TejasPant_Part1_Household_Income_Prediction.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Prediction of Household Income based on Demographic Data\n",
    "____\n",
    "Tejas Pant <br>\n",
    "07/06/2019"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Objective:** \n",
    "The objective of this study is to predict the class of household income for individuals based on their demographic data. The dataset used for this study is the publicly available NHANES dataset\n",
    "\n",
    "Following steps were taken in the study:<br>\n",
    "* Initial Exploration of Data\n",
    "* Feature Selection and Feature Transformation\n",
    "* Comparison of Performance of Machine Learning Models like:\n",
    "    * Random Forest Classifier\n",
    "    * Gradient Boosting Classifier\n",
    "    * Support Vector Machine Classifier\n",
    "    * k-Nearest Neighbor Classifier\n",
    "    * Naive Bayes Classifier\n",
    "    * Logistic Regression\n",
    "    * Multi-Layer Perceptron Classifier"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load all the required modules, APIs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import datetime as dt\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "from sklearn.metrics import accuracy_score\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.naive_bayes import GaussianNB\n",
    "from sklearn.neural_network import MLPClassifier\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.svm import SVC \n",
    "from sklearn import metrics\n",
    "from sklearn import ensemble\n",
    "from sklearn.metrics import confusion_matrix\n",
    "from sklearn.feature_selection import SelectKBest\n",
    "from sklearn.feature_selection import chi2\n",
    "from sklearn.feature_selection import f_classif"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Reading demographic dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
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       "        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>SEQN</th>\n",
       "      <th>SDDSRVYR</th>\n",
       "      <th>RIDSTATR</th>\n",
       "      <th>RIAGENDR</th>\n",
       "      <th>RIDAGEYR</th>\n",
       "      <th>RIDAGEMN</th>\n",
       "      <th>RIDRETH1</th>\n",
       "      <th>RIDRETH3</th>\n",
       "      <th>RIDEXMON</th>\n",
       "      <th>RIDEXAGM</th>\n",
       "      <th>...</th>\n",
       "      <th>DMDHREDU</th>\n",
       "      <th>DMDHRMAR</th>\n",
       "      <th>DMDHSEDU</th>\n",
       "      <th>WTINT2YR</th>\n",
       "      <th>WTMEC2YR</th>\n",
       "      <th>SDMVPSU</th>\n",
       "      <th>SDMVSTRA</th>\n",
       "      <th>INDHHIN2</th>\n",
       "      <th>INDFMIN2</th>\n",
       "      <th>INDFMPIR</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>9971.000000</td>\n",
       "      <td>9971.0</td>\n",
       "      <td>9971.000000</td>\n",
       "      <td>9971.000000</td>\n",
       "      <td>9.971000e+03</td>\n",
       "      <td>6.950000e+02</td>\n",
       "      <td>9971.000000</td>\n",
       "      <td>9971.000000</td>\n",
       "      <td>9544.000000</td>\n",
       "      <td>4.060000e+03</td>\n",
       "      <td>...</td>\n",
       "      <td>9575.000000</td>\n",
       "      <td>9909.000000</td>\n",
       "      <td>5226.000000</td>\n",
       "      <td>9971.000000</td>\n",
       "      <td>9.971000e+03</td>\n",
       "      <td>9971.000000</td>\n",
       "      <td>9971.000000</td>\n",
       "      <td>9626.000000</td>\n",
       "      <td>9642.000000</td>\n",
       "      <td>8.919000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>88717.000000</td>\n",
       "      <td>9.0</td>\n",
       "      <td>1.957176</td>\n",
       "      <td>1.509377</td>\n",
       "      <td>3.189941e+01</td>\n",
       "      <td>1.078561e+01</td>\n",
       "      <td>3.007321</td>\n",
       "      <td>3.213118</td>\n",
       "      <td>1.518650</td>\n",
       "      <td>1.045350e+02</td>\n",
       "      <td>...</td>\n",
       "      <td>3.459530</td>\n",
       "      <td>2.813503</td>\n",
       "      <td>3.596441</td>\n",
       "      <td>31740.150837</td>\n",
       "      <td>3.174015e+04</td>\n",
       "      <td>1.485809</td>\n",
       "      <td>126.266673</td>\n",
       "      <td>11.522439</td>\n",
       "      <td>11.252126</td>\n",
       "      <td>2.269277e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>2878.524101</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.202471</td>\n",
       "      <td>0.499937</td>\n",
       "      <td>2.476883e+01</td>\n",
       "      <td>7.015325e+00</td>\n",
       "      <td>1.317594</td>\n",
       "      <td>1.679606</td>\n",
       "      <td>0.499678</td>\n",
       "      <td>6.897295e+01</td>\n",
       "      <td>...</td>\n",
       "      <td>1.331829</td>\n",
       "      <td>5.962991</td>\n",
       "      <td>1.381068</td>\n",
       "      <td>32929.536529</td>\n",
       "      <td>3.410557e+04</td>\n",
       "      <td>0.499824</td>\n",
       "      <td>4.238500</td>\n",
       "      <td>15.191049</td>\n",
       "      <td>15.219413</td>\n",
       "      <td>1.576345e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>83732.000000</td>\n",
       "      <td>9.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>5.397605e-79</td>\n",
       "      <td>5.397605e-79</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>5.397605e-79</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3293.928267</td>\n",
       "      <td>5.397605e-79</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>119.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>5.397605e-79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>86224.500000</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>9.000000e+00</td>\n",
       "      <td>5.000000e+00</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>4.100000e+01</td>\n",
       "      <td>...</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>12878.501052</td>\n",
       "      <td>1.255053e+04</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>123.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>9.700000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>88717.000000</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.700000e+01</td>\n",
       "      <td>1.000000e+01</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000e+02</td>\n",
       "      <td>...</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>20160.468137</td>\n",
       "      <td>2.028132e+04</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>126.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>1.820000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>91209.500000</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>5.300000e+01</td>\n",
       "      <td>1.700000e+01</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.620000e+02</td>\n",
       "      <td>...</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>33257.364572</td>\n",
       "      <td>3.370815e+04</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>130.000000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>3.480000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>93702.000000</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>8.000000e+01</td>\n",
       "      <td>2.400000e+01</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.390000e+02</td>\n",
       "      <td>...</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>233755.841850</td>\n",
       "      <td>2.423867e+05</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>133.000000</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>5.000000e+00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 47 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               SEQN  SDDSRVYR     RIDSTATR     RIAGENDR      RIDAGEYR  \\\n",
       "count   9971.000000    9971.0  9971.000000  9971.000000  9.971000e+03   \n",
       "mean   88717.000000       9.0     1.957176     1.509377  3.189941e+01   \n",
       "std     2878.524101       0.0     0.202471     0.499937  2.476883e+01   \n",
       "min    83732.000000       9.0     1.000000     1.000000  5.397605e-79   \n",
       "25%    86224.500000       9.0     2.000000     1.000000  9.000000e+00   \n",
       "50%    88717.000000       9.0     2.000000     2.000000  2.700000e+01   \n",
       "75%    91209.500000       9.0     2.000000     2.000000  5.300000e+01   \n",
       "max    93702.000000       9.0     2.000000     2.000000  8.000000e+01   \n",
       "\n",
       "           RIDAGEMN     RIDRETH1     RIDRETH3     RIDEXMON      RIDEXAGM  \\\n",
       "count  6.950000e+02  9971.000000  9971.000000  9544.000000  4.060000e+03   \n",
       "mean   1.078561e+01     3.007321     3.213118     1.518650  1.045350e+02   \n",
       "std    7.015325e+00     1.317594     1.679606     0.499678  6.897295e+01   \n",
       "min    5.397605e-79     1.000000     1.000000     1.000000  5.397605e-79   \n",
       "25%    5.000000e+00     2.000000     2.000000     1.000000  4.100000e+01   \n",
       "50%    1.000000e+01     3.000000     3.000000     2.000000  1.000000e+02   \n",
       "75%    1.700000e+01     4.000000     4.000000     2.000000  1.620000e+02   \n",
       "max    2.400000e+01     5.000000     7.000000     2.000000  2.390000e+02   \n",
       "\n",
       "           ...          DMDHREDU     DMDHRMAR     DMDHSEDU       WTINT2YR  \\\n",
       "count      ...       9575.000000  9909.000000  5226.000000    9971.000000   \n",
       "mean       ...          3.459530     2.813503     3.596441   31740.150837   \n",
       "std        ...          1.331829     5.962991     1.381068   32929.536529   \n",
       "min        ...          1.000000     1.000000     1.000000    3293.928267   \n",
       "25%        ...          3.000000     1.000000     3.000000   12878.501052   \n",
       "50%        ...          4.000000     1.000000     4.000000   20160.468137   \n",
       "75%        ...          4.000000     4.000000     5.000000   33257.364572   \n",
       "max        ...          9.000000    99.000000     9.000000  233755.841850   \n",
       "\n",
       "           WTMEC2YR      SDMVPSU     SDMVSTRA     INDHHIN2     INDFMIN2  \\\n",
       "count  9.971000e+03  9971.000000  9971.000000  9626.000000  9642.000000   \n",
       "mean   3.174015e+04     1.485809   126.266673    11.522439    11.252126   \n",
       "std    3.410557e+04     0.499824     4.238500    15.191049    15.219413   \n",
       "min    5.397605e-79     1.000000   119.000000     1.000000     1.000000   \n",
       "25%    1.255053e+04     1.000000   123.000000     6.000000     5.000000   \n",
       "50%    2.028132e+04     1.000000   126.000000     8.000000     8.000000   \n",
       "75%    3.370815e+04     2.000000   130.000000    14.000000    14.000000   \n",
       "max    2.423867e+05     2.000000   133.000000    99.000000    99.000000   \n",
       "\n",
       "           INDFMPIR  \n",
       "count  8.919000e+03  \n",
       "mean   2.269277e+00  \n",
       "std    1.576345e+00  \n",
       "min    5.397605e-79  \n",
       "25%    9.700000e-01  \n",
       "50%    1.820000e+00  \n",
       "75%    3.480000e+00  \n",
       "max    5.000000e+00  \n",
       "\n",
       "[8 rows x 47 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('DEMO_I.csv')\n",
    "df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Description of all the features in the data <br>\n",
    "**SEQN** - Respondent sequence number. Unique number for each member <br>\n",
    "**SDDSRVYR** - Data release cycle. Same for all the entries in table since data is for 2015-2016 <br>\n",
    "**RIDSTATR** - Interview and examination status of the participant. Some members were only interviewed while others were examined too <br>\n",
    "**RIAGENDR** - Gender of participant <br>\n",
    "**RIDAGEYR** - Age in years at the time of screening <br>\n",
    "**RIDAGEMN** - Age in months of the participant at the time of screening. Reported\n",
    "for persons aged 24 months or younger at the time of exam <br>\n",
    "**RIDRETH1** - Recode of reported race and Hispanic origin information <br>\n",
    "**RIDRETH3** - Recode of reported race and Hispanic origin information, with NonHispanic Asian Category. Use this. <br>\n",
    "**RIDEXMON** - Six month time period when the examination was performed two\n",
    "categories: November 1 through April 30, May 1 through October 31. <br>\n",
    "**RIDEXAGM** - Age in months of the participant at the time of examination.\n",
    "Reported for persons aged 19 years or younger at the time of\n",
    "examination <br>\n",
    "**DMQMILIZ** - {Have you/Has SP} ever served on active duty in the U.S. Armed\n",
    "Forces, military Reserves, or National Guard? (Active duty does not\n",
    "include training for the Reserves or National Guard, but does include\n",
    "activation, for service in the U.S. or in a foreign country, in support\n",
    "of military or humanitarian operations.) <br>\n",
    "**DMQADFC** - Did {you/SP} ever serve in a foreign country during a time of armed\n",
    "conflict or on a humanitarian or peacekeeping\n",
    "mission? (This would\n",
    "include National Guard or reserve or active duty monitoring or\n",
    "conducting peace keeping operations in Bosnia and Kosovo, in the\n",
    "Sinai between Egypt and Israel, or in response to the 2004 tsunami\n",
    "or Haiti in 2010.) <br>\n",
    "**DMDBORN4** - In what country {were you/was SP} born? <br>\n",
    "**DMDCITZN** - {Are you/Is SP} a citizen of the United States <br>\n",
    "**DMDYRSUS** - Length of time the participant has been in the US <br>\n",
    "**DMDEDUC3** - What is the highest grade or level of school {you have/SP has}\n",
    "completed or the highest degree {you have/s/he has} received?. Only for people betweenn 6-19 years <br>\n",
    "**DMDEDUC2** - What is the highest grade or level of school {you have/SP has}\n",
    "completed or the highest degree {you have/s/he has} received?. For adults 20+ <br>\n",
    "**DMDMARTL** - Marital Status <br>\n",
    "**RIDEXPRG** - Pregnancy status for females between 20 and 44 years of age at the\n",
    "time of MEC exam <br>\n",
    "**SIALANG** - Language of the Sample Person Interview Instrument <br>\n",
    "**SIAPROXY** - Was a Proxy respondent used in conducting the Sample Person (SP)\n",
    "interview? <br>\n",
    "**SIAINTRP** - Was an interpreter used to conduct the Sample Person (SP)\n",
    "interview? <br>\n",
    "**FIALANG** - Language of the Family Interview Instrument <br>\n",
    "**FIAPROXY** - Was a Proxy respondent used in conducting the Family Interview? <br>\n",
    "**FIAINTRP** - Was an interpreter used to conduct the Family interview <br>\n",
    "**MIALANG** - Language of the MEC CAPI Interview Instrument <br>\n",
    "**MIAPROXY** - Was a Proxy respondent used in conducting the MEC CAPI Interview? <br>\n",
    "**MIAINTRP** - Was an interpreter used to conduct the MEC CAPI interview <br>\n",
    "**AIALANGA** - Language of the MEC ACASI Interview Instrument <br>\n",
    "**DMDHHSIZ** - Total number of people in the Household <br>\n",
    "**DMDFMSIZ** - Total number of people in the Family <br>\n",
    "**DMDHHSZA** - Number of children aged 5 years or younger in the household <br>\n",
    "**DMDHHSZB** - Number of children aged 6-17\n",
    "years old in the household <br>\n",
    "**DMDHHSZE** - Number of adults aged 60 years or older in the household <br>\n",
    "**DMDHRGND** - HH reference person's gender <br>\n",
    "**DMDHRAGE** - HH reference person's age in years <br>\n",
    "**DMDHRBR4** - HH reference person's country of birth <br>\n",
    "**DMDHREDU** - HH reference person's education level <br>\n",
    "**DMDHRMAR** - HH reference person's marital status <br>\n",
    "**DMDHSEDU** - HH reference person's spouse's education level <br>\n",
    "**WTINT2YR** - Full sample 2 year interview weight. <br>\n",
    "**WTMEC2YR** - Full sample 2 year MEC exam weight. Not using this since it is 0 for people not examined <br>\n",
    "**SDMVPSU** - Masked variance unit pseudoPSU\n",
    "variable for variance estimation <br>\n",
    "**SDMVSTRA** - Masked variance unit pseudostratum\n",
    "variable for variance\n",
    "estimation <br>\n",
    "**INDHHIN2** - Total household income (reported as a range value in dollars) <br>\n",
    "**INDFMIN2** - Total family income (reported as a range value in dollars) <br>\n",
    "**INDFMPIR** - A ratio of family income to poverty guidelines. <br>\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exploration of Data and Feature Selection\n",
    "____\n",
    "* In this section we initially explore the data to explore the features available for prediction of BMI\n",
    "* Box plots are made for some of the features to check for outliers\n",
    "* Histograms are made for the feature variables and the target variable BMI to see the shape of their distribution\n",
    "* We select feature variables that will be used for predicting the BMI using the different models\n",
    "* Features that have more than 50% missing values are outright rejected\n",
    "* Features which have redundant information are removed\n",
    "* Some of the features are removed after training a random forest regression model and looking at the feature importance plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SEQN           0\n",
       "SDDSRVYR       0\n",
       "RIDSTATR       0\n",
       "RIAGENDR       0\n",
       "RIDAGEYR       0\n",
       "RIDAGEMN    9276\n",
       "RIDRETH1       0\n",
       "RIDRETH3       0\n",
       "RIDEXMON     427\n",
       "RIDEXAGM    5911\n",
       "DMQMILIZ    3822\n",
       "DMQADFC     9444\n",
       "DMDBORN4       0\n",
       "DMDCITZN       2\n",
       "DMDYRSUS    7735\n",
       "DMDEDUC3    7324\n",
       "DMDEDUC2    4252\n",
       "DMDMARTL    4252\n",
       "RIDEXPRG    8683\n",
       "SIALANG        0\n",
       "SIAPROXY       1\n",
       "SIAINTRP       0\n",
       "FIALANG      329\n",
       "FIAPROXY     329\n",
       "FIAINTRP     329\n",
       "MIALANG     2994\n",
       "MIAPROXY    2993\n",
       "MIAINTRP    2993\n",
       "AIALANGA    4009\n",
       "DMDHHSIZ       0\n",
       "DMDFMSIZ       0\n",
       "DMDHHSZA       0\n",
       "DMDHHSZB       0\n",
       "DMDHHSZE       0\n",
       "DMDHRGND       0\n",
       "DMDHRAGE       0\n",
       "DMDHRBR4     396\n",
       "DMDHREDU     396\n",
       "DMDHRMAR      62\n",
       "DMDHSEDU    4745\n",
       "WTINT2YR       0\n",
       "WTMEC2YR       0\n",
       "SDMVPSU        0\n",
       "SDMVSTRA       0\n",
       "INDHHIN2     345\n",
       "INDFMIN2     329\n",
       "INDFMPIR    1052\n",
       "dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def featureSelection(df):\n",
    "    #dropping features with too many missing values\n",
    "    df1 = df.drop(['RIDAGEMN','RIDEXMON','RIDEXAGM','DMQMILIZ','DMQADFC','DMDCITZN','DMDYRSUS','DMDMARTL','RIDEXPRG'],axis=1)\n",
    "    df1 = df1.drop(['FIALANG','FIAPROXY','FIAINTRP','MIALANG','MIAPROXY','MIAINTRP','AIALANGA','DMDHSEDU'], axis=1)\n",
    "\n",
    "    #dropping because same for all features or redundant information\n",
    "    df1 = df1.drop(['SDDSRVYR','RIDRETH1', 'WTMEC2YR'],axis=1)#WTMEC2YR is zero for people not examined hence dropped.\n",
    "\n",
    "    #droppping because irrelevant information\n",
    "    #df1 = df1.drop(['SIAPROXY','RIDSTATR','INDFMIN2','INDFMPIR'],axis=1)\n",
    "    df1 = df1.drop(['SIAPROXY','RIDSTATR','INDFMIN2','INDFMPIR'],axis=1) \n",
    "\n",
    "    #Check if all people above the age of 20 have some entry for education level\n",
    "    assert (df1['RIDAGEYR'].loc[(df1['RIDAGEYR']>20) & (np.isfinite(df1['DMDEDUC2']))].count() == df1['RIDAGEYR'].loc[df1['RIDAGEYR']>20].count())\n",
    "\n",
    "    #Check if there are any people who have entries for both \n",
    "    #if (np.isfinite(df1['DMDEDUC3']) & np.isfinite(df1['DMDEDUC2'])).sum() == 0:\n",
    "    #    df1['DMDEDUC'] = df['DMDEDUC3'].combine_first(df['DMDEDUC2'])\n",
    "\n",
    "    # Drop DMDEDUC3, DMDEDUC2 since we have combined them\n",
    "    df1 = df1.drop(['DMDEDUC2','DMDEDUC3'],axis=1)\n",
    "    df1 = df1[np.isfinite(df['INDHHIN2'])]\n",
    "    df1 = df1[np.isfinite(df['DMDHRBR4'])] #all the entries that do not have HH country of birth do not have level of education\n",
