Credit Card Fraud Detection1.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "9e05b5e9",
   "metadata": {},
   "source": [
    "# The purpose of this project \n",
    "is to develop a sophisticated system for the detection of credit card fraudulent activities. With the increasing use of technology, credit card fraud has become a major concern for consumers and financial institutions, resulting in significant financial losses. To address this issue, it is essential to have systems in place that can detect fraudulent activities and minimize losses.\n",
    "\n",
    "One of the key challenges in detecting credit card fraud is the imbalance in the distribution of fraudulent and non-fraudulent transactions. Fraudulent transactions constitute a small fraction of all transactions, making it difficult to detect them using traditional methods.\n",
    "\n",
    "To overcome this challenge, I have obtained a credit card fraudulent activities dataset from Kaggle. The dataset will be used to analyze the relationships between various features and detect fraudulent transactions. Through exploratory data analysis, I aim to gain a deeper understanding of the dataset and develop a robust model for the detection of fraudulent activities. The link to the dataset has been providedt: https://www.kaggle.com/mlg-ulb/creditcardfraud\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "83193b1b",
   "metadata": {},
   "source": [
    "\n",
    "# Goal: \n",
    "The goal of this project is to use machine learning techniques to improve the accuracy of detecting credit card fraudulent activities. The model will be trained on a dataset of credit card transactions and the goal is to improve the measure called Area Under the Precision-Recall Curve (AUPRC). Additionally, the project aim to acquire more knowledge about the financial industry and how to apply machine learning to real-world problems."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "1ba7fb2f",
   "metadata": {},
   "outputs": [],
   "source": [
    "#importing the dependencies\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "from sklearn.preprocessing import StandardScaler, RobustScaler\n",
    "from sklearn.model_selection import train_test_split, GridSearchCV\n",
    "from imblearn.over_sampling import SMOTE, RandomOverSampler\n",
    "#from sklearn.metrics import classification_report, average_precision_score, plot_precision_recall_curve, plot_roc_curve\n",
    "from sklearn.feature_selection import mutual_info_classif\n",
    "\n",
    "\n",
    "#Importing models\n",
    "from sklearn.linear_model import LogisticRegression, SGDClassifier\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c596ac89",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Time</th>\n",
       "      <th>V1</th>\n",
       "      <th>V2</th>\n",
       "      <th>V3</th>\n",
       "      <th>V4</th>\n",
       "      <th>V5</th>\n",
       "      <th>V6</th>\n",
       "      <th>V7</th>\n",
       "      <th>V8</th>\n",
       "      <th>V9</th>\n",
       "      <th>...</th>\n",
       "      <th>V21</th>\n",
       "      <th>V22</th>\n",
       "      <th>V23</th>\n",
       "      <th>V24</th>\n",
       "      <th>V25</th>\n",
       "      <th>V26</th>\n",
       "      <th>V27</th>\n",
       "      <th>V28</th>\n",
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       "      <th>0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>-1.359807</td>\n",
       "      <td>-0.072781</td>\n",
       "      <td>2.536347</td>\n",
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       "      <td>0.462388</td>\n",
       "      <td>0.239599</td>\n",
       "      <td>0.098698</td>\n",
       "      <td>0.363787</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.018307</td>\n",
       "      <td>0.277838</td>\n",
       "      <td>-0.110474</td>\n",
       "      <td>0.066928</td>\n",
       "      <td>0.128539</td>\n",
       "      <td>-0.189115</td>\n",
       "      <td>0.133558</td>\n",
       "      <td>-0.021053</td>\n",
       "      <td>149.62</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1.191857</td>\n",
       "      <td>0.266151</td>\n",
       "      <td>0.166480</td>\n",
       "      <td>0.448154</td>\n",
       "      <td>0.060018</td>\n",
       "      <td>-0.082361</td>\n",
       "      <td>-0.078803</td>\n",
       "      <td>0.085102</td>\n",
       "      <td>-0.255425</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.225775</td>\n",
       "      <td>-0.638672</td>\n",
       "      <td>0.101288</td>\n",
       "      <td>-0.339846</td>\n",
       "      <td>0.167170</td>\n",
       "      <td>0.125895</td>\n",
       "      <td>-0.008983</td>\n",
       "      <td>0.014724</td>\n",
       "      <td>2.69</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.0</td>\n",
       "      <td>-1.358354</td>\n",
       "      <td>-1.340163</td>\n",
       "      <td>1.773209</td>\n",
       "      <td>0.379780</td>\n",
       "      <td>-0.503198</td>\n",
       "      <td>1.800499</td>\n",
       "      <td>0.791461</td>\n",
       "      <td>0.247676</td>\n",
       "      <td>-1.514654</td>\n",
       "      <td>...</td>\n",
       "      <td>0.247998</td>\n",
       "      <td>0.771679</td>\n",
       "      <td>0.909412</td>\n",
       "      <td>-0.689281</td>\n",
       "      <td>-0.327642</td>\n",
       "      <td>-0.139097</td>\n",
       "      <td>-0.055353</td>\n",
       "      <td>-0.059752</td>\n",
       "      <td>378.66</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.966272</td>\n",
       "      <td>-0.185226</td>\n",
       "      <td>1.792993</td>\n",
       "      <td>-0.863291</td>\n",
       "      <td>-0.010309</td>\n",
       "      <td>1.247203</td>\n",
       "      <td>0.237609</td>\n",
       "      <td>0.377436</td>\n",
       "      <td>-1.387024</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.108300</td>\n",
       "      <td>0.005274</td>\n",
       "      <td>-0.190321</td>\n",
       "      <td>-1.175575</td>\n",
       "      <td>0.647376</td>\n",
       "      <td>-0.221929</td>\n",
       "      <td>0.062723</td>\n",
       "      <td>0.061458</td>\n",
       "      <td>123.50</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2.0</td>\n",
       "      <td>-1.158233</td>\n",
       "      <td>0.877737</td>\n",
       "      <td>1.548718</td>\n",
       "      <td>0.403034</td>\n",
       "      <td>-0.407193</td>\n",
       "      <td>0.095921</td>\n",
       "      <td>0.592941</td>\n",
       "      <td>-0.270533</td>\n",
       "      <td>0.817739</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.009431</td>\n",
       "      <td>0.798278</td>\n",
       "      <td>-0.137458</td>\n",
       "      <td>0.141267</td>\n",
       "      <td>-0.206010</td>\n",
       "      <td>0.502292</td>\n",
       "      <td>0.219422</td>\n",
       "      <td>0.215153</td>\n",
       "      <td>69.99</td>\n",
       "      <td>0</td>\n",
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       "<p>5 rows × 31 columns</p>\n",
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      "text/plain": [
       "   Time        V1        V2        V3        V4        V5        V6        V7  \\\n",
       "0   0.0 -1.359807 -0.072781  2.536347  1.378155 -0.338321  0.462388  0.239599   \n",
       "1   0.0  1.191857  0.266151  0.166480  0.448154  0.060018 -0.082361 -0.078803   \n",
       "2   1.0 -1.358354 -1.340163  1.773209  0.379780 -0.503198  1.800499  0.791461   \n",
       "3   1.0 -0.966272 -0.185226  1.792993 -0.863291 -0.010309  1.247203  0.237609   \n",
       "4   2.0 -1.158233  0.877737  1.548718  0.403034 -0.407193  0.095921  0.592941   \n",
       "\n",
       "         V8        V9  ...       V21       V22       V23       V24       V25  \\\n",
       "0  0.098698  0.363787  ... -0.018307  0.277838 -0.110474  0.066928  0.128539   \n",
       "1  0.085102 -0.255425  ... -0.225775 -0.638672  0.101288 -0.339846  0.167170   \n",
       "2  0.247676 -1.514654  ...  0.247998  0.771679  0.909412 -0.689281 -0.327642   \n",
       "3  0.377436 -1.387024  ... -0.108300  0.005274 -0.190321 -1.175575  0.647376   \n",
       "4 -0.270533  0.817739  ... -0.009431  0.798278 -0.137458  0.141267 -0.206010   \n",
       "\n",
       "        V26       V27       V28  Amount  Class  \n",
       "0 -0.189115  0.133558 -0.021053  149.62      0  \n",
       "1  0.125895 -0.008983  0.014724    2.69      0  \n",
       "2 -0.139097 -0.055353 -0.059752  378.66      0  \n",
       "3 -0.221929  0.062723  0.061458  123.50      0  \n",
       "4  0.502292  0.219422  0.215153   69.99      0  \n",
       "\n",
       "[5 rows x 31 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "original=pd.read_csv(\"creditcard.csv\")\n",
    "df=original.copy()\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c79818bc",
   "metadata": {},
   "source": [
    "The code reads a CSV file named \"creditcard.csv\" into a Pandas dataframe \"original\", creates a copy of it in another dataframe \"df\", and displays"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "262ad706",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 284807 entries, 0 to 284806\n",
      "Data columns (total 31 columns):\n",
      " #   Column  Non-Null Count   Dtype  \n",
      "---  ------  --------------   -----  \n",
      " 0   Time    284807 non-null  float64\n",
      " 1   V1      284807 non-null  float64\n",
      " 2   V2      284807 non-null  float64\n",
      " 3   V3      284807 non-null  float64\n",
      " 4   V4      284807 non-null  float64\n",
      " 5   V5      284807 non-null  float64\n",
      " 6   V6      284807 non-null  float64\n",
      " 7   V7      284807 non-null  float64\n",
      " 8   V8      284807 non-null  float64\n",
      " 9   V9      284807 non-null  float64\n",
      " 10  V10     284807 non-null  float64\n",
      " 11  V11     284807 non-null  float64\n",
      " 12  V12     284807 non-null  float64\n",
      " 13  V13     284807 non-null  float64\n",
      " 14  V14     284807 non-null  float64\n",
      " 15  V15     284807 non-null  float64\n",
      " 16  V16     284807 non-null  float64\n",
      " 17  V17     284807 non-null  float64\n",
      " 18  V18     284807 non-null  float64\n",
      " 19  V19     284807 non-null  float64\n",
      " 20  V20     284807 non-null  float64\n",
      " 21  V21     284807 non-null  float64\n",
      " 22  V22     284807 non-null  float64\n",
      " 23  V23     284807 non-null  float64\n",
      " 24  V24     284807 non-null  float64\n",
      " 25  V25     284807 non-null  float64\n",
      " 26  V26     284807 non-null  float64\n",
      " 27  V27     284807 non-null  float64\n",
      " 28  V28     284807 non-null  float64\n",
      " 29  Amount  284807 non-null  float64\n",
      " 30  Class   284807 non-null  int64  \n",
      "dtypes: float64(30), int64(1)\n",
      "memory usage: 67.4 MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "1e1595de",
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "<Figure size 2000x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Draw distribution plot for Time and Amount\n",
    "fig, ax=plt.subplots(2,1, figsize=(20,10))\n",
    "sns.histplot(df.Amount,bins=500, color='r', ax=ax[0]);\n",
    "ax[0].set_title(\"Distribution plot of Amount Column\")\n",
    "sns.histplot(df.Time,bins=50, color='b',ax=ax[1]);\n",
    "ax[1].set_title(\"Distribution plot of Time Column\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f349d1aa",
   "metadata": {},
   "source": [
    "The code creates a 2x1 figure with subplots, plots a histogram of the 'Amount' column in red with 500 bins and a title \"Distribution plot of Amount Column\" on the first subplot and a histogram of the 'Time' column in blue with 50 bins and a title \"Distribution plot of Time Column\" on the second subplot using seaborn's \"histplot\" function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "919ca14d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "172792.0"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "max(df.Time) # this is equivalent to 2 days almost so try to convert out time into hrs(total time period is 48 hrs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "6e32b8de",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Time</th>\n",
       "      <th>V1</th>\n",
       "      <th>V2</th>\n",
       "      <th>V3</th>\n",
       "      <th>V4</th>\n",
       "      <th>V5</th>\n",
       "      <th>V6</th>\n",
       "      <th>V7</th>\n",
       "      <th>V8</th>\n",
       "      <th>V9</th>\n",
       "      <th>...</th>\n",
       "      <th>V21</th>\n",
       "      <th>V22</th>\n",
       "      <th>V23</th>\n",
       "      <th>V24</th>\n",
       "      <th>V25</th>\n",
       "      <th>V26</th>\n",
       "      <th>V27</th>\n",
       "      <th>V28</th>\n",
       "      <th>Amount</th>\n",
       "      <th>Class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>284802</th>\n",
       "      <td>172786.0</td>\n",
       "      <td>-11.881118</td>\n",
       "      <td>10.071785</td>\n",
       "      <td>-9.834783</td>\n",
       "      <td>-2.066656</td>\n",
       "      <td>-5.364473</td>\n",
       "      <td>-2.606837</td>\n",
       "      <td>-4.918215</td>\n",
       "      <td>7.305334</td>\n",
       "      <td>1.914428</td>\n",
       "      <td>...</td>\n",
       "      <td>0.213454</td>\n",
       "      <td>0.111864</td>\n",
       "      <td>1.014480</td>\n",
       "      <td>-0.509348</td>\n",
       "      <td>1.436807</td>\n",
       "      <td>0.250034</td>\n",
       "      <td>0.943651</td>\n",
       "      <td>0.823731</td>\n",
       "      <td>0.77</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>284803</th>\n",
       "      <td>172787.0</td>\n",
       "      <td>-0.732789</td>\n",
       "      <td>-0.055080</td>\n",
       "      <td>2.035030</td>\n",
       "      <td>-0.738589</td>\n",
       "      <td>0.868229</td>\n",
       "      <td>1.058415</td>\n",
       "      <td>0.024330</td>\n",
       "      <td>0.294869</td>\n",
       "      <td>0.584800</td>\n",
       "      <td>...</td>\n",
       "      <td>0.214205</td>\n",
       "      <td>0.924384</td>\n",
       "      <td>0.012463</td>\n",
       "      <td>-1.016226</td>\n",
       "      <td>-0.606624</td>\n",
       "      <td>-0.395255</td>\n",
       "      <td>0.068472</td>\n",
       "      <td>-0.053527</td>\n",
       "      <td>24.79</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>284804</th>\n",
       "      <td>172788.0</td>\n",
       "      <td>1.919565</td>\n",
       "      <td>-0.301254</td>\n",
       "      <td>-3.249640</td>\n",
       "      <td>-0.557828</td>\n",
       "      <td>2.630515</td>\n",
       "      <td>3.031260</td>\n",
       "      <td>-0.296827</td>\n",
       "      <td>0.708417</td>\n",
       "      <td>0.432454</td>\n",
       "      <td>...</td>\n",
       "      <td>0.232045</td>\n",
       "      <td>0.578229</td>\n",
       "      <td>-0.037501</td>\n",
       "      <td>0.640134</td>\n",
       "      <td>0.265745</td>\n",
       "      <td>-0.087371</td>\n",
       "      <td>0.004455</td>\n",
       "      <td>-0.026561</td>\n",
       "      <td>67.88</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>284805</th>\n",
       "      <td>172788.0</td>\n",
       "      <td>-0.240440</td>\n",
       "      <td>0.530483</td>\n",
       "      <td>0.702510</td>\n",
       "      <td>0.689799</td>\n",
       "      <td>-0.377961</td>\n",
       "      <td>0.623708</td>\n",
       "      <td>-0.686180</td>\n",
       "      <td>0.679145</td>\n",
       "      <td>0.392087</td>\n",
       "      <td>...</td>\n",
       "      <td>0.265245</td>\n",
       "      <td>0.800049</td>\n",
       "      <td>-0.163298</td>\n",
       "      <td>0.123205</td>\n",
       "      <td>-0.569159</td>\n",
       "      <td>0.546668</td>\n",
       "      <td>0.108821</td>\n",
       "      <td>0.104533</td>\n",
       "      <td>10.00</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>284806</th>\n",
       "      <td>172792.0</td>\n",
       "      <td>-0.533413</td>\n",
       "      <td>-0.189733</td>\n",
       "      <td>0.703337</td>\n",
       "      <td>-0.506271</td>\n",
       "      <td>-0.012546</td>\n",
       "      <td>-0.649617</td>\n",
       "      <td>1.577006</td>\n",
       "      <td>-0.414650</td>\n",
       "      <td>0.486180</td>\n",
       "      <td>...</td>\n",
       "      <td>0.261057</td>\n",
       "      <td>0.643078</td>\n",
       "      <td>0.376777</td>\n",
       "      <td>0.008797</td>\n",
       "      <td>-0.473649</td>\n",
       "      <td>-0.818267</td>\n",
       "      <td>-0.002415</td>\n",
       "      <td>0.013649</td>\n",
       "      <td>217.00</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 31 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Time         V1         V2        V3        V4        V5  \\\n",
       "284802  172786.0 -11.881118  10.071785 -9.834783 -2.066656 -5.364473   \n",
       "284803  172787.0  -0.732789  -0.055080  2.035030 -0.738589  0.868229   \n",
       "284804  172788.0   1.919565  -0.301254 -3.249640 -0.557828  2.630515   \n",
       "284805  172788.0  -0.240440   0.530483  0.702510  0.689799 -0.377961   \n",
       "284806  172792.0  -0.533413  -0.189733  0.703337 -0.506271 -0.012546   \n",
       "\n",
       "              V6        V7        V8        V9  ...       V21       V22  \\\n",
       "284802 -2.606837 -4.918215  7.305334  1.914428  ...  0.213454  0.111864   \n",
       "284803  1.058415  0.024330  0.294869  0.584800  ...  0.214205  0.924384   \n",
       "284804  3.031260 -0.296827  0.708417  0.432454  ...  0.232045  0.578229   \n",
       "284805  0.623708 -0.686180  0.679145  0.392087  ...  0.265245  0.800049   \n",
       "284806 -0.649617  1.577006 -0.414650  0.486180  ...  0.261057  0.643078   \n",
       "\n",
       "             V23       V24       V25       V26       V27       V28  Amount  \\\n",
       "284802  1.014480 -0.509348  1.436807  0.250034  0.943651  0.823731    0.77   \n",
       "284803  0.012463 -1.016226 -0.606624 -0.395255  0.068472 -0.053527   24.79   \n",
       "284804 -0.037501  0.640134  0.265745 -0.087371  0.004455 -0.026561   67.88   \n",
       "284805 -0.163298  0.123205 -0.569159  0.546668  0.108821  0.104533   10.00   \n",
       "284806  0.376777  0.008797 -0.473649 -0.818267 -0.002415  0.013649  217.00   \n",
       "\n",
       "        Class  \n",
       "284802      0  \n",
       "284803      0  \n",
       "284804      0  \n",
       "284805      0  \n",
       "284806      0  \n",
       "\n",
       "[5 rows x 31 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "85f7b461",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Time      0\n",
       "V1        0\n",
       "V2        0\n",
       "V3        0\n",
       "V4        0\n",
       "V5        0\n",
       "V6        0\n",
       "V7        0\n",
       "V8        0\n",
       "V9        0\n",
       "V10       0\n",
       "V11       0\n",
       "V12       0\n",
       "V13       0\n",
       "V14       0\n",
       "V15       0\n",
       "V16       0\n",
       "V17       0\n",
       "V18       0\n",
       "V19       0\n",
       "V20       0\n",
       "V21       0\n",
       "V22       0\n",
       "V23       0\n",
       "V24       0\n",
       "V25       0\n",
       "V26       0\n",
       "V27       0\n",
       "V28       0\n",
       "Amount    0\n",
       "Class     0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isna().sum() #Check if any values are missing--maybe there is a correlation with mssing values and fradulent activities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "560a594d",
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'df' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[2], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[43mdf\u001b[49m\u001b[38;5;241m.\u001b[39mhist(figsize \u001b[38;5;241m=\u001b[39m (\u001b[38;5;241m20\u001b[39m, \u001b[38;5;241m20\u001b[39m))\n\u001b[0;32m      2\u001b[0m plt\u001b[38;5;241m.\u001b[39mshow()\n",
      "\u001b[1;31mNameError\u001b[0m: name 'df' is not defined"
     ]
    }
   ],
   "source": [
    "df.hist(figsize = (20, 20))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "a32ba096",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    284315\n",
       "1       492\n",
       "Name: Class, dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"Class\"].value_counts()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "39113756",
   "metadata": {},
   "source": [
    "This Dataset is highly unbalanced\n",
    "\n",
    "class 0 represents Normal Transaction\n",
    "class 1 represents fraudulent transaction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "4f331d3b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Lets visualize this\n",
    "df.Class.value_counts().plot(kind=\"bar\", color=[\"Green\", \"Red\"])\n",
    "plt.xlabel(\"0: Real Transactions, 1: Fraud Transactions\")\n",
    "plt.ylabel(\"total Number of Transactions\")\n",
    "plt.title(\"Comparing real transactions with the number of fraud transactions in the dataset\")\n",
    "plt.xticks(rotation=0);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ce15375e",
   "metadata": {},
   "source": [
    "As you can see, the dataset is highly imbalanced which can significantly affect out ML model. A balanced dataset is best for training purposes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "2813e3a3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1500x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#See if the transactions occur at a given time period\n",
    "plt.figure(figsize=(15,10))\n",
    "plt.scatter(df.Time[df.Class==1], df.Class[df.Class==1], c=\"red\")\n",
    "plt.scatter(df.Time[df.Class==0], df.Class[df.Class==0], c=\"green\");\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bf4e45ea",
   "metadata": {},
   "source": [
    "There is no pattern for when the fraudulent activites occur. They happen at random"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "98e6c66a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2125.87, 0.0)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "max(df.Amount[df.Class==1]), min(df.Amount[df.Class==0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "c70367e3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,6))\n",
    "plt.scatter(df.Time[df.Class==0],df.Amount[df.Class==0], color=[\"green\"])\n",
    "\n",
    "plt.title(\"Transaction Amount of each Real Transactions over Time\")\n",
    "plt.xlabel(\"Time\")\n",
    "plt.ylabel(\"Amount\")\n",
    "plt.legend([\"Real Transactions\"]);\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "cf812d4b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(df.Time[df.Class==1],df.Amount[df.Class==1], color=[\"red\"])\n",
    "\n",
    "plt.title(\"Transaction Amount of each Fradulent Transactions over Time\")\n",
    "plt.xlabel(\"Time\")\n",
    "plt.ylabel(\"Amount\")\n",
    "plt.legend([\"Fraudulent Transactions\"]);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9d3a0966",
   "metadata": {},
   "source": [
    "The Transaction amount for each fraudulent transaction is significantly lower compared to the Real transactions. This makes it a lot more difficult to detect fraud activities. The max amount is approxiamtely $2100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "a1cfb6a8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,5))\n",
    "sns.boxplot(df[\"Amount\"])\n",
    "plt.title(\"Transaction Amounts\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "ce3ab9bb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "16.977724453761024"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.Amount.skew()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a326d184",
   "metadata": {},
   "source": [
    "The Amount is heavily right-skewed with a lot of outliers which we can fix using BoxCox transformation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0bc760ef",
   "metadata": {},
   "source": [
    "# Lets look at the Mean and Standard Deviations for V1-V28 feature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "3738d2c5",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Time</th>\n",
       "      <th>V1</th>\n",
       "      <th>V2</th>\n",
       "      <th>V3</th>\n",
       "      <th>V4</th>\n",
       "      <th>V5</th>\n",
       "      <th>V6</th>\n",
       "      <th>V7</th>\n",
       "      <th>V8</th>\n",
       "      <th>V9</th>\n",
       "      <th>...</th>\n",
       "      <th>V21</th>\n",
       "      <th>V22</th>\n",
       "      <th>V23</th>\n",
       "      <th>V24</th>\n",
       "      <th>V25</th>\n",
       "      <th>V26</th>\n",
       "      <th>V27</th>\n",
       "      <th>V28</th>\n",
       "      <th>Amount</th>\n",
       "      <th>Class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>284807.000000</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>...</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>2.848070e+05</td>\n",
       "      <td>284807.000000</td>\n",
       "      <td>284807.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>94813.859575</td>\n",
       "      <td>1.168375e-15</td>\n",
       "      <td>3.416908e-16</td>\n",
       "      <td>-1.379537e-15</td>\n",
       "      <td>2.074095e-15</td>\n",
       "      <td>9.604066e-16</td>\n",
       "      <td>1.487313e-15</td>\n",
       "      <td>-5.556467e-16</td>\n",
       "      <td>1.213481e-16</td>\n",
       "      <td>-2.406331e-15</td>\n",
       "      <td>...</td>\n",
       "      <td>1.654067e-16</td>\n",
       "      <td>-3.568593e-16</td>\n",
       "      <td>2.578648e-16</td>\n",
       "      <td>4.473266e-15</td>\n",
       "      <td>5.340915e-16</td>\n",
       "      <td>1.683437e-15</td>\n",
       "      <td>-3.660091e-16</td>\n",
       "      <td>-1.227390e-16</td>\n",
       "      <td>88.349619</td>\n",
       "      <td>0.001727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>47488.145955</td>\n",
       "      <td>1.958696e+00</td>\n",
       "      <td>1.651309e+00</td>\n",
       "      <td>1.516255e+00</td>\n",
       "      <td>1.415869e+00</td>\n",
       "      <td>1.380247e+00</td>\n",
       "      <td>1.332271e+00</td>\n",
       "      <td>1.237094e+00</td>\n",
       "      <td>1.194353e+00</td>\n",
       "      <td>1.098632e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>7.345240e-01</td>\n",
       "      <td>7.257016e-01</td>\n",
       "      <td>6.244603e-01</td>\n",
       "      <td>6.056471e-01</td>\n",
       "      <td>5.212781e-01</td>\n",
       "      <td>4.822270e-01</td>\n",
       "      <td>4.036325e-01</td>\n",
       "      <td>3.300833e-01</td>\n",
       "      <td>250.120109</td>\n",
       "      <td>0.041527</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-5.640751e+01</td>\n",
