnVP/TGApk2b+s+ex6sDwKjZ3f9H3P6NbmttS5IdvtFNkp2+0b0nyRGTjj88E1OS7+me71zf4ZhuGvNzk9y/m98HAAADqLV2cyaWmbk1yfpMfJ69NMm7k5xcVbcnObnbhiTJ1q1bkyT77LNPbrjhhuyzzz471AFg1O3ugPCpfqO7JsmZ3Z2JX5SJm5F8rpuO/N2qenV3nrfsdMy2c52e5LpunUIAAEZAa+13Wmsvba0d3Vp7c7ee9bdba69trR3V/fQFMo9xzTXX5Ljjjss111zTdysAMFB29xqEN1fVtm90H03y+Ux8o3tAkiuralEmQsQzuv03VNWVSb7c7f/W1tr3u9MtSXJ5kv2T/HX3SJJVST5UVXdkYuTgmbvzPQAAAMPJGoQAMLXdGhAmE9/oJvmdncrjmRhNONX+y5Msn6K+LsnRU9Q3pwsYAQAAnqyDDjoon/70p/MzP/MzeeCBB/puBwAGhlV5AQCAkfDQQw/l/vvvz0MPPdR3KwAwUHb7CEIAAIBB9P3vfz+vec1r+m4DAAaOEYQAAMBIWLBgQTZt2pQFCxb03QoADBQBIQAAMBI+85nP5L777stnPvOZvlsBgIFiijEAADASHnjggcybN6/vNgBg4BhBCAAAjIwDDzyw7xYAYOAICAEAgJGwYMGC3H777dYgBICdmGIMAACMhDVr1mTWrFl9twEAA8cIQgAAYCQsWbIkDz74YJYsWdJ3KwAwUIwgBAAARsLKlSuzevXqPPjgg323AgADxQhCAABgZAgHAeCxBIQAAMBIMMUYAKYmIASAIbV06dLMnDkzVZWZM2dm6dKlfbcEAAAMIAEhAAyhpUuXZmxsLBdddFEefvjhXHTRRRkbGxMSAiNt5cqVOfDAA7Ny5cq+WwGAgSIgBIAhdNlll+Xiiy/Oeeedl2c961k577zzcvHFF+eyyy7ruzWAXh1yyCF9twAAA0dACABDaHx8PIsXL96htnjx4oyPj/fUEUD/lixZkq9+9avWIASAnQgIAWAIzZgxI2NjYzvUxsbGMmPGjJ46Aujf2NhYDjzwwMdcHwFg1O3bdwMAwO53zjnnZNmyZUkmRg6OjY1l2bJljxlVCDBKtm7duv15VfXYCQAMFgEhAAyhFStWJEkuuOCCnH/++ZkxY0YWL168vQ4wiqoqhxxySL797W/33QoADBQBIQAMqRUrVggEAZK01raPGJwcDrbW+moJAAaKNQgBAICh9njTiU0zBoAJRhACAAAjYfKIQeEgAPyAEYQAAMBIOProo7PPPvvk6KOP7rsVABgoAkKAPayqZlbV56rqi1W1oap+r6sfXFXXVNXt3c+DJh3zzqq6o6q+UlWnTqofW1Xru9feV4ZDMMm8efNSVdsf8+bN67slgF6tWLEimzdvtj4rAOxEQAiw540nOam19vIkr0jy+qp6dZJ3JLm2tXZUkmu77VTVy5KcmWRuktcneX9V7dOda2WSc5Mc1T1evwffBwNs3rx5Wb9+fRYsWJBNmzZlwYIFWb9+vZAQGGknnXRS9ttvv5x00kl9twIAA0VACLCHtQnf6zand4+WZGGSK7r6FUlO654vTPLh1tp4a+3OJHckeVVVHZrkOa21z7aJRZU+OOkYRty2cPDqq6/O8573vFx99dXbQ0KAUTNt2tR/9jxeHQBGjf8jAvSgqvapqi8k+WaSa1prNyd5QWvtviTpfj6/2/2wJHdPOvyernZY93zn+s6/69yqWldV6zZt2rTb3wuDa9WqVbvcBhgVW7du3f784x//+JR1ABhlAkKAHrTWvt9ae0WSwzMxGnBXq6VPta5g20V95991aWttfmtt/qxZs55Wv+ydFi1atMttgFFz3XXX5ZRTTsl1113XdysAMFAEhAA9aq09mOSGTKwd+I1u2nC6n9/sdrsnyRGTDjs8yb1d/fAp6pBjjjkma9asycKFC/Otb30rCxcuzJo1a3LMMcf03RpAL2bMmLHDGoQzZszouyUAGBgCQoA9rKpmVdWB3fP9k7wuyT8kWZPk7G63s5Nc3T1fk+TMqppRVS/KxM1IPtdNQ/5uVb26u3vxWyYdw4i77bbbtoeEs2bN2h4O3nbbbX23BtCL8fHxzJ07N1//+tczd+7cjI+P990SAAyMfftuAGAEHZrkiu5OxNOSXNla+3hVfTbJlVW1KMldSc5Iktbahqq6MsmXkzya5K2tte9351qS5PIk+yf56+4BSSIMBNjJhg0bsn79+mzYsKHvVgBgoAgIAfaw1tptSX58ivq3k7z2cY5ZnmT5FPV1SXa1fiEAMMkb3/jGvlsAgIFjijEAADAyPvCBD/TdAgAMHAEhAAAwEubOnZuTTz45c+fO7bsVABgophgDAAAjYcOGDXnhC1/YdxsAMHAEhAAwpCZubr2j1loPnQAAAIPMFGMAGELbwsHp06dn7dq1mT59+g51gFFlDUIAeCwjCAFgSE2fPj2PPPJIkuSRRx7Jfvvtly1btvTcFUC/fvmXf7nvFgBg4BhBCABD6vrrr9/lNsAouvzyy/tuAQAGjoAQAIbUiSeeuMttgFH0C7/wC323AAADxxRjABhSW7ZsseYgAADwhIwgBIAh9Ku/+qtPqQ4wCqZNm5ZPfepTmTbNn0EAMJn/MwLAELrssstyySWXpLW2/XHJJZfksssu67