IDEAR/IDEAR.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Interactive Data Exploration, Analysis, and Reporting\n",
    "\n",
    "- Author: Team Data Science Process from Microsoft \n",
    "- Date: 2017/03\n",
    "- Supported Data Sources: CSV files on the machine where the Jupyter notebook runs or data stored in SQL server\n",
    "- Output: IDEAR_Report.ipynb\n",
    "\n",
    "\n",
    "This is the **Interactive Data Exploration, Analysis and Reporting (IDEAR)** in _**Python**_ running on Jupyter Notebook. The data can be stored in CSV file on the machine where the Jupyter notebook runs or from a query running against a SQL server. A yaml file has to be pre-configured before running this tool to provide information about the data. \n",
    "\n",
    "## Step 1: Configure and Set up IDEAR\n",
    "\n",
    "Before start utilitizing the functionalities provided by IDEAR, you need to first [configure and set up](#setup) the utilities by providing the yaml file and load necessary Python modules and libraries. \n",
    "\n",
    "## Step 2: Start using IDEAR\n",
    "This tool provides various functionalities to help users explore the data and get insights through interactive visualization and statistical testing. \n",
    "\n",
    "- [Read and Summarize the data](#read and summarize)\n",
    "\n",
    "- [Extract Descriptive Statistics of Data](#descriptive statistics)\n",
    "\n",
    "- [Explore Individual Variables](#individual variables)\n",
    "\n",
    "- [Explore Interactions between Variables](#multiple variables)\n",
    "\n",
    "    - [Rank variables](#rank variables)\n",
    "    \n",
    "    - [Interaction between two categorical variables](#two categorical)\n",
    "    \n",
    "    - [Interaction between two numerical variables](#two numerical)\n",
    "\n",
    "    - [Interaction between numerical and categorical variables](#numerical and categorical)\n",
    "\n",
    "    - [Interaction between two numerical variables and a categorical variable](#two numerical and categorical)\n",
    "\n",
    "- [Visualize High Dimensional Data via Projecting to Lower Dimension Principal Component Spaces](#pca)\n",
    "\n",
    "- [Generate Data Report](#report)\n",
    "\n",
    "After you are done with exploring the data interactively, you can choose to [show/hide the source code](#show hide codes) to make your notebook look neater. \n",
    "\n",
    "**Note**:\n",
    "\n",
    "- Change the working directory and yaml file before running IDEAR in Jupyter Notebook.\n",
    "\n",
    "- Run the cells and click *Export* button to export the code that generates the visualization/analysis result to temporary Jupyter notebooks.\n",
    "\n",
    "- Run the last cell and click [***Generate Final Report***](#report) to create *IDEAR_Report.ipynb* in the working directory. _If you do not export codes in some sections, you may see some warnings complaining that some temporary Jupyter Notebook files are missing_. \n",
    "\n",
    "- Upload *IDEAR_Report.ipynb* to Jupyter Notebook server, and run it to generate report."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <a name=\"setup\"></a>Global Configuration and Setting Up"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Set the working directory as the directory where ReportMagics.py stays\n",
    "# Use \\\\ in your path\n",
    "import os\n",
    "#workingDir = 'C:\\\\GitRepos\\\\DGADSCommon\\\\Utilities\\\\DataScienceUtilities\\\\DataReport-Utils\\\\Python'\n",
    "workingDir = 'C:\\\\Ghana\\\\Ghana hackfest\\\\Ghana hackfest\\\\IDEAR\\\\Azure-TDSP-Utilities\\\\DataScienceUtilities\\\\DataReport-Utils\\\\Python'\n",
    "os.chdir(workingDir)\n",
    "\n",
    "from ReportMagics import *\n",
    "\n",
    "merged_report ='IDEAR_Report.ipynb'\n",
    "%reset_all"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%%add_conf_code_to_report\n",
    "import os\n",
    "#workingDir = 'C:\\\\GitRepos\\\\DGADSCommon\\\\Utilities\\\\DataScienceUtilities\\\\DataReport-Utils\\\\Python'\n",
    "workingDir = 'C:\\\\Ghana\\\\Ghana hackfest\\\\Ghana hackfest\\\\IDEAR\\\\Azure-TDSP-Utilities\\\\DataScienceUtilities\\\\DataReport-Utils\\\\Python'\n",
    "os.chdir(workingDir)\n",
    "\n",
    "conf_file = '.\\\\para-short.yaml'\n",
    "Sample_Size = 10000\n",
    "\n",
    "export_dir = '.\\\\tmp\\\\'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Import necessary packages and set up environment parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\rinaa\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\statsmodels\\compat\\pandas.py:56: FutureWarning: The pandas.core.datetools module is deprecated and will be removed in a future version. Please use the pandas.tseries module instead.\n",
      "  from pandas.core import datetools\n"
     ]
    }
   ],
   "source": [
    "%%add_conf_code_to_report\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import os\n",
    "#os.chdir(workingDir)\n",
    "import collections\n",
    "import matplotlib\n",
    "import io\n",
    "import sys\n",
    "import operator\n",
    "\n",
    "import nbformat as nbf\n",
    "from IPython.core.display import HTML\n",
    "from IPython.display import display\n",
    "from ipywidgets import interact, interactive,fixed\n",
    "from IPython.display import Javascript, display,HTML\n",
    "from ipywidgets import widgets, VBox\n",
    "import ipywidgets\n",
    "import IPython\n",
    "from IPython.display import clear_output\n",
    "import scipy.stats as stats\n",
    "from statsmodels.graphics.mosaicplot import mosaic\n",
    "import statsmodels.api as sm\n",
    "from statsmodels.formula.api import ols\n",
    "import os\n",
    "import errno\n",
    "import seaborn as sns\n",
    "from string import Template\n",
    "from functools import partial\n",
    "from collections import OrderedDict\n",
    "\n",
    "# Utility Classes\n",
    "from ConfUtility import * \n",
    "from ReportGeneration import *\n",
    "from UniVarAnalytics import *\n",
    "from MultiVarAnalytics import *\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "#DEBUG=0\n",
    "\n",
    "font={'family':'normal','weight':'normal','size':8}\n",
    "matplotlib.rc('font',**font)\n",
    "matplotlib.rcParams['figure.figsize'] = (12.0, 5.0)\n",
    "matplotlib.rc('xtick', labelsize=9) \n",
    "matplotlib.rc('ytick', labelsize=9)\n",
    "matplotlib.rc('axes', labelsize=10)\n",
    "matplotlib.rc('axes', titlesize=10)\n",
    "sns.set_style('whitegrid')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### Define some functions for generating reports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%%add_conf_code_to_report\n",
    "\n",
    "if not os.path.exists(export_dir):\n",
    "    os.makedirs(export_dir)\n",
    "    \n",
    "def gen_report(conf_md,conf_code, md, code, filename):\n",
    "    ReportGeneration.write_report(conf_md, conf_code, md, code, report_name=filename)\n",
    "\n",
    "def translate_code_commands(cell, exported_cols, composite=False):    \n",
    "    new_code_store = []\n",
    "    exported_cols = [each for each in exported_cols if each!='']   \n",
    "    for each in exported_cols:       \n",
    "        w,x,y = each.split(',')\n",
    "        with open('log.txt','w') as fout:\n",
    "            fout.write('Processing call for the column {}'.format(each))\n",
    "        temp=cell[0]\n",
    "\n",
    "        new_line = temp.replace('interactive','apply').replace(\n",
    "            \"df=fixed(df)\",\"df\").replace(\"filename=fixed(filename)\",\"'\"+ReportMagic.var_files+\"'\").replace(\n",
    "            \"col1=w1\",\"'\"+w+\"'\").replace(\"col2=w2\",\"'\"+x+\"'\").replace(\"col3=w3\",\"'\"+y+\"'\").replace(\n",
    "            \"col3=fixed(w3)\",\"'\"+y+\"'\").replace(\n",
    "            \"Export=w_export\",\"False\").replace(\"conf_dict=fixed(conf_dict)\",\"conf_dict\")       \n",
    "        new_line = new_line.replace(\"df,\",\"[df,\")\n",
    "        new_line = new_line[:len(new_line)-1]+\"])\"\n",
    "        new_line = new_line.replace(\"apply(\",\"\").replace(\", [\", \"(*[\")\n",
    "        new_code_store.append(new_line)        \n",
    "    return new_code_store\n",
    "\n",
    "def add_to_report(section='', task=''):\n",
    "    print ('Section {}, Task {} added for report generation'.format(section ,task))\n",
    "\n",
    "def trigger_report(widgets,export_cols_file, output_report, no_widgets=1, md_text=''):\n",
    "    exported_cols = []\n",
    "    with open(export_cols_file,'r') as fin:\n",
    "        for each in fin:\n",
    "            each = each.strip()\n",
    "            if each and not each.isspace():\n",
    "                exported_cols.append(each)\n",
    "                \n",
    "    exported_cols = list(set(exported_cols))\n",
    "    conf_md, conf_code, md, code=%show_report \n",
    "    md = md_text\n",
    "    cell = code\n",
    "    new_code_store = translate_code_commands(cell,exported_cols)\n",
    "    gen_report(conf_md,conf_code, md, new_code_store, filename=export_dir+output_report)\n",
    "    \n",
    "def silentremove(filename):\n",
    "    try:\n",
    "        os.remove(filename)\n",
    "    except OSError as e: # this would be \"except OSError, e:\" before Python 2.6\n",
    "        if e.errno != errno.ENOENT: # errno.ENOENT = no such file or directory\n",
    "            raise # re-raise exception if a different error occured\n",
    "\n",
    "def handle_change(value):\n",
    "    w_export.value=False\n",
    "\n",
    "def getWidgetValue(w):\n",
    "    w_value = ''\n",
    "    try:\n",
    "        w_value = w.value\n",
    "    except:\n",
    "        pass    \n",
    "    return w_value\n",
    "\n",
    "def handle_export(widget, w1, w2, w3, export_filename='temp.ipynb',md_text=''):    \n",
    "    print ('Export is successful!')\n",
    "    w1_value, w2_value, w3_value = \\\n",
    "        getWidgetValue(w1),getWidgetValue(w2),getWidgetValue(w3)\n",
    "    st = ','.join(str(each) for each in [w1_value, w2_value, w3_value])\n",
    "    with open(filename,'a') as fout:\n",
    "        fout.write(st+'\\n')\n",
    "    trigger_report(w1_value, filename, export_filename, False, md_text=md_text)  \n",
    "    \n",
    "            "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <a name=\"read and summarize\"></a> Read and Summarize the Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Read data and infer column types"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ul><li>Categorical Columns are year</li><li>Target variable is distance_nearestlargemine</li><li>Numerical Columns are year, \n",
       "x, \n",
       "y, \n",
       "expenditure, \n",
       "income, \n",
       "ill_or_injured, \n",
       "malaria, \n",
       "forestloss, \n",
       "nightlights, \n",
       "distance_nearestlargemine</li></ul>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%add_conf_code_to_report\n",
    "\n",
    "conf_dict = ConfUtility.parse_yaml(conf_file)\n",
    "\n",
    "# Read in data from local file or SQL server\n",
    "if 'DataSource' not in conf_dict:\n",
    "    df=pd.read_csv(conf_dict['DataFilePath'][0], skipinitialspace=True)\n",
    "else:\n",
    "    import pyodbc\n",
    "    cnxn = pyodbc.connect('driver=ODBC Driver 11 for SQL Server;server={};database={};Uid={};Pwd={}'.format(\n",
    "            conf_dict['Server'], conf_dict['Database'],conf_dict['Username'],conf_dict['Password']))\n",
    "    df = pd.read_sql(conf_dict['Query'],cnxn)\n",
    "\n",
    "# Making sure that we are not reading any extra column\n",
    "df = df[[each for each in df.columns if 'Unnamed' not in each]]\n",
    "\n",
    "# Sampling Data if data size is larger than 10k\n",
    "df0 = df # df0 is the unsampled data. Will be used in data exploration and analysis where sampling is not needed\n",
    "         # However, keep in mind that your final report will always be based on the sampled data. \n",
    "if Sample_Size < df.shape[0]:\n",
    "    df = df.sample(Sample_Size)\n",
    "\n",
    "# change float data types\n",
    "if 'FloatDataTypes' in conf_dict:   \n",
    "    for col_name in conf_dict['FloatDataTypes']:\n",
    "        df[col_name] = df[col_name].astype(float)      \n",
    "        \n",
    "# Getting the list of categorical columns if it was not there in the yaml file\n",
    "if 'CategoricalColumns' not in conf_dict:\n",
    "    conf_dict['CategoricalColumns'] = list(set(list(df.select_dtypes(exclude=[np.number]).columns)))\n",
    "\n",
    "# Getting the list of numerical columns if it was not there in the yaml file\n",
    "if 'NumericalColumns' not in conf_dict:\n",
    "    conf_dict['NumericalColumns'] = list(df.select_dtypes(include=[np.number]).columns)    \n",
    "\n",
    "# Exclude columns that we do not need\n",
    "if 'ColumnsToExclude' in conf_dict:\n",
    "    conf_dict['CategoricalColumns'] = list(set(conf_dict['CategoricalColumns'])-set(conf_dict['ColumnsToExclude']))\n",
    "    conf_dict['NumericalColumns'] = list(set(conf_dict['NumericalColumns'])-set(conf_dict['ColumnsToExclude']))\n",
    "\n",
    "# Ordering the categorical variables according to the number of unique categories\n",
    "#filtered_cat_columns = []\n",
    "#temp_dict = {}\n",
    "#for cat_var in conf_dict['CategoricalColumns']:\n",
    "#    temp_dict[cat_var] = len(np.unique(df[cat_var]))\n",
    "#sorted_x = sorted(temp_dict.items(), key=operator.itemgetter(0), reverse=True)\n",
    "#conf_dict['CategoricalColumns'] = [x for (x,y) in sorted_x]\n",
    "\n",
    "ConfUtility.dict_to_htmllist(conf_dict,['Target','CategoricalColumns','NumericalColumns'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Print the first n (n=5 by default) rows of the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a1dfc2d1b57241f68da38be7d63f1ae9",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "A Jupyter Widget"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%add_conf_code_to_report\n",
    "def custom_head(df,NoOfRows):\n",
    "    return HTML(df.head(NoOfRows).style.set_table_attributes(\"class='table'\").render())\n",
    "i = interact(custom_head,df=fixed(df0), NoOfRows=ipywidgets.IntSlider(min=0, max=30, step=1, \\\n",
    "                                                                     value=5, description='Number of Rows'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Print the dimensions of the data (rows, columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The data has 1593 Rows and 10 columns\n"
     ]
    }
   ],
   "source": [
    "%%add_conf_code_to_report\n",
    "print ('The data has {} Rows and {} columns'.format(df0.shape[0],df0.shape[1]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Print the column names of the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The column names are:year,x,y,expenditure,income,ill_or_injured,malaria,forestloss,nightlights,distance_nearestlargemine\n"
     ]
    }
   ],
   "source": [
    "%%add_conf_code_to_report\n",
    "col_names = ','.join(each for each in list(df.columns))\n",
    "print(\"The column names are:\" + col_names)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### Print the column types"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The types of columns are:\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "year                         float64\n",
       "x                            float64\n",
       "y                            float64\n",
       "expenditure                  float64\n",
       "income                       float64\n",
       "ill_or_injured               float64\n",
       "malaria                      float64\n",
       "forestloss                   float64\n",
       "nightlights                  float64\n",
       "distance_nearestlargemine    float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%add_conf_code_to_report\n",
    "print(\"The types of columns are:\")\n",
    "df.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <a name=\"individual variable\"></a>Extract Descriptive Statistics of Each Column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%%add_conf_code_to_report\n",
    "def num_missing(x):\n",
    "    return len(x.index)-x.count()\n",
    "\n",
    "def num_unique(x):\n",
    "    return len(np.unique(x))\n",
    "\n",
    "temp_df = df0.describe().T\n",
    "missing_df = pd.DataFrame(df0.apply(num_missing, axis=0)) \n",
    "missing_df.columns = ['missing']\n",
    "unq_df = pd.DataFrame(df0.apply(num_unique, axis=0))\n",
    "unq_df.columns = ['unique']\n",
    "types_df = pd.DataFrame(df0.dtypes)\n",
    "types_df.columns = ['DataType']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Print the descriptive statistics of numerical columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "      <th>missing</th>\n",
       "      <th>unique</th>\n",
       "      <th>DataType</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <td>1590.0</td>\n",
       "      <td>1685.407547</td>\n",
       "      <td>718.072947</td>\n",
       "      <td>98.000000</td>\n",
       "      <td>2005.000000</td>\n",
       "      <td>2012.000000</td>\n",
       "      <td>2013.000000</td>\n",
       "      <td>2013.000000</td>\n",
       "      <td>3</td>\n",
       "      <td>9</td>\n",
       "      <td>float64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x</th>\n",
       "      <td>1593.0</td>\n",
       "      <td>-1.113771</td>\n",
       "      <td>1.033284</td>\n",
       "      <td>-3.203450</td>\n",
       "      <td>-1.901096</td>\n",
       "      <td>-1.012990</td>\n",
       "      <td>-0.265932</td>\n",
       "      <td>1.192945</td>\n",
       "      <td>0</td>\n",
       "      <td>1545</td>\n",
       "      <td>float64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>y</th>\n",
       "      <td>1593.0</td>\n",
       "      <td>7.386736</td>\n",
       "      <td>1.894350</td>\n",
       "      <td>4.761240</td>\n",
       "      <td>5.942012</td>\n",
       "      <td>6.701314</td>\n",
       "      <td>8.779180</td>\n",
       "      <td>11.127133</td>\n",
       "      <td>0</td>\n",
       "      <td>1545</td>\n",
       "      <td>float64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>expenditure</th>\n",
       "      <td>1590.0</td>\n",
       "      <td>1144.462657</td>\n",
       "      <td>863.878698</td>\n",
       "      <td>80.285172</td>\n",
       "      <td>547.153865</td>\n",
       "      <td>907.142060</td>\n",
       "      <td>1473.797550</td>\n",
       "      <td>7677.353500</td>\n",
       "      <td>3</td>\n",
       "      <td>1593</td>\n",
       "      <td>float64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>income</th>\n",
       "      <td>1590.0</td>\n",
       "      <td>1618.409123</td>\n",
       "      <td>2776.352511</td>\n",
       "      <td>-35.787189</td>\n",
       "      <td>350.336130</td>\n",
       "      <td>718.863950</td>\n",
       "      <td>1879.633350</td>\n",
       "      <td>61162.129000</td>\n",
       "      <td>3</td>\n",
       "      <td>1593</td>\n",
       "      <td>float64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ill_or_injured</th>\n",
       "      <td>1590.0</td>\n",
       "      <td>0.192963</td>\n",
       "      <td>0.121365</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.101038</td>\n",
       "      <td>0.171429</td>\n",
       "      <td>0.267536</td>\n",
       "      <td>0.628571</td>\n",
       "      <td>3</td>\n",
       "      <td>846</td>\n",
       "      <td>float64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>malaria</th>\n",
       "      <td>1590.0</td>\n",
       "      <td>0.414778</td>\n",
       "      <td>0.117298</td>\n",
       "      <td>0.091799</td>\n",
       "      <td>0.348880</td>\n",
       "      <td>0.422190</td>\n",
       "      <td>0.501839</td>\n",
       "      <td>0.683214</td>\n",
       "      <td>3</td>\n",
       "      <td>1565</td>\n",
       "      <td>float64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>forestloss</th>\n",
       "      <td>1590.0</td>\n",
       "      <td>0.003691</td>\n",
       "      <td>0.006236</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000037</td>\n",
       "      <td>0.000898</td>\n",
       "      <td>0.004506</td>\n",
       "      <td>0.072279</td>\n",
       "      <td>3</td>\n",
       "      <td>1293</td>\n",
       "      <td>float64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nightlights</th>\n",
       "      <td>1590.0</td>\n",
       "      <td>5.440169</td>\n",
       "      <td>11.395047</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.046607</td>\n",
       "      <td>0.855386</td>\n",
       "      <td>3.596005</td>\n",
       "      <td>60.936462</td>\n",
       "      <td>3</td>\n",
       "      <td>1157</td>\n",
       "      <td>float64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>distance_nearestlargemine</th>\n",
       "      <td>1593.0</td>\n",
       "      <td>104754.233128</td>\n",
       "      <td>99576.183657</td>\n",
       "      <td>676.799930</td>\n",
       "      <td>26915.229000</td>\n",
       "      <td>63871.512000</td>\n",
       "      <td>175418.700000</td>\n",
       "      <td>369073.840000</td>\n",
       "      <td>0</td>\n",
       "      <td>1552</td>\n",
       "      <td>float64</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            count           mean           std         min  \\\n",
       "year                       1590.0    1685.407547    718.072947   98.000000   \n",
       "x                          1593.0      -1.113771      1.033284   -3.203450   \n",
       "y                          1593.0       7.386736      1.894350    4.761240   \n",
       "expenditure                1590.0    1144.462657    863.878698   80.285172   \n",
       "income                     1590.0    1618.409123   2776.352511  -35.787189   \n",
       "ill_or_injured             1590.0       0.192963      0.121365    0.000000   \n",
       "malaria                    1590.0       0.414778      0.117298    0.091799   \n",
       "forestloss                 1590.0       0.003691      0.006236    0.000000   \n",
       "nightlights                1590.0       5.440169     11.395047    0.000000   \n",
       "distance_nearestlargemine  1593.0  104754.233128  99576.183657  676.799930   \n",
       "\n",
       "                                    25%           50%            75%  \\\n",
       "year                        2005.000000   2012.000000    2013.000000   \n",
       "x                             -1.901096     -1.012990      -0.265932   \n",
       "y                              5.942012      6.701314       8.779180   \n",
       "expenditure                  547.153865    907.142060    1473.797550   \n",
       "income                       350.336130    718.863950    1879.633350   \n",
       "ill_or_injured                 0.101038      0.171429       0.267536   \n",
       "malaria                        0.348880      0.422190       0.501839   \n",
       "forestloss                     0.000037      0.000898       0.004506   \n",
       "nightlights                    0.046607      0.855386       3.596005   \n",
       "distance_nearestlargemine  26915.229000  63871.512000  175418.700000   \n",
       "\n",
       "                                     max  missing  unique DataType  \n",
       "year                         2013.000000        3       9  float64  \n",
       "x                               1.192945        0    1545  float64  \n",
       "y                              11.127133        0    1545  float64  \n",
       "expenditure                  7677.353500        3    1593  float64  \n",
       "income                      61162.129000        3    1593  float64  \n",
       "ill_or_injured                  0.628571        3     846  float64  \n",
       "malaria                         0.683214        3    1565  float64  \n",
       "forestloss                      0.072279        3    1293  float64  \n",
       "nightlights                    60.936462        3    1157  float64  \n",
       "distance_nearestlargemine  369073.840000        0    1552  float64  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%add_conf_code_to_report\n",
    "summary_df = temp_df.join(missing_df).join(unq_df).join(types_df)\n",
    "summary_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Print the descriptive statistics of categorical columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>missing</th>\n",
       "      <th>unique</th>\n",
       "      <th>DataType</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <td>3</td>\n",
       "      <td>9</td>\n",
       "      <td>float64</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      missing  unique DataType\n",
       "year        3       9  float64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%add_conf_code_to_report\n",
    "col_names = list(types_df.index) #Get all col names\n",
    "num_cols = len(col_names)\n",
    "index = range(num_cols)\n",
    "cat_index = []\n",
    "for i in index: #Find the indices of columns in Categorical columns\n",
    "    if col_names[i] in conf_dict['CategoricalColumns']:\n",
    "        cat_index.append(i)\n",
    "summary_df_cat = missing_df.join(unq_df).join(types_df.iloc[cat_index], how='inner') #Only summarize categorical columns\n",
    "summary_df_cat"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <a name=\"individual variables\"></a>Explore Individual Variables"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Explore the target variable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "Button(description='Export', style=ButtonStyle()) cannot be transformed to a widget",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-15-160c3bb22619>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mi\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0minteractive\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mNumericAnalytics\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcustom_barplot\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdf\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mfixed\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfilename\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mfixed\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfilename\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m                                                    \u001b[0mcol1\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mw1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mExport\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mw_export\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\ipywidgets\\widgets\\interaction.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, _interactive__interact_f, _interactive__options, **kwargs)\u001b[0m\n\u001b[0;32m    192\u001b[0m             \u001b[0mgetcallargs\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mf\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[1;33m{\u001b[0m\u001b[0mn\u001b[0m\u001b[1;33m:\u001b[0m\u001b[0mv\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mn\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mv\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0m_\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mnew_kwargs\u001b[0m\u001b[1;33m}\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    193\u001b[0m         \u001b[1;31m# Now build the widgets from the abbreviations.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 194\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mkwargs_widgets\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mwidgets_from_abbreviations\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnew_kwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    195\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    196\u001b[0m         \u001b[1;31m# This has to be done as an assignment, not using self.children.append,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\ipywidgets\\widgets\\interaction.py\u001b[0m in \u001b[0;36mwidgets_from_abbreviations\u001b[1;34m(self, seq)\u001b[0m\n\u001b[0;32m    292\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0misinstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mwidget\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mValueWidget\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mor\u001b[0m \u001b[0misinstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mwidget\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfixed\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    293\u001b[0m                 \u001b[1;32mif\u001b[0m \u001b[0mwidget\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 294\u001b[1;33m                     \u001b[1;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"{!r} cannot be transformed to a widget\"\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mabbrev\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    295\u001b[0m                 \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    296\u001b[0m                     \u001b[1;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"{!r} is not a ValueWidget\"\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mwidget\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mValueError\u001b[0m: Button(description='Export', style=ButtonStyle()) cannot be transformed to a widget"
     ]
    },
    {
     "ename": "AttributeError",
     "evalue": "'int' object has no attribute 'children'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-15-7e2825a30b98>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m     40\u001b[0m     \u001b[0mget_ipython\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmagic\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'reset_report'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     41\u001b[0m     \u001b[0mget_ipython\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmagic\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'add_interaction_code_to_report i = interactive(NumericAnalytics.custom_barplot, df=fixed(df), filename=fixed(filename),                                                    col1=w1, Export=w_export)'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 42\u001b[1;33m     \u001b[0mhbox\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mwidgets\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mHBox\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mchildren\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     43\u001b[0m     \u001b[0mdisplay\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mhbox\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     44\u001b[0m     \u001b[0mhbox\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mon_displayed\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mNumericAnalytics\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcustom_barplot\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mdf\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfilename\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mfilename\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcol1\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mw1\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mvalue\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mExport\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mw_export\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mAttributeError\u001b[0m: 'int' object has no attribute 'children'"
     ]
    }
   ],
   "source": [
    "md_text = '## Target Variable'\n",
    "filename = 'tmp/target_variables.csv'\n",
    "export_filename = 'target_report2.ipynb'\n",
    "\n",
    "if conf_dict['Target'] in conf_dict['CategoricalColumns']:\n",
    "    w1_value,w2_value,w3_value = '','',''\n",
    "    w1, w2, w3, w4 = None, None, None, None\n",
    "    silentremove(filename)    \n",
    "    w1 = widgets.Dropdown(\n",
    "        options=[conf_dict['Target']],\n",
    "        value=conf_dict['Target'],\n",
    "        description='Target Variable:',\n",
    "    )\n",
    "\n",
    "    ReportMagic.var_files = filename\n",
    "    w_export = widgets.Button(description='Export', value='Export')\n",
    "    handle_export_partial = partial(handle_export, w1=w1, w2=w2, w3=w3, export_filename=export_filename, md_text=md_text)      \n",
    "    w1.observe(handle_change,'value')\n",
    "    w_export.on_click(handle_export_partial)\n",
    "\n",
    "    %reset_report\n",
    "    %add_interaction_code_to_report i = interactive(TargetAnalytics.custom_barplot, df=fixed(df), \\\n",
    "                                                    filename=fixed(filename), col1=w1, Export=w_export)\n",
    "    hbox = widgets.HBox(i.children)\n",
    "    display(hbox)\n",
    "    hbox.on_displayed(TargetAnalytics.custom_barplot(df=df0, filename=filename, col1=w1.value, Export=w_export))\n",
    "else:\n",
    "    w1_value, w2_value, w3_value = '', '', ''\n",
    "    w1, w2, w3, w4 = None, None, None, None\n",
    "    silentremove(filename) \n",
    "    w1 = widgets.Dropdown(\n",
    "            options=[conf_dict['Target']],\n",
    "            value=conf_dict['Target'],\n",
    "            description='Target Variable:',\n",
    "        )\n",
    "    w_export = widgets.Button(description='Export', value='Export')\n",
    "    handle_export_partial = partial(handle_export, w1=w1, w2=w2, w3=w3, export_filename=export_filename, md_text=md_text)       \n",
    "    w1.observe(handle_change,'value')\n",
    "    w_export.on_click(handle_export_partial)\n",
    "\n",
    "    %reset_report\n",
    "    %add_interaction_code_to_report i = interactive(NumericAnalytics.custom_barplot, df=fixed(df), filename=fixed(filename),\\\n",
    "                                                    col1=w1, Export=w_export)\n",
    "    hbox = widgets.HBox(i.children)\n",
    "    display(hbox)\n",
    "    hbox.on_displayed(NumericAnalytics.custom_barplot(df=df, filename=filename, col1=w1.value, Export=w_export))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Explore individual numeric variables and test for normality (on sampled data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "Button(description='Export', style=ButtonStyle()) cannot be transformed to a widget",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-18-716ff1e2a9b5>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mi\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0minteractive\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mNumericAnalytics\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcustom_barplot\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdf\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mfixed\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfilename\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mfixed\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfilename\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m                                                \u001b[0mcol1\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mw1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mExport\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mw_export\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\ipywidgets\\widgets\\interaction.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, _interactive__interact_f, _interactive__options, **kwargs)\u001b[0m\n\u001b[0;32m    192\u001b[0m             \u001b[0mgetcallargs\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mf\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[1;33m{\u001b[0m\u001b[0mn\u001b[0m\u001b[1;33m:\u001b[0m\u001b[0mv\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mn\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mv\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0m_\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mnew_kwargs\u001b[0m\u001b[1;33m}\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    193\u001b[0m         \u001b[1;31m# Now build the widgets from the abbreviations.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 194\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mkwargs_widgets\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mwidgets_from_abbreviations\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnew_kwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    195\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    196\u001b[0m         \u001b[1;31m# This has to be done as an assignment, not using self.children.append,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\ipywidgets\\widgets\\interaction.py\u001b[0m in \u001b[0;36mwidgets_from_abbreviations\u001b[1;34m(self, seq)\u001b[0m\n\u001b[0;32m    292\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0misinstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mwidget\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mValueWidget\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mor\u001b[0m \u001b[0misinstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mwidget\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfixed\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    293\u001b[0m                 \u001b[1;32mif\u001b[0m \u001b[0mwidget\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 294\u001b[1;33m                     \u001b[1;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"{!r} cannot be transformed to a widget\"\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mabbrev\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    295\u001b[0m                 \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    296\u001b[0m                     \u001b[1;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"{!r} is not a ValueWidget\"\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mwidget\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mValueError\u001b[0m: Button(description='Export', style=ButtonStyle()) cannot be transformed to a widget"
     ]
    },
    {
     "ename": "AttributeError",