    "    df1 = df1[np.isfinite(df['DMDHRMAR'])]\n",
    "    #df2 = df1[np.isfinite(df1['DMDEDUC'])]\n",
    "    #df2 = df2.drop(['SEQN'],axis = 1)\n",
    "    #df1 = df1[np.isfinite(df['INDFMPIR'])]\n",
    "    df1 = df1.drop(['SIALANG', 'SIAINTRP'],axis=1)\n",
    "    df1 = df1.drop(['RIDAGEYR','RIAGENDR'],axis = 1)\n",
    "    df1 = df1.drop(['DMDBORN4'],axis=1)\n",
    "    df1 = df1.drop(['WTINT2YR'],axis=1)\n",
    "    df2 = df1.drop(['SEQN'],axis = 1)\n",
    "    df2 = df2.drop(['SDMVPSU','SDMVSTRA'],axis=1)\n",
    "    return df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\tejas\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:23: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n",
      "C:\\Users\\tejas\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:24: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Index(['RIDRETH3', 'DMDHHSIZ', 'DMDFMSIZ', 'DMDHHSZA', 'DMDHHSZB', 'DMDHHSZE',\n",
       "       'DMDHRGND', 'DMDHRAGE', 'DMDHRBR4', 'DMDHREDU', 'DMDHRMAR', 'INDHHIN2'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2 = featureSelection(df)\n",
    "df2.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Box plots for select features to check for outliers\n",
    "plt.figure(figsize=(15,15))\n",
    "fnum = 1\n",
    "for i in df2.columns:\n",
    "    plt.subplot(4,4,fnum)\n",
    "    sns.boxplot(df2[i])\n",
    "    plt.xlabel(i, size = 12)\n",
    "    fnum += 1\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Histogram plots for select features\n",
    "hist = df2.hist(bins=20,figsize=(15,15),grid=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Correlation Heatmap for selected features\n",
    "plt.figure(figsize=(12, 10))\n",
    "sns.heatmap(df2.corr(), annot=True, cmap=\"RdYlGn\")\n",
    "plt.title(\"Pearson Correlation Heatmap\",size=20)\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Split Data into Training Set and Test Set\n",
    "____\n",
    "* All the feature variables are normalized using $\\frac{X - \\mu}{\\sigma}$\n",
    "* We split the entire data set into 70% training set and 30% test set\n",
    "* A validation set is not defined since the number of samples in the training set is small and we use parameter grid search for all the models which uses k-fold cross-validation to identify the best parameters \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "def splitDataset(df2):\n",
    "    y_ = list(df2['INDHHIN2'])\n",
    "    df2 = df2.drop(['INDHHIN2'],axis=1)\n",
    "    Xmean = list(df2.mean())\n",
    "    Xstd = list(df2.mean())\n",
    "    df2norm = (df2 - df2.mean()) / df2.std()\n",
    "    #df2norm = df2\n",
    "    #df2norm.describe()\n",
    "    #train, test, y__, y_test = train_test_split(df2norm, y_, test_size=0.2)\n",
    "    #train, valid, y_train, y_valid = train_test_split(train, y__, test_size=0.25)\n",
    "\n",
    "    train, test, y_train, y_test = train_test_split(df2norm, y_, test_size=0.3)\n",
    "\n",
    "    print('Size of Training Set: ', len(train))\n",
    "    #print('Size of Validation Set: ',len(valid))\n",
    "    print('Size of Test Set: ',len(test))\n",
    "    X_train = train.values.tolist()\n",
    "    #X_valid = valid.values.tolist()\n",
    "    X_test = test.values.tolist()\n",
    "    assert len(X_train) == len(y_train)\n",
    "    #assert len(X_valid) == len(y_valid)\n",
    "    assert len(X_test) == len(y_test)\n",
    "    return X_train, X_test, y_train, y_test, df2norm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Size of Training Set:  6518\n",
      "Size of Test Set:  2794\n"
     ]
    }
   ],
   "source": [
    "X_train, X_test, y_train, y_test, df2norm = splitDataset(df2)\n",
    "assert len(df2norm.columns) == len(X_train[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Use ANOVA Test to Select K-Best Features\n",
    "* Experimented with using ANOVA test for feature selection\n",
    "* Results were worse than the currently selected feature variables and hence not used"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Gives worse results. Do no use!!!\n",
    "'''\n",
    "X_all = X_train + X_test\n",
    "y_all = y_train + y_test\n",
    "X_all_new = SelectKBest(f_classif, k=4).fit_transform(X_all, y_all)\n",
    "X_train, X_test, y_train, y_test = train_test_split(X_all_new, y_all, test_size=0.3)\n",
    "'''"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Look at distribution of Classes in Test Set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "fig.set_size_inches(12, 10)\n",
    "sns.distplot(y_train, color=\"blue\", hist=True, bins=50, kde = False, label=\"Training Set\")\n",
    "sns.distplot(y_test, color=\"red\", hist=True, bins=50, kde = False, label=\"Test Set\")\n",
    "#ax.set_title('Distribution of Day of Year on which Driver Came Onboard \\n', size = 20)\n",
    "ax.set_ylabel('Count', size = 18)\n",
    "ax.set_xlabel('Day', size = 18)\n",
    "plt.legend(loc=1, prop={'size': 20})\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Training different ML models\n",
    "* In this section we inspect the performance of different multi-class classification models in predicting the class of the household income\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Random Forest Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "def RFGridSearch():\n",
    "    rfc = RandomForestClassifier(random_state=0)\n",
    "    param_grid = { 'n_estimators': [100, 200, 400, 800], 'max_depth' : [2,4,8,16,20]}\n",
    "    CV_rfc = GridSearchCV(estimator=rfc, param_grid=param_grid, cv=5)\n",
    "    CV_rfc.fit(X_train, y_train)\n",
    "    return CV_rfc.best_params_\n",
    "\n",
    "def RFClassifier(best_params):\n",
    "    rfc = RandomForestClassifier(n_estimators=best_params['n_estimators'], max_depth=best_params['max_depth'],random_state=0)\n",
    "    rfc.fit(X_train, y_train) \n",
    "    acc_train = accuracy_score(y_train, rfc.predict(X_train))\n",
    "    acc_test = accuracy_score(y_test, rfc.predict(X_test))\n",
    "    print(\"Train Accuracy : \", acc_train)\n",
    "    print(\"Test Accuracy : \", acc_test)\n",
    "    feat_imp = rfc.feature_importances_\n",
    "    return acc_train, acc_test, feat_imp, rfc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Accuracy :  0.961491254986192\n",
      "Test Accuracy :  0.7143879742304939\n",
      "Wall time: 4.9 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "#Carry out a grid search \n",
    "#rfc_best_params = RFGridSearch()\n",
    "rfc_best_params = dict({'max_depth': 20, 'n_estimators': 400}) #this was obtained from the Grid search\n",
    "rfc_train, rfc_test, rf_feat_imp, rfclf = RFClassifier(rfc_best_params)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "rf_cm = confusion_matrix(y_test, rfclf.predict(X_test))\n",
    "class_names = [1,2,3,4,5,6,7,8,9,10,12,13,14,15,77,99]\n",
    "fig, ax = plt.subplots(figsize=(12,10))\n",
    "sns.heatmap(rf_cm, annot=True, fmt='d', xticklabels=class_names, yticklabels=class_names)\n",
    "plt.ylabel('Actual')\n",
    "plt.xlabel('Predicted')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "         1.0       0.77      0.59      0.67        79\n",
      "         2.0       0.68      0.63      0.65       108\n",
      "         3.0       0.57      0.65      0.61       147\n",
      "         4.0       0.69      0.63      0.66       170\n",
      "         5.0       0.68      0.73      0.70       168\n",
      "         6.0       0.71      0.71      0.71       300\n",
      "         7.0       0.74      0.71      0.72       266\n",
      "         8.0       0.68      0.77      0.72       220\n",
      "         9.0       0.70      0.70      0.70       194\n",
      "        10.0       0.74      0.71      0.73       145\n",
      "        12.0       0.65      0.64      0.65        73\n",
      "        13.0       0.70      0.68      0.69        38\n",
      "        14.0       0.76      0.70      0.73       277\n",
      "        15.0       0.75      0.81      0.78       495\n",
      "        77.0       0.87      0.76      0.81        70\n",
      "        99.0       0.76      0.57      0.65        44\n",
      "\n",
      "   micro avg       0.71      0.71      0.71      2794\n",
      "   macro avg       0.72      0.69      0.70      2794\n",
      "weighted avg       0.72      0.71      0.71      2794\n",
      "\n"
     ]
    }
   ],
   "source": [
    "#Classification report\n",
    "print(metrics.classification_report(y_test, rfclf.predict(X_test)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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4uqquqKpzgNXD80mSJF2vjHPtxZ2Ac0durwHuu3CmJM8DXgxsDTxk5LEnLnjsTptUqSRJ0gwbp6VrsStDX+PKzFV1ZFXdAXg58Ocb89gkhyVZlWTV+eefP0ZJkiRJs2Wc0LUG2GXk9s7A2vXMfzTwuI15bFW9u6rmqmpuxYoVY5QkSZI0W8YJXScDeyTZPcnWtI7xK0dnSLLHyM1HAd8e/l4JHJxkmyS7A3sAJ137siVJkmbLBvt0VdW6JIcDxwPLgKOq6vQkRwCrqmolcHiShwG/Ai4GDhkee3qSY4EzgHXA86rqyi30XiRJkqZWqq7RxWqi5ubmatWqVVv+hbJYd7MJm7LPQpIkrV+SU6pqbpx5HZFekiSpA0OXJElSB4YuSZKkDgxdkiRJHRi6JEmSOjB0SZIkdWDokiRJ6sDQJUmS1IGhS5IkqQNDlyRJUgeGLkmSpA4MXZIkSR0YuiRJkjowdEmSJHVg6JIkSerA0CVJktSBoUuSJKkDQ5ckSVIHhi5JkqQODF2SJEkdGLokSZI6MHRJkiR1YOiSJEnqwNAlSZLUgaFLkiSpA0OXJElSB4YuSZKkDgxdkiRJHRi6JEmSOjB0SZIkdWDokiRJ6sDQJUmS1IGhS5IkqQNDlyRJUgeGLkmSpA4MXZIkSR0YuiRJkjowdEmSJHVg6JIkSerA0CVJktSBoUuSJKkDQ5ckSVIHhi5JkqQODF2SJEkdGLokSZI6MHRJkiR1YOiSJEnqwNAlSZLUgaFLkiSpA0OXJElSB4YuSZKkDgxdkiRJHRi6JEmSOjB0SZIkdWDokiRJ6sDQJUmS1IGhS5IkqQNDlyRJUgeGLkmSpA4MXZIkSR0YuiRJkjowdEmSJHVg6JIkSerA0CVJktSBoUuSJKkDQ5ckSVIHhi5JkqQODF2SJEkdGLokSZI6MHRJkiR1YOiSJEnqwNAlSZLUgaFLkiSpA0OXJElSB4YuSZKkDsYKXUkOSHJWktVJXrHI9BcnOSPJN5J8LsntRqZdmeTU4d/KzVm8JEnSrFi+oRmSLAOOBPYD1gAnJ1lZVWeMzPZ1YK6qfp7kD4E3Ak8epl1eVffYzHVLkiTNlHFauvYBVlfV2VX1S+Bo4MDRGarqP6vq58PNE4GdN2+ZkiRJs22c0LUTcO7I7TXDfUt5FvDvI7e3TbIqyYlJHrcJNUqSJM28DR5eBLLIfbXojMnTgTngwSN371pVa5PcHvh8km9W1XcWPO4w4DCAXXfddazCJUmSZsk4LV1rgF1Gbu8MrF04U5KHAX8GPLaqrpi/v6rWDv+fDZwA3HPhY6vq3VU1V1VzK1as2Kg3IEmSNAvGCV0nA3sk2T3J1sDBwNXOQkxyT+BdtMD145H7b55km+HvHYD7A6Md8CVJkq4XNnh4sarWJTkcOB5YBhxVVacnOQJYVVUrgTcB2wP/kgTg+1X1WOCuwLuS/JoW8F6/4KxHSZKk64VULdo9a2Lm5uZq1apVW/6FslhXtQmbss9CkiStX5JTqmpunHkdkV6SJKkDQ5ckSVIHhi5JkqQODF2SJEkdGLokSZI6MHRJkiR1YOiSJEnqwNAlSZLUgaFLkiSpA0OXJElSB4YuSZKkDgxdkiRJHRi6JEmSOjB0SZIkdWDokiRJ6sDQJUmS1IGhS5IkqQNDlyRJUgeGLkmSpA4MXZIkSR0YuiRJkjowdEmSJHVg6JIkSerA0CVJktSBoUuSJKkDQ5ckSVIHhi5JkqQODF2SJEkdGLokSZI6MHRJkiR1YOiSJEnqwNAlSZLUgaFLkiSpA0OXJElSB4YuSZKkDgxdkiRJHRi6JEmSOjB0SZIkdWDokiRJ6sDQJUmS1IGhS5IkqQNDlyRJUgeGLkmSpA4MXZIkSR0YuiRJkjowdEmSJHVg6JIkSerA0CVJktSBoUuSJKkDQ5ckSVIHhi5JkqQODF2SJEkdGLokSZI6MHRJkiR1YOiSJEnqwNAlSZLUgaFLkiSpA0OXJElSB4YuSZKkDgxdkiRJHRi6JEmSOjB0SZIkdWDokiRJ6sDQJUmS1IGhS5IkqQNDlyRJUgeGLkmSpA4MXZIkSR0YuiRJkjowdEmSJHVg6JIkSerA0CVJktSBoUuSJKkDQ5ckSVIHhi5JkqQOxgpdSQ5IclaS1Ulescj0Fyc5I8k3knwuye1Gph2S5NvDv0M2Z/GSJEmzYoOhK8ky4EjgEcCewFOS7Llgtq8Dc1V1d+AjwBuHx94CeDVwX2Af4NVJbr75ypckSZoN47R07QOsrqqzq+qXwNHAgaMzVNV/VtXPh5snAjsPf+8PfKaqLqqqi4HPAAdsntIlSZJmxzihayfg3JHba4b7lvIs4N838bGSJEnXScvHmCeL3FeLzpg8HZgDHrwxj01yGHAYwK677jpGSZIkSbNlnJauNcAuI7d3BtYunCnJw4A/Ax5bVVdszGOr6t1VNVdVcytWrBi3dkmSpJkxTug6Gdgjye5JtgYOBlaOzpDknsC7aIHrxyOTjgcenuTmQwf6hw/3SZIkXa9s8PBiVa1LcjgtLC0Djqqq05McAayqqpXAm4DtgX9JAvD9qnpsVV2U5P/SghvAEVV10RZ5J5IkSVMsVYt2z5qYubm5WrVq1ZZ/oSzW3WzCpuyzkCRJ65fklKqaG2deR6SXJEnqwNAlSZLUgaFLkiSpA0OXJElSB4YuSZKkDgxdkiRJHRi6JEmSOjB0SZIkdWDokiRJ6sDQJUmS1IGhS5IkqQNDlyRJUgeGLkmSpA4MXZIkSR0YuiRJkjowdEmSJHVg6JIkSerA0CVJktSBoUuSJKkDQ5ckSVIHhi5JkqQODF2SJEkdGLokSZI6MHRJkiR1YOiSJEnqwNAlSZLUgaFLkiSpA0OXJElSB4YuSZKkDgxdkiRJHRi6JEmSOjB0SZIkdWDokiRJ6sDQJUmS1IGhS5IkqQNDlyRJUgeGLkmSpA4MXZIkSR0YuiRJkjowdEmSJHVg6JIkSerA0CVJktSBoUuSJKkDQ5ckSVIHhi5JkqQODF2SJEkdGLokSZI6MHRJkiR1YOiSJEnqwNAlSZLUgaFLkiSpA0OXJElSB4YuSZKkDgxdkiRJHRi6JEmSOjB0SZIkdWDokiRJ6sDQJUmS1IGhS5IkqQNDlyRJUgeGLkmSpA4MXZIkSR0YuiRJkjowdEmSJHVg6JIkSerA0CVJktSBoUuSJKkDQ5ckSVIHhi5JkqQODF2SJEkdGLokSZI6MHRJkiR1YOiSJEnqwNAlSZLUgaFLkiSpA0OXJElSB2OFriQHJDkryeokr1hk+oOSfC3JuiQHLZh2ZZJTh38rN1fhkiRJs2T5hmZIsgw4EtgPWAOcnGRlVZ0xMtv3gUOBly7yFJdX1T02Q62SJEkza4OhC9gHWF1VZwMkORo4ELgqdFXVd4dpv94CNUqSJM28cQ4v7gScO3J7zXDfuLZNsirJiUket9gMSQ4b5ll1/vnnb8RTS5IkzYZxQlcWua824jV2rao54KnA3ya5wzWerOrdVTVXVXMrVqzYiKeWJEmaDeOErjXALiO3dwbWjvsCVbV2+P9s4ATgnhtRnyRJ0nXCOKHrZGCPJLsn2Ro4GBjrLMQkN0+yzfD3DsD9GekLJkmSdH2xwdBVVeuAw4HjgTOBY6vq9CRHJHksQJL7JFkDPBF4V5LTh4ffFViV5DTgP4HXLzjrUZIk6XohVRvTPWvLm5ubq1WrVm35F8piXdUmbMo+C0mStH5JThn6rm+QI9JLkiR1YOiSJEnqwNAlSZLUgaFLkiSpA0OXJElSB4YuSZKkDgxdkiRJHRi6JEmSOjB0SZIkdWDokiRJ6sDQJUmS1IGhS5IkqQNDlyRJUgeGLkmSpA4MXZIkSR0YuiRJkjowdEmSJHVg6JIkSerA0CVJktSBoUuSJKkDQ5ckSVIHhi5JkqQODF2SJEkdGLokSZI6MHRJkiR1YOiSJEnqwNAlSZLUgaFLkiSpA0OXJElSB4YuSZKkDgxdkiRJHRi6JEmSOjB0SZIkdWDokiRJ6sDQJUmS1IGhS5IkqQNDlyRJUgeGLkmSpA4MXZIkSR0YuiRJkjowdEmSJHVg6JIkSerA0CVJktSBoUuSJKkDQ5ckSVIHhi5JkqQODF2SJEkdGLokSZI6MHRJkiR1YOiSJEnqwNAlSZLUgaFLkiSpA0OXJElSB4YuSZKkDpZPugBtgmTSFVxT1aQrkCRpqtnSJUmS1IGhS5IkqQNDlyRJUgf26VJf9keTJF1P2dIlSZLUgaFLkiSpA0OXJElSB4YuSZKkDgxdkiRJHRi6JEmSOjB0SZIkdWDokiRJ6sDQJUmS1IGhS5IkqQNDlyRJUgeGLkmSpA4MXZIkSR0YuiRJkjowdEmSJHVg6JIkSepgrNCV5IAkZyVZneQVi0x/UJKvJVmX5KAF0w5J8u3h3yGbq3BJkqRZssHQlWQZcCTwCGBP4ClJ9lww2/eBQ4EPLXjsLYBXA/cF9gFeneTm175sSZKk2TJOS9c+wOqqOruqfgkcDRw4OkNVfbeqvgH8esFj9wc+U1UXVdXFwGeAAzZD3ZIkSTNlnNC1E3DuyO01w33jGOuxSQ5LsirJqvPPP3/Mp5YkSZod44SuLHJfjfn8Yz22qt5dVXNVNbdixYoxn1qSJGl2jBO61gC7jNzeGVg75vNfm8dKkiRdZ4wTuk4G9kiye5KtgYOBlWM+//HAw5PcfOhA//DhPkmSpOuVDYauqloHHE4LS2cCx1bV6UmOSPJYgCT3SbIGeCLwriSnD4+9CPi/tOB2MnDEcJ8kSdL1SqrG7Z7Vx9zcXK1atWrLv1AW6242YeN+Fta+eU3Zd0CSNDuSnFJVc+PM64j0kiRJHRi6JEmSOjB0SZIkdWDokiRJ6sDQJUmS1IGhS5IkqQNDlyRJUgeGLkmSpA4MXZIkSR0YuiRJkjowdEmSJHVg6JIkSerA0CVJktSBoUuSJKkDQ5ckSVIHhi5JkqQODF2SJEkdGLokSZI6MHRJkiR1YOiSJEnqwNAlSZLUgaFLkiSpA0OXJElSB4YuSZKkDgxdkiRJHRi6JEmSOjB0SZIkdWDokiRJ6mD5pAuQZkYy6QquqWrSFUiSxmRLlyRJUgeGLkmSpA4MXZIkSR0YuiRJkjowdEmSJHVg6JIkSerA0CVJktSBoUuSJKkDQ5ckSVIHhi5JkqQODF2SJEkdGLokSZI6MHRJkiR1sHzSBUjqIJl0BddUNd58s1y7JI2wpUuSJKkDQ5ckSVIHhi5JkqQODF2SJEkd2JFekrYUTwKQNMKWLkmSpA4MXZIkSR0YuiRJkjowdEmSJHVg6JIkSerA0CVJktSBoUuSJKkDQ5ckSVIHhi5JkqQODF2SJEkdGLokSZI6MHRJkiR1YOiSJEnqwNAlSZLUgaFLkiSpg+WTLkCSNIWSSVdwTVWTrkC6VmzpkiRJ6sDQJUmS1IGhS5IkqQNDlyRJUgeGLkmSpA4MXZIkSR0YuiRJkjowdEmSJHVg6JIkSerA0CVJktSBoUuSJKmDsUJXkgOSnJVkdZJXLDJ9myTHDNO/mmS34f7dklye5NTh3zs3b/mSJEmzYYMXvE6yDDgS2A9YA5ycZGVVnTEy27OAi6vqjkkOBt4APHmY9p2qusdmrluSJGmmjNPStQ+wuqrOrqpfAkcDBy6Y50Dgn4a/PwI8NJnGS9RLkiRNxjihayfg3JHba4b7Fp2nqtYBlwK3HKbtnuTrSb6Q5IHXsl5JkqSZtMHDi8BiLVY15jw/AHatqguT3Bv4eJK9quqyqz04OQw4DGDXXXcdoyRJkqTZMk5L1xpgl5HbOwNrl5onyXLgpsBFVXVFVV0IUFWnAN8B7rTwBarq3VU1V1VzK1as2Ph3IUmSNOXGCV0nA3sk2T3J1sDBwMoF86wEDhn+Pgj4fFVVkhVDR3yS3B7YAzh785QuSZI0OzZ4eLGq1iU5HDgeWAYcVVWnJzkCWFVVK4H3Au9Pshq4iBbMAB4EHJFkHXAl8NyqumhLvBFJkqRplqqF3bMma25urlatWrXlX2gaT64c97Ow9s3L2ifD2ifj+lC71FGSU6pqbpx5HZFekiSpA0OXJElSB4YuSZKkDgxdkiRJHRi6JEmSOjB0SZIkdWDokiTONHfaAAAgAElEQVRJ6sDQJUmS1IGhS5IkqQNDlyRJUgcbvPaiJEkzxUsYaUrZ0iVJktSBoUuSJKkDQ5ckSVIH9umSJGla2B/tOs2WLkmSpA4MXZIkSR0YuiRJkjowdEmSJHVg6JIkSerA0CVJktSBQ0ZIkqRrz+EuNsiWLkmSpA4MXZIkSR0YuiRJkjowdEmSJHVg6JIkSerA0CVJktSBoUuSJKkDQ5ckSVIHhi5JkqQODF2SJEkdGLokSZI6MHRJkiR1YOiSJEnqwNAlSZLUgaFLkiSpA0OXJElSB4YuSZKkDgxdkiRJHRi6JEmSOjB0SZIkdWDokiRJ6sDQJUmS1IGhS5IkqQNDlyRJUgeGLkmSpA4MXZIkSR0YuiRJkjowdEmSJHVg6JIkSerA0CVJktSBoUuSJKkDQ5ckSVIHhi5JkqQODF2SJEkdGLokSZI6MHRJkiR1YOiSJEnqwNAlSZLUgaFLkiSpA0OXJElSB4YuSZKkDgxdkiRJHRi6JEmSOjB0SZIkdWDokiRJ6sDQJUmS1IGhS5IkqQNDlyRJUgeGLkmSpA4MXZIkSR0YuiRJkjowdEmSJHVg6JIkSepgrNCV5IAkZyVZneQVi0zfJskxw/SvJtltZNqfDveflWT/zVe6JEnS7Nhg6EqyDDgSeASwJ/CUJHsumO1ZwMVVdUfgb4A3DI/dEzgY2As4AHjH8HySJEnXK+O0dO0DrK6qs6vql8DRwIEL5jkQ+Kfh748AD02S4f6jq+qKqjoHWD08nyRJ0vXKOKFrJ+DckdtrhvsWnaeq1gGXArcc87GSJEnXecvHmCeL3FdjzjPOY0lyGHDYcPOnSc4ao65psgNwwbV+liy2uLY4a7f2jbF56gZr3zjWDta+cawdetV+u3FnHCd0rQF2Gbm9M7B2iXnWJFkO3BS4aMzHUlXvBt49btHTJsmqqpqbdB2bwtonY1Zrn9W6wdonxdonw9qn0ziHF08G9kiye5KtaR3jVy6YZyVwyPD3QcDnq6qG+w8ezm7cHdgDOGnzlC5JkjQ7NtjSVVXrkhwOHA8sA46qqtOTHAGsqqqVwHuB9ydZTWvhOnh47OlJjgXOANYBz6uqK7fQe5EkSZpa4xxepKo+BXxqwX1/MfL3L4AnLvHY1wKvvRY1zoKZPTSKtU/KrNY+q3WDtU+KtU+GtU+htKOAkiRJ2pK8DJAkSVIHhi5JmkHDANSSZoihawtIsk+S7SZdh2ZPkhvM0o9pkpsmedSk69gcZmm5A5R9Q3Q9Mmvfz6UYujazYViNv2YYGDbJHSdb0cZJcuckO0y6jk2R5DlJ7jXpOjZFktsn2a2qfj1jP6aHAH+f5E7QQuOE69lko8t92jfwSV6U5GXD31Nd67hG38e0v6ckOyfZf/gc7j7pesaRZPks7yDNfz9nbcd0oZndQE6xJwGXVNXPk+wNvGTSBY0jyVySDwCvA35vuG/HJGOPtDsF7gV8Jsm3k7w6ya0mXdA4kjwOeCvw7STvS7JLkr2S3GsGNi4HAd8AngNQVb+ev6h9ktsk2WaSxW1IkvsnOSzJXyf5nfn7ZyD4Pgl4epK9qqrml/ksGFpH90hyoyTbJdl7WE+WJ7ljkkzz8k/ydOAo4EXAnsCHknw2yUMmW9kGHQw8DSDJrZLsOeF6xjYE3BckudHCHdMZ2EZejWcvbmZJ/hX4+6r6dJK/BX5SVa8apu0LHFBVr5hkjYtJ8mHaQLhfBv6UNt7aFcB2wD9W1RcnWN5GSbI/8HzgAcB/AUdU1VcnW9XSkhwP/E1V/UeSTwKXA3cAvke7YPwxEy1wCcMe/tuqat8kJwMfq6rXzf9oJvkH4F1VtWrCpS5qaJU+Gfgq7UoZNwP+cvh/b9pO6elVtXpiRS4iyT2AI4GPAg+uqgOH+28whN5HAJ+tql9Nss6lJPkUcCfa0YBvAD8G/g/wBdoyv7KqDppchUsbwuGptJ2NtcDPgFsDj6dtb15YVde46so0SPIJ4L1VtTLJa4E1VfX3w7SbVdUlk61waUneSbtU4KXAt4C/oK1Dv6iq906yto1lS9dmNLSsPBK46XCYZQ54x8gszwL+dxK1rc+wIdkL+LuqOgm4B20D+C7gTODQJLeYYIkbpaqOr6pHA7egha5Fx5CbBkluS9toHz/c9VvAy4H7Ah8Gfn+KWxsPAT49/P0sYL8kDxoC167AfaY1cA2eCHypqg4D/o42gPMngfcDLwX+GJjGH6KnAR+pqrcAWw87d/OtjLvQdvqmMnAN/pMWXA6hhZTnAD+k7fC9EHjuBGvbkIOAE6vqdNq68auqOhf4IG0H9aGTLG4pw3Zmt2Ewc4D9gf8YmeXtSR7fv7KxvRX4c9rRjHcDbwLeRvttmqkuJYauzWRo4rwYeBltw3E2rbVix5HZ7gpMY6vFHYBPVdUvk+wEfLGq/rmqTquqNwJ3B7aabIlLS7vM1N5Jbjx6f1X9GngzsHeSB0+mug3an3at0gcleSatZeXsqvpVVR0L7A6cP9EKl3Z/4FiAqvoGreVl/gdzvuVimv0JcEOAqroAOA/4AfCsqnow8NDh/mnzYOATw9/Poq3fDx9uP532OUyz/0fbGXob8Mgk9wNuUFV/U1Xfm9JlPu95wLnQDkHPH9qtqguBfwb2m2h1S9sfuEmS+e3MxVV1DlzV4rsnv9mBmjpVdSbwbVrL+j8C9wPOoa1HKzNDJ655eHELSbIbbQN4MO1w0c+BH1TVwRMsa6MlOQB4UVXtP+lalpLk0bS9/xNpl5z6Dm1ZXz5MPw34nar62eSqXNywwTuU1kK6C+1Qy18DXwOeAuxbVU+fWIFLSLuw/W2qas3IfTehXbniw8ATgD+pqq9NqMQNSvJ7wAto14T9HO2Q4qOq6tsTLWw90q5h+8Kq+uMkWw87Sn9EW0+elOTTwCunvIURgKGF4mm0w3L/UVWvnj9EOuHSFpVkK+ANwK60BotVwCeHHQ6SvA/4SlW9a2JFLmGR7cyPaP13VwFPBR5SVU+bWIEbkGT5cEnCp9N2Uu9Ka2V80YRL22iGrs0kyc7A7wMnVdXxC6bdl3Y8+p+mrW9UkpvTWif+g9Y697OqWjcy/aPAp6dxQzJveA/7AfcEbgdcCJwG3JzWirdtVR06sQKXkHbG3+Or6g3D7TvSQvoDaX1F7g384XAZrqmS5DHAr2mHn9cOlwJjaCn9Cq1fzu4TLHFsw6GX59CW/U2B44C3VtU3J1rYIpLctKouXXDfNsB7gLsAPx9a6abOsL4/tapeM3LfbwOvon1XXwJ8ddqvzzusL79Na+m9E62f0cm07ejctO3czfJ2ZqEkK4BX0ALkvlX1zWkO6osxdG0mSd5M6xj67qr61nAm1GNoe9BfmNY+FsMX8E20/ggX0ur9MrCG9qO6C3DOaBCbVsOe6FbAQ4DfAa6kdUb/j9EWmWkxdGb9U+CJVfXRBdMeBNy9qv5uIsWtx3Ao/Q3AzrQ95jOHf+dW1XeTHAjcsKo+PMEyN8nQSf1wYPm0BfXhDMWVtG4MnwOOq6ofD9NuAnyT1lH6iMlVubRhfX858H+q6hOjP5Zpw1/crKpeOdEi1yPJO4CzgGOr6gfDfXemHep6PO2kqWdMsMRFzep2Bq5qzDgQWEb7bf3FsP15QFV9abLVbRpD12aS5BTgMfNnrgxnod2SFmS+Dbx2yvsqkORU2sq9lnaY7ivAZ6rq4okWth5Dh+3n0/o+7Uw7tPjuqvrCfJP0RAtcjyQn0Q7FzQHPr6qLkmxXVZcPG/MfLmzVmAYjZyfuAjycVv+NaevNN2gni3xtWpf9EFDuANyK9iO6Argt7SxGgJtX1bcmVN56Jbk3rY/l79D6i34X+Cytde62wKXTehbaBtb3x9NapKcyqA87dE+lHQrdg9av6zhgZbXhgZbTdjQum2CZi5rV7QxAkhOBk2jr+69o4bZoZ9Y/inZSw3cmV+HGsyP9ZpDkAbTDcmvTLANOrqrfHs6iuytwo8lWOZbLaRv059LOJnoJ7cdpmr2X9gU8hha+zgBeleSF0/qjD5DkYcAFVfU3tI3I2wHm+6EB/wDsNpnqNuilSX6nqs6tqvdW1R8Cr6S1tDwGeNg0L3vgr2gB649ph9WfROtU/y3aiRfT2lJ0J1pfv/cDrwFeS+tM/Hja+3jAFAeuDa3vz6QF9qkz7GT8CvhgVT2b1pn+M8C+wHFJXgPcbUoD18xuZ5LsB1xUVS+oqjnaIfS3Av9O67/7WKb4BK+lLJ90AdcRFwA/TbJ3Vf3P0Pz5TrhqLKPtqup7E61wEWnjWS2vquOSPAH4drWmz3Noh4/eMNECN2Ck/j8fufvkJCcA/5TkKzW943M9G/jI8PfzgX9J8vyqevvQmnGDqjptcuUtLsmOtNrfPtzejtbhfyfa+zma1nI0zf4O2AH4PG0MuiuTHE0bLuI9E61sCUM/or+ntVScQTvT8rwkZwDb0g5xnTvBEjdkQ+v7LasNwzB16jeHg7ZPcnvaUBHbA/8D3IY2ZtRWwNcnU+F6zeR2ZnAwcHaSW1TVRbQuMHeinaRzKcBw/0yxpWszGA5FnAC8OO1SLuuq6kfD5OcyvafO3x54XJI3AW9kSvc01+MQ2pgtQNsjHfZK509H33dSha1P2hhu2wD/AjAcvn0V8OjhMMbjaXtz0+iZwPFD34rb0wYTfQFtQNE3AzeuKR0ccl5V/S9t/fh94Jhhx2iOFsAurHb6/7Q5BDizqs5IcsMkT0hyJm0svT2r6uNVdcqEa1zUmOv7cZOrcP2SPDDJd2mt6m+hjb24I+1Q43G0k6Sm7kSjWd7ODA0Xa2k7R68azlp8BvD6qjqnqi6axcAF9um61kb6t9ya9qPzcNpe6KdoG/IfAi+vqh9OsMxrSHI32gCc36QNjHq/YdJPaGf+faWm+9T55bTO21+ndS7+7OgyTnIk8KNp7VQ8L78ZRXwZbZTxZbQBAA+c0s7/fw18r6reNYT1WwL/XFUnDMv8u1X1pslWOb4kzwOeDCyrqvtPup6lJPki8Kqhr+IfAI8Gvkg7ZHQg8HtV9f1J1jiOWVvfAYbl/Re0lsQ30/ronjnlh9CvZhaXO1zVkX6+3+idaUNcnEbru3tSzWCAMXRtZsPhlicAd6S1fp1SVT+daFGLSBtT5t+q6qPDXs+taAPk7TH8f9k0n0kEV43zc3faHudtaZ2KP0Xr3/IF2unpU/dDNJyp9SXgtKr6+YJppwFbV9VdJ1LcBgyHJD5E27G4C60/1FeGQ3SfBI6sqmnde15OG7T1q7TBIS9NG27kEFon6Q/QhnWZqk7Fw/fzL2n9Ff+Ltl35S1rLXCX5PPDqaT2ba5bX93lJdqCtO4+hdcs5k3YVidNpYwJOXQCb5eWeNh7dCmD1fIvWcNLUAbRR/79RVa+dYImbzNB1LSTZlpa+/5fWWX4r2ngtW9HGnbmkhvGLpslQ94lVdY9Fpm1HC4xXDIdhplKSR9LO2lpGW95701rr5g8VXV5V95lchYsb+kSdQDtN+xdpgxY+g1b/+2hnu956Gg8VJdm+qn46nLV4T+CnVfX54VDAvYH3VdXek61yaWlDWfwr7aSLk2mtpKuq6idpQ7y8EHj2tIUuuKpl+v20/qP/W1V/NNy/I+0MurlJ1reUWV7f4apx524CfL+G8bfSLhT9eOBBtC46T6iqn0yuymua5eU+HDU6hrZtv4x2lZcVtDH0/hP4BbDDtHdjWIqh61pIchitc+uptJaVOwH3oe0F/ZoWXu5YVb+cWJGLSBuJ+33Aq2lj/UztqOGLGTaEX6mqXYfbd6s2SN4NaV/Oe9L2PqeuE32SP6dt7J4/9Il6Lm1g18/SDvM+Y0r7FJF2UfT5PfxTq+qK4f4b0/pH3WyaD+emXSXiDcA+tMMTN6CdsXsC7fu7rKq+MqHylpTkYNqludYmufH8D3zaQJEvow1V8LyJFrmEWV7fAdIu2n4Bbfyz1Un2po3/d9ZwuG6faternSqzvNyTvIJW+4uSvJW2Pf8x7XJoP62qP5logdeSHemvnfNoZ0B9HTim2vAQ/0ZrEn0IcN9pC1yDJ9MGKbwFrSPxfyd5yXD8fBY8maFzaJLHAvMX/P15tbNEvzSNgWtwQ9pZTwB/SOso+qJhQ3IOLbxMqw/TOsy/Bfhkkucm2QvYGjiKKT/btaq+W1VPpg0PcQzt7Ki/ol3F4D20/lFTJe2aih8C3pl2YesnJrnLMPlntMNb09yHbmbX96G1aK6q/rSqVg93v4PWGf11Se4yjYFrMLPLnXZR8c8Mf6+g/bYeROuLtleSqRuAdmMYuq6FqjqOdsHZS4AnpA26eE/ajxI1jFo8TYa+CbesqjdV1Yuqag/amYsPBD6f5CtJpn1srqfzmy/lo4EPzk9I8hzaRnFafZR2luvnadedO4rW7wLaj/9UnjYPUFUrq+rFtD5z29A64r6NdgHjfedbvqbVcIiFqvoI7fp5R9OGHDkc+F3aIcepMRy2/Qrth/4S2o/orYAXDic0PAz4SFV9d2JFbtjMru+0M3X/e/7GsIOxPW17+Wvg2cMZgtNoJpf7cBTjSuBuSZ5NO3L0MYCqmg+R50+ovM3Ccbo20bBBXFZV30/yHuCltC/oL6uNozOt9qYNZEmSZVV1ZVV9HPh4ku1pgWaaz2bZiTYy8W8Nf+/H1UPWI5nesZa2r6pT0gYsnO8T9eU0c8Bu09oJfYHfpfV9Oms4ZPc0pnzw3yRvA34+7FCcROsScDDwyiTPGg7dZaJFLjCcmfWToYXrlbTrzR1Da02/M+0khl/TxhebOteB9X0ZQzgZwtVa4CnDen8X4ME1hdf8m/HlfjFtcOK70vqJnktr3f0e8FPgVlX1HxOs71qzT9dmNCTzQ4C3VNXHkjacxKTrGpXkv4DDq+rrSW5TVT8czuqqmvILzQIM/bZ+l/alvCOtH93HaU3mPwXeNMWdimeyT1TaRYmfxG8GWXxtVe07uYo2ztDx/zTa2X+raB2j57sF3Jx29Yipa6XLggv5Dj+Yd6f1yzkPuButb9HlSzzFRM3q+j4vyX1oA+k+parOXjDtM8DfDkc7psqsL/d5aWcrztEaCm5CG+Lo61X1gokWdi0ZujbB0IH1sbQV4XNV9Y3h/uXD/S8GDqkpuyZU2sV831ZVDxrCy0dpV5+fujMsxzFrX8qh/9m+tDp/Tlv+X6KN5XYF8Ksp/fF/IPAIWmvW/WlnFD0bOG8W1p20M3LvB9yD1o/xl7TW0q/Rrr147pS2WBxOG8JlFW007t+lXYPufNrFi8+ZYHkbNKvr+6gkL6H1If04rRvDLrSzFh9XVftMsralzOpyH35XH0fbln+6qr453L+c1h3gnrSz7s+bXJXXnqFrEyT5Z1rn4VvS+li8nrbnHFrfqK2r6oNLP8NkDIcpLq2qV6eN8PuIqnraMG1X4IiqOnSSNa7PdeVLmeRVtMOi36Jd2/L7wEerauoOE6WNEXXlcKbWnWl9LO5G61B/OW1stH+sKRxmYTFp1y+8F62FdAdamPlwVX1+ooUtkOSWtHB1BW09eT1wNm0H44e09XxqL0Q/apbW98WkDTVyOLA7bYy3NbTx3Ka5G8nMLfdFflffCHyO9ru6L/A/89v8WWafro2UNsbV3lV1r+H2nWgd519KO/vpXKb3sj+/Tbv21o60Zua3jkx7Cm38k2n2Zn7zpfy9JKNfyvvSvpRTHbgGs9Qn6lG0C1wfB3yiqj4wdEi/G23ohT1oe9NTaYmg/r9DUN+F1nL3rQmWuKiqunAk5D6e1qfrk8CxNb3XylvKLK3vo0cybka75NUngE8M2/6axlaiJczMcl/P7+qLaf0Wf0gb2mXmQ5ctXRspbcycN9NOaz2NdhbX2bQfoRvUFI6ADlcdYjmMtqe8HW1v/89oA7t+izbo3Auq6tSJFbkew5fyvxf5Ut6WkS9lVb15clUubpb7RKUNI7IPbfT5x9DW9S/RrmZwXpIb1oLRrqfJGHvP3xw5K2pqJHka8LH5/lpDf66DaC3pO9BGoD96giUuaZbXd7jGOnNr2pAcn6NtZx5NW2embkiaWV7us/q7uikMXRspbeTqx9GCyzpaiLmgqp4y0cLGNOzh70O7dM5etM7nRRtTbOpGcJ83y1/KWe8TBVeNEv1F2lhcv0U71HIF7aSMH63vsZMyq0E97VJL762qewzf11vPt+AmuRHwEODsqprW0/5ndn0fY51ZC3yhqt4yuSoXN+PLfaZ/VzeGoWsjDIdVrqx2nbn5pv/7086A+i6tD8Z7prF/S5K70vb0vzTfaTjJLWiHHB9E64A+lXvOMLtfymGdWTfrfaKSPBV4ZFU9fQhguwJ3q6qjJlzakmY1qCd5A+0SYq9L8kfA71bVE6fxbOiFZr0P4AyvMzO73Bf5Xd2HdsLI1P+ubgpD10ZI8jha363jgI9X1ZnJVdeduw+tf8vLq+pXEyzzGpI8mTaUxX2Bi4D/C3xwWMlvBlBVl0ywxPWa8bA7us58oqrOWKRP1NStM3DVmVv/VlX/m+SjtI32J0emL6spHmZkhoP692hnP5+Q5CO05X5ckq2mcT0ZNcvrO8z0OjOzy31Wf1c3laFrIyzRv+XLtJV87bT2b0ny78D/q6rPDRuVZwA/oXUWPZt2CvGBk6xxfWb5SzmrfaKGs+c+RDuM+GPg9sCe0xzOR81qUE9yU+CdtKFQfkxb/rO03GdyfYfZXWdg5pf7TP6ubipD1yaYpf4taaO2n0zrNHx2Va1LcjHt0i2n0Vbws6f5mP914Us5S+vMqOGH6ADa2a370MaM+jDtQulTF3LnzXJQh6uW+/7AU7n6cv9kVa2bZG3jmMX1fdbXGZjN5T5vlmvfGA4ZsWkeShvF+qgF/VumccW4HW2D/QzgR0PH3NVV9drJljW+qloDrBmW9SHAP9C+lI9IcgVtDJ2pDl3M1joz30fkHrRDLGdU1VPSrtv5LODt/7+9M4+VqyzD+O/BIlUorQug4FIXUJFgAWkqVnAhuMUFRYtxgYgrohFFNCEGFMUFjSghuESCJqJYQhRMLMjSlHRRwdKWiFVMXUBEBKTFlCr08Y/vGz2O986dS+fOmXd8f0nTO8uZ85w3zzf3uee85/uAx1HOyIwq11MaoJ8JXCCpGdTPr0F95H55dtX95oB17xDK75WQnukiYt07RNbeN3mmq0+i9rfUv9SeVf8dDOwPzAa+Rbm75TrbW9pT2D/RmrkDe+ZQyrqEx1LWnrsNuIOif2N9z6w84zJYotc9qt+7ieQZiF33yNofKhm6+mAM+lvmAI+0fYfKxH+vpPw1txdlLpdbWhXYg6iDMrJnJC0DlgEXUO7eWkS5FX0RcKrtq1qUNy0iBfXIdY/s926CeSZs3SNr3xEydE2DaP0tkvYHTgb2oTSD/hP4dv03BzjQ9rXtKezNOAzKgJ55AuVyyiETvPYFYLNHfLHciEF9HOoO8fzeIaJnmkStO8TW/lDI0NUHXX0WW2zf0uizOIlytmjk+iwkraSY92bg95Q7cV5FWS7njBalTYuIgzKwZz4KHGr7mO5fNPWOrvOBl45w3UMG9TGoe0i/Q1zPQPi6h9W+I2TomoKofRaSXg6cbPuorucXAEuB947y5QqIOyijegZA0hcpi+Mup9wluhH4s+1762WX19k+pkWJfREtqEeue2S/NwnombB1j6x9R8nQNQVR+ywkLaV8WVzYeG4nlxmLjwP2s31aawKnIPKgjOoZ+HfQXUS5k+jplPncfkVpLD4X+JTtZe0p7E3goB627pH9DqE9E7bukbXvKBm6ehC1z0JlWog1lLXlVgBX2F7XeP18ynpcn2pJ4pREHZRRPQOgssiygFXAJmB34AjKHG9PBp5oe2FrAqcgalCPXPfIfofQnglb98jaB0GGrh5E7rOQ9DhKQDmcMqnffcC1wI8oq9C/wXUR3VEj8qAM7plbKeu0XQz8ndILuMb2n1Um2X2M7fVtauxF4KAetu6R/Q6hPRO27pG1D4Kd2hYw4uwJzJL0QeCVkp6hskwHlFmK7x5FY9TLh7Nt/8D2h4APAz+hnEK/grJw60gGrsqbKX/xI+lhXa99A3hhvSQwioT0TOUY4NeUOd12ARYDp9U7u54N3NSitp7UoL6H7XNsb7Z9p+3LbZ8IXENZQHdUCVt3Avs9uGfC1p3Y2neYPNPVg4h9FpJ2ofzVdgDlVPlSYKnt+yTtRDmeLbY3tCizJ8GbisN5pon+szbnHyhB/fHAC4D7RvXsIsT/6zlw3cP6PbJngtc9rPZBkKFrEiL3WQBI2pMyPcSrKAHmRuAi2z9uVVgfRB2UkT0jaY7rygSS9qMshj4LOI/SYDzP9u0tSuxJ1KAeue6R/Q6hPRO27pG1D4oMXZMQvM9iD9t3Nh7vBxwNLAGusX1Ka+KmIPKgjOoZSUcD7wBMWWvOlEu884H32L6oPXX9ETGoR697VL93iOgZiF33yNoHRYauSZC0CPg4cD+wAdiN0m/xu/r4KtvbWxM4AZKeQvkS3xu4C/iy7T82Xp8D4BFeazHyoIzoGQBJZwNvAG4H7qEs+rsOeCKwyfY9LcqbkqhBfQzqHtLvENczEL7uYbUPigxdPYjWZyHpHEqT4jLK2opbgUuBV1C+yH9r+8vtKZya6IMymmcAJO1OObvyHEoj676U5u0fA6ttb2tP3dREDerR6w4x/Q5xPdMhat0htvZBkKFrAqL2WUhaZfuw+vMjKHN1GVhNuVN1ue3vtiixLyIOyoiekSTbrjdY4DJx7lzKTRhHAAdRAu/rPGLzFDWJFtTHoe4R/d4kmmc6RK57ZO2DZFbbAkaNTp+FpIn6LP5Q+yy2tqdwYiQ9H1hUb8O90PbfJD2S8gV+/6h+eTfpDErbqyT9lTIoj6QMyquAea0KnISonqm/+A8G3gK8TNId1AXRba+UNJ/yRTjS3rG9RtKnKUF9G2Uuuk5Q39X2lW3q6yZ63aP6vdYeKFoAAAbxSURBVEk0z0DsukfWPmjyTFcXkfssJO0BvA34CMXUt9o+tF1V/RG5qTiqZ1TW4fwcReuFwEuB4ym/fN5p+4etieuTiH89R697VL93iOgZiF33yNoHTYauLsahzwJA0lOBkylG/zXwVtu/b1fV5EQelFE9I+lc4A53LQcl6XjKVCNvsv2PNrT1Q9SgPgZ1D+l3iOsZCF/3sNoHTYauyjj0WUyEyozui4ENtu9uW89kRByU0T0jaSXwgqp7F8rdXA8AO1Mud51ne3mLEnsSNahHrXt0v0NMz0Sue2TtM0WGrgbNPgvKoqedPosHG30WN7ancPyIPiijeqb2AF4HfAC42I153errNwAnjKL2DkGDeui6R/V7h4iegdh1j6x9JsjQVYneZxGZqIMyumcaPYCnUmbk/prtCyU9nrJ6wYtaFTgJYxDUo9Y9rN8jeyZ43cNqnykydFWi91lEJfKgHCfP1IbiD1JWLtgTOL37uEaJqEG9m0h1j+73qJ6JXPfI2meKDF2VqH0W0Yk8KMfRM7UH8FBg4yj2t0DsoD4ZQeoe1u+RPRO87mG1zxQ7tS1gFKh9Fs8DTlRZt3Cb7fttP2B7K/BU4G/tqhxbDgbOApC0i6TZkmZRZoreDhzWprjJGFfP2H7Q9ppR/cVfOQG4zvaptn9p+0u2n0O5XPc2SQ9vWd+0GfW6j4HfQ3omct0ja59JMnQBtlcCe1Gu6d8kaXU900Lts9g8iqedoxN5UKZnWiVkUI/MGPg9pGci1z2y9pkkQ1fF9p22v2h7L+A4YKGk24FbgavbVTeeRB+U6ZnhEzmoRyeq36N7JmrdIbb2mSJ7unoQoc9inIjUVDwZ6ZmZJ+rdf+NIFL+Pm2ei1H0iImsfBBm6kpHj/31QJv0zDkE9GS7pmaRNMnQlSRKeDOrJdEnPJG2QoStJkiRJkmQIZCN9kiRJkiTJEMjQlSRJkiRJMgQydCVJkiRJkgyBDF1JkkyJpAcl3SjpJkmXS5rXxzb3TfH6PEknNh7vLemSAWidL+mmHf2cae5zgaRXDHOfSZLEI0NXkiT9sNX2AtsHAHcD7xvAZ84D/h26bP/J9jED+NyhUmc2XwBk6EqSpCcZupIkmS6rgX06DyR9RNLPJa2X9InuN0vaTdLVkn4haYOk19SXPgs8rZ5BO7t5hkrSTyU9u/EZyyUdImlXSRfU/a1tfNaESDpe0g/q2blNkk6S9KG67RpJj258/jmSVtWzeQvr84+u26+v7z+wPn+GpK9LupKycO8ngSX1WJZIWlg/a239/xkNPZdKWibpN5I+39D6slqjdZKurs9N63iTJBltZrUtIEmSONS5jV4CfLM+PgrYF1gICLhM0uG2VzQ2ux842vZmSY8F1ki6DPgYcIDtBfWz5je2+R7wRuD0Omv43rZvkHQWcI3tt9dLnD+TdJXtv/eQfQBwEDAbuAX4qO2DJH2JMkv5OfV9u9o+TNLhwAV1u08Aa22/VtKLKQFrQX3/IcBi21vr8lXPtX1SPZbdgcNtPyDpSMq6f6+v2y2oerYBGyWdW2v0jbrNpk4YBE57CMebJMmIkqErSZJ+eISkG4H5wA3AT+rzR9V/a+vj3SghrBm6BJxVw8x2ylmyvabY3/frPk6nhK+ljf29WtIp9fFs4EnAzT0+61rbW4Atku4FLq/PbwAObLzvuwC2V0javYacxdSwZPsaSY+RNLe+/7K6dt9EzAW+JWlfwMDOjdeutn0vgKRfAk8GHgWssL2p7uvuHTjeJElGlAxdSZL0w1bbC2rg+BGlp+srlED1Gdtf67Htm4E9gENs/1PS7yjhYVJs3ybprno5bwnw7vqSgNfb3jgN7dsaP29vPN7Of38Hds8U7bq//5FX/+91tulMStg7up7BWz6JngerBk2wf3hox5skyYiSPV1JkvRNPUPzAeAUSTsDVwBvl7QbgKR9JO3Ztdlc4C81cL2IcmYHYAswp8fuvkdZoHiu7Q31uSuA90tS3d9BgziuypL6mYuBe+uxrqCERiS9EPir7c0TbNt9LHOB2+rPx/ex79XAEZKeUvfVubw4k8ebJMmQydCVJMm0sL0WWAcca/tK4CJgtaQNwCX8b5D6DvBcSddTAsyv6ufcBaysjetnT7CrS4BjKZcaO5xJuVS3vjbdnzm4I+MeSauArwIn1OfOqNrXUxr/j5tk22uB/TuN9MDngc9IWgk8bKod274TeBdwqaR1wMX1pZk83iRJhkyuvZgkyf89kpYDp9i+vm0tSZKML3mmK0mSJEmSZAjkma4kSZIkSZIhkGe6kiRJkiRJhkCGriRJkiRJkiGQoStJkiRJkmQIZOhKkiRJkiQZAhm6kiRJkiRJhkCGriRJkiRJkiHwL9tlPH7MneZZAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "features=list(df2norm.columns)\n",
    "importances = rf_feat_imp\n",
    "indices = np.argsort(-importances)\n",
    "featname_sort = [features[i] for i in indices]\n",
    "\n",
    "plt.figure(figsize=(10,10))\n",
    "plt.title('Feature Importances based on Random Forest Classifier')\n",
    "plt.bar(range(len(indices)), importances[indices], color='r', align='center')\n",
    "plt.xticks(range(len(indices)), featname_sort, rotation =70)\n",
    "plt.xlabel('Relative Importance')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Gradient Boosting Classification"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "def GradBoostGridSearch():\n",
    "    gb = ensemble.GradientBoostingClassifier(random_state=0)\n",
    "    param_grid = { 'n_estimators': [100, 200, 400, 800], 'max_depth' : [2,4,8,16,20]}\n",
    "    CV_gb = GridSearchCV(estimator=gb, param_grid=param_grid, cv=5)\n",
    "    CV_gb.fit(X_train, y_train)\n",
    "    return CV_gb.best_params_\n",
    "\n",
    "def GBClassifier(best_params):\n",
    "    original_params = {'n_estimators': 400, 'max_depth': 24, 'random_state': 1}\n",
    "    params = dict(original_params)\n",
    "    gbc = ensemble.GradientBoostingClassifier(n_estimators=best_params['n_estimators'], max_depth=best_params['max_depth'],random_state=0)\n",
    "    gbc.fit(X_train, y_train)\n",
    "    acc_train = accuracy_score(y_train, gbc.predict(X_train))\n",
    "    acc_test = accuracy_score(y_test, gbc.predict(X_test))\n",
    "    print(\"Train Accuracy : \", acc_train)\n",
    "    #print(\"Validation Accuracy : \", accuracy_score(y_valid, clf.predict(X_valid)))\n",
    "    print(\"Test Accuracy : \", acc_test)\n",
    "    return acc_train, acc_test, gbc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Accuracy :  0.961491254986192\n",
      "Test Accuracy :  0.7072297780959198\n",
      "Wall time: 2min 42s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "#gbc_best_params = GradBoostGridSearch()\n",
    "gbc_best_params = dict({'max_depth': 20, 'n_estimators': 400}) #this was obtained from the Grid search\n",
    "gbc_train, gbc_test, gbc = GBClassifier(rfc_best_params)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "gbc_cm = confusion_matrix(y_test, gbc.predict(X_test))\n",
    "class_names = [1,2,3,4,5,6,7,8,9,10,12,13,14,15,77,99]\n",
    "fig, ax = plt.subplots(figsize=(12,10))\n",
    "sns.heatmap(gbc_cm, annot=True, fmt='d', xticklabels=class_names, yticklabels=class_names)\n",
    "plt.ylabel('Actual')\n",
    "plt.xlabel('Predicted')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "         1.0       0.73      0.62      0.67        79\n",
      "         2.0       0.63      0.57      0.60       108\n",
      "         3.0       0.59      0.63      0.61       147\n",
      "         4.0       0.72      0.62      0.67       170\n",
      "         5.0       0.64      0.70      0.66       168\n",
      "         6.0       0.72      0.72      0.72       300\n",
      "         7.0       0.73      0.71      0.72       266\n",
      "         8.0       0.68      0.78      0.73       220\n",
      "         9.0       0.71      0.66      0.69       194\n",
      "        10.0       0.69      0.72      0.70       145\n",
      "        12.0       0.66      0.67      0.67        73\n",
      "        13.0       0.76      0.66      0.70        38\n",
      "        14.0       0.74      0.68      0.71       277\n",
      "        15.0       0.76      0.81      0.78       495\n",
      "        77.0       0.72      0.77      0.74        70\n",
      "        99.0       0.69      0.57      0.62        44\n",
      "\n",
      "   micro avg       0.71      0.71      0.71      2794\n",
      "   macro avg       0.70      0.68      0.69      2794\n",
      "weighted avg       0.71      0.71      0.71      2794\n",
      "\n"
     ]
    }
   ],
   "source": [
    "#Classification report\n",
    "print(metrics.classification_report(y_test, gbc.predict(X_test)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "features=list(df2.columns)\n",
    "importances = gbc.feature_importances_\n",
    "indices = np.argsort(-importances)\n",
    "featname_sort = [features[i] for i in indices]\n",
    "\n",
    "plt.figure(figsize=(10,10))\n",
    "plt.title('Feature Importances')\n",
    "plt.bar(range(len(indices)), importances[indices], color='r', align='center')\n",
    "plt.xticks(range(len(indices)), featname_sort, rotation =70)\n",
    "plt.xlabel('Relative Importance')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Support Vector Machine"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "def SVMGridSearch():\n",
    "    svm = SVC()\n",
    "    param_grid = [{'kernel': ['rbf'], 'gamma': [1e-3, 1e-4],'C': [1, 10, 100, 1000]},\n",
    "                    {'kernel': ['linear'], 'C': [1, 10, 100, 1000]}]\n",
    "    CV_svm = GridSearchCV(estimator=svm, param_grid=param_grid, cv=5)\n",
    "    CV_svm.fit(X_train, y_train)\n",
    "    return CV_svm.best_params_, CV_svm.best_score_ \n",
    "\n",
    "def SVMClassifier(best_params):\n",
    "    svm = SVC(kernel = best_params['kernel'], C = best_params['C']).fit(X_train, y_train) \n",
    "    acc_train = accuracy_score(y_train, svm.predict(X_train))\n",
    "    acc_test = accuracy_score(y_test, svm.predict(X_test))\n",
    "    print(\"Train Accuracy : \", acc_train)\n",
    "    #print(\"Validation Accuracy : \", accuracy_score(y_valid, clf.predict(X_valid)))\n",
    "    print(\"Test Accuracy : \", acc_test)\n",
    "    return acc_train, acc_test, svm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\tejas\\Anaconda3\\lib\\site-packages\\sklearn\\svm\\base.py:196: FutureWarning: The default value of gamma will change from 'auto' to 'scale' in version 0.22 to account better for unscaled features. Set gamma explicitly to 'auto' or 'scale' to avoid this warning.\n",
      "  \"avoid this warning.\", FutureWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Accuracy :  0.8488800245474072\n",
      "Test Accuracy :  0.6338582677165354\n",
      "Wall time: 17 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "#svm_best_params, svm_best_score = SVMGridSearch()\n",
    "svc_best_params = dict({'kernel': 'rbf', 'C': 1000}) #this was obtained from the Grid search\n",
    "svm_train, svm_test, svmclf = SVMClassifier(svc_best_params)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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f/v83kDcGPU9AQCAnTpygf9+X/JrhTJMmj6RixQrkZOfQv99ADhxw8IItByV5k5kx4yviE+aSm5PD6tXr+OQTsxcs5ebm0vepF4mbO5kAj4dx46eSkvKT0QwA1apVIXbqGCD/oqkpU2cyf8Fi4zk+nTiCm1o2pXLlimzbksSrr71LzLgpRjO4ZZ24YVm4IYPWx2/csizcksNnXHAepUmWW895KFXqYseDNa1s/uvuP7L28C9OR+Bo9gmnIwCQ44LxwgI9AU5HAOBETrbTEQjwuGP0tFwXfE0kIv8bcn5NP+vpfKYcX/6Z0TZOqab3Ovo36+cqRUREREy6wD4gu6NbQkRERETOS+rZFBERETFJPZsiIiIiIr6hnk0RERERg2zb+YtdTVLPpoiIiIj4jRqbIiIiIia56BeELMsqZVlWomVZqy3LWmdZ1qsnp9exLGulZVkbLcuaallWiZPTS558vOnk87X/6s9VY1NERETkwnUCaG3b9vVAA6CtZVlNgEHAe7Zt1wP2Az1Pvr4nsN+27brAeydf96fU2BQRERExyc4ze/uzKPmOnHwYdPJmA62BaSenjwe6nrzf5eRjTj5/s2VZfzpovBqbIiIiIhcwy7ICLMtKBnYDC4DNwIGTPzUOkAbUPHm/JrAdCn6K/CBQ6c/mr8amiIiIyHnMsqxelmUlFbr1Kvy8bdu5tm03AGoBEcBVfzCbUz+x+Ue9mH/685sa+khERETEJMODutu2PRoY/Tded8CyrMVAE6C8ZVmBJ3svawE7Tr4sDbgISLMsKxAoB+z7s/m6trGZ9xfnGJiQuG+j0xEA+GfVJk5H4OPdK5yO4BrWH36oM8/z56fIGJF3gf0Kxp8J8Ljji6JcF6wT57dMKexPu5wM0nbhTpZlVQGyTzY0g4FbyL/o51vgTmAK8AAw8+R/mXXy8fKTzy+ybVs9myIiIiKu4YIOtUJqAOMtywog//TKWNu251iWlQJMsSzrdWAVMPbk68cCEy3L2kR+j+Y9f1VAjU0RERGRC5Rt2z8CDf9g+hbyz988c/px4K6i1FBjU0RERMQkF5zuYpI7TjISERERkfOSejZFRERETHLXOZt+p55NEREREfEb9WyKiIiImKRzNkVEREREfEM9myIiIiImqWdTRERERMQ31LMpIiIiYpKuRhcRERER8Y3zsrFZsmRJ4pfNIck7n+RVC3lp4NOO5Ojd+yG83q/xJs3niSceNlb3pofa8dzX7/Dc/He46eF2ADzwQV8GxL3NgLi3eWnZ+wyIe9tYHnBuWRSWmprA90kLSFw5j4T4ucbqfjhqEFu3eUn0ziuYVqFCOWbNnkjyj4uYNXsi5cuXNZbHLftHrVphLJj/OT/+uJjk5EU82aenIzmi20Sxbu0SNqQs49kBTziS4RSPx8PKFV8x/csYR+q7YVm4YbtwQwY35RgzejA70laTvGqhI/XBPcvCZ/LyzN4cZtm27XSGP1SiZK1iBQsNDSEr6yiBgYEs/nY6/Z9+mcTEH4o0j6CAcz/LoH79yxk//n1atuzCr79mM3PmePr2fZHNm7cVeV7/rNrkb7+2xuW1eOD9vgzu8gK52Tk8Nv7ffP7iWDK37Sx4TdcXenDs8FG+Hv7l357vx7tXFClzYb5cFjl5ueecIzU1gWbNOrB37/5zngdAkKdo20Xz5hEcycpizJjBRIS3BeA/rz/H/v0HGDJ4FP2ffozy5cvx0sBBRZrvr7nZRXp9Yb7YPwCKc/yoXr0qNapXZVXyWkqXDmXlynnceefDrF+/seg5zjGDx+Nh/bqltG1/L2lpGaxYHkeP+3qfU4YAT/E/u/f9v0e44cbrKFumNLfd/tA5zSP3HN9YfLksrHNKkM+X28X/cgZf5ijuu3yLyMYcOZJFTMwwGjS8+Zzn45btIvvX9OJE8Yljs9412vgK7vyMo3+z33o2LcuKsCwr/OT9+pZl9bcsq72/6p0pK+soAEFBgQQFBRbrTfFcXHFFXRK9qzh27Di5ubksXbaSzp2j/V63Wt2abFu1kezjv5KXm8emleu5Njr8tNc06NCUH2Yl+D3LKU4tC7eIj09k/74Dp03r0PFWJk36AoBJk76gY6c2RjM5vX8A7Ny5m1XJawE4ciSLDRs2EhZW3WiGiPCGbN68ja1bfyE7O5vY2Jl07uTMtlmzZnXatWtNTMxnjtR3y7Jww3bhhgxuyrF02Ur27T/w1y/0I7csCzk3fmlsWpb1MjAcGGlZ1lvAB0Bp4DnLsl7wR80zeTwevIlfk562moULl+L1rjJRtkBKSirNm0dQsWJ5goNLER3dipq1avi9bkbqdi6LuIqQ8qUJKlWC+q0aUKFGpYLnL4u4ksN7DpzW0+lvTi2L37Ft5s6ZxPKEufTs+Q/z9QupWrUyu3ZmArBrZyZVqlT6i//hW07vH2e65JJaNLj+GhITzeYIq1md7Wk7Ch6npWc49gb27juv8O/n3yTPoa+83LQsTnFqu3BbBjflcIPzYlnYeWZvDvPX1eh3Ag2AksBOoJZt24csy3oHWAm88Uf/ybKsXkAvgICA8ngCQs85QF5eHuER0ZQrV5bPYz/m6vpXsC4l9ZznV1SpqZsZMmQUs+d8ypEjWaxZs57cnHP/Cvjv2rV5BwtHzaL3py9wIus4O9b/TF7ubxvaDZ2bG+3VBOeWxZmiWt1ORsYuqlSpRNzcyaSmbmbZspXGc7iB0/tHYaGhIcROHcPTz7zM4cNHjNa2rN9/s+REL2/7djeTmbmXVavW0LLl3z9txpfcsixOcXK7cFMGN+VwAy2L/03++ho9x7btXNu2jwKbbds+BGDb9jHgrE1s27ZH27bdyLbtRsVpaBZ28OAhlixZTpvoKJ/MrygmjI+lebOORLe5m/37D7Bp81YjdVfEfsu7Hf/N+3e/ytEDWWRuzQDAE+Dh+uhwfpiz3EiOwpxaFoVlZOwCIDNzLzNnzSO8UQPjGU7ZvXsP1apXAaBa9SpkZu51JIeT+wdAYGAgsVPH8Nln05kx4yvj9dPTMrioVljB41o1axRsJyY1bdaIDh1uJTU1gYkTRhAV1ZyYmGFGM7hlWYDz24VbMrgphxucV8viArtAyF+NzV8tywo5ef/GUxMtyyrHnzQ2faVy5YqUK5d/dW+pUqVo3TqS1NRN/i77O6e+Gq1VK4zOndvyeewsI3VLV8r/2yuEVeK6tuF8f7In8/LIa9m1ZQcHd+4zkqMwp5bFKSEhwZQuHVpw/5abW7JunTM9eQBxc7+he/c7AOje/Q7mzllgrLZb9g/Iv8p1w4ZNDB022pH63qRk6tatQ+3aFxEUFES3bl2YPWe+8RwDBw7isroRXHFFM+67/wkWL47noYf6Gs3glmUBzm8XbsngphxuoGXxv8tfX6O3tG37BIBtn3ayQBDwgJ9qFqhRvRpjx75HQEAAHo/FtGlziIszP2TDpMkjqVixAjnZOfTvN5ADBw4ZqfvwyP6EVihNbk4u0wbGcOxQFgA3dGpm/Cv0U5xaFqdUq1aF2KljAAgMDGDK1JnMX7DYSO2YccNo0bIJlSpVIHVjAm+8PpQhg0cyYeIH3P9AN9K27+C+HuaGmXHL/tG8WTg9etzJmjUpJHnzGzUvDnybefMWGcuQm5tL36deJG7uZAI8HsaNn0pKyk/G6ruJW5aFG7YLN2RwU45PJ47gppZNqVy5Itu2JPHqa+8SM26K0QxuWRY+44LzKE06b4c+8oXiDH3kS0UZ+shfijP0kS8VZ+gjXynq0Ef+Upyhj3zFLccPN6TwxdBHvnCuQx/5kuPjyshp3LB/gHu2C1cMffTlm2aHPrr9eUf/Zne8a4qIiIhcKFzwodAkd3wUFxEREZHzkno2RURERExSz6aIiIiIiG+oZ1NERETEJJdcXGmKejZFRERExG/UsykiIiJiks7ZFBERERHxDfVsioiIiJiknk0REREREd9Qz6aIiIiISRfYb6OrZ1NERERE/Ma1PZsBngCnI7jGx7tXOB2BJ6o2dToCAB+6YFnYuGN8NDfsI3ku+XRuu2DMulyXnINlOR0AXLGHeCw3LAnwWM736eTm5TodAXDHdiHOcG1jU0REROS85JIPp6Y4/5FLRERERM5b6tkUERERMckFp/6YpJ5NEREREfEb9WyKiIiImKRzNkVEREREfEM9myIiIiImqWdTRERERMQ31LMpIiIiYpJLfhDDFPVsioiIiIjfqGdTRERExCA7T+NsioiIiIj4xHnZ2KxX71JWrIgruO3atZY+fR42nqNPn554k+bj9X7NuHHDKVmypPEMvXs/hNf7Nd6k+TzxhH+XwV3/fZSXkkbR/+v/FkwLLhfKPyc+z7PfDuGfE58nuGwoAA27NKffV4Po99Ugen/xKjWuutgvmT4cNYit27wkeucVTKtQoRyzZk8k+cdFzJo9kfLly/ql9tk4vV24Zf8ASE1N4PukBSSunEdC/Fzj9UuWLEn8sjkkeeeTvGohLw182niGU6LbRLFu7RI2pCzj2QFPGK9fq1YYC+Z/zo8/LiY5eRFP9ulpPAPAmNGD2ZG2muRVCx2pD+7aLsqVK8vkyaNYvXoRyckLadz4BqP1tV34SV6e2ZvDzsvG5saNW2jSpD1NmrSnWbOOHD16jFmzvjaaoUZYNR7v/SAtIjsRHh6NJ8DDXXd1Mpqhfv3Leeihe2jZsgtNGrejXbvWXHZZbb/VS5r2HWMfePu0aa0e78KmhLX8t1V/NiWsJap3ZwD2bd/NqLtf4712/2Lh+19yx1uP+CXTpIlf0LXrg6dN6//04yxeHE+D61qzeHE8/Z9+3C+1/4gbtgs37B+FtYnuRkTjtjRr3sF47RMnTtAmuhuNwtvQKDyaNm2iiIgw+2YO4PF4GD7sDTp26sG117fi7ru7ctVV9YxmyMnJ4dlnX+W666KIjOzEY48/aDwDwIQJsXTo2N143cLcsl0ADB78CgsWLOb661sTHt6WDRs2Ga2v7UJ8wVhj07KsCaZqFdaqVXO2bv2FX35JN147MDCA4OBSBAQEEBISTEbGLqP1r7iiLoneVRw7dpzc3FyWLltJ587Rfqu3NXEDRw8eOW3a1bfeyPfTlgDw/bQlXHNrIwB+/mEjxw5lAfDLD5soV72iXzLFxyeyf9+B06Z16HgrkyZ9AcCkSV/QsVMbv9Q+G6e3i8Kc3D/cIivrKABBQYEEBQViO/CbxRHhDdm8eRtbt/5CdnY2sbEz6dzJf/vqH9m5czerktcCcORIFhs2bCQsrLrRDABLl61k3/4Df/1CP3PDdlGmTGkiIyOIiZkCQHZ2NgcPHjKaQduFn9h5Zm8O80tj07KsWWfcZgO3n3rsj5pnc9ddnYmNNVoSgIwduxg2dAwbUhPYvCWRQwcPs3DhUqMZUlJSad48gooVyxMcXIro6FbUrFXDaIbSVcpxODP/AHE48wChlX//lXX43VGkLk42lqlq1crs2pkJwK6dmVSpUslYbTdsF4U5tX8UsG3mzpnE8oS59Oz5D0cieDwevIlfk562moULl+L1rjKeIaxmdban7Sh4nJae4cgb+imXXFKLBtdfQ2Ki+WXhFm7YLurUuZjMzH2MGTOYFSviGDlyECEhwcZznKLtQs6Vv3o2awGHgCHA4JO3w4Xu/yHLsnpZlpVkWVZSTs6Rs73sbwsKCqJDh1v48kvz54KVL1+Wjh1v5er6Lah7WWNCQkO4556uRjOkpm5myJBRzJ7zKTNmjmfNmvXk5uQazfBXLmtan/C7WxH39mdORzHCDdvFKU7uH6dEtbqdJk3b07nL/Tz26ANERjY2niEvL4/wiGjqXBpOo0YNuLr+FcYzWJb1u2lO9KQBhIaGEDt1DE8/8zKHDxf/OPy/yg3bRWBgIA0bXsPo0RNp0qQ9WVnHGDCgt/EcoO1Cisdfjc1GwPfAC8BB27YXA8ds2/7Otu3vzvafbNsebdt2I9u2GwUGli52iOjoKJKT17J7955iz6uoWrWKZNvP29mzZx85OTnMmjmPxk1uNJ5jwvhYmjfrSHSbu9m//wCbNm81Wv9I5kHKVCkPQJkq5cna89tXQNWvvJg73+7F+Efe5egBcwev3bv3UK16FQCqVa9CZuZeY7Xdsl2As/vHKadOIcjM3Mv+VylHAAAgAElEQVTMWfMIb9TAsSwHDx5iyZLltImOMl47PS2Di2qFFTyuVbOGI6dXBAYGEjt1DJ99Np0ZM74yXt+NHN0u0jNIT8/A683/5mf69DgaNLjGeA5tF36QZ5u9OcwvjU3btvNs234PeAh4wbKsD3BgTM9u3Zz7inB72g7CwxsSHFwKgKio5qQaPrEbKPiKuFatMDp3bsvnhpdHyjffc+OdLQG48c6WrFvwPQDlwypx/6h+TOk3gj1bdxrNFDf3G7p3vwOA7t3vYO6cBcZqu2W7AGf3D4CQkGBKlw4tuH/LzS1Zty7VaIbKlStSrlz+qR2lSpWidetIUlPNrw9vUjJ169ahdu2LCAoKolu3LsyeM994jjGjB7NhwyaGDhttvLabuGW72LUrk7S0DOrVuxTIP8d6/fqNxnNou5Di8msD0LbtNOAuy7I6kP+1ujHBwaVo3boFffo8b7JsgSRvMjNmfEV8wlxyc3JYvXodn3xi/qviSZNHUrFiBXKyc+jfbyAHDvhvNfxj+JNc2uQqQiuU4fnlH7DgvWl8O3IW3Uf0JaJbFPt37OXT3kMBuOX/biekQmluez1/yJ28nDyGd37B55lixg2jRcsmVKpUgdSNCbzx+lCGDB7JhIkfcP8D3UjbvoP7epgbZsYt24XT+wdAtWpViJ06Bsi/aGrK1JnMX7DYaIYa1asxdux7BAQE4PFYTJs2h7g480Or5Obm0vepF4mbO5kAj4dx46eSkvKT0QzNm4XTo8edrFmTQpI3v6H74sC3mTdvkdEcn04cwU0tm1K5ckW2bUni1dfeJWbcFKMZ3LJdAPTr9xLjxg2nRIkgtm79hV69njFaX9uFn7hgOCKTLKfOC/orwcGXOB7M8wfnUV2onqja1OkIAHy4e4XTEbBxfNMEIM8F+26eC65yBOfObyzMDesDwA1HLTcsCbccvz2W8yMM5ua541x9N2wXADm/pju+cRx9v7fRxRHy5IeO/s36uUoRERERky6wnk3nP3KJiIiIyHlLPZsiIiIiJrnktBtT1LMpIiIiIn6jnk0RERERk3TOpoiIiIiIb6hnU0RERMQkF/yqj0nq2RQRERERv1HPpoiIiIhJLvlBDFPUsykiIiIifqOeTRERERGTdM6miIiIiIhvuLZn03bD6PqWo79b7yof7Ul0OgIA/6rSzOkIvLt3hdMRAMh1wThteS457yjPDccLl7BccNxyw/HbY7mjL6VEgPNvs0fzcp2OIBc45/cCERERkQuI7YLOApPc8dFPRERERM5L6tkUERERMUkXCImIiIiI+IZ6NkVERERMcsnFlaaoZ1NERERE/EY9myIiIiIm6ZxNERERERHfUM+miIiIiEkaZ1NERERExDfUsykiIiJiks7ZFBERERHxjfO2sVmuXFkmTx7F6tWLSE5eSOPGNxjP0KdPT7xJ8/F6v2bcuOGULFnygsnwwYdvs2lrIssTvyqY9p/Xn8P7w3ziV8zl089GUq5cGZ/X7fTOI/T//kMenf92wbSr2kfw2IJBvLh1IjWurVMwvU7kNfxzzus8+vXb/HPO69RuVt/necC5ZXGmD0cNYus2L4neeQXTKlQox6zZE0n+cRGzZk+kfPmyfs9xJo/Hw8oVXzH9yxjjtQHGjB7MjrTVJK9a6Ej9U6LbRLFu7RI2pCzj2QFPGK9fsmRJ4pfNIck7n+RVC3lp4NPGM5zi9LIA595DRowcxOZtiazw/na86HpbO1Z653Hg8CYaNrzWSI7C3LA+3LKf+oydZ/bmsPO2sTl48CssWLCY669vTXh4WzZs2GS0fo2wajze+0FaRHYiPDwaT4CHu+7qdMFkmDzpC+7o+tBp075dtIwm4e1o3qQDmzdupf/Tj/u87urPlzL5gf+eNi3zpzQ+f3QoP6/ccNr0Y/sPM+Xhd/ko+jlm9h9Fl/d8nwecWxZnmjTxC7p2ffC0af2ffpzFi+NpcF1rFi+ON5LjTE/26cmGVLP7Z2ETJsTSoWN3x+pDfoN7+LA36NipB9de34q77+7KVVfVM5rhxIkTtInuRqPwNjQKj6ZNmygiIsx/SHfDsgDn3kMmfTqN2884XqSk/ET3fzxO/LJEIxkKc8v6cMN+KufOSGPTsqxIy7L6W5bVxkS9MmVKExkZQUzMFACys7M5ePCQidKnCQwMIDi4FAEBAYSEBJORseuCyZAQ72X//gOnTVu0aBm5ubkAeL3JhNWs7vO6vyRu4NiBI6dN27NpB3u3ZPzutTvX/cyR3fkZM39KI7BkEAElfH8as1PL4kzx8Yns33d6jg4db2XSpC8AmDTpCzp2MrKLFqhZszrt2rUmJuYzo3ULW7psJfvOWD+mRYQ3ZPPmbWzd+gvZ2dnExs6kc6do4zmyso4CEBQUSFBQILZt/rwyNywLJ99DEuK9v9tPf0rdzKaNW43UP5Mb1ge4Yz/1qTzb7M1hfmlsWpaVWOj+I8AHQBngZcuynvNHzcLq1LmYzMx9jBkzmBUr4hg5chAhIcH+LnuajB27GDZ0DBtSE9i8JZFDBw+zcOHSCy7D2fS4704WzP/O6RgFrmofwc51P5P7a47x2k4ui6pVK7NrZyYAu3ZmUqVKJaP1333nFf79/JvkXWDDgJwprGZ1tqftKHiclp5BWJj/P4CcyePx4E38mvS01SxcuBSvd5XxDG5YFm54D3ELN6wP+d/nr57NoEL3ewG32rb9KtAGOGs/uGVZvSzLSrIsKyk398jZXvaXAgMDadjwGkaPnkiTJu3JyjrGgAG9z3l+56J8+bJ07HgrV9dvQd3LGhMSGsI993S94DL8kWcG9CYnN5fYqTOdjgJAlXo1af3cPcT9e6zx2m5bFia1b3czmZl7WbVqjdNRHGdZ1u+mOdGrmJeXR3hENHUuDadRowZcXf8K4xncsCzc8B7iFm5YH/K/z1+NTY9lWRUsy6oEWLZtZwLYtp0FnLXryLbt0bZtN7Jtu1FAQOlzLp6enkF6egZebzIA06fH0aDBNec8v3PRqlUk237ezp49+8jJyWHWzHk0bnLjBZfhTPf+43ai27bikYf7OZrjlDLVK3LX6H7M7D+K/b/sNlrbDcti9+49VKteBYBq1auQmbnXWO2mzRrRocOtpKYmMHHCCKKimhMTM8xYfTdJT8vgolphBY9r1azhyGk3pxw8eIglS5bTJjrKeG03LAs3vIe4hRvWx/nIzsszenOavxqb5YDvgSSgomVZ1QEsyyoN/P5jko/t2pVJWloG9epdCkCrVs1Zv36jv8ueZnvaDsLDGxIcXAqAqKjmpBq+SMkNGQq7+ZaWPNW/F/fc/SjHjh13LMcpJcuGcG/MMyz671TSkn4yWtstyyJu7jd0734HAN2738HcOQuM1R44cBCX1Y3giiuacd/9T7B4cTwPPdTXWH038SYlU7duHWrXvoigoCC6devC7DnzjWaoXLki5crlj0ZQqlQpWreOJNWBC7fcsCzc8B7iFm5YH/K/zy+Dutu2XfssT+UBt/mj5pn69XuJceOGU6JEEFu3/kKvXs+YKFsgyZvMjBlfEZ8wl9ycHFavXscnn5i9CMLJDGNjhhLZojGVKlUgJXUZb70xjP5PP06JkiWYMWt8Qb5+fQf6tO5tw5/gkqZXEVKhDH1XvM93703j2IEs2r76ACEVy3BPzAB2pfzM5PsHEf5AGyrUrkaLJ2+jxZP5m+Wk+97m6F7fXgjg1LI4U8y4YbRo2YRKlSqQujGBN14fypDBI5kw8QPuf6Abadt3cF8PZ4Y1cdKnE0dwU8umVK5ckW1bknj1tXeJGTfFaIbc3Fz6PvUicXMnE+DxMG78VFJSzH4AqlG9GmPHvkdAQAAej8W0aXOIizM/zIwblgU49x7yybhhBceL9T/F8+brw9i//wDvDH6ZypUr8vmXY1nzYwq3dXnQSB63rA837Kc+5YKLdkyy3HruRalSFzseLMBz3o4MVWSBngCnIwDwTKUmTkfg3b0rnI4AQK4LvhrJzjN/QdUfccOycAvPH5xjZ1qeC95X3HLMKhHg/A/1Hc0+4XQEV8n5Nd3xneTIv243upOUHvSlo3+zWlMiIiIiJrlo6CPLsi6yLOtby7LWW5a1zrKsvmc8/4xlWbZlWZVPPrYsyxpuWdYmy7J+tCzrLwfkdf4jl4iIiIg4JQd42rbtHyzLKgN8b1nWAtu2UyzLugi4Ffil0OvbAfVO3hoDI0/+e1bq2RQRERExyUU/V2nbdoZt2z+cvH8YWA/UPPn0e8CzQOHu0S7ABDvfCqC8ZVk1/qyGGpsiIiIi57HC45ifvPU6y+tqAw2BlZZldQbSbdtefcbLagLbCz1O47fG6R/S1+giIiIiJhm+Gt227dHA6D97zcnhKb8AniL/q/UXyP8xnt+99I9K/Nm81bMpIiIicgGzLCuI/IbmJNu2vwQuA+oAqy3L2gbUAn44OW56GnBRof9eC9jBn1DPpoiIiIhBtovG2bTyf5N0LLDetu0hALZtrwGqFnrNNqCRbdt7LMuaBfSxLGsK+RcGHbRtO+PPaqixKSIiInLhag7cB6yxLCv55LTnbduOO8vr44D2wCbgKPDQXxVQY1NERETEJBf1bNq2vYy/+Cnxwr8Maef/GlCRfm5O52yKiIiIiN+oZ1NERETEpAvsJ3bVsykiIiIifuPank37z4dsMiLXJZ88ypUMcToCx3OznY4AwLt7VzgdgaWV6zsdAYDW+1KdjoCd4/x+6hbWn5/yZExOXq7TEVyyJNyhRIDzb7NHs084HUEucM7vBSIiIiIXEhddIGSCvkYXEREREb9Rz6aIiIiISerZFBERERHxDfVsioiIiBiUPy76hUM9myIiIiLiN+rZFBERETFJ52yKiIiIiPiGejZFRERETFLPpoiIiIiIb6hnU0RERMQgWz2bIiIiIiK+cd42NlNTE/g+aQGJK+eRED/XkQzlypVl8uRRrF69iOTkhTRufIORukM/eIN1m+L5bvmsgmn1r7mCuQumsDhhFhOnjKR0mVC/Zvjgw7fZtDWR5YlfFUx7YWA/4lfMZWnCbKbPHEf16lX9msHJHLX++3/UT5rI5V9/UDDt4g+epV7cMOrFDePKZR9TL25YwXOlrqzNZV++w+XzR1Bv3vtYJYN8nmnYiDdZv3k5S1fMKZj2ccxQvl02k2+XzeSHNYv4dtlMn9f9M3369MSbNB+v92vGjRtOyZIljdYHdxwrwLnjRWFjRg9mR9pqklctNF77lFq1wlgw/3N+/HExycmLeLJPT0dyOLU+3LifumG7AIhuE8W6tUvYkLKMZwc84WiWYsuzzd4cZrl1YNGSpS4qVrDU1ASaNevA3r37z3keFlZxIvDxx0OIj08kJmYKQUFBhIQEc/DgoSLPp1zJkCK9vkmzRmRlHeWDUW9zU9POAMz79nNeffG/LI/3cm+P27n4kloMemP4357n8dzsImVo1jycrCNHGTXmXZpGtAOgTJnSHD58BIBHH3+AK6+sS7++A4s036LyR46llev/5WtCI64mL+s4Fw3px0/RfX73fI0XHib38FF2D58CAR7qzRnK9v5DOL5+GwHly5B7KAvy8v60Rut9qX87M0DTk9vFiI/+S4smHX/3/GtvPMehQ4d5d9CIvz3PYzm/FilDYTXCqvHNN9O48YZbOH78BBMmfsD8rxfz6afTijyvnLzcc87hi2MFuOd4UZxl0SKyMUeOZBETM4wGDW8+5/kUZ0lUr16VGtWrsip5LaVLh7Jy5TzuvPNh1q/fWKT5BHgCipHCd+ujdIlSRXq9P/bTA8ezipThTL7aLorD4/Gwft1S2ra/l7S0DFYsj6PHfb2LvF0A5PyaXryd1QcOPnCz0cZXufELHf2b/dKzaVlWY8uyyp68H2xZ1quWZc22LGuQZVnl/FHTbcqUKU1kZAQxMVMAyM7OPqcD1blYkZDEgf0HT5tWt24dlsd7Afju2wQ6dG7j1wwJ8V727z9w2rRTDTyA0JBgI7+g4FSOrMR15Bw8fNbny3WI5MCs7wAo06Ihxzds4/j6bQDkHjj8lw3Nc7E8IYn9Z2wXhXW5rR1fTptz1uf9ITAwgODgUgQEBBASEkxGxi6j9d3CyeNFYUuXrWTfGfuLaTt37mZV8loAjhzJYsOGjYSFVTeawcn14cb91A3bRUR4QzZv3sbWrb+QnZ1NbOxMOneKdjRTseQZvjnMX1+jfwIcPXl/GFAOGHRyWoyfap7Otpk7ZxLLE+bSs+c/jJQsrE6di8nM3MeYMYNZsSKOkSMHERISbDzHKRvWb6Rt+9YAdOralpo1aziSY+DLT7NuwzLuursLb7w+1JEMTucIjbianD0H+HVbBgAlL60JNtSZ8Cr15gylyqO3G80D+b0pmbv3sGXzz8ZqZuzYxbChY9iQmsDmLYkcOniYhQuXGqtfwOFjBbjveOEWl1xSiwbXX0Ni4iqjdd26PpzYT90irGZ1tqftKHiclp5h/EOInDt/NTY9tm3nnLzfyLbtp2zbXmbb9qvApWf7T5Zl9bIsK8myrKTc3CNne9nfEtXqdpo0bU/nLvfz2KMPEBnZuFjzK6rAwEAaNryG0aMn0qRJe7KyjjFgQG+jGQp76onneeiR7sz/7gtKlw7l1+yifS3uK/95dTBXXxnJ51Nn0uvR+xzJ4HSO8p1bcmDWkt8mBAQQGl6fX/oOZtOd/6JsdFNKN7vOaKbb7+zIl9PMnq9YvnxZOna8lavrt6DuZY0JCQ3hnnu6Gs0Azh8rwH3HCzcIDQ0hduoYnn7m5dO+jTDBrevDif3ULSzr998Cu/U0QPk9fzU211qW9dDJ+6sty2oEYFnW5cBZWzm2bY+2bbuRbduNAgJKFyvAqa/jMjP3MnPWPMIbNSjW/IoqPT2D9PQMvN5kAKZPj6NBg2uMZihs08at3H1bT9rcdAfTp83l562/OJYF4PPYWXTu0tbRDI7kCPBQNropB+f81oOXvXMPR1auJXf/IezjJzj8bRLB11xmLlJAAB06t2H6l2bfxFq1imTbz9vZs2cfOTk5zJo5j8ZNbjSaAZw/VoD7jhdOCwwMJHbqGD77bDozZnz11//Bx9y4PpzaT90iPS2Di2qFFTyuVbPG//RpN3aebfTmNH81Nv8J3GRZ1magPrDcsqwtwJiTz/lVSEgwpUuHFty/5eaWrFtXtIspimvXrkzS0jKoVy+/I7dVq+bndCKzr1SuXBHI/3TYb8BjjP9kivEMl15Wu+B+uw63sPGnzcYzOJ2jdGQDTmxJJ3vn3oJpR777geAra2OVKgkBHkIbX8PxjduNZbqpVTM2/bSFjB1mD9zb03YQHt6Q4OD8CyiiopqTumGT0QxuOFaA+44XThszejAbNmxi6LDRjtR34/pwaj91C29SMnXr1qF27YsICgqiW7cuzJ4z3+lY8jf5ZVB327YPAg9allWG/K/NA4E027aN7CXVqlUhduoYIP8ChClTZzJ/wWITpU/Tr99LjBs3nBIlgti69Rd69XrGSN1RYwfTLDKcipUqsCplMe+89T6hoSE89Eh3AOJmz+ezT7/0a4axMUOJbNGYSpUqkJK6jLfeGEab6Cjq1ruUvLw8tv+S7vcr0Z3McfHwZwhtci2BFcpy5fIYdr03mf2xCyjfqWXBhUGn5B7KIvPjGdSbNQRsm0PfJnH42ySfZxr9yRCaR0ZQsVIFfly/hEFvDmfSxGncdkcH4xccACR5k5kx4yviE+aSm5PD6tXr+OSTz4xmcMuxApw7XhT26cQR3NSyKZUrV2TbliRefe1dYsaZ/WDavFk4PXrcyZo1KSR58xsTLw58m3nzFhnN4dT6cNt+Cu7YLnJzc+n71IvEzZ1MgMfDuPFTSUn5yWgGn3JBb6NJ5+3QR75Q3KFMfKWoQx/5Q1GHPjqf/Z2hj0wo6tBH/lCcoY98qTjD/fiKW44X7lgWzivu0Ee+UtShj/yhuEMfnW/cMPTRgXtbGW3jlP/sW0f/Zv1cpYiIiIhJLhiOyKTz9heERERERMR56tkUERERMcgNV4ibpJ5NEREREfEb9WyKiIiImKRzNkVEREREfEM9myIiIiIG6ZxNEREREREfUc+miIiIiEk6Z1NERERExDfUsykiIiJikK2eTRERERER33Btz2ZenvPNfsty9HfrCxw8cdTpCNi448q5QE+A0xGIPrDZ6QgALKte1+kI3JiW4nQEAEICSzodgazs405HAMANRy03HC1KBLj27c04N2wT4I7tQpyhvVFERETEJOf704zS1+giIiIi4jfq2RQRERExSBcIiYiIiIj4iHo2RURERExSz6aIiIiIiG+oZ1NERETEIJ2zKSIiIiLiI+rZFBERETFIPZsiIiIiIj6ink0RERERg9SzKSIiIiLiI+dlY7NWrTAWzP+cH39cTHLyIp7s09N4hpIlSxK/bA5J3vkkr1rISwOfNp4BoFy5skyePIrVqxeRnLyQxo1vcCRHamoC3yctIHHlPBLi5zqSoXfvh/B6v8abNJ8nnnjYWN2wmtWZNjuGJStns3j5LP75WA8ABr72DEsT57AwfjqffDqcsuXK+Lx29Tefou7yydSZ82HBtJJXXcolsUOoPfN9LvliGKWuuxyA0jc3ofasEQXTg2+s7/M8Z+rTpyfepPl4vV8zbtxwSpYs6feaAO9/+BY/bV1JQmLc7zP9X0/2H9lExUoVjGQBdxwv3HDcPCW6TRTr1i5hQ8oynh3whJGaI0YOYvO2RFZ4vyqY1vW2dqz0zuPA4U00bHitkRzDRrzJ+s3LWbpiTsG0j2OG8u2ymXy7bCY/rFnEt8tmGskC2i78xrbM3hxm2bbtdIY/FFSi5jkHq169KjWqV2VV8lpKlw5l5cp53Hnnw6xfv7FI87Gs4q2g0NAQsrKOEhgYyOJvp9P/6ZdJTPyhyPPxWOf+meDjj4cQH59ITMwUgoKCCAkJ5uDBQ0Wej03xtpPU1ASaNevA3r37izWfQE/AOf2/+vUvZ/z492nZsgu//prNzJnj6dv3RTZv3lbkeZUtEVKk11etVplq1auwZvV6QkuH8PXiaTzc/UlqhFVj2ZKV5Obm8sIr/QF445Uhf3u+31at/ZevCW50DXlHjxH236fZ2rE3ABd98jr7xs0ga0kSoTc1otI/7+SX+57DCimFffQ4ACWvqE3YsH+zte2jfzr/G9NS/nbeM9UIq8Y330zjxhtu4fjxE0yY+AHzv17Mp59OK/K8SniKdkZQs+bhHDlylFFj3qFZRPuC6TVr1mDYiDe5/PJLiWrRlX1F2F6zso8XKcOZfHW8ONdjuq+Om0CxjhYej4f165bStv29pKVlsGJ5HD3u613kHCFBRfvg0qx5OFlZR/lozLs0CW8HwOVXXEZeXh7Dhr/Bi8+/xapVa4o0T4ASAUXbNps2a0RW1lFGfPRfWjTp+LvnX3vjOQ4dOsy7g0b87XkePJ5VpAyFnW/bBUDOr+mOt752RUUZbXxVW7zY0b/ZLz2blmX9n2VZF/lj3n/Hzp27WZW8FoAjR7LYsGEjYWHVjefIyjoKQFBQIEFBgef8JnCuypQpTWRkBDExUwDIzs4+p4bm+eCKK+qS6F3FsWPHyc3NZemylXTuHG2k9u5de1izej0AWUeOsvGnLVSvUZXvvk0gNzcXgB+SVvtlGz2WtJa8g4dPm2bbNp7S+Q1mT+lQsnfvy59+9LfGkhVcCgxsr4GBAQQHlyIgIICQkGAyMnb5vSZAQryX/fsP/G76G4Ne4JUXBxnfV8H544VbjpsR4Q3ZvHkbW7f+QnZ2NrGxM+ncyf/7akK8l/37Tt8mfkrdzKaNW/1eu7DlCUns33/wrM93ua0dX06bc9bnfe1C3y78xc4ze3Oav75G/w+w0rKspZZl9bYsq4qf6vylSy6pRYPrryExcZXx2h6PB2/i16SnrWbhwqV4vWYz1KlzMZmZ+xgzZjArVsQxcuQgQkKCjWYoYNvMnTOJ5Qlz6dnzH8bLp6Sk0rx5BBUrlic4uBTR0a2oWauG8Ry1Lg7j2muv4ofvfzxt+j09bmfRN0uNZNj95miqPvswl303nqrP9SRz8LiC50rf2pQ68z7iotGvkvHvoX7NkbFjF8OGjmFDagKbtyRy6OBhFi40swz+SLv2N5OxYydr125wpL7Tx4vCnDxuhtWszva0HQWP09IzHGncuFHTZo3I3L2HLZt/dqS+tgs5V/5qbG4BapHf6LwRSLEsa55lWQ9YlnXWE9Msy+plWVaSZVlJeXnn3u1/SmhoCLFTx/D0My9z+PCRYs+vqPLy8giPiKbOpeE0atSAq+tfYbR+YGAgDRtew+jRE2nSpD1ZWccYMKC30QynRLW6nSZN29O5y/089ugDREY2Nlo/NXUzQ4aMYvacT5kxczxr1qwnNyfXaIaQ0BDGThjGS8+/xZHDv23ffZ9+lNycXL6InW0kR/l727P7zTFsvukBdr85hhpv9i147siC5Wxt+yhpvf9Dlafu82+O8mXp2PFWrq7fgrqXNSYkNIR77unq15pnExxciv4DHuet1/3bwP4zTh8vTnH6uPlHpy+59XQv026/syNfTnPmnHdtF1Ic/mps2rZt59m2Pd+27Z5AGPAh0Jb8hujZ/tNo27Yb2bbdyOMJLVaAwMBAYqeO4bPPpjNjxld//R/86ODBQyxZspw20VFG66anZ5CenoHXmwzA9OlxNGhwjdEMp5z6ejQzcy8zZ80jvFED4xkmjI+lebOORLe5m/37D7Bps7mvxwIDAxk7YShffj6HuNnfFEy/694u3BJ9E0888qyxLOVuu4XD8+MBOPzVUkpd9/tGzbGktQRdVIOACmX9lqNVq0i2/bydPXv2kZOTw6yZ82jc5Ea/1fszdS69mEtqX8TS5XNYvW4xYTWr892ymVStWtl4FqeOF+CO42Z6WgYX1QoreFyrZg1jp1e4WUBAAB06t2H6l+Ybm9oufM/Os9ehRlIAACAASURBVIzenOavxuZpf5lt29m2bc+ybfte4GI/1TzNmNGD2bBhE0OHjTZR7ncqV65IuXL5b9SlSpWidetIUlM3Gc2wa1cmaWkZ1Kt3KQCtWjU/p5OpiyskJJjSpUML7t9yc0vWrUs1nqNKlUpA/tWVnTu35fPYWcZqD/ngP2z8aQsfjRhfMK3VzZH06ftPHrz3CY4dK97FJUWRs3svIRH5V9aGNL2e7G3pAARd/NtpBSXrX4ZVIpDc/f47x3d72g7CwxsSHFwKgKio5qRuMLuPnJKy7icur9OY66+O4vqro9iRvpObIruwe/ceI/XdcLwA54+bAN6kZOrWrUPt2hcRFBREt25dmD1nvmN53OKmVs3Y9NMWMnaYb2Bpu5Di8teg7nef7Qnbto/5qWaB5s3C6dHjTtasSSHJm78xvjjwbebNW+Tv0gVqVK/G2LHvERAQgMdjMW3aHOLiFhqrf0q/fi8xbtxwSpQIYuvWX+jV6xnjGapVq0Ls1DFA/gUhU6bOZP6CxcZzTJo8kooVK5CTnUP/fgM5cMDMxVIRTW7grnu6kLIulQVLvwTgrdeG8vqg5ylRIogpM8YC8IN3Nf/q/6pPa4cNeZaQiOsIqFCWy5ZMYM/wT9n54nCqvfAoBAZgn8gmY+D7AJSJbk65rjdj5+RgH/+VHU+97dMsZ0ryJjNjxlfEJ8wlNyeH1avX8cknn/m15ikfx7xH8xaNqVSpAmtTl/H2G8P4dMLnRmr/ETccL9xw3ATIzc2l71MvEjd3MgEeD+PGTyUl5Se/1/1k3DAiT24T63+K583Xh7F//wHeGfwylStX5PMvx7LmxxRu6/KgX3OM/mQIzSMjqFipAj+uX8KgN4czaeI0brujg9ELg0650LcLf3HDRTsmnZdDH/lKcYc+8pXiDH3kK8Ud+shXznXoI18q6tBH/vJ3hj7yt+IMfeRLRR36yB+KO/SRr7jhmO58gqIPfeQvRR36yB+KM/SRL7lhuwB3DH20o1kro4sjLOFbR/9m5/cCERERkQuI7YKB1k1yvstMRERERM5b6tkUERERMehCO2dTPZsiIiIi4jfq2fx/9u48Lqp6/+P46zuAbG65Iljmdq00t0BN0VAT3PXeculqt8x7u5XaZsttsbJfllaWWlZXM0xTk8x9C6PIXYYCNwT3FMQtdywV5vv7A/Hirsj5nhN8nj3mEXOGmc/bM98558v3nPMdIYQQQgiDnDD3pUkysimEEEIIISwjI5tCCCGEEAY5YIYyo2RkUwghhBBCWEZGNoUQQgghDJJzNoUQQgghhCgkMrIphBBCCGGQjGwKIYQQQghRSBw7sumEC7W0Qy4XU8r+HD4uZzQV7YCW4YQMAHfv2Wx3BD4v28LuCAD0O7TM7gj4eDnjM3I6+4zdERxBKWeMHHm7vOyO4Jh1UewuwRbnOGPrKIQQQghRTBS3frccRhdCCCGEEJaRkU0hhBBCCIPkAiEhhBBCCCEKiYxsCiGEEEIYpLWMbAohhBBCCFEoZGRTCCGEEMIg7bE7gVkysimEEEIIISwjI5tCCCGEEAZ55JxNIYQQQgghCoeMbAohhBBCGCRXowshhBBCCFFIimRnc/y4kexJX0tyUlyxzpDH5XKxZvUiZs2MNlbzk89GsGOnmwT34nPLbrqpDHPnTSZ53Q/MnTeZsmVLG8sDMHBgf9yJsbjd3zFx4hh8fX2N1A0OCeLbeRNZumY+P62axz8fexCALt2i+GnVPPYc2kiDhnUtz/HRJ++weccaViYsvOixgU/25/CJrZQrf1Oh1236wb/467pP6PDD8Iseu+2xjjywZwolypUEoFStKrSb+wY9d0zktsc6FnqWSylTpjRTp37G2rU/kJwcR9OmjY3UvZBd7TNP1arBLIn9hnXr4klO/oFBA/sbrZ9fVGQEGzcsJTVlOS88P8BY3Y8/Gc7WHQmsSlh0btkrQ55hxeoFLFs5j1lzJhIUVMnSDE7ZXuTx9fVlxfL5JLpjSU6K47Uhg43Vzs9J7bMwaI8yerNbkexsTpoUQ6fOfYp9hjyDBvYnNW2r0ZpTJn9L9+4Pn7fs2cGPEx+/gob12xAfv4JnBz9uLE+V4Mo8/sTDtAzvQlhYFC4vFz16dDFSOzs7hzdefZdWTTvTsV0v+v3z7/ylTk1SN23hkQcHsXplopEc06bM5P7uj1y0PCSkChFtwtm9K8OSutunLyO+z7sXLQ8ILkdQqzvJSj94btnpw1n8PGQSqZ8tsCTLpYwc+QZLlsTToEEbwsLak5pq9rMC9rbPPNnZ2bzwwlDq148gPLwLjz3+MLffXttoBsj943jM6GF07tKXOxu0plev7sZyTJ3yLfd173fesjGjxtOiWSdaNu/C4sU/8uJLgyzN4JTtRZ5Tp04RGdWT0LBIQsOiiIyMoEkT83+QOaV9ioKxpLOplCqhlPqHUures/f/rpT6WCk1QCnlY0XN/JYtX8Ohw0esLuP4DAAhIUF06NCG6OhpRuuuWJHA4UPn//s7dW7HlCnfAjBlyrd07hJpNJO3txf+/n54eXkREOBPZuY+I3X37zvA+rUpAGSdOMmWzdsIqlKZLZu3s23rTiMZAFaucHP4Em1y2IhXeOPVEWitLal7YE0qpw+fuGh5ozceJPmtaefVPfXbMQ6t3Y4nO8eSLBcqVaok4eFNiI7+GoAzZ85w9OgxI7UvZFf7zLN3736SkjcAcOJEFqmpWwgODjKaAaBJWCO2bdvJjh27OHPmDDExc+jaJcpI7Ut9Ro4f/1/bDQzwt+xzkscp24v8srJOAuDj442Pj7fl6+BSnNI+C4vWZm9Xo5T6Qim1Xym1Id+yhkqp1UqpZKVUolKqydnlSik1Rim1VSm1Til11b8+rBrZjAY6AU8ppSYDPYA1QBjwuUU1xSW8/94bvPTy23g89s8gW6lSBfbtPQDAvr0HqFixvLHamXv2MXrUeFLTVrJtewLHjh4nLm6Zsfp5br4lmHp33s4vP681XvtSOnRsS+aevWzYkGq0bkhkY37fe4gjKbuM1r1Q9eq3cODAIcaPH8nq1Qv59NMRBAT4G8/hlPaZp1q1qjRsUI+EhCTjtYNDgtidvufc/fSMTNs7FUNeH8zG1OX06NWNYW+NMlbXKdsLl8uFO+E7MtLXEhe3DLfbfLvIz872WYRNBNpfsOxdYKjWuiHw2tn7AB2A2mdvjwKfXu3Freps3qm17gX8FYgE7tdaTwb6AY0u9ySl1KNne8+JHk+WRdGKj44d2nLgwG8kJa23O4rtypYtTefO7ah7R0tq1WxKQGAAvXt3N5ohIDCAzyeN4bWXh3PiuP3t29/fj2eff5x3DO48Abz8S3DHk91Y/94Mo3Uvxdvbm0aN6jFu3GSaNetIVtbvPP/8E8ZzOKF95gkMDCBm+ngGP/f6eaN6pih18flldoyk5fd/Q0dS97Zwvpk+h0f//aCRmk7aXng8HsKaRFG9RhihoQ2pe0cd27LY3T6LKq31UuDQhYuBvIsrygB5fwV2AybpXKuBskqpKld6fas6my6lVAmgFBBwNiSAL3DZw+ha63Fa61CtdajLFWhRtOLj7uahdOrUjrS0lUyeNJaIiBZER4+2Lc/+/QepHFQRgMpBFTlw4DdjtVu3Dmfnr7s5ePAQ2dnZzJ2zmKbN7jJW39vbmwmTRjPzm3ksnLfEWN0rqV7jFqrdejPLVs1n7cZ4gkOC+Gn5HCpVqmBp3ZLVKlPyloq0//4duqwZRUCVcrT/bhh+Fctc/cmFLCMjk4yMTNzuZABmzVpIw4b1jOewu33m8fb2Jmb6eKZNm8Xs2Yuu/gQLZKRncnPV4HP3q4ZUMX5KweV8EzOXrt0uHPwpfE7cXgAcPXqMpUtXERkVYUt9J7TPwvInuUDoaeA9pdRu4H3gpbPLQ4Dd+X4v/eyyy7KqszkBSAWSgVeAb5RS4wE38LVFNcUFhgwZQc1aTahTpzkP/mMA8fEr6NfvKdvyLFzwPX363AdAnz73sWC+uY3o7vQ9hIU1wt/fD4CIiBakGbwQ5MOP32LL5u38d+yXxmpeTcrGzfylelMa1I2gQd0I9mTs5Z7wbuzff/DqT74BR1N3M6v+E8xr+jTzmj7NycxDLI56hT8OHLW07qXs23eA9PRMateuAUDr1i3YtGmL8Rx2t88848eNJDV1K6NGjzNeO487MZlatapz66034+PjQ8+e3Zg3P9a2PDVq3nru5w6d7mXL5m2W13TS9qJChXKUKZM7uOXn50ebNuGkGb7gNI8T2uefVf4jx2dvj17D0x4HntFa3ww8Q27fDuBSvdcrHn6wZFJ3rfWHSqnpZ3/eo5SaBNwLjNdaJ1hRM7+vJo/lnlZ3U6FCOXZuT2Tom+8TPdFsH9cJGewUPXE0LVs1o3z5m0jbspJhb43ig5GfMmnyx/zjoZ6k797Dg33NTWmS6E5m9uxFrFi5gJzsbNau3cgXX5i5aKpJs8b06N2NlI1pfL9sJgDvvDmKEr4lGDbiFcpXKMdXMZ+xYX0qD9z3L8tyfB79IS1aNqV8+ZvYkLac4cNG89Wkbyyrl6f5JwOodPft+JYrRbfEj1g/cgbbp/10yd/1q1iGqEVv4VPKH+3xUOefHVgQ8QLZJ363LN8zz7zGxIljKFHChx07dvHoo89ZVuty7GyfeVo0D6Nv3/tZvz6FRHdu5+7VIcNZvPgHozlycnJ46ulXWbhgKl4uFxO/nE5KymYjtSdEjyL87GckJW057wwbTWRUBLVq18Dj8bB7VwbPPDXE0gxO2V7kqRJUmQkTPsTLywuXSzFjxnwWLjQ/pZ9T2mdhMf11lVrrccD19tIfAvJGqL7hf9fcpAM35/u9qvzvEPslqcudC6OUmscVeqpa667XGLZAvEuE2HuSjoN4ueyfocrH5Ywvm9JX/uPJiFIlzF9Acimnss/YHYFPSje1OwIA/Q7ZdzFNHid8TgFOO6Bd2P8phcASfnZHAMDfu4TdETj0+3G7IwD2n3ub58zpDNsnntxQo7PRlVFv+/yr/puVUrcC87XW9c7e3wQ8rrWOV0q1Bd7VWt+llOoEDAQ6Ak2BMVrrJld67Sv1IN6/tn+CEEIIIYS4Vk77ukql1DQgAqiglEoHXgf+BYxWSnkDf5B75TnAQnI7mluBk+Re/H1Fl+1saq0vfZxLCCGEEEIUGVrrBy7z0EVXKurcIerrOg/uqsdGlVK1gXeAO4BzxyW01jWup5AQQgghhLi2idaLkms5ySia3Ak7s4HWwCRgspWhhBBCCCFE0XAtnU1/rXUcuRcT/aq1fgNoY20sIYQQQoiiyaOV0ZvdruUS4z+UUi5gi1JqIJABVLI2lhBCCCGEKAqupbP5NLnfAvQk8H/kjmo+ZGUoIYQQQoiiymlXo1vtqp1NrbX77I8nuIbL24UQQgghhMhzLVej/8gl5ujVWst5m0IIIYQQ16m4XY1+LYfR8393mx9wH7lXpgshhBBCCHFF13IY/ecLFq1QSsmE70IIIYQQBeCEK8RNupbD6OXy3XWRO5t8kGWJhBBCCCFEkXEth9F/JvecTUXu4fMdQH8rQ4nzaQec3HHG44wzJ5ywLo6f/t3uCI7x8KGldkcA4MWgVnZH4L19y+2OIPL5/cwpuyMAUMLrWnaz1vI4YLspzidXo1/sdq31H/kXKKV8LcojhBBCCCGKkGv5BqGVl1i2qrCDCCGEEEKIoueyI5tKqSAgBPBXSjUi9zA6QGlyJ3kXQgghhBDXSS4Q+p8o4GGgKjCS/3U2jwEvWxtLCCGEEEIUBZftbGqtvwS+VErdp7X+1mAmIYQQQogiq7hdsnUt52zepZQqm3dHKXWTUuotCzMJIYQQQogi4lo6mx201kfy7mitDwMdrYskhBBCCFF0ebQyerPbtXQ2vfJPdaSU8gdk6iMhhBBCCHFV1zLP5ldAnFIq+uz9fsCX1kUSQgghhCi6ZFL3C2it31VKrQPuJfeK9MVANauDCSGEEEKIP79r/R6tvYAH6Enu11XK1elCCCGEEAXgsTuAYZc9Z1Mp9Rel1GtKqU3Ax8BuQGmtW2utPzaWsACiIiPYuGEpqSnLeeH5AbZkGD9uJHvS15KcFGdL/Ty+vr6sWD6fRHcsyUlxvDZksG1ZXC4Xa1YvYtbM6Kv/ciFz0np44ol+uN3f4U6MZcCAR2zJMHBgf9yJsbjd3zFx4hh8fe07DdtEu+j+7r94IfETBnw3/Nwy/zKBPDT5Pzz140gemvwf/ErnfleFbyl/+nw+mCcWvc3A2BE06mH9967Xrl2D1asXnrvt27eBgQPNto2qVYNZEvsN69bFk5z8A4MG9jdaPz+7t+F2bi9Gf/w2KVtXsnTVvHPL6t15G4u+n86Py2azJP5bGjW+01gecM7+zO52IQruShcIpQJtgS5a63Ct9UdAjplYBedyuRgzehidu/Tlzgat6dWrO7ffXtt4jkmTYujUuY/xuhc6deoUkVE9CQ2LJDQsisjICJo0aWxLlkED+5OattWW2k5ZD3fc8Rf69etNq1bdaNa0Ax06tKFmzVuNZqgSXJnHn3iYluFdCAuLwuXlokePLkYz5GeiXSTNWMbkh949b1nLx7uyfeVGRrcezPaVG2n5RFcAmj7Yjv1bM/ikw8t80fstol7pg5ePl6X5tmzZTrNmHWnWrCPNm3fm5MnfmTv3O0trXig7O5sXXhhK/foRhId34bHHH7Zl2+mEbbid24uvp86k933/PG/Za28+z/vDx9K6ZXdGDBvN628+byRLHifsz5zQLgqTRhm92e1Knc37yD18/qNSarxSqi04IPFVNAlrxLZtO9mxYxdnzpwhJmYOXbtEGc+xbPkaDh0+cvVfNCAr6yQAPj7e+Ph4o7X56WRDQoLo0KEN0dHTjNfO44T1UKdOLRLcSfz++x/k5OSwbPkaunY13z69vb3w9/fDy8uLgAB/MjP3Gc8A5trFrwmp/H70xHnLbmvXmKQZy4Dczujt7e4Ccidb9g30A6BEgB+/HzmBJ9vcQa/WrVuwY8cudu3KMFYTYO/e/SQlbwDgxIksUlO3EBwcZDQDOGcbbtf2YtXKRA4fPnr+Qq0pVToQgFKlS7F3734jWfI4YX/mlHYhCuaynU2t9SytdS/gNiAeeAaorJT6VCkVebUXVkrVVEo9p5QarZQaqZR6TClVptCSX0ZwSBC70/ecu5+ekWnLBtNJXC4X7oTvyEhfS1zcMtzuJOMZ3n/vDV56+W08HvvOVHHCekhJSaNFiyaUK1cWf38/oqJaE1K1itEMmXv2MXrUeFLTVrJtewLHjh4nLm6Z0Qx57GwXgRXLcOJA7g70xIEjBFbI3Tyt+TKWirVCeD7hYwZ8N5xFQycb/cOkR4+uxMTMNVbvUqpVq0rDBvVISDD/GXHKNtwJ24s8r/znbV5/8wWSN8Yz9K0XeWvoB7ZlsYtT2kVh8WizN7tddZ5NrXWW1nqK1rozud+Tngz850rPUUo9CXwG+AFhgD9wM7BKKRVxo6GvUvuiZXaMYDmJx+MhrEkU1WuEERrakLp31DFav2OHthw48BtJSeuN1r2Q3esBIC1tGx988Bnz5n/F7Dlfsn79JnKyzZ6dUrZsaTp3bkfdO1pSq2ZTAgID6N27u9EM4Jx2caFareqTmfIr7zUZyKcdX6bTmw/hW9LfSG0fHx86dbqXmTMXGKl3KYGBAcRMH8/g517n+PETV39CIXPKNtwJ24s8/fo/wJCX36Fh3QiGvPwOoz4eZlsWuzilXYiCuZZJ3c/RWh/SWv9Xa93mKr/6L6C91votcqdMukNr/QrQHvjwck9SSj2qlEpUSiV6PFnXE+2cjPRMbq4afO5+1ZAqth0idJqjR4+xdOkqIqMijNa9u3konTq1Iy1tJZMnjSUiogXR0aONZsjPrvWQZ9KXMbRo3pmoyF4cPnyErdt2GK3funU4O3/dzcGDh8jOzmbunMU0bXaX0Qxgf7vIOnCUkhVzv4m3ZMWyZB3MPXTZuEcrNi12A3Do130c3n2ACjXNjD5HRUWQnLyB/fsPGql3IW9vb2Kmj2fatFnMnr3IlgxO24bbvb0A6PXAX5k/NxaAObMW0bhxfduy2MVp7eJGeVBGb3a7rs7mdcqbVskXKAWgtd4F+FzuCVrrcVrrUK11qMsVWKCi7sRkatWqzq233oyPjw89e3Zj3vzYAr1WUVChQjnKlCkNgJ+fH23ahJNm+CKdIUNGULNWE+rUac6D/xhAfPwK+vV7ymgGJ6yHPBUrlgdyr/7t2rU93xg+ZLo7fQ9hYY3w9889LzEiogVpqebXhd3tIvX7X2h0f0sAGt3fktQlvwBwZM9v1GhRF4DACqWpUKMKh3eZOUeuZ097D6GPHzeS1NStjBo9zrYMTtiGO2l7Abnn0zYPbwJAy3uasX37Ttuy2MUJ7UIU3LXOs3m9PgfcSqnVQCtgBIBSqiJwyKKaAOTk5PDU06+ycMFUvFwuJn45nZSUzVaWvKSvJo/lnlZ3U6FCOXZuT2Tom+8TPfFr4zmqBFVmwoQP8fLywuVSzJgxn4UL7Z2+wg5OWg9Tpn5KuXI3kX0mm2efGcKRI8eM1k90JzN79iJWrFxATnY2a9du5Isv7Ltwy4T7xwygerPbCbipFINXfcSPH85g2afz6DV2EI17RnB0z0GmPzEGgJ/GzOKv7z/GgMXDQUHs8K85edj6w8n+/n60adOSgQNftrzWpbRoHkbfvvezfn0Kie7cnfirQ4azePEPRnM4YRtu5/bivxNG0iK8CeXK38TalJ94952PePbJIQwb8TJeXt6cOnWKZ596zUiWPE7YnzmhXYiCU1ad86CUqgvcDmzQWqde7/O9S4TIyRhnuS5xropplzpfxg5OOEfHx8uqv9H+fLI9zpgN7cUg6+fCvJr39i23OwIA2TnZdkfA/k+pM7abAGX8CnaUrjAd/t38ubdOln06w/bGEVe5l9GPSdt90239N1u219RabwQ2WvX6QgghhBDC+WSIRgghhBDCIPm6SiGEEEIIIQqJjGwKIYQQQhjkhK+QNElGNoUQQgghhGVkZFMIIYQQwiA5Z1MIIYQQQohCIiObQgghhBAGycimEEIIIYQQhURGNoUQQgghDJKr0YUQQgghhCgkMrIphBBCCGGQp3gNbEpn88/Ao7XdEVAOyADg5fKyO4Ij3g+AHE+O3RHw8XLGJmR45k92RyCycgO7IwCwZP86uyPg8dh/+YPWmhLePnbHIMcB66K0bwDHTp20O4YoxpyxpxBCCCEKkRM6mk4hHU3n8cg5m0IIIYQQQhQO6WwKIYQQQgjLyGF0IYQQQgiDnHHmvzkysimEEEIIISwjI5tCCCGEEAbZP0eBWTKyKYQQQgghLCMjm0IIIYQQBnmUTH0khBBCCCFEoZCRTSGEEEIIg+RqdCGEEEIIIQqJjGwKIYQQQhgkV6MXAVGREWzcsJTUlOW88PwAWzKMHzeSPelrSU6Ks6W+k3JUrRrMkthvWLcunuTkHxg0sL8tOcqUKc3UqZ+xdu0PJCfH0bRpY+MZateuwerVC8/d9u3bwMCBjxjN4Ovry4rl80l0x5KcFMdrQwYbrZ/fwIH9cSfG4nZ/x8SJY/D19TVa3+51EVg6kJc+e4lPf/iMT+M+47bGt/HC2BcZs+gjxiz6iAkrvmDMoo+MZnK5XKxZvYhZM6ON1s3jlO2FXW3zo0/eIW37alasWXBu2YsvDWJD2jJ+WjGXn1bM5d7Ie4xkySP7VHGjlNbOPHPAu0RIgYK5XC42bVxG+44PkJ6eyepVC+n74BNs2rSlsCNeUcvwppw4kUV