pymc3_bayesian_data_workflow.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Analysing Online Auction Performance\n",
    "\n",
    "This notebook contains the code required to conduct a Bayesian data analysis on data collected from a set of multiple-lot online auction events executed in Europen markets, over the course of a year. We will build interpretable models of the average Return-on-Reserve (RoR), using variables that describe various facets of multiple-lot online auction events - e.g. the average number of bidders per-lot, the number of lots offered, etc..\n",
    "\n",
    "The ultimate aim of this endeavour is for this notebook (and it's surrounding directory structure) to serve as a template workflow for conducting an end-to-end Bayesian data analysis using PyMC3. It includes many helper functions for automating otherwise tedious tasks (e.g. interacting with Theano to score models on test data) and examples of how data pre-processing can be integrated with Scikit-Learn.\n",
    "\n",
    "The overall approach has been heavily inspired by the book 'Statistical Rethinking - a Bayesian Course with Examples in R and Stan', by Richard McElreath http://xcelab.net/rm/statistical-rethinking/, which is the most significant book on statistics and modelling that I have read during a career spanning more than a decade. Credit also goes to 'Bayesian Data Analysis', by Andrew Gelman & Co. http://www.stat.columbia.edu/~gelman/book/, which I refer to on an on-going basis."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Package Imports and Environment Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import warnings\n",
    "\n",
    "import arviz as az\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import pymc3 as pm\n",
    "import seaborn as sns\n",
    "from sklearn.externals import joblib\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.pipeline import Pipeline, FeatureUnion\n",
    "from sklearn.preprocessing import (StandardScaler, LabelEncoder,\n",
    "                                   FunctionTransformer)\n",
    "from theano import shared\n",
    "\n",
    "sns.set(rc={'figure.figsize':(10, 5)})\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load Data and Yield Pandas DataFrame\n",
    "\n",
    "We will be working with aggregated data from multiple-lot online auction events. An online auction event is comprised of multiple lots that can be bid on concurrently, and is usually time-boxed - e.g. the bidding on all lots is contained within a 2 week window.\n",
    "\n",
    "We start by loading the auction data from a local CSV file and taking a quick look. In practice, the data need not be in CSV format and could be collected via Spark and then transformed to a Pandas DataFrame directly from a Spark DataFrame, etc."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 6220 entries, 0 to 6219\n",
      "Data columns (total 10 columns):\n",
      "auction_id       6220 non-null int64\n",
      "RoR              6220 non-null float64\n",
      "STR              6220 non-null float64\n",
      "BPL              6220 non-null float64\n",
      "lots             6220 non-null int64\n",
      "product_types    6220 non-null float64\n",
      "avg_start_bid    6220 non-null float64\n",
      "avg_reserve      6220 non-null float64\n",
      "auction_mech     6220 non-null object\n",
      "country          6220 non-null object\n",
      "dtypes: float64(6), int64(2), object(2)\n",
      "memory usage: 486.0+ KB\n"
     ]
    },
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>auction_id</th>\n",
       "      <th>RoR</th>\n",
       "      <th>STR</th>\n",
       "      <th>BPL</th>\n",
       "      <th>lots</th>\n",
       "      <th>product_types</th>\n",
       "      <th>avg_start_bid</th>\n",
       "      <th>avg_reserve</th>\n",
       "      <th>auction_mech</th>\n",
       "      <th>country</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>100</td>\n",
       "      <td>1.026112</td>\n",
       "      <td>0.503097</td>\n",
       "      <td>8.324074</td>\n",
       "      <td>108</td>\n",
       "      <td>0.768519</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10568.250000</td>\n",
       "      <td>SealedBid</td>\n",
       "      <td>FR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>101</td>\n",
       "      <td>1.407666</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>5.571429</td>\n",
       "      <td>7</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4805.617249</td>\n",
       "      <td>EnglishForward</td>\n",
       "      <td>CZ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>102</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3550.000000</td>\n",
       "      <td>SealedBid</td>\n",
       "      <td>FR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>103</td>\n",
       "      <td>0.884021</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7693.876790</td>\n",
       "      <td>FixedPrice</td>\n",
       "      <td>LU</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>104</td>\n",
       "      <td>0.972593</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>4.533333</td>\n",
       "      <td>90</td>\n",
       "      <td>0.611111</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8661.111111</td>\n",
       "      <td>EnglishForward</td>\n",
       "      <td>NL</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   auction_id       RoR       STR       BPL  lots  product_types  \\\n",
       "0         100  1.026112  0.503097  8.324074   108       0.768519   \n",
       "1         101  1.407666  1.000000  5.571429     7       1.000000   \n",
       "2         102  0.000000  0.000000  0.000000     2       1.000000   \n",
       "3         103  0.884021  1.000000  1.000000     3       0.333333   \n",
       "4         104  0.972593  1.000000  4.533333    90       0.611111   \n",
       "\n",
       "   avg_start_bid   avg_reserve    auction_mech country  \n",
       "0            0.0  10568.250000       SealedBid      FR  \n",
       "1            0.0   4805.617249  EnglishForward      CZ  \n",
       "2            0.0   3550.000000       SealedBid      FR  \n",
       "3            0.0   7693.876790      FixedPrice      LU  \n",
       "4            0.0   8661.111111  EnglishForward      NL  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "auction_eval = pd.read_csv('data/auction_data.csv')\n",
    "\n",
    "auction_eval.info()\n",
    "auction_eval.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data Description\n",
    "\n",
    "- **auction_id** - unique identifier for a single multi-lot online auction event;\n",
    "- **RoR** - the average Return-on-Reserve over all lots sold in the auction event, where the return-on-reserve for a single lot is computed as its auction price divided by its reserve price;\n",
    "- **STR** - the proportion of lots (by reserve value) that were successfully sold in the auction event (not all lots get sold);\n",
    "- **lots** - the number of lots offered in the auction event;\n",
    "- **product_types** - the number of different product types offered in the auction event;\n",
    "- **avg_reserve** - the average reserve price over all lots in the multi-lot online auction event\n",
    "- **avg_start_bid** - the average starting-bid (expressed as a fraction of the reserve bid), over all lots in the auction event;\n",
    "- **BPL** - the average number of bidders per-lot;\n",
    "- **auction_mech** - the auction mechanism used for the auction event (English Forward, Sealed Bid or Fixed Price); and,\n",
    "- **country** - the local market running the auction.\n",
    "\n",
    "### Initial Variable Selection\n",
    "\n",
    "We choose the following variables to use for trying to understand and predict RoR:\n",
    "\n",
    "- **lots** - with the aim for controlling for the presence of available alternatives;\n",
    "- **avg_reserve** - to control for lot value - e.g. lower value lots may see more bidders willing to go above the reserve and vice-versa;\n",
    "- **avg_start_bid** - to control for the presence of a public price signal (we may need to derive this);\n",
    "- **BPL** - we know from basic [auction theory](https://en.wikipedia.org/wiki/Auction_theory), that the more bidders there are, then the better the expected prices will be;\n",
    "- **auction_mech** - whether the lots were traded via English Forward (EF) or Sealed Bid (SB) auctions; and,\n",
    "- **country** - to control for differences between local markets."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "RoR = ['RoR']\n",
    "model_vars = ['lots', 'avg_reserve', 'avg_start_bid',\n",
    "              'BPL', 'auction_mech', 'country']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The section below explores the data in greater detail - to get straight to the modelling head to the section titles '**Modelling RoR using Bayesian Inference**'."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Exploration\n",
    "\n",
    "Through visualisation and descriptive statistics we try to understand the characteristics of the individual variables that are available for using to predict RoR."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Descriptive Statistics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RoR</th>\n",
       "      <th>lots</th>\n",
       "      <th>avg_reserve</th>\n",
       "      <th>avg_start_bid</th>\n",
       "      <th>BPL</th>\n",
       "      <th>auction_mech</th>\n",
       "      <th>country</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.026112</td>\n",
       "      <td>108</td>\n",
       "      <td>10568.250000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.324074</td>\n",
       "      <td>SealedBid</td>\n",
       "      <td>FR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.407666</td>\n",
       "      <td>7</td>\n",
       "      <td>4805.617249</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.571429</td>\n",
       "      <td>EnglishForward</td>\n",
       "      <td>CZ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>2</td>\n",
       "      <td>3550.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>SealedBid</td>\n",
       "      <td>FR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.884021</td>\n",
       "      <td>3</td>\n",
       "      <td>7693.876790</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>FixedPrice</td>\n",
       "      <td>LU</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.972593</td>\n",
       "      <td>90</td>\n",
       "      <td>8661.111111</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.533333</td>\n",
       "      <td>EnglishForward</td>\n",
       "      <td>NL</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        RoR  lots   avg_reserve  avg_start_bid       BPL    auction_mech  \\\n",
       "0  1.026112   108  10568.250000            0.0  8.324074       SealedBid   \n",
       "1  1.407666     7   4805.617249            0.0  5.571429  EnglishForward   \n",
       "2  0.000000     2   3550.000000            0.0  0.000000       SealedBid   \n",
       "3  0.884021     3   7693.876790            0.0  1.000000      FixedPrice   \n",
       "4  0.972593    90   8661.111111            0.0  4.533333  EnglishForward   \n",
       "\n",
       "  country  \n",
       "0      FR  \n",
       "1      CZ  \n",
       "2      FR  \n",
       "3      LU  \n",
       "4      NL  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "auction_eval[RoR + model_vars].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Outlier Removal and other Dataset Filtering\n",
    "\n",
    "We are aware that outliers have found their way into the data. So, we will filter our modeling dataset by systematically removing values that don't 'feel' correct, based on our knowledge of the data (and the issues embedded within it). As such, we will filter-out the top percentile of RoR values, as we know there is ambiguity surrounding reserve prices (the denomintator in computing the return-on-reserve for a single lot). Likewise, we have spotted auction events with average reserve prices in the millions of Euros (i.e. errors), so we will filter-out the top percentile of mean reserve price observations, as well.\n",
    "\n",
    "We will also exclude Fixed Price (FP) auction events from the dataset as the RoR for these auction events is fixed at 1 and all auction events where nothing was sold and nothing can be said about price and RoR (i.e. where auction revenue = 0)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RoR</th>\n",
       "      <th>lots</th>\n",
       "      <th>avg_reserve</th>\n",
       "      <th>avg_start_bid</th>\n",
       "      <th>BPL</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>4175.000000</td>\n",
       "      <td>4175.000000</td>\n",
       "      <td>4175.000000</td>\n",
       "      <td>4175.000000</td>\n",
       "      <td>4175.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.989743</td>\n",
       "      <td>48.491018</td>\n",
       "      <td>11099.072681</td>\n",
       "      <td>0.205143</td>\n",
       "      <td>4.997294</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.140135</td>\n",
       "      <td>39.081027</td>\n",
       "      <td>4910.386793</td>\n",
       "      <td>0.390067</td>\n",
       "      <td>2.653911</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.052569</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>400.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.921498</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>7378.053377</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.885714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.000367</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>10218.566667</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.873239</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.041915</td>\n",
       "      <td>74.000000</td>\n",
       "      <td>13731.054182</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6.764655</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.617087</td>\n",
       "      <td>516.000000</td>\n",
       "      <td>30198.234375</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>20.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               RoR         lots   avg_reserve  avg_start_bid          BPL\n",
       "count  4175.000000  4175.000000   4175.000000    4175.000000  4175.000000\n",
       "mean      0.989743    48.491018  11099.072681       0.205143     4.997294\n",
       "std       0.140135    39.081027   4910.386793       0.390067     2.653911\n",
       "min       0.052569     1.000000    400.000000       0.000000     0.000000\n",
       "25%       0.921498    17.000000   7378.053377       0.000000     2.885714\n",
       "50%       1.000367    40.000000  10218.566667       0.000000     4.873239\n",
       "75%       1.041915    74.000000  13731.054182       0.000000     6.764655\n",
       "max       1.617087   516.000000  30198.234375       1.000000    20.000000"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ptile_thold = 0.99\n",
    "\n",
    "model_data = (\n",
    "    auction_eval\n",
    "    .loc[\n",
    "        (auction_eval['RoR'] > 0)\n",
    "        & (auction_eval['auction_mech'] != 'FixedPrice')\n",
    "        & (auction_eval['RoR'] < auction_eval['RoR'].quantile(ptile_thold))\n",
    "        & (auction_eval['avg_reserve']\n",
    "           < auction_eval['avg_reserve'].quantile(ptile_thold)), :]\n",
    "    .assign(\n",
    "        country=auction_eval['country'].apply(lambda x: 'country_' + x),\n",
    "        auction_mech=(\n",
    "            auction_eval['auction_mech'].apply(lambda x: 'auction_mech_' + x)))\n",
    "    [RoR + model_vars])\n",
    "\n",
    "model_data.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### RoR\n",
    "\n",
    "We start by reminding ourselves of the distributional characteristics of RoR - i.e. the data labels for our regression task."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = (sns\n",
    "     .FacetGrid(model_data, col='auction_mech', height=5)\n",
    "     .map(sns.distplot, 'RoR'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- EF auctions appear to have a bi-model distribution, suggesting conditioning on othert variables; and,\n",
    "- SB auctions appear to have 'fat tails' - i.e. a Student-T likelihood function may be worth considering.\n",
    "\n",
    "We now take a deeper look into EF auctions and the distribution of RoR, by whether or not start bids were used."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_data_startbid = (\n",
    "    model_data\n",
    "    .query('auction_mech == \"auction_mech_EnglishForward\"')\n",
    "    .assign(has_start_bids=auction_eval['avg_start_bid']\n",
    "            .apply(lambda x: 'true' if x > 0 else 'false')))\n",
    "\n",
    "_ = (sns\n",
    "     .FacetGrid(plot_data_startbid, col='has_start_bids', height=5)\n",
    "     .map(sns.distplot, 'RoR'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Some of the bi-modality in RoR does appear to originate from the presence of start bids (above left). This sub-distribution is, however, also bi-model so all of our questions have not been answered. We continue to dig-in to this and look at a scatter plot of RoR vs. avg_start_bid, to see if the magnitude of the starting bids plays a part in what we are observing."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "start_bid_analysis = (\n",
    "    model_data\n",
    "    .query('auction_mech == \"auction_mech_EnglishForward\"')\n",
    "    .query('avg_start_bid > 0'))\n",
    "\n",
    "_ = sns.scatterplot(x='avg_start_bid', y='RoR', hue='country',\n",
    "                    data=start_bid_analysis, legend=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Based on the above plot, it appears that there are some countries that are setting start bids that are greater-than-or-equal to the reserve price, which cannot be true. Thus, we will will filter-out these data points before we start modelling in earnest."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 261 observations with spurious start bid (and hence reserve\n",
      "      price) data to filter-out.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"\"\"There are {} observations with spurious start bid (and hence reserve\n",
    "      price) data to filter-out.\"\"\"\n",
    "      .format(model_data.query('avg_start_bid >= 1').shape[0]))\n",
    "\n",
    "_ = sns.distplot(start_bid_analysis.query('avg_start_bid < 1').RoR)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can, however, see from the filtered distribution above that the bi-modality is still present. With recourse to the scatter plot above, we can see that the bi-modality is country-related, which justifies the choice of country as a potential explanatory variable that we may need to control for (i.e. condition on)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Dependency Structure and Correlations\n",
    "\n",
    "Taking a superficial look at variate-by-variate scatter plots and Pearson correlations between RoR and the initial modelling variables, for a single trading mechanism (English Forward), across all countries (independetly coloured). Although it is hard to pick-up on specific country-by-country relationships, what the independent colouring by country achieves, is to demonstrate regional variations - i.e. differences in the underlying market structures."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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F+n3WpaYxliflmgukEvw94GjMJ+5XAOOAl3I8fwwwsVu3bp2Aj4Ebli1bFt1fg1MoGgNCJCe6lMMuKe7JkF7X8MrHV6XTpU4dcAezFz1GKLqV0/vfAZEdp5jxYADNyNyN3VnIq/ab1u80PXUyqgsbW+oqFV6BzGE7O6ef5joRTwUhqdRISyYQV52O8fX3nDX4Xl7/6uYdJSN978V4deEuxblcuobfkGxPrOd/H05I//6oIbfD7CcIbVqMEBrevJKMRac3r4TQ9rWY3pbplPm990XVXWqSYuf7H5ILXV1Tp+0HC4bmZuBRV/DGnBvTtjt68EMYmhu1ffMTEFqOvuKN9rxrz8jpkz277dN0XaA7mSVFR48uxT/mZyDB0mNZ/agIxaF9CabL5KxBD/P63Bsy/LjH8hDJ9aY5fKVmeOtex+whjTUlPddcIJTg7wGHkLJxL6S7deu2FhheM1W+W7duecB/gGuBtcDfgO+XLVt2Sz0u2QFYs3dHqThI2V/brB3IYbNSOmwpX8Hrc5KTyNihf2bml/fVct7nDvsLkYof8LmLIB5m+ZRfA8kJusPwSSyf9rv06838Eo4890VMf3GN95GEwxLbBl0HLb6eZVOvTqemdR31CN7izgek4u4BRKOw10jZSpZPH7/HtpPtGl1Oewh9URnW0R2xIyG0yijGuwvh+wCiqADzdxchCvJqX8uROFu3EXKH+PfHv6l135zZYwKBjx7hyPNeIhrZwpfvjk8vSHsOvY3lXzxBLFzGoDNfxO0rzrz2TveMzycQon5/gniojCX/vbjWYrr2femwpWIlr8++fsdCd8ijtCw8YO7F/WGzHWjCa4JgaCP/+uDyWrb78xOfI9/fpgFH1rSJRyqwwtuoCkYQRgEyUUlevheXrzlmtchaFhq9ve7sl7xeSXTbqp/kk1NEw1v5dOoltQLz4055EhEKoxUUEbXKM/xov+PvxT13PfbAdqz44GYMXzEtj7sCs/BQ9LII5qwlmOecnNV/Q25f2WH4JHwtu2f4y71BKFLGP2f+X6377Rcj/o7fu3ffa3fYw7mg4VMFFLtNkwzcs7ymL/D8smXL+tbjkh2ANWVlVThO5mdv2TKfLVuCezzWfU1jHx80/jHuzfG1bJm/XwOhbDYL4PXo4FRgSwuJw7Nvj6n1mstHTiG2bTWrF/6NowZcz7L/XZ5OXxcuM5kyn6OWVtc1LMvN9LfiVAYlBfmCUaeZ5HsrkXZkl8JyjdkmGuvY9sW4Gou96rogzx3DSkT3SJTQb0ZYPuWy2rWnZz2JphehV2S2kdMvHUPQl5c1ZbhQl8gtP1DZLMGLH15W6/lLTngej/Dib9mF8vIwHiNIpOpHErFKVi/8G9s3LwZg6HlvEIkn0/pduoZfh4qYm2k73TMuVwy7HqnLqbrNVAporhr31Gs1I4yUCYQwcBI+mjfPa5R2nYtc9r6fbLYDddhrY/URKQxPBc++ObrW4786/Q0S0ZwBZoPT2L/XPE+C7RWCt953p+/h034Wo1mhpCqa/RSzMdjrTuPJ+I5zzeVudxyDqqxCmC5dw4+NVp35FKpDM8HnruCjV86s9fiwc17l23+cndwUGP0YjssP1f7KkF4gzJIpl9fy6d0HPoDub5HTfyc/U21f2WnEZAx/CyJy79e4u9yVPDfjjFqPXz5yGlasIMtv7D9Sc4Gm2TiOjpOoe27dj2sCxV6kMafK56Rbt26HASOWLVv2fPVDgqQikEJxUOHSNTwVQex3PsU3ahihbRuypkuFylex6L0bk+3e/C05YuzTmPmHELbyAepUd9d0k+nTkhM9QGVQMv2tOGPPyieRSHcL3m+fWdG0sW2J6S+mIr2g3E3byZEamQhvRfebhOpIsd8ZzXGwPDpOeFPW+8btb0M8nkee0LBtiaPrLJp1e60TpZRYlUvXyA9XEQ05TPusMMs9Y2Lbu67o2p2uC7Ytq8WHlMjjwYgu9OzlEkJXi6KfgCV9vPW+k3EPv/W+m3PHaDTV5WbuudyoFqHL9CEpf2a/MAWreiM0v46NUCH0rKnwVGcaxYMBlr9xTVLINr4jyPUbVnbtk9bNCDq5g3bI9JU1VeU9eUVUbQ3tyddUJ405JT01F+zYsFFzwYFIkwzcgQjwYLdu3T4kmSo/DpjSoCNSKBqAmv2u5YAemPNXctbJmbW+p/e/g7WfP1bd7u1hpBVl9Xu3Jyc6XRDXJdulF5fwYdqi1omglCI90aeoDEqQarNW0QBU12QavmJKjr4El6cAJxHBsRPoMoFlO1TpOnG3jo1EB0y0rCfdjqYhpAuvu4gzBz3E1Lk76oTPGlxKIp6XESzvqu1b6n60/+/8HPdM/VNPVdcFRX0whIuxQx9nc6gC3ZWHbVXRyl+IIVwo0Z89x5E6lcFMIbrKoMSROk01cN/dubzm+gJAFvixQ1vxFgiCpo+4FEn/mgCQCKExYORfCFWsY+VXzxALl9F76GSs4Ob0NbNq6OSos3eEUS9xxdq+Erz5+6ZUyEn4OHPwI0ydk1nj7iT2vPWnQrE7NKnAvVu3bjOA25YtW/ZFt27drgKmkex58wlQ2qCDUygagFS/a9G+BOl1Y5w0iMJ35/Lz4aXYLfxoQiCrtnDUMdfiWBF0BxCSLqMfw9Ly2GxFmThnAYFwhBKflwcG9qOV6SZRo3WWEMmUupoTfkG+AKEmKcX+J2r76Dr6MaxwGatnTt6RHnnyXQjdg+5obBUJJs7+ooZdH0Mr08iwa4CIruPy2aye8QcMXzFnHfd7zGbt0ISBdJol2xvVYFdt31L3oxYKUZDvrnXPaCKGrosGETHanZRXRdNBCJNtTjNu+XoVgfAP1fbenvwDQ+OgwRBCZJ336qtT0RjZ3bk85c8AaF+CPbYPPyx6HllwLTd/taiGf+1PG8r5bNpvd9Suj3gIw12ITIRZ+/5d+Fv3oOToSzC8RWianuEHU11odi4NitqNLxi2bYmht+W84S9klCcp4V3F/qLRB+7Lli3rUOPfI2v8+1Xg1YYYk0LRWHA0DXFUZ1xDjsb611vYBX5cJw3CyG9OQiRY+mrtWuBOI+7AlX8oUeEw8dNk0A4QCEeY+OkCnhp6XIZiiWPHGXVa7bo4x47t50+rUCQXTsLtZ/XMazJbAL37B7qPfZ6EKZj48Rc72fUXPDXkaFy6kbHAMgixvHqxGA8GCE39XbIOc8zzhOLZg1rblsTxYephIIGph4mTXLil+s8b733IqAvOZ/rbVvqeOeVnEZZ/dh9HHHcTkf3cV3d3U14VTYdKqTHx0/k72fuXPD3s2AYeWdPG1EOMOs3D9LfsGvOejqmHiDXeTsp1srtzecqfyfJKxOn9WfH+DRQNu43rvlqxk73Np7RXi3SKfKQqwIKZN9J70CR8zTri8hXTpvcFrHn/zqyaHbtTGtQYUOVJioak0QfuCoUiNyF0Cs88gcRfX0mms5VXknj21eRke+2orHVjhq85UiawpExPvikC4QiWlNSs1rJtB5crxtizzGRKnZA4dv1EthSKfYF0ste5y4rtOIXerHYdDW+nhcdfnVKZulD92q7VRNcFmp3Z8qjviFLQ2xJCI//SMdgvTCHP+ZGTh27HcLcgEdvK2i/+SMWWbzjiuOtzXntfUSvltbwS+4Up+MddSIUSFm7SJCRZ7T0hoeGrbpswdpjyeXdx+vEXoXla4ES3Uj7vHxQMnQBkVzhv7OzuXB5CT/szinxJ3+htTiC8KeN1gXAEjMzvJFIVQHcXgoQOA69n6bTfZGy0rpwxIblBWu2PVWmQQlE/VOCuUDRhLNvBESK9IE8hyysRaFnrxoTQkcLA0KDElxnklPi8GFkOE2zbSYtqpXpoo9W9M67rAp8WxqqoIt/QCTuNdwdd0cTIURMpglEMGcxq1zK8Bc1tkG+wwxZzXIc6hIZMPZwO2iG5QP1q5gT6j3yeSNyb7j+vuSKsmPXbnEJ2+5OMlNdqdtXfXtE0MEQOP672Y34a0qZizYdUrPkw8/Eh1zXMePYSNefyXWHZTtqfoUeSvjGyLau9kajK+F1vXgm6Ow+xaTvSo+/RBqlPCyOcBFIz1PpBoaimaeb7KBSKNI6hk/jN6cSuH03iilOhfQmiqAAhDDqNmJycbCHdJgXdJGr78BHngeP6JiddkpPvA8f1xUc853ulWq8sn3IZi18azfIpl2FaG9D1zFWiaWr4te3YoR+JbvqOypn344vXfp3i4EPXBfFQGX6jEr8Z2SObSOCny8jSDNvuMvwe5Dfr8bqqatn1vX27EFnyCnZFgMj25eiubZieCAn8dN7pOjtqK3O/e81gHKj+OSlYZdkOFbYgbPnpO6K0OlinWhyyFI/jplCXuPT9N/2mUl5rIooKcDS1BGjq5BHngYH9Mv34wH7k1eHHFfVAM9N+IYWZXwKa2UAD2rfousBvRmr55ZQ/Ax9dTryXyJJXuLdvl53s7RiamUaGr+s59DY0lwf59gJEKJ79u8yxQarrAl98A2UvX8amp0ZT9vJl+OMbMM396690XWB4IrjclRiePZurFIq9jTpxVyiaMLouKLc3MPW7m3aoYZ9zH82tFtgfLsZ1fAc6DJ+EZnhxEhFcvmJiMh/bdpCWTWLZv/jroJ9jaya6E6ds6T8QPc7Hb2Tvse3Rwyx/Y0KdKW+6LnDF1rO0htDM4SfeRuUnT1EwYhLB/Vzfq2g8pDZ+lryx6/7kuXDpGv5gFfa739L9uHuR+R40Xx5y5tfQsx0r3h1PXrsBPDX4aqLRIDK8hciCP3Nov0upEjGmzr8vQw3Y425H1zHPI6SF0DQkAo8MEyXXCY+RveXRTifpmUJ2Fi6pIV6bi7V46n6vMa+Z8prR3x4dUCUvTRkBNJObuadPi7SqfDO5GUHLhh5ak0YIQaeT72L1u3/IFMBswuJ0uUhvyNfhl6Po+N0ldOx8GVI6PDPwaBK6ga5p5IkwS+Y9R/eBEzDcBSRilaxd/G+OGnQTIs+PfG8hXc68hxWzbsm4vtB0/EZlrbWGTwtT9toE7Iqkj7UrAmx9bQKtL3gWR8/fLz5T1wUJNjB1VqZ6vKHXf65SKPYFKnBXKJowmhFOTywAlaEAry/4PT8f9gxGnxJ028TbvDNSWgjhIi7yiUeTk17c9tG286l89dZlGUqwP3z0IBVrPsoeVNWjJjhbcL/qgzvpPGgCwsmdGqc48KnPxs+uSNVrU+DHZXuQRjNsl408pReI5DW3LZ1KbNuqdLu41oOuJRIMMHXhXRn3ytQ547nghBdISJDSIr59HVs+e4ZEuCznhsKuWsLVxLYlEdtLoS6RT7zcYDXmNVNe69PfXtF0sKTN63Mm1OorfeGJL1CoSzTHQWoaUtfQEpbqKFBPpB3jh0/+yGFDJuDyFGBFK/nhkz9y+Cn3AJ6GHt5epT5+2WNbWNNn4xrQAxFx0SxciUAgmhUQN206HXUBC2ffmfaJvYfchnDAGD0cWVGFWL6OI0c9hXQBuoGdCLHs1YvTgXyXkaW4jTY4UoBMpIP2FHZFABmsxJ/v2y8+M9vaauqc8Zw3/IVqYbq9g64LNCOsFOoV9UYF7gpFE0aSyFiwQXKCicfKWff5gxw66BpWz5hcY3J8mHx/GyqkSVw6uMxDGTDq70gngqbp6aAdcgRV9akJzhHca/4ipGZAZmvcBiFVpx+rrMJv6o1awfaAQiYwfMUZi+HAl3+rs9ZxZzTHSXZPOG0oVmAzVmubFVNuJB4M0PWMP6XtM7RpMStn3JDcgBo6Cenx4vO0YGDf2zHN5sTj21i49AlsJ8p/P/pN+lRl1JDbKZ/9RNr20altJ3W0hMs15oauMbdsp3rBq1ffgypwOxCwZSKHXSeQT7yW7iLg+vlIrDc/gsqQ6ihQD4TQcfmKMx5z+YoRoulrQqR1aqoV3IWQu9yQ1xwH69uVJL5diWhfguu0oSQ++YLgoD5YJcXYegF9hkxGCIEdq2TL1/+m/fHXE7ciCDuMq3c3rKmzIc+DPKUXy9/I7AqyYsYEug+4F16diz7uLPTCkozgXS8sgaoomn//+Ewps6+t5G7MVbtCneor9gQVuCsUTRhN6BT4S2qdtuiGl5KjL2H1zMmZgZIV5ce45KZP52b0uG7nciGwscJlGdePBwNoxPE3aNnfAAAgAElEQVQbyQk+VROc6rda2GkYrYaOJ0QCzQMi4csZ3Ov+FoSchu/LWp+0QMW+Qeie5GZSzf7rIyYjdE+qRHyXOJqG66RBWLO/hHMGsmLKFWlb2zDvGTqNmJy+fmHHYbQ//noQAlwmffvcx63zlxAIb6LE5+Xu/vdRFd2ccaoy/Ys7OLP/BL6ffiNCRln2+tVZ7SRSrYCs6yLZGk7PHcTXbKuU/i5SNeaNYCNL0XTRtOx2rWlGRoaH9dEXGOefBqEIsrIKf76fCmV7OZG6m0MHjkv7Fk03OHTgOKTubuCR/TSyzX9dRpZS2HFYetMequdsoZFvRAg7Phw0RI/OMPRIZIs8EsLgh7NO4KbPviSw+Nu0Rk7L8Bq2LplGSd9fYMVDuHz5OG5IaDFcJx+L45Ek4lW0HD4e4SlERivYPu9FQpsWI30mlFdivz6XlmNL2VKdLq8XltDi1HtwZq1EnNVhv/hMIYysaytRh3Dp7rK/TvUVBxZKmUahaNIIThlwOwX+pPBLgb+EUwbcjpOIYvhaYPiKaTdwHOtml/Lda1cSFB5u+vTLWj2uf9z2PZ9Nv5KSwdfgb90jfXUzv4Ro+dq0EJ0eW49dXRPc4+IZ+AZfyUNzr+LWmWdQOvdSqsQG4lkEv7qMLCUqihpFYOzRw+mNB9iRWeDRww08sgMf6djpoBqq+6/PnIx06r8SC6EjWhbhGtCjVlu40KbF/DD3MY4Y+zS9Lp5OuwFX8v2cR6nYtpyQNKuDmx22f+v8JcRFZhujylAAzVOImV9CbPu6Ou0k3RpuxmV8/J/RzJ9xGbqznjxPPEPIKISOfumYtEBcqsY8pBTdFT+RCN6sdh2pcSoo2pfgGnI0iWf+R/yJf2G9+h6uYGivCyS6dI1CXVIk7P0uwLi3EVhYkXLWzrqf7167krWz7seKlCOwGnpoP4ls89+KGRNof/z4jDn78J9NZtvrkyh7+TJ88Q3EDB1r1FEs/eQGFr10JpsrAsmgveZa4rOvKMdFm2N/hcvXEidexXdTruKbf57Dd6//mpi7Csd0sc1l88SyUu749AqeWFZK/oibaNX3l4hwUlBRLl6J5m5D6wuepeTCf9Fq2L0waxX6yYNr+cxcono/FSfh48zBj2Ssrc4c/AhOoi7h0t2j7lN9hSI76sRdoWjCSClYsPxfnNB3Avm+Q/DQGjthY2o6ui9M2wFXsOb9O4kHA8mA3N+aQHhFxjUC4QiapwORqgALP55M70GTWPnG79KnoT/MfQxITvDr5z9N8bA7qXLycGmSad8+QFk4OfGUhQM8OW88Ewa9gONqS7ezX0TIOEgHp1q4K9+INHx7lz3o3a3YS+yFVHnLdrBdLvQ8H8J20tkd/tY9adPvOlze1kinGUKUs37+0+T3u4CpX9zBqcNeytrv2nRnpsMW+EuQiQhdRj7M2ln3ZTy3s51kaw234L0b6D1oEqa3Zfp0vq4ac13XiBsatpToQmAmnJx9lRWKnUlIyTEtWnBF5+640Ylh88zKpSTkDt/qOvFYrFfeyjiBT+xljQWXrpEfrsJ+YUo6Pb9Jp+TbFoGvX870VV+/TIehNzT0yH4aWeY/w1cMms4RY55ECA2rchPhhdPxH3c9wtuCRFUlZl40LTgLIM08AuEfMq7T3O3GU9CJbdFy8oxmlC38U60Ngg7nPsOTn92UuW6YfxMTBj+JFhZw+ak4n6/EkYIQ+fjzfWh+B3FWh1q6HHVlz/1UbFti6G05b/gL+6z+fH+c6isOPFTgrlA0YZyEj8E9fs3cxU8zsP3NLJzmJlIh8RYK+pydh2hZTJuz/ouhg1urYl3F91l7sOb5WzLknP+yetFLeIo6cNRZT+MqLGHl278ntGkxAL7WPZH9rufKWd9S7DH51ZGdGH3kAwztuIZpS+9h7fZvKAsHcEigA3Zka3pnP3nq/hCVHz9DdMVH6IUlFI8tJWw2QHr6HvTuVuwd9iRV3qVr+LHRqgPeEDpSk+D3wdyFdBn5EOvnPUfLnr/nm+neavuX9D27JYccP4F/fXwllaEALiGz97vWdQ5vewI9u1yF39cecKFrDpoI4/IVc/jpD6O7C7BjlWxdMm0nO0ng9hVnqCmvXvg3NJe3lj5EthpzXdfYisPEj75lYzhGG5+bBwZ1p4WuqeBdUS+8us64w3qy8F8xIhUW3kLBuLN74ugxRI/OyMUrEXm+jDIN2PsaCynRyIYSYNzbSKHR7rir0TQdhIbhbU67465GiqabRQDUmv/8rXtw6KBr+O61K3bM1ac8gNHzGr6aZlb70+b0Pdug48/uQHd7EaafsKsZJb61aX96VFEzru7Zg3Eff1ftyzbxwMA/0L3/r0gENxL48m+ENi3GknY6aE9RFg4QjJYhKrchN36DOPcqElLHJSRhR5CwbXQ0LJeJ4xJoSFxWHI8eyimqB5mZVNnmkV1tKNm2rE5ZT20q7921SupUf+qczBr35Kl+w2cnKhonTdwDKRQHNy5dozhezMm97uW7acmgBSBSIfn61QQbtrq4aqrDpHckmyMFfP/DNO44OrMH6/0D+7Li/d/xxdvX0v7Ic9F0k9Dn/wQ0EjVq3vP7/5abv/yRYo/JuKOO4Lm5Lsa9HudPn7RjVPdH6NCsJ8W+EjSMHOl4N+LrdQaQVIgte20CPm3/p6dHbd8e9O5W7A12N1U+dYonn3gZ696nkU+8TH64Cs1xSHzwGUbfIzATfg4bcnc6aIek/X/1agLhFKZPM6Lh1Uzu3y3D9if374ZPWBxz1D1E5OHc9q7Nr6dEmfR2gkA0j5JB17Do81LmzriSRZ+X0ubYK0jgT49PaB669b+GpZ+W8vn0K1n6aSnd+l8D0qlxOp+buKExce5SNoZjAGwMx5g4dylxQ03NivrhTrhZ+Gosw/YXvhrDnTCJjj4K1x+ugsL8dJlGirTGwl5Cc5ysmwOa0zQ3oIRugB1n2RvX8M0/xrLsjWvAjicfb8LsPP+1HXBFLZ8ciwoWVgftsMOfSopIWBHmvTWO5e//jnuO3uFPLz/yCO6etyLTl326nO1xybrZpbQbOI7CjsNwCRfFvsye7sW+EiLRbehFh1HR+9dMfMfhyilxJr1jsS3hwvS42O64ueXdBFdNiXHLuwm2O+50F5GaZPO7ueaRhi7lsG2JQfJU//KR0zhv+AsYKK0dRd2o1YFC0YTJsxNYT/8PIk56kk0RqZD4XMmTjmZewbaoTq8jbsLrxHjw6BJeHNqde/q0oDC6morN3xCpCrDiq+cISi/2KXdRoRXSZfTj6Qle+FqyMRzj4m4d+csch82h5PttDkn+/ImXkUdM5NcDHkkK1OVIRxfeHYtHuyJQ3R5u/2LbkrirLV3HPE/vi6fTdczzSphuf1FnmUJtcp3iaVJCKIrjgIgJpK1ltX8cLV2jOHfR4xTqldzWrwXPDuvObf1a0EILYtl+NoVd/HlOLMOm7/swRkRrTvcT7qDXyQ9h+opZMPNG3KKKAlMDj5cqWUCV7cP0tUi+Z1WARR9NRkqnXlkctpTphW6KjeGY0qtT1Btpi6y2Lx2NBe9NIKrFqMC1zzUWUgKMNalrc0A6snHXw1txVrx1U+bm81s3gRVv4IH9NGrOfz1++Qaeog61fLLmKshqUy5fG77+6HYiVQEqNn9D+Wd/4M9HH8qUU0dwWF5eVl+m5R9CPBhgzft30n7w9eRZXn4zoDQdvBf7Sriy/4OYRgciRke2RXWaeZPrls0hyX2zLOLC5L5Z8Uz/PCtORDRLr09SZPO7ObNBGoGntW1JIurFihWQiHrrvQ7RdYHhieByV2J49l5tv6Lxo1LlFYqmjONA18MQXh1vocyYbL2Fgoq4pGsLjYv6mTxeHZi08rfj+sERlq28l/6dz2fVvCcAKGzVE1+v67ly1tJ0Kvyhee049JwpaMImZhs8enwRhYbJ5lDmhLc5JGnt74JpxarbZWVPR5eRHScyemFJg7WHs21JyPbSsmU+W7YEUWlp+4ndLFPI1UYNx8E4YziJp/6DLK9E/OZivIX5tezfjm7lzEEPMnXuTWws+4avvn2WIb1/hxULIhwLO+wjZrgoyRc084r0whCSNl0VDzNl1hUU+EsYOeB2vp/3BE4owiY7j3s/i1ffTx24YVApzJ+Q3gDTXO4aWRy5bUsXgjY+d8aCt40veZKk75Qun1avr2cLOsVBgp609Z1tH41q7YVEnRoLe4sQOvmXjkkHSKnNgSA6O7cedOkacuMW5HOvNdp6eCntrHocUjZ8sPdTSc1/4MVvRmr5ZMeqxFvYvJZNCWGn9TxSVEo/t876huv6dMrqywwBnUc+jMtTAJqbSjyYTgeuH/wq8cQ6YvFKYolDeXi2i82hKK38gt8OdvOPBXGWb00eEFhOpm+GpH9OSD2jy03N7Lma+XOa42AV+JFnD8Lxm2ihOLy3cL+249ybqDZyBzcqcFcomjDS0Imd0IloZCndRx/G0jd21Lh3Ge3m0UVxzu5ppIN2SE54j87xct+p97B27s1UbE7WsLfu81tu/GJHKnzyVD1GK7/g2sFu/r4gzvaIi8knGRzbTnJiF4M8U1AVl3ywIoGmCUAAMp2Ot3ONe+jjZ4Bk0N5i7MNITUfXhZpsDhKy2UVdAa7M0UZNbt6GyPcjC/yIS05BNNPoe7bBV68m0vbfa7SFpgfZ/tlznNljArqvOaa3mC3znie6bQ3m4FIe/NybXiymbHz51mTg0MovcOwgbZr3pG/367GMdnQ+8WmqhMa9bycy7qeH53q5+ZjrqHjvcrx5JZh5bYg7+WBLvGaEbMG2rms4Av48rCc/VEV4/tt1lEXj3NK/K3/6ajXj+3RCrw5iUur1333xFG26jcLwNsfjbYGuFxGPN45AR9EwWC6HXmPdLHottsP2x7qxXA7evBKoFgbNprGwV8exG5sDfmwSz73WqOvhhcvMrsfhMqFpH7pnkM0newq89BodZ9Eb5g6bOiNGIrwab15JOnhPrRk2hmO89N16bunflXvmL0/rdTx6/BEIXSPSoh9adBubIx4e+MSu3vAU/P6EThTmwaS3Mk/TH58T4/IBJvd9mFx/uLTk62sG7638AkPY6GYeR4x9FolASkE024amoREb25sFn9xMpCqAN6+EfmPvxWVoe+VvqesCzQjvMxG7nVFt5A5uVOCuUDRhElqUL9+/gaNG3Md7i65j0Kjr8RotsJwwUXdrtkeSwXW23ep4PEaXvlcQLFtOpCqA7m3JxvA6xvfuVjsVvsZE+u6yBOf3Mbn/w1h6Ar5puJtXVnzPKR1aUugD25FoerJtnC5sbKmTwE/hiEkUnXgd1rZ1lL9zH3aorOFE6hT7nVSa5pHnvoiViIIwsi+0qpG6huvnI7H+NSN9iue64hyIRJF5XpyLjseKlLH61WswfC3oOfIm3IWH4yQq0PIE4aoEzY4cxdb5yT7BZn4JHYZPIujkceen3lo2ftVxJne9n1wsXjfEjVv30K/nIzw6x1tt6za3n+TKej+5m3Wj+5mv4PMWIWYtwj+gJyG9jPnvTMD0teCQftfjLuyEbrpw25LNts3EWTtE6e4b1J1QwuKv36zl221Bfte7Y/osyNTDyaC95wXM+OKO9CnLWYNLcent1L1zEBN3NJ5bEmPkSJP2ZjLL6sklcS4/1k3fEaXEd5H1sTep7+ZArkyaRnUC6jhZ9Ti6n/1sAw9s71IzdV5IC03TQGhs/vRuepxyEbq7BdIJY7htNsz/J32G3ZFOl0+tGQC+3RbkyW/Wcl2fTnQu9GJqGttiCa7/cAkbwzEePb43z811Zaa7fxhn8kmerP40zxTpDVUzGuHm4wT3fiZ2BP3DXWz5+GYqV3+YoSafzRdaIpIO2gtb9aB9n4uJuh00PYSu5/8k/7mnp98/Jdivu42cCtwPdFTgrlA0YRyZIFIVwGX4CcW2MnfZowzqlgzeTaeKB05rTsy2su5Wu4RkxYJndihimz7a+NwUmEbOiRSgextXOmhPPffgrBj/d2wxE+cs5ff9D+Wer2fy4IBTaSn9NG/uZ8uWILou0XQHO7wNaSdrmlMidcUXPk9Q7RQfFNi2xPQXU7ElWP1I7sWKlrCw3vwI11knIgr8SL8PbAciMexCjXhwA2tn3U88GEgqCk//Ja36/BLfUafy+gcT0gupUUNuh9lPENq0GE9RB2KiFZtDmXX1m0OStgUaj5/pJRx3EDFJ87y2VIUkzbzJE/bNIcnGYPbTn3WRSq797F1KfPk81G84h0YrWDA3GbQ3O/Zuxn/xIxvDX9PG5+bx4T2ZODtTlO73c5fyyJCjGNerIxHbxtQ1dtSRJGjTbVQ6aIfkQu31ORPUKctBju3AZ+sdPlufWV986QBwagQPe6Kqva9wcmTSOJrWIKVTkMyAMYUJUoCQSCJZ9Tik07T7uGdjR+p80k7ytCCH9DqPVR/cmj6F73rGnyjp8ws0l5cBp/0FoWmEtGa08W1K+7FvtwV5c80mftXjML6Pxpi6MsAtPbvR3DBo5jXTfjTF5pDEkWT1p0VeweUDTP6+IM6EoR5KEgEeGFGMpZnoQqaDdshUkw9l8YWOtHYE7QPGZWx+/tQg23DH2F6xhdOOvZNovIJ5S1/c5en3T011V23kDm4amRqIQqHYHTRcePNKcKwooweXclL3P7Juele+/lsRS/9XhLUtysIlD3L94Ait/MnAu5VfcMOgCIa1kc3rPmLBezfw+fQrWfXRjdx9zCFEqgP9mrTyJ1PiAQrd2U/wC0yDjeEYrbz5BMJBbpr3NraZIB7aimlq+OIb2PzPX7H5pcspf7+UZsPGYR7So8FE6hQNg64L4qEy/EYlfrNuUR1H06AyhPXB58iYhaysgmAI67OFODKBZngzFtf+1j1o3msMr8+ZkBHgTv/iDlr0vxgzvwQhdAzhZLXx77c7/HlODH9UEHgjzid/jbJlepzf9TTp2iI5Xb6yMMHE4WbG/fTbIfD0d58AEAgHuXHxLILNmhGpCtC6z2+5tTqdFJJBelk0nlXIKZiwuHrWIh76ciXlsQR6WrDLwPA2r+OURXGwomtktWVNkBG0NyZV7RA6xuVj96lY3u6g6xp63M2XLyf45MkYX76cIB4qorDjCRmvS/qPpr1s1nWB34zk9L+W7SCFRmTev+k8aAI9zv4b3cc8xQ+fPsF3U67k+1kPECtbhV21lXwi3HdMu6QuB8ma9t/1ac/EOUtp7jYZ1+FwQtMNlv9N8s3Lca7vtcOPQtJOy8IOvx3szvSng9388ZMY930YY3tEIoTDd+/8hpUvDeHH18bgszemg/YUdYmcSmHgzSuhfZ+La21+Tp0zHs3I3d0mFWT/Z9alPDfjDP4z61ISbEhqjpga4fgWZn55H698cAUfflXK8b3G4fe0qNMva0Y43QKuvuOoSaqNXEp4NbONnOJAp2l7IIXiIMewPRw9opR4ZBt+0S5d4w5JFdilb7jpVnIGC74Zz3XHLqf01HLuPVXQpiCO8Pjpc+qfKGzVA4CKzd8QXvQonfMlk4YbGRPptYPdvPpNglZ+QTNv9oViZTxBG58bTSSfC4SDhKs2seS/l+CKrwdpUzzqDlqMfRjdX0zZjDspOO6SHSJ1igMeXRe42UJ4y1Ks0Ebi5ctxsyVn8B5CR790DK6TBmG98hZanh/r4y+wTjycaPAHnEQkQ1W45OhLiEXLswa4uq85XUY+TNmqWQTe+jU3DYpl2PjE4SYfrEhw0ZEGq6ZlttdaNS3GRUcmbXR7RFJpb+fywUGeHOPmrlNd/GnJWyzevin9foFwEAvw5pWguZvXCtKjlpNe7KZo43NTHk0u9lJt4RKmhu1xUaHlI3ydObzt8IzfUacsCl04XDckM/C5bogbXew4Tc+pqq03jLK7ZTuINi0R4y7EdfOViHEXNqgwnSlMvn41Xqv92aGD78hoG9pl5EOgu+u6VKNG1wWmtYHlUy5j8UujWT7lMkxrA6apZQTzEfwUHn8V8R8WInUNKxakTe+f0+P/XqfDKXeBy2DdJ4/y/az7OMzr8MywLrw28hgeH94DTXNR7DEpxmTNG07Gd7rijRiX9kj6q1SA/s+vEvxjQZyrjjN5aqyHySebvLkkqTWS2hR1iTCGrxioble3fV291ORTxCwf/U4qrffmZ03Fdt2syh1k60GmfpK5SfzOvDsYeNQVdfrlulPdd41qI3dwo1LlFYomjCMFfqsIMyGwMYlUZDr+SIXEa7Rg47ZveGvOZRT4Szh32F945aOr0ylapx97B2s/f4x4uIzDe16ElzAeZxP3n9KeuCPRhY0mQ4wf4sNC8r9V33P14EPSdfCt/IKrB2v8a+V6bh3Qlc3VyvElvnw0O5pso/PmBDoPncS2V36HXlhC8cjb2P7RE2j+omSNu7P/6jAVDYfXiJGoKEunt6cEn7yFBVTZZq3XpwSvCj3uZNAhJRzXmRWzbsbwFdN++EQ6jZi8Q0AqrxWh8KasaYSevEOIyzhmlyEc0nkIWijAHYM8aHntKKtYwoqV0ziz6xkc6j+KuVlaIbWvrrm8+njJy6vnc0HnXtyyYCqXH3EMZfHMk5ISXz6m5qLfSaVsiwQz1JaPap5Pnqlz64Cu3D1vh5DTbQO68cSiNelrbAzHiEvJtR8tTr/mgUG3A7Bqw6ydTlnUvXOwoukWBW4XVx1n4nEJopakwC3RdCtdYZ6tppwCP65giMQLUzKU3cP5+Xhsa5+n1AtNUGHvO7G83ULmaKmHQbfRj4HQQDo40qYp32sePczyNyZk1O1vmPcU7QZcxfKdBEPj/nb4jz6HtZ88QruBV2NrggUzfpMWd+s95DZCPy7CshNsjka4Zf6KtJ+6dUBXLEtm/U7b5cOTZ+mAxgtf7AjQdVeM/6xZyBntj+DEIxOc3tNDxI6S77LwxOJ0OuVuVr9zK6FNi9kw7xm6jHyYFTNuqJfIabLTTVu8nqpdppjvnMb+8589nzPIlsiszxXlH1anX94bqe62LatT8VPp+E3XLhW7hwrcFYomTBU6BR43wnYhdJm1LVDcTi7YCvwljB70ILMW/jFjh/jN+bdz3gl/Ib79B4RuIIXg+1n34B92DTNWv0z/wy4kz92SIq/JtR8uYmM4xsKySi4+tiOtvB4KPTrb41HO6lyC1wUPL5zLsDYduKbHIIS0aX3GEwTn/RVhJCcYuyJA2Yw7aXneYwh3HsFE/XuX7g10XeDTwggngV0VR9fdaqd6PyFkPKvg0xFjnwFqB+6QDN4tvbomtiKIzPcQDwYwfMVIxwFN54iz/pq8vuZi+xfPMeqY25leo47x7KGPURbewFMLbqUsHKDYV8JV/e6mCAehlfHG17dQGQrw7dopnD3webyFXWvdR0U+m8kjLAxTMK7HcQQTMf6va18+2LCK2/qdyJ0LPiAQDiZr3AecjIkB7kMp9EruH+wwaU6ypv2yow7jlrnfUewxua5PJwpMg4hto4lkjWiKNj43P1RFM1LsJ85dxpPD72J47+37Rb1Y0fiJ2fD6mnWM7tgOXWjY0uH1Nes5t+sh6cTzbDXlrpMGkdj5FP6dOfhPGYy1UzDfmNq07RNE9rlTyBjL3rgmY5PR5S7IeZlGj0zUqttv2f0MVszIDOZXzphA97HPYoW20rL7GcSqNrJw7v1pNflIVYCFs+/k2FFPs2n7Fm5ZGMvwU3fPW84zg/pk/05dYH33DyrXfsLlpzzO2X0EHpcg4lTRq0Ubpn2/lPMO70EsuJFmsXKCs//Kel8xhw26hk4n3UE8uImNi17BtiIcNmQChrcIw9eCmCjCrqPDhm1LiOdx5uBH0ifo2TY/d1ZsD8e25QyyhXCyPqdrJrE6/HIq1b2ucSgUuVCBu0LRhJFIotYmVswcT/GRZ9H77P9j4atWuoVL77NdREzBZSNfw4WOZcc5ouMZ9DniIqKxCtZu+IR2bUcSooiI3EL51y/QY9ANtDn5dl5Z+jgDO43nzvk/sjG8jqdObJYRbFTGEzz09RruGXgERaaHPN2NFDa39juBqGNxzdxp6UDm/mG3Q3Rbetx2RQAnWgFWHMy2QGZALTWDsLP3gxJdF/jiGyh7bQJ2RSB5+q9U7fcf0s4q+MQueiOnekRbXy5BG34EZn4JJUdfwqq3J5Hfrj+te57Dyrcm0nnkg5T0+QWBBf9Mt4Bz+1sRCgZ4atFtlIWT710WDvDUglsZf9zj5AmTs44v5fXqlMeF617ihLPv4+sa91Gfs93EXAl0DEJWlOs+nZ627Vv7nsCMdcv4y6CRxMJbcaLllM9/kLYDb2GDZTBxzlKKPSY3Ht2Zdn43Gg4bw7F0C6VfHtGOAtOgldfNkJLmzA5so43Pzf2Du/PQl6syvoeN4RiWI9BiqeBB2ezBji0llYlMwbTKhIUtZTpwz9ZjXbQsygjkAVwDemBlS6lvRG3a9gVxGafP2e50ury3UND3bIPN3z6T2cf965fpMPSGhh7uniMMzPwSDF8xJUdfgstTgOFtTjwYwN+6R/oxK1qJlBIZKsfIK8KWtfu3R6qSQn3CU8zG8BqOap6f9mWV8QSO26HXWJNFr+34TjuO1qiSlbiPPJvmnU9D6G78wPrwNp7+7hPK4mFu7ZvUFQh+fC/hTYvxt+5Bm94XsO7Tx8g7ahSarzmthl1PxdJ3CHz+V/yte9B2wBV4isAwzTq7lNi2xNCTKea51Nx3TmOft/RFThlwO+/Mu6NWkK3rgjMHP8zUOTfUeO5hpJVPXRkk9RmHQpELFbgrFE2YZOrbeOLBAIHPk6eOx1z0C3AMhO6QkJvQtgXYtuoT8vuPI+EqIOoK8vriRyn0FHNit9v4/dzlbAwvpI3Pzd3HXI+DRjxeSf/DLqwO2pM76Qnb4Te9OmSk9947qDuhqIv7Poyn0+ZvHJ7PCytmEggnTw8D4SCTvp7DM4NPp+Dch4jMeREnVIYTKqf8/VspvvB5Yrofn1OOXbUVO0SPHdAAACAASURBVFRO1TfTKDj+qj0OqHVd4NHDSbGaGi3HfFo4HbRDblX7/bGJcDAihYmZX5IRvJv5JUiR/bQ9hWU7hPLz8Bx7CNvfe4gupz2IbuZx+Cn3YfiL+e61K6uV5TexZek02vQ6HzOvFQgNYdk4gnTQ3qFZT0Z0G4fXaE5MLyRhVVBgNueCE57BkTZOtIqY2ES/i1ojpI4N/OXLOJ+tT9Vcuik2fQTCQQLhIHd/9SG39zsRaqhNxyJbCQuTiXOWpIP0CbO/pY3PzRNDu9LG56bYY/Lrnh0y+h7fO6g71/frhCZBE4KyaGaT4TY+N7o4cAMoxe7j1QXnderE3TPjNdpzdsKrW2mB9mw91m2SonAU+HGdeCzC54UCf/K/GgF9o2vTtk+Q6HmV9L/Ih3R0NE0ijCpa9DyTeHQ7sfA2tn03nTa9L0A2YXG6qO2jy+jHsMNl6cynrmf8icKOw2jT+wLWvH9nOrugy8iHsbdvxN2qC4mKtbQ6bBiHdBuF4S5ESoeolk+FXoTHqzGkpILzurbN8GX3DOzO6z+s4+RRrelgmhT5DP6+eh1nFrbg/9k77wCpqrON/85t03Zn2QLLCoLSFqQrRekIqGCJoMZuhGiiIDbUIBbE2I2aqCA2MJbEFKOiYosFlCIiFkBdpagIu8D23Sm3nu+P2Z3d2R3QGE3gyzz/wM7MvXPn3tOe8z7v8969fgVnHDyKBW/aDW02m5kjjuG+z17hpg/f4vfDJqKMvpzgsrspOuxcyj55GuOw05j/8bykYurCwXeSX7udguKJKdfdWBZuT/guiXlLGXtpxXrWffFnTh37KJ7nppBs15X4jU6cOvZRpHQQQgM3G2svkf/vex0ZZLAnZIh7Bhnsz2ghfSt97wFK33uAfue+hC3A81yy2g0glDOCmnqb3VacFbU6Zw66FwWFmctSS1Jdu3YHC8b2BQPydEFZtARI5OUWBHxcunxDyudr4pJHV1oppeHufNvm7MMHsKysKV+3NFpHXMLGbS/Sd8JMsvBT/fqduDWlKNLBH/+WXc2j4JOup/bdBwmPn/0vl4lLGvAsmdVqMheenSTtjWhytQ8kj89E5X8iCDU1J71Bfor4blLgkxHK/zELJZQwKfr8+elYdaX0OfPv9DjhXkTDOToMOY9NS69Knr/XlIcQVoz8YBHZRgHH9L6RG9d+SWl0J6OKCrm4f2+qJejSIRC1MNQitkbruOfL9zivVx8eXelLad/3vyM49/BhXPH+s0CibbcNhJi+oklhcusRc7E90jrHq4rG7cN7Uh53kgvdxvfmrPyMKw/rRpesAKrlcvuwXvxmZaKPjizK45KBXfAkENARSKQEw/Zw/z/LmDPYKxxX5+8fW1wy0CBXF1TZkr9/bPPLoQa66jaVgEMm8tWlALfBaf5XpyDqIjh/XpqMxGunT8J5aRny68Q4+d8u0/ZTQ1UFUm7ntVcvJxIpJRQqYsyYu1Glwbp199K12/H4s/IoGnExleufo6jNgf/tS/7BcF2JMEJs+efM5Lph+5qH6TLhRkqen4EezKfDqMtR/TnEYuVk9x4Prk0wv5iDB53PJx8/woDiS/D5DmB3tI573vuIPL+Piwf2Zebb61PGsmtWfcbVg7oTcWxUFRRF8vMeB2BLjyv7TuCaV1LXDQvebRpXVVReK9/Iz4++nbjQCRf05NlP70xRTD3w/pXMGnofW5+7uJXMv8fkRUDWD6qVnk7GPqz3BbhWVrNjm86RIOmh5mf4t59TBhnsDRninkEG+zOaSd86HnERItwOTwjiwuatD+8mGqtk8iEPsXuRg1MFubkBpk4r5refrOPnPbqlJRam67Fg49dc3L9PSmSwxrJbfT6gamlLw+X5QimvFQWz2Rapo+dhv8GLl+IYWUhAzSlCKAq7GwhZzvhZiEAYx46RPej0FEKtqYIQJorn4ikqEXw4aSbhdAY8jZO5lDpqTlEKeU+62jcsTL9vVD6Dfx3Ci7Ft5X0p8tNtK++j69E3ky7HvXntaSlt1FA+bY6by+cvJBZrRUMvRDpmiklR90l30m3iHah6ADtejaUqBPO7cuHQuyiPxxtIe4zjOnfk7J7dqYibuJ7HQbFsKv6o41SZhHJ93Hz2IGp9Mm37zjGayu4UBbP5pr4mRWFy9YcreHD4SSmmdJCImNfWbCYv90CCmj9t/wuoKkIRWD6FLCl4YGxfNCGoMB0ualgctw/6uHVYL0zXI8fQCKNkyPv/KISUnHewQeRJk1iVJCtXcN5ZPkCSHa3H3UO+uuN6SF3HbSDtkIiuO39einbSBOxHnkHkhtGnTsZRFTTE/8s8d02L8s/XE6QdIBIp5e23L2fU6Ds4bNClxONVxOOVbNzwR/r1Ox+5vxdjarHZH9m5ASdeix7Mp+2IGbyzal6zDYy7UIWGqgf4astrDOpyHRWPGilj5DVb1lJrpS9vWRhs2uxvTP8RQLaavqRsjhGkKJgNCI4+YDwXrn41uRl6w8Dp1JgVfFW1HkiQd6npdJx0K5oRwrPj2PVllL//R4SM43lO0mQu5C/giN7nk5vdCUP3gxdCKpG0hD4jY89gX0eGuGeQwX4MmxA9TrgPz45SK2O8uHw6QX8Bh/a+gsH9f0uOLdg138WpSkw6alhALVzX/VBM4XJW9w4Mys+njaFTbdm8X1EBwMx+fTAUwa3DelFp2tz8/hdcOqBLKyKSqPmeSt7bhQRtAwEeHjWZKjPGS19/zs+79uOBT9/jmt79WfnKNEKhIkZNmEeWSBBhJZRP1tgZbHqzmVRv4p0Izd8QHRJkx8pxH78Lp2o3Irct2efMoi5Q0Jq8pzHgaazxGvVyyJ9yV+toejNX++8Tlc/gB0Ko2NEKNi1tyhNNlPFpHXFvrD3dSDzUmVNoM2Ymbrw2mZPZtsfRfP7chSmbNF8uvZJeUx5CKj502hGrrqXe2smW6mV07z6N0ug2juvckXN79aAiblJlmhxIiNo/NvUTp0oSewLyp2u0Czmt2nfMjQNwVtf+/LzrAECw9OjzUF0V6cFusw5Vkdw+vCe/WfF5cuF605ADydOilJsaFfF4WmIvkVSaNnMaIu3tgz7uH9OX2Q2ye0gsiq9uiM47UhIK+SH6/49UZfDdyHIVdj4ZT2m7kSdNCi/24y5+FsIh9BOPRAQDyNp6Qtkhaho2KYXntcpzl1W1iHb5GHPOBynxauqQr64g++jhP7pJnaoqBDAQnkAqkhjWT7oBpaoKlq7hSlAFGLYD2EnSXlDQl959fkEo2B6Ewgdr7+XgLmfj9/fi0MOGsv3bJXTuPHbvX7Kvo2Gzv3HMDBX2Rfo60WHCA9TVf4XfX0AkUtqwgTGLI464Djfq0Kfbryi9T7YaI++56HDqDI8nxh9GnqdhWh47TZOnv/2W7ZFUc83ZKz7j0gFdqFRk2nWDxOXeYT9DEQqVZl1KStINH67imr4X8Oh7MwDIDxZRVfc1zy+7mHCoiKOHzGXdty8wdNRM7GgFru7j+RUJ0j6i34wWOeq/Y+UnD7F5+7Jkzrqudkgh7xkZewb7KjLEPYMM9mME8JCan/r67bz48a0E/QX063cb166JUBbZxt9GdsWpsvF1VsibqKPnKtjlHpV/snFrJdOmdeafH1us2uoRztY5eWIn7vm4hOWlldw1sjfPbSplev+Dk0Za1wzukZLHluMXXDXG4I63m/IrZ4/1URYv5w/rV1JhRbl1yNE8s2UDFWYUO74bSEQ1lq+ay1Hj5uMIh+wTbmD7yvtSCNi37z9M51FXEdLjqELF/effkVWJ42V2DrK+nKygjqu3yEFvsTCBphqvriuJGh3IP2MRwrPRDD81VqqrvFS+OyqfwQ+DUFS6TbwdJ1aFogfw7BhaIBehtCbuLWtP4zpUvHwDOeNnJc3p7GhF2k0aKQWyKsTOxR5OVRgtN4cBZx1InVXBqKJCpnQ9mPs/3sipB3SluxGmbcDPzrCVXJRCYmHqQ+E3Yw1ub+bhcPFIgSUcnj7yNAQ6lXUu7YNBzLhgycsmtXWScLbBpEkG+cEID4zugWnH8WkGPreauJLD7HcSrvIt+9O1Q3pQFPIzvaF6AyQWvBXx9BGtgKpy45oSFozpl5nM/0ehuDKl3UKi7SquTOSvTxyF85eXk1J4fepktAYCns5tXuSGAYn9wF+a5POnTsR5dQWhyeN/NJM66UkCUR87F1moYUHeUTpZbQN4qkcU80cn8KqqUI7C7Le3URaxaR/SuW14B4qUAKFQEYFAAQMGzmDVynkMGjyLzZteokfP63j1daOhTwuOm3QyQqn97i/bhxF3g/Q44X7qa6NowQJs2Ya/v+A0/MaDOGrc3Xzy8eVUVKwnEiklK/tAamq2gqvgVKWaIDpVEuEJ7v1wF5d1KKT2SQenStImV+f6acX8ftsWAPrkZTOj68Hk6To5AZ35m7dy0YjO3P+um7JuMAyPi99ZTWk0RlEwwJxBI3hg47tsqN5JabSObF9bIEHapx46j/c+ug9oqp8+duAsXnx/LicNvhnFM6mNlDJ24KwkaW/87PMrrmDswFls3r4sWZf952MWN5D19PghsvsMMvgpkJnrM8hgP4Yio9huHKEHqI2UcsTAG5m7JkJZJFHPfbdl0663QptRBrueNnGqJFquoN1pPiqWWuxcZDLgNIPNWxOEY+nLFldP7slVfUFV4G1fOV/XRhlVlMeUzh3JEz4WDB9APRaaIrj5/S+54tBunDPUbShr5VDtxrhp7XpuO2IcuT4NW7qc0qUvZ3Xrj0/xGD7p71ixnWxZv5CoVc2rDRH4EUfMxYlUEGnmJPv5P85risCPnYdaVw2AmDSZXa/MTZuDHneDdJt0F5ta1KVtrPHqurJB8h6gbVY27u66lHsa9YLfGZXP4IdBIhBCSanj3n3Sncg0hmutak+rCeVD3arH6Hrk9aAZ2LGqtJs0ipfHjsWpEfTqJwP4p1Zwcf9DuP/jT7miQz/qH/eIVUl25JoUnuWjfImF+XWCMGi5gq+iddz95QYuG9WfLnoIxRN4qkvcyMOQOtGo4K1XTUaNgOXvJvoQkOhLSy2mTAkh8PCrIaQb5aMP59Nj0NykYd3C9V8lqzS0D/rYEYlhuV4rkl4Vt9PL7hvSVzzZoKhRFSxdoSwSB7+WyX//H4CrQrC3QniIjhoUuFFJ7RobVwXfhGFJ0g6JaLrdzCU+ndu8NnUy9vNvpcrn//Iy2olHJsov/gCTurSR9XqZJO35k1Lnp8JpPmLBH5e8W7qWJO0AZRGb2Su2s3DsgYweczex2G5WrUzIxH1GDt2Lf50k7ZDo0y8utTllSjZg7uWb9m34fBr10QN5cZnJqBEGy9+1Un7ja28EOPH4+axeNYNAIA/TrGbNe7dy9Ogn0XJ9KZtEwd4KUsLcXgewc4GZMt7uWmTxs1+0Z2ttlJu69iT2hIdVJanKtfnl2Z149JuvmXvUwVTEbGKug98HX9dFKI3GACiNxrhl7XouGTCIq957iaJgNnn+Am4e9yxCCF5efR1lFeuT11IbKcVv5FAbKUUJ5FBV9w3hUFHyteZo/Gzzv6Xcs6KuZW33dFH6DDL4TyFD3DPIYD+GlA5e7S5Un5+fD3+SNsFuzOln83ppDT87MJcOIZ3AiQo7FqRKKXc9bVJwokHZYpO8LMFxE334/YJ4XGLFJX/6q0mXgxWmj+gGQP9+eSx/12TVVpdwtsexkwJ4AYv++dlUmhZXrdrIyKI8ZvQ/mDpbckn/Pjz66Rec1qMTEpc8XwDH87h05SvJnLWbB83FdRPS/EiklHdXzeOooxZg1pWiZxdi1WxHD+Y3uIWX8uVbc+k18bco4Vxcs5rccbOoXf0Y1o4NKTnoriuxtA4Jg5oWrvLfBy2j8ig6UlEJOTXIltH9DP4lCM/hy6VXppG2P9zqsynRwM5FkBWk3dmP4kWqML/5hGD/n+G6Ybof/zfM2q2Uvn8HdrQ84YYcN3GqUgmGUyUJ+ztShcfUTsXUL/ZS+sTOJ03anWGwY76JlisI/0LlqZ1fc+2gARTVBSlbmEosnLBE1wUnHu9HKBAMiuQCGBKLYOkqvLvCZkuDouXoCdfhV9UkCR9e1IbubbLxJAghcBwXQ9F4dNyhZOkqhgqOJxECHhjbj7vXbU6Wi7tmcA8Wrv+K9kEfmmiMKHr8ZtnGZAT/9mG9KFAz+e//n2EbNnlHJ8byxvbZfqoP07Dxpyn51tIl3ssOoc84HTyJqyhIAXLjplbHiKwg7g8wqVNVJRlZb95/ZDDR7wpObCLt0NAXF1kUXmRQT/x7nd8QBkgBQmLJhNy+pSzeBfJ9KnP6FZGna1TaDg+W7MKUkmytI+FwKCmZN60awjkDCAYtRo0wknPj2nU2nqexvxJ3v1/HdgxeXBqnYweFtgUKR433EY9Ltm516H6QRsAn0BEcfsQj+P21eJ7F+AkLESq0n+ajbFHiWQV7K4l294BJ4Rm+tKqPrlkh5vbuQezh1LE29oTHqb/swObaGmav/AyAh8f1w6+lUpLSaIyw7qcomM0dg8eT49l4jkvcjRONl6d8NhwqIm7VEA4VoWkhFEXj5NHzkci0tdbjVk3K30Loe7xvLWu7f98ofQYZ/BTIEPcMMtiP4QkdL1KD5j+UrUtsYjU27borXDiikI//YfJNjcnIc/ytJlU1LDDaK3SY6UfzCz770GLzVq9BDujjvKk+PE/BdcHzJBs/tRnQzyAatSjb6fHSUpMB4xyOOqgd7QM6zx07mArTSjGimTO4G4UBg+krnuWq/qMAUgy8rvlwBQ8OO4ajjnoY06ph44Y/4ikqy9b8NmmOM2LEXHh3PpGdGxIS6Nw8dj09AzWUT87w88k/bh5O7U5qli9IyUF3XUnk38hRa4zKq2qQYDzjMP9jwZMe2R0HU3To2QihIqVL6bonkhHj5khGA19bAWO6sutv03FrSvF3H03O6JmY9Tl8vCRErMYjkHMQA6Y8iC9UTf3uErLbdEfLNVPavZYrKIt9heprx4H+NuyoSl18O1USrY2CMUtS51l4OQpntOlKkRtMLlZ9nRVyj9TBAp+j8PYqM9lvJozz8dnnNl0O1vD7BSBRhMeII3wc0tNjy1YHy8oi5AgeHXUo6yoq6JgT5qK3ElHAkR2ymNq7gBlvfZOU8l47pJAF6zdTEbe4dkgPLuh3EJcN7MLWuhgL139Fnk/nhsOLcQDpU3lk3VcpEvvfrPyMB0b3RW1G3FVVYBkmjnTRhIrRIlUkg/0LAUtnx+JU4lu22OSAi324qpZWCq8gyfErqDX1OIufxWqItqtTJ+Nlh9LL57NDRFD5V12zAxhJ0t54fTsXWYm5J1egBgVqWFBwopFUDFS9aSO875bkq6qCavn4oFn99QEn+VADNjtdUmTxC4/sxNxeHdm8xKa8xiGQI5h7QkcqzBp8AY2gVAiFiohESvl22zv0zx/FkaN1ItHG74IjR+uomgRr79e170InGpGMGqFQUGAQiUjicUlpqcPg3jof/8NM3sdex/tw9SBr37+Jnr3OJEg7Nq+y6HSKgS8o8GULdtyfCAi40cSGTMvxttwyydN9VIStVs+3nc/g6S3f0jsvm2m9O5Gla4BK79w2bKxKKOuKggGKgiEeGnEc0txJneVRufoRDhxxOcePeYg6qxozXkH5rnUUdzsZy3M4ftxjRABfuAuq9PA8m9PHLaYssgMXgefEaBtox7vrEzL7cKiIk0bdj6qoiEA9UroIDNxmUviWtd2Bhr8tNF9GOp/BfxYZ4p5BBvsxIl6QwIFjWPOETawmMWl06Nc0AecUKag6KZOqr7NC/rEGOxbGkxGQkWf6iEQsynZ5rF5jMfxwndo6D10X2Lak9yEaGz+1GXSozosNebwhTWP2ig08MLYfErhm5ecppOGW9zexYExfSqN1dAyFEULQJ7eQDVU7gQR5j8RrWPna+QmSPvIWVNUgEGgyx3l31TzGT7iPba/Pw45W4FRvSziLj55BxdIbm8j0sTcgG4zsfkxkHOZ/XAgtQPu+p/DFkoubmRDekTAhbLEYbqw9nTVlOLv+9MvkM8jqezxWTYwPX3WSbT5WI/noHy4DTjTx5x3Kxn9adD/DR8WfmqWHTNMpC/rwqQE0VaRdaKJI5n3xIRsrq7l7+BB6BnPBFUnS3lLS29hvAPyeZFR/g8paj+UrLKIxyYRxPlasMgkGYdSIRGSrvFzy6ec2hw8p4O6NO5LS3UkHt2HOiu0pUt6/flHNzYN6I6RAKGCrDhVxE7+q8Nsjiqk2nWQZpvZBH9cPKabStNlYmdggK4uauFImxc2qKtitlDNr9V2UxsopChRw16BZtKUgs+jcT+G5pCW+ngsxoRKeOhmnuRT+1InYz7+FfuKRYNtoJx6J8+Z7yK9LcRc/i3LRGWgXnoo0LYSqgmVD0E/M58eJO62+v3nlB09REiXnmm0UCU+kjcaiSAqnGUhLkn+swa4/N+urp/tA976TIBvCSJJ2aBgHnrE47Cwfs1dsTelL1bUepUu8lM9uXmJTMBnqZDkfvP9bho+4iRXvXkvPXmcl7m2LLuFJEPtpupRhaDiuwDA8NF1n+bsmh/TUCQYEh/YxWPtUPOXefPaCyaCzDA477BKEm8u6P7vEaiS7vkzM8cPPbAoIVL1p0+40X8rY2H6aj7qwTVltnPbH+ls93zI7zoRO7VAVwU1rmvt89GHB+g1Umia3HT6QrVufprBwKIFQIY6U5I6dw04nxsz3bqc0Vs7owsM4v8dJ/Krh76JAAdf3/zVPb32F83tMpr5sDdnth3LFx48m379v0CyGHzaHIQN/g6ZoKG6cqvqtvLJmblopfMva7pAg/JV1X/GP5RdnpPMZ/EeRIe4ZZLAfw3UlUojkhAugB0SStPcZaVC72qb9+QZuFSiGQA3DjoWpEZrqp0yGn2bwzGsmA/vpRGOCt5aZSVOeCeN89OurUV+fiIKEswX5foPZ/YpRgO0RM615luV5FAWz2VpXxT3rV3DtwLE88Ol7bKjaSVEwm5A/zOgxv2Pjhj/y7jtzOPqYRQwfcROR+u189NEDlJevJ27X0m7kTEK+fGpeuIGcw89NknZoINMv3UDBGYt+9PubcZj/cSFcky9fvipVKv/yVQ1S+dZSRcf18HBSnoESCOMSTmnzkFhsaoFCpFDY9aWFWW/R/RQDwy+w4hIvW2K5eeTGNTxV0u50X6vF5LdmhOl9emGbgm6BHDShIA2PTrP9CE2wfX68Vb8Zc7aB3xNUP2ZS03CuY8708coHFq+/YTLhSAOJ4B/PxZP9afyRPlavsZjcN4/l2+sBCBtKkmgA9M7z88suhbz0vJ08bvQEnayQj5AOX9ZEufODTSmbZTeuKeHSAV2S8tP2QR+a0hS5tAwzSdoBSmPlzFp7F48cfgNqrHU5vgz2fUhdUjBFx0s0I4QGBVN0pC5xTA8ZCqA1uspHYzgvL0/UaD9yCNZ9f2oyn2t4XXVc7CVvoY08DLuZqZ1v6mSsFq7yLSs/tCw5ByCV9NFYIQSxYJyskJ8d97XIj/6zyQEzfajfleYhRdpxQHqk9CUAbQ+fDSkGhhFiyJDfoKgGw4bPQ9c7IqXAtmk1D6YRB+0XEIpBdYVHXp7CsndMBvQz+Oebid92xmR/8t7kFCl0P1zH8At0F+JeHEPore6dYzc9V/Nrj4qlFm1PNtDbKTjVHjvUOJbpEZBqcpyFpufbdrqPkF/lgrdTjThvWvMlC8YOwvWiSK+O/K5TiHkWu+JV2K6DIgT5/jb8YfBVBHU/rvT4qn4H+b42lMbKKY2V8/TWV7io12nU2hE6dhpPjV3PrN7n8NimJQBUOBFmrm22eTn4cnKzDuTEcYtxJDjSwZIuAdXGjWhpa7sfM2Qe73zSZI6Xkc5n8J9ChrhnkMF+DMNQ8KRFIEdgBKF4iEa2Ljn8JAMlS6CakvBQDRkV7P57YvLsMLO1dN6pkmT7Egv8rGyFZ5+PpxjWvP6GyUmT/cTjCVnwsRN9/PN1i2hU56BJOlK2Lm01sigPQ1G4b9gUyqK15BtBbvrwLS7rO5x71q/g5oHDWffOlcRj5YwYeTMfrL0Hz7PZsH4RZWVrGD3mdzhOHNe1WLVyHscc/ShepCJB3NKQaX4CMp1xmP9xIaW7Bxf4Pd/Mls/Ai9WCGiCQk5eymGzXXcEnFbDg8JMMPltps/bZRHsM5Aj6naWSXxug5nGX+rBHwRSdticbKIbAsyQiWxJQNHK0IM+/bLG6zuSX5/gQtYIdi/ecx5kTUti5sDWhb9wIy8pSeHZJan/655sJY6g2YcH8IztRa3nYnqR9SE8SjvN6tuOdfzopxy173WbAOFBzJAFVTbtZlutPbIAkar0XI5UoRrZOzLNxpJMk7Y0ojZXjCAcZkgTsALaVyYffnyAADPDlghASKcFppjL3JMjn3mwlfZf1CQ14c/M557k3kbsr0Yb0aWVq5zYztWtEy8oP6T4Xw6JwWsscdwM1S0A14KSPyHt1EFC+w6ROJGTdzceBQE5CndK8LwHUu27az7YJ+InHt+ApGrZZTSBQgOcpCCF4/Y3W8+DJk/3f78HsY/A8wXvvWxxzlI9DeupJ0g4QjcmGNYSgz0gjRanU9pcHoBsw6nSDeFRSssYhq0AhkAW+Zpufbq1EzRZ4cQ8tT+Evm7azZlc1Tx5+KKVp0pL0qCDb1CnwGynjWKNKCMWlzvFw7Cgz19xOvq8N1/X7FapioKCiqnDnhj+ybOdaigIF3D7oUv6+9XW21G/ntIOP4eIWEfgXti1jRs9TCakBquxa5g2cTq1Vz2OblvBgyTNc2fsX1Fj1XLH27uRxdw66nCKjHbblpdR2VxSFF1fNprSFOd7eDO4yyODHwj5N3IuLi8PASuC4kpKSr1q8NwB4GMgBlgMXlJSUtNZxZZDB/2OoSj1rNz3NoJ9PR6uSyIeqsctdfAUqxkW5WAjcSpKkHcCtTx8BGJvC7QAAIABJREFUiZqJqIKAFJMtGv6WEnJyYOxoA8uUlO1MLKZeWmoyaIKWUtpqZFEeU3t3YnozGe+cwaN54NNldAvns/CICehWFeE+v2iItl/DyFG3IYRKn77nUlOzhWVvX8GQoVej6wECgQIczyN/yl3I+t3/NplWVYFfjWLW1hMy1D2a12Uc5n9kCG0Ppfr2PBW1fAb1618g58hZDDhJ46NnEnL5dt0V+g3WsG+tQja0/4G/asOHKxysKPQ7SUdzJTWPJ5zmnSpJ+T9s8o/TUXME3m5J+dM2bi3kThP06aWwco2Lz1HYsXjveZyKKlvJlM2vPbJ9gnC2QMr0/SkYSPS1BR/tosJ0uXnYAdwyvENSLp/v06mts1sdF1I1pPSIuW5ap/m2fp2/TByArgiq7N1sqqvmgEBb7v/8aY4/cDRFgYIU8l4UKODL2m+4a+PjKQvVveXCN/afH2L+mMGPCwVQYxJrfqLtiwIVY0YublCQK1w8VUNLI5d3Xl6ePEej+Zw+dTL2M6+hHzcGGQ4hThqGDBmIiIV8/eMUUztIU/mhcxFM6I+n1BFSG9uFRyxoUnhRc1d5Ez9BsjGQ3h76lQE7HmoyqUvX5ixpMeAkHx+l5LgbuFjcNrwDsxv6UvuQTk5YofNJOh89Y6bkw9vx7Xy28Qn69T+PDeufIhavZMTIh/A8dY/z4P4GVRUoAqLRhNFlMJBqpLl6nc3Y43zopkySdgA1G4w6P84j1VDuEihQGXxRLl5YYcf9ZlOKRjjhVVC+xCS60UPLFVwytQt/YAu6kj4tSTGg7CGTS3/RhfPe+zj5Xvugj12xavIDOqZnkWOEuH/o1QQ1P5VmnMtX/ZnSWA1FgRxuOHQyFWYiH77KrGVajxPRhMpftr7KrN7nEDayqLXqeXrrK1xyyJlUmjWoqsJt6xYlyfm8AdPxKTqb67/ltvWLUtRIV669m4eHzUVrGPsaa7vr/hiRNOZ4ezO4yyCDHwv7LHEvLi4eSoKY99jDR54EzispKVldXFz8KHA+8MB/6voyyGBfgIvDQUVDUYkgH7KQ5QnmKstdrPur0K/Mw26RY7infDQzDEeNN4hEEwS++cQezk7kur/wksX4I32sWN2UfFhbJ/EpCveu/4orD+tGp6wAioAZDaQdGnPet3DFoMPRcFj5+i+TBnSjRt/BFyV/x+/PRVE0XDfOoEGzeOWVc/H5cnhn+WyGDL0a0IgaHQi2K6Bgyu8o/8cVP4hMq6rAcLbzxZLUcnGW1jo/raXDvFQyrvL/DqSeTfdJdyad5ZPl4PRsMNNH1VxXYgY6UnjaI8i6WqiPE4+bvLX5avofdzYBvYAcLYx9R11K++ehagb8JocNsZ1sVgQ93fYp/cD82sOLwo4/xVNeL1tkMmC6H7DA4zvzOKUjKX+uKZrY7jQf1cstTCeR415f76XtT4GA4J0VJuf1bcdlK7/hmpU7uPGIQq44LJ+OWQGyhUo422l1XMR1CavQPqhx7ZAeKfmhtw3vRcStoM6JcN2H85OL0xsGXMDpB0/k/s+f5vr+v+bGjx9Mvnf7oEsRKMzqfQ4Pf/EMV/Y5F5/rb5ULf9+Q2QSMAC4OOi7fLPsdtVve3mv/yeCnh2oLrPmVqWP//CqMq/Oxb3koEV3/1SkoF52B6rjgedgvLkvI5QE6F1F37Eicghx0IcjKDuFJF3dyf758c05TP518C4qupuSdt6z84P6sH1++PSfNuOolHeJVBAE1ilVThbDb4lmiVb9qd5oPz5bJOuF7HbMNk8POaO4qb+JaHgWqwoIxByZd5Q3bwTVcBp+tIx2VaKXk01csrEgBfY6fwycf30LPXqfjCHjjozmMH3BH2n6rqPtXG2+8d/i6MmGcj81bLLocbKT8trJdHms2WBw91Edls7Ew/0gN55HqlLZlN6wrGjdAyxabtJ/qY+fjLeTwiy0uv7ArrpB7fb4HhYLJDcj2QR/XD+3CvZ8+x+V9x+NKl1+vuonSWDl/GDKHOz5+g9JYwg2+NFbDDeuW8OCIy5HSZkv9dq5dN598Xw6X9T6LWivCrnglL2xbxpldjiXixIk4seS4mDhHOXM/WsB9Q2cjhUyrRnKl24oopZPO/2z43Xh2ZkM/g58e+yxxJ0HEZwBPtHyjuLi4MxAoKSlZ3fDSY8A8MsQ9g/8xqEIhO1iIHvdjlcdS3pPlLsIDz0qNaJhfe1QvtzjgVz7c+sT7Slgi6iSFmgBdcuLxBs+9YCVz+yZN9BEXNlMm+1j+jpWMtkNiMWN6HhVxC5+qUBaLYChaWhlvp1AbPnv/umTZnUiklOXLrmLc+AUoioGUkrq67QQCBXTsOBpdT5ToCYc74TjBBrd3A9Xo+IPJtF+NJheAkJBqb1o6ix6TFzU40aeied33REQ/MzH/UCh2LTtLXqXHCfcmXeV3bVxCUf9Tgaw9HhdwXdz5zyUlud5lJ7Bp+1ts2v4WAOcd8RxGeWq0Q5a7VMbrmP7hYvq06cC9fc9pFflRs/Yg041K+h2gg7uHPM62CvZuDzUbtv/BSolQCduj/Qk6tgDbJ4nG4bhJPl5c2pQr+7PjDdx6yfA+BkYIjj84h2EdsgkbBiFdQ1ckprAYd5TGG685KTnuasgFLJZ8+yLD2w7hD6MPQUFBCod7Pn2ISw45g+veT12c3vDRQhYcfg0bqjfx8rfvcu/Q32AoOooQ/HXrazyx5aWkpFTQOhc+39eGCquaGz66LUnk7xh0HsFIOdGdG/bafzL4aSFcmSRWjZDlLsKVGDNOR7ou0rZRdQ2EAENHO240zo5dyHCIb04Zx1WfrKH0kwhFwRB3njiaA+0YX748J9WL4s059DxpMdAkFY+rGllTT8Re/BxM6J8k7Y3HtGwXjSSypGH8LZ70BJrZg5qVqa7j1cstwkN0tNxEhH6vY7YVIJambJzreqiuldQHuA3f7wEf/NlMkcx/+kKA7pPOJhDK5a/LplMbKeXow2SrfnvcJB+K2L/G/8Z71+Wk5wgEJLltNBTFa/Xbhg4xQHNTxkgtIHDStS0v1fBWDe453UFtI6j5zKbjeQZCAelB1fs2gYM1tFzBt/FqrhjUgQNDbSiLVnLvp89RYdYT0v1c/V7TGBRQ/UnS3ojSWA07Y1VYXpR/fP0GV/b+BaZnc+Gqm1Nk8k9teYlLDjmTmOtPS85r7Hpyjey0aiRVpJYVhcSaoLl0PuMqn8F/EvsscS8pKTkPoLi4ON3bBwDNEyVLgY7/yvnz89MvEtu2zf5XTvMfx75+fbDvX+O+fn17Qro2G6+P4yo+PM1DFKgpCzhRoGLXSNQ80cqIq81og51PW7i1kvbnGqhVEv2+KuwGqaX/gjYcM94gmKUQlw7VXoxK06KzEeDQQRrl5c0Ns1SUkOSGocVoCtz90Wec3bN7WhmvgcO3295O+Q2RSCmmWYWqGoBk/ScPE4uVM37CAmwrQihUhKYFCIdb/v6mv/+VrEOztj5tnrUq3H2qbexL1/JDkLa91tSw66Mn2PVR6n5s+34n7/X3yqoazGaSXEVoSZff9vl90UNtEAXxVu0/15fFM4fNJIpFjVZP22nZ7F5kJ/uByGYvMl2TrKEK7af6kjWyG/M4q1dahA/VkTRF5H2dBO2P0XAerSLe0I98F+USyxb89ZtyTj4hHzcmcF2JUSuoeLypP14yrZAbt+5g+fZ62od05gwp5K9ffMMlA7oweYqB9BJ5u7vtGLe+v4mKuMWcIWO5v2QBG6o3URQoYP7hc1i2cy3ndDsu7eJUEYITOo5mYscRrfI/P6wsYUP1Jm78+EEeHnY9QiFFapqlBbnho4UpmwFXrX+E+UN+SfSFy753//GkR5VZi+XZGIpOri+MIhTgv9/e97QmgP/+te0NboWTduyXKtjz/4zIDaOfeyL2s28gN25C9O6GfsIY9F+fQlXA4KoVb1AajQBQGo1w5Zp3eHjE2LRjpHAt2rZtm3xN1tZjvboS/fyTsY34d46rVqSCT5sR8G8/uIODh91Lm9GhlPmp/VQfCMkB0/1oYbCj6b0xWrY5T0qq4i62J9EVQa5fRRGJXHvXc9hc9y1GNItYTeoGU6xGkpvbG0ctTzqHSwmKIjnxeB9CCKSUybKV+0J72Ft7bQ5VNNw7Kfj0M5s+vQ3q6ySuKzlqvEEopKAIyaff/JFeBx1D7tkBqp5I+Hm4NmnbllMnk+OiGhao2dBhph+3vilVSMsVeLZEVSGvv4p1d2UylSNvRi6VnzgUTNOJ5PoJY/DXLe/y5JbVFAVyuH3Iz4m7sZRxrNauoyiQk0LeiwI5VFnV3LVxMbN6n0O1XddK7n7jxw8yq/c5SCS1Vn1acl5l1vL4phe4fdCl/Gbt71Ny3Nv6ctCCe5LAf79n8N/AvtBGM/hpsM8S9+9AugKf/5KjTkVFPV6LWh9t22aze3fdv3NdPyn29euDff8af8zr+08PjOnabJbfwTGrsQI64gIFZSFNeY4X5bLrnw4543VQJQfM8IEncGo8pJQUnJAwCFJVD6shNxgajl9YTf7sPK7/5DOWl1Ymv6990Mf9o/swYJxDSNOotmxu/fQLKuIWd488hJvWfsjGqmqWfvUNtwzrxZyVn6XIeGV0c7JWbiNCoSLi8Ur8/jyEEJSXJwxfLKueeLyKMWPuJh4PEIn8OM8tZKhp86xdqe4zbfen6Ef7QnsN+9LfeyH2fu9zVJEiyVX9CscNnsd7X/6Jbr0u5IZNS5l9wUSCC83U9r/Ewdrow5/rx3eOxz2VS7ls5iSqoxa7rBh/2voFl0/rm6zTnpRxOhI1LAgerIMuOeDXPhACoYJre4S6ayjZEo8m4p9/pIbzaKqs1Lm/iuDVuTxVUslHu6Nc1bsDbaSSJO3QICtdZDLt3AKWb6+nLGJzy5qd/H50V8rjLvNWf5XM050zpBBoSD1Zs42LDz2VKz5IRJc8mZgCq8zatItTRSic12MKd218PO3CttGUCSmpsGuTn0tE1y9LujY3ojRWjgi1TT7D7+o/yVJ0a1uUovMKyMvLSnvsf7LNpmuvjdewr4wL6ZCrBTB+mYP1aE1T2/9lDjKxH4KsqsV+7LmE+Vx9JOEWv/CvyKpazCvOTpL2RpRGIziIPfRTLeVe5AoXuXETjBkMlVXfOa6G9FRyH9m5nq0rL6bHUY9wwAUN26+qpPxZK5krXTjNgLDvO8+tqgrlKCl57bcN70CBX8H0BJ6U1FkKfhkhkBNsZVJXUfclelDStcNoovFKwEEIjZpaia6DbUvCYUC47N6dqm5rxL7QXpujbdtsXJkYcxXVoWsXnXdXNpWBC4YEmubx7vpb+Wb3aoraHkIot5C8GQdQFxdsw6ZoehhtQW2ybWnnt8H1JUh5u7MMFF2w40GzVapQ3tEGUkiUCFj3V7VK5ci9Oo85X7zOz7Tu+DWNCR37cFTHvlSaEXShUmVFU8axxzY9y/WHnsuN615I5rhfO/BY5n+eGKfCRoJEp9u0zPWFEQge27SEGwZckNyEbNy4nP/5X9hQvYnzepzE7L7TODBUiKFofF7yJ/I6T0Rn/0oD+r5jVobc759Q/tsX8AOxHWjf7O8iYMd/6VoyyOC/Bik9vt34N1zpYLath9kh9Nvbol6Rhx0UZA/R0cICXIG9U7LjgTg75puULjDZfl+cHQvjCJe0UktFyhTSDg2Or8CMlR9z7vIPuHT1J2ysrKMsalJnO2ysqqYoGODU7l3I96vcPaoXj47vw4KxfWmj1OH3hRk95i5CoSIgQdqPGDaXzZteQHounucmX/f5wuTmdkPVOv6ok2bcDdJt0l0JUzRI5kvG3eCP9h0ZpIejhuk+6c6Ue9990p04anivx0VQUadORuSGERP688WLF1O1/D6O6DeLa9a9xNs7S7hy+9/4YkaMmpt8aFcnNq0iGxNk1qmSRB5XOLndUHYqEcr0KDd+9iFLvtlGbY7FAdP9dJjpp+BEg+rlFopfIe8onV1Pm7h14NTCjoVxvr4pRtlDFkIXIKBOcwidnZD0agGRXrLsJByuN1bGuWPjdsJBJa2stIO/qRxbWcRGIpi3ujSlFvXfvqjmmsE9WTBmAJcO6EZ7fwGQIOa74om++sK2Zdw+6FKKAk3vXd//11Rb9fx61W857eBj6NOmW/K7mi96iwIFxD07GXVqfP+qtfdwfo8pKddcFChAM0Lfu/9Yhpkk7Y3nnbX2LizD3OtxGewdig323+vQTw/jm52HfnoY++91KA6IzkXoU09EP+NYRGEB6rGjUtzi9dqEPL45ioIhdBS6j78ttZ+Ovw2lhWN2Msc9GoPVm+g+5uYWfbtFuxB68v1G2NFypGmyY2Ecq8xjx/yEwRkk+sXORRbCCX/nmG3pWpK0Q6K/zF6xnXoHZrz1Dae8tIWbV1uovjZ0+1nCYR4SpL3/FBWMKKs/fYQjB17JyH4zWfPFg6iqS05YEAoKcsKJTW5VSTWM3NfRON9pqoPf73LoAJ28XIVAUCCEkyTtE4feiKb4kHoh567cxinvbObcd75m1qZSdl6SjdGwrih/x2X3szbSBS2sJNVI0LAJ+bRJwXEGla9aaAEFGU+fyiE9ySlde/NIydsU+LJYVLKcsngNl773Jy5/7894UnDDgAuS41iFWU2u4eO+YWfw8IizuazvKOZ//nhScVRr1RNz4snPN6IoUECuEWZXrJIKs5qA6mf+4XN4dPgNzOp9TpK0FwUKCGmJzaO4Vc8bK67kg5LHeX7F5Sh69D/wpDLI4Pthv4y4l5SUfF1cXBwvLi4eXlJSsgI4B3j5v31dGWTwn4aCRlHxCdREt5MT6kClIrhh1Tb+MLATXmnCNKvwDB8VL1kUnpa+nJVURFo5XER6aeXumhBpX8/WNRaMHkatZbFgw2fM6NuDeete49qBY1EVB4HGgf4CkC4TjlpILFZBPF7Jjm9XMnzAdaiORsTcSceOY+jX/1eoahbxuL73Or4/AK4rsbQO9Ji8CFW4uHLPrvIZ/LiIRj2CoU70OulhpOcihIqjholG9/6MHdejLphFaMYZeEodVl0pVl0poVgN+f4sLut7NDl6gEo7yu+/fJ37DzknSdqT56iSdPDlcvaqlxlUUMgDo4dheR6KolBhR2ibrWC0UdA76cRMj0C7BMFWhKD8xdQc3IqXLNqdZfD0V5s5/qCuRH4BXiC9rNRVZdItfmNlHJf0LtrNt9Hbh3QEqbWoe+f7OaVHHrOWf5uMKN40rIjRhYM4u+ux/P7TpygKFHBGl4kEFR/X9f8VmqIlXZWPP3B0qwg7kFz0NkbW651o2qjVgaHCZASscTNA0wL0mLzoe/UfR7rpzZ8ydRX/LUhFQFgBYSXakADCClII4ueMw47Vo9ZWEXjxfYwJw3DDIWgg7tmvruKOk4/kqvXvUxpNkPg7ho4iSzh4wRAHjZmNogfw7BhKIIRUVDSVZI32CCrZUyfjvLoCbeRh8OYH9Dr8FmS2HyUrTEzJxm1WXrCRRG5aOquZOeVd4IfCaT6wSDtHCU9g+A7gkMmP4kkHKXRiLdqcK1vXbi+L2FSbbgqZn7NiN3OGqgRPsOis55Fj+Hhp7YVEzHKOHjIXIQSvrJlLbaQU06plcI+LECKApgl0NQokUrr2FzTOd7odIxQEXdfwPA9FAUWt4/DeUxmmnI/txHhm+UUcecTDKfdxQ2WcM1Z8xR+POoi2qk6bYwx2Lkps/ne8LH1pWbce3DqJgglBF9/lWdjPx/E2Jwo/iQIVT5UsWP8aFWY930aqOLbzAHL0xMZQaayG9sG26ELyyLC5bI/tptaq58nNLzKl83j8mspdHy5OGYue3voKM3qeyp2DLuPKtfekmG+qQnBgqJAHj7gWy7X5w6dPcdrBx6Soin43eBZ+RSPHqeP9T35PWUOpt0yZtwz2NexXxL24uHgpcH1JScla4Ezg4eLi4mzgQ+De/+rFZZDBfwEaAaQvwCvvzqI2UspJ45+nwnSJC4/4Gich+7USubnWLi8tYXA0iXVxNqEqgfAJpClxCgQPfPU11w7pwd9KtnNGx7a00zVygj4iQnDv6D5sq4+zaOM3VMQtrh3SnZvWfggCzi7uxsX9etM24OO6gWP5y+ZPOLZzT+5Zv4K7+vVj15bn6Nf/VwSDhYSCRXRQBmD/YRVuZRQjL8io86+lXvURiXj8VAsk15VE3EAzSdn+sxDb3xGNerRtW9RMyvf9NmYc16MGQUjVk7JZw7OZ0WscT29ezaldD6drdjtuPHQKOOlz16WakAKPOKAjd32yhqv7DyFcGcN5eAV2ZRSRF0SfNoz4Sj9a/0Qk3Y0m+k/ZYjPlXEKBvgU5ZBkeWr5KtfRoc1EbuL86KStVZrZh0bYqjs7L5qkhnRORel228pxod7qPMjth152QxBexO+ak1KI+q1cBt6xJjcBfu7KU3485nxp7FzcMuABFKFSaNQQ0P79d81ArOSg0SUeBhgXr5WhozOp9DqZrEXFiaaX25fHqViWWrjpkKhHr+xEZTajpzZ9obf6UwfeHZ0j0KQr2I+8gG9vwecPxDMntq86nIlpKfrCIC4++hbavrkSfMAz7kWcSB39dSqd1X7Bw7DgcKdEUhWynlvjuLXz19m2tpOm9Rt9Ntp5DXTALx/WaNtQmj0cK0E4ch/QknqIQkSqO5aGpCiFcFM/DQyHm69hq0zRqeqjBOFlBf3rPCRy8e59qKmc3dTLxoKB5u1NF69rt7UM6VWbqxlBZxEYRAa4vuZtb+v+Kdz/4HWWVCZL26pp5nDr2kWSe+4atz7Jh67MAnHfsEoSSTTS6f84VwnORdVWoQQ0zXo7pxVnasEFx5lFPEItXMXHojRj+MO1D0Vb3UVMVrlyzjS5hH7Muap/w+wg1lXrzdRLkj5NoWRIlbFN0gol978qmNnn2MKSdjdAUyBFsU+qoMOu5buAJLPjsTS7tfRSVViJtoyiQgytd/vDpk1x2yFnM/XBBctxY8u0yzu5yLA8ecR0SiSIUau16jj9wNPM//wu/7D6ZhUdcC4AiFDzpUWPWgwBNKOzY+jxTOwwhSzVYMORKbDdGlpGHbgZQlCir1t2efP6QKfOWwb6Hn5S4FxcX9wDqSkpKSpu9VgTcVVJScsb3OUdJSclBzf4/qdn/PwaG/HhXm0EG+x/iSoznl81KTjR+v59bhxdQiUOHiQZVL1vkjNZpP9VH5atW63JWU31EdRvNAfuJpjw2d3qYGtMmz9CYd9AByEeaJmDt3KHcuHkb5XGb24b3Is9QqHdc8v0+Tul+MLes/ZjSaIyiYIBrB/fj3OLDuOuTdymN1iG0EJs3P09Z2RqOHHc/Qa8N9sOJcwPIyij2w6sIXDymedWhDDJIonnUzpWSpzevZmqPkcRcm4tWPkFprIYxhcXMm3YSu5oZ0eX8QlCrxykKhgjrBstLt/PbnhLn4RWp7W/RSgqmj6b8zQShrl7Wut+0O91HqV1P2AhiOhoSiYPk0apqRl4YIl9TCQVUntpexelZOQTuS/QtClSc6WG8bIW2JxsohsCzJIQl9ULy50ld+KrW4sFPdgFw7ZAibmog67k+NW1EsTxex/mrr0t5/fkj7+GhYdfjSpev60uTclBIkOVCfx7Pjr0bVais3bWRAW170jW7IxVmDXlGm1Z5oL8beBE+LcDcjx5Ivnb3oMsTtd2/56aXYfm4a9CsVjnuhuX7d5vE/zQU18Z+pEUbfmQF+qVHUhFNzAsV0VIe2DCHK4fdipGfh+jdDW1IH2ReDluDGle++0Yy4n7rwAF0DOa3MoPTgvnUti3EjpgYhkS1FNwG8l6TtB1K/Ksi8KsR/IqNKlXksytxNmxC5IYJTZ1MXTCL3LxQyqap63rUq3EKp/nYuaipvGL7aQbe80uS8n5ZVYu7+FlCM85o9r2Jcm8ta7ffPKwDj32aqvJoH9IpCuby6LDrMFyTgoFXEInvZs1nf6S0Yj2edJLGl40Ih4qw7QgqRkMt7/0HjU7+jaaA3U56CFuRvP/lU4wdOIvc7M4IFGJUAeAXEW4dfgBXr9iRvI9zDz8AT3rceEQHPAkRy8OIwu5/WhSe6aP6LYuCkXHcP63ErYyiXjAC+6/rUtvkEyvRTxqFeXs9okCl48w2zB3wM+7/7A0q4vW08QX5/cbXKArkcEeDOd2pBx9NrRXhjkGXcVWzKPoxHYcD8E7ZOg5v14/yeDVhI4spnccR1HzUWhFu37CYCrM6GY2/ss+5BOwAbTpPbFXGTTcDDeqNTJm3DPZ9/GTEvbi4+EpgLiCLi4uPBd4BLgduAN7/qb43gwz+l+BIO2WBYUv4vOZzhhf2Zpdq40wU5OkCRYOckTpKlqTDDD9SJioDSc3Dq/fQFtSnmMeoC2qZN6cH2+pqkY+sTpmA/Y+9x8xzB/Pr90uYveIz/jCqO7ilXD6gDxcu+z/2zjs+qir9/+/bpmZSSCgRQREhIiBNQglKEVcFVIqrggWxoWIHVNwVsGFBXHdZC4ri6lrXQhEbqIACAgtIUwMogmICacxk6m3n98eESQYG1/2t+LXc9+vly2Hancmce+75nOd5Ps8KyqJJ456yaIx71mxkUrfj2Vyzh0JfgICvMWcPXQBomKYP2QarOr1+TFRHkf+D6Y7D75eGpQ77FIXBspt9eowHNi5MOQ5nu7wE8yI0utaDZEnsNYKUeQxW7t7OtB59qEkkKPT5kS074/gjEifQ3kvVQkHTMcm09ebjPAgTzFqbhM9A11TuWV5BeWQPzfwafy4u5Ixjcpi1sYKPd4d54bRWjD4iD2V6umGd+liI3ddlEfYKGqkq1YpJliZjmTaWLfPX9XtSC2a3Cn/u0YQmXheWMDNGFGNW+ucv9BawTw9T4M5lnx6lwJNLVWJf6rE7O1/D9M3/4Iq2w3lq6xss3bOWQm8Bf+1yHQXxMIpXo7G/kKd6T8YSNi4UqpfcRyRSyaPFlyE8uchGlAIlm4jx489TyxI0poDZPaeNA3nHAAAgAElEQVRiYaGgJIW/U6LyPyFZVmp+3o+ojiJZ6ZHmqmgZVp4fFBntrH6Iihpq9AQTN61Mc5WftP4zZvXsmWYG52vaAaXvnVzxyUcpgf9Aj5NprLixrPSoutAU9ER6z/U2g6ej9uuAWLAqJbozYVk2MV+Cpte6kOxkKzhVimFu2Z7+/WpCKLYNDbI1LMumQKG+d7siCBsJzmvbiG37EvWGdX2O4MutT3Jcy4HUJPahqV4U2cWArhP59POnATiz94MsWHFLSrwNKr4TTXZh/AoF3IGt9Mo++RtHDppG17YjWbf1JQZ0mUBtbC8bvnqdbm1HYpoxmhoyL/ZuhSEJYm4bG5t9CcG4j3ZRHjE4uXkWdx3XnOgWGyusUzgSzMfqN+BxqRnHJJ7k305UWhgz96GOk6mKh3mw+DxcssK1x/clZNSCpHPRsttTr+3btFtqPjJsk+e2L2BN1RYe6n4zmqxwTKA5lrBRJQWf7CYkx7ip/YXUJEK8vONdxhaNwB33YFj2D7Zxc9q8OfwaOJwR97FAO6AFMAG4HigBxpaWlr54GI/r4PC7QZKUtOiAT3FR3KQIU8BNdbWwHRp5mN6lBTWv6CjZEvmDXGnRwxZjXSQymdNZkCVJGS/A+Wpy6kjWuWs8tWYi40peSon29nm5XHRcG7JdLgo8Lvo2a8Xl7brhkwSxxH4jsmRKpdTIl3YMqZEPW5bAEe8Oh0BCQrU8uBSbRi4/LllN1blbQuBX3Yxd/mzKffi+E89BAINadMJGIt/l5YGeJ2PYEkqG8UdtAtXvQckCIyRRMadBlsqlbkQO3Pphetr6PavLmNCtGVed0Jgr2jeiRUhG0sl4bnmRuHjVTiApvv/evyWvbP+WEccWckOXRmS7NEK6wV/Wb2NLdS0vnd6JqF3FPb2b8ecV5WkiRFNr0mrP7+4yjizVi8/yorhs9FiQJ4tvxZZkFFlFQjCp/cV4ExFuaXsuN7Y+E5fipfL9O6jasxmADhfNJ2Jko5KM2B3Z/Uq2vz2ePQtuqjcGM9z8NyJGUSRcShSXZQAauuWI9p8ESco4hyKlN9/J9xWieXwYf3splXJuXj8yo6t8wojT6pTJ7PjgLvTaMrJ73sj16z9LE/i3rlrGEyUDcSMTiIax5ryJWRNCGjuYbStvTe8B/85Eju53G9rZJ6DM21gnujNjWTbh/X3ZLchRRH1Hif3fLy8bW5Y50B6hYe92y6vz2NZnGXn0cB7pV4gtoCpRRY4rSEHrYQB8uWsRRzbuhM/dCLcWYGDX21i87n66tDmPc/o+RixRQ8DbFJfqIRrVfp3jVRgHOPlvRlgG67a+RL/ONyOEQFN8DOx6GyAjVXqp/IeMWRNPuvpf5qYmW3D78u9S892y3WG+PUZHzZNI7LSxa0X6OiGqZxyTUkDGfbsfEQZzYYIifzNm9r6Q57YuZ1DL47ly5WQKvQU83utPaXPalUUjeGXHe6yvLuWSY89iSMu+nHJEDwzL4pt4GS39hXgkFZ+wWbRmKh2KLqTA14w8zc/VrQbSVM0modeL82TWxP7MifTf9D897uDwf83hFO6R0tLSb4Fvi4qKTgJWAu1KS0v3HcZjOhwm8nI0VNeP65bduHEAU49TE/x1ua/+GlEkF2eVTGf+8om0aNKD6oSLyphFy0C9Uc/m6jiPfbWX68c0hVqREu1QZ05nZzbVUmSJxj4PRoYLcKzuYtbM50YInapoGQqCkwubcm6bVvhVzwGt4ErIl5Ku1y4PCHQkScGQvLgv743ZMBX/8t7UZmr46OAAqEq9UMjK9tP08rOo1sP8ZdN75HuymNLlbIJ6jJs6nsZz25YDELMMXv5qFecdcxL3rksacb0x8EzcCQvp0l4Yz6ysr8UcdSLG0m2IPl3IO9vFnsfTz5fyZxI0ulbNmLbuVSVqdZNWkoYxcx/ayOyM55YhwxPdW9DEpRLwKTy7rZrTjiokYdk88tl2yqMJOjQKcG3rVjRu5yLPVpm89U0qEjWM734xLX0tIPQtwUXX0GLwDGb3noIpLBRJxm3L+KJxJE8Ql2kTD+9h9+qniOzZjL9pB1r0vo6vF0+tj4ae8SDl6+cQrRPtrkAhNKjpbJjhgDBA0v5rM0dFkZCt3ax5bzyxcBnerEK6DJwByq+rzdIvEaEoaBd0x3hhTf0YvqA7QlHI9xXW17j3mIE7loARvWHRBsTOMtSKGgp9/jTxXujzQ6yG7z59lKP73YYnuwXVSg5l0c/TjlsWjWAh8GNjzXmzPpXdo2TsuS5rXrYt+hPtznoYS0tghcrwuzIbg6ZF8JGRr/wj1pP/QmT7CQ/qj9GkAFmW0DAPaV7q0t2MbTvigNKMm1ix7hG+2r2E1s370qv9FcxfPrE+LbrPDKLxajTFw77wt/g9+QgrG0+Wn9raX25LwB9E0g5qpYdl0vP4y/jXkqtS3/304jtp4jqe8n+QNt/teTpB4+vcB813D2wp4y+XtqTimQRmFOQG6wRj8ZcHj8nLeqMv+AyxqaxujPbCcAmmrptLVTxMn8IWKc+Nr/d9x20dL6WlvxkK4LFNzmhewuKyVUz498PJHuvdbsAjbJpkNUdLJMeQrkj0bj/2oFR3M/HfbTI6OPySOZzCveFeaBA4r7S0NHPzS4dfPKrLw+qZ3X7084uvWws4wv1wowqB15XLwG6T8GV35ZH1ldzSoRDNlHii5ChmfrEHCbi0SQHB93QKhhzsLG/rAtelOejPNOgDfGkOdsSGqJ1xUYicdJa/r3c7Nn//Kvm+QiyrikuPb0t13ODe1V+kXOfLowluW/4lj57cGitRwbw6I71sfyFn9X4QO68A9w39kC2BLUvUSvWuxQ4OB+LHqhcKNSEkBLet+Rf5niyuaTeA61e+QIE7ixtan8EjHUcjK3DX568zuGW3lGgHiAajmLPXQtvGuK45GRFJQG0CY+k21DM6YGS7CYatzC7XVmYjrJgpKPTLxGpNsiotzLfDB51b1jU5NJMlmj5em7pv5NgcHtxawfWdG3N/7yLmbPmOm45sTex5m1iNjZFncNeYcYTzgghbp+LdcUT3bE721jZiFBg+pIogBHwkvHF0vYqv364X58cMnMq3K2bSvPiKlGiH/dHQWzi6321UfTE/5fJt4KehaeB+M8f/3yiUS4mmRDtALFzG+sXj6T7oGWK/sprhXyLCraKd2xVcKugmwq0iAbeUzMYi2dpz77K/sPHrpcnf+Ox7UeZBYOHHTL9oEBNXf1zvKt+lJ03dMk16/QmpNo6YtwzttF4ZBb5bklBtC71hNDyiZ+y5bsZD6LVliDwPX755WWpsHjtoBrpav4HTcGPObGBGx40X8a0hc+vy3ZSv3VHfp10hTbwrioSsRRHCoJkS4OneUwjG9pDjbcyKtffz1e4lAHRodWZKtAP43QUkwjZndnscRZXBH8M0XOj6r/talMnJX3ZnseDDG9K+O7oPWfFg1qQv080agWIfPN9VJiwSeRZHXOPBjttol5ZgPFPntRCKIzQ32nkngyqQshX0+esRm5LHE9VRjBdWYt1wElXxMNOLzyVH03i46zVkq14CuS0IhnawbOVtlFdtojC/I0N6P8iD7S9AVr0YepC1/76baLyS8/vPJpEh1V2WLWxbcVLdHX5z/Fyu8iFHtDs4/PTYVoJvPptN0w7nABLjjmrKphd1YkGBN0diyllHEhEmsWdNzBqBXnyws7wVBntxJBkd9EuIiMBYFEHt40MK2BgLNqEN7ww+F0R1jAWbOGp0Dx456VjW7HyGoibd6FD4EELOZtLyf3NH965preIgKd5tNN76pN5ILxQpY/6KWzin72MIt0oi6nLS4x3+I7JtY+4XCkcVYgibsliQmzqext3r51PgzmLqMeexY57CyqCON0fiurMGE/XG0oSHT5KTi8xPd6KX16INPA58LrQRXTBkN3HTJkLmTgx7jSD39zmCZzZXcf6RjWjs0sjyyFQpOvf8ey03tGpHmwIF+ysD4/Vkj20pW8bOkylP6DT7S7qnhHdWiFFX52HEq6lccTt3lPydisfs9P7IcyyOuDaLHSv+nBLtbc54EEsPI7kV+HQD9DwW3QqlOYLrtWV8vXgqxw2fhbCMjNFQT97RtBvxNEashu9Wz6J58VgU9aeMhhsp0b6f5L+dNkv/K5JhYby2Pjl+XYBpY762Htfonmx9fghtz/zrQeNh25I/0e7UafD6ClrtizK7Rz8MRUYzLXIjCaRgFOHNxnr9Q6gJEVixkelD+6YJ/Ok9TiJr4ceIjm3TUtnFog20GTaNbR/enhKKrU6ZzHcrH8UVKCS+b1eylWPTjjTvfCNSPJusgIuYy8JrGai2gQiFoa5tnagJYc55k/CNl3Brg3Tt/X3aH+vXAsVKWpkqioTBbuYtSY+4NvPkY1mJlGgH8LhyUteiwkYdGXjcw3w531t37bTpPCKA5Uq/jv0ayZQxo9t6xu/uG5B5vrOBf/ZqxY5Igr+W7qEyYTGtpDlGGL6fFa9zlXeRP6If7ibAXhvjn/Xt39x/9qdE+35EdRSXkLjzhBKy5QTCiGBFy1i55UkGdp2EJatE40ljwUi8Et2oJd+dw7zlExr8tg8hiWwO3GS0nI4xDr9hDqdwb1JUVHRzhtsAlJaWPnwYj+3g8LtAllSqv19DeN/XdOr/NGsXJEU7QCwo+Gq+Qa/zPeyq20UPbzFpNsZN+ZwESgAK/qDhKpBgZADjpVrs9YlUxN14vRZ1sAtCcfTZK1LHlBr52BP7hmkfXwxAn1ZnsS9WgSlplEVjhHQ9Y593TZbwuwsY3P5O/Go+EbOKJdtnEkvUkOV1kVx1Ojj8MLYsp4SCdGonFEmi0JtDjualLBbkjuOGs2O+knYe7Jiv0G5kVlrUsNJMkF+X3im+qUafvSKZUXJ1fype0rFqoXCsi/hoQegf9e70gdEQyYICcw+TWx3J3mcMYjUGRp5E9sUyEvC3HV/w2HU9sGbuw/7KwPwkinxegEjCoqXbhZEjp6XPi0qL5h6NfdFygns3YUX3YdbkpX1vs0ZgxRM0bncmhV0uwDZiWFaCL1+/PCniB9yLonqRpczi3AhXoHpyMkZD4zXfsHXBDan7YpVbaTvsmboo+0+BhjerME28e7MKAafN0v+MImeco5FlAGTNm3E8iIAH15hh2PE4gTVb0LoeD7URRDiKuXozar/uKCPPQM7NRuytpsWi1TzVqQNmlhc1bpBXE0Xqcjzmui2oIwdhvvR28pwMRXBLjWk34BFEQCMe/JbvVj6KEa2izaCH+GbJffibduTobjOoeMFbd16ZNBvjQrz/DvqWpPu8et4ZmO8sQ+wsQ9SE0G2RsTxFIFAUCcsSyFo0JdohuTk8b/nNnNd/NpIkk+0vxO8poLjdaPyegpQ/TO+im/hygTdtzvjsdZ1uo1zE9tfb/4ppmDGjKBKaCsNP/hua6iWgHsOGl9zEgoJtnxp0GOWm6sUGnh5XupCqDSQEx+gyf+vUgiqvhSoL8iyV2prkb5LYJaj6QKLx6RquJhLqWRrm/DAiaCNlqRlr3oUi0dJ9BMvWP8RXu5emUvYtW+fjjTPp32U8HlcOcT3I+2vuZmjJQ5zffza2sJAlBUlkE4//ujMiHBz+Ww6ncF8EdMxwG5wtMAeHnwTN9tD11IdYt2gCVixELJjeWikWFMn+pXW76Fnt1WRbuJEu3JpA/3sNibp0XfXaHELnSvhkN8bLkaTgWCjQRvbCeKm+Bti4pAOmP0yrvI6EEpXIksrczx/llLbjKPR5ef7LbdzevT3T1myvr3Hv3Ra/ZDC8zXSk2d8hqsrx5LsZfvl0Ku1dCGGlFl8ODj9EBIXAmGHJdHm/C822mNzlbGKmQaE3h0ZaFlXB9HEUCwqEBff16MOkVZ9QFo3wYtlX3HNFb6ynGvQaHlWM8eYump1xJOXvyOydpZN3nUreOA3FllA0qEpsJZ887Lgr1W4OksI6/JzNuIuO564v1hMusFFuzcUtS6hhgfFQDe5KC71AwXVZDsZrtdhfJRe9UoGC3yvz5cd/S76XGULNa3RQ5CsR3sX29yak7jtu+JNAgyjqkMeww7GM4tyI1aD5G3PMqXfy9aIpDWrcp/PN0vvT/l56bVkyOvcTRcN1y0eXgTNYvzi9xl23fn0u3b80bFVDu6w3xtMr0uqJbVXD37QDZjyUcTzIvixsVxYgDhbtJ3XDXLIGtVcn7FgcuSAPV3FHGoWjmO+tSj6+cAmEIqhDB2AuXIo2biSYFkhg10bQhBu7ysJLAa17/QkpOwdbVjGiVRzd+56UaIc674g5OkcMLUZs2Z6Msr/yDurQARhz5iLlZeMyM3dVMGq2EfC40NXmiAO6rEBSvNvC5Ns96xhx8kwi8WreXT0Fv6eA04vv5N3VU/BqBSnRvp9YUID47ZmtuDwGkUQ1i9feRyhSxsV9FxILJjfNg2U2mz/WafNHF4HGSasLuSKO+exW7KoEUr4bZXRbErZCrseFUWGn9XFvdrqK+XQN8f0ld+NyEXEbfWEsWdP+Qv06Qr2iNxE5iCbJdGo9ghOLLsQwY3jduYAgEq9k3if1c122vxDTEujxrAbfxhHtDr8/DptwLy0tHXO43tvBwSGJbUv43c3pOeRJhO3FmyPSFiDeHAkhiVQfasUnEd1ik9vdRn8+vU2V+fcgZeNi/HXXIqYP/iO+bxXsr0yM9xTUcSdTa1ZTpe/h9R2TCeqVjOw0CZfiIW4kI5hrdr7MA73u4NaVa3li8xYmdjuOI/1ewonvaeox8cSzMGd/jqhKRuJFVQJp9ncErm1MKFZOtvfX1yPX4efHtGxqfVn4x41C0nS8epB8d4CgHueB4nMJh2N4czwHnQdel8rTXyzghhO6kePyEdSjPFH1b665oR/U6FBrYswtQ+yIYH0XJf/c4/n+WYtgROeGjZ/yQK+uNDEr2Dj/Inqd/Rw+17GYNWb6Z6sRHBcI8LduLanSbW799DumHt+MNo9H0841/ekg2kXZ6H+pQSpQiI3NxnKZtO40mu9KF6Dleml2qUr5M2Z95GuMzPelC1LH2l83vB+9tgyhW7hcjTn2jAfY/s6taanK5Rte5uieN+JS8mk37ClENIYUN8GfixGtSvseBxrU/RCKIqNrAguBgoTLkA4yDLMsAUpzug96hmR6vIb+XxrcOWRGNiz0hXvQhhWDX4GIhbFwD65zfTTvdwu136zkmIFT0w0JB0xDUQNgW0hIGI+/knKaV887A/PjtajFHaBZAVIojDHr1dTj2iVnYyxfj9iZFMiSzwuhCKK8EnPRCrTzB2H+/aWDPqdy+5VEZJU2Z81ENZtSmcE7Ap8/9W9RE0LyeVOfyb/4Ex4o6cmt66vq+7Sf6Cf08T1URytpO+wZdEnL2INdlhSyfPkIZMK2Qt8ef0HXa/j8m7cZ2G0SWf78jNdOpN/W+NRcMhEhE7Rc9OoymQ1fPEZE34M3Jyf13YNlNls+1Ol0gQuvbmHO2Zp2zbb+sZWWN3egImZhvm+l1hb5A1TMp9PXFPqjSYNO8YVB5A8+PDf1RZg2KDIVcohwqJQsb1Nys45EN2P4PI1Q5eQmwqCe9/D2p39OK3mwfoXt+BwcfmoOe417UVGRH5gOnEEyL+594MbS0tLQD77QwcHhPxJGISCDhIYw9tDpnCPZ8Fp9jXunEW6+ixp4lwkKhrpQsiXUPAnVK2FmaFOVr/rZtG8397vf4e7bhyIZJqgwY+M4vt63Ke35Bb7m/GPdVEKJSm7u8xSxeBV+LcbtnbPxao2IGTt4Ye2jfLNvE/cMXAC2L7UASB2zKkGWVsDC9ZMZ1GMaTr2rw4/BtGwiioJPQNC2cckqTX3ZxE2DgnwPLUdobHzdSJ0HbYdCXIsz6tieBI0YMz9/h801uwG4qrAEc/qXae8vqhKovqRgzvVpPN63F98un0x22yF4swoRtkEk/BVq3tEHRcVjoe24G7fghiXfUx4xyFfTXeWhbqOsqULNnblUmRYvfl/BFa4Kdq2cQddTH2LvuueQkGl+zQ2Y0QhGfA+7NvyTZp3PJ1a9HSNaxbFnPACSRNHZj4EkIysakktB+TyE3PVojhv6OEa0CiNWQ/mGlzmy0xjEC0thZxnkZaNdP4q4UsZ3S+5Pa/2Vavf2I6LhiiJTISW4dfmyjP29G2JZos6Izmmz9JNiCcSGGvQNNen3n3M06z+4le5nPIpiCI4fOhthG0goyNU6WDaUV2K8vqi+Pr1BpJtGOUgAQiSj6h+uQuwsw3h2Hup5p2Os3pwsWUnoaGOGYbz+fjKtfW/Vodu3AcLUidd+k/HcoYEHhZSXDXnZqONGYr75AWzZTovySmaNHko0VgXxamo/vofonrrrkjCwjRzOLnk4zVX8rN4PEtdD5Ge3ptxQuX3DZ6mxelfXC1mx4U7+0K0JnUcczWevm6k5o/MIF7r49de470dRZPaKOLd8/HGD7z+F0h0v0OXMa1KlAt4ciROGK9y/qYypbQsyXrMty2JPwiY3JFH1tk7BUBfuJplbX4ojZbaOi/HXr+cz4YQz8HvczNy8iJvb92fzjgWc3Ol63lk1hUi8krP7zGDZhr8RjVdz0gnjkv432GiKFzOR5Wz0OTjw85jT/QVQgGF1/78GmAmM/hmO7eDwm8e2whjRCr569zZanvcyHUYpyEJlV7SWSo/gwdV7uXtAcyr/mezj3mSkG0u3M7apqjIjFHpzuKB1V/6ycSy1iUquLH6QgKdR2jHzfYWUh3ewoya5aIrGq3h10WjGDJ7Lm5vupCpalvZcGQ0h20j57tRCQGqVhTb4SCQhc0qbm1FlL+nxSweHQ+NTBDstnQnrF6b6td/R5Sw+/P5zBhxxPM1GCJq4cpAUqJFqueGTf6Y977EvPqQqHsaqG5dka2inNQefCrqFIUv4L4YaJUKBFaNi5xKMWCUdT56My5PDxk/vpOMFM6hK1elKNLtUQ+Q2oUbUt4urMi0aZTjXdsR0Llu1Kxk5LM6h/NO/EQuXsW7RBDr1vg1Mgy/eGpWW4hyt/JJ2w59EWCY7lz9CcMfSlGv8rk/+kqoj/m7JfZjRKgq7XYLqyaZph+GohjsVJRU1ISxibKtzmjajVbQ8aTyaNw8tqxlR88ctknVNpEQ7pPf3Vqz/8GKHnwShSkid8tB6NUmO3aiJsXIvQpGIhcvQ4zX4vM1QYgpUR5DcLoRugWEiNWmUJrAhOTZolIMkwHj0pfRIfF3NuZQTSEbfxwzDDNRFyUPJMWB+uCr53FfeqY/SjxmGqch4iVI6fzyar4CjL2hY4y7V1bivBpKiXRkzjGDdEjVwWgnW93sRO8vI3rOL3Q36xEN9hohlCby+AgZ2m4SmeonrQT7b/hqdjj2HhOTj1lUfpY3Vyes2Mq3TjXjcASTNotsoLZkeLwl0kThkq7lfE6oi4xcysg17ag3y3R7KopHU97+/81Aiyh66XNgaYdrUxr+l1p3Lst1hvjsqlyMbXLMBpHw3ZbrFY9squPeiI4k8b1A+J0Hzy10Z1xSfR8u4fOOzFHpz2BMP0ZRsLi86idLtL1N83GgisQr6db4JvyuHqjXP0aPDBby1ZgqvfnRVKtIumY0d0e7gUMfPIdx7lJaWdtr/j6KioiuALT/DcR0cfvP4sbAlgebJQa8tI2rp3LHpDSZ3HsGVq9/lgR4DqExY3LF9N9dc1IRGqkK5qnOET0O7Lg99Zk2qJZVyXYAm+TJ3ekt4Z8u9fFMnyt/+cjbnnjCRP7QdTW2impU7FzDouMt5ecODQFKYR2IVZPsLcUkurux8J09+NiXVP/iann9BMnzEXTrKZc2Qny5PiqShLTGe+wpRlSA33416lQvTLzmt4Bx+FLWKyYRVr1IWCwJQFgty9/r53NTxNMJmnBBxInaUXM3PjStfOOh5t54wmAJPFrWagevqo8mKKKnxKOW70a4qIuqvIBcPsiTjzSpk397NbP33o3QeMI1ErJJNm8bTdtSNuFwFmGYIKzuPRHgPWlabVD3u37+q4P6xhXhnhVLnmnZtgDx/Ja8NPhpVGPiJoOe2Irh3E7FwGe7cltiR6symYsLmy3nXHOQa3/Kk8Wx/ewLb3p6Qur397foa0RPOfCF1W8rLxhZm6j0iezanntvhovlYlkjrpW3LMhGUg85NC5Hm1A/1/b2Vn+JHdviPxNwC76AjMZ7cWj92r2ybvD+rED1eg8fbGMI6Zl10XcrLRh05CJEbSIuOS0cVop7aG8ntRuytSnd2r4vEm3M/BE1FGjeKIAqmbidbuI0ZhvXectTiDkgeF9q4kcmcivJKjNffh1AE6doh6LVl6LVlfLN2PM3PvxHVXYAru4CYbOAdNhDl7AHYskxtg/G2vzRGsW1sTTmovVnDDBHLivPGsuvT/kZVoa/p32tmxrGanXUUAoNE3ITf2NaxsAWBsMCc9QVWVYJW+W4evLSYW1jN5poqyqIRfP4WXLvy2dSm5owThxFwBWjmD/Hgl5VMv+xY3E9vT40t9aq2xH1xbu/ZFFM2yR0nk9ANJJ9AuS4Hc2Z968v41R7+umt+arP0la9WMeGEM/DYUZq0Hs47q+4gEq9kSPc72f3eVCJ7NuOv/pqhPSfhyjsacDnt3BwcDuDnEO5qUVGRXFpauv+KL5Pe493BweH/E9m2EZKMriq0OvdpLFmmKh7mm3AlhT4/z2/dwO3FvZi2uoJr6qJ79/VpTkiL4G1s4749gG3YVCS+48WvJjLMfz1PrBybev9WeR0Z0HokD39yRUqIX9VjBuWhneyo2US+r5BLukxhS+lLnF3yMLYVoKmvFRNLZmNjoaAR8OZTXR0D3YXRKIR+hUK+/2iMR7al1c6ZT2zFf3M7go7hjMOPQEekxPh+ymJBGrn8GLbFjateBGBWyeiMzzsqK5/FpX+nU/MzyJWa436uPG08Gk+U0vSmY1ANEzwuug2cwdrF49m3dzPx8F5O6DuVjUunsqxwv7IAACAASURBVPqjy2hyVF+O7XkDOjqSJ5vQ1wu4v+RMbltexubqOA96K5g8qSlKPIzsdrFj1wvkaSewafHVDczaHiCy72sS0SrksInqKchoKiZJckZBr3qyU7c1b7ojvStQiJSwEEcVIp3eFdEkB2SFnFZ9Ce5YmvY8JC1jL+3AmGHU+rLSxLuClLG/t4KEkwr/86DpIiXaoW7sPrkVbUI7Op48mW82v0yHnrdgvrQgPSX+pbfRrj4vFR0n2486uG+9O3wGZ3cpy1cXPVcI6oKG5mAi4Ec7rQRjzptpmwPmohX19fB7g6kxHdmzia3vXYYrUJisT9e96EiAUrdCrH9v07IJ1j2mWBKKN4+jRzyBIimowkXMcKfEnZShzj0Sr0SRRMaxGovtIcubf1h+m/9zag3MWeljw//MN1x/+QlcWfMRhT4/30aqU/NjvieLoGUza/M8JhX/gftWVzNxexU3XXEsx/g1dsWryGlkcdHiRw861JsDryO3iYKrbk0RFSH0gMkNuX+gWo/wyleruLyoD1+UPkubI/uS42vOGV1vR3MH2PX2JCJ7NgPJTcTIvBvocNF8IoYXZx5xcEjn5xDuHwCvFBUVPVH376uAJT/DcR0cfvMITSFoVDO3rj/6Oae9wf3dz+WZ0mVM6zGQ21d9wuOfr2TCiV1p7g9QlQjSyGNg2wZ7a7fz3o5XGNjmQp79YjJV0TISZox8X2Eq1f20tqN5bn196ntVtIwnVo1nfJ/Z3DNwAYqsoAiJJp0nYRs+bEughWuRn5uBqKlAymuMNHoCqicf0xIoFODJ9yEl5Iy1c7Kj2R1+JAoyhd6cNFHet2lbCjwBJEg9FjRiBz2v0JuDEAYrd82lrPYrbmr/KKJqZ9r7i6oEbqFhCwPrby/iv3w4PU97goQZxO1vjKlHaF9yGy5vIxKy4NWl16TqagedOIUcpZrHTsrDlr1oMghqMJQYtm0RaNSabza/TLte49Hc2RiJENvXPc2xXa7A4y1AenE5Amgz/D62fTCpgQP8Q1CrZxT0+43qXIFCNF+96HcFCmkzeAaSpznmSDWVHu8KFNJm0HSAVMr9/shlFlbStb+B0LPmvEn2uJGEFDUl3l2GxAM9TubWVek17i5DwnIW3D8LsgVmhrlUseCbzS/TtsuVaJYbI1NKvGVjvrMMdegApOZNU6nx+x8/0Nkdrwfh1ohY9Rsz+zd5pFD44Hr5l95OvR5AvLuONiNnpI3BH+unAPV92l87oE+7RvPUc2zDx4iT/04wshtN9WKYMXL8zVFFlHu6deXPa9elxurdXTuT5xbYv1HTM2GKjNfZAtWdPFd7nsT9G95MPXZxmxLuWj+PsliQHJeXGX0HoKCiyrBdr2bSF68xs/eFGedTVZL4+6rrOafDjeRmNUEIG1sP4bMMCgJNOa79ADCqcTU9EUXWWLzuPkraX4kPd0ZzTOlHmmM6OPze+DmE+83AHcA0ktH294C7f4bjOjj85kkoMeYuG5+KLtRGdvNhTZgbO/wBw7aY2ac/1YkI1YkgMz//kPNb96BWl/GpCprmZ0P5UkKJav7YcTx+Vw62bTG2+CFmrZ5AVbSMgLtRWr16q7yOnNZ2NJYwUXBDwoeeSmMT5Cg6Vp1oBxA1FRj/eAj/2KkEcWFZAsvyJntxZ6ids2WcDi8OPwpNV5lefB4TV79CWSxI36ZtuayoL1cv/wf5niwmdzmbu9bP47lty1O3G9a4m7bOVT0ewu/KwZJ0lEzjER1JqxMhs99AXH8mK16/mNwmHejU/75k33RvLvM+uiKtd/Tb/76TP540k6+X3kxR9+vYuHRqWmTdGziSozucz6Zld6Xu73jyZHw5LcEwEGd0RXpnHcobn9Hu1GmIgAfZ60fel6ybbzNgGts+vD0lfo4ZOJVvV8xMtXdTayXaFU9D+FxICQvZdQSGHU0JJqhrIff2RI4bPhu7z3iQNOJ1Tu+yZGNmEHpSsJaApqUi75Zl01hx80TJwB90lXc4jKhSxrkUVaJ9i0uQ3/ocaUiTjIZxIliL2FmGOfdDtLF/zFjv3tDZ3Vi4DHn4wLSsC3/dJo82avAhX586ZiiC5j6CtsOeQZEsLKGkxtyP4VB92s/tN+cHO5JIgGxbbPvyER7oPAafrxBVAjP2HS61BQn9tyfaAaRDjI08n8a0TkeR71KoSoRTj+VoXspiQTrkNef0Fh254dOnU3Pm1K5Due/Ec5i7Yy0PFJ/LratfTT32YPG5eLC4pOtUZElGRiYa3YvXk4tP9ZGo3o6W3ZSYlcCydT5cN52yqk1U7NvKqP5zDprP2gyYhuIY1To4ZOSwC/fS0lITmFL3HwBFRUWnkuzt7uDg8D9g2el9azd88SSnd7+PyniYiJng6EABOS4NWfIy+KhOPPrFB1TFwzza63zcmp98XyE7ajbxxKpkfWu+r5BLu93D+D6zqdWryXLlpiLwrfI6MvT4cakIfL6vkKuKHyZLaZ5aeMm2hVkn2vcjaipQ7PTqmIhkExjbNpXGJ+W7Uce2pVZyFvwOmTm45hoa29nM7nMpCdtAkWSuWv4PymJBymJBHv3iA249YTBHBfKpjIX5U+cz0WSFoBHjla9WcWP7/vxr0wyqomV0btaPy6+aivVEfS2nfOkRRMxdaL58pMtPh0UbkG0pVeu+ff1THHX8H9H12oy9ow0jwrFdrkiJdoBYuIz1i2+lx+BZrHv/prT7Ny27i+6nz2TZa+fgzSqk6/BpuN/YAK+vQBs5CGHLWAs/RjurP8qbG2g3+CFEIy96tBIhbFr2uQnNm48ad2O98V69ER0g3X4lqEbGFHvbtogY2XX3JM9jW5YzC71wFGvuh/jHjapLXQbLslEs6mrahRNp/5kJuXQ8V7RCeWpHauxaV7Qi4tLxz34XAYihp6BeOATzn2/Vp7FfMARzwUfJ26MGI0KRjL852f5kbfvHa1FPKyEkFFQlKdhlCWQhYNRg8Hszvz7Lh2vcSERCR+TnUmvJmJaXxo0DVFTU8t9Eug/Vp10Ig/3dClR3gn3hqlSf8mx/IacX30lBoDUl7a9k7vLxadF6M+H+rz7Dr4qAhnrAdda6tCmLPp9K17ajsPUq7ut2FpPWzqcsFiRmGhR6c7i4TQl3r5+f5gsydd1cpnQdyrBW3fApLp7scwmmbWMLg9U7XkZr0oM3l1xDtr+Qgd0m4fcW4FEDKJaNmtUUU1Z46YNL0z5eKFKGZRu439yQ3KD0uZCiOuLNDcgXtATHKcPB4SAOm3AvKirqRtI9vgoYU1paWllUVNQS+CtwOk7fJweH/xlFTq/nK6/aRKGmUmHU4HHnUhmv5fJP5hz0uoQexi2ZXNr1Lp5ZNzklxEd3vRNF1nhl44MMaD2SLeUrubJ4Ok+unpg5bX71zYzvPQfqoh22rCDlNU5F3AGkvMbYspLmbGFaNrVZMv6b2yHbYMtQK9mOMZ1DRn6o5jo3DoZmU4OUlr65uWY3N656kVdOHo1HUZm8bkEqQjS9+Fzmb34wNZY/K1/CbKZy0U2TSCRi+DwBEqKKdYv+lIqIdxs5HZ/kptsp01n7wUR2b52PEQ9SVDIxY+9olzsbVctKifP9xMJlCETG+w09nLq97pPb6XXJbDTLi70vhDV3cdK52+9DCkUQj82Howpxn9opGZH356BYbsy3P0yJdmjQikvSMqbYZ+rXHkFJmo01rFfeX+9cE