     "evalue": "'int' object has no attribute 'children'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-18-49074e32192f>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m     17\u001b[0m \u001b[0mget_ipython\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmagic\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'reset_report'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     18\u001b[0m \u001b[0mget_ipython\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmagic\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'add_interaction_code_to_report i = interactive(NumericAnalytics.custom_barplot, df=fixed(df), filename=fixed(filename),                                                col1=w1, Export=w_export)'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 19\u001b[1;33m \u001b[0mhbox\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mwidgets\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mHBox\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mchildren\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     20\u001b[0m \u001b[0mdisplay\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mhbox\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     21\u001b[0m \u001b[0mhbox\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mon_displayed\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mNumericAnalytics\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcustom_barplot\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mdf\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfilename\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mfilename\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcol1\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mw1\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mvalue\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mExport\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mw_export\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mAttributeError\u001b[0m: 'int' object has no attribute 'children'"
     ]
    }
   ],
   "source": [
    "md_text = '## Visualize Individual Numerical Variables (on Sampled Data)'\n",
    "filename = ReportMagic.var_files='tmp/numeric_variables.csv'\n",
    "export_filename = 'numeric_report2.ipynb'\n",
    "w1_value, w2_value, w3_value = '', '', ''\n",
    "w1, w2, w3, w4 = None, None, None, None\n",
    "silentremove(filename) \n",
    "w1 = widgets.Dropdown(\n",
    "        options=conf_dict['NumericalColumns'],\n",
    "        value=conf_dict['NumericalColumns'][0],\n",
    "        description='Numeric Variable:',\n",
    "    )\n",
    "w_export = widgets.Button(description='Export', value='Export')\n",
    "handle_export_partial = partial(handle_export, w1=w1, w2=w2, w3=w3, export_filename=export_filename, md_text=md_text)       \n",
    "w1.observe(handle_change,'value')\n",
    "w_export.on_click(handle_export_partial)\n",
    "\n",
    "%reset_report\n",
    "%add_interaction_code_to_report i = interactive(NumericAnalytics.custom_barplot, df=fixed(df), filename=fixed(filename),\\\n",
    "                                                col1=w1, Export=w_export)\n",
    "hbox = widgets.HBox(i.children)\n",
    "display(hbox)\n",
    "hbox.on_displayed(NumericAnalytics.custom_barplot(df=df, filename=filename, col1=w1.value, Export=w_export))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Explore individual categorical variables (sorted by frequencies)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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evWp0HBRzlAsAAAC3sfDwCI35cJGszLEA3JbMFmeleLZSr1eGKS0t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\nO3cuJSUl7N27l02bNlU4984771BUVMTp06dZunQpffv2Lb+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1a5M8DzdHXhkZCcDWXdtZ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\n/wf8sqsNCL9U8wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xfb863209b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Export is successful!\n"
     ]
    }
   ],
   "source": [
    "w_export = None\n",
    "md_text = '## Visualize Individual Categorical Variables'\n",
    "filename = ReportMagic.var_files='tmp/categoric_variables.csv'\n",
    "export_filename = 'categoric_report2.ipynb'\n",
    "\n",
    "w1_value, w2_value, w3_value = '', '', ''\n",
    "w1, w2, w3, w4 = None, None, None, None\n",
    "silentremove(filename) \n",
    "w1 = widgets.Dropdown(\n",
    "    options = conf_dict['CategoricalColumns'],\n",
    "    value = conf_dict['CategoricalColumns'][0],\n",
    "    description = 'Categorical Variable:',\n",
    ")\n",
    "\n",
    "w_export = widgets.Button(description='Export')\n",
    "handle_export_partial = partial(handle_export, w1=w1, w2=w2, w3=w3, export_filename=export_filename, md_text=md_text)       \n",
    "w1.observe (handle_change,'value')\n",
    "w_export.on_click(handle_export_partial)\n",
    "\n",
    "%reset_report\n",
    "%add_interaction_code_to_report i = interactive(CategoricAnalytics.custom_barplot, df=fixed(df),\\\n",
    "                                                filename=fixed(filename), col1=w1, Export=w_export)\n",
    "\n",
    "hbox = widgets.HBox(i.children)\n",
    "display(hbox)\n",
    "hbox.on_displayed(CategoricAnalytics.custom_barplot(df=df0, filename=filename, col1=w1.value, \\\n",
    "                                         Export=w_export))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <a name=\"multiple variables\"></a>Explore Interactions Between Variables"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <a name=\"rank variables\"></a>Rank variables based on linear relationships with reference variable (on sampled data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Xu44xDdD7IWs9HSkv1eLZUu/eva31CQBoPARsAABwXmjXMUZR//nfTT0MAMA5\njM9gAwAAAABgAQEbAAAAAAALCNgAAAAAAFjAZ7ABAAAQElZlB4C6nfcBO5wmCIlJAgAAND1WZQeA\nup33ATtcJgiJSQIAADQfrMoOAMHO+4AtMUEAAAAAAM4ei5wBAAAAAGABARsAAAAAAAsI2AAAAAAA\nWEDABgAAAADAAgI2AAAAAAAWELABAAAAALCAgA0AAAAAgAUEbAAAAAAALCBgAwAAAABgAQEbAAAA\nAAALCNgAAAAAAFhAwAYAAAAAwAICNgAAAAAAFhCwAQAAAACwgIANAAAAAIAFBGwAAAAAACwgYAMA\nAAAAYAEBGwAAAAAACwjYAAAAAABYEHLALiws1KhRo5SYmKiMjAyVlZWdsu3XX3+tq6++WgcOHPDv\nM8Zozpw56tOnj1JSUrR48eIzGzkAAAAAAM1ISAHb5/MpKytLmZmZKigoUHJysqZMmVJn26KiIt1y\nyy0B4VqSli1bpu3bt2vLli1auXKlVq1apby8vDM+AQAAAAAAmoOQAnZ+fr6ioqKUlpamiIgITZ48\nWWVlZSoqKgpoV1RUpFtvvVXjx48P6mPDhg2aMGGC2rVrp5iYGGVkZCg3N/fszgIAAAAAgCYWUsAu\nLi5W586d//3kli0VHR0tt9sd0O6SSy7R5s2bNXLkSBljTtuHy+VScXHxmYwdAAAAAIBmIyKUxh6P\nR06nM2Cf0+mUx+MJ2Ne2bdvT9uFwOPzbDodDXq83lGEEHe9shHrspub1elVZWdnUw2h0ta+5zdf+\nfEdN7aKe9oVLTZv7+AAAQOMJKWA7nc6gQOrxeE4bqE/mcDhUVVXl3/Z6vSE9X5JKSkpCan86J199\nb+7cbnfI9TqX2HztUYOa2kU97aOmAAAgXIQUsF0ul9auXevfrq6uVmlpqVwuV737iI2NldvtVmxs\nrKSawBjK8yWpU6dOQVfSz1TN1eBDVvpqDC6XS/Hx8U09jEbn8XhUUlJi9bU/31FTu6infeFS09px\nAgAAhBSwk5KSVF5ertzcXKWlpWnhwoWKiYkJ+Ez1d0lLS9PixYvVq1cvVVRUaMWKFZoxY0ZIg3Y6\nndau4p54u3o4cDgc5/UVbJuvPWpQU7uop33UFAAAhIuQFjmLjIzUokWLtHz5ciUlJSk/P1/Z2dmS\npPT0dK1fvz7oOS1atAjYHjdunC6//HINHz5cY8aM0dixYzVw4MAzPwMAAAAAAJqBkK5gS1JCQoJy\ncnKC9tei8i/fAAAgAElEQVQVriVp586dAdutWrXStGnTNG3atFAPDQAAAABAsxXSFWwAAAAAAFA3\nAjYAAAAAABYQsAEAQL0VFhZq1KhRSkxMVEZGhsrKyk7bfurUqZo+fXojjQ4AgKZFwAYAAPXi8/mU\nlZWlzMxMFRQUKDk5WVOmTDll+y1btmjDhg2NOEIAAJoWARsAANRLfn6+oqKilJaWpoiICE2ePFll\nZWUqKioKavvVV1/piSee0OjRo5tgpAAANA0CNgAAqJfi4mJ17tzZv92yZUtFR0fL7XYHtX344YeV\nmZmpiy++uDGHCABAkyJgAwCAevF4PHI6nQH7nE6nPB5PwL6NGzeqsrKSq9cAgPNOyN+DDQAAzk9O\np1Nerzdgn8fjUdu2bf3b5eXlevrpp7VixYqzOtbJof1snTzu5szr9aqysrKph3Fa1DM81P5/ZPv/\np/MV9bQvXGoayvgI2AAAoF5cLpfWrl3r366urlZpaalcLpd/3zvvvKMvvvhCw4YNkyRVVVXp+PHj\n2rFjh3Jzc+t9rJKSEmvjllTnbezNldvtDvijRXNEPcOL7f+fznfU075zqaYEbAAAUC9JSUkqLy9X\nbm6u0tLStHDhQsXExAR8Lnv48OEaPny4f3vBggXav3+/Hn300ZCO1alTp6Db0c9GzRXMQ9b6a0gu\nl0vx8fFNPYzTop7hwePxqKSkxPr/T+cr6mlfuNS0dpz1QcAGAAD1EhkZqUWLFmnmzJmaNWuW4uPj\nlZ2dLUlKT0/XpEmTlJ6ebuVYTqfT6lVHh8Nhra+G5nA4mv0VV+oZXmz//3S+o572nUs1JWADAIB6\nS0hIUE5OTtD+9evX19k+KyuroYcEAECzwSriAAAAAABYQMAGAAAAAMACAjYAAAAAABYQsAEAAAAA\nsICADQAAAACABQRsAAAAAAAsIGADAAAAAGABARsAAAAAAAsI2AAAAAAAWEDABgAAAADAAgI2AAAA\nAAAWELABAAAAALCAgA0AAAAAgAUEbAAAAAAALCBgAwAAAABgAQEbAAAAAAALCNgAAAAAAFhAwAYA\nAAAAwAICNgAAAAAAFhCwAQAAAACwgIANAAAAAIAFBGwAAAAAACwgYAMAAAAAYAEBGwAAAAAACwjY\nAAAAAABYQMAGAAAAAMCCiKYeAAAAAHC+8/l8KiwstNqn1+uV2+1WZWWlHA6HtX579OihNm3aWOsP\nOJcQsAEAAIAmVlhYqMwZy9WuY0wD9H7IWk9Hyku1eLbUu3dva30C5xICNgAAANAMtOsYo6j//O+m\nHgaAs8BnsAEAAAAAsICADQAAAACABQRsAAAAAAAsIGADAAAAAGABi5wBAAAAOKeE09eeSXz12bmE\ngA0AAADgnBIuX3sm8dVn5xoCNgAAAIBzDl97hqbAZ7ABAAAAALCAgA0AAAAAgAUEbAAAAAAALCBg\nAwAAAABgAQEbAAAAAAALCNgAAAAAAFgQcsAuLCzUqFGjlJiYqIyMDJWVlQW1McZozpw56tOnj1JS\nUrR48WL/Y8eOHdPMmTOVnJyslJQUzZ079+zOAAAAAACAZiCkgO3z+ZSVlaXMzEwVFBQoOTlZU6ZM\nCWq3bNkybd++XVu2bNHKlSu1atUq5eXlSZJefPFFHThwQHl5eVq/fr3efvttrVu3zsrJAAAAAADQ\nVEIK2Pn5+YqKilJaWpoiIiI0efJklZWVqaioKKDdhg0bNGHCBLVr104xMTHKyMhQbm6uJKm0tFTV\n1dU6evSojDFq0aKFIiMj7Z0RAAAAAABNIKSAXVxcrM6dO//7yS1bKjo6Wm63+7TtXC6XiouLJUk3\n3HCDdu3a5b99/LLLLtN11113NucAAAAAAECTiwilscfjkdPpDNjndDrl8XiC2jkcDv+2w+GQ1+uV\nVHOb+fDhw5WVlaXDhw/r9ttv10svvaQxY8aENA5bascVLrxeryorK5t6GI2u9jW3+dqf76ipXdTT\nvnCpaXMfHwAAaDwhBWyn0xkUSD0ej9q2bRuwz+FwqKqqyr/t9Xr9baZPn665c+fqggsu0AUXXKBJ\nkybpueeeCylgl5SUhDLs0zr56ntz53a7g+p9PrH52qMGNbWLetpHTQEAQLgIKWC7XC6tXbvWv11d\nXa3S0lK5XK6AdrGxsXK73YqNjZVUEwpr23z++ec6evSov22rVq3UunXrkAbdqVOnoCvpZ6rmavAh\nK301BpfLpfj4+KYeRqPzeDwqKSmx+tqf76ipXdTTvnCpae04AQAAQgrYSUlJKi8vV25urtLS0rRw\n4ULFxMQEfN5aktLS0rR48WL16tVLFRUVWrFihWbMmCFJ6tevn7Kzs7VgwQJ5PB796U9/0tChQ0Ma\ntNPptHYV98Rb2cOBw+E4r69g23ztUYOa2kU97aOmAAAgXIS0yFlkZKQWLVqk5cuXKykpSfn5+crO\nzpYkpaena/369ZKkcePG6fLLL9fw4cM1ZswYjR07VgMHDpQkzZo1Sz/4wQ80aNAgjR49WikpKbrl\nllvsnhUAAAAAAI0spCvYkpSQkKCcnJyg/bXhWqq57XvatGmaNm1aULsLL7xQjz/+eKiHBQAAAACg\nWQvpCjYAAAAAAKgbARsAAAAAAAsI2AAAAAAAWEDABgAAAADAAgI2AAAAAAAWELABAAAAALCAgA0A\nAAAAgAUEbAAAAAAALCBgAwAAAABgAQEbAAAAAAALCNgAAAAAAFhAwAYAAAAAwAICNgAAAAAAFhCw\nAQAAAACwgIANAAAAAIAFBGwAAAAAACwgYAMAgHorLCzUqFGjlJiYqIyMDJWVlQW1qaio0K9//Wv1\n6dNHffv21WOPPabq6uomGC0AAI2LgA0AAOrF5/MpKytLmZmZKigoUHJysqZMmRLU7rHHHlNERITe\nfvttbdq0Sfn5+Vq7dm0TjBgAgMYV0dQDAAAA4SE/P19RUVFKS0uTJE2ePFlLly5VUVGRYmNj/e0e\nfvhhVVdXq3Xr1jp48KCqqqrUvn37pho2AACNhivYAACgXoqLi9W5c2f/dsuWLRUdHS232x3QrlWr\nVmrdurXuvvtuDRo0SJdeeqmuuuqqxh4uAACNjivYAACgXjwej5xOZ8A+p9Mpj8dTZ/t58+Zp5syZ\nuv3225Wdna1f//rXIR3LJq/Xa7W/huT1elVZWdnUwzgt6mkfNbUrnOophUdNG0Lt73rbv/NtC2V8\nBGwAAFAvTqcz6E2rx+NR27Zt62zfpk0bdezYURMnTtSCBQtCCtglJSVnM9QgJ19lb87cbvcpa9pc\nUE/7qKld4VRPKTxq2pBs/85vSgRsAABQLy6XK2CxsurqapWWlsrlcgW0mzRpkm666SYNGDBAklRV\nVaULL7wwpGN16tQp6Gr52ai5MnTIWn8NyeVyKT4+vqmHcVrU0z5qalc41VMKj5o2BI/Ho5KSEuu/\n822rHWd9ELABAEC9JCUlqby8XLm5uUpLS9PChQsVExMT8LlsSUpISNCzzz6rxMREffvtt1q8eLHG\njRsX0rGcTqfVqzkOh8NaXw3N4XA0+ytZ1NM+ampXONVTCo+aNiTbv/ObEoucAQCAeomMjNSiRYu0\nfPlyJSUlKT8/X9nZ2ZKk9PR0rV+/XlLN6uJdu3bVkCFDNHbsWA0fPlw33HBDUw4dAIBGwRVsAABQ\nbwkJCcrJyQnaXxuuJal169Z68MEH9eCDDzbm0AAAaHJcwQYAAAAAwAICNgAAAAAAFhCwAQAAAACw\ngIANAAAAAIAFBGwAAAAAACwgYAMAAAAAYAEBGwAAAAAACwjYAAAAAABYQMAGAAAAAMACAjYAAAAA\nABYQsAEAAAAAsICADQAAAACABQRsAAAAAAAsIGADAAAAAGABARsAAAAAAAsI2AAAAAAAWEDABgAA\nAADAAgI2AAAAAAAWELABAAAAALCAgA0AAAAAgAUEbAAAAAAALCBgAwAAAABgAQEbAAAAAAALCNgA\nAAAAAFhAwAYAAAAAwAICNgAAAAAAFhCwAQAAAACwgIANAAAAAIAFBGwAAAAAACwIOWAXFhZq1KhR\nSkxMVEZGhsrKyoLaGGM0Z84c9enTRykpKVq8eHHA488995z69eunPn366N5771VVVdWZnwEAAAAA\nAM1ASAHb5/MpKytLmZmZKigoUHJysqZMmRLUbtmyZdq+fbu2bNmilStXatWqVcrLy5Mkbdy4UatX\nr9bq1auVl5enr776KiiAAwAAAAAQbkIK2Pn5+YqKilJaWpoiIiI0efJklZWVqaioKKDdhg0bNGHC\nBLVr104xMTHKyMhQbm6uJCknJ0d33nmnfvjDH8rpdGrevHm6/vrr7Z0RAAAAAABNIKSAXVxcrM6d\nO//7yS1bKjo6Wm63+7TtXC6XiouLJUk7d+7UkSNHNHz4cKWmpuqZZ57R97///bM5BwAAAAAAmlxE\nKI09Ho+cTmfAPqfTKY/HE9TO4XD4tx0Oh7xeryTp8OHDys3N1Z/+9Ce1bt1ad9xxhxYuXKisrKyQ\nxmFL7bjChdfrVWVlZVMPo9HVvuY2X/vzHTW1i3raFy41be7jAwAAjSekgO10OoMCqcfjUdu2bQP2\nORyOgIXLvF6vv03r1q1188036wc/+IEkacKECXr22WdDCtglJSWhDPu0Tr763ty53e6gep9PbL72\nqEFN7aKe9lFTAAAQLkIK2C6XS2vXrvVvV1dXq7S0VC6XK6BdbGys3G63YmNjJdWEwto2nTp10uHD\nh/1tjx07JmNMSIPu1KlT0JX0M1VzNfiQlb4ag8vlUnx8fFMPo9F5PB6VlJRYfe3Pd9TULuppX7jU\ntHacAAAAIQXspKQklZeXKzc3V2lpaVq4cKFiYmICPm8tSWlpaVq8eLF69eqliooKrVixQjNmzJAk\njRgxQitXrtQ111yj1q1b6/nnn9eQIUNCGrTT6bR2FffEW9nDgcPhOK+vYNt87VGDmtpFPe2jpgAA\nIFyEFLAjIyO1aNEizZw5U7NmzVJ8fLyys7MlSenp6Zo0aZLS09M1btw4HTp0SMOHD5dUcxv4wIED\nJUm33nqrqqqqdNNNN+nbb7/VsGHDNGHCBLtnBQAAAABAIwspYEtSQkKCcnJygvavX7/e/+9WrVpp\n2rRpmjZtWlC7Fi1aaNKkSZo0aVKohwYAAAAAoNkK6Wu6AAAAAABA3QjYAAAAAABYQMAGAAAAAMAC\nAjYAAAAAABYQsAEAAAAAsICADQAAAACABQRsAAAAAAAsIGADAAAAAGABARsAAAAAAAsI2AAAAAAA\nWBDR1APAucfn86mwsNBqn16vV263W5WVlXI4HNb67dGjh9q0aWOtPwAAAADnLwI2rCssLFTmjOVq\n1zGmAXo/ZK2nI+WlWjxb6t27t7U+AQAAAJy/CNhoEO06xijqP/+7qYcBAAAAAI2Gz2ADAAAAAGAB\nARsAAAAAAAsI2AAAAAAAWEDABgAAAADAAgI2AAAAAAAWELABAAAAALCAgA0AAAAAgAUEbAAAAAAA\nLCBgAwAAAABgQURTDwAAAAAA0Lz5fD4VFhZa7dPr9crtdquyslIOh8Navz169FCbNm2s9RcKAjYA\nAAAA4LQKCwuVOWO52nWMaYDeD1nr6Uh5qRbPlnr37m2tz1AQsIFmriH+Wiidm38xBAAAQMNp1zFG\nUf/53009jGaNgA00cw3710LpXPqLIQAAANCUCNhAGOCvhQAAAEDzR8AGcN5hkQ4AAAA0BAI2gPMO\ni3QAZ66wsFAPPfSQSkpK1LVrVz366KOKjo4OaFNRUaGHH35Yf/3rX9WqVSsNGTJE9913nyIieNsB\nADi3MdMBOC9x2z0QOp/Pp6ysLE2fPl2DBw/WwoULNWXKFL3yyisB7R5//HEdPXpUb775pjwejyZP\nnqwlS5Zo4sSJTTRyAAAaR8umHgAAAAgP+fn5ioqKUlpamiIiIjR58mSVlZWpqKgoqO3kyZPlcDjU\noUMHpaen64MPPmiCEQMA0LgI2AAAoF6Ki4vVuXNn/3bLli0VHR0tt9sd0G7WrFnq0qWLf3vr1q36\n8Y9/3GjjBACgqRCwAQBAvXg8HjmdzoB9TqdTHo/nlM+ZN2+eiouLNWHChIYeHgAATY7PYAMAgHpx\nOp3yer0B+zwej9q2bRvU9vjx45o5c6YKCgq0dOlStW/fPqRjnS60n4mTx92ceb1eVVZWNvUwTot6\n2kdN7QqnekrU1Dbb9QxlTiJgAwCAenG5XFq7dq1/u7q6WqWlpXK5XAHtahdDO3z4sFavXq0OHTqE\nfKySkpKzHW6Ak29jb87cbnedf7RoTqinfdTUrnCqp0RNbWvKehKwAQBAvSQlJam8vFy5ublKS0vT\nwoULFRMTE/C5bEmaPXu2Dh8+rKVLlyoyMvKMjtWpU6eg29HPRs2VDHtfo9eQXC6X4uPjm3oYp0U9\n7aOmdoVTPSVqapvteno8nnr/4ZeADQAA6iUyMlKLFi3SzJkzNWvWLMXHxys7O1uSlJ6erkmTJmng\nwIF65ZVX1Lp1ayUlJUmSWrRooSuuuEKLFi2q97GcTqfVqw8Oh8NaXw3N4XA0+ytZ1NM+ampXONVT\noqa2NWU9CdgAAKDeEhISlJOTE7R//fr1/n/v2LGjMYcEAECzwSriAAAAAABYQMAGAAAAAMACAjYA\nAAAAABYQsAEAAAAAsICADQAAAACABQRsAAAAAAAsIGADAAAAAGABARsAAAAAAAsI2AAAAAAAWEDA\nBgAAAADAAgI2AAAAAAAWELABAAAAALCAgA0AAAAAgAUEbAAAAAAALCBgAwAAAABgAQEbAAAAAAAL\nQg7YhYWFGjVqlBITE5WRkaGysrKgNsYYzZkzR3369FFKSooWL15cZ19Tp07V9OnTQx81AAAAAADN\nTEgB2+fzKSsrS5mZmSooKFBycrKmTJkS1G7ZsmXavn27tmzZopUrV2rVqlXKy8sLaLNlyxZt2LDh\nrAYPAAAAAEBzEVLAzs/PV1RUlNLS0hQREaHJkyerrKxMRUVFAe02bNigCRMmqF27doqJiVFGRoZy\nc3P9j3/11Vd64oknNHr0aDtnAQAAAABAEwspYBcXF6tz587/fnLLloqOjpbb7T5tO5fLpeLiYv/2\nww8/rMzMTF188cVnOm4AAAAAAJqViFAaezweOZ3OgH1Op1MejyeoncPh8G87HA55vV5J0saNG1VZ\nWanRo0drwYIFZzTok493NmrHFS68Xq8qKyubehinFU41pZ72UVO7wqGeDaX2d73N3/kNobmPDwAA\nNJ6QArbT6Qx6Y+rxeNS2bduAfQ6HQ1VVVf5tr9ertm3bqry8XE8//bRWrFhxFkOWSkpKzur5Jzr5\n6ntz53a7g+rd3IRTTamnfdTUrnCoZ0Oz+TsfAACgIYUUsF0ul9auXevfrq6uVmlpqVwuV0C72NhY\nud1uxcbGSqp5g+hyufTOO+/oiy++0LBhwyRJVVVVOn78uHbs2BHwGe3v0qlTp6Ar6Weq5srQISt9\nNQaXy6X4+PimHsZphVNNqad91NSucKhnQ/F4PCopKbH6O78h1I4TAAAgpICdlJSk8vJy5ebmKi0t\nTQsXLlRMTEzA560lKS0tTYsXL1avXr1UUVGhFStWaMaMGRo4cKCGDx/ub7dgwQLt379fjz76aEiD\ndjqd1q7onHgrezhwOBzN/mpWONWUetpHTe0Kh3o2NJu/8wEAABpSSIucRUZGatGiRVq+fLmSkpKU\nn5+v7OxsSVJ6errWr18vSRo3bpwuv/xyDR8+XGPGjNHYsWM1cOBA64MHAAAAAKC5COkKtiQlJCQo\nJycnaH9tuJakVq1aadq0aZo2bdpp+8rKygr18AAAAAAANEshXcEGAAAAAAB1I2ADAAAAAGABARsA\nAAAAAAsI2AAAAAAAWEDABgAAAADAAgI2AAAAAAAWELABAAAAALCAgA0AAAAAgAUEbAAAAAAALCBg\nAwAAAABgAQEbAAAAAAALCNgAAAAAAFhAwAYAAAAAwAICNgAAAAAAFhCwAQAAAACwgIANAAAAAIAF\nBGwAAAAAACwgYAMAAAAAYAEBGwAAAAAACwjYAAAAAABYQMAGAAAAAMACAjYAAAAAABYQsAEAAAAA\nsICADQAAAACABQRsAAAAAAAsIGADAAAAAGABARsAAAAAAAsI2AAAAAAAWEDABgAAAADAAgI2AAAA\nAAAWELABAAAAALCAgA0AAAAAgAUEbAAAAAAALCBgAwAAAABgAQEbAAAAAAALCNgAAAAAAFhAwAYA\nAAAAwAICNgAAAAAAFhCwAQAAAACwgIANAAAAAIAFBGwAAAAAACwgYAMAAAAAYAEBGwAA1FthYaFG\njRqlxMREZWRkqKys7JRtv/76a1199dU6cOBAI44QAICmQ8AGAAD14vP5lJWVpczMTBUUFCg5OVlT\npkyps21RUZFuueUWwjUA4LxCwAYAAPWSn5+vqKgopaWlKSIiQpMnT1ZZWZmKiooC2hUVFenWW2/V\n+PHjm2ikAAA0DQI2AACol+LiYnXu3Nm/3bJlS0VHR8vtdge0u+SSS7R582aNHDlSxpjGHiYAAE0m\noqkHAAAAwoPH45HT6QzY53Q65fF4Ava1bdvWyrFs8nq9VvtrSF6vV5WVlU09jNOinvZRU7vCqZ4S\nNbXNdj1DmZMI2AAAoF6cTmfQGyyPx2MlUJ+spKTEan8nX2Vvztxud4PU1CbqaR81tSuc6ilRU9ua\nsp4EbAAAUC8ul0tr1671b1dXV6u0tFQul8v6sTp16hR0tfxs1FzJOGStv4bkcrkUHx/f1MM4Lepp\nHzW1K5zqKVFT22zX0+Px1PsPvwRsAABQL0lJSSovL1dubq7S0tK0cOFCxcTEBHwu2xan02n16oPD\n4bDWV0NzOBzN/koW9bSPmtoVTvWUqKltTVlPFjkDAAD1EhkZqUWLFmn58uVKSkpSfn6+srOzJUnp\n6elav3590HNatGjR2MMEAKDJcAUbAADUW0JCgnJycoL21xWuJWnnzp0NPSQAAJoNrmADAAAAAGAB\nARsAAAAAAAsI2AAAAAAAWBBywC4sLNSoUaOUmJiojIwMlZWVBbUxxmjOnDnq06ePUlJStHjxYv9j\nFRUVmjp1qpKTk5WamqpHHnlEx44dO7uzAAAAAACgiYUUsH0+n7KyspSZmamCggIlJydrypQpQe2W\nLVum7du3a8uWLVq5cqVWrVqlvLw8SdLjjz+uo0eP6s0339Rrr72mjz/+WEuWLLFyMgAAAAAANJWQ\nAnZ+fr6ioqKUlpamiIgITZ48WWVlZSoqKgpot2HDBk2YMEHt2rVTTEyMMjIylJub63988uTJcjgc\n6tChg9LT0/XBBx/YORsAAAAAAJpISF/TVVxcrM6dO/u3W7ZsqejoaLndbsXGxp6yncvl0rp16yRJ\ns2bNCuhz69atSkhIOKPBAwCaB5/Pp8LCQqt9er1eud1uVVZWyuFwWOu3R48eatOmjbX+AAAAaoUU\nsD0ej5xOZ8A+p9Mpj8cT1O7EN0MOh0Nerzeov3nz5qm4uFhPPPFEKMMIOt7ZqGtczZnX61VlZWVT\nD+O0wqmm1NM+ampXONRTkrZt26ZfzVmjdh1jGqD3Q9Z6OlJeqvkPeHX55Zdb69PmnAQAAMJbSAHb\n6XQGvTH1eDxq27ZtwD6Hw6Gqqir/ttfrDWhz/PhxzZw5UwUFBVq6dKnat28f0qBLSkpCan86brfb\nWl+Nwe12B9W7uQmnmlJP+6ipXeFQT6lmnO06xijqP/+7qYfyncKlpgAAIPyEFLBdLpfWrl3r366u\nrlZpaalcLldAu9jY2IDbxt1ut79N7UJphw8f1urVq9Xh/7N353E15f8fwF+3vUgplBSSGfuuhZCy\ntjDKvoSQLfve2MpO9nztexgmRJI02caedaxjuVlS2jeltP7+8HB/cydbOZxu83o+Hj2m+zmn26sz\n6d73+Wzlyxc5dPXq1Qv1pBfX+54h4XpHvjdTU1PUqVNH7BifpUjXlNdTeLymwlKE6wn8t69pZmam\noDd+iYiISHEVqcC2srJCYmIijh49CgcHB2zatAlVq1aVm28NAA4ODtiyZQuaNm2K9PR07NmzB7Nn\nzwYAzJ8/H2lpadi1axfU1dWLFVpTU1Ow3gch5/X9CBoaGiW+50WRrimvp/B4TYWlCNcT4DUlIiIi\nAopYYKurq2Pz5s2YM2cO5s2bhzp16mDNmjUAACcnJ4wcORJOTk5wdXVFXFwcunbtCgAYMmQI2rZt\ni/T0dBw6dAiqqqqwsrICAEgkEjRv3hybN28W+EcjIiIiIiIi+nGKVGADQN26dXHw4MFC7UFBQbLP\nlZWVMW3aNEybNk3unLJly+LBgwfFiElERERERERUshVpH2wiIiIiIiIi+jgW2EREREREREQCYIFN\nREREREREJAAW2EREREREREQCYIFNREREREREJAAW2EREREREREQCYIFNREREREREJAAW2ERERERE\nREQCYIFNREREREREJAAW2EREREREREQCYIFNREREREREJAAW2EREREREREQCYIFNREREREREJAAW\n2EREREREREQCYIFNREREREREJAAW2EREREREREQCYIFNREREREREJAAW2EREREREREQCYIFNRERE\nREREJAAW2EREREREREQCYIFNREREREREJAAW2EREREREREQCYIFNREREREREJAAW2EREREREREQC\nYIFNREREREREJAAW2EREREREREQCYIFNREREREREJAAW2EREREREREQCYIFNREREREREJAAW2ERE\nREREREQCYIFNREREREREJAAW2EREREREREQCYIFNREREREREJAAW2EREREREREQCYIFNRERERERE\nJAAW2EREREREREQCYIFNREREREREJAAW2EREREREREQCYIFNREREREREJAAW2EREREREREQCYIFN\nREREREREJAAW2EREREREREQCYIFNREREREREJAAW2EREREREREQCYIFNREREREREJAAW2ERERERE\nRFgAeCUAACAASURBVEQCYIFNREREREREJAAW2EREREREREQCYIFNREREREREJAAW2EREREREREQC\nYIFNREREREREJAAW2EREREREREQCYIFNREREREREJAAW2EREREREREQCKHKB/ddff8HZ2RlNmjTB\ngAEDEBkZWeicgoICLFy4EJaWlrC2tsaWLVu+6hgRERGVbN/6PoCIiKg0K1KBnZ2djTFjxsDd3R3X\nrl1DixYtMGHChELn7d69G3fv3kVYWBh+++037N+/H2fPnv3iMSIiIiq5hHgfQEREVJoVqcC+cuUK\ndHV14eDgABUVFYwaNQqRkZGQSqVy5x0/fhxDhgyBtrY2qlatigEDBuDo0aNfPEZEREQllxDvA4iI\niEqzIhXYERERqFGjxv9/sZISTExM8OzZs8+eZ2pqioiIiC8eIyIiopJLiPcBREREpVmRCuzMzExo\namrKtWlqaiIzM7PQeRoaGrLHGhoayMrK+uIxIiIiKrmEeB9ARERUmqkU5WRNTc1CL5CZmZnQ0tKS\na9PQ0MC7d+9kj7OysmTnfO7Yl+Tn5wMAUlJSCr2YF9e7d+9QXj0dZfJfC/J835NEPR3v3r1DYmKi\n2FE+S1GuKa+n8HhNhaUo1xP4b1/TD69pH16jSjMh3gd8yfd4rQf+27+j3wOvp/B4TYWlKNcT4DUV\nmtiv9UUqsE1NTREQECB7nJ+fj5cvX8LU1FTuPDMzMzx79gxmZmYAgGfPnsnOqVGjxiePfcmHH+z1\na+H+p2pqamKuRxfBnu9HeP78udgRPkvRrimvp/B4TYVV0q8nwGsKvH+NKlu2rODPW5II8T7gS77H\naz3A31Gh8XoKj9dUWIp2PQFeU6GJ9VpfpALbysoKiYmJOHr0KBwcHLBp0yZUrVpVbp4VADg4OGDL\nli1o2rQp0tPTsWfPHsyePRsA4Ojo+MljX6Kjo4Pq1atDXV0dSkrcwpuIiMSXn5+Pd+/eQUdHR+wo\n350Q7wO+hK/1RERU0hTltV5SUFBQUJQnf/DgAebMmYNnz56hTp06WLJkCYyNjeHk5ISRI0fCyckJ\neXl5WLFiBQIDAwEAQ4YMwZAhQwDgs8eIiIioZPvW9wFERESlWZELbCIiIiIiIiIqjGOviIiIiIiI\niATAApuIiIiIiIhIACywiYiIiIiIiATAApuIiIiIiIhIACywiYiIiIiIiATAApuIiIiIiIhIACyw\niYiIiIiIiATAApuIiIiIiIhIACpiByD6nLdv3+LcuXOIiYlBnz598PTpUzRo0EDsWArr9u3bePHi\nBQoKCuTau3XrJlIixZaUlAQ9Pb1C7cHBwXBwcBAhUemSnp4ONTU1qKmpiR2FiL6j69evo3nz5khO\nTsbmzZuhq6sLNzc3/tsnKoXevXsHdXX1Qu3R0dEwMjISIZHwJAX/fqdNxRIaGoolS5YgJiZGVrwU\nFBRAIpHg4cOHIqdTTPfv38eIESNgbGyMR48eITAwEF27dsXcuXNZEBaDt7c3jh49itq1a0NZWVnW\nLpFIsHv3bhGTKS5HR0fs2rULFSpUAABERkbCy8sL9+/fx5UrV0ROp3gePHiAFStWYNu2bThy5Ahm\nzpwJTU1NrFmzBtbW1mLHIwLw/rV93759CAkJQUJCAgwMDNC1a1e4uLiIHU0hLVu2DCEhITh9+jRG\njx6N9PR0qKqqolKlSli8eLHY8RROTk4OQkND8eLFC+Tn58sdGzNmjEipFNvdu3exevVqvHz5stA1\nPXXqlEipFFfnzp2xdOlSNGrUSNbm5+eH1atX48aNGyImEw57sAUyf/58eHh4wNraGkpKHHkvhHnz\n5mHWrFno3LkzzM3NYWJigq1bt8LT05MFdjGcOHECBw4cwE8//SR2lFKja9eu6N+/PzZv3owTJ05g\n06ZN6NKlC1asWCF2NIW0YMECtGnTBvn5+Vi1ahWWLVsGXV1dLFq0CMePHxc7HhEAYOnSpbhw4QIG\nDx4MQ0NDREdHY9u2bXj9+jU8PDzEjqdwTp48id9//x2pqak4d+4cwsLCoKurCxsbG7GjKaSpU6fi\n9u3bMDc3h4oK3+YLYfbs2WjYsCGGDRsm10FBxTNw4EAMGzYMffr0gaOjI7y9vfHmzRts3LhR7GiC\n4b88geTn56NHjx78YyagiIgIdOzYEcD7XlYAaNasGZKSksSMpbC0tLRQuXJlsWOUKiNGjICenh6c\nnJxQo0YN7N69m1MYvoFUKsW+fftw9+5dpKeno1OnTlBRUcHr16/FjkYkc/jwYQQHB8tGrgCAjY0N\nunXrxgK7GNLT06Gnp4fjx4+jRo0aqFy5MjIyMmSv+1Q0Fy9eRFBQEAwMDMSOUmq8ePEC/v7+UFVV\nFTtKqdCvXz+0bt0a/fv3x9atW+Ho6IilS5eWqpsXrAYFMnr0aHh7e8PV1RVly5aVO1Za5hP8aDVr\n1sSJEyfg6Ogoazt79ixq1qwpYirF1bdvX4wdOxZ9+vQpNG/Y3NxcpFSK6ciRI7LPVVVVYWNjg9u3\nb+Pvv/+GVCoFwHntxaGrq4vHjx8jICAA1tbWUFFRwYULF2BoaCh2NCIZbW1tZGZmyrVJJBKUK1dO\npESKzdLSEpMnT8b9+/fRs2dPREVFYc6cOWjVqpXY0RRShQoV2NkjsFatWuHixYto27at2FFKhfv3\n72Pu3LkoV64cBgwYgG3btmHBggWYNGkStLW1xY4nCM7BFsiWLVuwatWqQnMzOAe7+O7fvw93d3dU\nr14dd+7cgbW1Ne7du4cNGzagYcOGYsdTOHZ2dh9tl0gknENURK6urp89znntxRMSEoKZM2eibNmy\n2Lp1K5KTkzFixAisXLkStra2YscjAgCsWrUKQUFBGDhwIExMTBAfHw8/Pz/Ur18fVlZWsvN4k+3r\nvH37Fr/99hu0tbXRs2dPSKVSHDt2DCNHjoSmpqbY8RSOr68vQkND4ezsXOhmOn8ni2f06NE4e/Ys\nzMzMUL58ebljfK0vuoYNG8Ld3R0jR46Eqqoq4uLi4O3tjb/++gsXLlwQO54gWGALxNzcHL6+vrCw\nsOAcbAGlp6fj3LlzeP36NSpUqIC2bdtCV1dX7FhE9J3k5+fL/oZmZWUhNze30KggIjF96QYbwJts\nJJ5P/X7yd7L4AgICPnnM2dn5ByYpHR49eoRatWoVag8JCUHnzp1FSCQ8FtgCsbOzQ3BwMDQ0NMSO\nUmpER0d/tF1VVRXlypX76BL/VFhQUBCcnJzkhjX/G+9qF9+JEycQEBCA+Ph4bNq0CZs2bcK0adP4\n+1kMaWlp2LdvH0aOHIn79+9jzpw50NXVhZeXF0xMTMSOR0TfQe3atT8535ojAKkkiY2NRWxsLPT0\n9GBsbCx2HIV2584dHD58GPHx8ViwYAECAgLg5uZWatZe4CQNgQwcOBAeHh7o06cPdHR05H5BOL+1\neFxdXREdHQ1lZWXo6uoiJSUFeXl5UFFRQX5+Ppo0aYJly5ZxjvsXHD16FE5OTjh06NBHj0skEhbY\nxbRt2zYcPnwYgwYNwrJly6Curo7Hjx/D29sbixYtEjuewpk5cyZycnJQUFCAWbNmwcLCAlpaWpg5\ncyZ7Xkh0mzdvxvDhw7Fu3bpPnsNtkIru31OUkpOT4efnh6ZNm4qUSPEdOXIEgYGBiImJgb6+Phwd\nHdGnTx+xYymspKQkTJw4ETdu3ICuri6Sk5NRv359+Pr6olKlSmLHUzhHjx7F8uXL4eLigmPHjiE/\nPx+HDh1CQkICpk2bJnY8QbAHWyCc3yq8ZcuWITMzE9OmTYOmpiaysrKwevVqqKurY/To0di4cSPu\n3LmDbdu2iR2V/qPs7OywZ88eGBkZwdzcHNeuXUNqaio6derEfbCLoVWrVjh9+jRiY2Nhb2+PK1eu\nQEtLC82bN8fNmzfFjkf/cXPnzoW3tzc8PT0/eQ73bRZGdnY22rdvjz///FPsKApnx44d2LdvH4YN\nGwYjIyNERkZix44d6NmzJ4YPHy52PIU0ceJEaGtrw9PTE5qamsjIyMCSJUuQnJz82Rtu9HGdOnXC\n2rVrUatWLdl7p9jYWLi4uODixYtixxMEe7AFcvr0abEjlDpHjx7F2bNnZdsiaGhoYPLkybCxscHE\niRPh4eEht6AMfd7bt28RFBSE+Ph4fLivlpubi4iICKxdu1bkdIopOztbtibAh1ErampqXMH1G2Rn\nZyMsLAyNGzdG2bJl8erVK5QpU0bsWETw9vYGwCL6R7h37x7Y/1M8+/btw5YtW1C9enVZW4sWLTB4\n8GAW2MV05coVnDt3DmpqagCAMmXKYObMmVzpvphSU1NhZmYG4P/fO+np6SEvL0/MWILiu0CBcH6r\n8DQ0NHDnzh00a9ZM1nb37l3ZH7ikpCSuMFoEU6dOxfPnz6Grq4v09HQYGxvj/PnzcHFxETuawrK1\ntcX06dMxdepUAO+HNvr4+KBNmzYiJ1NMPXr0gLOzMxITE+Hj44OHDx9ixIgR6N+/v9jRiGTS0tLw\n22+/4dWrV8jNzZU7xuK76Ozs7OSm1eXl5SEhIQHjxo0TMZXiSktLKzR1zsjICFlZWSIlUnyampqI\njY2VWwskLi6OW/MVk5WVFZYsWSJ77wQA69evh4WFhYiphMUh4gL596qNKSkpiIiIQPv27bFmzRqR\nUim24OBgzJ49G+3bt4ehoSGio6Nx6tQpeHl5oX79+hg6dCj69u3LO7JfqWnTpggLC0NMTAzWrFmD\nTZs24fTp09i5cyfntxbT27dvsXjxYgQGBuLdu3dQVVWFg4MDZs+ezZWvi+nu3bsoU6YMatSogfj4\neDx58gQtW7YUOxaRzNChQ5GWloaWLVvKRlh9wDnYRRceHi73WElJCSYmJjAwMBApkWIbN24c9PX1\nMWPGDKirq+Pdu3dYtmwZYmNjOZy5mLZu3Qp/f3/ZsPvo6Ghs27YNLi4ufA9aDElJSZg6dSquXr2K\nvLw8aGlpoW7duli5ciUqVqwodjxBsMD+jk6dOoXAwEAW2N/g77//RlhYGG7fvo1mzZrBwcEBERER\nqFWrFqKjo9G8eXOxIyqMVq1a4cKFC8jMzESnTp1kc9ssLS1x9epVkdMpvqSkJOjq6nKbvm/08uVL\nBAcHyxbn6dix40e38yASS9OmTXHx4kWOoBLIqFGjsGHDhkLtrq6u8PPzEyGRYouLi4OHhwcePnyI\n8uXLIzk5GU2aNMGKFSu4INc32LdvH4KCgpCUlARDQ0N07dqVIwCLKScnBydOnECLFi3w+vVrLF++\nHNWrV8fEiRML7TOuqFhgf2fNmzfH9evXxY6hkPz8/LBs2TLk5ubK5mJJJBLUrFkTx44dEzmd4nF3\nd4e5uTnc3Nzg4uKCX3/9FZqamvDw8Cg1i0qIgdt0CefixYsYO3YsbG1tYWRkhFevXuHs2bNYuXIl\nbG1txY5HBADo168fFi5cCFNTU7GjKKzo6Gj4+voCAI4dO4YuXbrIHc/IyMDNmzdx4cIFMeKVCi9f\nvpQVg4aGhmLHIZL59ddf8ejRIxw6dAiurq6oWLEi1NXVkZqaivXr14sdTxCcgy2Qa9euyT3Ozc3F\nyZMnUbVqVZESKb7NmzfD19cXSkpKOHnyJGbMmAEfHx/2GhTTzJkzMXv2bHTt2hVTpkzB6NGjkZOT\n89kVcenzuE2XsJYvX441a9agdevWsrY///wTPj4+LLBJdB+G11auXBn9+/dHly5doK2tLXcOh4h/\nHSMjI9SrVw8pKSkAgCpVqsgdV1NTg4eHhxjRFBa3kRNely5dcOzYsULrBPwTdwoqukuXLiEoKAhx\ncXG4efMmzp8/D21tbbRo0ULsaIJhgS2Q6dOnyz1WUlJCtWrVMG/ePJESKb63b9+ibdu2SEhIgI+P\nD7S1tTF9+nTY29uzKCyG6tWry4bbGRoaIjw8HNnZ2Vyh+Rvs3btXtk2Xj48PdHR0sG7dOnTq1Ens\naAopMjIS1tbWcm3W1taYOHGiSImI/l9UVBSA98WfjY0N0tLSkJaWJnIqxTVgwAAAQKNGjeRuqlHx\nfPj9/PBf+nZz584FACxZskTkJKVLVlYW1NTUEBwcjDp16kBPTw9JSUmF1rRQZCywBcJtuoRnbGwM\nqVQKMzMzJCYm4s2bN1BWVkZGRobY0RTSp+5qq6mpQUdHB5aWlnLbetCXcZsuYX2Y/vHLL7/I2oKD\ng1GzZk0RUxG9xxXCv49atWph1apVhbaQlEqlOHz4sMjpFMeHbeT69OmDRo0aFTp+/vz5Hx1J4X1Y\n5yc0NBSzZs0qdHzGjBmlauXrH6Vjx45wc3PDs2fPMGnSJEilUkyePBmOjo5iRxMM3wUKJCcnB6Gh\noXjx4gXy8/PljnFITvEMHjwYffv2RWBgIH755Rf0798fqqqqsLS0FDuaQoqJicHRo0fRsWNHGBkZ\nISYmBqGhoWjRogW0tLSwcuVKzJ07Fw4ODmJHVRjcpktYM2bMwNChQ7F//34YGRkhKioKz549w+bN\nm8WORiQTFRWFTZs2Yd68eTh//jymTp0KHR0drFy5EvXq1RM7nsKZMmUKAEBXVxcJCQmoX78+AgMD\n0aNHD5GTKY7MzEwkJycDeP/eKTg4WG4f8fT0dIwbNw63bt0SK6LCef36NQ4dOgQAOHDggOxm+gcZ\nGRnsXCsmLy8vhIaGQltbG9bW1oiMjET//v3RvXt3saMJhoucCWTChAm4ffs2zM3NC/Ve8a538UVG\nRqJy5cpQVlbG8ePHkZaWBmdnZ87DLgZXV1eMHj1abo7L9evX4evri127duHevXuYMmUKQkJCREyp\nWLhNl/ASExNx+vRpJCcnw8DAADY2NoXe2BCJaejQoTA2NoaXlxc6d+6MXr16QVtbGwcOHJC9Iaev\n16hRI1y6dAnR0dFYtGgRduzYgZs3b2Lx4sXw9/cXO55CSE5ORufOnZGamvrR46qqqnB2dua0xSJa\nunQpUlJSProQn6qqKjp16lRoWhMRwAJbMObm5ggKCuK+jVRiNW/eHJcvX5ab45KTkwNLS0vcvHkT\nwPvtZz58Tl/2YQoDwG26vsW/F4n8GHNz8x+QhOjLWrRogUuXLkEqlaJ79+4IDw+Huro6/34Wk62t\nLU6dOoXc3FzY2trKdrUwNzf/qr8NJG/AgAHYs2eP2DFKld9//x29evUSOwYpEA4RF0iFChU475JK\ntPr162PlypWYOHEi1NTUkJ2djVWrVqFOnToAgMDAQM7BLqLBgwdDXV0dbdq0gY2NDVq0aAE1NTWx\nYymcfy8S+W8SiYQrtVKJoaGhgbi4OAQHB8Pc3Bzq6up48OABR1oUU8OGDTF//nxMnToVVapUwcGD\nB6GpqVlohXb6Onv27MHbt2+RmppaaE47d2MoHkdHR/z++++F1gmIiIjA2rVrRU5HJRF7sAXi6+uL\n0NBQODs7Q09PT+5Yt27dREpF9P9iYmIwadIk3L17F7q6ukhOTkaTJk2waNEivHr1CnPmzMGKFSvQ\nsGFDsaMqlL///huXLl3ChQsXcP/+fTRq1Ag2Njbo37+/2NGI6DvYu3cvVq9ejdzcXGzZsgUqKioY\nOnQoPD09OW+4GJKSkuDj44MpU6YgKioKU6dORXp6Ory8vNChQwex4ymcPXv2YOnSpcjNzQUAFBQU\nQCKRyBaRpKLz8PDA8+fPoauri/T0dBgbG+P8+fNwcXGBl5eX2PGoBGKBLRBXV9ePtkskEuzevfsH\npyH6tNevXyM2NhaGhoYwNDQUO06pkJ6ejmvXruHChQs4dOgQJBIJF5Mpgs/t2/oBF4ukkiQxMREa\nGhooU6YMUlNTkZSUBFNTU7FjKaS//vrrk6tec/uuomvdujXmz58PJSUlhISEwNPTEz4+PtDU1OQW\np8XUtGlThIWFISYmBmvWrMGmTZtw+vRp7Ny5k+/x6aM4plkgH/YXJippWLx8PwsWLMD169cRHR2N\nhg0bwtzcHNu3b0eDBg3EjqZQuG8rKZrIyEi8ePFCbqXmv/76iyPWvtLnVr2WSCR48+YNV70uprdv\n36Jt27ZISEiAj48PtLW1MX36dNjb27PALiYtLS3o6elBU1MTDx8+BADY2dnxetInscAWCLfpopKK\nxcv3c/PmTbx48QJ2dnawsrKCubk557EXw5d2Wvj331QiMXl7e+Po0aOoXbs2lJWVZe0SiYQF9lfK\nysqCs7OzbNXrf88N/rDqNRWdsbGxbAHOxMREvHnzBsrKysjIyBA7msKqU6cONm/eDDc3N+jo6ODy\n5cvQ1NTk2kv0SRwiLhBu00WKKj8/nytff4MPw8OvXr2K69evIyEhAU2aNMGqVavEjqZwnjx5go0b\nNyIhIUFuIZkXL17IVhYmEpuVlRX8/Pzw008/iR2lVOCq18IKCAiQbR+5a9cuXLx4EaqqqjAwMMD6\n9evFjqeQnj9/jtmzZ8PHxwePHj3ChAkTkJOTg19//RX9+vUTOx6VQCywBcJtuqikY/Hy/Tx+/BhX\nrlzBlStXcOPGDdSqVYvzsoqhR48eqF69OsqVK4cXL16gTZs22Lt3L7p164bRo0eLHY8IwPuhoYGB\ngdzrXkDR0dEwMjLCu3fvcPDgQejq6sLR0VHsWAorMjISlStXhrKyMo4fP460tDQ4OztDU1NT7Gil\nQk5ODrKzs1GmTBmxo1AJxW4rgXCbLirpPD09IZFIYGZmBlVVVbRr1w4JCQlc7fobjBs3Di1btsTI\nkSPx9OlTODs749SpUyyui+nJkydYtGgRXF1dkZWVhUGDBmH9+vU4ceKE2NGIZPr27YuxY8fi5MmT\nuHbtmtwHFd2OHTtkw8G9vLzw22+/YePGjVi6dKnIyRRTRkYG/Pz8EB0dDYlEgsTERERGRnKk2jco\nKCjA3r174erqCnt7e7i7u+PkyZNix6ISjD3YAuE2XVTSNWrUCNeuXUNUVBRmzZqFvXv34unTp5g4\ncSK37iimDRs2oEOHDqhZs6bYUUqFdu3a4cSJE1BSUkKrVq1w5coVAECzZs1w48YNkdMRvWdnZ/fR\ndu7XXjydOnXC+vXrUblyZVhaWuLIkSPQ19eHvb09Ll++LHY8hTNhwgTk5eXB29sbenp6kEqlWLt2\nLbS0tDhlsZiWLFmCCxcuYPDgwTA0NER0dDR27doFBwcHeHh4iB2PSiB2uQokPDwcurq6OHPmjFw7\nFz2hkqJChQoAABMTE0ilUgBAzZo1ER0dLWYshbZz5064u7uLHaPUsLS0xPjx47F06VLUqVMHa9eu\nhYaGBipVqiR2NCKZ06dPix2hVElJSYGZmRnCwsJgaGgIMzMzZGdny/ZxpqK5dOkSLly4ADU1NQCA\nmZkZli5dChsbG5GTKa7Dhw8jODhY9j4KAGxsbNCtWzcW2PRRLLAFwm26qKRj8SI8e3t7rFixAp07\nd0aFChUgkUhkx4yMjERMpphmz56Nbdu2oaCgAN7e3vD29kZaWhoWLFggdjQiOdevX8fRo0cRExMD\nfX19ODg4oE2bNmLHUkh169bF0qVLER4ejs6dOyMpKQk+Pj5o0qSJ2NEUkpaWFiIjI2FmZiZri4mJ\ngba2toipFJu2tjYyMzPl2iQSCcqVKydSIirpOERcQEeOHEFgYKDsBdfR0RF9+vQROxYRgPf7jm7b\ntg2urq5ITU2VFS8zZsxAs2bNxI6nkGrXrv3RdolEItsrk77eiRMnYG9vX6jd398fPXv2FCERUWGB\ngYFYuHAhevfuDSMjI7x69Qr+/v6YOnUqevToIXY8hRMfH48NGzZAW1sbHh4eePz4MXbu3IkZM2bI\n9RjS19m5cye2b9+Onj17wsDAAHFxcTh48CCGDx/OFa+LadWqVQgKCsLAgQNhYmKC+Ph4+Pn5oX79\n+rCyspKdxxGr9AELbIHs2LED+/btw7Bhw2BkZITIyEjs2LEDPXv2xPDhw8WOR8TihUqk5ORkPH36\nFADg7u6OrVu34p8vS+np6Zg0aRJu3bolVkQiOQ4ODliyZAkaNmwoa7tz5w4mT56MP/74Q8RkRO+d\nOXMGISEhSEhIgIGBARwdHWFtbS12LIXl6ur6xXMkEgkXOCUZFtgC6dChA7Zs2YLq1avL2p49e4bB\ngwfj3Llz4gWj/zQWL9/fnTt3EBAQgLi4OCxYsAABAQFwc3OTGy5On5aZmYn+/fsjJSUFr1+/RuXK\nleWOq6mp4ZdffsGoUaNESkgkz9zcHJcvX5bbOSQ3NxdWVla4fv26iMkUi52d3Rf/TnLROCJSRJyD\nLZC0tLRCcy6NjIyQlZUlUiIiQENDA4sXL0ZKSgrevXuHadOmyR1XU1PjCItvcPToUSxfvhwuLi4I\nDAxEXl4eDh06hISEhELXmj5OU1MThw8fBgBMmzYNy5YtEzkR0ec1bNgQ27dvl/vbuX37dtSvX1/E\nVIpnyZIlYkcolT5344I3LIpn3bp1nzw2ZsyYH5iEFAV7sAUybtw46OvrY8aMGVBXV8e7d++wbNky\nxMbGfvYfJtGPwuJFeJ06dcLatWtRq1YtmJub49q1a4iNjYWLiwsuXrwodjyFcePGDTRr1uyz+wib\nm5v/wEREnyaVSjFs2DDk5+ejcuXKeP36NTQ0NLBx40aYmpqKHU8hvX37FqmpqbIRVrm5uZBKpbC1\ntRU5meIJDw+Xe5ycnIz9+/fD1tYWAwcOFCmVYvP09JR7nJycjKtXr+KXX36Bl5eXOKGoRGOBLZC4\nuDh4eHjg4cOHKF++PJKTk9GkSROsWLGCqzSTqFi8fD9WVla4cOECVFRUYGFhgfDwcOTk5KB169ay\nPZzpy5ycnBAUFMT9hUlhZGdn48aNG0hKSoKBgQEaNWoEVVVVsWMpJD8/Pyxbtky2LVdBQQEkEglq\n1qyJY8eOiZyudHjz5g2cnZ0RFhYmdpRS46+//sLq1auxY8cOsaNQCcQh4gKpVKkS/P398fLlSyQl\nJcHQ0BCGhoZixyLC3LlzERQUhOnTp3/0OIuX4rOyssKSJUswdepUWdv69ethYWEhYirFExQUWiBS\nLgAAIABJREFUBID7C1PJFhQUBCcnJxw5ckSu/dWrV3j16hUAriJcHJs3b4avry+UlJQQEhICT09P\n+Pj4QFNTU+xopUZKSgoyMjLEjlGq1K9fH3fv3hU7BpVQ7MH+Rps3b8bw4cM5P4PoPygpKQlTpkxB\neHg48vLyoKWlhbp162LlypWoWLGi2PEU0tmzZ+VWv+3atSssLS3FjkUEd3d3bNmy5ZMrCnMV4eJp\n1qwZbty4gYSEBLi5ueHYsWPIyMiAvb09/vzzT7HjKRxXV1e5Odh5eXl48OABevTogZkzZ4qYTHH9\n+6Zabm4uwsLC8ObNG+zdu1ekVFSSsQf7G0VFRcn9l6gkY/EiLD09PWzfvh3x8fF4/fo1KlasWGgV\nbPp6W7Zswa5du9CzZ080adIE0dHRmDx5MsaOHYvevXuLHY/+47Zs2QIAn7yBJpVKf3SkUsHY2BhS\nqRRmZmZITEzEmzdvoKyszB7XYnJxcZF7LJFIUK1aNTRp0kSkRIrv0KFDco+VlJRQrVo13rCgT2IP\ntkD++usvNGrUqFD7+fPn0bp1axESEcn7Z/FiaGiI6OhoHDp0iMXLN+JNC+G0bNkSe/fulVsoSiqV\nws3NjT1ZVGI0bdoUN2/elGvLyMhA69atC7XTlwUEBGDx4sUIDAzErl27cPHiRaiqqsLAwADr168X\nOx4RgPcj1rS0tKChoYGIiAjo6OhAX19f7FhUQrHA/gaZmZlITk4GADg6OiI4OLjQHsO9e/fmHsNU\nIrB4ER5vWgirVatWCAwMhJ6enqztzZs36Nq1K86cOSNiMvqvi4qKgpOTE7KysmSLcP1bq1atZL3c\nVDSRkZEwNDSEiooKgoKC8ObNG7i4uEBDQ0PsaAqjdu3aX9xX/OHDhz8oTenyxx9/YPr06dizZw/q\n1q2LnTt3YsOGDVi5ciWsra3FjkclEIeIf4OsrCw4OzsjNTUVAAptJ6GqqgpnZ2cxohEVoqSkBB0d\nHbm2SpUqQVlZWaREim/Hjh2Fblp07doVbm5uLLCLoV+/fnB3d8fo0aNhbGyM+Ph4bN68GW3atJFb\nBZ+r3tOPVqVKFYSFhSEzMxOurq7Ys2ePXKGtpqbGdReKadSoUdiwYYPscZcuXQC8n0vs5+cnViyF\nc+rUKRQUFMDf3x9Pnz7FuHHjUKVKFdl2sTVq1BA7osJavnw5tm7dirp16wIABg8ejAYNGmD27NkI\nDg4WOR2VROzBFsiAAQOwZ88esWMQfdL69etx6tSpQsWLqakpnJycZOexePl67HEV1qe26fonrnpP\nJVFeXh6kUil+/vlnsaMohOjoaPj6+gIAjh07JiuqP8jIyMDNmzdx4cIFMeIptBYtWuDMmTNyvf9Z\nWVmwsbHB1atXRUymuJo2bYpr167JdUjk5uaiZcuWhfYdJwLYgy2YPXv24O3bt0hNTZUNE8/NzYVU\nKi3Us00khoMHDwIAFi5cKNf+6tUrnD9/HgCLl6Jij6uwuE0XKYKQkBAsWLAAiYmJcu3lypVjAfOV\njIyMUK9ePaSkpAB4P0Lgn9TU1ODh4SFGNIWnpqYGqVSKevXqydoePnyIMmXKiJhKsTVp0gSrVq3C\n+PHjoaqqipycHKxbtw6NGzcWOxqVUOzBFsiePXuwdOlS5ObmAoBs6FjNmjVx7NgxkdMR0ffAHldh\nFRQU4NKlS4iPj5e15eTkICIi4pP7uBP9aO3atcOQIUOgrq6Oy5cvw93dHatXr0ajRo0watQoseMp\nHC4GKyx/f38sWbIEHTt2RKVKlRATE4NTp05h3rx5cHBwEDueQoqKisLYsWPx5MkT6OrqIjk5GQ0a\nNMCqVatgaGgodjwqgVhgC6R169aYP38+lJSUEBISAk9PT/j4+EBTUxOenp5ixyNi8UIlnqenJ86e\nPQsdHR3k5ORAW1sbjx49gr29PVauXCl2PCIA73uzbt26hdjYWIwaNQqHDx9GUlISevTowVEYReDl\n5QUvL6/PvkdavHjxD0xUely7dg1z587F8+fPMWjQILRr1w7NmzcXO5bCi4yMRGJiIgwMDLglJ32W\nktgBSou3b9+ibdu2qFu3Lu7evQttbW1Mnz4dJ06cEDsaEQDg119/xZQpU7Bx40b4+vpi586dmDNn\nDmJjY8WOprBycnIQGBgI4P1Q+3HjxmHOnDmy3QWoaMLCwmS9L/Xq1cORI0cwb948ZGZmih2NSKZy\n5cqIj4+HgYEBoqKikJ2dDW1tbdlwZ/o6HwqUKlWqfPKDiu7+/fuYOHEiypUrB3V1ddlUpiNHjogd\nTWE9ffoU3bp1Q0pKCho3bozdu3eje/fuiIyMFDsalVCcgy0QY2NjSKVSmJmZITExEW/evIGysjIy\nMjLEjkYE4H3xEhAQgISEBGzfvh1r166Fv78/e1y+wdy5c/Ho0SN07doVnp6eqFixInJycjBz5kzu\n31oMKioqMDY2hq6uLu7duwcAcHFxYe81lSjOzs7o3bs3Dhw4ADs7O4waNQpqampyc17py0aMGAEA\nSE1NxYQJEzhHWCDz5s3DrFmz0LlzZ1hYWMDExARbt26Fp6cnunXrJnY8hTRr1ix06dIFderUAQBM\nnjwZu3fvxsyZM7F7926R01FJxAJbIIMHD0bfvn0RGBiIX375Bf3794eqqiosLS3FjkYEgMXL93Dp\n0iUEBQUhLi4ON2/exPnz56GtrY0WLVqIHU0hfVizokuXLlBWVoZUKoWamhry8/PFjkYk4+7ujkaN\nGqFcuXLw8vLCjh078ObNGwwePFjsaArp+PHjmDJlitgxSo2IiAh07NgRAGSL7jZr1gxJSUlixlJo\nT548wf79+2WPVVRU4ObmJre9HNE/scAWiLOzM5o3b44KFSpg2rRpOH78ONLS0rgPNpUYLF6El5WV\nBTU1NQQHB6NOnTrQ09NDUlISVFVVxY6mkKZOnYpJkyahcePG8PDwgKOjIzQ1NTFo0CCxoxHJsbCw\nkH0+cuRIEZMoPhsbGwwePBi2traoWLGibG9xAOxxLYaaNWvixIkTcHR0lF3Ls2fPombNmiInU1zG\nxsYICwtD+/btZW3nzp2DiYmJiKmoJGOBLZCMjAz4+flhwIABqFq1KhITExETEwMlJU5zp5KBxYvw\nOnToADc3Nzx79gyTJk2CVCrF5MmT4ejoKHY0haSlpYUyZcogJSUF3bp1Q3h4OMLCwtC9e3exoxGh\ndu3acsXfP33YOeThw4c/OJXie/XqFVRUVGTbRX4gkUhYYBfDrFmz4O7ujr179+Lt27cYMWIE7t27\nx97WbzB9+nSMHTsWdevWRaVKlRAXF4fHjx/jf//7n9jRqITiKuICmTBhAvLy8uDt7Q09PT1IpVKs\nXbsWWlpaXAWTSoSnT59i8uTJWLBgARo0aIBff/0VYWFhOHToEO/CFlNWVhbOnj0LbW1tWFtbIzIy\nEleuXEH37t15c60Y+vTpg44dO2LgwIFQUVFBbm4udu/ejbNnz3KeG4kuKirqi+dwYS4qCdLT03Hu\n3Dm8fv0aFSpUQNu2baGrqyt2LIUWFxcHf39/qKqqIjc3F927d4eBgYHYsaiEYoEtEAsLC1y4cAFq\namqytqysLNjY2ODq1asiJiN6j8WL8GxtbREUFMTFeQTSrFkz3LhxQ66toKAAFhYWuHbtmkipiAqL\niYlBUFAQYmNjMX78eFy8eBGdOnUSO5ZCiouLw969exEfHy+bM5ybmwupVIrDhw+LnI4IuHfvHoYP\nH46qVavCyMgIr169QkREBLZu3YrGjRuLHY9KIHaxCERLS6vQcv0xMTHQ1tYWKRGRvCdPnmDIkCFQ\nUXk/M+TDIh0c0lh82traeP78udgxSo0P89z+ifPcqKS5cOECfvnlFzx8+BCHDh1Ceno65s+fj23b\ntokdTSFNmTIFt27dQnp6Ol68eAFtbW2cP38eLVu2FDsaEQBg0aJFmDJlCvbv34+VK1fi999/h6en\nJxYuXCh2NCqhOAdbIIMHD4abmxt69uwJAwMDxMXF4eDBgxg+fLjY0YgAcJGO76F8+fLo3bs3TExM\nUKFCBbn5mRwVUHSc50aKYNmyZfD19YWFhQXMzc1haGiIXbt2YejQoRg6dKjY8RTOnTt3cPHiRURH\nR2PRokX49ddf0blzZ06voxLjyZMnhdYD6NatGwts+iQW2AIZPHgwqlWrhpCQENy+fRsGBgZYuHAh\nrK2txY5GBIDFy/fQrVs3LsIjoJYtW+LkyZM4d+4cEhMT0bp1a7Rp0wZ6enpiRyOSiYmJQfPmzQFA\ndlPN1NQUb9++FTOWwipfvjw0NTVRrVo1PH78GADQtGlTjg6iEsPIyAhXrlyRG1URHh4OY2NjEVNR\nScYCW0C2trawtbUVOwbRR7F4ER634RNehQoVuGo4lWgNGjTA9u3bMWzYMFnbwYMHUb9+fRFTKa6G\nDRti3rx5mDZtGqpUqYKDBw9CU1OTU+yoxJg0aRI8PDzQrl07VKlSBa9evcLZs2excuVKsaNRCcVF\nzgRiZ2f3ye07Tp069YPTENGP8Lltezi3nah0ioyMxMiRI5GRkYH4+HiYmpoiJycHGzduhKmpqdjx\nFE5SUhJ8fHwwZcoUREdHY8qUKUhPT4eXlxc6dOggdjwiAMDff/+NkJAQJCUlwdDQEPb29vz3Tp/E\nAlsg4eHhco+Tk5Oxf/9+2NraYuDAgSKlIqLv6d/b9iQnJ8PPzw9NmzZF7969RUpFRN9TixYtEBYW\nhsePHyMmJgYVK1ZEo0aNoKqqKnY0hSSVSrFlyxbExMQgPz9ftpK4RCLhWhZEpJBYYH9Hb968gbOz\nc6FVcYmo9MrOzkb79u3x559/ih2FiL6DAQMGwM3NDe3atRM7SqnQpUsX1KlTB5aWllBSkt/chtNw\niEgRcQ72d5SSkoKMjAyxYxDRD3Tv3j3wviVR6ZWeng4PDw9oaGhAT09PbpoIp4QVXXR0NAICAmRb\nSBIRKTr+NROIq6ur3ItsXl4eHjx4gB49eoiYioi+p3+vvZCXl4eEhASMGzdOxFRE9D39+uuvYkco\nVRwcHHDs2DH2VhNRqcEh4gIJCAiQeyyRSFCtWjU0adJEpERE9L39e+0FJSUlmJiYwMDAQKRERESK\n5dy5cxg9ejTKli2LsmXLyh3jiAAiUkQssImIvkFaWhrOnTuHmJgY6Ovrw8bGBvr6+mLHIiJSCG3b\ntkX37t3RvHlzKCsryx2zsLAQKRURUfGxwP5Gn9um5wNu10NUOt27dw/u7u6oVq0ajIyM8OrVK0RE\nRGDr1q1o3Lix2PGIiEo8S0tLXLly5YvvpYiIFAUL7G8UFRWFgoIC+Pv74+nTpxg3bhyqVKmC2NhY\nrFu3DjVq1MDYsWPFjklE30G/fv3Qo0cPuLi4yNoOHTqE/fv3w9/fX8RkRESK4X//+x9yc3Ph5uaG\ncuXKiR2HiOibscAWSIsWLXDmzBloaGjI2rKysmBjY4OrV6+KmIyIvhdzc3NcvXpVbmuZvLw8mJub\n4+bNmyImIyJSDDY2NoiNjZXrwS4oKIBEIuEIQCJSSFxFXCBqamqQSqWoV6+erO3hw4coU6aMiKmI\n6HsyMjLClStX0LJlS1lbeHg4jI2NRUxFRKQ49u3bJ3YEIiJBscAWyJgxYzBw4EB07NgRlSpVQkxM\nDE6dOoV58+aJHY2IvpNJkybBw8MD7dq1Q5UqVfDq1SucOXMGq1atEjsaEZFCqFKlitgRiIgExSHi\nArp27Rrmzp2L58+fY9CgQWjXrh2aN28udiwi+o4ePXoEPz8/xMTEoFmzZrC3t4eamhqMjIzEjkZE\nREREPxgLbIHcv38fI0aMgLGxMR49eoTAwEB07doVc+fORbdu3cSOR0TfwZEjR+Dt7Y3MzEy5ds4d\nJCIiIvpvYoEtkN69e8PNzQ2dO3eGhYUFwsPDcePGDXh6eiI0NFTseET0HbRq1QozZ85Ehw4doKLC\nGTdERERE/3V8RyiQiIgIdOzYEcD71S8BoFmzZkhKShIzFhF9R0pKSujUqZPcKuJERERE9N/Fd4UC\nqVmzJk6cOAEAsq0mzp49i5o1a4oZi4i+oz59+mDZsmVIT08XOwoRERERlQAcIi6Q+/fvw93dHdWr\nV8edO3dgbW2Ne/fuYcOGDWjYsKHY8YhIQLVr14ZEIpGNVuH+rURE9DFpaWlYv349/vjjDyQmJqJK\nlSro1asXBg4cKPfaUZLUrl0bS5Ys+eo1hDIyMmBtbY2ZM2eiZ8+ehY7PmjUL8fHx2LRpk9BRiUok\nDhEXSL169RAaGopz587Bzs4OFSpUwNKlS6Grqyt2NCIS2KlTp8SOQEREJVxKSgp69eoFAwMDLF68\nGFWqVMGdO3cwf/58REZGYtasWWJHFESZMmXQtm1b/PHHH4UK7Ly8PISFhZWan5Xoa7DAFlDZsmXh\n6Ogodgwi+s64bysREX3J8uXLoa6uju3bt0NVVRXA+9cPDQ0NeHh4wNXVFdWqVRM5ZWH6+vqoWLFi\nkb7GyckJEydORHp6OsqWLStrv3TpEt69e4d27doJHZOoxOIcbCIiIiIiAWVnZyM4OBiurq6y4voD\nW1tb7Ny5E0ZGRgDeD8leu3YtrKysMHr0aACAv78/7O3tUb9+fVhZWWHevHmyaUmenp5Yvnw5Jk6c\niMaNG8PJyQkPHz7EqlWrYG5uDhsbG4SEhMi+X0xMDEaOHInGjRujXbt2WLduney5AgIC0LdvX4wZ\nMwbm5uY4duwYTE1NUaNGDQDA7t27YWdnh4YNG6JHjx64cePGR3/eNm3aQENDA2fOnJFrDwkJgZ2d\nHTQ1NQW4qkSKgQU2EREREZGAIiMjkZmZifr163/0uIWFhVzhffbsWRw4cACTJ0/GtWvXsHDhQkye\nPBmhoaGYN28eDh48KDc9affu3bCyssKxY8ego6ODQYMGITk5Gb///jvs7Owwd+5c2bljxoxBpUqV\ncPToUSxZsgTHjx/Hxo0bZcdv3bqFn3/+GQcOHEDr1q2xZ88eVK5cGQ8fPoSPjw+8vLwQEhKCZs2a\nYcKECR/9edTU1NChQwe5rWlzc3MRFhaGLl26FPs6EikiFthERERERAJKS0sDAGhra3/V+X369EG1\natVgZmYGLS0tLFq0CO3bt4eRkRE6duyIunXr4smTJ7Lz69Wrh969e8PExAROTk7IysrCrFmzYGpq\nigEDBiAtLQ0JCQm4fPkyXr9+jXnz5qFatWowNzfHtGnTsHPnTtlzKSkpYeTIkahRo4bc2kFRUVFQ\nUlKCkZERjIyMMGHCBPj4+CA/P/+jP0OXLl1w4cIFZGVlAQAuXrwIiUSC1q1bF/XyESk0zsEmIiIi\nIhKQrq4uCgoKkJqaChMTky+e/2G4OPC+eNbQ0ICvry+ePHmCx48f4+XLl2jVqpXsnH8+p4aGBipU\nqAA1NTXZY+D9MPWIiAgkJyejSZMmsvMLCgqQnZ2N1NRUAICenp7sa/+pVatW+Pnnn+Hk5IS6devC\nzs4OvXr1gpLSx/vnLC0tUaZMGfz555/o2LEjQkJC0KlTJygrK3/x5ycqTdiDTUREREQkoKpVq0Jb\nWxv379//6PHRo0fj8uXLssfq6uqyz8+fPw8XFxckJCTAxsYGvr6+cgUygEJF66e2/MrNzYWZmRkC\nAwNlH8eOHcPJkydlvev//N7/pKGhAX9/f+zevRuWlpYICAiAi4sL4uLiPnq+kpIS7O3tERoaitzc\nXJw6dYrDw+k/iQU20b/Y2dmhdu3ahT7q1KmDa9euAQCSkpLkFhD5L1m3bh1cXV0Ff15XV1esW7dO\n8OclIiL60ZSVleHg4IA9e/YgNzdX7tjp06dx5swZGBgYfPRr/f390aNHD3h7e6N79+4wNTXFy5cv\ni5XD1NQU0dHRKF++PExMTGBiYoKXL19izZo1X9yH+/bt29i4cSMsLCwwffp0nDhxAu/evfvkQmfA\n+9XE//zzT1y8eBFlypRB8+bNi5WbSJFxiDjRR8yaNQv29vaF2nV0dAAAPj4+AIDOnTv/0FwlxZde\nlImIiP7rxo4di169emHo0KEYM2YMDA0NceXKFSxfvhyDBg2SrdT9b7q6urh16xYeP34MiUSCTZs2\nISEhAdnZ2V/9vT+sEt6qVSsYGRlhypQpmDRpEtLS0jBnzhxYW1t/8bVcQ0MD69atg76+Plq2bInw\n8HBkZmaiVq1an/yaRo0aQUdHB6tXr4aDg8NX5yUqTdiDTfQRZcuWhb6+fqEPFRXekyIiIqIvq1Ch\nAn777TeYmJhg6tSp6NKlC3bv3o3x48dj+vTpsvP+XeiOHTsWenp66N27N4YOHQpNTU307dsXDx48\n+Orv/eE5lZSUsGHDBgBA7969MX78eNja2mLWrFlffI7atWtj8eLF2LZtGxwcHLB582b4+Ph88sbA\nBw4ODvj77785PJz+syQFH25xERGA90PEx40bh27dun30+Lp162RDmatUqYJTp07h6dOnWLx4MW7d\nuoXc3Fw0aNAA8+fP/+SL0OvXrzFr1izcvHkTmpqacHBwwIwZM6CiooKcnBwsXboUR48eRdmyZTF9\n+nRMmDABp0+fhpGREWrXrg0/Pz+Ym5sDeL+Hpa+vL06fPg0AOHXqFNatWwepVAp1dXW0adMGCxYs\ngKamJtatW4eHDx8iNTUVT548wf/+9z80bNgQy5YtQ1BQEACgdevWmDVrlqy3XiqVYvbs2Xjw4AEa\nN24MMzMzPHnyBLt375b7mdLT09GyZUts3boVFhYWAICMjAy0aNECO3fuRNOmTbFx40b4+/sjNjYW\n5cuXR+/evTFmzBgA74eIW1paYsyYMfD09AQALF68WPb8//y5s7OzP5t59+7d2LlzJxISEvDzzz/D\n09MTzZo1K8qvARERERFRkbEHm6iIhgwZAnt7ezg4OODQoUMoKCjAqFGjULVqVQQGBuLAgQPIy8vD\n8uXLP/kc8+fPR5kyZRAYGIj169fj5MmT8Pf3BwCsWrUKZ86cwcaNG7FixQr4+vp+cRjXh+ORkZEY\nP348+vfvj5CQEKxZswaXLl3CgQMHZOeePn0aXbt2xa5du9CgQQOsXLkS9+/fx9atW+Hn54f09HSM\nHz8ewPsVSIcPH45q1aohICAAHTt2lHuufypbtizatGkjtwfmmTNnoK+vj6ZNm+LIkSPw8/PDokWL\nEBoaijFjxsgK/qL6XOYHDx589b6dRERERERC4nhXoo+YO3cuvL295dqMjY1x7NgxaGlpybbA0NXV\nRWZmJvr27Yt+/frJ2p2dnbFt27ZPPn9UVBTq1auHypUrw8TEBFu2bEG5cuVQUFCAw4cPY+bMmbIe\n16lTp2LUqFFflTs/Px9z5sxBjx49ALzf9qNly5Z4+vSp7Bx9fX306tULAJCVlYW9e/fi8OHD+Omn\nnwAAS5cuhZWVFZ48eYKoqCikpqbCy8sL6urqMDU1RXh4OJKSkj76/R0cHLBs2TLZ0LPQ0FDZPHUj\nIyMsWrQIlpaWAN4PVfuwBUmdOnW+6uf7mszR0dGF9u20tbVFfn7+J7cWISIiIiISAgtsoo8YP348\nOnToINf2qfnXmpqa6NOnDwICAnDv3j1ERETgwYMHqFChAoD3xXpgYCCA9z3NwcHBGDZsGDw9PfHH\nH3+gTZs2sLe3R/v27ZGUlISUlBTUrl1b9vxNmjTB187kqFatGtTU1LBx40Y8efIET548gVQqRdeu\nXWXnGBsbyz6PjIxETk4OevfuXeh7PH/+HC9fvkS1atXktvBo0KABzp0799Hvb2tri5kzZ+LOnTv4\n+eefcf78efj5+QEALCwscOfOHaxcuRJSqRQPHz5EYmIi8vPzv+pn+1LmgoICPH/+HK1bty7Svp1E\nREREREJhgU30EXp6ejAxMfmqc9++fYvu3btDX18fdnZ2cHJyQkREBLZv3w7gfbE+bNgw2fmVKlVC\nly5d0LJlS4SFheHMmTOYMGEC3N3d4e7uDgByhaOamtpnv/8/t//4+++/0a9fP7Rr1w7m5uZwc3PD\nzp075c7/5/Pl5eVBIpHgt99+g5aWVqFr8PLly0KFt6qq6iezaGpqwtbWFidPnkRMTAwqVqyI+vXr\nA3i/7cjixYvRq1cvdOrUCTNmzPjq7b7y8vIKff6xzPr6+rJ9O8PDw3HmzBkEBARg//79OHz4MCpV\nqvRV34+IiIiIqDjYpUP0jcLDw5GQkAA/Pz8MGTIELVq0QFRUlKww/VCsf/hQUlLCqlWrEB8fj969\ne2Pjxo0YN24cQkNDoaWlhcqVK+Pu3buy579//77cHGxVVVVkZGTIHkdGRso+P3r0KCwsLODj44M+\nffqgfv36ePHixSezm5iYQFlZGcnJybJ8WlpaWLhwIZKSkvDTTz/h+fPnSE9Pl33Nl+ZMOzg44OzZ\nswgLC5Pb6mz//v0YM2YMZsyYga5du0JHRwcJCf/X3v27NA6AYRx/BOlglgqKWPwHFAqdFZ2qkyWF\nKhQqDgqiKIUOihCkYqn4L+ggiCBIobjoIGRxqOCoXeqvKhLEoqIoOgk3HFfsWb3DC5zC9wOZQsqb\nbE/fkOe66nb+93t83f9ZbWbDMJROp3Vzc/Op3k4AAADADQRsoIqHhwddX1+/OZ6fnyVJdXV1chxH\nV1dX8nq9enp60vb2thzHUSaT0dra2od9lcViUalUSoVCQUdHR9rZ2VFbW5skaXh4uPxxsnw+r3Q6\nXXGt3+/X6uqqzs/PZdu2stls+Vx9fb0KhYL29/dVLBa1sLCgg4ODd2cxDEN9fX1KJpPa29vT8fGx\npqamdHFxoZaWFrW3t8vn88myLJ2cnCibzWpra+vDZ9fV1aVSqSTbtis6ML1er3K5nM7OzpTP55VI\nJPTy8lJ1Nr/fr1wup93dXR0eHiqVSpU374ZhqL+/v2LmycnJ8sy/ejszmYwcx9Hm5uYfezsBAAAA\nNxCwgSrm5+fV2dn55lhZWZEkmaap09NThcNhBQIBjY2NaW5uTqZpamNjQ8lkUre3typwgZBdAAAB\nRUlEQVSVSlV/f3Z2Vg0NDRocHFQ0GlVTU5Msy5IkxWIxRSIRJRIJjY6Oqre3t+LamZkZ3d3dKRQK\naXl5ufz1bOln1VUgENDQ0JAGBgZ0eXmpiYmJD7szp6en1dHRoXg8rmg0Ko/Ho6WlJdXU1Ki2tlaL\ni4u6v79XJBLR+vq6YrHYh8/O4/EoGAyqubm5ItRalqXHx0eFw2HF43G1traqu7u7PNvrLb1pmurp\n6dH4+LhGRkYUCoXU2Nj4VzN/trcTAAAA+Ff0YANfnOM4CgaDsm1bPp/vf48DAAAA4B1ssIFvgP/B\nAAAAgK+PgA18A69fnwYAAADwNfGKOAAAAAAALmCDDQAAAACACwjYAAAAAAC4gIANAAAAAIALCNgA\nAAAAALiAgA0AAAAAgAsI2AAAAAAAuICADQAAAACACwjYAAAAAAC44AcMyY85kbvofwAAAABJRU5E\nrkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xfb8031ce10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Export is successful!\n"