s1gN5s3bo199xzT7Zu3dp3KwAwUASEADCExsfHs3jx4h1qixcvzvj4eE8dAQwGaxACwGMJCAFgCM2YMSNjY2M71MbGxjJjxoyeOgIYDDtfGwEANykBgKF0zjnnZNmyZUkmRg6OjY1l2bJljxlVCDBKpk2blpe85CWZNm2aacYAMImAEACG0IoVK5IkF1xwQc4///zMmDEjixcv3l4HGEVbt27N6173ur7bAICBY4oxAAypFStWZPPmzWmtZfPmzcJBYOQtWLAgmzZtyoIFC/puBQAGioAQAIC9SlUdWFVXVdU/VNXGqvrJqjq4qq6pqtu7nwf13SeDZ82aNfnoRz+aNWvW9N0KAAyU3R4QPtUPbFX1zqq6o6q+UlWnTqofW1Xru9feV1XV1WdU1Ue6+s1VdeTufg8AAAy0/5bkb1prL03y8iQbk7wjybWttaOSXNttw2NYixUAHuuZGEH4pD+wVdXLkpyZZG6S1yd5f1Xt051nZZJzkxzVPV7f1RcleaC19pIkf5Tk4mfgPQDAXm/27Nmpqu2P2bNn990S/NCq6jlJfjrJqiRprT3SWnswycIkV3S7XZHktD76AwDYG+3WgPBpfGBbmOTDrbXx1tqdSe5I8qqqOjTJc1prn22ttSQf3OmYbee6Kslrt40uBAAmzJ49O3fffXeOO+643HvvvTnuuONy9913CwkZBj+WZFOS/1lVn6+qD1TVs5O8oLV2X5J0P5/fZ5MMJmsQAsDUdvcIwqf6ge2wJHdPOv6ernZY93zn+g7HtNYeTfKdJIfs3EhVnVtV66pq3aZNm3bX+wOAvcK2cPDGG2/MoYcemhtvvHF7SAh7uX2TvDLJytbajyd5OE9hOrHPiKNtzZo1mTVrljUIAWAnuzsgfKof2KYa+dd2Ud/VMTsWWru0tTa/tTZ/1qxZu+4aAIbQTTfdtMMU45tuuqnvlmB3uCfJPa21m7vtqzLx+fMb3SyUdD+/OdXBPiOOtrlz5+brX/965s6d23crADBQdndA+FQ/sN2T5IhJxx+e5N6ufvgU9R2Oqap9kzw3yf27+X0AADCAWmv//yR3V9W/7kqvTfLlJGuSnN3Vzk5ydQ/tMeA2bNiQF77whdmwYUPfrQDAQNmtAeHT+MC2JsmZ3Z2JX5SJm5F8rpuG/N2qenW3vuBbdjpm27lOT3Jdt04hALCTAw44ILfccksOOOCAvluB3Wlpkj+rqtuSvCLJRUneneTkqro9ycndNgAAT8K+z8A5t31g2y/JPyb5xUwEkVdW1aIkdyU5I0laaxuq6spMhIiPJnlra+373XmWJLk8yf5J/rp7JBM3QPlQVd2RiZGDZz4D7wEAhsL3vve9HHvssX23AbtVa+0LSeZP8dJr93Ar7IXe9ra35X3ve1/fbQDAQNntAeFT/cDWWlueZPkU9XVJjp6ivjldwAgA7NrkQfYTg/IBRtfcuXNz/vnn59prrzXNGAAm2d1rEAIAA6SqcvXVVwsHAWINQgB4PAJCABhCRxzxg3uAnXbaaVPWAUbRhz/84b5bAICBIyAEgCH08MMPP6U6wKi46aab+m4BAAaOgBAAhtD999//lOoAo8INSgDgsQSEADDk/vRP/7TvFgAAgAEmIASAIffzP//zfbcAMDCsQQgAjyUgBAAARsaZZ57ZdwsAMHAEhAAAAAAwwgSEAAAAADDCBIQAAAAAMMIEhAAAwMg48cQT+24BAAaOgBAAABgZ119/fd8tAMDAERACAAAAwAgTEAIAACNj2bJlfbcAAANHQAgAAIyMz33uc323AAADR0AIAACMDGsQAsBj7dt3AwAAAHtCa23786rqsRMAGCwCQgAAYK/3ZAK/qfZ5vOMmh4kAMOxMMQaAIXbQQQfltttuy0EHHdR3KwDPqNbaLh9P9RgAGCUCQgAYYg888EDmzZuXBx54oO9WAHq1Lfh74bKPCwEBYCcCQgAAAAAYYQJCAAAAABhhAkIAAAAAGGECQgAAAAAYYQJCAAAAABhhAkIAAAAAGGECQgAAAAAYYQJCAAAAABhhAkIAAAAAGGECQgAYQvvuu+9TqgMAAKNLQAgAQ+jRRx99SnUAAGB0CQgBYIhNnz49a9euzfTp0/tuBQAAGFACQoA9rKqOqKrrq2pjVW2oql/r6gdX1TVVdXv386BJx7yzqu6oqq9U1amT6sdW1frutfdVVfXxnhhcW7ZsyQknnJAtW7b03QoAADCgBIQAe96jSc5vrc1J8uokb62qlyV5R5JrW2tHJbm220732plJ5iZ5fZL3V9U+3blWJjk3yVHd4/V78o0AAACw9xMQAuxhrbX7Wmu3ds+/m2RjksOSLExyRbfbFUlO654vTPLh1tp4a+3OJHckeVVVHZrkOa21z7bWWpIPTjoGAAAAnhQBIUCPqurIJD+e5OYkL2it3ZdMhIhJnt/tdliSuycddk9XO6x7vnN9599xblWtq6p1mzZt2u3vAQAAgL2bgBCgJ1V1QJKPJnl7a+2hXe06Ra3tor5jobVLW2vzW2vzZ82a9fSaBQAAYGgJCAF6UFXTMxEO/llr7WNd+RvdtOF0P7/Z1e9JcsSkww9Pcm9XP3yKOuzgla98Zd8tAAAAA2zfvhsAGDXdnYZXJdnYWnvPpJfWJDk7ybu7n1dPqv+vqnpPkh/NxM1IPtda