0KxbZxF9S+DuDCZuPMNbrhiAAWKj0oryl93vs7djYfjp048V9ZgvvMx6ohTkZokO4QIVUEbOQgkCaEqIEAdNRjzxYX1v/mowQiXhpQTQB12CqH9Lu/RMNbaz7FPOg5LmEh5CnLUQLtkKMazcxu4yQ/FeGspYsv25PuNGZZsCvz/Sab69Wx/elq1EDrvrp6SFpV/d/UUzus/G5UjObffHIQwkCTtd2F8ZmeD6+Z2CCHQiRGW9tLePYSPN84kEq9keP9Z3HlCCZrqBzvKvd3OwkbN6AtS4PbhlQwMPcTynfNY9NXzKd+bZWvuS7bfK5mOboTxqFnI8TBfzr8WvbaMo4ZMz/jbKZKanM9mvwvUbTTun7McNywHh4M4nBH3x4BXgZbAn4uKilYATwMrgE4/9EIHB4cfh9fyMrTkYeY26Ftr2wne/OAimuV3pG+P+zPWo+l6De5AcxpLOYwveQIbCRubmmg5r2yczo6aTXwX2sofO45n6df/4tpeM1FlLS1tHpLi3aY+2hHBTeDi8al0eSmvMdroCQQ5OKqRNByqE+qOXnf4Afw/UHMtbIEZC1Gjl2cc6/F4BX4Z7j2+O3k5bdCtKLmawobyJWnH+Kx8Cae0uYAZq68g31fI1e0npUXE134wkZ497sb98Qf0OnsWliyh2DLS2m8Z2nsGc1eMT6tx3/7pXzmu+Aa8WYVpIt2bVYiEnPH+RKwy9e9YuAy7NoSNhJybjXzBmYi9VRgfflrfbmtnGbweQTvvDMz3l8Ogk1D7dcf8fm+9+BozjBAKwvL9oBt3Q0zLptaXRfa4kUjBWkQ4Wt8KzFlU/6JQgMpEmMs3PJ+6r9CbgwL1BnELlyZd3bN8GItXIlZvxjVuJMaLC1Gv/COSAAwTWwL1vNORFAURjWEuWYPa90SELRABP6Zpk6MIrPeXYw4+nm3zr0hLb3a7mqGOG5nMxbAFYl8IwkkzOFETwpzzZlq2xn+LbfgO6tN+dsnDaTXqQliHiMpbqVKt+rjRb1e0q4qMKK9APP0Gek2IxPihPPXx+Qc9zxZ2miHt0XkduaDbgxnn0j212zg6uyWf711Fv9bn0rl5fwKuPDyyi76drsfvKeCdVZOJxCsZ2mkS7pxWtBn8MNsW3kzlmn8w5OQ7eWvNlLTfzrKz8BywSaiMGUYtCs7CwMHhYA6ncM8pLS2dUVRUpABbgXOBK0pLS18+jMd0cPhdIRkmuWoew7vdheJvhIIMskq2v5Dyqk0sXXUb93b9M39aV9/r+t4ug2ji0nhr5SQi8UoGdpuEL6s5Uz4Ykfbe+2vcV+yaR2nlam4qmZVmXAf1Pdr3X15NS1DrLcA/diqKbSUj8Ll5mFXpbXgcHP4bZPvQNddSwI/kdrO99HXu7Xr1QWM9Vzb4aN2DlFVtonXzvnTrOJbdtd9lHMsRPblQrYqWIWnpSWGxcBkivzFi4CCkvWVoTVsTsV34OxbRSBKM6j8HUyTANkGP0fK44UiSQteBD7Fu8YT6yP0p03FF1VTkfv/9J/SdSumamanjebMKkT0+rBfexwpF0K4+H2PRCqRTO2H4dOSrhqDGFSS3G+Olhcla5e/3olwwOGk2luWDgJ+w5sbUkypbV5vTdtgzIIy0mvZMmJZNSFEJaBrW3A+dRfUvFLdkcleXQUxe/3Zq3N/VZRBuyUS7diRCltHO6o8IRzHeXJzafCEvG+n6C5FqIxhP/ivNCd54awmEIsn0+vkfJW+PGwlIyLaN1fNYtr0zId0v4cPbadf3YTQzJ91Z/gBn+v8lW8OyBJrS/Aej5hKuzFF5XP/DX/nXhx8L4+k3UpudspAP+ru0bt4XWZLS5sJvajbx1uYHmF48gYkN6tindjmdT7c/iXbUEF7dPJ2OzUoQehgblbfWTScSr6R/l/Gp9m5ZrnwMORdDyUnNOZLi4bx+c7Ab/Ha6bmM3bPd3QCtABweHdA6ncI8ClJaWWkVFRR5gUGlp6WeH8XgODr8/ZBlb6Hz9+pWpu4oueJWzSqYzf/lEyqs24f/icZ4suR3TtpGxsWLluNUjyM8+hq7tRhPIPgoh7IxCppHaiGkDFwAaiuXnquKHeWL1zWk17tIBjrymJQjuXyRZ0FiWf6Y/hsNvlR+quTY/XI10fh+6tR3F2i8e58FOF+P3FeKSVTwYfLjuAcqqNpHtL+TEogvJdTcmS8thbPF0Zq2emBrLF3eZwtzPk22O8n2FCCNGTpMOHNl5NIonB2HE0KMVbH3j8jpH9hkItTlBSwIkcoQHbe4n2D2PRfhduCPZyItX4+7XnV6nP4UtmUiyglwdxZz3Hu6An57nPEmitgxhm8iKh0Sdu7I3q5CuJffCCx/V16prMtawTgeZOLlD2fXPqQkhZweQ8nIwRDLlfb9oh6TwifyHiGOalwCCaCCAx1lU/2KRJZkcxUylOxtmhBzFRJZkTCEh2wI0DfOAzZcgKn7LSolsaNAm7przEVX7MOc3GH92vf+BCHgy+iWQ7cF47ID3O8CZ/n/N1vhPUXPrEFF56zfqHH8oDtzs9HkaMbTrfcxdNyn1d+nf+WY+Wv8wl3SZwrN1ZXCdmvXlnI43gW3yRO9R7EvUEE5U8un2JxnQ+nzmfv4o+b5CVFlFEfBhnWg/u88MfK5cRvafXd+iL56cJ1JzjrH/06T/dg3b/R3YCtDBwSGdwyncG+ZCVTii3cHhp8fWVCSh4AoUEjiyO027XoTt8vDFtvmMOHkmiqxh2QZrNj/K5h3zUq+7+PRXadf2HGatviV1sW7oJp/vK+TqTvfge/5J1POvp0Z4sbHJUpozvvccbAxkNKTfQY2gw/89MUXBfd1Q7HAIKRRH/nQ7ap9uqUieZRfz8caZFLcbjUeyiAe3sOyLf3BKt1vp1HoEfTvdAMDSDX/llM4TCdhZSC4X4/s8hWUnV5OvbX6EHTWbkmO/+3TylABmr+uYtX5K6py4sstd+Jt2ILJnM9veHk/bYc/ULUrrFsqbtyNt3p66+AlAOrs/VmQ32xbfVi+4R87A4y7EDFXyzeIp6LVl+Jt24IQe41G9ebjc+UjPL4H9/a/zsjGleEq0Q4MoZ5+HUn8nKS8bU5Zx5WUTrKgl0wJYUSQ8SjRj1D2Tl4Bvf/92ITmL6l8gkhB4FA8q1biQESTwKPlIQtRtKoF6iIjmoboHEApjPPFq/TEaCO4ICv6s7Ix+CZKkYv+AM/3Pka3xY6LyvwcO2uyUZbITHkb2fwrbMlAUF3oixFe7lxKJV3NR+/Fk+5phSIJHll+VWhf8sePN5Ltb4G01nLmfP0ooUcnVPWawYesrdDlmKEN63kOiZicVi+7DiFZx7KAZxNTmv7u/t4PDz8XhFO5yUVFRHkkBLzW4DUBpaWn1YTy2g8PvAtuwwKVx3PCnSOhB1rx3PS5fPm17XMfry67jD93v4P01dx+UNihkmVkrb0lF2DeULwVgQs/HsWv3oUQieF97Hak2mGYsZ1mizojOW7f0ci7ODocXRZEQ+nesXDy+Pt18yHT4aEsq7VeVXETilcz7ZELqddn+Qlyqn1q7nHdWTaFf55voffwVuJeUIkq6YeouAlqcjc8Px9+0A2cXj2ZoqwsR8SD5CZW4F56qE+2QTJ9/cv1kxhWPJ7JgIpovH1my8GuhOnMsT8asAEvVU6Id9rdhG8/xw55GvL6cNmffy7YlfyKyZzPfLptBm0Ez0AwvViiSMmpSxgzDsDO7wgu3nDrWfmHkIrNAB3CZu9k6P73OXa9baB/KS+B/qUt2OLyYwuTNz2fS66gzcePFtHXe/Hwm559wS+o5AoGpxEFOjgVRNxYOlcmC35e6P2kyN4xgneA2LZuYK0CbQen92NsMmIYi+RGZ3i8vG2ncqJ8tW+P3VMueCUWRsJQY8rVDkPYGEZ/tJGLvYe2q+jm068CHUN3+VFndwk8mMLjPQzy/ZUbauuC70Fau7nYfqqlzXvvryfEV8vW3SylqVsLu96bSss9NfDPvhtSxtx+woeng4PDTcjiFe0egknqxXtXgMYFjSevg8D8TUxTUWBWJaAUbVtxPLFxGLFzGN6tmMqTrJPz+Izm7ZAbzGrTAOa14CroZO8hobkP5Us47/iYCzz+VMpZTLh5PbQZjOQeHnwuXEmXNe+MPNorrNA156y6UMcOIW/6D0mNPK57CO6smp9LkA54muJeUonQ5nqiikoMJkoorUEhkz2YiCyYmjxcopKD3VEzJzGjGKHly8DftQIve1/HlGw3MuQbej/vis7Cem5+WkmwIM3MbNmEihSIo8zbWt0JKWEjuI6i15IMipG4pkjnKmZ2DcvuVaZFUIeyMAl1256Xu2/85Gi60D+Ul4LjI/3KxhcWG8qWpzdf9nNtxPJAUcYfarIkgH9w9YOSgpAHi0AFIPi8ioWMG/Jh6veDWdRtLbU7RsGeQhIEsqYCPuKziHTMUY066s3xY0UjoFk62xuFn/+9d2uD3bjvsCda+fVXaHLpu8QS69rubISdO4a1/30koUobX0yjjnGcKg4WfTCDbX8h5/Z6khbsplR8/ihGtwojVpD1fry1LbhY6jaMcHA4Lh024l5aWOoWtDg6HGY0IWxeO5+hT70xzqA7u3cxn795AyZCnCW+Zxx/7PkY0UUM0Uc26rS9xcqebMta0K4oL9aopCNvGlhRqcWM6KW8O/6cYmVuqNc+vj+Lpdn16LAYSgo8+m5ES7UNLHsZn+rFLuhFVVHy1tUmxku2nzbBp6XXjp9yDklDRPIGM54iIB2lefAVfL56aHkVffBvt+jyUMoYTOQFCqIcU3ELSUPeLptnv1kfMLTljzacgsyt8xPJjCZGWxm5Ea1LP2//5tr89nuOGPZG5NrluoX2oCKzjIv/LRZGUzHO5pGACXiWaEnFQPxaKhj1DWPdS2yCNXsgywjBg2y6M1ZtTYzJiSRxUS24JwmlRbchRDIz3VtSL/mgM470VeIYNJOFkbPwseJToQZtzRrQy8xxq29Qsf5Szu49H9uQgadkZx1I8EUx6BfSeTvmyGQS/Xpry+fhu9ay09z1Ui0kHB4efhsMZcXdwcDjciGT6rJUIZWwvpfkb06T9cFySF9WtkqXlcWqXW1GXLubqLnfx+Kb6Hu5XFz+MrWdRnSbUHdHu8H+NlnFs22h1NbxJsdowPVZRJPp3nkS/ThNSNa41ZnIs52DWp4PXhFDehHanPwBNc2FvGWLea5i7tuNueSxXj7ibxzfeUX+O9JhBnpyHLA6Rtq6CMWcuAOrtV2KKQwvumOUj7pN+tJuyZYkf7QovLD2zQJeUH+zlnql/u+Mi/8vGg8KVXe/hyXV/rvdi6HoPHhTCgHSIsSrVbdYcuEmkap7/b4dv2bYxt2zH2LI97X7l7AE4GRs/Exl+bzNWk3kONWPJbKO3ktlGOcf05eqSGTy+anz9nHfiQ+TYPkaWPIHm8pJz0i2IkgkIScXAT/PiscQqt/7HFpMODg4/DY5wd3D4NSNpuAKFlP/7WTqdNJkNH9/VoIbtQaq+fIdAk+MQrmxce4Lw6XakEacid+5D40WvMbHnn7ECAdSsPCSRi647i3OHXxa65aPLwBmsb1Dj3mXgDPQfWBz+UI3rQeng/4+9e49zq6z3vv9Za+U0STPTdjrI0IKcF0UERKjKYYNQ8bbugq1yq8hGQEC3iKcCst0KBR9hcyj7fjzsWwQLqNvDs+UkUuQkoIBYQAVBXFBEwDJCO53OZJLJJFlrPX9kkmbayXRmOklWMt/368WLTiaZ/LJyXb9cv6xrXdfLPfjX3knoq5+ExDzcVH/x2vJUPztbb+K8I27AN11wLYx8nHTeJxEZGnvaeiZXvi69dJZ6/ILbn9RqyhNZFR7ACMXYb9l3CcfngmGSG3yDfzz1YzAi21ybXDnQLu3frq2ZmofhW8z2I/zrW/4NI9yGnx8i6Ucw/GKhbI5cDrJ1Wy1Obx9t1I4CplnclWAS771mbATAyJig8v3e+Oc7OOQ9V/P7e7dsS3nwMV8jGt6yyGAk2c38wz5JwVjABUesprC5D2swR9sPnygvkhn68tn0+dGKJ/OwJrHFpIjsOBXuIk0s68bZ54Rv05dKMxSexwHv+2/i1hAmPv2vrKVjl4PLU3ojyW72ef8qCph4bfNILD2d5Mhe6+lClLwG51JnlmVSCEXwMDDxCRVyuFu1Q9f1wZrPYUtWU9xPKExuCoPDclGCMXZx4Ruk2+aR+ORKrJF+MUgUd8inqyvJhg0pSoVy1t32LPo+x16Gf+tTY56lnmjBPR0sy6CQ3sBfR1arjyS72XPxSnY9/DOEcgbGL55l4Tsvw0/GMGe1M2QmcSu+sNPWTM0l78eIRGcTiyzANaJY0WEixiB5P0bxvYuzz7GXbbONIMRH/Z2xdhRIlnYUmOBng2ZsNF6eBPuc8E36UkMQbof8AB0xgzf++FMOOvxCoh0LyKd7iYQ7iIRns3D59Xieh2+EikV3zqPDasOvWKQSqn8BU8/cJiIq3EWammVZvFGYz2WP53gj7bNTwuBLR/gUfv//sMdRK3huZPEsGLkO964tC1FV7rWuD1upN8sy2exFufyeLW33346JMtsaHrN4H9qBwWFlUZJvTxD66BIKP16zTXFRLFq33y+2PotuGGEs2jA/thuGaeAbBgnfJW3V/2x18RrXL47q93+9byW7H3Mh1vAQ/jPr4JniVGZ/Tjtt55xMTtcfN62wkeXvQ0mueDjEG2mXnRJhvnRkkgWzsmSJkHZNktFdWPiuK/CjFsawixV9EynXpLKYno4dBXZ0xsaOnvEXiJjDrB/q5IrHQyN5dS5fOiLH8KaXWPfzzxFJdrPwn/8L/78fwh1IY5xzMoNu5QaW+gJGJMhUuEtNeIVhurqSE75/IZelrz9fw4hak2uGuOyBYuED8Eba54pHIlzyjrPxfXfchahEGqkQipSLdii23csfzPH14yMYbnZan2tUUdI3QOHOhwh98D0YO3VSqFJcVBYR/sAgIau4aNyW2108YqRJlG9PZjMUKga7kz1jOR2qXdNshtvwt7rOWCvGN7+Mn+CKh73RnwEPh7jivREgXyymw20kunYtFtPtY7f37e0oMNGieqozNqbjjL/AEPFt28MjES469POk7/xEcS2OwUzxEiEY1f+3vMd5vGQC85yTMXTJjEigqHCXmjBDUdZ+8+0Tvv+ic5+kOA1WJqPgG+UP6JI30j5W+64YRv+4C1GJNJLH2G3Xw5j2MnLrosR/uYf89TcT+vLZoxa4K9m6TccAeAAAIABJREFUiHBHiohMMllekX7r4iIIe6BbloGBP2a/9/JDGMOxUXMIdP1x88v7Fm+kR7+Bb6R9Cr6FMfKZOpFierzr00PUvqgOQv9pBQU/xBvp4VG3vZH2MWLzgG3X4jBMo7go4RhfnJij3mMV7SJBoC3bRJpYyChOMa60U8Igv/klSGXZZ8mqYrEOWy1EJdJYJmO3XXMHL9sIWSYdls8cw6XD8glZZrkoqVQuWsdQtYhw82PfXjozP8YZS9Or34A3ZmV4+eFr2OO4i0b3+/ddQbh9PtbsN5WPQ3mrL51tb2phc+x+FDIn14/SWFinLxuzfVTtD9P4jU8Q+k8rCJnumO3Bz27cshbHvcW1OEIffh++UbxvPd5jEdlxOuMu0sQsr8CX3x3msgfy5euEL3jXEP2PXMm8RRcSi3drxVcJpFAhx78dE+XyByuvcY8QKgxPeahYbbptJpkkPolrNqtNGzaqFBel63kbvqK2n6f/pYcoZHrZ7agVhGLtFLIDhOKdZPKzyIUnvv2cNIe4t5kvHRHhikciFeuc5Ih7g6QmcUnUeNenm8b40+inQyD6TwuIe/1c8C6LK3/btiWvHm3SFduFnY6+BisXwfznY/AzQxR+8yTGssXA9i+VEJFgUOEu0sRyuQLdbUNcfNg/INyOn93IwCP/h3xmI8awi+HDsJuoGJyraJdgcF2P2dYwXz++clX5bRemm4xqZ41i55w8qUWzqhUR/jjFRSAWdBrZCir9+jOsW3MeUDzjvu+y1VPafk6Cz/SLi5FedMgpGLF5+NmNpH//Q8wjz5/03yq4HmnLImEWC7mECWnLwsOveVEdiP7TAkzfx/3j5aPbw9piezDjnRi9myFqgWVh/fPR5eOrL05EmoMKd5EmF8pbzDFdXrjnU6O2+wlFdiJ/6/0k33uEFviRQHJdD8PNls/n7Oj4cLyzRgXfmHDRmrVCzDr9A+RvuK1cRIRP/wBD4QjRKsVFEPZAH2ubusp92qX1mMTZ9dAzeeGu87bk//ddjcnkL4marhkrUxGE/tMKxmsPRj5D4eZ7y+9h6PRlMLLkjb44EWkOgS3cbds+GfgKEAH+03Gcb2/1+4uATwB9Izddt/V9RGYCzzcI3fsCC//papgTxzBCmJtd/FwG/9l1uK+9oQV+ZEaYrrNGMbdA/u5HCX3gWIx4G35miPzdjxJetnjc4qLRe6CXtqnb/6SbKOSzujxmBvBcn9BjPez//u/gW2C44D/6At5Ru8Akc/50zViZqkb3n1ZQrT0YR3WXd7yA4ntbqFj8T1+ciDSHQBbutm3PB74OvB0YBh61bfsBx3H+XHG3w4CPOI7z20bEOJN0zC5+JVtc+X2LodRr/OnGpY0ISSqksUgef8SWAdecdowPv4/CXb8GdJ2azBzTddbI9DwKz64j/+y6UbdbJx47qTP3jeC6PpFEJ/0bUiO3qGhvZWkskm/fH/c7W/L/VM+UTteMFWmcau3BN4yq63OUxgb64kQk+AJZuAOLgV85jrMJwLbtnwEfAi6tuM+hwJds294T+DVwnuM407v5rwAQCce4+ieHbHP7eR/5fQOika2Vvimf/blT8HMF/Dd6Kdz1a/yXi9tB6To1mSmm66yRrveUZlHZ5iMG5H2mfKZU7b75VWsPCd/VeyvSAoJauO8C9FT83AMsKv1g2/Ys4A/AecDfgBuBrwL/PtEn6OycNebtXV3JycZaV/WKz88XMML1bR71em1Bf4+rqdZmfc+HwTS4LkTDGLOTMJAGih/M4U8sx5idpMts3FT5IB/zoMYW1Lgmqlp7LanX64tM4TG+5+N/Yjn5792y5Rr3APSjyahn+xmVgywLZiWK+0NPQqPb+3jttdGxTUaEqbV5qE27H69tNNNxDVqs47XXymMeDlnMnlVc76DZc9pkBe09q6eZ/NpbXVAL97GySPnrY8dxBoElpZ9t214FrGYShXtv7yCeN3oKYVdXkg3l6YXBU8/4urqSZL94JQCxay6oy3PW47VN5zGsd2Icq81WLiZUnhp89kmY55yMMXLGsR+LQu9gXWOtFOR+FdTYahFXENprZSxBPO6VQrFE+cy9FQmxuWA0tB9NRj2P75g56PRlk1oQs1q89Wyz1dprM7TVkumItbLd7+jnx3htY87cRMsd1yC01/GOOdP43gZdM/Xb6RbE9irTx2x0AFWsB3au+LkbeK30g23bu9m2fUbF7w0gX6fYRAJjzMWEvvs/+ECfb9HvGlpcRmQKCq5Hv2vQ51sY7dqVoZpqC5olNP+2KVW2+x39/FDbqL/xjvl0vrci0hhBPeN+H7DStu0uIA18EDi74vdDwJW2bT9Acar8OcCt9Q5SpNHGW0xIi9GJSK0pB0k147cNqQX1R5HWFsgz7o7jrKc47f0B4I/AjxzHWWvb9hrbtg91HGcD8EngDsCheMZ9VcMCllEO/Pgdo/4vtVNaTKhSecEZEZEaUw6SatQ26k/HXKS1BfWMO47j/Aj40Va3Lan4983AzfWOS7Yv1r4LP/j+IfzLqVp1vtbSWCTPPgmjdzNGNII/nMPvnD2lrYBEZrKQZZLAxRy5/jOtPYwnZLq24JPWUNmPfEzMs08qXr61VduY6gJ6Mj6NCURaW2ALdxGZGCNfoHDzveWBUej0ZRBudFQizaNyQafCSD9KTnKBtZlqurbgk+Y3Vj8Knb4M47OnYOULaht1ojGBSOvS3BmRJpbApbDVQjQFLf4jMilaRGvHaNErgbH7UeGGW8H11DbqRGMCkdamwl2mla5rry/T88of0CV+3wCmFv8RmTD1I5Edp37UeHoPRFqbCneZVrH2XRodwoyihWhEdpz6kciOUz9qPL0HIq1NPVmkiaWxsE5fVv6gLi3+k9a2LyITpn4ksuPUjxpP74FIa9PidFJV6KtnEpozt9FhyDgqF4aKGJD30eI/IpOkBdZEdpz6UeNpTCDS2nTGXaoKzZnLmuve3ugwZDtKC0MZc9q1+I/IFGmBNZEdp37UeBoTiLQuFe4iIiIiIiIiAabCXURERERERCTAVLiLiIiIiIiIBJgWpxMRaVKWZRA3MxheHt8Mk/HiuK7f6LCmrNVej0g9lPpNoX+QZNhSv5nh1B5EWpcK9xlibnsMKxpudBgiE2ZZBjErA34ejDBZV4OPSpZlEM+tp/eWFbj9PVgd3XQuX0UmMr8pj1MkYhLz+yikN+Kn+8g8fQftR36yaV+PSD1YlkHc20Bh83rccBt+foh4+3wyVpf6zQyk9iDS2lS4zxBWNEz2i1dO+P6xay6oYTQi47Msg0hhPc//fAW5VA+RZDd7L1lFLqQiriRuZspFO4Db30PvLSvoPHk1KbetwdFNjmUZhIb/znNrtrzfex17EQMPX0v74gub7vWI1Es8NEy+v5cXf/0fW/rOcSuJd7STciONDk/qTO1BpLXpGncRCZyYlWHdSBEHkEv1sG7NiuIZeAHA8PLlor3E7e/B8PINimjqYlaGF7Z6v1/81aXED1zalK9HpF4MP8eL968c3XfuX4nh5xocmTSC2oNIa1PhLjXjusMsOvdJDvz4HY0ORZqNny8PPEpyqZ7itHkBwDfDWB3do26zOrrxzSa8JKbK+20m5jTn6xGpE993x+w7Pm6DIpJGUnsQaW0q3KVmLCvKD75/CLH2XRodijQbI0wkOboojSS7wVARV5Lx4nQuX1Uu3svXuHvxBkc2BVXebysxrzlfj0ideEZkzL7joWnRM5Hag0hr0zXuM1zoq2cSmjN3Wv7W/qf9AoBhV1OyZMdk3Th7L1lVni5fusY968YBXeMO4Lo+mch8Ok9e3fSrsI/1fu+zZBVZYw6u6zU6PJHAUq6USmoPIq1NhfsMF5ozlzXXvX3M3y0568lxH1sYmQpf6e13fJQnl/6YDyz/xbTFKDOP6/rkQvPZd9lqrSo/Dtf1RxZua6M4E7I5j0/V9zunol1kPJV9xzJcXN9SrpzB1B5EWpsKdwHg6I/cQSK57ZT28Yr3kBXl6p8cUv75vI/8vvzv5CxNj6+X0rZpwwODJCKt8yHtuj7pUlEKNGtRKiIiIiKyo1S4CwCJ5C6jivBKlQX5WM5YeidzE93j3kdqQ9umSStQOxaZGvUdqaT2INLaVLjLDpub6C5PkZf6ilmZ8gc0bNk2bd9lq0fOVo+vdLZe09GlkWJWhlcfvZbdjlpBKNZOITvA+rXXsutRF06oHYvMVOo7UkntQaS1qXAXaWbjbps2/oe0vpmXoDAMn50P+ggv3X9puS3ucdxFGIbaoch41HekktqDSGvTdnAizWwHtk2LWZnyyrOw5Wx9zMrUJFSRagz88kATim3xpfsvxdC6BiLjUt+RSmoPIq1NhbtIEytt/VIq3kdv/bId456tF6kf33PHbIu+p1XlgyhkmXRYPnMMlw7LJ2RpKNEoE+07es9mBuVSkdamqfIzVPirZ2JN0/7t0jgGBjG/k4XvugI/amEMu1h+J3kMtrsK+8jZ+soP+YmerReZTn6Vtugb+ogKmpBlkswM4t5wK4W+AYw57SRPX0YqPouCq+Kg3ibSd/SezSBVP9eVS0Vagb5ynaGsOXNZ+82x92+X5pHAxf3uz/CvvRO+8XP8a+/E/e7PSBQ39R7XDp2tF5lGaovNI4GLe8Ot+H0DAPh9A7g33DqhnCPTbyJ9R+/ZzGHRxj7HXjaqPexz7GVY21nzRkSag76Ck8Do6kpu9z7ucJ5NA9k6RNMcTM+jMDIYK/H7BrA8D7DGfazr+uRC89l32WqtKi8NpbbYPHYk58j0q+w7luHi+tY2fUfv2cxh5l2sW59i4Xsuw49HMDI5/FufwvzYbui9Fml+KtwlMLJfvHK794ldcwGgwr3EM02MOe3lMykAxpx2PNNkIidTXNcf2SKm9G28CiVpDLXF5rCjOUemX6nvdHUl2bAhxdZ9R+/ZzOGZJsZAGv/6XwLFlqD3WqR1qHCXaTfs5ohaEYbdXKNDaXlpLJKnL8O9+xFCiw7AmBWHZIJBKwSuPqVFthayTBK4mJ6HZ5qksXSd7ySUc87I1GtjTjvW6ctIYQE6jkE0lfdM/aQ5pbFInn0SRu9mjGgEfziH3zlb/VOkRahwl6rOWLqGuYmdATjvI78v374p/Q9W37Gk6uOiVoS33/FRnlz645rHONMVXI9MMknivUdQqBiUxU9fhquFh0RG0SJdO67geqTis0icczLWSFGXUlEXaJN9z9RPmpuRL1C4+d7yeCB0+jLQmrMiLUGFu1Q1N7Ezh91+yTa3P37ixeV/n7H0zml5Lq8wPDINfvu6upIUcln6+rVtGUDMLZSLdqhYeOick+nHaHB0IsFRdZEu9ZVJKbjeyPGyRqbfqpgLusm8Z+onzSuBu814oKD3TqRlqHCXHTI30T0tf8cMRSe1yv2ic58EVLiDFh4SmSj1FZHtUz9pXnrvRFpbYAt327ZPBr4CRID/dBzn21v9/mDgOqAD+DXwKcdxCnUPdIY6c+kvGh2CjNDCQyITo74isn3qJ81L751IawvkPu62bc8Hvg4cCRwEnG3b9v5b3e2HwLmO4+wLGMBZ9Y1yZpud2GVC9/uXU4vXxi8698nyf2897Y5ahjbjpLGwTl+GMacdoLzwUFrfrouMor4isn3qJ81L751IawvqGffFwK8cx9kEYNv2z4APAZeO/PxmoM1xnMdG7n8jcAnwf+sfavOwvnom4Tlzyz8Xp5vDkrOenNTfGXYLRK3RTae0EN0dx31z1O39gxvpmDVv9M/JiRX9MjGlhYdmf+4U3FxBi0WJVKGF1US2T/2keVW+dxED8j5670RaSFAL912Anoqfe4BF2/n9gjrE1dTCc+Zy9U8OGfN3lavGb0/UCo25aB2MXrgOoGPWPP7Pt9Llnz//mXlbP0SmQcH1MOYm6duQ0mJRIuPQwmoi26d+0rxK711XV5L+DSn03om0jqAW7mMtfelN4vfb1dk5a8zbu7qSk/kzdVfr+M5c+osJT4NvtKkei6C/x9VUa7OVgvraghoXBDe2oMY1Udtrr832+hRvbTU63vHaa6NjmwzFWhtBi3Ui4wEIXtz1pNcurSiohft64KiKn7uB17b6/c7j/H67ensH8Tx/1G1dXUk2bEhNLtI62pH4qnXianu1T8Xtiz9PoeATChnb3cO9NE1/MPUGf77xfTv0vNvjDufxDZdQJDbhx0xku7l6J8ax2myloLbfoMYFwY2tFnEFqb0G9bhXo3hrq1q89Wyz1dprMx1LxVobE401CO21UjMd4+mm1x6s9irTJ6iF+33AStu2u4A08EHg7NIvHcd52bbtrG3bRziO8whwKnBXY0Ktv7ntMaxoeJvbvcIwZig6ub9VZa922HbaezW3v+dz7BKfXf559NT4xDb3f+fPtixO99iHlpaL+EXnPkl24DWevmnpdp9zMq+1eKzC2m5ORERERESaUiALd8dx1tu2/e/AAxS3g7vecZy1tm2vAS5yHOcJ4GPAdbZtJ4E/AN9oXMT1ZUXDZL945Ta3x665YMzi9MCP30Gsfdvp75PZ0u3X7/8KbaHiqqTDrsdv3v8VDMMg7BmYYQMv72OGi1cwnHt2HCtiMNg/9tULj31oKT3pDMvuuh+ANddtifn40x/h4E8/QcTa9mqInOvjpXt4+qalU9z3XUREREREpPkEsnAHcBznR8CPtrptScW/n2L0gnUTZQGY5liXyY++ffas6Jhntksme4a7kMvSnxq91fz2nmNrU5naEmvfhcHB15g1a5cJT4e/ffEX8PI+j594MYWcRyhU3DlwYypPMm4RGynisWDdF9Ls/Z8J1n2heKa99O89r4wD8NlPxstFfanAf1Okjcc+VDyzftwZa4lao7cqOfGmNFu7/eMJhhM7jzpDDzCUeo0/3bh0zC8oCu4wISs66v5b/67aWf5qbaTC7sDfgcJ27rejxm2zlSZyn0YIalwQ3NhqENfuBKi9BvW4V6N4a6tKvLtT+za73fbaTMdSsdbGBGPdnQC010rNdIynm177du1OfcYEMo0M3x//GpkWdCTwm0YHIS1jD+BvNX4OtVmZLmqv0mxq3WbVXmU6qb1KM6nHmECm0Uws3KPAYRS3kHMbHIs0v3p8W6k2K9NF7VWaTa3brNqrTCe1V2kmOuPeZGZi4S4iIiIiIiLSNMxGByAiIiIiIiIi1alwFxEREREREQkwFe4iIiIiIiIiAabCXURERERERCTAVLiLiIiIiIiIBJgKdxEREREREZEAU+EuIiIiIiIiEmAq3EVEREREREQCTIW7iIiIiIiISICpcBcREREREREJMBXuIiIiIiIiIgGmwl1EREREREQkwFS4i4iIiIiIiASYCncRERERERGRAFPhLiIiIiIiIhJgKtxFREREREREAkyFu4iIiIiIiEiAqXAXERERERERCTAV7iIiIiIiIiIBNhML9xCw+8j/RZqB2qw0E7VXaSZqr9JM1F5FZrCZ2PEXAC/19g7ief6oX8yZE6evL9OYqCYg6PFB8GOczvi6upLGtPyh7avaZisF9dgHNS4Ibmy1iCtI7TWox70axVtb1eKtU5sdt70207FUrLUx0ViD0F4rNdMxnm567YFprzLNZuIZ96pCIavRIYwr6PFB8GMMenw7IqivLahxQXBjC2pc06XZXp/ira0gxxvk2LamWGujmWKt1KxxTwe9dmlVKtxFREREREREAkyFu4iIiIiIiEiAqXAXERERERERCTAV7iIiIiIiIiIBpsJdREREREREJMBm4nZwdWNZBnEzg+Hl8c0wGS+O646/fYeIyEylnCkyeaV+U+gfJBm21G9mOLUHkdalwr1GLMsgnltP7y0rcPt7sDq66Vy+ikxkvhKoiMhWlDNFJk/9RiqpPYi0Nk2Vr5G4mSknTgC3v4feW1YQNzMNjkxEJHiUM0UmT/1GKqk9iLQ2Fe41Ynj5cuIscft7MLx8gyISEQku5UyRyVO/kUpqDyKtTYV7jfhmGKuje9RtVkc3vhluUEQiIsGlnCkyeeo3UkntQaS1qXCvkYwXp3P5qnICLV9n5MUbHJmISPAoZ4pMnvqNVFJ7EGltWpyuRlzXJxOZT+fJq7VCsojIdihnikxeZb8JGS4FX6uIz2RqDyKtTYV7DbmuT8ptA9rABVDiFBGpRjlTZPJK/aarK0nfhhTqNzOb2oNI69JUeREREREREZEAU+EuIiIiIiIiEmAq3EVEREREREQCLFDXuNu2fSnwIYoX5HzPcZxrbNteDFwDtAE/dRznKyP3PRi4DugAfg18ynGcQmMiFxEREREREamNwJxxt237aOBY4EDgUOBc27YPAlYDJwILgcNs237fyEN+CJzrOM6+gAGcVf+oRURERERERGorMIW74zgPAe8eOWu+E8XZALOBFxzHeWnk9h8CJ9m2/WagzXGcx0YefiNwUgPCFhEREREREampQE2Vdxwnb9v2JcB5wP8AuwA9FXfpARaMc/uEdXbOGvP2rq7kZP5M3QU9Pgh+jEGPr5pqbbZSUF9bUOOC4MYW1Lgmanvttdlen+KtrUbHO157bXRsk6FYayNosU5kPADBi7ue9NqlFQWqcAdwHOdi27avAO4A9hnjLh7FqfFj3T5hvb2DeN7ovS27upJs2JCazJ+pq6DHB8GPcTrjq3diHKvNVgrqsQ9qXBDc2GoRV5Daa1CPezWKt7aqxVvPNlutvTbTsVSstTHRWIPQXis10zGebnrtwWqvMn0CM1Xetu39Rhacw3GcDHAL8G5g54q7dQOvAeur3C4iIiIiIiLSUgJTuAN7AtfZth21bTtCcUG6awHbtu29bdu2gJOBuxzHeRnI2rZ9xMhjTwXuakjUIiIiIiIiIjUUmMLdcZw1wBrgD8CTwKOO4/wEOA24Gfgz8BfgZyMP+Rjwn7ZtPwckgG/UO2YRERERERGRWgvUNe6O41wMXLzVbfcDB41x36eARXUKTURERERERKQhAnPGXURERERERES2pcJdREREREREJMBUuIuIiIiIiIgEmAp3ERERERERkQBT4S4iIiIiIiISYCrcRURERERERAJMhbuIiIiIiIhIgKlwFxEREREREQkwFe4iIiIiIiIiAabCXURERERERCTAVLiLiIiIiIiIBJgKdxEREREREZEAU+EuIiIiIiIiEmAq3EVEREREREQCTIW7iIiIiIiISICpcBcREREREREJMBXuIiIiIiIiIgGmwl1EREREREQkwFS4i4iIiIiIiARYqNEBSOuyLIO4mcHw8vhmmIwXx3X9RoclIk1GuURE6q2Udwr9gyTD1ozKO8q5IsGkwl1qwrIM4rn19N6yAre/B6ujm87lq8hE5iv5i8iEKZeISL3N5Lwzk1+7SNBpqrzURNzMlJM+gNvfQ+8tK4ibmQZHJiLNRLlEROptJuedmfzaRYJOZ9ylJgwvX076JW5/D4aXx7LimoIlIhMyXi6BNk3pFJFpZ3h5rEQnc45bgdnWjjc0wMBjN5bzTiurzLmRXQ6g/Z2nYba1Y+FiWYbyq0gDqXCXmvDNMFZH96gBt9XRjR+KEc9oCpaITEzVXGKGsdCUThGZfn4oxuxjzqX3zpVbcsv7V+KHYuA2OrraKuVcK9HJ7KPPoXfNpcqvIgGhqfJSExkvTufyVVgd3QDlhG94rqZgiciEVcslGS+uKZ0iUhOG55aLdhjJLXeuxPBavGpnS87tOOKsctEOyq8iQaAz7lITruuTicyn8+TVo6awJrz+cae9iohUqpZLXNfHYPxp9CIiU1LlEh1mQG4p5dxkZ0L5VSRgdMZdasZ1fVL5NgbcdlL5NlzXL0/BqlSa9ioiMpaxcgmgfCIiNTHTc4vr+rhGZEYfA5EgUuEudTXetFcRkclQPhGRWlBu0TEQCSJNlZe6Gm/aq4jIZCifiEgtVOaWkOFS8K0Zl1uUX0WCR4W71J3r+qTcNqBtZHVWfQiIyNQon4hILZRyS1dXkr4NKWZiblF+FQkWTZUXERERERERCbBAnXG3bfti4H+P/Hin4zgX2La9GLiG4hKWP3Uc5ysj9z0YuA7oAH4NfMpxnEIDwhbAsgxiVobhgUESEYusW7vpVKXnws+DEa7pc4nI9IpETIZT/yAZLoAZYthPkst5jQ5LRGSUSMQkaqTI9veTjDZ/riqNnQzDx8DH91x8jaFEmkpgCveRAv144G0U5+L80rbtjwJXAEcDrwJ32rb9Psdx7gJ+CJzpOM5jtm1/DzgL+L+NiX5msyyDSGE9z/98BblUD5FkN3svWUUuNH/cDwPLMoibmUldOzXV5xKRxotETELDr/DcmvPL/XefJVdBdLcdGhBPJZeIiFRTylV/meZc1SilsdOrj17Lzgd9hJfuv3RaxlDKvSL1FaSp8j3ACsdxco7j5IHngH2BFxzHeWnkbPoPgZNs234z0OY4zmMjj70ROKkRQQvErAzr1hQLaYBcqod1a1YUz4pXYVkG8dx6en90Bq9fewK9PzqDeG49lmVM+3OJSDBEjRQvjAyEodh/X1hzPlEjNeW/OdVcIiJSTS1yVSOVxk5dC5eWi3bYsTGUcq9I/QXmjLvjOM+W/m3b9j7Ah4FvUCzoS3qABcAuVW6fsM7OWWPe3tWVnMyfqbsgxjc8MFj+ECjJpXqwDLdqvO5gL//4yQrc/uLj3P4eem9Zwc6n3oQ1q3Nan2trQTyGE1GtzVYK6msLalwQ3NiCGtdEjdVes/39Y/Zf/MKUX+9Uc8lkNdv7oXgnZ7z82ujYJkOxTo9a5KrpNJHxAGw5xqWxUyjWvsNjqJJ65d6pCsL71Cgz+bW3usAU7iW2bb8FuBM4D8gD9lZ38YCxvs6b1Nyl3t5BPG/0dJ6uriQbNgT329SgxpeIWESS3aM+DCLJblzfqhpvu5UtJ/sSt7+HQi7LpnFe41Seq9J0HsN6J8ax2myloLaPoMYFwY2tFnEFob0mo6ENAonvAAAgAElEQVQx+y9GaMqvd6q5ZDKC2k6qaZV469lmq+XXZjqWinX6tEfHHmsYRvWxRhDaa6XKY1waOxWyAzs0hqpUj9w7VUFvX7U00deu4r45BWmqPLZtHwHcD1zoOM5NwHpg54q7dAOvjXO7NEDWjbP3klXFATiUr5nKuvGqj/HNMFZH96jbrI5ufDM87c8lIsEw7CfZZ8lVo/rvPkuuYtif+gBiqrlERKQa34yxz/uuHJ2r3nclvhlrcGRTUxo7bXjuDvY47qJpGUMp94rUX2DOuNu2vStwG/Bhx3F+NXLz74q/svcGXgJOBlY7jvOybdtZ27aPcBznEeBU4K6GBC64rk8uNJ99l63GMlxcf/uryme8OJ3LV9F7S3GaldXRTefyVWS8OOPtE1r5XFpVXqS55HIeRHdj4Qevx/cKYOz4Ss1TzSUiItVkcmHikXb2O+GbYJjge2CEyeTCNGNeKY2ddj3qQgzDZ7/l1+N7Hr4RmvIYSrlXpP4CU7hTnBofA66x7fLs+O8ApwE3j/xuDfCzkd99DLjOtu0k8AeK18NLg7iuT9ptq5iiM/5q8jErgx+bxbxTrgffwPeNCa9GWnqu4g6BjPtcIhIsrutjhMK4rguYO/ylm+v6ZCLz6Tx5tVY2FpFp4bo+w5E5xIwUvl/AMKJk/SRuE64oX7Jl7DR6W92YlSHL5HOmcq9I/QWmcHcc53PA56r8+qAx7v8UsKimQcm003ZuIjNXqf//eZr7v+v6pEpf5rmgL/NEZEdYloE1/HeeWzM6V1ktMFaZznGYcq9IfQXqGndpfdrOTWTmUv8XkWbQyrmqlV+bSKureeFu23bStu3dav080iT8fJUtVvINCkhE6kb9X0SaQSvnqlZ+bSItriaFu23by2zb/ubI9ed/Ap6ybbvaNHiZSYxweTXTkuJ2UFqFVKTlqf+LSDNo5VzVyq9NpMXV6oz7vwHfBT4I/BbYDTilRs8lTUTbuYnMXOr/ItIMWjlXtfJrE2l1tVqcznAc50+2bX8JuMtxnJRt27qeXrSdm8gMVur/+590E4V8Vv1fRAJpKtvcNguNw0SaV60Kd8+27f8NvBc4z7btJWipSRmh7dxEZi7X9YkkOunfkBq5Rf1fRIJnMtvcNhuNw0SaU63Ogn8ROBv4suM4/wD+HfhsjZ5LREREREREpGXV6oz7PMdxFpd+cBznCNu2/wV4tEbPJwFjWQZxM4Ph5cEM45sWRiGLb4bJeJqSJSI7rjLPTCS3TPb+IjJzRSImcVLk+/qZHQmRIUku5zU6rJqxLIOEmcH0c2BYuGaETCGqHCkSINNauNu2vRQIA1eNXNNujPwqDFwG/GA6n0+CybIM4rn19N6yAre/B6ujm873r6TvwW/ipnvpXL6KTGS+PgxEZMrGzDPj5JbJ3l9EZq5IxCSWeYU3bj2/nC/mLbsK4ru1ZPFeyo8btxq3xROdZKwu5UiRgJjuqfIHA+cCO1GcGn/uyH9nAldN83NJQMXNTHlwDOD299B750o6/unTxX/fsoK4mWlwlCLSrCzLIGkNbptnxsktY+Yl5SIRGUOcFBtHinYo5ouNt55PnNR2Htmcqo3b/M3rlSNFAmRaz7g7jvM14Gu2bX/acZz/ms6/Lc3D8PLl5F/i9vcQan8TkV0OIPfaM8Up9OVFUUREJqZ0ZsgtDI2ZZ6rllmp5SblIRLbhFcbMF3iFBgVUW6Y/dn402zpAOVIkMGq1ON21tm1fYNv2A7ZtP2zb9kW2bdfqenoJGN8MY3V0j7rN6uim0Pd32t95GlZHN6ZpEbKMKn9BRGRspTNDXrpvzDzjm+ExH1ctL1W7f0nIMvBTm5ljDNFh5ZS3JHBClkGHlcPv26A2Ol1Ma8x8gWk1KKDaMqq8XiM6a7s5UkTqp1aF+9eBY4H/F7gGOBxNlZ8xMl6cecuvLn8IWB3ddC65iP5HrsNMzGHe/7oE7/YfkhzaqAGGiExK6cz5wGM30rnkotF5ZvkqMl58zMdlvDidy1dN+P5QLIiSQxvJfeurFK78LP61K5W3JFBKbdS/diXDl5+rNjpNfMxt88uSi/BpvcK92Fb8MV+vEY6NmyNFpL5qdRb8fcChjuPkAWzbvhN4CvhCjZ5PAsR1ffx4F3OPvxAj0oY3NMDmh76Nm+7Fis7Gve16eGUd7msvk/jkSvqJNDpkEWkSpTPnudeeYfND32bOcSswE3OwkjuTcmdVXUTJdX0ykfl0nrx6wqvKJxjG/f4q/L4Nxefu24D7/VXKWxIYaqO14fkGA0/8pJhf2trxhgYYeOIntC++sNGhTbsEw/CP9Qz8advX27H4Qi1MJxIgtSrczVLRDuA4zrBt2/nxHiCtJVOIEp/VNWoF53n/6xLcnxaLdigOMCzPbXCkItJMSmfOe29ZQe61Z+i7fxWdy1eNW7SXuK5Pym0D2sAFGP/+pudSGCmISpS3JEjURmsj48VpP/KT2+5C4cXZXt5oNqbnUrj3NjqWfIyNv7y4/Hq7lq9isAVfr0gzq1Xh/kfbtv8T+NbIz58Bnq7RcwWOZRnErAz4eTDCZN2Zt1fwqLNbhg+Ghz/Yj3Hs+/F/dSe8sg5jTheeaY0MoEVkJrAsg1y6l0Q4Oyo/TjRvTuXM+VR5poUxp6t8NhNQ3pJA8UwL4y2HwmFH4CcSGOk0PP6I2ugOcl2f4bYFzDvleny/gGGEyPpJ3CbYCq6US4cHBklErO2OQT3TwkjOBt+k88PfwjBMzIEUfttOuLmZNXYVCbpaFe7nAN8AHqF4Hf3dFIv3lmdZBpHCep7/+QpyqR4iyW72XrKKXKj19wq2LIOhoV6i0SymaQEGLj5Gbojnf35u+Xjss/QSQg8+gLX4Q6SIom9zRWaGUn7881b50Y0uwBr++4Tz5mTPnFeLJW5mxi3+00RJnrqiPBXZmNOFdeqKqnnLsgxCoQyQB8IUCtv/QmEqjxEpGbJihN73z7yw5rwtn7FLrqZgxcANfpEZVJZlEKaPYS8PhgFenrBRwLVmB7p/TmUMOhyOYSz7MPnhASzTw3ezWHPbMawINMEXFSIzybQW7rZt/4ktoxkDKJ2mOBh4CDhwOp8viGJWppwwAXKpHtatWcG+y1aTdlt3Ow3LMvD99dy15ouk0z0kEt286/CL+ctzP+aAhR8jHO8kl+ohl+rhhQcuZuGy60m5sygE+ANQRKZXtfy43/Lr+cua+uXN0pZy20yDjYwe3BZcn1TbPGZ/5mu4wzk80yJFdMy8VcqB9927JQcefcwq4vEuwMN1hzHNEK6bJDcyGB77MddgWa3/Ra9MjzBpnh8p2qHYd15Ycx77LltNTlt4TVk85pIeSvHQg+dV9M2rSMQSpDLB3SRpsmNQyzLI517lwQdXjB67PX0tBx30SSKRXcv5SkQab7qzz4w4qz4uP19OmCW5VE9x+mcLf4hGIhnuubs4+ARIp3v47aOXcOxx3ySXG2DX91zMq/deQvr1Z8ilenB9V0W7yExTNT8W6po342aGgYevpWPxCoy2dvyhAQYevpb2xReOnMnfouD6GHNn05dNVT27b1kGkchgOQfOm/dW3nLAx3HdLIX8APlChuedn7Hbm4+jvX032tpi5HJxQqFMuWiHYt586MEvsvg9N+C28Be9Mo38POF4J7sdtYJQrJ1CdoCeJ29s+TFHLVmWQcFLl4t2KPXN8zn+vdcDsxob4HgmOAYtzfQxTZd77l6xzdht8eL/YiD1KnPnzCOXi046DF0yKlIb01q4O47z0HT+vaZkhIkku0clzkiyG4zW3QczFjMBl0MPW0F78s1YoRi+X8DzXAzD4O5fnkEi0c2RR14MD3+bfKYX07RIRnMYhWxNr1EVkQAxwnTscTRdC5eWi4wNz90BRqhuedOyDCzDo23RR1j3q0vL00n3Ovai4nocE/wbpentphnD84YAi+OO+1ZxP2QrSir1Kr7nkhpcz6xEN/u/5VR+df9nRp1Zh1nlAXNJ8WcVXTIxhhVj18PP5a/3rSy35T0Xr8SwYsVmJJMWDmcAg6P+6Qra2ubieS6+7/LsMzfh+wFfOGACY9BYzMQ0B/B9AIPF7/kOpmnieR7P/Gk1L754O0NDG1n7u8s5+phVRCK7EvXTE15TZCZfMirBZtv2Zx3H+Uaj49gRtdrHfcbKunH2XrKqmCihnLCybuvug2lZWXzfY/bsvQmFiyuQpgd7+MPvv0mhkGWvvU4kne7h4d9ewpvecRZ7HHcRL//6StyhN/AGXmPgvv8gnluPpX1nRVqaayZYsOgsXvnNKv5yy9m88ptVLFh0Fq6VrGnejMVM2qODJCP9JEIpvJDFa0//hN2OWsF+y7/Lbket4LWnfwKGRyIyNG4u2jK9/XRuv20phcIAhuGTybxOLpcCDFw3R1uskxdf/AVrf3c52eE+hoc3l8/GH3rYClx3CNM0SSS6R/394s+t+0WvTC/fc9n00sPse8I3eOspt7DvCd9g00sP42tV+QmxLINodIhodIBodIhIxMQ0PcAg3taJ5xXwvQJDQxvZ/y3/gmUF+wu17Y1BiydaNuO6OTwvz+Nrr+CRh7/C5s0v4fsubz3wTE78wM/xfHdklsEKQsZmen90BqnfXo/rp4mE+kjEs7S1bTlulTkzZmVYN8alTzErQyRikmzL0h5NkYz0k4ylSbYN0x5Lk4z00x5NMSuW03hQauWiRgewo4J7oU6Tcl2fXGg++y5b3bJThEKWScIH0/fB8kkPD3D/r4pnkhYsOJpD3v45wpEkbz/08zzv3MKBB51Ff/9f2bjxT0RmL+DVuy8m/fozDG18nr3/6ULaD/1I1WmqItI6wn6Kv6w5f6vrcc9nv+XXk6lR3ozFTMyhV3hu5HkjyW72PeGbdL/tY/z13osJxzt58yGfZ69FX4E8vPzbr7PLorOrnh2qnN6+114n4rrD/Or+z7Dzzot4ywGnkc32ks1u4sV1d3DgQWez//6nMJjuYXbHnsyb91YOfts5/PbRS8r58uhjrt7qOtprKBS0BZNMjBkyedP+J+Bu6scKzcIrDPKm/U/ACFmQa3R0wTHWIpDAGGtMXE04vBP5/ACFQoZsto9wqI1CIYvr5gJ/xr1yDGoZLq5vjdq5I5d7lYcqrmc/4shLMc0ov/n1l8o56dDDvkgi0c0JJ95CIZ/BNw06PnQ1XixO38ArvPLy/ey19wk88vBXxl6bY+Tyjb3edRGh6BwKw3288tS3MSgQdl8nl9pUniHSscfRLFh0Fi9U5Oc9F68kGu9k2OpqqbGzTJxt2zHgemBvitPP/h04AjgO8ID7Hcf5d9u2VwIbHcf5lm3buwM/cxznUNu2/wzcQ3GNtRCwDPhXoMO27Rsorrt2BsX12FYBZzmO8/6R574FuNxxnMfr9XonQ4V7DbiuP7IISKkIDXbiKRbiJqYHnglpw6NQZTXakGWSTOcoXP8o7qYMxtw40dMO5vDDVxKOzCIanY1hgGFYACzc/yMYRojDj7iEF56/FcPzSL/+DFActBvhNnrvuJg5x63A8Oo/PVTXYYnUkVftWvZCzfJmxB8oF+2l58sNrOdvD/4H4Xgnex9yCf4PniW/aR3G3Dh7feLLDA9vIh7LkXLHOvOdL09vf+uBZ9Lf/xJHH30VGAb33/fpUQtZhcMJwKCj480YZoij/uk/AJ+jj7madLqHZ5+5iaef+i7Hv/d6PM/dZvE6ke0xPB9rIIrxg9fwN2UIzY1jnbYTXkRtqKTaIpCRyBzuvWfLGhNtbfMYGuolEkkSDscIhxPEYrPxPI82fLwmmcVQyqVdXUn6NqWZ5Zsj02s9fvPUd0e9XjBpa5vDccd9i3xhCMuKcu89n6KtbR5vPfAs2pMLGBx8jWh0NtnB14hEZnHgQWfx+Nqrtlmb4z3HF9fmMM029nn7pXjffwZ/08uE58bZ59RL8c0wQ31/5W8P/kc5H3ctXFou2qGYn/9630p2P+ZCYnMSLb2os4zrX4ENjuOcYtv2TsCdwOvAO0d+f7tt2+8f5/Fx4BbHcT5v2/b3gBMdx7l0ZKr86bZtnwYMOY7zXgDbtr9u2/YuFFeyWRDUoh1UuM94IcskOehTuPY53N5hjM4oyU/ty9CcPAVvCMMI4+W3FLMJHwrXP4q/KQOAvymDceMfmX3uYaS813ELWaxQlFwuhesO09Y2F9P0KRSy7Gt/EMOwSLzpANKvP0Mk2Y0/NIDb34OZmINvhuu676yuwxKpL8Ma+/pLw6zd1HDfc0c9X+JNB2DO2ZX5772EDmsB3refGJXP8t97jOhJ7wDChBLmGF9ihkkkumlrm0cul2Lt7y7n0MNW8MTjq0YNiAuFYR568PxRK8wXCmn+/OwP2WvvpcRicznyqK/jeT7gYxgA/sj1tXEV7zIhoUKM/I1rR7Vh98Y/Ev78PzU4suConCXTOe+t7H/Ax8m5Q4SNJLG2eeVLWEqzYdra5nHkUV8vb2sL4Ps+phkqn5RoBr7nbzO+e8fpK8gO9YIBhx52PqYZYvPml5iV6CYc68D3PY47/lpCZoR0+jXSmTcwDBPLijArOZ/BwR4eX3sV+y38KNnsJjZu/BNQLN59Pwe0YRaieN//7ag26X3/GcKfPwoz3DYqH4di7WN+mWuG27TA4sxmA/cBOI7zhm3b/9/Ivz0A27Z/DRyw1WO2vr7iDyP/fxWIjfEcz1b8+3vAxymezb9hhyKvMV3jPsMlfJPCtc/j9w4D4PcOU/jO8wxv3kh/5lVcP40VGSAWL15zZHp+ORmX+JsyFLKDPPH41aQG1+N5BWKx2SQSO/PMn27knrvPAt/jkYe/yj33nE3XkefQsefR7HXsRaR+eyNWRzdWYh4Zrzh1zbIMkuEh2q0BkuHxrzfdEeNdhyUiNWAY7Ll45ajrL/dcvJKRqrU2T2la5efrXHgCC5ZchmsamPG5GEZkzHxG1CT/nRdI+Nt+RBYKcY4+5hredsi55Smn0UhHuWifN++tHH7EJeVppFAs5ENWlFhsLgcedDYvrruDbHYTQ0MbMU1w3WH6+p7n8bVXMjS0EcPo0zWeMiGGa4zZhg1X7WeLfLloP2TR+XihCEYoQt4b5l1HXsq73/Nfoy5hOfzwlRhGiEI+zebNf2Uo8wap1Kt4XoFta4MAS+W3Gd+ZN7zOuxddzeGHryQe34lQqI1EYmeG/Tw/feBsHvvzagp+npw3TCzxJtrbd6dQyPLIw1/l3ns+hWGYHPDWT/CX537MWw74ePmpEonukS86wHTHHifigpcfKudjgEJ2YNTPUPxc8PJDLb2os2zXn4FFALZtzwMuA46ybduwbdsEjgaeBzLA/JHHvH2rvzHWGbjKDlz57fhNFKfTfwD47x2OvoZUuM9wpkc5qZf4vcN0RHfmnse/xg1rPshPHziLvsGX8K0NeJaBMXf0glHG3Dg5N8PBbzuHtb+7nNtv+wD33H0Wg4PrWbj/KbS1zeOhh87nLQd8vLxI3fwjPkfIM5hz3BfY6aPfIRuaU74GK55bT++PzuD1a0+g90dn1G7hunG3TRGR6eYXcrz66DdHLQr36qPfxHen52Lcsb70yxnt7LPkKjr2PJrZh36M/nQP//Pgv3LDXR+kN/O3MfMZabc4yB3jpLfr+oRCC4jHdyqfqYu1dZJIdJfP2oE/qpA/+G3n8PvffwMwePqp77Lfwo/yxOOruPuXZ3DvPZ8in8/w4ro72G/hR3n6qe/ie/mR63FFtsMc+zMZs4kKzJorzpI5+G3nkHOzPPXizQznB7n5oc/wvTXLWPPE1zAjs4i1zWPevLcSCicwDJOhbC9rf3c599xzVnGRyWxv4K9xr+QX/DHHd14uT2ZoA9nsJu6/79P0p17h9kdWsNtOizh4n5OKx+XOE/nJr84kld3IP3oe5+C3nUNb2zwefeRihoc3l2cNQbFoP/yISzCMCABe1TbpE2nfZdSXtxueu4N9lly1zZe54fb5Lb2os2zXtUD3yJn1XwDvp3iG/LfAWopF+23AT4HFtm0/yEihvx1P27Z989Y3Oo7TCzjAs47jDEzLK6gRw/dn3JTg3YGXensHR6YobtHVlWTDhlRDgpqIWsTXYYbwrnluVHI3OqOEv7iQ3vRL/L7nZ+w1/0ji0bnEoh3ErDlEN/nl6fLG3DjeqfszEN/Io4+uHLW1USLRzeFHfh0v9iYywwPMauvk979ZQe/GP/GBE29j4L8/jdvfg9XRTefyVQy3LSBOCjf1D7x0HwOP3UjutWeKvz/lJvDcCW9HUk3lMUxEhnj+1jO2mba777LVpHPbn57V1ZWs18hod6q02a3iCWT7DWpcENzYahFXENpre3SQ5245a5s+t3D5dQwM79jeyOUv/W5ZMSqvZCLziUYNPH+A/sw/yBXSxCIdRMMJ8KE9lcS9fm05n4VPXkT+th4YKGB+cSH9XoGuriSbNqXJhT1cPMImeIMv8dyzN3HgQWeRz2eK14v6Pi+8cBv77fe/ueees0mnezj6mKt54vFVHHrYCmKxuWSzm0ZNq4dirixNtz/0sBXM7tgLjBDDw+1TOhZBbdfVVIu3Tm12d8bJr0E/lh2hMNaGQfL//bstbfhj78DtmkV/IbhfQtfzuJaucQ9F2+kdeJHZsxbg45MvDJHK/IO1z91EOruRfz7sEgzfI5lcAMA9d5+1TT89/r3XMTSUrPaaGt5eK82LRBm+8pltxnfGF3ZnQ/bPvPD8zeyx91LaZ+9J78Bf6erYhwf+eA0H7LGUWKSDbK6f9Rue5vA3f4Jcuo9QrI0H1p7HIW//LIZpEY10kM1uIl8YIhGZQ5sZJ2N2YWDQnhkmf91vy20ydNbhpJIubeEoeFkMv4DvuRiGhR+KYbjZLT9bMTLD4R26ZDHo/baWJvra6zgmaAq2bf8YWOU4zhONjmU8usZ9hksbHslP7lueTmV0Rgmfuhf569fRPpBn8Sc/zy9eWsm69Q/SnujmxCNWUUjuStvnjsH0CmAZ/OYPK9l//49tsx9xrG0e/ZGdueCxe+nJpOiOJ7nq8Ks40spjeC5mohMr0Un7O0+DwhBxv5+++64m+8JDxUH3kovY/NC3ATAyG9h4y3nbDMh3JLGXtk0pTZcfvW3KjPtCS6TmSme/K1cQ3mfJVeSMdkbPWpu8uJkpF+0Abn8PvbesYN7Jq/FTfRQsn1AoyprffYWBdA/tiW7eu+hiXk6v5eDPLoWCh79hmPxtr8FAgfCn9mXAKMbk+T4bjAwXPPrLci677JAjWfSOL5NKvcyjj1xcXpH5wIPOJju8mcOPuIRHH7m4PI2+NMiNxeaOuXd76X6x2Fx838PQNFGZADcCZrKN8EnvgKgJwx5+sg03AhQaHV0wuK5PJLKAbP5V7nvy8lH9/5mX7uDIA8/h4ae/TTyxM4P9f8P3i/1+rH5a+l1TSIYJbTW+s87ek4efvpQDDzyTvff/KHc9fkn5eJx45Creuf8nuOPRLzGQ7mHv+cfw/jdfjLvqBazeYeiMcswZl5MyNhCPd+F5BeKJncH3CA8OgNdPMtlGyp1FYVYB61NvwwvP4q+Zfq5+4VdszGW4atHx7BxKYg69yro1KwjHO9n18HPLq8yXPhOs6G5aa0jqwrbtKPAw8ETQi3bQVPkZr+B6pGYZWCtsQpccQPije5C/7RX8lwaL17tfu47D5p8MwEC6h9sfWYFvpcmG0vz8oZMZjgyxcP+Ti9+4brUf8T4HfZYL1haLdoCeTIrzf3c3r21+hXvu+1ci7/0Cs99zPn33r+KNH3yCN350Nu2HfoTILgcUB91rLqX9nafRccRZ5aIdtgzI4+aOTSWt3DblgH/5OfsuW62F6URqKJv18Np2Y+EHr+PAU29n4fLr8Np2I5ud+mC4ND3e8nPlHFHi9vdg+jl6b1kBoQg/f+R8BkYG4wPpHu5eewn7dR5H7hqH3I1/g4JJeNnuhD+6B37SwB/5Aq9veIgL1v5yVC778u8fJk2ElGtw4FHXcNi7v81bDjiDp5/6LtHobGKxOSx6x7/R1jaPRKKb4Vw/L667g2h09ph7tw/n+kcWveskHEliWdaYeySLVLJyPoXbXoWCCX4ICiaF217FyulzrJJvprn94RXb9P8D9ljK3Wsv4V1vOQvwWfu7yzEME8Mwx+ynhtE857v+f/bOOz6KMm/g35nZmdmSTQcS6XWBEClC6AQsCFiwnKfX9A7lFBtKxIKeFBsnxUNE8bB7r/fee3cqeortlBqkiNIZpCgKS0lPts3szLx/bLJkSVDsQfb7+eTzyU559pnZZ37z/J5fE0SB6hQBcVI35Pt64SjyUZ1yiC+/XIogO+NKO9TO71YWEYpUxLf1a/lrzCd3J8TIC88cJN3RlhXL7+K9dycQCPgJhkqIRMpj87j/uQa3vh9bVinzqvzyo8Vc9dHrbK44FJsDrn2HiGhQFq4hY9QcskfO5MDGvzcoEeoUTk1reZIfH03TIpqm9dM0bcJP3ZcTIam4JyFqWtQ4KghEStAf24G9tya+zy6N4HFkxj9XBfzYtkFdspddu17H6czC6cygcPic+IvO48nFndouPtGtwx+sRnG1iJUPWXU3uhVJVMhrlfW6z6InA0dmm0Yn5LHycd8N07QJ6C4CRioB3ZVU2pMk+YEJhy1Uby7VehpVkZTvrLTX5cQwDn+KlJY40ZbSckGQMCv9mHogPiGtoyrgR7ZV7NII9t4a9IUa+tyt6I/tQDBs3I7YhFW3zEZlWcS2uW3LNn696r/csW0XFUoL8nv+kXff+SOri2cAIIgOCofPicewf7rzFYYVPpwgKwcOmsruXa9TOHwOe/a8zVtLrqK6ei+rVk7hvXf/gG3/QHk+kpz0CCbYG8uPjt2FGvbGcoSTJxT7R8G2jUaff6eSRlXAT0ZKGz5eN5dAwE8oVAaIFA6fnfCcFg6fjSQpP0Hvvz1R06LSilJOlCpsZMWNx5OLbhxHHjqOhgl6HFmNxsN+jqgAACAASURBVMgboRpKSjYTCPgpXjUVlzMTlNh5dYYV0w5SEypvVG6GbZubtm/jstX/5Y9r3sM+YwLuFkcThOvVfmxLT8q8JEkaocktHfp8vlSgGDhf07TPfD7f2cBcYjUh/qFp2j21x/UCFgFpwHLgOk3Tko5h3xJBkAlbJTiz1AbxUIFoWfxzqicXSZLAhlatCjmwfwWdO19ETc1+vN62DBn1D6K2gCgIgMkjA8/j6R3r2VJ+CIBctxen6qXfiAU41EzC7mY4Tx9LeNNioFZZd8XiOqW0XCRvDpYt4uxciPv0CxBcqdihKoKbXv9O5eOS9dt/PEwzQrNmiTGBhhGmoqLpxl8m+eFwu0Ui1X68sokgSkSlVILBb6e813ePr/rwObLG3EvpmzOOhtRccB84FFpc9wq67CDVk5swWU315GIIEcRG5J6NgRA8gqS0QhRFct3ehElortvLvppK/MFqemS04MouvbERMJyn0atwPnroEJs2LSQcKuHscxbSuculKHIKnTqPxbJMzjrrMURJRhQVamwnvn73UVGzj/37V8QnxH37FbFs6W0sWzqJs8+J1UhOkqQ+llQ7Xo8Zv5ZE0lW+HoIgN/r8h/VKUj25OCQVRU0HQJJUBMFGkpyMPPcpLCuKKIrs+3w5bdudCZycYSyyLCCJKsMKH0aPhhqXh9FQ/HMgWtronDCKTr/hf8WhZhKNlCFIKtSrcW9W+rEsEyN8JC4362RkhurCtG2yVDf+YDVZqpsyZNqNmUdzS0ep3MehjS+BDW5HDUFSknOzJEnq0aQs7j6frz+xOIMutZ9dwDPAWKAb0M/n842uPfxvwE2apnUhlt5//I/f458PluFGSU/DujoHIUsFYgLacV0n1u1/CYgJ9VEF04laBiWRGrr0+xO9h87GRsTpyubLsMS1H2zj0jc3MOGDLXxRE+HVvdu4IW8APTJakOv2MvWMs4hYInds28WvV/2X8aveoGLgeOTTYqutUlouthmNx7FXmymEBQ+eYePZVTyHra/+kV3Fc/AMG09E8Hyr0nHx+u2vjGPLixey85VxKNGkReuHQpJUXnyhT8KfLDdWUjPJzx23W4TAPrb/ezybXhzL9pfHQ2BfbPu3QLCMuDeOfmALFcsWkHFWEbkTXqfZ5Y8hpbZADxzEv+VlZBMuGjyb1FoLWl2M69ov/wfp2o4N5F7UGSWqB3A7ImSoLmb1P5dcd2wBKtft5eH+o3h6x3p6ZLRgQvf+vPH5Dqr0CNetfI0rVrzFHdt20fqMP9E8pz8h0Y2Q1p2ySIji4uks/eAWjGiQPXve4rOaKNct3cGlSz7mto9qaNPnAbKy8+Nx71AXa5tc6ErSEMMlIF3XJWH8Std1wXAl32f1sQw3YwfPbfD8b9n7OqMKphOJ1tD99HF06DgWRXGzds3DRCJlvPP2NSx+dSzvvP1HWuT05qQqB1cPSRIQxQCWbfLZ3ndwqemMHTwn4X6MrZWPddvW7X8JxzGy0b6mFRUp2dy1yeJ3y/Zz1yaLA7qTqNMbn8c5Oxciig5cajp/LhhJYU47JnTvzyObVzF++StMLP4PE7r354I2XZnQvT8Pb1zOxe++xPjVb+NXMmk9dBIIAtFQKW6xAq8rmpyfJUlSS5PKKu/z+Z4iVkvvRWA40Ba4V9O0s2r3/w4YAUwH3tc0rWPt9qHAdE3TzjyBr2lHMqs8DknAQwTRMrFEiQAqNiArOk5dQbBELFEg6tSpiBpYKEhEEc0yKkiJx67nur3MG3geqqhy/dKtHAweXZnNcatM7J3DI1uWsXDIRUiCCFh8WlXG0zti+R/qVmBbOD2kho4giQ4QJGzJRTCqYpr2cbO/+y55BtHSiQZKsAPlBDe9TuqQa78yaV2zZl6ClYe/Uzb5em395Fm6j+lPkxy/zZp5efGFPgnbfnflhibR16Z8z5JZ5b8erxyi9KVxCaE0zs6FpA2+hpJXbift7CL273ydVv2u4dMlt9P6nHupFHQyUtogiBICEDUj7Pzifdqn9CPT3ZYjNbtYt/8lBrY6H/+yuXQeMxt3sy4Eg2UcqjmM7G6BQ5QREDAsC4coYtoWkiAyd9MKlh38LN6XXLeXhUPGMnfTSkrDIa7uNoA2nnRkO8KezY+R2XoMd22yGsjNh04X2bbuqMXd48nl7HOeJRI5MfnUVMf18Uhmlf/2mG4Hf9mwh1+3zCFLdlBqRHlp/0Fu6dMBKdh0Te4/xX2VJAHZGSFoi0RtkLBR7SChSDlhvZLM1HZYpoEsyLz66oVkZ+eT1+MqVCWNiF5JSkprZNlFOJx2vGv6ycfrMf1JqKJjSdFYjL5tUl6xm/T0jpSUbUdR09AjlbFybzuepUf7C8hO60x59ee4lQwcYZlUpTmWZFMl21y7fFcDmbWgsDtSNATvzyRt5F2UIFGqh3E7ZNJkF+NXvNzAY+mRgefxxNYPOa9tV1IVlSo9whuf72ByXl8OvDzuaLK60X9GkmIZ60/U+t7Un9sfkmRW+Z83TcpVXtO0awB8Pl/dptOA+kE4fqDVV2w/YbKyGp8kHuvS29T4PvpnWxb2wS8wnp9NtPwIQkYz0q66DSGnNbbgptpRTtTSkUUXB0Mid6zaw8FghBy3yszB3Xhqx8q4AO6b3ZKgGaVST5x8AhwMRsh2pnBr/mB0y0TARLdMXt27lRt7DEQVJaaseye+ADCz50CEjx6ldd9xqF4vmamx3yhSVdNovXXBCrP91evjwr3jmfdStfJJskbdjZSSddzrlwSz0fYkwWzSv//xxmx9mnL/j6Wp9LWp9ONYmmq/TpTGxmu4srLRZ8+2T+zZs6woVk0JthlFkBwIniyaXTqXI/+eFHePzxgxkcP/uCFWtSK7HTnOy/l0ye3o1X4sUWL1lkWcdcYdrN66iK7tL8DlzKRj27PZsO15enb+JWWKRTff9djODBzubD598za6X/Y8YGE6vJSHw8zY8CYXtunK4Nx23FEv0/zUM86iNBKKhwZlqW4M2+LW0wdTGRGYUryDg8E95LhV7us7DsUBB4N7E67xYDCC7GrDoMHT+XjDfDyeXIaPmIvXm01q6ol7Jpxs4+en7u9Xydefum9fxf6aEMv8ZSzzlyVsv8nuQE4T7jf8+PfVsm12VQaZvObN+DN7f5/BbPxkNsFwCWMHz8GlpiHYNh5PLiUlm1m29DYgFuNe0P8u0tM7NonxcCLzATh6jyNVNdiCCNiEI5WsXfMQI89dxIZ6pSnPGfM8u/cvY/f+ZYwb8zIvL7+Z3478GwG5gpfX3EpVwM/Ys15pdK53KGQyY+1e/nzmNCxR5PPqMp7evpZSPcif+4+Ku8bX4Q9W4xBFftnxdO7/+IP473FP7xFEo5HEZHVL7qDTsDtJa576lXO74137qcipfO3fBJ/P1x64R9O0q7+n9q4EbiIWTyMCT2ma9mjtvg+AjHqHtwQ2app29jf5jialuDdCY6tB1ldsP2FOZYt7mqRjPz8bu/wIAHb5EYznZ8P1MzhkHWbh2kmUBv1cN/BZZqyPxIX0wWCEO1dtZ17hUM5r253dlYcZ2boLN656jbt7nU2OW22wCpvldJEqq8iCiIWJS3Lwe98ZTFn3Drf3HJaQpfnOjatZWPgnSsOVuCwbuTKAoVt4FAnFm9vASheu2Jcg3He/P4NOg4qI6mHKjnOfmjXzYtqNt2fa0je6vz+2YDyZLe6N0RT62pTv2Q9gcf9e2/s6Gre4N/7sCcLXP3uKIuIM7qPklclxJT374lnYqaeROfJOBMWFFarCClcherJIGXEDkar9qKkt499nhSsZmDee1VsXkef7Fc99PJ3SoJ8sdy43DniUKjOdezftxx88xG86d+AX5z2OaVuUIeKS4LAR4uGNS/EHqzmvbVeuXfFqggyb/tF/ubv3cG5c9To9MlpwQ94Ablr1Orf2KGTexwcTZOmf1h9gQaGvUbnpdWfhshz07XcbodARFCWdkpLACd/7pjquj8dXWNx/tD6crBZ3yS03OoYkQWjS/f4p7qvphMlr3k54Zu/ZsIr7867j7ZU3sHhVEZePeIpwuJwhQx9k5YopBAJ+PJ5cBg2ejtOZiSQ5j9vvpjBe61P/HntVAdu2ME2DZUuLcLmyAYHCwlksWzaZQMCPIqfE495t2yLVk4ssOROqcYhEGx1vVbrBwWCEO1ZtZ2LvNrz5mZ8Z/UZTY+iUhgM82G8kOyqP8MLOj9lSfohctxdZEONKO8R+j/s//oAnBoxMuA692o8gu75ybvdV136q8Q0s7j9Cb5o8bYGO30dDPp/vj8B1wHmapvl9Pl868I7P5wtomva0pmkj6h3bkVg+t+nf9HuauuK+H8ip9zkXOPAV25OcAKJlEq1V2uuwy48QliIs/DCmtAO45KxGrUFVusm8Tz5l5sC+OAQHU/uMpLnLzdT+XZi+ZmfcOv/goG48smEPK/xl5LhVpvTrxD937eLq7l3IUty4HInDzx+s5nAkxPgVb8RqvvcfRbbkbrTeeucxs/ls6UMJ5+vVsSz0X5e0Llm/PUmSnwbboTZax912qBD56nPdVHO4VmmHWAKkklcm0/w3i/D/c2L8uOxLZuMdOp5d78/A26ofrQrGxxcLStY9T+6o6XRtf0FcaQcoDfqpMqKUGVH+1K83qiQgCiLXLyvGHwyR63bx0MC+tPGk4w9Wc0GbrsfNNN/cFbOEXd21LzM2vI8/WE2q4mpgpcpyKkQsB/cUdOH+tUfl5p8Hd8UROcjKD++jpGRz3E0+SZLGcAjw4KBuTCnenvDudQjJt9mxmFiNPrMuVwugrmqOiWEEUNUMhg6biaqmI4pSvAycbUdp+lPnhtgI2FYUQRBxubLp1fsG1q19mN59buSssx5DEERwKJxbMJUNO/9OWK/isuFPIIoKhf3+DKITpyRgObK5pyCT+9d+Gh9vd/frwsLNnwGxOWILl4vLOnXipqVb6o1JL298rjGhe3/+b/cmrunWDwEa/T1MM4q7RQ+8BRPAmYGg18RCKL9DQuIkPzx2NDqQ6uAc2zRzBUny43UXCQ7H6u/ars/nE4CZwMXEUm4+CSwB/gpkAgHgZk3T1vl8vueApZqmPVd7rq1pmuDz+aYRs3B3JqasP6Vp2gPAo0AHn8+3APgn8DAgAduAocBITdN2+nw+D7AD6KxpWvg4Xb0HuFLTND+ApmkVPp/vKiD1mOtxAv8GZmmatuKb3o+mLn3WAD6fz9cJ2Av8GnhG07TPfT5f2OfzDdY0bRVwJbEfMckJYIkSQkazuMUdQMhoRtQ24xNZAJfsbnRl1eOQ8AdD3Ll6PZN75zNp1VqG5bbgll55PFrYA9O2EYAFGz9jRa373sFghAfX7WJi7zbcuXo9t/UpIBRNjL/LdXspj8QymsZqvr/Fk4MuQgoTr7delwVeECWMYGnC+Yo3F8mTTcD6agW8fv32ZFb5JEl+PIRohMr9n9D14ifBtkAQKduznKyOw/naTM1WtNGykFgmUlpufF/Vh8+RfuF0ZHcWzbqdjxGqoMPZ0/BvfIm0Xr/EFCUyUtsnyLp26fkgNWfW2o/wB0P878jh3LpyDf5gnTwKcdfq9TxROIhHBl5Am5QMTMukMKc9yw4eXdzMdXtRRYlFwy4mVXbGJ6VVeqiBLB2X14ZJK7aS5VS4pVcHUhWZkGmSpUosXTIxbukrHD6XaDS5qJikcaI2PLt1X3wMVekGz27dx6Q+HZF+6s41MSQarw7hVjzkZuUTCJdgWTqri6dz5lmPIcuZ2HbMmdM0I+zU/kXXblf8VN3/Tti2gBE4gpJ6Gvmnj2d18XQCAT/hcBm9ek3A7WmBYMOeA6sY0P0aXi++Hbczm5497+fF3UHGtMuiiyeNG5YVk6mqTOzdmXZeLwcCERZu/oytZbF7muNWcUoSU4q1BA+jKcU7mNg7j/s//oCFQy7CwmJfoLLR30N2puIYMYObNyyPu9DPKjiX5oKHb+hcm+RHwo5GB9oHS14znn012y6vQshIbSf/4aLXyMm+8HtQ3n8BDAbyiU0UVgI3AHdqmvayz+cbAPzL5/N1+Zp2TiemjKcDu2uV9ZuBaZqm3eDz+YYTS47eVtO0Sp/PNx34LXAvcCnwn+Mp7T6fLxtoTUxvjaNp2vZGDn8M2KNp2uyvv/SGNGnFXdO0sM/n+z2xlQkn8Cbwr9rdvwEW+Xw+L/AxsVWTJCdAABXvlUWYL8zBro1xl64sQhRksty58QmtEQ0wpV8nHly3K75qOqVfJ8JmTOH2B0M4HQ7yMtO5rHN7bli2Om6d+suQgXGlvY6DwQipioI/GKK9NxMsB88M+S1lkQCvf/EJv+yYzxPbjo55f7AaEwsJMVZv3XQRqwoYSzLT0Ao/h7CQgWl+vWA/tr3kpDhJkh8eXUglrWUvdrxybYLFXRdS+doJmehIUNChtk67KJF98SwqVy0iJf8CRE8GguSk9ZBbsPQAkisdOyUL1+A/8uiaIkqDfm4c+GiCrDvbdwN3rf4orqgLghD/Py8jnat83UmTVQRbYfFuP8v9n5DrdvHgwAEALDu4N5ano+BcdMtEESUOBKvik9IXdq5jSr9CHlx3NF9I6xQnB4OxUKQ7i4++2/89um+thd0AZKLR5KJikuNj2jZlEQPRlmv/oCxiYNp2UnE/BsUQmdX/3Li7fK7by329B6Lt+juj+k9DFCREQeLcUc+w8ZOFtO8wOq7gxhbR5iAIJ+ddDZtuVGcmAKmpbeJx7SUlm3nvvesBGDPmb/TseDH/WnYDHmc2wwseZt6Wz7msc3seXL+RvwwdgD8YqjXcrCMvI53reuRRGtYB4nPEQNRsNA4+VXHhD1Zj2Rb/3rOVX7Q/gwUDr+DLQBl/3bGSUj3IPb1HcDBYw9RapR1qDTlr344Zcn6sG5bkm1EdnFOntAPY5VUYz76ardz46zlkpA76jq0XAv+naVoEiPh8viHAPk3TXgbQNO1Dn89XBvi+qhHgA03TdOBw7fGNZZnUNE2rrP3/WeA9Yor7VcCUr2i7bgLzlQn/amPgC4G+X9PX49IkFXdN09rV+/+/QM9GjtkIFPyI3frZEDVtql3ZeK6dhlSbVb4aFXSY0H8OT9RObqv1Uv6528/E3m1IVRSqdJ1/7trFmHatAch1u6jSdX7n68SD6zfiD4bIy0hnQn43FFFq1FofNS2eLBxCKOxk5gcRDgckmnvSuHPEObyxfy3tUzL5U++RiIKIjY1LEjFrfaMkScCWg5gY2MhEpVYNreZ6cjU2SZKmSjhs4XS1oduli7AtE0GQ0IVUwuGvf26DeMm+eFaDGHdLlLFti7TBV1Pyyh1InizSx/wJSXbh//hF1H6/oVr3s2Lvv7ksvwiPkoZlmVzd90GeXj+F0qCfFKUZ/uCh+HdZtk2u20WmqnJj9748vsrmcMCmuUfn+sH5lIYjbC2vYMrqj5g7ZBC/6nw6oWiUDMXFlHXv0Cszhys69eTh/qO4fc1bAEiiyfzCfBBsVFEA22DO0DxckkSVbvDiji8pDes4BIuo4UGXxZjyJQsoWPEFSUkSj+4TBBTDOqHFyiQ/TxRR4Jb87sxbEa0dozK3DO2OIlqIzhAmBhIygpFcADJNixYK3J/XCUXNRI+UsX/vS3RrN4p/L7uRqoC/tizaHCKRCj75eAF9+xWhKmkY0RCqkopl6Rxd8D95ME2bqNIchxBAFGPJ9gL1arh7PLkEggdRaIbHmc2Q028gaAQZ0651fH5XJxfrFjW3llfwz127eHxEPlHLRhCgNBQmQ1Vqcxwp/K5rq7g3Ua7bySMDx+JyKAxt3pOpb5scDkRp7vFy94ixVJiHWLDtQ27sMaBRF3pLsFAk6ZQfx00R2zRz65T2+LbyKmzTyv0eUtcfWwu1Aw0VZIGYTmvX7fP5fMe68dW3lsePO4ZQ3T+apn3m8/k+9/l8lwAtNE1b08jxdceW+Xy+PcQU8uV1230+XyEwWtO0O30+Xx4wFzir3uLAN6ZJKu5Jfniipk0lSuyDCXUW5zS5NbcNWYRpm1SES/ltl5ZMXbclbkm/p28vHt+yPeH/G/K7x5X2Sb1OJ2zaPPLxbu7u14UH1h2N3by3oAuqQ6AqLPBYcYTDgdh3Hg7YzPxAZ8a5fakwIkxacTRW76FB3chRJCzTokbYz8LiSfFkUtcVzCXFrl/67dQW5lY08pXJRqJ6mPLKZC3oJD8t4bCFt1luveQ5J6Z06roF7jY0/81TYEVBdBDEi2oGIBqm5D9TMSv9ZJxVhBmq5NP3p5I7+n7mfXw31xbM4syOv+L93X9nYNsL8KqZpDubc02/mUQtHZeSkjAh/R9tFw8O7EtlyI4r7RCTVY+vgqsGdOf2D2Px7+WRMNM3vM/D/UchCSI39hhAttPDnWvfpr03g4VDxlIZgbuKd8Tl2iND84hYArM+OurNdE9BF9IcBm4hwgFk7li29Wjc+6BuZEuxjPIlWI3uSyrvpyaiLTNvReL7dN6KKDNHq8wp/kPi+1I6fqnUU4FYLXCLTNVFMLKfTdufp6DbVby9dno8+VpVwM/iVUVcVvg4H7x7fbwc46DB0wkED5GSctpPexHfAUEIEAmXs2fPmwwrnMXy2qR0rVoV0qvvLUT0KhTZQ2HPW3hzzT0M7D2VDGenBnJxyur18TnhuO5dkNARRAf+oMHfd/i5qntrHhjUlVDUSsjfcW+Bj8WfVtC+V3MeX2k0mAP+boDIlvJDVOmRRl3oJTOEEq1Ed5za47gpIkiSX8hIbVdfeRcyUhEk0f8Vp50oy4GJPp/vCWKu8v8H2D6f75J6rvI5wBagBMirPe+iE2j765JWPEPMo3v+CbQ1C5jj8/ku0DTtYK37/Bxgoc/nSyHmMT651vD8rUkq7kniSJJAyPiSxasmMWbIbGavGEe79Hym9LoBl9yOTFcWkiAwo6AnDkEkGLXIUlUyFJW/Dh+KV3ZQpZtxQV0WMbilVwcynDLNXSoicO0Hm5jWr0dcYNcR+yzFYvN6+uKxeu9+foTLO7fFEizKAyZeJZvSoJ/SoJ+FaydRNOhZME989du2LTxK6GcZ2y46VNbOP+O4+wtu+oi0dFBkZ8J23QhTWZFU6JP8OEiSgB4oxSOHv/EzqOsWOp54O24xgGgbCN4WcRd6KSUb2+VFdmchuTMpDfpRHW7e2LGIMzv+ihcSMsnPI2ibqKLO3MEFHAqYuCSZkGngcThIS3FxOJAY0nY4YJMmq0DM6yjb6eLW/ME4BJGtFYd4ZPMqbu85DIAzW3YE28FdxVsS4j0PBCNxpb1u2/1rd/LXM/OpsSFs6dzSqwMv7viSrWXV3FG8nScK8wHiSnvdeXX7pKTifkqiWzT6PtUtEpIvfpv35c8JSRIw2M+/PpgUt6yfWzAVl5waV9rrqAr4EQSRgv53ITtcGNEQDocLSVL5Gk/YJo6BYdSwffuL6HoVZ541H4fDSdCo4p/Lrk/wOPA4s9m4fQGFAx6NL2r+5/MvAXhkSH8coohlRXh/56Os/uJVppz1HjPW7OKefp2p1KO09DipiITJcirxkKAZazVu6dWBslC00TGbprjpkdECt0Pm0UHn82Wgiqd3rKc0EuSRfmchCV4qLBuXrCBhJBcrmxJed5H8h4vqx7gj/+GiErzuou/atKZpr/h8vr7ABmIl1uYBHxBTiKcTS217iaZpeq1y/w+fz7cJeJ/E0uGNsR1I9/l8LwJPN7L/ZWAR8OIJ9HOhz+dTgHd9Pp9V29cnNU17qtZFvhOxBYiJ9U47oGnamK9ruz5JxT1JHFEOUvzJQob2LkKVvUwe+jQIAh45DUl0gB1gf00psuTFMKtpm9aBP3TryqQV2+IrqnOH5jG9T3dUUaRCN1i0Yy9by6r515gz0G27Niu9QXOPnCC4m3sEJMHmV5068vgqK+7yd/vwtjy1RmfNlxbNPe24echc/rN9Ep9VbKY06MfCwKNwQoq4JAmESnex8z+TErLJnyqrt1Y0giI7mf2/fRK233bFBjLSSFrjk/zgSJKAEt3PtteKvtMzKEkCbn0/pS8XYVb6aXbZvHj8u+BOB0miZcF4QuX7yHLnAjCw7QVxpR3Al12AJCkQhbKgH0FI4+liR63sUZk4TMIWQjT3iA1klWFHyXW7mNI3n2nr36VUD/LooPN54/Md/GXAeXiFFGb1upDPgmVU6pEG8Z4uSeJgMEJepjfuSmrZFmWRKHeuOupxVJeteWtZNaYd60NjsaMmJGM/T1EcYmxMHjtGHWLicXXvy5PRzfv7QJSDLF46KcGy/vba6Vw+4ql4CbQ6Uj25RMIVpKd3xrJSUW0JbB1BKOfkTo4mY0RDtGo1gtNajiUYUnA6XazaMqeBx8HZZ9zFy8tvZsu2eTw04Abu+vBj/MEQHx0pZWzbbFq5RMK2Ts9WYxnS8Y8okou+zdPwyA7uL25chsXi3GXCltmoXG3hclF0+hCmrHsnnoPgz/1H0Ux1URlUuesdg8OBVJp7otw1XCVdiiSV9yaC4HCsJif7QuXGX8+xTStXkMTvLas8gKZpdwN3H7N5eCPH7QH61dt0S+32accc167exx6NtVmbzX4E8J6maSdUuay2ZnuDnGuapr0AvHAibXwdScX9FKR+rHj92DdBsOO1jVPVbC7Ou4nnP5pKadBPz5zhjO4+jZDtBlsiZKcTsSSm1LMkZTkVrICD9e+aVFXbpHplHhiTj+A2sIAUB8wZmkemKnH7cIWHl+q1k2SBu0aoiIIdV9ohtgL78NIIVxcorPky5gr46EoX957zGH/bcCPVegkObHa+Mu6ElACnFGTna5MSar/verOILhc/U5uo7ueN6FCPu8+hOGkYRpQkyfdL7Bks+s7PoFsMxpV2gMpVi8g6bxpV617CMGowQ2HUtFbsf3cq44dNRRBEvGrM+t4uPZ/zuk8m090G3YrgEFVcjvZMe1dMdDdebjJztJObBws8uioSl1U3D1bJ9SrM9WgKjAAAIABJREFUG9afw8FKspwu7ug9DLekMPn0QZjVMq+9Ha2VgV5GjZYZlpvJ8nrJOm1shuZmclX31lTqsWSfWS6VxzfubZBl/sGBXYlYFkqtq3z93CF5mV7G5bXBFmwslwNZT8a7n2qIwM2D1QZj9Bi9nSx3LiLySa12fhds22jUsh4IlzCqYDpvrZ1az+I8F5fDS1WVi7fetamqNkj1iowemUFq6tfUrWzCRKNu0lI70L3Hg7yxpG6eJnD22VMIhkrwl20GYvclw9uGji0LaddyCF6hhCcK+2FaAjWBfazbeA+7nFnk9ZjGjPVHyHIe5KaeLsbltSViWtzVtzN/3fI5W8uqeWDdTuYOzaMiEiVkmli2hSo6Gh2zNgZhM0qW6sYfrMYfrOaONW/x6ICLeeiDRNf6h5bqPDBSQTCPV5kryY+N4HCsJiN10Mnsk3IMjwAXAKPrNvh8vg+AjEaOXahp2sIfo1NJxf0UQ5KExmPFpZaYgh2vbXxZfhHPb5gat04VdryGsoiVEJP50KBucTcogPFd2rOsVmkHqKq2eePNCHkjDGZu0pg5uBsfHSxnY2k1RX06cvUgG5fkIGRGiQgm5WGlUfepFEVI+FwZcTAm7yGaOyMcXj73xJUA24gfW4de7Y9Z609RK0R90tNkKpJW9yQ/JN/TMyhYRkJ2ef3AFiqWzifj4plsf3k8sjuLjiPvxwiWEly+gLTR95OmZtEzZzgDO05k6vpP8Qf31tZnPwNZcHI4kFie8nDARo/avLDB4OoChRRFoEa3eWGDzlUFBuNW/o1ct5eH+4/ikyMHaOHxkudpyZK3E2XgW0sMJo3tzM7KTzgYjDA0N5MMVebWPh04EIgkyNR7C3woksA9q3ckyNlntu7jcl9LPA6J+wd25Z7VO8hyKkw4vV1iDfjaeHfLtjBdOlHbxCFIKLp6SngVnYropsALGyINxuikoWq8ckLde14wTt2ygoIgN2pZd6lpSKLK5SMWYdsWouggGklBEBTeejea8CwveUfksku8xDxzTz5M00aWs3ljSeJ1vfeei6EjbmVx8Tggdl8k0Unf/GvjyYqz3Llcfcb9uASDg6WbOXfIX7ljVUwO3dq7A2HT4voPNiXIsgWbYh6X1UaU65duIsetMmNAV7IUJ4+s0BuM2YlDHczY8D635g+OJ/X0B6uRBIXDgcS5yeGAjYUISTmX5AdC07RbqLXY19s24ifqTpyk4n6KYcvBuNIOibFvlmWSqmZzWX4Rud4OXJZfxNs7n2dv+WZSXa24Z9mOhNjKu4q3M/mMThSt2ApAuiLHXwZ1uN0CHVM9zOzbg0Agyi86n8b5HSwmrdia4PKZ41b5y5Bejbr81eiJn8sjOnM3fslfh3encs+yhO+rrwRIkogoKdi2gCDYCKKB4s1NUBwUby4IX1M/+iQm//ev4/J+fTKdNxedwZjxH5G0uif5QRHk7+UZtEW5QWk4M1CKbZno1X70aj/71z9D59EP8+mS2ylf8wyZgyZwcf69XL98/TH12T9i3uChjcoeEZOKkM1DH0QStpdFAgBkKW5qghbnNM9jb6CUGsOgqjq20JjTQqRvHxmnU0AWLKYNaEe2MwVJEJnwwSYeLcyPK91APAZ08hmdGsjZW3p14P61O5l8Ridap7iYOzQPRRK5cenmBvHuC4fns6vqCyatm40/VEKuK5s5fYtoRnZyUvszRBJpdIxKIrH3OgZiMqs8luFm7OC5LF41qZ5lfTZhvZrXiyckxHc7JS+WLdKqpcgZfWREQcCybT7aYGBZx/oynFzYtsjZIxRSUkQEAWpqLFZ9aOBWWwAxpX1UwXTKQwd48qO78arZXJR/D24lk6poDW29bQBwqs04GNzHLb06UKlHG+TsqItn/8sneygPG/Ht9364gyeG92l0zJp2FH+wmlTlqHdgrtuLaeuNutYjGlzz4TSy1HTGd7mENp4cFFQUXfnB72OSJD8VScX9FMPEiCvtdZQG/ViCjiK5uSx/UrxEUmyVfjZijUnziMCs3p3AsnEhUBqNMn/3flqnOOOum4FolFSvg6pqm5wWIoMHyCiqwGuLI7UuWQ5ajlGIOkKNxmmGLJ3rBzvqxbgL3DlC5R+fxGqENvcIXD9YZMHWvRwMRojawnGVAEkSiUZV/vO6HncHO390Kr6xj6Mtvj7BtT5s/nytEC7vaQkx7bddseEn7E2SU52w6abTmDnserPoOz2DQctN1iVz4u7yUlouWZfMwRaVuEwo3f4a4bI9dP3lC1REY5VXonZMWc/LTOd3vk60drs5DQeyFeWJM6E6ZHMwJPDq5yKX93KgKFHuHKEw84OjYT3XD7GZv72YC1t34+o2Q1iyxGBFdYRUr5fRo2U6tI8SDMKgAQrvvR+Jy58xYzJxiFWEzVj9drM250d9DgYjuCSpwbZURY7vKwnpzFir8ZdhPRo9PwqEog6Kul/Lc7v/wZaKXRStn8NTA6YhhZIT2p8bgqhz/zkK3kgEGRsDgWpVQRR1rIALcNW6x/8833EngiQJiHIQp5DOFWc+jWkZWHaUULiCN9fc0yC++4oRTyMJEj1Pl1n8+tFn+LzRKrIcRdd/4gv6lkiSSDgi8N4HR6/pnLNUhg+TSUnJYNyYl6mo+ZIVm+ZzVv9peNVsRnX/E9M+Xh2POf/LwPZccs6/cTubk+M+RKoSW3TNdspMz2tHlsMRnx9mOOV4jHuPzBRu6tiSLIeDDCPC7SNEHv6AuFy9fbjMC7tWUpjTnmw5k0WDf0PIDONVTZ7b8z9cP+RyHl+pxI+/cWiUMqOEfll5jG41hBkbn0xYqEy33T/x3U6S5IchqbifYkjIcfe5OrLcuRys+QyvmsHbO5+L70tTssmocCM/twUr9RDtL8jH+J912GVBsjLdzPp9f0xR5PER+RimjSTAyFEyG9ZH6XW6QtS0eXdJpIHr/OgLlUZrvB8Khll5oIxp53SkKgyVEZvluw3G9VO5tKfB4VCYBVtjrlc5bhVJEI+rBIiSElfa6777P0t0Lv9FI7XfT2ErRJIkPyamaWOqreh26VPYZqykW8T2YurfLPLWNG2CSkuyfv0MgmVgizKG5EERgnQeM4tP35yMXu3Hk9ubkB0hHA0iiTIlgQMMy23BZZ3b8+9P93J7bjuE9zYjFHbGeGk9zrIg7TPdTLpmMOUOmYc2bKY0HGH8oB60TvHiEG1mb34PgAkdh7L4tUQZs2SJwcUXqVSU23GlvW7fm2/qnHeRE8lhM2doHgKxnB/PbN3H1rJY2aMct0rINBOuNcetUqUbMRd7Z2ySfEuvDlREjEbl6OfVIYpW7CHHrTKl4Hoe0x5nS8UuTMxkArufISrgqarGeKqYaFkQMdNN9jWDCGS5TlKH7u+XumzydYnpUj25/Pqs5zCtKB5XNpcOm8+6HS+yZe9iIKa8W3YUyxR449j5y5IIl12iAien5i5JKq++nnhN7/43wohCBbfLRkDk5eU3A+AQHYzqenNcaYeYh1EoCoaVimKZPFoYy+lVHjaY1bE1zufWxOeHj10ziIBLZeaG3QjYzO7YGrV2v53ppuW4/swcnUrEFInaBs/vWkmVHubaLudw37s6hwMOmnu8TBxmsadmP3/b9wz3jryWaj1MwKzBEAPYtsQffZcya8vz+EMlAPhDJRStn8PzQ+4jmbIzyc+RpOJ+iiEYbq4rmMvCtUdj3K/sPZVXty2gKlLCZflFbDwYcz+/tP0NyM9uwS4LolzSK660A9hlQZzPrcGcWMg1xUezyj9WmM+woQovvxLhgvMUhg1RcDoFwmGb9RsMDh6yCBlWgxrv9xR04YlNn3FN9w5MezeS4BJVvC/MjHNl7vxQOxr32bcVHv0QUbVxRVwQhQZu+1XVNqYFET1mhYiRVNrrc7w68Mka8Em+DyRJQIp8yfZjFtukb1HZwTRtqs3YsywhoOpfEgoe4dCWl+k48n5kdyaGJKEDETMEBry1/RFu7reAm5Z/yPRu3XE/tw75kl4YL61PkG08tYqa3w/n/LYduf3DYm4pXkmu28W0gnz+0PUMBMOBJIiMPFtNkG1V1TZVepT0DEej8iesOwhbeoP67U9s+ozSsM7Mwd1QRDGukNdlZV59oJQ/5LXh1uVbEmJI5w7Ni4cd1W8LYtb3B9d+wc19LmfOticRRRFJEpILlT8zPGET46nihPFrPFWMZ+LwpOJOw2zybZoXUBM+wmurJscV+QsHzwJgy97FpHpyEQUJy3ZQVZ2Y9yI2hzh5U2/ZiI3KpbRUEQSJ8up9pHpy8TizsaIRmnna4Q+uiR97fd4gQlELhyBQEo4yfc1OspwK8/p0Qnpu5TEytBjnxOH8Pq817mAUddHqhP3iM2tIuWU4j+9Zy9DctlzYrist1Cz+9JZ+TJJQkYdH3Y0pVnHXRzMBuKHr5UyvZ2G/t+e1lEYq2VKxC4gp72FTR3ErRIggIiLjQIrImKYdK0mqRBrExh9ve5IkTYmk4n6KYZo2qUorJg1ZRFnIT0Cv5NVtC9hbHssm6lUz48emOTKwyz6PfXArcaFbh10WpDpoJMQ1fV4TorUicMF5KrIs0KxZrHb6nr1RBg1Q+GSTzpFwhEU7P4vXeE9TZEpCEW7u1Z5mqod0V2LSkn9vNhBtgXmnq9hyNoTLqF4+hU+DJbFEdI0o4oIQcwOr/5JK9cbi/pIcn+PVgS+4KRn/nuS7831llYe6Ou5BBMEGwSIatXFmduC0M/6AESxBVFKwJBUbeH7DVG4etIA0ZxYQc5fPUZwxmXYc2ZYixeq152WkM75LdzJklQxZZulhjeHpeby8OHw0K/OZKsUf6rjd4HSImJbN2PNV1qyLKfQ5LUT695NJU0RKqyMUNE/nvKxmZMkKVcEo9w/woVUEeHrLPv6Q15r5w/MJRU0UUcQhCvyiS8t44ic4GkM6b1gPJp/RidM8Mqrk4E+rtbj1vu64TLUlc/oVISIQVANIgoQkiKhRFduCkBzCtEwkUcJluLBMG12JgEAsW71lISHhNJ2EpXByUtvEEEy70fErJH8bIDGbfE5WPr16XEtVuJSBfe5g47anOVi6mddWTebSYfPZd3gtYwfPxjQCOBzQp5dEXvejMe5btxlIon3SvgnF2nmR2y0weIBMSoqIDYiiTdQQ2fnFB5xbMBXT1Hl1xUQuPDOWgLPO4t7clcLEFWuYN3QgE5dtjddnD4YMUhoZg1LUorPgQnLqRBrbb9mMat2d/9u9gV926kpZuIbDgcTqN4cDNuWRIH79M0ojFRTlXRl3i4eYkj5j45MU5V3JbevnApDrygZsIkRwSQpBI4woCURUHVWUOaJXUfThnLjiP7//nbicTqK2SdgyqIkGqdRraOlqThppSTmXpEmRVNxPQUwxgL96D3/f+FADl/l0ZzNuHPgob+xYRFQwETLdsUlBUD/6fy1CppvDRuIrLFNVkKMyry9JjKHK6+5g6zaDYUNUHtq0h61l1fzlkz3c3a8L963dGZ9sLh7Tjyv7KA3KhCiSweeLxzW8mONko7ZMnfNHq/xnSf0YdwW3WyAYbNhMkiRJfgS+p6zydXXcq1Y+iavgCg5s+l9yel7Bp2/eFrfkdz5vLg5RJWJHKA36USQ3Z3a9m33VAYbltsCtqgiZ7uPKthpTwCTKnV37suI9u1aOmJw/pjsfrk10kX/v/QjnnqPgcAi88Vqi7Nu+w6BbV5l3/xvb3rG9zOQe7THml2OXhMnMlhBvcvG3T79kS1k1v/K1Ykrx5njizxy3yrzCxuPZq4woRSu2smBEO5q50igNJ7rw5rhV0mQ3FjX8ecuzLDv0EbmubO7rfQM5ziwqzBomF8+NT2Bn9Z2EV3Ezd9uLXNF+VELc6Ky+k1i07d/xNpIJ75oGtiQ0On5tSYBT/LeRJAFdUrjwnBcRzAhhUeGa1Q/Ex/QDPSfBxrkcLN2MJCpcVriAbZufp0uXX+Bw2Pi6NIxxdzhO3nsqijbnj1GwLDAMgVdeO7r4OGqkyqC82yir2Uh6SiuqAn4UwkzvM5ipG1bhD1Zj2Tb+YAjLJkEe+XWDLo2MQcdBiMwtQZyU0ugYjQoS//z0cybk92f6xkcY1+G3NPe0bpCErjpaRYrDzcN9b0W3jLjSHv/+UAkZaioQU9qn9bqO8kg1z+x6lfFdLkEVZSYUP4g/VMK8gtuZufmZeBtZajqlkQpe2rOkgcyb1us6UlxuCCZVpZ8rPp+vPXCPpmlXfw9tLQX2a5r2m3rbpkGsjrzP5/sMGK5p2mff5XuS9sdTBIckkCbpZAghbAze2LGI358xgyx3LhBT2q/qM52n1k3h7xsf4lc97yDd3RL5NwMRMt0Y7+1A/k2/2ESXmNAVrhnES18eSfiedFHhzSUNY6iqqiCveyw+c0z7Fvx91BlMPqMTCzd/lhDfGbXMuNIOsdXWR1dFsGwplniuHl+Vjdo0LRyOCJdcJPP736pccpGMwxFBEBq6uUmSgEcJ4ZGrSHHq8f89SghJOnnd4pIkaXLUZpWvz7fJKl9Xx919+gXsfn8GzbpdwMGN/0uboUV0veSvtD/zTyCKVIcOEQgeIsudi26p3LX6Y57evpOb8nsxf6NI+MpBGGv2Iv+6b4Jsi1w1CDVdxWkLcaUdanNlvKnTvWusvzktRM4frTLybBVvitggJvbd/0boX3BUaQfo01GqVdpjsex2iYk1v4Kb2reNx7MfDEZo63Xx6nn9eKawDymWwoJBPcnLPBrKkuNWKQ3p5LhVMtVUPA6bmYO7kuNW4/unFLRm6sa53Lz2YS5vfy4Qm6gGoiFMLEojFWSp6UBs8jt5/VwMO8oFrQsbWLUmr5/LBa0L45+L1s+JWeaT/KSYkop89aCE8StfPQhTUr/mzJ83kiRwRCzh6tUz+FXx/RyyBe76JHFM373pKXp2v5pUTy6CILJ65VT27F6MrLTFMBqPcTeMk3fabJogywKhEAkyqara5q13IpimxDvr7gNi2eVrar6ghSIwrWd3nhl6Fg7BZFhuC0SBuJwBmL97P8I1x4zB3wzEWByrsW4sDsfnknX7w1cO4i8fw035vVBEhYld/0i66uSOEXIsYzwxpf2moSZuOcr0jQv58+ZnaaZm1FrUj5LryqaZmsG/hs+mKO9K3vhiBRVGNbfm/RanpKJb0fjv7nI4ExT/33e6kGmfLGxU5k37ZCFRITFcIsnxsaPGQLu8pNgqPbTXLi8ptqPGwJ+6TydAW6Dj99jeL3w+39jvsb0GJJeRTgEckoA3VIL5whyi3jTE3/2RX+TfStTUGdf3AVLVLA7VfM4rW+fHXeafXDuZe3v9A+MfJo6xQxFSwLZE5MuHITQT2ReJYHlkLvO1RKsMcDAYYVhuJk7BQVV1ohW+qtpGlgVEMSaMVx0o4429hxiX1yZuIcpxq9zb7zRCRojDgUTL2+GATdSy6XzhfD597Sb0aj9p7QtpO2QStm3gUWg0yZxpWphm+CvvjSQJKNH97HytCNmdRetBN7HnvWkJ8bf6t4i/TZIkSUPCppvOF87HqNqPKLuwjBByastvnFW+ro674EqtfVZbkNPzCvb+dwayO4vcobdgOj2EQzVYVpSbBj6GUWst8gdD1OhRPvzSpjys8ocze9PcA84bhqOKEBEgrMis9u/jnBZtqaoOJ5R2C4dtUr0xpb1+5vhfXuI8bl6N+ts9qhBX2uuwS0yaK554BuYct0pJSMetq6x4r85ryMFd53TjoW3bKQ3r3N2vC/+3cz939+vC4xu/5OoebVCkap4YkceBYBmVRmU8MR3EJrcXtipskIH53p7XsmBHLPu8P1SCKAikKimNWrVSlZSEz8mEdz89gg7GuzbKdYUg2mAJ6G/qSBd+v98jSSK6bGNiIyGgGAKm+c2SSv6Y6Eok7g4NDRU2iI1ht7sFYwfPZsOn/+D03hOwrCigHDdPjnWSTgUkSUCSothRBVmm0WsTcTC2cD57DqzmijOfwrZtkJw0l1IBBy7JwbjuXXhs01YeGtSNu4q3czAYoSRssD9FpvnNhdSEDDJUBWNhEGt3TOm1dkcx/gHCjSOoCFmU6wLP7hDQSix+11fmpqVH8yTNHZrN9YUVCLaDTKeHMuMAUzY8hj9Ugj9UQqUR4N6e1ybIsIf73opDlHhq58sA/L7zhZTr1eyq+oLXv1jG+C6XcGGrQl77chmWZTGv4HZcDidVeg0tXNlx2dbY+DBtK6konQB21BhoH/ziNePFR7Lt8iMIGc3ayb+79TVyWl8oOOTV36Vtn88nADOBi4Eo8CSwBPgrkAkEgJs1TVvn8/meA5ZqmvZc7bm2pmlCreW7JdCZmLL+lKZpDwCPAh18Pt8C4J/Aw8SyGm4DhgIjNU3b6fP5PMAOoLOmaV+lWNwPPO7z+VZomlb2Xa77eCTH4ymAhwjmC3OwvWkc+cWlPPHhhITEdEGjisdW35xwjlfNBtmBXWkTfUPHMSYFwSNgO2xsUeI0VWF3ZZAtgSqeLeiJRxCxBIHSGqvR2HLDiCX+WLo8wvVDO7ItUEmm08H84T2IGDWUBfexes9cLu1xX6P1lE3bRpDT6HLxM4iihRmqYMer131nBbt+zG2boUVxpR2+W/ztqUp6uowsO3/qbiRpwthRnc+Wzkx4dr/pm6iujrsdqkLx5iI6nOx683ZkdxY5wydTTpi3N82ib9tLSVGzcYkpqKKDXLcLfzDEkXCI5h4XWonNnbVzteYegd8NCHH7h8Xkul1M7JmHgUmH9iK9Tk8s7Xb+GJWhg2Xefveo1SoYsunYXqRPRwmPKqBjIwkCqZbNhMtU9IhNVdBGx0bNlhKUdyFbwuV0sHDjp5SGde4p6IJgSKx4z0qwii171+ThS3qgi1GqdIPz2reIey19Whngtr5pZLl0lh9eyYt73oi3n+vKRhIkrulyCXO2vnDc+NBcVzaWbVOl15BbO6Gt30aVXpPY5jdQ2yVJQJUjBEQTw7aRkFF0Jbko+h2xJcAjgaUCAlg2eMzYdvNrTj5BJEnkiBDhjlXL8QcD5Lo9/Ln/MJpJapNV3qO2mTB+jzemPXIqKaLCR9qL9O78S2qCh7GIIImORucy4klqcFcUnajpxLLs/2fvzKOjKNMu/ntr7SXppJMACYjsBFkEZAchoLjggqiMijvouAFuwIiMCui4i84IKm7gMjMuoyguqKOOCgICKoKgNIuKLAmQkKSTXqqqq+r7o5MOTcIo6nyDY+45OSddXVVd3f32U+99n/vcB8tq2APIBRasf4iTj7gUMxFjydo5dDxiEn/8dBXF0QiPDD6O21atpTga46wObZnSqz1eWSZsWtzx2WZydJWrurfBdVSUkTJCF7gRl8SiaghIKEIjqEHccQGLpn7B9kg0zbvj+iXr+UtRR4QURyFKjhRI+852xUp5fdtH3Nz9Mpp5c9ke2cXdX86nzKjgz33/gOVYjP/kzrSFycc3LmBy1ws56bDBqJLCzDVzU8/f3ftaipr1OuD4UNyDU4P9ZlFVOauWtAO45Xuwnn0gT7ti+iyCeQN/5tlHA4OAboAKfAyMB6aGQqEFhYWF/YGXCgsLO/7AeY4kScazgS01ZP1qYEYoFBpfWFg4FOgItAqFQpWFhYUzgfOBW4AzgTd+gLQDLAFygdnAeT+w70/CrzQENeJgILk2bvkeYsedzCNrbkrVtQf0PCzHJFMLpiTzAK2D3RjR5Y/cvPFVzGu8qKMzsZ4LY/2jCmELrDvLSUwppfUcg/P9+Xiei2BNKcW5ay/ZMYdRp2oEMpPZ9do6T68XwOWbbx1sByYtWY9huzy4Zh0+4XKYqnD2EROIrnmCG4dpaVKpqwZJ/HntZiJCQ4qVk9izOVXLCnUE2yP/++J1WRaYkbJ0Gfw+NbeKJ/Bv6m9/23ASBk2aZB7wL5iVvLmpqodnnzkq7a8RjaiFR46m2jfCj//t7o/aPu7Rta/TfvhMHCuGWVVM094XEbYqeGfL3+nf/jL+tG4VF338PFcs+xuRRJS7BhxFgc/L4uJt/GHo/nFG8HToKyBpXhfUdUrtCIOP1uq1dntjkUFmRrpD87ffJjixi0LOExV4/lpJbtzFv7AKUWLj3LsX+ZZScp6oINMB5bogIi9JekWejDQxi6jH4ZZ+HXl4WDceWfsdutSwA3RZrBzbtbno3S+YuuzrVKlRss+7j8mrZnFm6+EUNUsaTdbWak77fDaXL7+Nc9qcSNfs9qlz1mabajNXtmPz+raPuKX75SlJam2N++vbPko9ntV7Epr54+TYsiyQ2cN3sZ2MW34bIz+4lks/mc4eqbSxHOlnwvYkUPv7MB4oJ37jHowHylH7+7A9v5zE11RdbliRJO0AxdEIN6xYjKkeuosuipDTJNVPbX6NGT2uSBvTtx95KctX30vCMTl3+NMIIaFrmazc8GcU2eHkEXraXObkETqydGguVPwQHMeHaYBpumQF4Lhj09/b8cN1Fn9scPRhFzB3xWTKoztp3+Zs/vjpKnJ1D7MHHUdTTwbXdO9Kl2A2j3z5NbkelVtXhpi6LKkCOqtjC57bsB2l0sV6Noxx116s58Io52einpaBedde7Kl7aDannFs6KdxyjMYTX32Tdp0lUQOBwpXLb2fq57MB6n2P57YdgeUkmPDJnVyz8p6UWqgkVsqUTx+otzB5assiEo6N4ZjctHpO2vM3fPpnru18foMxLxnjtP/4d/O/ANexC2pJe2pb+R5cxy44wCEHgyLgxVAoZIRCoWrgaCAvFAotAAiFQp8Ae4HCHzjPB6FQyAyFQrtr9s9qYJ9QKBSqrPl/PnBuzf8XAU/9yOudBvT9T0nmGzPuPwGyLJITzV9JL3AhSYhgE2y/P0Xa2wS7MarzeP615TmOaTeGy/vdx6MrJlMWLebEThO4ZfUiimOVXNa8CO3JZHZIHRPAfLIyrTbTnFOR3L7awC21EXMryJyWw/BhGhmZUo2Lu0s0CgI46ww6+rovAAAgAElEQVQPsgRDCnKwXZerunUBWSKggHBtfD3HUIXFhf0sAppK2LRSvduv7dEaxx9Azsyh5ZBJlHz6FJFd6wBQfbkg2fh8JlE0LAcUIdBsgWU6KUn8V6/VtaHqMHI2yF4KRz9JIlaO6zhomQVp5P2n1N/+L0JS9AM6zkOj63wjfiT+jTmdLPt+dFyt7eMeGD4VWZFxHJMjznwS15eFkahmSLuLqLR1ZvQ8i0oryjObPuSaT/7O/b1P4aEhRyGEzgNffM4F/dvROjPAzkg1c75ax/ryCgAKfF5yPBqlsThRN9EggUYkneNVNSmfz1VdEg+Wp8VKdUwAc156zBSPVBC9Joj+hxxsw0XzCW75KsRHK/aS79O5Y+AR5OgqFaZFIFOtlxUrNffSyu9tsId7pVVJcayUMqOSiUeM4bou57O1upjZXz+fkszfuuZRHux3A+VmFWGzmte3fUSBN48H+93As5vfoNKqZsIR52A6Fo8PnJ7mKv+HzmOZ1PlCZA7OVV6To+yu2sUNG/5Wr9/yE/1nABn/9vhGHBh6TMGYs3e/+3I5+o05mJqNaf58omnjpkh7LYqjkRrZ/KEHTZMQwmFW7+uZ9On9Nb+JCnK1APd1uwgkFcusZE2NMV2/I8byxvKpnDLgLnyeIO1aDMJKSOzeYzL6dA+OC5KArdtMPPqhT+Rq56hGuBq/JidLkYSM4woWvWMw4niNrCyXM0d5kq7ywsVKuHTupOL1NqcsWoyieNHkTHL1cq7o3Ic7Vm1Jydmn9enC3HXrCWhKWtZ97pffMal9G6zZFWnjkbCL+Wx6HJQfqSB7anaDhpqykLj5yKvxK4I/f/W3NGl8mVGBR9LJ04P1pO0HKocI6gFkIR/weXA5o9WxZKh+ZvebiiJkVLRGRdBBQEhysQg2ab0veRfBJghJLv43h/1Y7D+5bEuSUqRdAklO69Y+V1hYuP/kfd9seWq//RCr/ScUCn1XWFi4tbCw8AygWSgUWtHA/vUQCoWihYWF44DngZdJLhL8Ymgk7geJfWuify110C4CZfTlKK5Drq+AsmgxJ3S8KEXa/7XlOUYUXsKY7jeSpeXRlNY80qkNpXaELNWDW5oc68LfcG2m8Iu0x1jw3fcJOnZQWfR2usPy0uUm0ajLdSMKeWnL9/xt0w7yfTp/6t2c6NoH6NBjHHh17l8Tqjcpje79mtCyGfQcfg+7dq2hYOB4ipc9BEDBoIl8u+5F1MLzueGTFRRHYxT4vNw94CiaajoakbQ2VKovFyNWxpp3ZhCrLsabUUCPopm0H3E3m9+6Ie27Pdj620Y0ohEHQI053f6LY0L2oJkHF1dt2yWKDz26PaXAKTznb/j9zag2VO5b/lkqDtze/wxe/m4JXj1IVfQbfJ6OLC7exeLiXXTJyeaKrp3YayTjTYHPyx39e1NpmNy66gseGTCknqy0bRuJeBw++Kiua8UFIzSsmvhYGysPFDN9muDlj5Kt4k75ncRHxcn7eknUYNqyr5k9tBtlMZMRIzTe2qczxuDjTOZuf5PJwQu4Y2Ah05aF6ibTfVsyJ/QwBd48yo0wtuuQp2dxzcp70l6/OFZK2Ipw2bJbU1l2wzb43YdTUtLSOV8/z+UdR6PHPanP38JBRksRNfugYqIFqq/hGtJfSs/9W4VNg2MMG3C+R9MO/9nkXUZQ4POnkfcCnx8ZwaF2b9Q0ibj9PQsXT8bnyeOerleSFWiNjMCKFPPuyump9nCQNGGLxPcQjhTzxvKpnD3scTxaFprq0LSJykuv1DmvnzxCR1UdTPPfXMB/GQeaozpqe1Z+ajLkaA1/BsTjgjcWpbe0/GqDSZ8+WfTIH0YiEcO0E1zSqUeKtEMyRt2xajPX9OzA7mgMXZa4dWUyDhUV5NAxww+XelISeWeLlZTMNzBGY/EEN/XtyJ9WbkzFsZv6duDmFZ+x1zC4qU9nyoxKHtrwAg/2u4GwFaHcCHPv+qe5uP3IetL2WCLeoNw9qGUSTcQOKIcXCNplHobjuGmLkgcX437jyMyapF5w3b417qgXXFdKZtakX+Dsi4FrCgsLHyEplX8RcAsLC8/YRyqfD6wDSoEuNceN+hHnTvDvufA8knXwsw/mgkOh0JLCwsJ/AFcCdx7MsT+ERqn8QeKXknr+f0CRBQEtQUQ1qWgWQOTkc2W/WeT6CvBrWQxodSrPrJ7JgFan8viqG1j09ePklDfFvSNM8BaLjg95CRo+pJ5JOaQbcVPyzlqIPBl3n3p0kScTS7j0OFLFqXY5bajOmcfr+LyCd9836H1UMoO06C2TPrnJnsolUYObPt1JsHAMZrycrctv5U+9m6e5I/+pd3N2fTGHWHUxq9/7Ay07jWTNklvJ730xBf1+z5rFM8g9Ygw3fLKa4mhywaw4GuOG5Z9jym69TF9+74tZszhJ2gFi1cV88dF0ZF8uHU+fR9cLXqPj6fMO6QWZ/yQ6X/wGfSd+RueL3/hvX0oj/ocgJJm2w2eknOW1zALaDp+BwPpJcdUjR1Ok3d+sK5WKw55YhBtrSDsk48AfP/mcizoMRZcUNCWIEDIFvqRvxfq9Fcxdt4EpPbvx0onH8PjQQTSRfeTLAW7o1hNJuBw/PCkrzW8qcdYInRP66STCLj5vctEyXOVSFq6Lj7Wx8kAxUwC4yQlzmZHOAkqiBq4LM1aEuHntOnocm+D88zV6nbCHudvncXab47FxeHHr8zw8rDMvjOjJ5N5ZzAk9TJlRwS3dL+f1bR8RS8TRJLVBB+ZyI5z8bGKl/OHTB/DIOi8Pm8VD/afR0teMG7tcSpYSIKpGsb1mjbGVwPaaGJ5YatuPhwpWtMFrOZg6+UY0AJkGxxgyfP7eFFSp6me/hGYJ7u43hAKfHyBV465Zv0yZgyxLZMgeMoWXDNmDLP/0qamkRInEyxjR71b6HXERq9c9wsrP78bjWHj1TE7sO5OAPxl/2rUo4qyhc8kNtGXcSa9wYt/pCCFQZB3bbthV3rYP7dKOA81RBS49jtQIVyVwHIk3FqW/t/f+ZdC5k8pbb9mM6Xo72ZmtaRE8nJYZgQZbUbYPZAEuObrCX4q68uzwHsxo2R7zrr0pibx6ZiZSOxXXaDgOej0yLglmD+3KQ8O68Jeirjz8ZVL5VByN8adVX3Fxu7NYV7GZmV88imlbzFr/DOsqNvP6to+4r8/1adL2bDWT23qOT9t2d+9reWXrv9ge3d1gucTdva/l5a3vIRwZLeZFjjVm2X8KhKIuF/ktR2pXTF+u3fCX77Qrpi8Xv4AxHUAoFHoFWAp8DqwC/gIMBK4uLCz8EpgDnBEKhUzgEaCosLBwLcm6+B/K+H8NZBcWFj57gOcXkDTAO9Dz/w7TgO/327a+sLCwuvbvJ5yzMeN+0PiF+hD/p6HIgoxEJSXGLh5Ze3PKjG7igDlc3ut2/N4mSEKmLFqMX8uiLFrMlUfcj/xgIk3OlJhTiToliLUtQWJRNdolWSm5vMiTUcdnk3gtOfZEnow6MYjIFBAG828m0XIXJSg48Tydtz8z8XjqJrrZWp2KpSRq4A12R6McM1aKueIm7u0xAW+wO7HyjexacROVu5OO95ovj5iaS6tj/ozjb4KfOLHqYmxJS03Wa1EcjZFw3XqZPlkPpEh7LWLVxdiOTcz0U/dd/jYDeEZmAb1eH8Nnpz73Hzm/bSdr5veFZcWpqGiU2/8vw7XjbFs2m8MHT0LxBEjEw2xbNpt2x9/+k+Kq2CceZ/e9iIdWTuHyAX9tMA6UmzF02YtHy+eBL9YzrXd37vh0Dbm6znXtu9JGzUROCGxcjLCgOu5i7fbjOVIhwwPnnqpDFErmGWzbL66V7Hb48HOLMycEScwpT8VK658RtKuyMR+uSMVMbVwW1vNhjjstk4Rf4v4N36Zda75PZ1t1jJKoQUnUYPyyNTW93As5peVgnv/2ba7pfB6rytYx2txFQPVzWEaA67qcT7kR5vlv3+aCdqeQrWWgSSr39bmeyavuTzNremjDC3WfTawUx3VQUZKS+ISHXe4eJn06K3XMrN6T0CSViZ/clbbtx/ZxN20fub5m3H3kZdyw9rH08/7IOvlGNAxbduvdl7VLsrBll1h1Ma7782vdbduhiawzd9DwX8xV3nVcMmRPskVrRFAyzyBR87tqNk4n5jMO+vyyLIiaZbz32Z2EI8UE/AWc0Hc6X3/3FrZjYdsWwYzDOXvY4wghETPKefHDK1L7nth3JmYihip7sZ2GXeVt59Am7geao7pIfLHWoGiwTqTabfC9eTwCn1fgsVQScY2KRCnB3Gye6NedTFlhr2Xx0JZvKY2b7I7FyPd7cVyY+OE67j2yE+6c/Uop51WiXhCAPAntsizMx+rGqDwxi61SDNOyKYlGuP3TNVzTvUuqXAmScTtLS/ZnX1exmee/fTspZZdkNoe38XHxah7qfyPlZhXlRph5m19lYqdzmDvgJkqNCsqNME9ufIVz245g9tfPU2ZUkKMFeHTATVSY1eyO7+XJja9wecfRSVl8zXxPlgWSGsV1LYRQcaxDuxz2UIFQ1OUE8wb+J34hoVDoj8Af99s8tIH9vgH67LPp2prtM/bbr/U+D7s2dM4aN/thwHuhUGjnj7jGofs9jpJ0sW/oNX8yGon7weIAUs9DrQ7aj0GkaiePbJ6RqmsvixYze/kErhv4CLLjpEzpImYlub4CmugtcErTV+fdUhuBgLFBJBUsGdQbcojbNqomYckC7bwAjAFksByQYoKdNTdhgES5S8XfDM4Y78F24Mzjdb7YZFGxj94s36ezN7yRN1dP5+R+M/luxWw2/vNyjjruPrYtn5Ui2VlNuxHsfxuXL15VI4P9jrsH9KZJq6HIjplyja5Fgc+LIkS9NlSyLwdvRkEaefdmFJBU4TTiPw1Z1usZ111w4ec01sn/j0OoWNEyNi+anNqkZRaApPykuCokGS2zAMWXi5zXlQsDf0GXVQp8XnJ1nfFtO5Or6lQ5FmBQYbjossPi4l0ckZ3F3wYORbEkrD0OZQss7LBL0zE61W+ayBnQ73cqTszFLgMpT2LnvHi9uDboHI2X/2kQjUGJLJAuzaZpUKIs6iBOySSYKVDHBJKy+YiL9XIVzhaLrHMDfKeVclZhCzbWtNQcXJDD1T3aU2FY3DWwC89u+J71e6tqWi6FmbX+GWb0uAKPpDG12zjuWfcUEzqdgyLJ5OrZ5OpZXNflAkrj5WRVu4R91cQSBo8PvIW4baLLKveteyZV7w41WW9XQY4la3fj3nhaG63aWvSp3cY1WJ9ee9y/g227IDehtTfAvAE3k3BdpEZX+V8EwgLrpar0MfZSFcoVWXgzChDi30/zVE0mrjgkXBdFCDwJCcusX75g2w6yTY0+4uBkxLIs4UVDOAJXcjHlBGaJQ/miBHkjtXrzhV3zTPIn6FQR+4Ezp0NSoyz8cFJKCh+OFPPOypmcWTSHlz+akNretc1p9O9yKQuXTk7b9+2V0xne60YA8jLaNOwqf4jz9gPNUV0HOndScexkB4wGXeUdlxG9NUrmGCTK/SjBDLxjNYLvQnS9Q3ZQ5YFxXakMWBTHq4lZCfIcD4/36k6OLBMvTfdBcEttRIFC+fIEGUdIaJNzwIFEtYuV6XLf6i8pMwym9+nJrEF9mLsulHZ8gc9LLJFUXRV487is8Ez8igfHdVPdMZbsWc3F7UcS1ANMOOIcZn/9PNd3uYBgDeG/uvO57ImVc3Xnc4kl4nglhQ0bn+PITheSowfoEDg86RxfMx2VZYHFDhZ+eH1qQee0Qfejyr9N9eVvHA8ApwIjajcUFhZ+AAQb2HduKBSa+/9xUY3E/SARt320P2lWSop0qNZBS45NQtdTpL0WZdFiquN70JBZ+81CLut7D4s2PMGFPafjyE5S3rlfmyKz1GXHE3UkWwkKcidoRGIueiWYmsAxXdQW4OwWuDKpm3AtEuUudqXLjtlxlKBg+DideXuS15bv07mtb0u+WDOVcKSYN1dN55SjbuSLt69he+h1jhp+L5tWP05+4SkoOT24csnn+8nhP2Xu4JsoXfcMd/c/PyWXr61x12yBg5vWhiqrTRFHDb83KSX05dK81wT0rNZEhIYqS4dsi5tGNOLXjAPFT8PN/Elx1ZVUDhv9FKUJk8uW/Z3iWCXntx3AnwcNILNCI/y0jVnu4g/qNB2Xya1bP+eqIzsztKAZvwu0ZfeDZirL1/QcnbJFJrufM2hytobkAWyBE4Y9Lxk0O1dvMK5l6iJV/7pilck33zqcdorOB4uTpna/G66S81y4flwVDqbt4lMcpvRqT46u4roKV3+4jZKIRb5fZVrfdsz9cgtlcZM8T4Cp3cYR1AK4uKna9Tkbnmd8p7O56pPbU5ns+zuPx/ePD/Fl+vGfVUQCh4kr7iJXz2Z8p7PZGN5aL+tdS8T2b6MFSaLuVTz1th1MH3fbdonaGoK65dHGGtKfDyFJuJUO5uzyum15MkKS6Dn8HhwnkSxzaIB0qJpMiRNj6pIlqTZvd/UbTL7mbZC8/xTIsoQ3qrNrXt1vLX+cTuVnFsHjVEA0+LuSHIlM2UuUH595d10rrX4dkoRcFkra9rLwN7iuw8hB96LKHgwrQiS+h5VfP42qeGuu2+W4Y3XefT/dp0eWD+0xe6AY6wjweQWO6/LVBovhx+hpLS5POlFHNlzK/5q+iFIy3yBvlEZ0fXJ76TyT3AkarxTv5uKcjoTfSZBVpOJm0eD8MSFcKj60qfgwfTy1mOjh9ra9+eM3nzJz1WrmDOnHJZ07sKkynJq/3dynCzZ7eWzgLSScBLpQGbd0Brl6Nvf2vo4pnz7AuorNzFr/DLd0v5yZ6x9lXcVmru58Lg9+9Xcu7XgGD371dz7a9Vmqi8D7y6cC0Nw4LWVcuK+CKLn4c33ags7Cpddz1tD52I1tgX9TCIVC11KTsd9n27D/0uWk0EjcDxK27WIqLeh4+rxD2lXekWQUw0iZ0dUi11dA3KgkAWzbvZKy8DcMO+IiMpUMLN3APyELa84+krsJQXa+kp4FTZS76EKgGIJdL9XJ25pf5WH3c3HyRmkowfSbsRIU2NX7rqgbjLmqBQMOy6aZV8Myt6b2DUeK8We3pc9ZH5JwZWJOjDb9rublxeMp6veXhuXwaLTqPAahwGNF/VKu8h5XQnGqkRSbDfuY01V+m2xr1G/kU2y3TK5d+SLFsUUUeLO4t8/ZNJEDjeS9EY34hVEbPzv/7mkSVrwufpoO8kHEVVkW+Dw235sG0URSCjxn4AU4rosqSWSbOnueTqRNQHfPMxk7tpDdsRg3dupB6UNW+vPPJyeoJfMN1Bwp2Q/bFux+Lpllt6Nug3EtM1MwZoSHmOUydLDG4EECIRxOGaHzxlsGS9YmGHl5NuLROrm8e3k231jV3LTmEx4bcixZmkCgMf6D7ymJJONtni7jjcv8uXtXXNml1N2D5SR4aMMLTOl6ccpkaV3FZh7a8AJTu43jMF9TPAmJ7Gfeg63JWBcceQxhSWdW70lM+nRWat/D/QVoDTgn17bR2t/AKZZIb1/bWJ9+aMAWoFySTeLJuvGlXJKNLWDrV/9g785V9DlpHrEGSEdccVKkHZJO8VNXLGHu4OHIP8GATZEl/NhIjoMjSUSQ8aClSDvUkMF5Bs0v07H2ujgRp8HflbnTofRV86Bk80KoBPwF9cznJEkh4C/g8KZ9GdDlUiSh4uIikHh58cQ0qbxAwkxEEMLF54NhRRqqKrAsF5/PRRziGfd956iysLHdpKu8Khx8fom1X5r066OxYlXSqM7nFfj8All2UIREPCDIG6Uh+wR21KX8Xxayr+5NJ8pdYobDJa06Uf6SSfYQDddy2f2aRd5+41CbGCShigPOB2Ovuoy/oDNzvvkK4epkKV7mDinCFSY7Yruw3b1IkkTYrCZby2TiyrspjpVSHCul2ooxu99UKq1qyo0wD214gXUVm5NxScic2rKIf+5YxpSuFzG+w6lEo7tSXQROKno4RdohXUGkOw0v/riHWDlsI367aDSn+wmwbZeI6SViBYiY3kOOtANE0PFnNufKHnekerTn+gq4st8sWgS70jy3B6cd8wxDB9xHdrAHjhzAkjQSQRnGBlGm5eFekI1hCez9vG2UoEC4gl37rczaYRc5IBBeyB+rowRFav/8i3WUYHK73kpKkn9H5sWNm7Fdm0WhJ+l1xEUAtGsxjFIjh2nvylyx0OXmf3nZHcvCp+dhmntTplK1KPB5kYGY6SUa1SAKahwUE6TYNja+Mg6zame9uq/Kbz8i4kpMXvkixbFk28biWCVTVr2Aqf1yPXAb0YhG1MG2XTR/br34+WPjarLVUQUVjsFjGz4ioHlIuDYTlj3LzNWv8l1VGaotN5jFO9zjJ9PQ8LoKckCQP1anxXgP+WN15IBA9iUnmWaxgx0BbFL7KUFq4tg+cW2sTukCgx13xgg/aUAZvPNPg6eeNTAMl2FFGkcP0inzSFRfFSQxIw+m5FCZ7WLIDrf0KsKwJcqt3ZQZFSnS3jXHw23tW+B/GkruMCibY+Et8/HmtiVc0eFM/LaX+3rXGTOVGRVoksr0L+biRKIp0i6CARxJwrZdmjh5PNF/Bnf0nEh7/+FkmBnIMbXe56yZSZK/fz/jFt6mDfQ4bqxP/29DCEHpUhv3guzUfbt0qY0Qgh0bX6spB6u7nymyRJbsEhQ2CbfhNm8J9+DnNIoskRmtxn3lPUTxbpTKMFmOieRIDf4WkQSSJtj7T4tm5+33uxqnU/4vKyWb9/LjWrA5lo/TBt2fMp+rlTkLJ8BZQx+ld6fziRoVlFd/T0VkGwuXTqonlfd788jyt6h5T5AVEPh9gqyAQPmVrFPVxlI9UEDETM6XTGcHquLQqVAltNFi0ACN3BwJf4ZAkhw++MiiMuaQe7JG6asmOx6KU/qqSe7JGs4+48HXRSKoK8gJQaCvyu7nDSRNEFnvUPJ2Im0c2n6JsGmRdZGc9v02O6/u+83XvVzdpQ/T30lw+QKDm962iMZ1gpqHmWvmctmyW5m1/hm8ik6unp26jjkbnidixUg4iZRhXYE3j9t6juemz+cwa/0zDGvSjU8+uxO/a7P5m1coKfuSgL+AQEbLA3a4kGUPZwx5kLOPeZzTjr6PgtxuBPwFiEOsHLYRv100Ztz/R7Bvb3khVGS8CDmTXFwmDZqL7TpUVm/jo1V30iKvJ83b/I4pK/9BcaySAm8Wd/c9C81NdpARmsTO55Kk3NdFIn+sTsn8usx603N0XKe+HN6xXXJP1tj9nIEcEDQZraHmSQgF9iwwiK53UsdXLDahFG5udRTzvwnRr9U5eFSZdi2KGNzzdm5822F3jVv97ojL/R/rXNvvOlZ//QAze93K9M82peRU9wzojWYlr93jkdDcMK5jIySZyt3f0ebY6aiZBal+7RXfLCaj3WAkXw4mboq016I4VontOsiN61qNaMQhB48cJSEcwvFyTm7Vg+JoJXevfZNcTwaTu55IhRkDiQazPIosoc9XscY4qViVimtjdFzJTUnmg8eooLpp+/m6SDS/IikZt0odHMvFroaCK3TULAlkGDlc5bX3LFavtejTR+Ott4y0dlI7XZOALii0g8g22JaLR2+O4djMPTaDcsMm31WIzU9XDMSf1bjt6vHY4e14gg5NtSymdhuHV/EQNqt5aMMLlBkVqPEEtCpAnHgUNM3CluLIJNULcuyH27nZtksT8niy/0xsEmjIZNoacVfiif4zauTxB9fHvRH/QSgOwRO0tHt0/lgdlGSG2ptRkPRAEAlcVUFUV2PNe4VEeRjllssabPOmCIHPI+OxTITjgCSRUBUkw0JIAlcIhOviCoHjQlxW8NsWiXeWogzuReKFt3DLw4hgAOnKsQ3+FoUCjukiZwCKS5PRGlJN2R2qi9pMYGxNjn2xjyGcLAtkNYqLiSxkFFcjZtW077JdVLkFZw2dn2YsFo876D6ZcM3i/ZotL1PU/doGM6txM4zfk4PjJkU3siySvc5JysydX9mQl2WBqlXz3AdXcUKvB9j6zeHJrj+uQADRiMOX6xP07K4hO24q1kGNEuk5g6bnJhdOfF0kck7Q2LPAIG+kjpwh0tRIxvcuO59KLj4mVZgyHl1CdWS00XLd96u4qX08usKcDxJp8707PzC5qshNy4hPXnU/U7uNS5UIravYzLzNrzKly3k8NuAmLMfCNqsI+Jrwx87nYMTLUhn2PRUhzh72OEe3Px8nXokZLm5QVaRIEjFjT5q54Yl9Z+L35CIcP6onkhpXwvHjSpGfbGDXaIDXiJ+KRuL+P4CG+nZ2OOYOlISHamU31QqpQAQwtN8dXPXJP9KyzP/c9iVntx1KRbWD86ZN8ys82OFkQK742CJvlIaWL2GWOJQtMlMr5PvejIWA3X9PBv1EuUvx40ZyQnyuRnR9chJRK0ltfoWHXX83sMMugy7Ix6OFCXgUBna5nMpoObsjgbT3uDviomt5lJR9CWtv4fYe15GV0QrFSZDhlJOQm6KqElLse75eNCX1OXQc+SCWY/LJm5cRqy6mddcLyDvqbF6tWWk/qehRCrxZaeS9wJuFLH6bpL3zxW+QUdOqqxGNOBQhhIsjBEa8lOYZbfEpOjOOGkUTb4BdNST+3m7n0HJMk3rE3KpwkjHLgd0v1J+gNr9CZ9ffTYytDuX/smh2nsbO+XX7Rdc77NwZp8nZGsWPG7S4xkPeqRq7/pb+OicPVKnQXJ76ZhfHDMsiW1WI2DY73Dhz1+zm9g6HUfps3TFNxunM+nYPi3dUk+9XeaZ/G0rK06XpiXKXSNUeFqy5mlGDZuGNQa6kMmX1w3W17b0nESSIcU4fNr01Oa3Gtba15b6LvAcqSRAIciss7Pmv4JaHIRjAP/Z0HF8GiRrJcp0Ds4Spur+Y23gjDhKWxN53jDR58953TJqcoePNKKD7kBk41ZWYL65APW4g1lHjtskAACAASURBVMvvJr9TIPud5dx1/GCmrkivcc/+bANa28Ow3lmGu34zIhhAvXgU1tLPYdP3KGePILHkM+ThA5BxyfB5wHFR+nZNkXYAtzyMs/BN8seNpGSfGvdm43SEHEUO6uSN0tn5cLwesW9+mU71ShslmDS0w64zDntpH+OwU/rMJEvLxZCbpMh7sha5rjOMLAscJ4HXk4vQmtG3ZzcSAtq1GMqWHR+mXjfgL0BX/bz/+T0c1+tmHCdARdhJSeUDAVDk9NZohzJc10FL7CBmxQhHivlq2wv06PgHPlxi0uNILa3GvduR1QTkDCobUEe4AUHzaR4UB3Y+mvQAKX0tSd6VoKD8XxZNz9HZ/fw+nQHO00EC3VbY+ZhR7/ttMlqDgEtYdVOkvRa7Iy65Wm7atuJYKS39zVKEu8Cbx+87jOL9ZVMp6n4176y4hdMG3oNsVfHauxekHRuOFOPYBt++dBkAvmZduXfoZKakdbi4DrN6O2+t+GM9FcbZw+YTN7ezcPG+hnX3sWztY2zZ8dFBG9g1GuA14ufgt8lO/sfQUN/OTf+aBtk+JE8WquJNX1kWWhpRHdmyB8cf1ovdsRh7zKSzslnisOvvBiXzDapX2pTMN7BKkzVnxlYHq8Kh6Zh0eZuS1bAkLrmum77NjroYW5OT6Kaah2xPNioKC5dOIm7soqk//ZimfoHf24QRg+bh9+SRq2tUvH0t3sj3bHptIh6q0dwwm2pIe+3nEK/ayefvTiZWXUx206407zwqRdoBPl83h9t7nkSBNwtIkvb7+p6NZv4217Rq28AdLJxE/fZujWjEfwJCuAg7QemeTwEYv+wZLl/6NK7rcuvqhRTHKrl74xvEfHGajNZoMd5Dk9EaItOl7LVkNkiSGzbEsqvB2JokncZWByfWsNGmJCcl9bKfFGmvfW73cwZSGJyEwzHNk6S9wkrwyFe7EAKu6tCUyLPp9fV75hmcc1gOACURi61RIxVba6EEBR5fkKI+91FpZxDRm3KY8PHIERexoN9NzO81jbZxH3asIkXaoa6Ps0eOkuEx0RPb2fjKONY9O5KNr4xDS+yo15Pdj11H2kkSMHv+K/hJN5iSZYk9wuCKpe9xxruvccXS99gjjJ/Vh7sRBwfXSS4olcw32PFQnJL5SXUbDhzZbxLFS2ez8Z3rEcd1h0w/yqhj0MaPQR07ClFSSuvPQjw6eDgLhp/K3H5FtP54LWp+E6x3lqH0TXZJcsvDWE+9ijq0L255mMQLb6EMPgphWSSeeQ3zzidwyyoQGb7UmEld3/rNqP4oLSaotPyjh/wJGlKgkkR4JyKW9LY5kJS+VjYfq7H8lnWTsrhJUb+HOeHox/F58nhj1XQi1TuSi1H7QdUkXJ9CTBUYIoe4nM8VHy/mjH++wWVLPqBz1xtp12IoUCOrP3oWoe/fo2ubUzETVTjSNnJyICNDkJMDmlqGa4Xrvc6hCitazuZFk3Cie2nXYigt2pzHA1s+oemRVWiZJqNP17nofJ3Rp2vsCX+II+INxp1NkTil8QR2VbJ0SA1KRNc77H3fJP9iHTvsUrbIpMlojcOneWlytkb5B2aySYzTcKxVm0pM3PI030X2NDjf02WV+4+aQdfsZDetAm8ellXFQ31v5JWhD/L4gJns3fEh0XgpAW8zxhwzD4+WhSRpqVKJWgT8Bciyh6y2RQCo/lwO8zXhyQE389oxf+bJgbeQ7Vj49KwD1LebLFy6v2HdZLq2OXWfx9cjqfXHYEOQ1GgD5/vxxzfit43fJjv5X8OB+na6NqqWQTi6I2XYUpDbDVWS0rLMF3YYwjVLP+Labv14e3sV153fjHADK6jxgEPGhSrVz1hUfZog+xglKYfPlbDKHKBh8ybHTA/aSlBgh+ukUllehfKvniPRaTjhSDGrv36A6wbdzwNLveyOuDT1C64epHP/EpOKWEduHHYXXmsTVrSMRDxc814T4Lr1PgdJ8aZavrXtfjGGUZEWmEvKvoQvbuexAXdjRPZCvIJmskSV1ZgxOhhIis7K2b3oO/Gz//alNOJ/HU4CxXHo1vFCdpRHeaDbhey1qlGFnIppX1bsYMrm55jY+ng6ZTTHxKLcNJHCyTrFAxnNyRl1RkpKUCD5GpbcO6ablCOrByD2mqCpqvL+uzbhqgSBTMHU4w6j0jUp0FSqy+sbfjbT6moo/xLaxQPjDmfPPr2tMy5U2U6CaatUSiJV5Pvj3NEnQL5TzsYXLqT7+QsRe6O4LTwN3g+EG8co+z7VWaN2++ZFk+h4+jwi+5iXSY5DYn8CVh5GdhzYx5DOVF1uWLo4zdzshhWLmTtoOPIvY0reiB+AOEBZCBJsebOu7aJbkIOodrFe/VdKxq6cPQLXp5O3dRdC13CjMRLfbCfxRQhl1DGQHUgSfJ8XNxrDrRmjbnkYkZWJ9dg/kv+3KkgWhGf6US89k8SXIeh2GK5fQ8Rt3LK9OM+9jXzZaOJOGZv3UQd2GfnqAaX0za/yEFONpHmlLLHL8HDTZ15KIlHy/VnM6HsXa9dORajepIKEWkd4gaKblJgenvy8lJPaZBPUZZp4vczqcQw4UJ6I8+SGr7im+1SGdJ9IZfUOfFoOrQsG8PqyP+DX8xjS9c+8/q6ZykqfclIOAX+6J8ChDNc2MauKKV31NP1HzOLKpR9THI1QFo8xteMQFr1Xl3EfdepJOIpN/jiVkn3ijvd8hTs27eCawmbkmjI5x6tYpcmyx+qVNtYuN6n2yEguZFoVDnteMGl6jp4shfA1bE7nSi6lRjX5fp3riyTu/8hJm+/d95FJRawl1x59PX/9fh5XdhhFQuhc/8mLqRLP23uexBktj8UFyqu3JT0KPHmc2Hcmb6+cnpYdj5mVNDl6Iq2KphE2S3nug0vwe/IYfORE3qzZ94whDzZobiiE1CCh92hZaY9/rIHdgbofNBrg/f+jsLCwDXBTKBS65Bc411PAh0AxcHfN5vZACVANfBsKhU7/ua/TuCz+K4LruClTmSzZRanNatT07dwXWmYBQsjokocMNZuT+v+JgL+AwUeOR1gV3Nv3rFSWWRYyxdEIz25cw9mFWTywYxe7j3WIB22aT/Bw+E1esq/UeGx7KdM2bse8WJBzvIZTc/9yTAc5IKhYZtU3pRunIwdI29Z0TNKYRAkKml2i4brb0Zq0xUjEOGvQXxne9XYCdhlTj97Ow6MULu+v8cznJhtLnZr6J4tqx0ObY2+h+LOn0DILkISS6um8L5xEjKatijjy+HvRc9qgagHatShK2ycaL0WUfsWuf1xA+Yd3JFMYjWhEIw4J7Gumla2BkDVwBUpVJhULg2yarxN9PQ9vdQZDmxUC0C27BVe2OZ6gHiChuszZ+k/iuoH/QlEn7RxT32iuYrlJ3iiNFhM9NL/KQ0J3aTau/n5qvqDiYwsSosEMlWO6lIedVJ/kcJXLR+9aKLaEX5MaPMan1d2OSw2bkBonchG0uMlDcLyGkeMwbdmOlIFdScRi2qowZrATbc56ElORSOzZi4RCVpsi2p90H53OeIz2J91HVpsihAt6oEWDpF7CxK/FUpl3R5IQwfRypVqju31h07C5WWObt/8/uLJT/747Vge57j6W1aYIIcuYGRZceRL065rKnEsencTL72I+9ByJV/+FMmIIBPyQk4VwXRIr1+FGY4gMH8JxEH27JseGECnSrowYQuKFtzHveJzEJ2tIDG3L1yunsfa18/h6+Q0YmTE47xjs6N566sDi9Y80eP1uNAxqDNNMoMgSjqowdenOtPE/Y2WEo7pMxrViIFRkWcLxaMRUiSpbw3Hhqu5NUSXBm99UQIXM9pcVNj0lE3k9g2mtjybTzcRKGGz8/gPkRC6ZoiNnD3yBY3rexrvv6mm/4TcWWVi/opZgQtbQMguI7FqHK9TUb/X37Y9iyXuk3lvLFhKSIfHpsw6r3zUJnKPRcpoX+xKJmzfvoNSw8WVJSDmg5klphoLG1qQS07XBcVxkD+SN0qhYbGJXgRWpPz6bjdUJ63EeGXQRCdfmnq/+ygUDSpkzSq0333v4Y40pnS4noAf5w8r0Es8/rl6EKXnZW/VdiqgXl33JkrWzGd7rRsae9DLDe92IlYgTiZdi2jEs4bB0/aOEI8X0PeKi1HEAy9c/zol9Z6abGx49i6rorgaz+H5PHqOHPsxZw+Yy5th5SJJcT73U4PdS0/1g//P92g3w3IQ5IFFZvMwq3/5torJ4mZswB/y3r+lHoBXQ7pc8YSgUeicUCvUIhUI9gE+BS2se/2zSDo0Z918NFFnCLdmD++QCEjWr5YGxp2Nn+pEcnQ4nzWLTPn07O4y4l+L1L9Gs6yjKV86joGgyZw17DIHghQ9+z4mD53JdtxPIUr3IkkSBz8+68jLmrF/G5Z17UZCh4oYllr8YJ1bp4s0SnH9qHreGd3Dxsu94tagdxms2uSclTXGajNHwd1BAdWkx3oNrA66L47rYFmSdq6GoAi0AO+Im+eerRM2dvLPlLwxq8zs8WW1wzRZsfC1R83o5HDHSQGTAbe8bdMyTuHWITpYmqDRdtIwCtr89EytaRoeT7sP94nvk7h3ocNK9Kbm8llmAN7sVLXv/noVLJ6dWX0cOvBegrjZp4D2Uvn8PWmYBbYfPQEgyiiylajl/Czh6zBv/7UtoRCPqodap2p6fNNMSl5+M0zQTIxzny0UmscrkxDNW6bLmJZPp543m2rYxMhUPm99PsGGTgzfLYuxpxzL/u/c56bCjaD+hCbItkdAs7EsjHKbn4uJimS5ZA7Vk23jFZd37Brs3OTTtINF1og6mAAFWpcOel5MlRd8NMsipUSHtW+MuBVwWf5SeVQ9XubT066iuW0/N1PQcnWo3maJO9m8v4JG1u1lfFmfusa244v2tzD22VYq01KIkYlEZK2fhB+MI+AsYNWgWWVtKOazP79n01r5eH7NBkhGuoOOpf2HHyseJ7FoHJBd5jcoduI6FN/twUDwg/KhjT8eqkcuLru0Rpw/EFlX45bq6eBnRoLmZjIBG8v7/A0cQ/tyi+WU6SAIcl4oVFtlDkiQgq00Rh/X9PV8v+H3d/OCke1FaFeC++C5URerk7QE/JBKo552Co6vYTgTO7IeNjLtyM6xYh3rRaTiDjsKpjiSz9sf0S6trp3/7eqUam96aQuuhU/EEWtZbOCr54imadT+PFpf5cCUF4SSwP/gnzqovUaZdhiKrZEar2SOUBsd/VkYb/Ik9mPgpRWLqh9soiVjk+1Vu6lvArM92Uha3eXJwa9b+bb+YscCg8wka/pzWDGh1I6v+atTMPyR6nNGCli0s1m+ok46Eq1wc59eT71J9wVRPdwU39VsNqp4Uac9vKjGgp8ZnzyfnerFKl5UvGXizBL3O07m39+HICsRiDl8vseg8VMMOu5S+btLkbA01WwIJhOqy5yWrzoR4jI7QXEoXWKjNkp4FKAJT2FRoMSzHIJIwKIlXUmZUM+nT+TwxYCK3vZ/eqSJZ/65iOfEGjYRdodQrBy0u+5IFi69m7EkvoypefJ4clITOa0unMLzXjRzVcQzR+F48Wla945asnc3Zwx7DcR0kdBAu7316Jyf0nc47K2emmda9teIWIvFSTuw7kw+/eIBIvJTTjp6FR2uJaR54/ljb/aBWLl9b4+5YPn6tcdNNmAOs0i2v7VkwJc+uLEbOKmjd5Ix7X1Pz2o0Uirb855y7sLBQAHcBp5NskfEo8BbwGJADRICrQ6HQqtqsdygUeqrmWDcUConCwsIZQAugA0my/kQoFLodeBBoW1hY+BDwD+AekrKyr4DBwPGhUGhjYWGhH9gAdAiFQukGNP/PaCTuvxL4sbGeXJBWc5h4ZynqKUVQHUUXPjqPegIbByFJlKx5ntwOwzGiZRw26GoSCYMXl0xgdNFDhCPFVFZ/zwNfraI4Vskbx13Lnf2O5sYVH7OuvIw7Vi/l2YGn8PmC9JvcN68nuPyUptyxthivLhENJyhblMxQyR4gA9wyF1e1sS0QOYJYHDZ8aFFZnAxi/S7XOf+j78j3q8wpyiUSL0WoHhQ5n09fTqS93tev6fS6QKH/YQ4XdNDY8rpBcc0iQuszddqdcCdG5Ta2r3yM1p0uw579PPplZ3DE6Y/hujZCUjAlWLh4clot0WvLpjB68GwGFl6Ex5uLHIvgHXQ1jhVDKB5c2yHLsUjIyT60vxYCn7CNnyxVD2Qka9s/O/W5X/iqGtGIg0OqF7QAyU2A48CYE7FEHDvXhwBkPS8VK2qh+UA3IbvKg5WAdgNVjIhF5U6HLQslRp7Wm0uXP0GBN4ube47kha9XcE67/jRTc/nsWSN1vp5n6mx4ry727d7ksA6Twv4ae/btrjFO59Zvd7I3luCGSwpoqWsICYpNkxgu0Vj69QUyBcUxC9lyyVxMmplYxWKTrDM15h7binLD5tEa0p7vVyk3ksSh3LDJ96tp5CXfrxI3dgHJ2Pbq0kmMGfY4W166LEWQVF8uiWgZ37w3I0Xc2g6fwbZls2sWPu9F9uZiVe0kVraFPV+/zmFHXoy7fDvKmcdBfh7xRAmbFl5aR/xGzkZofnDhnn6D+cM+5mZ39xuSNKj7lU5Af21wZJdAbwW7zEFWwbYg0FvBkV2OPP15RCAjRdqhhkgvmsIRZzyOKOqDY9uoY0dBdgDhuljvLYfjemJLYIZ3IKleHCuG3qsFEmA9vRB1wrk4AtSLR4Hr1pH2VgW4zbIaVnWoXuLhbWiZBWnPa5kFCNfCeXMR7vrNqe21Cg8/NvY7S9FGHdfg+NckGYMmmJLC1MXb0jLyf1pZzDU9m3Hjx9sRjqgXM2KVLrImEI7KFwuMtPnHFwsM+p2jpxH3QKZAkg79cV0bQ6moQtObc8SZT+DKcHe/o7lhxceUW3ECmRmEq1z6H6ViRd0GPxurCja8Z3DEQJVglkDvobDpE4vW5+qU/d2geK6RUla6mkvW6RrB00CRBVaFQ+krFsZWB2MrxDc5BM7RUJq5vPjdUka16U1JvJJnNi3llp6ncevqhVRa1TT1e9LM6pr6BRVVm7Hc8gaNhF3HwErEGpS4V1bvYMHiqwn4Czh14D34PXmoipe3VtzCsJ6TiJuV9Y6LxEspC3+L39MElSCSGiUSL+XjtQ8xrOckcgJtqKzewZK1syku+xKAt1dOZ1jPSSz8eDILP57EWUMfRZazD2g0d6DuB79mV3o7UjarlrQD2JXF7FkwJa/ZeY/PUrIKBv7M048GBgHdABX4GBgPTA2FQgsKCwv7Ay8VFhZ2/IHzHEmSjGcDW2rI+tXAjFAoNL6wsHAo0BFoFQqFKgsLC2cC5wO3AGcCb/y3STs0EvcGkZo4Og6OlCRvQL1tLu4PuvP+1NeMywoeO5F6vG/NoWhVgHzyEESGD6uiBDfgJ+ppSkJSUYSNT1TRpNPJJDBZ/cF0YtXFNG1VxGmD7qM6XkrAX8Carx/jth43cvMXb/NddSmf7NrM/QOHoEkKppMgZpoNBvKeAQ9/LmrJM1vKGH1+kNhfE5TMN/B3kWg6XMGcX06i1EbkyYgrstmwJEFlcfI83ixBcbzuphoxIgzo8nt0fzOwFGKVZr3XM2LlXNEzwNrn9rupvmzQ6xwvtjeTZkdPIC5rSOcNxadqqKVGUtqXk0VcCjdYSyTJKj5fM6o2fYgnkI/iCeDYFrs+nUeb/pMw73gMEQyQOfZ0qvZxUj6Uocg69z1/VNq2yed8/n/snXmYFNXVuN+q6nV6NpgZoNUoLng17qgoIAH3iIKKSTTu+qmJMRqT0cQlMaCfu6NRP3eiJuaXRQ0qKsYEBVQWEXFD5YJLVHAUZpi1t+quqt8f1d3TM9Ozwaxw3+fhYfr2rVunqm6fe07de84dIGkUiq4xDJ2Ux4eNhqFBIY1oqShOfRT0QpLzl2FMHku0OM7br7hJJoOFYcYd+zeCJS2GeElY44CJHlK3bUKrsfCXG2gXlSKmeFn+V1d3jC0cyZwjf47l2MRSSU4efRBBwwd2a6PVG2xv4G9YazNicorIObBzgQdbi/JxzVwu2+/7OFoBluOwKhbjwXdch3uv4QFuOG5H5uVsBXfEMV6cYIqH1tbwyyNGUvMXs1Uc6T1rvuXo0SXc/c632RnDa8aFeej9DQD85eMarhkX5qbl1dnvZ44L8d77N2TlbIxUYzs2O06qpPrtx4l8u4rwgedmnXZwnajP5s9EnHgfiYavcNAwm9az+p8X4CsKs/OR17HuvccZvc+5JGf/E+1XP2Dduw/xne9VYviLcewUTjLK2rmXYjZVU7zLFB7+3rVYmhcvGkUWRFV8e/+hgzfptBp7vT8fRlLX8NY5JEMd5MCxkvgmjcWpb3KXyJ90BMm3VpE6Ylcsox6iVjYfQuZlT+BQgf2vJWBZUN9AMmBDkR/tJ8fjvPsF1iHbk2zK75yn4o1Uv/04Y6bewdp5V7Sa/Xfe+xLvsRNIQksW+/NOxtZAdxzso8YTWrKCW8cfzG+WfpPt/7dM3B6fBYbmx5vSuWbfMA/JDXy4ybWtv4kkKU6HoNia00pngGuTJGMOvpCe36nXNYqLtJztHA0MT5TcPA+DDY+hU+h3aHL8JG0Nr+5QoKcwrQgfrarihr1PpazYYOepPl6cZxL0a5jR/PfGsRwOmODBeaQOs8bCW24w5sJS1n6cJPxDH0UVOnHNZuZHX2d3xPjdIWF28BsU+jytchmVne5n1esmO0w1+ctnyzhl54P589rF1MabKTKgav+jKAoV8pspBrcutLLx7r86LMGK928FDW4c+1uuXfliS4z72ONZ9fEf2W+3Gdm49lCgnPF7XUhp4Q40Rr8hXLYP1bUf8PySX3PUgVcTNxtojFRTGBzJqytvY/qE25i75NfZme9jx/2eN96/j0i8hlOnPAbAD6c8QF3Tlyz98BGm7P9L5rx2Wat7nhvv3hipJhKvIRTwpXc3yE9m9wPDKEDzRtE8DXi93XPAO8pKH/DtgKNHaIw04w0Y/erMO7YVzjjtGayGahzb6o1tiiYDT0opE0BCCHEY8KWUcg6AlHKZEGITILpoZ4GU0gQ2pOuX5KkjpZSZt0OPAfNxHfdzgGt64Vq2mCHtuAshTgd+C/iAu6SU921pm+2WZqaXpDteD9bDT2XLii76AXGtttUWbLlb7mzpOQvPO4nky0tIpQcx/eJT3biy4hCe476Ho+vEzWq++uTPGPtfzW2vwIaIyYiQxm8O87NdqISVL5yfTcy24YtFAOwx8SpOnFjFc4sr+eC9m7lv/K1ELYdjdtiHy5f9mV/ucyx3ffAyv9tjBsGS8naK3HQcvDqcsvswokmbkp95CTg6HsvBvGMTTo1rsTk1FvaD9ex54TCW/dMkWKKx3ww/D3zhzg5lZop2KP4OX867itHHPpR34GiMr6PQ2Y5YQ6jVPYs1OCRSFs008/LrV2aV10ljb6b4hffQGiN4Lz4Vvc7M+yZ2Y8NaFrxTxUkT7mDjskdo+GyRa0RMuREjpmOTk0n5ktNpoOu4JYVC0X0MQ6fe9nPzv82skfbrCRrmG78lGa1hzFG34D/qUJKJOt5+5TdZXRZrrubjt2ax/4z/5d05NrEGhz0neHEermulf3i4nsJfu5nagyUa6A7XrXyGs8dMZLgvxC7FFeiOA5bdSvckY/mN2E0JC3+hxZyVF3PMgVdTPmwXXlh0BuMPuJ7fv1PSaiawNmFBMMqx368j4B+JputYehy/HqdybDmOY1NxqZ9I3OLreJKb1q5n1aY49abF/YfvQKLpG7zBUu7+YBMf1rpOyIe1cZ5as4l7Jo8kEq+ltKCCJe9c5ybYTFMcCmM7KTaufp4dxl/CuqX34QkU53XcktEa1jz/C3xFYcSJ92XLP3/lenacVIlj+NB2CuMUF1Cx/2m89/r12Rcn+31vJt6CMsymaho/W0h8o2TPyXfi3PssDLEXnkMdTwLM/2vd983/q8N79XA3Lt2y889yWwA2qf/3ghsOURB0l7kvvAZx4n3I5y5p97JnzxmPoA0rxvHomEVx1uRsObjHifez9rmf4S0oY+cjr+PzV67Pfrfzkdexbul9JKO1WKkYO06qxBMoJhVvZN3yRxh96OUkH3gW7yU/hqPHQ8BP8vmFWSfeOPdErP3Lsd6cyV17n45WMIJgsAS/Bk7Ey9v/NLMhfddN257rV6/nw03uipXG9JLlr5Imu0738uncZLbu3sf7WbPQZJ8TfHl/87aTYNLhawh4y4kna1gin+CIAyqBwbuDSmFQZ13E4KaFqaxevebwQob5Yny6fiGfrl/IiYfdwarPX2Ta9Ovw4uWzZSn2Pt7PqhcTre6NJ2njPFLfWq8+Us/255Xywasm+53h4wszwc/2G8FP9xvBhmiSv8tNnLK7TqFhMOq0cjxeDTPusOp1EzPq8E3Cdbo9us61e00h6C2g0NDRfAEaI19Q7C3ipu9vj+140TWLl5dczjebPiBctg9lmskt+0zE8ISwUhFKNZP3Gz/l1ZW3M2nfS/jxEY8RTWziufTOQbmOeHXtB5QW7sBLb/6e4lCYgK+YIw/8DQFfMT+YfD+ReA1xsyFbF8AmzlMLL85xjqsI+kvz2pRxsyH7dzSxiQJ/BV0lmtvcbeF0bzR7DLRkpf/RlId4cuFPBmSLOU03qo2S8Ohc590oCaPpRnUnh3WXZJvPu0A7o1zD9WmdzHdCiLZJA3Jny7P12hDL/CGl/K8Q4gshxAxgpJTyzc2QvdcZOsE6bRBCbA/cCBwG7AdcJIT47pa2m28bnNRjz6DV1rfeGqf+23ZJVjJb7vTGOZOPPdt6K5bnFuA9/2Q8R08g9Y+XsEsN1r56DaE9z+S2pcHs0qINEYdb3/AQtQuyhm6GDV8sAjOCJ9bI9w+ZxXGHzKRIc3Aciz/KRVy7/zRE8ShuOfiHPPn1Esac6CpwcAexfWf4WZ8yqTPjmHYTCdvmgqVf8It3vkTTyCr3GXE79QAAIABJREFUDE6NRahYY9yZAfY4ysdnb5gcHS7JzhR98vlf0R2IfLuKZOJT9pthtDrfHtNiLJF30Zz4OlueIViiYXiNbMwRpJeKrrya5DH7Ze9ZQWGF68znJBs5dtzvWf7xn9z6S65gu/GXs++0/8ee427C8+qnUN/Ucg11jei2Mj4Vit4m5fFx80Kzle66bYmf4oMud5fzzr8KK16H7Tfa67IvF+ArauTg0x2+d7GPomFaXv2jWa6u2PsEP02pKKvq1nPXBy/j1w3e/eAennj+SN74+Bb2O8Wb1THr30+y/wx/G93npcD3JcXaeqLxGvy+4qzuee/je5g5LsSokGsjjAp5uXnCSJa+O5O/LTiJx/41nkfnHcIzC07DSkXYtPBa/I2SGt1knZ7k+lXVrEo7GeftHiBQ9yF1L/+cTf++nHN387Rq94zdPSx88+csevMSEpEPGf/d89vptoXv3U3pd0/g81euJ3zgudjJWN7kpam4O96YTdWtEnKaTdV4g8PQoiaeIw7Bwc467eC+OHnvtZmMOujcVsdQHHDvewdbxyn6Bs3OP/ZqNlBSBEs+ZczU27N9IJMDhyWfZhPMAW7W+KJAtj90uFPNuSdhOdGs0575LhnbhNlUTeTbVaxbeh87TqpkjxkPs8eJ92ed9jFT7+CrN/7AJ/OuYPWci/hk3hU0fL4IR3f7DQ1NOA1NJB96Mrts3qlrxIpuYu0rV9P42QK+feFCvnnyRNbP+TFe2+Ddf+YJ6RMjsjHuf/m4hlEhL8V+jVRRivAMnYk/CfDdY32sWWhiRhw0j93uN7//DD+L19zBc0vO5x+LpvPckvP5dP0CnEGevLbJ0rNOO7h69aYFSZLasKyuCPhK+HT9Al5ecRkbnPWMGG/xxVsmexzl45CzAhx8RoAv3jIx9Px9K1Dg6tRNZgrLgcsXfcXp8z7jlre+4cd7FPPA6pd47IuFaMUO78xLsOKZBGbUYefpFk9+vYRbx/2ITz97mleX/AJPsg5PpB6nbh26leTZN37Bn16YSKTpTZoaVxBN1AAwbs9zeGHJr5m36Cc8/8qZzFv0E15Y8mvG7XkO1bUf8K/ls7AdK+u0g2sTvrx8FuP2PMd1tqPfEInXuHry3TuJxjeB41Df/BUvvXkdz71xRdZpLw6FqWv6so1zXAl4OXHina307vfHzWL5x3/K6uBVnz/frURzm7stXEdZ6SPxmgHbYs4IlVVWzLi9xihx74tREqZixu01Rqissheafw2YIYTwCiEKgCcBJ+1Qk14qPwpYBdQAe6WPO6kbbafofBL7Udw4+Cc2U/ZeZyjPuB8FvCql3AQghHgaNw7i+i1ptKNtcDS/r3VZwMg7sLEZ2zl0eM6ClnacDz+BHxyD5ve7A5yTcrf4CZS3igcCV1GnHJ1gYbiVwRssDJNs3oDt8fDkqxdmy0eV7cM5e17E8GARNHzJcG+IX+1zLIaW4sCzgmDroGtEjSQjHA1NSxFLNGAk13HzwT6KQtuTSiTQyo1WSl4rN2jaZLP8uZaXZROO9DHrgAY+WfMAh+x2KkbCTWq0fuFthI+6jgNOH4GBH0e3mP/+TVRv+oAl8i6OmnYnq58PZt8G7zEtRpyNeZWXXehruWfHTGB4opjTJ/+RlJZkY8PaVm9UGyPV2LE43DMXhhXj+fFUUi8uarmGTCZlZYP2OZbVfi/4ZDJOfX3bl62KrQEbLa/u0gLlQNpR8BvoETOvLiNpsuovxwGw74wX8uofPLDHUT7WLDDZ56QQc468BJ+u85/Fv8zOVK/6/BkADjvrN9gpB4s4H339N3Y8YSwh30h8/gAvrriYSKKGUw9/mJMP+B2peENW93xT+wG8fxWzDriM4cV7sKlxNZ9/8lcm7HUhG+tXt8x+TLiNTcv/RMNni9hp4uVsl4pRFPJz/+HfwXIcnOZ11C+6kvU42RlLXr+aeyb9Fq1wRxqaPmPl+zcQTRueb6/5G0cc8GsOP6CSgK+k1WzRYbudidlUTbBsVzTNwy7H3MBn//5dy7Lno2fx1eJ7ANeRM5s3ZO+bryiMNzgc56lFaNMPx7FS7V6cxJqrMfzFrY7RNE82qj3f1nGKvsEyyNv3LQOcfy/GO+EA+Hgde578CI6ddGfal3yK94A9cXTNnUGvayT16pvoZx6Z7Q/5Zul1zYsTCmDT1M7+ScbqssdEvl3FJ/OuwFcUZs9pD7Dbkf+LZms4HoNktLbVcb6isPuSYVgxTnPU3XqurT3Ugb1ldxC3PrY4wANTvoOuw6xDt8Orpfh23sUAFB18GRH/dyisKGHfkzygOdh6Cm+JycFnhHBsDd1OYYea+XLFslZtF4fC6PrgNpuTts6GSKpV2YaIg2Xp2eXkmdjub2o/YPnbv+fQfX/FLkePwXAcDMOmvnYZu06aQLLBwZ+nb+lBjTX/Mtl7uociv5bWYeDVAaLccMA0nKZqmr/8M2N/fCqaHgDdIWIk+dXwYzCSdRSOOIARpbvgw8DwhVi3/GFS0VpOOvRqfKU7gqbz4rJrs0nh2iaSg5Yl6q5+vR3HsfLWKfAPZ9qE29A0jcMPqMzqycP3r8RgGCWhVPst5A6rYv6Km9u1ZVlxvKTj00mia+7Lnin7/5JoYhMr1/yNCXv9tFuJ5jZ3W7hMVvq2s/7RxKYet9VbaB7fUm/5rtNHnvFIlWNbYU03qo1QWeWWJqYDkFI+I4Q4CFiJO+F8N7AAeDAdh54AZkgpTSHEA8A/hBDvA6/ibs3WGR8DpUKIJ4A/5vl+DvAIynHvFbaj9QOpBsZ19+CyssK85YbPg5UeyDJow4pxEq3jr7W4lXdg83gDVJT2bBmV09ic/5zRWKvPmgb4PO6S+boovqIwTryGEaHh7ZJ52NFv2G/Sda2WN4496jbWLbiV8oPPafWj/6b2A6Lv3MSPD5+NJ1gKju3OoFtRlr14BrHmag794VM0N3/N/LdvbqcsTj1iNjFvAv9PC9EfTL/tT8eYysUtA0iwREN3mhllwIgdjqd+5d8J7DENcGfdNy69j+0mX0ncXI9HCzF+rwvYUL+a6k0fsPSLmzjqjOvRbR8YNv9+/yb22vn4vMpLbzaz94z6RlKPPYt3pzCcfSQL3qlqV98IhvBdfSH4vO5zboxkj/f+zwy00iIq9IFfKt9Rn91aMAw/T/y5dYz+WWevpKIi0KfnbfuyYLAwWOXqLl31V79XZ0RIa6e7nLg7w+IrCqMlLPjPexz449t5+5UrW3TZYTehp3Wg2VTNp4uvZsxP7sR6qEX/6D8pZcULJg3V7ss+XbN4acE5HH/ojUTT58jw5YZl1O/8IZaTbJU5ePqE23jx7duIJGo46bA78Zomn8//X8KTf5VHh7oJj15+4wqKQ2EmfvcCTp30fyQTDVjRTdS8chuRb1e5DpDux3A8FBLDMpv4csm9jNrvNGqiNZhN1Xzz3t/Zc8bDmM0bSEa/wtBiaFYDx+x/BR5vCDsV55DRp4Bl5tVpdrzBHR/sFHYqiq9oO/Y46QFcxe7wxRt3ZWUZM/UO1i1/OHvPxxxfhddXhn72ie5awoZv8r44sVOxlmOOuAl9k0lmLlIbVozh81BR3H2dNdD9vbP+OtCydUZ9JIHn4lKMB+qzfd+6uJSE36L4qPE4Xg/evcfg2BqaA+DAYWOxcbDmvILn1OPcrPBfVMMbkt2nVvHV8ofY5ehZfPaf3+fEolfhLPgI9twZTY+3s382fvw8Y467vdVuBmOOuAkj6kHzeEg9+S/YeYd2O79kZv+9559M8l+L8aS3m2tlD3Vgb+lG/rAWn1ejqLAlO7kZaWJ9+rcVfeHC7PHf/eGf8IXKAHAaLcx7Z2fP67nxQk6ceEerHWlOnHgHft1P8SDoDx31103Nibx61aM76EaQow68moLAcKZPvJ25i6/km9oPeHX5NXx/3Cz8eoBPXrsdM1rL+OmPQ0Eh3ktLMe9t6VvahaWsfMnEjIJHTxFo/ARPsIRE/ZfUfvIKFd+dztc5LwlLttuPDatfZMShF/Lcqxe201WnTXkQTQ8xetKVOI6Nrnsw4gaRgmSrpHChQHlee68wUM7UfSv56u3Z7Dbu53nrFAVH8so7t/Hp+kWtyg3NoKgwhOPsRNBfymlHzMZ2bDyGH10ziLQZJ4pDYXzeAKHiQsC9/45jE0s0UFQwklCwgqMP2pdQYDia1vWC5kgsfyinzxtgWHHHfcxxQpw06S6eff2XLWGih93J4lUP5pW3s7Z6E83jW9oLiejyIqW8Fri2TfGUPPU+Aw7OKbo8XT6zTb3ROR/3ztdmOpv94cB8KeXX3ZDx3Dxl7WTcUjTHGfwZMvMhhLgGKJBS/jb9+QLgICnlT7s4dDTweW1tM7bd+torKoqo2xTJxps76XhzT06Me6bMSMe4fzKvd2PcM+170zHu2Riv807G2G4E9fVRt+6/F5M6egxfvf8nN8Y9vVzejXFPEfbVsm7JvZR/dxqe4DC8BWVseP+fbHj3CUp2mcyw8RfybO6ANOE2mt95mqZ1bzFm6h34g9uBrhGJrWflf65g+HYHs/1+ZxJN1LV6K3n8oTeyfPWf+N5el+D3FeM3i9AsHVtPEU06vPdPPTtLvv8MD9+8fQ0Nny9ID9i3se6t2TR8vihrGPi1cqLU8Pb8SnwFZew89kIKSnbEo/nwzlsJa77EuPhHbNI2sPijhxi7+49bGdonjb2Z4qfTMe5t7+HPTmWTtoFnc7bgOGninZQa2xGx3O3f8iUm7ChOs6KiqL+8+dF00GfbyJM3OV1uWdvPAJf/cCkew5/NKt/2/+X3Hsi4S99m+b0HdnjuzPfjLn07r/O9JWUbNzbRV1RUFPVp+5tLX8g1mPprRUURmzZF3Bj3hbkx7gnMN37pxrhPrSLglJF6+GnYfUeco/fHTsTQAwV46lJoXg9xbwNr/+Uu2S3d+XB2OXQmWgxsn48PXrPYsNaNXz/gOBt/w5fU76Sz5MP2euP48TehawbLPvoje+88jQL/cELBMryan5SVwNB8eD+sxthhJHahhq05NFoNPJsTS/n9cbN4/f17icRrOOHgWcRWvcjIfX6AnYy1yug+ZmoVifQ44fPpeK0NpKK1VL/7Vyr2nIY3OAxvQTm6UUAytoG1867AW1BGeOKlvPfazJY480nX0fj5Egr2OraVLj/hoN/TtPLvjNr3NL557+/sMO5CHDQ+SbfzncMux184Ese2MZu/ZePqFyjb7Uj8pTviaIFWSVY9hk5RMkYk9Q0rX7sqe+4Dj67C32zgkEJLWHhKR5B64fVW41VPYtw76u/91GdH00l/Haw6IkNRkZfamE6sTqNQh2YbgsMcyoI2etREt210HJLPLcg+H88ZJ+AUFaAbhvtyJpmCeBwnaeFUlGITw9EAHLBSaClwlqzFs88YUs8vgKIQqeP3Yu1LOVvQTrkRz/ub0Cbtkd3VxdAKwAGnOYqeSOIkTJztyknpMXBSaJoHwynAtiBueChoasJ6eTGeSQdmt5jL2FsJrbbVlre7Ta3C8n8HYr7scvlgicb+p/iwfAmsnL5nGBq+1PpO7bV2dthV5+IELRKajePYaJqO39HBW0xT04DaBKPppL8WFXmpbtZbx7hP8RAONuPYJqZjYjsWupVC94VI2Ul03UOieQNr3/wDZrSWsUfdTt3ql4lUv8Po712FFvfjC+xAc4PGx0uSmFHYf4aHuk8eYMO7f2bE/mcxap9TSEZrsa0kmqbjKyhHi1pYBRpr5l5K0Q4HU3jAD3luSU5OoolVDNdHoSdtnIZmUitWYRw2Fj3gx/Yb1CbXZ1+c7Lr9ZCbsdVGrFynHHzyL/755L2a0lv2+N5O6j18kuPfxvPBWzsz5xDspCe5IQ+y/7V7CFAdG09xmdUKGbPx5my3bvPRezPiWnKNtVnnNDhG31vWorX60CYYkQog/ANOA46SUa9JlC4Bheao/KKV8ME95rzOUHfdzgElSygvSn38HaFLKrpbKj6YTx33jxqZBmVU+gsGw4aHW8mkOlh7H0XWiWjEp28CjpSjQoiQdP4YdASeJbnjRdQ+OlcBxLHTNh26EiNvNWKQw0tmAHSvhDqRaCM2GlMeLYadI0ozjpNA9BaQcC8tJ4jg2hu4BdHAsPBiQHqyTTgobB48WQLcKcSwNTbfx+JI4yWZsJ4WmGThGAOwUmmWiaR50PYSesrENjRRRbCeFrnnweIrRE0mwbNA1bK8HzbaJ6VE3Ns5xsBwLHS9BO4ietDq8h6XDgjQ01/TKFhqDyRFKy7NZjnsm87xy3AcP24LjvnFjU7us8iEawYpl9amGRiEWhm3jeA0023EdDcdxt6HyGFhazF0CrHnQtQL0lI2j6yQJYDs6umbjJY5m29h+D1Hc++o4Dg4WHs2HhoFNCsdxjXRD0/Hb7vkwQug22MkUtq6T9Hrx20lsT4qEk8B2LAzNg6Z5sOwEuubFh45txdEMH6Dh2ClwLGx87cYJw9AIehNojunqUM2H4QTRLBtHA0uPYzsWGH5sLFenazoamptZR/djOnF332HNwGtraDg4mg6OjYMGmsdtO22kG04QHIeUHse2LRzN0+H45TF0QoaNrbk62dG8pJwQQavz8aoniemU475lFBV5aU5ppGwdj25T6HFoamoJMfIYevZ3hK5hGzrYDrZDq2fn6DqO4e5ig+72L82ywXawDB1H19HTv4OYYeAlguak0DUDww7goKGl66BrWIZBDD1v38h3X3O3gtQcB8d2urS3DEPHp/nA0UBzMB2zldOewTC0Lu21tnaYXeBBMxvcFxGagePr2GmHwdFfwe0P0ZRG0tbx6jZFHhs70Yjj8aBZZvrFigHeQjCbcTQNByd7nbp3GJrZ6OpVww+Oja2BY5fg2DqabuPVU9hOM47tvoDRvUXYySb3ZR4eDDuA5oDt92CnXBtS84Uw7RiWY2FoBgE7hJ5ysL1e9FTK3a1A1zH9fvSEie43iDqN7osGzaDAKCWeanRtQ92LrhnYqThoXgzNwLHiaEYAEwtNt7DtlszqhSEPKbs+e26PXtqh056hP7Zc681zZNrS21x7RyjHfWgylJfKzwdmCiEqgAjuHnsX9UbDKctOZxE30rHNrqLOVxaxgrTEj2z+D7rdOS2LRJ7zta6rAQXpUhMNt2oT3nT9tGzZ8Ts3WYadc2wmjWKbJclm5sB0RvdEpg23Xr7I44qKIprSg7HZchAtBaE2R3hyzptO8piilWwkUulrzdybzL3IqZN7ik7uoabpJOO988y2dfY953kCxdtlP2/uHvKKbRfLstGseDYSOoKXFj3lAA71md+wCS1JYNP/m5DVc1kyOSnabreqQ9SmrQ5q0WOt85hkA5WSDhUVRdRubErrlRRRNDBzZc3gzznWT35a6xzLcmi2fO3O35I7tqCNoPniFVuWzcbpzNnMPTZ3/GgvV4aUZdNg0aaunR5xuh6vFH1PxkkflX7ubZ98yrJbfkcW6WeU/g21fXZW22TL6X6YArePtIzDZt6+mFvHAbrfN1psm1z5Wo7JZ29Zlk2s3W+9PZbldGmvtbPDmiygsOX3lBga/TrTH0am5a4HoCCtL3P0TBxydUdLeSYuOtjG0DPbVMzRCaZFPpvM1bm5OqzlfK6e1FyHPZMU3AKiSfdz1G5VP0Eqzzl8rf9Oy9uiA93n7DrphS1i0LnTDi1btvWlvdib58i01fbaFVsXQ9Zxl1KuF0Jci5ugwAfMllIuH2CxFIpBTcJKcf60eTz6/NRu1jcZd+nbJKy2AzYEirfLO0OuUCgUCoVCoVAoepch67gDSCn/Cvx1oOVQKAYz50+bB8Cjz0/Fb3jwh0a1+j5hmfiNtrN9Ln7Dl10yP+7St4k2fY2Nh8KiEQBMn/Ev5s75ft9egEKhUCgUCoVCsY0zpB13hUKRn/OnzWN4aBRxK8nw0CgSVioby57hwhP+TUlhOalU95ZT/eSZsTx0stvG+CdfB2DpjyZx1tkraWz+mufmnEDCSnHW2SuJp0wCHvdlQMLqeklaZwwr8VLXoLaEUygUCoVCoVBsu3S9X4FCoRhyDA+N4uDnZhEw3Bhcv+Hh4OdmAWSd+JLCcv7wf5HsMW9P+xvJlMPb0/5GKv1/5jPAPdNXkLBab2ifSOcb8AdHctbZK/EbHsY9cz8Bj49xz9zPuGfux294OOvslZx19kpOmvFCj6/F4+vb7eAUCoVCoVAoFNsWQoidhRD59m/fnLYWCiE+EUK8m/Pv5fR3M4UQM9vUP1cI8XhPz7MtzrgbAHoH+3J3VD5YGOzyweCXsRflGw2soztZTraMTvtsPhKWzXNH/ZKEZWNoGroFb069Djvp4MXAth0y24x6PFrWgf/5TwtalWU+m0kbv9c9IHeG3m/ojH/ydZb+aBLjnrmf16f/hOUn/wyAZ485i5P+/QRANpP95T9cmo2DP+vslTQ1f82zc07o8nq62kfZMuPUN7V/DCVFnk4dfzuVGLT9tQ/kGs0g6q+D9b53hJK3b+lA3tH0fZ/tsr8OpXupZO0buinraAZBf81lKN3j3kZde5eMphf7q22Z45PR2irHtsKablR7C8oqdcO3tDfa7kN2AnbtxfYukFIu7MX22jFkt4PbAg4DXh9oIRRbDTsD/+3jc6g+q+gtVH9VDDX6us+q/qroTVR/VQwleqW/2pY5Plb76dy1864sN5uq8RWFGTP19ppg2a7Tt9R5F0JowC3AybgvGR4CXgIeBobj7ix2mZTyrfQM9kIp5ePpYx0ppZae7d4eGIPrrM+WUt4ohHgf2AX4E/AUcBvuy7GPgEnAMVLKNUKIELAaGCOlzLuNhRBiITAzn+OemW2XUs7MKTsXmCKlPLcn92NbnHF/C/dhVJPeaESh2ALW9cM5VJ9V9BaqvyqGGn3dZ1V/VfQmqr8qhhK90l+T0dqqjNMOYDZVs3beleV7nvJIlb8oPGELm/8BMBHYB3cP1jeAS4CrpJRzhBCHAk8LIXbvop19cX87pcCnQoj7gMtwne1LhBBTgN2BnaSUDUKIWcCZwHW4W46/0JHTnsNsIURzzuenpJQ39uRiu2JbdNwTuA9doRgqqD6rGEqo/qoYSqj+qhhKqP6qGHQ4thXOOO0ZzKZqHNsK90Lzk4EnpZQJICGEOAz4Uko5B0BKuUwIsQkQXbSzQEppAhvS9Uvy1JFSyob0348B83Ed93OAa7oha0dL5W3a55XT0uU9QiWnUygUCoVCoVAoFApFj9F0o9pX1NpH9xWF0XSjuoNDekLbbYV2wXV6W4mAOxntZL4TQnjb1MmdLc/Wa0Ms84eU8r/AF0KIGcBIKeWbPZa8hTrcmf5cRqTLe4Ry3BUKhUKhUCgUCoVC0WO8BWWVY6beXpNx3jMx7t6CsspeaP41YIYQwiuEKACeBJy0Q016qfwoYBVQA+yVPu6kbrSdovPV548C9wBPbKbsGRYAJwghKgCEECXAabgz+j1iW1wqr1AoFAqFQqFQKBSKLUQ3fEuDZbtO3/OUR3o9q7yU8hkhxEHAStwJ57txHeEH03HoCWCGlNIUQjwA/COddO5V3FwQnfExUCqEeALIty3cHOARuu+4t41xBzcB3SohxE3AfCEEuP73I1LKl7rZbpZtMau8QqFQKBQKhUKhUCgU7Uhnsz8O+KmUcvpAy5NBzbgrFAqFQqFQKBQKhULhchcwDdd5B0AIsQAYlqfug1LKB/tDKDXjrlAoFAqFQqFQKBQKxSBGJadTKBQKhUKhUCgUCoViEKMcd4VCoVAoFAqFQqFQKAYxynFXKBQKhUKhUCgUCoViEKMcd4VCoVAoFAqFQqFQKAYxynFXKBQKhUKhUCgUCoViEKO2g1MoFAqFQqFQKBQKxTaDEGJn4LdSyv/phbYWAjsAzbj+dQL4nZRyXp7vM3wrpTy2J+dRjrtCoVAoFAqFQqFQKDYLyzLHm7HaKtu2wrpuVPuCZZWG4Vs60HJ1wU7Arr3Y3gVSyoUAQoiDgJeFEJOklB+1/X5zUY67QqFQKBQKhUKhUCh6jGWZ45vrPp278j9XlseaqwkWhkePPfr2uYXDdp2+pc67EEIDbgFOBlLAQ8BLwMPAcCACXCalfEsI8TiwUEr5ePpYR0qpCSFmAtsDY3Cd9dlSyhuBe4BdhBD3AU8BtwEG8BEwCThGSrlGCBECVgNjpJTx7sgtpVwhhPgHcAHwqy25B7moGHeFQqFQKBQKhUKhUPQYM1ZblXHaAWLN1az8z5XlZqy2qhea/wEwEdgHGAecB7wA3COl3Bf4JfC0EMLfRTv7AscAhwBXCSFKgcuAFVLKS9J1dgeOkFKeBfwJODNdfgrwQned9hxWAXvkfJ4thHg359+1PWxPzbgrFAqFQqFQKBQKhaLn2LYVzjjtGWLN1di2Fe6F5icDT0opE0BCCHEY8KWUcg6AlHKZEGITILpoZ4GU0gQ2pOuX5KkjpZQN6b8fA+YD1wHnANdshuwOEMv5vMVL5dWMu0KhUCgUCoVCoVAoeoyuG9XBwtY+erAwjK4b1R0c0hOSbT7vAmhtyjTcyWgn850QwtumTu5sebZeG7JOtpTyv8AXQogZwEgp5Zs9ltyd5f+oy1o9QDnuCoVCoVAoFAqFQqHoMb5gWeXYo2+vyTjvwcIwY4++vcYXLKvsheZfA2YIIbxCiALgScBJO9QIIQ4FRuEuS68B9kofd1I32k7R+erzR3Hj4J/oqdBCiHG4y/z/2NNjO0MtlVcoFAqFQqFQKBQKRY8xDN/SwmG7Tj902iO9nlVeSvlMOkP7StwJ57uBBcCDQohZuNuuzZBSmkKIB4B/CCHeB14Fuprx/xgoFUI8QX4Hew7wCN133GcLIZpxZ/QjwKnpmfu23+cyRUpZ38320RzH6W7drQUP7j5663DftCgUgx3VZxVDCdVfFUMJ1V8VQwnVXxWKfiCdzf444KdSyukDLU+GbXHGfQfg89raZmy79UuLYcMKqKu2VwfVAAAgAElEQVSLDoxU3WCwyweDX8belK+ioihffExf0GGfzWWw3vvBKhcMXtn6Qq7B1F8H633vCCVv39KRvP3UZzvtr0PpXipZ+4buyjoY+msuQ+ke9zbq2gdNfx3K3AVMw3XeARBCLACG5an7oJTywf4Qalt03DvE4zEGWoROGezyweCXcbDLtyUM1msbrHLB4JVtsMrVWwy161Py9i2DWd7BLFtblKx9w1CSNZehKndvoK5dsaVIKS8HLm9TdvgAiZOlTx13IcT1uIH5DvBHKeWdQoijgDuBIPAPKeVv03X3x40jKMFNRPBTKWVKCLEj8BdgBCCBM6SUzen99/4fbnbBjcCPpJTf9OX1KBQKhUKhUCgUCoVC0d/0WVZ5IcRk4AjcVPgHAZcKIfbDzdB3IrAncLAQIrME4S/ApVLK3XFT9F+YLr8fuF9KuQewAvhduvx/gdellHviOvx399W1KBQKhUKhUCgUCoVCMVD0meMupVwEHC6lTOHOlnuAUmCtlPLzdPlfgB8KIXYCglLKZenDH0+Xe4HvAU/nlqf/Ph53xh3gb8BxefbsUygUCoVCoVAoFAqFYkjTp0vlpZTJdKr+K4CngO1onZq/GjfRRkfl5UBj2snPLSf3mPSS+kagAvi6O7KVlRXmLa+oKOrO4QPGYJcPBr+Mg12+juioz+YyWK9tsMoFg1e2wSpXd+mqvw6161Py9i0DLW9n/XWgZesJSta+YbDJ2h17AAaf3P2JunbF1kifJ6eTUv5eCHEr8DwwJk8VG3dpfE/K6eK7LsmXkbOiooiNG5u620S/M9jlg8EvY2/K19+KsasssoP13g9WuWDwytYXcg2m/jpY73tHKHn7lo7k7c8+21F/HUr3UsnaN3RX1sHQX3MZSve4t1HXPrj662BFCLEz8Fsp5f/0QlsLcSeXm3F9VB24QUr5pBDiTcAPDAcKgS/Th50lpfygJ+fpM8ddCLEHEJBSviuljAoh5uAmqrNyqoVxZ8jXA6PylG8EioUQhpTSyikn55h1QggPUAzU9tX1KNpjGBqmL0HKsfBoBj7TP9AiKTaTfM/Ssjo3ChQKhUIx8GT0d3V0I1pQV/pbsU2Sa8fUxi0Mw6N+B/2IZZnj47HaKttJhXXNUx0IllUahm/pQMvVBTsBu/ZiexdIKRcCCCG+C7wlhFgopTwkXXYuMEVKee7mnqAvZ9x3AWYJIQ7DzSp/IvAQcLsQYjfgc+B04FEp5RdCiLgQYqKUcjFwNvBSeqn968CpwF8z5en256U/35T+/nUpZbIPr2ebxDA0fEYUSAJeTKsAy3IwDI2Neg2Vy6qojtUQDpZTdVAlpU7BQIus6CEdPcsKytWgp1AoFIMYpb8Vg4GObMX+PL/6HQwclmWOr6//dO6ihVeURyLVhELh0ZOn3DG3tHTX6VvqvAshNOAW4GQghetLvgQ8jDuDHQEuk1K+JYR4HFgopXw8fawjpdSEEDOB7XFXfu8EzJZS3gjcA+wihLgPN6T7NsAAPgImAcdIKdcIIULAamCMlDLeHbmllB8JIZrT59uwJfcgl75MTjcP17l+B3gbWCKl/DtwLvBP3JuympbEc2cAdwkhPgZCuDcT4GfARUKIzE38bbr8d8ChQogP03Uu6atr2VYxDA3dWs9b887ntSen89a889Gt9dm3mpUrXAUJUB2roXJFFXWJxgGWWtFTTJ+Z91maPnOAJVMoFApFZyj9rRhoOrMV+4uObFLTl+g3GbZl4rHaqozTDhCJVLNo4RXl8VhtVS80/wNgIrAPMA44D3gBuEdKuS/wS+BpIURXy373BY4BDgGuSm8rfhmwQkqZ8SF3B46QUp4F/Ak4M11+CvBCd512ACHEsbgvAT7u7jHdoa+T0/0e+H2bsleA/fLUfQ/3gbQt/wKYkqd8EzC9t2RVtMdnRHnr5Upize4PMdZczTvzKzl46qNEHbIKMkN1rAbTTuHBGAhxFZuJRTLvs7RJYqA2alAoFIrBitLfioGmM1sxZgX7RYaUY+X9HVhYyiLtB2wnFc447RkikWpsxwr3QvOTgSellAkgkV7J/aWUcg6AlHKZEGITILpoZ4GU0gQ2pOuX5KkjpZQN6b8fA+YD1wHnANd0Q9bZ6Vl2D7AJ+JGUsrkbx3WbPk9OpxjKJLOKOIP7OYlHCxAOlrdSlOFgOT7d0/0MgYpBgVfT8j5Lj9Z/b8sVCoVC0XOU/lYMPB3bitA/jrtHM/L+DgzltvcLuuapDoXCo3Od91AojK4Z1Z0c1l3ahkHvQvsE5RquT+tkvsuzRXjubHm2XhtimT+klP8VQnwhhJgBjJRSvtkNWbMx7n1Fny2VV2wNeAkWtn5Z5n724jP9VB1USThYDpCNJxrmLx4AORVbQsg2uHXfi1o9y1v3vYiQrQY8hUKhGMwo/a0YeDq2FfuLjmxSlTS5fwgEyyonT7mjJhRy+0EoFGbylDtqAsGyyl5o/jVghhDCK4QoAJ4EnLRDjRDiUNxk5auAGmCv9HEndaPtFJ1PYj+KG7r9xGbK3uuoGXdFh5hWAQccVcU7890lUMHCMAccVZVNOlJBObMPnZleiuRmItc19S5oqJFI+tnBU8g9e5wB3gJIRinzFJJI+nFfSioUCoViMKL0t2Kg6cxW7K8+2NYmDXh8aFGVVb6/MAzf0tLSXacfe+zsKtuxwrpm9FpWeSnlM0KIg4CVuBPOdwMLgAeFELOABDBDSmkKIR4A/iGEeB94Fehqxv9joFQI8QTwxzzfzwEeQTnuiqGAZTlgbM/BUx8lX6ZQy3IwYr7sQiRLGQlDEvc5VzCiKAQkITCq3zPCKhQKhaLn5OpvQ7ewbEPpb0W/0pWt2J9yZGzSsooiNjZtm/u4DxSG4VsaKgxP6Iu2pZTXAte2KZ6Sp95nwME5RZeny2e2qTc65+Pe+dpMZ7M/HJgvpfyaLpBStpMnT53Hgce7qtcZynFXdIplOenkIpk4JWUMbI2o56xQKBRDk4z+rqgoYuPGJpT+VvQ3yoZQbIXcBUwDjssUCCEWAMPy1H1QSvlgfwilHHeFQqFQKBQKhUKhUCgAKeXlpGfsc8oOHyBxsijHfZDiMXRCWOi2ja3rRFRmTEUHZPqKU9dAiaERwSBlqdz+CoVCoRhY8tkyanzqW5RNoFBsvSjHfRDiMXSKos1Yjz1Dqq4RbVgxReedjFNa0GfnNAwd0+tg4WCg4UtqWErRD3py+0oip680FRTigHqmCoVCoRgQOrJlmgoKB0SebcHOUTaBQrF1o1KAD0JCWFiPPYNT1wiAU9eI9dgz0Bzpk/MZhs5GLcFPF89nxn/m8tPF89moJTAM1T0GOx31lQLDUc9UoVAoFANGR+NTCKvfZdlW7BxlEygUWzfqFzsI0W07q3QzOHWN0EdvRk2vw2/efI3qqPtioDoa4TdvvobpVclFBjsd9ZUmA/VMFQqFQjFgdDQ+6Xb/z/JuK3aOsgkUiq0btVS+m/RnnJat62jDilspX21YMRg6pHpfyVo4WWWeoToaSS+n6h6GoREwoiQamwn5DOJqO5p+wdZ1tL12w5g8Fnu4D8dJQWOcZC88U4VCoVBsHfTUhsmM6ThJ0LybNaZ3ZMvYev/PGfWGnTMUyNgEnnF7oxUEcaIxUstXkXTyX7+tWRT7EspmUyiGCMpx7wadxWn1hfMewaDovJOzy520YcUY550MhSFINPf6+Qw0wgWhVko9XBDCQKM7W3oYhoYvtZ41cysxm6rxFYXZbWoVpmd7NRD0MXHDQ+iEScQT1ayde032/m93yp+36JkqFAqFYuugpzZMb43pHdkyTRj4evMCu8GW2jlDhbjhofDYCSQfezZ7z73nnYSh6XmvP7lxNWsW3aBsNsU2iRBiZ+C3Usr/6YW2FgI7ALmO2rdSymOFEH7gTmAyYAP1QKWU8q2enkctle8G/R2nlbJsmgoK0S45Hc81F6Fdcrr7Wdf65Hy+pMath3yPcEEIcJX5rYd8D1+ye+cLGFE+mecO8ABmUzWfzKt039Yr+pSAlSJVv4G1r17T6v5veu1Gbjtk0mY/U4VCoVBsHfTUhumtMb0jW2YgMpxvqZ0zVAhYqazTDu6zTj72LCWW0+76b95/X5reul/ZbIpeIWWZ4xsj1Uvqm776vDFSvSRlmeMHWqZusBOway+2d4GUcv+cf8emyy/H9bn3kVLuC1wNzBVCeHt6AjXj3g102yaVJ2bIsG3oo0VWKcumAc1t3wL3BU3fYFk2FYafByce1eNso4ah0eyB0u/fhBavp2n5H4l+u8od8J0kEOwzuRXpvhkwsgZWhsbPFrL3pN9s1jMF97mavgQpx8KjGfhMv3oTr1AoFIOQjL6ujm5EC+rt9HWPbRgn2W5M2dwxvT9tmc7YEjtnKNHRs/YkU1To7vXbmkVy42qaXptF9NtVwOY/3/5A2SODn5Rljq9t+HTuc4uvKG+MVFMcCo8+ceIdc8tKdp3uMXxLt6RtIYQG3AKcDKSAh4CXgIeB4UAEuExK+ZYQ4nFgoZTy8fSxjpRSE0LMBLYHxuA667OllDcC9wC7CCHuA54CbsNVih8Bk4BjpJRrhBAhYDUwRkoZ34zLGAX4AC9gSikXCyHOS58r2ZOGlOPeDTqN0+r/5Kh9gmXZGFZmCHe3C+kKw9DYqNfw0IdPM+07kxlWPJKyqTcTWPYIzeveAq3HL5IUPcTWdTTHw27T70b3BLESjXyz4nGS0VpwwEg4eZ9pZwNh5rlWLquiOlZDOFhO1UGVVFCuBkuFQqEYRBiGRoOngfWRDQQ9AWKpONsHR1BCSVZf99iG0bz4isKtnHdfUXjIj+mbY+cMNTp71pnrL/YlWLPohn5/vpuTN6Eje2SkUYFXjxPRLZKOg4EXn+lTNsoAEY3XVmWcdoDGSDXPLb6i/LQjZlcVh8ITtrD5HwATgX1wHd83gEuAq6SUc4QQhwJPCyF276KdfXGd8VLg07SzfhkwU0p5iRBiCrA7sJOUskEIMQs4E7gOOAV4oRtO+2whRO5S+afSLwjuBl4ENqaX1L8C/GlzXgKopfLdIIKBcd7JboI4yMZpRbaqlCbdxzA0Qr4Ylj/GQ2ue5rSdv0/Vh3/mfxbP5OJlN5M66EzGTL+XuNV3+84rXGKGQSJk8d6SW1gy7yLef7OK8MRL2X36Peiajc/X/ieeGQgvWDaTExf+gguWzWSjXoNhuEsGTV+CyhXuIAlQHauhckUVpi/Rr9emUCgUis6xAylqzXpu+eBRLlpyPbd88Ci1Zj12IJWt01MbJm4VsNvUKteZg2yMuxrTBz/dedYD8Xx9Pp0CvR4r8jXx2jV89fot+FLrs3ZHR3Rkj6Q8Ef4b+5rzl97A9AWXc8Gy37eyYxT9i22nwhmnPUNjpBrbscK90Pxk4EkpZUJK2QwcBpRLKecASCmXAZsA0UU7C6SUppRyQ7p+SZ46UkrZkP77MeD09N/nAI93Q9a2S+VvTDf6X2Bv4GjgTeBs4F0hRGk32myFmnHvBpk4rdAlp2OkM7I29WFW+f5gc7Pk5yatqZjxANO+M5nr33uolVK9YsUfmH3oLIyYevPZ1xhEeGt+JbFmV2HGmqt577WZ7H/Y7/jilRsYM7UKq03CGdOXyL69hpaBcPahMzFiPlKOlf0uQ3WsBgtrG31VpVAoFIOTJElmvvtgK30+890HeWTCdXjSGntzbBjN42P0lKvQvUHsZAzN09/p5BSbQ+6z9mmQdGj3rC3LwfRsz+4nP9rl7Hdv7KhkGBqexDpWz2tJdrjzkdexfvlDfGfSVUSsjpfnd2SPJByL37z/cId2jKJ/0XVPdXEoPDrXeS8OhdE1o7qTw7pL26XkuwBt39BouD6tk/kuT/x47ux2tl4bYpk/pJT/FUJ8IYSYAYyUUr65GbKTluUm4D4p5XJgOXCTEGIxriP/VE/aUjPu3SRl2TRYGnWOQYOlDXmnvSjajPPMfLTqDXgaGimxTfy+rt2y3KQ1HnSG+Ys7cPJSHbSg6F2SWac9Q6y5Gk33YDZVs3ZeJSEjwjDNosRw8Bh6p445gEczCAfLW30fDpZjKLddoVAoBhWWY+fX545ro3gMnRLDoch2bd8m3dulDRMwoqydeylrnv8Fq+dcxJrnf8HauZeq5GVDhIy9qg0r7vBZW5ZDxAwSSRYTMYMdOu1F0Wac+/5K6qaHce77K0XRZvw+gxLDaWVXdEbAiLK2TbLDz1+5noo9p6Xj6jumI3vEsju3YxT9S0GgrPLEiXfUFIfcCfbiUJgTJ95RUxAoq+yF5l8DZgghvEKIAuBJwEk71KSXyo8CVgE1wF7p407qRtspOp/EfhQ3Dv6JzZQ9w/bA74QQPgAhxHCgAvigpw2pGfdtkBAW1suL8Uw6kNQ/XspuGRI672SsrjK+5iStCcQaGFFUzh8nzqQu0cjjn8xlVf0naSdPda3+wNA8BAvDrZz3YGEYK+HGt5lN1TiNDaTueja7BZBZ6mXyyAOZ9p3JFPsKaTSbef6rRVnH3Gf6uXfcVayPtY6Z9Jn+rTImUKFQKIYqfk3Pq8/9mr75W9n2YnI6xdAl724ELy8mdOxEUj3pUx30J29wWJdx9T7TT9VBlTy0Jp1LyV9Mub8UJ7aJcLCcMn8p5+42nWJfIbFUHN8Qz8MwVPEYvqVlJbtOP+2I2VW2Y4V1zaguCJRVbmliOgAp5TNCiIOAlbgTzncDC4AH03HoCWCGlNIUQjwA/EMI8T7wKtDVjP/HQKkQ4gngj3m+nwM8Qvcd97Yx7gBTgJ8DVcAaIUQEMHFj9Fd3s90syrvaysm3zEm3k2jj9s467eAq5NRjzxC65PR0BtgOSCet8RSU8bVuc+WSG7IJQ67b7yf8/fN/cfouxxGzY5QYKlFIX+O1AoydeCMrF19LrLmaYGGY/SZdR/WS+wA3dk1riuPQsgVQyeVncuHup3Dlijuzz+72g35FwAqQTGf8Ne0kt3zwaKtkMAqFQqEYXBRTkFefF1OA1tE2cN0c57e25HSKFrqzBD5fhnrPuL1J9bRPddCfvAXlRK0CaDMh0DZ57iingovED7jirZYEdfeO+zV3H/hL6qxYNlQkm0jXKEfR/3gM39JeSESXFynltcC1bYqn5Kn3GXBwTtHl6fKZbeqNzvm4d74209nsDwfmSym/7oaM7eRpw0VdtdEd1FL5rZiOljk5uo5WWNAq6yi4Cli3Ow8ByCQ1KR5/MVe2iW2//r2H+Pmep3Hvx3/n0uW3qGRm/YDtaATmf8qh+93ElGlPccjUB9j47t+JfLsKX1GYMVNuxPnPe9n6Tl0jzVoia+SB++yuXHEnccMN/zF9ZgfJ6cz+v0CFQqFQdEgdsbz6vI4Yum1v0TivktNtnXRkG7Zd8p7JUJ/L5tiO+frTmKlVJLRh7SZ38iXPbdKbs047uH380uW3EfIXt8vvoBLpKnqRu4B7gSsyBUKIBUKId/P8+2l/CaVm3Ldi8i5zeuwZtMvOhKLQZm1xl0lq4ikozRtfVGc2sar+E7euSmbW50QwKDpmIqSfs7b3bux84hXY+1+MHijAmfsmzhctb7m1YcWYdJ58LqUl836f0pIYqBkXhUKhGCx0lLMk5VjYum+LxvnuJC9TDD06sg3bzppHMCg67+RsXW1Y8WbZjh32J7O9s58veW5Nor7DPq7i3BV9hZTyctIz9jllhw+QOFnUjPtWTIdv25Mpmr1+PF1sGZLZ9i3kbSTki2W32bAsh//P3nmHR1Wlf/xzy/RkUhGydAQuVVAQJYjBtmtDxa67NlRUEAtBxAbYUFcClkVFLKzuWnZ/NlRwV11BVnQRCwrChSgiaoIkJJlk+tx7f3/MzM1MMoGAlID38zw8D7kt595zcs55z3nf7ysiZxQM8UUazP9bYmZ7nqSCrG3CBdhuvAhh9DD0oB/BF8R4fxW2349oVsdSC3UnISFJAqIgZj4vWN2FhYWFRVtC2k5//WtS2bZGvMxi/6S1nhjJ+YUw4ULkW8chTLiQBptjl9qUphlxjw3BBkYUpxTImLotkzFeE/a10MYtIV2L3x7WjvsBTNLNKdPKaDiioW0nPUxq2rdk+o6eJ5cRSaQWc2pOZh0+icmfNsbVzRh8NY+ufcmMM7LEzPYOMU0nZheJGlvZ8PatZn31OnYmQk580E2tY1vEoGxoqekOn6wvp+akRq7FZsjMGHx1WtzYjMFXIxtWd2FhYWHRlnAJdv489EamrJxj9td/HnojLsFO9ABMZWvx69ne3LDpZnVM0xO78FL8nLb9uWNL7GhOmSSpIp9qvL+5eWmz+eaDQyfh1lwZ5zL2iGN3fCYLizaJYBi/OcOqG7CxuroBXU9/93btstm6tX6fFKo17Gz5UhVlk25O0nbUPyVJiKd7MaKIosS6V69IExPJ6V5C16OnoOsaDTY771eu5KgOh+KL+PHYXMiChCgI2LEjhuQ2uUK/O+u4Xbvs7aj77Fa60UKbTZJlD/LDsvtp13c0stNLLORj69o36XL0VBrCzVWAk+Ivcfd4Kb7I4oiyKfgzL3y3mPHKuUhivD51w8AmyLgjnl2q07b8d9VWy7YnytWW2mtb/e4tYZV3z9JSefdSm+3GdtprW/+WtiyNoB5BB3R0REREwCXaiTa03Z3Htv5dU2ltWdtCe21SHrZurU+b2yHYiOLBU9/6ueHO0vT3hTQ3TinA+tfGNhOo6z3mGfwRl3mf5ohSHa1lcorY4rRBV7H8ly8Z0/VYfFE/VaFa3ty8lCn9LsMecaTMZWQkQSCsR3HZ7AiBtjkP3dO0sfZqsZuxttAOYGI7sdredDW071lPp3WwnvYD6DDofNOY73Dhi3RwF/LK9+9xQsfhXPvJfWYnO+vwSeS7crBHHEQzxDBZ7H4EwaDDoPPZ+P5d5mp29+OmIaDFB8Mmg5emGUhBu+lQpmEQE2LM+PIJChy5NMSC3P7FX9JWsd149v6LWVhYWFi0SASdX8K13Pb5o2Z/fe9hEylyFSIcQC7DmYzB36JRtrO0tNPtz+6Eaw94YrT0+wQxK21O6W4/gOxhl1Mr6YiuCE7NyRZjK6Ufl1HgyOXRI6ZSF22gJuxj7rqXARha2J+O7oOoopbqcB0amjmXsSdE7ZruvrejMGM7aapcb484rPZksV9gBa0e4MQ0nTpNoMaQqNOEFjtmpxSgfFGp2bFGgzWmAihA0ZBLTaPQ3X4Agj2LPIeXQfkKN698KE1IZPKns1nv20SF8Qs2u9XE9jSSJCCgmfUD8RypG9+/CyMWik92WoFm6FQEqxjf51zTaAdLVd7CwsKiraIZumm0Q7y/vu3zR9GMA2fR3DQGXxvL6udPY/1rY7HHfsoYI22RTtO5XaS+gvJFpdjwt2puuLt+nyBK5pzS3X4AYskkJpT/k9Ef3MgVn8ygQW4wje7VteVsi/i4/KMZTF45G4AJfc7j/q+f4ewlkylb8xwT+56flrM9Yg+3kA2nucJ8JuX6rWKV1Z5+gyiK0l1RlEz523flWUsURSlPqMyvUhTla0VRzk2cm6Eoyozd8Xssq8oijhFNWw2t+GwB3Y+bZna0NleeeT572OXMWfsCBY4cDnLmZ1T1dMlOblo5m6AtuPfe4TeKUwoQDdak1R/EB8xYuCG+Q7EDJElAEiSeHjGD37natagqb2FhYWHRdtBaUtY2Dhxl7ZaMwdYuSv+WEYlknBuI7KGF+CZzyeTvMxDMlHDZwy5nytdPbVc53hdpoMhVyIDcnkwffBV3NUk/POPLJ9BSQn13RmF+Z4x8iwOersDBu/F5V6iqOlhV1UHAecCziqIctBufb7nKH8jslGuZYMOeXWR2uP4tq6lc9RJ9z34W9BiGodF79MNUl7+PnN+dpV8/znjlPPIdXh4eNgWX7MQXaWBB+UKqw7Xouk5p/4vRDA3BFbHckPYkRhQtEqDPmCexufNBEIk0/ELN9x8hO7IQBAOPPZix/uPuYhGChPmhvpL3f/4fVypn8vSIGdSEfSwoX8jq2nJLVd7CwsKiDSIKIhf1OIXTuoxCEkQ0Q2fhD0ta7K9lScSDhphwkfY3cZFuCy7pTcuotWAMxhelm2u4WKQgSGlzO4jHliNI2O0iThowjBiCIBMii8guhDc21UfK6V5C3calQDzMsuOwKxGMKHZnLn3PWkC1EKPi68zK8UljekH5Qh4YcgNBLYQv6m/BKI9hl+xxg1sweKp4OhE9iizK+CINvLl5aUaF+e0Z+QdOcMneJ6pFhvvC1WW6HisSRbnC6ygotUn2j3/tcxVFEYD7gTFADJgHLAaeBPIBP3CdqqqfKoqyAFiiquqCxL2GqqpCYre7I9CLuLH+lKqq9wKPAD0URZkL/BP4MyAB3wAjgd+rqrpeURQPsA7opapqqDXlVlX1G0VRGhK/b7dhGe4HCE0HuqAkIYV/3K6CZ9oAjY1epz3KhoUTzes7D59IrO4XNrx7c6NS+Ul/psZfTZGrkKAWpj7m5/6vn0lTH8+1ZVMX9VO25rlWxRpZ/DpE2Yloc/LtO7ek1PUs2iknoqbUZ6b63ypWmTlTk2rEs1Y/x9Itn5miMC9tfIcLe5xkqcpbWFhYtDFcop0/dCzmuv89kKK4fSNO0U6sybWpgrWxhChZdooomd0uIu9g3rCnyVRG6dozWjA+bdt5kgWAIdjpcfwMvntvhlmnPY6fgSA5kRt+ZO3i0pT5XRk4O+2U8Z4ppr3XyQ8CEAtU0/moG/ju33ek/I5Z2LIKWlCOL2Xyp/H5SHW4llx7Njd//BCl/S9udn2RqxC7YDPnMAWOXCb2PZ+7Vz2Zpjzv1JxESX+fTMr1Vhq5X0dUiwz/uf7bhfP+N7mwOlBBgbuo21VHzFr4u+yDT9sNxvvZwAhgIGAD/gtMAKaqqvqqoihHAv+nKErvHTznEOLGeC7wbcJYvw6YoarqBEVRRgG9ga6qqtYpinIn8CdgGnAW8FZrjXYARVH+QGCszG0AACAASURBVHwRYC1wSqvfdgdYW2gHAMmBzpj7ArGZT2LMfQGXXr9d17JMMWNGLIJy1l8ZcNFC+o55GilomEZ78hkbFk8hKxbjkcOuJ9/h5Y4v5jZzX5IlmelfPrbX3ZBkSSRHMsgTNHIkA1n6bTRv0dBMox0SLvKBKjYsmrxd18KIPdLMXWzKyjmM7lxi/nzXqnlM7HsBBfZcpLA1SbKwsLBoS4T0KDclUsFBvN++aeUcQnrz0CYPmqkkDvHc3dqzr+FBQ5ZEXHo9G/axS3qmMhqvLadXws0aMBcUQpp7r5VrfyUYdSC5C+g2aip9znySbqOmIovZCOEgGxaXNpnfleKkocVnZZpjZQpj2LDoJroePYWDT3zANNobf8dkHL4tPHjIODMHe5GrkKt6n02R2I75xdN549iHmF88HQODimAVC8oXMm3QVWnXlw0tRRN0cw5zac/TzBS2kPw7mE3AFiDqDoE7Zsaw2yMOyoaWNnuelUZu1/GFq8uSRjtAdaCCef+bXOgLV5fthseXAP9QVTWsqmoDcBRQqKrqqwCqqn4CbAOUHTznA1VVI6qq/pK4PifDNaqqqnWJ/z8LXJj4/yXAglaU9alEjPtq4Dbg3ESZdxvWFtoBQMaBrsG3XdcypxQwV0iT58oXlcYN9pgHURSIuMMZnyF7CoiIIBmxjO5GsiDtdTekHe0kHMjoejyGzdN+AEVDLkV2erG5C7G5C9LqrzGuzYUkCQQJZ6wnrz0r7WdZlMAAydZcnd7CwsLCYt+xvRj3phM8UdeJpeTuBsDrQcYgR48SFfa9S3qmMhqry3GMOY7eY57Zqy78druIQ6gnVFdHtkMmbGTvkiv5vkTTDMJSOzx5boxoDCFLwNBjGBIZ5wiG0dRPI47DLpEVDUO9H6MhgLFiNdl/GEE0K5axzei6higYGc/ZHB6092bw2PBrkPO6IyLj1JxUalsp/V+jB+DcI2+hyFXI6tpy5q57mdL+F5Pn8NLeWUAoFqYyVGW2fa89K+PfQV2knupwHZ087bE5onhiHqIRnXYU8tSRM9JT4lrzm11G12NFSaM9SXWgAt3Qilq4ZWdougrZA2iqJCgQt2mN5DlFUZruNqXulpvXNcEU5lJV9XtFUTYpinIm0F5V1f+1oqxXqKq6pBXX7TK/jS3JAxxR102jPYlQH0pThYcmrmUtCYj46ojNfJLo3BcRJDnjMxqcWTy5/hVsoo2nR8xg1tBJDMjtCcRXLiN61FzJTLKn3ZC2t5NwoCMI8ZiyTsMn8MOyMta9Og71jQl0Lp6Ip/0A87pkXBvExVl+8Fea9TQgtyezhk7i6REzyLNnp9XnpoYKqsK1hGVLuMXCwsKiLSELEiXthzBr6CSeLJ7GrKGTKGk/BFloPt7qooiQ5zV/FroWIZ9SQnTui0RmPglVvu3PG3YSSRLw2IN4bD489mCrVLublhFAyPOiGwL+iAt/1Is/4torRrsc/oF1r17BV8+dzrpXr0AO/4B9P8yUo2kGEi40zcfa18bx1d/GsPbVcRnnCILQfD9PlkQ89fVEH3+ZyMIPiNmjMOZwtGgdomhruc0I6Ury7UfPof15z9Hg8NBp+ERyRRv5uo5TcxK0BZt5AD78zQs8MPQG03h/c/NSCh25aIbGT8FfCGsRcw6TFLNLpchVSJbNzaub3uesD0q56uO7qWSrmSJXCtqxB11IQbtltP9KRFGuKHCnt4MCdxGiIFW0cMvO8CFwpqIoNkVR3MA/ACNhUJNwle8ArAaqgP6J+85oxbNjbH8T+xnicfDP72LZdzvWjvsBQHKgSzPey6vpdXKZ6faW7lpmNBOjg0SnXR/CAAyvB8EQ6HXyg2xYdFNa7JLPMPhjj1MYt/yutNjosBbBJsg8X/4W0wY1qoCmuiFp7JnOMeMqfY0PSdfhQI9bEmW6jLge9Y0JaR4U3703g26jprL+zevNuDZDsANxcZb56181Y9jP735iWn2l1ueDa/5KdbiW+cXTrQ7DwsLCog3hEG1c2ftM010+GePuEG1mjHtSz0YzokjXngGvLcdYXY58QjGxFxc1Lni/8zm9xsxkw39uTRnzU+YNO0FL+bx3FC/vRyL7sjHmQryQ50W6bAz1SMDe2+12CPWsS8x9oNEFvM+ZTxHBs9fKsbvQhAAbFt+03TlCr5PKCJFF0+/sQSP27GsYXg/a6YewYUk8hDKnewldj55Cr5NnmaF5qXNNly1Mj+Nn8POqF9GHXsyEhJJ8kauQBw8Zh7ZkFrKnEGHEBIyoQGn/i/Has9B1HR0dWZTJtWXx+PDbsAkytdEGrv74HvMZjx5xM2WHl1L6aRkLyhcyY/DVprt8UqNnzpq/MbpzCUu3fJZIV1zG/OLpOELO+HewcrnvFryOgtKrjpiVGuPOVUfMqvI6Ckp/7bNVVX1NUZShwOfEN5wfBj4AnkjEoYeBM1VVjSiK8jjwsqIoXwH/AXa0cLAWyFUU5XkgU1q4V4H57B7D/VZFUSan/HyVqqp/39mHCIbRukaqKMrZwGBgJnC6qqov7uwvayN0AzZWVzeg6+nv3q5dNlu31u+TQrWGlsonSyLZ0SBa7RYMp4Sgi2heG5s/fpR2fUdjc+VhcxcSFvJMN6/koFqeYtj3GnUv0htfASQ659uwuQvoOOxKHDmdAYMfPnoE7zE3c2Wi80xS5Cpk6sCxuCQnj6x9AYBLe55GL28XZEPe4x1ijmRgzH0hbfFCyPMiTLiQOq1xlX931nG7dtl7K+lnN1poswDZjgCGFuLrv53Z7NzAP76CIEqEajdh83YkTDs0zUBzRbjikxkUOHK5b8hExi2/e7v1ubq2nDeOfQh32LPT9diW/67aatn2RLnaSntNlKVNfveWsMq7Z2mpvHupzXZjO+21rX/LmCfMlcvvbNZ/zy+ejux3ZB7rTy7DYeuAqBnxnfZUuhYhXnQcur8BMctLUNw193CPPcj618Y22xzoPeYZ/BHXdr/rjpTv9wbZtjq+ev70ZscPufgN6iOZQmPbRnuFxoUaSdDQDIkoHhzGNr56vvkG5CEXvwGGsF1V+TxBIzbzSYQrTmTtilvN0LxOwyew8f27GueJuV0wBKcZxiBJAg620iBJXP7pg83a6Nye5wDw8C8ruLz3GG5e+ZApMpdqgD849EZybFmM+7j5POXJ4Xeg+jbhtWdR5Cxgc2CLqSqfzIrzZPE0xi2/y7zv6REzcIkO7KKNiSvuTxdR1vd/EeXW9lm7u72aqvKGViQK0m5Tld9XJNTsTwKuVlX1tH1dniSt2kBTFGUqcALQGZgDTFcUpaeqqnfvycJZtA4Dg7CtnqijBlF2oUeDyLE8YoFqyhfFF3eSA2YkEaemaQYRuaMZMyaJNtjmwzjjcASPmw1vjcfmLqBoyKWINhfhus0487pRt3Ep7hET0zrPAbk9ubbP+XT0tEPTde4bch0/+X/hxY2LmTLgMqSAfY/ttCdpK6v0+wIDgai/KqMHhYGOIDlx5nVDx04yciApzlK6soywFm0WG1bgyKV7VkdqI/VMH3wVf1n7EnbRRtgZQtN0a3XawsLCog2gGRqHF/Tnop6nmungni9/y4xxd0oBNi+fR5eRpchOL7GQjx9XzKPzyKnIhrOZt57g8yPjIebJwm9IxHY1pvtXpHCLaTp1CICUGLP2wRguyi0o2bdtv7Omng453UvoetQkEFtKCydTH0l6EGT+zqZXp8du3l805FI2vn9XPGbdXYCuRYkFtmHL6mDel4yv16TM6dwMZy4AozuXcPPKh6gIVjF90NWEtAh3HjqemB5DRCSsR0EQKHDkUhGsYkBuT8b3OZeDnPkgCOTas3nom79zac/TzGxGSYpchfgiDWk/14R93L7mOaYOHNtMRPmpI2cgBe27XgG/YWyS/eMCd1Hxvi7HbmQOMJq48Q6AoigfAHkZrn1CVdUn9kahWtsDnQ8cAXyiqmp1Ip7gY8Ay3PchyVVVUdSJBQJ8v+T+tHQfnYZfi/r61UDzAVOWRDySgaw5MAQHoVAlG5bEO/q+Zz2NzV1grqY2rtLPIqd7CZLYmEpjQG5Pbup/CSE9bO7aFrkKufvQCUzocx4xI4Zd2vMGXkzTqXdn4ZlwIVJilb5+H6zS7wsEyYYt+yB6nTKLDW83uqt1P24am5f/hU7DxvH9kvuIBuLhE4arM/ZojGwjj/nF0wDSUqMMyO3JxL7nc9XHjfX5yLAp1ER8lH5alr46baX4s7CwsNhnuCUH53T/fVo6uD8PvRG35ECQRETBoMOg89PG8u7HTUMUDEQBhMvGxN2gUxa865ATY2fm8bNVO+IthOMh2PDYg4R9DXjs0j7JE98awkZ2xlDBsJFNW94MSF2osWe3B8Ng3etXY3MXNEsLl3wfSTIaUwOnCP857BJuNAQEhMvGpG0QyE5vs533TCERmmYgImdMvyaEagHI87Y355Mem4s7Vzbuts8YfDVz1vyN6nAtfx56Iw7RTliPMCUlNGTG4Ku5ZeBYNF1n1tBJTF45O223fv76V83fOW3QVcxd9zIVwSpcsjPt21m53C1SUVX1BuCGJseO2UfFMWmt4R5VVTWsKHGlfVVVaxVFaZ5rpAmKokwHzk38+LaqqlMURTkemE3cgnxZVdXbE9cOJh5HkENciOBqVVVjiqJ0Af4GHASowB9VVW1QFCUX+DtxdcGtxCX3K1v5Pvs9qauqXUaW8sOysmaxS8rpc83rUwVm4q71IYRtfqIvLoKzitmQcH8CiAZr6DjsSrMjTj5zw6LJKKfPpUaLMuvwSUz+dDaX9jyN2mi9mcsd4p3fHV/MZerAsXhkF0XObDQNJEHAHtXR9pAx3SZW6fcJOnq4ASQ7fc58kmjDL0SDNfz48Vz8W1YTrFpPl5GllC+azIZFpfQ7fT7G3DfQa3zI40/nxzyDB4feaMZIXtn7zLS0KgWOXESyCMUClPa7igXfvszq2nJrddrCwsJiHxPWYzy1/jVK+11Fji2HumgdT61/jZsGXEK7QBjNFWk2lm98/y76jn6c2L1/RejfE9s156EjtGrBu7UZXEKam54nl6W56Pc8uQxD87Nh4cR9lie+tUQiOji60OfMp8CIgbB/qMoLKQs1qXPDSH0Fm5c/SrdRU3HmdsXQYwiOXMJhI6MWAa7OuAIBqA8Qe3EReD1Io0fR++Qy1i8qJRaKCxkmd95ldyF5JTPAmc+2UD2FeRH8WnzOaY84mD10EpNSDepDxlGfiHEvHHUTRa5CLu15mmmQQ2OK4dL+FzN55WymrJzDI0fcnPGaqQPHAjB//atMHTiWzp72VAar+ddPy7m+34Xc2O9PlNdvZu66+PylyFVIMJaektvK5W6xP9BaeczNiqKcQlzFz6Eoym3Apu3dkDDQfw8cSjw2foiiKBcQV+g7HegLHK4oStIF4W/ARFVVexOX6L8ycfwx4DFVVfsAK4E7EsfvAZapqtqXuMH/cCvf5YAgNXdmcuUzlfgOe3wgbJrz1IOGUF1ritKkuj8BVHy2AEdul4zPFEQJm8PLF1XrmDf8dnp6O+OSnRndoPIduTiFIq75YDVnv/MZ1yz9mip0pN9IfvW9haBF+HHFfGL+KtA1osEaKj5bgH/LagCzjST/rzfUm66R2W+vIE934JFczC+exqvHlNHVU5S2+36tMp4bP9zA1e9/xyOfB7hWGc+A3J7m6rSFhYWFxb5BQOCCbhfyyOcBJnzwPY98HuCCbhciIMRDx4KhzBlkgnGjxVhTTvTxl9FFkTpN2KGXWmszuKSG4w24aCG9xzyD5Co0jfZkOfZ2nvidQdMMdENEECR0Q2xziwuZEDDMhZqmc0P/ltWsf/N6ooFqtFiEcMyOW27AiAXpMrIUT/sBZp3Y9XqormucJ26qQHtzCfawl77DH8Dt6kavkx7E5spDdhcijbyHG9bonL/sJ67/KsxPMdmc62maQSfRzdye5/DK4bfweN9LKAqH6TLiOrqNnEy2nk3Z4aXkObzbTVFbEaxCEsQW55udPR24rt+FRPUYD3/zAoFYiOe/e5sJn9yHJEqUrXnONNrLhpbS0XWQlcvdYr+jtTvu1xJX1DsE8AOf0JiUviUqgFJVVSMAiqKsBXoDG1RV3Zg49jfgHEVRvgFcqqp+krh3AXCnoihPAUfTKOm/AFgK3AyckjgH8CIwV1EUm6qqO/QEOCBIiR9Lrnw2U4i3ORlw0cJmOU9FXUdw2M2BV/BH0u73b1mNgJj5mYKIPebmyHaHoOk6NskGhpHRDSrP1o7xH3xDZSCeRqwyEObm5Wt5vGQg0j5yYTcMHZsziGFEEQQberRtuum1FlkSMUSZDiOvIxKqJVSzgdp1b9Fp+ARzx92eXUQsFK/r1MwBAGyqoMOqn6k4ohs/1P+IS3aSb/dS0n4IS7d8xqUHn8fMFZvT6nDmis1cd9h5lH0zz1qdtrCwsNiXGE5mrvi2WR/9+DH94+7vvmDmsdwXNMeBncnAsjMZXDTNwK+5SIboeWy+fZ4nvrXsqir+vsbQtR3ODW1ZHeIu8uEfWZfiEdH9uGnmvMEwYmnzRAD52COILXjDPCZ1LUL+0yi8R97I9Z/9nNYGp3y0jvklA8jFQLdJ+EQR3AUIgWrqVjxNRWJuoox5Bi1mYJdt2G22jHPJZIx6kasQzdCbXXNRj1MQgQmfzKQiWEVJ+yFc3y++eDVr6CQWlC/E0I1medvR4akjZyAIoAsGuq4TIbzf6vdIkoBoC+DzN2BzSvv9/NYiM6013P2qqh6XyJ8nqaq6Q7lCVVXXJP+vKEov4DziufBSe+0KoBPwuxaOFwI+VVVjTY6Tek/Cpd4HtAN+bs0LFRRkZTzerl12a27fZyTLF0kxtis+W0D346alxRj1PnU2jqyDEIT4iqc75RmGrwE9HGkUpfn6R3qf+giRhp8RbXFxO2RHs3ioHsfPgPoI7lyoTzQdAWjvyueBoTeY4iJFrkLuPWwiUd0wO/IklYEwiMI++c6GobO1rpzXl92Iz1+B11PEGSPn0C6vp/md2jKZ2qze4KcqUs3rH5Wa73Tq0OlUfv4SRUMu5YdlZfQ4fgablz+aSPcyC97+pvEBXYuoHd6b2lA1r256n9GdS5AEkRv7/4kung7k2HKoDNSk/c7KQJh8R0dmHz6Zgzx5iFk7/nZt+e+qrZatrZartbTUxybZ397PKu+eZV+Xd3vtdV+XbXv83BDIOM7qhhAf499dRa/T72XDktsaY5uPnYnx2irzeiHPi2SXaedN/waGbkCDn3ismwRZHmjwozUVtGvh/qZEmmwSQNyQlG1O2uW2rW8c8VfzTcJoh0bvgH7n/BW7p2Afl67l9tqquWH2QYiBGr55Lf39Ut3rBVHGCDcg9O+JPGwAgtsFWe70tMObKuC9r5FPGkll4Mu0clQGwoQ1De2jz/jhqG5M+izFTf6Ym/CueJbOAy/BIXnwO6JM/O/9FDhym6USnjH4ah5d+5IZn9403XBJ+yGc1e14rvn4XiqCVZzWqYRLe51GTaSemrCPNzcv5YZ+f8QtO8hz5qAbOtvCPoKCH1EQcYsOtoRrmPTpLAocuVzZ+0y6eDrgll3kO7yI+8HcEFLmt0v2z/mtRetpreG+UVGUt4D5qqou25lfoChKf+BtYDIQBZQml+jE7b+mbO84Ozi3Q/b3dHCS5DDjx/xbVlO56iX6nPEEBiKGIBPS3Pir/Gn3pwrKCEWFyH88ldgHK5COPYKYvjVN3K7XCQ9gsxfQbdRU05iXnQWIQRvVQhBfxM+UlXOYPuhqBAFe+G4xpf0vJs/hJc/uJarFsAkS8449hJpQlOfX/ciabfV0cDtAN/bJd7Y5g6bRDuDzV/D6shs5d9SzREM7v9q/tydzmdqsyxkwjXaIv9P/yl/kmBETESQbB495Artfp+fvZ0IMxJiNurNHEjlxMDZfCNxOYug8/+1bzXK5zzq8lFw5nw7uCnNi2D8/m7H9u1DocCEDtTXBHWoWtOW/q7Zatj2UDm63Pm9HWOng9h0HSnn3ZpvdX9PBiW6JkUX5nNK9PV67DV8kytsbtyAKIJ93ErGXFyO98RV9T3wADspBl+zYgiKabzkGCaN73DnEYjpCVa0pNgeYseypwnWB7GzciQwueD3IJxQjtMsjFtNp2Obfrqt96rwldRe7IexAC+y5b7wr6eU8tswhBrFoiLoW2kNbaK/bmxsiyEi40Kp96HLm97O58uKeBUI2zvZ2bL8vJrrgdYwaH7YrzmqWhUAeqGBvCNHB7UhbQOrgdrA1Vo1xzBBikWCaPs5Nq+bx7FG3IS14F/3iroSNABXBKiqCVcxd9zKl/S+m0JlLoSMXDIN7D7sWA4M5a/7G0i2fURdtYO6Rt9AQDZLv8LIltM0Utzu7+wlM+OS+tFzuz3/7FjcPuIwt/q3UxvxpIruzhk4iqIU5vKA/J3U6Km0OtD+lh9uV+W1bXpC0aJnWGu7dgQuAWYqi5ABPAX9VVXXr9m5SFGUE8Apwg6qqLymKUgJ0SLmkiPgO+U8tHN8KeBVFkVRV1VKOk3LPj4qiyIAXqG7l++z3NE3nhmAjkKbOmt7RZBKUka84C+nc3xPTatnw+uR0Ibp3b6bvGfNwiV0wQmGEgA1ZclLjlYjoUVMc5CBXvumetHTLZwCUtB/KVb3GMX7ZaioDYTq4HUwbpvCi+iNX9O8SF6jbmx8rgWFEzU4tic9fgdEG3fRai0Ys7Z2KCgZyWO8L+MeyiY2rrsVl5HxYgTTyML6Ta5i0osxcWe6alQ+GwejOJdy1ah4FjlxT5Kg6GMDhruP+EX2Y+tE6Cpx2rjmkG/esWG/W6wPFfSmUxD0mOGhhYWFh0TI2KcrY/l24Zflas1++r7gvNilKbPGHyGcci+B2YQSCGHjxhQVkm9iYgcUmI9T70Z78p2mgZ182BsPtyhjL7pxwYTyDy3V/Qq73E00x7LPHnU3UqcfH1CYhekkE2Z62ISDIe1bctLVies3Yjip+WyZ1bpjM4x7Q3AgIie/w9/h3uOqUjO9ndxQgxVzURw0cohQ32r0ehLOKiXp1xPGnwRufYKwujxvxHQtxxbZx39BO3LLyR7MN3lPcnbBmMHHJOvPYrcPG8xf1MVbXlhNBh2wPPoeGqHt5pWQeW0K/8Jj6VyavnE1J+yGU9r+YmBFDNwzckpPRnUv448Gn4Is0MO2Lx1ldW86rx5RRE/aZ4nZJz0+Ix77ftWoepf0vJmJEKfdtTksXVxGsYvLK2UwdOJZLe51mGvzJc/uTAO+BOL/dGyiK0h24XVXVy3/lc/4APJD4sSdQCTQAG1VVHaMoigEk3ZwEIBd4BxifsG9bTasMd1VV64AngCcURRkEzCMuDuds6R5FUToDrwPnqar6n8Th/8VPKT2BjcTj5J9RVXWToighRVFGqKr6EXAxsFhV1aiiKMuIu9m/kDyeeNaixM8zE+eX/Wbi2xM0jR9raqyn0lRQBq8Hanzobp1ooAqbuyAtz2vFZwsI+yv57t3p9Bp1L/In38KRHqK5WeiGYXZuuqFT4MjljkHjOMiZjyiIiHi4bsnatHinu1aoPH7MIdjD2j4z8gTBhtdTlNa5eT1FCG18IN4+6e80rO8l/GvFnemrrstLuWDkE4RsYSZ9EjfaJ/Q5zxzQemZ3Js/hpcCRy7XK+ERMew0d3A7uH/E72rl0HhnVB1mwMf6Dr5tpFjwxaiBi0DLcLSwsLPY2UU3mluVr0vrlW5av5fFj+mM7dRRGIEj0rSXg8yNPuAAQ0jKw5Gi6mQ4OGg102zXno7UQyx4zBMAwjXYAw+shHP6ZDYtvbTEm3CkFWP/axGbGYu8xzyTmMrufFsX0JlyY+AaZaUkVPy7y27Z3YJNzw0ZvEYMcSU//Du98Tq8xM9nwn8b66jXqXoy/LUHL8uAdcxyCpiNccCJhRz0b3r8lxd2+DMcJwzHCYWJGPRvenIjsLmTuiXOoDDdQF62jIVbH/Su2taiPY5NtVJ51BNUNUe5ZUW4a93ccMZEPf3mXP3QcTtma5xjduYQ8hxebKLNqm8rz373NgNyeXNrzNPIcXmQhfvz+w67HY3NlFK7Lc3iRBJHuWR0znnfJTmoi9RnP7S/p4drC/DaiRYdXh+vKNEMrkgSposCRU2qXbB/vtQLsGl2Bg3/tQ1RV/RfwLwBFUZYAM1RVXdLkmsHJ/yuK4gVWExdxX8xO0NoddxRFOQy4lHh6txXAOTu4ZTJxw352Mo0cceP/UuK78E7ixvf/Jc79EZivKEo28AXxeHiA8cBfFUW5HfiB+M4/xNXlFyiKsgaoTdxv0QKpgjJC1yLkk44m9vJijItHoYtROhdPbBbPbuh6fPd9yW30PftJNF3EJspEUsRBGqJBbuj3R+74Yq7pXvTEEQ9kjLnTDIOoXSRmiIiCgCyAtBcNeT3q5oyRc9Ji3E8fMRs92vYH4pbQom7OOKqM1/8bd5d3O/IzrrqGI9X4w3E11tL+F5vuYAvKF3LfYRPJs3sZ1+tPzYTonl79A+MHdWJbuI58R27Geo1iIDhlJNij6f4sLCwsLNLRDLGF8VYkMvfFuHfdBSdj5GQhCAJ5gpbmLt6S2Byi0MwtWsjzoosiaM1F6oQTBplGIDTGhKcZ5Smiukn2tDjdzojppaJpBpqjU7N0cFobTwfXEs2+w6YKpNeg3yVPoTfUIzgdGFEN4ZTDkWxeYnNfjHtSXHWKabRDvL7WLyql71GzINdNNFBlppvLqf+WaWv/SkWwivlH/jlju+yVPYDHj7wXQdT4KbiNWSvr0uYcd//vex475gweXPN4hvC9SQAUHzQ47fiDQ29EQOCnwC+ZhZLtXgQEDDILKaeK3zU9t78I8OpRN6ePmM0bH03aJ/PbiBYd/m39jwtvWjm7MFEv3R4cOmnhwdmdTvu1xruiKAJwPzAGiBHfPF4MPAnkExdNv05V1U8VRVkALFFVdUHiXkNVVUFRvckQ9wAAIABJREFUlBlAR6AXcWP9KVVV7yVua/ZQFGUu8E/gz8Q7hm+AkcDvVVVdryiKB1gH9FJVNT2P4K5RSFx+bNvO3tgqw11RlK8AD/FUboepqrpDAThVVa8Hrm/h9KAM168ChmU4vgkYleH4NuC0HZXDIq40qUthuPEMhLCOnHsQscf/Ee+U/REEr8h3701vlge++7F3mD9HQ7XEAtvw5B+MLjuYe8S91IYDeG1uHl47P829SEfPGO9kAFcv+dpcWb19WG8KHDa8pLtaJ5Uxd7fyu6YZtMvrybmjnj1gVOUBsgwHZwy6BdGZg82Vb666digYyKC+1+F0tEd35eHR4+5kXnuWWV+ra8uZv/5VxvY6nc6ejlQGfjGf2z8/m3N7d+TGD1UqA2HKRvbPWK8/1IcoXbbGcp23sLCw2MtIgpCIcS9KiXGvQBLiu8lGjY/Yi4uwXXMe0b+8kOLWfg6GzYZIZgM9JklIiVj21Bj3eiRAR2hi2DdNKwvxuYNoRMkT7OiiiLYP3M91UWwsZ9ci6v8whKjXic2pIUXkFsd/SRKaqa73PLkMqY2ryrdE2ndIIGR7QJLR7Bob3hqfJl4oJbwyDaeUOZ1gvotoaBuaptHh9AUYNi8Odw6PHHY9133+MHXRuozzhW/rAjz05XfcP6Iv+factDkHJBedMMP30tzaP53N/OJpXLn8rrTjN62cw9SBY5m//tVm4nYPDL0BSRB4cPVfuaL3Wc3OTxt0FXPXvUyBI4dZh09i8qeNInrJ9HDaDgzfPTVn3Rk0zcAmdeTcUc8iihq6vndV5avDdWVJox2S9TK7cH7x9LIid2Hxr3z82cAIYCBgA/4LTACmqqr6qqIoRwL/pyhK7x085xDixngu8G3CWL+O+O74BEVRRhHPftZVVdU6RVHuBP4ETAPOAt76NUa7oihfJsp/ELCW+GLD/3b2Oa3dcb9HVdV/7OzDLfY9yZQm36SkNOl90izEZKf87irsFx2dOWe7FG8eOd1LwDD4fsn9yO5CbCc8xi3//ZlKf5QOngbuKb6aK3vWUxmqYsG3L7MlWMntw3qnxULPLO7LI198R4HTzg2De+C12whqGnWRGE6n3UwPJ0kCUX7ijSXpq4Y2afcMloIgJoQ6dhxesD/glAJsXvYo7QdfQFiSWPbFLP4wbDqfr3+Zg3tPZvoKP5X+ejp4Qsw8Io9HD5/CT6GqtJXl7xp+whcNkG/PThtoL+rTiX+s/4kbBvegwGXHa5OZPbI/k5atSVt8efyr74G2ke7PwsLC4reEXYSx/Xtw60c/JcZkGzNH9MCeIiRt1Pig3p8WKifU+9FeXITu9SBfcLKZr9s00DUB3FmNsfCiSH2KqJshCKb4nVHjQwhpmdPObaklNu/vCHlebOPOptfJs9mwaNJecz/3I5F92Rhi//6IH07sx6Rv5qYZZu3ILD7mlAJmKjhowYNgPyL5HcyFmAE90U8/FKL1bFjUROPoP7fS94SZGE9VNEsXDPF6DYdqiGZ1oTrm5JaPfqbSH6CDJ8rMYTk82W8sgtPDAyO6cPNHjTHu04YpzP1qI5WBMFM/Wsuco5WMxr0k0GJO94gebdHdfXVtuSlu57VnUeQqxCHaiGgRlm75jNGdS3hz81LuGDSO9q4CfvRvYe66l6kO13LLIZeTJTmZOnAsLtlJMBbCLtp2KHm9p+esO4OmGWhNQiT22u82tKKMoQaGVrQbHl8C/ENV1TAQVhTlKOAHVVVfBVBV9RNFUbbRXPy8KR8kUpT/krg+J8M1aiI8HOBZ4D3ihvslwK2/5iWSrvKKotwIjCUu3L7TtDZHwPRdebjFvscpBcwYLUi4OS2ejHDiYfELNlUgbIvneU3Fnl2Eoev0Hv0wXY8upXzxzXFXqOKbTaMdoNIf5fblFfwSsPPI5wGuVcbz0dYV5DlEbhrSk8dGHcJNQ3qS65DZFo5y9cBuPPTld4xf8hUPflaOQxIRUsLMJFvAdPWBuJv3Gx9NQrIF9vzH2g8RBIN2g88nYIRZ/s18BnQfjcOWRfGhdzJjhT+tnm79Xw2OsEEfdwdmHT6JIlchAFf2PpObP3uIJ9f/nZnF8YEUoMjj4NzeHXnoy++48v1VXP/hamrDMWYcofDSiUP4y6iBPP7V96zZ1qiwmwyJsLCwsLDY80R10TTaIdHXf/QTUb1xeifkeTEaGsdQ+dgjTEPd2FRB7O2lyGedgP3WcQgJ8bmYpsdj4TWBGkOiThPSxNx0A2LLPkM+41jsEy5Akjz0Ov5+cy5hpp1753MgEVv+5P/htLVHGfMMgy55i95jntmjedElSSBsD7ElV6D2/KNNox0axcci9nDGe4UW3PoFI5bx+rZOTNOpd2chTLgQ+dZxCOccTTRYTSxUl3lHvSgX4YoTMb7+kV7Hzkyv19GPUiG1Z32DkDDaU9reijqiYQOXfxs2I5o2D7RLjZO9ykAYUZC4fVhXc84R19Xpy8vfv06BI8ecoyRJzePe9HgwFt8IXV1bzuSVs5n+xWN8V/8jIS2MkbhmQflCzu9+InevepLpXzwOwF2HXsO84XeAYXD1J/dy/Yo/M275XVy/4s9MXHF/i+0jidjCnFX8jc1ZJUGqyFQvkiBVtHDLztBUv6wHzTOLCcQ3o43kOUVRmrrypO6Wm9c1IZj8j6qq3wObFEU5E2i/K7vjmVBVdQ5xofU/78r9rTXcv1YU5TZFUY5WFOWw5L9d+YUWe5mWYsraeRHyvPEDH35D75PK0jrm3qc+guzITqSIqyRSX4G7/QDwdjY76SSV/iheu80UHzmv26m4ZJlOHheFLpleOW4q/GHG9u/CvZ+ubyaiY6T87RhEMitjEtndX+aAwBAMVi27C7srn8N6X8AHX5Txt3//CV+wNmM9Gc58sgzoKB/E/OLpvH3co/TK7sLcI2/l4p6n4pQbeOyYfvzz5MPw2m3N6uuuFSq14Sg3fLiaiKZTHUqvl/hqecuCPxYWFhYWu4+YbmTs62MJG1vI82K79HRiK1ab5wW3K81l2thUQezd5SAKiLqOBw1Zaj49lCWRHMkgT9BAEpH/MILY6/8hMvdFtBffwSEdRL/R8xj0xzfoN+Zp5I9/jOf6Tv6eGh9CbT2S5sThLcIfce1Ro32rWMUVn8zgtA+upzJU3aL4WCYEUcq4oSGI+29O7NSFGMOI8t17M4gGazK+Z2Dbt6xdcSva8E443B3pd9YzHHLxIjqd9gK19t+xTXPG530Z2p6Y9Tsi3u5MWv4tpcvWMH7JV5QuW8PtH6/joj6dgPhcoSJYiS5U8XCJwosnDmLqsHy89hCD8nsTikXSNhiKXIXcOXi8mcc99fiswyfRM7szJe2HpF07f/2rRPUYBvDA0BsocOQgIPDYkbdy72HX0jO7My7JSdma5/BroZ1qH0m2r+b+26HAkVP64NBJVan18uDQSVUFjpzS3fD4D4EzFUWxKYriBv4BGAmDmoSrfAfiYm9VQP/EfWe04tkxtu99/gzxOPjnd7HsLTEJuExRlEN29sbWusofkfh3Rcoxg/iqh0VbpqWYsm1+5PNORMj1YlTVwFcV9B39OIYkIIgSSDJr/3lZPG9pyIc9u4icERP5IVBBB096Z93BYyPXYaN/fjwnpC9i45b/Nrrt3XdUR+yiQJHblVlEBwPNISEJAk7RkVEZUxT2D4GQvY2uawQbKhBlJ//6+CYztt3lyKGDJ9SsngKhSnKcWVREfuGJDa8woc951ER8zPjyCQocuUzsez4zvryfimAVz494OGN9dfW6mTZMQRZF7hneh9s/bnSFe6C47z5L92dhYWHxW0MShYxjsiSCcPsFCLqIHpORjh+O9vMv8V32cCQt3lnoWoR8SgnRpCBZhpRpmdKqGePOQb72QoRaH7qmIQTCGE+9jeH1wImHwQkDEYb0wHj707h3X2LnX8zO2jPfQhKJ2GQ0AyRRZ943r5jGWDJlWKvFxwToftw0Nr5/l+nW3/24aZn36PYTJEnAKQXAiGIYBpH6Cio+W9DsPXuc+AC+mEj+yU/id7iRxDAIIpu1LG7+6GdzbvdQSeeMbc/uziOq69wwuAfPr/vR9MqrDITx2m3mzvq8DU+ydMtK894iVyGl/S+mbM1zPHT4TThEW5rreq49i5M7jaTc9wPzi6cR1WP84K/kvq+eoTpcy6zDJ3GNcg5bQttwiLa4oS6IxAyN/9v4Lpf3HmOmi0sa/Pn2HHJsWeTZs3l6xAxqwj4WlC9kdW15q8Tp2oKae1vALtk+Pji702nzi6fvdlV5VVVfUxRlKPA58Q3nh4EPiGc6uxMIA2eqqhpRFOVx4OWENtt/gB3t+K8FchVFeR54OsP5V4H57GbDXVXVNYqi/BUoA07YmXsF47fn1toN2Fhd3YCup797Y1xI22RXypeMcU9NadLr2JlIr63CdkIxsY9XIZUcRiQ7xPrFkxuvOXkW3y+5D/+W1XjaD6DL0Tfh8+Rx65dPcEOfG7j7kxqz8751WBH/XL+Nc3rnYhN0XlR9jOmaT65NpjYa47VN27h6UDt0Q+OJr75nWUWjiGIHt4ObhvRsFDcb0ZccbTNvJIxQr6eIUw6/k1xPdwKhX5dLU5IEshxhYtFQizlmd4Z27bL31hDejRbarMse5NNFY+l//H089/4ldCgYyCGH3M/f18c4p3c+M1dUmPV0+7AistmMNyuPyz++h9L+F2MTZe7/+hkqglXMGjqJtzYv4+zfnUKeLZcch4eHvt7Eh03qa87RA6gJRQlqGvkOGwVOG5GYjiQIGVXl2/LfVVst254oV1toryllaZPfvSWs8u5ZWirvXmqz3dhOe23z39LjYHN9lHua9PWds21sfHq4OeY7hHaILicEQugCiE4HNAQwGgIYHhfa399uJlAnTLiQOi1eBTmSgTH3hWbXiBMuRIhG4+6bgSC6FmuWPqzXqHuR//Mt8lFDiC37DGHM8djzvbv1u0qSSBUiU1Ni/W8ZlsNf1j/C6tpyBuT2NNOgpsW465lj3LMdfrZ9u4TsHqejGxKioFH/3RvkHzyK+rAnYxnaQnttUh7zG0uSgIOtRH0/IbsLMRxdiYT8xBp+pGHjm+R1PwqbKw/ZcxCbQjZuXVFnfsd7h3rIxc+ElaQZ6SM7ZnFpv0JuW56ir1D8O575ZiPLKrbF87kP74M/qmETRYKaRk+vm5Ae5dnyFzi7+/FphnRSKG51bTkPD5tizk2SFLkKufvQCTglO9Xhuozn5w2/g1s/f5TqcC1zj7yVbeE6DnLmIwgwbvndGZ/nkOxMWTknrRwvbXyHq3qfRTu93XbniWaMexM1dxv7TsSwtX3WXpwT7Jck1OxPAq5WVbXNiKG3VlU+i7gUf1/iaeDuA0pVVW3Yg2Wz2A1omkFE7kjvMc9AQvFSwoX4xy4giUjHD0f36Kx/69p0cZJFk+nx+3vRGwxkRyE22YscqqQ6XEuMLcwu6YwvLFET1pj31S+sqQ6xoTbME8d24fIeLpa9F8NXH8ObLXD58e2JxmL4YlEmHXYwGz7wtyxu9tFa5o3qw6mDb0G0udCjQbLsBYSjDn6N0EYmkb6mOWb3RyKamyEnlNEQ3IrXU8SgvtclBOmibAvFuP7Q9uQ5JAocEg11Oh1dB0NEo9CRR3tXIVlSPncNmkJdtI6unnwmdL6SJf+W8NUbeLMFbjhJAVQ+TAzCM4v78tiqxkH59mG9KWDHK8uSJCDLAeKhSjZisf1fzd/CwsJiXxPRDf71fR1PDe+KA5EwOvO+3col/eMuq0mxsX5nPo1QE0RwORBlGb3Wh/bmEvD5sV02Bi0hWJukacq0ltKqCQII0ZiZ0z1T+rANS26j35lPEXtlOfIfRuBD4tctw2f4DjaZqUs2p8Vb37eijolDLmDyZ3ezuraclza+w/zi6ei6joQUVwxvaRySXcgdz+Kfr0fx1UfxZgucetJZIAfi+3v7GS5bmGhdNVtWv4530C0sXmzgq3fhze7NqSdNwc73yHYXPtzcuqIq7TvettLPX0qKqPT/kPbMZT81cM0hhTxd3AUnEkjw9MZN5uZMgdNOSNO5b+UGc853/4i+LNvyHke3H0G21J5Hh92JQ4qh+jaZRjuAS3ZmdF3Pd+Qw4ZOZ3Hno+Iznt4ZrmNDnPOauexkRgVx7Fk7JTkgLb/d5qdoHd62ax/ziO3AbEpHA9ucpqWruB1K2IgsA5gCjiRvvACiK8gGQl+HaJ1RVfWJvFKq1rvKPEHc3aE88uN9LPH/ehXuoXBa7EU0z8GsuZMmDBw1R19BtMhIGQjSKHgw1i4O3uQux6/2ofClKrMZAzhPoMLY7jw6bSl2sgW1hH9e+nz6IV/qjyJrIsvci+OrjnZav3mDZezFOOk1myorVPDpqIDcN6UnnLCd2UeS2j9c1EzeLGjZyvL2BKLhsRH7lzjgceAqxSTTNwOMqxIgGOL14Fj49m0p//HuuqQ5xy39/ZEC+kzn9uhB9NszPNRHkPIGyS6bgEwyuX7rWHFDnj1RY+O9oWt0tXhzhljMVrh0cQRZF5nz+rTkoVwbC3LNiPY+UDODcdz5rMR2cYegYxk+89+4k/P4KPJ4iSkbNRtoHqqsWFhYWBxIOQeCKg9rhe6xxrL7ionYIQmPfGqmvwNCixJ57y3SFly84GemM49Fef4/os68hn3UC0adeMe8R8ryIokCOJCBoOqIOtivOIvbucoxE3LqQ50UwDGIJox1oOX0YGvLwQWjZHmK/Mhd6qst30nsuYpAx3jrfng/Ed1ev6n02jpDTHHe2l+Yrprl4a3H6ePjW4ijnnulif7HcDd0gRzIQdR3NiPDdezMoGnkPb//H1eS9NM48/Xds+ve1ZJfcm/E76obRzC3+6I5ZtG+ws+XpMNU1UeQ8gXMu+h2r8n2s3lbPRX06mdmFAFNN/qGSE7hh6TdUBr5IGPN96OXtys0Dx7IlWMWC8oUEY6GMoQ26oVMRrMIXach4vibso2zNc0wdOBZJlJCR2BzYwkHOfEraD2Hpls8yPi+VimAVuq6hRVqX7SCp5n6gZCuyiKOq6g3ADU2OHbOPimPSWpWNQ1VVvQ2IqqoaAP4IDN5zxbLY3STj04y5L6D9/U2krdsQojFiLy5CqA81EyfpNGQKlc/EJwIAsRqDymei5MfyKbR3otCZQwdP+k5rB48NDMEcEJL46g1kQaTAaQcDSpet4bqlqzEgs7gZEIy4CEa8BHeXeE1LIn0HgICIEQvx47KHcEc1su1us176Fzi576hOzBrama3PhNPqsv6vIrkxR7xOiA+otaFYxrozdIHrlq4mrOlsC0e5v7gvj406hPuL+1LgtJOsnmQ6uIgt3q1IkoDDEcTv38LSJXGjHcDvr2DpkkmJHXgLCwsLi13FE5XwP58+Vvufj+KJNsbm2rOL4Je6RuM6kdtd8AeQjz0ibsy3yzcFa4U8L9Klp2PU1SOHI4iVW4n+/U1ir7yLfEoJQtciM22coRvp7vOJ9GGp2LOLoKqe6FOvIEZ/nSp70ntu/WtjWf38aax/bSz22E/IAhnnJO2dOSw85mGeOnJGi27xmdD0zHMZTd8/vItlScSo3Iox9wViM5/EiMXnQKKzMON7hUINdBh+DQ6nJ+N3lAR4uKQTs47uTP8CJx08Nu7o354tT6fPLYLP60xWegKYosWpVAbC1IW1Jsb8OjbV19AQ9fPm5qVM7Hs+HZwF3HPotWkidNMGXcUvoW2mQnxTkbppg65iQflCKoJVdPK0RzAMrlx+F5d/NINxy+/iyt5nUtJ+CANye/LwsCn85YhbEATBFLVLEo9t3443hoXFPqS1O+5NtaYkdpjd0KIt4UEz83fKF5xIRK/HsEkIZxUjfP0jvUbdy4Ylt5lu5E5vd2I16VUcqzFoCArM+HwDpYf24vZhRWlxdfcf1RFRjLtYpw4M3myBzQ0Rxg88GFmMD3qVgTAx3WDOyP7cuGwNBU47Y/t3oXOWE0GIx6s1jZX+VbQk0ncACIiIgkzHYVfy7TtTkd2F3DvyPhaUN8a4PzS4szmwJonVGARCcPXAg3ni629Zs62e6nAEb7atWd0hGlQGwjREolxzSDdzBb2D28F9xX2xiwL987NZs63eTAdnlwRzl72k5EGGHl6Kw57z/+ydZ4AUVdqFn1tVnad7IgMjQUCgyAoSJKOCLLiujOvnrq66YlbEhIJiThhRVwSzGHbXtGtWVFgFJEgQlKCWBEXBGWBiz3Su8P2omZ5ppsFBUWG3zx+mq6uqb9Ut6t5z3/c9h1i8mg3rn6WsbB122vzBm+2QQQYZZPBbQzJI+36X6oZPp7+ILuNmYL2wImUfqzKIcNkLtyI3AIqMmHgaDtPEDNYg4jr6P99piND/aSz63EXoL7yLY+Kp6AhqkPFhpAjdWfM+p3PxdDZ+OK2hxv3YO7FeXYnIDWBKUtMZ5T5gj9lzf3yOu4a0Tqlxv2tIa5xxsy4auvcI++6QJDPtXEZIB4f0qg+DxFOvNggQVoRx+oswo2UE/HlNrisa3YE3t4i1n97Orf2v4saVoQaB4SGtefDzMj7eXpu8r4VWHGHK6JWpwQ+90qKtx82cUUfgVmSGFeU10TWqjO4W0Q/H8Mhebvz8Hib3OJObP3uUO/tehiJk7jryMgIOH9+FSpn11Uvku7K5t98VXL3qAWZ99RIzB15DdaKWylgwmWpf5CnAKSnopslDA6fy/Ka3eXPbQq5e9QCPHHUdISPCVSvvT9a039vvSgAW7vg0qX3gjDv36XnJIINfC80l7otUVb0b8KiqOga4BFvRL4ODBMn6tEOLCAeifPqfqURqS/BkFdF3yB24lm2n2x8eJRbZgR4NEq/9HiW3TcqEQMkV7IrHOaNrO65bWkK+W+ayPi0JOCUiukUkEadKMhk3zsW778aTddLDRincs2E75TGDB0c0WIHoloVHlnj86N5UxBNcs+TLFHXyXK+DuLFn0bN9QdTw0mncjBSRvk7jZhA1mpcKdSBDkry4c9oRrymxbfs+vpbLjnuQSz62F1UqdJ2cXJGmLxNMX72Dy/q045qlG3h16zYuG6vy3tyGvvvdWCcJSWfGsB7IksTtn3zZxM7v6iM7cWGv9jy67lvKo3FkYdezz593JR5PARawauWMZJr8oME38dWXLyCEA5crQqbuPYMMMsjgp8GU7ff57u93U4LexS8iuTzIchZ6MJQy0oncAFbMznhTTh2HKQmq45ArQIQi6K9/mBqhf2kuyvhjSMx5HdO0qLYkwCQky/gnFCcDAyIYwuU6BPWkpxFGHLGzGuvV1YhgCHlCMTU/N+6zp+w5I0IBLmaPbGurygtwJvSfNG+QZYFhlDBmVDbvz3c1jIejdWQpDrh+evt/JeyuSWC9s5LOJ93Jrq0f8vtxPXj73UTyuo47NsLGr59H6VLMtm0fEYmWcW+/a3D72oJl8tBam7SDnTZ/zZLtzD66DdvLY/jSPHvfhMKUyXEe/GwLdw7uBpDUxZk+uBtzNqTWyrfyuqhOVFMSKaOVJ5/JPc4kx5XFzkgFLsnJg1/8gxPajuCKHqeT78pmcekanhh8I3FTpyJWjUAwY8NzjYj4Fdy3/rkkEb+n3xUAvLltIbplJEk72GnxV6+6nycG38Tk7mf+uPZBBhn8xmgucZ8KXANUA3cA7wO3/VKNymD/w5Qke7V79OF8+p+riNTaA1+ktoTVS67jqMOnI3ZVs2XZTcRrSijoNp5Dzp5K6dN6sm7Oc4bEHZu/4eLeh1EaSlAaSvD3L8s4vVsBAadErtvNw59v4oq+HRlf7GJXSKcqoXPPhu1sqIgCEIzryZf3P776nrO6tkUWJEk7NKRcp6jNp6md3hfUi/R1/79n95uq/IEC04oQr92VzCgI71iHP1KdrEWbu7OaSRMKKZsTb+jL0xWmb7QjE/luJzOG9aBtlhtF0jlqjIVbkslyycxY2yBM99CInmnT3jyyzK0rNK4+shMFLgfOhAlKArengD5DH6Q6FqR7/1vYsn4m5WXrWLb0Fsb87iksS8c0YwgkItGduFw5wN4VXDPIIIMMMmhAjWKQdaaD2ucaatyzznRQoxjkh53oc95GD/hQTj8B/e9vNUTQ//J78LqxakMY7yxE/ssJgIwlSUhZ3pT0d6iL0Hs9TaLmumFS483CN/E0ZNPElCRqkNFjpq2r0yKA/JfWDdt/bibdXrLnDMNENuJJA6+fGht3OMKsWvk3evY6l5OLO2JaClgxnM44HCROTPVzvmQ/bi1B+awNgcFj2LJlNsUnTiAWDWEYNShKhCP7XUY0UsFhh51Ih45j8fuzCYc3EXd1TJL2epSGEiAEMbdF+7PdyVI8JVfQ4mwnd3z1NRf37pBc3P/biJ5cekRHfghFeXXTD0zo0ZaN1Q0ixXcM7sLdG2ZQ5CnA7/Bx9aoHyHflcF6Xk8h35/CnDmOY/dXLyWj65B5nEjPiPLvpLU7uMJqnvn6NRwZdj27quGUn965/NlnLXhIpY8qqB3ho4FRWlm9AFtIeatpNnJF9z8zIIINfG80i7pqmJbCJ+m2qqgaAHE3Tor9oyzLYb1BkCRwgLhmPKRJElqSuVkdqS7CK8pBrBV3GP0IiUo7sCvCN9ggtThuB01mA5Mnm9q++YX1FDcG4nT6V75a5oHdhiuXYtAHtqI7pVESj3PdpeRN/z3y3k/uH9WDBtl0c3bYFCIEBeySE9X8/ueE7ruxzGIYpfnIE3jAsnL58qpM2Gf8dL2fTSvD90oeSXqyKtwCnN5dWvgT5bpnR7bO5/esS/nxGHi2cDnxuiUc27WR9RZRWPgc5bgc3fPJFwyA6qBset8QFH60h3+3krsHdCDgdGJa9Mt64r1p5XQTjCdvf3e/BIUyiJrjkXDoOuJ+LFjWoyd7W7w5YfR0C0BMRamq341A8JPQIbncuuh7G44kRi7kyCvQZZJBBBs2AkKDMr2P8FfySQo1pEM3SyZdk9JcC/OwiAAAgAElEQVTm2oQ74MOSJJQ/jka4nHak3eNCX7ACa8V6m+BJEtlYyJYJ2f5U0kdDhF6eUExYVsiWDSCMaelYwkGt4cWwRB1btsdm3TCpRgByyvZ9hSJLdcK6JiaeZmXPpXi672P0XZJMevY6ByEgGPw0OU75s1rjdOX8pGv4tRFCJvuck5Lp8iI3gDGsKwv+cy6hUAmB7Pa0bj2IaNRk4YJpyYy4Y499GEl2EA7vJBqtwBJ5TUTpTlNzqY6b3L6ihAKXzGV/bcmhPjc7Ygk0JURZNE4wXqdKH44hIZCERUQ3OKFjK7wOmDYgD1nYkXakStuHvd+V3L/hefJdOU2s+xpbxeW6AjgkhePbDuOpr1/jhLYjkBBMWn4Xs466NkWADmxiLguZm4+4EEXIaUXtfsyvPYP/Tqiq2gG4XtO0c/bDuRYAbYD6la4AsAX4i6ZpO+r2+QswBZt/m8DLwHRN05q9zthcO7hi4BhgGrAWyFZV9WZN0/7W3B/K4LeBIkv4ExFitT+w8cNptB0+mcJ2I2ijnoDDFcAydCTZiYVJzA9fLn+Qnd8txJNVRK/hN/L1qgeo2rmeQ7qM56xel6FVh3j+q++4fsBhRA2RJO1gr8JOX7GDGcNb89G2EqYPacu0RvVm04e05rvqIE98uY0r+3akKqazMxIn1+1I1kH1yPNzRtc25Lod+B0KPfL8AJzSpTUXLVibkkr/cyLw/00QkkwiXM62ZbNof+wt7PSqPLi2kmkDiogbVrKPFtWtmrfyObisT0tW7gxz59DWPLRmU0q2w3XL7BXyfLeTC3u1546Vdk37aZ0P4f5hPSipW1SJGAbZToUH1myhldeFJAT3rf6Wj0sqmDGsB/d+ujnlvDes+oE7e08i1yUTiZazYvmdycnC4CG3oCgeLCuOZZVlFOgzyCCDDJoBy4JpdT7a9Wjlc/DoMe2SxFs5ZiD6c280IeLK+GPQN36HcnYxViKB+fgrxCuDiB6dcJw1nsQzrydJn2NCMbrfRxQJbzRMLPZDSh37L2WvWi+sa8x5Db2uLe7zT0Ytfhqrkap8499NerrX2cPV12UXyPzonEGWBZZlIYRA1yNNximH00/zk1V/O+iGiWjVAtEoE0KXagiFShh41E0UFfXFNOMsXDA5KRzr8RQQiZazdMlNyWseNuafXD9A4vYVOygNJRjWOovxnfK4dMF3yczL85ZtpZXPwUMj25GlS/xteE+e/+p7wF7cFwJqEiYPfrYlOYebNqAtf/tqNuWxKh4bdAOTe5xJwOFj4Y5PefSo64mZcW7pczHBeC3PbHqTWz9/jDv7XkaWw4MiKQghsXjHGhbu+JSFOz7l+WHTufHwCzAtKy0xd0oKbbyFSJbJfX0mctWaWclFAbum3ZWJtP9v4lDgsP14vnM1TVsAoKqqBPwLuBKYqqrqWXV/F2uatllVVT/wLLZLW7MXDpr79rm27qR/BJYBFwD/ATLE/QCHDwOjagcbl9kDbNWWRXTuey6r509J1rj3HnEzny+6gVi4nD6j7sbfojtKfl9CrtZ0HTUbf1SA6SBuWcwa3pugniCU0OkY8HJX39a0djnBhO3ROPd9VYosJE5T2/HOlqpkDXwwbjJnQxlX9G3J7YO6UhlLcO+nm1K8PS/u3Z6wbnLdsoZa9+v6d0FgcfvKr5uk0j8yohdyhrhjQTLaXiN8XLO0lNJQghynzGVdC3l+UIeU/llfEaVDwMHsY9oSjMdThGPAvr8OBDMO70YkanBLt87M/GYrgw/Jozqup/TbjQNU8lwOLuzVngdWb+aULq2piCXwyHLaLIqsnN5kyTEqK79myJBbk2J1S5fcxHFjHgdIq0A/avScpMBQBhlkkEEGNhKWxYntszmtKBfJBFOCf5ZUkrBIRs2F15M+9b2oBcqp47CyvBgP/aOhpn3DJjvf6byTIRIFrwfT7aI6bpEt6ylzCki1V43ha4iOSxKh3dLj663cYsFafE75R0vWGgvr1rfbePxfyBNPo9pIb7+VztP9miXbmT2yLbKR6mSzO+xsLwu3O4eVK55MEVb98ot/0H/AFA6GGncAIQmqjYaMB49Tplu3M8jPV1m18n769b8q5focjqwkaQd7/A1Gqpi9rpLL+rQj4HTQxucibFhNLOMKXDK5uowccVCRiDNBbcuVHTrgtCTMGLz+XUnKHG76iu+5fuA5FHicGJaBQ1JQJJkRLY/E5/Bwy6pHU6Ltc7ctxiHLTFp+V3L7ff2v5Pg2w9gW3kkoEebFb97jnE7FSfG6xjXvL33zPs9veYciTwEPD5jKU4NuQbf0TE37fkTc0AdVxEIzdMsoUoRckufyTXbKyrKfe15VVQVwF1AM6MBjwFxswpsHhIBLNU1bqarqM8ACTdOeqTvW0jRNqKp6M9Aa6IxN1p/UNO0ObLvzjqqqzgJeAe7BFmD/AhgGHKdp2teqqvqAr4DO+5Bx7gMKgOV1n28GztI0bTOApmk1qqqeA/ygquqtmqZtbc5Jm0vchaZp61RVnQrM1TQtWLeSkMEBDsk00Rv5quZ0HJ4k7WCnya9deDPdBk1m9byr2LhmDjn9buXqJT9Q4ApzT8ds9EeDWGUGUoFM1sUBpBZO3LJCTlgmEFbYWWcH4swV3PXXNnwbiXP7ihKmDSjisbU72VDe8IxPOqKQzdW1yZVXaPD2vH9YjyRpr99+x8qv91hbbVhWJrkJEJZF6ecv0v7YW6gJdKA0tIWeeW7Ob10AOwW7Xmjon+lntuG+70uRJYPqRJTSkNUk/X1EUR555RLmw9U4ygyyC2QentSdmiyTe1anRtFvXaExe2RvbvjkKzZU1LCxOsTlR3S0yynSpNWb8SqiIjWKMWjwTXy2ZhaGEUeWXclJQz3szxkF+gwyyCCD3ZEtBKf7c4jfVYFVZiAKZE6/JJeIsFBOHYf+wrtY4Uj61PedFYgsL5imHX3/cHnSo93asAlG9ic+6wWcE09FkiQU2YlkJlLmFPWI15QgLL1JdNw/oZgabxa6YTZYub05udmR+t1F1sAm77Jpwh5mAMYePN0Na09HNEYCEICga7dTWbb0lpSxSoiDww4uPQRdu53CB++fz6DBNxGLVaUIx44YcS8eT0HKGJyI7KI8anLN0g38vn1LTu7UlrBupqTP98xzc0fnNuyaac818no4KBylEH+4kljdM3nBJW0Ittd589sdgD1/aOEu4OJPrk0h4tf1Opcvg980ibbPPmoaF38yPUVU7qqV9zP7qOtwSAo+xcs5nYuZ+umD9M/vwcyB16BIMpKQeOWbD3h+yzvJ4y5ZcTdPHnVzpqZ9PyJu6IO21Ox8c8qKlwtKItUUebLb3zPglDc7+gv/sB/I+8nAEKAX4AAWAxOBazRNe1VV1aOAf6mq2uVHztMbm4znAJvryPqlwM2apk1UVXUk0AU4VNO0alVVbwFOB27EDly/3QzS/qSqqiGgEKgAXgQeUFW1BfaCQYq9h6ZplaqqbgCOBJpF3JtLvk1VVU8BxgAfqKo6jv+WAuH/cpiShIgaSV9V2RVIkvZ6RGpLcLhs/9Y89TSmLvmB0lCCSw5rgauOtANYZQaO2UEqy3SqKkyMMtj5QqqHZ/DZBL64VJc2X8Lp3QqSv9PK50ASe/b2lIVIu10Sglbe1BXuVl4X8kE9gO4/COGg6IjTCFpOvq+10wIv7lyIOyg16Z/a5xJM62E/C37FxTvf7OC6/l2S97eV18WN3TtjPlyd0u/mzCp27YpxSpfWyfIFsPsnZppsqKhJfg44HTz/1TauH5B63tv7tyHH5UhJzQuFSli29Bb69J1EOLQDyzLx+VI9gO3PB79tXwYZZJDB/oYnKhN/uDLlfR1/uBJPVAbTRD51LOQEcPz1xBSfdseEYvS1Goln34BtO9Bf/xBl7HDEoUXJfSzDSNa2mzW1GE6LXS6ZmkAhgY4jU9rh9BchCblpdHzOa/jqZOLccjhZmw4NkXq3HN7j9dWLrDVGUiBvD5D34OkuN2PKIEluhJABkSTt0DBWWQeJOF06mKbANHWbqHtbsmjhlNTstoVXM2TobYwYeR8FBb0AqNm5hLuGdKWV18Vpajue3lCGUxZcP6AoeY8vU1sSej6RnGtk92/6TCYermLSoe2TbWnldfF9aHsKEX9v2xIiZowsh5dgvJa3vl/IxK5/It+Vg7QHUbldsUruWvc0YSNMgTPAI93+ytmd/sC3tT9w/epZlEbKk6S98XHGz/EkzKAJKmKhGfWkHaAkUs2UFS8XVMRCM/bD6UcAL2uaFtM0rRYYChRomvYqgKZpn2CTZPVHzvORpmlxTdN21u2fnWYfTdO06rq/5wCn1f39V+CZZrT1XE3TDscm+nnAu5qmxWngzOkC5s5mnDeJ5kbcJ2OH+K/TNK1UVdXrsFcpMjjAEULGn9OSzsfYvqpGLIgnqyiFvHuyikjE7IFW9hRSGrJJWL4iJ1+89bDKDAKShCFJSE6R1j+2rdvF4yPaY1pwiNfJA4Pb8drWCs7qUcD7W0vomJ2VNhprWE2jv628LhTg7sHdmLo01S7OY1p4ZGuPKXn/K4jjxeHNR5FbMGfFLqYPaY0/IiMZ6ftHNgWWpSBLcc7q0YZnNmzjhv5daOv2ISPhiJkk0va7wrSVG7j8iI5cs/RLwO6fnWnE6sqjcfKcgvv752CgoMcq2PLptbQcMCVtRN3rLeRr7d8c2n4UI0bex8IFV6XUuOv6wW/bl0EGGWSwvyEMK+04LQyLxEvv2f7rr84DwHHBKRAKg89LYtnnKH17kBCCqrYtiU34A45onJyTRiHVhBEFuSAJ5PP+iGnBN0JnyuL5lIRDFHl93DPoGgJAcMuCZORcNt17j47vycrN2nNGVYjd7OZyAz9qK+dM6Ok93RP6HumaLAtcrgSmGQUkTFOnZcuj6Nb9CoRwYVkxvvziASzr4CV8luVDUSRGHv13kIoYefRLJBJhIpEf+GLDA5SXryMS3sWqlTMYMvRWZMVHhVTAE1+t4boB3XDLEhMPL+Tyhd+n2AEfKlyUVjYEIhWPQE/zTLqwV07s8siuTF9/b/L7njmdGN16EBcuuz0lRf7Fb97j8u5/QRZS2tr1YLyWkkgZN3/2KE8MuoHyeTeTO3IKMza9QkmkjGC8NiNG9ytAt4yietJej5JINbplFO3hkH1BYrfPHYHdl+EENqe16r9TVXX3iE/jaHlyv90Qqf9D07RvVVXdqqrqSUBLTdOWp9k/LTRNW6qq6kPAc6qqHq5pWpmqqpuBQdjObNS1sQC7xn5Vc8/dXFX5xcAoVVVz6j4Pae4PZPDbQjdMahwefO4OdC9+ClMS9B19H6vnXZVS466tnIknq4iAJ8BTA3MJSBLZbhmpjwtzTQMxEwUy5bqBKZnkx+W0/rHBWotcl5P358UI1kQJ+AVXjjuEtdVlPL7he3rk+bmuf5ek6Fl9Lfs/tW1Ntt89uBuOuEkBEo+M6GWnxwuBx7Tw1dTsMSXvfwmRqEGuuxCnEJRHDUIJk0PcDsxqK23/GJKFJCzKggk6OfxM76piSvD+4gShMIwf4UAUpC7aiAKZ8kSc0nCMXLf9LmzldXHn4G48XefJag/G3clxCh4d2RVZCKpidaR9/UwE4HQG8PmKUsi7z1dEMPgdatdTiEYrWfv54xw35klM0ySjKp9BBhlksGdYskDq40IZ6kX4BFbIQl8cxpJFiv+6/vqHIMCqDaO/+RHW1hIS5ZV8f+Jwrv7koyQhv3fAMNrOWwbrNyUj8+WYTFm/nJJwCICScIgpK5bw5IibaD/kSizhIGJ4cVpm2pT8pH3cXqzcUpTjGy3E79Fubi/jvGGYFMg0y9NdlgUORxghDKLRahYumMzo4x5DUXx06nItr78VJ1gTJ+CXOH7stchybZpfPPAhywJFChEK5/LN1iy6OGXefU8iWOMj4O/Cccfez8avpxOLVxMKlbBk8Y0MGj2HKUsXk+9yg+Vi4kffccPAoqQo3bWLtwEwe2A7cnIFsh/yj1GQswTSFbnob9ZibrY5lyiQEYrgX+P6kjDjOOUY5bEqeuZ04qxOf6B91iFsD+8k35VDSaSMkkgZt37+GDccfj4excW965/lxsMvSKs0D3VRdMukw7E3IbsC3N/vSq5cdT/PbHqTm4+4kJs/ezQjRvcLQhFySZEnu31j8l7kyUYRcsleDmsuFgGXqar6CHb65cuAparqSY1S5VsB64EyoEfdceObcW6dvXPhp7Hr4Gf+hHbfj60JdyHwMHA98KCqqsdrmrZFVdUs4EngRU3TvmvuSZurKq8CrwI5qqoOAOZjq+J9tY8XkcGvDFkWuOQQep36qmJ6cL/5BYPGP44h6QjZQbS2FHXApcjCTVaFA8+smmStnHJJDjpgrokhCmRiFwZ4eLP9//DO7q0pPNWVTMdWcgV5Z7iIZVlEQhbHjXIRjVqsWp3g7XdjjC/Op5XXxYaKGl7+ejt/G9GdsB7Bq3h4+LOtfFxSQXVM5+GRdoqWjMBtmCTiNoGUDTO5RuqRrfQpeRNPq7Of+d+ClNDJWr+Ju4d048kN5Vx+RCGBfLlJ/xSe7SLqMpAjEh1rs7AeqyRe19fHXphDuUti3soEx16Yg3i0KvkcyJfkMHPTF7Tyugg4Hcwe2ZuIYZDlkJnc9zAuNTuiSAK/nKAs+D1RRxuuWdKQIXFbvzsolKuJx4OMGDkjmS7fuMZ98JBbcLuz2bZtIT16/hVZduNytfitb20GGWSQwQGLqNvAfaI/mZosCmScl+QSdRvI1InQZftxTCgm8c93kjXsADWDe3P1ysUphPzqFR/zxODe+NdvwqoMkpjzGvqkPyf3qUdJOETMEliJ+jR2i5C89+h41PCmtXJL4NtrbfxPsZXbk6e7LIuk3agkuYnFypj3wZUMGnQDy5bdhttTgCVkDCOb5SvjDB/qxO0WRKMWy1cmOHq4H9hzav+BCpcjhm76+GSFztDBLhYvjaVc2+rPBSOG3c6GdfcAdiaciUJJOMTlvQYyfcUuSkMJgnGTYa2zGNchJyk8vGRXLRPOy8dRbaI/WZWsa3eek03iXzVY1SbOS3KpddfiMMOY8WokbwEzB06lPFadQqob276VRMpo6c7jkjpBuvJYNZN7nEmuK0C2I4ubP3uU9VWbADuKLsVrEZLE1gXTOWzcvTx51M0YGDiFgyePugWDjBjdL4U8l2/yPQNOaVzjzj0DTinLc/km/9xza5r2mqqq/YDV2CXefwM+Ah6tq0OPASdpmhavI/cvqaq6FvgQ+LGFgy+xue3zwFNpvn8VeAJ4/ie0O1aXof6gqqrPa5r2oqqqOvCyqqpubMmNF4Dp+3Le5qbKzwQuB+7RNG27qqozsdX8hu/Lj2Xw6yKdEEzncTOQa0IoFXGsPBlT6MRjVezYuohu3S8nMbOmSV2S49o8rNNgaziO7Le4Qi4kIEnUWAa+lhKHXOIGEypqTJZvTnB4bwcfLYwRrLEI+AWjjnGx9JM4wrR4bGQ3EqaFjI5LMXAI20bsyr4ducJojwn8bc0WPi6psCPuQ7pR6JRIxFMH6j0K1ggLjzNKvQd4/EcUa/8bIMsC3RGD3oW0FdVM7u0nATz07U4mqoW0nOhCsgTbYnEu3/AdF3ZvySFRB+Kxhho0kS3hCJkcEpBwd1OIZAkSF+biliFqgMMvyHM5uOrIw3BIBi08DkwkdNNi0sIGm747h3TDUgqZtiRVZPCGVT/w2NHdWfTenzhuzJMMGHgtDsVDLF7NZ2tmEYmUIYQECHy+IqLRClatnGHb7zj8GTu4DDLIIIM0cMQEiTdqcJwaSEbcE2/U4DgjgIkd8cbrxnQ5IZhKvhMBX1pCrmc1pK1blUGcikKRN3XfIq8PGUHjEqYfi44bhkVcaU2X4qeRhYFh2aryWUYa5fg0C/E/x5vdPl5gWduTdqNHH/NQUijV622J21NAr74TefGjc/nzyDc4oreT+R+mzmUO1lHIEnEikTjdu7ZAT5hpry2WqKTtYWOpqt5CNFKGsOIUeX0UuH2UhqoAWLI9yFk9CriuURnCnUNaowD6k1WpWgtPVeO8Jg9TQMSt44p58Rk+EiJAjRHDK3uY9NndKXXut37+GJN7nMlVq+63bdxkR/L79VWbuGrV/QC8dvT9lMfsNtUrx0clB7FvFtN28KVIQkYOO5MLNzLglJ22noJUDXJTG8EMfjqcsrKso7/wD48PnbDfVeUBNE27Drhut80j0+y3BejfaNPlddtv3m2/9o0+9kx3zjo1+6OB+Zqm/dCMNqZrzz+AfzT6/C9si7ifjOYS93xN0+bZgXfQNG22qqrn/5wfzuCXh1sOJ0k72LVkG9+dTLcTHySk1LD6/WuT6fJ9R9+HGYmlrZXbUZtgq8Pgze8qub51IfLsRhH5STlc/10JxYfmsWGRYPhQJ2/PtQcDgGCNxfwPYxw3yoksCaI1Gh/OO582bUZyyOE3cs0yLUn6Zg7vzqRFX6Tavi35kkdHqDhkOeUFWy9Yk5KS17MTIaOU1e9NTl5Xn1Ez4L+Y9MmywKVv54vGKr1j7yac1ZHquEFpTKeF20HMMklIFn/pXkChVyFPaahBkw5z4Pijn/jTtiBdVoGMdUEO89bolO6071vAL5harFJtxXhy49/5U8cxZCuFXLxwfUp/XbvkS2aN7JVWZDBmCtyeAkxTR1HcLFlyY4o/rkBCCDkZgQ+FSvB48vnP/EsYfVzGDi6DDDLIYHcIBI7RvuT7WxTIOM/OTpJ25U9jSbzxEY7iY5Eu+hOJNz7C2mCnwbt8vrSEXKmNNJw/N0CWAXcPHM7U5YuSKfV3DxyOMyGapBv/WHTcMCxChocWLfzs2lUDWEjix5Xjf443u328wOmsJRyO0K//ZLZ9/zEBf1uGDLkV0zIQiotBQ2/jlYUXEQyVgCUx/8Nok7nMycXu5nbNAQXLNDCMMF5PIYoD5qeZp/2xOIeE3pZBgx/GssoIxiLMHDwGRZIZ1jqLj7fXMqR1IEnawVbrv3bJdl4c2D7t/LE0HGPm1m+5uW0nrIerkhl+7ot9RFua3Nn3aspiFTyz6d/JKHvAmZVUmU8YRtoa9V3RymT0Pdfp55mNb7KyfAOP978aJxKKJxvCDc/xT3E02BtkWSA5wlhWAiEcmInMIoBTVpa18mYP/q3bsR/xAHACMLZ+g6qqHwG5afZ9VNO0R3+NRjWXuFt1YX0LQFXVVjTHVSOD3xZ7EIIx87ysfufyFEu41fOuYsjoF7EKwk1qm00ZChMSd3QrSlrOQF1EfmYVp12Uy8yvdjJlVGu8QiQHg3oEayx8PonP1sY5rGMn2rQ5mu79b+DChane7BVxIy3hi0Sq8Lk8RBoRt3SCNdZJg1k999zkdTk9BUQiBt5sF5IM5o/4tx6MaLw442vZk8LBFxH3+HAIuFw9hHfnNugMDBulsH5XkK5tvNRETbx1dezKuKzkpA/qhI0eq2LYuTm8Mt8enIM1FsKSMKISkzqdTdCqYWcknLa/4qaZVmTwu1AVnQ+/lES8Bll2J6PuCT2CLLsRkk3cFcVL376X2tsl2x7OsuJk7OAyyCCDDFIhWTR5f8efrsZ5bR7S+GPQ5y6y0+NH9ifxz3dwTCjGKj4WAfi+/IZ7evVnyrqVKTXu/tcXAjSkuhuCFrh4dMgoDCxkhE3a95OeTNqF+Ma18fw8b/b6SPsH79uR9jZtRtCr93nMn38xbk8BvY+cxIsfncfYgbfapB0wLTPtXMY6WGPuwomilOP1Wei6lPbaIhHBK68ECPgF48a241HtBxZt/5ZWPgd3DGkNQMAppbXai0sWchptnGyXwrmHtsV6KPUZdcwOsX2SyTmr36bI6+f6vmfz8FdPUx6rosiTz+ODb2Rd+UZa+wqb1Kjf3ucSWrpzQQgShk5ppJzftxvB8FZHIhQ3JGLokWoai3WnC2RtencyXYqfJmR49omIy7IgwXbeWHAlwVAJAV8RJw65H8d/cZDofxGapl1OXcS+0bajf6PmJNFcO7hHsFXwClVVvRP4BJj9i7Uqg/2DOiGYxnD6i7AsM60lXMgjEbswgCiw12REgYx+cYAWQqb1zFooM9KuqBY6FTZURLlnw3Zkj5121RgBv6CqyuSQIoX35zk5st/t6JbUhPRVRhNpbd/0yC52F5WsT8kTE09DmXY+YuJp6MJIXld2i1607zeDuR+1Z87zcV59PYGuuw5qK5e0qFuc8bXsSe6wiby25jaefvck0JU60t6wov7xfJ2T2+fzzrsxwrLAuiDHFozxifTuAd6Gfgz4BVWVJm+/YvL6qwmMWje6qaftr52RINP6d0yxgrtzcFee+vITvIH2RKIVrF/3FKZpT7ZMM876dU9hWRaS5MDlChCLV7Px638Tiwfp1u0MJCmzTphBBhlksDssk7Tvb8uERJ0vu8gNYIUjyZp1tu8gMesFHD4P7f71IU+078nrA0by1FFH03beChzD++Gcdj6OiaeC34vTIZGFQUFMp0XCwrUfSTvYC/HyhOIUuzp5QjGhRvGhvXmz/xgUJczCBVcmRVEP63QCixZeTShUQveef+XdFTcRDJUQjVcTqLMjlYRIO5c5WH3cEwkvPl9LDMOej6W7ttrahvnCu3NjFB+aB9j3+bol27mwdyH5biWt1d7XerzJ/NF5djbKiyHaOz3p5xjCniOUhGu4ffVizuvyZ+7rdwVUbSO8dDY9cjtyzeq/MfPLF5nc40weH3wj1/Q6GwsLA4t/bH4HC4vbPn+c85feyowNz1Gth4hHg1i7L+bsxdGgnoi/vGACT717Ai8vmECC7ch78A+UHGHeWHJlcpEnGCrhjSVXIjkOPu2DDA4+NIu4a5r2FHADdp6+Azhf07RHfsmGZfDzUS8EU0/enf4iuoybgWRIeLJSCb0nq4iwbjBlSwkbL/JSeUsOGy/yssNhYD1g1y1ZISv5Uq6HKJAp8Cq8OqQDkw5rwRjDi54AACAASURBVMc7qvn9OFdyUKivnVq+MoHbbUfjw+EqZJqSvne+2cFdQ7qlen/3O4RK7QXS+Xjrhkm1Iai0ZKoNATiS13Xo4Zfz/n88KcT17blxwuH/MuJetzhT0P+vvL3qloZogZk+WqBg94GQBG+u0ak4Nwfy5bT96nQ19OHoY+0+rD/PwnnQwZXPo0OPYHiRPbjbqvLdeGXLZzzyxUIu69OKWUd35ap+rQm4LPLdHmRhEQgcSu/DL2DVyhl88MF5rFo5g67dTmXVyvswjGjSjqZrt1NZ+/ljqOrJCHFwpidmkEEGGfySEBJp399Cglhxb0TPTrYl3Ie2k5FVGUR4Pcl/2VqC//FXyZvzFjnf70CUloFpkXjkReK3P4bxr3l4qquxZv0TffrjWLP+iT9ciyKnnz4qskS2bJErDLJla4/7NUa6hfjdHWJ+jjc7JFKcTFzO7ORnpys7OW6u+PJZxgy4ySbvAkYd03QuczDbklpWLuEQLF+ZaHJtx491sWp1w8JIsMYix9GQlFsaSlAV07lt+Q8pHu6tfA6mDSjikXU7mbKlBMc1ebiuy8dxaoDEv2tsV6IdRtpntMxoILol4Ro6+A5B/+AWtv37PCq+fBNhGpREypK17ecvvZXLVtxDgTuHDRWbuaLH6UmVebBr5K9aeT9BK4GQd7PG3kMgC+HYZyJuWYnkvsn7FSrBsnZ3Lcsgg/2P5qrK/0fTtGOxJfkzOICwJwsVaBCCUYufRjLjsLMa64UViA5tmljC9R11L5WhbZTFHFy48vvk+V8d0iG5Uqq/W4vz7OyUWjrHJTnofw8SWBMju0Cm+6RcKiyL40Y58XokhIDaWhOvFzwe6NhBQjdq2LjqXu4adCPXLGuwfjurSy5tlAiPjVAJR6rQI7uoXPsAnfucT9z4cR/vuOGlz6gZrJk/GYerIC1xNQ5eC9a0kIVM57H3EiaWMpDUhrcS8LdJuQcBv0DHzoiIRi3CEXhlfoLz/ujEvVu/Os/OxnLAWWd4kAR8siJO6Y6GSVSwxiJcK/HB/BiXje3COT1D+B1OFpVs5Nxu/Ziy/D2mrLBT4O4cMIaaRJwrew9l02cPsrN0OceNeZJ+/SfjcmYnBerKytbRr/9k3J58PJ4Cli29hX79J2NaOlIzVIQzyCCDDP7XYAmajMvOs7OxBKxech2Dxj+O/vx/kmryIjeAZRg4zv0jZHlRLv4TAoEI+LCqapCPH47+wlwI+HCMPwZRmI9VXgUBH1QG9+rgosjSXtXh9wbdMAnJMj7JFp/1SRCSG+YzP82b3RazqyWPo459lo2f30d52Tpi8eqkLWk8ZkfZg6ESSsrXsXjtLEYdeS1Ygm+3xjnxBFtA17QsNnyR4Ihs5x5+7cCGTwoTiXkIR2S8XhBYFP/BjWVBOGIiSVbKGB/wC6oSevJzK5+DYNykPGrgUQSzj27HzohOZczgsbU72VAepZXPgWmBfkd5ym/rb9binJhDfFaDU405MYuHvp2b3KfI68eJQA83HCviobT17VtrS8h1B4gZ8ZTvwCbvUlZLHN5caKTdsCdHg6jhRYjqvRDxpiV6QjiSz0zyfvmKEKJpgCmDDPY3mlvjnqOqqk/TtNCP75rBr4XmDJKGYSHjxpr1ql0/dmgR0SPy2L7xPfqPnQVYhIPbSCRq2bX+Je4YMJXrVlQnB8aAV0p6epubEyT+bavV6i1lDGGhv1ib9Hm3a94rybk2j0oEr78VTSqWHj/WhaFbDBviQsgdaN99AoUegyeO7knCtFCEhU9ESegeXIDf7cZyFdH6qCnErSwwLHzOCNTZ2qVTAzUMC+TW9B/3NJYIEPCbTYir3IgAyrLAKdu2MAerAr1kRBGWhdOTkzKQfPH9Sxw/7lreeTee7INhoxQW7Qjy+3HZfLIizqhjXMz/MIYsBIl5oVRV4nkhxJ8DPPPPSDLiXlHZMLDXk/9gjcV7cxP8odjL3evms7D0W9447nSu6DWEfLeXgMPFw+uXsbD0W4q8fm4/4jSC1Zsx9CirVs5o4uduWSb/mT+RIUNvZfWnD+F251FTsx2PJ4Ystzno+ieDDDLI4JeEsEj7/nacHiBSW4Ih6yh+n71vbgDHWSdiOhSMJ/4NAR/ySaOoiMVIxGM4JMjN8kHndih9e6C/NDepIaP8aWyyXn534Tiw5yMBdPSfaNP6Y/OZffFmh3Ridh5uG3APfDqFzZveYviIe1m08Gq+WP8s4wbckkyXD0XLyPG1RpZN1C4O3ngrljKPkRXTNp86yCAJC9np4IcSnYH9nbwzN/W6PB6Lk4tdLF6aIBy2GDfWxYN1QtqtfA7uGNwaISyuOrIVHkXglKK4FAd/+2RHcr54x+DWlMVi5O5W625Vm1hRs+EZjVkkciDPbZPiIq+fuweMxhUuo8txM/j6gzpy7fI3qW+vt4srj1Xx0MCpaYm9JFx1LjUNaOxosPs80uFoIOJF+b0Y0O2veF15SJKMLIsm8w4z4eXEIfcno/T1Ne5m4scDTBlk8HMhmlPzq6rqIqA7sBaord+uadoffrmm/WJoD3xTXl6LaaZee4PK6YGJ3duXLVtYs/7ZRNBFXHo6GGYyCi+ZJvr0xwGwzv0dn3w+jV4jbiJuxPBktyFWW4pL8SOEYOOap2nR8xwcvjY4ZRndNPDsknA9EmqIsk/K4fuAScu4DFPLmrTTdU8LYgjihkVNDSz5LEE4YnH0CCdvvB0j4BeMHetA+KJIZoKty+5g19YFtDh0JO0GT8O0ZJQdFfjfWYIIhpAvPoW4EkaPVSMpHiwjjuzMIkEu8Xj6QTtXgcpqwVsLpeTgdMIIk/xcQXnctIVIjO2smZ+qQG/ug7hIixb+X6vYrT17eGZzHWFitT8Qd7qIKxJvLJmM113AyIEziegOCh0OPAnJFvaVISyZLFqcoHtXBy0KwELClzCRdhpNIjbhbImnXrPrxAJ+kdJ/9RZ/9UT+jDOcjP3wCXrmtuT2/qO5aPEbXNFrCA+sW0JJuOGZLfL6ubt7Jyq++wC16yksXHBVUll+xIh7EZKT5Z/cRiRSxoCB1xIIHMqSxdcTiZQxavQcYrH9K1B3oP6f/yXadSA8r43ackDe9z0h095fFntq76/0zLZnL8/rgX4vc2U3otRsGnFvJfHZyqm063YSgdzOOKMOMC2smhCWy4Hx6nzk44ezxetgytoVDeJ0/YfSQXIgSsrQ5y1NidQr448hMed1e54x8bS6ErUG0i0lEsRn/rNJG5Vp51NppaZKN3s+0+h39gWG28nFjcTsAIa1zuKKPoWYloEeLSPbJRGLluHztiRh6UQi5VhGHMUdwKN05pVXY00W///vJBfRaPoU6gPhed2tPezaVYMiS3jcccJRHwiF19+MNrmu4UOdLFoc5/fjXLi9Fs9/XU7PFl4CTomEaeGSBAUemUSkBFw5XL5sIX9odxi/P7QLvriCZIIhm8hC4KyyiM+sTHkeE/+uwdzc0BeRO7Ko9icI6XF8ihOPLBOp3ESRXIgUDGK1zKFCkbl2zSxu7XMxZbEqgvFantn0ZtK7/R/DpyOAySvvTxL7Gf2uoKVoSU62r9n/b+tr3JdueJS+XU7l/RW3pIrO0XReeCCryjf3nfUrzgky2I9obsQ9nSk9AJlI/G+HdF7mBHwoNSESjVatpYv+lFRsNX1OnN58DJePt5fenHw5Hd//Fsq0dzi063h8Ph+SEiFoyFy8eA35LheXXtyNfMVDQph4ci3+8vY3PNq/LZ3TqIjGSkx2vqFT+GcX8qI4vzvayXufxnE47HdEsMZi7twE/Y6LccPauUw/4iKKXNk4u57G+UvepSRcQ5HXz70nj6Td4nWEjB2s/uDqJMHuNfxGvl39OJ2PvGCP/t6mZRH4cB7/d9QATJ8PKRTC+eEKxMnHAeCUw6x8f3KKsv6a+ZPpP+7pFPX6Ax2m7CPk9fD6ksn43AWMHTidiNKZSxf+QP8WXi5v3ZIf5kTRKy2UXEGrCS48LsHbc2OccZqbN96KMmagQn6aiE1wTFbyd4I1Fv5s+OsZbqoqrRTSHvALhGTxxPBi/A4X/9q8jrsGjCFuGimkHew6NsWVR2npCo7ocwmjRj8KmEiSwtrPn6S0dAX9+k9m4YKrCPjbEotWUla2ru7o9GlrGWSwO3KzHSjO5uki6PEoldWZ2sQMDk5YgJ7m/S2f4adT33PZ+sUrZAXak3i0wYFFOXUc8vHDqS7IYconHyXt4ErCIa5euZgn2vck8O/5TaLswuuxo/YTiqlGpt7qzYftwy7GH5NWHd5qpA6fbLdpkS1bDQEGwY9awu0Ldhez65Hv5v+65HHxRw12cncPPYQCZ4LKqs1s/PrfHNbpBAI5h/Hywos5Zfhb6cvtzIOL69QvqkQcObz+ls7xY+W011WvQfT2uzGKT3LyD62CHmVhTu9WQMApURU3yVFqcbp9XLx0IfkuNyMPaY+vUmHX0zHkgCD/eCc7Xogh+6FgQi7OAgGKReLvqaTd1tBRMKwYUV3n+pXzKAnXMKJVBy7vpSL5c5GFhEtEKY9VsaVmGzM2PNcksp6leEmseZFZnf4Py52DiFYRWTIL59CpgK/Z98gwLBxya47pM5WXPjqnSa37KSOb2tEahlW3rX77gUHaM9g3qKraAbhe07Rz9uM5VwKlmqad0GjbcsAF5AFZwHd1X52hadq6pmfZM5pF3DVNe3YvX38M9N2XH81g/yCdhYoyejCJ3VLVEm98hDKhGH3Oa0ihOB36nscbS69OeTm9s/Imxg+4A48zAMKBHM8mYAhu7NaHWVu+4G/ffMkZqkr7gJ+IaTGsdRYPb97FvRcV4Xwk2ODrfk4Ope/p6JUWO1+MUTDeSdk/Ygz/i5NwtOHFFqyxKPJkUxKuYdpny5h91AVc/MkHSaJXEq7h6vULePL437P+rTNSCPa6RbfSbdBkVs/bM9EOIeM/bgjORnZx8oRiyPJBrBZIpFXWP9jIYVSEeX3JZIKhEoKhEqriOjct/4HSUIJLBhWyY3YMvdK+73qlRemcGCMmuimviCFJ9kD98VqdE8ZmYT3eUH9mXZDDx2sa6tsCftuvNxQ3yMlV8Hobto8b6+Af36xkUKt2uN0Kp3Y6AgMT3TR5edSpPP/1Gt767ivAjrhLlsHIkTOwLINPV91P9x6ns/rTh5IE3eXMttPmsTBNe7D3+YpIJ1CYQQbpoDjdrJh5ZLP2HTDpU3Z3rcggg4MFliwhj8ki8WTD+1s5NwdLlljz/hR6DLkGsbO6YZ4Q8EE8gVSYR1wSKR7uYJN3PcsWr9NfmpsSZSfgQxl/DJbPja43ZLvVBxH0D5fbZL9xiv2p4zBkicby74osYZXuwnrq1WSAQUwoRvTohLVhU3K/3S3h9gX1Ynb15P30bgVMX1GSYic3dfEPzOgPBdkd6X34+SxccBVHDbUt4SRhj2+7R6alg4u3JxdVjEvPxusVOBwi7XVFow1CvoauM6x1Fv/XJS95z1r5HEwf3Aq3bFESDnF938G0srzsfNqeYxSMd7LzBftvvRK2Pxm3gwWXOVGKs0h8ryefz/CFbu7euIDLeg/hqk/mUhKuoWdOS045rC+XLPqEknCEIq+H6f2782CfScze/CY3Hn5BUojO9nifTJ4ls37Nc7DmuZRrFsOmEIqUo7iiCOFAmD4sKbTX6LhhWAjT2Kda9wxSETeMQRWx8AzdNIsUSSrJc3knO2V52W/drh/BocBh++tkqqr2AuLA4aqqttU07XsATdMG1n1/FjBS07SzfupvNDfivjccZK+x/x6k8zIXLXKTtexi9OFYPieE4lh+L2LiaTiEhVdOL8Th9OSxbcNrtG9zAT/MMdArLXJzPdx1Zn+COSalYZPKqElEt7igdwseW7uLzT4Dz0QfXXwuYiUmpe/pxL5rIIqyV6BXWrTKllj/WYM9R8AvkCW7BqkkXIMpOdJGZxOQlmA7XIG9Eu16lVrfxNOQ61b0a5DJTY66tgJ943PbivQHFzm0rAQ+dwFH95mMz90Cy3UYpaGt9Mh340JKkvZ66JUWGDCuvxOkOus+IajwSLSYmodsAApUJCAcsY+pr4FbvjTOlm9MAn6DsWMd9BoYI9tlk/Zj2hyGQBDW4+iWxdTl7yUzJ+4aMAaAVWXbuWvAGCRZ4ftvXmXzptc49tiHWbr05iRp9/mKSOgRho+4F8OIJkWERoy8H13P1I9lkEEGGaQgISidq5N/Rg6KR6BHLErn6rQ8QyFSW4Ivux3itTpf9kOLUMYOTxJr5fK/UOT1pZD3Iq8PpdZ++TeOsiunjsMMxzBWrEdp3TKlCckgwtYS9LmLUMYfg8jygsdN4qW5yH85gcZRcx8GiadeTQkw6HNew3HRn0j8sDNlsb2mUWR/X7C7mF2uS05vJyc8zPvgPAYNvomhQ+/A7Ssk4CtClk3GjHbx/ryGWvAxo13I8oEvlCrLArccJhasRcgSVsCHLEwG9newfkOc48e6Umrcx/3Oxdp19r0J+AWhyHdMOuJQLm1UapDvlqmIgd/p5JFhY2np8iJFRXKOUT/Xawy90qK8NkYi26DVtGyshMW2WJC7Ns9jXdUOLu01ODnvO1Ptx/RV6yipm3iUhCNMW/kFDxzRiotbDcAte3hy8I2YlolkOXAbLgxq6HDKU5jhCspWPktox3oK+5xB0KjkjYWTG6W738fStY+zefvCvXquZ0TnfjrihjFoS03Fm1OXv1dQN/drf/fA373Z0Z/3h59L3lVVFcBdQDGgA48Bc4HHsSPYIeBSTdNWqqr6DLBA07Rn6o61NE0TqqreDLQGOmOT9Sc1TbsDeAjoqKrqLOAV4B7sl9UXwDDgOE3TvlZV1Qd8BXTWNC26l+ZOAOYB+cB5wI0/59rTYX8Q98xM+jdCOnJqAKJnJ/RjDmPjgmlJ9czO42YQU1pj6BYehyvtyykW3kWHzhMonW2mRGlrnzPJn+jkqk+/Ta68Xj+giElHtMC0BH9esIU5g9vjesNKeXEruQIjbKdo14RNunV1UFFpEQ5bjBjtwJTtiG6R148iJIq8/uRLvGdOS87vOhRhZtHjd8+zbfU9VO+0yZ0nq4hELJhCtNMJzemGWSeII9et2DcMuI0V6BvXuDdHvf5AgiK5GNZ7Eu/VCeuMG/4srXweLuxdiCXZ9373PsG0qHg+hu8sJ2PHONF1wbz/NAzix41y8cWXCYYPdeL1CLKyBDW1JuG6sr76UofDR4eQ3TqDWrUjx+UmGI+xIxLins8XpWROXLPifR4ZeiJnmH0oi4S4ZsX73N29B6HQbBCCSF36m03QZxCPB5EkCUXxkZfXjdHHzSFxANWPZZBBBhkcKBASGDXwwzP/z96Zh0lRXe//U3sv07MzMLhvVBRUEAUFZDEuiBuicd/AGNeYRBKjRqO4ayR+k4iiKG5RjHGBiGsMKIIC7gpqgYgoMjDMPtNbbff3R/X0TM/0wKhoIL95n4fnma6+dftW3aLuOfec875tTqlaIiHJwVqpeApSUxwBqIcMzTrtALFn53H7KYdx+fuLszXut+99ALGn5gV9lxRCLIiyu8+/Dk1xtAtPpkXRaC/RkhNEWFOFO3teEHn/14vQFO8UNc9X5ifqm/CRkDpstm+Ojb4rdCKzk6WcCDwEEXk3XUs8XoWqhgEJO1XPcSOmAhAKBdw8mibhOIJQaOtfgxRFQne/YcW/2tjT9zj+ZrRPLUrMvVFkFQnB+GNDpJKCRFKw9B2bgfvopNKCgQMTvLHsJobtf0f2XvUvC3H+PhU50fcHhxXi1fhZG6PV1utob1TbSa5f9D7TRh7IRhGnOBJi58ISauwEtu9RGYlRpkfYvaAP1w0uo9FJ87D1CcvrG6hKJPGVECue/w0Aw49+AFUJ44e3J+GtZc6CNnK4ow++luiqNyne9wSefO2CDunuv2XMoMms+ub1Taa//5ikc1tzjfx3QV06MbXVaYfA9vv9kpfK7z14/NQ+kdiw79n9icBwYG8Co38hcDFwhWVZz5imeSDwlGma/TbTzz4EzngxsCrjrF8KXGdZ1sWmaY4G+gE7WZbVaJrmFOAMAuf7BGDuppx20zS1TPvRBBsK/zBN83rLstyuzvku2BKOew/+S8gnBQcQPX4YK+f8HLs5eHHZzVWsfGEy/Y6fSdwLY3gRxu93C7PfuzL7cho/fCpyqhknGcetL8z5Hbde0JLyc1LMblxaxf+N2oG1LQn6RDWmfraem8/anpZHnGw9dcUpBg0LbIpPN3hpsU0iKTj+uBCKDGudJC4Sdx50FDtEi6i1U9x8wOFc9fYrlOkRfrXXkdz1BlTHbSqiO/O74XfC0t9gJ2qCGvdlT2QdbUUB2fsmW7Pe6oST2VFt79SnEzaKYuQw0G/LrPJCuFmnHeC95XcwZcjtFEc07v+8hkkTy9nwYDqnxr1ufjBHspBwbMGr89sIeJqaBa+8mmbkCJ25LwbUuSceH+KVV+0cQrqmZsGu0TIavCaims6XzQ3c/uECrh18SP7MCd9DAu7+ZEm2zj0arUSWFQ466BpkWSNtN4LweevNKRx2+HQUJUoqpWfmZNualx70oAc9+DHgqT59Jhqs7/Ce91Sf/YbfhPTGCrRzxuM8NDur357Fmip2fOLfPHD2sdjpNHo4RPSpV2FNVRBlP+0onFnPZwnqAJAkQp6L106qrTWIUHDxaSieh9hYh/viAmiK542a5yvza02LD4joOm+2f6d74/kono1CwDLfUU7u+gOifPHeDUSjlWhalJaWdSxdcguHj30Qz5OZ81xnErcTj+8ed8Z/CyElkXXaIWP/zbuKPQ+6DVUTFMQCmd5n5+ReW01NmhOPN3hu8QVU1X1MS+Ir+kSLWB938pYZtKR8/Fc8Kk4xqH4iTf08h4pTjWy6vFoiET5T4sYvPgkccCQcD+5a9gETf7IPE3bpz/xvVnHXsGNJpSNMecWhOi5REQ1zyfD9ueuTd6hLpzEiZfQ7fBr11j9xk/WsXnA1u514Xyfd9bnvTOGUMffTnNyQN6M0pBflfM6X/t5a637S6Ad/UIe6lQxvzmu5GwT5sgC2Fbi+X5nP9nOFX7kFuh8FPGlZVhpIm6Y5AvjKsqxnACzLWmyaZh1gbqaf+ZZl2UB1pn1RnjaWZVmNmb8fBF4lcNzPBq7aTP9HAVWWZX2SyRLwgWOAZzd/id1Hj+O+jWJT0ime5GVf2q2wm6sCCQzCtHgypWpfTh1zP6lUHZpegKGESdop0okNqCVFnXZNN9qdU8wUSWL34jC3DN+OKxd9w1Ur1vKrs3uzR0EYVIFwoeRYg8Z4sPg2NQuEACR46LPlXDawfzY6WxmJce3gn3LNoDFUhnpx3Sse1fFgDNVxwZ8WGdw6djph0YBA4icHXpF1tMN6skuiOZvIJp365DZOLuIJN2eRWl/7MXx0OWMOvI/HrDqa0h6TL+kTJBf5grr5Di1LPSL9ZcJhiEoyhx2ks+gDh/XVbfMUCgUlBe1l316d1+bQF8YkvojXUhCRmfnZO0z6yf78Zu+RlOgx7jzoGB74dCnLGjYAQUaFANKey1n9BlFihAlrCmN+ehcffzSTVavmAEHEfcjQKxk16k+4bhpJ2vY2UnrQgx704MeE8GWa37Pp+wsD5CCjqmGJQ2yUToFUgehfDGED7Rc/A03tXEfeFKf46w04D85Gu/p8OHBfpFEHINI2Qs81EaWSQsS6asTseZ2kZ13PpwEJVdGJ9umFcvoxXUbN4ygUnTshmy4v9d8d+bij8H2VAsUnid2lzNt3RWsEfvqYHXCEAFzs+GrC4TL22++XeG4KTQ0Tj1chfAdfkJfEbTNE7v99CCev/Sd6F+P7Eo2NPiXFchfXJhFPBxlwn69+nFtG3MCVC9dRqMudygw22g7FTRK1L9iUj9dRIhJCFvT9pcHGRIpqO8mNX3zCsvoGRlf2JppW2VMu44/mQTz09TKG9q5g37JKFMLc/pqTY+/dvQjOGzYATXO45p151NoJbh/yO+rfvQ+7uQrPd/I6557wSKTr8maUpuzGnM9dpb//GKRzspbIOu2tY+8qC2BbgSrLVZWR2M4dVYRUSa7axGndRUcSml3pXKYtEfi0ovW7TAS8PdpHy7PtOiDZ+odlWV+aprnGNM0JQG/LspZsZpwTgR1N0/wy87kQuIAex70H0EY4kk8v1ZU09Fhlzstbj1VmNSldz6dZCxOWJGw7yfv//j2Dj/gLRriMzz78C/1Ov5Lax8LZXdPek3Smr879v9cnqiFJPp831fHuhnqmjdkNw1eICAkJgdcM62e27byOPd3gjc9sFAWE8Jm0Vz+eXPVBTkr1lHf/wx8GjcYTUvYl3orquMD1FeLp9kyhrW26JprryB5vRMqwkxuJFkcRir5NRtnbQ5bUTotUIlWDJJKM3K6AI3sX4foCSZJoXuJQ0F+l+GAVkFg/PXd+XnrXZn21n3XW28u+QZtD3yrn94flC6m1E1wzaAxCaPzlg4+ypDJXH3Aw05a9Qa2d4NYhR6AikxQiKw9XGYnxp6Fjgyg7bWnyIaOIpuav+WDpNIaPuBnQ/wt3tQc96EEPtg20qD7qYBWnTiDr4NsCdbBKXPWRn3kV9ciROPf8I1s3rp1zHA4gln+eo88ulRTC+hqc+5/O9i2VFKKecBjO/U9nI/Du3Nc2qc++qRK19m2kPr2CtHhJwo2H+eZuG7feDTIGJoUg5pPwtrwDX+80cfnSNg6W24dcjuzWomlRkqk6otFKWpq/JhqrzE9OJ2+i860BXdh/vqQhfFjytsO4I4y81ybhcvT+UyjWTSRfQZI0bh5eRqGu5ZQZDCgNEdMV+l6o42z0qXvFwWsS9J6k0aLbtOBy/YfvU5VIMrqyN9fstB8bp7XN76RJe7POaKZAU/G8/PbeTrEY3yTXgxTYh5cv/Td/NQ9HX7sUyfPyOueypLJs9XMcMeTaXEm3EVN5c9m92Xb/bc11IfJvh2MEbwAAIABJREFUPGzLJHilRmTybUPHtq9x57ahY2tKjcjkLdD9AuBXpmneQ5Aq/yQgTNOc0C5Vvg+wDKgB+mfOG9+Nvl027QvPJKiD/9umOjFNszdwOLC7ZVnfZI7tClimae5qWdYX3RhLt7AlHPeWzTfpwZZGVzViiu+TIsLu46by+QttNU67/PSPrFlwO9sPOR9DK8cXYLsprLf/xr5jbkQzYvi+x+6Df86Kd29hp9POwDB6o0cLEaEkk6LlrGhIZ1PM7hy5HV7CYX+9N4O3643kCRDgN0vYzYKNT9k5dfINj6U54pIQza6Ppknoss/fV32YM/6qRDO9wwWsa6mnIhrLeZlXRCU0BJIi56l52xTRXJtTX1wxgH77X8zHC67PG33fFuF7McYPn5plli+MVnLEkGupWvcSf9zlZ1TPTLOuPkXpeIXCwRrrZ2aY/menO83P8FN0/v1WoOMaCcMRh+m8sShX9q0gKnHcsTr3rHojG1GviBTxqwVLckhlbnz7I+4eNRZJ8mlx0qxLNnHT+6/lqgYseYnpB13O4MG/JpGoZumSW3JI6rY1osAe/P+D4iINrZtyc46doqFHbq4HPxAUCUIhULWAaFQRICmClNS5pl3UN+E8NAftgpPguDEgBH5jMxRE0SYchvPMv3P6FvVNSBWl6L8/FyQpJ22+o1RbvtK9TdWnS7JEoydRoITYMDPXXlg/M02vE3XChQbJSHqLOe+25nP5my/lrEOXL/03dwzYi3ffvp0DhlzOsOFT+PSTxzhg6AGMPdzgpVfa+F/GHm4gy1u3rZDyOtt/u4+biifHED4kEoJ4vDPx3lFHGvh+HdHkLlTPUDKb+g47nRvjga8trhqyAzcvreaAXhEu3a43Gx9Is6EwTenhGr1PN0AVIAtCCZ2Q4zPlgP0oCukU2XrGaW+b340zHba/tJAGEqyN1+W191Y2bmTq8vlcPWgM93yyhGX1GyBSzi4//SPxL5cwfvgdzF7023blnncgixjD+l/Am8unM2bQZCJGKWGjBFUxOGTglYze97fdSn//NvXn36VW/X+RBE9XlLd2jZUee+/B46e6wq9UpS3HKm9Z1rOmae4PvAfIwF+A+cD0TB16GphgWZadce7/YZrmR8A8YHMR/0+BYtM0HyW/9PkzwAzg0c30cwbwQqvTnhn3F6Zp/gv4BXDF5q6zu+iW426aZkdWPAEkgGWWZY3cUoPpQfexqRoxzxPY6nb8ZML9OC3rcZL1rH1rGvENy0jWrGDPIX+AOY+jXngF6UQti587l2HjH+X9Vy9n4CG3sMOe45E0j3j6M75Y9gaxAeegpMI8fOCOCAUcwycaV/EbddbNatPvFI4gvtKheJiel13UaxBEdIlkqU19MslfDzyBsBKi0U7w0Mo3qbUTrI038cBn7/DLEWO5e2GwE1sRlbjqIIg8NRd5/KGddvg3RTSnK4msU7/rvudknXbYdrXb28O2fQpDJRw3YDJqrBI1VEjabsYsP4LqjBRcwRCFgn00nCpB79MMlFh+9tfKUpkxo3TmvWaTSAiOHmdwyCiNpmb45DOHA4foVNkN/Gn5/Jw0eF1S+M0+gyjSjBximdpUkkkLngRgxsjj89a+CzmE8GJoWrIDSV1nFnlVkYiSRvY9fFkhjoG7jW649GDbhqaHeGFG9+Tmxp3XIzfXgx8OUR9EUmJdhxr3qCGQKnvl1rQTONwIcKa3i8KffRw+AppypeGkkkJEdR0UFuC+vCin1r29VNumSvc2Ry4n+/nVT2RdYsPMNL0v0WlhUyTO3YeHn3cdihbtxvARNyPLISQJDhhyOaoiCBnkkNMZhkDZyiPurfZfv+NnokgenlBIeRE0dBYsTHPoIQYrVzkM2ldlwvgQiXhAULfkbZvDDixlw99zN/U3PGAz/Mw+3LXsQ64e0p8BShHr7s7YfeN0qp9oe+4qTjWofd5GNMn0PSvCHSs+4g/9BuWdX8WV0bQQJYbM70Zr/CmTLl8RlbhijM5NH71JVaKZG9+fz2/2Hs6dHy8ipEdZv/RudhpxGWsW/ZnjBkxGDhXhpxqpf2sGBSOuIGyUs+9uJ6CpYRLpOl774E7iqRpOGv0gbrow62hLan5Hu6v685C+fSdJOeA71ar/mCR4PyZ0RXlrCxDR5YVlWX8A/tDh8Og87b4ADmh36NeZ49d1aLdzu48D8vWZqVMfA7xqWda6zYxvKjA1z/ETOnx+CHhoU31tDt2NuO8NDAOeIkh+Oh74EjjJNM0hlmXdkO8k0zQLgTeBozO1AocCfybIBfmHZVlXZ9oNJNjRKCJIibjAsizXNM0dgb8DFYAFnG5ZVotpmsXAYwR1DhuBkyzLWv+tr34bRj4puPYkMJ4n8GWPrxbeSfGQsykZeSnFqUYalj4MvSshVoQ0ZxaDj/wT7/7nd3hukmRLFZ8uvoN++1/MR69dS7Klin2OfZRwcznND8OGeiebOu+nyJKQtOp39vmFTuF+Gs5GPy+7qNciqJltU3Gphi5Kmb5IZF7URfzq4CMpDKf5+8oPOGePYUR0wdWHqsRdm7KQQWH1V3g/3QvUJAWaivBSIGmkWlPduyCas2lz6tsk5NqwLWq3d4QsoOr1P1M56jKefivYgf7FqFez97/0MBW/hWwWROV5Rt75qW30mZMhpAOY+0JQ075goc3R43Rea1jOgPI+1NqJLOv/zgWlxFMyjy4mM5cBscysLz6m0Qki8JWRGCV6OEc1oPW4LBRs20dRtuPQwx6kdf5cN3cxVRWJWLIG75GpuPUbkUp6ETtrMs3h8h7nvQddYu9zniMc65v3u2TzOj5+6JgfeUQ96MGWhezIfPNgKjdi/WCa7S4JIao25t3gFzX1uVH4h+egnjy2kwa7NvF43FiUFDKRI4bjdSHVtqnSvY4b7e2hKDKSIO965HuBSo3kbznFYQW5y3UonW4j5VWUEK4nM3sbJKeDwHmPe2F69YqxcWMzIJAViS9W+4QMh3321qipFcx/Pff67IHkdbK3C0VYXt+AlBB4gja774lcJ796VpDRt/7BNC2P+Jx85m5ISv75dRt8aFZ44BOF4pDLdYfrNNpJmpwEKYlscKAq0UyJEeZPQ48gJkPs4CsQwqHxi9dp/OL1nLHuMHwynufwzIJLO90TIRwUJbJZRztf/fmby6czbMD5zFkwOee8sFHOU/O+fa36j0WC14PvjTsJyOWObD1gmuZ8oCRP2+mWZU3/MQbVXce9NzC41Tk2TfMmAr27g4F3gU6Ou2maQwmc8X6Zz2GCWoFRwNfA86ZpHmlZ1osEzvnPM8yADxBo390D3A3cbVnWE6ZpXgNcA/weuBF4w7Kso0zTPJMgbeLk73IDtiUIX1CkiCAVDUG6qJDQxaci+T5ClokrGq7dTnNFCREd9UumfXAttYkqyiKVnD/mRnxVR5x+HlJ9HRGjNwcdfi++LhEuqKShehkr3pnGngdNRg+VEDH2YP29Tu4O7EybvueHOul3KprMN/elUAqlLNNoe4b52hcCx1H2FP76Ri4ZyV1vSNxwuMGx2w/NsMkLKqIelxysoEgp6rX1rH5vBnailn1HXkfVor/hJGrZfdxUbLVrorn2Tr0se/8T2u0doYhwIPenCMYMmkxRdEdkUYhaEtxvSZJZ386wq3ulM/trn0kGs9+0c/ptrWlvahbMfcHm6PEmVU4DMw6eQFNS57b5DucOkXhgaboTscyNY/fDl2yeOOQUqpLNCC/FLfuN5Mr3FrSrLRyL7sh4mY2mTRHCREnjPTIVUb8x+LZ+I94jU4mefx2NPXXwPegC4Vhf7nhiv7zf/faU937k0fSgB1sews/vbOGDO29JZ2f8nPH5U+IVBeftjwMSO0UGWcbTVOIOuJ6H10F6tpV0TlVkVFw47ShEIok7bwliTVWnVPp8CKPjNopO61HFqQaC4G8hixwpue8D3ZG5fcjYDjXubetQK2RFJxEX2yY5HW1lC6K+kSJFIo6CLAUbD7vuovLCS2kOP9TodH2qlt/JLjZ0KiNh+hhhvJpgXrrSbVciUvbv7UIRZEXKP79C0PJomrNO1/nDwjSr620uHukQ0jymftSWXV0ZidE7FCHkqsTTwRxFdfLW8SNpSBJdpqFL3SCFy1d/PmCXY5izcHKn804ec/93rlX/viR4/2tyclsjLMv6NZmIfbtjY/5Lw8miu0k/Ze0j2pZl1WaO2XSdA3gegc5ea3rBEGClZVmrM5p2fwd+ZprmTkDYsqzFmXYPZY5rwEiCKH/2eObvowgi7gCzgCPzsAf+T0FVZMT6jYhpj+PefB/i2VcJNzbiTpuFffMM3GmziDQ3o7bL40pKHvdlnHaA2kQV9753NTXNX/DaUxNYvOQaEukNSHOWYCR0Bh86Neu8f/rWVBS9ELz8aWySmtEEh6x+p/CC79Jr/CzT6HYXh9ju4hC1L9ik1wSReF8WeclIZElFS+n84SCD60caFIcl7noD6pvWM/eDW9hpyMXokTI+XHAdffY/B7u5is9fmExISWzy3nmeIGmHSTkxBh/+54yzTgft9m0XAhmtoDeODMtXP48metPs+fSaGETWOxp26TU+tc/b9L0gmJvy8TpyFBLJ3DlpJamDwGCpTzpct/RjHFfjtvnBxkuBnp9YZn08xUWvv4nty/QvLqdUldgpEmHGiGN59tDTuXfYeHqJSLdrF2Xfyzrt2euu34jsbyGLrgc96EEPtkFIctta3Aq1RAKZQFP9xQWo4w9Bv+o8tItPRYSN/Cnxnoe6/wCc+/6JffMMnGmzkDfUEnNSOXZFzu9kUuSdabOwp80K9NuPHIm0U2VbKv2mxu5LSL5E7fNt9kL5eJ3a521kRaL3JIMk9ib7+DbwPJ9eIsK9w8Z3WocURSashggrYTSCksPCWO59LYxJW32qfOuciGmPk77hXsS0x4klWpAVn8N+ahAJB5vxrQS07eF6gopTjOzz1Bp08SWHP/UvpDhi0LTUCY7ZIu9z5yVE9u9iTUdx5fzzKwWOf4kW9FEdF/QJF1Okh6hNBzZdZSTGDYMO4q33piApbc9sax2/HgtsOT1WyR7H/g1HBnA4ecwMzjr8cY4bcQe7bTcqm4a+aVK4AK315+0RMUq7OM/r1PbHqFVvTed/8rWJPPDCMTz52kQcvkFRtlx2Sg+2XnQ34v6FaZq3APcR0OefSyBeP5Qu9kIty/o5gGlmZfX6kksSUAVsv4nj5UBTO+H61uM5fWVS6puAXrRtEmwWZWUFeY/36hXrbhc/KkRTC3ZGOgVAHTIA58HZnVLTin91BlJpcA21iZas096K2kQVkhbs8CVbqnj3P7/jwANvxr3vKSKXnsbQo2fgpBrQwmU0SVGkdP60d1TRSb8TIbJt02t81j+YRi2R6Hu+kXXa+0wy+NyJUxFVcxy+A7eXMeIKG+emSTYKwkUSvzrG4C8f20hyhKZ4FS+8M4VxAyfz0Su/QzGCtDa7uQpF8ro1b0L4OMleHHj0DITwkVUDI1yKJG3lK3EGXT2zXmMTaT/FW8tmcNBOV/HRLIVko0PFHh57XWIgSaLTHHpNAnt9uzm6JMThhxq88mobWU17RvnCmES9k6IqkaQ+7VCdWUNb7KAmrSOxTGOm7ZVvvcM9ow6iVFLRIiVEv+O9Fs0eXkmvHOddKumFYuj0in2//7Nb6//5rXVc3UVXz2srtqbr685Yvs94/xvXujXd3+7gvz3eTT2v/+2xbQp2k5tXx12owaaoWFOFO3se2vknIao2QHkJ2sTjcdqV2WlnH4coiOBOm9WWVl8YBdtBBookD+G4uPc+ma1hLzp3AhREsv1AYIe4/3gR9YTDkIpjSMUxesldOxOqLpO2fbymIL0/e7xEQomCHIFwLNrl+VsKQgiaq33efarN/uh/rMGRR+i8+LKdXROPHmegKP5W8Tx09byKphbsPGULoV+fTSSiIREow7zznsOhhxi8Oq9tzdd1ifoFbfJuXkLQsMCm9ESJIk2mWXVRDlFomGdTNErr9Ny11ri3PoM1s21Kj9Xzzm9rwKfeCWyHiqiEJFyK0hu4sf/u6EYpdrqODz+8gfW1HzNm4GUYERdFNoiESoA92OtnDyM8G0kN0ZDeyOzXJuaQ9C5b/RzDB1xAedFuyLJKPJnOG43XtRAlhcGcChFl/MF3MvuN32T7iobL856nqiGOG34Hc9qR5B03/A4Ko6XIsR9OtCuerOWpVztnDpx+6CNEw2XA1v3O6sH3Q3efrIkEVPjvE0TYnwd+TpCe/ttu9pHv7e1/h+Ob6qvbqK1twe+Q89RWD7T1oUTycuvUIuG8pDOe7VKfuQYlrFAWqcxx3ssilXipNj3LZEsVYvtSlAtPQm5OInlx7AIF2S4m5su4ik/h2RpNDzvZl3OviUEaW8MCJ/uC90WQQpbPgPBCgu3/EAZZUKUkuPOdD7lyzEHcNt/OkpFcNFjng8eCRRMg2ShY9VyaiUfrpO2AtKwpXoVqFBEuqMRLB9euxyrxhLLZeVMUCd39phPTaiIV+s7pRT/2izHfM6vrMmGnFldW2X/X8/lsdjh7D6tX+jRXp9n9VJk+k4wceb6OC6yt+eiyx7hjVTxfEFFV3lgYMMoXxiQOPlTi1s8+AaAunaIiGqY6Lnj6Y4dLhhvctSjdNpfDJe76JGhblUji+h6fPH02e4ybimtsj21/e4ZgVVGJnTU5my4vlfRCOWsyDY6K+z3+z26t/+d/iHFtDc9r+7H8kPf9217r5sbScbxbuv8tja31ue4KXY33x3xmu3pet/Z7GTPCoAr6nm+AJAVM8b5oM5Yy6fG+5+HNnpfVTdcuPhUamxEtCZxnX0U7enTWppB2qkQ9ejTu489nnXv19KMDZ76+KaiLf+AZtAtPyWuHSBVlNMoabm3XokPlZQW4wkMp65xK3ft0gw2zbHqdoVGf2vL3vmOaseaV8v5Tdo79sfxfafodqzNyhE4kLBGJSMiKjyyn2bgxmbffreF57WgrQmZOXJuQlsSnkKPHGcx9Ic2bi23GjNIpLpZRFRdbrid0qELNIyI7F8Vnu/g+FGgDEK7Kg401DP9pAZLuUxiR2e6SEG6DwHcEAkH50Tq+LfBSgsRyn8IjBWWnGdQ+nls62bDApuBMg7s/samISlw63EBxG8BNEZU9NNGCTBKJwEmua/6SZxZc2laXznZ4ng7o6FKS2Qt/k+PIvrx0CmMGTWb2wiAV3kmFURQjLylcOmmQaGl7zlSlb079ueRF85PJ+RJvLr+PMYMmE9KLSNmNweeBV+KkfjjeJNVI5c0AsJ0UiZbmbr+zepz7bRPdddwHW5Z1ap7j93yL3/qGQGevFZUEEfKujm8ECk3TVCzL8todb9/XWtM0VQKR+9pvMZZtDh1Z5EUi2SWrfMDyKlGQcLhwnxu456NrsjXu5w2awtq32uQIwwWVOPFadC2GkFTkgjAFrsGGe922l+z5OvXnykSRKdYV6ufYeC1QdpSeW7d0ikFitRMYEEqQqpdWfQQyrubSSJob3/2AunSaRq+BMw+UKNIMkp6NgpFdNFuRbBRsH4NqO8L4Mf/CdZuQcdh35HXUf/o8/Y75C0bxjgiChXhTch2a3kLSSVI56jJq3n6Y+IZlfP7CZPodP5P4NsooDxARLaT8NKocpThSQbLRzfk+2Shw0zLrYzZ9LzbAk/CSAiUaMMxLKgjV5/0PXbSd4tz28fv88YCBGJ7CgSOiHDxCZ3VLE7d+tozl9Q0AzF2ziivH7Mct821W1Pg8/4nNlMMNZAm+bG7irk/a2lZGwiiSghopZ+ULk9lz/HQMI0zCNZCQiAoZ2Qdfhrjkd8lA7HqC5nA50fOvQ8mwyjf3sMr3oAc9+P8cjuaiqSqy5yIhEELCVxUczSV61Xkgy/jxBN79T7fZD8s/h0OGYP/t8Ww/7W0K9ciDs047ZCLpj81FPXkszvQns8eQpbx2iCvnk21tg6LI2FU+6x9wUAolep+p0ffCEPjgNPjUPGfjNYktWt/e9tudWcNPG/FMXvujICpjRIP9kOZmn/c/chgzSiNQn9o60UlxaMdKtMNHg6chuzBvqYNhSBx3jIEsSQghsL31NKXX8sW6Rfxk1/H45yQpkAvxZIeQsj3r73Jw6z3UEp9zJpVxw+oq6pIuN+2xPY3/SVM8UmfjP+xcTqNMYCDVBCsX2+zxM51QVEIvkGjxbGITdNY6grMG66RcQaESp8CQaJIivLrw6uzcHDvsdsJGMS2pek44ZDaGUQ6Sj6akUNwwtu0jsPM6siG9KKfmvLukcJ3rz/2c82RJQ5IVPD/JgF2OYemnD1NV+3H2/NH7/pYfkvD4f1FOrgfdR3cd9+tM05xOQC43s71O3bfAEsA0TXN3YDVwWqavNaZppkzTHG5Z1iLgLOBFy7Ic0zTfIIjqP956PNPXC5nPN2e+f8OyrG1ab2dzGqhxFIrOnYCTSZd3ly5Dmzg+my7fmeU1jf/ArfSKFfH706bhuClUPYoqgTr4PCQtjHCSFIf6YDQW4M5chahNI5UZ6OeZ9D1Hwa2H2nk+1ffalFykYqgSrEtRPlrgJiSa33HodaKOViHjVAd17V6TILoXLLRsln8WrLhnnGGwIllPkaExqKyUM7bfg2TaZb2T5G/W+yyrb+Dfh40lXCTlLJ7hIglkidsWbp+J5pZy5RiDvkUpjH0KWPnCb3Oi560kde2h6zJp72uemt/GBnr0wdfCG4E8Ht0gEdmqIUFChXjjClSvlHDRzp3uYa8CGdVRWTctIA4sOUQDR8K3fbQ+EjVPOuw8UiMcK+KGoftRZOjUpWw+SdbycU0dE3bZmTv3HYQuwJYgFZJIu4LzD9QJqRIpV+B4giUbv2LvXqXUpQOjpjIS5uaD9uepVV9y7AEXsWHuhQgnjSYXUSjJSHEfZ/qneJnnrvCCPXCKHBKunncTxvVEGxGdB9uybEoPetCDHmwJ6LaKkraRGhJgyEF5W3EESdepFSpFCFTXw+0YhW1J5Dh47rwlqKeOw531AlJRLH/UtqgtQieVFOIqCkpHdZtf/AxBEPntSs89gkHVA8Gmv1sv2PCo0ykQ0HuSTnILOMiKImNrKp4I4gmGHO/EBF7Xsirv2llb5zP7pdwxjBzxw6VAbwnEUSiceDzug88iYlG0ceNwHl6DqF2LVGZwyDn9eO59mUcfb5PYO+EEn5ffCSLUiz/6K6P2+x2e8Ch2K6l/yqXiOBk1Eth9jS85XD+hLwKouiuYL6/FpuJUHaPIQZJ87LoUaoFMyTEGHy+waazyeefZNOEiicoJLqECGV32KdM1fM9BxUVPriUtilj+5cscffA/QDJApPl09Ux27TuMFP244w01YwvKXDZCoSJcja5XIEtKXkc2ZTd2cmg7OuWKAloouUlHvn2GhqKESKZrcqLvRwy5loUfTaOq9uMfxYH+X5WT+2/ANM1dgKstyzp3C/S1IzAN2ImAQ+4T4BLLsqpN07wO2mTpTNPsD7wCXGpZ1tPf5ne69QayLOsg0zT3BM4BFpum+SEww7KsOd39IcuyUqZpngM8DYQInO9W4rnTgRmmacYI0vH/mjl+EfCwaZpXA18BrVH/a4CHTNNcDjRkzt9m0R0NVNfzkfr0QmrH6tqiqITysLxCQObl1m+E+o0UJDzcpnpEicxGw+We5bdkI/DX7P93/JmrEbXB4iRq0zgzLLSf7Yz/zy/pc2Y/1r8oE1FktOYWnH8swi8MYYzdi9AhBdgNHkl0whUK5cfq+J5ApAUj99HZezeftz9x+Ly5kcuWLGV0ZW+u3XkwG6YFL/uSkjA3nbk/d677GEdzGHiCygdPu9kas70nGEx7185hLL9lfpobDg+RXPEylaMuy2p4fvP2veww4gpSRAKyOuGApOHKDrMX5LKBzn1nCscdMBnn9T/DNr5DmVZ85iyYzJFDr2fBsts4YvxdLJ+tZO/hfqfqyA0SniOyRlL9PIeSQ7SA/dWT8FqgICThSR6KJHPpgsVUJZJURsJMHXYAFY0O3v2LEHUJ9NIIkfOG8ydLZvHaNmOsIipx5oFFPP35av48YiiKJKFKEjM/XcHcNWs54YhR7DDid2ipCpzpK9F+tjPOP78MNot2iaIdUQm2i5oShNQaUkp5D0NqD3rQgx5sBorwwUuD5AAqSC54aRQRmHdxFIpiUaSSQiiMoh4yFCkSxpdAPe8EqGtCMnRE2kaUFCJfchoIkTeSTqZePRso8CRoxzYvNBWpJY533z+zjnw+PXe5C8LU7S4x8Pwg0p4knSUv3Vxgo8t7o8jUIHPFa1+zPu7QJ6px64i+jB/xV6JyXxAqyD6+0kzRCRofPO1k186BJxgseDeXGK8wJiHLWz8hqtDUgGegvDf2X1bk2HfKQys4+Ky9+Oe/g+sojEmknBqa4lWUFe7GgXudiyIA30MSKuUjUniPrsCrTSOXGZSf2Q8vLhBOO94cIdCkZpxpbyLqEkilEXpdeDBCF+w7xieVkPhyuUz5gXD9Jx9Sm05z96iDcGmk+Y2baVz9OrufeD+qHGaHHS7i2ldtquM2FVGZ34++iLDhcOPLIscW/PNCg8kHJdmuqBlV6Bx9wBTmvn1tjjP93opZHDf8DiQ/Sr5q2q4029vLw3VsM2HkX3n13VvypuXPf3/qt3agvws7fI+c3BbFTsBuW6ive4FHLMuaBWCa5pXAdGBC+0YZf/pF4KJv40e3ottbh5ZlfQr83jTNpwjq3Z+gG6HK9iL3lmX9B9g3T5sPCVjnOx5fA4zOc7wOOLa7Y9/a0V0NVEmWaPQkQAkijp5Hmnaf272YfFlBKumFiBWRUtOsXHoTvUZfxj0fTc1hmU8km4nU5u4oi9o0RFREbRpv/lr6nroj+Gmc+xdBYQjt6AE4j7+TfUEX/Hw41S8buC1QNi531/zQSQZrImn6lxZzct/d2PBAru5n8lG4+pKBCL+W/6y8g1GnTqElFaYuLajPWec4AAAgAElEQVTTRI5zCMELuz4JpXtPZM6CU9ui6Ptfi6zI6OlvWPGvtjr2nY+/K28KlRIpZfdxU0l52/YOpSd8muJVpOxG4ukaKPbY/9QIdhzshED3JKoeDLRV1RIJpVAK5uiJ3Hp3CgUJzeOqRe9QlQjq96oSScpdBe/+1xF1AcurqEvgzljE+DNHs3ht2ziq44IizWDumrXMXRN8cfeoYcxds5bKSJiG5i/YfacjcaauzHm+pF2iaOMrcR5fmn2e1LMGEOll0+xt25sqPdg24LvpbpPTuXaK+sZtOrmrB/9jkIQHaQfnyfey71Dt9ANAeMihJA4ODZJG7KKTkeubcWe9kK1zV48amduZ69GiaRQoIht9z9a4nzoOoWuoV/2iU6CgEQlV0ShybJyZ3bFl8hOmgk+zSOWkx3cnsNEVbE3NOu0A6+MOM5fV8vvdd+CdZ1ySjTbhIomfHCPxWe097HfaJBAKsiKB3sLAQT4ba4wsedthh6WRFR+2YgnSKF5240S78Jys094KUZsmFgrue2FM4tBDk7yx/E4Ko5Uk0/Uois4/5p9HU7yKXx/+Fu6juY6/9+gK1Ev6k6pXsnPYa5zAe/TNrJ1AYQipKYX72NtIdQkipRH2/vkw1muCKf32JIGPioSNQfGIK1BCxThGCNeLcdtrucGa216zuf5wg+p4Kuc6quMCVS3EFTa+H6NIL+OkkXeR9m0MrQAJiZH7/JKPvpjDoN1PJ5+7kk+zvaM8XMc2mhrOa1P2KurHSaMf/FYOdHc2DrrC95WT+yFge95BdenUVNf3K1VZrio1QpN1RXlr82duGqZpSsCtwPGAS+Agv0hAmF4KxAki12+bpvkQ8JplWQ9lzhWWZUmZiPd2wB4Ezvr9lmXdRBAo3tU0zWkEMue3E2hYfkIgeX64ZVkrTNOMAp8Be1iWlfswtqEP0F6m6i7ggA7X0o8gcH2hZVnPf5f70S3H3TTNCuBM4GyCC3qAQJKtB1sAsu93TmPrhgbqphDHCMi84jWsfOly7OYqpFARtYkqdinZmyP6nU1UL8IgjFRm5LzcpTIDEm7gVB1ShnPPfLQzhgQR1wkDs047BI6cc/8iik4YjU+bdjsEjnn9SzY7nBDhnoHDwJdwTvape9EhvcbPtpGdNGnV5vNv5jOg32+Y/O9ggb9yjJGfsTwt0KV4pyj6qWPuZ1WGfA4Cxnm7cW3eFCoj2gfbDl7uRYr/rXfytxZIkkxhtJKlnz7MEUOuRXcjvDOrjeRvzM/DuPWCluUufS8IBScJQZ+JOm491M9zqJ6VpvJSg7TvZ532VoQAry5Xbk/UJegTFrTniGxlkm9FZSRMk21TGQlz60H7EbJXYSfjKK3PWcJFKjPQjmhz2lv79h9Zhvbrg4kZNpKbQsgaCb9nN7kHPwxk1WDp3wZ3q+2QX75L1wqoAUaf8hyRWN+cY8XFGg0NPQ5/D7Y8JOFjP/Z27pr82NvovxrN1DcnZrPrLhryZ8oXLIeMraGMGgwtCdyn/53jnEd7GQhAGFoQtW2NxhsaPhKNonOgAAKHkeZ43hR7RZIoUEJIfqDLLlSXPqcK1s8KHL9If5nyYzWEH7RLYmej7d0NbOSDJ8g67a04ccdSPnrGzSGi++y5MDsePZJZC0/m5DEzQFJIpppQDZfRPxVoSiGO14RqSEiUf5dp+tGQY08mE3ntOz3qctYZKg0tq3lj+W3E0zUcM+x2wnohT752QdZeEr6f1/EXKZ/6eT69z9bx46CXpkm3sxO0Q3+C0+GZ9O5/k74n7Yc9fSFlpRFS5wzhyi8+ozad5taDLsUwHJKunF8qWCavLei6TdQ311EaC5H2eqGqLaRaNjJnYW4auyTltx02LQ+XX9e9Nf2+o00JeoaQrvt2Snc2DrYV2J530BdNjf+6YsmC8qpEnMpIdOdbh478166FRcduAef9RGA4sDegAQsJ5MavsCzrGdM0DwSeyjjFm8I+BM54MYEy2jTgUuA6y7IuNk1zNNAP2MmyrEbTNKcAZwB/BE4A5m7CaQe4Engsc95/CDYXnmz3/e7APODz7+q0Q/d13FcCA4ALLMvqb1nWnzNa7j3YAmglE2mP7migdoUgrcyHSAlUVGYdWZFqZN8+oxi/18X88+OpTH3jPB5deQvqBXsEzjrBS107czecl7/JdaoSNlJpBCJ6265qBqIugVogUCK5O+jGTjIlh2lINQrr7krz1U1JNv7DpvwYHWOn4NrUEgl0A0UOyDbSdg1Dt5e5coxBSVji+sNDDN0+aFsRlbhkuMG8lQ6p9IacMTTFq/CFl73WVmxcPIPjhv0pq7VZGK1k/PCpOBmnvVXv1L35vkDv1ElSoCeJak1E9eRWr4spSTJHDLmWSKgUCZCFnFOnJ0RgFBUO1lg3PcVXtyRZd28aPynRtNShbJyOUijhuYI1zS1URoLFon9JMbcfOAxFloJ5b/+bpREKwxIV0eDeVEQlfj9aY+6aVUCmtv3AQWwfdvnjfuUYoor3VjyOaoSyz5nz8jdoZ+4GMTXv8+Q01+A0rqbuuauofXwSEbtHo7QH2wYisb48+sh+Of80LfTfHlYP/lfhi7zvUHyRk11399LLSP9sGOpFJyPtVIlcGMtG1CFDQDfrBVTPQ3UcSNsQNqAgglReAmkb2e+8qa0qMkWKQPU9CIeQ+u+e873Uf3fceJgNdzmsvSnNhrscvCYdtcyl74mN7HiZR+nhKuum23x1U4oNdzmEEwZKRjBd9v28mwH5xtIRigR9ormZW710LS8RXVgrpyleRUuymkS6HkMvYN57t+KxHpQNeKxn3nu34npbLzEd5NqTzrw30M7aMce+U87fjaffu4QX374Aj/WMHHgpY4dci2YU4khw8KDJ9Cnbmz5le+PLZM9thVRm4DRl1mJPYuNTNqkqcu2ELuxEdDX7d+ihpfy+n0lVIskVb71Dk2egyCJrV7SiIiqhSoLLRqRzbI7fHuxSFJZ5a/kMIChpEAJeXjqFaKic40bcwZFDr8fzbOQuZGjzabZ3rFHv2Gbppw8zdsiUHJuyLT3+26E7uvLbCurSqamtTjtAVSLOFUsWlNelU1O3QPejgCcty0pbltUCjADKLct6BsCyrMVAHWBuog+A+ZZl2ZZlVWfaF+VpY1mW1Sq99SABHxsEgeuHNtW5ZVkvEUT1f05AsH478Ey7JhOA84Fi0zQv3cxYu0R3U+WPIZB9uyGTsqAAu1iWteN3/eEetCGOQqwjwUs7orlvg05pZecfhR4LnPeGpQ9z4pHX839vXpRd0D9Y/xpzojMZO/lcUqk0MTWE8/TXiNUtOU6V8+pnaKftD7aLVBrJeSlLpRHkAgWnJjf9reQQDT8OG5/KjcJveCxI3a6ZbVM+UaNZdylAZfzwqSxf8won7Tsgmy5VEZW4YozBKQMF1XF4/hObU/aV+PDTR3OuuzBaiSyp2WtthZOoJZxOc9yAySiRUvRQKSG5lMaUoEjxc3fyC6Ok0+tY+eJVmyW921og+bCxfhXDBpzPnIWTOfaAewgXlWcNk5VLHczxBuvuTuXMQfUTwRxUP5Gm14k6qxPNPPD5Cq7af1/+uXI1p+66N3cvEvQfLig+bf+c0gjttP0REtwwViNlxwnrBi9+diuX7Xspl+y9B7WJNcz+8DK+bAhYVssilZy77zUs/voRRlwwCXf654jVLTjzq9BP2iHv8+R5CVa9fh27D5tM3dO/pfaZyZSdNpPmbWwXugc96EEPflBkNlc7vkPpoJ9em6jCaW5C1mNw0lhA5HWIcVzs2x7IyMgdhzP3dcTyz4OI/MTjUdulqLe3N+xWTfhzjsOB7DnycUfxzd12rg0wM832v45BHwmJcIa1vP33Nr0v0Wkh1ZklnVwFnU1Bd1xuHb4dVyz6JlvjXhgSeYlwk04NhdFKHC/F84v/wMljZhBP1TBnYZvicWBnfLcsyB8LOfbkV1W4Cxeg//oIfEmipmUljrGSeDqoaZ+z8Lf0KduboQN/yfRFF2SzM84ZdC2K7zN37X0cc/4k/HtXZsmLlbP7sfF5n9IjdDb8PbDtav8j0ee0YXiPZ9Llu7ATSbRxBoi6BDuEIvQvKWZ5fQP1aZdCZR1XjNmOW+enc+y/j1ZMI2U3MuXQS0AOI4k0ETVNIuUSCZVS1/wl0VAvVKmYaKicEftczHsrZjFgl2OIGKV4IkUkquIJH89LZWvCu0Py1rFNPFVDNFTGyaMfxP+e9eX/S+zwru9XtjrtrahKxHF9v7KLU74NOu5k7EpnWXCJwKfNpoOaptnxRraPluemjbYhm3ZqWdaXpmmuMU1zAtDbsqwlXQ3QNM1S4BrLsn4DvAS8ZJrmDUCVaZq9Ms3+YlnW86ZprgEWmqb5eqZU/FuhuyHde4BFBLJrjwFNBCRz/5No3UEukbxgJ1n5bpHv7sL1fJojBUgXn4Z61S+QLj6tW/Vb+dApreyl99jjkJvRY5UZFnVydN0BXln1MBulr/lK/oLaSBLvpD5IN/SHEj27iyq+rMOZuwwRUtF+Pix7XCqNoJ43nJSm4UYDHXe1JPi/oBRIyHpuFB6ChVnvK5Oe6FBVkEDgU2fXUmj0YsBukzrVON06P03MkNilWHDeUJmScBMjB/2a3bYbBbTb8fRi7D5uKnoseE/osUr2GDcVw45RJPUl1qARTUeJO8H4Ou7kS4fty8p5V+Wk2n/+wuSA7G4rRUiOsvt2I5izMCDg+89H19B/vBcw8gN1X7WVJLSHW9+WIaH1krlz5TKW1zUwfdlnXDxgX+5eFBDBVMfBeX0l2oSB6JeORpswEOf1lSR9nwsXvE4SD1lqYEXtYlrSq0nZXzD9rUlZpx2C560g2odd+w5jYc1M/F/vgHpDf/wTy/hg43Oo5x2Y8zzJZw3AVVNBeUc4iBx4jVVI/ra3C92DHvSgBz8kXEVBO2tIzjtUO2sIrpLrYJZFKlGaUjgPz0FWFOgi0080BvrPor4J56E5qEMGZD+7Dz4bpMRnkC+N3XloDtpRI9F/eRrahSfjo+Zdf4QHjZ6E5+e3ESQ/WMPiBMz1rWNtDWzEu1FG6Hk+5fjcPXoHnjp6F6Yf0hdXrmLPY9PZNTKocU/y4VePctzwO5AlmaZ4FZ5vd4qsHjPkejTxw9qD3xeu55OIxVAvPhX9ql+gHv9TWnSJuCaQYzrvrHiMI4Zcm72uoQPO48H3rs3Jznjo/SlEI715ZdXDzKq+E++y3dCuH4Rz7l7EtRDFEwy0Cjk7b+mvBOtfMPBPGI1+9TiccBFqBztRO/0AnFc/y45TKo2wtkXibHMvKiNh6tNpFLWIonALN47VmX58iJvG6lREWvim5l122+UI7lpyBlP+M4y/LT6NBruGxZ88wKh9f8Vby2cwZ9FlCOExduh1vLdiFvv1O5X5709l1n8m8eT8C2hOriOeWs8LS67iydcm4hCIY2kEJG/njnuOk0Y/mNGHb8e94IlObSSvF3YqjJsuxEmFv3Ngp3VTYEtE7//bUGW5qjISzTlWGYmiynJVF6d8GywAJpimqZmmGSFIPxcZh5pMqnwfYBlQA/TPnDe+G327bDqIPZOgDv7RTbQBaASONU3zrHbHdgM2EET3IaMjaVnWMuAGYFbmer4Vvg053W2maZYTFOf/jMCR/5/D9yFC+T5wPT9Tr5W/fmxTaM+4Kvtgt99FX1OF8izsdc4D+MIlrkiURSpznPeySCX1ySqmL/ktV45+jM+FyjXvP0+5UcD/TTwG/cFMTXtTCmGo3Fu7joPPGUSFblAYNqjVJf6w5C0u2H0vdo5F6XtJoMcqZIG7vjMJjVoisTLRSKNms70aRZGgxU/T4jbhS9tR3aEmrTousJP12N4XzPhwCjG9nLF7/oYDBl7H8P0UwiTxfRtBHM/Ynn7Hz8yyyjtE0VQvYN4vlJGLY7i1LUBnvVMR1Tul2tvNVVu1ZFxSNJO0m7I7tlV1H/Py8ks49swZJNIOuqaQ8FJ558BLZOZG86nNSLgtr2ugIeVQHQ+Mmgctiat+2h8eaWOLTZ0zhG9wqEokuWrx+9wz6gAmDr4RRVLxfTfv89XUspaKwt3Ype8w/r74nJz6syajifAvD0D1FVL1q/jq3T+yw/BL0WOViGSmHrOoEiFr2QiLokhE5ASS7/TUwPeA0sIQirHtRSl60IPviyZFJRrW0U/aL0hFtl3ssE5cUbPv4rJIJRcOuJnwUx8G650Q+IaBNun4LJmcVFKIetpRuHNfy/Yt6puQIuGcz5rvoyoarud3yc+DquAWFRJHIYSfd/2RFMAN7IR837dquLcGNqJdKOhsDp7no+OgGs3UNK7iw1VPc8igy9nvNA2EgpAcEmIj++x2PIqiI7kZabHEehZ9fA8nj5mB76VxmzdQ985jlI68/LtN1I8EVZGJNjcHcnCZeY1OPB4vJpF+bQaj9j0GtWCH4LqEiyvJnYI5tYkqNMWgLFLJm1/P5s2vZ7NL8d5M2vsOQkoJaeHSaLs585b+SlA9W6L3xTp+ieCBr1Zz8DmD6BeNITXJ+KoLTUHAUyqNIJ87nPs+ljhrSCib6XfkLqXcuWwu1w8ax4vLb6I5XcOFQ6cycuCvmf7e1TmbC/cu/R1n9p+MJMkM2fNsln76ME2JKmRJYcAux/Dy0ik5teP/evNyDh18JUP2PJs5C3+brSUPHO/8JG/tGd9BQ7hFuJ7IafN98L/EDl9qhCbfOnRk+xp3bh06sqbUCE3+vn1blvWsaZr7A+8RBJz/AswHpmfqydPABOv/sXfe8VGV2f9/P7dMTWZIoYxYkOKIAgJKBwVFXUH62stacV3ssTfQFVER3V11RcHy1Z/uqgtSFiyrAiqiiIISy6WKAqGkTZJpd275/THJkAkDBEEJOu/Xa1/L3JZn7h3vc85zzvkcTdODweDTwGvBYPBrkvXke1o4+I5k6vrLJPXbGjITmMYeHHdN08xgMDgEeKw20h4BNgPDavc1POUx4Mza73LlHsaYRmMd97o381qgk6Zpi4PBYNPOF/qZ7IsQyoGg4UKDesWYndPKqsJguqk2BQ41zlU9J/PM0lsoi5RwXKuBDO90KwkrwT2nvg1Coaa6jAJXDisrNrG6YxzP5d3wSQqlRpxD8hx0U/IwZJXv9Sgfr1vFxcHOlMXjTF3zLX87qjebX4ilBGfyz1RpcZ4zTWk+52KJB1YXc2/Pbrz0/WrObtecKR9eRoEnwHV9XqOFV9pJhERRZJ76stZpP/Z+7l+2mpLITwQ8bu4/IchXX91NJFbKiH6PYaatmFro9RZEmtdLH9ypRCFm7pRq78gNNOmWcbYAp+pNS7eyBUSVCAnJYuGWlQzPPYEW54m0Z9DiXCeVHyZLFV7btJY7TziOB5d9RUkkStRM0MLrZFvYRiu1efB7J2MvGcghXovV4Wr+se57/tLlGCCpPG9YMKP4b1TFS7l5wPNc3esxnv7sprS0u8++eophfSbtNJm+s/Q+xpz4BBVsRTV11r97NY7cAFYiSrtTJlD9wRPI/gAFo6cQsZLpa7Is8OibKJtZhBkq2bHf0XRLGrL8sshOldhNj6Q+ux5r2sZ1liz7CyEgbntBKMjCxhSCuO1ECLitxzMkYhHkqhju/3wFG0qS9kFZJVIih5rc3FRLWSEJjDffx96wY/4TeT7seoKlIs+Hva2MXF8O1Z4cLDK3jTMkubYDjkVU1ml5mZOtz+tpPdrlHAFxiJJ5f/0e7nsb2HA4JJCrsWwDSSjIkhPDNFjyzTT6dxnHB8sfoftR56XmI583wIj+U3CrzYjFqxjRfwrLV71GOFZKvHwdP8y+PpnBd8YjIDVdewAgBzPltMOOTAn5mmGYNWUogGUZSJLKGwuu5o8nT9tpsf24VgMxhJu/9HuR7TU/8Pb3T1IVL6XcWo+RWEcLXxfcURn3eWq6XXGZg2tXLKGoW2d6B1oyftkKCpxOJrXrgfGehH/MQJQcG3Jkpq0SVEQtch0KLxWv56wOh/HP7+ZREg1x7/L53N1pLM99di1Pf1bETf2fzbi44HblUxpaQ/H6uZzR637AxrYtJEnNWDuuKm7UWgc9uV9HdbHL3u0/V/F9b2iK6vA/B4csL2nr8w+feuKp+11VHkDTtLuAuxpsHpjhuHWkK7nfULt9QoPj2tT72CnTNWtLwwcB72matrkRY9TYhXB7hr9v1157r2ms4/5ZMBh8jWT/9Hm1yn1Nv5nlz+CXUHj/JWm40GD875Od2rjIY8/CBvKEiWW5MB153NhvKkIobNdN/vbNAs5v34cJn71KSTREwO3nnm7D+ed3HyAkmUuWLUj9vWGHt+Ws9kFu+/RD6lbVRrXtwPieXVEjMqUv7KhVi3xjAQnyz1Jp8RcHtgUb42EeWPU1ZfE4WyJRvthexumtkxH2skgJM78Zzx2DHmLSgkSqxunWPlGEuZ2ySAmjOo+vddp3tCy7d5nG/V3G8c7Hf2b24ps4p5GKnDut5Ksy7YdMYc38orQa9ybdMs6GRV/9nWF9H2HuJ7ficRXSrfsEVldtp9CVw5kF3dn6hI7sExSOTArRyW6wHTYVp8W4d1UxxRWVHLu1Gbd068wRuTmoksR1AwT/+MhKtd+rdklcu/JLvqmoTCnGQ1KIrqRaY31FMjU+YcZwKl6uPuEhDEsnFg+x9KuniMRKMa3MQiy6EcXpyMGoXl9b3jAZ2dscqkspHD4RUzjSIuoeKZJy2iGZRp+tgc+SJcvvEU8Ctj6nY1RAXcmmkqfT8joH0ssLyDnjRIw3PtgRVT/nDIy3PoSqMK5x5xNGxislbR91xKC0+nT1khEk3k3a3cnPI0nM/B9UhfHWnttQn0e5dBS2AL9sp7q0RD1xWl7jSKnKR4njlpJpteYu9ps/M8PR5ZIwKSccLSMSL6d4/VxO7HItquImHCvl46+fomfHP+F1FXD2oGeTjp6QWL3xQ1rkdcDrKmB9yaccddgpdG07klxHPp0vnIltm2z7Zg6B486mKbeDky0LM1MWhOxEnHYt/1k2nqplJVw6ZAZV4RIUFC7tfl8qXf64VgM5uWMRV378fyl78JGeD4K+meItizm+zXnkJFS2PacT8elJu8IjsHSbhNekLB5nazTKy9oa/j6gNxVxHcNlEh9qYqte1lfbPPd5goqoxe2DHDiVOH/s0Ip/fjeP4spk+npJNITHkQck7ULTSlDgCZDrLOSUo8biceSRMML43C2JIXHScddTWfMTS75J6hKcNXBqxtrxhBFFkpTU5+2hVane6w0d8t+S4vuvhUOWl7TyePse6HHsRx4nqfF2Rt2GYDC4AMjLcOxUTdOm/hqDaqzjfiPQq7aX3Q3AYHYo7f2m2BchlANBw4UGe0MJxrxFqOPOw7JsLFVBVIdTfT0T14/EaqaCrKDbCrd9/ho3dj6dCV/OoiSaFFIsiYb46/I53Nj5dEJ6hIDHS53oxNwf19HB34wn+59CWTxKRTzOi1oxlwQ70caTQ0mFnja+yDcWYojOZiXCA8tWUBKJEvC4U6lR957Qgbe/uTd1/FdbFnBul3Lu6xVC8R+JIllsWzQJq+sfKfAEcKv5lETSFeVLIlEcjjbAjlXUxqa2p63k6yArrdNS7WNm005bsm2LtZsW4XY046yBU4kLF2M/eYUJ3UeiygrEk6lsRoXNlhd2RDC8twh0t5lKkS+Pxcl3OdETW7BkHy+vWc9FvdvR3OUmx6HwxMoVKaf97hO68s/i7wh43GnPr8ATYFv4JwAC3sOZufDq1Er1H3reh1Tbum6n1nyqF1ly4vS24vABRWxcOo3D+16L5M6l2vRjGumpacJKpJz2OnbUwGcn1CxZsvx+kMzMNeKSKZL2wFsfol51drJVWySK8daHqai6bFnkxqJppYHKpaNg9GDsihC2YaKeeRIMG4hVE8aKx9PONWyRtvgtYZOYvSDl+NcvM6yp04XKYEeZe9jfWGRZEDF+Smm+1JVjReMhQDB6wN+pimzB5fAjCYUFyx9l7aZFyfr1vo/w6bfTOa7dGPw5LcnPPQI1GkZ78+rUQn670x7AbuLidEgiow0blwURO8YZve4npodQZBejT/wHlqXTwtOaK7vdB0LgcLXm6iX/TrMHb136BtP6XUTfdu0wbBtbtzPaFb5bJe484TimFn9PeSzOxpowbkXm7s8/oriijE55Bdx//CBuPFFlddVmHih+l7J4Dbd1GZpy2gECbj8RvQJI2hWRaCljezxCpaly7/L5qQWFyT3P5tvvXmTtpoWpZ/3x10+xcMVjjOg/Je138Iee96Eq7qTDX+/YXTnkjWkVl+W3jaZpN1Absa+37WdFyfcnjXLca0P6n9b+ex7ws/vPNXX2p8L7r0GmhQaqwhgIQraE37R2pE2d0RcKm2HGy8AUWA43JdEQftWdeknXUbf91TWfMqnXYO747ONUhL1r8xbEzCgtXG6OFH56HRXAwMJQjIy1aj63AxwJ7ju+Ffmew7CtBGBS1LUjM74enyZkVuAJIGwTnyOBUf4ZstNPm/43UWVUcWn3+6gxky3L6vcbD3jc6HpS+8HnDSDtQ2aEadqED6K0JVko+LwBitfPBqBTp2spiYYIJaK4ZJW4SKQ9E+cREvmnqaBAVSzBPSd0RZYkmrucxM0qMONIdhWXH9Oe25d8SUkkyomBllzT5WguO7oVulGFzFZu7nIoee4CZn49gR8qV1LgCXBxt/HM+vYpRne6DoTEmB4Tkdx+hJAwq7dS9tnzjOg3hdmLd0ymw/o+wldr36RT8z6sf3Pcji/W73ps7IyLJrakIvsDac57wxr4LFmyZPk9YMmZa8Qt2UbK82FvKMGqCSPiOsLjRjm5F8YHn0FVOJkenyGtWrrmfGSHSuKFWSk7SL1kBInFy4H0YEbd4rdfljCfenWfywxlWcJN/ei73ujoezJKWrRTOVayN7sgFq/kvS8mpTn1kVg5JWUrmfvJrQzqVoSquHGKHBV7eH0AACAASURBVGQhs3r+zWlitWvfvZuOY6Y3+rscCAxZ3jnr8pIRVOrbU9+9XeuT6Os9JO1eDOv7CEIITKHsZA8WuHKoSOjcuvQ1JnQfSSSWwJXnw6iwk21/T1aRcwTCCe+u3UR5LM5DfXoQM+P8Y+UyiiuS3aPL4jEMEWVbrIKiZS+lrn9YTj4Btz/lkD/QfRjziu9PdqTpfj8uyUmNYXPvivlpCwq3LH2diceMYe2mhalnPahbEbM/vpmTu9/KaT3uIdfTEoFETXQrH3z5CEN7T2RQtyI+/vopSsqStmcmh/y3pPie5bdFo8Xpfi/sqxDKr82eFhoky8LweUlcOhjD78Ayw8xefDNeVyEn95lMwO0nYZmpl2YdAbefwzwF3HrUMEzD5tmep1EuapIOvUNh/o/fcHZOb0qfNzAqjNradZtmV0pUTiNV81R4mcp2qZxF3z3DgBZjyJdUSmvW89Hqx/G48xnW+So2VmmpeuixXe/DLZzops4PCx9Cry6hzYi/M+urSXhchfTtcg0P9enG7UuWp6L3dTXuPm+A0X2nEJdySbhsVCFQTUFC3/Wzk2WRVI0/SCLsDXGZHkb2f4xZH99EadU6HELh//W6mpaOZsgyvFW2gqGXdWP784lkuvxoFasGpCrBoboXQzGJeS0M28St+hCKG8OOkydFePqkXuiWgUOSsc0yXlp2Teo5/bnXFFySzoAjRzO4wwWE9RCzvn2KqngpcSOKjGDD23fvpBfQsss5nD1wKuFYMo3x02+n06vDBWz78Im047AtxC7SESOWh4LRU3aucbeacElDlixZsvwCxF06LS931KbL19aIX+4g7tLxjDsfWYCIRDFembcjnf28Idi5XmwhMraEk00r5bTXbUu8OBtl5MkYq3/MGMz4OWWGDZ10XTZwVKsN6t2dRD2NS53fZZQUG2HD7MU37+TU1zl6Xmchrbw9sW0JWZaQqUH1FHD4gCIUlw8jVkXJFy9iW8Yex3EgCZuC3FwvyphTEU4Hdlwn6hfMXrRjQaPTkcNS0WgAr7OQRETQzNMGYcoMbBlk4VYteWxea8Z3G0FIj3JX12G0dPuZUbKMyy8bSOhtg2YnJtvKyj5B/mkqt7TpgtHBJKzGKU8olMWTmRQBj5dJvfqTsHT++d37qfEG3H5kIXFbl6G4FZWokSDXkcvYHg9RXrWWJSv+gdeVT89ud2cMMDmcO7KWq8IluBx+fN4AhhHl3c//msHxVliwfMoeHfLGtIrLkuVAkHXcM7AvCu+/BvVV5C1sIvUEZhouNFiqTNUfj2PWl9fjdRXyh14TqAqX4HUVYsW2Mrnn2UQNg3u7jeD+5bNTK55/73UBSpWLr2ckiIbA7Ycjh7uZv+kDjsw9hbNa9KT0SSOt92rNS4KCayS4soZWSi6SKmHLFl5d4ayWt7HtBYPNFTZK3lEMvfAx5q25CZ/q59qOd2A73Ag9it/ZkoQdJy4LAifdROnn/4dQ3VSFS6gKlzBzwVW0KujM/V3Gke87Aaes4DRDHNbzfmTJQYnh4rZFn6ac+of7dKeFw0lCt1BkCbuqJlnrL0lEZRk5vpFVc4oOmr7tDYkgUyAdwgV9p4OzAKNKZssMhfWhBG6/4NQx3ZhXs5zB4zqRo6gY2wTb/1NPTOY8J2WEOX/xIgIeN/f06MyraxdwxdEDKJCq+W/xZL7asogj8zpzVucicp355LlaUBOvwLIM/K5Cpn5WlHLo/9T9PnzOAmq+fYu2p97Huv+NT93btoMnYFsGLpzY4Rpy8ttzSrc7UPQatkWSK/J1AkC2ZWIrmR1307SJOFpTcP7zWVX5LFmy/K6xsdmaEyV8iUGupFJt6WzNMfEjETIFftnGfr5BVP1f85HGnY9tkzGtGimzQy8CzZPtajMEM/a2zNC2bNyRdFG6Vpc5KX+7Yc/3HT3dMyHLEg7hAFsgbCftWw9izaYdujw+bwBsG3MXTr3L4SeQ35lTO/6NL1+ViIZs3H6Lbn9sRps/PEQ8spV4pJzy7//LYX2vRchNt74datvBudx4Wylg2SAJDFGT9t1dDn/qcyC/M4OPfozv57hrv7vJnWNGAzMp1WsY1/EUrlvyCoXOHK5vdwY+NZeLDzuJFzes4sIRHdj2dNJpLxiSdOB3CNU5+VfFEq7vciz5Ti/5Ti9OSZCwTQocSX2DZP38OTy+8m0WbV2VGl/A7WdK18Hke1tz0nHXJWvTyRxg0uMVqc91dewj+j3K1+tmc3rP8WkChCP7T8FrexnZfwqz6qXRZ3LIf0uK71l+W2Qd94OMTO3qPHV1ZLbYaaEhKkWZ9eUdeF2F9O8yjlDNJtq1PonuR53HvCW3c1iLXnQ+dhz3fPkmN3Y+nTY5hQggHrZrnfbkSyoaslk/R+b280cw6ZtZTGg/BqMifTY2Kmxq4jHOWvoknZu15v5257J2tsSxJ/vY9kb6ZFz5/9wM/NNtSLYgr1lbbDOB8DioiG5h7kd3p16oZw4YD2YiLWVpS9lKIsvvY0SnInLy2vP9rL+gV5dwxEVvc9uSL9KE625b8iXPntg7dd/0epkJ7mtGsn7pM2kr6puWPsNhA26vTZdv+sR1E68KZryAeIXEt+/E057Z1zMSnHFRN8pFiJzEDnV/SD6Hbf+K0/IvyTaSJZEof/18Jdd1PYFbl77BfV36MfTosQB8tWURb6ycwtiej7Bg7Wv0OvwMjNCP/HfDv7iw2z3kuVoiSRLVsXI8sof1386i6oePaDv4Phw5LQCbePVWSpY9T5sTbyHH3wbLchA2PAjVS8fR07AtAyHJmNEqJGQihpNdrWybpl0rROeu/c1nJ9MsTRfTjNO8eW7atkQiRmVlYhdnZMnSOOIW3Lj4s53Kx54e2AeZXUfChWVRI6kZM/YMWd6jWnxD9rbM0KyxU047JOejLc/HKRzpIPJNPUX5ej3dGyLLErLu5IsZeq3TKRg0ZhJwB2s2LUipxccTYeJGdcbU55geYkDH2/hujjNt7lz+H50Owyp4f+FleL0B+vcZT8nyV2lzELSD8zRoB6dcNyLtu8f0UOpz3+CNfD/X3cBuMLjzvKGEHVH+8smrFDpzmND2HNbPllkciuP2C4YNb0skkQzeFI7c4bRDrW3xfIIBfwoy9vMXgKSTfWPn03l85Ts83PNsbu4yBN0ycEkqZXo47TuURENYQgIg190CISmYZpyJ3YZwV8Ma95WPAslnObzfZNzOPL5dP492hwzgi1WvMKhbER5nPl5XAe4VWyg/ch2L179Yb3shwspDz5CZ+VtRfM/y2yLruB9k7G27Oqt2lfkPPcdjmDoeVz4Du97EwhWPc3KfR3G5WiIJQVmshluXvs4z/f4EgN/2pV7kdURDNrphsWjrKn44ZDs5eXlpdXXeYyV8spNZ3cbhc3lYvUgQDVk4XJnFc1p521G+eiZ5R/YjWr4OQ1WZ+9WktFS2/y67jzHdxzOyz6PEojYO2YduVuFy2VQsfQ7nsaNT6dimpKYZL5B0RhO2jR9rx307IoB+2nFYcoJWA65jy8f/ILRuUTLifsbDSHITF59pQAIXy99McPxZDnqPcSCT9GVXLTPY9LUJlqDKihGwyPgc6ttUJZEoftVDSTSEqnh5ZunNFPWfxoiOf0aWVCxTZ+CRY8jBxYblz3LG8ecxbfl9O3oF95yMw7I4fEARjpwWKE4fGz5+nND6RbWK8Y8SencysdWLdqS405oEuXikCBgJJGd+NoKe5TeFLDt5+aXuadsuuvhLIOu4Z9k3DMumZ2Eh17TpiNOWiAuLJ3/4DsOyky7zbiLhuyoNxGSvtX72tszQNjLPR3JOuh1Tv6c7pPfWdtjNWVbrtEPSRlkxw+DUCycxsOs2hJBRZTdRvRzIYUjvB5j/6Y7AwIj+U3A7/Mh6Ad+G0v9bjIZsVNkHQDhcwsdL7mNAtyJsq2kLqWSyEdUZSxg58jFm1aZ9F6+fy4h+jzJ78c241cKMtp5DcaNYTv7Z9VJayh7MMOQMtNGWGoRKbNbPgePOVojnGciezDZevpKT+lxfT+m2pa/zZN+LGPP+kwTcfh7qcRYz1i9jzk8rgKSTbxphJFcO8UQYG4v3v3iY/l2uYWqfczFtCEe3UCjidOtwNicedy0CiUisHMmpcPThZ+B0eDi56x1YdgJVKKhvLEbv055Zy++gKlzC2k2LgKTDf/bAF8gKzmU5WMg67gcZe1tHJoRKu9Yn4VBzeHvpLVSFS7jkjBm073g1N32Z7Jl5UsujeLjH2dz2+euEElEcQkE2o7j9rrQXutsvcCgSnfJa89j6t3jq8ktSdXXeYyWaD5ZJPFJJXqmJKKzhmCubEa+x0WOZxXMkGVy+VsQrf0R152EKM2Mqm+RqhqK34bs5Ru2qej5dhhsc1uc61r83PnWsbOkZhetUIZAsM3nfjghQNaZL8uX9VW1U/4TxGOEywluLWfPWbRw9cioOhyvjCmxTQ5ElLFuQf4SEK2KTeLICs9REFMp0vCYP1QXrarZyxRfP8e8ef0HJ8+70HDbGd6x2BzxuQolIStW1LFKCbVv45BwSeg2q08eP8+8glN+WQ3tcycbPpzHu2CIkTz5OVx4uS2LzZ89SvfFz2p56H1tW/Y8j+l2P1f1SrFgIOR4ltjo5Yaa1cUu4sxH0LFmyZNlLcmSFm1scg/FIJUapiVIoc/M1xxCWLRIk9hgJ31Vp4M/R+tmbMkOhkNEukH07tjfs6d6wt/bFJ80jGvKlXTcasrFNiYTuB5I9ZhyOljicEYSwOWfQtNpe3wqy5MAwEyAl7ZuG9k5cL019DodLkD35CKlpL+xntBGL15A/6hTOHTSdmvBm9HiINd+9zvBeE8l1NcftN9O+e4sOEkZEsPYjk2O6uDGmVWCXmrgLZbpd2YzlnySd92rbwH2RwIpmtvHKjZrU54DbTyhRmw0ZDWHaVurft3/+Bk/0vZB1Ndspi9UwsdsQWjhU9EQERXaiyk7CsVLeWHBV6no+byClT1Cfy4fMxYj7yPPlsr26GnCTK0yM4jVYpx6TVYrPkkYwGDwSuFvTtMv30/VOBsYDrUg6ZSuAGzRN2xgMBtsAq4Bvaw+XAB/wf5qmjc9wuYxI+2OgWX496lbP65OqI8t0fMLDoK5FzFmcdNoDBZ0xFR931TrtAIu2ruI5bRFT+/2JVi4/rdx+VI+g82gFtz+5+u32C44cbvKQNpuLO/SjNF7DBs92Cq9VCNylUjBKJvFkJXZpcjXaLjWxp1US7Kmw+tMEBec7UfLqeswKWl2mYivVeArasWnpNBR3HnYimqxHq4fPG8ChHMaKmUZ6KtccBSEHSNTWRgNUL5vKw727EfAkX8B1Ne6qKVL3LXHaccxafudOUf3CHslMA726hESkFBc1HAzkYCIJi2APhcSTFWn3P/FkBe26Kfx97VsATFw9G9+fSHsOLS5z8MKPSRGauhr3eT8uY0K3P/D+qmcp8ASQLBO7agtypArVtElEyij7bg4/LHyIQ7pdTEGzDuS7WuCxHRAP0/qEyzh61FQcOYdQ2PoEKubcS8WsO1Dd+VR+8Le08e9o4/brIcuCXDWKT67CrClDlnfOVKl/TK4azXhMlixZshxocqIKRoO513iykpxoMi5TFwkX485HuXNsska9tkXb7jBMi5ApqLCT6fH7W6BXzkk65fXno5aXOYiqOi2vUTn0Lictr1HThOkkNZISCwMI61tTNkodbr8Akb7wq+sWsYiLaNiNHs0lEfMTj3iJ1KjoUQ9xM0HXMY40e+fY4XFWfvt46hpebwCHKw9E0zabd2kj2gIsmU8/vpePFt7MurWzMc0EJcZW2o2w0r77Uac4WDEjTptjZOxpme06t1+wNRrl8c0rsVqbtLws3cZrfpnKqyWfAEmn/Z5uw3lp9eLU523RHYsLJdEQlfEIE48fzdQ+53KEpxmrf3qfl989nxkfXoMkZEb2m5KyD+tU8IvXz037nrtSfa+7J1KNntHGzCrF7x900+yzJRL5ZGNNeP2WSOQT3TT7HOgxNYIjgHb740LBYHAA8P+A2zRNC2qa1h5YALxZ77DNmqZ1rf1fF6AvcHMwGOzY2L+TjbgfZOx1HZlpI1SRmuh6dvwTNfHQTuqci7auYtyxg7nt89cpcOVwU6fTSfijeIaFOFTNoTxRw4R177KychMXdujLhO4jeXjlPG7vMpQLFz/L3OOvxVeankJml5q4PIJQicXq5TrHjnMisECYWPJ24qGkaFkiUsbmL16kVbcLOLPHffz38/E7xET6PYqwFKKh9P7w0ZCNbUl0GPooq+clW7bUbFzKUT0uZ9qJvUjYoNRTlQ/LyftmidBOK64eVyF24TG0OOtlJD2MaRrYdtNWjq1DtiwkEQPhwchw/zFtVtb2R11ZuYmbf3iVJ669GGEKTMlicfg7rut6DNcedwxgIguTC9q04+1vJlEdL2Vst/tRY2HW/m88hw8oYsNHU+gwZDKr599CeGsxa9+9mw5DJqOqORCphJpSqlbOJW/Q9VQseIyczsPIO+VGZG8BtpAww2Xp4/+ZbdxkWeCRInstTifLAo++aWdFescOQcLGHJPl4Mcw4/S89guA1P8DRKs3s/LFYQdqWFmy7BXCIOVY1WGXmggD6qrnmqLgrpAEUU+cltfUb/0Wx9QtdGrn3wbzQkPV+E+0xxk87LFUjbbbL+g6xoFux9kbTNMCR5zjz0+K3MmyiW6HiMaSEXevN8BJJz3C1mUv0rrH5TTl6OzubETb8HDSwMdYtPAmwuESpJzDuWnJvyh05nD1sNPomtOKVTVbsESAaMjG6RIZf1suj+C4MQ62OMKcfmQ+1614mWuOOQXnJQ5yZTflRg0vb1vOue17c0Pn07Ftm78Vv0NxxSYCbj/3HT+Kf3zzv9Q1A24/5XoYl1XDok9vYWjviSwu/ieQDK4YZpyKJc8yolMRSk5LZJeP5Wv+Q/ejzmN75ao9qr7X3RPHu4sZedqDqeBNVil+/6GbZp91VdVz7liyrLBWHLrNpD4nzGnryx3ukOUl+3LtYDAogIeAUYABPAO8BTwL5ANh4DpN0z4PBoMvAgs1TXux9lxb0zQRDAYnAK2BDiSd9emapk0E/gG0DQaDTwFvAI+QjJR/CwwATtM0bVUwGPQC3wMdNE3LrJQJ9wAPaJr2ad0GTdOeCgaD7mAw6NzFOQGSb+rqxt6PrON+kPFz2tUJdvSjdDn8VEZKMqpzSkLiyb4X8VNNOY8Vv8PE48fw1+9n7nRcc1cud30xg7JYDbmqi055rdmaqMZf6E57yYtCGdsbp9/VKpJkYontJKo2su69CSml8XanT6TDsL+xeu4NxMrXcVj/Gzhv0DRMK0GiqoTyJdPI6fvXjGls0bJvKP3+JY4e+TREE0geL/aib8ltX4Cd60LK8RGVclP3LZKbiyyRJtLSqqAzx3W9i7FL/p0SPHmk2zDayK6Do/xUEoANcu39bnD/46QvQJTGa1gR34BuGzy+8h2e6Hshj62cy7XHDOSZJVdwa//naZN7KFd0vw+zeguhz18hcfQw9OoS3AXtaN5xGLLiouPo6ZiWiSwkymfdTmJzcdrfMXtfTGz1ImKrF+E4pBPNBl5L1eevUjDkXsrm379Pbdz2xbH2SJHUedAgXb9WkLAxx2Q5+FFkJ4/+u/tO228+98sDMJosWX4elpL53W8p7PWC6K+NaVo71OIbMdaGvbVLyleyZMODnHrhJGxTAmGj241rHZdpLNHasXjlKE7h5MQT7kBS3ZixEFs+eIREpAzR66o9XOnAUt9GdAhI2KTZiLLcmsGnvgAkqK7t2V4SDfGX5S/wSM+zefz7d5h+wpXJUoGYjTvDb8v0GmyQSrnio+dT2xVJ5tLl6T3u5/y0gun9L0UREme17clFHfrRzOmlRo9SFktmNQbcfib1OIsXtA+57Ij2/KHnfSxcsSPTwecNoFf+SGjdIkLrkmV2/rYncfyAGxCyyrm1pQ8IB6aeeQE/dU9GDiZf2Jw/8HkMTEDJKsXvJ8rj8Sl1Tjsk9ZLuWLKs8OmBfae08nj67uPl/wj0AzoDKvAxMA64XdO0mcFgsDfwn2AweNQertOFpDPeDFhb66xfB0zQNG1cMBgcCBwFHKFpWigYDN4HXAjcC4wB/rsbpx2gN3BTw42apj0KEAwGAQ4JBoMrABdQCHwOjNI0beOeb0OSpp3zkyUje5vCVtePsk5Bdc36GUzsPpSAO1kDFnD7ebjH2TxR/C5j3n+Sh7+ex21dhqJKCvd2G5F23L3dRrApUklZrIZ7ug2nOhHj4g79+PuP/yPyZyeiMFn/JQpl1Gv9CLeKJCQkoZCo2Zpy2iGZlr72nbuQZSeHDyii3ekTcea0YvPCR1n1f6NZ/+Y4QusW8dPi8XQbo6alcnU+M8qWL/9GaP0ivp91NcLpQKqyMLrk893SO/l61nl8O/sKlPhGclw6XrUKJ9WoC79lZLcHU+lS3Ttdk1IphWTK1q3L5xKSDo41LUOWQZJI2FtQr/Gn3X/HtXngVJh+/BV0btY69fzynV5eWr2YkmiIKj3Goq2riJtRrjxuPJvm3cqGN65E3r6eLf97gFZdzqXkixdx5AawLYMfP5qCkFRidi4SKpINVoYouhWu16Kl9yWUzZtAbPUiKhc9Rd4pRbS46DlaXDD9Z0Wxd+VYe6TIHs8VViJ1Xh0N0/Ubc0yWLFmyNAWiHh31mrz0ufeaPKIefQ9nHnzUt2Ug6dT1OXYscVMnakaJGrHdOu2yLOFWXLhlN27FhSxnNoFjpgcbE7e7gB/fHc/6ebeQiJTRYchkkJp+WnWdjSjyfDvZiKZpE4+7icd9KCgp+65zs9a0sPN46YS/EDF0up6j8sO3JuLKZmm/rdjVLjYqlSiSlGYbNnN6Up/rqIuk37HsP0RMnSs+foGyWDWPFr/NjZ1P55l+f+LGzqejCIkrgwMIqD68zmaEazMd6rIut386Le26oXWLcFgCtTqOy5QxE83Qo+7G2RKmjSPhxk74ScQaeU6WPWJYdiCTOLRh2YFdnLI3nAS8rmlaXNO0GqA/UKhp2kyA2gh3ORDcw3UWaJqma5q2rfZ4f4ZjNE3T6qKVLwDn1/77T8CLjRirDRAMBh3BYHBF7f9+DAaDdYsXmzVN6wocA7wMOIAPGnHdFAeHd5Jln6jrR3nOwBcQkoXPewifFD/N1D63YiKjyCpTvn4r1UezJBri1qWv8cKAyyhwermty1DcikrUSNDM4SVhGdzY+XReW/sZQ4/oil91s7JyEw8532LC7UNIhCvRqUJxOFn5kko0ZCRT2EYfjeopTDnukHTe6xzCjqOnoddsJbR+Udr4Q+sXcMSACnqc7wVUomXfUvLZ3whvXbnjGjJYXlg95660hYHV84sIDn8CI1qOnojiOP4QfB+t5bwuk7ByHNR48imJzk/7eyXREIZl4TgI1rViSLikGr7/75/xHdqLw++4HWEJLOCrhQm2rbZw+/N4bMwlRHPDbI2GqDHiqZS10ng1AbefXMlJ+YdPEd6ajJx7CtrTZuDtbFzyFIlIGUeeci+2odNhyBR0OQ9neCNlM4uQvQUUDJ1A2bwJqeh34aiHCS1+LjVGye1LOcL65mJKZybFZFpeNWevJ01ZFsi2vhvHevcRcVtSkf2BtPMbpus35pgsWbJkaQrEbINwgU7BHXlIpsCSbbY7wsi2hMjQaWZPKLKEFxOpNqMv3AhRuv1xbmPYl97amVrHdR3jBMfOEXrTtBFOJ7LiTrUqRZKxTAPbSpC0tQ9+VF1hcs9zmP79Iq5tPZT1b8r8FErg9jtpNgaCf5AwLYHzznwwbWJSgnXmVp4sfh+A27oM5YicfExg1vpl3NNtOH9dPieVvTipx1k8uvKtlKJ8wO0naiQortjErUtfB5LO/dRe51L+7l2s3lqMt2UnRva+A2feEcQrNuBzFLA5kh4ccOQGEJsrsKe/jXLnWEx7988/Uxvl3Lo2yvtZu+H3iiKJkoDH3aahOLQiiZLdnNZYGkZN2sJOLzdB0qe16/YFg8GGq2z1o+Wp4xqQ+gKapv0QDAY3BIPB0UBLTdM+28M4PyeZGfCNpmk60LV2HAtp8NLQNM0KBoO3kBSvuxmYtIdrp2j6nkmW/YJA4E648ERd5CmHcWrX28gVAqdRRiRWnnLa6yiJhogZcVoJQbvcQlq4fRyRU8DU797n4g+n8fjKdzinXS/mbVhBKBEl4PZzcfvjeXP5tUxfMpIwUVbOVNPbtMw0CfRI74GarHEvp/0ZD2PbJoloBY7cwE7HiO3lSO8uQpbL+Onju1NOe2q/kLHC1WmLApB03o1YiO9njuWHhQ9hWNWIHu1Rp72N8/E5OELRjKvEchMXoKnDhYVtJtCrSyj9bhbfv38FEYfFJ6/rbFudnJCiIZuvZuhsLAtx5eIXkIUg4PYzoftI5m1YwcPHDaHsnTtTTrsjN4Besw3LTHBYv+s4fEARW776N4rLT1xpjWqGUxFvfXMxlQufIP+02wmMnUH+GfdgCxl//7HI/uRztPVo6t91pBzhvaAuRd4o++FnXy9ieSgYPSV1fnq6fuOPyZIlS5amQMIyuXP5f1isr+FraSOL9TXcufw/JH5G27I6B8d+6lWMB5/FfupVciM1KLuITO+vc/cG07RJxNwYcd9eRUwdwsGKnVrH6ThEZidcAHroR76beSVfvzyS72eOxYiWNXlV+b3BNC2aWz7GHzOG9XPktHvz1YwE28q/4+m3ehFSfmKLq4JBH0/mz0teorhiE8UVm7jhs1eJ6yEsy+TEQ47mtbWfcWPn05ne/1Ke6HshM9cvSwUJokaCCd1H0szhTovUT+7xR3Jj5Ri1znkiUoZLckHlFn6YfT1mNETbwRNSdqEjN0CHgROx//cVIs+HuQth5vrsso1ydiV+v5HvdBZN6nNCaX1x6El9TijNdzqL9sPlPwRGB4NBNRgM3DzV8gAAIABJREFUeoDXAbvWoaY2Vb4VUAyUAsfWnjeyEdc22H0Q+3mSdfAvN+Ja44F7g8Fgr7oNwWCwC8mFhp1+bJqmGSSd9juDwWCrRlwf9jDYLL8RUquN7yxG9OyEkuNByfVSozpRbC85zkTGmneHJPPjggcIrV+Er+1AWg68hxs6nc5FHfpRrod5be1nXHn0Sfgsk2d7n8OSryazpSzpUO+qN6jTd2TSMaytce8w5FGMeDWKqxnx0Ea2fzeXI0+5l/Xv37/jmDMmY//7c0RVGHnIgJQ4Wv39su3BrN6eunYdjtwAiWgybVuvLmHdexPoOGIqAKJTezxem4ePG8JtX81PrRJP7nkODl3BbAICPntCMU0Mi9T3jmwtRrJExnt/qJpDwJ3sGvBk34tQhcQtx56CJ1LK2tpJ05EboMPQKWCZrHtv/A4tgpPvBVtKRiJITyXXNxez/Y3rCfx5NpL/UGyHB8mM0+K8qSDJCIeXgtFTdq5J38va9roUedlb8LNr5U3TJuJoTcH5zyOsBIrDRUh3phl/DY/ZG/G7LFmyZPk1UYWgLFaTimBCcv5Wxd5H23fp4Iw7v1bc7pc591fBzjwvYu9ibJbFunfvScvgW/fuPXQc81zm4w9SBCAZme+NWy3E5w0gC4Wqmg0Z7USX4mLld1Pp0HYMRZ1Px7QsEBJ/K36HRVtXpWwqv+rk0ZXvUKaHua3LUA7z5iGqNmIUz0A+5kzaDLwdSXVjJaIIxcVPH07GkRsgXrWRki9eTNptQkBNHHvGYkRVGOXSUVTtQpi5PnvbRjnL3uOQ5SVtfbnDnx7Yd4ph2QFFEiX5TmfRvgrTAWia9mYwGDwB+JJkwPnvJNXap9bWoceB0Zqm6cFg8GngtWAw+DXJFPQ9Rfy/A5oFg8GXgUz/cc8EptEIx13TtI+DweA5wAPBYLBl7VjLgCJN0z6qbQfX8Jy3g8Hgp8ADwBV7+huQddx/F3gxMd9ZjDLgeIzX3kopjXovHUWVJwc17mByz3O4ZelrKef10eNGk2co+Npegt1pLCKiY0+fixtwXT6M5k4vbVsdQfW7d/BTbXpT75OuY3ulRlW4BN2swu3P30lQTlJljh7xT2zbRK/Zxg8LJyVTsU++hy1fv8ahPa5g4+fTOXxAEao7D9VTiCL5kIbnYtdEsCtrcKoFdBz2NLawEbZATjhheyV8uoYOZ05h9fyilMN55Cn3snHJU6kx6NUl2BLJ9Co1zuo3L0fxFPBEz6vA1QyhhymUnYQTTd9pB8C2kaMSHQZOZPXCZJmAQM8o5ldjRnm4xx+JxyuIxsto6SnEK7zYnpYcNep5sBMgVCQhU/XuRNr3LUK4fdjRKiJL/406+Pbkn9xFKrkpHMQlL67qH9n25i07UudHTybhPXyfHeG62nMzVJKqlZfcPmTfIVRbuY2+nmnaqZ7xzXNyMbfvLOZZ/5hsX/ksWbI0VXy2yeSeZ3PL0tfrLT6fjc82a7vNNJ59cXCavHMk7IzzYsPWcXXYViJjBp/9G9M68co2VsLIeG90s4phPR/AaUJLVCb3+CO3fP6fHb+z7iPxAX2OuQxJyIjwFsxYNcKRw63HDOLGYwahSjLb5t9MpbeQW/rdhG7Ecbl8OKo2IkkyyrHDEQ4vbocX29SJVf7Ijx9OTpXo1ZXrUVKOmn8IticH+4JhWJJEVSNLMerawdn1fp+pNsrZoPt+wyHLS/aDEF1GNE27C7irweaBGY5bB/Sot+mG2u0TGhzXpt7HTpmuWatmPwh4T9O0zY0c52Lg1F3s+wFok2F7xuN3RdZx/w0jywKHHMEggTSiJ8acpWmr4UbdargpaI6PaX0vxcJCRZBrKtimBTM+gYqqlNsi8nz4dAlD1lm18MHUxBbeWoyy7BXO6z8VKxJFaZaPf4TFitnSjnqy4Qai5gcSRg1rP7g/LeoO0LzjMLavepcj+t4AsQSSw4VseTHe/hhxQieMWR+Az4s8ejBKuY5wOrDjOrZXwVz0BfLp/Yg5c1JOqCTJbPjwkVQKOCQjyhYOKmwZr22gV5ckI9Vzr00dU3jRHJLClQcBQkB1BOXTtXQc+BhWYQ62qKHraD8rZlqpe3/caAXLn4PDjmOYNoWO1mD7qY7Vn/SSKU6yLPD1v2qXEfK6VPJM+3Pl6pTTDsna89KZt9DigulUJrzsiyNcf8GgrlZe9gcoOP/5XzQa/nNbz2X57TPw3Ll4cg850MPI8jtGskxy1i9iWt8LUzmfxur/IbU/Za+vtS8OTlN3jnRbp+sYZypdfk+t44SQMmbwiYOkjK4hdfZgslxYRTeT85himiTmvEu3UWey/E2j3r1RUbz5KEJCmBauhMmhoprpPc9C16PIkQr8NaUII0b5uw/hH1zEmk+m7HS/Dh9QhBEp47A+49jy8RQO6zEW+YOV0L4AO9eJ5HAi1QBCJezKxZHnot1pfyVW+WPKae8wcCJ8sAaGH0YVCoZt7VVbw71to5wlSy2PA8OAM+o2BIPBBUBehmOnapo29dcYVNZx/40iywLJ3MTn7xQRrSnBnROg++CJOKvDsCH5Yq2/Gm6aFlJUQkLCBqqwUeTd9AM1PbQfMoU19aLbhx77J+SXFsKGEsTAHih92tD99Cg4fKBX4XC5qV76BonSdaloruJrRWTlW6gt2uFp3h5vvABmLUM58QSQHNhuGWXA8Qi3C/Xqc0ESGKqC8HoRloWQBAiBGDU42fJEt9BJRkplWdC651VES1elxnjUmY8RM2tTqoWacWJGHCROO2ALge31IJ/ahzDb+XLeTURrSmhx+CBOOG88ZiyKES/F4XQjmW6QHEg2xHTPLtV395Qqvtv9wsgoHIdlZPpTe8XuFgx+qYh4tqd7lt3hyT2El19Kbyl30cXZdnJZfj0kyUvOoV35cu4l9eb6yUiSl711SvbFwWnqzlHDXu17bB0nq7QdPCGtfW3bwRNAPnjsgzoy2YPdBk8BuTVYNnbxGhye9+l57gCMaDV2eCuxj/8fzh7nUrHwCcxwGQVD7qXynYfQa1u/WoD659lAco6vXvIiHc54hNVv3Zq6X+3PeBjFlUfHMdPBFhzZ/1bspWtQjj4S0SwXZBlbkTEVQdgUKfvN4fDi8Tto1+cuRHUMPliDclo/alQnhr73q0B17YC9485DWBa2JBGW1Z91rSy/HzRNu4HaiH29bYMO0HBSZB333ygOOZJ6SQNEa0r4cvFd9D71QcT05LY9rYbvqWe8rrTmqFHPI9kJxOYy7NlfpRYFpHYFVCx6gpzOw5CIYplVhBbNJafzMEq/nkP5jGS0NO+UIqo/ehrZH6Dl2c8iFbSGMw/FqqrGnPcR8knHgwWJ5xsYA54cDFs0GPvOyrB1Y6xLA3f7CgmXhoFky5eGiw/th0zZ4dgfBAjbxnhvCfao3nz5zp2p573txwVUl39P76HP4MxpBpKTcKqWW6UxteC7SxXf5X5JyZhGz35or3cgas+zPd2zZMnSlDHMGr5875b0uf69W+gz9Dlg7wQ19zTn/1Ln/lrU79W+JyTLRnbkpNVey44cJOvgsA3qk8keXP5eET2GPI+JK5kpsXQlYmsprsHHQct81K4jqVz4RMpRL5t/P3mnFKW6wtSVx8nYyP4Aic3FRJa9wdEjn8a2TBCCRLQcKx7BqTYHScJYtAylbWuELGNvLcNYWowYNZhQAxtD1y0sORev14PktrBGtkmmxf9MR1uRJTzV1Rj1FpU8l47CzKrKZzkIyTruv1kSqZd0HdGaEmyfCwGNXg03TKtWWEbeKTXJNG3Cphu/7MKeMRfq17fluIitXkRsdXprN1/vi4Fape6hE6hc+ERtHfQUMB0knn0j9WJVzjkDLBvjtbd/tuBN3Rjr0sA9tWluqbY1ais6jnoOyzaxhULMPLjSoC1VQT2tL7FIVebnbRjYL3+IcsGwPbZM2R9EyKVw1GRKG9S4R8hlf0Rdfu3a8933dM867lmyZDmwWBgZ3/3Wz8xP392c/0ue29SwjQRVb00it88lCNmNpCeoWjSJguGN7trUhMhsD0KCGrz4Lh2VdGo3lGDNDCP95Uy2v3F92vFmqATJm8wQrp/t5hMmhX+YSOnbdxH9eg52NIT/5Buww3GcMTey5ET4bExJoB5/DIl6zrN66UhqZAXMnX+r+/O31OSFE7Nk2QuyjvtvFhV3TiDtZe3OCSB8fpQ7x+7X1fBMKXIi15cx8io78wmc+0ryRWwpFAx/EFOohC0PAoF33PmoloW9rQzjrQ9RzxyYVjMH+y54k6mnp3rpKKo9XgTgl61frA/t/kZKGCTe/QRpRM/Mz7siiqgK/2p1hrpugedwWlwwPZkeLynIuYVUlUX3fHITJNvTPUuWLE0ZCSXju19qCoJwBzGWULHCZZTPuDm1TfYHsMTBaDZntgdBxTAtqhpkSlhSLLP9ltuKllfNwZZU4sJLjmkimTaQT4vTHgWnjHB7MWd9iqgOoww9CeOVeRgVVahXjCEx439pznPihVm4xp1P/Bd2npu8cGKWLHvBwamykWWP6KaHboOn1L6cSdU0RQ0vFbZMyBT7zSGtS5ET487Hec+fEePOJyzn7tQLu/APEzFfXYT5xBzMf87BfGImwvRSnUj2YjVMi5ApCEkqti8HqsLYkSgiz5f291Ip/j+TXa2+5mD+Kn1o9yuWjf3NGnhlAd37TUx73t37P4gqvMiXjiL8K05Oum5RqXupNPxU6l6k/ZAmf6DI9nTPkiVLU0Y1XTu/+/tNRDVdB3hkBze/pXf/ruxB3Ux+lzrbq842DO/iu1ebOVSZPqKWF2910lbSH3wW85V5SHiwZn6KOftT1OGDUC8ajvGv+Sk7SzgdGYMwkvXLB0bqhBPrs692ZJYsB4qD16I+CDiQatSmaYPcmh5DnqehiugvQV1aU/PmuYS2V4NpYdarR5YkBWvm4lQNPOy6xr5+rZwtQKlL49pPgje7W31NHGTpVGadku+GEpxvQu9TH8T2uZBcHnhlAdIFwwhJapPOGmjKNPWe7lnF+yxZft8IG1wryul92j+xJRAWSIvXIvq3OdBDO6ip/+5XhIlhywfN+7VuXjBCNeSqyXFbe2EP7mneyxT8MP41H3XceRgIQsjkWok0R70uCHMgug40deHELFn2hqzj/jOQZYFLjiDsBEKSsRHYtkjVR9ftl6wYRvmPVH80DStc9qurUZumTbReffevLbhWvx5ZQSL3tH6Ym7Y16sW5o74JlP0seLOrtjVIYr+n5f/S1CDjG/tHjMqt2C4ZKWYimzmYr7wPVWEMSdrtvar7rdaJ9zWlGv+mMram2tM9q3h/8DJs9DwAmjfP3WlfzNRxyY6M50UTcWoq9V90bFkOLixVRpzUEQkT27YQioQ4qSOWJEP2PbBP1L37mzfPpWJ7NU3l3b87ZFngkWsQmBi2hRAWHrmGiJlDVG+8Pbi7eW9XwQ/LsgnZEmBhyel2lvHBZyjnDUlF4X9N5/lgEE7McmAIBoNHAndrmnb5frjWQmCTpmkX1Ns2AXb0kQ8GgxcAt5L0vy3gdeBBTdMavXyVddz3ElkWOIxNrJqzQ4n8yFPuZctX/6Z1z6swnYcixzem7W938r3ULHjqd61Gva9qtftT8GZXq6+GLDfpPrSZsLGJiTJWL7kt9XvrcMoklFwvypjTqNrNpJjpt9x+yBR05cA7fk15bE2FrOL9wUuznADHzz0v474vhv1rt/tqyDruWXZgyyaJaAWr59+yYw4YMhlHjptsNeTvD4/TxAzv/HvweN1UR/bP72FXwY/6tlJDO4uqMHauF2nc+YgD4Dz/loQTmyq6afUpj+lTDNsOKEKU5LscRQ5ZWnKgx7UHjgDa7cfr/TEYDL6uadrshjuCweAlwE3AKE3T1gaDwVzg/4BngUYvHGQd973EJUdSzgSAXl3C+vfv5/ABRayZX8TRo6fz/fz0/Ws/uJ/2fYson3Hz71qNuqm8OHe1iIDJQZdOlen3uPr9OzhmzHOEyd1t+5RM566ZX8RRo56vVeI/cDTlsTUVsor3WbJksYxIykmD2jlg/i10HD0NyDmwg8vyqyPMX/730JjU890Ha7LO828N3bT6rKsKz7lj8XeFWyJxWnmcbSb16zinrc87fF+d92AwKICHgFGAATwDvEXS4c0HwsB1mqZ9HgwGXwQWapr2Yu25tqZpojby3RroQNJZn65p2kTgH0DbYDD4FPAG8AjJFNtvgQHAaZqmrQoGg17ge6CDpmm76yn5APDPYDD4kaZp5Q32TQAu0TRtLYCmadXB/8/emYdJVZyL+z1Lb9PMDMuAjhgFFEpccGFRtgCKKCigaHJzTYxZNPHGn94kqNEsAl4TjIq50WuiFzUm5iZqDEZAiIoCKqAg7gul4BZ0FAaYrafXc+r3x+nu6Z7pWYAZpkfrfZ55pk+dOnW+U/WdqvpOVX0lxHeBT4QQ10spP+xIfmjDfW9RyWyFmCFRX4UdLPPCVargeSNU1mXeqC3LJGX7cTEwUdipBI6eAtQmrX1E6HHTqVQSX0kF/b58A0awAhWrpu7F/8ZRDvFkO4rWii6jisDwK2bZigTt8d6jvLcPgOCtV+eFj7l8c3eI06XEnUTB6fWgp9F/UVGuU7ANUOoLVAloshwIfejoDMpiGazRdD27Y4lFGaMd4NPGONeue7vi91NGLDo4HBy3n8mfD4wHjgN8wHPAZcA1UsolQohTgIeFEMPaSWcEnjHeG9iWNtavAOZLKS8TQkwGhgGHSylrhRALgG8A1wHnAcvbMdoBngX6AbcDuVPm++N9MNiYG1lKuUcI8SYwEtCGe5dg+PCXVuYZFf7SSlKxOvyllWDYBc+rZDTHI2nnTfW1LJMaN8DCJxLsiCgGhA2unRygtxXXxvs+0OMaGiuEf8JvuH59IF3+fbl6wm9QlvJ80LRFK7qM4etamTtCMctWJGS8HrdY497JdUyx4/cFueWBkwqeu/JrL3X6/VoznA8EAcuvp9Fr8rGDBdsALG24fyE5QPrQ4/pKmi4lpVRlxmjP8GljHEepyk5IfhLwkJQyDsSFEBOAj6SUSwCklM8LIXYDop10VkspE8COdPzyAnGklLI2/fsPwCo8w/0i4KcdlPenwKtCiNk5YZlOWSG7u7BTm1bQC6D2kphTwpEzFnlGBGTXuO98exlHzlhEXJW2OD90xi3YFcO7xGlUyvazcI1ntAPsiCgWrkmQsvdKDzQ9lAhl3JRuoMEr/5vWB4hQ1s6VhXX5yBmLiDndv91NMctWLOR6/j3o+0vpd8G92jFdF+Om4u1H0mgOIA30LtgGNNC7myXTdAdaHzTdgW0YVQeXBPLCDi4JYBlGVSuX7A3Nh6GGQIutngw8o1hlzgkhmo/05I6WZ+M1I5r5IaX8APhQCDEHOEhK+UJHhJVSNgLfAX6HN5UfKWU1sA0YmxtXCFGBt8b+xY6kDXrEfa9xHEXCHsiwc+/FUCkM00Rh8KWJ13herxMuVvp8njfsuKIrRsFcjGwFnWFHROFiHFA/6CUlJrZTR6y2lrKAhfKXYSTqUK6DYVkoM4hKNWIaJsq0MVAo1wHD8LJFOWCYKMNPNBloYXw09zBumBY4sYJe/dtCKZewP5rdEQDTBjeFch1UkXlV7wiOomD5O6p9P/iOo3ACh3LUnLtBpcC0UfgIOrVg+bJGciHP7u15fA8GTfx2ApIxTyeCFimzjMZGNz+OSuuIaeHYZZipenA9WbKypY/jqhQn0bGv+u3J5/ebBIx6YrW1lAa8tBMdTLuYKFaP959XTDvAxttHfi6n4Wt6Jim3cBuQcot1L5SeQ2mpiZHI79fU1xd3O9GWPpSWmNgqAspFuSkMw/T6QHYAktF0mAW+ICqVxHWKb7cZTXHSN+ifu3D88Nw17iwcP7y6b9A/txOSfwb4TyHE7/Gmyj8EKCHEnJyp8gcDbwDVwDHp687pQNop2raF78VbB3/73ggspXxWCPE34D+AhengnwP/LYQ4S0r5nhCiF3A38ICU8qOOpt2jDXchxAV4GeEHfiOlvONA3NdxVCsOslSz812/DZuJNz0+t6IeEPbWuh8oSkpMiHzE22mHKANOuJD+4ox8r6bTb+LT1/9G/fZNDJ1xM0q5fLzpHg4+/mu8/9T12XhDps4nUNKPuNU/21AU8jA+ZOp8/rX+dpKNu/K8+rflddyyDKK7tvLO8h+TqK+ifPAkDh19Me+uvLrHei7fn/K3LAMrvp0tK+biK+nHl8Zdznur5uflhWH7eeeRy/PCCu2ckJtvwaCJjzpS9TUFPNseRmOjSzBoYkabdKZ88CQOHXMJW5rF/3DjYmrfX5u9h9WBsmnPI73fb2LHP2pxLwKH9Ujj/YtCn3Iftj/Y3WJoNEVFMfQBPo+Ulpo4dR+1aMNKyw4rauO9NX3wmWDEPyORiLDtn9fm9aXskr78a/3/ZNvaoTNuZqd8nB2v3N8j+0WaA4/fMjcMKQvP+v2UEYscpSqtTvQqL6V8RAgxCngJb6b4b4HVwJ3pdehxYI6UMpE27h8UQrwGPA20N+L/NtBbCHE/cE+B80uAxcD9+yD6T4Gzcp7jASFECnhICBHE+7b6V+BXe5NojzXchRADgV/iLeiPA+uFEKullG91r2QHFjuV4NrJgex0eW+Nux87FT9g/qlspy5rgAEMOGYW7yy9It+r6cqrGTbrNna9vZR3V1zFoMnX0H/4zKzRnon33qr5DJp8DcE+4ezHkUIext9bNT/tyf/KPK/+bXkd99L5cTad/sNnZo32TLo9zXP5/pR/br4eNnFu1miHprwYNPmaFmGFdk7IzTe/qkMpt03Ptn6VrzP9h88sGP+wiXOpfX/tXpVNex7pA0Z91mjPvddRc+4mQXivy0BzYLD9QTbePrJFuB799mjuuK75WnztvO7zSTH0AT6PGIm6HumtvzV9CFNDrO4TPlhzY8E+V//hM7Nt7bsrrmLYrNvY8cr9PbJfpOke/Ja5oRMc0RVESvkz4GfNgicXiPceMDon6Ifp8PnN4g3KOTy2UJppb/ZTgFVSyk86IOPkZseNeF7sc8MeBh5uL6226LGGOzAVeDrjbl8I8TCe58Hru1WqA4zjuPS24vxyWq5X+QPrmE65Tp4TMcOwCnvWN6zsb9MXwvSFCsYzfaF87+FtePLP/d2u1/Fm6WSvaZZuT/Jcnlv+mBa4TsfLPyc/WssL0xdqEdbazgmZfFOuA6iCcTKebZvrTGv3z5Rx83t09LkKXuu2Jn+q7XQ1B5S+ZUGsgHZG2FHaclwH2nnd55X9agM0rdK8jYL8NqxYaU0fSMXa7HPltvW5/bXMcU/qF2k0ncRvgJnA9EyAEGI10KdA3DullHceCKF6suF+CPlTIKqAMd0kS7fiOC6GE8uuZzvQzYphWnkewJVyCnvWTzd4/tJK3GQU10kWjOcmo/new9vw5J/7u12v483SyVzT0z2XZ8q/f/9Sdu6MdLz8c/Kjtbxwk9G8S9raOSGTb4ZpoZRbME6mM9BcZ1q7f6aMm9+jo89V8FqzNfl7cnX4+cMK+Ij9+KbscfPt3jQajcc+twGaVmneRkF+G1bMFNIHw7Zwk9FW23nXSeaF5X6g6In9Io1mf5FS/pD0iH1O2JRuEidLT+6pFvIG2OFPzP36FZ7q1J1b/XSEYpQvlQowdMbN2WllO95cmnecWeNe9dL92fVTmTXug0+7rsUad1+4gmBZBSWGt+mBUmGGnX1rdm167hr3jFf/T199gGFn30oo57rmNE9n59vLGDr9prw17u2l0Z20prO57I1+5OZH1eb7GDJ1ft4a92Fn34ph+bMNfSbM36uiRXnk5pvjBEk2VrfUgRk3Y5X0o3+ZH8cJ5p3f+faygvG3b1wMsFdlU0hfcq913VDBe/l7VdC/rHiqxGJ81/eG9vS1pz9fT6SY87y7ZWtLX7tbtr1By9o5pFK+VtqwPvQv635fGx3pD0BTHqdSAfypKEecubDVNe5A9jl3vLk0e1zM/aK2KGb96mq+yM/+ecdQqmc6mxBCXARMlFJenD7+BWBIKdubKj8IeH/XrgZcN//Zva+T9V0hbqdQzPJlvMor5WAYOV7llecx3PMqH8U0DJRlY6jO8Cofz3r176hX+YqKMNG66uyOAE1e5V2UYe+V99T+/UsLfTzqCgbRis42k2ev9SM3Xw0r6JVJjid22H+v8hkdaNWrfFpnsl7lVQoMm6RRiuVGWr1HR5+rLa/ymXsVm1f5rnjXi0lf+/cvJZWI7bWzudbWuBfax/07M1fQN3wwALsjn3LvshnZcxfPXE7v8CHEU1ECdoiayCfcvexswNv7vdB9MvfKeJVfsXgkMy7ZzP1/yr/3hd98qd2wC7/5Upv7sXf2ucz5Ym0/WtP3A6Szg2hDX4u53W2OlrVzyXiVz+3XtOWYrhj0tZk8eXlc8gXyKt8T9Kur6OizH8A+gaYTKZ7hpb1nFTBfCNEfiADnAd/rXpG+uHgGWa+mCiPuHefT0S+ALRuIlp76wdtMoO3rmmMYJpFE83VauXtP9qzGaX/Jy9fsTLn83RAK7ZDQ3s4JsZhLDJs8nWg2IcaLk6MjcRfynMO56fT3fneG9uRLJFwShFuVTdP1tOZsrjX21gld3/DBjH50AQCbZs/Lhn9n5kp6hw8CIGB7+tE7fAhXfu2lbJzjf7CRgFV4SmxPdYbX3HldLtpxnUbTEs9Ib96v6bl4/bTW1qnntL1x8MyDrt8ZSaPR7B091nCXUn4shPgZ3pYAfuBuKeXGbhZLo9FoNN1E7ih7a/QNH8TJS/6vzTgvzPl6wfBI/SesfWAmMy7pecZ7W87rtOM6jUaj0WiKnx5ruANIKf8C/KW75dBoNBpN95FrsBcaZY87Ka782kvEchwwtUeh6fe5o/LtMXPOY/TuVZk9vvCbha9ddtodHFLSN0fW7hnVy66FTcTYU9vxfNJoNBqNpicihBgM/FwUnMMmAAAgAElEQVRK+d1OSOs+YI2U8j4hxBrgUKAhJ8pnUsoz9vc+Pdpw12g0Go0mMy0+11jPJWDZBc8/csY5HBJumiL6SSTCuY//g7jjcPlXNuVNl0+mvOmiMy7ZTCqlsqPuF37zJZJJhwf+Ojov7d69Ktsc4c5wSElfxj70bPZ4w1cnduSRO5W4kyBgeUuPbH+Q/v2bfA/oafQajUajaY+E447dHXMWpVxVaZtGVd+gNddvmRu6W652OBw4oovSvlhKuaazE9WGu0aj0Wi+EMQdh4Bl5U2FP+XhZSw/43QqSoMcEg5nz7lJBTnL3H22gZNQWH4D227y6dNQ6xIMm9kR9VRKZX8/P/0v+HLiplIKJ71eNGO8Nx9hjztu9lw0lSJk2znnnOy5Txp3M/Opy/YvQ9LoafQajUaj2VcSjjv2/dr40mvXfVzxaSTJwWHfoIXjBy4dXB6Ytb/GuxDCAG4EzgVSwF3ASuB/gb54fs6ukFJuyh31Tl+rpJSGEGI+MBAYimes3y2l/CVwGzBECHEH8DfgJryW/y1gIjBNSvmOECIMbAGGSilj+/M8+8sX0XC3AEyzsDPF1sKLhWKXD4pfxk6UbxCwHa8i6Ura1NlcijXvi1UuKF7ZukCuQRSZvmY45qLHCZdVZI8jddW8+ceWM8pGXLSMYNkheWFOSmHZButn/AKAjdOvw/B7986MsKuEyhttd5MK0+fFef78mQDs/meC0JEW0a0Oux9PcuRvwmz9USTvXoXChtxUgmkbqITCaGbU281mvVsu2P6mLZVUQhHwm9lRdjepMK2m60O2jZtUuAbYtpGdAVAVidMv2DvPwAe6xKjPOLXLfPRoPV7++dxR/OZEk3Ea6/Kn47eiL4Poep1tV1+LtY4ohJa1a+igrIMoAn3NpSflcWejn71dBtFJ+ro75izKGO0An0aSXLvu44rfnXr4ooPD5rj9TP58YDxwHOADngMuA66RUi4RQpwCPCyEGNZOOiPwjPHewLa0sX4FMF9KeZkQYjIwDDhcSlkrhFgAfAO4Ds8B+vK9NNrvFkLkTpX/W/pjwX7xRTTcKwH69AkXPNnRvTG7i2KXD4pfxk6U731gMPBBZyXYCm3qbC7FmvfFKhcUr2xdIFfR6WtrHtrDZRUFzzU32gGstKHs83kGccZoz6V5WMZoz6XvmZ6RGTrSyv4+8jctn6FQWEfv295xIblMn0Hz3ZMrw4G849xRefCm3+dOx89QKKwj54A2jfZC51sz2gFCvgChfvnP0Iq+HwidbVdfi7WOKISWtWvooKxFoa+59KQ87mz0s7dLp+lrylWVGaM9w6eRJI5Sla1csjdMAh6SUsaBuBBiAvCRlHIJgJTyeSHEbkC0k85qKWUC2JGOX14gjpRS1qZ//wFvB7PrgIuAn+6l3HqqfCexCe+LSxXgdLMsmp7P9gNwD62zms5C66ump9HVOqv1VdOZaH3V9CQ6RV9t06g6OOwblGu8Hxz2YRlGVSck39xb6hCg+VduA8+mVZlzQghfszi5o+XZeM2IZn5IKT8QQnwohJgDHCSlfGEfZO90voiGexxvmoVG01PQOqvpSWh91fQktL5qehJaXzVFR9+gNXfh+IG5a9xZOH5gdd+gNbcTkn8G+E8hxO/xpso/BCghxJycqfIHA28A1cAx6evO6UDaKdq2he/FWwd/+74K39l8EQ13jUaj0Wg0Go1Go9HsJ37L3DC4PDDrd6cevshRqtIyOs+rvJTyESHEKOAlwAR+C6wG7kyvQ48Dc6SUibRx/6AQ4jXgabyZKW3xNtBbCHE/cE+B80uAxcD9+yB68zXuAJOllDX7kFYWQym1P9drNBqNRqPRaDQajUbzuSDtzX46cKmUclZ3y5NBj7hrNBqNRqPRaDQajUbj8RtgJp7xDoAQYjXQp0DcO6WUdx4IofSIu0aj0Wg0Go1Go9FoNEVM811mNBqNRqPRaDQajUaj0RQR2nDXaDQajUaj0Wg0Go2miNGGu0aj0Wg0Go1Go9FoNEWMNtw1Go1Go9FoNBqNRqMpYrThrtFoNBqNRqPRaDQaTRGjDXeNRqPRaDQajUaj0XxhEEIMFkLc04npfVMIsUkI8YoQ4jUhxBU559YIISY3i3+fEOJbe3MPbbhrNBqNRqPRaDQajWafSDpq7M4Gd31Vvfv+zgZ3fdJRY7tbpg5wOHBEZyQkhPge8ENglpTyBODLwDeEEN/tjPQz2J2ZmEaj0Wg0Go1Go9FovhgkHTX2oxp36Y2r4xU7IooBYWPQNVMCSw/rbc7yWcaG/UlbCGEANwLnAingLmAl8L9AXyACXCGl3CSEuA9YI6W8L32tklIaQoj5wEBgKJ6xfreU8pfAbcAQIcQdwN+AmwALeAuYCEyTUr4jhAgDW4ChUspYK6L+HPimlLIKQEpZI4S4CCjbn+dvjh5x12g0Go1Go9FoNBrNXlMTVYsyRjvAjojixtXxipqoWtQJyZ8PjAeOA8YA3waWA7dJKUcAPwIeFkIE2klnBDANOBm4RgjRG7gCeFFKeVk6zjDgVCnlhcAfgW+kw88DlrdmtAshKoAvAS/khksp35ZS5obdnZ5G/4oQ4hVgVvuPn4823DUajUaj0Wg0Go1Gs9ekFJUZoz3DjojCUVR2QvKTgIeklHEpZQMwAaiQUi4BkFI+D+wGRDvprJZSJqSUO9LxywvEkVLK2vTvPwAXpH9fBNzXRtpu+r/RjgwXSylPyPwBS9uJ3wJtuGs0Go1Go9FoNBqNZq+xDaoGhPNt1gFhA8ugqhOSTzY7HkJLA9nAW/6tMueEEL5mcXJHy7PxmhHN/JBSfgB8KISYAxzUbOQ8DynlbuA9YFRuuBBikhDixtau2xe04a7RaDQajUaj0Wg0mr2md8iYe82UQHXGeB8QNrhmSqC6d8iY2wnJPwPMEUL4hBAlwEOAShvUCCFOAQ4G3gCqgWPS153TgbRTtO3v7V68dfD3dyCtm4FFQoiD03JVAIuArR24tsNo53QajUaj0Wg0Go1Go9lrfJax4bDe5qxfnRlc5CgqLYOq3iFj7v46pgOQUj4ihBgFvIQ34PxbYDVwpxBiARAH5kgpE0KI3wMPCiFeA56Gdkf83wZ6CyHuBwptC7cEWEwHDHcp5Z1CCD/wpBDCTct6l5Ty7g49aAcxlFLtx9JoNBqNRqPRaDQajeZzTtqb/XTgUinlXjuR6yq+iCPuNnAosB1vioRGU+xondX0JLS+anoSWl81PQmtrxrNgeE3wEw84x0AIcRqoE+BuHdKKe88EEJ9EUfcBwHv79rVgOvmP3ufPiXs2dPYLUJ1hGKXD4pfxs6Ur3//0va8R3YWg2hFZ3Mp1rwvVrmgeGXrCrmKSV+LNd9bQ8vbtbQm7wHS2UG0oa89KS+1rF1DR2UtBn3NpSflcWejn71o9FXTyWjndDnYttXdIrRJscsHxS9jscu3PxTrsxWrXFC8shWrXJ1FT3s+LW/XUszyFrNszdGydg09SdZceqrcnYF+ds3nFW24azQajUaj0Wg0Go1GU8Row12j0Wg0Go1Go9FoNJoiRhvuGo1Go9FoNBqNRqPRFDFfRK/yGo1Go9FoNBqNRqP5giKEGAz8XEr53U5K71RgHnAwYAGvAD+UUm4XQkwGlgNbAQPwA3+WUv5yb+6hR9w1Go1Go9FoNBqNRrNPpBw1tq7eXV9T675fV++uTzlqbHfL1AEOB47ojISEEBOBPwM/kVIKKeWRwGrgkZxoL0opT5BSHg+MBi4VQhy9N/cp6hF3IUQZsB44W0r5QbNzJwCLgXLgGeBSKaXe07KbKC21cVyTSCRFSUkIVxk4joFpgGkqDEMBBikHDJLYVgMWCpWKYxgmmJ4qKuViAMq0MNwUynUxTBOFgaHcbLzcuBgmyklgGDYpqxTLqQc3BXaIhCpHuQrTcLCNRhLRWkoDjaBcMCywgxipKMp1MEyLhFFGLOZ2RxbuM+GwiWWmiDTuwh9KoFQK07TxW2UkkzaOa2CZCp8dwzBskk4AM70JiOOYKBQoA6W8slKAZSoc18R1wTTA53NJpYxsWpaVIpk0sQwXnx3DcaM4ysGyQriuJ4NhWJimTSQSIxRKoZSDYZiYZtCL4yYxTBvTsHCVi2GYuG4C07AxTR8pJ4ZpmFiugatMYk4JACVmI6ahMHDBdcC0aaSURKKp3CzLIGg1gkqC4SPmlOA4KnuuxJ/EcGPEamspDdjEVcvrS8xGDDcJps/Tx1QMZfpodJvS0uw9paUm8foqSn3eO6f8ZdTXt/3OZcrDVEkM24drGuAkvTrAtMGwUAYYSoFyvPfZ8oNyUW4Kw7S8OE4Cw7RR4NU7ykUBSUPhKgfbCqAwcZ0wrmthWQqfnaSxMUUwGMbJeR8c18B1jew7YlneMziOiavAshSGAamUgW1571W2TrRcDBygNv1eNHkBtrBxVALXTWFZAVy33HvvDBefFUG5CQylcJWLokm3c3U+EUlgWYGsnvr9JgEjXS+aLfVdo9F8/ikt9eG4ttfHSvfRXAWWCYbpolwDcAGFbUdxnIhXxxo2lhXEcWJe/8KwsU0fSikMFLipdB/KRuX2qQwLbL/XThsWOElc5WAaFlg+cOIo5aIMPwb5bSyQbYM70u42b/OVCh+QPNV4pBw1dtcud+ljK+MVdfWKslJj0FnTA0v79TNn2ZaxYX/SFkIYwI3AuUAKuAtYCfwv0BeIAFdIKTcJIe4D1kgp70tfq6SUhhBiPjAQGIpnrN+dHum+DRgihLgD+BtwE95I+VvARGCalPIdIUQY2AIMlVLGWhH1F8ANUsrnMwFSyjuEECEhRKBA/BJIdwT2gqI13IUQJ+MZ5sNaifJn4GIp5fNCiHuAS4DfHyj5NB6WZVBSYhGLW54RqMB1DZaviJN+eTn9tAA+H5iG4um1SRobFWee7ifor6Lq6V+RbNzFkKnzMX0hlFLsencV/cUZvLviKhL1VfhLKxl82nV8+uoDVJ5wAaYvBIBSik9evJfKEy7gX+tvJ1x5Iv3FGWxZcRW+kgr6jvsNK59KZOWYfppBeWg3/9pwO7Xvr6V88CQOHXNJ3n2GzriZYOiwHmO8h8MmpmokmowRS9azdN1V1EWqOGLgFMaJhTy2MpV9/nNmlgAGhukZGrG4wQub4pwwws+qp2PZeLNn+ommDB5b2RR21vQA8p0kL73iZI9ffS3J9o9dzp5RQrgkgW35SaUixON1+P1lmCYo18FVDq6bwMBEGRCP72DtmrlEIlWEw5VMmryIcHggXn0MrhsHpbDtEI4TxzEVO1/5C/2HTccy/dQ9fTtlo77GrhXX49RWYZVXUnHuzVByGImEi2UZ+FMf887SudlyPXLGIhL2QABKjBqcSB3vrrw6r9wJNF1fkviYXUvmZtPvd9Z89qy5HSeyi35zFtHoH6iN932gtNTEqfuoxTtXWnZYq8Z7bnmY4X6UTb8WJ9HAe6vmZ9M44oxfYof6kmispurl+6kY8VV8ZZUkav7FZy8sztYx/1p/O8nGXRwx7QYMy8fHL95D6UlfY/mLCwgHKzj1pGtIxQ/mySdd6uodhgw2+fKEAPF4/vswe6afeBz++UR+WCxm8PiTsby67+0tCYYf5ePJp/LrxIDfQqkAb715PSOO/y7BYB8Mww+mgZNIEY/V4DI07x0+e3qYsLmHd5f/Z55uO4FDseLbC+q8ZRnY8Y/Y0izPM/qu+fzgpuL071/a6vlUIsae2uQBlEhTLJSW+ojFvS6/40BjIzz5VMs2fshgHy+9kuCUMSX0CjtEo58Rje6itNdAfP5yXFfhuElAYSlIRmvZuuLKvLpl+8bF1L6/1juefhNGsAwVr8+v96ffxPZNd2fjHXn6f1G/6r9xI7vo99XbIZXIb4PbaHcLtfnDzr4VyzpEt9MHiMZGtShjtAPU1SseWxmvOH9OcFFZqTFuP5M/HxgPHAf4gOeAy4BrpJRLhBCnAA8LIVqzFzOMwDPGewPb0sb6FcB8KeVl6answ4DDpZS1QogFwDeA64DzgOVtGO0ApwA/bh4opbwFQAgBMEoI8QrejPcjgYeAT9rPgiaKear8JXgF0+KBhBCHA6Gcrxr3AV85cKJpLMsgGIxSUuKQSJq4jkVdHZhGk9EO3sv75FNxolGINMKok3zU1Sv++aRN0u3FIV/+EYn6Kt5bNZ9UdA9OrIYBx8zKVvAAifoq3n/qevoPn5mNl4mbCasc+a286ypG/pCVTwXy5Fj5VICG+ij9h88EoP/wmS3u8+6Kq/BT3w05um9YqToSKoWjUlmjHeDYwy/MdvjBe/7aOoPaOjANE8cxeGxlnKOP8rHq6fzyMvDONauAOeZoX97xyHRZLl+RJOWEicdraWysJhjsSzIZIZVKEIvX8OQT32Ppo+fxzjtLMAyVNdoBIpEq1q6ZSzJZg0q3ry9uupWGhk+Jx2vZ8vYDNEQ+pfcxM9m+6S5SdR/T67iZWaMdwKmtovqRqyhJl1vQamTrirl55bp1xVyCViMlpvdFPmO0Z86/u+Iqb0QS7yt/psOQSX/XY/MpO+Vb3u8lc710NHuNkagr+M4ZibpWr8ktj9Kx3yLZWJ012jNpbHv8Z+CmqHr5fvqc+DXWbvwvHn30XJ55cSH9J1yGr6Rftp5I1Fex7Ymfk4ruoffRZ7P8xQXURaoYM/wiolHFk0821RtHH+XDdVq+D3V18M8nWoY9/mTLum/kSU1Ge254pBEao2EGD7mQtWuuYs+ebTQ2fkostgfbDpJySnhspZN33fKVDo5Z0UK3A0Z9qzofMOoL5nlG3zWfH0w7wMbbR7b6Z/uD3S2ipptIJP24joHrGNTV0aJOyrTxT6zy+gXLVySJJ/288MKNbHxhIdHYrvRMOpNEoo6UEyeJ9+Gved2S6WMl6qt4d+XVWIbVsg5aeXVevK1P/oLSsV4bq2o+btkGt9HuFmrz31n+Y28EXnNAcF0qM/qUoa5e4bpUdkLyk4CHpJRxKWUDMAGokFIuAUjbgrsB0U46q6WUCSnljnT88gJxpJQyMwL+B+CC9O+L8GzN9lAAQgi/EOKV9N9HQojMx4vMVPkRwABgEHBNB9LNUrQj7lLKiyH7haI5hwBVOcdVwKF7k36/fr0Khrf1tboYKAb5lHKpq/uIxlg9AfqAW4JhGPh8YBgGhV5en8+bm+3zNYUF/BXYtkn4oGOJfPZGdiTdMKxsBZwhUV+FHSwjUV+VjQdg+kLZc7nXmcGKgnIYvjJsXxQgm17z+ygnQUXFAG8qbRFRSGdjNbW4hmdsZ4x2gKCv5fNnykCppnIKBluWV2tlaBpGwWOvcrZwUo0o5VBTs42NLyxk2hl389SqH2SN9COHziYa3ZU9zhCJVBGN7qKkxMYwLI44cibrnvs5Y06+liOHzubppy5nzMnX0nf42Ri+EKYdyjboGZzaKnBT9O9fSryuoWC5WoaDBaQMs+B5lHd9qrahYPpmqCz72zacLn8Xi+Fd3x8K6mttbeF3TrWen7nlYYS8mRwFy88w6Tv8bJ7dsCDvw9BzGxYwcdRc3n/sKuxgWTa+6QthmqHsexP0l4NTlqf7waCBYbZ8H3y+joVl3pO26kTTrCASqcJnh3hm7dWMOflaSnsZBIOV1DWbhVBXr3CN/Bl3Gd1tTeeVctrU92Khu2VprU8A3S9bZ1JMz1JMsrRHscnalr7mkpG7ptbFMJr6YW3VVZl+QTwR45Tx84jF9pBIRVHKoaHhY2w7xPp184hGq70Zc+k+HDT11TIk6qtQbuH6qXk8I93GGv7CbXxr7W5bbX6xlduB4kA/t2lSVVZqDMrVq7JSA9Okqo3LOkrzaUJD8Jy75WLg2bQqc04I4WsWJ3e0PBuvGdHMDynlB0KID4UQc4CDpJQvtCPnJryZAW9KKRPACWk51uA5ostDStkghHgEOL2ddPMoWsO9HQpl9l7N+du1qwHXza+4+vcvZefO4h2FKBb5QqEE9bFqVmycR12kiu+cuRpUL5JJhVLey9r85U0mvWPHaQqrr99Gnz69GTDqIj5+5lbcpPe+KOXgL63Mq4j9pZWkYnX4Syuz8QBcJ5k9Z4f6ZK9zY9WUlfZtIYdK1pFyvNG9THrN7xOr+QjXCBJJNH0gKMSBrhgL6WxZwMI0wFEpysKVWSMklmz5/JkyMAwD1/Wmx8ViqkV5KdUyrKzUwFWFj8tKvXXvkdgeNr6wkPHjrycS8RrrXCPdNExisd2Ew5V54eFwJbHYboLBfpimIuAvzxoypmFlf1t2L1RjA24yiVVemdewW+WVYNrs3FlP2G8VLFdHWd6ovnILnsfwri/1WQXTd6N12d8pZbGnC9/FrnjXi0VfC+W9YVitPm9ueahoHa7fV7j8lItV0rfghyErWJ6tJzLx3WQUVyWy700sUYtFKO+9Ua73Uaz5+5BMtnxHCoVl3pO26kSDasLhSuKJ2qyuG4ZJQ/37lJUOanGdqeJ5z5fR3dZ03jSMNvW9GGhN3w+kzhbS14wMxZJP7dGR/CqWZ+lp+doRWYtBX3PJlTsQDJNKTxtvr67K9Av8Pj8PP3M5dZEqysKVzB6/iO3/epaDK0dzzLEXsXbNlaxdMzf7YRTIq2czxxhmq3263GOVbmNVIlqwDW6t3W2rze8pOtaZdIe+lpQYc8+aHshd485Z0wPVJSXG3E5I/hngP4UQv8ebKv8QoIQQc3Kmyh8MvAFUA8ekrzunA2mnaNsWvhdvHfztHUhrHvCAEOLVjJEvhBiB96HBwVs7n0UIYQGTgZc6kHaW4hpS7Dgf4xVShkr2co2AZt9xSWSNdoCN8jZMK0VZGbhKcfaMAGWl3reVzHrOUAjCJfDiS0nKSg2mnRbl9dd+jeMksEr6MmTqfOxQH6xgb3a8uZShM272KnzIrnHf+faybLxM3ExY1eb78q6r3vzfTD8tnifH9NPi9CoNsfPtZQDsfHsZQ2fc0uI+H29c7Dk46QE4dhl+w8YybGaNv5mysPcsb3x4P2dNt/Oev6Qkmi4jF8tSnDU9wFtbkkw9Nb+8FN653LCzpgd4861k3vHmdFmeNd3EMPbgs0NEIlXEE7WEw5UYpk043DRLylUu27YuS69p98LD4UrGjpvHtq3LME0bpdzs9clUFFc52d/+kgrssoE0vL6MfjOu84x1yK5xb8RrhGJOCUfOWJRXrkfOWETMKfGc3hg+hk6/Ke/80Bk3E1fe9Y1uCf3mLMpLv99Z86l7/r6mtXZp5zmavUP5y1q820Nn3Izyl7V6TW551G+4D19JBUOmzm+Wxi24roM/1DdP58DTMTcZzdYT/tJKjph2A3aoDzVvLWf2OO+92fj2HwmFDE4/vaneMEx4Zl28xTtSXgZnTssPKyuDM05vWfdtfinJ6ae1DA+XQEkowvvv3c+XJ93Em2/8MU/vX3/t15w13cq77uzpFpZb3UK346q0VZ2Pq9KCeZ7Rd41G8/nH70tgWgrLUpSV0aJOyrTx06Z6/YIZ003Wvr4g28+ri1Tx6Lq5DBk2G58dIuD3ZhlHIlVYJX29e6TrlkwfK7OWfadcyeDTrsuvg6bflBfvyNP/i/oNXhtr9B7Ysg1uo90t1OYPO/vWrENbTddjW8aGfv3MWefPCW741oWhD86fE9zQGY7pAKSUjwDr8AzcTcBvgXHAFUKI14H/AeakR7l/D0wSQryGN/rd3oj/20BvIcT9rZxfgucAr7XzuXI+B/wbcIMQ4jUhxBt4Bv9cKeWz6WijMlPo8ZzdNQK/bi/tXAyl2v5i190IIT4AJhfwKv8G8H0p5TohxGLgHSnlzR1IchDwvh5x3zcsy8D01XD3Y7Pywo8dfC4Tj7salIXrGsTi3tTRjFf5RFLh9xmkUilqat7mrTd/QyxWzbjxCyjtNRA7/SGq07zKqxRYLb3KW7aFm2zyKm9YFtGdEtMXIhWro2rzfSQbdzHs3Hs7MuJeaOZHVzCIVnQWoFcvC8tIknRTpNwESjmYpoXfKiORtD3P1yrKRnkbAX85o4f9oF2v8gYKV3le5V1X8e7WJEcf5fdG2VWSRGIH/sDBmIbLO/Iuhok51NV9yMYXFhIKVXDCiZcRDh9CMtmQXdM+fPiFDB5yJtHGGsp7H0o0uotYbDfbti5jxPHfI9pYQ+8+g9m08dccfcw38fvL2LZ1KV86bDLBQG8wBuA4Ku1VHs8r9356lVfKAaP4vMp30Yh7UehraamJkazLeh3eO6/yKQzbLuBV3uSDNTdyyKjvkvRZrMlxfjh58iLCgb4oQKVn6xh2AMP0kVAJlGGQSkVJJBswlCJUMgDl9ka5FmBy3/0xDj7IZNRJPoJBbzTqoAEGhqlwc3ZeaOFV3lQYZmGv8obh4LpRHOdTbDvIG6//gU8/3ci48QsIBvvx1pt/4tNPNzJ23AJSqRJKS4/Atgx8ZkOOV3mFwi7oVd72BWmIF/Aqr1IF9b27aWPE/UDo7CDa0NdiaHc7Sv/+pWy8fWSr58dcvrlonqWn5WsHRzC7XV+byZMnd2mpj2TSRySi6NUrvStGM6/y8WQ9exo+oLxXCX964mst0vzujEeI1P0L102wds2VhMOVnHHGPVhOKs+rvOskwTCIRXehXG+qZbjsS7hOCtMwu9yrfKisgurqyN7n7ueAItPXHkvam/10vF3LZrUX/0DRo6bKCyFWANdJKV8Evg4sFkKUAi/jTWXQdCGWZZDkYyL1O/OmZQN8tON5PqvZxJJnrmDOhD+z5qmWUzzPOweefuor2Q71hIm/IuDrReTxmzGD5ZSd/E1My4Z0Jb13HcuMke0CuduARHN++7wKraFpoollGfhL+mcdm+SOVKV9TBQ1tmXi21WP84dHsPbUYfcpw/r2uUTLe1EX/4h/rLsyb5pbr0A/onWvsuTF6/LKryxcydSR17ZZfgcPeI1nn/kO4I1iTjvjbiwrwOAhZ/COfJgjjpzFuPELWL9uHq+8fAfjxs+noZAP+TsAACAASURBVOEzpp1xD0qlAMXOHW8x4KBjsawSSkpsgsF+jB5zNTV7PiBU0gfbDjF6zNXZ7bHEUed7W8OlmgyNeqfQB5V8XXEcRcQJ0aQXKu9cfdQGeuU0cC2vr89c72RC/enfxa8XxUx9vUv//pVNHYt4++95U3mQ2XwAaHK0ZVkGA8d8n60r5uIr6ceXT76WQJ/DMEw/H6+9ia3vrc3G9ZdWMvz8e6mN7+Qf6+Zm349Z425iq3yYzz7dyKTJtxL2VZBSYcpKDT79zGX5Sm+KelmpwVfmWDzxzzlEIlX0qziOU8bP44GnL2/xTp09egEOLis3Lcje55wJiwj7++K6jaSSjTipGMcc+01GHH8xYLJt22N8+ulGJk1eRCDQB9c1SKWSRJOKKD68mYK5ZJYhNel8/96lOI1NHbdEwiWRVy8Wj9Gu0Wi6HtsysatrSfXux4rHEy3a94lT3mH1qz9j9oRFVFYMxG22/A68Os00fQSDfdi08ab0rjA3k0o2kjIPIhFz8ftNSojhOCkiid08u35ezg4yt2IYuZ7hmy/7zW9j89vgttvd5m1+SZH5KNL0SH4DzMQz3gEQQqwG+hSIe6eU8s4DIVTRj7h3AYPQI+77hD8Y5cE13yYcrGDCiMt4fGNTZ/TMMQt49rXbqdr1OpV9j+PLx/531jtzWanBmaen+OD933Lol8YT8JeTTEXp02cYlvJhpJLgJlF2CMctQ7mAoUioBI7TuR3MQnnY1uhsO2l1+whmuaVQd/wFtSe9VuzwStQZU3EPqmBXw7s8+/avqdr9OuA1uv8+5R7MRJTaxC6Wb5rX4fI7e7rNm29cy/btq9MN8C3YdtP2abbdiGWZQBLH8Swr07R44vFLmDDhlzz33M8IhSo45tiLCJccjG2HsGzP8MrsY73js9fo228oG9YvYOKXb8R1XcBHKtV1I9zd/U61xud5xD0tS6c/X6H3GMCf+jjvw9zQM2/GTfn468v/2aJT+tXJd6IaqgmVDSGVKCGzmmz1+gTb3ne9d2GGH8vcRjJZz/p1Xqf00EMncfQJ3+PRnA9l50y4lRJ/H/7y9LcL3ufpJy7N2xLRdRK4yiEU6odhBEkm913vi1WvW0OPuHcOesS9ayiyEcxB7MOIe6avwNenUlt6OMtXJLPt+9SpUZ5988dU7X49Wz8F7DB10c/y6rTZ428haIVobNyBZfkJ+MtpjO5kw/oFTD39D8TjntFsWQYBfwMbN97M0MEXEvBXEE9U8+779zNy1E+y8bqSnqRfnU2R6aumk+lRI+6aA4tlmfgNPygDDIVrRqmLVFEXqeK51+5g2uhfUFpyELYZYPmGa6na5RmIVbtf55k3fsj5c+4iEY/h9wd47tnL2bXrdbZteySb/uxzluIAKdfbX9xqDPDK3xNEaxWhcoMTzguAP97pxntz2hqdLXZM1yWVY7SnzjuPaMyPVW8QSgzjzONu45+vX0HV7tepi1ThqBSuNYA+4TL+fcrdOGmjefmGa1qU37nn3IFBANNQWFYDo8dcyajRP8IwbBynaQTccRSOEyIQiLLqyYuzzsGOOGI2p09bjFKekzpv67crs7JPm7aYdeuuY9ToudnwM6f/kWi0Gte1iMczXnN7Tnlouo/c9zi37jL8RyDO+xOGE8X4ZBfqwRdJzRlNXaSKyn7HMWb4RQT95cQStSSSEWzTR6K+hJf/nszWRV8+P8Ckid70dNvazbPP/IpRo69izMnX4rNDJFNRegX6cuZJ1xIM9cPv68XLm25FHPONPKMdvLWisXgNo0bPJeAvJ1TSH9P047oO+R+qtN5rNJrOIdtXsFLYbGPilBgVZUdRXbeFt/61jHHiR4R8FUST1SSSngf5f237J1+ZdAeGYWEYFslEHevWzWNXtddXOOfcpezY8RqjRs8FEgQCZOsvhcmxR/6Ut5aF0vVoX46d+VNM02lbUI1G0yZ6LommIJZlYiUCbP5LkufujLP5L0lUfR9GiYuYPeEWppx4JeXhgURjNThukkisOu/6SLyamroX8flqaGx8k1iz8+FwJTU177DqyW+j1McEzCajHSBaq3jl7wmv861pFdc0MfqkHXuddQZxJ8BbjyfY+OcYbz2egEQvJh/3M8Ab6dtd/wExZzvRZIBYtBfJWDlKWQXLr7p+I8qoYtWT57Lk71N54vGLSSQiJBK9WqwH9wWjuEaCk0bPpV/FcVRUHMfgIdOprX2PurqPCjoMS6aijB03jzff+GM2LB6vZdLkW0mltFMZzb7RvO568f8SJCJlmEZveH4ryWnHo0pDfPXU/2Xa6F9gmV4dY5l+DNMmEDoya7RDui56OI7pKJKJGK4L0Wg1L266GddNZO/rOAnefHUxQbuEp5+4lO3b1+K6yazDyAxl4UpijTtZu+ZK1q27jrq6j3Bdk3i8jHg81OX+EzQazRePTF/BiCRIRatZ/erPqG5Yz5sf3s+Jh/yAj5YP45X7+vDR8mH444djW7044qjzwLCoi37G8g3XsmTdXI476TL6VRznOaA1TA49dDwvblrEo/+Yle3PWZaB6fTOGu3g1aNvLQthOr27OSc0mp6NNtw1BfEb/gKGdJLRQ76PZfpZ/fIt/G3NpfjsENt3vMKZYxZkO6hl4Uqmj57HG68uJpmMYNuhgp7E33zjj+lR2B+DUtl7ZYjWek7TNK0TwcL69rkYfcpQfXrzxvJ4Xpm9sTxOeeAwr0xOvp4Nby7m0XU/xhdoJFASwResxTAcvnbq3RwxcBLgld8ZY+bxxvvLqK//KDuCftDBYzBsP6ZvD/5QBL/fzPo9eGjNt7n7sVk88eoijjvpMk448TI2rF+Azw7x+muLGTtuXl75T5q8iN69j2DL23+luvr1bFifPgLbPlQbL5p9pnDdlSBl2DR+ZRQ7y+t4bNN1bPv4WVw3xarNC3nw6UtYtXkhrpsC12qzLkqlSpg0+Vai0eqs8R0KVWCaJieedDmx2J7s2nfb16tF3XjWyTfwVtqD/Jcn3USvXgP1hyqNRtOlZPoKPL+VXnZ/zh2/iJC/D1OPu54tzQzsV5c4kAzytzX/wT2PzeafL8zjtJE/4bABY1i5aQHHHn8J4ydcj3Jd1q65MttHyPTnbLsRt5V61HP6qdFo9hU9VV7TCmbBSrc+Us2qzQuZOe4mXt36MI+um8tXJt/Jlg8fZ+rIa+lbejg1e97l9ZfuIBatJhjszWuv3k08XsO0M+7BdVPU1LzDKy/fQXV6ulUkUoVhOoTKjbx7hsq9Kfqa1kk5LvUlvQhfdgHKsInW5m9jF61VGIbN1JHXeh7UgTPHzKMxsZtHn2tyzDXjlBs47aSrmXLCXDAMtm5/hnHHfJ/Nzy8EYMgRszly+Fd5+Jn/l+fsLujvy8Orf5y3ZczKTQv46qTfZbeGi0areeXlO7JTg5OpKK6TYNPGmzhp5A8ZOepH1NV9xMYXFhKNVjNp8q1Y1kBtvGv2DWUUrLsaIrv509pzPOP5lF9SFj6EnTXvMP3k64klatn49h95dN1cvv7lh9usixxH4fcfyunT7iIer8XnC/PS5t8Si+1m/IQbqKl5l3C4kqOPvYilG35COFjBlBPnEkzrfln4EMaMuZpAoAzbLiUatbWuazSaLiXbVzhnKn4LGtwqVrzwc84/+X6itYG8uNFaRSIey2vXl667ivMn/Y5dde9RXj6YRHQP0Vh11mjP4B0nAbdgPaq0Y0yNZr/QI+6agmQM6VxC5QbBYJjDBowhGt/DyUd/h/Mn3YFpWAwfNJ0Nby4GDEL+ckaMuIQpp/6WTRtv4dAvTUxPG00Bfl7ctChrtEN6n2WrkRPO82fv6a1x95NQCTRtk3Jcah0Dy0fBMtsTeY8lz1xBSbAf009eQDjUn3iygTPHzOPfTl3MlBPnsmnLn3DcJDtr32H1y7fwpQEnUhqsJBb1ptAffdxFWSc10LSnq1KJgmt4MW1mzVlGWZ9hnHbGYiZMuplevQ7jrbf+jG0HSTkxtm9fi2marHryP1j99BVUV7+e98Veo9knDFXwPfAHgll937jlj6ScOKs2L+SZV2/DMv1MP3kB00b/giifMnxWPK8uOvH8QF5dZBgRnnzi+zQ2fsZTqy5j+/a16TpNsW3rMsaOm0cg2Je6SBVVu17n0eeu5MGnL2HJM1dQ37CdlSsu5MknLiWVSmijXaPRHBAyfYWIGeMfz3kf3G2f3UpfrxffmfEIX51yJ5X9jqMuUkUqFeWssb9CobD8YQKhCiaddhv9Ko7LXuvNrPO22tR9Oo2m89GGu6YgKbuGo2cn8irdo2ZGWfPmDZw49N/48LNN3PPYbB5eexk1ke2sfvkWJo643PMk/sQlbHxhIclkA7HYbgL+csLhSkzTyk4zzZ82fSuJhB/HH2fkBT4mXBpg5AU+nAPgmO7zhD9scML5+Q3l0bMTvPHxg3zt1Htw3CQPr72MP6w4j3++MA8weebV21j98iJOGvbvxJMNrH55EaPEN1j/5l2kVLSprAyroIFuGGbBNbzg8uDq73H3Y7N4cPUlRGI7MX0BRo2+ms8+e4VQ+CCmnnkvyrAJhiryrm/6Yq/R7D2FOozHz7FY8+YNPPj0JVl9Nw2LwwaMYcKIy1i1eSH3rpjDE5v+C8eJsa327wye9QETf+Bn5AU+SgeYzeqiJJFIFQF/ed6IUyTyKcOP/jpb3v4rwWDvgu+G6ybTcatQSuu5RqM5sCgShIMVzJ5wC8of5aiZ0bz6cvisOP944fs8vPYHmKaPaaN/weQTrsJRDg+t/h53L5/Fw8/8P2oaP2Hze39nxMjLs+veMz5qHMfVfTpN0SOEGCyEuKeT0rpPCPGt9O81Qoj/a3Z+vhBi/v7eRxvumhZYloFlGPj7xBh1ocVJ367jsLPfYdWWH7P149U8um4uJxx5fvYr7OMbFzBy2NchUYKV6MeUifcSClbw3LM/47gRl5BMRRk/4QbAj+MoDGMgU0//A7PPWcbU0/+Q3dfTcVyiqRhRJ0o0FdMV/F5iGAZWaS3Dz9/DxP8IMPICm1Cpj7HHXEyvkgHZqfHgGd3/3DiPMcMvypahzwp6U91fuI6xx1yCUgp/qC9Tz7gbA4Nvz/g7xw6enb1fWbgSw7BarOGdPWERL7/7cP40u/VX4yoX0/Jx0KFjeWjtD/i/p7/DA6svzjb6GTJf7DWafSG3wzjxP4KMvtCmwdrCSHEBsyfcQjhYweMbF2AaNmOP+R6Pb1xAOFDBeWPvZdbIu4hHFEcPOotnt/yapPUZ0VQMw2jua8PnzRRSDlNOvY1p0xYzafItvP/eSmw7xNBh5+Ez/Mxo9m7MGLMAK93saj3XaDTdgWX6mTjicmobPgPlsuHDX3HY2e8w/lKTwbM+4Mm3f5jdiWbF8z/HtgIM+9JplNpDOP/k+zlv7L2EA149euzgmazYOI9xE/6LaWfck7dPu+7TfbFwU2pstNZd37jHfT9a6653U2psd8vUAQ4HjuiitM8XQsxuP9reode4a1pgB+I0xHaydN1VTD/5eh5ce0ne+bpIFUo5TBxxGQ+tvpRwoIIy9zheXerwVm2SUPkwRs28lRdf/zFlZYdhmj5c1yGRCAAqu31YT9x+rdhxlYOKB3nx4aZt9Y6a6cfotavgiHnQX579HU9GmsJ9Zbz07gMMP/wMlq67Kruufdb4mwH4aMdGzhyzgIboZ7z1wWN8dfKdRGK7aIzvZv0bd3HSsH/nk+pXslvM1UWqiMb34LNCNMb35K0rXrFxHmeedC1rn7oi74u91gvNvuI4LgkrjumrIZ5qYMULP83q8MxxN/FB1QYa47tJOTHCgQqmHnVr1kFTqLwvx59ncdbYhVhGoODcj1SqhFNP+x/i8Ro2rF+Q3Y993PgF+P3lBAL9cVWC1zbfzrTj5+IPlJOI1/La5tsZeZLWc41G030oXLZ98ixHH34m725fw5STrsR1Uzjs4qF138iLWxepwjRs4nv8vPWoIlobIFQ+jKkzb2XVlh8T9Jd7fUIgkeill/58QXFTamz9TnfpK0viFem+56AT5gSWlvY3Z5m2sWF/0hZCGMCNwLlACrgLWAn8L9AXiABXSCk3CSHuA9ZIKe9LX6uklEZ6pHsgMBTPWL9bSvlL4DZgiBDiDuBvwE2ABbwFTASmSSnfEUKEgS3AUCllrIOi3wD8TgjxrJRy9/7kQS7acNcA3ii76WtEqSQGPhpju5l+8vWUBPpQFq7MM/rKwpXUNGynT+lhAEwc/hNeXeK02Pbj+Jk/IRarpTaZIFx+BKZP4af5lFNNZ2I75WxZll8WW5aFGPmNLxUsRyc9bbcsXEkiFWH2hFsoCfTFNC1GDfs6f3362y0c1PzblMUM+9Jp+H0lPLX514w95hIeWnNpsw8DBpNPvpGGeB2J+G62vv83kk6MxsRuVm1emDWizhgzj+deu4OyssHMPmcZ+ftYazT7jh2Ik3KcFjNNlq2/mn+bspgHV1/ClBPnMnH4T9iytJlX5b87/H/2zjxMjqrc/59T1XvPkslMyEzCEpZwRPYtLGFJkEWDBhK8ihEvBlRUFpHhSgQuBK8oW8ANWSVyvT8QZEciKCaAhEjCvnrYZAuTkEkmmZmenq7uqvP7o7o73TPdsySzJufzPHkyXV116nTVqW+d95z3vO9+c6ro0CsJ2hPzZdq2hRP0cHAJWmN548VfF0VUfmbppRxz7ELS6RjBoENnspl/PHF+/vh4vIF4RUN+H9PODQbD0CPYd/JXSKbWs8u2h9PRuY6Hn/kRXz7ytyX7CTgx3ngw2K1fMeNrvyERTPG1GYuwbAGiAzC6tjWSSugFOaMdstlc7kvVTTklsiBaLQ7dzOK/DEwF9sR3U3saOBOYp5S6T0p5MHCPlHLXXsrZC98YHwO8mzXWzwHmK6XOlFJOA3YFdlBKbZBSXgacAlwCnAT8uR9GO8A/gFrg18DX+3FcjxhXeQOhkIVnr+GT9pWsTadJ6AAvv3sfdy3+Nk+98mtOmHpNkbvncVMuzQei219+g5qKySWjOFdX70wwuAtBezItrRlWp1IkgjZeJIRtm6Y3GGjPzwZQPcFi35PCTDklwmeODgEWs474ddF9nDn1aqzsGvUZB/+USKiKJS8u4M6/n8bfX7iahHaZPvUajjv8F9TX+q7sOW8LgL8/fyWJzmbGVGxb9KKvr92TneX3+f6yx/nG03/n4tffYbc9fkQkNKabEfXY8ss4ZPdvg4BMptrksTb0Gdu2iAYiRO0o0UCkm6Zo7ZBMtZT0NPG8DK2JJt5d+Q/GVuxcJm2RxYNLz8MKduTPt0Z0cMYzDzDr8f/Ht59+iLrPfp/auj2prduTA6fdwl6H/ZakiBMMOTy3YkG3NIiHHHopK5ZfjeO0bOJvFrhRh1QkiRt1sO3hT5dp2xZuROBEwI0Io+0GwwjEtgWhWBod07R5YT5p+5S/v3AVdy85g3QmyfbbHEzArWHOYffxlan/R8PYPfP9PcdJldTIDY7mkuee5P0OzQa3kk+TrXh2c591aSTqmWHT0B4Npd+jNJQ5pD8cCdytlEoppdqBw4A6pdR9AEqpfwLrANlLOUuUUo5S6tPs/tUl9lFKqQ3ZvxcCc7J/nwr8fhPqfiEwZSBd5s2M+1aObQsItNOUEPz3yx/Q1PEGDbE4P9nvLBKda3l35ZMAfHX6LWS8FG0dq3n6letJdDbTmW5jwk4n8m77h0SrG4qEfZvJFpmkzSv3uiQ32ESrY+w8M8hlL3zM2pTLFVMnUmdjZt8HGGFptplsscOBIV57JJV3l99rdogNkThfPWoh7R2fEA2PwbaCRIKV/Me0G7FEgLuWfIvWRBP1tXuykzyVb/3zZzQlm2mI1nH53ufBy9fS0dmMEDau5/C5/S8gaEcAmH3Er1j2+i00rX2VvXf7Lhe/uIymjjYAmjrauGD537j5sC8WpcbKucqPqdiW9o5PqYgGs0soDIaesW0L2wnz/L0bl4Tsc1IYCoIfae2RdjvZeeKR7LHjl/Jt7rV/P4xl2VTFG9h54uG0da4kWl3fLW1Ra+fH2YEq3yvFCXr86JlHi9r1xS8t4xf7nU+COi5ckWBVooP6eBNXTJ1AsnMdL714PUd97tc4Tiud2c/Nza/S0vIWRx+zsF/t3bYFa6xmGv+5IP9cLjigkXHUDdtglz+YkeKCpU/R1JGgIRbnyoOOYJwdNtpuMIwQbFvg2c2sTMB/v/BS/ln9yX6X8srLl/HCW3cybZef8eIdLskNGaLVkzh+9s20Wq/yj1d+zeGfuYBodUU3jUx4Dt/77FH8fPlaViXWUx8PctmUKNtXOLgdPcfvGIl6Zth0hEVTtFpM6tpGhEVTD4f1la4r1nYCuo7yCHybVue+k1J2bYSFs+X5/bqQzP2hlHpfSvmBlHI2MF4p9Wx/K66U6pBSngb8EbgXf8BgszBD41s5VrCDDs/OizlAU0eCS154hb13+z4A7658ktaOJu598iyEsIhFxjJz6tVsSHfQuOJafvHe7ew4szgC/a6fs3kp26kGf+Tt3YfSnCG3YVUizbylK3GCZtxooLBtgZNYS2fAZfLnNhrt4F/7V+5zSCQCJHUAT7s8+fIv0YBlBci4KbTO5Gcm9/7s6Vz0yq00ZVPBNSWbueiVW9lvj+9xwtRrCFhhXvv3w6TS7dz71Nnctmg2jz//cw7f62waavckHBmXN25yNHW04WrB4XudzZIXF+Sjex++19l0Oq3Z3K5mxN3QN0Ii1E1fXrrXISRC+X2EsImGxnDo7t8panOH7v4d3v74KWZOvZpYeCyLX72sW1TlfU4K8uTrl2cDMPrvfhevZLsOxXfkkhUJViX8voWvb5+w237/ze57nIolLDo71/H6a7fn02BuSuYEJ5Si8bkFRc9l43MLcEKp/l/AAcIJai549qmid8cFzz6FEzQdb4NhpGAFO/i0o6VsP2/v7b/Rbbnjy/e5uJ0BEp3NBGOiW5ahHWdqOgNe1mjfqH2XLm+jU4dLV6SAkahnhk0nHBeN+8wONxe9R2eHm8Nx0TgAxT8FzJZSBqWUMeBuQGcNarKu8vXAa0AzsHv2uBP7UHaGniexb8NfB/+HTaw7Sql/4K+fP2NTyyjEGO5bOZo0GU1ezHM0dSQIhWoA362609mQd20+at/zeentP2EFojQlm3l1/dtc8v61xGZ+xOS57ezzdRCWKOlaNTZrrK9KpDGDqgODbQtCmZW88adTSaYzrHfckte+wgriYvOc+j/23/Xr2CJIR6qFp1+9HiECeTf6YKg6/zLN0ZRsprpqErFwLR4u0/Y5j8eWX9YtSv0XD7mC6ug4GmKVRcc3xCqxdIZHl1/a7ZiM55DOJGltfR+tVxrj3dA7urS+oAvbjiASqubBpecXtbkHl55PdcV4nHQ70XANiVQzj//rPLb/4lvs880Wdpz5PomAIpFq5oSp1+KlYwDYWCXbNQTzHdccqxJpQrEGnluxgAcfnM1zKxawz75nUpfNnrApEeUz2i35XLq4/SpnIHHRJd8drgm4ZzCMGLROY9vxsv28eGh8ST2tq/wMxx7436QzbejYpxzwDZsp30qx19dcfv3xUwhhl9Q+V9u91mkk6plh07ECYlnlOGvmlFMiy474XvT9KadElg1EYDoApdT9wFLgBWAF8EvgUOAcKeWrwG+A2UopB7gBOFJK+Qr+uvjeZvzfBMZIKcsZ5vfhB8DbZMM9y4XAh5tZBmBc5bd6AsKmM7mGhlixqDfE4jhOS1EAMfA7vonOdXz46XL22f07NETr8sb7d1+aT0O0jt8dcgkV6Rqi1aKba9W6dAaA+ngQY58NDBG7g7ceasRpa0K3fUyL3qHktW/30lSKAHvvfBLBQJT21BraO1bz7sonOWq/H3HclEt5bPllpJ0N+fuaoyFaRzLZzCPLLuCEwxYQDlaWWTvsEcwEuGrK5/nRct+tuCFWydUHHUdUpEseUxGpw3HaeWH51XQmm/vtQmzYChG6ZBtHbPwsRADPS5Zsc7HwWJ546TqO2u+/mHHwT1n0z4u5d9lpfjrDqdcQCdfy1WkLcQsCyIXSVrd2fdWUzxPA17PCDmx9PEhH23tFgeuWPXMZBxzYyHMrFmxSRPmAsEs+lyFsaoSLZ1kksMkMoYu6jSj57rARmGj5BsPIQIggrpso+ay6boJIpL6knrYk3uOepd/P9wNDoRj3PHsGs4/4Dafvuhdr005J7bNLeiAXU07PbHo3+g0jEysglg1AILqSKKUuAi7qsnlaif3eAw4s2HRudvv8LvtNKvi4R6kys9HspwOPK6U+6UMdv1nw97Qu33XgR7TfbMyM+1ZO0BNUC4+fHrA/DbE44Iv5FQcdyvY1O3D0/j/m6Veuz6f1qoo3EI/UcsLU60h2prnhoCv51YE/YY8xu/hrlA48j2AqSspLsc9JoSLXqp1nBrlJfUp9PMgVUycSyhrxhs1Ep3HafANh/TNXUhlLsfPMYNG1322WTTyeIaQ7Co7TLH/zdgA8L8MLb93J9H0bqYuO4+r9f0BDtA7wX6ZX7Pt9/vni1f6M5dONCOz8DH2OnFux63qM0zFuOvRE7j/669x25EnUeXHQZY4BXlh+NWubX90kF2LD1oejnW76ss9JIRzt5PfRnovIBl8spCreQCxSS6KzmcUvXA0aTj5qIf/5xX/wxWn3IMKT0JkqnM7iQIld2/VNh57IOB0jmM5wxdSJ1Mf9GfT6eJArDq3n7ZevKTpvItHEmDG7cvQxC4tyHfeVkBNmwQGNRc/ltfufR+XdT5L52c3o6++gsqOdwBAGhwulBVcedETRu+PKg44glDajsgbDSMFLx9gmVsP/7LdPl2d1KnErwzNv/ZLdZqaK9HSPEz0IdfD1Y+/g+CP+FzewPQ5jOW7KZfzjlV9R6XzCBJr5+dSGYu2bOpFgH/p2pfRswQGNhJze3ewNhiHiOvyI8PnUMFLKJVLKl0r8XpkQ7gAAIABJREFU++5QVcrMuG/lCA0ty3/HhAPmctPh08hoQSq1lpqAg5tJE892cMHv8J5w2ALeX7UCu+pQLnl2A6sSH1AfD/LzqfMIZ/7N+PAY2ts0oCGUYv85IdACYUEy6DL/4AnYAkLpjAleNFCIIKHKBpy2JjpWv0rkxd8QP+RH7DknhPBgjZOhI6aps8ESgtqqnWjrWM2TL/8iPyCTSDZz4Gf+k0X/vJjWRBM7T5zGzQfPQ4sA69YrXnrhClYV5GQHwQlTr+XBpeflU7ttdCvWuK6H7fruxbWVMda0tQGxbsfMmHIZy56+lLXZtb+b4kJs2PpwXa9IXxAaR6eKNMXTaSwh8jPquTb3+SmXIRB8/iD/f43FqlSceUubWJVI5zufpYJnFrZr8Ne9A9TZ8Ntp26HR4DlYFkze+3x4+ZoubTtEKhVlU2ajXVczjjpuPXg+Li4hbCrvfhJeewcA3dKKu/B+4mfO6aWkgcN1PcbZYW6cejQuGhtBKC2MthsMIwjX1VTbtUQ6P+XmQ44gYwewdJplL13OuyufoCrewIGf+QYHfKMB7QosGxLeStLOGDqYwIVPfZLVxnbmT5lIonMdlh3k6UdPpbZuT3629zmEIuOpiNUScLw+Pf9d9czGJuSETWA6w4hBKXUu2Rn7gm3Th6k6eYzhvpVjexG23f1U3v7Lj6nc9kDqDz0TJxQknW7H1S7/+vCvnHTErxHCxraCvL9qBXXbTOPsJ9cUBST58dImbpg+iUg4Rnub74rluh7JXBBHF0hDLnSUWcU0cHS6MSbPWMDbi3x3+dCuJ/LdxR91c1/71bSJVIokrhMiGGgrGpCx7RChQIyj9/8x0UgtXjCOxiIgbN5574G80Z7bX2tBkIl8ZdpCtE4jRBCvl7zUrqsJ2huPsUQQ7SbozLrKxeMNm+RCbNg6KdKXEggRpK1jJbYd4vMHXUY8UoslbCxh8/bHT7HzxMMQCBxRyw+WrOwSXG4lv522HbbrlC2/a11CZGjGYt7ST7Od3Cj/M+UqeP5HdCabN6tt27bACaVIaZcANlEnRpWXIZM12nPollZsb2iN5o2DGQDarG83GEYgVtol8It7qdqhgfSXDkSPq+Kovc9l2t7nYAkb2wrT2vkOqXQbVbGJtHjb0JzRXPPsJ0XaOH95gp/ufz7RaA3xeANrm1+lc8UlHDntWoQzpl+Gt+tq7GQo7xzfk3bkNDCjXQLCGPmGrZcRa7hLKecAF+Pbetcppa7v8v1+wE3Z7z8CTlFKrR/yio5yPC0ILH6X3aZdy4Zql78+fzkHf/Z0kqn1xCJj2WvnE7FEANsK4noZRPVOpMsEY8roEEJsdNO0bQsnGMDVmFn2QcR1NcHwBHY75Ep02Ka1Zgd+sG+GqpBFq+Pxf2828/raTtZ1aoKROJbrELQn8tVpC9E4CGEjRAidiVBbXcWqdCuNz15dkKLlhwD5kfnczLrr6uxa9Nx69N5fol2Pse0YRx+zEN89Pkgm07PxbzD0FS8dIxoeg5PpIJPpJOW0Ew5VYFlBJm83DYsQ6VSYdMAqE2CJfq22dIIB5j3xUVEn97+Xt3Hj9N8S8RIl23ZfNLJc2qS4XYuoqUK3tOb3FTVVeJZZAWcwGIrxLAuxxy5sOHZnHnixMe+BdOLUBVQGx+FkIliihb+u+B+OPPAafrwixX8f1FBSG2urd8HRFgcfey8B4RIlRdoJDdq726SOMxg2MiLf8FLKicDlwGHA3sB3pJSf7bLbL4FLlFJ7A4qCNQiGvpPAxj52KpmARXtqLQfIU0hnOrCsAK7rELCi6HQNqY44KRHjwpdvxhI6v6YpR308iFWwrNG2LZqx+P4TH/Efi97j+098RDMW9hCuv9yaSLgWwcpxsPgN1qfhly+u5szFH/LLF1dzxl7bcPjEClpSLpnsO851NU5nlHRnNU6yglRHCMfxSGpofO7aLilaruPQ/X7M6TMe5ivTFhKk/+tzy+G6mlQqSipVRSoVNS9hw4DhuhrhjqMyug1jq3YkGh6DQLDstZu5a/G3cD3Xn/ERlNSz/gbPdDUlO7lpL1CybfdVI8ulTVpvp7HnzkLUVAG+0W7PnUXCBHcyGAxdSGCTPukQHnjxwqIsGw8sbSSFi+N4eS+6yvgkViXStDpeN208fGIFGxz47pKP+PIj/+a7S5pocqKUTok9MJjUcQbDRkaqFXU0sFgptU4plQDuAb7cZR8bqMr+HQOSQ1i/UY1tC0KRJMHIBqxQK8maAJ3VNo8//3PuWvxtHl1+GUJYPPHSdXjZzi1ARmdoSjazOvkpF08pDkhy8ZQGAgURnZ1ggHlLu7ufmtztg0PG9RD142j/yvHdrvvPljdx5t7bsOjf67sZI7YtCMccQtF2gpENuGRKpmjJaE0mVUW60xjXhtFFonMtL759N56XBgSH7P4t9txxFlr7z0ioVHC5TQie2d8BgL5qZLm0SRkytMUqEGfOIXDhdxBnzqEtVjGkUeUNhi2dMWOCuO7oNxAzrocbsJi+byNfPeoWTjjsGvbY8QSm79uIxiEY8bvQXjqGRYb6eJD/e7OZC7v09c7ZZzzznh7avp1JHWcwbGSkWlETKM691wRM6bLPecDfpJS/ABLAQf05QW1tRcnt48ZVltw+Utjc+mntsWb9O9zzxA+LgjUFA1HikTpaE035fO1H7/9jQsEINVX+Odd2ujRE6/iNuo0fffaHnL9/PdGAIJnR1EZtamOhfB1XJdIlZ5+wrGG/xsN9/k2lXJstxEGXvO6JtMe39qhlm4oQVqUftVVrj5a2D1nf3pzPrz7jyN+WTNESCYSo3YzrNpKv+Uit20itV1/prb0Oxe9LJNfy8r/+wm47HMe9T51dEEjxGiKhCqJZbRujNbccPYm0pwlagpqIjSWKLe7e6utpzZWHb8sF//g4H+TuysO3LXrmCumrRuZ0t9QzWVMRLzo+VPD3aGs/w13fntrrcNdtIBlJv2Uk1aU3xo0bWdHO+9IfgI3X2O/7fcKSFxfkdXDm1KtZ9votvLvySd9t/vDrqIiM48kVP2X+lPOZvzzBTa98yvn717NdZZBYwMLxSvcxBrNv15MG9tQvGU3ta6DZmn97f5BS7ghcrJQ6fQDLXAGsUkp9qWDbN4Fr6Z7L/Qyl1LP9KX+kGu6l5ijy0whSyijwO+BzSqnlUsrzgP8Fju/rCdaubcfzimcOx42rZM2atk2r8RAwEPULRpI88PQPi1ylHl1+KUfv/2Om7HYqDz7trziIR+qordoJJ9NJuu1TvHQMQYAFBzTS+NwCrnrjOr4z+T+pi04kRIBgOsPa5vaNdYyESub3xPOG9RoP5D0eamEs1WYLGTeuEhu35HWvCVtEXP8e5QjHHDQa2wowfd9Glr95Oy+8dgM/2+d8Lnz55qK1ZKIjkI0M339G8nM1Uus2GPUaSe11qK57INzJvrt8mXVtH/CFg35Cp7OB5W/ezoNLz+er039H+5pipzMb/0Wztr24nL7Wt9a2+O207YrWrBc+c0X0USNte6Pu9vWZHKntuhzl6juUbbZcex1N17Iv12uk/JbRcl1z17QvdR0J7bWQwmvs9/3OK+r7PbT0v5i+byPvrnzSd5v/xw/56vRbeXflEhKdzfz8wHnEYtsQIEPcSpJJRhHB4JD37bYGDRxI+vrbjXEPwA7AzgNVmJRyT8AB9pZSbqeU+qjg64cKc71vKiPVcF8JHF7wuQH4pODzHkBSKbU8+/km4H+GqG6jGq3TeeHO0ZpoIhiIEswGDGuo3ZPD9zqbu5Z8uyjVV5CJjPMK0hGJEJ5nk9GggwFCbHQtzbmf5lxBC91PjXPT4BERKa48tIY1qXDeG2JcOEVMJEg5G914bVuQTK3hwaUbg9QcN+VSnn7lel556Rp+d+jVZDQmRYthVGPbEZKpNTz+/M+7tXOt++cK3xf8COtOQZTk8vRFI3PB6ypo4NaDr0KIJFpr80waDIZ+Ua7vFwlVF33W2mXnidP57ORvEY9tR2v7v3nh9Wvo6GzmhKnXEvG2HfK+nUkdNzrQGX1Ipk0vwKUBm6ZApWgUAbFsc8uVUgrgCmAWkMG3+f4C3AyMxfe6PkcptUJK+XvgCaXU77PHaqWUkFLOByYCk/GN9VuVUpcDvwJ2klJeD/wJuAp/DP8NfDv0WKXUW1LKOPAvYLJSqnw6G5gL/A2oBb4NXLK5v78rI9VwfxyYL6Uch39DTgK+U/D9O8B2UkqplFLACcCKoa/m6EOIIFXxhiIBr4o3kM5sDBFwyO7fzrtOgy/mDy49j69MW0i6M4qdDBHKBlaat/SjIvEeo30hdV0vn9vYRJUfOnQmjBZwzfOFOakb8DJQ4LSCFezgwScai+7xY8svY/q+jSx5cQFhD6xOfyDHpHcyjFa05+YHp4CiZUBCDO/rrzeNzAWvy0Wqz+eXp295kg0GgyFHub5fp7Oh6LNlxdh9958wb2kTqxIfUR+PMn/KFbzyyrx8P7DOjQ95364/qeMMQ4/O6ENSTd5Dqxam6jItmkCNmFQ/N/xQuMGaOQDG+5eBqcCeQBB4GjgTmKeUuk9KeTBwj5Ry117K2QvfGB8DvJs11s8B5iulzpRSTgN2BXZQSm2QUl4GnIJvfJ8E/Lkno11KGczuPw1/QOEuKeVPlFK5WYKZUsqXCg5JKaX6tcwbRmhwOqXUSuAiYAnwEnBH1iV+kZTyAKVUC/BN4G4p5SvAafijHIZe8NIxTph6LVXxBoD8Gvfq+ETqqnfj9BkPM7ZyUsmR2VwwJygfWKmlc+OYq+t62J0OoZSD3emYzuYQ0GkFsi/cwvvSRKdVbKSUG32Phcfm070ZDKMdr0w7r6ncHtzhdxPsSSNNgE+DwTBQlOr7nTD1Gl7798MFn68l6cW79SHmL0+w927n5PuBpm9n6EqmTS/IGe0AmRbNqoWpukybXjAAxR8J3K2USiml2vEzjtUppe4DUEr9E1gHyF7KWaKUcpRSn2b3ry6xj1JK5UazFgJzsn+fCvy+l/KPB5qUUm8AS/Fny75U8P1DSql9Cv7122iHkTvjjlLqDuCOLttmFPz9F3xXCUM/cF1dMod3JhUm5WggRDCSLDkyK8RGV+vyqY+0SUY0jJS7L11zUpcbfa+I1uM6FcYFzbBFUK6dWyKC44zszmZfn2WDwWDojVzf7yvTFqJ1GiGCCC/O9H1+zLS9z0eIIF46RrKM7oRCtd36gQZDHpeGnNGeI9OiwaVhAEpPd/m8E91joQl8m1bnvsvOgBdSOFue368LefdjpdT7UsoPpJSzgfF9CCI3F9heSvl+9nMV8F3g/l6O6xcjcsbdMLiUyuFdaKiVHpktnoUtl/ooWJDM3bYtooEIUTtKNBAxOdwHEdu2SLV7VLsBbpy6A7uPjeS/K5WSqtw9Nka7YUsgpz2BTC1zDv8Tu0ycDhS285HvUTJQ+eUNBoMB/L5fujOaT+3qOF7RZ9fV5ft2ZJhz+J8IZGpNf87QHZumQE3xyylQI8CmqcwR/eEpYLaUMiiljAF3AzprUJN1la8HXgOagd2zx53Yh7Iz9DyJfRv+Ovg/9FSIlHI8cCywh1JqklJqErAvcJSUcqc+1KPPDNqMu5Ty31B+EYpSakB/iGHgKDUy66VjRQZducBKNRGbte1+x9l2wjx/r0NygyZaLdjnpDCEUsataoDJXet/3tmZv9aXztyWy978mLUpt2TgmL7cY4NhNFJKe6afdCXT912H1oyadm4CfBoMhqGmlO5cd8RExnQGef7/OSQ3dJr+nKEbgUrRWD83XLjGnfq54eZApWjc3LKVUvdLKQ8AXsCfcP4l/lLqG7Pr0FPAbKWUI6W8AX9t+SvAYuh14OBNYIyU8g/42cq6ch9wC70Y7vhr2xdll3rn6v2elPIh/Bht/6L7GneAa5VS/9tL2UUMpqv8l7P/fx8/NP7N+CMbcylON2sYgbiuxnWjkI0033UMplxgpVzu45AI5TvOAMkNmpfuddh/TogkPQVkNPSXUtf63YfSXHvK9iSsTNnAMb3dY4NhNFJee2pIZjoZLe3cBPg0GAxDTSndqXRtnrvH9OcM5REBsSzcYM2ceHZkwKPKAyilLsKPfVbItBL7vQccWLDp3Oz2+V32m1TwcY9SZWaj2U8HHldKFWY2K1W/BUC39fxKqZMKPv6+pzL6yqAZ7kqp5wGklHt0WYB/npRyeZnDDKOIHlMfaZEX+RzJDRq08fMccMpca+FqbMcxs3OGrYstSHv6k17OYDAYBoKuuqPt6BajqYbBQwTEsmCNOHS46zGAXIcfXO4LuQ1SyiVATYl9b1RK3TgUlRqK4HRjpJTjlFJrAKSUE/AX7BtGILYtiNgdoNMggnS6m+hWKnwX1UKxj1YLEKNjtmtU0cO1HrD7aTCMFrYA7THPrcFgGEp61JwtQFMNhv6ilDqX7Ix9wbbpw1SdPENhuP8CeFVK+Rh+BL9jgR8NwXkN/cS2BaHMSt56qBGnrYlQZQO7zFiAE5jY706jox32OSnMS0Vr3EM4OjVItd96KXetXcshlBqY+2kwjBZGu/YMpA4bDAZDb/SmOaNdUw2GLYlBN9yVUjdIKZ8BPoe/uPAqpdRrg31eQ/+J2B154QZw2pp4Z1Eju866jYQb7eXoYlzXg1CK/eeEfHcqoXG0CWQyGOSu9cGnRkk7Xv5aR0jw1qKBuZ8Gw2hhtGvPQOqwwWAw9EZvmjPaNdVg2JIYzKjyRymlFufC9QPvZ//fVUq5q1LqvsE6t6Fv2LbACnZszOmpdV64czhtTb7rFP3vMLquZwKXDBGu6xGusGhdk9i40UoTjNXScOR5WJFqvM4NNK+4fZPvp8EwkumqZ05aj84Zap0eUB02GAyGHtG99xVMf85gGBkM5oz71/BD8Z9d4juNH2LfMEzYtiDNSh584jxaE01UxRs4ceoCqnc6kg3vPQlAbPyeVB3cyHq7FssWJqLxKEME49R+/pe0ptrpTK3mnY8f4aAjzkbYEUgPd+0MhoGjlJ6dMPVagvbwupfbtoUTDPQvKrwIEqpsKDLeQ5UNIII9HGQwGAybhrAj1BxxNg+uuDSvn1884rJ8X2GTdMxgMAwKgxlV/tvZ/4d9Ib+hO1awI9/JBWhNNPHA0kZOPvImkmveIhCrI3DEVZy7opVViX/ncwjX2ZQU7Fxgk1RrO/GQbYIpDTG2LXASa4kHO0EEcYjzkWMz7+lPsrlYq5k/5XyefesajtrnguGursEwoJTSsweXnsdXpi3MpjwcemzbohmLeU98VJSHvZyG5uh0Y+wyYwHvLCpeb9rpxhjIVHYmAJ7BsHXQ27Pu4PLnrNEOvn7+ecWlfHXawk3WMYPBMDgM+hp3KeU2wC+BY/Dn+RYBjUqp9YN9bkN5tE7nRTpHa6IJVwh/XZMd54wlTaxK+FOzqxJp5i1dyW+nbYftOkXHmWBKw0vu+r9RcP0nzr6TeU+vLrp/85cnuGzfOXjG5dawhVFOz/QwtnUnGMh3dqFnDS3EdTVOYCK7zrpt0Ixqo9kGw9ZBX551r4x+ejq9yTpmMIwGpJQ7AhcrpU4fgLLeB6Yppd7vsv0JYL5S6omCbb8HnlBK/b6/57E2vYp95hbgPWAKcDjQAtw0BOc19IAQQariDUXbquINCIIknChpHcgLdY5ViTQeUG1raoRLta0J2BYRuyM/OwQbA5tE7I6h+jlbNaWufzK5oeT9i4THI4zLrWELo6ye9aGtB2yrm6YNBK6m5DPY1S4udX7X1SScKIl0FQknOuDGtNFsg2HroNyzHrU78roTFIGS+hkUATR90zGDQaf1Id5a9xnv08y/vbXuMzqtDxnuOvWBHYCdh7sS/WEo0sFNUkqdUPD5fCnlq0NwXkMPeOkYJ0y9lgeXFq8J9dIxArZAeC718WCRYNfHg4Q8F339HWRaWhE1VVTOnUW6ImOCKQ0jokQwK93xKfXxqm73rzJSjZcWDKTLrcEw3PSkZz219YBtUdnRjrvw/iJNa4tVkNlMN1BbUFJDbTE05+8REwDPYNg6KPOsC89BX38fmZZWgnvswoknLOCBZxo3xjza7+cEbvsrwRnTe9Uxg0Gn9SF6Zeah1G9a6nSzi6izJ4XPqnmIiYGZIiiWbU7ZUkoBXAHMAjL4k79/AW4GxgIJ4Byl1IquM9lSSq2UElLK+cBEYDK+sX6rUupy4FfATlLK64E/AVcBNvAG/mTzsUqpt6SUceBfwGSl1LBGaRyKGfdPsq4IAEgptwWaetjfMAS4ribIRL4ybSGnz3iYr0xbSBDfdSqOS8W9j3LlvrXUx/0Zq/p4kCunTqTi3kfRLa0A6JZW3IX3Y4mAHzypABNMaegodf2Tb9zBlVMnFN2/Kw6bQMSzjCusYYujJz3riTgu7sL7u2laHHez6xRKZ7hi6sTiZ3DqRELpzJCcv0eyAfCK6ms022DY8ijzrItPN2zUndfeofrBN5gz7Ta+ffzDfO0zV1F1z8vwQRMVi5Zw5X51PeqYwaBbvQU5ox1AN7ukftNSp1u9BQNQ/JeBqcCe+N7bc4E/A79SSu0F/BC4R0oZ7qWcvYBjgYOAeVLKMcA5wHNKqTOz++wKHKWU+gZwO3BKdvtJwJ+H22iHwU0H9zD+VMc44CUp5eOAC0wHXhms8xr6juvqbOCm3AyL38m1PA/vtXfYri3BTcceQaZiDIH2BDXCIfPaO0Vl6JZWAl5kSIIpGUpjexEmT7uct5+4KH/9t9v9G4SdBDftEiQzcVuE8LMCpB0TTMawZVJOz3rC8jwy2c5rDt3Siu15+IPum1Mfjzobfjttu7LRmAfz/D0xVAHwDAbD8FLqWZ88YwH6zuVF++nX3iEy8yggTOaG/7fxiw+a2O6eh7n5tP8gpYWJKm8ojasbckZ7Dt3sgqsbyhzRH44E7lZKpYCUlPIw4MNcWnGl1D+llOsA2Us5S5RSDvBpdv/qEvsopdSG7N8LgceBS4BTgQs3sf6lHhZRZnuvDKar/D1ltj+S+0NKGVdKJcrsZxgmPMtC1FShP2ii8pa7ABA1VYgzv+ZvL+hoipoqPC3ywZRs4eJqE1V+KPG0ILD4XXY7+GfoWAjR4cDidxAHRql6YDHizDlscMVgz+EZDKOOvNZ11TTLYiAeGNf1sF0nb4J3LXKwz1++XoMfAM9gMAw/pZ71AFF0a6JoiC6vO9m/izSpNUFV2mGD6/vHm76EoRu2aBJ19qRC413U2WCLgfCw7prAeCd8w7cQgW/T6tx3UsquLmSFs+X5/bqQzP2hlHpfSvmBlHI2MF4p9ewm1B382G5jumzbJru93wyaq7xS6vae/mV3+8dgnd+w6SSwsefOQtRUAb6I23NnkbCDpbdj54MphasaBiWYkqE8CWzsY6fCvc/Arx6Ce58hcNj+ZJa/lr8/BoOhO2W1boiemeE8/2AHwDMYDCODrs96wrXK6s5wa6JhdCKqrMbwWTXNos5vJ6LOJnxWTbOoshoHoPingNlSyqCUMgbcDeisQY2U8mCgHngNaAZ2zx53Yh/KztDzJPZt+Ovg/7CJdQf4O/CfUsoAgJTyM8ABwCat/R+K4HQ9UTa8hZRyDnAxEAKuU0pd3+V7iR+goAZYBZyslNqk0QtDMRnXoy1WQfycUwi6Lnga1/LXRrfFKoifOQfb8/AsizbswQ2iZOiVjOvRUVlJxVlzwHXBsvBsGzHraHN/DIYeyGvdMGnacJw/YFvEcf0lUZZFwmiEwbBVUa6PV/Sd6ecZ+oEIimVMDMwM/7h2Aa5uwBZNospq3NzAdABKqfullAcAL+BPOP8SWALcKKW8DEgBs5VSjpTyBuAuKeUrwGJ6j6n2JjBGSvkH4Hclvr8PPztaXw3316WU+VFwpVQFfhC9nYGXpZQe/qz+HKVUcx/LLGK4DfeSQ/xSyonA5cD++DfkGSnlEqXUG9nvBfAQ8AOl1KNSyiuAecAFQ1PtrQOrLUE6GzipMNqx7y5lZ/2ljJgPNwHbItbWVnSv7LmzSAx2ZGqDYQsg43psYPg0bSjPP2xR7A0Gw4ijXB9vuDXRMDoRQbFM1NqHDkbZSqmLgIu6bJ5WYr/3gAMLNp2b3T6/y36TCj7uUarMrK05HXhcKfVJH+o4qcz2DNCY/bfZDLfhXo6jgcVKqXUAUsp78KMK/iT7/X5AQin1aPbzz+i+fsCwGZSNdnzmnKygg21bRAkhPIG2NEkctKepsCNF20wQk8GlL/cK/PsVs0NYrgWewLM8OkiZ+2PYIimlT5vT1ge6vOGgr1phMBi2bMpqwTnfwKXvfbgtQRcNhjJcB3wJ+EJug5RyCb6nd1duVErdOBSVGqmG+wSK3Rua8FMA5NgFWCWlvB3YF3gVOLs/J6itrSi5fdy4yn5VdKjpWj/taWhP+C7Stg0VcYS1+R0w3bKBVIloxyHh10F7GmeVR9OtKTItmkCNoOH0CE7GZfWN6Y3bvhUhVG8NSJ0GipF+j8tRrs32dq/AbydOs4u7VrDqzuJ7FmoY/Pszkq/5SK3bSK1XXynXXnMM5u8rqU+boUXa08Q7I72WN1h6vCmUur590YrhYrjP31N7He66DSQj6beMpLr0xkira2/6mqOw3oX6pD2N01ULKuPQFmb1bU6fdHOgdXagGWn3bCjZmn/7QKGUOpfsjH3BtunDVJ08I9VwL/XEFw7hBfDdGY5QSj0npfwf4Frgm309wdq17Xhesaf+uHGVrFnT1u/KDhVd61fo9ljoIj0Qbo/VtigZ7TitYcOaNirsCKtv9Q10gEyLpul3KcZ9OVS87dYU488K0u4Oe+pDYGDv8VALY6k2CzCmzL3KaFif/a0VdgSvWbDmnlS3ezbY92ckP1cjtW6DUa+R0l5zdRnM615SnzZDi2rC8XzntFx5g6nH/aXc9e1N14eLcvUdyjZbrr2OVI0oRV+u10j5LaPluuauaV/qOhLaayGF17irPgW/dVLpjRdGAAAgAElEQVQ3LbCOPZpPskY79K6bA62zA8loaV+DQV9/uzHuRyeDbrhLKYVSSnfZVpMNJNde5rCVwOEFnxuAwvUFq4C3lVLPZT/fSfn0c1ssg+n22GkHqPjeV6EtgW7v8COUHzeVNmzAQ3giL9Y5Mi0auxLq54YJ1IAVFLidfjZi27aM+9QgoW2LwNdmkLlz0UaD4ZsnIATUCBfPstBCYNdZjJ8Txu3QtL+eoWL3AHZMmPtj2OIop0/C67su5l1AhUBnYPycMJ7W4IFlC9wOjSgorjc9HglB4RLYVM6d1X1wIavrBoNhy6SrPmX+9ky+30BVnMAxh+JtM45MS6rouJ50s2w/0LOpsCN5t/lQKEDUDYEnwNIkbQfHyQzODzUYtnCGYsb9efw16YUsBT6rlDqizDGPA/OllOOABHAS8J2C758Bxkkp91ZKvYy/BuH5ga32yMfyPDIl3B5tz4PNSN1RKthZYO4sEpWVZBw/R6O2fLeoQtGO7W6BFrQudxhzRIhVCze6T9WfFoG4RmuzBmqgsdIZMo88SeDEoxCxKJ72EE6GzG/u8O/f7rugjzuBpts6ybRoYrtbjD2u+P6MPy1MMmbWuxu2DErpU6DGX4OZS0Lc09pM27aIdoRpeTTta9kfO7GrBLXHh/j0rkJdC2PH/EGvnvQ4YAdHRFA4EzF6yybjpphydvmuUMZNlf3OsGXTVZ/0B01+v+GcryPaOkgvvB9xwhcJ1IztUTcLKaezzicezQ+kGX9amExVhuCGIJ8U9gfnhqEKY7wbDJvAoOVxl1L+XUrZCuwlpWwt+JcA1vV0rFJqJX70wCXAS8AdSqnlUspFUsoDlFJJYBZwi5TydeAoBiha32jCs6x8rs0coqYKz9q821pq5iiz8H4i7kaRTeIw/rQQgRp/JDZQI6ibGWbV71NUTQny6R+L3UpX3ZYi8xGs/k2aaEcY2x60prfV4VkWtCZIL3wA5/o7EckUmTseyd8/cdhU//pn70fVlGDeaAf//qy+zSFKaNh+g8EwkJTSp/GnhUjiABsN89W/SfPx5aluuhQlxOrbnCItqzkqyKd3dte13HPTkx6XnY0v1RseZDKuxwZX0KJtNrjCGO1bEAE7zDV/3K/sv4AdHu4qGoaJUvpEawJcLz9J4y1eQv3JXlnd7Eopnd3m5DAti9P5fkUkE+rW31i1MEXMNf1Ag2FTGMwZ91nAWPzk9XMLtmfoPa8eSqk7gDu6bJtR8PezFAes2+oYLLfHvszku65HMpZiwlkR3HXgdmi8lPbdpGJl3Key21ff5lB/Vpg2kptcR8NGurWDiljRujWqx5Jp2fjiLXd/+uNGbDCMZFzXw6lMM+GscJF7puv4upgzzLsOXo0/K0Q7nXkXULtq47PS23PTkx5XeulB8Y4yGAyGvlBOn7SnN/YXPmyCRfcz4cTpiAn1ZCxNsofMM7l+4PizQtjCghS4nVBzVJCWxWlSH3hoj5K6qTMQdYynn2F4kVLuCFyslDp9AMp6AtiW4mXgtwCPAG8Bb2S3WUAVcLtS6tL+nmfQDHelVCvQKqXUSqkPBus8WzOD5faYG5ntGsDIs6widynX9XBtj9V3+KOr218QIVDjr/0s5T7ldmzsJFuuZdZVDxC5djDmB6fgOhm0VRyASnRxZyt3f8q5wxkMow3btgi1BfnktsLlICHcmIfrlo/RkTPCcy6gdoT8s9Lbc9OTHnt23zTVYDAYBoNy+hTHLdamD5vQD/4ZzpxDu9v7YL7reiRth1gikvfsy828r3/KQViU1E284sFSg2GY2AHYeQDL+5ZS6onCDVLKScAnSql9CrZNAN6WUv5RKfVmf04wFGvcq6WUcaVUYgjOtdWRcb1sIDo72wHcfEM4aQeJfW8uuq0T2trQK5YXBaYr2heH8af56UO8tM6L9TYnh/MupjkRX7vIn/UN1AjSazyi9eUFeyQEchpNZFwPxlTgrW/D8jyC3/sq6QeXoF9/B93eyjZfq8m7+bYuT1M/N9wlBkGYDvPyNGwh9DajXm5tpm3DGB1BC/+Z8DI6r2Uti9Ns87Vw/jnKDQY4dppqtK9VaF+rtCjSYxMUzmAwDDel+osJu7Q2ddgBqslgCYHWETzPwrO8kjGKooSKluNlWjSf/jHFhO+H8QJe9/7G3DDrlqSNp98Whk57h+i29AJc3YAtmkRlsFEErWWbW66UUgBX4HtyZ4CbgL8AN+N7dieAc5RSK6SUvweeUEr9PnusVkoJKeV8YCIwGd9Yv1UpdTnwK2AnKeX1wJ+Aq/Dd4N7AD5J+rFLqLSllHPgXMFkpNRCd5Qb8DGr9Tn0wFIZ7B/CBlPIVCtwHlFIzh+Dchn6Sm6laeZtDpiVAoGYs9afNJFGZJlMikEjOJXXi923QmnWPpamaEsSKaiZ8J4zngF0hWHNfitQHXpERP+6UYMk6FKYtGc5ATqOJgG2hV61B/+6+/DULzJ0Fsz6HXt+GFXEY9+UQwVqL9FqP9U+nqTsxhB0TeI6GSp13IzYYRju9zagXDjhuHLwK4balWfV7nQ/iOG52mHWPpjY+K1qzzZwQgTEWruXi2Gniba29apUJCmcwGEYipbSpww4Qa2vDfWwpmcOPZdUf0z0Gsi2nt3QksV2HTKyKiWdG0C7gadYtSdO+3DWeflsQOu0dops6HnJueqtOr00hasOTQmfs+hANsZkDYLx/GZgK7AkEgaeBM4F5Sqn7pJQHA/dIKXftpZy98I3xMcC7WWP9HGC+UupMKeU0YFdgB6XUBinlZcApwCX4QdL/3Aej/VYpZc7WbVNK5TKkTZBSvgREgDpgBTBLKfVxH69BnqEw3H83BOcwDBClZqpW3eYw/qwgDqUjgEbdNN4Nd6Ar44ydMYtVf9TF7qkBj+pDg9RM893l1y5ycFt1WcEezDR3WypxXNK/u69bQMHASceQufVe2L6B0Mn/gZsOYFcIOt/2aF+e8g2Wb4Yxs36GLYneosoXrs0UnsC2NHr9ej75v1j+mI7XPdaQYuznQ0UuoONPC9FuJXFdj2p0n7VqMLyjDAaDYXPpqk3VZHCzUeab/miV9VzKUU5vWd+C++Cfsc75Bi4hSFrdtDSJyXSwJaDb0gtyRjuAXpvCuemtulDj7gvE2PChm1n8kcDdSqkUkJJSHgZ8qJS6D0Ap9U8p5TpA9lLOEqWUA3ya3b+6xD5KKbUh+/dC/CxnlwCnAhf2oa7dXOWzfKKU2kdKaQEL8AcRFvehvG4MuuGulLq98HPW5WGXwT6vof/YtsAuE0jE1v73rqu7HWd5HpmqOOKYvdGVzUw4ow6SHqIqShspyEC0KszqPgr2YKW525KxbHC/NwNsEC7ov7+GXrUWtz4KP5iJSDi4TyyBqcew7q+OP4NYIbArBOv+7jDmmKEYwzMYhoZSM+pdNcd1vXzns8Zz0Z7dTfs6XvcYe5Jm23MjZBwvmzZu42zT5miVbQsidgfoNIggnW6spL72twwAJ7GWeLBzk8s1GAxbD111xPLCvgdRLF4mTzvEQ8m8tjh2mvrTQqwq9GA62cNbtARaWrHTaTZoDztm5QdLu2qpYZTj6oac0Z5Dr02BqxsGoPR0l887QbdZPIFv0+rcd1LKrm69hbPl+f26kI+arZR6X0r5gZRyNjA+GxR9s1BKeVLK/8LPmHY+8PP+ljHovXUp5RnA1UC8YPMaoH6wz23oO7YtCGVWkmxzCdRM6jZymlz/NqFKGycwsVsn0AvauLP25u3FF+K0NRGqbGDyUT8jaO+Imw1mXji71Ztg9zU4nsEnFLJIpT7k7UX/lb/+u37pV+jOJP966Dsb78m0ywnSTvWhFVghgduuaX4o6/1wnHFXM2w5dJ1R74vm4CQI1IS7z9JrTaDKomVNotszsqlaldPbtx5qzD+fu8xYUFJf+1PG5Jm/Rmcc3tiMcg0Gw9ZDSR2ZsYDAHrtAR2lN7Fj3Ou8/czG7zFiAG94WO/URH750C9ucfArByHiC0Uq8v/8DPmwq0sPCwVLT39jCsEWTqA1PKjTeRW0YbNFrFrE+8BTwAynlDfiu8ncDWko5u8BVvh54DWgGds8ed2Ifys7Qsy18G/46+F9vauW7opTKSCnPB/4kpVyolFrVn+OHIoniPOAY/HD4++K7HNw/BOc19IOI3cE7ixr5+PmrGPf1ZFFeznFfT/Lx81fxzqJGf1S2Cy7JvNEO4LQ18fbiC3EL0r25rke720mbTtLudvY4yprAxp47K59zNBcsJWFm20sSFm15ox386++0fcLbf7ug+J48cRFUuVhVgtV3pFi1MIXbqnvM02owjFb6qzlWbZj6r+kuOYzDPT4bm6pVOb0tfD7L6Wt/yki3rtzscg2jl5TrcP7JL5T8d9qXHhnu6hlGIKV05O1FjYhZh6JXLO+W133c15OsfOkXeW0JizbeWdTI+n8v4a3HTuf1B7/IG4+cjNhroum7bUWIymBj6Ixdm0Vt2P9cGyZ0xq7NojLYuLllK6XuB5YCL+CvDf8lcChwjpTyVeA3wOysG/wNwJHZuGpT6T39+JvAGCnlH8p8fx9+ALxy328SSqlHgX8CP+3vsUPhH7tOKfVsdlH+eKXU5VLK54fgvIb+oNNZg6+J959vZOLJ5xII1xGMV/PO4kYSq1/N7wfR4kOzxxbitDWhS+zbF0wgp37iZbpdfysYLXlPXJ0iGes07moGQwEZ16MtGCa+DUw8K4j2BJ4FHfRs8G+yVpXRzFL62p8yyj33/SrXMGoJ2yH2f/hrJb97/kt3DnFtDKOCMlrkCg971tHYQmc1EX+m/flf5PuDvrZ07384bU3oCbVYZ84xfbetBBG0ltEQmxlq3H3Ao8oDKKUuAi7qsnlaif3eAw4s2HRudvv8LvtNKvi4R6kys0u7pwOPK6U+6UMdu9Unu/19YFKJ7cf0VmYphsJwT0spa4C3gSnA34CKITivoT+IIKHKBpy2JhKrX+Wtx04nVNnA9odvNNpDlQ0gSkSCLzg2R9l9+4gJ5NQPrEC36++lkyXviRYB465mMJQg43pscIF+PhubpFUDoZklyij33G+OFhsMhi2YMlqkRYAN+TzuncRDSd5/5uIS2tK9/xGqbMATQdpcgem7bT2IoLVsAALRjSSuA74EfCG3QUq5BKgpse+NSqkbh6JSQ+EqfzPwZ3xX+TOklM/h58IzjCA63Ri7zFjgCzFk1zldzZo3H85/3mXGgnzwo96Oze1r2xYVdoRKEaXCjmDbQ9Hkti5SupLJM64uuv6hqglMLnFP0lSY+2EwwLBqU0+auTllBKsmbna5BoNh66GvWlSyjzjzeoRbx2e/eC9yxh+Ij9/TaI5hi0Epda5Samel1FsF26YrpfYp8W9IjHYYmhn3hcBdSqmElPIQ4ABg+RCcd1QTsC3iuFhZ98vBXiPkuhonMJFdZ92WjyyaJs52h89ju8Mae4xOXHisLVxcbWdFWxDt6BrZuXsOUMPm4bkQjG7HbrNvResMiAApXYmL7nI/Kwi1hcz9MGz12LY1rNpUSm/7G/29XBkE4LP/cTuZ9NBFlS/1vjLusQbD8JB7HnXLBqpt0ePz2Fct6rqfsKLQWkVTXkMnsfNpt6Cr2khmQiYYpsEwSAyF4f68Umo/AKXUSmCllPIN4LNDcO5RScC2qOxox114v5+So6aKyrmz0GMGZwRzY6fLxSNCgnhW5D0cokAU2xZE7Q6ElcYSASBGwrXyLwPX1STcKOPGVbJmTRugqbDD3XLCl8oBath08m3lsaUEDt8PaqtxAw5h1qPtIMmCF3CFHTT3w2AAooSG/VnIaebGtefFHd2uxnCnHSDiZroZx6XKCMVr2bCmDQDb9lM3bU7auZ4o975qi1UY491gGGIKn8dUH5/HrloUsAXVttdNa1xX00mMiN2B7cb4pIuGrrotTf1ZVbhusuR5DAbD5jNohruU8u/4AQJiUsrCRLc28OJgnXdLII6Lu/D+fIoh3dKKu/B+7B+cstlll+oMxtraeux05dKFqMJ0IUf9jMrwBNqC0bIvA+GJkjlAhVcqdaJhU4jj+kb7tAPJPLmCzFE78/YTFxWldQkH6/G0QHuWuR8GAyNfm7oZw7vvQsVxh5J+7BnElD0IVMSorozTHgqTcsovxh+ItHO9Ue59FT9zTnbtv8FgGCr68zyW8+wsNxCn0Xk92WX6jWRaipf6Zlo0tqsJ2JYZtDMYBonBXNQ3C9gLP//engX/dgWOGMTzjnoszyvKCwy++LKZQpjrDOrr7yDzs5vR199BvK0N97Gl3UW+IDJTyXQhiy/EXb+6aL+uaGtjaqV8HWr8SOaGgcHyPAJT9iBzxyNw8C55ox02pnVxmz5AX38HFhlzPwwGRr42de18B6bsQfqxZwgcvj+ZBxbj/PoO0jfcRbytjUAPa/MHIu1cb5R7X1me6bgbDENNX5/HUv3Byo524rYubfjjFulJJtVcWkPXNPfYLzQYDJvHoBnuSqlWpdT7Sqmj8FPCfQA0AJ8Dk9SxJzzLyucFziFqqmAzgyeVGonNLLyfwJQ9inesihNAUyNcqm2NKJfuLWz32DlL4jD+tFCXvMgmZ/hA4lkWoiIGVXEYP6b0fYqF0C2teA8+Qr25HwbDiNembp3vMVUEjz+CzF1/6abfPXaSe0w7NzCUe195lgl8aTAMNX19HsvNzAdct0h7xA4NBE48ioDnYhXoycqXfsG4ryeLNLT+ZA/vr4+bQTuDYRAZ9DXuUsrLgMlSynnAg8Dr+DPu3xrsc49WEthUzp2VF1VRU4U9dxZUxCHVvsnlWp5HpsRIrKjYuHZe7NBA4PgjSV9/58Zzn3WiH7E4VkvD/t8kEKnCSycRBPyXQZl+o+t6JGMpkzN8EElgUzWmksDxR5Jpbit9nzwLDejX3yEwO8n4syLmfhi2aka6NuU637oqjjj+QDIVGYT20FVxKNBw3dKK7XmUHQsfhFSdXSn3vmrDxqSCMhiGlr4+j+X6g3ja156WVr8/+IWNA4bijOOL0ga//3wj2379R0QrdwadxvOaEV/YDy9oM0LGQA2GHpFS7ghcrJQ6fQDKeh/owG/9QeAD4FSl1Bop5TeBa4EPuxx2hlLq2f6cZyiC0x2Pb6ifAdyplDpXSrliCM47qihaa4Smo7KSyJlzsLNrj9qwqbE2b71gvjNYOJpaUwX/n713j4+rrPb/38++TCYzmUnTCxBRCtiyf0AFD0irxUIprdgWaEKBmgJCELnYn+g5iCJ+9evxHPAG+v0e5SK34lGpXFMuba2Fcim0UA4onKJn0wqiQoBe0mQyk2T25fn+sWcmM5k9SVrSJG2f9+vFi2Zmz97P7Mua9Txrrc9KxAuvG3Om4y5bWbIKS8t6jmj4GW5mO288/t2S+mlX1/tN4Vc9w/csrucjDQ1v2UpkMs4R59yI66dKr9Op30efWI/oSONLSaenrodC0dc2GbpGrS5HhTJ6Gp3EpWfT0/MOm9d+rfdZbrwevQV4K5iIFyJpFZ7lfAunfHpraaumoSkLcD2fVKyGeJ/fK1XjqlAMP67nk0kkiC9pQvgSqQnSuonbRwujkj/oaRp6buJvzJpWmuXzu5eZ3Hg9m9deSzbVipPZhjmmGqdrM5sfv6bExuhDqKOh2DuQrvcp2dF9I56sRxetIhm9Shj6hpEe1wBMBD46hPubZ9v2XwEsy/o/wNXA13PvPWLb9kUf9ADDMXHHtu2MZVmzgV/kXqoa6DOWZS0G/hcQAX5q2/ZNFbabD/zctu3Dhmq8w02YKm8sLxAnRc4pG7wTVElwROBhXH4ucmsb7pr10JFGv/QcPF3HvOJzoAmkEOX1UZu2YJx9Iq8//uWy+ukjGu8im1Odj+oZejo6iUf0YWlBpAiuteb24CXjGPNn4NVU8fpDffQInvgmRy78D8zYOPA9xuoaad3sV9RKoRjNDGX7MUPXiOsSI9WJs5vK6IXxCBBSIn054Lj6+w6u5+NEfTavurZMW+TIM3+C/NlyxJRJiMbpeCJFXB9cC6c91R7O9fyc8JW+y79XCoVi6DB0jVgqhVsUcY83NxJNxNF8v2CfJBrapefg3XZ/WWRez038EWB+8Wyk7+GZDn5PF0a3x1EL78b1ekCYCAGvP/rlMh2NoxrvBKpVa8j9BOl6n5KtHY9k71g/Xu7IIMbGDo1cMv0R6pNnftDJu2VZAvgBgXaaSzCXXAXcBowF0sCVtm2/aFnW3cBTtm3fnfustG1bWJb1XeBgYDLBZP0O27avA/4DONyyrJuA+4EfEaSw/QmYAXzGtu3XLcuKA/8DTLZte8DWM5ZlaUAit58hZTgm7tsty7qZoH/7OZZl/QB4p78PWJZ1MHAdcDzQA6y3LOtJ27b/1Ge7A4EbYO+Wrh1KVd7Q1jyXnoNwXNylLXi518zmRtzaGkR7J95t9xdeN5obEUdPQr62pbBPcfQkpFe5VlLXY3tcuVj1CQ4njoefSqOfNZseuRW/0w+/TvEIzs97yx9qmhsgkVSTd8Vex662H+vPduT3JTo6cR5cU9EGS19WjMYXt2QUM47vTSvtZ1yD+Q6yUn36mBjGNRfTw3Y2P3zJgDZ3oLZzCoVi36GSlpF+3nyE65fYJ6O5EXHl+eiOW8iUAYKJ/+rnMGYcj/PsS0G3mt/3dqs5Yt6NRKrqyWBg+m2hdspva0P8qkW1htxPkB3dN+Yn7QByR4bsHevHR74y80YxNj79A+7+bOBEAoFzE3gWWAJcY9v2Q5ZlfRJ4wLKsIwbYzzEEk/ExwF9yk/Urge/atr3EsqyZBALqE23bbs+Vep8PfAdYCDw2iEn7SsuyssABBMvY/1r03pmWZf2x6O8e27anDfTl+zIc6jGfJ5ioz7dtO0PgNVwIkFvBCGM2sNa27R22baeBBwguXF/uoPSk7JUMpSpvmNEW23cWVl/zrzlLW9Bzk/m+Bt48Y2ZB3ETUJTHPmAnvtwe1kUXkayWr97BycSX10/7UlPcXNN9HCIGX2cHmtdfidLWFX6f32/tc/+XEvaETqFIohouKC50h+eID2Y78vkRVpKINNnQN+e7WAfdhzDiuTDyu0rgG9R1y9enF5J9lv8pj8x5Wi1coFHsfFf3JmniouCWeT5vUafcEruf32rOpU3DvXRXareb1lVfh7XiXmlQHmh5up0Qm268NVOxjeLI+P2nPI3dkwJf1FT6xK5wM3Gfbdo9t253Ap4Hxtm0/BGDb9vPADsAaYD9P2radtW37/dz2tSHb2LZtt+f+vRRYnPv3hcDdgxjrPNu2P27b9ocIsgRW5zIGIEiV/3jRf7s8aYdhiLjbtv0e8O9Ff3+z6O11wHEhH/sQULyE1wpMLd7AsqwrgZeB53dnXOPG1YS+PmFCYnd294GQHZ14IbVGesRgQrJ0nAONT7a109PHaFdySoUvw9vOdXVhNMxCHDge+d42yHQFtU0LrivpEX7EvBuJ1ozD6WgNXXHVhTck51N2dJINcXLHfOV8xNhd3/9IXOOhIOyelR2dyFg1Uuskm2ql9aW7OezU7/DmE98ruU5y2cbSz+Wu/3Cdi9F8zkfr2EbruAZLJRubZ3e/X5iNk20dRET5PgeyHfl9yUxXaL2nHjEYgyR750P97iObjCPGJELtaei4BvEdpIxzxLwbeb2oPn3yzOuQD78MF84a0ObubffPSI+3v/t1pMc2lIym7zKaxjIQo22sle7XSv4kMtzfiwgYP64GOtPgeUhfkm3rQMSqg+3jkfDMn9pqnJb1GGfPZvLMUt8wsFOvlBxjJM7faLtmw8mwf3ddtIqxsUOLJ+9ibAw00drPpwZL3yjT4ZRnWguCOa3Mv2dZVl8V1uJoeWG7PnTl/2Hb9l8ty3rLsqyzgAN3VUQO+DXwc2DcLn6uX4alxr0fKuWBh71eCD9bljWFIG3hVODDu3Pg7ds78f3SlMEJExJs3Zrand19IAxdC1UB3ekK3KLxDGZ8tbooc0BlTzZclE4r31bUJZEdaZylyzGbG3CXr0Vvmos5ZzqmHuOo+bfi93Qh0llE1Ydw29OwtT1UudiT+pCczzrhhf7geFmXtl3c/1Be4+E2jGH3rKFr1JoGYqdHJFFP+r1N/GPDTRwy4yrM6joiNQeh+9V4HemSBFlRl0RqYlju95F6rgbDaB3bnhjXaLhfi8eyu98vzMaJuiSOhPY++xzIduT35a59AWPR3JI00rwNTvjOgPsw5kxHbts56HEN5jsYukaiqp6jzrwNKV1oyyAffhHRkUY4sl+bO1rv60pUGu9w3rOV7te96VwO5nyNlu+yt5zX/DkdzFhHw/0a5k8aTfOQ7alQm+NKEO+8X9jevGRhsF1uMZN0NrwzxdYOjKlTEI6H8coOjpp/K9IUCBfkE68giwQ0w2zgnmZvub/2BIP97kN5v4pk9KrIJdOLa9yJXDJ9m0hGrxqC3T8DfMWyrFsIUuXvA6RlWWcVpcofBGwCtgFH5z7XMIh9u/Q/F76LoA7+Z7sx7lOBv9u2vc2yBkoGGDwjnWtcqdjubYKLkKee0rr4c3Kv/RewEviQZVnr9sgIh4G8Kq9Yshjj2ksRSxbvdk1QGh29ubEk1V2OGxPUMhW9ZjQ34qx7GWPR3NK0+AsX4K4NFpXctS+gX7QAoem4D67B+emvkLc+htldhT7mINKeFqRl/e5lJs+8rpAulVecD5SLPziqT3BlXM/H03WM2gOYPOv6wuT9b+tuRMsKeGA9oi2F8cWFpde5uYG0PnQtoRSK4SLMxunNjQURzmIGsh35fdGRxl31DMbCOUS++UW0JYsDZWY8NAic2Yn1FfchJtThrllfbk8rjGug71Cogf+Pe/D//ddw80oMvxpRE8dYNBe59tUymztpCG2uQqHYOyn2J6u+fTnaksXIRBw3xN/TmxuRulZStuOuWY/RNA934yaMRXPh+S0cMfeGUv9u5nXI372MqIkhTQPz+KOQtz6G/JOTOfsAACAASURBVN5vkLc8inH8FMTE+n5ts2LfQhj6BlGfPDPylZkbqv733L9GvjJzgxgCYToA27ZbgOcIsqxfBP4vMB240rKs/yaIap9l23YWuAU42bKsVwnq4geK+P8ZGGNZ1q8qvP8QgQBepff7stKyrD/mxnUt8Lmi987MvVf83+cHud8CQsqRE6qxLOtl27bLUuVz4nTPEqTHp4H1wKW2bW8M2fZQAgXBQwd52EOBN0dTxH2wDHZ8lVTli1/TBLj/dmvQp3PWtCAtKtMFBx+IW9TD3fzS53Bu/m3ZKq22ZDE7PcEYXeLfdE/Qb3jOschYBCE1jLEHIZ2hEZIrFnIqUT/djcWNIY64D5co4qFUuGchd350H+G6eEYWv6MdkepGrnkF3moNFmrOPx1RHQVNA0OncxhV5UfzczVax7aHIu6j4n7NjeUDfb/BilVWsh2ZRIKo5wYLj5qG1DW0nEBT3l72/ZzRNA93xdNBN44+9idvB0nGe+1pTxbv4ANpz4afg/6+Q60ukTfdU2Z3zS+ejXPvqiCaNbE+sLkfGoffRy1+tN7Xlegn4j4c9+yh9HO/7k3ncsKEBMc/2hT63ktnLANUxH1X2cWI+4jfr33Gw9atqX67XiR8B/f620o+JybWY15wJr4QCClBF7jv/h1ZpQe162teQXSkMS87F7mzA/fe35XbqiVNSBixDjZ7y/21J9iFiPteLey9p8nVps8FLrdt+8yRHk+ekU6VD8W27bcty/oW8CRBO7g7bNveaFnWSuA7tm3/18iOcHRTqTVPd8QgjoPhe6BpiJNPQD79Is7S5UDvhFwU9eP1KwidCN8HdKSuBQ7tspXIO36HOHoS5mem4/zHPQMqK+/K91F9gvtHdGZw72rBXDyf7E3LS1JZZK5ezfntSuhII5YsVmryir2awbYfC7MdGd0glkqVKLqXTsR9anVZrsy8bCXmkiZcRJn96UQvpKc6S5f3Rpo8QaXEsv6+g+b7uKH6I929KaiAHq1D82vAl5iaT6eu7KJCoSil19ZAoRI1Z3N8XUMcPSlIe88FcNyNm3ARtLsCEBhoJOLjSxYyzQsX4Kx9HvOEj4VrJbV14N6zglhzI55SlVfsnfwUOINg8g6AZVlPAnUh295q2/atwzGoUTlxB7Bt+x7gnj6vzQvZ7q8EK5CKfqiK6NSkAjXxguFtbsAB5NMvlvTwDAxs4EzW6lpoXZSvaeCB5ri4K54OxOxi1RCvxrn9gSFpbVeM6hNcmTge7l3BD2olkS25fSfG/JORiXiu5Ys6f4r9g762oxZ3wPablSbOvi9plxp9n5+hXlzMp/iX6ZIk4sH/k3H0s2YjehycogypZHMjHbH+RQEVCoUiT7duUHPa9DLfsFM3wAsW+F3PJ5NIUHPFIkilIR7DWbYC+VYr8uhJ4T5HpmvI/D+FYiSwbfurwFf7vHbKCA2nwEgXCXeO8PH3G2K4OOntyM/PRFzyWWQyHgjQzTiu37r6gWoxfU2DnJhd9qZlkO4astZ2isGh+X5QqnDJZ3HqBOJLZyKmTAJyegaL5uKuWR9kRZimWvlW7NcMpv3m7uhquJ5PuydKWisNhKFr1EagNpIhYXZQE+lC10VFu9tpViGWLMa84ExEKhM8033aO6nWSwqFYrBEPbcwaYfedrFRzy3dDg9n+ztktU5ckYFE0M05L+xZoqG0aG5BK0n5fwrF0LLHI+6WZX2nz0sSyACbbNs+aU8fXwG6Lsj2vMPrG77R265jwXXoD78Kvk9KixRSRPP01l86+Il4kEIfEklKF6WIyraOigr2+Qi9YujxTR2v8Vg2r7229/rOu4Fo46mwtQ131TOF9Frd9zF0NXlX7L9UimYX26i+dq04I2moslUMXSPhdNHT+U7Jsztp3o1kjYPDI/hZjx4EdcJHq9Dm0/R9ZFs7tbkFAPWsKxSKSlTKLsr7CkFtvCTb826pDzn/hqD31qYtuOtewrxiESCQ728v8TmU/6dQDC3DEXH/GHAZQR+7McDFwOnA9yzL+vYwHH+/J6pnCr2AIejBufmpbyE+exx4flmEJi/oJG+6B/f625D/8WtEpouUZpZFksoU8T9yUJmCvVIV3bN4dBUcf8hd3999DTe9HefW+0p+QOX720lkOjH0kU62UShGhsGo0ve1a5GvnP+BdDrCiOPh7Xyv7NndsvIqonqm3wi+r2mFRdJi8s94z7/9AnnTPepZVygU/VIpu0hqvX6g1/pWuQ+56muIM6cR+cYXMKZOwXn4SVzTQCZroCNd2I/y/xSKoWU4atwPBI63bftdAMuyrgPuB2YALwH/Ngxj2L+RTkkPTggMLwfU4qx+AX32dCgyrHFdIjo6MRfPD4RK1r7Qb51ScQ3phEScNgclJDeMyErXNx4pRBYLYjLr/wCb/6ZqzhT7LYOtRy+xa8ka3CFWKNZ8Hzeqhz+70gGqgXD1+TSQGDemVxg0r3x/3um4jz4JDJ2+iEKh2HeplF3k6xr+0hZIxuHAMaF2Smo+zm9W9mb0LZilhIQVij3McEzcx+Un7QC2bW+3LGucbdtZy7KcYTi+QphEEvUlhjeSqIdUN2z+G/5nPl1IYzJ0DSPVifPgml5ncNFc3FXP5OqUBl45VUJyw0yl69vlBOlrqTSyM4OzZgPGjONx39s+6GupUOyLjAYb5WsaotsLf3aFCZS2s8sr4Oe7dKTMKPEJVZhLmsCXoAmcXz1ScKKhN+VVPesKhSKMSguZCcfBS8Yx5p6Euy0Vbqd2pMtS4keDbVUo9mWGY+L+hmVZ3wduI+hD8QXgL5ZlTUNVvQwL3V6MSfNuZEsu1SmSqGfyzOvg8VfL6jbjeDh92yDduwpj4Rxc08DTwEOiI4g4Ak+tpI44la6v3m3g3HlvSR2s+877GAvn4IXUnOm6RtaU6voqFHuQ/HO2Faj60CFMPu2nbF79zyU17t1eDJBBOn0lBXxP0O5BvuKtFllIUc2j6ksVCsVAhE22fV3DmDMd59mXSJ3yCQ4461e4O/9Kx/P/Bzeznclzb4QVrwHsEQ0QhUIRznBM3JuBnwF/ABxgBXAJsAj42jAcf58lLIUyLCXJ8yRZ42COaLwLIV00oaP7UfyGw8rSmPoKlYiJ9RizpiHrx/M3P8vVG56hNZOmPhbnh9NOYoJepSZ3I4znSbyqD3PUWXchfQchDHQZRbgSLxnHzLXqy5c9iAljczVnvddN1zW2ih6+8Zy6vgpFX9sqfVnxvTC7W2mbsOfsx9NO4siFv0R63Uhh0uXF8LzgeP0JR/WNog+HoJ5Codh3KbFbuoE8aDx/O20aX//vFwv26kdzfsJkAxyqEQ316GfOQmgCKQRx6ZHWVWq8QrEnGY6J+/G2bTeFvH7LMBx7n6W/FMpKk/e0Vx2yp9JtixWXxcT6IE3q3lV0nDObq/+6idZMENFpzaT5xgvPcMenZ2NkNWWoRxBD16jp7Cz0cufoSYgzZyINHbNxNs4vH+4te2iahxcxcbOl1ytrysJkAnqv760nzkZX0TrFPsJgJ919bav8wlkY0aD9USW7C+QUmEGkO3FDtukJec6uzj9nTiQ3gt5FgsEo4OcpTnmNCHAkqr5UoVAMioLdW/0cYuoUjJoYbRPG8PWNL5bYq6+/sI7bJ32csVE36Djkuch32/DWrIeOdL9+qEKh+OAMh9zsdy3LetOyrG9blnXwMBxvv6BiCuUHyIk0dA0BmJefi3nJQvT5waRdtnXg1MQKxjtPayaN05FSysUjTA1eYdIupk7BPGMmdGYQPQ7Omg2lZQ/LVkLYwg4y9Pp6RZMIhWJvpqxbRgXV9TDb6tz5EHG8ynZXl4V9i3+8i1vBNg/mOTN0jVpdUie8IHn10nMG3aUjr0Qv6pKD7iWvUCgUcTy81c8FOjjL15L92T30pDOh9sodPwbhOOjdPTj3rMB9cA3G3JMgGf/AfqhCoeifPR5xt237U5ZlHQlcBDxvWdYrwO22bT+8p4+9L7MrKZSDoSqiE0+lcJe24OVVyJsb8ZJxaOvA7MxQH4uXGPH6WByjI413/+NKuXgE0X0/uGZTp2B++nicX9xXKizY2SsgI9s6ECH3iI4Ivb46AtTkXbEP0G+9eJHt6t+2Evqe6Xk4q5/DaJiFOHB8aH913ffRMfp9zsKi/UZzI+LK89EdV6k0KxSKPYLm+4ipUwrBGgCzrSPc79u2k+zN95V0q3HvXYXRMAtn6XIliKlQ7EGGJUxq2/afbdv+BnAWMB747XAcd1+mUu9NX9v1SxqLGtR4TlmUyFnagjFnOgCJ1Rv40cdOoD4WpIvWx+L86OPTSKwOIrqarxzJEUMTiJNPwPzMiaHCguaiuYiJ9UDleyTiCH447aSS6/vDaScRcdRijGLfQPP9wrMhJtZjNjdgLp6PkZsw5+nPtvZ9T0ysx7xkIfgS84yZuBs3Id/bVvHzAz1nYYsL7tIW8PzQfu5QGqGv1aXKflIoFLuMr2mImljJomNi9QZ+9PFppX7fMVNJrFgH5PzEXz6M+ZkTYfIhiFg14uhJCE0oe6RQ7CH2eMTdsqwDgAuACwmW4O4E5u/p434QBiv6NpIMlRBRVUSnur0dHDc0SiTG1xWc0MN7fO488VSy0sfwPRIii5h/ArzWijA1asnQs7ODRDSC5kfRHK/k/O0N53VvxDUN9E9/HFfvRi6Zj9CNIEi+rR254kXo6sY8aw6+40A8FnqPeJ7PBL2KW0+crVTlFfsMxTZHaAJx9CSIRzGn/1OJ9kOyuREZr8aX4Jgm1UVtFN2NmzDnfpr2XAQpb3dJxjHOOAX3N48F+zl6UlCm0pPFvOxcnEefQr62pcQ255+zX3x6Nr6UmEKQ8CCTyyzd1UyqSlonckxsSM+jrguieiboLy9MHOKYpAt/dxcJ6ikUipElb/dkWzu1ugj1tfo+013ESSTigb+XjGPMmgZjkhyOwe2TPo4bNYnU1BD/5SPQp+Uk7SnM6f+EX2ViLjgF2lPQmUFu3ETtaScGtlUTuHQh+7EZykdUKAZmOMTpNgMPAZfbtr1+GI73gdhV0beRolLvzf7GGGYU456Ds3o95vyTiHx5ceCorn0B+VZrYMANHePKxYhUF87SFuLJONHGY9m89tpC+yLrjJ/Rnfobmx+/prcd2azr0VteQeTESnpqk1T3dBecYblxE4nTThx153VvRAA97ntsfvRrhfN/2Knf4d3/+S0fXngxfreL9+vHMBbOgaoImOH78Twf3ctPD6Sqb1fs1YTZcrO5ERmL4ty0rCyqbTTMQr7xNtXHH1XIXMmnqnPAeNy2IF00b3cNZGE/YmI9xozSMhXzwgXIs07Fl6LENgtg3M50b2T96EnULjgFXwgwdcxLFiKqIoUuEHSkkRVaulVK/9e/cv6QnUddF0Tct3n9kaDdZO1hJ/PhqV/k9ZVXl7SwyxoHq8m7QjHCFNu9npwtqm1uxE3ESecydvo+0/lnOFP9EaKXnoNIpXGf/i/MM2Yi0hnGdmVxV6zDmDUNtyNd4hmIumTvAudpJ+Lc9kBJqZ6z+jn0k48jG+ko8RuLbYaha8R1iZHqxBnlvrdCMdIMRw7LGcA44N8sy1prWdbTlmX9bRiOu1vsCdG3PUVeiKhSCmUeQ9eojQhq+wgzJTOdIAgcztsfIPuze3CXr8WYe1IQPbpwAU7LEwint7e7mNM7aQfIplrpSb1dmLTnX9u89lrEnGML56+6pxvnlnt7jzHjeLzVz43K87q3If1ONq/6Wsn5f/OJ7zHhyDPY/Pg1eHQH164qgntXCzXqnCv2A0JF5pa2IDwvNLuIMUnMTx1bXm6ytAWRyRS2dT0/EIfzZWE7Y9a0ktrQfAqpkKD7HrreW3JSPK6CmGQqDTvbETs6cB9cQ/amZYGdnH8y+kULEI4TmnJanP5f8l2G0NGN6hm2rLyqYF8mHHkGm3OTdgjszZaVVwXRO4VCMaJUsnv62+8VxDj7PtP5Zzjip9BMA/e1vxQWIov9Qve1LRiL5paIZZoXLQhenzoltFTPmDoFf2ykzG/M24z8QoP+9ntlnx+tvrdCMZIMx8T9FuA5IAn8BugAHhyG4+4WlRyhvbWGuz+j6C5tQUjKHE733lWYjafirP8D8rUtQZQ8/348UjC+eTSzuuy1bKoVGYsU9lmyjyKDrglUfeYHREo39Pwb0WRwHYzcqnimq0RkS6HYl6k4qfVlaA26MA1IZwacCOdtKtLvdWBj1eGfS3Xi3HIv8VSKqoge2DjfC0Tspk4JUvZzzrHIuri/frSsC4To6sG77f5QB7ZSPT5DaUelU2Jf8nalmGyqNUi5VSgUI0oluyeqIr0T4T7PNATPsN/WhnPTMsxPHRvqFxpHT8L98xuYS5qIXHMJ5hfPxnn5fzCOnlRWH184bk2soo+CdAoLDaIqsk/53grFnmK4xOl+CDwF/A9wDnDScBx3dxhK0behRvqy4iS3kkBRJaMoJtZjNMwCKSs7qu9tD/7uzPQ6qA5EEvUl2/tOV9lrkUQ9IpMNPpNLpSo7xthaRLprwPZMiv4RmhF6/t3ujuA69HiBuvzaF4LrqCnBOcXey2DF2CrZcplKl0eNLlwA3T0ltq7kM7njAsR1iejoBCkxLzsXcfQkZKYr/HMdwYKlu/o54qkU8qZ7yF5/O+7ytUEHiD/8T69gXgXHVeh6RQc2jY7e3FjWLo6aeOVzF4HaSIaE2UFNpKskGyAUYZbYl7xdKSaSqAdRoQZHoVAMGxXtXm7h3vB9DBHuM4hMNrBB3T3htqg2gXnckTg3LSP7gztwbn8A48jDYXwd1CbCjzsmAYZZ0WbkFxoq2dDR4HsrFKOJ4Xgi8k//X4Aptm13M4r7RFRyhCr1zR0uDF1Dvrs1dJLbX3/iMKMopk7BbJqfWwmVmJcsJLKkCbO5ATGxPjC2W3cEKfNTpyDj1ZjNjYgpk/BigsNnf7dghCOJeiLJg5k8+wclr02edT1yzSu5utIG3DfeLvk+oi6JqI5W7HesGDyaUcPkeT8uOf+Hnfodtv75USbPuxHdTOKuegY60hhN83D1Ufv4KRT9Mthe7BBuy43mRmQiHkSNvnh2EDVa0oTz5tvIVBp346bySX1zI35bOwmnm6qIjpFKB+nsP7gT5xf3Yc75FLJ+AuYVi4h8eXFgR4+eVFgsAzCmTgnt2mF+6thCx4eKk//c62EObF7rRCxZjHHtpYgli4O/QxbnDF0j4XThtL/Jn1q+wKu/OhO75WIi7tv9Tt67vRiT5t1YsC+BXSm1N5Pm3Ui3N7SCeAqFYtcJtXtFC/fy/e34d/+eybOuL/XZZl4X+GwT6yFaFZ7JE6/GuXs5JOOFrhy4LsSiOC1PlNlO45Kz6M78nb+u+zGHnfqdUJuRX2hw175Q9vnR4HsrFKON4RCne8GyrHuBbwMrLMs6glCZnVIsy1oM/C8gAvzUtu2b+ry/APhXAq2fN4Fm27bbPuhgd0f0bTiI4+Hc+VBoD2KgYn/ivkbRXfcS5olBemZBFfnBNb1iIk3zkKaJu+EPGJ+YgnnqJ5Fb23C2/A1x1nReX34JZmwch8y4CiOaxHe60CJJDH0cRzXeiZQudPagd2top89EZroC8bsFp+C8apcIPskK0X7VA3TX8L00/9h4O4fMuAozNh69Ko50sxx60tXoIoEme9Ca5oOU+IZO2lO92RV7J4PtxQ7htrwDHV0XxI8/Cuf2B0rtUSKOUVeLm+/HXhODeAxn7fOw+W8YTfOIRyNlJUfOmg2BKFORoF2+t7HMqS9XSiMlnUGffxKiqyeosb9wQYnavbFobrDIcMUifN+nVi9XWnY9P/fd9dwva/hvVRwPb+d7bN5QXmt6RONdpL3q0M95niRrHMwRjXeVqMoX/61U5RWK0UHe7tUsWYzuecitO0oX7lc8DW+1orfAkZ/9IRw4Bt7biXz4ZXirFaO5AWfDK5gXLcC5u9cWmc0NSEHgN849qZBKH9S5N0BnGnfVM722M1aNk9rK5mcD/SM3sz3wUarrMGsOIuPW4HmStN7bIcld9QzGwjmICWPxdH1U+N4KxWhjOCbu/wxMs237dcuyvgrMBhb39wHLsg4GrgOOB3qA9ZZlPWnb9p9y7ycJaudPsG37bcuyvgd8F/jKUAx4sI7QcNJ/myAqvpfSzBKjaC6ej3NroHxsNswqtDLKf8ZdthLj/NMxjjsad9nKUnXQrgzZVGvO2fta4VhTLniENicCxBhv+PT85De4fcbvL5iF6ONAx/GCFeDiFP58ZEkF3QeN9Bza33ya9jefLnn9mIZlaPEYzm33F/34NkJMpbQq9k52tV1amC2PI8ui3+7SFsSSxaRjNcQbZyN8H/n+dtxHnixMvt1lKzGXNJVNwMNEmZxfPoyxcA7Oxk1BBCnXZqmvrZOOi1YdxVm2qrel3OXnQtaB6ii+rmPEoji33Ft4hndXaVnzfdyo3k99evjEHYLJezCxz2/jk6X4bzVpVyhGC67nsxPB+HFjcHUd/bwz0DSB86tHCvaMt1qRv1iB+e3LkHEDL68WP7YWPZnAh2ASXRVB9mTxPYnYthNjzvRyIc67l2M0zMJZuhxn6XIAIkuakCYFe5N+b1PBb5xywSOFhb7iBVbN9/FK2sCNvO+tUIw29vjE3bZtCTyf+/cKYMUgPjYbWGvb9g4Ay7IeAM4Gvpd73wS+ZNt2Pv/6VeC8oRz3aCMfOQ+d5Ob+HfZeX6MI9NZUVhBUEvEYclsb5uL5hZZE7r2r0C4/nUiivsTxK6tt1PWKY2n3Sh3o4pXWvFO6O73o93dErl6t73URqW6o8kquo1MhOqlQ7A30awcHudjX3+TflYJ2BOMEOHc8WLYNvl9+/EqiTAeMI3LtpaAJXNPAaG4sLBjkF0OloeHevbzXCX5tC84772MsaaIDg7jnIfvJMNiVvse+piG6vYFtuEKxnzG21kSPREd6GEOO0ETB7xqLDx3p0vfrkiDpjdD7fqCB8+62QiZm8bZ601y08WPC7V2sumRb2ZNF9GQHZW9GY7BMoRitDEfEfXf4EFAcFmgFpub/sG17O7AcwLKsauAa4Ge7coBx42pCX58wIbGLQx0epC+RXzirkC4v6pKYXzgLMSYYb6X3Jmgi+GxnGno80LVATOm1LYXayb7GGSOIXDmPPRWkVy2ai7vqGfRuncmn/ZTtTicyUoPIdjI+MZaqxDi6slmyvscOoVN72bl4xf2Mi8ZS9r3GxIKew54fKCHXxKnbw+Jpo/UaD0Sle9Zrh8mfvYHNv+vt4z555nWwdgvyk3GcOx7sTbtd9QyaqeNHwfF9TE1jXLQaYw8LwIzmcz5axzZaxzVYKt2veXbn+/VnB8PsS/4zdKbB80DXkcIMtXt6xGBCMhiz39EZbhsB86IGnNxkW9QlIVkDUyaRmn4MTk0MszNDYv2rIMC5+beF7eSSJvQvL6YdSRaJ0ZGmrqYmXElZCOrq4si2dnpC3o8IGD+uBvnuVpw7Hyr0Pa79wlmIgyaUnd/8b4Cc8OEyW3HE/J9QnRxPTIysCNRI3+/93a8jPbahZDR9l9E0lr99//jQ1w/55kvA6BorDGxf8+TH7bs+xqVnw/b2QhSdcbWIZIIxmijYEvOCM0KFMknG0ZKJYGIfYu+kDCLooi6Jftm5tFWbZDNdfKjxl+x49no63ngqsDenD5+9GW3XbDjZn7/7vs5onbiHeWBlS3CWZdUSTOBfsW37l7tygO3bO/H90vS+CRMSbN2a2pXdDCvjD5pQkm7ejo67vRMAIxovqeXMv5cXcyqOapsXNeBAUPfeNK80Jb5pHs6vHimZsLv3rsJYOAfpuLxTM5arX3mN1kya+licH02biJnq5J83PFn02klMvPJ8DN9HSInvS/ydqYLISHmESAICXAk9nXv0HA7lNR5uwxh2zwLEogZV0XqOWnA7fmcqiLSv3YI5Zzq+aQTigPmsieYGtrjdXPPcusL1+sG0GRykVeNk90x9wmh+rkbr2PbEuEbL/Zofy+5+v0q2LnTbEPtnNDeiX3oOXlEJid7cyE5X4ObGZOgayYsbce/qYzcffhI604U6THQNt8rk7w0nc/XG3mfqxw0nc2imG5JxaOsI0vGXP8HfG2dy9QvP9G437SQ+MmUSbNpSGLOoS+JIaN+aolYXoQsIjgR2ppB9dE+cOx9CLFlMZGyycH77ngNjyiSOarwDX/ORGHR5MdLbSiNxw02l+2E479lK9+totRFhDOZ8jZbvMprO61Cdt9FwvxZTfI4NXSPpeqWaRhc30t7RRRyvYEtkKl2WOSkm1mPMPxnnF/chj5jI3xtO4uqNz5bYu8PMKMa3L8fTNN7ws3z9uSd6fcLp1/KxGd9AykDscjjszWi6v4abwX53NbnfOxmtfRbeBg4q+rseeKd4A8uy6oF1wCvAJcM3tJEjn/bUJnXaPVEuUBTyXpiYk3P3cszTT8Y8fSZSE0FPzmsvxVg4B3fF08i3Wnv7ds6aFhj5CXXsHJvk6hcC5xSgNZPm6y88wztdnWWv7dSBdBfuTct61Z+dbpIhitD5/saql/vuEXEdxLZ25EMbMHeCWVWHccIUnN+vR2zdgbt8LcbckyAZZ0ddDdf0uYbXvLCObkOlpin2DirZujDC7J+7tAVpmr1K7Feej4xXU+s7jNN9aiMCXRfImhjm5ecS+cYXMC87F+f364NMpbdace54EOfWe5Fvv0d76/uFSTsEz9TVG9exs7s76MyRU41PTT+mMGkvbPfCM3SeM6eiknJ/XU4q9Wvu2zau7Bxs2oL8+XI0r4bObLUSlVMo9gPieIWFSMjZwrtaCoGU/Ovu2heQ8RjGeacX7I4xZ3ohwJM6dnJh0g699q7tva2IdBftuuDrfezc119YR1qLYXhRhCrTUyg+EKM14v448F3LsiYAaWAhcGn+TcuydOAx4D7btv99ZIa4d1CpnhMBJOLQGfQZFqYRWtMp4864hgAAIABJREFUYtWFlddsLFIwxnlaM2mqdaPsNV/KModZbN9ZUjeVr9esuWIRzi33FtI9d1d8aX9F930QIqiPfW1LyXti5gm9izAL5+BIGXoNXSmVjr9in6OS/RO+z06pY+gmyVQn7tIWvKKso3gihvvYM7ivbQmi7Zedgyx6tsTEeoxZ0xAHjseNaLS+GvJMRU3cpY9iLPos9GRxPzSB1j+Vb+dIibjyfHTHLetiEqaMn9EN4p6LpoVH4/u2jdtVQT+FQrHv0Z8dKNYOkW+14tlvYJwwJRDK9GXgX+Q+69TEwn2IqBnY0a8uDn3f2dmOXPooyeZGZLwaX9KvJodCoQhnVIY2c6Jz3wKeBP4I3GPb9kbLslZalvUJ4Ezgn4CzLcv6Y+6/O0ZwyKOWvEEuJi9I4vziPkS6C/eeFRX7dsqebC5lfh1md5b6WLxkm/pYnC7PLXstIiiLBoXVTcm2DkilVS/3D4IQSCkr9oCG3GRlfB2G54deQ0OoVXDFvkcl+5ef3MbxyhXml62E7e0YU6cUXpPbdvZGvSfWB+2Qlq8l+4M7MLbtDH+mOruC525MMsh6eWdr+Hbv7wDPr5hBUJxhkEYnlkohb7oH51ePYDTNK4vGd+sGsqOzkMEkBzgHCoVi36c/W1ic2SMm1mP+f4fj/nwZ2e/fgXPb/YVtAczOTL/2LuLJft93l7Yg/vFuIeNSZVgqFLvGqH1ibNu+x7btKbZtH2Hb9o9yr82zbfu/bNtusW1bs23740X/7Rfp8rtKWKql2dyIjJiBszomidEwC2nqmBcuKN3uogY4+ICgB2hNnLqxdfx46oyCUa6Pxfnx1Bl8OBoree1H//RJartdIl9ejNncUEgVlT3Z8MllZ6bktbB0T0VlpBAwrrbMiTcWzcVd+0Lhb5nOMOZ36/nBtNJr+INpM4i6o9YUKBS7TX+p5kDFdHNRFSlRSXZftTGvWBTYtEVzcde9VPhcYsU6fnTM1FIb+LETSKzeEDx329qQbR0kVm8os58/+tgJJFasK7F3hq4xRpeMNSTjdJ9xmseYXAlRcdq7fKsVd8XTGAvnELn2UsSSxWQSCWKpFNn/++tCOZJwHIx+zoFCodj3GcgWylg15hWfw7zgTJw1G3rtYjKO35nGzH02sXpDv/autj3Nj0/4dOj70JvJqYI0CsXuMVpT5RVDRFiqZTs6cekhTj4BIQTO8rW9PYQvOxe6upAdaZyH1mCedwbGhQsQnV04Ny3jI8k4t8+fgXvAWIzODHU7OqE6yp0nnkpWECgld0u8/+xNfTfyju64MeUtkZobcVc/VzJm1ct91/AB3fVwVjyNecUikDLIqHj0KeRbrcF5Pu90pKYjOrv4qBHl1hmzcaXEEIKoq+0xYTqFYiQJs3/FqeiV2svJnmygQk8uwv6JKSW91I1Fc3E700FP5LdaOeT+J7jj4gYcKTHe30HigbWIjjRmcwPOsy8HO36rlcN2dHL7pI/jxqsxq0zGpLOIOdPB1Kn1JN26QTyVwl39HNqM43Fy/ZJFXbKQYlqc7pqvtzeuvZR2T1CLW1ai5N12P+LK8wvCpkITSCGIS4+0rlJVFYr9gUq2ECiIV3p97BsQZBf9ZgVeMl4Q5Tzcc7n9mE/i1sRK7d3Fjfi+z0cefobbpx+De9B4jG07STywFnL94/tmAqqSHYVi11AT9/2AsB6Z3RGDmhM/XnBGoaiHcMMsnKXLg5VZTeD74OedwbYOEjffl6v7PBdnWdAWqSYfyY9V4965rDT19N5Vhb7EmJT8cKR1g9hpJ+K9877q5b6bZA2TaimDHq2uh3P7A5CMBzW4M09A9mSRuoZIZzAXnAJZh5gRoSfrARJHrZAo9mH66xGcRqe2uRGneDGxaR7UVOOuWAeUCjNBkU1rmBV05pg1DVETY6zj46x7GePwgxGnz0RmunBWr8f41LE4GzcB4K14hrqFn0Gke3DvaOld3Fw8H/nUi9QsOAVnaUuw79ykvXDMpS0YS5r67WNfsY7VcUlpJonurpKFU6UnolCA7/YU2r7ty4TZwlq9XI8ob9+AXjvU1lFoLWsuaWKclDh/ehMjWYP43LzAV8x04/3nI4GfuGlLQY3e7UgjKcoEXPUM5P4WmsBAUzZIoRgkauK+nxL1XMh0h6eJJuO9KfWaQEgwGmYF6U2ZrkB19K1WSGdK1eqXtmBefm7oPqUvcWVgmEt+ODwPr5+ImGJgok4WH4nZ3AhZp3ANC3geIhHH/c9HCg57vLkRTznsiv0c1/Nxa2sCESYhQAj8zgzeUy9iTJ2CmDUVauLh2hxja4NoVFFUPO+Uylx0CUCceUrvZLsmjqipho5OzMXzC/bUvWdF4Cjn9D5ErBqSccw+dhcp0ZsbS9rbFS90Vsog8DUtVGHfW9pCfMninE1WKPZPNKOKjT8L7+M+9cv79oS+ooBnTQx8GW772jpw7lmBcclCRMSEdBdETIRplGyfL+cxr1gE6QxUV5dmAi6ai9vyBInTTlQLiArFIFET90GSry8s7T++9xoZzfcDQxvi5JGowbxiEX5VBOG4aJnu3nT64tT3kNp0fBm6T42gRjPsnOVXgQ3dJI5Hwnfw9b3/HA8bAjQf/GwWLR5DHD0JY8bxJRMK88IFpT2llcOuUGDoGnp7Z2nEffF89E8cjRAasjODSMRDbZqojuL0ba+Ui1Q5S5cXtkPXMK/4XBCR0nVERydOcS/l3GRfxKqD49Ul8aUfRKpykf5CJoAm6KlNEl3ShPB9pKaR1k3cXKlLGp1EhYl9wneGTF1+X/s9VCj2JfLPp2xrp1YX/T6flRb7qI6CaYSXEmW6An8i3YVzx4O9fkZzI+LoSSUdOOhIg6bhLF8bjG3uDMTpJ4Np4O/YCZ1ptYCoUOwCauI+CAxdK9QA7Ssty3xNQ3ge+ucXINIZRCwK1VGkqYPv4zz8JOaCU5A7UzghaaLmFYtwHn6yZJ+iLolMBSImJY7work4Dz9JvHF2RcM8mHOsnMVyjFwKPJqGt+VvaCd8DHPBLJA+etNcvBVB9M/55cMlEwpVW6bYH+lrQ9Bluar8PSswFs4hm0sLNS5ZiHlRA87dy4sc1AbozIRGo0RNDKCwndPyBDLfVm5JU2E/heOtewnzc/NyO5Dol54D2SykMqVR+WUrMT5/JlG9uyTdPVaUPZOvYx3zlfPxsqXt5Xy9cjR+V6pl9sXfQ4ViX6H4+ewZxPOZRidx6TmI7TuDzj89WRg3BuexpyEeLfhzJOMYc6Yjxo9B7kyhzz+prITIWdoSlFAWlT4ai+YG3YlmTcuJ5Qqcx57GmDoFrSaG1jQfZ+3zOYFO5Y8oFAOhJu6DYG9LMTR0jbjuAxl86SKFSZcXw/NkieNKTQyxvb3QW70wyV73EuZnpuObOv74CPLzMxHpLHLNK/BWa+E8mKedWGKgzYsagv6cuhakfY5JIkwDunswpk5B9nOqBjrHYc5ibXMjbiJOOqSF0v5CHA9naQv6Vy/APPKjOD+/B3nEIYjZH0OO1xAXzUZs/Aty1foSlWwlAKjY1+k7Se/WDWKpVIkNMZsb8S9agPfQ44X09ryqfP7f7h0PYixpwlj02cCe1SZwWp4IUunDIlW1Ccz/dRlIGWQq5aJPsq0DHLd0+6lTMKf/E85t9/dGyC87B01o4VH5aFVh2/w++/4WuZ4PdXGyHdvQyFItdKQZocuPBiUyFdLsB8ve9nuoUOxPVHw+rzwPV+8C6YAw6c75hADCcUv9wIsb0RfORutxkKaBceV5iFSmJCBjXtSAl8viY2I9Ys6xyHgE1+xBb/osmtCDRcd1L2HOPwlqYsHkfd1L5RmBFzXgmzp1jqeCMgrFAKiJ+yCoKPgzClcIDV0j4XTR0/kOm9deSzbVSiRRz6R5N+JVfZh4qnfya37lfNzfPBae6rlmPe68o9j8u68V9jF5wXXoD4PIi6A9+xLmkibwfOTWHTgPrYGOdKAU/8bbGEdW9Uapjp6EWT+BOiFCDfNA5zjsx8hZ2oKxcA6JZM1+G+3RfB9v8iFojhuc6yMOwZt5GJsfvaL3us37MUZXIFIH7LbDrlDsLYQt9MVzHSyK2xzJjk60A8aiLT4d54kNyI2bSlSPITeRb09BrBq3tgbDcTFnnoDMZSx5//lw6cJnyxMYJ38CEnHIKTMX9tWeKkz2xcR6zFmfxPnFfSV2TWzbWZi0519z712FsXAOaCI0yl/8W6Trgq7tW3j9sX8p2IDDZ38XIzaOdOIAqgepJ1Ipw2lv+j1UKPY3Qp/PZBy35x02r7yqxCfMGgcTxyvPOrqrJciqzC0SmpcsLLNJzt3LMRbOwVmzHm/BMWx+qtffnDzrevSWVxAd6SDi7nlQm0Ak4ugnHw9ZtySbqLCvXJaTyuBRKCqjJu6DoD/Bn9EWsYzj4e18j80bAiMKkE21smXlVRzZeGdvtGViPaK6KjzVM1YNn5xUmLTn97H5qW9x5Gd/iGEkcVY8EzingHPrvSX7cZe2BCmhNy0rHMuYcXxJO6W+0fKBznFFAZWqyH5dr+1rGuYp08D1gvNx6hQ2P/al0uu28mqObLwdud0lcs0lYBq0S7Wirdh3CVvoc3Nq7c5rObXjPsJy5oULcNLdGCd/AnfF04V9iboksjODu3ETxmknltXDG1csQqTSwTY5YTr3nfcxFs5BP2MmIt3VKzD35zcxLm7EvasFY9a0EoHPwvGqIuF2eXwd0tAH/C2K6hlef+RfSmzAG49/l0NnXkOkLk67V02Ywn4x/aXD+4TrmIzG38P9jR7P5aUzlvX7vmLfJtSX+uxxhUk79PqERzTeheZEQn2rvFAm9G+TxGePY/NT3yj1OdZey1EX3Ib+dmcQcV9wCu0YxE2JUVWFs6xc0LM4y8lb2kLNksVIHVUaqVD0QU3cB0F/gj+jLWKp+T5uVC8Y0TzZVCtSukFaE2DMmobsSFcUHpFjoqH7YHwSmY1izDgOoWvBG/l0qRyBSJ1f2K8xa1pZa6O+0fI09HuOK/ZbznTt19GeNDq1ugeuF5wPnfBr77u4P19WqLNVKPZl+lVKpoJN+uXDmEua8B03EFSitH2RMWtaaD28efm5ZH92T/mx4lGEbuD8ZkVJSqhbm0Bbshjhe8jWrWV2TfZkw1PwAffVzeUaIs2NdBT9FgnphNoAzawO0mSpZiD6S4ffm34P9zeqdIMTHv7Xiu+/uOB/D+NoFCNB2PMpD6gN9+ekg69Fw32rnPiwmFgP8erwbXZ2wPhEuM+BD7qOcfrJdJpVuFkPgSzX+MhlE/XNctI9D+fWe5WOhkLRBzVxHwR5wZ+9oWWZr2mIbo9Ior7EmEYS9QhhQN74jkkifYnRNK9UuTinGK81fDJ0H7SlocogpaVxTR1jRzs1Z80uqREVdUlk0URbxKrDV2uLo+We6Pcch/0YFVZq9+Noj+v5oGs4L/wxcOj9bPi11wyYWB9cI98nrnlDkqGg6wJpZvBw0DERTm/dnEIxUlRUSs4pxBds0sR6uk47Fq8mgt6ZJSEgZUZJLmlCtKdKouiiJhZqxxAi/FjRaFk9unP3cswlTXTqJnEkjK0NIv2/7E23l/EYxnmnF8qYCin4a5/HOO5onNXPBe05a2IQj+HrGrouiCPRBPhSD7UBvtMFwhzU+esvHd6V/dtqhUIxchT7qxEBjgRf6w7354QZ6luZzY04q58rZCY5K54J/K2+dek9PdBRYd/v7sB9cD3mxY1E8YkJD4Qgc870gr2tXv1KYFvH1+EsW1H4vKhLIrfuUDoaCkUIauI+SPItywZKMRxp0ugkxhzI5FnXl9W4d1NTECcSpoF7+wOBUmjDrKDvdzSKjJiYp5+M885WJs+7gc0ri2rc596A5tfRynvc8qdvsj3TyrhYPVcc833qz5hZiOgazY2kdTNQO17agsx0DSpa3t85zv8Y1SxZjO57QV191sGYMx05bsx+He3p1E3in/wYMhpFT/lMnvdjNq+8uqjG/QYkoC0+BR7dCFIOiYKrrgs6xdvcuv5fCvfC5VN/Qo1+sJq8K0aUSlHhrqoo1V/6XLDRlElsPe2j3LKp15Z96cCfEONgOjBImCZeURtMKrSFAzAvWoBzd1Gte9M8ZJ+exhA4oFJKalIdOEuL9D+WNEF+oWD54wBBTXv9eDw3hdPThXbqMbiPbkS+tgW3M40xaxoC0OIx4m4X7m33IxpmIV/cxOQ532fzE98sqXHXY+Po9mLAwM/mQKVLe8vvoUKxP5J/PidMSNC+NYVOjEnzbmRLnxr3bi+GAPxEPLBBvsTTNLpMk+rTpiM70oXJutuZ7l0wjFXj/HZlYBMXfrrcV5x5HfLhV4J+73e1FGrht53/CW5+q8h3PPt6JqyOg66VZDmZzY04D/6+5Dvtz5mVCkUxauK+j+F6Pimzmnj0MI5qvLNUVT7r4+cmv4VU9rYO3LUvBE6g6yMScZznX8X71If4x8ZfcMiMqzCr6zCjYxHP/oXMKWO4ZX1geAG2Z1q55dVv8o0T7yLxrUuRmkBqOlHPJZNIEF2yGCkIBOs+YLTc9Xw6dZ1kd1fpvpobYXCBpH0Sz5NBjXsmg4bAeP5djjz9ZqQhAMFbz/6E9jefDn5Q59+A7rn4kegHzlCQZqYwaYfgXrh1479w1fSl4A2cjqtQ7CkqZUnh+ES7enBXP0fPWZ/klo1fLLl/b87dv153de/ndQ3N85CC8jT1pnk4v3kMDv1wzvH1QdPwTQOxoz2Y2CfjgX2NVQcCkUIUJu1AoDo/a2pZur2zZj1+01ReL3K2J8/7McaHD8A49CMl0S+jaR4k48ExNm1BT6U5cv4NyLpqhNARZpROJzroBTWVDq9Q7Dt4niRrHMwRjXeVqMoLREHLIptfRFxwClU9PsSDCXrBTr3VWmgnG1nShAS8WR9lc8vFmLFxHDrzGqJjDkFsyyAffhGKu3QcMJaei+dw8/ovlPqOm67l62ffQVZGiBbZardoIp9nf86sVCiKURP3fRDX82n3AGJFr8rCezKigesijp4U1KqPSSC37cR57CnoSCO+dCavP3op2VQr7W8GIk2RRD1HTr0eF69gePNsz7Tiuj04N7dgnHc63qNPQkeaWL4myfUx8tFyz0Nu3YG76hnoSO+yMxiqgPoBUqj2hd7wcTzc3z2HfvbsoPxh0iGItI5bq/On5ZeUisas+hpHNd5JNwZ4H+wX0MMJvRd8BldHq1DsScKiwrVFfdud+R/r9/51PZ/uiFEeHb9iEQiBfG97QcTOOPLwXjHOfMRowx/RL2pA9GR7y5FyjrF5wRnIVBp37QvIt1qRnZlQQanX+whKbf7d1RzVcAfuz/rUiS5bidEwqze76a1W5M2PBDuqS8KSxbuUBbM3lYcpFP1RO8YkYkb73cb1eoZpNCOH50nSXjW9v82SWt0vESzuKyJsXrgAcfQkyGf45BYffekj5hxbUJLPplp5/dGvBH7ip35YmLRDLrvy/R04yXB/wRESejx6imy1gVALhwpFBdTEfT/E8DycP7+Bedr0Xod0yiTkBafid6URuo8ZG1dSs5RNtSITUQxhMi5WX2KAx8Xq0dsCdWT3N48Fys1Ll5fUJLmez04Ehh4hftAE9PPO2C1ncChbEfWnnLw3Oaia7yOmTkG4Ps7yteizPwWOg59Kl4nGmLFxeMLDkG3oVSY97u7XpOuE3wsapvppVYxKiu2HvrNrwPs37jll0XHnnfeDrhl3PAiA2dzQK3Q3sR5/zrF0044251jo9Hon7SGOcT7zyN24qSyaz4RkRaHJSt1AnMeeKqtF3V2HV6XDK/YFImaUG357XL/bfO1zLw/TaEYXxfawkmCn8f83wfb2Xjs2ZRKy4ZN42hg+ctJVvPtfd5N+bxOQE7ybkOzVN8plA7krnkY/7dgK9tYosyxq4VChqIw20gNQDD9SE5hHHt7rkE6sp3v2R9n04g10OP+gq3sbEz/zPcYdeWbhM5FEPVqshrgX5Ypjf8C4WD0QGN4rjv0B0UdeDPadcyDz/w5qqXsJsgEEbVKnPdcKbiB0XVAd6aI60oET6UFMmVTyfiGFahepqJy8l+Vi+ZoW1J15PvK1LYieHtxlKxGpQDQmT/zAKdSf+GWeX3EpT913JhtXXEyVvpN4NE2sqp14NE0kMvjzKJwYl0/9Scm9cPnUnyCc2ACfVChGhnztNkD16le4Ysr1pbasz/0rirpj5Ml3zcjvhzEJ/IXT8a5qxPv8ybz297v540vX0ZF+k54xHv7imTCxPtQxdu9dhTFnOsaM4/GRGAvnEFnShNEwC3akS55fyAlNer219YVx1iWRPdmgFd26lzAvO5fIVy/AWNK01y1EKhSK4aHYHlYUEfb8wqQ97ytuWH0pT9/fyKsv3Ej99CXED5wCQO1hJ+Mj8JbMh+9eiPzqQnqqe/DnHEv1K/8os7f9+Qu74ysqFPsDKuK+HyJ8WdI/WM45ls1/vptDp3yO/37me3R1tlJdU89xs39I9443cDLbOWLejcjH/4h26qeYsHIzV0//Pn59HfrWDqL3vlxIjcqLzuX//UFrknRdoHlv8+LqqwrjOv6MG6kC5KYtHyiiNJTR+5EkjU5tIg5eMJkQuh5c2zWvMHnBdWx+6ltkU63UT/sirzzzXbo6g2s19kMn4GQ7+MPjXy+65j8mEjmEbHbgc+l5khr9YK6avhQfB02pyitGOSW122+1MmF1nG803o7Tk0bf2UUNB7Gz6P6VldTpNQ29uRHv98+RrtrJS89eW3iGjpn5r2h6FX984pre56rxOkyRCHeMx435f+zdeXycVb348c95nnlmzdI0CTQUtJVlrOxQCm1BKHpl0VpXRL2K7FzBe6UBFC9Sil6UpcUrcEVWRa+gV9RaQfSnQIUWLAVZxQG0gpaUNmmaZdZnOb8/JvNkJplJ0zZNZprv+/XqqzPPPPPkzPOc58w5c875nnygJ8D66PsGe90P2o/9338Dr/56SNCnNa8OixlSiPAcvPCT6FQa+94H0K93EPjKeThaKrxiUGtr/Yivu1mbLb2ZcUqNmEgl5WGFIMK4Xkld8ZnVX/HrEOn+Dp577GoOObqdzj+vZNrR5/Lkby4YLAuPv4rEupvIpro4Yv5/0fr4Bi478jrc1gZMM4iXi0l9QYjtJA33ycjTJXMqvViQveML/UY75AvkZ373JY455buYrkL/7ll45Q28Iw8k+L75qN+sxnzvXBT1OL1JNANrHn/6AzgrHxmzOUlBM+U32gvpevp37RzzsTuxPnjiTg2h2lbk5FrhuB5eOAg5G+tzH0L3Jf15ruYKmPUv16Drw3gNUf88ArzjkM+w7qF/H3LNL+XoD9xBjtio/rbr6oFAdJGBqyxfwqJ6FYZgFi/3pu75PaHXO/L3zIUzSvbPWEEiZ35ocEpRUwPWmR8ibQXJRQOEPzafpx84u+Qeev7RJRw4/8ul99Xq/2Tuv9xafnWNTV35JZGaGtCRUD5yczSS/wH00deYNecamDYVNm6Bh1/DfN98kgOBP03PQxkKbRq43/5FyQ+RtViWiZ2Tdd0R12rPui760mUjHiO8/DJAGu6TQfGQ9EpBhHVPX0ldsbgOAfnyLTJ1P952/KU8+atzS8vCVVcxa247z/y/S3hm9X9yzJHXUm80ojMR+qwwrvSiC7HdlNbVWdGOx+OfAq4AgsCNiUTiliGvHwbcDjQCfwAuSCQSzigOPQNY39XVj+eVfvbW1no2b+7b5gFMUxE2UyhtowwTjUJrRcbN9zYWv24YJuj86ylv53ojC+nzA6qZCo8UnlKkjCnYnsJSLlGVxNZhLJVBK5cMLq52MZRJQAXQSuFpjxwWttaEVYDGXBAcDaZCKYWRyz92QiaBnJ3/1TVgorRGK43SGjzQpoHGwrDBs0BpUE5+OL4XANfUaA3KVhgmpIM2Vs7CdMEzFf2mh1aKgGmTdjURU6G9AK42GFiiHFN5KCDoGvnfAAwP27JJuw4BBREyeF4OQ5lYRog+HcDWYCloME1wM+R0Flc7mIaFqSxsL4vWHqYRIOCZ9CsT2/MIGgHq8MBJo1SADHUVe59bW+vHa0HRGVTIswD19Rb9jiKgDOqyKn/+A+BEPYx0fuSAArSrUAYQ8MBVaA2mBu15aAtMV+Ur+SZkIw5mJoByQQfBdLMoV6NNRTJskgW0F8T1IGhqPMDxIGCAh40GggZkPfC0xlQQMDxMFNGMwnQHLpCrQIGhXbTnggl20MVzbGxiWCT9KLg2MSJuBsNz8QyTJCGcnfy1frT3/HjbnrIoaqRQno02rBHLmGrJrwNpYfPmPkzTwAkE8VAEDKhjKzgZlGFimhHwAhh2PqK7HcjieTaGYREwY7g6haNM+gdGx4RUgLp0yM///WGHpOdgKIiYBrZ2CaoAwYyF4So8U5OzIOI4BFwXPA2GQisDrUw8ZZC2HEJOAANQjoH2QBngWR5JA1wN9Z7CcMnn5YDG9DTa1ejgwD0HGJr8vWSAEwDX8ghlTP+eSkdcUhocrTGUKswsp842US54JvRZDkopXA2upwkYCsvwyHngao2pPCzTwXatgY+iQWXQaEJGgJSbxVAGUSNI2rNxtYupTIJGgLSbxVQGQcMC7eEBrvZwtIupDEJYRBT0aBtHuwRUgLAdwR7FyJwC01SErCxJw8XWGhOLYC6I6+qK+X2c8uwMRsiv1VpGlNMwNUbIrDzdKet66EtvGPEY4eWXjcvnHa/z2tpaP6o57mtvOrLsa3O+8DTAqNJaDfkV8nWClKOwPYOw6VFne/kvaEOTs1JoBSE3gDYNHOXRqxS252EqRb0ZxMgEMVwTZSi8gEfQdmGgrLItE8PLl1G4yi8TsTwM20a5AytrBCwMN193xDRwrAAB28nXJU2DVMgiB+RcI1+H0PkqqGWAQpNzDUxDEzBzZL0sQVPhuVEcT2EoD2Vm8LSNRufrN2gUClMZeFpjawdDGQSUiaUhD8vjAAAgAElEQVRMkm4GU5mEjAA5z8XRDqYyUCgMDFDgaQ+NxtMepjKIYYD2cL0cphHMr9KkXZQKYigT10tjGAEMZeK4WZQyMFQIOxvaZl3fNBWGlUJjYygTBtoR3ihHLfrv1zZKWXgDUw4MK4VhuHieuc1jjWOdQIyhquxxj8fj04H/Ao4EssCaeDz+SCKR+HPRbj8EzkkkEk/G4/E7gXOB7+zqtJmmIuhs4JVfDi7RM/M9V7LxufuYPud83NDemNl/lry+74lXkl57Hw3Hnk8quHNrXPsB1Z7+M9lj2vjHujsIHHEF16522JTU7BFTfOlYi70iW8lkt7JV5bjtmSvoSnVw6LTj+fC7vkDGzdDnhbjimZW0hOq4ZcbHcW/7M7ori2oOYX12X3K/eAMaLKz370nuzjXQEMZaeDC5R1/BOn5/cj9ah96SQk2NYn1mHrlVYM2LkruzB93polpMAudMgUYDBWz+cQ63VzPtzBBbfpMj9ZJHoEkR+9cQd67P8bFDLf7Ss5lDm1vpyyq+9Vhm8PMcH6TZVTx9f4Z0jybSqDjko0HufiPBus5Orp4d57nnriAWbuZdB13Bl5/4Ix2pNG3RCNfOPZKpRg8/+8NF9CY7aIi18cH51/PES7fz1w2r2Hf6CbzroHYufer/6Ej30BZp5LrDF+I8cjVOqov9T1kG4b1HNXR8ItTXW7yZNHjsrx6f2gPsm7f45z94URNbnrOpO9jirR9mcbo10QMNpp4UpPs3OVrmm+Tu3IpqNLA+Vk+26NoFL2rCfjIJSRfrXxT2nWv86x07Zx7phnqu+H8ZpkQUnz0iyLdXZ/3r9e/HmTz65gbe+/ZWvrLmZTamskyLhrh2XpwZSQPv1ldxGiysD70N++EOrBObyf1o7WB+OucYNnU+TMP0Q/nH2tsHl7I79Qb0r3+F89I6VFMr9Z9tpy/SstON91plmopobgNdP2vH7enAbGyj+SPLdrqMGS+mabDVC/GN3+b8vHPZPJPc41dgpzrZ/9TrsUJNuI+/TOaIFp557HJ/CObsk76NbZps0hZ3/GUVF836F5q7IyX5P3bRFL6z6TXWdnbyzbmzmWIFsLZavHVXDqdbEzvQoPUDNiqZJXdPUf779FEQsjDMEKFQEBzwHMXGuzM43ZpAk2LamSHCEY3tgk7Cmz/MYtbDtFMC5O4YvKfs3yaxToqRu6Po3jq7EbPBwP5pD96fsqgWk8hFTTyU6WX5s5uYFrP4r3nT2bM/wMbvZ/2/WfdZi856h6+s2cDGpM20mMU186dz10t/47GOLUyLhvjGvFnc9dJ6//lX5uzDvX//Eecc8GH+b/1vearrJa6ffTG3v/IzVr31NG2RFq6bfXHJa1OsOjZmtvDVP91CR7qTtkgLXzv8QhqtGP++9jp/2/WzF9MW3GNUjXfTVJhs5u/pfr70/G3+MZbNbqeVlnHIbZNDyDSY+5PHKr7+xGnHSV96GY6b9RvolV6vFfX1Fh39Btc86tAUcfnPd3rYd73i1+/UmXvy578uZ7/DziIYbeYNx+XStfn6z2feMZdzmhbw1l02TrfNlBNMmg5zyd2WGKwfnhfHjobQfYq3fpgvExtPMJl6RAb7jtX5cvTgNqyTDyRXVG+wzplH7tcvoV/oQE2NEj17Plvr6vj5n3Ms2NcqrUPMD3HPM1m2pjVfXhDib8kNzIi9nesesf19LjrOIGCluPO1n3D6zJO4b/1DnLXfh7C1U1J2XXXYBUwNNvDwm0/x596/ce4BH+HSdTf6r1956Pnct/4hzt7/w2TcHEue/Z+iMu5imoFnEj/gXTPez0Nrl/j1yJPnLOWx528imekc9jgWbsakteL3sGkqbDaw4tHF/vFOmrOEZ165l3kHXoBljvwdXu79i+YvJ2AG+cmjF5Vs29axRO2p1uB07wUeTiQSWxKJRBL4KfCxwovxePztQCSRSDw5sOl7wMfHI2FhM8VrQ5boWf/7q2mdtZDXHmwnpPqGvf7Xh68meshCun7WTtRI7dTfLwRUU/P259VfX0Js1r9y7eogm5L5G3NTUnPt4wGSuo6+XLffaAeY+/aFdKbfZGsuyRXPrKQj3cN/vP1E1G1/RXflv5h0Vxb7nr9inTQda26z32Cz3vtO7P99CuvomdgDjXYAvSWF/YM1BE8N+Y12AN3p4tyxFb1FYxiKphMtnG7NxruzNMzJL7rudGuSP8yycIbFdY/mOHrPPdjUD996LFvyeXIpeP7+LOme/LZ0j+b5+3Ocu98sOlJprlyX4NBZF7LfzNP58hPP0DEwx74jleZLTzzNpmQPvcn8OehNdvDL1Zdy0MyFAOw386N+ox2gI93DZX9aSf2c8weWT2snTP9OXbNdqd9RfOMRh4++PYBzc3fJ+c/d3E3TUQG/0Q7QMMdi491ZGo8yce7ciu50CZxaN+za5W7uJnhclOCpQT8PwMD1vmMN9dn8NfrowYNfuJC/Xt9+zOWDM/f2G+0AG1NZ3F4X79ZX0V1ZrJOm5/PZ3GbsgUb74PGfpPXtJ/Pqg5fSOit/nXJ9Hbz64CVw1Pz8ft2bce9ZRozaqVCNtaiR8hvtAG5Px5iUMePFCQT5xqO5krxz3ZoQDbO/OHC9L0Xj4s3f12+0Q34IZl/yTZJGiMvW/oT3v/0wWrIx7Ju3lpY/N2/lohn5MuLLT6yj3gmzaaDRDtA4x0N1JbHvGZL//vcpVH8GtTVFwHUxDMXGuwfvoUI5FnAVEZR/fzWfGMiXeUX3VODYqN9oL6Qrd2cPdLoEjo0Obru5m0UtjQBsTNp4/Zre79slf7P/Hhu3X7Mxafv7fWX1Bt4/Mx/saWMqy+VrXub9M/f0n1+z9h8s3PskLlt3I5/Z7wN0pDu5dN2NLNzneAA60p3DXvPAr/gW9vnqn27hzXRnybZL1y0nbaVHda2DZoqu1Ft+o71wjPZ1y8gFJ+89XI207dDaWj/iv6kNIy+vVmsCZogb7jui4r+AGZroJI5aylFc82i+I+fMuEFooNEO+fodd7/FzHd8kmce/hK9KuA32gH+da/5bLprsNyZMkdhDzTaC++3b0sQVG5JvaLpaO032oF8PbFMvcE6eubg8ztX0+zk+NBBZeoQq7N89GCLTUnNNx/JcujUmX6jvbDPzY8Z9GYNFu6zgKuf+y4L9zmerXbfsLLrqmdv5c10J6fscywL9zneb7QXXi+8tzvX6zfaC69duu5GsqbFUe/8jN9oh3w98qG1S5gz64yyj3uSGzCsyt/DhpVixerFJcf7zdqlHDRzIStWLx7xvZXev2L1YnqSG4Zt29axRO2pyh53YC+geCJNBzBnG6/vvT1/oLm5ruz2bQVuyfb2l12iJxAeWLpHO2VfV5EG3J4OAsrd5t8YiaU02e5eMHX+uOEWvzAr2JTUuCqEsiIlS2/EgvmKoSLiF9QtZhTd9VbJ+3VXFqIBUPgFL9Fg/nHh/+L9t6TA8PzKqb+90yVgAUphDgQOdbo1ZnRwdI7TrWmyVD7NniIcYNjniQaU32gvSPdoQgNDZDtSaYLBGQOPSz9LRyqNGSi91r3JDsID58IKNfnnwn9PugfCUwD8a7oz12yslMuzG3vzDZ8g4JQ5/8rA/3IFMKMq34MXUf7+KqbKXjsMBYYue72tfFQD6oKqbP4zleE32gsaDNOvABAN5B/HzLLHV57h31cFub4OdGxw7r3u3kxQ6Z2+NtVwbcvZVrqcnn6/0V4wFmXMWKlUxvoMk03JXMmmTUmNCud7YHN9HWjtoQ2Gzas0rAgOJh3pHhqtCEHXLJv/Qzr/23RHKo3hqpJ7IRDVoAPly7NgADBQSoMqfR8M3FNKDT6GsvdUpXtLhRSESrcZRR3X9YZJrrt05pfTrak3Sr+yNyZtGoLW4PNUdtjzRquNjnQnpho4F+lOGoKD12boax6eX3kt3icSCA/b5mqXtlHktXRfP1jRssfVRv78TXSeHSm/TnTaxpOyAmQWXzfiPuHll9Haao24z2jU0nmttrRWyq9v9dpsSubLjiZLD37nDtBdWULBaaT7O3CgpP4T0hZOt+0/N1T59+PpkjJRKa+0HK1UT4wGS55baExVvg5RF1T+Y9crv0/UjBA06kvKtEpll4dHQ7Cu7OsjvVcrE6U8v0FcUFyPHPrYCkQwjMrfw73J/orH6012jPjekd5vBSLDtm3rWKL2VGvDvdy8C287Xt+mHZ3jHguaBOvbShrnwfo2nExvfukeFSj7uk73Yja24WiT7h2c19XaWo+tVT5yuKvyx810skdsakmhtkdMYeostl26TnEy10PACOLg0RZppCPdQ6ebork5VFI4q+YQpBzARU2N5gvcVA41Ner/X1woq6lR8AxUi1lSSVUtJq4Npta4qYHKbZPyHxeed9v5oU+mock4+cfFnyfl5IfHFzfeI42K7EDUpbZohFxui/+40ONeeO46pT3mDbE2Mrn8l5Wd7fbPhf+eSCNktgL417TC/MvyF2oXKZdnA5Ege8QUOcAsc/61lz/HhS9ZN5UfduuktX+9dFKXvXZ4+cZ5uettD9yC/bnh12uPmMLVHtOioZLGe6/nDua1lJPPZ0m37PG14fn3VUGwvg2VTPrh71RTK7ZW9OzEPMlqnb86mnTVWyZmY1tJ432kMqYa8mtJWjy3bN7RmXzlKVjfhlIGynWJ1LWVNN49O43CpS3SSI+dJme6ZfN/VuW/FtqiETxTl9wLTkphmk758izn+LFJoPR9kL+n0INlmtOty99TFe4tndVQ1C5XLSZe0fi3Ps8lVuZv9nmlPwJMi1n05gYr2tOioWHPe+we2iItuAPR5dsiLfTmBsvEoa8ZGLRFWkoqsW2RFtJO6SDrtkgLpjJHdf9EgibYqbLHVV6+LJnoMnZ3mOM+nudrZ8/JeM5xHwujnOM+Jn9rNCrlV2ugTrApqem2FVPK1O+yuS4idW0EoKT+k1V2SVnnaYUqVz80VMl+Whul5WilemIqV/LcRuHq8nWI/pz2H5tG+X1SbpqM2+eXaZYRqFh2GRj05vrLvj7Se5V20dqlIdZW0lgurkcOfWw7aTyvctlohc2Kx2uItY343pHebzulI6C2dSxp0Nemah0qvwGYVvS8DXhzO17fZTJulP1OXeavr1uY47755ZXsd+oysrp+2Ov7nnglqedX5uefeju3xnUSE/PMD6PXvMr+p9xA8uUf8qX5OfaI5Ss/+TnuDjHVT32wifOO+Lq/buYTr6+kJbIXU4Ixvn7EQtoijfz36w+jz9s3XxiDP8fd/s0G7Ce6sM6ely9gf/cXrE8fhf3H9Vifmp0vhGFwjvuDWYJnN+YbfODPcVdTFZ6n6X7Y9ueG9q7NVywLc9xX/t3mshOC/PGtTexRB188LlTyeYJROOSjISKN+W2FOe63v/YybdFIfo77y7fw2vr7+ObcI2gbWEe+MMd9j1gjDbH8OSjMcX9x/UoAXlt/P9cf9fF8Yx38Oe59a7+bn1d9yjIybKPncALVBTSXLwhw/+sOgYuaSs5/8KImup9y2PNfQ/mGBtC71mbamSF6nnIJnD0F1WLiPNg/7NoFL2oi91iK3IM5Pw8A/ly1vlD+Gt3/gs2/zy+9Xv9+nMkv1/+Ta+bNYlo0n6+mRUOYDSbGBfujmkPYv9mQz2dPdGF9as6Q4x/D5tcfYv9Tr2fzy/nrVJjjzlOr8/s1tWJ+tp1kcbflJJPyojR/ZBlmYz5v+3Pcd7KMGS8BJ8flJwRL8s5l87L0rvvWwPW+HoWJsfqvHHHcN4jU5T9npK6N+thexLws1805jQdef5bOUBLroiml5c9FU7j57/ky4ptzZ9MXyLDHWUH/XuhZa6CbY1ifHZL/Pn0Uui6MnhLFMU08Lx+bo/C+QjnmmJo02r+/uh528mVe0T3lPJ4ieM6Qe+vsRmgxcR5PDW67qIkVnfmK37SYhVGnaDjDKvmbdZ+1MOsU02KWv98186fzwPp85a0wx/2B9W/5z78yZx9W/vM3XDf7Yn7w2q/8eZsr/7EKwJ/jXvyaAXzt8Atpi7T4+3zt8AvZK9JSsu362YuJ2KU9PJXk3CjN0T259pDzSo6xbHY7wdzkvYeFGGvRgOYrJwTYI6a4O+GRPeuAkvodZ+7J+r/dyxEnXkuDdrh+zmD954dvrmaPswbLna1rNdZ58dL64XlxctosqVd0/1FhnTPfL0ftP64vW2+w/7h+8PnZ8+kKBPnFi2XqEPND3P+CzR4xxZcXhHhuy3ouW2CV7HPRcR4NIY+V/3iEKw89n5X/WMUUq35Y2XXVYRewV6SFX//jcVb+YxXXz7645PXCe5uCDSw97PNDyriLCbk2T/3lB5w8Z2lJPfLkOUtZ+/L3yz5ujE33g8WV49lRFs1fXnK8k+Ys4cX1K1k0f/mI7630/kXzl9MYmz5s27aOJWpPVUaVHwhO9zj54fFJYA1wXiKRWFu0z4vA+YlEYnU8Hr8deCWRSFw/isPPYMyiyjsowxghqryDYRjjFlXe8RSB7Ywq72hNqFxUeTsfYXnUUeUd8AI7EFU+4KEpH1V+IMhzPqq8gqAzNKq8S0DpgajyNoYythFV3sU0AkOiylsEMOnHwNEQMEzqXQfczG4TVd5PpKvyP9WNQVT5HOBJVPldZlJHlXczKFWdUeXz5c9gVHlPQ92YRpXPl3nlo8q7KMVAVPn8vTYxUeU9AsrcqajyjtYYElV+zLW21m87ON0ohsGPZp9a6nEfTVT5kfa55PRndoOo8hoMr3JUeZ3/fvajynsmSm07qnyhTJyIqPJa23hoDMDbpVHlbUzDkqjyoipU5VD5RCKxIR6P/yfwCPnl4O5IJBJr4/H4g8CViURiHfBp4PZ4PF4P/An49nilz3U1SbdcT4Me1es7y3E9ehhoZFH4NS2LIr+pjyDgkSFY8j6X0iV9DfInVwNbGRheWTyt0gOKR944ZSppjjf4Jqfoy1gD9sC/4uPZkCtsHHheSHfQT5/tV1wLuzEkKWShMMMuQxgIDzzOK7zWizvwLL9lil9ZCA78pUGFmyF//grnrjqjyRfr68t/iimt9WxO9VGUEYYbmgkKCidCkf/IyaKNxdOQXQ1Jb2BXmwCDZ6hw/grDeNyBbYU8ocnnFH/we+n05vwfd8i3bAaOnCO/RnyeR65wXVyQNePzZU2fO3COavCcuK6HcjOY5FPeR4iSyd9o/BzllOaFwj1fyG82Ht2kB/N/cvAutgcyfQ6HXKG88suj4gTpgRcG9snly6uSRsaQe6jkNisuUIbmb0VJuZgsbBu43xSD5Vbhk/vH9kANHNtksGx0hzz3MDBxmTaknHOB0MB3hQ0ECPn3q1f0muf/heF/px8wMf1t9naWja6rSbnBks/p1lh+rXaerXnitOOGbTMsRUdSggBOFoU6wZ4D5cCWwgsuMFA3Tfp753/cL5SVKTQUB30trhNWqj8M3e55+elG/useuEOep/LPh9Yh9MC/QvmUr0eYA/tkihotCkXQL/+Lhw8bwN6tzX6Z7TBYxuXLTBNzSP0YBsu7gsHJQeGSon1Q8TGKY4Bsu1xzXY3rFn+njf695d9faH9Eir6vpHzdHVVlwx0gkUj8CPjRkG2nFj1+jtKAdUIIIYQQk5JhKV67OFmybb8bY8y772XWnD5rglIlhBBirFRtw10IIYQQQlSXwpJxlbhZmy29smK8EEKMNWm4CyGEEEKIUdnWknGhaxdvM2K1tp0RXxdCCDGcNNyFEEIIIWqczmn2uzE2bHthmLzOjc+c19GsBV9o3Bfm4A/l2RrtOdJzL4QQRSZjw90EMIzywRQrba8W1Z4+qP40jmH6ZgD/pDR8y64wYp4tVq3nvlrTBdWbtl2QrhlUUX6t1vNeiaR316qQ3hns+jy7zfxaO+fSY3iIraGvV3DlBYSnNAD5qPHFsq5LyBw8rueMHOjOc7LDjjF8nwyKQNl5+ZCfm+857og9946TIRAIl30t63iEAvmQZZec/oy/3XU0ZmD49Szs09vXyW0PvG/Y66PMAzOogvxarHby7tiTz75NMxifOoEYQ1W5HNwudixQeb0UIbbPTODvu/hvSJ4VY0Xyq6g1uzrPSn4VY0nyq6gl41EnEGNoMjbcQ8BRQAflF7YQYnuMx6+VkmfFWJH8KmrNrs6zkl/FWJL8KmqJ9LjXmMnYcBdCCCGEEEIIIWqGMdEJEEIIIYQQQgghRGXScBdCCCGEEEIIIaqYNNyFEEIIIYQQQogqJg13IYQQQgghhBCiiknDXQghhBBCCCGEqGLScBdCCCGEEEIIIaqYNNyFEEIIIYQQQogqJg13IYQQQgghhBCiiknDXQghhBBCCCGEqGLScBdCCCGEEEIIIaqYNNyFEEIIIYQQQogqJg13IYQQQgghhBCiiknDXQghhBBCCCGEqGLScBdCCCGEEEIIIaqYNNyFEEIIIYQQQogqJg13IYQQQgghhBCiiknDXQghhBBCCCGEqGLScBdCCCGEEEIIIaqYNNyFEEIIIYQQQogqNhkb7gFgxsD/QtQCybOilkh+FbVE8quoJZJfhZjEJuONvzewvqurH8/TJS80NUXp7k5NTKpGodrTB9WfxrFMX2trvRqTA21bxTxbrFrPfbWmC6o3bbsiXdWUX6v1vFci6d21KqV3nPLsiPm1ls6lpHXXGG1aqyG/FqulczzW5LNXTX4VY2wy9rhXFAiYE52EEVV7+qD601jt6dsZ1frZqjVdUL1pq9Z0jZVa+3yS3l2rmtNbzWkbStK6a9RSWovVarrHgnx2sbuShrsQQgghhBBCCFHFpOEuhBBCCCGEEEJUMWm4CyGEEEIIIYQQVUwa7kIIIYQQQgghRBWriajy8Xh8CXDawNMHEonEZfF4/L3AciAC/DiRSFwxYQkUQgghhBBCCCF2karvcR9ooL8POBw4DDgyHo9/ErgLWATMAo6Kx+OnTFwqRa3Q2sMKpwmEerHCaUyz9lfDME2FFU7Tm+zYbT6TEGJ0Cvf/7lSmie0j3wFCCDE51EKPewfQnkgkcgDxePxl4ADg1UQisX5g2w+BjwO/nrBUiqpnmorNPa/xi8cupjfZQUOsjUXzl2OZ03HdkddDrVamqbDZwIpHF+82n0kIMTqV7n+t95/opIlxIt8BQggxeVR9j3sikXgpkUg8CRCPx/cHPgF45Bv0BR3A3hOQPFFDDCvlN9oBepMdrFi9GMNKTXDKdpxhpVixevFu9ZmEEKNT6f5PZbonOGVivMh3gBBCTB610OMOQDwePxB4ALgEsIH4kF287Tlec3Nd2e2trfU7krxxU+3pg+pNY2+y36/cDG7rwDDcqk1zsXJ5tlY+UzWlZahqTVu1pmu0KpWxBbX2+aoxvZXuf9fL0draPEGp2jETfX5Hyq8TnbaR1Mp3QDnVnr5i1ZbWbZWvBdWW7vEkn13sjmqi4R6Px+cD9wNfTCQS98Xj8eOBaUW7tAFvbs8xu7r68bzSYWStrfVs3ty3s8ndZao9fVDdabTCJg2xtpJKTkOsDc8zdyjN410wlsuzY/2ZdoVqzhPVmrZdka5qyK/FaanG815Jtaa30v1vGsGqTG8llc7veObZSvm1Wq99QS18B5RT7ee12GjTWg35tVgtneOxJp+9uvKrGDtV33CPx+P7AL8APpFIJB4e2PzH/Evx/YD1wKfIB6sTuxHTVBhWCq1tlLLw7OhOzdnz7CgfOu7GYXPcPTsK1OZcQM+Osmj+clasXkws3MLcA8+lqf5tKPLnT+Y4CrFjisufZDqHaYaq7n4qvv+Ly7RouIlUf3KikyfGgWdH+ei7b6YnuQErEMF20jTGptf095oQQojyqr7hTn5ofBhYHo/7o+NvBT5Hvhc+DDwI/HQiEid2jV0RcMd1Na1N+3HaCXeP2Y8BE811NZY5ndNPvId0bjMrHm+XAEVC7KRaCfhVuP+HlmlKVX34GjGGHDfH757+RmlenehECSGEGHNV33BPJBL/AfxHhZcPHc+0iPFjWCm/0gyDAXdOO+FuXDeyw8dVysDORIDCMaqnEr6jXFdjeK7faIexO19CTEa7qvzZFVxXD6Rp9ynTxOjVUl4VQgixc+RneVGVtLbLBtzR2p6gFFU3OV9CjB25n0StkLwqhBCThzTcRVVSyqIh1layrSHWhlIyALAcOV9CjB25n0StkLwqhBCThzTcRVUqBF0qVEhKA8mJoQqB9+R8CbHzpPwRtULyqhBCTB5VP8ddTE6Vgi5VU2CoarI7Bt4TYqIMLX+CVphsuvqiygtRnFcNw8XzTCn7hRBiNyUNd1G1JOjS9tkdA+8JMVGKy5+mhnpS/ZNzTWBR/Qp5dXD9Zin7hRBidyRD5YUQQgghhBBCiComDXchhBBCCCGEEKKKScNdCCGEEEIIIYSoYtJwF0IIIYQQQgghqpg03IUQQgghhBBCiComDXchhBBCCCGEEKKKyXJwoiaZpsKwUrJmOYPnojfZjxWWNXyF2B5SlohaJ98BQggxOUjDXdQc01TYbGDFo4vpTXbQEGtj0fzlWOb0SVdZkXMhxI6T+0fUOsnDQggxechQeVFzDCvFitX5SgpAb7KDFasXY1ipCU7Z+JNzIcSOk/tH1DrJw0IIMXlIj7uoKqMZtqq17VdSCnqTHWhtA5FxTO3E29a5kGHAQlS2o2WJ3FeiWmhtEwu3sODwdsLBRjK5Hta+/P1J+X0ohBC7O2m4i6ox2iF/Slk0xNpKKtwNsTaUsiYi2RNqpHMhQyiFGNmOlCVyX4lqYpphjjvkCzy0domfH0+esxTTDONMdOKEEEKMKRkqL6rGaIf8eXaURfOX0xBrA/Arzp4dHfc0T7SRzoUMoRRiZDtSlsh9JaqJ9ly/0Q75/PjQ2iVoz53glAkhhBhr0uMuqsZoh626rsYyp3PaCXdP+qGqxefCMFw8bzCisArIlAIhRrIjZYlM1RHVxKuQHz3Jj0IIsduRHndRNQrDVucCmB8AACAASURBVItVGrbquho7E8HJNmBnIpOy0V5QOBcNsbaSc7E951OIyWp7yxK5r0Q1kfwohBCThzTcRdWQIfBjS86nEGNP7itRTSQ/CiHE5CFD5UXVkCHwY0vOpxBjT+4rUU1Gmi4lhBBi9yINd1FVXFfjuhEG5+ZJ5WNnyPkUYuzJfSWqSSE/trbWs3lzH5IfhRBi9yRD5YUQQgghhBBCiComDXchhBBCCCGEEKKK1cxQ+Xg83gCsAT6QSCT+Ho/H7wKOA5IDuyxNJBI/n7AECiGEEEIIIYQQu0BNNNzj8fjRwO3AAUWbjwLenUgkOsq/SwghhBBCCCGEqH21MlT+XOBC4E2AeDweA94G3B6Px5+Px+NL4/F4rXwWIYQQQgghhBBi1JTWtRN9NB6P/x04gfwPDsuA84F+4FfAvYlE4vZRHGYGsH6XJFCMCa09UpluXC+HaQSJhptQqip/l1Hj9HdmMIo8W0PnTUyMqsqvYvtNwnt8PPLsDGo8v07CfFGtJL+KWjJedQIxhmpiqPxQiUTib8CHC8/j8fhNwGfJD6cfla6ufjyv9EeLwaVUqlO1pw92Lo3BoIEK9OF6Obr73uCJl24nmelk0fzlWEwfk3Vpx/IctrbWj8lxRqtcni0wTYVjvMnqF77DQTMXEg1NxXZTmHoqmYw3rukcqprzbbWmbVekq5rya7We9wLTVBhWyl+nvSE2ld7klgldt900FTYbWLF6Mb3JDhpibRXLxmo/v0NVSu945tlK+bXaz6VpKrS5mZ7kBqxABNtJ0xibjnJbq3ot92o/r8VGm9ZqyK/FaukcjzX57NWVX8XYqcmGezwePxg4IJFI3D+wSQH2BCZJ7KRg0CDjvsGKP1ziV0pPmrOEx5+/hRWrF3PaCXcPrJssyjGsFKuf/Q5HHPBJfrN26WDF/thlhIP7kMtNbONdiFrhN5AfzTeQ951+PPMOPI8Vqy8pbTCbY/Nj4mgZVspPE0BvskPKRoEVytLd38Xvnv6Gnz9PnrOUproG3FRwopMnhBBiDNXqWCoFfCsejzfF43ELOA+QiPJVxDQVVjhNINSLFU5jmtsYkWP2+RVjyFdKf7N2KXNmnUFvsgOt5XeZkWhtc9DMhX6jHQYq9o+3g9k7+usgxCRnWCm/VxvgoJkLh5VNK1YvxrBS2zzWdpeDI9Da9tNQIGWj8HSWh9YuKcmfD61dgqezE5wyIYQQY60me9wTicTz8Xj8G8BqwALuTyQS905wssSAoT1Wo+mh8rRTtlIaDjbSEGtDKWun0lMY9ppM5zDNUFUPIdwRSllEQ1PpTXbQ1nwwc2adQTjYSCbXA2jufHDhhPUUClEL/HKCHAsOb2fty9+no+sFwsHGERrMlXu6d6QcHEl+yH5bSVp2tmwUtU9rj1i4hQWHt/tl/tqXv4/WMspKCCF2NzXVcE8kEjOKHv8P8D8TlxpRyY4M6TRUoGyl1HbSLJq/HM+OAttf2R3rynO18uwosUgL+04/fvhw+fk30NZ8MB1dL8jQWiHKKFdOFKbqZHI9O9RgHuuh7Z4dZdH85cPmuO9o2Sh2DwEzxHGHfMHvdS8MlQ+YIZk/KIQQu5laHSovqtgODel061k0/wYaYm0A/vzs1sZZOxWYbuiw1+0Z5lpLXFdTH9mTBYcvHj5cfvUlzJl1hv9chtYKUapcOVGYqvPi+pXDyya/wVzZWA9td12NxXROO+Fuzj51JaedcPeYBe0UtcvTboWh8u4Ep0wIIcRYq6ked1Ebhg7pbGs+mLkHnotSGiucLhuROZfzCAffxicW3InWDkoFwK0nk/LYmd6kkSvPu1evs2laoI2Sz1sYNt/c8A4WHXsDL65fKUNrhRiiUjnR2ngA7zniCgxDc9oJ30UpE6WCONltT7fZFUPbXVcP9NYXyi5ptE92nueUHSrvec5EJ00IIcQYk4a7GHPFQzpj4ZZhw/gqDVV3XY1hGGitAANvDHqSJt+80MHP29Z8MMcecuGwYfPKiwEy/1GIAqNCOWEYEdLZzrJLsG2LDG0X48E0ImWHyptGRIbKCyHEbkaGyosxVzyk8wNzvzlsGF+5oeqFOaY/efRM7nxwIT959ExsNux0FPRC5Xl7h7nWquLPO2fWGWWHzWsjOcGpFKJ6mKbC8ZKcPGfpsHJCe+4OT7WRoe1iPMhQeSGEmDykx13sEoUhnYFQ76iGqu9oIKfiiPFKWcOG4buuxjLzlWetbYJWmGx694oqXzgHvcl+DMskZu7Be4+8nCl1e0+aaQJCjEa58sKwUvzk0YtKhhvbTppIqAXXzezUPSRD28WupnWuQh7NIeW8EELsXqThLnap0Q5V35G56KONGF9ceW5qqCfV3zdmn2+ilT8Hy3jipduZM+uMSTZNQIjKKpUXYTWF3mRH/sfCxy/x9z/71JWTcKqNqDVKmRXyqDmBqRJCCLEryFB5sUuNZqi6aSoMw/T3KdhWBXmyRIwfSflz0M7cA89l7cvf56Q5S4ade+XFsMJpAqFerHB6p6cjCFELKpUXoCuWPWXLr2OXDcSJEGLiGSowbJrHyXOWYijplxFCiN2NlOxih5UbdjrU0KHqQ4ezF3rBVv3pVk6as2RIILWRAzlNpojxlVQ6B031byOZ6eTx52/hvUdeTnPjvqAVWrtounnk2WX8dcOq3XZdeyGGqnSveNqtGETOdTXh4N6ctuC7JNOdpLJbWPPid5l34AXD7pltTdsRYldwvRx//vsDfPTdN6GUgdYeT/3lBxzzrnOB8EQnTwghxBiShrvYIZWGnTruO3BiWVzPxTRMInYEO+dVnOdZPLc9ldnCgsPbiYamUheZhpurG7HiK8NYK58Dg7D/Y4lphodFxj5pzhJSmS10dL1QNpaAaSpywRyOsjEwsAhgZi1piIiaVbG8wPKDyJVrdGsjyU8eOb/kfZu3vlJyz4x22s7Oyt+XWRztElAmwVwIoOw2MTmYRpAj4p8hZVhoDJTyOCL+GUzDkqjyQgixm5Gh8mKHlBt2+ufXf82rff/k3DVLWfTIFzl3zVI69CZCMaficOziXrCOrhdY8fgl3Pv7s/A8d5sV3skWMb6c4nPQ1nwwH3n3t/n4Cd/xX3OyDXhlImP/Zu1S5sw6w3+eH6WQZ5qKzUYn5zy5hEUPf5Hznria19Nv0hPokWH1omaNVF64rsbORHCyDdiZSEnZM/LInrxKw/DNYP+YTUkZvC+vYtGj/8E5T15FT6Bn2LbNRieeluUeJw1l0AX82x+v48OPXsK//fE6uga2CyGE2L1Ij7vYIUMrs9OaD+ad8U9x7pqv0ZHuBKAj3cml65bznaMvI0iqbO/TzvSab2sY/mRQOAenn3gP6dxmVjzeXhp4K7g3mvJRh8PBRmD4+c4Fc7Q/uazkOl717K18+eCziMTCmOng+H1AIcbIjpYXoymjKjXu+9Mbuff3Z+1wD3yhh93FxTQU333xpyX35Yb0Jr75wl0l29rXLeN7x34NkOBkk0ESj0vX3Tjke/dG7ph3peQAIYTYzchPsmKHFCqzkG+0H3Xkf5L1HL/yUNCR7gRl5nufygSN29le85F6yiYL19X59aYHGu0AsXALycxmtNGNq+2ywbcyuZ5h5zs/5DdX9jo2ButwkbWBRe2qVF6YpqoYsNGzo3zouBtHLKOKy8OChlgbqewWYMcCZxb3sH/wkf/gnDVXc/rMkzloyn7+PpFAuOy9mnIyMjpmknC1VzYPuDLqQgghdjvS4y52SKHBvWL1Yg5919lstpNgJ2mLtJRUItoiLZgqkB9ayvB1ZaXXfGwU96q3NR/MsYdc6Af623f68Xxw/vX8cvWlg73xxy4jbDVx2gl3l5zvwlzZctexLhDFlD4csZvZ1vx019W0Nu03YhlVXB4Wx5F4/Plb/H22N3BmLpgdNvLl6ue+S/uBn+WSdcsBSDuZsvfqG8kO9ou9HdAlc9+lXN39GMoomwcMGSovhBC7HSnZxQ5xXe0HdNpjyiz2iU1jamgK187+Im2RFiBfebjhqMUE1Mjrykqv+c4rrOULMGfWGX6jHeCvG1bxxEu389F338Sn3/e/LHrP3TjWVNIEhjVAHO2SdnNceej5JdfxykPPJ2xYEvhK7HZGs6ykUsaIZVRxeXj2qSv5xII7eeaVe+noesHfZ3sDZzraLduT2hRqAPL35Yy6Nm44avGwe/X2V35Gjtywue/SC7/7USiWHvb5kjyw9LDPo5BrLYQQuxvpcRc7LF95jbLV3Ez7U8vpSHdy/J5Hcssxl9NrJ+nJ9eN5GtezB9aVDWKF09KzvgsoFeTkOUt5aO0SwsHGYfNt/7phFccceB6bXYevDMQhaIu0sGx2O63kK3y5YBbTUGxJbeVnr/+e9gM/S0Owjt5cP/etf4jLDvqcXC9Rk0Zaqm2slpXM987nV88wTcW8Ay9g89ZXRr285VABZZbtSW0KNnDbvCsxUCSdDLcl7qf9wM/SFGqgKVjP9179JV3ZrbyR7Bg29/2OY64qiVFRLkq93OO1xVAGYTOYj0ESCJN2MoTNoPS4CyHEbkga7mKn5IdzLvcriKveeppXel/nywefRUt4ClODDYQ8GyfcTM7p5f4/XLRLl0uarJxsiLpIC+898nJi4ZaywbR0sJ6vPHltmcr8UnqcXtqfXMZRzQfy6X3fz2f2/QBf/dMtfgP/hqMWE1SWzHAXNWdbQ+F3xbKSOzoFqKQhTYCb5nyZL6z9pn8fXnXYBfTlkvzvXx/gkoPO4Lw1V9OR7mTVW08D+Yb9lw8+i9PfcTLXPH9nybE70p35IHdFf2uz0ekPxy/+IU/K5NqhteZLT39r2A88d867SvrchRBiNyMNd7HDTFORYzAg3UFT9uNz+32QhmAd08LN3PHKz3iq6yWWHdXOXtYU7v39vw4bjlpu/fBKPWOiMtfVtDS9DUNFMQyPD867jl+uucxvqJw8ZylaWWWH3jrKpn3dMppDU/jo299Lxs3SEp7CbfO+Sq+dpCPVyW2J+zk//jFaTanUi+pXXI4YhslPHxk+FL5Q9pSbn17cO26aimS6i0Aos11lUnEPfN62G+3DGtJHtXPdkRcTCYQwlMGm9Bbueu0XXHHIOfQ7aTrSnSXlbm+un5l1exE0gnRlt5Ycvy3SUhKjotwc+nK98qK6OdqlOTSlZITU9177JY52kasohBC7F2m4ix1S6MXq6eumLdJCc2gKF77zE1z93Hf9SueVh57P3/o30P7UMu6c+9VtDkct1zP2ofnLmBreG2W7aE/jGQZJTBxXIuYWRKMmnu6hp78H0wjgofn9M9ex4PB2wsFGMrkeHnv+Jt477/ryQYww6Eh3suTQC8h4Wa569taSa/i9137Ji1tf45Xe16VSL8ZdwDSI4WJ4nn//A8O2FcqEYNAg6/6TXwyUI598z10lZU9b88HMmXUGmhxWOB9YrjA/fegPhoUy6ae/K99bPxqmqQibKdA2KIuMW77hX7Yh/dQybjnmci588hsl92TOc3kjuZHj9zyS02eeXFLuXjv7i7SGmlg2u53vvvJTFu5zPE2hBlpCUwg7YWzy56nSHPriXnlR/SwjwBdmnV5Sbl912AVYhlTvhBBidzPhk6Di8Xj9RKdBbL9CQKdnXvwONxy1mHMP+IhfeYTBCMif2++D+V5dNPtOP55Fx97AJ068nUXH3sC+048vGY5aLkjUL1a3k9LdOL/4Pc41t6Fv+RH1qX4C5oRn3aoQjZr0Z1/n3kfO4Y4HPsi9D5+NbSc57tAv+I32tS9/n2Smkwgmy2eXBrJaNnsxwYG5tHtEpvqVPyi9hoXnshycGE8B06A+1Y++5Uf+/d+Q6qfezpRsK5QJAdPApJdfFJUjqewWP3BjYcWFR/60jDsf+CA/efRMbDYAlA0+t63AdSMtI1d4Pehs4JWfn8WLP/ggr/z8LILOBkxTYZoKN5IjG07jRnK4lG9Id+f6ht2Tjna4/ZWf8R/v+tSwcvdL676FpzV7qlbOi3+MZS/dw9mrr+KCJ77OW3qzn8bCHPpiQ3vlRfVztTes3L7q2VtlOTghhNgNVUPrZ8NEJ0Bsv0JAp41dLzAlEGF6dI+ylc6GYB1tkRY0cOzBX+CRPy3jxw+fyyN/Wsa8A89DebFhxyzWm+wgnenCOya/drHu7sW9++fEpAEJgKd7WLH6kpL121PZrTz0xyX+eT7ukC/w0XffjJntxVt9M9+ZdQYrTriB6w78NE89dRWPPf11bppzGQaq4jUEqdSL8RfDxb375+juXiB//zt3/xzVtbVkW6FMiOHi9veVlCNrX/4+J81ZQkOsbdiKC9taX32kwHWF3vifPHomdz640P8RoLjxHjZTvPZgO7m+/DFyfR289mA7YSvrr9FeiPqulS7bkO7O9pZs60h34mmPruzW/FSWMvesxiNjZrjkqeFD4XPBLADBXIhls9uH/JDXLitH1Bi30sgJLd+RQgixu6mGhrvET6lBhYBO05oPxnPSBA2rbKUz7WS48tDzWf7SD9ic3jSkwnwJ2kgOO2axhlgbdnoLOjY4PFt392J40psA+UpbccNizqwzeGjtkpLz/NDaJViBMP984iZ6//YowVwvDz56Hg+u+jwbu14gmenCdW1//fZibZEWenP9AwHqpFIvxpfheX4DvUB396JCwWHbDM/L/+vNlJQjHV0v8Mwr9/LJE7/HHlPeySlHX82iY2+grflgoHjKznCVyiSlrFEtI4e2/UZ7Qa6vg37DpX1daaN6+Us/4IYjhy+nufIfq0re3xZp4a30Fq489Hx6Bu7Noa8HDatkKPxBU/bjhtmLWXr45/EMD6IOAK1eC3cccxW/XPDf3HHMVbR6EsOi1lQaORGosPyqEEKI2lUNDXepJdQgz47ykXffzCGHXcJbTpZ+J8VVh10wrNLZZDVwy19+zKq3nsYIlC6t1JvsQGOXHPND85f5FeWGWBunzl7CxsSvUMmcv59qasAzqiHrTjyzaP32tuaDaW7Yl1OOvpqPnfA/nLbgVj5x4u0sOLydTLaH+iNOJ7bnQRjhweXipjUfzHvmfhNbwU0v3zts/fZrZ3+RPSMttB/4WaZYdRP2OcXk5BkGqqmhZJtqakBnc8O2eYaBZxgEn3iNDx1+TUk5cvwh/04qu4UfP3IuL63/FVMbZnLqMV/nrFN/xpHxz1SMIF8IXFd8rELgupGXkSskzCJYX9rwD9a34Wg9rJd01VtPU+963DX3Cla+57+56egvk3FynL3/h4fdk/eu/zW3/OXHhIwg182+uLTX/KjFNIUa/AbdQVP248J3foJlL93DeWuu5rw1V/N6+k16Aj0AmOkgwXQEMx2URnsNMpXB9UPywPWzL8aU5eCEEGK3I9FLxA5xXY0bbOQrzy3n1rlXsPylH/CJmSdx89GXEzQDeFrjaY9eN9+jnh9mXVopbIi1oQaiNucjMGtCwX34xAnfJZPuxE5vYeML93HAYedh/OrPaPIVdPPMD9OHCUivu6EaWTT/Bta8dBtHHPBJfrrq8yWR5P/w3LdJZjpZOO86/vjavcw76gy8TA8NsTai4RYOPnQxf01u5Jsv3EVHupN3NbyD7879Kh4eAWXywBuP8Z1X/4+2SAu3z7sSN2RDSooNMT6SmNSf+WF/uLxqaiBw5ofRViDfgB/YNlgmQP375tP429V8cu438BrCBBqm4CiPn/7hIt62xxwO2//j3L+qeFnKGzCJ+UHbihWWdfv0e+8hZ5dGlbesbS8jl3Gj7HfqMn+4fLC+jf1OXUZSWcMCRX7mHe/HiDaS1R6O63DPayt5quslrpt9MdcdeTENwRhKKe5I/IxzDvgIl627kQue/DrH73kktxxzOb12ks7MVqZY9fm1vd0wt869Ak97fP7Ja4bNgV562L8RCYcl2GSNc7XHs10Jv9w2MPjDxqdZ0HaUTGwSQojdjNJ61//CHo/HX6B8z7oC3plIJLa5YG48Hm8A1gAfSCQSf4/H4+8FlpMPSf7jRCJxxSiTMwNY39XVj+eVJqm1tZ7Nm/tGeZjxVw3pK15mKWeG2JTdyvRoC0k3Q1e2h+5sLyv/sYrTZ57Mfesf4lPvOAVTmYRNi72sKD9++By/wnzSnCU888q9LDjscuxM6ZJwQTMFOJjKxNJRlOuNSVT5sTyHra314zXNYwYV8ixALGbieD30pd8ild3C2pe/T0fXCzTE2vjEgttw3CzP/20F++41n8bYdDzPRSnF5kwXFz93J0sP/zzf/vOPuOKQc4kEQnRmt/rX8dwDPoJCETLyt2g4ECKQDG9X4qsh31ZSrWnbFemqlvw6kJZRf77tjSpfsr9l0u2+ieOmuff3Z3HmKT/l/j98YVhj+/QT78TzjJJo8sXLUjbWtdDdnSrZZhkxHN2D69lo7fL831bwrrefikVpxPmyUeVDNq+n3/SDin3mHe/npOnzuHTdjX5k8OtmX8z/rf8tT3W9xC3HXE5dIErGzeFoh7ARIufZdOV6iJkR6qwIrvYwlIGlAoAm7WZ5I7mRxmAdN7x4T8mScd977ZcsPfzfiKgQRmriG+6V8sM45dkZjJBfq7WM8NXZ9Nkp3kxvJhIIk3Yy7BVppd6KQv82q1YTpurPa5HRprUa8uuQ9NTMOR5r8tmrJr+KMTZeXWcX7cyb4/H40cDtwAEDzyPAXcDxwD+AB+Lx+CmJROLXO5tQUVnxcm3RcAvzj/46jVaMTdluLnlqeclyRfetf4iF+xzPVc/eym3zriTkZAB431FfxTQsMrkeHn/+Fjq6XuCEQy9hcK3jfC9X2o0M+esDw/5ckJ72Qaap6Mv8o2QN6pPmLPHPbW9qI7/+45V85N3fxnVtfvzIef5+py64PR/oyvO47KDPkdM2Fz9xfcl1vP2Vn/GFWZ8k42ZpDk4hp20ZpiPGleN69KAAs+T+L7dt6P6WkWbFHxaz4PD2gd5wo+zwdtfL8eizNzLvwPOJxfYkmdlUuizlsTdimhY/eTTfU39k/DO86+0n+4EhCz33UWtvMpnS8sl1Nckh67lnPZubXr7PX3t7WriZ85/4Wkmv+GXrbuTbR3+JX/5zFQrFpkw3l64bLGdvmL2YaaGpbLX7OXfN1SVLgdUFonzjhbvoym7ltrlfLbtcWHe2l2h0D9xIDke7BJRJMBeS4fI1aEuuxx81Vbi+9VZ0opMlhBBijI3LJKhEIrEK6AKagdcSicSq4n+jOMS5wIXAmwPP5wCvJhKJ9YlEwgF+CHx8V6RdDCoOxjT7kC+wId1JwDT9RjsMLle0cJ/jaQjWDUZAdrJ42sXzHH788LmsePwSv1e40vxSsW3lAmT9Zu1S5sw6g32nH0801MQpR1+NUgYrVrf7+0XDLWjtcvyeR9IaaaI718uX1n2r7HUMGCa3v/Kz/PB5LddK1I7CPPRCZHmNLhtsrrvvDQ6auZAVq9vJOltZ89KtLDi83Y8RsfrF79CT3ODfP4e8Y1HJag6FYJueGuUoAmXSld3KJeuWc96aq3G0UzYyuGUE+N93X4NlBDCU4pZjvsLKE/+bW+deQSQQxlNwybrlw4bBd2a3+ktxFrYV9mkOTSHj5pgaaiDn2Vz357v9yPabjc5hS9qNpaFL4O3KvzVZ2NotuxycLVHlhRBitzMunWfxePxMYBnwKrBvPB7/VCKR+O1o359IJM4ZOE5h015AcbdJB7D39qSpubl8oK3W1upeVn4i09eb7B9s+EXbiOR68coEWepId9IUaqA720tbpIW/979J2AwyRTUwpW5vf15oQ6yNDx13I411Laj6Xf8bktYeuWQXDaEcygxiRZtQNRTAp1yeLb4mg9s6qIvsydwDz/WHBX/yPXeVBKQ7+NDF3P/GKs454CNszfURCYQrXsfX+zs4febJaDSt0QYCddtfbFTzfVWtaavWdI1WpTK2YDw+XzKdoyHWRkfXCzz+/C2ceMSlLDp2GSsebx82QuXdh/5/9s47Poo6/ePvKTuzJT2hrICA9CY9QAAB704RVAQbd94PT7AgqAgBxEbxUBEIFkQREJGz93KnnqcCUpQmIkUpigi4BFI32Ta7M/P7Y5MhS4JdjDLv14sXye5md3a+9fk+z/N5bsIf8CGLCl1a/tUqG1f5GrWKOOOJPPemGftB38swDeZ1z2WCVa5NqJbz7nVlYZgmfi2QENF0X9ebCesa0z59hBmdx9Q4bl2yk9PVNOZ2m4AiORLU5ce2vtyq/V4ZWVMYKWV7yV5yN+XxZJ9/UseZ9jPu+om/817/ASZ8PNf67HndJ9I8vRHw2/f37+qvv/W1fRcHA8Ea+4BhGrX6uqF231eI7xmiwWIifh+p7tq1Z/i++bWS2n6Pf03s727zR+RkRb3eBLTftWvXt61ateoF3A38YMO9Bmo6pv9R8dN2jvuPx+GULKNblhyEYmEkQaxxw1lHTWf53jeZ3W08gWiIZ756m4ntRhAMHubPXW8lPfl0ZEHB0JMpKAh8x6f+MkiSgMpRov5DiA4XRjSEI6UBEer85NDQkz0x1tRnq7ZJJSkeLy41jRcqwuIBgpEi63Ud247i1s+WkNtuBJM33c/MzjcQioVrbMd0JZn7dzxFpprKpPZXcjhUiGzKPyqk9rfut99Fbb22XynH/Rd9v+/jl8px/zlIksqQ3nms2/EY7ZtegCjKuNUMBvaYgYBgpewEwgWEtbhoownVar3/d8MMLu73sPW+pmmcQJhOTvheNeW3Q7y+++mCkwXNL8V0ppEkOpjdbTyTq+S4P5g9GREBRXKQ224Ey/a+wfaSvRRrfissurJU4/HjNhQLY6ombx5Yxbi2V1iv+UfzCy2jHY5F1uS2G2F57sMx7VdpG92lMWHj3ITPnrBxLkt6Tqd+UuaJctx/8es4Eb/XHHfZI9XYB2RBqtXXXdvvqyQJKLFD1YQlNbnBCde+2tBfq1Lb7/Gvif3df1CO+0m4GptfmpN2dLhr165vK/7/CKjzAWnh6AAAIABJREFUM9/uEFC/yu9ejoXR2/xKGFE3Q/pUlGszDZolNcApKsztPiGhFM30TqPRjCiT2/+D+7Y9wYytCxnedCCiIJKZfAbpSQ0RDRMxWIJqFqMo398NJUnAo4TwOPx4lNCPDrF0OSLowUK+XjmLL165lq9XzkIPFuJyRH7Svagt1FSu6qI+86p5BCtDhVM8XhxKKplqGmckN2ROt/Gc5q5DY4+X+7ol1pCe3W08y/a8AcDwpgO5Zt1dDPng5pMSUmtj83OQJAGHM4Qgl5LkqstZZ96EJCpo0QBHS3bjVtPZtOspXl8zkUC4gHOzp7F935ucmz2NsOav0ZsuCrI1zj776nWG9J57XJm4uaiCas1RqlMkppRRECumTDQJyRBWytHVANHAt0RKD1C8cjZHXryKkB7hxX3vsijnTl4ZkMfS3tMpiwa5/uO7GbV2Onk7lnNLh6tY2PMOUitSkIC4yFynMdXm3zRHMg/ufIYLGvXjwZ1PW3N0SpW/rcQXKiBFSbL+XkL6VULaq9aVr/rZOnZI989BEWXmdEtcg+d0m4Ai2mokPwenFLSMdgCtzMfet3LjB3E2NjY2vxEna2Y//lgw9jPfbz3QqlWrVs2BfcDfiIvV2fyK6LqJU2nEZf0fwxAVSmNBDoWOkiS7md9jCqIgoJsG/9r7bzYW7uDRXrcDx7w6S3Km8uwHV1nhp+d3m0bZ2kU07H4d+necYleefO9+44effB+PYGp89d70hEX4q/em03rYYuC3V1X+qei6SYozi4s63orgcKF46iBKTgwzluAR9BVu45Pdz3L5gMVEBImb217B2IoSUf3qdeWalhfz+O5XubPjtdRzZqBIDgrDfr4qP1Sjly53Ux5Les5ACtk57za1i6oimh5nFuf3updAuJD3Nt+bUCrxT12m0K/jzUiigihKdGx2MWs+W0CvdtfU6E0XUbms/xOWqryEh8sHPI5pxhAEGYce44sX/w+tzEfKGf0Reo8lt4oHfXqn0cz//DkKIyXM6Xg9DWWVZgNncWjzE0iSwsbCHZxV2pW8Hct5qMct3LHlYXyhAtqnNecfzS9EM6JkOdNQxWOl5LaX7OWhz59hRqfrqevKwDBNjoSKmLPjSbaX7OWKZoNZlb+Zq1teTG67EdR1ZtTonY0ZsXgN+G65OHUn+eJRcj/Os649r1su9aQ6hKXwTxayq6wrf/xnS3bRsp+FZuj899BaHupxC5IgopsGb3yzkuFNz7Pv7c/BjFr7hUq0Ml88eobjxXNtbGxsTg6/VbLOz5Kt3bVrVxj4B/AysBP4Anjp51+WzfehaQYC6URMnUPBozzz1dsYmNy4fhbDVuRy0/r7OK9hHzLVNHRD54bWw4G4sRfS/AmCT+v3Pkta2/PZ81YubrnM8qQf7113OSI//+Tb1E+wCP8BvD1mDCkWRZVcCJKDmBEBQbA87BA3PHq2vZoPtszBHzrKnVsWWEbBDW2GM2nTPAojpQgI3LB+Fhe8P45bP3mQKR2uonVKkxo9ZRq2uJRN7UKSBBxKuSXYmN3mSgwzxjsbpiWEvr+zYRq6obH0raE8v+JqguFislLbMLjn3aQJHi7IvqtaFAuGB8UA1QDFAMMA0xQxTQEROLBmnjXHuNoNsYx2OCYYVikYt3jfW5S70yhNyiJlwC0UR8qY1WUcbx5YxdSO1xGKRazxObb15eTtWM6otdO5cf0sjkZKeDB7suVhLYyU4JRV7t/xFMNWTGD0xzPZXrLXSnXpV68r+aECJm6ax+FgAdM7ja7moW+a1IAlPadTx8giLIXJ3ZRX7aCuXC7n6o+n/2QhO0VTyeuWm/DZed1yUTT15zf8KY1JTt1O3LT+PmsNzqnbiZ+5zbIRHCjJiUKWSrIXbDFdGxub35CT5XHv2KpVK3+V390VvwuAuWvXrpQf8ia7du1qUuXn94GOv+hV2nwvkiRQJpZjGAYu2ckFjfqxZPcrVlkjv1bOc/ve4ZqWwzgYPEKGmkr7tOYURkpQJZX/bclLEHxyiEloZT60sm/56n/TaHHhfMyYluBdbzFoLg53ZoLh/WNPvg0UlGRvwnsoyV6M37G3HeLtoWkl7Nv7JvU7DOetDybhD/gYdtZDbP3yZQZ0zsWppGKaOi4lhW6t/o7gzEwwCvzRQHxz3m5ENc/64oq2fbz3dIojfivP1uvK4puAj+ae05FCv+97aPPHwNKx0AXLSHcqqRiGXmPoO4A3swMAgfBRVIcHAQVVTePoR/MZ0j4XyZ2B4srC46lHqPArdlccIKae0Y/0Xtfw2ocTEyKIYoFCAvnbMZ1pNR52ZTnTWNjzDpIcbq6piHipNJ7dkpu/Nj2PZMVNqiMJryurxmiX2z+ZzxO9Z7A4ZypRI4YkSHx4eDPDmw5kt39/Qrk4zYgyvt3f+e+BdQCIoshDO59JmK/nf/4c93S+ESXkQsc8YUh7QaSkhqib6T94/Ou6SR2yWNJzOjo6Enb5uV8CE5Pn9r1TbQ2e1P7K3/rSfteEdTfNB+VVy3GP61TYfdbGxua34WQZ7mcc97sAXAa8AkRP0jXY/AJoSoSCSAl11PS4oJk7i+FNB3LX1sfIVNO4puVl3NTmSlRJZtGuF9hYuJ0pHUaSqaaxa+9L1QSfLus7HyXZSyzsRyvzEfUf4uuVsxK863vemkiT/lPY/eY46zp+7Mn3H3URVqQgG/+bS4ucCby16Zig1u4DH9Cj0y2UR0oJ6CFSZRcvrByNP+Bj+Pn/STAKctuNqDH/tX1ac4Y3HWjVl65UoH5u3zsMbzqQBV88zz2db7SDMW1qBU4piFZ8iJjqskLdw1opsuxiUL/HEGUP0UgxWz9fRDBcQFkon75njk0Qo0vxeLmodx6Nz5oMpokpKISiKnrYnxD1k9b2fF47rhzcvzfNYEj3XAL/noSkazWGhac4PJRq5czYVL1815QOI4kaMUZ/PJM3z36Q6Z1GI4tyNSM6U02jUCtNUJqf3W087x5aR267EaSrKWSqqbz89Xv866v4WL+v282sPrqFUCxslaGrel1VQ6pPFNJeHPEnXEdlfvqPGf+6biKFFOtv9N/x3FtbEBAY2fwiSqIhMGUcopORzS9CqFHD1+aHousmmtyAlkOXIgk6uikR1t32QZONjc1vysky3E8DniQuIHcv8DywC5hCvEb7/pN0HTY/EUUREaUy/EBxxE+WmkoDd11USWHixnlkqmmMbT2CmVv+gy9UiteVyh2dB/NV+UGaJJ3GvB3/4qoG2bBrufWe/oAPPRqi6Z+mcvCjBQCIDleNIe1q2umWx/ynGN2Vi3DbS58kFg1bCs+//0U4Sqjch9NT3/KuG6aBX0pj9EfPWW1xd+dBuJ1ZuJ1ZSJBgFCzb+0ZFeG6isvyJFKgX50xl0a6XKYyU2DmUNr8psiTiQUc0DHQziqSmohshBmbP4J0N0/jy0BqathrFlG3vVhkLt1NfkQmEjpDqaUBx2X48ziw8ziyy21xJVA8TFoPkr32YBt2vA7kBpq4lzEuiM7VGL77kzsBdrz1RVxrTO4226mtXGs8P7nyGK5oNTshdr/SS1nNm4I8F8bqyOBQ8Srqaglt2VjOir2k5zDLaIT4uJ2+6n8d63YmBgYhI3o7lrMrfbD1/y6YHWJRzJ7IgM7f7hASjvzJcvdKIrgxprwyX97qymNt1HIv2vJbwfe389NqBKEiEDYHZW9+3+vjULhcgCnbb/Fx03SSgu6qodP/e9ws2Nja/d05Wjvs84HbiBvvrwHm7du3qAfQE7jxJ12DzE1EUkYh+gGdXjCIY/JZ6zkzKYyE+PvIZhmlUlBkaahntAL5QKTO3/IdrWl4GwKr8zajOTOs962d2YEi/hzBcKYTEY5X8jGgoIa/MU68Dp134L/yil0YXv0L7K9+m5dClP0qYrhJdN1E8mQSiKQQ01x/AaAdwULdxP2KCyYoteTz/wTUEDLj9k8S2uH3LW3Q7czwdO09izs6ncYqqFY67vWQvC754nlRHckKFgHQ1pcaQ2fxwEZc2OYclPeeAkYapOpGk2lHb1ubUQZZEkoPlmAueIXbPIigJITtTMGSF1Z/NZ2D2NDq3H8ukDS9WGwu6nAqyk8Ole9j65cuc3WUSZ3e9FV2oT8jI4nAgTHr2KA5tfAynFESQlIR5yQiXWjnwlaR4vKie+njPn8e30TLcspuHetzCU33v5rFed5DhSGFV/mb8Wjn96nW1ctevXXcXeTuWo2OQJicxp9t4nt33Nk9/+R9kQaqWk97QU6/GcXk0UsxFH4ynRCuzjPaqz/tChYxcOw0RkRmdruf1sx9gSc8ZZDhSCTqC6K4ouGMEHUEyHKk83msGr5/9AItzppJqwKimA4/LT59g56fXAnTT5Pm9G5nYbhhLet3IxHbDeH7vRv4Qy9vP5NeojmBjY2PzW3KyPO6eXbt2vQjQqlWrWypKwrFr167drVq1speXWo4olfHah7m4nVmERYVSrZRZ25byaK/bMUyjIgQ02docV+ILlXK6x0t5tAyvK4tkJY0Ujxe3M4senW7kiU+mURj0ken2cm3/u/DsWo0zvRktBs1lz1sTcbizUPrcz4x1KkcCGnU9Arf2zyBNjKDrxgmu9tRC09207DWB51ZeZ3kARdlTY1u43acxZn087L0wUsoNrYczp9t4Jm26n+0leymNlvHK3veZ2fkGMtQU9Iq2raZAresIhpc73zc4EghXtItKmmS3i83Jw4OO/sSrmMV+aOyFZCdGtBzVlYnbmYEJlIYKahwLReECHlw9kky3l9HZc3ErmRwud5L3kcyRgEldTwYT+kQ4rW8uAiYOd3pCqk3Jzn8zJGcOr6+bZIXYD+k9D11P5qh+xKqz7nVlMaPTGExTIGJEeDB7MqlKEhPbX8m16+5K8JpP3DiPxTnTCEUijG/3dxyCjEOQyFRTmdJhJC7ZSSgWxvEdoezt05qT5HDV+LxfK7dqpy/KmYpkihTrfiZuPOZZr1S+z1RTuablxUzadMwz/2DX8SzqMQVdEHCIMi7dgxa1x/tvjYDE35oM5pE1UkXfdTKmz2AETu22kSSBo2JBteoIdcj6gxza29jYnIqcLDdZVenu4uOes2fQWo5uxvAHfHRsO4pbP30Ml+wkU00jEAvxwM6nmdNtPCE9jNeVmvB3XlcqAuCSVeZnTybVMPlr/8UMyrnXMtoBCoM+Fm2ZSmrnS/ni1Wv4euW9NOk/Be95C5m9TuVIIN5FjgRM7l2pEZPjYkiyJJIqmaQLOqmSiXwKen113cRESAjbjUaKa2yLqvmy20v2Mvrjmcza9gRLcqbx6oB5NPLUozBSimZEeWDn0xSES5jTbXyCl21qx+swDQ8Pr5artYvpcNgeDZuTgiyJyIYBKR7k8X/H+Gs2n785mh3PX0HR1pcZ0GkC/90wg0i4oMaxUB6Jj4PCoI+FGyYSjKnMPa5Pz1ujEiaVslh8yarMdz1zxOt4O16BO2oy/KxHGHXeywzrehcpjizCUiQhjD1TTSOkh0lR3KiSwqxtS/nHmqkcCRfVXNPc1El2uIkaMVb4NuILFzL/8+cqROhEGid5+fDwJ0zteF21cbls7xv8o/mFPLjzmWrP39ftZpbtfcP6nCPhInb6v7KM9srHK5XvL2jUzzLaK58bt/l+vgoe4aIVuVy97p8c1o/a470WIBouy2iHeN99ZI2EaJzaJcs0JVJjdQRNifzGV2ZjY2Pz0zlZlo55gp9tajmSJCAKEikeLw4lFV+oAL9WbuVZrsrfTHk0RIbiYXb2ZdYm2etKZVb3SymIFFAQLsEjuziy7SXkaARdj1hGeyWFQR+6EUMr8xHI387uN8cRDBRbm5FKjgRMDIRqYbLmgmdIDpafcsa7ooiYmAlhu1s/X8TdnQcltMU9XS7AIZrWZr6SwkgJoiDwTeAwsiBzTcth3LX1MVblb7YM+/k9pvB47+nkthvBgi+exyMl19guoUAhSuyQvZm3+VWpHPuGvwxp2J8x3Fhq7wBHPv0XetiPP+Bj6+eLmN39koSxML3zQN7fvch6v8KgD1NQa+zTuinx2tpcguHieL6r5sIUHJimzpfv3MIXy4ex/9Ubceg6mDEMopahUFm1Yda2pezxf8PkKuXhiiP+amPR68pCQLBKevWt34XJm+6nMBKPGNBNg/3lPpqnnM7bB9fwUI9beGXAPBbnTGXdkU/ZXrKXFCWJVfmbqzyfx0M9bsEpqmwv2Wt9TnHEX02MEo4p35/oOZfstH62jaDagW6KNa+T5qm1Fh7Piaoj6PwBSsDa2NicspysUPkzq5SDc1f5WQCcJ+kabH4kkiQQ5RCrtizkvB53URYL4XVlsWzvG9zVeYy1KL51cDWXNj2HRbufZXyHAaQraWSpKRhmDDPmIBgLo5k6aR0vRhCcGIKDcWe9QHnkKO/vXsjXxdvIdHuRRBlPvfYE8rcDYAbzqetJTdiU1PUIiJjHwmRTPEjDcsCtYJYX4El2U3oKrcuSWM7/Ps3j3OxpljJ2MFxAphhldsf+iJKLVFcW/1s3gfN7z+GRnrdSpJVRHPHz5oFV3Nh6OEWan1nblpKppjGj8/UJm53tJXuZ/ulCbulwFXk7lpOpppGsqNT1CNXaxelMoiRUjOiOIZoSTkPEaQaIlZaT7JAIGn8EMUCb3xqPZCL4yxGy0kAQiAmBaoKWsfJ8UjxeDhduI9UoZWGv4ZRHSklx1+GVrTP5unib9dpMtxeMEHU9avW5RojGRTQNDSpKRwqiRKkpkT4wD8LFRPe+i25oGEQRRdUKU68q7ni8IVwpCFn5vNeVxZxuEwjGwrRPa872kr0UREoqRD8vT3jdg9mTOb9RP25af98x8bjuEwCs/PnzGvZJeH52t/FWWc6pHa9jwRfP84/mF55Q+f5wqPCE4faV/BRVeZtfHkk0apyPRdFIEG80RJEAErFTJJ3pRNURfoygoiQJuMWgvYbZ2NjUGk6W4d7sJH2OzS+IpAR5acUE/AEfLiWNnA7Xk9dtAm8fWotDlK1F8az6XS1v0qr8TUB8gVycM5XZny5jfLu/IwoCuhFjvx5j8sZ38AXL8LqTmd75Tj768hEGnfE3nLrAGefO5Kv/3kEgfzuBz5/itn73cM+qWEXunsCt/RXkWATRMIileBAuOJMj79yGXupDSvVSZ1gekvLjhet+r+hmjC8PrSIYLuKSfo8QCBcQ1kpZ8clsfIXb8GZ2YFDPmXicmRzWypi46YEElevSaIA7tjxcIV5VQH4NG/bCSAmBaIjcdiNoldqEvO2PMabPSB5ZoxxrlwEKZWYhN3+2GV9wJV53MnOyz6VB4Ft0U8eMhnCnNCAo1Tll2sbml0eWROSycqIfb4WezTGTnQgpyVbFiUpKdv6bIX3yeH1NLpFoGe+um4zHmcUFvedwcftxnNNyBGWRIj7a/yZ/bvZXtu56mAl9bmDeGtXq07l9NUS9gGFnPYRh6CiuEKbu4ZuYwaTPd1pz2Ozsa/ly4xyO7l/JmRe/YBnkVY11v1aeMK62l+zluX3vsDhnKrppICDw9oE1vHZwhWVYF0f8VgRM1XBfX6jAyqGvfGzixnks7HUHDkGmeUojrv/o7hpV5wUB5m5fzvaSvTUeHkzteB2v7v+AS5r8pZr6fGX+eyW2qnztQJJCTO7vZvbKqNV3J/d3IElBkoNh9CdeJVbsR0hPIfmqoZS5k04J472m6gjHV1D4LiRJwK0dovCVXGt/kTksj+AptL+wsbGpfZwUw33Xrl12ubffGYoiYphhK3e6WYO+vL/5Xnp3uIGBDXszd/uTzO42nsmb7j9hWGXEiFIYKSFTTSUUyEd0NWDyx//BFyyLvyZYxvQtH7Gw52Q8oQK+WT2Xhjk3Un/wg0R1FRMHLi3MfX1NNJcbUQSHoCPEBAxEpHO7cOSdW9BL49eol/o4+koumX9bSplePb9PlkRMfznpskFYDhMlhoADI/r7PUWXBJkUjxdf4TYK/V+yYkue1Wb1Mzrwp+yHKI1Eyel8D7N3PpKwmb9l0wPM7zEloe0e+eKFapv5+7rcTDAq41VOQzLcFERKeMP3PHf85QokQUE3NVyOINesfjehbSdt+C/z27Tl8OvXoiR7aXHefbidUcpCJ+u80OaPhged6LtriZ3djD0rb0Mr85HatB8tBs3l4MZFpLU9H9GdgerKRJJU/tz1VlI9p+EP+BiYPY2jwUM8vvkOSxTzuuzZ7Nz9EmHNT91kJzPPVTBMAVk0iGmHUB0eXltzL/6Aj2YN+tOryzRCYZ3xHXqzfPcWthfnM3nD/8hrfSlH968kXH6I5w5vILfdCLLUNMtYr8lIvrblxRwOFfLAzqctT/jqo1u4a+tj3NnxWp7f919ubntFtbnVJTtrnG8LIiWkOpJwiDKZahq57UZYpeaW7X0D3dTRdZ2rWw5jt3+/dXiwoOet+KMBCsIlvH1wDec17MPoj2aSqaYxpcNITvd4UQWFoB6iMFIC8KONIJtfD003+Tq4n7sHNkU3BCTRZGvRPpJcWcfEGwGz2I/+xKt4xv6N0lOgxruum9QhiyU9p1dEhkjx/voD13q3GLSMdojvLwq/Y39hY2NjczKwd9A21ZAkAVMsprjsG1I8XvwBH04llS8PraJDm1FM/DS++RzVfCiP9rw9wfteideVhUOQmN/jFlyiwoH89TRtOpxpXc7BHw2zfNcmtpfk4wuWYSBx4MM5mEC+qVBWrvDwapMjgQg9Gkpc3klh1ruRKl53GVEVcNVJtRbVSvRSH4IRBRIX1sq8WO3dtZSe04zXttxmqUFf1DuPZDUd0xSI4sFBAMzo76LWu24kcVHveby2dgIbPn/Sql/tVrPoeuYD3Pk/B0cCMnU9BmP6jKQgUsL2kj1AfLOvigoPdZ+KS3ZTqvlZ9uULPLfvHR7peRsARRE/erQui1ZXKhbrTDprMoLs56aPX7W8jvf1GEim6rYMd4gb76aSBIBW5mPP27fQ+qKFSFJarb6nNrUX0TDQeza3jHZPvfbUP/NyJFc66b2u5bW1uVXG9Vwyk5tgCvFSbS53PRauG5MgivnYhslM7ruMolA6U97WrCoJN/VW8TjqIWg+PM4s3M4smrUaw3Vr3rD6/B2dB/DozvVggiujFa0vfB5RDzOm2YXcvGU+meqxWu7HjOTbUASJsBGlPBYkEAsxqd2VzNnxJHdtfYzcdiOYuGke9V2ZjGx+Ef5ooNrcGoqFT6gqn64kIyFwY5vhCTXkp3caTWGklPquTBRT4aEetxCKRchQU5mzfZlVPm5utwnW4YIvVMC4DbPxuuLGT2os9ScbQTa/HqqocoanKbe/c2yNnDKgKaqoWUZ7JWaxH8kw4AdESvwRwux13UQKKda3/TGHTIIR/cH7CxsbG5uTxamtXmJTI6IjSCBcwEc7FnNu9jRSPF7CWinNGvTHoaZbG8ZyPcj9O5/CMI1qtYandxrNkXAxoZhGSPOTedpQxqz6mDGrNvDgp3u4vl0f2qfVw+tORqhYTpOzr+eIJvPwaqx8vbNbOJi1InKcgnmMKBKGpCClJtZSllK9mKLj2O+SgEcJ4RJL0AMFaP3bWkY7gD/gi2/2C3ew+9WRyJFvOLB6Ftv/dSG7Xx1Z68XWNM0gU/Ly167zGdzzbjKSGzP87Mf5S88FVtgvVCoNK4w84wrrb/vV60apJjH3k0OMWfkZD32az02tr2dk84u4c8sjOASJDEcD5q9OVCx+8EORsoiU4F2/Zf07jGrdLeHavO5kCB8rIqGV+YhFSnHL5Qn3tLKNPA4/HiVUq++3zW+LIYqYyU7LaG/Yayz7PvgnpQU7LKMd4uN67Y5FCKKMaZpc0u8RDMwaRTE1I5l7V2gJffyhtRGKwm5KQjrZba6kY5vR3Lnlo4Q+P3PLCsa07cHY9n25YfVm/rb6c8Z/epiokcTynBnc02k0TZyZLO15O68OmMcVZwzCJSocCh3lxvWz+MeaqczatpSwEeGG1sOtXHivK4sDgXwihgYmzOx8Q8Lc2sBdh7ndJ1RTlX/zwCpkQQZBsIx2OKYWrxlR8sNFXPjBOG5afx+BWAhVcHBNy4ut90pXU04o6FVpBCkhF1JIsY32WkJMV6qtkbNWRIjpCkJ6SsJrhfQUDPH7t322+CuYouN79xc2NjY2Jxvb436KcvxpekiSLE+zhkkwUkQgXMDnX7/N5QOWYKLTs/Mkvgwctrw9sijz16bnETMFVNHDQz1uxzR1BEEiEA2ToniQBRPTkJiydgu+YAgAXzDEPZu2MbFLNhmqygsH3+OcfhMQxGRcppMjAZOWWSIXd3DQKFVkVLbCy9ui7C6In/YfCZjETAHJVMkalkfB8TlohhswkSQBJXaI3W/EFaeVZC9Nhi5IKJ0G8U2+6EyNe4XfmsTpfXMp3bcKrczH3rdyaTl0KYFaHBpnIuJR0om+uILopb2ImmGCEZEjAY/1msr72Ti5OQuzZ/Hc/pcZ1+Yqxq3enNAuMzfuZEq3xhRGSoiZBkXhAEcCSQmfdyRg4pISNSV9wTIaelLwupMtj+SsTr0pWzXDeo2S7EVWU0DXcIlFmJKTKB5k/Qha8SFEhwsjGkJNaUDEzoW3qYEAEp6kFJRkL96u/2Df+3eR3LA7alaLhHHtzexA7/ZjOOg/gCh7MGIBvCmNyXR7SVaz+FPLa3Er6URjAXRT4kggUdHySMDEKQvIQgqqEMIQkhKiSdqn1eMfLXI4zVmHb8rLyFBVfMEQvmCI2zbuZFG/Hhxa9hfr9RltLsTT9Qqipl6jUb2g5214XVmEYmErx31ml7GURMpJkl0Jddx1w0BC4tFet1MYKaU44ue5fe9wTcth5O1YzlUthtRofKuSQkTXrN/v2voYi3OmsXj3y1ZYfYrD87MFvWxOLrohkOYSGJWtkKQIlGsmL2+LxsPmrxqK/sSr8bKJf8lBqJOOTnz9/y7veVKl+OspGmYPEDQxZ6VaAAAgAElEQVTcZA7Lq57jXrG/sLGxsfktsA33U5DK03RLtKZ9c+TB7dj9dtzAbTLkQbbvf5MLcu4jGgsT0UpR1VQMRN7/dj3zs2/hUOgoXmcWpVGNG9Y9jS9USr96LRnZ6iymbHyOTDWJG9sOoq4rDUkUrI1tJb5giMZJ6RhmjGGnn4eOjlNyEioN0KNhCoPbKjy89ljo3w29VZ76RGN3QVxB12HEiP3zMYT2zak3fAmGYGAIcoLqq1MKWkY7xD2+WukBK/y/khSPFyNcar1Gdh7zUmhlvnjYfC0NjVMVCVGPYho6sbObEQrmE5VEXGqWpTTcMkvk712q3s863DrgJlRRS2gTgAxV5XR3Ax7pcQ+mqWMKgRoVi9NVhYV9h+DXIizfvYXCSJD8UDnjO/QmXXVxmisF04yhDcwjQxAQyo+QJJoYRpQD6x6mdN8qlGQvLS+cTyxcwtcrZ1mHK2f8eTqu1BTKdeXk3kybWk9MNwgpybQYlIcRC5HcsDv1O1xKoHi/Na69mR04P2cW3wTLuH3bWnyhUryuVOZkN+Dm3ov4NhRg6pa3rMcf7dmuxj4ejpnIgh9RCKEZGl53Mpmqm9wz++A0M5m1QuNIIEJdj8oNvbvx8M5N7CguwRcMETOFBME8R/MB3Lz5QR7tdXuNRjWYzO42nkA0xMNfPEdhpIS9/gPk7VjO9E6jWbz7lYRybrntRrC1aDeXN7mILAUmtWvL81+/xqr8zVzQqF+Nxne6ksKRUFHC5+qmzqr8zVaofPu05tVy8e1c9tqNIhmM6KLwUJX18qbeKopkUOZOwnPT35HLAkQrDPHvE6mTJRFJj6D/jDD7PwK6bhJxNaTuFUvAiIEoEyQZXft9pQvY2Nj8sTh14p5sLDzHnabTszl73j5m4B79eDG921yN6khm8+6nEUSZYLgI04xy4en9iZhRZm1byoHAUW7Z8CK+UNzoHdy4E1M2vkimmsRNbS/in+sPculbmxmzYhtjOrSnXXqadQ1etwvdNLhx3Ztc8t6z3LzubQ4G/dRxO7iyu8MyMiHu/Xp4bYSLOzgqctwlPEYRNPZibt+LvuA1MJMoi7oSvbRmtFqZqKMfL+ainLlW3fMUj5fzu02jYOOTQNwrHAsf27AoyV4Qam9onEePYpT40VWdPStvxwgWETM0Pto6nVsHKNT1CFzcofr9vHeFBqYDr/vYgUS79DTGdGjPmJXbufztTxm3ajdpShoT+sUNGYj/f8sAB/N3rmT06te5f9taxrbryT3dz2Hhzg1MXv8OD25bR6EW5Jo1bzDs/Re4ft1bfCuncNSRyjcfLaBOmwuAioMU/yG+evfOhMOVr96bjmja9aFtakbTDCJyAxxJ9Tmtywj2vD2Zox8vZkjObJo16EefM8cSNEVurzDOAXyhUiZteIEIDstor3z8gZ1vMKVirACW4ZPhDFInyUO6nEEDNY0Heg3mpva9KItQYbRXSUNZa3Jlq7ZAfG4zMGk56OH4/AE4UhqQ224EAgIPZk+mfVpz6/t4XVkoosLWwl2M/ngmhZESHsiejFt2MqPzGMK6xg2thwNxwzq33QhapzThvNMuZMyKHVz61ieMWbGDs+r+hfZpzVm29w1mdxufEEp/X7ebWbbndcQqYdJeVxZSRcmsSo6p3U/jjQEPsqTndOoYWXb0Sy3GRLCMdjiW6mEixA1z3bCMdqjiPT9BPXMPOubR4p8cZl+bkSQB3aURcYbQXdp3pmVJkoAaOsiRp6/Gt3AIR56+GjV00E7lsrGx+U2xPe6nIKJhEKtymm56lGoGrq6HiUaitG96AWXBw+gCbD30LjnNr+Dadf+sCJV3WBtggFSHC1+olDs6Xsxd67/icDBufB0ORpi5YQ/3n9WZokiEcCxGoyQPhSGNuzpfSKkWZNmedczY/D73dD8Ht5zo/YL4ZqRxmsC95wo4yvcQ2PkeniuGYQaCENAQBROOD+ETHNXKREWDhaTJmfwt5zF0I4qoOvh29TwC+dsrlM/ncHDjYiButDcflEdYr72hcYJhENuwDXNgR7QyHwUbn8Q7cAbBcAEeZ4D/61VKw6TTaryfpilwb6+uLN25h0FNGnFGSirjVm1PaLcJq3fw6IB2jOxzmFQ5jQxnMnnb3iNFcfLi2VchCTKSoAMi49r+mVItSKoTbln/TkI+8F2ffMDkjmfRsN2lyI5jByGiw1Wt72llPkzT9mrYnBgBAdH0YIjxwzmtzIdzy0v8qecknltxDef1ezxhboK4kW6agvV4+7QGjGjRn1SHG48zyN0DVXRDRhRMJCGCImiIgRCCmkY5GThRkBxRwqJe43hKdah43S5u69aBB7at4dYze9PgkqeImgaGAG/ufY1V+ZsSSqsVRkqY0WkMc7Yv49pWF/PvPz2EJEgUa37+uXVRQh32Cxv247yGfeKq82eOY9aGfQlj9Z/rv2ZK9pWMWX8ngWjICq/3a+XM3raMwkgJfzqtB3BMFV7FwdxuE5i46VjZt+taXoIadlrGuu1pr91EDWrsj1EjvsE7fr2H7/aei4ZB7H/rkC8/j9jzb1teesdVQylFAn6fc7MkCRwVC8j9OLE8XB1qPpiyVeVtbGxqI7bhfgpiiCJCeop1Ai8ENMvA9dRrT4NzpvHC6hsZ0DkXt5qBYeqosoucJkMQTMhtdxUpjmROc2fx4tljECrk5UJRjX71WlHPlc7h4NcJn3k4GEFAAAQ8soKmOVnwoVgR2pfKjX0G8u+DG1DMDA75zRpDV4Oh/WjRr3E5M0jqcTG+T1/myJZ/xQ3uQXlIcmJ91bDupvmgPPa+dSzHvcXZ92As+y/yfh8yIPTvTpN+kzBzbkbQwdzyDU1ajMLsk4vxO1CVN0UR+cxWxATR8u5JpkCvdteAoDN3xytMbDeMup6savdTEAxUKcJVbVtw20ebubN7F8sQqORwMEJ+uISFe5ZxQ+uRRCMaKYqT4Y37MPN/UdJcsSphmjJ1PalMGaCQqVRXmHfJMriziJUdsB43oqFqhytKshdBtKcmm5qxUn3+uxbhshyr/xR+/gZZPa5hQPY9SJLKi2ePJT9UysIvVrC9+BBeVyqmGcPrSiVTTWJMm8Hcs2kHvmAIr9vF9O6taOSWeemDqxmSMxshCkf3foDRZkyF+FeIuh6Bu85xUtcTrjaeMl0y4zq14NEda0CAo9EIkysOsLzuZO7oMozCSAnbS/Yy/dOFPNLzNr4sO8hDnz/D9pK97PbvJ7fdCByizCv7PyC37XWkOlIpjZayZPer3NDmcm5afx++UAF1nXU5fJzQ3uFghHrOugA8u+9trml5MZOqGOQzOo3BMA0e7z2des5MwrEII9bdkVD2TUFB0Wzhud8TskCN66VccY59/HoPce+5KAqkYlZTizdEEfwBYm9/iHzR2QhuF2ZEI5bsIfY7DhPXlIhltEM8VSR3Ux5Lek5HClVPyxKMKErj7iT3/D8QJTB0yj7+l60qb2Nj85simOYpt0A3AfYVFpZjGInfvU6dZI4eLavxj2oDv9T1Vc1xNyty3GOD23Fw02MkdxmOKSs8+/5I2jcdQq92V1MWPILuUBAEmYDp4fFdq7myZR8cosySL1YyuHEnMhQPmWoSkiDzVVkZczcdSjAC67tVJnVtTu7qHdzfpyOPr5OrbTTu/IvEP/+nk+YSjsvJFpjYN4bqOMCijZOtGsyju8+m7L3Zlre85dClBLTEBVWSBJxSEMwosiBjvLMZs0NDDI+CGAPTJbD73UTDXlVPo8zh+t7SN3XqJJ+smLkmnKDPqopEUjRCVI1h6mFMU0ePhtHdqRQZEiXREM/s+Yi/NRnMI2sk635OGaCAXIZbVnhp79d0yMqgeWoqN67cXq3d5vdvi2ZoPLpjPYMbt+IMj5d//s/kSMDk1gEqj2/QqrXlqN5l3PTxy9ZjXncykzueRbPkNEKfLOPop8vj9/uCB0CPsuetScfaYNAcJHddymrYTP3S1NYx/2tcV23or1Wu5Sd/v1TJxHz1PaQL+xNz6ejBAg5sXIKn0/8hpzWhWAswZeOLVg779C4X8czejxjT5mxcskTUFDAMifFrNpHhVPm/Vs1JURTCsRgtUj0Y+Rso2PgkjXrfRMjThjveS/Ro9mgoxktUrjg2P03u7+DebW+wvSQfgPt7DWb21g8TDq+87mRuPrMDEzfdB8CinKlcu+6uhO+2rM9dZCpplEYUblu3i8PBCPXdKrdlN6JhkoPz378RgFf7L2Tcql3Vxuoj/dtimmUoDhdyxEFEjhAxI3wTOMzi3a9QGCkhr9t4MhwZXPXRndXy4E9kxPzanKg/nKQ+24Tv6K+1dY6oRHS7+dZPtRz301LACAatNYJgGBQHpq4jqArRT3bC+m1Ix+W7V9sfpKdUe80vwcm+rxFniCErx1V7/I0BD6KEqhviya4YevBwDWtTfcpCNR8s14b+etz11Oq++2tif/fv/+4ncU9g8wtiu7VOQWK6QSA5CenmoehmDEmQEcQkTus3iWdXXM3A7GlcdvYikpxZBMJFuD1e5q4ZxZicx3l8xwoub9YDvxbm1a83cXmzHvxzyxtkqklc3ao/zZPrkxVTeapnF74OBHlgz1cUhDXuyG7Jo599DYBLkmsM7XMIDo4EYqS5BEzTZOqfnYgCOGWD0vKdLNo4LaEG88KNkxmbnUvgzUknFJHTdbNCEd5FqgKRnIZ8suY2QuU+XEleOp41HYc70wq33fPBbbQauvR341mIaDpuj0JELycSKUSMaWgOB6aZxriPnyHTmcTo1gPwJhnMOFehTNNIVRQC/iAO00GRoXF+k9N5dPvnXNbCwR3ZLZm5YTeZToWr255BQ48b0zBYuG0nl7XowjsHdtKyxekcCcQNhiSl5rSGhp6MBIX5qV3OxinJ5H22lqvbXUabVucQLTtMLFDI4c+e5/S+ucjOFGJhPwc3LKZxv8mALU53qlO1+oUpipiSiByNYfTriuHQ0IMl4EhC7J3L2A0vML7Dudy/7b8JOezTP3mNJX1HUhQp4+a1z+ILlfJk3zF0rZPFla3aUhqJUhQJ8+/9+xnVtiX15BRkdyaGYWKIKukujXGdFdIdAsVRk+VfRElSTEb1LqOhJwNRMNEJUqgFgbiB3tCTkmC0QzzqJEvNiL+mQkG+Kl5XFmlKMvvKipi7qTQhDP6eDQdY0L+tJTqXHz7IHdmNmblhv2Xc35HdGFXUSIm4EQWZCAGcus7Xq+fSqN0QZrS4FCFcQmjtAqL9JtUokmcQJUXRq0UaVT0A5XcQiXQqoekCK77UuPPPKpIgoJsmr22PcumZCqorRNTQ8JeU4vzPJwj+APLl5xF9Zy3y4L7QojFCNEoKMfySTEw3iOkVonZj/4ZUUXWm7Fes4S5JIi4UBEPAFE1CaOi/wmfJFXoOP7highGxjHbAqjrTetgS7K2zjY3Nb4U9+5yCSJJAWD/I6x9OwB/wkeLxclHvucimiMeZhSBIvL1+Kv6Aj26trqRXk5FM7/osZkzk1g6DyS/w08GVRbtmXu7+8t8VYafn8OKXO5jaqDGhpSK+4giedJkHRrbHnxblzo93ATArpw2ZLgd1PdFqXlpJNOnRUKymKH/rAAVVSamxBrPgTAWOich91wYzKoQsox0gVO5j64fT6dR3Ov6YhulMQwiXYP6OziCTkxwUhb62algPO+sh3ls/g7NzHsQXKsVXESp8Z+ch3PzRE0zrdDEZhXWQlstoxSaedBXPCJGRrVvQwHQTCuss79mJElHkrg/iqtk9G4pM79wBUY/R4YxsApJhhWaWazWnNRRHyrm9c39O96RhYBI1dPJD5RRGQkze+B4PtWpB/lsTaXPx45TuW0XpvlWJX6zvhLiQkG0cnLJUq36RnoL810EYmIipyehGEEFNogSZieufwxcqtXQ2quILlRLWo0yuIqSZrDi5vGl7ntoY5aLG0EZV6dKqHU9+8zUXN29Fcr/bCAsOMHQmt1Uo/1eEULFJUrrA5P9TEUWTxikuIMShgJ+thT7u7zUYRZQQBAEBk/t7DebxLzYhmHBTk57Uk5NIw8mIMy5gYMMcFFG2DIlKAbn7dzzF35tezuHgkYTvcDgYwTAF7ut2M4/vfg3DVKnn8nD/Wa0IxUIUaaVkqjHcz60lVhZAH9qRPR/cxhl/mUEskGigxwIFyKZeoxETLdjN7pWzaT4oD60i9UiSBFSO2iUbaymKZDC0rUymFsGBSRSBoW0VFMlg7pqrrAi16y+5hzovfUbs+beRLx8I5SFiz75Vo9J8TDcol0ScjjCYUVTBgckvf1gjSSKuoEr+Uo1YsYmcLlBvpErIHfnFjXdFU8nrlkvupsQc9xNWTDBiONyZCYfKvs3LwIz9otdlY2Nj82OwDfdTENER5PWVE6ySaP6Aj9fWTmT4gMX07XijZbT3bj+WbmlD0R/4EKMoiJDhJm1UbzyvuTG2FKNmScy8cShFmRFKoxGmtfkzpS/FyLpIQXIL6EGT0neipF3sIK9zOxymwL5AkOVf7OOGPo15eI2eELqt7XmJq7oNZer/qiug3zPwdDLd3gTjPdPtxQyXVoSwzUUXPSiRgwl126tuQE0zahntlTjcmRzx1GfSxpes0Nq52U3JksRf5dT/lyamF1tGO4BDdtG+6VA8rixe/tMNOEUZ3RSRkXih2w2Ihkg0aBBOiRIrNuP/3jNp/hcP0fklJBXoCFkSKaPTSHdBukvg+iZhxAfXYVb0AXVkNpMHJDF7Bby8LcpNvdWEMM0b+oIkRVEMmdJoODHPt/MAHt25HpzpKMleHO6sGnPcMQycUrAiWsLmVOT46hdmsZ/Ys2/FjQ5BABwcNGKEDM0yyEujIbyuVLpnNeWKFjlICJiYOAQpwaCXTJV1X8XIbRHBeHyt1bevvjqHYlNEFxzopoRermG+LyXMaf73NdIvcRCSBfb4C1jt28fARi0Z/9F/Evr5a/t2MPnMvniL3SgLgpgFQcysCGNvvJgyJUzY1FjaewZhXUI3BBwiFEZKKY2WUt+tVguD31O2jw/z13J181Hcvm43h4M+6rtVZvVuTZsUJxQWU3RORxweF4Xr8tDKfBiGidR/ImM/OyZ0N6f/RNRAKXPOvJZJVR6f3eFqylbNQyvzsfet3Hjqke7C5YgQLS20SzbWUhzAaeXlRB9fS6woiJjh5rRRvQmoSQkRao9uv41J596La9E7CKnJRBe9eMI67ZIkoMQOnXAt/aVwoZC/VENKEawxZvhN3MkqZXro+9/gR6DrJnWIp4Po6EhIcaP9BN9HkBUa5dzIV+9NT+j3gmT3eRsbm9+O33dtD5ufhGlGE+qYA3icWRimQbKrHv6Aj/ZNL6JLw8vRF3+EWRQPATWLgkQfX4vcN37eYxboGPNLSQuqnBFNRdUFMv7ioOA1jYJ/awgyZF2oIpsCgVdjfHt3BM+TMqPqnM5/vtnPqJwYCy5SmTlQIVUtI71pT4iFawy9Ng2Z67vPJdMdF2CrzHFPcdenSf8pyFEnilFuCdEB1gbUKQUr3smBK8mb8N6ndb3BMtoh7p2buOF5NOX3caqum3pCW7qddcloOIjr1ixj2uZXORAI8MqXe0gqUjn8sMY3d4c4+pJG1lAH3tEqDcY6qTPIQXR+CWZBvDyQWaCjLCzhqlYyV7UycS5fl9AH5KUbUCN+RvUuI/cshfopBjMHKiwc5mTmQAdpbo0Mp4vT3CmW0Q7xUOGZW1YwvdufUJPr0/qSZeDwcMafp1vCepWbo0h5fkXqg82pimgYCYJaEDcwBEnCLAvgj8SYuPFFirQAXlc88mb5nrXM6/FXLmnanZs/eppLPljATR89TWk0RL96LWmf3oDZ2ZchI/LXJqZltEO8b5tL1pEWBd0QORoK45Yl0s5SKHhN49CCMP4NUbIuVJFiIsmaSoaSxN9bdMUhSmSqbjqk1eOulmfTKJLM7c374QxKKI8GE8ZWdH4pznI4HCqkKCQxbuUu/vbOVm5c+QXjW99EXWcq9+S0pr5bBbBy3Jd9+Txn1etdYbQfC6OfsvYLgobEiF3zuGDLHVy1+V6MbiNw12tPmYhlnEM8HH7SZ4vw60H0lXN5otedvDngfhY0vxRj1TyC+dsBqqQegWBqlvFS+dxX701HMLVfs/ltfiCeSJTocf04+vhaPJHE+bMw6ENPUuJl3gShxrElGvHDaqcU/J619JdBMIS40T7UgVDVjRQGRfnl/Uq6biKFFJSQCyn0PSKMplljv+fU04WysbGpRdge91MQQXCQ4vEmGHy92l1DeegobmcGXVuNoEmzvyFqJrGixIXaLAoiJFX5vUBHLRWI3F2IkCUhX52Gq4VIclcHR56LWOFvdYer6OUakf0GoX8ZjB3blE9DpUiyA1EQKA8EiAoCyYqHh/8CRRGTp3ZG2V0QD8uWiFDf0YDJvRYRE3Sixd9Q9N5sioKFtPjTvZgvrUa48uwaS4uJaHgcUQTRSddz5rH53QlWjrua2hhf6K2Ev/GFStFNA+l3cK4lCZLVlvUzO2DIaUSK/NzfYQTJqpO5uzYyrWUO+QvibQEgpQiYmsDR5+OPNR6nWIZFJWaBTl1VIGqa1obQeq4oiFfxoLhkBDT2+EO4JImQrpOmiszd+j6FWpBZ2eeSqVZXly8IB5ix+QPmZJ9LfdmN7M6kSf8pVhiuIDvxbVpKo75Tfv0baFNrMU+ghm0GQ8Q+WE9s5GB8oVLW+HYzP+fvlESCFGkBVMnBhPXPJhzGTd7wPI/1voqYCbphkqwLUK7X2LfLQhEe3beXKe064TFkvn0uTKzYRG0sknaWwrcLw9a81mxkOkccAQAmduhLg5Jj3nUhS6LhxHS0gsRQdbNAR9SieNMacf2KHQlG+Iz1+5jUtTlLd3zF9B6tqOtSMTAxMbjzzLF4pFSmZmv4tSj/+uIgAP/XuiGGKZLb9jqWffk820v2MnnbEhZkj0KXlBpz2aXUhjT783RE3cAUHHyxcnb1qBehomyjqdc4r2LWXAfc5uQi6EaN/Vg4LmIs0+1FDuvIl5+HUR6IG/ApHuSze1jK8bpDRtJBRDtBm/+yiuqmaJJ5oSO+Hr1UZb/wVxWX04HGyTtAlyQRRVDAFEAwMQnVeA8Mw+73NjY2vx224X4KYkTdDOk9j9fXHstxT0tqBMCX366jTat/YJgm/8/eeYdJVZ7v//OeMn17YZdFOiwICEhRQYXYsAuSxEoiWANYUYklsQKWYGzYKLbYvolGsceGSFGwgIC4FAUEdpftszvttPf3x9mdZWRR8wsq6NzXxcW1Z87MnDnnbff7PM99WyqI3EDKokDkBpCOgueSoEvg4wJpuQsEWW1jzakn74pcts5pJYpWnWTHswnyR3uoeNQ93hAzuXvFV9w2vDchXePpr6OMb9+ZT55LEGuQ+LMEl57k5cn1Br/b36Dqg1sIDruETS9NRA/kUTL0fLodcwsKHuSbn0I4grBoM+06XreJdS9fiiejmNKT72foifMQ0qCpfhPRpu0U+7NS0miL/VmoYu8n7QCamsPo4X/jxcVXcvABV6CH/dS/pFLeICnsIbjxN4eiSYFV1xodyzlCZ8czrc9HeAQiX00h7yJfJcsvsKWCbKMNrG2McsOHm5gxrDcvbijng/JaigJepg/rzS1DjmV9Qw3zvvyEc3sN5vKlrybfWxzIIGwkKI82ctWyN5k7/CRUTzsyMnPBlkg/GLKGTodeQYIg+6pncBr/GzRVQZhxtDOOT6nD1c46Eevl9+CwA9EEjGjXk2P368fFS/6RLHV5YNgfKI810DenhD/0GE6W7seWkrBpM/XDhZRHI8w/ZAwZTQIlNwCZPvSjekHAA4ZFQoFJHfvx+VMWg05Sk/0k54jWzUhwx7WqeQa5k/34/Br11Y27RNeptNvsW6o/i/y44LkhAzGQ3Ld5E/M3VVIRTZDp0eiS6UdXFCYu+DwpPjdjWG/+/vlXyb526yG9MGzJzct2Vp+fyP1lD7C6fgME8hDRmjZr2a26Tax6cZJbZnTCTHqcfB/r51+ckhYdtwOAxMHT5rjqpMUj9w6oCqJfMfpBXdw2HDUwP/oaVCVZXpYXKGbi0LsIKcVgS4TjoE4Yg4glUvqXesFv8Yga4uGqtm06WzZz9hBiGGRk+9l2fzx1vfBMgpLJvj36Xd8FVVVQDS+fPG8k1x8DxuZQOPAP7PjsieR5noxilH1kbZBGGmn8MpEegX6FsG1Jpp7P6P7X8McRszltxINoigdV9ZLR7lCe2/gRprSpVhLo5w5H5AYAl7BpFx2G0Eyslz7AuO9NzOcXIrQYSrfW9HmhkJyEW2DVSdSAq/qm5QhqTbM5zXMtjpRMLu3KupcsYg3u+2INko0vJzh/oEZQqSX81XtI6aAH8ohUrmbdy5fy5YsTcTBRRwxGu+B3yHdW0mPktF3Srrctmw24u+Vl8yejSSAc5eM3L2Xrsr8zo/+xyVTbYn8WfxvyO3z2vrGn1dhkkuUr5IyRj9DO15uVzQuPrGKFHgM97HggAZYbxWiBGhApz8cxJZ4JWYh8V11X5Kt4JmVjPRVGPhRBP+uQlDYgzhvGfRtdu79rlqzlhC7tADdieO2StWyoj3HPZxVMKB1Oj8w8zu7WHyBZ+/vEus8AN/ouJfjqYpj3LMK4+S2sexaj1qlsWfR31MRWVHUfUgpMY48hiI39yD+xXn0fbfQReCadgTb2aMjLQp0wBquDRs3707isz1E8t/EjLu83ioeH/5HL+43CRjKiXU8m9j6Cv696kwsXP45hyyRpB9ieaKJhmYI6/lD0k/phvrAC494FmP/3KUWmoPpDdwyKR1r7zrf7DbjjWlPMBASdfNm7ZK5Y85vQJmen9C314mxEDMwZtVhTq1HvrOeqws6c3LkdRQEv+T4PE/bvxHVL16ZE47/d1xoMK0naW45NX/YN53Q7jWJ/PoFgIQW5pdw1+AqK/fmAS9rvPOACwo8is+0AACAASURBVEsfBJqVsl+dgqr56XXqHPqNe5meY+al1DLH7QDdj5+ZMq62Evs0fm44moZ+XJ/WNvzCCvTj+uBoGlce/CDTDnmOqzrNoMgpRDEd2FaJaGhC0fUkaYfmOvf6Sja8NoVty2bT5ci/pjzzHkdMR93D/uW27SCdttcL8ifcs/UIDyua505w+/6K503y+55HVtcR7jnNWjqoe3bzIo000kjjv8G+wU52g9LS0neBdkBLMdeFZWVlH/2Ml7TPQNpxNr3kepr2PecVGs0GLDWTOWWLGF96OBcv+Qe39BhDwfwM9NMOR+QIUBRQwHjyg9R6un8sQTvlMIx7LTe6JF1yvvNkrOW4wk5ajsA/TmHaxq8Bd7FZHTNxbJGcNFsQa5CE4ya+UD5ZXUaQCG+lwyGT2Lp0FpHK1RiN5ZjRGoQ3D03JgnVbUCtq6H30dGTAreXbunw2HQ6ZjJZRiJQOZtMOQCLCcfyhYsI7VsOHM7hr4IWo/jz8eoj6xXfhOXQq5h5epPxYkGaMLW9eR6ej5yTvYY+DdWqedqODte+ZFI33JrMdHEOmPB+rXuKsjeO9PAcUARoY70RwPnMJgfkc6GMPxyoCQxXcv3EbEsFtw3qT6dHJ8+v0yc1gTW1jc8RQbybxX3Ll4BKO6diTkzr3RgjBzZ+8y+o61+u6OJBBlqlgzkmtz+TJNRSfeVqKQFYavy4ojoNVF4a6MOajLyaPe669AFtPsL65/jZn5HVJS8qWiPtdB53BZX1HMXHJE8lMGr/mTZJ2gNeqN3L5sUNw4g72U4tS2p89ZwmdTxvJjvWw/kOTvmd6qXk6kRy/vj2u+b0qUWliKgLPTtF1pZuOdnIIJyTQ/pxLOGGyLR6nRwjsGXWpde/313PJ1Z3ZUWoiJZjS4bIBXXnyy62sqXVLTVr6Vgv8qpoiYNdyTjtfJ2YOvoJMJ0A44ZCvBplz8I3uJqdjU/XGtcladqDZCnMbX711Q5sCZLYtMbQSeo6Zl7aD2wuhWBbGnFQdEnPOEjyXHsHKNydycP/pKM8vQfnTaUhdRRTlu2UoUrqkvVMxjaMOwQwF0DN8aM2b41uXzkoqqntDxahVBjgSSN1MbcuyUTEtHEUh8h02ctKRZKkSIZw2+5VUHX6yTHnZ9vojHg1TcvgUOg67FKSD0IPpEpE00kjjZ8U+G3EvLS0VQC+gf1lZ2YDmf2nS/gMhFB1PRjHBdn2xhOSlRVOImVHO6HowIix5sNfZlAaLICQAD4mZUeJTG5ANVtv1dKHmSO3FOThBKJrgTUaqWixejGKbrEka12/8ktXNi9GigJewYVJlGPizUhcE/ixBo22BtOhw6KVsWzabr9+5meJB5wDuDrgZq0MKibBs1At+hwhHkHPeQDy5AKHotOv3W2xFsOz1SSz8129ZsegW4kY9yoYaDhw+LUnev1k8naxEAzX/uZbwVwv2GWG0gE9DCBUtkIcizOQ99