FinalProject_group016.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Introduction and background"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Overview"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For our final project, we performed a predictive analysis on data from Kickstarter to see which factors are more correlated with status of a Kickstarter project (successful or failed, which is defined whether they raised the goal amount of funding) and see if we can extraploate those correlations to predict which Kickstarter projects are more likely to be successful. We did so by taking a look at some of the variables associated with projects, such as duration, USD goal, categories, and start/end months for any associations between them and whether a project is successful or failed through visualization as well as statistical tests."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Names\n",
    "\n",
    "- Alan Lloyd Willey\n",
    "- Enlin Wei\n",
    "- Kanami Hannah Tanaka\n",
    "- Karen Rodriguez Pinto\n",
    "- Yumi Minami\n",
    "- Yuxiao Fan"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Group Members IDs\n",
    "\n",
    "- XXXXXXXXX\n",
    "- XXXXXXXXX\n",
    "- XXXXXXXXX\n",
    "- XXXXXXXXX\n",
    "- XXXXXXXXX\n",
    "- XXXXXXXXX"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Research Question"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We are conducting this research to investigate what could be most predictive of a Kickstarter project's outcome, so the research question we wanted to ask for this project was \"Among the US-based Kickstarters, which factor (within the information given in the dataset) contributes most to a Kickstarter's outcome?\"\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Background and Prior Work"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before we introduce Kickstarter, we will take a look at crowdfunding platforms, which is what Kickstarter is. Basically, crowdfunding platforms allow those with innovative projects to pitch those projects to the public with a goal of a certain amount of money to raise; and if people like that idea and would like to support it, they can donate funds to help\n",
    "\n",
    "A crowdfunding platforms like Kickstarter allows users to raise money and typically provide backer rewards or pre-order products. For example a filmmaker may offer a digital copy film, a live viewing of premier, signed posters, etc. A tech company could be offering pre-orders of their new phone cases or other product.\n",
    "\n",
    "Kickstarter is a crowdfunding platform which was created by Perry Chen and Yancy Strickler in 2009, to be a place where the main focus is not Kickstarter's profit but success for those who pitch their projects. If a project raises enough money to meet its goal, it will receive those funds, and Kickstarter makes money from a 3-5% fee taken from the funds. Kickstarter does make efforts to ensure you keep your promises to backers and fraud charges could be made if you can't deliver or use funds improperly. Because funds from backers to creators cannot be charged unless the project reaches their goals, we consider this website is based on the perspectives of all-or-nothing.\n",
    "\n",
    "References (include links):\n",
    "- 1) \"Kickstarter crowdfunding site officially launches in Canada\". The Canadian Press. 10 September 2013. Retrieved 8 June 2019. https://www.cbc.ca/news/business/kickstarter-crowdfunding-site-officially-launches-in-canada-1.1703774\n",
    "- 2) Isaac, Mike and David Gelles (September 21, 2015). \"Kickstarter Focuses Its Mission on Altruism Over Profit\". The New York Times. https://www.nytimes.com/2015/09/21/technology/kickstarters-altruistic-vision-profits-as-the-means-not-the-mission.html"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Hypothesis\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "we raised four hypothesis.\n",
    "\n",
    "(1)We hypothesize that longer durations would likely mean a Kickstarter would fail, as that would mean backers are not as interested in the projects and thus the projects take longer to receive enough pledges to reach the goal (or may not reach the goal at all and fail). On the contrary, projects that are popular would receive pledges quickly and can hit the goal very soon.\n",
    "\n",
    "(2)We hypothesize that the Kickstarters which fail will likely have a high USD goal, as pledgers are likely more drawn toward projects that are \"cheap\" (having low goals which can be reached quickly); especially when something has a goal that is relatively high, pledgers wouldn't want to have to pledge that much for something that isn't worth that much.\n",
    "\n",
    "(3)We hypothesize that the main categories which possibly have strong influences on funding and become successful are ‘music’, ‘film and video’, and ‘publishing’ because those categories are easier to be promoted through funding promotions. Those categories are quite all rounders, which means that are quite inclusive to any age group, gender, or so on. Also, if the producer possibly have followers on their artistic work, it could make easier for them to acquire help for funding. Also, there could not any possible harms which be led from those products to backers, so psychologically speaking, it could be quite easier to be funded for them. Interestingly, we also assumed that the categories that failed easier could be the same categories which we assumed as the successful ones, because their funding is based on backers’ interests and preferences. In order to succeed in funding, the projects have to consider the backers’ popular and public trends; if one project was focused on one specific group of people, then it has a higher chance to fail.\n",
    "\n",
    "(4)We hypothesize that projects which end later in the year (around October, November, December) have a higher chance of success because the end of the year is Thanksgiving and Christmas, where consumerism goes up because people tend buy a lot of things on holidays and might be more likely to try out the new products from Kickstarter projects. So people would likely pledge projects near the end of the year so that if it becomes successful they can buy the products for the holiday season."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dataset(s)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Dataset Name: Kickstarter Campaigns\n",
    "- Link to the dataset: https://www.kaggle.com/yashkantharia/kickstarter-campaigns\n",
    "- Number of observations: 192548\n",
    "\n",
    "This dataset contains information about Kickstarter crowdfunding campaigns from 2014 to February 2019. The information includes the names, currency, main and subcategories, launch date and deadlines, goal amount of money to raise and actual amounts raised, whether the campaign was successful or failed, and geographical locations of the campaigns (country and state).\n",
    "\n",
    "We found this dataset is interesting because of the following reasons:\n",
    "- Kickstarter funding have done by creators and backers, and they are not based on profits consideration for each other; backers do the funding for creators if they think their projects seemed successful or beneficial.\n",
    "- We can observe the data while considering the reasons why one projects went successful on funding but the other did not; There should be some factors having a correlation with successful ones and failed ones. \n",
    "- This dataset has quite a lot of columns that we could make many researches, although we are not going through all of the possible research."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Cleaning & Pre-processing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.6/site-packages/statsmodels/compat/pandas.py:56: FutureWarning: The pandas.core.datetools module is deprecated and will be removed in a future version. Please use the pandas.tseries module instead.\n",
      "  from pandas.core import datetools\n"
     ]
    }
   ],
   "source": [
    "# imports\n",
    "%matplotlib inline\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "import patsy\n",
    "import statsmodels.api as sm\n",
    "import scipy.stats as stats\n",
    "\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.model_selection import train_test_split\n",
    "sns.set(style=\"white\")\n",
    "sns.set(style=\"whitegrid\", color_codes=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# loads Kickstarters data into dataframe\n",
    "df_kickstarters = pd.read_csv(\"Kickstarter_projects_Feb19.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>name</th>\n",
       "      <th>currency</th>\n",
       "      <th>main_category</th>\n",
       "      <th>sub_category</th>\n",
       "      <th>launched_at</th>\n",
       "      <th>deadline</th>\n",
       "      <th>duration</th>\n",
       "      <th>goal_usd</th>\n",
       "      <th>city</th>\n",
       "      <th>state</th>\n",
       "      <th>country</th>\n",
       "      <th>blurb_length</th>\n",
       "      <th>name_length</th>\n",
       "      <th>status</th>\n",
       "      <th>start_month</th>\n",
       "      <th>end_month</th>\n",
       "      <th>start_Q</th>\n",
       "      <th>end_Q</th>\n",
       "      <th>usd_pledged</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1687733153</td>\n",
       "      <td>Socks of Speed and Socks of Elvenkind</td>\n",
       "      <td>USD</td>\n",
       "      <td>games</td>\n",
       "      <td>Tabletop Games</td>\n",
       "      <td>2018-10-30 20:00:02</td>\n",
       "      <td>2018-11-15 17:59:00</td>\n",
       "      <td>16.0</td>\n",
       "      <td>2000.00000</td>\n",
       "      <td>Menasha</td>\n",
       "      <td>WI</td>\n",
       "      <td>US</td>\n",
       "      <td>14</td>\n",
       "      <td>7</td>\n",
       "      <td>successful</td>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "      <td>Q4</td>\n",
       "      <td>Q4</td>\n",
       "      <td>6061.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>227936657</td>\n",
       "      <td>Power Punch Boot Camp: An All-Ages Graphic Novel</td>\n",
       "      <td>GBP</td>\n",
       "      <td>comics</td>\n",
       "      <td>Comic Books</td>\n",
       "      <td>2018-08-06 10:00:43</td>\n",
       "      <td>2018-09-05 10:00:43</td>\n",
       "      <td>30.0</td>\n",
       "      <td>3870.99771</td>\n",
       "      <td>Shepperton</td>\n",
       "      <td>England</td>\n",
       "      <td>GB</td>\n",
       "      <td>24</td>\n",
       "      <td>8</td>\n",
       "      <td>successful</td>\n",
       "      <td>8</td>\n",
       "      <td>9</td>\n",
       "      <td>Q3</td>\n",
       "      <td>Q3</td>\n",
       "      <td>3914.50512</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>454186436</td>\n",
       "      <td>Live Printing with SX8: \"Squeegee Pulp Up\"</td>\n",
       "      <td>USD</td>\n",
       "      <td>fashion</td>\n",
       "      <td>Apparel</td>\n",
       "      <td>2017-06-09 15:41:03</td>\n",