     ]
    }
   ],
   "source": [
    "md_text = '## Rank variables based on linear relationships with reference variable (on sampled data)'\n",
    "filename = ReportMagic.var_files='tmp/rank_associations.csv'\n",
    "export_filename = 'rank_report2.ipynb'\n",
    "silentremove(filename)\n",
    "cols_list = [conf_dict['Target']] + conf_dict['NumericalColumns'] + conf_dict['CategoricalColumns'] #Make target the default reference variable\n",
    "cols_list = list(OrderedDict.fromkeys(cols_list)) #remove variables that might be duplicates with target\n",
    "w1 = widgets.Dropdown(    \n",
    "    options=cols_list,\n",
    "    value=cols_list[0],\n",
    "    description='Ref Var:'\n",
    ")\n",
    "w2 = ipywidgets.Text(value=\"5\", description='Top Num Vars:')\n",
    "w3 = ipywidgets.Text(value=\"5\", description='Top Cat Vars:')\n",
    "w_export = widgets.Button(description='Export', value='Export')\n",
    "handle_export_partial = partial(handle_export, w1=w1, w2=w2, w3=w3, export_filename=export_filename, md_text=md_text)\n",
    "w1.observe (handle_change,'value')\n",
    "w_export.on_click(handle_export_partial)\n",
    "\n",
    "%reset_report\n",
    "%add_interaction_code_to_report i = interactive(InteractionAnalytics.rank_associations, df=fixed(df), \\\n",
    "                                                conf_dict=fixed(conf_dict), col1=w1, col2=w2, col3=w3, Export=w_export)\n",
    "hbox = widgets.HBox(i.children)\n",
    "display(hbox)\n",
    "hbox.on_displayed(InteractionAnalytics.rank_associations(df=df, conf_dict=conf_dict, col1=w1.value, \\\n",
    "                                                         col2=w2.value, col3=w3.value, Export=w_export))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <a name=\"two categorical\"></a>Explore interactions between categorical variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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p1KgRHh4epKamEhcXR3JyMp999hkdOnRAU1NTBP+CILwU\n6gcRgIyMDIYNG8avv/6Kvr4+e/fuxdjYGF9fX9LS0jh69Cht2rShcePG7Ny5kz179rBixQpSUlIY\nN24ctWvXfs1nIwiC8GaytLQkJiaGRYsW0b59exo2bMiGDRvo27cvVatWpXr16pw/f57Tp0/Tq1cv\n/Pz8KCws5PTp03Tv3p2BAwe+7lP4R5RKJU5OTuzcuZOkpCRCQkK4cOECKSkpfPjhhygUCszMzEhI\nSCArK4tRo0ZRWlrK8ePH2b17Nz169KBPnz6VPq7yE6DFxcUcPHiQW7duYWZmxowZMxg4cCCWlpYY\nGBjIP6ObN2/i6+tLkyZNqF69OgcOHKB9+/aYmZn9V99T/X/u5s2b2bZtG/C0loCWlhaBgYEcPXqU\nL774Ajc3Nzw8PDh8+DCNGzfG3Nwca2trLC0tOXToEL169fpbSXexBUCQpaenExISwoIFC/j11185\ndOgQSUlJ9OjRg9jYWB49eiQXK8nNzUWlUlG1alX561u2bImpqelL2/+v/mVZsGAB77//PgkJCeza\ntYuEhASMjIywtbXl2LFj8us9PT25ePGiXKQDoGfPnrRr167C8SqbSqXi4cOHHDlyhKKiInJzc9HR\n0cHZ2ZmysjICAwMJDw9n5MiRDBgwgG3btnHy5EmGDRuGlZUVM2fO5IcffmDPnj04ODi8lDEKgiCo\nKRQKeUnq3r17qV69OrGxsXz77bdYW1uzceNGHj9+TEhICI8fPyYmJgYjIyOioqL49ttvGT16NLGx\nsXKhKkEQBOHF3N3duXTpEgcOHMDHxwdPT0/mz58vf37MmDGcP3+e7du3U7duXT7++GMiIiLo0qUL\n8PKWvle2vLw8eUtZ+bigrKwMTU1NNm3axIMHD+jduzdWVlby3n4zMzM++ugjtm3bxpUrV+jSpQsz\nZsxg69athIaGyseoTOol9EuXLuXzzz9n9uzZJCQkoKenh6mpKUlJScDTFQympqZoaWlRVlaGSqVC\nW1ub5s2bc+jQoQoF4/8vd+/eZcKECURGRgJPa5iNHDmShg0bYmJiwubNm/niiy8YM2YM2tranD9/\nnjFjxshfHxgYiEKh4OTJk3/rnEUCQJDFx8djb29PZGSkXETv0KFDWFlZ4erqyogRI7h27Rr37t3j\n+PHjeHl5vXAZ/cucqT579iwHDx5k5syZjBs3jp49ezJ37lzq1auHiYkJ+/btkwsR7t+/H39/f+rW\nrfvSxqNW/mZUvXp13N3dKS4u5sCBA6SlpcmzYgqFAjc3N+rXr8/gwYPlG/qJEydo27at/Jo3odWJ\nIAj/Ts/WJUlJSWHkyJFkZ2eTmZkp34tWrFhBUVERZWVlrFmzBicnJ1q0aMGcOXNo2LAh6enpWFtb\n07x589dxGoIgCG+cvwpOy8rKKCkpwcHBgZYtW7Jy5UqKi4uZNm0aMTEx8l53MzMzQkJCyM3NfS5w\nhrejK9SVK1dYsWIFOTk5wJ9xgXqmvV27djg4OPD9999Tv359AgMDiY2NJTs7G01NTRo2bIirq6vc\nWk9fX1/+eng512DChAnExMQQFhZGgwYNOH/+PPv27WPQoEGsW7eO/Px8tLS00NLSoqioiDp16lTY\ne69UKp/7v/Wv3gupqanMmDGDU6dOsW7dOr755ht5JV1UVBS3b9+moKAAe3t78vPzSUhI4KuvvpJX\ngJSVlXH8+HFKSkqoU6fO3zpfsQXgHXPx4kWMjIzkqpZqpaWlzJ8/n6CgIFxcXDAwMMDQ0JCUlBR0\ndXXp378/+/bt48iRIyxevJgGDRrwxRdfvLQl9Pr6+hWWpart2bOHK1euMHToUIyNjQkMDCQyMpKq\nVavSvn17zpw5w7Jly4iNjeXgwYMMHz4cW1vbSh/js9TjPHLkCEOHDsXJyQktLS1Onz5NdHQ0VatW\nRaFQYGdnh6WlJcbGxsyaNYsrV64wadIkzMzMGD58ODo6Oi99rIIgvJtSU1PR1NSUC6GqaWpqMm3a\nND788EMCAgIwNTUlLCyMJ0+eMG7cOO7evcuhQ4fw8PCgRYsW1KtXj8GDB7+S5KogCMLbonyNqkeP\nHslLs9WFnJVKJRkZGbRt25YVK1YA4O/vT25uLmvXrpWXt/v4+NCkSZMKz8Bv0zbQx48fs3btWnJz\nc0lJScHW1hZdXV05YC4sLKR27dqsWrUKLy8vPDw8SE5O5tKlS/j7+6Onp4e/vz++vr4VjvsyAn9J\nkigoKGDr1q188cUXeHl50bJlS27dusXNmzcJDAwkNzeXn376iaysLBYtWkR2djaDBg3C2Nj4L8dX\nUFBAbm4uRkZGz31PAwMDbty4wenTp2nRogXVqlVDV1eXqlWrsmLFCj799FNiYmJISEhg5syZNG7c\nmOHDh2Nvbw88fS/s3LmT6tWr0759+7/13hAJgHdIVFQUixcvxsHBAUtLS+DPjKSWlhZJSUlcunSJ\nDptc0nsAACAASURBVB06UFZWRs2aNdm2bRvnzp0jKCiIPn364O3tTa9evejQoQMaGhovDNL/iXv3\n7uHn54e3tze1atWSs4XqAnp5eXlkZWXJBUTgaWZw1qxZ9OvXj44dO+Lj44ODgwPh4eFYW1tX2tjK\nUxcjVF+DkpISpkyZwsGDB+nZsye9e/dGoVBw/vx5Tp48SePGjVmyZAkZGRnUrFkTHx8fQkJCMDc3\np0uXLgwcOFAE/4IgvDSJiYns3bsXb29viouLmTp1KnXr1sXExARNTU3S09PlFUrnzp0jKyuL+fPn\nU7VqVWJjY7l58ybXr18nODgYGxubCtu/BEEQhKeB2f379xk2bBhxcXGcPn2aBg0aUKVKFfLy8hg1\nahQRERH07dsXHR0dtm7dSvPmzWnfvj0rVqwgKCioQlBZ2c/YL1P55/WqVauye/duduzYgYeHB0FB\nQWhoaPDgwQM+++wzEhMTad26Nffv32ffvn306tWLP/74g5MnT9K8eXP09PTQ1tYGXv41UO/7nzVr\nFn369KFatWooFAp0dHSIi4vDyMiIYcOGYW5uTnZ2No6OjsyZM+e54P9ZP/zwA1FRUXTp0oWCggK5\nNllpaSm6urro6+uTn5/Po0eP8PDwkFd7HDlyhLZt29K2bVvs7e0ZNGgQISEhaGhoIEmSXKjQw8OD\ngICAv31tRALgX678m8XOzo4DBw5QWlpKvXr10NPTQ0NDA6VSydWrV3FycmLdunU4ODjIS9aPHz/O\nnTt3AHBxccHY2JgqVapQVlZWIdNZGePU0NBAT0+P+/fvExUVRe/eveXPqbOGp0+fJjc3l4KCAho2\nbAg8XWq0d+9eiouL8ff3x9TUFBsbG+DPyvuVqXyxkCdPnqClpYVSqeTGjRvEx8fj7e2Ni4sLVlZW\nZGdnk5OTw4QJE+jQoQPnzp1j1qxZFBYW0qJFC+rUqUONGjUqdXyCIAhq6vtV7dq18ff3JyUlhays\nLK5du8a6deuws7Ojdu3axMTEULt2bZydndm/fz9Hjx7F2NiYJUuWcOnSJebNmyfvvxQEQRD+DE7V\n99nt27dz/PhxVCoVoaGhREVFcfXqVR49esSKFSswMDBg3bp16Onp4erqyurVq8nPzycgIIAPP/zw\nuaDybQj+1deg/LP2o0ePkCSJoqIi3NzcsLGx4fLly3Tq1AlHR0emTZuGqakplpaWLF68GCsrK0JC\nQujQocNzK9T+6TVQL8N/9jgqlUouLK6jo0NmZibx8fF06NABeFqQb968eeTl5WFvb4+Pj49cs0H9\n9S+KL0pKSlAqlTRr1oyJEyeyfv16DA0NcXJyQlNTE6VSyZUrVygrK6O4uJjU1FS0tLSwtbXlyJEj\nPHjwgC5duqCnp4eVlRVGRkYVxqr+nv+0NbhIAPyLqd+cCoWCkpISdHR00NTUZO/evdSuXRtra2sK\nCwsZM2YMU6ZMoXPnzhgbGzN37lzu3bsn70Px8vIiIyMDb29vdHV1AV7YuuLvKJ+gUGvUqBELFizA\n2NhYbvVx+PBhRowYgbm5Oebm5sTHx3Pt2jWKi4vZvHkzvXr1YtGiRXTv3h0DA4MX3pAqi/qYc+bM\nYenSpSQnJ1NSUkL37t05ceIEWlpa1K9fH319fapUqcKdO3e4cOECISEhBAUF4erqSrdu3d6KfVyC\nILzd1PeZHTt2kJSUxJYtWzA1NWXUqFHcunWL3bt3Y2ZmhoGBAbGxsXTu3BlnZ2dycnKIj4+nSpUq\nzJ8/XyQqBUEQ/r9nW1Krn7O7detGenq6vLfd09OTCxcukJeXx+jRowkJCUGpVPL48WM0NTXx8vKi\nadOmGBgYAH8dVL7J1LFAbGwsEydO5Pjx4/zxxx/07NmTatWqsWHDBuzs7GjYsCHt27fn/fffl7ch\nGxoaUrduXVxdXTE2NkahUFT6NVDHK6dPnyYtLQ0tLS0MDQ3libzDhw/z5ZdfMmTIEBYvXoyOjg62\ntrakpKRw+fJlqlWrRllZGQ0aNEChUMgz9X81RqVSyZMnT0hNTSU2NpbHjx/z888/o1QqKSgoYPTo\n0UydOpXg4GAaNmxIUlISy5cv58qVK2zcuJGwsDAcHBwqdCor36K9sogEwL+Y+s25bNkydu/ejaGh\nIQEBAXJPyRo1arBs2TIKCwvZtGkTNjY2eHl5UadOHbnn5rx587C3t2fq1Kn07NnzuczcP6F+cysU\nCrKysti6dSuPHz/G1tYWQ0NDZs2axSeffMLKlSuZM2cO/fr1Y9CgQXh6emJpaUlycrLc5u+jjz7i\n+PHj8hLWyv5FKf+LWFpayrhx40hPT2f06NFkZGSwc+dOdHV1ad26NRs3bqROnTrY2NhgampKdnY2\nSUlJ1KlTBysrK2rXrv1WZHUFQXj7XLx4kSdPnqCpqYmWlhanTp1i48aN7N27l5EjR/Lw4UNSU1Op\nU6cOISEhaGlpMWXKFOrWrUtOTg6+vr4YGRnh6+tL27Zt6dChg7wUUxAE4V2mDv7UQeX58+eJjIxE\nkiRsbGyoWbMm+/btY/jw4SiVSszMzLh9+zZpaWkEBwfLz37q2gDq5Gv55+G3wbNttDdu3MiPP/7I\nkCFD0NfXJzY2Vm7tl5yczI0bN3B1dcXKykqunq9QKFAqldjZ2WFkZFRp1yAtLa1CR7KioiLGjRvH\n0qVLuXPnDlFRUejq6mJjY8Po0aNZvnw5H3zwAa1bt8bS0pLo6GjWrVvH1q1bGTt2LI8fP+bixYu0\nbdu2QjtytWcTFmlpafTp04d+/foxatQo1q1bh0qlwtPTk3Xr1pGRkcGWLVuws7PD2NgYSZJ4+PAh\nFhYWrFmzRu7+9dLjBEn41ygrK5NUKpX879TUVKlz585S9+7dpZEjR0rvv/++dOzYMenatWtSr169\npJ07d0r5+fny6588eSL/PS0tTf779u3bpREjRkh//PHHSxn3999/L7m7u0sff/yx5OrqKh06dEhS\nqVRSSEiIFBERIZWWlkqlpaXy60tKSiRJkqSioiIpNzdXkiRJun//vhQWFiZdvXr1pYxRkiQpMzNT\nSk5Olu7cuSP16dNHunjxovy5PXv2SJ6enlJxcbH0zTffSJMmTZJu3LghSZIk5eXlSb///vtLG5cg\nCML169el0NBQKTAwUOrWrZs0ZMgQqbi4WAoNDZX8/Pyk5ORkSZIk6caNG9KoUaOkiIgI+Z6+adMm\nqXfv3lKDBg2khw8fvs7TEARBeCOVfw6VJEk6dOiQ1LhxY2nw4MFS06ZNpbi4OEmSJKlFixbSkiVL\n5NclJiZKfn5+UkFBwSsd78vw7DWQJEl6/PixNHLkSGn79u3yxxITE6UBAwZIe/fula5cuSK9//77\nUmRkpLRlyxbpwYMHL218OTk5UnBwcIXn88TEROmDDz6Q46MNGzZI7dq1k1atWiX98ssvLzyf3377\nTf53TEyMNHTo0Bee+19p3bq1NH78ePnrGzZsKN25c6fCa9QxV15enjRr1ixp7Nix8v/J/8v3+rve\njlST8H9S7w9RKBRy65ADBw7g6enJ5s2bGTduHMbGxmzatInatWvj6+vLgQMHyMvLk7++/CzPjh07\n6NGjB127dmXu3Lny0vp/Ql03oLyTJ09y4cIFdu/ezZIlS2jevDlr1qzh/v37jB8/noULF5KdnS0v\nqYGnFatVKhVXrlyhX79+TJ06lTZt2lC9enVq1ar1j8b4nyxevJioqChKSkq4fv26/L0kSaJFixbU\nr1+fffv20bdvXxISEkhNTUWSJExNTV9aMUJBEN5tpaWlhIeH07VrV9zd3Tlw4ABDhgwhJyeHmJgY\nvv32WzQ0NMjLy5NbBvn4+HDt2jW5t3G3bt2YNWsWY8aMES1IBUEQylE/t5bvFf/dd9+RnJzMqlWr\nWLhwIcHBwezevZv79+/z3XffERERwbZt23j06BFHjx6lVatW6Onpvc7T+EfU++jV12D79u1ERkZS\nUFCAjo4Oly5dori4WH69q6sr9vb2nD17Fnt7e0JCQti+fTtnzpyRtxK/DGZmZrRt25ZPP/2U4OBg\nysrK+PXXX3F0dEShULB582bmzZuHm5sbbdq0oU2bNsDTffvqn7MkScTFxREfH8/q1auZNm0aLVq0\nqLDn/tn2fmPHjmXx4sXyv+fOncvWrVu5dOkS7dq1w9HRkYiICAD5OqljLlNTU5o2bcrDhw9Zs2YN\n8M/39/83xBaAfwn1vpmVK1cyffp0rK2tOXbsGH369EFfX5+ff/6Ze/fuUVJSQmlpKT169GDjxo2o\nVCqcnZ3lCvTS/1/e4uHhgaenJ3Xr1mXatGn/OICV/v9eKQ0NDX7//XcAdHV1WbduHUqlki5dunD4\n8GHS0tI4efIkRkZGtG/fnvT0dLZs2UL37t1RKpUV9sOYmppiZWXFo0eP6NevH/3793+uveH/Sl07\nQH0d4uLiSE5OpkGDBlhaWrJixQoGDhzI9u3bKS4upnHjxmhoaFBaWsrmzZvx9PTE29sbS0tLAgMD\n//F4BEEQ/pNBgwaRnJzMgQMHeO+994CnxYv27NmDnZ0dAQEBpKamkpaWho+PD3p6etjY2JCcnMz1\n69dxcnLCyMgIIyMjubCqIAiC8JT6ufPmzZuEh4dz9uxZSkpK2LFjB56enjg4OGBvb8/OnTspLi6m\nQ4cOXLt2jUWLFnHr1i3OnTvHmDFjMDU1fc1n8vepr0Fubi6ffPIJCQkJnDt3jqSkJFxcXNDW1ubw\n4cN06tQJeBrcqp+TW7ZsibOzMx07dqRNmzaVGtxKL6gjNn/+fC5evEjr1q0JCgoiMzOTZcuWER8f\nT3JyMuHh4fTo0YN58+Zhbm5O9erVK8QXmpqanD17lpSUFJKTkxk/frycKChfBFwqtw0iJyeHefPm\nMXDgQBQKBRYWFly9epV9+/bJyfkpU6Zw7Ngx/vjjD1xdXSuMuUaNGty5cwd7e/tX0rocRALgrVW+\nLYYkSeTl5dG7d285++ju7k6jRo3Q1NQkNDQUc3NzJk+ezLFjxzh16hT+/v5UrVqV0tJSPD095Tdi\n+V8AMzMzuefkP6WhoUFBQQGjRo1i0aJFJCYmcv36dYYOHYqXlxcREREsXryYsWPHYm1tzapVq/Dx\n8aF58+asWrWK9u3bP7cCQalUYmtri5eXl9y1oDLGqf4zPz+fsWPHsmvXLpo1a4aFhQWZmZmYmJjg\n4+NDeHg4devWpWbNmhw/fpykpCS56Imtre0ryeAJgvBu8/DwYPv27fTr10++55w4cYKDBw/SuXNn\natasiaurKwsWLMDa2hobGxv09PQoLi6moKCAJk2avNUzU4IgCJXt2X3dCQkJLF68mMLCQiIjIwkI\nCCArKwuVSkX9+vWxsLDg4cOHHD16lPr16xMcHMyKFSsYPHgwEyZMwMTE5K1q6fciy5YtY9GiRfL/\nJ4GBgezduxdtbW2cnZ05deoUqampNGrUiLy8PLZv306nTp2oV68eCoUCbW3tCi20/yl14K9QKLh/\n/z6nT5+mevXq+Pv7Y2tryy+//ELnzp1xcHDg0KFDVK1alY0bN2JjY0NSUhIxMTEMGTKkws9Z/TPy\n8vKiRYsW9OjRgzp16sifV7921apVLFq0iN9++w0TExOCgoJITEwkOTmZli1bAuDp6cn06dNxdHSk\ncePG2Nvbo6GhQWhoKPr6+vIxJUlCU1MTDw8P7Ozs/vF1+W+JBMBbqHy26/79++jp6aGvr8+FCxc4\nc+YMwcHBmJmZUaVKFY4cOYKmpiZTp05FT0+Pffv28eDBA3Jzcxk4cCAeHh4vpejIi250a9asIT8/\nn8jISOrWrSu3ysvJyWHDhg1ERUVRp04dLly4wP79+3ny5AkBAQEMHTr0H28/+G8VFBTIWcFatWrx\nxx9/cOzYMYqKitDV1eXy5cvUrVuX9957j9LSUg4ePMjGjRv55ZdfGDVqFE2aNHkl4xQEQQAwNjbm\n0qVLXL58GUdHRz799FPWr1/P8OHDCQoKoqysDCMjIx4+fEh0dDRNmzbF2NiYevXq0bRpUxH8C4Ig\n/H9SuUJ0paWl3L17F0NDQ4yMjEhNTeX8+fO0bdsWExMTCgsLOX36NHp6etjb29OgQQPWr1/Po0eP\nCAoKIj8/n7i4OHr06EFpaelbOymkvibGxsasWrWKmjVr0rRpU0xMTORn5MaNGxMQEMDy5cs5evQo\nP//8s9zasLx/2kHs3r17aGlpVaiKHxERwWeffcbly5fZtWsXbdu2xc3Njbi4OH7//XcCAwOxsLAg\nKiqKvLw84uPjiYiI4MMPP8TDw6NCQqL82J6d5Yensc3EiRM5fPgwAwYM4Ny5c+zfvx9JkujWrRuT\nJ0+mQ4cOVK1alfz8fGJjYzl37hzdunXD3t6epk2boqur+8Lv+aqTQyIB8JYoLi6Wbx4aGhrcvXuX\nzz//nL1795KUlEStWrUIDg4mKioKe3t7OeN26NAhduzYQa1atZg2bRoPHjxg2rRpdOzYUT52ZWYl\n1dm9FyUVpk2bRtOmTfHy8sLCwoLq1atz+/ZtHj9+zMqVK7G3t+fq1ats3LiRvn37EhYWRrVq1Sr0\nWK1MLzpmbm4ucXFxbNiwgfbt22NiYoIkSejo6FBSUsKBAwdQqVQEBQXh6elJu3btaNCgAV9++eUr\nzdwJgiCo+fn5MWjQINatW0ezZs1Yvnw5jo6OwJ8J4yZNmrB69Wp5i5IgCIJQkfpZODIykjFjxpCU\nlERKSgouLi44ODhw5coVioqKcHd3x9bWllOnTpGVlUWtWrUwMzPDxcWFwMBAdHR0CAgI4JtvvsHE\nxAR3d/fXfGb/t7+KBSRJorS0FDMzM3JyckhLS6N58+YYGBjg6urK3r17+eOPPwgODqZ37964uroy\ncOBAWrVqJX99ZcQY6enprF27lrp162JkZATAypUrOX78OKtXr5Zrm6Wnp9O6dWuMjIzkFcTOzs44\nOzujUqnIz89n6tSp8pa5vxrbi5I2mZmZREVF8dNPP8l1BHJycjh58iQ+Pj5IkkRERAQ1atRg+fLl\ntG/fnvbt21O3bt0K1/lN6PYgEgBvgf3797Np0ybs7e0xNDQkLy+PMWPGYGtry/Dhw7l58yabNm3C\nzc0NS0tLtm7dStOmTTEyMqJx48ZkZ2dz4MAB7OzsiIiIwMTEBPjzl70ys07q4126dInvv/+ezMxM\n8vLysLW15cqVK0iShK+vr/zmX7NmDWlpafj7+7Nq1SoOHjzIyJEj6dKlC/r6+i+lNYo68Fcfs7Cw\nEG1tbVQqFcbGxrRp04YjR46QlpbGgwcPMDY2xtvbGxMTE/bs2UNOTo58c9HU1KR69eqVNjZBEIT/\nlZaWFlZWVmRnZzNv3jy5Lon6Pqd+kOnatWulbZcSBEH4N3g28E1MTGT16tVMnz6dtm3bcv36dWbN\nmsXgwYO5c+cOqamp2NnZyc9+8fHxWFtbY2tri7m5OTo6OvKknZOTE46OjpiZmb2u0/uvlJ+4e/To\nkdymUKVSoVQqUSqVZGRk0Lp1a5YtW4aBgQEODg5oaWmhra1NVFQUzs7O1K5dm2rVqqGnpycXJ/+n\nMcaDBw/kWfPVq1eTl5fHqVOnsLW1ZevWrfj4+ODn58fZs2fJzMwkMTERNzc3mjVrxunTp1mzZg0n\nT54kLCwMd3d3AgICMDEx+cvx/fTTT6hUKrn22ebNm8nNzcXGxobCwkIWLlxIp06d5JoORkZGHDx4\nEAcHB0JDQ0lPT+fXX3+lTp06fPrpp8/VUHtTtoGIBMAbTB2o3rhxg4SEBLS0tHB2dubmzZvEx8fz\n448/YmJiwuXLl9m6dSu2trb07duX9evXA+Ds7IyWlha+vr506NCBwMDACsf9p2/Cv8rqbdu2jdGj\nR+Ph4cH9+/eZP38+9vb2FBYWcuvWLQwMDOSH0O3bt+Po6Mj777+Pn58fI0aMkAtgVFbW8Fnqm1x6\nejoffvghlpaW1K5dW77h3b17F19fX27fvk18fDyXL1/mvffew8/Pj4KCAvT19WnVqpVcOFEQBOF1\nc3BwYPbs2djZ2VG3bt0KSVP130VRUkEQBLh16xYrV67Ex8enQj0tDQ0NYmJiKC4uJiwsjMLCQnbs\n2EF6ejo9evSgRo0apKamkpGRgZ+fHzY2Nri4uDy3/VM9c2xra/vGB//wNCi9f/8+w4YNIy4ujtOn\nT9OgQQOqVKlCXl4eo0aNIiIigr59+6Kjo8O2bdto0qQJpqam2NnZ4eTkhKenZ4Vj/tM4o7CwkIkT\nJxIZGcn27dsxNzcnPT2drVu34urqSuvWralWrRo+Pj5MmzaNTZs2ERoaira2NkeOHKFjx474+Phw\n9epVatWqRdOmTeVkT1lZWYXCfwUFBeTn52NgYMCmTZvYsmUL3t7e9O7dm6tXr7J582bKysqoW7cu\n2dnZ5OTk0KRJEyRJolq1avzwww84OjrSoEED/Pz86NixIy1atABeXizzT4kEwBtM/dCmUqk4d+4c\nd+7cwcXFhdu3b3Pw4EFcXFz45JNPOHv2LBEREVhbW8tZqzlz5hAcHEzVqlVRKBQolUq5bUVlzaaX\nnzlXH7OkpIQFCxYwfPhwwsLC8Pf3R6FQcPjwYXx9fXnw4AHr16/HwsKCgwcPEhsbS2hoKBYWFhgb\nG8vnWxkJivKere4/YcIEdu7cScuWLXn//fdRKpXcunWLUaNGMXfuXPr374+XlxfZ2dnExMRw9+5d\nOnXqhK+vL23atBHBvyAIbxQNDQ08PT2ZOHEiffr0eSOWGAqCILxpUlNT6devH05OTvj6+gIVq8kn\nJCRgZGTEvn37mDJlCr6+vixYsIDo6GiCgoK4ffs2Fy5cwM3NDWNjYznAf1MDvRdRPxOrn7e3b9/O\n8ePHUalUhIaGEhUVxdWrV3n06BErVqzAwMCAdevWoaenh6urK6tWreLx48d4eXmhVCorfVvZsWPH\n+Oijj7C0tGT06NFoaGiQnJyMk5MTCoUCZ2dn6tWrR926dTlz5gx79+5lw4YNODs7s2vXLuLj4ykp\nKSEwMJCgoCB8fHyAv95vHxkZyY4dO2jTpg2tW7dm6dKl/Pbbb/Tu3ZvJkydjbW0tbzPQ1NQkISEB\nACcnJ44fP87Fixfp168fxsbGKJVKNDU15ZjrTX1PiOmAN9iTJ08YN26cvNzoyJEjuLi40LdvXx4/\nfkzPnj2ZMWMGnTt3BqBDhw6MHj1anp22sbGpcLzKfCCcOXMmR48eJTo6usJxi4qKyM3NpaCgQP7Y\nxx9/TKdOnSgoKOCrr77ip59+Ij4+nlu3bvHjjz/i7Oxc4diVWSilfJVQ+PMG7ejoyJYtW/joo4+A\npy08vvjiCxwcHFixYoX89SNHjqSgoEBelfCm7N0RBEF4VqNGjTAyMuL06dOiIKkgCEI5mZmZcnHn\n6tWrU7NmTTZv3kznzp3lZe7wdNZ+6tSpODg4sGPHDqysrDh69Chbtmyhd+/etG/fnu7duz9XnPpN\nDfTKe7ZOl1KppKSkhK+//hoLCws2b95M9erVmT17NuvWrePcuXOEh4fLy90fP36Mrq4u8+bNo2rV\nqnIv+8p2/PhxwsLCGDhwIPB0hZtao0aNmD9/PtbW1gQFBXHlyhUMDAwoLCwkOTmZkpISZsyYQYMG\nDYA/i/mp/66Wn5/P9u3b6d+/P40aNSIuLo7333+fYcOGMXHiRIYNG0ZYWBiSJNGmTRt27tzJrl27\n6N+/PwBz5sxh165dXLhwgU8//fS57XVveqzwZo/uHaJSqZ772LVr17h+/TpbtmxhwYIF9O/fn5SU\nFM6ePcvYsWMxNDTEycmJwsJCfvjhB3R0dHBycgLA39//pY43LCyMzMxMDh8+jIaGBiUlJfLnzMzM\nuH//PoWFhfLHbG1tSUxMBGD48OFMmjSJNWvW4OzsLGfJXgb1L+DGjRsZPnw4M2fOJC0tjQ8++AAX\nFxd+/fVXAExMTFi+fDmTJk0Cnhb/UP9MvvrqK3r16lXheIIgCG+izZs3i+BfEAShnNjYWFq2bElJ\nSYm8dXb69OnUrVtXrip/8uRJuU6Kt7c39vb2nD9/njNnzvDdd9/RvHlztLW1MTc3x8DA4KU+u1a2\n8u33FAoF58+f5/vvv5e3F0+fPp2HDx9ibGyMJEnUr1+f+vXrk5ubS5UqVVCpVJSVlaGrqws8Dcir\nV68uB9aVLTo6GlNTU0pLS7ly5QqHDx/miy++YNKkSZSUlGBgYMDx48cpKirCy8sLLS0twsLCGD9+\nPO3ataNz587Uq1evQuBfPvg/ceIEvXv3pqioCHha9yAlJYXs7Gx8fHxo0aIF9vb2nDx5Uv66MWPG\ncOzYMa5cuUJoaCjbt29n6NCh/Prrr/Tu3fulXIeXSWwBeM3Ub051YHn37l05q7hv3z5u3bpFz549\nAahXrx7nzp0jMzOT0NBQSkpK2LNnD6tWrSIvL4+ZM2dSs2bNVzJuQ0NDSktLWbhwodx/WqVSoaen\nR35+PklJSUiShJOTE0VFRWzZsoU+ffrI/TTVmVZ1gZHKVH6Pj4aGBnPnzmXHjh2EhYVx8eJFEhIS\nkCSJHj168M0339ChQwdMTU3R1taWb+hKpVL+mYigXxCEt4W4XwmCIDylDnrr1atHdHQ0T548QalU\noq2tTUFBAaGhoRgYGBAeHs6MGTPo2bMnHTt2xMPDg3v37rFv3z5iYmLo2rUrw4cPr3Dst2HGH57f\nVnv48GGGDh2Krq4ua9euxdramvbt27NlyxZUKpW8l7+oqIiVK1cSGhqKjo7OC8/3ZV2DkpIS5s6d\ny549e0hMTGTt2rXUrFmT7Oxsrly5gqGhIenp6Tx58oSCggJ69OhB06ZNGTduHPb29sB/3pJx8eJF\nEhMTGT16NLNmzaJ58+YEBASQnZ1NQUEBbm5uODk5ER4eLtcaMDEx4ffff2f37t20adOGatWqYWVl\nhVKplIvuvk00pJeVvhH+o+zsbCwsLOQl5WlpaUyYMAENDQ2sra3p1KkTZmZmdO7cmVOnTsl7OWlp\njQAAGb5JREFUzleuXMn69euZOHEizZs3p7S0lNu3b8uB9atcol5cXEzr1q0JDQ3l448/pri4GG1t\nbYqLi9myZQvLli3Dzc2NxMREmjVrxtSpU19Zz+kHDx5QUFBAzZo1GTx4MAMHDqRx48bcunWL/v37\nU7t2bZYtW8bgwYNRKBQsWLDglYxLEARBEARBeHnKTy6VlpbK+7aHDBnC7t27qVOnDoMGDaJatWpM\nmjSJCxcu4Ozs/NySdnXhZ/Vz9du0DfTZAHjp0qVkZ2ejo6NDcHAwLi4uTJ06ldzcXMLDw7l8+TID\nBgxg8uTJBAcH8/PPP1NYWMg333zzWs45Li6OkpISioqKaNGiBSYmJhQXF/Ptt9/i6uqKpqam3CFt\n0qRJ8s9O/fMuLy0tjQsXLlRogd6yZUvee+898vPzsbOzY+jQoSxdupTDhw8ze/ZsLC0tGTZsGCUl\nJSxZsgR4mpg4d+4cjRo1enUX4iURKwBescLCQr7++mumTp1K79690dXVJScnhwkTJtCsWTNGjBjB\no0ePmD17Nm3btuX27dskJCTQqlUrNDQ0yMnJ4ciRI+jr6+Pi4oK+vn6F4nmVPZv+nyiVSiwsLJg2\nbRofffSRnKRQKpXcu3cPNzc3GjVqRM+ePenbt69cZb+yvah36bRp0zh48CD+/v7MmTOHQYMGsWrV\nKsaPH0/Lli35/PPPefz4MW3btmX8+PE0bNjwuVYdgiAIgiAIwtuj/B73hIQE7ty5g46ODo6Ojpw5\nc4YDBw7QqVMn6tWrx5IlS7Czs8PHx0feD1/+OVpbW7tCsby3ZdYf/pydv3nzJuHh4Zw9e5aSkhJ2\n7NiBp6cnDg4O2Nvbs3PnToqLi+nQoQPXrl1j0aJF3Lp1i3PnzjFmzBh5//+rZmdnh729Pc7OzvLk\noVKpZO/evTg6OtKlSxeCg4Np165dhZ/Zs8mK0tJSQkJC2LVrF3Z2dtSuXRtNTU0ePXpEVlYWfn5+\n/PLLLzRq1AgXFxdOnjzJ9evXadasGc2aNeObb76hQYMG2NjYvJSCh6+LSAC8QosWLWLkyJHY2tqy\natUqjIyMgKft6GJjY5k9ezaGhoYcO3aMuLg43N3d6dWrFz///DNJSUkkJyezYcMGBgwYQP/+/alS\npUqF47+ODJ29vT2//vorKSkptGzZkpMnTzJ8+HAiIyP5+OOP8fb2lvcJvawKqepjPnz4EB0dHcrK\nyrh58yYKhYL33nuP5ORkwsPDMTAwYObMmXTt2pVvv/2Wixcv0rp1a2rUqEGjRo2eK+giCIIgCIIg\nvNkePHggB+saGhrk5uYyYsQIduzYwdWrV4mOjsbCwoK+ffsSHh6Om5sbnp6eZGRkcOzYMby9valS\npcpfTqK9LbP+5btywdMEyOLFiyksLCQyMpKAgACysrJQqVTUr18fCwsLHj58yNGjR6lfvz7BwcGs\nWLGCwYMHM2HCBExMTF44yfaqzmXhwoXs27cPJycn8vPz+eyzz8jKypIr7uvo6PxlfKEet0KhQKVS\nkZubS2ZmJg8fPsTFxYWcnBzy8/Px8vIiKyuLM2fO0LFjR548eUJ0dDTHjx/H1taWLl264O7u/tIm\nMV+Xt+Md/Za7e/cuPj4+HD58mJUrV8qBvlpWVhZmZmbs2bOH1q1bExcXJ1celSSJyMhIgoODkSSJ\niIgIuc/lm1KARN1Sr2/fvnz44Ye4u7uTmpqKm5ub/Br1L2FlKV80saysjB9//JGpU6dy4cIFFAoF\nhoaGJCUlATBw4ED09fUZPHgwDg4OXL9+nWvXrtGsWTMAunfvTvXq1SttbIIgCIIgCMLLVVhYyNix\nYxk0aBD9+vVj8+bNAJw6dQqlUkl8fDwrV64kICCAyZMnU1xczMCBA5k+fToAo0aN4sSJExw5cuSl\nFbR7FdRjV+9Hz8rKAsDFxQULCwsyMzPJycnB0NCQpk2bkpaWJj8jf/DBBzx8+JA9e/ZgampKnz59\nWL16NcBr3duuUCiwt7dn7969jB07lg8++ABra2u2bdtWoeL+s/HFvXv3mDhxIjExMcDTczAyMqJj\nx44EBQVx8uRJFixYQOPGjTl58iQ2Nja0bt2aa9eukZSUROfOnenevTv37t1DV1eXRo0aoaen91a/\nP15ErAB4BfT09Fi4cCERERFyWwqgQiZq7ty5xMbGMm7cOMaPH4+JiQnDhw/HxcUFV1dXHB0dCQwM\nlOsGwJuTkTQ3N+f+/fvk5uaycuVKQkJCgMq9cTyb3VMoFDx+/JisrCyqVq2Kqakp6enpLF68mLZt\n2+Lg4MDmzZtxdnamUaNG6OjosGLFCqKjo1m+fDk9evSge/fulTI2QRAEQRAE4dV5tld8WVkZ6enp\nODk5sXbtWry8vGjYsCFLly5lyZIldOjQAT8/PwICAvjpp59QqVQ0bdoUd3d3mjdv/lbP8KqfjyMj\nIxkzZgxJSUmkpKTg4uKCg4MDV65coaioCHd3d2xtbTl16hRZWVnUqlULMzMzXFxcCAwMREdHh4CA\nAL755htMTExwd3d/redkZ2dHt27d8PHx4YMPPiA4OBh4fqVDeTo6Ohw7doz9+/djbW1N7dq1ycjI\n4MCBA3z99dfY2toyefJkPD09OXHiBPr6+rRr146rV6+yc+dOunXrRsOGDenSpQvVqlWrMJ5/E5EA\neAUUCgUuLi5MnjyZ3r17U1JSwpQpUxg3bhxeXl7Y29ujq6tLVlYWvr6+GBsbyy05BgwYILfdgD8L\nkLxpb0RfX1+6d++OsbExKpUKDQ2NSq1HoD5f9ZKelStXMnLkSM6fP8+yZcto27YtnTp14syZMyQm\nJnLnzh1q1qyJqakpNjY2uLu707ZtW+rVq8cXX3yBr69vpY1NEARBEARBeHW2bNlCkyZNGDt2LGZm\nZjRu3Jj33nsPAwMDfv/9d1asWMG2bdv4/fff+eGHH/D29mbu3LkEBARgYGBAcnIy7dq1o1atWmhq\nar60baovy7NL8xMTE1m9ejXTp0+nbdu2XL9+nVmzZjF48GDu3LlDamoqdnZ28orX+Ph4rK2tsbW1\nxdzcHB0dHYqLi1EqlTg5OeHo6IiZmdnrOj2Zrq4uVatWRV9f/7+aANXQ0MDb25s7d+7w008/ERwc\njLu7O/PmzcPa2prGjRtjYWHBoUOHePz4MaWlpQQGBmJgYICdnR3169eXr+1/SjS87UQC4BWxtrZm\n7dq1HDt2jNmzZ2NsbMyKFSvkFQGurq4UFRVx5MgR1q9fL7evMzExqXCcN/Xm9Gxbv8oc56BBgzh3\n7hzNmzcHntZMWLJkCdOmTWPw4MHcvn2b9evXY29vT5cuXSgpKSEyMpKTJ0/i5eWFo6MjpaWl6Onp\nYWVl9VZneQVBEARBEN5148ePJyAgAHt7e65du0Zqairz588nKSkJe3t7EhMTadmyJT/++CPVq1cn\nOjqaCxcu0KVLF1xdXWnfvn2FZ9U39fm6vFu3brFy5Up8fHzk8aoTFzExMRQXFxMWFkZhYSE7duwg\nPT2dHj16UKNGDVJTU8nIyMDPzw8bGxtcXFxo0qRJheOrn+VtbW3fiOD/WeoaD/8XTU1NfHx8OH36\nNCkpKVStWhVLS0vS09Px9fXF0dGRKlWqsHfvXu7evUuXLl2oXbu23EJQ/T3+rcE/gOb//RKhsixb\ntozAwEAWL15MQEAA8HSZvHq2vF+/fqhUKvLy8rCwsABefWX/f6oyx6q+qXXr1o0xY8YwbNgwjI2N\niY6OxtTUlEaNGpGZmUlKSgr3799HW1sbAwMDOnfujFKpZNq0aSQlJdGpU6fnWoIIgiAIgiAIb6c+\nffrw3XffsXLlSgwNDbl48SJ+fn7cuHGDO3fuYG1tzf79+9HW1ubu3bvExcUxZcoU4M9n67fpGTs1\nNZXBgwfTrVs3+WOSJFFWVoZSqeTJkyfUqVOHSZMmERMTQ9euXZk1axbbtm2jb9++ODk5kZycTEZG\nBrVr18bBwUE+xtuQ/Pg7xo0bx9atW1m6dCm1atWiZs2aPHr0CD09PXx9fVm0aBEPHz58ZS3K3yQa\n0r+tqsEb7ssvv8TS0pLPPvvshb0q1dRVLf/N2acXUalUZGZmPteSr3///ujq6rJgwQL27t1LZGQk\ndnZ27Nu3j27dujFkyBA2bNhA586d5eTJtWvXqFev3us4DUEQBEEQBOEl+k+94t3c3LCwsCAjI4M7\nd+4wcODAN3JW+/+SmZlJrVq1SExMZM6cOfTs2RMNDQ15sksdJ0RHRzN16lQcHByYMWMGVlZWHD16\nlJkzZ7J161YePHiAnp7eO9fx6uHDh0RFRTF//nwcHR3lQpHlEx//5iTIXxHToq9YeHg4vr6+hISE\nYGdn95ev+2+XufzbDBgwgKSkJD7//HP8/f1xdHQE4OuvvyYkJIQLFy7g7OxMcXExv/32GwkJCWhq\napKZmcn69evp1KmTfCwR/AuCIAiCIPw7tWrV6rmPaWtrU1xcjJ6eHi1atKjwOfWe7rfl+To2NpZP\nP/2Uc+fOYWJiwuXLl5k+fTpLly6Vt7OePHmSadOmMXHiRLy9vTE3N+f8+fPk5OTw3XffERgYiLa2\nNubm5sCftcTeFUZGRgwaNIirV69y5MgRLl68iJOT01u3/aOyiRoAr5iWlha6urosXbpUVKF/AW9v\nb1avXk1ZWRmrVq2iqKgIQ0NDHB0dKSoqYsWKFQwZMoTi4mJ+//13dHV1ycjI4KuvviIoKIjWrVu/\nUzc2QRAEQRCEd9F/6hXfv39/jI2N5dld9VL5tyHYU4+5Xr16REdH8+TJE5RKJdra2hQUFBAaGoqB\ngQHh4eHMmDGDnj170rFjRzw8PLh37x779u2TtwEMHz68wrHfhvOvTOqCfp6enoSFhVVoIfguE1sA\nXgNJkkhJScHDw+N1D+WN9M0336Cnp4efnx/bt2+X+3J26dKFXr16MXv2bFq2bElUVBQXLlzgypUr\ndO7cmV69er3uoQuCIAiCIAivgCRJxMXFMWnSJBwdHUlLSyMoKIiJEye+7qH9LeVrEqi3CSckJDBk\nyBB2795NnTp1GDRoENWqVWPSpEnyqlhtbe0KxykoKEBfX1+eEHvXZv3/k7ep7sPLJBIAr9G7uOfk\nv1FUVIS3tzc7duzAzs6O2NhYNm/eTEFBAWfOnMHKyor9+/e/7mEKgiAIgiAIr9n9+/d58OABVapU\nkff5v22BXvmYICEhAaVSiZ2dHebm5gwePJiSkhKWL1/OxYsXGTZsGN9++61cULykpOSFHa7etmsg\nvDpiC8BrJIL/F9PS0sLY2JhVq1bRuXNn6tWrR0hICDY2NmRnZ3P+/HlsbGyoX7/+6x6qIAiCIAiC\n8Br9r73i3xQPHjxAW1tbrvuVm5vLiBEj2LFjB1evXiU6OhoLCwv69u1LeHg4bm5ueHp6kpGRwbFj\nx/D29qZKlSp/GeS/DddAeD3ECgDhjVRWVoavry+zZs0iICBAXr5UUFDA/fv3qVWr1useoiAIgiAI\ngiD8TwoLC5kyZQrXr19HR0eHjh070qNHD2JjY9m6dStLliwBYNGiRWzZsoWoqCjWrFlDfHw8e/bs\noaCgAH9/f8aPH0/Xrl3FhKLwPxOpIeGNpFAoWLhwIVOmTKG0tFTOYhoYGIjgXxAEQRAEQXjrHDt2\njODgYEpLS5k8eTJ+fn6cP3+eu3fvEh8fT7NmzQBYunQpS5cupUWLFujq6vL555+Tn5/P4sWLMTAw\nYOHChbRv314E/8LfItoACm+sRo0aYWRkxOnTp2nSpMnrHo4gCIIgCIIg/G3Hjx8nLCyMgQMHAuDg\n4CB/zt7eniVLlrBp0yZ0dHRYuXIlJiYmfPfdd0yePJkRI0Zw9OhRJEnC29sbEPXEhL9HJACEN9rm\nzZtFARNBEARBEAThrRcdHc3w4cMpLS0lPT2drKwsdu3ahZGRER4eHigUCpo3b85XX30FwNq1a8nJ\nyUFLS4s+ffrQp0+fCscTwb/wd4gaAIIgCIIgCIIgCC/ZsmXLWLhwIVZWVhgaGnLx4kX8/PwoKipC\nR0eHgoIC7t69S3BwMHfv3iUuLo4pU6bQrl07uaq/qO4v/FMiASAIgiAIgiAIgvA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      "text/plain": [
       "<matplotlib.figure.Figure at 0xfb80303978>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Export is successful!\n"
     ]
    }
   ],
   "source": [
    "md_text = '## Interaction between categorical variables'\n",
    "filename = ReportMagic.var_files='tmp/cat_interactions.csv'\n",
    "export_filename = 'cat_interactions_report2.ipynb'\n",
    "silentremove(filename) \n",
    "w1, w2, w3, w4 = None, None, None, None\n",
    "\n",
    "if conf_dict['Target'] in conf_dict['CategoricalColumns']:\n",
    "    cols_list = [conf_dict['Target']] + conf_dict['CategoricalColumns'] #Make target the default reference variable\n",
    "    cols_list = list(OrderedDict.fromkeys(cols_list)) #remove variables that might be duplicates with target\n",
    "else:\n",
    "    cols_list = conf_dict['CategoricalColumns']\n",
    "    \n",
    "w1 = widgets.Dropdown(\n",
    "    options=cols_list,\n",
    "    value=cols_list[0],\n",
    "    description='Categorical Var 1:'\n",
    ")\n",
    "w2 = widgets.Dropdown(\n",
    "    options=cols_list,\n",
    "    value=cols_list[1],\n",
    "    description='Categorical Var 2:'\n",
    ")\n",
    "w_export = widgets.Button(description='Export', value=\"Export\")\n",
    "handle_export_partial = partial(handle_export, w1=w1, w2=w2, w3=w3, export_filename=export_filename, md_text=md_text)       \n",
    "w1.observe(handle_change,'value')\n",
    "w2.observe(handle_change,'value')\n",
    "w_export.on_click(handle_export_partial)\n",
    "\n",
    "%reset_report\n",
    "%add_interaction_code_to_report i = interactive(InteractionAnalytics.categorical_relations, df=fixed(df), \\\n",
    "                                         filename=fixed(filename), col1=w1, col2=w2, Export=w_export)\n",
    "hbox = widgets.HBox(i.children)\n",
    "display(hbox)\n",
    "hbox.on_displayed(InteractionAnalytics.categorical_relations(df=df0, filename=filename, col1=w1.value, \\\n",
    "                                                             col2=w2.value, Export=w_export))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <a name=\"two numerical\"></a>Explore interactions between numerical variables (on sampled data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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6ClgS+xUQEREREUkT7wggIp3Yr4CIiIiISJq4EUBEOrFfARERERGRNLE0gIh0\nUvUrSN6fjDETxrAsgIiIiIhIIrgRQER62Uq/AiIiIiIiMh+WBhARERERERE1INwIICIiIiIiImpA\nuBFARERERERE1IBwI4CogVBkKBC7KhaKDIW1Q7EqXgfL4HUlIiIiqj+4EUDUACgyFAiPDcdbV95C\neGx4g/2wxutgGbyuRERERPULNwKIGoCkfUnI9coFHIFcr1wk70+2dkhWwetgGbyuRERERPULNwKI\nGoCIsAh45ngCZYBnjifGhI6xdkhWwetgGbyuRERERPULNwKIGoAA/wCkvpmKWPdYpL6ZigD/AGuH\nVGO1qUUP8A9A3Pg4DMsahrjxcfX6OtgSKb2+iIiIiBoCB2sHQER1I8A/oN5/QFPVoud65WJd7DqT\nP3QqMhSI2RSDXJ9cnN10Fr4+vvX+mtgKKby+iIiIiBoK3hFARPVGbWvRWctORERERMSNACKqR2pb\ni85adiIiIiIibgQQNTj1+fvea1uLzlp266rPrz0iIiIiKWGPAKIGpLY19ragtrXorGW3jpOnT2Ls\nirH1+rVHREREJBW8I4CoAWGNPFnLrgO7+NojIiIishHcCCBqQFgjT9YyatgovvaIiIiIbARLA4ga\nEFWNfPL+ZIyZMIa3ZlOd6da1G197RERERDbCpu8ISEtLw6hRo9C7d2+MGzcOf/31FwDg2LFjiIiI\nQFBQECZMmIC8vDwrR0pkG3Q1Y9N+LMA/AG/MekP8IGbtBm7Wnp/qjvZrj4iIiIisw2Y3AiorKxET\nE4P58+fjjz/+QEREBP7973+jrKwM0dHRePHFF3H48GEMGDAAs2fPtna4RFanagT41pW3EB4bDkWG\nQudjhs6xdsxERERERGRZNrsRcP36dVy/fh3l5eUQBAF2dnZo0qQJfvvtNzg7OyM8PBwODg6YMWMG\n8vLycO7cOWuHTGRVuhoBGmoOaO3mgdaen4iIiIioIbLZjYBWrVrhySefxLRp0xAYGIjly5fj/fff\nR1ZWFnx8fMTj7Ozs4OHhgezsbCtGS2R9uhoBGmoOaO3mgdaen4iIiIioIbLZjYDKyko0b94cn332\nGY4ePYrZs2fj5Zdfxu3bt+Hk5KRxrJOTE0pLS60UKZF5qNfK66ubr66eXtUIMNY9VvyOdl2PGTrH\nmLmMXYch1c1/8vRJ9g4gqgX23yAiIiJ9ZIIgCNYOQpevv/4aKSkpSEhIEB8bPnw4Ro0ahTNnzmDl\nypXi42NTszFrAAAgAElEQVTHjsVLL72EYcOGGTX27du3kZGRAblcDmdnZ7PHTnWrtLQUOTk58PLy\nqrJJVF+cPH0SEf+JwAWfC2j7V1vImshQ0KUAHtke2DlnJ7p17aZxjPrjlo7HlLnMEWNpaSkOHDyA\nV7a/goudLlp8rWRZUnh/1keW/H3BnEoL8yktzKe0MJ/SU1JSgvz8fPj7+6Np06ZWjcVmvz7w8uXL\nKC8v13isUaNGCAgIwLfffis+VllZidzcXHh7e5s8R35+PvLz82sdK9mGnJwca4dQY59s/QQXfC4A\njsBlXAa6AHAE8rzz8NmWzzBl3BSNY9Qft3Q8psxlrhgPHj6Ii50u1slaqW7U5/dnfVQXvy+YU2lh\nPqWF+ZQW5pMswWY3Avr374+VK1di//79GDZsGHbu3ImSkhL07t0bRUVFSElJQXh4OBITE+Hp6anR\nN8BYvCNAGqSwWzr1manYu3wv8rzz0BZtITvzzx0Bz895Hv5d/TWOUX/c0vGYMpc5YiwtLcUjfR7B\nnh17xL9mWnKtZFlSeH/WR5b8fcGcSgvzKS3Mp7Qwn9KjuiPAFtjsRoCfnx+WL1+OlStXYv78+fD1\n9cW6devQvHlzrF27FgsXLsTixYvh7++vUSZgisaNG1v9lgwyHycnp3qbT6cmThjjo2yUF/WfKABA\n8v5kjJkwRqybDw4KxtdvfV3lcXNTZCjwzU/fYHXkapzIOmFwLkWGAkn7khARFmG2GDt5d0LS3CR8\n+/O3Fl2rlKjnwRavV31+f9ZHdfH7gjmVFuZTWphPaWE+pcOW+trZ7EYAADz66KN49NFHqzzerVs3\nbN++3QoREZmfIkOB8Nhw5HrlwjPHE1GIEhv9adP3uEViSfPU2WBQ3/HrYtdpNCmsrW5duyE4KLjW\n4zQE+vJADZulf18QERFR/WWz3xpA1FAk7UtCrlcu4AjkeuUieX9yvYnFlmJvyJgHIiIiIjIFNwKI\nrCwiLAKeOZ5AGeCZ44kxoWPqTSy2FHtDxjwQERERkSlsujSAqCEI8A9A6pupFq/9t0QsthR7Q8Y8\nEBEREZEpuBFAZANqW8tb00ZxKXtTELchDjETYzD68dE1isWY4xUZCiRuTERhUSHauLRBVGRUjddr\n603xrIX14ERERERkLJYGENVzqkZxb115C+Gx4VBkKIw6L2VvCsbGjcX3nb7H2LixSNmbYrH4Qt8O\nxWphNTZnbsbqotV49O1HjY5Te6yarJWIiIiIiP7BjQCieq6mjeLiNsShIrgCcAQqgisQvzHeYvEV\ndC4AHAH0BZAP5HfOr1FDOzbFIyIiIiKqPW4EENVzNW0UFzMxBvbp9kAZYJ9uj+jIaIvFJz8rB8oA\npAGQA/Kz8ho1tGNTPCIiIiKi2uNGAFEdUWQoELsqVuft7NU9Z4iqUVyseyxS30wFAINjKTIUOJ55\nHB898RFCs0Px0RMf4Xjm8Srn1CYu1bkA8N073yHGLgbjO49HTJsYfPfOdybXs6t6A8SNjxPXypp4\nIiIiIiLTsVkgUR1Q1bbneuViXew6jQ+x1T1nLFWjOGPGUj/GM8cTcZFxiNkUU+Wc2sSl69xVS1aZ\ntCa9Mad5chOAiIiIiKgWeEcAUR2orrbdnHXvxoylfUz8hnid59QmLnPX8rM3ABERERGR+XAjgKgO\nVFfbbs66d2PG0j4memK0znNqE5e5a/nZG4CIiIiIyHzsFy1atMjaQdS18vJyFBYWwtnZGU2bNrV2\nOFRLqny6urqiUaNG1g5HJzdXN4R1C0O7K+2wZPISjdva3Vzd4NPEB4U/FOLtCW9j0EODqpyvyFBg\n7aa1cGnpAjdXN73zXC28ihu5N9Dfrj9eeuwl/Hj4R7i0dMHVwqvi+QH+AQjrFgaHEw7o0rILwoaE\nIXJwZJXY1GN+bvBz4lj65lfFWFxUjG2p2+AquOLhpg/jo+iPTLqNX5XPq9eu4tOtn2rEXPJTCcqv\nlCOgUwD8uvgZPaYqvthVsUg9kIqO7TpWex1tgfr13P71doO5t1X14f1JpmFOpYX5lBbmU1qYT+kp\nLS1FSUmJTeSUPQKI6oiqjl+bIkOhrNHvlIszm87A18dX4zhja/XVj3M/5o6tp7eioHMB1ry9BsId\nAQXdC8TzASA5Kxm5XrnYFbsLqW+m4o1Zb+iMGYDxfQda5MIu1Q6VwZXAecD9gjuiIqNMvlbnss/h\n1R2v4oLPBXHOzKxMbMncgorgCoyNG4sd2IHRj482ajxFhgKhb4cqv8bwKLD9+HbsX7bfZvsMqF9P\n+1R7VARX1Lh/BBERERGRNpYGEFmZofp3Y+vj1Y8rEAqUH3odgfzO+SgQCjTON6Xm3qS+A/lQbgI4\nAuipjKMm9fwHDx/EBZ8LGnPGbYhDRXAF4AhUBFcgfmO80eMl7UsSr0dt4qor6tdTtWb2RiAiIiIi\nc+FGAJGVGap/N7Y+Xv04d5k75GflQBkgPyuHu8xd43xTau5N6jsgB+zS7YAyAEeVcdSknv+RPo/A\nI9tDY86YiTGwT7cHygD7dHtER0YbPV5EWIR4PWoTV11Rv56qNbM3AhERERGZC3sEsEdAvWeu+in1\nOnz1mnpz1WXrq/Ovrn+A9vP6avUVGQokbkxEm8o2GNpsKFa9sgqTHpmEdlfa4b2p7+GhTg9p9CAw\nNKe++XUdq8hQIGlfEiYPmYxAh0DMGj4Lbhfd0Ne9L+JeiTP5VvZjJ45h576dmBY2DT2FnuKcfl38\n0KN1DxT+VIgPXvzA6LIA1RqGBw6HwwkHo+IytieDJWhfz9GBo1H2ZxkWRS7S2T/C1rG+UXqYU2lh\nPqWF+ZQW5lN6bKlHgEwQBMGqEVjB7du3kZGRAS8vL7i4uFg7HKolVT79/f1rvLGjXl8vPysXa+o9\nc8zznfXq49d0TH1jaNe/u9u7a9S/m2NuS65Le7zhi4fjgs8FeGR74Ou3vq7zmnhLXi9T544bH6fs\nH2GFWMzFHO9Psi3MqbQwn9LCfEoL8yk9RUVFyMnJsYmcsjSACJp18Lpq6s05fk3H1DeGofp3c8xt\naky1GU/VGyDPO88qNfGWvF6mzr36y9VWi4WIiIiIpIsbAUTQrIPXVVNvzvFrOqa+MQzVv5tjblNj\nqs14qt4AHtkeVqmJt+T1MnXuWRNmWS0WIiIiIpIulgawNKDeM9dtU4oMBZL3J4sftlT/Nudt9LUd\nU98Yqpp2QRAQFRmls47f3Oux1Njpf6bjsy2f4fmnn0dwULAZIjSdJa+XqXNbMxZz4G2N0sOcSgvz\nKS3Mp7Qwn9JjS6UB3AjgRkC9J6VfkqpGcRFhETo/9Kme7+7bHcczj+s8TtU4UBAETJ8wvcqGQXXj\nm3pcbc5RX8v+X/dDJpMhKjIK3h299eazJnHZivocuym01yml9ycpMafSwnxKC/MpLcyn9NjSRoCD\nVWcnIpF6o7h1seuqNIZTf94+1R4VPhVYl6Z5nHbjwO3Ht4uNAw2Nb2wcNYm9uuNl22UQmgtAL2D7\n29uxa/4uyCAzS1y2oj7Hbgpd6/Tu6G3tsIiIiIhIC3sEENkIQ03q1J+vCK4A8qseV13jQGOb4NWk\nWZ6p56gfLzgrNwFUjRr3fL/HbHHZivocuykayjqJiIiI6jtuBBDZCENN6tSft0+3B+RVj6uucaCx\nTfBq0izP1HPUj5eVyIAjEBs1jhg6wmxx2Yr6HLspGso6iYiIiOo7+0WLFi2ydhB1rby8HIWFhXB2\ndrZ6bQbVniqfrq6uaNSokbXDqZaqqZ9LSxe4ubppPJ60LwmTh0xGYHkglkxeAgAax7q5uiGsWxja\nXWmHWcNnIdCh6nEB/gEYHjgcDicc0Ne9L+JeiROf9+/kj8jBkWh3pR2eG/wcfjz8ozh2yt4UzFw4\nE85Ozhj00CBxniWTl4hlBbriVlGPTXVOdet2c3WDTxMfFP5QiNmjZ8O3mS/62/XHqphV6NKpi5jP\nM5lnNNZW3Ry1zYG56Bpf3/WxdCzGxGZOutZZn96fZBzmVFqYT2lhPqWF+ZSe0tJSlJSU2EZOhQbo\n1q1bQnp6ulBYWGjtUMgMVPm8deuWtUOp1omTJwTP8Z4CFkDwHO8pnDh5Qu/j+o41dszqntd+LC4h\nTrAPsxewAIJ9mL2QvCfZpDlqsu7qxlTl8/CRw7Wa19hYzMmU8S0di7XnU6kv708yHnMqLcyntDCf\n0sJ8Sk9hYaHN5JSlAUR1RF/9tK7HzVXPb8zYK/+7Utlz4H7vgfiN8SbNUZN1GzPmrgO7zF5vbuka\ndlPGr+t6etbvExEREZEKNwKI6oi++mldj5urnt+YsWdPmq3sOXC/90B0ZLRJc9Rk3caMOWrYKLPX\nm1u6ht2U8eu6np71+0RERESkwh4B7BFQ71mqfspQPbUiQ4ElK5fgm4PfwFPuabDmWlUXn703Gz3b\n9sSgvoOq1P6rav7V+wVo1/Orz5/wZQJcBVc80uwRfDjzQwDKfgDFRcVY8981SP8rHTPDZ2r0HdDu\nRTBi+Ai0ut0Kp1NOY9EzizDp2UlV4jZU/x+7KhapB1LRsV1HuLm6idfu2LFj+OjzjzDl4SkIcQoR\nz9e1ZtW1buXcCoWFhYAMuJt/F/1k/fBR9Ee1/ro9XX0YajJmda8L1bpKfizB9dzrOJ15Gn6d/Koc\npx6L6wVX+LXyQ/CDwRbtE2Aoj5aien9evXYVn279tM76IdSEeq8Mvy5+Fj+vvmLNqrQwn9LCfEoL\n8yk97BFgZewRIC2WqJ8ypvbefaS7gHAIWABBPk5usObamHO0503ek6y3r4D2WOKx0yHYhdkJWAAB\n4RDcR7pXW5dfm9rxEydPCO7j3DXmEuN4BgJCobf3gL41Hz5yWNiybYvQ4ZkOZqtnN1d9vDHjJO9J\n/uf6h0JwGeqicZz6GO4j3cXrV5d1+3Xp1q1bZs+nJSTvSa62V4a5z6vPWLMqLcyntDCf0sJ8Sg97\nBBDZOGNq7wuEAqAnAEcgv3O+wZprY87Rnnf1l6v19hXQHit+Q7zy2HygMrgScATQEygQCqqty69N\n7XjSviQUdC7QmEuM+RyAvtDbe0Dfmvd8vwcHDx/EBZ8LZqtnN1d9vDHjxG2I++f69wWK/i7SOE59\njAKhQLx+Uq7bN3c+LSFuQ1y1vTLMfR4RERGRNXEjgEgHY2rv3WXuwFEAZYD8rNxgzbUx52jPO2vC\nLL19BbTHip4YrTxWDtil2wFlAI4C7jL3auvya1M7HhEWAflZucZcYsydAKRBb+8BfWseMXQEHunz\nCDyyPcxWz26u+nhjxomZGPPP9U8DXFq4aBynPoa7zF28flKu2zd3Pi0hZmJMtb0yzH0eERERkTXJ\nBEEQrB1EXbt9+zYyMjLg5eUFFxcXa4dDtaTKp7+/v1l7PigyFEjen4wxoWN01lMrMhRI3JgImUyG\naeOnGVVzbcw52vPqi0PXWKpjA30C8f1v30MQBERFRml8b72+sapbq6E1rd20VmMu1XgtHFtg14+7\nEB0ZjdGPj652DNX83h29kZGRAcFOwLc/f1ujmAzNUZvxjBknZW8K3k98Hz4dfLBg1gKdfRVUYwAw\nS1y2SvX+NHc+LSFlbwriN8YbfL2a67z6ylK/c8k6mE9pYT6lhfmUnqKiIuTk5NhETm16I2D37t1Y\nuHAhZDIZAEAQBJSWluKDDz6Ah4cH3n77beTk5CAgIABLly6Fh4eHUeNyI0BazP1LUtXIrbtvdxzP\nPI6IsAizf3BRzVHbsY0dR31NBw4dgCAICH0oFMczj6Nlk5ZIPpiMmIkxGP346Cpj6pvDmLlVmxWF\nRYVo49JGY1NCn/Q/0/HJV59g6jNTERwUbPJaAeUHs7gNceKaDDFXPuqCoVjNsRZzXg/+R4z0MKfS\nwnxKC/MpLcyn9NjSRkC9ahb43//+Vxg/frxw8+ZNYeDAgcLevXuF8vJyIT4+XnjiiSeMHofNAqXF\nnI1UxEZu0yE2ADN3c7O6bFyncdx0CHah95vYPaz271CI641LiDO6WaGhuTUaCd6fw1BTxRMnT4hN\n5Tye9ahRQ0NTm7eZKx91wZgmlrVdi7mvBxsdSQ9zKi3Mp7Qwn9LCfEoPmwXWwIULF7B69WosW7YM\nf/zxB5ydnREeHg4HBwfMmDEDeXl5OHfunLXDpHpObOSWD7EBmLmbm9Vl4zqN4/KByr73m9g1V/t3\nX4jrXfnflRpjig0Ia9BgUKOR4P05DDVVTNqXJDaVy/POq1FDQ1Obt5krH3XBmCaWtV1LfboeRERE\nRFQz9WYj4KOPPsKzzz6LDh06ICsrCz4+PuJzdnZ28PDwQHZ2thUjJCkQG7nJITYAM3dzs7psXKdx\nnBywS7vfxO6m2r/TIK539qTZGmOKDQhr0GBQo5Hg/TkMNVWMCIsQm8p5ZHvUqKGhqc3bzJWPumBM\nE8varqU+XQ8iIiIiqhn7RYsWLbJ2EIZcunQJS5cuxYcffggnJyccOnQIt27dQmhoqHjM7t270bVr\nV3Tt2tXgeOXl5SgsLISzs7P1azOo1lT5dHV1RaNGjWo1lpurG8K6hcHhnAO8G3tjaLOh+HDmhwbr\n79duWguXli5wc3Uzeo52V9phyeQlVeruVWNdLbyK2FWxSD2Qio7tOopjp+xNwcyFM9HZszNmjZ6l\ncxyd891oh1mPzYLdcTs0LW2KuWPmIsQpBGO6j0FxejEGeQ/CpHGT0K9DPxT+UIjnH34euVdyMXnI\nZASWB4pzqOrHtR9Xxb9k5RJ8c/AbBD8YjIc6PoScvTl4sNWDeKzDY1gVs0ocQ9c1c3N1wyCfQWh0\nvBHen/Y+enbvqXc+7Wul+veghwahR+seynlbP4jiG8Xo2K6jxjHqc14tvIobuTfQ366/wVwbk29T\nXw+mHF/da6e65805h6njab8/Tb0+ZHvM+TuXrI/5lBbmU1qYT+kpLS1FSUmJTeTUppsFqqxbtw4K\nhQIrV64EAHz++ec4evSo+DMAjB07Fi+99BKGDRtmcDxV4w25XA5nZ2eLxU11o7S0FDk5OfDy8oKT\nk1Otxzt5+iQi/hOBCz4X4JHtgZ1zdqJb1261PtaUedv+1RYVDhUo7FYIHAXa2rXFnsV7cC77HMYn\njkdlcCXs0u2wKWoTRg4fWau1ARAfcz/jDuGOgMsdLsMuyw6VwZUa66puvSdPn8SIhSNwufIy0BNw\nOeKCRs0boaBLgdFjAJr5zM7N1nms9rWSNZFpzAMAI98biYIuBcBRoHVpazi6OJocizHXT/14c49n\nDuaew9TxjMkn1S/m/p1L1sV8SgvzKS3Mp/SUlJQgPz/fJpoFOlh1diP99NNPePbZZ8Wfvb29kZSU\nJP5cWVmJ3NxceHt7mzRufn4+8vPzzRYnWVdOTo5Zxvlk6ycadeqfbfkMU8ZNqfWxpsx7GZeBblDW\n1/cELv91GZ9t+QyH/zqMymBlbX9lcCU+/ORD+Hb0rdXaKoVK8bGCLgXAX1D2E7g/j/q6qlvvJ1s/\nUcbdUxl3kUMR0AUmjaEuJydH77FVrpXWPJVCpXIt96/ftX3XgAE1j6W666d+vLnHMwdzz1HT8arL\nJ9VP5vqdS7aB+ZQW5lNamE+yBJu/I0AQBPTq1Qt79uxB+/btAQB3797FsGHDMGfOHISHhyMxMREH\nDx7Ejh07jBqTdwRIiyXuCHhi+RPI884z6o4AY481ZV5L3hGgHS8A8TFj7gjQt15T7gio7ppp/wVZ\n17Ha16o2dwSYkj9Dx5t7PHMw9xymjmdMPql+4V+opIX5lBbmU1qYT+mxpTsCbH4j4Nq1awgJCcGx\nY8fg6OgoPn7y5EksXLgQ2dnZ8Pf3x9KlS+Hh4WHUmKqNAC8vL7i4uFgqdKoj5viOVe3vTU/Zm4LV\nX67GrAmz4Ovja/B725P3J2NM6Bi99eXa4+v7nnb1sTKzMvF+wvvw8fDBglkLxONS9qYgfmM8Rg0Z\nhd+O/YZzeecQOSIS1+9cR3ff7tj/637IZDIMGzAMxzOPVzuHeg256jEASN6fjECfQJzIOlFlXdrX\nJuHLBMhkMkRFRiEzKxNLE5aik2cnLIheII6lPYa+a6bIUCD+i3hcK7qGOS/NQXBQsHhsoE+gxnp0\nxawaT5GhQMKXCSguKUbrVq0RFRllcizVvVZ0XT9VPvXNY8p45mbuOUwZT/v9WRfrrS19709rj2mJ\nuGqC32stLcyntDCf0sJ8Sk9RURFycnJsIqc2vxFgCdwIkJba/pJUZCgQHhuOXK9ceOZ4Im58HGI2\nxSDXKxfux92BJkBB5wJ45ngi9c1Uk/8DvLrx9Y2pfY72MYoMBYa8OgRFsiLlrfi/AWgKyEpkEFoI\nQE/ALt0OlT6V8Py7ZnEbWov8rBxlRWUoaqKMwTXDFfb37FHQvWbXSpGhQOjbocqvHLx/F8SB/xwQ\nP9hXdz30xVjTnJmiruerb+rbf8RYIp/mGNOWXmf1LadUPeZTWphPaWE+pceWNgLqzdcHElmK9vem\nr/5ytfhzgVCg/GBqxu9lVx9f35jGfF98kX2RWI+P/gDOAYKzID5WGVwJ5Jv3u+DV48rvnI+iv/+J\n4ar/VRQINb9WSfuSxGuNnsraf9UYpny3vSnHmkNdz0eWZYl8mmNMvs6IiIjInLgRQA2e9vemz5ow\nS/zZXeYO+Vm5Wb+XXX18fWMa833xbSraAEcBlEF5R0An5R0Bqsfs0u0AuXm/C149LvlZOVxauIjz\nuWa4wl3mXuNrFREWIV5rHAXaoq04hinfbW/KseZQ1/ORZVkin+YYk68zIiIiMieWBrA0oN4zV48A\n7RpzffXn5h6/ulvcqztGkaHAe/HvISs3C+NHjMffZX8j0CcQBw4dgEwmw9D+Q3XW+NeW9rVJ3JgI\nmUyGaeOnAajdtVJkKPDxfz9GcVExXp3xKoKDgnXOa2jsuq5Drw9179ZSH29rtEQ+zTGmrbzO6mNO\nST/mU1qYT2lhPqXHlkoD6sXXBxJZWoB/gMZ/WOv62VTajb3Um/3FbYhDzMSYasfVjkEXl1YuaO3c\nGkMHD9U4Nm5DHIb2H4oxoWM0mvkZ08wQUN6G3N23O45nHhf/V/051b8TvkxAVk4Wiv4uQtNGTXHw\n8EG4tHBBQUEBpk+YXqWvgfYc6k3PVNdl2lPT4NvRF/5d/auc2923O5L2/fPVodqNClXXdfTjo6s0\n8tO3DnN8oNKXK2s1d7OVpnL1lTHvPWuMaYm4iIiIqGHiHQG8I6Des8XdUn2NvVL2pmBs3FhUBFfA\nPt0eO2J2YPTjo2s0vnpjPXd7d+xfth+ZWZni+HZpdnig/AFcb3Yd6Km8lf+7d76rtjGh/Kwcwh0B\nBd0LYJ9uj4rWFbC/Zo+K4AqN58RGgZVFQFP807CwC4BcADcB95bKmLSb/elqwKgRd7od/hP+H8x4\ncYbYZV51rn26PSp8KiAv0mxU2Op4K5QUl0AYLGhcV/HcFrmwz6q6Dks2XbNWczdbaioH2Ob7k2qH\nOZUW5lNamE9pYT6lx5buCGCPACIL0NfYK25DHCqCKwBHoCK4AvEb42s8vnpjvQKhAMn7kzXGr+xb\nieu3rovN/PI75xtsTJjfOV9s+FcRXAGcgzie+nNio8Dm0GxYmH//5xb/xKQ9h64GjBpxB1di676t\nOuOrCK4A8qs2KizuXqxslKh1XcVz83Wvw5JN16zV3I1N5YiIiIjIEG4EEFmAvsZeMRNjYJ9uD5QB\n9un2iI6MrvH46o313GXuGBM6RmN8uzQ7ODdzFpv5yc/KDTYmlJ+Viw3/7NPtgU4Qx1N/TmwUeBOa\nDQvl93/++5+YtOfQ1YBRI+50OzwV9pTO+OzT7QF51UaFrY63UjZK1Lqu4rly3euwZNM1azV3Y1M5\nIiIiIjLEftGiRYusHURdKy8vR2FhIZydna1+SwbVniqfrq6uaNSoUa3HS9mbgqdeegprPluD9q7t\n4dfFT3xOkaHA2k1r4dLSBW6ublV+VrlaeBU5R3PQ/GxzvPv8uxj00CAAQEVFBYrPFqPZ2WZYPXO1\nzrIAfWOqnluycgniPonD+aPn4XbRDaMCR+H1Z1/Hj4d/REhwCLo27YrjW45joNdALIlaAtd7ruhv\n1x+rYlYBANZuWoviomKs+e8apB5IhXNzZzjedEQ/WT+silmFSY9OQrsr7TBr+CwENg/ErOGz4HbR\nDf6t/TGmzxgU/1SMTs06oVu7bnjQ7UF4whMuuS74V5d/4WraVfja+8KzuSeWTV8mrtvN1Q0+TXxQ\n+EMhFk9ZjNlPzEa7K+3wiM8j+OjzjyB3kaPl3ZawO26HwV6D0d6tPQ78fgBurdwQ4B+AsG5hYkz2\nmfa4V3gPT4Y8iXuX7mFIkyH49I1PERYQhsKfCvHBix+I1/