+35VfbeqXp2JKcpvSbJiD70N9iK33npr3y0A/FBe/nufzHf+Zffdjf3Id/zlD32O5+4/PV/8nVN2QzcA0D8BIcCed3ySNydZX1Vf6GoXZCIYvLKqFiW5K8kZSdJa21BVVyb5cibugPzW1tr3u+OWJLk8yf5J/rp7AMBQ+c6/bMnX3v2zfbexg90RMgLAoBAQAuxhrbW1mXr9wCR57eMcszzJ8inq65Icvfu6AwAAYNRYgxAAAAAARpiAEAAAAABGmIAQAAAAAEaYgBAAAAAARpiAEAAAAABGmICQoXPqqadm2rRpqapMmzYtp556at8tAQAAAAwsASFD5dRTT80nP/nJLF68OA8++GAWL16cT37yk0JCAAAAgMexb98NwO50zTXXZMmSJXn/+9+fJNt/jo2N9dkWAAAAwMB6RkYQVtU+VfX5qvp4t31wVV1TVbd3Pw+atO87q+qOqvpKVZ06qX5sVa3vXntfVVVXn1FVH+nqN1fVkc/Ee2Dv1FrLu971rh1q73rXu9Ja66kjAAAAgMH2TE0x/rUkGydtvyPJta21o5Jc222nql6W5Mwkc5O8Psn7q2qf7piVSc5NclT3eH1XX5TkgdbaS5L8UZKLn6H3wF6oqvLOd75zh9o73/nOdPkyADAknsoX0gAA7NpuDwir6vAkP5vkA5PKC5Nc0T2/Islpk+ofbq2Nt9buTHJHkldV1aFJntNa+2ybGPr1wZ2O2Xauq5K8tqQ/dE4++eSsXLkyv/Irv5LvfOc7+ZVf+ZWsXLkyJ598ct+tAQC715P6QhoAgCf2TIwgfG+S/5xk66TaC1pr9yVJ9/P5Xf2wJHdP2u+ernZY93zn+g7HtNYeTfKdJIfs1nfAXusTn/hETjnllIyNjeXAAw/M2NhYTjnllHziE5/ouzWA3vzET/xE3y3AbvUUv5AGAOAJ7NablFTVG5N8s7V2S1W95skcMkWt7aK+q2N27uXcTExRzuzZs59EKwwLYSDAjpYtW5bTTz+97zZgd3pvJr6Q/pFJtR2+kK6q5091oM+Ie6cfmfOOHHPFYA0K/ZE5yURODQB7v919F+PjkyyoqjckmZnkOVX1p0m+UVWHdh/WDk3yzW7/e5IcMen4w5Pc29UPn6I++Zh7qmrfJM9Ncv/OjbTWLk1yaZLMnz/fHSoAGFnCQYbJ0/hCegc+I+6d1p+9fred68h3/GW+9m7BHgBMtlunGLfW3tlaO7y1dmQmbj5yXWvt55OsSXJ2t9vZSa7unq9JcmZ3Z+IXZeJmJJ/rvv39blW9ultf8C07HbPtXKd3v8OHOwCA0bDtC+mvJflwkpMmfyGdJDt9IQ0AwBN4pu5ivLN3Jzm5qm5PcnK3ndbahiRXJvlykr9J8tbW2ve7Y5ZkYl2ZO5J8Nclfd/VVSQ6pqjuSnBcLUAMAjIyn8YU0AABPYHdPMd6utXZDkhu6599O8trH2W95kuVT1NclOXqK+uYkZ+zGVgEA2Pu9O8mVVbUoyV3xeREA4El7xgJCAAB4Jj3ZL6QBANi1PTXFGAAAAAAYQAJCAAAAABhhAkIAAAAAGGECQgAAAAAYYQJCAAAAABhhAkIAAAAAGGECQgAAAAAYYQJCAAAAABhhAkKGzrx581JV2x/z5s3ruyUAAACAgSUgZKjMmzcv69evz4IFC7Jp06YsWLAg69evFxICAAAAPA4BIUNlWzh49dVX53nPe16uvvrq7SEhwCiaO3dupk2blrlz5/bdCgAAMKAEhAydVatW7XIbYJT80i/9Ur773e/ml37pl/puBQAAGFACQobOokWLdrkNMErOP//8PPvZz87555/fdysAAMCAEhAyVI455pisWbMmCxcuzLe+9a0sXLgwa9asyTHHHNN3awAAAAADad++G4Dd6bbbbsu8efOyZs2azJo1K8lEaHjbbbf13BkAAADAYBIQMnSEgQAAo6eqnvy+Fz/xPq21H6IbANi7mGIMAEPsgAMOyC233JIDDjig71YAnlGttcd9PJ3jAGCUCAgBYIiddNJJmT17dk466aS+WwHonQAQAKZmijEADLHJa7ICjLqnMg0ZAEaJEYQAAMBImD59etauXZvp06f33QoADBQBIQAMMWsQAvzAli1bcsIJJ2TLli19twIAA8UUYwAYYt/73vdy7LHH9t0GAAAwwIwgBIAhNXPmzB0W5J85c2bfLQEAAANIQAgAQ6iqsnnz5lTV9se2bYBRZQ1CAJiagBAAhtDhhx/+lOoAo8AahAAwNQEhAAyhu+++O8cdd9wOU4yPO+643H333X23BtAbIwgBYGoCQobO5Ol02x4Ao+iqq67a5TbAqDGCEACmJiBkqEwOA08++eQp6wCj4vTTT9/lNgAAQCIgZEi11vLJT34yrbW+WwHoxRFHHJGbbropxx9/fO67774cf/zxuemmm3LEEUf03RoAADBgBIQMnckjB6faBhgFd9111/aQ8Ed/9Ee3h4N33XVX360B9MYahAAwtX37bgB2t2uuuWaX2wCjQhgIsKNtaxACADsygpChVFU55ZRTrD0IjLR58+btcMOmefPm9d0SQO8WL17cdwsAMHAEhAyVyWsOTh45aC1CYNTMmzcv69evz4IFC7Jp06YsWLAg69evFxICI29sbKzvFgBg4AgIGTqttcc8AEbNtnDw6quvzvOe97xcffXV20NCAACAyQSEDJ3J0+m2PQBG0Zo1a3a4Fq5Zs6bvlgB697a3va3vFgBg4AgIGSqTw8CrrrpqyjrAKJk5c2b+7u/+LjNnzuy7FYCB8Mgjj/TdAgAMHHcxZihtm1bcWhMOAiPtlFNOyYtf/OKccsopRhACxBqEADAVIwgZOpNHDk61DTAqfuzHfixr1qzJrFmzsmbNmvzYj/1Y3y0BAAADSEDI0Dn99NN3uQ0wKu69994dbth077339t0SQO+sQQgAjyUgZChVVT760Y+aXgyMrKrK5s2bs//+++fmm2/O/vvvn82bN7suAiPvfe97X98tAMDAERAyVLatPZjsOHJwch36VlV/UlXfrKovTaodXFXXVNXt3c+DJr32zqq6o6q+UlWnTqofW1Xru9feV5IfJtm6dev2kPDVr3719nBw69atfbcGAAAMGAEhQ2fydLptDxgwlyd5/U61dyS5trV2VJJru+1U1cuSnJlkbnfM+6tqn+6YlUnOTXJU99j5nIy4rVu37nAtFA4CAABTERAC7GGttb9Ncv9O5YVJruieX5HktEn1D7fWxltrdya5I8mrqurQJM9prX22TaTgH5x0DCRJli5dmpkzZ6aqMnPmzCxdurTvlgAAgAEkIGTorF69OkcffXT22WefHH300Vm9enXfLcGT8YLW2n1J0v18flc/LMndk/a7p6sd1j3fuf4YVXVuVa2rqnWbNm3a7Y0zmJYuXZqxsbFcdNFFefjhh3PRRRdlbGxMSAiMvGXLlvXdAgAMnH37bgB2p9WrV+fCCy/MqlWrcsIJJ2Tt2rVZtGhRkuSss87quTt4WqZaV7Dtov7YYmuXJrk0SebPn2/O/Yi47LLLcvHFF+e8885Lku0/L7jggqxYsaLP1gB6dfHFF/fdAgAMHCMIGSrLly/PqlWrcuKJJ2b69Ok58cQTs2rVqixfvrzv1uCJfKObNpzu5ze7+j1Jjpi03+FJ7u3qh09RhyTJ+Ph4Fi9evENt8eLFGR8f76kjAABgUAkIGSobN27MCSecsEPthBNOyMaNG3vqCJ60NUnO7p6fneTqSfUzq2pGVb0oEzcj+Vw3Dfm7VfXq7u7Fb5l0DGTGjBkZGxvboTY2NpYZM2b01BHAYDj55JP7bgEABo6AkKEyZ86crF27dofa2rVrM2fOnJ46gseqqtVJPpvkX1fVPVW1KMm7k5xcVbcnObnbTmttQ5Irk3w5yd8keWtr7fvdqZYk+UAmblzy1SR/vUffCAPtnHPOybJly/Ke97wn//zP/5z3vOc9WbZsWc4555y+WwPo1Stf+cq+WwCAgVMTN78cbvPnz2/r1q3ruw32gMdbg3D58uXWIBwBVXVLa21+330MMtfD0TJz5swdphTPmDEjmzdv7rEj9iTXxCfmmjg6JgbbT20U/h4ada6HAE9st44grKojqur6qtpYVRuq6te6+sFVdU1V3d79PGjSMe+sqjuq6itVdeqk+rFVtb577X3dFLp00+w+0tVvrqojd+d7YO921lln5c4778xJJ52U/fbbLyeddFLuvPNO4SAwcg455JCMj49n7ty5+frXv565c+dmfHw8hxxySN+tAfRq2w3sAIAf2N1TjB9Ncn5rbU6SVyd5a1W9LMk7klzbWjsqybXddrrXzkwyN8nrk7y/qvbpzrUyybmZWG/rqO71JFmU5IHW2kuS/FEStyFju8nfDr/5zW+esg4wCu6///7MnTs3X/rSlzJ79ux86Utfyty5c3P//ff33Rr8UJ7OF9Iw2V133dV3CwAwcHZrQNhau6+1dmv3/LtJNiY5LMnCJFd0u12R5LTu+cIkH26tjbfW7szEOlqv6u7g+ZzW2mfbxJj/D+50zLZzXZXktSX9YSettXzwgx80ZQQYaX/1V3+1y23YSz2lL6RhZ9dcc03fLQDAwHnGblLSTf398SQ3J3lBd8fNdD+f3+12WJK7Jx12T1c7rHu+c32HY1prjyb5TpLHzJeqqnOral1Vrdu0adNuelfsDSaPHJxqG2BUvOENb9jlNuyNnsYX0gAAPIFnJCCsqgOSfDTJ21trD+1q1ylqbRf1XR2zY6G1S1tr81tr82fNmvVELTNEPvShD2XmzJmpqsycOTMf+tCH+m4JYI87+OCDs2HDhlTV9seGDRty8MEH990a7DZP8gtp2IE1CAHgsXZ7QFhV0zMRDv5Za+1jXfkb3bThdD+/2dXvSXLEpMMPT3JvVz98ivoOx1TVvkmem8SCSuxgfHw8Z5111g537wQYJT/3cz/3lOqwt3kKX0jvfJxZJiNu1apVfbcAAANnd9/FuJKsSrKxtfaeSS+tSXJ29/zsJFdPqp/Z3Zn4RZm4Gcnnum99v1tVr+7O+Zadjtl2rtOTXNcsNEdnxowZ25+vXr16yjrAKLjssstyySWXpLW2/XHJJZfksssu67s1+KE9xS+kd2CWCR/+8If7bgEABs7uHkF4fJI3Jzmpqr7QPd6Q5N1JTq6q25Oc3G2ntbYhyZVJvpzkb5K8tbX2/e5cS5J8IBM3Lvlqkr/u6quSHFJVdyQ5LxagZpLx8fE8/PDDO/xB/PDDDxtJCIyc8fHxLF68eIfa4sWLXQ/Z6z2NL6RhB2eeeWbfLQDAwNl3d56stbY2U68RmCSvfZxjlidZPkV9XZKjp6hvTnLGD9EmQ2zGjBkZGxvLeeedt702NjZmBCEwclwPGWLbvpBeX1Vf6GoXZOIL6CuralGSu+LzIgDAk7ZbA0Lo2znnnJNly5YlmRgpMzY2lmXLlj1mFA3AsHM9ZFg9nS+kYbJ99903jz76aN9tAMBAERAyVFasWJEkueCCC3L++ednxowZWbx48fY6wKhwPQSY2p/+6Z+aZgwAO6lRuL/H/Pnz27p16/puA3iGVdUtrbX5ffcxyFwPYXS4Jj4x18TRMbF05dRG4e+hUed6CPDEdvdNSqB3M2fOTFVtf8ycObPvlgAAGBDnnHNO3y0AwMAREDJUZs6cmfHx8bzgBS/Ixo0b84IXvCDj4+NCQgAAkiT/83/+z75bAICBYw1Chsr4+HiS5Bvf+EbmzJnzmDoAAKPNDUoA4LGMIASAITVv3rwdllyYN29e3y0BAAADSEAIAENo3rx5Wb9+/Q619evXCwmBkWcNQgB4LAEhAAyhyeHgX/zFX0xZBxhFl112Wd8tAMDAsQYhAAyx1tr2n1XVczcAAMAgMoIQAIbUK1/5yl1uAwAAJAJCABhat956axYuXJhvfetbWbhwYW699da+WwIAAAaQgJChtWzZsr5bAOjdmjVrMmvWrKxZs6bvVgAGwqJFi/puAQAGjoCQoXXxxRf33QJAb7atPfhk6wCjYtWqVX23AAADx01KAGBICQMBAIAnwwhCAABgZHzgAx/ouwUAGDgCQobKMccc85TqAACMll/+5V/uuwUAGDgCQobK+vXrs2DBgrTWtj8WLFiQ9evX990aAAAAwECyBiFDZ82aNamqvtsAAGDATF6b1edFAPgBASEAADAShIIAMDVTjBlar3jFK/puAQAAAGDgCQgZWl/4whf6bgGgV6tXr87RRx+dffbZJ0cffXRWr17dd0sAAMAAMsUYAIbQ6tWrc+GFF2bVqlU54YQTsnbt2ixatChJctZZZ/XcHQAAMEiMIGRovelNb+q7BYDeLF++PKtWrcqJJ56Y6dOn58QTT8yqVauyfPnyvlsDAAAGjICQofWRj3yk7xYAerNx48accMIJO9ROOOGEbNy4saeOAAbDxz/+8b5bAICBIyAEgCE0Z86crF27dofa2rVrM2fOnJ46AhgMb3zjG/tuAQAGjoAQAIbQhRdemEWLFuX666/Pli1bcv3112fRokW58MIL+24NoFd//Md/3HcLADBw3KQEAIbQthuRLF26NBs3bsycOXOyfPlyNygBRt5b3/rWvlsAgIFjBCEADKlly5Zlw4YN2bp1azZs2JBly5b13RIAADCABIQAMIRmz56du+++O8cdd1zuvffeHHfccbn77rsze/bsvlsDAAAGjIAQAIbQtnDwxhtvzKGHHpobb7xxe0gIMMqsQQgAjyUgBIAhddVVV+1yG2AUWYMQAB5LQAgAQ+r000/f5TbAKPqt3/qtvlsAgIEjIASAIXTEEUfkpptuyvHHH5/77rsvxx9/fG666aYcccQRfbcG0Kvf//3f77sFABg4+/bdAACw+911112ZPXt2brrppvzoj/5okonQ8K677uq5MwAAYNAYQQgAAIyMn/mZn+m7BQAYOAJCABhCs2fP3n4n43vvvXf7HYxnz57dd2sAvfrpn/7pvlsAgIEjIASAIbQtHLzxxhtz6KGH5sYbb9weEgKMMmsQAsBjCQgBYEhdddVVu9wGGEU/9VM/1XcLADBw3KQEAIbUz/zMz2S//fbLxo0bM2fOnDzyyCN9twTQu2nTjJEAgJ35vyMADKGDDz44t99+e5LkzjvvTJLcfvvtOfjgg/tsC6B3n/70p/tuAQAGjoAQAIbQoYcemlmzZmXDhg154QtfmA0bNmTWrFk59NBD+24NoFdvetOb+m4BAAaOKcYAMIQ2btyYzZs3Z/r06dtrW7ZsycyZM3vsCqB/9957b98tAMDAMYIQAIbQnDlzsnbt2h1qa9euzZw5c3rqCGAwfOYzn+m7BQAYOAJCABhCF154YRYtWpTrr78+W7ZsyfXXX59Fixblwgsv7Ls1gF79+q//et8tAMDAMcUYAIbQWWedlSRZunTp9rsYL1++fHsdYFTdfffdfbcAAANHQAgAQ+qss84SCALs5CMf+UjfLQDAwDHFGAAAGBl//Md/3HcLADBwBIQAAMDIuPPOO/tuAQAGzl4ZEFbV66vqK1V1R1W9o+9+APrkmggAT94f/uEf9t0CAAycvS4grKp9kvxxkn+b5GVJzqqql/XbFUA/XBMB4MmbPn161q5dm+nTp/fdCgAMlL0uIEzyqiR3tNb+sbX2SJIPJ1nYc08AfXFNBIAnacuWLfniF7+YLVu29N0KAAyUvfEuxocluXvS9j1J/s3OO1XVuUnOTZLZs2fvmc74oR1zxTE/1PFHX370M3Lu9Wevf9rHwjPsCa+Jrod7px/2evhMck1kUFXV65P8tyT7JPlAa+3dPbfEAHrrW9/adwsAMHD2xoCwpqi1xxRauzTJpUkyf/78x7zOYPph/+ismuo/jwmt+c+AofSE10TXw72TEA6emklLLpyciS9L/r6q1rTWvtxvZwyK6dOn55FHHtm+vd9++xlJCACdvXGK8T1Jjpi0fXiSe3vqhQEzY8aMp1SHIeCaCDDBkgvs0pYtW7LffvvlxhtvFA4CwE72