       "      <td>2017-07-09 15:41:03</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1100.00000</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>NY</td>\n",
       "      <td>US</td>\n",
       "      <td>21</td>\n",
       "      <td>7</td>\n",
       "      <td>successful</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>Q2</td>\n",
       "      <td>Q3</td>\n",
       "      <td>1110.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>629469071</td>\n",
       "      <td>Lost Dog Street Band's Next Album</td>\n",
       "      <td>USD</td>\n",
       "      <td>music</td>\n",
       "      <td>Country &amp; Folk</td>\n",
       "      <td>2014-09-25 18:46:01</td>\n",
       "      <td>2014-11-10 06:00:00</td>\n",
       "      <td>45.0</td>\n",
       "      <td>3500.00000</td>\n",
       "      <td>Nashville</td>\n",
       "      <td>TN</td>\n",
       "      <td>US</td>\n",
       "      <td>15</td>\n",
       "      <td>6</td>\n",
       "      <td>successful</td>\n",
       "      <td>9</td>\n",
       "      <td>11</td>\n",
       "      <td>Q3</td>\n",
       "      <td>Q4</td>\n",
       "      <td>4807.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>183973060</td>\n",
       "      <td>Qto-X, a Tiny Lantern</td>\n",
       "      <td>USD</td>\n",
       "      <td>technology</td>\n",
       "      <td>Gadgets</td>\n",
       "      <td>2016-11-28 16:35:11</td>\n",
       "      <td>2017-01-27 16:35:11</td>\n",
       "      <td>60.0</td>\n",
       "      <td>30000.00000</td>\n",
       "      <td>Troy</td>\n",
       "      <td>MI</td>\n",
       "      <td>US</td>\n",
       "      <td>15</td>\n",
       "      <td>4</td>\n",
       "      <td>successful</td>\n",
       "      <td>11</td>\n",
       "      <td>1</td>\n",
       "      <td>Q4</td>\n",
       "      <td>Q1</td>\n",
       "      <td>40368.00000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           id                                              name currency  \\\n",
       "0  1687733153             Socks of Speed and Socks of Elvenkind      USD   \n",
       "1   227936657  Power Punch Boot Camp: An All-Ages Graphic Novel      GBP   \n",
       "2   454186436        Live Printing with SX8: \"Squeegee Pulp Up\"      USD   \n",
       "3   629469071                 Lost Dog Street Band's Next Album      USD   \n",
       "4   183973060                             Qto-X, a Tiny Lantern      USD   \n",
       "\n",
       "  main_category    sub_category          launched_at             deadline  \\\n",
       "0         games  Tabletop Games  2018-10-30 20:00:02  2018-11-15 17:59:00   \n",
       "1        comics     Comic Books  2018-08-06 10:00:43  2018-09-05 10:00:43   \n",
       "2       fashion         Apparel  2017-06-09 15:41:03  2017-07-09 15:41:03   \n",
       "3         music  Country & Folk  2014-09-25 18:46:01  2014-11-10 06:00:00   \n",
       "4    technology         Gadgets  2016-11-28 16:35:11  2017-01-27 16:35:11   \n",
       "\n",
       "   duration     goal_usd        city    state country  blurb_length  \\\n",
       "0      16.0   2000.00000     Menasha       WI      US            14   \n",
       "1      30.0   3870.99771  Shepperton  England      GB            24   \n",
       "2      30.0   1100.00000   Manhattan       NY      US            21   \n",
       "3      45.0   3500.00000   Nashville       TN      US            15   \n",
       "4      60.0  30000.00000        Troy       MI      US            15   \n",
       "\n",
       "   name_length      status  start_month  end_month start_Q end_Q  usd_pledged  \n",
       "0            7  successful           10         11      Q4    Q4   6061.00000  \n",
       "1            8  successful            8          9      Q3    Q3   3914.50512  \n",
       "2            7  successful            6          7      Q2    Q3   1110.00000  \n",
       "3            6  successful            9         11      Q3    Q4   4807.00000  \n",
       "4            4  successful           11          1      Q4    Q1  40368.00000  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# viewing the first rows of the dataframe\n",
    "df_kickstarters.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We decided to add a column with the difference in goal_usd and usd_pledged."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_kickstarters = df_kickstarters.assign(goal_minus_pledge = df_kickstarters['goal_usd'] - df_kickstarters['usd_pledged'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will first take the subset of US-based kickstarters only, since other countries may have different opinions on the kinds of projects they like and that could introduce confounding variations in our analysis. So we'll use country as a control and drop projects that are not US-based."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_kickstarters = df_kickstarters[df_kickstarters['country']=='US']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We checked to see that the country and the currency are both US-only after the drop."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['US'], dtype=object)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_kickstarters.country.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['USD'], dtype=object)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_kickstarters.currency.unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We then checked to see if any cell has null values, and if so to drop those entries."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>name</th>\n",
       "      <th>currency</th>\n",
       "      <th>main_category</th>\n",
       "      <th>sub_category</th>\n",
       "      <th>launched_at</th>\n",
       "      <th>deadline</th>\n",
       "      <th>duration</th>\n",
       "      <th>goal_usd</th>\n",
       "      <th>city</th>\n",
       "      <th>...</th>\n",
       "      <th>country</th>\n",
       "      <th>blurb_length</th>\n",
       "      <th>name_length</th>\n",
       "      <th>status</th>\n",
       "      <th>start_month</th>\n",
       "      <th>end_month</th>\n",
       "      <th>start_Q</th>\n",
       "      <th>end_Q</th>\n",
       "      <th>usd_pledged</th>\n",
       "      <th>goal_minus_pledge</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>0 rows × 21 columns</p>\n",
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      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [id, name, currency, main_category, sub_category, launched_at, deadline, duration, goal_usd, city, state, country, blurb_length, name_length, status, start_month, end_month, start_Q, end_Q, usd_pledged, goal_minus_pledge]\n",
       "Index: []\n",
       "\n",
       "[0 rows x 21 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_kickstarters[df_kickstarters.isnull().any(axis=1)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We checked the unique states."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['WI', 'NY', 'TN', 'MI', 'WA', 'CA', 'IL', 'CT', 'OK', 'VA', 'AZ',\n",
       "       'MN', 'TX', 'PA', 'RI', 'MO', 'IA', 'MA', 'OH', 'CO', 'Kabul', 'FL',\n",
       "       'AK', 'MD', 'KS', 'NJ', 'LA', 'Istanbul', 'SC', 'HI', 'Vienna',\n",
       "       'IN', 'San Juan', 'NC', 'WV', 'DC', 'NE', 'UT', 'Central', 'MS',\n",
       "       'VT', 'GA', 'OR', 'AR', 'ME', 'Auvergne', 'Phnum Penh', 'SD', 'MT',\n",
       "       'AL', 'KY', 'ND', 'NV', 'Gaza', 'Shanghai', 'Siem Reap Province',\n",
       "       'Udmurtia Republic', 'Tuscany', 'ID', 'England', 'ON',\n",
       "       'DKI Jakarta', 'WY', 'NM', 'Seoul', 'NH', 'South Bohemian Region',\n",
       "       'Rajasthan', 'Santiago Metropolitan Region', 'Saitama Prefecture',\n",
       "       'Tokyo Prefecture', 'Shiga Prefecture', 'Central Kalimantan',\n",
       "       'Ã\\x98Â³Ã\\x99Â\\x88Ã\\x98Â³ Ã\\x99Â\\x80 Ã\\x99Â\\x85Ã\\x98Â§Ã\\x98Â³Ã\\x98Â© Ã\\x99Â\\x80 Ã\\x98Â¯Ã\\x98Â±Ã\\x98Â¹Ã\\x98Â©',\n",
       "       'Pirkanmaa', 'Sud', 'Beirut', 'West Bengal', 'BC', 'Satakunta',\n",
       "       'Limburg', 'Ulaanbaatar', 'Thessaly and Continental Greece',\n",
       "       'Splitsko-Dalmatinska', 'Autonomous City of Buenos Aires',\n",
       "       'Magdalena', 'Nairobi Area', 'Reykjavik', 'Guangdong', 'Veneto',\n",
       "       'Francisco MorazÃ\\x83Â¡n', 'Umbria', 'VIC', 'DE', 'Ile-de-France',\n",
       "       'Tamil Nadu', 'Kanagawa Prefecture', 'Northern Ostrobothnia',\n",
       "       'Beijing', 'Baden-Wurttemberg', 'Grand Cape Mount', 'Ha Noi',\n",
       "       'North Holland', 'Omsk Oblast', 'Otago', 'Stockholm', 'Manabi',\n",
       "       'Canterbury', 'Zaporizhia Oblast', 'Dhaka', 'Campania', 'Tel Aviv',\n",
       "       'Hovedstaden', 'Beograd', 'PotosÃ\\x83Â\\xad', 'Masovian', 'Jiangsu',\n",
       "       'Taipei City', 'Lower Silesia', 'Chungcheongnam-Do', 'Guatemala',\n",
       "       'Distrito Federal', 'Madhya Pradesh', 'Berlin', 'Hong Kong Island',\n",
       "       'Port of Spain', 'Bremen', 'Baja California Sur', 'Maharashtra',\n",
       "       'Managua', 'Rhone-Alpes', 'Kiev City Municipality', 'Ouest',\n",
       "       'Distrito Especial', 'Andalusia', 'Norrbotten',\n",
       "       'Ciudad de la Habana', 'Western Cape', 'Jerusalem',\n",
       "       'Baja California', 'Scotland', 'National Capital Region', 'Kadiogo',\n",
       "       'Puglia', 'Aragon', 'Lublin', 'Bavaria', 'NS', 'Pomeranian',\n",
       "       'Lazio', 'Ashanti', 'Lima Metropolitan Area', 'Kanungu',\n",
       "       'Moscow Federal City', 'Fukushima Prefecture', 'Lisbon',\n",
       "       'Pichincha', 'South Kivu', 'Mbale',\n",
       "       'Ã\\x98ÂªÃ\\x98Â§Ã\\x98Â¯Ã\\x99Â\\x84Ã\\x98Â© Ã\\x99Â\\x80 Ã\\x98Â£Ã\\x98Â²Ã\\x99Â\\x8aÃ\\x99Â\\x84Ã\\x98Â§Ã\\x99Â\\x84',\n",
       "       'SA', 'Western', 'RÃ\\x84Â¼ga', 'Solola', 'Brazzaville',\n",
       "       'Greater Accra', 'Oslo Fylke', 'Madrid',\n",
       "       'Capital Region of Brussels', 'Cherkasy Oblast', 'Oaxaca',\n",
       "       'Shandong', 'Primorsky Krai', 'Matagalpa', 'Kwazulu Natal',\n",
       "       'Kampala', 'Plaines Wilhems', 'West Java', 'Cairo',\n",
       "       'ChiriquÃ\\x83Â\\xad', 'Panama', 'Ljubljana', 'Minsk', 'Puebla',\n",
       "       'Austur-Hunavatnssysla', 'Bangkok', 'Yucatan', 'Galicia',\n",
       "       'Grad Zagreb', 'Lesser Poland', 'Cusco', 'Prague', 'Brakna',\n",
       "       \"Provence-Alpes-Cote d'Azur\", 'Catalonia', 'Attica', 'Bishkek',\n",
       "       'Dakar', 'Punjab', 'Gisborne', 'Batdambang', 'Skane',\n",
       "       'Saint Croix Island', 'Osaka Prefecture', 'Svalbard',\n",
       "       'Epirus and Western Macedonia', 'Zhejiang', 'Haifa', 'Cayo', 'AB',\n",
       "       'Hesse', 'Guanacaste', 'Fukui Prefecture', 'Midtjylland',\n",
       "       'Lviv Oblast', 'Uusimaa', 'Budapest', 'Tunis', 'Uttarakhand',\n",
       "       'Sichuan', 'Northern Ireland', 'Silesian', 'Arbil',\n",
       "       'Rio de Janeiro', 'Doha', 'NT', 'Chiba Prefecture', 'Peten',\n",
       "       'Rio Grande do Sul', 'Northern', 'San Jose',\n",
       "       'South Moravian Region', 'NB', 'Tak', 'Sardinia', 'Vilnius County',\n",