PhEsi431EcDXVIyyUfH6/xoJdBugpdgH4X25+h4cgSe3wQx/tVI/JoqErfXoh/gQ+nmkgRno0XiriYU4eOxLZVsDMe4qF9n7l7xFRMXfM6l76/mon6d6ZObkXye4JKIDoFs5q79GL+qE7dMahKtXtd3HjQKJdbYZnvSvDkpAllp/LrgNNe37wyRk4kTbsRxTPRAHqWjH0IiuOWz+eT5Qtwx9PfceOBoKmNhEKSUvzQYUYoDQQD65uRxdmlfbt78KTKz7fpgX6A5a+VgHeGXFF3kRe8odhnXCiZ4eGbbBqqqEiQciediN7qudNPRf5uB+WQY68pq7KfCZKgaxV4vHqkgslKnXllt40MhbjtMXPA5p73+CXev+CrZr8AdK02nlQTFbDspYNeCooCXTI+fTqtqUEyXYLQIcuXYCt7ar7GiNSnv8WQUY8XD3ylAZtuSiOEnYmYSMfxp0r43YTc17jgOsaZyZFEO+oW/B1VBhpsw5y+Amgbkjlro250tvz2C8zetZsyy9zh/6ULUETcRaNeXSOVqNrx2JV+9dQPCcLDf/xQlEkNTW9tui2WjnPU01vRHcGY9jVpVi/3Uy8hZT5MRbUo5f+f3yYoq5KynsR9/hqJxSkq/KprgJa78hGO/kG2uP+KJSoxIFav+cSpl8y/GjtXs5gPS+D7kZOkUFGS0+S8nK53FkEYaPxT7csS9FJDA66WlpYXA7LKysvt/5mvaJ6CpCh7bS4+jboNAEKNZmTyo+ujYlI99XxhZbSLzG/BMysac3+QKKnXTEEGlzbp3kafjuSZAw2oLT4OGlitpP9lHk2Gh6IJXqio4NlCIJhUu69GVlyorGLlfPiVBH5XRBP/ZXsmfxnbl851qzLqdrBIO2NhmBDwe8kf9HQsFS4HMriMpPuA06jYtIZjfC1M2gceDuOxshBPBkRZIG8uKs3LhjSne7Z++NYVDjpuDb+U3HHziIxhNO7BidZQvcSP5KcJMezn8poFjqnQ69HI2L/or/U+dzsoXLIy4JNBHIedoHScCmCCFBB2EKVCDksKjNYz76jCaLeA8E7Iwww7ORhNjXgP6GZkY99WhdNPQT/FhyTjndiqiqWcJFbFESkRw2vJ1XDWoOx5F4aFVmwCXRGyLRPl9twMBuGPlBzww7HhisWqk2USRUYcVbmizPZmJun3qOaSxZxFBJWP8mKQdXIuHu1QVhK6z37CLcaw4RryOPF+Iib2PSIm6Pzz8HEa2K+XM4mHkqSGijsHdh/yG+Zs3ckqXnghgQXkl69p3oGcb7U/LVOh3uIfqpxLU17l9KW+0BxGStJ/sxXQkpnB4bGsZv83sSuxJSbhOYvexKZiaC0iM2+uax00d/eggxt/qCFbbGPkqnnOzMP/ViLOxWbk9X0Wq8OiaLSmp79OWr+OyAV25e8VXXD+0J35NoU9uBjVxg+KAl9uH92bq4rU71bjvx11fzOaaguPIcRxATf6umB3Am1lC16NuTLW4Ovomvll8L/DjCJC1QFUFHjWKmyCnY6Sj9nsGattzMopCYccRiOowxkPPJPuQOmIQ1jOvQ2aQpj+cxNUfLUhmo5RHI1zz2QruPfgyoi+d56aHj5yGfHkZ2mGDMN9cTHDMUTQ0R913a9k4+gjMR19MsZjbGUFszLkvIDOCKEf8Brw2JZN82BE3A6z2DYOcY3XsgPOT2LIa0mDAWG8yXd6fJdj/pBirNzxJ384nuOc0lrP+tavoPXb2j349v0RoHh/L7hvU5mtDL/6E1sTZNNJI47uwLxP3HOAd4E+4q4wFpaWlZWVlZW/9kDfn5YXaPF5QkLHHLvDHwJ64PhluwrZsyCmkyagl0riNzGAx+U4+1n3hlBROY1Y9+hmZWGEb/Xcqxssr0M8cjPn0x0nvY/XMYVT+G7KPgUBXPZmSreUICsd7qFVNTgoVUXG/ezyYo3HZhK7cvKGM95uFlq4b0pMqPU7xqYICjxepSDYZEZ79YhuX9NDZJgqZunRdcoF6+/AbSFR+SEHPY1j77/Ndwbrhl+DJbI/jxLETTdiJBnw5XXbxbo81leOoEm1gR7a8fztF/U/nm4UzkwvZHifMxJ+ZT2AvE6Fpq8061XUIW4IQNHz9HllDN5F9ShDLn0X+WD9WNTQsMcg+3EPtmwY5v/FQ+VSCwlM07CdTLeB2Juuy2kZkKi5pP03FfGohstkjOOu8YVxXtonquMl1Q3ry0KpNrKltpGPIz70rvmJNbaNLIoZ056HVa6hNJHhgxCHUJKI01q/ji2W3MmL4rTS9Ph01mE/eeddizvkw2Z7EuD6Uf3kfPU+86yd5Dntrn99br+uHYndjbAu+7/fJ7ADqpWcjLbeNmk/OR/zhKKTl2pN1PfomZGMF5/UckSTt4EbaF5Z/yU0dxrJjnolRJ/Hl+Gh3rodTOvXgsg8+5NL+fSgO+Hm1qpL9zxuG1ZxqLHID6GcNQRoWje+JFDX58gdax7XMP6oYeTbDMouIPSmTab6RNQ6J7Qb7XdTq1KAdH8KY15Da1+Y2oI/LxPh7nbtpNjmHf1dV8vueJdQmzJT0+C6ZAS4b0JUHP99ETdzggZEHIHDwN20m6vFxyYEBsvRiGswGXts2n5M6jMIIdaRBUckL+lBEK2mSMoDpz6X3qbOR0kY6Nts/eYxIc+q8J6MYTfdRkL1n256UDo21G1j+Wqujx6Bj7iInvzuiuX//3O39u9rrz31t3wWrwUI/dxjm3J3a8LnDcFSdHgeej3jXLUtrIdX6hb9PlqEYiURKCQm45F3P7cYBo59BNMaRL61Ebi7H2rYDbfQRKKL1fsi6BhJt2MqRnYE471hk0IPQYuTnFCSfs5QOZmMV8rxjwWzP9ses5n6VoPB0L3XvmiQ2OxjbDTpc5kfL/WnmYcexGXwWxKJh4olKVm94kj69TmPHolnJc4zGcqRj7xXt4fvG1xbsDdf6Q/BjXOe+8tt/DPyaf/svHfsscS8rK1sKLG3+M1JaWjoXOB74QcS9pqYJx0nd7S8oyKCqqnE37/j58f9zfaoq3NTHnWoTM1WHWioxInEMK4LPk8XpRz6BiIg2bcFEpoJ2ghfzGbe23WxMoJ86ADK8yICf8mcEiS0OmcNIWrpAszrsowbtL/Syfd63js8zOH1cB94vr01Glh4YeQCm7jBjRVlSOXnakA7ogQBT30/1Lp66+EseHnEQW9+/CT2QR/GwSWxY/RSd+57OqoU3JxeHBx51O4UdR7Bjy/vJ3+QPFeM4Ko40afj6faxoTbKWz4qHUb3ZVFenLmZ29zx+SrTVZvNUBTtDBWm7Ka/eEHevfY0/9jiSYb5O7HgmTv5oT1LVv/KpZvLhF1htPeugu8gX+SrkKoiLApj3L0itQZ+zhIvPGcKFy8tSIoI7Ygkm9+/CxQO6UB6JIoTDpAP6EDZcRfs7DxpFiSbZ75i5qMJL6KTpSEWnCR/+S0aiSAmKxFJjdCiYStwOEPkBz+G/haoKAkoU4ZhoHh8Nhnevi/z9GGPR3tBed76WH/L73FTcOCLcBBlBHEyk49qTWfEwzvbP6ThwXEpaPEBPvT075pkpY07lXIPIORbl0RiLtlcw7eDByCaJZXrRf38geDRXkfvlVRCOkzV2JFaTQrvTPWx/JHX8Cj9ukztZo9DjI9aGsJYtZFJNXgR3M64WaGjX5mPFJDvetuh+ZIiblpdxzeAexCybooCPQunBk1CoNU0E7tiHtPHVfMbWZbMJDT2XmRv+SXmsmr7Z3ZlcOpHpy76hIvoZRQEvdwzvRYlmETddz2pVFXisiqRHd4uAZ7z2K8xoDd2Pn0lTwosd3bNtz++JJW04wd08/eQ/VzDk+HnEDP9u28NP2WZ311739nVBnqJhvLHGnZNbVOXfWINn7CA+ffsqDu4/HVFRgzi6PzLowfIaiL7dkas3oNc3UhwIppD34kAQjyXh7y+y892QdWFEKICUErM2TASVIGIXWzlHQNzTwPpl17Zuhh8/E69ehKMoGIntbHhtCp2H3Ur9s4Xf6T5jGQ51VXtuDlBVBVPXsJGowsYnEtiJVj93VRV4QireUD5DC65k6/t3Jje1oEVZX9lte9gb2uvO2Jva7vfdmx9jvttbfvtPjR/629Pkft/EPkvcS0tLDwW8ZWVl7zQfEqRzbVLgLtK2sW7+lBSbn5gni8WfP8Ihfc7ntY+uJ+DL5/Ah1+BTg21aF5GhIASt5G1TLcacJQB4rjue/JO82FGJmtG2OiyibTXmdt7W+syKaIKKaIKbl5Vx2/D9ufLAzjhSoAiJYTttijAZUiX70D/jadrCig9upPchU5KkHZrT4t+eytDjH6Sxdl0rmT96JoYdQFcjeDKKk7V84E7MvcfM3UNP4MdHTPegySgVK/+PHsfdQcKbydV9z+S6Jds56GCZVPPf+X8AKybbfNYy4h6PXhhivR2h0LDJaqN+Mk9zh46KaIICv2tVFTEt7l/5NWf1chc305Zt2ClDojcFG96j5u07ULOKyT/1b8hAAVHLi207JM3qbCApRrfnybSqCgLGNmpemILdUI6aVUzeqTOJekr2OvKeRmsqLplB1LOOJF73FY7HjyejmPJPHqPr0TfToCi7WDoWapltEuoMRadPbjajOnXgsbXr+EvPgSgNCYyHFu3y3d4iyD/Jgx1te1zTbIVMvwczx9xFWMvUBfrF2dj31Sf71Lf7WqLKYftjrVNWyYk+8nweOoSCRA2LooiH6kcNrDpJdo7OreN68c+87QihEPZ3pmDUPcTL/sWdB1zAVZ8/wjndTmsm7a0bnFcv/pJ7DvCS6/NhaCX41GhyPgA3gvjV2zfS69TZOFL9EUXnzDYzn9wpOy0++T/BcZCryjFWpd5fTm2ucS/Oxjl1AOvfuaaVSJ84Ew3IeHMpd/zuSK7+fBnl0QjFgSB39BtCVnU9dk5mMgUeXI0JggHMJ+dDOELG+DFEMzIIXPA7RGOk1VbuwhNY//rUlDa2/rUp9B46HVSVDUvd1zRvftvuM5mCovFe1JBAUUBF2SPp8qqqUI3Cnxd8Q0XEpCioc9PQDIp9YTxqAUI015Sh48gcPCJCyeBzadfnVBTdj2PG0Pw5oO6zy+Y00kjjF4C9Kxf4v0M2cGdpaamvtLQ0A/gj8O+f+Zr2KvjUaDKyAiTFhxCSww+4mPmLryIcKWdQ7z/y0EdTiHmb0C7OSLEu0s7Npvo9ExnSkpZgLRC5AYxa2DYrTvWLBghBoE9qkwr0URAaKXZk4P7t9bSe2yJq5lrEfYHhSP60YDWnvPopWyJmmyJMGxqbuGjJ51QFuuAJ5KN7M9tcHAqhcNCJsxlx2ksccspj2IpL0uKE6HFcqs1Rj+NmIpQQOcImS5VtCuvsTYjGLaS02bHiSWo3LyFmebhuyXYGF/qRzffdkZL2k7xouSL5HGretdDOTbWp0i/OpqG9w/o/6TxStxVTOmQEvG0+9xrLlfstCnjJ9en87dON3Lp8PWf0KiHP72P68g3fypBYSzynGwB2QznVL1yJ3LGWgFOFzxfD6w3j9cZ+dPu3gBJNkvaWa6l5YQoBZVdBrjR+HmiqQpYqyRE2GhIyg8jN5chYhMYPZqOqXnocdwdmtAbHMkAK/jLw5BRLx6xAoM0xR9EEdx4wlE52iOv2749XVVAz1TbbuHQUKp9KYDe5Ne5F472UTPJRNN7rjnMCHD26i2Bd4RleEhFJZZaJc002Vic1KVoHzePqednUvGulXJvfq3HpgB5Mfm8LTQ0ySdrBJTSxJx3+2KkjE9/bxunvNXLRwmoS3c+kvaPxYO8/0iPUsc0NTqlntIrOSTPFmxvcecFxnB9ZdE7HHypOOeL+ndaw+F8hm2vcd4bIDSAVBX+oGImdJO3QSqTF2OHopx9HV3+QuYcexYtHn8ScoYfTcdHn2K8uRDvtuKRApMjJRB8/Bsdp3nzKDCLCTYRMA+H5lq2cT92ljemBfERBN0ROdzoPu5Vgu35Yieo2+6gaEFS/aLDtvjjb70/gj3pR98A8bOoaf168jYpIs3hqxOSGZY3siDQilTrefms8L714Em+/NR7L2gqKjhAqmxbcxpcvXMCmBbchhApC/Z5vSiONNNL48bDPbh2WlZW9UlpaehDwGa4Cz6zm9Pk0WtDGIk0P5BE1GrCsOOFIOcV5/cjJ7EKGN5+YUDDzDbKvzkU4kKh0qHjDIrFFYlQI2k8YjjlvcWtt+9nDqHhFAG5kt2JegvYTfWzfHsdqFnTKHeWh6gW3dm3Hs601ov6zNWqVVvLXUisN7mKzNmEnF6Hz1mzh+qE9uXVZa417S/10eTTG1A8/Y+agyzATdfhDxSnk3R8qxkEnFnejOgWZGTRG3BQiw3DA14HeY+YipYUQGqrlwb77SaxmQayM8WNoDIR2a2nzcyMjoKM4HjeFr/1wamIWFRGTs3rvR9gyaT/ZixOFinkJCv/gofAMLzueSZDYIqlebFNwZS6KAl/FoxBKMO7tFfTJzeCifp25dfk6Tu5SyNnnD8Oe3Vo/GT/nIO7b+E3yuQngpoN7YDkJPKqCI91n2Cc3g3G9OpDp0QkbJmq2l+DZDyIVFRlrQGQV02TUsOrze+nW/SR8vlz8/nxUNcd9Nj8ChGMmSXsL7IZyhJOO/O0NaFGpth/9d7IPamccj/Xq+xCO4URqCP/nTrKOuZpeox/E1FRsmWBJxXruG3Y29YkotUaEOrOJwjOy2PHMTnobZ3jRvJLt9xmomYLQCRrbn0mgZkDR2cOw/9HaxtVxw7BMHasuQdMai9xRnhTtjqLxXvBK9IYQjiEp+K0HxeNaXta8amCHJYWX+PjSinPrsnKGFAaYODUfPwqoYJtgN2cyajmCwglemjw2Miq4dGA72ik6kbrUBDKrThKOOSnEY+ri7fy9b4zKVy6k3YkPUxTwppD3ooAX4rUYjeUIGUcKH56M4pR5YXcikDvbfH2ftdf3wbADDDxqJp+9PSWZ+TTwKDfz6cfIrPk1wfbq6OcNT9pqitwA+nnDcbw6/Q/7K9KMtb1ZE25ANfzgMQk99lKrCORpx2G9vhDr9YVoY49G5GUjd9RgvrkYbcRg1FOPBkdiPfESZAbRzzghNTIfMVLaWLBdPzoP/jvbHxRYdRZaTk86nzWTyq8foN1ZE6l6yt/aryZ4qZ6fWpZSOc+g3WQPTcT/q/uiqgqGrmFL0ATY2Mm+04KKiInHk4eUJgcOmcIXqx+npnoV7y+4gmNGzWHb8ke+teFxJb3HzgE8/+1j2ieQna2j6z5MM059fTqBNY009kbss8QdoKys7C/AX37u69hrIfRdFmkFB5/Pi4umcOzQGzjnuOcRmhdQOHXAbVyw6AluKj2Vpsd18kd7qH7JSk6giS0SUw3hjB2JFpCoOSrbn5AktrQuuqw6iROV5I/2oAYEaohkbajdZLjHQwI7U3Lr2nIuKSzk2WMPZFskkRQ4A3exWRdvnTTW1Dby4OebeGBkPxwpWR8O89DqNaypqwegPBrDl9WFrUueoP+Rt1NvmKCHwGwiP5iNYe1+cWgYDgZutCJLldgPPJ2ikLs7Vdy9BZ5EAktX6HrMLTQFOxCPORQFdXyKICuqYYYlVf9yI3eaT6HyxUTy+dhRSfmzJu3O9nLV519y38h+FAW8jOvVgWnL15Hn89AvP5u/rNvGmecMoUfIT0XCpFYXTDygK2HD5P/WbePygV1piK7insUTuXXUe1hScFhxLr/vWcK05a2bLbcN60Vx9n4Y8WoS0oPuD7Bq1f306n0GS5fcRCRSTjBYzIiRM1HVDj9K9E8qOmpWcQp5V7OKkYrupumn8bNityrVY4/GfGsJ+SdPp/r1a6l+7A/4eozAO+oKNm+ez9gup6b4ts8fcjk1rxopbb3mVYP8kz1Yde4Y1ULqrTqoeMVL/mkj8RaAUQsVLwtyjnRJdaiPliTt4I5zFY+6m5S1byTIGelh++xdSYViw63LysnzqRzdOYvxH25JpujefXgH8id7UKWgxrDY7DG47t1tydfnDetMog1v6ypjV+IhAoUAxL54htuH/ZWpS8qSfW76oPY0fnA9noxiEvVb8Ob1pvvxM1Nq3LsfP5P4twh0Wxso/8smpm1LUEsYcvw80qryexYioVD7qY+cPx2BEA5SKtR+JMg+TKF8ySyKB53T5maNaIxjPf8u6lknEP7dUa6Pu2mRIwX6WScCIHUNJ2GiFOSiH3kQMhoHr46IRJF1YfTRRyCr6xA7pdXLt1bSY8x01r/r1rh3GHQ1Vf/wpvSfqqf85J5+EtvWzqDzpJuR0oejOCAk0TWp7cuqkwjnv5t/20qLv3dEe4qCegp5LwrqeL2ZhKNr+c/KmRw35AZWfTqLmupVGEYDxYdeQuHg8ViRKnZ8/DiRytVI56cyl//poes+nnziQMb94VPSladppLF3Yp8m7ml8N+J2YJdFmie7I0FfPn5fHhEnzsOLJjNh6L1ctfxlymMN5KkhjDpJ3bvmLlFyxadQ8aLAqoPii3TsRiPl+7QcgVXvLmoBSib5Won/Zid5vP21Pq7vVYw0JPduWM+xnTtRE3c/qyjg5bZDSpn7xdaUz66JG2hYoMA9K1dTHo0lXysO+PEIjd7DrmebpTD1448pj35DccDP7Yd0IR83K+D7oDiOq7a7E2RdGPVbtkp7FRwHaSf4ZtHdFB43C68iuH5oMRmWSsW8BO3ObF0woYAdbn0+0FzCoMDfD98fw7a4fmhPdEVQEXXt3lqI9/vltfTJzeBPB3ROyXy4fmhPNGGzYONzHLLfaGoSknlfrGJS/75ctnB1Srr8n5d8yR0DvXz4zvhmgv63FNIOEImU8/6CKRx9zKPY9p6PgEedAHmnzty1xt1JR/72BuyuD4rCPLSzTgJdofDYuyDTi1X/DbZQ6dTxeBycJGnvm11CwOelLmzv0tbtpmYRqkAqKU5skWybDSUX+9j2UBxoHgPP8CLUtmvc7bAkc6iOHXXHx2+TbEdxifWlA9sxfVl5SqT8soVbuXRgO+75rJJ7R3bkugWpKby3fVHO9eOLk+nyWo4gf4KHh75OjZwWBXW8Hj+9x85FD+SjqgqzD+2NoYBV/xXhD67HilbT5ci/snXpLLqNmobt7UDPMfNSBEu/TaDb2kD5XzcxbVsSs/20Zrak+9uegHSgYYFNw4KWIy7xzR4ORYPPoe6rhbtYAPYYOQ350krIDPJ1doCrln3SWuN+wFA6PvUKIhxBO+tERMCLOfv5ZEReHz8GJ9ctSxEBP+YrC9wo/XOvu+eEI/i87ek9dh6OY6FaBVTVpa4VrDpJIK8PHQ67mibbwXaiYENI9bXZl6Qi/6uNVUPXkqQd3D5138oaZgwv4ZrFrRtk1wzN497VH3Bul/aEI+W8vvwmjuk/ha83vIzj2Lz93qTkhvKhh96A9tmzCCW9bN4dcjN9qN7/vvzFsRK7FUqzjDh1DelNhDTSaEF6BPoFw7YlhlZC6djHEdIAaWMqCof0OR9Hr+sprQAAIABJREFUKDy87EpqouX49JzkojeKgS/HR2KzQ81rrVFyK0PS4DMJjtOJPGlS+7obqa38x07po+d4qf1P6wS9uwWtrJJUzE6g5QjOG1fKnE1lzBqxP/HIDoTZSJ6o5bw+HVjfEEkSxGlDOrDunYvx+PO4/ZDrmLr0U8qjMYoDfu446ECybYda1cfUpUuSpL48GmPq0uU8eNghqD9g0ncUJSVyAG5tn6Moe280VlEQioYZrSFgVpHrb88/vqihb3c3/XDnZ2A2OMlU+Z3Th03VRlMEFdEYAc1DQNMpCnjJ9OgpabctmQ/3juhLdcwkZtvkeVWUz57lhO5nIQJduXTRx5RHY/yhV2mb9bZCywdaCPqVHHX0g0nS3oJIpBycOKq65yNyti2JekrIO3PeXq0q/2vF7vqgpSg02ALNVsjwZCEjDdQvnk3jydO4cvm/uLzfqKRA3R96jGTG2pVcPq4fsSdJScOtfcMdn3Y3NqkhkTxuhyUiU6LqSpvn2k0SNSSonm/sssmZ+UeNqMemKKiT6VHaTNFtOV4bt3Z5feG2Jir6mBRN9qAZMRyvnx2KyR/3z2ddfSJJPGYMLyFofoPuyUWttrCfeYpQXRgxeTQxpZHs4RdjxcNsXToLM1pDvG4TnkAEzd+BiElz9HzXtr9PbmL+SiEU2myfKPD5RzPpf/iN6Hoe+58yG+lYCKGi1BrYQPiEw7hq2QcpPu5Xf76M2aMOIeORF7CeegVt7NEpGzjmo/9Gn3i6+7dtQzjiptWPPgKRGQSfD6mpaJYgbtZjNNaj5XRu4/p2zdyIYdBugpfKea0bVu0meIiR2OXc74It2aVPfbCticsH5nPJgT6K/AXk4iVhmvy+ZAA5GX5OOfRvLFv7OF5fLoOHXMFb/7koZUN50dKbOOaYR0DZu3Vv/lu0pMf/UHwfOY9fcUebx313Xb3b9yiaN+3xnkYaPxBp4v4Lh6oKnFg161+bgh7Io9Pxt5GT0QkDm5qoOympolWVOepxyGsm54nNDtUvGhRO8BLxWUgUwlkWnSZ7kfXg2JL2F3pxEqAEBPWLXb9wY7u7gA0vMyka7031dT/DS82r7uLZFVyC0ed0QlckWQEdnCwqPn4cBcHskVdgSEjUb2T7h9fSsGNV8nc9dOi12Kh4FJWsxhj2opXYvxmcEokHl7zb/LClZgSVjPFjkpEmkZOJOn4Mjai0RDH2NhheL7ql0GvMI0jyyHVULurYjqYaBy1HUPeuSbuzvFQ+laD2VZP8U/VkPa5jSBJBkwo7hl/oFPqCVESjSBymD+tNXcLcpWa2Jm6gKwqFfg3NsfGrEUS/Y2inhqjGm7z/1fFYm/W2VqI2+Xck4goHjjp2HvF4LWtWP0519SqCwWJkYxXBkI/wjxB1t21JY3PkryCUgf0rtYzZG/F9fVAisUMCRQbQxtzBlR8+Q3msgSfWL+YvA0/mls/mk6UHqI6XU+sz2G9SEBzYFo9QlWmSe2wQY7uRjKZ/exOr9p3W9HrHkJQ7JgXoFJ3jpeKxnc493Uv9QoP80V7ssKTmNYOC33rQCxR2WAkqPDHyhcZtw4upjss2U3TDzToOdQm7zddDHoG25gu+6daVqYs2URExOawkxN0j9iNsmIQNk8zEVkQihnzpI5QTRybJtnz5I/RTDmD9W9clo6wtUXczWsP+Jz1ChuWlUfe1mfq+T25i/lqhObvMs0XjvaC5qvIrF97IwcPvRm20sJ5+FacujGzRjijMpvzzXX3crZA77sq6MMKbWs8t68IgQYwYgp3vhUknQFUYa/MO9Hb7QyQKTVGsEKx//wr0QD6dz5qZUstecHaC9W9djhmtpvvxMzE0VzDWth1igQTtJnsQjhtpj5FIqsrvXLeuCvCYbtq6R3hAChASQxqogjb7lG0neHXLKi7ucDhr5zvEGhT8WVl4TlVZ8/WrjBhwGaFAMdhGmxvKjnSQ4pe1bG5JjweaU+S/G6pXT5Jz7S/noeXkprzeQtCtulqsW+bs4atNI400flkjUBopUFWBV9bxZTNpzzlsEsvXP8sBPU9DRSUvUExp/lBUReGvA0/h5s9eIqD5aFDj7HeRhqpqbDFs7tlSyZhADtcudms0Dy8J8Zcu7amaZ9DuTC/bZsUJDVXJPdKDYzi0v8CLY7hkfvtXBqHfefAGBN4MQeUTCRKbWxeKVp2kSyCDNYunUrV5Af5QMf0P+ytVK54laFShJxpY8ca5Kb+ravMCeg+ZzIaXLqb3mEdw/u8dtCMOQrctigP+NtLof1g01bIdGgMhgpPORG0WZGr8HwSZfgo0Rk1yPAIjVsBnz5v0Okrly7cTeAKCvmd6qXk6QfXLBoVnetCyFVAkqg9QBGjw1o7t9PMVcPnCL1KE/97cvJFjO3dgxrDeXLNkbWud+vDemI6FgsNLC8cRjpTTrWQk+/e9Hq/qJO//k1+u59ohfZLq8kUBLzMO7kZt2SxGDXsEn56Ho5ju4syxURQPg4dcxepVc9m/zx/AMFF+pKh7GnsvvqsPtlj5Vb8wBSWYhzPmzmSm0Oq6bTyw9l3+MvAUOgZzuLHnEDa+4LC5IYE/S9DtZC81Ri2P7VjA5EnH4EdH6pL8i3V0RwUhkTtMcgdLrKhF9csOiS0SzxUaEceBxQ7tL/JhN0nsJkn9QoPcYz3M/qaK4eNCFHg0HD/s0GJsMOp5dd0Gruk/CF3VCGo204eXcO1OKbrXDi3m4c93APDa1/VMG1bCdUu2pUTSraatRHt1YerCiiQB+WBbE+vrE1w5KI8Cv0qOyABUlDN/g1RDrWR7cznqS9D7Dw+RiFYmo+4tntROtAm1MUawqKDN1Pd9cRPz1wppC/BJ9puoIRwHqSiYUrrHcZ1VZJYf696Xd9GO8Fx+dps+7lqTO4eKnExkIjXNXeRkIlWBdUh71s8/P7kx1PO4mfDhSuieh8z2ITJD6IE8IpWr2PTJFEpOvwx/dk/ijZvY9PEdRCrdjfgNr02h55h5RJo3aW3baRWi22mTqK269b8f3oHsmM4nzyeINUj8WYIBY734VZPbhpckVeSLgjq3HdqeDD3Gdfsfycp/WMQa3Hkl1iD5/AWb/ieO47UPr2PM8LuINW2jQ4cRdOt+El5PFgmjgY0bXkZKB0fapN0QXGg5ubw2u+1I+fHnf8IvVw0gjTR+PqSJ+y8YPjWKGanGaCyneMQVfNOwke5djmPmovPJ9OZz2bAHURUPCEGuJ8gtA0+lW8SD/fA6nJoEMs9Lhwt6MqZbdnLRCW4a5y1sZ+qkYlThppY2LbMRGOSN0BBI1ADEpOTLt21aZt+hv3WjUzvDtWhyyTi4i4yVH9zMQcc/yPbl8ygeMqFNpXghFIzGcqRlwuZyRMBPKF7P9IE9uPaz9ck0+ukDe5DhRFFUH5EfEHe3bKd5Ias2X/bev0g10fnseRNPAHJyYPCxOom4ZNNak9JJPuwGl2xUvuJummg5gpLJPmwTjsvvyOObt6TUok9fvoFLB3Zk2scrmHbwIK4Z0hVNUQgbBnO/WMvorp3omBGgY+FBrP76Rbp3OZ0/L/2UQQV5TD9kMNcu/Zg1dfX8c8MG7hvZF6RNLFZOsV/Suf1FMGcrsqYCkedFu7AQwx/AtGIIIRg85Cri8VqEz49Vu4VAvq85Ov7TQlUFASWKcEykohN10hsIPxV21wd3tvLLOmoKtfWbU/zbu4UK6CXa4WlU0aICT8Ah1uAuzDfOdxg0roDxpYcRlhGu+PRFbhr4ey5duoyHhgwnL+pgPVmGXZNAyfPS/oJSDNtLuWZSG3fIXi+orEyQc4SOGhBkDdPZrho8VVbLU7hZJEVBnUsODHL3quXcPnQYhqMzZaFLMvrk+Zoj5TaZHpVZK3ewpiZOUVBnfJ98Xlhfy5WDiuiU4WFzo8HfPqmgJg4zhmvk+dSUyGFFxKRT0Ed2bBtfvnFZa93ykTPwnnMKdotCeDiCcBS+euuGNoXJhDcHZTep79/eQBGKQApBUNpE1L17M/NXBwW0xgTm3DJkTcIdV88txclz05/9oWIUqaRkT4BL3rMMmzv6DeHqVctTatwz/vmOqzB/1okQ8LlkPTNI4wmHYRXkoEmbmm8prn+z/GE6DD2f9W9clWyTXY+6kW+W3EekchXr3jyX3mPnUvaauxEfbNePkgGXoXnz0ZxMVNX+Tr/2turWG8IOm+YnUkj4iucNBp+t0c5Tz0O/KcGSCoqAhFFPVSRKOy0zeX4LYg2SkNetc9f1IHXxRg4cdAVICyEEPl8ugwZfwdZvFtGx08g98NDSSCONNP7/8Msq1kkjFdLEjNWR1XUEvvxSuu43ggc/mkKmN5+T9/8TiqKzw7CYseIVHCQ91Tzsh9Yha1wSJ2sSOI+so7vUyPemLu4WbmsirNt8JRMUjvcS7KOQO0DBvKuWxJ+rMG6rxdckySpujeaULTZ38TwumKBjqbUpnx1rKkciqVk7HzsW5sCjbk96APtDxfQ//Easxh3uArTOjQzIaAwRjiI+vZe7e2fy3KG9ubt3JuLTexFbK5CzniYj2oR0flnky+tRkY6CJwADh2nYd9QibqnG/2g9PXoqbPnCQOhQ/aKRJO1F471UvZCgYnqcmvsNzsnvSN/cVmGYimiC7plZzDr8YLyKZMYnK5j4/mLuWbma03p0Jcurcc+qRQzoezFnHf0EwUAHyqMxXtm8lec3fM1dhx7Ec6N+w+UD+rBqzd949tURvPTu6ehxtZm0t7Yv6+GvsBoiLPtoBpYVQ1FUPlg4FeHLoGHx7Gabtp8WLZHdmqcnUPnwydQ8PYGAse1H95hP47uxs5Wf8GcS/vB+7hwylmJ/Fv2yS7gqdxTabU3YU2vwzq5j4DAtOf7EGtwI5F8+eYGaeBM18SYcJ8qMQwaTIcB6pCylXZqPlEHMosj2sLi+Cf/ZWlLYsfLpBGTCbasqUq6vImLSIzOP2YcfS0gLgIBLB7Zj1hEdObt3PlUxi78u3c4tH23n+C7ZzDqiI1cOKiJiOny8I0auT+XeFZVcufAb1tTEqYiYXLN4G+P7FKR8T1FQx6tK1jeTdmi2qnrnGuxEA9rYo/FMPRdt9BHIt1fQ49i/uZZvkBQm48MNyIThpr7vBpbtuJud8QTWrGewbnkoOY5qe8BXO409A+FYWHNT2681twzhWPhDxRx46HR0y5v0ZE++LycTxTDp+OZHzO7clxeHjmR26YF0jdt4zjoRfdIZSCTWgmWoZxzHN+OO5/wNKxj9ziuc/+FC5KBJBNr1TX5eQe+TkqQd3Db51ds3UjL0fMBte3ogH09GsWsRN2gm9c/2pOLuHLbf53yvX3tbdeshVW2ThEeiNcx+5VjWrH+EJsth4nvfcMZ/arnqQxtLCPxZqWO5P0vg9frpVjICiaSweBCoClGjgdqGr/j003sxjUY6dzkKIdLzQBpppPHzIT37/gKhqQpZqkQTGuHtK8k++DyeW3ABDdFyMr35jN5/Egs2/h8RGwzH4YROA3hm44coNsnJvwWyJoETtrm0tF3K8aKgjioEL2yopTLDpGC0jjW3HlntRtdltY05q47Soa1JHUZU4mQa5E906HC9l4JJ8GX5A8Savkn5bH+oGGm7SVY1699CVwMcOHIaI8YuYMgx/4cv0Iu6TUvocfxM+MJdJFjLVqNlF7Jfvz9S9/7NVP7zNOrev5n9DjgH+dbKpCoyTan1fPs6graJUBx6D9ORs1Pvv5xdT36hihmU5E/0UnKtj+LJXmrfNJKWO1adpPpRg0nduiQ/syjgZXu0kYmL3ibLo3P/4UN59pgR3HPYQUhMZq5cwPsVX1MXr8FQBAFvFsUBNyr+yuatnPGfBVz2wYdYVow1X78IQGawGGGLNttXTmZ3/P58liy+ASltt5YwHsaO1Lg2bT8xdo7sguvzXvPCFDKURjL0WJrA/wxQVYGiqhSOm0v+qX8D28KK1lBgNTFt/yE80O9snPvDu7T/lvHHnyUwMKiJN1Hkz2TGwKOQdg2rv3kcD223S9Uj2TEvwYQueYhCh3aXeMi8WqFuXIwyPUx1IrXYuyios7nR4JtGm8fXNtCQcLjns0omvbuFez6rRBEwbVh7auI21yzayi0flZPnVykOqvx5SAHg8MG2ppTPrIiY7BfSKArqye+4fXh7QnZjm97cUgNzzvPQFMV89EXkR6vR3v+K/U+ZwwGjn6H30Olo725EO3wwMi/7e7OQdqsuny5032ugWrLt9mtJDu4/He8LKxGRGNppxyXJe4tfu7lgGfqhg8j859vk3PUUmf94DUXXkYBMGIhIDH1IP+pzM3YRsbtmxedkDJmY/E7dn9Nmm/RldqT/mS/Se8xcEiKH7sfPdC3immveodWv3f8d/ugtdes7o8m22yThEaOSorx+dO92Pn9e9C3HhlXlDBjrSb7PnyXodVKMd1ffyMgBV2CYEeJmmOfeu4Cn3p3Af1bOZP8BF+LxZAIK4hdW4/5jwnfX1cl/aaSRxp5BegT6hWFn/12ZGST3nFN5duGfCEfKcWyTE3qdz7sbn+Xg7hdw8YfPUR5roNifxYwhv8N0QMvzpiwCRJ4XxxT0yPHyz8O6UWWYPLu1lvF98vmssokzeuXTaNhYjkwumlsgq218gdbJccCpKlJtpDb6Obm5vWlq2kb3HiejSJLp8P5QMQcedQeVnz5JVpcRFPQ8hh1r5pPT7UI+fsZprmNTGDDmQhKrHkYbeizaYRfiSEFE1fD5urD/mLlIaUF1I/KF5bDZXUzIujDYDuxU06mqAp8a/U5rpL0ZwnEQegOh7ByMNu5/KFdw/ZpyFjYTgmeHd0U0QdF4b9Lfuu5dkwKPu2Bya9y78dAXbupkwnHYFv6Caas2UB5tFXErDmTQmKjiyVW3cumhz3Ht4P5M/3hlskTh2sH9cRy3HWUGixk19AbCxg5CbbSvSGIHBw66hE8/uRcpHY4ZNRc8frLPeogEQX7qcoWdI7stsBvKscPbqXnlBtc+zlOyT7WTvQmqKjAiNQT1+A/qcy0ZEDt2tvAbfRvdj76FaKyGpStn0Ougf2G20f79QTe61uVkmxoR4c6hp6EiUWWM2ctvpCZaznElE1DbaJdWVGDVOdixWjI9fqxYGH8gm+e+2khVPMH1B/Xn1o927FK3XhO3mXn4fsk0eXAJwy0flXP/bzpywyF52BLCRpx/blzBqP16MuPjjVw2oPsuglqHlYTQFbj38GIUIRGRCnI8TSi2bNubO2pATiZyZ5HOdVvg2MNRgwFUvwOjO2GpKhFbfG/Ke1pdfh+AIhBttF8UgZjzhpvmHo5gvfsR2tijEYW5yB21WK8vRG4ux6qsSTluvvAWhILoo4Zjvvgusi6MceW4lDp4cMm7CLjZIDtH03dpkxX16N4cyPISVcDWSghledu0iFOctmNJmqqQ6ZjcPryEqTvVrWdlKnQaq7Nipxr3A05VafC2Y8TQe4hZok3HhisGGnQbvZVMXwdQbOqNr4nEqzGtGJF4NW9/MoNwszhdOFLOS4uncOyB1xD05eH3F/7/P6tfGXZWinfV4dNII43/FWni/gtDSoSkLgyG5LCBUwj6Cwj6cgk5FoM7jeXGz95I1oaWxxq4Zvk/mTPsIrIv6InzyLpkrZx6Tk9sr8b2++NYdZLsHMEN57anQTcpyfAmF6dzD+pI53w1hbyLfBU1ZDL8QgHCpCnxBSGniI+Xz+SII+9jyeIbOObIB9A0L0OPvc/1tZESJxGhcP9T8AQLWPvvC9nv0FtZ8W8ntY7t3w4DjxpB9QtTyDtzHo2WH2y72TQmQJYqkc+87N6DluvJyQRVAavZy1kVeKxtrJvf6nO/s8LtvgCpKCgSpGIh2rj/UiFJ2vvm+sj1q3jO1DGrHapfMbDDksIzvBCyeeiIPtQlYjz0xXJW19VQHAgCFh9v/ic3DpzIjZ8tpTza+P/YO+8wqaqzgf/ObdNnO7JgARGQIggISpOOgoCAnagRjZpojFGwJygm1ogpRk3USBK/RGNMAFEwigoqqIAgTamiEVwEFtjZnXrL+f6Y3dkddpZiKLt6f8/Dw87MvXfO3Pue8p63UeoPcU+33rz2yS8oj5VhOyn+uWEzN3btRNgwiKTSryefejKXDHmWWHIXy9Y/T//O16P98CSsP2ysjcW89iQIV/DJR0/SrfsNCKFimlFe/89VBAKlDBw4jZCnhJiVXbLtcMagS0VHzSvNUt7VvFKceCRjfS+a8OxRib1v6tT0uU8Oos/l9ICYeTsll01HCosLBj6JSGk55V8PCYrHRXjsv/O5vtMQpi6fRXmiiod7XUDIU0x5rIwv7C20uOokvH+qlUv1snbsmOvg76Sg2YVsezyFGg5ROFzh3nanYesOVXqS3w08lh1xm0jK4Y8r03HrkLYO5ioBJ6XF3UsXZClBFWaKJweeBjhZCbX6twxyZadirnt7S0ZRue+0AAWOBFTaDn2QDfNuz4px540N6Feci/n6++l7UF13u8IWWHadvAG25EDqqLvZ5Rs/jqqiX94W868bMvKrX94WR1XTlvVLRmK9ugAiUdA0zHnvo53WOf0aIBJFBP2Ys95GrtkIgD5xLGYdTws9Es2ZxM5n5NN1wgz4eg+qXkC7kdNYP2dSVr143tqIPKMrbC8nFA5S6Q82WMJO0R2CtrdORvkUAjLGiOPCAZ4aOQjzmGNRhEA3LWzDpscEA4GCKSQPrkpvVDcPRLmvT0v6twxmebI0D+jYThJHi/DmJ3fRufVo/J5CRpx+L7rmw5FWRmmvIRItQ9N8LJg/meFnPQP78Az4rjPg4tkEQi2A+sp6LuU9XvnVEWmXi8u3BVdxb8JoqkIAG6U6+3IUFcUxay0kJ5RSocR4bs00ymNlFPlL+WnfPxD0FGeU9hrK4hUkpc3Tu6q4+sZOUOlgVQmkqvH1n1PZLm1/StLsBg/XLd6SWZz+esN2pl1XivZE2l1VFKtoP8gnlUqQ8nyFrvlY++nf6NnrVgYMnIaZqsLnK8Yyq9AVAxmvYOPrP6ud8Ec8hB3dRaqyDNVTnDOOTfiKsSvKquOgs5WohrIiEwxAsiqt+GlVrK1WICDt1rd3htvGTlTV8QoT29AQV+dDtbu8KFYRV+cTV9ILlWKPyi9OasnOJ1JZJa3K56TY/nySZjcIvJrkN0trkxTdd1pPgqpg1MlX88raJ3is9y1EzSiVyR289skv+Hz3Kor8pSRim7j0pGO4+6M1GYv7g727YSe3EEvuwmvk0bn1aGLmHt77/Al6XjWBgHYMUWsXS764hzO73kj7DpcQCDRHCBWfN11eJhotY/78SQwf+iR+J0LSaIaPFIpMIoVEmglksgoZr8Cf35KYWnJIlPeY46do/LSMsqjmlVI0cgp7FjwO0KDMuewfrxrLbJTBgfW5XB4QnhN6sscsZ+bCSUSiZVw5+HX8OeS/XMa5Y/ULTOl2LlOXz2L17q0A3Lr4n0zt8mP+8P61zFrzIBd0+TXaj9rRUtewdsK2uQ52JRxzmcFXTyRRw4KikUZWrfaiy00oFvziw7L6Zadk7nJUiaov+GW3Lvxs+cpMP/vByR1Z9s51JOI7GTTk9/zmDAPFaIYAbngn2833rqVR/nBmEV/NuIx2w6fRod8jSA1E0kYLHwdn+DEXLkfr1RkxsGc6jj3kx0p9M68VN7t848cRAmF40C9qDx4gCY6hI4VIx6mrCtr4YbAnkmVl1394IUSiyFgcKURGaQcQfl/WZk3oP+/z8PmD6yWxK4gksWemNwWUHx2P+vYmOo5+CidWhahMwFsb0Yf1wXEk9sx5EIkSuH4CQiRofrFg2wtKbQm774NdKfaq4e5BDSWzjBHBJ/+OKAgjrp9ARU3mfBLYXoPr9kped9eirfxmwHFs2JPMbH7d36c5ivUVH63/G93bXcJ/Fk8lEi0jHChlTN9H8OohwoHSLOU9HCjFcUyi0TKkdHes9kUg1IJHXuh+wMf/9IL0JuO+LPIlJbU5eFJmgoo9bl13l+8uruLeRKnrEm9VL6hCE8ch/b6MhSR+VleeXDo5U6+9PFbGS6seZewpd2RlYwYo9eWxLbGdISccw5Q127n42EJaNNPJ15WsXXGocWnLtiit3pWgzONw3MQCNB2suGTbXAu7UqPFj9tiAj1O+yWKkmTxhw8Qj++kT9+pGP4ScFRii/7KSX0moQQKUAPFRD96CeO4rhihUuzkTnx5hVnKuy9PgB2j8KLfIhVJQI1nudw2VFaqQBEZq5+ZiOeMyUM2HaUsmbLx+EE6Dp+udGg1MR+PV2A5YHsFqhQ83a8Ve2IW8T9ZWRsw219IUjzWYNv0JJHoLt788lF+3+dWookIqdRu1n86jRan3gSpSi7ofCNC2EglxXOrfpnZCPrR6dNYuuqPRBO7uLfL9RhGK2yrCm/qM7z+Y5i9fFpmUXTBwCfZuHU+G7fOz/oNPU++nECwBUIo2HYSTfdnPotGy4gld6EpHsJaEnvH5+xa+n+ET7uY8jn31irW59yDvyBMpf2/W0JsWxIzWlI04VlUmcIq/5w9Cx4n9VW6lJaaV5qOvXfXbweNkGbOPidkw4WD9vaAMFp0xtP3Ct5c9TuGdbkPn16Mqnr5/EuHZtXyn0hIPl9p036Yn7+dcT2/2Tgno7RDeqOyJNiKIn8pn+9Zxevr72Ns57spRxJuoVNyOaBaVMV3Y+32UTy2VmmHdP8p/6tBi5+ka7XfvrAsoxj8rFcpz6/dyc96lfLi+l2MO6GQIo9OgVdh25aXqNiznid6X4NUDBRpoSa3U74zXRrr7Td/zGk9J2HIQkzvSTmt9inT5Pj+k7CJo+YXwt8WIL8oQ9x5DbIoD2IJLDWBNEApDJFSVL6psDbFEpnfOSzBtpkWRYN1NCGwpKR8psUxl2uk7vtjrdX9rQ+R1WFjRKLIbTsxp6dzkOgTx2Z5VshYPNvT4osyjv/Ph/zpwmGkbAdDUcjbsQd78Spq6xs7AAAgAElEQVS0YX0QJQXpEqPr/4vcVo4++HSEvwB5Rlekz4P9t1cy360Kia3EIZykxbWFEHcgEgHTy1d/oV7ce8sfGzh1wzVOKCU1uieOHsFrqGjSIG56SOVIXrctahI1HW7sdgwFHpXmfg2faaHIVgzqNIX5a36ZUdADnmJSUUkoeAwX93uBt1bfQzS+k94dbyM/2BpVkfTocQtCfPtDRGw7mVGWTTPBnsOoKGuq56AU/ckXLwNcxd3lu4uruDdRGkoaJH5yKWq1hcQOGhmlvYYV2xZwfqeb+FWvi7hlcW2M+8+7jeEfmz7g0pP68tPuzVAAT6VK1S4np0ubVJx6FqUAGlufyY5bA0hUwPI5STqM9qIFDaRMK2SLFt7NwN734lH9hIdORjgOiuYlIXwEO41gz3t/pO2Ih9iyZDpdxvyMlS8btbVax9gous2G1x5s0OU2V1kpKR38WhVmIo7qDeeMyUM0nRqtoaBOomoLG5Y9yIln/JxVL+sYAUG7QQarX66N+zvjQi9f7o5nnWvtlqj+dDm/JDFWbJvPeZ1vwBCVKKpJ/y43IBC8VsciMbrPQ1zV9ecoqo5jm+TphQw89SZ2V/6X99c8TjSxk7N63c2y9c/T6+Tvc96ZjyGEipQ2scSunJaMWHIXAW8RimJg21UIoTJ02B9QhIppxbHtFO+9exfDh/2B2NL/I3jK6IzSDtWu06/eQ7MJT3OoXBhtW1Jp+1BVP/5gCXa0HEgr7UXjpxFz/ByIq7FLNoqq0ezUy2jWaUxGLraveRlFVRtci8UcP8Xjp7GzphRc36tJmUl6n3Ana2f7aseE8Tqb3kuxfYODL0/QeZSHlTNTpKKSiecOYXPlDlbtSSvvpb48FBxu7vcUlp0iGvuatz64gW3laQX6osFPYxhFVCT3YBS0Q/WLnBuYtmmxZu0UpnabgM9bit/wo6kOV3QsxKfCTSeX8uqcFJFKk3BIcM6I8bRosYW3511FNFpGIFBK3373Ulx8Cjt3riIaLcPrLcTvP4avK7/MabU3dJ3/vjut1jvp3PvQ3gogt5cji/OwRnViw5zsUAT1fwj/aYolMr9LOGraO+SrP9fKiVYgcNT0c6qp2a5+7xxENI4I+iEcxInFMa6/BBmLY63ZmFbun5+TPn7xavQrxmL+eWbG00I78zTytu3CeuIfiBNKEZeNQe/XI+NSLzqdVO1iPxNz+szaDYM6SrvofBJJc1uWfLYdeB/a0k0oo8dg7c5OsmftlkhH1G4inFBK5IJTmfnRpMycNKrnVPKMIkzRImd/yfeAT0kSMvxolYJl/4J4hYkvz0Pv0XcSje8EYOjJj7L2ZR+fVJj48lQGnf8Qlu4wa7ZFpNIhHBKMGnk+qpqdQPLbiKp6eO6vaWX6sstdRdnFpTHhKu5NlAaTBplWxkKiGXGK/KVZynuRvxQUwarPX+T3fb7H7mScXako/9j0IVedPIB83YtifkWiMsGnL7fC8As6T/BQ/vdaF9GCy5KYRowH+h7DHQu/zliaQl6JmUPJTyUk8QrJp7OTdL/Eyxm9H+eD96+nvHqRvGHuLRzffxL/fXcaJ42chqm1RASOo3DwrUhFcuwpFyH8uzllZBxFC+NYEfSAny8XPX1QLreqKoiXb2T9KzeTqiwjr/UA2o54mA1zb81a5CbspqOUSWs3y+bdQryqjFYdr6HjWSfiL1RY+nwiKydAdHfuDRgnJWk20UMydDw/Pf3/qExG+NV7V1PkL+WHvR5h65dvMrTHHRQEj6cysZ23lv2KsvJVlBadQv8uN/DCWxPruBn+ipRZxUfrn6d3xx/w/ifPsGnrgsz3tWk5gHP7TmPWwtpFV42S36P998j3t2Trlvc57vh+5IVbs2DBZOLxnfTtdy8+XzGpWDn+LqNRvOGcyeM4DC6Mda3vbk33Q4BqUNL+LNa//JPahfvIX4Ha8IaLbUuErwXNBj8EHhVCPhzCrJ3tyc578e8kp13qod1QiJdL1r+douKrtPKyaZbCjeeO4AcfPUOpL4+He13AzFUPsWLbfIr8pVzR7e7M94UDpZhWHL+i82bZc1xw2Z04caOBDUybTVvfZtPWtyktPIVeJ9+EVy8mHChClYIZc1JEKtPnRColr861GDe2GdHqzatotIyF703htJ6TWDB/MoFAKT5fCYqisW75g9zb80GmLIlmxtgH+xzDrvemZpeBm38XHcc+hfXcm3B2dza8f1uTDv9xOTgsb4xjrvLz9Z/quJhfZWB5Y7ULvHAAxTAw//ZqrSJ+yUjM6th37ZKRyPwQ2iUjEUKkQyx0Ff2HF0E8AR4DJ5FKu7tDOi4+ZWbFwcs1GzEB/ZoLQFGwNRWZMjOx9KIgjBjXhw2zflBPfjuc/yyk7NxzlAJatTEiNbwrMz+6PStx3CtL7mZs1zsIFeRl5YhoHtC5p1cAJfUlL71+MT88+z0++peZNWasne2jz6ibADKbgDWfffxSinZjDM7sZ+Ct9uL5YLHJoDP9QH0DhYuLi8uRwFXcmyj7ShpUYyHR7SA/On0aT344KePafE2vh3lp1aOs2LaADbuWMfaU22kTasa4Vqfx8Mo5lCequK/bSFp6mhOvSCvcq99N0fYCA8Mr0MMWUXU3mmPQ3GPz5KDmVCYihH35JM2vKLgsn93PeWrjQCd4WP1uepKLV0hiUcmrbykMH/IoG9bfj52oIFVZhuYNZy8yEz5MNUSQKqSdZMPsG+pZxo/vP4mKzbWK4f7c3NPxtTdnrlNzbrsxv8NORNCDzYlZwSallDmOTbyqjLxmnfH4j2Xhc0l6XeqtlxNg3UKTbld62PZs7QZM84kenCC8uSjFps0O4VArRo7QmNL/NXbFv+LVtc8wvtP1PDfnfMKBUs4fkLaoA/TudDWvLb47awH18sJbuGDAE/Q86SI0xUOPdt9jx571GSW9T6drie7+gosGPY3tmEhps/KzWZzW/lLeWfE7Rp7xC447/kyWLnmEnr1u4fQzfs6HH/yChe9Nodfpd2DHdqEECnGqdudOHicOT8KgGus7+Kotjk1HPhodVoINc7JrPW+Ycwsdxj8NBBs8TTFtrKdeBUC96mxkQSBn3otdiSqCupePXrTqfdYjeAwzh1yPKhT+vfKXrNg2H0iHEP15+VQu6zSJd5dP4+xeU/F58lm5/kXOOfkH/HPt/Yw98UaaX9kyq/8UXBpnT2oz4UApAU8x/Ts9yrx5PiKVknBIMmqkgd9fq7hDWnlH6rRpcy7HHtcfj5FHMlVBwN+cQKCUPn2nkkpV4vUWpt3nl93OQ90n4w+2wlAVgnaEVZ+9nfXbUpVlONVJw0RJHicOm4qViFD20Z+Jfr263rhoGApeqpDSQgiNBEFS3zAG3uXo42BREY6Qd70XQ+qkhMUuI0KozjHasD7ZSna1FV4bOxhz+sz035eOQuSHwHYQoQAyUon5ajom3rjzaux576dDMqpLyZEys9YfkFbeGdgT8++vIq6fQNzrI3D9JQjHQSoKKSWau4yhY+LMepXmFw/PinsvvdJAqElioRDe6yfgaJVEVtRPHCd0H9hxivHwxMDjcABN2HhEJcgQbVoOQEiNeEW25TheIQkYx+BIO+d4EgwozH0rUd2nBcOHemjqHid5+TqG7s16L21Vz/675n/LzvaCcHFxObq4insTZX9Jg1RVoCW3EFvyFDf3e4wqM0I8sQtdClZsSyusn+9eRWVyF7d99J+sePe7ls/hb6f/EF9eOpN7RZnD0hlJfHmC0y5VMK0Yuu4jEt0CwFsfTmHk6b/EcpLoRR5a/CQItkpVucPqd1NUlKUnOl+eIJ6URColr7/pY/y5d7P19RswQqVYifQCoO4i07IdKgngLzg+52Sv+wqy3tuvm3uO+NqKzQto0f1yhOZrcko7gKKoNDthAM1PuZiq1DZ8ec0x42nX4boLkVRM4oRNSm/wEKuEqoRkB5I3Xk7h9wtGjfDg9QriMYmmFrJ5ZYhL+v0KIeGqER9QGfscpJKxvkucnJl3k6kIjhlD6CkKg8dz0aCnsJ0UsejXVOxcR15xO/7x9tV1XO8fZsXGl4gmdqIIFenYbNmygE6dv4+i6Jza7XrmvfFDwuHjKXv3N4R7/5SK9/9K0cgp2THu46cRreO+3tTL/H1bkdLOvXDfj7dE3Y1Ke94K1EtPrCfjvjzBtmQFJCvw5RXX+2xHxWreWHkXYwc+kVHaayiPlVGc37Z6UymFEArHlnRl0+evcdEpkzFjhbyxIsWpFxvkeQXeACSUKAGlCxeeORtFSOa/myJSmR7rIpWSV+YkGT7U4KUZSZofo9DndJ1gSEFRJKd0vY2li+9iy5a3CQRKGTBwGr373M3yZY8Rj+9k+FlPM2DgI3i9hXg9IXat+hPFXS4kvvuz3CW3UhLr3C5sePmHGU+G1kOmsOX9xzFj5Zlx0TAUtMQWPp1bx1V5xDTwHptR3nMlPd07pt3tX42HmA0/ev+v9XLWPNX3cgyqLd3F+fWV7N0RhN9X+zcgy3ZgVZeA44RSxLCuEDod00ihjR+CGNwLWRXDevcj9HMH5TQeyFg87f0nwF9ZiVV3jfLjsTnlVxEazpqNUBmlxdhB4A9ALIoqdazfzSAwcRx2KIAqtJzhVtKMg1/Hth0MTEy2MnPhzZl55ty+jyBUco4ZAX8BEokvT9b7LJGUnDvagyIEjpSs+cSkW9emE0qXC0P3HnTyuLrJ4YCsuuwjr3bLvLm4HElcxb2Jsr+kQXWzNxd2/x4vLbgagHP6PZLlPu83CnJmmI9rCU49L8DH1a5lvjzByaPjvLHyfrq0GYeUEtNKx0yfd+bviSV38fqSX3BKq/No0/z7fLg4Sa/OBqlYeiL05Qm6jvewZE16xztSKbETCcxYeWaBCfWVb9uWOIY352SvB5vRbvRv2br4acxY+f7d3IXewHWanqW9BqEV0Lb3Tbz18aOc0fEHdDlPY/O7Jp3P8bD61doY9w6jPSSsFBKLmKKxfIPJgH4GwwYbGB7Bq3OTGavCuaMNenQz+PfMWkvD2cPbgC0pDjUHaaOogksGvUos+TWL1/6asl2rCAdK8RhhFi24nWi0jHPHziAR28nrr6dlr//AR5i1cHKWlX72olsZ2uMOurW9COwUimoQCJSSSOxi6ZJpDB36BIFAKU68gpY9r0XoeRQOvRUpBM2+9wzScXCEluW+fiBl/moUj2SkioChuorHEUIoGnmtB1DSYTSaN4yViLDj09kIZd9TUdZG5RdlKAuX0O28fiyvMz61HmNzz2evA3DPmIvY/LKaNXbNW/trItEyKqq+zBlCJIBYcjezF92aFcqhyyJmzrWIVEo2bU5bn05srXB6z8LqfpOOXx862IPXY3Jiaw2vV+DYkvw8weUTPJhWdh8bNsRDx05TiMd3Ul6+igXzJ3Faz0nsrE5SJ6XN0iXT8HqLOaXLbeR3/hGxRAW7Nr5N6yFT2PzmvXVCDR6BiMOGd+7K8mTY/Oa9tBp4O5q/JDMueqnKKO01x22YO4kO4/5ECn+DSU8r/cHM3PJtKKP5bcKWMuccbiMzMexyT2WDSnbm77wQMj+MNnEc1usLsQa3YcP8O7OesVHYAiUURIwbSpWq4d/LeKBdNAJr7jvpzQIpM0o7pDcHmLGItqOm1cvBAP50G/5bhvPnv2faxNjBae+A6TPQzhuG9sYixl74EDOX3pYV4x4wijIyrugxZs2/ea867JOZMOSvdBij8OnLnsy40HW8QsTaxIefPMug8x7MWu+cer4HS5fMmp3K9NtzRnhQlO+WjH+z5HEuLi6HC1dxb8LsK2lQ3ezNTqIis0v90ad/4Ypud/Pn5VMpj5VhWtGcGeZ3RjawfNXv6T/mNgoCramIf8m8NfdRtmsVZ3b9CY608OhBUnYMXfMx950pHF9yBh2P/z7/mpleoEajKc44y8DvEwQCgmWrU7RurbFmrU04JDC8Adqf+zj/Xfhbol+vrl6ETsMkkPVbErafk0ZOY2Odyf7Eofew6bU7MGPltB35CIqvhLi5d61vBUU1kFIghMREpd2oRzMx7jWLhqaqtANUVpkYXkHn1qOZvehWBve6H7V3MXqwhG4Xe0gloSomeeuDFKf30nl7QYpjW0oGnqmTSIBlwxvVCgWkN1TicXh9XvZ7r72eZPxYD5apURFR8Png3XfyicXyGDr0UT767H76dr6aj5f+JhO/6zg2phUnECglGi3D8OTltNLnB1oiHBtQEEJnyNDHWbP6L+nSOzgMHDgNj5F+vvGEBAI57kTt89tfyTFX8TiK6D6O6/NjUpF07V5F1Tmuz49B90Gi4dP23qgUikBVU/T6noGNYFPV19yzaW4m+dxjW1/lzkvOQRcedkQ+YV715hLAh6ufrhdCNLH7VGLRMl5bPJWAp5hBXe/DqxdjaAqWrRGpzHax7XiynlHEId1HPl6ZotdpBnNey1bQpQPz3s4+9o03kwwaEKDLqXfx9psXE42W4THyAKr7y9d4vcV06foor7/pI1JpEQ4FGTH4Onaue4Lj+09C84bR/cUoqhe0VE5PBm9BK2J2fkaupbQa8HhIhxY0lPQ0cP2E6rnmm5X0czl86IqScw7XhULq8ecBECeUZiWfq1vfvcZbL4KGZTlo/iD+8/qyYcZVuZ+xrA4Zsm1sf5Dg9RNQbRu5YxfW3HcgEkWdOA7pyPpW/tUb8YwbQrtxz6IKG1umN01NW9TzIKzZBIBqjwCPAV+UEX4RLhn7a5xCP4qozSpfK+NmznnGcuIs+2o6fSbcSCIRJZr6mvkbn+OMTldxescribGe1mMEBYETiaW2owVb8q+X9s5RkeSC8dlu5i4uLi5HEldxb0JIR5KnyiwXRkgvthQBQkqkI3EUBamoGevyziV/YVT/u3ll6VS2la9izbrnubnvH3CkRBEKD/QYw/QNiznn+B4UegIUGl5Wf/J7ynat4sWFlxIOlDKo26SMVRUEHi1I0qrib69fxg/OeZnjS86g3yl3YJoiM9Ft2+4w87W0herC8V5KS9OWqHBIMGJIkv++fhMgKe1xBS26X47qDfPlot/Tste1WVmQbVuS0lrSbtyzKKRI7P6cLxc9RvTrdHmuDXMm027cs/WUdsvy8Eqd3fJRIwxCxW1oN+7Zb5WLpyJU/J5CItEyPlj5KKd0vYPtqQCvvJjt0qfr6WdzSicNKRVemZNg+FBPVgwugN+n1HsvUilxHMFf/x7PKCR9z9D516wk8+b5GDvmZxh6nC1banMOfLLmOTp0vJQ+faeyaOHdpJIVOd0cq6q2UhA+ActKEol8zfuLptK7z90kk3sQQsXwFFAVNzjg2PIGSo7VhGC4isdRxEpixXbx+fwHszbhVCPI/kow1tuotB0ggaoqeIMKO5PpbM+lvjwub9MdS9lOZWo3b6y8O0vmYomdhPU8burzBAiFPZVf8OHHjzGg60/qxapfPsHLnj3pjNJ1+4TfJ+r1kY4n6xmlHWoV9LGjvTn7k64LAv4TKSo6hURiZzrWPVDKgIGPsPjDB+nY6aZqpb32enPf8nFOv9FsnHMVRqiUVgNvx59/EqDm9CZyMLBtiWEo1fG+MuOlVDN+GqFShEgvBRpMeuo46fsO9fqX/5jOhHpexx7Fg+IVGKbAdsvFHTHCUvKrXhdwy+J/ZqrE/KrXBYSlrLWyR6LIUADl+gmZeHNbVVC/NxqpKDiqQsg0kaoCqsRpYINn7xwylu2wB4GmGgSal6B+bzSOriFtB9Vx0H9wHtYbi2qzyheEcaQgmvJRUhJix45K0uO6pLJmE8BxkNvLMzXna86r8Q7gizL0385Eu/Madsua0my1/UsInTYtB9C59Wi8Rh6JVAWrN88GBJ1aj2ZLYhOqGiClJqlK7OTlhbdw4aA/kkpV4S/Ioyq5kbil4LHq9/FIpcQVbRcXl6OJq7g3ETRVQW7bgfzTvzMujOGJ45C6hv3KAkT/Hlj/mFsbS/aTC2k36rckomUomg+BwsUD/oBlxlAMP28vf5RNWxcQDpRy3oA/cPXJw7jtg3cpi0Up9Qe4t/ullEc2sa18FZFoGV4jj3CglLN7TU27ca7/O8eWdCUcKEVTffTueBuWpRCN1l/khkOCWFxmLO/nj/Py5WvXEf06bQHbOGcyACePf4qKzQuI71xfT4mybUnU9hHQTdbPvjHr3uRaUCiqkVHaoTrmdG6Ki873Ekv56hzbtJV2r1fB0PwEfCWEA6XpclYrHmBEz8frPQfTTG9g+P0Kjp2+J4mErHecUMj5DEX13zUKybgx3szrRCKKIlIZ6zrApk2zMIwwHTpOYPhZTwOCsf2mMfO92qzyI3tNJWDkoygeLKuCj5c/TjRaxvuLpjJs+B9YuuRRepx2x8HdlAZCImpCML5JLXGXQ4Rj8dm8e7I2TT6bdw8dxj+1z9NUVWCoMdJliXRSdTbcbNuhhDBP95mIjYWQFk7Vf1m/fg5t2p9Xr5LB2b2m8sqi24kmdnLBwCeZteAnACRSFfTueFtGaQcQQvDhkhRDB3uY91atJd0fEAekzEcqJULk7k+mKdlTAad0uQ2fT+Lx5DNs+B+JxXYQj+/E8BTnvJ4WaJHZ8NB9Rch/L0JWRmk77n42vJXt2iwUlZAviR3bwdrqpIA153656LG0x9KIaSQIAs4+k55mSsHX6V/+Yzqjnnk3N368krLlGyn1B3jo9DMpUT2u8n6E0KTC8arK030uxSK9qAtLC00qODWhdLqKSRwpE6BWb1inJJqqE4pV4dQJjdAuGYlD7KBKpdZsqmmqTqgyHWph72XZr7HE1+ThyYWIxTH/sxCtf4+sbPSZa9Qct7dM1r2GE6BPp2syYVk1FU+2794IoU7c+cF7ddY5d7NyxVTiyQocaZGIfslH659nUJeHURrot4qo/50uh5crR79KYaA087qkJETcTFK1x83u7/LdQznaDXA5MALYmH/6d3ZW2OkzEOV70Hp1zijtADIcIGXuIWlGWLHoQRbNuYZl83+OTEYxPGFenP/DTJmugLeYpPBmlHaAsliUKctW0rXDdUDaKhr2l3LhoKfIC7Zk5WczObFFX1Zvns2YPg/j2CEcRyMWlUgHRo30EA6lZ7ea2M9P1pr4A4IVq9IDrRnbmfX7cieoy0H1onHvc/deUEj53dgt9zqVpKwo8dQezu41NaO8V5hbGTBMZD2HUBiGD/UgAUemFZCly0yGDs5+XqoqGTYk+71hQzxUVdXevEilRFbf3nBIkEru5JM1zzFg4DQC1RNsIFBKy2P7svjDB9mz5zOqqrYSMAoZ1XMqV474FxcOeALVcfh4+eNIabJ0ya8yMb7RaBlSSrp2vRbL8h/UPakJraiRk+wyfyCqvVHqYoRKEYo7HB5upHQacNVuuGOqqkCxt7JkzpW88+IYlsy5EsXeiqrWrqBt20GJKwSdBPNmjOCtN67ls02z2LTuX2iqh6E97mDC0L9w/oAnKQgex4jTp3LRoKdRFaPaiwgWf/oX8oOts8YNR0piMcmiD1Kc2c/g/HFeBg0wUBWHs4Zl9xGvr7a/1RAOCaqqnHp9bNgQD6EQfLjEJBQ+CdOMsnTJI1RUfI7Hk0e//vdhW5Gc1zP8YTqMfxpvXiuUWcuRqzfCF2WoM1bQofdDdLnsZTpe8GeEZrDuX9/HSUXqZfL/bN49nHT2A3QY9zSqPx+dKKoqiKKiThyXji+GjBt1jXcXZPevUM/ruOPjlVlzx20fvkNKb9obok0JYTukojv5ZPYVrHj+LD6ZfQWp6E6E7VBhCyKKRir5FetmXMnq58awfsaVGFa6/+QKjbCen4OKl7YD72twDG2Ihq6nXzYGcf2ErFwJDZ67ZiPW3HfQxg7GuGEC2o8nIEMBCAUQPzgbbhqL+PFY4qqa8zpSidbLpfLywlsI5nfk1mqlHWrXOd07/xSPHkQRarqUaaeriSbKUJTc86CqurJ9pCkMlNJj9iVZ/3y652g3y8XlqOBa3JsIDbkwCk+6BJYMBxDn9UEGDETATyq5g4/fuZt4VXryileVsWzeZLqPfDzLbbRXh+9jmUmmtu9FseZhp5Xkd5+vZPXucgyjIJ2Rtd80hFAQgEDQo+3FSKDHiefx2dqX6Nj5DqRDxqru9UrGj/USi0pi8XTs5xm9DHbvTtG6lY6iStqe8wgbXp1cLwMy7HtnP1e8e66kdELUtySHQwL126abORaOIrGsBO+ufIxB3SbhNfLAU8I9qxdw9eDu5Ote9pgJylIamz/2MbC/wcpPTM4Z4eHVuUkWfZBi0ACD/HwFVZEkE5KAHwYNMND1tGVQ1yXz36ndTKlRSNIJe1Q+Wf0cW7a8TX5+O4YN/wPxeDmJxC7Wfvo8Xbpei9dbQDy+k6qqrSjA/Hk/xuctpmfHm+nXeSoyYWc5PwQCpSiKjqodd9ClquqGVuQKiZCIegm+Wg+ZgsQ1pRxuhKLlzoq+j+R0hhpjyX8mZY1ly+dNoufIZ4nXC23Qs7w+Wh7Xn3+98+N64RmDuk2iJK8dQgjO6nU3/1k8FST4LYsrR2tUJgTvrnD4aJnJqJEeXpmT5JW5ScIhwcizPSxfYdK2jcb547w4Tlp0zZST6VN1Y9wXvp/C74exY7woCkgJipB8uMQiFpPs2f0Jyz6ayoCB0zCMEKtWPkNFxWd073Ezo0bqvDLHzFxvxOA4IrED2whhWBrW6o21P/2LMuQfX0W78xocQ2JGtnLisKkoit5ACS6btTN/hO4vomWvq/HlH48UXqKhIL4Gkp5Cdv/ao3goW74x69plsSg2ktxqlcuhJqlYbFwxna6n3YPHKCKZKmfjiul06HMboO8zNEgxjZzrCkWoqLNW0mHY/dC8EKHqVNmB/YaVNbROcRxJhVTYVym1uufKL8owp88EQLvzGqJeL9qoTvWS2qk58pI0FOMuhZFR2msoi0XJC7ZGV1Joqoch3W5BxiOIoBeQ+PeaB/3+tAeNi+pKh3AAACAASURBVIuLy9HCVdybCA25MMpkCmmo2OO6ZrlJth37+8xCt4Z4VRmKqmfFGYd9pRRUhWj2zCZkeZKiIg8PX9mLh72ryA804+LBf0JaIaykxLC2ZhTmvBMH0LLfzRScchVSSKqqHD5Za9Kvj4fycsnuPSnanGjgDwgG9vfgSIdoVMPvl0jHIqUeS7txzyKkhcDhi/cezSSo21d2+P0pZZn7ZacYNcLDK3OzY9z9fkEsduifz1FD0VBEOsN/NLGTWe+lww7O6vck5ckENy55I3PogNJjuannGXy80uTk9jpr15mZUjeKCps+SxEOabzzXoqRZxnkhQWKKpAy7WYfq64QEA4JRo304PVILhivgdxJ23bj6HzKFXi9+aiqH79fxecr5rSek0gmKwCBz1cCgGlG6dfvfgqTrbD+uAmrfA2iyMPAKx9g/to7iCd2MnDgo9h2+BvXl64JrcgVEiGlYNuKFzIJvqxEhG0rXuC4/rd/o+9yOQiEQpuzH2DTa3dkxqo2Zz+Qjs9oEDPnWJZ2m89W3C3Lz4CBj7Jg/s3phG/ewpyLeL+nELl7C1YqxrKy2YzoNZXmybbYv96AXj0Ojr6iHW+tF/i8krGjPSQS6c3JlavS/Wfu60n8fsHpPXXy8xQSCfj8vyZjx3gxTYnHgGhM0q+PgWlKkA5CwO7daUt7LCYZNVLH7ytlyNAnsG2TN16/hmi0jECgFF3zEPn0Cc7pNwDFW4yT2MmeFf+Hr/NYDE9hw27tuooZ3ZrJI9Bu9G9zbpZIx0L3F3Fs7+uzNrFOGjmNKq0lthT1kp7WUNO/FK+g1B/IUohK/QHUdHGx/QiDy6FAAJ3a3AzTv0aWb8Nf5KHTxJtr7/4+cn44ijf3usK20QefjvD5wfRhqZ4DygUjFJHzekIROd3a67KvMA2dKOvnHFheEiH0nLlUNCFzyqquKCRiPvJUiZw5D844CZkfxSkoRFMhLywQIj0PKqp0pdrFxeWo4iruTYQoKnlXjc+4y4uCdNkWqWvYsfKM0g7pSS1ZsQVfsDRrwesLlqJvr2Js9weYueyOdPyXbIbzx7TSDiDLkwSe/Zy7J/UkZUmSqXQ8WsCIZ+3aV3y2gPiO9XQY+BtkcxufT9Cjm8HqNSk6dtDQNJ1/zUjULmzzFYqLJGCSSKQttzUTrqoKjut/O8f1m3RACeP2pZTVHuOgaUnGjzVAChASx04iRK6M5E2XhBJCFwnyAy05u9dUXlucTsS1cfM/eOj0O7ntw9p4vsvanMDHmx+m44kXEfCfSJdTjGqviPSmy6ldDD5emWLk2R4UIVFUiaaa2LaG3wfnj/PgSIHAwbYTJJM15aHChMPtABMpdUzTi04cR0gkEq+3EHCQ0kEID0I0o1BvhvW7dVlyJ57dxtBJjxPXYliW/xsr7fu9Z7aflr2u3a/XhsuhxxIBVCNAq4G3o+g+HDOOagSwRHYliWz0nGMZ1PfKsW2JqrZk6LDpgAmKmnMRH/AUEp/zc9RgEX0HXoNTmcJ+OnscVP+8nqE/bYNDHEkY2xG88156IzCRTHsVCdJ7DooiCYcVjjtW4/V5SWIxydjRGuGQxLFBUUGI3USjX2PoPgb2D+HzhVEUi1QqgKYJDMPL8LP+hOM4aI5AfXctnlMHs+HNO7Ji01V/uvSVoH4mbnXiOEziGW8mgK2Ln+bEofdkcgukq3f8iq+W/ZXSHldklHY4+ESNhil46PQzue3DdzLjzEOnn5lOUOf2pSOCYfoxp6/PHkunf40xqR0g95nzI6vMYs264nujkKqK/Y/XstYa2j7c3GuQQqSzwdfJt6NdNAJ5AGbqXG2piYn37CfhaF0c08+5fR9lVlYd92n4nSS/6H4qP1/2cUZWf9H9VDxYpKi+F8P7Yk+fAbsjqPf/hFSOJbKquLlQXFxcjh5NWnFv3779BOBngAH8et26dY8fiutqqpLO1J4re3t1ohebOEgToahIBFKKjMJZUyNaSBNFUUGmP69ba3p/35lQNby2VacNIJqXIK6fgFqTQV5VcIghffkUnflLhLcYmdhJZOlv2L3hTboPe4Rlb0wmXlWGL1hKj2HT0EUJhVUxLuk0DcejYOAjVT3h1yDLkxiOIGrX2SJvYOKU+T6UZCUBr4HH4+fULjoIidcr026kMr2olU6SRCL3hHcgivg3wbbTCua3mUTCQQ/qoLbE4z+W8YP+hSZ3kYyWEVCSPNVvUCZhEaltvL/9A9ZsnkGbloMYcuovCQY9BAKCgWd6AMnAMz0IHKS0UJQYqZSBbTeQb6Aa25bYWc/PwVbz8elJhEyB7eCgk7Rryu45BNAyC80aZHkSYaskbR9Q248OdQWAul4bdUsSNcXqAqoq8CsxhGMiFX2fY0xjIBZz8PuPwVfkQzo2qF6i5GPaoPkgyB6wEulxVfUTS6qkbD/dhk5j+bxJmbGs29BppBrYaBEIvJYXxTFwdLXeIn5sv2kElSDBMfcjFZ2EEsAXFJjlK7KuI8uTGEIHCzy6iadAz4xpqiKBJKpTiWKbiK/2oO2xKO7QnhHDNRTFQVejKKaJA8RMP6oaIhAA6VgIRWDbZMZEu46SnKdK5ON/T2dz/6yUDuc8giz0IzQdR9QtfSWzSuTVuLV75Z6ssTr69Wq+XPQYHcY/Vb15piFUg8otSyjpMOqAFaK61M5XJgHd4Kl+w7Clgy4EIRti+7GuuhxCHJFzLMVRADtneFlN2dW9yyxKRQFVYP/ubxAOoI8djPD7kJEqAqEAFfuzmkuQn36GfvX5oCjgOJgfrkIr7k6BqF1P5doA2LstdcM0POq+E47WxbYlutqSCwdOR0oTIXSEE8DjOLTwxLm/6wmoagDbjtLMA3YyXbGk3vfHUnj9kDINHAdURWDoJpWV+54PXVxcXA4nTVZxb9++fUvgPqAHkAQWtW/f/u1169Z98r9cV1MVQrF0VtR62duf+idWOFDPLb31kClsW/ECLXtdi+05FjW5JatGdJvBU4gvfoFwv2uJGfVjsnJ9Z3DiWMz/LMJasxFRECY0cRzk+9O7wtEqrI8+wTqjlC+XPoPR65c8sCzI9qikWaCQ2/r/hmZKGV998BRdTp+E5itI1/t9bSXmh7OAWluVuOsGRJEna+IXRR6cvT0dG9i1d4ROzPZjJLfWs2Babl3sw04oqFMWVbh/vlX9/AV3DirhmKCGE93JV3OvzTyzwDGdGXvGHXgKWiExkI6DmtxQ77nV1jPX+aabKLYtqbINwNir7E8aRyG33FWHQR7uWus1m0W52tZUUFWBP7WV8n9Pwq4oQ80rpWj8tJxjTGMiFnMoKSll164oe0wPD8xPZWT31j4qqfd+hhnbSduRv8LvKSBmB3HUlvQc+Sy5ssrXJddYWnTN+Vw8aDrSSaHsjuGLBLH/+mLGquebOA7pz8spj2wvx3zmeURBGO/EcZnkWk6NfNZVhgbfjz79n4ia7Nn+IJZdM8XK6vbW9fjJbb3MihP+ogz5xMsAqHdeQ0Sq1JXVvUvkqapEIOuN1WasHOk4xJz8zObySSOnYcV2HFT28IbucXH1fCXXbITq+WpfichcDiGaklt2NQFm9caq51g6nvsMTlUEUZmAV9bgGZ6PU/2M6spQgWNDOIA24swsy7l+AFb3hKoR7NEB8+mX6pw3FvPdZcgFSzJrmUp/MOf59Uo+VveRA81tU0OuzeQUoKrFtAj6qxX6fBwzexyp9/2VJmBm5onkt9sO0KRI2ilKSkKZ126WeZfvCk05VddQ4K1169btWrduXRR4CTj/f71ozqyo1dnb5e4IYljXem7pm9+8l5IOo9k4ZxIeUZmZXGo+3/TWvfi7jKb835PwK/UDrHN9pzl9JlqvzpnX9vQZUBXNHCv6tGXD3MkEOlzKAwsctkfTk8/2qOShhQYVCUnF5gVsenUy6166ivUzfog49YSs7xUFYSzVRru2XXqiJz3ha9e2IyqyJ+d9Zequa8Hs+v1XaDfu2UOmYLnsm5gtMko7pJ///W+bxGUIzVdA2zrPzIyV4/eWYJv5mAkfOtF6srpxzqS0lfswExXOPuXOq8aOWtuaCn4lllHaAeyKsgbHmMaIpRkZpR3SsvvwIg/h035KqrKMDXNuQWDjV2LYtiSe8hFPhYmnfA2OLbnGUvuplwikPHh/+wr+CNh/fTn78+kzEIqJ/v0TsuRR//4JmK/PzzouUB2om0s+N7x1J8oVw/ebPXt/1MT61iVT/mo/eNUYX7z3KK2HTMkeq0c8xBfvPZrpPzVjtqeoA21HPnJQ2cMPdL4K7C+o2eWQUKUrJK/MHkuTV7ajSq+VF59tI38/E349E/nMa8jVGxt8Ro6ioA3rk12pZncE8wCeqde2MKfPrC8bJ7bMvP4mslF3jdH5spe/8RrDtiVmwoeVDGMmGh5HXI4eV45+lckXL8v6lwuPamRlmVcUQUlJKPMPIJhvHMmmu7gcEZqsxR1oAdT18SsDeh3oyUVFuXd8dSFJ7it7e8DI6VqoecPVLoZW7hrRvjB2RRmasLN2CdPXr8j9nX5f1mtsp7Z9qkxf11ucWfjWsD0qQc9e+KUqy6BZXib5iygIo181HhEOQBjUWzsjLYnQBIR0CnIUK5WyLR0v+AvSTiFUA91fQDArqVTtPT24Al5Hlr3vf1Mhl8x+HTHZHs0OQdgelVhSA9vC52nR4DNLRqpyyqqaQ0b/V3JdT+bLBuXuaLetMbC/dlkVVRmlvYaGxpijQUNjbAZFZXs020KyPSoR3mKgtkzcwfyeBsdSR2bGVJnjc8WySc2Zg35Rf/D5EXl+Un+fAf8tyzrOEOnn0pB8SuHgKQzzvywXpSORe+Uz0a8aj8gPUbKfItLJSBUVmxdgxcqzki8iBBWbF9DqzFv2updBZLBgP+P6Xu07wPmq5l4dKEdbZvclr0e7bfvi64jJtLUKEyd2pECX7DYF09c6TCpROKa63Q09s1zPSDoSads5+8n+nunByAZ8k/t69NYYjU0G9ju+VtPY2r0/akq/1eWj0c/v97waRX7v83wl382ycU3tubscOE1Zcc+1gjlgE0d5eRWOk63wlpSEMGXurKgymV5gimgqp2uhlYhUuxjmLnck4xHUvFIsqbJ7R2XW9+apDXxnLJ71GlXBtJx0llZbpK+b2EmzQGGW8t4sIMDMnjyNUCmOYqDWiR+rQMUqr8q+MSlgr3i5bIzqf8BepVVq7uGOvX5fY+JQtu9ID4y5ZFb3GTQLiHrPXxM2wgFLSipSuZ9ZwFBzyqot1UP6DA/onu8ld42qbUeBA2lXSFdR80qzlPeGxpiaax5JcslrVlscO6fsysROoLpMnFAa/D25aHAsrcl2HYs3/HllFPPPLwKgTxyLqIxmRwsVhDElVOyoPOzyqXkDWbG+OcfqHNS0K/r1ajbOmZxp1/H9J+2nffse1+tyoPNVzb06EBqS9yMpsw3Ja2MdI2rQfQa743D7wlordrOAQFecTLsbemYNPaN8VT2o42s4GNkwoFHf17ocqAw0BnmtS652NyaF7srRrwI0aFU/FDQVGTuUNEZ5dTl0NGVX+a1A8zqvS4Gv/teLRlFRJ47LuCpmsrcX5acnoDdW0Hbw/Vmuha2HTGHHp7M5aeQ0kjJUz6W8zeApxFbOTsefOvX3iXN9pz5xLNbi1ZnX6sRxEAxkjpWLNtB2xCNEP/0/bu0dTyvrpCfs2/pZFIR89dwf47afCluwW6pU2MKNP/wW4Fcldw7Usp7/nQM1/DKCKgKZxIq52Ff4w9GmMbetsRBz/BSNn4aal75HmRj3HGNMY0SzUtwx0MiS3Vv7JIks/U0m87lEPajfk2ssVSeOI6rqqBPHYS1ejXbRiAY/r3nfWrw6rbzvfVx1fzrc8mnZzjcaq3O1q+78dCjad6Dz1b7GHpdDh19rYA7QapW6BvtFA8+o6iCP39f3uLLh0hA11vW6/w41JSUh8vIbztnh4tLUEFI2zRif6uR075F2j48Ci4Br1q1bt3g/p7YCNjdkcd+xo/IgsspbCEXZR1Z5C0VRDlFWeZWCwkB2+1SBQwxHCGJKHpZU0bDwESPleNCJHvKM3PujsVsnDrHFff81bg4NrWhAZiGdoC5mC0xHQVcc/EoC1VapMve/4D9cmdvr8k3veWNu2+HmQNt1MFnlG4u8VreFHTsqUVUFSzNwEGhKdVZ5O4EQtVnlD/aZ5xq/Ldupfb+mKocjc3+eYwxWDY09VnZ/OhLy+U1QVUHQk8Q2kznnp0PBgcxXB7MxvA+L+5GQ2VbsQ14b6xhRl1BIJ2bVmQM0WS/7eUP9oiEO9viGzmtINprCfa3hICyYR11e92pPTov7Iy90P+Avm3zxssN2/OSLl+V0b/8m7zV0zCMvdGfyxcuajKwdChqZvLocYpqsq/y6deu2tm/f/i7gbdJeV88cgNJ+QDSU2TTzXgpyl8pJD6K15c1yf35A32nbJHO0IetYG2ojvVII0m9VoZPOonroS6y5ND4qq9ILtGOqB+tKFNLPe//P/HCV4jsUNOa2NRZsW1JZc49saGr3yLYdhJ2gJld6JR6gbkziwf+ehsbv2vchE2mV8/P6Y3BJOIi110KoscqnbUuMQFGOhduha9/BzFcuh58aJb12DqhPQ/2iIQ72+AbPc2XjO8OVo+cA2a7vcSuJT6sd03dFt/Hs7JFHvG0uLt8WmqziDrBu3bq/A38/2u1wcXFxcXFxcXFxaSw4VvKIxjEXBprTc9bUrPeWnHt31ntLzr37iLUnaacymwg198EtG+fS1GnSiruLi4uLi4uLi4uLSzaK5mHxYz2y3ut1w0dH5LtnDbuRFv58AN455058WjrOPGlbhzUZXV0ayjRfhau4uzRdXMXdxcXFxcXFxcXFxeWA+cHoV8gPtMj5WQt/Pl9Fq2gRCKIIlV4zngBg8bjrMsr0gZR5O9Qk7VSWF0LSTuFRswt4pswEFXvMvU91cWkUuIq7i4uLi4uLi4uLy3eAq0e9jt9bCFISS+7m6VeG1zvmytFzKAykCzfVWMgTtolX1UnaNh5VxTFr82Y4pkTRBR+OnIKiCxxT0iIQpPeL7zL/vL4sHncdccsCshX22UMeY/SbNxzOn5vF3lb4RSP/Uu8YqSgHFWLgKvouR5LvouKuAihK7mSKDb3fWGjs7YPG38ZD2L5WwBbAOlQXbIB9ymxdGuu9b6ztgsbbtsPQrlY0InltrPe9Idz2Hl4aaG8rDr/M7ldem9K9dNt6eDjAtraiEcjr/sgLFtf+rRfnPCZXvPp7o35O3LLxaSpl0TilAR8bb4oCcOLD6UTJii7YeFOUk34dyJznURV6v/guC8f1A2qVfIAW/mIWjfg7Hq3299Qo9mXRPYx660ff+HceCA250x9MJv2fXvD+QSv6lZHDOw03Inl1OcQ02XJw/wP9gHePdiNcvjW0Bj4/zN/hyqzLocKVV5emxuGWWVdeXQ4lrry6NCWOxJrA5RDyXVTcPUBPoIzq4iQuLv8DR2K30pVZl0OFK68uTY3DLbOuvLocSlx5dWlKuBb3JsZ3UXF3cXFxcXFxcXFxcXFxcWkyKEe7AS4uLi4uLi4uLi4uLi4uLg3jKu4uLi4uLi4uLi4uLi4uLo0YV3F3cXFxcXFxcXFxcXFxcWnEuIq7i4uLi4uLi4uLi4uLi0sjxlXcXVxcXFxcXFxcXFxcXFwaMa7i7uLi4uLi4uLi4uLi4uLSiHEVdxcXFxcXFxcXFxcXFxeXRoyruLu4uLi4uLi4uLi4uLi4NGK0o92Ao0H79u0nAD8DDODX69ate3yvz08FngbygHeAH65bt85qRO2bAlwF7K5+6+m9jzkCbQwDi4BR69at+3yvz47q/TvANh71e3io2J+8HKE2ZN3r9u3bDwUe5f/bu/sou6ryjuPfIRCJUJuCskRpAAv8AIEESCJYMQRUVoC1aCvEEtqKL7yDLCS1LIUCguVFSERBobwrFKpgsKwkREBsQ0MQ2oS8AD8tFdry0gZkmUakJjD9Y+8JJ+PMnXtn7j333LnPZ61ZmXten7PzzDl7n73PuTAO+Hvb5+blSs0NSecDM/PH+ba/UKHYvgwcDfQCN9qeU5XYWmU05KqkCcBtwHaAgeNsr5M0HrgdeB+wBphp+6URxjri/C0z3hzHiPO67JgLsQ+43wGWWQ08kyf9t+3DmhVDnXFWug7TL5bK12f6xVP5us1QqnCeLVu95/XRqJHrROh8XdfjLum9wFeADwETgRMl7dlvsduAM2zvBvQAJ1QsvinAn9qelH/KbrR/AHgY2G2QRdpWfn3qiLGtZdgsdeZLq2PYpKwljQNuAo4C9gCmSJqRFy8tN/KF62PAvsAkYH9Jx1YktmnAIcA+wGTgDEkTqxBbq4yiXP0m8E3buwOPA+fl6RcDi23vQarcXzXCWJuVv6XEm2NuVl6XFnM/g+23aArwd4VrR9mN9krXYYo6oT5T1Al1m6FU4TxbtgbP66PKMK4TocN1XcMd+AjwI9u/sP0r4C5S7wAAknYExtlemifdAhxTlfiyycBfSVoh6WpJW5YYH6SL1WnAC/1nVKD8+gwaY9buMmyWevKl1fqX9VTgZ7Z/nnsjbgOOaUNuvAicbfs3ttcDT5Eu7G2PzfY/AtNzDNuRRj+Nr0JsLdTxuSppC+DDpNg3Ts+/H0HqDQa4A5iRlx+uEedvyfE2Ja/LjrnPEPstmgLsJelxST+StHcz9t+AqtdhijqhPlPUCXWboVThPFu2us7r7Qquxeq+TrQzyNA83dhwfw8p0fu8COzQwPxWq7l/SVsDy4DZwH6kStFAvQItY/uzthcPMrvd5QfUjrEKZdhEbS/vAcp6sJhKjdX26r5KlqRdgU8Ab1YhthzfekkXAk8CD9aIoe3/x03S9uNoQq6+E1hbGB5bPIaN6+T5a4F3jSDWZuRvafEW4h5pXpcec1Zrv0WvA9+2PRm4ArhH0tgmxVCPqtdhiipfnynqhLpNHTolzqZp4Lw+6jR4nQijQDc+494zwLQ3G5jfajX3n5+3O7zvs6QrSUNivtT60OrS7vIbUgeUYSOqWN6DxdSWWCW9H5hPqhyuBzRADG2Jzfb5ki4D7gV2HSSGKv4fD0cVj6PRXK11DC05vhHmb+nxwojzuuUxSzoGmNtv8k/r2bbtCwq/L5B0CWk46hONxjFMVa/DFHV6faaoSuVaS6fE2UpdVwZ1XifCKNCNPe7PA+8ufN6eTYdFDTW/1WruX9IESZ8uzO8h/ZFWRbvLb0gdUIaNqGJ5DxZT6bFK+kNSr985tm+tSmySds8vOsL2a8D3gelViK2FqngcjebDGuAdksb0m77JtiRtDrwDeGUkwTUhf8uOtxl53fKYbX/P9g7FH+CwGvstHuMZkrYtTCr7+lH1OkxRp9dniqpUrrV0Spyt1FVl0MB1IowC3dhwfwA4VNK7JL0d+DhwX99M288Br+c/BIC/ABZWJT7g18DlknaW1EN6rmdeifHVVIHyq0ely7BBQ+VLOzwKSNIuuRI8C1hYdm5I+n3gHmCW7TurFBvprdjXS3pbHmZ7FHBdRWJrlY7P1fwM4WLScMSN0/PvC/Jn8vzFeflhaUb+lhlvNuK8bkPMQBriX2O/RdNIb0HvexnfGODpZsRQp6rXYYo6uj5TVLFyraWK59myDXiebHNMLdHIdaJdMYbm6rqGu+3nScOwHgKWk94O+xNJCyRNzosdB8yV9BSwFfD1qsRnew1wEmkIokl3qK8sK77BVKX8aql6GQ7HYPnS5pheB44H7iY95/o0b73wqczcmA1sCcyRtFzS8hxX22OzvYDUCFkG/AuwJF902x5bq4yiXD2V9KbmJ4GDSF+7BOnZ3AMkrc7LnDbC8JqVv2XF28y8Li3mfgbcr6STlb7mDuBM4KOSVpGecT/WdmnDUKteh2kk1k64FlexXGup4nm2bEOc10ebRq8TocP19Pb2tjuGEEIIIYQQQgghDKLretxDCCGEEEIIIYROEg33EEIIIYQQQgihwqLhHkIIIYQQQgghVFg03EMIIYQQQgghhAqLhnsIIYQQQgghhFBhm7c7gFAeSb3AKuANoBd4O7AWOMX240OsewvwUWBNnrQZsDVwre3LWxVzCACSDgautr1XjWX+GnjC9g9KCyyEEEYZSb8LzLN9SCvWk3Q8cLTtIweYdwNwp+0H+k2fDNxle6dGYgqji6SdgGeAlXnSGOA14PPA8/3mQfqKwats31RPPSKEqouGe/eZbvvlvg+SZgPfAA6sY925tq8orDsBeErSP9h+uvmhhtCQQ0jfWRpCCGH4fg+YWuJ6G9n+7EjWD13h17Yn9X2QNBO4hdS51H/ee4FVkmp2ToXQKaLh3sUkbQ5MAH6RP28BzAEOJfXKPwqcZft/B9nEDvnfweaH0FS5R+caYBJp1MhC4IvAScBk4KuS3iCNDJlDuhvfC1xi++62BB0qR9JmwFzgAOB3SL0yJwP3ArvZfikvtxS4EHgcuBn4A+AV4CVgle0LauzjeOAzwFbAL21Pl/QZ4FTSiKVXgNNtPy3pQwyQr5LGApcB0/K8ZcDnbK+V9CzpHL0PcAFwru29877HAz8H3kcaWXU16Vy/Bak382+GX3qhDCXl6LuBbwPvzJPm2z4vb2ecpOXA/sAnSefYscA2wKW2v9U/x/M2Nq5n+40ah7i9pPuA9wDPASfYfknSj0m9ondJOgU4K2975eCbCl1uW+DFgWbYfl7Sz4DdgJcHWiaEThLPuHefhyQ9IekF4Kd52qfyv+eSLqIT889mwFcL654labmkZyS9DHwBONL28yXFHsLXSZXSvUkN9YnAbNvXkCquf2l7HqkiO8f2/sCnSb3xIfT5AOlcd6DtPYFbgdnAPODPACTtAWwPLCLl3WrbewDHAB+scz/vBw7OjfZppAbQQbb3BS4Hvp+XGyxfzwE2kBpBE4EXgEsL21+VY/ousHUeTgxwMgp+tgAABMdJREFULKkR9irwHeCmvO2pwEdyD1WotjJy9ATg323vBxwE7Jpvjn6Kt3oux+XlDs95+wlS7vbZmOPF9YZotENqSJ1uex9So/yq4kxJk0g3pD5sewrwmzqOJ3SHcbkuulzSc6TcuWSgBSUdCOxCuskZQseLhnv3mZ4rgEeQemKW2P6fPG8G6Zn19bbfJA2hn1FYd26+kO8DLAXeBP6pvNBDYAapN6bX9v8B17Jpjvb5LnCNpNtJPUZfLDHGUHG2HyHdqDxJ0hXA0aR3dlxPalxDaoTcnM+FhwN/m9d9Ebirzl2tsL02/34EqQK5JPdIXg5sI2kbBs/XI4GjgGV5nT8C9ixsf3GOqRe4ETi+EPsNkrYi9dZflNdfSup5n0SotJJy9D7g45IWkHrUz7H9y+ICtteR8vAISRcBX8px9CnmeCMesP1v+fcbScOciw4Fftg3soB8bCHw1s2hSbZ3BA4G7iSNSik26leRGvTH2f7PNsYbQtNEw71L2V5GGoJ2Q37ZB/x2PmxGGlrZf91fAX9OuqP/+RaGGUJ/9ebodaRe+fuBw4AVuScpBCQdAczPH39AugHUY/thYHNJU4FZwE15mQ2kSmGfoXoT+6wr/D4G+E5fhRPYjzRq5NUa+ToGOLOwzlRSA26g7d8MzMw9leNt/ziv3wN8sLCNA4AYKl9xZeSo7ceAnUmN4p2An0japKde0g7AcmBH4GHSzYSidQxPMb4eYH2/+b1sejwbhrmfMMrZXgIYmMmmjfq9bB9se2GbQwyhaaLh3sVs3wE8AnwtT1oEnCxpi/x83WmkiuRA674KnA2cn1/+EUIZFgGnSeqR9DbgRN7K0Q3kRrykJcC+tm/Jy4wnvTgpBEi9e/fa/hbwGKkne0yedwNptNEK2/+Rp80nPcuLpG2BPyY1LBrxQ+BYSdvnzycDD+ZtDpavi4DTJY3N5+TrGWRIaH5k6VHgunwM5J7QpeQbrPnZ938m9eKHamt5jkq6FDjP9j3AmcBq0hD2DcAYST2km0trgIttLyL1viNpzACbLK43lOn5BbcAp5DeV1J0P/CxfOMA3hpNEsImJO1Gytt57Y4lhFaLhns4HZgh6TDgYtILbZYDT5EaQWcOtqLt20nPFV9ZQpwhAHwO2I70TORK0l32r+R59wJXSPok6f0LX5a0DHgIuND2s+WHGyrqWmCapBWkm5fPADvnxvGtpKHkNxSWPwvYXdJK4G7Sy7Rea2SHudFzGXB/3u8s4E/yMPfB8vUi4FnSS+meJPVAnl1jN9cD++Zj6DMLOCDH/ihwRz53h2orI0e/BkzKQ4ofJ73Q8A7Si77+lVQPeAz4L8A5PyeQGvK7DLC9jevlmwe1rABuyvueQL/Re7ZXkv4uHsxvBN9yiO2F7lEcDr+c9FjIidT3HoQ9JK3r9xOj8ULH6OntbbTTIIQQQugekk4Fltl+JI/0WAycH0MwQ1VEjoYQwugXXwcXQggh1PYk8I08PHgs8D3bCyUtJn1V10AOqvFVmiE0W6VyNP42Qgih+aLHPYQQQgghhBBCqLB4xj2EEEIIIYQQQqiwaLiHEEIIIYQQQggVFg33EEIIIYQQQgihwqLhHkIIIYQQQgghVFg03EMIIYQQQgghhAr7f8xZpGzJMPhhAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 998.6x900 with 30 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = sns.pairplot(\n",
    "    model_data[RoR + model_vars]\n",
    "    .query('auction_mech == \"auction_mech_EnglishForward\"'),\n",
    "    diag_kind='hist', hue='country')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RoR</th>\n",
       "      <th>lots</th>\n",
       "      <th>avg_reserve</th>\n",
       "      <th>avg_start_bid</th>\n",
       "      <th>BPL</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>RoR</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.069050</td>\n",
       "      <td>-0.072248</td>\n",
       "      <td>0.175049</td>\n",
       "      <td>0.210993</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lots</th>\n",
       "      <td>0.069050</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.013865</td>\n",
       "      <td>0.365629</td>\n",
       "      <td>0.012851</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>avg_reserve</th>\n",
       "      <td>-0.072248</td>\n",
       "      <td>-0.013865</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.000236</td>\n",
       "      <td>-0.036440</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>avg_start_bid</th>\n",
       "      <td>0.175049</td>\n",
       "      <td>0.365629</td>\n",
       "      <td>-0.000236</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.497484</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BPL</th>\n",
       "      <td>0.210993</td>\n",
       "      <td>0.012851</td>\n",
       "      <td>-0.036440</td>\n",
       "      <td>-0.497484</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    RoR      lots  avg_reserve  avg_start_bid       BPL\n",
       "RoR            1.000000  0.069050    -0.072248       0.175049  0.210993\n",
       "lots           0.069050  1.000000    -0.013865       0.365629  0.012851\n",
       "avg_reserve   -0.072248 -0.013865     1.000000      -0.000236 -0.036440\n",
       "avg_start_bid  0.175049  0.365629    -0.000236       1.000000 -0.497484\n",
       "BPL            0.210993  0.012851    -0.036440      -0.497484  1.000000"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model_data[RoR + model_vars].corr()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Initial thoughts on the choice of modelling variables:\n",
    "\n",
    "- **avg_start_bid** should be mapped to a categorical variable - 'has_start_bid' - as it is almost binary;\n",
    "- neglecting **avg_start_bid**, there doesn't appear to be any obvious sources of multi-collinearity - via 'post-treatment bias', or otherwise - that could interfere with model interpretation."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Modelling RoR using Bayesian Inference\n",
    "Whereas in the past we have trained multiple ML algorithms when the ultimate aim was prediction, we are currently focused more on statistical learning, model interpretation and modelling real-world economic phenomena - than we are on prediction accuracy. Hence, we will concentrate our efforts on using a single approach - estimating linear regression models using Bayesian inference techniques."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data Preparation Pipeline\n",
    "\n",
    "We define data transformation pipelines to:\n",
    "\n",
    "- select the variables of interest;\n",
    "- center and scale the continuous variables; \n",
    "- handle categorical features in a way that makes sense for our models - e.g. encoding factors (or levels) as opposed to one-hot encoding; and,\n",
    "- use a log-transform on the dependent variable (using a separate pipleine for this variable as in production we would be predicting this variable and would not have access to it).\n",
    "\n",
    "The motivation for centering and scaling the data is threefold:\n",
    "\n",
    "1. the numerical routines required for and posterior distribution sampling (i.e. MCMC), are more stable when all of the input variates have the same scale (i.e. the same units);\n",
    "2. centering the variates so that the mean level corresponds to 0 makes it easy to isolate the impact that just one independent variable (e.g. lots), has on the dependent variable (i.e. RoR), by setting all other variables to 0 (i.e. their mean level); and,\n",
    "3. both centering and scaling the variables by the standard deviation leads to easy interpretation and comparison of parameters estimates - e.g a parameter estimate is 1, then we know that when the independent variable (e.g. lots), is 1 standard deviation above the mean, then it will impact the dependent variable (i.e. RoR), by precisely 1.\n",
    "\n",
    "The motivation for using a log-transform:\n",
    "\n",
    "- RoR is bounded in the range $(0, \\infty]$, by construction;\n",
    "- we intend to use maximum entropy distributions (e.g. Normal) as likelihood functions, but these are defined with support on $[-\\infty, \\infty]$; so,\n",
    "- by defining the following transformation of RoR, $y = f(\\text{RoR}) =  \\ln(\\text{RoR})$, we can use a maximum entropy distributions as likelihood functions, with confidence that they are correctly expressing the uncertainty in the transformed dependent variable, $y$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>lots</th>\n",
       "      <th>avg_reserve</th>\n",
       "      <th>avg_start_bid</th>\n",
       "      <th>BPL</th>\n",
       "      <th>auction_mech</th>\n",
       "      <th>country</th>\n",
       "      <th>start_bids</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.522890</td>\n",
       "      <td>-0.108115</td>\n",
       "      <td>-0.525979</td>\n",
       "      <td>1.253689</td>\n",
       "      <td>1.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-1.061794</td>\n",
       "      <td>-1.281815</td>\n",
       "      <td>-0.525979</td>\n",
       "      <td>0.216361</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.062253</td>\n",
       "      <td>-0.496550</td>\n",
       "      <td>-0.525979</td>\n",
       "      <td>-0.174842</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.985481</td>\n",
       "      <td>-1.225603</td>\n",
       "      <td>2.037988</td>\n",
       "      <td>-0.714990</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-0.933839</td>\n",
       "      <td>-1.441667</td>\n",
       "      <td>-0.525979</td>\n",
       "      <td>-0.281616</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       lots  avg_reserve  avg_start_bid       BPL  auction_mech  country  \\\n",
       "0  1.522890    -0.108115      -0.525979  1.253689           1.0     10.0   \n",
       "1 -1.061794    -1.281815      -0.525979  0.216361           0.0      5.0   \n",
       "2  1.062253    -0.496550      -0.525979 -0.174842           0.0     18.0   \n",
       "3  0.985481    -1.225603       2.037988 -0.714990           0.0     16.0   \n",
       "4 -0.933839    -1.441667      -0.525979 -0.281616           0.0      5.0   \n",
       "\n",
       "   start_bids  \n",
       "0         0.0  \n",
       "1         0.0  \n",
       "2         0.0  \n",
       "3         1.0  \n",
       "4         0.0  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def cat_col_selector(df):\n",
    "    df_cat = df.select_dtypes(include=['object'])\n",
    "    return df_cat.values\n",
    "\n",
    "\n",
    "def num_col_selector(df):\n",
    "    df_num = df.select_dtypes(exclude=['object'])\n",
    "    return df_num.values\n",
    "\n",
    "\n",
    "def cat_col_str2fact(X):\n",
    "    fact_cols = [LabelEncoder().fit_transform(col) for col in X.T]\n",
    "    fact_mat = np.vstack(fact_cols)\n",
    "    return fact_mat.T\n",
    "\n",
    "\n",
    "def cat_col_fact_names(df):\n",
    "    def list_of_fact_names(col):\n",
    "        fact_names = LabelEncoder().fit(col).classes_\n",
    "        return fact_names.tolist()\n",
    "    \n",
    "    df_cat = df.select_dtypes(include=['object'])\n",
    "    X = df_cat.values\n",
    "    fact_name_cols = [(col_name, list_of_fact_names(col))\n",
    "                      for col_name, col in zip(df_cat.columns, X.T)]\n",
    "    \n",
    "    return dict(fact_name_cols)\n",
    "\n",
    "\n",
    "def make_new_vars(df):\n",
    "    start_bid_map = (\n",
    "        lambda x: 'start_bids_true' if x > 0 else 'start_bids_false')\n",
    "    \n",
    "    new_df = df.assign(start_bids=df['avg_start_bid'].apply(start_bid_map))\n",
    "    return new_df\n",
    "\n",
    "\n",
    "# pipline for independent variables\n",
    "feature_data_pipe = Pipeline([\n",
    "    ('make_new_vars', FunctionTransformer(make_new_vars, validate=False)),\n",
    "    ('union', \n",
    "     FeatureUnion([\n",
    "        ('num_vars', \n",
    "         Pipeline([\n",
    "            ('get_num_vars',\n",
    "             FunctionTransformer(num_col_selector, validate=False)),\n",
    "            ('scale_vars', StandardScaler())\n",
    "         ])),\n",
    "        ('cat_vars', \n",
    "         Pipeline([\n",
    "            ('get_cat_vars',\n",
    "             FunctionTransformer(cat_col_selector, validate=False)),\n",
    "            ('factorise',\n",
    "             FunctionTransformer(cat_col_str2fact, validate=False))\n",
    "         ]))\n",
    "     ])\n",
    "    )\n",
    "])\n",
    "\n",
    "# piplines for data labels (i.e. the observed dependent variable)\n",
    "label_data_pipe = Pipeline([\n",
    "    ('log', FunctionTransformer(np.log, np.exp, validate=False))])\n",
    "\n",
    "label_itfm = label_data_pipe.inverse_transform\n",
    "\n",
    "# get variable names\n",
    "num_var_names = (\n",
    "    make_new_vars(model_data[model_vars])\n",
    "    .select_dtypes(exclude=['object'])\n",
    "    .columns\n",
    "    .tolist())\n",
    "\n",
    "cat_var_names = (\n",
    "    make_new_vars(model_data[model_vars])\n",
    "    .select_dtypes(include=['object'])\n",
    "    .columns\n",
    "    .tolist())\n",
    "\n",
    "all_var_names = num_var_names + cat_var_names\n",
    "\n",
    "# get levels for categorical data\n",
    "cat_col_levels = cat_col_fact_names(make_new_vars(model_data[model_vars]))\n",
    "\n",
    "# perform transformations\n",
    "y = (label_data_pipe\n",
    "     .fit_transform(model_data['RoR'])\n",
    "     .values\n",
    "     .reshape(-1, ))\n",
    "\n",
    "X = (feature_data_pipe\n",
    "     .fit_transform(model_data[model_vars]))\n",
    "\n",
    "X_df = pd.DataFrame(X, columns=all_var_names)\n",
    "X_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Partition Data into Test and Train Sets\n",
    "\n",
    "We select 20% of the available observations to hold-back from training our model on, so that their out-of-sample performance can be tested along side other measures of Out-Of-Sample (OOS) predictive accuracy, such as WAIC."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3340 samples in training dataset and 835 samples in test dataset\n"
     ]
    }
   ],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(\n",
    "    X, y, test_size=0.2, random_state=42)\n",
    "\n",
    "print('{} samples in training dataset and {} samples in test dataset'\n",
    "      .format(X_train.shape[0], X_test.shape[0]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Define Experimental Setup\n",
    "\n",
    "In addition to assessing competing models using Bayesian information criteria (e.g. WAIC), we would also like to understand the Root-Mean-Squared-Error (RMSE) of RoR predictions, both in-sample and out-of-sample (due to its ubiquitous use in machine learning model evaluation). The helper function below facilitates this analysis. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "def model_performance(y_, trace_, model_, samples_=500, intvl=0.95,\n",
    "                      y_inv_tfm=None):\n",
    "\n",
    "    # if no inverse has been provided use identity\n",
    "    f = (lambda x: x) if y_inv_tfm is None else y_inv_tfm\n",
    "\n",
    "    # compute two-sided percentiles for range\n",
    "    intvl_lwr = (1 - intvl) / 2\n",
    "    intvl_upr = intvl_lwr + intvl\n",
    "\n",
    "    # generate samples from the posterior predictive distribution\n",
    "    # use the expected value as the final prediction\n",
    "    post_pred_samp = pm.sample_posterior_predictive(\n",
    "        trace_, model=model_, samples=samples_, random_seed=42)\n",
    "    \n",
    "    pred = f(post_pred_samp['obs'].mean(axis=0))\n",
    "\n",
    "    # compute prediction ranges\n",
    "    pred_range_lwr = np.percentile(\n",
    "        f(post_pred_samp['obs']), 100*intvl_lwr, axis=0)\n",
    "    pred_range_upr = np.percentile(\n",
    "        f(post_pred_samp['obs']), 100*intvl_upr, axis=0)\n",
    "\n",
    "    # compute error on model scale\n",
    "    actual = f(y_)\n",
    "    error = pred - actual\n",
    "\n",
    "    # compute deviance using lppd\n",
    "    waic = pm.stats.waic(trace_, model_, progressbar=True)\n",
    "    deviance = waic.WAIC - waic.p_WAIC\n",
    "\n",
    "    # number of observations in prediction range\n",
    "    in_range = ((actual > pred_range_lwr)\n",
    "                & (actual < pred_range_upr)).astype('int')\n",
    "\n",
    "    # assemble results\n",
    "    performance_data = np.concatenate([\n",
    "        pred.reshape((-1, 1)), actual.reshape((-1, 1)), error.reshape((-1, 1)),\n",
    "        pred_range_lwr.reshape((-1, 1)), pred_range_upr.reshape((-1, 1)),\n",
    "        in_range.reshape((-1, 1))],\n",
    "        axis=1)\n",
    "\n",
    "    # print metrics and return\n",
    "    print('RMSE = {}'.format(np.sqrt(np.mean(error ** 2))))\n",
    "    print('Deviance = {}'.format(deviance))\n",
    "    print('% observations in {}% prediction range = {}'\n",
    "          .format(100 * intvl, 100 * np.sum(in_range) / in_range.shape[0]))\n",
    "\n",
    "    df = pd.DataFrame(\n",
    "        performance_data,\n",
    "        columns=['predicted', 'actual', 'error', 'predicted_lwr',\n",
    "                 'predicted_upr', 'in_range'])\n",
    "    \n",
    "    return df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Map Data to Model Variables\n",
    "\n",
    "To make the model specification easier to read and to facilitate prediction with PyMC3, we explicitly map data columns to their own name. We also explicitly define them as variables in Theano, whose values can be changed, for example, when we need to load test data after estimating on training data (see http://docs.pymc.io/notebooks/posterior_predictive.html for more). We provide two helper functions for these purposes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "def load_test_data():\n",
    "    y.set_value(y_test)\n",
    "    lots.set_value(X_test[:, 0])\n",
    "    mean_rsv.set_value(X_test[:, 1])\n",
    "    avg_start_bid.set_value(X_test[:, 2])\n",
    "    BPL.set_value(X_test[:, 3])\n",
    "    auction_mech.set_value(X_test[:, 4].astype('int32'))\n",
    "    country.set_value(X_test[:, 5].astype('int32'))\n",
    "    start_bids.set_value(X_test[:, 6].astype('int32'))\n",
    "    return None\n",
    "\n",
    "\n",
    "def load_train_data():\n",
    "    y.set_value(y_train)\n",
    "    lots.set_value(X_train[:, 0])\n",
    "    mean_rsv.set_value(X_train[:, 1])\n",
    "    avg_start_bid.set_value(X_train[:, 2])\n",
    "    BPL.set_value(X_train[:, 3])\n",
    "    auction_mech.set_value(X_train[:, 4].astype('int32'))\n",
    "    country.set_value(X_train[:, 5].astype('int32'))\n",
    "    start_bids.set_value(X_train[:, 6].astype('int32'))\n",
    "    return None\n",
    "\n",
    "\n",
    "# initial setup\n",
    "y = shared(y_train)\n",
    "lots = shared(X_train[:, 0])\n",
    "mean_rsv = shared(X_train[:, 1])\n",
    "avg_start_bid = shared(X_train[:, 2])\n",
    "BPL = shared(X_train[:, 3])\n",
    "auction_mech = shared(X_train[:, 4].astype('int32'))\n",
    "country = shared(X_train[:, 5].astype('int32'))\n",
    "start_bids = shared(X_train[:, 6].astype('int32'))\n",
    "\n",
    "# derived constants used in prior definition\n",
    "n_country = len(set(X_df['country'].tolist()))\n",
    "n_mech = len(set(X_df['auction_mech'].tolist()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Handling MCMC Simulation and Persisting Computed Chains to Disk\n",
    "\n",
    "If we expend compute-time on running MCMC simulations to evaluate our models, we do not want this to be wasted if we want to re-run a notebook with the models as-is (e.g if we add a new model and want to compare WAIC against previous models). To facilitate this efficiency we define a function for persisting the chains to disk and only re-computing them if the number of 'draws' or 'tune' steps has changed (or we have explicitly asked it to)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "def run_or_load_mcmc(model_, draws_=1000, tune_=500, parallel_chains=2,\n",
    "                     path='models/', force_rerun=False):\n",
    "\n",
    "    model_str = [k for k, v in globals().items() if v is model_][0]\n",
    "\n",
    "    path_to_filname = (\n",
    "        path + model_str + '_tune' + str(tune_) + \"draw\" + str(draws_)\n",
    "        + 'chains' + str(parallel_chains) + '.pkl')\n",
    "\n",
    "    with model_:\n",
    "        try:\n",
    "            if force_rerun:\n",
    "                raise Exception('forcing MCMC re-run')\n",
    "            print('loading traces from: ' + path_to_filname)\n",
    "            trace_ = joblib.load(path_to_filname)\n",
    "        except:\n",
    "            print('computing traces...')\n",
    "            trace_ = pm.sample(draws=draws_, tune=tune_, njobs=parallel_chains)\n",
    "            joblib.dump(trace_, path_to_filname, compress=9)\n",
    "            print('saving traces to: ' + path_to_filname)\n",
    "\n",
    "    return trace_"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Model Specification #1 - Weakly Regularising Priors and Normal Likelihood\n",
    "\n",
    "We start by defining a simple and pragmatic linear model and then estimate using MCMC methods. We have chosen the mean and standard deviation (StdDev) of the priors such that there is a very low probability that a 1 StdDev change in an independent variable impacts the dependent variable, $\\ln(\\text{RoR})$, by 1 (or RoR by, $e^1 = 2.72$).  \n",
    "\n",
    "We have chosen Normal priors on the parameter estimates to reflect maximal uncertainty (i.e. entropy) under the constraint of having a fixed mean and variance, while of the prior on sigma we have deliberately chosen a non-flat but weakly regularising prior for the benefit of efficient MCMC estimation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "load_train_data()\n",
    "\n",
    "with pm.Model() as ror_basic:\n",
    "\n",
    "    # priors for unknown model parameters\n",
    "    alpha_country = pm.Normal('alpha_country', mu=0, sd=0.25, shape=n_country)\n",
    "    alpha_mech = pm.Normal('alpha_mech', mu=0, sd=0.25, shape=n_mech)\n",
    "    alpha_start_bids = pm.Normal('alpha_start_bids', mu=0, sd=0.25, shape=2)\n",
    "\n",
    "    beta_lots = pm.Normal('beta_lots', mu=0, sd=0.25, shape=1)\n",
    "    beta_mean_rsv = pm.Normal('beta_mean_res', mu=0, sd=0.25, shape=1)\n",
    "    beta_BPL = pm.Normal('beta_BPL', mu=0, sd=0.25, shape=1)\n",
    "\n",
    "    sigma = pm.HalfCauchy('sigma', beta=2)\n",
    "\n",
    "    # expected value\n",
    "    mu = (alpha_country[country] + alpha_mech[auction_mech]\n",
    "          + alpha_start_bids[start_bids]\n",
    "          + beta_lots[0] * lots + beta_mean_rsv[0] * mean_rsv\n",
    "          + beta_BPL[0] * BPL)\n",
    "\n",
    "    # likelihood (sampling distribution) of observations\n",
    "    pm.Normal('obs', mu=mu, sd=sigma, observed=y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Markov Chain Monte Carlo Model Estimation\n",
    "\n",
    "We use Markov Chain Monte Carl (MCMC) techniques to randomly draw samples from the posterior distribution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loading traces from: models/ror_basic_tune2500draw10000chains2.pkl\n"
     ]
    }
   ],
   "source": [
    "ror_basic_trace = run_or_load_mcmc(ror_basic, draws_=10000, tune_=2500)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We use a forest plot to visualise credible intervals and MCMC diagnostics for the model. Given the number of variables in the model, we have opted against using tables of summary data and trace plots."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 720x957.6 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = az.plot_forest(ror_basic_trace, r_hat=True, eff_n=True, combined=True,\n",
    "                   rope=(0, 0))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Values of the Gelman-Rubin statistic (r_hat) are close to 1 and the the effective number of draws for each marginal parameter distribution (eff_n) are acceptible for this demonstration. Thus, we have confidence that the MCMC algorithm has adequately inferred (or explored) the posterior distribution for our chosen probabilistic program."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### In-Sample Prediction\n",
    "\n",
    "We simulate predictions of alpha from the posterior distribution, conditional on observations of the input variables (as held within ror_model_basic). We do this for predictions both on 'model' and 'inverse transformed' values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 10000/10000 [01:48<00:00, 91.77it/s]\n",
      "20000it [00:03, 6627.59it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE = 0.13149981480019418\n",
      "Deviance = -4040.616579630759\n",
      "% observations in 95.0% prediction range = 95.62874251497006\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ror_basic_insamp = model_performance(\n",
    "    y_train, ror_basic_trace, ror_basic, samples_=10000)\n",
    "\n",
    "_ = sns.scatterplot(x='predicted', y='actual', alpha=0.25,\n",
    "                    data=ror_basic_insamp)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As above, but applying the inverse transform to the model's prediction to get to the 'natural' scale of the data labels (or dependent variable observations)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 10000/10000 [01:46<00:00, 103.39it/s]\n",
      "20000it [00:02, 6679.62it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE = 0.11590071831249613\n",
      "Deviance = -4040.616579630759\n",
      "% observations in 95.0% prediction range = 95.62874251497006\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ror_basic_insamp_tfm = model_performance(\n",
    "    y_train, ror_basic_trace, ror_basic, samples_=10000,\n",
    "    y_inv_tfm=label_itfm)\n",
    "\n",
    "_ = sns.scatterplot(x='predicted', y='actual', alpha=0.25,\n",
    "                    data=ror_basic_insamp_tfm)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The model shows some great performance, but with some terrible estimates as well. We now take a look at the residuals on the 'model' scale, as a check to ensure that our choice of likelihood function was adequate and that there is no obvious multi-modality that may be due to a lack of informative independent variables to condition on."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = sns.distplot(ror_basic_insamp.error)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Looks like a nice Student-T distribution would better approximate the 'fat tails' we can see here."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Out-of-Sample Prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 10000/10000 [01:53<00:00, 88.47it/s]\n",
      "20000it [00:02, 7541.85it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE = 0.11783936918330803\n",
      "Deviance = -676.0851303933935\n",
      "% observations in 95.0% prediction range = 95.80838323353294\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "load_test_data()\n",
    "\n",
    "ror_basic_outsamp = model_performance(\n",
    "    y_test, ror_basic_trace, ror_basic, samples_=10000,\n",
    "    y_inv_tfm=label_itfm)\n",
    "\n",
    "_ = sns.scatterplot(x='predicted', y='actual', alpha=0.25,\n",
    "                    data=ror_basic_outsamp)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Model Specification #2 - Weakly Regularising Priors and Robust Estimation\n",
    "\n",
    "We adapt our basic model to use a Student-T likelihood for robustness (and 'fat tails'), with the same weakly regularising priors as for model #1. We have chosen a parametrisation for the degrees of freedom, $\\nu$, that allows us to explore all possible values using only a small uniform interval. This will improve the performance of the Hamiltonian Monte Carlo (HMC) algorithm used to generate the Markov chains, by defending against the vanishing gradients along this dimension of the posterior distribution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "load_train_data()\n",
    "\n",
    "with pm.Model() as ror_robust:\n",
    "\n",
    "    # priors for unknown model parameters\n",
    "    alpha_country = pm.Normal('alpha_country', mu=0, sd=0.25, shape=n_country)\n",
    "    alpha_mech = pm.Normal('alpha_mech', mu=0, sd=0.25, shape=n_mech)\n",
    "    alpha_start_bids = pm.Normal('alpha_start_bids', mu=0, sd=0.25, shape=2)\n",
    "\n",
    "    beta_lots = pm.Normal('beta_lots', mu=0, sd=0.25, shape=1)\n",
    "    beta_mean_rsv = pm.Normal('beta_mean_res', mu=0, sd=0.25, shape=1)\n",
    "    beta_BPL = pm.Normal('beta_BPL', mu=0, sd=0.25, shape=1)\n",
    "\n",
    "    tau = pm.Uniform('tau', lower=0, upper=1)\n",
    "    sigma = pm.HalfCauchy('sigma', beta=2)\n",
    "\n",
    "    # expected value\n",
    "    mu = (alpha_country[country] + alpha_mech[auction_mech]\n",
    "          + alpha_start_bids[start_bids] + beta_lots[0] * lots\n",
    "          + beta_mean_rsv[0] * mean_rsv + beta_BPL[0] * BPL)\n",
    "\n",
    "    # likelihood (sampling distribution) of observations\n",
    "    pm.StudentT('obs', mu=mu, sd=sigma, nu=1/tau, observed=y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Markov Chain Monte Carlo Model Estimation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loading traces from: models/ror_robust_tune2500draw10000chains2.pkl\n"
     ]
    }
   ],
   "source": [