xoDw75McVVUvqqr9kpyZZE3PPTEgNm/e/JgwcMaMGdm8eXNPHcEzzjURYMJUSy4ctvNOVXVuVa2rqnWbNm3aY83Rr20zSbZs2ZITTjhhezhohgkATNjrphi31h6tql9N8olMrC/zJ621DT23xQARBjJKXBMBtrMMDbskDASAx7fXBYRJ0lr7qyR/1XcfAIPANREgiSUXAACetr1xijEAAOzMkgsAAE/TXjmCEAAAJrPkAgDA0ycgBABgKFhyAQDg6THFGAAAAABGmIAQAAAAAEaYgBAAAAAARpiAEAAAAABGmIAQAAAAAEaYgBAAAAAARli11vru4RlXVZuSfL3vPtjjnpfkW303wR71wtbarL6bGGSuhyPL9XA0uSY+AdfEkeWaOHpcDwGewEgEhIymqlrXWpvfdx8AfXM9BPgB10QAeCxTjAEAAABghAkIAQAAAGCECQgZZpf23QDAgHA9BPgB10QA2Ik1CAEAAABghBlBCAAAAAAjTEDIXqWqfrSqruqev6Kq3vAkjnlNVX38h/idf1VVBz7d4wGeST/sdbGqfqGq/vsz3Scw2qrqyKr6Ut999GXU3z8Ag09AyF6ltXZva+30bvMVSZ7wD+Hd8Dvf0Fp78Jn+PQBPRx/XRYBBUFX77k3nBYBBJiBkj6qqt1TVbVX1xar6UFX9X1V1c1V9vqo+VVUv6Pb73e7166rq9qo6p6sfWVVfqqr9kvyXJG+qqi9U1Zuq6lVVdVN3rpuq6l9P8ftnVdU1VXVrVf2Pqvp6VT2ve+0vquqWqtpQVedOOuZrVfW87ndvrKrLun0+WVX775l/OWBY9X1d3KmXF1bVtV0/11bV7K5+Rvc7vlhVf9vV5lbV57rfdVtVHfXM/ksBQ2CfnT9HdSOf/667jvzvqjooSarqhqqa3z1/XlV9rXv+C1X151X1/0vyyao6tKr+trsWfamqfqrb73tVdUn3me/aqprV1V9cVX/Tfeb7TFW9tKtfXlXvqarrk1xcVeur6sCa8O2qeku334eq6nVVtU9V/deq+vuu9/9n25usqt+YVP+9nf8RqurHuuvyTzyj/9oA8BQICNljqmpukguTnNRae3mSX0uyNsmrW2s/nuTDSf7zpEPmJfnZJD+Z5Ler6ke3vdBaeyTJbyf5SGvtFa21jyT5hyQ/3Z3rt5NcNEUbv5PkutbaK5P87ySzJ732S621Y5PMT/K2qjpkiuOPSvLHrbW5SR5M8u+f4j8DwHYDcl2c7L8n+WBrbV6SP0vyvq7+20lO7Xpc0NUWJ/lvrbVXZOK6ec/T+CcARstUn6M+mGRZd91Zn4nPak/kJ5Oc3Vo7KcnPJflEdy16eZIvdPs8O8mt3We+T08676VJlnaf+X49yfsnnfdfJXlda+38JDcmOT7J3CT/mOSnun1eneTvkixK8p3W2k8k+Ykk51TVi6rqlO59vioTo7qPraqf3vYLui9qPprkF1trf/8k3isA7BGGz7MnnZTkqtbat5KktXZ/VR2T5CNVdWiS/ZLcOWn/q1tr/5LkX7pvc1+VH3zom8pzk1zRjWJpSaZPsc8JSf5d9/v/pqoemPTa26rq33XPj8jEh7tv73T8na21bT3ckuTIXfQD8EQG4bo42U8m+b+75x9K8v92z29McnlVXZnkY13ts0kurKrDk3ystXb7E75bYNTt/DnqxUkObK19uqtdkeTPn8R5rmmt3d89//skf1JV05P8xaTzb03yke75nyb5WFUdkOS4JH9eVdvONWPSef+8tfb97vlnkvx0kq8nWZnk3Ko6LMn9rbXvdUHgvKratsTDczPx2fGU7vH5rn5AV78ryawkVyf59621DU/ifQLAHmMEIXtSZeIP1MlWJPnvrbVjkvw/SWZOem3nfXfe3tnvJ7m+tXZ0kv9rp3NN7uGxxarXJHldkp/sRsh8/nGOH5/0/PsRsgM/nEG4Lu5KS5LW2uIkv5mJL0++UFWHtNb+VyZGE/5Lkk9U1UlP8dzA6Nn5c9SBu9j30fzgb5Wdr10Pb3vSWvvbTAR5/5TkQ9umAk+hded7sBtlve0xZ6rzJvnbTIwa/KkkNyTZlOT0TASHycT1e+mk87yotfbJrv6uSfWXtNZWdcd8J8ndmRiZCAADRUDInnRtkv+wbepuVR2ciW9b/6l7/eyd9l9YVTO7/V+TiW+IJ/tukh+ZtD35XL/wOD2sTfIfut9/SpKDJh37QGvtn7u1aF795N8WwNM2CNfFyW5Kcmb3/D9m4pqZqnpxa+3m1tpvJ/lWkiOq6seS/GNr7X1J1mRi+jPAU/GdJA9sWzcwyZszMR04Sb6W5Nju+el5HFX1wiTfbK1dlmRVkld2L02bdNzPJVnbWnsoyZ1VdUZ3bFXVy6c6b2vt7iTPS3JUa+0fM3E9/PX8ICD8RJIl3cjFVNW/qqpnd/Vf6kYrpqoOq6rnd8c8kuS0JG+pqp/b1T8MAOxpAkL2mG4qxfIkn66qLyZ5T5LfzcQ0j89k4o/OyT6X5C8zsc7L77fW7t3p9euTvKxblPpNmZgK966qujHJPo/Txu8lOaWqbk3yb5Pcl4k/qP8myb5VdVsmRtz83Q/1ZgGehAG5Lk72tiS/2F0L35yJNRGT5L92C/Z/KROjar6Y5E1JvlRVX0jy0kysIwbwVJ2diWvMbZlYs++/