VQ2iEc/eUohrQcgsUTFyOwPBDvTX0P\nkx6dBIcTDujSsguCHwyucp2183C18KrenOg7Rz3uJZOX1FlZQNK+JEweMhmB5YF1Nm918SRuSkQj\nNEKXzl1q/f6s7r1Bdcfcv3PJuphPaWE+pYX5lJ7S0lKUlJTYRk6FBujWrVtCenq6UFhYaO1QyAxU\n+bx161atx0rekyzYPWonYAEEhEJAMITkPcmCIAjCiZMnBM/xngIWQPAc7ykk70nW+PnEyRPice4j\n3QWEQ8ACCPJxcuHEyRNVzlcdr666Y8Rxh0HA9PvxLYDQ7LFmysfvz+Uy1KXK3BpjT4dgF3p/jcMh\nyAbKjI5JNlAmYDjEc91HumuubToE+zB7nddEe13Je5LFYxEKASPunzsdgl2Ync6YqpwzXX/c6sfa\nh9mLeTR0nbWfdx/pLriPc6/2GhkzpqVZe/7q4nF/0l04fOSw2cazhfU1ZOb8nUvWx3xKC/MpLcyn\n9BQWFtpMTlkaQKQmbkMcKvtUKmve+yofq1Jvfr/2evWXq3XWYiftS1LWoGvV5htTu13dMeK4/aCs\nxe+rHP9W0K2qtfs6+gKo18tX9r2/xl4Qa+uNiUlwFoBeEM9V9QHQVYuvfU2016XeFwB9AWT+0wOg\nMrIxprsAACAASURBVLhSZ0xVzsnXH3d1/RgM5cJQTwNdrF2bb+35q4unoEsB9ny/x2zj2cL6iIiI\niOozbgQQqYmZGAO7w3bKmvc05WNV6s3v117PmjBLZy12RFiEsgZdqzbfmNrt6o4Rx/0dylr8NOX4\nzf5sVrV2X0dfAPV6ebu0+2s8ArG23piYZCUy4AjEc1V9AHTV4mtfE+11qfcFQBoA3396AKhyoB1T\nlXPk+uOurh+DoVwY6mmgi7Vr8609f3XxuJ9xx4ihI8w2ni2sj4iIiKg+Y48A9gio92pSP6Vd/71k\n5RJ8c/AbhA0Jw6NdH8WRDUfgUOyApVFLMenZSQD+qXO/+uNVLIpchNGPj9ZZA+7m6obHej6GktMl\naHa2Gd5/4X0MemgQ3FzdENYtDPbH7eHXyk9nbbrqGO0xU/amYFHcIrwY9iJ8W/jiZvpNXDt7Dd6F\n3vBq7oWZI2YixCkEUx6ZgrvX7gKXgdDmoVj3+jrx6/vE2nGHQIzuPhrF/yvG4I6DsWTKEgSWB6J1\naWu88t4r2PvtXvQL6ifGph5TzMgYuFa4onNJZzzs8zBixsTgx8M/Iv9iPrKPZ8Pnpg+a326Orte7\nAteAtD/S8Pufv8O5uTNu5N1A0zNNMerBUVi/fT369eiHAe0H4HTKaUQNjUKQaxB8mvpg4AMD8XTv\npzGg8QBMeWQKfjz8o1gTXlFRgeLMYjQ70wwTBkxAk7wmeP7h53H09NEqdeN+XfzQo3UPsW+Ar4+v\nRv2+ei5bt2qtUXuunquAtgHoI++DSwcu4ZVRr2DE8BFI2ZuCmQtnwtnJWewhoX6dnhv8nEbcxtS2\n6zrGlJp4fa8dY+YxdS5jqOJxveCKSSGTEDIgpFa1cMaujyyPNavSwnxKC/MpLcyn9LBHgJWxR4C0\nmFo/pV5rrKumvrraf2NrlPUdW5M6Z+1a97iEOOUYz/zTJ0D1uDG9CXStb94785S9BxZAwDAIzYKa\nGYxNfVxVvT6GQRmXaqz7j9s9aqd8/uF/npMNlAltItqIsar6HHg86yFs2bZFOHzksN641Y9X9RUw\npX5f31g6c6V1nee9M09v7wFDc5nSG8ISNfHmfF0ai/WN0sOcSgvzKS3Mp7Qwn9LDHgFEVqRea6yr\npr662n9ja5T1HVuTOmftWveV/12pHOMcxD4BqseN6U0QvyG+SgwJWxKUvQccAfQDbpXcMhib+riq\nen30gzIu1Vj3H6/sU6l8vvk/zwnOAgr9C8VYVX0O8rzz8GP6j9h1YJfengzqx6v6CphSv69vLJ25\n0rrOiVsT9fYeMDSXKb0hLFETb87XJRERERHVX9wIoAZHvdZYV019dbX/xtYo6zu2JnXO2rXusyfN\nVo7RCWKfANXjxvQmiJ4YXSWG6U9PV/YeKAPwO9DMuZnB2NTHVdXr43co41KNdf9xu8N2yudvAvgN\nYr8B1wxXMVZVnwOPbA8MCR6CUcNG6e3JoH68qq+AKfX7+sbSmSut6xz1VJTe3gOG5jKlN4QlauLN\n+bokIiIiovpLJgiCYO0g6trt27eRkZEBLy8vuLi4WDscqiVVPv39/Y3u+aDIUCB5f7L4gSdxYyJk\nMhmmjZ8m1tSrnlevRdb3uKE5ajqGSsreFMRvjEd0ZDRGPz5aHKOFYwvs+nGXxuPaa9E1p64Y5i+e\njzWb1+BB3weR8J8Eo2LTjiPYLxjpp9IR7BeMHw7/gNYtWsPXxxdD+w/F9799D0EQ0Nmjsxizr4+v\nRh6S9yfjXwP/BVmlDP7+/sg+n603btXxgT6BOJF1wuD1rO4aqMbSlyvt66ydD1Pmqq52X/uYmrxW\nDDHn69IYNXl/km1jTqWF+ZQW5lNamE/pKSoqQk5Ojk3klBsB3Aio92r7SzJlbwriNsQhZmKMxoc6\nVYO9iLAIizQmMzS+IkOBhC8TIJPJEBUZBUB5C3d33+7YmroVmeczsWDGAvj6+OK9+PeQeT4TQ/sO\nRdrJtCprMTaWnHM52PrtVnT27IyH+j6E0IdCcTzzOCLCIgAoN0wEQcD0CdOrxKwa49b1W9iwawN6\ndO2B/7z5HwT4ByBlbwqWJixFJ49OWDBrgca56tff18cXW/ZuQaBXIEaEj0D2+exq59Seu7tvdzHe\n6o5Vv67qzRRV6zQl75Z8nVQ3tr7XrS1RZCg08mnt/4enikn7mlr6vS41/A9TaWE+pYX5lBbmU3q4\nEWBl3AiQltr8kkzZm4KxcWNREVwB+3R77IjZIf5lPTw2HLleufDM8UTqm6lm/YBgaHxFhgKhr4ei\noEJZ8++a4Qr7e/YoaF8A2VkZhH6CsgTgb6A5muPm4JvAAYg1+OprMTqWylzgCoD+UI5dANi1tkNl\n30rIz8pRdrMMRUFFwFHA3d4d+5ft1/ggFR4bjty/c4Hb/4zR6l4rvPPEO5i9fTYq+1YCR4E2Qhv8\n8MEP4gaB6vrLfpLBxdUFhf6FcD/jjpXPrsTsr2ajoHOBzjmrxN8iF/ZZ9qgIrtCbM+3rKj8rx/89\n93+I2RSDXK9cyM/KIdwRUNC9wKi8W/J1Ut3Y+l63tkQ9fvcz7ti9YDeCg4JtJibVNQVg0fe6FPE/\nTKWF+ZQW5lNamE/psaWNAPYIoAZNuxGfqvGbpZunGRo/aV+SRuO/q/5XlT/nQ7kJ4Ajlc87AzTs3\nlT9XQGzEp6uJncFYzkH5AV41th2UH95VTRXti8TnCoQCjZjFMTI1xyh2LMbK/64Ux0FPoNC+UDxX\n/fqrNw8s6FKAhK8SlJsAeuasMnc+xLGqa8qn3VBRvXmivsaBBq+dBV4n1Y2t73VrS9TjL+hSgD3f\n77F2SHXWlJGIiIjI1nEjgBo07UZ8qsZvlm6eZmj8iLAIjcZ/rhmuyp/lgOx3mbIR31EAJcADTR5Q\n/mwPsUmfriZ2BmPpBLGRH44CqATs0uzEhnptKtqIz7nL3DViFsfw1RyjVVkrzJ40WxwHR4E2FW3E\nc9Wvv3rzQPcz7pj+zHTIz8r1zlllbjnEsapryqfdUFG9eaK+xoEGr50FXifVja3vdWtL1OP/f/be\nPCqqK2v//1QVIIoyFYVgBJXBiIAjgkMc4kCMMY6t6Tgn6UQTlWhGY9KJeTUmJm86in67NT28v8Sh\nO6OaqN1t1KidOCBRFJBWEQ1oQKliEgFB6v7+uHVv3SqqmJwr91nLBXXvOXvvs/cplnXrPM8OOh3E\n6KGj73RIt02UUYUKFSpUqFCh4m6HbsmSJUvudBC3GzU1NRiNRnx9fe/4kQwVNw6pngaDAXd39ybN\n7dK5C939u2Pcb+TDpz+Uj1cHGgJJ7JpIu8vtWDprKQAfb/oYvY+eQEMgmVmZNq+VyMzKZOFbC/lg\n7QdUXqlk45aN7Ni9gw7tOshjJfu6dB1d/Lrg29qX//fJ/+Nf3/+L0OBQoqOiebjHw+gKdfTV9uX5\nMc/TsqYlCa0SmNpvKme/PYvbJTfmPzqf6JBoWqS34JrxGqG6UDxPebJ02lJmPD7DJiZn8UdHRYtr\nrWlHJ10nTm89Teui1rQSWhGqCcV8woxPlQ+v/PYVIq9EEh8Uz7i4cSz+38X88f/+SF5uHiv/v5V0\natmJPoF98Kny4dqRa/Ty78WIHiPoGd2TkuwSivcXE1AVQM/7enLuwjlCg0MZ2H8gfhV+nNp6itmJ\ns+ns15ne5t6M7jqaPFMeTw9/Gm26llZlrVgxZwUD+w9k6/atzH1zLmWmMr778TuiwqOYOmgq7a60\nY/7I+cTUxLB01lKnGgZPJT6F4bqBiJII4trHkTg4UZx/uR3Ln1rOjBEzbOry5T+/RO+j52DKQea+\nORfflr6cOnOKuW/OJTI0kvlj58v7pLFHyp3tH+l6samYL3Z8QYA5gO7XutMjqAdx3eLksc72rT2k\nXPm29KVL5y6Niq25sPcl7XHDBQMzBsxgQL8BTX5/3mzYv6+jo6IdXruXUN/foluFG/mbq+Lug1pP\n14JaT9eCWk/XQ2VlJSUlJXdFTVWNAFUj4J7HreZP2fOKk6cky5xye05xZlYmg18cjEljEo+fHwYi\ngdx6ePUdc9Hs1yC0FqCX+K30d29/53CcDVf/KGjKNQiDBJv5HIUgd6uvG4r/ENBZjJ8y2LJIPDY9\nYdUEzH3MYlu9AiAU6AGaFA1ChEDQxSDwhILIArQpWszVZngAOIB4ciGhLj9fl6qjNqyWIGMQNeU1\nmHqZCEq32gk9H8pLg15i4dcLxWPxKUAAhGqbzuVvKAfSWCkm/Wk9xW7FmOPMsB80LUSdhubw851x\n/5VaB9ocrehLUeOm8tdvp45Afb5UfuOtw63WMnEGtaauBbWergW1nq4FtZ6uB1UjQIWKewj2HOLV\nG1Y75RRv3rlZ5NJbOOgkAPnUz6u38OPphcxTdzbOhqvfyzLPbj69bH3Zx6/kxDcYf19r/PjCmo1r\nSF6fLD4E8ADigRrk8UK8APmif4nfb443g7fFnkXM0BE/vzauVpzbuQCTm7hGpZ3cjrms/HSlzI0n\nHshpHpe/oRrax2QqM4kfzD3EPEg6Dc3h5zvjpCu1DmRfiho3lb9+O3UE7gXNAleEqm+gQoUKFSpU\nqGgu1AcBKlQ0AHsO8fxp851yiscnjhe59BYOOoeBYOrn1Vv48RxF5qk7G2fD1T9qmWc3n6O2vuzj\nV3LiG4z/kDV+SmDe1HkkTU9Ce8TC+U8B3JHHa1O0ECz6l/j92hQtlFnslSPrGNjz83WpOnHu6SD0\n1/Uit1xhJ/R8KAtmLJC58aQAYc3j8jdUQ/uY9N56tKmWNZdYdRqaw893xklXah3IvhQ1bip//Xbq\nCNwLmgWuCFXfQIUKFSpUqFDRXKgaAeoxm3seN8qfkjj9b//hbf5z6D90Ce9iw6OXOeiX2zFz0EzS\ns9OZNXgWgRcD0dfqycrOorqymi//+SVR4VHMemgWJadL8DrtxSvjXyHyusirT34huU7f8lmDZxFT\nE0PSo0kYag301fZlVdIqm+O9B1MOcmDXAXxO+9A/rD+Lpy0m8GIg4S3CiQ2KJbYyltigWEIIoeXp\nlvQ29KaLoQtZ2VmEBoeSnZPNsR+OMcRzCGtfWsvA/gNlTvTMQTP5fPvnNtoEj/R6hJLTJWhOaGgn\ntKM6o5oQTQhPJz7N17u/JqF7Av3a9+Po34/SztyOZ8Y+w/X863S/1p3eQb3pru1OxzYd8avxQ5+n\nZ2q/qVw6c4mKHyrQlero5tuNyR0msypplRyLW4YbfpV+BBgDeGroU7SoakH7X9pjLjUTrA2m3aV2\nvPPEO8x4fAaV5yrJ/CqTqfFTeSD4AQyCgW27trHqb6sI9AmktrZW5tn/8dM/smP3DuK6xck1XDpr\naZ0c7DuyT+ZYKznj80fOJ8YthhXzVnB/q/tJ/yydgREDmffwPC7uvEjritYUlxbLe8bZ/lJyuAMN\ngYR5hmHca+SJIU+QdirNRqtBl60jvFU4sVWxDAkbwmuPv+ZU98CZj63bt5K8PpnJvSfjme1Zr45A\nc2Dvrz7NApXfeOtwp/QN1Jq6FtR6uhbUeroW1Hq6HlSNgDsMVSPAtXAj/ClHnH69oOevL/y1Docc\nsOXqm6oxeYrztKlazGFmQstubu/5rdu3MiF5gnhUPAW4AkGBQaydvVaMzzsXXY5O5mbXhtWiybDq\nBfil+1FSXIIwqC6fPTMrk+GvDqegVmynV582QcCxAIpqijDHm9GmaPFz98PU0+QwN5r9GgStINIA\nQkGTrREpA5JewhlInpTM/NnzHcahPaLF3MIMlYg0gjSgHIJ8glj8yGJZI0CboqVNTRtKvUrF2h0F\nykDvo8fUwYQ2WyvSEtLq6jM0tRb2Mfql+lFiLhHXlQJ6s559a/Y1yr4yV1LNpH2jvNdYzre9D6WO\nwq3QBmgqL13lN7oe1Jq6FtR6uhbUeroW1Hq6HlSNABUq7hI44vSbykwOOeR1uPpl1nnmODPk3/ze\n88nrk6188XigVuTNy/HlY8PNJt9WL6A4tljmmNtztzfv3EyBUCCvoT5tAqPOKH6otnD+JZ0CR7kR\nfAVRE6AHYjzxgq1eQgKsXL/SaRzmPmbIRtYSoAfgLa5bqRFgjjdTerXUWrtegD9ibPnI8TrSZ2hq\nLexjLPYotq4rXtwzjbXvSIPgRnra289R5uhW8PVVXroKFSpUqFChQsW9D/VBgIpfNRxx+vXeeocc\ncnuuvt5bb+XGp4rc+Jvdez5pepKVL54C6ETevBxfMDbcbIJt9QL80v1kjrk9d3t84niCNEHyGurT\nJgioDRC5/hbOv6RT4Cg3mhKNqAmQhhhPisZWL+EwLJi+wGkc2iNaiEDUJ6i22CkT163UCNCmaPH1\n8rXW7ihQJMZKMHK8jvQZmloL+xj9qv2s9lPEPdNY+440CG6kp739HGWObgVfX+Wlq1ChQoUKFSpU\n3PtQNQLUYzb3PG6EPxVoCOR+3/s5uf8kPjk+PNT1If729t9suOudfToT1y1O5nBL/eafGPUEukId\nfbV9mZIwhZqsGt6a9hYD+w+08ZGZlcmyVcvYsXsHNVU17DuyT9YGsOfoSzxziYM9IG4AIzqPIOur\nLLzLvekX3o/gFsH8+4d/MydxDgP8BzA2Ziw1R2uY1HsSlw9exlxkJs4Qx7jgcSwct5ALGRcw7jWS\ncF8C/Xv358t/foneR6TEVF6uJKAqAH2unvd+9x7+fv5yrL6tfXG/4k5kSSR9OvXhwbAH+WX3Lyx5\nfAnTh0/n/LbzdA/qTnBAsLwm7QktlMJ92vsQCgR6u/Um2jeaKweuUHWhijYX2rDw0YWY3czoffQU\nGgvZvHMzI7qOoOhMEWGXw3ArccPjkgf+1f4E/RJEV6+uBLcIZsWcFfh4+5DxYwY+p314KOYhpg+f\nTvHpYsJMYQRrgpk2aBr52fm0LWrL65Nex/9nf7xKvXhvznsM7D/Qhtsu+ZZqoeRYO+L1R3pHkvrv\nVNyz3Pld4u8IaRFC1eEq7tPdx8oXVtapu7S/ErsmUrq/lOpL1URHRNvoE0gaBPY97ZX7rqHe8PY8\n8dEjR9fh6ze317yjeU3lpav8xnsT9e0ZtaauBbWergW1nq4FtZ6uB1Uj4A5D1QhwLdyoRoAzvnNT\n+OP12Rj+1nCxBd4B0LqJvHWpl/2cdXPqcPQBxz3vvXPRntWKR+fTQFOmYdW0Vfzv/v8VufmHNQiV\nAgwBDsOiQYv4874/Y6oygS8Qijw/KD0IPKEgskDmqQddDOK623WMUUZr//oYQdQgCKuVtQic6SPo\nT+spdisWqQyHAQNQCLRE5vtrj2jxq/XD1NdkjUFfINuWdQSyEU8FnICAtgEYo4xWnYIIC3UgHhuO\n/UuDXuL5Dc8jeAsijz/djxa0oCC2wDaPFo0HoUqQ7zVUd4DB8wZj0ppEisZhcV26ajHu+vbH1u1b\nmZg8sdGc/ZvdG7659m5WHCq/8d5DQ7VXa+paUOvpWlDr6VpQ6+l6UDUCVKi4S1Af37kp/PH6bBRE\nFohc8tZW3npux1zWrF/jkKNvb2/N+jXW/vJ9rLx3wVdg5acrrdz8BAH8kfn46z5fJ+oY+CPz9aX5\nBUKBHJfEUy8QCsSHAMr+9fnW+xLv3Jk+gqnMZNUzSAByLD8VfH9zH7M4VxmDwrasIxBv+emPHJOs\nUyDdt+PYr/x0pRizxOOPLRbza8mjUvchPzLf5l5Ddd+8c7MYd7w1v2Rb465vfySvT24SZ/9mc/Cb\na0/VAvj1Qq29ChUqVKhQ4fpQHwSo+FWjPr5zU/jj9dkIPhMscsnLrbz10POhzJs+zyFH397evOnz\nrP3lj1h575oSDQtmLLBy8w9roAiZjz978mxRx6AIma8vzQ/SBMlxSTz1IE0QhiyDbf/6YOt9iXfu\nTB9B76236hkcBsIsPyMsPy38f7233jYGhW1ZRyDF8rMIOSZZp0C6b8exXzBjgRizxONP9xPza8mj\nUvch+Eywzb2G6j4+cbwYd4o1v0RY465vfyRNT2oSZ/9mc/Cba0/VAvj1Qq29ChUqVKhQ4fpQqQEq\nNeCex40em8rMymTLri2MGz7OYfs3Z/eaYuPjTR8jCALD+g0jIydDHpeZlcm6jevQaDQ8M+UZm+Pp\nSnvS65iwGL7Y8QVnc8+yaM4imf8t3ft408ecOH2CV373CvNnzyczK5Plq5eTcSqD2C6xTBo1SfYP\nyPOU1+xjle7bj5PiHtp3qHw9OyebNRvXENcljtT/pjJm8BiyL2STfTabovIiFs1eRERYhLw2+xi8\nPbzZ8M0Gqiuq8WjlweLnFtuMl+yPGTyGsuoym5iio6LZun0r7619j/DQcF6b95ps3z6PSt+NrbuU\ny5wLOUx5ZIpD/86wdftW1mxcw7yp8xrVyq+x+66xaK69mxGHeqzx3kR9tVdr6lpQ6+laUOvpWlDr\n6Xq4m6gBd7VYYF5eHs8//zxvv/02W7duJTQ0lA4dOnD8+HGeffZZVqxYwQ8//ECfPn3w8fFptF1V\nLNC1cCNCKtIH8dy8XDLPZNKhXQcKjYUsXbmUf33/L+K6xTHxkYkcTDnI3Dfn4tvSly6du9SxsXnn\nZsaPGA/gUFyturKaz7Z/xi8Fv/DM49YP/AdTDrJt7zb6d+/Pzh92smP3Djq060B0VDSDEgbJsfyU\n/hPTxk3D388fY4mRV+e8ir+fPx9v+pio8CgmPjKR2tpacvJyMPgZqKqporqyms+3f06rVq14d9G7\nzJk5h9raWvYd3EfqiVTiusXhhhvvrn2XjPQM1ny6hoNHDuLu4U5Lz5YkDk6U7WZlZzEgboA1F2/M\n5fjJ4+Rfymdo/6H0792ftRvWkpqeipenFzp3HW/Mf4NOHTqReiIVs9lMZKdIEgcnEh0Vjd5bz+ad\nm+XYu3TuwqCEQbT2ak1VTRXx0fF4eHqQm58r16DQWMi+I/tY+ORCOnXoZBNToCGQzKxM9h3Zx6tz\nXiU4IJi5b8xl7fq1HDp6iJDAEBLiEig0FpKVnUVUeBQAWdlZuGvcZQHFQmOhTU6VImmBhkAmPjKR\n3z3+OxLiEhiUMEjOTVR4lByDI4G1Lp27MGPiDHnvNCTeF2gIZFDCoDr3miv6V589aa8rxSpvNA7l\nfT9fP6fvz/rsNHetNwN30rcz3K6YJD+O3gMSVPEq14JaT9eCWk/XglpP18PdJBaIcJfCbDYLo0eP\nFtatWycIgiD85z//EXr16iVUVFQIDzzwgLB9+3ahpqZGWLNmjTBhwoQm2b569aqQmpoqGI3GWxG6\nitsMqZ5Xr15t0ryMkxlC0KQggcUIjEJgCELAwwGCfqhefL0YIXhSsJC8NlnQJeoEFiPoEnXClm1b\nbGyETgmVxwY9KtoLnRIqZJzMEARBELZs2yJoE7Win+EI+qF6IeNkhrBl2xbR7hwEhiHHEfRokJBx\nMkOM79EgOZaAhwPkeO19bdm2Rbw3R/TBYgTNMI3AEOs65DEWP76DfcUxiy3+f1s3ji3btsjrC50S\nKiSvTRbojxwTIxHoj+Az2Mf22hBxnQHjA+R1M8cah9KmlCdlLjXD68ZeX56Vc/VD9QIDxBjkmIYi\nLHp7kTwm6NEgOV9SbZ3Vr779o1yHs3U1NK8hPzc6rz57yv0VPCm4UTYbisP+/pGjRxy+P+uzc7PX\n2hTcSd93OqbG+mnu31wVdyfUeroW1Hq6FtR6uh6MRuNdU9O7ViPg2LFjVFdX88wzzwDwwAMPsGnT\nJo4cOYKvry+jRo3Czc2NZ599lry8PM6ePXuHI1Zxr8FGyK8H0FoUpFMK4eVH5rPy05VOxd6UolrO\nBOiS1ydbRfTiRVG9Lbu2WEXk8pHF9OghiuhJAnVKMUGjzijHa+9r9YbVsvCeJGgnJAjQ2roOeYzF\nT8nVEnGMJH53tm4cslChxc/KT1ZaxQctooL4Q+nVUttrrcV1yuKDFvG//Mj8OjalPClzKcTXjb2+\nPCvnmspM4CfGIMfUVxRPlMY4EiqsT0DQ2f5RrkMZY3PFJZvi72aICDoSq7zROOzvb9uzrcl27qRY\n3d0olHe7Yrob165ChQoVKlSouDW4ax8EZGVl0alTJ95880369evHhAkTKC8vJycnh7CwMHmcVqsl\nJCSEc+fO3cFoVdyLsBHySwPKRUE6pRBe8JlgFsxY4FTsTSmq5UyALml6klVEL0UU1Rs3fJxVRC4Y\nWUyPNFFETxKoU4oJBtQGyPHa+5o/bb4svCcJ2mkOa6Dcug55jMWPr5evOEYSvwuvG4csVGjxs2Dm\nAqv4oEVUkCLRls21cnGdsvigRfwv+ExwHZtSnpS51KTUjb2+PCvn6r31UCzGIMd0SBRPlMY4Eiqs\nT0DQ2f5RrkMZY3PFJZvi72aICDoSq7zROOzvjx46usl27qRY3d0olHe7Yrob165ChQoVKlSouDW4\nazUCfvzxR7788ksee+wx3n//fby9vXnllVeIjo6moqKC4cOHy2O//fZb7r//fu6///5G2VY1AlwL\nzeVPFRoLuZBxgcLdhVy/eJ2+IX1579n3aE1rAioD0OfpeW7kc5zJO4ObyQ3zcTNLpy5lxuMzbGxc\nyb2CIdeA2xU35o6ey4CWA5g5aCb7juxD76NnYP+B9PDvwcmvTtKmvA2DYwczMH4gA/sPpLt/d85/\nf54Obh3w+9mPYWHD+PPrfwbEb+dGdB1Bdko27hnu/H7675k6aCrnt5+nV3AvXn38VWJqYpg5aCbp\n2el09enK+b3nuc98H7oMHe1pT62pFv9z/ujNeob2H0q3gG6kf5HOA/c9wN/f/zveV705/vlxDJUG\nrp29hs6owzPLk45uHXlp0kukZqbiVuSGNl1Lq6ut6B3TGz/8qPq5ijZn2hB4PZC+Hfrifs2dsuwy\nYq/G8mDkg8QGxJLQOYHxvcZz8buLeBg96FjZkQ/nfEhEWATleeVEFEfQs11P4rrFUWgsZO2GtVRd\nrOL6T9eZ0G0C/cP607msM37Vfuw8sJM5I+YwoOUAlj+1nBkjZqBL19HFrwtx3eKIjormcuZlNNPK\nbgAAIABJREFUjv39GG4Vbhi0BryrvPEo9ECTruHFMS/y7pvvEuYZRuG+QpY+uZTRPUZjPGzk+VHP\nM6DlAJ588Ela1rQkQZPAR/M+ciqOp+RQTx00lXaX27F01lIG9h9IYtdEm7iU/GppnrvGHY9yD4d+\nlDxwSa9A4oRLe62vti/PPfycvL+ayxcPNATycI+H0RXq6Kvty6qkVY0SBAw0BJLYNVFeN9jqYtjf\nv379On/97K+EBIdQXFIsj42OirYZp/Rtb+NmCCY2FnfS952OqbF+VM6qa0Gtp2tBradrQa2n6+Fu\n0gi4a7sG/OUvf+Hzzz9n586d8rUxY8bw0EMPcebMGVauXClfnzhxIs899xzDhg1rlG1JgTM4OBhf\nX9+bHruK24vKykrOnz9Px44dadmyZaPmnDx1kkeXP0pB5wLxW/BI4AT46n0piS1Bm6rF7G9GW6QV\nj/WnARXQtnVbtv3PNrre35WTp04y/v3xXPC9ANlAvNhKb8XoFaw6sIoLYRcIORfC1y9/DcDoN0dz\nyXwJekDQ6SC+Xfytw+srH1/JS1+8xAXfC2iyNeIx+TSgBHzcfChtXepwrBQDh4GWiN/c+yIe/T4K\n/ALatlrMfcxoU7Us7LOQj458hDnMDCcsY0OBM0CC+K28ECBAofhaioFQCNGE8MFvPuD5/3ueS1WX\nRL+W+y8++CKfnf2MC2EX0B7RYtabwSjGpj+qx721OwWdC8Qch5kJMgZRbaqmqEWRSCtIA0rhnQnv\n8OG2DynSFYm5PaJl05xNPDryUWvuLTmeHDaZDw9+CH0RTx9EgOaMBj+zH0X9igg5J8b70hcvcSHs\nAkGngxCqBC51u1TnnlSzrvd3dbhvlH7txzm7r7wurTuk1Ha+ckzbE23ReGoo6FzQYOzOYr0daEw+\nxq0Yx8Xwi3XWdCfjVnFjaM7fXBV3L9R6uhbUeroW1Hq6HkpKSsjPz78rugbctQ8Cdu3axZtvvsmB\nAwfka6NHj+bFF19k5cqVbN26FQCz2UxCQgKfffaZDWWgPkgPAlT8evGXz//CWre1In+8GsgEaoFu\nWK99B4xQvD4hzn0u+jmenPSk1UYmEG0dd9+/7+PiQxfl18/VPodZMLP25Fob+86u90nrw5EeR+rY\n5QRQACRar8WnxZPSI6Xu2K+BCLv1fAVMtL5u81Ubrky8Yrt2ezuOcnAZGG6JU3vE1scJ8D7jTdnE\nMsc2Uu1ikvzttF0XJ+C+/Pu4qLlYZ71//J8/1qmfvBZHdkfb5Uq5lji7nCtq8+SkJxvcN/bjnN13\nuN+ibefbjLHLk318ytidxXo70KR82K3pTsatQoUKFSpUqFBxJ6E+CKgHlZWVjBgxgmeeeYbp06fz\nzTff8O6777Jnzx4SExN5+eWXGTVqFOvWreP777/nq6++arRt9USAa+GWnggwid+gOzsRMOGDCeT5\n5NU5EZB8MJm8TnnNPhHw8pcvk+eT16gTAdLYGzoRcBxRYO8mnQj4POdz8jrl3dITARM+mCDnuLEn\nAl7+8mXyOuU5PBEg3WvoRIDSr6NvwB3dV16v70SANMbRiQBnsd/pEwEN5cPZKQf1RMC9C/UbKteC\nWk/XglpP14JaT9eDeiKgkcjJyeGtt94iKyuLdu3asWTJEnr16sXJkyd58803OXfuHFFRUbz77ruE\nhIQ02q70IKBjx47o9fpbuAIVtwNSPZv6hlq9bjXv/+V92ri34UrNFR7q9xDpOelEdohk0qhJZORk\nEBMWw55Dezh6/Cjn8s/x6u9eZf7s+WRmZbJu4zrO5pyl6EoRQ/oMYe+RvYSFhDH5kcnsOrCL4pJi\n/Hz9mDNtDgDrNq7DVGQCDej99MyeOpvoqGjZlkajYWjfoaRnp+Pj6cOmbZvwa+3HZdNl/pvzX0Lb\nhnKd62CG+F7xTBo1id0Hd2M0GTEEGLjw8wW+3fctrVu2puxqGZ5unuha6PDy9MLgb2DUkFFs37sd\njVZDn6592JO6h6FxQ/nZ+DNxXeLYsXcHhUWFXK24isas4Ur1FcxVZjq274g+QM/pn08z+aHJ5Jvy\n+eGnHxDMAt3v7w4aSD+Tjk6jY0jcEI5lH+OxkY9x4r8nSD2ZSufQzoS2D6X0Sik/X/iZDvd1wMfH\nh5KSEs6cP0NVVRUIoNFqQAOCWcDD3YM5U+eQeylXzHF5EYtmLyIiLILNOzczPnE8AFt2bSEmLIb0\n7HSull7l/776P65VXKOGGh7q9xAXiy+i99YT3imc2VNny3MkEbSPN31M9tlsTFdMTB09lTN5ZwDk\nsZt3biY2Ipb07HTGJ46X66X0K12XsHX7Vt5b+x6d2nfisdGPyWMkf4XGQgwBBp6Z8oxsb+2GtWg0\nGiJDIvnm+2+YN30eEWERNn5iI2LZc2gPZrOZ4f2Hk5GTwbjh4+rVMpByJY1RXpPWZ/+7cuy6jesQ\nBEHew/ZjpHFSTu2vb965GU+tJ1/86wteeOoFYqJiHI51BvsYmsqNd5SDO42GYrqRmG/Xepv7N1fF\n3Qm1nq4FtZ6uBbWergeTycT58+fvipre1Q8CbhXUBwGuheb8kdy6fSsTkydSG1eLLlXHywNe5oMf\nP5Bff5X0FWMfGetw7EcTPmL57uVi+znLSYGAlgG4ublRcF8BuhydPLY2rJagi0HgCQWRBQSfCUao\nEiiILSD0fCg73thh88Fr1LJR5Hrnos2xaBMcBcoQj1RL3/ingd91P7Q6LaaeJkiD1sbWlLuVgzfi\nt+rSvCHieJ9iH660uSLa3It4YiABSIFFAxex6dQm0W+2FrOnGSqt9zEC14DxwD7AHegv2uUXxHaC\nfcUuBUKlIPr8BmhrtfFU1FP87djfELwF6GE5bRAhiGuKwPrzDKLvIcjf7IeWiXkCxPx0zJVzZ3/t\npUEvsfDrhdSG1conG+ztKPM9+MXBmDRiu0jNYQ3+Hv6YepoISrfWTKqjcr5cK0Us0vXhbw0X98YB\n0LppMcebCT0fSvKUZJI2JdWJf/irwymoFdv4aVO0mCPMDtdc396xh6P4lLaU63NkF7CuIw30VXrc\n9e4URDbs29leDjkXwj9//89Gf0C1yWUaBOmC2LViV5PmO6rRnURDMd1IzLdzvep/TF0Laj1dC2o9\nXQtqPV0Pd9ODgLu2faAKFbcSyeuT5f7xtXG1rPt8nc3rNRvXOB278tOV4ocTD8Rj963BqDOKPdkV\nfelr42ohX9GzvoFe9XIP73zED+weiB/q/YF8xIcAFp/FHsWYdCb5dXlpuTiuF7bzLPdLi0qtNv0R\nPyB7iDbXfb7O6jfeLH4oV9zHDaiyvPZDfAggrd0N8Ti+BwgJgtVnja2Njds3IvgKcs96IV6wrkn5\nM0ERt+WalCdHPc7tr638dKWcd5s15DvOt0lnssaUIMg5VdZMsqec76zf+uadm617o7Uln5Yxa9av\ncRh/gVAgx2CONztdc317xx4N5aqhPWmzjh5gKjPJrxvTX97RXs7rlNekvvT2MRQIBU2e76hGdxIN\nxXQjMd+N61WhQoUKFSpU3L1QHwSo+FUiaXqS3D9el6pj9uTZNq/nTZ3ndOyCGQvEHvTViN+Kl0NA\nbYDYk13Rl16XqoNgRc/6BnrVyz28g0WtAaoRv9kvAoIRv9m2+PSr9iOgNkB+3dqntTjuKLbzLPd9\n/H2sNouAQ5Z7KTB78myr3xSt+M38Yet9rgOeltfFwAGrXa5bbWkOa6w+3W1tTH1kKpoSjdyzXpOi\nsa5J+fOwIm7LNSlPjnqc219bMGOBnHebNQQ7zndAbYA1psMaOafKmkn2lPOd9VsfnzjeujfKLfm0\njJk3fZ7D+IM0QXIM2hSt0zXXt3fs0VCuGtqTNutIA723Xn7dmP7yjvZyyLmQJvWlt48hSBPU5PmO\nanQn0VBMNxLz3bheFSpUqFChQsXdC5UaoFID7nk099jU1u1bWbNxDfOmzmPsI2PrvK5vrNTv3Vhk\nlPn+YOWsS/oCEo9bumf/u/3RXSX/fM+hPQiCQGRIJJu2bcJd405pRSkx98eweN5iQOScC4LA7Kmz\n2bN/D+//+X28W3ljKjUR2SGSDiEd8PfzZ/bU2WTnZMtryL2Qy8r1K1kwfYGseaD0+58f/0P62XSu\nV1/nqUlP8ehDj9rMXbJ6CddrrvNA3AOMHDSSb/Z9U8cuYOND4s6Hh4YzadQk9hzaQ3ZONtk/ZyPU\nCnSO6ExYhzBC24byxb++YNLISVzjmk2eHPHR7a9JtYrrEkfqf1MZM3gMZdVlTvO9fM1ycnJzWDRn\nkczLV9ZJWcfGcuOlugzrN8xmrrP4lRoR9r6Uc+rbO/ZoKFcN7UnlOuz1FRrL79+yawsR90WwP2U/\nTzz2BHE94xqcZ29DGUNzOPNNifl2oKGYbiTm27Ve9aiqa0Gtp2tBradrQa2n6+FuogaoDwLUBwH3\nPG70j2RmVibLVy8n/VQ6IUEhIEDepTxCgkII6xjmVKRs6/atvLv2Xfxb+6PVaSksKWTxs4vrPERQ\njk9en0zS9KQ6onfK3yXhuGH9hskicfaidK/9z2us2bCGnl178qd3/1Rn3u6DuzEVmfD382d4/+E2\ndnw8fdjw7QYiOkSweN5isnOySV6fTHzXeL4/8j1h7cNkkTulb8lHUUkR/r7+cl7sBeikMYJZQKPR\noPevK4xoNBkJ0AcQGRLJxm0bccONy8WXqaqswtvbmyfGPUH7kPa8s+Ydqq5V0ad7H0KDQvnsX5+x\ncOZC+cGClH8/fz/8fa1rVQr7LV+znPQssbbhYeFyLMp6SDVzJqbnTGxv7Ya1nPv5nFx7QI4pIjzC\nZt312bIXG/z9R79HqBUY/eBovj/yPfo2enz9fCkpLsF0xcRrc16z2WeNFYmzj9+REJ80Rll7aY8o\nc9VYVFRUsG3HNjLOZ/DYI485zUdT1nGrcDv93+m13gjU/5i6FtR6uhbUeroW1Hq6HtQHAXcY6oMA\n18KN/JGUBeMEk8irPwDoEPnlR4EqCGpTV6Rs6/atTEieILbek0Tp0kBTpmHzos0OTxRIgoPaFC1+\n7n6YeppshNqC0oOouV4jiteFIous2YvVbfhiA+/9+z25NaDXMS88r3li8hT57tojWszhZsgFKkBz\nXYPQXkBXJIoYshdZVLDN/jZcbXVV5HEfBgyI7QIrgW7IwofBZ4KpNlVj8jDJLf6CdEGsnb1WFsCz\nib8Hor1aoL94/PxPM//EnE/mUKAvsG11GImYQwOiwGEFYALaYG1/uBeRnmBpD/hU1FP836n/c5h/\nIUYgtEwU5/vdX3+HMcpoU9fgM8G8Nuw1UVRQIQ4ZERbhUEzPkdieo3xQABp/S7tHSy6Da8V1OxIJ\ndCTstnX7ViasmiC2rExBpEnEW/ITibVNZYqWrxd8LZ9OaYxInHJcUHoQ192ui7lRCPEp45L2nf60\nnmK3YnkvKoU0G4PUY6lyq05noon1CTDeLtxO/3d6rTcK9T+mrgW1nq4FtZ6uBbWeroe76UGAbsmS\nJUvuaAR3ADU1NRiNRnx9fe94AVTcOKR6GgwG3N3dmzT3400fs/38dlmsDSPQ2/J7IFAM5ZTTTtOO\nQQmD5Hlz35xLTkwO5AA9LeMNQCkYTxmZMXGGjR95vAcIQQKVhZUQAuW+5ZRfKhd//6WcSm0ldAdy\nQOghiOPbCpADpZ1LaXe5HcmfJFPVrkoc5wE1gTVUnqyEAcj2yUHsNFCM+AE6D4SBoj2KkddbfbLa\nej0Y+AkYhPiB/Ko1hnLfctHHA9a1ll8qp/C/haR1ShPHKOOX7BUjr9O418iJiBO2OQvG+vonRCHC\nYsSHEe2x2ipW1CUIsjZnUZNY4zD/XBVzZdxrJKNzRp26lvuWc2rrKYr6F8n5Ne43Unmtki3uW+S1\nlHctBw8obSPmPSs7y3rfQT7IseROkcvyPuUU7rPmyJEt6dqghEE2+4Qgi02NZY2KtQpBYswzJs7g\n400fO7TlaK8r11cRU2FTy3Ya27ikfVdprJT3iJQr+/1dH9ZuXMsOrx1yfMa9Ro6FHasTb2PXcatw\nO/3f6bXeKG7kb66Kuw9qPV0Laj1dC2o9XQ+VlZWUlJTcFTVVxQJV/KohC8ZJInvlWEXmjoqvHYmU\nJU1PEkXQlKJ0aaAp0dgIDSrHSyKC2hStLEqnFGoL0gRZxesUImv2YnVzHpsjflNsEZjzOuaF3ltv\nFZw7YonLImSoKdFAuFXEUCkq2MazjVVE8DAQhlWwTyF8GHwmWPRxFBvxtvnT5tsI0CnF9zhsyadl\n/rzp80TxN6Xw4WGsOQyzxowHNmu0Fzic+shUp/mXcjVv+jwMWYY6dQ0+E2wVFVSIQzoT03Mm3Gef\nD8wWEURFLoPPBNvkqD7hQ3lfHdFaRQ7Nivwo8qZN0cr7rLEicfbrk3OjEOJTjpH2nd5bb7MXHe3v\n+jBm2BiCTlvFCB2JJjZlHbcKt9P/nV6rChUqVKhQoUKFeiJAPRFwz6MpT0szszJZtmoZO3bvoKaq\nhn1H9vH0yKe5kn2Fsh/KCHULpfLnSjTpGrp7d+c3/X9D8gvJgPgtXrGpmC//+SVt/dtSeraUsqNl\n9NT3pKOxI7W/1LLsiWX4ePsw9825lJnK2LB5A//6/l+4adzIPZ6L71lfEqMTeW3qawReDCTKP4qk\n8UkEXgwk0C2QCL8IQjQh6Av1vDz2ZQa0HMD8kfPRZmupuVxDmxZt+HLHl1w6ewntL1p61fRiQMQA\nwv3D8bvqh/mYmd/0/A21p2rR5GvwKPegg3sHWhhb8Jsev0F/Qc/kfpMpO1tG21/asvrl1fS7rx/p\nn6UT4RVBa2Nr/Gv86duxL31a9aG9pj0tT7ckvn08i2cuxlBrwDPTk9qLtTzc7WH+ffDf9Db0pvRA\nKS9PepnBXQaTvjedgJ8DqMyrxLfal4iyCJ4f/Ty5l3N5cuiTBBYFEt4yHL8cP4pOFdHyQku6enXF\nu9gbr1IvdEYdwjWBAaEDuJJzBW26lo4tOzKk4xAufneRaJ9ofHx9CHULhVPgdcWLVqdb4VXmxWN9\nH8O/yJ8lU5cw9pGxjOo2itL9pWiMGnoH9eZh/4dZlbSK0SNH41fhx6mtp1jy2yX07tGbzTs3M2vw\nLAwXDHhWeHK98DrDWw9n7UtriY6KJtAQSGLXRNwy3Ijyj2Lh5IUYag0Ycg3or+l5qNtDXEi/gE+O\nD77XfOl4vSMfPvshYx8ZS2LXRNpdbsfSWUsBUXtgaPhQqo9Vs2TqEgb2HwhAl85d6OHfg6yvsmhb\n25bRcaMpTCmkm383YrWxUADtC9uzdsFa+Xh+obGQ8rxyEjQJfDTvI3mv6n30FBoL5d8BeVzyC8nM\nGjYLtww34oPiSX4hWV5jmGcYxr1Gnh/1PAP8B7Bi3gpGdB7B+R3nifWNpbi8mA7tOhBoCGzU+9PX\nx5fwFuFEV0ez/KnlDOw/sE4+lq5cyk/pPzF31FxiamJYOmvpbT8qL9VXiutW+r9ZvrZu38rcN+fi\n29KXLp273OQonUP9hsq1oNbTtaDW07Wg1tP1cDedCGi2RsCVK1f45ptvOHfuHM899xzHjx8nPDyc\n0NDQmx3jTYeqEeBaaCx/KjMrk+FvDRd7kx8FTbkGYZBg5el7FcBpxD728eI3618//7UNd1yXqqPW\nvxbNBQ2CtwA9wJBlQHddR0FsAfpDVj41hxDb6z2A+Hsg4hH1eGy0AWS+uaetNoDEHc7OyZb1BeTW\nfUOAw+BZ7knVsCrxm+kyRDrACcRv1Fth5eorePhBV638dxvfPcRvtIUIAf5r8SNx9I9CkHsQix9Z\nLHLr/WvF4/sJWLUFLoCmhQYhQbD6zAYCQFtku6Y9+/eQ9GmSbN8v3Y//rPiPqH+w/z3RrnQCYBCQ\ningqIADoiJUrL+khWPxIMTXEu1ZytO11GqquVVHiViLqLSi4+PbzlD5Wr1tN0pdJYutFhWaBxL1X\nCvGNWjaKXO9cWX/BWazOYqyPV6/k39uvy17zoCEdAXs/8nvHwbrqQ33vz8ysTIa/OpyC2gLoIb4v\nvnv7u3uKL3+noNQdaY52w41A5ay6FtR6uhbUeroW1Hq6Hu4mjYBmUQNOnz5NYmIiX331Ff/4xz+4\nevUqO3fuZOzYsaSkpNzsGFWouCnYvHOz+EHGA+gFgq/Ie86PzKdAKICziO+IeMADzH3MrNm4hs07\nN5PbMRc8ED+M51jmWnj2hVGF4nwPMJWZxIcAHojCdt5Yfz9rtS37tPxuKrMI7OUjz8/tmMuWXVtI\nXp8s+vVA5ND7W2wmQFVtlbwe/MX5+AOtseoeJFiuJwA5UCAUyHmw8e2BKHSXb5nvr7DRS5y38pOV\nYixnLfY8rHbxRXwIoPQZL96zX9NHn3xkY784tpgtu7aw9rO1Vrt9RZt4AFLXuV4Ku5Yaya8VMUl+\n6tsLUk2VtSgQCijxKJHjMseLe8DRPKWPjz75SIxByrOHuLYCocAmDnl+PnJNncXqLEblePt41qxf\n43RdUs3ry42z9dm8dxysq7nYvHOzGKMl3/mR+TfF7q8Byr8LtXG1NvtUhQoVKlSoUKGiITTrQcCy\nZct4/PHH+frrr+UjDe+++y5Tpkzh/fffv6kBqlBxszA+cbzM++aohU+u5OmHI3KyJR72EW0d7rgu\nVQdhlrkW/rohyyDz/JV8ag4hfksv/R5uta3UBpD55nbaABJ3WKkvwAHEb8YtPHRPnadVz8DC66cI\nkROv5OorePhK/ruNbwv3nGDLfCVH/6g4b8FMC7c+HCs3X+L3l4DmsMbWZ4p4z35NC2cutLHvl+5n\n1T+Q7B4SbVKNeCIAyzqVXHlJDyEFm5ga4l3b8/2VOg1+1X42+VBy4p1xuxfOXCjGYKdZYK8vIc9X\n6C84i9VZjPXx6pX8e/t12WseNJQXez/ye8fBupqL8YnjxRgt+Q4+E6zy5RsJ5d+F5mg3qFChQoUK\nFSp+3XBrzqT09HSWLVtW5/pvf/tbNm7ceMNBqVBxKxAdFc13b3/Hx5s+RugtMKzfMDJyMhg3Tfzg\nsWXXFs4ZzvGPf/4DzzxP9AY9n237jNeTXmfHGzvYsmsLMUkx7Dm0h0LfQjRaDRcyL3A29ywjHxjJ\nz2d/Zt4L4n/G12xcQ9zgOLbv3c61fddoq29LTXkNQwYOYcf+HZhrzTzz22coqy4jpn8Mn+/4nPSs\ndGK1sUxOmsznOz7nbNlZ9uzfw+nc0/T37M+5neeIj4rn3z/+m6pPq+jWuRtv/f4t9hzag9BbIDIk\nkk3bNuGmd6OsvAwfNx9KU0rxbunNlewrtDO0w8/fD/ygpKSEgMMBhASG4NvFFwTx4YYQKZB3MY/j\nvxxHqBXoEdCD0JJQ/Hv74+XhxYp1K7jf637KjGU8NOAhMtMzcWvpxvXy6yxatIjcC7m888d3uFZ5\njYrsCtq0bIP7ZXeqr1cT3SKa7rHdyc7JprSqlKd6P8Xn//4cg9HAtZprvPnumxzLPkacZxzH1h9D\ne12Loa0Br71e9Oneh8lJk9l9cDdFxUUIkQIB2gCGPj+UP//jzxy8cJCAygDmTZ8n53Tzzs1k52Sz\n68Au0tLTOJd/jumPTsfLx4vYiFge8HmAnBM5TBk9hUMnDnH2xFlem/MaEWERLF+znIzDGcR0jiEi\nLMJmDyVPSWb1htXMnzYfgCnPTiHnQg5PRT3F90e/p0dYD1J2ptAxqCM9u/Wssw/HdByDVqtl6Oih\n7Dm0B3NHc50xUo/55CnJdfbouGnj5KPz0VHR8t6Uxkj2n3n7GXmOd6g3G77dwNCSobz2xms2VAVl\nL3ulPWUO07PT+dPMP4l7rafA7Kmzndpo6nty14pdrNu4Do1GwzNvP6PSAhqJsY+M5Su+Ys3GNcxL\nmnfbaAEqVKhQoUKFCtdAszQChg0bxptvvsngwYPp2bMn33zzDSEhIWzdupXk5GR27959K2K9aVA1\nAlwLN4s/peTcKjnuerOefWv21eFk+3zvQ6lXqXgk/DDQEkK9rX3ih786nIKaArnPvL5Kj9nLTHFs\nsdzzftW0VSzfvdyGey3z8ONqbXnyPwDuiEfPU4AACNXa8bgd8K0BmZeuydAguAliS8FeFjsRYLhk\n1TmQ154LFEPyTFEsUcnp5ygEaAJwc3OTeevJU5J56g9PYdKarDnJB9phkyNdtU7mNTvUGrgE3I+s\nAyDpEzjipDviSSs1HTT7NQhVghi3gr+vTdViDjPDf0Gjs+gaKLjvcs7q6XUffCaYigsV8h7Qpmp5\nZcArfPDjB9SG1crxS/PtbSr5/PXx/hvbY97ZPGdc8vr8NFbLoDGxqvxG14NaU9eCWk/XglpP14Ja\nT9fD3aQR0KyuAS1atGDFihW0aNGCH3/8kbCwMHbv3k1ycjLPPvss3bp1uwWh3jyoXQNcCzdLUdWm\nh7uiv33lyUratanb6/zakWswAuv4A1Daz9on/tucb60ce4Nop6p/lU3P+1OHTpHXO8+mn/upQ9Ye\n9wSL4wgBTEBvrD3mf4LSXrZ92L/N+Ra6I/e6t+lZnwO0QOZ5K3vVV3StoPxSuehHWns34AqcOnyK\ng2kHKdGXyLYJhIrCCsoR55S2KaVwXyGZ+ZniQwsp9qPASNscCcOsPen5CdvxqcBga+4lX1Kfe/te\n68qaST3uK69VyjWSaRKDbG0KbQXxtbsipwarHzln9fS6L/ct59pR6x4Q2gpkfp1JxdAKG1/SfHub\nhfsKSeuUVq+PpvSYdzbPUY5mTJxRrx/5Xg4IPQSnsTQmVlXx2PWg1tS1oNbTtaDW07Wg1tP1cDd1\nDWiWRsBvf/tb3n77bXbs2IGnpyfvv/8+P/zwA0uXLmXatGk3O0YVKm4LbLj4Co673lvvkJPt4+8j\nc9U5DITb9okP0gTZ9JnXe+vxS/ez6Xm/YMaCOtxrZY97G558GdYTAhbuvT2P2xHfWslL15RoxA/G\nRxV2gm11DuS1pwEmWDB9QR1OP0choDbAhrc+f9p8UW9AmZNW1MmRktdMGLZaA+HAQWyytTVCAAAg\nAElEQVR0ACR9AkfccUc8aWWNNCUacaAdf1+batVCkHUNFNz3+rjySg6+cg9oU7XMnjxbjEcRv3JP\nKG3Onza/QR9N6THvbJ4zLnl9fhqrZdDcWFWoUKFChQoVKlTcWTS7feC9DJUa4Fq4mcemtm7fKvL7\nu8SxN3UvYe3DWDx/cZ3j0Ft2bWHc8HHs2b+HletXMjlxMq39WjNu+Dib49XrNq6jqLgIfz9/Zk+d\nDcC7a97lbO5ZFs1ZJB/R/njTxwiClXstxTFm8BjO5J2RbUSGRPLNvm8YM3gMZdVlNv6UPjUaDc9M\necYmli27thATFsPug7sxFZvQoEEQBAL0ATwzRcEn9/Bmzfo1lF4p5fXnXmf+bJELv3rdat7/8/uE\ntQ+je0x3eT1SLqRj7ctXLyfzTCb3Ge7D18+XvLw8zuWfY9qj02jt15qYsBgycjLkn+XF5Xy+83N6\nhPUgLSeN8UPGc+j4IbLPZXN/xP2yL2fH46VczZs6z6bNn3K9aSfS6sSw59AeBEHUipB+t+e+K9fm\nqP4Ay1cvJ+dCDotmi/VU1s6+RvY2G+OjKZx5Z/Mc5aghP8ocZuRkOI2loVjVY42uB7WmrgW1nq4F\ntZ6uBbWeroe7iRrQLLHA1157zeF1jUaDu7s7BoOBxMREOnfufEPBqVBxqyEJncVGxJKenc74xPF8\nt+k7MrMyKb9WjkajITsnu46gGoitz3w8fejYviPt2rbjTN4Z1m5Yy5xpc+RxycuS6/jc8P82yH4j\nskQhOkOAQbafmZVJenY6K3+/EoDSnaXMnjqb7Jxsfv+H31NZUckXFV9QXFrMyf+epG+3vmz5fgtJ\n05MY+8hYIkMi+eiTj2jl3govHy/GJ45nz/49/PXvf2Vo3FDOXT5H0vQkIsIiWLdxHUaTkbUb1tI5\ntDOfbfmMyspK4nvE07d7XzZu28ih44dYPH8xQwcN5UzeGbLPZrP3wF5yzudgrjVTVF5ETFgMAGs3\nrCU3L5cLBRco+KUATy9P3N3c6RbZjeNZxzl59iRGkxGPFh5MGD6B9Jx0IjpEsGD6ArZ8v4UF0xew\nbfc2TuacpE90H/7w9h/knCS9kUT22WyKyotkUT+pLt9t+q5OTaV8RoRFsI51tL+vPVerr9I3rC/p\n2ek2D0qUDxCmPjeVlLQUWrZsydOTn2bzzs0AchySbWkP2D8oArhy5YqcN4CkN5IQBIE50+Ywbvg4\nG5v2D46kca/Pf73OXn0n+R1yLuTw2pzXHIrDKfemBEc5ss8TwLJVy2wE/5SxjaWuL+X81+e/TmZW\nJstWLbN5L90p4b+GBAwbI3B4IyKIKlSoUKFChQoVdzuadSJg2bJlbNy4ke7du9OjRw8EQSAzM5PU\n1FSGDx9OTU0Nhw4dYuXKlTz44IO3Iu4bgnoiwLXQ3KelSqEzXaqO2rBaQstEEbc56+aIonuhoM3R\nYo4z1xV9M+eCEVHQziK6R65VcK6+DxhKwTmhSrAR3JME5ILSg8ATCiILMGQZKLxUKPL2s+18ngEi\nQZejY9b9s/hr1l9thPH80v0oNhXDEGRBPq1Ri7fWm5K4EvG4/y+AP9AX8XUF4nH5buKafK/64ubv\nhrGtEU4giu+FWn1oU7S0qWlDaWkp6LGK/0mig78AfkA/hf0qRG5+O6x53IuoY9BPnO9T4cMnr3/C\nnE/miIKKks0MCDAEYIwy1iu0lzwl2TrXki9tthZzhJnQsroCeYNfHIyp0iRSGnogUjECRVFGZ7Wx\nF+absHIC5ngzpIHfdT+0Oi2mniZZMNJd715nXmZWJsPfGm4jGqncQ5lZmQyeN1gWYtSmavk66es6\nDwPq21sOxQDrWUtj3zv2+1b5Xtrxxg46deh0W7/NaEjAsDECh80VbPy1QP2GyrWg1tO1oNbTtaDW\n0/VwN50IaJZGwM8//8yzzz7LP/7xDxYtWsRrr73Ghg0bWLBgAdevX2fdunW88cYbrFq16mbHq0LF\nTcPmnZvJ7ZgLHogK/fmQ2zGXNevXUCCIyvvkgznODB7ivS27tljnnUX88Oph+ZkP9IACoYAtu7Y0\nym9+ZL7oy2J/9YbV8r0CoUD8YOgBhVGF4gf1fAc+E8SftXG1bNy+0fa6B2KXAn/LnAQgB8zxZko8\nSqzCgZWIDwGk162x+usBJVdLMEYZxdf+yLmRfJjjzZReLRXtJCh8WebjhvjhXmk/APDGNo/+inEJ\nUFpUyuoNq+U8yDZ9EeNR1MU+t1I+5bmWvJjjzXKtlXXavHMzJp1JjE0SU+wr5qu+2ijtJK9PFu1b\n1lnsUSzatLw2lZkcztu8c7M1Tgd7aPPOzZjKTHKezHFm1mxc06S9ZW+vobXUB/s8r1m/xuF7qTG2\nbjbsY7OPoaH7jR2jQoUKFSpUqFBxL6NZDwKOHDnCmDFj6lwfOXIkBw4cAGDAgAGcO3fuxqJToeIW\nQil0Jgm8hZ4PZd70eVbRvWCLsJwj0bdwrIJ2khhdmnNhO0d+g88E1xHck+4FaYJkIUFDlkEU6wt2\n4NMi7qdL1TH1kal1hPH80v3EuZIgX5j4Db5ftVW4kJZYhQjTEAUFJX9p4OvlK8YQjFU0UCm+l6LF\n18tXtKMU/5NEB68jigAq7RsRBRDDFXOKFOMOi4KM86fNtwoqSjZLLDlpQGjPZq4lL9oUrVxre4G8\ngNoAMTZJFPEQsiijs9rYC/NpU7TyOv2q/USbCsFIR/PGJ46vIxppH5tSiFGbqpVF/xq7txyKAdaz\nlvpgn+d50+c5fC/dCfHAhgQMGyNwqIogqlChQoUKFSpcHc1qH7h9+3Z0Oh1xcXE217/44gvy8vKY\nPn066enpHDx4kFmzZt2kUG8e1PaBroXmtlYJNASS2DWR0v2lmC+ZiXOPo7NfZzJPZ+Jb60urklbE\necQRFxxHaGEo2hIt0RHRDOw/kDDPMApPFDK0w1BKD5YyodsEWuS2YFCHQfz59T/XOYq8bNUyduze\nQYd2HYiOiiaxayLtLrdj+VPLad+iPae2nOKFsS8w4/EZ8r2u/l05uv8oAbkBhLUKw73cHe9fvNFd\n0lGbVotnsSexQizupe54nvfknRnvEN8rnp/2/ASnoFdgL7pd60bFLxW4l7jjecqTjrqOeF72ZOn0\npSydvZSS/SUYM41UmapwK3bDM8uTFoUtqDXW0s69Ha1+bsWQDkN4evTTHP/hOJyBLr5dCLweSPuS\n9lw9d5XWOa15vM/jlBvL0VzRYL5kpja1Fi5Dy3MtES4J6Cp0dG7VGfcsd6rOV9GyvCUxhhgCNYHE\necfRuU1nNGka3MrcqC2oRUgTCLweyEN9HyI6MpqWlS2JKIkgRBeC3qTnld+8QrBHMH21fXnu4ef4\n0/o/8cG6D8jJzuHof46iOa7h6eFPM/fpuYyMGYlbhhvhLcN5MOBBpvSdQvV/q1kydQkD+w+Ua7R5\n52aeHvk02hIthemFXD92nW5+3fhNt98wd9Rc0rPTmTV4FoYLBqLbRjO2x1iqj1ntrF63msV/WMx9\n5vvQZejo5deL3p16E+4bTuy1WIZ0GsKaRWuY8eAM2l1ux9JZS+V9EmgIJKJVBOe3n2dQaN09FGgI\n5JH4RyjJLsEr24uXx77MkYwj/Ov7fxEaHEqgIdBmT0t7a8YIW1+SMGVUeBRTB00Vx81e7jAme0hz\n9T56mz28dNZSBvYfKL/uY+jDLwd+4YUxLzB65Gin70+lPSn+xtxraFygIZAwzzCMe428Ne0tmxrb\nr33moJnsO7Kvjh9lHuvLya8Vajsr14JaT9eCWk/XglpP18Pd1D6wWRoBP/zwA8899xzdu3cnJkYU\nCcvIyCAtLY3Vq1fTtm1bZs2axZNPPsns2bNvetA3ClUjwLVwI/yprdu3MjF5IrVhtTLfnTTEln2h\noC0S9QEkfrkuR8dHEz7if/f/rw0fWpdjy4tWcrHr437L/uNq0aXq+CrpK8Y+MpbV61aT9EWSNZ4K\nS8CXEDn1Ege/AnhQHNOmrA1XPa+KR9NTgFrEMz8J2HLvLXGsnb2WWcmzKKkqsR6HP4D4LX2Q5bWF\np1+qKRV1AXqI36i/MvAVVny3AsFbsNEKIAXxyH8hIpdfmdMi8PX2pSSuRM5b0EUrP51DgBnoglWH\noIf47bc5zMrpB2x48BUXKij1KrXRRSAFMEHy7GS564FUD3vut9Je6PlQXhr0Egu+XGDD82/RogUF\nsQVWPr2+QKx5XC2h50OZcv8U3tv/ntV3IWgCNAgJgsO626MpnPTMrEyGvzpc1LDoIX7z/93b3zWZ\n198U3ntj5zrazyMeHFHn/Vmfvcb6cjauMTV2dk39wN84qJxV14JaT9eCWk/XglpP18M9rxHwwAMP\nsH37dnr16sW5c+fIy8ujd+/e7Ny5kwEDBuDm5sby5cvvyocAKlQokbw+WeY0y9z2Hohc9bNWfQCJ\nX14bV8vKT1fW4UM740U3xP2W/VtsSbzvjz75yDae1pZ/9hx8vXXMlaorVn56PHBeMVbJvbfEsXrD\nalEnwBsrJ74/4l+FHlYfpUWlVl0Aix7Aus/WIfgKdbQCiBfzJnP5lWsIQNYlkPKl5KfT17JGpQ6B\nhQ+vzK09D760qLSOLgLxgA5Wrl9pU29H3G/7ays/WVmH5y9x7eV4pZpb5qz7bJ2t7yrEhwBO6m6P\npnDSN+/cbNWwsOSgObz+pvDeGzvX2X5uir3G+nI2rjE1dnZNhQoVKlSoUKHi14JmPQgwGo18+umn\nnDhxgoqKCkpLS/npp59YuHAh/fv3JzIykmHDht3sWFWouOlImp4kc5plnrrl22vCrfoAEr9cl6pj\nwYwFdfjQznjRDXG/Zf8WWxLve+HMhXU5++XU5eCbrGPaeLax8tNTgI445t5b4pg/bb6oE1CGlRN/\nAPFb+TSrDx9/H6sugEUPYPZjs9GUaKxaAVKsKVg5//Y5NSLrEkj5UvLTOWRZo1KHwMKHV+bWngfv\n4+9TRxdBOhGxYPoCm3o74n7bX1swc0Ednr/EtZfjlWpumTP7sdm2vj1Bc1jjtO72aAonfXzieKuG\nhSUHzeH1N4X33ti5zvZzU+w11pezcY2psbNrKlSoUKFChQoVvxY0SyNgwYIFpKen079/f3bs2MHD\nDz9MTU0NBw4c4MUXX6R79+63INSbB1UjwLVwI/ypLp270N2/O+f3nMdQY0A4LhBYEUhNUQ0xbjH0\nNPREn6fnociHKE0rZclvlzB/9nyZgzyp9yQu/XAJc6GZLte64Gv2JTo8mi6duwC23O9u3t14oMsD\nxHWLI9AQSGZWJvuO7GNs7Fhq0mr48OkPiQiL4Innn+AfO/5BqDYU8zEzXiVeCEUCbkVuvDT9JQJr\nAsn6OgtdkY6hkUOpSKmgnbkdMxNnUnK+BN1xHcIlgdZVrRkQPID8Pfm0qmzFwjEL6SX0Ij4onuQX\nkvH386cgu4DC04VUna+i1elWDL9/OLFBsWQfyabj5Y509u3M85Ofp+BUAZezLtPiRAv6duiLv78/\n0wZOo/hMMYN9BxN4LZDz/zxPq5JWeOR7QCGYM814lXtBGngUemBwN+B93Zv+bv0JrA2k/Gg5La+1\npFtANxI0CXhXeHP1wlU8sj0wF5kJIQTP/3oS0SKCjlUdeeeJdxjYf6DMAT+64SiVFysZ33881y9d\nx/cXX3wqfSj9oZQWRS3o16UfVyqu8NcNf2X1J6upvFJJ2qk0Zg2eRUxNDEtnLSU7J5slyUsYGTVS\n1AQwdGPm5JmMuH8EJ788iXe5N4OjBvP4wMepPlbN04lP09atLX29+jIlYQrF+4vpHtSdqPAozvx0\nBo5BVOsovDRe+Nf406mwE1qTllGxo/j7jr/j29KXLp272HDbD6Yc5OV3X6aDewdG6Ufxh7l/IDsn\nm1kvzuL7H77HDTe+/OeXFJuK+eOnf2Tnvp108u5ErG8sD3o9yKqkVU6Pziv584XGQsrzyknQJPDR\nvI/qPQZvP1fKeeG+QhttBfvxA+IGMKLzCIz7jXz49IeMfWSsw/dnfRx86Z5bhhudfTrL7xd7OLPh\n6Hpjr93NaKxuwu2AfU3vpthUNB0qB9m1oNbTtaDW0/Vwz2sE9OzZk7/97W/07NmTiRMnsnjxYnr3\n7s3HH39MSkoKf/nLX25FrDcNqkaAa+FG+VNy/3iNSebFy/z2cuD/Z+/Mw6Oosv7/qe7OvqezSwJk\nQQIJRAhBUZBNBFERnUFlcwYXUIFBZ0Rh3lHHDR3HGUVmBpjl9zoK76u+ChlHx3FjUVlCQCCECIQA\ngZCQdPbOnu76/XGrqqs7CQSQMcT6Po9PuqruPefcc27xWFX3+71XgalIaAW47ZkeXAy5CC57ltIv\nEsxVLq6/xlcOLnbjlOv3Xddzlq998FpqLbUuXn0ZgnOfqRwXA0FAGK597htEjBo/Xo2/WOkfBQwT\nKvubnt/U6b71NEJMkNANUMemxsvHij+97eMQ4yV472+9+xYvbnlRLO3X6StQofTZDrQAYxFfy6uA\nyWi6CxxR2vbBXW9AyadqR+XCA1y35DpqLDWuHPiDqdkklvRvA8yKjVylhqrvCEgwiXwXFhVqfHZN\n26DOpZ+wYM0CjYev6hSoWhCxlbG0VrZS6avMGWUs0gGJQO9A6n3rO44lpaPGhHWHlWpzNc4RQtfB\n6rTy1IynXBoFe5T401xzUF+vrnQHPHnync2389ErgK759Ofi9F/I/Xkxega9ET0tH/qaHjtxrEfF\nZuD8YXCQexeMevYuGPXsfbjsNQJkWSY6OhqA5ORkDh48CMCUKVPIy8v77qIzYOA/AG3/eB0vXuOb\nO8RvVSvAbc/0UsVAlq5fkTs3WuMhe3DK9fuu6znLtQ217rx6E+IlgHrchtAFUGO92hWjm3ZAqa7/\nMHG+IrWiy33rCRQ8dv3Y1Hg1wUG97WEu3vvqt1eLODz0FbQ+1yjnVP68SfdbjbuFjnoDSj7VY5UL\nv+GTDUJrQJ+DQly8/kCdjUwP30WufOv57Oo1lc+/6s1Vbjx8VadA1TYoTSmlsk43Z5SxyKEy9f71\nnY+lE42JyrpK8RJAsVFZV8mrf9dpFAxDvGjSzUF9vbrLn+9svnWF8+XTXwquvcHfd0dPzkdPjs2A\nAQMGDBgw0DUu6EXAoEGDyM7OBiA1NZWvv/4agFOnTn13kRkw8B+Ctn+8jhev8c3N4reqFeC2Z3qs\nYiBH1y/RnRut8ZA9OOX6fdf1nOXQgFB3Xr0T8VVbPfZC6ALo97k3486PV+NX++8R5yMLIrvctx67\n4LHrx6bGi7MT23tcvPcFdy5w1zNQ9BW0PtuVcyp/3qn7rcbtg0tvQO8r0XWscuGnT5outAb0OUjG\nxeu344on18N3oivfej67ek3l8y+cs9CNh6/qFKjaBrFHYrEGW10xKGORaiSCGoM6H0snGhPWYCum\nXS5dB2uwlSVzdRoFexArLHRzUF+v7vLnO5tvXeF8+fSXgmtv8Pfd0ZPz0ZNjM2DAgAEDBgx0jQui\nBuzevZsFCxbw8MMPM23aNG655RbCwsI4ffo0t956K0899dSliPU7g0EN6F34LpZN5Rfk88KqFygq\nLmJw/8Fs2rOJGZNm0NDagCRJjL96PAeKDnDbxNu0pfUbP9tIWmIaa9evZf/h/dx4zY2csJ1g4ayF\nTJs6zc222rYzG+qx2nbpc0vZfWA3mWmZ3D/zft756B1y9+Xi6+PLM48+Q/GpYp5+7WkwwQMzHtBi\nTO6TzD+2/IO+EX3555Z/EhwYzB033sHmXZtJSkhi2cJlbkt2VV6vrcqGNczK/FnzO4ztQNEBMcZ1\na9ldsJuU+BT6xvclPCxcaw+w7Jll/HH9H0mJTyE6KprCE4U0NTZh8jIREhDCTWNv4l9f/gvZIXPf\nnfexc/9OcvbkIJklModkMmPqDD7f/jmSJOEle/H2x28zPms8h08dJjwwnOSkZB6Y+YBbnh5/7nH2\nHd7H7FtmExgWSFpiGu9+9C5Hi48y8+aZFJ4qxFZlo6a6hip7FTOnzqSutc4t39kfZrNq3Spuvf5W\nCk8VIsuyWx7WrFvjVn99DQHtupr7hbMWkpyYrM2lsSPGkvttLpkDM8n9NlebG/raFxYV8uKaF0ns\nk8jyRcsZnDqY7A+zeXH1iyQmJDLjphma7y92fNGhXmeb0/r51dl8627frs6drb2KC70/zyfeHwJ6\nUj48a9qTYjNw/jCWHvcuGPXsXTDq2fvQk6gBlgvpNHz4cDZt2kRzczNhYWG89957fPbZZ4SGhjJl\nypTvOkYDBi4J8gvy2fDJBqZPmk5hUSFHi4+S2CeRW268Bb8gPxpaG7SHrewPs/ni6y9IS0yjsKiQ\nFatXYA2yUlZWxm/+6zcdHrCfe+05pk+aDqD5AMgrzKOwqJA169YgyzITR01kwycbKCwqJK8wj+mT\npvOb//oNq99azbETx3jhTy8wPms8ZX3KyBqUxYrVKwgPDGfW7bOYP2s+hUWF/Op3vwIZ/Mf6U1dX\nx7bibTQ2N/LTO37K1cOvZtOuTZw4eYJ7l97LrJtnceTkEc230+nk5KmTfPbVZ3y57UscOKiqruJ0\nxWmmj5/OM8ueYemzS8nNz+XKflcSFBDE/oL9pKemA+IFwOtvvU54QDjPPfIch4sPI0kSsdZY3v74\nbaJCoyizlfFV7ldcEXUFlXWVnD5zmiMnjjBi2AgSohP42/t/4/OtnxMcEsyIoSO4KvUqQoNDKTxe\nSENzA14mLzb8cwP//e5/ExUexW9/+VumTZ3GjWNu5OCxg8RFx5HQJ0GrSeaQTMaPGc+i1EWd1lr/\nYJtXmMfCWQvJK8zr8KJhwycbmHDNBD7f/jmfbfuMBbMXuNXw8+2fay8OAA4XH+bz7Z+TnJjM8oXL\n2fDJBtKT07G32Nn/7X7q6+u1eAqLCrX5lJyYzNQJU91iS05MZsTQEajvaQ9+e5B//PsfzL5lNpER\nkW5tOxuj57xb/F+LkWWZBbMXnPPlgdrvl4t+6XZenbOd5VO16TmXz+ehMPvDbFa+uZLFcxZrL9Jk\nZ/ffU6sxpSenX5D/ng59nruDzub8pcL5xmbAgAEDBgwY+P5xQSsCLncYKwJ6Fy5WjMxNsG0nUA3E\nABliCfiyCct45P1HBD/8E5BCJeQsWSwHr4eYKJdom95uTF4M+EJZSpnbb1V4jmKQ6iTkPjLmKiHM\nF5MXQ1t7G5WOSpdAYA2C596Em/BcWFEYNY4asV/9Vwj9AC8ER14V0SsHrgMKcQkaqkKCNQh9Aauu\nfbvSXvErVUvIcbK7eKEiPuj7tS/N5mbB0d8JnAL6I7Yt3A8Ei3bsUeJQcsp2QFaOVUFBVRiwDJfQ\n307E1obDgcO4iRHeO/xe/lrwVzGmTSD5SyIP56hJB/E7DxFHz2t6gT5rsxUvqxdl1jK38xFyBHKL\nrAkHRhZEYm43U3ZFGdIBCblNFgKPWWJ5/9Jrl/Ly1y/jyHRgyjER5hVG5VWVbv41Icc9Sg7G4iaC\neDbBvtgjscjNMmXpYt61W9qxpdoE7cHcfYFB1b6nsGSEHIHFYqEsvaxTMUFzrhBUTKgT1/r37X/O\n+zP7w2xNuNGc6y6o2B0BOn3snv5/iA+ol1pc0PhC1btg1LN3wahn74JRz96HnrQi4II0AgwYuNyh\nF7hyE2wbibgrFBG40pRSXv37qy5RORAvAVSBOIe7aJvebplcpgny6X+rwnNkCHE5jrqE+crkMiFc\nqBcIDEc8yHsIz1V7V4uHX2/EQ7dV+asX0WsTbd0EDUt1dh0e7YPd/cpNckfxQkV8sDmo2SUSOBLB\nXx+m2A93tWOYe065BvGyQi8oqAoDBnqckxV7HmKE6z5c5xqTFVcezlGTDuJ3HiKOntf0An2VdZWi\nhh7nbWabm3BgRWqFEBpUxANxuPLvzHSy5u01mk9nllPU28O/JuQ4DJfYoS43ZxPsK00pFf6V+WRL\ntWmxno/AYFfCkjazTbPfmZigKqh4PsJxeuFGT0HF7ti5WP+9DYaAnwEDBgwYMGDgXDBeBBj4QUIv\ncOUm2LYTIWaniMDFHollydwlLlE5QMqRXAJxZnfRNr3dGClGE+TT/1aF59grxOVIcgnzxUgxQrhQ\nLxBYhdhmz0N4Lqw1DGmnEksdQkSwDncRPS/R1k3QMFZn1+zRvs7dr+QndRQvVMQHfet9XaJ8OxEP\ninsU+1WuduxxzynbEYJ+ekFBVRhQL/S3E5AUex5ihLOmznKNqRJXHs5Rkw7idx4ijp7X9AJ91mCr\nqKHH+QhHhJtwYGRBpBAaVMQDMbvyb8o1Mf/O+ZpPU45J1NvDvybkuAeX2KEuN2cT7Is9Eiv8K/Mp\nsiBSi/V8BAa7EpaMcERo9jsTE1QFFc9HOE4v3OgpqNgdOxfrv7fBEPAzYMCAAQMGDJwL5qeffvrp\n7zuIrvDSSy/x0EMP8ec//5nVq1fzxhtvcN9997Fv3z4efPBBXnrpJb766itGjBhBSEhIt+22tbVh\ns9kIDQ393pdkGLh4qPWMjIzEy8urW30qbBWc2H+CgEMBLLp9EVKlRN1XdVwVeRXpfdLhNFhPWLk2\n8VrmzpjLDQNu4PiHxxl6xVD86/yp31FPWnAa49PH0z+kP1t3bGXLji2EBobibfcmuTqZzH6ZLLp5\nEWltacy7YR6NJY0072gmvD2cQe2DiJViWfqjpSSbk/Gq9sL+tR1TrQm/Vj+i2qJIa0xDLpNpr2gn\nqC6IUbGjKPm0BOcZJwHFAQyNG0ofSx8adzQS3BxMYGsgPg0+WBusNOc2My1tGlZfKxU7Kwi2BxNf\nEU9qUCq+xb74V/oTKofi1+JH45FG5P0ylIB3ozcBBQG0nGwhoCGAG66+gWhnNPYddjgF7TXtSGck\nhrUOY3TqaMrzymnY0YDljAU/kx9+9X6kOdJoOd1Cc0kz0h4JSsHSZMGvyo/23e2kB6Xj3eBNCik4\nTztpzW3FVGHCedSJX5MfcY44mnc341vhi7PWiV+xH+YyM+372jGVmnj8rseZML5/HzsAACAASURB\nVHoCuzftxuuAF4tuXYRcLlP1ZRVJliSSIpJ4acFLVFVX8fCTD5OSkMKiaYuIK4/j2Z88S2FRIY+t\neIzwlnBCS0MZFj2MmJMxVJ2o4grrFdw8+WYsNgv7/7mfJK8kgo8GEyfH8eidjxJtiebqgKuZOXIm\n1V9WMyZhDH/91V/56U0/peZwDQGHA1h400K8mr2QCiSG9xnOiMQRhDSG0LCzAWuTlZDQEO4bdx9t\ne9t45YFXePSuR4krj+OeMfewZdcWUpNSmTtuLpYDFrJis1g+cznmPDMBTQEsnb6Ua/2u5dmfPKst\n21+7fi2pSanMGjOLuPI4Xrj3BUYljaJiSwXPznuWR3/0KJYDFpK8k8jsl0nmkEyiIqPc7geVT/6T\n639CWluaZh8gKjKKyWmTRTwxWaz6xSrm3jBXy+fg1MFERUaR6JuIbbONHw//MT6nfHh61tOMHjW6\nW/enw+Gg6nAVgYWBvP7w6wzPGI79pJ2R0kh+v/D351zWHhUZxaRBk4grj2PR5EWkWdzH0FOh1s8a\nYu1Qk4vpr8/HpcjDhfyb+30h+8NsHn7yYUL9Qhk4YOD3HU6PxOVUTwPnhlHP3gWjnr0PTU1N1NTU\n9Iia9miNgHnz5jFr1iwmTJignWttbWXChAksW7aMSZMmsWbNGr744gvee++9bts1NAJ6F86XP+XG\ned4GJotJ7Nuu52PrfsceieVP9/yJBW8soMxaBkeAkWDaZSKoNYja1FqNg2/KMeGMcGqc/4TjCayc\nubJDX3KAZIgpiaGFFqrTq116AEOAI+Bf609jSKNovxmxxDwMsVx8rxKfU4lX5f5/qxvPJ4g96LMU\nf+VAHyABl2bAVwjJUJXn74dLi0CJMawkjIYTDbRGtIp22xBf6q9xtWEfEKLEth1BSRij2GzDpTvQ\niGtLwgAlZjUnO3XHKYrtcMW+vs0JMPU34RzhxJRrwq/CjwZrg2injCvimwiq2qpwZjkx55p5b/F7\nTJs6jewPs7l95e1iaf9mwBeheaBqFeTAvan38v8O/T/RRtEcwA+kdgk5TSamxKX30KmuQKGSfyU3\nEScicFgcbjW2+lrZsmpLpxz/7nK6z8bp71IToRP73wWfXLPRiebCuTQCPP2vnLmSxesXXzJ+e0/B\nxeb9UusAnA2XC2fVU3tC/XfAgDsul3oa6B6MevYuGPXsfTA0ArqJb7/9liuvvNLt3I4dOwgNDeWm\nm27CYrHw4IMPcvLkSY4ePfo9RWngcoMb5zlQ8LQ78LF1v0tTSnn9rdc1frjK03aOcFLbUOvGwXdm\nOaHInXfeWV+ygFLB2a5Or3bXA1DaNdY3utqHI8T0VN59BuIhX41X5f7rx4MrLrKAFqWfXjMgGHee\nv16LQImxOr2a1rpWV7tAxEsAXRusutiuUWJTbep1BwKVmEt0MXtoH2h/TTr7+jYtaJoOzkwnDTUN\nrnbKuGxmm5YHR6aDVetWAYKLrvH7w5Wx67UKsoT+gNZG0RwgUOH7l7rrPXSqK5DldMuNzWzrUOPK\nusouOf7d5XSfjdPfpSbCOfQFLpRPfjbNhfMdx+tvvf6D4LdfbN4NHYBzw1N7Qv13wIABAwYMGDDQ\ng18EVFRUUFNTw4oVK7jmmmu466672LdvH0VFRSQmJmrtTCYT8fHxHDt27HuM1sDlBDfOs118xe/A\nx9b9jj0Sy6LZizR+uMprN+0yERoQ6sbBN+WYINGdd95ZX3KAWMHZDssLc9cDUNr5B/m7uPFViK/W\nKu9eXT2gxqty//XjwRUXOYCP0k+vGVCHOydfr0WgxBiWF4ZPsI+rnR3x1V/XhkpdbNuV2FSbet0B\nuxLzFbqYPbQPtL9OnX19Gx80TQdTromA0ABXO2VcEY4ILQ/mXDMLZy0EBBdd4/dXKbHqtQpyhP6A\n1kbRHMCu8P1j3fUeOtUVyDG55SbCEdGhxtZga5cc/+5yus/G6e9SE+Ec+gIXyic/m+bC+Y5j0exF\nPwh++8Xm3dABODc8tSfUfwcMGDBgwIABAz1YI6CkpIRjx46xcOFCHn/8cSRJYvny5aSmptLY2MjE\niRO1th988AFXXnllh9UDXcHQCOhdOF/+VIWtgsaSRnwO+OCodPDQDQ/Rt7IvTceb8KrzwnLQQmBt\nIKYqE8HHg5k3bh7fHv8W33pfWg+0IpfKxJTFMGXwFObeMJeSLSUEtwQzOXQyz8x5hrTANKalTePU\nx6fwbfDF39uf6hPVZJBBtDOalt0tpPik0K+5Hy8ueJHbMm/j4P8dxKfSh+D2YHyKfGg/3U5iRCJy\nhUzjl414NXkxIm4E5QXlSPslzKVmpFqJkNYQ/A/7kxqSSmBxIAGNAURL0Yx0jiQlIgW5XManwAev\nai8GxQyCM9Ce3064PZzWb1qJaImg4WSDeEA9BaYqE30cfajPqcer3Ivrgq8jUo6koaYBn0ofmnY0\ngQ2u4Apiy2KxF9lxFDgIbgym5XgL7AevWi9CW0IxHTBBOTgrnPgW+BLTGkPd8Tq8Gr0w15kxVZoI\nKg7CecaJc7cTTgPfgrnajO9RX7CDucJMWEUYo2JGcfqz08hnZKJDosmIyiC0KJSrIq4iIyUDi81C\n4/5GZl89m+t8ryPOJ44+lj5Yi61MSp7E6rdXs3XLVta+uxZro5W2b9pIt6YzbuA4xvUZx7jEcZz+\n4jS/vvvXzPzRTKoOV2HOMzM8SnD8xw4Yy7K7lxFZGUmMdwxhrWH4fetHZnwmsRGxbNm1RfDrLWlM\nS59GYXYhcoXMhLAJrHt+HfNumEft1lqkMokJgyfwt1//TVvG/9xrz/Hvzf8mpCUE30O+ZMZlEhcZ\nxx///kc++vwj+sb1JSoyivyCfB556hFeXv0yTfVN7D20t0tOv54fDuLr8fik8bTtaeOp2U8xetRo\n7X7Qt1d1CvSc8+7w2CtsFYLT7z+SJ370hFtM73/wPo88+wjbcrcxKHlQBxue8Y4eNRqLzcKh7EM8\neuuj3Dz55gv4V6Hn42J5/HpdBs+aXmpcLpzVgQMGMjR8KLatNl65/5VeRQu4WH0JPS6XehroHox6\n9i4Y9ex9MDQCLhC33HILU6ZM4fDhw7z66qva+TvuuIOHHnrITUvgbFD5NrGxsYSGhl6qcA38h9DU\n1MTx48fp168ffn5+Z2178NBBpv9mOqdCT7nx+v2d/tivtrs473sBf8TS8c3K7yzcee4JwCnEcvdh\nEHM4hg+WfwDA5OWTqTRVijaqpkCOiWApmJoRNZof63ErXoFelA0oI/5YPDMSZ/DKpleEzUwEH9+k\niyNY+HL7rdiSDknILbLQDNiMy8ZOBK3AhksvoBGhRXBYsa2uMEjAxZffCRwHrkQsaf8XYjm9eq0U\niFPy9ZUST6jSdpuSo7G6nNmAaKX/XoRmgRl33QOdRoJeL0A6LCHXyMKHv/Ah7ZCQnTLE6Ma2FUL9\nQqnxqoEMCNwRiF2yu2sQFIqYTYUm1j+4nlsm39JxfiSeIv5YPO8/9j6DrhykXbvlhVsoGyC0JTCj\naUU4k5zE18bz8o9e5uE/PyxqnyFq7ulD7+uWF26hLKIM9utyl4tYOaHkLtoUzWs/fc3NrjqW+Fr3\nGDvzoY7HlGvCmejssk9nYwe6zEd3cvbBxx9w1+/v0ra1jDgYwb+e/FeX8ap9Zq6ZiTNTaECsn995\n/n7oOFveLzXO599cA989vuvaG/XsXTDq2btg1LP3oaamhtLS0h6hEdBjXwTs2bOHQ4cOcffdd2vn\nbrzxRp544gleffVVsrOzAXA6nYwcOZK3337bjTJwNqgvAgz88PCXd/7CastqyAcGI3jbrYgHsUzl\ndz6CFz5EuZ6r+622BfEgG+V+7SHHQzhlJ6sPrhbnz8dPKwT9XxD1A+o7993V71adH9W+5/VPgRs8\n4jB3EtsZj3ZvAnOU438Ck3TX/ge4W/H9LeIh2zNPmbrfR4A7dNc/QTzEe/ZR48r3+NtVe33MuUpt\nzpUn5W/W3iz++MwfUaHND1095/14XsdrXdgdsXcEu0y73K55+ujgq5N54Jm7LGcWOaacTn3qY+zS\nRzf6dDZ2p+zsMh/dydmDv3qQXeZdHe6RruLV+ly165z5+6HjbHk30Lth1N6AAQMGLn8YLwLOggMH\nDjB37lz+8pe/MHToUNatW8d///d/8/HHHzN+/Hgee+wxbrrpJtasWcOmTZsuaNcAY0VA78D5rgi4\n/eXbORly0lgR8H2sCIjS+fsuVwSoMXe2IgC7a1eEbqwIuP3l2znZ/2SvWRGgjqc7KwI8xw50mY/u\n5MxYEXDpcLa8X2oYX6i+X3zXtTfq2btg1LN3wahn74OxIqCbyM7O5g9/+AMVFRWkpqbyzDPPkJyc\nzMGDB3nyySc5duwYqamprFixgvj4+G7bNbYP7F24kO0D165fy+69uzlRdoKl9y0loU8C9y29D1uV\njbDgMPr36c+hY4dwSk5mTp1JWWUZuw7sIj4qHi9fL8aOGMvmXZtpbmimtLKUK/tfyZDBQ5g4aiLv\nfPQO+w/ux9vsTeHJQlpbWvEP8OeBOx/A3mKnuqYaWZbFFnyA7JQxmUyEhYYxcdRE/vw/fyZ3fy59\nYvpQUlpCZV0lkizh5eWFNcxKvz79yNmVQ7OjGV9fX+Jj48kalsXIISN5fuXzVNorSYpLIikxicLi\nQspOl1HfXI8kSzhlJ8iQfEUyzaZmIoMiOVN9hnJbuXioNkH/qP4crzhOaFAoCbEJFJ4oxOJjYfr4\n6fzz839SUVeBRbIQHRGNxWThZPlJwoPCKS8vBzOYzCZGDBpB7sFcHA4HyODv509QYBBVtVW0tbWJ\ngTshyhpFeVW5kgiQvJSXGV7ier8r+hEcHkywfzBlFWVU11RT11BHaEgovt6+4IQwaxg3jbmJjzZ/\nRHVdNZIk4WPxIWtYFssWLuOLrV/wm7/8hiDvIKrsVYQHhlPfWs/S+5ayaP4iQGwztmL1ChL7JHLn\nzXdyoOgAt028jcKiQlasXkF4YDjJSclMuGYCf17/Z7Z/s53AgECuy7qOhOgE3vn3OyyZu4RF8xeR\n/WE2T77yJJjgmUee6ZSXnF+Qz4ZPNpCenM4XO76g8Gghp8pOEX9FPIl9E5lwzQS+2PEFsiwz4ZoJ\n5BXmkZ6czp/X/5ncvFwGJA4gIy2D+bPma1oDGz7ZwPRJ0wG034NTB5P9YTar3lzFreNupa61jrTE\nNM2e/u/0SdMpLCpk1ZurWDhnoRZ3fkE+Gz/bqInRqXGrfVT/ahtPrvvb77/Nc68/x+ABg/nVkl+5\nXdfHrT+f/WE2q9atYuGshRfF6+7Kfm9BZ3n/T4zZ2M7q+8fZ7rnzhVHP3gWjnr0LRj17H3rS9oE9\n+kXApYLxIqB34UJeBEx8fCJljjLIgMiCSOqL6mmOaNa+dvtU+dAypUV8pS4DKVxCzpIx55r5/e2/\n54XPXxBbyOm/MvuCqVnZQ34PYrWA7iu5tFNCTpFJqBN7pS94Y4GwsQcku9ijXr8H+y/G/IJH3n9E\nbH+l+6ovFUrIcbJmN+CbANY9vI57Xr6HWq9a8dV/B9AEDMX9a7O64uEwBLYGYh9jJyYvhhZaXPvc\nl0NYbJjruBGkdonXZr/Gr7N/TaWk+ypdgVgVMAz3XBxD6AF4fuUegrYSgx2IVQVhiCWu/ritoHBb\nIVCMEBP09xhLIzBW7GxQXVotVhwo/iLMEWx+ZTOAtt967JFY5GaZsvQybe/1wqJCbl95u9gyMAes\nTitbVm1xP6/kP6wqjGp7tRZD8L5g6mvrkce45sZvt/72rHu7e+7/vnLmShavX9xpH33b2COxtFa2\nUukr8h97JJZPf/2p2/hi8mLAF8pSyjq1rR0HF2tzzZxrxpHoIKbEva9n7Fosur7d2b++q/vTMw/n\nsnO+uNT2eyL+U2M2/se0d8GoZ++CUc/eBaOevQ896UVAj9014FLC2DWgd+F8FVXXrl/LB0UfiIdk\nb2gMb6Q9tx2miGNiwbHfIR4oI4EiYIy4JkfLHMo+xMnhJ7W2FAFXAV+DPFEW56OAA0AfND9q29oB\ntVRsqSAvOc/VthZoADlD9K8NquXQxkNUXVvl6rsbGI14yZDostsW1YZts42CMwVanMQC9cImvroY\nYpR4h0HroVZIBftpO81DmsX1SOAoNI/SHVcLG4d2HOJ0wGn38eQBE+iYi2+A/jq/0YhtBBuU62r7\nvUBf5Xiorr/qW+0zBPFCQ5/PGOV6POIlzlHgWpe/xopG4qQ4CgoL2Oi1EbzBHmrHfsYO8SLHceVx\n/O8//5eitCLNZtPBJuKCPM4r+W8ObgY/VwwtkS2idvGuuXE847hWw7jyOMaMHNNh/qnx1AbVYtts\n45vEbzrto29rD7XTdLBJG6M91E5cucf4TtuxD7Jrtiq2VLC3/96Ovopcc02OlqEI7E73vp6xa7EU\nuc/TzsaoR1f3p2cezmXnfHGp7fdE/KfGbKhY9y4Y9exdMOrZu2DUs/ehJ+0aYPpevRsw8D1g+qTp\nxEgx4iG0VawI8Avxc9ur3sffx7XvuxO3PemXzF2i7SOv7XmvfGnX9pDfg1jeXoXmR9op9qFX90rX\nbOxx7VGv34N9yT1LtGN2Ih7+c8DkZXKzG/BNAAvnLCQ0IFTE0Yr42m5TYtO1Vfe2ZwcE+QZBK8RI\nMe773IP7sV3Et2TuEiIcES5bOwEfZayeufD28JurHKvX1Rh9lfN2pW0srjrs1fXZi3gA9xxLlfgd\nlhcmAtf5i3BEcNvE29z2W489Eitqr9t7ffGcxZhyTZpNa7C143kl/2GtYW4xBO8LFrXTzY1z7e3u\nuf/7wjkLu+zjGbs12Kr5jj0S22F8MVKMNq/UedapL91cM+eaIbZjX8/YNT8e8/RC96/3zMOF2vm+\n7PdE/BDHbMCAAQMGDBi4MBjUAIMacNnjQpZN5Rfks2bdGiRJ4oGZDwCw4PEF7D+8n4dmPsTsH89m\nxaoVHC0+yhMLngBw4yyrOgOFRwupslcxc+pMjX/97kfvcrT4KDNvnsnHWz9m94HdZA7J5P677te4\n5yqveu36tRoP/EDRAdIS09zaqFzpvhF92bRnE0vmLGH8mPHMWTiHvCN5DB04lDdee0Ozt/S5pew+\nuJvhqcN5YNYDvPvRu2zdvpW6hjokJOrsdVi8LDw671Fm/3i2G/dbP97kxGTWrl/L0aKjVNZV8sSC\nJ7Rxv7DqBQ4cPkBaShozps7g8+2fU1VdxYmTJzhy8gjDBw1n8pjJvLzmZUrOlCAj0/+K/pgtZuob\n66mvrcfiYyE9JZ2Q4BB25+2mxl5D/7j+ePl5ceLoCWqbawnwC2DF0hUUnirEVmXDGmYlJT6F9f9c\nj7fZm5r6GvpE9yE5KZkHZj5AYVEhT/7uSZpbmskcmsnyhcvdltjrx+rJrc3+MJsX17xIYp9Eli9a\n3uG8qhGg+nlx9YskJSSxbOEywav3mBvn4u56tjlbH8/Y9fO2O+Prypc61/RzrrPcdBaL5zw9G852\nf36XPOfOcKnt90T8J8ZsLFXtXTDq2btg1LN3wahn74NBDfieYVADehcuZNlUVGQUU8ZPYcr4KURF\nRhEVGcXIjJG0O9ppbW8lNDCUMlsZPl4+HDxykLLKMu666S4+2/YZ695fx/r317Nl5xZiI2NZMm8J\nufm52O12Jl0/idFZo3HIDgb0G4C3nzcrHl/BkgeWMHDAQMaMHEOFrYK169eSmpTK3BlzSYhNYMuu\nLUy/YTrhYeEUFBaQmpRKha2Cdz58h7raOgqOFTBs0DCqKqt47KXHuGvqXTx6/6Ns27uNf332L9as\nW8Pg5MEMTx9Ozt4cDhQc4K1/vEX56XLwgVvH3oq92Y63lzcR4REEBgYyeuRoBiYOZMMnG/CSvHBK\nTh5f8DhV1VU8vfJpKk5XsGXPFoYNGIbJ18Rrf3yNx156jGFXDmPB7AX87z//l03bNjE4aTBf5X5F\neWU51hArozNH84/N/yAsOIyQ0BDGjxrPj2/6MZ99+RkVNRXIDhlriJWEPgmEhoZikkw0tDQwOHkw\nq19cTWVVJQeOHiDUL5TZP5rNDWNu4IN/f8DmnM1cN+w6po6fyuZdm/Hz8uPkmZOcOn2KjNQMpk2d\nxoP3PMiieYu4Y+odVNgqePbVZ/l408dkDslkYOJA1qxbw783/xtbpY38w/kcLTzK/UvvZ9OOTTy5\n6EmWP7Kc7TnbefjJhwn1C2Xa1Gncd/d9zLpjFq1NrTy98mlirbEkJCRw/933A7Bl1xYemfcIVdVV\nPPzkw6QkpHD/7PuJiozSXvZYQ6xERUYBOqHApHS27NpCdWU17370Lna7ncwhmW7tnnvtOd7e+Db7\nCvYxOGkwo0eNZsr4KVos3x78lhV/WoGPyYcTJSfYnSdeOt0x9Q7NTlRkFNZgKxs+2YA1RLz4LCgs\nIDo8mk1fb+KDLz7gjhvuYPSo0URFRjFm5BitrycqbBVa3zOVZ0hNSu2yrTp2W4WN9z95n/jYeOJi\n49yupSalusXalQ01f53l82z9zmW/u+iO3+wPs7V5M3DAwIvydzE4Vw2/CxhLVXsXjHr2Lhj17F0w\n6tn70JOoAcaKAGNFwGWP7+JtaX5BPhOfmijE+7aByaKI/u1E7PE+CtiKEKvLxLUlXh1IIRLyNTLs\nhQg5AovFQtkVZZ0Kqp1NKE4v9KYJw7VXim0AMxBbAvoA1wDbgRbEFnM5CD2AJpAiJeRI2X0LwAYE\nCcgbsRRf2aovtCEU3yhfylLKNME462Er1ZZql0CeuoVfKWKJvmrzDHAr8DliG71g3LcA9FF8qu2L\nEUKA+q0H++G2FR6FYks/Z5LT1e4o+Mf60xjQKAQGdyr2R9BBVHDj8o1uSvd6QciIbyLAF2zRNpdY\nYS6CPhGDJub4+JjHefnrlzURvfcWv8e0qdPI/jCbO1beIYQbFRpIbKVLeDCyIBJbhU0TDXxv8Xsk\nJyZ3EG4DOgjuqdv6UQwx5hg+e+kzANd8VPJjKjLx/mKxpZ8Wi5q7w4BTzFNVRLArwUE1ZmmnhNwk\ntps05QrbZ1PoPx+xQH1bU5EJZ6aT+GPx/OtX/3Ll4ByCducjqni2fhcrmNcde/r5oZ83vRXGF6re\nBaOevQtGPXsXjHr2PvSkFQGGRoABA4gt0cpSysTDciDiJYA34kEzEPE7FPESwBvxABsImBAvAZRz\nNrONMrkMShEPat5Q3K+YjZ9t1PwU9yvWzq96c5V2XCaXaTGUppRSWVep7b+ONxCOeAngrfwNV35n\nIV5WtIA8UhaieSNxxX9aaRuIeFhXYq1pqNH8OTIdUAqVdZXiJYDat1T5W+ths0357VBs6+wSDpzw\naN/ucezQjUv1kwXONmeHfo1tyksA9Zyki0vnc9W6Ve71lMs0HzazDVuqTfODt1JLkysOeaTMmrfX\naHVzZDo0myvfXKmdJ0v4L00pFT68oSK1AjlUduvnWeuNn210ndPND2emU8SVIeaA2k6bj0p+nJlO\nVq1b5R6LmrurXfO0NKVUm2+ec04fszxS1uaQavts6Cx2/dzuqq06n072P+meg7P094zb8145n35d\ntesuumNPXxP9vDFgwIABAwYMGOipMF4EGDCAENnSxPvsOtG/neKYVsSX6FzcRPRwgrRd0s5FOCKE\nGF0XgmpnE4rTi7VpwnB1uATwqhArAVqVv4pQHjmIr/I+iiBhEm7Ch8ThEuTb44o/NCBU86cKxlmD\nre4Ceap4X4iHTYvy26zY1tmlCrETgGd7/bEZd9FBRUTQ5GXq0M/fy98lMLgTkOlUVHDhrIVu9dQL\nQkY4IogsiHQXK8wV9dOLOc6/c76biJ5qc/GcxS7hRkVwUS88GFkQ6SYauHDWwk6F2zoT3DPlmjRB\nxBgpRmvnKUhpyjWxcNZC91jU3O1wzVNVRFCfi87EEqWdkjaHVNtnw/mIBerbqvMp/lh8B3HDswna\nnY+o4tn6XaxgXnfs6WuinzcGDBgwYMCAAQM9FYZGgLHM5rLHhfKnVN5vdWU1W3ZtYd74eUSVRGFt\ns+LT4MOV1VcS0hJCZlwmU8KnMOu6WZTsLyH4aDDRLdE0nW5iZNJIfjH9F5R8WkJ0SzS/X/J7lsxY\nQlx9HIsmLyKtLY1nf/IsgMZZnjVmFnHlcTz7k2fZm7eXf2/4N94HvLk68Wp+MvYnVH9ZzbDYYaTH\npFO4t5A+zj605rbirHTiXe2N4xsHoc2h9PXrS3NuM32cffBp9mHskLHEE8+xbcfgJLAPQRGogsSg\nRBw2B5YKC3Gn47juiutI65NG/4D+pLekkxaeRjrpjBwwknH9x3FkwxFMVSZa97UiVUjEBscSVBtE\nY04jAwMGMu3aaex/ez+yTYYq8Kr2wpkrvmxHmaJoLW3FWeqEveBb40tCRAI1R2pETKVg9bMSXB+M\ntF+itbgVDkFAbQCPznuUvC15tOxqwVRuIik+iZszb6ZgWwHt37QT3hjOz378M9oPtRNUG4R9p504\nRxxvPPkGgMbRHj1qNCnBKRzbfYyxPmNZNmsZ/s3+pLSkEG+KpzW3FbPNTIxXDA0nGjDtNTEqYRTL\nf7acGwbcgG2rjZ9N+RnF5cVC92DUaMIaw9izbg/BTcEk2hN55aFXuDnzZva8tQd7sZ3U8FQiiyMZ\nf+V4pt0oloV/9dFX1HxZw7xx87j7R3cTFRlFom8ix744RnpoOlOsUxjbbyzHNx9nSPAQJgyZQOaQ\nTAAaSxpJqUkhpCkE52Enz856luEZw/nTm3+i8UQj8RXx3DzoZmr31jIsbBiVxyvJcmTx9vNvu9EC\nHlz2IId2HqJPRR9W/WwVS2YswZxnJikgiZDWEFp2tXBVxFU0tTZReKSQxU8vZvPXm7Fg4Q9v/IGP\nN31MQmwCg1MHM2nQJMyFZsJbwrGetPL8T58nPCxc02JIiE3QNDcmDZpEXH0c94+7n6hTUbz4wItk\npGe4rin3QFfL+1e/tZpIIklvSuequKuYdP0kt3unq+X+3bGvv//PxvtXyySWvgAAIABJREFURUW9\narwILw7nhZ++wOhRozu0GzhgIEPDh2LbauOV+1/RxDbPpWXQ09BdDYaeyFntbuwGOqIn1tPAhcOo\nZ++CUc/eB0Mj4HuGoRHQu3ChuwaovF+VH59Ql8AvxvyCR95/xMUFj4AEk+AnL3hjgViuvRekOgk5\nTSamJIZ2S7tYdr7XxfHWP3x0xTF+fc3rLP77YrHE2x+Npy47ZMFbV3n+mxFfrsMRPHuV467yw/cj\nloVnKucigW+APri49tXAZDQdA7lFptK3EhLQONxqHshF0CCydPbqgDIgCkED2KacU/j1/ANBY1C1\nAhQePfsR4xuFS1cBxJfoSFwc/0aE5oETmKDrfwSoRKxqyEDbFvGJO55w4/I/du1jbse/v/33/Hbr\nbzvw4mOPxNJY3kitX60Yo5pjRWchIjyCza9sBujAT7/3d/dSaaoUecmBkIYQ5HCZuqF1YgyVIAVJ\nyFkysUdiqS+txx5s1+JeOWMl48eMd3H/FZ2GOq86QUXpRHugQ+ynGqkNqBUxbIWIyAihe3DENY6V\nP1rJovmLyC/IZ9Rjo6iLr9PmTPC+YP7+4N81rr20VUI2yS4diu2IFRejlHmn1FPVHQDctBciCyJx\n1jrFXMroqE8A539/euo7mHJMOJOdJNRdPN9f7+NcvH833RBljsYEdby/L8R2T8T5xN3TOKuXa857\nCnpaPQ1cHIx69i4Y9ex9MDQCDBj4nqHn/ar8+OJ+xbz691fdueBF4vzrb73u4mxnIPjgpYLTbUu1\naedVjndXvvQc49+/8XsXd1/HUycQd55/OBChtNFz3FV+eDgu7YKRImZacOfaq2KBio5BZV2lZk/l\ncKt5AA8fRYpvEy4tgFG48etpw10rIEsX2yiXbwKV//TxqeetiJcD+v4jEbQC1c/Voq8nl9/z+NW/\nv9opL740pZTahloRpz7His6CzWzrlMe+6s1VImdZrva1VbXiJYA6BgfIWbLmx95sd4v71Tdfdef+\nKzoNmh5FJ9oDHWKvqnXFEIpL90A3jlfffFWbd3VD69zmTN3QOjeuvRwqu+tQXINLE0NXT1V3wFN7\noSK1wjWXOtEnuBB4+nBmObX782Jt632ci/fvWSsCO7+/L8R2T8TlGjdc3rEbMGDAgAED3xeMFwEG\nfpDQ835VfnzC8QSWzF3izgVPFOcXzV7k4mzvRfDBYwWnO7IgUjuvcry78qXnGD9yzyPia7cdN546\ndtx5/lUIdfu9uHPcVX54FS7tgp0iZnxw59o7cdMxsAZbNXsqh1vNA3j4SFR8O3FpAWzDjV+PF+5a\nATm62La5fGNX/vNBfN3Xn69EfKHX99+JEBpU/ewQfT25/J7HS+Yu6ZQXH3skltCAUBGnPseKzkKE\nI6JTHvvCOQtFznJc7UPCQwjeF+wagxmkHEnzE+Qb5Bb3kjlL3Ln/ik6DpkfRifaA5++Q8BBXDDW4\ndA9041gyZ4k274L3BbvNmeB9wW5ce6lGcteh2I5LE0NXT1V3wFN7IbIg0jWXOtEnuBB4+jDlmLT7\n82Jt632ci/fvWSvsnd/fF2K7J+JyjRsu79gNGDBgwICB7wuGRoCxzOayx4Xwp/Q84hGRIzi++TgJ\nXgnYm+yENIfg3OPkoUkPMXnAZJ79ybOMHjWayWmTsRywkBWTxbK7l5FmSWPeDfMoKyij7us6EpwJ\nNFY0cuDgATIGZ1Bhq3DTBTDnmfGq8eJv7/yNr3Z+xdwZcxkYNpCvP/4ax2kH8eXxLLhhAW22NjJ8\nM4h2RtOyq4UrQ6+k7ngdbSfb4ADipcA3EN4STlR1FL52XxynHJgOmohqjsJ+0A5NQAlwAIJqg4gJ\niEHeKxPeFE6UJYqf3/lzpDKJpgNNPDjxQUKOhVCeX050VTSjkkcxIHAA1pNWpFMSdd/WEVQZRJgl\nDEeZg2vka0jxS+HYoWNwXPigBkx2E/IpGemAhFe5F84DTrHbQAkEHA2g/WQ7lIOp2kSAHIDjjAPf\nb33hJDgrnHhVe2E1W2nNaUUukTEdMyGflukT2Iemoiac+5yEN4Xz0s9eIr8on5J9JTTvbCaaaG4a\nexO1R2up/aqWJVOXsPzny7HYLBzaeIhZo2aRbE0m4ngE3g3e/OyOnxHWGoZULHGFfAWNOxux2CwE\ntAbQUNbA17u+5uCRg/T17cu4gHH87uHfER4WzsHcg5QfLMdywEI/n348cc8TtJS2UPFFBZZyC8GO\nYHzsPgyqHUQ44YxLHceJPSfwO+zHS/NeYvyY8axZtwbvGm/8j/gz3Dqc64dcz6xrZtG2t40Zw2fQ\n/m07EY4IzA1mJgZO5O5r7qb4cDEZTRmMShrFz2f9HFOlidottZjrzUQ5omg90Ep7STumfBPzrpvH\n8796Xpvjg0IGsf1/ttN4XGgKrP3FWqZNnYbFZiHv3TyGRAwhwSeBlpMtjPUdy6KbFlGSX0L06Wh+\nOfOXIk97JUYmjCQ2MpYtu7Zw76R7iWyP5GrT1fzs1p/RUt2CdFpiYtBE1j6+tsOS7H0H9vHXt/9K\nfGw8cbFxnXK59ecGpw5mSsYUag7XEHA4gMdue4xrw689K9+/O/D0cS4dgajIKO2eT/JJYuyAsax8\ndOU5Y6iwVVBfXM/Vpqv53cO/u2yWqKv/JloOWBgQMoDMIZldcu17Gme1u7oQ3cEPUWugp9XTwMXB\nqGfvglHP3gdDI+B7hqER0LtwMfyp7A+zuX3l7WJ5/GZcXPs9EON1dj5wfkE+1//8eiolwbXXeNo7\nIbA+kMDoQMrSy1wc8z/cK9pmCPsRUgRPTnuSJf+3RCx/3gYmiwlnlsLXD3dgqlL2mD+C+AJvcvng\nNELNPwOXbsDnQAAwQBfPdsRS/LG4vr7XgCnahHOEEylHQq6SXXx/ZeyjQkfx/un3O9rYgXjRMNR9\nzKQoxymKH3/EUv6dgB/iC3OoywfNiBcFocCVOlu5SoxjEV+ySxAaAYofv1o/mjKbhP6Aak8XnynX\nxNJrl2qaAeQAvoq/LLR93pMTkwUXvb5M7GKQosvjDpHD2MpY/nTPn4Q+QHOlu57DDgm5WRZxfoxY\nSq/XbjgCRIK5SmgWvPD5C5RZyzQfplxR24Q6RYNizQLKass0qoi0U0Jukl15SIaEugRmXjmTF7e+\n6NI2OAnEC5tSjsSGJRuYNnWaizcdXIy5yIwj00HCcaGDseT9Ja457yvq1Jm2Qmtlq8b/18f70X99\nBODGoe9KH2PyM5M5lXiK+GPxvD7rdU2fQOVyAx343Z2du9iHu/8Eh/xy56p3N/7eylm93Ot3oeit\n9fyhwqhn74JRz96HnqQRYKwIMG6qyx4X87b04ScfpiitSDzgVQNXIX5Hgf2MnTgpjjEjx3Tad+36\ntXx4/EPxQFyk6xsLrd+0Yg+3QzzUBtVSsaWC/PZ80Vax31jRyKEdh6i6tkqcs4E8THDM5WgZdoN8\nneyy/RVC8E/xwV6gH9Cg810LDPeIJw6x/DsewcGvAcpBnih8EaO0v9Z97IdzDiPfJHe0EQvUe/iN\n1fksQjz4D9dd+xq4ArfxU40QCRzrEW+0zlcMQvhwistW+9528fDqq7Oni0+Olsl/L5/G8Y2u8X0N\nTETLrW2rjaaWJj4o+kC08cyZMh77QDu2zTbyy/Jd+gVDdW3UOI8AYzrJhVLDQ9mHODn8pJsPOVrU\ntnZALbbNNva37heUic7sKzWqHVBL/nv5NE9sdo1tr25exIBtq425d8xl7fq1bPTaCEUgZ4g61gbV\ncij7EFWjqlxzfrgrnkPZhziecRy8wR5qp+lgkzYv9PHGlcdRUFjAB75K/iI7v1/Wrl9Ltne20CcI\nrqNiSwV7++/VYlHtbPTaeM5zXd2H3YGWi+/I3vft51Khu/H31i9Ul3v9LhS9tZ4/VBj17F0w6tn7\n0JNWBBgaAQZ+0Fg8Z7HGkXfj2u85Nx94+qTpRDgiXNx9HSc/MCRQ43arGgNaW8V+hCOCJXOXuDji\ndrTf5lwzJOr2mN+JeOjX8/59ETQBvW5ABeJrtj6e7Wj7xbMX8XDpA6ZdwpeUI4EDt9hipBimXT+t\ncxs7EHx+jzFrx7FKXDt015KV/jof2BF+t3vYytX5ykG8VND58Q/yd+kP6LntSh9TrslNM0DbgUDJ\nkbrPu8ZFt+viVvOo5DD2SKxLH6AKdz2HHZIrTicdtRsUfQVVsyD2SKybD7W2qgZBjBTjxteXdkru\neVDazr9zvru2gY/LppQjaXvYa7zpWLRcqDoYbnN+hysvntoKev6/Pl5VL0DPoe9KHyP+WDy0Qvyx\neBbNXtSBy90Zv/u75nz/pzjklztX/XKP/2LxQx+/AQMGDBj4YcFYEWCsCLjscTFvSwcOGEhGeAbH\nPzrOkKghjLhiBEOahzA28dx84KjIKKYOmyq4zCcDuHHAjVRsreC6+Ot4+/dvM/eGuRpndfSo0Vpb\naZ/EhJQJ/PVXf+XmyTeTYc3g+IfHGZM8hmfmPENaWxqLJi8iLVD8jaqKorW4ldoTtXhVeCHvlwlr\nCmP6+Oncf+P9lHxZglQu4f2tN+MGjmNMvzEc33Kca2OuRSqQmD9hPgmBCUh5EgN8BhDnHceqx1dx\n59V3Yttq43cP/I5RA0aRtzWPjJYMbs24lZWPrmThAws5lXuKgg0F3Jp2K/1D+tOU08Rzc55jaOxQ\ndr23C8dJB+Z8M/61/gyRhmCxWfA65sXA0IG0lbbRuqsVnyofhoYNRa6SaSluweegD6ENofg2+jIu\nXcR79POjJHolEn4inNCWUKKcUbR/045PtQ9ZA7NIsCTg3O/kudnP8cKSF6jdVUvN8Roohb62vjw1\n8ynCCCOgMIDXH36dh+9/WNvXfclNS7i237Xcln4bbXvbeOX+V5g2dRpRkVFMyZiCucZMckAy3oXe\n1BbVMqRpCOMGjGNcxDheW/yaqF3WVGpO1CBVSWRGZDIlfArLfrwMU52JgMIAlt69FMkm0ZTTxI+H\n/RhrtZUZw2fgW+nLK/e/wty75wq++VELSX5JjAsYxxN3PEGaJU2bH1MypmCuNRPZHIm12MqqRau4\na/RdrjEoPPm7f3Q31iYree/mkeyTjMVhgTPQt7Ivf/3FX5k2dZo2PycNmkRcfZyYT23C182Tb9bm\n/JgBY7h/wv1aXubePVfjWr9w7wv89KafYq4wc7Xpard4B6cOduPQZ8VkdXq/REVGMTpxNF55Xrz4\nwIuMHzO+A5e7M373d8n5dsvFd2Tv+/ZzqdDd+HvrF6rLvX4Xit5azx8qjHr2Lhj17H3oSSsCDI0A\nQyPgssfFagQsfXEpNdU13DL+Fnbm7UQyS2QNyuL9T9/HITu4bth1TL5+Mm998BbJfZNZvnA5AGvW\nrUGWZSaOmkheYR7TJ00HxFZW0ydN73Rf8g2fbCA9OZ3Pt3+OLMs01Tfx3ufvMX74eGpaawj1DuWL\n3V+w4M4FzP7xbLf2tkobe/fvpbCkkMTYRCIjItl/ZD+yUyY5Ppn6pnpa21oJCQrh/jvv591/vcuO\nPTvw8/XjuZ8/p4nVybLMgtkLtFjTk9N556N3+HLbl1TVV4EE4UHhRIRGUFJVQkp8Cn3j+3Ky5CSH\njh8ic3Amv/nVb3jr3bd4/c3Xkdol2k3t9Ivuh5e/F22NbZRUlXBD1g3sL9xPaXkp3t7ejMscx6bd\nm6iprEG2yJjbzYSGh9LmbCMyNJKxWWP5YMsHOFodtDnaSLsyjZDAEI6eOoqz3UnWVVksX7Sct959\ni9Vvr2bBnQtY8eQK8gvyeX7l8xw4dICEuASCg4KRTBLVVdVU2atI65/GB1s+IDggmN/+8rcArHxz\nJYvnLHb7rT5Aq3U6Ww31tW6obeDtj9/mkXseYdH8RR3qbKu0EWGNYP6s+Zq97A+z3fx2x2eIbwgb\nN21k8ZzFJCcma+fW/XMd1iArSYlJmo/8gvwO8zM9OV37+86H73D05FGWLVjGtKnTtHj6R/Xni9wv\ntLF0hvyCfFa/tRpJktzG1FXuuro/zzbmi8XF2PbseynjvFxhcFZ7F4x69i4Y9exdMOrZ+9CTNAKM\nFwHGi4DLHhf6j2T2h9lMf3W62Pt9J1CGWLqdhbs4Xo5yLQHIgLC8MEztJiqvqhRbCdZJyGkyMSUx\n4AtlKWUdhKb0IlSq6BrfIIThVLG9SMTSfuU4oCqAhpENmApNOJOdIg5VkG4Hgl8/HrF0uwyIQAgd\n7kXoACQgluhnAdsgyBRE/dX1sBeszVa8rF6UWcuQjkjIkTKcAMJwie81A+OU2GwIjn+GOLacsNDe\nt71DzG6ChpsRwnpZCCpAnZJPdazFuIv9VSvHvoj969VxDEEI7NWDL740BzRrIoT3DrqXjfkbhZBf\nqCs+LS5VtG+kYq9KiW+sIsbXIsMYdwHBrsTC9DWMyXPVWhMHLIQnRj/B+kPr3etcCCQL4cFPf/0p\nhUWF3LHyDhyZjg4CfWfzqVIcTEUmwtrDqLy60s236uNP9/yJBW8sELF1IkCpz7spx8TS0YqwYrjD\nVcscWPmjlR1eBuQX5AuBRUcZZAj6wKe//lR7YO4sd53dn5dSlO1ibHv2XTlzZQdxQ+NlgPE/pr0N\nRj17F4x69i4Y9ex96EkvAgyNAAM/WKx8c6V4CeCNePhpRzy0egPXIB66vZVzbYiHTG+oTq+m0qwo\nyGeAHCpDKZTJZeLhyxuK+xWz8bONmq8Nn2wQD3PeCLX2UgQ/fiQu/0fdjxtqGqAUsaNAKeJuVeO7\nGvHgr8SACfESQD0OV+yp7UdBvX+9dr2yrlLEWgrySFm0tbrGyDXKsRpbs+7aSGhvbu80Zo7rjsN1\n/ofp8jkSIZoX7uHPgngxMsxjHKWKHQc0O5SXAIqddR+uo7Ku0t2Wan+k0nekzl6EKw55pCweiL3B\nkelg1bpVbnU6Ww31tdb8ZMGad9Z0rHOWuF6aUsrGzzay8s2VYjcDxe+rf3+1Wz5VO85Mpxizh2/V\nx+tvve6KLVCZP4ovz7w7s5yseWeNuKavZRa8+uareGLDJxsok8u0/uqYPGP1HEdndrrb9nxxMbY9\n+656c9Uli9OAAQMGDBgwYOD7hPEiwMAPFovnLBZCearAmwWX4JteHC8H8EITTQvLCxPCf4pImlQj\nQawQS1PF0zyFpvQiVJoAoBl3sb0k9+OA0ACIVQQEY3EXpNuB+EqvCgA6cQkdql++k3Ttt0FQY5B2\n3Rps1cTrpJ2SaFuJu/hepS42X921nWDxtXQas5ugYZXO/x5dPhURvQ5if+0IMb49HuNQBfbM4Gv2\ndRMhnDV1lkvIb6+Hfb1on2rP5opD2imJFQceAoJdiYXpr+lrrRcanD9jfsc6K0J/sUdiuW3ibSye\ns1gT7/MU6DubT9WOKdckxuzhW/WxaPYiV2ydCFDqc2XKMTF/hiKsqK9lDiyZswRPaAKLSn91TJ6x\nnkto7VKKsl2Mbc++C+csNMTjDBgwYMCAAQO9EoZYoLHM5rLHhQqpDBwwkAxrBnvW7cFSZeHGq26k\nJL8EU56J6xOup7ywHOc3Tq6yXsWyny6jZG8J0aej+fltPyfWP5aUmhTG9h/LuAHjOPzpYbzrvBka\nM5QRjCDBN4GtO7ayZccWtn61lV/+7pdMTJ6IzyEf+pr7wiGQ62RN/G9cwjiSvJPoL/Xn1KeniHJE\n8esHf8214deyaMoi6vfUU1lcibPEiWOvA+mMREBjAG172pDOSOKhvRJ8D/riOO3AKlsJLg+m4VgD\n0n6JOGccDWcaCDsWRpwcx/Vp13P3NXfT+m0rMzJnULyjmMbSRizlFvgG5HIZS60Fr2+9iGiOYOyQ\nscS0x1D2aRmOMw7GZYwjtDmUst1lUIKgOdjETgiBtYE05DRAGVhqLfgc9MGnygefOh/avmkTS9NL\nEHSGcqVvOQQTTMupFigDaZ+Ef7U/bWVteBd7w2nADgOsAwisD6Tmqxr6SH2oslcRJodRf6oe6YzE\nlbVXYio30VLYgk+dD3FVcfT37k/bnjb60Ie//fJvjOo/ij3/s4eA2gD8W/xhD8wZNYdWWvGSvKg/\nWU/AoQCen/c84WHhPPvqs3y86WPqaurI3ZRLy84WHDUOUkNSuS32NsYljuP45uNcl3AdP3/w58QS\ny6HsQzww7gFCTodQe6yW60Ou582n3mRw6mAGDhhIWGMYh7IP8fRdT7No/iJNoOyeMfewZdcWrCFW\noiKjqLBVYD9pZ6Q0kvTgdA5/epjotmiW37OclPoUrK1W/E76keKfQlxdHA9Nfoji8mLmjZ9HVEkU\nWfFZzLpmFtVfVpMels7kxMksn7kcU4WJgMMBvL7wdcZeN5bqwmqk4xJXSFdgPmjmudnPdaoRUGGr\n4NS3p2g61kSfij68suAVRo8aDXQttKbenxVVFfztnb9hDbEyOHXweYmy5Rfks3b9Wi0vZ7veme1z\n9VfhOYbRo0ZfcvG47sbWk9Abxasuxzp8V+iN9fwhw6hn74JRz94HQyzwe4ahEdC78F3wp/IL8hn7\ny7HYUm0ubroJjT+u53Gbc804Eh0k1CXwizG/YMl7S3COcIqvqX4gNUuCcpCDWIqu8q53APWiDb64\n8fmtvlb++uhfufd391JpqoQs8eX3/cXvA3D7ytsF31zlu29DaBionH6VK34YsTpgFOIrezRw7P+z\nd+7hUVXn/v/suWVym0zuCZAEQsI1AYQIiIpyKfVaQFtqRWnPsRUvwNG2aLX9tVY9Xk8rBZ5TwPb0\ngtBqaxEF26KAWCu3gAESgiQkIQlkcpskk+tMMrN/f6y9Z/ZMwh0Fwv4+T57M3ntd3vW+awJ7rff7\nXYiU+xC+vKptQCGBlPxPETvCNyPsdwI2SIlOYYp9Cn87+beAHkC7MpbkkDG2AzMCYzPVmehJ6glw\n+Lcr47+OgL5BEiKb4CAiNT2CYL5/qJ5ABwEqw04EzeIGxX4XkKI82yXaTjcIfjcg4hzWEMSHxwkM\nA4PTIFL6FR0FwqBRagzWMYgP+DC2J5bfLfmdn0cevyueJlOTaONjkMIk5EmyX4NAFQbsi8N+On56\nYnEi9bX1Ii7qnImJp/GaxiC9Au3cVMd7Kk6/Ou/VPkPr9iVaOPPJmThaHf74hLbXFzo6Otj0/iZ+\n8PYPqM6svmDefmjdC31+KXE523Y69DfO6pUah4uF/hbPqx16PPsX9Hj2P+gaATp0XGbYsGWDWATQ\nctM1/HEtj9ub54UawRle9sdlYhFA5WuXEtAdmEiAq67y+mXARi8+f6OrkZVrVwrut8Kr9+X5WLlu\nJcvXLg/wzdW2ogjm9Ktc8cnKM5V3X0ZAiyCEL69qG2AnwMufQrA2gkG055AdbNyxMVgP4ITSh5Zb\nPhnx4q4ZW09XTzCHP16pp9U3GK/YF6fYH8r3D9UT8IZc2zT2GzTPJov6Kr/bH+cQPjwGMQ5fni9I\nR6HR2BjcT2ewD5ssTUE88kZXY6ANu6JDoNEgUOdaX7zz0Psr3ljhv64fWR+IizpnFJ0KrV6Bdm6q\n4z0Vpz+0z9C6ofC3pYlPaHunwva926nOrL4ovP3Quhf6/FLicrbtaoIeBx06dOjQcTVCXwjQoQPB\nDU4sTgzmpmv441oetzHfCKmCM/zYgscw7DUE+NpZBHQH9hDgqqu8fgmxYx3C54+3xbPo/kWC+63w\n6g35BhbNX8SS+5cE+OZqW20Ec/pVrvgu5ZnKu88koEUQwpdXtQ1oJsDL/5RgbQSfaC9FSmH2TbOD\n9QAGKn1oueW7EDvtmrGZrKZgDn+jUk+rb7Bfsc+p2B/K9w/VEzCGXLs09vs0z3aJ+iq/2x/nED48\nPjEOQ74hSEchwZsQ3E94sA9jPbFBPPJ4W3ygjWZFh0CjQaDOtb5456H3F9+32H+dWJwYiIviV1Wn\nQqtXoJ2b6nhPxekP7TO0bij8bWniE9reqTDt2mmkladdFN5+aN0LfX4pcTnbdjVBj4MOHTp06Lga\noWsE6Gk2VzzOlz+lckIPHDjAa79/jYUzF3J803HqD9ZjdVvJisjCWGRkbPxYLOEWHr3tUXK6c5id\nMxtnvpPBYYOpb6rH1GCicUcjco1MqjeVcYnjCDscRrw7nlszb+X20bdzcttJFs5YyDWDryGsJYy2\nijZiymIY4BvApMGTGD1gNDv37cTX6mMgA/Hs8xDvjqfaUc1HOz+iqaQJU6kJc6OZ7v3dUAPmTjOW\negumIhM95T1i57wKaAVpn8QQyxDCasNIt6bTdrwN3+c+YrtiuVa+lpj2GFKNqchHZYbbhxPliiL+\neDy35N7CiQMn6MzvhJOQHJ6MpdVCkpTEoWOH8FZ78R30keZNw+vyYm2y4in1QDVQCOHN4Zg7zfTs\n6hE7/A0QbgknNymXqJYoDAUGPI0efFU+OAhSjSLYdwKxS1+D0DpotjLUOZTO6k6yycbQbMB93E3Y\nkTAiWyPxtfgwnDRAgUjnpwmsh6yMSR5Dq6MVT7kHW5mNUbZRyJUy45LG8ZWpX6G0rJS9H+2ltaCV\nHkcPFEByTzI3597MtfZrGWQYhHRI6BMkhiUyY8QMTh46ycCagXxvxveorajFfdJN2OEwkruTmTFm\nBqOzR9Na1UrE0QgWz12MvdtO5NFIVj62ksGWwRx86yATkiZwfd71/PXvf8UsmbG0WchqyiI9PJ2i\no0V0d3WzY+8OvnPTd8jpzunFT3/pey8xK2cWh/96mDBnGGnhaXz/698nuzWbJFMSQyKHMC1yGvdO\nuhdnvpMh1iHsKdhDcWkxS+YsIbEnkazmLPIG5ZE3Js/Pga5vqKeioIKokiiWzl7K9XHXn5ILn5SY\nxK3jbsXYbCTLmsW0iGn8asmvgmgGfXGsu7u78fZ4+eYN3yTDmdGr/b7qFRUX+bUZ8sbkMX/q/FPy\n9E+lTaB9nmnNpH5HPc/Mf8avaXA54Ey2X44oKi5i9frVmDEzLHvYJec3XgxciXG4mNA5yP0Lejz7\nF/R49j/oGgGXGLpGQP/C+fCn/JxQW6U4g30iSDsl5HpZ8MsncuZqC0QoAAAgAElEQVQz2lV+ewIi\n1f8jRIr6+EBd9ex49T+WGzdv7HWG/AubX8DR7RD1ChA8dB9i9xkEHzsdwZ9XefK7EDQDA8Hc/92a\n60aIjoqmLaxNpKgXILj1PUo7Tk17n4DBIs6bD9IbaELs1KsceTeCp66WqUS8yHcCMfTm9qs8/AII\nqwnDHecO2Kk+r0DoA6j324AZEF0QzdpH1gqevK8ymNOfoNhn1YxBa1MHIksgNtB/dFc0rV2tEIbI\nzJis8XcGSNUScpQciEOb4qubxbW93Y41yYoj24FhjwFfjw+mgGGvAd9QHxwBg0n4ML1C0Y/422OC\nKrBb8dHNYufdG+cN0iNQ9RpOxc9XoZ0/hnwD0a3RtMS2wDiRNeBr8dFobRTzRZnXqSVi3qp6AyoH\nGk6vH3AuOB3H+nTfz77qXUy7zmSbjnOD1pcpR1N47+n3yLsm71KbpeMCoXOQ+xf0ePYv6PHsf9A1\nAnTouMTwc0LVM9gtIF8nQ3fguq8z2leuXRk4o13lt6t8/zgCXPtJBJ0dr6KvM+QdsiNQbxyCQ+9F\ncLFVPrbKn9dy3yvozf3XXndCa1ern6fOOKU9O+IlUdueLXDefJDegJFgjnxcSD+qnoKR3tx+LQ9/\nHLg73MF2qvoJnhD7veJz67jWAP8+lNNfpvg+LqRP1aYo5bmm/9aIVlG+Qhmb1t9limaCNg42gnj5\nze3N/tj7Jvr8Wgy+axX9hqiAD/36EXkanyptefO8vfQIVL2GM/GTtfPHl+ejxdniH3/9yHqhMaHO\nF2Ueq/M2lAN9Jv2Ac8H5cqz7qncx7boQ23T0htaXjmEONm3bdKlN0qFDhw4dOnScJ/SFAB1XJfyc\nUPUMdo/ICMAcuO7rjPZF9y8KnNGu8ttVvr+TANd+N0Fnx6vo6wz5FCklUK8AwaE3InakVT62yp/X\nct8H05v7r70Oh2hrtJ+n7t/lbgayQtpzBc6bD9Ib8BLMkXeG9KPqKXjpze3X8vALICwiLNhOVT/B\nEmK/UXyOLogO8O+HKvZotRd8IWPQ2tSmPNf0H90RLcoP1rSl+jtT0UzQxsFFEC/fHmn3x96wx+DX\nYjDsVfQb2gI+9OtH5Gt8qrRlzDf20iNQ9RrOxE/Wzh9DvoGYuBj/+BOLE4XGhDpflHmszttQDvSZ\n9APOBefLse6r3sW060Js09EbWl+mHE3hjul3XGqTdOjQoUOHDh3nCZ0aoFMDrnicb9pUUXER73z4\nDjaLjXd3vMui+YvYtW8Xy/5vGSaLiXHDx5GRnoEsyyTEJ/DgvQ8GnUne4GwAGVpaWig5XoLslRmW\nOQy73d6rjhYbN29k5bqVLJq/yH+c3Op1qyk7XkZjcyP33nEvuw7uorC4kLTUNFxtLo5WHGVYxjA6\nOjs4XHaYcFM4CYkJJMUl0drZirvdTbmjHJ/bR1hkGLGRsdw45UaeXvQ0pWWlvLTqJeJt8WQOyWTG\ndTPYtmsbpcdKqa6tJm1AGpkZ4n5hWSHvvfsee47sIdWWyrhx46h2VGM2mimvLsdispCcnEzeyDz+\nufOfDBkwBFuUjaNlR3F3u+nu6cbT48HX6aOpswlJloi2RXNj3o28/JOX2fbxNn6+4ue0NLUgG2TS\nk9MxWUycrDlJR08Hdosdj+RhWMYw1vzPGvKuyQuK0/pN6zFLZmqdtXR2dgLQ4+3B3eNm1JBRZKRn\ncOToEY5WHmXeV+fR6e2k8PNCcobnBPmi9kQtlY2VJNmTeOqRp3B5XORk5rB151acTU6am5tpdDVy\n87U389Hej8hMz+TpRU8D8M6H7/jLSpLE9MnT2bZrG7Is+304Z+YcRo8czcbNG3lp9UtkDspk3u3z\nKCwrJCczx//7VPVOB+38ycrMYvW61UiSxIP3PgjA6nWrcTY5+5y373z4TlAf6txT619Iynxf7cOZ\nv59ftF2ns03HuaOouIi/vP8XRmWM4o7b7rjkaY06Lhx66nH/gh7P/gU9nv0PlxM1QF8I0BcCrnic\n7x/JjZs3snztcpbcvwSA//r5f1FbV8uQgUMwWU3ERMRQ21SL1WLle9/8HiVVJew/sJ8KRwX333k/\nbe42ysrLqKqrIic7hx8v+XHQS8bGzRv5f7/4f7jaXJgMJiZNmMS82+bx4acfIkkS2WnZvLP9HeZM\nm0NLVwu5WbkcKj3E3Flz/S9uG7ZsIDcrl7c2v8WhI4ew2+w0u5qxR9tpcjUxZtQY0pPT+b+//R9h\nxjDSB6RT21CLwWRg6KChxMbFIvtkWlwtVNVUkT4gnSEZQ5g5ZaZo8/NDtDpbqWqqIsYSQ0pyChU1\nFYwfNZ55t8/j9TdfBwkmjp7I37b+DXenm4GpA5k6YSrv7XiPmKgY7v7q3Wzfu514Wzz2GLEI8nnp\n5xQUFSBLMrYIGxFREXi7vdww/ga2528HCaZNmMbu4t0MSRmCZJDYW7CXru4u8EJcZBwt3S2YTWby\ncvOIscVwsOggLZ0tGH1GOj2d5I3JY9XLq3jjL2+wYu0KrGYrsTGxpCal4mh0EGYO4/kfPs/s22ez\nYvUKXvvDazz+7cdZvHCxP0ZPPfsUK9auIC46jqULl1JSVSIWSOqqSUtOw263i4ISyD7xYt1X3NSY\nzrhuBlt3bqX0WCnONifz75hPS1dLr5iq16HzcPbts/22FRUXseqNVf52tXNDWya0PbXe1h1bKT1R\nyp033ok12krp8VKefvjpXn2cqr6zyUl8XDwL5y/s9YIuyzIP3fcQQK/6p/p+lh4vZc1ba/zj7Kvv\nC8WZ2vwi+rzY+DJsvNA+9P+Y9i/o8exf0OPZv6DHs/9BXwi4xNAXAvoXzuePpFZ0jY8QonOTEanh\nLoTYWh3BgnJWArzz3QhRugwEF3sPxPvi2bFyh38neM4Lc4LF/ZJAqpeQvTKMwC/mporfGZ1GvHle\n0ivSWX7vciHuZqsUIoEWpX9VyK4RwVHXCgSWIrjhKQQLCO4C2hHCeWr9OtGnVtiQEoRAYY/igxYg\nTVMmEWhQbN6FSL0foelHTafvUGwNEU7025dBsLjfQUSKvF3jj0aE+KDWT6FigB4wNhjxDvIG4uQQ\nfvb32wIPXPcAvy3+rb/t5V9fzuKFi3nq2ad46eOXAgKETqWfEmWslRq/Dw6xQ+MLv3DgCDAcMwjN\nAK1PEyHdoImpRrSutKw0SDzy7SVv+1+S/YJ56WAoE8KCWrG70wrtNTqC594wMR7JJbHhRxv8fZyy\nfqvDL/yoivUBzPzZTL9QZnxXPOZ4M45sx2lF+Do6Ovj167/mifefwJfn84tk/s/H/3NRBfzOJAp4\nJYgGfhk2Xow+9P+Y9i/o8exf0OPZv6DHs//hcloI0DUCdFyV0IquEUdAPG68cn2M3oJyFQSL2nUR\nEBacCI2uRr8Q2fK1y3uL+5UhhPuiCBJzY6LoT7WncnBlQNxNFQmMIljIzktvgcCJiJf4UAHByUp5\nbX3oJWzoF/hTfdATUuaYxubJBMahEeTDTkDEL7R91b5Qcb84xR6tP4z09lOoGGAceLu8wXEyhPQL\nrNu8LqjtZWuXAbDqzVXBAoSGED9o/R5qh8YXfuHAGkU4MNSnZSKmK95Y0Uu0LlQ8cuW6lQDBgnk1\nAWFBrdjdaYX2Quee4jfZLgf1ccr6GuFHVaxvw5YNQUKZja5G//WZRPje/Oeb/jGoIpkXW8DvTKKA\nV4Jo4Jdh45XgBx06dOjQoUPHFw99IUDHVQmt6BpOhBCeB5ER4CRYnE7dgR9MsKidlYCw4B6It8X7\nhciW3L+kt7hfJkK4r40gMTf2iP5Ue9Ir0gPibqpIYBvBQnZGegsE7gFM9BYQ3KWU19aHXsKGfoE/\n1QemkDJDNTbvIjAOjSAfzQRE/ELbV+0LFfdzKvZo/eGlt59CxQCdYLQag+PkC+kXmH/7/KC2H7v/\nMQAe+uZDAdv3KHW1ftD6PdQOjS/8woGpinBgqE8zRUwX37e4l2hdqHjkovmLAIIF81IDwoJasbvT\nCu2Fzj3Fb1KzFNTHKetrhB9Vsb65s+YGCWXG2+L912cS4fvmV7/pH4MqknmxBfzOJAp4JYgGfhk2\nXgl+0KFDhw4dOnR88TA+88wzz1xqI86E0tJSbr75ZmbPnk10dDQHDhzg4Ycf5uWXX+aTTz7h2muv\nJSYm5qzb6+7upqGhAbvdfslTMnRcONR4JiYmYjabz6rOiGEj6Czv5MCbBxgaORRTs4muXV34yn3i\nJagcojqi4AAMlAfy3H8+R7Y9G3OjGc8+D4PkQfh6fIQ3h2M+bMbeacfkNvH7P/8eq9HKhHETqDhY\nwcmCk/j2+zDWG7HUWvja6K9h89lIrk3GXeNmUM0gsi3Z1HxWQ4aUwYJhC7gj9w7+sPEP3DLyFmo/\nrUVulhllGwV10LGzA7lKxuqxYqo14T3oJbYjFvdBN9QiKAD1QCFYW62EFYdhbjJj89oId4UzuHYw\n1mYrM0fNxFnqJOF4ArHtsbQeaCWsIYx0QzpNxU3QCgmGBLy1Xrw7vaLNMtF2ak0qk5InUVlUibXC\nylDLUNz5brzVXqytVnpaepCckkjT3w/UgrXairfaK6gDdYiTFmqBYjC3m/HV+0Sq/T5EvTal3BGw\nd9rx7vfiO+GDo0AV4ARzq5mslCxcx11493ox1BowdBiIaomCg5DgSWD29bN54tEnsLXZyF+bT0R7\nBCMyR7Bxy0a6fd3k2nI5suEIES0RPD7vcWJOxlB1oArfcR8jbCOYNWYWaVIa4ZXhTEiawERpIoMM\ng0hoT+C+6+7DetTKf93+X8R6Y4msjmRW9iyOv38cQ52BIV1D+Nm3fkacKw5PrYcbr72RW3NvpX5H\nPbeMuIXf/PU3TBo7iQxTBgfeOkBech4L5i2gvqGeDVs28MCsBzDUGYisjmTp7KVkt2YzLGYYeWPy\n/GW+c9N3yOnO4bnvPMfokaNJSkwi25ZNeVE5YXVhtO9uZ3bObMZbxxPpimTlYyvJyszi+V89T/7B\nfO4ccyfd+7v52X0/48YpN1LfUE9nXSdZUVnkxuYyLWIav1ryK0aPHC2enewkqzmLm4fczMofrWTB\ntAUMqBvg7z8URcVFrF6/muz0bO6+9m6aP23mF9/7BQu+tYBZo2adtq5af836NTQ1NvHXv/+V+Jh4\nkhKT+ixTc6KG8kPl3GS5iVVLV/VqMykx6ZR9qm301f4XgVP1dzobLxbUPkyFJv98OpcxqzE1Y2ZY\n9rCz/pur4/LF+fwbquPyhR7P/gU9nv0PnZ2dNDc3XxYxvew1ArxeL/fccw+FhYVs3bqVhIQEZsyY\nwVNPPcWsWbNYvXo127Zt4+233z7rNnWNgP6F89UImPvSXGSDHEiD/phAKrWGjx7Kq75p0U00GhoD\nfPYqBJdew2+Pjo2mdXKr0B8wIPjyKl+7A4hEpI2/CyTj5/qbHWa8qV6Rbr4dwdOepKk3GPFSPgnR\ndhTiKL2jBHjyjUq96+hbTyAx0EYoX9u60UpXSlegbDtCN+A6ZWxZIH0uIbfKgoufTrBGQAfQqenv\nE8SRjJOArcq4Jyvj6QFu6MPvbcAMAhkGcYgdbpXzvhMYDhwBJMW23Ygsgj40BVIbU3GVumiPaw+M\nywV8RRy5Z+wx4sh1EL8rnsauxiBu/Y9u+hHrP19P5eBKUktSkbtkHLmOoM8ph1LAikiTV7UTpohM\ngSdufIJX//0q3jwv0scS8YnxNIxs8PuSfJDsEvJEGQogtieWsLCwXn2cqr9QjvfZ8OT9PP/9ILVJ\nyFPlYF2KPuqeD69cWyflaArvPf0eedfknbbOqeob8414M72ku05hl6/Sr9mg1Vo4136+DO2Ay0Gr\n4HxtuNCY6rg8oXOQ+xf0ePYv6PHsf9A1As4Bq1evJi8v8B+NXbt2Ybfbue222zCZTDz88MNUVVVx\n7NixS2iljisNy9cuR7bLgRd0C+IFUOWba/joobzqRldjMJ/dTS9+e2tEa0B/wE4wX/skAW56N0Fc\n/+6ObrEIYEHoEmh5/gkIbrp6Lw7IU+zU8uS9iJfjU+kJlAWuQ/naXa6u4LInNW1NFH3J1ylrhwp/\nPUgjICqkP5vmc6LGzsnKs778nqhpLw7xYq/lvF+n9BulsW0Sp9QUqMmuob2pPXhcsvhcP7JecOIt\ngvMeyq1f/dZqv29qsmv8ZbWfHbIjwJ1XtRMU7YDVb632awDIdlksAmh8CYhFAGW8TZamPvs4VX+h\nHO+z4cn7bR0vbFLL9qVhcLbt9gVtHccwB5u2bTpjnVPV9+Z5oeY0dmk0G7RaC+faz5fBmb8cOPrn\na8OFxlSHDh06dOjQcfngsl4IOHLkCH//+995/PHHURMXysrKyMzM9JcxGAykpaVRXl5+qczUcQVi\nyf1LkJolsTOscqmbCfDNNXz0UF51vC0+mM8eRi9+e3RHdEB/oJlgvvYAAtx0M0Fcf3OEWXDOPYid\nfC3PvwHBTVfvOREp9qkE8+SNBDQP+tITyAxch/K1rTZrcNkBmrb2iL6knZJwYkEffbeF9OfSfK7X\nlN2lPOvL7/Wa9pyInXMt532n0m+bxjY1k6APTYHUklQiYyODxyWJz4nFiYIT7xGc91Bu/cJ5C/2+\nSS1J9ZfVfk6RUgLceVU7QdEOWDhvoV8DQGqWSCxODPIlgLRH8o831hPbZx+n6i+U4302PHm/rfuF\nTWrZvjQMzrbdvqCtk3I0hTum33HGOqeqb8w3Qupp7NJoNmi1Fs61ny+DM385cPTP14YLjakOHTp0\n6NCh4/LBZasR0N3dzcMPP8zPf/5zBg4cyMqVK/n2t79NYWEh7e3tzJw501/2vffeY/jw4QwfPvys\n29Y1AvoPzlcjIK47jkM7D5HQmYDrExdSs0R0SzTufW6oButxK6ZGE5PTJ7Ng3gJ27tnJ0heXEumJ\npLWsFUORgWxLNiafCfcJN5FHIjE5Tfzgnh8wZ9IcDv3lEAMMA/A1+bA2WpEOSmSHZ5NqTSWyJZK2\nXW0kWhKZnDKZE1tPMMw6jAnDJ9BwpAHPfg8ZlgyiO6PhACSTjN1jp7W4FfmEjKnYhKXFQs/JHqwV\nVnocPYKPX4V4wT4BxmIjYY1hGFwGpAaJtLo0vn7N16kvqCcrMovEykSmD5vOoJRBFO0uwrfXR6er\nE8khIe+TkZwSti4b7mq3aLsezGVmlt61lHlT53FoxyEGOgfia/BBPvRU98AJBD2gCixHLfjqfES0\nRRBTGoOnzoOv2geHgGrEAsBu5XcNcEDYLXVKmA+Y8Z30YWm3YHaY8TX5kKtk+AzCXeFEnogk1hOL\n2Wmma3cX1IHUJGE8aiSmPQbjISOWZgspjSlkRmXidDjprOok6lgU9193Pz0tPdhKbUzNmsqT33qS\nnO4cXl70Mja3jd1bdmM8YOT6jOt5+r+eZv7U+QyoG8ALD7zAgq8sCPpsPGRkdPJoZo+bTdO/mkjq\nSaK9up3Io5EsuX0J7Z52zE4zbf9qIy0yjaV3LeX68OuZkzuH7s+7+eWSXzJl0BQOvXWIsTFjmTV+\nFnPy5uD5zMOzC57ljrw7aPiogWcXPMtj8x6jYmMFJ0pOMNAwkKhjUUR1RjFu5DhGDBsBCP53pjWT\n8s3lDLEO4e1Nb/PUy0/x0Scf4Wxw8trvX+P20bfT81kPUzOm8tx/PufXGHA2Ofl0y6ckn0zm1Qdf\nJS42zs9jHz1ytL/dcUnjuHHSjX3yyouKi3hu2XP8Y/s/yBuTx6RBkzj27jGGhA9h+g3TaWpuOmsu\nvpYvPztnNp4jHp6Z/ww3TrnR35eqk5DYnkiCJ4H46nhWPLrirGkBof08953nAL5QvYCLoQNwrpoG\noeXrG+pprWxlsmEyv3z0l2dtg2p7YnUiC65fwPXXXX/J+Y06Lhw6B7l/QY9n/4Iez/4HXSPgLPDa\na6/h8Xh48sknARgxYgRbt27lgw8+oKCggGXLlvnL3n333TzyyCPMmDHjrNpW+TapqanY7fYvxH4d\nXx46OzupqKhg8ODBhIeHn7KcxwP//KeR6GiZqpMVPPzwQGTbEYh6HbJ+D8O64XNEuvmniHwZhXcf\n1RVFm6cNchA7j3GInWq1vIbPHt8TT1NPk0jx/wjB189CpLhnAQcJ0AX2Ay549Z5Xeen9l2h0NAYo\nAbsRZ9mnE8zvV7jQFBA4fm8SsE3pS6txUIrg+U9TxuQJ9G3YY8CX4AtoDqjtSZrxlWj6VjQTaIa4\nsDicyc6ALSHaA+wGioFRynN1x3+qxrdJCEFAVdugEkhRyn+ESLHPU+oOQ+ggDFNsagcpSuHWf4Sg\nGYwnwL0v6cOebOH7SFsk7ePb/ZoGyVHJbHp2E8fKj3Hvr+8VcVPaSWkQPOhRw0f1mk+HPz/M3Ffm\nUp1ZLXzZ6hOxG4fI1GgDbkZoIyiaCYa9BtY/tJ47b7kzuA17NYYyA748H4Z8A75MHykNKchdMrVj\nakkrT2Ne5jx+sesXYhxaXQYX/PnxP3PnLXdy+PPD3PHTO6jtqRVx1vrXidCYUGKWVp7G35b+jVHD\nR/HeP97jntfu8VNl7IfshMlh/r5f/fqrPPanx3AMc0ABJBuEz7R+8fftq4VxkHA4AV+LD2e4E8ZB\n3L44LNEWHMMcQX2fCVo/q/UA/73kg8lIVumc2z3bvs63rS8K52pjaPlXv/4qP/zLDy9ojGf7N1fH\nlQE9nv0Lejz7F/R49j80NzdTU1NzWWgEXLYLAbfeeisNDQ1IkkhDdrlcREVF8fOf/5w1a9awceNG\nAHw+H5MmTeLNN98MogycDupCgI6rCw0NJm65ZewX20nS4zBxGYxB8LDzEZ+LgNHKby+B5x7gIAys\nGciJ1BPiBe9uzbM3gPs01x8CMzXXW4BZIX2pz9Q+DyJeqPMVG8ecoT2UNtX6fbXnQCwYfOU0bf0e\n+E7wOP12jAE+CKn/tmbspxqL+lvrl1OVDW3/FL4HeGT0I+w9uJe91+zt1c4j3kf4z2/8J6H4zVu/\nYZVpVd+x0I53U/D9iQUT+d9n/ze4jdP5Ok/ci347mta7W3uXPQgTfaLN37z1G1YdXtW3fw8iFgY0\nMVLH9vD/e5i9xr29faP0fW3Btewdtzfo2SOjg/0S1PdZzM9T+fVMfn7E+wg+2Re4d57tnm1f59vW\nF4VztTG0fGgsL8cx6tChQ4cOHf0d+kLAOWDEiBFs376duLg4ZsyYwdKlS7nttttYvXo127dvP69T\nA/SMgP6Bs10tPXpU4pprrqDV1JutcMJ95oyAWMSu76XICNDuuF+FGQF3vXoXVUOqLigj4K5X76Iq\npursMgJ2/iLgg6soI0D1szYjQL13sTMCQvu6HDMCzsXG0PKvfv1Vlv516QWNUd+h6l/Q49m/oMez\nf0GPZ/+DnhFwHhg5ciRbt25lwIABHD58mJ/+9KeUl5czcuRIXnzxRdLS0s66Lf34wP6Fsz1apbsb\nTp4Elwt27oSFC79EIy8hwpPuxR32JhbJQmxULPWt9aSnphMZGUnuyFwmj5nMyrUrKT9eTrenWywE\nSCBJEiaDie7ubswmM5gAL4RHhmMLt1HXUkd6XDrH6o4htyvK9z0IsUAD4sXfoFxLYDKa6OnpAR8Y\nTAZ8sk+cuBAG+CAyIhKv14vP6CMmLIb65npR3wuWMAsetwckiLJFMW74OGw2G5/mf0qzq5lwSzhm\nq5kISwRhEWF0tXXR2dNJrC2WBHsCBw8fpNvTjRQmMXHkRE40n2BI6hDSBqVRdaKKshNlPPm9J0kf\nlM5Lq14izhaH3W4nPjaeGdfN4FDpIebOmht0bN2GLRuIscbw7vZ3yRuVx1//8VfqnHXERMSQOzIX\nu91OVXUVRSVFSEiYwkz8x9z/IDImktysXD789EOczU5kn0xiQiLTJ0+nsKyQnMwcCssK/QJuTzz3\nBAdKDvDkd5/kZO1JVqxdQXR4NHH2OKpqq3h0/qO8+NMXKSouYtUbq3A2O2luaqa6rprWplYq6yuJ\njYrFFmWj0lFJ1sAsJoyfQKw9lplTZrJ151ZkWWZY+jB+89ZvALjtptvYtmcb2RnZPLXoKUaPHO3n\nmTc4G5B9MgnxCSycv9D/bMOWDeRm5bJ151Yamxr9vvvnx/+krKKMGHsMRoORxIREHrz3wXPixhcV\nF/HOh+8wZ+Ycf3+r160GYOF88UXWPr8QhPZ1uUE79r7m5qnqhPrvQsZ4pR5npc7TM/nrasOVGk8d\nfUOPZ/+CHs/+h8vp+MArZiHgYkJfCOhfOJ8/khs3b+Su5Xfhy1N2f08AAwnw3X1gNBvx5nn952wD\n3PTkrTSW/zcU3v8FjeYyRlgRjB8LYV6ReZBO8M60EwhHvLxPQuzUGwgc0bgfQSlIQPg5H2hFZCsU\nAHVgsBsC2gpqRoCqv5CO2OHXcuR3B64fGPUAmx2bxfF4nyqLDRN9SLsl5GoZBhGUvWBoMGBtt9IR\n2yHs2wXL5y1n8cLFpz3DHgh+FucV2Qyq7sNOxALHzaJNeoAbCLLJsMeAr8cHU4RfUswpfPjyh71e\nTlasXsGSvy7xZ0nYYm24xroCPhkDxjIjr931Gi9sfgGH1wHp+LML2IXICIlFZEyo9dqAUcIHvok+\nKIAEOQGTyYQj0uHPGjDmG3l7ydt+8b2i4iJmPjlT9DNOnGbw62//miXrl/jPpF9+7/Kg61fufoVF\naxfRMKoBCiDF2PdYzxba2KjfzavlpU479tSSVOQuGUeu40v3w5X4H9Ored6cCVdiPHWcGno8+xf0\nePY/XE4LAaZL2rsOHZcIy9cuFy9K6pnufyL4/Pk/gfdb3qBztmWfTGNuFUxYAIMX9OZTOxCp7aF8\n9b546Q4gdjF8sPzLHPaFwT0advb0vr+1j7Kh994Puc64DvJ2CV9YEC/QWxAvpRYENWGM5tlBoAzB\nby9CxEiNlXK97s/r6LqnS9yPAt8Y0ZY8SRZ1tXU+BN9MHx1blEUACzAZlq1dxuKFi3ufYV8ElaMD\n8yDo2YcImoNq73UExjVZ81ljk2+iL3B/PDgOOnjnw3d6vbsGuv0AACAASURBVJi89ofXxEKJ4hPX\nGFewT2qEDcv+uAxHnHg5p4jA3J4s/Mr4EF82AsfA9xWf/37DwQaQxX1VW8Cb52XlupX+hYANWzbg\nkB1+n9Vk17DijRVUZgbOpF+5diWVQwPXq/+0WiwCKP2caqxnC21s1O/m1fJCpx17TXaNfw5dbX44\nH1zN80aHDh06dOjoC4ZLbYAOHZcCS+5fgiHfEDjT3Urw+fOD8Z//rp6zPXfW3MA58G0EzqVXeNqg\n3FfOoTfkGyBVnPvur1cACd4EcWa9eQXWpRIZNxiYcJfELeMkFkyS+OFQiVfGSvwuVWLzUIn9NhMV\nYRIdJgmZ3j+HrclfrvMuBn67E16QYZMMz8jic77y+xnl/guaZ5tk2KN83qh59uutkGyA3TD/9vmk\nlqT642PYI+Ir7ZbES6gar91ApngeYY7wx4td8Nj9jwGnP8O+17NMRDaE2s5O5VppExe9bDLsMYi5\n4kFkBEgpfZ7l/vi3Hw/MSyfYDtgCc84JpAobHlvwGClSirifSmBu70JQM/YTXC8MGBqwR52XKVIK\nDMXfpzHfyKL5i/z2zJ01N9CPR2QELL5vcdCZ9IvuXxR0vfBbC0k4nODv51RjPVto/a/G5GqBduyp\nJakiFlehH84HV/O80aFDhw4dOvqCTg3QqQFXPM43bWrj5o28tPolMgdlMu/2eaxZv4aDRw9y3533\nERUbFcTV1nLDX1z5Iv/a/S/aOtrIGZbDoIGD/Hzo7Z9sobumhnSLlRvTh1NXUsSkAZmYGhsp3fsp\nUe2dDI2wYXI24qutxerp7mWXOzwcl9VCU5iZrhgbg8aMp94g8aedH3K8q4OErFEUdtRzw8w57K4+\nxp7D+8nLySN3eC5r3lxDR1sHRrORhLgEcrJzkGWZ0qpSZK+MUTZysvkkM6+diavHxaJ7H2X2xCl8\n9Ke1bPztCjaX/paSzrM7hrO/YeGj77Jq5df81yqP+lTzQPssJzOHt95/i8KjheRk5zDv9nkUlhVi\ns9hYv2k98fZ4MjMymXHdDH/5rTu34mxyEhcb5+fa94UVq1ewbO0yHrv/MaZPnc6a9WuQZZnstGze\n3fEui+YvYvbts/3ccUmS/HoD/v5t8bS2t/J5xedMGDWBB+c/6Ldj265tyLIcxLW3WWxBbWuh7Ufl\n+p+Ogz4kYwib3t/ER/s+wmQ0nXasZ4vLncf/RUI7drh42gjngis1VfVqnjenw5UaTx19Q49n/4Ie\nz/6Hy4kaoC8E6AsBVzzO9Y9kUXERTzz/BAc+P8CT33uS6VOns3rdakqPlbK/cD/ONicGr4Hk5GQy\nBmTQUHOCFFnmxkFZPHDzbXy25X2O7PmYsXEDoKEOW5ebNGMYybKEpa2tV3+dRgO+hASawyzYhmQS\nnTkUkpJwyD4+OFLAUVcz++qqKO9oozvGzqQpU5k8djLvbH+HOdPmsLNgJ2XVZcy/Yz4lVSW89/57\nVNRU+MX1erw9mCQTXoOX8dnjKa8rJyYqhru/ejebd2ymxdWC3CPT7evG5XJhMptIiEngpPMkFsmC\nKczEyMyRjB873i8+FmONYd2mdaRaY7jOFsvMmBScOz8mtd7JEFcHEfX1APgkiY7UVA4ZvOxobeSQ\nWeZomIVDvsG4aw5f7FBfMZg2byZzp8+mpKoEWZZ56L6HghYRVq9bTUNjA5JBIs4ex7D0Yf54t3S1\n+EX3+qq76o1VSJJ0yhfqUNHAqtoqcofn8vTip/0v6f+9/L8pqy7jqYeeIiszy9/mjOtm8OGnH/bZ\n/vkKrWm/n+XHy/1tAH1+Vm0MHWdo/2ey50KF4XRhuVND/4/pxcWlnmt6PPsX9Hj2L+jx7H/QFwIu\nMfSFgP6Fc/kjWVRcxA2P3UCzqRlLDqT+C4a2h2NP6ST1EAywwAAbpJ6AAV5IbYeEEFq8R4K6KKiX\noc4MdQOhzgV1HqhPgLqR4DoURmWcm/op0PEZcBKYS5Dw4MyfzcQR7wgW3GtGiLslKPd2AV0I/nmp\ncv84QvxNFeDrQqRdpxMsWqcK6VUg0tNvRojwoZTRiv2pAnpOA744X+CIQvVYwGoCon8fQbQVRqVB\nTj6MdkKOD0Y3wQCPEhMjHIyA/VbYnwKf5UFhBXiGI445TNOMrx2YoYy/CaGfkIn/uD+ObYDaqzSN\nd8IdpAzYx4cvfwjQS6jvg59/0OtlXVvGf5xipRAD/M2jv+GBXz5Ao6FRxPdjsEfYaTY1i/IfI0Qa\nxwe3fyFCa+r3UzbI3P0/d/cSuks5lAJWcGQ7/GKDD61+6JwECUPtuVBhOF1Y7vTQ/2N68XA5zDU9\nnv0Lejz7F/R49j9cTgsBuligjv6P/fth40Y4cQLrv3fw8YlmUnsgwS9g1wkHwS3BSRvUeOFkInzU\nBCdToSYLTtrhpBVq/gnO+xAca1X4L0/5/DbwNQQf/aBbvHhrxAdDhQcd2Y5g4TutkJt6TxWbq0G8\nuH0AJBMQphuvPAchiKcVrVOF9NQyqggfSplQ0T1FQI8P8IvFqfeD2o2D1jGw2wK7Bypt1wIPQGwP\njK2Ga/4F18TATaWwsAGMh8BjgML9sN8L+4bA/jo4NAE6i0PGf0Jjexxw81zxPJ/eQoyjNf2rflHv\nq+X+BtwF5KfClpNnnC6XFfZtwrEPct5Tb9SIX++LTzl/Ca0wOqgMIOIXUUvDtBRWrl1Jo6sRZiH8\nY4dmmgN+teP/XJNd4xdUuxhCa+9ufbdPoTuH7BCLPkrbK95Y0UuQMFSAMFSgMNSeC7VXF5bT8WVB\nn2s6dOjQoeNSQV8I0NH/sX49/OlPMGgQiWmD+XN7FeXhbk4Og5oqaDFEUDK2g6a9CNV/dYf8GsRO\nfgfi5WgPhMWGwR53YDfbR0CALgyxQz8eIqIj6NjdEWjLSkCk6j6xu/2/P/tfalJrxHNtRoBVaXsy\nwRkBuxFCbseVsqEZAZmIjAD1mZoRsJ+AYJ1T8UkBIiNA7VsV0Ms34BuqHKk4MXCfak27TsRLeZ6m\n7aGibNMk+KgWProesbNvhfB4GJsM1+yGCRJMKIdvbwGzLA5UKLHCwVI44IODEhyQoWoXMAzxsqj2\n26jpV32u+myoZuzpBOzfhdgR3wNk1cAMSfikNPD8roF3sbF2ozgBQN1Br1DGNQYMxwz4rhVH7NEI\nhmgDPveP4V/PnnrOXW7oSIbNMh+q1/khzzf1/fknwE+W+D8BkHLrV5nzi3PP0PjajK/xh//5QyAj\nQJJxeBykSClIJRI12TWkV6Sz+L7FFK0uwlEQyAhY9O1FHF1/1L9ruvi+xZSsL/Ffq98pFXNnzeX1\n518/5fMz4ULr69BxttDnmg4dOnTouFTQqQE6NeCKx/loBDz5/JPkF+aTnZGNLcrG7s9209jcCD6Q\njBJyj0x4dDgRYRG4Wlx4DV5io2IZkTWCgkMFtHe3YzVaiY2Nxe11M3nsZG6ZegvrNq1jaPpQnl70\nNK/9+jX++O4fiYuO445pd7B933bmfXUebe42Cg4WcLTyKGlJaZSUl+DqcIEPTCYT1024jusnXM/v\n3v4dFpOFBHsC9a567rvzPjq6O/jd2t/R2tkaPCgvYAWzbKbb2w1GiA6LprVDKScjFi0MIEkSkVGR\ntLvbkTtlDBEGosOiSUpMIjkhmdrGWlwuF109XVhNVvBBj6GHaHM0zg4n35j1Df699998Xv05seGx\nPPODZ3hl1StUV1aLXWU3YlHEDZiVvg1gNpqRwiS627oxd8vkGmCsB8Z6YUyP+IlT/ho1S1BmEu/j\nFWaoMEKrPZZjJi8nwsxUtbvo9nQjSRKyVwYD2MJtYIJuXzcGn4GEhATSB6RTUVWB0+XEKBmJtkZT\n01yDz+0DIwxMHMg/3/wn2z7exiu/eYWMlAwGpw/m8JHDHK08yvCM4QzPHo7BYOB41XEOHzss/CjB\nqKxR2KJtlB4vRZZloqxR1LvqGT5wOHuL9zIwcSDtXe00tzQTY4thzMgx+Lw+SipLkJDIHpxNmGko\n76xdhixffQe4TP/qJrAvY8n9i8nKzOolNngugoShO6iqxoDBYPDXP1fownKnRujf3IvBcb/UPPlL\niUs91/TU4/4FPZ79C3o8+x8uJ2qAvhCgLwRc8TifP5JFxUWCo5/tECnUEQS49Z8iXvZuQBwF50ak\n+e9GZF0nKeXHgbRLYsP3N5CVmRXE8wzlOft3548qbQxA7MR/itipV9tvAMwQbYum1doq6iq73+mu\ndL4S/xV+u++34oXbgtgdV3fFvcAQoA6RTVCA2JVPQOzqa3bBGQZ8huCDT0LshDsQGRFZmrK7gU5E\nRoKqJ7AViFT62A0UA4OVtvII7KofAKI1NjYBY5V+jQjNgfHKsw7h50EtMMYIOQkw5AgMdoumBzeD\n1ReIX5MVjhvBYYGGAdDYDg1uaLBBwyhoLBM6BZ3XQOdh6BwKXWXgbVPil6vY54YIdzjhyeE0DnPC\nIYisjaA9rkPYtg+Ih7iGWJoMTcjjEVkQtcAgkHOh5xB4W6EnDLwjwHeIgIbDLqU/reaCkpEQ74tn\nx8odANy06CYauxr9czCxOJHXH3i9Fy/+odUP4Wh1CF9GKnMgApEF8cGTcOwlrjZMmwZ//jMkJYnr\ny4Fz3d8RKgB5of7WY3Zpob9o9C/o8exf0OPZ/3A5LQTo1AAdVyU2bNkgFgEsiBfdQQR40lMIcOqv\n03yehNABiAqUlSfLrFy3kpsm3RTE81y5dmUQz9nPeZ8MrCfAzZ/SR/tmaI1oDdgzWdStHF3Juj+v\ng1HKINTnKrfeARwjwO8fB2xBvIgXIV5ENe3h1dgxUel7YkjZSQQ0CtSyiQTrEBQjuPxjNG0VAfF9\n2Fij9JvYx7MoqHZC9Rx434J40VXKSG5I2guDS2DwOBjcBhmlkGSFtDa4ph0SmiHeAabPNYHer/ze\nGTIBPtRedIqfzep1h/i1Q1umqfe9I6HtIMT2gG4DeP8JPQbw+qDHAj07oUcC907oCgd3RyMxt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axg4fyys/eQWAVW+swtnk5LMDn3Hs5DHuuPEOBqQNQJIkOlwdvL31be6ecTeDhw7297fqjVU4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r7/aR3ITxlLpb+udheDBg5C8ko4m53Mu24exRXFKnwP0M2R9R+sZ+WalSydv1QF6nUHG1v/\nwXqeeekZ0vun89jSx7rMMQUQqJ2X/rC9symrQAYlSVLvH6WOtAFpuvvzXMBo3wae932WPx86U5vd\n/U3o7vv5bPtsZfzDtHepJ+XzYoMTe4N6Uj4NfXcZ+ex9Ml4EXGQZLwJ6l77tH8lVq1exdO3SLkvs\nYztjMdlNOLLEcmpaETT7/ujAckklSfz1jr+y6J+LxF7te8HUbEKaKJFansqDEx/k16/9GilSglQw\nHzbjvdxLankqH/7uQwBm/H4GFQMrSC1PZeWtK1n6xlIqBlZg2m5CCpdEW8py9E8RS/0H41tOnm8m\ntD6Ulj4tws4wSi4XhFiOr1l6rvaxBIgHc62Ih71yv5LRWRCUZe2WfAuedA+JxxPpDOrE0dfhq/Nj\nOSZlSfwOoBJhh9Ast6ccSMO3NN6J2KJPviasPoyW0BZfPXvlca8FIjV17ZXjikTkTbEXlENUWxQN\nQQ3CdqBYMpSxU/peIeo0R5jx5sp9P4XgQij1NwHZok5Tswmpv6S3BMRr6i1AWBFS9XODrYAdGA2m\nXSZigmOoHVCLpcyCJ8dD/MF4ao7ViBhHo7cw7ERsYTge4r6KIyg8iOpB1eqcuu+d+/DkeLDkW3h7\n6dtkpmfq5tGHv/tQfWEwe+VsvDleyINYbyx/v//v6hyz5FvwxHiwOEVM/nMwsSgRbFA9qPr0ZSMr\nMJfK41kAcVIcQUFBVGeLmN9+8G1MXhNZWVkcOXokYKyBdODggbMueyHKnw+dqU3/89p8BPp+LjGf\nz/4a/zDtXeop+bwY92RvVE/Jp6HzIyOfvU896UWA5cknn3zyokZwEeR2u3E4HERFRV30BBj67lLy\nGR8fj9VqPevrfrb0Z9RPqBde80SEz34UtH3dRuvYVnE8HqhDPOwek7+PBIKhOaqZmm01FGUWibIJ\nCD97CjRENHBo/SHqoutE+TKQRkkQLM4ln0rmYOlB3rW+qx5zfOrgq/SvRF1OEQv5CK97sBzHZXKc\nl4pjUl8J91du8VA9UlMuBLVdpazax0uBPSBNkHxxH8AHNEwS55nga4MyaPY20zq8VV9niX5MSEY8\n1KZpjiUhHphnaL4fAa7wXePOd8MAzTUJiAdsB+IFjPb4YeBKTV1l4rzrG5fveKLf2Cl9HwGUgjRR\n0/cyTSwJiAfyFrnNBjnvE9GPjfI9Xi6vvPxQ4qyX8ydf01bTBi2+OdAa0yr68RO/dlPkNurE59bq\nVpqHNqtz5NC7h3Be4VTz4tjuoK29TTePkk8lM3HMRO59/F7Khpep/W/7uo2ayhoK0gp8ec33zQP/\nOdh8ollt+7Rly0C6VFLHo7WmlWaa1fsg+f9v7+6jqqrz/YG/9wF5EOL5OUUhUVBQQB5UAm9kaGqa\naZmTmq5ZRlOmeGduZa5Vk67KmeYuvdo0QneNd82dnDtNjdH8XK7MZkYdUx5DjfABFSEB4zE4cjgg\n5/v7Y5+9OQcOKIZwHt6vtVyyn777u7+fvWGf79mf764Pw5SJUxAYGIj9f9lvsa6W5B3Iu+N1R2L9\n4XC7ffZd3nCsN16WpodS5+E83rv9nUvWyVriORrXpD2ylnjS8GA87Y9Op0Nra6tVxFQzqnsnGkVb\nnt0if/vaBfkb41AAxYC/lz8CKwLl+WWQB+FrBfAA5A/oZfI2oZdC8dLqlxB6KVRetxSQWiWgCwiv\nCkfO2hx5ukwuW1OkUZc9Pu9xLMtahvCqcHXexjUb1WmpVZI/UD8A+VvoLuO+TxnraZynKdbA09tT\nrmOZyXptUPerbl9oMh3ZWx+UQn7bQKFxPeNyZdqp2AkIBUKkELldTMs0mLcJTkHuNGk0mXca8hMK\nBSbl95hv4+HjYV6O8g25M+SnAkznA71xKzAeUyng4+EDqUDqPVbTtlOOvUw+Vk2hybEb+pTf0lum\n1CqZl6O0jTJdZjz+yD7t0GQsq0t+IiCgJwAINbZlF+R2RO86KDVur7SXVv45oCdAPb/Cq8KR82yO\nWoZTsRM2PrOx33mkjAuwac0maIo16vH7e/njpdUvqes6FTsBD/TWqe85GCKFqPsedN1Qk/Ysk+sc\nIoWo6y3OXAzFQHW1ZCjrjsT6w+F2++y73DRelqaHUufROF6ioeA5SkQ0svhEAJ8IsHlD7S1VBgdc\nmLkQ+mt6nP3oLJwbnRHcFIwItwg8Pfdp1F2og9u3bvBq80IwgjE7YjYmS5PhpnNDcmAykpGMCI8I\n1DXUYdNjm9B+oh1tl9sQ5RmFiS0T8db6t7B21VrEB8ejqqQKc33mYvua7YjtjsWzGc9i3x/34X8+\n+R88/8jzSHNPw7MZz+Jc5TlEe0aj9mgtsudnIyE4AbP8ZwHXgetHr0NqkjCmeQwMlwyI84hDZHsk\nHpzwILISs3Dx64vw0/rB/4o/2uvb4dHmAel7CYYKA3w6fOB23g367/TwqfOBS6MLDN8Z8G/j/w3O\n3zrj1vVb8BAe6LnRA5QBE6QJCDeEY7LnZITVhSErKgs/fP0D/uPJ/4C4IXDhiwtwvuEM1wuu8Lvl\nh5t1N4F6wOUbF2gaNHCWnBEiQqC/rofzWWd4d3rjJwt+gmtfX4OuUAfUAWP1Y9Fd2w18Dbi1umF8\n0HhsyNqAtso23Dx1E13XuuAv/LF55WZUFFdAd0UHl29dENQdhDD3MAR0BaDtqzagHghuDsaSGUuw\nf/t+RHtG49xfzuF+w/1wuu6EoO4gdBR0QNOggeaSBoH6QCSOT0Tnd53oKurCOGkcdmzYAV+9L6Qz\nEh6Oehgbsjag8kglxjSOwcbHNmLB5AWIcIrAxc8uwr3FHW4NbgjqDsK4+nHouNqBIEMQOis74dLu\nAtdGVwTWBMLnlg98dD6Y0DwBuVty8e9P/zucLzsjwjUCM/QzEOkZCW/hjaYLTRBfCwT3BCM+JB6+\n13wxyX0SXLWu8KvyQ0ZMBl558hXEdsdix7odWLxgMXRXdSj/pBybHt2EFze8iKDAIES6RaLhWAN+\n+cwvkT4nHeUV5ThWdAwpQSmoOlyFSS6TEDg2EBNCJiBACkBgVSBc2lwwb/w8bF+9XS2/uaUZZSfL\nMNd1Lj7Y9gHWPrQWYd+H4aUFLyHwZiD8uvzgXuGOpPFJWDp/KZ7JeAZh7WFIDkpG1eEqTPeajnkz\n5mHTsk3QnNWgu6EbUyZOgZ+PHwIDA9H6Qyu0NVqkSqnYtXHXoI/9BgUGIWtqFsK+D8OOdTssDuCX\ndyAP/t7+CAoMUtd3/sYZk70nI2l6EoICgwYtP9ItEo3/bMQbq99A+pz0QcsfDrc7pr7L0+ekDzo9\nlMemb7fvoeA3VPbFWuI5nOeoI7OWeNLwYDztjzU9EcAxAjhGgM0bSv6UaQ5iYEUgGhsaIWJF76vf\nTHPqlfxv42vqlFepqbnyxjEEvFu80e7ZLufbFwJoB0KCQnD0V0ctfniZ+/O5aJLk1w9qCjXYvWI3\nfnP8N6ieWK3msjtdkfO/AWDZ7mUQKfKj2dBCfVWhR7MHbk65qeby93uVofLY+jUAwZBz6k1z2vu8\nNg9BkHPfAwFNo0kOvZK7/nfI4xAoufnukL/FNh0fQG8s25hDr+SxA8CyXcvk/H2lDtMBXIQ8FkCm\n/ITCyw++jF+f/LWc134EkLwls232rN2DNz96E02dTb37LQZCXEOwL3ufWX67Hnq03N8i78P02HXG\n+FbK7eZ7zhcnfnVCHYitb3z+mvNXTIqcZDZffa2hlzGwxvEZlNfkoRoIceo9B9TzzqtafU2k2ZgN\nUYDvdV9obmrQZGgyKzP0Uii+ePMLNe9/+Z