    "ror_robust_trace = run_or_load_mcmc(ror_robust, draws_=10000, tune_=2500)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Forest plot, as above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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hdq+UX5L8jWMtv+S4AvhZRPwauA+4qcPm11HMcv+kfP6BzPTGcH3AqIahjGoYSm6tdyWSpJ4ya9YpfS689sWatPcGtbe317sGdVNr6zOerB524yO3MHvym+pdhqQe0Ng4sjvtgHvEz+f+z+tDXdmTa6M37oO9UxHxUYpWk47WZeasXqzjGorb8HX07czszt1OJEmSpPoH7Mz8HPC5PlDHGbteS5IkSdq5PbmLiCRJkqQuGLAlSZKkChmwJUmSpAoZsCVJkqQKGbAlSZKkChmwJUmSpAoZsCVJkqQKGbAlSZKkChmwJUmSpAoZsCVJkqQKGbAlSZKkChmwJUmSpAoZsCVJkqQKGbAlSZKkChmwJUmSpAoZsCVJkqQKGbAlSZKkChmwJUmSpAoZsCVJkqQKGbAlSZKkChmwJUmSpAoZsCVJkqQKGbAlSZKkChmwJUmSpAoZsCVJkqQKGbAlSZKkChmwJUmSpAoZsCVJkqQKGbAlSZKkChmwJUmSpAr1mYAdEYdHxKpdrLMgIhb0SkG7KSJOiojl3VjvjRHxk4j4eUR8qhdKkyRJUi/qMwF7XxARw4F/Bv4A+B3g2Ig4ub5VaVc2tm1l5dqNbGzbWu9SJKkyLS1LmT3nZJqapjF7zsm0tCytd0n7JM/DwDSkt3cYEUOAxcBRwFgggbd3WOcqYDvwCmAUcHFmfr18+biI+D4wAbgyMxdExIHAFcBEYDxwB/CezGzvoobDgeuBR8p93AMsB84CRgNvy8yHIuJY4HPAAcAG4IOZ+WhETAe+Ui5/EjijHLoxIlqAl5XHdVpm1qay44CfZ+ajZR1XA6cBN3Xz7VMvW/HAYyxZ9jCHjB7O409t5vSZU5lx5KH1LkuS9kpLy1IWLlrEuKa5TJ8xhbbWlSxctAiAWbNOqXN1+w7Pw8DV6wEbeC3wbGbOiIj9gNuBWcC9HdabWK47Frg3IpaVy8eWy0cCqyPis8Bs4P7MPC0iXgI8CBzdyZi1Xgm8D/gx8DCwqqzpb4FzIuI84HJgTmb+IiLeDFwGvBG4BjgvM5dGxLnAnwE3AocBpwCrgR+U695Ys8/xwPqa5+vL46ybS6/5UT13X4kNGzfzxNNVzS4P4Vvc/sKz/Yfsx4VnHcuEMSNYu2ETF131Qy674cGK9vWbDj5wKGNGDe+x8aty3hlH17sESXuheXEz45rmMnJsABR/Ns2leXGzwa4XeR4Grl5vEcnMO4AvRcQ84AvAy4GGTla9MjOfy8w1wF3A68rlN2Xm1szcQDGrfFBmXgssi4g/B74IHNzFmLUey8z7MnM7sAa4rVy+mmIWeyrFTPS3I+J+4FJgckSMAcZl5tLyeBZn5l+W2/44Mx8tx3wIGNNhn4M6qWP7LupUHR104FAmjBkBwIQxIzho5NA6VyRJe2/dmtU0NE550bKGximsW7O6ThXtmzwPA1c9WkTeClxEEa6vpAihnQXPbTWP96t5Xru8HRgUER8B3gl8FbiVov2kszFrPbuT/QEMBh7JzOll3YMpZs+f63A8wyhmpjutrcOYa4Ha/oJxwLpd1NmjBsJM5PV3PsK371rVI2M/+fRW1m7Y9MIM9pPP9Gwf9u++YhynnjC5R/chSeMnTqKtdeULM6cAba0rGT9xUh2r2vd4HgauerSIvBH4ZmZeGRHjgddThOKO3hUR11G0XRwPfACY3sWYM4GvZOaSiDiyXG/wXtb538BBEXFCZt4JvB84IzNPioj/jYiZmbkMeDdwIkU7ya7cDURETAEeBU6n+NKj9sKpJ0yuLJTe+MgtzJ78pheer3jgMS65+t4XerDPOvkIe7Al9Xvzzp1X9Po2zaWhsej9XX/ftZw/f369S9uneB4GrnoE7MuAJRFxGrCVolf5pZ2sdwDFlw+HAudk5hMR0clqAHweWBwRHweeAb7fxZjdlplbyxq/UM5SPw28t3z5zHJ/n6FoU3k30GVxNWNuiYizgG8Bw4AW4Lq9qVM9a8aRhzJt0mhaN26hcdQwRjXYIiKp/9vR39u8uJmVy1czfuIkzp8/377fXuZ5GLgGtbd3eqONuirvIrI8M6+qcyl9SmvrM33vZA0wHWewJQ0cjY0jd9U6uMf8fO7/vD7UlT25Nuoxg90rIuJlFDPFnTk7M+/pzXokSZK0b+iTATszz6pgjP+h655tSZIkqUf4LzlKkiRJFTJgS5IkSRUyYEuSJEkVMmBLkiRJFTJgS5IkSRUyYEuSJEkVMmBLkiRJFTJgS5IkSRUyYEuSJEkVMmBLkiRJFTJgS5IkSRUyYEuSJEkVMmBLkiRJFTJgS5IkSRXqMwE7Ig6PiFW7WGdBRCzolYJ2U0ScFBHLu7nu/hFxW0Sc1LNVSZIkqbf1mYC9r4iIAJYDr61zKaqxsW0rK9duZMvmelciSb2jpWUps+ecTFPTNGbPOZmWlqX1Lmmf5HkYmIb09g4jYgiwGDgKGAsk8PYO61wFbAdeAYwCLs7Mr5cvHxcR3wcmAFdm5oKIOBC4ApgIjAfuAN6Tme1d1HA4cD3wSLmPeyhC71nAaOBtmflQRBwLfA44ANgAfDAzH42I6cBXyuVPAmeUQzdGRAvwsvK4TsvMrR12/wHgM8Cfd+8dU09b8cBjLFn2MIeMHs76J1/CeB5jxpGH1rssSeoxLS1LWbhoEeOa5jJ9xhTaWleycNEiAGbNOqXO1e07PA8DV68HbIqZ22czc0ZE7AfcDswC7u2w3sRy3bHAvRGxrFw+tlw+ElgdEZ8FZgP3Z+ZpEfES4EHg6E7GrPVK4H3Aj4GHgVVlTX8LnBMR5wGXA3My8xcR8WbgMuCNwDXAeZm5NCLOBf4MuBE4DDgFWA38oFz3xtqdZuZ8gIjo1YB96TU/6s3dVW7Dxs088XTH31Wqsf+Q/bjwrGOZMGYEazds4qKrfshlNzzYI/s6+MChjBk1vEfG7gnnnXF0vUuQ1AOaFzczrmkuI8cGQPFn01yaFzcb7HqR52Hg6vUWkcy8A/hSRMwDvgC8HGjoZNUrM/O5zFwD3AW8rlx+U2ZuzcwNFLPKB2XmtcCyMrR+ETi4izFrPZaZ92XmdmANcFu5fDXFLPZUipnob0fE/cClwOSIGAOMy8yl5fEszsy/LLf9cWY+Wo75EDBmd94b1cdBBw5lwpgRAEwYM4KDRg6tc0WS1LPWrVlNQ+OUFy1raJzCujWr61TRvsnzMHDVo0XkrcBFFOH6SooQOqiTVbfVPN6v5nnt8nZgUER8BHgn8FXgVor2k87GrPXsTvYHMBh4JDOnl3UPppg9f67D8QyjaEvptLZd1NBr+vtM5PV3PsK371rVI2M/+fRW1m7Y9MIM9pPP9MxMOcDvvmIcp54wucfGl6TuGD9xEm2tK1+YOQVoa13J+ImT6ljVvsfzMHDVo0XkjcA3M/PKiBgPvJ4iFHf0roi4jqLt4niK3uXpXYw5E/hKZi6JiCPL9QbvZZ3/DRwUESdk5p3A+4EzMvOkiPjfiJiZmcuAdwMnUrSTqIecesLkHgumKx54jEuuvrfswd7EWScfYQ+2pAFt3rnzil7fprk0NBa9v+vvu5bz58+vd2n7FM/DwFWPgH0ZsCQiTgO2UvQqv7ST9Q6g+PLhUOCczHyiuAFHpz4PLI6IjwPPAN/vYsxuy8ytZY1fKGepnwbeW758Zrm/z1C0qbwb6LI49W0zjjyUaZNG07pxCz/+1d2Ga0kD3o7+3ubFzaxcvprxEydx/vz59v32Ms/DwDWovb3TG23UVXkXkeWZeVWdS+lTWluf6Xsna4C58ZFbmD35TfUuQ1IPaGwc2WNte34+939eH+rKnlwb9ZjB7hUR8TLgW128fHZm3tOb9UiSJGnf0CcDdmaeVcEY/0PXPduSJElSj/BfcpQkSZIqZMCWJEmSKmTAliRJkipkwJYkSZIqZMCWJEmSKmTAliRJkipkwJYkSZIqZMCWJEmSKmTAliRJkipkwJYkSZIqZMCWJEmSKmTAliRJkipkwJYkSZIqZMCWJEmSKmTAliRJkipkwJYkSZIqZMCWJEmSKmTAliRJkipkwJYkSZIqZMCWJEmSKmTAliRJkipkwJYkSZIqZMCWJEmSKmTAliRJkipkwJYkSZIqZMCWJEmSKmTAliRJkipkwJYkSZIqZMCWJEmSKmTAliRJkipkwJYkSZIqZMCWJEmSKtSvAnZEnBQRy3dzm09GxAl7uL8FEbGgyvEj4mMR8d8R8XBEvH1P6lJ1NrZtZeXajWxs21rvUiRJXWhpWcrsOSfT1DSN2XNOpqVlab1LqsxAPrZ92ZB6F9ALTgS+2xfGj4hjgTOB6cCBwIqIWJ6ZT/ZgferCigceY8myhzlk9HAef2ozp8+cCsPrXZUkqVZLy1IWLlrEuKa5TJ8xhbbWlSxctAiAWbNOqXN1e2cgH9u+rj8G7DERcTMwAbgbmJeZWyPiLcBFwP7Ao8AfA7OBVwOXR8TbgIOATwMHAKOB+Zn5r93ZaUScAnyKYtb/EeCDwJs7jD8TeC+wHfivzPxgh2FmAf+WmVuALeVs/CnA1/bkjdCe29i2lSXLHuYTZx7DhDEjWLthE5dcfS8nzax3ZZKkWs2LmxnXNJeRYwOg+LNpLs2Lm/t9CB3Ix7av61ctIqWXAh8BXgmMBD4UEY3AJcCbM7MJ+A5waWZ+DbgHODszf1pud3ZmHg18ALiwOzuMiEOArwCnZuYrgbuAf6odH3gI+CuKwH0MsD0iJnQYajywvub5emDibh6/KtC6cQuHjB7OhDEjAJgwZgSHjB7Opk11LkyS9CLr1qymoXHKi5Y1NE5h3ZrVdaqoOgP52PZ1/TFg35GZP8/MduAa4CTgeOAw4LsRcT/wYeDlnWx7JnBURFwAfAxo6OY+j6OYkV5VPv8q8Pu1K2TmNuD7wA+BvwWaM3Nth3EGdTL29m7WoAo1jhrG409tZu2GIlGv3bCJx5/azIgRdS5MkvQi4ydOoq115YuWtbWuZPzESXWqqDoD+dj2df0xYG+reTwIeA4YDHwvM6dn5nTgWOCdnWx7J0VYvpeiVaSzwNuZju/TIDpvrzkVOLd8/eaIOLHD62uBQ2uejwPWdbMGVWhUw1BOnzmVS66+l4v/5YdccvW9nD5zKsPswZakPmXeufNYf9+1PPPLpH378zzzy2T9fdcy79x59S5trw3kY9vX9cce7NdFxGHAGop+55sperEvj4ipmfkwcAFFj/ZZFIF8SEQcBEwFTsjMLeXdQQZ3c593A1+JiMPLWexz+L8vNu4Yv5EiwL86M1dExESKNpb/rBnnpnKcfwBGUMyCd6tNRdWbceShTJs0mtaNW2gcNYxRDUO58ZGf1LssSVKNHb3IzYubWbl8NeMnTuL8+fMHRI/yQD62fV1/DNgPAP9MMft7O3BFZj4fEe8HvhkRgynC95nl+jcDXwbeA1wOPBARTwMrgAMiYkRm7rTzNjN/GRHnAP8eES8BVlP0cHcc/yvADyPi18AvgKs6jPNfEXE1RRvJEOCCTtpI1ItGNQxlVMPQepchSdqJWbNOGbChcyAf275sUHt7e71rUDe1tj7jyephNz5yC7Mnv6neZUjqAY2NI7vbFrjb/Hzu/7w+1JU9uTb64wx2pSLioxStJh2ty8xZvV2PJEmS+rd9PmBn5ueAz9W7DkmSJA0M/fEuIpIkSVKfZcCWJEmSKmTAliRJkipkwJYkSZIqZMCWJEmSKmTAliRJkipkwJYkSZIqZMCWJEmSKmTAliRJkipkwJYkSZIqZMCWJEmSKmTAliRJkipkwJYkSZIqZMCWJEmSKmTAliRJkipkwJYkSZIqZMCWJEmSKmTAliRJkipkwJYkSZIqZMCWJEmSKmTAliRJkipkwJYkSZIqZMCWJEmSKmTAliRJkipkwJYkSZIqZMCWJEmSKmTAliRJkipkwJYkSZIqZMCWJEmSKmTAliRJkiq0RwE7Ig6PiFW7WGdBRCzYk/G7WcM5ETG36m26qjsiXh0Rl3eyfJfvRYf1T4+IByNiZUTM6+52kiRJ6h/68wz2a4GhvbANAJl5T2aevSfb7hARE4BPA68DXgWcExHT9mZM7b2NbVtZuXYjG9u21rsUSepVLS1LmT3nZJqapjF7zsm0tCytd0n7HM/BwDRLVLQWAAAgAElEQVRkZy9GxBBgMXAUMBZI4O0d1rkK2A68AhgFXJyZXy9fPi4ivg9MAK7MzAURcSBwBTARGA/cAbwnM9u7qOFA4Frg0HLRJ4FfA28Ffi8i1gNrgS8CDcAhwGcz8x/LmejXAIcBX67dJjO/s5NDPy4i7i7H+2pmfiEiTgIWZOZJEdFUHgPAj2tqPR2YDzwPPAqcmZlbasZ9I3B7Zj5Zrn8d8E7gop3Uoh604oHHWLLsYQ4ZPZzHn9rMtFcNgsn1rkqSel5Ly1IWLlrEuKa5TJ8xhbbWlSxctAiAWbNOqXN1+wbPwcC104BNMeP7bGbOiIj9gNuBWcC9HdabWK47Frg3IpaVy8eWy0cCqyPis8Bs4P7MPC0iXgI8CBzdyZg7vA1YlZmzI+J3gPdn5l9GxLeB5Zn5nYj4PPCpzLwtIiZThN5/LLcflpnTACLi6B3b7OK4x1HMMg8uj+c/O7z+NeCjmXlrRFwAvKFc/ingNZn5eER8CjgCuL9mu/HA+prn64HjdlFLpS695ke9ubu9tmHjZp54uudmlvcfsh8XnnUsE8aMYO2GTVx01Q95/92398i+Dj5wKGNGDe+RsXvSeWccXe8SJPWA5sXNjGuay8ixAVD82TSX5sXNhrte4jkYuHbaIpKZdwBfKnuFvwC8nGJWt6MrM/O5zFwD3EURTgFuysytmbkB2AAclJnXAssi4s8pZp0P7mLMHb4PnBoR15fjXtzJOh8DhkXEX1G0YNSOd/fOjrEL38jMTZn5NHADcOKOFyJiDDA+M28tF11Vs90NwF0R8RlgaWbWhmuAQZ3sa/se1KeKHHTgUCaMGQHAhDEjOGjkHnUQSVK/s27Nahoap7xoWUPjFNatWV2nivY9noOBa1ctIm+laF/4AnAlMIbOQ+K2msf71TyvXd4ODIqIj1C0RXwVuJWi/aSzMQHIzJ9HxBHAW4A5wMfKmexa3wSeogi43wD+qOa1zTs5xK7U1j0IeK7jcXS2bmb+WURcQTFLf3VELMjMq2vWXQucUPN8HLBuD+rbY/1tNvL6Ox/h23et6rHxn3x6K2s3bHphBvvJZ3putvx3XzGOU0+w/0RS3zB+4iTaWle+MHsK0Na6kvETJ9Wxqn2L52Dg2lWLyBuBb2bmlRExHng9RSju6F1lP/FhwPHAB4DpXYw5E/hKZi6JiCPL9QZ3VUBEfBiYnJl/ERE3Ab+g6PXeVlP/TOCIzFwXEWeV23U2Zu02O/POiPgn4ACKUD+Hot2FzHwiIlZHxOzMvBE4vdzfEOAh4MTM/LuI2B9oAmoD9q3AgohoBDYB7wDO6UY9+6xTT5jco6F0xQOPccnV977Qgz39mOc49w0ze2x/ktRXzDt3XtHv2zSXhsai/3f9fddy/vz59S5tn+E5GLh2FTYvA5ZExGnAVuAHwEs7We8A4B6KO3ScU4bQrsb8PLA4Ij4OPEPRAtLZmDt8Dbg2In5KMZO8IDN/FRG3Agsj4lfAAuB75eMEVnUx5gvbZOZ1O9nnaopWl+HAwsx8KCLG1rx+JnBl2We9AiAzt0XEhcCtEfFr4FfAe2sHzcy1EfHXwHeBlwCXZ+Z/7aQO9bAZRx7KtEmjad24hcZRw/je4x3b7SVpYNrR49u8uJmVy1czfuIkzp8/397fXuQ5GLgGtbd3evOObivvIrI8M6+qoiB1rbX1mb07WdqlGx+5hdmT31TvMiT1gMbGkV22I+4tP5/7P68PdWVPro3utEv0uIh4GfCtLl4+OzPvqXh/H6XD7HJpXWbOqnJfkiRJ2rfs9Qy2eo+/Afc8Z7ClgcsZSu2M14e6sifXRn/+lxwlSZKkPseALUmSJFXIgC1JkiRVyIAtSZIkVciALUmSJFXIgC1JkiRVyIAtSZIkVciALUmSJFXIgC1JkiRVyIAtSZIkVciALUmSJFXIgC1JkiRVyIAtSZIkVciALUmSJFVojwJ2RBweEat2sc6CiFiwJ+N3s4ZzImJu1dt0VXdEvDoiLu9k+S7fi062OTAifhYRh+/OdpIkSer7+vMM9muBob2wDQCZeU9mnr0n29aKiOOB7wFT93Ys9Z6NbVtZuXYjG9u21rsUSapMS8tSZs85maamacyeczItLUvrXdI+x3MwMA3Z2YsRMQRYDBwFjAUSeHuHda4CtgOvAEYBF2fm18uXj4uI7wMTgCszc0FEHAhcAUwExgN3AO/JzPYuajgQuBY4tFz0SeDXwFuB34uI9cBa4ItAA3AI8NnM/MdyJvo1wGHAl2u3yczv7OTQj4uIu8vxvpqZX4iIk4AFmXlSRDSVxwDw45paTwfmA88DjwJnZuaWDmP/MTAP+DrqF1Y88BhLlj3MIaOH8/hTmzl95lRmHHnorjeUpD6spWUpCxctYlzTXKbPmEJb60oWLloEwKxZp9S5un2D52Dg2mnAppjxfTYzZ0TEfsDtwCzg3g7rTSzXHQvcGxHLyuVjy+UjgdUR8VlgNnB/Zp4WES8BHgSO7mTMHd4GrMrM2RHxO8D7M/MvI+LbwPLM/E5EfB74VGbeFhGTKULvP5bbD8vMaQARcfSObXZx3OOA1wGDy+P5zw6vfw34aGbeGhEXAG8ol38KeE1mPh4RnwKOAO6v3XDHLHhE7KKE3nfpNT+qdwl7bMPGzTzxdBWzy0P4Fre/aMn+Q/bjwrOOZcKYEazdsImLrvohl93wYAX76tzBBw5lzKjhPTZ+lc474+h6lyBpDzUvbmZc01xGji1+Ho0cG9A0l+bFzYa7XuI5GLh22iKSmXcAX4qIecAXgJdTzOp2dGVmPpeZa4C7KMIpwE2ZuTUzNwAbgIMy81pgWUT8OcWs88FdjLnD94FTI+L6ctyLO1nnY8CwiPgr4NMdxrt7Z8fYhW9k5qbMfBq4AThxxwsRMQYYn5m3louuqtnuBuCuiPgMsDQzXxSu1T8ddOBQJowZAcCEMSM4aOQedRlJUp+ybs1qGhqnvGhZQ+MU1q1ZXaeK9j2eg4FrVy0ibwUuogjXVwJjgEGdrLqt5vF+Nc9rl7cDgyLiI8A7ga8Ct1K0n3Q2JgCZ+fOIOAJ4CzAH+Fg5k13rm8BTFAH3G8Af1by2eSeH2JXaugcBz3U8js7Wzcw/i4grKGbpr46IBZl59R7svy7682zk9Xc+wrfvWtUjYz/59FbWbtj0wgz2k8/0bB/2775iHKeeMLlH9yFJ4ydOoq115QuzpwBtrSsZP3FSHavat3gOBq5dtYi8EfhmZl4ZEeOB11OE4o7eFRHXUfQ6Hw98AJjexZgzga9k5pKIOLJcb3BXBUTEh4HJmfkXEXET8AuKXu9tNfXPBI7IzHURcVa5XWdj1m6zM++MiH8CDqAI9XMo2l3IzCciYnVEzM7MG4HTy/0NAR4CTszMv4uI/YEmoN8E7P7s1BMmVxJKb3zkFmZPftOLlq144DEuufreF3qwzzr5CHuwJfV7886dV/T7Ns2lobHo/11/37WcP39+vUvbZ3gOBq5dhc3LgCURcRqwFfgB8NJO1jsAuIfiDh3nlCG0qzE/DyyOiI8Dz1C0gHQ25g5fA66NiJ9SzCQvyMxfRcStwMKI+BWwAPhe+TiBVV2M+cI2mXndTva5mqLVZTiwMDMfioixNa+fCVxZ9lmvAMjMbRFxIXBrRPwa+BXw3p3sQ/3EjCMPZdqk0bRu3ELjqGGMarBFRFL/t6PHt3lxMyuXr2b8xEmcP3++vb+9yHMwcA1qb+/05h3dVt5FZHlmXlVFQepaa+sze3eytEudzWBLGhgaG0d22Y64t/x87v+8PtSVPbk2utMu0eMi4mXAt7p4+ezMvKfi/X2UzmeX12XmrCr3JUmSpH3LXs9gq/f4G3DPcwZbGricodTOeH2oK3tybfTnf8lRkiRJ6nMM2JIkSVKFDNiSJElShQzYkiRJUoUM2JIkSVKFDNiSJElShQzYkiRJUoUM2JIkSVKFDNiSJElShQzYkiRJUoUM2JIkSVKFDNiSJElShQzYkiRJUoUM2JIkSVKFDNiSJElShQzYkiRJUoUM2JIkSVKFDNiSJElShQzYkiRJUoUM2JIkSVKFDNiSJElShQzYkiRJUoUM2JIkSVKFDNiSJElShQzYkiRJUoUM2JIkSVKFDNiSJElShQzYkiRJUoUM2JIkSVKFDNiSJElShQzYkiRJUoUM2N0QES0RMb7edUiSJKnvM2B3Q2bOysx19a5Dfc/Gtq2sXLuRjW1b612KJPUbLS1LmT3nZJqapjF7zsm0tCytd0l143sxMA2pdwF9TURMBK4BRgDbgT8FvgGcBKwFvgy8rnzcDlxcbvrXwCDgZcB1wEbg1HLZrMz8ZUR8GHh3zdh/mJkP9cqBqXIrHniMJcse5pDRw3n8qc2cPnMqM448tN5lSVKf1tKylIWLFjGuaS7TZ0yhrXUlCxctAmDWrFPqXF3v8r0YuJzB/k0fAJZm5quB+RRheocPUYTjI4D3AcfWvHZ8uexI4FygtRzjJ8AfRcSBFIH7pMw8Crge+JMePhb1kI1tW1my7GE+ceYxXPDeY/nEmcewZNnDzmRL0i40L25mXNNcRo4NBu03mJFjg3FNc2le3Fzv0nqd78XAZcD+TbcCH4+IJcAE4J9qXpsJXJOZ7Zm5Grit5rWfZeb/ZuavgQ01r60GRmfm08DpFGH774A5QEMPH4t6SOvGLRwyejgTxowAYMKYERwyejitG7fUuTJJ6tvWrVlNQ+OUFy1raJzCujWr61RR/fheDFwG7A4y8y5gGvAd4A+BG2pefp6u37NnOzzfVvskIn4bWAH8FnATcBVF+4j6ocZRw3j8qc2s3bAJgLUbNvH4U5tpHDWszpVJUt82fuIk2lpXvmhZW+tKxk+cVKeK6sf3YuAyYHcQEYuAd2fmvwAfBo6ueXkZxQz0oPKuIidR9GF3x7HAysz8HHA3cDIwuLLC1atGNQzl9JlTueTqe7n4X37IJVffy+kzpzKqYWi9S5OkPm3eufNYf9+1PPPLpH378zzzy2T9fdcy79x59S6t1/leDFx+yfE3fRFYEhFnUcxYnwssKl+7DJgO/BRYT9H+sRk4oBvj3gKcGxEPAlspQvZRlVauXjXjyEOZNmk0rRu30DhqmOFakrphx5f3mhc3s3L5asZPnMT58+fvk1/q870YuAa1t3d3AlYRMRsYlJlLI2IUcB/w6sx8sjf239r6jCerh934yC3MnvymepchqQc0No7ssbY8P5/7P68PdWVPrg1nsHfPg8DXI+JT5fMLeytcS5IkqX8wYO+GzHyUF9+2T5IkSXoRv+QoSZIkVciALUmSJFXIgC1JkiRVyIAtSZIkVciALUmSJFXIgC1JkiRVyIAtSZIkVciALUmSJFXIgC1JkiRVyIAtSZIkVciALUmSJFXIgC1JkiRVyIAtSZIkVciALUmSJFXIgC1JkiRVyIAtSZIkVciALUmSJFXIgC1JkiRVyIAtSZIkVciALUmSJFXIgC1JkiRVyIAtSZIkVciALUmSJFXIgC1JkiRVyIAtSZIkVciALUmSJFXIgC1JkiRVyIAtSZIkVciALUmSJFXIgC1JkiRVyIAtSZIkVciALUmSJFVoSL0L2JWIOAlYkJkn7cY2nwRuzcw792B/C4APAY8Bg8r/zs/MpeXr7cCPgXZgMPAM8KHM/GlELC9rXb6T8X8LuAaYDLQC78rMx3a3TvW+jW1bad24hcZRwxjVMLTe5UiSdkNLy1KaFzezbs1qxk+cxLxz5zFr1in1LqvP1qW90+cD9h46EfjuXmz/5cxcABAR04FbgEN2vJiZ03c8jogPAl8Dmro59qeAOzNzdkS8G/gC8Id7Uat6wYoHHmPJsoc5ZPRwHn9qM6fPnMqMIw+td1mSpG5oaVnKwkWLGNc0l+kzptDWupKFixYB1DXM9tW6tPf6S8AeExE3AxOAu4F5mbk1It4CXATsDzwK/DEwG3g1cHlEvA04CPg0cAAwGpifmf+6G/seBfxyJ6/fAfzDbow3G3h9+fhaoDki9s/M53ZjDPWijW1bWbLsYT5x5jFMGDOCtRs2ccnV9zJt0mhnsiWpH2he3My4prmMHBsAxZ9Nc2le3FzXINtX69Le6y892C8FPgK8EhgJfCgiGoFLgDdnZhPwHeDSzPwacA9wdmb+tNzu7Mw8GvgAcGE39vehiLg/Ih4CbgM+19lKETEIOAO4azeOZTywHiAztwFPA427sb16WevGLRwyejgTxowAYMKYERwyejitG7fUuTJJUnesW7OahsYpL1rW0DiFdWtW16miQl+tS3uvv8xg35GZPweIiGuA9wH/AxwGfDcioOiHfrKTbc8ETomI04DXAA3d2F9ti8jhwN0RkZl5V7ns/nK9ocBDwDm7cSyDOlm2fTe2Vy9rHDWMx5/azNoNm16YwX78qc00jhpW79IkSd0wfuIk2lpXvjBTDNDWupLxEyfVsaq+W5f2Xn8J2NtqHg8CnqMI1N/LzLcCRMQwitntju6k6MdeTjEbvWR3dpyZqyLi+8AMypnq2h7sPbAWOBRYExFDgAOBJ/ZiPPWwUQ1DOX3mVC65+t4X9WDbHiJJ/cO8c+cVvc1Nc2loLHqd1993LefPn29d6hH9JWC/LiIOA9YA7wVupujFvjwipmbmw8AFFD3aZ1EE8iERcRAwFTghM7eUdwgZvDs7Lu/6cTTwxYqOpQV4D7CQ4suNd9p/3ffNOPJQpk0a7V1EJKkf2tHP3Ly4mZXLi7t1nD9/ft37nPtqXdp7/SVgPwD8MzAOuB24IjOfj4j3A9+MiMEU4fvMcv2bgS9TBNnLgQci4mlgBXBARIzIzE072d+HIuJUilvxjQQuy8zbu1nrTRHxfM3zaZn5i5rnFwBXRcQDwK8oerjVD4xqGGqwlqR+atasU/pkcO2rdWnvDGpvb693Deqm1tZnPFk97MZHbmH25DfVuwxJPaCxcWRn34GphJ/P/Z/Xh7qyJ9dGf5nBrlREfJSi1aSjdZk5q7frkSRJ0sCxTwbszPwcXdx6T5IkSdob/eU+2JIkSVK/YMCWJEmSKmTAliRJkipkwJYkSZIqZMCWJEmSKmTAliRJkipkwJYkSZIqZMCWJEmSKmTAliRJkipkwJYkSZIqZMCWJEmSKmTAliRJkipkwJYkSZIqZMCWJEmSKmTAliRJkipkwJYkSZIqZMCWJEmSKmTAliRJkipkwJYkSZIqZMCWJEmSKmTAliRJkipkwJYkSZIqZMCWJEmSKmTAliRJkipkwJYkSZIqZMCWJEmSKmTAliRJkipkwJYkSZIqZMCWJEmSKmTAliRJkirUKwE7Ig6PiFW7WGdBRCzojXr2RkSMiojr92L7wyLijoj474j4j4hoqLI+7drGtq2sXLuRjW1b612KpH1YS8tSZs85maamacyeczItLUvrXZLqwOtgYBpS7wL6odHA9L3Y/kvAlzLzGxFxAXABcF4llWmXVjzwGEuWPcwho4fz+FObOX3mVGYceWi9y5K0j2lpWcrCRYsY1zSX6TOm0Na6koWLFgEwa9Ypda5OvcXrYOAa1N7eXtlgETEEWAwcBYwFEnh7+Xh5Zh4eEVcB24FXAKOAizPz6+Xs9XHAbwETgCszc0FEHAhcAUwExgN3AO/JzC4Lj4iPAh8CngduyMzzImJsOc5hwDbg/My8eceseWYuKLddBZxU/vcW4CBgMnBLZv5JRHy7XH4j8FHgZmADsAUYWh7PLRExCHgYODEz15Vj7w88ARyUmdsi4reB/8zMyd15f1tbn6nuZPVBl17zo70eY8PGzTzxdNcz0/sP2Y8LzzqWCWNGsHbDJi666oc8t237Tsc8+MChjBk1fK9rA/j/7N1/dFf1ve/5ZxCbAoEcMCkmZBUbaV9WxCHa4qIW21roEhAP1uIZWq/Vq3VUpl16R2EWc67D0rmsypz29Ic5ueqtUGvBOrb1KkYWei1LC9SpiPecI7PeToYBh1+aYCcShAg288feYWL8fhNNdr5f+Ob1WCuL/d378/3s904+K76/b997Z9l3LshkHjP7+Kqrx5YN1dwf9/fz/AVzGT3lCsZO1Il9h94M3m15kqefeibz+Kx/xVgfXgenhoGsjaxbRL4EvBcRM4EpwChgXo5xdenYS4F/kNRdQpwIfA24ELhT0lhgPvBqOudngZlA3ixF0gzgVpJk/XzgQkkXAj8Hno+I84FvAQ+lSXd/13NVOs8CSdOAHwD7IuLK7lMC10TEbOAh4Jp0/yygpTu5TlUB70TE8fT1/vR7YQUyYVw5k6rGADCpagwTxpYXOSIzG4727dlNRfWUD+yrqJ7Cvj27ixSRFYPXQenKtEUkIl6QdFDSEuAckoQ4V4/x6og4BuyRtBn4crr/mYjoBDoltZFUetdJmiHpNuDzwBl55ux2CUnVuj19PRtA0qXA99I4d0p6Cbion0vaEhGH0vfvJKlmH+o15q2I2JVuPwaslDQa+C6wptfYXJ+A+i6fDiNZVHefeHEnT27elff42+90srft8IkK9tuH+u/DvnhaDQtnfaT/yWBm9pHU1k2mo7XlA5XLjtYWausmFzEqKzSvg9KVaYIt6QrgbuCnwGqSim2upPJ4j+0RPV733N8FlEn6PknF+QHgOZL2k75K9cd6xVQLvMuHq/VlJNff1evY6T22j/aOJ8f5jnRvRMRhSc3AIuDrJJX0nlqBcZJOi4j3gRpgH5aZhbPq+0yGt752gB8+su1ED/Z1c8/5QA/20zs3Mr/+G4UI1cyGsSW3LEl6bRsWU1Gd9N7u376O5UuXFjs0KyCvg9KV9U2Os4HHImJ1mtheQpIU93a1pMdJ+qEvAm4g/42Dc4D7I2KtpKnpuNP6iOFF4GZJd5EkyOuAe4Dn0/P8WFI9cDFwC0mS+1U40V5S0881Hqfv79tDwG9IqugfKI9GxDFJLwJ/B6wFrgXcZFVAM6eeybmTx9PafpTqyk9SWeEWETMrvO4b2BqbGmnZtJvausksX7rUN7YNM14HpSvrBPtBYK2kRUAn8CfgMznGjQZeJrkp8KaIOCgpxzAAfgI0SbqDpD1jS545AYiIVyTdB2wlqUz/LiKek7QDeEDS9STV6BsjYr+kR4Gr0uPbgO39XOObwBuS/gBcn+P8myV1kVTwc7kV+KWkvwfeABb3cz7LWGVFuRNrMyu6efMudyJlXgclKtOniHwU6VNENkXEmoKeuADSJ4ecBzwcEQ1Zz1/qTxE5GbhFxKx0nUxPEbGTj9eH5TOQtXFKPgdb0tnAb/McvjEiXi5kPD3cBtxJ0oNtZmZmZsNQwSvYNnD+BDz0XME2K12uUFpfvD4sn5PhOdhmZmZmZsOaE2wzMzMzsww5wTYzMzMzy5ATbDMzMzOzDDnBNjMzMzPLkBNsMzMzM7MMOcE2MzMzM8uQE2wzMzMzsww5wTYzMzMzy5ATbDMzMzOzDDnBNjMzMzPLkBNsMzMzM7MMOcE2MzMzM8uQE2wzMzMzswwVJMGWdJakXf2MWSFpRSHiGQxJlZKeyGCeu0+F6zUzMzOzj8cV7I9vPDB9oG9OE/RfAHdkF5IVQ3tHJy1722nv6Cx2KGZ2impuXs/8BXNpaDiX+Qvm0ty8vtghWYF5DZSmkVlOJmkk0AScB0wEAvhmrzFrgL8C04BK4J6I+FV6eIakLcAkYHVErJA0DvgFUAfUAi8A10ZEVx9x3A7cDLwPPBURyyRNTOf5NHAcWB4RG7qryBGxIn3vLuCr6ddlwASgHtgYEbcCPwNqJf0euB3YALQBR4Hy9Ho2SioDXge+EhH7eoT3t8D/Cfyov++nnby2vnaAtc++zqfGj+Ktvxzh23M+x8ypZxY7LDM7hTQ3r2flqlXUNCxm+swpdLS2sHLVKgDmzbu8yNFZIXgNlK5ME2zgS8B7ETFT0gjgeWAesK3XuLp07ERgm6Rn0/0T0/1jgd2SfgTMB16NiEWSPgHsAC7IMScAkmYAtwJfAA4DGyRdCCwDno+IH0uqB/4oqeEjXM9UkkQ9JDUBPwA2RcSVks4CBFwWEbskXQ9cA2wEZgEtvZJrIuLhNM4V/ZzbBujeX78y4PcePHoa/7r1Fdraj3DwnfyV6dNHjuCu677IpKox7G07zN1r/syDT+3oc+4zxpVTVTlqwLH1tOw7F2Qyj5kVT2NTIzUNixk7UQDJvw2LaWxqdHI1THgNlK5MW0Qi4gXgnyQtAX4KfBaoyDF0dUQci4g9wGbgy+n+ZyKiMyLaSKrCEyJiHfCspNuAnwNn5Jmz2yUkVev2iDgeEbMjYhtwKUkFm4jYCbwEXNTPJW2JiEMR8S6wk6Sa3dtbEbEr3X4MmCNpNPBdYE0/89spasK4ciZVjQFgUtUYJowtL3JEZnaq2bdnNxXVUz6wr6J6Cvv27C5SRFZoXgOlK+sWkSuAu0mS69VAFVCWY+jxHtsjerzuub8LKJP0feBbwAPAcyTtJ7nm7HasV0y1wLt8+MNEGcn1d/U6dnqP7aO948lxviPdGxFxWFIzsAj4Okkl3QpsMNXdp3duZH79BTzx4k6e3Lwr77i33+lkb9vhExXstw/134d98bQaFs6qH3BsZlZaausm09HacqJ6CdDR2kJt3eQiRmWF5DVQurJuEZkNPBYRq9PE9hKSpLi3qyU9TtIPfRFwA/lvHJwD3B8RayVNTced1kcMLwI3S7qLJEFeB9xD0q5yA9DdInIxcAtQQ9Jv3d1eUtPPNR6n7+/bQ8BvSKrovvvtFLVwVn2fyfDW1w7ww0e2nejBvm7uOe7BNrOPZcktS5J+24bFVFQn/bf7t69j+dKlxQ7NCsRroHRlnWA/CKyVtAjoBP4EfCbHuNHAyyQ3Bd4UEQcl5RgGwE+AJkl3AIeALXnmBCAiXpF0H7CVpDL9u4h4TtIO4IG0T7oLuDEi9kt6FLgqPb4N2N7PNb4JvCHpD8D1Oc6/WVIXSQXfStTMqWdy7uTxtLYfpTiFPJUAACAASURBVLryk1RWuEXEzD6e7h7bxqZGWjbtprZuMsuXLnXv7TDiNVC6yrq68j6MY0ikTxHZFBFrCnriAkifHHIe8HBE9HcD5cfW2nqosD+sYShpEflGscMwsyFQXT22r/bCQfHv51Of14flM5C1kXUFuyAknQ38Ns/hGyPi5ULG08NtwJ0kPdhmZmZmNgwVvIJtA+dPwEPPFWyz0uUKpfXF68PyGcja8F9yNDMzMzPLkBNsMzMzM7MMOcE2MzMzM8uQE2wzMzMzsww5wTYzMzMzy5ATbDMzMzOzDDnBNjMzMzPLkBNsMzMzM7MMOcE2MzMzM8uQE2wzMzMzsww5wTYzMzMzy5ATbDMzMzOzDDnBNjMzMzPLkBNsMzMzM7MMOcE2MzMzM8tQQRJsSWdJ2tXPmBWSVhQinsGQVCnpiUG8/2JJf5b0qqT/ImlylvHZ0Grv6KRlbzvtHZ3FDsXMSkBz83rmL5hLQ8O5zF8wl+bm9cUOyQrMa6A0jSx2AKeg8cD0Qbz/18AVEfHPkv4t8DPgbzOJzIbU1tcOsPbZ1/nU+FG89ZcjfHvO55g59cxih2Vmp6jm5vWsXLWKmobFTJ85hY7WFlauWgXAvHmXFzk6KwSvgdJV1tXVldlkkkYCTcB5wEQggG+m25si4ixJa4C/AtOASuCeiPhVWr2eAfwNMAlYHRErJI0DfgHUAbXAC8C1EZE3cEm3AzcD7wNPRcQySRPTeT4NHAeWR8SG7qp5RKxI37sL+Gr6dRkwAagHNkbErZKeTPc/DdwObADagKNAeXo9GyWVAa8DX4mIfenc5cCiiHgkff0F4MGIaPgo39/W1kPZ/bBKxL2/fiWzudraj3DwnfyV6dNHjuCu677IpKox7G07zN1r/syx43/NO/6MceVUVY4adFzLvnPBoOcwM6iuHls2VHMP5Pfz/AVzGT3lCsZO1Il9h94M3m15kqefeibT+Kx/xVgfXgOnhoGsjaxbRL4EvBcRM4EpwChgXo5xdenYS4F/kNRdBpwIfA24ELhT0lhgPvBqOudngZlA3oxD0gzgVpJk/XzgQkkXAj8Hno+I84FvAQ+lSXd/13NVOs8CSdOAHwD7IuLK7lMC10TEbOAh4Jp0/yygpTu5BoiIzh7J9QhgBTDgdhMrrAnjyplUNQaASVVjmDC2vMgRmdmpbN+e3VRUT/nAvorqKezbs7tIEVmheQ2UrkxbRCLiBUkHJS0BziFJiCtyDF0dEceAPZI2A19O9z8TEZ1Ap6Q2YEJErJM0Q9JtwOeBM/LM2e0Skqp1e/p6NoCkS4HvpXHulPQScFE/l7QlIg6l799JUs0+1GvMWxGxK91+DFgpaTTwXWBNrkklfQL4Jcn3f2U/MVgfsqzuPvHiTp7cvCvv8bff6WRv2+ETFey3D/Xdh33xtBoWzqrPLD4zKy21dZPpaG35QPWyo7WF2jrfmjNceA2UrkwTbElXAHcDPwVWA1VArrL68R7bI3q87rm/CyiT9H2SivMDwHMk7Sd9leqP9YqpFniXD1fry0iuv6vXsdN7bB/tHU+O8x3p3oiIw5KagUXA10kq6R8gqQJ4EjgI/G36QcNOAgtn1XP6pBbm138j5/Gtrx3gh49sO9GDfd3cc9yDbWYDtuSWJUm/bcNiKqqT/tv929exfOnSYodmBeI1ULqyvslxNvBYRKxOE9tLSJLi3q6W9DhJP/RFwA3kv3FwDnB/RKyVNDUdd1ofMbwI3CzpLpIEeR1wD/B8ep4fS6oHLgZuAWpI+q2720tq+rnG4/T9fXsI+A1JFT1XifMRoAX47/rqI7eTz8ypZ3Lu5PG0th+luvKTVFa4RcTMBq77JrbGpkZaNu2mtm4yy5cu9c1tw4jXQOnKOsF+EFgraRHQCfwJ+EyOcaOBl0luCrwpIg5KyjEMgJ8ATZLuIGnP2JJnTgAi4hVJ9wFbSSrTv4uI5yTtAB6QdD1JNfrGiNgv6VHgqvT4NmB7P9f4JvCGpD8A1+c4/2ZJXSQV/A+Q1EDyxJAdwPb0mvdFRK4+dTsJVVaUO7E2s8zMm3e5k6lhzmugNGX6FJGPIn2KyKaIWFPQExdA+uSQ84CHP+qTQT4OP0Vk6D29c2PeFhEzO7WdbE8RsZOL14flM5C1cUo+B1vS2cBv8xy+MSJeLmQ8PdwG3EnSg21mZmZmw1DBK9g2cP4EPPRcwTYrXa5QWl+8Piyfk+E52GZmZmZmw5oTbDMzMzOzDDnBNjMzMzPLkBNsMzMzM7MMOcE2MzMzM8uQE2wzMzMzsww5wTYzMzMzy5ATbDMzMzOzDDnBNjMzMzPLkBNsMzMzM7MMOcE2MzMzM8uQE2wzMzMzsww5wTYzMzMzy5ATbDMzMzOzDI0sxEkknQVsioiz+hizAiAiVhQipoGSVAn8MiIWDvD9s4CfAJ8A/m/guxHxlwxDNDMzM7MicgX74xsPTB/E+1cD/yYipgE7gDszicpOSu0dnbTsbae9o7PYoZjZSaa5eT3zF8yloeFc5i+YS3Pz+mKHZEXgdVCaMq1gSxoJNAHnAROBAL7Za8wa4K/ANKASuCcifpUeniFpCzAJWB0RKySNA34B1AG1wAvAtRHR1UcctwM3A+8DT0XEMkkT03k+DRwHlkfEht6Vc0m7gK+mX5cBE4B6YGNE3Ar8DKiV9HvgdmAD0AYcBcrT69koqQx4HfhKROzrEd7nI+KYpNPT6/zn/r6vdmra+toB1j77Op8aP4q3/nKEb8/5HDOnnlnssMzsJNDcvJ6Vq1ZR07CY6TOn0NHawspVqwCYN+/yIkdnheJ1ULqybhH5EvBeRMyUNAJ4HpgHbOs1ri4dOxHYJunZdP/EdP9YYLekHwHzgVcjYpGkT5BUfS/IMScAkmYAtwJfAA4DGyRdCCwDno+IH0uqB/4oqeEjXM9UkkQ9JDUBPyBpd7kybX0RcFlE7JJ0PXANsBGYBbT0Sq5Jk+tpwHPAMWB5PzFYxu799St5jx08ehr/ujX/8Z7a2o9w8J38lenTR47gruu+yKSqMextO8zda/7Mg0/tyDv+jHHlVFWO+kjn7suy71ww6DnMbGg1NjVS07CYsRMFkPzbsJjGpkYnVsOI10HpyrRFJCJeAP5J0hLgp8BngYocQ1dHxLGI2ANsBr6c7n8mIjojoo2kKjwhItYBz0q6Dfg5cEaeObtdQlK1bo+I4xExOyK2AZeSVLCJiJ3AS8BF/VzSlog4FBHvAjtJqtm9vRURu9Ltx4A5kkYD3wXW5Jo0Iv4lIiYC9wC/6ScGO0VNGFfOpKoxAEyqGsOEseVFjsjMThb79uymonrKB/ZVVE9h357dRYrIisHroHRl3SJyBXA3SXK9GqgCynIMPd5je0SP1z33dwFlkr4PfAt4gKTqe16eObsd6xVTLfAuH/4wUUZy/V29jp3eY/to73hynO9I90ZEHJbUDCwCvk5SSe8ZyydJqt1PpLseAX7Ux7XYEOirwvv0zo3Mr/9oFeAnXtzJk5t35T3+9jud7G07fKKC/fahvvuwL55Ww8JZ9R/p3GZ2aqutm0xHa8uJyiVAR2sLtXWTixiVFZrXQenKukVkNvBYRKxOE9tLSJLi3q6W9DhJP/RFwA3kv3FwDnB/RKyVNDUdd1ofMbwI3CzpLpIEeR1Jpfj59DzdLSIXA7cANST91t3tJTX9XONx+v6+PURSlX4qInpnVMeARkn/T1pVvxr4Yz/ns5PUwln1fSbEW187wA8f2XaiB/u6uee4B9vMAFhyy5Kk17ZhMRXVSe/t/u3rWL50abFDswLyOihdWSfYDwJrJS0COoE/AZ/JMW408DLJTYE3RcRBSTmGAckj7Zok3QEcArbkmROAiHhF0n3AVpLK9O8i4jlJO4AH0j7pLuDGiNgv6VHgqvT4NmB7P9f4JvCGpD8A1+c4/2ZJXSQV/N7H3pf0d2kcpwF7gRv7OZ+domZOPZNzJ4+ntf0o1ZWfpLLCLSJmlujur21saqRl025q6yazfOlS990OM14HpausqyvvwziGRPoUkU0RsaagJy6A9Mkh5wEPR0R/N1B+bK2thwr7wxqGkhaRbxQ7DDMbAtXVY/tqLxwU/34+9Xl9WD4DWRsF+UMzWZN0NvDbPIdvjIiXCxlPD7eRPNd6UZHOb2ZmZmZFVvAKtg2cPwEPPVewzUqXK5TWF68Py2cga8N/ydHMzMzMLENOsM3MzMzMMuQE28zMzMwsQ06wzczMzMwy5ATbzMzMzCxDTrDNzMzMzDLkBNvMzMzMLENOsM3MzMzMMuQE28zMzMwsQ06wzczMzMwy5ATbzMzMzCxDTrDNzMzMzDLkBNvMzMzMLENOsM3MzMzMMuQE28zMzMwsQwVJsCWdJWlXP2NWSFpRiHgGQ1KlpCcymKdBUmcWMZl9VO0dnbTsbae9w0vP7GTR3Lye+Qvm0tBwLvMXzKW5eX2xQ7IC8s+/NI0sdgCnoPHA9MFMIGk0cB/wiUwiMvsItr52gLXPvs6nxo/irb8c4dtzPsfMqWcWOyyzYa25eT0rV62ipmEx02dOoaO1hZWrVgEwb97lRY7Ohpp//qUr0wRb0kigCTgPmAgE8M1eY9YAfwWmAZXAPRHxq/TwDElbgEnA6ohYIWkc8AugDqgFXgCujYiuPuK4HbgZeB94KiKWSZqYzvNp4DiwPCI2dFfNI2JF+t5dwFfTr8uACUA9sDEibgV+BtRK+j1wO7ABaAOOAuXp9WyUVAa8DnwlIvb1CvFHwD8CX+rr+2ml7d5fv5LpfG3tRzj4Tv7K9OkjR3DXdV9kUtUY9rYd5u41f+bBp3b0OecZ48qpqhw16NiWfeeCQc9hVooamxqpaVjM2IkCSP5tWExjU6MTrGHAP//SlXWLyJeA9yJiJjAFGAXMyzGuLh17KfAPkrrLaBOBrwEXAndKGgvMB15N5/wsMBPI+19rSTOAW4EZwPnAhZIuBH4OPB8R5wPfAh5Kk+7+rueqdJ4FkqYBPwD2RcSV3acEromI2cBDwDXp/llAS+/kWtIVwOiIeLyfc5tlasK4ciZVjQFgUtUYJowtL3JEZrZvz24qqqd8YF9F9RT27dldpIiskPzzL12ZVrAj4gVJByUtAc4hSYgrcgxdHRHHgD2SNgNfTvc/ExGdQKekNmBCRKyTNEPSbcDngTPyzNntEpKqdXv6ejaApEuB76Vx7pT0EnBRP5e0JSIOpe/fSVLNPtRrzFsRsSvdfgxYmbaAfBdY03Ng+kHi77tjsuEt66ruEy/u5MnNu/Ief/udTva2HT5RwX77UP992BdPq2HhrPoMozSznmrrJtPR2nKiggnQ0dpCbd3kIkZlheKff+nKukXkCuBu4KfAaqAKKMsx9HiP7RE9Xvfc3wWUSfo+ScX5AeA5kvaTXHN2O9YrplrgXT5crS8juf6uXsdO77F9tHc8Oc53pHsjIg5LagYWAV8nqaT3dDnJB4QXJHXH9yowqzuRNxuohbPq+0yGt752gB8+su1ED/Z1c89xD7ZZkS25ZUnSc9uwmIrqpAd3//Z1LF+6tNihWQH451+6sr7JcTbwWESsThPbS0iS4t6ulvQ4ST/0RcAN5L9xcA5wf0SslTQ1HXdaHzG8CNws6S6SBHkdcA/wfHqeH0uqBy4GbgFqSPqtu9tLavq5xuP0/X17CPgNSRX9AyXCiPhPwH/qfi2pKyIGdcOk2Uc1c+qZnDt5PK3tR6mu/CSVFW4RMSu27j7bxqZGWjbtprZuMsuXLnX/7TDhn3/pyjrBfhBYK2kR0An8CfhMjnGjgZdJbgq8KSIOdld0c/gJ0CTpDpL2jC155gQgIl6RdB+wlaQy/buIeE7SDuABSdeTVKNvjIj9kh4FrkqPbwO293ONbwJvSPoDcH2O82+W1EVSwTc7qVRWlDuxNjvJzJt3uROqYcw//9JU1tWV92EcQyJ9isimiFhT0BMXQPrkkPOAhyOiIev5W1sPFfaHNQw9vXMj8+u/UewwzGwIVFeP7au9cFD8+/nU5/Vh+QxkbZySz8GWdDbw2zyHb4yIlwsZTw+3AXeS9GCbmZmZ2TBU8Aq2DZw/AQ89V7DNSpcrlNYXrw/LZyBroyB/Kt3MzMzMbLhwgm1mZmZmliEn2GZmZmZmGXKCbWZmZmaWISfYZmZmZmYZcoJtZmZmZpYhJ9hmZmZmZhlygm1mZmZmliEn2GZmZmZmGXKCbWZmZmaWISfYZmZmZmYZcoJtZmZmZpYhJ9hmZmZmZhlygm1mZmZmlqGRhTiJpLOATRFxVh9jVgBExIpCxDRQkiqBX0bEwgG+/1rgXuDNdNfTEfE/ZRWfmZmZmRWXK9gf33hg+iDe/0Xg30XE9PTLyXUf2js6adnbTntHZ7FDMTPLVHPzeuYvmEtDw7nMXzCX5ub1xQ7JisDroDRlWsGWNBJoAs4DJgIBfLPXmDXAX4FpQCVwT0T8Kj08Q9IWYBKwOiJWSBoH/AKoA2qBF4BrI6KrjzhuB24G3geeiohlkiam83waOA4sj4gNvSvnknYBX02/LgMmAPXAxoi4FfgZUCvp98DtwAagDTgKlKfXs1FSGfA68JWI2NcjvC8CUyT9j8C/AN+PiL/0860dlra+doC1z77Op8aP4q2/HOHbcz7HzKlnFjssM7NBa25ez8pVq6hpWMz0mVPoaG1h5apVAMybd3mRo7NC8TooXVm3iHwJeC8iZkoaATwPzAO29RpXl46dCGyT9Gy6f2K6fyywW9KPgPnAqxGxSNIngB3ABTnmBEDSDOBW4AvAYWCDpAuBZcDzEfFjSfXAHyU1fITrmUqSqIekJuAHJO0uV6atLwIui4hdkq4HrgE2ArOAll7JNcB+4IfA/w6sBO4DvtNPHCede3/9yqDnaGs/wsF38lemTx85gruu+yKTqsawt+0wd6/5Mw8+tSPv+DPGlVNVOWpQMR08ehr/uvUVln3ngkHNY2bWl8amRmoaFjN2ogCSfxsW09jU6MRqGPE6KF2ZJtgR8YKkg5KWAOcAnwUqcgxdHRHHgD2SNgNfTvc/ExGdQKekNmBCRKyTNEPSbcDngTPyzNntEpKqdXv6ejaApEuB76Vx7pT0EnBRP5e0JSIOpe/fSVLNPtRrzFsRsSvdfgxYKWk08F1gTe8JI+LK7m1Jq4Cd/cQwbE0YV86kqjEATKoaw4Sx5bz5lyNFjsrMbPD27dnN9JlTPrCvonoKLZt2FykiKwavg9KVdYvIFcDdwE+B1UAVUJZj6PEe2yN6vO65vwsok/R94FvAA8BzJO0nuebsdqxXTLXAu3y437yM5Pq7eh07vcf20d7x5DjfiYwvIg5LagYWAV8nqaT3jKUS+LcR8Y89YvhAvKeKLCq8T7y4kyc378p7/O13OtnbdvhEBfvtQ333YV88rYaFs+oHFdPTOzcyv97VazMbWrV1k+lobTlRuQToaG2htm5yEaOyQvM6KF1Zt4jMBh6LiNVpYnsJSVLc29WSHifph74IuIH8Nw7OAe6PiLWSpqbjTusjhheBmyXdRZIgrwPuIWlXuQHobhG5GLgFqCHpt+5uL6np5xqP0/f37SHgNyRV9N4ZYQewVNKWiHgJ+O+B3/dzvpK1cFZ9nwnx1tcO8MNHtp3owb5u7jnuwTazkrDkliVJr23DYiqqk97b/dvXsXzp0mKHZgXkdVC6sk6wHwTWSloEdAJ/Aj6TY9xo4GWSmwJvioiDknIMA+AnQJOkO0jaM7bkmROAiHhF0n3AVpLK9O8i4jlJO4AH0j7pLuDGiNgv6VHgqvT4NmB7P9f4JvCGpD8A1+c4/2ZJXSQV/N7H3pd0dXo9o0hugry2n/MNWzOnnsm5k8fT2n6U6spPUllRXuyQzMwy0d1f29jUSMum3dTWTWb50qXuux1mvA5KV1lXV96HcQyJ9CkimyJiTUFPXADpk0POAx6OiP5uoPzYWlsPFfaHNQwlLSLfKHYYZjYEqqvH9tVeOCj+/Xzq8/qwfAayNgryh2ayJuls4Ld5Dt8YES8XMp4ebgPuJOnBNjMzM7NhqOAVbBs4fwIeeq5gm5UuVyitL14fls9A1ob/kqOZmZmZWYacYJuZmZmZZcgJtpmZmZlZhpxgm5mZmZllyAm2mZmZmVmGnGCbmZmZmWXICbaZmZmZWYacYJuZmZmZZcgJtpmZmZlZhpxgm5mZmZllyAm2mZmZmVmGnGCbmZmZmWXICbaZmZmZWYacYJuZmZmZZcgJtpmZmZlZhgqSYEs6S9KufsaskLSiEPEMhqRKSU8M4v01kp6WtF3SZklnZRhe0bV3dNKyt532js5ih2JmdlJrbl7P/AVzaWg4l/kL5tLcvL7YIVkReB2UppHFDuAUNB6YPoj3/wp4PCL+o6SbgXuBv8sksiLb+toB1j77Op8aP4q3/nKEb8/5HDOnnlnssMzMTjrNzetZuWoVNQ2LmT5zCh2tLaxctQqAefMuL3J0ViheB6Ur0wRb0kigCTgPmAgE8M1eY9YAfwWmAZXAPRHxq/TwDElbgEnA6ohYIWkc8AugDqgFXgCujYiuPuK4HbgZeB94KiKWSZqYzvNp4DiwPCI2dFfNI2JF+t5dwFfTr8uACUA9sDEibgV+BtRK+j1wO7ABaAOOAuXp9WyUVAa8DnwlIvalc1cB/w0wJw11NfBf+v3GZuDeX7+SyTxt7Uc4+E7u6vTpI0dw13VfZFLVGPa2HebuNX/mwad29DnfGePKqaocNei4ln3ngkHPYWZWKI1NjdQ0LGbsRAEk/zYsprGp0YnVMOJ1ULqybhH5EvBeRMwEpgCjgHk5xtWlYy8F/kFSd5lzIvA14ELgTkljgfnAq+mcnwVmAnmzKUkzgFuBGcD5wIWSLgR+DjwfEecD3wIeSpPu/q7nqnSeBZKmAT8A9kXEld2nBK6JiNnAQ8A16f5ZQEt3cp06G3gD+EdJ/xV4HHivnxhOGRPGlTOpagwAk6rGMGFseZEjMjM7Oe3bs5uK6ikf2FdRPYV9e3YXKSIrBq+D0pVpBTsiXpB0UNIS4ByShLgix9DVEXEM2CNpM/DldP8zEdEJdEpqAyZExDpJMyTdBnweOCPPnN0uIalat6evZwNIuhT4XhrnTkkvARf1c0lbIuJQ+v6dJNXsQ73GvBURu9Ltx4CVkkYD3wXW9Bo7EmgA/ueIuE3SjcAvSarlQyqrCu8TL+7kyc27ch57+51O9rYdPlHBfvtQ/33YF0+rYeGs+kxiMzM7VdTWTaajteVE5RKgo7WF2rrJRYzKCs3roHRl3SJyBXA38FOS9ocqoCzH0OM9tkf0eN1zfxdQJun7JBXnB4DnSNpPcs3Z7VivmGqBd/lwtb6M5Pq7eh07vcf20d7x5Djfke6NiDgsqRlYBHydpJLe0wHgUER038GwlqTl5JSxcFZ93oR462sH+OEj2070YF839xz3YJuZ5bDkliVJr23DYiqqk97b/dvXsXzp0mKHZgXkdVC6sr7JcTbwWESsThPbS0iS4t6ulvQ4ST/0RcAN5L9xcA5wf0SslTQ1HXdaHzG8CNws6S6SBHkdcA/wfHqeH0uqBy4GbgFqSCvIaXtJTT/XeJy+v28PAb8hqaJ/oIQbEf+XpL2S5kbEM8ACYFs/5ztlzJx6JudOHk9r+1GqKz9JZYVbRMzMcunur21saqRl025q6yazfOlS990OM14HpSvrBPtBYK2kRUAn8CfgMznGjQZeJrkp8KaIOCgpxzAAfgI0SbqDpD1jS545AYiIVyTdB2wlqUz/LiKek7QDeEDS9STV6BsjYr+kR4Gr0uPbgO39XOObwBuS/gBcn+P8myV1kVTwc7kSuF/S/wq8Q9JKUjIqK8qdWJuZfQTz5l3uRMq8DkpUWVdX3odxDIn0KSKbImJNQU9cAOmTQ84DHo6Ihqznb209VNgf1jD09M6NzK//RrHDMLMhUF09tq/2wkHx7+dTn9eH5TOQtXFKPgdb0tnAb/McvjEiXi5kPD3cBtxJ0oNtZmZmZsNQwSvYNnD+BDz0XME2K12uUFpfvD4sn4GsjYL8qXQzMzMzs+HCCbaZmZmZWYacYJuZmZmZZcgJtpmZmZlZhpxgm5mZmZllyAm2mZmZmVmGnGCbmZmZmWXICbaZmZmZWYacYJuZmZmZZcgJtpmZmZlZhpxgm5mZmZllyAm2mZmZmVmGnGCbmZmZmWXICbaZmZmZWYZGFuIkks4CNkXEWX2MWQEQESsKEdNASaoEfhkRCwfw3k8BG3vsqgSqI6Iiq/jMzMzMrLhcwf74xgPTB/LGiHgrIqZHxHTgAmAXcFOGsZ0y2js6adnbTntHZ7FDMTMriubm9cxfMJeGhnOZv2Auzc3rix2SFYHXQWnKtIItaSTQBJwHTAQC+GavMWuAvwLTSCq490TEr9LDMyRtASYBqyNihaRxwC+AOqAWeAG4NiK6+ojjduBm4H3gqYhYJmliOs+ngePA8ojY0LtyLmkX8NX06zJgAlAPbIyIW4GfAbWSfg/cDmwA2oCjQHl6PRsllQGvA1+JiH05wrweeDci1ub9hpaora8dYO2zr/Op8aN46y9H+PaczzFz6pnFDsvMrGCam9ezctUqahoWM33mFDpaW1i5ahUA8+ZdXuTorFC8DkpX1i0iXwLei4iZkkYAzwPzgG29xtWlYycC2yQ9m+6fmO4fC+yW9CNgPvBqRCyS9AlgB0n1t/ecAEiaAdwKfAE4DGyQdCGwDHg+In4sqR74o6SGj3A9U0kS9ZDUBPyApN3lyrT1RcBlEbFL0vXANSRtILOAllzJtaTTgL8Hrujn/AV1769fyWSetvYjHHwnf2X69JEjuOu6LzKpagx72w5z95o/8+BTO/qc84xx5VRVjhpUXMu+c8Gg3m9mlpXGpkZqGhYzdqIAkn8bFtPY1OjEahjxOihdmbaIRMQLwD9JWgL8FPgskKu/eHVEHIuIPcBm4Mvp/mciojMi2kiqwhMiYh3wsS0yHQAAIABJREFUrKTbgJ8DZ+SZs9slJFXr9og4HhGzI2IbcClJBZuI2Am8BFzUzyVtiYhDEfEusJOkmt3bWxGxK91+DJgjaTTwXWBNnnkvA16PiH/p5/wlacK4ciZVjQFgUtUYJowtL3JEZmaFtW/Pbiqqp3xgX0X1FPbt2V2kiKwYvA5KV9YtIlcAd5Mk16uBKqAsx9DjPbZH9Hjdc38XUCbp+8C3gAeA50jaT3LN2e1Yr5hqgXf58IeJMpLr7+p17PQe20d7x5PjfEe6NyLisKRmYBHwdZJKei4LgUfzX0JxZFXhfeLFnTy5eVfe42+/08netsMnKthvH+q/D/viaTUsnFWfSXxmZsVWWzeZjtaWE5VLgI7WFmrrJhcxKis0r4PSlXWLyGzgsYhYnSa2l5Akxb1dLelxkn7oi4AbyH/j4Bzg/ohYK2lqOu60PmJ4EbhZ0l0kCfI64B6SdpUbgO4WkYuBW4Aakn7r7vaSmn6u8Th9f98eAn5DUkXPlznOBO7t5zynrIWz6vtMhre+doAfPrLtRA/2dXPPcQ+2mQ0rS25ZkvTaNiymojrpvd2/fR3Lly4tdmhWQF4HpSvrBPtBYK2kRUAn8CfgMznGjQZeJrkp8KaIOCgpxzAAfgI0SboDOARsyTMnABHxiqT7gK0klenfRcRzknYAD6R90l3AjRGxX9KjwFXp8W3A9n6u8U3gDUl/ILlRsff5N0vqIqng51MP7OnnPCVr5tQzOXfyeFrbj1Jd+UkqK9wiYmbDS3d/bWNTIy2bdlNbN5nlS5e673aY8TooXWVdXXkfxjEk0qeIbIqINQU9cQGkTw45D3g4Ivq7gfJja209VNgf1jD09M6NzK//RrHDMLMhUF09tq/2wkHx7+dTn9eH5TOQtVGQPzSTNUlnA7/Nc/jGiHi5kPH0cBtwJ0kPtpmZmZkNQwWvYNvA+RPw0HMF26x0uUJpffH6sHwGsjb8lxzNzMzMzDLkBNvMzMzMLENOsM3MzMzMMuQE28zMzMwsQ06wzczMzMwy5ATbzMzMzCxDTrDNzMzMzDLkBNvMzMzMLENOsM3MzMzMMuQE28zMzMwsQ06wzczMzMwy5ATbzMzMzCxDTrDNzMzMzDLkBNvMzMzMLENOsM3MzMzMMlSQBFvSWZJ29TNmhaQVhYhnMCRVSnpiEO8/S9ILkl6VtEnS5Czjs4Fp7+ikZW87R48UOxIzGy6am9czf8FcGhrOZf6CuTQ3ry92SFYEXgelaWSxAzgFjQemD+L99wDrIqJJ0veB/wBck0lkNiBbXzvA2mdf51PjR7H/7U9QywFmTj2z2GGZWQlrbl7PylWrqGlYzPSZU+hobWHlqlUAzJt3eZGjs0LxOihdmSbYkkYCTcB5wEQggG/2GrMG+CswDagE7omIX6WHZ0jaAkwCVkfECknjgF8AdUAt8AJwbUR09RHH7cDNwPvAUxGxTNLEdJ5PA8eB5RGxobtqHhEr0vfuAr6afl0GTADqgY0RcSvwM6BW0u+B24ENQBtwFChPr2ejpDLgdeArEbGvR3inAePS7TGAa6Z53PvrVzKZp639CAff6cx7/PSRI7jrui8yqWoMe9sOc/eaP/PgUzvyjj9jXDlVlaMGHdey71ww6DnM7NTU2NRITcNixk4UQPJvw2IamxqdWA0jXgelK+sWkS8B70XETGAKMAqYl2NcXTr2UuAfJHWXCycCXwMuBO6UNBaYD7yazvlZYCaQNzORNAO4FZgBnA9cKOlC4OfA8xFxPvAt4KE06e7veq5K51kgaRrwA2BfRFzZfUrgmoiYDTzE/1+NngW09EquAf498O8k7QX+B+DefmKwITZhXDmTqsYAMKlqDBPGlhc5IjMrdfv27KaiesoH9lVUT2Hfnt1FisiKweugdGVawY6IFyQdlLQEOIckIa7IMXR1RBwD9kjaDHw53f9MRHQCnZLagAkRsU7SDEm3AZ8HzsgzZ7dLSKrW7enr2QCSLgW+l8a5U9JLwEX9XNKWiDiUvn8nSTX7UK8xb0XErnT7MWClpNHAd4E1Oeb8JXBTRPxnSVcBv5d0fl8V+eEqqwrvEy/u5MnNu/Ief/udTva2HT5RwX77UP5qN8DF02pYOKs+k9jMbHiqrZtMR2vLicolQEdrC7V1vi1nOPE6KF1Zt4hcAdwN/BRYDVQBZTmGHu+xPaLH6577u4CytE/5W8ADwHMk7Se55ux2rFdMtcC7fLhaX0Zy/V29jp3eY/to73hynO9Ei0dEHJbUDCwCvk5SSe8ZSzVwTkT853T8byX9R5LvU2sf12SDsHBWfZ8J8dbXDvDDR7alPdiHuW7uOe7BNrMhteSWJUmvbcNiKqqT3tv929exfOnSYodmBeR1ULqyvslxNvBYRKxOE9tLSJLi3q6W9DhJP/RFwA3kv3FwDnB/RKyVNDUdd1ofMbwI3CzpLpIEeR3JjYXPp+f5saR64GLgFqCGpN+6u72kpp9rPE7f37eHgN+QVNF7l0LbgKOSvhwRf5R0MXAoIpxcF9HMqWdy7uTxtLYf5b/+vy85uTazIdfdX9vY1EjLpt3U1k1m+dKl7rsdZrwOSlfWCfaDwFpJi4BO4E/AZ3KMGw28THJT4E0RcVBSjmEA/ARoknQHSXvGljxzAhARr0i6D9hKUpn+XUQ8J2kH8ICk60mq0TdGxH5JjwJXpce3Adv7ucY3gTck/QG4Psf5N0vqIqng9z7WJembwM8ljUqv56p+zmcFUFlRTmVFOR/6SGRmNkTmzbvciZR5HZSosq6uwrb+pk8R2RQRawp64gJInxxyHvBwRDRkPX9r6yH3aQ+xp3duZH79N4odhpkNgerqsX21Fw6Kfz+f+rw+LJ+BrI1T8jnYks4Gfpvn8I0R8XIh4+nhNuBOkh5sMzMzMxuGCl7BtoHzJ+Ch5wq2WelyhdL64vVh+QxkbRTkT6WbmZmZmQ0XTrDNzMzMzDLkBNvMzMzMLENOsM3MzMzMMuQE28zMzMwsQ06wzczMzMwy5ATbzMzMzCxDTrDNzMzMzDLkBNvMzMzMLENOsM3MzMzMMuQE28zMzMwsQ06wzczMzMwy5ATbzMzMzCxDTrDNzMzMzDI0shAnkXQWsCkizupjzAqAiFhRiJgGSlIl8MuIWDjA988AGoFy4A3gxog4kGGIZmZmZlZErmB/fOOB6QN5o6Qy4HFgaUScDzwMPJBhbJZDe0cnLXvbae/oLHYoZmYnNDevZ/6CuTQ0nMv8BXNpbl5f7JCsCLwOSlOmFWxJI4Em4DxgIhDAN3uNWQP8FZgGVAL3RMSv0sMzJG0BJgGrI2KFpHHAL4A6oBZ4Abg2Irr6iON24GbgfeCpiFgmaWI6z6eB48DyiNjQu3IuaRfw1fTrMmACUA9sjIhbgZ8BtZJ+D9wObADagKMkVel7ImJjmky/DnwlIvaloVUBoyLiD+nr9cAjksojwtnfENj62gHWPvs6nxo/irf+coRvz/kcM6eeWeywzGyYa25ez8pVq6hpWMz0mVPoaG1h5apVAMybd3mRo7NC8TooXVm3iHwJeC8iZkoaATwPzAO29RpXl46dCGyT9Gy6f2K6fyywW9KPgPnAqxGxSNIngB3ABTnmBE60YNwKfAE4DGyQdCGwDHg+In4sqR74o6SGj3A9U0kS9ZDUBPyApN3lyrT1RcBlEbFL0vXANcBGYBbQ0iO5hiQRPyzpGxGxEfhvgdOBM4Ce40ravb9+JbO52tqPcPCd/J9NTh85gruu+yKTqsawt+0wd6/5Mw8+tSPv+FGjT+Nfzxh8fMu+c8Gg5zCz0tXY1EhNw2LGThRA8m/DYhqbGp1YDSNeB6Ur0xaRiHgB+CdJS4CfAp8FKnIMXR0RxyJiD7AZ+HK6/5mI6IyINpJkdEJErAOelXQb8HOSZDTXnN0uIalat0fE8YiYHRHbgEtJKthExE7gJeCifi5pS0Qcioh3gZ0k1eze3oqIXen2Y8AcSaOB7wJreg5Mq+5XAcslbQf+BjgIvNdPHDZAE8aVM6lqDACTqsYwYWx5kSMyM4N9e3ZTUT3lA/sqqqewb8/uIkVkxeB1ULqybhG5AribJLleTdISUZZj6PEe2yN6vO65vwsok/R94FskvcrPkbSf5Jqz27FeMdUC7/LhDxNlJNff1evY6T22j/aOJ8f5jnRvRMRhSc3AIuDrJJX0D8UXEV9NY5sA/Hvg7fyXU3qyrO4+8eJOnty8K+/xt9/pZG/b4RMV7LcP9d2Jc9ZZXdx5havPZja0ausm09HacqJyCdDR2kJt3eQiRmWF5nVQurJuEZkNPBYRq9PE9hKSpLi3qyU9TtIPfRFwA/lvHJwD3B8RayVNTced1kcMLwI3S7qLJEFeB9xD0q5yA9DdInIxcAtQQ9Jv3d1eUtPPNR6n7+/bQ8BvSKroubK51ZJujog/A3cA/1tE/LWfc1oeC2fVs3BWfd7jW187wA8f2XaiB/u6uef02YP99M6NQxGmmdkHLLllSdJr27CYiuqk93b/9nUsX7q02KFZAXkdlK6sE+wHgbWSFgGdwJ+Az+QYNxp4meSmwJsi4qCkHMMA+AnQJOkO4BCwJc+cAETEK5LuA7aSVKZ/FxHPSdoBPJD2SXeRPB5vv6RHgavS49uA7f1c45vAG5L+AFyf4/ybJXWRVPBzuQW4P20j+WeSpN+GyMypZ3Lu5PG0th+luvKTVFa4RcTMiq+7v7axqZGWTbuprZvM8qVL3Xc7zHgdlK6yrq68D+MYEulTRDZFxJqCnrgA0ieHnAc8HBH93UD5sbW2HirsD2sYenrnRubXf6PYYZjZEKiuHttXe+Gg+Pfzqc/rw/IZyNooyB+ayZqks4Hf5jl8Y0S8XMh4ergNuJOkB9vMzMzMhqGCV7Bt4PwJeOi5gm1WulyhtL54fVg+A1kb/kuOZmZmZmYZcoJtZmZmZpYhJ9hmZmZmZhlygm1mZmZmliEn2GZmZmZmGXKCbWZmZmaWISfYZmZmZmYZcoJtZmZmZpYhJ9hmZmZmZhlygm1mZmZmliEn2GZmZmZmGXKCbWZmZmaWISfYZmZmZmYZcoJtZmZmZpYhJ9hmZmZmZhnKNMGWdJakXf2MWSFpRZbnHQqSKiU9kcE8d/e8Xkl/I+lpSf+HpBcknTnYc1j22js6adnbTntHZ7FDMbMS1dy8nvkL5tLQcC7zF8yluXl9sUOyIvA6KE0jix3ASWw8MH2gb5ZUCfwYWAys6nHofwFejIj5kv4N8FPg7wYTqGVr62sHWPvs/8fe/QdXVWd7n38HoSMQyENMDPlRYkd0eUX6Em3xiQptK1gCovgD50EtxdHrIFwtmVKYy9QwDFbxKNNa3a3pjNKatD9Aefz1CEYmWDQlDWhp0DtzpWbRqdzQF1BJwBsIQiSa+WPv5MbjOQk52cmBw+dVRbGz9/d89/om38J1lmuf7OLsUUPZ/81R7ph6AWXj9D5IRKJTXb2eFStXUlA6hwllY2lprGPFyuA/FdOn35Di6GSgaB+kr4z29vZev8jMBgMVwMVAPuDALeHxZnc/18yqgB+A8UA28Li7vxxWcycC/wkoAirdfZmZjQReAIqBQuBD4G53TxigmS0E5gHfA+vcfbGZ5YfznAO0AUvcfUNHFdndl4WvbQCuDv9cD+QAJUCNu883s3fD8+8BC4ENQBNwDMgM11NjZhnALuBX7r6vS2x3h+sYDnzf5b7/Ckx2938Lv48HgbPc/XhP3/fGxsO9/2GlkSdf3RHJPE3NRzlwKHFlesjgQSydexlFucPZ23SE5VWfcLzth4TjzxqZSW720D7HtfjOS/o8h4gklpc3IqO/5u7tv88zZk5j2NgbGZFvnecOf+18W/cu7617P/L4pGep2B/aB6eGZPZGsi0iVwDfuXsZMBYYCkyPM644HHsN8Jsu7RD5wK+BS4HHzGwEMAP4PJzzfKAMSJhxmNlEYD5Bsv4L4FIzuxR4Btjk7r8AbgNeDJPuntZzazjPTDMbDzwM7HP3mztuCdzl7lOAF4G7wvOTgLquyTWAu7/k7k8QJP9dFQJfhmPagENAXg/xyQDKGZlJUe5wAIpyh5MzIjPFEYlIutm3ZzdZeWN/dC4rbyz79uxOUUSSCtoH6SupFhF3/9DMDpjZAuBCgoQ4K87QyrAyu8fMtgJXheffd/dWoNXMmoAcd19jZhPN7BHg74CzEszZYTJB1bo5/HoKgJldA/xDGGe9mX0MXN7Dkra5++Hw9fUE1ezDMWP2u3tDeLwWWGFmw4B7gKoe5u8q3rugxOVR6RRVhfedLfW8u7Uh4fWDh1rZ23Sks4J98HD3fdhXji9g1qSSSGITkdNDYfEYWhrrflS5bGmso7B4TAqjkoGmfZC+kkqwzexGYDlB/3AlkEv8xLGty/GgLl93Pd8OZJjZQwQV5+eBDwjaT7oryf+opcLMCoFv+WlVPoNgne0x14Z0OT4WG0+c+x3tOHD3I2ZWDcwGriWopJ+ovcBogjcdg4GRwIFevF76aNakkoQJ8Xv1NeQc/QVPvFLb2YM9d9qF6sEWkUgteHBB0GtbOoesvKD39svP1rBk0aJUhyYDSPsgfSX7kOMUYK27V4aJ7WSCpDjW7Wb2BkE/9OXAfSR+cHAq8Jy7rzazceG4M7qJYQswz8yWEiTIa4DHgU3hfZ42sxLgSuBBoICg37qjvaSghzW20f3350XgdYIqem8+aqIauBtYQfBw45YT6b+WgVM2bjQXjRlFY/Mx8rLPJDtLLSIiEq2OB9jKK8qp27ybwuIxLFm0SA+2nWa0D9JXsgn2KmC1mc0GWoGPgJ/HGTcM+JTgocAH3P2AmcUZBsBvgQoze5SgPWNbgjkBcPcdZvYssJ2gMv2Wu39gZjuB583sXoJq9P3u/qWZvQbcGl6vBT7rYY1fA38zsz8D98a5/1Yzayeo4PfG/wZUmdkXwL8Dd/by9TIAsrMylViLSL+aPv0GJVKifZCmkvoUkRMRforIZnev6pcbpFD4ySEXAy+5e+lA3fd0/xSRgfBefQ0zSq5LdRgi0g9Opk8RkZOP9ockkszeOKk/B9vMzgPeTHD5fnf/dCDj6eIR4DGCHmwRERERkU79VsGW6OkdcP9TBVskfalCKd3R/pBEBvJzsEVEREREJA4l2CIiIiIiEVKCLSIiIiISISXYIiIiIiIRUoItIiIiIhIhJdgiIiIiIhFSgi0iIiIiEiEl2CIiIiIiEVKCLSIiIiISISXYIiIiIiIRUoItIiIiIhIhJdgiIiIiIhFSgi0iIiIiEiEl2CIiIiIiEYo0wTazc82soYcxy8xsWZT37Q9mlm1m70Qwz/J46zWz/9HMqvo6v4iIiIicXFTBTmwUMCHZF4cJ+gvAozHnzzSzJ4Df9TE+OUk0t7RSt7eZ5pbWVIciIqeQ6ur1zJg5jdLSi5gxcxrV1etTHZKkgPZBehqczIvMbDBQAVwM5AMO3BIzpgr4ARgPZAOPu/vL4eWJZrYNKAIq3X2ZmY0EXgCKgULgQ+Bud2/vJo6FwDzge2Cduy82s/xwnnOANmCJu2/oqCK7+7LwtQ3A1eGf64EcoASocff5wO+BQjN7G1gIbACagGNAZrieGjPLAHYBv3L3fV3Cuwn4K/BUTNiTCd7YLAIuT7Q2OTVs/+IrVm/cxdmjhrL/m6PcMfUCysaNTnVYInKSq65ez4qVKykoncOEsrG0NNaxYuVKAKZPvyHF0clA0T5IX0kl2MAVwHfuXmZmg4BNwHSgNmZccTg2H6g1s43h+fzw/Ahgt5k9BcwAPnf32Wb2M2AncEmcOQEws4nAfOCXwBFgg5ldCiwGNrn702ZWAvzFzEpPYD3jCBJ1N7MK4GFgs7vfbGbnAgZc7+4NZnYvcBdQA0wC6mKSa9z9pTDOZTHna4AaM5vbQ0zSR0++uqPXrzlw7Az+Zft/vK6p+SgHDiWuTA8ZPIilcy+jKHc4e5uOsLzqE1at29ntPc4amUlu9tBexxZr8Z2X9HkOEUmN8opyCkrnMCLfAIK/S+dQXlGuxOo0on2QvpJqEXH3D4E/mNkCglaH84GsOEMr3f24u+8BtgJXheffd/dWd28iqArnuPsaYKOZPQI8A5yVYM4Okwmq1s3u3ubuU9y9FriGoIKNu9cDH9NzpXibux9292+BeoJqdqz97t4QHq8FpprZMOAeoKqH+SVN5YzMpCh3OABFucPJGZGZ4ohE5FSwb89usvLG/uhcVt5Y9u3ZnaKIJBW0D9JXsi0iNwLLCZLrSiAXyIgztK3L8aAuX3c93w5kmNlDwG3A88AHBO0n8ebscDwmpkLgW376piGDYJ3tMdeGdDk+FhtPnPsd7Thw9yNmVg3MBq4lqKTLSSaZCu979TXMKPmP172zpZ53tzYkHH/wUCt7m450VrAPHu65D/vK8QXMmlTS69hEJH0UFo+hpbGus3IJ0NJYR2HxmBRGJQNN+yB9JdsiMgVY6+6VYWI7mSApjnW7mb1B0A99OXAfiR8cnAo85+6rzWxcOO6MbmLYAswzs6UECfIa4HGCdpX7gI4WkSuBB4ECgn7rjvaSgh7W2Eb3358XgdcJquh6ui1NzZpU0m0yvP2Lr3jildrOHuy50y5UD7aI9GjBgwuCXtvSOWTlBb23X362hiWLFqU6NBlA2gfpK9kEexWw2sxmA63AR8DP44wbBnxK8FDgA+5+wMziDAPgt0CFmT0KHAa2JZgTAHffYWbPAtsJKtNvufsHZrYTeD7sk24H7nf3L83sNeDW8Hot8FkPa/wa+JuZ/Rm4N879t5pZO0EFX05TZeNGc9GYUTQ2HyMv+0yys9QiIiI96+ivLa8op27zbgqLx7Bk0SL13Z5mtA/SV0Z7e8IP6eiT8FNENrt7Vb/cIIXCTw65GHjJ3Xt6gDIyjY2H++eHJZ2CFpHrUh2GiPSDvLwR3bUd9on+fT71aX9IIsnsjWQr2APCzM4D3kxw+X53/3Qg4+niEeAxgh5sEREREZFO/VbBlujpHXD/UwVbJH2pQind0f6QRJLZG/pNjiIiIiIiEVKCLSIiIiISISXYIiIiIiIRUoItIiIiIhIhJdgiIiIiIhFSgi0iIiIiEiEl2CIiIiIiEVKCLSIiIiISISXYIiIiIiIRUoItIiIiIhIhJdgiIiIiIhFSgi0iIiIiEiEl2CIiIiIiEVKCLSIiIiISISXYIiIiIiIRijTBNrNzzayhhzHLzGxZlPftD2aWbWbvRDDP8q7rNbO/M7MtZva5mW03swl9vYf0v+aWVur2NtPc0prqUEQkTVRXr2fGzGmUll7EjJnTqK5en+qQJAW0D9LT4FQHcBIbBSSd/JpZNvA0MAdY2eXSKuAJd19vZtcAfwL+vi+BSv/a/sVXrN64i7NHDWX/N0e5Y+oFlI0bneqwROQUVl29nhUrV1JQOocJZWNpaaxjxcrgPxXTp9+Q4uhkoGgfpK+kEmwzGwxUABcD+YADt8SMqQJ+AMYD2cDj7v5yeHmimW0DioBKd19mZiOBF4BioBD4ELjb3du7iWMhMA/4Hljn7ovNLD+c5xygDVji7hs6qsjuvix8bQNwdfjneiAHKAFq3H0+8Hug0MzeBhYCG4Am4BiQGa6nxswygF3Ar9x9X5fwbgL+CjwVE/YfgffD4/8njFN66clXd0Q2V1PzUQ4c6qhMD+ZNNv3o+pDBg1g69zKKcoezt+kIy6s+YdW6nd3OedbITHKzh/YprsV3XtKn14vIyau8opyC0jmMyDeA4O/SOZRXlCuxOo1oH6SvZFtErgC+c/cyYCwwFJgeZ1xxOPYa4Ddm1lH2ywd+DVwKPGZmI4AZwOfhnOcDZUDCDMPMJgLzgYnAL4BLzexS4Blgk7v/ArgNeDFMuntaz63hPDPNbDzwMLDP3W/uuCVwl7tPAV4E7grPTwLqYpJr3P0ld3+CIPnver7K3TvOLQf63IYi/StnZCZFucMBKModTs6IzBRHJCKnun17dpOVN/ZH57LyxrJvz+4URSSpoH2QvpKqYLv7h2Z2wMwWABcSJMRZcYZWuvtxYI+ZbQWuCs+/7+6tQKuZNQE57r7GzCaa2SPA3wFnJZizw2SCqnVz+PUUgLDt4h/COOvN7GPg8h6WtM3dD4evryeoZh+OGbPf3RvC47XACjMbBtwDVPUw/4+EVe//E/jPBG80pJeirO6+s6Wed7c2JLx+8FAre5uOdFawDx7uuQ/7yvEFzJpUElmMIpJeCovH0NJY11m5BGhprKOweEwKo5KBpn2QvpJtEbmRoPr6O6ASyAUy4gxt63I8qMvXXc+3Axlm9hBBxfl54AOC9pN4c3Y4HhNTIfAtP63KZxCssz3m2pAux8di44lzv6MdB+5+xMyqgdnAtQSV9BMStte8RNAe8+subxAkRWZNKulMht+rr2FGyXU/ur79i6944pXazh7sudMuVA+2iPTJggcXBL22pXPIygt6b7/8bA1LFi1KdWgygLQP0leyDzlOAda6e2WY2E4mSIpj3W5mbxD0GV8O3EfiBwenAs+5+2ozGxeOO6ObGLYA88xsKUGCvAZ4HNgU3udpMysBrgQeBAoI+q072ksKelhjG91/f14EXieoovfmoyV+A4wEruvl6yRFysaN5qIxo2hsPkZe9plkZ6lFRET6pqO/tryinLrNuyksHsOSRYvUd3ua0T5IX8km2KuA1WY2G2gFPgJ+HmfcMOBTgocCH3D3A2YWZxgAvwUqzOxRgvaMbQnmBMDdd5jZs8B2gsr0W+7+gZntBJ43s3sJqtH3u/uXZvYacGt4vRb4rIc1fg38zcz+DNwb5/5bzaydoIJ/QswsD/hH4F+Bjzu+F+6uj+o7yWVnZSqxFpFITZ9+gxIp0T5IUxnt7Qk/pKNPwk8R2ezuVf1ygxQKe6gvBl5y99KBum9j4+H++WFJp3gtIiKSHvLyRnTXdtgn+vf51Kf9IYkkszdO6s/BNrNG87PiAAAgAElEQVTzgDcTXL7f3T8dyHi6eAR4jKAHW0RERESkU79VsCV6egfc/1TBFklfqlBKd7Q/JJFk9kakvypdREREROR0pwRbRERERCRCSrBFRERERCKkBFtEREREJEJKsEVEREREIqQEW0REREQkQkqwRUREREQipARbRERERCRCSrBFRERERCKkBFtEREREJEJKsEVEREREIqQEW0REREQkQkqwRUREREQipARbRERERCRCg6OczMzOBTa7+7ndjFkG4O7Lorx31MwsG/iTu8/q4zzLgR861mtmFwF/BIYDB4G57r67j+GKiIiIyElCFezERgETkn2xmWWb2QvAozGXyoHl7v73wOvAf00+RJHTR3NLK3V7m2luaU11KCKRqa5ez4yZ0ygtvYgZM6dRXb0+1SHJANMeSE9JVbDNbDBQAVwM5AMO3BIzpgr4ARgPZAOPu/vL4eWJZrYNKAIq3X2ZmY0EXgCKgULgQ+Bud2/vJo6FwDzge2Cduy82s/xwnnOANmCJu2+IrZybWQNwdfjneiAHKAFq3H0+8Hug0MzeBhYCG4Am4BiQGa6nxswygF3Ar9x9X5fwbgL+CjwVE/ZUd28zs0HAGOCbROsTkcD2L75i9cZdnD1qKPu/OcodUy+gbNzoVIcl0ifV1etZsXIlBaVzmFA2lpbGOlasXAnA9Ok3pDg6GQjaA+kr2RaRK4Dv3L0sTBQ3AdOB2phxxeHYfKDWzDaG5/PD8yOA3Wb2FDAD+NzdZ5vZz4CdwCVx5gTAzCYC84FfAkeADWZ2KbAY2OTuT5tZCfAXMys9gfWMI0jU3cwqgIcJ2l1uDltfDLje3RvM7F7gLqAGmATUxSTXuPtLYZzLYs63mdl/Ctc3jCDBFzmlPPnqjsjmamo+yoFD3VelhwwexNK5l1GUO5y9TUdYXvUJq9btTDj+rJGZ5GYPjSS+xXdeEsk8IrHKK8opKJ3DiHwDCP4unUN5RbmSq9OE9kD6SqpFxN0/BP5gZguA3wHnA1lxhla6+3F33wNsBa4Kz7/v7q3u3kRQFc5x9zXARjN7BHgGOCvBnB0mE1Stm929zd2nuHstcA1BBRt3rwc+Bi7vYUnb3P2wu38L1BNUs2Ptd/eG8HgtMNXMhgH3AFU9zP8j7v7v7l4I/BfgXTM7ozevFznd5IzMpCh3OABFucPJGZGZ4ohE+m7fnt1k5Y390bmsvLHs26PHck4X2gPpK9kWkRuB5QTJdSWQC2TEGdrW5XhQl6+7nm8HMszsIeA24HngA4L2k3hzdjgeE1Mh8C0/fdOQQbDO9phrQ7ocH4uNJ879jnYcuPsRM6sGZgPXElTST4iZ3Q78N3dvD1tXhhL0ezed6BwiqRZlVfedLfW8u7Wh2zEHD7Wyt+lIZwX74OHuK95Xji9g1qSSyGIU6Q+FxWNoaazrrF4CtDTWUVg8JoVRyUDSHkhfybaITAHWuntlmNhOJkiKY91uZm8Q9ENfDtxH4gcHpwLPuftqMxsXjuuusrsFmGdmSwkS5DXA4wTtKvcBHS0iVwIPAgWE7Rhhe0lBD2tso/vvz4sEDymuc/fePHX1aDj3W2b2a6AprOSLnJZmTSrpMRne/sVXPPFKbWcP9txpF6oHW055Cx5cEPTbls4hKy/ov/3yszUsWbQo1aHJANEeSF/JJtirgNVmNhtoBT4Cfh5n3DDgU4KHAh9w9wNmFmcYAL8FKszsUeAwsC3BnAC4+w4zexbYTlCZfsvdPzCzncDzYZ90O3C/u39pZq8Bt4bXa4HPeljj18DfzOzPwL1x7r/VzNoJKvi9MTeMbynQTFC1F5FulI0bzUVjRtHYfIy87DPJzlKLiJz6OnpsyyvKqdu8m8LiMSxZtEi9t6cR7YH0ldHenvBDOvok/BSRze5e1S83SKHwk0MuBl5y954eoIxMY+Ph/vlhSaf36muYUXJdqsMQkX6Qlzeiu7bDPtG/z6c+7Q9JJJm9EekvmomamZ0HvJng8v3u/ulAxtPFI8BjBD3YIiIiIiKd+q2CLdHTO+D+pwq2SPpShVK6o/0hiSSzN/SbHEVEREREIqQEW0REREQkQkqwRUREREQipARbRERERCRCSrBFRERERCKkBFtEREREJEJKsEVEREREIqQEW0REREQkQkqwRUREREQipARbRERERCRCSrBFRERERCKkBFtEREREJEJKsEVEREREIqQEW0REREQkQkqwRUREREQiFGmCbWbnmllDD2OWmdmyKO/bH8ws28zeiWCe5fHWa2bFZnbQzM7t6z1ERERE5OShCnZio4AJyb44TNBfAB6Nc20Q8EfgZ8mHJ73R3NJK3d5mmltaUx2KiAgA1dXrmTFzGqWlFzFj5jSqq9enOiRJAe2D9DQ4mReZ2WCgArgYyAccuCVmTBXwAzAeyAYed/eXw8sTzWwbUARUuvsyMxsJvAAUA4XAh8Dd7t7eTRwLgXnA98A6d19sZvnhPOcAbcASd9/QUUV292XhaxuAq8M/1wM5QAlQ4+7zgd8DhWb2NrAQ2AA0AceAzHA9NWaWAewCfuXu+7qEdxPwV+CpOKEvAj4ALky0NonO9i++YvXGXZw9aij7vznKHVMvoGzc6FSHJSKnserq9axYuZKC0jlMKBtLS2MdK1auBGD69BtSHJ0MFO2D9JVUgg1cAXzn7mVhNXYTMB2ojRlXHI7NB2rNbGN4Pj88PwLYbWZPATOAz919tpn9DNgJXBJnTgDMbCIwH/glcATYYGaXAouBTe7+tJmVAH8xs9ITWM84gkTdzawCeBjY7O43h20cBlzv7g1mdi9wF1ADTALqYpJr3P2lMM5lMXFfCvwamAb8Yw9xpbUnX90RyTxNzUc5cChxZXrI4EEsnXsZRbnD2dt0hOVVn7Bq3c4EowezeeRWcrOH9jmuxXde0uc5RCQ9lVeUU1A6hxH5BhD8XTqH8opyJVanEe2D9JVUi4i7fwj8wcwWAL8Dzgey4gytdPfj7r4H2ApcFZ5/391b3b2JoCqc4+5rgI1m9gjwDHBWgjk7TCaoWje7e5u7T3H3WuAaggo27l4PfAxc3sOStrn7YXf/FqgnqGbH2u/uDeHxWmCqmQ0D7gGqepgfgHB8OfAP7v7DibxG+i5nZCZFucMBKModTs6IzBRHJCKnu317dpOVN/ZH57LyxrJvz+4URSSpoH2QvpJtEbkRWE6QXFcCuUBGnKFtXY4Hdfm66/l2IMPMHgJuA54naJ+4OMGcHY7HxFQIfMtP3zRkEKyzPebakC7Hx2LjiXO/ox0H7n7EzKqB2cC1BJX0EzEJGA28a2YQtMJUm9nN7u4nOEfaiKrC+86Wet7d2pDw+sFDrextOtJZwT54uPs+7CvHFzBrUkkksYmIxFNYPIaWxrrOyiVAS2MdhcVjUhiVDDTtg/SVbIvIFGCtu1eGie1kgqQ41u1m9gZBP/TlwH0kfnBwKvCcu682s3HhuDO6iWELMM/MlhIkyGuAxwnaVe4DOlpErgQeBAoI+q072ksKelhjG91/f14EXieoop/Qk3Pu/n8D53Z8HfaBT+9SGZckzJpU0m1CvP2Lr3jildrOHuy50y5M2IP9Xn0NM0qUXItI/1rw4IKg17Z0Dll5Qe/tl5+tYcmiRakOTQaQ9kH6SjbBXgWsNrPZQCvwEfDzOOOGAZ8SPBT4gLsfCCu38fwWqDCzR4HDwLYEcwLg7jvM7FlgO0Fl+i13/8DMdgLPh33S7cD97v6lmb0G3BperwU+62GNXwN/M7M/A/fGuf9WM2snqODLSaxs3GguGjOKxuZj5GWfSXaWWkREJLU6+mvLK8qp27ybwuIxLFm0SH23pxntg/SV0d6e8EM6+iT8FJHN7l7VLzdIofCTQy4GXnL3nh6gjExj4+H++WFJp6CCfV2qwxCRfpCXN6K7tsM+0b/Ppz7tD0kkmb2RbAV7QJjZecCbCS7f7+6fDmQ8XTwCPEbQgy0iIiIi0qnfKtgSPb0D7n+qYIukL1UopTvaH5JIMntDv8lRRERERCRCSrBFRERERCKkBFtEREREJEJKsEVEREREIqQEW0REREQkQkqwRUREREQipARbRERERCRCSrBFRERERCKkBFtEREREJEJKsEVEREREIqQEW0REREQkQkqwRUREREQipARbRERERCRCSrBFRERERCI0OMrJzOxcYLO7n9vNmGUA7r4syntHzcyygT+5+6w+zrMc+KFjvWY2GXgb+LdwyGfufm9f7iEiIiIiJw9VsBMbBUxI9sVmlm1mLwCPxly6DPiNu08I/yi5TmPNLa3U7W2muaU11aGIyEmouno9M2ZOo7T0ImbMnEZ19fpUhyQDTHsgPSVVwTazwUAFcDGQDzhwS8yYKuAHYDyQDTzu7i+Hlyea2TagCKh092VmNhJ4ASgGCoEPgbvdvb2bOBYC84DvgXXuvtjM8sN5zgHagCXuviG2cm5mDcDV4Z/rgRygBKhx9/nA74FCM3sbWAhsAJqAY0BmuJ4aM8sAdgG/cvd9XcK7Cfgr8FRM2JcBZ5vZ7QRV7AXu/m9I2tn+xVes3riLs0cNZf83R7lj6gWUjRud6rBE5CRRXb2eFStXUlA6hwllY2lprGPFypUATJ9+Q4qjk4GgPZC+km0RuQL4zt3LzGwQsAmYDtTGjCsOx+YDtWa2MTyfH54fAew2s6eAGcDn7j7bzH4G7AQuiTMnAGY2EZgP/BI4Amwws0uBxcAmd3/azEqAv5hZ6QmsZxxBou5mVgE8TNDucnPY+mLA9e7eYGb3AncBNcAkoC4mucbdXwrjXBZzr38H1rj7fzezecBrwJU9xCcRefLVHd1eP3DsDP5le/djAJqaj3LgUPdV6SGDB7F07mUU5Q5nb9MRlld9wqp1OxOOP2tkJrnZQ3u8d08W33lJn+cQkf5XXlFOQekcRuQbQPB36RzKK8qVXJ0mtAfSV1ItIu7+IfAHM1sA/A44H8iKM7TS3Y+7+x5gK3BVeP59d2919yaCqnCOu68BNprZI8AzwFkJ5uwwmaBq3ezube4+xd1rgWsIKti4ez3wMXB5D0va5u6H3f1boJ6gmh1rv7s3hMdrgalmNgy4B6jqYf5O7j7P3f97ePx/AePCfm9JMzkjMynKHQ5AUe5wckZkpjgiETmZ7Nuzm6y8sT86l5U3ln17dqcoIhlo2gPpK9kWkRuB5QTJdSWQC2TEGdrW5XhQl6+7nm8HMszsIeA24HngA4L2k3hzdjgeE1Mh8C0/fdOQQbDO9phrQ7ocH4uNJ879jnYcuPsRM6sGZgPXElTSexRW+/8JeMLdv0+0Fuk/PVV336uvYUZJzxXgd7bU8+7Whm7HHDzUyt6mI50V7IOHu694Xzm+gFmTSnq8t4ikh8LiMbQ01nVWLwFaGusoLB6TwqhkIGkPpK9kW0SmAGvdvTJMbCcTJMWxbjezNwj6oS8H7iPxg4NTgefcfbWZjQvHndFNDFuAeWa2lCBBXgM8TtCuch/Q0SJyJfAgUEDQb93RXlLQwxrb6P778yLwOkEV/YSeYHP3H8zsZoLe7LVmdjfwcVg5l1PIrEklPSbD27/4iideqe3swZ477UL1YItIpwUPLgj6bUvnkJUX9N9++dkalixalOrQZIBoD6SvZBPsVcBqM5sNtAIfAT+PM24Y8CnBQ4EPuPsBM4szDIDfAhVm9ihwGNiWYE4A3H2HmT0LbCeoTL/l7h+Y2U7g+bBPuh24392/NLPXgFvD67XAZz2s8Wvgb2b2Z+Ann/Th7lvNrJ2ggt8b9wCrzOx/B/YDd/fy9XKKKBs3movGjKKx+Rh52WeSnaUWERH5Dx09tuUV5dRt3k1h8RiWLFqk3tvTiPZA+spob0/4IR19En6KyGZ3r+qXG6RQ+MkhFwMvuXtPD1BGprHxcP/8sKRT0CJyXarDEJF+kJc3oru2wz7Rv8+nPu0PSSSZvRHpL5qJmpmdB7yZ4PL97v7pQMbTxSPAYwQ92CIiIiIinfqtgi3R0zvg/qcKtkj6UoVSuqP9IYkkszf0mxxFRERERCKkBFtEREREJEJKsEVEREREIqQEW0REREQkQkqwRUREREQipARbRERERCRCSrBFRERERCKkBFtEREREJEJKsEVEREREIqQEW0REREQkQkqwRUREREQipARbRERERCRCSrBFRERERCKkBFtEREREJEJKsEVEREREIjQ4ysnM7Fxgs7uf282YZQDuvizKe0fNzLKBP7n7rD7Osxz4oWO9ZjYSqAAuCofc5+47+nIPERERETl5qIKd2ChgQrIvNrNsM3sBeDTm0tPAv7l7KfBPBMm2nAaaW1qp29tMc0trqkMRkZNAdfV6ZsycRmnpRcyYOY3q6vWpDklSQPsgPSVVwTazwQSJ4cVAPuDALTFjqoAfgPFANvC4u78cXp5oZtuAIqDS3ZeFld0XgGKgEPgQuNvd27uJYyEwD/geWOfui80sP5znHKANWOLuG2Ir52bWAFwd/rkeyAFKgBp3nw/8Hig0s7eBhcAGoAk4BmSG66kxswxgF/Ard9/XJbybgL8CT3WJNwO4Ffh5GMsGM/u3ROuT9LH9i69YvXEXZ48ayv5vjnLH1AsoGzc61WGJSIpUV69nxcqVFJTOYULZWFoa61ixciUA06ffkOLoZKBoH6SvZFtErgC+c/cyMxsEbAKmA7Ux44rDsflArZltDM/nh+dHALvN7ClgBvC5u882s58BO4FL4swJgJlNBOYDvwSOABvM7FJgMbDJ3Z82sxLgL2ZWegLrGUeQqLuZVQAPE7S73By2vhhwvbs3mNm9wF1ADTAJqItJrnH3l8I4l3U5fTbQCvyjmd0KfEOQvEsKPPnqTztzDhw7g3/Z3vuOnabmoxw4lLgyPWTwIJbOvYyi3OHsbTrC8qpPWLVuZ8LxZ43MJDd7aK/jiLX4zkv6PIeIRK+8opyC0jmMyDeA4O/SOZRXlCuxOo1oH6SvpFpE3P1D4A9mtgD4HXA+kBVnaKW7H3f3PcBW4Krw/Pvu3uruTQRV4Rx3XwNsNLNHgGeAsxLM2WEyQdW62d3b3H2Ku9cC1xBUsHH3euBj4PIelrTN3Q+7+7dAPUE1O9Z+d28Ij9cCU81sGHAPUNXD/B0GE7y5+CZsEfmvwNsn+Fo5heWMzKQodzgARbnDyRmRmeKIRCSV9u3ZTVbe2B+dy8oby749u1MUkaSC9kH6SrZF5EZgOUFyXQnkAhlxhrZ1OR7U5euu59uBDDN7CLgNeB74gKD9JN6cHY7HxFQIfMtP3zRkEKyzPebakC7Hx2LjiXO/ox0H7n7EzKqB2cC1BJX0E9FEsPbV4TwbzSzLzM529/0nOIdEJF519736GmaU9L7q+86Wet7d2pDw+sFDrextOtJZwT54uPs+7CvHFzBrUkmv4xCRU0Nh8RhaGus6K5cALY11FBaPSWFUMtC0D9JXsi0iU4C17l4ZJraTCZLiWLeb2RsE/dCXA/eR+MHBqcBz7r7azMaF487oJoYtwDwzW0qQIK8BHidoV7kP6GgRuRJ4ECgg6LfuaC8p6GGNbXT//XkReJ2gin5CT625e2vYJvNfgAoz+88EbwqaTuT1cvKaNamk24R4+xdf8cQrtZ092HOnXagebJHT2IIHFwS9tqVzyMoLem+//GwNSxYtSnVoMoC0D9JXsgn2KmC1mc0m6Cn+iPDBvRjDgE8JHgp8wN0PmFmcYQD8liDpfBQ4DGxLMCcA7r7DzJ4FthNUpt9y9w/MbCfwfNgn3Q7c7+5fmtlrwK3h9Vrgsx7W+DXwNzP7M3BvnPtvNbN2ggp+b9wHPBe21xwH/gd3/6GXc8gppmzcaC4aM4rG5mPkZZ9JdpZaREROZx39teUV5dRt3k1h8RiWLFqkvtvTjPZB+spob0/4IR19En6KyGZ3r+qXG6RQ+GkgFwMvhb3UA6Kx8XD//LCkU9Aicl2qwxCRfpCXN6K7tsM+0b/Ppz7tD0kkmb0R6S+aiZqZnQe8meDy/e7+6UDG08UjwGMEPdgiIiIiIp36rYIt0dM74P6nCrZI+lKFUrqj/SGJJLM39JscRUREREQipARbRERERCRCSrBFRERERCKkBFtEREREJEJKsEVEREREIqQEW0REREQkQkqwRUREREQipARbRERERCRCSrBFRERERCKkBFtEREREJEJKsEVEREREIqQEW0REREQkQkqwRUREREQipARbRERERCRCg6OczMzOBTa7+7ndjFkG4O7Lorx31MwsG/iTu8/q4zzLgR861mtmn/If3/ehwHlAkbt/3Zf7iIiIiMjJQRXsxEYBE5J9sZllm9kLwKNdz7v7L919grtPAD4Glp4uyXVzSyt1e5tpbmlNdSgiIiel6ur1zJg5jdLSi5gxcxrV1etTHZL0M/3M01NSFWwzGwxUABcD+YADt8SMqQJ+AMYD2cDj7v5yeHmimW0DioBKd19mZiOBF4BioBD4ELjb3du7iWMhMA/4Hljn7ovNLD+c5xygDVji7htiK+dm1gBcHf65HsgBSoAad58P/B4oNLO3gYXABqAJOAZkhuupMbMMYBfwK3ff1yW8m4C/Ak8liP1a4O+BexOtL51s/+IrVm/cxdmjhrL/m6PcMfUCysaNTnVYIiInjerq9axYuZKC0jlMKBtLS2MdK1auBGD69BtSHJ30B/3M01eyLSJXAN+5e5mZDQI2AdOB2phxxeHYfKDWzDaG5/PD8yOA3Wb2FDAD+NzdZ5vZz4CdwCVx5gTAzCYC84FfAkeADWZ2KbAY2OTuT5tZCfAXMys9gfWMI0jU3cwqgIcJ2l1uDltfDLje3RvM7F7gLqAGmATUxSTXuPtLYZzLEtzz/wD+V3f/vofYIvXkqzsin7Op+SgHDnVflR4yeBBL515GUe5w9jYdYXnVJ6xat7PHuc8amUlu9tCoQgVg8Z2XRDqfiEgUyivKKSidw4h8Awj+Lp1DeUW5kq00pZ95+kqqRcTdPwT+YGYLgN8B5wNZcYZWuvtxd98DbAWuCs+/7+6t7t5EUBXOcfc1wEYzewR4BjgrwZwdJhNUrZvdvc3dp7h7LXANQQUbd68naMO4vIclbXP3w+7+LVBPUM2Otd/dG8LjtcBUMxsG3ANU9TD/j5jZOCDX3U+b/w+UMzKTotzhABTlDidnRGaKIxIRObns27ObrLyxPzqXlTeWfXt2pygi6W/6maevZFtEbgSWEyTXlUAukBFnaFuX40Fdvu56vh3IMLOHgNuA54EPCNpP4s3Z4XhMTIXAt/z0TUMGwTrbY64N6XJ8LDaeOPc72nHg7kfMrBqYDVxLUEnvjVnA6718TST6o3r7zpZ63t3a0O2Yg4da2dt0pLOCffDwifVhXzm+gFmTSiKIUkTk5FZYPIaWxrrOaiZAS2MdhcVjUhiV9Cf9zNNXsi0iU4C17l4ZJraTCZLiWLeb2RsE/dCXA/eR+MHBqcBz7r46rPBOAM7oJoYtwDwzW0qQIK8BHidoV7kP6GgRuRJ4ECgg6LfuaC8p6GGNbXT//XmRIEle5+69fWqvDPhtL19z0po1qaTHJHj7F1/xxCu1nT3Yc6ddqB5sEZEuFjy4IOi/LZ1DVl7Qj/vlZ2tYsmhRqkOTfqKfefpKNsFeBaw2s9lAK/AR8PM444YBnxI8FPiAux8wszjDgCDhrDCzR4HDwLYEcwLg7jvM7FlgO0Fl+i13/8DMdgLPh33S7cD97v6lmb0G3BperwU+62GNXwN/M7M/E+dBRHffambtBBX83ioB9iTxulNW2bjRXDRmFI3Nx8jLPpPsLLWIiIh01dFzW15RTt3m3RQWj2HJokXqxU1j+pmnr4z29oQf0tEn4aeIbHb3qn65QQqFnxxyMfCSu/f0AGVkGhsP988PSzq9V1/DjJLrUh2GiPSDvLwR3bUd9on+fT71aX9IIsnsjUh/0UzUzOw84M0El+93908HMp4uHgEeI+jBFhERERHp1G8VbIme3gH3P1WwRdKXKpTSHe0PSSSZvaHf5CgiIiIiEiEl2CIiIiIiEVKCLSIiIiISISXYIiIiIiIRUoItIiIiIhIhJdgiIiIiIhFSgi0iIiIiEiEl2CIiIiIiEVKCLSIiIiISISXYIiIiIiIRUoItIiIiIhIhJdgiIiIiIhFSgi0iIiIiEiEl2CIiIiIiEVKCLSIiIiISocFRTmZm5wKb3f3cbsYsA3D3ZVHeO2pmlg38yd1n9XGe5cAPHes1s1HAq0AR0Ao84O6f9zFcERERETlJqIKd2ChgQrIvNrNsM3sBeDTm0v8M/L/u/vfA48CzyYco/aW5pZW6vc00t7SmOhQRSVPV1euZMXMapaUXMWPmNKqr16c6JEkB7YP0lFQF28wGAxXAxUA+4MAtMWOqgB+A8UA28Li7vxxenmhm2wiquJXuvszMRgIvAMVAIfAhcLe7t3cTx0JgHvA9sM7dF5tZfjjPOUAbsMTdN8RWzs2sAbg6/HM9kAOUADXuPh/4PVBoZm8DC4ENQBNwDMgM11NjZhnALuBX7r6vS3g3AX8FnooJ+wxgRHg8HDiaaH2SGtu/+IrVG3dx9qih7P/mKHdMvYCycaNTHZaIpJHq6vWsWLmSgtI5TCgbS0tjHStWrgRg+vQbUhydDBTtg/SVbIvIFcB37l5mZoOATcB0oDZmXHE4Nh+oNbON4fn88PwIYLeZPQXMAD5399lm9jNgJ3BJnDkBMLOJwHzgl8ARYIOZXQosBja5+9NmVgL8xcxKT2A94wgSdTezCuBhgnaXm8PWFwOud/cGM7sXuAuoASYBdTHJNe7+Uhjnsph7/Qb4yMz2ASOBqT3EJqEnX90RyTxNzUc5cChRZXowQwb/fyydexlFucPZ23SE5VWfsGrdzoTznTUyk9zsoX2Oa/Gdl/R5DhE5NZRXlFNQOocR+QYQ/F06h/KKciVWpxHtg/SVVIuIu38I/MHMFgC/A84HsuIMrdT1pfwAACAASURBVHT34+6+B9gKXBWef9/dW929iaAqnOPua4CNZvYI8AxwVoI5O0wmqFo3u3ubu09x91rgGoIKNu5eD3wMXN7Dkra5+2F3/xaoJ6hmx9rv7g3h8VpgqpkNA+4BqnqYv6tngWfdvZAguX7dzLpbpwywnJGZFOUOB6Aodzg5IzJTHJGIpJt9e3aTlTf2R+ey8sayb8/uFEUkqaB9kL6SbRG5EVhOkFxXArlARpyhbV2OB3X5uuv5diDDzB4CbgOeBz4gaD+JN2eH4zExFQLf8tM3DRkE62yPuTaky/Gx2Hji3K+zlcPdj5hZNTAbuJagkn6ibgIeCOfZbmZfA38HfNKLOU5LUVV439lSz7tbGxJeP3iolb1NRzor2AcPd9+HfeX4AmZNKokkNhE5PRQWj6Glsa6zcgnQ0lhHYfGYFEYlA037IH0l2yIyBVjr7pVhYjuZICmOdbuZvUHQD305cB+JHxycCjzn7qvNbFw47oxuYtgCzDOzpQQJ8hqChwY3hffpaBG5EngQKCDot+5oLynoYY1tdP/9eRF4naCK3psn4f4ZmAW8YmbnE/Sb7+rF66WPZk0qSZgQv1dfQ87RX/DEK7WdPdhzp12oHmwRidSCBxcEvbalc8jKC3pvv/xsDUsWLUp1aDKAtA/SV7IJ9ipgtZnNJviouY+An8cZNwz4lOChwAfc/YCZxRkGwG+BCjN7FDgMbEswJwDuvsPMngW2E1Sm33L3D8xsJ/B82CfdDtzv7l+a2WvAreH1WuCzHtb4NfA3M/szcG+c+281s3aCCn5v3AM8Z2b/C8H37h53b+7lHNKPysaN5qIxo2hsPkZe9plkZ6lFRESi1dFfW15RTt3m3RQWj2HJokXquz3NaB+kr4z29oQf0tEn4aeIbHb3qn65QQqFnxxyMfCSu/f0AGVkGhsP988PSzq9V1/DjJLrUh2GiPSDvLwR3bUd9on+fT71aX9IIsnsjUh/0UzUzOw84M0El+93908HMp4uHgEeI+jBFhERERHp1G8VbIme3gH3P1WwRdKXKpTSHe0PSSSZvaHf5CgiIiIiEiEl2CIiIiIiEVKCLSIiIiISISXYIiIiIiIRUoItIiIiIhIhJdgiIiIiIhFSgi0iIiIiEiEl2CIiIiIiEVKCLSIiIiISISXYIiIiIiIRUoItIiIiIhIhJdgiIiIiIhFSgi0iIiIiEiEl2CIiIiIiERoc5WRmdi6w2d3P7WbMMgB3XxblvaNmZtnAn9x9Vh/nWQ780LFeMzsf+COQAzQB/5O77+pjuCIiIiJyklAFO7FRwIRkX2xm2Wb2AvBozKVKoNLdxwP/BKxNPkQ5WTS3tFK3t5nmltZUhyIip4jq6vXMmDmN0tKLmDFzGtXV61MdkqSA9kF6SqqCbWaDgQrgYiAfcOCWmDFVwA/AeCAbeNzdXw4vTzSzbUARQbK5zMxGAi8AxUAh8CFwt7u3dxPHQmAe8D2wzt0Xm1l+OM85QBuwxN03xFbOzawBuDr8cz1BRbkEqHH3+cDvgUIzextYCGwgqDgfAzLD9dSYWQawC/iVu+/rEt5NwF+Bp2LCLgX+WxjLR2ZWaGYl7l6faJ1yctv+xVes3riLs0cNZf83R7lj6gWUjRud6rBE5CRWXb2eFStXUlA6hwllY2lprGPFypUATJ9+Q4qjk4GifZC+km0RuQL4zt3LzGwQsAmYDtTGjCsOx+YDtWa2MTyfH54fAew2s6eAGcDn7j7bzH4G7AQuiTMnAGY2EZgP/BI4Amwws0uBxcAmd3/azEqAv5hZ6QmsZxxBou5mVgE8TNDucnPY+mLA9e7eYGb3AncBNcAkoC4mucbdXwrjXBZzrx3AHOCPZnYtcBYwGlCCHbEnX93R69ccOHYG/7L9x69raj7KgUOJK9NDBg9i6dzLKModzt6mIyyv+oRV63YmHH/WyExys4f2OrZYi++8pM9ziEhqlFeUU1A6hxH5BhD8XTqH8opyJVanEe2D9JVUi4i7fwj8wcwWAL8Dzgey4gytdPfj7r4H2ApcFZ5/391b3b2JoCqc4+5rgI1m9gjwDEHiGW/ODpMJqtbN7t7m7lPcvRa4hqCCTVgV/hi4vIclbXP3w+7+LUGimxNnzH53bwiP1wJTzWwYcA9Q1cP8Xc0FbjGzfwamAv8MfNeL18tJJmdkJkW5wwEoyh1OzojMFEckIie7fXt2k5U39kfnsvLGsm/P7hRFJKmgfZC+km0RuRFYTpBcVwK5QEacoW1djgd1+brr+XYgw8weAm4Dngc+IGg/iTdnh+MxMRUC3/LTNw0ZBOtsj7k2pMvxsdh44tzvaMeBux8xs2pgNnAtQSX9RA0GZrn7d2H1/wHgX3vxejlByVR436uvYUbJj1/3zpZ63t3akPA1Bw+1srfpSGcF++Dh7vuwrxxfwKxJJb2OTUTSR2HxGFoa6zorlwAtjXUUFo9JYVQy0LQP0leyLSJTgLXuXhkmtpMJkuJYt5vZGwT90JcD95H4wcGpwHPuvtrM/v/27j+6qjq99/g7CEYgkIKJkJAKZhgfB3ANwVGLDOioeAVEcRRbdJaDwjgg1aWthlnUWq62XKUdqzNmcpVR0OGHWnVciJELXmWJgFYQyy30PjaXEssvTcAGgpCBMfePvZMJx/MDk51zyOHzWivLc/b+nn2e7zlfT57z8OydoeG405LEsBaYYWYPEiTIy4CHCdpVpgHNLSKjgJlAEUG/dXN7SVGKOR4j+evzLPAiQRX9m5zZNg94gaAPezqw0d33fYPHS5pNGl2aNCHesHUvjyze1NKDPXXceerBFpGkZs2cFfTalk0hrzDovd2zeRlzysszHZqkkdZB9mprgr0AWGpmk4FG4H3gnDjjegAbCU4KvMPd95lZnGEAPA5Umtl9wEFgfYJjAuDuH5nZk8AGgsr0q+7+lpltA54O+6SbgOnuvsfMXgBuCPdvAjanmONnwKdm9g5wW5znX2dmTQQV/G9iNvB82Ju9i6BlRDqxkUP7M2RgH2rrj1CYfwb5eWoREZHkmvtrKyorqF5TQ3HJQOaUl6vv9hSjdZC9cpqaEl6ko13Cq4iscfdFHfIEGRReOWQY8Ly7pzqBMjK1tQc75s2SFkGLyFWZDkNEOkBhYa9kbYftos/nzk/rQxJpy9qI9A/NRM3MvgW8kmD3dHffmM54WrkHuJ+gB1tEREREpEWHVbAlevoG3PFUwRbJXqpQSjJaH5JIW9aG/pKjiIiIiEiElGCLiIiIiERICbaIiIiISISUYIuIiIiIREgJtoiIiIhIhJRgi4iIiIhESAm2iIiIiEiElGCLiIiIiERICbaIiIiISISUYIuIiIiIREgJtoiIiIhIhJRgi4iIiIhESAm2iIiIiEiElGCLiIiIiERICbaIiIiISIS6RnkwMxsErHH3QUnGzAVw97lRPnfUzCwfeM7dJ7Xx8aOAx4FuwD7gdnevMbM/ApYApUAtcJO7740obBERERHJMFWwE+sDDG/H45cA09x9eHj7F+H2vwXWuvt3gAXAE+2KshOrb2ikelc99Q2NmQ5FRCTtqqpWMGHiOMrKhjBh4jiqqlZkOiTJAK2D7NSmCraZdQUqgWFAP8CBH8aMWQR8BZwP5AMPu/tvwt0Xmdl6YACw0N3nmllv4BmgBCgG3gVudfemJHHcC8wAfg+87u6zzaxfeJyzgWPAHHdfGVs5N7MdwGXhz9VAX4Kq8ip3v5MgIS42s98C9wIrgTrgCJAbzmeVmeUAnwCXuvvu8Ni5wAPuviUMdQtwV3h7AjAmvL0MqDCzbu5+NNE8s9GGrXtZuvoTzurTnc+/OMzNY89l5ND+mQ5LRCQtqqpWMG/+fIrKpjB85GAaaquZN38+AOPHX5Ph6CRdtA6yV1tbRC4BfufuI82sC/A2MB7YFDOuJBzbD9hkZqvD7f3C7b2AGjP7OUHi+bG7Tzaz04FtwIg4xwTAzC4C7gS+BxwCVprZBcBs4G13f8zMSoH3zKzsBOYzlCBRdzOrBO4maHe5Pmx9MeBqd99hZrcBPwJWAaOB6ubkGsDdG4HFYZxdgLnAa+HuYmBPOO6YmR0ACoGWx2fSo0s+iuQ4dfWH2XcgcWW6W9cuPDj1QgYU9GRX3SEeWvQhC17flvSYZ/bOpSC/e7vimn3LiHY9XkQkChWVFRSVTaFXPwMI/ls2hYrKCiVWpxCtg+zVphYRd38X+JWZzSJocfg2kBdn6EJ3P+ruO4F1wPfD7W+6e6O71xFUhfu6+zJgtZndA/wSODPBMZuNIaha17v7MXe/0t03AZcTVLBx9+3AB8DFKaa03t0PuvuXwHaCanasz919R3j7JWCsmfUAfgwsinfQ8IvCEoIvMvPCzTlxhn6VIr6s07d3LgMKegIwoKAnfXvlZjgiEZH02b2zhrzCwcdtyysczO6dNRmKSDJB6yB7tbVF5FrgIYLkeiFQQPzE8Vir211a3W+9vQnIMbO7gBuBp4G3CNpP4h2z2XEtFWZWDHzJ17805BDMsylmX7dWt4/ExhPn+Q4333D3Q2ZWBUwGriCopB/HzPKA5QQnOF7XqgVkF9Af2Bm22vQOx5wUoqrwvrZ2O8vX7Ui4f/+BRnbVHWqpYO8/mLoPe9T5RUwaXRpJfCIimVRcMpCG2uqWyiVAQ201xSUDMxiVpJvWQfZqa4vIlcBL7r4wTGzHECTFsW4ys5cJ+qEvBqaR+MTBscBT7r7UzIaG405LEsNaYIaZPUiQIC8DHiZoV5kGNLeIjAJmAkUE/dbN7SVFKeZ4jOSvz7PAiwRV9HjZ4WKgGvhpTB95FXArQUX7TwlOeMy6/utJo0uTJsMbtu7lkcWbWnqwp447Tz3YInLKmDVzVtBrWzaFvMKg93bP5mXMKS/PdGiSRloH2autCfYCYKmZTQYagfeBc+KM6wFsJDgp8A5332dmcYYBwSXtKs3sPuAgsD7BMQFw94/M7ElgA0Fl+lV3f8vMtgFPh33STcB0d99jZi8AN4T7NwGbU8zxM+BTM3sHuC3O868zsyaCCv5xwp7v6wj6yDeHc97t7uOBvwYWmdlW4L+AW1LEkZVGDu3PkIF9qK0/QmH+GeTnqUVERE4dzf21FZUVVK+pobhkIHPKy9V3e4rROsheOU1NCS/S0S7hVUTWuPuiDnmCDAqvHDIMeN7dU51AGZna2oMd82ZJize2r2JC6VWZDkNEOkBhYa9kbYftos/nzk/rQxJpy9qI9A/NRM3MvgW8kmD3dHffmM54WrkHuJ+gB1tEREREpEWHVbAlevoG3PFUwRbJXqpQSjJaH5JIW9aG/pKjiIiIiEiElGCLiIiIiERICbaIiIiISISUYIuIiIiIREgJtoiIiIhIhJRgi4iIiIhESAm2iIiIiEiElGCLiIiIiERICbaIiIiISISUYIuIiIiIREgJtoiIiIhIhJRgi4iIiIhESAm2iIiIiEiElGCLiIiIiESoa5QHM7NBwBp3H5RkzFwAd58b5XNHzczygefcfVIbHz8KeBzoBuwDbnf3mlb7bwfGuPvUCMIVERERkZOEKtiJ9QGGt+PxS4Bp7j48vP0LADM7w8weAZ5of4iSTvUNjVTvqqe+oTHToYhIFqiqWsGEieMoKxvChInjqKpakemQJAO0DrJTmyrYZtYVqASGAf0AB34YM2YR8BVwPpAPPOzuvwl3X2Rm64EBwEJ3n2tmvYFngBKgGHgXuNXdm5LEcS8wA/g98Lq7zzazfuFxzgaOAXPcfWVs5dzMdgCXhT9XA32BUmCVu99JkBAXm9lvgXuBlUAdcATIDeezysxygE+AS919d3jsXOABd98ShroFuCu8PYbgi005cHHiV1lOJhu27mXp6k84q093Pv/iMDePPZeRQ/tnOiwR6aSqqlYwb/58isqmMHzkYBpqq5k3fz4A48dfk+HoJF20DrJXW1tELgF+5+4jzawL8DYwHtgUM64kHNsP2GRmq8Pt/cLtvYAaM/s5MAH42N0nm9npwDZgRJxjAmBmFwF3At8DDgErzewCYDbwtrs/ZmalwHtmVnYC8xlKkKi7mVUCdxO0u1wftr4YcLW77zCz24AfAauA0UB1c3IN4O6NwOIwzi7AXOC1cN8qYJWZTU0Rk5ygR5d81O5j1NUfZt+BRqArr/D21/Z369qFB6deyICCnuyqO8RDiz5kwevbkh7zzN65FOR3b3dss28Z0e5jiMjJpaKygqKyKfTqZwDBf8umUFFZocTqFKJ1kL3a1CLi7u8CvzKzWQStDt8G8uIMXejuR919J7AO+H64/U13b3T3OoKqcF93XwasNrN7gF8CZyY4ZrMxBFXrenc/5u5Xuvsm4HKCCjbuvh34gNSV4vXuftDdvwS2E1SzY33u7jvC2y8BY82sB/BjYFG8g4ZfFJYQfJGZlyIGOYn17Z3LgIKeAAwo6EnfXrkZjkhEOrPdO2vIKxx83La8wsHs3lmT4BGSjbQOsldbW0SuBR4iSK4XAgVATpyhx1rd7tLqfuvtTUCOmd0F3Ag8DbxF0H4S75jNjsbEVAx8yde/NOQQzLMpZl+3VrePxMYT5/kON99w90NmVgVMBq4gqKQfx8zygOUEJzhe5+5HY8dINKKo8L62djvL1+1IuH//gUZ21R1qqWDvP5i6D3vU+UVMGl3a7thEJPsUlwykoba6pXIJ0FBbTXHJwAxGJemmdZC92toiciXwkrsvDBPbMQRJcaybzOxlgn7oi4FpJD5xcCzwlLsvNbOh4bjTksSwFphhZg8SJMjLgIcJ2lWmAc0tIqOAmUARQb91c3tJUYo5HiP56/Ms8CJBFT1etrUYqAZ+mqyPXE4Ok0aXMml0KW9sX8WE0qu+tn/D1r08snhTSw/21HHnqQdbRNps1sxZQa9t2RTyCoPe2z2blzGnvDzToUkaaR1kr7Ym2AuApWY2GWgE3gfOiTOuB7CR4KTAO9x9n5nFGQYEl7SrNLP7gIPA+gTHBMDdPzKzJ4ENBJXpV939LTPbBjwd9kk3AdPdfY+ZvQDcEO7fBGxOMcfPgE/N7B3gtjjPv87Mmggq+McJe76vI+gj3xzOebe7j0/xnHKSGjm0P0MG9qG2/giF+WeQn6cWERFpu+b+2orKCqrX1FBcMpA55eXquz3FaB1kr5ympo4proZXEVnj7os65AkyKLxyyDDgeXdPdQJlZGprD6oS3sESVbBFpPMrLOyVrO2wXfT53PlpfUgibVkbkf6hmaiZ2beAVxLsnu7uG9MZTyv3APcT9GCLiIiIiLTosAq2RE/fgDueKtgi2UsVSklG60MSacva0F9yFBERERGJkBJsEREREZEIKcEWEREREYmQEmwRERERkQgpwRYRERERiZASbBERERGRCCnBFhERERGJkBJsEREREZEIKcEWEREREYmQEmwRERERkQgpwRYRERERiZASbBERERGRCCnBFhERERGJkBJsEREREZEIKcEWEREREYlQ1ygPZmaDgDXuPijJmLkA7j43yueOmpnlA8+5+6Q2Pn4U8DjQDdgH3O7uNWb2HeBpoBdwGJjp7h9HFLaIiIiIZJgq2In1AYa34/FLgGnuPjy8/Ytw+wLg0XD7XwHPtSvKTqq+oZHqXfXUNzRmOhQRkYyoqlrBhInjKCsbwoSJ46iqWpHpkCQDtA6yU5sq2GbWFagEhgH9AAd+GDNmEfAVcD6QDzzs7r8Jd19kZuuBAcBCd59rZr2BZ4ASoBh4F7jV3ZuSxHEvMAP4PfC6u882s37hcc4GjgFz3H1lbOXczHYAl4U/VwN9gVJglbvfSZAQF5vZb4F7gZVAHXAEyA3ns8rMcoBPgEvdfXd47FzgAXffEoa6BbgrvP1r4M1W289ONL9stWHrXpau/oSz+nTn8y8Oc/PYcxk5tH+mwxIRSZuqqhXMmz+forIpDB85mIbaaubNnw/A+PHXZDg6SRetg+zV1haRS4DfuftIM+sCvA2MBzbFjCsJx/YDNpnZ6nB7v3B7L6DGzH4OTAA+dvfJZnY6sA0YEeeYAJjZRcCdwPeAQ8BKM7sAmA287e6PmVkp8J6ZlZ3AfIYSJOpuZpXA3QTtLteHrS8GXO3uO8zsNuBHwCpgNFDdnFwDuHsjsDiMswswF3gt3Leo1fM+1Lz9ZPDoko8iOU5d/WH2HUhcme7WtQsPTr2QAQU92VV3iIcWfciC17clHH9m71wK8ru3O67Zt4xo9zFERKJQUVlBUdkUevUzgOC/ZVOoqKxQYnUK0TrIXm1KsN39XTPbZ2azgPOAbwN5cYYudPejwE4zWwd8P9z+ZpiENppZHdDX3ZeZ2UVmdg/wHeDMBMdsNoagal0f3r8SwMwuB34SxrndzD4ALk4xpfXufjB8/HaCavbBmDGfu/uO8PZLwDwz6wH8GFgU76DhF4XnCF7nea225wB/D/wJ8IMUsWWdvr1zGVDQE4ABBT3p2yuXz744nOGoRETSZ/fOGoaPHHzctrzCwVSvqclQRJIJWgfZq60tItcSVF+fABYCBUBOnKHHWt3u0up+6+1NQI6Z3QXcSHAC4FsE7SfxjtnsaExMxcCXfL2vPIdgnk0x+7q1un0kNp44z9eSAbr7ITOrAiYDVxBU0o9jZnnAcoITHK8Lv2g0t9c8T9Ae84NWXxAyLqoK72trt7N83Y6E+/cfaGRX3aGWCvb+g8n7sEedX8Sk0aWRxCYicjIoLhlIQ211S+USoKG2muKSgRmMStJN6yB7tbVF5ErgJXdfGCa2YwiS4lg3mdnLBH3GFwPTSHzi4FjgKXdfamZDw3GnJYlhLTDDzB4kSJCXAQ8TtKtMA5pbREYBM4Eign7r5vaSohRzPEby1+dZ4EWCKnq8DHExUA38NKaP/B+A3sBVCR7X6U0aXZo0Id6wdS+PLN7U0oM9ddx56sEWkVPKrJmzgl7bsinkFQa9t3s2L2NOeXmmQ5M00jrIXm1NsBcAS81sMtAIvA+cE2dcD2AjwUmBd7j7PjOLMwwILmlXaWb3EbRnrE9wTADc/SMzexLYQFCZftXd3zKzbcDTYZ90EzDd3feY2QvADeH+TcDmFHP8DPjUzN4Bbovz/OvMrImggn+csOf7OoI+8s3hnHcTtJP8OfAfwAfNr0V4RZFTxsih/RkysA+19UcozD+D/LzcTIckIpJWzf21FZUVVK+pobhkIHPKy9V3e4rROsheOU1NCS/S0S7hVUTWxJzUlxXCHuphwPPunuoEysjU1h7smDdLWryxfRUTSq/KdBgi0gEKC3slaztsF30+d35aH5JIW9ZGpH9oJmpm9i3glQS7p7v7xnTG08o9wP0EPdgiIiIiIi06rIIt0dM34I6nCrZI9lKFUpLR+pBE2rI29JccRUREREQipARbRERERCRCSrBFRERERCKkBFtEREREJEJKsEVEREREIqQEW0REREQkQkqwRUREREQipARbRERERCRCSrBFRERERCKkBFtEREREJEJKsEVEREREIqQEW0REREQkQkqwRUREREQipARbRERERCRCXaM8mJkNAta4+6AkY+YCuPvcKJ87amaWDzzn7pPa+PhRwONAN2AfcLu715jZEODXQE9gPzDV3WsiCltEREREMkwV7MT6AMPb8fglwDR3Hx7e/kW4vQJ4yN2/C7wI/I92RSnUNzRSvaue+obGTIciInLCqqpWMGHiOMrKhjBh4jiqqlZkOiTJAK2D7NSmCraZdQUqgWFAP8CBH8aMWQR8BZwP5AMPu/tvwt0Xmdl6YACw0N3nmllv4BmgBCgG3gVudfemJHHcC8wAfg+87u6zzaxfeJyzgWPAHHdfGVs5N7MdwGXhz9VAX6AUWOXudxIkxMVm9lvgXmAlUAccAXLD+awysxzgE+BSd98dHjsXeMDdt4ShbgHuCm+PdfdjZtYFGAh8keSllhQ2bN3L0tWfcFaf7nz+xWFuHnsuI4f2z3RYIiJJVVWtYN78+RSVTWH4yME01FYzb/58AMaPvybD0Um6aB1kr7a2iFwC/M7dR4aJ4tvAeGBTzLiScGw/YJOZrQ639wu39wJqzOznwATgY3efbGanA9uAEXGOCYCZXQTcCXwPOASsNLMLgNnA2+7+mJmVAu+ZWdkJzGcoQaLuZlYJ3E3Q7nJ92PpiwNXuvsPMbgN+BKwCRgPVzck1gLs3AovDOLsAc4HXwn3HzOyPwvn1IEjws8qjSz6K7Fh19YfZdyBxZbpb1y48OPVCBhT0ZFfdIR5a9CELXt+W9Jhn9s6lIL973H37jpzGv25IHv/sW0akDlxEJImKygqKyqbQq58BBP8tm0JFZYUSq1OI1kH2alOLiLu/C/zKzGYBTwDfBvLiDF3o7kfdfSewDvh+uP1Nd2909zqCqnBfd18GrDaze4BfAmcmOGazMQRV63p3P+buV7r7JuByggo27r4d+AC4OMWU1rv7QXf/EthOUM2O9bm77whvvwSMNbMewI+BRfEOGn5RWELwRWZe83Z3/y93Lwb+DFhuZqeliE8S6Ns7lwEFPQEYUNCTvr1yMxyRiEhqu3fWkFc4+LhteYWD2b1Tp+ScSrQOsldbW0SuBR4iSK4XAgVATpyhx1rd7tLqfuvtTUCOmd0F3Ag8DbxF0H4S75jNjsbEVAx8yde/NOQQzLMpZl+3VrePxMYT5/kON99w90NmVgVMBq4gqKQfx8zygOUEJzhe5+5Hw+03Af/k7k1h60p3gn7vusRT7VyirPC+tnY7y9ftSLh//4FGdtUdaqlg7z+Yug971PlFTBpdGnffG9tXMaFUFWoR6VjFJQNpqK1uqVwCNNRWU1wyMINRSbppHWSvtraIXAm85O4Lw8R2DEFSHOsmM3uZoB/6YmAaiU8cHAs85e5LzWxoOC5ZZXctMMPMHiRIkJcBDxO0q0wDmltERgEzgSLCdoywvaQoxRyPkfz1eZbgJMXXw5aQWIuBauCnMX3k94XHftXMfgDUjAZ22AAAEclJREFUhZV8iWPS6NKEyTAEPdiPLN7U0oM9ddx56sEWkZPerJmzgl7bsinkFQa9t3s2L2NOeXmmQ5M00jrIXm1NsBcAS81sMtAIvA+cE2dcD2AjwUmBd7j7PjOLMwwILmlXaWb3AQeB9QmOCYC7f2RmTwIbCCrTr7r7W2a2DXg67JNuAqa7+x4zewG4Idy/CdicYo6fAZ+a2TvAbXGef52ZNRFU8I8T9nxfR9BnvTmc8253Hw9MDeN7EKgnqNpLG40c2p8hA/tQW3+EwvwzyM9Ti4iInPya+2srKiuoXlNDcclA5pSXq+/2FKN1kL1ympoSXqSjXcKriKxx90Ud8gQZFF45ZBjwvLunOoEyMrW1BzvmzZIWQYvIVZkOQ0Q6QGFhr2Rth+2iz+fOT+tDEmnL2oj0D81Ezcy+BbySYPd0d9+YznhauQe4n6AHW0RERESkRYdVsCV6+gbc8VTBFsleqlBKMlofkkhb1ob+kqOIiIiISISUYIuIiIiIREgJtoiIiIhIhJRgi4iIiIhESAm2iIiIiEiElGCLiIiIiERICbaIiIiISISUYIuIiIiIREgJtoiIiIhIhJRgi4iIiIhESAm2iIiIiEiElGCLiIiIiERICbaIiIiISISUYIuIiIiIREgJtoiIiIhIhLpGeTAzGwSscfdBScbMBXD3uVE+d9TMLB94zt0ntfHxo4DHgW7APuB2d69ptb8E2AKMcPcd7Y9YRERERE4GqmAn1gcY3o7HLwGmufvw8PYvmneYWRfg18Dp7YpQvqa+oZHqXfXUNzRmOhQRkaSqqlYwYeI4ysqGMGHiOKqqVmQ6JMkArYPs1KYKtpl1BSqBYUA/wIEfxoxZBHwFnA/kAw+7+2/C3ReZ2XpgALDQ3eeaWW/gGaAEKAbeBW5196YkcdwLzAB+D7zu7rPNrF94nLOBY8Acd18ZWzk3sx3AZeHP1UBfoBRY5e53EiTExWb2W+BeYCVQBxwBcsP5rDKzHOAT4FJ33x0eOxd4wN23hKFuAe5qFXo58BZwXqK5yTe3Yetelq7+hLP6dOfzLw5z89hzGTm0f6bDEhH5mqqqFcybP5+isikMHzmYhtpq5s2fD8D48ddkODpJF62D7NXWFpFLgN+5+8iwGvs2MB7YFDOuJBzbD9hkZqvD7f3C7b2AGjP7OTAB+NjdJ5vZ6cA2YEScYwJgZhcBdwLfAw4BK83sAmA28La7P2ZmpcB7ZlZ2AvMZSpCou5lVAncTtLtcH7a+GHC1u+8ws9uAHwGrgNFAdXNyDeDujcDiMM4uwFzgtfD+BcAPgHHAn6eIK2s8uuSjdh+jrv4w+w4krkx369qFB6deyICCnuyqO8RDiz5kwevbEo4/s3cuBfndj9u278hp/OuGbxbr7FtGfKPxIiIVlRUUlU2hVz8DCP5bNoWKygolVqcQrYPs1aYWEXd/F/iVmc0CngC+DeTFGbrQ3Y+6+05gHfD9cPub7t7o7nUEVeG+7r4MWG1m9wC/BM5McMxmYwiq1vXufszdr3T3TcDlBBVs3H078AFwcYoprXf3g+7+JbCdoJod6/NWvdIvAWPNrAfwY2BRvIOGXxSWEHyRmReOrwB+4u5fpYhJvqG+vXMZUNATgAEFPenbKzfDEYmIxLd7Zw15hYOP25ZXOJjdO2sSPEKykdZB9mpri8i1wEMEyfVCoADIiTP0WKvbXVrdb729Ccgxs7uAG4GnCdonhiU4ZrOjMTEVA1/y9S8NOQTzbIrZ163V7SOx8cR5vsPNN9z9kJlVAZOBKwgq6ccxszxgOcEJjte5+1EzuxzoDyw3MwhaYarM7Hp398RT7fyiqPK+tnY7y9ftSLh//4FGdtUdaqlg7z+YvA971PlFTBpdety2N7avYkKpKtIi0rGKSwbSUFvdUrkEaKitprhkYAajknTTOshebW0RuRJ4yd0XhontGIKkONZNZvYyQT/0xcA0Ep84OBZ4yt2XmtnQcNxpSWJYC8wwswcJEuRlwMME7SrTgOYWkVHATKCIoN+6ub2kKMUcj5H89XkWeJGgih4vk1sMVAM/be4jd/f/BQxqHhD2gY/XVUROzKTRpV9LiFvbsHUvjyze1NKDPXXceerBFpGT0qyZs4Je27Ip5BUGvbd7Ni9jTnl5pkOTNNI6yF5tTbAXAEvNbDLQCLwPnBNnXA9gI8FJgXe4+76wchvP40Clmd0HHATWJzgmAO7+kZk9CWwgqEy/6u5vmdk24OmwT7oJmO7ue8zsBeCGcP8mYHOKOX4GfGpm7wC3xXn+dWbWRFDBP07Y830dQR/55nDOu919fIrnlHYYObQ/Qwb2obb+CIX5Z5CfpxYRETk5NffXVlRWUL2mhuKSgcwpL1ff7SlG6yB75TQ1JbxIR7uEVxFZ4+6LOuQJMii8csgw4Hl3T3UCZWRqaw92zJslLYIWkasyHYaIdIDCwl7J2g7bRZ/PnZ/WhyTSlrUR6R+aiZqZfQt4JcHu6e6+MZ3xtHIPcD9BD7aIiIiISIsOq2BL9PQNuOOpgi2SvVShlGS0PiSRtqwN/SVHEREREZEIKcEWEREREYmQEmwRERERkQgpwRYRERERiZASbBERERGRCCnBFhERERGJkBJsEREREZEIKcEWEREREYmQEmwRERERkQgpwRYRERERiZASbBERERGRCCnBFhERERGJkBJsEREREZEIKcEWEREREYmQEmwRERERkQgpwRYRERERiZASbBERERGRCCnBFhERERGJkBJsEREREZEIKcEWEREREYmQEmwRERERkQgpwRYRERERiZASbBERERGRCCnBFhERERGJkBJsEREREZEIKcEWEREREYmQEmwRERERkQgpwRYRERERiZASbBERERGRCCnBFhERERGJkBJsEREREZEIKcGOiJnlm9lrmY5DRORkVN/QSPWueuobGjMdipxkqqpWMGHiOMrKhjBh4jiqqlZkOqS0OtXnn626ZjqALNIHGJ7pIERETjYbtu5l6epPOKtPdz7/4jA3jz2XkUP7ZzosOQlUVa1g3vz5FJVNYfjIwTTUVjNv/nwAxo+/JsPRdbxTff7ZLKepqSnTMWQFM1sOXA28AWwDrgD6AnXAD919r5k1uXtOOH4qcJm7Tz3R56itPag3q4O9sX0VE0qvynQYIiedR5d8dMJj6+oPs+/AHyrV3bp24cGpFzKgoCe76g7x0KIPOXrsq5b9Z/bOpSC/+wkde/YtI0486BiFhb1y2vzgFPT53DYTJo6jx+Br6dXPWrYd/Mz5sno5b7z+ZlpjycT6OJnmL4m1ZW2oRSQ6dwO7gfuB84BL3P1coBq4JZOBiYhkUt/euQwo6AnAgIKe9O2Vm+GI5GSxe2cNeYWDj9uWVziY3TtrMhRRep3q889mahGJmLtXm9lfAtPNzICRwP/LcFgiIu3yTSrHr63dzvJ1O1ru7z/QyK66Qy0V7P0Hj+/DHnV+EZNGl0YVqnQixSUDaaitPq6C21BbTXHJwAxGlT6n+vyzmRLsiJnZBcAy4DHgZeD3QE6r/Tnu3gR0y0yEIiIda9Lo0uMS5g1b9/LI4k0tPdhTx52nHmwBYNbMWUHPcdkU8gqDHuQ9m5cxp7w806Glxak+/2ymBDs6xwhez0uBNe7+P80sH6gEXg/H1AFDzWwrcC2wLyORioik0cih/RkysA+19UcozD+D/Dy1iEig+US+isoKqtfUUFwykDnl5afMCX6n+vyzmRLs6HwGfApMBHqY2RbgKLAFOCcc8zNgBbAXeA8oyECcIiJpl5+Xq8Ra4ho//ppTOqE81eefrZRgR8TdjwKXpBjzDPBMeiISERERkUzQVURERERERCKkBFtEREREJEJKsEVEREREIqQEW0REREQkQkqwRUREREQipARbRERERCRCSrBFRERERCKk62B3Hl27dMlJPUraJe/0Huh1Fslag4CdBH95N0r6fM4Og9D6kPgG8Q3XRk5TU1OHRSORGgT8R6aDEBHp5M4BdkR8zEHo8zlbaH1IIt9obSjB7jy6AiWZDkJEpJPrkAol+nzOFlofkogq2CIiIiIimaKTHEVEREREIqQEW0REREQkQkqwRUREREQipARbRERERCRCSrBFRERERCKkBFtEREREJEJKsEVEREREIqQ/lS7HMbOzgcXAWYADt7h7Q8yYImAh0B/4CrjP3d9Od6ztYWY3Aw8ApwP/6O4VMfuHAwuAfOBdYIa7R/3HB9LmBOZ7HfDfgRyCvzh2m7t/kfZAI5Bqrq3GTQCedPdz0hlf1E7gvTXgKaAPsBf4s2x9b81sBMFcTwf+E/iRu/9XpuPqTMysN7AeuMbdd5jZlcBjQHfgRXd/IBwX9zMy0e8QM/sjYAlQCtQCN7n73jRP76QV+7pnOJxTgpn9DXBTePcNdy+P8viqYEusXwG/cvfzgI3AX8cZ8/fACncfDkwBlprZaWmMsV3MbADwd8D3ge8Cd5jZkJhhi4G73P1cgqTzJ+mNMjqp5ht+sFcCE9z9u8AWYG4GQm23E3xvMbN+wD8QvLed1gm8tznAcuCR8L3dDPwsE7G21wm+t08AD4ZzdeC+kySuTsHMLgbeA84N73cHngWuA74DXGhm48LhiT4jE/0O+Vtgrbt/hyAxf6LjZ9Q5xL7u0vHCL45XAWXAcOACM7s+yudQgi0tzKwbMAZ4Ody0CJgcZ+irBJUIgGrgDCCvo+OL0JXA2+6+390PEcz3xuadZjYQ6O7u74ebFhH/degsks4X6Abc6e67wvtbgLPTHGNUUs212a8JKvadXar5jgAOufvK8P48oLNWV0/kvT0N6B3e7gEcPkni6ix+AswCdof3LwL+3d3/I/wXvMXA5ESfkSl+h0zgD783lgHjwvHy9dddOt4e4C/d/XfufhT4NyL+vacWEWmtADjQqhViD1ASO8jdX2119z5gs7vXpyG+qBQTzK3ZHoJfJMn2f+116ESSztfd9wGvQUvF6mfAL9MZYIRSvbeY2d3AR8D7dH6p5jsY2GtmzxFUav4PcFf6wotUyvcW+AtgtZk9DhwCLj5J4uoU3H06QNBVBCT+LEy0PdnvkJbHhK0kB4BClFTGe92lg7n71ubbZvZt4E+BS6J8DiXYpygzmwz8Y8zmT+IM/SrJMe4BfgpcGmFo6RCvLeCrb7C/szmh+ZhZPkGi/S/u/lyHR9Uxks7VzIYBNwBX0Lm/NDVL9d52BS4Dxrj7RjN7mKCfdmrHhxa5VO9td+AZ4Ap3/2cz+wvgeYLKacbi6uQSze2bbk92LJGMMbOhwBsE55L9e5THVovIKcrd/8ndS1r/AP8N6N2qn7qIBNUFM5tP8M9aY9z9P9MTdWR2EZyg2Sx2nqn2dzYp5xOeuLoW+BdgevpCi1yquU4Ot20EqoBiM1ubvvAil2q+ewn+iX9jeH8ZnbS6Suq5DgMOu/s/h/efIvhykem4OrNEc0u0vZbEv0NaHmNmXQlaefZ1WOQiKZjZKOB/Az/riKKSEmxpEfYhrSX4pxKAW4E3Y8eFlesfAKPcfWf6IozMW8AVZlZoZj0IKprNPaq4ew1wJPyfDxK8Dp1I0vmGvwxXAC+5+z3u3pShOKOQ6r39G3c/NzxBdzyw291HZyjWKCSdL8FVCQrN7Lvh/YnApjTHGJVUc60G/tj+8O/s1wEfngRxdWYfEFyIZnD4OXEz8Gaiz8gUv0OqwvuE+9eG40XSzsz+mOBfbG929xc64jmUYEusOwnOgt8GjCa49BRmNsPMHgqvSvA3BJdgWmNmH4c/xZkL+ZsJT+b7K+Ad4GNgafhPylVm9r1w2C3AP5rZvwE9gV9kJtr2O4H5XkvQn3tjq/fz1xkMuc1O8L3NGqnm6+6HgeuBBWa2Fbgc+MvMRdx2JzDXLwhaX14ysy3A7cBtmYqro583Hdz9CMFr+gqwDfi//OEExkSfkXF/hxBcTeRPwnV4J8FJfSKZch/BBRoea/V7b0aUT5DT1NSZi1UiIiIiIicXVbBFRERERCKkBFtEREREJEJKsEVEREREIqQEW0REREQkQkqwRUREREQipARbRERERCRCSrBFRERERCKkBFtEREREJEL/H1Z/EX/AmxDfAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 720x1036.8 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = az.plot_forest(ror_robust_trace, r_hat=True, eff_n=True, combined=True,\n",
    "                   rope=(0, 0))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Values of the Gelman-Rubin statistic (r_hat) are close to 1 and the the effective number of draws for each marginal parameter distribution (eff_n) are acceptible, as for the previous model."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### In-Sample Prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 10000/10000 [02:02<00:00, 81.45it/s]\n",
      "20000it [00:04, 4292.03it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE = 0.14114484400693203\n",
      "Deviance = -6274.349036693466\n",
      "% observations in 95.0% prediction range = 95.59880239520957\n"
     ]
    },
    {
     "data": {