dPU/zEQAd1MmgrrH85pMjGz+fCbWNPxvXf3hJHOr6pZMLOew7bz/Mcmi7pq7IcnCXZz75iT/p3v+mSSHpfviJMkHknw5ya3dtfF/JNm3G0X4v5J8tqrWJ7kqk764aa09nOSNSf5TVe3qdwPAHlWtPdHsJNjzqup3k3yvtfaHu/m8M5J8v7X2aFX9ZJKV3aLWAAPtmbouAgyjqvpea+2AvvsAgL2F9dMYNbOTXFlV0zIxzeOcnvsBAAAA6JURhAAAAAAwwqxBCAAAAAAjTEAIAAAAACNMQAgAAAAAI0xACAAAAAAjTEAIAAAAACNMQAgAAAAAI+z/A2UWgx9jq3NOAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1296x2880 with 10 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "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>age</th>\n",
       "      <th>educationno</th>\n",
       "      <th>capitalgain</th>\n",
       "      <th>capitalloss</th>\n",
       "      <th>hoursperweek</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>skewness</th>\n",
       "      <td>0.532784</td>\n",
       "      <td>-0.310621</td>\n",
       "      <td>11.788871</td>\n",
       "      <td>4.517536</td>\n",
       "      <td>0.340536</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>kurtosis</th>\n",
       "      <td>-0.155931</td>\n",
       "      <td>0.635045</td>\n",
       "      <td>150.147899</td>\n",
       "      <td>19.376085</td>\n",
       "      <td>3.201287</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               age  educationno  capitalgain  capitalloss  hoursperweek\n",
       "skewness  0.532784    -0.310621    11.788871     4.517536      0.340536\n",
       "kurtosis -0.155931     0.635045   150.147899    19.376085      3.201287"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "num_columns = dfa.select_dtypes(exclude='object').columns.tolist()\n",
    "plt.figure(figsize=(18,40))\n",
    "for i,col in enumerate(num_columns,1):\n",
    "    plt.subplot(8,4,i)\n",
    "    sns.kdeplot(df[col],color='g',shade=True)\n",
    "    plt.subplot(8,4,i+10)\n",
    "    df[col].plot.box()\n",
    "plt.tight_layout() \n",
    "plt.show()\n",
    "num_data = df[num_columns]\n",
    "pd.DataFrame(data=[num_data.skew(),num_data.kurtosis()],index=['skewness','kurtosis'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dc225f7f",
   "metadata": {},
   "source": [
    "## 4. SVM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "cb75ccfa",
   "metadata": {},
   "outputs": [],
   "source": [
    "col= df1.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "7b4c9ebd",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train= train[col[0:13]]\n",
    "y_train= train[col[13]]\n",
    "x_test= test[col[0:13]]\n",
    "y_test= test[col[13]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "667527a1",
   "metadata": {},
   "outputs": [],
   "source": [
    "def norm_func(i):\n",
    "    x= (i-i.min())/(i.max()-i.min())\n",
