{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# 5 Modeling" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 5.1 Contents\n", "* [5 Modeling](#5_Modeling)\n", " * [5.1 Contents](#5.1_Contents)\n", " * [5.2 Introduction](#5.2_Introduction)\n", " * [5.3 Imports](#5.3_Imports)\n", " * [5.4 Load Model](#5.4_Load_Model)\n", " * [5.5 Load Data](#5.5_Load_Data)\n", " * [5.6 Refit Model On All Available Data (excluding Big Mountain)](#5.6_Refit_Model_On_All_Available_Data_(excluding_Big_Mountain))\n", " * [5.7 Calculate Expected Big Mountain Ticket Price From The Model](#5.7_Calculate_Expected_Big_Mountain_Ticket_Price_From_The_Model)\n", " * [5.8 Big Mountain Resort In Market Context](#5.8_Big_Mountain_Resort_In_Market_Context)\n", " * [5.8.1 Ticket price](#5.8.1_Ticket_price)\n", " * [5.8.2 Vertical drop](#5.8.2_Vertical_drop)\n", " * [5.8.3 Snow making area](#5.8.3_Snow_making_area)\n", " * [5.8.4 Total number of chairs](#5.8.4_Total_number_of_chairs)\n", " * [5.8.5 Fast quads](#5.8.5_Fast_quads)\n", " * [5.8.6 Runs](#5.8.6_Runs)\n", " * [5.8.7 Longest run](#5.8.7_Longest_run)\n", " * [5.8.8 Trams](#5.8.8_Trams)\n", " * [5.8.9 Skiable terrain area](#5.8.9_Skiable_terrain_area)\n", " * [5.9 Modeling scenarios](#5.9_Modeling_scenarios)\n", " * [5.9.1 Scenario 1](#5.9.1_Scenario_1)\n", " * [5.9.2 Scenario 2](#5.9.2_Scenario_2)\n", " * [5.9.3 Scenario 3](#5.9.3_Scenario_3)\n", " * [5.9.4 Scenario 4](#5.9.4_Scenario_4)\n", " * [5.10 Summary](#5.10_Summary)\n", " * [5.11 Further work](#5.11_Further_work)\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 5.2 Introduction" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In this notebook, we now take our model for ski resort ticket price and leverage it to gain some insights into what price Big Mountain's facilities might actually support, as well as explore the sensitivity of changes to various resort parameters. Note, this relies on the implicit assumption that all other resorts are largely setting prices based on how much people value certain facilities. This means comparable prices are set correctly.\n", "\n", "We can now use our model to gain insight into what Big Mountain's ideal ticket price could/should be, and how that might change under various scenarios." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 5.3 Imports" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "import numpy as np\n", "import os\n", "import pickle\n", "import matplotlib.pyplot as plt\n", "import seaborn as sns\n", "from sklearn import __version__ as sklearn_version\n", "from sklearn.model_selection import cross_validate" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 5.4 Load Model" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "# This isn't exactly production-grade, but a quick check for development\n", "# These checks can save some head-scratching in development when moving from\n", "# one python environment to another, for example\n", "expected_model_version = '1.0'\n", "model_path = '../models/ski_resort_pricing_model.pkl'\n", "if os.path.exists(model_path):\n", " with open(model_path, 'rb') as f:\n", " model = pickle.load(f)\n", " if model.version != expected_model_version:\n", " print(\"Expected model version doesn't match version loaded\")\n", " if model.sklearn_version != sklearn_version:\n", " print(\"Warning: model created under different sklearn version\")\n", "else:\n", " print(\"Expected model not found\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 5.5 Load Data" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "# Load our model features\n", "ski_data = pd.read_csv('../data/ski_data_step3_features.csv')" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
124
NameBig Mountain Resort
RegionMontana
stateMontana
summit_elev6817
vertical_drop2353
base_elev4464
trams0
fastSixes0
fastQuads3
quad2
triple6
double0
surface3
total_chairs14
Runs105.0
TerrainParks4.0
LongestRun_mi3.3
SkiableTerrain_ac3000.0
Snow Making_ac600.0
daysOpenLastYear123.0
yearsOpen72.0
averageSnowfall333.0
AdultWeekend81.0
projectedDaysOpen123.0
NightSkiing_ac600.0
resorts_per_state12
resorts_per_100kcapita1.122778
resorts_per_100ksq_mile8.161045
resort_skiable_area_ac_state_ratio0.140121
resort_days_open_state_ratio0.129338
resort_terrain_park_state_ratio0.148148
resort_night_skiing_state_ratio0.84507
total_chairs_runs_ratio0.133333
total_chairs_skiable_ratio0.004667
fastQuads_runs_ratio0.028571
fastQuads_skiable_ratio0.001
\n", "
" ], "text/plain": [ " 124\n", "Name Big Mountain Resort\n", "Region Montana\n", "state Montana\n", "summit_elev 6817\n", "vertical_drop 2353\n", "base_elev 4464\n", "trams 0\n", "fastSixes 0\n", "fastQuads 3\n", "quad 2\n", "triple 6\n", "double 0\n", "surface 3\n", "total_chairs 14\n", "Runs 105.0\n", "TerrainParks 4.0\n", "LongestRun_mi 3.3\n", "SkiableTerrain_ac 3000.0\n", "Snow Making_ac 600.0\n", "daysOpenLastYear 123.0\n", "yearsOpen 72.0\n", "averageSnowfall 333.0\n", "AdultWeekend 81.0\n", "projectedDaysOpen 123.0\n", "NightSkiing_ac 600.0\n", "resorts_per_state 12\n", "resorts_per_100kcapita 1.122778\n", "resorts_per_100ksq_mile 8.161045\n", "resort_skiable_area_ac_state_ratio 0.140121\n", "resort_days_open_state_ratio 0.129338\n", "resort_terrain_park_state_ratio 0.148148\n", "resort_night_skiing_state_ratio 0.84507\n", "total_chairs_runs_ratio 0.133333\n", "total_chairs_skiable_ratio 0.004667\n", "fastQuads_runs_ratio 0.028571\n", "fastQuads_skiable_ratio 0.001" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Locate and view Big Mountain\n", "big_mountain = ski_data[ski_data.Name == 'Big Mountain Resort']\n", "big_mountain.T" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 5.6 Refit Model On All Available Data (excluding Big Mountain)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This next step requires some careful thought. We want to refit the model using all available data. But should we include Big Mountain data? The motivation for this entire project is based on the sense that Big Mountain needs to adjust its pricing. One way to phrase this problem: We want to train a model to predict Big Mountain's ticket price based on data from _all other_ resorts! We don't want Big Mountain's current price to bias this. We want to calculate a price based only on its competitors." ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "# Remove Big Mountain from model design matrix and target\n", "X = ski_data.loc[ski_data.Name != \"Big Mountain Resort\", model.X_columns]\n", "y = ski_data.loc[ski_data.Name != \"Big Mountain Resort\", 'AdultWeekend']" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(277, 277)" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Check vector lengths\n", "len(X), len(y)" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Pipeline(steps=[('simpleimputer', SimpleImputer()), ('standardscaler', None),\n", " ('randomforestregressor',\n", " RandomForestRegressor(n_estimators=233, random_state=47))])" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Apply our model to our design matrix of features and response vector\n", "model.fit(X, y)" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "# Cross-validate the model\n", "cv_results = cross_validate(model, X, y, scoring='neg_mean_absolute_error', cv=5, n_jobs=-1)" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([-12.29858906, -9.13243332, -11.56087007, -8.30959188,\n", " -10.61311198])" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Grab our 5 fold cv scores\n", "cv_results['test_score']" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(10.382919263140293, 1.4814013000415358)" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# View mean absolute error stats\n", "mae_mean, mae_std = np.mean(-1 * cv_results['test_score']), np.std(-1 * cv_results['test_score'])\n", "mae_mean, mae_std" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "These numbers will inevitably be different to those in the previous step that used a different training data set. They should, however, be consistent. It's important to appreciate that estimates of model performance are subject to the noise and uncertainty of data!" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 5.7 Calculate Expected Big Mountain Ticket Price From The Model" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [], "source": [ "# Run Big Mountain data\n", "X_bm = ski_data.loc[ski_data.Name == \"Big Mountain Resort\", model.X_columns]\n", "y_bm = ski_data.loc[ski_data.Name == \"Big Mountain Resort\", 'AdultWeekend']" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [], "source": [ "# Obtain predictions\n", "bm_pred = model.predict(X_bm).item()" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [], "source": [ "# Grab actual price; this and the above combine to form our loss function\n", "y_bm = y_bm.values.item()" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Big Mountain Resort modelled price is $93.82, actual price is $81.00.\n", "Even with the expected mean absolute error of $10.38, this suggests there is room for an increase.\n" ] } ], "source": [ "print(f'Big Mountain Resort modelled price is ${bm_pred:.2f}, actual price is ${y_bm:.2f}.')\n", "print(f'Even with the expected mean absolute error of ${mae_mean:.2f}, this suggests there is room for an increase.')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This result should be looked at optimistically and doubtfully! The validity of our model lies in the assumption that other resorts accurately set their prices according to what the market (the ticket-buying public) supports. The fact that our resort seems to be charging that much less than what's predicted suggests our resort might be undercharging. \n", "But if Big Mountain is missing the market, are others? It's reasonable to expect that some resorts will be \"overpriced\" and some \"underpriced.\" Or if resorts are pretty good at pricing strategies, it could be that our model is simply lacking some key data? Certainly we know nothing about operating costs, for example, and they would surely help." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 5.8 Big Mountain Resort In Market Context" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Features that came up as important in the modeling (not just our final, random forest model) included:\n", "* vertical_drop\n", "* Snow Making_ac\n", "* total_chairs\n", "* fastQuads\n", "* Runs\n", "* LongestRun_mi\n", "* trams\n", "* SkiableTerrain_ac" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A handy glossary of skiing terms can be found on the [ski.com](https://www.ski.com/ski-glossary) site. Some potentially relevant contextual information is that vertical drop, although nominally the height difference from the summit to the base, is generally taken from the highest [_lift-served_](http://verticalfeet.com/) point." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It's often useful to define custom functions for visualizing data in meaningful ways. The function below takes a feature name as an input and plots a histogram of the values of that feature. It then marks where Big Mountain sits in the distribution by marking Big Mountain's value with a vertical line using `matplotlib`'s [axvline](https://matplotlib.org/3.1.1/api/_as_gen/matplotlib.pyplot.axvline.html) function. It also performs a little cleaning up of missing values and adds descriptive labels and a title." ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [], "source": [ "# Add code to the `plot_compare` function that displays a vertical, dashed line\n", "# on the histogram to indicate Big Mountain's position in the distribution\n", "# Hint: plt.axvline() plots a vertical line, its position for 'feature1'\n", "# would be `big_mountain['feature1'].values, we'd like a red line, which can be\n", "# specified with c='r', a dashed linestyle is produced by ls='--',\n", "# and it's nice to give it a slightly reduced alpha value, such as 0.8.\n", "# Don't forget to give it a useful label (e.g. 