      "image/png": 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AimOpRGnBPCro+DYgiJISkKSFwfE04f7ejMAxWBt4dFoW4zAjy0qEkOiqggachClSrVONX0WA72Sesf1wTBznmIZKjMI8zvFcHTF+OhC8/AKXNQin8i5N+i9cJinhi8ZXMosK5FF49tEOOg6+a7zwlHdqqEQlURXoBeeD5++Hi7ExIA1LXrzbubzL4/nvY5raWY8PBQXTfPFO93Si6pqCqta58VJKSinQFY1FmnN4EiEEbAx89GXKr2lIuoG9NFb14hi4Vr10npNAOb2OshTkeXVmdKSUVGUdY1GyCk1XyAtxVm3vOgb7JxH39ub4jsEiKdgaeHTaDvEoJYznuLaOEHD7Sof7uzM0RcF1TFq+SZaXtD2bu48m6LpKL7C5uuYSZxWH45gwLvAs/dILRlZKFnG+zElQOBonzOKcwDX58JrAVJVz39UTOYx5VBDGOSsdF8dU6bW/7um/T+6tUz/TV7Mzf3FSwtNurqKShHFON7Coqic1PIqqfsHQ5EvF5rZn4rs6iuqhINF1FZYbK0t/f1yMjQFp4DK7ncu5PF4kCSLqYrv1gLKSdNoOUZgQpyW59rRCac3ZRBV1vvvRJGKelAhFwXY1oiij33EIFxlZUdHyrLPJt77i4nsmcZYTRgUt12C+SFkkJf65jCxFAYmC7+hYplcLJqoKRVnxswcTur7JOEwxNA1NVWpj5JlsPxwDkOQlWV4SZSX5KGJ/tKCqJB/d6pFnFYfjiE8ejFFVhUHHxtQUUOqF7+ZWaxnpUHAsnfu78zPJi4sLBi807nlRF591WjZ7RyHl8rTmOTrzRcZKx0FUy4UXbfn9PKnOr4RkfSUgsDW+TrvbiyzdmbOEJBccT2s5m7ZnMOi4b3Vn/kWBz1odQZ7rQSQlKMhzhqY+wYZxjm1qPNoPMU0NW1eYx+Xy51qj7dSt+j64GBsD0nCp3Y5pqGi6cqHJjeSiy+NF72MaGhIQS30gVVWIC0F2HH1BofSJpo/KSsdmf5RQVhWBb+M4JlKIegFXVUxN4aNbA2xDxTZ1RvOUT3fnnExSJBLfrYOVpqpSlRLT1OocfPWJgfNslUpAUVWkeYUQdYqw6xgsEhulqnA9k6vrAUiQSi3Hblo6LddkGmYcTRMCxyBMCgLHICtKpAJhnGPoKkUpCKMCz8lJs4q8lCySnG9c75NnBWleARLfMymqWrjxNKtsEVfPDOKffk4oCoqUbAw8Do5CSiFwbZ2rqwFpVlIuXSSmoT21Eair8+us6Isns3fLRYlzgCitGIfpmVy+EJLZIsOx9HewM7+YFXVaGFiJc89QwLX1paGJiTLBaFaLcOZlxSRMURSFzRX/7Ofr6wGikku3avBeKAw0BqThEqcLwSTMOJqkhFGGrims9jyuDLwLk/ZF7xM4+oVdm5C1cFx9GqifN57VFbanmj6aKrFMA9NUKKVKmQuEEIxnKe3AIU5zHMtgOk+5th6AAvd3Qz7fDymKCk2rxeZMTa0rdkUtsb3Sc9E1dbmbh/E8p5KChwchBycR19ZbCCRCQJKVuIbKIsrZHPhkaUGcleSFYBLmzBcZ3ZbDWs9hvshZ67p4tkHbtSmFYLrIuL7Z4rNHU0ohGE1Tbmy0eHgwx3dMHu7N+OBah27LYhrlzKMMXdNQpcB1LfpFxTRMTyMXz/ycTqUxfNfk6lqAkLUIX5zWgnuGqeJadSW8aahf44Xp6Yw7ySKpME0NIQUnk5SVrouqPGlhmuYVRSWI0hLrnL7ZV8/5pA9J3n5WGrqK1TKppETMUnzXYBqmmKaOlLWrKztVMpBPxBfl8ov+KpSD3zSNAWl4Seqi5GiW8dP7ozrYq6vYlo6mKHjuxQn74ve5uGuzbJPZNL7wepRaadc2NFQFwrTirz87AUXl0cGcla5LWpT4tsXhZIFrm6RZimXq2JZOUZYcTBIe7s2oBLV7o+siVYVSgqnXcRTXNs7cAKdaVoamsN738V0Tx9I4mkbc352yseKhtB1cQyVwDLqBxV9/doJlabSEjqKqFEXFatfGs00+25lyPIvptS3avkWUZBSl5Ju3+nQ8k6yoKMuKLK+oRMpoLvnuB31OpjFHk5i9owUKcGUtwDArdo/mJJnAc0x8R0OUAnnucwKQUiHLS25sdSjy6mzxtU0d09SIk4IkKTgaJ2wMXAYdi5Np9jVbmL6Yced7JosoQ1FUNlf8OqV6lmCZOlVakFf177qmErgGUtjvKMj8/DqNrJRMZim6qpAtT7dClrVsv1J//qpWZ/GdnuwVTaGo6tOz/8wmVF8fGgPS8MJCvloTKKU6beBUSZKkoL0UijvV+nnZ+9Q82bU5nrUMqD8Zx2n3PgBFVdg9WlBUcDJdYFk6P7k3Yr3n8mA35KObPQ4nMd+43iPPC7KiQghYxBkoYFsqjm3w6c6UMM6xDJXNgc/NzRb1/rWejHlRoSCZxyX3dqZESUFWlty50mX/OCZOK4SI+NXhGqUQxHFFkZe4Zp36q2kaUZwy6Hj87OGIjYFHGOW0PJ1eYKJpLXYOQh7tz0h6LoZWLyRt3wRVRQpJVcEnj6fkZcWV1QCAJC25uuoxTyq2H5yg6xr9lsON9RaBq6FrKppWu66kolBWUFaCKwObtm8ynqc4Tt2KN4wKTFMny3JGs4TvfjDgxqbPPBaUZb3DP1UF+CJvJ5X0WRl3YZRTVqCrEoU6hXseZbQ8l6ysKNMcy9FZ7brIpevn3QWZn12HcaaVdhbHi1GkxDB0NBXG05g0rdhc9dGQLEpBHldUpUBRlK9l5tV5GgPSwBd3UPUkCJOSshIYyywoVQXL0Jf9DcA0nr6pLy974jlP/MOnzXFqN1C9My4rSSkkqgq2qWMYGut9j7ZvUErBNMpQVZVFnLI+CJjMMvKyYmPFrzvCCXhwMCdwDVa6DllecTiJaPkWZSXoBrWirmmoJIXgs8dTjqcJ+bKnx8FowUc3+/S7DkVRsXsc8mA/xLY0TmYp/ZZBy7OpZO2e+3xvyqePZvQCk1/6cAUhJYeThONJQppXfHC1w/EkZpJWeLaB5xhMFhm3NjsIJIaukGaS41mCgkqYZAyvdxlNQzzXZvd4TpELxmHKN673WEQpiqLSbdnL7DCBYWqUpaCsBOEiQdEMdo9DpIQkLxhe62Eq9UI7XWjsHoUURZ00cHurzY11n4sFjG8vlfRZGXeqoiCEQNVVdE2l5Rp4tsHmisf6wONkEqFr6lka8un7fJ2CzBd0rIw6iaRONFfQFMiXMcWyErRaDskoPkvy+LpmXp2nMSANS053UMoX2nOiSDZXXPZGCT+5f0JVSW5ttml5xjMWnZdVxNY72sk8xXd1BA6jaYqtKsRxjmXqZHmJtqyFaAd1Yd2nj6eMZilZ5tBpWwS2iapB4Nn8/OGIQctBURV8x+T2lRZ1343atXM4TjgcLfBtC8sIsY066+lbtwZ0AxNVVVgkOXlZUVZi6UJTGHQddE3lZByzSAvyXOA6tXstygQH4zmaprJIcjb6Hh9eb2NoOvO4YP8kZjxPyYoKQ1dwbJ2Ngc88zrm64oOq4p5EfLYzIU4z0qKuY1ksCgAsXWUcZhxPUqaLFNc2aLcsDkcJcZLjuxZxVvLzhxNubbZQVJX94wVZUeGYGq5j8fNHJ+wex8zCnH7b4T9Mdvm1b64xCjM+3w/xHJOOb6ID93Zn9DvuUgOs5tVSSb/cSeWLGXcxIBl0bVzLqF07isJ636Hrm/XJeKqcnYzh6xTLecKFeg8JipAEvsk8zBDUrquqqg3Ku1TVfV0aA9JwgYuLhiRKc47GCdc2A/aPF7R8m5ajo2vPXnRezJMdbavlcHgSoaosG+NICglCVmyutkBKAs/keBJzPE4xDIWbmy2SrKAsKiqzYmutxd98ekxZ1nUhnx/M6bUtbq4HuK6JqWlMk4woL3Ftk/Eipb0w0dt157+TWV3UqOsabd/EMg2qqiIrKzR12RRLAd3QON6fIaRCmCis9Z1lnEGl7dZjfLAf4rsGP7p/wH/yy5tMwwzb0sjykvmi4OPFCb/y4RoI6AQWJ7OESgjWuh6WrhG49cnGdw1cW8e3DaqqRCiCNK8XZVUB21LqimelNu6TeUK26nNvd0S/5bA/ilAUlVmYYhgavm2QpCWTMKPXstgbRaz3PMQyfmBoCh2/rl9IsoLAfrIkvIou1Jc9qZxfaOuWwAGeY5zrCXMxDmDpvBdB5medykESLvIvxAody0BR3o2q7uvSGJCGC5xfNIpKMlvUlc2aquK6Brqi4HsWoqwAiNL8BQVdF3elcGqcJKNZys5RyDzKuLXVpuVaqCpnBWKBYxA4tdpomgvW+i6TeQpKvQu+c62LqijEaUnbt3l4OKeqBIukwHVMDFXh23cG/OBnB0SjEtOs0yRtU8M0VFRV5eHBnDCpDWS37bL9YEQYl7R8nasbbXaPQtq+xWiW4NgmizhnPMu4vu7jmCaupRN4Ju1ZwqODkM0Vj+H1LpapM48yBoaNYxtMwoyiEhSiwjR1DsYRslLYOQxZ7Xt8thvi2QbX1lqs9lwGHZtH+3Mc2+Ab13ok6RFZXlfErw8CPr53jJAKuq6wuRqwcxQSp4KiSjgcJZhmLQ0+j+uU4s2Bz8E4xnPqgLoQEt1USaOKvJIkeYVlqDhP9dC9bLOqL1f09uQeeVHQ+HysbTmSdyYg+Oo8fSp/doZVYKvviVF8QmNAGi5wftEoKlGn02r1gnsyjskKQWuRcWO9haYqHJwk2Eb2jF2nPKt4Po1x9No2UgqKCuZphqYpWKaGkPDjz44ZdJy6p7pnLuXXwdA1DF2lpRnoWt1cpxdY9AKLspTc2WoDknmU4Vi1NEcU5xSl5NZWm18ZDsgK0HSF40nEvcdzAI6nUwLXxFz61z/fm3JtvU2SFVxd87n7eIKp6diWxu2tNsfThA+utCmqktWuz4/uHhKlJVIIvnNnFSEkcVJrcHmOxtX1gKqsYyerPZeOb9L1LP704wNuX+2wiHJuXe1y7/EUz7WYhSlhkKGoCsezmP2TGFFWfPvOgP/4u1uEaYGlKtzbm5Hkdb2KZWj0AoFt6rhWRZJXLJKcvuXWnQ8dg0VSoqgJYVzwK8MVDkcLxvOUrZWAT5MReV4gTI3VtYBFkmPq6gVtssssaK+vq/VlTy7vRkDwy/N84/f+GMWaxoA0XODJolGn2Kqawlrf42S0YGPFZ/cwBKkwmadsrvjYRv26p3ed9a40ZhYVZxIgcVoLB2a54HiWEsUZCpBkBSi1DHrHsxhNUyxDoxSCKMoQEnYOQwDCtKATWPzoz49Y7bkUpWDQcdDVkHlUEHhmveMvK2ZhLbT4g58fEiUFmq6y3vOwLZVJmNXvF+U4ts5az0NR6sDtNMxAKrR9E1XVuLczxdBU5lHORs/jj/7iIS3fpiwqDKPuIRJ4JoejGAk82g+5utai1w6oJCDB0DR+dPcYCXVgv21jmhq/+Z0NwkXKQylY6bn89P6YQdvGs3U01eLf/nCXq6s+lqWz1nPrvhG+U2fzLNN5P7rZwzBUkqQgSlzankE7aPFof8rWal2XsjHw+fnDMd/7cJWffXbCR7d6/Na3N/FsA02FvZOI43HE5sBnvf+ksvsyC9rrttV9X+Q6vhqeZ/zeL6PYGJCGp6ibK1VSImcJatsmjHPmSUXL0VkZrnCawN56qg7k/K6z7tchz4wHQJqVrHouo2mEpA4YrvZdjicJqz2fjm9SlhV7JwsUFY6mCWlWMY9SBp26grdv6fz5x/uUVZ2ievtqh893Z/zatzb44SdHQL0YDq/3+GxnQpRWxGnBoOMwW+TsHIb81rfXGc8y0qyWWS8riaYo3NhscTKLcU2DJK0wdZVPH0+QEtK8BClxTINuYOPYOqtdh7IEU9e5vxMSxhmLtKj1suyED653sIw+UZoznqVsrnhsDjzivOSThxMORzFXVz0+ut3nt769ga4pzFbqk4AiBKNFQtu3CHyLveMFJ9OE1b7Hx/cPkcDmiodtaSRZRVFUDDo2uq5yf2/OwSjm2nqLlm8SuEbthrPq+pePbg9Y6TicTGLCKAeWygKyVvW9uIi/fEF7nX4u0CgC/yLQGJCGc9T+6DgteHy4IC+XhU9CMp4nGLqHayu0XJNKgK7X8iCnnN91moZGtVy6AB5/AAAgAElEQVSUThESLENla81DVVWm84SiFAghaXsGhqYymiYoCuSl4MefHqOqCp5jYsQ5x+OEQcdmnhSYmooC+KZOsGLQ9ky+90Gfh/sh/Y7N4Sii27Y5mSUcjGImi5zVrsvuaME4TNnou4RJQS+w2R9FSCn5s5/s8r0P11hpG6AExGlB2zNpeSaeo2EaRp2lZancfTih27IxDR3LdHBthbLSMU0VIRRmUV2lHsUlNzYC1vse8yhjNMs5nkSkWYltaaRFxeePZwz6DuN5RpzkGJrGrSsd5tEYz9FJshLPNkCpG3CdSs6vdhwMQ+VHdw9Y7fl88qDOyLqz1akl7qOM43HMg92SaxstTKMCIXEtvW6xWwqEhNEs4epaQCXKMx2uV1vEX8/18ronl4avD40BaVhyKlYXM4tL/vJnB7iOSZIVbA18tlY8ikpyNEkxDYOrqw4KKsfP2XVaOgy6Liez5EzieqXjoigKogLbVHFtExCYpo5tGhRVhaLWWUFpXuE5Bq5tkOUleVZXcHd8i82+h2PVsZNFWvDJgzGH4zrt07UMBGBZOoqs5UhUVSHPK0Ql+ehGD98xub83QwqYRTm+bSKqCk3Tebg3peuvkhcleVFRSUlVCQzd5ucPxvieQZwUdNo2+ycRnm1gmwrfvr3KT+6d1DItQrAxqIPphq4xi3PKSjKbp+wcRpRCECY5K22XOC+oFLj7cIahK3UlvKkxmSVIIYmSWu5d0xS6vk0vsPg7v3kNRYGWZ/HHP3iMqmoskpwwLvjp/TG3ttpsP55wc72NZWpIJFdWPGwzoONZFKWoBQC7DpPlCVFKaPsWhqa85iL+6q6X1z25NHx9aAxIA/DEH11JhcNJhATmUY6uKzw6DLlztU2v5ZAkJZ6jIVCwDY3VvkdRVk/1Ea9bxCZxyqBtEyYF/cDB0mspFF0r2R8nxHGKqtW71aNJQZILOp5JnJXM45y1vst4lqNpKllecmWtxf4oYms14PBkQb9jczxN+NbtAXGSUVZ1v5BrG232T+b4rsO32g4Ho6RO/60E37jeZ+doTlEIFCSOYeBaGoNugKkraKrCyTzl090Zs3nGas8hykp+8sNdNLVOLFjpuMRpwe0rHaKkYBrmtIOU21c6SCGWHRBz7u9NGU0zykrQb9vc2mpjmDp7xzFVKZBCUFUSzzJI0wqpwKODOZ5tYJka37zR4wefHLJ/UnLnWgfL1DmeLEgyENRilrUcu0O0zK7KhUTTVfJcMI9ztnyPtZ7LLMp5vJ+yuuKDEIhl691e28G5YtDxLZBPqp/fziL+/gWNGy7SGJAG4EmP8bSomIY5632Po3EdFJaAa5mEiwwJFIXkp/dHtDyLyTyl41u0fJPQMei3bEByMIrJllXdHc9aVokHjGdJvaAGJr3A4O7jKbECVSkZTxPKVZ+9kxDDMPAsjTjNsW2Dta7LNEpRFbi1EfDhtTZZXmeJfb47xbZ0XMvg+kaLbstis7fBT+4dM1lkeI7BWs9hY1AHypOsjm9srvrMFjn3dmeczBJWOg62pWPoCklSEPgmrm1wb2dGmhXcudJGVRUeHcxp+RZxUnD7aptKQJ4LDschRVVxdcVnreczmRd0fIv9kwXzRcbDvTlrPYd+28J36/FmRUm/5SAVyeP9EN8xUdVa6HF/FPGd2yukeR2reXAwY2PgcW9ngmObXFsL2Oi7HE0SHFNnteeiKaCrCq6lc2XVxzZrBd7Dgzm2bZ71T7my6pGkBZN5ynfu9Gl71jvSXHq/gsYNF3knBmQ4HP594B8CJvBPt7e3/9lTj/8S8AdAG/j/gP92e3v7i51dGt4QkiQvOZrE2KZOGOcUleDKmo/vWIRRttRwgvW+y+FSQmJ/FOEYGrMoZzSvpbY7voXvGeychFQVGBp4rllLrYc5n+3MGc9jTNOg17L4yWcn9AIb29Lodh0WScGNjQ53H41pOz5JVhImBVUlcEyN6SLlh9vH6LpKHBeMwgzH1tFUldEswXP1un4lTPE9g7ZvousaKJK7j6bc3AgYdGwC2ySrKo4ncR2o9kweHIToKlxdaxG4JnFaYho6jqXTDSwcU+ckTFjturi2gZCS+7sz4qwiigo+utUnKyRhXLCIS+7uzCjyim7HxrYMorRgstA5nsRcX28xCRMc2+Duwwkf3uiyfxRRVoKiFGwMbNK0jj3lpSCMc3zHZB7lKKrGw4MQFQUUlZWug+uYKEjWey62oTG83iVJCxRF4eH+HCHB1FUqIciKCk1XcV2TtmvimAaWrj2j1uJlCMJUkGTFuRNoYwj+NvHWDchwONwC/jHwq0AG/MlwOPz+9vb2z8497f8E/qvt7e0/Gw6H/wfwXwP/+9se6xf5+vcofh2ysvbPr3RcxmHCra0OD/amy0cFwxsddFWlX1mgLDN2VFBQMAyNveMFjqMTJyUn0xRFgV7LYhrVSql5Jem0FGSYAgIUlZ3DBVlWB6ltU6XfdpguMoSQVKXkxnqbyaLWu0qSnO2HU9a6Dneudfjru8e4to5laLR9g3lU4LT0ujGUbdJ2Dbq+weOjCCR4jsJnu1N0VaUdWMzCjMMqRi6r3Q9PYj59PAGpMLzewTIVbl9po+t1j+vD8ZyNQYesKPAdk8ki5dZWmz/5yT79jsPhKCHJK/7m02N+5zev82Bvhu/UgX3FqyXpVzoOmqZwcBzj2jp//vEB8yTnwytdsrJkPMv4jW+vsYhL4iRnNMvYH0V843oP24Q8L4mSnLZvkuYlcVrULXrnCdfWW1xd9Wj7FllRkRUVe8cLdEWh13HI8gLD0IiSgsk8Qdc1FBTyvKCyzRe2FX4+ggcHC+7tzqiqOkZze6vNxsAlL76qToENXzfexQnkd4A/3t7eHgMMh8N/Bfw94H9e/n4dcLa3t/9s+fx/CfxPvHMD8n70KH4d8qKiErXY29agls3+4Eq71sESkjSv+OxwhqqqOKaKqql0AqPuF77MxprMs3rnneTkRcWvfXOdVmARxSUPD0IWScH+8YLrWx08U6Md1G6t3/rOBrN5yt1HU2zHwNAUojSri9oMFVWFwNGpqgrX0QmjvJZC8SyurHpIJLe32qwPXE6mMaoCjw5m/PI3N7i3NwepIOK87tXRdzk4jhFScOdqm7IU/PXdk9qoxHX1dpKVgMb/+xc7gOTqisc3bw7q1FpF4XgyR9M0Pn08QUjJeJLQCkzCwwW9Vm2cHu7PgaXh6DrsHIW1UQ0sdL1OO0rykqIUqBr4hsndx2MUtc/DvRnrAxchBR9e66Joks93ZnRbDrZd95NY67nYhs7OUYjvGJi6TpxVJFnMZJFxY6PF1qrPILAAUNVVPnkwrlWUA5vAtfjZ5yes9VzaQhDFBVbrNH51OcJUnBkPgKoSfHxvRCklZS5+oeZHw/N5F+fNTWD/3O/7wJVXePyd8Lyip6yUL37he8B5xdCqqjOXykpQLGs5Pr43YjRLORzFlBJsq9ZYWu166LqCZxukWUmcllRV3Z/iZBrjuyazOEfIOusnKyr2jub0Oi6KAklWMV+k2JaJqqvkecXO8YJZVBcWpoWgqgS3r3a4tdVBUWoJ837bQVUkuqaS5RWPDkI+35ujqxpFVXFlvcMnD0YYmkaSFlimhmlorPc8HuzP2DlZ8NefjlAUFV2rNa+qStBvO3iOyed7MxZxhqYqHM0S9o5DKglFWdXtRnWVeZwzC3OkArpaS1CsdGoRQMc2OJmldU3L8YLbm208R0fTlKWir4Fp1E2uDF1lusgwdB3LqFOWF3HB1kqLncMZaVJRSYUoLej6Nt/7cBVTV7my5nNrs82trTZJlmHpGmGcs1hkJElJuMhwHAvXMdkceHyw1WZz1efmRgvLqEUnVzoutlln0r3qfZxkxQUhw1LANMrI87rV0y/S/Gh4Pu/iBPKs7Yh4hcdfSr/vv9KALoPrmrTb7jP/3ms7b/z/fRlWVoJXer6UElXXGM/Ts9OVZajEacnu8QJNV9FNjbKS5IXAsxX8wOWDazaVhEdHIaMwZZ6UKCrcWG1xNEvZXK2W7j6dMMq4c7XHzmHI4TjGMXSurnr4jsn2wwlVKahkLQeSqBX9js1W32d/HHMwiqnKCiElpmbz4dU2i7RkNEv4zu3BUr5dcvfhmEHH5cef7vCb31qhNfDQtQ6GprI+cPnhz0/Q9Fr+W5FwOInptGw822B4o0dVCZK8IIxyAs+q/5+us3sSwyjhcBSRZBUfXu/Q9kx6LZv5Iq+rw1cCrm8E/NXPDzF1BUOvW+cmeYHvGszj+kR160oL21T53p0VTuYxtqFTVQnfujNAVIJFkrFISmzLYKXr8/n+HCnr6nVVUxhPFnQDh7ysWO25KCp8cLXDZzsTFnHFSs+n5VtUQtay822HUlZ0uy6uazCPS8K0xNIVWoFNx6/7srzyfaxrtFuL+pRKrYkWeDadlo2qPtmXPu99L3OPSlmnMedFHYvyHB1FebunmVedS++KdzXOd2FAdoHfPvf7BrD31OPrL3j8pYxGi7OmNG+ClZWAOM6ZzeIvFD11PYMqf9Px/dePtaysBBwfh6/8Hw0kHde4IHx4cJwQxhlFKfj08RQpJSs9h+G1uh9F7CjkZd1f/KObPSxDI0prPajANciykvW+x6ePxhQVFKVga9XDtXU+fTwhzgtub7ZBlXiOwcG4DhhvDjxurLcIo5yiLOm2HHRF5cHBnL2TkO/eWaEUdU+Plmcynmf81SdHCARbKwHdwETXdbYfjDmeJqx0XNYHHqsdm5W2zXiR1qedo5Dv3Vnl7qMxYZRzY6vNzc0Of/rjfWaLjH7boe1ZfL43Z33gnhVPPj6oq9knYcb3Plhh56h2X4Vx3aP7cByz0nFY77lomoKm1c2xRN/Ft01ubrbRNUDpUVWS9Z7D9uMxuqbRazv0OnBrq8X3//IxncBCVRWurvrsHoVsrfrsH0z5lW+s4VgarmOgqwo938J3FHQVyqJkMs+wDZW9owJjeVJrByZSKMRG7c7TRMVslrzmfSxY61hP3FgKXF31iBcp5XK797z3vdw9+u5dxq87l942b2Kcqqq81sb7XRiQPwL+0XA4XAEi4O8C/+D0we3t7YfD4TAdDof/0fb29n8A/gvg/3kH47zA2yt6epMT51UM0RcVQ9u+xcODkKQoUVUwdJ3RNGHez2o3T1LHIw7HCYoi2RwEHIwjrq0FFKKi27KZRzlbqwFlJei1bGxT52QW0wksDkYJLUenyAWBa9Br2SzSkigpzuorXMukLEo+eTxnrVdXfs/jgryoQFT81fYRqz2Hj273sPS662CvZbN7EjGaJWwMAsazFM+uM5IC10BSNyAaz1IkgjtXu+wdL4iTknCRcnOrgxBTQNAJbPqdHCkELc8gjAs6LfvM/RRGKYOug4pA1w1ub7UxDI1FUmAadcOnh7szTLOWHLEtyePDOaqm8id/s8eH17toqsrucYyhq6z1XFquycHJgs1VH8fUWes7HE8Srm8EBJ7Fes/FseoT43RWKwnf3OyiqLW2l2VoFKVgPEsQor6H2r5Jv+2w3lO5suoxm6dU4svcxyo31n36HXeZhaVT5hVH06S+m77k/PjbrZP1/vDWDcj29vbucDj8PeD71Gm8/3x7e/svhsPhvwF+f3t7+wfAfw78wXA4DIAfAf/r2x7nF3k7RU9vbuK8iiF6lqEB19TZWg2YhDl3rnZJs5xBx2W2yAhck52jkLWeT9u1mEYZCnX2VJIWSARxWvLxvTFrPZu2b9HxbcqqYK3vcXAcMehaVFIhLyse7CdsrQb0WhYbfZc4yRj0bPaOFgy6Lu3ApN/x2Dmek+QVSVrwm99ax7ENfM9i92jOdFEH6r83XMWYwLX1Dvd3Z0yjjMNJxH/6a9c4mkZ0fJtFnNPyTT7bmWEbGvvjGF1VcR2NwNH5nd+4iqqp6BqUomLncIFj6az0HNa6Ho6lcjgWdeaYTLANjZNpwgfXuqz3XFq+hRQVUVIwGHh0fRMFhUrWzbQcVaUb2ByNE8qy4rd/6QpJWmCYGrKqaPs2nZbEM3XSosQyNeKkQlQpV9cC9o4WLJKCaxstbENFiooPb6wQhimlkByO63qP03sojAsMXSOwdQJHX9Z9fNn7WCWw1Sc9RGwd9w3Nj0Yn6/3gndSBbG9v/yHwh0/97XfP/fw3wG+87XG9nK++6OlNTZzLGSJJVgpG85QoKZCVrHerS72lRVxQlCWGqeJaOopv8vhgTiXhs519qkqw0plxdaPF57tT2oHNZt/FtTVs3eTh4QzH1nBsg8NRzNFowZ1rfT57POFonLLZryu6TU1lre+zd7zgx/dOuLXR4s7VLqKqe0UfHsckWcVffXLI9z5c5e6jE2xD56f3x2i6yu7Pj/joZp+ylPiexd5xBIrC3ccTDE3DNjQMvU43HnRrA6Cv+SzinINRzM7xgisDl5ZvkxUVR9MUxzaZzlNansntrQ6OpdeS7WlBnOV8tlOSpoKH+3NubbW5tzND1xWSrOJklvD4KDwrzru/O+GXv7HGD39+xErXZb7I+KXhKneutTka19/JwWhBmtUxo7ZvM1kUaAp4jsndRxO+fbsPCA7GMbMoR1dVbEvDMursKSlrKfvAMQiTgkG7DugLIVFVhZWOe0506qu6j9/c+zY6We8HjSl/69SLdpgUZKWgrvN+wunEOc/rTJwXGaLTcYzmGZ89nvHTeyMe7ofklSAt6tTW7UcTxvOURVqiKQoP9+aMwxzd1Nk9rsUHTVPjaJowDVPWBz5JUpIXkkoqPDycsXscMZ6npFnF3Z0pvbbH3UdjxrOMw3FElJd8tjOj23b52f0RaVZRCUkrsPm3P9xhHpd8/OmIjVWfj270cB2dzx6PubXZxbYMth+NKcq6N8bOcVifokpBlJT02zbr/Trbq99xWO25WKZOWVRoukKal/z8wRgJtD2LTuCAlGz0Xb59a8Ct9RbX1lt0ApskqwPltqnRbTlMZinjWcaVdR/XNkiyEgkMOi6PDuYcjWMe7oeYpsYszvjuByt8vjdnfxQzXVbGf/zZybKJlM/+yYL9UczdxxNs26Dt1xX90ygjL8s6uyotmc5ToqSkqiS6rnA8jqnOxRtMQz+7hxyz7r99dS3g+nqAY6rv1eJ76jI+nQuNTtbXk0bK5K3ycrfSm4q1vGwHd3pCycpqKaZXdx/MiopSCAxUjqYJR9OYQcvh5pV2XX1+EqFpCmUlyZKCNKtAwqDl4Fk6uqbgGBq9lsPeUcRa16PlmdzcaOG7OpNQxdRVbm60KApBktbxDNcxENS91g9HEVAv8nkp+NH2Ed+9M0BT6t7i/Y5F4Br02za9tk3LNSkrASiUpaAStYqwlAq9to3nGKgS0rzgex9ukGV1Bpfv1FIs3cBh++EYy9TIK8GN9Rb/7if7PFjGLj66OeDz3QlX1wKSrMQyDBQNPFtneK2DqqlousrBSVT3J2l7zKKcw1GMAqz3fEazhJsbLSopCFyTNIsxNJXjSW1gLUOl13KoKkFRCU5mKXtHMetdlw+vddAUiWPXyrxlVdFvBxSFpKye1Fx4jk4S1fdQr13fQwoghHwPF99GJ+t9oDEgb5HLuZWeN3EgK8WlJ9PLDNHpCcXQ1DNDU6fDCny3dt+ESU64KDA0jcNJwtbAZb3n8vhoQRJmXFn1CTwTx9B4dDBn7ySi17IYdNY5mUW0WjYPduc4tkbbMykryb3dGWGUc/tqByEqPro94P9v786jLM3Pwr5/3/3e9+61V/Xes/w0zGgDKTlhkeyDZE5EjEhsmQgOAkeJUDgG5EAOnBPAgwhgg7ESwCwOxJItEYwwJjGI2AFsEATsyKCRLGl+oxn1LN3V3bXeW3d99/zxvlVdXV3TXX276lZ19/M5R0dVt96679M1Vfe5v+15an7+Lj5NM75cVXnhShvbgnLJwTDyxLbRGXHxdJOra12yFIIo5cpKj5evbdGoupQ9G9uxMJKMmVaF517cJE5TVjeHtBplSDO+8nWLfOlyhzhJcG2LpbkKjYFLPwh5o5qjVffyUVoYEQQxj5xt8dLVLS6vdJiZqtAPEi5f67I463Nqusal5Q4V32Vza8TClE8cxTh2fsDyrW88TRCEWJbNtc0+3WHMbKtMmuXVxc4t1vC8fD3CL9mUPJtqxWCrFzDbLLE0XcF1TM7M1Sl5JtfXhwyCiJlGmZkpH9cyePR0nUdON2kUvz83trje6cX3fqmoIHWyTjrr6aefPu4YDlMT+MBwGN4yfXMvKhWPwSC85+cZBjFb/Vufp1J28G6aXjCwTQPPsbDN/A97fStgebXHVj+k0wvyvfuexd4//Bux5l+vVTwqZYfpZrloE3tjTqDTCzANMIx8IduyTdbaQ0quSbsXsdkNIYPuKGSmUeKJ801M02JxpoppGvkupjRlrRNgWfkUiWnAWmfA2bkGz7/SxjTh4mKTDINr633mpiqsdYb0+iF132NuqoxjG1w81cRzLFzbZDCKmJuqECcxcQRBmOLY+aG/x85M4domV9d79AYxnV5IuxfSqLj5YUPyCrWea9HpjViaqRLHCY2aRxQnOHZeNiXLYKs3otUoUyu7pGmG49j84Z9fJggTqpW8WOKZ+RpLs1UWW2Vc12S66XN6rkZ/EOE6dt4v3rKoVxxmmz5RktLtR2x2R6TAXKvE5etdziw0+cKlDcgMBqOIJy5OE0cxV1Z6TDWrWEZGFKds9SPOLdYxTaiWXYw0pVUv8ciZOlP1MrZlEIQJQZhyZrHOmZkStpn/Htz8e7r3d+hG8jjo79JROay/p6P2MMW5fRYI+F+B9h0u3yEjkAmafOvPV38Ht3uEUvcdSp6dr2s4FmmW8ZkvXibOMi4uNTndrNJseFxa7tIZRFRKdt5kybMZBBHtQQ87MDg1W+HKal4QMIwT/JLDy9e6rG+NuLLapVFxyZKE1z82hwE8cqrOy9e7bLaH2I5Nq16iWraYbsyiX9nAs20S4M1PzhNHCTMtn6trPaYbPi9c3qLsWVxYqjMMY4Io5fr6gOsbAy4s1ekOAp66OMuV1R5RlDIYRTx+tkkSpzzzxRXKrkvFt5lr+bxweZPBKGEUhLxRzTIKYizTpN0NsEwTsoxmrcSXrnYoey5f+NIGl651iaKEN33ZPGEYAz79QcTKZt68quJZtGol1tsjXM/lyuoW5xfr1KoOjmVxdbWL59icXmgQhREzi1OkaUqt4pHECeWSg2MahHHGwrRPq+oy18j7nG9uBTi2iZEkrG9FTN9FGRLZHisOkySQCbqX1p9hnM+NO5aJYxlkmTHmlsYb0xdV36HqO4RRykZ3xH949jol12G1M2BmysexTF5cbpNlDb7w4gZnFuq0uyNKc1WeeW6VpdkaaZaSJVmxayukVnFxbINWvUzdH7AwVWaq7tEfhozCfLG5bGUYJjRqHotJQjbt8/zlNq+sRlwr6ju9Xs1S810y4JnnVpmql8AwKHk2aZoyCmKiOCl6hSR4rsV0o8TG1pCSa+S9Q9a6+GWb2dYUZ+drDEYj1nohizM1FmcqpHFKyUp5/EyLtW5AHKdcW+2SGiZXVroszubVgHuDENc2ODffQL+yQXcYUnJMyp7Nf3x+jVa9xKm5Gi91tmjWPGzLJCXjCy9u8OQjM5gGtLshSTLijFVnq99nYbpC1XdxbVicqoORl4R55XqXOE5ZmLbAMjEN8Et56+AgNuhsBRgZxFG+en63L/6yPVYcJkkgOyYxLzzOwuCNUuvJ9jbbqkej4oyxq+bGIr4BmJZBqeRQdvI6SlU/X5y+vjmgWrZZ7+S9yLf6AcMgQb+0iedapGmX2VaZZtUpXuxmubbWpeq7rLQHzLUa/IfPX+X0fL5w7rkGp+drXFpu0xuEDIYxj55t8YVL65yazRem0ySj2xtR9hyiNCOIUobreRyPn2vmP4cg5MsuzBCnGW954ymee6VDmiQ8cqpOtewSJQmzrQqtmsdoFPLUxXkgL7Px0rU2ozBlozOiWs67/vklm5VORH8UYVkGL1zZwvccuv2Q5bU+wzDF9ywuXd0iSjJe/9gMNd+j1485NZe3kE2zjLO+Q7Xs0N4KCKJ8nWqqnu8Cq5dtrg5CeoOQRtVjYys/aLfWGTI35ZMkKZZtYQFkGTNNnzRN8Wyj2NlVxrPz9a9OP8A082rI6a4RxN28+Mv2WHGYJIEA453+Hjfh3N3CYBCnbPUC5lp5T+0gzLd1nl2o3cWUQx5rfxSz0R1hGTCMUq5c7TMcBSzN1Xl5pcvK+gC/bGNisDBdodMNKZUsev0UyzLY7I6oV6usd0a8+Yl5MOHzX1qnWrZ55MwUtmkQxxkbnT61iofnGMw0qzzzxTX6w4ALSy0qZQfLNNjoDPjslzYJo5SSaxGlGaMgIU4zTAwqJTs/ad0N8rpSRR/wq+sDLq90mWuVeeJ8g1atxKj4dy2v9vMX75rLmfkGV9d6+c8wyrsZPv/yJrZtYhoZQZjkzbBqJdY7Ix453SBLb4zMZlplXrnW4/FzTRZnKtR9mzRJcSyDTj/AdgweP5v33GjV86ZRpxdqrLaHebfBLOXUTJWa75Kk+dTgly63qU75VMo2U7USJhluyWGxVSZK8iZclmnkBxp9j9lmCc82WN/KT/yHccrK5iAvguiYpNndv/hLG1lxmCSBMM688KTq9GSstke8eLVLlmVYVr6IWy1ZVIppjYM8x3as/SBmo5MvLK93hmz1RzTrJZ57pc2lqx0cy6Q7zFvIWrZJzXeoVTwsI3+eIHQouw5r7RGNmstae8jCVIWK7/LicofVzSFnFmo4tsPm1pDZqTKXlrd4cTkvh7LeCYmShCcvzjJVc6lXXV5cbvP6x+eZqZcxMUjSjKlGielGmc+/sE6UgmkmXFnpcW6xxkyS0htGXF/v89iZFmUvZhAktLsB9aqHVexEsm0Tg4ykKPduW2bRXz2lWS+zutmn6ntk5C1gh6OY7jAkCBMWpr+jlxgAACAASURBVCrMNMpsdvIT9+1uyGpnRG8Q8BVPLOIWpUoGQcTMfI3ZVonL13vYlsH5hVpxqA/OLtRod0fUfAeylK/7zy4QRhG9QcT1jbyQoudCkqV0ugGlXYmgX7SqDWJ2fs8cy6Dmu6y2B5ydr2GMtT1XtseKwyMJhLufF57UQmQQZ3S6AVmWkWUQxymrmwP8xdqB33XujtWxTLIsY31rSJRkuI7DemfEMIyxLJOtYUh7K+TUbAXPtaj5VeIkxbbKXFnt8xWvmaPTy0cfa5t9XlkZkJEfarOL546ihKudPkGUYGJQ9hx6w5AgTinZFnEMUZQQp3B9o4/vOviuxVTD49EzTV66ukV3ELLRGfDYuSmefXGDNE2o+S5TNY/l1R61soNlmbyy0sW2TDa6eS+SLAsxLYvSyGC263Pp6hZn5+tsbo2Yn6rQrHm0ah6dfohlWVRKeRc+24p57pVNpmp5Da3eKGK26fFX33qRV652mK57rHYGhI5NfxTx5WqO3iimN4j4/IvrvHS9x/X1AbVS3r3wwukGjmUSRilWcXZmfrrCC69sMN0sgwFPPTJLo+JgZhkbnZAoznCsG787uw993vjdNKj7DmXPplHzaFS8MV/8ZXusOBySQLj7eeFJLUSGUYJl5msenV6wc+CvUnbGWjT1bIPZVpkgynuJd/oBpmEwGkWQZZQ9h8BL8nMfG0M8x+TsYg3fs/OT0b2ArUFEksKjpxustgOW1wbYlsVGZ8jCbJWa7/DcKx2mah5lzyaKEk7P17i+MSBJUxamfaplh0rJZmm6ysXTDVY6Q0ojm888t0bFd5mqezi2xUtXN5mf9vEch7XOgJR8ZOE6NutbI+oVj4pv89L1LpvFVNdWf5hP/TgWcZry+UsbLM36dIchM80KWVHFN0lSTs3VCIKYrNhC26y6nJqtEiUJUZySJil/8dwaYZSyNFvh1FyVTz+3QhxnPH+lzenZCr5r0xtFnJuv0+4Neelal3rVozeK6A8iTs1WKXsO3V5euXcQJFy+3mWzM6TbC5hr+VRKJqMwA25slHBtY+f37+bfTQPXNorkIQlAHC9JINz9vPCkFiLz+9x41xklKZ5tMV0vcdB3nduxGsAo2j59nq8nLE5VefbldUqeTcV3uXy9S8l1mJ8uY1v5TqSFaZ/llR6LMz4Xlupg5BVfO/2AasVlLsnLhNd8h5qfl+F48xPzzDY9BqMQxzY4PVOhVnGwLZPFqTKNqodtGrz24jQZ+cE6z7YJ44S0H2CZ0B+VadR9rq/3Wd/qYFsmllGiVSsxDCNsy6Lk2oRRStV3WOsMma64WKbBY2dbhHHMysaIkmeRYQAWq+s93qDmSeM07xR4vcswCJluVUizISubQ2xrxJninEeSJDxxfpo0zXBdkyiKGQX5+sZGe0i1ZFH2XF66tAFZxpc/Mcf8VCU/q9GJGIUJKxt55WHLNBgGKcurPVIyTCM/Ib6yOeD8Yo161eVSURrdtg3OLzWKKSaTmWaJtfZo1+9mCcjoDiOZghLHShIIcLfzwpNaiNx9H8cycG2zuM/B33luP8dGd8TKSt7PpO67xHFMuzfkjY/P8cIrm5R9hzNzVRzH5vp6l/XOiHNLTeZaZXqDkBeXu3z+0gauYxMEef2pbi/gjU8ssNEeYbowChOmbZ80HfHcK23qFZdTMxWeuDDF8loP0zQJo/yMxZW1LsMgzft7BzGeY6HOtsjIE9RgGFKveLTOT7G81idLEhZnKkw3fEzTYKbZY2MroDsIWdvo88jpZr7WgEG3HzDf8nnkdB3btri4WKfXD+iOMpIkzQ9Bbgw5PV9nFMa88Momrm2SJhlhmHB1rYc6N02appxZqNEfBqy1R3iOxWsfmcG2zHxxPIGab/GGx2dIU5hv+XzuS2tYpoVl2zh2Rka+c65e9XAcIx9Beg7DIKHsWWQZuK5NFEScna+RpHlHyJevbeWHFW2T2WaZ80t1wijFdUz6g4gXl7f2WX8TYrIkgey4m3nhSS1EHsZ98ucwTDMv6W3l/75rGxH9UYxBhrowzVY/ZBBEXF/rMtXwKXkum90Rzzy3wux0lSBO6Y1iDOCJC1OQwbLd59P6Ommaos5NY5sGy6tdhkFMp5vX1RoEMfWyx1Y/oFVzaVRLXF3rcW6hySvXt6j5Ll+63KYXJtR9j3LZ5kox4vFKDleud5lpeFTLLqvtIX/8zJdwXYtzCzX6o4jhKOT86QZX14Y899IGT12czneQ9UdYVn4y/vp6n6l6Cb+cj1DiJMP3HFwzIwB6o5itXsB0w6fkW8y38tPxy2sjMAxGo4T5VhnbNFnrDPG9Co+dadIdhtiWzWAwolQ0kpqqlfFckzTNaNv5OY6peolaxSPLMsqejWMZeK6TT8F5NrWyw/VBBGRYlsHllS5pmu1MZ622h1R8l1rZIYhTVndtw46TjI3uiKrvHPLvnhB3JglkbJNaiDyM++TbYiueXUy75Yu7/WHI9c0R1zZ6lIs+3aZl8cKVNpvdgIunmly53qVW9WhWSpgY+TUmPPdym1OzVfqjkIbv89nn11ma9Yu+6ilRkmBGJhCTJCnn5muEUcbnvrSO65iUSw4lz8H3TM4s1Fle7dEdBFw4VWdp2md1c8RzL29wfW1Ive3y5CPTjEYRs60ycZKy3h7ieRYXl5o0ah6+53J+scZCq4xpGlxZ7XN+oU4YxSRphmEYPHlhimrZBcPAWNkiywzqFYskzn8epplPK/VHMc0MXMvEciyurfUYBgkzDY/NrYA4gTc8PsWX1ad5+XoXdb5FyTGIkvz8SsmzaHfz9Q3XtYr2uwNc22JxusJWP2QUJliGwcJ0Gb9k70yJxklGmuajlu1kv3t9LYySYjoyvalce9lzOLUg/cfFZEkCeUjsng4LY8jSlNc+Nou+tIlpmLx8bYuLp5pstAfMNH38ksMoiFiaq5LGGZERMdssMQryef3eMMKz82J/q+0BrmsyjBKyJO817jpW3mMktej3My4sNlnZ3GKzF2BbJqZtsb455MvOt1hrD7iw1MAyDc7M1BhGMf/+c9cxTDg9V6VZ97hyvUenHzIchczPVCFNqVdLpFnet+Tlq1vMTft88ZU2Z+cblF2HhVa+VrT9Tr5azt/FQ35gb609hDTl3GKdtfYIw8iwTIPFmQq2CQvTFUZxmvcVjxKa9TKP2CZZktGslen3Q3q9cOdwZ9138F2Ym65wbt4gTVNeuNKm38+LQVqWSRQnzLV8DMOgUnYwijcI2/9tLNPAdU2aVQ+7aIdLUWIGijUty2BlZbDTtjnL8t16/eFht1YW4vYkgTw0bkyHdfoBJdciKQr1DYIIz3Xo9gMsO9+91O2HPH6mxaNnGpQ8i17RKvXaxgDDqtGslri81mOqXqbTDVltj4iThMfPTbPZHeE5JmXPoV5xMI18BLS82idNMmzXYm2jT6NaolpxsTcseoOQJy9Oc+lqm0Y1LwDp2mbegGkQYlp5eff+KOYzz6/x6OkGxjDgtY/M0O8HPHqmyeXr3eJwXcZMq1y8gzd2Kg7f2ORw42cxGEWkGZxbqBNECZ5j4TkGoyDNF/ODlHY3ACNjGEZ4tkVs5KVUTNPANA3SNKPTy/uhu7ZJpeTg2SYbvZBuP8S2TOoVlzSDV67lJ/ZLrgVZwtX1AYZp3FRWxrBMXlpukyRgWQaPnGoAKd1hvqhe9R2yYgfHdvKyTAgjSSBisiSBPFTyd7uNisdmZ4Rl5r05wKFZdUnSlDRNmZ/yOTNXY6ZRYraRV/ENamU6/QDHtjHNjKXZKuvdIZ3uiGrZZqY1xUtXt1i+3uV1j81Qcm063RFlz+bcQpVapcSphSrdXv5O2TRNRmFM1feYnSpzbr4GZNiWSck1WJrxubTcxbICesOIjc6AU7NVdC/I35kbBhcWG7x8tcv8lE8YDjm7UKNVKzPT8KiUXfqD8DabHIqpwWpeiXetPcA28/pi0w2fZhWurY/Y6oeESUqz6rGy3mem6bM4U8EyDdI4Za51o/NfsnOwL68gECUxSQbr7T5hDJBRLrs0Ki4l22AQ5tV3HcfEyDKmGmWqvkMSxcy1Kjsjp7X2kChJSeKilE3N4/RclWGY7NRGMwwD17EZhpJExORIAnkI7ezM6gyZa/mstvucmavS7Ye06mVsC1zbwtiZOjHwit+Uza0hSZJRqzicW6iz0RniuQ6fv7Sejxx8l0opPxx4fn4Wy8rLorg2PHluii++0qFSzsuwn5qtstUdEgQxX7i0wbmlOsNR0U1wyqc/iomTjJKbl0wfjPIe4I5tM13PT52X3HxU8frH5vIT4MX22NlmidlmOT+MVyww5B0gKXYzWcULPbiOSaNeYqublzbv9QLq9RKthscgihkGPhudAbZt8fJKfs5jdb3PVMPHd03OL9ZIsoypuk/Vt4qT/yMyIAhjRlHeH951TequBUZGL8jQL22QphAnKTON/L+HYZoYGJRcEzsxyYCtQUil7GKQr4d0uiOmm3lnxN0JcruhlBCTIgnkoXTz7q4LpxqQJfSGcbHDJz+sNtP0dzWzyuhsjZht5u+4wyihVfEIooTNzohWrUSzVsIvmSRJyiDImAaSOIMMPNvm8dMNmtUSm70Rm8UJ+37RkdB1bTq9gE43L7tyfrFOrezSH4acmm0wCiKGQUK3P+LUfI2NrQH18vaUkU2S5PfJdkYb+QJ0b5AU260zesMY17Uo2fmUluNYBGFMGOfnMeanfHzPojtMeemFdUquxX+8tJmXXamVeO6lTdIMzs/nBzDXOnlJkUGQEIYJWdKn3TXpdEOqZZsMSLOMSslmYbpClmU4dl5JeWNrSM13izpf+YL4uYUaJhmjOGVlIx/VRGma7xizDaJ4e83DoOzaNHbOilh7GkoJMRmSQB5ae3d32dTKLlP18r5bhsMoIUmh5JhcWKzRGyV0enk71jDOmG6UWO8M6I9sFptlbDdvb5skN0YxU/USFd9jblRmaxCx0R4wCFMsa0h/EFJybbaMkN4gYq0zoOa7LK9HXN9Y4cKpFoNRRLnk0O2NKHl5ZduLp1tUPIuF2drOYvN23EGc7pzViZKMze4IwzA4t1AD4IUrHeZaeRMoA1htjyi5Fi9e7WAYBq1GmTRJ80OKDR+AWskGwyCKE6abFSpllyDMp/Hylrr5fTy3Qsm1cGyL/iDGNAw8Nz8YutbJi0TGScpcy4EsL4efpHldrjBMdtY4LMMgiBJ276/aXs/xbFNOo4tjJQlE7PLqW4a3T7SnGRgZrG4OSLOMsmNi1T2GQcKjZ1t88dImKQaGAaMoYWmqclO73u11h1q1RDCKcOw0L+kxVcHIUvySQ1I0VmpVXa6tD9loj1jZHFCvuEzXPdSZJisbA5I0P1E/1fCplW7tqLe7jEuUpDulYJJim2ycZIzCBL9kUat6XFvv45cqpBn0+iGDUcRUo8TyapcozvusL85WieMUsnyqzDDzUYZV3Nsu1iOiJMVLTRanK/T6IbZp4NpWfhbHNqiWHYZhwvWNPqfnamQkTDVKkEG1bOO5N9ZA8j7oNxbNpXquOCkkgTy07q4c/e6tpnGSkWUZ9arLemdEtxcwilOqAxt1foozcxW6wwgjM6j4+1UNNoqGTglhlDDTLKFf3iQMyQsFVlxM8pauC9M+Z+er+GWHwTBiMIiIKx6zzTJJmnFqrrZv8oCbS85s78TKd03BZnfExtYQy4Q0dVnr5HWskjTDti38cv6ziZOU6XqZqapH7dEZNrYCKiWbtFib6fdDVjbz0VLdd8hSmJvy84Vt06DiWfynTy0RhREpMAwiar4L5Du3PMeiXvGYnyoz1/AI4ry9qGMZO+dA3IrD0tytIywhjpskkIfSOOXo92x9TTPSLOV6lJIBlpmX6RgF+bv+kp3/aoVRXr/rlmczjJ0pmFrZwrLM/KyEadAbhFh2/p4+SzNc28J3TOLIIgiTfAdUmjHbLL9q8oBbS8G0aiVKnsX1zT5Z0a43ThJevLbFdMPnzHyVLIVhEFJ289ax5ZLDTLOE41j0hyHnFus0Km7ev92EJMmYbfqstgfFNl6DMzMVgiTd6e8BIY1aUeAxzijyAmXPIUkzLp5q7Pw7PDvbp0zO/iMsIY6bJJCH0D33WC+2vr6y0qPsWXieT6vmMQgi4iglivPyhQcvMGky1yjRqLgMRjHTzTKObebTOb5LpzsiywwaFYezCzUqJeeA78T3loIxGYzy9sCOZeYLz6ZLuxcxGEZExYu+X7JYmCpzZrHBRqfPKIxxLJNHTjcpuRYzTZ+N9pBiUxclx+TsfG2nxDpkrCxv7fT3yHdOBZxfqrMw7e/87N0iwd2cHKRfh7h/SAJ5CN17Ofr8Rc51bUqulY8+0nwhupuE2FY+QrjbufreILplVLTQyivw7v9imm/Nvf0L7Z51nZKxU9IlzcA2TXqDgFrFAxNaVY80S2nWSrS7I1p1nzRJaFa8nZ1pVd9hvT3ENMAoamvZBvnIxDbpDqNX+fmmB0wO0q9D3B8kgTyEDqccvUGtZDG7M90yzgjhhtuPivbbbTReV8i9lZTTJOX8YoPuIIA4r4e1MFXFsU1qFY/pls9U1YWMXf8mmG2WubzWZ2VjQJZltGolerUQr166w893d3LYXoeKZaQh7kuSQB5Ch1eO/vCmWybXFfLmmDEMDLaYqnvESUoQ+bR7AY5lYnkGSzNVHNJb/k0V38EyDKYapZ3T4GvtEVXfO+DPd1JtkYU4OhNPIEqps8BHgTlAA9+ite7tc83ngBeKh65rrb9uooE+0A5znv1wplvurStkRpTk5c/7oxiveqd+8TePAsJGvi5hYFB2LRbOTe2MohZnKqyt9W55hjBKsUwD373xJ3Qj4Tl3/PlOqi2yEEfpOEYgPw/8vNb615RSPwT8EPD9e655M/CrWuvvmHh0D42TNc8+flfIjK1BRKcX7HRvjBOPsmsXJUxSMMzbbIG9fTK9+XT3ja3PGAaGkZFlN76+t2Dj7X6+k2qLLMRRmmgCUUo5wFuAbywe+jDwh+yfQJ5SSn0K2AK+R2v92UnFKY7DeF0hr60PdpLH/JTPKEy4fGmdesVjc2uIZZqkWcZMw6fsmkw19psmevV1iWznVf7mKSfLBM+1CcKYLIMkzYscUrTovdNoblJtkYU4SpN+qzMDbGmtt0uGXgVO73PdCPgnWus3AX8f+C2llDuhGMWxMYpzIU7xYn7ntYyl2Qqn52qcW6jhe1Zx9sLk6nqfIMpYXuuTprCyOQDD2OkJv788Sby43OHKSo8XlztcXeuznVR2TzklKURRwtJcjXrNw3VNBoOQF5e3WN8KgFe7R247AW4PcOSEubgfHdkIRCn1LuBDex5+bp9L070PaK2f3vXxJ5RSPwE8ATxzkHtPT1cPHugBzc7WDv05j8r9EuthxFmuRIRpMf0TJ/i+h2MbxJlBnCS4noPj2TiWhVd280OJvstUo3zLc/UGEfFWSKOoewWwsTXi/GIDK4pvenyb57kMwpRa9cafUgyUK+U7tpmdmck4PYyL0Y5NpWzfc0HEh+m//SRInLd3ZAlEa/1x4OO7HyumsNaVUpbWOgEWgeW936uU+i7yNZD14iEDiA567/X13k63tsMwO1tjdbV7aM93lCYf692VRNl2b3HuvqeJQ8ZqZ4hpGgyHAX6jRBJFRHFGGEREgUNETDB0GaYZrYpDsk/fjO4wYnNzcNNjzabPyloX17HodAa3TDl5Frd8D4DvmAzLB+9TPgzjey7Ffr/8nkqch+sw4jRNY6w33hNdA9FaR0qpTwLfBPwq8B7gd/e59K1AGfhJpdRbAQt4dmKBigM6jq2o+92zxPmlOmGUUqu4dHsjzFaF1XafhZm8jPp8y8ckY+pAC/M3HrtR+Xb/Rf7d/cz3fo8QD7rj2IX1ncBHlFI/CLwMvBtAKfV+YElr/cPA9wAfVkq9BxgC79Za3zLVJY7XcWxF3f+e+fmLWtmhVrZ3Tq7PTZfpbI1IiumsSsVjuu5ykNpZ20liql7aOQey/yI/h3SmRoj7z8QTiNb6JeAv7fP4L+76+Arw9gmGJcZwHFtR73xPo3jxzri2EZJmeWVb17ToDsJ8raFkv2oJkb1J4uZzIPtvzZXaVeJhJSfRxdh2n8XYPsjn2Rauc3Sb+w62/TVjtT3ipatd0jTDcUxadY/BMKY3jKmWbaZrJab2nWq7OUkcbFH7ZJ2pEWJSJIGIseVTPiUuLXd3uv3NTfn0BxFe/U7bcO/lnrefMgrijE7RMhfAcyxeutZjOIqoVzxc22QYJFR8Z99S88djvM0IQhwnSSDiHhhUfZdGzaVSdrAtgyzNWG0PqRzZOsidDxyGUYJlQqPq0ekFWKbF8mqXmaaPbeadBFc2BpyZq+JVjyqB3E1CuPWQYqNeouzakkzEiSYJRNyTMEpJiv4fSZLtevxe10Fu9wJ8+ymjfJorL2tS9mww80RXKd2okZVlGdlEd4q9+u603RsDTAOGYcrLz68x1/JxbVOKLIoTSxKIuCdHU5Lj3rYH7+1EaNsG5+ZrO2VHDANatRKV0t4Y90tad+9ud6ft3hhgmAYrmwPSNNvpiS5FFsVJJQlE3JPDKw1/w71vD761E2Gr5nJtfUQQJ3i2xcJ0ec8IZv+kNTNz9wdS73Z32u4kHCcZaZphGOz0RJcii+KkkgQi7tHht2A9nO3BNxdIxPdYMi2iNMMxDfzSzb/6QZy3sw3iZFd/jyGnh7eeWL+Tux2V7U7ClmlgWQY138WxjDt+rxDHSRKIOASHu431cKfFtkcWAzr9iO4gZLbpU/FMarXthWqTje6I5bXezuijUfWo+w5hFO88z0EXxe9+VHZzEq5VbvSBl4OJ4iS7bQJRSn357b6utf7zww1HiMOdFtueDgvjjE4vIMtgtT3Anq7yYrFQbRoGGRm2bRJFKVkGnV5QNJWyGYbRXa7JjDMqu5GEd5+ml11Y4iS70wjkn9/maxlw8RBjEaJw+K1yoyS9aU1lfWtIUhx+BNjcGrE4XWV5rVesQRg0ah6Vsk27k7FRFGuMkwzLNNjo3GlN5l5GZXIwUdwfbptAtNYXJhWIEDc73Fa5jmXuTIttz4ztXqhO0wzThHMLNeIkw7YNZpslDMMgjBKGYbqzO8o0DeZavixsi4fegdZAlFIzwLcCVfK3gRbwqNb6W44wNiHu2Y3psAGNqkd3EDI/5bPWGdKoejsL1a1aCcsySOIM04CpWulGcjAMVtuDnRYBaZqx2h5w4VTjuP5ZQpwIB11E/3XyqrhPAv8PeaHDTx5VUEIcnpunw7aHITPN8k0L1ReWasU16a1TZllGzXd31lAMA2q+yy1bxYR4yBw0gZzTWj+ilPp54JeAp4HfOLKoxAMvyzKCOJ3gQnFGnKRkGFRKJq7jYFsmYZxR821qJQsw962N5ToWjUp+qn37cJ9rG7K1Vjz0DppArhX//0XgKa31x5RSsgVYjCnj6lqfF5c7E2hElbGxFXB5rc/KxgDI8FyLSjkfUcRxSqtW4sJSjel6ad/759NgfnGy3ZSttUIUDpoEVpRS/yPwp8CPKKW2AJkAFmMJ4oz2YDSRRlRBnLHeHbGycWMB/PrGkCDqcXa+RhSlbHZHlNdtqr73Kvc//MOSQjwIDrqF5DuAQGv9x8CngA8C339kUYkHWhglpGlGBliWgWncOGl+FPeK42xnATxJM5IkYxQlZEWPyyyDIE7ucP/tMxrOTuMqIR52BxqBaK1XgJ8pPv5+JHmIsWX0RxEvX+/T2RrubIktu+aRrCm4joVtG5imQZpmO6VCSo6FcWOTVdEIS9Y0hLgbB93G+1lubJ/fobV+3aFHJB5oebOnEZWyw1Z3uLMl9rWPzhzJmoJnG0zXSgyDZGcNZH6qvLMGsl2ZNy+uKKMKIe7GQddA/tauj13gG4Hlww9HPOjyk+EG040SWZLs7GoquzZHMy1kMFX3qPgOZ+aqO7uwAAajpPjckmkpIcZw0CmsP9z9uVLq94D/F/ixowhKPLi2T4YbhlFUvTUnUG3WwLOtW7oPelXZSCjEvRi3DsM0sHSYgYiHw/bJcNPIF9AxoNUo4d0Xr+X52ZXuMCKIU/aZ1RXioTLOGogBnAX+0VEFJR5kBtN1l24IyytdLNNgszPEMowT3rb1Tl0Sb5R73z7tLtt9xYNunDWQDFjVWn/hCOIRD4EghsEoolRMWx3lOZDDcvsuibC+FbDRGTIMU1bbA2q+S6PiMNP0T3hiFGJ8B00g79Fav3f3A0qpf661/mtHEJN4wB1Ox8HJul3MYLHWzrckb1fs7fQCyp594hOjEPfiTg2lfgE4BXyNUmp215dcQB1lYOLB5ToWgyi96bHbL6QfvBvgUbldl8Tt5LLdzxzY6UHiWOaJToxC3Is7jUB+BXgKeD03N5eKycuaCHHXPNtgql6i3R4coOPgndYeJhfzq3dJzJOLZd44sLi7B4kcUBQPqjs1lPoU8Kli2+5FrfUfKaWmgLdorb80kQjFA8hgcaZCWpQPud2o4vZrD5Mchbx6PSzPzpPJRmfIXMvfWQNxi6Qj01fiQXXQNZD/HvhK4C8DPvADSqmntNb/87g3Vkp9EEi11k/v8zWXfPTzJvI+JN+stX523HuJk8cw8tpSd5raOVnrJa/WJfHm5HLhVEN2YYmHwkH/At8J/BUArfVl4K3Afz3ODZVSDaXUrwDfd5vLvhvoa62fAD4AfGSce4n73/baw24nc1roRrHFWsmWoovioXDQBOJoraNdn4dA+moX38E7yfuK/PRtrvl64GMAWus/AmaUUmfHvJ+4j22vPWwnEenFIcTJcdAprD9RSn2MfFopA74d+Hfj3FBr/U8AlFJP3+ayJeDqrs+vAqeBl8e5p7ifSS8OIU6qgyaQ7yLvAfIPyHdg/R7wI7f7BqXUu4AP7Xn4Wa312w5wv/1eHQ484pmerh700gObna0d+nMelfslhi+KkwAADwNJREFUVonz8N0vsUqch+u44jxoAnkd8BiwQf7i/pWAJi9psi+t9ceBj48Z1xVgAXi++HyRu6j+u77e29mPfxhmZ2usrnYP7fmO0v0Sq8R5+O6XWCXOw3UYcZqmMdYb74Ougfwy8CdADfgo0OHmcyGH7RPAewCUUl8NjLTWMn0lhBAnyEETSKa1/nvAvwWeBd4FvOUwA1FKvb/Y2gvws4CnlPoceSfEbz3MewkhhLh3B53C2h4fvQA8pbX+E6XUPe2j3Hv+Q2v9i7s+HgHfdi/PL4QQ4mgdNIH8O6XUPwN+CPgdpdTjQHJ0YQkhhDjpDjqF9beBD2mtnyM/2GcC33xkUQkhhDjxDtrSNgP+rPj4d4DfOcqghBBCnHxSY1oIIcRYJIEIIYQYiyQQIYQQY5EEIoQQYiySQIQQQoxFEogQQoixSAIRQggxFkkgQgghxiIJRAghxFgkgQghhBiLJBAhhBBjkQQihBBiLJJAhBBCjEUSiBBCiLFIAhFCCDEWSSBCCCHGctCWtkIck4wgzgijBNex8GwDMI47KCEEkkDEiZaxvhWw1h6SZWAYMNMsM133kCQixPGTKSxxYgVxtpM8ALIM1tpDgjg73sCEEIAkEHGChVGykzy2ZVn+uBDi+EkCESeW61gYe2aqDCN/XAhx/CSBiBPLsw1mmuWdJLK9BpIvpAshjpssoosTzGC67lH1XdmFJcQJJAlEnHAGnm3g2TJYFuKkkb9KIYQQYzm2EYhS6oNAqrV+ep+vnQU+B7xQPHRda/11EwxPCCHEHUw8gSilGsA/AN4N/OSrXPZm4Fe11t8xscCEEELcleMYgbwT+CLw07e55s3AU0qpTwFbwPdorT87ieCEEEIcjJHtPak1IUqppwFeZQrraeCq1vqXlFLvAH4WeEJrHd7hac8Dlw41UCGEeHhcAF486MVHNgJRSr0L+NCeh5/VWr/tTt+7O6lorT+hlPoJ4AngmYPce329R5oeXmKcna2xuto9tOc7SvdLrBLn4btfYpU4D9dhxGmaBtPT1bv+viNLIFrrjwMfH+d7lVLfRb4Gsl48ZADRYcUmhBDi3p3UbbxvBd4LoJR6K2ABzx5rREIIIW5yYg4SKqXeDyxprX8Y+B7gw0qp9wBD4N1a6/RYAxRCCHGTY0sgexfPtda/uOvjK8DbJx2TEEKIgzupU1hCCCFOOEkgQgghxiIJRAghxFgkgQghhBiLJBAhhBBjkQQihBBiLJJAhBBCjEUSiBBCiLFIAhFCCDGWE1PKRIijkxHEGWGU4DoWnm2Q1+cUQtwLSSDiAZexvhWw1h6SZWAYMNMsM133kCQixL2RKSzxQAvibCd5AGQZrLWHBPHxNFIT4kEiCUQ80MIoYW/TzSzLHxdC3BtJIOKB5joWxp6ZKsPIHxdC3BtJIOKB5tkGM83yThLZXgPJF9KFEPdCFtHFA85guu5R9V3ZhSXEIZMEIh4CBp5t4Nky4BbiMMlflBBCiLFIAhFCCDEWSSBCCCHGImsg4gEmJUyEOEqSQMQDSkqYCHHUZApLPJCkhIkQR08SiHggSQkTIY6eJBDxQJISJkIcPUkg4oEkJUyEOHqyiC4eUFLCRIijNvEEopT6KuB/ARxgHfhvtNYv7bnGBX4FeBMwBL5Za/3spGMV9zspYSLEUTqOv6yPAe/VWr+h+Phn9rnmu4G+1voJ4APARyYYnxBCiAOYaAJRSnnAD2qtP1M89Bng7D6Xfj15ckFr/UfAjFJqv+uEEEIck4lOYWmtA+CjAEopE3ga+K19Ll0Cru76/CpwGnj5iEMUQghxQEeWQJRS7wI+tOfhZ7XWbyvWOD5S3P/H9/n2/VY604Pee3q6euA4D2p2tnboz3lU7pdYJc7Dd7/EKnEeruOK88gSiNb648DH9z6ulKoC/xf5Avo7tdbRPt9+BVgAni8+XwSWD3rv9fUeaXp4J45nZ2usrnYP7fmO0v0Sq8R5+O6XWCXOw3UYcZqmMdYb7+NYRP8oeWL4G8WU1n4+AbwHQCn11cBIay3TV0IIcYJMdA1EKfVG4J3A54G/UEoBLGut36GUej+wpLX+YeBngV9SSn0OCIBvnWScQggh7mzSi+h/wauc5NJa/+Kuj0fAt00qLiGEEHdPTlgJIYQYiyQQIYQQY5EEIoQQYiySQIQQQoxFEogQQoixSAIRQggxFkkgQgghxiINpcQBZARxJo2ZhBA3kQQi7iBjfStgrT0ky260hp2ue0gSEeLhJlNY4raCONtJHgBZBmvtIUF8eMUqhRD3J0kg4rbCKNlJHtuyLH9cCPFwkwQibst1LIw9M1WGkT8uhHi4SQIRt+XZBjPN8k4S2V4DyRfShRAPM1lEF3dgMF33qPqu7MISQtxEEog4AAPPNvBsGbAKIW6QVwQhhBBjkQQihBBiLJJAhBBCjEUSiBBCiLE8aIvoFoBpHv4OoaN4zqNyv8QqcR6++yVWifNw3Wucu77/rg54GdneY8b3t68GPnncQQghxH3qa4A/PujFD1oC8YA3A1cBqbUhhBAHYwGLwP8HBAf9pgctgQghhJgQWUQXQggxFkkgQgghxiIJRAghxFgkgQghhBiLJBAhhBBjkQQihBBiLJJAhBBCjOVBK2VyKJRSZ4GPAnOABr5Fa93bc80i8E+BWWAIvF9r/ekTHOs/BhaAFPg+rfUfnLQ4d137duAHtNZfO8H4vhn4QcAFPqS1/od7vv4G4H8DGsAfkf/3jicV30Hj3HXdR4B/o7X+8ATD2xvDnX6m7wR+hLw72SXgb2qtN09gnP9lEadFftDufVrr8KTFueu6rwd+Tmt94ahjkhHI/n4e+Hmt9WuATwE/tM81Pw78htb69cDTxfcch4PE+lPAb2ut3wC8G/hVpdSkm5rfMU6llKmU+l7g17jLmjz3Qil1Cvgx8lI4rwfep5T6sj2XfRT4Lq314+QveP/dpOLbdpA4lVJLSql/Cbxr0vHtieO2sSql6sAvAF9f/A19hvzv6KTFWQF+Dni71vpJoAR8+0mLc9d188DfZ0ItQyWB7KGUcoC3AL9RPPRh9v9jfC/wj4qPLwDH8c7poLH+JvCx4uPnyf8Iqkcd37a7iPOJ4n+TfnF+G/AHWusNrXWfPM6/vv1FpdQ5oKy1/rPioQ9zPC/Qt42z8C3A/wn8+qSD2+NOsTrAd2qtrxSffwY4O+EY4Q5xFo+d11pfL5LJHMfwt36nOHf5ZfLR0kTIFNatZoCtXdMTV4HTey/SWqcASqlngfPAOycV4C4HjfU3d336fcBfaK07E4hv20Hj/Bzw3yql/tIEYwNYKmLadhX4T+7w9Vvin4A7xYnW+qcAlFJfPcG49nPbWLXW68BvASilysAPAD87yQALB/mZRkqp/5x8FHoF+NeTC2/HHeNUSn038OfAnzEhD3UCUUq9C/jQnoef2+fS9NWeQ2v9mmJ+/F8rpV6jtd44zBi3HUasSqkPAN8BvPUQQ9t7j3uO8xjsN9xP7+Lrk3JS4jiIA8WqlGqQJ5JntNYfOfKobnWgOLXWvwtMK6V+nHzq7ZuPOrA9bhunUuop4K8BX8sE39w81AlEa/1x4OO7HyumW9aVUpbWOiGvULm893uLhao/1Fr3tNafVkq9BFwEjiSB3EusxbU/CXw98Bat9eWjiPEw4jwmV8jLWG/bG98V8g0Ir/b1SblTnCfJHWMtNnf8K+APgL89udBucts4lVJTwJu01tujjo8B/2xy4e2408/zXcVjnyJfZF9SSn1Sa737ew6drIHsobWOyHuKfFPx0HuA393n0m8D3gdQLGYtAM9OIsZtB421GHn8ZeCrjjJ5vJq7+Jkel98DvlYpNauU8snfyf3f21/UWr8EjJRSX1U8dFzx3zbOE+a2sRabOH4b+HWt9Qe01sdVFvxOP1MD+GixixDgb3AX/TIO0Z1+R/+O1vrxYqPMO4Dlo04eIAnk1Xwn+S6Hz5Nn/R8EUEq9Xyn1weKaDwBfp5R6hnyL7LtfbVvqccaqlDKAv0O++PdvlVKfLv63dJLinHAsNykWcv8n4N8AnwZ+VWv975VSn1BKvam47FuADymlvgBUgJ85oXGeCAeI9RuANwJ/fdfv5C+ftDiLtZr3Ab9d/K0/Dnz/SYtz0vFsk34gQgghxiIjECGEEGORBCKEEGIskkCEEEKMRRKIEEKIsUgCEUIIMZaH+iChEJOglOoBT5GXdPkBrfV+NYy2r30z8F6t9fvv8h4/B6xprZ++l1iFuBuSQISYEK31p9i/AN5uT3I8dbaEuGuSQITYpSjk+FPkpSMukvd6+Xbyw2NTwCPkJ6h/CPh75HXFLOAvgO/WWm8ppb6GvDBgRt4/wtz13D+ntX5KKVUtrvkqICavB/ULwAeBhlLqH2ut/6ZS6q9yowfEgLyXy58W5dB/mby099XiOY7jhLR4iMkaiBC3+nLgp7XWryOvMvBPi8d9rfWTWuvvJ68eGwNfUfSzWAb+rlLKJa8F9r1a6zeSnxwu73OPD5KX1X8CeAN5InkE+GHgk0XyeIy878w7iud6H/CbRVnxHyFPbq8hr4OkDvuHIMSdyAhEiFs9o7X+ZPHx/w78Q/J3+bvf4f8XQBN4u1IK8hHCCvBaINJa/z6A1vr/UEr90j73eBvwPxTFJROKCslKqW/fdc3byQvk/X5xD8grsD5afP92DalVpdS/uJd/sBDjkAQixK12t6o1iv8lwO5aZxbwPUWZb4opqRJ5U6S9pbf3a30bk09xUXz/GfIpqt0s4Pe11t+057rl4nt332fi7XWFkCksIW71BqXU64qP3wf8CdDec82/Av6WUspVSpnk/dJ/AvgsYCil3gGglPoGoLXPPX4P+Laija9H3mHureSJwCmu+QPgryilXlM81zvIO/eVyCuxvrf4/hbH09BMPOQkgQhxq2vAjymlPgt8I/Ct+1zzo8CL5IvnnycfDXxvUbr+G4EfVUp9GvivyKe29voRIASeKZ7jE0XnyD8FXqOU+hdFh8b3Ab9WVIL9UeAbipamTwMReQuBf0meuISYKKnGK8Quu3dKHXcsQpx0MgIRQggxFhmBCCGEGIuMQIQQQoxFEogQQoixSAIRQggxFkkgQgghxiIJRAghxFgkgQghhBjL/w/Diasd/HSWfwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ror_robust_insamp = model_performance(\n",
    "    y_train, ror_robust_trace, ror_robust, samples_=10000)\n",
    "\n",
    "_ = sns.scatterplot(x='predicted', y='actual', alpha=0.25,\n",
    "                    data=ror_robust_insamp)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Applying the inverse transform to the model's prediction to get to the 'natural' scale of the data labels (or dependent variable observations)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 10000/10000 [02:04<00:00, 89.04it/s]\n",
      "20000it [00:04, 4079.07it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE = 0.12263353677327299\n",
      "Deviance = -6274.349036693466\n",
      "% observations in 95.0% prediction range = 95.59880239520957\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ror_robust_insamp_tfm = model_performance(\n",
    "    y_train, ror_robust_trace, ror_robust, samples_=10000,\n",
    "    y_inv_tfm=label_itfm)\n",
    "\n",
    "_ = sns.scatterplot(x='predicted', y='actual', alpha=0.25,\n",
    "                    data=ror_robust_insamp_tfm)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We take a look at the residuals again, just because it makes me comfortable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = sns.distplot(ror_robust_insamp.error)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Looks like a nice Student-T distribution, just as we specified in our model! We now use the model to score the test dataset."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Out-of-Sample Prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 10000/10000 [01:58<00:00, 89.44it/s]\n",
      "20000it [00:03, 6124.11it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE = 0.12880914571341537\n",
      "Deviance = -1527.639708198232\n",
      "% observations in 95.0% prediction range = 95.08982035928143\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "load_test_data()\n",
    "\n",
    "ror_robust_outsamp = model_performance(\n",
    "    y_test, ror_robust_trace, ror_robust, samples_=10000,\n",
    "    y_inv_tfm=label_itfm)\n",
    "\n",
    "_ = sns.scatterplot(x='predicted', y='actual', alpha=0.25,\n",
    "                    data=ror_robust_outsamp)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model Comparison\n",
    "\n",
    "We begin by comparing marginal parameter distributions using side-by-side forest plots, starting with all non-categorical parameters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = az.plot_forest(\n",
    "    data=[ror_basic_trace, ror_robust_trace], model_names=['basic', 'robust'],\n",
    "    var_names=['tau', 'sigma', 'beta_mean_res', 'beta_BPL', 'beta_lots'],\n",
    "    combined=True, rope=(0, 0), figsize=(6, 6))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then starting-bids and auction mechanism catgories."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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55IAzM7NccsCZmVkuOeDMzCyXHHBmZpZLDjgzM8slB5yZmeWSA87MzHKpWQJO0ghJE5qhnyMkndfEc4ekP3TaUJsJkkY0pf81rOHi9HfkmvWc+uqWdKSk0UWON/pa1Gn/PUnPS/qnpGPW9DyzBi1fQqvFr8DyJaWuxDZRLe0Pnu5R6gLW0f7AoxvgHAAi4m7g7qacW0vSnsApQH+gEzBV0uSIWLwu/dqmrfy1Z2g7627KOvakZsnbfLTrkazaakCpy7JNTIMBJ2kI8CugHJgNfAMYD+wOrAbGRsRNqfn2kqYA3YB7gB8CWwOTI2Kb1N+o1HYM8DugX3p8NfA4MDK1ewWYBYyOiGF1auoEXA9sCWwBTAFOq9NmMjAXGAxUAOdGxIPp6eGSzgY+D4yJiHGSqlKfnYFewG0RcWEDr8uWwC1A+/Q6fBvYERgEXCfpaKBrus5KoAtwQUT8Mc10uwHbA5cWnhMRs+obEzhc0jlAW+DnEXF7mtUNiYgRkg4BrgCWA88X1HoecHqq86mIOKtOv8OAOyJiObA8vXaHAzexkWr72LWlLqFkypYuptWyd0tdBpS3ofKYUZR3qWLVO/PgjlHw9B84HGDGX0pW1urPdaamsmvJxm8JPtqv7ltAfq3JEuWOwIERcTowClgUEf2AA4FRknZL7bYFjgUGAPsCRzbQ5z5A14gYABwMfDEingOuAa6JiBsiYnrdcEuGAzMjYm9gB2BvYGCRdu0iYiBwEnCjpLbpeAVZ8A0nCyCAE8lCbS9gN+BsSd0bqP/rwL0RMQi4ANg3Bf104IwUVOekrwem9hcVnL8oInaOiBvrnNOQylT3l4FfS9q89glJ7YAbgeMiYg9gWTremuyDxiCy2fHqFOaFtgDmFzyeT/bhwazJyjp0o7xL9qNW3qWKsg6bdqhYaazJEmVExHvp6wPJ3qyJiIWS7gKGAO8Dd0fEAgBJt6fj/6inz9lZMz0A3Af8YE0LjojbJH1B0rnAzmSzoQ5Fmo5P7WdKmk8WXAB3RUSNpDlA99RmrKQDJJ1PNqtsSzY7W1hPGQ8Dd0gaAPwF+E2RNqeQzbq+AuxVp8Yn1/R6C9wYEdXAG5KmkoVdrV2BNyJibm1bslletaQngGnAXcBvI2JenX6L/Rn41U2or8XYlD6h1tV67kO0iodLXQY1Hyxi1TvzPp7B1XzQMla8V/UeRPXOQ0tdhm0gaxJwywq+rjvjKyvoo7rO8ZVADZ9+A20DrIyIRZL6AkPJlshmpMeNSst0xwHjyIKmH8XfpAvraVXwuBoghVxtn5cDfYBbgTvJZpXF+iSd+7ikXciW8o4HRqRrKfQY2d7aZGBS6rvWMtZesde3Vg2f/t4Utj2KLGAPAyZKOjki/lrw/Dxg84LHvYDC520jUr3z0BbxBl7+2jNw15hP9uD6H8uqrQYw6dUpHNT7S6UuzzYRa3sX5SOkGVxawjuK7A0cYJikzpIqyJb8HgbeBbpI6pGW0Q5N5x4J/J5s9vNt4ANgK7I35sZCdyhwbUTcQvbG3p9sj7CuE9JYg8j2wBpaAhwKXBYRf0x1VNXTJ6nPXwGnpiXGb/HJEmk10FpSV7Kl3Ysi4j7gkAb6W5NrBjhRUpmkrYE9gacKnnsW6Clp99q2qc4eZHuRsyLiIuBBPpnJ1rofOFZSZWp/EFkgmzXZqq0GsOzA81jedxjLDjzPN5hYSaxtwI0GukqaRXZzx5iImJGee55suXEG2f7Ug2lp8zKyJbKH+eRN+X6yWcycdOyOtAc1BThZ0jmSBkm6r0gNVwI/kzSD7OaUJ8j2/+rqk9qMA46PiFUNXNclwM2Snga+T7YvVqzPWleRhcJM4M9kN98ATCTbR9wJuA6YI+kZoCdQKal9kb4mAtdI2qeB8SD7EPA0cC9wVkR8vHwaESvJQu3mdM2V6fgC4FpgWrq2LsCEwk4j4imyDxvTgL8BPy2yjGm29io6srrr1lDRsdSV2CaqrKamptQ1NLt0J+CoiJhc4lJyb9q0Z2sqKytLXYZtJLxEaU3Vt+/29W4b1ael/R5ci5F++fqqep4eFhFvNPN4l/HZfTyA6RFxRnOOZWa2KcjlDM42HM/gbG14BmdN1ZQZnP8vSjMzyyUHnJmZ5ZIDzszMcskBZ2ZmueSAMzOzXHLAmZlZLjngzMwslxxwZmaWSw44MzPLJQecmZnlkgPOzMxyyQFnZma55IAzM7NccsCZmVkuOeDMzCyXHHBmZpZLDjgzM8slB5yZmeWSA87MzHLJAWdmZrnUutQF2MatXbsKli5dWuoybCPx0fLl/nmxDcYBZ+ukV69epS7BNiJzVr/ANttsW+oybBPhJUozM8slB5yZmeWSA87MzHLJAWdmZrnkgDMzs1xywJmZWS454MzMLJcccGZmlksOODMzyyUHnJmZ5ZIDzszMcskBZ2ZmueSAMzOzXHLAmZlZLjngzMwslxxwZmaWSw44MzPLJQecmZnlkgPOzMxyyQFnZma55IAzM7NccsCZmVkurXXASRoiafK6DixppKSR69pPQX+N1iVpgqQRzTVmkf4vlrRfc59TX92SjpQ0usjxtf4eSaqSNH9tzjEza8lal2rgiLimVGOvR/sDj26AcwCIiLuBu5tybiFJw4Argc3XtS+z9em9D1aw4L3l9Nisgs06tCt1OdbCNTXgukuaCFQBTwLfjIgVkr4FnAq0B1YDx0fEXEljgaHAKuCuiLhY0iiAiBgl6STgJ0ANMA04E9gdGB0RwwoHltQJuB7YEtgCmAKcVqfNZGAuMBioAM6NiAfT08MlnQ18HhgTEeMkVaU+OwO9gNsi4sL6Ll7SlsAtBdf5bWBHYBBwnaSjga7AGKAS6AJcEBF/lDQB6AZsD1xaeE5EzGrgNT9c0jlAW+DnEXF7mtUNiYgRkg4BrgCWA88X1HoecHqq86mIOKtI318HjgEaGt+spKbOeZNbH/onPbt8jrffWcZJQ3dk777+TGb1a2rAbQscDbwI/AEYKekG4CiyN9xlaens7BRuh0VEX0kVZG/mFbUdpXC5AtgjIl6XdDMwPCLuBIbxWcOBmRHxFUltgeeAgUXatYuIgZL6A/dL2jodryALvr5kM6dxwIlkoXajpM2A1ySNjYiF9Vz/14F7I+IySUOAfSNirKSvAaMiYpakPwFnRMTzkg4Efg38MZ2/KCKOSNf/1dpz6n21M5Wp7p7A05KmFLyG7YAbgQPTB4rr0vHWwA/JPgisAn4rqSoi5hV2HBHHpvaNlJB/v7xlRqlLaHEWvreMRe+vaKbeWvN/PNKkM9u0bsVFI/akqnt75i38kNETpjH+nueaqa51061TO7pv9rlSl1ESPzi52Ntvy9DUm0ymRMQLEVFDNpMZEhHvAycBJ0i6BDgC6ADMA5ZJehz4LvCTiFhe0NfewOMR8TpARJyawq2oiLgNeEjSucBVZLOhDkWajk/tZwLzgd3S8btS3XOA7qnNWOBVSeeTBVFbstlZfR4Gzpd0K9ks9jdF2pwC9JP0U+B7dWp8soG+63NjRFRHxBvAVLKwq7Ur8EZEzK1tCxAR1cATZLPinwG/rRtuZhuLrp3aUdU9+2dZ1b09XTt6idIa1tQZXHXB12XASklbAZPJ3uzvB94EBkREtaTBZHtNw4CpkvYvOH9lYceSegBExIJiA6dluuPIZl4PA/1SDQ3V2KrgcXXqv6Z2xiLpcqAPcCtwJ3BwPX2Szn1c0i7A4cDxwAiyJdhCj5HNECcDk1LftZbV13cDPvOaFzyu4dMfVgrbHgXsBRwGTJR0ckT8tQnjbxJa8qfRUrnzsX9x9+Mvl7oMFr+/gnkLP/x4Brd4SXPNKtfdF3ftxVH79Sl1GVZHUwNuX0m9gdfJ9ncmAnsCL0bEFWnJ7EfAAkkDyGZaQyLikfS4cC1sGnC1pM0j4k2y5crJwHX1jD0UuDYibpXUF+gPlJMtwRU6AZgmaRDZHlhDS4BDgZER8YSkA8hmZeX1NZb0K7IZ05WSHgWeSU9VA60ldSXbk9svIpan/cb6+qtmzb4PJ0q6A+hN9lqfSRawAM8CPSXtHhH/IFtyrf2w8BgwKCKmpr3D3QAHnK2xo/br02xv3n/514MM73NIk86dOudNLv390x/vwY04bCfvwVmDmrpEOQf4HVlozCO7QeNBoJWk54C/Ay8D20bEM2RLarMlzUjH76/tKC25fQd4QNJsstnNDZIGSbqvyNhXAj9LfV1NtgS3bZF2fVKbcWQ3u9QNwEKXADdLehr4PjC9nj5rXQUcK2km8GfgG+n4ROAaYCeygJ4j6RmyfbNKScWWPScC10jap4HxAD4AngbuBc4q3B+MiJVkoXZzuubKdHwBcC1Z0D9NFvQTGhnHrEXau+/m/PcZgznx4B357zMGO9ysUWU1NTWlrqHZpbsoR0XE5BKXknsLFizJ3w+QrTfrMoOzTVuPHh3r3TaqT8l+D66lS798fVU9Tw9LM8/mHO8yPruPBzA9Is5ozrHMzDYFuZzB2YbjGZytDc/grKmaMoPz/0VpZma55IAzM7NccsCZmVkuOeDMzCyXHHBmZpZLDjgzM8slB5yZmeWSA87MzHLJAWdmZrnkgDMzs1xywJmZWS454MzMLJcccGZmlksOODMzy6VmCThJIyRNaIZ+jpB0XhPPHZL+0GlDbSZIGtGU/tewhovT35Fr1nPqq1vSkZJGFzne6GtR5JwqSfPX5hwzs5aspf3B0z1KXcA62h94dAOcA0BE3A3c3ZRzC0kaBlwJbL6ufZmtq9VL36VmyULKOnanVWXnUpdjG7EGA07SEOBXQDkwG/gGMB7YHVgNjI2Im1Lz7SVNAboB9wA/BLYGJkfENqm/UantGOB3QL/0+GrgcWBkavcKMAsYHRHD6tTUCbge2BLYApgCnFanzWRgLjAYqADOjYgH09PDJZ0NfB4YExHjJFWlPjsDvYDbIuLCBl6XLYFbgPbpdfg2sCMwCLhO0tFA13SdlUAX4IKI+GOa6XYDtgcuLTwnImbVNyZwuKRzgLbAzyPi9jSrGxIRIyQdAlwBLAeeL6j1POD0VOdTEXFWkb6/DhxD9pqblczKF55g+RO30KpTT1a//zYV+5xMmx32KXVZtpFakxncjsDWEfGepF8BiyKin6TuwFOSZqZ22wL9gfeAR4AjgX/U0+c+QNeIGCCpG3B5RIyXdA1ARNyQ2g0rcu5wYGZEfEVSW+A5YGCRdu0iYqCk/sD9krZOxyvIgq8v2cxpHHAiWajdKGkz4DVJYyNiYT31fx24NyIuSx8C9o2IsZK+BoyKiFmS/gScERHPSzoQ+DXwx3T+oog4AkDSV2vPqWesWpWp7p7A0+nDBKmPdsCNwIERMVfSdel4a7IPGlsAq4DfSqqKiHmFHUfEsal9IyXky9J7Lil1CS3G6iULqflg0Xof50vAEm6tv0F5GyqPGUV5lypWvTOPpXeMYvmj49Z7XY0p69CNVh27l7qMDaryiB+WuoR1tiZ7cBER76WvDySb6ZDe/O8ChqTn7o6IBRHxEXB7wfFiZgOS9ABwCvCDNS04Im4DHpJ0LnAV2WyoQ5Gm41P7mcB8YLd0/K6IqAHmAN1Tm7HAq5LOJwuitmSzs/o8DJwv6VagCvhNkTanAP0k/RT4Xp0an1yDS63rxoiojog3gKlkYVdrV+CNiJhb2xYgIqqBJ4BpwM+A39YNN7OWpKxDN8q7VAFQ3qWKsg5dS1yRbczWZAa3rODruoFYVtBHdZ3jK4Ga9HWtNsDKiFgkqS8wlGyWNiM9blRapjuObOb1MNkyZ1mRpoX1tCp4XA0QETW1MxZJlwN9gFuBO4GD6+mTdO7jknYBDgeOB0akayn0GNkMcTIwKfVdaxlrr9jrW6uGT39vCtseBewFHAZMlHRyRPy1CePnTh4+oTaXFdP/zEcz7ip1GdR8sIhV78z7eAZX88HiUpcEQJsd96XdoKNLXYatpbW9yeQRsuW5b6clyqPI9m52A4al2cpysiW/i4B3gS6SegDvA4cC90g6EjgV+E9gInAQsBXZG3NFIzUMBa6NiFtTKPYn2yNcVafdCcA0SYPI9sAaWgIcCoyMiCckHUA2Kyuvr3Faqn0jIq6U9CjwTHqqGmgtqSvZ0u5+EbHhrKXXAAAfD0lEQVQ87T3W1181a/Z9OFHSHUBvYE/gTLKABXgW6Clp94j4B9nrT3rdHwMGRcTUtHe4G+CAs09pN+joDfIG/pd/PcjwPofU+/zKF55g6d2/+GQP7ktf9R6cNdna/prAaKCrpFlkN3eMiYgZ6bnngfuAGWT7Uw+mpc3LyJbIHgaeSm3vJ5vFzEnH7kh7UFOAkyWdI2mQpPuK1HAl8DNJM8huTnmCbP+vrj6pzTjg+IioG4CFLgFulvQ08H1gej191roKODbtP/6Z7OYbyML6GmAn4DpgjqRnyPbNKiUVW/acCFwjqbF/xR8ATwP3AmcV7g9GxEqyULs5XXNlOr4AuJYs6J8mC/oJjYxjVjJtdtiH9l8ZQ8U+J9P+K2McbrZOympqakpdQ7NLd1GOiojJJS4l9xYsWJK/HyBbbxqbwZnVp0ePjvVuG9Wnpf0eXIuRfvn6qnqeHpZu9mjO8S7js/t4ANMj4ozmHMvMbFOQyxmcbTiewdna8AzOmqopMzj/X5RmZpZLDjgzM8slB5yZmeWSA87MzHLJAWdmZrnkgDMzs1xywJmZWS454MzMLJcccGZmlksOODMzyyUHnJmZ5ZIDzszMcskBZ2ZmueSAMzOzXHLAmZlZLjngzMwslxxwZmaWSw44MzPLJQecmZnlkgPOzMxyyQFnZma55IAzM7NccsCZmVkuOeDMzCyXHHBmZpZLDjgzM8slB5yZmeWSA87MzHLJAWdmZrnkgDMzs1xywJmZWS454MzMLJcccGZmlksOODMzyyUHnJmZ5ZIDzszMcskBZ2ZmueSAMzOzXGpd6gJs4zZ//nxWrFhe6jJsI7Hwjbd4udW/S12GbYR69Nhtrc9xwNk6WbFiOZWVlaUuwzYSbSsq/PNiG4yXKM3MLJcccGZmlksOODMzyyUHnJmZ5ZIDzszMcskBZ2ZmueSAMzOzXHLAmZlZLjngzMwslxxwZmaWSw44MzPLJQecmZnlkgPOzMxyyQFnZma55IAzM7NccsCZmVkuOeDMzCyXHHBmZpZLDjgzM8slB5yZmeWSA87MzHLJAWdmZrnkgDMzs1xywJmZWS454MzMLJcccGZmlksOODMzyyUHnJmZ5ZIDzszMcskBZ2ZmueSAMzOzXHLAmZlZLjngzMwslxxwZmaWSw44MzPLJQecmZnlkgPOzMxyyQFnZma55IAzM7NccsCZmVkutYiAkzRE0uRm6GekpJHNUFJtf43WJWmCpBHNNWZzkjRC0oQ1aHeSpOckvSjpmxugNLP1bsnSlbzy9lKWLF1Z6lKsRFqXuoDmFBHXlLqGjY2kKmAMsAewAnhC0qMR8VxpKzNrumdeepd7/v4mPTp/jgXvLuOIvTZnwHadS12WbWAtKeC6S5oIVAFPAt+MiBWSvgWcCrQHVgPHR8RcSWOBocAq4K6IuFjSKICIGCXpJOAnQA0wDTgT2B0YHRHDCgeW1Am4HtgS2AKYApxWp81kYC4wGKgAzo2IB9PTwyWdDXweGBMR41JwXA90BnoBt0XEhfVdvKQhwI+BMmA74E/Ae8BR6diwiHhL0qHAaKAN8G/gzIhYJOlg4HKyWfkrwEmp6+1T7b2BSRFxZp2hDwYeiYjFqY4/AcelMWwNXXvfv0tdQovwzpKPePfD6gZadOMh5qz3Otq0bsVFI/akqnt75i38kNETpvG/f5233sddE53bt6ZLx7alLqOkzhq27QYZp0UsUSbbAucAuwEdgZEpeI4ChkREP+BO4GxJWwOHRcTuwD7ADpIqajtK4XIFcEhE9AXKgeERMb1uuCXDgZkRsTewA7A3MLBIu3YRMZAsPG6UVPtTWkEWfMPJZkMAJ5KF2l7pms6W1L2R12Aw8FWgL/ANYEFEDAKeBU6Q1AO4FPhyRAwAHgB+KakdcAtwekTsmtqfnvrsDRwD7AwcJqlvnTG3AOYXPJ5PFvRmG62undpR1b09AFXd29O1Y7sSV2Sl0JJmcFMi4gUASbcAX42IX6eZ2AmSdgQOBWYC84Blkh4H7gV+EhHLJdX2tTfweES8DhARpzY0cETcJukLks4lC4JuQIciTcen9jMlzScLLshmkDWS5gDdU5uxkg6QdD7QD2hLNgtd2EApsyPitfQaLAQmpeOvAF3IArA38Gi61nJgMbArMC8iZqaxf5T6GJFe19rZ2Uu19RUoK1LH6gZqtCI21CfSlu6hGW8zaeaCUpfB4vdXMG/hhx/P4BYvWVHqkj62xw5dGDqwZ6nL2CS0pIArXNcoA1ZK2gqYDPwGuB94ExgQEdWSBgP7A8OAqZL2Lzj/U7vKaeZDRBT9lyfpHLJluXHAw2SBVOyNv7DGVgWPq1P/NbUhK+lyoA9wK9nM8+B6+iz0UQPjQRZof4uII9MYFWSz3S3qXM9m6XjdPmqK1DAP2K/gcS/gjUbqNCtq6MCeDb55T3p1Cgf1/tJ6r+OZl97lkpunf7wHd8wXe3kPbhPUkpYo95XUW1IrsuW1h4E9gRcj4gqyfbnDgHJJA4C/ks1OzgeeA1TQ1zRgsKTN0+MrgP9oYOyhwLURcQtZCPQnC5O6TgCQNIhsRjWrkT4vi4g/AluR7S0W63NtPAnsnWazAD8FLgMC6CFpl3T8AmBN7yZ9GDhIUg9JlcCxwMR1rNOspAZs15nvHr0dw/bswXeP3s7htolqSQE3B/gdWWjMI7tB40GglaTngL8DLwPbRsQzwFRgtqQZ6fj9tR1FxBvAd4AHJM0GlgE3SBok6b4iY18J/Cz1dTXwBNmeYF19UptxZDe7rGrgei4Bbpb0NPB9YHo9fa6xiHgT+Bpwu6RZZPuE34uI5cApwE2SngV2IdurW5M+55Hd3PIo2fLvrRHx1LrUadYSdKxsw9Y9K+lY2abUpViJlNXU1JS6ho1CuhNxVERMLnEpLcq0ac/WVFZWlroM20hsqCVKy5++fbdvbIvnM1rSHlzuSdoPuKqep4elmaeZmTUDB9waioghzdDHY2T7e2Zmtp61pD04MzOzZuOAMzOzXHLAmZlZLjngzMwslxxwZmaWSw44MzPLJQecmZnlkgPOzMxyyQFnZma55IAzM7NccsCZmVkuOeDMzCyXHHBmZpZLDjgzM8ulFhtwkkZImtAM/Rwh6bwmnjsk/aHThtpMkDSiKf2vb2v6Gko6SdJzkl6U9M0NUJqZ2XrXYgOuGe0BdCp1ES2VpCpgDLAvsDvwX5J2KW1VtklavoRWi1+B5UtKXYnlxAb/g6eShgC/AsqB2cA3gPFkb66rgbERcVNqvr2kKUA34B7gh8DWwOSI2Cb1Nyq1HQP8DuiXHl8NPA6MTO1eAWYBoyNiWJ2aOgHXA1sCWwBTgNPqtJkMzAUGAxXAuRHxYHp6uKSzgc8DYyJiXAqO64HOQC/gtoi4sJHX5cdAGbAd8CfgPeCodGxYRLwl6VBgNNAG+DdwZkQsknQwcDnZh5ZXgJMKXsPJQG9gUkScWWfog4FHImJxquNPwHFpDLMNovy1Z2g7627KOvakZsnbfLTrkazaakCpy7KNXKn+oveOwNYR8Z6kXwGLIqKfpO7AU5Jmpnbbkv0F7PeAR4AjgX/U0+c+QNeIGCCpG3B5RIyXdA1ARNyQ2g0rcu5wYGZEfEVSW+A5YGCRdu0iYqCk/sD9krZOxyvIgq8v8CgwDjiRLNRulLQZ8JqksRGxsIHXpbaPRcDbwPciYpCkG4ATJN0KXAocEBHvSDoL+GVaVrwF+HJEzJT0C+B0YAlZsPUHPgRektQ3IuYUjLkFML/g8XzgCw3UuNFq+9i1pS6hRSpbuphWy97dIGMdDjDjL599orwNlceMorxLFavemQd3jIKn/7BBamrM6s91pqaya6nL2GA+2u+sUpfQbEq1RBkR8V76+kCymQ7pzf8uYEh67u6IWBARHwG3FxwvZjYgSQ8ApwA/WItibgMeknQucBXZjLFDkabjU/uZZEGwWzp+V0TUAHOA7qnNWOBVSecDvwbaAu0bKWV2RLwWEUuBhcCkdPwVoAtZAPYGHk0fAr4F7ADsCsxLdRERP4qIq9K5UyJicUSsAF6qra9AWZE6VjdSp1mzKuvQjfIuVQCUd6mirMOmEyi2/pRqBres4Ou6IVvGJ3VV1zm+Eqjh02/KbYCVaZmuLzCUbJY2Iz1ulKRzyJblxgEPky1zFnvjL6ynVcHjaoCIqJFU2+flQB/gVuBOsqXAYn0W+qiB8SBb1v1bRByZxqgAOpLNwgqvZ7N0vG4fdV87gHnAfgWPewFvNFLnRilPn0ybU+u5D9EqHi5pDTUfLGLVO/M+nsHVfLC4pPUUWtV7ENU7Dy11GdYEpQq4Qo8AXwe+nZYojwKOIZsdDZP0U2A52ZLfRcC7QBdJPYD3gUOBeyQdCZwK/CcwETgI2IrsDb6ikRqGAtdGxK0pFPuThcmqOu1OAKZJGkQ2o5rVSJ8jI+IJSQcAVanPdfEkcJ2kHSPin8BPU78jgR6SdomI54ALyMLsxTXo82FgVHo9PwSOBf5rHeu0jUj1zkM32Bv4pFencFDvL33mePlrz8BdYz7Zg+t/rPfgbJ21hIAbDVwtaRZZAIyJiBmSdgOeB+4ju1Hj1tqbOiRdBkwDXgOeSv3cTzYLm0MWiHdExCxJXYAbJb0FTKXITSbAlcD/pOXEJcATZPt/dQOij6QZ6evjI2JV7YytiEuAmyW9C7wFTE99vrQWr82nRMSbkr4G3C6pHHgdOCUilks6Bbgp7SG+RBb2x61Bn/Mk/Zhs77AtcF1EPNXIaWbNatVWA1jWY3taLV3M6squUNGx8ZPMGlFWU1NT6ho2CulOxFERMbnEpbQo06Y9W1NZWVnqMmwjUd8Mzqwxfftu39gWz2e0hBncJkPSfmQ3sRQzLCJyufdlZlYKDrg1FBFDmqGPx8j298zMbD3bFP4nEzMz2wQ54MzMLJcccGZmlksOODMzyyUHnJmZ5ZIDzszMcskBZ2ZmueSAMzOzXHLAmZlZLjngzMwslxxwZmaWSw44MzPLJQecmZnlkgPOzMxyyQFnZma55IAzM7NccsCZmVkuOeDMzCyXHHBmZpZLDjgzM8ul1qUuwDZu7dpVsHTp0lKXYRuJj5Yv98+LbTAOOFsnvXr1KnUJthGZs/oFttlm21KXYZsIL1GamVkuOeDMzCyXHHBmZpZLDjgzM8slB5yZmeWSA87MzHLJAWdmZrnkgDMzs1xywJmZWS454MzMLJcccGZmlksOODMzyyUHnJmZ5ZIDzszMcskBZ2ZmueSAMzOzXHLAmZlZLjngzMwslxxwZmaWSw44MzPLJQecmZnlkgPOzMxyqUUEnKQhkiY3Qz8jJY1shpJq+2u0LkkTJI1orjGbk6QRkiasYdtOkmZL2mb9VmVmtmG0LnUBzSkiril1DRsjSYOB8cCOpa7FNrz3PljBgveW02OzCjbr0K7U5Zg1m5YUcN0lTQSqgCeBb0bECknfAk4F2gOrgeMjYq6kscBQYBVwV0RcLGkUQESMknQS8BOgBpgGnAnsDoyOiGGFA0vqBFwPbAlsAUwBTqvTZjIwFxgMVADnRsSD6enhks4GPg+MiYhxkqpSn52BXsBtEXFhfRcvaQjwY6AM2A74E/AecFQ6Niwi3pJ0KDAaaAP8GzgzIhZJOhi4nGxW/gpwUup6+1R7b2BSRJxZZPgzgW8CN9dXn+XT1DlvcutD/6Rnl8/x9jvLOGnojuzdd/NSl2XWLMpqampKXUPtm/tfgP7Ai8AfgCeAG4A7gCMiYpmk0UAXYCxwX0T0lVQBXAecAdQGyHhgBrBHRLwu6Wbg/yLiznrGPxHoExFjJLUFngOOBzoCoyKidqnyXxHxNUn9gfuBrYFxQDfgSKAv8GhE9JB0PrAgIm6UtBnwWhpjYQOvwd2pj0XA28D3IuJaSTcAM4FbgYeAAyLiHUlnAXuShdOrwJcjYqakXwDzgSVkYdgf+BB4KbWZU08NLwNDIuLlYs8Xs2DBkrX+AfrlLTPW9pTcWfjeMha9v6LUZdCmdSsuGrEnVd3bM2/hh4yeMI2V1atLXRbdOrWj+2afK3UZLcIPTh5Y6hJahB49Opat7TktYg8umRIRL0REDXAL2Rvt+2QzkRMkXQIcAXQA5gHLJD0OfBf4SUQsL+hrb+DxiHgdICJOrS/c0vO3AQ9JOhe4iiywOhRpOj61n0kWILul43eluucA3VObscCrKeh+DbQlm4U2ZHZEvBYRS4GFwKR0/BWyYB9MNhN7VNJM4FvADsCuwLxUFxHxo4i4Kp07JSIWR8QKsoDr3kgNtgnp2qkdVd2zH8uq7u3p2tFLlJYfLWmJsrrg6zJgpaStgMnAb8hmTG8CAyKiOu0b7Q8MA6ZK2r/g/JWFHUvqARARC4oNLOkc4Diy2djDQL9UQ0M1tip4XJ36r5FU2+flQB+yWdedwMH19FnoowbGAygH/hYRR6YxKshmmVvUuZ7N0vG6fdSsQQ3rnT+Rwp2P/Yu7H3+51GWw+P0VzFv44cczuMVLSj+rBPjirr04ar8+pS7DNnItKeD2ldQbeB04HZhItvz2YkRcIakd8CNggaQBZDOtIRHxSHqsgr6mAVdL2jwi3gSuIAvK6+oZeyhwbUTcKqkv2ZJeOdn+XqETgGmSBpHNqGY1cD1DgZER8YSkA8j2FsvX6JWo35PAdZJ2jIh/Aj9N/Y4EekjaJSKeAy4gC7MX13E8W0+O2q9Pi3gDnzrnTS79/dMf78GNOGyn9boH95d/PcjwPoest/7NCrWkgJsD/I7shoxHyG7Q+BzwDUnPASvI3uD7RcQzkqYCsyUtBZ4hm+HtARARb0j6DvCApHJgKnBDCqbP3GQCXAn8T1pOXEK2/7ctnw2IPpJqN5COj4hVtTO2Ii4Bbpb0LvAWMD31+dLavjC1IuJNSV8Dbk/X9TpwSkQsl3QKcFPaQ3yJ7Mac45o6lm0a9u67Obts3cV3UVoutYibTDYG6SaTURExucSltChNucnENl2ewVlTNeUmk5Y0g8s9SfuRLa0WMywi3tiQ9ZiZ5ZkDbg1FxJBm6OMxsv09MzNbz1rSrwmYmZk1GwecmZnlkgPOzMxyyQFnZma55IAzM7NccsCZmVkuOeDMzCyXHHBmZpZLDjgzM8slB5yZmeWSA87MzHLJAWdmZrnkgDMzs1xywJmZWS454MzMLJdabMBJGiFpQjP0c4Sk85p47pD0l7wbajNB0oim9L++rc1rKKmTpNmStlm/VdmmZvXSd1n11ousXvpuqUuxTcym8AdP9yh1AS2dpMHAeGDHUtdi+bLyhSdY/sQttOrUk9Xvv03P7XeDPqWuyjYVGzzgJA0BfgWUA7OBb5C9ue4OrAbGRsRNqfn2kqYA3YB7gB8CWwOTI2Kb1N+o1HYM8DugX3p8NfA4MDK1ewWYBYyOiGF1auoEXA9sCWwBTAFOq9NmMjAXGAxUAOdGxIPp6eGSzgY+D4yJiHGSqlKfnYFewG0RcWEjr8uPgTJgO+BPwHvAUenYsIh4S9KhwGigDfBv4MyIWCTpYOBysln5K8BJBa/hZKA3MCkiziwy/JnAN4Gb66tvY7D0nktKXUKLsXrJQmo+WFTqMqC8DZXHjKK8SxWr3pnHTneMYsmcqaWuirIO3WjVsXupy9jgKo/4YalL2KBKtUS5I3BgRJwOjAIWRUQ/4EBglKTdUrttgWOBAcC+wJEN9LkP0DUiBgAHA1+MiOeAa4BrIuKGiJheN9yS4cDMiNgb2AHYGxhYpF27iBhIFh43SmqbjleQBd9wsqAFOJEs1PYCdgPOltTYv6jBwFeBvmTBvyAiBgHPAidI6gFcCnw5XecDwC8ltQNuAU6PiF1T+9NTn72BY4CdgcMk9a07aEScERGPNVKb2Vor69CN8i5VAJR3qaKsQ9cSV2SbklItUUZEvJe+PhD4ejq4UNJdwBDgfeDuiFgAIOn2dPwf9fQ5O2umB4D7gB+sRTG3SfqCpHPJgqAb0KFI0/Gp/UxJ88mCC+CuiKiRNAfontqMlXSApPPJZpVtgfbAwgZKmR0Rr6XrXQhMSsdfAf5fe/cfa3Vdx3H8eS+gCBpoXRMsAla8CdekdmtL0GxGGWwYCzK8rewXOjcaTStXOs0N2mKNlmWT2kIFVuBIC6WYA1LnSumGOItXv928WjmwH5TGBW5/fD/HTsdz7zk37vl+D9/7emx3O+f7/Z7ved1z7zmv8/l+P/fcM8kKcBqwOyIgGwUfAt4E9Enal+7782kfVwIPSjqUrv+ukq+MRtu706H8e+/3OdJ7b9ExGDh8kGPP9700ghs4fKjoSACMmzWfU7uXFB3DWqyognuh6nLtKLKD/+Y6WrO8HxhIlyvGAf3pMN15wAJgIdBbb7RST0SsBJYC64EHyAqpo86m1Xk6q64fBUglV9nnV8jONmwG7iEbVdbbZ7UjQ9wfZIX2sKTF6T7GA2eQHVat/n4mpeW1+6h97KykTu1e0hYv4P2/eYR//WDNS+fgDszu5q3zrio6lo0S7TCLchdpBJcO4b0P2JPWLYyIyemFfDlZ+fwVODMiutKhuUvTbRcDG4H7gE8Bh4HXkr3ANyryBcDtkjaRlcBcsjKp9cF0X91kI6onGuxzraStKce5g+xzOH4GvD0iKpNBbgTWAgK6ImJOWv5Z0rlHsyKNe8MFTFy2mvEX9DBx2Wr+MmVG0ZFsFGmHgrsFOCsiniCb3LFaUm9ad4DscGMvsF3SznRocy3wGFnhPZq23UE2MnwyLdsmqbLPnohYGRHdEXF/nQxfBW6KiF6yySmPkJ3/qzUzbbMeuFzSsSG+ry8Bd0XEz4HPAHsH2WfTJP0J+BiwJT1ebwGulfQi8CHgzojYD8whO1dnVrjOCZMZ8+rX0zlhctFRbJTpGBgYKDrDSSHNRLxZ0p6Co7SV5577h3+BrGn3/X4ni2a+u+gYdhLq6jpj2KdXRsPfwbWNiLgQuHWQ1QslPZNnHjOzMnPBNUnSxSOwj4fIzu+ZmVmLtcM5ODMzsxHngjMzs1JywZmZWSm54MzMrJRccGZmVkouODMzKyUXnJmZlZILzszMSskFZ2ZmpeSCMzOzUnLBmZlZKbngzMyslFxwZmZWSi44MzMrJRecmZmVkgvOzMxKyQVnZmal5IIzM7NScsGZmVkpueDMzKyUXHBmZlZKY4sOYCe1sZ2dHUVnsJPI6adMwL8z9n+aDjwNHG32Bh0DAwMtS2OlNx34Q9EhzGzUmAH8sdmNXXB2IsYCryk6hJmNGh7BmZmZeZKJmZmVkgvOzMxKyQVnZmal5IIzM7NScsGZmVkpueDMzKyUXHBmZlZK/qgua7mImAZsBM4GBPRIOlyzzRTgLqALeAG4WtK+Ns35HeAc4DhwnaRd7ZazatsFwPWSLskxIhFxBXADcAqwTtI3atbPBb4FTAIeJPt5N/0HvHnlrNruDmC3pA05xqu+/0aP52XAF4EOsk8X+qik59sw55KUcwzwGLBC0pFW5fEIzvJwG3CbpNnAXuDGOtusAe6WdD5wc7pN3prJuRbYLmkusBzYHBFjcswITeSMiM6IuBb4LtmLSW4i4lxgNTAfOB9YERFzajbbCKyUNIvsRfmTeWaE5nJGxNSI+CGwLO98VRmGzBkRrwC+CSxKz5/9ZM+hdss5Efg6sEDSecB44MpWZnLBWUtFxDjgIuDutGgD9V8sPg6sT5dnALm++xxGzm3ApnT5t2RP0tNbna9iGDnfmL5yLw7gXcAuSYck/ZMs69LKyoh4HXCapJ+mRRsopkCGzJn0APcCW/IOV6VRznHANZL60vX9wLScM0KDnGnZdEl/TmV3Ni1+nvsQpbXaq4C/Vx1+epY6n18p6ThARBwg+xDny/IKmDSbc1vV1euAX0j6Ww75KprN+STwiYi4OMdsFVPJclU8C7ytwfoiPtO0UU4krQWIiPk55qo1ZE5JB4F7ACLiNOB64NY8AybNPJ79EfFeshF8H7CzlYFccDZiImIZsK5m8a/rbHp8sH1Imp3Oz+yMiNmSDo1kRhiZnBGxCrgKeMcIRqu9jxPOWZB6/w/n+DDW56VdcjTSVM6ImERWdI9LuqPlqV6uqZySdgCvjIg1ZIdWr2hVIBecjRhJW4Gt1cvSIbWDETFG0jFgCvBM7W0jYhHwE0mHJe2LiKeAmcCIF9yJ5EzbfhlYBFwk6emRzjdSOQvUB1xYdb02Yx/ZJJ3B1uelUc520TBnmvz0Y2AX8On8ov2PIXNGxFlAt6TKqG0T8L1WBvI5OGspSf3AQ8DladGHgR11Nv0IsAIgnZg+BziQR0ZoPmcaub0TmNfKchvMMB7PIj0AXBIRXRExAXg/8KPKSklPAS9GxLy0qKjvYcicbWTInGmS03Zgi6RVkor6FzGNHs8OYGOaBQzwAeDhVgZywVkeriGbUfVLsnd4NwBExNURcUvaZhXwnoh4nGwa/vLBpr4XlTMiOoCbyE6O74mIfelrajvlzDnLy6TJDl8AdgP7gM2SHo2I+yOiO23WA6yLiF8BE4GvtWnOwjWRczHwZmBp1e/kt9stZzpXuALYnp7ns4DPtTKT/x+cmZmVkkdwZmZWSi44MzMrJRecmZmVkgvOzMxKyQVnZmal5IIzM7NScsGZmVkpueDMzKyU/gMCE2UFjlmlTAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = az.plot_forest(\n",
    "    data=[ror_basic_trace, ror_robust_trace], model_names=['basic', 'robust'],\n",
    "    var_names=['alpha_start_bids', 'alpha_mech'],\n",
    "    combined=True, rope=(0, 0), figsize=(6, 6))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And finally the country category."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x864 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = az.plot_forest(\n",
    "    data=[ror_basic_trace, ror_robust_trace], model_names=['basic', 'robust'],\n",
    "    var_names=['alpha_country'],\n",
    "    combined=True, rope=(0, 0), figsize=(6, 12))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And we note that both models estimate marginal parameter distributions are *largely* in-line with one-another."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Model Selection\n",
    "\n",
    "We now use WAIC to help select which model to choose for subsequent interpretation. WAIC estimates the OOS predictive accuracy of a model (also known as the deviance), using only the training data. We are also in the fortunate position that we have a test dataset that we can use in addition to WAIC (to compute the actual OOS deviance).\n",
    "\n",
    "Unlike other Bayesian information criteria (such as AIC and DIC) - that are based on an asymptotic Normal approximation of the posterior density - WAIC should be suitable for comparing models with different likelihood functions. See Chapter 7 of 'Bayesian Data Analysis', by Andrew Gelman & Co. for more discussion."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>waic</th>\n",
       "      <th>pwaic</th>\n",
       "      <th>dwaic</th>\n",
       "      <th>weight</th>\n",
       "      <th>se</th>\n",
       "      <th>dse</th>\n",
       "      <th>warning</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>robust</th>\n",
       "      <td>-6225.73</td>\n",
       "      <td>48.6219</td>\n",
       "      <td>0</td>\n",
       "      <td>0.805375</td>\n",
       "      <td>159.869</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>basic</th>\n",
       "      <td>-3992.42</td>\n",
       "      <td>48.1965</td>\n",
       "      <td>2233.31</td>\n",
       "      <td>0.194625</td>\n",
       "      <td>378.92</td>\n",
       "      <td>347.192</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           waic    pwaic    dwaic    weight       se      dse warning\n",
       "robust -6225.73  48.6219        0  0.805375  159.869        0       1\n",
       "basic  -3992.42  48.1965  2233.31  0.194625   378.92  347.192       1"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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NO0jmqMyTNHh0dZ1jgEeHr/qDU0Pvu0IIbcARJBt+C69vzLcDLwF/UL18DMm7nqbRr/8xwDkkE6nu3tatsu3313srbfvzSN7QrQJOCiFMIxnRPkmyWwoy1H8Nvb9QfUy8TPKCvgU4tbr67l7L/S43jX79vwk4OcbYGUJ4hiT43jaUz/uGmosyhLACGAWMAC4DLgROqV5eDmwHbiTZnfPDGOPaEMI3SPbFHgYsjDE2TkMp7Kf3ScAFJO9iryZ513I7yd9gU4xxVQjhSuA4ks8hvhBj/H09aj9YIYQcyWcsvwPeQrKL5iJaYNsfoPfTaJFtv6cQwr0xxukhhE8Bs0hGKreThF2m+9+j9xOBZdWrbwM2Vv/fCbwcY7w6hDCHZNfcaJLHfV89aj5Y1cf+7STP6SOApcBMhvB531ABJ0nSUGmYg0wkSRpKBpwkKZMMOElSJhlwkqRMaqiZTKQsCSF8nuRE3GdIzud5EVgy0BF/IYQzgUKM8d5DXqSUYR5FKR0i1YBrizHeWb18Mcl5XONIDvt+K8kh4XfHGD8WQuggOWXgXpI3n/9FEpCvAEcCnyE5CfYHJLM+/CzG+O3q1EU5ksPmrwI+SnIu2eHAxhjjd4ajX6nRuItSGj4/A44lmZLtdyTPv/HAxhDCZJLzPu/YY/le4O9JTgI/hSQQ24HrSKZxmlOd6ml0dbqjS0jOF7oSeJXkJPEzDn1bUmMy4KTh8xGSWUv+Jca4DPge8N8kJ7teSHLy7r/tsfwi4I+Bp0jmqcwBO6ontu4i2e3ZTjKPHySjvncDr1Zv/2vAjw9pR1ID8zM46dCaG0KYShJG/wt8ELglhPARkimHLoox7gghjALujzFWQgi7190MTASOJ5nlZmz/G48x/jKE8HIIYRXJPH1fAe4KIfwDyfO7+1A2JzUyP4OTJGWSuyglSZlkwEmSMsmAkyRlkgEnScokA06SlEkGnCQpkww4SVIm/T/Do6Y7rgcJewAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x144 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "load_train_data()\n",
    "\n",
    "comparison = az.compare({'basic': ror_basic_trace, 'robust': ror_robust_trace})\n",
    "\n",
    "az.plot_compare(comparison, plot_ic_diff=False)\n",
    "comparison"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Model Selection and Interpretation\n",
    "\n",
    "The model with the lowest WAIC is the robust linear model. Furthermore, its actual OOS predictive performance, as measured by the OOS deviance, agrees with predicted OOS deviance as represented by WAIC. Perhaps most importantly, however, the distribution of the residuals are clearly leptokurtic, something which the Normal likelihood of the basic model cannot capture. To add to the weight of evidence for the robust model, we note that the Normal likelihood is a limiting case of the Student-T, as $\\nu \\to \\infty$, and that **all** of the probability mass/density for $\\nu$ is < 2. \n",
    "\n",
    "We now need transform the parameter estimates back to the natural scales of the data and compute the sensitivities of the dependent variable to changes (deltas) in the independent variables. We do this for each independent variable at a time, holding all other variables at their average levels (which is equivalent to setting them to zero as they have been standardised). \n",
    "\n",
    "Because we took the modelling decision to transform the dependent variable using the natural logarithm, the process of computing sensitivities for the polynomial model is not as trivial as it would have be otherwise. More specifically, a small change in the average level of an independent variable, has a measurable change to the *arithmetic return* of the independent variable, as we will derive below. \n",
    "\n",
    "Furthermore, because we have selected a model that uses the Student-T distribution as the likelihood function, there are further complications when it comes to computing means and variances - i.e. they are not well-defined for $\\nu < 1$ and $\\nu < 2$, respectively. Consequently, we will proceed by analogue with the Normal distribution - i.e. by computing means and variances as if, $\\ln[RoR] \\sim N(\\mu, \\sigma^2)$, and then mapping $\\mu$ and $\\sigma$ to account for the non-central Student-T distribution, [as described here](https://en.wikipedia.org/wiki/Student%27s_t-distribution#In_terms_of_scaling_parameter_σ,_or_σ2)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We start with the expression for the expected value of RoR in the presence of a $\\Delta z_i$ change in the *i*-th standardised independent variable,\n",
    "\n",
    "$$\n",
    "\\text{E}[RoR_{\\Delta z_i}] = exp \\left\\{ C + \\frac{\\bar{\\sigma}^2}{2} + \\sum_j \\beta_j \\cdot (z_j + \\delta_{ji} \\cdot \\Delta z_i) \\right\\}\n",
    "$$\n",
    "\n",
    "where,\n",
    "\n",
    "$$\n",
    "\\bar{\\sigma} = \\sigma \\cdot \\sqrt{\\frac{\\nu}{\\nu - 2}}\n",
    "$$\n",
    "\n",
    "And where $C$ is equal to the sum of all constant (or intercept) terms in our model. We can now show that the impact of a $\\Delta z_i$ perturbation in $\\text{E}[RoR]$, can be expressed as an arithmetic return as follows,\n",
    "\n",
    "$$\n",
    "r^{\\text{RoR}}_{\\Delta z_i} = \\frac{\\text{E}[RoR]_{\\Delta z_i}}{\\text{E}[RoR]} - 1 = exp \\left\\{ \\beta_i \\cdot \\Delta z_i \\right\\} - 1\n",
    "$$\n",
    "\n",
    "i.e. all the constant terms cancel out (something that extends to any centring terms that may be present when applying the inverse of a standard scaling operation). We can now approximate $r^{\\text{RoR}}_{\\Delta z_i} = f(\\Delta z_i)$, using a Taylor expansion, assuming that $|\\beta_i \\Delta z_i| < 1$,\n",
    "\n",
    "$$\n",
    "f(\\Delta z) = \\sum_{n = 0}^{\\infty} \\frac{(\\Delta z)^n}{n!} \\cdot \\left( \\frac{\\partial f(q^{'})}{\\partial q^{'}} \\right)_{q^i = 0}\n",
    "$$\n",
    "\n",
    "If we only keep linear (first order) terms in $\\Delta z$, then we have that,\n",
    "\n",
    "$$\n",
    "r^{\\text{RoR}}_{\\Delta z_i} \\approx \\beta \\cdot \\Delta z = \\frac{\\beta \\cdot \\Delta x}{\\sigma_x}\n",
    "$$\n",
    "\n",
    "Where we have applied the inverse of the variable standardisation transformation (note, that this relationship holds irrespective of whether or not centring has been applied as well as scaling). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>hpd 3%</th>\n",
       "      <th>hpd 97%</th>\n",
       "      <th>std</th>\n",
       "      <th>delta_nat_unit</th>\n",
       "      <th>delta_impact_pct</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>country_AE</th>\n",
       "      <td>-0.02</td>\n",
       "      <td>-0.11</td>\n",
       "      <td>0.08</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-2.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country_AT</th>\n",
       "      <td>0.01</td>\n",
       "      <td>-0.08</td>\n",
       "      <td>0.10</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country_BE</th>\n",
       "      <td>0.05</td>\n",
       "      <td>-0.04</td>\n",
       "      <td>0.14</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country_BR</th>\n",
       "      <td>0.02</td>\n",
       "      <td>-0.07</td>\n",
       "      <td>0.12</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country_CH</th>\n",
       "      <td>0.35</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.44</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>35.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country_CZ</th>\n",
       "      <td>-0.03</td>\n",
       "      <td>-0.13</td>\n",
       "      <td>0.06</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-3.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country_DE</th>\n",
       "      <td>0.07</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>0.16</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country_ES</th>\n",
       "      <td>0.08</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.17</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country_EU</th>\n",
       "      <td>-0.13</td>\n",
       "      <td>-0.24</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-13.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country_FI</th>\n",
       "      <td>0.01</td>\n",
       "      <td>-0.08</td>\n",
       "      <td>0.10</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country_FR</th>\n",
       "      <td>0.05</td>\n",
       "      <td>-0.04</td>\n",
       "      <td>0.14</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country_GB</th>\n",
       "      <td>0.04</td>\n",
       "      <td>-0.05</td>\n",
       "      <td>0.14</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.00%</td>\n",
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       "    <tr>\n",
       "      <th>country_GR</th>\n",
       "      <td>-0.12</td>\n",
       "      <td>-0.22</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-12.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country_HU</th>\n",
       "      <td>0.03</td>\n",
       "      <td>-0.06</td>\n",
       "      <td>0.12</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country_IE</th>\n",
       "      <td>-0.13</td>\n",
       "      <td>-0.22</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-13.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country_IN</th>\n",
       "      <td>-0.06</td>\n",
       "      <td>-0.16</td>\n",
       "      <td>0.03</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-6.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country_IT</th>\n",
       "      <td>-0.05</td>\n",
       "      <td>-0.14</td>\n",
       "      <td>0.04</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-5.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country_LU</th>\n",
       "      <td>0.03</td>\n",
       "      <td>-0.07</td>\n",
       "      <td>0.12</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country_NL</th>\n",
       "      <td>0.07</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.17</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country_NO</th>\n",
       "      <td>0.19</td>\n",
       "      <td>0.09</td>\n",
       "      <td>0.29</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>19.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country_PL</th>\n",
       "      <td>-0.09</td>\n",
       "      <td>-0.18</td>\n",
       "      <td>0.01</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-9.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country_PT</th>\n",
       "      <td>-0.16</td>\n",
       "      <td>-0.25</td>\n",
       "      <td>-0.06</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-16.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country_RO</th>\n",
       "      <td>-0.12</td>\n",
       "      <td>-0.22</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-12.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country_SK</th>\n",
       "      <td>-0.00</td>\n",
       "      <td>-0.10</td>\n",
       "      <td>0.09</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country_TR</th>\n",
       "      <td>-0.03</td>\n",
       "      <td>-0.13</td>\n",
       "      <td>0.06</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-3.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>auction_mech_EnglishForward</th>\n",
       "      <td>0.02</td>\n",
       "      <td>-0.23</td>\n",
       "      <td>0.25</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>auction_mech_SealedBid</th>\n",
       "      <td>-0.00</td>\n",
       "      <td>-0.25</td>\n",
       "      <td>0.23</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>start_bids_false</th>\n",
       "      <td>-0.01</td>\n",
       "      <td>-0.24</td>\n",
       "      <td>0.23</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-1.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>start_bids_true</th>\n",
       "      <td>0.02</td>\n",
       "      <td>-0.22</td>\n",
       "      <td>0.25</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lots</th>\n",
       "      <td>-0.01</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>39.081027</td>\n",
       "      <td>100.0</td>\n",
       "      <td>-2.56%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>avg_reserve</th>\n",
       "      <td>-0.00</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>0.00</td>\n",
       "      <td>4910.386793</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>-0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BPL</th>\n",
       "      <td>0.03</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.03</td>\n",
       "      <td>2.653911</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.13%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nu</th>\n",
       "      <td>0.72</td>\n",
       "      <td>0.67</td>\n",
       "      <td>0.78</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sigma</th>\n",
       "      <td>0.04</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.05</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             mean  hpd 3%  hpd 97%          std  \\\n",
       "country_AE                  -0.02   -0.11     0.08     1.000000   \n",
       "country_AT                   0.01   -0.08     0.10     1.000000   \n",
       "country_BE                   0.05   -0.04     0.14     1.000000   \n",
       "country_BR                   0.02   -0.07     0.12     1.000000   \n",
       "country_CH                   0.35    0.25     0.44     1.000000   \n",
       "country_CZ                  -0.03   -0.13     0.06     1.000000   \n",
       "country_DE                   0.07   -0.03     0.16     1.000000   \n",
       "country_ES                   0.08   -0.02     0.17     1.000000   \n",
       "country_EU                  -0.13   -0.24    -0.02     1.000000   \n",
       "country_FI                   0.01   -0.08     0.10     1.000000   \n",
       "country_FR                   0.05   -0.04     0.14     1.000000   \n",
       "country_GB                   0.04   -0.05     0.14     1.000000   \n",
       "country_GR                  -0.12   -0.22    -0.03     1.000000   \n",
       "country_HU                   0.03   -0.06     0.12     1.000000   \n",
       "country_IE                  -0.13   -0.22    -0.03     1.000000   \n",
       "country_IN                  -0.06   -0.16     0.03     1.000000   \n",
       "country_IT                  -0.05   -0.14     0.04     1.000000   \n",
       "country_LU                   0.03   -0.07     0.12     1.000000   \n",
       "country_NL                   0.07   -0.02     0.17     1.000000   \n",
       "country_NO                   0.19    0.09     0.29     1.000000   \n",
       "country_PL                  -0.09   -0.18     0.01     1.000000   \n",
       "country_PT                  -0.16   -0.25    -0.06     1.000000   \n",
       "country_RO                  -0.12   -0.22    -0.03     1.000000   \n",
       "country_SK                  -0.00   -0.10     0.09     1.000000   \n",
       "country_TR                  -0.03   -0.13     0.06     1.000000   \n",
       "auction_mech_EnglishForward  0.02   -0.23     0.25     1.000000   \n",
       "auction_mech_SealedBid      -0.00   -0.25     0.23     1.000000   \n",
       "start_bids_false            -0.01   -0.24     0.23     1.000000   \n",
       "start_bids_true              0.02   -0.22     0.25     1.000000   \n",
       "lots                        -0.01   -0.01    -0.01    39.081027   \n",
       "avg_reserve                 -0.00   -0.01     0.00  4910.386793   \n",
       "BPL                          0.03    0.02     0.03     2.653911   \n",
       "nu                           0.72    0.67     0.78     1.000000   \n",
       "sigma                        0.04    0.04     0.05     1.000000   \n",
       "\n",
       "                             delta_nat_unit delta_impact_pct  \n",
       "country_AE                              1.0           -2.00%  \n",
       "country_AT                              1.0            1.00%  \n",
       "country_BE                              1.0            5.00%  \n",
       "country_BR                              1.0            2.00%  \n",
       "country_CH                              1.0           35.00%  \n",
       "country_CZ                              1.0           -3.00%  \n",
       "country_DE                              1.0            7.00%  \n",
       "country_ES                              1.0            8.00%  \n",
       "country_EU                              1.0          -13.00%  \n",
       "country_FI                              1.0            1.00%  \n",
       "country_FR                              1.0            5.00%  \n",
       "country_GB                              1.0            4.00%  \n",
       "country_GR                              1.0          -12.00%  \n",
       "country_HU                              1.0            3.00%  \n",
       "country_IE                              1.0          -13.00%  \n",
       "country_IN                              1.0           -6.00%  \n",
       "country_IT                              1.0           -5.00%  \n",
       "country_LU                              1.0            3.00%  \n",
       "country_NL                              1.0            7.00%  \n",
       "country_NO                              1.0           19.00%  \n",
       "country_PL                              1.0           -9.00%  \n",
       "country_PT                              1.0          -16.00%  \n",
       "country_RO                              1.0          -12.00%  \n",
       "country_SK                              1.0           -0.00%  \n",
       "country_TR                              1.0           -3.00%  \n",
       "auction_mech_EnglishForward             1.0            2.00%  \n",
       "auction_mech_SealedBid                  1.0           -0.00%  \n",
       "start_bids_false                        1.0           -1.00%  \n",
       "start_bids_true                         1.0            2.00%  \n",
       "lots                                  100.0           -2.56%  \n",
       "avg_reserve                          1000.0           -0.00%  \n",
       "BPL                                     1.0            1.13%  \n",
       "nu                                      0.0            0.00%  \n",
       "sigma                                   0.0            0.00%  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "num_var = ['lots', 'avg_reserve', 'BPL']\n",
    "\n",
    "param_names = (\n",
    "    cat_col_levels['country']\n",
    "    + cat_col_levels['auction_mech']\n",
    "    + cat_col_levels['start_bids']\n",
    "    + num_var\n",
    "    + ['nu', 'sigma'])\n",
    "\n",
    "param_est = az.summary(ror_robust_trace)\n",
    "param_est.index = param_names\n",
    "\n",
    "param_est['std'] = np.hstack(\n",
    "    [np.ones(29), model_data[num_var].std(), np.ones(2)])\n",
    "\n",
    "param_est['delta_nat_unit'] = np.hstack(\n",
    "    [np.ones(29), np.array([100, 1000, 1], dtype='float32'), np.zeros(2)])\n",
    "\n",
    "param_est['delta_impact_pct'] = (\n",
    "    100 * param_est['mean'] * param_est['delta_nat_unit'] / param_est['std'])\n",
    "\n",
    "param_est['delta_impact_pct'] = (\n",
    "    param_est['delta_impact_pct'].apply(lambda x: '{0:.2f}%'.format(x)))\n",
    "\n",
    "results = param_est.drop(['sd', 'eff_n', 'r_hat', 'mc error'], axis=1)\n",
    "results"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Model Interrogation\n",
    "\n",
    "Now that we have chosen a model that we believe is the most representative of the processes that led to the observed data, we can exploit the fact that this model is a *generative* model of these processes, start to ask detailed questions of it and stop relying on analyses of point estimates to answer complicated questions that these sorts of approximative analyses cannot address completely."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Analysis #1 - English Forward vs. Sealed Bid Auctions A/B Test\n",
    "\n",
    "The first question that we will ask, are English Forward (EF) auction mechanisms perform better than Sealed Bid (SB) auction mechanisms. We already know that the *mean* (point estimates) of the EF and SB factors imply that EF auctions out-perform SB auctions *on average*, but these can only be taken at fact-value if there is correlation between the parameters (remember, these are also random variables). As we are now in a position to explicitly compute the differences and factor-in any dependency structure, we proceed with this approach."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "P(EF-effect > SB-effect) = 0.9988\n",
      "mean difference in RoR between EF and EB auctions = 0.025188116606057145\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "auction_mech_ab = pd.DataFrame(\n",
    "    ror_robust_trace['alpha_mech'], columns=['EF', 'SB'])\n",
    "\n",
    "auction_mech_ab['diff'] = (\n",
    "    label_itfm(auction_mech_ab['EF']) - label_itfm(auction_mech_ab['SB']))\n",
    "\n",
    "prob_EF_gt_SB = (\n",
    "    len(auction_mech_ab[auction_mech_ab['diff'] > 0]) / len(auction_mech_ab))\n",
    "\n",
    "mean_diff = auction_mech_ab['diff'].mean()\n",
    "print('P(EF-effect > SB-effect) = {}'.format(prob_EF_gt_SB))\n",
    "print('mean difference in RoR between EF and EB auctions = {}'.format(mean_diff))\n",
    "\n",
    "_ = sns.distplot(auction_mech_ab['diff'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It is conclusive that the EF auction mechanism *slightly* outperforms SB auction mechanisms."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Analysis #2 - Quantifying the Impact of Bidders-Per-Lot\n",
    "\n",
    "We would like to understand how BPL impacts the RoR for a lot, in isolation of all other variables. We achieve this by sampling form the the posterior predictive distribution while setting all other numerical variables to their average values (which is 0 as we have standardised the input data), and, by considering only the EF auction mechanism as used by the EU country category."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 10000/10000 [01:54<00:00, 86.99it/s]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def BPL_control_data(n):\n",
    "    # setup BPCc support\n",
    "    BPL_mean = model_data['BPL'].mean()\n",
    "    BPL_std = model_data['BPL'].std()\n",
    "    BPL_range = np.linspace(0, n, n+1)\n",
    "    BPL_range_stdised = (BPL_range - BPL_mean) / BPL_std\n",
    "\n",
    "    # setup all other numerical variates at average/control levels\n",
    "    all_other_vars = np.zeros(n+1)\n",
    "\n",
    "    # setup categorical variabes to be EF auctions for EU\n",
    "    auction_mech_fix = np.zeros(n+1)\n",
    "    country_fix = np.zeros(n+1) + 16\n",
    "\n",
    "    # set values on model variables\n",
    "    lots.set_value(all_other_vars)\n",
    "    mean_rsv.set_value(all_other_vars)\n",
    "    avg_start_bid.set_value(all_other_vars)\n",
    "    BPL.set_value(BPL_range_stdised)\n",
    "    auction_mech.set_value(auction_mech_fix.astype('int32'))\n",
    "    country.set_value(country_fix.astype('int32'))\n",
    "    start_bids.set_value(all_other_vars.astype('int32'))\n",
    "    return BPL_range\n",
    "\n",
    "\n",
    "BPL_support = BPL_control_data(30)\n",
    "\n",
    "BPL_pp_dist = pm.sample_posterior_predictive(\n",
    "    ror_robust_trace, model=ror_robust, samples=10000, random_seed=42)['obs']\n",
    "\n",
    "RoR_pp_mean = label_itfm(BPL_pp_dist.mean(axis=0))\n",
    "\n",
    "RoR_pp_lwr = (\n",
    "    RoR_pp_mean\n",
    "    - label_itfm(np.percentile(BPL_pp_dist, 2.5, axis=0)))\n",
    "\n",
    "RoR_pp_upr = (\n",
    "    label_itfm(np.percentile(BPL_pp_dist, 97.5, axis=0))\n",
    "    - RoR_pp_mean)\n",
    "\n",
    "BPL_control_df = pd.DataFrame(\n",
    "    {'BPL': BPL_support, 'RoR_mean': RoR_pp_mean, 'RoR_lwr': RoR_pp_lwr,\n",
    "     'RoR_upr': RoR_pp_upr})\n",
    "\n",
    "_ = (sns.lineplot(x='BPL', y='RoR_mean', data=BPL_control_df, ci=None)\n",
    "     .errorbar(x=BPL_control_df.BPL, y=BPL_control_df.RoR_mean,\n",
    "               yerr=[BPL_control_df.RoR_lwr, BPL_control_df.RoR_upr]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see that BPL has a positive impact on performance, as one would expect from basic auction theory."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Analysis #3 - Posterior Predictive Check\n",
    "\n",
    "As a check on the distributional properties of our model, we compare the posterior predictive distribution (below in blue), to the distribution of the test dataset (below orange, overlaid onto the posterior predictive distribution)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 10000/10000 [02:27<00:00, 67.78it/s]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "load_train_data()\n",
    "\n",
    "pp_test_dist = pm.sample_posterior_predictive(\n",
    "    ror_robust_trace, model=ror_robust, samples=10000, random_seed=42)['obs']\n",
    "\n",
    "_ = sns.distplot(\n",
    "    pp_test_dist.ravel(), bins=50, norm_hist=True, kde=False, \n",
    "    hist_kws={'range': [-2, 2]})\n",
    "\n",
    "_ = sns.distplot(\n",
    "    y_test, bins=50, norm_hist=True, kde=False, \n",
    "    hist_kws={'histtype': 'step', 'color': 'r', 'range': [-2, 2],\n",
    "              'linewidth': 2}, ax=_)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "By visual inspection alone, it is possible to see that the distributions are a good match, but that the distribution of the data is more leptokurtic than that of the model's - i.e. the 'tails' of the data are fatter than the Student-T we have used for the likelihood."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Conclusions\n",
    "\n",
    "- English Forward auctions are likely to out-perform sealed bid auctions, on average;\n",
    "- the number of lots offered has a small negative impact on price - e.g adding 100 more lots than usual will reduce prices by ~2.6%, on average;\n",
    "- the number of bidders per-lot has a positive impact on RoR; and,\n",
    "- there is a lot of variation in regional market micro-structure - e.g the factors that determine supply-and-demand dynamics (how much of what can be sold to whom, given competition), varies considerably on a regional basis."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}