7lg44RYJq773RFHt9BOda+r7NUyli6aKnFsk0HI5z3\nxjzU+9erZSn1qrxSqW6nlB+oN15bGQKaYg1+vfDXmJsxF8t/s3xY8n8HyiUeSo7xYOsyV3lwzFm1\nL4ynfWE87QvjaX84RsAo4xMB9mUovaWmOYgdfh3yh7mbkB9n75tTr3yQdgEw3kKuvHEdfakeYp7o\nzUWvBLSeWoRJ/fMb8w7k4VDVITWXXIQIXMi/gKr4KrNcdhEv53+fPnMaV+OuysuCYZZH3l3cLX/w\nNs1fN80zLwEwB3L+f1afY+oz3oFZ7ntxnxx6pcxWyGMUKOufBHA/zMcHUMo21knJYzc7DqUONyEP\nlNdubN8QgfK/lkOXqZPXu4jenH/jNhdOX0BtR6153YMB7Q0tGs735k9ra7XonN4pxzOxz7F3AJB6\n49wZ0KnmolqKj5KHbzofYcZzxc84bbK+MhaB9kbvOaCedyZjRZiN2XAF6IzthO5bXb8ytT5ai3n/\nA40RYJa7Hy/6jxNhMnaCUsba5Wstlr12+Vr1vP2b29/MylLq9X//7//MxiJACdCR2qGOlyGCBVpP\ntqJH9MhlDEP+70C5xEPJMR5sXeYqD47fUNkXxtO+MJ72hfG0P9b0RADHCCCHYpqDGFgRKOeAh6I3\nv9s0/13J/zbma2uKNea58sZ1vP28e/PtCwE4yetYym9clrVMzhc35pJrCjXIWZuj1knJZVfyvzet\n2QSp0Jj3XozePPICY179A1Bz+aXTktlyRBqPwRm9OfXKMT0A89z70+jNfX+gTw69UmYjzHPzJ6H/\n+ABK2cY2NDsOJX9fqUOosbxGY1sUaZD9VHZvXjvQb5uctTnw9/I332+x3N6m+dMhUgh8z/nK+zjV\n59h7jPs2tpvvOV81Vpbio+Thm87HKchjC2hhNj6DpkijjkVgeg6o510ozPL21fMtVK6Hv5d/vzJD\nL4Wa5f3fbowA09x9ZXwHdfwHZewEk/EfNj6zccCyTc/b0EuhZmUp9TLdDoXyeaReW8br5qmsp7Dk\n4SXDlv87UC7xcI1BwFxlIiIisnd8IoBPBNi8ofSWmuYg7tywE1nTstBY1IicpTnw1fui80wncAPo\n+boHQd1BiA+Nh6vWFePqx+G1Fa8hzS8NU/2morywHJObJ8PzB0/4j/XH+oz1uFV2C9P9piM5IhlJ\nE5Pg4+mDjw9/DH9vfzQ0NiDvQB5iHojBg1EP4tvj3yK4Nhj7tuzD2lVrkTU1C07nnBB4KxDuVe7I\nnJKJpfOXIn1OOuL943Hq96fQUd0Bl2YXoByIco3CQykPIc4tDt4d3tCX6BEfEA+nFie0nWrDRM1E\nhHWGofVSK9Y/uh7rH1qP0gOl8Nf5w7fLFx2XO7A0fikSghOgL9DDr8sPsa6xGNMyBv5t/ojxioHb\nBTeEiTA8Fv8Yaj+vhb/GH/56f2hPaxHQEQA0APdL90PTpIHXRS94dXlBX6+HVCMhc0ImguuDkT4x\nHUsXLIWfrx/O/vMs6o7WQaqV4NXlBbdrbnBrcYOh1QCnM07w7vbGfa73ofFyI/wq/ZC3LQ+rH1yN\nbz/5FsFdwVg/bz0+++dniPKPQrAmGE3nmyDKBDzaPPDLdb/EzPiZuHb2GjwueODx5MdRda4Kt8pv\nIcgQhKjWKBjqDEgITUDcuDjoz+ohbggEXw/GwzEPIz01HQ2NDTh45CDmx87Hd2e/g/dFb8yPnY+l\n85diWsw0LEpchNaLrdAX6OHb5YvZk2cjeVwy4oLi4KP1geFrA1YkrIBrtSsywjPwwbYP1MfJlXz0\nqr9XIc4nDilSCuL84hCuDYd7mzuS3JKQMTkDy+csR8vVFkS4RcCnwwfz7puHvFfy1HKiJ0djht8M\nNB5vxOZHN6P6+2qMkcagvbodHpc88Nb6t7B00VL5HG+Xc/tjnWPxeNzj6C7rRs7CHKSFpeHxuMfR\ncqJFjU9QYJBZ2f+54T/VtACl/gtiF8D5sjMecH8AD3k8hP/a9F+YFjPNbDulfPXaOt6It9a+hcTp\niZgaPRWLZizql/97N7n4A40H0DfHGMCAZQ+Wj2xvucrDPd6BtXxDdS/GcXBE1hJPGh6Mp31hPO2P\nNT0RwDECOEaAzRuO/KnyinLM3ThXzj13gZqfLRVKEJOEmvO9Lmkddp7YKedbF0D+Vn2heS65kguu\nvDM+9FIoRKdAfVy92c8Wc5tNtlOWA5Dzs6Pq++V447ixrkkAvoI8+n8q5BHvtRJErEB4m4W8cZPy\nlf3Pe2Ue6tvr5QZxg/xIvZJX3wn5se944L7T90Gr0crjFihjBXQAmAw1f1w6LcHP1Q9NCU0IvRSK\nju868IPHD7156u0AugHJT+otJwq9ryNsAN5d+i5+8dIvAAD5h/LxxO4n1HfVox5y2kKiMQ4NgO8E\nX7TEtQBfGtvBOIaAVCDh4JaDZrn0oZdC0dXUhSY3Oec/4OsAOHs6o96/Xm0fp2I5vz68zUI79dSr\n+ftbH96KLX/dYpaLbynnvO92St6/aT66U7ETevx64NTcP0Z9z9d+Yw6UmY9LcLvzfaRy4Ae7Pn9M\nPW63LfP8ZfeiHawhZ5XxHT7WEE8aPoynfWE87Y81jRHA1AAiAAePHERTW5Ocn+0J9R3wIkUAdfJ0\nvahH7p9z5Q+zLpA/cOvknw0pBrz34Xs4eOSgPOhfHeTB01yAuqg61Iv6fj9XT6zGp0c/Vfffdztl\n+cEjB+VOABfI+76M3jr4QO4EcDHWO9X4cyIgfOS6V0+sxt4/7h2wfGX/9aJeLsMTvXn18ZDbRNPb\nJu1j2+V2UdqgEvJgfHW99RKzBJqcmtRj/qH5h946p0B+PF8D83LqjP9fkf//3Z9+p8Znz//ukTsB\nlDppTOqYCkAPuRPAxVi2n0kMU4V5bIx1amprUtdpdGqU29ikfXqSetT269dOxu3qouqw+w+71XWV\nYzTdZqDt+sVe2edlyzHqe74q8TQk9bZLvai3uP6A2w+yj5HwY+pxu22t5RhHm722g70eFxER0Uhh\nRwAR5JxgNffcJD9bKpTMcr6zV2b35lsr34b3ySU3y8825lIr71U3/dlibnOo+bvaH5/3eG9+toUc\nb7RCHjugy1hvZXyDUqjjH5i9f9xC+cr+Q6SQ3vx05f32Sl69obdN7uu4r3cMAWWsgNMwyx+XTkty\nTr3xmL39vM3z1J3kMtXxD4x58urYBgXAz1b9TI3PpjWbzN5VD4NJHQsAuMo59ugylm0yhoBUIPXL\npQ+9FCrH27hOQKKwRgwAABDaSURBVE+AmgNvmievtF+/djLJ389Zm9MvF99Sznnf7SzltTsVOwEP\nWI5R3/O135gDZQOPTTHg9qOcA/9j6nG7ba3lGEebvbaDvR4XERHRSGFqAFMDbN5wPTZVXlGOt/e+\njaIzRQCAlPgUPLnwSfz99N8hhED2M9mYFjMNe3P3Yvf/7sZTWU+h+kY1rlRfwavPv2r2qrVPj36K\n2MhYfHPlG/UG9dOjn/b7ue+jzH2365tH3djUCEmSIIRAgH8AMmdl4stTX6K5pRkCAhCAJEnw8/XD\nw7MfNitnsPKVfeR+mIumFvn1dRJ6y/no0Ef45sI3iIuOw9aNW1F5pRI7c3fCz9MPvr6+aGlpQWV1\nJXQ6HXx9fbF9y3ZMipxkdsxv730b5ZfK4eXuhW7RjVeffxUAsDN3J/RaPRq0DUiJTkFZZRmeeOgJ\nvLntTbN45h/Kx859OxEZHomnFj6FDw58gFNnTsHfyx/vbnsXkyInIe9AHoQQiBofhf/+6L8BCdi+\nZXu/2Ch1yv0wF5Ik4bmfPKfGRWmf27WTsp3yWr/3PnwPS+YuQVtXW79tBtpuoNgPtO++5Snb9D1H\n74RpW9zLR6pvd33+mHrcbtuROkZrN9ztYC2PqjK+w8Na4knDg/G0L4yn/bGm1AB2BLAjwObxl6R9\nYTztC+NpfxhT+8J42hfG074wnvbHmjoCmBpARERERERE5EDYEUBERERERETkQNgRQERERERERORA\n2BFARERERERE5EDYEUBERERERETkQNgRQERERERERORA2BFARERERERE5EDYEUBERERERETkQNgR\nQERERERERORA2BFARERERERE5EDYEUBERERERETkQNgRQERERERERORA2BFARERERERE5EDYEUBE\nRERERETkQNgRQERERERERORA2BFARERERERE5EDYEUBERERERETkQNgRQERERERERORA2BFARERE\nRERE5EDYEUBERERERETkQGyiI2D//v3YunWrOn3mzBksW7YMCQkJWL16NWpqakaxdkRERERERES2\nw6o7AgwGA/Ly8vDuu++q87q6urBx40Zs2LABRUVFmD17NnJyckaxlkRERERERES2w6o7Al555RWU\nlpbiqaeeUuedPn0aPj4+WLhwIZydnfGzn/0MNTU1uHz58ijWlIiIiIiIiMg2WH1HwL59+xAQEKDO\nu3LlCiIjI9VpjUaD8ePH4+rVq6NRRSIiIiIiIiKbYtUdAaYdAAqdTgd3d3ezee7u7tDpdCNVLSIi\nIiIiIiKb5TzaFRgqd3d3dHZ2ms3T6XQYO3bsHZdhMBgAAFqtdljrRqNDr9cDAFpbW9khZAcYT/vC\neNofxtS+MJ72hfG0L4yn/VE+fyqfR0eTzXUERERE4ODBg+q0wWBAdXU1IiIi7rgM5aJqbGxEY2Pj\nsNeRRkddXd1oV4GGEeNpXxhP+8OY2hfG074wnvaF8bQ/er0enp6eo1oHm+sImDVrFpqampCfn4+F\nCxciNzcX4eHhZuMG3I63tzcmTpwIV1dXaDRWnR1BREREREREdsBgMECv18Pb23u0q2J7HQGurq7I\ny8vD66+/ju3btyMmJga7d+8eUhnOzs7w9/e/RzUkIiIiIiIi6m+0nwRQSEIIMdqVICIiIiIiIqKR\nwefiiYiIiIiIiBwIOwKIiIiIiIiIHAg7AoiIiIiIiIgcCDsCiIiIiIiIiBwIOwKIiIiIiIiIHAg7\nAoiIiIiIiIgciE12BFRWVmLt2rVITk7GI488gr/85S/qsubmZjz33HNITEzE/PnzceLEiVFbRvfe\nmTNnsGzZMiQkJGD16tWoqakZ7So5rKNHj2Lx4sVISkrCihUrUFpaCmDwGI30Mhq6yspKTJ8+HbW1\ntQAYT1tVU1ODdevWISEhAY8++iiOHz8OgPG0VYWFhViyZAlmzpyJJ598EmfPngXAeNqi/fv3Y+vW\nreq0NcWQ8R26vvEc6N4IYDxtQd94KvreGwE2Gk9hg+bPny/2798vDAaDqKioEKmpqaK0tFQIIcQL\nL7wgduzYIbq7u8Xx48dFcnKyaGpqGpVldG/p9Xrx4IMPikOHDonu7m7x3nvviSeeeGK0q+WQampq\nxMyZM0VRUZEQQojPPvtMpKamCq1WO2CMBovfvVhGQ3fr1i2xYsUKER0dLa5fvz7iMWM8h4fBYBCL\nFy8Wubm5QgghTpw4IRITE0VHRwfjaYN6enpEamqq+Oqrr4QQQnz44YciMzOT16eN6enpEbm5uSIm\nJka8+uqrQoiRjxPjO3wsxdPSvVFKSoq4efMm42nlLMVT0ffeSAjbvT5triOgpaVFZGdnm8176aWX\nxP79+8XNmzfF1KlTRUtLi7osOztbHDhwYMSX0b137NgxsXjxYnW6p6dHJCcni8rKylGslWMqLCwU\nv/rVr8zmpaSkiN/97nf9YpSSkiIqKystxu9eLOM5cfd++9vfip07d6p/7EYqZozn8CopKRFZWVlm\n886fP8942qjm5mYRHR0tjh07JgwGg/jTn/4kFi5cyHjamF/84hciOztbvPHGG+oHDWuIIeN7dyzF\nc6B7o/LycsbTylmKp6LvvZEQ1nHt3k08rTY1oKenB+3t7f3+ubm5Yd++fep67e3tKCkpwZQpU3Dt\n2jV4eXnBx8dHXR4REYErV66M+DK6965cuYLIyEh1WqPRYPz48bh69eoo1soxJScn4+WXX1any8rK\noNfr0dPT0y9G48aNw9WrVy3G714s4zlxd86fP4/Dhw9jy5YtEEIAsHzNMZ7Wr6KiAhEREXj99dcx\ne/ZsPPHEE9BqtYynjfL19cWKFSvw3HPPITY2Fu+++y527tzJeNqYV155Bfv27UNAQIA6zxpiyPje\nHUvxHOjeaMKECYynlbMUT8DyvRFgHdfu3cTTajsCvvrqKyQnJyMlJcXs35tvvqmu09nZiRdffBEz\nZszA7Nmz0dHRAXd3d7Ny3N3d0dnZOeLL6N7T6XQW21+n041SjQgArl27hk2bNmHz5s3QaDQDxmiw\n+N2LZXTnuru78dprr2HHjh1wcXFR5490zBjP4dHW1oYTJ04gLi4OJ06cwE9/+lO88MILA/4NYzyt\nm8FggKenJ/bv34+ysjLk5ORg8+bNjKeN6fsBA7Cu37GM79BYiqcp5d4oJycHHh4ejKeVsxTPge6N\nAOu6dofCajsC0tPTcf78eVRUVJj9e+eddwAATU1NWLNmDcaOHYvdu3cDsPwhXKfTYezYsSO+jO49\ntr/1OXv2LFatWoWVK1di/fr1vCZt1HvvvYfU1FTEx8er84QQjKeNGjNmDO6//348+eSTcHZ2xqJF\nixAcHAwhBONpgz7//HNcvXoVs2fPxpgxY7BmzRr1ppTxtG3W9DuW8R0+pvdG69atA2BdsaY7Y+ne\nSGGr8bTajoDBXL9+HStXrkRMTAzef/999Q9geHg42tra0NbWpq579epVREREjPgyuvciIiLMHoEx\nGAyorq5m+48S5ZvGn//853jxxRcBDB6jkV5Gd+7IkSP4+OOP1SexAGDp0qUIDAxkPG3QxIkTodVq\nzeYZDAZMnTqV8bRBN27cQHd3t9m8MWPGYNq0aYynjbOmv5mM7/CwdG8EWFes6c5YujdasmQJDh06\nZLPxtLmOgFu3biE7OxuZmZnYvn07NJreQ/D09ERGRgZ27dqFrq4unDhxAqWlpcjKyhrRZY888sgo\ntpDjmDVrFpqampCfn4/u7m68//77CA8PN8uZoZFRVVWFzZs34+2338by5cvV+YPFaKSX0Z07fPgw\nioqKUFhYiMLCQgDA3/72N8ybN4/xtEFpaWnQaDT4wx/+ACEE8vPz0djYiNTUVMbTBs2aNQslJSU4\nevQohBD45JNP0NraipkzZzKeNs6a/mYyvj/eQPdGgHXFmu7MQPdGixYtst14DmloQSvwj3/8Q0RH\nR4v4+Hj1X0JCgvpapKamJvHCCy+IpKQksWDBAvGvf/1L3Xakl9G9V15eLpYvXy4SExPFM888I6qr\nq0e7Sg5p586dIiYmRiQkJJhdl8XFxYPGaKSX0d0xHRmX8bRNly9fFqtXrxYzZ84Ujz32mCgpKRFC\nMJ626siRI2LRokUiKSlJPP3006KiokIIwXjaor1795qNSm5NMWR8h840noPdGwnBeNqCvtenKdN7\nIyFsM56SECZDHhIRERERERGRXbO51AAiIiIiIiIiunvsCCAiIiIiIiJyIOwIICIiIiIiInIg7Agg\nIiIiIiIiciDsCCAiIiIiIiJyIOwIICIiIiIiInIg7AggIiIiIiIiciDsCCAiIiIiIiJyIOwIICIi\nIiIiInIg7AggIiJyIF9++SXmzp2LhIQEnDx5csD1Dh48iMzMzGHf/4EDB4a9TCIiIhoadgQQERE5\nkL179yIjIwOHDx9GcnLyoOtKkjSs+y4qKsL27duHtUwiIiIaOufRrgARERGNnPb2diQmJiIkJGTE\n920wGIa9c4GIiIiGjk8EEBEROYjMzEzU1tbitddeQ2ZmJqKjo/HFF1/gkUcewfTp0/H888+jra3N\nbBshBFJTU3Hs2DF1XlZWFrZu3apO79q1Cy+//DIA4JtvvsHKlSsxY8YMrFq1Cnv27MGaNWtw/fp1\nPPvssxBCICYmBkVFRSNz0ERERNQPOwKIiIgcxCeffILg4GBs27YNe/bsAQDk5uZi165d+OMf/4hz\n587h97//vdk2kiRh9uzZKCgoAAB8//33qKmpQWlpqbrOyZMnkZGRAa1Wiw0bNiAuLg75+flYvHgx\n8vLyIEkSwsLCsHfvXkiShJMnTyIhIWHkDpyIiIjMMDWAiIjIQfj6+kKj0cDT0xO+vr4AgE2bNiE2\nNhYA8Nhjj+HcuXP9tktLS8Of//xnAEBxcTHmzJmDgoICNDc3w8nJCefPn0daWhoOHToEDw8PbNu2\nDZIkYeLEiSgtLUVDQwMkSYK3tzcAwM/Pb4SOmIiIiCzhEwFEREQObMKECerPnp6euHXrVr910tPT\ncf78eWi1WhQVFSE9PR1TpkxBSUkJCgoKEB0dDV9fX1y8eBFTp041GwcgPj5+RI6DiIiI7hyfCCAi\nInJgY8aMMZsWQvRbJyQkBBMmTEBxcTGKi4uxbNkyXL9+HSUlJdDr9UhPTwcAODk59dvWUnlEREQ0\nuvhEABERkYMaygj+aWlpOHr0KGprazFt2jQkJSWhpKQEJ0+eVDsCoqKiUFFRYbZdeXn5Xe2PiIiI\n7h12BBARETmooXxbn5aWhvz8fMTFxcHJyQlJSUkoLy9Ha2ur+vj/okWLoNVq8fbbb6OqqgofffQR\nDh06pHYAuLu7A5A7B7q6uob/gIiIiOiOsCOAiIjIgZh+Kz+Ub+hTU1Oh0WiQlJQEAPD390d4eDjm\nzJkDjUa+nRg7diz27duH4uJiLFmyBPn5+ViyZImafjB58mTMmTMHq1atwvHjx4fxqIiIiGgoJMHk\nPSIiIhoG3333HW7cuIGZM2eq87Zv3w6dTod33nlnFGtGREREpvhEABEREQ0LrVaL9evX4/PPP0dt\nbS2OHDmCzz77DI8++uhoV42IiIhM8IkAIiIiGjYff/wxPvjgA9TX1yM0NBQbNmzA8uXLR7taRERE\nZIIdAUREREREREQOhKkBRERERERERA6EHQFEREREREREDoQdAUREREREREQOhB0BRERERERERA6E\nHQFEREREREREDoQdAUREREREREQOhB0BRERERERERA6EHQFEREREREREDoQdAUREREREREQO5P8D\noAqXVyBbOTkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xfb802df780>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Export is successful!\n"
     ]
    }
   ],
   "source": [
    "md_text = '## Interaction between numerical variables (on sampled data)'\n",
    "filename = ReportMagic.var_files='tmp/numerical_interactions.csv'\n",
    "export_filename = 'numerical_interactions_report2.ipynb'\n",
    "silentremove(filename) \n",
    "w1, w2, w3, w4 = None, None, None, None\n",
    "\n",
    "if conf_dict['Target'] in conf_dict['NumericalColumns']:\n",
    "    cols_list = [conf_dict['Target']] + conf_dict['NumericalColumns'] #Make target the default reference variable\n",
    "    cols_list = list(OrderedDict.fromkeys(cols_list)) #remove variables that might be duplicates with target\n",
    "else:\n",
    "    cols_list = conf_dict['NumericalColumns']\n",
    "w1 = widgets.Dropdown(\n",
    "    options=cols_list,\n",
    "    value=cols_list[0],\n",
    "    description='Numerical Var 1:'\n",
    ")\n",
    "w2 = widgets.Dropdown(\n",
    "    options=cols_list,\n",
    "    value=cols_list[1],\n",
    "    description='Numerical Var 2:'\n",
    ")\n",
    "w_export = widgets.Button(description='Export', value=\"Export\")\n",
    "handle_export_partial = partial(handle_export, w1=w1, w2=w2, w3=w3, export_filename=export_filename, md_text=md_text)       \n",
    "w1.observe(handle_change,'value')\n",
    "w2.observe(handle_change,'value')\n",
    "w_export.on_click(handle_export_partial)\n",
    "\n",
    "%reset_report\n",
    "%add_interaction_code_to_report i = interactive(InteractionAnalytics.numerical_relations, df=fixed(df), \\\n",
    "                                         col1=w1, col2=w2, Export=w_export)\n",
    "hbox = widgets.HBox(i.children)\n",
    "display(hbox)\n",
    "hbox.on_displayed(InteractionAnalytics.numerical_relations(df, col1=w1.value, col2=w2.value, Export=w_export))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Explore correlation matrix between numerical variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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KFRERESnirzw25m7tWBomVERERKSIqjFUCiRUdRhD1VCwy4+IiIjIRKxQERER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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xfb800e9be0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Export is successful!\n"
     ]
    }
   ],
   "source": [
    "md_text = '## Explore correlation matrix between numerical variables'\n",
    "filename = ReportMagic.var_files='tmp/numerical_corr.csv'\n",
    "export_filename = 'numerical_correlations_report2.ipynb'\n",
    "silentremove(filename) \n",
    "w1, w2, w3, w4 = None, None, None, None\n",
    "w1 = widgets.Dropdown(\n",
    "    options=['pearson','kendall','spearman'],\n",
    "    value='pearson',\n",
    "    description='Correlation Method:'\n",
    ")\n",
    "w_export = widgets.Button(description='Export', value='Export')\n",
    "handle_export_partial = partial(handle_export, w1=w1, w2=w2, w3=w3, export_filename=export_filename, md_text=md_text)       \n",
    "w1.observe(handle_change,'value')\n",
    "w_export.on_click(handle_export_partial)\n",
    "\n",
    "%reset_report\n",
    "%add_interaction_code_to_report i = interactive(InteractionAnalytics.numerical_correlation, df=fixed(df), conf_dict=fixed(conf_dict),\\\n",
    "                                         col1=w1, Export=w_export)\n",
    "\n",
    "hbox = widgets.HBox(i.children)\n",
    "display(hbox)\n",
    "hbox.on_displayed(InteractionAnalytics.numerical_correlation(df0, conf_dict=conf_dict, col1=w1.value, Export=w_export))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <a name=\"numerical and categorical\"></a>Explore interactions between numerical and categorical variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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UXse29owdVZ2Obe3ZunVrpeMAwKCw432z98/Q/3R1u+1WWR86dGgOOeSQnH32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\nRK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xfb88150ef0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Export is successful!\n"
     ]
    }
   ],
   "source": [
    "md_text = '## Explore interactions between numerical and categorical variables'\n",
    "filename = ReportMagic.var_files = 'tmp/nc_int.csv'\n",
    "export_filename = 'nc_report2.ipynb'\n",
    "silentremove(filename) \n",
    "w1, w2, w3, w4 = None, None, None, None\n",
    "\n",
    "if conf_dict['Target'] in conf_dict['NumericalColumns']:\n",
    "    cols_list = [conf_dict['Target']] + conf_dict['NumericalColumns'] #Make target the default reference variable\n",
    "    cols_list = list(OrderedDict.fromkeys(cols_list)) #remove variables that might be duplicates with target\n",
    "else:\n",
    "    cols_list = conf_dict['NumericalColumns']\n",
    "    \n",
    "w1 = widgets.Dropdown(\n",
    "    options=cols_list,\n",
    "    value=cols_list[0],\n",
    "    description='Numerical Variable:'\n",
    ")\n",
    "\n",
    "if conf_dict['Target'] in conf_dict['CategoricalColumns']:\n",
    "    cols_list = [conf_dict['Target']] + conf_dict['CategoricalColumns'] #Make target the default reference variable\n",
    "    cols_list = list(OrderedDict.fromkeys(cols_list)) #remove variables that might be duplicates with target\n",
    "else:\n",
    "    cols_list = conf_dict['CategoricalColumns']\n",
    "    \n",
    "w2 = widgets.Dropdown(\n",
    "    options=cols_list,\n",
    "    value=cols_list[0],\n",
    "    description='Categorical Variable:'\n",
    ")\n",
    "w_export = widgets.Button(description='Export', value=False, options=[True, False])\n",
    "handle_export_partial = partial(handle_export, w1=w1, w2=w2, w3=w3, export_filename=export_filename, md_text=md_text)      \n",
    "w1.observe(handle_change,'value')\n",
    "w_export.on_click(handle_export_partial)\n",
    "\n",
    "%reset_report\n",
    "%add_interaction_code_to_report i = interactive(InteractionAnalytics.nc_relation, df=fixed(df), \\\n",
    "                                                conf_dict=fixed(conf_dict), col1=w1, col2=w2, \\\n",
    "                                                col3=fixed(w3), Export=w_export)\n",
    "\n",
    "hbox = widgets.HBox(i.children)\n",
    "display( hbox )\n",
    "hbox.on_displayed(InteractionAnalytics.nc_relation(df0, conf_dict, col1=w1.value, col2=w2.value, Export=w_export))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <a name=\"two numerical and categorical\"></a>Explore interactions between two numerical variables and a categorical variable (on sampled data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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oNAjLmVFdoarRhVr/3k7VnjdewwYXJrpJCTejukI1lcVyHnWropiK8lL4+fM1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DnFF+IMAZ5WvyeV17T54YDTNt4CXpZg28746aBqrotVdzlvDjZ4ZonfXjZ0TD4kKAr9vCPJfv\nb6+k39td28TfmZPL93i2xPtXmVtOf2elkxuQAvM8nDswL7qp8rJzaSRPnqRs128230nX82jLPqFt\nWONG0rAmMZIaeXnRuFFMh9npaVw+C5fHkTRih4eXAK0qdNPzs7KAP8angn56NvsWRF4bd34WNe66\nXfwOqq60iRVZ3GOorhDPVYM5CpunO20cdk83DBJWfr3587J4cSNh9V0+IjKMajIs5/5GLEgG3IhH\nLNLc3xwLn6tsSbSa3lD26/IUGzL+lGC5bOAKyMoG6vVyO+25+OSOjy4r2GajGX+w46PUQHE9udbG\nzH1byKOVAH0cBCnDimVp3Baj+ZqGlbUaNPR6imtcFdSwci0DxVqg1/jhctjw6INbl98FZpMBjz6w\nVVUW0Am9FSJuRKWCjWzgUUYBhcVQsgw22cQqoWRvneel8N4kdZxlYWduSdghgGtexCnIqiPEk/xh\nnEPyNgHAQVIclh8dGY8gWb3zstwSJH3pHqCkrwxlDv4gm0lwMitWr7xrOU8pmfZnVx8P533n4or8\n/hVzeeqimPd//FTKqp2esywLf7VHS6liYI+KxJGX53n5tYsBXsaqsYz3vamMz2FWkpemykqKynV5\nkYPmqJYV8aiFPbutlDthz27xAr8yd4n+zt45TtZ4YoB70N8e7KbtQ0Y/V7AMopKi1zgl8+hqMfF3\njo5zRUAWsZG0cKLBuFU8V/I1zoSfDx76PLhcYz09xHtgRFY1IiRWK6jpQjgheiOLwHO5izQemZNW\n7nLF7x0hZTAf2LuD7tkH7uigfft8SarQynK5t5U1Ue//tlJx7Ke7U+dBugZ06hKPzvAv8EfVLHls\nTQ6bqBFuYoR7UgrsPKomP0vM4690u1FkK0k7a4tsJVIlf9ofpsqyzDA9HZ2gZ/N0VDw/aypssHgy\nDAieC1TJB4BL0700leHytJhq1O8fRhLpxqIE1pDfnuHNl0Ut764USVMBYGeFKK8qzaXGD1nEnx7F\nvaWokfIPtBRxI48exVCvN/eqEWFx3uPJxKpGhBOdZJjyzQAAIABJREFUvBwpKxt4PfnQRxoO4OuH\nP4ePld+Lrx/+HI40HKDt9Pbd2T8Kc3VX2r41VV9A5wB/2wHQxUFwpOEAHr//i/j8oT/F4/d/UTpu\nQJ9BQ6+nmHF+RAdaoMX+/3t0r8f4cXSvB4//5V34/bsL8fhf3vWuljy8nbBWQs0bValgIxt4JNmg\nCrcT9OSLAcDdu6rx3JuiVfnwDjE8cEASXjgwHqA5gJ29cjKWTIJDhySEJ0fCY6AnamFyOgRT0cCy\nxyjlQZ+Y4YpBZ68P0SvbgJF6mFyTSPiLgLCDjhsAurvi0GyGtMenljTiYncM2J3etqzMAotNzCuu\nKOCK3tnLk3TsZ3tK8MG70j2phYVGWIyiR7zYzfturs/B2Yz3q8EAtDSIXp1qazNGIukKsKYBNXae\nmuAuNCCz5L3BALgLue1yfDyOmL8FlppuGIzJZYVpLE/0ckeMM1TJj5h4rn1jZR5AHCf1VaLBweNo\nxCntjPA763Ibad+HGnbg18O/EtofbOCKoTXJHxk2TZSX5ZYsVqZYitBIEfbJjFMGW5gq7gYL8eiZ\nuDcm18wVA1u8CJoG4XfaY2L+dHjBuPjKXDkWDQhKvPO72krxvbdEuZRVvHQGhgyns8EIOMvE9d9e\nU4vXT5QtpzNoGpDwlWH7Lh622zs4S7+3niHRY1SeX4D4QAvM1Vf3bHygGWX5MuJVJ7SpGoRnSmHM\nCiAZyoUxaZN6xmamNSSDGesfzMX0TBLIOJ7N9viiQmtY6RG/AIvtEO378kw33SuXZi8C2JYmdxdk\nA3OaYOAtzON3yuAMZ1QfnJ5EhTPd4DjsH8VULD3VZCo2imH/KCpcYmpOSomMp5RlrO5dLMjKo/uW\nEXuupuRXukUjhbR86axonMo3F0FLindEnoVzJywrqOYojNkBJIO5QNyKExfGqfI+HOBcLSOBUTQV\npRNCdg+P0eiJi8NjtO/lOV+hqMrmXItbEfW2wlx94eo5nlLcyBs7pRj+07+fQyyeXFUxTHmKVxpX\nVvMUr2ZE2EzurV1tpXjymS5Bzs6h63KQAHDaHKjJLl9V2dQz34D+tKTVOAi2NfL96LTn0jljfcsM\nGqzvo3s92LelDN7ROXjKnKsqYt6ROUTHKwFf8fL5ibh11XHrwZGGA9hTuR0D/mFUuyrglERZrYQz\nx4q6UjucOdxJpfDuQGZs2rel7F1R3o/u9aC9IQ/H3urEgd1tKC3i5VnXG1SkgAIGx/hFIMsXbK11\nC/wBxflZaK4VH0FT5LEDAD4/l09J5Kz9vITsg5UmAoBASJI+QKoPNNZl00fQploe0rhMPLKi1i4g\nJx6xmbKoB9BqEEMpw8YZeoGHjLwut9ESpWM3WsTfGbZM8GoCFl7CLov/fNiJ/N6dWyjT+r07eA66\nJsn9TQb5RfvBg/XUA/jbd4kh5JMTSWpsmpzk/o6KbJJuoBlQkS0avrbXk/r1GrCtjod4640qMc+X\n0pJqpnmx/c+Od9EKDj97VXy4AosKI823JnOeneTkftkJTu7XNznJS95Ninvr7PAVSsB3bvgK7dvl\nAqwZodVWT7e0dFjEwFNtIhCVtN2tpYj3bUP43H5E+5sQPrcf8b5t0jKqB3YV0e/t4E7x0ekdmUN8\nIn3PxieqV/UWatDSvL+rlbHqnRqiKTu9U2KaxKw2SlNHZjTuLWzM53n/Tfniw7+4LE7PlaIyngqk\nJ+//5Og52sc7o2JZP0C/d9GYzVMfjNli6kPPMDdm9I5w+f76LeR3GnBnvXgm9g9zroqBIR6xsaut\nlHrzZYayqQVOSjoVFO8VX5hHT/gi/J7QM+edvT7EJ6oyvomqVZm81xpCrNdTrCdiBVhU8NheySUK\nn8wp4ZNErOiB3j2ul6/gRhK8XU/fekovmk3GtPPz3Samc9pzsbmkeU0GAYX3Du9FpYKNaOBRRgEF\n3Uya/vkIJjNYuydnQzTca0FSBjAQ5H1PSTwpzLhQJMnbLJJwDbB62gAQiYnyHt8gfQT1+niOs17i\nkdxsK1Voc0mKw9yUjT6Y/T5+Icasfjr2uFUMN5cZUOaDfK4CgbXnLC/WWU6XGYyQ1lnWEpLyXnE+\nh03VS567jHDZhmrRo+fIS/LHm5P/ngu9KdKupbElgZi3Bd09omLwZg9JHzACb/Tw9IHzVxajSlYq\nndEr26SP4Fy7g+R+tyKXeI5OD/XStT89yJXr4LyRzjnLn3fn2omRxyCNKMrO4sprNvk8I/5suscj\nc9wK1TXmBTJKh8GQXJQTuBIeqtC6Eh6xrcOGu9oXy5hpIScQt+Ku9krpA9TuCtI5t7nEs2z5kWqO\nwpAzB5ijqz5S9Zax6vTJyB3F1BTNxL9xo6Q8YHtNHRIZxqyErwzbq0VFQi8XQltNGZLTpemGsukS\ntFaJnv8dZVtoHx3lW6k8hcTSAzGR4N98CvMLMqOyKI9oXKGLJLniXul2Y5/7nrS0l33ue2jqQygU\no3eE7F52uSBwENg8F6WGsjurd1L5PiLf39RM1/POptU9wUljGEanD0mjXPEdnJCQGE6snve/FsUw\n5SleOYfRsUqpYrBaxIqsf/Z9sv6vV7Gei8zDGxzGXITzcaSgJ9daD18BcGMJ3tZr3wq3Nm6VSgXr\nDSp9QEG3Qnuic0zUDTTgRNcYDu+uSZNvby7GD164JPTRvomHbhXmcyWgkCj6Mn+ZzJFWXMDzx0vy\nxYvQFHbS0E1DhB8oi0zRgGa6GrppSFilxCMVRUv/5oqQVgCoLBbHMjEVR2xBDJOfkhDwlWaVojMo\njr0kR/R0+sdyoOUY0jyGWtIA/xifq23lTXiqT2zPcpYnRs10DqdGzYBH7PvqPkznTpDtQ2+KgToj\nXJaFBsbmcuhYovP8dw6MB2Auu5KWbm0uu0KjZ+rcVeiaFvtucHO27VBoRVRJ+Op6yx77d2wuw09f\nqkZiRQg54lbcsVlUmO7c1Ix/G35RGMtdkse7zx9CYrIaiUABTHmTSMwupr2wyJygcZpHlRi4x9FT\n4cJFkrrrqRC/oQ+/bwu+/PoLGWHvDnz0EFcAU5EfmSHeUxMa3Vu1+RV4ZUpMq6itEJVU/3wErw+/\nAfv2zuV0gNeHJuCf30wfk75xiziWJDA1bgUynLQuhw1NB7zoXehaHEfVRdTntEofqWkEbyv2uAyF\nWjV6tTfE0HejyM3QWF6IX5OU6PqKQtr3wHgAsSvbEBuvhrlwGPGpCmAhn6aCpbgQMs8sny+JSlJ9\nMBCZhzGj+oTRPYpAZF6YmwpXGQotZZiMXk3vKLKWocLJPeL++Qi+9dRZpChokhrwrZ+clYaR7m/Y\ngqf6fpR+xmncm+9yGgHiLHe65MQ4g135CI++b/lbHizLB+4R26UFKq2BZ6ffPwwtw1CmGRLS0HeH\nqQCJqbLleU9FLDmMnMeh3tFydd9qQL1DTtbon4/gn489A8vWq9/QPx+fwL4tfyjM+fAEV3Zlcj3Q\nmzqSiljJPD9llSr0hO3rSXtI4fmeY3jy1A8RTybw1Niv8In2j66an58ylKwFRxoOoCqnBi/3nMTB\nhh1oLuP8LSnoCdvXi/Xat8Kti+v53vRibiGKK2NhVFRHkZ0tCaNdZ1BGAQVUlfILT1ZOsF9iwWf8\nAcOTkgt/ch4tJN0gGJHUNg+L8r5h0fMNAH2jXC4jlvIFRAUoMG+gj9p5h/x1ZiwU84plKJREORQQ\n+cxcBIlpUSn0SbxRd22twy9/KI79ro/WCW1DIRMS4dL0/OnpUkQ0HkQUDZmhRWzAUi66pgFa1IZI\nWGS3P3luBolYZt8leHt+BvftFfuurrTRmuwy0i6LxUhzua1mkQ+hobwEsbfFOWnYxkPf/YbBtHx7\ngwGALYw5wyCAdOWgoawEsVMty9UKFj35zahv430vSPZ4kOxxAIjFlh6ctgUYC0aRnFoMh2SklxOT\niaV9u3JOmjEmKafndmWlz2HlJcT6W1CYJypApngWVcSNCb6XvSPcG8fkFRUaDXsvreAWvkujo9Qj\nfml0FIDoMZ4JzdG0itmgOJbO/lEYqzrTPK7Gyi50DoxiX6tHaP+LE+eATNuSAfjFibM4tDX9mxv2\nj+JKsCttHFeCXdJ8+Dynje7xvFzO+VGcnwdk2mg0oMQluosX69qL6ymra++bSfGsLO5zc9EQYv2t\nmJoV94peLoRfnHuTrucvzr+JRw7emyYf8vkwGRm7ek4YgMnIGIZ8PprH39nro/nQMr4XLW5FzJv5\nDbVAi4nGmN3lHXj68nPCHO4q5/wgXX0+XB6cBXBVSb08OIuuPh9aM+7DHJuFrn22fRft25LMputp\nTvLHqh4enLlwAAPhS2n7djB8CXPhAA2b1vMN/eY+D/7zHTG95d53gYRNr2LQVlOG+M/T+Q3iAy1o\nvZ+XkdXbvx4FVUZ6uKdy+7sSqv5//erf8ZrveRiMSbww9AL2uY/gz+/57VX/jh6jg16s174Vbl3c\nSIPQs6978e2fnkU8oeFfX34Fj3xo64YgjlTpAwq46OWevu5+LnfIQuIJwd/kNOcImJjhcq9E0b8y\nIsoDIa4UM44AQD5uJnfYLTy8X0Ji+MsTl2he8XMnxCgJQG6I4WzOSy+xjPBKmXlidi5Cxz5D6myP\nz87CVJBRIqtgHGOznK/Ar40KyrLBFoY/KeYhD/h8tO+BKR76fHpQEvo+JDJzA8DzJy/TOX/+pBi2\nPzQWoHMyKPFG9YTe4ZUTQqeEttUluTDmzqRFFRhzZ6TM3HqNWQUuO6ytr8He+iYsJUOwt74Ja+tr\nlKBqNWJPhkgiKLKn11xAKC6Gvg9Mc46AQR8PuQ3xTCAqf+HS27TvFy/xmt/9A1Eatts/yL/9K5J0\noB6fqIyETNO0bcTISSlzq/i85FWJ86I3H/6Vc1foHn/lHE8HGfSP0FSWQb/4fZ66OEHTQU5d5nni\ni6X6RFJSVqoPwKIivuLMyqxwsxK+KA/PnomIc3i89xxZHw2v9vI5nJTx10j4bp5/s3/pf2lpf77w\nVr/QdmhAQ3LBmZ72sODE0AD/rT9+kacUPfWfotySFadrb7FzA98pLy8ZesbLU96WIxEyeHAY9LL4\n6/mGlqPmMir9lBXJx6MXqb232h5cbjuVfk9oU9f2oOspkbbWfHi9c64HQz7fskEAWFyb13zPY8gn\n53FQUFiPWOv3pgdXSQwXz5N4QrtmCdD1AmUUUMA5SWm785K81USCX6wxIt/exK2zsvSB2kqeAFlf\nIcq3NnBPrMwi3DvCFd3eYVG+/BszFHH2GwHgnf7L9BH0Tj9/BOqphLCtgYfzyuTLHBEZY2fh6fkl\nUTruglKuXB0ffIs+PF8dOiG0ra830L4bGvixc+LsLFX0Tp7h63Z5sp/2f2lKLBuQn2J+zpgTt5Nf\nFHUFNVReT+RvXLq0HA0BpGqPj+KNy9wgNC7hzRj3cflL3WeoF/2l7jNC20giSBWJSJL3fW78IiWb\nOz8ujj2RMND1kVQARY27nLb3uEVixtBEAW0bnODhyc58je5DVx4fzN3bNtH+D28XK0ToJbz8SPv7\nKKHmgx13C23LrXV0HGVWkRwTAIb8w3SPD82N0PZuazHt320Tz8SSygRNBykrTwhtAcCaN0vbW/NE\no8DLJ0VjCwChpnsKm4o4G3xjsZiCUyxJMSsu4BErMlJbmTyCEI1Yimhi+4FpH41AGZQoVwZJ0hsz\n8J64wu+Ut709tI8iazEtR1lo42kVm+sWU95WKuMGA2jKm96a7FkJXi7Wrol8L96ROUqQ+G4QgqUe\n74klY0Aiufrjfbk884p7YrXyzCnoUTzWWjdd75zrwdvey8sGgRQMxiRO9vO9paCgcBXvBYnhzYIy\nCijICfgkcj2Kfs+gRKEb4vKqIv7wrigW5R1N3CjQvonLU2QzmbCZxdD3hmrONrypisvd9hL6CCrM\n4ozlespA5mTrK724jAzPC0NzSQ0dd1MxV4r3V+2mSsf+yj1C26F+A+170MvHkjCEqKKXMPLHuyHi\npP0bI6IBqbOXe7PPSQxfCz5JlQkiPzvZScd9boIz/ltS5DcZ6yPbn29PnKD9vz3xttg4W1+pqVBo\n7akMAcMwHcccuIIqW8+4QVxPY1LCBK/xPb67fhNVgHbXb6LtbTkxOhZLtmgom5pOLpEvpvpdTAeZ\n8nFluamoQTAW1RfUoKlQTNe5dGWBGhAueXnEiimaR3+nJcqNpzu38NKGOzeLcpfVSb/lXCsP8R+d\n5BUcRqdEeVc//64ueLncZSyjY3GZRIW2qbiKzuGmIu7RrSZ3ByCLygI2bTLRb6hpk5htWVML2tZT\ny+O4Hryb78+H3icap9qqKuictBEeDABo9hSI1gWDhqYavicAwFQ0mKGM86gCpz0Xu1y/kUZIutP1\nG1JiuqpCNyUwZRwEbrdxKa0r3ZDpLlj9eboW5Vrv4/16ywauFc++7sXDX3wan//B03j4i0+vWjfd\nac/FJ9o/kkYG+HD7R1YtTTgXDuDceDfmwquTNO70NC6vTQpa0ogdnoa1/hQFhdsWG5nEUBkFFLCn\njefL7SVEZsDqPAGZ6BnkIbc9EqPAiI/3PTolyvWW+ClycUWvgJAYnpMokWcl8prCQvoIqiY5roA8\nNeMikcuI9mRGgenZ8JLn5cWlx96LMBUNwEfm6wN7mum4P7CHE9OZIoU0XNYUEdnDQkETEhmM4onp\nEoSCnMqkMKuEe7rs3NO1o7F6saTeyrEEHdjVKHpSalORJvZ5mEr7APvifqov54d40J9FH+QLc+Lj\ncJOLl2rblCeSLwKLnji2PpslpJQOI3/U55oIIVheIR1LhYtHlez2tNFyh3d4WoW2pU5uDCyX9P3+\nbVto3+/fJpIH9voGqNLeS6I+AKBjUzGEvwBgu8QguEggljkWAyUQG5mYp+kgsnMPAL50z1/h09sf\nQ719Cz69/TF86Z6/ou24dx5S73xbnZu4kTW0SvbKSPQKnceRaJ/Q9qVOXqngpc4LtO+moga6t5oL\nxSgHT9nS95Zh+Kor58aMlSlJK8disIgKX/foKFF+gYujvJRik4cwGwJoquHyXZ5GIJNTRTNiR62o\nuDeXlXEDRTm/O5fL+a44h2TlfGfCs3ROZiI8XWMo2E/bDwfFtAdgMe/fXN2Vpoybqy+gc0CcR/98\nBK+8YEoLqz/2a5NUIb96N6eTxrJIuJn4JPVaz8Z5SgmwpFx/4Vf4mydew8Nf+JVUufaUO2HMmBSj\n0SB9vN/IsoEp8kXzlsVz37zlRfzz8WeuGTGgLR1cWuYBloHne47h0af/Gn/70jfw6NN/jed7jknb\nVrrdqNX2pt37tdpeKXHke4G1RlAoKNxsbOSqFsoooIBRSV71kMQzJPP+M7nsQdZCysYBwM9e5vnj\n/07kHolCJ7vwY5JSVPG4GNLJjBCryadnQjRnnSniwCLJEwNL2RjzLa1DhkLLPHQAcLJ3kOb+vtMj\neoFGU31nPN5GfLxv30wI0a59CHftQWy8EuGuPYh27aP5uXu25cPkzuQUGMMd2/naFzht1NOVLwnx\ndxfFaVh9XqHo5T7XOwVL3RnYtxyHtfoi7FuOw1J3Bmd7uJEHWQH6wDZliR4Yq5GELWuA1cDDmbNz\nkrB4MtenC/Ycvj8XZvnvn58VDRTjC+N03KPBcdrHvq3lVMG6Y4vojSwy1ohKYRJwGz20b4M5Rvtm\nkStWk4UqnDYzZ9q/ONlP0x4uTXIjQr5sb5FLPMsVoukg2S4esQIAX/v+SXz12304/0oFvvrtPnzt\n+5wLoamohhonGou5l9uYO0M5Aoy53NgqrbNO5KGEpJxegv/Ojk3FlIOAGWKqi3NpSDiL+AKQZtxb\n7joJaCRlY3zIRPfK+IgY8QXI+TRYJRFgkWgw4SvJKL1YQmvbT4f9dI/PhCScLPMRzOa/kXYOzea/\nQRUhvd5cX4DfTb55LjfmrD2qaNnjviKsfjWP+1Xvf6pfSL3/esPkr+bzLn5I8URy9XzezO+Ht1r8\ndy38SSyL4tKD1cgXGVJEg4mlAyOhJfHdUz+iUQBz4QD+73f+LY2U8Dvv/Js0YsA/H8Hl066090rP\nGddNU8iffd2L//Lfn8PfPPEa/st/f27VCAoFhVsBR/d68M3PHMDv312Ib37mwIYgGQSUUUABQEBS\nCm0hyMPOwzHu1YrERbmMVK1Xlnsj2ZFGo3iVHz/DCXdk8jGZou8TL87BUQlh2xiXj80u5Wxn5KxP\nTEvyxyV55RNEPjI5TxXaEYnn0q+N0NzfWU0M8/5///McNSD8+CVOiNabIsNbyEe8fzOwsKjgMyLI\n/jmuuPXNeWnfZ0cvUYX27CjPze8P9dD2AyHRgBTBLFX0Igb+eE+CfxNxTZSPLhAmfCMwukDqvQE4\nPXGetj8zzonSshMlVAnKTojKWBz8UZfU+Lc8LPUuisr1W51jYBrQm538UfvkGz+nfT/55s+FtgsG\nTtYXMHLSu1+fvkzn5Ndn+F55y9tF+3+zX0zxeHv0NG17YlTkcAAWlcuX3xlKM9q9/M4QVTq7vdM0\nwqFbQvbaR/hOAKBPUtmhc5JzmHQR+fScRImUKJeLRKDpMoNRo0Sg+QUGym2Rn89VstkF8nsMwHRQ\nPFcqyriRrKKEG5BkpT5l8lfOXoExgyDVWDBOyR1nA0G6D2dIRRsAeO70eVp68VenxW+/0u1GIWrT\njBOFqJV6c6d8/PdM+XiKkMtUCE1LXw8taYDLJEYE6Q2X1eP9T4XJW5YMA5ZrhMnrSQlY5ghYgdU4\nAt44y1Oh3jjPzzg90GOEAfQRDV6YvIxkhrUxoSVxYZJzBOg18txIpEqGruR9+NZPzqqIAYVbHs4c\nK+pK7XDmyMsErzcoo4CCVHFnih4AGETHuhRt9Ty0eKsk/LWpinuRm2vEUOmfvMQvvJ9K5I4c/ph0\nZoseVwmfIGTkxYMSY8HAGL9k4wluWEmQMnNhiUIblii0bpIOAQCFeWL6RNAyzmvPm7lneWRSYhQh\nBgqLlR8vViv36E1LCcH442B2iOdEz46IXtGAlefDBywS9uw4H0swLnpXQ4l5Oo5QUvLYm+YPT5nc\nbjXREGW7RZzHsRm+30Zm+bd8eZwbLnqIfCIyTo08kyG+V0b93Js9OivKw758OofhSR5pNBy9SNdz\nKHKRtg/HuWIUJQbOujJ+ZjWW8vSJ59/sp0Y7xlY/GZ2gc+iLcONHjZvnldfk87zyYo0TKhZBzGW3\n5vI9bs3lEQTnu6KUw6OzU1RGX+m+QBWgYxe7ad8XZrrpenbPiOt5ZpwY1QzAmYlO2neOjadZydKy\nuie8dOwXx8X1fLGXV814qZfwfQB4a/Asbf/W0Fmh7ZDPhyn0pZ37U+iTMsSX51Tz1KFsHoWyWH1C\nvNBY9QmXw4Y7t6XvuX1by6XhstGw2LWmARFJFP6RhgN4/P4v4vOH/hSP3/9FHGk4wBti0UDB5pAZ\nKHRzBBDnA7B6dMFaUZlbTr+fSif/lvVEUMieZLJx30o50auVDFVQUHhvoYwCClJiPhmRn+ymYeJX\nz3Kl65jEm7+lgT+82+pEuVty4RdK5LKqBNs3iUrArlaex75bIrdbeZ58lo3Loa19Ejdt5SRpzVu4\nopOcK6AeoGRANLgsSIjmFkLcaBGL8RB3FiWytbKWPgy3VXhoH+2VLTS0ekcVz813WgqR8JVlhPmW\nIc8kKpKlJj6WUlMt7dtk44YIc5bocT89eYauz6lx7lmulih0nnyRlR8Aemau0Dz0nlkxT9zl4vsq\nz8kNMRcHuUJ/cUiUuy3FnEzTys+JEomCWg5xPUNz2dAi9rS11CJ2hAPcwLWvpp32fcDTTtvXuero\n3qpziWSA8wvc4+pfkJRA1aap0S6QFL3/2yvr6Bxuq+TVB6orrXRvVVVyhfbkyRidx3dOivs2PzuH\n9iGT1xYWUQ6P2mLx/JydsNDfOTPJPSrGAI+GMQbE8zbfynkz8q3cmJMnST/Ky+XyphIPHXtziUi+\n2urcSsfS4tpK+7bF+NjtUXHsehnibTkSI08Oj0qzOBd4NQmHmDrmn4/g1TPpRsvXzo5Ivbmv9nLD\nzWtXuOEGWIwY2FzSDKedp5ikMLfAy5HOkVLEeku0HtnNCXZlcj3w+ZKUv8fn43eqHqLB1qJGGDMW\n02gworlY5MEAbq2caNlTSEFB4b2HMgoo4Df3eaj8nju43CkhuMvNFh98fUOSmuyS6IRCqZdblOdm\n8Qemg4wDkCvodiLfLIlwaKvj8j1tvMrAbolcFm7E5vBI6zbqKb67dTvt4/27NiHmzXx8tODoTtFb\nWOuspQaEOpeH9t1CCLEAoNUjygtLEvRh6C7hBofmylIkpjOU/OlSNFXwORyZmF80dKTGry0aPgZJ\n1EJVXhk1IFTlc0KwMhmpXq74O40+kmuvAaZpD+1jb812mj99Rw1fTxl3Ri3x6rQVctLDtmJuWKl2\n1NP21Q5RWW6qLKWP2qZKvj45WXa6/tlZ4sPz8P6CNLI5g2GRfO7Ifr7f8vPMtG+ni3/juzdVIz7Q\ntqzsaUkDEgOt2LlJLHm3EON8GsEYV67yyv10LPnlYtTGzLRG53B6hisGraUeGJFu0DHBhNYybsyq\nqrLBYI2kz6M1iupKcc73ebhhZW9NB+07Ky9MOTyynKL7933tjfR3Ht7GjR8P7Gun3+eDe8VvwpbL\nq1pYHXx9uvt4akZ3P49kObilDvGB9LHHB5pxYIv4TezdRJQuDbijkef9791aQse+d5to/KjM5waE\nyjx+B73U9waPWvC+SdvH5nKo8SM2LxqF9LL4exyNdOy1Dq6k6sGJTh7ddOKCaMgMhfSljlSV5OJg\nR7on/mBHJSollSr0wFPuhGHak5bHb5zxrOqdP9JwAF8//Dl8rPxefP3w56QRFE57Lj7Z8TGYDYtn\nhdlgwic7PrZqpYKjez148nP34H88ug9Pfu6em5YTvbnOLaSHmowGWhpTQUHhxkIZBRTgctjwxw9t\nW0m2jT9+aJvUanzHVu7pvINUK3jgbv4IeEjGc8c2AAAXhElEQVRSmknPBdEoIStsksgXiCcBAAJB\n8YGg96IqL+aXb3kRlz8omxdSmiqajFMyq1iS/x6b2URJD80k3PzOVg81IOxt9dC+zRLCJdO7QMRk\nMEVhKsgkJhyXllRsaXTQvOXNjeKcJxIaYle2IXxuP6L9TQif24/YlW2IS/JEypx8nUud4oPck9NI\nvbO1uXyNW2oKSLynQVo67EDjVmq4OdAoeiOD8QhVDIJR7tFzOEy0fW6OuFc217rpvpIx4ZdKynSW\nkDKduWWEUM8AOEolhHrghphCI/fouRw2PHLXfUicvxuRC7uQOH83/uiu++gZ92D7Idr3Qx0Had+H\nN+3kRrumXUJbzQA6hzI47bn45I6PpnkL/2DHR6WPfac7QkPfnW5x/UdmpzkppZ+H7YZtI7R9yCam\nveg5g4BFVn5P7GDa9+mJHaSs/Hd6uPHszlpuzNglM9i28Kivxb1yP+LnFsceP3cIj9x1P90ri4SX\n6TKDEVLCy7uaW2hlg/3NYrWPoZkpniIzy8lRm136ohYObKmjhpsDbaLBSW+4+cHWZiQzjDxJXxkO\ntHDjpB7oWc8siQNDljoCAJ/5+A5887N34xP3t+Gbn70bn/n4jusbaAaWvfOwIxlwwwL7mrzzTpsD\nNdnlqyr4wKIB4Vsf/BI+f+hP8a0PfmnVFIyVY9rWWHRTWdNdDhsefWBrWtTCpx7YuiGY3BUU1hsk\nsc0KmThz5gz+23/7b/B6vWhra8OXvvQlVFWJXqb1iqN7Pdi3pQze0Tl4ypyrHsiyEPIoyYf/wJ11\nePLpTkRW/B2bxYjf3Mc9XakL4ts/PYt4QoPZZMAjH+IXhKz+tIzh+kBHJX7wgkhEdtd2MWzb5bDh\nwPaKRQKxJezfXiGdF9kjQyZvrXWjsSoPl1dUbGisyqOP4FRu4UrSodXYmZf1xxSJ0CrY1VaK5I+q\nEZ4phTErgGQoF4aEFbta+cOrWuIxYXJ7tBhaEmkhqlrSAHuch5s73GGq0DgKeCJqU5MZz7wptm8g\n9cQPtFfgB89fBMIOJMJXH1ds7QHgN1q34+fDT6Xlf2uaAXe3bhPa/t4HWvF//uM04JyApXgAsYlq\nYK4Yv/fpFtr3IglXusxg1DAbn0QlxPXavaka33y+FebqCzAYk9CSRiQGWrDzfvH8aSrx4C2vIW0e\nZaHPAHBgUzN+Qtrf2SSWpNzVVgoDFtnZU/vKYIB0r3xgbwt++WTLEgt58mq5y0+Ife8o24L/fean\ngryjnCs0u+rr8a1Xy4GCRUVV0wBtphw7arknGlj7GXewrRnfOVGDoL1/ue/scA0OtPIynRWuMuyv\n2YXjAyeWZftrdqHCKSopKWNjcsUcXssrdqThAPZUbseAfxjVropVw6v1rGdxQTbgFfsozufRWnd6\ntuPH3f8hyokynlIi4yt+57Vylr/+ZwfR1efDiycHcfeOKrRKopIqXGXYX50x39V8voGr3t+VZ/m1\nvL9r3SvjQyZoSXG+x0dMANkuTnsu/mjnx/Cdd36EhBaHyWDGH+zgIeE7PY34/iVjWgrBatUH3r+l\nHT/q+imwFM2haYC24MSRzdyIUlWSi/1V+/Dy6atn/8GtdXReUgrtP/37OcTiyWuGm7scNvxhx+/j\nn559DUnHBIzzxfijo/veFUVPz3ouf28ryIDW4oWuKslF1bsQHZAJPe+s64HTnovNdn5O3cq40fOi\noKCwNiijwBoQjUbx6U9/Gn/913+Ne+65B0888QT+7M/+DE899dTNHtq7ipTV+FpYfvCtCCdc7cH3\n4/95P5559Qp+fvwK7ttfhw/cKYZhrsTRvR60N+Th2FudOLC7DaVFIskgALTVu2E0GNJIaoyrXPh6\nHhPSHMrf2kwvrOt5fKz1EZzKLfzuqR8hloxfk51Zz1hcDhsee2gbnvjJGSQCbpiMwKcelEeJ7G4t\nXX5wpiBTDNtqypB8ZvNyGSYtaUByqA2t90tqeC+FSidxNb1gtVBpPe31KgaVbjf2FdyD13zPLyu0\n+9xHKPP3VQMPEJtbNHjIDDyAfiNPysv9Tz8vRcIyB1PMiT+6byddo4Nb6vDkKy0wV19VxOMDzThw\nP//mKt1u7HOv7Xem7ZUkFvfKA/K9okfp0KvouRw2fLL993QrHWs94/6fh/8KL3d24xedb+LezXtw\nsG31h/af7P0DPNh6FO+MnkdH2WZUuPgeTxk916pcpbDWx76e9dxZ1QLDOwZoK8IcDDBgR7XotQb0\nrZFeJTKF1lq39BxcibXOdwqf+fgOfPTwJpy4MI5dLSVrUvjWslcObKnDj4jh68Dd/MwC1m7kWVzL\nI2tay9R4P9n6GL793EtAwTAwXYFH3n9o1TnXMy96FbcbqeitddzX+73dSKz1DLrdoOZFQeHmw6Bp\nhH5WIQ2vvPIKvvrVr+Lpp58GACSTSdxxxx34wQ9+gPp6uWcqhWAwiAsXLqClpQXZ2SID/HrEs697\nhYv23cxJW+ucPfu6V4gquNY4BscD13xMnLk0ib954jVB/j8e3Se9uG70nMyFA2vyFl7PWPzzkTU/\n3hbnfLFOtNlkxCMfkvf97Ote/NPP305TZlcbx/M9x/DkqR8hnozDbDTjE+0fWTUMUm/7taz9Sgz5\nfDjZ34MdNQ2odK+urKzFwLNy3JlGnmuFe651jZ593YtvP30CSWsAxmguHrl/1zX3oZ7fOTY5e02D\n3UromfNh/+iaFT1A3769lXCjx73W9Xy+5xi+884PkdASMBlM+IOOj15zH+pZo/W6Pnrwte+fxMtn\nr6QZvt6tkHNA37cJ6P8+bwes5324Ed+PtzPUem4crKe1XOtYlVFgDfjud7+LU6dO4Rvf+May7MEH\nH8Rjjz2Gw4cPX/Pvr6eNowc38qLVM2c3Yhz++Qge/sKvhGiIJz93z6r/xq30+LiRY9HTt95Hqh7j\nx/W0v1VwI8d9q3ybCrc+xmYm8Nr5N7Fv8x6U5ksqziisCr3GxhsJ9X1uLKj13FhQ67lxsJ7Wcq1j\nVekDa0AoFEJWVnqeZVZWFkIhXgLodsGtEu51I8ZxveGvt8qcADd2LHr6duZYUVdql1ZcENrrzItc\nr3mUN3Lct9I+VLi1sVYiMwU5blQOuoKCgoKCwnsFZRRYA7KyshAOp5OdhUIh3Zah292IoAepubqZ\nc3ZwWzHaGw5gYHwe1SUOOHOsCAZ52SsFOW6FtVR496DWc2NBrefGglrPjQW1nhsLaj03DtbTWq51\njMoosAbU1tbipz+9yoydTCYxMDCA2lo5mRCD1+t9l0e28XErzJkJwPDAOIZv9kDWOW6FtVR496DW\nc2NBrefGglrPjQW1nhsLaj03DjbSWiqjwBpwxx13wOfz4Wc/+xnuvfdePPHEE6iurkZd3eos+pnw\neDxCGoICRygUgtfrVXO2AaDWcmNBrefGglrPjQW1nhsLaj03FtR6bhysp7VMjfVaUEaBNcBms+Hb\n3/42Pv/5z+MLX/gCWlpa8Hd/93e6+8nKyrrlyShuNag52zhQa7mxoNZzY0Gt58aCWs+NBbWeGwtq\nPTcONtJaKqPAGtHa2oof//jHN3sYCgoKCgoKCgoKCgoKCgrvGow3ewAKCgoKCgoKCgoKCgoKCgo3\nB8oooKCgoKCgoKCgoKCgoKBwm0IZBRQUFBQUFBQUFBQUFBQUblMoo4CCgoKCgoKCgoKCgoKCwm0K\nZRRQUFBQUFBQUFBQUFBQULhNoYwCCgoKCgoKCgoKCgoKCgq3KZRRQEFBQUFBQUFBQUFBQUHhNoUy\nCigoKCgoKCgoKCgoKCgo3KYw3+wB3A5IJpMAgFAodJNHsn6Qmis1Z+sfai03FtR6biyo9dxYUOu5\nsaDWc2NBrefGwXpay9QYU/qoDAZN07T3YkC3M3w+H7xe780ehoKCgoKCgoKCgoKCgsJtBo/HA7fb\nLf3/lVHgPUA8Hoff74fNZoPRqDI2FBQUFBQUFBQUFBQUFG4skskkIpEIXC4XzGZ5koAyCigoKCgo\nKCgoKCgoKCgo3KZQbmsFBQUFBQUFBQUFBQUFhdsUyiigoKCgoKCgoKCgoKCgoHCbQhkFFBQUFBQU\nFBQUFBQUFBRuUyijgIKCgoKCgoKCgoKCgoLCbQplFFBQUFBQUFBQUFBQUFBQuE2hjAIKCgoKCgoK\nCgoKCgoKCrcplFFAQUFBQUFBQUFBQUFBQeE2hTIKKNx0vPDCC7jvvvuwc+dOPPTQQ3jnnXcAAGfO\nnMGHPvQhtLe343d/93cxODh4k0eqsBY899xzOHr0KDo6OvDhD38Yp0+fBqDWcz2jp6cHW7duxcjI\nCAC1lusZX/7yl7F161Z0dHSgvb0de/fuBaDWdD1icHAQDz/8MNrb23H06FG88sorANRarkc8/fTT\naG9vR0dHx/K32dzcjGeeeQZnz55V67kO8dZbb+GDH/wgduzYgQ9/+MM4e/YsAPV9rle8/PLLy7rK\npz71KYyPjwPYYOupKSjcRAwODmo7duzQTpw4oWmapv3Hf/yHtmfPHm1+fl7bv3+/9swzz2ixWEz7\nx3/8R+2BBx64yaNVuBaGhoa09vZ27ezZs5qmadpTTz2lHTp0SItEImo91yni8bj20EMPac3Nzdrw\n8LBay3WOT3ziE9oLL7yQJlNruv6QTCa1++67T3viiSc0TdO0Y8eOaR0dHVowGFRruQHwve99T/ud\n3/kd9RZap0gkEtqePXu01157TdM0Tfv+97+v3X333eqsXacYGBjQtm/frj3//PNaPB7XHn/8ce1D\nH/qQFg6HN9R6qkgBhZuK0dFRfOQjH8HOnTsBAPfffz80TcO//Mu/IC8vD/feey/MZjMee+wxDA4O\nore39yaPWGE1VFRU4NVXX8WWLVsQjUYxMzODvLw8vPHGG2o91ymeeOKJ5e8TgFrLdY7u7m40NTWl\nydSarj+cOnUK0WgUjzzyCABg//79+Nd//VecOHFCreU6x9DQEP7hH/4BX/7yl3Hy5Em1nusQfr8f\nfr8fsVgMmqbBaDTCbrers3ad4tixY+jo6MDhw4dhMpnwqU99Cl6vFz/84Q831Hoqo4DCTcWuXbvw\n2c9+dvm/T58+jUgkgkQigbq6umW50WhEVVUV+vr6bsYwFXQgKysLly5dwvbt2/GNb3wDn/3sZ3Hl\nyhW1nusQ3d3d+P/au/+Qqu4/juMvvRpZrSlb1OwH3XWJbtOmNrzeLo2iiMEWQWblwM0V6SiZRRD0\nA7tl5ZpBRBm1xpxRFFTQ/aPb7xHTcrQlWpm1Vf5ihpX9NI2u3rM/xi6T7x/f7/74ejv3PB8gXN/3\nXPh8eHGvl9e953jy5EmtWLFChmFIElma2IMHD/TkyROVlJTI7XZr4cKFqqurI1MTamhokN1uV1FR\nkdxut+bOnavOzk6yjADbt29Xdna2Ro0aRZ4mlZCQoHnz5ikvL09JSUkqLS3V119/TZ4mFQwGNXDg\nwD6z6OhoBYPBiMqTUgCvjebmZn311VcqLCxUdHS04uLi+twfFxen7u7uMK0O/8a4ceN07do1eb1e\nFRQUqLu7mzxNJhAIaM2aNSouLtaAAQNCc7I0r8ePH8vlcik/P1+VlZXKzMxUfn6+Xrx4QaYm8+zZ\nM1VWVio5OVmVlZVavHixli5dqq6uLrI0sba2Nl24cEG5ubmSeL01q2AwqCFDhqi8vFy1tbVavny5\nCgsLeX6alMfjUXV1tS5evKienh599913evnyZcTlSSmA18LVq1eVnZ2tBQsW6IsvvlBcXJxevnzZ\n55ju7m4NGjQoTCvEv2Gz2WSz2TR37lwlJiaSpwnt2rVLLpdLKSkpoZlhGGRpYuPHj1d5ebkmTZqk\nmJgYZWVladiwYYqKiiJTk4mNjdXIkSOVlZWlmJgYffzxxxo+fLgMwyBLEztx4oSmTp2qhIQESeL1\n1qROnz6txsZGud1uxcbGKicnJ1Suk6f52O12bd26VZs3b9a0adPU09Mjh8Mhm80WUXlSCiDs/v6U\nY+XKlVq2bJmkv56A//z6TTAYVEtLi+x2e7iWif9BdXW1Fi1a1GcWCATI04TOnDmjo0ePKj09Xenp\n6ZKkOXPmaNiwYWRpUjU1NTp06FCf2atXr+R0OsnUZMaOHavOzs4+s2AwqIkTJ5Klif3000+aNWtW\n6Hf+dppTe3u7AoFAn1lsbKzee+898jShzs5Ovfvuu/L7/aqqqlJOTo4aGxs1YsSIiMqTUgBh1dTU\npMLCQm3ZskWZmZmheUZGhjo6OuTz+RQIBLR7926NGTOmz7k7eP1MmDBB9fX18vv96u3t1YEDBxQM\nBuV2u8nTZE6ePKlffvlFly9f1uXLlyX99W+zZs6cSZYmNWDAAJWWlqqmpka9vb3av3+/AoGAPB4P\nmZqMx+NRdHS09u/fL8Mw5PP59PDhQ7lcLrI0KcMwdP36db3//vuhGe+FzCkjI0NXrlzRuXPnZBiG\njh07pidPnmjy5MnkaUIdHR3Kzs5Wc3Ozurq69M0338jtduujjz6KqDyjjL+vHgWEwdatW1VRUaGB\nAweGLmQWFRWlffv2KS4uTkVFRWpsbJTT6VRJSYlGjx4d5hXjv6mpqVFxcbH++OMPTZw4UV6vV2PH\njtWNGzfI08ScTqfOnz+vxMREsjQxn8+nsrIyPXjwQE6nUxs3bpTD4SBTE7p7967Wr1+vhoYGJSYm\nyuv1Ki0tjSxN6tGjR/J4PKqrq+tzHRfyNKezZ89qx44dam9vl8Ph0Pr16zVhwgTyNKkjR46orKxM\nXV1dmjJlijZu3KihQ4dGVJ6UAgAAAAAAWBSnDwAAAAAAYFGUAgAAAAAAWBSlAAAAAAAAFkUpAAAA\nAACARVEKAAAAAABgUZQCAAAAAABYFKUAAAAAAAAWRSkAAAAAAIBFUQoAAAAAAGBRlAIAAAAAAFgU\npQAAAAAAABZFKQAAAAAAgEVRCgAAgLC4cuWKPv30U6WkpCg1NVV5eXl6+PChJKmqqkqzZ89WSkqK\nlixZok2bNmn16tWhxx4+fFgzZsxQamqqPvvsM/3222/h2gYAAKZGKQAAAPpdZ2envvzyS02dOlV+\nv1/ff/+9WlpatHfvXrW2tmrp0qX65JNPdPz4cSUnJ+vgwYOhx/74448qKytTUVGRfD6fPvjgA33+\n+ed6/vx5GHcEAIA52bxerzfciwAAANby7NkzxcfHa8mSJXrjjTf0zjvv6P79+7p586Y6OjpkGIY2\nb96s+Ph4uVwuVVVVKSEhQTNnztS6deuUnZ2t2bNn680335TL5ZLf75fNZtOkSZPCvTUAAEwlJtwL\nAAAA1vP2229rzpw5+uGHH9TQ0KDbt2/r1q1bSktL061bt5SUlNTn+JSUFD19+lSSdOfOHZWWlmrb\ntm2h+wOBgBobG/t1DwAARAJKAQAA0O/a29uVmZmppKQkeTwezZ8/XxcuXFBtba1iYv7z7YlhGKHb\nvb29Wrt2rTIyMvocM3jw4P/7ugEAiDRcUwA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      "text/plain": [
       "<matplotlib.figure.Figure at 0xfb8a53cf98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Export is successful!\n"
     ]
    }
   ],
   "source": [
    "md_text = '## Explore interactions between two numerical variables and a categorical variable (on sampled data)'\n",
    "filename = ReportMagic.var_files='tmp/nnc_int.csv'\n",
    "export_filename = 'nnc_report2.ipynb'\n",
    "silentremove(filename) \n",
    "w1, w2, w3, w4 = None, None, None, None\n",
    "\n",
    "if conf_dict['Target'] in conf_dict['NumericalColumns']:\n",
    "    cols_list = [conf_dict['Target']] + conf_dict['NumericalColumns'] #Make target the default reference variable\n",
    "    cols_list = list(OrderedDict.fromkeys(cols_list)) #remove variables that might be duplicates with target\n",
    "else:\n",
    "    cols_list = conf_dict['NumericalColumns']\n",
    "    \n",
    "w1 = widgets.Dropdown(\n",
    "    options = cols_list,\n",
    "    value = cols_list[0],\n",
    "    description = 'Numerical Var 1:'\n",
    ")\n",
    "w2 = widgets.Dropdown(\n",
    "    options = cols_list,\n",
    "    value = cols_list[1],\n",
    "    description = 'Numerical Var 2:'\n",
    ")\n",
    "\n",
    "if conf_dict['Target'] in conf_dict['CategoricalColumns']:\n",
    "    cols_list = [conf_dict['Target']] + conf_dict['CategoricalColumns'] #Make target the default reference variable\n",
    "    cols_list = list(OrderedDict.fromkeys(cols_list)) #remove variables that might be duplicates with target\n",
    "else:\n",
    "    cols_list = conf_dict['CategoricalColumns']\n",
    "    \n",
    "w3 = widgets.Dropdown(\n",
    "    options = cols_list,\n",
    "    value = cols_list[0],\n",
    "    description = 'Legend Cat Var:'\n",
    ")\n",
    "w_export = widgets.Button(description='Export', value=False, options=[True, False])\n",
    "handle_export_partial = partial(handle_export, w1=w1, w2=w2, w3=w3, export_filename=export_filename, md_text=md_text)       \n",
    "w1.observe(handle_change,'value')\n",
    "w_export.on_click(handle_export_partial)\n",
    "\n",
    "%reset_report\n",
    "%add_interaction_code_to_report i = interactive(InteractionAnalytics.nnc_relation, df=fixed(df),\\\n",
    "                                                conf_dict=fixed(conf_dict), col1=w1, col2=w2, col3=w3, Export=w_export)\n",
    "hbox = widgets.HBox(i.children)\n",
    "display(hbox)\n",