       "      <td>-7.271573e+01</td>\n",
       "      <td>-4.832559e+01</td>\n",
       "      <td>-5.683171e+00</td>\n",
       "      <td>-1.137433e+02</td>\n",
       "      <td>-2.616051e+01</td>\n",
       "      <td>-4.355724e+01</td>\n",
       "      <td>-7.321672e+01</td>\n",
       "      <td>-1.343407e+01</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.483038e+01</td>\n",
       "      <td>-1.093314e+01</td>\n",
       "      <td>-4.480774e+01</td>\n",
       "      <td>-2.836627e+00</td>\n",
       "      <td>-1.029540e+01</td>\n",
       "      <td>-2.604551e+00</td>\n",
       "      <td>-2.256568e+01</td>\n",
       "      <td>-1.543008e+01</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>54201.500000</td>\n",
       "      <td>-9.203734e-01</td>\n",
       "      <td>-5.985499e-01</td>\n",
       "      <td>-8.903648e-01</td>\n",
       "      <td>-8.486401e-01</td>\n",
       "      <td>-6.915971e-01</td>\n",
       "      <td>-7.682956e-01</td>\n",
       "      <td>-5.540759e-01</td>\n",
       "      <td>-2.086297e-01</td>\n",
       "      <td>-6.430976e-01</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.283949e-01</td>\n",
       "      <td>-5.423504e-01</td>\n",
       "      <td>-1.618463e-01</td>\n",
       "      <td>-3.545861e-01</td>\n",
       "      <td>-3.171451e-01</td>\n",
       "      <td>-3.269839e-01</td>\n",
       "      <td>-7.083953e-02</td>\n",
       "      <td>-5.295979e-02</td>\n",
       "      <td>5.600000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>84692.000000</td>\n",
       "      <td>1.810880e-02</td>\n",
       "      <td>6.548556e-02</td>\n",
       "      <td>1.798463e-01</td>\n",
       "      <td>-1.984653e-02</td>\n",
       "      <td>-5.433583e-02</td>\n",
       "      <td>-2.741871e-01</td>\n",
       "      <td>4.010308e-02</td>\n",
       "      <td>2.235804e-02</td>\n",
       "      <td>-5.142873e-02</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.945017e-02</td>\n",
       "      <td>6.781943e-03</td>\n",
       "      <td>-1.119293e-02</td>\n",
       "      <td>4.097606e-02</td>\n",
       "      <td>1.659350e-02</td>\n",
       "      <td>-5.213911e-02</td>\n",
       "      <td>1.342146e-03</td>\n",
       "      <td>1.124383e-02</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>139320.500000</td>\n",
       "      <td>1.315642e+00</td>\n",
       "      <td>8.037239e-01</td>\n",
       "      <td>1.027196e+00</td>\n",
       "      <td>7.433413e-01</td>\n",
       "      <td>6.119264e-01</td>\n",
       "      <td>3.985649e-01</td>\n",
       "      <td>5.704361e-01</td>\n",
       "      <td>3.273459e-01</td>\n",
       "      <td>5.971390e-01</td>\n",
       "      <td>...</td>\n",
       "      <td>1.863772e-01</td>\n",
       "      <td>5.285536e-01</td>\n",
       "      <td>1.476421e-01</td>\n",
       "      <td>4.395266e-01</td>\n",
       "      <td>3.507156e-01</td>\n",
       "      <td>2.409522e-01</td>\n",
       "      <td>9.104512e-02</td>\n",
       "      <td>7.827995e-02</td>\n",
       "      <td>77.165000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>172792.000000</td>\n",
       "      <td>2.454930e+00</td>\n",
       "      <td>2.205773e+01</td>\n",
       "      <td>9.382558e+00</td>\n",
       "      <td>1.687534e+01</td>\n",
       "      <td>3.480167e+01</td>\n",
       "      <td>7.330163e+01</td>\n",
       "      <td>1.205895e+02</td>\n",
       "      <td>2.000721e+01</td>\n",
       "      <td>1.559499e+01</td>\n",
       "      <td>...</td>\n",
       "      <td>2.720284e+01</td>\n",
       "      <td>1.050309e+01</td>\n",
       "      <td>2.252841e+01</td>\n",
       "      <td>4.584549e+00</td>\n",
       "      <td>7.519589e+00</td>\n",
       "      <td>3.517346e+00</td>\n",
       "      <td>3.161220e+01</td>\n",
       "      <td>3.384781e+01</td>\n",
       "      <td>25691.160000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 31 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                Time            V1            V2            V3            V4  \\\n",
       "count  284807.000000  2.848070e+05  2.848070e+05  2.848070e+05  2.848070e+05   \n",
       "mean    94813.859575  1.168375e-15  3.416908e-16 -1.379537e-15  2.074095e-15   \n",
       "std     47488.145955  1.958696e+00  1.651309e+00  1.516255e+00  1.415869e+00   \n",
       "min         0.000000 -5.640751e+01 -7.271573e+01 -4.832559e+01 -5.683171e+00   \n",
       "25%     54201.500000 -9.203734e-01 -5.985499e-01 -8.903648e-01 -8.486401e-01   \n",
       "50%     84692.000000  1.810880e-02  6.548556e-02  1.798463e-01 -1.984653e-02   \n",
       "75%    139320.500000  1.315642e+00  8.037239e-01  1.027196e+00  7.433413e-01   \n",
       "max    172792.000000  2.454930e+00  2.205773e+01  9.382558e+00  1.687534e+01   \n",
       "\n",
       "                 V5            V6            V7            V8            V9  \\\n",
       "count  2.848070e+05  2.848070e+05  2.848070e+05  2.848070e+05  2.848070e+05   \n",
       "mean   9.604066e-16  1.487313e-15 -5.556467e-16  1.213481e-16 -2.406331e-15   \n",
       "std    1.380247e+00  1.332271e+00  1.237094e+00  1.194353e+00  1.098632e+00   \n",
       "min   -1.137433e+02 -2.616051e+01 -4.355724e+01 -7.321672e+01 -1.343407e+01   \n",
       "25%   -6.915971e-01 -7.682956e-01 -5.540759e-01 -2.086297e-01 -6.430976e-01   \n",
       "50%   -5.433583e-02 -2.741871e-01  4.010308e-02  2.235804e-02 -5.142873e-02   \n",
       "75%    6.119264e-01  3.985649e-01  5.704361e-01  3.273459e-01  5.971390e-01   \n",
       "max    3.480167e+01  7.330163e+01  1.205895e+02  2.000721e+01  1.559499e+01   \n",
       "\n",
       "       ...           V21           V22           V23           V24  \\\n",
       "count  ...  2.848070e+05  2.848070e+05  2.848070e+05  2.848070e+05   \n",
       "mean   ...  1.654067e-16 -3.568593e-16  2.578648e-16  4.473266e-15   \n",
       "std    ...  7.345240e-01  7.257016e-01  6.244603e-01  6.056471e-01   \n",
       "min    ... -3.483038e+01 -1.093314e+01 -4.480774e+01 -2.836627e+00   \n",
       "25%    ... -2.283949e-01 -5.423504e-01 -1.618463e-01 -3.545861e-01   \n",
       "50%    ... -2.945017e-02  6.781943e-03 -1.119293e-02  4.097606e-02   \n",
       "75%    ...  1.863772e-01  5.285536e-01  1.476421e-01  4.395266e-01   \n",
       "max    ...  2.720284e+01  1.050309e+01  2.252841e+01  4.584549e+00   \n",
       "\n",
       "                V25           V26           V27           V28         Amount  \\\n",
       "count  2.848070e+05  2.848070e+05  2.848070e+05  2.848070e+05  284807.000000   \n",
       "mean   5.340915e-16  1.683437e-15 -3.660091e-16 -1.227390e-16      88.349619   \n",
       "std    5.212781e-01  4.822270e-01  4.036325e-01  3.300833e-01     250.120109   \n",
       "min   -1.029540e+01 -2.604551e+00 -2.256568e+01 -1.543008e+01       0.000000   \n",
       "25%   -3.171451e-01 -3.269839e-01 -7.083953e-02 -5.295979e-02       5.600000   \n",
       "50%    1.659350e-02 -5.213911e-02  1.342146e-03  1.124383e-02      22.000000   \n",
       "75%    3.507156e-01  2.409522e-01  9.104512e-02  7.827995e-02      77.165000   \n",
       "max    7.519589e+00  3.517346e+00  3.161220e+01  3.384781e+01   25691.160000   \n",
       "\n",
       "               Class  \n",
       "count  284807.000000  \n",
       "mean        0.001727  \n",
       "std         0.041527  \n",
       "min         0.000000  \n",
       "25%         0.000000  \n",
       "50%         0.000000  \n",
       "75%         0.000000  \n",
       "max         1.000000  \n",
       "\n",
       "[8 rows x 31 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "2e0a6db9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vs = df.drop(labels=[\"Time\", \"Amount\",\"Class\"], axis=1)\n",
    "\n",
    "plt.figure(figsize=(10,10))\n",
    "sns.barplot(x=vs.columns, y=vs.mean(), color=\"red\")\n",
    "plt.xlabel(\"Columns\")\n",
    "plt.ylabel(\"Mean\")\n",
    "plt.title(\"V1-V28 Means\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "aec7b7f5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,10))\n",
    "sns.barplot(x=vs.columns, y=vs.std(), color=\"darkblue\")\n",
    "plt.xlabel(\"Columns\")\n",
    "plt.ylabel(\"Standard Deviations\")\n",
    "plt.title(\"V1-V28 Standard Deviations\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "fbffbcf6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,10))\n",
    "sns.barplot(x=vs.columns, y=vs.skew(), color=\"green\")\n",
    "plt.xlabel(\"Columns\")\n",
    "plt.ylabel(\"Skewness\")\n",
    "plt.title(\"V1-V28 Skewness\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "b1c5122e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>V1</th>\n",
       "      <th>V2</th>\n",
       "      <th>V3</th>\n",
       "      <th>V4</th>\n",
       "      <th>V5</th>\n",
       "      <th>V6</th>\n",
       "      <th>V7</th>\n",
       "      <th>V8</th>\n",
       "      <th>V9</th>\n",
       "      <th>V10</th>\n",
       "      <th>...</th>\n",
       "      <th>V19</th>\n",
       "      <th>V20</th>\n",
       "      <th>V21</th>\n",
       "      <th>V22</th>\n",
       "      <th>V23</th>\n",
       "      <th>V24</th>\n",
       "      <th>V25</th>\n",
       "      <th>V26</th>\n",
       "      <th>V27</th>\n",
       "      <th>V28</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-1.359807</td>\n",
       "      <td>-0.072781</td>\n",
       "      <td>2.536347</td>\n",
       "      <td>1.378155</td>\n",
       "      <td>-0.338321</td>\n",
       "      <td>0.462388</td>\n",
       "      <td>0.239599</td>\n",
       "      <td>0.098698</td>\n",
       "      <td>0.363787</td>\n",
       "      <td>0.090794</td>\n",
       "      <td>...</td>\n",
       "      <td>0.403993</td>\n",
       "      <td>0.251412</td>\n",
       "      <td>-0.018307</td>\n",
       "      <td>0.277838</td>\n",
       "      <td>-0.110474</td>\n",
       "      <td>0.066928</td>\n",
       "      <td>0.128539</td>\n",
       "      <td>-0.189115</td>\n",
       "      <td>0.133558</td>\n",
       "      <td>-0.021053</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.191857</td>\n",
       "      <td>0.266151</td>\n",
       "      <td>0.166480</td>\n",
       "      <td>0.448154</td>\n",
       "      <td>0.060018</td>\n",
       "      <td>-0.082361</td>\n",
       "      <td>-0.078803</td>\n",
       "      <td>0.085102</td>\n",
       "      <td>-0.255425</td>\n",
       "      <td>-0.166974</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.145783</td>\n",
       "      <td>-0.069083</td>\n",
       "      <td>-0.225775</td>\n",
       "      <td>-0.638672</td>\n",
       "      <td>0.101288</td>\n",
       "      <td>-0.339846</td>\n",
       "      <td>0.167170</td>\n",
       "      <td>0.125895</td>\n",
       "      <td>-0.008983</td>\n",
       "      <td>0.014724</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-1.358354</td>\n",
       "      <td>-1.340163</td>\n",
       "      <td>1.773209</td>\n",
       "      <td>0.379780</td>\n",
       "      <td>-0.503198</td>\n",
       "      <td>1.800499</td>\n",
       "      <td>0.791461</td>\n",
       "      <td>0.247676</td>\n",
       "      <td>-1.514654</td>\n",
       "      <td>0.207643</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.261857</td>\n",
       "      <td>0.524980</td>\n",
       "      <td>0.247998</td>\n",
       "      <td>0.771679</td>\n",
       "      <td>0.909412</td>\n",
       "      <td>-0.689281</td>\n",
       "      <td>-0.327642</td>\n",
       "      <td>-0.139097</td>\n",
       "      <td>-0.055353</td>\n",
       "      <td>-0.059752</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.966272</td>\n",
       "      <td>-0.185226</td>\n",
       "      <td>1.792993</td>\n",
       "      <td>-0.863291</td>\n",
       "      <td>-0.010309</td>\n",
       "      <td>1.247203</td>\n",
       "      <td>0.237609</td>\n",
       "      <td>0.377436</td>\n",
       "      <td>-1.387024</td>\n",
       "      <td>-0.054952</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.232622</td>\n",
       "      <td>-0.208038</td>\n",
       "      <td>-0.108300</td>\n",
       "      <td>0.005274</td>\n",
       "      <td>-0.190321</td>\n",
       "      <td>-1.175575</td>\n",
       "      <td>0.647376</td>\n",
       "      <td>-0.221929</td>\n",
       "      <td>0.062723</td>\n",
       "      <td>0.061458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-1.158233</td>\n",
       "      <td>0.877737</td>\n",
       "      <td>1.548718</td>\n",
       "      <td>0.403034</td>\n",
       "      <td>-0.407193</td>\n",
       "      <td>0.095921</td>\n",
       "      <td>0.592941</td>\n",
       "      <td>-0.270533</td>\n",
       "      <td>0.817739</td>\n",
       "      <td>0.753074</td>\n",
       "      <td>...</td>\n",
       "      <td>0.803487</td>\n",
       "      <td>0.408542</td>\n",
       "      <td>-0.009431</td>\n",
       "      <td>0.798278</td>\n",
       "      <td>-0.137458</td>\n",
       "      <td>0.141267</td>\n",
       "      <td>-0.206010</td>\n",
       "      <td>0.502292</td>\n",
       "      <td>0.219422</td>\n",
       "      <td>0.215153</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         V1        V2        V3        V4        V5        V6        V7  \\\n",
       "0 -1.359807 -0.072781  2.536347  1.378155 -0.338321  0.462388  0.239599   \n",
       "1  1.191857  0.266151  0.166480  0.448154  0.060018 -0.082361 -0.078803   \n",
       "2 -1.358354 -1.340163  1.773209  0.379780 -0.503198  1.800499  0.791461   \n",
       "3 -0.966272 -0.185226  1.792993 -0.863291 -0.010309  1.247203  0.237609   \n",
       "4 -1.158233  0.877737  1.548718  0.403034 -0.407193  0.095921  0.592941   \n",
       "\n",
       "         V8        V9       V10  ...       V19       V20       V21       V22  \\\n",
       "0  0.098698  0.363787  0.090794  ...  0.403993  0.251412 -0.018307  0.277838   \n",
       "1  0.085102 -0.255425 -0.166974  ... -0.145783 -0.069083 -0.225775 -0.638672   \n",
       "2  0.247676 -1.514654  0.207643  ... -2.261857  0.524980  0.247998  0.771679   \n",
       "3  0.377436 -1.387024 -0.054952  ... -1.232622 -0.208038 -0.108300  0.005274   \n",
       "4 -0.270533  0.817739  0.753074  ...  0.803487  0.408542 -0.009431  0.798278   \n",
       "\n",
       "        V23       V24       V25       V26       V27       V28  \n",
       "0 -0.110474  0.066928  0.128539 -0.189115  0.133558 -0.021053  \n",
       "1  0.101288 -0.339846  0.167170  0.125895 -0.008983  0.014724  \n",
       "2  0.909412 -0.689281 -0.327642 -0.139097 -0.055353 -0.059752  \n",
       "3 -0.190321 -1.175575  0.647376 -0.221929  0.062723  0.061458  \n",
       "4 -0.137458  0.141267 -0.206010  0.502292  0.219422  0.215153  \n",
       "\n",
       "[5 rows x 28 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vs.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "fd87822e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(284315, 31)\n",
      "(492, 31)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "count    284315.000000\n",
       "mean         88.291022\n",
       "std         250.105092\n",
       "min           0.000000\n",
       "25%           5.650000\n",
       "50%          22.000000\n",
       "75%          77.050000\n",
       "max       25691.160000\n",
       "Name: Amount, dtype: float64"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# separating data for further analysis\n",
    "valid = df[df.Class == 0]\n",
    "fraud = df[df.Class == 1]\n",
    "print(valid.shape)\n",
    "print(fraud.shape)\n",
    "# statistical measures of the data for amouunt field\n",
    "valid.Amount.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "a110924f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count     492.000000\n",
       "mean      122.211321\n",
       "std       256.683288\n",
       "min         0.000000\n",
       "25%         1.000000\n",
       "50%         9.250000\n",
       "75%       105.890000\n",
       "max      2125.870000\n",
       "Name: Amount, dtype: float64"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fraud.Amount.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ce2059e7",
   "metadata": {},
   "source": [
    "# Correlation Matrix to see how each variable is related to each other and the target variable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "37bbd314",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: numpy in c:\\users\\sohel\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (1.24.1)\n"
     ]
    }
   ],
   "source": [
    "!pip install --upgrade numpy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "25593ec1",
   "metadata": {},
   "outputs": [
    {
     "data": {
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4du0ajh49CltbW5XjzetBSAjCwsKwdKl6y//AQYPw9u1biEQiTJ82Dd9++y0A9Z7XksrPqtZXuS5cuIDk5GQMyVNXqKu+0tPTQ7u2bbFj5040b94ctWvXxunTp3H//n1BT88DwPz587H6t98wcNAgaGpqQkNDA4sXL5Y+tSlPly5d4LN/Pzq0b49GjRrhxs2bCDx/HmKxGED5OM+KiMVirFu/HlZWVjAzMwNQca43x44fh56eHnoXMrW5EOqsr6KionDr1i30798fmzZuREREBJxdXJCVlYXp06YVuq2q9fPdu3fhHxAAn/37y1W8ueTVOfn1798f7969w9SpUyGRSCASiTBixAhMnjQJQPkus8U57jZPT8yZMwdfffUVgOyn4p89f45Dhw4Vq/xFRUXh1atXOPf331ju5ASRWIz169djwcKF2Pr774K2L069EBcXh6vXrmFVzsw+gHrPcVHHFqKwNn9h5LVrynqZzVXc9kZ5vl4JuR4JaeOU5fazKu2roo5ZlvO2Kvn5x4kT8SE5GSNHjYKGhgbEYjFmzpiBAQMGACjb8ZYENzc3GBkZoXPnzgDUG2/Tpk2xdOlStDAzQ3JyMvbt24fJU6bg4J9/ol69eiUST17lORZlrkdF5aOyek+DiIiIiIgqNqUGSWzZsgWHDh1C7dq1YWNjg6/zTHsXHx+Pzp0749mzZ0XuZ82aNVi+fLnMMkdHR8zqXbx3AZek12/eYOOfB7Dpl7nQrlpVLcc4efIkfluzRvp544YNOHDgAPbt26f0uyKbNm0Kn/37kZycjL///htOTk7w3LYNpqamePLkCVJTUwu87zg9PR2ROTenR40eLV0+adIk6Y8BRRGLxWhtYSHtvLcyN0fYs2fwK+ZNc3maNWsmnYoZAKysrBAVGYn9Pj5YuWIFIiIikJaWBts873oGsp8cNc95rcHo0aMR8+oVAKD9p59i8+bNgo4tlkhQpUoVrFq5UjpNcsacOViwcCEWLFgAHR2dAtvkP7+bS/D97XmpM+6ivvO85OVnAOjZsyfGjxsHADA3N0fwvXvwO3So0Bsd1atXh8/+/UhJScHNmzexYcMGNGzYEB0/+wxPnz6FSCTC8BEjZLbJyMiQTr3bI8/0nwMGDMAiBwdB8ebl7+8PMzMzWOZMqawu2z09kZqaivv378PdwwONGjdG/379ynx+Lk59lcs/IABdv/hC5l3M6qyvVqxYgRUrVmDAwIHQ1NSEubk5+vXti0ehoQXWlVd+Hzx4gPv372P9unUwMTHB7Tt34JLzzuzPFTztOM/eHqtWr8bIUaNQpUoVNGzYENZDhiDg6FEA6i2/qpxnZTi7uCAsLAw78rxqq7xcb4qqnwMCAtC/f/9iDeAEoNb6SiKRwNDQEIsXLYKmpiYsLCwQGxeHvXv3FvjRoiTq5w8fPmCZoyMWL1oEAwODMh2vIvLqnPxuBQXBy8sLCxcsgKWlJSIiIuC6bh127NiBqVOnlusyq+pxJRIJIiMjsXLlSqzO8z55kUgkXX/27Nm4k/PEukn9+jh48KCgY0vEYmRkZGC5kxOaNm0KAFi2dCm+nzABL168kGmDyE17MeuFY8eOQV9fH7169ZIuU+c5LurYQhTW5i+MvHZNWSyz6mhvlOXrVUldj4pq45SV9nNJta+KOmZZydsllZ/PnjuHU6dOYdWqVfjE1BSPnzzB+vXrYWxsjMGDB5fZeEui/+vt7Y0zZ89i29at0nKgznjbtWsn/ZEeyO7/jhw1CocOHcIMAa/nU1Z5jkWZ61FR+ais3NMgIiIiIlKFpLQTQCoTPEhi8+bNcHBwwKRJk5CYmIiBAwfCyckJDjkdNJFIJJ3+sSgODg6YO3euzDJtbW0kX7+pRNL/n4F+DWhqaOBNUpLM8jfvk1A73/tKhQp9+QJv3ydh0qr/7zSJxGLc/e8J/M4H4sKWbdDUEPy2Erm+/PJLWFpaSj+fO3cOb96+xeA87yUWiUTYuGkT/jhwAEcLeddk1apV0bhxYwCAhYUFHj58iD8OHMDiRYuQkpoKIyMjbNu6tcB2NWrUgL6+vsxToTXzzchRGCMjIzTP1wlu3qwZAgMDBe+jONq0aSOdKjE1NRVA9s2nunXryqxXNWegy6ZNm5CVlQVAudlLjIyMYGxsLPMe6ebNm0MikSA2NhZNmjQpsE3+81vYjzLFoc645cn7neeVP15DQ0NoamqiefPmMus1b968yNcbaGhoSPOzubk5nr94AW9vb3T87DOkpKRAU1MTe/fsgaampsx2uVPs5s3Penp6SsUHZH+nZ86cwU82Nkpvq6zcd1SbmZkh4c0beHp6on+/fmU+PxenvgKAmJgY3LhxAy4uLjLL1VlfNWrUCJ45g1I+fPgAIyMjODg4yH1PuLzyO2PmTLiuXSt9H3SLFi3w5MkT7Nu3T+FNfENDQ6xzdUV6ejoSExNhbGwMN3d3NMx5B29ZO89CObu44J/Ll+Hp6SnzJFp5ud4UVj/fuXMHL1++xJrfflN6v/mps74yqlMHWlpaMvtt3qwZEhISkJmZKc0/QMnUz5GRkYiOjsZce3vpstwZUT7v0gV+vr5lJl55FNU5+W3duhUDBw6UzupjZmaG1NRUrP7tN0yePLncltniHDf3PC1ZvFgmHwHZ12sg+33xubPE5b5rXOixNTU1pQMkAEh/yHj1+nWRgySKUy9IJBIEHD2KgQMHyuSfj9GuUnRsIQpr8yuiqF1TFstsSbc3yvr1qqSuR0W1ccpK+7mk2ldFHbOs5O2Sys+bN23CxIkT0a9vXwDZ16aYmBh4eXtj8ODBZTbe4vZ/9+7dC+/du7HFwwMtWrSQLv8Y+TmXlpYWzM3NEREZqfI+ClOeY1HmelRUPior9zSIiIiIiKhyEXwXc9u2bdi+fTvG5TxxOGPGDHz77bdITU3FCiVHX2tra8vt1CQrtZf/V1VLC+ZNmiIo9BF6ts+ellMsFuPWo0cY0fsrlfbZ0cICex1lZ7tY7e2FpvXr4/v+A4o9QALI7uDm7eQOGzYMPXr0kFln1uzZGDhgAIbkuZEihFgiQWZGBgCgVatWSEhIgKamJhrk/DCXX27nVllWVlYFBse8DA+HSf36Ku1PWY+fPIFRnToAsm/oV6tWDa9ev1Y4S4Eq73wGst+Ve+7cOaSkpKB69eoAsuPU0NAo0InPlf/8qos645Yn73eel7x427RuXSB/hIeHK50ecc6TpkD2oAmRSIS3b98qfDJJ1fyc69y5c8jMzJROYfuxSMRiZGZmAij7+bm49VXA0aMwNDRE927dZJars77KpaurC11dXSQlJeHa9euYPWtWgXXyx5ucnIysrKwCT/1paGhALCl6rKi2tjbq1q2LrKwsBAYG4pucJ1fL2nkuikQigcvatbhw4QK2bd1aYIBJebneFFY/+/v7w8LCAi1btlQpnXmps76ysrLCqdOnIRaLpT9Uh4eHw8jIqMCPjyVRPzdr1gwH/vhDZtnvW7ci5cMH2Nvbo169ehCJRGUiXnkU1Tn5paWloUq+Np5Gzg19iURS7spsSRxXR0cHxsbGiIqKUnhdVDV9VlZWEIlEiIyMlL4WIPcd7ELKdnHqhaDbtxEREYGh1tYyyz9Gu0rRsVWRt82viKJ2TVmpo/IqqfZGeblelfT1SFEbp6y0n0u6fVXW83ZJ5ee09HTpsXJpamhAkvMdldV4i2P3nj3YtWsX3N3c0Lp1a5m/fYz8nEskEuHp06foVkT7QVUVKZbCrkdF5aOyck+DiIiIiIgqF8GDJJ4/f46uXbtKP3ft2hWBgYHo06cPMjMzMWfOHHWkT7Cx3/TFKq+daNW0GVo3b44/z51DWkY6Bud0AFfs2gFjA0PMGJ49jWFmVhaex0QDALKyshD37i2eRISjurY2GtWtBz0dXXzSUPY99bra2qilr19geUkxMDAoMIW1lpYW6tSpI/Mk3YwZM9Crd2+MyZkC1t3dHV27dkX9+vWRkpKCU6dOISgoCG5ubgCAzzt3Rtu2bTFv3jzMnj0bTZo0QVxcHP65cgW9e/UqcNMhV2ZmpvT1KZmZmYiLi8Pjx49RvXp1aUd93HffYfKUKdjl5YVv+vRBSEgIDh8+XOjTbLlSUlIQEREh/RwVHY3Hjx+jVq1aqF+/Ptzd3REbF4cVOa9m8fHxQYOGDfGJqSnS09Ph7++PW7duwT0nTj09PXz//fdYv349JGIxPv30UyQnJ+NucDD09fQKnXb52bNnyMzMRGJSElJSUvD48WMAkE7t2L9/f+zcuRPLV6yAzfTpePfuHTZv3gzrIUOUmv46MTERr169Qlx8PABIb6DWqVMHRkZGAIBljo6oa2wMu5ypJos6D+qMu6jvvCgTJkyAw6JF6NC+PTp27Iir167h8uXLMk/t5Y/Xy8sLFq1bo1HDhsjMzMSVK1dw4sQJOCxcCCB7Ws8B/fvD0ckJc37+Gebm5nj77h1u3riBFi1aSJ9Ckyc3vtTUVLx9+xaPHz9G1apVC0wJ6h8QgJ49eyqcUl4eZfPzwYMHUb9+fWnZvn3nDvbt348xY8YAKPv5WdX6Csge9HL06FEMHjSowBPH6qyvrl27BolEgqZNmyIiMhKbN21Cs2bNYC3gRyp9fX106NABmzZvhraODkzq18ft27dx4sQJ/JLn+pc/Pz948ACxsbFo2bIl4uLi4OnpCYlYjB9++AFA2T/P+Tk7O+PU6dNY5+qK6tWrIz6nLtPX14eOjk6Zvd4IlZycjHN//62wTZM/PxdV7tVZX40YMQIH//oLruvWYczo0YiIiICXt7e0DimKsvWztrY2zMzMZPZRI2fmgdzlZTXewuqc/GW2R48e8PHxgbm5OSzbtEFEZCS2bt2KL3v0gKamZrkos8pej4Qc12b6dKx1dYW+vj6++OILZGZm4uHDh0h6/x7fjx+vMC0RERFISUlBQkIC0tLTpTGbmpqiatWq6Ny5M1q1aoUVK1Zgrr09JGIxnF1c8Pnnn8vMLqGIkHohf7y5/P39YWlpWSBfq/McF3XsohTV5s+fn6XHU9CuKatlNi9V2xvl/Xql7PWoqDZOWW0/q9q+KuqYZTVvq5qfe3Tvjl1eXqhfvz5MTU3x+PFj7Pfx+Sjnt7hlWZX+r/fu3di2bRtWrVoFExMTafmtXr06qlevrtZ4t2/fjrZt26JRo0ZITk7Gnr178erVK3w7dKigeOUp7Lpc3mLJpez1qKh8VJbvaRARERERUcVVRSIR8IgGgCZNmmD//v0Fnnx4+PAhvvrqK/Tr1w/79u2DSCRSOTEJF/9ReVsA8A38G/vPnMKbpCS0aNQYv4wdhzY5HURbVxeY1KmDJZOmAABi4uMxYtGCAvto39IcHvN+lbt/W1cXtGjcGHPGfFesdAJAnZ7d8T7f60HkGWJtje/GjpXO4JG7bPDgwbCZPh0AsGLlSty8eRPx8fHQ19dHCzMz/DBxIrrkmZ70w4cP2PL77wgMDMTbt29Rp04ddGjfHra2tqiv4Gm76OhoWMvpQHfo0AGe27ZJP1++fBnuHh6IiIhAgwYNMH7cOAwbNkxmmxo1axaI91ZQEH766acC+x88aBCcnJzg5OSE6JgY6bF279mDw4cPIy4uDjo6OjAzM8O0qVPRsWNH6bYSiQQHDhyAr58foqKiUKNGDbQyN8ekSZPQoUOHQr/nmJiYAstv3fz/V8C8ePECLmvXIjg4GAa1aqFPnz6YMWOG3B8u5MULAEePHsVyOTOvTJs2TXo+p9vYoIGJCZycnAAIOw/qilvId15YvED2zUtvb2/ExsaiaZMmmG5jg149e0r/nj/eLb//jrNnzyI2Nhba2tpo1rQpxo4di74508sC2QObdu7cieMnTiA2NhYGBgZoa2kJGxubQn9w6NipU4FlJiYmMlPbvnjxAiNHjYK7u7tMGSoqXmXz84E//8ShQ4cQHR0NTU1NNGrUCMO+/RbDhw+XPl1T1vOzvOMWVV8BwPXr12E3axb8fH3l/gimrvrq7NmzcPfwQGxsLGrWrImvvvoKtjNnykwxX1i88fHx8PDwwPV//0VSUhLq16+PYcOGYfy4cdInIPPn56CgIPzP2RlRUVHQ1dVFt27dMMvOTmb64dI+z0LPLyC/DAGA47Jl0icgS/t6U5TC4j106BDWrV+P06dOFcgXQMH8XFS5B9RbX927dw/rN2zAkydPYGxsjKFDh2LiDz/ITGVckvVzfk5OTnifnIx1rq7SZWUx3sLqnPwxZmVlYZeXF06cOIG4uDgYGBjgyx49MHPmTNSoUQNA6ZfZvErieiT0uKdOncKevXvx/Plz6OrqwuyTT/Ddd9+hd+/eCmOebmOD27dvF1ge4O8vfXo/Li4OLmvX4t9//4Wujg66du2KOXPmSN/FXlS8RdUL8uJNTk5Gv/79Mc/eXm4dos5zXNSxC4u3qDa/vDJbVLumtMtsYfEqIqS9UR6uVyV5PRLSximL7WdAtfaVkGOWdt4uyfz84cMHbN26FecvXMDbt29hZGSEfv36YdrUqdLZHMpqvKr0fxXVpXm3UVe869avx/nz55GQkICaNWqglYUFZsyYgVb5Brsp034u6rpc2rEIURLXo6LyUWnf08gfLxERERGRUFN+/6PolSqAnTOK/9t4WSN4kMS4ceNQr149bNiwocDfQkJC0Lt3byQkJJTqIInyROggiYpCmZsIFQHjrdgYb8XGeCs2xluxMd6KjfFWbIy3YmO8FRvjrdgqY7xEREREREJxkET5Jfh1Gw4ODggKCpL7tzZt2iAwMBB+fn4lljAiIiIiIiIiIiIiIiIiIiKikiR4kISVlRU6deqEzMxMjB07VjrlcC5LS0tYWlqWeAKJiIiIiIiIiIiIiIiIiIiISoKG0BUvXrwIS0tL2Nvbw8TEBBMnTsTly5fVmTYiIiIiIiIiIiIiIiIiIiKiEiN4kESPHj2wc+dOxMTEwM3NDS9evEDPnj3RsmVLODs749WrV+pMJxEREREREREREREREREREVGxCB4kkUtPTw+TJk3CxYsX8eTJE4waNQoeHh5o0qQJrK2t1ZFGIiIiIiIiIiIiIiIiIiIiomJTepBEXmZmZli0aBGWLFmCGjVq4Pjx4yWVLiIiIiIiIiIiIiIiIiIiIqISpaXqhpcuXcKuXbvg5+cHDQ0NjB49GlOmTCnJtBERERERERERERERERERERGVGKUGSURHR8Pb2xve3t54+vQpunbtis2bN2P06NHQ09NTVxqJiIiIiIiIiIiIiIiIiIjKDLFEUtpJIBUJHiQxYMAAnDt3DkZGRvjhhx8wefJkmJubqzNtRERERERERERERERERERERCVG8CCJqlWrwtfXF4MHD4ampqY600RERERERERERERERERERERU4gQPkggICFBnOoiIiIiIiIiIiIiIiIiIiIjUSqO0E0BERERERERERERERERERET0MQieSYKIiIiIiIiIiIiIiIiIiIgAiURS2kkgFXEmCSIiIiIiIiIiIiIiIiIiIqoUOEiCiIiIiIiIiIiIiIiIiIiIKgUOkiAiIiIiIiIiIiIiIiIiIqJKQau0E0BERERERERERERERERERFSeiCWlnQJSFWeSICIiIiIiIiIiIiIiIiIiokqBgySIiIiIiIiIiIiIiIiIiIioUuAgCSIiIiIiIiIiIiIiIiIiIqoUOEiCiIiIiIiIiIiIiIiIiIiIKgWt0k4AERERERERERERERERERFReSKRSEo7CaQiziRBRERERERERERERERERERElQIHSRAREREREREREREREREREVGlUEXCeUCIiIiIiIiIiIiIiIiIiIgEm+C2r7ST8FHsnfV9aSehxGmVdgLySnwZXtpJ+GhqNW2C90lJpZ2Mj6ZGzZqMtwJjvBUb463YGG/FxngrNsZbsTHeio3xVmyMt2JjvBVbZYyXiIiIiKgy4us2iIiIiIiIiIiIiIiIiIiIqFLgIAkiIiIiIiIiIiIiIiIiIiKqFDhIgoiIiIiIiIiIiIiIiIiIiCoFDpIgIiIiIiIiIiIiIiIiIiKiSkGrtBNARERERERERERERERERERUnkgkktJOAqmIM0kQERERERERERERERERERFRpcBBEkRERERERERERERERERERFQpcJAEERERERERERERERERERERVQpapZ0AIiIiIiIiIiIiIiIiIiKi8kQskZR2EkhFnEmCiIiIiIiIiIiIiIiIiIiIKgUOkiAiIiIiIiIiIiIiIiIiIqJKgYMkiIiIiIiIiIiIiIiIiIiIqFLgIAkiIiIiIiIiIiIiIiIiIiKqFLRKOwFERERERERERERERERERETliURS2ikgVXEmCSIiIiIiIiIiIiIiIiIiIqoUOEiCiIiIiIiIiIiIiIiIiIiIKgUOkiAiIiIiIiIiIiIiIiIiIqJKgYMkiIiIiIiIiIiIiIiIiIiIqFLgIAkiIiIiIiIiIiIiIiIiIiKqFJQaJLFjxw5MnDgRXl5eAIA///wTFhYWMDU1haOjo1oSSERERERERERERERERERERFQStISuuHHjRixZsgT9+vXD4sWLER0djQ0bNuCXX36BSCTCunXr0LBhQ0yfPl2d6SUiIiIiIiIiIiIiIiIiIiJSieBBEtu2bYOnpyfGjRuHO3fuoHPnzti6dSumTJkCAGjYsCF+//13DpIgIiIiIiIiIiIiIiIiIiKiMknw6zZevnyJ7t27AwDat28PTU1NdOnSRfr3nj17IiwsrORTSEREREREREREREREREREVIZIKsl/FZHgmSSqV6+ODx8+SD8bGxtDX19fZp2srKySS5kAfwX4Y99ffyHhzRu0MP0E82xt0aZVK4Xrn7t0Edu8dyPm9Ss0btgQdlOnolvnz6V/X77WBcfPnpXZpkvHjtj82xrp510++3Hlxg08CQtDVS0tBB4+UmLxxMbGws3NDVevXUNaWhoaNWoEx2XL0Lp1a7nrBwYGwtfPD0+ePEFmZiZMTU0xfdo0fPHFF8VKR3p6OtasWYNHoaF48eIFunfvjnWurgXWy8jIwPYdO3Dy5EkkJCTAyMgIU6dOxVBra0HHuX37Nvbu3YtHoaGIj4+H69q16NWrV6HbFPeYiqx1dUVwcDDCwsLQvFkz+Pj4FFhHIpFg3759OHzkCGJiYmBgYICRI0diyuTJxTp2LicnJxw7flxm2RddusDNza1Y+xX6PT9//hyb3dxw+/ZtiEQimDZvDhcXF9SvX1+l43748AFbt27F+QsX8PbtW5i3bAl7e3u0adNG7vqlmZ/lffcAYNq8OQ4ePCj4WCkpKXBzd8fFixeRmJiIBg0aYMyYMRg5YoSg7U+fOYPFixejZ8+ecsucMuLj47Fh40Y8evQIERERGDtmDOzt7Qus5+PjA18/P7x+/RoGtWrhq6+/hp2tLbS1tVU6rirluqRief/+PbZs2YLA8+eRlJQEExMTzJ07F927dSvW8eX5bc0aHDp0CHN/+QXjxo0TtI23tzfcPTzw3dixctOvjLCwMGzdtg2hoaGIiYlRmA5lryvF3Q4A7gYHw8bGBp+YmsqtS5XxMcuvKnWwl5cXzp8/jxcvX0JbWxvt2rXDLDs7NGvWTPBx5VHn+fX19YWvnx9iYmIAAKamppg6ZQq6KSgnhw8fxvETJ6QDYS1atcJMW1tYKqjLhSrNci20/G7z9MT27dtlljVt2hR+vr4qHxtQf/lVpR4+efIk9uzdi/DwcOjr66Nr1674efZsGBgYFCPSj9e+6tipk9zls2fPxg8TJsj9mzquV4B687ay5TcrKwteXl44dvw44uLi0LRpU8yys0PXrl2LFePH6ivk2ubpiTNnzuD169eoWrVqdj00cyYsLS0VbqNsO1So0qq71FEfqbsuKoqy+Xm6jQ1u375dYHm3bt2waeNGldPxsc9pYGAg/A4dQmhoKBITE7F/3z6Ym5sXuk1FKcu5hlhbS897XqNGjsSCBQtU2mdp52dV2oTlOU+LRCJ4enri5KlT0jwxZPBgTJkyBVWqVClWulRRltsbytZ1QgnJ8+ooa0REREREFYngQRKtWrXCvXv3YGFhAQCIiIiQ+XtoaGixfxRQxtkLF7Bx2zYsnD0bbVpZ4MChQ5i9yAF/7dyF2oaGBda/FxKCpb/9hpmTp6B7l89xOvA85js5Ya/HFnzSvLl0vS86dsLSefOkn6tVrSqzn6ysLHzd40u0tbBAwKlTJRZPUlISpkydio6ffYZNmzbB0MAAERERqFmzpsJt7ty5g88//xy2M2eiRo0aOHr0KH6ZOxfe3t5oVcSNlsKIxWJo6+hg7JgxCAwMVLjeQgcHvHnzBkuXLEHjxo0RHx8PsUT4aKLU1FS0aNkS1tbWmP/rr4K2Ke4xC2M9ZAgehITg6X//yf2767p1uH79On6ePRtmZmZISkpCYlJSiRw7V9cvvsCyZcukn6tVq1bsfQr5niMjIzF12jRYW1vDxsYG+np6CAsLK9bxV61ahbCwMKxYvhzGxsY4cfIkZtra4q+DB1G3bt0C65dmfp43bx7s7Oykn0UiEcaNH4+v+/RR6lgbNmzAzVu3sGLFCjQwMcH169fh7OICYyMj9OzZs9Bto6OjsWnTJrRv316pYyqSkZEBQwMDTJ48WeEP1adOnYK7hweWLV2Kdu3aITw8HE7Ll6NKlSqY+8svKh1XlXJdFCGxZGZmwtbWFoa1a8PZ2Rl1jY0RExODGjVqlEga8jp//jwe3L8PY2NjwduEhITg0OHDaNGiRYmkIS0tDY0aNkSfPn2wfv16ueuocl0pznZA9s1WR0dHdOrUCW8SElSKLa+PWX4B5evg27dvY9SoUWjdujVEIhE8tmyB3axZ+OvgQejq6ip9/FzqPL9169aFnZ0dmjRuDIlEgmPHj8N+3jzs37cPn3zySYH1g4KC0K9vX7Rr1w7a2trYvXs37OzscPDPP+XW5UKVVrlWtvyamppii4eH9LOWluCms0LqPL+A8vXw3eBgODo5Ye4vv6BHjx6Ii4vDb2vWYPXq1Vi7dq3S8eX3MdpXp06elPl89epVrFy1Cl/17q1wG3VcrwD15m1ly++W33/HyZMnsXjxYjRr2hTXr1/H/F9/xc6dO8tFXyFX0yZN8Ov8+WjYsCHS09Ph88cfsLWzw5HDh2Eop98HKN8OFao02yQlXR+puy4qirL5ea2LCzIzM6WfExMTMW78ePT5+utipeNjn9PUtDR8amWFb/r0warVqwVtU1HKcq49u3dDJBJJP4eFhcHWzk6ltluu0s7PqrQJy3Oe3r1nD3z9/LDcyQmmpqZ4+OgRVqxYAX19fYwdO1bldBVHWW1vKFvXCSUkz6ujrBERERERVSSC76w4OztDT09P4d/Dw8NhY2NTIokSwsfPD98OGIAh/foDABb+/DOu3PgXR0+fxkQ5nbIDRw6jS6dOmDB6NADgpx9/xI3bQTgY4A+Hn+dI16tatSqMatdWeNzpP0wEABw7c7oEowF2796NevXqwdHRUbqsYcOGhW6Tf9S9ra0tLl68iMuXLklvlojFYuzevRuHjxxBQkICmjRpgilTphTa8dbV1YXDwoUAgODgYLxPTi6wztWrV3H79m34HzmCWrVqAQAaNGggLNgc3bp1U2r0vNBjHjlyBPv270d0dDRMTEwwdswYjBo1qtB9z88ZGPPW01Nup/r58+fw9fXFnwcOSAcDFXV+VFG1WjUYGRkp/PurV6+wcdMmXL9+HRoaGvj0008xz96+0O9eyPfssWWL9KnRXI0aNVI+gBxpaWkIPH8e61xd0aFDBwCAzfTpuHz5Mnz9/DBzxowC25RmftbX15eZGefChQtISkqC9ZAhSsUdfO8eBg8ahI6ffQYAGD58OA4dPoyQhw8LHSQhEomwZOlSTJ8+HXfv3CmQxoyMDGzZsgWnz5zB+/fv8cknn2DWrFnS48jToEEDzMvJ1wEBAQrTa9WuHfr37y/dpl/fvngQEqJU3HkVld/UFYt/QAASk5Kwa9cu6Y8GytZJQsTGxmKtqyvcNm/GHIEDSVJSUrB02TIsXrQIO3ftKvD39+/fY+OmTbh48SIyMzNhYWGBub/8gpYtWyrcZ5s2baRPw7q7u8tdR5XrSnG2A7Kf0O/frx80NDVx8cIFmb+V9fILFF0H55d/lgknR0d807cvHj16JK37ytr5/fLLL2U+286cCT8/P9x/8EDujdpVq1bJfF6yZAkCz5/HjZs3MXjQIADlp1yrUn61NDULzRNl7fwCyrev7t+7l91eymk/N2zYEMOHD8eePXtk1ivL7av85+jipUvo+NlnhbZlhHxPZS1vK1t+T5w4gcmTJkmfCh45ciT+vXED+/ftw8qVKwGU7b5Crtx2Sq5f5syBv78//vvvP3Tu3LnA+kLboWXt/BalsPqoLNZFRVE2P+fmo1xnzpyBjo4O+uT5sa88nNNBAwcCyB4gLVRFKcu58g9u2r17Nxo1aoTPymjbSQghbcL8ynOevnfvHnr27Cl9JW+DBg1w+vRphBTSjxSSLqDitTeE1HXqyvNFlTUiIiIiospOQ+iK3bp1w6effqrw7zNnzpR5klOdMjMzEfrfE3Rq//8New0NDXRq3wH3Hz2Uu839hw/Rub1sR6BLx464/+iRzLLb94LRb9QojJw8Cf/bvAnvSnimAEUuXb4MCwsLLFi4EN/07Ytx48fj8OHDSu1DLBbjQ0oKaubpbHt5e+P4iRNwWLgQfx44gHHffYdly5YhKCioeOm9dAmtLSywZ88eDBg4EMNHjMDGjRuRlpZWrP0W95gnT57E1m3bMHPGDPx18CBsZ87E1m3bcOzYseId+/JlNGzYEP/88w+shw7FEGtrrFy1ComJicUNS0ZQUBC+6dsXw0eMwJr//Q/v3r2T/i0rKwuzZs9G9erVsWP7duzcsQPVdXUxa/ZsmSdQlCUWi3HlyhU0bdIEdrNm4Zu+fTHxxx9xId8PnMoQiUQQiUQFnsLW1tbG3bt3BafrY+Xn/Pz9/dG5c2eYmJgotZ1Vu3a4dOkSYmNjIZFIcOvWLYSHh6PL558Xut2OHTtQu3ZtfDt0qNy/u7i44N79+/ht9Woc+OMP9Pn6a8yePRvh4eFKpU9eeh+FhkoHRURGRuLK1avFnvqzMOqK5dKlS2jXti2cnZ3Rt18/jB4zBru8vGSenCkusViMZY6OmPD990o99ePs4oJu3brhcwX5YMHChXjz5g02b9qEvXv2oJW5OWbMnFns+kXV64qq2wUEBCAqKgrTpk2T+/eyXn6BwutgIZJzflzI+0RiWTu/eYlEIpw+cwapqalo17atoG3S0tKQlZWFWnliLA/lWtXyGx4Rgf4DBmDo0KFYsmQJXr16JfP3snx+hWrbrh1ev36Nf65cgUQiQUJCAgL//hvd8kzjXp7aVwkJCfjnn38wVME1VRllOW8LKb+ZmZmolu/1WTra2rgbHCz9XN76CpmZmTh8+DD09fUV/ngktB1als+vPIXVR+W9LlLleuQfEIC+33wj85R+eTunQlXEspwrMzMTJ06ehLW1tfQ1DeU9PwPy24RFKU95ul27drh58yZevnwJAHjy5AmCg4OL/QqYit7eUFTXqSvP5yWvrBERERERVXbFnzNYBenp6UhPT5dZpp2v01+Yd0mJEInFBV6rUdvQEC/zvQYkV8Lbt6htaCC7voEh3rx5I/38RcdO6N29OxrUN0FkdDR+99qFOYsXYefGTdDU1BScPlVERUXBz88P48eNw6RJk/AwJASu69ahatWqGDx4sKB97N23D6mpqfgm58mDjIwMeHl5YYuHB9q1awcge3aAu8HBOHT4MD4r5OkDIem9GxyMatraWLt2Ld69ewdnZ2ckJibKPJlRkoQcc5unJ+bMmYOvvvoKQPbTAc+eP8ehQ4cEf4+Kjv3q1Suc+/tvLHdygkgsxvr167Fg4UJs/f33Eonvi65d0bt3bzRs2BCRkZHw2LIFs3/+GV67dkFTUxNnzpyBWCzG0iVLpJ1aR0dH9OrdG0FBQejSpYtKx33z5g1SUlLgvXs3ZsyYgVl2drh27Rrm//ortv7+u0r5RE9PD+3atsWOnTvRvHlz1K5dG6dPn8b9+/cFz1DxMfNzXnFxcbh67RpW5TyVpYz58+dj9W+/YeCgQdDU1ISGhgYWL16s8OkhALh79y78AwLgs3+/3L+/evUKR48dw7GjR6XTw0+YMAHXrl3D0aNHYWtrq3Q6c/Xv3x/v3r3D1KlTIZFIIBKJMGLECEyeNEnlfRZGnbFERUXh1q1b6N+/PzZt3IiIiAg4u7ggKysL0xX8aK+s3bt3Q1NTU+EUsvKcPnMGoaGh2LN7t9y/3717FyEhITh75oz0x5w5c+bgwsWL+PvvvzF8+HCV06vqdUWV7cLDw+Hu4YHtnp5yp/8uD+W3qDq4KGKxGOvWr4eVlRXMzMwAlM3zCwBPnz7FpMmTkZGRAV1dXaxduxampqaCjuvm5gYjIyPp09vlpVyrUn4t27SBk6MjmjZtivj4eGzfvh1Tp03DnwcOQE9Pr8yeX2V9amWFVStXYtGiRUhPT4dIJEKPHj1k3lVdntpXx44fh56eHnoXMvW1EGU1bytTfrt06QKf/fvRoX17NGrUCDdu3kTg+fMQi8UAyldf4fLly1i0eDHS0tJgZGQED3d3GBgYyF1XSDu0rJ5fRQqrj/77779yWxepej16EBKCsLAwLF26VLqsvJ1TZVSkspzfhQsXkJycjCE5+akiXFvltQmLUt7y9I8TJ+JDcjJGjhoFDQ0NiMVizJwxAwMGDFA5TUDFbW8UVtepM8/nlb+sEREREVHJKc7rCKl0KTVIYsuWLTh06BBq164NGxsbfJ1n6sb4+Hh07twZz549K3I/a9aswfLly2WWOTo64pdJk5VJTonrm6dzY9a8OVqYmmLYxB8QdC+4wCwUJU0sFqO1hYW0o9vK3Bxhz57BT2Bn8NSpU9i+fTvWubqids7rQiIiIpCWlgbbfDN8ZGZmwjzn9QWjR49GTM5TSO0//RSbN28Wll6JBFWqVMGqlSul05xnzJmDBQsXYsGCBdDR0REWuBKKOqZEIkFkZCRWrlyJ1Xne7yoSiaTrz549G3dyniAzqV8fBw8eFHRsiViMjIwMLHdyQtOmTQEAy5YuxfcTJuDFixfSKRuFOnnyJH5bs0b6efOmTejXt6/0s5mZGczMzPDtsGEICgpC586d8d9//yEyMhJf5nttQ0ZGBiIjI3Hnzh3M/vln6fJFDg6CblJIcirwnj17Yvy4cQAAc3NzBN+7B79Dh1S+qbZixQqsWLECAwYOhKamJszNzdGvb188Cg0tctuPnZ/zOnbsGPT19dGrV69C15N3Dh88eID79+9j/bp1MDExwe07d+Di4gJjIyO5swh8+PAByxwdsXjRIoU3+p8+fQqRSIThI0bILM/IyJBO0dojzxSeAwYMwCIHB0Gx3goKgpeXFxYuWABLS0tERETAdd067NixA1OnThW0D2WoMxaJRAJDQ0MsXrQImpqasLCwQGxcHPbu3avSzev853fjhg04cOAA9u3bJ/jJm1evXmHdunXwcHdXOBDwyZMnSE1NLfBe2PT0dETm3MwblfOaKACYNGmS4EEsql5XlN1OJBJhyZIlmD59urR+zK88lN+i6uCiOLu4ICwsDDu2b5cuK4vnFwCaNm0Kn/37kZycjL///htOTk7w3LatyB+mvL29cebsWWzbulWap8tiuS6J8gtAZladFi1awNLSEoOHDMHZc+fw7dChZfb8KuvZs2dwXbcOU6dOxRdduiA+Ph6bNm/Gb2vWYNnSpUhNTS1T7St55bd9+/bSzwEBAejfv79SA7DlKYt5G1Cu/M6zt8eq1asxctQoVKlSBQ0bNoT1kCEIOHoUQNnsKyg6vx07doTP/v149+4dDh85AodFi+Dt5SVtJ+ZXVDu0rJ5fRQqrjzLS08ttXaTq9cjf3x9mZmawzJlqHiib57So+kqo8liWhfIPCEDXL76QDgKoCNdWeW3CopSXPJ3r7LlzOHXqFFatWoVPTE3x+MkTrF+/HsbGxip/lxW5vVFYXafOPJ9X/rJGRERERERKDJLYvHkzHBwcMGnSJCQmJmLgwIFwcnKCQ04nTCQSSafaK4qDgwPmzp0rs0xbWxtpr14L2t6gZi1oamjgzdu3MsvfvH2LOrUN5W5Tx9AQb96+k13/3VuFN9YAoKGJCQxq1UJkVLTaB0kYGRmheb6bQc2bNUNgYGCR254+cwYrV62C8//+J/NDbGpqKoDsHwfq1q0rs03VqlUBAJs2bUJWVhYA5WbzMDIygrGxscx74Js3bw6JRILY2Fg0adJE8L5K6ph6enoAgCWLF8PS0lJmWw2N7DfLLFmyRDqLibynnQs7tqampswPgLkd6VevXys9SOLLL7+USaO8jmqjRo1gYGCAiMhIdO7cGSmpqWjVqpXcJ6QNDQ2hpaUlMxtBYXk7LwMDA2hqaqJ58+Yyy5s3by741RjyNGrUCJ6enkhNTcWHDx9gZGQEBweHIt/9WRr5OZdEIkHA0aMYOHCgdJ+KyDuHM2bOhOvatdJ3s7Zo0QJPnjzBvn375A6SiIyMRHR0NOba20uX5T4R9nmXLvDz9UVKSgo0NTWxd8+eAk+z507Fmve855YDIbZu3YqBAwfi22+/BZD9w3BqaipW//YbJk+eLC03JUWdsRjVqQMtLS2Z/TZv1gwJCQnIzMws8nzml//8njt3Dm/evsXgIUOky0QiETZu2oQ/DhzAUTnv1Q0NDcWbN2/w/YQJMtvcuXMHB//6C1evXEFKaiqMjIywbevWAtvXqFED+vr6Mt+JMlP2qnpdUXa7lJQUPHz0CI+fPMHatWsBZOdjiUSCz7t0gbubm/T8luXym1/+Orgwzi4u+OfyZXh6eqJevXrS5WXx/ALZ33njxo0BABYWFnj48CH+OHAAixctUrjN3r174b17N7Z4eKBFixbS5WWxXJdE+ZWnRo0aaNqkCSJzZi0rq+dXWV7e3rCyssIPOXVVixYtoKuri6nTpmHmjBnSgSVlpX1VWPm9c+cOXr58iTW//SY4DYqUxbwNKFd+DQ0Nsc7VFenp6UhMTISxsTHc3N3RMOe982Wxr6Do/Orq6qJx48Zo3Lgx2rZti2HDh8Pf3x+TFPxQVFQ7tKyeX6Hy1kf6NWqU27pIletRamoqzpw5g59sbGSWl8VzKqS9IUR5LMtCxMTE4MaNG3BxcZEuK+/XVkVtwsKUpzyda/OmTZg4caJ0kLGZmRliYmLg5e2t8iCJlJQUABWzvVFYXafOPJ9LXlkjIiIiIiIlBkls27YN27dvx7icJ81nzJiBb7/9FqmpqVixYoVSB9XW1pbbMRf6VsuqVauiVYuWuHn3DnrlPFUjFotx6+4djLKW/z7Atq1b4+adO/guz1R1/96+jbYWFgqP8zouDolJSTCqI+zH5uKwsrIqMMjkZXg4TOrXL3S7U6dPS0fa5/4wm6t58+aoVq0aXr1+rXA2AFXe2Q4AVu3a4dy5c0hJSUH16tWl6dXQ0ChwY6akFHVMHR0dGBsbIyoqSuEMCqqmzcrKCiKRCJGRkdJpenPfA1rUOZJHT0+vyJsYr1+/RmJiIozq1AGQ/aTL2bNnYWhoKHOTKq/cjrcyqlatijatWxfIf+Hh4Srnj7x0dXWhq6uLpKQkXLt+HbNnzVK4bmnl51xBt28jIiICQ62ti1w3/zlMTk5GVlZWgaeUNTQ0FE631KxZMxz44w+ZZb9v3YqUDx9gb2+PevXqSd+r/fbtW4VPnqly3gEgLS0NVfINhNDIuVEmUcMUUebm5mqLxcrKCqdOn4ZYLJbeRAsPD4eRkZFKP0bkP7/Dhg1Djx49ZNaZNXs2Bg4YgCF5fnjNq1OnTgXO74oVK9C0WTNM/OEHaGpqolWrVkhISICmpiYa5Nzozq8434kq1xVlt9PT0ysQp6+vL27eugXn//0PDRs2hFgsLtPlV578dbA8EokELmvX4sKFC9i2dWuBQWBl8fzKI5ZIkJmRofDvu/fswa5du+Du5obWrVvL/K0sluuSKL/ypKSkIDIqCgONjACUn/NblLS0NGjl+/El9/uWSCTSH8jKSvuqsPLr7+8PCwsLtGzZUqX05FUW87Y8RZVfILvvVbduXWRlZSEwMFD6KrOy2FcQUj8D2X2/jMzMItdT1A4tL+dXkbz1UbPmzStEXQQIy8/nzp1DZmZmgfqoLJ5ToflZqPJUloUIOHoUhoaG6J5nppTyem0tqk1YmPKUp3OlpacXGFCvqaFRrD5knTp1Kk17I29dp848n0teWSMiIiIiIkDwY8LPnz9H165dpZ+7du2KwMBAeHp6SmeT+JjGjRgB/xMncOzMGTwPfwnnzZuRmpaGwf36AQAcXZzhsXOndP2x3w7DtVs3sd/3L7wID4fnnj149OQJRucMqkhJTcVmT0/cf/QQ0a9e4cad25jv6IhGDRqgy2cdpft5FRuLJ2FP8So2FmKxGE/CnuJJ2FOk5Dy9oXI8332H+/fvY5eXFyIiInDq1CkcPnwYo0aNkq7j7u6OZXne+3nq1Ck4Ojpizs8/w7JNG8THxyM+Ph7JyckAsjt133//PdavX49jx44hMjISoaGhOPDnnzh27Fih6Xn27BkeP36MxKQkJCcn4/Hjx3j8+LH07/3794dBrVpYvmIFnj17htu3b2Pz5s2wHjJE8JSbKSkpMvuNio7G48eP8SpnGtD88Qo5ps306fDy9saBAwfw8uVLPH36FAEBAdiXZ+S9PBEREXj8+DESEhKQlp4uTVdmzs3Xzp07o1WrVlixYgVCHz/Go0eP8NuaNfj8888VTi+vjJSUFGzatAn3799HdHQ0bty4Aft589C4cWN88cUXALKnzzQwMID9vHm4c+dO9ntEg4Kw1tUVr18rnoWlqO8ZyH636dmzZ3H48GFERETgz4MHcfnyZYwaOVLlmK5du4arV68iKioK1//9Fz/99BOaNWsG65wfMMtSfs7l7+8PS0tLwe+OzUtfXx8dOnTAps2bcSsoCFFRUTh69ChOnDiB3nmm/l/m6Ah3d3cA2Tc6c6f1z/1XQ18f1fX0YGZmhqpVq6Jp06YY0L8/HJ2cEBgYiKioKDwICYGXlxf++eefQtOUG2dqairevn2Lx48fy7wSqUePHvDz88PpM2ek52nr1q34skePAk8rCVVYflNnLCNGjEBSUhJc163Dy5cv8c8//8DL21umDi0OAwODAudKS0sLderUkXnyaMaMGfgzZ9pXvZzzmPefjq4uDGrVkuaxzzt3Rtu2bTFv3jxcv34d0dHRCA4OhseWLXj48KHC9GRmZsrUU3FxcXj8+DEicp5wB4RdV+RR9nqkoaFRIE7D2rWhXa0azMzMoKurW+bLr5A6GJA9vwDg7OyMkydPYtXKlahevbq03kpLyx72WRbPr7u7O27fvo3o6Gg8ffoU7u7uCAoKQv+cm9F56ygA8N69G1u3bsWyZctgYmIijTH3ab/yUK5VKb8AsHHjRgQFBUnP27z586GhoYF+OW3Nsnh+AeXbV1/26IHA8+fh6+uLyMhI3A0OhqurK9q0aSN9arI8tK+Sk5Nx7u+/MXSo/AHT+c9vUd9TWczbypbfBw8eIDAwUPpatlmzZkEiFuOHH34AUPb7CkD2E9YeHh64f/8+YmJi8OjRIyxfsQJxcXHok+fVj/nPb1Ht0LJ4fgtTWH1UVuuioiibn3P5BwSgZ8+eBV5VV17OaWJiYvb+nz8HALx8+RKPHz9GfHy8dJ2KWJbzE4vFOHr0KAYPGiQzI0B5zc9FtQmBipWne3Tvjl056YiOjsb58+ex38dH5pV3+dsbQtJVEdsbRdV16szzgOKyRkREREQlRyKRVIp/FVEVicDImjRpgv379xd4Eu/hw4f46quv0K9fP+zbtw8ikUjlxCS+DFdq/YP+R7Dvr7+Q8PYtWpp+AvuZM2GZMzPET/PsYVKvHhzn/ypd/9yli9jq7Y2Y16/RuEFDzJo2Fd06Z0+Bn5aejvlOjnjyNAzvPyTDuE4dfN7hM9j8+CPqGP7/KzyWr3XB8bNnC6Tl97Wu+MzKSnDaazVtgvdJSTLLLl++DHcPD0RERKBBgwYYP24chg0bJv27k5MTomNi4LltGwBguo0Nbt++XWDfgwcNgpOTE4DswnngwAH4+vkhKioKNWrUQCtzc0yaNAkdOih+hcgQa2vExMQUWH7r5k3p/7948QIua9ciODgYBrVqoU+fPpgxY4bcmyU1atYsEO+toCD89NNPCtOfP16hxzx16hT27N2L58+fQ1dXF2affILvvvsOvXv3Vhivou8ywN9fOpo/Li4OLmvX4t9//4Wujg66du2KOXPmSN8HWlS8hUlLS8O8+fPx+PFjvH//HsbGxujy+ef46aefUCfPU8zx8fFwc3fHlStXkJKSAmNjY3Tu1Ak///yzwtklivqec/kHBMDb2xuxsbFo2qQJptvYoFfPnoLSLy/es2fPwt3DA7GxsahZsya++uor2M6cKU1nWcvPycnJ6Ne/P+bZ28uUO6HxAtnnx8PDA9f//RdJSUmoX78+hg0bhvHjxklnmJhuY4MGJiYy331eTk5OeJ+cjHWurtJlWVlZ2LlzJ46fOIHY2FgYGBigraUlbGxsCv1BuGOnTgWWmZiYSKeWz8rKwi4vL5w4cQJxcXEwMDDAlz16YObMmahRo0aR8cpTVH5TVywAcO/ePazfsAFPnjyBsbExhg4dKp2xQRlC4x1ibY3vxo6VzrCUu2zw4MGwmT5d7jbTbWxg3rIl7PO8YuXDhw/Y8vvvCAwMxNu3b1GnTh10aN8etra2qK/gyabo6GhYy7kx16FDB5k6s6jriqJ4lb0e5bfN0xMXL1yAj4+PdFlZLr9C6+D851devgQAx2XLpDMUlLXzu2LlSty8eRPx8fHQ19dHCzMz/DBxIrrkvBIofx2l6PufNm2a9HsoS+W6JMuvw6JFuHPnDhITE2FoaAgrKyvYzpwpfQIRKHvnF1CtfXXgzz9xyM8PUdHRqFGjBjp17IhZs2bJPLFZ1ttXhw4dwrr163H61Cm5baL851dI+6i083Zxy29QUBD+5+yMqKgo6Orqolu3bphlZyczZXhZ6SvIixfIfif7kiVL8CAkBO/evUOtWrXQunVrTJk8GW3atJFJT97zW1Q7FCh757cwRdVHpV0XCVHc/Axk56mRo0bB3d1dul5epX1OC4s319GjR7Fczkycea+r5bEsK9v/vX79OuxmzYKfr2+BH6nLY34W0iYsz3k6f7wfPnzA1q1bcf7CBbx9+xZGRkbo168fpk2dKp2JQl57Q0i6Klp7o6i6DlBvni+srOWNl4iIiIhUN2q9V2kn4aP4a678V56WZ4IHSYwbNw716tXDhg0bCvwtJCQEvXv3RkJCwkcdJFGeyRskUZEpe9OkvGO8FRvjrdgYb8XGeCs2xluxMd6KjfFWbIy3YmO8FRvjrdg4SIKIiIioeDhIovwSPNeag4MDgoKC5P6tTZs2CAwMhJ+fX4kljIiIiIiIiIiIiIiIiIiIiKgkCR4kYWVlhU6dOiEzMxNjx46VmYodACwtLWFpaVniCSQiIiIiIiIiIiIiIiIiIiIqCRpCV7x48SIsLS1hb28PExMTTJw4EZcvX1Zn2oiIiIiIiIiIiIiIiIiIiMocsaRy/KuIBA+S6NGjB3bu3ImYmBi4ubnhxYsX6NmzJ1q2bAlnZ2e8evVKnekkIiIiIiIiIiIiIiIiIiIiKhbBgyRy6enpYdKkSbh48SKePHmCUaNGwcPDA02aNIG1tbU60khERERERERERERERERERERUbEoPksjLzMwMixYtwpIlS1CjRg0cP368pNJFREREREREREREREREREREVKK0VN3w0qVL2LVrF/z8/KChoYHRo0djypQpJZk2IiIiIiIiIiIiIiIiIiIiohKj1CCJ6OhoeHt7w9vbG0+fPkXXrl2xefNmjB49Gnp6eupKIxEREREREREREREREREREVGxCR4kMWDAAJw7dw5GRkb44YcfMHnyZJibm6szbUREREREREREREREREREREQlRvAgiapVq8LX1xeDBw+GpqamOtNEREREREREREREREREREREVOIED5IICAhQZzqIiIiIiIiIiIiIiIiIiIiI1ErwIAkiIiIiIiIiIiIiIiIiIiICJBJJaSeBVKRR2gkgIiIiIiIiIiIiIiIiIiIi+hg4SIKIiIiIiIiIiIiIiIiIiIgqBQ6SICIiIiIiIiIiIiIiIiIiokpBq7QTQEREREREREREREREREREVJ5IJJLSTgKpiDNJEBERERERERERERERERERUaXAQRJERERERERERERERERERERUKXCQBBEREREREREREREREREREVUKHCRBRERERERERERERERERERElYJWaSeAiIiIiIiIiIiIiIiIiIioPBFLJKWdBFIRZ5IgIiIiIiIiIiIiIiIiIiKiSoGDJIiIiIiIiIiIiIiIiIiIiKhS4CAJIiIiIiIiIiIiIiIiIiIiqhSqSCR8WQoREREREREREREREREREZFQ1s47SjsJH0XAgqmlnYQSp1XaCcgr/l1iaSfhozEyqIX3SUmlnYyPpkbNmoy3AmO8FRvjrdgYb8XGeCs2xluxMd6KjfFWbIy3YmO8FRvjrdhq1KxZ2kkgIiIiojKCr9sgIiIiIiIiIiIiIiIiIiKiSoGDJIiIiIiIiIiIiIiIiIiIiKhS4CAJIiIiIiIiIiIiIiIiIiIiqhQ4SIKIiIiIiIiIiIiIiIiIiIgqBQ6SICIiIiIiIiIiIiIiIiIiokqBgySIiIiIiIiIiIiIiIiIiIioUuAgCSIiIiIiIiIiIiIiIiIiIqoUtEo7AUREREREREREREREREREROWJWCIp7SSQijiTBBEREREREREREREREREREVUKHCRBRERERERERERERERERERElQIHSRAREREREREREREREREREVGlwEESREREREREREREREREREREVClolXYCiIiIiIiIiIiIiIiIiIiIyhOJRFLaSSAVcSYJIiIiIiIiIiIiIiIiIiIiqhQ4SIKIiIiIiIiIiIiIiIiIiIgqBQ6SICIiIiIiIiIiIiIiIiIiokpBq7QTQEREREREREREREREREREVJ5IICntJJCKOJMEERERERERERERERERERERVQrFHiRx4cIFpKamlkRaiIiIiIiIiIiIiIiIiIiIqIJ78+YNxo8fj5o1a8LAwABTpkxBcnJyodv06tULVapUkfn3008/KX3sYg+S6Nu3L168eFHc3RAREREREREREREREREREVElMH78eISEhODs2bM4duwYLl26hOnTpxe53bRp0xATEyP95+LiovSxtYSu2KFDB7nLs7KyMGLECOjo6AAAbt++rXQiiIiIiIiIiIiIiIiIiIiIqOJ79OgRTp06hZs3b6Jjx44AADc3NwwcOBCurq5o0KCBwm2rV6+O+vXrF+v4ggdJ3L9/H3369EGXLl2kyyQSCYKDg9G7d2/UrVu3WAkhIiIiIiIiIiIiIiIiIiKisiM9PR3p6ekyy7S1taGtra3yPq9duwYDAwPpAAkA6NOnDzQ0NPDvv/9i2LBhCrfdv38/9u3bh/r162PIkCFYunQpqlevrtTxBQ+SuHDhAiZOnIjOnTvD0dERGhrZb+pYvXo1bG1t0bp1a6UOTERERERERERERERERERERGXXmjVrsHz5cplljo6OcHJyUnmfr169KjAJg5aWFmrXro1Xr14p3G7cuHFo2rQpGjRogHv37mHBggV4/PgxDh06pNTxBQ+S6NatG4KCgvDTTz+ha9eu2L9/Pz755BOlDlbSJBIJdnh64qj/EbxPTka7du0w79cFaNykSaHb+f31F3z278ObhASYtWiBX+znoXWbNtK/+x8+jLNnTuNx6GOkpHzAqXN/o0aNGgX2c/Wff+C1ayeePn0K7WrV8Gn79vjfWtcSi++3NWtw6NAhzP3lF4wbN07QNt7e3nD38MB3Y8fC3t6+WMcPCwvD1m3bEBoaipiYGLnpGGJtjZiYmALbjho5EgsWLCh0/7dv38bevXvxKDQU8fHxcF27Fr169VK4fmBgIHz9/PDkyRNkZmbC1NQU06dNwxdffKFSfLnS09OxZs0aPAoNxYsXL9C9e3esc5U9j05OTjh2/HiBbU2bN8fBgweLPIaXlxfOnz+PFy9fQltbG+3atcMsOzs0a9ZM4TbTbWzkvr6mW7du2LRxY5HHVCQ+Ph4bNm7Eo0ePEBERgbFjxhTIK1lZWfDy8sKx48cRFxeHpk2bYpadHbp27Sr4OMqeXwDIyMjA9h07cPLkSSQkJMDIyAhTp07FUGtrVUKVWuvqiuDgYISFhaF5s2bw8fEpsI5EIsG+fftw+MgRxMTEwMDAACNHjsSUyZMFHycwMBB+hw4hNDQUiYmJ2L9vH8zNzQvdRkg5U4WQfH0rp07P79TJkzAyMiryGJUl3uLUc6fPnMHixYvRs2fPAulRlpCyCwA+Pj7w9fPD69evYVCrFr76+mvY2doWa0RnfqqceyGE5o/Y2Fi4ubnh6rVrSEtLQ6NGjeC4bFmxBmwWN6bSONfv37/Hli1bEHj+PJKSkmBiYoK5c+eie7duRR6jMsWryvXo4MGDOPjXX4iJiUG9evUwefJkDB40qDhhAij6ehQdHQ3roUMLbOe1axfatm2r9PGUbReWp/OaV2XKz4qo0tYUojTrZXmE9o+2eXpi+/btMsuaNm0KP1/fYh2/tL+PbZ6eOHPmDF6/fo2qVavColUrzJw5E5aWlsXar9B68vnz59js5obbt29DJBLBtHlzuLi4qDy9ZVZWFrb8/juuXLmCqKgo6Ovro3PnzphlZwdjY2NB+/jY/V9Afec3ISEBbm5uuP7vv3j//j06tG+P+fPno0kR9zeKou5+vTyq1kklXTcCH6e/Dyjf3rh79y42u7nh5cuXSEtLQ/369TF8+HCML2bfSEi8QPH73qq0r06ePIk9e/ciPDwc+vr66Nq1K36ePRsGBgYqRPr/PlZ/Xx5VvoeilFZbIpcq5bc0+/klUX6JiIiIqGgODg6YO3euzDJFvzksXLgQzs7Ohe7v0aNHKqdl+vTp0v9v27YtTExM8PXXXyMsLEypsQuCB0kAQK1atfDHH3/Ay8sL3bt3x/Lly1GlShVldlGi9u/dA9+Df2LJMkeYNGiA7du2Ye7Ps7HvwJ8KT8y5s2fhtmkj5i9YiNZt2uDggQOY+/Ns/HHwLxjWrg0ASEtLw+ddvsDnXb7A1i0ecvdzPjAQzmt+g82MGfisY0eIskR49iysxGI7f/48Hty/L/jmEACEhITg0OHDaNGiRYmkIS0tDY0aNkSfPn2wfv16uevs2b0bIpFI+jksLAy2dnb4uk+fIvefmpqKFi1bwtraGvN//bXI9e/cuYPPP/8ctjNnokaNGjh69Ch+mTsX3t7eaFWMH+fEYjG0dXQwdswYBAYGyl1n3rx5sLOzk34WiUQYN368oDiB7I7zqFGj0Lp1a4hEInhs2QK7WbPw18GD0NXVlbvNWhcXZGZmSj8nJiZi3Pjx6PP110pEV1BGRgYMDQwwefJkuTcPAGDL77/j5MmTWLx4MZo1bYrr169j/q+/YufOnYK/a2XPLwAsdHDAmzdvsHTJEjRu3Bjx8fEQSySCYyuM9ZAheBASgqf//Sf3767r1uH69ev4efZsmJmZISkpCYlJSUodIzUtDZ9aWeGbPn2wavVqQdsIKWeqEJKvc/n5+kJPT0/6uXZOXViUyhKvqvVcdHQ0Nm3ahPbt2wuIoGhCyu6pU6fg7uGBZUuXol27dggPD4dTzrV67i+/lEg6ANXOvRBC8kdSUhKmTJ2Kjp99hk2bNsHQwAARERGoWbNmsY5dnJhK41xnZmbC1tYWhrVrw9nZGXWNjRETEyN3UKc8lSleZa9Hvr6+8NiyBYsXLULr1q0R8vAhVq9ejZo1auDLL79UOr78iroeAcAWDw+YmppKP6vy44Gy7cLydl7zqkz5WRFV2ppClGa9nJ+y/SNTU1Ns8fj/vpyWllJdX7lK+/to2qQJfp0/Hw0bNkR6ejp8/vgDtnZ2OHL4MAwNDVXer5B6MjIyElOnTYO1tTVsbGygr6eHsLAwVKtWTeXjpqWlITQ0FFOnTEGLFi3w/v17uK5bh7n29ti7Z0+R25dG/1dd51cikWDe/PnQ0tLCOldX6OnpYb+PD2ba2n6Uclycfr08qtRJ6qgbgY/T3weUb2/o6Opi9OjRaGFmBl1dXdy9exe/rVkDXR0dDB8+XPBx8xPaLypu31vZeO8GB8PRyQlzf/kFPXr0QFxcHH5bswarV6/G2rVrBR9XkY/R35dHlfseRSmttkQuVcpvafbzS6L8EhEREVHRlHm1hr29PX788cdC1zE1NUX9+vURGxsrszwrKwtv3rxR6oGMzz//HADw9OlT9Q2SyDVp0iR0794d48ePR1ZWliq7KDaJRIKDBw5g4qTJ6NGzJwBgqZMThgzoj8sXL6JP375yt/vzDx8MGfotBg0ZAgCYv3Ahrl69gmNHj2LCxIkAgDHffQcAuB0UJHcfWVlZ2LR+PWxnzcIQ6/9/2q95npvZxREbG4u1rq5w27wZcwT+qJWSkoKly5Zh8aJF2LlrV4G/v3//Hhs3bcLFixeRmZkJCwsLzP3lF7Rs2VLhPtu0aYM2OTNsuLu7y10n/8243bt3o1GjRvisQ4ci09ytWzd0U2KEe/6R87a2trh48SIuX7ok/eFeLBZj9+7dOHzkCBISEtCkSRNMmTKl0IEFurq6cFi4EAAQHByM98nJBdbR19eHvr6+9POFCxeQlJQE65x8VBQ3NzeZz06Ojvimb188evQIHRR8V7Vq1ZL5fObMGejo6KBPno5eRkYGtmzZgtNnzuD9+/f45JNPMGvWLHT87DOFaWnQoAHmzZsHAAgICJC7zokTJzB50iTpEwgjR47EvzduYP++fVi5cmXRAUP583v16lXcvn0b/keOSGNv0KBBgfWOHDmCffv3Izo6GiYmJhg7ZgxGjRpV6L7n58T71tNT7k2T58+fw9fXF38eOCB9OqJhw4aC055r0MCBALJ/cBFKSDlTV77OVbt2bZVuplSWeFWp50QiEZYsXYrp06fj7p07BdKjrrIbfO8erNq1Q//+/aXb9OvbFw9CQgTFKpSQc6+u687u3btRr149ODo6SpepUl7zUyU/A6V3rv0DApCYlIRdu3ZJf/iTV2cqUpniVfZ6dOLECQwfNgx9c9qSjRo1wsOQEOzes0dmkIQ6rke5atWqJWhGH0WKahfmVx7Pa16VKT8rIqStWd7q5bxU6R9paWoWWo7K4/eRe33P9cucOfD398d///2Hzp07A8ieqnLjpk24fv06NDQ08Omnn2KevX2heUxIPemxZYv0qe9cjRo1KkY02X2svANZAODX+fMx8ccf8erVq0JviJRW/1dd5zc8PBz379/HnwcOSG/oOCxciH79++P06dP49ttv1RpXcfr18qjS/xVSN5bV/j6gfHujlbm5zAMIDRo0wPnz53Hn7l3pIAl1xSu0710YZeO9f+9edntp7FgA2eVm+PDh2JNvQFRZ7u/LU9T3UJ7aErlUKb+l2c8vifJLREREVBziknnOt0IxNjYW9JDLF198gXfv3iEoKAif5bSRAwMDIRaLpQMfhLh79y4AwMTERKl0aii1dh4tWrTA9evX8fbtW1hYWKi6G5VFR0cjISEBHXNuBgHZDePWbdrgwf37crfJzMzE49BQdOrcSbpMQ0MDHTt1UriNPE8eP0ZcXCw0qmjgxwnfw3rgANjP+RnPwoo/k4RYLMYyR0dM+P57pUa7OLu4oFu3bgozzYKFC/HmzRts3rQJe/fsQStzc8yYOROJiYnFTnOuzMxMnDh5EtbW1h9lhhGxWIwPKSmomWcwgZe3N46fOAGHhQvx54EDGPfdd1i2bBmCFAx4UZW/vz86d+6sdIHLlZzTsVPmiSP/gAD0/eYbmZH7Li4uuHf/Pn5bvRoH/vgDfb7+GrNnz0Z4eLhK6cqVmZmJavlGhOloa+NucHCx9luYS5cuobWFBfbs2YMBAwdi+IgR2LhxI9LS0qTrnDx5Elu3bcPMGTPw18GDsJ05E1u3bcOxY8eKd+zLl9GwYUP8888/sB46FEOsrbFy1aoSLR/Foe58PW78ePTr3x8zbW3Veo6FKsvxCq3nduzYgdq1a+NbOdPmA+oru1bt2uFRaKh0UERkZCSuXL2q1A3MkqKu686ly5dhYWGBBQsX4pu+fTFu/HgcPny4hFKtvNI615cuXUK7tm3h7OyMvv36YfSYMdjl5SXzFKg6VIZ4MzIzCzwZra2jg5CQEOngYHVdj3LNtbfHN337YsrUqbh48aLS2xfVLsyvMpxXeSpy3PLamuW1Xla1fxQeEYH+AwZg6NChWLJkSYF3WZbX7yNXZmYmDh8+DH19fekP5FlZWZg1ezaqV6+OHdu3Y+eOHaiuq4tZs2fLzFCnLLFYjCtXrqBpkyawmzUL3/Tti4k//ogLFy6UUDT/Lzk5GVWqVJH5wUue0ur/quv85p6fvE/laGhooFrVqtKbPUD57dcL6f8KqRvLS39fFaGPH+PevXsyA1PUFa+QvndJa9uuHV6/fo1/rlyBRCJBQkICAv/+G93yvNKzIvb3y3NbIpcq96/kqcjll4iIiIhUY2Fhgf79+2PatGm4ceMGrly5Ajs7O4wdO1Y6CDgqKgqtWrXCjRs3AGTPfLhy5UoEBQXhxYsXCAgIwA8//IAvv/wS7dq1U+r4xZpzVENDo8DT7kKkp6cjPT1dZpmy70p/k5AAoOA06bVr10bCmwS527x79w4ikUjuNuEvXwo+dnRUFABg547tmPXzHJiYmOCAz37YzfgJB/7ylfnRXlm7d++GpqamdHS9EKfPnEFoaCj27N4t9+93795FSEgIzp45I73pP2fOHFy4eBF///13saZyzOvChQtITk7GkMGDS2R/Rdm7bx9SU1PxTc7MChkZGfDy8sIWDw9pQWjUqBHuBgfj0OHD0lFIxRUXF4er165hlcAZFfITi8VYt349rKysYGZmJmibByEhCAsLw9KlS6XLXr16haPHjuHY0aPSEVkTJkzAtWvXcPToUdja2qqUPgDo0qULfPbvR4f27dGoUSPcuHkTgefPQywWq7zPokRFReFucDCqaWtj7dq1ePfuHZydnZGYmCh9UmubpyfmzJmDr776CkD20x/Pnj/HoUOHMLgY+S4qKgqvXr3Cub//xnInJ4jEYqxfvx4LFi7E1t9/L5H4VKXOfG1Upw4cHBzQ2sICGRkZOOLvDxsbG+z29karVq1KKgSllPV4hdRzd+/ehX9AAHz275f7d3WW3f79++Pdu3eYOnUqJBIJRCIRRowYgcmTJqm8T1Wo87oTFRUFPz8/jB83DpMmTcLDkBC4rluHqlWrFqseUEVpnuuoqCjcunUL/fv3x6aNGxEREQFnFxdkZWVh+rRpKu+3MJUl3i+6dMERf3/06tULrVq1wqNHj+B/5AiysrLw7t07GBkZqe16VL16dcyZMwefWlmhSpUqCAwMxLz58+G6di165sycVpSi2oX5VZbzml9FjlteW7M818uq9I8s27SBk6MjmjZtivj4eGzfvh1Tp03DnwcOQE9Pr1x/H5cvX8aixYuRlpYGIyMjeLi7S1/Jc+bMGYjFYixdskT647ajoyN69e6NoKAgdOnSRaVjvnnzBikpKfDevRszZszALDs7XLt2DfN//RVbf/+9xPpZ6enpcHN3R7++fQsdJFGa/V91nd9mzZqhfv36cPfwwCIHB+jq6mK/jw9ex8YiPufeR3nt1wvt/xZVN5aX/r6yBg4ahLdv30IkEmH6tGnSWUPUGa+QvndJ+9TKCqtWrsSiRYuQnp4OkUiEHj16YMGCBdJ1Klp/vzy3JXKpcv9KnopafomIiIio+Pbv3w87Ozt8/fXX0NDQwIgRI7B582bp3zMzM/H48WOkpKQAAKpVq4Zz585h48aN+PDhAxo3bowRI0ZgyZIlSh9bqUESW7ZswaFDh1C7dm3Y2Njg6zxTosXHx6Nz58549uxZkftZs2YNli9fLrPM0dERdnMUT516+tQprP3fGunntes3KJP0EiWWZP9QPPHHSeid03lbtHQZhg0ZjMC//8a3Am9OnDx5Er+t+f+YNm7YgAMHDmDfvn2Cn9h49eoV1q1bBw93d4UDTZ48eYLU1NQC7+NLT09HZE5ncdTo0dLlkyZNUukHNf+AAHT94gvB7wkujlOnTmH79u1Y5+oqHfQSERGBtLQ02OZ5FyGQXYDMc6axHD16NGJyniJr/+mnMgVNqGPHjkFfXx+9evVSKe3OLi4ICwvDju3bBW/j7+8PMzMzWOZMXwhkv1tHJBJh+IgRMutmZGRIBy/1yDMt+IABA7DIwUHQ8ebZ22PV6tUYOWoUqlSpgoYNG8J6yBAEHD0qOM3KEkskqFKlClatXCm9KZoxZw4WLFyIBQsWQCKRIDIyEitXrsTqPO8bF4lE0vVnz56NO7nT6tSvj4MHDwo6tkQsRkZGBpY7OaFp06YAgGVLl+L7CRPw4sUL6ZSceeUvv5tL8H3meakzXzdr1kwmNisrK0RFRmK/jw9Wrlghs25li1eRouq5Dx8+YJmjIxYvWiT9wSI/dZbdW0FB8PLywsIFC2BpaYmIiAi4rluHHTt2YOrUqYL2kZ8q516d1x2xWIzWFhbSm4qtzM0R9uwZ/JS4eVoS+bm0z7VEIoGhoSEWL1oETU1NWFhYIDYuDnv37i1wY7SyxVtcU6ZMQXxCAn7MyZO1a9fGoMGDsWfPHlSpUgWpqalqux4ZGBjg+/HjpZ/btGmDuPh47N23T9AgCSHtwrzK43llfi6avLZmWa+Xc5VE/wiAzAxKLVq0gKWlJQYPGYKz587h26FDy8X3oSivd+zYET779+Pdu3c4fOQIHBYtgreXF2rXro3//vsPkZGR+DJffZGRkYHIyEjcuXMHs3/+Wbp8kYMDBgwYUGRaJJLsuUN79uyJ8ePGAQDMzc0RfO8e/A4dEvzjVmHlNysrCwsdHCCRSLAwZ2p1eUq7/6vO87vWxQUrV67EV19/DU1NTXTu1Aldu3YFcr7/8tqvF9r/LapuLC/9fWVt9/REamoq7t+/D3cPDzRq3Bj9+/VTa7xF9b11dHRKMMJsz549g+u6dZg6dSq+6NIF8fHx2LR5M35bswbLli5Va/tKlf5+SSjPbYlcqty/kqeill8iIiIiKr7atWvDx8dH4d+bNWsmvS8BAI0bN1Zp5l15BA+S2Lx5MxwcHDBp0iQkJiZi4MCBcHJygkNOA14kEuGlwNkYHBwcMHfuXJll2traeJ+qeGq/7j16SN9vBwAZmRkAsp9qyfuu2Tdv3qBFC/nv4zQwMICmpibevHkjs/zNmzeoXbuOoLQDQJ062cdr1ry5dFm1atXQoGFDvH79StFmBXz55ZewtLSUfj537hzevH2LwXnemycSibBx0yb8ceAAjsp5F2FoaCjevHmD7ydMkNnmzp07OPjXX7h65QpSUlOzn3rcurXA9jVq1IC+vr7MU3SqTKEXExODGzduwMXFReltlXX6zBmsXLUKzv/7n8z0qqmpqQCyb6bWrVtXZpuqVasCADZt2iSdKlvZ2UuA7I5owNGjGDhwoHSfynB2ccE/ly/D09MT9erVE7RNamoqzpw5g59sbGSWp6SkQFNTE3v37IGmpqbM33JfyZH3vOrp6QlOp6GhIda5uiI9PR2JiYkwNjaGm7s7GpbQOy7lMTIygrGxscxTY82bN4dEIkFsbKw0/UsWL5YpN0D2rDYAsGTJEuksNbnv5RR6bE1NTekNEwDSGyWvXr+We9Mkf/lV1+Cgj5Gv82rTpo3cV1BUtnjlEVLPRUZGIjo6GnPt7aXLcmdg+bxLF/j5+qq17G7duhUDBw6UPoFmZmaG1NRUrP7tN0yePFlaVpShyrlX53XHyMgIzU1NZZY1b9YMgYGBgvdREvm5tM+1UZ060NLSktlv82bNkJCQgMzMTJlrVGWLt7h0dHTgmPOe+4SEBBgZGeHw4cPQ09ODoaEh3r59C0A91yN5LNu0wb///itoXSHtwrzfYXk8r8zPhVPU1izr9XKukugfyVOjRg00bdIEkRERAMrH96Eor+vq6qJx48Zo3Lgx2rZti2HDh8Pf3x+TJk1CSmoqWrVqJfcJWkNDQ2hpacnElX+GRUVy+9HN8/R/gey2et5XQagaU+4AiVevXuH3LVsKnUWitPu/6jy/Ojo68PHxQXJyMjIzM2FoaIiJP/6I1jmvNy2P/Xpl+r9F1Y3lob+vioYNGwLIbrcnvHkDT09P9O/XT63xFtX3btKkSbFiksfL2xtWVlb4IafstmjRArq6upg6bRpmzpghHQhXVvr7JaG8tiVyqXL/SpGKWn6JiIiIqHwT3KvYtm0btm/fjnE5T47MmDED3377LVJTU7FC4BO4ubS1teU2eAsbJKGnpyfTYZBIJKhTpw6Cbt6UvoP1Q3IyHoaEYNjwEXL3UbVqVZi3aoVbN2/iy569AGTfEA26eQsjRo0SnP5WrVqhWrVqCA9/CatPPwWQfWMnJjoG9esLf+dd/piGDRuGHj16yKwza/ZsDBwwAEPy3BjMq1OnTjjwxx8yy1asWIGmzZph4g8/QFNTE61atUJCQgI0NTWl73DJr3HjxoLTLU/A0aMwNDREdzW/9/7U6dPSJwu6d+8u87fmzZujWrVqePX6tcKnmYr7TsKg27cRERGBodbWSm0nkUjgsnYtLly4gG1bt0pvhAhx7tw5ZGZmFnjKy9zcHCKRCG/fvlX4BGVxz6u2tjbq1q2LrKwsBAYGSl9tog5W7drh3LlzSElJQfXq1QEAL8PDoaGhgbp160JHRwfGxsaIiopS+MRb/s624GNbWUEkEiEyMhKNGjUCAOk7Qk3q15e7Tf7yqy4fI1/n9fjJExjVKThorLLFK4+Qeq5Zs2YF6uTft25FyocPsLe3R7169SASidRWdtPS0lAl30AIjZwbZ3lHWypDlXOvzuuOlZVVgUGZL8PDFZZVeUoiP5f2ubayssKp06chFoulN47Dw8NhZGRU4KZgZYu3pGhpaUlvCJ85cwbdu3eHhoYG6tSpo7brkTxPnjyRGRBcGCHtwrzK43llfpavqLZmWa+Xc5VE/0ielJQUREZFYWBOWSoP34fQvC4Wi5GRmQkge1aDs2fPwtDQUOFAA1Xiqlq1Ktq0bl0grvDwcKXaZfJiyh0gER4ejm1btyqc3SVXafd/P8b5zT134eHhePToEWb89BMA9ebbXCXVr1el/1tU3ViW+/slRSIWIzOnPKsz3qL63uqQlpYGrXztkNzzLJFIpAM3ykp/vySo856NOtvGxbl/pUhlKL9ERERUeal6351Kn+BBEs+fP8+e6jFH165dERgYiD59+iAzMxNz5sxRR/oUqlKlCkaPHYvdXrvQqHFjNGjQANu3bYWRkRF65JledLbtTHzZqxdGjsqednLMd+OwesVytLKwQOvWbXDwwAGkpaViUJ6pMRMS4pGQ8AaRkdlPGoU9fYrqenqoX68eataqBT19fQwdNhw7Pbejbt16qG9iAp99ewEAvfO8gkRZBgYGBW4KaWlpoU6dOjIj22fMmIFevXtjzOjR0NPTK/BeQB1dXRjUqiVd/nnnzmjbti3mzZuH2bNno0mTJoiLi8M/V66gd69eaN26tdz0ZGZmSl+fkpmZibi4ODx+/BjVq1eX6ciJxWIcPXoUgwcNUmo0f0pKCiJynuYCgKjoaDx+/Bi1atXKfh+ruzti4+KwIufVLKdOnYKjkxPm2dvDsk0bxMfHZ8erowN9fX3o6enh+++/x/r16yERi/Hpp58iOTkZd4ODoa+nV+j0p8+ePUNmZiYSk5KQkpKCx48fA4B02r9c/v7+sLS0VPpdjM7Ozjh1+jTWubqievXq0rTr6+tLp7Jc5uiIusbGsMs3/aB/QAB69uxZIG80bdoUA/r3h6OTE+b8/DPMzc3x9t073LxxAy1atCgwiCSv3PhSU1Px9u1bPH78GFWrVoVpzlNRDx48QGxsLFq2bIm4uDh4enpCIhbjhx9+EByzsue3f//+2LlzJ5avWAGb6dPx7t07bN68GdZDhki/I5vp07HW1RX6+vr44osvkJmZiYcPHyLp/XuZ6cnzi4iIQEpKChISEpCWni6N39TUFFWrVkXnzp3RqlUrrFixAnPt7SERi+Hs4oLPP/9c5mmToiQmJuLVq1eIyzm/uTdQ69SpI/2BK/95LqqcqTNf+/j4oEHDhvjE1BTp6enw9/fHrVu34O7mxnjzKayeyxujtrZ2gfqhRs6N7tzl6iy7PXr0gI+PD8zNzWHZpg0iIiOxdetWfNmjR4EfR4ujqHOvzuvOuO++w+QpU7DLywvf9OmDkJAQHD58GIsXLVJrTEDZOtcjRozAwb/+guu6dRgzejQiIiLg5e2NMWPGMN58lL0evXz5EiEhIbC0tETS+/fYv38/wp49g5OTk3Qf6roeHTt2DFpVq6JVTr0VeP48Ao4exZLFi4uME4CgdmFFOa95Vab8rEhRbc3yWC8DqvWPAGDjxo3o0aMHTExMEBcXh22entDQ0EC/fv0AqLd/pK7vIzU1Fbt27cKXX34JIyMjvHv3Dgf/+gtxcXHok9MHHTBgAPbu2wf7efPwk40N6tati5hXr3D+/Hn8MGGCwieBi6onAWDChAlwWLQIHXJe+XH12jVcvnxZ7qwGQmVlZeHXBQvwODQUGzZsgEgkkubdWrVqSX/oK0v9X3Xm93PnzsHA0BD169XD07AwrFu3Dj179kSXLl3UHheger9eHlX6v0XVjWW5vw8o3944ePAg6tevL63Lbt+5g33793+UeIX0vUs63i979MCq1avh6+uLLl26ID4hAevXrUObNm2ks8qU9f6+st9DeWtL5FKl/JZmPz9XccovEREREVVOVSQCh7g0adIE+/fvL/Akz8OHD/HVV1+hX79+2LdvH0QikcqJiX+XqNT6EokEOzw9EXDkMJKTk9HOygr2v/6KJk3+v5Mz4tuhGDhoEKZMmy5d5vvXQfjs24c3CQlo0bIl5sy1R5s80/nt3O6JXTt2FDjeoqXLpIMpsrKysNXDA6dOnkR6ejpaW7bBz7/8AlPTTwSl3cigFt4nJRW53hBra3w3dqx0Bo/cZYMHD4bN9Olyt5luYwPzli1hn2cK4Q8fPmDL778jMDAQb9++RZ06ddChfXvY2tpKb3zlFx0dDeuhQwss79ChAzy3bZN+vn79OuxmzYKfr6/CDmaNmjULxHsrKAg/5TwVk9fgQYPg5OQEJycnRMfESI813cYGt2/fVrg+kJ0nDhw4AF8/P0RFRaFGjRpoZW6OSZMmoUOHDnLTBmR/pzExMQWW37p5U/r/ycnJ6Ne/P+bZ22PYsGEK9yUv3o6dOsldz3HZMulTcNNtbNDAxETmR5gXL15g5KhRcHd3R5c8rxbJlZWVhZ07d+L4iROIjY2FgYEB2lpawsbGptCOobz0mJiYSKcsDgoKwv+cnREVFQVdXV1069YNs+zsFE5pXRLnNzdel7VrERwcDINatdCnTx/MmDFD5kbNqVOnsGfvXjx//hy6urow++QTfPfdd+jdu7fCeBXlnQB/f+lTWHFxcXBZuxb//vsvdHV00LVrV8yZM0f6rtCi4gWAo0ePYrmcmXWmTZsmLa/5z7OQcqaufL17zx4cPnwYcXFx0NHRgZmZGaZNnYqOHTsy3nzxFlbPySu7eTk5OeF9cjLWubpKl6mr7GZlZWGXlxdOnDiBuLg4GBgY4MsePTBz5kzUqFFD7j4Vnd/CCDn36rzuXL58Ge4eHoiIiECDBg0wfty4IuvlXCWZn/P7mOcaAO7du4f1GzbgyZMnMDY2xtChQwvMFsB4lb8ePX/+HIuXLMHLly+hpaWFjh07YpadXYGpmNVxPTp27Bh279mDmJgYaGpqolmzZpgwYYL0B9D8hJTf/O3C8nhei4q3MuVnZY4JyLY1y2q9nEtovEL6Rw6LFuHOnTtITEyEoaEhrKysYDtzpvQJYqD0vw9lr7/p6elYsmQJHoSE4N27d6hVqxZat26NKZMny7yWMj4+Hm7u7rhy5QpSUlJgbGyMzp064eeff1Y4u0RR9WQu/4AAeHt7IzY2Fk2bNMF0Gxv0yvOAQmHkxavo+wSyXyHWMedp47LW/1XH+QWAAwcOYO/evUjIeaXooIEDMXXqVJmnwku7X69ISfV/i6oby2p/H1C+vXHgzz9x6NAhREdHQ1NTE40aNcKwb7/F8OHDZWZYUFe8QvreJRmvNGY/P0RFR6NGjRro1LEjZs2aJTNDRFnu78tT1PdQ2m0JIUqi/JZmPx9QvvwSERERlaR+q1V/eKA8Ob24YLu3vBM8SGLcuHGoV68eNmzYUOBvISEh6N27NxISEj7qIInyTOggiYpClZtE5RnjrdgYb8XGeCs2xluxMd6KjfFWbIy3YmO8FRvjrdgYb8VWGeMlIiIiKkkcJFF+CZ5D0cHBAUFBQXL/1qZNGwQGBsLPz6/EEkZERERERERERERERERERFQWCZyLgMogwYMkrKys0KlTJ2RmZmLs2LEFpu22tLSEZZ5XVhARERERERERERERERERERGVJRpCV7x48SIsLS1hb28PExMTTJw4EZcvX1Zn2oiIiIiIiIiIiIiIiIiIiIhKjOBBEj169MDOnTsRExMDNzc3vHjxAj179kTLli3h7OyMV69eqTOdRERERERERERERERERERERMUieJBELj09PUyaNAkXL17EkydPMGrUKHh4eKBJkyawtrZWRxqJiIiIiIiIiIiIiIiIiIiIik2rOBubmZlh0aJFaNq0KRwcHHD8+PGSShcREREREREREREREREREVGZJJZISjsJpCKVB0lcunQJu3btgp+fHzQ0NDB69GhMmTKlJNNGREREREREREREREREREREVGKUGiQRHR0Nb29veHt74+nTp+jatSs2b96M0aNHQ09PT11pJCIiIiIiIiIiIiIiIiIiIio2wYMkBgwYgHPnzsHIyAg//PADJk+eDHNzc3WmjYiIiIiIiIiIiIiIiIiIiKjECB4kUbVqVfj6+mLw4MHQ1NRUZ5qIiIiIiIiIiIiIiIiIiIiISpzgQRIBAQHqTAcRERERERERERERERERERGRWmmUdgKIiIiIiIiIiIiIiIiIiIiIPgYOkiAiIiIiIiIiIiIiIiIiIqJKgYMkiIiIiIiIiIiIiIiIiIiIqFLQKu0EEBERERERERERERERERERlScSSWmngFTFmSSIiIiIiIiIiIiIiIiIiIioUuAgCSIiIiIiIiIiIiIiIiIiIqoUOEiCiIiIiIiIiIiIiIiIiIiIKgWt0k4AERERERERERERERERERFReSKWSEo7CaQiziRBRERERERERERERERERERElQIHSRAREREREREREREREREREVGlwEESREREREREREREREREREREVClwkAQRERERERERERERERERERFVClqlnQAiIiIiIiIiIiIiIiIiIqLyRCKRlHYSSEVVJDx7REREREREREREREREREREgvVyci/tJHwUF5zsSjsJJa5MzSSx98KN0k7CRzOhV2e8T0oq7WR8NDVq1mS8FRjjrdgYb8XGeCs2xluxMd6KjfFWbIy3YmO8FRvjrdgYb8VWGeMlIiIiIvk0SjsBRERERERERERERERERERERB8DB0kQERERERERERERERERERFRpcBBEkRERERERERERERERERERFQpcJAEERERERERERERERERERERVQocJEFERERERERERERERERERESVAgdJEBERERERERERERERERERUaWgVdoJICIiIiIiIiIiIiIiIiIiKk8uONmVdhJIRZxJgoiIiIiIiIiIiIiIiIiIiCoFDpIgIiIiIiIiIiIiIiIiIiKiSoGDJIiIiIiIiIiIiIiIiIiIiKhS4CAJIiIiIiIiIiIiIiIiIiIiqhQ4SIKIiIiIiIiIiIiIiIiIiIgqBQ6SICIiIiIiIiIiIiIiIiIiokqBgySIiIiIiIiIiIiIiIiIiIioUuAgCSIiIiIiIiIiIiIiIiIiIqoUOEiCiIiIiIiIiIiIiIiIiIiIKgUOkiAiIiIiIiIiIiIiIiIiIqJKgYMkiIiIiIiIiIiIiIiIiIiIqFLgIAkiIiIiIiIiIiIiIiIiIiKqFAQPkoiNjZX5fPfuXUycOBHdunXDyJEjceHChZJOGxEREREREREREREREREREVGJETxIwsTERDpQ4urVq+jcuTNevnyJbt26ISkpCd988w0uXbqktoQSERERERERERERERERERERFYeW0BUlEon0/52cnDBhwgTs3LlTumzOnDlYvnw5/v7775JNIREREREREREREREREREREVEJEDyTRF4PHjzAtGnTZJZNmzYN9+7dK5FEEREREREREREREREREREREZU0wTNJAMD79++ho6MDHR0daGtry/xNR0cHKSkpJZo4VUgkElw8egh3L59HWmoKGn3SEgPH/Yja9eor3ObKyQCE3rmFhFcx0KpWFY1MW+Dr4WNRp76JdJ3j+3bh+aMQJCe+RTVtHTT6pAW+Gj4GRvUblGj6ExIS4Obmhuv//ov379+jQ/v2mD9/Ppo0aVLodu/fv8eWLVsQeP48kpKSYGJigrlz56J7t24qpyU9PR1r1qzBo9BQvHjxAt27d8c6V9cC62VkZGD7jh04efIkEhISYGRkhKlTp2KotbVSx/ttzRocOnQIc3/5BePGjVO43jZPT2zfvl1mWdOmTeHn66vU8fILCwvD1m3bEBoaipiYGIXpiI2NhZubG65eu4a0tDQ0atQIjsuWoXXr1kUeIzAwEH6HDiE0NBSJiYnYv28fzM3NSyRdyhJyfm8FBeGnn34qsO2pkydhZGRU6P6V/Z7i4+OxYeNGPHr0CBERERg7Zgzs7e1VDzCPta6uCA4ORlhYGJo3awYfH58C60gkEuzbtw+HjxxBTEwMDAwMMHLkSEyZPFnp43l7e8PdwwPfjR1baAw+Pj7w9fPD69evYVCrFr76+mvY2doWqF+V8bHLLSA83vJeT23z9MSZM2fw+vVrVK1aFRatWmHmzJmwtLRUuM3t27exd+9ePAoNRXx8PFzXrkWvXr1UCVWG0PJSUt+50Pp5iLU1YmJiCiwfNXIkFixYoNQx81J3/azKdidPnsSevXsRHh4OfX19dO3aFT/Png0DAwOV4wQ+Tn2VlZWFLb//jitXriAqKgr6+vro3LkzZtnZwdjYWOF2IpEInp6eOHnqlLQcDRk8GFOmTEGVKlVUjvlj5GcnJyccO35cZtkXXbrAzc2t0O2Kc81XpKzGW17LL6BavOW5PZmSkgI3d3dcvHgRiYmJaNCgAcaMGYORI0Yo3Obo0aNYvmKFzLJq1arh6pUrygeZhzrzs6+vL3z9/KT50tTUFFOnTEE3BdscPnwYx0+cQFhYGABkX6dtbWHZpk2ZjVEeVfoLgYGB8PL2RkREBLKystCkcWOM//57DBo4UKlj5yckdlXzlpeXF86fP48XL19CW1sb7dq1wyw7OzRr1kzhNtNtbHD79u0Cy7t164ZNGzcKjiu/j32Onz9/js1ubrh9+zZEIhFMmzeHi4sL6tdXfM+itNrR8upXADBt3hwHDx4sdP8fPnzA1q1bcf7CBbx9+xbmLVvC3t4ebQopkyXZR8nrY7SvitPuvxscDBsbG3xiaio3bcr4mP0jVeqrilKO81O1rVkUoflKlXqlKKq0N0rzWqyOvKWO/rw6r61EREREpBylBkm0bNkSQHbn8datW2jfvr30byEhIWjQoGQHDKji2unjuBl4BtY/ToeBkTEuBvjBZ7MLfnL6H7SqVpO7zcsnoejYqw8aNDOFWCTC+SN/Yf8mZ/zk9D9U09YBAJg0aQbLzl1Rq3YdpKZ8wKWjh+Cz0QV2v62HhoZKE3IUIJFIMG/+fGhpaWGdqyv09PSw38cHM21t8dfBg9DV1ZW7XWZmJmxtbWFYuzacnZ1R19gYMTExqFGjRrHSIxaLoa2jg7FjxiAwMFDhegsdHPDmzRssXbIEjRs3Rnx8PMR5Xs8ixPnz5/Hg/v1Cf5zJy9TUFFs8PKSftbSUyspypaWloVHDhujTpw/Wr18vd52kpCRMmToVHT/7DJs2bYKhgQEiIiJQs2ZNQcdITUvDp1ZW+KZPH6xavbrE0qUKoecXAPx8faGnpyf9XLt27ULXV+V7ysjIgKGBASZPnlzsG0PyWA8ZggchIXj6339y/+66bh2uX7+On2fPhpmZGZKSkpCYlKT0cUJCQnDo8GG0aNGi0PVOnToFdw8PLFu6FO3atUN4eDicli9HlSpVMPeXX5Q+bq6PWW4B4fFWhHqqaZMm+HX+fDRs2BDp6enw+eMP2NrZ4cjhwzA0NJS7TWpqKlq0bAlra2vM//VXpY5XGCHlpaS+c2Xq5z27d0MkEkk/h4WFwdbODl/36aPUMfNTZ/2synZ3g4Ph6OSEub/8gh49eiAuLg6/rVmD1atXY+3atcWKFVB/fZWWlobQ0FBMnTIFLVq0wPv37+G6bh3m2ttj7549CrfbvWcPfP38sPz/2LvzuJry/w/gLyWViqKQkCWypGbBkDHGjCGGLDOMYYyxZokxliFrYsbPvhVhqGyDKSlGxGQby4zJOiEjSzsVStpv9/eH7v3eW/d2z711udXr+Xh4PNzTOfec9/l8zmc593M+x9MTzZs3x+07d+Dl5QVTU1MMGzZM7Tgl3lR+du7SBYsWLZJ+rlFDcbtQoqx1vjK6Gm9FvH5lqRsvUHHbk+vWrcOVf/6Bl5cXGlpb4/Lly1ixciWsLC3RvXt3pduZmJjIDQIpy+AmCW3m53r16sHd3R1NGjeGWCzG0d9/x8xZs7B3zx60aNGixPqRkZHo3asXHB0dYWhoiICAALi7u+PggQOoV6+eTsaoiCb9hVq1a2PM6NFo2rQpDAwMcP78eXh5eaGOhQW6dOmi9jFICG2fa5K3rl69iiFDhqBt27YQiUTw2bwZ7lOnltrvXbVyJfLz86Wf09PTMXzECPT89FM1oirpTaZxfHw8xo0fD1dXV7i5ucHUxAQxMTGllllvsx09a9YsuLu7Sz+LRCIMHzFCUN2wbNkyxMTEwGvJElhZWeFYWJj03oaya7K8+iiKaLt9pWm7/+XLl1i8eDE6duyIZ2lpgrdT5k32jzQpryrDdayMJm0RVYTkK03KFSE0aW+8zbpYG3lLG/15bdatRERERKQewXcCT58+LffZ2tpa7vPDhw8xYcKE8jkqDYnFYvz9x3F82NcV9u+8DwBwHe2GdbPcEX09Eu06Kr5BNPx7+YZu/+8mYN2sKUh6/Ai2rVoDAN776BPp381hhY8HfIntS+fjRVoK6ljVL5fjj42Nxa1bt3Bg/37pjT+PuXPR28UFJ06cwMCBAxVuFxIaivSMDOzcuVN6c7f4gJXCwkIEBAQg+PBhpKWloUmTJhg7dmypnQVjY2N4zJ0LALhx4wZeZmaWWOfixYu4evUqQg4fRu3atRXuW5WnT59i1erV2LRxI6YL/HG4ur5+qTMZvHz5Eus3bMDZs2eRn5+PNm3aYMYPP0gH+ijSrl076VMt3t7eCtcJCAhA/fr1sXjxYukyGxsbQccMQPo0V2JiouBthByXttJXok6dOmrdONDkPDVs2BCzZs0CAISGhipd7/Dhw9izdy8SExNhbW2NYV99hSFDhpT63bOLvvf5tm0Kb4o9fPgQgYGBOLB/v/TpNXXSVSIrKwsLFy3C/HnzsGPnzlLXvXHzJpwcHeHi4gLgdfy9e/XCv1FR0nV0+bpVN96KXk4BkKaVxA/TpyMkJAT//fcfOnXqpHCbrl27Kn3iVSIvLw+bN2/GifBwvHz5Ei1atMDUqVPR4f33lW4j5HoRcs5VUbd8Lj5YJCAgAI0aNcL7770nXaZr5bMm2926efN1+VM0MMDGxgaDBw/GrmIDDHS1vDI1NZX7YRgAfpw9G6O++w7JyclKnzi7efMmunfvjg8//BDA6/x04sQJRMmUW7qcnw1q1FA5C5IsIXmjMsVbEa9fWerGC1Tc9uSNmzfR7/PPpfls8ODBOBQcjKjbt0sdJFGtWrVS49W1/PzRRx/JfZ4yeTKCgoJw699/FQ6SWLZsmdznBQsWIOL0afx95Qr6ff65TsaoiCb9heLH//XXX+Po77/j+vXr0kES2oodUJ23FCn+dLXn4sX4rFcv3LlzB+/JlDuyJO04ifDwcBgZGaGnzA/2up7GPps3S2efkmjUqFGp27zNdrSpqSlMTU2ln8+cOYOMjAy49u9f6jHn5OQg4vRprFm9WpqebhMm4Pz58wgMCsLkSZNKbCO0za6r7Ssh7X5Ffl6+HC69e0NPXx9nz5yR+5uu9480Ka8qw3WsjKq2SHJyMtZv2IDLly9DT08P77zzDmbNnFnqMQjJV5qUK0Jo0t54m3WxkLylLlXnX9fqViIiIiJSj+BBEqXdcAOA77//vswHU1YvUlOQmZGOZm3+N/W5kXFN2DRrjvgH95UOkiguNzsbAGAs8+S8rLzcHNy4eA7mllaobVG37AdeRDLiWXaqfT09PdQwMMD169eVDpI4d+4cHNu3x4oVK3D23DmYm5vDxcUFo779Fvr6+gAAP39/hIWFwWPuXDRu3BjXrl3DokWLYGFujvdLabyrcu7cObRt0wa7du3CsbAwGBsb46Nu3TBx4kQYGRmp3L6wsBCLFi/GyG++UXizU5nYuDi49OkDwxo10L59e7i7u8v9qDNn7lwYGhpi44YNMDU1xaFDhzBp8mQcCgoq0XFSx7nz59G5c2fMmTsXV69ehZWVFYZ8+SUGDRqk8XeWB22lr8TwESOQl5eHFi1aYMKECXjHyanU9bV1nsLCwuC7dSt+nD0b9vb2iI6Oxk8//wxjY2P069dP4+89d/48bGxs8Oeff2La999DLBajU6dOmDZ1qlr5ZcXKlejatSs++OADlYMGnBwdERYWhn+jouDQrh3i4+Nx4eJF9JWZFllXr1tN4q3I5ZQi+fn5CA4Ohqmpaak/lgmxcuVKPHj4ED//9BOsrKxw+vRpTJs2Dft//VXlq5ZKI+Scl0bT8lkiPz8fx8LCMGLECLmnXnStfNZku/aOjvDZvBl/XriArs7OePbsGSL++ANdnZ2l6+h6eVVcZmYmqlWrJvdDSHGOjo4IDg7G48ePYWtri3v37uHGjRv4Yfp06Tq6mp+B10+2fdarF8zMzNCxY0dMmjix1NejCMkblSleWRXl+pWlSbwVtT3p5OiIc+fOwdXVFVZWVoiMjERsbKzKmaiys7PRr39/iAsLYd+6NaZMnixXvutyfhaJRDj1xx/Izs6GY/v2grbJyclBQUEBasvM0KHLMZYXsViMK1eu4PHjx5g6dap0ubZiB1TnLSEyi37IVWcGmZDQUPT67DO5mSd0OY0LCwtx4cIFfDtyJNynTkV0dDQaNmyI0d99V+r07W+zHV1cSEgIOnXqVOKhmeJEIhFEIlGJJ9kNDQ1x/fp1hdsIabNXtPaVKqGhoUhISMBSLy+F/amK1D/SVEW7jktTWlukoKAAU6dNQ/v27fHL9u3Q19fHjh07MLUoLgMDA432qWm5IoSm7Q1Zb7IuLk5R3ipvul63EhEREVHpyj6nrAZyc3ORm5srt0x2YICmMjNeAABMasl3Yk1q1car9HRB3yEuLET4wT1o1KIV6tk0lvvbP2dO4Y9D+5Gfm4u69a0xfPoc6JfDtLwSTZs2RYMGDeDt44N5Hh4wNjbG3n378OTpU6SWMu1iQkIC/vnnH7i4uGDD+vWIi4vDipUrUVBQgAnjxyMvLw9+fn7Y7OMDR0dHAK9HlV+/cQOHgoPL1LlOSEjA9Rs3UMPQEKtWrcKLFy+wYsUKpKenyz0dp0xAQAD09fXVmqbboV07eC5eDFtbW6SmpmL79u0YN348DuzfDxMTE1y/fh1RUVE4GR4uvSkzffp0nDl7Fn/88QcGDx5cpniDgoIwYvhwjB49GrejorB6zRoYGBiU6aZMWWgzfS3r1oWHhwfatmmDvLw8HA4JgZubGwL8/dG6dWul22nrPG3dtg3Tp0/HJ5+8ntnFxsYGDx4+xKFDh8r0vQkJCUhOTsapP/7AEk9PiAoLsXbtWsyZOxe+W7YI+o4T4eG4e/cudgUECFrfxcUFL168wLhx4yAWiyESifDFF19gzOjRALSbrmW9bgH1463I5ZSs8+fPY978+cjJyYGlpSV8vL0F/+ioSHJyMo4cPYqjR45IX2cxcuRIXLp0CUeOHMGUKVM0/m5V51wVTcpnWWfOnEFmZib6y1ybulg+a7LdO05OWLZ0KebNm4fc3FyIRCJ069YNc+bMka6jy+VVcbm5udjk7Y3evXqVOkjiu1Gj8CozE18OGQI9PT0UFhZi8qRJ6NOnDwDdzs9dnJ3Ro0cP2NjYID4+Hj6bN2Pa99/Db+dOpTfFVeWNyhavrIpy/ZYl3orcnpw9ezZ++vln9P38c+jr60NPTw/z589X+vQ9ANja2mLhwoVoaWeHzMxM7NmzB2PGjsXBAwdQv359nc3P9+/fx+gxY5CXlwdjY2OsWrUKzZs3F7TfTZs2wdLSUjrbk67GWF4yMzPRp29f5OXlQV9fH3PmzEHnDz4AoN3YVeUtIQoLC7Fm7Vo4OTnBzs5O0Db/RkUhJiYGCxculC7T9TR+9uwZsrKy4B8QgEmTJmGquzsuXbqE2T/+CN8tW5S2d99mO1pWSkoKLl66hGVLl6pc18TEBI7t2+OXHTvQrFkz1KlTBydOnMCtW7eUPuEupM1ekdpXqsTGxsLbxwfbt21T+LqnitI/KouKeB0ro6otEh4ejsLCQixcsEA6AHXx4sX4uEcPREZGonPnzhrtV9NyRQhN2hvFvcm6WJaivFXedL1uJSIiIiLV1PqFf/PmzTh06BDq1KkDNzc3fCozxV9qaio6deqEBw8eqPye5cuXY8mSJXLLFi9ejBYf91WyhWK3/rqAY3v9pJ+Huc9Ua3tFwn4NQEpiPEbNLtmQdvjAGc3bOOBl+gtcPnkMh7Z547sfF6K6gWbv+QsLC8PPy5dLP2/csAGrVq7E0qVL8cmnn0JfXx+dOnaEs7MzUMq7IcViMSwsLDB/3jzo6+ujTZs2eJqSgt27d2PC+PGIi4tDTk4Opsi8SxR4/ZSgvb09AGDo0KFISk4GALz7zjvYuHGjoBgKxWJUq1YNy5Yulf6wkjd9OubMnYs5c+bIPYVQPN7169Zh//792LNnj1rv1pOd6q5ly5ZwcHBAv/79cfLUKQwcMAD37t1DdnZ2ifek5ubmIr7o5seQoUOly0ePHi39YVplvIWFaNumjbSz09reHjEPHiBIwU0ZRen77rvvCo5TKG2mb9OmTaXTjQKAk5MTEuLjsXffPiz18lK6nTrnSajs7GzEx8dj6dKl+EnmfacikUia96ZNm4ZrRU8mWTdogIMHDwr6bnFhIfLy8rDE0xO2trYAgEULF+KbkSPx6NEjuXOgSHJyMtasWQMfb2/BA77+iYyEn58f5s6ZAwcHB8TFxWH1mjX45ZdfMG7cOJ25bssr3opSTkkou347dOiAfXv34sWLFwg+fBge8+bB388PderUEXQsxd2/fx8ikQiDv/hCbnleXp70qbVuMtON9+nTB/M8PAR9t6pzXlq8mpbPskJCQ+HcpYv0hhEAnSmfy7rdgwcPsHrNGowbNw5dOndGamoqNmzciJ+XL8eihQt1rrwqrT4qKCjAXA8PiMVizC2amlmZk6dO4fjx41i2bBlaNG+O6Hv3sHbtWlhZWaFfv346m583btiA3r16ST/b2dnBzs4OAwcNQmRkpNLX5ajKG5UtXlm6fP2WV7wVuT3577//4tatW1i7Zg2sra1x9do1rCx6R/gHRT+KF+fo6Cj9kQ143ab7csiQ17NjTJqkM/m5OFtbW+zbuxeZmZn4448/4OnpiW1bt6ocKOHv74/wkyex1ddX2lbRxRjLs79Qs2ZN7Nu7F1lZWbhy5QrWrVsHGxsbdHj/fa3GripvCbFi5UrExMTgl+3bBa0PvJ7RwM7ODg5Fr7cBdC+NFbWvgNezdI4YPhwAYG9vjxs3byLo0CGlP2a+zXa0rKNHj8LU1FTw0+leXl7w8vJCn759oa+vD3t7e/Tu1Qt37t5VuL6qNrtYLNap9lVZiEQiLFiwABMmTJDur7iK0j8qi4pwHSuiSVvkv//+Q3x8PD4qNktvXl4e4uPjce3aNUyTmaF3noeHdCCyqpgA9csVITFp0t6Q9abrYlmK8lZ50/W6lYiIiIhUEzxIYuPGjfDw8MDo0aORnp6Ovn37wtPTEx5FDTyRSITHjx8L+i4PDw/MmDFDbpmhoSEOXrqhxqEDrZzeg02z/z1pIip4/bqKVxnpMKttLl3+KiMd9Rsr7njKOv5rAP67dR3fzpqPWhYlf/AyMq4JI+OaqFO/ARo1t8PqH9xw91okHDoJe41HcR999BEcHP73ahArKysYGRlh3759yMzMRH5+PiwsLDDqu+/Qtk0bpd9jWbcuqlevLvekXLOmTZGWlob8/HxkF70+ZP26dahXr57ctpIp/TZs2ICCggIA6s3qYWlpCSsrK7knT5s1awaxWIynT5/KTS9XPN5Tp07h2fPn6CfzPlORSIT1Gzbg1/37caSUd/PJMjMzg22TJoiPiwMAZGVnw9LSElt9fRWua2pqin1790qXqTOlq6WlJZoVuynbrGlTRERElFhXUfpqgzbTV5F27drh+o3Sr1V1zpNQWVlZAIAF8+fLnVfg9WtpgNfvu5TMUqPoaZzSjldfX1/uBpXkRljykycqb4rdvXsXz549wzcjR0qXiUQiXLt2DQd/+w0XL1wo8SSrr68v+vbtK32Njp2dHbKzs/HTzz9jzJgxOnPdlle8FaWcklB2/RobG6Nx48Zo3Lgx2rdvj0GDByMkJASjBf4wVlxWVhb09fWxe9euEudMMi2obHllouQ1UIqoOueyU7qWd/mclJSEv//+GytXrpSPV0fK57Ju5+fvDycnJ3xbdA20bNkSxsbGGDd+PCZPmiQdWKIr5ZWy/CwZIJGcnIwtmzeXOosE8Ppm6ahRo6Q3ge3s7JCUlAQ/f3/069dPZ/Ozovq3UaNGMDc3R1x8vNIf0VXljcoWr4SuX7/lHa9ERWpPTpo8GatXrcKHH34I4HUZdO/ePezZs0fQjxbA63LH3t4ecfHxAHQnPxdnYGCAxo1fz+7Xpk3A3B1WAAEAAElEQVQb3L59G7/u34/58+Yp3Wb37t3wDwjAZh8ftGzZUrpcF2Msz/6Cnp6e9FzZ29vj4aNH8Pf3R4f339dq7MUVz1uqrFi5En+eP49t27YJfjo2Ozsb4eHhmOjmJrdc19K4ePpaWFhAX18fzZo1k1uvWbNmSl9BIWTfb6I/KBaLEXrkCPr27Sv4tQCNGjXCtm3bkJ2djVevXsHS0hIeHh6wsbFRHKeKNrskvXSlfVUWWVlZuH3nDqLv3cOqVasAvB5AJxaL8UHnzvDetEmaZ3W9f6SpinIdK6JJWyQrOxutW7dWOBOLhYUFqlevLheX0EH45ubmGpUrxZV3e+Nt1MUSyvJWedPlupWIiIiIhBHca9y6dSu2b9+O4UUjkydNmoSBAwciOzsbXqU8Ua6IoaFhubxew9DIGIZG/3u3nFgshmmt2nh0NwoNigZF5GZnI+HhA7zf/VNlXwOxWIwT+3ch+nokRs6YBwvLekrXld1GLP7fwAxNmJiYKG0kSzqrsbGxuHPnDiZNnKj0e5ycnHD8xAkUFhZKbw7ExsbC0tISBgYGaNasGWrUqIHkJ0+UjiJX9U5Rpft2dMSpU6eQlZWFmjVrAgAex8ZCT0+vREe+eLyDBg1Ct27d5NaZOm0a+vbpg/4yP8ypkpWVhfiEBPS1tAQAtG7dGmlpadDX10fDhg0VbiO5gaguJyenEoOBHsfGwlrm/dUSpaVvedJm+ioSfe8eLOvWLXUddc6TUHXr1oWVlRUSEhKUPlFRPM8J5eTkBJFIhPj4eOn0r7GxsQAg6Jg7duyI/b/+KrfMy8sLtk2bKn2/aU5ODqoVXa8SekXricVinbluFdEk3opSTkkIvX4LCwuRl695PWBvbw+RSITnz58rfRKrLOVVaedcVnmXz6FHjsDCwgIfyjypDehO+VzW7XJyclC9WD6XnGOxWCy98awr5ZWi/CwZIBEbG4utvr6CXhuTk5srjVNCX09P+gSbruZnRZ48eYL09PRS6zNVeaOyxSuh69dveccrUVHak5mZmSgoKCgxy4+enh4KS5l5rjiRSIT79+9LZ9TQlfysSqFYjPy8PKV/D9i1Czt37oT3pk1o27at3N90MUZt9hcKi56MB7Qbe3HF85YyYrEYK1etwpkzZ7DV11fpD+eKnDp1Cvn5+SXqWF1LY0Xp265t2xLXf2xsbKnt3LfZjpaIvHoVcXFxGODqqva2xsbGMDY2RkZGBi5dvoxpU6cqXE9Vm93IyEin2ldlYWJiUqI/FRgYiCv//IMV//d/sLGxQWFhYYXsHwlVUa5jRTRpi7S2t8fJkydhYWGhdGCyJnEZGBhoVK4UV57tjbdVF0soy1vlTRfrViIiIiJSj57qVV57+PDh69c+FHF2dkZERAS2bdsmnU3ibatWrRo6feqCP4+F4N6Nq3iaEIcQP1+YmZvD/p3/dSr3rF2OK6dPSj8f/zUAt/66iIFjJ6GGkREy018gM/2F9Abc85SnuBAWiqTHD5H+LBVxMfcQtG0TDGrUgJ2DU7nGcOrUKfwTGYn4+HicOXsWU9zd0b17d7n3Ey5avBje3t7Sz1988QUyMjKwes0aPH78GH/++Sf8/P0xZMgQAK87O9988w3Wrl2Lo0ePIj4+Hnfv3sX+Awdw9OjRUo/nwYMHiI6ORnpGBjIzMxEdHY3o6Gjp311cXGBeuzaWeHnhwYMHuHr1KjZu3AjX/v1VTtlvbm4unYZQ8q969eqoW7eu3JMakyZNwgGZaTLXr1+PyMhIJCYm4saNG5g1ezb09PTQu3dvAMAHnTqhffv2mDVrFi5fvixdz2fzZty+fVvp8eTn50vjy8/PR0pKCqKjoxFX9EQhAAz/+mvcunULO/38EBcXh+PHjyM4OFh6rlVJT09HdHQ0Hjx8CAB4/PgxoqOjkZqaKl2nePqqOi5tpu++fftw5uxZxMXF4f79+1izZg3++ecflfEKOU/e3t5YVOx9p5L9Z2dn4/nz56/PlcwrfNwmTICfvz/279+Px48f4/79+wgNDcUemdH5isTFxSE6OhppaWnIyc2VO58A0KlTJ7Ru3RpeXl64Gx2NO3fu4Ofly/HBBx8onf5UlomJSYm8bGRsDPPataXvVS6ert26dUNQUBBOhIcjISEBl//6C76+vvioWzfo6+vr7HWrabwVtZySyM7Oho+PD27duoWkpCTcuXMHS7y8kJKSgp4yr54qXl5lZWXJHU9CYiKio6ORXDQtrq2tLfq4uGCxpyciIiKQkJCAf6Oi4Ofnhz///LPUY1J1vag656XRtHwGXv8oc+TIEfT7/PMST/DpYvmsSXn1UbduiDh9GoGBgYiPj8f1GzewevVqtGvXTvokma6WV8DrARI/zpmDO7dvY9nSpRCJREhNTUVqaqp0P0DJ9O324YfYWZQ3ExMTcfr0aezdt0867bau5uesrCxs2LABt27dQmJiIv7++2/MnDULjRs3Rpcu/5sNrHi8qvJGZYsXqHjXb1nirajtSVNTU7z33nvYsHEj/omMREJCAo4cOYJjx46hh8wU+MXr4e3bt+Py5cvS+nXhokVITk7GwAEDAOhmfvb29sbVq1eRmJiI+/fvw9vbG5GRkXAp+tGjeIz+AQHw9fXFokWLYG1tLS3XJLOR6WKMimjSX/Dz88Plv/5CfHw8Hj58iD179uDYsWPoW3SutBm7qrylzIoVKxAWFoZlS5eiZs2a0vTKyclRGqdESGgounfvXmKAX0VI45EjR+LkyZMIDg5GXFwcDhw8iPPnz2PIl18qjftttqMlQkJC4ODgIG3rC3Hp0iVcvHhR2teZOHEimjZtCteigRbF21dC2uy63L5S1e6XjVdPT69EW9uiTh0Y1qgBOzs7GBsb63z/CNCsvJKoyNdxcULaIn369IG5uTlmzpqFa9euISEhAf9ERmLV6tV48uRJqd9dWr4ChJUr6tK0vfE262IJZXlLE6Wdf12sW4mIiIhIPdXEYmGPHDVp0gR79+4t8WTp7du38cknn6B3797Ys2cPRCKRxgez+8zfGm8rIRaLcfbIIVw7fxo5WVlobNcKfYaPQt36/xtBvWneD3Ds0g3d+w8GACxzG6nwu/qPGg8n54/w8sVzHN39C5IfP0J21iuY1KqNJi3t8dHng1C3gWYj90d+3AkvMzJKLN+/fz92796NtGfPYGlpic/79sW4cePkRrVPcHNDQ2treHp6SpfdvHkTa9etw71792BlZYUBAwbIPdEtFouxf/9+BAYFISEhAWZmZmhtb4/Ro0fjvffeU3qc/V1dkZSUVGL5P1euSP//6NEjrFy1Cjdu3IB57dro2bMnJk2aJNe5NqtVS2G8ivb39bBh0hlLJMv69esHtwkTAAAe8+bh2rVrSE9Ph4WFBZycnDBl8mTpEx8A8OrVK2zesgURERF4/vw56tati/fefRdTpkxBAyVPgiQmJsJVQYfjvffew7atW6Wfz58/D28fH8TFxaFhw4YYMXw4Bg0aJLeNsniPHDmCJQpmXhk/frw0vuLpK+S4tJW+Abt2ITg4GCkpKTAyMoKdnR3GjxuHDh06qIxX1Xny9PREYlKS3Lnt0LFjiWOxtraWm9r/+PHj2LV7Nx4+fAhjY2PYtWiBr7/+Gj169FAa5wQ3N1y9erXE8tCQEOnToSkpKVi5ahX++usvGBsZwdnZGdOnT5e+S1JVvIr2ad+qFWbOnCn9LJuuBQUF2Onnh2PHjiElJQXm5ub4qFs3TJ48GWZmZgDe/nVbnvECul9OlRZvbm4uFixYgH+jovDixQvUrl0bbdu2xdgxY9BO5j2nxcurfyIjMVHBTED9Pv9cLi/s2LEDvx87hqdPn8Lc3BztHRzg5uZW6o1oIdeLqnOuLF5FhJTPAHD58mW4T52KoMBAhTeVdbF81qS82n/gAA4FBSEhMRFmZmbo2KEDpk6dKvf0na6WV8rOJ/D6VUAdip5WLJ6+r169gq+vL06fOYPnz5/D0tISvXv3xniZdoou5uecnBzMmj0b0dHRePnyJaysrND5gw8wceJE1JWZaUBRflaVNypbvBXx+tU03orcnkxNTYWPjw8u//UXMjIy0KBBAwwaNAgjhg+XPvFZvB5es3YtTp8+jbS0NNQyM0PrNm0wadIktC56rz2ge/nZa+lSXLlyBampqTA1NUVLOzt8O2oUOhdN8V08RmXtAdl29tuOUVZ59hc2b9mCkydP4unTpzA0NERTW1sMGzYMvYpej6TN2IXkLUXxKvpeAFi8aJF01ipF7clHjx7hyyFD4O3tLc0LsnQljUtrX4WEhsLf3x9Pnz6FbZMmmODmho+7d5f+Xdfa0ZmZmejt4oJZM2eWKKdKi/fkyZPw9vHB06dPUatWLXzyySeYMnmy9Cl6Re0rIW12XW1fqWr3K4pX1tZt23D2zBns27dPukyX+0eAZuWVZN+6fB0L7R9JCG2LpKamYpO3Ny5cuICsrCxYWVmhU8eO+P7775XOLiGkPwmoLldKU57tjbddF6vKW6XFq4iq8/+261YhzNR4JRwRERFRVSN4kMTw4cNRv359rFu3rsTfoqKi0KNHD6Slpb31QRIVhbJBEpWVup3Mio7xVm6Mt3JjvJUb463cGG/lxngrN8ZbuTHeyo3xVm6Mt3JjvJUbB0kQERERKVdd9SqveXh4IDIyUuHf2rVrh4iICAQFBZXbgRERERERERERERERERERERGVJ8GDJJycnNCxY0fk5+dj2LBh0ungJRwcHODg4FDuB0hERERERERERERERERERERUHvSErnj27Fk4ODhg5syZsLa2xqhRo3D+/HltHhsRERERERERERERERERERFRuRE8SKJbt27YsWMHkpKSsGnTJjx69Ajdu3dHq1atsGLFCiQnJ2vzOImIiIiIiIiIiIiIiIiIiIjKRPAgCQkTExOMHj0aZ8+exb179zBkyBD4+PigSZMmcHV11cYxEhEREREREREREREREREREZWZ2oMkZNnZ2WHevHlYsGABzMzM8Pvvv5fXcRERERERERERERERERERERGVq+qabnju3Dns3LkTQUFB0NPTw9ChQzF27NjyPDYiIiIiIiIiIiIiIiIiIiKicqPWIInExET4+/vD398f9+/fh7OzMzZu3IihQ4fCxMREW8dIREREREREREREREREREREVGaCB0n06dMHp06dgqWlJb799luMGTMG9vb22jw2IiIiIiIiIiIiIiIiIiIionIjeJCEgYEBAgMD0a9fP+jr62vzmIiIiIiIiIiIiIiIiIiIiIjKneBBEqGhodo8DiIiIiIiIiIiIiIiIiIiIiKt0nvbB0BERERERERERERERERERET0JnCQBBEREREREREREREREREREVUJHCRBREREREREREREREREREREVQIHSRAREREREREREREREREREVGVwEESREREREREREREREREREREVCVwkAQRERERERERERERERERERFVCRwkQURERERERERERERERERERFUCB0kQERERERERERERERERERFRlcBBEkRERERERERERERERERERFQlcJAEERERERERERERERERERERVQkcJEFERERERERERERERERERERVAgdJEBERERERERERERERERERUZXAQRJERERERERERERERERERERUJVQTi8Xit30QRERERERERERERERERERERNpW/W0fgKzYp6lv+xDemCb1LPEyI+NtH8YbY1arFuOtxBhv5cZ4KzfGW7kx3sqN8VZujLdyY7yVG+Ot3Bhv5cZ4KzfGW7mZ1ar1tg+BiIiIKhC+boOIiIiIiIiIiIiIiIiIiIiqBA6SICIiIiIiIiIiIiIiIiIioiqBgySIiIiIiIiIiIiIiIiIiIioSuAgCSIiIiIiIiIiIiIiIiIiIqoSOEiCiIiIiIiIiIiIiIiIiIiIqgQOkiAiIiIiIiIiIiIiIiIiIqIqgYMkiIiIiIiIiIiIiIiIiIiIqErgIAkiIiIiIiIiIiIiIiIiIiKqEjhIgoiIiIiIiIiIiIiIiIiIiKoEDpIgIiIiIiIiIiIiIiIiIiKiKoGDJIiIiIiIiIiIiIiIiIiIiKhK4CAJIiIiIiIiIiIiIiIiIiIiqhI4SIKIiIiIiIiIiIiIiIiIiIiqBA6SICIiIiIiIiIiIiIiIiIioiqBgySIiIiIiIiIiIiIiIiIiIioSuAgCSIiIiIiIiIiIiIiIiIiIqoSOEiCiIiIiIiIiIiIiIiIiIiIqgQOkiAiIiIiIiIiIiIiIiIiIqIqoUyDJHJzcxETE4Pc3NzyOh4iIiIiIiIiIiIiIiIiIiIirRA8SMLf3x+XLl0CAOTk5GDs2LEwMTFBq1atYGpqiokTJ3KwBBEREREREREREREREREREekswYMkvLy8oKf3evWFCxciIiICv/32G6KiohAYGIjTp09j4cKFWjtQIiIiIiIiIiIiIiIiIiIiorKoLnTFxMREWFtbAwBCQ0OxZcsWuLi4AABat24NCwsLjBw5EitXrtTOkRIRERERERERERERERERERGVgeCZJBo0aICYmBgAwKtXr2BpaSn3dysrK6SlpZXv0RERERERERERERERERERERGVE8EzSYwYMQLz58/HsWPHMHLkSHh5eWHfvn0wNTVFVlYWPD090bVrV20eawlisRgBO35B2JEjyMx8iXbtHTFt5iw0aty41O1CDgXht1/34dmzZ2jRwg5Tpv+A1m3bKvz++bNn4cpfl+H503J0/egj6d981q9D1K1bePTwARrb2mKrX0C5xBQREYGgQ4dw9+5dpKenY++ePbC3t1e53cuXL7F582ZEnD6NjIwMWFtbY8aMGfiwDGmSm5uL5cuX487du3j06BE+/PBDrFm9Wm4dT09PHP399xLbNm/WDAcPHlT63X5+fjh9+jQePX4MQ0NDODo6Yqq7O5o2bap0m5iYGPhu3Yq7d+8iKSkJM374AcOHD9c4PgkhcQJAXl4etv/yC8LCwpCWlgZLS0uMGzcOA1xdBe9Lk/QNDg7G78eOSQcptWndGpOnTIFDu3bqBVpMamoq1q1fjzt37iAuLg7DvvoKM2fOLLFeeeWtn5cvx6FDh1SmmyZ5Qwih+efp06fYtGkTLl66hJycHDRq1AiLFy1CWwVlhDL+/v7w9vHB18OGKTynwOu84Ofvj7i4OBQUFKBJ48YY8c03+LxvX41jBN5sumpaXkmcCA/H/Pnz0b17d4XXnDreRNxpaWnYtGkTLv/1F16+fIn33n0Xs2fPRpMmTZRuM8HNDVevXi2xvGvXrtiwfr1aMcp6E/Fqkr4VOd4OHTsqXD5t2jR8O3Kkwr+9evUKvr6+OH3mDJ4/fw77Vq0wc+ZMtKtg5XNxW7dtQ3h4OJ48eQIDA4PX9c7kyXBwcCjT9169ehW7d+/Gnbt3kZqaitWrVuHjjz8usd7Dhw+xcdMmXL16FSKRCM2bNcPKlSvRoEGDMu1fmbKWZcq8yXpHVkFBATZv2YILFy4gISEBpqam6NSpE6a6u8PKykrQdwipx4R6E+dB0zTct28fAoOC8OTJE5jXro1PPv0U7lOmwNDQUKNYgTfTrqwq5bOmbcKKmq4SmtRHgYGBCAwKQlJSEgCgefPmGDd2bJn759q+fjXZ7uDBgzj4229ISkpC/fr1MWbMGPT7/PMyxQkAq1avxo0bNxATE4NmTZti3759JdYRi8XYs2cPgg8fRlJSEszNzfHll19i7JgxZdq3NtLvbdVBElu3bcP27dvlltna2iIoMFDh+gUFBfDz88PR339HSkoKbG1tMdXdHc7OzmU6jjd57Wpa/4pEImzbtg1hx49L992/Xz+MHTsW1apV0yhu4M20JxXdD+rSuTM2bdpU6nbayHfajlfT9FX3WhBKyDXe39VVWq7IGvLll5gzZ06p3y+03S4h9PxrQlX5nJiYCNcBA0ps57dzJ9q3by9oH+rGe/36dWzctAmPHz9GTk4OGjRogMGDB2NEGe9RvokyS9P21du67/xPZCQmTpxYYtvjYWElHuAkIiIiUpfgQRKLFy/Gv//+i+bNm6NDhw44f/486tevDxsbGyQmJqJu3bo4efKkNo+1hAP79uJwUCB+nLcADayt4b9jOzxmzsCO3XtQQ8lNsDN/nMJW702YNnM22rRti0O/HYTHzBnYue9XWFhYyK176OABoJQ+ae/PP8fd27fxIOZ+ucWUnZODd5yc8FnPnlj200+CtsnPz8eUKVNgUacOVqxYgXpWVkhKSoKZmVmZjqWwsBCGRkYY9tVXiIiIULjOrFmz4O7uLv0sEokwfMQIfNqzZ6nfffXqVQwZMgRt27aFSCSCz+bNcJ86Fb8dPAhjY2OF2+Tk5KCRjQ169uyJtWvXah5YMULiBIC5Hh549uwZFi5YgMaNGyM1NRWFYrFa+9IkfSMjI9G7Vy84OjrC0NAQAQEBcHd3x8EDB1CvXj219i8rLy8PFubmGDNmjMKbgED55a3Tp0/j31u3BP04o0neEEJI/snIyMDYcePQ4f33sWHDBliYmyMuLg61atUSvJ+oqCgcCg5Gy5YtS12vVu3aGDN6NJo2bQoDAwOcP38eXl5eqGNhgS5duqgVm6w3ma6a5GeJxMREbNiwAe+++65a2ymj7bjFYjFmzZ6N6tWrY83q1TAxMcHeffswecqUUvPmqpUrkZ+fL/2cnp6O4SNGoOenn2oWaJE3kc6apG9Fjvd4WJjc54sXL2LpsmX4pEcPpdssW7YMMTEx8FqyBFZWVjgWFibNExWlfFbEtkkT/Dh7NmxsbJCbm4t9v/6KKe7uOBwcXKKtpI7s7Gy0bNUKrq6umP3jjwrXiY+Px7jx4+Hq6go3NzeYmpggJiYGNWrU0Hi/Ko+rDGVZad5UvaNov3fv3sW4sWPRsmVLvHz5EqvXrMGMmTOxe9culdsLrcfUOR5tnwdN0vD48ePw9vHBooUL4ejoiNjYWHguWYJq1aphxg8/CI6vuDfRrqwq5bMmbcKKnK7SGDSoj+rVqwd3d3c0adwYYrEYR3//HTNnzcLePXvQokULtfYvS5vXrybbBQYGwmfzZsyfNw9t27ZF1O3b+Omnn1DLzAwfyTzQoCnX/v3xb1QU7v/3n8K/r16zBpcvX8b306bBzs4OGRkZSM/IKPN+tZF+b6sOktW8eXNs9vGRfq5eXfntp81btiAsLAzz589HU1tbXL58GbN//BE7duxA6zIMXHyT166m9W/Arl0IDArCEk9PNG/eHLfv3IGXlxdMTU0xbNgwtY5B1ptqTzp36YJFixZJP6tqs2kr32k73rK0r9S5FoQSco3vCgiASCSSfo6JicEUd3eV9+sAYe12WULOf1moKp8BYLOPD5o3by79bG5uLvj71Y3XyNgYQ4cORUs7OxgbG+P69ev4eflyGBsZYfDgwYL3W9ybKLM0aV+9zfvOEkGBgTAxMZF+rlOnTpn2TURERASoMUiiRo0aCAkJwfHjx3HkyBHo6+ujsLAQ1tbW6Nq1K4YPHy7XWNE2sViM4IMHMeLbUXDu1g0AMGf+QgwZ0B8Xzp9HDyWN/qADB9Cnf3+4FD1t8v2s2fjr0kWc+P0ohn3zvydz7v93D4EH9sNn+w58NbDkSNwp01/fZEt/8aJcB0lIniJPTEwUvE1IaCjSMzKwc+dOaWerYcOGcusUFhYiICAAwYcPIy0tDU2aNMHYsWNLvTFqbGwMj7lzAQA3btzAy8zMEuuYmprC1NRU+vnMmTPIyMiAa//+pR5z8ScLPBcvxme9euHOnTt47733FG7Trl076dO53t7eCtfRVpwXL17E1atXEXL4MGrXrg2g5DkWQpP0XbZsmdznBQsWIOL0afx95Yr0qam8vDxs3rwZJ8LD8fLlS7Ro0QJTp05Fh/ffV/q9DRs2xKxZswAAoaGhCtcRkrdUefr0KVatXo1NGzdiuoCb00LyxsuXL7F+wwacPXsW+fn5aNOmDWb88ANatWql9HuF5J+AgADUr18fixcvli6zsbFRecwSWVlZWLhoEebPm4cdO3eWum7xtPn6669x9Pffcf36dekgCV1OV0Cz/Ay8Hky1YOFCTJgwAdevXStxzeli3LGxsbh16xYO7N8vvVntMXcueru44MSJExg4cKDC7STlhUR4eDiMjIzQU6aO0sV4Ac3StyLHW/wplLPnzqHD+++jUaNGCtfPyclBxOnTWLN6tbRscpswAefPn0dgUBAmT5qk0/GWxsXFRe7zD9OnIyQkBP/99x86deoEAEhOTsb6DRtw+fJl6Onp4Z133sGsmTNLPYauXbuqfCrWZ/NmODs74/tp06TLlKVBeRGS13W13lHE1NRU7kY8APw4ezZGffcdkpOTS52RQ1U9pqvnQZPy6sbNm3BydJTm94YNG6J3r174NypKuo6utiurSvmsSX+hIqerhLr1EYASAwSmTJ6MoKAg3Pr3X2m7RdeuX022O3bsGAYPGoRevXoBeF0/3I6KQsCuXXLn4PDhw9izdy8SExNhbW2NYV99hSFDhpT63bOL8vHzbdsU/gj38OFDBAYG4sD+/dKnbctaXkuoSj9dSzuhquvrC37K99ixYxgzerT0ieQvv/wSf/39N/bu2YOlS5cC0P1rV9P69+bNm+jevTs+/PBD6b5PnDiBKJlyS9fKZ1kGNWqo9TS3kHyni/GWpX2l6lrQ1jVefHBzQEAAGjVqhPeV1KGyhLTbZQk5/4B2ymeJ2rVrazyzgLrxtra3lxvA1bBhQ5w+fRrXrl+XDpLQ1TJLk/bV27zvLFGnTp1yeSCAiIiISJbaw5ddXFxK3Dx/G5KTEvHsWRre7dBBuszE1BSt27TF7ah/FQ6SyM/Px7170XKDIfT09PBehw64HfWvdFlOTg6WL1mCqT/MRJ26dbUbSDk4d+4cHNu3x4oVK3D23DmYm5vDxcUFo779Fvr6+gAAP39/hIWFwWPuXDRu3BjXrl3DokWLYGFujvdL6WiqKyQkBJ06dYK1tbVa22UWNYTL+vSAtuI8d+4c2rZpg127duFYWBiMjY3xUbdumDhxIoyMjMp0zOrKyclBQUEBasucq5UrV+LBw4f4+aefYGVlhdOnT2PatGnY/+uvpb4KQBUheas0hYWFWLR4MUZ+843GT0Epyhtz5s6FoaEhNm7YAFNTUxw6dAiTJk/GoaCgEj8CqOPc+fPo3Lkz5sydi6tXr8LKygpDvvwSgwYNErT9ipUr0bVrV3zwwQcqB0nIEovFuHLlCh4/foypU6dKl+tqupbVL7/8gjp16mDggAG4fu1aib/rYtySp29lp+rW09NDDQMDXL9+XekgieJCQkPR67PP5J7Q0MV4y0tFjTctLQ1//vknlnh6Kl1HJBJBJBKVeFrO0NAQ169fl36uCPGWJj8/H8HBwTA1NZXeqC0oKMDUadPQvn17/LJ9O/T19bFjxw5MLYrLwMBAo30VFhbiwoUL+HbkSLhPnYro6Gg0bNgQo7/7rtTpbt8EXa13hMrMzES1atXkBrYqoqoeq+jnQZaToyPCwsLwb1QUHNq1Q3x8PC5cvIi+Mq+9qsztyopYPgvpL1S2dBVSHxUnEolw6o8/kJ2dDUeZacZ17frVZLu8/PyS9a6REaKiolBQUIDq1asjLCwMvlu34sfZs2Fvb4/o6Gj89PPPMDY2Rr9+/coUp42NDf78809M+/57iMVidOrUCdOmTi3T+StOUfrpWtoJFRsXB5c+fWBYowbat28Pd3d3pT8k5+fnl5gN1MjQENdv3JB+rkjXroSQ+tfR0RHBwcF4/PgxbG1tce/ePdy4cQM/TJ8uXUeXy+fIyEh81qsXzMzM0LFjR0yaOLHUJ/iF5DtdjleW0PaVqmtBW9e4rPz8fBwLC8OIESPK9BqXstBW+SwxY+ZM5OXloUmTJvh25Eh07969HI5amLvR0bh58yYmFQ2UBypOmSWkfaUL952HjxiBvLw8tGjRAhMmTMA7Tk5l/k4iIiKiss/xpoHc3Fzk5ubKLVP3HbHP0p4BACws5KfXsqhTB8+fpSncJj39BQpFIlgUm5LLwqIO4h7HSj/7btqItg4O0hkqdF1CQgL++ecfuLi4YMP69YiLi8OKlStRUFCACePHIy8vD35+ftjs4wNHR0cAr5+6uX7jBg4FB5fbIImUlBRcvHQJy4qe9BCqsLAQa9auhZOTE+zs7DTevzbjTEhIwPUbN1DD0BCrVq3CixcvsGLFCqSnp8s9AfEmbNq0CZaWlnJP8x45ehRHjxyRvs5i5MiRuHTpEo4cOYIpU6ZovC9VeUuVgIAA6OvrazxNqKK8cf36dURFReFkeLj0Jun06dNx5uxZ/PHHH2Wa2jAhIQFBQUEYMXw4Ro8ejdtRUVi9Zg0MDAxUdtpPhIfj7t272BUQIHh/mZmZ6NO3L/Ly8qCvr485c+ag8wcfANDtdC2L69evIyQ0FPv27lX4d12Nu2nTpmjQoAG8fXwwz8MDxsbG2LtvH548fYrUNMV1TnH/RkUhJiYGCxcu1Pl4y0NFjvfo77/DxMQEPUqZ2tzExASO7dvjlx070KxZM9SpUwcnTpzArVu3pE/7VpR4FTl//jzmzZ+PnJwcWFpawsfbW3rDOzw8HIWFhVi4YIH0JuvixYvxcY8eiIyMROfOnTXa57Nnz5CVlQX/gABMmjQJU93dcenSJcz+8Uf4btlSroM61aGr9Y5Qubm52OTtjd69epV6E19VPVbRz0NxLi4uePHiBcaNGwexWAyRSIQvvvgCY0aPBlC525UVsXwW2l+obOkqpD6SuH//PkaPGYO8vDwYGxtj1apV0mnHdfH61WS7Lp0743BICD7++GO0bt0ad+7cQcjhwygoKMCLFy9gaWmJrdu2Yfr06fjkk08AvH5C/cHDhzh06FCZypOEhAQkJyfj1B9/YImnJ0SFhVi7di3mzJ0L3y1bNP5eCWXpp4tpJ4RDu3bwXLwYtra2SE1Nxfbt2zFu/Hgc2L9f4QyknTt3xr69e/Heu++iUaNG+PvKFUScPo3CwkIAFe/aBYTXv9+NGoVXmZn4csgQ6OnpobCwEJMnTUKfPn0A6Hb53MXZGT169ICNjQ3i4+Phs3kzpn3/Pfx27lQ66EBVvtPleGUJTV9V14I2r3FZZ86cQWZmJvprqV0lhLbK55o1a2L69Ol4x8kJ1apVQ0REBGbNno3Vq1ZpfaBE388/x/PnzyESiTBh/HjpwxMVpcwS2r56m/edLevWhYeHB9q2aYO8vDwcDgmBm5sbAvz90bp1a42/l4iIiAhQc5DE5s2bcejQIdSpUwdubm74VGbKrNTUVHTq1AkPHjxQ+T3Lly/HkiVL5JYtXrwYYya7K93mj/ATWL96lfTzshWrlK5bFhf/PI9rVyPhu8NPK98vKywsDD8vXy79vHHDBrz77rtqf49YLIaFhQXmz5sHfX19tGnTBk9TUrB7925MGD8ecXFxyMnJwRR3+fObn58P+6Lp4YYOHYqk5GQAwLvvvIONGzeqfRxHjx6Fqamp2k97rli5EjExMfhl+3a19ylLm3EWisWoVq0ali1dKu0A502fjjlz52LOnDkKR2uXV/rK8vf3R/jJk9jq6ysdWHT//n2IRCIM/uILuXXz8vKkTx10k5nCtU+fPpjn4SFof6rylqzi8a5ftw779+/Hnj17NH5SQVHeuHfvHrKzs0u8RzM3NxfxRTcvhwwdKl0+evRo6Y1xVQoLC9G2TRvpjZfW9vaIefAAQSo67cnJyVizZg18vL3VGvBVs2ZN7Nu7F1lZWbhy5QrWrVsHGxsbdHj/fZ1JV4nyyM+vXr3CosWLMX/ePKVPF+lK3IriXbVyJZYuXYpPPv0U+vr66NSxI5ydnQGB7/4MCQmBnZ0dHIqmRdX1eMtaXlXkeENDQ+Hi4qLyevby8oKXlxf69O0LfX192Nvbo3evXrhz965OxVsaZeeiQ4cO2Ld3L168eIHgw4fhMW8e/P38UKdOHfz333+Ij4/HR8VuOubl5SE+Ph7Xrl3DtO+/ly6f5+EhvdGvKiYA6N69O0YMHw4AsLe3x42bNxF06FC5DJLQJK/rYr0jNKaCggLM9fCAWCzG3KKpbBURUo/pynkor/Lqn8hI+Pn5Ye6cOXBwcEBcXBxWr1mDX375BePGjdOZdmVVK5+VEdpfqCjpKlFe9REA2NraYt/evcjMzMQff/wBT09PbNu6Fc2bN9eZ67es240dOxapaWn4rujY6tSpg8/79cOuXbtQrVo1ZGdnIz4+HkuXLsVPP/0k3U4kEknTZNq0abhWNOOTdYMGOHjwoKA4xYWFyMvLwxJPT9ja2gIAFi1ciG9GjsSjR4+kr+DQlLL008W0E0J22vqWLVvCwcEB/fr3x8lTpzBwwIAS68+aORPLfvoJXw4ZgmrVqsHGxgau/fsj9MgRALrX1wfKp/4FgJOnTuH48eNYtmwZWjRvjuh797B27VpYWVmhX79+OlM+K4q3d9GrbwDAzs4OdnZ2GDhoECIjI6UPdRSnKt/pcryapK+qa0Gb17iskNBQOHfpIh148qZps3w2NzfHNyNGSD+3a9cOKamp2L1nj9YHSWzftg3Z2dm4desWvH180KhxY7j07q2TZZYiQttXb/O+c9OmTeXqWCcnJyTEx2Pvvn1Y6uUlOFYiIiIiRQQPkti4cSM8PDwwevRopKeno2/fvvD09IRHUWdEJBLh8ePHgr7Lw8MDM2bMkFtmaGiIJ+kvlW7T5cMP0brt/27k5efnAQCeP3+GujLvnHv+7BlatGyp8Dtq1zaHnr4+nj97Jrf8+fNnsKj7enaJ61cjkZSQgIF95V8p4rVwPhwcnbBmk+J3/Wnio48+goODg/Szpp0Vy7p1Ub16dbmR+s2aNkVaWhry8/ORnZ0N4PWP1vXq1ZPbVjIl9oYNG1BQUABA/Vk9gNcN5tAjR9C3b1+1ptlesXIl/jx/Htu2bUP9+vXV3q8sbcZpaWkJKysruScEmjVrBrFYjKdPnyqc8rG80ldi9+7d8A8IwGYfH7SUyeNZWVnQ19fH7l27SjytIZlCWfapfUVP7iijKm/JpnXxeE+dOoVnz5+jX//+0mUikQjrN2zAr/v340gp76kElOeNrOzs10+J+fqW2MbMzAympqZy8arzChdLS0s0K3riTjbeiIiIUre7e/cunj17hm9G/u9VPiKRCNeuXcPB337DxQsXFD5Jo6enh8aNGwN4/UPgw0eP4O/vjw7vv68z6SpRHvk5Pj4eiYmJmDFzpnSZ5OmwDzp3RlBgoM7ErSheIyMj7Nu3D5mZmcjPz4eFhQVGffcd2rZpo3Lf2dnZCA8Px0Q3N7nluhxvWVTkeK9du4bHjx9j+c8/q9xno0aNsK3oxtirV69gaWkJDw8P6XuVdSXe0ig7F8bGxmjcuDEaN26M9u3bY9DgwQgJCcHo0aORlZ2N1q1bK5w5ysLCAtWrV5eLq06xGbyUMTc3h76+Ppo1aya3vFmzZnKvMCkLTfK6LtY7spTFJLmBn5ycjC2bN5f6lKOQekxXzkN5lVe+vr7o27ev9Ik/Ozs7ZGdn46eff8aYMWN0pl1Z1cpnRdTpL1SUdJUor/pIcvySdmWbNm1w+/Zt/Lp/P+bPm6cz129ZtzMyMsLiRYswf948pKWlwdLSEsHBwTAxMYGFhQWeP38OAFgwf77ceQVet7sBYMGCBdJZLSXvVRfC0tIS+vr60gESAKQ/2iQ/eVLmQRLK0s/Gxkbn0k4TZmZmsG3SBPFxcQr/bmFhgTWrVyM3Nxfp6emwsrLCJm9v2BS9817Xrl2gfOpf4PWP76NGjZIOOLCzs0NSUhL8/P3Rr18/nSmfhdRHjRo1grm5OeLi45UOklCV73Q9XnXTt7ji14I2y2eJpKQk/P3331i5cqXa25aXrKwsANopnxVxaNcOf/31V5m+QwhJv8/Ozg5pz55h27ZtcOndWyfLrOLUaV/pwn1nWe3atZN7HRMRERGRpgS3Ordu3Yrt27djeNGTfZMmTcLAgQORnZ0NLzVHbhoaGippECkfJFGzpglq1vxf50csFqNOnbq4FhkJu5av35H96tUr3L1zG/0HKn6HpoGBAVq1sse1yH/QtWjkeWFhIa5FRmLA4Nej1IeNGIk+/VzltpswaiQmTp2Gzs5dS3xnWZiYmKjVoVPGyckJx0+cQGFhobRzERsbC0tLSxgYGKBZs2aoUaMGkp88UfoUprW1dZmOIfLqVcTFxWGAq6vqlfE6/VauWoUzZ85gq6+vtGNRFtqM08nREadOnUJWVhZq1qwJAHgcGws9Pb0SHQCJ8kpfAAjYtQs7d+6E96ZNaNu2rdzf7O3tIRKJ8Pz5c6VPFkpuuKlLVd6SVTzeQYMGoVuxV9ZMnTYNffv0QX+ZgRPFqcobrVu3RlpaGvT19dGw6KZZcWWJt/hgr8exsbBW8u5ciY4dO2L/r7/KLfPy8oJt06Zqvd+0sOgJNUB30lWiPPJz06ZNS5ynLb6+yHr1CjNnzkT9+vUhEol0Iu7S4pXcjIiNjcWdO3cwaeJElfs+deoU8vPzSzxNryvpXJ7lFVCx4w0JCUGbNm3QqlUrwfs2NjaGsbExMjIycOnyZUybOhWA7sRbGqFpX1hYiLz8fACvn/g7efIkLCwslN4Y1iQuAwMDtGvbtkQ5HBsbW+Z2ioQmeV0X6x1ZimKS3MCPjY3FVl/fUt8NDgirx3TlPJRXeZWTk4NqRdeOhF5RfS0Wi3WmXVnVymdZmvQXKkq6SpR3fSSrUCxGflG7Uleu3/LYDnj945nkB53w8HB8+OGH0NPTQ926dWFlZYWEhASlMxgpSwtVnJycIBKJEB8fL32tVmzs61d2qlNmCyVJP11MO01kZWUhPiEBfWUecFHE0NAQ9erVQ0FBASIiIvBZ0dP1unbtAuVT/wJATm6utGyU0NfTk86wpSvls5D66MmTJ0hPT4dl3bql7rO0fKfL8WqSvsUVvxa0eY1LhB45AgsLC3zYtXzvaapDm+WzIvfu3YOlivKmvIkLC5Ff1F/SxTJLepwatK904b6zrOh790otZ4iIiIiE0lO9ymsPHz58Pa14EWdnZ0RERGDbtm3S2STepGrVqmHQ0KHYFxCAi3+ex8OYGKxcthR161qiq8wPs7O/n4bDQYHSz1989RWOHT2C8LBjePzoETauWY2c7Bz07vs5AKBO3bpo1ry53D8AqFevPqxlOiwJ8fG4/989PHuWhrzcXNz/7x7u/3dP2iDWVHp6OqKjo/Hg4UMAwOPHjxEdHY3U1FTpOosWL4a39/9mtPjiiy+QkZGB1WvW4PHjx/jzzz/h5++PIUOGAHjdufvmm2+wdu1aHD16FPHx8bh79y72HziAo0ePlno8Dx48QHR0NNIzMpCZmYno6GhER0eXWC8kJAQODg6lvsNO1ooVKxAWFoZlS5eiZs2aSE1NRWpqKnJycpTGmZ+fL91/fn4+UlJSEB0djbiiEfjajNPFxQXmtWtjiZcXHjx4gKtXr2Ljxo1w7d9fransNElf/4AA+Pr6YtGiRbC2tpaeK8lIfFtbW/RxccFiT09EREQgISEB/0ZFwc/PD3/++WepxyOJMzs7G8+fP399bDKvzFGVt0pjbm4unXJT8q969eqoW7eu3JNWkyZNwgGZaRRV5Y0POnVC+/btMWvWLFy+fBmJiYm4ceMGfDZvxu3bt5Uej6r8AwDDv/4at27dwk4/P8TFxeH48eMIDg5WGa+JiUmJWI2MjWFeu7b0miiern5+frj811+Ij4/Hw4cPsWfPHhw7dgx9i24Y6Gq6ylI3PxsaGpY4T2ampqhZdP4MDAx0Ou5Tp07hn8hIxMfH48zZs5ji7o7u3bujc+fOCuOVFRIaiu7du5e4kabL8WpSXlXkeAEgMzMTp/74AwMUTAMNlCyvLl26hIsXLyIhIQGX//oLEydORNOmTeFaNGBQ1+NVJDs7Gz4+Prh16xaSkpJw584dLPHyQkpKCnoWvWatT58+MDc3x8xZs3Dt2rXX76iNjMSq1avx5MkTpd+dlZUlV78mJCYiOjoayUXTrgKv3zl98uRJBAcHIy4uDgcOHsT58+cx5MsvyxRXaVTldV2sd0pTUFCAH+fMwZ3bt7Fs6VKIRCJpXSrbTpXNz0LqMV0+D5qUV926dUNQUBBOhIdLr2FfX1981K0b9PX1dbpdWVXKZ036CxU5XWWpWx95e3vj6tWrSExMxP379+Ht7Y3IyEi4FLUrdfH6FbKdt7c3Fsm8X/3x48c4duwYYmNj8W9UFDzmzUPMgweYMnmydB23CRPg5++P/fv34/Hjx7h//z5CQ0OxR+ZJbEXi4uIQHR2NtLQ05OTmysUNAJ06dULr1q3h5eWFu9HRuHPnDn5evhwffPCB3OwSmigt/XQx7YRYv349IiMjpcc7a/Zs6OnpoXfv3gBKXrv//vsvIiIipK/tmjp1KsSFhfj2228BVIy+vib1LwB0+/BD7CwqaxMTE3H69Gns3bdP+hpTXSyfgdftug0bNuDWrVtITEzE33//jZmzZqFx48bo0qWL0nhV5TtdjVfT9FV1LWjzGgdeD3Q+cuQI+n3+uVqzM6hqtxcvnwHV519b5fPRo0dx/MQJPHr0CI8ePcJOPz+EHjmCr2ReU1Le8R48eBDnzp1DbGwsYmNjcTgkBHv27pUOANHlMkuT9tXbvO+8b98+nDl7FnFxcbh//z7WrFmDf/75p1zqKiIiIqJqYrGwl6k3adIEe/fuLfFk+O3bt/HJJ5+gd+/e2LNnD0QikcYHE/s0VfVKMsRiMQJ2/IJjR0KRmZkJh/aOmDZjJhrJTC32zZAv0KtPX3w7Zqx02eGgQPz2677Xr+awa4nJ309HG5l38hb3Wbeu8PxpuXT2CQCYOdUdN69fK7Hu7oOBaCBgdGyTepZ4mZFRYvmRI0ewRMHMHOPHj4fbhAkAgAlubmhobQ1PT0/p32/evIm169bh3r17sLKywoABA+SeYBeLxdi/fz8Cg4KQkJAAMzMztLa3x+jRo/Hee+8pPc7+rq5ISkoqsfyfK1ek/8/MzERvFxfMmjkTgwYpnsXDrFYtuXg7dOyocL3FixZJZxkoHmdiYiJcFdwofO+997Bt61atx/no0SOsXLUKN27cgHnt2ujZsycmTZqksBNSPF4JTdJX2bHJblNQUIAdO3bg92PH8PTpU5ibm6O9gwPc3NxKHbiiKB2sra3lXoWhKm+VFm9x/V1d8fWwYdIZaSTL+vXrJ41FSN549eoVNm/ZgoiICDx//hx169bFe+++iylTpqCBkiefhOQfADh//jy8fXwQFxeHhg0bYsTw4SXytZB4J7i5wb5VK8wserVE8XTdvGULTp48iadPn8LQ0BBNbW0xbNgw9JJ5r+vbTldV8WpaXsny9PTEy8xMrFm9WmfiVhbv/v37sXv3bqQ9ewZLS0t83rcvxo0bJ/fUkaJ4Hz16hC+HDIG3tzc6f/BBie/V1Xg1Td+KGi8AHDp0CGvWrsWJ48cVzpBQvLw6efIkvH188PTpU9SqVQuffPIJpkyeLLetLserSG5uLhYsWIB/o6Lw4sUL1K5dG23btsXYMWPQTqatlJqaik3e3rhw4QKysrJgZWWFTh074vvvv1c6u8Q/kZGYqGDmlX6ffy6Xh0JCQ+Hv74+nT5/CtkkTTHBzw8cC3yesbryAsLz+tusdZRTFq2y/wOtXEXQoerqreH4urng9Brz981Ce5VVBQQF2+vnh2LFjSElJgbm5OT7q1g2TJ0+GmZkZgLffrqzq5bMm/YWKkK7K4pWlbn3ktXQprly5gtTUVJiamqKlnR2+HTVKLp118fpVtZ2npycSk5Kk+3r48CHmL1iAx48fo3r16ujQoQOmuruXeNXF8ePHsWv3bjx8+BDGxsawa9ECX3/9NXr06KEwTuB1Xrp69WqJ5aEhIdKnu1NSUrBy1Sr89ddfMDYygrOzM6ZPn47atWuX2E6d+khV+r3ttBOieLwe8+bh2rVrSE9Ph4WFBZycnDBl8mTpLBzFr93IyEj834oVSEhIgLGxMbp27Yqp7u5yr3TQlWtXUbyA5vXvq1ev4Ovri9NnzuD58+ewtLRE7969MV6mn6Fr5TPweuaeWbNnIzo6Gi9fvoSVlRU6f/ABJk6ciLoyT3gram+oyne6GK+m6avqWgC0e41fvnwZ7lOnIigwUOmALkXxqmq3Fy+fAWHnXxvl89GjRxGwaxeSkpKgr6+Ppk2bYuTIkdIB3tqId/+BAzh06BASExOhr6+PRo0aYdDAgRg8eLB0pgVdKbPKo30FvL37zgG7diE4OBgpKSkwMjKCnZ0dxo8bhw4dOij8PjMNXklDREREVZfgQRLDhw9H/fr1sW7duhJ/i4qKQo8ePZCWlvZGB0lUZMoGSVRWmvxoUZEx3sqN8VZujLdyY7yVG+Ot3Bhv5cZ4KzfGW7kx3sqN8VZujLdyq4rxEhEREQkleK41Dw8PREZGKvxbu3btEBERgaCgoHI7MCIiIiIiIiIiIiIiIiIiIqLyJHiQhJOTEzp27Ij8/HwMGzZMOl2phIODAxwcHMr9AImIiIiIiIiIiIiIiIiIiIjKg57QFc+ePQsHBwfMnDkT1tbWGDVqFM6fP6/NYyMiIiIiIiIiIiIiIiIiIiIqN4IHSXTr1g07duxAUlISNm3ahEePHqF79+5o1aoVVqxYgeTkZG0eJxEREREREREREREREREREVGZCB4kIWFiYoLRo0fj7NmzuHfvHoYMGQIfHx80adIErq6u2jhGIiIiIiIiIiIiIiIiIiIiojJTe5CELDs7O8ybNw8LFiyAmZkZfv/99/I6LiIiIiIiIiIiIiIiIiIiIqJyVV3TDc+dO4edO3ciKCgIenp6GDp0KMaOHVuex0ZERERERERERERERERERERUbtQaJJGYmAh/f3/4+/vj/v37cHZ2xsaNGzF06FCYmJho6xiJiIiIiIiIiIiIiIiIiIiIykzwIIk+ffrg1KlTsLS0xLfffosxY8bA3t5em8dGREREREREREREREREREREVG4ED5IwMDBAYGAg+vXrB319fW0eExEREREREREREREREREREVG5EzxIIjQ0VJvHQURERERERERERERERERERKRVem/7AIiIiIiIiIiIiIiIiIiIiIjeBA6SICIiIiIiIiIiIiIiIiIioiqBgySIiIiIiIiIiIiIiIiIiIioSuAgCSIiIiIiIiIiIiIiIiIiIqoSOEiCiIiIiIiIiIiIiIiIiIiIqgQOkiAiIiIiIiIiIiIiIiIiIqIqgYMkiIiIiIiIiIiIiIiIiIiIqErgIAkiIiIiIiIiIiIiIiIiIiKqEjhIgoiIiIiIiIiIiIiIiIiIiKoEDpIgIiIiIiIiIiIiIiIiIiKiKoGDJIiIiIiIiIiIiIiIiIiIiKhK4CAJIiIiIiIiIiIiIiIiIiIiqhI4SIKIiIiIiIiIiIiIiIiIiIiqhGpisVj8tg+CiIiIiIiIiIiIiIiIiIiISNuqv+0DkJX+8uXbPoQ3praZGV5mZLztw3hjzGrVYryVGOOt3Bhv5cZ4KzfGW7kx3sqN8VZujLdyY7yVG+Ot3Bhv5cZ4K7eqGC8RERFpjq/bICIiIiIiIiIiIiIiIiIioiqBgySIiIiIiIiIiIiIiIiIiIioSuAgCSIiIiIiIiIiIiIiIiIiIqoSOEiCiIiIiIiIiIiIiIiIiIiIqgQOkiAiIiIiIiIiIiIiIiIiIqIqgYMkiIiIiIiIiIiIiIiIiIiIqErgIAkiIiIiIiIiIiIiIiIiIiKqEjhIgoiIiIiIiIiIiIiIiIiIiKoEDpIgIiIiIiIiIiIiIiIiIiKiKoGDJIiIiIiIiIiIiIiIiIiIiKhK4CAJIiIiIiIiIiIiIiIiIiIiqhI4SIKIiIiIiIiIiIiIiIiIiIiqBA6SICIiIiIiIiIiIiIiIiIioiqBgySIiIiIiIiIiIiIiIiIiIioSuAgCSIiIiIiIiIiIiIiIiIiIqoSOEiCiIiIiIiIiIiIiIiIiIiIqgQOkiAiIiIiIiIiIiIiIiIiIqIqgYMkiIiIiIiIiIiIiIiIiIiIqErgIAkiIiIiIiIiIiIiIiIiIiKqEgQPkmjfvj2WLl2KuLg4bR4PERERERERERERERERERERkVYIHiQRFRWFDRs2oFmzZnBxcUFQUBAKCgq0eWxERERERERERERERERERERE5Uat123cvHkTgYGBqFGjBoYNG4aGDRti1qxZuHPnjraOj4iIiIiIiIiIiIiIiIiIiKhcqDVIonr16hg4cCBCQ0MRGxuLH374AaGhoXBwcICzszN27typreMkIiIiIiIiIiIiIiIiIiIiKpPqQlesVq2a3Gdra2t4eHjAw8MDZ86cwY4dOzBt2jSMGTOm3A9SQiwWY9vWrTgcHIzMzEw4Ojlhzty5aNKkSanb/XbwIPbs3o20tDS0bNkSs2bPRjsHB+nfc3NzsWH9eoSHhyM/Lw+dO3fGj3Pnom7dutJ1OnXoUOJ7l/30E3r17g0ASE1Nxfp163Dnzh3Ex8Xhq2HDMGPmTLXiu3r1Knbv3o07d+8iNTUVq1etwscff6x0/YiICAQGBeHevXvIz89H8+bNMWH8eHTp0kWt/RaXm5uL5cuX487du3j06BE+/PBDrFm9usR6eXl52P7LLwgLC0NaWhosLS0xbtw4DHB1LdP+JTw9PXH099/llnXp3BmbNm0q0/cKPc8PHz7Exk2bcPXqVYhEIjRv1gwrV65EgwYNyrR/TY9HHampqVi3fj3u3LmDuLg4DPvqK8wslh+PHDmCJV5ecstq1KiBixculGnf6vL394e3jw++HjasxDGqIyYmBr5bt+Lu3btISkrCjB9+wPDhw+XW6e/qiqSkpBLbDvnyS8yZM0fjfQPA06dPsWnTJly8dAk5OTlo1KgRFi9ahLZt2yrdRlvX0KrVq3Hjxg3ExMSgWdOm2LdvX4l1xGIx9uzZg+DDh5GUlARzc3N8+eWXGKthGf7z8uU4dOiQwvMua+u2bdi+fbvcMltbWwQFBmq0Xwkh6Q9olk4SERERCDp0CHfv3kV6ejr27tkDe3t7ldvt27cPgUFBePLkCcxr18Ynn34K9ylTYGhoqFGsgLBy+p/ISEycOLHEtsfDwmBpaVnq96tbLl2/fh0bN23C48ePkZOTgwYNGmDw4MEYUUpeEOJN10fqlvsT3Nxw9erVEsu7du2KDevXq7VvWULK8LLsu6CgAJu3bMGFCxeQkJAAU1NTdOrUCVPd3WFlZaV0Oz8/P5w+fRqPHj+GoaEhHB0dMdXdHU2bNtUkTCltX7+axluWfZZGSPoCwMuXL7F582ZEnD6NjIwMWFtbY8aMGfiwa1e19ie0fNZWHfkmymdZVS1eibfVngTKL68qo0n9KzQd1KXt+leTfBEWFoZdu3cjNjYWpqamcHZ2xvfTpsHc3FyjGCXeRHtS3XiF5klNaDteTerQ4OBg/H7sGGJiYgAAbVq3xuQpU+DQrp3GcQK6c21v3bYN4eHhePLkCQwMDF7HN3kyHGTu1Wjibfb3q1J5BWgW79vM15reAxGJRNi2bRvCjh+X9jX69+uHsWPHlrhXKlHWc6uMkHRVdC8NAJo3a4aDBw+q3Iembf631e8Fyt4f1LS/EBgYiMCgIGmbsnnz5hg3diy6lrGcfFPtybKUgyfCwzF//nx0795dYZqo403US5rUOZWtv0BEREQlCR4kIRaLlf7t448/xscff4yMjIxyOShldgUE4MD+/Vjs6YmGNjbYumULpk2digMHDyptdJ8MD8f6desw18MD7RwcsP/XXzFt6lT8FhSEOnXqAADWrV2LC3/+ieX/938wNTXFqpUrMWf2bPxSbGaMRYsXo7PMAAQzMzPp//Py8mBhYYExY8bgVwU3VITIzs5Gy1at4Orqitk//qhy/WvXruGDDz7AlMmTYWZmhiNHjuCHGTPg7++P1gJ+uFOmsLAQhkZGGPbVV4iIiFC63lwPDzx79gwLFyxA48aNkZqaisJS8okmnLt0waJFi6Sfa9SoUebvFHKe4+PjMW78eLi6usLNzQ2mJiaIiYkpl/1rcjzqysvLg4W5OcaMGaPwBp+EiYmJ3I/Tyjr42hIVFYVDwcFo2bJlmb8rJycHjWxs0LNnT6xdu1bhOrsCAiASiaSfY2JiMMXdHZ/27FmmfWdkZGDsuHHo8P772LBhAyzMzREXF4datWqVup02ryHX/v3xb1QU7v/3n8K/r16zBpcvX8b306bBzs4OGRkZSNewDD99+jT+vXVL5Y+NEs2bN8dmHx/p5+rVBVdFSglJf03TSSI7JwfvODnhs549seynnwRtc/z4cXj7+GDRwoVwdHREbGwsPJcsQbVq1TDjhx8Ex1ec0HIaAIICA2FiYiL9LKn7SqNuuWRkbIyhQ4eipZ0djI2Ncf36dfy8fDmMjYwwePBg1QEp8SbrI03K/VUrVyI/P1/6OT09HcNHjEDPTz9Va9/FCSnDy7LvnJwc3L17F+PGjkXLli3x8uVLrF6zBjNmzsTuXbuUbnf16lUMGTIEbdu2hUgkgs/mzXCfOhW/HTwIY2Nj9QOVOR5tXr+axlvWMkMZIembn5+PKVOmwKJOHaxYsQL1rKyQlJQk1/YUQp3yWVt15JsonyWqWryy3lZ7srzyamk0qX+FpIMmtFn/apIvrt+4gcWenpjxww/o1q0bUlJS8PPy5fjpp5+watUq9YJTQJvtSU3iFdrH0ZQ249WkDo2MjETvXr3g6OgIQ0NDBAQEwN3dHQcPHEC9evU0jlNXrm3bJk3w4+zZsLGxQW5uLvb9+iumuLvjcHAwLCwsNP7et9nfryrllYQm8b7NfA1odg8kYNcuBAYFYYmnJ5o3b47bd+7Ay8sLpqamGDZsWKnbanpulRGSrrNmzYK7u7v0s0gkwvARIwS3cTQpr952v7es/UFN+wv16tWDu7s7mjRuDLFYjKO//46Zs2Zh7549aNGihVqxFj8ebbcny1IOJiYmYsOGDXj33XfVikuZN1EvaVLnVLb+AhEREZUk+JepUaNGqbwBrs2KWiwWY/+vv2LM2LHoXvQUgKeXF1x69cLZM2ekMzoUt2/vXgwcOBD9i0YPz/XwwIU//8SR0FCM+u47ZGZmIjQkBEuXLUPHjh0BvB4MMfTLL3Hr1i20b99e+l2mZmZKR3w3bNgQM2fNAgAcCQ3VKMauXbuqNdq4+KjaKVOm4OzZszh/7px0kERhYSECAgIQfPgw0tLS0KRJE4wdO7bUH1GMjY3hMXcuAODGjRt4mZlZYp2LFy/i6tWrCDl8GLVr1wbw+hyUN4MaNUodZZ+cnIz1Gzbg8uXL0NPTwzvvvINZM2eWeixCzrPP5s3Sp7AkGjVqpH4AAqg6nry8PGzevBknwsPx8uVLtGjRAlOnTkWH999Xuk3Dhg0xqyg/hpaSH6tVq1ampxjKIisrCwsXLcL8efOwo9iApJcvX2L9hg04e/Ys8vPz0aZNG8z44Qe0atVK6fe1a9cO7YqePvH29la4TvGOT0BAABo1aoT333uvTLEEBASgfv36WLx4sXSZjY1NqdsIvYYOHz6MPXv3IjExEdbW1hj21VcYMmRIqd89uyjtn2/bpvAm78OHDxEYGIgD+/dLnwZRdbzKPH36FKtWr8amjRsxXeDNj+r6+qXmO22lvybpJOvzvn0BvL4hINSNmzfh5OgIFxcXAK/TuHevXvg3Kkq6jrbKaYk6deqofUNb3fqotb293OC8hg0b4vTp07h2/bp0kISu10ealPuS/UmEh4fDyMgIPWVummirDBeyb2VMTU3lBioBwI+zZ2PUd98hOTlZ6ZNDxWdy8ly8GJ/16oU7d+7gvaJyVBevX03jFbJPbaVvSGgo0jMysHPnTulAMnXztbrls5A6UhfTV6KqxVvc22pPlkdeVUWT+ldIOuha/atJvrh18+br9mHRj3Q2NjYYPHgwdhX7QUcX25OaxCu0j6OL8QqpQ4tbtmyZ3OcFCxYg4vRp/H3lCvp9/jmAin1tS9rHEj9Mn46QkBD8999/6NSpE4CK19+vKuWVhCbxvs18DWh2D+TmzZvo3r07PvzwQ+m+Tpw4gSiZPp0ypZ1bbaWrqakpTE1NpZ/PnDmDjIwMuPbvr/J4Ac3Kq7fZ7y2P/qCm/YWPPvpI7vOUyZMRFBSEW//+Kx0koavtSU3LQZFIhAULF2LChAm4fu1aiTTR1XpJSJ1TXGXrLxAREVFJekJX9PPzK9enBtSVmJCAtLQ0uYaLqakp2jk44NatWwq3yc/Px927d9Hxgw+ky/T09NCxUyfcunkTAHDnzh0UFBSgk8w6TZs2RYMGDaTrSKxasQKfffopvvv2W4SGhJQ6u8bbUFhYiFdZWagl88OJn78/fj92DB5z5+LA/v0Y/vXXWLRoESIjI8u0r3PnzqFtmzbYtWsX+vTti8FffIH169cjJyenrGHIiYyMxGe9emHwF19g+f/9H168eCH9W0FBAaZOm4aaNWvil+3bseOXX1DT2BhTp02Te7pWXYWFhbhw4QJsmzSB+9Sp+KxXL4z67jucOXOm7AFpYOXKlbh56xZ+/ukn7P/1V/T89FNMmzYNsbGxZf7u7Oxs9OvfH59//jlmzJwpnfLyTVixciW6du2KD2SuPYk5c+fi2bNn2LhhA3bv2oXW9vaYNHky0tPTy23/+fn5OBYWBldX1zLPoHHu/Hm0adMGc+bOxWe9emH4iBEIDg4ufRsB11BYWBh8t27F5EmT8NvBg5gyeTJ8t27F0aNHy3y8NjY2+PPPP+E6YAD6u7pi6bJlap/fwsJCLFq8GCO/+UatpyRi4+Lg0qcPBgwYgAULFiA5OVnu79pKf03SqaycHB1x5+5d6c2h+Ph4XLh4Ue7GrbbKaYnhI0agt4sLJk+Zgus3bpTLd6pyNzoaN2/elLt5oMv1UXmV+yGhoej12Wdyg0q1WYar2rc6MjMzUa1aNbkbqkK2AeQHyVaU61dIvEL2qa30PXfuHBzbt8eKFSvQq3dvDP3qK+z085N7kqk0mpbPEsrqSF1N36oWryZ0Na++TbpW/2qSL9o7OuLJkyf488IFiMVipKWlIeKPP9DV2Vm6jq62J7V1HehqvMUpqkNVycnJQUFBAWrLbFNZru38/HwEBwfD1NRU+sNSVenvC6Fr5VV5epP5GtDsHoijoyOuXLmCx48fAwDu3buHGzduwFmmrFWmtHOr7XSVCAkJQadOnWBtba3R9kLKq7fZ79XW/Ul1+0cikQgnwsORnZ0NR5kH7nSxPVmWcvCXX35BnTp1MHDAAIV/rwj1kqI6R8g2lb2/QEREVBWVfY5zDeTm5iI3N1dumap31KWlpQEA6tStK7e8Tp060r8V9+LFC4hEohLT2dWpUwePHz2Sfq+BgUGJASDFv9dt4kR06NABRkZGuHz5MlauWIHs7Gx8pWJqvTdp9549yM7OxmdFT5Hm5eXBz88Pm3184OjoCOD1qODrN27gUHAw3i9lFK8qCQkJuH7jBmoYGmLVqlV48eIFVqxYgfT0dLlRrmXRxdkZPXr0gI2NDeLj4+GzeTOmff89/HbuhL6+PsLDw1FYWIiFCxZIG6iLFy/Gxz16IDIyEp07d9Zov8+ePUNWVhb8AwIwadIkTHV3x6VLlzD7xx/hu2VLmc6bupKTk3Hk6FEcPXJEOnX0yJEjcenSJRw5cgRTpkzR+LttbW2xcOFCtLSzQ2ZmJvbs2YMxY8fi4IEDqF+/fnmFoNCJ8HDcvXsXuwICSvzt+vXriIqKwsnwcOk0f9OnT8eZs2fxxx9/lGnqfllnzpxBZmYm+vfrV+bvSkhIQFBQEEYMH47Ro0fjdlQUVq9ZAwMDA/RT8v1CrqGt27Zh+vTp+OSTTwC8HjX+4OFDHDp0SOn3Cj3e5ORknPrjDyzx9ISosBBr167FnLlz4btli+DvCQgIgL6+vsopRmU5tGsHz8WLYWtri9TUVGzfvh3jxo/Hgf37YWJiotX01ySdysrFxQUvXrzAuHHjIBaLIRKJ8MUXX2DM6NEAtFtOW9atCw8PD7Rt0wZ5eXk4HBICNzc3BPj7o3Xr1uUSX3F9P/8cz58/h0gkwoTx4zFw4EAAul8flUe5/29UFGJiYrBw4ULpMm2W4ar2rY7c3Fxs8vZG7169BN8ELCwsxJq1a+Hk5AQ7OzsA2i2/y/P6FRqvqn1qM30TEhLwzz//wMXFBRvWr0dcXBxWrFyJgoICTBg/XuX2mpTPshTVkbqcvlUtXnXpcl59W3Sx/tUkX7zj5IRlS5di3rx5yM3NhUgkQrdu3eTek62r7UltXQe6Gq8sRXWoEJs2bYKlpaXcLAsV/do+f/485s2fj5ycHFhaWsLH2xvm5uYAUCX6+0LoYnlVnt5kvtb0Hsh3o0bhVWYmvhwyBHp6eigsLMTkSZPQp08fpduoOrfaTFdZKSkpuHjpEpYtXarR9kLLq7fZ79XG/Ul1+kf379/H6DFjkJeXB2NjY6xatQrNmzcHoLvtSU3LwevXryMkNBT79u5V+Hddr5dKq3NUqez9BSIioqpKrUESmzdvxqFDh1CnTh24ubnhU5kp0VJTU9GpUyc8ePBA5fcsX74cS5YskVu2ePFi/CDz+ojjYWFY/vPP0s/r1q9X51DL3dhx46T/t2/dGjk5Odi9e7fODJI4fvw4tm/fjjWrV0sHhcTFxSEnJwdTZN5FCLwe/WpfNC360KFDkVT0FPe777yDjRs3CtpfoViMatWqYdnSpdIOQ9706Zgzdy7mzJkDIyMjtY4/LCwMPy9fLv28ccMG9O7VS/rZzs4OdnZ2GDhoECIjI9GpUyf8999/iI+Px0fdu8t9V15eHuLj43Ht2jVM+/576fJ5Hh6ldmIlJDOEdO/eHSOGDwcA2Nvb48bNmwg6dOiN3jS5f/8+RCIRBn/xhdzyvLw86TSC3WSm9+vTpw/meXgI+m5HR0dp5xQAnJyc8OWQITh06BAmTZpUDkevWHJyMtasWQMfb2+Fg6Pu3buH7OzsEu/4y83NRXzRzckhQ4dKl48ePVra8VZHSGgonLt0EfTeclUKCwvRtk0baYevtb09Yh48QFApN2NVXUNisRjx8fFYunQpfpJ5v6tIJJKuP23aNFy7fh0AYN2gAQ4ePCjoeMWFhcjLy8MST0/Y2toCABYtXIhvRo7Eo0ePpFMIyyp+ja5ftw779+/Hnj171JqJQ/ZJkpYtW8LBwQH9+vfHyVOnMHDAAK2mvzrppKhM0uR9m/9ERsLPzw9z58yBg4MD4uLisHrNGvzyyy8YN26cVsvppk2byqWlk5MTEuLjsXffPiz18lI7FiG2b9uG7Oxs3Lp1C94+PmjUuDFcevfWufpIUX4Gylbuh4SEwM7ODg5F02YC2i3DVe1bVmn5uaCgAHM9PCAWizG3aCpbIVasXImYmBj8sn27dFlFuH7ViVfVPrWZvmKxGBYWFpg/bx709fXRpk0bPE1Jwe7du0vcBCyv8lmWojpSV9O3ssdbHnQlrwpRXvWvKrpY/2qSLx48eIDVa9Zg3Lhx6NK5M1JTU7Fh40b8vHw5Fi1ciOzsbJ1qT5Y1XlV0OV5ZiupQVfz9/RF+8iS2+vpK+1CV4dru0KED9u3dixcvXiD48GF4zJsHfz8/1KlTR+f7+1WtvNJGvG86X2t6D+TkqVM4fvw4li1bhhbNmyP63j2sXbsWVlZWSssrVedWm+kq6+jRozA1NcXHRa8tVpfQ8upt9nvLoz9Ylv6Rra0t9u3di8zMTPzxxx/w9PTEtq1b0bx5c51pT5ZH//fVq1dYtHgx5s+bp3Rgga7US5rUOapU9v4CERFRVSV4kMTGjRvh4eGB0aNHIz09HX379oWnpyc8ihozIpFIOvWcKh4eHpgxY4bcMkNDQ+Tk5Uk/d/voI7RzcJB+ziv627O0NLn3Bz579kzp1Fjm5ubQ19fHs2fP5JY/e/YMdYtmpKhbty7y8/Px8uVLudkkZNdRpJ2DA3b88gvy8vKko0XflhPh4Vi6bBlW/N//yb26IDs7G8Drxm+9evXktjEwMAAAbNiwAQUFBQBUz+Yhy9LSElZWVnIjqps1awaxWIynT5+iSZMmasXw0UcfwUEmvRX9cN2oUSOYm5sjLj4enTp1QlZ2Nlq3bq1wRLyFhQWqV68uN7pZSKMX+F++adasmdzyZs2a4XrRDbU3JSsrC/r6+ti9axf09fXl/iaZUl02RhMTE433Vb16ddjb2yMuPl7j7xDi7t27ePbsGb4ZOVK6TCQS4dq1azj422+YNGkSLC0tsdXXt8S2ZmZmMDU1lYtZnSlqJZKSkvD3339j5cqVmgVRjKWlJZoVPSkg0axpU0RERJS6TWnXkCQtF8yfL3dtAK9fGwS8fn+rZFYeyTsZhR6vvr6+9AYvAOkNnOQnTxTe5C1+jZ46dQrPnj9HP5n3mopEIqzfsAG/7t+PI6W8B1aWmZkZbJs0QXxcHAAgKztba+mvTjoJKZOE8PX1Rd++faUzKtjZ2SE7Oxs//fwzxowZo9VyWpF27dppdQpdyTsy7ezskPbsGbZt2waX3r11rj4qnr4WFhZlKvezs7MRHh6OiW5ucsvfRBmubN+ylOVnyQ3A5ORkbNm8WfAsEitWrsSf589j27Ztck/d6fr1q268qvapzfS1rFsX1atXl/veZk2bIi0tDfn5+dLrRlG8ZS2fldWRupq+lT3e8qAreVWI8qp/VdHF+leTfOHn7w8nJyd8W9SubtmyJYyNjTFu/HhMnjRJOnBIV9qTxbcv7+sgKysLgG7GK6GsDi3N7t274R8QgM0+PmjZsqV0eWW4to2NjdG4cWM0btwY7du3x6DBgxESEoLRo0frfH+/qpVX5R3v28jXxQm9B7JxwwaMGjVK+iCPnZ0dkpKS4Ofvr9aPlbLn9k2kq1gsRuiRI+jbt6/a1yygXnn1Nvu95dEfLEv/yMDAAI0bNwYAtGnTBrdv38av+/dj/rx5OtOeLI/+b3x8PBITEzFD5gHHwsJCAMAHnTsjKDBQZ+olTeqc0lSF/gIREVFVJfiuwNatW7F9+3YMLxphOmnSJAwcOBDZ2dnwUvOJVENDQ4UNXtlBEiYmJnKNJbFYjLp16+LKlStoVTTKODMzE1H//osvio1QlTAwMEDr1q1x5e+/paOmCwsL8c+VK9KRnG3atEH16tVx5e+/8UnRzBiPHz1CcnIy2suMMC/uXnQ0atWq9dYHSBw/cUL6pMyHH34o97dmzZqhRo0aSH7yROnTEJq+k9DJ0RGnTp1CVlYWatasCQB4HBsLPT29Eh0eIYqntyJPnjxBeno6LIsGr7S2t8fJkydhYWGhtOMi6aiow8DAAO3ati0x6Cc2Nlbj86Upe3t7iEQiPH/+XOlTGprEqIhIJML9+/flnvTXho4dO2L/r7/KLfPy8oJt06YY9e23SE1LQ1paGvT19dGwYUOF31HWmEOPHIGFhQU+LKdYnZycSuSXx7GxsG7QQPk2Kq4hIyMjWFlZISEhQekTUZpca5LjFYlEiI+PR6NGjQBA+n5IZcdc/BodNGgQunXrJrfO1GnT0LdPH/SX+aFKlaysLMQnJKBv0eC31q1bay391UknIWWSEDk5OahWdFNeQq+oUy8Wi7VaTisSfe+etAzVNnFhofR90bpWHylK37KU+6dOnUJ+fn6Ja/VNlOHK9i1LUbySG4CxsbHY6usraJpRsViMlatW4cyZM9jq6ysdFCOhy9evJvGq2qc209fJyQnHT5xAYWGh9Ie92NhYWFpalrjJXd7ls7I6UlfTt7LHWx50Ja8KUV71ryq6WP9qki9ycnJQvdiPEJJ0EIvF0h+OdKU9WXz78r4O6tatq7PxqqpDlQnYtQs7d+6E96ZNaNu2rdzfKuO1XVhYiLyi9qOu9/erWnlVnvG+rXxdnNB7IDm5udLrQEJfT086K4lQsuf2TaRr5NWriIuLwwBXV7W206S8epv93vLqD2rSX1CkUCxGftH9bV1pT5ZH/7dp06Yl7uVt8fVF1qtXmDlzJurXrw+RSKQT9ZImdU5pqkJ/gYiIqKoSPEji4cOHcHZ2ln52dnZGREQEevbsifz8fEyfPl0bxydVrVo1DPv6a+zcsQONGzdGQxsb+G7ZAksrK3SXmTZu8qRJ+PjjjzH0q68AAMNHjMAST0+0adsW7dq1w/59+5CdnS192szU1BSuAwZg/bp1qFW7NkxMTLB61Sq0d3RE+/btAQDnz51D2rNnaO/ggBqGhvjrr7/g7+cn9yQ88HrgBPB6JOnz589xLzoa1Q0MpO+iUyUrKwtxRU9TA0BCYiKio6NRu3ZtNGjQAN7e3niakgKvoleVHD9+HIs9PTFr5kw4tGuH1NRUAICRkRFMTU1hYmKCb775BmvXroW4sBDvvPMOMjMzcf3GDZiamJQ64v3BgwfIz89HekYGsrKyEF0Um2QaPBcXF+zYsQNLvLzgNmECXrx4gY0bN8K1f3+1X7Wh7Fxs374dn3zyCerWrYv4+Hhs3LQJjRs3RpcuXQC8npZt9549mDlrFia6uaFevXpISk7G6dOn8e3IkUpHuqs6z8Drd+Z5zJuH94qmY7t46RLOnz+vcHRwecSq7HhsbW3Rx8UFiz09Mf3772Fvb4/nL17gyt9/o2XLliUGxsiSpFl2UX6Mjo6GgUx+3L59O9q3b49GjRohMzMTu3bvRnJyMgYOGFDuMcoyMTEp8S5LI2NjmNeuDTs7O7Ro0QLt27fHrFmzMG3aNDRp0gQpKSn488IF9Pj44xI3USTy8/Olr/vJz89HSkoKoqOjUbNmTblOSWFhIY4cOYJ+n3+u1tNjpRn+9dcYM3Ysdvr54bOePREVFYXg4GDMnzdPuk7x61fINeQ2YQJWrV4NU1NTdOnSBfn5+bh9+zYyXr7ENyNGKD2euLg4ZGVlIS0tDTm5udK80Lx5cxgYGKBTp05o3bo1vLy8MGPmTIgLC7Fi5Up88MEHck/Hlcbc3LzETYPq1aujbt26ck/STZo0CR/36IGvigamrV+/Ht26dYO1tTVSUlKwdds26OnpoXfv3gCADzp10lr6C0mn0qSnpyM5ORkpRWWtpMNat25d6QxHixYvRj0rK7gXTSParVs37Nu3D/b29nBo1w5x8fHw9fXFR926QV9fX6vl9L59+9DQxgYtmjdHbm4uQkJC8M8//8B70yaVsapbHx08eBANGjSQpv3Va9ewZ+9efFVUF1eE+khIuV88fSVCQkPRvXv3EteENstwVfsuTUFBAX6cMwfRd+9i3bp1EIlE0jZE7dq1pTeZil+/K1aswPETJ7Bm9WrUrFlTuo2pqSmMjIx09vrVNF5V+9Rm+n7xxRc4+NtvWL1mDb4aOhRxcXHw8/eXXlOl0bR8BkqvI3U1fatavMq8rfZkWfKqUJrUv6rSQRfrX03akx9164ZlP/2EwMBAdO7cGalpaVi7Zg3atWsnfWpSV9uTmsQLqM6TuhqvqjoUKJmP/QMCsHXrVixbtgzW1tbSbWrWrImaNWtW6Gs7OzsbO3fuxEcffQRLS0u8ePECB3/7DSkpKehZ9PBKRezvV5Xyqizxvs18rek9kG4ffoidfn5o0KABmjdvjujoaOzdtw+uMoMPipdXqs6tNtNVIiQkBA4ODiXuv6iiSXn1Nvu95dEf1LS/4O3tDWdnZzRo0ABZWVk4fvw4IiMjsakonXW5Palu/9fQ0LBEXjIrGsAmWa6r9ZKQOgeo/P0FIiIiKqmaWODQ5yZNmmDv3r0lntS6ffs2PvnkE/Tu3Rt79uyBSCTS+GDSX74s9e9isRjbtm5FcHAwMl++hNM77+DHOXPkbkoM6N8fn/frhwky004fPHAAe3bvRlpaGlq1aoWZs2fLTbuVm5uLDevXI/zECeTl5aFzly74cc4caafu0sWL8PH2Rnx8PMRiMRo1bowvvvgCAwcNkhtN3qlDhxLHbG1tjZAjR0osr21mhpcZGXLL/omMxMSJE0us2+/zz+Hp6QlPT08kJiVh29atAIAJbm64evWq0vUl52z//v0IDApCQkICzMzM0NreHqNHj8Z7772n8DwDQH9XVyQlJZVY/s+VK9L/P3r0CCtXrcKNGzdgXrs2evbsiUmTJinshJjVqlUi3tLk5ORg1uzZiI6OxsuXL2FlZYXOH3yAiRMnyr0GJTU1FZu8vXHhwgVkZWXBysoKnTp2xPfff6/0aRNV51kiJDQU/v7+ePr0KWybNMEENzd8XOx9qMqoE6+q4ykoKMCOHTvw+7FjePr0KczNzdHewQFubm6ldnY7dOxYYpm1tbV02uk1a9fi9OnTSEtLQy0zM7Ru0waTJk1C62IdayHUTd/iJri5wb5VK8wsmrbv1atX2LxlCyIiIvD8+XPUrVsX7737LqZMmSK9sVVcYmIiXBXc3Hjvvfek1wwAXL58Ge5TpyIoMFDwgIDiFMV7/vx5ePv4IC4uDg0bNsSI4cMxaNAg6d+LX7+AsGvo+PHj2LV7Nx4+fAhjY2PYtWiBr7/+Gj169FB6fMrKhtCQEOno9pSUFKxctQp//fUXjI2M4OzsjOnTp0vfE6kqXkX6u7ri62HDpDMOSZb169cPbhMmAAA85s3DtWvXkJ6eDgsLCzg5OWHK5MnSJ/IA7aa/qnQqLd4jR45giYKZk8aPHy+Nb4KbGxpaW0vLkoKCAuz088OxY8eQkpICc3NzfNStGyZPnix9xZO2yumAXbsQHByMlJQUGBkZwc7ODuPHjUOHYnWVonjVrY/2HziAQ4cOITExEfr6+mjUqBEGDRyIwYMHyz3Rquv1kapyv3j6Svb95ZAh8Pb2RmeZV15JaKsMF7JvZfEqu16A11Pldih6uqv49avomABg8aJF0if2dfH61TReIfvUZvrevHkTa9etw71792BlZYUBAwZg1Lffyk0xW57lM6C6jtTF9GW8r72t9iQgLK8KUZ71r5B00MX6V5P25P4DB3AoKAgJiYkwMzNDxw4dMHXqVLmnZ3W1PalJvELypC7GK6QOLZ6PleU12byvK9e2uv3B3NxcLFiwAP9GReHFixeoXbs22rZti7FjxqBdu3bS9Spaf78qlVeaxvs287XQeyDF43316hV8fX1x+swZPH/+HJaWlujduzfGjxsn/fG8eHkl5Nxqs3+UmZmJ3i4umDVzZon2RXHlUV69zX4vUPb+oKb9Ba+lS3HlyhWkpqbC1NQULe3s8O2oUXJ9M11uT2rS/5Xl6emJl5mZWLN6tXTZ266XFMUrtM6pqP0FIiIi0pzgQRLDhw9H/fr1sW7duhJ/i4qKQo8ePZCWlqbVQRKViaJBEpVZWX9Er2gYb+XGeCs3xlu5Md7KjfFWboy3cmO8lRvjrdwYb+XGeCs3xlu5Md7KjYMkiIiIykbwXPMeHh6IjIxU+Ld27dohIiICQUFB5XZgREREREREREREREREREREROVJ8CAJJycndOzYEfn5+Rg2bJh0ujQJBwcHuVdYEBEREREREREREREREREREekSPaErnj17Fg4ODpg5cyasra0xatQonD9/XpvHRkRERERERERERERERERERFRuBA+S6NatG3bs2IGkpCRs2rQJjx49Qvfu3dGqVSusWLECycnJ2jxOIiIiIiIiIiIiIiIiIiIiojIRPEhCwsTEBKNHj8bZs2dx7949DBkyBD4+PmjSpAlcXV21cYxEREREREREREREREREREREZab2IAlZdnZ2mDdvHhYsWAAzMzP8/vvv5XVcREREREREREREREREREREROWquqYbnjt3Djt37kRQUBD09PQwdOhQjB07tjyPjYiIiIiIiIiIiIiIiIiIiKjcqDVIIjExEf7+/vD398f9+/fh7OyMjRs3YujQoTAxMdHWMRIRERERERERERERERERERGVmeBBEn369MGpU6dgaWmJb7/9FmPGjIG9vb02j42IiIiIiIiIiIiIiIiIiIio3AgeJGFgYIDAwED069cP+vr62jwmIiIiIiIiIiIiIiIiIiIionIneJBEaGioNo+DiIiIiIiIiIiIiIiIiIiISKv03vYBEBEREREREREREREREREREb0JHCRBREREREREREREREREREREVQIHSRAREREREREREREREREREVGVwEESREREREREREREREREREREVCVwkAQRERERERERERERERERERFVCRwkQURERERERERERERERERERFUCB0kQERERERERERERERERERFRlcBBEkRERERERERERERERERERFQlcJAEERERERERERERERERERERVQkcJEFERERERERERERERERERERVAgdJEBERERERERERERERERERUZXAQRJERERERERERERERERERERUJXCQBBEREREREREREREREREREVUJ1cRisfhtHwQRERERERERERERERERERGRtlV/2wcgKy09420fwhtTt3YtvMyoOvGa1WK8lRnjrdwYb+XGeCs3xlu5Md7KjfFWboy3cmO8lRvjrdwYb+XGeCs3xlu5mdWq9bYPgYiIKhm+boOIiIiIiIiIiIiIiIiIiIiqBA6SICIiIiIiIiIiIiIiIiIioiqBgySIiIiIiIiIiIiIiIiIiIioSuAgCSIiIiIiIiIiIiIiIiIiIqoSOEiCiIiIiIiIiIiIiIiIiIiIqgQOkiAiIiIiIiIiIiIiIiIiIqIqgYMkiIiIiIiIiIiIiIiIiIiIqErgIAkiIiIiIiIiIiIiIiIiIiKqEjhIgoiIiIiIiIiIiIiIiIiIiKoEDpIgIiIiIiIiIiIiIiIiIiKiKoGDJIiIiIiIiIiIiIiIiIiIiKhK4CAJIiIiIiIiIiIiIiIiIiIiqhI4SIKIiIiIiIiIiIiIiIiIiIiqBA6SICIiIiIiIiIiIiIiIiIioiqBgySIiIiIiIiIiIiIiIiIiIioSuAgCSIiIiIiIiIiIiIiIiIiIqoSOEiCiIiIiIiIiIiIiIiIiIiIqgQOkiAiIiIiIiIiIiIiIiIiIqIqocyDJJ48eYLk5OTyOBYiIiIiIiIiIiIiIiIiIiIirRE8SOLZs2f48ssv0aRJE0yaNAkikQjjxo2DtbU1bGxs4OzsjKSkJG0eKxEREREREREREREREREREZHGBA+SmD17NqKjo/Hjjz/izp07+OKLL3DlyhWcP38ef/75JwoKCjB37lxtHisRERERERERERERERERERGRxqoLXTEsLAyBgYFwdnbGkCFDYG1tjRMnTqBr164AgHXr1uGrr77S2oESERERERERERERERERERERlYXgmSTS09NhY2MDAKhfvz6qV68Oa2tr6d8bNmyIFy9elPsBEhEREREREREREREREREREZUHwTNJtGzZEkePHsWUKVMQFhYGIyMjhIeHw8HBAQBw4sQJNGvWTGsHCgBisRi/bNuK0MOH8TIzE46Ojpg9Zy4aN2lS6nZBvx3E3j178CwtDXYtW2LGrNlo266d9O+5ubnYtGE9ToWfRH5+Hj7o3BmzfpyDOnXrStf55++/sW2rLx7ExMDIyAh9Pu8Ht0mTUL16yVMYHxeH70Z+Az09PYRHnBYUm5+fH06fPo1Hjx/D0NAQjo6OmOrujqZNmyrdJiYmBr5bt+Lu3btISkrCjB9+wPDhwwXtrzS5ublYvnw57ty9i0ePHuHDDz/EmtWr5db5JzISEydOLLHt8bAwWFpaCt6Xp6cnjv7+u9yyLp07Y9OmTUq3uXr1Knbv3o07d+8iNTUVq1etwscffyx4n8qkpqZi3fr1uHPnDuLi4jDsq68wc+bMEuu9fPkSmzdvRsTp08jIyIC1tTVmzJiBD4tmVVHm1atX8PX1xekzZ/D8+XPYt2qFmTNnop1MXiwuLCwMu3bvRmxsLExNTeHs7Izvp02Dubl5mWJdtXo1bty4gZiYGDRr2hT79u0rsY5YLMaePXsQfPgwkpKSYG5uji+//BJjx4wRtI+CggJs3rIFFy5cQEJCAkxNTdGpUydMdXeHlZWV0u1EIhG2bduGsOPHkZaWBktLS/Tv1w9jx45FtWrVNI5ZaPru27cPgUFBePLkCcxr18Ynn34K9ylTYGhoqHIfmuRnAHj69Ck2bdqEi5cuIScnB40aNcLiRYvQtm1b9YKUoc14NSmvAM2vndIIKa8AIC8vD9t/+QVhYWHSfDVu3DgMcHUVtJ+Kmp/Les4fPnyIjZs24erVqxCJRGjerBlWrlyJBg0aKFw/ODgYvx87hpiYGABAm9atMXnKFDiUUs4Joe141a1XhB6PJlSVz4mJiXAdMKDEdn47d6J9+/Zq78/f3x/ePj74etgwpTEUFBTAz88PR3//HSkpKbC1tcVUd3c4OzurvT9ZQq5fReUqADRv1gwHDx4UvK+t27YhPDwcT548gYGBweu8OXmytB2rSEW9fstSp1y/cQNubm5o0by5wraBOt5U+VyVrl9N6t+IiAj4+fsjLi4OBQUFaNK4MUZ88w0+79tX7fhkCTmPR44cwRIvL7llNWrUwMULF9TaV0REBIIOHcLdu3eRnp6OvXv2wN7evtRt3mZ9pGnc/V1dkZSUVGL5kC+/xJw5cxRuU5HbVhKatJ+3btuG7du3yy2ztbVFUGCgWvsuTkj/WpN0UqWi1jdCaHL9yjoRHo758+eje/fuCvOhOrRdbmnaX5AlpF0mlND7RZq0G9S9Bt9mXQSUbx5Xt39U3vuX0HZZrW77qrzuERb3pu5PVtX+vjIdOnZUuHzatGn4duRIjb9XaL7S5DorTVVMX036vxX1fjsREVFZCB4kMXv2bIwaNQrr169HXFwc9uzZg++//x5//fUX9PT0cOjQIaxdu1abx4o9u3bhtwMHsGCxJxo2bIhtW33xw7Sp2HvgoNIf9E6dDMfG9esxe+5ctGvngAP7f8UP06bi198CUadOHQDAxnXrcPHCn1i2fDlMTU2xZtUqeMz5EVt/2QEA+O/ePcz8YTpGjR6NRZ5LkJLyFCv/7/9QWCjC1O+ny+2voKAAixbMh9M77+DWzZuCY7t69SqGDBmCtm3bQiQSwWfzZrhPnYrfDh6EsbGxwm1ycnLQyMYGPXv2LNdzX1hYCEMjIwz76itERESUum5QYCBMTEyknyXnVB3OXbpg0aJF0s81atQodf3s7Gy0bNUKrq6umP3jj2rvT5m8vDxYmJtjzJgxSn8YyM/Px5QpU2BRpw5WrFiBelZWSEpKgpmZmcrvX7ZsGWJiYuC1ZAmsrKxwLCwMk6dMwW8HD6JevXol1r9+4wYWe3pixg8/oFu3bkhJScHPy5fjp59+wqpVq8ocr2v//vg3Kgr3//tP4d9Xr1mDy5cv4/tp02BnZ4eMjAykZ2QI/v6cnBzcvXsX48aORcuWLfHy5UusXrMGM2bOxO5du5RuF7BrFwKDgrDE0xPNmzfH7Tt34OXlBVNTUwwbNkztOCWEpO/x48fh7eODRQsXwtHREbGxsfBcsgTVqlXDjB9+ELQfdfNzRkYGxo4bhw7vv48NGzbAwtwccXFxqFWrlvDgFNBmvJqUV2W5dkojtLya6+GBZ8+eYeGCBWjcuDFSU1NRKBYL3k9FzM9lPefx8fEYN348XF1d4ebmBlMTE8TExJSapyMjI9G7Vy84OjrC0NAQAQEBcHd3x8EDBxSWc0JpO1516xUhx1MWqspnANjs44PmzZtLP2syeC4qKgqHgoPRsmXLUtfbvGULwsLCMH/+fDS1tcXly5cx+8cfsWPHDrRW44eO4oRcv7NmzYK7u7v0s0gkwvARI/Bpz55q7cu2SRP8OHs2bGxskJubi32//oop7u44HBwMCwsLhdtUxOu3LHXKy5cvsXjxYnTs2BHP0tI0ik3Wmyqfq9L1q0n9W6t2bYwZPRpNmzaFgYEBzp8/Dy8vL9SxsECXLl3Uik2W0PNoYmIi96OZJjeUs3Ny8I6TEz7r2RPLfvpJ0DZvsz4CNIt7V0AARCKR9HNMTAymuLsrLe8qettKlrrtZwBo3rw5Nvv4SD8renhBXUL61+qmkxAVsb4RSpPrVyIxMREbNmzAu+++Wy7Hou1yS9P+goTQdplQQvJzWdoN6lyDb7MuKs88rkn/qKKW1ZredyuPe4Sy3tT9yarY3y/N8bAwuc8XL17E0mXL8EmPHmX6XiH5SpPrTJWqmL6a9H8r6v12IiKishB8J2HEiBFo2rQpLl++jC5dusDZ2Rlt27bF//3f/yErKwvbtm3DqFGjtHagYrEYB/f/iu/GjMFH3bsDABZ5LkE/l9449//s3XVYVEsDBvCX7sZASkrS7u7ua+u1Ua96scDA7u7GRrAQu7uvn9euq2AXIN0N+/2xsLDAUi6hvr/n2Ydnd+ccZnZmzpk5Z87MjRto3aZNjtsd3L8fXbp1Q6fOwlHSU6a54p87d3D61EkMGjwE0dHROHXyBOYuWCgaKTtj9mz0790LL54/h0Plyrhy+RIsLC0xzHEEAMDI2BhjnZwwc/p0DHMcIdYId9uyBaYVK6JW7doFGiSR9UmZuXPmoHWbNnj16hVq1KiR4zb29vaiWQg2btyYY5jU1FS4u7vj2PHjCAkJgYmJCYYPH45WLVtKjIuKigpcp00DADx9+hRR0dESw+rq6v5wg0VBUbFAI8sbNmyIhnmMIk1MTMTmzZtx4eJFREVFwcLCAk5OTqhVs6bEbSpUqAAXFxcAwMmTJ3MMc+LkSURERmLXrl2iiwAVKlTIM87x8fG4eu0aVq1cKcrPUSNH4tatW/A+cgRjRo/Ots3zZ89gYGAgangbGhrijz/+wN4sDfjjx4/Dc98++Pn5CcP36YNevXrlGp/JaekM27Ytx4v4Hz58gLe3Nw4dPCh6OjF9uZ38UldXF7toAgBTJk/G4CFDEBAQIHEE+LNnz9C0aVM0atQIgPD3vXDhAl6+fCkKU1T5+/TZM1StUgXt2rUTbdO2TRu8yPS/81LQ8uzu7o5y5cphzpw5os+y/talLb2FOV7lp+4U1fHqn3/+waNHj3Di+HFoaWnl+L/z8jOW58Ier9Jt2rxZNHtNOiMjo1y3Wbhwodj7mTNn4uq1a/j3/n106tgRQOlMb37OKwWND1A0x+d0WlpaP/RUVmxsLGbNno0Z06dj565duYY9e/Yshg0dKnqCo2fPnrj377/Y5+mJBQsWACi6+quurg51dXXR++vXryMyMhJdOncuUHrTj3PpJk6YgBMnTuDNmzeoU6dOjtv8jPU3P+cUSRYvWYJ2bdtCVk4ON65fF/uuNB+ff6f6W5jzb9ay2K9fP5w+cwZPnjwR3ZgqqnIMCG8u/sixCoDoSWM/P798b1OS5yOgcOnOesHa3d0dRkZGqPmLtq0yK2j7GQDk5eRy3SYqKgpr163DjRs3kJSUBFtbW0yaOBGVKlWSuE1++tcFzaf8+BnPN/lVmPoLCAdFzpw1CyNHjsSTx4+zlcPSVn+BwvcXgLzbZUVVnn+k3ZBXHcysJM9F0izjhekf/azH6oK2r9Lldo2wNF+f/B37+7nJWrdv3LyJWjVripX3gIAArF23Dv/73/8gKyuLatWqwcXZOdc45KdcFaae5eV3zN/C9H9/xuvtREREP0q2IIEbNmwIZ2dn0fTKdnZ22Lt3L7y9vYt0gAQA+Pl9Q0hICGplOpGrq6vDzt4eL57nPBghKSkJPq9fo1btjG1kZWVRu3YdvHj+HADw+tUrJCcno3am/VasWBHlypcXhUlMTISSovhMFUpKSkhMSIDP69eizx7cv49rVy7DZfKPj7aMTmv4/+jT5Lv37MGZs2fhOm0aDh08iP79+mH27Nl4+PDhD8cRAPoPGIC27dphzNixePL0aaH28fDhQ7Ru0wZ/9OiBJUuXIjw8/IfjtXz5cjx7/hyLFy3CwQMH0KplS4wbNw6fP3/+of3evHkTVSpXxrJly9CmbVv07tMHu3bvFnuaKCcpKSlISUnJNvJZSUkJT548yXGbylWq4Pv377h95w4EAgFCQkJw9coVNMw0vfm5c+ew1c0NY0aPxmEvL4wdMwZb3dxw+vTpH0vnrVswNDTE7du30aVrV3Tu0gULFi5ERETED+03OjoaMjIyYje8sqpSpQru37+PT58+AQB8fX3x9OlTsWndiyp/q1apglevX4sGCXz9+hV3/vmnQBcHClqeb966BVtbW0ydNg2t27RB/wEDcOzYMbEwpTm9QP6OV/mpO0V1vLp58ybsbG2xd+9etO/QAX/06IG1a9ciPj7+h/Zb2stzYY9XgPAC1p07d2BqYoK/nZzQuk0bDB4yBNez3DjNS3x8PJKTk6GVqWyUxvQWhaI6Pqeb5OyM1m3aYLijI27cuFHg7ZctX46GDRuibt26eYZNSkqCYpYZu5SVlMTO+0Xd3kh34sQJ1KlTBwYGBoXeR1JSEo4dOwZ1dfVcby78jPU3P+eUnJw8eRLfvn3DiBEjcvz+Zzs+/6jSXn/TFbS/IBAI8O+//+LTp0+onumGblGVY0D4RFqnzp3RsWNHTHJ2Fi1/UdyK83wE/Hi6k5KScPbcOXTp0kXiU+y/UtuqMP3Bz1++oF379ujatStmzpyJgIAAse+nTpuG0NBQrF+3Dh5798LG2hqjx4z54f5MZvnJp/z4Gc83RW3Hjh3Q1dVFtxyWKAJKd/3NLD/9BSDvdllRlefCthuAvOugJMV9LpJWGS9s/+hXOlbnR27XCH+G65OZ/cr9/YIICQnB7du30TXT8Tg5ORlO48ZBVVUVO7Zvx84dO6CqogKnceOQlJRU6P8lresQ+fE75W9++7/58TOkl4iIqCB+fE7KQkhISEBCQoLYZ5KWy0iXPu2vrq6e2Oe6unoSpwQODw9HSkpKtinWdHV18enTR9F+FRQUso021tXVRUjafuvWqw+vgwdx8cIFtGzVCqEhIdiVthRHcHAwACAiPByL5s/D7HnzoZZHBzgvqampWLV6NapWrQpLS8tC7ycxMRG7d+/G5k2bUKVKFQDC0bdPnj7F0WPHUDOXUZ550dfTg6urK+xsbZGYmIjjJ05g1KhRcN+zBzY2NvneT/0GDdC8eXMYGhri69ev2LR5M8aNH4/du3ZBTk6uUHELCAjAqdOncfrUKdHacgMHDsTdu3dx6tQpjB07tlD7BYBv377hwYMHaNeuHdalLT2zbPlyJCcnY6SEGwuAcMrOKpUrY8fOnTAzM4Ouri4uXLiA58+fSxwRXa1qVSxcsADTp09HQkICUlJS0LhxY7G1bt22bcOECRPQokULAMKnPt5/+ICjR4+iU6dOP5TOgIAAXL5yBfPmzkVKaipWr16NqdOmYeuWLYXaZ0JCAjZs3Ii2bdrk2gkZMngwYqKj0bNXL8jKyiI1NRVjRo9G+/btARRt/rZr1w7h4eFwdHSEQCBASkoKevTogWFDh+Zr+8KU52/fvuHIkSMY0L8/hg4div9evsTKVaugoKCATp06ler0Avk/XuVVd4ryePXt2zc8efoUikpKWLFiBcLDw7Fs2TJERESIPTVVED9DeS7s8QoAQkNDERsbiz3u7hg9ejSc/v4bd+/exeQpU7B1y5Z858eGDRugr68velKhtKa3KBTV8VlVVRUTJkxAtapVISMjg6tXr8Jl8mSsXLECTdNm2srLhYsX8fr1a+x1d89X+Hr16mH/vn2oUb06jIyM8O/9+7h67RpSU1MBFG17I7OgoCD8c/cuFqbNXlFQt27dwvQZMxAfHw99fX1s2rgx12UOfsb6m9c5JSefP3/Gxk2bsH3bthynyv7Zjs/SUJrrb7qC9Beio6PRvkMHJCYmQk5ODlOnTkW9tBtxRVmOTU1NMWvWLFhZWiI6Ohqenp4YNnw4vA4dQrly5Qq938IozvORNNJ9/fp1REdHo3Mu5e1XaVsVpv3sYG+PuXPmwNTUFMHBwdi+fTscR4zAoYMHoaamhidPnuDly5e4dPGiaJD6hAkTcP3GDVy5cgV//PFHodOeWX7yKT9+xvNNUXry5AlOnDyJ/fv25fh9aa+/6fLbX8irXVaU5bkw7QYg7zqYk5I6F0mrjBe2f/SrHKvzktc1wp/h+mRmv3p/vyBOnzkDNTU1NM+01MbFixeRmpqKWTNnigYJzpkzB82aN8fDhw9Rr169Qv0vaV2HyMvvkr8F7f/mpbSnl4iIqDAKNEhi8+bNOHr0KHR1dTFq1Ci0zDQlWnBwMOrUqYP379/nuZ8lS5Zg3rx5Yp/NmTMHThMnid5fOH8Oy5csEb1fuWZNQaIqVXXr1cNYp3FYsXQJFsydAwUFBQwZPhxPnzyGrKywMbh08SK0bttWbCR8YS1bvhzv3r3Dju3bf2g/X758QXx8PMZmWssbEI4gtU5bQ7x3797wTxvxX71aNaxfvz5f+65YsaJoGQYAqFq1Kr59/Yp9+/djwfz5OW5z7tw5LM6Up+vXrUPbTMukWFpawtLSEt26d8fDhw8lTv+Vl7dv3yIlJQV/9Ogh9nliYqJoisHGTZqIPm/fvj2mu7rma98CgQA6OjqYMX065OTkYGtri8CgIHh4eOTZaJs/fz7mz5+P9h06QE5ODtbW1mjbpg1eZZqNJLP3799j5apVcHR0RP169RAcHIx169dj8ZIlmD1rFuLi4vD161csWLAAizKt75qSkiJq5I8bNw6P02aqMChfHl5eXvlLZ2oqEhMTMW/uXJiamgIAZs+ahT8HDsTHjx/F8j5dTvmbvn5scnIyprm6QiAQYFraVImSXLp8GefPn8fChQthYW4OH19frF69GmXKlEGnTp2KNH8fPHyI3bt3Y9rUqXBwcMCXL1+wctUq7NixA46OjnmmtzDlOTU1FXa2tqLOhI21Nd69f48jaTdiSkt6Jcnv8SqvulOUx6tUgQAyMjJYuGCBqG4kTpiAqdOmYerUqVBWVs62za9QngtyvMqa3rVp59ymTZtiQP/+AABra2s8ffYMR44ezdfFiT179uDipUtw27pVNBCytKS3qBXl8VlbWxt/Dhggem9vb4+g4GB4eHrm6yZrQEAAVq1ahU0bN+Y5QDWdi7MzFi5ahJ69ekFGRgaGhobo0rkzTp46BaBo2xuZnT59Gurq6mjWrFmu4STV31q1amH/vn0IDw/HsePH4Tp9Ovbs3i1xveKfpf5mltc5JauUlBTMnDkTI0eOFJ3vsyptx+eiVprrb2YF6S+oqqpi/759iI2Nxf3797FmzRoYGhqiVs2aRVqOq1SpIroRAgj7Cz179cLRo0cxOoel5oDcz7+FVdzno8KkO6sTJ0+iQf36ogvQOfnZ2laA9NrPmWc9s7KygoODAzp17oxLly+jW9eu8PX1RVxcHFq2aiW2XUJCAr6mDQbv1bu36POhQ4cWaJBwuvzkU378jOebnEij/sbExGD2nDmYMX26xBs5paX+SqO/kJ92WVGW54K2G9LlVQdzUlLnosKWcWn1j37GY3Vh5HWN8Ge4Pvkr9/dzk9ex++TJk2jXrp3YMerNmzf4+vWraDnszOn6+vUrHj9+jHHjx4s+n+7qKhpYkFeagB+7DpFXmn7F/JVW/zcvpSW9RERE0pTvQRLr16+Hq6srhg4dioiICHTo0AFz586Fa9rJLiUlRTT9VF5cXV0xadIksc+UlJQQHZ8xu0Sjxk1gb+8gep+YmAgACA0NEVsbLTQ0BFYSporS1taGnJwcQkNDxT4PDQ2Frp5wRgpdPT0kJSUhKipKbDaJ0NBQ6OllzFrRb8AA9O3fH8HBwdDU0IC/vz+2btqECmnrNT588AC3b93CgbSnHQQCAVJTU9G4fj1MdZ2OTl265Ou3WbZ8OW7fuoVt27b98BNWcXFxAISdubJly4p9p6CgAABYt24dkpOTAeQ9m0de7O3tc53SrkmTJnBwyMjTnC4mGRkZQVtbG1++fi30IInY2FjIycnBY+/ebE8fqaioAIDYUymSnnTIib6eHuTl5cX2a1axIkJCQpCUlCT6XXNiZGSEbdu2IS4uDjExMdDX14erq6vENT9379mDqlWrYtDAgQCEFx9UVFTgOGIExoweLRqtPXPGDLHfFRAuKwMI119On7Ulp6dDJaZTXx9ycnJiN0zSO50B37/nOEhCUv6md0ACAgKwZfPmPKcaXb9uHQYPHiy6YGppaQl/f3/s3rMHnTp1KtL83bp1Kzp06IBu3bqJ/ndcXBwWLV6MYcOGiX7X3NKbWX7Ks76+PszMzcU+M6tYEVevXgVQtOW5IOnNSUGOV3nVnaI8Xunr66NMmTJiZc/MzAwCgQCBgYEwMTHJts2vUJ4LcrzKml4dHR3IycnBzMxMbJ9mZmYSlwjKzMPDA3vc3bF50yZYWVmJPi8t6S1qsbGxAIrm+JwTB3t73Lt3L19hX79+jdDQUPyZdm4BhG24x48fw+vwYfxz5062vNHR0cGqlSuRkJCAiIgIlClTBhs2boRh2hqhxdHeEAgEOHnqFDp06JBnXkqqvyoqKjA2NoaxsTEqV66M7n/8gRMnTmCohBsJP0v9Fdsuj3NKVrGxsfjv1Sv4+PpixYoVAIQ3TAQCAerWq4eNGzaI0lJajs9FrTTX33QF7S/IysrC2NgYgPBC84ePH7Fnzx7UqlmzSMtxVvLy8rC2tsaXr18lhslP+6ogSuJ8lFV+0p2Zv78//v33XyxfvjzXcD9b2woouv6ghoYGTE1M8PXLFwBAbFwc9PX14bZ1a45h1dXVxfK3MEtc5jef8uNnPN/kRBr19+vXr/Dz88MkZ2fRZ+kzV9WtVw9HvL1LTf2VRn8hP+2yoizPBW03SJK1DuakpM5FhS3j0uof/YzHamnJfI3wZ7k++av293OT27H78ePH+PTpE5YsXiy2TWxcHGxsbHKc4U9HRwfy8vJi6crvTfn06/iFvQ6R7nfLX2n1f/NSWtJLREQkTfm+qufm5obt27ejf9pIztGjR6Nbt26Ii4vDfAkjcyVRUlLKscGbeZCEmpqa2MlUIBBAT08PD+7fR6VKwlHGMdHR+O/lS3Tv0TPH/6OgoABrGxs8vH8fTdOeOkxNTcWDB/fRo1cvAICNrS3k5eXx4P59NE+bUvfTp4/4HhAAh8qVxfYnIyMjamhcungB5cqVg7W1cOq2bTt3ISU1Y52sWzduwtNjL9x27ECZMuIdgJwIBAIsX7EC169fh9vWrRJvnBeEmZkZFBUVEfD9u8TRtj+ypndWPr6+0M80sCSrrHmak+/fvyMiIiLX/eTF2toaKSkpCAsLk/jkSnrnvKCqVq2K8xcuIDU1VXSh/PPnz9DX1893g01FRQUqKiqIjIzE3f/9D+OcnHIMFx8fD/ksjc70/ykQCEQd3m/fvkkckZ2185lfVatWRUpKCr5+/SpaDiR9fTmD8uVz3Can/E3vgHz+/BluW7fma1q3+ISEbDfn5WRlRSPKizJ/4+PjIZPlf8um5UH6/08nrfJctWrVbAPMPn3+LPqdS0t6MyvM8SqvulOUx6uqVarg8uXLiI2NhaqqKgDhbywrKyuxjvwK5bkgx6uc0mtvZ5etbH7+/DnPfHDfuxe7du3Cxg0bYGdnJ/ZdaUlvUdPT0yuy43NOfH19xQaQ5qZ27do4eOCA2Gfz58+HacWKGDxoUK5LXSkpKaFs2bJITk7G1atX0TrticbiaG88fPQIX758Qdd8DDrNz/EZELYJE3NZM/dnqb9Zt8vtnJKVmppatvLg7e2N+w8eYNnSpTA0NERqamqpOj4XtdJcf6XVX0hNmzEMKNpynFVKSgrevn0r9gRyVvmtv/lRUuejrPKT7sxOnjoFHR0dNMoj/M/WtgKKrj8YGxuLr9++oUNaXbKxsUFISAjk5ORQIW1AX1Y/mr/5zaf8+BnPNzmRRv2tWLFitvPSlq1bERsTA2dnZ5QrVw4pKSmlov5Ko7+Qn3ZZUZbngrYbJMlaB/OjuM5FhS3j0uof/YzHamnJfI3wZ7g++Sv393OT27H7xIkTsLW1RaUsDyfaWFvj0qVL0NHRkTjQoDDpUlBQKPR1iMx+t/yVVv83L6UlvURERNKU70ESHz58QIMGDUTvGzRogKtXr6JVq1ZISkrChAkTiiJ+IjIyMujdtx/cd+2CsbExKlQwxLatW6Gvry82vZfTmNFo2qw5eqZNN9i3f38snDcPNra2sLO3x6GDBxAfF4dOnToDANTV1dG5S1esX7sGmpqaUFNTw+qVK+BQubLYIIl9Hh6oV78+ZGRkcOP6NXi4u2PB4iWimwkVs4xyff3qFWRlZGBhkfsawemWLVuG8xcuYNXKlVBVVUVwcLAofulT4M2eMwdly5TB32nT0yUlJYmWN0lKSkJQUBB8fHygqqoKY2NjqKmp4c8//8Tq1ashSE1FtWrVEB0djSdPn0JdTS3X6RPfv3+PpKQkRERGIjY2Fj4+PgAgmgZv//79qGBoCAtzcyQkJODEiRN48OABNm7YkK/0AsKO9Pbt29GiRQvo6enh69evWL9hA4yNjVG/fn1RuNGjR6NZ8+bok5ansbGx+JLpCYVvfn7w8fGBlpYWypcvD1NTU7Rv1w5z5s7FhPHjYW1tjbDwcNz/919YWVmhUaNGEuOUns64uDiEhYXBx8cHCgoKME97uqJHjx7wOnwYK1etQp/evfHlyxfs3rMHffr0yTO9d+/ehUAggKmpKb58/Yr169ahYsWK6JJ2w2fjxo0IDArC/LSlaJo0boyFixbB29sb9erVQ3BICFavWgV7e3vRYJ1RI0dixcqVUFdXR/369ZGUlIT//vsPkVFRYtM5Z/XlyxfExsYiJCQE8QkJonSbm5tDQUEBderUgY2NDebPn49Jzs4QpKZi2fLlqFu3rsTpuLNKTk7GlKlT4fP6NdasWYOUlBRRudbS0hI1crPmb+NGjbBr926UL18e5ubm8PHxwb79+0W/U1Hmb+PGjbF//35YW1vDwd4eX75+xdatW9GkceNcbxwChS/P/fv1w7Dhw7Fr9260btUKL1++xLFjxzBj+vRSm97CHK/yqjtFebxq164ddu7ciXnz52PUyJEIDw/H+vXr0aVz53xPMfozlucfOV4BwrUlXadPR420aRr/uXsXt27dEnuKLWs+73F3h5ubGxYuXAgDAwPRb6SqqgpVVdVSm968zitZj8/5iU9RHZ9Pnz4NeQUF2KSV76vXruHkqVOYOWNGnukEhHXN0lK8baKsogJtLS3R51nz9cWLFwgMDESlSpUQFBSEbdu2QZCaikGDBon2WVT1N92JEyfg4OCQLe75ERcXh127dqFJkybQ19dHeHg4vA4fRlBQEFplWjruV6i/eZ1TAPH2hqysbLbfVEdXF0qKimKfl+bj8+9Ufwtz/t29ezds7exgZGiIpKQk3LlzB2fPnoVr2vTCRVmOt2/fjsqVK8PIyAjR0dHY6+GBgIAAiVOxSxIREYGAgAAEpaU3/cK5np6eaIBJaTof/Ui6U1NTcerUKXTq2DHbLCW/WtsKKHz7ee3atWjcuDEMDAwQFBQEt23bICsri7Zt2wIA6tapg8qVK8PFxQXjxo2DiYkJgoKCcPvOHTRv1izboJl0efWv85NPhfEznm/yq6D1V0lJKdt5SSPtBlz656W1/hamv5CfdllRluf8tBtyklcdLE3nImmW8cL0j37WY3VB21d5XSMs7dcnf8f+fl6io6Nx+cqVHK/3t2/fHh6ennB2ccFfo0ahbNmy8A8IwLVr1zBo4ECJM53lVa6A/NWzgvrd8rew/d+f9Xo7ERHRj5AR5Pa4cCYmJibYt28fGjduLPb5f//9hxYtWqBt27bw9PRESkqKhD3kLSQiMtfvBQIBdmxzw4ljxxAdHY0qVavCZcpUmGS6aftH1y7o0LETHEeOFH3m7eWFfZ4eCA0RLs0x0dkF9pmmoUpISMCGdWtx6eJFJCUmom69enCZMhV6mUbB/z16NHx9XiMxKQlWVlYY5uiI+g0kPzVy5vQprFu9GhevXsvxez0tTURFZqS3Vu3aOYabM3s2OncWDugYOWoUKhgYYO7cuQAAPz8/dMmhs16jRg1sc3MT/WYHDx6E95Ej+PbtGzQ0NGBjbY2hQ4eiRo0aEuPfuUsX+Pv7Z/v8wf37AIRPZh07dgxBQUFQVlaGpaUlRjg6olatWjnuT0NTPL2A8Cl2l8mT4ePjg6ioKJQpUwb16tbFX3/9JbbUSecuXdCpUyeMSsvTBw8f4q+//sr2Pzp17Cj6bZKTk7Fz506cOXsWgYGB0NbWRmUHB4waNSrXGyw55YOBgQFOnTwpev/s2TOsXrMGvr6+KFOmDLp27Zrt6duc0nvp0iVs3LQJgYGB0NTURIsWLTB2zBjRqOu5c+fCz99flHcAcPDQIRw9cgTf/PygoaGB2rVqwcnJSWzU//nz57HXwwMfPnyAiooKLC0s0K9fPzRv3lxiOkeOGoVHjx5l+/zkiROip1OCgoKwfMUK3Lt3DyrKymjQoAEmTJggWmcus5zSK6l8AsJlHmqlPT2QNX9jYmKwdetWXLt+HWFhYdDX10fbtm0xwtFR1HEpqvxNTk7Grt27cfbsWQQFBUFbWxtNGjfGmDFjxJbjkWZ5BoBbt25h46ZN+PLlCypUqIAB/fuje/fuou9LW3oLc7wC8q47RXW8AoCPHz9i+YoVePr0KbS1tNCqVSuMHj06x4tDv0p5Bgp/vEp34uRJ7NmzB4GBgTA1McHIUaPQLNPAxKz5LCkvRowYIfpNSmN68zqv5HR8zk98iuL4fPr0abjv3Qt/f3/IycmhYsWKGDhwoNjFjsxyy9/M/9O6UiU4p01tnTVfHz58iKXLluHbt29QUVFBw4YN4fT332JTsRZl/Y2Ojkbbdu3g4uwsdmzMb3oTEhIwc+ZMvHj5EuHh4dDS0oKdnR2GDxsGe3t7sbj8CvU3r3NKTuU5M7dt23Dj+nXs379f9FlpPj7/TvW3MOffzVu24NKlSwgMDISSkhIqmpqib9++aJM2bTBQdOV41erVuHbtGkJCQqCpoQEbW1uMHj1aNEgkr/SmO3XqFOblMHNh5nNLaTof5TfdOaX3f//7H/52csIRb+9sA5N/5raVpPQWtv3sOn06Hj9+jIiICOjo6KBq1aoYO2aMaAY8QHgM37xlC65evYqwsDDo6emhRvXqGDt2rOhGTFb56V8DuedTbumV5Gc43+RFmvU3q7lz5yIqOhqrVq4UfVYa629h+wtZZW2XAUVbnvNqN+SU3rzqYGk6FwEFL+PS7B/l5/+X9LFaGu2r/FwjLM3XJ3/X/n5ujh49ilWrV+PC+fM5zhYRHByMDRs34s6dO4iNjUWZMmVQp3ZtjB8/XuLsEvm5ngvkXc9yw/wtfP/3Z7neTkREJE35HiTRv39/lCtXDmvWrMn23cuXL9G8eXOEhIQU6SCJX0nWQRK/usI2yn9WTO+vjen9tTG9vzam99fG9P7amN5fG9P7a2N6f21M76+N6f21Mb2/Nqb31/Y7ppeIiEia8j03pKurKx4+fJjjd/b29rh69SqOHDkitYgRERERERERERERERERERERSVO+B0lUrVoVtWvXRlJSEvr27Ss2FTsAODg4wCHTEhZEREREREREREREREREREREpYlsfgPeuHEDDg4OcHZ2hoGBAQYPHoxbt24VZdyIiIiIiIiIiIiIiIiIiIiIpCbfgyQaN26MnTt3wt/fHxs2bMDHjx/RtGlTVKpUCcuWLUNAQEBRxpOIiIiIiIiIiIiIiIiIiIjoh+R7kEQ6NTU1DB06FDdu3ICvry969eqFTZs2wcTEBF26dCmKOBIRERERERERERERERERERH9sAIPksjM0tIS06dPx8yZM6GhoYEzZ85IK15EREREREREREREREREREREUiVf2A1v3ryJXbt24ciRI5CVlUXv3r0xfPhwacaNiIiIiIiIiIiIiIiIiIiISGoKNEjCz88Pe/bswZ49e/D27Vs0aNAA69evR+/evaGmplZUcSQiIiIiIiIiIiIiIiIiIiL6YfkeJNG+fXtcvnwZ+vr6GDRoEIYNGwZra+uijBsRERERERERERERERERERGR1OR7kISCggK8vb3RqVMnyMnJFWWciIiIiIiIiIiIiIiIiIiIiKQu34MkTp48WZTxICIiIiIiIiIiIiIiIiIiIipSsiUdASIiIiIiIiIiIiIiIiIiIqLiwEESRERERERERERERERERERE9FvgIAkiIiIiIiIiIiIiIiIiIiL6LXCQBBEREREREREREREREREREf0WOEiCiIiIiIiIiIiIiIiIiIiIfgscJEFERERERERERERERERERES/BQ6SICIiIiIiIiIiIiIiIiIiot8CB0kQERERERERERERERERERHRb4GDJIiIiIiIiIiIiIiIiIiIiOi3wEESRERERERERERERERERERE9FvgIAkiIiIiIiIiIiIiIiIiIiL6LXCQBBEREREREREREREREREREf0WOEiCiIiIiIiIiIiIiIiIiIiIfgsyAoFAUNKRICIiIiIiIiIiIiIiIiIiIipq8iUdgcxCIiJLOgrFRk9LE/tv3i/paBSb/k1qo9ncjSUdjWJzfe7f8LrzsKSjUWx6N6yJsCfPSjoaxUanWhWM3320pKNRbNYN/QPfD3iXdDSKTbl+PfFt+bqSjkaxMZwyHo/efirpaBSbGpam+BwYXNLRKDYmZfXx+N3nko5GsaluYYKoyN+nPamhqfnbtZ+jwsNLOhrFRkNbG5F+/iUdjWKjWcEAEVFRJR2NYqOlofHbpZf199elWcEA7/0DSzoaxcbcoOxv118Ie/SkpKNRbHRqVMObbwElHY1iY2VYHvd9P5R0NIpN7Upmv9356NP3oJKORrExLVfmt2tfRQb8PscrzfLlERUWVtLRKDYaOjolHQUiol8el9sgIiIiIiIiIiIiIiIiIiKi3wIHSRAREREREREREREREREREdFvgYMkiIiIiIiIiIiIiIiIiIiI6LdQ4EESnz9/hkAgyPa5QCDA58+/z5rXRERERERERERERERERERE9HMp8CAJMzMzBAUFZfs8NDQUZmZmUokUERERERERERERERERERERkbQVeJCEQCCAjIxMts+jo6OhrKwslUgRERERERERERERERERERERSZt8fgNOmjQJACAjI4NZs2ZBVVVV9F1KSgru3buHatWqST2CRERERERERERERERERERERNKQ70ESjx8/BiCcSeL58+dQVFQUfaeoqIiqVavCxcVF+jEkIiIiIiIiIiIiIiIiIiIikoJ8D5K4du0aAGDo0KFYt24dNDU1iyxSRERERERERERERERERERERNKW70ES6Xbv3l0U8SAiIiIiIiIiIiIiIiIiIiIqUgUeJBETE4OlS5fiypUrCAwMRGpqqtj379+/l1rkiIiIiIiIiIiIiIiIiIiIiKSlwIMkHB0dcePGDQwcOBAGBgaQkZEpingRERERERERERERERERERERSVWBB0mcO3cOZ86cQcOGDYsiPkRERERERERERERERERERERFQragG+jo6EBXV7co4kJERERERERERERERERERERUZAo8SGLBggWYPXs2YmNjiyI+REREREREREREREREREREREWiwMttrFq1Cu/evUO5cuVQsWJFKCgoiH3/6NEjqUWOiIiIiIiIiIiIiIiIiIiISFoKPEiiW7duRRANIiIiIiIiIiIiIiIiIiIioqJV4EESc+bMKYp4EBERERERERERERERERERERUp2ZKOABEREREREREREREREREREVFxKPBMErKyspCRkZH4fUpKyg9FiIiIiIiIiIiIiIiIiIiIiKgoFHiQxLFjx8TeJyUl4fHjx3B3d8e8efOkFjEiIiIiIiIiIiIiIiIiIiIiaSrwIImuXbtm+6xnz56wt7fHoUOHMHz4cKlEjIiIiIiIiIiIiIiIiIiIiEiaZKW1o3r16uHKlSvS2h0RERERERERERERERERERGRVBV4JomcxMXFYf369TA0NJTG7vJNIBBgxzY3nDx+HFHR0ahSpQomT50GYxOTXLc7ctgL+zw9ERoSAksrK0xymQw7e3vR98ePHcWlCxfg4+OD2JgYXLhyFRoaGmL72LNrF/65cxtvfH2hoKCAi1evFUka8yIQCHD95BE8unUN8bGxMLashI4DhkKvXHmJ29w6exKvH91HcIA/5BUVYWxhhVY9+kC/fAVRmFMeO/Hh1UtEhYdBUUk5LUxf6BtUkLjf4jK0eR10qmEPdWUlvPjij9Wnr+NbaITE8EOa1cGQZnXEPvscHIZBG/eJ3k/q1Aw1zY2hr6GGuMQkvPjij22X/8Hn4PCiSka+CAQCXD3ujQc3ryE+NgYmlpXQZdAw6JUzkLjNjTMn8OrhfQT5+0FBURHGllZo07MfymTKu/vXr+DZvX/g/+kjEuLjMH3jdqioqhVHkkS8L5yH56mTCA0Ph6WpKZyHDoO9pZXE8Ffu3sU2r4PwDwqCcfnyGDvgTzSoXkP0fUh4ODbt98S/z54hKiYG1W1tMWnocJgYZPxWXwMCsMFzL56+fo3E5GTUr1oNk4YOg562dlEmNVftq9uifiUzqCgq4ENgCA7ffYygyBiJ4Rtam6GRjTl01VUBAP7hkbjw5DVeffsuCqOnoYZutSvDvJwe5GVl8erbdxz531NExScUeXokOfrv/3Dwzi2ERkfDonx5jG/fCXZGxjmGPfXwPi48fYz3gcI0WRsYYkTL1qLwySkp2H71Ev73xhf+YaFQU1JGLXMLjGrVFvqamsWWpoJSq14F6nVqQk5NFUmBwQi/fB1JAd/z3E7FphJ0u7RH3Jt3CD12uhhiKh0CgQDenntx9cI5xMREw9rWHsPGjoNBLm2FVy+e4fSRw3j/9g3CQ0MxaeYc1K7fsBhjnTOBQAD3nTtw7tQpREdHwb5yFYxzdoGRcc5lON2Jo0dw+MB+hIaGwsLCEmMnTISNnV2O+58x2QX37/0PcxctQcMmTbKFiYyIwKihgxEcFIRjZ89DPUu7pLgJBAIc9nTH1fNp+Wtnj+Fjx8HA0EjiNq+eP8OpI4fx4a0vwkJD4TxzLmo3KN789fLygoenJ0JCQmBlZYXJkyfDIVMbMKvLly9jy9at8Pf3h7GxMZycnNCoYUacBQIB3NzccOz4cURHR6NqlSqYNm0aTDK1RSMiIrBixQrcun0bMjIyaNGiBVycnaGqKjyOJyQkYMmSJXj1+jU+fvyIRo0aYdXKlVJLc1G1lxMSErBh3VpcvngJSUmJqFuvHlymTIWunp4ozIN//8U2t614/+4dlJWV0b5jJ4waPRry8sIuiL+fH3p0yz5L3badu+BQuXKh0ut1+DA89u3LyGNn59zz+MoVbHFzy8jjsWOz5/G2bTh24kRGHk+ZIpbHnbt1g7+/v9h+/x4zBkMGDwYAfPz0CUuWLsWHDx8QHRODMvr6aNu2LUY6Oop+C2nxOnYMnocOIiQ0FFYWlpg8bhzsbW0lp//6dWzdtRP+AQEwNjKC08hRaFivnuj7bXt24+LVq/geFAQFeXnYVKqEMcMd4ZDDsSwxMRFDxozGm3fv4Ll9O6xzaddJi0AgwDY3Nxw/dgzR0dGoUrUqpmapgzk57OUFTw8PUTlxmTwZ9g4Oou8TEhKwbu1aXLx4EUmJiahXrx6mTJsGvbTyHR4ejtmzZuHtmzeIiIiAjq4umjZpgtFjx0JdXf23Sd9hLy8c9vKCv78/ypUrh6HDhqFjp06FTm9x198HDx/irzFjcty3++7dsLez+y3q7+27d7Fj7168ff8OioqKqFG1KlYuXCTVtOVEIBDAY/dOnD99CjHR0bBzqIy/JznDUEIfId2pY0fhffAAwkJDYW5pgdHjJsDaNiNNU8Y74fnTJ2LbdOjcFU7OLmKfXTp3FkcPH8K3L1+hqqaKxs2aY+yESVJLX14K0jdQtrKARv3akNfWBmRlkRwWjuj7jxD33+scw2u3aQG1apURfuUGYh4+KbpEFID3xQvwPHUKoRHhsDQxhfOQobC3tMwx7PsvX7DN2wuv339AQHAQJgwchL4dOoqFefzqP3iePgWf9x8QHB6GZZNc0LR27eJISo4EAgH27dmFC2dOIyY6GrYOlTFmwiQYGkluGwPA6ePHcPTQQYSFhsLMwgKjnMbDOku9f/XyBTx27oDP61eQlZWFuYUl5i9fCSUlJQDAsH59EPg9QGybwY4j0av/AOkmMhcCgQBH9nng2sVziI2JQSVbOwwd44TyFST3/V6/eI4zR73x4Z2w7zdh+mzUqt9ALMz9f27jyrmz+PjuDaKjorBo3SaYmlsUaVpKY1syISEBS5Yty+gvNGyIVStWSDnlGQQCAfbu2pmp/1sZ4ya5wDCP/u/Jo0dw+OABhIaGwtzCAmPH59L/neKCB/fuYc6ixWjYOKP/6/PqFXa6bcUbXx/IALC2tYPj6NGwkGK7sjS3r65dvYoj3t7w9fVFUlISzMzNMWLkSNSvX19q6fc6dgyeB9PbGxaYPH587u2Na9ewddcuYXvD0BBOf/0lam8kJydjy44duPO//+Gbvz/U1dRQp2ZN/D1qFMro64v28drXFxu2bsV/Pj6Qk5VF8yZNMHHsWFGfuDh5eXsLrwmEhsLK0jJ/dXzbNvE63iDjWHX12jUcOXYMr1+/RkRkJPbt3QvrSpWKIylERCQFBZ5JQkdHB7q6uqKXjo4ONDQ0sGvXLqwowgZaTjz37sXhQ4cweZorduzaDWUVFUwc54SEBMk3Ai9fuoj1a9dimKMjdu/1gKWVFSaOc0JoaKgoTEJ8POrWr49BQ4ZI3E9ychJatGyF7j16SDNJBXbn/Gncu3IRHf8cBsfp86CoqATPtcuQnJQocZtPvq9Qu3lrDHedi4ETpyI1JRmea5YhMSFeFKaCqRm6DhmJsfOX488JUyCAAB5rlyE1NbU4kiVRv4Y10KNuVaw+fR2jdxxGXGISVgzsAkV5uVy3+xAYgj9W7hK9nHYdEfve1z8Iy05cweBN+zDZ8yRkZGSwYmBXyMrIFGVy8nTr3Cn87/IFdBk0DKNmLoCikjLcVy1FUi75+9HnFeq0aI2RM+djsLMrUlNS4L56qVj+JiUmwsqhKpp0zH5jojhc+ucO1u11h2OPXnBfugxWpqaYsHgRQiNyHuzyzMcHs9evRefmLeC+dDma1K6DKSuW493nzwCEHZypK5fD73sglrtMwd5ly1FevwzGLZyPuHhhuuPi4zF+8UIAMtg4ew62zV+ApORkTF6+tMTKdcvKldDE1gJedx9jzelrSExOxl9tGkFeTvKhOTw2DqcevsDKU1ex8tQ1vPEPgmPL+iivLbxhqigvhzFtGkIAATaev4W1Z29ATlYWI1rVR0mV5isvnmHThbMY0qwFdowaC8ty5eHiuQdh0dE5hn/88QNaOlTBusHDsWX4XyirpQUXjz0IihSWj/ikJLzx98PgJs2xY9RYLOzTH59DguF6wKM4k1UgKjZW0GreGFF37iHQ/QCSgoKg37sbZFVVct1OTlMDWs0bIeHLt2KKqfSc8vbC+VPHMXzsOCxYvR5KyspYOssViYmSj18J8fEwMTPHsNF/F2NM83Zo/z4cP+KN8S6TscFtO5RVlOHqPAmJubQ3rl+5DLeNG/DnkGHYsmMXzC0t4eo8CWFhYdnCHvU6hLwq6KqlS2BmUbQXBAvipPchnD95HI5/j8fCNRugpKyMJXnkb3x8PEzNzDF0jFMxxjTDxYsXsWbtWoxwdISnhwcqWVnByUm8DZjZ06dPMWPmTHTt2hX7PD3RrGlTuLi44O3bt6Iw7nv34uChQ3B1dcWe3cK2qJOTeFt01qxZeP/+PTZt3Ii1a9bg8ePHWLR4sej71NRUKCkro2+fPqhTBBf3i6q9vH7NGty5dQsLlyzBpq1uCAoKhuvUKaLv3/j6wnniBNSrXx97PDyxYPFi3L51E1s2bcz2/9Zv3IRTZ8+JXja5XKTLzcVLl7Bm3TqMGD4cnu7uqGRpCafx4yXn8bNnmDFrFrp27ox9e/eiWZMmcJkyBW/fvROFcffwwEEvL7hOnYo9O3dCWVkZTuPHZ/v9/ho5EufPnhW9+vTuLfpOXl4eHTt0wMb163HEywuTJk7E8ePH4bZtW6HSKTH9V69i7ZbNcBw8BB7btsPKwgJOUyYjNIfjDgA8ffECMxfMR9cOHeG5fQeaNmoEl1kz8fbDe1EYEyNjTB4/Hgd27sL29RtQoXx5/D1lMsLCw7Ptb72bm9jF0OKw190dhw4exDRXV+zaswcqysoY55R7+b508SLWrlkDxxEjsNfTE1aVKmFclmPBmtWrcevmTSxZuhRbt21DUHAwpk6eLPpeVlYWTZo2xcrVq+F99Chmz5mDf//9F0uXLPlt0uft7Y3NmzZhxMiROHjoEEaOGoUVy5fj1s2bhUprSdTfqlWqiNXb82fPolvXrjCsUAF2acehX73+Xr1xA3OWLEbn9u2wb8dO7NiwEW1btpJq2iQ5fGA/Th45AqdJLli7xQ3KKiqYOdk51/bVjatXsG3zRgwYMgQbtu+AmYUlZk52RniW36ldp87Yd+S46DXsr9Fi3x/1Ogj3ndvRu/+f2LpnL5asWoOatcUfrChKBe0bpMbHI+rufQR5HkLgnn2IffEfdDq0hlLF7Df0lK0soGBQHilROfe1SsKlu/9gncdeOPboAffFS4X9/6WLJfb/4xMTYFi2HMb26yfxgYa4hARYmZjCZdiwIox5/h05eACnjh7F2InOWLVpK5SVlTF7qgsSEyWX55vXrmLHlk3oN2gw1rlth5mFBWZPdRErz69evsCcaVNQvVZtrN60FWs2u6FT9+7ZrlUNGDoMHt5HRa/O3f8osrTm5PSRw7h4+gSGjRmHeSvXQklZGctmz8hH388Mg/8am2sYazt79BlcPPlcWtuSqampUFJSQt/evYukv5CVV1r/d5yzC9a7bYOysgpcXfLq/16B26aN+HPIUGzesRPmlpaY7iKh/3vYCzI5dIDjYmMxfbIzypYrh/Vbt2H1ps1QUVXFdBdnJCcnSy19pbl99fjxY9SpWxdr162Du4cHatWqBeeJE+HzOudBcQV18epVrN20CY6DB8Nje1p7w8Ulj/bGAnTt0AGe27ejaePGcJkxA2/fC9sb8fHxeO3ri+GDBsFj+3YsX7AAn758gfP06aJ9BAUHY+ykSTA2NMTuLVuwbvlyvP/4EfOWLpVKmgpCVMcdHYV13MoKThMm5F7HZ88W1nF39xzreFx8PKpVrQqnsZKPZUREVHoVeJDE2rVrsWbNGtFr/fr1OH36ND59+oQuXboURRxzJBAI4HXwAIYMG4YmTZvC0soKs+fOQ3BwMG7euCFxu4P796NLt27o1LkLzMzNMWWaK5SUlXH61ElRmD79+mPQ4CFwcJD8BJvjyFHo278/LCSMfC8OAoEA966cR5OOXWFTrSbKGZmg27C/EBUejtePH0rc7s8JU1GtYROUNTRCeWNTdB06ChGhIfD/9FEUpmaTFjCtZANt/TIwMDVDi269EBkagvDgoGJImWQ961WFx80HuOPzAe+/h2DJscvQ11BDIxvzXLdLSU1FaHSs6BURGy/2/emHL/Hskx8CwqPwxj8IO6/+D+W0NEQ3nkuCQCDA3Uvn0bRzN9hWr4Xyxibo4TgaUeHhePXogcTtBk+ahhqNmqKcoREMTEzxx7C/EBESDL+PH0RhGrRpjyYdu8DYomTK74Ezp9G1ZUt0at4cZkbGmOo4EsqKijh97WqO4Q+dO4N61arhzy5dYWZkhFF9+sLazBzeF84DAL74++PFmzeY4jgCdpaWMK1giCmOI5CQmIiLd+4AEA608A8MxOwxY2FpYgpLE1PMHjsWr96/x4MXL4ot7Zk1tbPExWc+ePHZH35hkfC8+QBaKsqobCJ5xpaXXwLw39fvCIqMQVBkNM48+g8JycmoWEYXAGBWVg+66mrYd+sh/MMi4R8WiX23HsBYXwdWBmWKK2livO7eQacatdChek1ULFsWzp26QllBAWckHKdm9+iN7nXqwcqgAkzLlMGULt2RKhDgYVonTF1ZGasHDUMLh8ow0S8De2MTTOjQGT7+fview02b0kC9Vg3EPHuJ2Bf/ITkkFOEXrkKQlAzVypJHq0NGBjqd2iHy9j0kh0ueLac0EggEOHfiGLr36Y9a9RvA1MwcY5ynICw0BA/u3pG4XbVaddBn0FDUbtCoGGObO4FAgGNeXhgwaDAaNG4Mc0tLTJ0xCyEhwbhz65bE7Y4cOoT2nTujXceOMDUzw3iXyVBSVsKFM+Kzgbx94wvvQwfhMm26hD0Bp9KecOnVt7/U0vUjBAIBzh0/hu59B4jyd6zzVISF5J6/1WvXQZ/BQ1GnhPJ33/796NatG7p06QJzc3O4urpCWVkZJ0+ezDH8wYMHUb9+fQwaOBBmZmYYPXo0bGxs4HX4MADh73DgwAEMHzYMzZo2hZWVFebPm4eg4GBcT2uLfvjwAf/cvYuZM2fCwcEB1apVw2QXF1y8eBFBQcI2lYqKClynTUP37t1FTxlJS1G1l6Ojo3Hq5Ak4TZiIWrVrw8bWFjNmz8bzZ8/w4vlzAMCVy5dgYWmJYY4jYGRsjOo1amKskxOOeHsjJkZ8xiRNbS3o6euLXoV9OnvfgQPo1rUrunTuLMzjadOEeXzqVM7pPHQI9evVy8jjv/6CjbW1eB4fPIjhQ4dm5PHcuWJ5nE5VVRX6enqil4pKxo0uI0NDdOncGZUqVYKBgQGaNmmCdu3a4fGTJ4VKpyT7Dx9Gt44d0aV9e5hXrAjXSZOE6T93Nuf0HzmC+nXqYGDfvjAzNcXoYcNhY2WFw8eOicK0a9UKdWvWglGFCrAwM8OEMWMRExODN5kuDALAnXv3cO/BfYzPciOyKAkEAhw8cADDhg9H02bNYGVlhbnz5yM4KAg3rl+XuN3+ffvQrVs3dE47FkxLOxacOplRvk+eOIEJEyeidu3asLW1xew5c/Ds2TM8Tyvfmpqa6NmzJ+zs7GBgYIA6deqgZ69eeCLFPC3t6Tt39iy6//EHWrdpA0MjI7Rp2xbdunfHXnf3QqW3JOqvgoKCWL3V1tLCjZs30blTJ8ik3YD8letvckoyVm3cgHGj/kKPLl1hamwM84oV0bp5c6mmLScCgQDHvb3Qd+Ag1G/UGGYWlnBxnYGQ4BD8c1ty++rY4UNo37Ez2rTvCNOKZnCa5AIlZWVcPHtGLJySkjJ09fRELzW1jFkTo6KisHfnDji7zkDzVq1RwdAQZhaWqNew+NonBe0bJH75hvg375AcGoaU8AjEPHyCpKBgKBqJ9xtl1dWg3aopwk6fh6CEH3DJ7MCZM+jaoiU6NWsOMyMjTB3uKOz/X895RlY7C0s4DfgTrRs0hIK8Qo5hGlSrjr/69EWzYhzcIolAIMCJI4fR58+BqNewEcwsLDBp2nSEBofg7u3bErc7ftgLbTt0Quv2HWBSsSLGTnSGkpIyLmWq9zs2b0Ln7j3Qq/8AmJqZwcjEBI2btYCCoqLYvlRVVKGjqyd6KavkPhhfmgQCAc6fPIauvfuhZr36MDEzx18TJyM8NAQP//ePxO2q1qqNXgOH5DpzYKMWrdC93wA4VKteFFHPprS2JVVUVOA6dSq6d+sm9f5CVgKBAMcOH0b/gYOE/V8LS0yZMRMhISG4k8vx+YjXQbTv1BltOwiPz+OdJ0NJWTlb//fdmzc4cuggnKe5ZtvHl8+fERUZiUHDhsPYxAQVzcwxcMhQhIWG4ntAQLbwhU1faW5fTXJ2xqDBg2Fnbw8TExOMGTsWxiYmuJXLtYeC2O/lhW6dOqFLhw7C9oazs7CMn5XQ3vD2FrY3+vWDWcWKGD18OGwqVRK1N9TV1bFp9Wq0btECFU1MUNneHpPHj8crHx8EfBfOjnTrn38gLy+PKRMnoqKJCextbeE6aRKu3riBL1+/SiVd+SWq4506wdzMDK5TpwrTfzrnWVtFdfzPP4V1fNQoYR339haF6di+PUYMH14sA5iIiEj6CjxIYvDgwWKvgQMHol27dtDR0SmK+Enk5/cNISEhqFUno0Okrq4OO3t7vHj+LMdtkpKS4PP6NWpl6kTJysqidu06ogu6P5Pw4CBER0TA3DZjai9lVVUYmVvgy/s3+d5PQlwsAEAl04WDzBIT4vH4zk1o65eBlm7RNsZzY6CjCT0NNTx8/0X0WUxCIv77+h12RpKXFwEAQ11teDsPxf7xAzHjj9YoqyV5GlxlBXm0r2YLv7AIBEaW3NMXYUGBiI4Ih4VdDvn7Lv/5Gy/KX+lN/fsjkpKT4PP+PWpXriL6TFZWFrUrV8HzN745bvPC1xe1HaqIfVavalU89xWGT0xOAgAoKmRcQJGVlYWCggKe+rwShZGRkYFCpjCKCoqQlZHBUx/pjMguCD11VWipKsPXL1D0WXxSMj4Fh8KsrG6+9iEjA1Q3M4KSvBw+BApHPcvLyUIAAZJTMi6KJaWkQiAQwLxc8T7dCQBJycnw9fNDLfOMATmysrKoaW6Jl18/52sfCUlJSE5NgWYuF3pi4uMhAxmoKyv/cJylTlYWCuXLIuGjeHoTPn2GYgXJxy6NBnWRGhuL2OcvizqGUhcYEIDwsFA4VMtYEkdVTQ0W1jZ48/pVCcas4AL8/RAaGoLqtWqJPlNTV4eNrR3+e5nzAKukpCT4+vqgRs2MTrKsrCxq1Koltk18fDyWzJsHp4nOYksUZPbpwwd47tmNqTNnQla2ZGc3Speev5UzXaxUVVODpbUNfF/9V4IxkywpKQmvX79G3TribcA6dergmYQ24LPnz7Nd6Khfr57oIte3b8K2aJ0sbVEHe3s8f/ZMtA8NDQ3YZZpmtk6dOpCVlcWLYhigV1Tt5devXiE5ORm1M+23YsWKKFe+vChMYmIilBSVxPatpKSExISEbE9CTXV2Roe2bfDXCEfcuil58EZuJOZx7dqFz2M/P8l5nGWf7nv3omXr1ug/cCD2enjk+rTbly9fcPfuXdSoUUNimIJKSkrCa18f1KlZU/SZrKws6tSoiecvc66Xz/97idqZwgNAvdp1JIZPSkrCsdOnoK6mhkqWGTPbhISGYvHKFZg3fTqUlZVy3LYo+Emog/YODtnyJ116Oaldt67oM1lZWdSuU0dUb1+lle86mcJUrFgR5cuXF4XJKigoCNeuXpVqnpb29CUlJkIxy006JSUlvHz5ssBPe5Z0/U134+ZNREREoHMuS4b8SvXXx/cNAoODISMriwEjHNGuxx8YN3WK2GwURSXA3x9hoaGoXlO8fWVtZ4vX/+Xc9k1KSsIbH19Uy/I7VatZC6+ybHPt8kX06dIJfw0ZhN3btiI+PuMhiccP7iM1VYCQ4GCMHPQn/uz5BxbPnY2gwLyXwZOKQvYNMlMyMYa8jg4Sv/iJfa7bsS2i/n2E5JCcn4gtCUnJyfD58B61Mz2EJCsri9oOlfH8Tf6va5Rm39PKc+ayqaauDmvb3MvzW9+cynNN0TbhYWHwefUftLW14fL3GPzZoxumTRiHlzm04Q4f2I9+3Tpj3MjhOHLwAFJSpPfUfV6CvgcgIixMbCCDqpoaLCr9XH2/kj4XFaQtWZTS+781amWkK73/+0pC/yUpKQlvfH3F+syysrKoXrMWXr3MqAPx8fFYMn8e/p4wKcf+r5GJCTS1tHD+zGkkJSUhISEB58+chompsJ0iDaW9fZVVamoqYmNioCmFpWWF7Q3f7O2NmjXx/GXOx6rnL3Nqb9SWGB4AomNiICMjI1pCJCkpCfLy8pCVzbgNlb5c0JNivB+TlJSE1z4+qFtb/DpNrnX8xYtc6zgREf38CvWYVnh4OHbu3IlXr4SNXXt7ewwbNgxaWlr52j4hISHbFFbpJ8f8Cg0JAQDoZrlpr6urJ/oup3inpKRAV1c3yza6+JRpFoWfRXREOABALUtDSU1DEzESpi3MSpCaivMHPWFsWQllDcXXlrt/7RIuHTmIpIQE6JU3wMCJ0yAn5XVXC0JXXbhOWWh0rNjnYTGxou9y8t/XACw9fhlfQsKhp66Gwc1qY/3QPzB08wHEJSaJwnWt7YC/WjeAiqIiPgeHwWXvCbEbzcUtOm1pAXVN8XqlpqmF6Hzmb2pqKs4e8ICJZSWUy2Nt1+ISHhmFlNRU6GY5XuhoaeGjX85LCoSEh0NXO2t4bYSk1YGKFQxRXl8fWw7sx9QRI6GirIQDZ84gMCQEIWHCMA5WVlBWUsKmfZ4Y3a8/BAIBNu3fh5TUVIRImFauKGmoCm/mR8WJHwuj4hKgoZL7jX4DHU1M7NgM8nKySEhKxs6r/8P3iCgAwMfAUCQmp6BLLQecfvgSMjJA55oOkJOVhaZq8Q8giIiNRYogFTpZ1ufWVVPH53zOTLP10nnoa2iipoS1RxOSkrD18gW0rFwFaqVwkISsqgpkZGWRGit+7EqJiYWSbs4DYhQNK0Ctih0C9+wvjihKXUSY8MKslo622Oda2jrZpkMu7ULTLjLr6IjnlY6uLsJCc25vRESEIzUlBTpZ8ldHRxdfPmVcEN+6YT3sHBzQoHHjHPeTmJiIxfPmYsSYsShbrjz8/fxyDFfcwkX5Kz5AtjTnb25twI8fP+a4TUhISLaLd7q6ughJa2em/836NJeunp5YmKwDieXl5aGpqSkKU5SKqr0cGhICBQUFaGhoZAuTnq669erD6+BBXLxwAS1btUJoSAh27dgJAAgODgYAqKiqwmn8BFSpWhUysjK4fvUqpk2ejKUrVqBxk6YFSmuuefzpU47bhISE5Bg+Wx7nFCbTlKx9eveGjbU1tDQ18fT5c2zavBnBISGYNGGC2HbDHB3x2scHiYmJ6N6tG/4aObJAacxNeESEsH2V5Vilq6ODj59zHpQYEhoKvRzCh4SJ31y7dfcfzJg/H/EJCdDX08PGlaugraUNQPg03rxlS/FHly6ws7aBX4D4etpFKT1/cqunWeVavtOOBSH5KN/pZk6fjhs3biAhIQGNGzfGjJkzfyRJYkp7+urVr48Tx4+jabNmsLGxwatXr3DixAkkJycjPDwc+gVYeqUk629mJ06eRL26dVGuXLls3/2K9febv7Bdsd19DyaOHgOD8uWxz8sLf02YgCMentCSwg0ZSdLbUDq64udIHR1dhEnIn8iICKSm5tS+0sHXzxnlpFmr1ihXrhx09fXx4d077HLbiq9fvmDWgkUAgAA/PwgEqTjk6YG/nMZBVU0de3dux3TnSdi8a4/YoPqiUJi+AQDIKCqi/JjhkJGTAwQChF+6hoRM7Ur1urUgSE1FzMMnRRX1QgmPjMyl/1862rY/Kr3Mamepk9o6OgjPozxrZ2knauvo4GtavQ9Iq6P79+7BsFGjYW5piasXL2KGyyRs2rkHhkZGAIDOf/wBC6tK0NDQxKuXL+C+YxtCQ0MwYkzxLGGY3v7XzLI0iqa2NiJKad8gJz9DW7I4pPd/s5ZNHV2d3I/PKSk59pm/ZDo+59X/VVVVxYp1GzBvhiv27xXOTFXByAhLVq6W2vXo0t6+ysrTwwNxcXFo1bp1vtKXm/CICGE6suRt3u2N7OEltaUSEhKw0c0NbVq2hHraw5i1atTAmk2b4HHgAPr27Im4+HhsTFu2LLgY+sTpJOajjk7u1wRyCF8cfXkiIioeBW5hPHjwAG3btoWKiopo1OXq1auxaNEiXLx4MV9PVCxZsgTz5s0T+2zOnDlwmjhJ4jYXzp/D8kxrdK1cs6agUf/pPfvfHZz23CV639/J5Yf3eWa/OwL9vmLYlFnZvqtctyHM7SojOiIc/1w8A2+3DRg2bTbkFRRz2JP0tapcCc6dm4neT9uX89RXefn3bUZD7/33ELz6FoCDEwajub0lzj7OGNV++ZkvHrz7Aj0NNfRpUB1zerWD064jSExOKXQaCuLp3ds4uXen6P2fE6bkEjp/TnvuRuC3L3B0nfPD+yrN5OXlsdTZBYu2bkGb4UMhJyuL2pUro3616hBAAADQ0dTC4onOWL5zO7zOn4OsjAxaN2wIazMzyBTD09k1zY3Rp0HGkxVulyRPO5mXwIgoLD9xBcqKCqhW0RADGtfC+rM38T0iCjEJidh97R5616+GJnYWEAgEePT+K74Eh0EgEEgjKcXK89YNXHnxHOuHOEIphwuWySkpmHP4IAQCAZw7Ft+ST0VJRlEBOh3bIOz8FaTGxee9QSlw+9oV7Ni4TvR+ytyFJRibH3Pl4gWsXblC9H7hshW5hC68f27fwuNHD7F1526JYXa5bYWJqSlatW1bJHHIr9vXrmD7hrWi91Pn/bz5+6srTe3luvXqYazTOKxYugQL5s6BgoIChgwfjqdPHotmRdHW1ka/AQNE29jZ2SM4KBj7PTwLPEiiJP3ZP2MpHCsrKyjIy2Px0qX4e8wYsSftFy9ahNiYGPi+eYP1GzbAY98+DB44sCSiXCC1qlXHvh07EB4RgeOnz2D6vLnYvXkLdHV0cOjoUcTGxmJI/wF57+gHnT93DksWLxa9X7N2bZH/z7xMmDQJjiNH4vOnT9i0aRPWrlmDqdOmFWpfP1v6hg0fjpDgYAwbMgSA8CZAx44d4bF3r2ipip/J9+/f8b9797Bk0aIcv/8V629qqrBvMHTAn2jRVHjMnT11Kjr27oUr16/jDykup3r10kVsWLVS9H7e0mVS23dWHTpnxNvM3AK6enpwnTQBft++oYKhIVIFqUhOTsZf48ajZtqsSVNnz8GAP7rh2eNHqFmnrqRdlyhBYiIC9+yHrKIClEyNodW8CZLDI5D45RsUypWFes1qCNx7oKSj+Vu4dvkSNq1eJXo/Z8nSIvk/grQ62q5TZ7Ru3wEAYGFVCU8fP8Slc2cxZIRwsFb3Xn1E25hZWEBeQR6bVq/CEMeR2ZblkIY7169i16b1ovcus+dL/X/8bvLbliwKVy5exLpVmfu/y4vk/9y9fRtPHj3Clp27JIZJSEjA6mVLYOdQGa6z5yI1NQWHDx7EzKmTsXHbjgI/YAn8fO2rzM6fP48d27dj5apV2W7Ul0bJyclwnTsXAoEA0yZl3OOxMDPDXFdXrNm8GZu2b4esrCz69OgBXV1dsdkliIiISkKBB0lMnDgRXbp0wfbt20XrBScnJ8PR0RETJkzAzZs389yHq6srJk0SHxChpKSE6PgECVsAjRo3gb19xrIDiYmJAIDQ0BCxp1RCQ0NgValSjvvQ1taGnJwcQrOMdgwNDZU4zXVpYl2tBowyPUmdnCScei0mMhIa2hmjOmOiIlHO2CTP/Z3d7443zx5jyOSZ0MxhGQ1lVVUoq6pCr1x5GJlbYtn4UXj16AEq120ghdTk7Y7PB7z6ljHlpYKcHADhjBKZZ5PQUVPF24DgfO83Oj4RX0PCYairLfZ5TEIiYhIS8S00Av99DcCpqSPQyMYcV18UzxSQNtVqwijTkgTpU+tFR0aI529kBMqbmOa5v9Oeu+Hz9DEcp80u0WVSstLW1ICcrCxCs8yGERYRAb0sTx6k09PWRmh41vDh0NPKCG9jbgGP5SsRHRuDpORk6GhqYdgMV9hmqjN1q1bFkfUbER4ZCTk5OWioqaHDSEcYls3+tJi0vfjsj09BGcceeTlhR0BDRQmRmW6Ea6go4Vto7jOFpKQKEBwlXM/9a0g4TPR10NTeEl7/PAYA+PgFYsGRi1BTUkSqQIC4xCQs6NMBIVHFu9YfAGipqkJORhZh0eJL14TGRENXPfclYA7cuYX9t29i9aChsMhhakXhAIkD+B4RjrWDh5fKWSQAIDU2DoLUVMiqis94I6emipSYmGzh5bW1IK+tBb0emS5Mp91sqODihO879iIlPH+zyRSXmnXrw9LaRvQ+KUk4S09EWDh0Mh1/IsLDUFHCjCClRf1GjWBjl7EedFKSsL0RFhYKvUztjbDQUFhYWeW4Dy0tbcjKyWV70iYsLBQ6esKLG08ePYT/t2/o1qGdWJj5s2bAoUpVrNqwEY8fPcTH9+9xs1kT4ZdpA516dO6I/gMHYfBwxx9LbD5Jzt+wbPlrWkrzN7c2oKR1ffX0ss+2kDl8+t+QkCxt0ZAQVEpri+rp6SEsyxN0ycnJiIyMLJL1hIurvayrp4ekpCRERUWJPS2V9ffsN2AA+vbvj+DgYGhqaMDf3x9bN21CBUNDiWmwd7DH/X/vFSDVecc769N76fT09HItE6I8Dg3N8vuFopKE+g8ADg4OSElJgZ+/PyqaZrTZyqc9nW5ubo7U1FQsWrIEf/bvD7m0Nu6P0NbSEravsjxFHhoWJjn9urrZnjoPDQvL9nS6iooKjA2NYGxohMp29vjjzwE4cfYshg4YgAePH+H5f/+hYRvxp9sGjxqFdq1aY65r9vWmC6txkyawd8ihfGetg6GhojqYVX6OBXr5LN8AoK+vD319fVSsWBGaWloY6eiI4Y6OBZpF4WdNn7KyMmbNmQPXGTNEx8Fjx45BTU2twEtxlob6e+r0aWhpaaFpkyY5/r9fsf7qp/1G5hUzjlOKioowNKiAgMBASFO9ho1gY5ux9FR6WyIsNAy6epnaV2GhsLDM+fiqqaUFWdmc2lfi7ZGs0v+v/7evqGBoKDqXmZhWFIXR1taBppYWAothyY2C9g0ySwmPQAqApMBgyOvpQqNebYR8+QZFowqQVVNF+b+GicLKyMpCq3ljqNeqju9ukgflFjVtTc0C9/9Lu7oNGsLa1lb0PilthtLwMPFri+FhYTCztMy2PZBRnrPOwhYeFiaaLUUnh7IKAMYmprkuD2NtY4eUlBR8DwiAkUne1wYLqkaderColNE3SE7rL0WGi/f9IsPDYWJuLvX/X1RKw7konaS2ZFEQ9n8zH5+F+RkeFpal/xsGi9zKs5wcwrKcl8JCQ0Uz2j159BD+ft/QvWN7sTALZs2EQ5UqWLl+I65euoTvAQFYt8VNdPPcdfYc/NGxPf65fQvNW7YqcPp+tvZVuosXLmDRggVYsmyZ2BIeP0JbS0uYjizHnbzbG3mHT05OhuucOQj4/h2b16wRzSKRrl3r1mjXujVCQkOhoqwMGRkZ7PfygqGBgRRSlj8S8zEsLPdrAgUIT0REP58CD9d78OABpk6dKhogAQif4p4yZQoePHiQr30oKSlBU1NT7JXXaFA1NTUYGRuLXmbm5tDT08OD+/dFYWKio/Hfy5dwqFwlx30oKCjA2sYGDzNtk5qaigcP7sOhcuUctylNlJRVoFu2vOhVpoIh1LW08P51xjpgCXGx+Pr+HYzNJTe2BQIBzu53x+vHDzDIeTp0ypTN838LBAIIIEBKMa6JF5eYhG+hEaLXx6BQhETFoIaZkSiMqpIC7IzK4b+vAfner4qiAiroaiEkWvIFCBkI70kqyv/4Ra/8UlJRgV658qJX2QqGUNfSxvtMa1jGp+evRe75e9pzN/579ADDpszIV/4WJwV5BVibm+N+pvXbUlNTcf/Fc1S2yrlD4lCpEu6/EF/v7d/nz1A5hw6MuqoadDS18NnfH6/fvUOTWrWzhdHW1ISGmhoevHiOsMhINM60bmJRSUhORnBUjOgVEB6FiNh4VDIoIwqjpCAPU31dfAgs2BqyMjKAfA6jr2MSEhGXmAQrgzJQV1HCi8/FNwV2OgV5eVSqUAEPP7wTfZaamopH79/B3kjyBZv9t29i781rWPHnYNgYGmX7Pn2AxNeQEKwZNAxaqpKX3ClxqalICgiEkqn4kjdKpsZI9Mt+7EoKCcP3XZ4I3LNf9Ip/+x4Jn78icM9+pERGFVfM801FVRXlKxiKXkYmptDW0cWLp49FYWJjY/DO5zWsbGxz2VPJU1VVg6GRkehlWtEMurp6ePzwoShMTEwMXr/6D3aZbkZnpqCggEqVrPH4YUa7KDU1FY8fPhRt03fAQLjt2Yutu/aIXgDwl9M4uLhOBwDMWbgIW3e7i76fOEX4dMmajZvR5Y8eRZH8HOU3f9/6vEalTDdAShMFBQXY2Njg3yxtwPv376OKhDZglcqVcT9TeAC4d+8eKqeFNzQ0hJ6enliY6OhovHj5EpWrVBHtIyoqSrREHSBsS6empsLBIefy8yOKq71sY2sLeXl5sf1++vQR3wMCsrWpZWRkUKZMGSgpK+PSxQsoV64crDMNusnK19dX7IJsfhU6j7P0X+79+29GHleoIDmPc+k7+Pr6QlZWNttUtpmlCgRITk6W2ixPCgoKsKlkjfuPHmX8j9RU3H/0EJXtc66Xle3sxcIDwL2HDySGF+1XIBBdQHdxGod9O3bAM+21Nu3p8MWz52C04/AfSVI2ampqMDY2Fr3M08p31vx5+eKFxPxJLyf3//03Iz2pqXhw/76o3tqmle/MYT59/IiAgABRmJykpgqX6Uu/+P67pE9eXh7lypWDnJwcLl28iIaNGhX4qcCSrr8CgQCnTp9Gx/btxa5zSPKr1F+bSpWgqKCAT5+/iL5PTk6G//cA0aAQaVFVVUUFIyPRy6RiRejo6uLJI/H2lc9/r8QGq2amoKAAK+tKYtukpqbiycOHsJWwDQC8eyt86CH95rWdgzD/v37JmHEyKjISkRERKFtOOmve56qAfQPJZIRLbwCIe/kagbv3ifUfUqKiEf3vI4QcPibFyBecgrw8rM3MxfrzqampuP/yBSrncpO4NFNVVUUFQyPRK6M8Z9TJ2JgY+LzKvTxbVqqEp1nK89NHj0TblCtfHrp6+vj65YvYtt++fkHZXOro+3dvISsrm225BGkR9g0qiF6GJqbQ0tHBy6dPRGFiY2Pwzrf09/0yK+lzUWb5aUtKi6qqqoT+b0a60vu/thL6LwoKCrCqVAlPHmY5Pj96CFt7YXnuM+BPbN3tji07d4teADDqbyc4TxP2fxMS4iErIys2I5WsjAxkZGQgSC3ccsg/Y/vqwvnzWDB/PhYuWoRGjRoVKt0S01GpEu5nyaf7jx6hsn3Ox6rK9vZi4QHg3oMHYuHTB0h8/vYNm1avhnYuy7Hr6epCVVUVl65ehaKiIuoWw/XYdAoKCrCxti5YHXdwyH5NIFMdJyKin1+BZ5LQ1NTE58+fYWMjfnHzy5cv2dbdKkoyMjLo3bcf3HftgrGxMSpUMMS2rVuhr6+PJk0zpud1GjMaTZs1R8/evQEAffv3x8J582Bjaws7e3scOngA8XFx6NSps2ibkOBghISGiDoi796+haqaKsqXKw/NtBN9QEAAIiMj8D0gAKmpqfD19QEAGBkZQ7WYbtbJyMigbst2uHXmOPTKloO2fllcO+ENDW1t2FSvKQq3d9Vi2FSvhTot2gAAzu7fg+f37qLv2IlQUlZGdEQ4AEBJRRUKiooICwrEi/v/g4V9ZaipayAyLBS3z5+CgoIirCpXLZa0SeL9v6cY2KQWvoaGwz8sCsNb1EVwVAxuv34vCrNqUFfcfv0ex/4VdsJHt2mIf3w+4HtEFPQ01DC0WR2kpgpw5bkvAMBARxPN7a3w4N1nhMfGoYymOvo3qomEpBT8703O6w4WBxkZGdRv3Q7XTx+Dbrny0ClTBleOHYaGtjZsa2Q0InevWATbGrVQr6VwOvbTnrvx7H//oP84ZygqqyAqLX+V0/IXAKIiwhEdEY6QtKcPvn/9AiVlZWjp6kM1j6f7paFfx05YsHkTbC0sYGdhiUNnzyA+IQEdmzUHAMzbuAFldHUxJm3q5j7tO2L0vDnYd+oUGtaogUv/3MGrd+8wbcQo0T6v3L0LbU1NlNfXx7vPn7HafTea1K6DulUzyuzpa9dQ0dAQ2pqaeP7GF2v27EbfDh1hWkHyE61F6cZ/b9Gmqg2CImMQEh2DDtXtEBEXj+efM9ZmHdu2EZ599sOtV8Iy3qmmPV59DUBYTByUFORR09wYluXLYOvFO6Jt6lqaIiAiEtHxiTAro4s/6lbBjZdvERgZnS0OxaF3/YZYcuwIrCsYwtbQCIf/9w/ikhLRIe04tejoYehramJUK2EZ3nf7JnZdu4xZPXqjvLYOQqKEgwJUFBWhqqSE5JQUzPLaD19/fyzrPxApqamiMJoqKlCQ0lqV0hT94BF0OrRBUkAgEv0DoF6rOmQUFBD7/D8AgE6HNkiJjkbkzX+AlBQkB4s/vZ4anwBZINvnpZWMjAzad+2O4wf3o3wFQ5QtXx6HPfZAR1cPteo3FIVbOH0KatdviLaduwIA4uPiEJBpbeKggAB8fPcO6hoa0C9bMgO+ZGRk0L13b+x3d4ehkREMDCpgz47t0NPTR8NMa6lOHj8ODZs0QbcePQEAPfr0wfLFi1DJxgbWtnY4dtgL8XHxaNuhIwDhhfqcZrEqW7YcDCpUAABUyDJAKDLteG5iagr1YmxzZSUjI4P23brjWHr+ljOAl8ce6OiJ5+8C18mo3aAh2nXuBiA9f7+Jvg/8HoCP795CXUOzWPJ3QP/+mDtvHuxsbWFvb4/9Bw4gLi4OnTsL24Cz58xB2TJl8PffwvWb+/bti5GjRsHT0xONGjXChYsX8d+rV5g+fbrod+jXrx92prVFDQ0NsWXrVpTR10eztLaomZkZGtSvj4WLFsHV1RXJyclYvmIF2rRpgzJlMgbJvX//HklJSYiIjERsbCx8fITtSmtr6x9Kc1G1l9XV1dG5S1esX7sGmpqaUFNTw+qVK+BQubLYIIl9Hh6oV78+ZGRkcOP6NXi4u2PB4iWiJ6/Pnj4NeQUFVEpL541r13Dm1ClMmzGjUOkd0K8f5s6fL8xjOzvsP3gQcfHx6NypEwBg9ty5wjweO1aYzj59MPKvv+C5bx8aNWyIC5cuCfM4bfYDGRkZ9OvbFzt37xbmcYUK2OLmJpbHz54/x4sXL1CrZk2oqqnh+fPnWL12Ldq3awdNTU0AwLnz5yEvLw9LCwsoKCri1atX2LR5M9q0bp2vG7L51b9XL8xbugS2laxhb2uLA97ewvS3Ez6xN2fxYpQpo4+/06bn7tujB0ZNGA9Pr0NoVK8eLl69ilc+Ppju7AwAiIuLwy5PTzRp2AD6unoIj4jA4ePHERQUhJZNmwFAthupqioqAABDwwooV8QDdWVkZNC3Xz/s2rlTWL4NDbF1yxbolymDps2aicKNGT0azZo1Q+8+wunI+w8YgHlz58LWzg729vY4uH8/4uLi0KlzRvnu0rUr1q5ZA00tLaipqWHlihWoXKWK6ILondu3ERoaCjs7O6ioquL9+/fYsG4dqlatigppx/BfPX2fPn3Cfy9fwt7BAVGRkdi/bx/evXuHOXPnFiq9JVF/091/8ADf/PzQrWvXbPH6leuvupoa/ujSBdv27Ea5smVRvlw5eB46CABolamMFQUZGRl069kbBz2E7atyBgbw2LkDevp6aNAoo301bdJ4NGjURDQ4tHuvPli1ZDGsrG1gbWuL496HkRAfJ1qKwO/bN1y/cgm169aHpqYmPrx/B7dNG+BQtSrMLIRPQBsZm6B+w0Zw27Ae41wmQ1VVDbu3u8HIxARVq+e9fKw0FKhvAEC9bi0kBQQiOTwcMnJyULaoCFV7G4RfugYASI2PR2q8+DJ9gtRUpMTEIDk0vFjSlJt+HTtiwZbNsDW3gJ2lBQ6dOyvs/6eVxXmbN6KMji7G9BMuOZCUnIwPX4WzICYnJyMoLAy+Hz9CRVkZxmkzDMbGx+NrQMagEr+gQPh+/AhNdXWUL8Rgyx8hIyODrj164ZDnXhgaGqGcQXl47t4FXX091M90g3O680TUb9QYnbv/AQDo1qs31ixdAitrG1SyscGJI96Ij49Dq7R6LyMjgx59+mKf+26YWVjA3NISVy5cwNfPn+E6R7jExauXL+D76hUqV68OVRVVvPrvJXZs3ohmrVoXW39BRkYG7bp0x/FDB1CuQgWULVce3p57oa2rh5r1MmaiXTxjGmrVb4A2nYQzJsbHxeG7f6a+3/cAfHr/DmrqGX2/6KgohAQFIixU2A/2/yYsF1o6OtDWyfnJ9x9RWtuSQFp/ITlZ2F+IiYGPr/CaprWE2Q8KS0ZGBt179cL+ve4wNDJGeQMD7Nm5A3p6emiY6fg8ZcJ4NGzcBF17CI/PPXr3xYoli2BlbQMbW1scPeyF+Li4vPu/5TL6vzVq1cb2LZuxYc0qdPujJ1IFqTi0bx/k5OSkdnwu7e2r8+fPY96cOXB2cYG9gwOCg4UzJysrK0NdCtdr+/fujXlLlsDWxgb2NjbC9kZcHDq3T2tvLFqEMmXK4O+Rae2Nnj0xatw4eB7K0t5wES4BnpycjKmzZ+O1ry/WLF2KlJQUBKfNxqilqQmFtGVzvY4eRRUHB6ioqODegwdYv2UL/h45sljvJQFpdXzBgow6fuiQsI53FJbT2fPmCev4mDHC9Pfpg5GjR2ev45mWR4mIiEDA9+8ISsurT5+E9xL09PREs3YREVHpVeBefZ8+fTB8+HCsXLkSDRoIG7t37tzB5MmT0a9fP6lHMDd/DhqE+Pg4LFu8GNHR0ahStSpWr1svNivFt2/fEB4eLnrfqnUbhIeFY/s2N4SGCKcaXr1uvVhD7djRo9i1Y7vo/ZhRwobBjNmz0THt4vAOt604e+aMKMyQP/8EAGzcshU1amYMUChqDdt1QlJiAk557EJ8bCxMrCrhz/FTIK+QsWZdaFAgYqMznjx+cP0KAMB9pfh6q12HjES1hk0gr6CAz298cO/yecTFxkBdUwumVjYYNm021DQljwYtDgfuPIKyojxcOjeHurISnn/2xxTPU0hMThGFMdTVgpaqiuh9GU01zOrZFpoqyoiIjcPzz34Ys+MwImKFFxESk1NQxdQAPetVhYaKEsKiY/H0kx/+3umN8Ji4Yk9jZo3bd0ZSQgJOuu8Q5e+gSdOgkDl/A78jNiojf/+9dhkAsGvZArF9dR82CjUaCTth969dxrWTR0Xf7Vw6P1uYotS6QUOER0Ziu9chhISHw6piRaxxnSGabjMgJBgyshkjx6tYW2O+03i4HTqArQf3w7i8AZZPngKLTFNHBoeHYZ2HO0LDw6Gvo4P2TZpiWA/xJ60/+X/D5gP7EBkdDYOyZTGk+x/o17FTkadXkivPfaEoL4c+DapDRVEB7wNDsPXiHSSnZIyQ19NQg1qmY5qGshIGNK4FLVVlxCUmwS8sElsv3oGPX8aUuGW11NGppj1UlRQRGh2Di898cP3l22JNW2YtHaogPCYGu65dQWh0FCzLG2Dln0NEy218j4gQe1LgxP17SEpJwWwv8TV1hzRtgWHNWyIoMhJ3fF4DAIZt3SgWZt3g4ahuVvqm9Ix7/QayKirQaFQPcmqqSAoMRvDh40iNFS4dJKepIbWnEUuLzj17IyE+Hjs2rEVsTDSs7RwwbcFisTVVv/v7IyoyY+rd9298scB1sui9xw43AECTlq0xelLG58WtT/8BiI+Lw9oVyxEdHQ2HylWwZOUqKGaqm/5+3xCZaRrhZi1bITw8HO47dwiX5rC0wuKVq0TT5/7suvTsg4T4eGzfsBax0dGwtnfAtPlLsudvRKTo/bs3vlgwzUX03mP7VgBAk1atMWbSlCKPc5s2bRAWHo6tbm4ISVsSY8P69aKpMgMCAiCb6VhUtWpVLFq4EJu3bMGmzZthbGyMlStXwjLTNLODBw1CfFwcFi9ejKjoaFSrWhXr14u3RRcsWIDlK1ZgzJgxkJGRQYsWLTDZJeN3AIDxEybA3z9jtp8Bae3KB1meWimMomovj5s4ETKyMpg+bSqSEhNRt149uEyZKva/7/7zD9x370JiUhKsrKywbOVK1G/QUCzMnl07EeDvDzk5OZhWrIj5ixajRcuWhUprm9athXm8bVtGHq9dm5HH37+LPeFetUoVLFqwAJu3bsWmLVuEebx8OSwtMpaNGTxwoDCPlyzJyON160S/n6KCAi5euoRtO3YgKSkJFQwM0L9vXwzItLa0nJwc3PfuxecvXyAQCGBQvjx69+yJ/lLuO7Vp0QLhEeFw27MbIaGhqGRhifXLloumww0I/C7Wvqrq4ICFM2dhy66d2LxjB4wNDbFywUJYpp1HZeVk8fHLZ5yZcwHhERHQ0tSEnbUNtq3fAAszM6nGvbAGDR6M+Ph4LF68GNFRUaharRrWZamD375+FSvfrdu0QVhYGLZt3SoqJ+s2bBCbNnfipEmQlZXFtClTkJiYiHr162PK1IzyraSsjOPHj2PN6tVISkpC2XLl0Lx5cwweMuS3SV9qair2eXri06dPkJeXR81atbBz585CDxIpifqb7sTJk6hSpQoqVqyYLV6/ev0d/9doyMnJYc6SxUhISIC9rS02r1oNzWK4adGrX3/Ex8dh/coViI6Ohn3lyliwfKV4++qbn1j7qmmLlogID4fn7p0IDQ2FhaUlFixfKWpfKSjI4/HDBzjufRjxcfEoU7YsGjVpir4DB4v9b+fpM7Ft0wbMmTYFMrKyqFy1GhYuXynVgS+5KWjfQEZBAdptmkNOXR2C5GQkhYYi7MwFxL0unqVBf1Tr+g2E/X9vL2H/37Qi1kxzzej/B4dARiajfgeFhWKQa8Yxad/pU9h3+hSq29phy+w5AIBX799h7IL5ojDrPPYCADo0aYrZo8cUQ6rE9ejbD/HxcdiweiVioqNhV7ky5i9dAUXFjPIc4Cdenps0b5FWnnchLCwU5haWmL9shVh/oWvPXkhMTMSOzRsRFRUFM3MLLFixCgZpS5cpKCji5rWr2O++B0lJiShnYICuPXuhe8/exZd4AJ169EJCfDx2bVyP2JhoVLKzx5R5C8X6BoEBfuJ9v7e+WDw9Uz7v3AYAaNyiFUZNFLaVH927i23rVovCbFy+BADQvd8A9Og/UOrpKK1tSQAYP2mSeH9hoDD9D+4VfJm6vPTuPwDx8fFYuzK9/1sZi3Po/0akDeIHgGYthcfnvbuE/V9zS0ssKmD/18TUFPOXLIPnnl0YP+YvyMrIwMKqEhavWFmomeYkKc3tq+NHjyIlJQXLly3D8mXLRJ937NSp0ANRM2vTogXCw8PhtmuXsL1haYn1K1Zkam8EQiZzGXdwwMJZs7Bl505s3r4dxkZGWLloESzTltIJDArCzTvCh7YGDBefRW7r2rWoWb06AODlq1fYtns3YuPiUNHEBNOdndGhbdsfTk9Bier49u3CfLSywoY1ayRfE6hSBYvmz8dmNzds2ro1xzp+89YtzFu4UPR++qxZAIARw4dj1IgRxZQyIiIqLBlBAe/KJCYmYvLkydi6dSuS05ZeUFBQwOjRo7F06dI8l83ITUimC+m/Oj0tTey/+eMXvn8W/ZvURrO5G/MO+Iu4PvdveN15mHfAX0TvhjUR9uRZSUej2OhUq4Lxu4/mHfAXsW7oH/h+wLuko1FsyvXriW/L15V0NIqN4ZTxePS25GbNKW41LE3xOTC4pKNRbEzK6uPxu895B/xFVLcwQVTk79Oe1NDU/O3az1GZLlb+6jS0tRHpV/xLZZUUzQoGiMg08PdXp6Wh8dull/X316VZwQDv/QPzDviLMDco+9v1F8IePSnpaBQbnRrV8OZbQZY++blZGZbHfd8PJR2NYlO7ktlvdz769D2opKNRbEzLlfnt2leRAb/P8UqzfHlEhYWVdDSKjUYxLLlDRPS7K/AweUVFRaxbtw5LlizBu3fCNeYtLCyKbYkJIiIiIiIiIiIiIiIiIiIiosIo9FyCqqqqojW1iIiIiIiIiIiIiIiIiIiIiEq7Ag+SiI+Px4YNG3Dt2jUEBgYiNTVV7PtHjx5JLXJERERERERERERERERERERE0lLgQRLDhw/HxYsX0bNnT9SpUwcyMjJFES8iIiIiIiIiIiIiIiIiIiIiqSrwIInTp0/j7NmzaNiwYVHEh4iIiIiIiIiIiIiIiIiIiKhIyBZ0A0NDQ2hoaBRFXIiIiIiIiIiIiIiIiIiIiIiKTIEHSaxatQpTp07Fp0+fiiI+REREREREREREREREREREREWiwMtt1KpVC/Hx8TA3N4eqqioUFBTEvg8NDZVa5IiIiIiIiIiIiIiIiIiIiIikpcCDJPr164dv375h8eLFKFeuHGRkZIoiXkRERERERERERERERERERERSVeBBEv/88w/u3r2LqlWrFkV8iIiIiIiIiIiIiIiIiIiIiIqEbEE3sLGxQVxcXFHEhYiIiIiIiIiIiIiIiIiIiKjIFHiQxNKlS+Hs7Izr168jJCQEkZGRYi8iIiIiIiIiIiIiIiIiIiKi0qjAy220a9cOANCyZUuxzwUCAWRkZJCSkiKdmBERERERERERERERERERERFJUYEHSVy7dk3id8+fP/+hyBAREREREREREREREREREREVlQIPkmjatKnY+6ioKBw4cAA7duzAw4cP8ffff0stckRERERERERERERERERERETSIlvYDW/evInBgwfDwMAAK1euRIsWLfC///1PmnEjIiIiIiIiIiIiIiIiIiIikpoCzSQREBCAPXv2YOfOnYiMjETv3r2RkJCA48ePw87OrqjiSERERERERERERERERERERPTD8j2TROfOnWFtbY1nz55h7dq18PPzw4YNG4oybkRERERERERERERERERERERSk++ZJM6dO4dx48Zh9OjRsLKyKso4EREREREREREREREREREREUldvmeSuH37NqKiolCzZk3UrVsXGzduRHBwcFHGjYiIiIiIiIiIiIiIiIiIiEhq8j1Iol69eti+fTv8/f0xatQoHDx4EBUqVEBqaiouXbqEqKiooownERERERERERERERERERER0Q/J9yCJdGpqahg2bBhu376N58+fw9nZGUuXLkXZsmXRpUuXoogjERERERERERERERERERER0Q8r8CCJzKytrbF8+XJ8/foVBw4ckFaciIiIiIiIiIiIiIiIiIiIiKTuhwZJpJOTk0O3bt1w8uRJaeyOiIiIiIiIiIiIiIiIiIiISOpkBAKBoKQjQURERERERERERERERERERFTU5Es6ApkFh0eUdBSKjb62Fh6/+1zS0Sg21S1MEPbiv5KORrHRcbDDiXtPSzoaxaZr3aoIuX23pKNRbPQa1cezD19KOhrFpoqZMT4HBpd0NIqNSVl9nPz3WUlHo9h0qVMFUcG/T/5q6Ovjyfvf5/xbzdwEB28/LOloFJu+jWoi+Mr1ko5GsdFv2QzbL90p6WgUmxGtGyIiKqqko1FstDQ0sOLE5ZKORrGZ3LXVb5e/x/73pKSjUWy616uGhd4XSjoaxWZmz7Z48OZjSUej2NSyqohIP/+Sjkax0axg8Nu1nyO+fi3paBQbLSMjREVGlnQ0io2GpuZvd/4Ni/x90qujqfHbleffLr2/2fkoKiyspKNRbDR0dBAVHl7S0Sg2GtraJR0FIvoNSWW5DSIiIiIiIiIiIiIiIiIiIqLSjoMkiIiIiIiIiIiIiIiIiIiI6LfAQRJERERERERERERERERERET0W+AgCSIiIiIiIiIiIiIiIiIiIvotcJAEERERERERERERERERERER/RY4SIKIiIiIiIiIiIiIiIiIiIh+CxwkQURERERERERERERERERERL8FDpIgIiIiIiIiIiIiIiIiIiKi3wIHSRAREREREREREREREREREdFvgYMkiIiIiIiIiIiIiIiIiIiI6LfAQRJERERERERERERERERERET0W+AgCSIiIiIiIiIiIiIiIiIiIvotcJAEERERERERERERERERERER/RYKNUji/PnzuH37tuj9pk2bUK1aNfTv3x9hYWFSixwRERERERERERERERERERGRtBRqkMTkyZMRGRkJAHj+/DmcnZ3RoUMHfPjwAZMmTZJqBImIiIiIiIiIiIiIiIiIiIikQb4wG3348AF2dnYAgCNHjqBTp05YvHgxHj16hA4dOkg1gkRERERERERERERERERERETSUKiZJBQVFREbGwsAuHz5Mtq0aQMA0NXVFc0wQURERERERERERERERERERFSaFGomiUaNGmHSpElo2LAh/v33Xxw6dAgA4OvrCyMjI6lGkIiIiIiIiIiIiIiIiIiIiEgaCjWTxMaNGyEvLw9vb29s2bIFhoaGAIBz586hXbt2Uo0gERERERERERERERERERERkTQUaiYJExMTnD59Otvna9as+eEIERERERERERERERERERERERWFQs0k8ejRIzx//lz0/sSJE+jWrRumT5+OxMREqUWOiIiIiIiIiIiIiIiIiIiISFoKNUhi1KhR8PX1BQC8f/8effv2haqqKg4fPowpU6ZINYJERERERERERERERERERERE0lCoQRK+vr6oVq0aAODw4cNo0qQJ9u/fjz179uDIkSPSjB8RERERERERERERERERERGRVMgXZiOBQIDU1FQAwOXLl9GpUycAgLGxMYKDg6UXu3zEY8e2bTh14jiioqNRpUoVuEyZCmMTk1y3O3L4MPbv80RoSAgsraww0dkFdvb2ou9PHDuGSxcvwOe1D2JjY3D+8hVoaGiIvvf388OeXTvx8MEDhISGQl9fH23btcfgoUOhoKBQZOnND4FAgMOe7rh6/hxiYqJhbWeP4WPHwcDQSOI2r54/w6kjh/HhrS/CQkPhPHMuajdoWIyxzpn3ubPwPHEcoeHhsKxYEc7DHWFvVUli+Cv/3MG2AwfgHxQIYwMDjP1zEBrUrCn6PiQ8HJs89uLfp08QFROD6nb2mDTcESYVKojCHL94ERdu34TP+/eIjYvDpb2e0FBTK9J0SiIQCHDxqBf+vX4FcbExqGhlg+5DHFGmvIHEbd6//g83zp7E148fEBUehkHjXeBQs45YmKiIcJw9tA++L54hPjYGZta26DpwWK77LQ5Hrl7GvvPnEBoRAUtjE0zq/yfszM1zDPv+2zfsOH4Urz99REBICMb37Yc+rduKhTl67SqOXb8K/7RjklkFQwzr0hX1K1cp8rTkRCAQ4JCHO66cO4uYmGjY2NljhNP4XOsmAJw/eQInvb0QHhYKU3MLDBvzN6ysbUTfB/j5Ye8ON7x++QLJSUmoVrMWho1xgraOjijMmEEDEBT4XWy//YcOR/c+/aSbyEwEAgHcd+7AuVOnEB0dBfvKVTDO2QVGxsa5bnfi6BEcPrAfoaGhsLCwxNgJE2FjZ5fj/mdMdsH9e//D3EVL0LBJk2xhIiMiMGroYAQHBeHY2fNQz3QcL2rC+nsI966l1d9KNvhjyIg86+/1Myfx7eN7RIaHYfD4yXColb3+njnoiTcvniEurf52GzS8xOuv15Ej8Ni/HyGhobCytMTkiRPhkEO+pbt89Sq2bN8O/4AAGBsZwWn0aDRq0AAAkJycjM3btuHO3bv45ucHdTU11KldG05//YUyZcoUV5LECAQCHPZwx5VM51bHv3M/twLAhVMncMr7sKj+Dh09FpZZ6q/njm2i+lu1Vi0MHf23WP31+/oV+3Zug89/L5GclAwTMzP0HjQEDlWrFVVycyQQCHDthDce3ryG+NgYmFhWQqeBw6BXTnLZu3nmBF49uo9gfz8oKCrC2MIKrXv1g3554Xk3Njoa1054493L54gIDYaahiZsqtdCi269oKyqWlxJy+bIjWvYf+kSQiMjYGlkhIm9+8KuolmOYd/7+WHH6ZPw+fwZAaEhGNezF/q0aCUWZufpU9h19rTYZyblyuHAnPlFloaCEggEuHPmOJ7/cxMJcbGoYG6J1n0GQadsOYnb3LtwBr5PHyL0uz/kFRRhaG6JJl17QjdLmfB7/xa3Th+F/8f3kJWVRVlDE/QYOwkKiopFlpZtbm44fuwYoqOjUaVqVUydNg0mefQPDnt5wdPDAyEhIbCysoLL5Mmwd3AQfZ+QkIB1a9fi4sWLSEpMRL169TBl2jTo6ell21d4eDj+7N8fgYGBuHLtmlg/IjExETu2b8f5c+cQEhICfX19DHd0RJeuXaX3I+RDQxtzVDE1hJKCPPxCw3Hx6WuEx8RJDF+toiGqVTSCpqoKACAkKhr/+HzAh8CQ4ooygNKdv9euXsURb2/4+voiKSkJZubmGDFyJOrXry/dHyEPAoEAl44dxn1RH8Ia3QY7Qj+XtsK1U8fw8uG/CPT3g4KCIkytKqF97wEoY1BB4jYlqamdJaqZGUFZUR5fg8Nx9vF/CIuOlRi+hrkxapobQ1tNWH6DIqNx69U7vAvIuHbRoYYdzMrqQV1FCYnJKfgaEo6rz30REhVT5OmRRCAQ4Mi+vbh24TxiYqJRydYOw8aMQ3lDQ4nbvHrxHGeOHMaHd28QHhqKiTPmoFb9BmJh7v9zG5fPncHHt28QHRWFRes3o6K5RVEnJxuvY8fgeeigsP1oYYnJ48bB3tZWYvjL169j666dGe3HkaPQsF490ffb9uzGxatX8T0oCAry8rCpVAljhjuKtUm79O0D/+/i/aKxI0ZgSP8B0k9gHn719nNWh48fh6eXV1p+W8DFyQn2NjYSw1++cQNuu3eL0vv3iBFoWLdujmGXrFmDY6dPY+KYMejXo4fU4+7l5QUPT0/ROWTy5MlwyHQNMVvcL1/Glq1b4e/vD2NjYzg5OaFRw4xrbAKBAG5ubjh2/Diio6NRtUoVTMtyLouIiMCKFStw6/ZtyMjIoEWLFnBxdoZqpjby3bt34bZtG96/fw9FRUVUr14dEydMQIW0a1zBwcFYs3YtXr16hS9fvqBvnz5wdnYu1G9QUudfX19f7N2zB0+ePkVEeDgMDAzwR48e6Nsv41rGvLlzceb06Wz/28zcHIe8vAqd3u1ubjhxXJjeylWqYko+0uvt5QVPTw/R9WbnyZNhby+e3vVr1+LSJWF669arh8lTM9J7+tQpLJw/L8d9n71wEbq6urh29SqOHvHGG19fJCYlwdzcHI4jRqLeD7Q3SqKMT5w0Cb6+vggLC4OGhgbq1KmDcU5OomPWx48fsWTpUnz48AHR0dEoo6+Ptu3aYeSIEZCXL9TtjBJNb7rExEQMGTIEvm/eYJ+nJ6ytrQEAfn5+OfYHdu/ahcqVK/9QerOS5vkHAK5ev44jx4/jtY8PIiIjsW/3blhXEr9+HxwSgnWbNuHf+/cRExsLUxMTDBs0CC2bN5du2ry9hXmbnjZn59zz9soVbNm2LSNvx44VS5tAIIDb9u04duKEMG8rV8a0KVPE8vb169dYv2kT/nv1CnKysmjRvDkmjh8vdryulam9km7RggVo27r1j6X38GF47NuXUZbzk143N/H0Zi3L27ZlpLdKlWzp7dytG/z9/cX2+/eYMRgyeLDYfjz37cOx48fhHxAAbW1t9OzRA8OHDv2h9BIRFYVCzSRRq1YtLFy4EB4eHrhx4wY6duwIAPjw4QPKlZN8MVXa9nnshbfXIUyeOg3bd+6CsrIKJo0fh4SEBInbXL50CRvWrcWw4Y7Y5b4XlpZWmDR+HMJCQ0Vh4uPjUbdefQwaMiTHfXz69AmpqQJMnuYKzwMHMW7CRBw/ehRumzdLO4kFdtL7EM6fPA7Hv8dj4ZoNUFJWxpJZrkhMTJS4TXx8PEzNzDF0jFMxxjR3l+7cxro9u+HYuw/cV6yClWlFTFgwH6ER4TmGf/b6NWavWY3OLVvCfeUqNKlTF1OWL8W7z58ACE/OU5ctgd/371g+zRV7V65G+TJlMG7eXMTFx4v2E5+YgPrVqmPIH9LvWBfU9TMncOfSOfwxZASc5iyGopISdq5YhKRc8jIxIQEGJhXRfdDwHL8XCARwX7sCoUGBGDJhMsYvWA4d/TLYvmwBEhPic9ymOFz+9x7WHzqIYV26YfecebA0NsbENSsRGhmZY/j4xARUKFMGo3v0gp6WVo5hyuroYHSPXtg9ey52zZqLmra2mLphHd5/+1aUSZHoxOFDOHfiGEaOG48lazdCSVkZC2dMy7Vu3rlxDe7bt6LXnwOxbONWmJqbY9GMaYgIDwMAxMfHYeGMqZCBDOYsXYEFq9YiOTkZS+fMFA1kS9dn4BBs2+8lerXv2q0ok4tD+/fh+BFvjHeZjA1u26GsogxX50lIzOX4fP3KZbht3IA/hwzDlh27YG5pCVfnSQgLC8sW9qjXIUAm9zisWroEZhbFf8EXENbf2xfP4Y+hI+E0dwkUlZSwY/nCPOtvBRNTdBssuf7uWbtcWH8nTsGEhcL6u23pfCTGl1z9vXj5MtZs2IARw4bBc9cuVLK0hNOkSQjNId8A4Onz55gxdy66duqEfbt3o1njxnBxdcXb9+8BCM9Jr3184DhkCDx37cKKxYvx6fNnTJo6tTiTJebk4UM4d/I4HJ3GY9HaDVBWVsbimbmfW/+5cR17t7mhx4A/sXTDFpiamWPxTFex+rt4xjRABpi9dAXmp9Xf5XNnidXf5XNnIiUlBbOWrsCSDZtgam6O5XNmITxTu6U43D53CvcuX0DngcMwYsYCKCgpw2P1UiQlSf4NPvm+Qp3mrTFixnwMcnZFSkoK9q5aKjrfRIWHISo8DG1798fY+cvRbdhfePviKU7s2VZcycrm8oP72HDEG8M6dsQu1xmwNDTCpA3rERaV8/koITERFfT1Mbpbd+hpakrcr5lBBZxcslz02uJcupan+/fyOTy+cRmt+w7CAJeZUFBUgvemVUhOSpK4zZe3PqjepAUGuMxEr7+dkZKSgsMbV4sd5/3ev4X35jWoaGOPPyfPwp+TZ6Fa0xaQkcnjAP4D9rq749DBg5jm6opde/ZARVkZ45yccu0fXLp4EWvXrIHjiBHY6+kJq0qVMM7JCaGZ6tma1atx6+ZNLFm6FFu3bUNQcDCmTp6c4/4WLlgAS0vLHL+bPm0aHty/j5mzZuHwkSNYsGgRTE1NfyzRBVTH0hQ1zI1x6elr7Lt5H4nJqehVvzrkZCV3DaPiEnDjv7fYe+MePG78i0/BYehetyr0NIp3MHFpzt/Hjx+jTt26WLtuHdw9PFCrVi04T5wIn9evfzzhBXDj7En8c+kcug1xxNjZi6CgpIxdKxfn2gb54PMK9Vq2xdhZCzF8ygykpKRg54pFJdo/kKS+tRlqW5rg3KOX2H31f0hMSUH/RjXzKL/xuPrCFzuu3MXOK3fxMTAEvRtUh75mRvn1D4vEqQcvsPXCbRy49QAyAPo3rplXc7NInT7ihQunTmDoWCfMX7UOSsrKWDp7eq7tj4T4eJiYm2PIX39LDBMfHw9rO3v0HZJzm7M4XLx6FWu3bIbj4CHw2LYdVhYWcJoyWXL78cULzFwwH107dITn9h1o2qgRXGbNxNsP70VhTIyMMXn8eBzYuQvb129AhfLl8feUyQgLDxfb16ihw3DuyBHRq0/3P4oyqTn6HdrPmV26dg1rt26F46BB2Lt1K6wsLDBu6lSJ6X328iVmLVyILu3bw8PNDU0bNsTk2bPx7sOHbGGv3b6NF69eoUwOg9qk4eLFi1izdi1GODrC08MDlays4JTlHJLZ06dPMWPmTHTt2hX7PD3RrGlTuLi44O3bt6Iw7nv34uChQ3B1dcWe3buhrKICpyznslmzZuH9+/fYtHEj1q5Zg8ePH2PR4sWi7799+wZnFxfUrlUL+/ftw8YNGxARHo7JmZZATkxMhI62NoYNGwYrK6sf+h1K6vz7+tUr6OjqYv78+Th46BCGDhuGTRs3wuvQIVEYZxcXnD1/XvQ6deYMNLW00LJly0Kn12OvO7wOHcRUV1fs2L0HKirKmJCP9K5buwaOjiPg7uEJK6tKmJAlvWvXrMbtWzexeMlSbHHbhuDgYEybkpHeVq1b48y582KvevXqo3qNGtDV1QUAPElrb6xeuw579nqgZs1acJk0ET4+hWtvlFQZr1WrFpYuWYIj3t5YvmwZvn39iqmZjlny8vLo2KEDNm7YgCPe3pg0aRKOHz8ONze3QqWzpNObbv369dDPZfDa5k2bcP7cOdHLNpfBg4Uh7fMPAMTFx6NalSpwGj1a4v+ds2ABPn3+jFXLluHg3r1o3rQpXGfPxuu05dylkrZLl7Bm3Tph3rq7C/N2wgTJefvsGWbMno2unTtjn7s7mjVpApcpU/D23TtRGHcPDxz08oLr1KnYs2OHMG8nTBDlbVBQEMaMGwdjIyPs2bkT69euxbv37zF3wYLsv8HMmTh/5ozo1SyHh70Kld7hw4XptbSE0/jxuad31ixhevfuzTu9O3dCWVkZTuPHZyvLf40cifNnz4pefXr3Fvt+5erVOH7yJMaPGwdvLy+sXrEC9rkMxCEiKkmFGiSxdu1aPHr0CH///TdmzJghukjk7e2NBg0a5LG1dAgEAngdPIjBQ4ehcdOmsLSywqy5cxEcHIxbN25I3O7Qgf3o3LUbOnbuDDNzc0yeNg1Kyso4feqUKEyffv0wcPBgsdHNmdWrXx8zZs9G3Xr1YGhoiMZNmqDfgAG4cf2a1NNZEAKBAOeOH0P3vgNQq34DmJqZY6zzVISFhODB3TsSt6teuw76DB6KOg0aFWNsc3fg1El0bdUanVq0hJmxMaaO+gvKSko4feVKjuEPnTmNetWr489u3WFmZIxR/frj/+3dd1hTSRcH4F9CIBB6VZo06WJFFLtr73XtfXftrrr28om9u4quvRfA7loXu7t2sQMiCHZFRSD0znx/BEJCE0gB8bzPk0eT3CTnMLfMnTt3xtHGFkf/OQcAeBf5EUFhYZg+chRcqtvDytwc00eOQlp6Gi7cuC7+nn6du2BIz15wdXBUSp5FYYzhxvlzaNW1J1zr1YdpNSv0HTUe8cJYBD8MKPJzTrXqoH3vfgXuPs/19VMk3ka8QI+hv8LStjpMTM3QY+ivyEhPx6Ni1hFFO3jhPLo2a47OTZrCxswc0wcPBV9NDWdu/Ffo8i42thjfpx/aNGgI1SJ6kDepXQeNataCZZWqqFa1Kkb37A0NvjqCX4YXurwiMcZw9sRx9Oo/EPU9G8PK1hbjp4m2zYBbRf/dzxw/hlbtO6Jl2/awtLLCyAmToMbn48p5fwBAaHAwvnz+jHFTpsHKxla0zU+djpcvwhD0+JHUd2kINKBvYCB+qKtrKDTfE4cPY+CQoWjUtClsq1fHjDn/Q3T0V9y8fr3Izx07dAgdunRB+06dYGVjg4lTp4Gvzsf5s9J3hYS/CMPRQwcxdebsIr/rdM4dLj/3GyC3vEqKMYbr/mfRqmsv1KhXH2bVrNAvd/t98I3t9+f+cHMv/A6pr58i8Tb8BXoO+y1n+zVHz2G/ibbfO+W3/focOoTuXbqga6dOsLWxwaxp06DO5+NUIXfzAMDBw4fh2aABhgwcCBtra4wZORJODg44fPQoAEBLSwubvL3RplUrWFtZwa1GDUz/4w+EhIbi06dPykwNgKg8z/19Aj37DUT93GPr1G9vv2dPHEOrDh3Qsm17WFhZ4dcJE6HG5+PqhfMAcrbfL58x9o9pqGZjg2o2Nhg3JWf7ffIYgGg0lMgPH9CtTz9Y2djC1NwCA4b/irS0VLx981oJ2YswxnDnkj+ade4OpzruqGpZDT1/GYMEoRDPH94v8nODJ89EnSbNYWJugaqWVujxy2jExXzFx9eiBu4qFpboN24yHGvXg4FJFdg6u6JVjz4IffIQWVlZykpPyqErl9ClcRN08mwMG1MzTOs/UHQ8unWr0OWdra0xvmdvtHavD1Ve0aOJqahwYairK37oaWkpKRnwcgAAW/xJREFUKoVSY4zh4dWLaNiuC6rXrANjc0t0HPIrEuOECH/ysMjP9R73B2o0bAIjU3OYWFRDh0EjkBAbjc/vXouXuXr8IOq2aIUGbTvByNQcBlVM4VTXAzwFjbzGGMNBPz+M+OUXNG/RAvb29pi/cCG+RkXh32vXivycr48Punfvji5du8LW1hYzZ82Curo6Tp86BQBITEzEqZMnMWnyZNSvXx/Ozs6Y5+WFp0+fIjAwUOq7jh49isSEBAwcPLjA79y+dQsPHz7EWm9veDRoADMzM9SsWRO1cqYxVJZ6dtVwJ/QVwj9FISo+EeceBkFLnQ9706IbbCM+f8WrL9EQJqUgNikZN0IikJ6ZBTP9wjurKkJFL98/pkzBkKFD4eLqimrVqmHsuHGwrFYN14up+8gbYww3z5/DT116wrVuzjnEyHGIF8biWTHnECOmzoZ70xaoYmEJs2rW+PnXsRBGf8V7iQvQFYVHdSvceP4SYZFR+BKXiFP3AqGtwYejmUmRn3kRGYWIT18Rm5iMmMRkXAsOR3pmFiwM9MTLPHr1Hm+/xiIuORWfhAm4FvwCugIN8egTysYYg//Jv9G9b3+4N2yEaja2GPPHdAhjovHgduHHJACo7V4ffQYPK3ZkyKY/tUbP/oNQo3YdRYReIr5HjqB7p07o2qEDbK2tMeuPP6Curo5TOefv+R08dgyeHh4Y3K8fbKysMGbEL3Cyt8eREyfEy7Rv3RoN6rnDwswMdjY2mDR2HJKSkvBCovEfAAQCDRgZGIofGhrKL+PKXn/Oz/foUXTv2BFd2reHrbU1Zk6aBHU+H6f9/Qtd/uDx42hYvz4G9+0LGysrjB4+HE729jj8999Sy32JisKaDRuwcPZsme8sL4qPry+6d++OrjnHkFk5x5BTOceQArEfPAhPT08MGTwYNjY2GDNmDJycnHD4yBEAom3bz88Pv4wYgRbNm8Pe3h4LFyxA1NevuJbTlvnq1Svcun0bc+fORY0aNVC7dm1MmzoVFy5cQFRUFAAg5PlzZGVlYcyYMbCwsICTkxMGDRqEsLAwZGZmAgDMzMwwdepUdO7UCVoy1D3L8/jbtVs3TJk6FXXr1YO5hQU6dOyILl274urVvPZXLS0tGBkZiR8hISFIiI9Hl65dy5zvIT8/DB/xC5o1F+XrtWAhvn6Nwn//Fp2vn68PunXvjs5du8LG1hYzcvI9I5Hv6ZMnMXHyZLjXrw8nZ2fMneeFwKdPEZSTr7q6OgyNjMQProoK7t8PkBphYPKUKRg8JK++MWbcOFhaVsON/8pW3yiPdRwABg4YADc3N5iamqJWrVoYOnQoAoOCxOuvhYUFunbtCgcHB5iamqJ58+Zo3749Hj1+XKY8yztfALh58ybu3L2LSRMnFhmfrq6u1Pos732bvI8/ANCpfXv8NmIEPOrXL/J3nwYFoW/v3qjh4gILc3P8OmwYtLW08FyOnYl9/PzQvVs3dO3cWZTbjBmisi0qt0OH4NmwIYYMGiQq21Gj4OToKM6NMQa/Q4fwy/DhaNGsmahsvbxEZfufqL36+s2b4KmoYMa0abC2soKriwtmz5iBK1ev4t27d1K/p62tDSNDQ/GDz+fLJ98uXUTr8syZonwlrnEVmm/uujx6tChfyXX54EFRvrnr8vz5ha7LAoFAKhfJutSrV69w9NgxrFm1Cs2bNYO5mRmcnZ3RsIjRoAghpLyVqZNEzZo1ERgYiLi4OHh5eYlfX7VqFfbu3Su34Irz8eNHREdHw90j72KwlpYWXFxdxZXL/DIyMhD6/Dnqe+QdtLlcLtzr1y/yMyWVlJQI7WLuIFSGL58+QRgbAzeJxg6BpiaqOzohLORZOUZWOhkZGQiNiED9mrXEr3G5XNSvWROBYaGFfiYoLFRqeQBoWLs2AkNFPVLTM0SVbDW1vEZ5LpcLVVVVPAkJkXcKMouJ+oKEOCHsXfOmhtAQCGBpWx1vwsveyzb3ZENyWhgulwueqipehyn3LrdcGZmZCH3zGu7OeT1KuVwu6ru4Iihfg1ZZZWVn4+LdO0hNT0MNu8Lv7FSkL58iRdtmnbri1zQ1tVDdyRmhRWybGRkZePkiDDUlPsPlclGzTl3x9pyRkQEOpMtTTVUNHA4Hz4ODpL7vxOGDGP5zD0wbNwonjxxS6AXIT5EfERMTjTru7uLXNLW04OTsgmf54sqVkZGBsLBQ1K0nvX+u6+4u9ZnU1FQsW7AAEyZPgUERdwu9efUKB/bsxoy5c8HlKv/+P/H2WyNvSEQNgSaq2VbHm/DC92ElkZkpuqObV8j2+yq0fPZjGRkZeB4aigb1pcvNw90dT4MKL+unwcHwkFg3AMCzQQMEBgcX+TuJiYngcDhKnTIll/jYWqfgsfXF88K338yc7dettvT261a7Ll7kbL+ZhWy/qqqq4HA4CM1Z57V1dGBmYYn/Ll9EamoKsrKycOncWejq6cG2umx3g5VG7NcvSIwTwtYlr/OoukAAc1s7vIt4UeLvSU0WDYWuoVl0I21qSgr46hpQUVEpe8BllJGZidC3b1HfMe9uHS6XC3cnJwTJeKHw/Zcv6DprOn7+3xzM370Tn5Q8Ekhx4qKjkBQfByunvOMwX0MAU2tbfHxd8uNwWqpoqgZ1gejO7KSEeES+fgmBlg581yzBplmTcHDdcryPkN/dQvl9/PAB0dHR8Mh3fuBao0aBi925MjIy8Pz5c9SXaLThcrmo7+GBwKdPAQAhISHIzMyEh8Qy1tbWqFq1qngZAHj58iV2bt+O+QsXglvIaBn//fcfnF1csH/fPnTq0AG9evaE97p1SFXiaEC6Ag1oqfPxJipvHUzPzEJkbHyJOzxwADiZV4Gqigo+xsYpKNKCKnr55pednY3kpCToKPEcMbcOUt01rw6iLj6HKMX+OkW0vxZUoA5dAKCnqQFtDT5efc6b5iUtMxMfYuJgYahXou/gAHCxqApVFRW8jxYWuoyqigpqWZsjNjEZccnlM5pG1GdR/cNVoi4h0NSEnaMTXjyveOevpZGRkYHnYaHwkJgak8vlwqNuPQQGF163CnwWjPoSywNAw/oeRS6fkZGBE2dOQ0tTEw7VpUeW2+vri9bdumLgb79i/8GDyMzKlDGj0vkR6s+SROUdhvp1pevF9evWReCzosr7mdT6AQAN3d2lls/OzobX8uUY1KcP7KytFRf78+doIHHc4XK58PDwwNMijjtPAwMLXCj0bNhQfJz6UMSxrIarq/iY8zQwENra2nCRuOvWw8MDXC4XQTnriLOTE7hcLk6dPo2srCwkJibi3D//wMPDQ+4XVcv7+JtfYmIidIs5tp46eRIeHh4wNS3blJS5+dbPn69rDQQ+/VZ7cyH5BopyeZ6Tr+Qy4nwDC8/33NmzUFdXR8ufih4VIzs7G8nJSdDRLX19o7zW8fzi4uLg7++PmjVrFrn+vnv3Drdv30ZdiX1JaZVnvtHR0ViydCkWLlgAdXX1ImP8Y8oUtGnbFr/8+iv+LeYm0LJQ1vGnMDVr1MDFy5cRFx+P7OxsnL90CWnp6agnQ3lKKjK3+vWLLtugoOLLNufak+Qy4rLNWSY9PR2qqqrgSoxoltv54fGTJ1LfvWL1arRq1w5DRozAydOnwRiTLd/C1uXi8v3Wupybb2Hrcr7v3LtvH1q1aYMBgwdj3/794usNAPDfjRswNzfHjRs30LV7d3Tp3h2LlixBXJzyzhsJIaQ05FpzLu4gLyktLa3AMD2l7T0XEy1qGMkdbiyXgYEBomMKnxtXKBQiKyur0M+8ffOmVL8v6f27dzh6+DDG/150T1BlEMaKGjt1JeYyBwBdPX0Iixg2qyISJiQgKzsbBnrSDbX6unp4XcRUCdFCIQx09aSX19NDdM6w5tbm5qhqZIzNBw5gxugx0ODz4XfmNL5ERyO6Av5tEnKmFdHKN5WEtq4uEvINF1oaJqZm0DM0wj9HfNFz+Eio8dVx3f8M4mKiZfpeWYjLW0c6VwMdHbzJN8dZaUW8f4eRSxcjPSMDGnw+lo2bABuzoufwVZTc7U9PT3rb1NPTE2+3+SXExyE7Oxu6egW35w85vZHtnZzBV1fHgV07MGDYCDAw+OzagezsbKkphDp06wHb6tWhpa2D0JBg+O7eidiYGAwbVfRQeLKIiRb9tr6+9L5W38AAsUXsn+PihMjOyoJ+vv2zvr4B3r15K36+ZcN6uNSogUZNmxb6Penp6Vi6YD5+GzsOJlWqIvLjR1lSKZPcbUk73z5JS1dPvG2XhYmpuWj7PeyLXiNGQo3Px3X/s6LtV4bvlUVxx9XXb98W+pno6OjCj93Rha8baWlp2LB5M9q1bg0tTeUO6w4Uc2zVL/rYGp+7/RbymY/vpbdfn1070D9n+/XdtVNq++VwOJi7dAVWL/LCsJ7dwOFwoKunh1mLlim1wTsx52RWK99+WktHF4nxJTvRzc7Ohv/B/ahW3QFVLCwLXSYpIR7/nj6Bes1/ki3gMhImJuYcj6T/tgbaOnj7uex3YbrY2GDOkGGoZlIF0fFx2HX2DMb+uQr753pBs4R1Z0VKypnaSqAt3bAq0NZBUgnLl2Vn4+pRP5jbVoexmQUAIO6r6E7HW+dOonmPPjCxqIZn927hyIbVGDZ7EfRN5D9FX+5+JH8nuuL2McXtx968fi3+XlVVVWjn2+4kvzc9PR1z58zB7xMnomrVqvjw/n2B3/rw4QOePH4MNTU1rFy1CkKhECtXrEBcXBzmSXQ8VyRNvhoAIClNerj+pLR0aKqrFftZI21NDGxWHzwuF+lZWfj73hNEJyQpLNb8Knr55ndg/36kpKSgtYxzDZdGYhHnEFo6uuL3viU7OxtnfPbCyt4RVS2Kn3td2bTURW0GSfnaEpJSv73+GutoYfhPDUTrb2YWjtx+hK/51t96tpZoVdMBajwevsYnwvf6fWTL0IAtC3H9Q09P6nVdPT0IhRWno11ZCOPiRMfbfOcKBvr6RdcfY2JgWMjy0fnOpa7fvoU5CxciNS0NRoaG+Gv1GuhJ1Mn79uwFJwd76Gjr4GlwEDZu346v0dGYPG6cfJIrgR+h/iwpr7yl68UG+vp4k+8u21zRMTGFLi85hPi+gwfBU1FB356Kmy6l2LLKOYbkFx0dXexxKvdfw/zLGBpKLaOfL38ejwcdHR3xMubm5vhrwwbMmj0by5YtQ1ZWFmq6ucHb27tsyRajPI+/+T198gQXL1zA2iLyjIqKwu1bt7Bw8eJv5lWUIvM1LH2++hLrSlnyPX3qJNq2a19se7vPAVF9o1Xr0tc3ymsdz7V+wwYcPnwYqampcHNzw9o//yzweyNGjMDz0FCkp6ejR48eGD1qVKlylFRe+TLGsGDBAvTs2RMuLi74WEg7lUAgwKRJk1C7Vi1wOBxcuXIFU6dNw+pVq9C8efMy5ZufMo4/RVm+aBFmzZuHVh06QEVFBerq6li9dCksLSxKl0QRisxNX7/4si1k+QJlW0z+9d3dsdbbG/sOHED/vn2RkpKCDTnTsX+V+BuNHjkS7vXqQV1dHXfu3sWKVauQkpyMfn37yjdfAwO8LuIa17fKsth8JY6/ffv0gZOjI3R1dPAkMBAbN23C1+ho/DFpEgDROe+nT59w6fJlLPDyQlZ2Nv5ctw4zZs3ClgowVT0hhORXpk4SWVlZWLt2LQ4fPoy3b98WmBOzqLmPci1btgwLFiyQes3LywvjJ00u8jPn/f2xavky8fNVf64tQ+TyF/XlC/6YNBEtW7VC1+7dlfrbN65exvYN68TPZywo+0lAZcfj8bB8+gws2fQX2g4dDBUuF/Vr1oJnnbpgKJ+GL0kPb13H8d15c7APnzJLIb+jwuNhyO9TcWTnZswfMwJcLhfVXd3gWLMOUAH+DvJWraop9notRGJKCq4+CMDinTuwccZMhXeUuH7lMrauz9tHzVq4RCG/o6unhylz5mH7X9745+QJcDgcNG7xE2yq24MjMYJCl169xf+3srUFj8fDtvXrMHD4L1BVK75BuSQuXziPdatXiZ8vXrGqmKXL7taN63j08AG27Nxd5DK7tm5BNSsrtG7XTiExFObhzes4tjtvXswRCtx+h06cisM7NsNr9HDx9utUs06F2I8pQmZmJmb+739gjGFmEXPDy9v1K9LH1pkKOrbq6Olh8uz/Yedf6+F/6u+c7bclbKrbi+9QZoxh16YN0NHVw/xVf4qm2/H/Byvn/w9L1/8FfQPFzL389M4NnN63U/x84MTpxSxdMmd9duPLh3cYMbPwC8GpKcnw8V4FYzNztOzaS+bfq0g8XfNG4KgOC7hY26DX3Fm48uA+ujRW/lRnzwJu46LfPvHznmMmyfydlw4fwNfID+g/OW//l3tnTK0mLeDmKerYVsXSCm9CQxB4+zqadetd6HeVhv8//2CZxPzca9etk/k7y2rjX3/BxtoaHTp2LHIZlp0NDoeDRYsXi4e9npSejpkzZmB6znCw8uZsURVtazmJnx+787jM3xWTmIy91+6Cz+PBwcwEHeu64uDNBwrrKPG9la8kf39/7Ni+HavXrCnQGClPj25dx4k928XPh/0xU+bvPLlvFz59eIcxcxZ8e2EFq2Fpio718u6kPnij6CmAviU6IQnbL94GX5UHZ4sq6FrfDfuv3ZPqKBH0NhIvv0RDW52Phg7W6NmwFvZcvYes7GyZ8iiJm1evYOfGvIt+07wKzmVNvs29dh347NgBYVwc/j5zFrMXzMfuTZvFF9wHSsyZbW9nB1WeKpb+uQbjfvsNanI4L6oIyqP+rGwhYWE4ePw49m/ZAk4JRvapjL5+/YolS5eiU6dOaNeuHZKTkrBl61bMmDEDGzdulOnvUpGOv5IiwsMxdcoU/Prbb2jYsGGhy5w9cwZaWlpo0aJFib/X/59/sGJZXr5r1q6TMVL5CHz6FK9fvcL8BQuLXOa8vz92bt+OlasVW99QlCGDB6Nb166I/PQJ27dvh9f8+Vi3dq3U+rt06VIkJycj7MULrF+/HvsPHMDQIUPKMerSO3ToEJKSkzF82LAil9HT08OggQPFz11dXRH19Sv2Hzggt04S5Wnz9u1ISEzEJm9v6Onq4tr165g5bx52bNqE6nZ23/6CCsrO1hYL5s3DWm9vbNy8GVwuF/369IGhgYHUevzriBHi/zs5OiI1NRX7fXzK3EmiPA0akDetsb29PVR5PCxdvhzjx46FmpoaWHY20tPTsWD+fFhVE3W4njdnDgYNHYrXb97A2sqqvEInhJBClamTxIIFC7Bjxw5MmTIFc+fOxZw5c/D69Wv8/fffmDdv3jc/P2vWLPzxxx9Sr/H5fCSkFD2UZZOmTeHq6ip+np4h6pgRExMDIyMj8esxMTGwt3co9Dv09PSgoqJSoBNHTEwMDMpwoSEqKgoTxo6Bm5sbZsyaXerPy6peA09Ud8xr9MzIEA3FHhcbK3XhJE4YCyvb76fCoaetDRUuFzFC6bsXY+OEMMx3J00uQz09xOS7OypWKIShxF34TnZ22L9mLRKTkpCRmQl9XV2MmDkdzhWgMuZSxx3V7PKGTs/MKcvEuDjoSOSQEBcHMytrmX7LwsYWkxeLeqxmZWZCS0cHG+bPhoWNrUzfW1bi8s53t2pMfDwMdEs27HNRVHk8WFQR3anqZG2NkFevcPjSRcwYMkym7/0W94aeqO6Ut21mpovKUyiMhb5E73KhUAjrIrZNbR1dcLlcxAml71SPE8ZCT+Kuklr13PHX7v2Ij4uDiooKNLW08Gv/n1Glaosi47N3dEZWVha+fP4Mc8vC7+guDc8mTeDkkrd/zsjZP8fGxsBQYv8cGxMDO/vCpwjQ1dUDV0VFagSM3O/QNxSd7D9++ACRHz6ge8f2Usss/N8c1KhZC2s2/IVHDx/g9cuX+K9FM9GbORfpenXphAGDh2DoL7/KlmwhXOq6o1r1vGlcMnOm90mIE0ptv4lxQjlsv3b4Y8lqpCQn5Wy/uljvNQsWNuWzHyvuuJq/93kuQ0PDwpfPd+dFbgPvp8+fsXn9eqXdBefe0BP2TiU4tsbGwrqI44dO7vabb6SJuNiC2+/63fuktt+RA/rAxLQFACDo8SM8uHcXuw4fhyAnf9vx9gh89AD/XrqI7n36ySXn/Bxr1YO5V946nZUzdGJifBy0Jdfp+DhUtfz2Ce5Zn90Ie/III2bMg24h9a20lBQcWLsCfHV19Bs/GSoKmlP6W/S0tHKORwlSr8ckxBcY7UgW2gIBLE2q4H3OnNLKVt2tNkyt8475ueWbnBAPLYm7bZMT4mFSgrvILx0+gJdBT9B30kxoS9zlq5nzNzOsaia1vGFVUyQUMYpSaTVt1gyuNfI6oeR23I6Jji5wfuDgUPrzg9z9kqGhITIyMpCQkCB195/kMvfv30dEeDiu5AwZndtJpG3r1hg+YgRGjhoFQyMjGBsbS80Lbm1jA8YYvnz5gmrV5H/XfvinKERKTImhkjMUrCZfTWo0CU2+Gr7EJRT4vKRsxiBMEk2r8jkuAab6Oqhna4kLTxQzZdv3Vr65Lpw/jyWLFmHZihVSQ4grgksdd1hKnENkFXEOkRgfB9Nq1t/8vpP7duH5k4cYNXt+oftrZQuL/IIPFyXWXxVRY7Mmn4/EVIn1V10Nn4XfXn9jk0TTiHwSiqaX8bC3wrmHecP3p2VmIi0xE7GJyXgfLcTUbj/BydwEwe/KPppQSdVt0BB2jo7i57nng3FCYb5zeyGsyqneJy96urqi422+Y0FMbGzR9UcDgwKjRsTExhYYXUJDQwOW5hawNLeAm4sreg4aiJPnzmG4xIUnSa7OovOij58+wVoB++DCVMb6c3Hyylu6Xvyt8i5s+dyLwI8DAxErFKJr//7i97Oys+G9ZQsOHjuGk76+8om9BMeQArEbGopHvi1s+dx/o/Mfy6KjxccyQ0NDxObLPzMzE/Hx8eLPHzlyBFqampj4++/iZRYtXIhOnTsjKCgIbm5uKKuKdPzN9fLlS4wbOxbde/TAL78Wfk7PGMPpU6fQoWNHqSkNS5tvRlH5RsfAvpT5xpYxXwA4dfJvODg4wMnZucB7AHDxwnksXbwIS5eXvb5RXuu45O/r6enBysoKNtbW6NS5MwIDA1GzZt7Uw1WrVgUA2NraIjsrC0uWLsWggQPLND1jeeUbcP8+AgMD0ahxY6nvGTJ0KNq3b48F8+cX+ts1XF1x9+7dkif4DYo8/hTn/fv3OHzsGA7t3w87W9F5qIO9PR4/eYLDx45h9nTZb8ooMrfY2OLLtpjlxWVbyLUnB4m2zfbt2qF9u3aIjo6GhoYGOBwOfPz8YGFe9A16NVxdsWPXLqSnp5epk6YiyrKk+RbIpUYNUV0qMhLWVlYwMjKCioqKuIMEIJpaCAA+ffpEnSQIIRUO99uLFOTj44Pt27djypQp4PF46N+/P3bs2IF58+bhzp073/w8n8+Hjo6O1ONb021oamrCwtJS/LCxsYWhoSEeBASIl0lKTMSz4GDUKOJkQFVVFY5OTrgv8Zns7Gw8CLhf5GeKEvXlCyaMGQ1HJ2fM/t88qbmnlEVDIEBVM3Pxw6KaFfT0DRD05JF4meTkJISHPoeDs0sx31SxqKqqwtHODgESc/JlZ2cj4Gkg3BwcC/1MDQdHBOSb2+7e0ydwcyx4AqOlqQl9XV28/fgRzyMi0Ky+YhsvS0JdQwNGVaqKH1XMLaCtq4cXz/Lm/EpNSca7l+Gwql74SVlpaQgE0NLRQdSnSLx/FQHXuvW//SEFUOXx4GhljQch0vOL3g95hhpy7sCSzZj4gqciaQgEMDUzFz8srHK2zccS22ZSEsKfh8CxiG1TVVUVtvYOCHycd8dcdnY2Ah8/KnR71tHVhaaWFgIfP0K8UAj3ho2KjO/1ywhwuNwCw/eWlUCgCXMLC/HDytoGBgaGePTggXiZpKQkPA95BheJO6olqaqqwsHBEY8e3Be/lp2djUcPHog/02/gYGzdsw9bdu0RPwBg9ITfMTWno5rX4iXYsnuv+P3J00V3VK79axO69lTM3emi7ddU/MjdfsOD8+Z0TE1JxtuX4bCqXvg+rLQ0BJrQ0tHN237rldP2q6oKJ0dH3LsvXW4BDx6gZo3Cy7qmqysCJNYNALgbEAA3iY6QuQ28b9+9w6Z166AnY4ep0ijq2BqYf/sNfQ57p8K3X554+837THZ2NoIeP4J9MdtvkHj79QQApOcMJ56/jsHhcMEUeFcrX0MDhlWqih/GZubQ0tXDy5C8eUdTU5Lx4WWE1MW5/BhjOOuzGyEP72PYtDnQNzYpsExqSjL2/bkMKjwe+k+YClXV8ruLU5XHg2O1argfmjfXe3Z2Nh6EPkcNOXYkTE5NxYevUTBS4notSU1dA/rGVcQPw6pm0NTRxZtQiQuFKSmIfP0SZtZFH4cZY7h0+ADCnzxEn9+nQ8/IWOp9XUMjaOnqIeaL9NRZsV8+Q0dOF181NTVhaWkpftjais4PAiTq+omJiQgu5mKBqqoqnJycEHDvnvi17Oxs3A8IgFtOA62zszN4PJ7UMm9ev8anT5/Ey6xYuRI+vr444OODAz4+mDN3LgBg6/bt6P3zzwCAWrVqISoqCsnJyeLvefvmDbhcLkxMCm4f8pCRmQVhUor4EZ2QhMTUNFQzzms8U+OpwFRfBx9jSza9Sh6OuNOFInxv5QuI7uhctHAhFi9ZgiZNFD9SDD/fOYRJbh2k0HOI4vfXJ/ftQvCDe/htxv9gUMj+ujykZ2YhNilZ/Pgan4SElDRYm0ivv+YGungfLSzVd3M4KHb95XAAjoLXcUn56x/mOfWP4MfS5/YRoc9h71T4BbPvhaqqKpwcHBHwUPo8J+DhA7i5Fl