       "       'NSW', 'Antioquia', 'QC', 'Hamburg', 'Galway', 'Salzburg',\n",
       "       'Santa Catarina', 'Samtrediis Raioni', 'Usti nad Labem Region',\n",
       "       'Nord', 'Baghdad', 'Central Singapore', 'Aomori Prefecture',\n",
       "       'Louth', 'Lombardy', 'Agadez', 'Kyoto Prefecture', 'Arusha',\n",
       "       'Northland', 'Penang', 'Federacija Bosne I Hercegovine', 'Banghazi',\n",
       "       'Al Khartum', 'Camuy', 'Sacatepequez', 'Hiroshima Prefecture',\n",
       "       'Jalisco', 'Delhi', 'Sanma', 'Kerala', 'Khomas', 'Burgundy',\n",
       "       'Dublin', 'Vasterbotten', 'Pasco', 'Lodz', 'Canton of Zurich',\n",
       "       'Kalmar', 'Saxony', 'Aquitaine', 'Belize', 'TÃ\\x83Â³rshavn', 'QLD',\n",
       "       'Fianarantsoa', 'Canton of Basel-City', 'Saarland', 'Antananarivo',\n",
       "       'Mexico', 'Karnataka', 'Uttar Pradesh', 'Constanta', 'Piedmont',\n",
       "       'KecskemÃ\\x83Â©t', 'Isle of Man', 'Quetzaltenango', 'Azuay',\n",
       "       'Durango', 'San Martin', 'Sonora', 'SK', 'East',\n",
       "       'Distrito Nacional', 'Central Visayas', 'Okinawa Prefecture',\n",
       "       'TÃ\\x82Â´bilisi', 'Saint George', 'Tungurahua', 'Piaui', 'Shanxi',\n",
       "       'Ã\\x99Â\\x85Ã\\x98Â±Ã\\x98Â§Ã\\x99Â\\x83Ã\\x98Â´ Ã\\x99Â\\x80 Ã\\x98ÂªÃ\\x98Â§Ã\\x99Â\\x86Ã\\x98Â³Ã\\x99Â\\x8aÃ\\x99Â\\x81Ã\\x98Âª Ã\\x99Â\\x80 Ã\\x98Â§Ã\\x99Â\\x84Ã\\x98Â\\xadÃ\\x99Â\\x88Ã\\x98Â²',\n",
       "       'Nordur-Mulasysla', 'Amman', 'Calabria', 'Bucuresti', 'Erongo',\n",
       "       'Basque Country', 'Western Area', 'Jinja', 'Cabo Rojo',\n",
       "       'Himachal Pradesh', 'Sicily', 'Emilia Romagna', 'Kharkiv Oblast',\n",
       "       'Saint Petersburg Federal City', 'Ho Chi Minh', 'Brittany',\n",
       "       'Sikkim', 'West Pomeranian', 'Alta Verapaz', 'Brandenburg',\n",
       "       'Lower Austria', 'LeÃ\\x83Â³n', 'Skagafjaryarsysla',\n",
       "       'Santiago del Estero', 'Piran', 'MÃ\\x83Â©rida', 'Western Visayas',\n",
       "       'Karelia Republic', 'Champagne-Ardenne', 'Sharjah', 'Opole', 'Puno',\n",
       "       'Kiev Oblast', 'Preah Vihear', 'Sao Paulo', 'Valencia', 'PE',\n",
       "       'Houet', 'La Paz', 'Madang', 'Agana', 'West-Vlaanderen', 'Liguria',\n",
       "       'Jammu and Kashmir', 'Yona', 'Auckland Region', 'Toyama Prefecture',\n",
       "       'Wangdue Phodrang', 'Hovsgol', 'Chiang Mai', 'Bratislavsky',\n",
       "       'Udon Thani', 'Nuevo Leon', 'Bali', 'Los Lagos Region', 'ACT',\n",
       "       'Nassarawa', 'Goias', 'NevÃ\\x85Â\\x9fehir', 'Salta', 'Islamabad',\n",
       "       'Hsinchu City', 'Marche', 'Canton of Vaud', 'Shizuoka Prefecture',\n",
       "       'Al Mafraq', 'Gauteng', 'Oost-Vlaanderen', 'Michoacan de Ocampo',\n",
       "       'Culebra', 'Rumphi', 'Rift Valley', 'Tombouctou', 'Ceara',\n",
       "       'San Salvador', 'Dar es Salaam', 'Limon', 'Chongqing',\n",
       "       'Pointe-Ã\\x83Â\\x80-Pitre', 'Odessa Oblast', 'Tamuning',\n",
       "       'Republika Srpska', 'Kigali Province', 'Kinshasa', 'Navarre',\n",
       "       'Cochabamba', 'Skofja Loka', 'Canton of Geneva', 'National Capital',\n",
       "       'Kuala Lumpur', 'Murcia', 'Nayarit', 'Canton of Berne',\n",
       "       'Yamagata Prefecture', 'Hebei', 'Yangon', 'West',\n",
       "       'Hyogo Prefecture',\n",
       "       'Peloponnese Western Greece and the Ionian Islands', 'Gavleborg',\n",
       "       'South Karelia', 'Poitou-Charentes', 'Juzhna Bachka',\n",
       "       'Aichi Prefecture', 'Midwest', 'Finland Proper', 'Vastra Gotaland',\n",
       "       'San Marcos', 'Vestgronland', 'Bamako', 'Chalan-Pago-Ordot',\n",
       "       'Santa Cruz', 'Canton of Neuchatel', 'Nordjylland', 'Sipaliwini',\n",
       "       'Sakha Republic', 'Saint Michael', 'North Rhine-Westphalia',\n",
       "       'Aegean', 'Northern Cape', 'Kayseri', 'Jeollanam-Do', 'Ovorhangay',\n",
       "       'NU', 'Saint Mary', 'Sor-Trondelag', 'Malta Xlokk', 'Lagunes',\n",
       "       'Vratsa', 'Halland', 'Utrecht', 'Groningen', 'Jiangxi', 'Timis',\n",
       "       'Gabrovo', 'Kankan', 'Fujian', 'Yerevan', 'Aguascalientes',\n",
       "       'Santa Fe', 'TAS', 'Andhra Pradesh', 'Warmian-Masurian',\n",
       "       'MayagÃ\\x83Â¼ez', 'Mykolaiv Oblast', 'Troms Fylke', 'Guangxi',\n",
       "       'Montevideo', 'East Java', 'Perak', \"Qacha's Nek\", 'Daegu',\n",
       "       'Saint Thomas Island', 'Uppsala', 'Okavango', 'Tehran',\n",
       "       'Pays de la Loire', 'Antwerp', 'Coamo', 'Liege', 'Eastern Visayas',\n",
       "       'Grenadines', 'Demerara-Mahaica', 'PÃ\\x82Â´yongyang-si', 'Wales',\n",
       "       'Cartago', 'Ternopil Oblast', 'Shumadija', 'Bolivar', 'Guerrero',\n",
       "       'Centre', 'Nicosia District', 'Shefa', 'Koper', 'Kuiavia-Pomerania',\n",
       "       'Cauca', 'NL', 'Miyagi Prefecture', 'Quang Nam', 'Nordland Fylke',\n",
       "       'Luxemburg', 'Tripura', 'Centro Sur', 'MB', 'Coast', 'Pchinja',\n",
       "       'Velenje', 'Special Region of Yogyakarta', 'Granada', 'Aqtobe',\n",
       "       'Saga Prefecture', 'Ankara', 'Daejon', 'Sofiya-Grad',\n",
       "       'Kabardino-Balkaria Republic', 'Mae Hong Son', 'Puntarenas',\n",
       "       'Addis Ababa', 'Kasese', 'South Holland',\n",
       "       'Islas de la BahÃ\\x83Â\\xada', 'Hradec Kralove Region', \"Ha'apai\",\n",
       "       'Prachuap Khiri Khan', 'Sjaelland', 'Balearic Islands',\n",
       "       'Kaliningrad Oblast', 'Hordaland Fylke', 'Hokkaido Prefecture',\n",
       "       'Ajaria', 'Paktia', 'Mandalay', 'Kilimanjaro', 'Amazonas',\n",
       "       'Chiapas', 'Tainan City', 'Languedoc-Roussillon', 'Sibiu',\n",
       "       'Minas Gerais', 'Tuva Republic', 'Gulu', 'Zacapa',\n",
       "       'Nord-Pas-de-Calais', 'Aisen Region', 'Guelders', 'Thimphu',\n",
       "       'Chimaltenango', 'Banjul', 'Lagos', 'Hhohho', 'Nova Gorica',\n",
       "       'Tokushima Prefecture', 'Dubai', 'Tsarrbuus', 'State of Kosrae',\n",
       "       'Imbabura', 'Karategin', 'Eastern', 'ColÃ\\x83Â³n', 'Quintana Roo',\n",
       "       'Hormozgan', 'West Bank', 'Ruvuma',\n",
       "       'Ã\\x98Â·Ã\\x99Â\\x86Ã\\x98Â¬Ã\\x98Â©Ã\\x99Â\\x80 Ã\\x98ÂªÃ\\x98Â·Ã\\x99Â\\x88Ã\\x98Â§Ã\\x99Â\\x86',\n",
       "       'Guanajuato', 'Gyeongsangbuk-Do', 'Dahuk', 'Parana', 'Cork',\n",
       "       'Southern', 'Mimaropa', 'Erzincan', 'Eastern Cape', 'Hadramawt',\n",
       "       'Tafea', 'Kranj', 'Asturias', 'Aizputes Novads', 'Davao Region',\n",
       "       'Guaynabo', 'North Brabant', 'Bahia', 'Kampot', 'Canary Islands',\n",
       "       'Piura', 'Conakry', 'Gansu', 'New Providence', 'Jonglei',\n",
       "       'Castelo Branco', 'Chinandega', 'Tyrol', 'Clare', 'Midi-Pyrenees',\n",
       "       'Romana', 'Tianjin', 'Hedmark Fylke', 'Donegal', 'Dimashq',\n",
       "       'Puducherry', 'Murmansk Oblast', 'Louangphabang', 'Orissa',\n",
       "       'Safaqis', 'Puerto Plata', 'La Guajira', 'Maribor', 'Thuringia',\n",
       "       'Cluj', 'Salinas', 'Styria', 'Toamasina', 'Sud-Est', 'Brasov',\n",
       "       'Eyjafjardarsysla', 'Canton of Zug', 'Flacq', 'Chihuahua',\n",
       "       'Kyeongki-Do', 'Lusaka', 'Greater Poland', 'Anhui', 'Suceava',\n",
       "       'Lendava', 'CortÃ\\x83Â©s', 'Saint Andrew', 'Trzic', 'Lapland',\n",
       "       'EstelÃ\\x83Â\\xad', 'Kilkenny', 'Arunachal Pradesh', 'Jharkhand',\n",
       "       'Monrovia', 'Antalya', 'Seydisfjordur', 'Aveiro', 'Qinghai',\n",
       "       'Porto', 'Wellington', 'Taichung City', 'Kochi Prefecture',\n",
       "       'Mari El Republic', 'Pilsen Region', 'Tindouf', 'Pouthisat',\n",
       "       'Holguin', 'Cordoba', 'Chiang Rai', 'Toledo', 'Sinaloa',\n",
       "       'AsunciÃ\\x83Â³n', 'Alexandria', 'Krabi', 'Ã\\x84Â°zmir',\n",
       "       'Swietokrzyskie', 'Veracruz-Llave', 'Lower Saxony', 'Orellana',\n",
       "       'Harare', 'Sabah', 'Paro', 'Upper Austria', 'Kerry', 'Lilongwe',\n",
       "       'Araucania Region', 'Upper Normandy', 'Coahuila de Zaragoza',\n",
       "       'Saint John Island', 'Sud-Ouest', 'Yaroslavl Oblast', 'Domzale',\n",
       "       'Morelos', 'Gujarat', 'Kolubara', 'Vysocina Region', 'Zhambyl',\n",
       "       'Mures', 'Krasnoyarsk Krai', 'Loreto', 'Saint James', 'Leiria',\n",
       "       'Al `Asimah', 'Chisinau', 'Yunnan', 'Busan', 'Tipperary', 'Gurabo',\n",
       "       'State of Pohnpei', 'Mashonaland East', 'Vastmanland', 'Rasina',\n",
       "       'Rhineland-Palatinate', 'Abu Dhabi', 'Vorarlberg',\n",
       "       'ComerÃ\\x83Â\\xado', 'Sisaket', 'Almaty', 'Valle del Cauca',\n",
       "       'Corozal', 'Tolima', 'Carabobo', 'Sindh', 'Pathum Thani',\n",
       "       'Yamaguchi Prefecture', 'Huila', 'Bihar', 'Cundinamarca',\n",
       "       'Ohrid Municipality', 'Guayas', 'Lower Normandy',\n",
       "       'Magallanes and Antartica Chilena Region', 'Saxony-Anhalt', 'Fars',\n",
       "       'Littoral', 'Barbuda', 'Santiago de Cuba', 'Valparaiso Region',\n",
       "       'Mangochi', 'Central Luzon', 'Tierra del Fuego', 'Saint Catherine',\n",
       "       'Zulia', 'Bjelovarsko-Bilogorska', 'Kumamoto Prefecture', 'Ninawa',\n",
       "       'Nord-Ouest', 'Dnipropetrovsk Oblast', 'Rio Negro', 'Fajardo',\n",
       "       'Phuket', 'Tochigi Prefecture', 'Vieux Fort', 'Caguas', 'Gand Turk',\n",
       "       'Tongatapu', \"Hawke's Bay\", 'Dalarna', 'Quindio',\n",
       "       'Queretaro de Arteaga', 'Tamaulipas', 'Alsace', 'Oita Prefecture',\n",
       "       'Napo', 'Surat Thani', 'Mato Grosso do Sul', 'Relizane', 'Izola',\n",
       "       'Esmeraldas', 'Quiche', 'Niigata Prefecture', 'Windward Islands',\n",
       "       'Alajuela', 'CuscatlÃ\\x83Â¡n', 'Bulawayo', 'La Libertad',\n",
       "       'KoprivniÃ\\x84Â\\x8dko-kriÃ\\x85Â¾evaÃ\\x84Â\\x8dka', 'Al Anbar',\n",
       "       'Adjuntas', 'Yukon Territory', 'Vega Baja', 'Nong Khai',\n",
       "       'Zanzibar West', 'Galapagos', 'Limerick', 'North-West', 'Masaka',\n",
       "       'Eastern Tobago', 'Podlaskie', 'Chaguanas',\n",
       "       'Central Bohemian Region', 'SÃ\\x83Â£o Filipe', 'Dededo',\n",
       "       'Ã\\x98Â§Ã\\x99Â\\x84Ã\\x98Â±Ã\\x98Â¨Ã\\x98Â§Ã\\x98Â·-Ã\\x98Â³Ã\\x99Â\\x84Ã\\x98Â§-Ã\\x98Â²Ã\\x99Â\\x85Ã\\x99Â\\x88Ã\\x98Â±-Ã\\x98Â²Ã\\x98Â¹Ã\\x99Â\\x8aÃ\\x98Â±',\n",
       "       'Heredia', 'Jayuya', 'AÃ\\x83Â±asco', 'Andaman and Nicobar Islands',\n",
       "       'Haryana', 'Rakhine State', 'Mwanza', 'Ogun', 'Rivas',\n",
       "       'Vinnytsia Oblast', 'Heilongjiang', 'Estuaire', 'Djibouti',\n",
       "       'Shaanxi', 'Presovsky', \"Vava'eu\", 'Castille la Mancha', 'Kigoma',\n",
       "       'Crimea', 'Tuamasaga', 'Luhansk Oblast', 'Utuado',\n",
       "       'Leeward Islands', 'Choco', 'Cidra', 'Da Nang', 'Brong-Ahafo',\n",
       "       'Radovljica', 'Canton of Valais', 'Risaralda', 'Ancash', 'Salto',\n",
       "       'Caldas', 'Incheon', 'Basilicata', 'Quang Tri', 'Arecibo', 'Yigo',\n",
       "       'Friuli-Venezia Giulia', 'Harari', 'RÃ\\x83Â\\xado Grande', 'Para',\n",