    "hbox.on_displayed(InteractionAnalytics.nnc_relation(df, conf_dict, col1=w1.value,\\\n",
    "                                                    col2=w2.value, col3=w3.value, Export=w_export))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <a name=\"pca\"></a>Visualize numerical data by projecting to principal component spaces (on sampled data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Project data to 2-D principal component space (on sampled data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Anaconda\\envs\\py35\\lib\\site-packages\\sklearn\\utils\\validation.py:420: DataConversionWarning: Data with input dtype int64 was converted to float64 by StandardScaler.\n",
      "  warnings.warn(msg, DataConversionWarning)\n",
      "C:\\Anaconda\\envs\\py35\\lib\\site-packages\\sklearn\\utils\\validation.py:420: DataConversionWarning: Data with input dtype int64 was converted to float64 by StandardScaler.\n",
      "  warnings.warn(msg, DataConversionWarning)\n"
     ]
    },
    {
     "data": {
      "image/png": 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pz6I3m80sW7YMBwcHfH19LVxh9ijQi4iIiIiI1bl48QKHDu2kcePnKVmypKXLESvxyiuv\nsGnTJkaPHs2pU6fw8PBgy5YtHDp0iFGjRuHm5mbpErNFgf6OwMBAHJ6QezsehVq1amFvb2/pMkRE\nREREHtoffwSycKEv9euHMnVqZYYP/4EyZcpauiyxAg4ODqxatYrZs2ezadMm4uLi8PDwYNq0abRr\n187S5WWbAv0dC9ad4uL1WEuX8Uj8GRHOkolQv359S5ciIiIiIvLQtmxZTZs2odjawnPP/c6OHf9H\nv37DLF2WWIlChQoxYcIEJkyYYOlSHpoC/R353criapNs6TJERERERORfNGniw/ffL+WZZ67z66+l\nePnl5y1dkohFKNCLiIiIiIhVqV+/CcnJX7F37yb8/LpQrVpNS5ckYhEK9CIiIiIiYnUaN36Oxo2f\ns3QZIhZlY+kCRERERERERCT7FOhFRERERERErJACvYiIiIiIiIgVUqAXERERERERsUIK9CIiIiIi\nIiJWSIFeRERERERExAop0IuIiIiIiIhYIQV6ERERERERESukQC8iIiIiIiJihRToRURERERERKyQ\nAr2IiIiIiIjkOSdOnKB69eocOHDA0qU8MAV6ERERERERyVPCwsJ47bXXSEtLs3QpD0WBXkRERERE\nRPKMH374gZdeeomIiAhLl/LQFOhFREREREQkTxg4cCCvv/46xYoVw9fX19LlPDQFehEREREREckT\nwsLCGDZsGOvXr6d8+fKWLueh2Vq6ABEREREREZHHYcuWLdjZ2Vm6jBxj8TP0J06coGPHjtSpU4ee\nPXty4cKFe9rExsYyYsQIvL29adq0KZMmTSIlJQUAs9nMRx99RMOGDWnSpAlLlix53F0QERERERGR\nv7hx4waHDx8mKSnJ0qVkkJvCPFg40CclJeHv78+AAQM4fPgw3t7evPXWW/e0mzZtGsnJyezcuZPN\nmzdz6tQpli1bBsDKlSs5efIkP/74I1999RVff/01u3btesw9EREREREREYDDh/cybVoDfv3Vm+HD\nWz1xoT43sWigP3jwIK6urvj4+GBra8uQIUO4cOECwcHB97QdMmQIjo6OFCpUiLZt23Ls2DHg9iUT\n/fr1I3/+/JQtW5aePXvy7bffPu6uiIiIiIiICPDDD5/j6xtG9eqpeHntJSAgwNIl5VoWDfQhISFU\nqFAh/bWNjQ3u7u6EhoZmaDdhwgS8vLzSX+/evTv99d/34eHhQUhIyCOuXERERERERDJTunQNQkMd\nAAgLc6dcuXIWrij3smigN5lMGI3GDMuMRiMmk+m+20yfPp2QkBD69euXvg9HR8f09Y6OjiQkJDya\ngkVEREREROQf9e79NjY2k9m/vw9du66maNGili4p17LoLPdGo/Ge8G0ymXBycrqnbWpqKuPHj+fw\n4cOsWLGCAgUKALcDfGJiYnq7hISETLfP6xISEoiPj8/WNne/WPmnL1jyIo3L/WlsMqdxyZzG5f7+\n+r4mIiJibQwGA6+88o6ly8gTLBroPTw82LBhQ/rrtLQ0wsPD8fDwyNDu7uR5MTExrFmzhkKFCqWv\n8/T0JDQ0FE9PTwBCQ0Pv2V5uj8uDftERFhaWs8XkEhqX+9PYZE7jkjmNi4iIiMiDsWigb9SoERER\nEXz77bf4+PiwaNEiypYtm+GeeICJEycSExPDihUrcHBwyLDOx8eHJUuWULduXWJjY1m9ejXvvffe\n4+yGVfDw8KBq1arZ2sZkMhEWFkb58uXvuTUiL9O43J/GJnMal8xpXO4vKiqKK1euWLoMERERecJZ\nNNA7ODiwePFixo8fz4QJE6hatSpz584FoG3btgwePJjmzZuzbt067OzsaNSoEXD7Eo569eqxePFi\nevXqxfXr12nfvj0A/fr1o3nz5pbq0hPL0dHxgc/QG41G3caQCY3L/WlsMqdxyZzG5V66DUFEROTR\n8/f3x9/f39JlPBSLBnqAatWqsXbt2nuWf/fdd+k/nzlz5r7b58uXj5EjRzJy5MhHUp+IiIiIiIjI\nk8iis9yLiIiIiIiIyINRoBcRERERERGxQgr0IiIiIiIiIlZIgV5ERERERETECinQi4iIiIiIiFgh\nBXoRERERERERK6RALyIiIiIiImKFFOhFRERERERErJACvYiIiIiIiIgVUqAXERERERERsUK2li5A\nREREJCumTp3Kl19+ia2tLWazGUdHRw4cOGDpskRERCxGgV5ERESsQlBQELNnz6ZFixaWLkVEROSJ\noEvuRURExCqcPXsWLy8vS5chIiLyxFCgFxERkSfejRs3iIqKYsqUKXh7e9OtWzdOnDhh6bJEREQs\nSoFeREREnni3bt2iYcOGDBo0iF9++YXOnTszaNAgoqOjLV2aiIiIxegeehEREXniVa5cmeXLl6e/\n7tKlCytXruTo0aP85z//ydI+EhMTiY+Pf1QlPlYmkynDn7mB+mQd1KcnX27rD+TOPiUmJubIfhTo\nRURE5Il39OhRgoKC6N69e/qypKQkHBwcsryPK1eucOXKlUdRnsWEhYVZuoQcpz5ZB/XpyZfb+gO5\ns08PS4FeREREnnj29vZMnz4dLy8vatWqxZdffklycjL16tXL8j5KliyJq6vrI6zy8TGZTISFhVG+\nfHmMRqOly8kR6pN1UJ+efLmtP5A7+xQVFZUjXzIr0IuIiMgT76mnnuL9999n9OjR3Lhxg6pVq7Jo\n0SLs7e2zvA8HBwecnJweYZWPn9FoVJ+sgPpkHXJbn3JbfyB39Smnbh9QoBcRERGr4Ofnh5+fn6XL\nEBEReWJolnsRERERERERK6RALyIiIiKSx9y8eZO4uDhLlyEiD0mBXkREREQkD1n0zjtsrV6dpTVq\nsHPdOkuXIyIPQYFeRERERCSPSEpKInXdOnpfv86boaEELF5s6ZJE5CFoUjwRERERkTzCzs6OyIIF\nMQMmIKVwYUuXJCIPQYFeRERERCSPMBgMdFy2jDmTJ2MoWJABc+dauiQReQgK9CIiIiIieUj1evWo\nvn69pcsQkRyge+hFREREROShrZowgfkNGvBxu3bExMRYuhyRPEFn6EVERERE5KEEBwfjNHs2vaKi\niAeWjRmD/4IFli5LJNfTGXoREREREXkoqamp2KWmApAPSEtJsWxBInmEztCLiIiIiORxm5cs4fyG\nDdhUqMDAOXOwtc1eTKhcuTJ7hgxh/vffE128OEOmTHlElYrIXynQi4iIiIhYiWtXr7JuxgxKV61K\n+379MBgM2d5HUlISQUFBlC1bloIFCxIcHEzcmDH4R0Rw2WBgVZEivDxmDPt//hl3T08qVq6cpf32\nnzoVpk4lPj6eyMhIChUq9ED1iUjW6ZJ7ERERERErkJSUxGc+PgyYOZPy/v58OXlylrb74/RpZnbo\nwIwuXQgLCWFSy5bcrFePhQ0a8Mfp00Rcu4Z7VBQAxc1moi9dYrKPD24+Phxq2pQfvv46yzUeO3aI\ncePqsnJlTcaO7UJaWtoD9fXvUlJSSE5Oxmw2c/36dZKTk3NkvyLWTmfoRURERESswLVr16gdFoYd\nUCshgV+OHcvSdt/068fYX38lDRgdGkqv336jJtD899+ZP38+ry1YwMcdOhB04ADnS5SgTZ8+3PDx\noSZQ88YN5q9fz/PdumXpWN99N5f27YMwGODIkW2cO3eOylk8w38/21as4MykSRhSUznr7EyLq1cJ\nKlmSXuvXU75ixYfat4i1U6AXEREREbECpUqVYkmNGtTcs4eThQpRvnXrf2x//vx5HBwccI6NxcDt\nyerczGaOlCxJzStXOOHoSOmaNbGxsWHs2rXExcXh5OREQkICM8uWxffUKYLs7SlQo0aWayxYsCyR\nkeDmBjduFKVIkSIP12kg8NNPeefcOQAmAV2BtJs3mT91Km8sWfLQ+xexZgr0IiIiIiJWIF++fIzZ\nto2f1q2jfOXK1GrQ4L5t584dQWzs5yQm2mNq1JDP/vyTJFtbar/xBi5ubsxfs4aiderQdfDg9G2c\nnZ0BMBqN9Nq4kU9nzaJ4lSr08vfPco1Dh05i3rxkTp8+j69vfwoXLsz2//6XP3bvpmG3btT/z3+y\n3e9EZ2fMd36OsLWFlBQu2NgQGR/PJ35+2JQuzcA5c7C3t8/2vkWsnQK9iIiIiEgO27BgAec3buRW\noUJUWro0x/ZrNBpp27Nnput+/PprAletwlyqFJcK7cbH59bt5T9G8MrZs9jY2ODo6AhAo9at+XXf\nPkJDQqjg6XnPvsp5ej7Qc+RtbW15++2Z6a9/WruWfEOH4h8dzdLvvqPwzz/j6eVF8JkzrBk4EGNs\nLB4DBtDhtdfuu8/uixczc9gwDKmp1GralPmHDpFUujTFNm9maHg4N4Fljo4MnjUr2/WKWDsFermv\npKQkTp8+TXx8fPp//rlNrVq19G2uiIiI5KigwEBS33uPt27d4qLBwNdeXgycOPGRHW/1xIlcX7+e\nPwID+TgxkVSgx3OuJCTcvvTdbC6Gk5NTenuz2czkjh1pvXUrBwsXJmjGDNq88sojqS3wl194LToa\ngBaXL3P6yBE8vbzYMGYMY/btwwB8MnMmSQMG3PczWbmKFRn+7bcZlp07d46zK1cC4AYkXL36SOoX\nedIp0Mt9nTx5kln/PUJ+t+uWLuWR+DMinCUToX79+pYuRURERHKRiOvXcY+JAaCE2UzstWuP7Fih\noaE4zprFO1FRmIDPgWa2UKtOPK3bwm+/2eHh0QGAmJgYtixfTiF3dyofOkSDtDQa3LzJ/A0b4BEF\n+lYDBjBryxaeDw5mfe3avOXre3uFwYAZMABpBkO2H2/n6enJ+nbtuPXjj1woUoSOI0bkeO0i1kCB\nXv5RfreyuJaoZOkyRERERKxGo2ee4eMOHTh+4AB/uLoydPToHD/Gd999TXBwAI0a+WFrvn2HuQ1w\nxsmJQ2UL0b7hJQBq107m+PEAkpOTmfHCC/gfPMjhAgX4NX9+ugLh+fJhXylnP+uZzWZWTZxITGAg\nNV56iV779xN44gTvNGxIgQIFAOg6cyZTY2JwjI3Fa/Bg7OzssnUMg8HAyC+/JDIykvz582d7e5Hc\nQoFeRERERCQH3Z01PjIykpCQEEqUKJGj+1+5chYm03tUrRrPqlXbqDFgAPO2byemWDFGL1tG/vz5\nGTOmBbduHcNotKd48fNcuHCBBmfOUAzwjYnhaNOmzGrVigRbW4bk8BcOX8+aRaNJk6icnMyy3bup\ncOgQzZ5/PkOb6xcvUuSZZ2jTrx9lypV74GMVLlz4YcsVsWoK9CIiIiIij4Cjo2O2LyX/N59/Ppk9\ne+bi6hpPpUpQtmwwrbqsw2P69AztqlTxoUKFYxQokMS5cxs5c6Yr+ypU4Pzx40TZ2VGsfn2ur11L\n29OnWbR3L69s20bpsmXTtzeZTHwxZgyJt27Rcfx4ymUycd793AwKolJyMgA1rl7lQmgo7u7u6ev3\nbNrEjVdfpefNm8xds4b+e/fmyOPtRPIiG0sXICIiIiIi/+7Qob3ExEyhb9/rNGoEmzbBhQvVKVOm\nzD1tjUYjqam3f05NtcFodMLs7EwvoFtyMtvnz8f/9GnqAO8EBrL1888zbP/ZoEF0nzuXN1au5IuX\nXspWna3ffJOPq1ThexcXtrRoQX1v7wzrA7ZupfPNmxiBtkFBnDx8OFv7F5H/UaAXEREREbECkZE3\ncHWNA6BwYYiLe54pU3bcc//49evXad78RY4d68YPP9QjOnoA//lPG/KfOkUBwBOoHhHBZhcXADY7\nO1OrefP07ePj48l3+TKu3A4LRW/eJCUlJct1VqpenTeOHKHy8eO8t23bPfXVad+er4sVIwrYVLUq\ntRo2zP5giAigS+5FRERERB67lJQUzGZzlidzM5vNVKpUg59+8iUo6CQmU1mmT/8GlzuhHGD/tm18\nOnw4xnPnqGRjQ9HevXl94f/OfoeXKsXZ6GgigThbW47Z2hIDmJOTMQcFUdPbm6kdO1ImIICTRiPL\niheneFwcSS1bYmt7/9iQmprKri1bcC1ShKcbNwbA2dkZz/tcpt/Ex4eATZvYvHs3fXv00H3wIg9B\ngV4km5KSkjh9+jTx8fE4OjpaupxHolatWvd9FqyIiIg8nO2rVnFqwgTypaXhMWwYfkOH/mN7s9nM\nxy+9RPW1HBmRAAAgAElEQVQdOyhTpAgNP1uC998mmdu7ZQuLhnSkcPlkipUCt1C4sGkTKfPnp4fx\nuUePMuyFFzDeuoVTrVp0W70aT2C0VxIX/3iHb1+ZyfBt56gAFDDC4c49aPLue/hUrnxPTWlpaXy1\nYAH7Fy2i4Pnz2MXE0MjZmdWjR9Pz3Xf/dQxqNmxIpZo1WTF+PFcuXMDFyYnKjRrhN3BglsdRRLIY\n6K9l49mZxYsXf+BiRKzByZMnmfXfI+R3u27pUh6JPyPCWTIR6tevb+lSREREcqUzCxYw7Nw5AGYv\nWgT/EugvXLhA1R07aB8dDdHRfLLk3kC/ccVyvF5JpmkLuBUBZ4dAmJ0d+fLlS2/j6OjIgt27AYiN\njWV6YCAFfv+Npu9B0aImTKZzfL7HFnP5FBr7Q/Kvmzh0sCmVK1fm6P79XDx3jqZt2wLw2dChJK9e\nzWSzmfzATsAlLo4/du6ELAR6gPl9+tD1m2/4ChgOHPvqK9aaTLz45pvEx8ezfORIkm7dov277+JZ\ntWqW9imS12Qp0Ddr1uy+M3SazeYM6wIDA3OmMpEnWH63sriWyNlntoqIiEjekOjkhPnOzwnOzv/a\nvnDhwoQUKwbR0VwFHNzd+embbzizejU25coxcNYs7IsXwbXo7fbO+WG/PXSfOPG+n+FPHj5M6lNP\nEeAAhJ+maNEELl92JKhEGbr2O0fp0lC6459s6D+UA/OW0vbcORyjo3nbaKRkzZo4REdTymwm7c7+\nUoEbgPkfnmlvNpvZ//PPGAwGvP/zHxwvXSIaaAwYgLoJCRw4ehSAhYMH03/VKvIDE86cYfzRozn+\nxACR3CBLgX7Hjh3pP//yyy+sXLmSUaNGUaNGDezs7Dhz5gxTp07lpWzOgCkiIiIiktd0X7yYGcOG\nYUhNpfOUKf/a3sXFheZLlzJ3wQLOBgVR6bvv+L8FC5iemEgcsCJ/fl4b/R59WnxOSI0UooPB+88C\nNGvRAoBDP/7I4Y0bqde+PY1ateLzsWMJWTaVJNc08l+AM5GFuXXrWVLiCzP09038sgkqvgMn9sFz\nN8z8cuk0vgkJfAz4mUxcOnSIPUYjLwIzgFRXV6I8PfHu0oWhw4fftx+f+vtTZ+lSzMBnAwdSuE0b\nzp48yd4//8TNbOZQyZLU6toVANurVylwZ7tikZGkpKRkeb4BkbwkS4G+7F+eSbl06VJmzZpFnTp1\n0pc1btyYiRMnMnToUF5++eWcr1JEREREJJcoV7EiI779NsvtY2Nj2Tp5MjGBgbx46RItUlOJA1YC\ng4G4S5coXbo0M1fs5dPBgyllZ0fDJcMpXbo0J3/9lT969sT/2jW++r//w3HjRn79cQ3eH6ZR3gvW\nLwO/L6Mo5TeJgO3baRn/NVW3wTfHICIaXo+FjSVcOXbtGpFmMzbA64CPycSSTp2o26IFnQYOzHTS\nvFu3brFy+HDMKSl0mzKFtH37aJyUBMCx/fspOmUcW/t6kmTKx/EGA3juuecp7+EBQOVevVgSGEiR\nP/8kuU0bhXmR+8j2pHixsbGZLo+Pjyc5OfmhCxIRERERkf9ZOHo0Ttu3kwL8eWdZMnDKyYlJFSrQ\nbeRI4PZEcwuPHcuw7dGff6bjnfmwOly/zn9/+IFYN1vK3Znnrpo3bAyoxmc1a+JZsSIzvv2W+r//\nTnIpLyp2e5b5UVF8OG4cC956i6BNm+h+Z79lAfcyZeh65/7/uLg4pkzpA1zB07MdffuOYlHPnry9\ndSv5gKnnz5PPw4NrJ06wJT+cLuhA8Pfj6NDhLGYz/PBDMXq8+r8J8Vr36sWN1q2JjY2l452QLyL3\nynag9/X1ZeTIkbz99ttUqVIFs9nMyZMnmTNnDl26dHkUNYqIiIiI5Ap/n38qK0K/+47ZQCLgDxy2\nscGQlkaUoyMvTZlCperV0/cdHx+P81/uy2/RvTufLl9O599/Z0OlSnTr2ZN6fj7Mm92GajUiOX78\nKebt3oODgwMODg6M27ePy5cv80Lp0ulnxS9eDMdYx5ESbt5M33OVZlExXChXjjfGjk0/zmefjaNx\n47U4OcHevYGEhHTBOSIChzvrC0RE0P/773ml61N06hFC1evHCQgwAnB7OO49MVi0aFGKFi2arbES\nyWuyHejHjRvH7Nmz+fDDD4mOjgagUKFC9OjRg6H/MkOniIiIiEhe9fXHH3N16VJMzs68MG8edZ99\n9r5tY2JimPfSSxS4fJniMTHYA/ZAYQcHPkpMvL2/yEi29u5NjeBg4uPjmDzZj0KFrpKS0pDJk9di\nY2NDmXLl6PfLLxzbs4dXmjaleIkSlKUCM+b8wcWLF3n9Da8Ml7Pb29tTvnz5DLXMmfMKbdrsAmCL\n67NU7TCRnk8/neGLg6SkeO4+8dbBIYGEhASKv/giq0JDsUtNxbFtW37+eRtuZWIpUQJKlDBx5Eg5\ntmwpSXy8DU29X8JsNnMpPJx9mzdT//nnqeDllRPD/ljcuHaNLwYPxjYujsbDh9OwVStLlyR5RLYD\nvZ2dHSNHjmTEiBHcvHkTgCJFimjWSRERERGR+0hJSeH64sW8FRoKwOwpU/4x0K96913e3rYNJ2CU\nrS2bjUYSHRywqVOHk7t24WU2EwjUuXWLmf364dKwBJ06HSVfPjhzZhMHDuyjSZNnAChWrBgvvPgi\nZrOZOXOGExUVQMmSjRk06INM61z01lvE/vEHZ90uU7K8HWFhl7n79Ds7uxicnZ3v+ezfv/8kpkwJ\nwsHhKoULP0+1atWoVq0aV3r0IDExkdmzXyXftY9xcbFj3z5wd7enXr32lEoriXnCBIotHcqE9Vtw\nDgjgleBgvilblhabNlGlVi1SU1M5fuwYJUuVolSpUjnx68hxXwwZwtsbN2ILfHzpEg1OnVI+ksfC\n5kE2unTpErNmzWLixIkAbNy4kRMnTuRoYSIiIiIiuYWNjQ0JDrcvQE8FUh0d/7G9IV++9EfCPevo\niPmrr6hz5AgzfvqJld270doZXIALQPHwcFxdSxIZeTtARkYWpGjR4gDsWr+eTzp0YMHrr/PVVwsp\nXPgTmjf/gYTYCQxqXIeIiIgMx105YQKdPv0U89kddO9zilatjlGjRjRff12cHTvKULVq9/S20dHR\nHNy/n/DwcN719SV++w1aNfyYkSPnp7cpWbIkBoOBUqV+o0IF8PVN5o8/qmE0fsrrr3/Mlc2b6XLr\nFs2SknDcvZvewcEUBQaFh7Pz669JS0tjUvv2mBo1Ymv9+uzeuPFhfg2PjG18fPqZUqf4eFJTUy1a\nj+Qd2T5D/9tvv9G/f3+8vb355ZdfGDFiBL///jvvvfcec+bMoWXLlo+iThERERERq2VjY0OTGTOY\nPWsWyU5O9F6w4L5tzWYz5ooudGxqpFSJFJKTSrD0+edxcnLizJkAIlPWMXAp/PwF+O2AkPr16d9/\nLLNn3+DMmWCqVm1P5cqVuXnzJoFvv80b4eFcB0aFN+bFgbfvVS9e2kyRk8dZMGQI9jY2nIw5jkfd\nahjOGShuNmeox87OgYEDt+Lp6YmdnR2BgYFcvXKFL/38aH36NB/Z2TE0OZmiwPu9e9PgyhVcXFzS\nty9evDgXL7pTv340Fy/a4+39El26vApAarly3AQKArfc3Vnn4sLA8HC+KlmSxn5+XLx4kdr799M0\nNZWmly8z/8svadahQ87+cnJA05Ej+fjiRZzi43Hr1y/TWf9FHoVs/02bNm0ab7/9Nr17905/dN2o\nUaMoWrQoc+fOVaAXEREREclEE19fmvj6/mu7tWuXcfnyx3TolkL16hAXd44lSybx5puT+frrT3l5\nYBL58oHvEFh8uQwbP/sMg8HAiBHzMuwnIiKCchERJAJFgCoOpdm82RuHuIPYHTXzfiwM2LYNQ8k/\n6T0HHB2DWHOzGhNq16bY5cssnmGg0tMlKVPGl7p16wK3n2wFsGPFCt45fRpnoHJyMm8D1QFjfDzx\n8fEZAr2joyPN6rzBondG45xoS+dh/7tsfujChawoUQJTZCRvf/ABkVeuMG/VKhr6+lKrUSNMJhNn\nSpakfVQU5/Plw1ip0kP+Fh6N+s89R72TJ0lLSyPf3fsTRB6DbAf6oKAgZsyYcc/y559/njlz5uRI\nUSJinZKSkjh9+jTx8fE4/sulhNaqVq1a2N+d9UdEROQBfDV1KhF791KgXj16jR9/z73W4eGBlCiR\nQkrK7depqZAvny2XL1/i3LntpKZCy5aweyPEhEXwfq1aFHv2Wbp/8AHLhgzBNiaGBm++iXfr1kx2\nc+OsyUSQvT3d+/ZlVJs2fPHBB/x5ZjPvNbTD9/BhfncD4+0J5ylYMJ5xvx7HZDIxtECB+/aheuPG\n/FS4MO0jI9lkMDDEbKY+MMTOjmLFit3TPnz5StaciARg5ief4Nu/P3B7Er4Bkyent9v3zTfYr1vH\n0XXruD5qFH5Dh9L5m2+YN2sWrp6e9Bk9miUjR5L42284PP00/adOfWLuVTcYDArz8thlO9CXLFmS\nkydP4u7unmH5nj17nthJKkTk8Th58iSz/nuE/G7XLV3KI/FnRDhLJkL9+vUtXYqIiFipX7ZupfTE\niXSPi+Pojz+yrVIl2rz8coY2PXuOYOLEn4mIOMNvv9lTqlQLxowZxurVc+ndO4yQEPjmG3DeApX+\nNBFx6iR7w09yaO8uPj9xGntg+vnzOBYrRu9r12iRlkZqQgIL1q2jeZs2NPDz47CjIxXj4njh0CEK\nnYHvF4G5lB0lSnfAzs4uw8z3mXn62Wc58NlnzN++nXMHDtArMBCAin+bIf+uZHt7zIABSPmHL8Yv\nfPEFb4aHAzB32TIYOpTKTz1F5WXLANj65ZfU/+QTaicmcmzfPrbXrUvrbt2yNPYiuVG2A/2bb77J\nu+++S2BgIKmpqWzatIlLly6xefNmpkyZ8ihqFBErkt+tLK4lnszL4URERCztckgIz8TFAVApIYG1\na9dy9pNPSHByolSrVtxcvZpUW1temjiRCnXrcmjDBi7NnMnKNbVJ6OZHQFxhGjSIJDoYrkVDMQPE\ntoM3+sLmr08TchqqpED++Hhc8ucnqEABuHGDSMCpWDGO79/P0Rdf5MUrV/jUw4Op1apRLTCQkK35\nefqNN+jaddA9NQccOsSPH32E2cmJrtOmpS9v0bUrLbp25ZfNm5k6ejT2iYl43Ocx1p3nzePtwb25\nYXOJKk2fxmw2Z3pmPb5AgfTJAOMzuULg1rVrPH3nsX0lExMJvHo1m78Bkdwl24G+devWlClThuXL\nl1OhQgW2bduGh4cHK1asSL+3RkREREREMkpNTeVKQAAzXF2xSUnBsUYNCp04wdshIZiBwUeOsPDP\nP/kE+LFbNyK8vDAEB+MVE8MA4LMf9lJ5wgJ++mkjQXsDcHjKyPWQo3R7FQoUgG6vwvgAN56Nd8G5\nRw+8vLwImjiReevXYy5blsEffMDi0aN5KvoKc2oAkaG4tX0d+6tX+SYyknmTJjFh2RyMbRtRvkoD\nEhIuUqFCQ85NXsTYgACSgZkJCbR67730/tjY2PBMu3Y0bdsWs9mMjU3mD9HK7+aGg/dNBrS5Snj4\ncr74oiJ9+44AIC0tjRPHj1OseHF6LFvG7JEjwWCg1/Tp9+yn89ChTN2+naJBQdzw8mLU4MGP5Hcl\nYi0eaPrFp556ipkzZ+Z0LSIiIiIiT7y9W7ZwfPt2nunenVre3lne7uvZs+n8+ee4p6WxzdmZQh9/\nzIG+fdPXGwwG9gP1AK/4eNYcO8ZrwE3gcyDOxYUyZaoxePAzlJ5YGoAedWuy8rOTlKwIocEw4rOv\naNy4efol8+0HDYJB/zvrXr1FC765Mpeug9K4eQPWLd/D6MhIDEApJ0h4NZYGz/3I5s0/UauWmYiI\ndew0JxHzIqSdhiJRUQBsmDuXG0uXkujoSNNp02ji6/uP97KHh4dTtuxFAMqWTWb//tuX6JvNZiZ3\n6sQzW7dyrEgRys2Zw7C1a++7H0dHR97fvp3U1FTdry7CAwT6lJQUNm/ezMmTJ0lJScH8t8da3H02\nvYiIiIhIbnNg+3ZuvvIK/hERLNqwgfw//USFypXT18fHx7Ptv//FvXJlqterl2HbP69fp0ja7QvK\nS5tMXLt1iwojRjBn4UJMTk60evVV1s2fzwsBAUSlpeEOJACFgSMlSlCglhM//ViPC2G2FLDtxvsz\nP6dahcpEFzyJT2eIj4etW5fRrNnz962/dKVKlK/tAJhwKwJlqpZi3ulbdA4P55v8MLj57XaNGpkJ\nDISmTePw9IY23eHGDTi6rzxms5mry5YxLCQEgNkzZ/7r7P21a9dm9epmpKT8Qni4Oz16DATg+vXr\nVN63j2bJyTS7coX5X31Fi65d//X3oDAvclu2A/17773H1q1bady4cYbHUYiIiIiI5Ha/bd/OaxER\nALS9eJFff/klPdCnpaXxcZs29N+zhzMFC7Lp/fep9Oyz6dt2GzuWqQcPUiw8nKinn2ZU27a3g+lf\nLhvv9OqrLB01iqCdO9nx228Ep6VxBkgrUoQCBX+jTt1k6tRNZvOoFaz7pBYulSpx9/yaoyPY26fx\nTypWrEjkrTbs37+TGzeK0bv3+xR+rSibV6/G/bdDrP7iVxo2ucnWrY40aJDEwmlQv3kap07BkSM2\nPP10JQwGA4l3psVPBZKdnP513Ozs7JgxYxuBgYGUKVOGwoULA1CoUCF+L14c882bXDIYsKtQIau/\nChHhAQL9tm3bmDdvHs/+5T8nEREREZHcKCEhgYULxxMfH0W/fhN4vk8fPtmwgXZhYXxVrRoD2rZN\nb3v9+nVqnjlDWaBsdDRzd+7MEOhdXV35YM+ef71cvP/Uqfy6fz+1mzThWSAFGHzxIsHBrri4QLEi\nUOJqGlePHeON5csZ1GsvX686QZqhLGPGTc6wr+TkZKKioihSpAgGgwEbGxumTFnLpUuXKFy4ME53\nwviQ8eMBWLZsKkeOzKdgwQR2rU9i2okYlp8F157Qu3ca3323lEqVnqbZ9OnMmjWLVEdHes6fn6Wx\ntLOzo2bNmhmW2dvb0+2bb/hk+nQKlCtH/zv354tI1mQ70Lu4uFC6dOlHUYuIiIiIyBNl2rSB1K69\nCicnmDLlFHPn7sd5924C9u9nUMuWFClSJL1tkSJFCChfnrY3bxLo6Ej+OnUy3ee/XS6emprKttmz\nSTUYCDCb6QQkeZbH1TWCEiXg+6+hdmJRnu7eHYPBwOLVv5CWlnbPhHThISEs79gRrytX+L1hQ8Zu\n2ICtrS0Gg4EyZcpkeuwzZ76ga9fb97p/8w0sdYVSv0OTlrfX16kTRnDwafr2HUKTF17I4ij+s4rV\nqvHm8uU5si+RvCbzaSj/weDBg5k8eTLnz58nLe2fL+kREREREbFmKSkXKFAAbG3B3v4yISEhlHZ3\nx6dbtwxhHsDW1pY3t23ji9GjubRwId1GjXqgY65buJDe69fzodlMY2B8o0bU6dEGP78LlC0L3QeD\n3chBeP8lUGc2u/zGqVN5LyCAbjdu8MLWrRw+cOBfj52WZrzzJ6SmQtHGDpyv8gzbthXj5k04dKgq\nVatm/kWFiDx+2T5Dv2LFCi5fvkzr1q3TL9v5q1OnTuVYcSIiIiIillSpUnv27g3AaPyTi9siOLmk\nLv/n48PIL7/MdFZ3Nzc3Bk+ZAtyeIO9BJJpMGO+cOCtgMNBu4EBKVPPkp5+W0rjxDY4eLUGnTh0z\nbLNn0yaOfvopKa6uDFy8mAIFClCofHmO29iQlJbGmcKFaZ6Fq2y7dZvD55/7c/NmEHXqJPP7qcrU\nDLlE1O92HI7qzvDRk4m4M4eAiFhetgP9hx9+mKMFnDhxgg8++ICwsDCqV6/OlClTcHd3z7RtVFQU\nnTt3ZtWqVZQqVQqAuLg46tWrh9FoxGw2YzAYeOONN+jTp0+O1ikiIiIieU+vXm8THNyeRQP6899T\nuzAAph9+4Pr16xQvXjy9nclkYuOSJRQtU4aWnTpl6xgxMTEsXDiOtLRUBg+ezEtvvMHM/fvJHxRE\nfI0aDOvdm3z58pGQ8AUHD26lVauO1KxZN8Oxj7zzDu8EB2MCFjk48NaKFdRp15o5Z6fydKNo9u3K\nT9dixf61lgYNnqVBgwAuXLjA5csXMX73NsNCTgIw+8BpihUrliOB/uyJExzcsoVmL76Ix1+eEiAi\n2ZPtQO+djWdt/pukpCT8/f0ZM2YMrVq1YtGiRbz11lusW7funrbBwcG88847XL58OcPyoKAgvLy8\n2LhxY47VJSIiIiJyl6enJ+WqP8XNnbsoCpwvUoSCBQtmaDO1fXsG/fgjF4xGvhg+nD4TJmR5/5Mn\nv0zz5lswGOCjj0KYPn0bY9avv6dds2Y+NGvmc8/yxMREnCMjATACN4OCAPjuu6X06BONwQBOTqHs\n2/czL7zQPks1ubu74+7uzs/OzqQBBiDB2TnLffone3fs4OdevXjj+nWWf/45nX/8kbIeHjmyb5G8\nJkuB/oUXXmDNmjW4urrSqlWrTC8vumv79u1ZPvjBgwdxdXXFx+f2f0xDhgxhxYoVBAcH4+npmd4u\nODiYPn36MGzYMMaMGZNhH2fPnqVKlSpZPqaIiIiISHYNmDmTZXZ2JF6+TJu338bR0TF9XWJiIqXO\nnqUkUNJk4tdDh7K173z5rnJ3d7a2V7Ndm6urK4cdHUkFbgGJUVEAeHnV5+xZZ6pWjeP330vTrFnN\nf9xPZnosXsysYcMgJYXOd24leBiHd+5kZ5cueMfEMBcYEBLCvu+/p+zQoQ+9b5G8KEuBvn///umP\ntBgwYECOHTwkJIQKf3nWpI2NDe7u7oSGhmYI9CVLlmTHjh0YjUZGjx6dYR9nz54lNDSU1q1bYzKZ\n8PHxYdiwYdjaZvviAxERERGRTNnb2zN41qxM1zk4OHC5UiUiL14k3NERp3r1srXv0qXbcODAH9jY\npFGy5IPNHO9VoQKvXrmCHTAjf34AOnbsw//9XzIHDx7C17c75cuXz/Z+y3p6MvwvV8I+6LwAdx1Y\nsoT3YmKA24/jm1+6NINyaLZ8kbwoS6m3S5cumf78dykpKdk6uMlkwmg0ZlhmNBoxmUwZlt39MiEz\nzs7ONGzYkIEDBxIbG4u/vz8LFy7E398/W7WIiIiIiDyoEZs3s3bePIq6u9P35Zezte3QoRMJCuqJ\n2Wx+4CtPW3z0EXPHjiX4/HncgRXvv0/vDz6gS5cBQM6dkHtYLp6ehNnYUD4tjYOFC9N1/XrK/eVE\nnohkT7ZPY0dGRrJkyRL++OOP9MfWmc1mkpKSOHfuHIeycYmR0WgkISEhwzKTyfSPAf7vRv3lcSAu\nLi4MHDhQgT4TCQkJ2f5G9e+/m9xI45K5BxmXu9vldg8yNne/pPz7l5V5ncbl/hITEy1dgohkk7Oz\nM6/87UrS7PDy8nqo49dt1oxbw4fzbI8eNLp0id9OnWJ71aq07tbtofab01754ANW5ctHzLlzdBgy\nhNoNGli6JBGrlu1AP3bsWEJDQ2nRogUrV66kd+/ehIeHc/DgwQzhOis8PDzYsGFD+uu0tDTCw8Px\nyMakGPPmzaNDhw7pM+MnJibi4OCQrTrygtDQ0Gx9UQJw5cqVR1TNk0PjkrkHGRfQ2PybsLCwnC0m\nl9C4iIjkjGvnz9PizpekHgkJnMri/6+/bN78/+zdd3RU1fbA8e+kTHojhYSQEEgCBAKhQxQBaSKI\ndJAOYmhSBSkiXVBBkN4NRapK7yC9SCAQAoT0QkgjvU/KlN8fJ+T9fPLeIwqieD5rsVYyM/fOvpMb\nzT5nn33ElneVKuG3fj2WlpYvLUZ9fX2GzZv30s4vSf80FU7oAwIC2LJlC40bNyYgIID27dvTqFEj\nNm7cyPXr1yu0XVyLFi3IyMjg8OHDdO7cmY0bN+Lq6vqrdfX/y8OHD4mLi2PRokVkZGSwefNmBg4c\nWNHLeu1Vr14dLy+vCh2TmZkJpL6cgP4i5OfybL/ncwH52fwnOTk5nD17Ficnp181UXqd1KtXD6VS\nWaFjVCoVcXFxuLm5/Wb51T9ddnb2P2KATJKkF6v7yJF8feQI1cLDeeTpybTx4//nMU+3vJscFUUh\nsEmpZNLWrS8/WEmSXogKJ/RarRYnJycAPDw8ePjwIY0aNaJz5874+/tX6FxGRkZs2rSJOXPmsGDB\nAry8vFi5ciUA7733HqNHj+a999771TH/3mF/0aJFzJs3j9atW2NgYED//v3p169fRS/rtWdsbFzh\nWcXXNfH4/+Tn8my/53N5etzr7vd8Nrdv32b57kAsbF1fUlSvVl5GPJsXGtO0adPfdbyJicnvrnp4\nXcllCJIk/R6mpqbMO3eOwsJCTE1N/+vOVE8VFRVhk58vjgd0ZR3yJUn6e6hwQu/l5cWxY8cYOXIk\ntWrV4vr16wwaNOg3+8M/rzp16vDTTz/95vFjx4498/WhoaG/+r5SpUqsWrXqd723JEnSn8XC1hVr\nR89XHYYkSZL0mlMoFJhVYL94Gxsbij74gA3795Nhacl706a9xOgkSXrRKpzQT5kyhTFjxqBUKune\nvTvfffcd3bt3JzExkXffffdlxChJkiRJkiRJrw2tVsv3368iNfURQ4bMoHLlyq80ntHffkvRl1+i\nVCrR09N7pbFIklQxFU7omzZtyvnz5ykuLqZSpUr8+OOPnD17Fmtra7p27foyYpQkSZIkSZKkv60n\nKSn8OGkShvn5NJk0iTuxV7Gz+5aGDdUsXHiVVasCXnki/U9YNidJr6MKJ/TArzpfVqlShaFDh76w\ngCRJkiRJkiTpdbJv8mSmHj2KAbA0OZmCfjXw8VEDYGeXQG5uLtbW1q82SEmS/paeK6GvW7fuczXV\nAHjw4MEfCkiSJEmSJEmSXif6xcXlf3QbFxXh5NGRgIDrODhkk5fXACsrq1canyRJf1/PldBv2bLl\nZcchSZIkSZIkSa+llp9+ypcpKZgUFFD5ww/pP2gi9+61Ijk5nkGDOj/3xJkkSdK/e66E3tfX9zeP\nxUgq1cQAACAASURBVMbGEh0djZ6eHjVr1qRq1aovPDhJkiRJkiRJ+rvz8fXF9+5ddDpdefJev35D\n6tdv+IojkyTp767Ca+gzMjKYNGkSgYGBmJmZodVqUalUtG7dmm+++QZzc/OXEackSZIkSZIk/a3J\nmXhJkl60CrfTnDVrFjqdjlOnThEYGMidO3c4duwYOTk5zJs37yWEKEmSJEmSJEmSJEnSv6vwDH1A\nQAA//PAD1apVK3/M3d2duXPnMmDAgBcanCRJkiRJkiRJkiRJz1bhGfqqVasSGRn5m8dTUlJwcnJ6\nIUFJkiRJkiRJ0j9BTk4O2dnZrzoMSZL+pio8Q9+3b1/mzZvHw4cPadiwIQYGBoSFhbF161Z69OjB\n0aNHy1/btWvXFxqsJEmSJEmSJL0u9q9YQfqyZSh0OqwnTaLv1KmvOiRJkv5mKpzQb9myBRMTE44e\nPfqr5N3IyIgTJ05w4sQJQDT9kAm9JEmSJEmSJD1bws6dTExIAGDlrl0gE3pJkiqowgn9pUuXXkYc\nkiRJkiRJkvSXo9FouHHlCpWdnfHw9Hyh5y6wskJT9nV8URGrx4+n0+jReNat+0LfR5Kk11eF19Av\nXbqUkpKS3zweFxfH4MGDX0hQkiRJkiRJkvSq6XQ6FvfogbJdOwJ9fTmyZQuRkZEkJCSg0+me+zzh\noaFcOHuW43v2EP7gQfnjw7ZvZ0W/fkxr0oSWjx4xbs0aDnXvTkZGxsu4HEmSXkMVTujPnDlDt27d\nuHv3LiBGLdetW8f777+PsbHxCw9QkiRJkiRJkp4lLi6GhQuH8OWXY/mqf39Wt23LoXXrXtj5MzMz\ncQ8IoKlWywcZGRz/9FO21K7NcTc3ZnfpQlFREfHx8Wg0mv94jks7dxLTrh36HTsSMGAAt9u148L+\n/QBUqVqVKXv3UqN+fXqoVCiA1tHRRD+jAbUkSdKzVDihP3bsGO3atWPIkCHMnTuX7t27s3//fpYv\nX87mzZtfRoySJEmSJEmS9BvLl/fjzTe/p3799eTe3sv4CxcomD+fx48f/+p1T548ISgoCLVa/dzn\n1mq1JCQkcMfeHg0Qq6eHKjubr7RaRmk0uJ8+zfwGDQjy8WFBx44UFxc/8zxF167RKyeHVoAT0C81\nlZBDh371msZ9++Lv5EQEcLxJE7zr16/YB/H/FBQUoNVqf/fxkiT9vVR4Db2RkREff/wxiYmJ7Nu3\nDwMDA5YsWUL79u1fRnySJEmSJEnSP5hKpUKr1WJmZvarx7VaLSYm6ejpgZkZ6NsDkWCbn09eXl75\n6y5dOsGpU6Nxckpm5872LFlyDH19fQDO/fADD/fswbB6dT5asgQDA/GnsU6nY9asftjbH0O/izVT\nanXE3aMBlqtXk6ZS4QBcNTBgU3g4+oDn+fNcPnmSDt27l8empyfmzQqrVCEFqASkALfNzHBq1uxX\n19LinXdwuHSJB7du0chMyeqZMzHTauk3ezb2Dg7P9TnpdDq+/fBDrM+cIdHWln67d1PT2xuA6ydP\ncnvXLmzr1aP/tGkoFIoK/QwkSfrrqnBCf/z4cZYuXYqxsTFbt24lLCyMWbNmceTIEWbNmoWLi8vL\niFOSJEmSJEn6h9m/fwsBAYvQ09NSt+4EBg+eUv6cnp4eNjaduHFjF3l5JiQUmbDGTYG6XTve8fIq\nf92VKzt45x0xY19cfJW4uDjc3d1JSkoibtIkxicnk6hQ8L25OcMXLOBhYCB7x41D53ubRo3UQAqX\nL7dg/JyvOduoEXNmzcJCX5/qLVsSvnMndUpKeGBrS30PDzQaDUs++ADLwEDSq1XDb/dufAYOZF2l\nSsRduYLCzIyk8ePpNWIEABcPHuTB8ePU6dSJVt27s3LNKOrVu0B+CdTdCWsCA5n/yy+kJCWx59NP\n0el09F+6FBtbWzZsmEtRUS4ffjgfBwcHYmJi8DhwgPdzc9ElJbHqyy+puWsXCQkJhPj5MT4xkRCl\nkp+MjekzceKf+nOUJOnlqXBCP336dEaMGMHHH3+MUqnE19eXjh07Mn/+fN577z2Cg4NfRpySJEmS\nJEnSP8zt21vo3DkOgFOntgNTfvX8jBnriYqagpmZGU6LnMpnxktLSwkNDcXFxYVKlWqSnKyPo6OG\n8IdmmA4yBSA1NRX39HQAquh05JaV6R+fPp3PAwIYZga69yEzA5IjMwHo0K8fHfr1A8SM+GZHR746\nfJh6HTvS19ubs4cO0eXAAeprtRTGxfHR6Heo5xtDnnEJ72WoeTsKvr92jW0pKVw+coQ29+4xrqiI\nwwcPsjcrCwe7K3h4gIcHXLsKjklJpKWlMbdzZ+YFB2MPLElJIdQ5F0vL2xgawqJF91mx4grhwcFc\nUyrpCmQDMXFxrPT2JkmhoGViIgB1Skq48PDhS/2ZSZL056pwQn/w4EE8/23LDmdnZzZt2lS+B70k\nSZIkSZIk/VFqtQUaDejpQWmpxTNfY2xsTFJiIg4ODujr61NSUsIX77yD77VrLPIxxPlNdx7F1EYd\nEUqt6CesDunG3CtXqF+/Pou7dOHyuXPcLi6myZUrbPv8cxQaDRqgzmW4Ngos88CrvjEajYY106eT\nn5zMwPnzqermxvHzG2nRNYPohw/5ZqaO1p17kmJsTO3CQtYAJhYP8fXVgi/sCIbL1yFlxw7GajS0\nAN4vu4a3MjPpOn48lZqp8X0THkWBKhUeN63HwjeakVUYx8fmYJsPuugI3Ful0KYNpKTATz+FMWNQ\nD4oDjlK9RIdf1aqUGhriExjIxJIStMBHdnaY5ecT6OrK+2PH/uGfS3paGhv9/XHy8KDfpEl/2xJ+\nnU7HN99MICPjItnZVixYcABTU9Py59VqNfr6+n/b65P+GZ6rKd6dO3fKu3f+ezL/lEqlIrFs9E+S\nJEmSJEmSfo+CggKWDxrEqnfeoZFbNy5d6s2FCz0YM+Y7tFotR7Zv58DmzWg0Gn7eu5ezTZtS6OvL\n4p490Wq1BAUG8t6lS9yrUsrwhYW83/0+btUe8k24lhlqKL5zh9jYWPT09Gjapw+uBQVsKClBEx2N\n4Zo11B4zhlVNmxKvNGV6JOi0EGQZRe8WNbBatgyX3buZ1bgxFy9epEWHDHzfgQ8m6zh/ZgNRYWH8\nZGzMx8BwwDRGi1YL+flg9QTMAXuNhktADDAbCAB614Fec4txrQTzh0HCDLiepiD6yhWya8YxZie0\n+wxsrCE5OwNnZ/F3uZ0dpDzWoLE5TvctWorH6ijJSWZebCzGZdtMawGvtm2pHBjIqJs3qe3j84d+\nPhqNhrOTJzNu3TqaTJvGdzNnPtdx92/dYt+aNX+pLflu3QrA0HALnTo9oFu3a2zduqj8udWjR7PJ\nw4OFjRsTEx7+CqOUpP/uuWboBw4cyNWrV7G1tS1/rHv37mzYsAFHR0eg7D++y5fj5+f3ciKVJEmS\nJEmSXnvfz5jByF27MAc2hIUx+e5dbGxsAFjp50fHbdsw0mhYfv48xkVFjE9JAeDo5aMMbWdKsVEV\n3qhSBbVBIoaG4pzmZqCPaExnoFRiamLColGjuL9vH3vLOsK3BS7k52Nx+zamDRvSZ+5cek74iDaj\nnjC0WQxBAeAcAh1UEJ2by4FZsyh0M+RRaikARQVFnPhkJP3y4bgNrPUE8wTYOAqMi6B2AjgDQ4BQ\nYBXwGJgI9PsQGjaGhi0g3A+uaaCdTke8fi6124NCAXV9IcIWNNFFXFplSGzzUlLugX5sPm9MF937\nG7eH4/4azuRBIjADSPD2wMWtEqGhodSoUYOrR49ydd48Ykpy8O47CEXSEyrXrk2fCRNYO24coed+\nJNejGIdabzB79h6sra3LfzaXjxxh36qveJwbRYoCHpiouXzlAD0zp1GpUqX/+DO9dPAgT0aN4u20\nNNZs2cKUq1cxNzcHIDE+njM7dtCgbVsavvHGH7+BKkBPTw+dTsy+azSUN0uMjY2l6t699MjJQffo\nESsXLGDSrl1/amyS9LyeK6HX6XS/eezRo0eUlpa+8IAkSZKkf4aSkhJCQkIoLCzE2Nj4VYfz0vj4\n+KBUKl91GJL0t6HNyeFpP3ur3FzWTp3KG50707ZXL/SDg/Eq23rO9MED8ps3Zx7iD9rsd3SMGF2M\nShXLT3veovSGMbcWJFOtvi1Z0dbE6z/koZ4edoMH88UbbzAgKQkP4ATQATgAZGk0fL58OTkaDUu2\nb6e5aTGetUUs7l5wzwTygDsq8Lx5k1hTd8YOisbCAi45QWQYfHUNWvWENt1h925wMoTcZDibBWsK\nxLlqAqV64N4MbCvDhZMiof9hL3SfAE7OsOozMKsKhtEQGAjW1lDYAtTWoCyqSb/vQggGEjzV7NsD\nHTvBme+h2BCyjSCjGHLtoF6fKDy8ovhh4QZOTnHFo1IlUtR3afkpRN6fT/294F1gyJKYGKpt24ZV\nj0L6fAQlJadYu/YTZs3yByAqPJwT4wZTfVAu3afDJ8vhzbdhUINI5sx5l5Urr5cnxP/uwbFjfJyW\nBkCne/cIffiQps2akZ6ezo6OHZkQHs7xVaso2LqVll26vOA76j9r0qQZV6+O5cyZ82RlWbFw4WcA\nmJubk2FuDjk55AGGZQNKkvRXVOE19JIkSZL0Ity/f5/luwOxsE191aG8NHkZ8WxeCE2bNn3VoUjS\nS6fT6QgPD8fU1BRXV9fffZ4O06fzRXQ0VmlpPMjNZaO/Pz8fOMD2uDhCDAz4GQgEItRqlBF3qF4F\nmj+B05XF8cbGEB9yk/5JxfSJhGV39Khax4kzvXvTd+pUTJ88IWXTJq4D0UBPYKoBPPaE/AIIjNdw\noQbYVy8mOBzC50KVVvDkCqR6gYMHWBTBzUdgbRaNkZF4XwsLSE4Fh0aQlgfFxeKxrl3F898lwJRA\nqKWDJ0C1mtBxkegPcOxHWDMOFE7g3V+83rQqTPkM9PUhNBT27oX588XXh/eE8MW78PA2tO8E7TvA\nqVPg6gNj5sGPO2DYDjjlAr6txPk8WkHcmngSdTqq9AFXV/Hvys/Q424pd4KOE+KpxkJU82NgAOF3\nbrBy6FBqvP8+T+LjURjl0qSjeL5dN9BqQakER8cY0tPTcXBweOZ6c4+33+b0/v20zcnh59q1GVer\nFgD3AgLoFh6OGdA3LY01x4//qQk9wKRJ31BYWEhoaGj5+nl7e3ucv/iC1bt3U+rgwOglS/7UmCSp\nImRCL0mSJL0yFrauWDs+uzeL9NeQlpbGxYsXyc/Pp0WLFnj9v+3AAAoLC/H392fcuHGvKELpVbiw\nfz8P9u3DwsuLofPmoVAoWDNmDO47d5JlaorJ7Nn0HD/+Px5/4/Rpbm7ejGHVqny0dCmGT2vjAc+6\ndfn8zh3OHD5M/qgeLPQEw/hszOfMYW5hIdOVSjaWlHD8cRghvRRUGwsrt0L2dcjMMSTxsQb3esWY\nfgqDVoF5ej76iTfJ0t0kbX0IOlzIfgviU6FZOHQCTreE8XOgoAC+ngwTvwC7yvDwDtScCcF34VBl\n6OsHLi7w+DH07guGhrBjB6Sni+S2eXNwdISoCNjpD7mF4ppiYyGvCjT/DMw2w4NUyCuBt0vByAiy\nCqHnZ3DzJoSHgmMVyE+B9FSo7AQJMeDlCceOwYNgmD5fJPjT+kFhAXz3Heh0MH68KB3P18DuDyE1\nDIyuQsMmkHsD5gOTk5JIuAHNO0NcNGiSwc/NkN7jo7G3h01r9Nm4QocqXUfPX0IJ0IZisWMH1mZm\nhNvaoDyYRaO2cPKwEQ2barC3V5OaWgd//7lkZZ0lKQnefHMkI0dOLZ+xf2fQIK7Y2PDd1asMHT0a\nKysrAOo3b87m2rVxCQvjhL09Dbt25dKlk9y6dY5u3Ubg6enFq/LusGEwbNgre39Jel4yoZckSZIk\n6Znu3LnDyJEjsbOzA2DJkiW8//77LFy4sHwZQWFhIWvXrpUJ/T9IfHw8cePGMT4lhUhDQ/aYm9N/\n6lQ4e5bOBQVQUMCaAwdEdlnmXkAAlzZvxsnHh7SMDJIWLmShVksKsNXQkOGLF3Po0Pfk5hbi5eVF\nRno6+zcspf5n4O0Dv1yFuC8K2QnULinBGIioBJVddJw6BeOni5nudUtNME7KpdtUkeTa1oa8PDHL\nPckP9PUfsH7dAz6eD0VFsHQ0dIgHpZtYp37uHBg4g3FZzb/SAtbWB50TjGwNV6+KhN3WViT1Pj4i\nqR8+HCpXhl27RGIfEwc2NqAohpkzoW1b8PSEew8h1xucrkHzVNi2BZSmEBMNCUlQowZ8vx2qh4PG\nAdZvABMjUCZAiQNMmA5u1eDMGfG+6elQqRJYW0GHjnDggIijWTOoW1ck97Nnwq2N0CMBcoAuGg3d\nr8O2IXCiAAbnQEgzA+ztxVLaWp4akr8CF0AJLAZmAh4FBZiVlmLvuYztn37Jpsh07p2HfW1aMO7r\nlZw58xadO+ej0cCuXTNISbnH/Pm7uHTwILe/+YYSIyN6r1lD1WrVyu8LOzs7hpw+zf6dO2nw9tuk\n5iUTfNOPxo0zWb/+ENOnX6Ny5cp/wl0tSX9fz53Qnzlzprx5BYBWq+XcuXPljfLy8vJefHSSJEmS\nJL0yX3/9NYMHD2bixIkAXL58mc8++4zhw4ezadMmzMzM/scZpNdRQlwc3k+eAOBRWsrJyEgUCgWZ\nDg6oY2IoAIqdnMpfn5aWxoX+/ZkYG8sdQ0OuqtW0K+vP5AhkRUUxe3Yf6tU7jFZrxMaNiahO3afO\nneu4i1sPz9rgYgzvF8NQQ0Mu6nTcstHg8lDH48eUb21XVZdLfh5s2CAS686dRSf45cvF9/r6YGH5\nr1JxpRI2AEUXYTfgWgNmzBSz3wDJSVCvDbRuDebmkJgI+/eDk5MYKIiKguhocHAoi9MT4uPFrLuj\nI5SWiuc8PcHNTRxrYACZ7eCymRgUsLWFUaMhLAzat4fWreDruTBuGri7i1l7lUpco4kJeNeD02cg\nOxsaNYK4OHiSClWqwBtvwPr1YgChbl3IyIBWbeHxHXg7Ab4GGgJOwKdJovS/FeB6X8W2NeBdF0KP\ngK45xBVDs2Ao0EEj4CMgu6SECUtX0qrEgMpAhxII1Vlga2uLSmUC5FNUBJaWUFp6H51OR8Ds2UwL\nCUEHLP3kE6adOvWr+8nZ1ZVhn4m1619/PZbmzTMBqF8/mnv3AunQ4c8twZekv5vnSugdHBzYsGHD\nrx6ztrZm69atv3mdJEmSJEmvh4iICL755pvy71u1asXu3bsZOnQofn5++Pv7v8LopFelqa8vizp0\nICUggHvOznwweTIAfj/+yNo5c1BaWeHdvDlrRowAOzviw8LoHhcHQKPSUi4BIUAREKBQ4FavHnHx\n3+DcCZydi/n555uoU56Q5goXvoZaPpBwCTbngDHQqEsX9hsbY6zbS61a0KIFfP45WJgZUDleTW4d\n6NQRateGH38UybWzM2zZAiUlIvHfsxUUUZAcDWuBGnHw8za4OFW8vk8fMQuuUIhjLlwQa+Hv34cJ\nE0RiXnbZREWJAQAHB5HwDxoEq1dDWhqMHi1es3u3SPBLSsTAQI8eYlDg0iUID4fcXPE9gL0DWDuL\npFinE+vcz54VyX9yspiRT02Gd98TM/r29iKuffvg7h2oUlUMAKxbJ/oJDB0K/r/APmA0sAbRXT8L\naI2YtY9UQel+yLoAVYeAqYXoAXBAAz88gQ5lrU5MgbT4eG56evJjdjaJBgY4d++Oi4sLNWvOZuvW\nRSgUT2jfHsLD6wCgX7b1tQLQK2to+J+89VYvTp48hI9PMrdv16Vbt//e9V6tVnPY3x9jMzM6Dxgg\n94uX/pGeK6G/fPnyy45DkiRJkqS/GEdHR+7du4eLi0v5Y66urvj7+zN48GD8/Pz44osvXmGE0qtg\naGjI7BMniIqKQnX5MqlJSbh7eVGlalUm+vtzLyCAsK5dGZeWxkGFAm+djj36+hhoNFxxcOCBgQE9\nk5PZZ2SEa58+ZCxfjml1Ffm9ITsLTE29iKwby9CRoFbD5unwRjCsUSjIrl+fN/v144chQyjtAnXq\niGR78GCIjlbT8mMx471/v0iE4+PB1QU+KGs0t2kTNKwFxpugdhI8Aua5Qp4+OJdA5E5IDYaoUjE7\nXr26SNIvHIdr16BNGzh5EpKSxKy/o6NImr294ehRmDIFCgvFWnytFh49ggcPRByLF0PPnrBnD/Qv\ni6dKFTEzf+qUKJ+vV0+cW6mE69fFc3oKsLSCcePAzAw2bgR9Q7Eu38pKDCjUry++r+MNCfFiJr9p\nU4iIgCWLwVUPkurAwoeiw34ekA2cf/NNdDod8UG/kOeto8ARvIzh7bdF+b6iNoxcDmsXQcpFeAAs\nAO5FRhKpUDCoqIgtO3fiUrMmuQ9SmPf5Fa7fPEtRURFz505AoVBQe+pUlq1cSamxMZ3mz/+v99Yb\nb7SjUqUzBAVdZ/bs7uXbFf4n3/TvT7/9+ykwMGDd9et8vHbtH7m1JelvSa6hlyRJkiTpmT766CNm\nzZrF7du3GTZsWHnn8urVq7N161ZGjBjBwIED/7R4goODmTdvHnFxcdStW5cvv/zyV4MN0p9HX1+f\nvRMnMvj0aR6ZmbF71iwGzJwJQMgvv9ChbIuyLjodW4GvNBoGe3nRKy6OmkDQ0KF8t2EDs5o0waeg\ngK4PYNswOO/iRl3FLXASU8IGBmBvIbrR6+nrY+ziwpNRo7AvLSU+RJSbp6WJBDQsTCTzIGatN20C\nLy+R4IKYtU54AClHwKAGbC8FExvIqQVVq0JUNJgYgOUlMGsikvcrV8R5nT1Fct+pkzjX/v3g4QEB\nASJ537dPrMlfsUI8b2goZuJ/+UUk8WlpEBMjBiisrWHZMnG+4GCR+I8YIc63YQN89JGoDujWDVq2\nFK/JzhYz9iCWEOTnQ0oKnDoOMz8Xj2dliRJ/92pw/yy82QOybkOXwVC/oYgzfAR88gSuAwXAtRo1\naHbsGD+462g7ABo0EBUDv/wCkSEweIT4GbR+D0ovgYsBNCyFpsAanQ5XQBsWRnLfvgzPymLWzp2Y\nmpnhlJfHkotBtBszhk7DhtFlxIjnvrdq1/amdm3v53qt+YMHVNfpoLSUi0FBz/0ekvQ60XvVAUiS\nJEmS9NfUq1cvVq1aRXZ2NgUFBb96ztPTk/3799O8eXOMnu7b9RKVlJQwbtw4/Pz8uHXrFr6+vkya\nNOmlv6/0bIWFhVS9f58awNsFBWSWVXPqdDoSSx8xuaM5nznBVKWSasDqmjVpoKfHQJWKrioVlYKC\nMDQ0pFpeHomI9euR+UY4GNgxLyiI3tdK+H6pHptWm3P3roLGgLtajemxYxywziWjNxRZwsa1ohT9\n5ElRVr92NZw+ruDkEQXNm0Fqqnh+/XrRIb5tN6jcGT5bBX2ngH1dMbufnAwzZsDkTyGmHaQlwdo1\n0KoVfPqpaHCXmCiSb5UKHj4USXVhoXh+4UIxS967t0i+33pLvHfPnmK2vXdvseY+I0MMOkybJsrp\n335bzPJ7eory/kaN4OBBMcMOYhDAyEgcc+iQSLRDHojj330XcnIhJ0ecKycH3nkHgu6AWx7s/wIM\nc6BUK86l1UKxaF1ADnAfuL5zJ42ysnikLwY1QHTxP7QNFDfh/h1ROXDufGXyZiqptQam1YYo4C4Q\nASSYm9MjKwslYBofj0VoKJqEBOJ37uRxy5Ys7tEDXVnPhBctr3ZtUoAofX203t7l92BpaelLeT9J\n+iuSM/SSJEmSJP1HrVq1olWrVs98zt7enmXLlv0pcdy4cQNra2s6d+4MwJgxY9i+fTvR0dG4u7v/\nKTFI/2JiYsKj6tUpSErisaEhRvXqAXDixI9YWm1gxMwiIiOVGBouw7JGfUZ6e7Np+HDyQ0JQANlO\nTizo14+EpCSygRGAhULBmfx8IoGgHMg9oaU6+awGDgMtgTmWYNkcHGuAW13R+K1SJbFW/uZNyEmD\ntPM6PLzh2n7oMRb69YOtW8UMel4BuLnD9u0iWZ4wQSTLlSuLhBrAzgEmTIIN60W5fEiISJiflvLr\n6YlZ9jffLCvHvyASez09UaZvYQHHj4FaA4cPi8T7wAGx3j0hQZTfHz4sSvXr1BFN9Y4fF0n9zz+D\nqal4zcOHYjCgRg3xtaoQipLBpLIYoFCpoH4D2LoZSrKgfS8xw+83TsRRshuatBDXEB4GCVegQA03\n3SElC5zdwTZHxzh3UBSJHgN16kBQIMyLhADgflgjIsLz0c9+TNsOJQBEtIJzYaA0NibK358PLSzY\nPWIE76SmctvMjAUFBTQCcoFtOh01b9wgPT0de3v7F34fTtm3jx9Wr8bE3Jxxfn6kpKSwaFE3zM2T\n0df3ZcGCPejpyflL6fUmE3pJkiRJkv6jrKwstm/fzqBBg8q3rwNYvnw5Wq0WPz+/8j2lX6aYmBhq\n1KhR/r2enh4uLi7ExsbKhP4VUCgUTDl+nJ1LlmDv6spHI0cCkJaWRHp6EUFBoFaXYKK8RH5wNKVZ\nWYzbtYsds2ej02pRWigJPvANLe1ALxneAHKLirgUE8M8hYL5Oh2PgDGAOVAHWAe4D4LufUTCe+0a\n5GSCwkCUx/ftK0re82yh68di27pz50QZ+qhRYqZ7w3qx5tytukioT56EgQNFwr58uSiTb9BAJPd1\nygYM8vLg7l1R0t68uWhgl5EhZuBDQ8W5L18WTeRWrIDSEpg7TwwaKJWwZIkoW581S8SyaJGoCBgx\nQmxzV62aSOgVCjHbn54ujnGtBMVa0UjPwAAqWcCE+SL+mBh48gQGDBAN96Ij4cZ1kcg//TXxaSRe\n8/77cP8mJB6GYV9AdS/w9xcl/omJovt+VJSIv2VLKD4JnYGwqtB30B3sHWDjAkiMg8pVoTAYhgFT\n3NzoXNYM4MHx45y+coWhtrbkfPghaDQUItbcR1hY0NPa+qXch0qlkkFTppR/v23bQrp1u4mBAYSE\nJHHjxnXeeKPlS3lvSfqr+F1DVlqtlitXrvD999+Tl5fH/fv3yc/Pf9GxSZIkSZL0CqWkpNCnsDRd\njgAAIABJREFUTx8OHz5Menr6r56zs7PjxIkT9O3bl9TU1Jcei0qlwuRpHXIZExMTVCrVS39v6dms\nrKxo88EHqNVqjh87RHDwXfr2HUlwsAX9+olEOTP8KB+vWIFq+HACTp5k7Lff0mXyZIIeLOfjdeD8\nLexzgYW9Ydsn8KhKCa46HaeAQQYw0xdGd4Gf7SHTCOr6iPeuWhWCb0KoP4QFirJ1PT1R9j52nGgc\n5+BQlqAWi2QewLUaDBos1p9PnSrWth86JDrMJyaKWfzYWJHAx8SIpnMqlUiSlUqxv3v//mIwYMMG\n0cQuP18k0iNGiMZ1Op1Yr25uLt67RQux7j0mRhzn5CTK8i9cEGvyg4LEeerVE+9hZCRK/avVBeeq\nIvnXaqFFK5H0e3qKigALC3FN6eng6AyqXPDxEQn+9etwaB3c/w4OLQb1arCxEsk8iOsICRHxhYSI\npN/REXZOA9cw8Zo4R3B0Elv9edWC7MmwdBiUBMDgypVpMGwYUaGhAHg3acKAyZPpM2QIUZMnM696\ndWYqFKwBmufkcO+XX/6Ue9LS0o7cXPF1drYllSrZ/fcDJOk1UOEZ+idPnjBixAjS0tLIz8+nTZs2\nbNy4keDgYPz9/fH09HwZcUqSJEmS9CdbsWIF1apVY+3atRgbG//quSFDhtCrVy9GjhzJypUrWbRo\n0UuNxcTEhKKiol89plKpMDU1fe5zFBcXU1hY+KJDeyWeDmT8kQGNkpISdi1cSHFGBl1nzMC5rOnh\n8zp/5Agnhw0jxbWYthMh4KaC+/erYGdXFRCJnrWqGAXQKSuLFWfO4NulC4vHjqVWA7Gw264yVHGH\n9z4W5yzIgdjv4EF1OO8CE+aJJPbwBnALhqvXxJ7rwcHQph3Ex4F+Chw5Irrah4ZCu3aQnydK8SMj\nRXn8okViGztjY9Eoz9BAJMrOzuJ9S0th2DCx/VubNqLJXUKCKG13dhaJr7W1KM0HUZr++LF4LCxM\nlMmLnwfU94G1a0UTOxcXKFslwvr1IqkvKBAz8du2ieOqVhVJ+eXLommegYGoNjh2TFQFjBolPoMV\nK8QgRUiISPAfPhTHqVTwKEck+v7fga2deFxRGUwtISQAhiRCjBFs3wJN3xDLE0pLxOdhawu3b8N7\n78HFAxALDATyo+HUQXCtCXcugVM2rMkGO2BuRgbvzpjBiZUrebJ1Kw3feqv8vmjt58fajRv5WqdD\nCQzIyGDt4cN4NWkCgEaj4cmTJ9jb22NoaFihe+5/GTjwE1avTqS4OBZ393dxdXV9rt/5F/H79Ffy\nul0PvJ7XVFxc/ELOU+GEfv78+dSvX58FCxbQtGlTQJTdzZw5k4ULF7Jjx44XEpgkSZIkSa/WtWvX\nnpnMP2VmZsbEiROZNm3aS4+levXqHDx4sPx7rVZLfHw81atXf+5zJCcnk5yc/DLCe2XiyvZ3/z0O\nLlzIpMOHsQFm3LxJvx07nrmPt1qt5sDnn2MXHU2amxu9vvwSAwMDfpw+nTXFxcxvJkrT69bVkZOT\nyKPzqWx+pETfwZHSiAziKWC/sTGP09MZ6e2NS2wsAdGQkQXRoUC8mOU2M4PYJ+BYBdqtEOXwWq2Y\nIS6wgEe2MOkDUQIfGQkPwiDZGTzriIT7/n2RyG71h+xMMdvdpYtI1r/6CjIzRZn5smVgEQ4HZoBV\nZci1gIkLnn6e4tyRkfDhh6IJXU6O2H5OoSg71uJf6+pdXP412x4cLGa5e/YUSXJEhKgAAJHEW1hA\n48biPPHxYpb9/HnxvEYj9qw/dEhsNxcYCHfuiOTewEBUH3iVlcpbWkBsnLi2Ll3ENndXr4pBgJwc\nsV7fw0N8Ju3bw3FHmLQOOhXDzwcNiApR08QV8oth4BgR9927oFXDBVNobwAD1HApC9JXQT19GKWB\nD6tUwTkpiSvAWLUaZ8AvOZk5332H8f9bjhN85w6d8vLYCgwGvjMxoW6TJoSGhlJUVMRPEyfiGxnJ\nLScnOqxcia3di51Ff/fdMeVfh5ZVEDyvP/L79Ff0ul0PvJ7X9EdVOKG/desW+/btw8DgX4cqlUrG\njx9Pjx49XmhwkiRJkiS9Ovn5+f9zH2gnJydycnJeeiwtWrQgIyODw4cP07lzZzZu3Iirq+uv1tX/\nL05OTli/pLW8fzaVSkVcXBxubm6/WYrwvK7k5/M0laqRl4eHhwdKpfI3rzu8dSsjz53DXacjKTaW\n0xcv0m/8eCpXroxZfDy54WJmOTtbrPdum1nKxBAYaZxK/6IigoDUoiLeO3SIz32guAcYacHMEoZ/\nDD8vgXUroEZt6NgdDiVDN3ORjK5fLxJhLy/o3AW+mAOVHEVS36YNmLUWyWifPiLWH34Qia2evki4\nQSTQSkRJfFYWXL0CxhbQMBJmJkMPV9i9C6ysxblatYIFC0RiPHLkv7abe/wYxo+HVatg/nyRaH/7\nrUjWFy0Sne5dXeH770VJ/+TJYvZ+3jwRi7e3mPUPChIz4o6OYkAgNlaca9kycZ1nz4r1+dOmwY0b\n4v0sLSExEoz1wM4e+g8QAxggEvenlQYWFuLfW2+JBn4AOdnwLmAL+BaqcbkLde/Cah8Ra/v24FgZ\ncvLgi9VwZBa0+gVSgKvAdQ3sMjHBoVkzxsXEYFKpEvYPHjA3PZ1j1tY06tyZM2e+o7RUxaBBs/Hy\n8GCliwuNU1KYY2NDr/XraV2239/JvXsZd/s27kCP3FzWnTyJ3+LFv+v+fZFexO/TX8nrdj3wel5T\ndnb2CxlkrnBCb2RkRGZm5m/+BxoXF4e5ufkfDkiSJEmSpL8GT09Pbt68+V/3ev9fz78oRkZGbNq0\niTlz5rBgwQK8vLxY8XTT7wqcoyIl+n8HJiYmv/uaavTpw65793DMzaWgTZv/ONhhYWlJkb4+qNUU\n6etjYWWFqakpH/n7M7NHD8xCElgwpgg7SyjOhJXJUAyYFRXhAXgitjlbWBumzBaz15s3Q6d3xflr\n94DcG3r07q1Fo4HsQtFQzt4edFowzBcz5LcCoFEL6NVLlJvHxYlkXaEQCbO2rIEciMcePRJJeU4O\nJD+BvXvFjPmHI0Q5/p7JMDYPlPVFgpycLJLk1q3F+dzcYOdO0TBOT0+UxyuVosz+6Ufl7Cy2mAsO\nhg8+EOvgNRqYO1fEFxYmknY3N7G3fGCg2H8+JgbathVN9kpL4csvRUy9e4tk38ZGJOYdOogu9RFh\nUOkW1JsEecWiTP/uXfBfJwYJ8ovgcTw8joN+AyEzDRKvgX8Q1A6BQuBcA2jaAMJug+F9yA+G+t1F\nU75q1cR2eQoFUAl0wA3AzNSUtMJCklQq5h46RBiQaWSE2sCAUY0aMWTBAk7f2MYbb/yEoSEs+SqY\nxidS2ZWYyEZbW5pOmULbLl3Kt7b08PbmgY0N7llZhBobU83b+y/1O/lHfp/+il6364HX65pe1PKB\nCif0/fr1Y968eUyfPh2A+Ph4bt++zbJly+jZs+cLCUqSJEmSpFdvwIABfP3119SoUYOGDRv+5vmg\noCCWLl3K2LFj/5R46tSpw08//fSnvNc/wfujRvGoUyeys7KY4uPzH1/XZdAg1ly/zoWgINR16zKh\nrKN9TW9vZgcFMdHNjclRRZw0gQJHGGkOihIlS0tK2ATEGRpSamREgVE+T+d+rKzgzm2x3vzmVTNq\nePZgzeI9VE7V0DIXWvYFQ0PYs1Mkv5OHiZL8vXvFWnMfH9HlPjsbSopg0WdgkgtFjqIsPTNTJL09\ne4oE+6AFPAwG31YiCb97F9KqQ6oOWvmKRLZKFfGe586J2XhDQ9HR3soKEhOgIFfMwmu14nilUiT7\njRuLJNzdXST0mZliQODUKXjagP2HH6BJEzH7/+23YJJFefO20lLxtZ6eGOh4HC9m4UePFs3tjIyg\nMAX2At8chqzGsGwJ5CaDCTB1kZj119eHmF9g+0zoWALdVXBKD9rkwRQbqOUDeWYQUxUeWYDVXbhz\nEXzfgqgISLgPpzLg7l19VqNhBPBVYSGuwOfALiAVmF9cDMXFrMzLo2WXLpy+8SVPJ0wVusd8kJiO\nPjA8I4Pl06ez+MwZ5pw+jb6+Pj7NmvHT4Hc5nHiSUmz5pmvXF3pPS9I/UYUT+nHjxmFhYcHMmTNR\nqVSMGDECKysrhg8fjp+f38uIUZIkSZKkV6B79+6EhoYyYMAAfHx88Pb2xsLCgtzcXEJCQrh37x69\ne/dmyJAhrzpU6XeqVq0a1apV+6+vUSgUjF+//pnPnfz+exZkZJCtD3cGQbsBcO2yEmXJWHaevkpK\nURF9Y2OpXZDPGDtR4l1YKMrAzZSD0OHEsi0TqVLFmeVegXiGhREEHJoKlZ0h0wBqNxCz46mpYru4\nx4/hyk6x1v7TeaL8fuMXUKyBkmx4sy/UqgUXL4jmdKam8M47kHQXbn4Pdy9DZU+YPr1szf1WkTTf\nvy9mxS9cEIm7QiFm1Rs0EEl8UJAYXBgzRpSzX7ki1uaDKJdPShJN+VxdYc4c+PprcZyenkjYc3LE\nIISlJaRFwO3vRbm9QiGWCVy6JLr0Dx8ukv7PPhPd9Tt2BFU02D0GFzVERILSFmZ9DbduibjefFPM\nsNtbgcN9OOqhz4ivNHQ2gm/2g2kuDB0qmv1NmSKS/w1fQt8zcDsKlPlQXGiISq3G2cyEyAYelNas\nSdbJkwzPy8MC+BCxXZ0KsYQh3dKSrzp3JiXtMT9rzDC30BH/0JgJFhbMzsvjGPAB8ODOHZKSknBx\ncSEnJweN2RWGjMtCrc5iw4ZPmDt314u5mSXpH6rCCb1CoWDYsGEMGDCA4uJi1Go1JSUlVH7a9lOS\nJEmSpNfGzJkz6dixI4cOHSI4OJjc3FxsbGyoW7cuM2bMoEGDBq86ROkVKiwoYL2eHilmWjp1FI/5\ntiwhKMiAybdusWvZMjymTmWMJ4yeJLZyO3kSMjObsXTF90Q/fMiOwUNQZ2dzXi+Cmr0hNRQaRyqZ\nFVZC99bg6ws7dojke/JkkQCvmwV5pSIJf/AAxi8QM+rzJ4uSdhD7yB85KraJu3YNUlTgWA9adxSD\nACDK/6tUgaNHxRZyLVrAjz+KzvE5OaL5XdOmoolddLQYjNBqoVs30cjvaeWvt7fY8k6hEFUBIDri\n79sn3isuTlxHerpY337XAh6HwcjeotQ+MVHE37y5OLZtW7E3/dPil3eGwexYeHMp2OSI+JRKkch/\n/TUUFcLD22AUDPn2UKOhhuru4lgXV7DJF9ejpyeSeQBzC2gIfJAIOUAqpSwGcvLzmfToEZMCA3nz\n6lXWdOzIlJISNlha0m72bNaFhJCdmgp6ekw5dgxDYOEje27m57NZlYA1MMLKihH5+bhpNHzv7Ewz\nAwO0Wi0ajQY9PTUgYtHp1C/jtpSkf5QKJ/RJSUl88sknNGnShKlTpwLg6+uLm5sbK1askIm9JEmS\nJL1GDh8+zNmzZzE0NGTo0KG89957rzok6S8k4/RpvtBqSc+Fsev06TRIw717HowfL6o2W/Xti9+J\n6XTorGH/ftGVPTtTj/HjN6NWq9k9diyfX7rEDxbgvgGcqojZ7D1j9Rll4kF2fC771qeCBgzsRBII\nYFQdPvYTgwNxUf/aZ756VbH+vnZt0akeYOJEkfxmZUG/fmKGfPduUa6fliaS8qcl7yBm5JcuhUaN\nxMz++nViTfu4caLZ3fz5orzezEx0l9doxMx+aalYT//TT2Xl7zHg5ycGCGbPFs+lpIj19jY20GYk\nnJoFxd6QlADJWbBhPZiYQshdUOjB/WDwrg+R5yBMCY1KRG8Bf3+xLj84GKws4fgP4BIFW4EvOkOJ\n/b8GCYqKxODCV4vBvjKsWQMmSrC9At8B1YA7enp002rLf64GWi1arZYWrVtjffMm2/fvp1OPHng1\nbEhhYSGhoaGc+/JLysYGsFWp8FCpqFL2fY2cHFKXLWN5WBiZt26xyM0NpbExLRYswM1tLCdP7qW0\n1JoJE758rvssOzubzMxMqlev/sydGCTpn6zCCf3cuXOxt7dn6NCh5Y8dO3aMuXPnsmDBAtauXftC\nA5QkSZIk6dXYvn07S5YswdfXF7VazcyZM4mIiOCTTz551aFJfxFqU1M0iL3J66TUpHr1lViUxnB8\n7HjU9vZEl6Tx0RgNdnZi3fvixeCcqGVf4gwMUlLIu3cPACs1RKeVJfTpUC9fRUZ+Aj1NrJlwDY4D\nx61hmx6oTaFaWW/m9u3hzh74eTvoW0BsMNRqJrZtK3wM0cYiaXd2FjPq585Bjx5iP/dLl0Rp/P37\nooHe0aNw8aKYhbewgKfLu5OTxbp2EAMHSkNRXt+tmzhGoxEz/VotPHkiStvPnBIDBKdPi8Q7MVHE\nFB8vqgWmT4dLO2BhGASFwfwa0PhNGP6hGCRo1kw01Dt1Gn7aBfY6MGooqgTCQ6E4HE6eED0IlEYw\nbDzcmw3LcyGrGAb3FNdy/LA+9tYGRKcW414L/CaJ9f2bl0NYKvQBXIHQJk0IcnXl5vHjJOvr03bG\njPI94mv7+FD7GT0Wui9YwOKUFCyzs1G/9RYRGzZwDtFNvxCwrl0bdWkpus2bmQAYl5Swcu5cBkVH\nY2v7+XPfYzfOnCFg9GhqpKezr1MnZuzbJ5N6Sfp/KpzQBwYGcujQIezt7csfs7W1ZcqUKfTu3fuF\nBidJkiRJ0quzd+9eFi1aRPfu3QE4c+YMM2fOZPLkyfIPagmAwevWsQwwUKnoPG0ang0as3fYR0yI\njycZmGNmyO1q8E4XuHdPzI7XD4PwwEA6pKVxD/gU0KggdikcqiLK8o3bw1ttiwhdkQIp0BmIyQbt\nEYhoAk/MxFr6U6f0GfhER+dtWkqARKDNUVh7FcblQKSb2PoNIPmxKL//9ltRBm9nJxLyqlXFuvVN\nm8TMu0IhkviEBFGOHxEhGt0dPChm/Wd+JpL1DRtE8n7ypDge4MexcH4xdPwMDh8W1/LBB+I1J06A\njRXkJ8Hy2eBYCb5whIIM8GoByrLy/dRU0Rnf0VEMPmg0sG0beLlB3bqiC/+qj+DGGdA3EF3/dTrR\nb+ATYOhF+DkLNLlQN0TDtxoNn30AGrN/7QKgeQwuwHZgiKUlb0dEkPbmmxT06oXjw4ekRkSg1WpR\nqVRs3rwQAwND/Pw+L+9WHxsZiZFCwafnzpU/FhoYSH5gIArAxsAAb29vIlQqwvX1UWo0AFjpdJQ8\nDeI53dy0iYmxsQCUnDtHYmIiVatWrdA5JOl1VuGE3sbGhoiIiN80UImLi3ttthCQJEmSJAkeP36M\nr69v+fdt27ZFpVKRmpoql9hJADg5O/Px7t1ERUXh4eFBVlYWdvn5ANgAhcU6Wm6EtT9DjhbIhzqp\n+lyvbMhu4G2gE/AV0DUR7neE7kPEeu9Ll6CkAQRFig7vJYiZ315hcMAK9kRAXoklNwflcjYcHH+B\nsVrYrIaTaaIhmzYCsvOgWA/cG0P//iLuVStFmb2jo1i3fvSoWPt++jRMmiRm25ctE0342rYV29RF\nRYly9/37RSl7cbEYIMjLhdN7ICka9KPB2Uqsf2/fXjTY8/cXZf1xD8E1UST5k74VVQCXz4NhDoRH\nwTvNxVKAiAgxmODpKWItKhIz/56eoru+qhCyC/U4ey+Ffj2d0aeU6AD4IRNOA8ocSMwEi7qQWAxf\nhYJbNajXUlznw6vwQzAogEnAh7m56AELd+9mSGoq1XQ6woODOfrWW1wP20/r1sdRq2HhwnC++OIH\nTu3YgWrKFOoUFrK4XTvmnjmDnp4eG27cYEbXrqiioujw+ee4urri6urKw4kTmeDvT2UDA5w/+ggn\nJ6cK3WNKV1eeAJWBGDs73q1U6Y/cspL02qlwQj9w4EBmzZpFTEwMderUASAsLIytW7f+qgxfkiRJ\nkqS/N7VajYHBv/5UMDAwwMjIqMIzbNLrKy01lfUdO/J2SAjf1K3L2DNneNKvH+uPHyfdxgYPHx90\nu3bx410Ny5RKwjp14kjKz9RJSqIGonP6AuD/2LvvgKzK/o/j75uNgANBERVFRMUtWmq5cktuM3Pl\nNk39ZWrObDgzV45Kw5aVK/fI+eTeWxE3OAGRKXvevz9u48lHKzAIsc/rn7gP17nO91wcie+5Vj3g\nJSDyYX+RgwNcvgxRwTClGbg5gud+OBwEG2Oh9H8g0sGBRqMiebEBpKbCzgFQ4wZ4AQ7Ay8AVoG4w\nnALCXEy93Skppl7x9yeZeu9nzTIl5vfvmxabi401zY83N8Arr5hWmQdTD/6NGzBqlCm+/fvhyy8h\n7Sa8vgG+rgKOA2DnPhjd3bTYnZcXbNxoellgHQJjLkM31//O+bd1gCKuEPnA1PufPz+4FQa7QhAX\nB8uXwzV/B4q4xNCggWmkwPy5MD4kndGdOlHlYCoWB6Aa8A7wAhDlCEOmmuoKDYWoAbBsFUSmFiIx\n0ZFKfteJAyY7gGVV6PwAZp2H+3Z2PFxGAHOjkfT0dMzMbmYs/Gcw3ABg97RpLIiPB6D8gQOEhITg\n6uqKubk5M3/55bFn5P9mzza9HXlK/WbM4BszMxLv3KHZ//2fOhBF/keWE/p+/fphY2PDypUrWbhw