63cnNxlVoeAO4+uF/k8uLvZUzcgbswYeHh4HK5BaZ2UKTKWH8ujqi8HRDwSLpefP/RI7i5FFXeLoWU9wPx8h1at4bv9u04sG2b+GFsaIhBffpg/YoV8o3dyQn38rUhBgQEoGYRx52abm5SxykAuHv3rvg4ZW5uXuixLCg4WHzMqenmhoSEBISE5NVJ79+/j+zsbNTIWUdSU1PBybd/yr1onC3jeUJFOv4CQEREBMaOHo2OnTphbDFT4zx88ADv3r1Dt27dZMrXppB8kxITERwcBLeaxbc3BwRI5xsQEAA3N1EuTrn5BhSSr1tNqe9LTk7G5UuX0KWIXC6c98fihQuxaMkSNJahvlFe63hhcjugphfTZpfNGDIzM8XLllZ55Ttt6lT4+vjA58AB+Bw4AO+c0VmWLl2KsWOKngY3LCxM6mK1rBR1/PmW1CLaNbhcbpnLMj9xbqUp2xo1CpbtvXt5ZWtmVrBsk5JEZVvIdxoaGkIgEODCpUtQU1NDAw+PIuMNDQuDjo5OmUexKvO6LFH2QAnyzV2Xi7luFhYWJlWXqlWzJrKysvBeYnrCtznTuZiampYyU0IIUbwy3aonqsCJdo5aWlqIy5mrunPnzvjf//4nv+iKweFw0KdfP+zdvQsWlpYwMzPD9q1bYGRkhKYSw1D9Pm4smrVogd4/i4ZV7Nt/AJYsXAAnZ2e4uLji8MGDSE1NQafOncWfiY7+iujoGLzPmTc8IjwcAk1NVK1SBTq6uoj68gXjx4xBVdOqGP/77xBK3OltaCi/yktpcTgcdOjeAycO+qKqmTlMqpji8P490Dc0hLtnXm/VRbOmoX6jxmjfpTsAIDUlBZ8+fhC//+XzJ7yOCIeWtg6MFNRg+y39u3TFog3r4WxnBxd7exw6cwapaano9FMrAMCC9d4wNjDA2EGDAQB9O3XGmHlz4XPqJBrXrYeLN28gJCICM0fnVTYv37oJPR1dVDUyQsTbN/hz1040q++BBrVri5eJjo1FtFCI959EDfoRb95AoKGBKkZG0FXi/O8cDgdN2nXElZPHYVTFFAbGJrhw7CB09PSlOjNsW74QrvU80LiN6M76tNRUREvMmx4T9QUf37yGhqYW9HMq1k/v3Yamtg70DI3w6d1bnPLZA9d69eHgVktp+eXXr207LN65HU7WNnCxscWhSxeQmpaGzo1Fw3Mv3LENxvr6GNNL1AidkZmJVznrbGZmFqJiYxH29g0EfHXxyBGbjx1Bwxo1UdXQAMmpqbhw9w4ehT7H2slTlJ4fh8NBpx49cczPR7RtVq2KQ/tE22b9Rnnb5oKZ0+DRqDE6dO0OAOjcsxc2rl4JO3tHVHd0xNkTx5GWmoqWbfNGUrh6wR/mltWgo6uHsJBn2L1lIzr16CUeISL02TOEh4bAtVZtaGhoICwkBHu2bkazn1pBS0HrNIfDQY8+feC7dy/MLSxgamqGPTu2w9DQCI2bNhUvN23i72jcrBm650wH0qtvX6xcugQOTk5wdHbBiSOHkZqSinYdOwEQzemYfy5IADAxqQJTM9Gdymbm0vMZxueMMFPNykph+ebH4XDQtH0nXD55DEZVq8LA2ATnjx4Sbb8SnRm2LluAGu4eaNymAwAgLTUFX/Ntvx/evIJAUwv6ORcfn9y9DS0d0fYb+e4tTh3YDdd6HnAsx+13YN++mL9kCVycnODq4gLfw4eRkpqKLp1E5TZv0SKYGBlhfM7Jf78+fTBy3Dgc8PNDk0aNcP7SJTx7/hyzZ8wAIGrgnT5nDkLDwrB25UpkZWeL53LU1dEp1V1B8sDhcNAx59hqai46th7aX3D7XTQz59ias/126tELm9ashJ29A+wcHXHu7xNIS0tFizZ5U8FIbr8vnj/Dni2b0LFHT5hZiLZfe2cXaGlpYeOaleg1YBDU1Pi44n8OXz5/Qh0P5XXw43A4aNi6Pf47cwKGVapC38gYV04cgbaeHpzquouX27NqCZzruqNBK1GOZw/sRuDdW+g/YQrU1DWQkLM9qmsIoKqmhtSUZOz/czky0tPQ67dxSEtNQVqq6C51TW2dcumA2ven1liybw+crKzhYmWNw1cvIzUtHZ08RR3PFu3ZDSM9PYzp3gNAzvEoUlRnyMjKRJRQiLB37yDg82GRU4f669hRNHYTHY++CuOw4+xpqHC5aO1ePp2b8uNwOKjbsg3u+J+BvnEV6Boa4+bZE9DS1UP1WnXFyx1evwrVa9VF3eaiutilwwfw/P4ddB/5O9TU1ZGUMyKUmroGVNXUwOFwUL91e9w8exLG5tVgYmGJ4Ls3EfM5El1/GauwXPr1749dO3fC0tISZubm2LJ5M4yMjdFcYtjlsWPGoEWLFuiTM7zpgIEDsWD+fDi7uMDV1RUHfX2RkpKCzl26ABCd73Tt1g3r1q4VdWrS1MTqVavgVrOm+JzIIt98ukKhEABgY2MjvluwXfv22LlzJxYuWICRo0ZBKBRi/fr16NK1q0Km2ijKg4i38HSwQWxSMuKSUtDE2Q6JqWl4EZk3ukmfRnXxIvILHr0SNW41dbbDqy/RiE9OhRpPBc4WVVHNSB9Hbj8q6mfkrqKXr7+/PxZ4eWHK1KlwrVEDX79+BQCoq6tLjR6iSBwOB43bdcSVUyfyziGOi+ogLhLnENtXLIJr3fpolHMOcXLfTjy+cxNDJk4DX10DCTn5qQsEcpmaTZ7uhb9BE2c7xCQmQ5iUghau1ZGQkobQj1/Eywxs5o7QD19wP0LUINuyhj0iPn1FXHIK1Hg81KhmCitjA/heFzX662lqwMWiKl5+jkZyWjp0BOpo5GiDjKwshH/6Wi55cjgctO/WHX8f8kNVc3MYV6mKowf2Qs/AEPU88zpDL509A+6ejdC2i+hCWmpKCj5F5s11HvX5E16/jICWlrb43D4xIR5fo6IgzKlfRea0e+jp60NPv/C7D+VtwM8/Y8HyZXB2cISrszP8jh4V1R/bi+rFXkuXwtjYCON/GwkA6NerF0ZNmogDhw+hScOGuHDlCkJCQzF7iujcLiUlBbsOHECzxo1gZGAIYVwcjvz9N6KiotCqeQsAwNPgYASFPIN77ToQCAQIDA7G2k0b0aF1G+go8VwfqPz15/wG9O6NBStWwNnBAa5OTjh47BhSUlPROWeKRK/ly2FiZIRxOSME9OvZE6MmT4bP4cNo3LAhLly9ipCwMMzOGZFWT1e3QCcQHo8HQwMDWMlhpERJAwcMwPwFC+Di7AxXV1f4+vkhJSUFXXKOIfO8vGBibIzx48eLYu/XDyNHjcKBAwfQpEkTnL9wAc9CQjB7tqhTP4fDQf/+/bFz1y5YWlrC3Nwcm7dsgbGREVrktGXa2NigkacnFi9ZglmzZiEzMxMrV61C27ZtYWwsOi9s0qQJfP38sH37dtF0G8nJ2LhxI0xNTeEoMSpNaGgoANE2Ehsbi9DQUNENGbYl7wBcnsffiPBwjB0zBg0bNsSAgQPFx1YVFRXo5+vcdOrkSdSoUQN2EqM8lgWHw0Hf/v2xZ1devtu2bIaRkTGaNc/Ld/yYMWjesgV+7iPKt/+AgVi0YD6cnV3g4uqKQ36+SE1JQSeJfLt064b1a9dCV0eU75pVq+DmVrPAjXuXLl5AVlYW2ncoOM3XeX9/LJzvhclTpsLVtQaic/4m/DLWN8pjHQ8KCkLws2eoXasWdHR08P79e2zesgUWFhbiC7z//PMPeDweqlevDlVVVYSEhGDjxo1o26YNeDKMPFge+eaOhpFLIBAAACzMzVElpw3zzJkz4OVc6AeAK1ev4tTp05g7Z06Zcy00fzkffwAgLj4enz59QlTOuvgm54K4oaEhjAwNYW1lBUsLCyxduRITx4+Hno4Orl2/jrsBAVi7cqX8cuvfH/MXLRKVrYsLfA8dks5twQJR2Y4VnYv269sXI8eMwQEfHzRp3BjnL14Ule1M0c1WHA4H/fv2xc49e0Rla2aGzdu2icq2WTPx7x46cgS13NygIRDg7r178N6wARPGjhWfI/x3/TpiYmJQo0YN8NXUcPfePezeuxeDixjlqlT5LlyYl+/Bg6J8c65xzZs/X5RvTueyfn37YuTo0QXznTUrL99+/bBz9+68fLdulVqXnwYGIigoCO716kGgqYnAwED8uW4dOrRvDx0dHQCAh4cHnBwdsXDxYvwxeTJYdjZWrFqFBh4eUqNLEEJIRVGmWoWFhQUiIyNRrVo12NnZ4cKFC6hbty4CAgK+OSKEPA0cPAQpKalYuWwpEhMTUbNWLazx9paK4cOHD4jLaeQBgNZt2kAojMWObdsQEx0NewcHrFnnLXXh7e/jx7Frxw7x83GjRcOnzv7fPHTq3Bn37t3D+/fv8P79O3Tvkte5AgBu3r2H8tS1d1+kpaZi+4Z1SE5MhKNrDcxcuEyqZ+LnyEgkxMWLn0e8CMOimVPFz/dv3wIAaNa6Dcb+IfuQV2XRpnETCOPisf3gQUQLY2FvY4O1c+eJp9v49DVKam6vmk5OWDhpMrb6+WKLzwFYmppi5fSZsKuWN4TT19hYeO/ZjZi4OBjp6aNDixYY0ftnqd89fuE8dh4+JH4++n+iyujccRPQ+aefFJhxQS06dUN6WhqO7d6K1ORkWNs74Zeps6UaKqO/fEZSQl5Zvn8Vga3L8uYPPuMrmnO8XpPm6DtSVCmKF8bitO8+JMYJoa2nj3qNm6FVd9nnBZdFa48GECYkYPvfJxATHwd7y2r4c/IU8XQbn2OiwZUo76/CWAxbkDevve95f/ie90cdR0dsnC6q3MXGx2PRzm2IjouDpoYGqltYYu3kKfAoYiQDRev2c1+kpqZi6/q1SE5MhJNrDcxZvFx62/z4EQlxeXdxNm7eEvFxcTi0fw+EsbGwtrXDnMXLpIbr//D+HXx270RiQgJMqlRBz34D0VlixARVVVXc/PcqDh/Yh4yMDJhUrYrOPXqic0/FlnnfAQORmpKCdatWIjExETXcamLZ6jVQk9g/R378gHiJfFu0ag2hUIi9O3eIpuaobo+lq9dA/zucW1O0/abi6K6c7dfBCb9Om1PI9ps3NPT7Vy+xZel88fPTvnsBiLbffqNEJ+gJwlic9t2bt/02aY7W3RUzQkZJtW3dGrFCIbbs2IHonGH4NqxZIx7i79Pnz1Lbby03NyyZPx+btm3Dxq1bYWlhgdXLlqF6TkPdl6go/HfjBgBgQL45O7ds2AD3unWhbF1/Fh1bt63PO7bOWlTIsTU+b3/cqHkLxMcJcfjAXghjRFNzzFq0VGr7jXz/Hn57dom33x79BqBTj7zy1NHVxaxFS3Fw724smjkNWZlZsLCywrR5C4qcqkdRmnTogoz0NJzeuwOpycmoZu+AQZNnSo38EBv1GcmJeet0wLVLAIDdK6XnVe8+fBTqNGmOyDev8f5lOADAe9ZkqWUmrfAWdw5Sptbu9SFMTMSOM6cQEx8PewsLrBn/OwxyTvg/x8aAw5U4HsUJMXzZYvFzv0sX4XfpIurYO+CvnE55X4Sx8Nq9A/FJSdDT0kJNu+rYOm0m9JV8QaY4Hq07ICMtDRf89iItJRnmdvboNfYP8CQuqgi/fkGKRPk+uX4VAHDIW/qOzfaDRqBGQ9EdbfVatkVmRgauHfNDSnISTMwt0Xv8FOgp8C71IUOHIjU1FUuXLkViQgJq1a4N7/Xrpc8P3r8XX+QGgDZt2yI2NhbbtmxBdM7QuN4bNkgNzTr5jz/A5XIxc/p0pKeno6GnJ6ZLNA6WhEAgwF8bN2L1ypUYOngwdPX00Lp1a4wu5g4yRbgX/gaqPBW0q+UMvioPH2KEOHr7MbIk7jzV09SAhsQ+TsBXQ8e6rtDk85GWmYmv8Qk4cvsR3kTJZ+qUkqrI5fv38ePIysrCyhUrsFLiTuZOnTvDq4hhlBWheceuSE9Lw/E923LOIRwxfOqsgnUQie35zpWLAIBtEucRAND71zFwb9pCKXGX1O3QV1BTUUGneq5QV+Xh3Vch/G48kFp/9TUFEPDz9l+afDV0re8GLXU+0jIy8CUuEb7XH+DVF9FF5MysbFQz0oeHvRU01FSRlJqGt19jsefqXSSnFT0KgaJ17tUHaamp2LnBG8lJiXBwccWMhUuk6x+fpOsfL1+EYcnsvHP4Azu2AgCatmqD0ZNF5/wP7t7BtnVrxMv8tXIZAKBn/0HoNXCwQnPK1fannyCME2Lrnt2i+qNddaxfsTKv/vjls9TxtlaNGlg893/YvGsnNu3YAUtzc6xetBjVc0Z64qpw8frdW5z1Og9hXBx0dXTg4uiEbes3wM7GBgCgpqqKi1euYPuePcjIyICZqSn69/4ZA3/+uWCAis7/B6g/S2rTsiVi4+Kwbc8eRMfGwsHODt7Ll4vz/fzli1S+NV1dsWjOHGzZtQubdu2Cpbk5Vi1cKC5LZWrbtq2orLZuFR9DNqxfLz6GfPr0SbqsatXCksWLsWnzZmzctAmWlpZYvXo1qktcuB86ZAhSU1KwdOlSJCQmonatWlif71i2aNEirFy1CmPHjgWHw8FPP/2EaVPz2u3q16+PxYsXY9++fdi3fz/U1dXh5uaGDevXS3W8HDhokPj/ISEh8D9/Hqampjh96lSp/g7ldfy9fPkyYmNj8c8//+Cff/4Rv25qaoqTp0+LnycmJuLKlSuYIvE3ksXgIUORmpKK5UuXIjExATVr1ca6fPm+/1AwX6EwFtu3ivK1d3DA2vXS+U6a/Ae4HC5mzRDl26Bh4fWN0ydPoXmLllLTcuT6+4SovrF65QqsXplX3+jYqTPmlaG+UR7ruLq6Oq5evYpt27YhJSUFRkZG8PT0xC8jRoiPcSoqKti7bx/evn0LxhhMq1ZFn59/xoABA0qdY3nnW1I7d+5EZGQkVFRUYG1tjaVLl6J1q1Yy5ZufvI8/gKgTwIKlS8XPZ3uJ2mt/GzECo375BTweD96rV2PD5s34Y/p0JKekwNLCAvPnzkWTRkWPglvq3Nq0EeW2fbuobO3tsWHt2qLLtmZNLFm4EJu2bsXGLVtEZbtyJapLjGo8dPBg0b5v+XJR2dasifXr1kmVbfCzZ9i2fTuSU1JgbWWF2TNnolOHDuL3eTweDh87hj+9vcEYg6WFBSZPnIgepRz1psh8t23LW5fXrcvL9/NnqRtPatWsiSWLFmHTli3YuHlz0fmmpGDpsmV567LEtTY1VVVcuHgR23bsENelBvTrh4ES2yWXy8XaNWuwcvVqjBw9Ghrq6mjk6YlJEyfKlC8hhCgKh5VhXKOZM2dCR0cHs2fPxqFDhzBo0CBYW1vj7du3mDx5MpYvX16mYL4KSzvE6/fLSE8Xj3LubPkR1LGrhtigZ99esJLQr+GCk3eflHcYStOtQS1E37hd3mEojWETTzx99a68w1CamjaWePulfO6iKw/VTIxw6t7Tby9YSXT1qImErz9O+WobGeHxyx/n+FvbthoO3njw7QUriX5N6uHr5WvlHYbSGLVqge0Xb5Z3GErzW5vGiJPoXFbZ6WprY9XJS+UdhtJM69b6hyvfE3cel3cYStOjYW0sPnq+vMNQmrm92+H+i9flHYbSuNtbI/5j5LcXrCR0zEx/uPpznMSw2ZWdroWFVOejyk5bR+eHO/7Gxv84+erraP9w6/MPl+8PdjxKiI399oKVhLa+vniEtx+BtpymhSaEkNIo00gSkp0g+vbti2rVquH27duwt7cXD09FCCGEEEIIIYQQQgghhBBCCCGEEFKRlH0SLwmenp7w9PSUx1cRQgghhBBCCCGEEEIIIYQQQgghhChEiTtJnCrFfHVdu3YtUzCEEEIIIYQQQgghhBBCCCGEEEIIIYpS4k4S3bt3L9FyHA4HWVlZZY2HEEIIIYQQQgghhBBCCCGEEEIIIUQhStxJIjs7W5FxEEIIIYQQQgghhBBCCCGEEEIIIYQoFLc0C1+5cgUuLi6Ij48v8F5cXBxcXV1x/fp1uQVHCCGEEEIIIYQQQgghhBBCCCGEECIvpeoksW7dOvz222/Q0dEp8J6uri5GjRqFP//8U27BEUIIIYQQQgghhBBCCCGEEEIIIYTIS6k6STx58gTt27cv8v22bdviwYMHMgdFCCGEEEIIIYQQQgghhBBCCCGEECJvpeok8fnzZ6iqqhb5Po/HQ1RUlMxBEUIIIYQQQgghhBBCCCGEEEIIIYTIW6k6SZibmyMoKKjI958+fQpTU1OZgyKEEEIIIYQQQgghhBBCCCGEEEIIkbdSdZLo2LEj/ve//yE1NbXAeykpKfDy8kLnzp3lFhwhhBBCCCGEEEIIIYQQQgghhBBCiLzwSrPw3Llzcfz4cTg4OGD8+PFwdHQEADx//hwbN25EVlYW5syZo5BACSGEEEIIIYQQQgghhBBCCCGEEEJkUapOElWqVMGtW7cwZswYzJo1C4wxAACHw0G7du2wceNGVKlSRSGBEkIIIYQQQgghhBBCCCGEEEIIIYTIolSdJADAysoK586dQ2xsLMLDw8EYg729PfT19RURHyGEEEIIIYQQQgghhBBCCCGEEEKIXJS6k0QufX191K9fX56xEEIIIYQQQgghhBBCCCGEEEIIIYQoDLe8AyCEEEIIIYQQQgghhBBCCCGEEEIIUQbqJEEIIYQQQgghhBBCCCGEEEIIIYSQHwJ1kiCEEEIIIYQQQgghhBBCCCGEEELID4E6SRBCCCGEEEIIIYQQQgghhBBCCCHkh0CdJAghhBBCCCGEEEIIIYQQQgghhBDyQ6BOEoQQQgghhBBCCCGEEEIIIYQQQgj5IVAnCUIIIYQQQgghhBBCCCGEEEIIIYT8EKiTBCGEEEIIIYQQQgghhBBCCCGEEEJ+CNRJghBCCCGEEEIIIYQQQgghhBBCCCE/BvYDS01NZV5eXiw1NbW8Q1EKyrdyo3wrN8q3cqN8KzfKt3KjfCs3yrdyo3wrN8q3cqN8KzfKt3KjfCs3yrdyo3wrN8qXEPKj4TDGWHl31Cgv8fHx0NXVRVxcHHR0dMo7HIWjfCs3yrdyo3wrN8q3cqN8KzfKt3KjfCs3yrdyo3wrN8q3cqN8KzfKt3KjfCs3yrdyo3wJIT8amm6DEEIIIYQQQgghhBBCCCGEEEIIIT8E6iRBCCGEEEIIIYQQQgghhBBCCCGEkB8CdZIghBBCCCGEEEIIIYQQQgghhBBCyA/hh+4kwefz4eXlBT6fX96hKAXlW7lRvpUb5Vu5Ub6VG+VbuVG+lRvlW7lRvpUb5Vu5Ub6VG+VbuVG+lRvlW7lRvpUb5UsI+dFwGGOsvIMghBBCCCGEEEIIIYQQQgghhBBCCFG0H3okCUIIIYQQQgghhBBCCCGEEEIIIYT8OKiTBCGEEEIIIYQQQgghhBBCCCGEEEJ+CNRJghBCCCGEEEIIIYQQQgghhBBCCCE/BOokQQghhBBCCCGEEEIIIYQQQgghhJAfQqXvJDFs2DB07969vMMghBBCCCGEEEIIIYQQQgghhCgBh8PB33//Xd5hEEIqqO+6kwSHwyn2MX/+fHh7e2PPnj3lHapSdOnSBe3bty/0vevXr4PD4eDp06f4/fffUa9ePfD5fNSuXVu5QcpRSfJ98uQJ+vfvD0tLS2hoaMDZ2Rne3t5KjlQ+SpLvv//+i/bt28PMzAx8Ph+WlpYYP3484uPjlRyt7Eq6PueKjo6GhYUFOBwOhEKhkqKUn5LmW9i+7uDBg0qOVnalKd89e/agZs2aUFdXh4mJCcaNG6fMUOWiJPmuX7++yOPZly9flByxbEpavgEBAWjVqhX09PSgr6+Pdu3a4cmTJ0qOVnYlzffy5cto1KgRtLW1UbVqVcyYMQOZmZlKjrZ05Fm3ePr0KZo2bQp1dXVYWlpi5cqVCoy8bOSVb2pqKoYNGwY3NzfweLwK22FXXvleu3YN3bp1g6mpKTQ1NVG7dm34+PgoOPrSk1e+oaGhaNmyJapUqQJ1dXXY2tpi7ty5yMjIUHAGpaOIc4Pw8HBoa2tDT09P/gHLSF75vn79utBj8Z07dxScQenIs3wZY1i9ejUcHBzA5/Nhbm6OJUuWKDD60pNXvvPnzy+0fDU1NRWcQenIs3zPnz+Phg0bQltbG8bGxujVqxdev36tuODLQJ75Hj58GLVr14ZAIICVlRVWrVqlwMjLRp5tGdeuXUPdunXB5/NRvXr1Ctn+Ja98IyMjMWDAADg4OIDL5WLSpElKiL705JXv8ePH0aZNGxgbG0NHRweenp44f/68MlIoFXnle+PGDTRu3BiGhobQ0NCAk5MT1q5dq4wUSkURbZE3b94Ej8erkG208sr32rVrhR5/P336pIw0Skye5ZuWloY5c+bAysoKfD4f1tbW2LVrl6JTKBV55Tts2LBCy9fV1VUZaZSYPMvXx8cHtWrVgkAggKmpKUaMGIHo6GhFpwAAuH37NlRUVNCpUyel/J68tGjRQiHH7k+fPmHChAmwtbUVXw/p0qULLl++LPffIoRUQuw7FhkZKX6sW7eO6ejoSL2WkJBQ3iEq1YkTJxiXy2Xv3r0r8N7w4cOZu7s7Y4yxCRMmsL/++osNHjyY1apVS8lRyk9J8t25cyf7/fff2bVr11hERATbv38/09DQYBs2bCiHiGVTknxjYmLYpk2bWEBAAHv9+jW7dOkSc3R0ZP379y+HiGVT0vU5V7du3ViHDh0YABYbG6ukKOWnpPkCYLt375ba16WkpCg7XJmVNN81a9YwMzMz5uPjw8LDw9mTJ0/YyZMnlR2uzEqSb3JyslS5RkZGsnbt2rHmzZsrP2AZlSTfhIQEZmBgwIYNG8aeP3/OgoKCWK9evViVKlVYenp6OURddiXJ9/Hjx0xNTY0tWLCAvXjxgl27do05OTmxKVOmlEPEJSevukVcXByrUqUKGzhwIAsKCmJ+fn5MQ0ODbd26VdEplIq88k1MTGSjR49m27ZtY+3atWPdunVTcORlI698lyxZwubOnctu3rzJwsPD2bp16xiXy2WnT59WdAqlIq98IyIi2K5du9jjx4/Z69ev2cmTJ5mJiQmbNWuWolMoFXmfG6SnpzN3d3fWoUMHpqurq6Coy05e+b569YoBYJcuXZI6Jle0Y5M8y3fChAnM0dGRnTx5kr18+ZLdv3+fXbhwQZHhl5q88k1ISChQ33JxcWFDhw5VcAalI698X758yfh8Pps1axYLDw9nDx48YM2aNWN16tRRdAqlIq98z507x3g8Htu8eTOLiIhgZ86cYaamphXu/F9ebRkvX75kAoGA/fHHH+zZs2dsw4YNTEVFhfn7+ysznW+SV76vXr1iv//+O9u7dy+rXbs2mzhxohKzKDl55Ttx4kS2YsUKdu/ePRYWFsZmzZrFVFVV2cOHD5WZzjfJK9+HDx8yX19fFhQUxF69esX279/PBALBd3m+UJq2yNjYWGZra8vatm1bIdto5ZXv1atXGQAWGhoqdQzOyspSZjrfJM/y7dq1K2vQoAG7ePEie/XqFbt16xa7ceOGslIpEXnlKxQKpcr13bt3zMDAgHl5eSkxm2+TV743btxgXC6XeXt7s5cvX7Lr168zV1dX1qNHD6Xk8csvv7CJEycyLS0t9uHDB6X8pjw0b95c7sfuV69eMTMzM+bi4sKOHj3KQkNDWVBQEFuzZg1zdHRkjIna0k+cOCHX3yWEVB7fdScJSbt37y60sW7o0KFSDdPNmzdn48ePZxMnTmR6enrMxMSEbdu2jSUmJrJhw4YxLS0tZmdnx86dOyf1PYGBgax9+/ZMU1OTmZiYsEGDBrGoqCgFZ1U6GRkZrEqVKmzRokVSryckJDAtLS22efNmqde9vLwqZAW8pEqbb66xY8eyli1bKiNEuSprvt7e3szCwkIZIcpVafLdtGkTa968Obt8+fJ320mipPlWlopdSfKNiYlhGhoa7NKlS+UUpfyUZfv98uULU1VVZfv27VNWmHJTknwDAgIYAPb27Vvx+0+fPmUA2IsXL5QdskxKku+sWbMKdO46deoUU1dXZ/Hx8coMt1TkVbfYtGkT09fXZ2lpaeLXZsyYIT5prSgUUZfKXxetSBRZd+zYsSMbPny4vEKVC0XmO3nyZNakSRN5hSoX8s53+vTpbNCgQUWed5U3eeWb20ni0aNHCoxWdvLK99mzZ4zH47Hnz58rMlyZKWr7ffz4MQPA/vvvP3mGKzN55XvkyBHG4/GkLkKdOnWKcTicCtXxR1759u/fn/Xu3VvqtfXr1zMLCwuWnZ0t97jLSl5tGdOnT2eurq5Sy/Tt25e1a9dO/kHLQBFtN4q40CIvimyrcnFxYQsWLJBbrPKgyHx79OjBBg0aJLdY5UHe+fbt25fNnTu3wrbRyivf3E4SFb29Tl75/vPPP0xXV5dFR0crNF5ZKWr7PXHiBONwOOz169dyjVdW8sp31apVzNbWVmqZ9evXM3Nzc/kHnU9urM+fP2d9+/ZlS5YsEb+Xu535+/uz2rVrM3V1ddayZUv2+fNndu7cOebk5MS0tbVZ//79WVJSkvhzqampbMKECczY2Jjx+XzWuHFjdu/ePfH7hZ3/nThxgknef527D9u3bx+zsrJiOjo6rG/fvuL2rqFDhzIAUo9Xr17J/Pfo0KEDMzc3Z4mJiQXey93f5G9Lnz59OrO3t2caGhrMxsaGzZ07V6pe/PjxY9aiRQumpaXFtLW1Wd26dVlAQABjjLHXr1+zzp07Mz09PSYQCJiLiws7e/aszHkQQsrPdz3dRlnt3bsXRkZGuHfvHiZMmIAxY8bg559/RqNGjfDw4UO0bdsWgwcPRnJyMgBAKBTip59+Qp06dXD//n34+/vj8+fP6NOnTzlnIo3H42HIkCHYs2cPGGPi148cOYKsrCz079+/HKOTv7LmGxcXBwMDA2WFKTdlyffjx484fvw4mjdvrsxQ5aKk+T579gwLFy7Evn37wOV+v7u00pTvuHHjYGRkBA8PD+zatUtq+e9FSfK9ePEisrOz8eHDBzg7O8PCwgJ9+vTBu3fvyjHysinL9rtv3z4IBAL07t1bmaHKRUnydXR0hKGhIXbu3In09HSkpKRg586dcHZ2hrW1dfkFXwYlyTctLQ3q6upSn9PQ0EBqaioePHig7JBLTF51i9u3b6NZs2ZQU1MTv9auXTuEhoYiNjZW7nGXFdWlROSRb0Wsbykq3/DwcPj7+1e4+pY8871y5QqOHDmCjRs3KiJUuZB3+Xbt2hUmJiZo0qQJTp06Je9wZSavfE+fPg1bW1ucOXMGNjY2sLa2xq+//oqYmBhFhV4mitp+d+zYAQcHBzRt2lReocqFvPKtV68euFwudu/ejaysLMTFxWH//v1o3bo1VFVVFRV+qckr36LqW+/fv8ebN2/kGrMs5NWWcfv2bbRu3VpqmXbt2uH27duKCbyMqO1GRNZ8s7OzkZCQUOH+JorK99GjR7h161alqV8Vlu/u3bvx8uVLeHl5KTRmWci7fGvXrg1TU1O0adMGN2/eVFjcZSWvfE+dOgV3d3esXLkS5ubmcHBwwNSpU5GSkqLwHEpDUdvvzp070bp1a1hZWck9ZlnIK19PT0+8e/cO586dA2MMnz9/xtGjR9GxY0eF53D48GE4OTnB0dERgwYNKrRdeP78+fjrr79w69YtvHv3Dn369MG6devg6+uLs2fP4sKFC9iwYYN4+enTp+PYsWPYu3cvHj58iOrVq6Ndu3alPh+IiIjA33//jTNnzuDMmTP4999/sXz5cgCAt7c3PD098dtvvyEyMhKRkZGwtLSU6W8RExMDf39/jBs3rtCp84qaIlJbWxt79uzBs2fP4O3tje3bt0tN7zRw4EBYWFggICAADx48wMyZM8X15nHjxiEtLQ3//fcfAgMDsWLFCmhpacmUByGknCmhI4ZSlGYkCcm7vDIzM5mmpiYbPHiw+LXIyEgGgN2+fZsxxtiiRYtY27Ztpb733bt34mHCKpKQkBAGgF29elX8WtOmTQvteV1ReymXRmnyZYyxmzdvMh6Px86fP6+kCOWrpPn269ePaWhoMACsS5cu3+V0DIx9O9/U1FRWs2ZNtn//fsbY99MzvSglKd+FCxeyGzdusIcPH7Lly5czPp/PvL29yyFa2X0r32XLljFVVVXm6OjI/P392e3bt1mrVq2Yo6Oj1N3o34vS7q+cnZ3ZmDFjlBSd/JUk38DAQGZnZ8e4XC7jcrnM0dGxwt1pUFLfyvf8+fOMy+UyX19flpmZyd6/f8+aNm3KADBfX99yirpk5FG3aNOmDRs5cqTUa8HBwQwAe/bsmbxDlom861IVeSQJxhRTdzx06BBTU1NjQUFBcoxUPuSZr6enJ+Pz+QwAGzlyZIUbLpgx+eT79etXZmlpyf7991/GWNHnXRWBPPKNiopia9asYXfu3GH37t1jM2bMYBwOp0JO9yWPfEeNGsX4fD5r0KAB+++//9jVq1dZ7dq1K+TIe/LeX6WkpDB9fX22YsUKOUcqH/LK99q1a8zExISpqKgwAMzT07NCni/JI9+tW7cygUDALl26xLKyslhoaChzcnJiANitW7cUGH3pyaMtw97eni1dulRqubNnzzIALDk5WSFxl5W8224q8kgSjCmmrWrFihVMX1+fff78Wd7hykye+ZqbmzM1NTXG5XLZwoULFRWyTOSRb1hYGDMxMRG3K1fkNlp55Pv8+XO2ZcsWdv/+fXbz5k02fPhwxuPx2IMHDxQdfqnJI9927doxPp/POnXqxO7evcvOnj3LrKys2LBhwxQdfqnJe3/14cMHpqKiwg4dOqSIcGUmr3wPHz7MtLS0GI/HE7e/K2OUrkaNGrF169YxxkQjYxgZGYlzyW0XlxyRd9myZQwAi4iIEL82atQo8ahTiYmJTFVVlfn4+IjfT09PZ2ZmZmzlypWMsZKPJCEQCKRGSp02bRpr0KCB+Lm8j913795lANjx48eLXQ7fGJV51apVrF69euLn2trabM+ePYUu6+bmxubPn1+meAkhFdMP2Uli7NixUstUq1ZNvNNnjLHs7GwGQNwQ1rt3b6aqqso0NTWlHgAKTMtRETRq1Ejc6ePFixcFDvy5KnIFvDRKmm9gYCAzMjIqMKTW96Yk+UZGRrKQkBB28uRJ5uLi8l1faC0u38mTJ7O+ffuKl/3eO0kwVvL1Odf//ve/73I6lVzF5btkyRIGQOpE5MuXL4zL5Va4eXZLqqTle+vWLQaA3b9/X8kRyldx+SYnJzMPDw82ZMgQdu/ePXb79m3Wq1cv5urqWuEadUvqW+W7Zs0apqOjw1RUVJhAIBCfrB48eLCcIi45WesW31MnCcbkW5eq6J0kGJNvvleuXGECgYDt3btXAZHKh7zyffv2LQsODma+vr7M3Ny8wl5olTXfHj16sBkzZoifV+ROEowp5lxo8ODBFW46lVyy5vvbb78V6Pz/4MEDBqBCTsEhz/L19fVlPB6Pffr0SQGRyoes+UZGRjJ7e3s2bdo09vDhQ/bvv/+y5s2bs1atWlWo6SdyyZpvdnY2mz59OlNXV2cqKipMX1+fzZ8/nwFgd+7cUXD0pSdrW8b31EmCMfm23VT0ThKMyTdfHx8fJhAI2MWLFxUVrszkle/Lly/Z06dP2bZt25iBgUGF7VAuS76ZmZnM3d1damj/it5Gq4i212bNmlW46VRyyZpvmzZtmLq6OhMKheLXjh07xjgcTqXfPy9dupQZGhpW6JubZM03ODiYmZqaspUrV7InT54wf39/5ubmxkaMGKHQuJ8/f854PJ5UZ7lx48aJt6PcdvEvX76I39+1axcTCARS3zNv3jxWp04dxhhjT548YQAK3LDUvXt38fSZJe0k4eLiIrXMn3/+yWxsbMTP5X3svnPnTpk6SRw8eJA1atSIValShWlqajI+n8+MjY3F73t5eTEej8datWrFli1bxsLDw8Xvbd++nfF4PNaoUSM2b9489uTJE7nlQwgpHz9kJ4n8O2MrKyu2du1aqdckd57t27dnPXv2ZC9evCjwKGy+o/K2c+dOcc+92bNnMzs7u0IbQCp6BbykSpJvcHAwMzExYbNnzy6nKOWnpOWb6/r16wwA+/jxoxKjlJ/i8q1VqxbjcrlMRUWFqaioMC6XywAwFRUVNm/evHKOvGxKW75nzpxhAFhqaqoSo5Sf4vLdtWsXA8DevXsn9RkTExO2bdu28ghXZiUt3xEjRrDatWuXQ4TyVVy+O3bsYCYmJlJ3XqelpTGBQMD8/PzKK2SZlKR8s7Oz2YcPH1hycjJ79uwZAyA112NFJWvdYvDgwQU6Cly5coUBYDExMQqKuuzkWZf6HjpJyCvfa9euMU1NTbZ161YFRis7RdSV9+/fzzQ0NFhmZqaco5WdrPnq6uqK61r561s7d+5UQgalo4jy/euvv1jVqlXlHKl8yJrvvHnzGI/Hk3otOTmZAWAXLlxQVNhlJs/y/emnn1j37t0VFKl8yJrv3Llzmbu7u9RruaNi5o6cWZHIq3xzR+1KS0tj586dK3DBoKKQtS2jadOmBdq3du3axXR0dBQZdpnJs+3me+gkIa98/fz8mIaGBjtz5oyiQ5aJItrmFi1axBwcHBQRrsxkyTc2NlZcl8p9cDgc8WuXL19WZioloojynTp1KmvYsKEiwpWZrPkOGTKE2dnZSb2We/4fFham0NjLQl7lm52dzapXr84mTZqk6JBlImu+gwYNYr1795Z6TRnt79OmTSuw7+ByuUxDQ4MJhcJCbx4s7JqZZD2qJJ0k9u7dW6Bucfjw4QKdJPLXzdauXcusrKzEz+V97I6OjmYcDqdAh9H8JK/z3bp1i6moqLDFixezgIAAFhYWxhYuXFjgbxQaGsr+/PNP1qZNG6ampibVEePt27ds8+bNrEePHkxVVZWtX79ebjkRQpSPW/gkHERS3bp1ERwcDGtra1SvXl3qUdh8R+WtT58+4HK58PX1xb59+zBixAhwOJzyDkthvpVvcHAwWrZsiaFDh2LJkiXlGKl8lLZ8s7OzAYjmZ/0eFZfvsWPH8OTJEzx+/BiPHz/Gjh07AADXr1/HuHHjyjPsMitt+T5+/Bj6+vrg8/lKjFJ+isu3cePGAIDQ0FDx8jExMfj69WuFm9ewpEpSvomJiTh8+DB++eWXcopSforLNzk5GVwuVyr/3Oe5+63vTUnKl8PhwMzMDBoaGvDz84OlpSXq1q1bThGXnKx1C09PT/z333/IyMgQv3bx4kU4OjpCX19fESHLhOpSpc/32rVr6NSpE1asWIGRI0cqKFL5UET5ZmdnIyMjo0Luv2TN9/bt2+K61uPHj7Fw4UJoa2vj8ePH6NGjhwIjLxtFlO/jx49hamoqpwjlS9Z8GzdujMzMTERERIhfCwsLA4AKWd+SV/m+evUKV69erfD1LVnzza1vSVJRUQGASrm/yqWiogJzc3OoqanBz88Pnp6eMDY2VkDEspG1LcPT0xOXL1+Weu3ixYvw9PRUeOxlQW03pc/Xz88Pw4cPh5+fHzp16qSs0MtEEeWbnZ1dYduyZMlXR0cHgYGBUvWr0aNHw9HREY8fP0aDBg2Unc43KaJ8v+f61bfybdy4MT5+/IjExETxa2FhYeByubCwsFBKDqUhr/L9999/ER4e/t3Xr76Vb3H1K8aYQmLOzMzEvn37sGbNGql9x5MnT2BmZgY/P78yfa+dnR3U1NRw8+ZN8WsZGRkICAiAi4sLAMDY2BgJCQlISkoSL/P48eNS/5aamhqysrLKFGdhDAwM0K5dO2zcuFEqtlxCobDAa7du3YKVlRXmzJkDd3d32Nvb482bNwWWc3BwwOTJk3HhwgX07NkTu3fvFr9naWmJ0aNH4/jx45gyZQq2b98ut5wIIeWgvHtpyIsiR5L48OEDMzY2Zr1792b37t1j4eHhzN/fnw0bNqxC3i3GGGO//PIL09fXZyoqKuzDhw9S77148YI9evSIjRo1ijk4OLBHjx6xR48eVehhsL6lqHwDAwOZsbExGzRoEIuMjBQ/KuJdJKVRVL5nz55lu3btYoGBgezVq1fszJkzzNnZmTVu3Lgco5VdceuzpMow3QZjRed76tQptn37dhYYGMhevHjBNm3axAQCwXc7akau4sq3W7duzNXVld28eZMFBgayzp07MxcXF6XM86co31qfd+zYwdTV1b/79ThXUfmGhIQwPp/PxowZw549e8aCgoLYoEGDmK6u7nc78g1jxZfvypUr2dOnT1lQUBBbuHAhU1VVLXZexIpGlrqFUChkVapUYYMHD2ZBQUHs4MGDTCAQVOgRB2StSwUHB7NHjx6xLl26sBYtWoiXqahkyTd3io1Zs2ZJ1beio6PLI5USkSXfAwcOsEOHDrFnz56xiIgIdujQIWZmZsYGDhxYHqmUiDzPDSr6dBuMyZbvnj17mK+vLwsJCWEhISFsyZIljMvlsl27dpVHKiUiS75ZWVmsbt26rFmzZuzhw4fs/v37rEGDBqxNmzblkUqJyGN9njt3LjMzM6uw5/OSZMn38uXLjMPhsAULFrCwsDD24MED1q5dO2ZlZVUhh/tmTLZ8o6Ki2ObNm1lISAh79OgR+/3335m6ujq7e/dueaRSIrK0Zbx8+ZIJBAI2bdo0FhISwjZu3MhUVFQq9NSEsrbd5JZ5vXr12IABA9ijR49YcHCwstMoMVny9fHxYTwej23cuFFqGcnh+ysaWfL966+/2KlTp1hYWBgLCwtjO3bsYNra2mzOnDnlkUqJyLMt8nsY7VeWfNeuXcv+/vtv9uLFCxYYGMgmTpzIuFwuu3TpUnmkUiKy5JuQkMAsLCxY7969WXBwMPv333+Zvb09+/XXX8sjlRKRx/o8aNAg1qBBA2WGXWay5Lt7927G4/HYpk2bWEREBLtx4wZzd3dnHh4eCov3xIkTTE1NrdBjwPTp05m7u3uZRpJgjLGJEycyMzMz9s8//7Dg4GA2dOhQpq+vLx71Mzo6mmlqarLff/+dhYeHMx8fH2ZmZlbqkSR+++03Vr9+ffbq1SsWFRUlNbJsWUVERLCqVasyFxcXdvToURYWFsaePXvGvL29mZOTE2NM+jrfyZMnGY/HY35+fiw8PJx5e3szAwMD8d8oOTmZjRs3jl29epW9fv2a3bhxg9nZ2bHp06eL/1b+/v7s5cuX7MGDB6xBgwasT58+MudBCCk/1EmCfbuTBGOMhYWFsR49ejA9PT2moaHBnJyc2KRJkyrkPJ6M5c1n37FjxwLvNW/enAEo8Hj16pXyA5WTovL18vIqNFfJA/T3qKh8r1y5wjw9PZmuri5TV1dn9vb2bMaMGd/9xdbi1mdJlaWTRFH5/vPPP6x27dpMS0uLaWpqslq1arEtW7bIpVJZnoor37i4ODZixAimp6fHDAwMWI8ePdjbt2/LIUr5+db67OnpyQYMGKDkqBSnuHwvXLjAGjduzHR1dZm+vj776aefKuTQz6VRXL4tW7YU758bNGjAzp07Vw4Rlp2sdYsnT56wJk2aMD6fz8zNzdny5cuVGH3pyZqvlZVVoctUVLLkO3To0ELfb968uXKTKAVZ8j148CCrW7eu+Hjs4uLCli5dylJSUpScRcnJ89zge+gkIUu+e/bsYc7OzkwgEDAdHR3m4eHBjhw5ouQMSkfW8v3w4QPr2bMn09LSYlWqVGHDhg2r0J2cZM03KyuLWVhYfDdTMcqar5+fH6tTpw7T1NRkxsbGrGvXriwkJESJGZSOLPlGRUWxhg0bMk1NTSYQCFirVq3YnTt3lJxB6cjalnH16lVWu3Ztpqamxmxtbdnu3buVF3wZyJrv99a+I0u+Ra3vQ4cOVW4SpSBLvuvXr2eurq7i42+dOnXYpk2bKnR7hzzbIr+HThKy5LtixQpmZ2fH1NXVmYGBAWvRogW7cuWKkjMoHVnLNyQkhLVu3ZppaGgwCwsL9scff1TYDoqMyZ6vUChkGhoa3830uLLmu379eubi4sI0NDSYqakpGzhwIHv//r3C4u3cuXOR7Yh3795lAJi3tzcDSt9JIiUlhU2YMIEZGRkxPp/PGjduXGBa2BMnTrDq1aszDQ0N1rlzZ7Zt2zap9o2SdJIIDQ1lDRs2ZBoaGsWeb5bWx48f2bhx45iVlRVTU1Nj5ubmrGvXruzq1auMsYLX+aZNm8YMDQ2ZlpYW69u3L1u7dq34b5SWlsb69evHLC0tmZqaGjMzM2Pjx48Xn+uPHz+e2dnZMT6fz4yNjdngwYPZ169f5ZIHIaR8cBhT0BhAhBBCCCGEEEIIIYQQQgghhBBCCCEVCPfbixBCCCGEEEIIIYQQQgghhBBCCCGEfP+okwQhhBBCCCGEEEIIIYQQQgghhBBCfgjUSYIQQgghhBBCCCGEEEIIIYQQQgghPwTqJEEIIYQQQgghhBBCCCGEEEIIIYSQHwJ1kiCEEEIIIYQQQgghhBBCCCGEEELID4E6SRBCCCGEEEIIIYQQQgghhBBCCCHkh0CdJAghhBBCCCGEEEIIIYQQQgghhBDyQ6BOEoQQQgghhBBCCCGEEEIIIYQQQgj5IVAnCUIIIYQQQgghhBBCCCGEEEIIIYT8EKiTBCGEEEIIIYQQQgghhBBCCCGEEEJ+CNRJghBCCCGEEEIIIYQQQgghhBBCCCE/hP8D5VqL2nIetngAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 3000x3000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "corr=df.corr()\n",
    "\n",
    "mask = np.zeros_like(corr, dtype=np.bool_)\n",
    "mask[np.triu_indices_from(mask)] = True\n",
    "\n",
    "# Set up the matplotlib figure\n",
    "f, ax = plt.subplots(figsize=(30, 30))\n",
    "\n",
    "# Generate a custom diverging colormap\n",
    "cmap = sns.diverging_palette(220, 10, as_cmap=True)\n",
    "\n",
    "# Draw the heatmap with the mask and correct aspect ratio\n",
    "sns.heatmap(corr, annot=True, mask=mask, cmap=cmap, vmax=.3, center=0,\n",
    "            square=True, linewidths=.5, cbar_kws={\"shrink\": .5});"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "09270d67",
   "metadata": {},
   "source": [
    "Correlation matrix does not make sense. There is no correlation between the V# variables due to the PCA performed on the features. A correlation matrix only makes sense if the values are linear. Therefore, we are going to have to use other techniques to visualize and fit the data to the Machine Learning model\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "bdd7023a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((199364, 30), (85443, 30), (199364,), (85443,))"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X=df.drop(\"Class\", axis=1)\n",
    "y=df.Class\n",
    "X_train, X_test, y_train, y_test=train_test_split(X,y, test_size=0.3, random_state=42)\n",
    "X_train.shape, X_test.shape, y_train.shape, y_test.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "e98e7a6e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0    199008\n",
       " 1       356\n",
       " Name: Class, dtype: int64,\n",
       " 0    85307\n",
       " 1      136\n",
       " Name: Class, dtype: int64)"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_train.value_counts(), y_test.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "349ad857",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "y_train.value_counts().plot(kind=\"bar\", color=[\"Green\", \"Red\"])\n",
    "plt.xlabel(\"0: Real Transactions, 1: Fraud Transactions\")\n",
    "plt.ylabel(\"Number of Transactions\")\n",
    "plt.title(\"After splitting Comparing real transactions with fraud transactions in training set \")\n",
    "plt.xticks(rotation=0);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e1796b69",
   "metadata": {},
   "source": [
    "# StandardScaler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "2a2ecbcc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((199364, 30), (85443, 30))"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ss=StandardScaler()\n",
    "X_train=ss.fit_transform(X_train)\n",
    "X_test=ss.transform(X_test)\n",
    "X_train.shape, X_test.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "afe1bb38",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-1.95144063, -1.16681856, -0.28654908,  0.53924737, -1.20368154,\n",
       "        0.58967831, -1.23993846,  0.75411155, -0.45490037,  1.2064479 ,\n",
       "       -0.39869658,  0.32182001,  0.58170129,  0.11222719, -0.22290476,\n",
       "        1.38644463, -1.0221033 , -0.35174842, -0.7336555 , -0.49340827,\n",
       "       -1.06710984, -0.28780091,  1.26352311,  1.37067196,  0.69925952,\n",
       "        0.59643511, -1.6211327 ,  0.96676   , -0.4486209 , -0.33974783])"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "86298399",
   "metadata": {},
   "source": [
    "# RobustScaler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "b1fce2c6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((199364, 30), (85443, 30))"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rs=RobustScaler()\n",
    "X_train=rs.fit_transform(X_train)\n",
    "X_test=rs.transform(X_test)\n",
    "X_train.shape, X_test.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0fa16df8",
   "metadata": {},
   "source": [
    "#  OverSampling to fix the imbalanced dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fc33b535",
   "metadata": {},
   "source": [
    "Lets compare RandomOverSampler and SMOTE to see which yields better results"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f021d50e",
   "metadata": {},
   "source": [
    "# RandomOverSamples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "c31f42d3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([[-9.69678271e-01, -1.03021196e+00, -3.89853106e-01, ...,\n",
       "          2.40755159e+00, -1.20903442e+00, -2.92621752e-01],\n",
       "        [ 8.12154550e-01, -1.46415710e-01, -2.94566741e+00, ...,\n",
       "         -1.79529722e+00,  7.51939966e-01,  1.63349822e+01],\n",
       "        [ 1.49019884e-01, -8.15596610e-01, -4.52020772e-01, ...,\n",
       "         -3.91749500e-01,  5.82663156e-01,  7.38521563e-01],\n",
       "        ...,\n",
       "        [-5.65296474e-02, -7.16684334e-02,  6.60692298e-01, ...,\n",
       "         -7.53519424e-01, -1.57703469e+00, -2.51654706e-01],\n",
       "        [ 3.90988402e-02, -1.32501489e+00,  1.63186753e+00, ...,\n",
       "          3.05204820e+00,  2.46482626e+00, -2.92621752e-01],\n",
       "        [-9.66569404e-02,  5.45508041e-01, -6.07057191e-01, ...,\n",
       "         -1.30272865e-04,  2.06669957e-01,  1.26802759e+00]]),\n",
       " 2557      0\n",
       " 247823    0\n",
       " 152342    0\n",
       " 103385    0\n",
       " 8771      0\n",
       "          ..\n",
       " 119879    0\n",
       " 259178    0\n",
       " 131932    0\n",
       " 146867    0\n",
       " 121958    0\n",
       " Name: Class, Length: 199364, dtype: int64)"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train, y_train"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2317d154",
   "metadata": {},
   "source": [
    "# Making sure is actually correctly balancing the dataset out"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "7c0a5638",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Count of \"Class\" feature in training set after ')"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "lol=pd.DataFrame(data=y_train, columns=[\"Class\"])\n",
    "lol.Class.value_counts().plot.bar(color=[\"Red\", \"Green\"]);\n",
    "plt.xlabel(\"Classes\")\n",
    "plt.ylabel(\"Count\")\n",
    "plt.xticks(rotation=0)\n",
    "plt.title(\"Count of \\\"Class\\\" feature in training set after \")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "36899f93",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}