       "       'Cayey', 'Irkutsk Oblast', 'Nyanza', 'Canton of Ticino', 'Kano',\n",
       "       'Subcarpathia', 'Ibaraki Prefecture', 'Rarotonga', 'Jaeju-Do',\n",
       "       'Chittagong', 'Tomsk Oblast', 'Phu Tho', 'El Beni', 'Neamt',\n",
       "       'Kherson Oblast', 'Barrigada', 'Constantine', 'Azores', 'Khon Kaen',\n",
       "       'Rostov Oblast', 'La Altagracia', 'Lao Cai', 'Olomouc Region',\n",
       "       'Rivne Oblast', 'Carolina', 'Chungcheongbuk-Do', 'Mopti',\n",
       "       'Putumayo', 'Atlantico', 'Grand Bassa', 'Quebradillas'], dtype=object)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_kickstarters['state'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are still many entries that are NOT US states, so we will clean that up so it only contains US states."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "def check_state(state_abbrv):\n",
    "    lst_states = ['AK', 'AL', 'AR', 'AS', 'AZ', 'CA', 'CO', 'CT', 'DE', 'FL', 'GA', 'GU', 'HI', 'IA', 'ID', 'IL', 'IN', 'KS', 'KY', 'LA', 'MA', 'MD', 'ME', 'MI', 'MN', 'MO', 'MP', 'MS', 'MT', 'NC', 'ND', 'NE', 'NH', 'NJ', 'NM', 'NV', 'NY', 'OH', 'OK', 'OR', 'PA', 'RI', 'SC', 'SD', 'TN', 'TX', 'UM', 'UT', 'VA', 'VI', 'VT', 'WA', 'WI', 'WV', 'WY']\n",
    "    if state_abbrv in lst_states:\n",
    "        return state_abbrv\n",
    "    else:\n",
    "        return 'X'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_kickstarters['state'] = df_kickstarters['state'].apply(check_state)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_kickstarters = df_kickstarters[df_kickstarters['state']!='X']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "50"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# checking to see only 50 states\n",
    "len(df_kickstarters['state'].unique())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We found no null values in the dataset, and so we proceeded with data cleaning."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We first dropped the column 'id' since it gives no useful information, just an ID associated with the project. We then dropped columns 'start_month' and 'end_month' since the information about the start and end months of the projects are already given in the dates in the 'launched_at' and 'deadline' columns and so is redundant. We checked to see that the country and currency are all US-based, so it would not be necessary to keep those columns."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_kickstarters.drop(columns=['id', 'country', 'currency'], inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, we noticed some of the monetary amounts have more than 2 decimal places, which should be cleaned up since we don't work with monetary amounts more specific than 2 decimal places. So we decided to round the amounts to 2 decimal places."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_kickstarters['goal_usd'] = df_kickstarters['goal_usd'].round(2)\n",
    "df_kickstarters['usd_pledged'] = df_kickstarters['usd_pledged'].round(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data visualization"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Since our project aims to analyze which factor is most important for the success of kickstarters, we will divide the dataframe into two separate ones, one with all the successful projects and one with all the failed projects."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# divides df_kickstarters into successful and failed ones\n",
    "df_successful = df_kickstarters[df_kickstarters['status']=='successful']\n",
    "df_failed = df_kickstarters[df_kickstarters['status']=='failed']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We next plotted the categories to see which ones are more likely to be successful."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plot histogram of the amount of projects among all the main_category\n",
    "plt.figure(figsize=(20,8))\n",
    "axPlt = sns.countplot(x='main_category',data=df_kickstarters)\n",
    "\n",
    "for i in axPlt.patches:\n",
    "    # get_x pulls left or right; get_height pushes up or down\n",
    "    axPlt.text(i.get_x()+.18, i.get_height()+150, \\\n",
    "            str(round((i.get_height()), 2)), fontsize=11)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Grouping by status:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,10))\n",
    "ax = sns.countplot(x='main_category',hue='status',data=df_kickstarters)\n",
    "\n",
    "for i in ax.patches:\n",
    "    # get_x pulls left or right; get_height pushes up or down\n",
    "    ax.text(i.get_x(), i.get_height()+100, \\\n",
    "            str(round((i.get_height()), 2)), fontsize=11)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It seems that there are unequal numbers of successful and failed projects; to confirm we'll take a look at how many successful and failed kickstarters there are."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of successful kickstarters: 80965\n",
      "Number of failed kickstarters: 50231\n"
     ]
    }
   ],
   "source": [
    "# views number of successful and failed kickstarters\n",
    "print(\"Number of successful kickstarters: \" + str(len(df_successful))); print(\"Number of failed kickstarters: \" + str(len(df_failed)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It seems that there are different numbers of successful and failed kickstarters; we will account for that by comparing the ratio of each category in the successful versus failed kickstarters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fa985931390>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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VJEmSJElSLcyaNatnlVVWmb/WWmvNmz17dtePfvSjtUd7z/bbb//MAw88MPaqq65abWjaddddt/LAwAA77rjj09dee+3qDz/8cC/AeeedN2p7nWbPOkmSJEmSJNXC7rvvPuviiy9ea9ddd504bty4/le+8pXP3XbbbauM9J4111xz/oknnvinL3/5yxscf/zxPfPmzeuaMGHCnLPOOutPW2211d8PPPDAh975zne+cs0115z7+te/ftbSWpZFZbFOkiRJkiRpBdc/d/68i6fu3fY6Uf/c+fP6xvSMOt+FF174jyGsp5566t3N5pkyZcrTU6ZMuR1g44037v/DH/5w89Br22677XONbTQ66KCDHj3ooIMeHXp+2GGHzVyIRVjqLNZJkiRJkiSt4PrG9Nw8+lyL1O6SaHa55jXrJEmSJEmSpJqwWCdJkiRJkiTVhMU6SZIkSZIkqSYs1kmSJEmSJEk1YbFOkiRJkiRJqgnvBitJkiRJkrSCG5jXv1V3b1/b60QD8/rndff2LZE7zS6vLNZJkiRJkiSt4Lp7+3rvPvYdbW93k6OmLVe1pzvvvHPsoYce+nKAAw44YOZ+++33t1bz7rTTTlt84xvfuGuLLbaYvTCfsVwlTJIkSZIkSVpSLrnkkpdMnDjxmRNOOOG+JfUZFuskSZIkSZLUMc8++2z3oYceutG99967Uk9Pz+CGG244e6eddpr1y1/+cvVvf/vbdwOcffbZazU+nzp16vjLL798za6uLlZaaaWBadOm3dHT08NZZ5211ve///2XAowZM2bw9NNPv2v8+PHzLr300tVPPfXUCf39/V1jxowZPOKII+7ffvvtn73jjjvGHn744RvPnj27e2BgoGvPPfd87NBDD334Jz/5yRonnXTSut3d3cyfP7/rqKOOuu+hhx4ac/755790cHCQ3XfffdWTTjrpz+973/s2a+w9t6i96RpZrJMkSZIkSVLH/PznP3/x008/3XvFFVf8EeBvf/tbzyWXXLJGq/nPOeectX71q1+tccEFF9yx+uqrDzz22GM9PT09XH311audccYZE84999w7JkyYMO/pp5/u7u3tHfzTn/409pRTTplw9tln37n66qsPzJgx40UHHXTQpr/97W9vPeuss9bZYYcdZh1++OEPDX02wMknn7zuZz/72fve8IY3PDNv3jyeffbZ7ilTpgzce++9L3ruuee6jznmmL8uqXxYrJMkSZIkSVLHbLHFFs99+ctfftGnPvWpDbfbbrun99hjj1kjzf/LX/5y9X333ffR1VdffQBg7bXXng9w5ZVXrr777rs/PmHChHkAq6222kA5/cUPPfTQ2He+852vHGpj/vz5XTNnzuydPHny01/72tc2mDt3btcOO+zw9JQpU54GmDRp0tMnnHDCBjfccMPfdtlll1mL01NuYXUvrQ+SJEmSJEmShnv5y1/ef9lll83Ycccdn/rd73734re+9a2b9/b2Dg4ODnYNzTNnzpx/1LAGBwebtjPS9MmTJ8+67LLLbhv6d+21194yfvz4eW9/+9ufPO+88+7YcMMN55x22mnjP/rRj24McNxxx91/7LHH3jtmzJjBj3/84y//zne+s3aztnt6egYHBgb+EWd/f/9i19os1kmSJEmSJKlj7r///jE9PT3svffeTx5zzDH3z5o1q3fDDTecc/fdd680e/bsrjlz5nRdccUVLxmaf8qUKbMuuOCCcU899VQ3wGOPPdYDsMsuuzx52WWXrTVz5sxegKeffrp79uzZXTvvvPNT119//eozZsx40VAb11133coAd91119jx48fPPeCAAx4/+OCDH7z99ttXAbjjjjvGbrnlln8/+OCDH9l9990fv/XWW1dpFvuECRPm3HjjjasA/OIXv1jtySefXOxRrA6DlUYxMLefTY6a1ukwXmBgbj/dY/o6HYYkSZIkaTkwMK9/3iZHTWt7nWhgXv+87t6Rf7vOmDFjpa9//evrAwwMDHTtv//+M3fcccdnJ02a9NTuu+/+6gkTJszZaKON/v7YY4+NAXjPe97z+MMPPzzmHe94x6u6u7sHV1555fkXXnhhTpky5ZkDDzxw5gEHHLBZV1cXfX19g6eddtpdm2222ZwvfvGL9xx55JEbzZkzp3vevHldW2yxxTPbbrvtXy666KKXXH755Wv19vYOdnV1DX7605++D+BLX/rS+n/9619f1NPTM7jqqqvOP/744+9tFvsnPvGJB4488siNf/jDH6695ZZbPjNu3Lj+xc2ZxTppFN1j+tjrsIs6HcYLXDx1706HIEmSJElaTnT39t28hNoddZ499tjjqT322OO24dOnTp16X9M2u7v55Cc/OfOTn/zkzOGvHXjggY8deOCBjw2fvttuuz212267PTV8eqt2zjjjjD83++zPfOYzDzY+33bbbZ8bujFG6R83nvj1r399a7M2RuMwWEmSJEmSJKkmLNZJkiRJkiRJNWGxTpIkSZIkacUz2OruqVqyyrwPtHrdYp0kSZIkSdIKpqura1Z/f/+YTsexIurv7x/T1dU1q9XrFuskSZIkSZJWMPPnzz/jwQcfXGVgYKCr07GsSAYGBroefPDBVefPn39mq3m8G6wkSZIk1cDA3H42OWpap8NYwMDcfrrHjH4nR0nLnoGBgW8+9dRTW9966607Aj2djmcFMh/4zcDAwDdbzWCxTpIkSZJqoHtMH3sddlGnw1jAxVP37nQIkpaQSZMm9QP/1uk49EIOg5UkSZIkSZJqwmKdJEmSJEmSVBMW6yRJkiRJkqSasFgnSZIkSZIk1YTFOkmSJEmSJKkmLNZJkiRJkiRJNWGxTpIkSZIkSaoJi3WSJEmSJElSTViskyRJkiRJkmqit8pMEbEZcBawFvA4cEBm3tVi3gBuBL6RmZ9sV6CSJEmSJEnS8q5qz7pvASdn5mbAycApzWaKiJ7ytR+3JzxJkiRJkiRpxTFqsS4i1gG2Bs4tJ50LbB0R45rMfgRwCXBn2yKUJEmSJEmSVhBVetZtADyQmfMByv8fLKf/Q0RsCbwZ+Fq7g5QkSZIkSZJWBJWuWTeaiBgDnAa8LzPnF5etW3gzZsxoRzhMmjSpLe202/Tp0zsdwgLMUzV1zROYq6rMUzV1yxOYq6rMUzV1zROYq6rMUzV1yxOYq6rMUzV1zROYq6rMUzV1y5OWnirFuvuB9SKipyzE9QDrltOHTABeDlxaFurWALoi4sWZ+cGqwUycOJGxY8dWj76Fgbn9bHLUtMVup50G5vbXdgdQN+apOnNVjXmqxjxVZ66qMU/VmatqzFM15qk6c1WNearOXFVjnqppR57mzJnTto5RWnpGLdZl5iMRcROwH/Dd8v8bM/PRhnnuA9Yeeh4RRwOrdupusN1j+tjrsIs68dEtXTx1706HIElaTtX1JFX3mL5OhyFJkiQtc6oOg/0QcFZEfB54AjgAICIuBT6fmX9YQvFJkqRReJJKkiRJWn5UKtZl5h3Adk2mv6XF/EcvXliSJEmSJEnSiqfK3WAlSZIkSZIkLQUW6yRJkiRJkqSasFgnSZIkSZIk1YTFOkmSJEmSJKkmLNZJkiRJkiRJNWGxTpIkSZIkSaoJi3WSJEmSJElSTfR2OgBJkloZmNvPJkdN63QYCxiY20/3mL5OhyFJkiRpOWWxTpJUW91j+tjrsIs6HcYCLp66d6dDkJY4C+WSJEmdY7FOkiRJC7BQLkmS1Dles06SJEmSJEmqCYt1kiRJkiRJUk1YrJMkSZIkSZJqwmKdJEmSJEmSVBPeYEKSljLvsihJkiRJasVinSQtZd5lUZIkSZLUisNgJUmSJEmSpJqwWCdJkiRJkiTVhMU6SZIkSZIkqSYs1kmSJEmSJEk1YbFOkiRJkiRJqgmLdZIkSZIkSVJN9HY6AEmSJEnLt4G5/Wxy1LROh7GAgbn9dI/p63QYkiS9gMU6SZIkSUtU95g+9jrsok6HsYCLp+7d6RAkSWrKYbCSJEmSJElSTdizTpIkSZIkrbAcqq+6sVgnSZIkSZJWWA7VV904DFaSJEmSJEmqCYt1kiRJkiRJUk1YrJMkSZIkSZJqwmKdJEmSJEmSVBPeYEKSJEmStMyo4507wbt3Smofi3WSJEmSpGVGHe/cCd69U1L7OAxWkiRJkiRJqgmLdZIkSZIkSVJNWKyTJEmSJEmSasJinSRJkiRJklQTFuskSZIkSZKkmrBYJ0mSJEmSJNWExTpJkiRJkiSpJizWSZIkSZIkSTVhsU6SJEmSJEmqCYt1kiRJkiRJUk30VpkpIjYDzgLWAh4HDsjMu4bN8zngXcC88t+RmXl5e8OVJEmSJEmSll9Ve9Z9Czg5MzcDTgZOaTLPdcDkzNwKeD9wfkSs1J4wJUmSJEmSpOXfqMW6iFgH2Bo4t5x0LrB1RIxrnC8zL8/M58qntwBdFD3xJEmSJEmSJFVQpWfdBsADmTkfoPz/wXJ6KwcAf87Mvy5+iJIkSZIkSdKKodI16xZGRLwROAZ408K+d8aMGW2JYdKkSW1pp92mT5/e6RAWYJ6qqWuewFxVZZ6qqVuewFxVZZ6qqWuewFxVZZ6qqVuewFxVZZ6qqWuewFxVZZ6qqVuetPRUKdbdD6wXET2ZOT8ieoB1y+kLiIjtge8Ce2dmLmwwEydOZOzYsQv7tmVGXXcAdWOeqjNX1ZinasxTdeaqGvNUnbmqxjxVY56qM1fVmKfqzFU15qmaduRpzpw5besYpaVn1GGwmfkIcBOwXzlpP+DGzHy0cb6ImAycD+yTmTe0O1BJkiRJkiRpeVd1GOyHgLMi4vPAExTXpCMiLgU+n5l/AL4BrAScEhFD79s/M29tb8iSJEmSJEnS8qlSsS4z7wC2azL9LQ2PJ7cxLkmSJEmSJGmFU+VusJIkSZIkSZKWAot1kiRJkiRJUk1YrJMkSZIkSZJqwmKdJEmSJEmSVBMW6yRJkiRJkqSasFgnSZIkSZIk1URvpwNQ5wzM7WeTo6Z1OowFDMztp3tMX6fDkCRJkiRJ6giLdSuw7jF97HXYRZ0OYwEXT9270yFIkiRJkiR1jMNgJUmSJEmSpJqwWCdJkiRJkiTVhMU6SZIkSZIkqSa8Zp2ktvGmJZIkSZIkLR6LdZLaxpuWSJIkSZK0eBwGK0mSJEmSJNWExTpJkiRJkiSpJizWSZIkSZIkSTVhsU6SJEmSJEmqCYt1kiRJkiRJUk1YrJMkSZIkSZJqwmKdJEmSJEmSVBMW6yRJkiRJkqSasFgnSZIkSZIk1YTFOkmSJEmSJKkmLNZJkiRJkiRJNWGxTpIkSZIkSaoJi3WSJEmSJElSTViskyRJkiRJkmrCYp0kSZIkSZJUExbrJEmSJEmSpJqwWCdJkiRJkiTVhMU6SZIkSZIkqSYs1kmSJEmSJEk1YbFOkiRJkiRJqgmLdZIkSZIkSVJNWKyTJEmSJEmSasJinSRJkiRJklQTFuskSZIkSZKkmrBYJ0