\nIZaWlpQqVYpRo0ZpH3oRERGRf5Etvr68e/YsDkC1s2dZ9803dJ86FeOUKRQqVAiDwcCOli15Z+5c\nil+8SIEtW5j1cPj1byledXNz9jo70y8khG+XwqobcDMIuvY0zTfv0sVUbqsBGqyAm126UNzbm/O+\nvgTdjCEmxrT1XIoXNLGFhhfhNHABqAq8BYx0gWhnmPEBFAoGW09TL/zNm6b59OHhcPQoTJ0KO3ea\nesUdnUxJdvPmpmTfxcVU1srKFI+9HaTeh2FXYUIB6P+haS69S0U4dRCatjHV6fFwtXlzd+j/EhRz\nM/XEm5ubEu4CDlCmLESFgb0lXDoBrR/ApbJwMsaWtUdv07mjE5cupXLhArzeFb6MN6PA/v2kOkCS\nAe7GmtHezIw3UlMpmAJh900JfWQwFEmBLoEQG96O6UuW8BmDmPrttzg0SKPtKNNLjuFTivD597tZ\nPmYM+S5eJLFKFYb37o3/J0e4cOEy6ekWODrWByA1MZGLQDngsJkZhfftY+3u3VRv25Z6r76a7c+Y\npaUlb82ale31ijwvspzQg6mXvnv37tkdi4iIiDxjtm7dir29fcbn9PR0du7cieP/DHv9bZ69/Lt4\n1a3L/kKF8ImMZH/BglyP8mf27EqkpFjx8ssf07ZtL5p37crluXMZFhvLTMCIabh3GHAYONmoEV0n\nTGDW/PmE3bxJSbMaPLBZSokSpi3NUlJMQ9wjIyAEcLaywrZMIW7bBhCzHc4cAbea0GOQaV/2zfOg\n/n3T/PBeTk5cDgsjrREMessUs++7kJxk2qO+cWPTvPSkJBg72jSkvUMH05D5/ftNSfHs2abe8gkT\nTAn49ElQ3Rn8LkBaKnxrhJQkuHQenF0hKR4OLYVTm8ElHB5UhQt+4JAfipQzDcUvXtwUy7p1kPQA\nAr+E18LgC6Ay8Dqw6ARUJ4FerZ14oX4qP/0Ik6eYzkvvk86yBBg8Giys4KsZ1my/ZuB2aiovxMDs\n6ZYUqFKAlBPhVE0wUsXGhmvFi5Oens5IX18mJicTl7gUMK0HULCYIyXc3Hhv+XL2b9vGg4gIQu/d\nI2nNSR7csOaaexkW7J8MgGvduhzauJENQHr16iQPGcLQiAiWr1+P35YtVK5VK8efOxH5r6dK6I8d\nO8b58+dJTU3FaDQ+8r1BgwZlS2AiIiKSu1xdXfnmm28eOVa4cGF+/PHHR44ZDAYl9P9StRs3Ztu8\neXy+axceTZuSeH4KPk2DAdi162vatjVNx4x1diYRaA0MLlAABzs7Yh484GBaGolmZqybPok7adG0\nGTeGV19tw48/lmb1so9IjUxn1iiws4QH/hBvMFC7ell27RpE1Qbp3LwJrnameemHD5sWjPvP93D2\nAZzIV4BijRvzf6tW4XD/v73iNomQWBBatTL1zAPExYJDATh1yrS1nIeHach8eBCkJYJbRdNiemYG\niDwPt1Kh1btQsxlsXgbtvoVvDkAZT7h8FpaFgUsYdATsdoNFOrT+0DRkf90a6D/Q9MLA0xN2LYN1\nYaaXHEG2sO1F6GIJLseghhnE1U7lQYxpO7tLF6GCF5w8CV51oWRpU/zFSyfy9TkjacAAoNb1FNwG\nj6XaiBdZ9dknbHc+SoWinzBq1CFmzdpOjQYN2Dx+KT/GQ3o0uJSuymfDhnHl+HG6nTuHR2IiE8uW\n5YurV7ECbkSeY+eqVbTr3ZvyjRtz9NgxEgoUwP2FF2hx+DAAzUJD2XngQJYT+oSEBGxsbLTQpshT\nynJC/+mnn/Ltt9/i6en5yBt7MP0PXQm9iIjI8+HXX3/N7RDkH5SUlERYWBjFihXD7LdN2TOhZc+e\n0LMnANuGL8BoNM1pT08vmFFm8E8/4Tt2LMa0NKZMm8ayvn35v82bARh3YBeGN4y81h5WLe1LzZrn\nGThwItOWbmfQwYM4Yuq5TgIGYaTt4pmUa5rOa6+Z9nz/bZOllSth1wZIK2CF3fxkDu6N5c66VbQA\n/hMFQ7qaVrBfGgiG3bAhHhKS4PgvYOFiGi5vbw+dO5vqO3UK+vWDk4fB77Jp6H0+G1h6yIwIj3Sq\nNzaVq9sCZu6BqeNMLwxOloX5/vBiNNgBqUDcIfhhCITkd8Hd4MbXM+IpVbMyW5fupMiJcI4BLwIH\na8C7H5nq9Z0KhfaChTm07mQaRfDll3DxkmkrvEuXTFMGrKwg3szIR2VgUgBUB4YB07Zvp0nnzuBp\nTeeWD99csJ/Tp09TukYNipSpQ739Fznp7s75q/sx8wwmwh7uAYeKg1lcCBdsbKiRmMjOAg7Ehd0g\nMDCQ8FmzmB0SQnJICJ9WrMjs8uVpdfkymypXZlC3bpl+boxGI3P69CH/rl0EOTnRc+VK7gcHE3r7\nNi26dMHqt7kNIvKnspzQ//zzz0yfPl1v4kVERESeEzduBDBrVnuKFbtLWNgLfPrppoxmpdv7AAAg\nAElEQVR9yLPi7be/46efPsDc3JYRI+ZmHC9YsCDDFi36b8FixQgHHAG/wjDyTdPh1q/Fc+zYr5Qp\nUwb3Nm34z5EjlEpL4yimBfRuAW2vxbKjjGmrtqQk01x4gwFizkPDY2AYncyxY1ChchqhV2H4cYg2\nmMoApDqBoSx8cgwqAXeAtxvCkHEwewasXgX5C5rqLVwYmreGuBQIug3HDxSjtGckrd5JZPlyqFMH\n9iyFF2JNw/Lz54fwMNifAHHAd0AEMCzVQOXiTZjx0084FymS0QwBly7xU/Pm7L59mwkGA/Zp/x35\nmpYKJ1IgPcX02cwMHOxNUwLW/wz5LsE3F6BRBxgyFDb/DGN9zWicno45EBcQwCFvb5JtYwksZ4Z7\nmXQunHPg6Ict6R4bi72nJwU3bKB/2bJ8Nr0ULV6DyEjY4Ai9BoPhaBwrrnVg5e37JJU/R+0SHzNz\n5s9UTkwETEmEnaUlbx48iP+ZMwyrWZOCBf/7EudJUlNTGefjg+Xhw6Tb21MsMpIBSUmk373LsK5d\n6XD1Kl6xsUz/6Sc+3LYtaw+fyL9UlhN6MzMzatSokROxiIiIiEguWLFiFh07nsfMDK5c2c7Bg3tp\n1KhpluspV64iH3+8+pFj1/z9WTt8OMakJOwbNqRljx68tWAB3+TLR1JoKCWi77Fj7W5eaWNk967C\njBrTAICuY8ZwslEjJjRvTqcHDzgPfAPUcgL3QBj7f6Ye8OWHIdjSnKZ3HLha0pEjh24xfmIqBgM4\nFoLhp+DedfCfZ1rYrrwXlG0DawdARDIctoXIvTDdH2ziwO8AONSFwiVNe8cXK2ZaDK9aNfCsMJwd\nq+Zibh5CaqppeL6tIwy8D++PAfOSEOkPdtYOWCXHcAzTAn39jEYOWFhQ2MmJs0eO8EWvXiSEhRH9\n4AGJDqmU6Q41ihrx3wsrxkOcGbidhveA/1sBGy9CbAjcv2tgwQkj9W5Dh3h42w28vU3JftAtG158\nuz9Hv/mG/1hakgS8ER5OF2DAnCKcfMmLAssP8m5cKuWBFv7+fLFmDTWmTycqxg54wPXrUK+56eXH\nC3XSWXb2NnFBFxkwLgaAOnX82XWrPnsCTlPI2pVxU6ZQuHBh6jdpkqnnY+mkSRTeuZOxALGxjHi4\ni0YUYBcZSdOHWx6WOH+e+Ph4rWgvkglZTui7du3KwoULmTx5MjY2NjkRk4iIiIj8g1xcPAgOtqB4\n8VSCg51p3Lh0ttW9ZtgwRv/6Kwbg43372LtkCRW/+47Bn32WUWb37m0cO7aTVq3rUrx4iYzjNWvX\nptkrr9B/wwZ+Bf5TDArPhMquYJgFk3+BDywsaD9iBG1GjGD9559T/8vJ3AgAdw+4fBo6G2GRI1Sq\nASVKQJkycOwwHLQGqxFQvjo4TYH42+DcFKJj4d33TUntiu/hyh54dQCsWuFK4TtbSHmQzKwpMPHh\n1nB16sAnh6D7JfC7BBOBOGJ4u1gxFoWE8P3D9aZSDh5k9+7d/Ni6NbaJiSQAK4FpFaFxf9P9JqWA\n+XmwPF2A/A1fYsytW9hfuMCcYEgA5lhZsq+CHbbvRDL7OLyxEgLehhB7CLqRxO1z65gZH08y8I6t\nLfGAJVDayYtiJRrjHbeXk0B54ISFBSWrVsXOzo6XXvqA2WPHYAxNw6YItB8K/v7FMdt1gV6JcZza\nBTWawN69rhSvcokWo2I5cCCSexHBlMYz089CzN27GV8bgZQSJVhQoQLG4sVxL1CAywsW4JaSws3S\npbG1tc36wybyL5TlhP7s2bMcP36crVu3UqRIkceGY23fvj3bghMRERGRnNer1wg+/zyCgIBLeHt3\noGzZstlWt0VyMr8td2YP9A0OZuHPP1Pntw3egVdeaUnt2g24ePHiY+e3mzaNaSEhxJ4+TU3HZFwf\nrhBfwhvu/wLlihal56RJWFtbY0hNZXgYjJoAfkUgMhA2tITX+8LK5eDvB+mRUPscWLpC7Uamuqo3\ngSvXod9QWLXKtAaApSUkRIHbdUcubquPl609d2J/YsinpsXpdqyDjj1h02pwijOnNWlcwpRAFwRe\n8vTEomdPAmbNwj09HT8XF0I+/JAvExOxxjTP3QaIDTNtk2dtDbGxkFLIhrG7duFesSI93d2xALpj\n2mP+VHIy9RonU8HLtDjeymPw5QWYBbyCkXxBQVg+jMHLw4NvOnQgIS4Oq/R0ws+c4dsqVXAJCGCg\nrS0vv/suvfr3Jzk5Gb8Zn2MVmIYTEHPHksh7H9C69Sts/LQhzdPAMBdmrLLDsWxx6rQ9DkCdOvc5\ncmQ7tWs3yPSz0G7sWGbv2cOo27eJK1iQ/1u7Fq+HI3+NRiNrypZl961bjBgzRovkiWRSlhN6Hx8f\nfHx8ciIWEREREckFBoOBoUOnZktdkZGRLOrRA7vQUJw6dKDOmDG8d+kSZmFhNAB2mJvj/tJLf3h+\namoqQUFBFClSBAsLC8pWrMj4w4eZ7OlJVMB1Vi8Cd284usUWt0I2pLVpg7W1NQCd33uPjw4epEJw\nMNcLFMWsgT0VWm+jcGHTyvLfDYAfbpn+AN6eBn5HwaMqBO8Gy/KOQARNm8K8eWBnZ9qC7o0vvqBV\nly7M7t4di3JgYQGVq8DmH2BGN6gWCS/4fsPyGzfg/Hl2bN5MtI0NRdq0wWfQIOZHRXH/7Fnyly2L\ny7Vr/Da+NR5TIh55GX4ZBrdcoRDA5TQ2z57NzWvXmBEaSiim3uyXgd7AoENQryHcuA5+MdaMMiRT\n12jkCmBvNLLEzo60woXx6t8fn969mdO9OwOXLcMOmFy9Or0uX8bFxQVzc3MA/M6cwTIwkPmYFh8c\nkJLC+UQD5cqVx7ZgQaaGhxMQD/lvJDPq6nG+T4MX34Tjx0tToUJ+Pv30XVwtS3Dvm+9ItbSk0Sef\nULt5c+Li4oiMjKR48eIZyXlpT08+u3KFmJgYChQo8EjSbjAYeG3w4Gx5BkX+TbKc0Hf+benPJ0hN\nTf1bwYiIiIhI3hUTE8P4xo2Ze+YMNsDyGzdwO3WK0rVq0XzbNrYDdxwc+PCNN554fmxsLJ82a4b3\ntWuc8fRk5PbtGYlfODAzAS6thC9DX2HRjlUkJCRQsmRJAKKjo/mgQQNsL17krJMTn+7fT2pqKh99\n1IKChS5wdBfEh8EiTAvVlQ2Ho/MKcD85GrNYawz5SjP30wc4u6bSqRMcO2aaO79r4UJadO7MG598\nQq+eKyh7Pp2ICLBNgXX3wNfcHA8vL2r07MnMnj05bW1NRKFCdH3pJdNuAUYj3U6fptrRo/RzcWGu\nszM24eEUtLTkhJsbFkWK8PKFC8y7FoUv0JgUlm/YQLS5OWUxJfPHMCX0MUD+3XD4KhSPAZ9Slaiz\naApLR4ygWVgYl8qV483vv8fJySljgTrL+/f5bV8qp8hIihYtmpHMA+xduZKPMI0WGA0MBir4+/NT\n48ZEFyzI/bQ0vo+K4ouUFLyBEjtg1ql8OL3THjOzSdSsGc/Xs63x9UvCDpg9dSpWdnbs6tOH4mFh\nbC9alJc6dODNiROxtbXF3Nz8LxfPE5HMy3JCHxERga+vL1evXiU9PR0wDZFJTk7m2rVrHD16NNuD\nFBEREZFn3+w2bfA4c4bf0kWL9HTS0tJwqF2biL17eT0hgS+8vf9wfvShdet499gxCgNNjh5l3Rdf\n0HvcOFJTU6mQkoIVUBWoZG6Ok5PTI+fOGjyYZD8/6gP17t1jRMOGvJCYSIOgIL5ebcn86BQ8jTAW\nmA6M8PDgzXnz8O/QgeEpSbD3FAsHDuSE3za+v3Abbw8jtvuhYsJlwsLCcC1RgqrenpibX8bdHRIf\n/hX9cload+/e5Y6LC2W3bKFjdDTG6GimfPIJr8+cyYlrK4h7I5kvj0DJKyHcs7LCY+JEhvXqxbev\nvUa/gwf5zsGBtoUKMSIykoNA04QEagFTgHrA6gIFuFezJlH585Nv+3bG30gAYJRVMC/Ur0/DCxfY\nuno11WNiKFmyZMaIBYDyvXqx6PJlHOPioE0bLCwe/fPfo3ZtlmLav/59wN3CgrCff6ZHSgqlgcEl\nS5IeFUVlYJaZGZWtrDBWq0t6ehDlysUDUL1+Mre2QgUg1dycfQsW8N7Vq3wCzI+MxDh9OvMuXmTs\nunVZfqZE5M9lOaEfP348gYGBNGnShKVLl/Lmm29y69Ytjhw5wpgxY3IiRhERERF5xqWkpOASEEAn\n4FMgyc4O90GDKF26NKU/+oj/VKvGrps3GfPWW4+ct2LGDMJ378bo6YlzmTKct7enUWws5+3sKFWx\nImDaZSmsVi2O3b1LsL09zi1aPFKH/9mzlNu8mcnAcUwry9uHhjI8MpKjQPUo8HpY1s7cnDmenvT7\n+msSU1KoaTBQCFPvt3PBgmw4eJOvJ0yg+syZVE1JYUpNN1J2/ISf31IiI42cOVOO6LvB2F5OYoq1\ngeTatRnfsiVJSUnsNBi4A1wFvHfuZGLHOgz+LAZLS7j2MpQaBvWSk+m1fC7XEwJpeeoUpYBRMTH0\nrAw/NjEQ7G/BJv8UzAF/wLdUKb4+dQpHR0cAju7cyTuvv06xqCjaBAezoFs3StSqRakZM6gYH8+M\n1av5YOvWjLZp3r07kT4+xMfHU7x48cd+bm06d2bMt9/Sc98+GiQmMjA1lXRgPjAUKOXtzcyKFbGJ\njCR/mzY4t2pFF6ORu3cvsn//r3h4hOHvXwFjvcJstLKi/Zw57F66lHuYdiEo8PA69jdvPs1jJSJ/\nIcsJ/dGjR1myZAk1a9bk6NGjNG3aFG9vbxYvXsyhQ4fo3bt3DoQpIiIiIs8yS0tL7letSvTt29Sz\ns+PW6NH0/OCDjO836dDhsXOO798PH39MTEIChu3budyyJfkmTmThkSMUefllXm/XjusXL/LjG29Q\n/P59ljZqxOA5c6hUteoj9QT4+fFyjGlrNW+gK2BmMBAM7Ma0oNzXQLy1NaXGjKHHhAlYWVlx+dw5\nphUowOqYGFK8vPj0Ybx9p0xhbYkSHLl6ld5Dh7L4q1do2fIW6ekw930HVh6OIR/wRf78tP3pJ2xs\nbNj01VcMiY3FATgEdE1MxBiSSNh9KOYKd29CzVSYXAHenPkAg2EpC3bb0eB4HBOdof8MyJfPSMD1\nFGYPN9Ar1sgDYOTNm/ifPUu9V14BoHazZhwrXZphZ84AsPfaNfZfuED1+HjcARc/P5KSkjJ66aOi\novjhB19KlixO+/bdHltszmAw8OnWrYSEhLD+hRf42OoOcTXgwh0Lwm1eZsgXXxAREsKaXr3It3gx\ne2/epOGgQTRr1omyZaty9eoFPl/UDjs7u4w6y3zyCUvS0ji/eTN7bt3C3MwMs5df/tPnJzU1laWT\nJxMXGkrniRNxcXX90/IiYpLlhD49PZ1ixYoBULZsWfz9/fH29sbHx4dvvvkm2wMUERERkbxh7Lp1\nbF2+nMLFitGzWbO/LB8WFMTFhAQ+BMyADw4cwGf5cgqOHp1RZuO0aXxw7hwGYEtEBGb/s8MSwCvt\n2/NJ3brUOXqUw+npNAWKRkQwyNycGmlpvA6EAV/Wrcuwjz8GTFNGJwxpQa2+9wm/Bml+YRn7nhsM\nBjoOGsT+/bsJCr5Lerrh4TlgjInjtwHt+ePjSUlJ4Ydp09j3ww90SkkhBrj98PuvRsDgcZCvamHs\n7KuxpNhl4r0isLc3DZkvU78ks2o04OrWZdSJjiVfPoiLs+J2m9bMWbuFwgWTmFmoELPKlXvkfq0b\nN2bHlSuEpqeTFhTEvOholj28x/3p6SR060btt97C2aM0H374IrVqRbNiBZw5s4uPP/72iT8LFxcX\nEnr3pGDh6TSsDk2TUzl9ujIurq4sHz6c9/38MADL163jfqdOeHl5UalSNSpVqvZYXZaWlgz+7DOM\nc+dyZO9eAAY3bPhnjwJfDh1K58WLcQImnzjBR8eOaaV7kUzIckLv5eXF5s2bGThwIOXLl+fQoUP0\n6NGDoKCgnIhPRERERPIIS0tL2r75ZqbLN+3YkXVFi2K8d4/7gH2+fBlrNP0m4Pp1wgEn4FpqKqXS\n0h6rx87Ojr4//cTm6tUZ/+AB+YDPgVeKF+d+rVpMP3QIg5MTLSZMACAuLo4ZQ4fiUesedVqa6ljy\nfuQjdU6a1Btn52UkJFiTmNiI7dudSUlxoGR8IFO5QX7gbJky7GvaFK+AAJyAdywtaWljQ6C7O8PC\nwvAKCmLFLdgWmUzVc19TunRp5sx5l3PnFmEwGHEu2pjRsz/ntSsj+Wh8V5xKpOHu0YoFy6bTv1ct\nGnY5SYXUSBYtGsHkySszYhs4ezZnu3fn4vr1DJg8GVugL9CxaFF8g4JwWruWz86eJa5PM/r2jcbM\nDJydYcuWPX/682jRtTsbN34BRBMfD/fuhTBjxttEGhKJBRyA+/b2uGZyj3iDwUDdRo0yVZbAQFwe\nflk8JITk5ORH1gIQkSfLckI/cuRIBg8ejJWVFe3bt+frr7+mffv23L17l1atWuVEjCIiIiLyHLK0\ntOTtTZvoNLIxFWsmcPmqBb1SUh4p4+7uzrLDhwFIh8cS/t8UL16ciDJlsDpzhjPA+UKFaPDWWwwf\nP5709HQMBgMGg4F7ISGMrVmTIUFBfNsSAqrAkSMQZVeApKQkbGxMG8vFxx+iYsVUIJXo6AcMHrSB\nk7t3Y9fEkTNLlmAoWJA6bm50+ugjnICbwJfm5uTfsoUFdevy3cSJNP30UyzT07ng4kITZ2cA3n13\nDgcPtuP06WO8+qrpbUKZcuVYuvrkI/fj7JrIwwEDGI03Hrvfat7eODk7s2zZMt66fp3VxYpRoUIF\nnO7dA6BURAQRLp5cuGBOlSpp+PmBo6PXY/X8XsWKlTh2bBy//voLZw8HULPuBmrXTmVHtCszOrbD\nOT6Jcj16YG9v/6f1PI0Sbduy6sQJij94QMRLLymZF8mkLCf0L7zwAr/++itJSUk4Ojry888/s3Pn\nTgoWLEibNm1yIkYREREReU6dOLubPiNjKVAA6jwIYs0aX95++/2M7zcfPpxfTpygUnAwJxs0oFKl\nSk+sx8rKire2bGHxrFkUK1+edxs1Iu1hb76ZmRmpqalYWFiwfuFCqgYFUQNI+w/MNYe3RkJs7F3m\nzPk/xo//CoCUlJIkJV0jIQEu+IXwfn8PnC8lUtDMg247duBWpgzrfH25b26OU1oaocD98uV5+eWX\nMTMzo8+UKXxtZsads2dpO27cI3PMN2yYTfnyW9iwYTp+flPp0uXtx+7HweEl/P2vkpJihpNT/Sfe\nc/GSJXl9+3bW/fwzdVq0oHpsLDPv3qVUeDiBzZszuu+7LFtmydKl3+HsXIW5c33/8ufRu/cYloyP\nxsx/H/XHm45VqxaERc2OdOr0JvHx8Vy8ePEv68mqDkOGcK15cyLu32d0nTrZXr/I8yrLCT1A/vz5\nM752dXWlV69e2RaQiIiIiPx9aWlpLJ8zh9iICLqPH4+Dg0Nuh5Rh/5YtnN25kya9elGqVHmuXLGj\nQIE4bt60oXRpz0fKVn7hBUqfPEloaCitSpc27e3+B1xcXRkyZw6+vpNZs6Y2lpapbN3aH85HYbt7\nN6FFilDlrbdIy5ePqfHxlEwB11IWGAypODhAcnJIRl0ffrgOX9+PCQm5T/16K6junUrYPQh5+zq/\nrlhB7/Hjad+/P1+eP8+W48eJc3dn0fffZ8Rnbm5OjwkTuHjxIl5e/+0Zj4mJIV++E5Qta6Rs2Sj2\n7v0FeDyhHzduMfv3v4GVlRV16tT7w3su5eFBr7FjMz5XOH2a6OhoOru4YDAY6N59GN27D/vLn8nv\nxd25Q5dQWDIfqraHAwc8+eSTV7NUx9Mo6+kJnp5/XVBEMmQqoa9cuTL79u3D0dGRSpUq/ekCFX5+\nftkWnIiIiIg8nc/ffpuOS5ZQKD2dWUeP8uGvv+Z2SADs27iRB336MCQigoXr19Nh3z7u3v2A3bv3\nYWFRhiZNHh/xaW9vn6Vh3rdubaFJk2gANm7cjM/KuzRNTCTt1i0+r1aNUrNn47B3L+Yvvoh95Gm+\n+GIVYEatWuUz6ihQoACjRs1h69Z1BAUtAyCfA5wtYMc7zZsDpjnib8+f/9j1ExMT/3DIuL29PeHh\nxUlNDSEszJz8+cs/sZzBYKBBg8aZvuff5MuXL2Nxv6fVYuRI1p48Sbl9IeyPLMena7dkbJv3d90K\nCGDjZ59RonJl2g0YoIXvRP6mTCX0vr6+Gb3yS5YsydGAREREROTvM7tyhRIP55s73biB0Wh8JpKn\nc7t2MTQiAgCfmzc5d+gQvXuPJj5+aLYN5U5PdyUhAczNISmpKKH20ZCYSDRg4+hIu0GDYNAgABYs\nGE/16kk4OsKuXcsIDh6RsaMTQIsW7fjww9c5f3Y/QQHmDPt8EZVr1XriddPS0nj//S6YmR0hKqoY\nI0eufKyMmZkZ77+/maVLp+HkVJJ33hmZLfecnSpUq8bIU6eIiopiYJEi2fbcxMfHs7RtW8ZfuMA5\nGxtWRkfzxnvvZUvdfyU5OZmYmBgcHR2fiX8HItklUwl93bp1M76ePXs206ZNo9z/bJ8hIiIiIs8O\nh/r12XPsGE6JicTUrPnMJDENundn0fr1+Ny+zfJKlRjcrBmrVy/myJGFxMZC375f8uKLfzzEPDPG\njVvKokXvk5qaxOTJU9lXeSUL1q4lrUQJBk+eTGhICD+88w4kJhLiYaRyZdN5hQuHExYW9khCb2Zm\nxuTJyzN13a+/XkCJEmuoVAlSU+8y/i0fRk3/8bFyLi4ujB79eM/+s8Ta2pqiRYtm+bzU1FSSkpII\nCwsjOiqKKlWrZjx7d+7c4cXAQMyA6omJHDh9OpujfrILF86yeHF3Che+T0pKYyZPXvbM/HsQ+buy\nPIc+JCQEc3PzbAvg7NmzfPTRR9y4cYNKlSoxffp0SpYs+cSyUVFRdOrUiR9++AFXV1fAtIfotGnT\n2LhxIxYWFvTu3ZsBAwZkW3wiIiIieVGvSZM40rgxQRERvNeuXW6Hk6Fq7drk372bs4cOMahlSwoV\nKsThw7No0+YaRiOsXfsxL764829dw97enlGjPsv43H7wYBg8OOPzt/37M3LLFsyB96pVYm1KFQoX\nDiU5uQGVf8vu/0JUVBQ/TpgABgNvTptG/vz5OXlyFcWLm74fEQ6u/gHcvHmTihUr/q37ySvOHDzI\n1oEDibh7lwpJSZQ2GpnTpQsjv/8eMO1Y8KO3N24HDnDa2ZkK/9BzuXbtTDp0uIDBACdObOLKlSuU\nL//kqQ4ieU2WE/oOHTowYMAA2rdvj6ur62Pzg7Ky0n1ycjJDhw5l3LhxNG/enMWLFzN8+HDWrFnz\nWNnr168zYsSIx/a7X7p0KefPn2fXrl1ERkbSp08fPD09aZTZPS9FREREnlN1ntG/h0p7eFDawwMw\nbUNnNP6+syj7Oo7+iPWDBxl/BJdISGHo3As8ePCAQoUKZbrn9ouuXXl32zaMwLwbNxi3eTOFCxd6\n+FICrp2EWnH5Hlnd/p8SHR3NmgULKFWxIk06dvzHrrtn9mzG+fuzAOj38NiVPXsydhiwtLRk3I4d\n7PvlF2p6eVHuH3rRYW9fjKgoKFQIwsMds209AJFnQZYT+o0bNwI8Mek2GAxZSuiPHDlCwYIF8fHx\nAWDw4MF8//33XL9+HY+Hv+TBlMz37t2bkSNHMm7cuEfq2LJlC/3798fBwQEHBwd69OjBhg0blNCL\niIiI5AFmZmY0a/YxW7fOJSYmnbffnvGX56SmpvLN+PEk3rjBi/37U6d5c1bNmkXIypXEFS7MgB9+\nwOnhvu9PUmnQID67exeb5GSKvPkmFhYWWU7yHIKDsX34tX1wMAADB87n88+TCfI/QKtziZRLiufY\n8uU0aNAg0/VGRkYyd+5A4AGNGg2lceOsbQudmprK7BYtGHX0KH758rEyIIAuo0ZlqY6nZShUiFgg\nDQgHCgL3ihTBwuK/KYetrS0tOnX6R+L5zZAhU/nsswQSEm7zyitv4vwnz4ZIXpPlhH7v3r3ZdvGA\ngADKlCmT8dnMzIySJUsSGBj4SEJfrFgxduzYga2tLWN/ty3Hk+pwd3dn/fr12RajiIiIiOSsVq26\n0LBhGy5evEiZMn+9bdl3H3zAq7NmUdxoZMHx4xTato342bP5v5AQkoEvRo1i+MNh3k/SrFs36nfs\nSFpa2lP3oOdr2ZJNAQGkAw4PO6dKl/Zg5sydLKxUiaGx/kAKp0+dylK98+YNpV691VhZwaZNgdSr\n1wIrK6tMn3///n2qXrtGfuCl+HgWHjwI/1BC33/+fHxTU0kLDWWenR1OhQoxYOLEf+Taf8bKyorR\noxfmdhgiOeKp9qGPjIzk1q1bpKWlAaZ57MnJyVy8eJG+fftmup6EhARsbW0fOWZra0tCQsIjx/5s\n642EhARsbGwyPtvY2JCYmJjpGEREREQkb4m/eZPiRiMAnqGh3L9/H/OHK/qbATz8+s/8/u/Hp9Hv\nk0+41Ls3ZmZmjy0WHe3mRqy/P8lAlItLluo1GmP5LX+3sYknOTk5Swl9kSJFOFe+PA0PHeKCvT1F\nszA64O+ys7P70xcpIpL9spzQ//zzz0yaNImUlBQMBgPGh79MDQYDlSpVylJCb2tr+1jynZCQkKW9\nM21sbEhKSsr4nJiY+Lf33nweJSYmEh8fn+Vznndqlyd7mnb57bznnZ6ZJ1O7/LGnaZvf/39NRB7X\ncNgwZh4/TrnQUPwaN2bcSy9xY+hQ5q9eTYyjI/1m/PWw/exQoUKFJx5/5+ef+fHjj0kzM6Nd+/ZZ\nqrNt2zEsXRqItfUDSpXqhr29fZbONzc3571t29jo64tbhQp0fjh6QESeT1lO6BctWkS/fv0YOHAg\nzZs3Z8WKFcTGxjJu3DheffXVLNXl7u7OunXrMj6np6dz69Yt3N3dM12Hh4fHI0P0AwMDs3T+v0Vg\nYGCWX3QEP5wP9jxTuzzZ07QLqG3+iNrlyf4N7QJP/+9JRP5YtTp18Dh1ivDwcKMa1WQAACAASURB\nVNq6uWEwGOgxcSI8A8O7wbTK/qCZM4mPj+fixYsZx+/cuUPQnTt416r1yLzy36tZ8yW8vc+Slpb2\nh2X+ioODA91HjHiqc0Ukb8nyb4l79+7RqVMn8uXLR8WKFTl//jytWrViwoQJTJgwgT59+mS6rjp1\n6hAeHs6GDRvw8fFh8eLFuLm5PTIn/q/4+Pjg6+uLt7c3sbGx/Pjjj0x8Rn6ZP0vc3d3x8vLK0jkR\nERFAaM4E9IxQuzzZ07QLqG3+iNrlyf4N7QJP1zZRUVH/mhceIk/L3t4+y73XuWnPunVcHzKEiqGh\nTG3WjIlbtmBmZvbEsgaD4amTeRH5d8nybwpHR0eioqIoWbIkZcqU4dKlS7Rq1QoXFxfu3buXpbqs\nra356quv+OCDD5g0aRJeXl7MmzcPgNatWzNo0CBat279yDn/u5VIz549CQ0NpW3btgD07dtXK9w/\ngY2NTZZ7iP7u3LK8QO3yZE/TLr+d97zTM/Nkapc/9jRt879ryYhI3nd+2TKGPXxRF3r4MLdv36ZU\nqVI5cq0Vn35K+KFDONapQ9f/WVBaRJ4vWU7oW7RowdixY5k6dSr16tVj7NixVKlShd27d+Pm5pbl\nACpWrMjq1asfO7558+Ynlv/9sCUwzRMaPXo0o0ePzvK1RURERESeRmRkJA8ePMDt4ZD/v2JXvjwB\n5ua4p6VxwdWVZjm0ddqejRspMWkSb8TFcXjnTn4tX57GHTrkyLX+jqSkJE4dO0bpsmUpVqxYbocj\nkmc9eZzPnxg9ejTNmzcnLCyMevXq0b59e8aNG8exY8f48MMPcyJGEREREZFnxp61a1leowanqldn\nXv/+mTqn96RJHJo8mQX9+tH5559zbG2NO1euUCEuDoAK8fHcvnw5R67zdyQnJzOteXMsGzRgQ+3a\nHPvPf3I7JJE8K1M99OfPn6dKlSoAWFpa8s4772R8b9SoUYz6h/a2FBERERHJbee/+YZhN28C8M22\nbcTGxv7lfH4zMzN6jBuX47G1e+stZq5fT6UrV7jg6cmot9/O8Wtmlb+/P00PHaIWUOv2bRb+8AMv\nNmmS22GJ5EmZSuhff/113NzcaN26Na1bt9Yq8iIiIiLyr2V0cSEKKAAEOTpia2ub2yFlcHBw4KN9\n+4iIiKCzo+MfLryXm9zc3PiuVCnqXb+On7U1zlWr5nZIInlWphL6PXv2sHXrVrZt28YXX3yBl5cX\nbdu2xcfHhyJFiuR0jCIiIiIiz4yBCxfyja0tyWFhdBozBnNz89wO6RFmZmY4OTnldhh/yNHRkRYr\nVvD54sW4VK3K60OH5nZIInlWphL6okWL0rt3b3r37k1QUBDbtm3jl19+YdasWdSsWZPWrVvTsmVL\nHBwccjpeEREREZEsCQ0N5fvvp+HoWIw+fd77273WNjY2vL1gQTZF9+9UqVYtKtWqldthiOR5Wf5t\n5urqSt++fVm1ahXbt2+nQYMGrFmzhgYNGjBUb9dERERE5BliNBqZNKkN1avPw95+PHPnvpvbIYmI\nZJssb1v3e8WLF6dp06YAxMfHc+DAgWwJSkRERETkfxmNxkxtEfd7iYmJFCx4F0tLKFo0nUuXruRQ\ndCIi/7ynSugvX77Mzp072b59O4GBgdStW5e+ffvSrFmz7I5PRERERP7l0tLSWPrRR0QvX05s/vx0\n+vprvGrUyNS5tra2JCfX4urVICIi8uPh0SKHoxUR+edkOqE/d+4cO3bsYOfOndy+fZvq1avzxhtv\n0KpVKxwdHXMyRhERERH5l1qzxpcDBz7hQeBNOt5Pw+c6zP34Y7zWr890HdOnr2H37u3Uru1K1arV\nczBaEZF/VqYS+kaNGnHv3j3KlSvHa6+9xquvvoqrq2tOxyYiIiIi/3LHjn1Ou3YBAGyPhmZ7gHz5\nslSHubk5TZv6ZH9wIiK5LFMJfYcOHWjdujUeHh45HY+IiIiISIbUVFuMRtPXNywK8Fm7RvSbPz93\ngxIReUZkKqF/5513cjoOEREREZHH9OnzBcuXj8doNGPyl7MpW7ZCbockIvLM+Fur3IuIiIiI5KTK\nlWswderW3A5DROSZlOV96EVEREREnsa5I0eYUacOc7y92fHjj7kdjohInqeEXkRERET+ETvff58x\nR48y4vRpzk2f/qdlo6OjWb1oEWePHv2HohMRyXv+1pB7f39/Tp48idFopHr16lStWjW74hIRERGR\n50y6wYARMABGg+EPyyUmJjK7WTMGHT/OkcKFuTd/Ps27dfvH4hQRySueuod+yZIlDBkyhFOnTnHi\nxAkGDBjAwoULszM2EREREXmOtJ01i08bNGB2nTq8OGnSH5a7du0ar5w7hyvQMTycK7/88s8FKSKS\nh2Sqhz4sLAwnJ6dHji1fvpxNmzZhb28PmHrr+/Tpw9ChQ7M/ShERERHJ88pXq8aYvXv/spy7uztr\nPT2p5+fHYXt7Star9w9EJyKS92Qqoe/evTuNGjViwIABGYl9qVKlWLBgAfXq1SM9PZ1Nmzbh7u6e\no8GKiIiIyPPPzs6O/lu3smThQsq98ALtOnXK7ZBERJ5JmRpyv2nTJkqVKkX37t2ZNm0aYWFhzJo1\ni6SkJGbOnMncuXOxtbVl3rx5OR2viIiIiPwLuJYoweBPPqGJknkRkT+UqR56KysrunXrRufOnVm9\nejU9e/akfv36DBkyBGdn55yOUURERERERET+R5YWxbO0tKRr165s2rSJsmXL0qtXL6ZOnUpYWFhO\nxSciIiIiIiIiT5CphP7cuXN07NiRGjVq4OPjw8GDB3n99dfZuHEj5cqVo1evXkyZMoXQ0NCcjldE\nREREREREyGRCP2bMGFq2bMnatWsZPHgw7777LsnJyVhYWNC5c2c2btxIhQoV6NevX07HKyIiIiLP\niT3r17Nw2DDOHT2a26GIiORJmZpDHxkZSY0aNXB3d8fGxoakpCSSkpKwsrICwNzcnNdee40OHTrk\naLAiIiIi8nzYu2EDCX37MjQyki83bMBq69bcDklEJM/JVEI/bNgw+vfvT4ECBYiOjqZv3744ODg8\nVs7c3DzbAxQRERGR58/5X39lSGQkAK1u3+bUsWOUqlo1l6MSEclbMr0PfatWrbhz5w4uLi4UKVIk\np+MSERERkedY4169WLhhA61u3mR55cr0adaMe/fu5XZYIiJ5SqYSegBHR0ccHR1zMhYRERER+Zeo\n6O1N/n378Dt6lCFNmmBjY6OEXkQkizKd0IuIiIiIZKcSbm6UcHMDID4+PpejERHJe7K0D72IiIiI\niIiIPBuU0IuIiIiIiIjkQUroRURERERERPIgJfQiIiIiIiIieZASehEREREREZE8SAm9iIiIiIiI\nSB6khF5EREREREQkD1JCLyIiIiIiIpIHKaEXERERERERyYOU0IuIiIiIiIjkQUroRURERERERPIg\nJfQiIiIiIiIieZASehEREREREZE8SAm9iIiIiIiISB6khF5EREREREQkD1JCLyIiIiIiIpIHKaEX\nERERERERyYOU0IuIiIiIiIjkQUroRURERERERPIgJfQiIiIiIiIieZASehEREXnm7dmzh8qVK+Pt\n7U2NGjXw9vbGz88vt8MSERHJVRa5HYCIiIjIX7l06RLdunVj/PjxuR2KiIjIM0M99CIiIvLMu3Tp\nEhUqVMjtMERERJ4p6qEXERGRZ0JaWhrx8fGPHbewsODSpUvExsYyd+5c7O3tGTBgAB07dsyFKEVE\nRJ4dSuhFRETkmXDo0CEGDBiAwWB45Hi7du0oVqwYbdq04csvv+TChQu89dZblCxZkhdeeCHT9Scl\nJT3xhUFelJCQ8Mh/nwe6p7xB9/Tse97uB57Pe0pKSsqWepTQi4iIyDOhfv36XLp06S/LVa9enTZt\n2vDrr79mKaEPDg4mODj474T4zLlx40Zuh5DtdE95g+7p2fe83Q88n/f0dymhFxERkWfa/fv3Wbp0\nKSNHjsw4lpycjJ2dXZbqKVasGAULFszu8HJFQkICN27coHTp0tja2uZ2ONlC95Q36J6efc/b/cDz\neU9RUVHZ8pJZCb2IiIg80woUKMDatWtxdnamZ8+enDx5kq1bt7J8+fIs1WNtbU2+fPlyKMrcYWtr\nq3vKA3RPecPzdk/P2/3A83VP2TV9QKvci4iIyDPNysqKRYsWsWXLFry9vZkwYQLTpk2jbNmyuR2a\niIhIrlIPvYiIiDzzqlSpwsqVK3M7DBERkWeKeuhFRERERERE8iAl9CIiIiIiIiJ5kBJ6ERERERER\nkTxICb2IiIiIiIhIHqSEXkRERERERCQPUkIvIiIiIiIikgcpoRcRERERERHJg5TQi4iIiIiIiORB\nSuhFRERERERE8qBcT+jPnj1Lhw4dqFGjBj169OD27duPlTEajUydOpXatWvz8ssv4+vrm/G9uLg4\nvLy88Pb2pkaNGnh7e/Pdd9/9g3cgIiIiIiIi8s+zyM2LJycnM3ToUMaNG0fz5s1ZvHgxw4cPZ82a\nNY+UW7p0KefPn2fXrl1ERkbSp08fPD09adSoEZcvX6Z8+fKsX78+l+5CRERERERE5J+Xqz30R44c\noWDBgvj4+GBhYcHgwYO5ffs2169ff6Tcli1b6Nu3Lw4ODri5udGjRw82bNgAwKVLl6hQoUJuhC8i\nIiIiIiKSa3I1oQ8ICKBMmTIZn83MzChZsiSBgYF/Ws7d3Z2AgADAlNAHBgbSsmVLGjZsyIwZM0hN\nTf1nbkBEREREREQkl+RqQp+QkICtre0jx2xtbUlISHisnI2NTcZnGxsbEhMTAbCzs6N27dqsXr2a\nlStXcvz4cRYtWpTzwYuIiIiIiIjkolydQ29ra5uRmP8mISGBfPnyPXLMxsaGpKSkjM+JiYkZZcaM\nGZNx3N7enoEDB7Jo0SKGDh2ag5HnPYmJicTHx2f5nOed2uXJnqZdfjvveadn5snULn/sadrm9//P\nExEREfkjuZrQu7u7s27duozP6enp3Lp1C3d390fKeXh4EBgYiIeHBwCBgYEZZRYsWED79u0pWbIk\nYPojyNra+h+6g7wjMDDwsRclfyU4ODiHonl2qF2e7GnaBdQ2f0Tt8mT/hnaBp//3JCIiIvJXcjWh\nr1OnDuHh4WzYsAEfHx8WL16Mm5vbI/PlAXx8fPD19cXb25vY2Fh+/PFHJk6cCIC/vz83btxg6tSp\nhIeH4+vrS/fu3XPjdp5p7u7ueHl5ZemciIgIIDRnAnpGqF2e7GnaBdQ2f0Tt8mT/hnaBp2ubqKio\nf80LDxEREXl6uZrQW1tb89VXX/HBBx8wadIkvLy8mDdvHgCtW7dm0KBBtG7dmp49exIaGkrbtm0B\n6Nu3L40aNQJg6tSpfPTRRzRs2BALCwu6du1Kly5dcuuWnlk2NjZZ7iH6/boFzyu1y5M9Tbv8dt7z\nTs/Mk6ld/tjTtM3/riUjIiIi8iS5mtADVKxYkdWrVz92fPPmzRlfm5ubM3r0aEaPHv1YOUdHR+bP\nn5+jMYqIiIiIiIg8a3J1lXsREREREREReTpK6EVERERERETyICX0IiIiIiIiInmQEnoRERERERGR\nPEgJvYiIiIiIiEgepIReREREREREJA9SQi8iIiIiIiKSBymhFxEREREREcmDlNCLiIiIiIiI5EFK\n6EVERERERETyICX0IiIiIiIiInmQEnoRERERERGRPEgJvYiIiIiIiGSLlJQUrl27RmJiYm6H8q+g\nhF5ERERERORfwGg05mj9sbGxjBjRiPXrazBqVB2Cg4Ny9HqihF5EREREROS5lpiYyGQfHz738GBK\n69YkJSXlyHW2bl3Fyy8folatWNq3P8uyZXNz5DryX0roRUREREREctGdO3c4eugQqampOVL/6s8/\n562tWxkaGEjfLVtY99VXOXIdD4/K3LhRCICAgHyULVstR64j/6WEXkREREREJAeFhoby4Yev88EH\nbTh9+ugj39uzdi07XnwRY/36TG3ThvT09Gy/fgFnZ+5bWgJw38qKgs7Of6u+mJgYTp06RVxc3CPH\nvb1fxMtrLgcPdsHGZjLt2vX4W9eRv2aR2wGIiIiIiIg8z+bNG8grr2zAwgK+//4ONWqczvie34oV\nDA0OBuD+kSPcvn2bUqVKZev1W/fsyVdnzrD79GmsatZkQJcuT11X8N27LGnZksYXLzKrShWG7tpF\n4cKFM77frl0v2rXr9ad1hIaGYmNjQ/78+Z86DjFRQi8iIiIiIpKDDIYYLB5mXhYWMRiNRgwGAwB2\n5csTYG6Oe1oa54sVo2mRIjlwfQNvzZmTLXVtWrSI0X5+WAPlz5xh+9KldHv33UyfP3fuu0T/f3v3\nHlVVnfdx/HOOIBcRRJxwZZhoU2paQSLiZXRQK++SmpNjihYk5gjYlDIqjkTqIzlqmpk4lXabMsfb\nNF6X9wxx1HSa0fUUYuKlvAVHRkDgnOePxvPE8pJcN/vwfq111vLsvc/e39/2x97ns28n7wMVFDRQ\njx5z1KdPxQ8ugEAPAAAAANWqR48J2rAhR+7uhXrggVHOMC9Jo2fO1Ife3vpbVpaGJSbKy8vLwEp/\nXtvOnbXTz0+P5+VpT0CA2oSH3/FnS0pK9N13a9SnzwVJF7R9+58J9JVEoAcAAACAatSrV5S6d++v\nkpKSGwK71WrVyKQkgyorv659+mjj669r8fbtat2nj0I6d77jz9arV08FBX5yOKSiIslqbVyNldYN\nBHoAAAAAqGbu7u5y/++D6UpKSpSXl6fGjRuXOVtf3ex2u6zWyj8Xvc+oUdKoUeX+nMVi0fPPr9Cq\nVamSvDVp0uJK11LX8ZR7AAAAAKghOSdP6tUOHbS5bVu9OniwSktLKzQfh8Oh8+fPq6Cg4GenLSgo\nUMpjj2lpq1ZK7ddP165dq9Ayq0LLlg/IsecHtVi2Ta/16yebzWZYLa6AQA8AAAAANWTtnDmaduSI\nRpw/r95/+5sy9+2r0HwWPPectrVrpzceflgHduy47bQfL1igCVu3avzJkxr9979r3Z//XKFlVoW/\nvfuuYrZvV/S5c3pp7159Mn++YbW4AgI9AAAAANQQv6AgnfnvZe9ZjRsrsFmzcs/j/PnzCtywQSMu\nXNDvv/5a+xYtuu30/k2b6rv/Xu7/vYeH/AMDy194FWnaooVONGggSTrh4aGmwcGG1eIKuIceAAAA\nQJ124cIF3XPPPfL29q72Zf12yhQtv3xZxd98o5ZRUWrZsmW559GwYUOd9feXLlxQriTrz/zU3cDo\naKV/9ZV2fPmlPDt21NioqApWX3nd+vTRh1OnavHevWoQGqroZ54xrBZXQKAHAAAAUGelpb0gh2ON\ntm1rrL59FyoyckC1Lq9evXp6ft68Ss3Dy8tL3Zcu1cJFi2S96y499zOXrVssFsXeYplbPvpIX+/e\nrfDhw9WhR49K1XWnRpjoqf61HYEeAAAAQJ1ks9lUXLxJvXrlScrTjh3Lqj3QV5WwX/9aYb/+daXm\nsX31atWLi9MLeXlavn69Gu/cqZa//GUVVYiawD30AAAAAOokLy8v2WyNJEn5+VL9+re/dN3V/Hv3\nbkXm5UmSep49q2MHDhhcEcqLQA8AAACgTnJ3d9eIEUu1dm1PHTnyXJ37XfTHnntO81u21D8lrXzk\nEXXp29foklBOXHIPAAAAoM566KEwubv/j9q0aSMvL68aX/61a9f06afvyN+/iZ544klZLJYaW/b9\n7dvrt/v26fiRI0rs1Em+vr41tmxUDc7QAwAAAIBBpk0bonr1xikn57datGhKjS8/MDBQ3R97jDBv\nUgR6AAAAADCAw+GQ1fovBQZK999fpEuXuIcd5UOgBwAAAAADWCwWFRf/Unl50qlT7vL1bW90STAZ\nAj0AAAAAGCQ1da2+/362PD2XaNKkBUaXA5PhoXgAAAAAYBAvLy/Fxtb8vfNwDZyhBwAAAADAhAj0\nAAAAAIDb2rVmjRY+/rheGz5ceXl5RpeD/+KSewAAAABwUQ6HQ29OnCjH0aNyDwtTTFpauX/rvqCg\nQIdfekkJWVkqlPSmh4cSV66snoJRLgR6AAAAAHBRa5cvV6+lS3V/SYkO7d+vbZ06qffQoeWaR1FR\nkXyvXpUkeUjSlStVXygqhEAPAAAAAC7KdvmyGpeUSJICioqUfflyuefRqFEj2UeO1BuffKJcX18N\nnMJD/GoLAj0AAAAAuKjh8fF6bdcuNfrf/5WtXTu9NGZMhebz3Ny5Kpk1S/Xq1Sv3JfuoPgR6AAAA\nAHBRnp6emvb3v1fJvNzciI+1DU+5BwAAAADAhAj0AAAAAACYEIEeAAAAAAATItADAAAAAGBCBHoA\nAAAAAEyIQA8AAAAAgAkR6AEAAAAAMCECPQAAAAAAJkSgBwAAAADAhAj0AAAAAACYEIEeAAAAAAAT\nItADAAAAAGBCBHoAAAAAAEyIQA8AAAAAgAkR6AEAAAAAMCECPQAAAAAAJkSgBwAAAADAhAj0AAAA\nAACYEIEeAAAAAAATItADAAAAAGBCBHoAAAAAAEyIQA8AAAAAgAkR6AEAAAAAMCECPQAAAAAAJmR4\noD9y5IiioqIUEhKikSNHKicn54ZpHA6HXn31VYWHh6tLly5KT0+/o3EAAMB8jh49qscff7zMsMuX\nLys2NlahoaF6/PHHtWfPHoOqAwCg9jA00F+7dk0TJkxQTEyMDhw4oIiICCUkJNww3cqVK/XPf/5T\n27Zt00cffaS//OUv2rlz58+OAwAA5rJz507FxMSopKSkzPDp06erefPmyszM1LRp0/Tiiy/q8uXL\nBlUJAEDtYGigz8jIUKNGjdS3b1+5ubkpLi5OOTk5ysrKKjPdZ599prFjx6phw4Zq3ry5Ro4cqXXr\n1v3sOAAAYB6rVq3SvHnzFBsbW2b41atXtXPnTk2YMEFubm7q1q2bQkNDtXnzZoMqBQCgdjA00J84\ncUItW7Z0vrdarQoKClJ2dvZtpwsODtaJEyd+dhwAAKhdSktLdeXKlRtehYWF6tmzpzZs2KD27duX\n+cy3334rX19fNWrUyDmM/T0AAJKbkQsvKCiQl5dXmWFeXl4qKCi4YTpPT0/ne09PTxUWFv7sOAAA\nULvs27dPMTExslgsZYYPHjxYs2fPvulnrl69etPvCxcuXKi2OgEAMANDA72Xl9cN4bugoEDe3t5l\nhnl6eqqoqMj5vrCw0DnN7cbdCbvd/mMtjovysV8tdxvMwOKRr6KiIl26dKlcnysuLpa/R74a2M9V\nU2XGYr3cXEXXi8S6uRXWy825+nqRKr5u8vPzJf3/PsqVdOvWTcePHy/XZ+70+8KtXF+P19erK7j+\n3Sc3N/eGEyFmRZvMgTbVfq7WHsk121RV+3pDA31wcLDWrFnjfG+323Xq1CkFBweXma5Vq1bKzs5W\nq1atJEnZ2dnOaVq2bHnLcXfieucY1ffBSrXFDE6ePFmu6f38/DTjhQHVU0wtwnq5ufKuF4l1cyus\nl5urK+tFqtjfk/TjPsrHx6dqizGh5s2by2azyWazydfXV9KP+/sePXrc0eev7+svXryoixcvVleZ\nhjh3zvUOiNEmc6BNtZ+rtUdyzTZVdl9vaKDv1KmTLl26pHXr1qlv375666231Lx58zL3xEtS3759\nlZ6ertDQUOXn5+v999/X9OnTJUn9+vW75bg74efnpxYtWsjDw0NWq+G/4gcAgOx2u4qKiuTn52d0\nKbWCj4+PfvWrX2n+/PlKSkrS/v37dejQIb366qt39Hn29QCA2qaq9vWGBnoPDw8tW7ZMycnJSklJ\nUZs2bbRw4UJJUv/+/TVu3Dj1799fzzzzjM6fP6+BAwdKksaOHes8Kn+7cXfCzc1NAQEBVdouAAAq\nizPzZaWmpmr69Onq0qWLmjRpovnz59/x/pt9PQCgNqqKfb3F4XA4qqAWAAAAAABQg7juDAAAAAAA\nEyLQAwAAAABgQgR6AAAAAABMiEAPAAAAAIAJEegBAAAAADAhAj0AAAAAACZEoHdR27Zt09NPP62w\nsDB17dpVL7/8ss6fP1+jNeTm5qpnz546e/ZsjS4XFWNkn8nPz9dLL72kiIgIde3aVampqSopKamR\nZaPijO4ziYmJCg8PV+fOnTVnzhzZ7fYaWTbMq6ioSElJSerYsaO6du2q9PR0o0uqMkVFRXriiSe0\ndu1ao0uptG+++UajRo1SWFiYevfurVWrVhldUoUcOXJEUVFRCgkJ0ciRI5WTk2N0SZW2bds29e/f\nXx06dNDQoUN16NAho0uqEt98840eeughl/jOmpOTo+joaIWEhKhPnz7avXu30SVVWmZmpgYOHKhH\nH31Uw4YN09GjR40uqcLeeecdJSUlOd9XxXaCQO+C3n//faWkpGjixInav3+/Nm3aJG9vb40ePVrF\nxcU1UkNWVpZGjx7tEhvGusDoPjN37lwVFxdrx44d2rBhg7766iu9/fbb1b5cVJzRfWbOnDlyc3PT\nnj17tGnTJmVkZGjNmjXVvlyY2+zZs5WXl6fdu3frk08+0XvvvacDBw4YXVaVeO2111wiMErShAkT\nFBkZqczMTC1atEjz5s3T4cOHjS6rXK5du6YJEyYoJiZGBw4cUEREhBISEowuq1JOnz6tKVOm6I9/\n/KP+8Y9/aPTo0YqLi9PVq1eNLq1SSktLlZSUVGPfkauTw+HQ+PHj1blzZx0+fFhTp05VYmKiCgsL\njS6twux2uyZOnKikpCQdPHhQUVFRSkxMNLqscrPb7Vq2bJnS0tKcw6pqO0GgdzFXr17VvHnzlJqa\nqoiICFmtVvn4+Cg5OVkPPvigTp06pV27dmnQoEEKCwvTiBEj9NVXX0mSzpw5o+7du+uNN95QeHi4\nevTooV27dmn69Ol69NFHNWDAAGVlZUmSkpKSlJqa6jxKO3nyZBUVFUn6McxHR0drzJgxhq0H3Lna\n0GckKS4uTp6envL391f//v1N9+WtLqkNfWbmzJmaNWuW6tevr7y8PBUVeF8XmAAAC7VJREFUFcnP\nz8+wdYLar7i4WOvWrVNycrI8PT11991364MPPtD9999vdGmVlpmZqaNHjyokJMToUiotNzdXLVq0\nUHR0tCwWi1q3bq2OHTvqyJEjRpdWLhkZGWrUqJH69u0rNzc3xcXFKScnx7l9M6Nz587pqaeeUocO\nHSRJAwYMkCSdPHnSwKoq76233nK2yewOHz6sa9euKTY2VpLUtWtXffjhh7JazRv58vLylJeXp+Li\nYjkcDlmtVnl6ehpdVrlNnjxZhw4d0lNPPeUcVlXbCfP+7+Kmroegrl27lhlutVr12muvqaSkRAkJ\nCZo8ebL279+voUOHKiYmRjabTZL0/fffq6SkRBkZGRoyZIjGjx+v0NBQ7d+/X23atNHy5cud81y/\nfr3mzp2rnTt36ty5c1qwYIEkqWnTptqyZYsGDx4sh8NRQy1HRdWGPpOSkqIHHnjAOd2uXbtc4ku2\nq6oNfaZevXpyd3dXfHy8evfurWbNmikyMrKG1gBqs9LSUl25cuWG18mTJ+Xp6amtW7cqMjJSvXr1\n0t69e01xIOhWbSosLNTVq1edB7gsFovRpd6xW7XJ09NTS5cudU535coVHTx40HT7hBMnTqhly5bO\n91arVUFBQcrOzjawqsoJCwvTyy+/7Hz/5ZdfqqioSPfee6+BVVXO8ePHtXHjRiUmJrrEd9Zjx44p\nODhYycnJioiI0JNPPqn8/HzVr1/f6NIqzN/fX0OHDlVsbKzatWuntLQ0zZkzx+iyym3y5MlaunSp\nmjRp4hxWVdsJAr2Lyc3Nla+v7y2PxG3cuFE9e/ZU586dZbVa9eSTT+ree+/Vrl27JEkWi0VjxoyR\nxWJRhw4d5OPjo6ioKLm5uSk8PFznzp1zzmvw4MFq27atfHx8FBcXp82bN0uSGjRoIC8vr+pvLKpE\nbegzP5WWlqYTJ05o7Nix1dNgVFpt6jNpaWn6/PPPlZubq4ULF1Zfo2Ea+/btU1hYmDp27FjmNWvW\nLNlsNh07dkwbN27U4sWL9frrr5vikvtbtWnmzJmaO3euoqKi1KpVK6PLLJfbtem6wsJCvfDCC3r4\n4YfVuXNnA6stv4KCghu+C3l5eamgoMCgiqrWt99+q4kTJyohIUENGjQwupwKKS4u1h/+8Ae98sor\npg68P2Wz2bRnzx61b99ee/bs0bPPPqvx48c7D6ibkd1ul4+Pj9555x19+eWXio+PV3x8fJmrPM3g\np0H+uqraThDoXUxAQIDy8vJu+nCoH374QZcvX1azZs3KDL/77rv13XffOd/7+vpK+vEMmI+Pj3O4\n1WotM9+goCDnv5s2baqLFy9WWTtQc2pLnyktLdXUqVO1detWrVixwhRnzeqq2tJnJKl+/foKCAhQ\nbGysduzYUbmGwSV069ZNx48f17Fjx8q8EhMTZbfbFR8fLw8PD7Vu3Vr9+vXT9u3bjS75Z92qTQMG\nDNC///1vPfvss0aXWG63atPs2bMlSZcuXdIzzzwjb29v55U5ZuLl5XXDfcsFBQXy9vY2qKKqc/To\nUT399NMaPny4oqOjjS6nwhYvXqzw8HA98sgjRpdSZdzd3dWsWTMNGzZMbm5u6tevnwIDA0398MLN\nmzcrOztbERERcnd316hRo1S/fn3t27fP6NIqraq2EwR6FxMSEqJ69epp7969ZYaXlpZq6NChCgwM\n1OnTp8uMO336tAICAsq9rAsXLjj/ffbsWQUGBlasaBiqNvSZa9euKS4uTllZWfr44491zz33VKAl\nqCm1oc+MGzfOecZf+vEJ39cPEgA3c++998pisejKlSvOYWb/ZYRNmzYpKytL4eHh6tixow4dOqSZ\nM2cqJSXF6NIq5cyZMxo+fLjatGmjJUuWmPLsaXBwcJnLZu12u06dOqXg4GADq6q862d9X3zxRb3w\nwgtGl1MpW7Zs0aeffuq8OkSSBg4cqM8++8zgyiquRYsWys/PLzPMbreb+naC77///oYHFrq7u8vN\nzc2giqpOVW0nCPQuxsPDQ7/73e+UnJysjIwMORwOXbp0SVOmTJG3t7d69eqlnTt36osvvlBpaalW\nr16tEydOqHv37pJUrj/4v/71r8rOzpbNZtPSpUs1cODA6moWqlFt6DOvvPKKbDabVqxYIX9//2pp\nJ6pObegzbdu21dKlS2Wz2XTu3Dmlp6dr0KBB1dJeuAY/Pz91795db775pgoLC3X8+HF99tlneuyx\nx4wurcJSUlJ08OBBZWZmKjMzU6GhoZoxY4aSk5ONLq3CSkpK9PzzzysyMlIpKSmmfZhXp06ddOnS\nJa1bt07FxcVasmSJmjdvXuZ+WbM5efKk4uPjNWvWLA0ZMsTocipt48aNOnDggPPvR5I2bNigfv36\nGVxZxXXp0kVWq1UrV66Uw+HQunXrdPHiRYWHhxtdWoV16tRJBw8e1LZt2+RwOLR69Wrl5uYqNDTU\n6NIqraq2E+Y/tIEbREdHq2HDhpozZ47OnDkjDw8PdevWTW+//bZ+8Ytf6E9/+pNmz56t06dPq1Wr\nVlq+fLkCAgJ05syZcj1QJzQ0VAkJCfruu+80YMAAxcXF3TCNmR7QU5cZ2Wfy8/O1evVqubu7q1On\nTpLkvLd62bJl1dVkVJLR25m4uDjZbDY98cQT8vT01IgRIzRs2LDqai5cRFpamlJSUhQZGSl3d3dN\nmjTJJZ4Mf50r7HP37t2rrKwsnTlzxvn78xaLRePGjXM+udsMPDw8tGzZMiUnJyslJUVt2rQx5a0D\nP/Xxxx+rsLBQkydPdj4cz2KxKD09XY8++qjB1VWexWIx9Zls6cdLuFeuXKkZM2bo9ddf1913360l\nS5aY+laP1q1bKy0tTQsWLFBSUpLuu+8+paenm/bZDT9VVdsJi8PsPReGSEpKUrNmzTRhwgSjS4FJ\n0GdQXvQZAACA2zPndUwAAAAAANRxBHoAAAAAAEyIS+4BAAAAADAhztADAAAAAGBCBHoAAAAAAEyI\nQA8AAAAAgAkR6AEAAAAAMCECPQAAAAAAJkSgBwAAAADAhNyMLgAAAACAMSIjI3X27Fnnezc3NwUF\nBek3v/mNRo8e7Ry+du1affjhh/r666/l4+OjLl26KCEhQU2bNr1hnuvXr9eqVav03nvv1UgbgLqM\nQA8AAADUYdOmTVOfPn0kSSUlJfriiy80depUNWrUSIMGDdLs2bO1fv16/f73v1fHjh31ww8/aOHC\nhRo5cqRWrVolf39/57wyMjI0Y8YMtW/f3qjmAHUKl9wDAAAAdZiPj48CAgIUEBCgwMBADR48WBER\nEdq6dasOHjyolStXasmSJRoyZIiCgoL00EMP6Y033lBpaalWrFjhnM/ixYsVGxuroKAgA1sD1C2c\noQcAAABQhpubm9zd3bV27Vo9/PDDCgkJKTPe09NTb775ppo0aeIc9sUXX+jtt99WRkaGMjMza7pk\noE7iDD0AAAAAST9ecr9lyxZ9/vnn6tmzp44fP6527drddNrWrVuXCfQffPCBOnToUFOlAhBn6AEA\nAIA6bcaMGZo5c6YkqaioSF5eXhozZoz69++vRYsWqWHDhgZXCOBWCPQAAABAHRYfH6/evXtLkurX\nr6+77rpLFotFkuTv7y+bzWZkeQBug0APAAAA1GGNGze+5YPsHnzwQf3rX/+66biVK1fq4sWLmjRp\nUnWWB+A2uIceAAAAwE0NGDBAR48e1eHDh8sM/89//qN3331XdrvdoMoASAR6AAAAALfwyCOPaOjQ\noYqLi9Pq1auVk5OjzMxMxcbGyt3dXTExMUaXCNRpXHIPAAAA1FHX75W/nZSUFN13331asWKFUlNT\n5efnpy5dumj+/Pny8/OrgSoB3IrF4XA4jC4CAAAAAACUD5fcAwAAAABgQgR6AAAAAABMiEAPAAAA\nAIAJEegBAAAAADAhAj0AAAAAACZEoAcAAAAAwIQI9AAAAAAAmBCBHgAAAAAAEyLQAwAAAABgQgR6\nAAAAAABMiEAPAAAAAIAJEegBAAAAADCh/wN2Vhq8zIJp0QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xfb863f4d68>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Export is successful!\n"
     ]
    }
   ],
   "source": [
    "num_numeric = len(conf_dict['NumericalColumns'])\n",
    "if  num_numeric > 3:\n",
    "    md_text = '## Project Data to 2-D Principal Component Space'\n",
    "    filename = ReportMagic.var_files = 'tmp/numerical_pca.csv'\n",
    "    export_filename = 'numerical_pca_report2.ipynb'\n",
    "    silentremove(filename) \n",
    "    \n",
    "    w1, w2, w3, w4, w5 = None, None, None, None, None\n",
    "    if conf_dict['Target'] in conf_dict['CategoricalColumns']:\n",
    "        cols_list = [conf_dict['Target']] + conf_dict['CategoricalColumns'] #Make target the default reference variable\n",
    "        cols_list = list(OrderedDict.fromkeys(cols_list)) #remove variables that might be duplicates with target\n",
    "    else:\n",
    "        cols_list = conf_dict['CategoricalColumns']\n",
    "    w1 = widgets.Dropdown(\n",
    "        options = cols_list,\n",
    "        value = cols_list[0],\n",
    "        description = 'Legend Variable:',\n",
    "        width = 10\n",
    "    )\n",
    "    w2 = widgets.Dropdown(\n",
    "        options = [str(x) for x in np.arange(1,num_numeric+1)],\n",
    "        value = '1',\n",
    "        width = 1,\n",
    "        description='PC at X-Axis:'\n",
    "    )\n",
    "    w3 = widgets.Dropdown(\n",
    "        options = [str(x) for x in np.arange(1,num_numeric+1)],\n",
    "        value = '2',\n",
    "        description = 'PC at Y-Axis:'\n",
    "    )\n",
    "    w_export = widgets.Button(description='Export', value=False, options=[True, False])\n",
    "    handle_export_partial = partial(handle_export, w1=w1, w2=w2, w3=w3, export_filename=export_filename, md_text=md_text)       \n",
    "    w1.observe(handle_change,'value')\n",
    "    w_export.on_click(handle_export_partial)\n",
    "    \n",
    "    %reset_report\n",
    "    %add_interaction_code_to_report i = interactive(InteractionAnalytics.numerical_pca, df=fixed(df),\\\n",
    "                                                    conf_dict=fixed(conf_dict), col1=w1, col2=w2, col3=w3, Export=w_export)\n",
    "\n",
    "    \n",
    "    hbox = widgets.HBox(i.children)\n",
    "    display(hbox)\n",
    "    hbox.on_displayed(InteractionAnalytics.numerical_pca(df, conf_dict=conf_dict, col1=w1.value, col2=w2.value,\\\n",
    "                                                         col3=w3.value, Export=w_export))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Project data to 3-D principal component space (on sampled data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Anaconda\\envs\\py35\\lib\\site-packages\\sklearn\\utils\\validation.py:420: DataConversionWarning: Data with input dtype int64 was converted to float64 by StandardScaler.\n",
      "  warnings.warn(msg, DataConversionWarning)\n",
      "C:\\Anaconda\\envs\\py35\\lib\\site-packages\\sklearn\\utils\\validation.py:420: DataConversionWarning: Data with input dtype int64 was converted to float64 by StandardScaler.\n",
      "  warnings.warn(msg, DataConversionWarning)\n"
     ]
    },
    {
     "data": {
      "image/png": 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S7OBZrwedndmNN5LODNkA/F3qAfgHAwu8PxmvSU1qdxFX47OWjHmp1W0cUCdoJ6K7OhGp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\nQRBEVPP/AdNEqo9mEgA1AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xfb802dfeb8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Export is successful!\n"
     ]
    }
   ],
   "source": [
    "md_text = '## Project Data to 3-D Principal Component Space (on sampled data)'\n",
    "if len(conf_dict['NumericalColumns']) > 3:\n",
    "    filename = ReportMagic.var_files='tmp/pca3d.csv'\n",
    "    export_filename = 'pca3d_report2.ipynb'\n",
    "    silentremove(filename) \n",
    "    if conf_dict['Target'] in conf_dict['CategoricalColumns']:\n",
    "        cols_list = [conf_dict['Target']] + conf_dict['CategoricalColumns'] #Make target the default reference variable\n",
    "        cols_list = list(OrderedDict.fromkeys(cols_list)) #remove variables that might be duplicates with target\n",
    "    else:\n",
    "        cols_list = conf_dict['CategoricalColumns']\n",
    "    w1, w2, w3, w4 = None, None, None, None\n",
    "    w1 = widgets.Dropdown(\n",
    "        options=cols_list,\n",
    "        value=cols_list[0],\n",
    "        description='Legend Variable:'\n",
    "    )\n",
    "    w2 = ipywidgets.IntSlider(min=-180, max=180, step=5, value=30, description='Angle')\n",
    "    w_export = widgets.Button(description='Export',value='Export')\n",
    "    handle_export_partial = partial(handle_export, w1=w1, w2=w2, w3=w3, \\\n",
    "                                    export_filename=export_filename, md_text=md_text)     \n",
    "    w1.observe(handle_change,'value')\n",
    "    w_export.on_click(handle_export_partial)\n",
    "    \n",
    "    %reset_report\n",
    "    %add_interaction_code_to_report i = interactive(InteractionAnalytics.pca_3d, df=fixed(df), conf_dict=fixed(conf_dict),\\\n",
    "                                              col1=w1, col2=w2, col3=fixed(w3),Export=w_export)\n",
    "\n",
    "    hbox=widgets.HBox(i.children)\n",
    "    display(hbox)\n",
    "    hbox.on_displayed(InteractionAnalytics.pca_3d(df,conf_dict,col1=w1.value,col2=w2.value,Export=w_export))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <a name=\"report\"></a>Generate the Data Report"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Processing .\\tmp\\target_report2.ipynb\n",
      "Processing .\\tmp\\numeric_report2.ipynb\n",
      "Processing .\\tmp\\categoric_report2.ipynb\n",
      "Processing .\\tmp\\rank_report2.ipynb\n",
      "Processing .\\tmp\\cat_interactions_report2.ipynb\n",
      "Processing .\\tmp\\numerical_interactions_report2.ipynb\n",
      "Processing .\\tmp\\numerical_correlations_report2.ipynb\n",
      "Processing .\\tmp\\nc_report2.ipynb\n",
      "Processing .\\tmp\\nnc_report2.ipynb\n",
      "Processing .\\tmp\\numerical_pca_report2.ipynb\n",
      "Processing .\\tmp\\pca3d_report2.ipynb\n"
     ]
    }
   ],
   "source": [
    "filenames = ['target_report2.ipynb', 'numeric_report2.ipynb', 'categoric_report2.ipynb', 'rank_report2.ipynb',\n",
    "           'cat_interactions_report2.ipynb', 'numerical_interactions_report2.ipynb',\n",
    "             'numerical_correlations_report2.ipynb', 'nc_report2.ipynb',\n",
    "             'nnc_report2.ipynb', 'numerical_pca_report2.ipynb', 'pca3d_report2.ipynb'\n",
    "           ]\n",
    "\n",
    "def merge_notebooks():\n",
    "    merged = None\n",
    "    for fname in filenames:\n",
    "        try:\n",
    "            print ('Processing {}'.format(export_dir+fname))\n",
    "            with io.open(export_dir+fname, 'r', encoding='utf-8') as f:\n",
    "                nb = nbf.read(f, as_version=4)\n",
    "            if merged is None:\n",
    "                merged = nb\n",
    "            else:\n",
    "                merged.cells.extend(nb.cells[2:])\n",
    "        except:\n",
    "            print ('Warning: Unable to find the file', export_dir+'//'+fname, ', continue...')\n",
    "    if not hasattr(merged.metadata, 'name'):\n",
    "        merged.metadata.name = ''\n",
    "    merged.metadata.name += \"_merged\"\n",
    "    with open(merged_report, 'w') as f:\n",
    "        nbf.write(merged, f)\n",
    "\n",
    "def gen_merged_report(b):\n",
    "    merge_notebooks()\n",
    "    \n",
    "button=widgets.Button(description='Generate Final Report')\n",
    "button.on_click(gen_merged_report)\n",
    "display(button)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <a name=\"show hide codes\"></a>Show/Hide the Source Codes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       "    .widget-label { min-width: 20ex !important; }\n",
       "    .widget-text { min-width: 60ex !important; }\n",
       "</style>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<script>\n",
       "code_show=true; \n",
       "function code_toggle() {\n",
       " if (code_show){\n",
       " $('div.input').hide();\n",
       "\n",
       " } else {\n",
       " $('div.input').show();\n",
       "\n",
       " }\n",
       " code_show = !code_show\n",
       "} \n",
       "//$( document ).ready(code_toggle);//commenting code disabling by default\n",
       "</script>\n",
       "<form action = \"javascript:code_toggle()\"><input type=\"submit\" value=\"Toggle Raw Code\"></form>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Provide the path to the yaml file relative to the working directory\n",
    "display(HTML('''<style>\n",
    "    .widget-label { min-width: 20ex !important; }\n",
    "    .widget-text { min-width: 60ex !important; }\n",
    "</style>'''))\n",
    "\n",
    "#Toggle Code\n",
    "HTML('''<script>\n",
    "code_show=true; \n",
    "function code_toggle() {\n",
    " if (code_show){\n",
    " $('div.input').hide();\n",
    "\n",
    " } else {\n",
    " $('div.input').show();\n",
    "\n",
    " }\n",
    " code_show = !code_show\n",
    "} \n",
    "//$( document ).ready(code_toggle);//commenting code disabling by default\n",
    "</script>\n",
    "<form action = \"javascript:code_toggle()\"><input type=\"submit\" value=\"Toggle Raw Code\"></form>''')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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