    "    return (x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "08231b1f",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train= norm_func(x_train)\n",
    "x_test=  norm_func(x_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b9c77331",
   "metadata": {},
   "source": [
    "### 4.1 Linear"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "55d847cb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy: 0.8097609561752988\n"
     ]
    }
   ],
   "source": [
    "model_linear= SVC(kernel = \"linear\")\n",
    "model_linear.fit(x_train,y_train)\n",
    "pred_test_linear= model_linear.predict(x_test)\n",
    "print(\"Accuracy:\",metrics.accuracy_score(y_test, pred_test_linear))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca998844",
   "metadata": {},
   "source": [
    "### 4.2 Poly"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "86cbd8a3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy: 0.8435590969455511\n"
     ]
    }
   ],
   "source": [
    "model_poly= SVC(kernel = \"poly\")\n",
    "model_poly.fit(x_train,y_train)\n",
    "pred_test_poly= model_poly.predict(x_test)\n",
    "print(\"Accuracy:\",metrics.accuracy_score(y_test, pred_test_poly))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "214489a6",
   "metadata": {},
   "source": [
    "### 4.3 RBF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "23e4876a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy: 0.8432934926958832\n"
     ]
    }
   ],
   "source": [
    "model_rbf= SVC(kernel = \"rbf\")\n",
    "model_rbf.fit(x_train,y_train)\n",
    "pred_test_rbf= model_rbf.predict(x_test)\n",
    "print(\"Accuracy:\",metrics.accuracy_score(y_test, pred_test_rbf))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1422ab27",
   "metadata": {},
   "source": [
    "### 4.4 Sigmoid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "28eab8fe",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy: 0.5768924302788845\n"
     ]
    }
   ],
   "source": [
    "model_sigmoid= SVC(kernel = \"sigmoid\")\n",
    "model_sigmoid.fit(x_train,y_train)\n",
    "pred_test_sigmoid= model_sigmoid.predict(x_test)\n",
    "print(\"Accuracy:\",metrics.accuracy_score(y_test, pred_test_sigmoid))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "df45343c",
   "metadata": {},
   "source": [
    "## 5. Conclusion"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4ea4839b",
   "metadata": {},
   "source": [
    "###### >> Poly Model gives the best accuracy\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a958761c",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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