mSJEmSJNWExTpJkiRJkiSpJizWSZIkSZIkSTVhsU6SJEmSJEmqCYt1kiRJkiRJUk1YrJMkSZIkSZJqorfKTBGxGXAWsBbwOHBAZt41bJ4e4ERgd2AQOD4zT29vuJIkSZIkSdLyq2rPum8BJ2fmZsDJwClN5nkP8ApgU2B74OiI2KgdQUqSJEmSJEkrglF71kXEOsDWwJvKSecCJ0XEuMx8tGHWdwKnZeYA8GhE/BjYFzihQhw9AP39/QsT+4jWWKWnbW21w5w5czodQlPmqZq65QnMVVXmqZq65gnMVVXmqZq65QnMVVXmqZq65gnMVVXmqZq65QnMVVXmqZp25amhzlKvBdSIugYHB0ecISImAWdn5qsbpt0GvDczb2iYdivw/sy8vnz+aWD9zPzYaEFMnz59R+DXi7YIkiRJkiRJGsFOkyZN+k2ng1A1la5ZtxRcD+wEPATM73AskiRJkiRJy4MeYAJF3UXLiCrFuvuB9SKiJzPnlzeSWLec3ug+4GU8vwJsCPylShCTJk2aA1jhlSRJkiRJaq8/dzoALZxRbzCRmY8ANwH7lZP2A24cdr06gAuA/4iI7ogYB/wzMK2dwUqSJEmSJEnLs6p3g/0QcEhE3AkcUj4nIi6NiG3Kec4B7gZq/X5TAAAYsElEQVTuAq4FvpCZd7c5XkmSJEmSJGm5NeoNJiRJkiRJkiQtHVV71kmSJEmSJElawizWSZIkSZIkSTVhsU6SJEmSJEmqCYt1kiRJkiRJUk1YrFsIEfHPEbFtp+NYFkTE2yLihE7HUVcR0VfeTfmWiPhaREyJiN06HdeSFBGDEbFqp+Oos0XN0fK6vZX73Nsj4saIiIV879ER8ZUWr30oIj7Rnijba/gyR8RNEbFS+dq9ETGxDZ/xurLdWyLiuoh4ySK2c2lEvLzFa1dHxJ6LF+nStzjrXIv2Wq6HWjY0boMdjuMf239EnB4RO3U6prqKiC9ExDs7HUczi/I9HxEbRcQHl1RMi6Ku+/gyV49VeW20bXuUttaNiKsWP+JFV36/9C3G+8+MiI+2Oaa2HKd0SmNOl1B+FutvphVPb6cDWFZERA/wz8AfgOs6HE7tZeZPgJ90Oo5OiYjezJw3wiyvBV6Wma8u5z8aWBX4v6UQnpYzy/H2dhDw+cy8oJ2NZua32tlemw1f5tcsgc/4GvBfmXlRRKwHzF6URjLzLe0NqxaWyDqnZVdmtm0bjIiezJy/uO1k5gfaEc/yKjM/3+kY2mwj4IPAqe1stMKx6nJtcbbtzHwQ2LmN4SyK/wK+AvR3OI7lyZLO6SK1v6Jvqysyi3VARHwPCGAs8Cfg/cBWwNeBXwOTgf8B3gbsGhEfAL6amWd3JuL2iYjtgROA1cpJnwKeAE4EVgGeBT6WmddHxEYUxcrTgN2BlYD3AB8CtgP+DuydmTMj4kBgz8zcp/yc9wOHlp/RD+wJDALfB15aTr8iM2vZ22W4Fnk7Ffg28E/A3RFxFHAu8GLgRcBPM/PTZW+N7wHrRsRNwI8octgdEbsC5wHfYRnNzZCIeDtwHPA34NKG6S/Y3jLziYiYQrHN/R7YnmL9eFdm3l6+7wXrUGY+HBFvAY6iyHE/8InMvHbJL+HiGyFH2wHHU6w7UBQPfhoR69BkvWiyvR0LvBN4HLga2CUztxktx3USEV8DdioexkeAB2m+3gRwJrAy0AOcmZlDPZnWi4hLgU2APwP7ZuZzQ8XxzPxkeSLmSxT7NIDLgMMzc35EnElRyNoM2AC4Bvi3zBxcGsucmTtHxCCwWmY+M2zeq4HpwLYUP+T+H/AAcAiwLvCpEQpOs4GNATLzgVFiugvYJzNvLp8fAmydme+LiHsp1rsZEbE5cAYwBriNYnscamMC8L/AhhTfG+dm5nHla5Np8n0zcqaWjCbr3Jcovvt7gEeBgzLzT+W8hwP7l2+9HjgkM5+JiNUpvgc2B+4r3/fwUl2QNouIdwDHUnzHX1A+Xg04hdb78v9HcWLzdcBcilz9FzARuB94e2Y+W/YwOBZ4I9AH3Ap8uMzlB4FPAHMoRoL8a2besVQWusHQNgi8iubHRlOAr2TmNuX8/3jesM8dOpb8YkTsQ4v9SkS8m+J7bqjnxScz8xdNYrq6/IxLWuWp3D6/C+wCrAccAawDvBtYE3hfZv66TWlaaGVeP0txInwt4D+AXSn2xWMo9te3N/l++8fziNgBOIliuccAX8zMc8t99x8y86RyHTuubHc+cHdm/stSWLb/BnYrl+3IzJzWMMvHIuJfytc+NfRaROxO833OycDG5THjn8plb7nvLHsDHQo8SXFscXBmrt1wHH8SRa6/W+7jv0ixz+4Fjs3M88p2rgZuojhptD7wg8w8smE53hgRR1B85/wgM48o4zojM//RuyoibqbYrn/XjjwOLUdmrl3Ot8DzctpXgDdQfOd8pNm63rBtP1fm5J8otqNnMvP1DfMdC7yF4jjj3zPzN01iGKQ4Fm32d226Dx3+vb6QuTm5fPi7iBig+I36eWBLir/lVcB/lscy61GsK5uW7zk3M/+nfDwxIq7khfuiM2m9n3op8C3g5UAXcEKz38QR8QqK74lxwDyKv99lI+UE+AiwYWZ+tJzvpcAtwMaZ+dyi5quKJjm9l9b5eTHwVZrn+zDgXRTb02yKdf+mJu1PAQZGaOdq4HcUv7FnA29dksuvenIYbOHQzNwmM7cA/ggcXk7fAvh+Zr4uMy+i6LlyfGa+Zjkp1K1JUSj6dGZuBWwN3AxMAz6XmVtSHEhNa+iyuxbwm8x8LcUPkl8AJ5fzTgde0F24PFg9Enhz+Tk7A7MoCn1/ycwtytx/YYktbBu1yNvQj8sJmblzZv47xUHSXpk5ieJAZ5uI2D0zE/gAcFu5Lv03xZfe2eXz41lGczOkLCqdRlG83YEFzyC12t4AXg18q1yffkCx/rVch6IYgvc5YI8yzx8o31d7I+RoDYr14d3lMu0JnBIRa1BhvYiIvcr3bEVRkNt02CxNc1w3ZXH6DxQ/QHam9XrzEeDSzNyq/HHw7YZmtqH4Yfoqih9y72nyUR+k2D63Lv+9tpw2ZCLFQfqrgUkUP3CWiCbLPJr1KYoc21GsCxPLdelfKXrPtXIXcGRE7F3hM84G/q3h+YEURbnhzgG+kZlbU/zomTysjRMzc1uKHO4REW8qv1dG+r5ZqhrzT1HsPgd4Txnb9ylOshARe1AUn3agOE7oodgPQfFj6anM3Bx4L8XfZ5lV7qdOpfguey3FD6shI+3LN6c4NtiC4gfO5RQ/QDanKJjsV873aWBWZm6bRS+XB4HPlK+dAOxWTp9MUfzslG4WfV1tPJa8pJzWar9yOfC6MtfvAs6q0P5IeRqbmdsD76D4vplbbodHUhSFOu3JzJxMse5cxPPHl2dTFD5GczjwtXLZJwI/azLPZyhO2GxdHj/8R1siH91AuT9+G3BquS0Neapc7v0piihD21rTfQ5wMM8fM+4z0r4zIrakWOYdys9YfVhcawG3Z+aOWfQyvwHYscz7rsBXYsFLI2xeTn8NsFcsOPR1Q4qC2GuBD0TEpmXB8JmIeGO5XDuVuVioQl2DkfLYylrALeW6/lHg3IgYO8L8W1Es4+blOtK4jGsB15T5+QLFSZxWWv1dW+1DF1lmHlw+3KFc/z8P/LJc5tdQFObfX87zXeDazNyyXF9Oa2hqpGOcVq+dCMwo29oN+FI0H/r6PYp935YU34ffjYhxo+TkNGCfeH6o+AfLNpZooQ6a5vRJWufgq7TO99mZOblcts9RHNO/oP3MfHKUdig//82ZaaFuBWWxrnBAREyPiFspftgNdYu+KzOv6WBcS9r2FF/+vwPIYmjGOkB/Zl5RTvsFRRFh6No9z2TmT8vHNwB/zcybyufTgVc0+Zy3Uuy4ZpZtPpOZs4Frgd0i4oTyy3+RzzAtZS/IW2Y+Ub7WWMTtAU4ozyhOp9jhVu1yv6zmZsjrgBvKwiQsOHSj1fYGkJl5Y/n4WoqzdtB6HXpzOc+vyjPO3wN6yzNxddcqR1tT9Hr6WblMP6PoAfcKqq0XO1Oc4X42Mwd44Y+9Vjmuu1brza+A90fEMRHxTxQHV0Muz8wns+gJ93uaL+uuFL3x+jOzn6IQ1Xiw+uPMnF2+dkOLNjrlgswcyGI4zuMUJxGg2N+sFxEvGv6GiDiI4uztdhQ/yvYsp19WFsWHOwvYLyJ6y4Px1Sl6CTW2+WKK/ds5AFn0bL21fG0VirPHJ5br83UUvTBeRfG9MtL3TSdtB9ycmbeVz88AXhMRq1GsH+dl5lPlunUqz68zO1MWjDPzMeCHSzfsthvaT91VPv9Ow2uj7cuHjg1uAG7KzL+WzxuPFd4GvDeKa0fdVD4f2sauBM6Iojfnekvjx9oIXsair6vNjiVb7VdeDlweEX8EzgfGR8T4UdofKU/nl//fQNEraOh5q+O1pa0xvsGG48uq8V0FfCYiPgtsW/74HW5P4Otlroe2y6VhaD+QFMv3uobXziv/v5ZilMXQPrnVPme4kfadUyhOYD3a0E6j2Sx4UnMccGFEzKAoFq/Jguv1WZk5L4teYOdR9D4bMvQdNAu4nefX4xMpTqRBUWg8mUU3Uh5b6acoUJGZv6QoBo20rd5Nccz+7YjYf9hrzzQU2Uc7Zmr2dx1pH9pObwM+Ve5Hb6AoLG1WFr12oOEE3rBtYKRjnFav7UrRY47MfAj4KcOGBJfr7Wso179yvb6JIh8tc1L+nvoJsH9E9FIU17+5SBlpj1Y5aJrv8rVJEfGrcpv6KiP/9hupHSgKlQ5/XYGt8MNgyzM+H6aocj8axRCEoV4Vy1qBZGF1tZjWbIjX0LQ5DdPms+C1jubTfJ1q9jlk5jUR8RrgTRRnoY4Adhwl5jpoujylxnXmP4GXANtl5uyIOJWGoWEjWYZzM6RVjl5L6+0NWq9PrdrrAi7LzAMWJ9gOGWmZbsnMNzR7scJ60WobHlJlm62VkfbTWQyJuYbi7O4RFGck31u+dfiyNruQdLN8NT6vc76GxzYbihMIUdwboVmsbwO+m5n3RMSbgf8riwHjgd8Onzkz74uI24A9KH4EnpXNhwG3Wue6y9cmZ+bcxhfKHiAL09bSNNJ2NNI6M9L3w7KoVR4Wdl/ealvsohiidmWTz3g7RU+xfwKuiogPZWaznlNLw0jHRvNY8OT38O/5ZseSrfYr5wKHZeaPI6KbYnjeaMcNI+Vp+D5h6HPrsi9rjGf48eVQfC3zm5lfj4iLKYoH/xsR/5eZw3uL12GbHL7+NNtXj/bdPVJ7QwYrtPPssH34NymKI2/PYnjfnbRe55ouR6nxb3YB8D8R8VqKIk5jT6HFMfT5o21zrd7XVGbOiohXU3zH7ULRU2zr8uVW62Uzi/t3XRxdwD9n5t2NE2P0m5mMdIwz0msjHTcNxdPMIM8fF7RyIkXP0kcoeoHeOcK8S9pIv0ua5bsPuBB4Q2beEBHrUlyipJWm7TRY3msRGoU964ohZ7OAx8su0iN9oTzFC7uTL8t+B2wexfXXhm6i8TAwNiJ2LqftTDF8bHF2lBdTnIF/adnmqhExNiI2pugyfh5FYWtSeXBady/IWzS/m+IawENloW49YKQhZwusW8twboZcA7w2IoaGYA5dDHthtrdGTdchihty7F4eZFG+NrlFG3XTKkc3AJsObYNQLFNEdFVcL64C9o2IlcvXhp8lXha1XG+iuCbKzMw8k+LaNgt7x+6fAwdGxJiIGEMx5POKtkRdT3+gOGO9cnlw+FGKYSfnDy+mNTiTYv3cjybD8jLzKWAGRe8qorhr+hbla09T9MQ7Ymj+iNigLBDeQfu/b9rlGopeLa8sn/8bcGO5PD8H3hURq0VEF0VuhtaZXwDvA4iItSiuX7Qsu5ZiPzPUy+nA8v9F3ZcP9xPgP+P5Ox6vFhGvKntUbJKZ12VxaYj/oygQdsq9tF5X7wE2iYiXlOvDfi1bGd0aZXsA/05xPcCWapinJeHPwJblcWMfsM/QCxGxWWb+OTNPobhOYrP9/8XAx+P5Ozyu3WSeJWFoP7ApRc+a348y/0j7nOG/P0bad14NvKVhORsvY9DMGsC9ZaHuTbywR+P+UfSsXgXYl+IYY0Tld8l3KLbv7y1mr9hmeZwJjGnYL7172Hv6eP77aCeKYl7SQkSMA1bK4npqR1Ds2zZZjJgbtdqHtsPTPL9e/AQ4ovwtR0SsHREblz0if0dxXUuGXlvMz72C8uRM+V3+FoatF+VxwU2U61+5Xm9F8fcbMSeZOYNitMDXWbxemYuiMacjaZpvnr/24/3lfB8Z9r7h7bdqRwIs1kExxOzPFF98P6P4odzKOcC7oxiusSz25FlAZv6N4ozsVyPiFophB1tQXNvkuHLacRQXF1/ku+KUXdD/B7giiiGhV1IcHEwBboznh/p9qBy2V2st8japyawnAq+PiBspzly+4CLRDX5EcU27m6K4WO8UlsHcDMnMRyi+yC+OiN9RnAWF4su86vbW2F7TdajsQv9eiqELN0fE7RR3c6y9EXL0BEXvp/9qWKajKc6+TWGU9SKLO8NeTnH9ySspLvw+a4kv0JI10n76X4Fby+3sf3n+JiRVnUpx8eIby3+3sOD1XJY3x1L8aLkhIqZTXJ/tX4CDYsFrETWaRrHu3ZaZra4bdgBwSETcQDFspfEmL++hOMFxaxRDJs+n2H77afP3TbuUQ8j2B75fxvbe8h9lr6XvUvy4vrV8yxfL/48BXhJFb8RzWMbv8J2ZD1PcAOmnEfFbih5xcyn2MQu9L2/ieIp91fVlnn9DMUS6BzizXGduBiZQDrvqkPm0WFezuEnLVIpjgSuAhxbjcz4O/DgifkNx45jHR5m/bnlqu3II8RUUJwQuoRhuOeRjEfHHcv9/CM2vc3c8RbF1aKj10rob+Jxym7mE4kYRj4w080j7HIrvpYyIGRFx4Uj7zixuBvRl4JqI+DXF9/9IxwBHUFwS4RqKQugtw16/gSL/N1HcKO0Sqjmd4sYmizuE8QV5LIcFHgr8PIqL8A+/w/LjFCc9fw98A9hvlO+VDXj++PIWin1aW25UNsI+tB3D+qcCV5br9dEUebi5/J69jCL/UKxHry/Xn5spTgQsjo8BW5Xr3s+BIzLzj03mew/FZQ5uoegpt39mPloxJ6dT3HzhpyxdjTldY4T5Pk6TfJdFys9TfKf9iuLmL03bj+Ja1E3baesSaZnWNThYh9EmkqR2iYjVMvPpKHrWnQ482GRokCSNamh/Uj5+H8XdEJelyzIssiguhP4XYOUWw7+lF4gWd/Feip/fuM0eDbwiM9878ruatnM15V2HF+G976Uoki3yhfE7ncd2WZH3oa2MlpOIOJ3iUoUndCpGqQ7qcL0KSVJ7nR0RG1GcrZxOcZZdkhbFxyJiX4pjxr+x9O6m2VFRXG9rGvAFC3VaxhwfEa+nGA56NwteT3KJi4jLKS7E/7al+bk1tkLuQ0fRNCdRXOPtKoqhzh/rXHhSPdizTpIkSZIkSaoJr1knSZIkSZIk1YTFOkmSJEmSJKkmLNZJkiRJkiRJNWGxTpIkSZIkSaoJi3WSJGm5EhHfiojPdToOSZIkaVF4N1hJkqQ2iYgzgb9m5mc7HYskSZKWTfaskyRJWg5ERE+nY5AkSdLis2edJEmqhYi4FzgZ2B94OXAecCRwJrAj8Htg38x8IiIuAHYCVgJuBj6cmX8s2zmTsndbREwBvgt8DTgcmA8cmZlnjBLLSsAXgX2ANYBbgTdl5t9bfXZEfLCMfxDoB67KzL0iYl3gf4E3AM8AX8vMExs+51vA24CZwBnAxzJz/fL1VwHfBF4DPAB8JjN/0rCcfwdeBrwROBr4JLBeZs4r53kH8LnMfE2FP4EkSZJqwJ51kiSpTt4BvAnYDNgL+BlFwW5tiuOWj5Xz/QzYFFgHuAH43ghtjgdWB9YD/h04OSJeMkocXwEmATsAawKfBgZG+uzMPLV8/OXMXLUs1HUDF1MU9dYDdgE+HhFvLtv6L2AjYJNyud87FEBEjCnf+3/lZx0CfC8ioiHOdwPHAqtRFAQfL9sZ8l7gnFGWVZIkSTXS2+kAJEmSGvxvZj4MEBG/Bh7JzBvL5z+iKHaRmd8ZekNEHA08ERGrZ+asJm3OBb5Q9ja7NCKeAQK4tlkAZYHt/cDrMvOBcvLvhl5fyM+eDIzLzC+Uz++OiNOAdwGXA/9K0TPvibKdEyl6yAG8DlgVOD4zB4ArI+ISYL+GeS7KzN+Wj2dHxFkUBbqfRcSawJuBjzRbTkmSJNWTxTpJklQnDzc8/nuT56uW12Y7FtgXGMfzPd7WBpoVzB4fGhZaeo6iCNbK2sCLgD8Pf2ERPvtlwLoR8WTDtB7g1+XjdYH7G15rfLwucH9ZqBvyF4oees3mh2LI7+0RsSpFIfDXmflQk7gkSZJUUxbrJEnSsubdwN7ArsC9FENcnwC62tT+Y8Bsiuvm3byQnz38YsD3A/dk5qYtPushYH3gtvL5Bg2vPQhsEBHdDQW7DYE7G+ZZ4PMy84GIuAb4F4pr/32zxedKkiSppizWSZKkZc1qwByK67OtDBzXzsYzcyAivgN8NSL2p+jdty3F9elG++yHKa4/N+Q64KmIOBw4keLGE68CVsrM64EfAJ+JiOvL9j7a8N7fA88Cn46IqcDrKa7jN3mURTgbOIKiV9+PFmLRJUmSVAPeYEKSJC1rzqYYDvoARY+0pteeW0yfpLgD7PXA34AvURw3jfbZ3wY2j4gnI+LHmTmfosD2GuAeil57p1P0yAP4AvDX8rUrgAspioFkZj/FXWL3KN/3DeCAzLxjlNh/RFmoy8xnF2XhJUmS1Dldg4PDR2tIkiSpEyLiw8C7MvONi9nOn4GDMvOK9kQmSZKkpcVhsJIkSR0SERMohs1eA2wKHAactJhtvoPiWnZXLnaAkiRJWuos1kmSpBVSRPyRYrjocAdl5veWUhh9wCnAxsCTwHkUw10XSURcDWwO7D/sLrKSJElaRjgMVpIkSZIkSaoJbzAhSZIkSZIk1YTFOkmSJEmSJKkmLNZJkiRJkiRJNWGxTpIkSZIkSaoJi3WSJEmSJElSTfx/Mc6SWJHssgsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_categories = df_kickstarters.groupby(['status','main_category'])['status'].count().unstack('main_category').fillna(0)\n",
    "sub_df_categories = np.transpose(df_categories.div(df_categories.sum()))\n",
    "sub_df_categories.plot(kind='bar',stacked=True,rot=0, figsize=(20,5))\n",
    "\n",
    "plt.legend(('failed','successful'), loc='center left', bbox_to_anchor=(1.0, 0.5))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next we tried visualizing all the numerical data to see their distributions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fa9857c9be0>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#distribution of duration\n",
    "plt.figure(figsize=(20,8))\n",
    "plt.title('Distributions of duration')\n",
    "plt.ylabel('proportion')\n",
    "\n",
    "sns.distplot(df_successful['duration'],label='Successful',color='green',hist=False)\n",
    "sns.distplot(df_failed['duration'],label='Failed',color='red',hist=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fa9858c15c0>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#distribution of goal_usd\n",
    "plt.figure(figsize=(20,8))\n",
    "plt.title('Distributions of goal_usd')\n",
    "plt.ylabel('proportion')\n",
    "\n",
    "sns.distplot(df_successful['goal_usd'],label='Successful',color='green',hist=False)\n",
    "sns.distplot(df_failed['goal_usd'],label='Failed',color='red',hist=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fa9856cd128>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#distribution of usd_pledged\n",
    "plt.figure(figsize=(20,8))\n",
    "plt.title('Distributions of usd_pledged')\n",
    "plt.ylabel('proportion')\n",
    "\n",
    "sns.distplot(df_successful['usd_pledged'],label='Successful',color='green',hist=False)\n",
    "sns.distplot(df_failed['usd_pledged'],label='Successful',color='red',hist=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fa9856b4828>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#distribution of blurb_length\n",