'Big Mountain') so it's listed\n", "# in the legend.\n", "def plot_compare(feat_name, description, state=None, figsize=(10, 5)):\n", " \"\"\"Graphically compare distributions of features.\n", " \n", " Plot histogram of values for all resorts and reference line to mark\n", " Big Mountain's position.\n", " \n", " Arguments:\n", " feat_name - the feature column name in the data\n", " description - text description of the feature\n", " state - select a specific state (None for all states)\n", " figsize - (optional) figure size\n", " \"\"\"\n", " \n", " plt.subplots(figsize=figsize)\n", " # quirk that hist sometimes objects to NaNs, sometimes doesn't\n", " # filtering only for finite values tidies this up\n", " if state is None:\n", " ski_x = ski_data[feat_name]\n", " else:\n", " ski_x = ski_data.loc[ski_data.state == state, feat_name]\n", " ski_x = ski_x[np.isfinite(ski_x)]\n", " plt.hist(ski_x, bins=30)\n", " plt.axvline(x=big_mountain[feat_name].values, c='r', ls='--', alpha=0.8, label='Big Montain')\n", " plt.xlabel(description)\n", " plt.ylabel('frequency')\n", " plt.title(description + ' distribution for resorts in market share')\n", " plt.legend()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 5.8.1 Ticket price" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Look at where Big Mountain sits overall amongst all resorts for price and for just other resorts in Montana." ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot_compare('AdultWeekend', 'Adult weekend ticket price ($)')" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot_compare('AdultWeekend', 'Adult weekend ticket price ($) - Montana only', state='Montana')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 5.8.2 Vertical drop" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot_compare('vertical_drop', 'Vertical drop (feet)')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Big Mountain is doing well for vertical drop, but there are still quite a few resorts with a greater drop." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 5.8.3 Snow making area" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAA0oAAAHUCAYAAAAEKdj3AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8o6BhiAAAACXBIWXMAAA9hAAAPYQGoP6dpAABs8UlEQVR4nO3dd3gUVfv/8c+SsimEQGhJIIbQexGkSpcOUkQQC6BYUapI0UcBC0EQhEcfwUYABQEV+SJILwEFlCKgIFWqEIMIhJJCkvP7I78s7KaQQMKG5f26rrmu2TNnZu+ZMzObOzNzxmKMMQIAAAAA2ORzdgAAAAAAkNeQKAEAAACAAxIlAAAAAHBAogQAAAAADkiUAAAAAMABiRIAAAAAOCBRAgAAAAAHJEoAAAAA4IBECQAAAAAckCjdxf773//KYrGoatWqzg4FDpo1a6ZmzZrdsJ7FYtFLL72U+wEhS8aMGSOLxaJ//vnH2aFkauPGjbJarTp27JizQ7lpV69eVZkyZTRlypRbWs769etlsVi0fv16W1nfvn1VqlSpbC3n1KlTGjNmjHbu3Jmt+dL7rtw4rj/66CPNnDkzTfnRo0dlsVjSnXY7fPDBBypbtqw8PT1lsVh0/vx5p8SR14wbN06LFi3KseWlt5+7gpw85165ckVjxozJ0W10p/wmIGMkSnexGTNmSJL27Nmjn3/+2cnRALgdjDEaPHiwnnnmGYWGhjo7nJvm4eGhN954Q2+++abOnj2bo8t+/fXX9d1332VrnlOnTmns2LHZTpRu5rtuRkaJUlBQkDZv3qwOHTrkegyOdu7cqYEDB6p58+Zau3atNm/eLD8/v9seR16U04nSvffeq82bN+vee+/NsWW6mitXrmjs2LEul0zi1pAo3aW2bdumXbt22X4cP//88yzNl5SUpPj4+NwM7Y525coVZ4cAF5YTx9/y5cu1Y8cODRgwIIeiyprcODZ69eoli8Wijz/+OEeXW6ZMGdWqVStHl+kodXvcju/KjNVqVf369VW0aNHb/t179uyRJD3zzDO6//77Vb9+fbm5ud3SMrO7n+W1c3ZsbGyuLLdAgQKqX7++ChQokCvLv91iY2NljHF2GHlGXtuPXQmJ0l0qNTEaP368GjZsqHnz5qU50FJvyZgwYYLefvtthYWFyWq1at26dZJSkq0HH3xQAQEB8vLyUq1atbRgwQK7ZZw5c0b9+/dX5cqVlT9/fhUrVkwtWrTQxo0bsxzr3Llz1aBBA+XPn1/58+dXzZo10yR2M2bMUI0aNeTl5aWAgAB17dpVf/zxh236lClTZLFYdOjQoTTLHzFihDw9Pe0uja9evVotW7ZUgQIF5OPjo0aNGmnNmjV286VeUt+xY4e6d++uQoUKqUyZMpJS/mv/0UcfqWbNmvL29lahQoXUvXt3/fnnn3bLMMZowoQJCg0NlZeXl+69914tW7Ysy9sm1ccff6zy5cvLarWqcuXKmjdvnm3a0aNH5e7urvDw8DTzbdiwQRaLRV9//XWGy05OTtbbb7+tChUqyNvbWwULFlT16tU1derUNNtiz5496tWrl/z9/VW8eHE99dRTunDhgt3y4uLiNGrUKIWFhcnT01MlSpTQiy++aHfLzSuvvCJ/f38lJSXZygYMGCCLxaKJEyfays6ePat8+fLpgw8+yHT7pN7KFBERYVuPOnXqaMuWLTLGaOLEiQoLC1P+/PnVokWLNPvJqlWr1LlzZ5UsWVJeXl4qW7asnnvuuSzdTrFv3z6VLl1a9erVU3R0tCQpKipKzz33nEqWLClPT0+FhYVp7NixSkxMtM2X2fGXlTbJyLRp03TfffepQoUKduXz589X69atFRQUJG9vb1WqVEkjR47U5cuX0yzj559/VqdOnVS4cGF5eXmpTJkyGjx4sG16Thwbv/76qzp27KhixYrJarUqODhYHTp00MmTJ211PD091bNnT33yySdZ+qNp3759atu2rXx8fFSkSBE9//zzunjxYpp66d0O9/XXX6tevXry9/eXj4+PSpcuraeeekpSym1N9913nyTpySeflMVikcVi0ZgxY2zLy58/v3777Te1bt1afn5+atmyZYbflSqz4/r67exo5syZslgsOnr0qCSpVKlS2rNnjyIjI22xpX5nRrfe/fjjj2rZsqX8/Pzk4+Ojhg0baunSpel+z7p16/TCCy+oSJEiKly4sLp166ZTp06lu06pmjVrpscff1ySVK9ePVksFvXt29c2/Ubn9NRtl9F2Tc/t2i+zco6TUtqlY8eOWrhwoWrVqiUvLy+NHTtWFotFly9f1qxZs2ztlXor9pUrVzRs2DCFhYXZtk2dOnX01VdfZbq9M7rFNH/+/Dp06JDat2+v/PnzKyQkRC+//HKW/iGTGv+SJUtUq1Yt23ljyZIlklL2j0qVKsnX11d169bVtm3b7Obftm2bHnnkEZUqVUre3t4qVaqUevXqleaW4NT9bOXKlXrqqadUtGhR+fj4ZBjjzZxzjx49avtnQWobOO6TjrJzHv77779v+Nv4v//9T02aNFGxYsXk6+uratWqacKECbp69apdvWbNmqlq1arasGGDGjZsKB8fH9u5KCYmxrZ/pO57gwcPTvc8jiwyuOtcuXLF+Pv7m/vuu88YY8xnn31mJJmZM2fa1Tty5IiRZEqUKGGaN29uvvnmG7Ny5Upz5MgRs3btWuPp6WkaN25s5s+fb5YvX2769u1rJJmIiAjbMvbt22deeOEFM2/ePLN+/XqzZMkS069fP5MvXz6zbt26G8b6+uuvG0mmW7du5uuvvzYrV640kydPNq+//rqtzrhx44wk06tXL7N06VIze/ZsU7p0aePv728OHDhgjDHmzJkzxtPT07z22mt2y09MTDTBwcGmW7dutrIvvvjCWCwW06VLF7Nw4ULz/fffm44dOxo3NzezevVqW73Ro0cbSSY0NNSMGDHCrFq1yixatMgYY8wzzzxjPDw8zMsvv2yWL19u5s6daypWrGiKFy9uoqKi0iyjX79+ZtmyZeaTTz4xJUqUMIGBgaZp06Y33D6STEhIiKlcubL56quvzOLFi03btm2NJPP111/b6nXt2tXcc889JjEx0W7+hx9+2AQHB5urV69m+B3h4eHGzc3NjB492qxZs8YsX77cTJkyxYwZMybNelSoUMG88cYbZtWqVWby5MnGarWaJ5980lYvOTnZtGnTxri7u5vXX3/drFy50rz33nvG19fX1KpVy8TFxRljjFm+fLmRZDZt2mSbt2LFisbb29u0atXKVjZ//nwjyezdu/eG2yk0NNQ0bNjQLFy40Hz33XemfPnyJiAgwAwZMsR07tzZLFmyxMyZM8cUL17cVK9e3SQnJ9vmnzZtmgkPDzeLFy82kZGRZtasWaZGjRqmQoUKJiEhIc12OHPmjDHGmPXr15tChQqZzp07m8uXLxtjjDl9+rQJCQkxoaGh5uOPPzarV682b731lrFaraZv3762ZWV2/GWlTdITHx9vvL29zfDhw9NMe+utt8z7779vli5datavX2+mT59uwsLCTPPmze3qLV++3Hh4eJjq1aubmTNnmrVr15oZM2aYRx55JM12uNlj49KlS6Zw4cKmTp06ZsGCBSYyMtLMnz/fPP/882naOnUf2L17d6brHhUVZYoVK2ZKlChhIiIizA8//GAee+wxc8899xhJduejPn36mNDQUNvnTZs2GYvFYh555BHzww8/mLVr15qIiAjzxBNPGGOMuXDhgomIiDCSzH/+8x+zefNms3nzZnPixAnb8jw8PEypUqVMeHi4WbNmjVmxYkW632VM1o/r1O3sKDWWI0eOGGOM2bFjhyldurSpVauWLbYdO3YYY67tZ9eft9evX288PDxM7dq1zfz5882iRYtM69atjcViMfPmzUvzPaVLlzYDBgwwK1asMJ999pkpVKhQmv3G0Z49e8x//vMf23dv3rzZHDp0yBiTtXP6jbZrem7HfpnVc5wxxoSGhpqgoCBTunRpM2PGDLNu3Trzyy+/mM2bNxtvb2/Tvn17W3vt2bPHGGPMc889Z3x8fMzkyZPNunXrzJIlS8z48ePNBx98kOn2XrduXbr7uaenp6lUqZJ57733zOrVq80bb7xhLBaLGTt2bKbLS42/ZMmSpmrVquarr74yP/zwg6lXr57x8PAwb7zxhmnUqJHd+bZ48eLmypUrtvm//vpr88Ybb5jvvvvOREZGmnnz5pmmTZuaokWL2s6hxlzbz0qUKGGeffZZs2zZMvPNN9+YxMTEHDvnxsXF2X53+vXrZ9vuqftkenLyt9EYY4YMGWKmTZtmli9fbtauXWvef/99U6RIkTT1mjZtagICAkxISIj54IMPzLp160xkZKS5fPmyqVmzpilSpIiZPHmyWb16tZk6darx9/c3LVq0sPtNQ9aRKN2FZs+ebSSZ6dOnG2OMuXjxosmfP79p3LixXb3UH9AyZcrY/TFoTMofrbVq1UrzB3bHjh1NUFCQSUpKSve7ExMTzdWrV03Lli1N165dM43zzz//NG5ubuaxxx7LsM65c+dsPyjXO378uLFarebRRx+1lXXr1s2ULFnSLrYffvjBSDLff/+9McaYy5cvm4CAANOpUye75SUlJZkaNWqYunXr2spST4BvvPGGXd3NmzcbSWbSpEl25SdOnLD7I/XcuXPGy8srzXb46aefjKQsJ0re3t52yVdiYqKpWLGiKVu2rK0s9Ufyu+++s5X99ddfxt3d/YY/iB07djQ1a9bMtE7qtpgwYYJdef/+/Y2Xl5ftBJ36Q+RYL/WP3U8++cQYk9IOnp6e5s033zTGGHPy5EkjyYwYMcJ4e3vb/th45plnTHBwcKaxGZOynQIDA82lS5dsZYsWLTKSTM2aNe1+QKZMmZLpH97Jycnm6tWr5tixY0aS+b//+7802+HMmTPmiy++MJ6enmbgwIF2+9xzzz1n8ufPb44dO2a33Pfee89Isv1BlNnxl5U2Sc/PP/9sJNn9sZvZOkZGRhpJZteuXbZpZcqUMWXKlDGxsbEZzn+rx8a2bduMJNsfsZk5ePCgkWSmTZuWab0RI0YYi8Vidu7caVfeqlWrGyZKqW1z/vz5DJe/devWNAnH9cuTZGbMmJHutPQSpawc11lNlIwxpkqVKumeU9JLlOrXr2+KFStmLl68aPf9VatWNSVLlrQdL6nf079/f7tlTpgwwUgyp0+fTvN96cW5detWW1l2zumZbdf03I79MqvnOGNSEg03Nzezf//+NMvx9fU1ffr0SVNetWpV06VLlxuuq6OMEiVJZsGCBXZ127dvbypUqHDDZYaGhhpvb29z8uRJW9nOnTuNJBMUFGRLVIy5dr5dvHhxhstLTEw0ly5dMr6+vmbq1Km28tT9pHfv3mnmyclz7pkzZ4wkM3r06BuuuzE5+9voKCkpyVy9etXMnj3buLm5mX///dc2rWnTpkaSWbNmjd084eHhJl++fHbHkzHGfPPNN0aS+eGHH7K0XrDHrXd3oc8//1ze3t565JFHJEn58+fXww8/rI0bN+rgwYNp6j/44IPy8PCwfT506JD27dunxx57TJKUmJhoG9q3b6/Tp09r//79tvrTp0/XvffeKy8vL7m7u8vDw0Nr1qxJcxuFo1WrVikpKUkvvvhihnU2b96s2NjYNJfHQ0JC1KJFC7vb5Z588kmdPHlSq1evtpVFREQoMDBQ7dq1kyRt2rRJ//77r/r06WO3XsnJyWrbtq22bt2a5hL2Qw89ZPd5yZIlslgsevzxx+2WERgYqBo1athufdi8ebPi4uJs2zFVw4YNs/WQfcuWLVW8eHHbZzc3N/Xs2VOHDh2y3Q7SrFkz1ahRQ//73/9s9aZPny6LxaJnn3020+XXrVtXu3btUv/+/bVixQrFxMRkWPfBBx+0+1y9enXFxcXZbn9Yu3atJKVpr4cffli+vr629vLx8VGDBg1sbbVq1SoVLFhQr7zyihISEvTjjz9KSrlF8oEHHsg0/lTNmzeXr6+v7XOlSpUkSe3atbO7fSm1/PrbP6Kjo/X8888rJCTEtg+ntlF6+/E777yjvn37avz48Zo6dary5bt2ql2yZImaN2+u4OBgu/0jdR+MjIy0W5bj8Sdlr02ul3o7VLFixdJM+/PPP/Xoo48qMDBQbm5u8vDwUNOmTe3W8cCBAzp8+LD69esnLy+vG37fzR4bZcuWVaFChTRixAhNnz5de/fuzfA7Utflr7/+yjSWdevWqUqVKqpRo4Zd+aOPPnrD9Ui9ra5Hjx5asGDBDb8rI47bIzNZOa5zw+XLl/Xzzz+re/fuyp8/v933P/HEEzp58qTd+V1K/7iXdFO9KmbnnJ4qO9s1vfo5uV9m9RyXqnr16ipfvnyWY69bt66WLVumkSNHav369bf8TJPFYlGnTp3SxJTVtqtZs6ZKlChh+5x6/mzWrJl8fHzSlF+/3EuXLmnEiBEqW7as3N3d5e7urvz58+vy5cvpnlcza+ecPOdmVU7+Nkopt3U++OCDKly4sO0c3Lt3byUlJenAgQN28xcqVEgtWrSwK1uyZImqVq2qmjVr2q1nmzZtXLLHw9uFROkuc+jQIW3YsEEdOnSQMUbnz5/X+fPn1b17d0nXesK7XlBQkN3nv//+W5I0bNgweXh42A39+/eXJNuzG5MnT9YLL7ygevXq6dtvv9WWLVu0detWtW3b9oYn+DNnzkiSSpYsmWGd1N6uHGOUpODgYLvesNq1a6egoCBFRERIks6dO6fFixerd+/etgeIU9ete/fuadbt3XfflTFG//777w23jzFGxYsXT7OMLVu22LZNamyBgYFpYk+vLCOZzX/9+g8cOFBr1qzR/v37dfXqVX366afq3r37Db9r1KhReu+997Rlyxa1a9dOhQsXVsuWLdPcby5JhQsXtvtstVolXXtA+ezZs3J3d0/z4LjFYlFgYKBdvA888IC2bNmiy5cva/Xq1WrRooUKFy6s2rVra/Xq1Tpy5IiOHDmS5UQpICDA7rOnp2em5XFxcZJS7kNv3bq1Fi5cqOHDh2vNmjX65ZdftGXLFrt1u96XX36pEiVK2P4Zcb2///5b33//fZp9o0qVKpKU5rmn9Pbt7LTJ9VJjdUxyLl26pMaNG+vnn3/W22+/rfXr12vr1q1auHCh3XxZOSYziz2rx4a/v78iIyNVs2ZNvfrqq6pSpYqCg4M1evToNPfrp67Ljc4nZ8+eveljrUmTJlq0aJESExPVu3dvlSxZUlWrVr3hcyHX8/HxydaD9Fk9rnPauXPnZIzJ8Jya3vff6LjPjuyc06Xsb9f0lp2T+2V2znEZrWdm/vvf/2rEiBFatGiRmjdvroCAAHXp0iXdf3JmhY+PT5rzgdVqtZ3/buRmz6tSyj8pPvzwQz399NNasWKFfvnlF23dulVFixZNd9/JbFvl5Dk3q3Lyt/H48eNq3Lix/vrrL02dOlUbN27U1q1bbf/cdNwe6W2Lv//+W7t3706znn5+fjLG0EX5TXJ3dgC4vWbMmCFjjL755ht98803aabPmjVLb7/9tl3PQ44PCxcpUkRSykmiW7du6X5P6oPiX375pZo1a6Zp06bZTU/vAWpHqT80J0+eVEhISLp1Uk8+p0+fTjPt1KlTtlila/8R/e9//6vz589r7ty5io+P15NPPplm3T744APVr18/3e+8/r+8Uvrbx2Kx2N5V4yi1LDX2qKioNHWioqKy/B6XjOa//juklB+lESNG6H//+5/q16+vqKioTK/WpXJ3d9fQoUM1dOhQnT9/XqtXr9arr76qNm3a6MSJE3b/NbyRwoULKzExUWfOnLH7Q8IYo6ioKNt/7qWU/6i//vrr2rBhg9asWaPRo0fbyleuXKmwsDDb59z0+++/a9euXZo5c6b69OljK0+vY5BUy5cvV8+ePdW4cWOtWbPG7gphkSJFVL16db3zzjvpzpv6x2iq9B7Wv9k2Sd2/HZP9tWvX6tSpU1q/fr3tKpKkNA+fX39MZsXNHhuSVK1aNc2bN0/GGO3evVszZ87Um2++KW9vb40cOdJWL3Vdrj/W01O4cOFMj5Ub6dy5szp37qz4+Hht2bJF4eHhevTRR1WqVCk1aNDghvOn146ZycpxnfoHbnx8vN22u5U/iAoVKqR8+fJleE6Vbrytb0V2zulS9rdrevPk5H6ZnXPczcTv6+ursWPHauzYsfr7779tV5c6deqkffv2ZWtZznThwgUtWbJEo0ePtjue4+Pj05yfUmW2rXLynJtVOfnbuGjRIl2+fFkLFy60iz2j1w2kty2KFCkib2/vdP/hnTod2ccVpbtIUlKSZs2apTJlymjdunVphpdfflmnT5++Ya9rFSpUULly5bRr1y7VqVMn3SH1XRgWiyXND8/u3bu1efPmG8bbunVrubm5pUmyrtegQQN5e3vryy+/tCs/efKk1q5dm+aP6CeffFJxcXH66quvNHPmTDVo0EAVK1a0TW/UqJEKFiyovXv3Zrhuqf8Zy0jHjh1ljNFff/2V7vzVqlWTJNWvX19eXl6aM2eO3fybNm3K1i0ra9assV0Jk1Laef78+SpTpozdf/69vLz07LPPatasWZo8ebJq1qypRo0aZfl7JKlgwYLq3r27XnzxRf3777+2XrWyKrU9HNvr22+/1eXLl+3aq27duipQoICmTJmiqKgotWrVSlLKlaZff/1VCxYsUOXKlW/6Ry6rUn+QHPfjzLqkDg0Ntf3R1bhxY7v/9nbs2FG///67ypQpk+7+kd31yU6bpN7+cvjw4Ztax/Lly6tMmTKaMWPGTXVTntVjwzG2GjVq6P3331fBggW1Y8cOu+mpvZJVrlw50+9u3ry59uzZo127dtmVz507N1vrYLVa1bRpU7377ruSUm6XSS2Xcq5756wc16n/TNm9e7fdvN9//326cWclNl9fX9WrV08LFy60q5+cnKwvv/xSJUuWzNatYtmV3XN6TsjJ/TI757jMZKW9ihcvrr59+6pXr17av3//HdVFtMVikTEmzTnns88+s+vtNKty4px7K8fwrf42pncONsbo008/zfIyOnbsqMOHD6tw4cLprmd2X6KNFFxRuossW7ZMp06d0rvvvmvravR6VatW1YcffqjPP/9cHTt2zHRZH3/8sdq1a6c2bdqob9++KlGihP7991/98ccf2rFjh6276Y4dO+qtt97S6NGj1bRpU+3fv19vvvmmwsLC7LpCTk+pUqX06quv6q233lJsbKyta829e/fqn3/+0dixY1WwYEG9/vrrevXVV9W7d2/16tVLZ8+e1dixY+Xl5WW7CpGqYsWKatCggcLDw3XixAl98skndtPz58+vDz74QH369NG///6r7t27q1ixYjpz5ox27dqlM2fOZJq4SSnJ1rPPPqsnn3xS27ZtU5MmTeTr66vTp0/rxx9/VLVq1fTCCy+oUKFCGjZsmN5++209/fTTevjhh3XixAmNGTMmW7feFSlSRC1atNDrr78uX19fffTRR9q3b1+aroQlqX///powYYK2b9+uzz77LEvL79Spk6pWrao6deqoaNGiOnbsmKZMmaLQ0FCVK1cuy3FKUqtWrdSmTRuNGDFCMTExatSokXbv3q3Ro0erVq1aeuKJJ2x13dzc1LRpU33//fcKCwuzdePbqFEjWa1WrVmzRgMHDszW99+MihUrqkyZMho5cqSMMQoICND333+vVatWZTpfUFCQIiMj1aZNGzVp0kSrVq1S1apV9eabb2rVqlVq2LChBg4cqAoVKiguLk5Hjx7VDz/8oOnTp9/w1rabbZOSJUuqdOnS2rJli922a9iwoQoVKqTnn39eo0ePloeHh+bMmZMmqZBSurDt1KmT6tevryFDhuiee+7R8ePHtWLFijRJv6OsHhtLlizRRx99pC5duqh06dIyxmjhwoU6f/68LWFOtWXLFrm5ualJkyaZfvfgwYM1Y8YMdejQQW+//baKFy+uOXPmZOm/8G+88YZOnjypli1bqmTJkjp//rymTp1q9xxXmTJl5O3trTlz5qhSpUrKnz+/goODbzqRz8px3b59ewUEBKhfv35688035e7urpkzZ+rEiRNplpd6JWT+/PkqXbq0vLy80k0AJCk8PFytWrVS8+bNNWzYMHl6euqjjz7S77//rq+++uqmruJkVXbP6TkhJ/fL7JzjMlOtWjWtX79e33//vYKCguTn56cKFSqoXr166tixo6pXr65ChQrpjz/+0BdffKEGDRpk6wqGsxUoUEBNmjTRxIkTVaRIEZUqVUqRkZH6/PPPVbBgwZta5q2ec/38/BQaGqr/+7//U8uWLRUQEGCLLT05/dvo6empXr16afjw4YqLi9O0adN07ty5LC9j8ODB+vbbb9WkSRMNGTJE1atXV3Jyso4fP66VK1fq5ZdfVr169bIVF0T34HeTLl26GE9PTxMdHZ1hnUceecS4u7ubqKgoW29IEydOTLfurl27TI8ePUyxYsWMh4eHCQwMNC1atLD1pmdMSnfEw4YNMyVKlDBeXl7m3nvvNYsWLUq3p6eMzJ4929x3333Gy8vL5M+f39SqVStNz1KfffaZqV69uvH09DT+/v6mc+fOtp5sHH3yySe2XqUuXLiQbp3IyEjToUMHExAQYDw8PEyJEiVMhw4d0u2a9/puTK83Y8YMU69ePePr62u8vb1NmTJlTO/evc22bdtsdZKTk014eLgJCQkxnp6epnr16ub77783TZs2zXKvdy+++KL56KOPTJkyZYyHh4epWLGimTNnTobzNGvWzAQEBNh105qZSZMmmYYNG5oiRYoYT09Pc88995h+/fqZo0eP3nBbpNf7VmxsrBkxYoQJDQ01Hh4eJigoyLzwwgvm3Llzab576tSpRpJ55pln7MpTeyrLrAel66Vup+tltH+n9g51fVvv3bvXtGrVyvj5+ZlChQqZhx9+2Bw/fjxND0npbYfz58+bRo0amYCAAFtvRGfOnDEDBw40YWFhxsPDwwQEBJjatWub1157zdYzX2bHX1baJCOvv/66KVSokF03xcakdIHdoEED4+PjY4oWLWqefvpps2PHjnR7ctu8ebNp166d8ff3N1ar1ZQpU8YMGTIk0+1wvRsdG/v27TO9evUyZcqUMd7e3sbf39/UrVs3zSsMjDGmcePGaXqpzEhqO3p5eZmAgADTr18/83//93837PVuyZIlpl27dqZEiRLG09PTFCtWzLRv395s3LjRbvlfffWVqVixovHw8LDbN/r06WN8fX3TjSmjXu+yelz/8ssvpmHDhsbX19eUKFHCjB492vbKh+uPu6NHj5rWrVsbPz8/WxfZxqTf650xxmzcuNG0aNHC1kb169e39Q6aKr1e64xJv4e19GQ0vzFZO6dntl3Tc7v2y6ye40JDQ02HDh3SjWXnzp2mUaNGxsfHx64X1JEjR5o6deqYQoUKGavVakqXLm2GDBli/vnnn0zXPaNe79Lbfhn1pugoo/izer49efKkeeihh0yhQoWMn5+fadu2rfn9999NaGioXY9/me0nOXnONcaY1atXm1q1ahmr1WokpdvzYKqc/m38/vvvTY0aNYyXl5cpUaKEeeWVV8yyZcvStFvTpk1NlSpV0o3p0qVL5j//+Y+pUKGC7dipVq2aGTJkiF0vmsg6izG82hi4W0RHRys0NFQDBgzQhAkTnB0OnODUqVMKCwvT7Nmz1bNnT2eHc0sOHz6scuXKacWKFWmuNAEAcKtIlIC7wMmTJ/Xnn39q4sSJWrt2rQ4cOGDXpSvuLiNGjNCyZcu0c+dOu2507zSpXf7f6DZIAABuxp37Cwkgyz777DM1a9ZMe/bs0Zw5c0iS7nL/+c9/9NBDD930+4DygsTERJUpU8bu3WAAAOQkrigBAAAAgAOuKAEAAACAAxIlAAAAAHBAogQAAAAADlz+hbPJyck6deqU/Pz8cvUleQAAAADyNmOMLl68qODg4Bv2/OryidKpU6cUEhLi7DAAAAAA5BEnTpxQyZIlM63j8omSn5+fpJSNUaBAASdHAwAAgFyTnCz9/XfKePHi0h38rjjkjpiYGIWEhNhyhMy4fKKUertdgQIFSJQAAABcWWys9NhjKeMbN0re3s6NB3lWVh7JIc0GAAAAAAckSgAAAADggEQJAAAAABy4/DNKAICU7lATExOVlJTk7FDgRG5ubnJ3d+d1GQCQBSRKAODiEhISdPr0aV25csXZoSAP8PHxUVBQkDw9PZ0dCgDkaSRKAODCkpOTdeTIEbm5uSk4OFienp5cTbhLGWOUkJCgM2fO6MiRIypXrtwNX7YIAHczEiUAcGEJCQlKTk5WSEiIfHx8nB0OnMzb21seHh46duyYEhIS5OXl5eyQgJzl5iY9/PC1ceAWkCgBwF2AKwdIxb4Al+bpKY0Y4ewo4CI4WwIAAACAA64oAQAAwDUYI50/nzJesKDEM5m4BVxRAgDcsY4ePSqLxaKdO3c6O5Tbpm/fvurSpYuzwwDyprg4qVWrlCEuztnR4A5HogQAyJP69u0ri8ViGwoXLqy2bdtq9+7dtjohISE6ffq0qlatekvfVapUKVksFs2bNy/NtCpVqshisWjmzJm39B2OmjVrpsGDB2d7vqlTp+Z4LACAtEiUAAB5Vtu2bXX69GmdPn1aa9askbu7uzp27Gib7ubmpsDAQLm73/qd5CEhIYqIiLAr27Jli6KiouTr63vLy88p/v7+KliwoLPDAACXR6IEAHer2NiMh4SErNeNj79x3ZtktVoVGBiowMBA1axZUyNGjNCJEyd05swZSenferd48WKVK1dO3t7eat68uWbNmiWLxaLzqc8tZOCxxx5TZGSkTpw4YSubMWOGHnvssTSJ2PHjx9W5c2flz59fBQoUUI8ePfT333/bpo8ZM0Y1a9bUF198oVKlSsnf31+PPPKILl68KCnlallkZKSmTp1qu2J29OhRJSUlqV+/fgoLC5O3t7cqVKigqVOn2n234613zZo108CBAzV8+HAFBAQoMDBQY8aMycZWBgCkh84cAOBu1bhxxtMaNZKu/wM9s/v9771X+uSTa587dbr2MHWqbdtuOsxUly5d0pw5c1S2bFkVLlw43TpHjx5V9+7dNWjQID399NP69ddfNWzYsCwtv3jx4mrTpo1mzZql//znP7py5Yrmz5+vyMhIzZ4921bPGKMuXbrI19dXkZGRSkxMVP/+/dWzZ0+tX7/eVu/w4cNatGiRlixZonPnzqlHjx4aP3683nnnHU2dOlUHDhxQ1apV9eabb0qSihYtquTkZJUsWVILFixQkSJFtGnTJj377LMKCgpSjx49Mox91qxZGjp0qH7++Wdt3rxZffv2VaNGjdSqVassrTsAIC0SJRdTauTSXFv20fEdcm3ZAJCeJUuWKH/+/JKky5cvKygoSEuWLMnwXUDTp09XhQoVNHHiRElShQoV9Pvvv+udd97J0vc99dRTevnll/Xaa6/pm2++UZkyZVSzZk27OqtXr9bu3bt15MgRhYSESJK++OILValSRVu3btV9990nSUpOTtbMmTPl5+cnSXriiSe0Zs0avfPOO/L395enp6d8fHwUGBhoW7abm5vGjh1r+xwWFqZNmzZpwYIFmSZK1atX1+jRoyVJ5cqV04cffqg1a9aQKAHALSBRAoC71caNGU9zfKP9qlUZ13VMWr7//uZjctC8eXNNmzZNkvTvv//qo48+Urt27fTLL78oNDQ0Tf39+/fbEpVUdevWzfL3dejQQc8995w2bNigGTNm6KmnnkpT548//lBISIgtSZKkypUrq2DBgvrjjz9s31+qVClbkiRJQUFBio6OvmEM06dP12effaZjx44pNjZWCQkJaZI1R9WrV7f7nNXvAgBkjEQJAO5W3t7Or3sDvr6+Klu2rO1z7dq15e/vr08//VRvv/12mvrGGFkc3ptijMny97m7u+uJJ57Q6NGj9fPPP+u7777L0nekV+7h4WE33WKxKDk5OdPvX7BggYYMGaJJkyapQYMG8vPz08SJE/Xzzz9nOt/NfBfgktzcpNQOXxz/4QNkE4kSAOCOYbFYlC9fPsVm0EFExYoV9cMPP9iVbcvm81FPPfWU3nvvPfXs2VOFChVKM71y5co6fvy4Tpw4YbuqtHfvXl24cEGVKlXK8vd4enoqKSnJrmzjxo1q2LCh+vfvbys7fPhwtuIH7mqenhKdmSCH0OsdACDPio+PV1RUlKKiovTHH39owIABunTpkjp16pRu/eeee0779u3TiBEjdODAAS1YsMD2zqH0rgKlp1KlSvrnn3/SdBWe6oEHHlD16tX12GOPaceOHfrll1/Uu3dvNW3aVHXq1MnyupUqVUo///yzjh49qn/++UfJyckqW7astm3bphUrVujAgQN6/fXXtXXr1iwvEwCQc/JMohQeHi6LxWL38j1jjMaMGaPg4GB5e3urWbNm2rNnj/OCBADcVsuXL1dQUJCCgoJUr149bd26VV9//bWaNWuWbv2wsDB98803WrhwoapXr65p06bptddek5TS1XhWFS5cWN4Z3EJosVi0aNEiFSpUSE2aNNEDDzyg0qVLa/78+dlat2HDhsnNzU2VK1dW0aJFdfz4cT3//PPq1q2bevbsqXr16uns2bN2V5cA3IAx115LkI3bboH0WEx2bt7OJVu3blWPHj1UoEABNW/eXFOmTJEkvfvuu3rnnXc0c+ZMlS9fXm+//bY2bNig/fv32z0gm5mYmBj5+/vrwoULKlCgQC6uRd5Ar3cArhcXF6cjR44oLCxMXl5ezg7HKd555x1Nnz7d7v1IdzP2Cbi02Nhrrz7YuDFHn5mEa8hObuD0K0qXLl3SY489pk8//dTuXnBjjKZMmaLXXntN3bp1U9WqVTVr1ixduXJFc+fOdWLEAIC87KOPPtLWrVv1559/6osvvtDEiRPVp08fZ4cFALjDOD1RevHFF9WhQwc98MADduVHjhxRVFSUWrdubSuzWq1q2rSpNm3alOHy4uPjFRMTYzcAAO4eBw8eVOfOnVW5cmW99dZbevnllzWGh7sBANnk1F7v5s2bpx07dqT7oGpUVJSklDelX6948eI6duxYhssMDw+3e1kfAODu8v777+v99993dhgAgDuc064onThxQoMGDdKXX36Z6T3S6b0PI7Oei0aNGqULFy7YBu5JBwAAAJBdTruitH37dkVHR6t27dq2sqSkJG3YsEEffvih9u/fLynlylJQUJCtTnR0dJqrTNezWq3Z6tkIAO4GeaDfHuQR7AsAkDVOu6LUsmVL/fbbb9q5c6dtqFOnjh577DHt3LlTpUuXVmBgoFatWmWbJyEhQZGRkWrYsKGzwgaAO4qHh4ck6cqVK06OBHlF6r6Qum8AANLntCtKfn5+qlq1ql2Zr6+vChcubCsfPHiwxo0bp3LlyqlcuXIaN26cfHx89OijjzojZAC447i5ualgwYKKjo6WJPn4+GT5xatwLcYYXblyRdHR0SpYsKDc3NycHRKQ89zcpJYtr40Dt8CpnTncyPDhwxUbG6v+/fvr3LlzqlevnlauXJnldygBAKTAwEBJsiVLuLsVLFjQtk8ALsfTU3r3XWdHAReRJ144m5t44WzO4YWzwJ0tKSlJV69edXYYcCIPDw+uJAG4q2UnN8jTV5QAADnHzc2NP5IBAMgip79wFgAAAMgRsbFSnTopQ2yss6PBHY5ECQAAAAAckCgBAAAAgAMSJQAAAABwQKIEAAAAAA5IlAAAAADAAYkSAAAAADjgPUoAAABwDW5uUqNG18aBW0CiBAAAANfg6SlNnersKOAiuPUOAAAAAByQKAEAAACAAxIlAAAAuIbYWOn++1OG2FhnR4M7HM8oAQAAwHXExTk7ArgIrigBAAAAgAMSJQAAAABwQKIEAAAAAA5IlAAAAADAAYkSAAAAADig1zsAAAC4hnz5pHvvvTYO3AISJQAAALgGq1X65BNnRwEXQaoNAAAAAA5IlAAAAADAAYkSAAAAXENsrPTAAylDbKyzo8EdjmeUAAAA4DrOn3d2BHARXFECAAAAAAckSgAAAADggEQJAAAAAByQKAEAAACAAxIlAAAAAHBAr3cAAABwDfnySZUrXxsHbgGJEgAAAFyD1SrNnu3sKOAiSLUBAAAAwAGJEgAAAAA4cGqiNG3aNFWvXl0FChRQgQIF1KBBAy1btsw2vW/fvrJYLHZD/fr1nRgxAAAA8qy4OKlTp5QhLs7Z0eAO59RnlEqWLKnx48erbNmykqRZs2apc+fO+vXXX1WlShVJUtu2bRUREWGbx9PT0ymxAgAAII8zRjp9+to4cAucmih16tTJ7vM777yjadOmacuWLbZEyWq1KjAw0BnhAQAAALhL5ZlnlJKSkjRv3jxdvnxZDRo0sJWvX79exYoVU/ny5fXMM88oOjo60+XEx8crJibGbgAAAACA7HB6ovTbb78pf/78slqtev755/Xdd9+p8v/v/75du3aaM2eO1q5dq0mTJmnr1q1q0aKF4uPjM1xeeHi4/P39bUNISMjtWhUAAAAALsJijHNv4ExISNDx48d1/vx5ffvtt/rss88UGRlpS5aud/r0aYWGhmrevHnq1q1busuLj4+3S6RiYmIUEhKiCxcuqECBArm2HnlFqZFLc23ZR8d3yLVlAwAA3LLYWKlx45TxjRslb2/nxoM8JyYmRv7+/lnKDZz+wllPT09bZw516tTR1q1bNXXqVH388cdp6gYFBSk0NFQHDx7McHlWq1VWqzXX4gUAAADg+pyeKDkyxmR4a93Zs2d14sQJBQUF3eaoAAAAkOdZLFLp0tfGgVvg1ETp1VdfVbt27RQSEqKLFy9q3rx5Wr9+vZYvX65Lly5pzJgxeuihhxQUFKSjR4/q1VdfVZEiRdS1a1dnhg0AAIC8yMtLWrDA2VHARTg1Ufr777/1xBNP6PTp0/L391f16tW1fPlytWrVSrGxsfrtt980e/ZsnT9/XkFBQWrevLnmz58vPz8/Z4YNAAAAwMU5NVH6/PPPM5zm7e2tFStW3MZoAAAAACCF07sHBwAAAHJEXJzUo0fKEBfn7Ghwh8tznTkAAAAAN8UY6c8/r40Dt4BECVmWm+9oknhPEwAAAPIObr0DAAAAAAckSgAAAADggEQJAAAAAByQKAEAAACAAzpzAAAAgGuwWKSgoGvjwC0gUQIAAIBr8PKSvv/e2VHARXDrHQAAAAA4IFECAAAAAAckSgAAAHAN8fFS794pQ3y8s6PBHY5nlAAAAOAakpOlvXuvjQO3gCtKAAAAAOCARAkAAAAAHJAoAQAAAIADEiUAAAAAcECiBAAAAAAO6PUOAAAArqNgQWdHABdBogQAAADX4O0trV7t7CjgIrj1DgAAAAAckCgBAAAAgAMSJQAAALiG+Hjp2WdThvh4Z0eDOxzPKAEAAMA1JCdLO3ZcGwduAVeUAAAAAMABiRIAAAAAOCBRAgAAAAAHJEoAAAAA4IBECQAAAAAc0OsdAAAAXIeXl7MjgIsgUQIAAIBr8PaWfvzR2VHARXDrHQAAAAA4IFECAAAAAAckSgAAAHANCQnSoEEpQ0KCs6PBHc6pidK0adNUvXp1FShQQAUKFFCDBg20bNky23RjjMaMGaPg4GB5e3urWbNm2rNnjxMjBgAAQJ6VlCT99FPKkJTk7Ghwh3NqolSyZEmNHz9e27Zt07Zt29SiRQt17tzZlgxNmDBBkydP1ocffqitW7cqMDBQrVq10sWLF50ZNgAAAAAX59REqVOnTmrfvr3Kly+v8uXL65133lH+/Pm1ZcsWGWM0ZcoUvfbaa+rWrZuqVq2qWbNm6cqVK5o7d26Gy4yPj1dMTIzdAAAAAADZkWeeUUpKStK8efN0+fJlNWjQQEeOHFFUVJRat25tq2O1WtW0aVNt2rQpw+WEh4fL39/fNoSEhNyO8AEAAAC4EKcnSr/99pvy588vq9Wq559/Xt99950qV66sqKgoSVLx4sXt6hcvXtw2LT2jRo3ShQsXbMOJEydyNX4AAAAArsfpL5ytUKGCdu7cqfPnz+vbb79Vnz59FBkZaZtusVjs6htj0pRdz2q1ymq15lq8AAAAAFyf068oeXp6qmzZsqpTp47Cw8NVo0YNTZ06VYGBgZKU5upRdHR0mqtMAAAAAJCTnJ4oOTLGKD4+XmFhYQoMDNSqVats0xISEhQZGamGDRs6MUIAAADkSd7e0rZtKYO3t7OjwR3Oqbfevfrqq2rXrp1CQkJ08eJFzZs3T+vXr9fy5ctlsVg0ePBgjRs3TuXKlVO5cuU0btw4+fj46NFHH3Vm2AAAAABcnFMTpb///ltPPPGETp8+LX9/f1WvXl3Lly9Xq1atJEnDhw9XbGys+vfvr3PnzqlevXpauXKl/Pz8nBk2AAAAABdnMcYYZweRm2JiYuTv768LFy6oQIECzg4n15UaudTZIdy0o+M7ODsEAABwJ0tIkF5/PWX8rbckT0/nxoM8Jzu5QZ57RgkAAAC4KUlJ0po1KUNSkrOjwR2ORAkAAAAAHJAoAQAAAIADEiUAAAAAcECiBAAAAAAOSJQAAAAAwAGJEgAAAAA4cOoLZwEAAIAc4+Ulbdx4bRy4BSRKAAAAcA0Wi+Tt7ewo4CK49Q4AAAAAHHBFCQAAAK4hIUEaNy5l/NVXJU9P58aDOxpXlAAAAOAakpKkJUtShqQkZ0eDOxyJEgAAAAA4IFECAAAAAAckSgAAAADggEQJAAAAAByQKAEAAACAAxIlAAAAAHDAe5QAAADgGry8pFWrro0Dt4BECQAAAK7BYpEKFXJ2FHAR3HoHAAAAAA64ogQAAADXkJAgvf9+yviQIZKnp3PjwR2NK0oAAABwDUlJ0tdfpwxJSc6OBnc4EiUAAAAAcECiBAAAAAAOSJQAAAAAwAGJEgAAAAA4IFECAAAAAAd0D467QqmRS3N1+UfHd8jV5QMAAOD2IlECAACAa7BapcWLr40Dt4BECQAAAK4hXz4pONjZUcBF8IwSAAAAADjgihIAAABcw9Wr0kcfpYz37y95eDg3HtzRnHpFKTw8XPfdd5/8/PxUrFgxdenSRfv377er07dvX1ksFruhfv36TooYAAAAeVZiovTFFylDYqKzo8EdzqmJUmRkpF588UVt2bJFq1atUmJiolq3bq3Lly/b1Wvbtq1Onz5tG3744QcnRQwAAADgbuDUW++WL19u9zkiIkLFihXT9u3b1aRJE1u51WpVYGDg7Q4PAAAAwF0q21eUjhw5khtxSJIuXLggSQoICLArX79+vYoVK6by5cvrmWeeUXR0dIbLiI+PV0xMjN0AAAAAANmR7USpbNmyat68ub788kvFxcXlWCDGGA0dOlT333+/qlataitv166d5syZo7Vr12rSpEnaunWrWrRoofj4+HSXEx4eLn9/f9sQEhKSYzECAAAAuDtkO1HatWuXatWqpZdfflmBgYF67rnn9Msvv9xyIC+99JJ2796tr776yq68Z8+e6tChg6pWrapOnTpp2bJlOnDggJYuXZruckaNGqULFy7YhhMnTtxybAAAAADuLtlOlKpWrarJkyfrr7/+UkREhKKionT//ferSpUqmjx5ss6cOZPtIAYMGKDFixdr3bp1KlmyZKZ1g4KCFBoaqoMHD6Y73Wq1qkCBAnYDAAAAAGTHTfd65+7urq5du2rBggV69913dfjwYQ0bNkwlS5ZU7969dfr06Rsuwxijl156SQsXLtTatWsVFhZ2w3nOnj2rEydOKCgo6GZDBwAAgCuyWqUFC1IGq9XZ0eAOd9OJ0rZt29S/f38FBQVp8uTJGjZsmA4fPqy1a9fqr7/+UufOnW+4jBdffFFffvml5s6dKz8/P0VFRSkqKkqxsbGSpEuXLmnYsGHavHmzjh49qvXr16tTp04qUqSIunbterOhAwAAwBXlyyeVLp0y5HPqW3DgArLdPfjkyZMVERGh/fv3q3379po9e7bat2+vfP9/ZwwLC9PHH3+sihUr3nBZ06ZNkyQ1a9bMrjwiIkJ9+/aVm5ubfvvtN82ePVvnz59XUFCQmjdvrvnz58vPzy+7oQMAAABAlmQ7UZo2bZqeeuopPfnkkxm+2+iee+7R559/fsNlGWMyne7t7a0VK1ZkN0QAAADcja5elSIiUsaffFLy8HBuPLijZTtRyqgThet5enqqT58+NxUQAAAAcFMSE6VPPkkZf+IJEiXckmzfvBkREaGvv/46TfnXX3+tWbNm5UhQAAAAAOBM2U6Uxo8fryJFiqQpL1asmMaNG5cjQQEAAACAM2U7UTp27Fi63XiHhobq+PHjORIUAAAAADhTthOlYsWKaffu3WnKd+3apcKFC+dIUAAAAADgTNlOlB555BENHDhQ69atU1JSkpKSkrR27VoNGjRIjzzySG7ECAAAAAC3VbZ7vXv77bd17NgxtWzZUu7uKbMnJyerd+/ePKMEAAAAwCVkO1Hy9PTU/Pnz9dZbb2nXrl3y9vZWtWrVFBoamhvxAQAAAFljtUqzZ18bB25BthOlVOXLl1f58uVzMhYAAADg5uXLJ1Wu7Owo4CKynSglJSVp5syZWrNmjaKjo5WcnGw3fe3atTkWHAAAAAA4Q7YTpUGDBmnmzJnq0KGDqlatKovFkhtxAQAAANlz9ar01Vcp4716SR4ezo0Hd7RsJ0rz5s3TggUL1L59+9yIBwAAALg5iYnSf/+bMv7wwyRKuCXZ7h7c09NTZcuWzY1YAAAAACBPyHai9PLLL2vq1KkyxuRGPAAAAADgdNm+9e7HH3/UunXrtGzZMlWpUkUeDpc0Fy5cmGPBAQAAAIAzZDtRKliwoLp27ZobsQAAAABAnpDtRCkiIiI34gAAAACAPCPbzyhJUmJiolavXq2PP/5YFy9elCSdOnVKly5dytHgAAAAAMAZsn1F6dixY2rbtq2OHz+u+Ph4tWrVSn5+fpowYYLi4uI0ffr03IgTAAAAyJzVKn388bVx4BZk+4rSoEGDVKdOHZ07d07e3t628q5du2rNmjU5GhwAAACQZfnySbVrpwz5burGKcDmpnq9++mnn+Tp6WlXHhoaqr/++ivHAnNVpUYudXYIAAAAAG4g24lScnKykpKS0pSfPHlSfn5+ORIUAAAAkG2JiVLqq2q6dZPcs/2nLmCT7WuSrVq10pQpU2yfLRaLLl26pNGjR6t9+/Y5GRsAAACQdVevShMmpAxXrzo7Gtzhsp1mv//++2revLkqV66suLg4Pfroozp48KCKFCmir776KjdiBAAAAIDbKtuJUnBwsHbu3KmvvvpKO3bsUHJysvr166fHHnvMrnMHAAAAALhT3dSNm97e3nrqqaf01FNP5XQ8AAAAAOB02U6UZs+enen03r1733QwAAAAAJAXZDtRGjRokN3nq1ev6sqVK/L09JSPjw+JEgAAAIA7XrZ7vTt37pzdcOnSJe3fv1/3338/nTkAAAAAcAk50rl8uXLlNH78eD3++OPat29fTiwSAAAAyB5PTyn1NTaenk4NBXe+HHsLl5ubm06dOpVTiwMAAACyx81Nuv9+Z0cBF5HtRGnx4sV2n40xOn36tD788EM1atQoxwIDAAAAAGfJdqLUpUsXu88Wi0VFixZVixYtNGnSpJyKCwAAAMiexERp2bKU8XbtJPccu3kKd6Fs7z3Jycm5EQcAAABwa65elcaOTRl/4AESJdySbPd6l5PCw8N13333yc/PT8WKFVOXLl20f/9+uzrGGI0ZM0bBwcHy9vZWs2bNtGfPHidFDAAAAOBukO00e+jQoVmuO3ny5EynR0ZG6sUXX9R9992nxMREvfbaa2rdurX27t0rX19fSdKECRM0efJkzZw5U+XLl9fbb7+tVq1aaf/+/fLz88tu+AAAAABwQ9lOlH799Vft2LFDiYmJqlChgiTpwIEDcnNz07333murZ7FYbris5cuX232OiIhQsWLFtH37djVp0kTGGE2ZMkWvvfaaunXrJkmaNWuWihcvrrlz5+q5557LbvgAAAAAcEPZTpQ6deokPz8/zZo1S4UKFZKU8hLaJ598Uo0bN9bLL79808FcuHBBkhQQECBJOnLkiKKiotS6dWtbHavVqqZNm2rTpk3pJkrx8fGKj4+3fY6JibnpeAAAAADcnbL9jNKkSZMUHh5uS5IkqVChQnr77bdvqdc7Y4yGDh2q+++/X1WrVpUkRUVFSZKKFy9uV7d48eK2aY7Cw8Pl7+9vG0JCQm46JgAAAAB3p2wnSjExMfr777/TlEdHR+vixYs3HchLL72k3bt366uvvkozzfE2PmNMhrf2jRo1ShcuXLANJ06cuOmYAAAAANydsn3rXdeuXfXkk09q0qRJql+/viRpy5YteuWVV2zPEWXXgAEDtHjxYm3YsEElS5a0lQcGBkpKubIUFBRkK4+Ojk5zlSmV1WqV1Wq9qTgAAABwB/P0lMaPvzYO3IJsJ0rTp0/XsGHD9Pjjj+vq1aspC3F3V79+/TRx4sRsLcsYowEDBui7777T+vXrFRYWZjc9LCxMgYGBWrVqlWrVqiVJSkhIUGRkpN59993shg4AAABX5uaW8v4kIAdkO1Hy8fHRRx99pIkTJ+rw4cMyxqhs2bK27ryz48UXX9TcuXP1f//3f/Lz87M9d+Tv7y9vb29ZLBYNHjxY48aNU7ly5VSuXDmNGzdOPj4+evTRR7P9fQAAAACQFTf9uuLTp0/r9OnTatKkiby9vTN9bigj06ZNkyQ1a9bMrjwiIkJ9+/aVJA0fPlyxsbHq37+/zp07p3r16mnlypW8QwkAAAD2kpKkdetSxps3T7nCBNykbCdKZ8+eVY8ePbRu3TpZLBYdPHhQpUuX1tNPP62CBQtmq+c7Y8wN61gsFo0ZM0ZjxozJbqgAAAC4myQkSCNHpoxv3Ch5ezs3HtzRst3r3ZAhQ+Th4aHjx4/Lx8fHVt6zZ880L5AFAAAAgDtRtq8orVy5UitWrLDrnU6SypUrp2PHjuVYYAAAAADgLNm+onT58mW7K0mp/vnnH7rlBgAAAOASsp0oNWnSRLNnz7Z9tlgsSk5O1sSJE9W8efMcDQ4AAAAAnCHbt95NnDhRzZo107Zt25SQkKDhw4drz549+vfff/XTTz/lRowAAAAAcFtl+4pS5cqVtXv3btWtW1etWrXS5cuX1a1bN/36668qU6ZMbsQIAAAAALdVtq4oXb16Va1bt9bHH3+ssWPH5lZMAAAAQPZ5eEijR18bB25BthIlDw8P/f7779l+sSwAAACQ69zdpU6dnB0FXES2b73r3bu3Pv/889yIBQAAAADyhGx35pCQkKDPPvtMq1atUp06deTr62s3ffLkyTkWHAAAAJBlSUnS5s0p4w0aSG5uzo0Hd7QsJUq7d+9W1apVlS9fPv3++++69957JUkHDhywq8cteQAAAHCahARp8OCU8Y0bJW9vp4aDO1uWEqVatWrp9OnTKlasmI4dO6atW7eqcOHCuR0b7jKlRi51dggAAACApCw+o1SwYEEdOXJEknT06FElJyfnalAAAAAA4ExZuqL00EMPqWnTpgoKCpLFYlGdOnXklsE9n3/++WeOBggAAAAAt1uWEqVPPvlE3bp106FDhzRw4EA988wz8vPzy+3YAAAAAMApstzrXdu2bSVJ27dv16BBg0iUAAAAALisbHcPHhERkRtxAAAAAECeke1ECQAAAMiTPDyk4cOvjQO3gEQJAAAArsHdXerRw9lRwEVkqXtwAAAAALibcEUJAAAAriE5Wfr115TxWrWkfFwTwM0jUQIAAIBriI+XnnsuZXzjRsnb27nx4I5Gmg0AAAAADkiUAAAAAMABiRIAAAAAOCBRAgAAAAAHJEoAAAAA4IBECQAAAAAc0D04AAAAXIO7uzRw4LVx4BawBwF5XKmRS3N1+UfHd8jV5QMAcNt4eEi9ezs7CrgIbr0DAAAAAAdcUQIAAIBrSE6W9u1LGa9YUcrHNQHcPBIlAAAAuIb4+Gu33m3cKHl7Ozce3NFIswEAAADAgVMTpQ0bNqhTp04KDg6WxWLRokWL7Kb37dtXFovFbqhfv75zggUAAABw13BqonT58mXVqFFDH374YYZ12rZtq9OnT9uGH3744TZGCAAAAOBu5NRnlNq1a6d27dplWsdqtSowMPA2RQQAAAAAd8AzSuvXr1exYsVUvnx5PfPMM4qOjs60fnx8vGJiYuwGAAAAAMiOPJ0otWvXTnPmzNHatWs1adIkbd26VS1atFB8fHyG84SHh8vf3982hISE3MaIAQAAALiCPN09eM+ePW3jVatWVZ06dRQaGqqlS5eqW7du6c4zatQoDR061PY5JiaGZAkAAOBu4O4uPfvstXHgFtxRe1BQUJBCQ0N18ODBDOtYrVZZrdbbGBUAAADyBA+Pa4kScIvy9K13js6ePasTJ04oKCjI2aEAAAAAcGFOvaJ06dIlHTp0yPb5yJEj2rlzpwICAhQQEKAxY8booYceUlBQkI4ePapXX31VRYoUUdeuXZ0YNQAAAPKk5GTp6NGU8VKlpHx31DUB5DFOTZS2bdum5s2b2z6nPlvUp08fTZs2Tb/99ptmz56t8+fPKygoSM2bN9f8+fPl5+fnrJABAACQV8XHSz16pIxv3Ch5ezs3HtzRnJooNWvWTMaYDKevWLHiNkYDAAAAACm4HgkAAAAADkiUAAAAAMDBHdU9OJBXlRq51NkhAAAAIAdxRQkAAAAAHJAoAQAAAIADbr0DAACAa3B3l5544to4cAvYgwAAAOAaPDykQYOcHQVcBLfeAQAAAIADrigBAADANSQnS1FRKeOBgVI+rgng5pEoAQAAwDXEx0sPPpgyvnGj5O3t3HhwRyPNBgAAAAAHJEoAAAAA4IBECQAAAAAckCgBAAAAgAMSJQAAAABwQKIEAAAAAA7oHhwAAACuwc1Nevjha+PALSBRAgAAgGvw9JRGjHB2FHAR3HoHAAAAAA64ogTc5UqNXJpryz46vkOuLVu6s2MHAOQCY6Tz51PGCxaULBZnRoM7HIkSAAAAXENcnNSqVcr4xo2St7dz48EdjVvvAAAAAMABiRIAAAAAOCBRAgAAAAAHJEoAAAAA4IBECQAAAAAckCgBAAAAgAO6BwcAAIBrcHOTOna8Ng7cAhIlAAAAuAZPT2nMGGdHARfBrXcAAAAA4IArSgAAAHANxkhxcSnjXl6SxeLceHBH44oSAAAAXENcnNS4ccqQmjABN4lECQAAAAAcODVR2rBhgzp16qTg4GBZLBYtWrTIbroxRmPGjFFwcLC8vb3VrFkz7dmzxznBAgAAALhrODVRunz5smrUqKEPP/ww3ekTJkzQ5MmT9eGHH2rr1q0KDAxUq1atdPHixdscKQAAAIC7iVM7c2jXrp3atWuX7jRjjKZMmaLXXntN3bp1kyTNmjVLxYsX19y5c/Xcc8/dzlABAAAA3EXy7DNKR44cUVRUlFq3bm0rs1qtatq0qTZt2pThfPHx8YqJibEbAAAAACA78myiFBUVJUkqXry4XXnx4sVt09ITHh4uf39/2xASEpKrcQIAAABwPXk2UUplcej/3hiTpux6o0aN0oULF2zDiRMncjtEAAAA5AVublLLlimDm5uzo8EdLs++cDYwMFBSypWloKAgW3l0dHSaq0zXs1qtslqtuR4fAAAA8hhPT+ndd50dBVxEnr2iFBYWpsDAQK1atcpWlpCQoMjISDVs2NCJkQEAAABwdU69onTp0iUdOnTI9vnIkSPauXOnAgICdM8992jw4MEaN26cypUrp3LlymncuHHy8fHRo48+6sSoAQAAALg6pyZK27ZtU/PmzW2fhw4dKknq06ePZs6cqeHDhys2Nlb9+/fXuXPnVK9ePa1cuVJ+fn7OChkAAAB5VWys1LhxyvjGjZK3t3PjwR3NqYlSs2bNZIzJcLrFYtGYMWM0ZsyY2xcUAAAAgLtenn1GCQAAAACchUQJAAAAAByQKAEAAACAAxIlAAAAAHBAogQAAAAADpza6x0AAACQY9zcpEaNro0Dt4BECQAAAK7B01OaOtXZUcBFcOsdAAAAADggUQIAAAAAByRKAAAAcA2xsdL996cMsbHOjgZ3OJ5RAgAAgOuIi3N2BHARJEoAck2pkUudHcJNy+3Yj47vkKvLBwAAt4Zb7wAAAADAAYkSAAAAADggUQIAAAAAByRKAAAAAOCAzhwAAADgGvLlk+6999o4cAtIlAAAAOAarFbpk0+cHQVcBKk2AAAAADggUQIAAAAAByRKAAAAcA2xsdIDD6QMsbHOjgZ3OJ5RAgAAgOs4f97ZEcBFcEUJAAAAAByQKAEAAACAAxIlAAAAAHBAogQAAAAADkiUAAAAAMABvd4BAADANeTLJ1WufG0cuAUkSgAAAHANVqs0e7azo4CLIFECACcoNXJpri376PgOubZsAADuFlyTBAAAAAAHJEoAAABwDXFxUqdOKUNcnLOjwR2OW+8AAADgGoyRTp++Ng7cAq4oAQAAAICDPJ0ojRkzRhaLxW4IDAx0dlgAAAAAXFyev/WuSpUqWr16te2zm5ubE6MBAAAAcDfI84mSu7s7V5EAAAAA3FZ5+tY7STp48KCCg4MVFhamRx55RH/++Wem9ePj4xUTE2M3AAAAAEB25OlEqV69epo9e7ZWrFihTz/9VFFRUWrYsKHOnj2b4Tzh4eHy9/e3DSEhIbcxYgAAADiNxSKVLp0yWCzOjgZ3OIsxd07fiZcvX1aZMmU0fPhwDR06NN068fHxio+Pt32OiYlRSEiILly4oAIFCtyuUDNUauRSZ4cAwMUdHd/B2SEAAJAnxcTEyN/fP0u5QZ5/Rul6vr6+qlatmg4ePJhhHavVKqvVehujAgAAAOBq8vStd47i4+P1xx9/KCgoyNmhAAAAAHBheTpRGjZsmCIjI3XkyBH9/PPP6t69u2JiYtSnTx9nhwYAAIC8Ji5O6tEjZYiLc3Y0uMPl6VvvTp48qV69eumff/5R0aJFVb9+fW3ZskWhoaHODg0AAAB5jTFSag/Jd85j+Mij8nSiNG/ePGeHAAAAAOAulKdvvQMAAAAAZyBRAgAAAAAHJEoAAAAA4IBECQAAAAAc5OnOHAAAAIAss1ik1PdtWizOjQV3PBIlAAAAuAYvL+n7750dBVwEt94BAAAAgAMSJQAAAABwQKIEAAAA1xAfL/XunTLExzs7GtzheEYJAAAAriE5Wdq799o4cAu4ogQAAAAADriiBAAuptTIpbm6/KPjO+Tq8pEWbQoAtx9XlAAAAADAAYkSAAAAADggUQIAAAAABzyjBAAAANdRsKCzI4CLIFECAACAa/D2llavdnYUcBHcegcAAAAADkiUAAAAAMABiRIAAABcQ3y89OyzKUN8vLOjwR2OZ5QAAHkGL1ZFXnIn7493a+zWq/H6+vt1kqSH/ZYq3sOaU2FlSW6fY3KzXTk/psUVJQAAAABwQKIEAAAAAA5IlAAAAADAAYkSAAAAADggUQIAAAAAB/R6BwAAAJcR7+bp7BDgIkiUAAAA4BLiPax6+PEJzg4DLoJb7wAAAADAAVeUAADZktsvssxNd3LsuYmXWAI5404+x9zJLynOLSRKAAAAcAkeSVf16roZkqRxzZ/SVTcPJ0eEOxmJEgAAAFxCvuRk1f7rD9u43JwcEO5oPKMEAAAAAA5IlAAAAADAwR2RKH300UcKCwuTl5eXateurY0bNzo7JAAAAAAuLM8nSvPnz9fgwYP12muv6ddff1Xjxo3Vrl07HT9+3NmhAQAAAHBReT5Rmjx5svr166enn35alSpV0pQpUxQSEqJp06Y5OzQAAAAALipP93qXkJCg7du3a+TIkXblrVu31qZNm9KdJz4+XvHx8bbPFy5ckCTFxMTkXqDZkBx/xdkhAABw2+SV39+bkdu/2bm5be7W2JOuxutScnLKePwVJScn5VRYuEV55VyQGocx5oZ183Si9M8//ygpKUnFixe3Ky9evLiioqLSnSc8PFxjx45NUx4SEpIrMQIAgIz5T3F2BHnXnbxt8nLsjVJH/veEM8OAg7y2z1y8eFH+/v6Z1snTiVIqi8Vi99kYk6Ys1ahRozR06FDb5+TkZP37778qXLhwhvPktpiYGIWEhOjEiRMqUKCAU2KAPdok76FN8h7aJO+hTfIe2iTvoU3ynrzUJsYYXbx4UcHBwTesm6cTpSJFisjNzS3N1aPo6Og0V5lSWa1WWa1Wu7KCBQvmVojZUqBAAafvHLBHm+Q9tEneQ5vkPbRJ3kOb5D20Sd6TV9rkRleSUuXpzhw8PT1Vu3ZtrVq1yq581apVatiwoZOiAgAAAODq8vQVJUkaOnSonnjiCdWpU0cNGjTQJ598ouPHj+v55593dmgAAAAAXFSeT5R69uyps2fP6s0339Tp06dVtWpV/fDDDwoNDXV2aFlmtVo1evToNLcEwnlok7yHNsl7aJO8hzbJe2iTvIc2yXvu1DaxmKz0jQcAAAAAd5E8/YwSAAAAADgDiRIAAAAAOCBRAgAAAAAHJEoAAAAA4IBE6Tb46KOPFBYWJi8vL9WuXVsbN250dkguacOGDerUqZOCg4NlsVi0aNEiu+nGGI0ZM0bBwcHy9vZWs2bNtGfPHrs68fHxGjBggIoUKSJfX189+OCDOnny5G1cC9cSHh6u++67T35+fipWrJi6dOmi/fv329WhXW6vadOmqXr16raX/jVo0EDLli2zTac9nCs8PFwWi0WDBw+2ldEmt9+YMWNksVjshsDAQNt02sQ5/vrrLz3++OMqXLiwfHx8VLNmTW3fvt02nXa5vUqVKpXmOLFYLHrxxRcluUh7GOSqefPmGQ8PD/Ppp5+avXv3mkGDBhlfX19z7NgxZ4fmcn744Qfz2muvmW+//dZIMt99953d9PHjxxs/Pz/z7bffmt9++8307NnTBAUFmZiYGFud559/3pQoUcKsWrXK7NixwzRv3tzUqFHDJCYm3ua1cQ1t2rQxERER5vfffzc7d+40HTp0MPfcc4+5dOmSrQ7tcnstXrzYLF261Ozfv9/s37/fvPrqq8bDw8P8/vvvxhjaw5l++eUXU6pUKVO9enUzaNAgWzltcvuNHj3aVKlSxZw+fdo2REdH26bTJrffv//+a0JDQ03fvn3Nzz//bI4cOWJWr15tDh06ZKtDu9xe0dHRdsfIqlWrjCSzbt06Y4xrtAeJUi6rW7euef755+3KKlasaEaOHOmkiO4OjolScnKyCQwMNOPHj7eVxcXFGX9/fzN9+nRjjDHnz583Hh4eZt68ebY6f/31l8mXL59Zvnz5bYvdlUVHRxtJJjIy0hhDu+QVhQoVMp999hnt4UQXL1405cqVM6tWrTJNmza1JUq0iXOMHj3a1KhRI91ptIlzjBgxwtx///0ZTqddnG/QoEGmTJkyJjk52WXag1vvclFCQoK2b9+u1q1b25W3bt1amzZtclJUd6cjR44oKirKri2sVquaNm1qa4vt27fr6tWrdnWCg4NVtWpV2iuHXLhwQZIUEBAgiXZxtqSkJM2bN0+XL19WgwYNaA8nevHFF9WhQwc98MADduW0ifMcPHhQwcHBCgsL0yOPPKI///xTEm3iLIsXL1adOnX08MMPq1ixYqpVq5Y+/fRT23TaxbkSEhL05Zdf6qmnnpLFYnGZ9iBRykX//POPkpKSVLx4cbvy4sWLKyoqyklR3Z1St3dmbREVFSVPT08VKlQowzq4ecYYDR06VPfff7+qVq0qiXZxlt9++0358+eX1WrV888/r++++06VK1emPZxk3rx52rFjh8LDw9NMo02co169epo9e7ZWrFihTz/9VFFRUWrYsKHOnj1LmzjJn3/+qWnTpqlcuXJasWKFnn/+eQ0cOFCzZ8+WxLHibIsWLdL58+fVt29fSa7THu7ODuBuYLFY7D4bY9KU4fa4mbagvXLGSy+9pN27d+vHH39MM412ub0qVKignTt36vz58/r222/Vp08fRUZG2qbTHrfPiRMnNGjQIK1cuVJeXl4Z1qNNbq927drZxqtVq6YGDRqoTJkymjVrlurXry+JNrndkpOTVadOHY0bN06SVKtWLe3Zs0fTpk1T7969bfVoF+f4/PPP1a5dOwUHB9uV3+ntwRWlXFSkSBG5ubmlyYqjo6PTZNjIXam9FWXWFoGBgUpISNC5c+cyrIObM2DAAC1evFjr1q1TyZIlbeW0i3N4enqqbNmyqlOnjsLDw1WjRg1NnTqV9nCC7du3Kzo6WrVr15a7u7vc3d0VGRmp//73v3J3d7dtU9rEuXx9fVWtWjUdPHiQ48RJgoKCVLlyZbuySpUq6fjx45L4PXGmY8eOafXq1Xr66adtZa7SHiRKucjT01O1a9fWqlWr7MpXrVqlhg0bOimqu1NYWJgCAwPt2iIhIUGRkZG2tqhdu7Y8PDzs6pw+fVq///477XWTjDF66aWXtHDhQq1du1ZhYWF202mXvMEYo/j4eNrDCVq2bKnffvtNO3futA116tTRY489pp07d6p06dK0SR4QHx+vP/74Q0FBQRwnTtKoUaM0r5c4cOCAQkNDJfF74kwREREqVqyYOnToYCtzmfa43b1H3G1Suwf//PPPzd69e83gwYONr6+vOXr0qLNDczkXL140v/76q/n111+NJDN58mTz66+/2rpiHz9+vPH39zcLFy40v/32m+nVq1e63VSWLFnSrF692uzYscO0aNEiT3VTead54YUXjL+/v1m/fr1dF6JXrlyx1aFdbq9Ro0aZDRs2mCNHjpjdu3ebV1991eTLl8+sXLnSGEN75AXX93pnDG3iDC+//LJZv369+fPPP82WLVtMx44djZ+fn+23mza5/X755Rfj7u5u3nnnHXPw4EEzZ84c4+PjY7788ktbHdrl9ktKSjL33HOPGTFiRJpprtAeJEq3wf/+9z8TGhpqPD09zb333mvrGhk5a926dUZSmqFPnz7GmJSuQ0ePHm0CAwON1Wo1TZo0Mb/99pvdMmJjY81LL71kAgICjLe3t+nYsaM5fvy4E9bGNaTXHpJMRESErQ7tcns99dRTtvNR0aJFTcuWLW1JkjG0R17gmCjRJrdf6vtePDw8THBwsOnWrZvZs2ePbTpt4hzff/+9qVq1qrFaraZixYrmk08+sZtOu9x+K1asMJLM/v3700xzhfawGGOMUy5lAQAAAEAexTNKAAAAAOCARAkAAAAAHJAoAQAAAIADEiUAAAAAcECiBAAAAAAOSJQAAAAAwAGJEgAAAAA4IFECAAAAAAckSgCAWzZz5kwVLFgww+lHjx6VxWLRzp07b1tMruxG2/t2Wrt2rSpWrKjk5GRnh5Kh6OhoFS1aVH/99ZezQwFwByFRAnBX2bRpk9zc3NS2bVtnhwK4hOHDh+u1115Tvnx590+KYsWK6YknntDo0aOdHQqAO0jePasBQC6YMWOGBgwYoB9//FHHjx/PtK4xRomJibcpMudLSkrK01cFkHtudl/ftGmTDh48qIcffjgXokqRU8fhk08+qTlz5ujcuXM5EBWAuwGJEoC7xuXLl7VgwQK98MIL6tixo2bOnGk3ff369bJYLFqxYoXq1Kkjq9WqjRs3yhijCRMmqHTp0vL29laNGjX0zTff2OZLSkpSv379FBYWJm9vb1WoUEFTp069YTx79uxRhw4dVKBAAfn5+alx48Y6fPiwJCk5OVlvvvmmSpYsKavVqpo1a2r58uW2eRs0aKCRI0faLe/MmTPy8PDQunXrJEkJCQkaPny4SpQoIV9fX9WrV0/r16+31U+9fWvJkiWqXLmyrFarjh07dsP5Uue955575OPjo65du+rs2bNZaQLt27dPDRs2lJeXl6pUqWJbrjFGZcuW1XvvvWdX//fff1e+fPls28XR+vXrVbduXfn6+qpgwYJq1KiRjh07JkkaM2aMatasqS+++EKlSpWSv7+/HnnkEV28eNE2f3x8vAYOHKhixYrJy8tL999/v7Zu3WqbXrt2bU2aNMn2uUuXLnJ3d1dMTIwkKSoqShaLRfv37083vtQYZsyYoXvuuUf58+fXCy+8oKSkJE2YMEGBgYEqVqyY3nnnHbv5Jk+erGrVqsnX11chISHq37+/Ll26lOF2PXv2rOrWrasHH3xQcXFxN9xnM9rXd+3apebNm8vPz08FChRQ7dq1tW3btgy/d968eWrdurW8vLxsZYcPH1bnzp1VvHhx5c+fX/fdd59Wr15tN198fLyGDx+ukJAQWa1WlStXTp9//nmmsd1onc6dO6fHHntMRYsWlbe3t8qVK6eIiAjb9GrVqikwMFDfffddhusDAHYMANwlPv/8c1OnTh1jjDHff/+9KVWqlElOTrZNX7dunZFkqlevblauXGkOHTpk/vnnH/Pqq6+aihUrmuXLl5vDhw+biIgIY7Vazfr1640xxiQkJJg33njD/PLLL+bPP/80X375pfHx8THz58/PMJaTJ0+agIAA061bN7N161azf/9+M2PGDLNv3z5jjDGTJ082BQoUMF999ZXZt2+fGT58uPHw8DAHDhwwxhjzwQcfmHvuuccu/g8++MCUKFHCJCUlGWOMefTRR03Dhg3Nhg0bzKFDh8zEiRON1Wq1LSMiIsJ4eHiYhg0bmp9++sns27fPXLp06YbzbdmyxVgsFhMeHm72799vpk6dagoWLGj8/f0zXN8jR44YSaZkyZLmm2++MXv37jVPP/208fPzM//8848xxph33nnHVK5c2W6+IUOGmCZNmqS7zKtXrxp/f38zbNgwc+jQIbN3714zc+ZMc+zYMWOMMaNHjzb58+c33bp1M7/99pvZsGGDCQwMNK+++qptGQMHDjTBwcHmhx9+MHv27DF9+vQxhQoVMmfPnjXGGDN06FDTsWNHY4wxycnJJiAgwBQpUsQsXbrUGGPM3LlzTWBgYIbrnRpD9+7dzZ49e8zixYuNp6enadOmjRkwYIDZt2+fmTFjhpFkNm/ebJvv/fffN2vXrjV//vmnWbNmjalQoYJ54YUXbNMjIiJs2/vEiROmUqVK5oknnjBXr141xpgb7rMZ7etVqlQxjz/+uPnjjz/MgQMHzIIFC8zOnTszXL8aNWqY8ePH25Xt3LnTTJ8+3ezevdscOHDAvPbaa8bLy8vWLsYY06NHDxMSEmIWLlxoDh8+bFavXm3mzZuXaWw3WqcXX3zR1KxZ02zdutUcOXLErFq1yixevNguth49epi+fftmuD4AcD0SJQB3jYYNG5opU6YYY1L+yC5SpIhZtWqVbXrqH2iLFi2ylV26dMl4eXmZTZs22S2rX79+plevXhl+V//+/c1DDz2U4fRRo0aZsLAwk5CQkO704OBg884779iV3XfffaZ///7GGGOio6ONu7u72bBhg216gwYNzCuvvGKMMebQoUPGYrGYv/76y24ZLVu2NKNGjTLGpPyxLcnuD+GszNerVy/Ttm1bu+k9e/bMUqJ0/R/VV69eNSVLljTvvvuuMcaYU6dOGTc3N/Pzzz8bY1IS0KJFi5qZM2emu8yzZ88aSbY/lB2NHj3a+Pj4mJiYGFvZK6+8YurVq2eMSWlbDw8PM2fOHNv0hIQEExwcbCZMmGCMMWbx4sXG39/fJCUlmZ07d5qiRYuaIUOG2Lbzs88+a3r27JnheqcXQ5s2bUypUqVsCa0xxlSoUMGEh4dnuJwFCxaYwoUL2z6nJkr79+8399xzjxkwYIAtac7KPpvevm6MMX5+fhlu7/T4+/ub2bNn37Be5cqVzQcffGCMMWb//v1Gkt2xd72bPQ47depknnzyyUzjGDJkiGnWrNkN4wUAY4xxd851LAC4vfbv369ffvlFCxculCS5u7urZ8+emjFjhh544AG7unXq1LGN7927V3FxcWrVqpVdnYSEBNWqVcv2efr06frss8907NgxxcbGKiEhQTVr1swwnp07d6px48by8PBIMy0mJkanTp1So0aN7MobNWqkXbt2SZKKFi2qVq1aac6cOWrcuLGOHDmizZs3a9q0aZKkHTt2yBij8uXL2y0jPj5ehQsXtn329PRU9erVbZ+zMt8ff/yhrl272k1v0KCB3a2BGWnQoIFt3N3dXXXq1NEff/whSQoKClKHDh00Y8YM1a1bV0uWLFFcXFyGz78EBASob9++atOmjVq1aqUHHnhAPXr0UFBQkK1OqVKl5OfnZ/scFBSk6OhoSSm3iF29etVuO3t4eKhu3bq2mJo0aaKLFy/q119/1U8//aSmTZuqefPmevvttyWl3CY2ePDgTNfZMYbixYvLzc3NrvOD4sWL2+KSpHXr1mncuHHau3evYmJilJiYqLi4OF2+fFm+vr6SpNjYWN1///3q1auX3a2eWd1nJft9XZKGDh2qp59+Wl988YUeeOABPfzwwypTpkyG6xYbG2t3252Ucovr2LFjtWTJEp06dUqJiYmKjY21PRO4c+dOubm5qWnTpplut+wehy+88IIeeugh7dixQ61bt1aXLl3UsGFDu/re3t66cuVKpt8LAKlIlADcFT7//HMlJiaqRIkStjJjjDw8PHTu3DkVKlTIVp76h6gkW+cGS5cutZtXkqxWqyRpwYIFGjJkiCZNmqQGDRrIz89PEydO1M8//5xhPN7e3jeM2WKx2H02xtiVPfbYYxo0aJA++OADzZ07V1WqVFGNGjVscbu5uWn79u1yc3OzW07+/Pnt4rh+mVmZzxhzw9iz4/rvf/rpp/XEE0/o/fffV0REhHr27CkfH58M542IiNDAgQO1fPlyzZ8/X//5z3+0atUq1a9fX5LSJKIWi8XWpqnrkdl29vf3V82aNbV+/Xpt2rRJLVq0UOPGjbVz504dPHhQBw4cULNmzTJdv/RiyCyuY8eOqX379nr++ef11ltvKSAgQD/++KP69eunq1ev2uaxWq164IEHtHTpUr3yyisqWbKkpKzts6mu39ellGeqHn30US1dulTLli3T6NGjNW/evDSJcaoiRYqk6RzhlVde0YoVK/Tee++pbNmy8vb2Vvfu3ZWQkCApa/u+Y2xZWad27drp2LFjWrp0qVavXq2WLVvqxRdftHvu7d9//1XRokWz9P0AQGcOAFxeYmKiZs+erUmTJmnnzp22YdeuXQoNDdWcOXMynDe1k4Pjx4+rbNmydkNISIgkaePGjWrYsKH69++vWrVqqWzZshl2PpCqevXq2rhxo90fvqkKFCig4OBg/fjjj3blmzZtUqVKlWyfu3Tpori4OC1fvlxz587V448/bptWq1YtJSUlKTo6Ok3cgYGBGcaVlfkqV66sLVu22M3n+Dkj19dLTEzU9u3bVbFiRVtZ+/bt5evrq2nTpmnZsmV66qmnbrjMWrVqadSoUdq0aZOqVq2quXPnZimWsmXLytPT0247X716Vdu2bbPbzs2aNdO6deu0YcMGNWvWTAULFlTlypX19ttvq1ixYnZ1c8K2bduUmJioSZMmqX79+ipfvrxOnTqVpl6+fPn0xRdfqHbt2mrRooWtTlb22cyUL19eQ4YM0cqVK9WtWze7DhEc1apVS3v37rUr27hxo/r27auuXbvaOlA4evSobXq1atWUnJysyMjILG6RrK9T0aJF1bdvX3355ZeaMmWKPvnkE7vl/P7772muqgFARriiBMDlLVmyROfOnVO/fv3k7+9vN6179+76/PPP9dJLL6U7r5+fn4YNG6YhQ4YoOTlZ999/v2JiYrRp0yblz59fffr0UdmyZTV79mytWLFCYWFh+uKLL7R161aFhYVlGNNLL72kDz74QI888ohGjRolf39/bdmyRXXr1lWFChX0yiuvaPTo0SpTpoxq1qypiIgI7dy50y6p8/X1VefOnfX666/rjz/+0KOPPmqbVr58eT322GPq3bu3Jk2apFq1aumff/7R2rVrVa1aNbVv3z7duLIy38CBA9WwYUNNmDBBXbp00cqVK7N0250k/e9//1O5cuVUqVIlvf/++zp37pxdMuTm5qa+fftq1KhRKlu2rN2teo6OHDmiTz75RA8++KCCg4O1f/9+HThwQL17985SLL6+vnrhhRf0yiuvKCAgQPfcc48mTJigK1euqF+/frZ6zZo109SpUxUQEKDKlSvbyj744AN169YtS9+VHWXKlFFiYqI++OADderUST/99JOmT5+ebl03NzfNmTNHvXr1UosWLbR+/XoFBgbecJ9NT2xsrF555RV1795dYWFhOnnypLZu3aqHHnoow1jbtGmjWbNm2ZWVLVtWCxcuVKdOnWSxWPT666/bdTtfqlQp9enTR0899ZT++9//qkaNGjp27Jiio6PVo0ePdL8nK8fhG2+8odq1a6tKlSqKj4/XkiVL7JLYK1euaPv27Ro3blyG6wMAdpz4fBQA3BYdO3Y07du3T3fa9u3bjSSzfft220Pk586ds6uTnJxspk6daipUqGA8PDxM0aJFTZs2bUxkZKQxxpi4uDjTt29f4+/vbwoWLGheeOEFM3LkSFOjRo1M49q1a5dp3bq18fHxMX5+fqZx48bm8OHDxhhjkpKSzNixY02JEiWMh4eHqVGjhlm2bFmaZSxdutRISrdnuNTe+EqVKmU8PDxMYGCg6dq1q9m9e7cxxr7ntOzMZ0xKD4IlS5Y03t7eplOnTua9997LUmcOc+fONfXq1TOenp6mUqVKZs2aNWnqHj582EiydaiQkaioKNOlSxcTFBRkPD09TWhoqHnjjTdsnSSMHj06TRu8//77JjQ01PY5NjbWDBgwwBQpUsRYrVbTqFEj88svv9jNc/78eePm5ma6d+9uK/vuu++MJPPhhx9mGmN6MfTp08d07tzZrqxp06Zm0KBBts+TJ082QUFBxtvb27Rp08bMnj3bbt90bLurV6+abt26mUqVKpm///77hvtsevt6fHy8eeSRR0xISIjx9PQ0wcHB5qWXXjKxsbEZrt+///5rvL29bb01GpPS1s2bNzfe3t4mJCTEfPjhh2nWLzY21gwZMsTWdmXLljUzZszIMDZjbnwcvvXWW6ZSpUrG29vbBAQEmM6dO5s///zTNv/cuXNNhQoVMlwXAHBkMSaHbzYHAOAW/PTTT2rWrJlOnjyp4sWLOzsc3MDw4cN14cIFffzxx84OJVN169bV4MGD7a68AkBmeEYJAJAnxMfH69ChQ3r99dfVo0cPkqQ7xGuvvabQ0FAlJSU5O5QMRUdHq3v37urVq5ezQwFwB+GKEgAgT5g5c6b69eunmjVravHixWl6NwMA4HYiUQIAAAAAB9x6BwAAAAAOSJQAAAAAwAGJEgAAAAA4IFECAAAAAAckSgAAAADggEQJAAAAAByQKAEAAACAAxIlAAAAAHDw/wA4zxNQbDmuIwAAAABJRU5ErkJggg==\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot_compare('Snow Making_ac', 'Area covered by snow makers (acres)')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Big Mountain is very high up the league table of snow making area." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 5.8.4 Total number of chairs" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot_compare('total_chairs', 'Total number of chairs')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Big Mountain has amongst the highest number of total chairs, resorts with more appear to be outliers." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 5.8.5 Fast quads" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot_compare('fastQuads', 'Number of fast quads')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Most resorts have no fast quads. Big Mountain has 3, which puts it high up that league table. There are some values much higher, but they are rare." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 5.8.6 Runs" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot_compare('Runs', 'Total number of runs')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Big Mountain compares well for the number of runs. There are some resorts with more, but not many." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 5.8.7 Longest run" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAA0oAAAHUCAYAAAAEKdj3AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8o6BhiAAAACXBIWXMAAA9hAAAPYQGoP6dpAABc/0lEQVR4nO3deVxUZf//8ffIMqyCorKkCSnu+5poornllqal5Z5a9rVyy6+l1i12G5qmaV9vLbtLsTKXyrRMEzey1HK3zNRyTUHT3BcQOL8/+DE6AwijwEF6PR+P83icuc451/mchRk+c13nGothGIYAAAAAADZFzA4AAAAAAAoaEiUAAAAAcECiBAAAAAAOSJQAAAAAwAGJEgAAAAA4IFECAAAAAAckSgAAAADggEQJAAAAAByQKAEAAACAAxIl3DPmzZsni8Wibdu2mR1Knvv1118VFRWlI0eOmB1Kjm3YsEEWi0UbNmwwOxRJtz+HzZo1U7Vq1e6q/vPnz6tEiRJauHDhXdVzq8zOYVRUlCwWS67tw1HTpk01bNiwu6rjyJEjslgsmjdvnq3sTuK+evWqoqKinL6HMttXaGioOnTo4FQ92VmwYIGmT5+e6TKLxaKoqKhc3V9OLVq0SFWrVpWnp6csFot27dplShwFzaxZs+zuybuV2X1eGOT2Z2t0dLS+/PLLXKlL+md99qPgIVECCqBff/1V48ePv6cSpYImr8/h+PHjFRISou7du+danXXq1NHmzZtVp06dXKszO//+9781a9Ys7d+/P1frHThwoDZv3uzUNlevXtX48eOdTpTuZF934naJ0ubNmzVw4MA8j8HRX3/9pd69e6tcuXJatWqVNm/erAoVKuR7HAVRbidKwcHB2rx5s9q3b59rdRZGuZ0oAWZyNTsAAHnj6tWr8vLyMjuMQunvv//We++9p7fffjtXW3uKFi2qBx98MNfqy4nIyEhVrFhRU6dO1Zw5c3Kt3tKlS6t06dK5Vl9m0u/x/NhXdvL7uqU7cOCAbty4oV69eikyMjJX6nT2vePatWvy8PDI05ZPZ+TVe5/VajXtOueFGzduFJhrVhDwmYnM0KKEQuf7779XixYt5OvrKy8vL0VERGjFihV266Q35a9fv17/8z//oxIlSiggIEBdunTRyZMn7dZNTEzUSy+9pKCgIHl5ealp06bavn27QkND1a9fP7t1ExISNGjQIJUuXVru7u4KCwvT+PHjlZycbLfe7NmzVbNmTfn4+MjX11eVKlXSmDFjbLE98cQTkqTmzZvLYrFk290jvevRjh079Pjjj6tYsWIqV66cpLRuZs2aNcuwTb9+/RQaGmp7nd6t5K233tK0adMUFhYmHx8fNWrUSFu2bLndKb+tbdu26dFHH1Xx4sXl4eGh2rVra/HixXbr5Pb1yOk53Lp1qx566CF5eXnpgQce0KRJk5SamprtMc2bN0/JyckZWpP69esnHx8f/fbbb2rTpo28vb0VHBysSZMmSZK2bNmiJk2ayNvbWxUqVFBMTIzd9s50X1y0aJEaNWokb29v+fj4qE2bNtq5c6fdOocOHdKTTz6pkJAQWa1WBQYGqkWLFhm6ZvXu3VsLFizQpUuXst3vyZMn1a1bN/n6+srPz0/du3dXQkJChvUy6w63bt06NWvWTAEBAfL09NT999+vrl276urVqzpy5IhKliwpKa21Lv2apV/T293jt+vmt3TpUtWoUUMeHh564IEH9M4779gtT7/3HFseHa9Fs2bNtGLFCh09etQW2637zKzr3S+//KJOnTqpWLFi8vDwUK1atbK85p9++qnGjh2rkJAQFS1aVC1btsy2la9fv35q0qSJJKl79+6yWCx2f+vLly9Xo0aN5OXlJV9fX7Vq1SpDy9vtzmtm0s/X6tWr1b9/f5UsWVJeXl5KTEyUlHv3ZWpqqiZPnqxKlSrJarWqVKlS6tOnj/7880+7utK70X733XeKiIiQl5eX+vfvr9DQUO3du1dxcXG2a5X+fpeamqoJEyaoYsWK8vT0lL+/v2rUqKEZM2bc9nzfrovp3r179dRTT8nPz0+BgYHq37+/Lly4cNv6bo1/8+bNioiIkKenp0JDQzV37lxJ0ooVK1SnTh15eXmpevXqWrVqld32v//+u55++mmFh4fLy8tL9913nzp27Kiff/7Zbr30++yjjz7SSy+9pPvuu09Wq1W///57pnHFx8erbt26Cg8P18GDByVJFy9e1MiRIxUWFiZ3d3fdd999GjZsmK5cuWLbzmKx6MqVK4qJibGd98w+f251u8/DW126dCnbz4dFixapdevWCg4OlqenpypXrqxXXnnFLkbp5nv1zz//rNatW8vX11ctWrSQJCUlJWnChAm2e69kyZJ6+umn9ddff932OFA4kSihUImLi9PDDz+sCxcu6IMPPtCnn34qX19fdezYUYsWLcqw/sCBA+Xm5qYFCxZo8uTJ2rBhg3r16mW3ztNPP63p06fr6aef1rJly9S1a1c99thjOn/+vN16CQkJatCggb799lv961//0sqVKzVgwABNnDhRzzzzjG29hQsXavDgwYqMjNTSpUv15Zdfavjw4bY38vbt2ys6OlqS9J///EebN2/OcXePLl26qHz58lqyZIneffddZ0+fbZ+xsbGaPn26PvnkE125ckXt2rXL0Ye+o/Xr16tx48Y6f/683n33XS1btky1atVS9+7dM038cut65OQcJiQkqGfPnurVq5eWL1+utm3bavTo0fr444+zPa4VK1aodu3a8vf3z7Dsxo0b6tKli9q3b69ly5bZ6h0zZoz69u2r/v37a+nSpapYsaL69eun7du35+xk3iI6OlpPPfWUqlSposWLF+ujjz7SpUuX9NBDD+nXX3+1rdeuXTtt375dkydPVmxsrGbPnq3atWtnuHebNWumK1euZJugXbt2TS1bttTq1as1ceJELVmyREFBQTnqfnjkyBG1b99e7u7u+vDDD7Vq1SpNmjRJ3t7eSkpKUnBwsO2fwAEDBtiu2WuvvWZXjzP3+K5duzRs2DANHz5cS5cuVUREhIYOHaq33nor23gdzZo1S40bN1ZQUJAtttt199u/f78iIiK0d+9evfPOO/riiy9UpUoV9evXT5MnT86w/pgxY3T06FH997//1Zw5c3Tw4EF17NhRKSkpWe7jtdde03/+8x9JaffE5s2bNWvWLElp3QQ7deqkokWL6tNPP9UHH3ygc+fOqVmzZvr+++8z1OXse0f//v3l5uamjz76SJ999pnc3Nxy9b78n//5H7388stq1aqVli9frn//+99atWqVIiIidObMGbtY4uPj1atXL/Xo0UPffPONBg8erKVLl+qBBx5Q7dq1bddq6dKlkqTJkycrKipKTz31lFasWKFFixZpwIABGf4unNG1a1dVqFBBn3/+uV555RUtWLBAw4cPz9G2CQkJevrppzVw4EAtW7ZM1atXV//+/fX6669r9OjRGjVqlD7//HP5+Pioc+fOdsnByZMnFRAQoEmTJmnVqlX6z3/+I1dXVzVs2DDTRHv06NE6duyY3n33XX311VcqVapUhnV++eUXNWzYUFarVZs3b1Z4eLiuXr2qyMhIxcTEaMiQIVq5cqVefvllzZs3T48++qgMw5CU1gXV09NT7dq1s5339HsyM9l9Ht4qJ58PBw8eVLt27fTBBx9o1apVGjZsmBYvXqyOHTtmqC8pKUmPPvqoHn74YS1btkzjx49XamqqOnXqpEmTJqlHjx5asWKFJk2apNjYWDVr1kzXrl3L+kKicDKAe8TcuXMNScbWrVuzXOfBBx80SpUqZVy6dMlWlpycbFSrVs0oXbq0kZqaalfX4MGD7bafPHmyIcmIj483DMMw9u7da0gyXn75Zbv1Pv30U0OS0bdvX1vZoEGDDB8fH+Po0aN267711luGJGPv3r2GYRjGCy+8YPj7+9/2WJcsWWJIMtavX3/b9dKNGzfOkGT861//yrAsMjLSiIyMzFDet29fo2zZsrbXhw8fNiQZ1atXN5KTk23lP/30kyHJ+PTTT28bw/r16zPEXKlSJaN27drGjRs37Nbt0KGDERwcbKSkpBiGkTfX43bnMDIy0pBk/Pjjj3blVapUMdq0aXPb4zQMw/Dy8jKee+65DOV9+/Y1JBmff/65rezGjRtGyZIlDUnGjh07bOVnz541XFxcjBEjRtjKMjuH6dc23bFjxwxXV1fjxRdftNv3pUuXjKCgIKNbt26GYRjGmTNnDEnG9OnTsz2epKQkw2KxZDivjmbPnm1IMpYtW2ZX/swzzxiSjLlz52YZ92effWZIMnbt2pVl/X/99ZchyRg3blyGZbe7xx33ZRiGUbZsWcNisWTYX6tWrYyiRYsaV65cMQzj5r13+PBhu/Uyuxbt27e3+5u5lWPcTz75pGG1Wo1jx47Zrde2bVvDy8vLOH/+vN1+2rVrZ7fe4sWLDUnG5s2bM92fY5xLliyxlaWkpBghISFG9erVbX9jhpF2j5QqVcqIiIiwld3uvGYm/Xz16dPHrjw378t9+/Zl+n7w448/GpKMMWPG2MrS/5bXrl2boZ6qVatm+t7XoUMHo1atWtkeq6P098jM7vPJkyfbrTt48GDDw8PD9pmTlfT4t23bZitLf2/w9PQ0Tpw4YSvftWuXIcl45513sqwvOTnZSEpKMsLDw43hw4fbytPvk6ZNm2bY5tbP1tjYWKNo0aLG448/bly7ds22zsSJE40iRYpk+PxN/7v+5ptvbGXe3t5278W3k5PPw5x+PjhKTU01bty4YcTFxRmSjN27d9uWpb9Xf/jhh3bbpH+W3PoebhiGsXXrVkOSMWvWrBwdFwoPWpRQaFy5ckU//vijHn/8cfn4+NjKXVxc1Lt3b/35558ZvmF79NFH7V7XqFFDknT06FFJaS1UktStWze79R5//HG5uto/4vf111+refPmCgkJUXJysm1q27atXV0NGjTQ+fPn9dRTT2nZsmUZvh29G127dr3rOtq3by8XFxfba8dzklO///67fvvtN/Xs2VOS7M5Ju3btFB8fn6fXIztBQUFq0KBBhv1ld5znz5/X1atXM/0mVkrretKuXTvba1dXV5UvX17BwcGqXbu2rbx48eIqVaqU0+f122+/VXJysvr06WN3Tj08PBQZGWlrFSpevLjKlSunKVOmaNq0adq5c2eW3Qrd3Nzk7++vEydO3Hbf69evl6+vb4br1KNHj2zjrlWrltzd3fXss88qJiZGhw4dytkBO3DmHq9atapq1qxpV9ajRw9dvHhRO3bsuKP959S6devUokULlSlTxq68X79+unr1aobWqOzufWfs379fJ0+eVO/evVWkyM2PeR8fH3Xt2lVbtmzR1atX7bZx9r3Dcf3cvC/Xr18vSRm6Njdo0ECVK1fW2rVr7cqLFSumhx9+OMexN2jQQLt379bgwYP17bff6uLFizneNiuZXb/r16/r9OnT2W4bHBysunXr2l6nvzfUqlVLISEhtvLKlStLsr8nkpOTFR0drSpVqsjd3V2urq5yd3fXwYMHtW/fvgz7ut11jomJUbt27TRw4EAtXrxYHh4etmVff/21qlWrplq1atld3zZt2tzVaKfOfB7m5G/k0KFD6tGjh4KCguTi4iI3Nzfbs3s5OR9ff/21/P391bFjR7vjrFWrloKCggrMqK7IPyRKKDTOnTsnwzAUHBycYVn6h83Zs2ftygMCAuxeW61WSbI1r6evHxgYaLeeq6trhm1PnTqlr776Sm5ubnZT1apVJcn2AdC7d299+OGHOnr0qLp27apSpUqpYcOGio2NvaPjvlVmx+6s7M5JTp06dUqSNHLkyAznZPDgwZKU4UMxN69HdjJb32q1Znuc6ctv/SfiVl5eXhmWubu7q3jx4hnWdXd31/Xr13MasqSb57V+/foZzuuiRYts59RisWjt2rVq06aNJk+erDp16qhkyZIaMmRIps8ieXh4ZHvsZ8+ezXDupbSkMzvlypXTmjVrVKpUKT3//PMqV66cypUrl+1zIY6cuccziyu9zPG9ILedPXs2V9+LnN23lPm5CgkJUWpqqs6dO2dX7ux7h+P6uXlfZhe/47lzNvbRo0frrbfe0pYtW9S2bVsFBASoRYsWdzX89N1cv6zeGxzL3d3dJcnuPWPEiBF67bXX1LlzZ3311Vf68ccftXXrVtWsWTPTfd/uXC1cuFCenp4aOHBghmf+Tp06pT179mS4tr6+vjIM446/8HPm8zC7c3z58mU99NBD+vHHHzVhwgRt2LBBW7du1RdffGG3XjovLy8VLVo0w3GeP39e7u7uGY41ISEhV7/YxL2BUe9QaBQrVkxFihRRfHx8hmXpfbpLlCjhVJ3pb8ynTp3SfffdZytPTk7O8GFdokQJ1ahRQ2+88Uamdd36zeDTTz+tp59+WleuXNF3332ncePGqUOHDjpw4IDKli3rVIy3yuyBdg8Pj0yfL8rrN/z0cz169Gh16dIl03UqVqzoVJ3OXI+8kh7D33//nS/7c5R+Xj/77LNs75WyZcvqgw8+kJQ2OtrixYsVFRWlpKSkDM+hnDt3Ltu/j4CAAP30008ZyjMbzCEzDz30kB566CGlpKRo27Zt+r//+z8NGzZMgYGBevLJJ3NUhzOjdGUWV3pZ+nVMT2rTByNId7d/HwEBAbn6XuTsviVluf8iRYqoWLFiduXOjn7muH5u3pe3xu84muHJkycznDtnY3d1ddWIESM0YsQInT9/XmvWrNGYMWPUpk0bHT9+/J4a+ezjjz9Wnz59bM9kpjtz5kymz1De7lx98skneu211xQZGanVq1erVq1atmUlSpSQp6enPvzww0y3vZv7Obc+D9etW6eTJ09qw4YNdiNAZvXsWWbnIn2gCMdBM9L5+vrmOB4UDiRKKDS8vb3VsGFDffHFF3rrrbfk6ekpKW2Eo48//lilS5d2+vdFmjZtKiltJJ1bf9vms88+yzCSXYcOHfTNN9+oXLlyGf4JuV3Mbdu2VVJSkjp37qy9e/eqbNmyd/VtsqPQ0FAtWbJEiYmJtnrPnj2rTZs2Zfg2LTdVrFhR4eHh2r17d4YP8TvlzPXIzXN4K3d3dz3wwAP6448/crXenGrTpo1cXV31xx9/ONVdqkKFCnr11Vf1+eefZ+h2dvLkSV2/fl1VqlS5bR3NmzfX4sWLtXz5crtuMAsWLHDqGFxcXNSwYUNVqlRJn3zyiXbs2KEnn3wy16/Z3r17tXv3brvudwsWLJCvr6/t/kkfCW3Pnj12ifvy5csz1JeTFsd0LVq00NKlS3Xy5Em7L0nmz58vLy+vPB1mumLFirrvvvu0YMECjRw50vYP4ZUrV/T555/bRsLLTbl5X6Z3o/v4449Vv35927pbt27Vvn37NHbs2BzVnZPr5e/vr8cff1wnTpzQsGHDdOTIkWz/DgoSi8Vi+7tJt2LFCp04cULly5d3qq7ixYtrzZo16tChg5o3b66VK1fa7tMOHTooOjpaAQEBCgsLu209zvyd3Cqrz8OcSr/PHc/He++9l+M6OnTooIULFyolJUUNGzbM8XYovEiUcM9Zt25dpj8i2q5dO02cOFGtWrVS8+bNNXLkSLm7u2vWrFn65Zdf9Omnnzr9zWPVqlX11FNPaerUqXJxcdHDDz+svXv3aurUqfLz87Pr///6668rNjZWERERGjJkiCpWrKjr16/ryJEj+uabb/Tuu++qdOnSeuaZZ+Tp6anGjRsrODhYCQkJmjhxovz8/Gz/FFSrVk2SNGfOHPn6+srDw0NhYWFOdy+T0ro2vPfee+rVq5eeeeYZnT17VpMnT87TJCnde++9p7Zt26pNmzbq16+f7rvvPv3999/at2+fduzYoSVLljhVnzPXIzfPoaNmzZpp5cqVd13PnQgNDdXrr7+usWPH6tChQ3rkkUdUrFgxnTp1Sj/99JO8vb01fvx47dmzRy+88IKeeOIJhYeHy93dXevWrdOePXv0yiuv2NWZPvx78+bNb7vvPn366O2331afPn30xhtvKDw8XN98842+/fbbbON+9913tW7dOrVv317333+/rl+/bvt2umXLlpLSvq0tW7asli1bphYtWqh48eIqUaKE3TD2zggJCdGjjz6qqKgoBQcH6+OPP1ZsbKzefPNNW6JQv359VaxYUSNHjlRycrKKFSumpUuXZjoyXPXq1fXFF19o9uzZqlu3rooUKaJ69epluu9x48bZnlv817/+peLFi+uTTz7RihUrNHnyZPn5+d3RMeVEkSJFNHnyZPXs2VMdOnTQoEGDlJiYqClTpuj8+fO24epzU27elxUrVtSzzz6r//u//1ORIkXUtm1bHTlyRK+99prKlCmT49HkqlevroULF2rRokV64IEH5OHhoerVq6tjx46qVq2a6tWrp5IlS+ro0aOaPn26ypYtq/Dw8Fw/N3mpQ4cOmjdvnipVqqQaNWpo+/btmjJlyh3/rpivr69WrVqlLl262EYcbN68uYYNG6bPP/9cTZs21fDhw1WjRg2lpqbq2LFjWr16tV566SVbYlG9enVt2LBBX331lYKDg+Xr65tl74GcfB7mVEREhIoVK6bnnntO48aNk5ubmz755BPt3r07x3U8+eST+uSTT9SuXTsNHTpUDRo0kJubm/7880+tX79enTp10mOPPeZUXLjHmT2aBJBT6SPfZDWlj1q1ceNG4+GHHza8vb0NT09P48EHHzS++uqrTOtyHMEns5Gurl+/bowYMcIoVaqU4eHhYTz44IPG5s2bDT8/P7tRhQwjbdSuIUOGGGFhYYabm5tRvHhxo27dusbYsWONy5cvG4ZhGDExMUbz5s2NwMBAw93d3QgJCTG6detm7Nmzx66u6dOnG2FhYYaLi0uGkZYcpY+89Ndff2W6PCYmxqhcubLh4eFhVKlSxVi0aFGWo95NmTIlw/bKYiSy7M6dYRjG7t27jW7duhmlSpUy3NzcjKCgIOPhhx823n33Xds6eXU9sjqHkZGRRtWqVTMcg+M5ycratWsNScZPP/2UYXtvb+8M62e1v7Jlyxrt27e/7fFmNqKbYRjGl19+aTRv3twoWrSoYbVajbJlyxqPP/64sWbNGsMwDOPUqVNGv379jEqVKhne3t6Gj4+PUaNGDePtt9+2G9XQMAyjd+/eRvXq1bM9bsMwjD///NPo2rWr4ePjY/j6+hpdu3Y1Nm3alO2od5s3bzYee+wxo2zZsobVajUCAgKMyMhIY/ny5Xb1r1mzxqhdu7ZhtVrtRjK83T2e1ah37du3Nz777DOjatWqhru7uxEaGmpMmzYtw/YHDhwwWrdubRQtWtQoWbKk8eKLLxorVqzIcC3+/vtv4/HHHzf8/f0Ni8Vit8/M/kZ+/vlno2PHjoafn5/h7u5u1KxZM8PfcWaj1hlG5iOsZSar7Q0j7R5p2LCh4eHhYXh7exstWrQwfvjhB7t1snvvcJTd6KO5dV+mpKQYb775plGhQgXDzc3NKFGihNGrVy/j+PHjdvvL6m/LMAzjyJEjRuvWrQ1fX19Dku1ve+rUqUZERIRRokQJw93d3bj//vuNAQMGGEeOHLntsd9u1DvH85fVaIqOcvrekE6S8fzzz9tenzt3zhgwYIBRqlQpw8vLy2jSpImxcePGDKOd3u4+yeyaJiYmGl27djU8PDyMFStWGIZhGJcvXzZeffVVo2LFioa7u7vh5+dnVK9e3Rg+fLiRkJBg23bXrl1G48aNDS8vL0NSpiMPpsvJ56Eznw+bNm0yGjVqZHh5eRklS5Y0Bg4caOzYsSPDdcvqvdow0kYqfeutt4yaNWsaHh4eho+Pj1GpUiVj0KBBxsGDB7M8FhROFsP4/4PfA8ixTZs2qXHjxvrkk09yNOIX8pYZ16NGjRpq3LixZs+enS/7yysXL15USEiI3n77bbvf+wIA4J+ORAnIRmxsrDZv3qy6devK09NTu3fv1qRJk+Tn56c9e/ZkOfoZ8kZBuR6rVq3SY489poMHD95xN5eCYPz48Vq0aJH27Nnj9BDrAAAUZnwqAtkoWrSoVq9erenTp+vSpUsqUaKE2rZtq4kTJ5IkmaCgXI9HHnlEU6ZM0eHDh+/pRKlo0aKaN28eSRIAAA5oUQIAAAAAB/zgLAAAAAA4IFECAAAAAAckSgAAAADgoNA/vZuamqqTJ0/K19fX6R8bBQAAAFB4GIahS5cuKSQkxO6H6jNT6BOlkydPqkyZMmaHAQAAAKCAOH78eLaj1hb6RMnX11dS2skoWrSoydEAAP7xUlOlU6fS5gMDpWy+0QQA5J6LFy+qTJkythzhdgp9opTe3a5o0aIkSgAA8127JvXsmTa/caPk6WluPADwD5STR3L4GgsAAAAAHJAoAQAAAIADEiUAAAAAcFDon1ECAABA4WcYhpKTk5WSkmJ2KDCRi4uLXF1dc+VngUiUAAAAcE9LSkpSfHy8rl69anYoKAC8vLwUHBwsd3f3u6qHRAkAAAD3rNTUVB0+fFguLi4KCQmRu7t7rrQm4N5jGIaSkpL0119/6fDhwwoPD8/2R2Vvh0QJAID85OIiPfHEzXkAdyUpKUmpqakqU6aMvLy8zA4HJvP09JSbm5uOHj2qpKQkeXh43HFdJEoAAOQnd3fp5ZfNjgIodO6m5QCFS27dC9xRAAAAAOCAFiUAAPKTYUjnz6fN+/tLPEsBAAUSLUoAAOSn69elVq3SpuvXzY4GQAF35MgRWSwW7dq1y+xQ8k2/fv3UuXNns8MwP1E6ceKEevXqpYCAAHl5ealWrVravn27bblhGIqKilJISIg8PT3VrFkz7d2718SIAQAAgLvXr18/WSwW2xQQEKBHHnlEe/bssa1TpkwZxcfHq1q1ane1r9DQUFksFi1cuDDDsqpVq8pisWjevHl3tQ9HzZo107Bhw5zebsaMGbkey50wNVE6d+6cGjduLDc3N61cuVK//vqrpk6dKn9/f9s6kydP1rRp0zRz5kxt3bpVQUFBatWqlS5dumRe4AAAAEAueOSRRxQfH6/4+HitXbtWrq6u6tChg225i4uLgoKC5Op690/MlClTRnPnzrUr27JlixISEuTt7X3X9ecWPz8/u3zALKYmSm+++abtgjVo0EChoaFq0aKFypUrJymtNWn69OkaO3asunTpomrVqikmJkZXr17VggULzAwdAAAABd21a1lPSUk5XzcxMWfr3gGr1aqgoCAFBQWpVq1aevnll3X8+HH99ddfkjLverd8+XKFh4fL09NTzZs3V0xMjCwWi86nP/+YhZ49eyouLk7Hjx+3lX344Yfq2bNnhkTs2LFj6tSpk3x8fFS0aFF169ZNp06dsi2PiopSrVq19NFHHyk0NFR+fn568sknbY0Z/fr1U1xcnGbMmGFrMTty5IhSUlI0YMAAhYWFydPTUxUrVtSMGTPs9u3Y9a5Zs2YaMmSIRo0apeLFiysoKEhRUVFOnOU7Y+pgDsuXL1ebNm30xBNPKC4uTvfdd58GDx6sZ555RpJ0+PBhJSQkqHXr1rZtrFarIiMjtWnTJg0aNChDnYmJiUq85Wa+ePFi3h8IAAAACp6HHsp6WePG0q3/oN/uucE6daQ5c26+7tjx5qAst9q27Y7CTHf58mV98sknKl++vAICAjJd58iRI3r88cc1dOhQDRw4UDt37tTIkSNzVH9gYKDatGmjmJgYvfrqq7p69aoWLVqkuLg4zZ8/37aeYRjq3LmzvL29FRcXp+TkZA0ePFjdu3fXhg0bbOv98ccf+vLLL/X111/r3Llz6tatmyZNmqQ33nhDM2bM0IEDB1StWjW9/vrrkqSSJUsqNTVVpUuX1uLFi1WiRAlt2rRJzz77rIKDg9WtW7csY4+JidGIESP0448/avPmzerXr58aN26sVq1a5ejY74SpidKhQ4c0e/ZsjRgxQmPGjNFPP/2kIUOGyGq1qk+fPkpISJCUdlFvFRgYqKNHj2Za58SJEzV+/Pg8jx24VegrK/Ks7iOT2udZ3QAAwFxff/21fHx8JElXrlxRcHCwvv766yx/C+jdd99VxYoVNWXKFElSxYoV9csvv+iNN97I0f769++vl156SWPHjtVnn32mcuXKqVatWnbrrFmzRnv27NHhw4dVpkwZSdJHH32kqlWrauvWrapfv74kKTU1VfPmzZOvr68kqXfv3lq7dq3eeOMN+fn5yd3dXV5eXgoKCrLV7eLiYve/elhYmDZt2qTFixffNlGqUaOGxo0bJ0kKDw/XzJkztXbt2sKbKKWmpqpevXqKjo6WJNWuXVt79+7V7Nmz1adPH9t6FoehUw3DyFCWbvTo0RoxYoTt9cWLF20XGAAAAP8gGzdmvczFxf51bGzW6zomLV99decxOWjevLlmz54tSfr77781a9YstW3bVj/99JPKli2bYf39+/fbEpV0DRo0yPH+2rdvr0GDBum7777Thx9+qP79+2dYZ9++fSpTpozd/9BVqlSRv7+/9u3bZ9t/aGioLUmSpODgYJ0+fTrbGN59913997//1dGjR3Xt2jUlJSVlSNYc1ahRw+51Tvd1N0xNlIKDg1WlShW7ssqVK+vzzz+XJFv2mZCQoODgYNs6p0+fztDKlM5qtcpqteZRxAAA3CUXFyn9QW3Hf9QA5C5PT/PXzYa3t7fKly9ve123bl35+fnp/fff14QJEzKsn1mDgWEYOd6fq6urevfurXHjxunHH3/U0qVLc7SPzMrd3NzsllssFqWmpt52/4sXL9bw4cM1depUNWrUSL6+vpoyZYp+/PHH2253J/u6W6YO5tC4cWPt37/fruzAgQO27DksLExBQUGKvSXDT0pKUlxcnCIiIvI1VgAAcoW7uxQVlTa5u5sdDYACxmKxqEiRIrqWxeAQlSpV0tatW+3Ktjn5bFT//v0VFxenTp06qVixYhmWV6lSRceOHbMb9OHXX3/VhQsXVLly5Rzvx93dXSkpKXZlGzduVEREhAYPHqzatWurfPny+uOPP5yKP7+YmigNHz5cW7ZsUXR0tH7//XctWLBAc+bM0fPPPy8p7UYZNmyYoqOjtXTpUv3yyy/q16+fvLy81KNHDzNDBwAAAO5aYmKiEhISlJCQoH379unFF1/U5cuX1bFjx0zXHzRokH777Te9/PLLOnDggBYvXmz7zaGsHk1xVLlyZZ05cybDUOHpWrZsqRo1aqhnz57asWOHfvrpJ/Xp00eRkZGqV69ejo8tNDRUP/74o44cOaIzZ84oNTVV5cuX17Zt2/Ttt9/qwIEDeu211zIkfgWFqYlS/fr1tXTpUn366aeqVq2a/v3vf2v69Onq2bOnbZ1Ro0Zp2LBhGjx4sOrVq6cTJ05o9erVdv0hAQC4ZxjGzaGEneguA6BwWrVqlYKDgxUcHKyGDRtq69atWrJkiZo1a5bp+mFhYfrss8/0xRdfqEaNGpo9e7bGjh0rSU49fhIQECDPLLoQWiwWffnllypWrJiaNm2qli1b6oEHHtCiRYucOraRI0fKxcVFVapUUcmSJXXs2DE999xz6tKli7p3766GDRvq7NmzGjx4sFP15heL4UynxnvQxYsX5efnpwsXLqho0aJmh4NCilHvAOTYtWs3hyzeuDFXn3UA/omuX7+uw4cPKywsTB4eHmaHY4o33nhD7777rl1XuX+y290TzuQGpg7mAAAAAMA5s2bNUv369RUQEKAffvhBU6ZM0QsvvGB2WIUOiRIAAABwDzl48KAmTJigv//+W/fff79eeukljR492uywCh0SJQAAAOAe8vbbb+vtt982O4xCz9TBHAAAAACgICJRAgAAwD2vkI9PBifk1r1AogQAAIB7lpubmyTp6tWrJkeCgiL9Xki/N+4UzygBAJCfXFykFi1uzgO4Ky4uLvL399fp06clSV5eXjn+4VUULoZh6OrVqzp9+rT8/f3lcpfvsSRKAADkJ3d36c03zY4CKFSCgoIkyZYs4Z/N39/fdk/cDRIlAAAA3NMsFouCg4NVqlQp3bhxw+xwYCI3N7e7bklKR6IEAACAQsHFxSXX/kkGGMwBAID8dO2aVK9e2nTtmtnRAACyQKIEAAAAAA5IlAAAAADAAYkSAAAAADggUQIAAAAAByRKAAAAAOCARAkAAAAAHPA7SgAA5CcXF6lx45vzAIACiUQJAID85O4uzZhhdhQAgGzQ9Q4AAAAAHJAoAQAAAIADEiUAAPLTtWtSkyZp07VrZkcDAMgCzygBAJDfrl83OwIAQDZoUQIAAAAAByRKAAAAAOCARAkAAAAAHJAoAQAAAIADEiUAAAAAcMCodwAA5KciRaQ6dW7OAwAKJBIlAADyk9UqzZljdhQAgGzwVRYAAAAAOCBRAgAAAAAHJEoAAOSna9ekli3TpmvXzI4GAJAFnlECACC/nT9vdgQAgGzQogQAAAAADkiUAAAAAMABiRIAAAAAOCBRAgAAAAAHJEoAAAAA4IBR7wAAyE9FikhVqtycBwAUSCRKAADkJ6tVmj/f7CgAANngqywAAAAAcECiBAAAAAAOSJQAAMhP169LHTumTdevmx0NACALPKMEAEB+MgwpPv7mPACgQKJFCQAAAAAckCgBAAAAgAMSJQAAAABwQKIEAAAAAA5IlAAAAADAgamJUlRUlCwWi90UFBRkW24YhqKiohQSEiJPT081a9ZMe/fuNTFiAADuksUiPfBA2mSxmB0NACALprcoVa1aVfHx8bbp559/ti2bPHmypk2bppkzZ2rr1q0KCgpSq1atdOnSJRMjBgDgLnh4SIsXp00eHmZHAwDIgumJkqurq4KCgmxTyZIlJaW1Jk2fPl1jx45Vly5dVK1aNcXExOjq1atasGCByVEDAAAAKMxMT5QOHjyokJAQhYWF6cknn9ShQ4ckSYcPH1ZCQoJat25tW9dqtSoyMlKbNm3Ksr7ExERdvHjRbgIAAAAAZ5iaKDVs2FDz58/Xt99+q/fff18JCQmKiIjQ2bNnlZCQIEkKDAy02yYwMNC2LDMTJ06Un5+fbSpTpkyeHgMAAE65fl3q1i1tun7d7GgAAFlwNXPnbdu2tc1Xr15djRo1Urly5RQTE6MHH3xQkmRxeNDVMIwMZbcaPXq0RowYYXt98eJFkiUAQMFhGNL/7z0hwzA3FgBAlkzvencrb29vVa9eXQcPHrSNfufYenT69OkMrUy3slqtKlq0qN0EAAAAAM4oUIlSYmKi9u3bp+DgYIWFhSkoKEixsbG25UlJSYqLi1NERISJUQIAAAAo7Eztejdy5Eh17NhR999/v06fPq0JEybo4sWL6tu3rywWi4YNG6bo6GiFh4crPDxc0dHR8vLyUo8ePcwMGwAAAEAhZ2qi9Oeff+qpp57SmTNnVLJkST344IPasmWLypYtK0kaNWqUrl27psGDB+vcuXNq2LChVq9eLV9fXzPDBgAAAFDImZooLVy48LbLLRaLoqKiFBUVlT8BAQAAAIBMTpQAAPjHsVik4OCb8wCAAolECQCA/OThIX31ldlRAACyUaBGvQMAAACAgoBECQAAAAAckCgBAJCfEhOlPn3SpsREs6MBAGSBZ5QAAMhPqanSr7/enAcAFEi0KAEAAACAAxIlAAAAAHBAogQAAAAADkiUAAAAAMABiRIAAAAAOGDUOwAA8pu/v9kRAACyQaIEAEB+8vSU1qwxOwoAQDboegcAAAAADkiUAAAAAMABiRIAAPkpMVF69tm0KTHR7GgAAFngGSUAAPJTaqq0Y8fNeQBAgUSLEgAAAAA4IFECAAAAAAckSgAAAADggEQJAAAAAByQKAEAAACAA0a9AwAgv3l4mB0BACAbJEoAAOQnT0/p++/NjgIAkA263gEAAACAAxIlAAAAAHBAogQAQH5KSpKGDk2bkpLMjgYAkAWeUQIAID+lpEg//HBzHgBQINGiBAAAAAAOSJQAAAAAwAGJEgAAAAA4IFECAAAAAAckSgAAAADggEQJAAAAABwwPDgAAPnJ01Pats3sKAAA2aBFCQAAAAAc0KKEHAt9ZUWe1n9kUvs8rR8AAADIKVqUAADIT0lJ0ssvp01JSWZHAwDIAokSAAD5KSVFWrs2bUpJMTsaAEAWSJQAAAAAwAGJEgAAAAA4IFECAAAAAAckSgAAAADggEQJAAAAAByQKAEAAACAA35wFgCA/OThIW3ceHMeAFAgkSgBAJCfLBbJ09PsKAAA2aDrHQAAAAA4oEUJAID8lJQkRUenzY8ZI7m7mxsPACBTtCgBAJCfUlKkr79Om1JSzI4GAJCFApMoTZw4URaLRcOGDbOVGYahqKgohYSEyNPTU82aNdPevXvNCxIAAADAP0KBSJS2bt2qOXPmqEaNGnblkydP1rRp0zRz5kxt3bpVQUFBatWqlS5dumRSpAAAAAD+CUxPlC5fvqyePXvq/fffV7FixWzlhmFo+vTpGjt2rLp06aJq1aopJiZGV69e1YIFC0yMGAAAAEBhZ3qi9Pzzz6t9+/Zq2bKlXfnhw4eVkJCg1q1b28qsVqsiIyO1adOmLOtLTEzUxYsX7SYAAAAAcIapo94tXLhQO3bs0NatWzMsS0hIkCQFBgbalQcGBuro0aNZ1jlx4kSNHz8+dwMFAAAA8I9iWovS8ePHNXToUH388cfyuM0vk1ssFrvXhmFkKLvV6NGjdeHCBdt0/PjxXIsZAAAAwD+DaS1K27dv1+nTp1W3bl1bWUpKir777jvNnDlT+/fvl5TWshQcHGxb5/Tp0xlamW5ltVpltVrzLnAAAO6Gh4cUG3tzHgBQIJnWotSiRQv9/PPP2rVrl22qV6+eevbsqV27dumBBx5QUFCQYtM/TCQlJSUpLi5OERERZoUNAMDdsVikYsXSptv0kAAAmMu0FiVfX19Vq1bNrszb21sBAQG28mHDhik6Olrh4eEKDw9XdHS0vLy81KNHDzNCBgAAAPAPYepgDtkZNWqUrl27psGDB+vcuXNq2LChVq9eLV9fX7NDAwDgziQlSW+/nTY/fLjk7m5uPACATBWoRGnDhg12ry0Wi6KiohQVFWVKPAAA5LqUFGnJkrT5IUPMjQUAkCXTf0cJAAAAAAoaEiUAAAAAcECiBAAAAAAOSJQAAAAAwAGJEgAAAAA4IFECAAAAAAcFanhwAAAKPatVWr785jwAoEAiUQIAID8VKSKFhJgdBQAgG3S9AwAAAAAHtCgBAJCfbtyQZs1Kmx88WHJzMzceAECmaFECACA/JSdLH32UNiUnmx0NACALJEoAAAAA4IBECQAAAAAcOJ0oHT58OC/iAAAAAIACw+lEqXz58mrevLk+/vhjXb9+PS9iAgAAAABTOZ0o7d69W7Vr19ZLL72koKAgDRo0SD/99FNexAYAAAAApnA6UapWrZqmTZumEydOaO7cuUpISFCTJk1UtWpVTZs2TX/99VdexAkAAAAA+eaOB3NwdXXVY489psWLF+vNN9/UH3/8oZEjR6p06dLq06eP4uPjczNOAAAKB6tVWrw4bbJazY4GAJCFO06Utm3bpsGDBys4OFjTpk3TyJEj9ccff2jdunU6ceKEOnXqlJtxAgBQOBQpIj3wQNpUhMFnAaCgcnV2g2nTpmnu3Lnav3+/2rVrp/nz56tdu3Yq8v/f7MPCwvTee++pUqVKuR4sAAAAAOQHpxOl2bNnq3///nr66acVFBSU6Tr333+/Pvjgg7sODgCAQufGDWnu3LT5p5+W3NzMjQcAkCmnE6WDBw9mu467u7v69u17RwEBAFCoJSdLc+akzffuTaIEAAWU052j586dqyVLlmQoX7JkiWJiYnIlKAAAAAAwk9OJ0qRJk1SiRIkM5aVKlVJ0dHSuBAUAAAAAZnI6UTp69KjCwsIylJctW1bHjh3LlaAAAAAAwExOJ0qlSpXSnj17MpTv3r1bAQEBuRIUAAAAAJjJ6UTpySef1JAhQ7R+/XqlpKQoJSVF69at09ChQ/Xkk0/mRYwAAAAAkK+cHvVuwoQJOnr0qFq0aCFX17TNU1NT1adPH55RAgAAAFAoOJ0oubu7a9GiRfr3v/+t3bt3y9PTU9WrV1fZsmXzIj4AAAoXq1WaP//mPACgQHI6UUpXoUIFVahQITdjAQCg8CtSRKpSxewoAADZcDpRSklJ0bx587R27VqdPn1aqampdsvXrVuXa8EBAAAAgBmcTpSGDh2qefPmqX379qpWrZosFktexAUAQOF044b06adp8089Jbm5mRsPACBTTidKCxcu1OLFi9WuXbu8iAcAgMItOVl65520+SeeIFECgALK6eHB3d3dVb58+byIBQAAAAAKBKcTpZdeekkzZsyQYRh5EQ8AAAAAmM7prnfff/+91q9fr5UrV6pq1apyc+gy8MUXX+RacAAAAABgBqcTJX9/fz322GN5EQsAAAAAFAhOJ0pz587NizgAAAAAoMBw+hklSUpOTtaaNWv03nvv6dKlS5KkkydP6vLly7kaHAAAAACYwekWpaNHj+qRRx7RsWPHlJiYqFatWsnX11eTJ0/W9evX9e677+ZFnAAAFA5Wq/TeezfnAQAFktMtSkOHDlW9evV07tw5eXp62sofe+wxrV27NleDAwCg0ClSRKpbN20qckcdOwAA+eCORr374Ycf5O7ubldetmxZnThxItcCAwAAAACzOJ0opaamKiUlJUP5n3/+KV9f31wJCgCAQis5WUr/KY0uXSRXpz+KAQD5wOk2/1atWmn69Om21xaLRZcvX9a4cePUrl273IwNAIDC58YNafLktOnGDbOjAQBkwemvsd5++201b95cVapU0fXr19WjRw8dPHhQJUqU0KeffpoXMQIAAABAvnI6UQoJCdGuXbv06aefaseOHUpNTdWAAQPUs2dPu8EdAAAAAOBedUcdoz09PdW/f3/1798/t+MBAAAAANM5nSjNnz//tsv79Olzx8EAAAAAQEHgdKI0dOhQu9c3btzQ1atX5e7uLi8vLxIlAAAAAPc8p0e9O3funN10+fJl7d+/X02aNGEwBwAAAACFQq78eEN4eLgmTZqkXr166bfffsuNKgEAKJzc3aX0n9lw+PF2AEDB4XSLUlZcXFx08uRJp7aZPXu2atSooaJFi6po0aJq1KiRVq5caVtuGIaioqIUEhIiT09PNWvWTHv37s2tkAEAyH8uLlKTJmmTi4vZ0QAAsuB0i9Ly5cvtXhuGofj4eM2cOVONGzd2qq7SpUtr0qRJKl++vCQpJiZGnTp10s6dO1W1alVNnjxZ06ZN07x581ShQgVNmDBBrVq10v79++Xr6+ts6AAAAACQI04nSp07d7Z7bbFYVLJkST388MOaOnWqU3V17NjR7vUbb7yh2bNna8uWLapSpYqmT5+usWPHqkuXLpLSEqnAwEAtWLBAgwYNyrTOxMREJSYm2l5fvHjRqZgAAMhTyclSeu+Jtm0l11zpBQ8AyGVOvzunpqbmRRxKSUnRkiVLdOXKFTVq1EiHDx9WQkKCWrdubVvHarUqMjJSmzZtyjJRmjhxosaPH58nMd4LQl9ZYXYIAIDbuXFDSv+catmSRAkACqhce0bpTv3888/y8fGR1WrVc889p6VLl6pKlSpKSEiQJAUGBtqtHxgYaFuWmdGjR+vChQu26fjx43kaPwAAAIDCx+mvsUaMGJHjdadNm5btOhUrVtSuXbt0/vx5ff755+rbt6/i4uJsyy0Wi936hmFkKLuV1WqV1WrNcYwAAAAA4MjpRGnnzp3asWOHkpOTVbFiRUnSgQMH5OLiojp16tjWu10ycyt3d3fbYA716tXT1q1bNWPGDL388suSpISEBAUHB9vWP336dIZWJgAAAADITU4nSh07dpSvr69iYmJUrFgxSWk/Qvv000/roYce0ksvvXRXARmGocTERIWFhSkoKEixsbGqXbu2JCkpKUlxcXF6880372ofAAAAAHA7TidKU6dO1erVq21JkiQVK1ZMEyZMUOvWrZ1KlMaMGaO2bduqTJkyunTpkhYuXKgNGzZo1apVslgsGjZsmKKjoxUeHq7w8HBFR0fLy8tLPXr0cDZsAAAAAMgxpxOlixcv6tSpU6patapd+enTp3Xp0iWn6jp16pR69+6t+Ph4+fn5qUaNGlq1apVatWolSRo1apSuXbumwYMH69y5c2rYsKFWr17NbygBAAAAyFNOJ0qPPfaYnn76aU2dOlUPPvigJGnLli363//9X9vvHeXUBx98cNvlFotFUVFRioqKcjZMAAAKJnd3adKkm/MAgALJ6UTp3Xff1ciRI9WrVy/duHEjrRJXVw0YMEBTpkzJ9QABAChUXFzSfj8JAFCgOZ0oeXl5adasWZoyZYr++OMPGYah8uXLy9vbOy/iAwAAAIB8d8c/OBsfH6/4+HhVqFBB3t7eMgwjN+MCAKBwSkmR1qxJm1JSzI4GAJAFp1uUzp49q27dumn9+vWyWCw6ePCgHnjgAQ0cOFD+/v6aOnVqXsQJAEDhkJQkvfJK2vzGjZKnp7nxAAAy5XSL0vDhw+Xm5qZjx47Jy8vLVt69e3etWrUqV4MDAAAAADM43aK0evVqffvttypdurRdeXh4uI4ePZprgQEAAACAWZxuUbpy5YpdS1K6M2fOyGq15kpQAAAAAGAmpxOlpk2bav78+bbXFotFqampmjJlipo3b56rwQEAAACAGZzuejdlyhQ1a9ZM27ZtU1JSkkaNGqW9e/fq77//1g8//JAXMQIAAABAvnK6RalKlSras2ePGjRooFatWunKlSvq0qWLdu7cqXLlyuVFjAAAAACQr5xqUbpx44Zat26t9957T+PHj8+rmAAAKLzc3KRx427OAwAKJKcSJTc3N/3yyy+yWCx5FQ8AAIWbq6vUsaPZUQAAsuF017s+ffrogw8+yItYAAAAAKBAcHowh6SkJP33v/9VbGys6tWrJ29vb7vl06ZNy7XgAAAodFJSpM2b0+YbNZJcXMyNBwCQqRwlSnv27FG1atVUpEgR/fLLL6pTp44k6cCBA3br0SUPAIBsJCVJw4alzW/cKHl6mhoOACBzOUqUateurfj4eJUqVUpHjx7V1q1bFRAQkNexAQAAAIApcvSMkr+/vw4fPixJOnLkiFJTU/M0KAAAAAAwU45alLp27arIyEgFBwfLYrGoXr16csmiT/WhQ4dyNUAAAAAAyG85SpTmzJmjLl266Pfff9eQIUP0zDPPyNfXN69jAwAAAABT5HjUu0ceeUSStH37dg0dOpRECQAAAECh5fTw4HPnzs2LOAAAAACgwHA6UQIAAHfBzU0aNermPACgQCJRAgAgP7m6St26mR0FACAbJEoAkInQV1bkaf1HJrXP0/oBAMDdIVECACA/paZKO3emzdeuLRXJ0U8aAgDyGYkSAAD5KTFRGjQobX7jRsnT09x4AACZ4mssAAAAAHBAogQAAAAADkiUAAAAAMABiRIAAAAAOCBRAgAAAAAHJEoAAAAA4IDhwQEAyE+urtKQITfnAQAFEu/QAADkJzc3qU8fs6MAAGSDrncAAAAA4IAWJQAA8lNqqvTbb2nzlSpJRfjOEgAKIhIlAADyU2Liza53GzdKnp7mxgMAyBRfYwEAAACAAxIlAAAAAHBAogQAAAAADkiUAAAAAMABgzkA/3Chr6zIs7qPTGqfZ3UDAADkJVqUAAAAAMABLUoAAOQnV1fp2WdvzgMACiTeoQEAyE9ubjcTJQBAgUXXOwAAAABwQIsSAAD5KTVVOnIkbT40VCrCd5YAUBCRKAEAkJ8SE6Vu3dLmN26UPD3NjQcAkCm+xgIAAAAAByRKAAAAAODA1ERp4sSJql+/vnx9fVWqVCl17txZ+/fvt1vHMAxFRUUpJCREnp6eatasmfbu3WtSxAAAAAD+CUxNlOLi4vT8889ry5Ytio2NVXJyslq3bq0rV67Y1pk8ebKmTZummTNnauvWrQoKClKrVq106dIlEyMHAAAAUJiZOpjDqlWr7F7PnTtXpUqV0vbt29W0aVMZhqHp06dr7Nix6tKliyQpJiZGgYGBWrBggQYNGmRG2AAAAAAKuQL1jNKFCxckScWLF5ckHT58WAkJCWrdurVtHavVqsjISG3atCnTOhITE3Xx4kW7CQAAAACcUWCGBzcMQyNGjFCTJk1UrVo1SVJCQoIkKTAw0G7dwMBAHT16NNN6Jk6cqPHjx+dtsAAA3ClXV6l375vzAIACqcC8Q7/wwgvas2ePvv/++wzLLBaL3WvDMDKUpRs9erRGjBhhe33x4kWVKVMmd4MFAOBOublJQ4eaHQUAIBsFIlF68cUXtXz5cn333XcqXbq0rTwoKEhSWstScHCwrfz06dMZWpnSWa1WWa3WvA0YAAAAQKFm6jNKhmHohRde0BdffKF169YpLCzMbnlYWJiCgoIUGxtrK0tKSlJcXJwiIiLyO1wAAO5eaqp08mTalJpqdjQAgCyY2qL0/PPPa8GCBVq2bJl8fX1tzyT5+fnJ09NTFotFw4YNU3R0tMLDwxUeHq7o6Gh5eXmpR48eZoYOAMCdSUyUHn00bX7jRsnT09x4AACZMjVRmj17tiSpWbNmduVz585Vv379JEmjRo3StWvXNHjwYJ07d04NGzbU6tWr5evrm8/RAgAAAPinMDVRMgwj23UsFouioqIUFRWV9wEBAAAAgArY7ygBAAAAQEFAogQAAAAADkiUAAAAAMABiRIAAAAAOCgQPzgLAMA/houL9MQTN+cBAAUSiRIAAPnJ3V16+WWzowAAZIOudwAAAADggBYlAADyk2FI58+nzfv7SxaLmdEAALJAogQAQH66fl1q1SptfuNGydPT3HgAAJmi6x0AAAAAOCBRAgAAAAAHJEoAAAAA4IBECQAAAAAckCgBAAAAgAMSJQAAAABwwPDgAADkJxcXqUOHm/MAgAKJRAkAgPzk7i5FRZkdBQAgG3S9AwAAAAAHtCgBAJCfDEO6fj1t3sNDsljMjQcAkClalAAAyE/Xr0sPPZQ2pSdMAIACh0QJAAAAAByQKAEAAACAAxIlAAAAAHBAogQAAAAADkiUAAAAAMABiRIAAAAAOOB3lAAAyE8uLlKLFjfnAQAFEokSAAD5yd1devNNs6MAAGSDrncAAAAA4IAWJfwjhL6ywuwQAAAAcA+hRQkAgPx07ZpUr17adO2a2dEAALJAogQAAAAADkiUAAAAAMABiRIAAAAAOCBRAgAAAAAHjHoHAIVMXo/yeGRS+zytPy/l5bm5l88LACAjWpQAAAAAwAEtSgAA5CcXF6lx45vzAIACiUQJAID85O4uzZhhdhQAgGzQ9Q4AAAAAHJAoAQAAAIADEiUAAPLTtWtSkyZp07VrZkcDAMgCzygBAJDfrl83OwIAQDZoUQIAAAAAByRKAAAAAOCARAkAAAAAHJAoAQAAAIADEiUAAAAAcMCod/ks9JUVZocAADBTkSJSnTo35wEABRKJEgAA+clqlebMMTsKAEA2TP0q67vvvlPHjh0VEhIii8WiL7/80m65YRiKiopSSEiIPD091axZM+3du9ecYAEAAAD8Y5iaKF25ckU1a9bUzJkzM10+efJkTZs2TTNnztTWrVsVFBSkVq1a6dKlS/kcKQAAAIB/ElO73rVt21Zt27bNdJlhGJo+fbrGjh2rLl26SJJiYmIUGBioBQsWaNCgQfkZKgAAuePaNaljx7T5r76SPD3NjQcAkKkC+xTp4cOHlZCQoNatW9vKrFarIiMjtWnTpiy3S0xM1MWLF+0mAAAKlPPn0yYAQIFVYBOlhIQESVJgYKBdeWBgoG1ZZiZOnCg/Pz/bVKZMmTyNEwAAAEDhU2ATpXQWi8XutWEYGcpuNXr0aF24cME2HT9+PK9DBAAAAFDIFNjhwYOCgiSltSwFBwfbyk+fPp2hlelWVqtVVqs1z+MDAAAAUHgV2BalsLAwBQUFKTY21laWlJSkuLg4RUREmBgZAAAAgMLO1Baly5cv6/fff7e9Pnz4sHbt2qXixYvr/vvv17BhwxQdHa3w8HCFh4crOjpaXl5e6tGjh4lRAwAAACjsTE2Utm3bpubNm9tejxgxQpLUt29fzZs3T6NGjdK1a9c0ePBgnTt3Tg0bNtTq1avl6+trVsgAANydIkWkKlVuzgMACiRTE6VmzZrJMIwsl1ssFkVFRSkqKir/ggIAIC9ZrdL8+WZHAQDIBl9lAQAAAIADEiUAAAAAcECiBABAfrp+XerYMW26ft3saAAAWSiwv6MEAEChZBhSfPzNeQBAgUSLEgAAAAA4IFECAAAAAAckSgAAAADggEQJAAAAAByQKAEAAACAA0a9AwAgP1ks0gMP3JwHABRIJEoAAOQnDw9p8WKzowAAZIOudwAAAADggEQJAAAAAByQKAEAkJ+uX5e6dUubrl83OxoAQBZ4RgkAgPxkGNKhQzfnAQAFEi1KAAAAAOCARAkAAAAAHND1DijgQl9ZYXYIdyyvYz8yqX2e1p+X7uXrCgDAPwEtSgAAAADggEQJAAAAABzQ9Q4AgPxksUjBwTfnAQAFEokSAAD5ycND+uors6MAAGSDrncAAAAA4IAWJRQYjAIGAACAgoIWJQAA8lNiotSnT9qUmGh2NACALNCiBABAfkpNlX799eY8AKBAokUJAAAAAByQKAEAAACAAxIlAAAAAHBAogQAAAAADkiUAAAAAMABo94BAJDf/P3NjgAAkA0SJQAA8pOnp7RmjdlRAACyQdc7AAAAAHBAogQAAAAADuh6B+CeFfrKCrND+EfKy/N+ZFL7PKu7wEhMlF58MW3+//5Pslqz3SSv7/V/xHkHACeRKAEAkJ9SU6UdO27OAwAKJLreAQAAAIADEiUAAAAAcECiBAAAAAAOSJQAAAAAwAGJEgAAAAA4YNQ7AAByQU6H8LbeSNTHCdckSb1eXalEt+yHB0fW7uXh6u/l2FH48DMEGZEoAQCQjxLdrHqi12SzwwAAZIOudwAAAADggEQJAAAAABzQ9Q4AgHzklnJDY9Z/KEmKbt5fN1zcTI4IAJAZEiUAAPJRkdRU1T2xzzYvF5MDAgBkikQJAAAABUZej76Wl+7Fkd2QNZ5RAgAAAAAH90SiNGvWLIWFhcnDw0N169bVxo0bzQ4JAAAAQCFW4BOlRYsWadiwYRo7dqx27typhx56SG3bttWxY8fMDg0AAABAIVXgE6Vp06ZpwIABGjhwoCpXrqzp06erTJkymj17ttmhAQAAACikCvRgDklJSdq+fbteeeUVu/LWrVtr06ZNmW6TmJioxMRE2+sLFy5Iki5evJh3gTohNfGq2SEAQIGV1+/VBeE9OOVGoi6npqbNJ15VamqKyREVnM/IO5GX1/Revh+5pubgvGetoJyb9DgMw8h23QKdKJ05c0YpKSkKDAy0Kw8MDFRCQkKm20ycOFHjx4/PUF6mTJk8iREAkHv8ppsdQf5onD7zn95mhmHzTznvzrqXz8u9HPu9jPOetYJ2bi5duiQ/P7/brlOgE6V0FovF7rVhGBnK0o0ePVojRoywvU5NTdXff/+tgICALLfJLxcvXlSZMmV0/PhxFS1a1NRYkHu4roUP17Rw4roWPlzTwodrWjgVpOtqGIYuXbqkkJCQbNct0IlSiRIl5OLikqH16PTp0xlamdJZrVZZrVa7Mn9//7wK8Y4ULVrU9JsEuY/rWvhwTQsnrmvhwzUtfLimhVNBua7ZtSSlK9CDObi7u6tu3bqKjY21K4+NjVVERIRJUQEAAAAo7Ap0i5IkjRgxQr1791a9evXUqFEjzZkzR8eOHdNzzz1ndmgAAAAACqkCnyh1795dZ8+e1euvv674+HhVq1ZN33zzjcqWLWt2aE6zWq0aN25chq6BuLdxXQsfrmnhxHUtfLimhQ/XtHC6V6+rxcjJ2HgAAAAA8A9SoJ9RAgAAAAAzkCgBAAAAgAMSJQAAAABwQKIEAAAAAA5IlPLRrFmzFBYWJg8PD9WtW1cbN240OyTche+++04dO3ZUSEiILBaLvvzyS7NDwl2aOHGi6tevL19fX5UqVUqdO3fW/v37zQ4Ld2H27NmqUaOG7UcOGzVqpJUrV5odFnLRxIkTZbFYNGzYMLNDwV2IioqSxWKxm4KCgswOC3fpxIkT6tWrlwICAuTl5aVatWpp+/btZoeVYyRK+WTRokUaNmyYxo4dq507d+qhhx5S27ZtdezYMbNDwx26cuWKatasqZkzZ5odCnJJXFycnn/+eW3ZskWxsbFKTk5W69atdeXKFbNDwx0qXbq0Jk2apG3btmnbtm16+OGH1alTJ+3du9fs0JALtm7dqjlz5qhGjRpmh4JcULVqVcXHx9umn3/+2eyQcBfOnTunxo0by83NTStXrtSvv/6qqVOnyt/f3+zQcozhwfNJw4YNVadOHc2ePdtWVrlyZXXu3FkTJ040MTLkBovFoqVLl6pz585mh4Jc9Ndff6lUqVKKi4tT06ZNzQ4HuaR48eKaMmWKBgwYYHYouAuXL19WnTp1NGvWLE2YMEG1atXS9OnTzQ4LdygqKkpffvmldu3aZXYoyCWvvPKKfvjhh3u6BxUtSvkgKSlJ27dvV+vWre3KW7durU2bNpkUFYDsXLhwQVLaP9a496WkpGjhwoW6cuWKGjVqZHY4uEvPP/+82rdvr5YtW5odCnLJwYMHFRISorCwMD355JM6dOiQ2SHhLixfvlz16tXTE088oVKlSql27dp6//33zQ7LKSRK+eDMmTNKSUlRYGCgXXlgYKASEhJMigrA7RiGoREjRqhJkyaqVq2a2eHgLvz888/y8fGR1WrVc889p6VLl6pKlSpmh4W7sHDhQu3YsYMeGYVIw4YNNX/+fH377bd6//33lZCQoIiICJ09e9bs0HCHDh06pNmzZys8PFzffvutnnvuOQ0ZMkTz5883O7QcczU7gH8Si8Vi99owjAxlAAqGF154QXv27NH3339vdii4SxUrVtSuXbt0/vx5ff755+rbt6/i4uJIlu5Rx48f19ChQ7V69Wp5eHiYHQ5ySdu2bW3z1atXV6NGjVSuXDnFxMRoxIgRJkaGO5Wamqp69eopOjpaklS7dm3t3btXs2fPVp8+fUyOLmdoUcoHJUqUkIuLS4bWo9OnT2doZQJgvhdffFHLly/X+vXrVbp0abPDwV1yd3dX+fLlVa9ePU2cOFE1a9bUjBkzzA4Ld2j79u06ffq06tatK1dXV7m6uiouLk7vvPOOXF1dlZKSYnaIyAXe3t6qXr26Dh48aHYouEPBwcEZvpCqXLnyPTWQGYlSPnB3d1fdunUVGxtrVx4bG6uIiAiTogLgyDAMvfDCC/riiy+0bt06hYWFmR0S8oBhGEpMTDQ7DNyhFi1a6Oeff9auXbtsU7169dSzZ0/t2rVLLi4uZoeIXJCYmKh9+/YpODjY7FBwhxo3bpzhJzYOHDigsmXLmhSR8+h6l09GjBih3r17q169emrUqJHmzJmjY8eO6bnnnjM7NNyhy5cv6/fff7e9Pnz4sHbt2qXixYvr/vvvNzEy3Knnn39eCxYs0LJly+Tr62trBfbz85Onp6fJ0eFOjBkzRm3btlWZMmV06dIlLVy4UBs2bNCqVavMDg13yNfXN8Nzg97e3goICOB5wnvYyJEj1bFjR91///06ffq0JkyYoIsXL6pv375mh4Y7NHz4cEVERCg6OlrdunXTTz/9pDlz5mjOnDlmh5ZjJEr5pHv37jp79qxef/11xcfHq1q1avrmm2/uqawa9rZt26bmzZvbXqf3oe7bt6/mzZtnUlS4G+nD9zdr1syufO7cuerXr1/+B4S7durUKfXu3Vvx8fHy8/NTjRo1tGrVKrVq1crs0ADc4s8//9RTTz2lM2fOqGTJknrwwQe1ZcsW/k+6h9WvX19Lly7V6NGj9frrryssLEzTp09Xz549zQ4tx/gdJQAAAABwwDNKAAAAAOCARAkAAAAAHJAoAQAAAIADEiUAAAAAcECiBAAAAAAOSJQAAAAAwAGJEgAAAAA4IFECAAAAAAckSgCAQstisejLL780OwxJUlRUlGrVqnVH2/bu3VvR0dF3tf958+bJ398/V+JxlJiYqPvvv1/bt2/PlfoAoCAgUQIAk/Xr10+dO3c2O4y7kpv/dBcGuZmg7dmzRytWrNCLL754V/V0795dBw4cyJWYHFmtVo0cOVIvv/xyntQPAGYgUQIAmCYpKcnsEAq8mTNn6oknnpCvr+9d1ePp6alSpUrlUlQZ9ezZUxs3btS+ffvybB8AkJ9IlACggIuLi1ODBg1ktVoVHBysV155RcnJybblzZo105AhQzRq1CgVL15cQUFBioqKsqvjt99+U5MmTeTh4aEqVapozZo1GVo9Tpw4oe7du6tYsWIKCAhQp06ddOTIEdvyDRs2qEGDBvL29pa/v78aN26so0ePat68eRo/frx2794ti8Uii8WiefPmZXos6a1nEydOVEhIiCpUqCAp8xYYf39/Wz1HjhyRxWLRF198oebNm8vLy0s1a9bU5s2bnTqX2R1jenxvvfWWgoODFRAQoOeff143btywrRMfH6/27dvL09NTYWFhWrBggUJDQzV9+nRJUmhoqCTpsccek8Visb1O99FHHyk0NFR+fn568skndenSpSzjTU1N1ZIlS/Too4/alYeGhmrChAnq06ePfHx8VLZsWS1btkx//fWXOnXqJB8fH1WvXl3btm2zbePY9S4zc+fOVeXKleXh4aFKlSpp1qxZtmVJSUl64YUXFBwcLA8PD4WGhmrixIm25QEBAYqIiNCnn356230AwL2CRAkACrATJ06oXbt2ql+/vnbv3q3Zs2frgw8+0IQJE+zWi4mJkbe3t3788UdNnjxZr7/+umJjYyWl/bPduXNneXl56ccff9ScOXM0duxYu+2vXr2q5s2by8fHR999952+//57+fj46JFHHlFSUpKSk5PVuXNnRUZGas+ePdq8ebOeffZZWSwWde/eXS+99JKqVq2q+Ph4xcfHq3v37lke09q1a7Vv3z7Fxsbq66+/dup8jB07ViNHjtSuXbtUoUIFPfXUU3ZJ4+1kd4zp1q9frz/++EPr169XTEyM5s2bZ5f49enTRydPntSGDRv0+eefa86cOTp9+rRt+datWyWlJR3x8fG215L0xx9/6Msvv9TXX3+tr7/+WnFxcZo0aVKWMe/Zs0fnz59XvXr1Mix7++231bhxY+3cuVPt27dX79691adPH/Xq1Us7duxQ+fLl1adPHxmGkaPz8/7772vs2LF64403tG/fPkVHR+u1115TTEyMJOmdd97R8uXLtXjxYu3fv18ff/xxhiSwQYMG2rhxY472BwAFngEAMFXfvn2NTp06ZbpszJgxRsWKFY3U1FRb2X/+8x/Dx8fHSElJMQzDMCIjI40mTZrYbVe/fn3j5ZdfNgzDMFauXGm4uroa8fHxtuWxsbGGJGPp0qWGYRjGBx98kGE/iYmJhqenp/Htt98aZ8+eNSQZGzZsyDTOcePGGTVr1szRsQYGBhqJiYl25bfGks7Pz8+YO3euYRiGcfjwYUOS8d///te2fO/evYYkY9++fVnuz5ljTI+vbNmyRnJysm2dJ554wujevbthGIaxb98+Q5KxdetW2/KDBw8akoy33377tsczbtw4w8vLy7h48aKt7H//93+Nhg0bZhn/0qVLDRcXF7uYDcMwypYta/Tq1cv2Oj4+3pBkvPbaa7ayzZs3G5Js133u3LmGn5+fXTy3XrMyZcoYCxYssNvPv//9b6NRo0aGYRjGiy++aDz88MMZYrnVjBkzjNDQ0CyXA8C9hBYlACjA9u3bp0aNGslisdjKGjdurMuXL+vPP/+0ldWoUcNuu+DgYFsrx/79+1WmTBkFBQXZljdo0MBu/e3bt+v333+Xr6+vfHx85OPjo+LFi+v69ev6448/VLx4cfXr109t2rRRx44dNWPGDMXHx9/RMVWvXl3u7u53tO2txxkcHCxJdq05t5PdMaarWrWqXFxc7PZz67l0dXVVnTp1bMvLly+vYsWK5SiG0NBQu2eNbq07M9euXZPVarW7/uluPReBgYGS0s6tY1lOzs9ff/2l48ePa8CAAbZz4+PjowkTJtjOTb9+/bRr1y5VrFhRQ4YM0erVqzPU4+npqatXr2a7PwC4F7iaHQAAIGuGYWT4J9n4/12pbi13c3OzW8disSg1NTXLOhylpqaqbt26+uSTTzIsK1mypKS0rmRDhgzRqlWrtGjRIr366quKjY3Vgw8+6NQxeXt7ZyizWCwZuojd+lxQuluPM/2Y0o8zOzk5Rsd9pO/n1nOZmazKHd2u7syUKFFCV69eVVJSUobkMrNzcafnJ32d999/Xw0bNrRblp401qlTR4cPH9bKlSu1Zs0adevWTS1bttRnn31mW/fvv/+2O5cAcC8jUQKAAqxKlSr6/PPP7ZKdTZs2ydfXV/fdd1+O6qhUqZKOHTumU6dO2VoZbn1uRkr7J3jRokUqVaqUihYtmmVdtWvXVu3atTV69Gg1atRICxYs0IMPPih3d3elpKTc4VGmJSq3tlAdPHgw11smcnqMt1OpUiUlJydr586dqlu3riTp999/1/nz5+3Wc3Nzu6vzkS59yPVff/01T4dfDwwM1H333adDhw6pZ8+eWa5XtGhRde/eXd27d9fjjz+uRx55RH///beKFy8uSfrll19Uu3btPIsTAPITXe8AoAC4cOGCdu3aZTcdO3ZMgwcP1vHjx/Xiiy/qt99+07JlyzRu3DiNGDFCRYrk7C28VatWKleunPr27as9e/bohx9+sA3mkJ589ezZUyVKlFCnTp20ceNGHT58WHFxcRo6dKj+/PNPHT58WKNHj9bmzZt19OhRrV69WgcOHFDlypUlpXUpO3z4sHbt2qUzZ84oMTHRqeN/+OGHNXPmTO3YsUPbtm3Tc889l6H15W5ld4w5UalSJbVs2VLPPvusfvrpJ+3cuVPPPvusPD097VrtQkNDtXbtWiUkJOjcuXN3HHPJkiVVp04dff/993dcR05FRUVp4sSJmjFjhg4cOKCff/5Zc+fO1bRp0ySlDR6xcOFC/fbbbzpw4ICWLFmioKAgu5H0Nm7cqNatW+d5rACQH0iUAKAA2LBhg621Jn3617/+pfvuu0/ffPONfvrpJ9WsWVPPPfecBgwYoFdffTXHdbu4uOjLL7/U5cuXVb9+fQ0cONC2vYeHhyTJy8tL3333ne6//3516dJFlStXVv/+/XXt2jUVLVpUXl5e+u2339S1a1dVqFBBzz77rF544QUNGjRIktS1a1c98sgjat68uUqWLOn0ENFTp05VmTJl1LRpU/Xo0UMjR46Ul5eXU3VkJ7tjzKn58+crMDBQTZs21WOPPaZnnnlGvr6+tnOZfjyxsbEqU6bMXbewPPvss5l2F8xtAwcO1H//+1/NmzdP1atXV2RkpObNm6ewsDBJko+Pj958803Vq1dP9evX15EjR/TNN9/YEvbNmzfrwoULevzxx/M8VgDIDxYjpx2rAQCFxg8//KAmTZro999/V7ly5cwO5572559/qkyZMlqzZo1atGiR6/Vfv35dFStW1MKFC9WoUaNcrz+3PPHEE6pdu7bGjBljdigAkCt4RgkA/gGWLl0qHx8fhYeH6/fff9fQoUPVuHFjkqQ7sG7dOl2+fFnVq1dXfHy8Ro0apdDQUDVt2jRP9ufh4aH58+frzJkzeVJ/bkhMTFTNmjU1fPhws0MBgFxDogQA/wCXLl3SqFGjdPz4cZUoUUItW7bU1KlTzQ7rnnTjxg2NGTNGhw4dkq+vryIiIvTJJ5/k+jNVt4qMjMyzunOD1Wp1qjsoANwL6HoHAAAAAA4YzAEAAAAAHJAoAQAAAIADEiUAAAAAcECiBAAAAAAOSJQAAAAAwAGJEgAAAAA4IFECAAAAAAckSgAAAADg4P8BuBZC3gFODVMAAAAASUVORK5CYII=\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot_compare('LongestRun_mi', 'Longest run length (miles)')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Big Mountain has one of the longest runs. Although it is just over half the length of the longest, the longer ones are rare." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 5.8.8 Trams" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot_compare('trams', 'Number of trams')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The vast majority of resorts, such as Big Mountain, have no trams." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 5.8.9 Skiable terrain area" ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot_compare('SkiableTerrain_ac', 'Skiable terrain area (acres)')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Big Mountain is amongst the resorts with the largest amount of skiable terrain." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 5.9 Modeling scenarios" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Big Mountain Resort has been reviewing potential scenarios for either cutting costs or increasing revenue (from ticket prices). Ticket price is not determined by any set of parameters; the resort is free to set whatever price it likes. However, the resort operates within a market where people pay more for certain facilities, and less for others. Being able to sense how facilities support a given ticket price is valuable business intelligence. This is where the utility of our model comes in.\n", "\n", "The business has shortlisted some options:\n", "1. Permanently closing down up to 10 of the least used runs. This doesn't impact any other resort statistics.\n", "2. Increase the vertical drop by adding a run to a point 150 feet lower down but requiring the installation of an additional chair lift to bring skiers back up, without additional snow making coverage\n", "3. Same as number 2, but adding 2 acres of snow making cover\n", "4. Increase the longest run by 0.2 mile to boast 3.5 miles length, requiring an additional snow making coverage of 4 acres\n", "\n", "The expected number of visitors over the season is 350,000 and, on average, visitors ski for five days. Assume the provided data includes the additional lift that Big Mountain recently installed." ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [], "source": [ "expected_visitors = 350_000" ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
vertical_dropSnow Making_actotal_chairsfastQuadsRunsLongestRun_mitramsSkiableTerrain_ac
1242353600.0143105.03.303000.0
\n", "
" ], "text/plain": [ " vertical_drop Snow Making_ac total_chairs fastQuads Runs \\\n", "124 2353 600.0 14 3 105.0 \n", "\n", " LongestRun_mi trams SkiableTerrain_ac \n", "124 3.3 0 3000.0 " ] }, "execution_count": 31, "metadata": {}, "output_type": "execute_result" } ], "source": [ "all_feats = ['vertical_drop', 'Snow Making_ac', 'total_chairs', 'fastQuads', \n", " 'Runs', 'LongestRun_mi', 'trams', 'SkiableTerrain_ac']\n", "big_mountain[all_feats]" ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [], "source": [ "# In this function, we copy the Big Mountain data into a new data frame.\n", "# For each feature, and each of its deltas,\n", "# we create a modified scenario dataframe (bm2), and make a ticket price prediction\n", "# for it. The difference between the scenario's prediction and the current\n", "# prediction is then calculated and returned.\n", "# Complete the code to increment each feature by the associated delta\n", "def predict_increase(features, deltas):\n", " \"\"\"Increase in modelled ticket price by applying delta to feature.\n", " \n", " Arguments:\n", " features - list, names of the features in the ski_data dataframe to change\n", " deltas - list, the amounts by which to increase the values of the features\n", " \n", " Outputs:\n", " Amount of increase in the predicted ticket price\n", " \"\"\"\n", " \n", " bm2 = X_bm.copy()\n", " for f, d in zip(features, deltas):\n", " bm2[f] += d\n", " return model.predict(bm2).item() - model.predict(X_bm).item()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 5.9.1 Scenario 1" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Close up to 10 of the least used runs. The number of runs is the only parameter varying." ] }, { "cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[-1, -2, -3, -4, -5, -6, -7, -8, -9, -10]" ] }, "execution_count": 33, "metadata": {}, "output_type": "execute_result" } ], "source": [ "[i for i in range(-1, -11, -1)]" ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [], "source": [ "runs_delta = [i for i in range(-1, -11, -1)]\n", "price_deltas = [predict_increase(['Runs'], [delta]) for delta in runs_delta]" ] }, { "cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[-0.24034334763948095,\n", " -0.6180257510729632,\n", " -0.8841201716738141,\n", " -0.8841201716738141,\n", " -0.8841201716738141,\n", " -1.5836909871244558,\n", " -1.5836909871244558,\n", " -1.6523605150214564,\n", " -1.7982832618025668,\n", " -1.7982832618025668]" ] }, "execution_count": 35, "metadata": {}, "output_type": "execute_result" } ], "source": [ "price_deltas" ] }, { "cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Here, we create two plots, side by side, for the predicted ticket price change (delta) for each\n", "# condition (number of runs closed) in the scenario and the associated predicted revenue\n", "# change on the assumption that each of the expected visitors buys 5 tickets\n", "# There are two things to do here:\n", "# 1 - use a list comprehension to create a list of the number of runs closed from `runs_delta`\n", "# 2 - use a list comprehension to create a list of predicted revenue changes from `price_deltas`\n", "runs_closed = [-1 * num for num in runs_delta] #1\n", "fig, ax = plt.subplots(1, 2, figsize=(10, 5))\n", "fig.subplots_adjust(wspace=0.5)\n", "ax[0].plot(runs_closed, price_deltas, 'o-')\n", "ax[0].set(xlabel='Runs closed', ylabel='Change ($)', title='Ticket price')\n", "revenue_deltas = [5 * expected_visitors * price for price in price_deltas] #2\n", "ax[1].plot(runs_closed, revenue_deltas, 'o-')\n", "ax[1].set(xlabel='Runs closed', ylabel='Change ($)', title='Revenue');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The model says closing one run makes no difference. Closing 2 and 3 successively reduces support for ticket price and so revenue. If Big Mountain closes down 3 runs, it seems they may as well close down 4 or 5, as there's no further loss in ticket price. Increasing the closures down to 6 or more leads to a large drop. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 5.9.2 Scenario 2" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In this scenario, Big Mountain is adding a run, increasing the vertical drop by 150 feet, and installing an additional chair lift." ] }, { "cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [], "source": [ "# Call `predict_increase` with a list of the features 'Runs', 'vertical_drop', and 'total_chairs'\n", "# and associated deltas of 1, 150, and 1\n", "ticket2_increase = predict_increase(['Runs', 'vertical_drop', 'total_chairs'], [1, 150, 1])\n", "revenue2_increase = 5 * expected_visitors * ticket2_increase" ] }, { "cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "This scenario supports a ticket price increase of $0.695\n", "Over the season, this could be expected to amount to a revenue increase $1,216,738.2\n" ] } ], "source": [ "print(f'This scenario supports a ticket price increase of ${ticket2_increase:.3f}')\n", "print('Over the season, this could be expected to amount to a revenue increase $'+'{:,}'.format(round(revenue2_increase,2)))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 5.9.3 Scenario 3" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In this scenario, we are repeating the previous one, but adding 2 acres of snow making." ] }, { "cell_type": "code", "execution_count": 39, "metadata": {}, "outputs": [], "source": [ "# Repeat scenario 2 conditions, but add an increase of 2 to `Snow Making_ac`\n", "ticket3_increase = predict_increase(['Runs', 'vertical_drop', 'total_chairs', 'Snow Making_ac'], [1, 150, 1, 2])\n", "revenue3_increase = 5 * expected_visitors * ticket3_increase" ] }, { "cell_type": "code", "execution_count": 40, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "This scenario increases the ticket price by $0.695\n", "Over the season, this could be expected to amount to $1,216,738.2\n" ] } ], "source": [ "print(f'This scenario increases the ticket price by ${ticket3_increase:.3f}')\n", "print(f'Over the season, this could be expected to amount to $'+'{:,}'.format(round(revenue2_increase,2)))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Such a small increase in the snow making area makes no difference!" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 5.9.4 Scenario 4" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This scenario calls for increasing the longest run by .2 miles and guaranteeing its snow coverage by adding 4 acres of snow making capability." ] }, { "cell_type": "code", "execution_count": 41, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.0" ] }, "execution_count": 41, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Predict the increase from adding 0.2 miles to `LongestRun_mi` and 4 to `Snow Making_ac`\n", "predict_increase(['LongestRun_mi', 'Snow Making_ac'], [0.2, 4])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "No difference whatsoever. Although the longest run feature was used in the linear model, the random forest model (the one we chose because of its better performance) only has longest run way down in the feature importance list." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 5.10 Further work" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The data on which our study is based speaks to revenue growth and the assets that best support it. This is, however, only the top line of the Income Statement. Additional data on Big Mountain's cost structure relative to competitors would be highly valuable. This would allow us to compute asset utilization, working capital, leverage, and profitability metrics, as well as a one or more earnings forecasts and forecasts of free cashflow to the firm. This would assist management in capital budgeting and/or allow them to place a value on the enterprise, if the owners wish to engage an investment bank and sell the business to obtain greater personal liquidity. " ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.13" }, "toc": { "base_numbering": 1, "nav_menu": {}, "number_sections": true, "sideBar": true, "skip_h1_title": false, "title_cell": "Table of Contents", "title_sidebar": "Contents", "toc_cell": false, "toc_position": {}, "toc_section_display": true, "toc_window_display": true }, "varInspector": { "cols": { "lenName": 16, "lenType": 16, "lenVar": 40 }, "kernels_config": { "python": { "delete_cmd_postfix": "", "delete_cmd_prefix": "del ", "library": "var_list.py", "varRefreshCmd": "print(var_dic_list())" }, "r": { "delete_cmd_postfix": ") ", "delete_cmd_prefix": "rm(", "library": "var_list.r", "varRefreshCmd": "cat(var_dic_list()) " } }, "types_to_exclude": [ "module", "function", "builtin_function_or_method", "instance", "_Feature" ], "window_display": false } }, "nbformat": 4, "nbformat_minor": 4 }