09GgaNmprtLYVOW7kurmgoEpUCapEUvIGSpYMZM2axdx//yMFek+8XF4FzvH55x+wYkUC0dFf4+PjQ0CAP0ePHrvu11GFdBWhy+Vi27Y13HNPd3btyrju5+d4cgpcOzAwgKysk3h7exP/4yyeHfw6CQm/XPfr+HgV/OBIleDKfP/9DO5qfC9//HGKSZM/Jva7eL76asZ1v9aZnOwC5yisdRFZucF1P+eZD55hY8JGYr+OxdvHG19/X7KOZZ17vP+r/ck6fpKvR0+75tdcsn/ddefI76kn/0Xju+pTulRJ/vq3fgV6DY+n4OM2hbW9KOHtU+AMhdk2fb2uL8fdLcLIOpHFp+Peo0XTTkBuZzMr6yQfj5lw3fUBjp06WaDnQdHcp2afzrD9UvBpwX2Mdr4e2DPF1n9zkRvZbBLWiG3bdrJjxy7OnDlDTMwcunaJMp5j2fI1HDp8xHhdJ+bYu3c/SckbADhxIovU1C0EBwcZzVCqVEnCw5sQHf01AGfOnClQR7MwtW7dgh07dhWoo3mjsrJydz4+Pt74+Hhj1x+d3t5e+Pv74eXlRUCAP5mZ+4xnsGtd+Jf0p26TesR+HQtA9pns8zqaAOGdW7J0zk9G8gCEhATRoUMboqOvvXNb2JywvQD72uaqFW4OHz5qpNa1kH2qKAxFrrMZHBLE7vQ95+6nZ2TasqESl1atWlUaNqhHQkKS0brVq9/CgQOHGD9+JKtXL+TTT0cQEOBvNMOFevToSkzMXFtqu1wu3AnfkZG+lri4ZbjdZt8PgMw9+xg9ajypaSvZtj2BY0ePExe3zHgOu9ZF0C1VOHboKE+PfIbRC8cwaMST+Pr/71Bt3SZ1OXLwCHt27rnCqxSu9997g5defvuGRiYLk13bC6e0zfz++Whflq2ax0efvEOZsqWN1ZV9qjU8KKM3uxW5zualDnE69VSB4iYwMICY6eMZ/NzrHD9+wmhtb29vGjWqx7hxk2nWrCNZWb/z/PNPGM2Qn4+PD5063cvMmQuu/ssW8Hg8hDWJonqNMEJDG1L3jjrGM5QtW5rOndtR946W1KrZlIDAAHr37m48h13rwsvbRc16tVg4eSFPdXySU7//QY8nepx7/J5u9xgd1ezYoS0HDvxGUtJ6YzWvSTwCTQAAIABJREFUxM7thVPaZp4vPp9K4/ptadW8K3v37uett18yVlv2qaIwWNLZVEqVUUoNV0qlKqV+O3vbdHZZ2Ss871GlVKJSKtHjybrcr11RRnomN1cNPne/akgVWw7NifN5e3sTM30806bNYvbsRcbrZ2RkkpGRidudDMCsWQtp2LCe8Rx5oqIiSE7ewP79B23LAHD06DGWLl1FZFSE8dqtW4ez89fdHDx4iOzsbObOWUzTZncZz5HH9Lo4mPkbBzMPsjk5DYAVC1dQs14tAFxeLu5u35yl85YayQJwd/NQOnVqR1raSiZPGktERAuio0cbq5+f3dsLp7XNAwd+w+PxoLVm0sQYGt9V31ht2adaQxu+2c2qkc0Y4DAQobUur7UuD7Q+u+ybyz1Jaz1Oax2qtQ51uQILVNidmEytWtW59dab8fHxoWfPbsybH1ug1xKFZ/y4kaSmbmXU6HG21N+37wDp6ZnUrl0DyD1f0vQJ7vn17GnfIfQKFcpRpkzuYTg/Pz/atAknLW2r8Ry70/cQFtYIf38/ACIiWpCWajaHneviyIHDHMw8QEiNEAAatGjAri27AGgY3oj0ben8tvc3I1kAhgwZQc1aTahTpzkP/mMA8fEr6NfvKWP187N7e+GEtplf5coVz/3cuUs7NqVsNlZb9qmiMFg1z+atWusR+RdorfcCI5RSls7zkpOTw1NPv8rCBVPxcrmY+OV0Ugx+MPN8NXks97S6mwoVyrFzeyJD33yf6IlfF8scLZqH0bfv/axfn0KiO3cj9eqQ4Sxe/IPRHM888xoTJ46hRAkfduzYxaOPPme0fh5/fz/atGnJwIEv21K/SlBlJkz4EC8vL1wuxYwZ81m40Px0IonuZGbPXsSKlQvIyc5m7dqNfPGF2QtT7F4Xn732X54b8zzePt7s3bWXUc+NAqBV11YsnWvuELqTOGF7YWfbHP/Fh7Ro2YTy5W9iQ+oyhr89mhbhTbmz/u1ordm1K4NnnxxiJAvIPlUUDkumPlJKxQLfA19qrfedXVYZeBhop7W+92qvUdCpj4Q17D+9ONeNTH1UWApr6qMbdSNTHxWWG5n6qDDdyNRHhaUgUx9Z4UanPioMTrjA6EamPipM1zv1kRVuZOqjosgJUx9NCulrtI/zj4yviuTUR72A8sBPSqlDSqlDQDxQDuhxpScKIYQQQoiiw5JhCa31YeDFs7fzKKX6AfZ8NYUQQgghhM3sH/s3y46pj4baUFMIIYQQQtjAkpFNpdTlThpSQGUragohhBBC/BkUt4tSrDq7vzIQRe5UR/kpYKVFNYUQQgghhMNY1dmcD5TUWidf+IBSKt6imkIIIYQQjuex/Xp4s6y6QKj/FR77uxU1hRBCCCGE8zhjkjwhhBBCiGJCrkYXQgghhBCikMjIphBCCCGEQTKyKYQQQgghRCGRkU0hhBBCCIO0XI0uxMWcMgFttifH7gj4evvYHQEA+9cEnM4+Y3cEwBntc8n+y32XhVn1y1W3OwJJB7fZHYFT2Wfwctl/8M6jndA6hbCXdDaFEEIUOU7oaApxOXLOphBCCCGEEIVEOptCCCGEEMIychhdCCGEEMIgOYwuhBBCCCFEIZGRTSGEEEIIg4rbHAUysimEEEIIISwjI5tCCCGEEAZ5itmk7jKyKYQQQgghLCOdTSGEEEIIgzyGb1ejlPpCKbVfKbUh37L3lFKpSql1SqlZSqmy+R57SSm1VSmVppSKutrrS2dTCCGEEKJ4mwi0v2DZEqCe1ro+sBl4CUApdQfQG6h79jmfKKW8rvTi0tkUQgghhDDIaSObWuulwKELlsVqrbPP3l0NVD37czfga631Ka31DmAr0ORKr18kO5vjx41kT/pakpPibM0RFRnBxg1LSU1ZzgvPD7AlgxPWhRMyOCnHwIH9cSfG4nZ/x8SJY/D19TVa39fXlxXL55PojiU5KY7Xhgw2Wj9P1arBLIn9hnXr4klO/oFBA/vbksMp7QLA5XKxZvUiZs2MNl73q9jP+eDL4QCMm/URU5ZMYMqSCSz8ZSbvfTHMaB4nbDvBvvcjT+3aNVi9euG52759Gxg48BHjOZzyGXFKuyimHgEWnf05BNid77H0s8suq0h2NidNiqFT5z62ZnC5XIwZPYzOXfpyZ4PW9OrVndtvr208hxPWhRMyOCVHleDKPP7Ew7QM70JYWBQuLxc9enQxmuHUqVNERvUkNCyS0LAoIiMjaNKksdEMANnZ2bzwwlDq148gPLwLjz3+cLH9jOQZNLA/qWlbjdft/c/72bHl13P3H/3rIPq060+fdv1Z//NGfly41FgWp2w7wb73I8+WLdtp1qwjzZp1pHnzzpw8+Ttz535nPIcTPiNOaheFQRu+KaUeVUol5rs9eq1ZlVKvANnAlLxFl/knXVaR7GwuW76GQ4eP2JqhSVgjtm3byY4duzhz5gwxMXPo2uWq59AWOiesCydkcFIOb28v/P398PLyIiDAn8zMfcYzZGWdBMDHxxsfH2+0Nj/F8N69+0lKzj0X/cSJLFJTtxAcHGQ8h1PaRUhIEB06tCE6eprRupWqVCS87d3MmbrgoscCAv0JbdGYnxYvM5bHKdtOu96Py2ndugU7duxi164M47Wd8BlxSrv4s9Jaj9Nah+a7jbuW5ymlHgI6A330/3YU6cDN+X6tKrDnSq9TJDubThAcEsTu9P+t+/SMTFt2pMJZMvfsY/So8aSmrWTb9gSOHT1OXJy5HXkel8uFO+E7MtLXEhe3DLc7yXiG/KpVq0rDBvVISLA3h53ef+8NXnr5bTwes9+a/OzQQYx569NL1o3o0Ar38p/JOnHSWB6nbDvtej8up0ePrsTEzLU7hm2c0i4Ki0eZvRWEUqo98CLQVWudfyMwF+itlPJVSlUHagMJV3ot6WxaRKmL3107Ro+Es5QtW5rOndtR946W1KrZlIDAAHr37m48h8fjIaxJFNVrhBEa2pC6d9QxniFPYGAAMdPHM/i51zl+/IRtOezUsUNbDhz4jaSk9Ubrht97N4cPHiZ1/eZLPh7VvS3fzTZ7np4Ttp12vR+X4+PjQ6dO9zJz5sWjz8WFE9pFUaaUmgasAuoopdKVUv2Bj4FSwBKlVLJS6jMArfVGIAZIARYDA7TWOVd6fUu+QUgpVZrcS+SrAou01lPzPfaJ1vqJyzzvUeBRAOVVBpcr0Ip4RmSkZ3Jz1eBz96uGVLHlcKlwltatw9n5624OHsy96G/unMU0bXYXX38925Y8R48eY+nSVURGRbAxJc14fW9vb2Kmj2fatFnMnr3o6k8oou5uHkqnTu2Iat8aP19fSpcuRXT0aPr1e8rSug3C7qRlZAuat22Gr28JAksF8uZHr/LaoLcoc1Np7mh4O8/3f9XSDBdywrbTrvfjcqKiIkhO3sD+/Qdtqe8ETmgXhckZ4+X/o7V+4BKLJ1zh94cB13zloFUjm9HknkD6LblDrd8qpfIuuW12uSflP6fgz9zRBHAnJlOrVnVuvfVmfHx86NmzG/Pmx9odS9hsd/oewsIa4e/vB0BERAvSUs1egFChQjnKlCkNgJ+fH23ahJNm00UQ48eNJDV1K6NGX9PpQ0XWkCEjqFmrCXXqNOfBfwwgPn6FkY7N2HfG0Tn0fro17cXLjw/FvfwXXhv0FgBtO0ew/PtVnD512vIc+Tlh22nX+3E5PXsW70Po4Ix2IQrOqs5mTa31f7TWs7XWXYFfgB+UUuUtqneeryaPZfnSudT5S012bk+k38O9TZQ9T05ODk89/SoLF0xlw7p4ZsyYR0rKpQ9VWckJ68IJGZySI9GdzOzZi1ixcgFu93e4XIovvjB7AUKVoMosiY3h58QlrFo5n7i4ZSxcaH5KkxbNw+jb935at25OojuWRHcs7du3MZ7DCe3CiSK7tSV29vfG6zpl2+kU/v5+tGnTkjlzFtuWwQmfEWkXf27KinMelFKbgLpaa0++ZQ8BLwAltdbVrvYa3iVC5GQM4Ui+3j52RwDgTE721X/JYk45Z8oJKbxczjgFvn656nZHIOngNrsjOOb9cCn7czhhW+Ek2aczCnjJTOF5p1pfo5utl379ytZ/s1WfgnnAeUMUWusvgcGA2WMyQgghhBDCNpZcIKS1fuEyyxcrpd62oqYQQgghxJ+BxxHHY8yxY3x/qA01hRBCCCGEDaya+mjd5R4CKltRUwghhBDiz8BpUx9ZzZLOJrkdyijg8AXLFbDSoppCCCGEEMJhrOpszif3qvPkCx9QSsVbVFMIIYQQwvGK1xmb1l0g1P8Kj/3dippCCCGEEMJ5rBrZFEIIIYQQl1Dcztm0f7ZZIYQQQghRZMnIphBCCCGEQR7bv8PILBnZFEIIIYQQlpGRTSGEEEIIg4rbNwhJZ/MKitko9xUp5Yy14dH2f0BPZZ+xOwLgjPZp/7vhHDkeZ5zyn3Rwm90RqBBQ2u4IABw8eczuCOQUu0tBhLiYdDaFEEIUOU7oaApxOcXtD3U5Z1MIIYQQQlhGOptCCCGEEMIychhdCCGEEMKg4nYmr4xsCiGEEEIIy8jIphBCCCGEQcVt6iMZ2RRCCCGEEJaRkU0hhBBCCIOK17imjGwKIYQQQggLycimEEIIIYRBcjW6EEIIIYQQhURGNoUQQgghDJKr0YuAqMgINm5YSmrKcl54foAtGapWDWZJ7DesWxdPcvIPDBrYv1hmAPD19WXF8vkkumNJTorjtSGDbckxftxI9qSvJTkpzpb6TsnglHYBzvisOiGDU3LYlSE4JIhv501k6Zr5/LRqHv987EEAunSL4qdV89hzaCMNGtY1lgec8X44YXsBzlgXTsohrp/S2pm9a+8SIQUK5nK52LRxGe07PkB6eiarVy2k74NPsGnTlut+LVWQAGcFBVWiSlAlkpI3ULJkIGvWLOb++x8pUA4nZFDqRtYGBAYGkJV1Em9vb+J/nMWzg18nIeGX634dzw2015bhTTlxIovo6NE0bNS2wK9zIwozQ0HfkcJsFzey9SjMz+qfOYNTchRmhgoBpa/r9ytVrkjloIqsX5tCYMkAYuO/pV+fgWit8Xg8vDdqKENffZe1yRuv+TUPnjx2vbHPccL7Ac7YZjllXRRmjuzTGTe2QysEz9za22jn68OdX9v6by5yI5tNwhqxbdtOduzYxZkzZ4iJmUPXLlHGc+zdu5+k5A0AnDiRRWrqFoKDg4pdhjxZWScB8PHxxsfHGzv+yFm2fA2HDh8xXtdpGZzSLpzwWXVCBqfksDPD/n0HWL82BYCsEyfZsnkbQVUqs2XzdrZt3WkkQ35OeD/AGdsLp6wLp+QQBVPkOpvBIUHsTt9z7n56RqZtHaw81apVpWGDeiQkJBXbDC6XC3fCd2SkryUubhlut33rQvyPne3CCZ9VJ2RwSg4nZAC4+ZZg6t15O7/8vNZ47TxOWRdO4JR14ZQchcVj+Ga3ItfZvNThXjtPFQgMDCBm+ngGP/c6x4+fKLYZPB4PYU2iqF4jjNDQhtS9o44tOcT/2N0unPBZdUIGp+RwQoaAwAA+nzSG114ezonjWUZr5+eEdeEUTlkXTskhCsaSzqZSKkgp9alSaqxSqrxS6g2l1HqlVIxSqsoVnveoUipRKZXo8RRsQ5ORnsnNVYPP3a8aUoXMzH0Feq0b5e3tTcz08UybNovZsxcV2wz5HT16jKVLVxEZFWF3lGLNCe3CCZ9VJ2RwSg67M3h7ezNh0mhmfjOPhfOWGKt7KXavCydxyrpwSo7Cog3/ZzerRjYnAinAbuBH4HegE7AM+OxyT9Jaj9Nah2qtQ12uwAIVdicmU6tWdW699WZ8fHzo2bMb8+bHFui1btT4cSNJTd3KqNHjbKnvlAwVKpSjTJncCwb8/Pxo0yactLSttuURzmgXTvisOiGDU3LYneHDj99iy+bt/Hfsl8ZqXo7d68JJnLIunJJDFIxVnc3KWuuPtNbDgbJa6xFa611a64+AahbVBCAnJ4ennn6VhQumsmFdPDNmzCMlZbOVJS+pRfMw+va9n9atm5PojiXRHUv79m2KXQaAKkGVWRIbw8+JS1i1cj5xcctYuND8VB5fTR7L8qVzqfOXmuzcnki/h3sXywxOaRdO+Kw6IYNTctiZoUmzxvTo3Y3wVk35ftlMvl82k7btWtGh8738svFH7gpryFcxnzHt2/FG8jjh/QBnbC+csi6ckkMUjCVTHyml1mqtG5z9+S2t9av5Hluvtb7zaq9R0KmPCpPtcyM4yI1OfVRYbmTqo6LGCe+IvBviUq536iMr3MjUR6Joc8LURwNv7WV08/nxzulFcuqjOUqpkgAXdDRrAWkW1RRCCCGEEA5jyddVaq1fu8zyrUqpBVbUFEIIIYT4M5Cvq7TeUBtqCiGEEEIIG1gysqmUWne5h4DKVtQUQgghhPgzKF7jmhZ1NsntUEYBhy9YroCVFtUUQgghhBAOY1Vncz5QUmudfOEDSql4i2oKIYQQQjhecTtn06oLhPpf4bG/W1FTCCGEEEI4j1Ujm0IIIYQQ4hI8dgcwzI6r0YUQQgghRDEhI5tCCCGEEAbpYnbOpoxsCiGEEEIIy8jIphBCCCGEQcXtnE3pbF5B8RrkvgrtjLXhUsruCPj7+NodAQAX9q+LM54cuyMAzjgk5e3ysjsCAH9kn7Y7AgdPHrM7At+Wu8fuCAC867XX7gisOZBmdwRRzElnUwghhBDCICf8gWySnLMphBBCCCEsI51NIYQQQghhGTmMLoQQQghhUHG7QEhGNoUQQgghhGVkZFMIIYQQwiCPQ2Z4MUVGNoUQQgghhGVkZFMIIYQQwqDiNa4pI5tCCCGEEMJCMrIphBBCCGGQp5iNbcrIphBCCCGEsIyMbAohhBBCGCRfV1kEjB83kj3pa0lOiivWGQCiIiPYuGEpqSnLeeH5AbZkqFo1mCWx37BuXTzJyT8waGB/4xl8fX1ZsXw+ie5YkpPieG3IYGO1P/5kOFt3JLAqYdG5Za8MeYYVqxewbOU8Zs2ZSFBQJctzfPTJO2zesYaVCQsvemzgk/05fGIr5crfZGmGTz4bwY6dbhLci88tu+mmMsydN5nkdT8wd95kypYtbWmGCz3xRD/c7u9wJ8YyYMAjxuo6pV1cyOVysWb1ImbNjDZeO4+p7VbDDx+l/YZPaR0/4qLHaj7eiW57p1KiXCkAvEv503TSc0TEvUPrn97llt73WJZrxuqpTPr+cybGjmPCwk8BGPDqv5n600S+XDKetz9/k5KlAy2rfyHZn4kbVSQ7m5MmxdCpc59in8HlcjFm9DA6d+nLnQ1a06tXd26/vbbxHNnZ2bzwwlDq148gPLwLjz3+sPEcp06dIjKqJ6FhkYSGRREZGUGTJo2N1J465Vvu697vvGVjRo2nRbNOtGzehcWLf+TFlwZZnmPalJnc3/3izlRISBUi2oSze1eG5RmmTP6W7t0fPm/Zs4MfJz5+BQ3rtyE+fgXPDn7c8hx57rjjL/Tr15tWrbrRrGkHOnRoQ82atxqp7ZR2caFBA/uTmrbVeN08Jrdbu6cvZdUDF3c0/YLLUanVnZxMP3BuWfV+kRzfnE5825dY8bf/o+7rfVA+XpbkAhjU41kejnyU/h1zPw/upT/zYJtHeKjdv9i9fTcPDvy7ZbUvJPuzwucxfLNbkexsLlu+hkOHjxT7DE3CGrFt20527NjFmTNniImZQ9cuUcZz7N27n6TkDQCcOJFFauoWgoODjOfIyjoJgI+PNz4+3mhDk+quXOHm8AVt4fjxE+d+DgzwN5LlUjkAho14hTdeHWEkw4oVCRw+dH6GTp3bMWXKtwBMmfItnbtEWp4jT506tUhwJ/H773+Qk5PDsuVr6NrVzGfEKe0iv5CQIDp0aEN09DSjdfMzud36bXUqp4+cuGj5nW8+yMb/m3r+/DRa413SHwDvQD9OHzmBzja3G09YmkhOTm69jb9solKVisZqy/5M3Kgi2dkUuYJDgtidvufc/fSMTFs6eflVq1aVhg3qkZCQZLy2y+XCnfAdGelriYtbhtttPkN+Q14fzMbU5fTo1Y1hb42yJUOHjm3J3LOXDRtSbakPUKlSBfbtzR1B2rf3ABUrljdWOyUljRYtmlCuXFn8/f2IimpNSNUqxupfip3t4v333uCll9/G47FvLMTu7VZQZGN+zzzMsZRd5y3f8UUsJWsHE7V2LK1/HMGGIZPAoj8GtNZ8OO09Jiz6jK59Ol30eKfeHVj1Y4IltZ3K7nZR2Dxooze7GetsKqXMn3xUzCmlLlpmeqQkv8DAAGKmj2fwc6+fN4JjisfjIaxJFNVrhBEa2pC6d9QxniG//xs6krq3hfPN9Dk8+u8Hjdf39/fj2ecf5x2bOrpOkJa2jQ8++Ix5879i9pwvWb9+EznZObZmsqtddOzQlgMHfiMpab2xmpdi53bLy78Ef3m6O6nvfnPRYxVb1+fYhl/5rsEA4tu+xJ1vP3xupLOwPd79SR5p/28G9/0Pf3u4Ow2a1j/32D+e7ENOdg6xM7+3pLZTOW1/Jq6PJZ1NpVS5C27lgQSl1E1KqXJXeN6jSqlEpVSix5NlRbRiJSM9k5urBp+7XzWkCpmZ+2zJ4u3tTcz08UybNovZsxdd/QkWOnr0GEuXriIyKsLWHHm+iZlL127tjdetXuMWqt16M8tWzWftxniCQ4L4afkcKlWqYDTH/v0HqRyUe0iwclBFDhz4zWj9SV/G0KJ5Z6Iie3H48BG2btthtP7lmG4XdzcPpVOndqSlrWTypLFERLQgOnq0sfp57NxuBVSrTMAtFWn9w3DauUfjV6Uc98QOw7diGW7pfQ97FroByNq5j5O7DlCydvBVXrFgDu7L/Qwc+e0ISxct546GtwHQoUckLe5txtCBwyyp62RO2p8VBm34P7tZNbJ5EPg53y0RCAF+OfvzJWmtx2mtQ7XWoS6XuSvtiip3YjK1alXn1ltvxsfHh549uzFvfqwtWcaPG0lq6lZGjR5nS/0KFcpRpkzuVc5+fn60aRNOmo0XQdTIdxFKh073smXzNuMZUjZu5i/Vm9KgbgQN6kawJ2Mv94R3Y//+g0ZzLFzwPX363AdAnz73sWD+EqP18w7bV60aTNeu7fkmZq7R+vnZ2S6GDBlBzVpNqFOnOQ/+YwDx8Svo1+8pY/Xz2LndOp66m8X1HmdJ2FMsCXuKPzIP8VPkK5w6cJTfM36jYst6APhWKE3JmlU4+ev+Qs/g5+9HQKD/uZ+b3BPK9rQdNI0Io88TvXnx4Vc59cepQq/rdE7an4nrZ9U8my8A9wLPa63XAyildmitq1tU7zxfTR7LPa3upkKFcuzcnsjQN98neuLXJko7KkNOTg5PPf0qCxdMxcvlYuKX00lJ2Ww0A0CL5mH07Xs/69enkOjO3Ti8OmQ4ixf/YCxDlaDKTJjwIV5eXrhcihkz5rNwoZlpPCZEjyK8ZVPKl7+JlLTlvDNsNJFREdSqXQOPx8PuXRk889QQy3N8Hv0hLc7m2JC2nOHDRvPVpIsPF1opeuJoWrZqRvnyN5G2ZSXD3hrFByM/ZdLkj/nHQz1J372HB/uandJkytRPKVfuJrLPZPPsM0M4cuSYkbpOaRdOY3K7ddenA6nQ/HZKlCtF5C8fkfret+yaFn/J3938wUwajX6M1j8OB6VIeWsapw8dL/RM5SrexNsT3gTA28uL2NlxrIl3M335ZHx8fRj19XsAbPwlhff+Y+YUGNmfiRulrDrnQSlVFfgQ2A28DqzVWte41ud7lwixf9xXnHPx2TL2uNR5O6b5+/jaHQEAlwPelTMee89vzOOEw0TeLuumwbkef2SftjsCOTZeYJTn23LWzYN5Pd712mt3BNYcSLM7gqNkn86wfeP5t2pdjW60Zv4619Z/s2UXCGmt07XWPYAfgSVAgFW1hBBCCCGEM1n+dZVa63lKqe+BmgBKqX5aa/u+mkIIIYQQwkbF7Up6I1Mfaa1/11pvOHt3qImaQgghhBDCfpaMbCql1l3uIaCyFTWFEEIIIf4MnDDRuklWHUavDEQBhy9YroCVFtUUQgghhBAOY1Vncz5QUmudfOEDSql4i2oKIYQQQjie/fM1mGVJZ1Nr3f8Kj/3dippCCCGEEMJ5LL8aXQghhBBC/I8T5gY2ycjV6EIIIYQQoniSkU0hhBBCCIOK29XoMrIphBBCCCEsIyObQgghhBAGFbdvEJLO5hXY+q31+SjllCT2c8K6cMpGwsvLy+4IjuHtgHXhlHZxygFbLvsTwLPZqXZHACB1wwy7IxAY0sruCAB4HPIZEeZJZ1MIIYQQwqDiNs+mnLMphBBCCCEsIyObQgghhBAGyTybQgghhBCi2FBKlVVKzVBKpSqlNiml7lZKlVNKLVFKbTn7/5sK+vrS2RRCCCGEKN5GA4u11rcBDYBNwH+AOK11bSDu7P0CkcPoQgghhBAGOWlSd6VUaaAV8DCA1vo0cFop1Q2IOPtrXwLxwIsFqSEjm0IIIYQQRZhS6lGlVGK+26P5Hq4BHACilVJJSqnPlVKBQGWtdSbA2f9XKmh9GdkUQgghhDDI9Ly8WutxwLjLPOwNNAYGaa3XKKVGcwOHzC9FRjaFEEIIIYqvdCBda73m7P0Z5HY+9ymlqgCc/f/+ghaQzqYQQgghhEEetNHblWit9wK7lVJ1zi5qC6QAc4GHzi57CJhT0H+vHEYXQgghhCjeBgFTlFIlgO1AP3IHJGOUUv2BXUCPgr64dDaFEEIIIQxy2qTuWutkIPQSD7UtjNcvkofRx48byZ70tSQnxdmWoWrVYJbEfsO6dfEkJ//AoIH9bcnh6+vLiuXzSXTHkpwUx2tDBhfLDHlcLhdrVi9i1sxoYzXHfjqCbTsTWO1edG5Z9792YI17MUeOb6VRozuN5Bg99m02bVvFstXzzy37PHoUPy6fw4/L5/DL+h/4cXmBj5Jck48+eYd9PI6AAAAgAElEQVTNO9awMmHhRY8NfLI/h09spVz5As8bfM1Gf/w2KVtXsnTVvHPL6t15G4u+n86Py2azJP5bGjW29n251PsB8M9/P8jqnxezfM0CXn/zeUszXKhMmdJMnfoZa9f+QHJyHE2bNjZaH+zbdpbwLcHM2EnMj/+aRcu/4akXHwPgwf69+CFhDtsO/sJN5coWet1Tp07T+59P8beHnqBbn3/z8eeTz3v87Q8+Iezev567n5i8nh79BtKgVSdif1xW6Hku5JTttxP266LgimRnc9KkGDp17mNrhuzsbF54YSj160cQHt6Fxx5/mNtvr208x6lTp4iM6kloWCShYVFERkbQpInZHYgTMuQZNLA/qWlbjdac8tUM/ta933nLUlI20+fvj7NieYKxHF9PmUmvv52/4/5nv6dpHd6N1uHdmD83lgXzYi3NMG3KTO7v/shFy0NCqhDRJpzduzIsrZ/n66kz6X3fP89b9tqbz/P+8LG0btmdEcNGW97Ru9T7Ed6yKR06tqXV3V0Ib9qJsWMmWJrhQiNHvsGSJfE0aNCGsLD2pKaa/ayAfdvO06dO0/ev/6ZzRG+6RDxAqzZ30/CuO/k5IZkH73uM9F17LKlbooQPX4wZzswvP2HGl2NZseZn1m7YBMCGTZs5diLrvN+vUrkSb70ymI7tWluS50JO2X47Yb9emDxaG73ZrUh2NpctX8Ohw0dszbB3736SkjcAcOJEFqmpWwgODrIlS1bWSQB8fLzx8fE2PuWCUzKEhATRoUMboqOnGa27coWbw4fOb4+b07axdcsOozlWrUzk8OGjl3282187MHPG/Ms+XhhWrnBz+BKfzWEjXuGNV0cYaxeXXBdaU6p0IAClSpdi794CX3hZ4AwP93+A0R+O4/TpMwAcPHjI0gz5lSpVkvDwJkRHfw3AmTNnOHr0mLH6eezcdp7M+h0Abx9vvM9up1LWp5GxO9OymkopAgL8gdyOdnZ2NkopcnJyGDl2AoOfOP8PkpAqlalTqzoupSzLdCEnbL+dsF8XBVckO5tOU61aVRo2qEdCQpIt9V0uF+6E78hIX0tc3DLcbvM5nJDh/ffe4KWX38bj8Riv7XR3Nw/lwP6DbN/2q/HaHTq2JXPPXjZsSDVeO79X/vM2r7/5Askb4xn61ou8NfQD4xlq1qrO3c1D+e6Hb5i78CvLD+XnV736LRw4cIjx40eyevVCPv10xLlOkF1MbztdLhfzfpxGwqbvWRG/hrW/bDBSNycnh/seGkCrzg9wd1gj6te9janfzqN1eDMqVihnJMOVOGH7XdRowze7SWfTYoGBAcRMH8/g517n+PETtmTweDyENYmieo0wQkMbUveOOld/UhHL0LFDWw4c+I2kpPVG6/5Z/O3+zsycscB4XX9/P559/nHeeWuU8doX6tf/AYa8/A4N60Yw5OV3GPXxMOMZvL29KFO2NFFtevD6kHf5fKK59eLt7U2jRvUYN24yzZp1JCvrd55//glj9S9kx7bT4/HQpfUDtKjfngaN6/KX22oaqevl5cW3X44lbtZk1qdsJjF5PbE/LuPv93c1Uv9q7N5+iz8/SzqbSqn2+X4uo5SaoJRap5SaqpSqfIXnnfs6JY8n63K/9qfh7e1NzPTxTJs2i9mzF139CRY7evQYS5euIjIqothluLt5KJ06tSMtbSWTJ40lIqIF0dGjjWZwKi8vLzp1jWTWTPOdzeo1bqHarTezbNV81m6MJzgkiJ+Wz6FSpQrGs/R64K/Mn5t7zuqcWYto3Li+8Qx79uxlwdkMST+vw6M15Q1cMAWQkZFJRkYmbncyALNmLaRhw3pGal/I7m3n8WMnWL3iZ1q1bW60bulSJQlrXJ+EX9axKz2Tjr0eIfK+h/jjj1N06Hnxuc6mOWEfUlQ4aZ5NE6wa2Xw7388jgUygC+AG/nu5J2mtx2mtQ7XWoS5XoEXRzBk/biSpqVsZNfpy3xBlvQoVylGmTGkA/Pz8aNMmnDTDF8g4IcOQISOoWasJdeo058F/DCA+fgX9+j1lNINT3dO6OVs3bydzzz7jtVM2buYv1ZvSoG4EDepGsCdjL/eEd2P//oPGs+zdu5/m4U0AaHlPM7Zv32k8w6L539PynmYA1Kx1KyV8fPjtt8NGau/bd4D09Exq164BwP+3d+9xUlR33sc/v7kAclEUlHuEgGE1ZgEFotwC6AMaEddETdyQ1ZgnPNloIlHjmniLMboxXhJ8YrKCeIuCIIooEjMEIYCCzAgDDDCIXNRBEC8IgsptfvtH1+AIMyBMV9Vh5vvm1S+6e3r6fPtUnZrTp05VDRjQm+XLVyZS9t7S2HYe06wpTY5sDED9BvXp3e/rrFq5NvZyP9j0IVuikdtPt29nXuFCTurciX8+N5aCpx6h4KlHaNCgPn+b8GDsWaoSwvZbDn9JnGezu7t3je7/wcwu2e+rs+Cxv97HN/qdTvPmx7B2dRG3/OYuHnr4ibiL/ZzevXowbNgFLFmyjKLCzEjFDTf+jhdeeDHRHK1atmDMmD+Qm5tLTo4xceIUpk5N9tQRIWRI04MPj6RP36/TrNnRLH/tJW7/7Ug2bfqQO+++mebNj+HJp8ewZPEyzj/v0lhzjHrwHnr36ckxzY5m8fJZ3HH7vTz+14mc/+1zYj8wqMIDD/2B3lFdlKyYw+9uG8ljjz6ZSNmV3T/m7j11sWjZP/n9f/9/rvrZjdx2x6/Izc1j+/btXHXlTbFmqHp5PMW9f76d2fOmsHPHTq748X/FmmFvP//5TTz88L3Uq5fPmjVvMnz4NYmWD+ltO49tcSx3/umWPdup5ydPY0bBbC750Xf50U8v4djjmvH8rPHM/MccfjXi1qyV++77m7j+t3exu7wcL3cGD+xL/95fr/b1S5avYMQvb2XLR1uZ+dIr3PfAY0x+vNoxnBoLZfsdwt/1bAphtDFJFsdRZWZWBtwDGHA50NGjgsxssbsfcP9UXr02qS+J5I712z9L8KjD0IVQF/Vz89OOAEC93PSvybA7kIOt8nJz046QyhG6Vdm649O0I7C7fHfaEfjSkdXO2EpUaenEtCPQqE2/tCMABHEKHoBdO9al/ofk9DYDEq2MuetmpPqZ49qNPhpoAjQGHgGaA5hZS6A4pjJFREREJDCxDI24+y3VPL/BzGbEUaaIiIjI4SCUPSFJSePUR1V2REVERESk9ollZNPMFlf3IyCMiTQiIiIiKahrBwjFdYRBC2AwsPc5Owx4OaYyRURERCQwcXU2pwCN3X2fg4HMbGZMZYqIiIgEzzWyWXPu/sP9/Ozf4yhTRERERMKT/on6REREROoQHY0uIiIiIpIlGtkUERERSVBdOxpdI5siIiIiEhuNbIqIiIgkqK7N2VRncz9CWRUs7QDUvYaxP5/s3J52BAA+DiBHCOsmhNNWJRxvbHkn7QgANGzdN+0IfK1Zh7QjALD4/TVpR5CUqLMpIiIikiDN2RQRERERyRKNbIqIiIgkqK5dQUgjmyIiIiISG3U2RURERCQ22o0uIiIikqDyOnaGF41sioiIiEhsNLIpIiIikiAdICQiIiIikiUa2RQRERFJkOZsioiIiIhkiUY2RURERBKkOZu1wOhRd/N22SKKF05PNcfgQf1ZWjKL0mVzuPYXl6eSoX79+rw0ZwpFhQUUL5zOTTdenXiGtm1bM63gSRYvnklx8Yv89IofJp4hhHqAMOoCwmgjodRFCO00hOUBYdRFKDlCWCZpt5GcnBzGFjzIyEfv+Nzz1/52BHNeL0g0C4SxXsihqZWdzUcfncA5Q76XaoacnBzuHXkbQ84dxte6DOA73/k3TjzxhMRzbN++nUGDL6J7j0F07zGYQYP607PnKYlm2LVrF9deewv/+q/96dPnXH78n5cmXhch1AOEURcQRhsJoS5CaachLI9Q6iKUHCEsk7TbyMU/upA1K9/43HMndulMk6MaJ5ahQijrRbaUuyd6S1ut7GzOnvMKH2z6MNUMPXt0Y9WqtaxZ8yY7d+5kwoTJDD13cCpZtm37GID8/Dzy8/PwhFe8DRs2srC4BICtW7dRWrqS1q1bJpoB0q8HCKcuQmgjIdRFKO00hOURSl2EkiOEZZJmGzmu1bH0PeN0nhn73J7ncnJyGHHj5Yy89S+JZKgslPVCDk2t7GyGoHWblrxV9vaex2Xr1qfSqYDMBqJw/t9ZV7aI6dNnU1i4MJUcAMcf35auXU5m/vzkM4RUD5BuXYQmrboIqZ2mLZS6CCVHaJJuI9f85meM/O1fKC//7Ev5dy77NrMK5vDexvcTyVBZbVsvPOF/aYuls2lmC8zsBjPrGMf7Hw7MbJ/n0hhJAygvL6dHz8F0+HIPunfvyldP6pxKjkaNGjJh/GiuvuZmPvpoa+Llh1IPkH5dhCTNugipnaYtlLoIJUdIkm4jfc/sxQfvfcjyxSv2PNe8RTPOPHcAT4x5Kvbyq6L14vAW19HoRwNNgRlmtgEYB4x397f390tmNhwYDmC5R5GT0yimePFbV7aedm1b73nctk0r1q9/J8VEsHnzFmbNmsugwf1ZumzFgX8hi/Ly8pgwfjTjxk3imWf+lmjZe0uzHiCsukhb2nURYjtNSyh1EUqOUKTRRrr0/BrfGNSbPmecRr369WjUpBETZz7Gjh07mDz3CQAaHNGAyS8/wXm9vptIptq2XoQwjzJJce1G3+Tu17j7l4CrgROABWY2I+pQVsndR7l7d3fvfjh3NAEKi4rp1KkD7du3Iz8/n4suOo/npiR/9F7z5sdw1FFHAtCgQQMGDuzDihWvJ55j9Ki7KS19nT+OHJV42RBOPUD6dRGStOsilHYaglDqIpQcoUijjfzp9vs5+9RvMaTnhfzyx7+maM6r9D/xbAZ1OY8hPS9kSM8L+fSTTxPraILWi8NdXJ3NPePd7j7b3X8CtAHuAE6Pqcw9HvvrfcyZ9Sydv9KRtauL+MGlyTWICrt37+bKETcw9fmxlCyeycSJz7Fs2WuJ52jVsgXTCibwatE05r48henTZzN1arKn8ujdqwfDhl3AgAG9KCosoKiwgLPOGphohhDqAcKoCwijjYRQF6G00xCWRyh1EUqOEJZJCG0kFKGsF9lS1+ZsWhxzHszsCXevUcvMq9cm/doJRE4Vc1WSFsrcmKrm7SQtlLoIIUX6SyMjhLoQqUoIbeRrzTqkHQGAxe+vSTsCALt2rEt9sXy5ebdEN1ur31uY6meOa2TzZTNrF9N7i4iIiMhhIq4DhG4FrjOzVWQODnrS3d+NqSwRERGRw4Z7edoREhXXyOZqoC2ZTuepwDIze8HMLjGzJjGVKSIiIiKBiWtk0z3TbS8ACswsHzgbuBi4Czg2pnJFREREglZex2aax9XZ/NxEVHffCTwLPGtmR8RUpoiIiIgEJq7O5neq+4G7fxJTmSIiIiLBC+WsJkmJZc6mux++J78SERERkayJa2RTRERERKpQ1+ZsxnU0uoiIiIiIRjZFREREkqQ5myIiIiIiWaKRTREREZEEldexkU11Ng8DdW2l3J8Qdj3kmB34RQkIIUUo62YIdRFGTUiFENYJCGO9WPz+mrQjANC0QaO0I0hK1NkUERERSZAH8TUkOZqzKSIiIiKx0cimiIiISIJCmBKWJI1sioiIiEhs1NkUERERkdhoN7qIiIhIgnS5ShERERGRLNHIpoiIiEiCdICQiIiIiEiWaGRTREREJEGhXH0tKRrZFBEREZHYaGRTREREJEGas1kLDB7Un6UlsyhdNodrf3F5KhlGj7qbt8sWUbxweirlh5YjhGUSQob69evz0pwpFBUWULxwOjfdeHWdzFAh7WXStm1rphU8yeLFMykufpGfXvHDxDNUSLsuQskQQo5Q1otQtt9p5Rh53+0sXzWX2fOm7HnugYf+yIw5k5kxZzILlrzIjDmTE80kh8ZC7V3n1WtzSMFycnJYvnQ2Z33zYsrK1jNv7lSGff8nLF++MtsR96tvn6+zdes2HnpoJF27nZFo2aHlCGGZZDNDjlmNsjRq1JBt2z4mLy+PmTMmcdXVNzN//oIavWdaGWoy7yiby+RQl0jLlsfRquVxLCwuoXHjRrzyygtccMFlh5ShJlvS2tZGQshRk1YaynoRwvY7mzmaNmh0UK8/vVd3tm37mPvu/z19Txuyz89/c9t1bNnyEXfdcd9Bve97W16r2UY8C45q3DHRztfmratS/cy1bmSzZ49urFq1ljVr3mTnzp1MmDCZoecOTjzH7Dmv8MGmDxMvN8QcISyTEDJU2LbtYwDy8/PIz89LZXdKCBlCWCYbNmxkYXEJAFu3bqO0dCWtW7dMNAOEURchZAglRyjrRQjb7zRzzH25iE2bNlf78/POP5unJ06p9ucSjlrX2WzdpiVvlb2953HZuvWpbCTkMyEskxAyVMjJyaFw/t9ZV7aI6dNnU1i4sE5mCGmZABx/fFu6djmZ+fPrZl2EkCGkHBXSXC+keqf36s67G99j9ao30o5ySNw90VvaYulsmlljM/uNmS01s81m9q6ZzTOzS+Mob6+y93kuhIquy0JYJiFkqFBeXk6PnoPp8OUedO/ela+e1LlOZghpmTRq1JAJ40dz9TU389FHWxMvP4S6CCFDSDkg/fVCqvetC4bw9MTn044hX1BcI5uPA6uBwcAtwL3A94EBZnZ7db9kZsPNrMjMisrLtx1SwevK1tOubes9j9u2acX69e8c0ntJdoSwTELIsLfNm7cwa9ZcBg3uXyczhLJM8vLymDB+NOPGTeKZZ/6WePkQRl2EkCGkHCGsF1K13Nxczhk6iElPH76dzXL3RG9pi6uz2d7dH3b3Mne/Bxjq7iuBHwDfqu6X3H2Uu3d39+45OQc3kbhCYVExnTp1oH37duTn53PRRefx3JSCQ/sUkhUhLJMQMgA0b34MRx11JAANGjRg4MA+rFjxep3LAOEsk9Gj7qa09HX+OHJU4mVXCKEuQsgQUo4Q1gup2jcG9OL111az/m0NJB0u4upsbjOzPgBmNhT4AMDdy6nZQYIHtHv3bq4ccQNTnx9LyeKZTJz4HMuWvRZnkVV67K/3MWfWs3T+SkfWri7iB5d+N/EMoeQIYZmEkAGgVcsWTCuYwKtF05j78hSmT5/N1KnJnk4khAwQxjLp3asHw4ZdwIABvSgqLKCosICzzhqYaAYIoy5CyBBKjlDWixC232nmGPXgPbzwj/F0OqEDi5fP4nvfvwCA8799zmF/YJAn/C9tsZz6yMy6AKOBrwAlwGXu/pqZHQtc7O73Hug9DvXURyJxq+mpj2qTEHbPQMzfYL+gMGpCKoSwToDWi8oO9tRHcQnh1EeNGrZPdNXY9vHaVD9zbOfZNLNOwPlAO2AnsBIY5+7Vn8egEnU2JVTqbH5Gnc3PhFETUiGEdQK0XlSmzuZn6lpnM66j0X8G/BmoD3QHjiDT6ZxrZv3jKFNERETkcFDXDhCK69roPwK6uvtuM7sHmOru/c3sfmAy0C2mckVEREQkIHF1NiveezeZ0c0mAO7+ppnlx1imiIiISNDq2vm/4+psPgAUmtk8oB9wB0B0gNAHMZUpIiIiIoGJ8wChrwInAiXuXnqwv68DhCRUOkDoMyHMBYIwDgYJoyakQgjrBGi9qEwHCH2mfoN2ia4a2z99K9XPHNtudHdfCiyN6/1FREREJHxxztkUERERkb3UtTmbcV1BSEREREREnU0RERGRJLl7orcDMbOzzGyFmb1uZtdl+/OqsykiIiJSR5lZLnAfcDZwEnCxmZ2UzTLU2RQRERFJkCd8O4CewOvuvtrddwBPAOdl43NWUGdTREREpO5qA7xV6XFZ9FzWBHs0+q4d62p8TigzG+7uo7KR53DOEEqOEDKEkiOEDKHkCCFDKDlCyBBKjhAyhJIjhAyh5AghQzZko49zMMxsODC80lOjKtVjVVmyerh8bR/ZHH7gl8QuhAwQRo4QMkAYOULIAGHkCCEDhJEjhAwQRo4QMkAYOULIAGHkCCHDYcfdR7l790q3yh32MqBdpcdtgbezWX5t72yKiIiISPUKgRPMrIOZ1QO+CzybzQKC3Y0uIiIiIvFy911mdgXwdyAXeDC6CmTW1PbOZgjzOkLIAGHkCCEDhJEjhAwQRo4QMkAYOULIAGHkCCEDhJEjhAwQRo4QMtQ67j4VmBrX+1tdu2SSiIiIiCRHczZFREREJDa1srNpZg+a2UYzK0kxQzszm2Fmy81sqZldmVKOBmY238wWRTluSSNHlCXXzBaa2ZSUyl9rZkvMrNjMitLIEOVoamYTzaw0Wj9OT7j8zlEdVNy2mNmIJDNUyvLzaL0sMbNxZtYghQxXRuUvTbIeqtpOmdkxZjbNzFZG/x+dQoY7o3VzsZlNMrOmcWbYT45bowzFZlZgZq3TyFHpZ9eYmZtZ86QzmNmvzWxdpTb7zZgzVLmNMLPxlZ5ba2bFMefYp22aWRczmxtty58zsyPjzCBZkvT1ORO6Bmg/4BSgJMUMrYBTovtNgNeAk1LIYUDj6H4+8ApwWkp1chUwFpiSUvlrgeZprROVcjwC/N/ofj2gaYpZcoENwPEplN0GWAMcET2eAFyacIaTgRKgIZk57P8ATkio7H22U8Dvgeui+9cBd6SQYRCQF92/I+4M+8lxZKX7PwP+J40c0fPtyBw88Ubc25Bq6uLXwDVxf/5q8lS5jQDuBm6Ksdwq2yaZI6e/Eb3mMuDWNOpFt4O71cqRTXefBXyQcob17r4guv8RsJwsn5H/C+Zwd98aPcyPbolP1DWztsA5wANJlx2S6Ft4P2AMgLvvcPcPU4x0BrDK3d9Iqfw84AgzyyPzRyWr53b7Ak4E5rn7x+6+C/gncH4SBVeznTqPzJcRov//LekM7l4Q1QXAPDLn3ItVNTm2VHrYiAS2W/v52/EH4NqUM6Rln22EmRlwETAuxnKra5udgVnRa6YB344xg2RJrexshsbM2gPdyIwqplF+brS7YyMwzd3TyPFHMhvr8hTKruBAgZm9Gl1NIQ1fBt4FHoqmFDxgZo1SygKZ86nF+QejWu6+DrgLeBNYD2x294KEY5QA/cysmZk1BL7J509unLQW7r4eMl9YgeNSzAKZkaO/pVW4md1mZm8B3wNuSinDUGCduy9Ko/xKroimFTwY9/SKvVS1jegLvOPuK2Mst7q2WQIMjV5zIem2V/mC1NmMmZk1Bp4CRuz1TT0x7r7b3buSGaHoaWYnJ1m+mQ0BNrr7q0mWW4Xe7n4KcDZwuZn1SyFDHpldZH9x927ANjK7SxMXnbx3KPBkSuUfTWYkrwPQGmhkZsOSzODuy8nsKp4GvAAsAnbt95fqCDO7nkxdPJ5WBne/3t3bRRmuSLr8qJNzPSl1dCv5C9AR6Ermi9ndSRS6n23ExcT8JXU/bfMyMtvvV8lMUdsRZw7JDnU2Y2Rm+WQ6mo+7+9Np54l2184Ezkq46N7AUDNbCzwBDDSzxxLOgLu/Hf2/EZgE9Ew6A5nLgpVVGl2eSKbzmYazgQXu/k5K5Z8JrHH3d919J/A00CvpEO4+xt1Pcfd+ZHZfxjlacyDvmFkrgOj/jWmEMLNLgCHA99w9hPPjjSWd3aUdyXwZWhRtv9oCC8ysZZIh3P2daNCgHBhNctuufbYR0ZSXbwHj4y68qrbp7qXuPsjdTyXT4V0Vdw6pOXU2YxLNaRkDLHf3e1LMcWzF0aRmdgSZP/ClSWZw91+6e1t3b09ml8yL7p7oCJaZNTKzJhX3yRwEkfjZCtx9A/CWmXWOnjoDWJZ0jkjsoxMH8CZwmpk1jNrLGWTmNifKzI6L/v8SmT+iadbJs8Al0f1LgMlJBzCzs4D/Aoa6+8dJl18pxwmVHg4l4e0WgLsvcffj3L19tP0qI3Pg54Ykc1R8AYmcT3Lbrqq2EWcCpe5eFnfhVbXNSs/lADcA/xN3Dqm5WnkFITMbB/QHmptZGXCzu49JOEZv4PvAkkqnh/iVZ87Sn6RWwCNmlkvmy8UEd0/l1EMpawFMyvRpyAPGuvsLKWX5KfB4tItqNfCDpANEuwf/D/D/ki67gru/YmYTgQVkdo8tJJ2rgzxlZs2AncDl7r4piUKr2k4BvwMmmNkPyXTGL0whwy+B+sC0qL3Mc/cfp5Djm9GXsnIyR4HHmqG6HEn/7aimLvqbWVcy887XkkC73c82Isl53vu0zeh0SJdHP38aeCihLFIDuoKQiIiIiMRGu9FFREREJDbqbIqIiIhIbNTZFBEREZHYqLMpIiIiIrFRZ1NEREREYqPOpogkwsx2m1mxmZWY2ZPRqVUO9b36m9mU6P5QM6v2Kkxm1tTMfnIIZfzazK451IwiIpKhzqaIJOUTd+/q7ieTucTc586baBkHvU1y92fd/Xf7eUlT4KA7myIikh3qbIpIGmYDncysvZktN7M/kzm5ezszG2Rmc81sQTQC2hgyV7Yxs1Izm0PmaiJEz19qZn+K7rcws0lmtii69SJzovSO0ajqndHrfmFmhWa22MxuqfRe15vZCjP7B9AZERGpMXU2RSRR0bWVzwaWRE91Bh51927ANjKXoDvT3U8BioCrzKwBmWtCnwv0Baq7NvW9wD/dvQuZa84vBa4DVkWjqr8ws0HACWSuL90VONXM+pnZqWSujtKNTGe2R5Y/uohInVQrL1cpIkE6otKlW2cDY4DWwBvuPi96/jTgJOCl6FKJ9YC5wL8Aa9x9JYCZPQYMr6KMgcB/ALj7bmCzmR2912sGRbeF0ePGZDqfTYBJFdcDN7Nna/RpRUQEUGdTRJLzibt3rfxE1KHcVvkpYJq7X7zX6yquC50NBvy3u9+/VxkjsliGiIhEtBtdREIyD+htZp0AzKyhmX0FKAU6mFnH6HUXV/P704H/jH4318yOBD4iM2pZ4e/AZZXmgrYxs+OAWcD5ZnaEmTUhs8teRERqSJ1NEQmGu78LXAqMM5ICrDIAAACUSURBVLPFZDqf/+Lun5LZbf58dIDQG9W8xZXAADNbArwKfNXd3yezW77EzO509wJgLDA3et1EoIm7LwDGA8XAU2R29YuISA2Zu/YaiYiIiEg8NLIpIiIiIrFRZ1NEREREYqPOpoiIiIjERp1NEREREYmNOpsiIiIiEht1NkVEREQkNupsioiIiEhs1NkUERERkdj8LyEEw/elBhtMAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 864x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# creating a confusion matrix \n",
    "svm_cm = confusion_matrix(y_test, svmclf.predict(X_test)) \n",
    "class_names = [1,2,3,4,5,6,7,8,9,10,12,13,14,15,77,99]\n",
    "fig, ax = plt.subplots(figsize=(12,10))\n",
    "sns.heatmap(svm_cm, annot=True, fmt='d', xticklabels=class_names, yticklabels=class_names)\n",
    "plt.ylabel('Actual')\n",
    "plt.xlabel('Predicted')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Logistic Regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "def LogRegClassifier():\n",
    "    lgc = LogisticRegression(penalty='l2', solver='lbfgs', multi_class='multinomial').fit(X_train, y_train)\n",
    "    acc_train = accuracy_score(y_train, lgc.predict(X_train))\n",
    "    acc_test = accuracy_score(y_test, lgc.predict(X_test))\n",
    "    print(\"Train Accuracy : \", acc_train)\n",
    "    #print(\"Validation Accuracy : \", accuracy_score(y_valid, clf.predict(X_valid)))\n",
    "    print(\"Test Accuracy : \", acc_test)\n",
    "    return acc_train, acc_test, lgc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Accuracy :  0.2433261736729058\n",
      "Test Accuracy :  0.2279885468861847\n",
      "Wall time: 1.01 s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\tejas\\Anaconda3\\lib\\site-packages\\sklearn\\linear_model\\logistic.py:758: ConvergenceWarning: lbfgs failed to converge. Increase the number of iterations.\n",
      "  \"of iterations.\", ConvergenceWarning)\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "lgc_train, lgc_test, lgcclf = LogRegClassifier()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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jMaZtjrs/8kfNHLXPWubkVIHAwEBatmzC5MkzbK0bVCiI4aMG8d47/Th+LIWRw3+g1p3NuLfeAyTtS+b9vt1szeO0Fi0ak5R8gLVrNziWIahQEMNGDeT97v05fiyFJzs+TK93Pia08r30fvdjBgz+wJYMw0cPpmf3ftmjmv0+GEj12xsx6cfpdOzcwe8ZcvL5fNQIbUrFSjUIrVGN22+/2db6buG2dstJ2hanK1iwAF27daHvBwMdqe+W/eGWHHnG8tl7cZi/RjafA+6yLKsd0BDoaYx5NfO+884bMMZ0NsZEG2Oifb6U8z3sghLiE6lQPjj7dvmQciQm7s/VuvJCs2YNiYnZSFLSAdtqer1eho8ayOQfpzMzYh4AB5J/x+fzYVkWY0b9SDU/HoziRnVqh9KqZVO2xq1gzOgvadSwLiPC7RvF83q9DBs5kCk/zmDW9Ix98tCjbZkZMReAiJ9+9usBQlkZvhs9mEkTIrLr5jT5x+m0atPErxnO58iRoyyOXE7Tpg0dqe80t7VbTtK2OF2l667l2orlWbZyBhtiIwkJKcuSZRFcXaaULfXdsj/ckkNyx1+dzQDLso4DWJa1m4wOZ3NjzGdcoLNpWdZQy7JqWJZVw+MplKvCUdEx3HBDJSpWrEBgYCDt27clYvqcXK0rL7Rv35YJE+z9Cv2zIR+wbetOvv1yZPaynA1Ti1b3ssXmyd1O69GzP9ddH8pNN9emwxNdWLhoGU8/84pt9Qd80YftW3cy9Kv/7ZP9iUnUrhsKQL0GYeza+atfM3w+5EO2xe3g2y9HZC+rdN212debNb+Hbdt2+TVDTqVKlciezlGgQAEa31OfuLgdttV3E7e1W07Stjhd7KY4rq9Ykyq3NaDKbQ1ISNhH/bqtSdpvzwCGW/aHW3LkGZ/P3ovD/HWezX3GmDsty4oBsCzruDGmFfAd4Nfhm/T0dF59rQczZ4wjwONhxMjxxMZu9WfJ8ypYsACNG9fnpZe621azZq3qPPRIW2I3xTF3yWQA+vUZyP0PtuD2yrdgYfHbngS6vdbLtkxjRn/J3Q1qU6pUCXbvjKZ3n08JH/GDbfWdFlqrOg9m7pM5kZMA6P/BQLq+1os+/d7G6/Xyxx9/+nWf1KxVnfaPtiN2Yxzzl0wB4KM+n/PYkw9yww0V8fks4n/bS9fX3/dbhjOVK1eG74YPJCDAg/F4mDgxgpkz59lWP4sbXp9uabe0Lf7HqW3x3YhB1KsfRsmSV7F56zI++nAQo0dN8Hvd83HL/nBLDskdv5z6yBhTHkizLGvfOe6ra1nWsoutI7enPspLeXXqo7/rUk595C9/59RHeenvnvooL1zqqY/85VJOfeQvf/fUR3nF8cZC5Dwu9dRH/vB3Tn10OXLFqY9WfG/vqY9qP+ro/9kvI5uWZcVf4L6LdjRFRERE5PKgn6sUERERsZML5lHa6bI7qbuIiIiIuIdGNkVERETspJFNEREREZG8oZFNERERERtZlvNnE7GTRjZFRERExG80sikiIiJiJ83ZFBERERHJGxrZFBEREbGTpZFNEREREZE8oc6miIiIiPiNvkYXERERsdMVdoCQOpsXkO5zx3mwiucr7HQEfj951OkIAFiW5XQEyhUo4XQEAH49keR0BJzfG3Im43QA9LrIKcDoC0QRdTZFRERE7KQDhERERERE8oZGNkVERETsdIXN2dTIpoiIiIj4jUY2RUREROykOZsiIiIiInlDI5siIiIidtKcTRERERGRvKGRTRERERE7aWRTRERERCRvaGRTRERExE46Gv2fr1nThmzaGMmW2KV069rFkQz58+dn+bLprImeS0zMAt57701b63s8HibNH83XYz4D4MPPezBl4Vh+WjSWgcP7EVSooK15sjKtXjWbKVNG2F67fPlg5s75kfXrFxETs4CXX+pka/1pqyfww4IRjJ37HaNmDzvtvg4vPEJ04hKKlSjmt/rBIWWZEjGKZatnsmTldDq/8CQAbdrdx5KV09l/aDNVq1X2W/1zGTZ0AHvj1xGzdr6tdc/khvbCDTmcfo/k5PS2cDLDF1/1Y+uuVSxfPTN72fCRg4hcPo3I5dNYt2kRkcun2ZYH3LE/3JRDLt1l19n0eDwMHtSXVq07UKVqIx5+uB233nqj7Tn+/PNPmjRtz101mlCjRlOaNW1IWM3qttV/ovMj7Ny6O/t2v56fc3+jx2nX8HESE/bzWMeHbMuS5eWXO7Fly3bb6wKkpaXRrVtv7rijIfXqteaFF5+2/XXx/IOv8niTjjx533PZy8oEX03Y3aEkxu/za+30tHTe79GfujVbcN+9D9Pxuce46ebr2Ry7lac7vMyKZVF+rX8uo0ZNoGWrx22vm5Nb2gs35HDDewTcsS2czPD92Mk82K7jacs6PfUqDeq0oUGdNkyb+jMR0+bYkgXcsT/clCPP+Hz2Xhzmt86mMaamMSY08/ptxpg3jDEt/FUvS83QauzYsZtdu/aQmprKhAlTadO6mb/LnlNKygkAAgO9BAYGYlmWLXXLlLuau++ty8SxU/+X5XhK9vUCBfLbkiOnkJByNG/emO/Cx9leG2DfviTWxmwE4PjxFLZs2UZwcFlHsuT0Ru+XGfzBV35/bezfn8z6dbFAxmtha9xOygWXYdvWnezYvsuvtc9nydJVHDx02JHaWdzSXrghh1veI27YFk5mWL4sikMXeF/c/0ALJv0YYUsWcMf+cFMOyR2/dDaNMe8Dg4GvjTH9gCFAYeBtY8y7/qiZJTikLL/F782+HZ+Q6FinwuPxEB01h70J65k3P5LVUWttqdv9w9f5tM8X+M74NNN3UE+WbJpFpRuuZcx/x9uSJcuAT3vRvXtffD57OtwXcu215bmzamVWr7ZnfwBYlsWXP3zG6J//y/0dWgPQoGldkvYlsy12h205ACpcE0KVO25lTfQ6W+u6kVvaC7fkyOLEeySLG7aFGzKcS526oSQlHWDnjl9tq+mWbeGWHJI7/hrZfBCoCzQAugDtLMvqAzQDHvZTTQCMMWcts2tE8Uw+n48aoU2pWKkGoTWqcfvtN/u9ZsMm9Th44BCx67ecdd+7r37A3VVasnPbbpq3beL3LFlatGhMUvIB1q7dYFvN8ylUKIgJ44fx5lvvc+zYcdvqdmrzbzo07cQrj73FQ08/QLVaVen46pN888lw2zJAxv8/fPRgenT/iOPHUi7+hMucW9oLt+QA594jWdywLdyQ4Vz+9VArJv043daabtkWbsmRZyyfvReH+auzmWZZVrplWSeAHZZlHQWwLOskcN7/tTGmszEm2hgT7fPl7g9hQnwiFcoHZ98uH1KOxMT9uVpXXjly5CiLI5fTtGlDv9eqVvMOGjWrz7zonxgwtC9h9Wrw8Ve9s+/3+XzM+mkuTVvd4/csWerUDqVVy6ZsjVvBmNFf0qhhXUaED7atfhav18uE8cP4/vsp/PTTLFtrH9j/OwCHfj/MolmRVK99J8HXlOP7+eFMWz2Bq8uVZuyc4ZQsXcJvGbxeL+GjBzNxQgQzIub6rc4/iVvaC7fkcPI9ksUN28INGc4UEBBAqzbNmDJphq113bIt3JJDcsdfnc1TxpigzOt3ZS00xhTjAp1Ny7KGWpZVw7KsGh5PoVwVjoqO4YYbKlGxYgUCAwNp374tEdPtm0ydpVSpEhQrVhSAAgUK0Pie+sTF+f/r0s/7fkWjO1tzb412vNn5XVYtjeY//36fayqVz35Mw2b12bl9t9+zZOnRsz/XXR/KTTfXpsMTXVi4aBlPP/OKbfWzDBs6gC1btjNw0FBb6xYoWCD76P8CBQsQdncosTGbaVqlDW1qtqdNzfYkJSbzeNNO/J580G85Bg7py9a4nXzz5Qi/1fincUt74ZYcTr1HcnLDtnBDhjM1bFSXbVt3snevfw8mPJNbtoVbcuSZK+wAIX+dZ7OBZVl/AljWaeO3gcBTfqoJQHp6Oq++1oOZM8YR4PEwYuR4YmO3+rPkOZUrV4bvhg8kIMCD8XiYODGCmTPn2Z4DMr5+6PfF+xQuXAhjDFtit9G768eOZHFK3TqhdOjwIBs2xBIdldFA9ejZn9mzF/i9dsnSV/F/330EQIA3gJ+nzGXFwtV+r5tTWK27ePjRdmzaGMfCJT8B0LfPZ+TLn49+n/SkZKkSjJvwLZs2bKb9A8/akmnM6C+5u0FtSpUqwe6d0fTu8ynhI36wpXYWt7QXbsjh5HskJzdsCycz/Df8c+rWD6NkyavYGLeU/n0HMWbUjzzwYEtbDwzK4ob94aYckjvGrXMevPlCHA929gwRZ9xQPMTpCOw4svfiD7KBG16vVUte53QEAH49keR0BA6dtH9On1yYG9ot59+l7lEkn/3nND7TsVMnnY7gKmmnEhx/m5yc/JGtb5OCD7zj6P/5sjvPpoiIiIi4h36uUkRERMROLphHaSeNbIqIiIiI32hkU0RERMROGtkUEREREckbGtkUERERsZMLzqxiJ41sioiIiIjfaGRTRERExE6asykiIiIikjc0sikiIiJiJ41sioiIiIjkDY1sioiIiNjJ0simiIiIiEie0MjmBeT35nM6AgCHTx13OoLkkO6ST6TF8xV2OgKHTuq16TZX1tn7zs84HSBTUGB+pyNwIu1PpyMAkH6FzVOU/1FnU0RERMROV1jHW1+ji4iIiIjfqLMpIiIiYifLsvdyAcaYAsaY1caYdcaYTcaY3pnLxxpj4owxG40x3xljAjOXG2PMYGPMdmPMemNM9Yv9d9XZFBEREbly/QncY1lWVeBO4D5jTC1gLHALUAUoCDyb+fjmwI2Zl87A1xcroDmbIiIiInZy0ZxNy7IsIOtoz8DMi2VZ1sysxxhjVgPlM2+2BUZlPm+lMaa4MaacZVmJ56uhkU0RERGRK5gxJsAYEwMkAXMty1qV475A4AlgduaiEOC3HE+Pz1x2XhrZFBEREbGTzSObxpjOZHzlnWWoZVlDs25YlpUO3GmMKQ5MMcZUtixrY+bdXwGRlmUtyVrdOUpccGKoOpsiIiIil7HMjuXQv/C4w8aYRcB9wEZjzPtAaeD5HA+LByrkuF0e2Huh9eprdBERERE7WT57LxdgjCmdOaKJMaYgcC+wxRjzLNAMeNSyTlvJNODJzKPSawFHLjRfEzSyKSIiInIlKweMNMYEkDEIOcGyrOnGmDTgV2CFMQZgsmVZfYCZQAtgO3ACeOZiBdTZFBEREbGR5XPPD8talrUeqHaO5efsI2Yehd7lUmpcll+jN2vakE0bI9kSu5RuXS9pe/wtX33zMbt2R7E6anb2svvvb0FU9M8cPb6DatWr+D1DcEhZJkaEE7kqgkUrpvHsCx2y7+vY+XGWRM1g0Ypp9Oj9pt+znMnj8bB61WymTBlhe+3y5YOZO+dH1q9fREzMAl5+qZOt9WdETWTCwlH8MG8EY38eDsC9rRsxcfEY1uxdwm1Vb/Fr/Xz58zHx55FMW/g9M5dM4JVuGdNvatcP5af5Y5m2cBzfTx/ONZXKX2RNeWfY0AHsjV9HzNr5ttU8F6faCzfmcEMGN7wu8ufPz/Jl01kTPZeYmAW895597WVwSFl+nBbOopXTWLB8Kp2ez2jDvx7+KXMiJzEnchIr181hTuQk2zIVK1aU78d9w/p1C1kXs4CwsIuew9sv3PD6lNy57EY2PR4Pgwf15b4WjxIfn8jKFTOJmD6HzZu3+b322NGT+PabUQwbNiB7WWxsHI89+iKDv+jr9/oAaWlp9O7xCRvWbaZQ4SB+XjSRyIUrKHV1SZq1uIfGddtx6lQqJUuVsCVPTi+/3IktW7ZTpGhh22unpaXRrVtv1sZspHDhQqxaNZt58yNteV1k6fyvlzl88Ej27R1bdvJmx3fo8X9d/V771J+nePKBFziRchKv18sP04cTOX8Zvf+vOy8+8QY7tu3msWceossbz/Kfl3v5PQ/AqFET+OqrcMLDB9lS71ycbC/clsMNGcAdr4s///yTJk3bk5JyAq/Xy+JFU/h59kJWrf7F77Wz2vCN6zPa8NkLfyRy0Qpe7PRW9mPe+6ArR48ev8Ba8taAAb2YM3cRjz72AoGBgQQFFbStdha3vD7zjIvOs2kH20Y2jTGj7KhTM7QaO3bTAowCAAAgAElEQVTsZteuPaSmpjJhwlTatG5mR2mWLVvNoYOHT1sWF7eDbdt22lIfIGn/ATas2wxAyvETbNu6k7Llruapjo8w5PP/cupUKgC/HzhoWyaAkJByNG/emO/Cx9laN8u+fUmsjck4i8Px4yls2bKN4OCyjmTJsmvbr/y6Y49t9U6knATAG+jFG+jN/BUzi8JFMjr/RYoWZv++ZNvyLFm6ioOHDl/8gX7kZHvhthxuyADueF0ApKScACAw0EtgYCDWRX7yL68k7T/AxvVnt+E5tb6/GVMnzbAlT5EihalfL4zw8B8ASE1N5ciRo7bUzsktr0/JHb90No0x0864RAAPZN32R80swSFl+S3+f0fgxyckOt6pcEr5a4KpUuVWflmznutuqEhYnbuYMe8HJs8YSdVqlW3NMuDTXnTv3hefC+apXHttee6sWpnVq9faVtOyLL764XPG/jycBzq0sa1uTh6Ph2kLx7Fy81yWLVrJul828u7rHzDs+0EsWTeTdg+1YOigEY5kc4pb2gs35HBDBjfxeDxER81hb8J65s2PZHWUfe1FlvIVgql8x62sXbM+e1lYnbtITvqdXTvt+aBaqdI1JCcfZNiwz1i1chZff/2JIyObl93r00VHo9vBXyOb5YGjwGfAgMzLsRzX/SbziKnT2PWJ1E2CCgUxfNQg3nunH8ePpeANCKBY8aK0vPcR+vT8lKEjPrMtS4sWjUlKPsDatRtsq3k+hQoFMWH8MN58632OHbPva6hnWr/IY0078tLjb/LwMw9QvVZV22pn8fl8tGn0GPXvaM4d1Stz4y3X88zzj/Pco69Sv2oLJn0/je4fvGF7Lie5pb1wQw43ZHATn89HjdCmVKxUg9Aa1bj99pttrR9UKIhhowbyfvf+HD+Wkr283b9aMHXSzAs8M295vV6qVavM0KGjCKvVnBMpJ+jqwHxJvT7/2fzV2awBrAHeJeP8S4uAk5ZlLbYsa/H5nmSM6WyMiTbGRPt8Ked72AUlxCdSoXxw9u3yIeVITNyfq3X9U3m9XoaPGsjkH6czM2IeAIl79zEzYi4AMb9swOfzUbLkVbbkqVM7lFYtm7I1bgVjRn9Jo4Z1GRE+2JbaOXm9XiaMH8b330/hp59m2Vo7ef8BAA4dOMyCWZHcXu02W+vndOzocVYti+buxnW45fabWPdLxvSCGT/NpXroHY7lcoJb2gs35HBDBjc6cuQoiyOX07RpQ9tqer1eho0cyJQfZzBr+rzs5QEBATRvdS/Tpsy+wLPzVkJCIvEJiURFxQAwecpMqt1p7zdjoNfnP51fOpuWZfksy/qcjHMvvWuMGcJfOBjJsqyhlmXVsCyrhsdTKFe1o6JjuOGGSlSsWIHAwEDat29LxPQ5uVrXP9VnQz5g29adfPvlyOxls2csoF6DMACuu/5aAgMD+f33Q7bk6dGzP9ddH8pNN9emwxNdWLhoGU8/84ottXMaNnQAW7ZsZ+Cgi/6IQp4qEFSAoEJB2ddr312THVvsm8cLUKJk8ewDs/IXyE+du8PYsXU3hYsWpuJ11wBQt2EYO7btsjWX09zSXrghhxsyuEWpUiUoVqwoAAUKFKDxPfWJi9thW/0BX/Rh+9adDP1q5GnL6zeszfZtu0jca18na//+ZOLjE7npxusAaNSoriMH5Vx2r0+fZe/FYX49Gt2yrHjgIWNMSzK+Vve79PR0Xn2tBzNnjCPA42HEyPHExm61ozThIwZRv0EtSpa8irhty+n74UAOHTrMpwN6UapUCSZN+o7162Np1/Ypv2WoWas6Dz3SlthNccxdMhmAfn0G8v2YyXw+5EMWLp9Kamoqr/77Hb9lcKO6dULp0OFBNmyIJToqo4Hq0bM/s2cv8HvtkqVK8Fn4RwAEeL3MmjyH5QtX0ah5A/7T93WuKlmcwWP+j7iN2+jyqH++xi5dphSfDOmNxxOAx2OYNXUeC+cuoccbHzIk/P/w+XwcPXKU7q/28Uv9cxkz+kvublCbUqVKsHtnNL37fEr4iB9sqw/Othduy+GGDOCO10W5cmX4bvhAAgI8GI+HiRMjmDlz3sWfmAdCa1Xnwcw2POv0Rv0/GMiCuUto+0BzW79Cz/L66z0ZMeIL8uULZNeuPTzX2f5T57nl9Sm5Y9w658GbL8TxYAW8+ZyOAECRfPZPxj7T7yftP/rwXNzweq1coqLTEQA4nv6H0xHYdWSf0xFEzunsGX7OuLpQcacjcMAl7Xe6S073k3YqwfGXx4kv/m3rH7Ogl79y9P98WZ7UXURERETc4bI7qbuIiIiIq7lklNcuGtkUEREREb/RyKaIiIiInVxw/IGdNLIpIiIiIn6jkU0RERERO2nOpoiIiIhI3tDIpoiIiIidXPCrPnbSyKaIiIiI+I1GNkVERETsZGnOpoiIiIhIntDIpoiIiIidNGdTRERERCRvaGTzAv5IO+V0BAACPQFOR8Byya8deDzOfz4qHVjE6QgAJP152OkIBAa4owlJTU9zOoK4jDtaLMjncf49kn6FndNR3Mf5d4GIiIjIFcS6wj4AOD9MJCIiIiKXLY1sioiIiNhJBwiJiIiIiOQNjWyKiIiI2EkndRcRERERyRsa2RQRERGxk+ZsioiIiIjkDY1sioiIiNhJ59kUEREREckbGtkUERERsZPmbP7zNWvakE0bI9kSu5RuXbtccTm++KofW3etYvnqmdnLho8cROTyaUQun8a6TYuIXD7Ntjz58+dn+bLprImeS0zMAt57703baucUF7ecNdFzWb1qNsuXzbCtbvnryvP17C+zL1NiJ3F/p3Y89+6zDF84jG/mfM37w3pSqGghv2UIDinLj9PCWbRyGguWT6XT8x0AuL3yLUTMGcecyEnMXDCeO6tX8VuGc+nS5Rmio+ewZs1cXnqpo621s1zp7YXbMrglh1MZ8uXPx09zxzJz8QR+XjaZ1/7z4mn39+r/Nht/XWFbHnDH/nBTDrl0xrLc2bv25gvJVTCPx8PmTUu4r8WjxMcnsnLFTDo88W82b96W1xFty1EkX8FLenyduqEcP36Cb4b9H3Vqtjjr/g8+6s7Ro8f4v/5D/vI6j586eUkZzlSoUBApKSfwer0sXjSFN954n1Wrf7nk9Xg8uf98FBe3nDp1WvL774dyvQ6Au0vfnuvnejwexkWN4ZU2r1Hh+vKsXRaDL91Hp+4ZHa3h/b77y+vadPy3v/zYq8uU4uoypdm4fjOFCgcxe+GPdOzwCr0/+g/Dvh7FwnlLuadJfV58pSMPtX7mL6/34B/H//Jjz3TbbTcxatQQ6tdvw6lTqUybNopXXnmXHTt2X/K6UtPTcpXhcmwv/skZ3JIjLzNUKFLqkp8TVKggJ1JO4vV6+XHmCHq/8zEx0RuocudtPPP84zRtcQ+Vr639l9f327EDl5whixv2R17nSDuVYPwQ8ZKk9Gxva+er0AcTHP0/2zKyaYypZ4x5wxjT1N+1aoZWY8eO3ezatYfU1FQmTJhKm9bN/F3WVTmWL4vi0KHD573//gdaMOnHCFuyZElJOQFAYKCXwMBA3Pohx9+q1buTxF8TSUpIYk3kL/jSMyaJb1m7hdLlLv2P0l+VtP8AG9dvBiDl+Am2bd1J2XJXY1lQpEhhAIoULcL+fcl+y3CmW265gdWr13Ly5B+kp6ezZMkq2ra1972q9sJdGdySw+kMJ1IyPtx7A714vV6wMjpb3Xu9Qb9en9uWA5zfFm7LIbnjl86mMWZ1juvPAUOAIsD7xpi3/VEzS3BIWX6L35t9Oz4hkeDgsv4s6eocZ6pTN5SkpAPs3PGrrXU9Hg/RUXPYm7CeefMjWR211tb6AFgWM6aPZcXyGXTq9Jj99YG729zNwqmLzlrerH1TohZG25KhfIVgKt9xK2vXrOf9d/rTo89bRG2cR88+b9Gvj31/yDZt2kq9ejUpUaI4BQsW4L77GlG+fLBt9cE971M35HBDBrfkcDqDx+NhxqLxRG9ZyNLFK4lZs4Enn32EebMXkbw/96OUueH0tnBbjjzjs+y9OMxfI5uBOa53BppYltUbaAo87qeaABhz9kixE6Nobslxpn891IpJP063va7P56NGaFMqVqpBaI1q3H77zbZnaNjoAWrVbkGbtk/ywvNPUa9emK31vYFeajepReSMJactf/TlR0hPT2f+lAV+zxBUKIhhowbyfvf+HD+WwpMdH6bXOx8TWvleer/7MQMGf+D3DFni4rYzYMA3TJ8+lmnTRrF+fSxpabn7Ojy33PI+dUMON2RwSw6nM/h8Plo2fJjaVZpStVplatauTou2TRk57HvbMmRxelu4LYfkjr86mx5jzFXGmJJkzAtNBrAsKwU4718TY0xnY0y0MSba50vJVeGE+EQq5BgdKR9SjsTE/bla19/hlhw5BQQE0KpNM6ZMsu/gmDMdOXKUxZHLadq0oe21s7Z/cvLvTJ02m9Aad9paP7RRDbZv3M7hA/+b4tDkwXsJaxxG/5c/8Xt9r9fLsJEDmfLjDGZNnwfAQ4+2ZWbEXAAifvrZ9gOERo4cT506LWnSpD2HDh1m+/bdttZ3y/vUDTnckMEtOdyQAeDY0WOsXBZFrXqhVKxUgUXRESxZO5OCQQVYGGXPVCi3bAu35JDc8VdnsxiwBogGShhjygIYYwoD552kalnWUMuyaliWVcPjyd2RuVHRMdxwQyUqVqxAYGAg7du3JWL6nFyt6+9wS46cGjaqy7atO9m7d5+tdUuVKkGxYkUBKFCgAI3vqU9c3A5bMwQFFaRw4ULZ1+9t3IBNm+JszdCobcPTvkKv0fAu2r/4EO937MWff/zp9/oDvujD9q07GfrVyOxl+xOTqF03FIB6DcLYtdPe6RWlS5cEoEKFYNq2vY8JE6baWt8t71M35HBDBrfkcDJDiZJXUaRoEQDyF8hPvbtrsXHdZmre1pj61VpQv1oLTp74g0ahrW3J44b94aYcecXy+Wy9OM0v59m0LKviee7yAff7o2aW9PR0Xn2tBzNnjCPA42HEyPHExm71Z0nX5fhv+OfUrR9GyZJXsTFuKf37DmLMqB954MGWth8YBFCuXBm+Gz6QgAAPxuNh4sQIZs6cZ2uGMmVKM2H8MAC83gB+GD+VOXMX2VY/f4H8VK9fnYFvD85e1uWDLuTLF0j/cR8BsPmXLQx+5wu/1A+tVZ0HH2lL7KY45kROAqD/BwPp+lov+vR7G6/Xyx9//Em313r5pf75fP/9N5QocRWpqam89tp7HD581Nb6ai/clcEtOZzMcHWZUnz65YfZ7eWMn+awYE6kLbXPxQ37w005JHcuu1MfXY4u9dRH/vB3T32UV/7OqY/yyt859VFeupRTH/nL3zn1UV7K7amPRPwtN6c+ymt/59RHlyM3nPro+H8esLWPU/jjyZf/qY9ERERE5Mqkn6sUERERsZMLTkdkJ41sioiIiIjfaGRTRERExE6W80eI20kjmyIiIiLiNxrZFBEREbGT5myKiIiIiOQNjWyKiIiI2MjSyKaIiIiISN7QyKaIiIiInTSyKSIiIiKSNzSyKSIiImInn86zKSIiIiKSJzSy+Q+QL8D53eTxuONzicE4HYH8xvn9AXBjoXJOR2Bt6i6nIwCQmp7mdARxmQCXtFl1C1/vdAR+OHbA6QhyhXPHX00RERGRK4UOEBIRERERyRsa2RQRERGxk0Y2RURERETyhkY2RURERGxkWRrZFBERERHJExrZFBEREbGT5myKiIiIiOQNjWyKiIiI2EkjmyIiIiIieUMjmyIiIiI2sjSy+c/XrGlDNm2MZEvsUrp17eJIhmFDB7A3fh0xa+fbWjc4pCyTI0ayZPUMFq+M4LkXngDgvQ+6sjRqJguXTSV8zBcULVbE1lzFihXl+3HfsH7dQtbFLCAsrLqt9W+88TpWrZqVfUlK2sRLL3WyrX7bTm35ct6XDJn7JW990ZXA/IG0fKoV30YOJWLPdIpeVdTvGQoXLUTvb99j1KLvGLlwOLdVv5X3vurBf3/+hv/+/A0/rBjDf3/+xq8ZhnzVn+27VrNi9azsZW+/8wqbty5jyfIIliyPoEnThn7NcCY3tBduyeFUu3UmN2wLp9qsZs+0pN+cgfSfO5BmHVuddl+Lzm0Z8+tkCl9lb/vthv3hphxy6S67zqbH42HwoL60at2BKlUb8fDD7bj11httzzFq1ARatnrc9rppaem83+Nj6tdsSYt7H+GZ5x7nppuvZ/HC5dxdqzWN6rZlx47dvPJGZ1tzDRjQizlzF3FH1UbUCG3Gli3bba2/bdtOwsKaExbWnNq1W3LixEmmTZttS+0SZUrS+pnWvN7ydV5q0oWAAA8NWjdgc3QsPR/rwf7f9tuS46XeXVi9KIonG3akU9Pn2bN9D33+/SHPNnuBZ5u9wOKZS4ictdSvGcaNncS/2j1z1vKvhoRTv05r6tdpzdw5i/yaISe3tBduyeFUu5WTW7aFE21W+ZuuoeGjTXi/TTfeue8NqjW+izIVywFQolxJKte7gwPxyX7PkZNb9odbcuQZn2XvxWF+6WwaY8KMMUUzrxc0xvQ2xkQYYz42xhTzR80sNUOrsWPHbnbt2kNqaioTJkylTetm/ix5TkuWruLgocO2103an8yGdbEApBxPYVvcDsoGl2HxgmWkp6cDsCZqHcHBZW3LVKRIYerXCyM8/AcAUlNTOXLkqG31z3TPPXXZtWsPe/Yk2FbT4w0gX4F8eAI85C+Yn4P7D7Jz006S4pNsqR9UOIiqYVWY8X3GiGJaahrHj6ac9phGre9m/tSFfs2xfFkUhxx4X5yPW9oLt+Rwqt3KyQ3bwqk2K/iGEHas3cqpP07hS/exZVUsNZqFAdDhvY780G+07ScDd8P+cFMOyR1/jWx+B5zIvD4IKAZ8nLks3E81gYyvkX+L35t9Oz4h0daOlZtUuCaEynfcyi/R605b/liHfzF/bqRtOSpVuobk5IMMG/YZq1bO4uuvPyEoqKBt9c/00ENtGD9+qm31Du7/nSlDp/DdynBGRY8m5egJ1i5Za1t9gOBrynH44BHe/qwrw2Z/Q9f/e4MCBQtk339HWBUOJR8iYZd9HfCcnnv+CZatnMGQr/pTvLj/pxRkcUt74ZYcbuCGbeFUmxW/dQ8317yNwsULk69APqo2qk7J4FJUvzeUQ/t+Z8/m3X7PcCY37A835cgzPpsvDvNXZ9NjWVZa5vUalmW9ZlnWUsuyegPX+akmAMaYs5ZdaT8LBRBUKIjhowfTs3s/jh/73wjWa289T1paGpMmRNiWxev1Uq1aZYYOHUVYreacSDlBV4fm2wQGBtKyZRMmT55hW81CxQoR1iSMZ+t24qnQJykQlJ+G9ze0rT5AgDeAmyrfyNTRETx33wucPPEHj3V5JPv+xm3v8fuo5vkM/+9Y7qzSiHq1W7F/fzIffvSObbXd0l64JYcbuGFbONVm7d2ewPRvpvD22F50G9WTPbG7SU9Lp81L/2LiZz/4vf65uGF/uCmH5I6/OpsbjTFZE7PWGWNqABhjbgJSz/ckY0xnY0y0MSba50s538MuKCE+kQrlg7Nvlw8pR2KiPXPi3MLr9fLd6MFMmhDBzIi52cvbP9qOJs0a8e/nutqaJyEhkfiERKKiYgCYPGUm1e6sbGuGLM2aNSQmZiNJSQdsq3lnvTvZ/9t+jh48SnpaOstnr+DWu261rT5AcmIyyYnJbF67BYDFMyK5sUrGfKeAAA/1m9djYcQiWzNlZ0v6HZ/Ph2VZjAz/gbtqVLWttlvaC7fkcAM3bAsn26zF4+fTo+VbfNi+JymHj3MgPonSFcrw0azP+HzpN5QoV5IPZ3xKsdLFbcnjhv3hphySO/7qbD4L3G2M2QHcBqwwxuwEhmXed06WZQ21LKuGZVk1PJ5CuSocFR3DDTdUomLFCgQGBtK+fVsips/J1br+qT4f8iHb4nbw7Zcjspc1alyPl157licfeZGTJ/+wNc/+/cnExydy040Zg9qNGtVl8+ZttmbI0r59WyZMsO8rdIDkhGRuqX4z+QvkB6Bq3ar8tv03WzMcTD5E0t5kKlxXHoC76lXn122/Zlyvfxd7duwhOdG+DnhOZcqUzr7eqnVTNsduta22W9oLt+RwAzdsCyfbrKIlMw5rKBlcihr3hbFk0iK63PUMr9d7gdfrvcDBxN/p0fItjiTbM7fWDfvDTTnyiuWzbL04zS/n2bQs6wjwtDGmCBlfm3uBeMuy/P4xJD09nVdf68HMGeMI8HgYMXI8sTb+8coyZvSX3N2gNqVKlWD3zmh69/mU8BH+/xqkZq3qtH+0HbEb45i/ZAoAH/X5nL6fvEu+fPmY8NN3AKyJXke313v5PU+W11/vyYgRX5AvXyC7du3huc5v2lY7S8GCBWjcuD4vvdTd1rpbY7aybOYyBs4cSHq6j52bdjB73GxaP9OaB174F1eVvorBc75gzYJovvjPF37LMbjnEHp80R1vvkASf02k/5v/B8A9bRqy4Cd7vkIfHj6QevXDKFnyKmLjltKv7yDq1Q+jyh23YVkWe36N57VXetiSBdzTXrglh1PtVk5u2RZOtVmvftOVwlcVIS01nZHvDePE0dx9y5dX3LI/3JJDcse4dc6DN1+IO4M5oGRBe8+pdi6H/3S2wctiOHvejt2aXH2H0xEAOOazd4T6XNYe3uV0BABSTjm/LcRdAjzuOLPfQ2VCnY7AD4mrnI7gKmmnEhz/Q3L40Ua29nGKf7/Q0f+zO96NIiIiInJZ0s9VioiIiNjJBacjspNGNkVERETEbzSyKSIiImIjNxwhbieNbIqIiIiI32hkU0RERMROmrMpIiIiIpI3NLIpIiIiYiPN2RQRERERySMa2RQRERGxk+ZsioiIiIjkDY1sioiIiNjI0simiIiIiEje0MjmBRinA2Q6nvqH0xFcw+eCj4M7/0x2OgIAJbyFnY5AoCfA6QiAO96rbjm2VNsiQ7rP+bYCoKjRn1kRvQtERERE7OSOz0K20dfoIiIiIuI3GtkUERERsZELZoTZSiObIiIiIuI3GtkUERERsZNGNkVERERE8oZGNkVERERspDmbIiIiIiJ5RCObIiIiIjbSyKaIiIiIXBGMMRWMMQuNMZuNMZuMMa+ecf9bxhjLGFMq87Yxxgw2xmw3xqw3xlS/WA2NbIqIiIjYyGUjm2nAm5Zl/WKMKQKsMcbMtSwr1hhTAWgC7Mnx+ObAjZmXMODrzH/P67Ic2WzWtCGbNkayJXYp3bp2cSRD/vz5Wb5sOmui5xITs4D33nvTttpff/MJu3dHExX1c/ayq64qRkTEaNatX0hExGiKFy9qWx6AYsWK8v24b1i/biHrYhYQFnbRD0J+4fF4WL1qNlOmjLC97sR5o/hyzAAA+g7qyc9RU5g0fzST5o/mlttv9HuGwkUL8cHQ9xmzOJzRi77j9rtuy77vkecfYknCfIpd5d/XRXBIWX6aPorlUbNYumoGnV98EoDiVxVj4k/hrF47h4k/hVPMptdn+fLBzJ3zI+vXLyImZgEvv9TJlrrn4nS7pW1xumFDB7A3fh0xa+f7vVaHT17k4+hh9Pj50+xlQcUK8fLoHvRaOIiXR/egYNFCABQsWojO377Fu7P+j24/fUS5myr4PZ8b9oebclxuLMtKtCzrl8zrx4DNQEjm3Z8D3QArx1PaAqOsDCuB4saYcheqcdl1Nj0eD4MH9aVV6w5UqdqIhx9ux623+v8P+Zn+/PNPmjRtz101mlCjRlOaNW1IWE17OlhjRk+kXbunTlv25psvsmjRcqre0YhFi5bz5pv/tiVLlgEDejFn7iLuqNqIGqHN2LJlu631s7z8cidHaj/x3MPs3Lb7tGUDen/Bvxo/wb8aP8GWTdv8nuGVPi+xamEUHe5+hmeadObXbb8CcHVwaUIb3MW++P1+z5Cels577/anTmhz7mvcnk7PPc5NN1/Pq693JnLxCmpWa0rk4hW8+npnv2cBSEtLo1u33txxR0Pq1WvNCy8+7Uh74YZ2S9vidKNGTaBlq8dtqbVy4iKGPPXRacuavdiOuOUb6NXoVeKWb6DZv9sBcF+X+4mP3U3f5l0Z+eYQHnr/ab9mc8v+cEuOPGMZey9/kTGmIlANWGWMaQMkWJa17oyHhQC/5bgdz/86p+fkl86mMeaVzKFX29UMrcaOHbvZtWsPqampTJgwlTatmzkRhZSUEwAEBnoJDAzEsqyLPCNvLFu2moMHj5y2rGWrJowdOxGAsWMn0qp1E1uyABQpUpj69cIID/8BgNTUVI4cOWpb/SwhIeVo3rwx34WPs7VumXJX06BJXSaNnWpr3ZyCCgdRNawK07+fCUBaahrHj6YA8HKvf/NV36G2vD73709m/bpYAI4fT2Fr3A7KBZehecvGjB83BYDx46bQotW9fs8CsG9fEmtjNmbn2bJlG8HBZW2pnZMb2i1ti9MtWbqKg4cO21Jr++rNpBw5ftqyO5qEsnLiYgBWTlxM1SahAJS7sTxxyzYAsH/HXkqWL02RUsX8ls0t+8MtOf6pjDGdjTHROS5nfaI3xhQGJgGvkfHV+rvAe+da3TmWXfAPiL9GNj8go1e8xBjzb2NMaT/VOUtwSFl+i9+bfTs+IdGRBhMyPolFR81hb8J65s2PZHXUWkdyAFx9dWn27UsGYN++ZEqXLmVb7UqVriE5+SDDhn3GqpWz+PrrTwgKKmhb/SwDPu1F9+598fns6fRnefuD1xnQZ8hZdV/p/gKTF47hP31eIzBfoF8zBF9bjsO/H+Gdz7sx/Odv+M//vUmBggWo26Q2yYkH2BG706/1z6XCNSFUueM21kSvo3TpUuzfn/H63L8/mVKlStqe59pry3Nn1cqsXm3/+9RN7RZoW7hBkdLFOJqc0dk9mnyYIqUyppbEb/6VO+/LmB53bdXrKRFSmuJlS/gth1v2h1ty5BXLZ/PFshwpFI8AACAASURBVIZallUjx2VozjzGmEAyOppjLcuaDFwPVALWGWN2A+WBX4wxZckYycw5oFge2MsF+KuzuTOz+AfAXUCsMWa2MeapzMmnfmPM2R1uu0YUz+Tz+agR2pSKlWoQWqMat99+syM5nOb1eqlWrTJDh44irFZzTqScoKvN821atGhMUvIB1q7dYGvdu5vU5eCBg8Su33La8s/7fkWruu15uNkzFCtelGdfetKvOQICAripyo38NGoanZq9wMkTf9DxzSd58pXHGf7pCL/WPpdChYIYMfoL3n37I44fS7G9/rnyTBg/jDffep9jx45f/Al5zE3tlraFu835+ieCihWi+8xPaPhUc+I37cKX7r+jTdyyP9yS43JkMjbucGCzZVmfAViWtcGyrKsty6poWVZFMjqY1S3L2gdMA57MPCq9FnDEsqzEC9XwV2fTsizLZ1nWHMuyOgHBwFfAfWR0RM8p5zCvz5e7P0AJ8YlUKB+cfbt8SDkSE/0/F+1Cjhw5yuLI5TRt2tCxDElJyZQtmzHAXLZsaZKTD9hWOyEhkfiERKKiYgCYPGUm1e6sbFt9gDq1Q2nVsilb41YwZvSXNGpYlxHhg/1et1rNqjRs1oA5UVP49NsPCatbg/5f9uJA0u8ApJ5KZcoP06lc/baLrOnvSU5MJjkxmdi1GZ3eRTMiuanKjZS7pizhc4cyYeVYSpcrzfCfv6FE6av8msXr9RI+5gsmTohgRsScjHzJByhTJuP1WaZMaQ4c+N2vGc7MM2H8ML7/fgo//TTLtro5uaXd0rZwj2PJRyhaujgARUsX59iBjKlHfxw/yeiuX/8/e/ceZ1PV+HH8s87MuI1brmOGJyE9XaWMO7kUkagn6aaLdFfp/nv0UFFKRSG6UA0pRSG3yYOQ+63chyH0aBi3UhjlMmf9/hjjkQeZy957NfN9e53Xa84+5+z1tfbe56yz9trr8ErrZxj+xCCKli7OTz/u9CyHK9vDlRx5VAPgdqCZMWb50Vvr0zw/kYy23PfAUOBPLwLxqrH5h68g1trD1toJ1tpbgL+d6kXHd/OGQtHZKnjJ0uVUq3YOlStXIioqig4d2jFx0tRsrSsnypQpRYkSGac9ChUqRPNmjUhO3uh7jkyJk6dz223tAbjttvZMnjTNt7J37NhFSkoq1c+tAkDTpg1Yu9b7C2KO171HH6pUjaf6efXoeHsXZs6ax12dHvW83P6936Z5zWtpEX89T93fnUXzlvLPLi9Qptx/TxM3b3UF36/zdt/4edcedm7bRaWqFQG4vGFN1q/aQNsa7elQ9zY61L2NXam76NzyAX7etcfTLAMGv8z65I28Mzjh2LIpiTO46dbrAbjp1uv5arL3VwBnGjqkH+vWfU//AUP+/MkeceV9S3XhjpXTl1K3/RUA1G1/BSunLQGgcPEiRERFANDg5uZ8v2gtv+//zbMcrmwPV3LkFhs2vt5Om8XaudZaY629xFp76dFb4gnPqWyt3X30b2ut7WKtrWqtvdhau/TP/r9ezbN506kesNZ6d1QA6enpdH2sO4mTRxIRCjFs+CiSktZ7WeRJVahQng8/6E9ERAgTCvHFFxNJTJzuS9nDhg2kUeO6lC59Fus3LOCll96kX793GDFiMHfc2YGUH7fRsaO/V6M//ngPhg17iwIFoti8eQv33uffVFAueu2dXpxVuiTGGNatXk+vp1/1vMz+Pd7iubeeJSoqim1bUnn5idc8L/NEdepezk23XMea1euYOTfjgqnevd5gwJtD+GDYADre0Z6UH1O5+07vvwgANKgfT8eO7Vm1KomlSzI+uLr36MOUKTN8KT+TC+9bqos/+njEYK5oXI8yZUrxw6al9OzVl4Rhn3lSVqeBXale9wKKnlWM3gveYfKbo5n6zpd0Hvw49Ts04+dtu3n/oTcAiKkWx539HiYcDrN9QwojnnnXk0yZXNkeruSQ7DGujnmILBAXeLAznyzAWwUivb145EwcCacHHQFwY4zOuSVPO8ODb0pFFg06Amv3/fjnT/LBr78HP+4z+D0zgwvvW67UhQvui20QdASGbJsXdASnHDm0NfDDZFv9pr4eJrHzZwb6f85z82yKiIiIiDv0c5UiIiIiPrJZmGg9L1DPpoiIiIh4Rj2bIiIiIj6y3k2N6iT1bIqIiIiIZ9SzKSIiIuKjP5v7Mq9Rz6aIiIiIeEY9myIiIiI+cmDKaF+pZ1NEREREPKOeTREREREfacymiIiIiEguUc+miIiIiI/UsykiIiIikkvUs3karlwsdjj9SNARCOe3S+dOI92Rn37YdXhv0BGIMG58X9Xe+V+qCxFxjRqbIiIiIj7Kb/03bnRLiIiIiEiepJ5NERERER/pAiERERERkVyink0RERERH1mrnk0RERERkVyhnk0RERERHzkyg55v1LMpIiIiIp5Rz6aIiIiIj8IasykiIiIikjvUsykiIiLiI12Nnge0bNGENatnsy5pLs883SXf5wiFQixeNIVx44YFlsGFuhg6pB/bUlawfNnXvpcdCoUY+/XHvPvxGwDcdveN/HvRWNbtXELJUiUCy/H6Oy/y1fwvmPDNZ/Tu34PIyAhPy4+Ni2HsxOHMWTyZbxZO5N4Hbgfg//71KDPnjefrOeMYNe4DyseU8zTH8VzYN13J4UIGV3L4maHjaw/y6tKhdP9332PLipSI5pER3Xlh5gAeGdGdwsWjAShcPJr73nuKf331Os98+TIVqlfyNBu4sT1cyiFZl+cam6FQiIEDetPm2o5cXKMpN910Heeff26+zQHwyCOdWbfu+0DKBnfq4qOPRnNNm9t8LxfgjvtuZtP6zcfuf7d4BXe378LWLdsCzTHxi69oVb89ba+4mUKFCtK+43Weln/kSDrPd3+VRrWvofWVN9Pp3tuofl5VBg/8gKYN2tG80fVMmzKLJ//vIU9zZHJl33QhhwsZXMnhd4aFX8xi0J0v/2FZywevI3n+Kl5o2pXk+ato+VDGsXl1l+tJSfqB3q2eZviTg7jx+bs8ywVubA+XcuQWGza+3oLmSWPTGFPAGHOHMebKo/dvNcYMMsZ0McZEeVFmptrxNdm48Qc2b97C4cOHGT16PG2vbellkU7niIurQKtWzfkwYaTvZWdypS7mzF3Ez3t+8b3c8hXKccWVDfn8k/HHlq1dvZ6tP6YGnmP21/OP/b1y2RpiKnjbo7hzxy5WrUgCIG1/GhuSNxITW579+9KOPadIdGGstZ7myOTKvulCDhcyuJLD7wzfL15L2q/7/7DskqviWfjFNwAs/OIbalwVD0CFcyuSPG8VADs2bqN0xbIUK+Pd2REXtodLOSR7vOrZTACuAboaY0YANwKLgHjgfY/KBDJO0/2Y8t/eopStqcTGxnhZpNM5+vV9gW7dehMO+/PhfTKu1EVQnn3pCfr2GogNBzux2ulyREZG0PbG1syZscC3PJX+FsdFl5zPd0tXANCtx2N8t2YmN9zYhtd6D/Qlgyv7pgs5XMjgSg4XMhQrW4K9uzK+HO/d9QvFyhTPyLL2P1x6dR0Azq5RlVJxZSkZU8qzHC7UhUs5cou1/t6C5lVj82Jr7U3A9UALoL21dgTQCajpUZkAGPO/3cV+9ZK4lqN16+bs3LWbZctW+VruiVyoi6A0uaohP+3ew5qV65zO8dyr/2TpgmV8u2i5L3mKRBfhgxED6dHtlWO9mq+82J/LLmzKmM8ncfd9HX3J4cq+6UIOFzK4ksOFDKcy9Z0vKVIimm6Jr9HkzlakrNlMON27L7Ku1IUrOSR7vLoaPWSMKQBEA0WAEsDPQEHglKfRjTH3AfcBmIgShELRWS54a0oqlSrGHrtfMa4Cqak7sryenHIhR/168bS5pgVXt2xGoUIFKV68GMMSBnJXp0d9zeFCXQTlsto1aNayEVc0r0+BQgUpWjSa197uxTMPPedMji5P3UOpMiV55K6X/3xFuSAyMpIPRwxkzOiJJE6c9j+Pj/18Ep+MfpfXX3nL8yyu7Jsu5HAhgys5XMiwb9evFC9bkr27fqF42ZLs270XgN/3/8aIp9859rwX5w7ipx93epbDhbpwKYdkj1c9mx8A64DlwL+Az40xQ4ElwGenepG1doi1tpa1tlZ2GpoAS5Yup1q1c6hcuRJRUVF06NCOiZOmZmtdOeFCju49+lClajzVz6tHx9u7MHPWPN8bmuBGXQTljd6DaXJpG5rXaseT9z3LorlLfG9oni5H+9va0bBpPZ68v7tvvQRvDnqJDckbeW/wsGPLzqly9rG/W7ZqxoYNm0/yytznyr7pQg4XMriSw4UMK6cvpW77KwCo2/4KVk5bAkDh4kWIiMqYNaLBzc35ftFaft//m2c5XKgLl3Lklvx2gZAnPZvW2jeNMaOO/r3NGPMRcCUw1Fq72IsyM6Wnp9P1se4kTh5JRCjEsOGjSEpa72WRTudwgSt18fGIwVzRuB5lypTih01L6dmrLwnDTvndx1O333MTnR++nTLlSjNh1qd8M30ePZ7o7XuOF17/J9tStvNZ4ocATJs8k7f7eTesunbdy+hwy3UkrU7m6znjAHi515vcekd7qlWrTDhsSflxG08//rxnGY7nyr7pQg4XMriSw+8MnQZ2pXrdCyh6VjF6L3iHyW+OZuo7X9J58OPU79CMn7ft5v2HMqYri6kWx539HiYcDrN9QwojnnnXs1zgxvZwKYdkj3F1zENkgTg3gwUgdJKxKn4LO7qfBKFaydg/f1I+sefgvqAjAPDTb27kEDnRfbENgo7AkG3zgo7glCOHtgb+obq6ShtfP1Qv2jQp0P/zKXs2jTETgVNWhrW2rSeJRERERCTPON1p9L6neUxEREREsiG//VzlKRub1tpv/AwiIiIiInnPn14gZIw5F3gFuAAolLncWlvFw1wiIiIieVJ+uwziTKY+SgDeAY4ATYGPgBFehhIRERGRvOFMGpuFrbVfk3Hl+n+stS8AzbyNJSIiIpI3ha3x9Ra0M5ln83djTAjYYIx5GNgKlPM2loiIiIjkBWfS2HyMjJ+cfBR4kYxezTu9DCUiIiKSV+lq9BNYa5cc/XM/0MnbOCIiIiKSl5zJ1egzOcnk7tZajdsUERERyaL8djX6mZxGf+q4vwsBN5BxZbqIiIiIyGmdyWn0b09YNM8YownfRURERLLBhSvE/XQmp9FLHXc3BFwOxHiWSERERETyjDM5jf4tGWM2DRmnzzcDnb0MJX8UMmcyHaq3rE0POgJwksHDAThw5PegIzjjULpG1LjGhf4SF47TkHGhJiCN4N873agJN/YLV+hq9P91vrX2D5+uxpiCHuURERERkTzkTLrM5p9k2YLcDiIiIiIiec8pezaNMTFAHFDYGFOT//bEFydjkncRERERySJdIPRfLYG7gIpAP/7b2NwLPOttLBERERHJC07Z2LTWDgeGG2NusNaO8TGTiIiISJ6V3y6WOpMxm5cbY0pm3jHGnGWMecnDTCIiIiKSR5xJY7OVtfaXzDvW2j1Aa+8iiYiIiORdYWt8vQXtTBqbEcdPdWSMKQxo6iMRERER+VNnMs/mx8DXxpiEo/c7AcO9iyQiIiKSd2lS9xNYa18zxqwEriTjivQpwNleBxMRERGRv74z6dkE2A6EgQ5k/Fylrk4XERERyYZw0AF8dsoxm8aY6saY54wxa4FBwI+AsdY2tdYO8i1hNrRs0YQ1q2ezLmkuzzzdJV/nOPfcKixa9NWx286da3j4YX9/2r5ixVimTf2clStnsXz5DB7xufxMQ4f0Y1vKCpYv+9rXcgsWLMCEaSOZMvsLps8fxxP/fAiAO++5hdlLJ7Pl51WcVarkn6zFmwyV/hbH+Gmf8M2SSQz+4HWios70+2f2vPX2K6zfvIj5ixP/sPzeB25n8XdTmb/kK3q++IynGU4U1H5xoqDfL1w5TiH4usgUCoVYvGgK48YN863MqzpdQ+9/v8nLU/vT4u5rAPjbBZXpMe4VeiX25YUJr1KlRjXf8mi/kNxgrD35bE/GmDAwB+hsrf3+6LJN1toqfgSLLBCXrWmoQqEQa9fM4erWt5CSksrCBYl0vP0h1q7dkNsRfcsRGYrItUybNi2mceN2bNmyNUuvTQ+nZ7vcmJhyVIgpx7LlqylaNJpFi6bQvv3d2aqLnMxN1qhhHfbvTyMhYQCX1mye7fXEFi2V5dcUiS7MgbTfiIyMZMxXw3mh26scOniIX3/Zy6iJH9Km2c3s+fmXP19RDpwsw70P3cFXk6YzcewUXu7Xg6TVyXycMPqM17nv0G9ZylC/QTz79x/g3aGvU792xqQWDRvX5cmnH+SmG+7l0KFDlClbit27fs7SerOa43i5tV/kRG6+X2R3JJgrx2lu1UXI5HxMXNeu93L5ZTUoVrwo119/V7bWcUuFOmf83LjqlXjorSfo2e7/OHL4CE8N78Hw7kO4o9c9/PvDSayctYxLmlxG6wfa0efm5894vSO3LcxOdCDv7RcARw5tDXzA5OyYG32darPx9s8D/T+f7mr0G8g4fT7TGDPUGNOcLLyPGWOqGmOeMsYMMMb0M8Y8YIwpkdPAf6Z2fE02bvyBzZu3cPjwYUaPHk/ba1t6XayzOY7XrFkDNm/ekuWGZk5t376TZctXA7B/fxrr1m0gNjbG1wwAc+Yu4uc93jboTuVAWkZjKDIqksjISKy1rFm1jpQftwWaoX6j2iSOnwbAF59NoOU1zTzNMH/eEvacsA3uvudW+vd7j0OHDgFkuaGZU0HuF5lceL9w5Th1oS4A4uIq0KpVcz5MGOlbmbHVKrJx2XoO/X6IcHqYdYvWcHnL2ligUNHCABQpXoRfduzxLZP2C8kNp2xsWmvHWWtvAv4OzAIeB8obY94xxrQ43UqNMY8C7wKFgHigMFAJWGCMaZI70U8uNi6GH1P++wGesjU1kAPDlRzHu/HGtowaNT7QDGefXZFLa1zE4sXLAs3ht1AoxFfffM6y5G+YO2shy79dFXiG/2z+kb2/7iM9PaPXOnXbdmIqlPM9V7VqlanXIJ5pM79g0pSR1LzsYt8zBM2194sgj1NX6qJf3xfo1q034bB/HVApyVs4r/YFRJcsSoFCBajR9DJKVSjDJz0/5OZud/DG/Pe4+dk7+Py1T3zLdDztF7knbP29Be1P59m01qZZaz+x1rYh43fSlwP//JOX3Qtcba19iYyr2C+w1v4LuBp4M4eZT8uc5NTJqYYK5IccmaKiorjmmqsYO3ZyYBmio4swetRQnnzqefbt2x9YjiCEw2FaXXEjdS66khqXXUT18/0bc3WqDOdW/98RMUHsopGRkZQsWZyrmrbnuX/1IeGjgf6HCJhL7xdBH6cu1EXr1s3ZuWs3y5b5+6UwdeNWJr/7Jc98/DxPDe/BlrU/EE5Pp1nHlox8cRhP1L+fkS8Oo/OrD/maC7RfSM6cyaTux1hrf7bWvmetPZNzbZlXGhQEih19/RYg6lQvMMbcZ4xZaoxZGg6nZSXaMVtTUqlUMfbY/YpxFUhN3ZGtdeWEKzkytWzZhOXLV7Nz5+5Ayo+MjGT0qKF8+uk4vvzyq0AyuGDv3n0snLeEJs0bBJ6hZvwlFC9RjIiIjDHBFWJj2LF9p+95tm7dzsQJUwH47tuVhMOW0mWyPi72r8yV9wsXjlMX6qJ+vXjaXNOC9ckL+HjEYJo2acCwBH++BM0e/TXPt3mal2/qQdov+9m+OZWGNzRh6ZSMcZeLJ8/39QIh0H7hhTDG11vQstTYzIL3gSXGmCHAAjKuZscYUxY45YAsa+0Qa20ta22tUCg6WwUvWbqcatXOoXLlSkRFRdGhQzsmTpqarXXlhCs5MnXo0I7Ro4M7hT50SD/Wrfue/gOGBJYhKKVKn0Xx4sUAKFioIA2vqMvG9ZsDz/B98iYWzF1C63ZXAdD+5rZMTZzpay6AxEnTaHxFXQCqVqtMgQJR/LTb33GbQXPl/cKF49SFuujeow9VqsZT/bx6dLy9CzNnzeOuTo/6Unax0sUBKBVbhsuvrsvCCXP5Zece/l73QgAuqH8xO35I9SVLJu0XklOezHNirR1gjJkOnA+8Ya1dd3T5LqCxF2VmSk9Pp+tj3UmcPJKIUIhhw0eRlLTeyyKdzgFQuHAhmjdvxMMPdwuk/Ab14+nYsT2rViWxdEnGm0P3Hn2YMmWGrzk+HjGYKxrXo0yZUvywaSk9e/UlYdhnnpdbrnxZ3nj7JSIiIgiFDJO+nMrXU2fT6b5beeDRuylbrjRT54xhxvQ5/F/XF3zNsCF5E4Pef42nn32ENavWMerjsZ6Un+n9hDdp0KgOpUufxerkufTpPYCPP/qCQe/0Yf7iRA4dOsyD9z/taYYTBbVfHM+F9wtXjlMX6iJIj7zzNEXPKkb6kXRG9BjKgb1pfPjPd+j4/N2EIiM4fPAQCd3e9S2P9gvJDaec+iho2Z36KC/KramPciInUx/lJhd2iuxMfZRX5WTKodzkSg4XBH/CzI3jNDemPsoNWZn6yCs5mfooN7mwX4AbUx99Xf4mX6uj+Y5Rzk59JCIiIiKSI97+XIiIiIiI/IF+rlJEREREJJeoZ1NERETER9aJ0dX+Uc+miIiIiHhGPZsiIiIiPtKYTRERERGRXKKeTREREREfqWdTRERERCSXqGdTRERExEe6Gl1EREREJJeoZ1NERETER+H81bGpxuZfQXo4PegIGOPGkWGtDToCh8JHgo4AuFEXB44cDDqCnCD4vcINYQeOD4B99nDQEbi2wuVMSP026BiSj6mxKSIikoepoemesMZsioiIiIjkDjU2RURERMQzOo0uIiIi4iM3RhT7Rz2bIiIiIuIZ9WyKiIiI+Eg/VykiIiIikkvUsykiIiLio7Ajc1f7RT2bIiIiIuIZ9WyKiIiI+EhXo4uIiIiI5BL1bIqIiIj4SFej5wEtWzRhzerZrEuayzNPd8m3OSpWjGXa1M9ZuXIWy5fP4JGHO/ue4XihUIjFi6YwbtywQMofOqQf21JWsHzZ176WGxsXw5iJw5i9aBLfLJjIPQ/c/ofHH3y4E9t/WUupUiU9zTB24nDmLJ7MNwsncu/RDM+9+DRzlyQyc954Ej5+i+IlinmW4WRKlCjOpyPfZeWKmaxYPoM6dS7ztXwI/jh1KUdQx8iJXKiLoDK06dyW/tMG0X/qWzw+8CmiCkbxcN+uvDN3KP0S+9MvsT+VLzjHtzzgxvZwKYdknbHWzZEDkQXishUsFAqxds0crm59CykpqSxckEjH2x9i7doNuR3RtxzZvWYtJqYcFWLKsWz5aooWjWbRoim0b3939jLkwpVzXbvey+WX1aBY8aJcf/1d2VpHOAf7a6OGddi/P42EhAFcWrN5ttdTpkjxLD2/XPmylI8py6oVSUQXLcLUWWPodNvDrE/eSGxcDP0Gvsi51avQ4oob+PnnX854vVk5dv+YIZpp34zhrlu7UCEuhrnfLCQ9PZ3uPZ8E4KXn+53xen85mHbGzz2Z999/g3nzFpOQ8BlRUVEUKVKYX3/dm+X1pIez10+QF98vciK3jpGccKEucjND2wqXn/FzS5UvRe8xr9K1eRcOHTzEk4Of4buZS7mw7sV8O2MJCxLnZ7l8gAmp32brdeDG9sjtHEcObQ38UvBPY2/ztfF1y7ZPAv0/57mezdrxNdm48Qc2b97C4cOHGT16PG2vbZkvc2zfvpNly1cDsH9/GuvWbSA2NsbXDJni4irQqlVzPkwYGUj5AHPmLuLnPWfemMstO3fsYtWKJADS9h9gw/qNxFQoD0Cvl//Ji8/3zVLDMecZ0tiQvJGY2PJ8M2Me6enpAHy7ZIWv+0exYkVp1LAOCQmfAXD48OFsNTRzwoXj1KUcQR0jx3OhLoLMEBERokChAoQiQhQsXJCfd/zsS7mn4sL2cCmHZE+ea2zGxsXwY8q2Y/dTtqYG0sByJUems8+uyKU1LmLx4mWBlN+v7wt069abcNjNnnS/VPpbLBddfD7ffbuCFq2akpq6g6TVyT5niOOiS87nu6Ur/rD81o438PW02b7lOOecv7Fr188MHfoGixZ+xTvvvEaRIoV9Kx/cOU5dyeECF+oiqAw/7/iZ8UO+5L0FH/DBkuEc2JfGijnLAbj1qY68MWUgnXp0JrKAf5dbuLA9XMqRW8IYX29By3ONzZOd7g1iqIArOQCio4swetRQnnzqefbt2+97+a1bN2fnrt0sW7bK97JdUiS6CO9/NJDnnu1D+pF0Hnvyfl57+S3fM3wwYiA9ur3C/n3/PQX+2FP3c+TIEcaMnuhblsjISGrWvIghQz6iTt1WHEg7wNM+j8Ny5Th1JYcLXKiLoDJEF4+mdos6PNjwXu6pfRcFCxei8fVN+OS1j3ik2UM80/YJipYsxvUP3OB5lkwubA+XcuRVxpgPjTE7jTGrT1j+iDEm2Rizxhjz2nHLuxljvj/62J92MXvS2DTGlDDG9DHGrDPG/HT0tvboslNeBWGMuc8Ys9QYszQczt5YsK0pqVSqGHvsfsW4CqSm7sjWunLClRyRkZGMHjWUTz8dx5dffuV7+QD168XT5poWrE9ewMcjBtO0SQOGJQwMJEtQIiMj+eCjAYz9fCKJE6dx9jmV+NvZFZkx90uWrJxOhdjyTP1mDGXLlfE0w4cjBjJmdEaGTB1uuY6rWjbloXuf9qzsk9m6NZWUraksWZLRczN2XCI1L73I3wyOHKeu5HCBC3URVIZLGl7Kjh93sPfnvaQfSWfRlAX8/fK/s2fnHgCOHDrCjM+nc+6l1T3PksmF7eFSjtxifb6dgWHA1ccvMMY0BdoBl1hrLwT6Hl1+AXAzcOHR17xtjIk43cq96tkcDewBmlhrS1trSwNNjy77/FQvstYOsdbWstbWCoWis1XwkqXLqVbtHCpXrkRUVBQdOrRj4qSp2VpXTriSY+iQfqxb9z39BwzxvexM3Xv0f0tkKAAAIABJREFUoUrVeKqfV4+Ot3dh5qx53NXp0cDyBOHNQS+xYf0m3hs8HIB1SRu46NyGxF9yJfGXXEnqth20uOIGdu3c7W2G5I28N3jYsWVNmzfk4cfu4Y6bH+S33373rOyT2bFjFykpqVQ/t0pGlqYNfL/owJXj1JUcLnChLoLKsHvbLqrXPI8ChQoAcHGDGqR8/yNnlTvr2HPqtKjLluT/eJ4lkwvbw6UceZW1djZw4gDhB4E+1tqDR5+z8+jydsBn1tqD1trNwPdA7dOt36uBH5Wtta8ev8Baux141Rhzt0dlApCenk7Xx7qTOHkkEaEQw4aPIilpvZdFOpujQf14OnZsz6pVSSxdknFQdu/RhylTZviawxUfjxjMFY3rUaZMKX7YtJSevfqSMOwzz8utXfcybry5HUlrkpk+ZywAr/Tq7+v4yNp1L6PDLdeRtDqZr+eMA+DlXm/S+7V/UaBAAUZ/+SEA3y5dwTOPv+Bbrscf78GwYW9RoEAUmzdv4d77nvStbHDjOHUpR1DHyPFcqIugMmxYvp4FifPoO7k/4fR0Nq3ZxNSR/6bH8BcoXqo4xhg2J23mvWff9jxLJhe2h0s58pnqQCNjTG/gd+Apa+0SIA5YeNzzUo4uOyVPpj4yxkwFpgPDrbU7ji4rD9wFXGWtvfLP1pHdqY/youCH9ubO1Ee5ISdTH+WWrE595BUXxivldOqj3JLdqY9EvJaVqY+8kpOpj/IiF6Y++iiuo69v4Hdu++R+4L7jFg2x1v7hlKcxpjIwyVp70dH7q4EZQFcgHhgFVAEGAQustR8ffd4HQKK1dsypyveqZ/Mm4J/AN8aYckeX7QAmADd6VKaIiIiInOBowzKr4+lSgLE2o2djsTEmDJQ5urzScc+rCGw7yeuP8WTMprV2j7X2/6y1f7fWljp6O99a+3/AdV6UKSIiIvJXEPb5lk1fAs0AjDHVgQLAbjI6Dm82xhQ0xpwDnAssPt2Kgpj6qGcAZYqIiIjISRhjPgUWAOcZY1KMMZ2BD4EqR0+nfwbcaTOsIeNC8CRgCtDFWpt+uvV7chrdGLPyVA8B5b0oU0REROSvIPgR939krb3lFA91PMXzewO9z3T9Xo3ZLA+0JGOqo+MZIHs/7ioiIiIifzleNTYnAUWttctPfMAYM8ujMkVEREScFw78enh/edLYtNZ2Ps1jt3pRpoiIiIi4x6ueTRERERE5ifw2M3AQV6OLiIiISD6hnk0RERERH6lnU0REREQkl6hnU0RERMRHVleji2ucmPzVOpECF47PA4cPBh0BAGOCr430cH47GeS+iFDwJ6y0X/zXor0bg45AyIH3CoCwI58j4j81NkVERER8lN++jgX/FVhERERE8iw1NkVERETEMzqNLiIiIuIjnUYXEREREckl6tkUERER8VF+uy5fPZsiIiIi4hn1bIqIiIj4KOzG1Ke+Uc+miIiIiHhGPZsiIiIiPtLV6CIiIiIiuUQ9myIiIiI+Us9mHtCyRRPWrJ7NuqS5PPN0l3ydY+iQfmxLWcHyZV8HUj5AwYIFmT9vEt8uncby5TN47rkn81WGwe+8ysYfFrNwyVf/89gjXe9hb9omSpU+y/Mcg97uw/ebF7Ng8X9z/PPZR1m7fh5z5k9kzvyJXNWiiec5Mrmwb4Ibx6krOZKT5/Pt0mksXjSF+fMmB5IB3KiLoDLExsXw+YQEZi2cwIz54+l8f0cA3vmgL1Nnj2Hq7DEsXDGVqbPH+JYJIBQKsXjRFMaNG+ZrucdzYb+Q7Mlzjc1QKMTAAb1pc21HLq7RlJtuuo7zzz833+b46KPRXNPmNt/LPd7Bgwe5qkUHLq91FbVqtaBliybUqX1Zvsnwycdf8I/rOv3P8ri4CjRr1pAtW7b6kmPkJ2O44SQ53h6UQKP619Ko/rVMmzrLlyzgxr7pynHqSg6AFi07ULvO1dRvcE0g5btQF0FmOHLkCD27v0aTum25tsUt3HXPLZx7XlUe7PwULRrfQIvGN5A4YRqJE6f7kifTI490Zt26730t83gu7Be5yfp8C1qea2zWjq/Jxo0/sHnzFg4fPszo0eNpe23LfJtjztxF/LznF9/LPVFa2gEAoqIiiYqKwlr/d/+gMsyft4Q9P//vNnjl1e706N7H3xwO7AuZXNg3XTlOXcnhAhfqIsgMO3fsZvXKtQCk7T/AhvWbiKlQ7g/Pufb6lowf41/Pc1xcBVq1as6HCSN9K/NELuwXkn15rrEZGxfDjynbjt1P2ZpKbGxMvs3hilAoxNIlU9m2dSXTv57N4iXL8mWGTK1aNyc1dTurV60LLEOme++/nXkLJzPo7T6ULFk86Di+cuU4dSUH1jJ50icsmD+Zzp1v9b983KgLFzIAVKwUy0WXnM+yb1ceW1an/uXs2vkTmzdt8S1Hv74v0K1bb8Lh4PrIXNkmuSVs/L0FLc81No3531oNohfNlRyuCIfD1IpvQeVzahFfqyYXXnhevswAULhwIZ5+pgu9X+wfSPnH++D9T7j04qY0rNeGHTt28dLLzwYdyVeuHKeu5GjS9B/Urdeatu3u4IH776Rhwzq+Z3ChLlzIUCS6CEM/6s/z3fqwf1/aseXX3dCa8WMSfcvRunVzdu7azbJlq3wr82Rc2CaSfZ40No0xxY0xrxhjRhhjbj3hsbdP87r7jDFLjTFLw+G0Uz3ttLampFKpYuyx+xXjKpCauiNb68oJV3K45tdf9/LN7Pm08PFCFNcynFPlbM6uXJF5CyezKmk2cXExzJk3kXLly/ieZdfOnwiHw1hrGZ7wGZfXquF7hiC5cpy6kiOzzF27fmL8hCnE17rU9wwu1EXQGSIjIxk6vD/jPp/MV5P+OzYzIiKCVm2uZMK4Kb5lqV8vnjbXtGB98gI+HjGYpk0aMCxhoG/lZwp6m+S2sM+3oHnVs5kAGGAMcLMxZowxpuDRx+qe6kXW2iHW2lrW2lqhUHS2Cl6ydDnVqp1D5cqViIqKokOHdkycNDVb68oJV3K4oEyZUpQokXF6tlChQjRv1ojk5I35LkOmpDXJVK1cm4svaMzFFzRm69btNGpwLTt37PY9S/nyZY/93ebaFqxNWu97hiC5cpy6kKNIkcIULRp97O8rmzdmzZpkXzOAG3URdIZ+b/Xi+/WbGPL28D8sb9SkHt9v2EzqNv8aWd179KFK1Xiqn1ePjrd3YeasedzV6VHfys8U9DaRnPFqns2q1tobjv79pTHmX8AMY0xbj8o7Jj09na6PdSdx8kgiQiGGDR9FUgAfoK7k+HjEYK5oXI8yZUrxw6al9OzVl4Rhn/maoUKF8nz4QX8iIkKYUIgvvphIYqK/V1IGmeHDYQNo2KgOpUufxdr183j5pQGM+Gi0L2Uf74OE/sdyJCXP5ZXeGbkuvuQCrLVs+U8Kjz3a3bc8LuybrhynLuQoX74so0cNBSAyMoLPRo1n6rRZvmYAN+oiyAzxdS+j/c3tSFqTfGx6oz4v9mfGtDm0+0crX0+hu8SF/UKyz3gx5sEYsxa40FobPm7ZncAzQFFr7dl/to7IAnEajOEQB8YXO6NwVME/f5IPTjaGyW9ph34POoKcICIU/FD89LALJ+7cUD66ZNAR2HXg16AjABB2ZIzlkUNbA3/zfOXsjr5WRrf/fBzo/9mrd6WJQLPjF1hrhwNPAoc8KlNEREREHOPJaXRr7TOnWD7FGPOyF2WKiIiI/BWEnZhq3T9BnG/pGUCZIiIiIhIAT3o2jTErT/UQUN6LMkVERET+CvLbqGavrkYvD7QE9pyw3ADzPSpTRERERBzjVWNzEhlXnS8/8QFjzCyPyhQRERFxXv4asendBUKdT/NYMD+4KyIiIiK+86pnU0REREROIr+N2Qx+9l8RERERybPUsykiIiLio3Dgv2HkL/VsioiIiIhn1LMpIiIi4qP89gtCamz+BYRMPutvP42wDf4ALRDhxmGz9+CBoCOIg9LD+e3SA7f99Nu+oCM48b4p+Zsbn5oiIiIi+UR+a/5rzKaIiIiIeEaNTRERERHxjE6ji4iIiPgov42sVs+miIiIiHhGPZsiIiIiPspvUx+pZ1NEREREPKOeTREREREf5a9+TfVsioiIiIiH1LMpIiIi4iNdjS4iIiIikkvUsykiIiLiI12Nnge0bNGENatnsy5pLs883SXf5wiFQixeNIVx44YFlsGFHEFtjwGDX2btxgXMWTjp2LILL/o7X00fxewFE/lk1LsULRbtW55MQW8PcOMYcSGDKzlcyOBKDhcynHtuFRYt+urYbefONTz8cGffc7hQFy7lkKzLc43NUCjEwAG9aXNtRy6u0ZSbbrqO888/N9/mAHjkkc6sW/d9IGW7kiPI7fHZJ2O56R9//IDoP6g3Lz7fl8b1rmXyxGk83PUeX7IcL+j9woVjxIUMruRwIYMrOVzIALBhwybq1GlFnTqtqFfvGg4c+I0JE6b4msGVunAlR26xPt+Clucam7Xja7Jx4w9s3ryFw4cPM3r0eNpe2zLf5oiLq0CrVs35MGGk72W7lCPI7bFg/lL27Pn1D8uqVTuH+fOWADBr5jyubevvvhH09gA3jhEXMriSw4UMruRwIcOJmjVrwObNW9iyZauv5bpSF67kkOzJc43N2LgYfkzZdux+ytZUYmNj8m2Ofn1foFu33oTDwX63CTqHK9sj09q162nVujkA7a5rRVycv1mC3h7gxjZxIYMrOVzI4EoOFzKc6MYb2zJq1Hjfy3WlLlzJkVvCPt+Clucam8aY/1lmrf8fqC7kaN26OTt37WbZslW+lutiDhe2x/EefehZ7r7vNr7+ZixFi0Vz6PBh38p2YXuAG9vEhQyu5HAhgys5XMhwvKioKK655irGjp3se9mu1IUrOSR7PLka3RgTAzxPRoP6OeAR4AZgLdDVWpt6itfdB9wHYCJKEApl/aKJrSmpVKoYe+x+xbgKpKbuyPJ6csqFHPXrxdPmmhZc3bIZhQoVpHjxYgxLGMhdnR7Ndzlc2B7H+37DJm687m4AqlarzFUtm/hWtgvbA9zYJi5kcCWHCxlcyeFChuO1bNmE5ctXs3Pnbt/LdqUuXMmRW6wTIyn941XP5jAgCfgRmAn8BlwDzAHePdWLrLVDrLW1rLW1stPQBFiydDnVqp1D5cqViIqKokOHdkycNDVb68oJF3J079GHKlXjqX5ePTre3oWZs+b53qBwJYcL2+N4ZcqUAjK+rT/x9EMM++BT38p2YXuAG9vEhQyu5HAhgys5XMhwvA4d2jF6tP+n0MGdunAlh2SPV/NslrfWvgVgjHnIWvvq0eVvGWM8nbchPT2dro91J3HySCJCIYYNH0VS0novi3Q6h2QIcnsM+fANGjSsTanSZ7Fy7WxefXkg0UWL0Pne2wCYNGEaIz8e40sWl7hwjLiQwZUcLmRwJYcLGTIVLlyI5s0b8fDD3QIp35W6cCWHZI/xYsyDMWaFtbbG0b9fstZ2P+6xVdbai/9sHZEF4vJXH/NphE4yViW/CjswRqdkIf/nxDyZvQcPBB3Bie0h4rLIUETQETgSTg86glOOHNoa+Ifqw5Vv8vXNc9APowL9P3t1Gn28MaYowAkNzWpAskdlioiIiIhjPDmNbq197hTLvzfG+H85nYiIiIgj9HOV3usZQJkiIiIiEgCvpj5aeaqHgPJelCkiIiLyV5C/+jU9vBodaAnsOWG5AeZ7VKaIiIiIOMarxuYkoKi1dvmJDxhjZnlUpoiIiIjz8tuYTa8uEDrlXJrW2lu9KFNERERE3ONVz6aIiIiInEQ46AA+C+JqdBERERHJJ9SzKSIiIuIjm8/GbKpnU0REREQ8o55NERERER/ltzGbamz+BVgbfHd78AncUTAiKugIAJQoFB10BH79PS3oCACEHThGxC0hY4KOAMCKyhcGHYELN53qd1ZE/KHGpoiIiIiPNGZTRERERCSXqLEpIiIiIp7RaXQRERERH+W3C4TUsykiIiIinlHPpoiIiIiP8tsMGurZFBERERHPqGdTRERExEf5q19TPZsiIiIi4iH1bIqIiIj4KJzP+jbVsykiIiIinlHPpoiIiIiP9HOVeUDLFk1Ys3o265Lm8szTXfJ1joIFCzJ/3iS+XTqN5ctn8NxzTwaSw4W6CCpDbFwMn09IYNbCCcyYP57O93cE4MKL/s7EqSOZOnsMiTNGcellF3uaYdzEj5i3OJE5Cydx3wN3AND2uquZs3ASO/aspUbNizwr/3RCoRCLF01h3LhhgZTvwr7pSo6hQ/qxLWUFy5d9HUj5mVyoC/Bn34yMKUOl4X2oPPk9Kk98l5K3twOgaMuGVJ74LtWTJlPwonP/8JqC1Svzt8/eoPLEd6k84W1MgSjP8oE728OVHJJ1xjo611NkgbhsBQuFQqxdM4erW99CSkoqCxck0vH2h1i7dkNuR/Qth8lhlujoIqSlHSAyMpJvZo3jiSeeZ9Hi77K0jpzsJS5sk9zMUD66ZJaeX658GcqVL8vqlWuJLlqEKTM/5+6Oj9Lz5f9j6DsfMXP6XJpd1YgHH72bG6/tdMbrPRQ+cuaZy5elfExZVq5IIrpoNF9/M4Y7bu2CtZZw2NKvf0+e7/EaK5atztL/7dff07L0/JPp2vVeLr+sBsWKF+X66+/K1jqyO2edC/umSzkaNazD/v1pJCQM4NKazX0tO1Nu1UXI5PSdM3f2zVXnnP5LZETZs4gsW4qDSRsx0YWpPGYgW7u8CNZibZiYno+y87X3Obj66P8/IkTlsYNIfeZ1DiZvJlSyGOG9aRA+9W/SXLhpZbaygzv7Zm7mOHJoa853jhy66ezrfG18jfrPl4H+n/Ncz2bt+Jps3PgDmzdv4fDhw4wePZ6217bMtzkA0tIOABAVFUlUVBR+f8FwoS6CzLBzx25Wr1wLQNr+A2xYv4mYCuWwFooVKwpAseLF2LF9l2cZduzYxcoVSUczpLE+eRMVYsuzYf0mNn6/2bNy/0xcXAVatWrOhwkjAynfhX3TpRxz5i7i5z2/+F7u8VypC7/2zfRdeziYtBEAm/YbBzf+SGT50hza9COHN2/9n+dHN7icg8mbOZiccdyGf9l32oZmTrmyPVzJIdmT5xqbsXEx/Jiy7dj9lK2pxMbG5NsckPGNcOmSqWzbupLpX89m8ZJlvpbvQl24kAGgYqVYLrrkfJZ9u5Lnn+1D915PsWT1dHr0eopXer3pS4ZKf4vj4kvO59ulK3wp73T69X2Bbt16Ew4Hc4bFlf3ClRwucKUugtg3I+PKUej8qvy+IvmUzylQOQ5rLRXff4mzx7xFqc7tPc3kyvZwJUduCWN9vQXNt8amMaacT+X8z7Ighgq4kgMgHA5TK74Flc+pRXytmlx44Xm+lu9CXbiQoUh0EYZ+1J/nu/Vh/7407rj7Jl549lXiL7qSnv96lX4DX/Q8Q3R0ERJGDKR7t5fZvy/np8BzonXr5uzctZtly1YFlsGF/cKlHC5woS6C2DdNkULEDezOzlfeI3z0bNRJRUZQ+PILSX3qNbbc9hRFr6pPkbqXepfLge3hUg7JHk8am8aYUifcSgOLjTFnGWNKneZ19xljlhpjlobD2fsg3JqSSqWKscfuV4yrQGrqjmytKydcyXG8X3/dyzez59OiRRNfy3WhLoLOEBkZydDh/Rn3+WS+mjQdgBtvaUfixGkATPzy355eIJSZIWHEQL4YPZHJR8sNUv168bS5pgXrkxfw8YjBNG3SgGEJA33NEPR+4VoOF7hQF77vm5ERxA3szt6JM9k/bf5pn3pk+25+W7KK9F/2Yn8/SNo3Syh4QVXPormwPVzKkVusz/+C5lXP5m7g2+NuS4E44Lujf5+UtXaItbaWtbZWKBSdrYKXLF1OtWrnULlyJaKioujQoR0TJ03N1rpywpUcZcqUokSJ4gAUKlSI5s0akZy80dcMLtRF0Bn6vdWL79dvYsjbw48t25G6k3oN4gFo2LgOmzf9x9MM/Qf1Zn3yJt4dPMzTcs5U9x59qFI1nurn1aPj7V2YOWsed3V61NcMQe8XruVwgQt14fe+GfPSYxzc+CN7ho370+emzf2WgtXPwRQqCBEhCsdfzKGNWzzL5sL2cCmHZI9X82w+A1wJPG2tXQVgjNlsrT3Ho/KOSU9Pp+tj3UmcPJKIUIhhw0eRlLTe62KdzVGhQnk+/KA/EREhTCjEF19MJDFxuq8ZXKiLIDPE172M9je3I2lNMlNnjwGgz4v9efqxF+j1yj+JjIzk998P8sxjL3iWoU7dy7nplutYszqZmXO+BKB3rzcoULAAr7zWg9JlSjFy9HusWbWWDv+4x7McrnFh33Qpx8cjBnNF43qUKVOKHzYtpWevviQM+8zXDK7UhV8KX3YhJa67koPJmykybhAAu98cjikQRbnuDxJRqgQV3+3JwXWbSLmnO+G9+9kzbCxnfz4ArCVt9hLSvlniWT5XtocrOSR7PJv6yBhTEXgT+BF4Hlhhra1ypq/P7tRHeVHgczSQs6mP8pqsTn3klaxMfeSV3Jj6KDdkd+ojybtyY+qj3PBnUx/5ISdTH+VFLkx99I+z2/r6pjX2PxPy5tRH1toUa+2NwExgGlDEq7JERERExE2e/1yltXaiMWY6UBXAGNPJWpvgdbkiIiIiLspvV9L7MvWRtfY3a23mT5P09KNMEREREflzxpjHjTFrjDGrjTGfGmMKGWPOMcYsMsZsMMaMMsYUyO76PenZNMacaoCIAcp7UaaIiIjIX4ELE61nMsbEAY8CF1hrfzPGjAZuBloDb1prPzPGvAt0Bt7JThlenUYvD7QE9pyw3ACnn0RMRERERPwUCRQ2xhwm4xqbVKAZcOvRx4cDL+BYY3MSUNRau/zEB4wxszwqU0RERMR53v2afdZZa7caY/oCW4DfgKlkzJH+i7U2c9qTFDLmS88WT8ZsWms7W2vnnuKxW0+2XERERERy3/G/0Hj0dt9xj50FtAPOAWKBaKDVSVaT7XP/nl+NLiIiIiL/5fdPSFprhwBDTvHwlcBma+0uAGPMWKA+UNIYE3m0d7MisC275ftyNbqIiIiIOGkLUNcYU8QYY4DmQBIZ86S3P/qcO4Hx2S1APZsiIiIiPnLpanRr7SJjzBfAd8ARYBkZvaCTgc+MMS8dXfZBdstQY1NEREQkH7PWPk/GT4sfbxNQOzfWr8amiIiIiI/y2y8IqbH5F5AxhCJYrhwYwdcEFIksFHQEAMKHfws6AgUiooKOAMDBI4eCjuDMSbGIUPBD8dPDwU/sEjLB1wNAlbmDg44AsY2CTiD5nBqbIiIiIj4K/uuYv9z46iciIiIieZJ6NkVERER85Pc8m0FTz6aIiIiIeEaNTRERERHxjE6ji4iIiPjIpUnd/aCeTRERERHxjHo2RURERHzkytzVflHPpoiIiIh4Rj2bIiIiIj7SmE0RERERkVyink0RERERH2lS9zygZYsmrFk9m3VJc3nm6S75PkcoFGLxoimMGzcssAxB10XFirFMm/o5K1fOYvnyGTzycGffyi5QsABf/Hs4E2Z+SuKc0Tz6zP0A1GsUz5dff8KEmSP5dNIH/O2cip5liI2L4YuJCcxeNJFZCyZwzwMdjz129323MWfJZGYtmED3nk96lgHg7XdfZfMPS1i8ZMqxZddf35olS//N3v0bqXnZxZ6Wf6Ig94sTBX2MACQnz+fbpdNYvGgK8+dNDiQDBF8X555bhUWLvjp227lzDQ97vG+kp6fT/q4uPPT08wCkbNvOLfc+RuubOvNkj1c4fPgwAIcOHeLJHq/QqsPd3HLvY2xN3eFpLgh+e7iWQ7LOuHpFVGSBuGwFC4VCrF0zh6tb30JKSioLFyTS8faHWLt2Q25H9C1HyJgcZena9V4uv6wGxYoX5frr78rWOsI52E9ysy6yWxMxMeWoEFOOZctXU7RoNIsWTaF9+7uzlaFyiZgsv6ZIdGEOpP1GZGQkn036gJf+9TqvDe7Fg7c/wcYNP3BrpxupcdmF/N8jL5zxOvcf/u2Mn1uufBnKx5Rl1Yq1RBctwr9nfcHdtz1CmXKl6frk/dze4QEOHTpM6TKl+Gn3z2e83n2HzjwDQIMGtdmflsbQof2oHX81AOedV5Vw2DLwrd48++zLLPtuVZbWCXDwyKEsvwZyd7/IyTtpbh4jEaHs9yEkJ8+nfv1r+OmnPdleB0B6OJzt1+ZWXUSGIrKd4cQ8mzYtpnHjdmzZsjXLr9+XMuuMnjf8s7GsWbeB/WkHePv1njzZ42WaX1Gf1lc2oedrb3Heuedw8/Vt+GzsJJK/38zzzzxC4vRZfP3NAvq92O206y4c2yjLuTPlxc/UI4e25uxDNRc0jmvua+Nr9tavA/0/57mezdrxNdm48Qc2b97C4cOHGT16PG2vbZlvc8TFVaBVq+Z8mDDS97IzuVAX27fvZNny1QDs35/GunUbiI3NeqMxuw6kZTTKIqMiiYyKxNqMqS+KFisKQLHiRdmxfZdn5e/csZtVK9YCkLb/ABvWbyKmQjnuvPtmBr35PocOZfSaZKWhmR3z5i1mz8+//GFZcvJGNmzY5Gm5pxL0fpHJhWPEFa7VRbNmDdi8eUu2GppnavvOXcyev5gbjv4/rbUs+nYFLZpkNBLbtb6SGbMXADBjzgLatb4SgBZNGrHo2+WeTqPjyvZwJYdkT55rbMbGxfBjyrZj91O2pgby4eFKjn59X6Bbt96Ew8H1YLtSF5nOPrsil9a4iMWLl/lWZigUYsLMkSxcO415sxay4rvV/OvxFxn66QDmrEjkuhtbM2TAMF+yVPxbLBdffD7ffbuSKtUqU6f+5Uye/hljJw+nRs2LfMngoiD2i0zOHCPWMnnSJyyYP5nOnW/1v3wcqoujbryxLaNGjfe0jFcHvMcTD3XGmIyP5F9+3UuxotFERmb0zpYvW4adu34CYOeun4gpVwaAyMgstfXyAAAfDklEQVQIikYX4Zdf93qWzZXt4UqO3GJ9vgUtzzU2zUlOOQcxVMCFHK1bN2fnrt0sW5b105K5yYW6yBQdXYTRo4by5FPPs2/fft/KDYfDtG16K40uacUll13EuX+vSqf7b+PeW7rSqEZrxnw6gW4vPuF5jiLRRfjgowE89+wr7N+XRmREBCVKFueaK2+mV4++DBn2hucZXBTUfpHJlWOkSdN/ULdea9q2u4MH7r+Thg3r+J7BlboAiIqK4pprrmLsWO/Gr86at4hSZ5Xkwr+fe2zZyf6/mfVyuse84Mr2cCWHZI8nV6MbY6621k45+ncJ4A0gHlgNPG6tPemIZmPMfcB9ACaiBKFQdJbL3pqSSqWKscfuV4yrQKoPA6hdzFG/XjxtrmnB1S2bUahQQYoXL8awhIHc1elRX3O4UBcAkZGRjB41lE8/HceXX37le/kA+/buZ9G8pVzRvD5/v7A6K77LOIU7+ctpfDjqLU/LjoyM5IOP+jP280kkTpwOQOq27SROnAbA8u9WEQ6HKV36rByP2fsrcWG/cOUYySxz166fGD9hCvG1LmXu3EW+ZnClLgBatmzC8uWr2blzt2dlLFuZxKy5C5mzYAkHDx0mLe0Arw54j3370zhyJJ3IyAh27NpN2TKlAChfrgzbd+4mplxZjhxJZ3/aAUoUL+ZZPle2hys5covm2cwdLx/3dz8gFbgWWAK8d6oXWWuHWGtrWWtrZaehCbBk6XKqVTuHypUrERUVRYcO7Zg4aWq21pUTLuTo3qMPVarGU/28enS8vQszZ83zvaEJbtQFwNAh/Vi37nv6Dxjia7mlSpekWPGMsZkFCxWk/hV12Lj+B4oWL0rlKn8DoEGTOmzcsNnTHG8MepEN6zfx3uDhx5ZNmTyDho0zeq+qVD2bqKiofNXQhOD2i+O5cIwUKVKYokWjj/19ZfPGrFmT7GsGcKMuMnXo0I7Ro709hf74g534+suPmTpmOK/3/Ce1L6/Bqy/8H7Uvu4Sps+YAMD5xOs0a1QOgacO6jE/M+LI4ddYc6lxew9OeTVe2hys5JHv8mGezlrX20qN/v2mMudPLwtLT0+n6WHcSJ48kIhRi2PBRJCWt97JIp3O4wIW6aFA/no4d27NqVRJLl2S8QXXv0YcpU2Z4XnbZ8mV4bVBPQqEIQiHDV+OnM3PaHLo/8RKDEl4nHA6z99e9dOvay7MMtetexo03tyNpTTLT5owF4JVe/fn047G8OeglZs4fz+HDh+n60LOeZQBIGDaARo3rUrr0WSRvmE/vl/qzZ88v9O33AmXKlGLMmA9ZuTKJ69p5+jZxTJD7xfFcOEbKly/L6FFDgYyxgJ+NGs/UabN8zQBu1AVA4cKFaN68EQ8/fPorvb3y+IN38/TzfXhryEecX70q/2jTAoB/tGlJtxdfp1WHuylRvBiv9/ynpzlc2R6u5Mgt+a1n05Opj4wxKWScOjdAF6CqPVqQMWaltfaSP1tHdqc+yotyOvVRbsjJ1Ee5KfiayN7UR17IytRHXsnq1Edeye7UR7nJjSMkZ1Mf5ZacTH2UW3Jr6qOcOtOpj7yUk6mP8iIXpj6qF9fU17eMBVtn5smpj4YCxYCiwHCgDIAxJgZY7lGZIiIiIuIYT06jW2t7nmL5dmPMTC/KFBEREfkryG9X0gdxvuWkDVERERERyXu8mvpo5akeAsp7UaaIiIjIX0F+u0DIq6vRywMtgRPnUDHAfI/KFBERERHHeNXYnAQUtdb+z8VAxphZHpUpIiIi4jyrns2cs9Z2Ps1jwfzgroiIiIj4zo9J3UVERETkKF2NLiIiIiKSS9SzKSIiIuKj/HY1uno2RURERMQz6tkUERER8VF+G7OpxuZphEygv1t/TEQoIugIhNOPBB0BwIkTD3sPpQUdAYD9h38POgIHjxwOOoKcID0cDjqCE9LD6UFHAKBi1dZBRxAJnBqbIiIiIj7SmE0RERERkVyink0RERERH+W3XxBSz6aIiIiIeEaNTRERERHxjE6ji4iIiPgonM+mPlLPpoiIiIh4Rj2bIiIiIj7SBUIiIiIiIrlEPZsiIvL/7d15fFTlvcfxzy+AyqIFMRC2ioIbtdedqiAFFRBE0NZiKbi2xVas4kWtXqFqxVZtqcqtVytVUUQEUcpaClVUQJB9l0WUSlgkrUuVYg3J7/4xJzRigpLMOecx+b55zSszh8n8vnPOmSfPPGcTkQRpn00RERERkSzRyKaIiIhIgrTPZhXQtUtHVq96lbVr5nDzTQNSzZKTk8OC16czYcLIVOoPGHAlixbNYPHimVx77VWpZIAwlklaGZo2y+OFyU8ye8FUXpk/mR//5FIAfn7bdcyaO5EXZ09g7ITHaJzXKNYcDz9yH5s2LWLhwr/smdagwdeYPHkUy1fMYvLkUdSvf0isGfZWndeLEHOEkCGEHM2bN2XmjOdYseJlli17iZ9d+8PEapfXXvzirpuYs3Aas+ZO5Imn/5dDvnZwYpnSXh6h5ZD9Zx7ofgM1D2hWoWA5OTm8sXo253XvQ37+NubPm0a/S6/hjTc27P9rmVUkwmdcf/2POeXkEzj4kHpcdNEVFXqNGjk1KvR7bdoczVNP/Z6zzurJp58WMmnSU1x33W1s3Lhpv1+rsGh3hTJAdpdJCBka1t6/Rr5R41wa5+Wycvka6tary8xXnueKHwxg69btfPzRTgB+dPWlHH1sK26+4Y4v/bofF36yXznatWvLzp07GTHid5x2WlcAhg69hfff/5Bhwx5m0KCfUr/+1xgy5J4v/Zr/3l24XxlKq2rrxVc9RwgZspmjMq13Xl4jmuQ1YumyVdSrV5fXX5/OxRdfVaF5cWiW2osmzfKY88p8ioqKGHznIACG3j7sS73mP3Z9tN+5S1S19QJg96dbKv/HvZKOzj010c7X+oJFqb7nKjey2fa0k9i4cRNvv/0OhYWFjBs3kZ4XdE0lS7NmTejW7Rwef+KZVOofe2xrFixYyq5dn1BUVMTs2a/Tq1fy8yKEZZJmhh3vFrBy+RoAdn68kw3rNpLXtPGejiZAnbq1ifuL39y5C3jvvQ8/M+38Hp0ZPXo8AKNHj6fHBZ1jzVBadV8vQssRQoZQcmzfvoOly1YB8PHHO1m7dgNNm+YlUru89uKVl+ZSVFQEwOKFyxPLE8LyCCmHVEyV62w2bZbH5vytex7nb9mW2Idyb8N+ewe33no3xcXpjB6vXr2e9u3bcuih9ald+yDOO68TzZs3TTxHCMskhAwALb7ejOP/6ziWLFoOwK1DBrJk9Sy++70e3Hf38MTzNGqUy/btBQBs315Abu5hidUOYZmEkCGUHCFkCClHicMPb86JJxzPggVLE6+9d3tR4gf9vsuLM19NJEMoyyOUHNniCf9LWyydTTNbYmaDzaxVHK//BbU/Ny2NXQW6dz+HHQV/Z+nSlYnXLrFu3ZsMG/YIU6aMZtKkp1ixYg27d1d8c3hFhbBMQshQp24dHhs1nCG3/nrPqOav73qAk7/Rieefm8JV/fslmidtISyTEDKEkiOEDCHlAKhbtw7jxo5g0I2389FHHydau6z2AmDgjVeze/dunh83OZEcoSyPUHJIxcQ1stkAqA/MMrMFZnaDmX3hkJqZ9TezRWa2qLh45xc9vUxb8rfRotToXfNmTdi27d0KvVZlnHnGafQ4vwvr183j6VEP0aljO0Y+kfzI1ZNPjuXMM8+nc+fevP/+B7z55qbEM4SwTNLOULNmTR4fNZznx01m2uSZn/v/F56bQo+eyW3CLrFjRwF5ebkA5OXlUlDw98Rqp71MQskQSo4QMoSUo2bNmowbO4IxYybwpz/9OfHaZbUXvftcSOeunbjmxzclliWU5RFKjmwpdk/0lra4Opvvu/uN7v51YBBwFLDEzGaZWf/yfsndH3X3U9391JycuhUqvHDRMlq3PoKWLVtQq1YtevfuxeQpMyr2Liph8JB7OLLVaRx9zBn0u3QAs16eyxVXXpd4jtzchgC0aNGUXr3OY9y4iYlnCGGZpJ3h/t8PZcO6jfzhoZF7ph1x5OF77nftdjYbNrydWJ4S06b+lb59Lwagb9+LmTrl8x3huKS9TELJEEqOEDKElGPEo8NYu/ZNHnjw0cRrl9VedDqnPdcO/BGXff+n7Nq1fwcHVkYoyyOUHFIxcZ1nc894t7vPBmab2c+AzsAlQGyf3qKiIq4fOJhpU5+hRk4OI58cy5o16+MqF7wxYx7h0EMbUFhYyMCBv+CDD/6ZeIYQlkmaGdqefjK9+1zImlXreHH2BAB+9cv7+cFlF9O6dUuKi538zVu56YbbY80xcuRwzupwOg0bNmD9hnkMHXo/w4Y9zKhRD3HZ5b3J37yVfv2uiTVDadV9vQgtRwgZQsnR7szT6NfvYlauXMOihZkOzeAh9zB9+kux1y6vvbj7vts44IADGPenxwFYvGj5fp29oqJCWB4h5ciWEPajTFIspz4ys2fd/fuVeY2Knvoom7Jx6qNsqOipj7KpMqc+qmr299RHcdnfUx/FoTKnPhKJUxit9/6f+igOlTn1UVUUwqmPjjzspET7OG/9fWmVPPXRa2bWIqbXFhEREZGviLg2o98F3GJmG4ExwHPuXhBTLREREZGvDPfitCMkKq6RzbeA5mQ6nacAa8xsupldbmbpb1MQERERkUTENbLpnum2zwBmmFktoBvQB/gtkBtTXREREZGgFVezA4RiPxodwN0LgUnAJDOrHVNNEREREQlMXJ3NS8r7D3ffFVNNERERkeBVt6sfxbLPprt/dU9+JSIiIiJZE9fIpoiIiIiUobrtsxnX0egiIiIiIhrZFBEREUmS9tkUEREREckSjWyKiIiIJKi4mo1sqrO5D6GsDFbNLmsVul27P007AgA1TBsmRMoTRusNHxd+knYEkdSpsykiIiKSIA/m61AyNDQiIiIiIrHRyKaIiIhIgnQ0uoiIiIhIlqizKSIiIiKx0WZ0ERERkQTpcpUiIiIiIlmikU0RERGRBOkAIRERERGRLNHIpoiIiEiCQrlCYVI0sikiIiIisdHIpoiIiEiCtM9mFdC1S0dWr3qVtWvmcPNNA6p9jnXrXmPxopkseH06r82dmkqGEObFiEeHsTV/OcuWvpho3YcevpeNmxYwf+Gf90wbPOQGXnt9GnPmTeFPk54kL69RKjlK/Oz6H/HPnW9xaMMGsecokdby2FsI62YoOULIEEqOtDI8/Mh9bNq0iIUL/7JnWoMGX2Py5FEsXzGLyZNHUb/+IYnlgTCWR0g5ZP9Vuc5mTk4Owx+8mx4X9OObJ3Tikksu5Ljjjqq2OUp06dqbtt86jzPbnZ947VDmxVNPjeP8Hn0Trzv66fF858IrPzPtwQdGcOa3utP+jB5M//NL/PzW61LJAdCsWRPOPrs977yzJfYMpaW1PEoLZd0MIUcIGULJkWaGp0eN58ILL//MtEGDfsrLL7/GCf/ViZdffo1Bg65JJAuEsTxCypEtxXiit7RVuc5m29NOYuPGTbz99jsUFhYybtxEel7QtdrmCEEo82L2nNd57/0PEq/72tyFvP/eZ+t+9NHHe+7XqVsnkU0qZeUA+PW9gxky+J7EN+uktTxKC2XdDCFHCBlCyZFmhrlzF/Deex9+Ztr5PTozevR4AEaPHk+PCzonkgXCWB4h5ZCKqXKdzabN8ticv3XP4/wt22jaNK/a5gDAnalTRjPvtan88Ic/SLx8UPMiIENuH8SadXPofUlP7h56fyoZunU/h23btrNq5dpU6qctlHUzhBwhZAglRwgZSmvUKJft2wsA2L69gNzcwxKrHcq8CCVHtrh7ore0xdLZNLN6ZvZLM1ttZh+aWYGZzTezK+Kot1ftz01LY0aHkgOgY6fvcPoZ3enZ6zJ+cvXltG//rUTrhzQvQnLXncNoc0x7xo2dxNVXX5Z4/dq1D+Kmmwdw910PJF47FKGsmyHkCCFDKDlCyBCKUOZFKDmkYuIa2RwNvAV0Be4EhgOXAp3M7Ffl/ZKZ9TezRWa2qLh4Z4UKb8nfRovmTfc8bt6sCdu2vVuh16qMUHIAe+oWFPyDiZOmc9qpJyZaP6R5EaLnxk6k54XJbw464sjDObxlc+bOn8rKNa/SrFkes+dOplHj5EZN0hbKuhlCjhAyhJIjhAyl7dhRQF5eLgB5ebkUFPw9sdqhzItQcmRLsXuit7TF1dls6e4j3T3f3X8H9HT3DcCVwHfK+yV3f9TdT3X3U3Ny6lao8MJFy2jd+ghatmxBrVq16N27F5OnzKjYu6iEUHLUqVObevXq7rl/7jkdWL16XaIZQpkXIWnVquWe+93PP5f1695KPMOa1eto1bIt32zTgW+26cCWLds5q90F7Hg3uT9kaQtl3QwhRwgZQskRQobSpk39K337XgxA374XM3XKzMRqhzIvQskhFRPXeTZ3mll7d59jZj2B9wDcvdjKGgvPoqKiIq4fOJhpU5+hRk4OI58cy5o16+MsGXSOxo1zGTd2BAA1a9bg2bETmTHz5UQzhDIvnh71EN/ucAaHHXYom95axJ2//C1PjHw29rqPj3yQ9md9i4YNG/DG+rn8auiDdOnakaOOPoLiYmfzO1sYeN3gVHKMempc7HXLk9byKC2UdTOEHCFkCCVHmhlGjhzOWR1Op2HDBqzfMI+hQ+9n2LCHGTXqIS67vDf5m7fSr19yR6OHsDxCypEtHsAR4kmyOPZ5MLMTgBHA0cAq4Cp3X29muUAfdx/+Ra9R84Bm1WtJ7EONnPSP4yoqLk47QjDq1Dow7QjB+Ffhv9OOIBK0A2vWSjsC/95dmHaEoOz+dEusg15fRt06LRPt4+z816ZU33MsnU0AM2sNXAS0AAqBDcAYd/9wn78YUWfzP9TZDIs6m/+hzqbIvqmzGR51NpMX19Ho1wH/BxwInArUJtPpnGdmHeOoKSIiIvJVUN0OEIprn80fAye6e5GZ/Q6Y5u4dzewPwETgpJjqioiIiEhA4upslrx2EZnRzYMB3P0dM0t/m4KIiIhISqrbOULj6mz+EVhoZvOBDsC9ANEBQu/FVFNEREREAhPnAULfAI4DVrn7fl8LTwcI/YcOEAqLDhD6Dx0gJLJvOkAoPCEcIHTgQS0S7eP8+5PNqb7n2Daju/tqYHVcry8iIiIi4Ytzn00RERER2Ut122cz/e2zIiIiIlJlqbMpIiIikiB3T/T2RczsPDNbZ2Zvmtkt2X6/6myKiIiIVFNmVgN4COgGtAH6mFmbbNZQZ1NEREQkQZ7w7Qu0Bd5097fc/VPgWaBXNt5nCXU2RURERKqvZsDmUo/zo2lZE+zR6Nk4D5aZ9Xf3R7OR56ucIZQcIWQIJUcIGULJEUKGUHKEkCGUHCFkCCVHCBlCyRFChmxI+lyfZtYf6F9q0qOl5mNZWbJ6uHxVH9ns/8VPiV0IGSCMHCFkgDByhJABwsgRQgYII0cIGSCMHCFkgDByhJABwsgRQoavHHd/1N1PLXUr3WHPB1qUetwc2JrN+lW9sykiIiIi5VsIHGVmR5jZAcD3gUnZLBDsZnQRERERiZe77zaza4G/ADWAx6OrQGZNVe9shrBfRwgZIIwcIWSAMHKEkAHCyBFCBggjRwgZIIwcIWSAMHKEkAHCyBFChirH3acB0+J6fatul0wSERERkeRon00RERERiU2V7Gya2eNmtsPMVqWYoYWZzTKzN8xstZldn1KOg8xsgZktj3LcmUaOKEsNM1tqZlNSqr/JzFaa2TIzW5RGhihHfTMbb2Zro/XjjITrHxPNg5LbP81sYJIZSmW5IVovV5nZGDM7KIUM10f1Vyc5H8pqp8zsUDObaWYbop8NUsjwm2jdXGFmE8ysfpwZ9pHjrijDMjObYWZN08hR6v9uNDM3s8OSzmBmd5jZllKf2e4xZyizjTCzsaWmbTKzZTHn+Nxn08xOMLN5UVs+2cwOiTODZEnS1+dM6BqgHYCTgVUpZmgCnBzdPxhYD7RJIYcB9aL7tYDXgdNTmif/DTwDTEmp/ibgsLTWiVI5ngR+FN0/AKifYpYawHbg8BRqNwPeBmpHj8cBVySc4XhgFVCHzD7sfwWOSqj259op4D7gluj+LcC9KWToAtSM7t8bd4Z95Dik1P3rgEfSyBFNb0Hm4Im/xd2GlDMv7gBujPv9l5OnzDYCGAb8Isa6ZX42yRw5/e3oOVcBd6UxX3Tbv1uVHNl091eB91LOsM3dl0T3PwLeIMtn5P+SOdzdP44e1opuie+oa2bNgfOBPyZdOyTRt/AOwGMA7v6pu3+QYqRzgI3u/reU6tcEaptZTTJ/VLJ6brcv4Thgvrv/y913A68AFyVRuJx2qheZLyNEPy9MOoO7z4jmBcB8Mufci1U5Of5Z6mFdEmi39vG3437g5pQzpOVzbYSZGdAbGBNj3fI+m8cAr0bPmQl8N8YMkiVVsrMZGjNrCZxEZlQxjfo1os0dO4CZ7p5GjgfINNbFKdQu4cAMM1scXU0hDUcCBcAT0S4FfzSzuillgcz51OL8g1Eud98C/BZ4B9gGfOjuMxKOsQroYGYNzawO0J3Pntw4aY3dfRtkvrACjVLMApmRoz+nVdzM7jazzUBf4BcpZegJbHH35WnUL+XaaLeCx+PevWIvZbURZwHvuvuGGOuW99lcBfSMnvM90v28ypekzmbMzKwe8DwwcK9v6olx9yJ3P5HMCEVbMzs+yfpm1gPY4e6Lk6xbhnbufjLQDRhgZh1SyFCTzCayh939JGAnmc2liYtO3tsTeC6l+g3IjOQdATQF6ppZvyQzuPsbZDYVzwSmA8uB3fv8pWrCzG4jMy9Gp5XB3W9z9xZRhmuTrh91cm4jpY5uKQ8DrYATyXwxG5ZE0X20EX2I+UvqPj6bV5FpvxeT2UXt0zhzSHaosxkjM6tFpqM52t1fSDtPtLn2ZeC8hEu3A3qa2SbgWeBsM3s64Qy4+9bo5w5gAtA26QxkLguWX2p0eTyZzmcaugFL3P3dlOqfC7zt7gXuXgi8AJyZdAh3f8zdT3b3DmQ2X8Y5WvNF3jWzJgDRzx1phDCzy4EeQF93D+H8eM+QzubSVmS+DC2P2q/mwBIzy0syhLu/Gw0aFAMjSK7t+lwbEe3y8h1gbNzFy/psuvtad+/i7qeQ6fBujDuHVJ46mzGJ9ml5DHjD3X+XYo7ckqNJzaw2mT/wa5PM4O63untzd29JZpPMS+6e6AiWmdU1s4NL7pM5CCLxsxW4+3Zgs5kdE006B1iTdI5I7KMTX+Ad4HQzqxN9Xs4hs29zosysUfTz62T+iKY5TyYBl0f3LwcmJh3AzM4Dfg70dPd/JV2/VI6jSj3sScLtFoC7r3T3Ru7eMmq/8skc+Lk9yRwlX0AiF5Fc21VWG3EusNbd8+MuXtZns9S0HGAw8EjcOaTyquQVhMxsDNAROMzM8oHb3f2xhGO0Ay4FVpY6PcT/eOYs/UlqAjxpZjXIfLkY5+6pnHooZY2BCZk+DTWBZ9x9ekpZfgaMjjZRvQVcmXSAaPNgZ+DqpGuXcPfXzWw8sITM5rGlpHN1kOfNrCFQCAxw9/eTKFpWOwXcA4wzsx+S6Yx/L4UMtwIHAjOjz8t8d/9JCjm6R1/KiskcBR5rhvJyJP23o5x50dHMTiSz3/kmEvjc7qONSHI/7899NqPTIQ2I/v8F4ImEskgl6ApCIiIiIhIbbUYXERERkdiosykiIiIisVFnU0RERERio86miIiIiMRGnU0RERERiY06myKSCDMrMrNlZrbKzJ6LTq1S0dfqaGZTovs9zazcqzCZWX0zu6YCNe4wsxsrmlFERDLU2RSRpOxy9xPd/Xgyl5j7zHkTLWO/2yR3n+Tu9+zjKfWB/e5siohIdqizKSJpmA20NrOWZvaGmf0fmZO7tzCzLmY2z8yWRCOg9SBzZRszW2tmc8hcTYRo+hVm9vvofmMzm2Bmy6PbmWROlN4qGlX9TfS8m8xsoZmtMLM7S73WbWa2zsz+ChyDiIhUmjqbIpKo6NrK3YCV0aRjgKfc/SRgJ5lL0J3r7icDi4D/NrODyFwT+gLgLKC8a1MPB15x9xPIXHN+NXALsDEaVb3JzLoAR5G5vvSJwClm1sHMTiFzdZSTyHRmT8vyWxcRqZaq5OUqRSRItUtdunU28BjQFPibu8+Ppp8OtAHmRpdKPACYBxwLvO3uGwDM7Gmgfxk1zgYuA3D3IuBDM2uw13O6RLel0eN6ZDqfBwMTSq4HbmaTKvVuRUQEUGdTRJKzy91PLD0h6lDuLD0JmOnuffZ6Xsl1obPBgF+7+x/2qjEwizVERCSizegiEpL5QDszaw1gZnXM7GhgLXCEmbWKntennN9/Efhp9Ls1zOwQ4CMyo5Yl/gJcVWpf0GZm1gh4FbjIzGqb2cFkNtmLiEglqbMpIsFw9wLgCmCMma0g0/k81t0/IbPZfGp0gNDfynmJ64FOZrYSWAx8w93/QWaz/Coz+427zwCeAeZFzxsPHOzuS4CxwDLgeTKb+kVEpJLMXVuNRERERCQeGtkUERERkdiosykiIiIisVFnU0RERERio86miIiIiMRGnU0RERERiY06myIiIiISG3U2RURERCQ26myKiIiISGz+H8VUD58fca0DAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 864x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# creating a confusion matrix \n",
    "lgc_cm = confusion_matrix(y_test, lgcclf.predict(X_test)) \n",
    "class_names = [1,2,3,4,5,6,7,8,9,10,12,13,14,15,77,99]\n",
    "fig, ax = plt.subplots(figsize=(12,10))\n",
    "sns.heatmap(lgc_cm, annot=True, fmt='d', xticklabels=class_names, yticklabels=class_names)\n",
    "plt.ylabel('Actual')\n",
    "plt.xlabel('Predicted')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### k - Nearest Neighbor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Nearest Neighbor\n",
    "def kNNClassifier(nNeighbors):\n",
    "    knn = KNeighborsClassifier(n_neighbors=nNeighbors)\n",
    "    knn.fit(X_train, y_train) \n",
    "    acc_train = accuracy_score(y_train, knn.predict(X_train))\n",
    "    acc_test = accuracy_score(y_test, knn.predict(X_test))\n",
    "    print(\"Train Accuracy : \", acc_train)\n",
    "    #print(\"Validation Accuracy : \", accuracy_score(y_valid, clf.predict(X_valid)))\n",
    "    print(\"Test Accuracy : \", acc_test)\n",
    "    return acc_train, acc_test, knn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Accuracy :  0.9559680883706658\n",
      "Test Accuracy :  0.699713672154617\n",
      "Wall time: 284 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "num_neigh = 1 #number of neighbors\n",
    "knn_train, knn_test, knnclf = kNNClassifier(num_neigh)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# creating a confusion matrix \n",
    "knn_cm = confusion_matrix(y_test, knnclf.predict(X_test)) \n",
    "class_names = [1,2,3,4,5,6,7,8,9,10,12,13,14,15,77,99]\n",
    "fig, ax = plt.subplots(figsize=(12,10))\n",
    "sns.heatmap(knn_cm, annot=True, fmt='d', xticklabels=class_names, yticklabels=class_names)\n",
    "plt.ylabel('Actual')\n",
    "plt.xlabel('Predicted')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Gaussian Naive Bayes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Gaussian Naive Bayes\n",
    "def GNBClassifier():\n",
    "    gnb = GaussianNB()\n",
    "    gnb.fit(X_train, y_train) \n",
    "    acc_train = accuracy_score(y_train, gnb.predict(X_train))\n",
    "    acc_test = accuracy_score(y_test, gnb.predict(X_test))\n",
    "    print(\"Train Accuracy : \", acc_train)\n",
    "    #print(\"Validation Accuracy : \", accuracy_score(y_valid, clf.predict(X_valid)))\n",
    "    print(\"Test Accuracy : \", acc_test)\n",
    "    return acc_train, acc_test, gnb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Accuracy :  0.19254372506903958\n",
      "Test Accuracy :  0.19577666428060128\n",
      "Wall time: 46.9 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "gnb_train, gnb_test, gnbclf = GNBClassifier()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# creating a confusion matrix \n",
    "gnb_cm = confusion_matrix(y_test, gnbclf.predict(X_test)) \n",
    "class_names = [1,2,3,4,5,6,7,8,9,10,12,13,14,15,77,99]\n",
    "fig, ax = plt.subplots(figsize=(12,10))\n",
    "sns.heatmap(gnb_cm, annot=True, fmt='d', xticklabels=class_names, yticklabels=class_names)\n",
    "plt.ylabel('Actual')\n",
    "plt.xlabel('Predicted')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### MLP Classifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "def MLPGridSearch():\n",
    "    mlpsearch = MLPClassifier(solver='lbfgs', alpha=1e-5, random_state=0)\n",
    "    #param_grid = { 'hidden_layer_sizes':np.arange(10, 15)}\n",
    "    param_grid = { 'hidden_layer_sizes':[(100,100,100,100), (200,200,200,200), (400,400,400,400)]}\n",
    "    CV_mlp = GridSearchCV(estimator=mlpsearch, param_grid=param_grid, cv=5)\n",
    "    CV_mlp.fit(X_train, y_train)\n",
    "    return CV_mlp.best_params_, CV_mlp.best_score_\n",
    "\n",
    "def MultiLayerPerpClassifier():\n",
    "    #mlp = MLPClassifier(solver='lbfgs', alpha=1e-5, hidden_layer_sizes=(500, 500, 500, 500), random_state=0)\n",
    "    mlp = MLPClassifier(solver='lbfgs', alpha=1e-5, hidden_layer_sizes=(400,400,400,400), random_state=0)\n",
    "    #mlp = MLPClassifier(solver='lbfgs', alpha=1e-5, hidden_layer_sizes=(12), random_state=0)\n",
    "    mlp.fit(X_train, y_train) \n",
    "    acc_train = accuracy_score(y_train, mlp.predict(X_train))\n",
    "    acc_test = accuracy_score(y_test, mlp.predict(X_test))\n",
    "    print(\"Train Accuracy : \", acc_train)\n",
    "    #print(\"Validation Accuracy : \", accuracy_score(y_valid, clf.predict(X_valid)))\n",
    "    print(\"Test Accuracy : \", acc_test)\n",
    "    return acc_train, acc_test, mlp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Accuracy :  0.7387235348266339\n",
      "Test Accuracy :  0.5508231925554761\n",
      "Wall time: 3min 51s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "#mlp_best_params, mlp_best_score = MLPGridSearch()\n",
    "mlp_train, mlp_test, mlpclf = MultiLayerPerpClassifier()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# creating a confusion matrix \n",
    "mlp_cm = confusion_matrix(y_test, mlpclf.predict(X_test)) \n",
    "class_names = [1,2,3,4,5,6,7,8,9,10,12,13,14,15,77,99]\n",
    "fig, ax = plt.subplots(figsize=(12,10))\n",
    "sns.heatmap(mlp_cm, annot=True, fmt='d', xticklabels=class_names, yticklabels=class_names)\n",
    "plt.ylabel('Actual')\n",
    "plt.xlabel('Predicted')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Conclusions\n",
    "____\n",
    "* Predicted Accuracy for Different Models on Test Set:\n",
    "\n",
    "| Machine Learning Model \t| Accuracy \t| Computational Cost |\n",
    "|------------------------\t|----------\t|----------\n",
    "| Random Forest          \t| 0.71    \t| 4.9 s\n",
    "| Gradient Boosting                  \t| 0.70     \t| 162 s |\n",
    "| SVM     \t| 0.64    \t| 17 s |\n",
    "| Logistic Regression \t| 0.23    \t| 1.01 s |\n",
    "| k-Nearest Neighbor \t| 0.70     \t|284 ms  |\n",
    "| Naive-Bayes \t| 0.19    \t|46.9 ms  |\n",
    "| Multi-Layer Perceptron \t| 0.55     \t| 231 s  |\n",
    "\n",
    "* From the table it can be observed that the **Random-Forest model** has the highest accuracy in comparison to the other models <br>\n",
    "\n",
    "* The nearest neighbor classifier also performs very well in comparison to the other models is computationally cheaper in comparison to the random-forest model. The lower cost is because the size of the test set is not very big.\n",
    "\n",
    "* From the feature importance values obtained from the random forest and gradient boosting models it is observed that some of the features which signficantly affect the prediction of the class of the household income are **household reference person age,  ethnicity of participant, education level of household reference person**\n",
    "\n",
    "* The performance of all the models is significantly improved by excluding the features with the lowest feature importance obtained from the random forest and gradient boosting models\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Recommendations\n",
    "____\n",
    "* Since the distribution of the number of samples for each class of the household income is not equal, it is expected that the performance of the models can be improved by gathering more data so that we have a more balanced distribution of the number of samples for each class."
   ]
  }
 ],
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