    "plt.figure(figsize=(20,8))\n",
    "plt.title('Distributions of blurb_length')\n",
    "plt.ylabel('proportion')\n",
    "\n",
    "sns.distplot(df_successful['blurb_length'],label='Successful',color='green',hist=False)\n",
    "sns.distplot(df_failed['blurb_length'],label='Failed',color='red',hist=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fa985664c88>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#distribution of name_length\n",
    "plt.figure(figsize=(20,8))\n",
    "plt.title('Distributions of name_length')\n",
    "plt.ylabel('proportion')\n",
    "\n",
    "sns.distplot(df_successful['name_length'],color='green',hist=False)\n",
    "sns.distplot(df_failed['name_length'],color='red',hist=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fa985551c18>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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xOhEReykZJSIiInI3OXcOFi6E/v3BxwP/K9ivn5WUmjzZ/XuJ5GCzzFnEJ8XzWovXXFonzAgDYI45x46wRETcQskoERERkbvJjBnWQHF3t+ilqlABWra0BqY7nZ7ZUyQHCt8fTlCRIIwShkvrVC5Wmdqla6tVT0SyNSWjRERERO4mkydD5cpw332e23PAANi1C3bs8NyeIjlIsjOZ5QeW065Su0yfoJeesOphrDq4irNXztoQnYiI/ZSMEhEREblbnDoFy5ZZySEbPvBmWJ8+VkugWvVE0rXtxDbOXjlL20ptbVkvzAgjyZnEgj0LbFlPRMRuSkaJiIiI3C2mTYOkJM+16KUqUwbatrWSUWrVE7lJ+P5wANqEtLFlvUYVGlGmQBm16olItqVklIiIiMjdYtIkqFED6tTx/N4DBsDevbBpk+f3Fsnmlu1fhlHCoELhCras5+PwoUf1HizYs4CEpARb1hQRsZOSUSIiIiJ3g6NHYeVKqyrKky16qXr3hjx51KoncoOrSVdZeXClbS16qcKMMGISYlhxYIWt64qI2EHJKBEREZG7wdSpVovcgAHe2b94cejYEaZMUaueSBq/H/2dSwmXbE9GtavcjoA8Acw21aonItmPklEiIiIid4NJk6BuXatNz1sGDICDB2H9eu/FIJLNpM6Lah3S2tZ18/vlp2OVjsw2Z+NUAlhEshklo0RERERyuwMHYN06zw8uv1HPnuDvbyXGRASA8APh1C1Tl5L5S9q+dpgRRvTFaLae2Gr72iIirlAySkRERCS3mzLF+r1/f+/GUaQIdOlitQwmJ3s3FpFsIC4xjjWH1tjeopeqW7VuOHCoVU9Esh0lo0RERERyu0mToHFjqFzZ25FY1VlHj8Lq1d6ORMTrIqIjiE+Kd1syqkzBMjQNbKpklIhkO0pGiYiIiORmkZGwebP3W/RSde8OAQFq1RPBmhfl6/ClVXArt+0RZoSx8dhGDl887LY9REQyS8koERERkdxs8mTr9379vBtHqoIFrYTUL79AYqK3oxHxqvAD4TSq0IjCeQu7bY8wIwyAuZFz3baHiEhmKRklIiIikptNnw7Nm0NgoLcjuWbgQDh1Clas8HYkIl4TEx/DhiMbaBvinha9VDVL1qRKsSpq1RORbEXJKBEREZHc6sgR2LIFevTwdiTX69LFqpBKrdoSuQutOrSKxOREt82LSuVwOAgzwli2fxkx8TFu3UtEJKOUjBIRERHJrebPt37v1s27cdwoIAB69oRp0yAhwdvRiHhF+P5w/H39Ca0Y6va9eho9SUhKYPG+xW7fS0QkI5SMEhEREcmt5s6F4GC45x5vR3KzgQPh3DlYutTbkYh4Rfj+cEIrhhLgF+D2vZoHNadYvmLMMme5fS8RkYxQMkpEREQkN4qLsxI93bqBw+HtaG7WsSMULapWPbkrnYk9w5bjW9w+LypVHp88dKraiWX7l+F0Oj2yp4jI7SgZJSIiIpIb/forxMZmvxa9VP7+0KsXzJhhJc5E7iK/HvwVJ063z4tKq3nF5hyNOUr0xWiP7SkicitKRomIiIjkRvPmWbOZ2rTxdiS3NnAgxMTAwoXejkTEo8L3h1PArwCNKjTy2J7NApsBsDZ6rcf2FBG5FSWjRERERHIbp9OaF9WunZWQyq7atoWSJWHSJG9HIuJR4fvDaRXcCn9ff4/teW+Ze8nvl5+I6AiP7SkicitKRomIiIjkNrt3w/792bdFL1WePNC/P8yaBRcvejsaEY84FnOMXad3ebRFD8DP14/GFRqz9rAqo0TE+5SMEhEREclt5s2zfu/a1eWlzsedd3mN2xoyxJoZ9csv7t1HJJtYfmA5gMeTUWC16m05voXYq7Ee31tEJC0lo0RERERym7lzoU4dCApyaZnJOyZT7JNidPm5C2sOrbEpuBs0aQLVqsH48e5ZXySbCd8fTrF8xahbpq7H9w6tGEpiciK/H/3d43uLiKSlZJSIiBccPH+Q5mOb83nE594ORURym/PnYfVq6N7dpWXiEuMYtnQYIUVD+P3o77T4oQVtxrVhadRSe4+Gdzjg4YdhxQo4eNC+dUWyqfD94bQOaY2vj6/H924a2BTQEHMR8b48ntrIMIzqwDigBHAGeNg0zT03XNMR+BCoA4w2TfMfab7mC/wH6Aw4gY9N0/zOQ+GLiNhm+4ntdP65M0djjrLhyAbaV27PvWXu9XZYIpJbLF4MSUkuz4v6YsMXHLxwkGUPL6NJhSZ8u+lbPl37KR3Gd6BJhSa80fINulfvjsPhcD3mwYPhrbfg55/h9dddX89TrlyxZl5t2ACFC0OhQtbvKb+C4uKgShUYNAjq1fN2tJIN7D+3n/3n9/P3Zn/3yv4l85ekeonqSkaJiNd5sjLqK+AL0zSrA18AX6dzTRTwF+DTdL72EFAVqAY0A94xDCPEPaGKiLjHrwd+peUPLQFY/shyiuUrxhOznyAxOdHLkUlucPD8QX3AEGteVPHi0LRplpc4d+UcH6z6gM5VO9O2UlsK+BfgxaYvEvVCFF91+4oTl08QNimM+l/XZ445x/WYQ0KgVSv43/+skwBzgqQkeOgh6/Xu3BkaN4YKFayvHT4M69ZRNDwcPv8cOnaEEye8G69kC+H7wwHvzItKFVoxlIjDEfZWOIqIZJJHklGGYZQGGgATUx6aCDQwDKNU2utM09xrmuZmIL1PZQOAb03TTDZN8xQwE+jnxrBFRGw1bec0Ov3UiXKFyhHxRAStQ1ozpusYfj/6O/+K+Je3w5Mc7uyVs9z/4/20/KElk3ZM8nY44i1JSTB/vpUc8c16C9BHqz/ifNx5Pmn/yXWP582Tl6fue4rI5yIZ98A4riReoeeknuw9u9fVyK1B5qYJv/3m+lru5nTCSy/BjBkwahSMG2dVdc2ZY7UbbtoEe/eybckS2LrVOinwL3/JOYk2cZvwA+GUKVCGmiVrei2G0MBQTseetuffWxGRLPJUm15F4IhpmkkApmkmGYZxNOXxUxlcIwhIO0jgUMr9GbZjx47MXJ5rbdy40dshSC6m91f6ph6YyogdI6hTrA6fN/icU3tPcYpTVHZWpnWZ1rwV/hZVE6sSVNC1YcO5md5bt+Z0Onn595c5cvEIRmGDwdMHc/jAYdqUa+Pt0HKE3PTeKrB9OzVOnyaqVi3OZfF5Hb9ynH+v+zfdArtx9fBVNh5Of517uIdR9UbRfVl3PlrwEc/UeMaV0PGpVo26/v6cHjmS6FdfdWktdyv9009UHD2a44MHc6R5c7jNa73xyhVKP/ccFUeO5MDbb3PmgQc8GKlkJ06nk0WRi7ivxH1s2rTJ5fWy+rOr8MXCAExYNYHuFV2bLSe5U27676JkXx6bGZUd1K5dm7x583o7DK/auHEjDRs29HYYkkvp/XUzp9PJW8vf4pMdn9Cjeg8m9Z1Efr/8113zs/Eztb6oxb/3/5vwR8LxcehsiRvpvXV7I9eOZOWJlYzqNIrH6z9Op5868frm15lpzKRrta7eDi9by3XvrZkzwceHyk8/bbXqZcEjMx/B4XDwZd8vqVjkzn/v1/lQZxYdX8Q3g75xfSBzr16UXrqU0uPHg7+/a2u5y+TJVjVU//6UHTeOsj63/pn95/urfn3YsoWQf/2LkEcfteZIyV3HPG1yJv4MfRv2pWED137uuPKzq76zPn9d/1eO5TmWu37+iS1y3X8Xxe3i4+OzVPjjqU880UCFlCHkqcPIy6c8nlGHgOA0fw7K5P0iIh6VmJzIk7Of5INVH/Bk/SeZPmD6TYkogPKFyvN5p8/59eCvfLPxGy9EKjlZRHQEw5cNp3fN3rzQ5AUK5S3E/IfmU6dMHXpP7s3SqKXeDlE8ad48CA3NciJq6/GtjN86nr81+VuGElEAj9d7nCMxR1gStSRLe15nyBA4cwYWLHB9LXdYudI6+a9lS6s17xaJqISkBB6e8TBvbX6LZGeydd2PP4Kfn/UcEzUn8G6UOtOvRVALr8bh4/ChWWAzzRgUEa/ySDLKNM2TwBZgUMpDg4DNKbOfMmoq8BfDMHxSZk09AEyzN1IREfs8Necpxm4Zy9ut3uabHt+Qx+fWxaiP1XuMdpXa8eqSV4m+oDy7ZMyZ2DMM+GUAFQtX5Puw7/881axovqIsHryY6iWqEzYxjFUHV3k5UvGII0dg82aXTtEbtnQYxQKK8VrL1zJ8Tw+jByXzl2Ts5rFZ3vdPHTtC6dIwfrzra9lt507o2RMqV7Yq0PLlS/eyhKQE+k7py/ht41lwZAHvr3zf+kJgIHz5JUREwCefpHuvWMPzl+xbwtWkq94OxXZro9dSLF8xqpeo7u1QaBbYjB0nd3Ax/qK3QxGRu5Qne0GGAs8bhhEJPJ/yZwzDmG8Yxn0p/9zCMIzDwN+BpwzDOGwYRqeU+8djnba3B1gH/NM0zSgPxi8ikmEX4i4wftt4nr7vad5t8+4djz53OBx82+NbkpxJDJ03VCfcyB0lO5N5ZOYjnLh8gqn9plI0X9Hrvl4ifwmWPryU4KLBdJ3QlfWH13sp0uwvMTmRJfuWEBMf4+1QXDN/vvV796zNgFkatZRF+xbxRss3bno/3Y6/rz+D6wxm5u6ZnI49naW9/+TnBw8+aA0CP3fOtbXsdPQodOliJaAWLLhl5VlqImpO5By+7PolXSt05Z0V77Bo7yLrgkGDYOBAeOed286ZupskO5PZdGwTH6z8gBZjW1Dy05J0/Kkj//z1n94OzXZrD6+lWcVm2aIdP7RiKE6cuf6/DfGJ8cwx5/DozEcZvzUbJrlF7mIemxllmuZuoEk6j3dN88+rgcBb3J8EPO22AEVEbDQ3ci5Xk68y5N4hGb6nUrFKfNj2Q15c9CITtk/goXsfcmOEktN9tvYz5u2Zx5guY2hYPv3ZDqULlGbZw8to9UMrOv3UifBHwmlQroGHI82+4hPjmX5wOgPWDGDfuX08WOdBfu79s7fDyrp58yAoCO65J9O3JjuTeXXJq4QUDeHZRs9m+v7H6z/OqPWjmLB9Ai80eSHT919nyBBrJtOUKfDUU66tZYeYGKva7MwZq00vJCTdy25MRD3d6Gnudd5L9NVoHpz+IJv+uongosHwxRewahUMHmyduhcQ4Nnnkw2cjzvPor2LWLB3AQv3LuTE5RMANCzXkNdbvM6m45sYGTGSp+57isDC6X40yHHOx51n56mdPFj7QW+HAkCTwCY4cLA2ei0dqnTwdji2SkxOJHx/OJN2TGL6rulciL8AwCxzFg/UeIBCeQt5OUIRAc9WRomI3DV+2fUL5QuVp0ngTTn423qu8XM0C2zG3xb+jZOXT7opOsnpVh9azevLXqdfrX480+j2J5iVL1SeZQ8vo0i+InQc35EdJ3Wy7KWES4xcO5LK/6nMh9s/pHhAcfrf058J2yew5tAab4eXNXFxsGSJlTS5QyVmeiZun8jm45t5v8375M2T+cNe6pSpw33l7+P7zd+7XtlZv76VUPvf/1xbxw5OJzz0EGzfDr/8Ag3ST+bGJ8bflIgCyOebj2n9p5GYnEi/qf2IT4y3qqp++AF274bhwz35bLKFi/EXqflFTQZOG8icyDm0qdSGcQ+M4/jLx/n9r7/zXtv3+KLrFyQ7k3kj/A1vh2ubdYfXAdCsYjMvR2IpnLcwtUvXJuJwhLdDsUWyM5mVB1fyzLxnKD+yPJ1+6sQvO3+hZ42ezHtwHqsfW835uPOazSmSjSgZJSJis0sJl1i4dyF9avbJdCm+r48v34V9R0xCDC8scLG6QHKlU5dPMfCXgVQqVonvwr67YwsoQHDRYMIfDsff158nZz/pgSizpzOxZ3hnxTsEjwrmH0v+QY2SNfiiyResf3I9Y8PGElg4kOcXPE9ScpK3Q828X3+F2NgszYuKS4zjjfA3qF+2PoPqDLrzDbfweL3H2XZiG5uPb87yGoCVTBsyBNauhb17XVvLVVOmWC2Dn34KnTune0l8Yjz9pva7KRGVqlqJavzY80d+O/obLy16yXqwQwd44QX4z3+sJOJd5MctP3L80nFmDJjByX+cZGKfiTxc92HKFCzz5zUhRUP4W5O/MX7reDYd2+TFaO2zNnotPg4fGldo7O1Q/hRaMZSIwxHWkP0c7snnlJEEAAAgAElEQVTZT3L/j/fz45YfaVupLdP7T+fkKycZ98A4ulbrSvOg5rSt1JbP131uJYVFxOuUjBIRsdmCPQuIS4yjT80+Wbq/VqlavNXqLSb/MfnanBERrL/5HTJjCKdjTzOl7xQK5y2c4XurFK/Ci01fZP2R9ew/t9+NUWZPn675lOBRwbz767u0CGpBxBMRLHt4GU1KNcHhcFDAvwAj2o9g8/HN9gzi9rR586x2r7ZtM33rl799ycELBxnRYYRLs2wG1RlEvjz57Hn9HnrISkr99JPra2XV+fPw4otw331W4igdd0pEpepVsxevhL7Cf3//77W5NR9/DDVqwKOPwtmzbnoS2UuyM5nRG0bTLLAZD9R4AF8f31te+3rL1ymRvwT/WPyPXDFHMeJwBPeWuZeC/gW9HcqfQiuGcjH+IjtP7fR2KC45dOEQ47aO48n6T3LylZNM6juJXjV7kS/P9YcMDG8+nKMxRxm/TbOjRLIDJaNERGw2bdc0Shco7dLRzcOaD6Nk/pL6Hya5znebvmPRvkWM6jyK+uXqZ/r+frX6ATB151S7Q8vWDpw/wLClw2ge1JztT29n1sBZNA1setN1A2sPpEVQC14Pf53zcee9EGkWOZ0wd66ViMrk/KGL8Rd5f+X7dKrSifaV27sURtF8Reldszc/b/+ZuMQ4l9YiMBDatbNO1fNWIuL11+HkSfj6a/C9OWmS0URUqg/bfUir4FY8Nfcptp/Ybn2vfvrJ2uO1jJ9emJMt2ruIvWf38nzj5+94bZF8RXjn/ndYfmA5cyPneiA690lKTmLd4XWEBoZ6O5TrhFa04omIztmtel/9/hUAb7Z687bJvvaV29OwXENGrBmRMytgRXIZJaNERGx05eoV5kbO5QHj9n/jeyd+vn50rdaV+Xvmk5icaGOEkpP9vP1napeuzVMNszbUuVKxSjSu0Jgpf0yxObLs7ftN3wPwTfdvqF269i2vczgc/KfzfzgTe4Z3V7zrqfBct3s37N+fpRa9eZHzOBd3jjdbvWlLKI/Xe5zzceeZuXum64sNGQJRUVa7nqetWwdffWVVRN1iTtRby9/KcCIKII9PHib3nUyRfEXoM6UPF+IuQMOG8Pjj1nys7HR6oJv8Z8N/KFewHH1qZaxy+K8N/4pRwuCVJa9wNemqm6Nznz9O/cGlhEt/Jn+yiyrFqlAyf0nWHvbCv2M2iUuM49tN3xJmhFkHBNyGw+FgeIvh7Dm7h+m7pnsoQhG5FSWjRERstHjfYi5fvUzfWn1dXiusehjn4s7l3IHKYqtTl0+x+tBqetfonaE5UbfSv1Z/Nh7byN6zXp7F4yFXk67y/ebv6VKtyx0/qADUL1efJxs8yZjfxrDr1C4PRGiDefOs37OSjNozj5L5S9Is0J6hym0qtSG4SLA9rXq9e0P+/J4fZH71qnWKX4UK8M9/pntJYnIi47aOo3fN3hlKRKUqW7AsU/pOIepcFI/NesxqP3v6aWsA/Y8/2vQEsqfIM5Es3LuQofcNxd/XP0P3+Pn6MaLDCMwzJt9u+tbNEbrP2mgr2ZNdhpencjgchFYM/TO+nGjSjkmcjj2doWo7gF41elG9RHU+Wv1Rrmj/FMnJlIwSEbHRtF3TKJavGK1DWru8VscqHfH39WdO5BzXA5Mcb7Y5m2RnMr1q9nJpnX73pLTq/XF3tOrNjZzLsUvHMlVN9kHbDyjgV4AXF72YMz6szJwJdepAUFCmbktKTmLh3oV0qdrFpUrOtHwcPjxW7zGWRi3l4PmDri1WsKCVkJo82UrWeMqoUbBtG4weDYXSPwJ++f7lnLx8kofqPJTp5VsGt2REhxHM2D2DL377AurVg2bN4L//heScP0j6VsZsGIOfj1+mKzt7VO9B65DW/N+K/7OqyXKgtdFrKVOgDJWKVvJ2KDcJDQwl8kwkp2NPezuUTHM6nYzeMJpapWrRJqRNhu7x9fFlWPNhbD6+mSVRd9fhASLZjZJRIiI2SUhKYLY5m541euLn6+fyeoXyFqJNSBtmm7NtiC7nOBpzlHb/a8egaYP4cNWHVjIh9ljOSAq40YzdMwgpGkLdMnVdWieoSBDNApsxZefd0ar39cavqVCoAl2rdc3wPaUKlOLd1u+yeN/i7J8MPngQ1qyBgQMzfev6I+s5c+UM3aplvqLqdh6t9ygA47aOc32xhx+GCxesmViecOAAvPMO9OwJDzxwy8sm7JhA4byFM/W+Suulpi/RvGJzvvztS+uBZ56BPXsgPDxL62V3F+Mv8uOWHxlQe8B1p+ZlhMPhYGTHkZyOPc1Hqz9yU4TuFXE4gtCKoS5VtbpLarXWusPrvBxJ5q07vI5NxzbxXKPnMvXaDr53MBUKVcix7yeR3ELJKBERmyyLWsaF+AtZPkUvPT2q92DP2T2Yp03b1szu3lnxDqsOriIiOoI3wt+gx8Qe9AjvQdFPitJibAuenvs0E7dPvKuSUzHxMSyJWkKvGr1s+TDT/57+bDm+hcgzkTZEl33tP7efxfsW80T9J8jjkydT9z7T6BlqlarFS4tecn0YtztNmmT9PmhQpm+dGzkXX4cvnap2sjWk4KLBtKvcjh+2/OD6kfFt20L58vDll+4fZO50wnPPWaf4jR59y8viEuOYvms6vWv2vum0roxyOBwMqj2IXad3WSeZ9e0LJUtazzMXGrdlHDEJMbzQOP1TCe+kQbkGDLl3CKPWjeLA+QP2BudmJy+fZO/Zvba1wtrtvvL3kccnT45s1Ru9YTRF8hZhSN0hmbrP39efl5u9zIoDK3JkEk4kt1AySkTEJtN2TaOQfyE6VO5g25o9jB4Ad011VOSZSMZuHsvT9z3NgRcPcH7YeVY/tprhdYbzUJ2HcDgcTNgxgQenP5jjT1fKjAV7F5CQlECvGq616KVKnWmW2weZf7fpOxwOB082eDLT9/r5+jGq0yiizkXxr4h/uSE6m/z8s9XiVSnz7T/z9syjRVALiuYrantYj9d7nAPnD7DiwArXFvL1heHDYflymOrm1tLp0635W++9BxUr3vKy+XvmczH+Ig/WftCl7XrV7IUDB7/s/AXy5bMGmc+eDYcPu7RudpPsTGbMb2NoUqEJjSo0yvI6H7T9AIfDwRvhb9gYnfulnlSX3YaXp8rvl5/6ZesTcThnnah3LOYYU3dO5bF6j932BL1b+UvDv1A8oDgfr/7YDdGJSEYoGSUiYoPE5ERm7p5JD6MHefPktW3doCJB1CtbL/u3CtnkreVvkS9PPt5oZX3YKJKvCM2DmtM3uC9fdvuSVY+t4vQrpwkqEsSnaz/1crSeM2P3DErlL2Xbh5nAwoG0CGrB5D8m27JednQ16Spjt4yla7WuVCxy68TC7XSo0oGeRk8+WPUBRy4esTlCG2zfbv16MPNJkegL0Ww7sc32Fr1UD9R4gCJ5i/DDlh9cX+yZZ6wT7V58ES5edH299Fy8aJ2cV68ePH/7QcgTd0ykdIHStKmUsRk1t1K+UHmaBzVn2q5p1gNPPWXNjPo25w7qTs/ifYuJPBPJC02yVhWVqmKRirzc7GUmbJ/AhiMbbIrO/SIOR+Dn40fD8g29HcotNQtsxoYjG3LUiYVfb/yaxOREnm38bJbuL+hfkOcbP88scxZ/nPzD5uhEJCOUjBIRscHKgys5c+WMrS16qXpU78Ga6DWciT1j+9rZyaZjm5jyxxReavoSpQuUvuV1fr5+vNT0JVYdWsX6w+s9GKF3xCfGMy9yHj2NnrYNmQbrVL0dJ3dYLUK50GxzNscvHc/0sOQbjew4kqvJVxm+bLhNkdlo4kSrcqhfv0zfOn/PfAC6VXdPMirAL4AH6zzILzt/cX3otK8vfPUVHD8Ob71lT4A3evNNOHYMvvkG8ty6pfNi/EXmmHMYcM+ATLd+pqdPzT5sO7GNPWf2QOXK0KWLlYy6mnOSAncyesNoyhYsa8sps8OaD6NMgTK8vPjlHNOqvTZ6LQ3KNchyS6cnhFYMJfZqLNtObPN2KBmSkJTA1xu/pkvVLlQtXjXL6zzf+Hny++VnxNoRNkYnIhmlZJSIiA2m7ZxGfr/8dK7a2fa1w4wwkp3Jf354zK3eCH+D4gHF+UfoP+547RP1n6BovqJ8FvGZByLzrvD94cQkxLh8it6N+tTqgwNHrj1V7+uNXxNYOJAuVbu4tE6V4lV4udnL/LTtJzYe3WhTdDZwOmHCBGjfHspkbiA0wNw9c6lUtBI1S9Z0Q3CWx+s/TlxiHJN2THJ9sUaN4OmnYcwY2LTJ9fXS+u03a91nn7X2uY2Zu2cSnxTPoNqZn9GVnt41ewNcq456+mkrKTZrli3re9ueM3uYv2c+QxsOxd/X3+X1CuUtxLut32X1odX8evBXGyJ0r4SkBH47+lu2bdFLlRpfTmnVm7ZzGscvHef5xrevYryTEvlL8NcGf2XC9gmun/4pIpmmZJSIiIuSnclM3z2dLlW7kN8vv+3rNyjXgHIFyzE7MvfOjVp5cCUL9y5kePPhFMlX5I7XF8pbiKENhzJ913T2nd3ngQi9Z8buGRTyL0S7Su1sXbd8ofK0Cm7F5D8m55gKg4yKOhfFkqglPFn/SVuqyYY1H4a/rz8Ttk+wITqbRERYJ+lloUXvytUrLItaRrdq3dx6ulfDcg2pU7oOY7eMtWfBDz6AUqVg6FBISrJnzfPn4dFHoVw5eP/9O14+YfsEQoqG0DSwqS3bBxUJokmFJtbcKLAqo4KDc80g8y9++wI/Hz+eus+1CsW0htQdQn6//Dli5t3W41uJS4zL9smoikUqUqFQhRwzxHz0htFUK17NlsMXXg59GQcORkaMtCEyEckMJaNERFy0Nnotxy8dt6UFIT0+Dh96VO/Bor2LiE+Md8se3uR0Onlt2WuUL1Se5xo/l+H7XmjyAnl88vB5xOdujM67kpKTmGXOomu1rrbOIkvV/57+7Dq9iz9O5a55Gd9u/BYfhw9PNHjClvWK5CtCu0rtmLF7RvZJ3E2YYA29fuCBTN+64sAKriRecVuLXiqHw8HA2gPZcGQDJy6dcH3BokXh88+tSqZvvnF9vfh46/XbswfGj4cit0+En7x8kqVRSxlUe5CtSbw+Nfuw8dhG9p/bb7UkDh1qDWzftcu2PbwhJj6GsZvH0v+e/pQtWNa2dfP75ad79e5M2zWNpGSbkpJukprcya4n6aUVWjE0R1RGbTy6kYjDETzb6Fl8HK5/lA0sHMjgewfz3abvOHX5lA0RikhGKRklIuKiaTunkdc3r9sGAYN1ql5MQkyOaEvIrHl75rE2ei1vt3qbAL+ADN9XrlA5BtcZzA9bfuB07Gk3Rug9EYcjOHn5pG2n6N2oT80++Dh8ckSFQUYlJCUwdstYulfvTmDhQNvW7VWjF/vP788eM1WuXoUpUyAsDAoXzvTt8/bMI79fflqHtLY/tht0rNIRgGX7l9mz4KBB0K4dvPYanHAhwZWcDI88Ar/+Cj/8AG3b3vGWqX9MJcmZxIN1XDtF70Z9almzBqfvmm498Pjj4OdnzcnKwcZtHUdMQozLrVTp6VerHycvn2TlwZW2r22ntYfXElQkiAqFK3g7lDsKrRjKgfMHOBpz1Nuh3NboDaMp4FeAR+s9atuaw5oPIy4xjm822pDkFpEMUzJKRMQFTqeTabum0bFKRwrlLeS2fdpVakdAngBmm7mrVS/Zmczry16navGqPF7/8Uzf/4/Qf3Al8QpfbPjCDdF534xdM/D39adLNdfmHt1KmYJlaB3SOle16s3aPYuTl0+6PLj8RmFGGA4czNg9w9Z1s2TZMjh1Kkstek6nk7mRc2lfub1HBirXL1uf4gHFWRK1xJ4FHQ744gu4cgVefjnr67z6KkyeDJ98Ag89lKFbJuyYQO3StaldunbW901H5WKVaVCuAb/sSmnVK13aGkr/449w+bKte3lKsjOZMRvG0LhCY5oENrF9/a7VuuaIVr2I6Ihs36KXKrV6KyI6+1ZHnbp8ikk7JvFw3Ycz1NKfUUZJg/rl6tuXNBeRDFEySkTEBb8d/Y3oi9FuOUUvrQC/ADpU6cCcyDm5JmkAMHH7RLaf3M57bd7Dz9cv0/fXLFWT7tW7M+a3McRejXVDhN7jdDqZsXsG7Sq1o3DeDFS/xGethbN/rf5EnonMHhU/Nvhm0zcEFQmiUxXXZ4mkVaZgGZoHNWfm7pm2rpslEyZYLWudM39gws5TOzl44aBbKznT8vXxpV2ldizet9i+n12GAcOGwc8/Q3h45u//979h5Eh47jl45ZUM3XLg/AHWRq/lwdr2VkWl6lOzD+sOr+PwxcPWA888AxcvWt/rHGjJviWYZ0y3VEXBtVa96bunk5ic6JY9XBV9IZroi9E5okUPoH65+uT1zZut50Z9t+k74pPiM9XSn1GtgloRcTiChKQE29cWkfQpGSUi4oJpO6eRxycPYUaY2/cKqx7GoQuHck3SICEpgbdXvE29svXof0//LK/zSugrnI49zbgt42yMzvu2ndjG/vP779yil5wMTzwBAQFQty688AJMnw6nM9a62Ltmb3wdvtm+wiAj9p7dy9KopbYNLr9Rrxq92HpiqzXbx1tiY2HGDOjbF/Jmfo7YvD3zAKuyxFM6VunI0Zij7Dpt4wyk116DypWtpE1mErFTp8JLL0GvXjBqlFVplQGpJwIOrD0wK9HeUerMwT9b9UJDoU4da5B5DvwLiDG/jaFMgTL0q9XPbXv0r9U/W7fqpc5fyimVUf6+/jQJbMKqQ6u8HUq6EpMT+e/v/6VdpXbUKlXL9vVbBbciLjGO34/+bvvaIpI+JaNERLIotUWvXaV2FAso5vb9UocNz4mc4/a9POH7Td8TdS6KD9p+4NIQ0pZBLWlcoTEjI0Zm+2G2mTFj9wwcOO6c6Bw2DMaOhQEDrPae776DPn2sU8fq1LGqP6ZOhTNn0r29VIFStK3UNle06n278Vt8Hb62DS6/0QM1rGHhXm3VmzMHLl3KUoseWMmoemXr2TpP6046VO4AWNUytgkIsNr1TBM+/TRj96xcCYMHW4men3+2hoVn0MQdE2kW2IxKxSplMeDbq16iOrVL1752qp7DYSXatmyB9evdsqe7XIy/yMK9Cxly7xC3HLyQqku1LhTwK8DUP6a6bQ9XRERHEJAngLpl6no7lAxrHdyajcc2ciHugrdDucms3bOIvhjttmq7FkEtALJtclMkN1IySkQki7ad2Ma+c/vc3qKXqmzBsjSp0CRXzI2KvRrLeyvfo0VQC7pUdW0eksPh4JXQV9h3bl/2aKGyyYzdM2ge1JwyBcvc+qLPP4fPPoNnn7XaeZYssY6qX7MGPvgAype35s707w/Vq0N0dLrL9L+nP/vO7WPz8c3ueTIekJCUwA9bfqCH0YPyhcq7ZY/KxSpzb5l7vZuMmjDB+r62apXpW89dOceaQ2s81qKXKrhoMNWKV7NvblSqzp2t2UoffABRUbe/9o8/oGdPq5pq9mwrmZVBf5z8g20nttk+uPxGfWv2ZfWh1Ry/dNx64KGHoFAhqzoqB1kWtYzE5ES6V+/u1n3SnqqXHVv11h5eS6MKjbLUgu4tbSq1IdmZnC2ro8ZvG0+FQhXc9r4qVaAUtUrVUjJKxIOUjBIRyaJpu6bh4/D5s1rCE3pU78FvR3/jWMwxj+3pDqPXj+bYpWN81O4jW45I71WjF1WKVeHTtZ/m+OoegKhzUWw7se32LXo//2wNcO7b15qBk/o6+vtblR+vvw6LFsG5c9Zcnfh4ePLJdFt+etXoRR6fPEzeMdlNz8j9Zu6eyanYU7YPLr9Rrxq9WHNoDScuuXCSW1adPQsLFsDAgZmq6km1aN8ikpxJHk9GgVUdteLACvvnsfzrX5AnD9SqZSVcO3aEv/zFSlD99BOsXm1VF3XpAvnyWa9f8eKZ2mLijon4OHzc2nIGVqueEyczdqUkOwsVgiFDrEHrGWy7zQ7m75lP4byFPdKe1v+e/pyKPcWvB7LXSbNXrl5h07FNhAbmjBa9VE0Dm5LXNy8rDqzwdijXuZRwiUX7FtGnZh+3tGCnahXUitWHVueqKmuR7EzJKBGRLFq8bzFNA5tSqkApj+2Z2rI1N3Kux/a0W+zVWD5e8zFdq3X9syzeVb4+vvy92d9Zf2Q9qw+ttmVNb0qt8LplMmrRInj0UWjdGsaPv31iws8P2rSxWpkWL4Zvbj66ukT+ErSv3J4pO6fk2GTe95u/J7hIMB2rdMzUfXlOn4ahQ6FbN1i48I7zeXrV6IUTp3faZadNg6tXXWrRK5m/JI0rNLY5sDvrUKUDl69etv+krgoVrPf1Cy9AvXpw4YJV+fTmm1Yip2VLqF/fSsouWAAhIZla3ul0MnHHRNpXbn/7KkUb1CpVC6OEce1UPYCnn4aEBKsVNwdwOp0s2LuADpU7eKQiqEvVlFa9ndmrVW/jsY0kJifSrGLOGF6eKl+efDSr2IzlB5Z7O5TrLNy7kLjEOHrX7O3WfVoFtyImIYatJ7a6dR8RsSgZJSKSBZcTLrPx2EbuD77fo/vWLl2bkKIhOXpu1MK9Czkfd56/N/27res+Wu9RSuYvyadrMzg/JhubsXsGdcvUTX8+zW+/WTOh7rkHZs60qj0yYuhQaN/eqqbaf/MA7v61+nPg/IEcObz1UsIllu9fTr9a/TI+fyw+HkaMoHafPtYH/c2breqZhg3hl18gKf2/Gb+3zL2EFA3xTqvehAlW9U+DBpm+NSk5iQV7FtClahe3VhbcSpuQNvg6fO1v1QNo1gxGjIApU6z5SidOwOXLsGuXlWD85huIiLCSVZm04cgGos5FMaj2IPvjvoHD4aBvrb78euBXTl0+ZT1Yuza0aGHNgssBieLtJ7dzJOaIy+3XGRXgF0APo0e2a9VLPZEup5ykl1br4NZsPraZ83HnvR3Kn6bvmk6p/KVs+wusW2kZ3BLQ3CgRT1EySkQkC9YfWU9iciItg1p6dF+Hw0GP6j1YErWE2KuxHt3bLjN2z6B4QHHuD7E3kZffLz/PNnqWOZFz2HXKxlO7POzEpROsObQm/aqoPXuga1drOPmCBVCkSMYXdjjg+++tKqrHHrNO4UvjgRoP4Ofjl+0qDDJiWdQyriZfpUu1DHwAdjph1iwrmTdsGDENGljzhA4csJJSly9bc4juuceat3X16nW3OxwOetXoxdKopVyMv+iW55Ouw4fh11+tqqgstLauP7KeM1fOeKVFD6BIviI0CWzinmRUevLnhxo1oFMnq22vdu0sLTNh+wTy+ua986mWNulbqy9JziRmmbOuPfjEE9a/+2vWeCQGVyzYswAgY/8u2qR/rf6cjj2drVr11kavpVrxah6tnLZLm0ptcOLMNgmZ+MR45kbOpafR0+2J9MDCgVQuVjnbPHeR3E7JKBGRLFh5cCUOHF45sjnMCCMuMY5lUcs8vrerEpISmBs5lzAjjDw+eWxf/9lGz5IvTz5GRoy0fW1PmW3OxomTXjVv+PB7/Lj1wRqsNr1y5TK/eFCQNWPn119h9OjrvlQsoBgtg1uycO/CLEbuPQv2LqCgf8E7/635jh3QoQM88ADkzQuLFrHvX/+CatWsWVuPPQY7d1oVNgEB1p+rVrVeq9hryd9eNXqRkJTw5wdvj5g82UqkZbVFL3Ievg5fOlXtZHNgGdehcgd+P/o7Z6+c9VoMmZGUnMTkPybTrXo3iuTLROLXBXXL1KVyscpM2zXt2oP9+kHBglYyOZubv3c+dcvUddshAunpXLUzBf0LMuWPKR7b83acTicRhyNyXIteqiYVmpAvTz6W788erXrL9i8jJiHG7S16qe4Pvp+VB1fm2JZ1kZxEySgRkSxYdWgV9crW89gHlLRaBbeicN7COfJUvRUHVnA+7rzbqgxKFSjFo3UfZfy28Z6tWrHRjN0zqFysMnVK17n24MWLVgvZyZMwf77VqpVVjz1mVVe99hpERl73pY6VO7L95PYcNSDf6XQyf8982lduj7+vf/oXnTtnnThYty5s2gT/+Y811LpjOvOlfH2tD/+bNlmvdcWK1+YRHbdOOQutGEqp/KU826o3YQI0amQlzrJg3p55tAhqQdF8RW0OLOM6VO5AsjOZ8P3hXoshM5YfWM6Jyyd4sLZ7T9FLy+Fw0LdmX5ZGLeXclXPWgwUKWEPrp0yBmBiPxZJZF+IusObQGrpW6+rRfQP8AuhRvQfTd0/PFq16UeeiOHn5ZI4bXp4qb568hFYMZcXBFd4OBbBa9ArnLUzbSm09sl+r4FacuXKGXadzboW1SE6hZJSISCYlJCUQER3h8Ra9VP6+/nSu2pm5e+aS7Ey+8w3ZyIxdMyjgV4AOlTu4bY+H7n2IhKQEFu1d5LY93OVi/EWW7V9Grxq9rj9lcPhwq6pn2jQrIeEKhwO+/daaNfXoo9fNRupQxfq+LI1a6toeHrTz1E6iL0bTteotPgAnJ1uVUF9/bQ2D3rMHnn/eGux+Ow6HlQBcvdqaO3TkCHTuDOfP4+vjS0+jJ/P3zCc+Md7+J3Wj3but5FgWq6KiL0Sz9cRWr7XopWpcoTGF8xZmyT4Pteq5aObumeT3y+/x5ErfWn1JTE68/i8cnnjCqs6bnH1PvFwStYQkZ5LHXy+AfrX6cTr2dLY4BS51XpTbK6cTE61Kzvnz4dIlW5duE9KGrce3er2KMTE5kVnmLLpX707ePHk9smer4FaA5kaJeIKSUSIimbTp2CauJF75839YvKFH9R4cv3Q8Rw2bTnYmM9OcSZdqXQjwC3DbPs0Cm1EioASzI3Ne5djCvQtJSEq4vnLs8GGrPeeJJ6616bmqfHkYM8Ya6jzyWktjvbL1KJm/JIujFtuzjwfM3zMfuM2Mmq++gpUrrSHWY8ZAiRKZ36RTJ5gxw/rg16MHxMbyQI0HiEmI8UyVz88/W8mxAQOydHvqa9StuneTUX6+foXgvUkAACAASURBVLQJaeO5uVEuSD0Vrm2ltm79eZWe+8rfR1CRoOtb9Zo0gZo1s/Wpegv2LKBovqI0DWzq8b2zU6texOEICvkXolapWvYs6HTCsWNWe/Znn8Ejj0D9+tRv1cqabdetm/UzKta+OZKtQ1rjxOn1OVyrD63mdOxpetfwTIseQKWilahQqIKSUSIeoGSUiEgmrTq4CsDtp7rcTueqnXHgYPG+nJM0WHd4HccvHXf7IGBfH1+6V+/OvMh52aJlIzOW7Fty84e5ESOs6p7hw+3dbNAg6N0b3nrLGuAN+Dh8aF+5PUv2Lckx8zIW7F1AndJ1CCwcePMXDx2CYcOsOVGPPebaRh07wk8/WUOk+/enXcVWFPQv6P5WvUOHYNQo6N49a3PCsFr0QoqGULNkTZuDy7wOlTuw//x+9p3d5+1QbmvP2T1EnYvy2KlwaTkcDvrU7MOifYuutRs7HFZCOiLCOiUwm0lN3nWs0tEt8wDvJMAvgDAjjOm7vN+qtzZ6LU0Dm9ozbPv4cSsJWb68VZn5yiuwdCmULcvJAQNg/Hj473+t98WAATcduJBVjSs0JiBPgNcrzabvmk6+PPnoXLWzx/Z0OBy0Cm6luVEiHqBklIhIJq08tBKjhEGZgmW8FkPJ/CWpX65+jqgwSDVj1wz8fPw80ioUZoRxLu4caw5l/9OnUjmdTpZELaFtpbbXPsQcO2a11D38MISE2Luhw2F9iClc2Pqb9pQPMR0rd+TE5RNsP7nd3v3c4GL8RVYdWpV+wsDphKeesn7/5pssnUB3k/794csvYd488v31GbpV6cIscxZJyUl3vjcrnE6rtTA52ZpzlQVxiXEs27+MbtW6Xd/66SWpraDZPZH+56lwXkhGgdWql3rgw5+GDIE8ebJlddTWE1s5dumY114vsFr1zlw549XB22evnGX7ye00r9jc9cWSk62f/YcOWQdPLF8Op09bLcMLFnDkb3+DwYNh6FDr59LcufDXv1o/N1zk7+tP86DmLD/gvdcy2ZnM9F3T6Vy1MwX8C3h071bBrTgSc4Soc1Ee3VfkbqNklIhIJiQ7k1l9aLXX5kWl1b5SeyKiI7iUYO+sCHdwOp1M3z2ddpXbeWToe8cqHfH39c9RQ973ndvHwQsHaV+p/bUHP/vMShK9/rp7Ni1d2mpj27gRPvoIuJYsyAlzfZZFLSMxOTH9GTU//WTNevrwQ3sTeUOHwvvvw08/8e7sGE5eOsm6w+vsWz+tiROteTAffJDl57Dq4Cpir8Z6ZY5PeqoVr0ZwkeBsn0hfuG8hRgmDSsUqeWX/poFNKV2gNPP2zLv2YOnSVpvo//5nWwWMXVJbQTNVweJ0WpU9FSpYbYgLF7qUSElt1Zu6c2qW13DVwr0LSXYm/z975x0V1dVF8T30jhQVUEHaDNgFldgIiIiKYgO7scRETTQxGjWWRE0sMZrEaDQaG2rsBREUUCGW2LEDAlJEEJDe6zDv++OIirSZYRp+77dWVpI37917Zphy37ln7yOZSp5Nm4CLF6kycv58wMWlfpnx7NnAqlWAr6/Eqmhd27viScYTZJVkSWQ8UQlPDcfLwpcylehVw/pGsbDIBjYZxcLCwiICERkRyCvLQ38L+Sej3K3dUSmobBaLpScZT5CQmyCzRaWOmg7cLN3gH+PfbMrsq5M/1ckgZGRQomjiRMDaWnoTjxlDkr01a4CUFLTVawt7Y/tm4Rt1/tl56Knr1TYKfvWKbt769KEuepJm2TLgm2/AOxSMldeUpCPVy8oCvv6abtLnzRN7mJD4EKgpq+Fji48lGJz4cDgcuFu5IywxTO5yqvoorSzF5eeXZSoNeh8ljhI8rD1wIf5CzUYVM2bQd8O5c/VfLAeC4oLgYOoAEx0T4S6Ijyfp6yefUDLq1StqGNC/PxAmng+bhorGG6leZZV8knWBsYFoqdUSPds0sdHE7dvA8uXU2fOzz4S75ocfgC++IGn3b781bX6QbxQAuflGnX56GipKKhjGHSbzue2N7WGsZYyrLxR/fcXC0pxhk1EsLCwsIlDtFyVP8/Jq+pn3g4aKRrOoYPF76gcOOPDieclsTi+eF+Jz4xGdFS2zOZvCpcRLsNC3gLXB68TTb78BpaXSq4p6l3XrSBLy2szc3codV5OuooxfJv25xaTao8bdyh2qyu91xps3j7pL7d4NKEvAt+V9OJw3RsKrwgTQ2uUr+aTnN98A+flNfg4h8SHob95f5jKXhnC3dkd+eb7CNmC4/PwyyvhlcpWcAYCHtQeySrJwP+3+24ODB5N32J498gvsPXJLc3Ej+Ub9HS3fpbKSkiWdO1PCZft24NYtIDaW/vv5c8DNDXB1pU6WIjK2w1hkl2bLxeuIL+AjOC4YQ22HQonThFus/HzaIGjTRjSJMYdDcl5vb2DhQqo6awI9zXpCW1VbLlI9hmFw6ukpuLZ3hYGmgczn53A46G/ev1ls9rGwNGfYZBQLCwuLCFx7cQ1t9drCQt9C3qFAQ0UD/c37K7zcBQBOR59GX/O+MvXZqt5NbQ5SvSpBFcISw+Bu5U6+PtnZwLZtZEhrZyf9ANq3ByZNohufzEwMsh6EMn4Z/nsh+s2grHiS8QQvC1/WThj4+QEnTgArV5Lxr7RQUgJ278Zz565YdTIbyTs2SG7s4GCSGS5dCnTqJPYwKQUpiMiIkGuFT124WbopdAOGoLggaKpo4uP28q0mG2Q9CBxwEBwX/Pagigp5vJ0/D6Smyi+4d7iYcBECRlB/R8tq7t4FevakpgKDB5MR+5w59FlSU6P/josjWdrTp1Ql5eEB3LkjdCweNh7QVdOVS1e9Wym3kFuW27RKnmqfuBcvgMOHgRYtRLteWZm+OwYMoCq6oCCxQ1FVVkU/835ySexFZkYiLicOo+1lL9GrxtnCGQm5CUgpSJFbDCwsHzpsMoqFhYVFSBiGwdWkq3C2cFYII2CAKlgiMyORWqgYNyV1EZ8Tj8evHsvc96GtXls4mDrgbKziJ6PCU8ORV5aHgVav/aI2b6bKnuXLZRfEd99RJdYff+Dj9h9DVUlVoavu3hhMv3sDnJtLMpVu3ajrlLRRUYHmyTO4agG0nbuMDOGbSmEhGa/b2ze5Kq462eNh7dH0uCSIkZYRHM0cFTaRHhQXBFdLV2ioaMg1jpbaLeFo5oiQ+JCaD8yYQZWMBw7IJ7D3OP/sPAw1DeHUxqnuEwoLSTb70UdAZiZw+jT906ZN7XM1NEiempAAbNwI3L9PUtXXnnaN8UaqFy17qV5gbCBUlFTgbuUu/iD795NX3OrVJDMWB3V1Ssp37kxVUrfE97Rzae+CyMxIZBRniD2GOJx+ehoccDCCN0Km875LdQV8dUU8CwuL5GGTUSwsLCxCkpCbgLSiNIUwL6+mOnlxKeGSnCOpn2o/nVH2o8QfhM8HcnJEvsyL64WbyTeRWZwp/twyoPrv52blBuTlkdRizJgmVcWIjL09MHo08Oef0CmtQp92fRTaN+p83Hl0bd0VZrpmbw8uXEg3u3v2AKqq9V8sQVq3bI+flnyEa510KRG2bFnTulmtWAEkJ5M8T129SbGFxIfATNcMnVrJ8H0kJO5W7riVcguF5YXyDqUGcTlxiMuJk7tErxoPaw/cTL6JvLK8twdtbalqaO9eiXROawoCRoDguGAMsh70tgvouxQUUDXUli1ksh0VBYwS4rdASwv49ltKSo0ZQ35IDx4IFdP4TuORU5pTO4knZc49O4f+5v3Fb9IRE0Med66uTTch19OjqihTU8DTk2SQYuDa3hWA7H2j/KL90KddH5jqmsp03nfp2rordNV0WakeC4sUYZNRLCwsLEJSvSBRpGRUV5OuaKnVUmErDABaVHYz6Yb2LdqLfnFZGbBzJzqNGQMYGwOLFwMVFUJf7sXzAgOmZkcqBeRiwkV0N+kOYy1jYOtWuoFbsUL2gSxbRn4l27fD3codD9MfynxHXBjyy/Jx/cX1mh3iLl4E9u2jiigHB5nGM6TrGLiNKEDBtAlUwTF1qkjv0zfcvEl//y+/FL8q4jVVgipcjL9IUi8FqeR8F3crd/AFfLlIgBriTcWdgiSjBtsMRhVThdCE0JoPfPop8OyZWL5KkuRB2gO8Kn5Vv1/UvHkUZ3AwSY/1RUzU6OqSfNjYGJg2TajPlYe1B4y1jPHP439Em6sJJOUlISIjQnyJXnk5MH48oKlJMjtJeN21bg1cuABUVVFiTwwcTB2go6YjU9+ohNwEPEx/KFeJHgAoKymjn3k/1sSchUWKsMkoFhYWFiG59uIajDSNYN9SDB+a69fp5tLTk+QK27bRIvH5c1ooiokSRwluVm64lHBJIbvGpRWm4WbyTdElevn5wIYN5GU0ezb4LVoAkyeTbOOjj8hPRAi6mXRDW722Cu0bVVxRjBvJN0jaUVAA/P474OVFUjNZ4+BAXi6//47BZiRRUMSqu4sJF1HFVL1NGBQVUccpLpe8omTMSLuRqFIGfGc5UVfCgwfps15QIPwg5eXAzJlA27ZkKN9E7qbeRW5ZLgZbK5ZfVDV92vWBlqqWwvlGBccHw9bQFtaGUuxgKQJObZygp65Xu8rH25sSNXv3yiew1wTFUfLOw6YOKeixYyQlXLGCOueJi6EhsHMn8PixUJ8NVWVVjO84Hv4x/sgvyxd/XhGo3vDwtPUUb4AlS4CHDwFfX8DMrNHThcbKihL0AQFiyfVUlVXR37y/TJNRfk9fV1PbNaGaWkI4WzgjKjNK4aurWViaK2wyioWFhUVIriZdRT/zfqJ3yXn0iG5Mk5PJcHb3bmDuXDJmtbQkOUKHDsDEidTOXUTcrdyRXpSOyMxIka+VNv4x/mDACC/Re/WKqnPMzUmm0LUrEBaGaF9fuqnx96fX0dER2LGjUYkKh8OBF9cLIfEhCtsZ7mrSVVQKKklyuX07+R59/738Alq+HMjMRPdz92CgYaCQVXdBz4Kgr66P3u1604HVq8nwd88e8pyRMTaGNrA3tod/7Fl6/fbtAy5fBj7+WHiT6fXrScK0cyclGZpISFwIOOC89SFTMNRV1OFs4axQ768yfhn+TfxXoQzfVZVVMdBqIILjgmtuOGhrUyXN8eOiJT0lzPln59HTrCdaabeq+cCLFyTL++gjyXyfeXlRk4W1aylp0wiTu0xGGb8Mp56eavrcQnDu2TnYGNqAa8QV/eLAQOCPP8gra1gTzM/r4+uvgZYtxf47uLR3QXRWNNKL0iUcWN2cjj6N7ibdYWlg2fTB+Hzg2jXxKlXx1jdKkZt5sLA0Z9hkFAsLC4sQpBWmIT43/s3CRGji4ijppKtL1VEPHpCZ68uXdLO6axctFHk8MnSdOFHkSqlqs1RFNJv2i/aDraEtOrbs2PCJeXnkt2NhAfz8M71m4eFASAj5Z1TLjLy8aHfc2Zk6Do0YAWQ0LCPz4nmhpLIEYYlhEnpWkuVSwiWoK6ujn1F34NdfqTKpRw/5BdSvH+DsDKVNv8LDfAAuxF9QqKo7hmEQFBeEQdaDoKKkAqSkkLTtk08odjkxgjcCV55fQW5pLsmJAgPp89+7d8OVfCUlwNWrVPExaRIwRDLysJD4EPRs0xNGWkYSGU8aDLIahJjsGCTnJ8s7FADki1PKL1UYiV41HtYeSC5IRnRWdM0HPv2U3j/HZd85DgCyS7Jx++Xt2q9XVRV9Hvl8kpypqEhmwi1bACMj+nxVNmxO3qtNL9ga2spEqlf9++Jp6ym6JDYvD5g+nSphN0iwI+e76OhQZ85Ll2jdISLVvlGykNSmFabhRvKNpkv0ystpfcXj0XrB05PWXiLSw6wHNFQ0WN8oFhYpwSajWFhYWITg2gvqpiKSX1RqKuDuTgvyCxeo2gegxIqZGVVNzJwJ/PILdb7580/yvVm1SqTY2um3A8+Ip1AVBgCQV5aHsMQwjLIb1fACnWHoddi1C5gyBYiOppsrR8e6zzc1pbbmf/xBr2uXLg22r3Zp7wIdNR2FlepdTLiIfub9oLlnP1XG/fCDvEOi6rSUFMyJ0kZqYSqeZgkni5QFj149QlpR2lu/qDVrqLOYiJ8bSePF80IVU4XguGA64OEBXLlCN0V9+5I0d/16SroOH043n0ZGVOHy8cfkpbN5s0RiyS3Nxe2XtxWui977uFu/TqQryHdXUFwQNFQ04NLeRd6h1KD67/jmvVVNr15UVbtnjxyiom6NAkZQ07sNIDn1lSv0m2YtQbljtVzv0aNGu+txOBxM6TIFl59flnqyMywxDGX8MvH8ov74g7739+5tcsOCBpk9m9YdK1aIbHrf3bQ79NT1ZJKMOhN9BgDET0aVlNBram0NfP45vWeWLwf+/RdwcQHSRavuUlNWQ++2vVnfKBYWKcEmo1hYWFiE4GrSVWiraqO7aXfhLsjJoZvRrCxKlNgL4TP16ae0Q7pmDXBONMPtgVYDcSXpCsr55SJdJ00CYwPBF/Abl+gdOwacOkXPe9cu8v1pDCUl4KuvgLt3SX4wdCh5cQkEtU5VV1HHYJvBCIgNgICp/bg8SS9Kx5OMJxjSxoVu4NzcqJJG3gwaBDg6ovfhq1CugkL5+px/dh4AGTsjIYFuxD/7jPzF5EivNr3QSrsVzsa+k/R0cCBT8latSJq7bBm935OTgXbtgHHjqCLq4EFqYW9sLJFYLiVcgoARKJTcrC46tuwIUx1ThXl/BcUFwaW9CzRVNeUdSg0sWljAztgOwfHvJaM4HPrduHWLJJ4y5nzceRhpGqGH2TuVnOHhJAfz8aHqKEkzYgRVEP/0EyWlGmBSl0lgwODQk0OSj+MdAmMDoaOmI3rldF4eeQSOGgV0F3JtIS6amvR3uX6dzORFQEVJRWa+UaejT4NnxIO9sYjenPn5lKBs357WAtbWVFl95w6tLQICaKOrTx8y1BcBZwtnPEx/KDP/MRaW/yfYZBQLCwuLEFx7cQ192vUhWVBjFBeT70NsLHDmDLW1FgYOh6onuncns+6EBKHjc7dyR0llCW6liG5QKi38ov1gpmuGXm161X9Sejp1DnNyAhYuFH2Szp0pIfXFF7Qb+vffdZ42nDscqYWpuJ92X/Q5pEh1h6yxNwvIL0sRqqIAei8uWwbVhOeY98JEYSpXAEoYOJg6wETHhKqhVFXl03nwPZSVlDGcOxznn51HRdU7/iSWlnTTHBtL3w3Z2eR5ExBAHmFLl9LnvV07icUSEh8CfXX9hj97CgCHw4GHjQdC4kNQWdWw7EraJOQmIDY7VuEketUMth6Mq0lXUVpZWvOByZNJBlfPd5+0EDACBMcFY7DNYCgrve78VlxMUlMTE/L0k1YXxy1bqOKlEbmelYEV+rbri4OPD0pNasww1K3V3codaspqol28eTMlUWTVdGHGDErWiFEd5dreFbHZsUgtFNIDTwxySnPwb+K/GG0/Wni5Y1UVeQZaWFCyv0cP8oi6coU2VarHGTKEqqMKCykhdeeO0HE5WzhDwAhwI/mGGM+KhYWlIdhkFAsLC0sj5Jbm4smrJ8JJ9CoqqMvR7dvAkSNU6SIKmprAyZP0397eQGlpw+e/xqW9C5Q5ygqTNCipLEHQsyCM5I2s3/CdYUg6UFxMHYTE9RXR0CA5iJsbsHgxGee+x1DboVDiKCmcVO9iwkW0UjNE293HScrlLOLOujQZORKwt8e3VypxJeFfhai6yy3NxY3kG5QwiIoiP5q5c0m6qQB48bxQUF5Q219EXR2wtaVmBVKGYRiExIdgoNVA4ZLncsaL64W8sjxcT74u1ziCnpHUV2GTUTaDUcYvw5WkKzUfaNWKKoV27iQvQhkRnhqOrJKsmq/XggVUdXLgACWLpIWRESW7Hj4kj8EGmNJlCqIyo/AwvXHTc3F4kvEEKQUpokv0cnOpKmr0aGrUIQvU1CiBf/8+WQOIQLV0VZpSPb+nfqhiqkTrovfrr/ScBgwA7t0jCX993oG9egE3bpCHp6trg/L+d/mo7UdQUVJhfaNYWKQAm4xiYWFhaYTrydfBgGm8BL+qCpg6lUrgd+6kRaY4WFmRbOfBA7rRFgJ9DX04tXVSmGTUhfgLKOWXNuz7cPgwdcdbuxaws2vahBwOSfyqqoBZs2rt+hprGaNvu74KlYxiGAaXEi5h2SsuOElJ1H5bkVBSApYuRZvn2XCNKsXNlJvyjggXEy6+9aj54Qcy5l2yRN5hvWGg1UBoqGjI9X0WlRmFlIIUhfeLqsbdmipK5P3ZDI4PhrWBNWyNbOUaR304WzhDQ0UDIXEhtR9ctYq++9askVk8Qc+CwAFVtgGgKuC//6YNAVdX6QcwahQwYQLJ9R4/rvc0n44+UFNWw8HHB6USRmBsIADU9s1qjM2bqQuirKqiqpk8mX5vv/9epGYp3Uy6oYVGC/ybKB2pHsMw2HZ3Gzq16lRT9tkQkZH0PMaMIam/g0Pj19jaUkKKxyPvPl/fRi/RUtVCT7OetRPBLCwsTYZNRrGwsLA0wrWka1BVUm1Y8sIw5GF09Ch1xJk5s2mTDhtGpfR79wptTutu5Y7w1HDq5iVn/KL9YKBhUH8CLy0NmDePyuXnz5fMpJaW5BkRHEzJvPfw4nnh0atHSMpLksx8TSQ6KxovC15iUvDLtwtjRWPCBAgszLHiGnChrptgGRMUFwQDDQM4pavQzceCBVQloSBoqWrB3codZ2POyq0DYUg8/Z3eJAkUHB01HbhZusn1NSvjlyEsMUyhPbY0VTXxscXHtX2jAPru++wzYPduID5eJvEEPgtErza9YKxlTM06Zs6kZMCPP8pkfgAk1zMwIK/FeuR6hpqG8LT1xOEnh8EX8CUewrln59DDrAfJhoUlN5eSUWPGUAMOWaKsTLK2qCharwh7mZIynC2cpeYbdSP5Bh6kP8C8XvOEk+hVVpInmb4+8NdfoklCTUyoq6CLC7131q9vVLbobOGMu6l3UVJZIvw8LCwsjcImo1hYWCSGcl6eyD4EzYGrL66iV5teDZvaHj1K/i/ffks7w5Jg1Srqxvfll1R+3ggDrQZCwAgQlhgmmfnFpLKqEgExARjOGw5VZdXaJzAMVS+VlgL79tHiWFLMnUtyt/nza3XN8eJ5AQACYgMkN18TuJRwCQMSAeOYZHrfKCngT7KKCpS+WwqnFCA36LRcQxEwAgQ9C4KHjQeUf1hJMqAFC+QaU12M4I1AUn4SHr+qv1pDmoTEh8De2B7m+uZymV8chnOHIz43HtFZ0XKZ/1rSNZRUliisRK8aD2sPRGdF151QX7GC/NNk0FUypSAF4anhGMEbQU0jpk+nLmaHDpEUTFYYG1Mi4v59krzVw5QuU/Cq+NUbjz5JkVWShZvJN+Fp6ynahb//TlVR8vII9PYmaeDKlQ16br2Pi4UL4nPjpdKdcOudrWih0QKTOk8S7oJ16+jvvnMnNTERFT09kvRNnEheU40k5pwtnMEX8HEzWf4VwiwsHxIKuPJlYWFpdvz3HzBgALoNHEhdzVJS5B2RxCipLEF4anjDflEVFXQj0K0bVUVJCmVlkrK1akWLx5ycBk93auMEXTVdXEq4JLkYxCAsMQy5Zbnwtveu+4SDB8m8ef164TrniYKSElWSlZSQqfk7yVGuERc8I57CJKMuJlzEyjuaQOvWJJ1QVKZNQ6GRLnxOxyK7JFtuYTxMf4hXxa8wtdCaqt+WLKEbCgVjGHcYOODIRXZWUlmCK8+vNBuJXjXDeVQVKK/PZlBcENSV1eFqKQN5WROortyqrn6rgakpVeceOgREREg1jur39ki7kVSddOECJViaKrcWh9GjAU9P+j3JrbsqeKjtUBhoGEhcqhccFwwGjGjJqJwcqory9pZ9VVQ1Skokb4yPB/bvF/qy6s+HpH2jXha8xKmnp/Bp90+hrabd+AX37pEkdfJkkmuKi5oarUc6dGi0OqpPuz4AgNsvb4s/HwsLSy3YZBQLC4v43LyJF052QP/+KHkUjjTv0cDVq0DHjiQv+wCqpG6l3AJfwG/YL2r3bup8t26d5KtbjI2BEyfImHbKFNqFrgdVZVW4tHeRu2/UiagT0FXThbu1e+0HX76kG6b+/enf0oDHIxmCn99bM/jXePG88G/ivygoL5DO3EJSWVWJrJuhcI4upddBQ0Ou8TSIhgayv5yOAc+BJ0c2yy2M88/OAwwwYHcYySyE9FOTNa11WsOprRPOxso+GXU16SrKq8qbjUSvmrZ6bdHdpLvcfKOC4oLwcfuPoaUqfYP5pmBnbId2eu0QHFeHVA+gqlxdXal3l/SP8YetoS3sUisoKezlBXz+uVTnbJB166grXT2bQeoq6hjbcSz8ov1QVFEksWkDYwPRWrs1HM0chb/o99+po5u8O6cOG0ZdbH/8ESgXrjlFl9ZdYKZrBt9HvhINZUf4DlQJqvBFzy8aP7m8nLw5W7WiRGhTUVKiz82TJw0amrfQaAEbQxuEp4Y3fU4WFpY3sMkoFhYW0bl7lyqg+vSBRmQMfvDUgvHsQnR2vILd+75CVbcuwKeffhBVUteSroEDzptdsVoUF9MOo7MzMFhKfiNOTrSAPX+eKqUawN3KHfG58UjMTZROLI1QWVUJv2g/ePG8oKHyXoKFYcjXpLKSkpXSlKUtXAg4OlLCIivrzWEvnhcqBZV1mwDLkDsv72DOlRLwNTWAOXPkGoswtF2yFsktOLBc/1eDCVFpcib6DObl86B2/SawfLlMOtOJywjeCISnhuNlgey6mwFASFwINFQ08LHFxzKdVxJ48bxwI/kGMoszZTrv87zniM6KVniJHgBwOBwMthmM0MRQVFbVIa8yNKRGCP7+1NFVCuSX5ePfxH/hbekJzqRJNOfu3aJ59kiaLl2ASZOAP/6ot6PglC5TUFJZAr+nonWRqw++gI+Q+JA3nVqFIieHYvTxATp3lkgcYsPhUPOQ5GQynhcCJY4SvvnoG4QlhuF2imTeX+X8cvx9UhVRswAAIABJREFU/28M4w6DlYFV4xesXEnG5Xv2kF+YJJgwAWjXrtHOjD3MeuBeWuOWCSwsLMLDJqNYWFiE58ED2gHt1QuC27ew3lMfbivbY+HJVJybGQZrXWt89vRntB4SiaCvPcF8AFVS115cQ1eTrtDX0K/7hC1byJto/XrpLsbnzAG6d6fOMQ3sYlZXI8mrOury88vIKc2Bd4c6JHr79tHO44YNgI2NdANRUaH3XU5ODYP03m17w0jTSC5VK+9y59YpjI8A+J9Ok9yCWoqoaOng9EQHWMRngxHB9FZSJOQm4F7qPSwLLgbMzSmpqcDIy58sJD4EzhbODfvbKSjDucPBgKEKOBkS9IyqIZpDMgog36iC8gLcSrlV9wlff00eOsuXS2X+oLggVAoqMfdUCiUF9u0Tz7NH0qxeTd3hfvqpzof7tOsDyxaWEpPq3Ui+gbyyPAzjDhP+ot9+A4qK5F8VVc2AAWTivXYtbawJwSzHWTDQMMD6/9ZLJITjkceRUZyBeb3mNX7yjRvAxo30/S/JzT81NdrAunaN5qgHR1NHvMh/IfOEOQvLhwybjGJhEYJbKbfgdcQLz7KfyTsU+REWBvToAfz3H5g1azBxU2+sdCrBvkknoK+hD1dLV2z/aDtufnoTfSz6YajBOXT9goOE9vrNtkqqsqoSN1Nuwtm8HoleTg4lVoYPp65w0kRJiRJez583uIvJM+KhrV5buSWjTkadhI6aTm3PmpQU4JtvaOH7hRCl+JKgSxe6ITt0CAik9tvKSsoYxh2GwNhAVFRVyCaOOjDdcwwcABrffie3GERFfeoMPGwNVC5bIrSsQ1KcijqFEdGASXQK7Yyrq8t0flGxN7aHtYG1TGVnL/Jf4GnW02bnF1WNg6kDzHTNZJ4oDooLgmULS3CNJOxfJyXcrNygzFGuX6qnq0uGzKGh9I+E8Y/xx/hkfZj5nqTEl7QqgkXFyoqkgrt3A89qr9U4HA4md5mM0MRQpBamNnm6wNhAqCqpwt2qDjl6XWRn0+aVjw/QqVOT55cI1dVRr14B27YJdYmuui7m9ZoH/xh/RGZENjmErXe2ws7YDgOtBjZ8YnExyfPMzYFff23yvLWYOZOq/Brw/exh1gMA2OooFhYJwiajWFga4WTUSbjud0VAbAAmnJog1xtYuVFQQN1ybGyAhARsHaiLYy/O4xf3X978OFfzUduPcHbCWTya/QgdnIbBdmQyVnu3fFslJURXOEXhftp9lFSWoL9FPeblGzbQa7N2rWwCGjQIcHWlnd/CwjpP4XA4GGg1EGGJYagSVMkmrtfwBXz4RfthGHdY7cqM5cvJ6H3PHtl2jVu2jBb+s2YBeXkAAO8O3sgry5Ob0XvBqxfwvJyKCJeOgIWFXGIQB3cbDyxxB9SSUoAdO2Q69+nIE9h0TZMM7z/5RKZziwOHw4EXzwuhiaES9ahpiGrpaXNNRnE4HAznDkdIXAjK+GUymbOcX46wxDAMthksXDt5BaCFRgv0bte7bhPzambPJtnR8uUSrUquqKrAnQeB2HGqgr5XG5E1yZwVKyhRXU/l0eQukyFgBDj8pGG5uzCce3YOzhbO0FXXFe4CRauKqqZPH8DDgyqOioT7rvrK6Stoq2rj5+tN+/vfTrmNu6l3Mbfn3MY/f0uXAnFxVImnK+RrLgra2sC8ecDZs1TxVwfdTboDAO6lNp91LAuLosMmo1hY6oFhGPxy/Rf4nPBBd5Pu+HvY37iXdg+rLq+Sd2iyZ9Eiqmzx9cX90gQsurgIw7nD8bXT1/Ve0qV1Fxz1PopTE/ywqlMmTh79gTpfTZ0q86oKcbmadBUA6u6k9/Il7XJOniw77wcOh6qjMjNpYVsP7lbuyCnNwYP0B7KJ6zVXk64isySzdhe9yEjqWDNvHu1eyxI1NZLrpafT+xj0+uir6+NE1AnZxvKal798D90KoHJB/Z8fRcTa0BppvTsh3F6fEqL5+TKZNykvCVYhd2GTWkpmuyoqMpm3qYzgjUBFVQUuxF+QyXwh8SFoq9cWHVp2kMl80sCL54XiymKJd+uqjytJV1BcWdxsJHrVeFh74F7aPWQUZ9R9goYGVRDevk2dSyXE5cR/sflEEXRK+ORfqGiNF0xMqAL36FGyFXgPrhEXvdr0wj+P/2nSNIm5iYjKjBJeolddFTV2LG3KKRqrV5O34p9/CnW6kZYRPnf8HEeeHGmSP+XWO1uhq6aLT7o2ssEQFgZs3UrNPlxcxJ6vUebOJS/CX36p82F9DX3YGtoiPI01MWdhkRRsMoqFpQ4qqyoxO3A2llxagrEdxyJsahg+c/wMM7vPxM///Ywrz6/IO0TZceECycIWLEChQyeMOzkOrbRbYd+IfULtJI/gjUAPsx5YkrAT/O3bKDGxbp0MAm86Yc/DYG9sj9Y6rWs/+NNP5E+xerVsg3JyolbWmzZRUqoOqsvdL8bLVqp3MuoktFS1MMT2vRu777+nncwlS2Qazxt69gS+/ZbkG5cvQ11FHSPtRsLvqZ/sKx3Ly2G27yQuWSuhi4fiV/i8z/jOEzCrfz7dXG3cKJM5z906gF9DgLKunUji0kzoa94XBhoG8I/xl/pcfAEflxIuwcPao9lU+NTFAMsB0FLVQkCMbLy2/nn8D/TV9RuXCCkYg21IGtfgd/zUqYCtLVVHVUmmSjb797UYHgtUrV8nfwPu+li0iORWy5bV+fCULlPw6NUjPHn1ROwpzj07BwDwtPUU7oJffyWZmaJVRVXj5ERWChs3UrW3ECzsvRBKHCVsurFJrCnTi9JxPPI4pneb3nB1WVERMGMGvZfXS8anql6MjcmP6vBh4MWLOk/pYdaDrYxiYZEgbDKKheU98svyMezIMPx9/28s7bcUR8YcedMV7PfBv8Pa0BpT/KYgryxPzpHKgPx80tHb2YFZvRqzz81GQm4CDo8+DCMtI6GG4HA4WPXxKiTmJeJA2yyS2KxbBzx8KOXgm0ZFVQWuJl2Fm6Vb7QefPaPExuzZgKWl7INbuxYoKalXHthKuxW6tu4qU9+oKkEVTj89DU9bz5rt0e/cAfz8KBlkJNx7RiqsXEl/qzlzgPJy+HTwQX55vswTdjh0CPq5JQgd0x3qKorte1QX4zqOw30z4OnAblSdl9p075XGsFq9BUalgMb+f2Qr8WwiKkoq8OR64lzsOfAFfKnOdTvlNvLL85utRK8aDRUNDLIehLOxZ8FIuelFYXkhTj09hXEdxzU7w3cHUwcYaxkjOL4e3yiAKgh/+gmIiKBKoSYiiIrEyF3/4UHXVlCbv6DJ40kNfX2SdAUHA1dqbxyO6zgOKkoqYhuZMwyDM9FnwDXiwtbItvELXr2iqp5x44AOCly1uGoV+WBu3SrU6W302mBq16nY82AP0ovSRZ5uZ/hOVAoq8WWvLxs+ce1aICmJ5Hmy6KC64PV7u57qc0dTRyQXJNdflcjCwiISzWdVx8IiA17kv0C/ff0QlhiGPV57sM5tXY2WvTpqOjg8+jDSitIwO3C21BfLcmfhQpKj+fpiX8xRHH5yGKtdVtfvoVQPQ22HoodZD6y9thaVm36hpMSMGUBlHa2pFYRbKbdQUlkCN6s6klHff0/yBCl1K2oUOzt6/f76iwzN68Ddyh3Xk6+juEK4DjlN5b8X/+FV8avaXfSWLaNOS+90tJMLWlpk0BodDWzcCHdrOUj1BAJUbliPByaAsdd42c0rQawNrdHTrCe+c+EDfD7dwEiRrGP7MPhWFm5OHQB07SrVuaSBF9cL2aXZuJl8U6rzhMSHQImj1OwqfOpiOHc4UgpS8DBduhsWJ6NOoqSyBFO7TZXqPNJAiaOEQdaDcCH+AgSMoP4TfXyAbt2oIqcpv7fl5SgdOxpFqgziNi1X/KTwl18CbdpQUuq9dVpL7ZYYbDMYvg998bLgpchDb7+7HaGJoZjebbpwF6xcCZSVyb6KWlR69gSGDaMqLiEl2Iv7LkaloBKbb20WaaqKqgrsuLcDg20GN9w44NkzSgpNnQr07SvSHGJjbg5MnAjs2kUVwO/xxsScrY5iYZEICv5rwsIiO+6l3oPTbie8yH+BoElBmNF9Rp3n9WzTE6tdVuNY5LEm+w4oNMHBZDa9aBGirHQx9/xcDLAcgKX9loo8FIfDwcqPVyIhNwH/pJynJMqDBzKT+YhDaEIolDhKcGnvUvOB+/eBY8fIl6J1HfI9WbFyJd0QrFxZ58OeXE9UVFXIrJvXyaiT0FDRwFDboW8PVndzWrZMOoajojJkCN2crVkDtcQXGGU/Cmeiz6CcLyMPs3PnoBobh019AE+eCO3AFYzxncbjLD8CudMn0HfE06fSmSg3Fxpz5+NRa8Bk7R/SmUPKDLYZDDVlNal/DoPiguDUxgkGmgZSnUcWeNp6ggMOAmKlK9Xb/2g/bA1t0bttb6nOIy08rD2QUZyBB2kNeAMqKVFlSUIC/VucDTSBAFi0CNqRsfhshBIG9JkkftCyQlOTfhtv3qzTM2vtgLUo5ZfC87AnCsvrbgZSF5efX8bXwV9jGHcYFvdd3PgFkZGU1PjiC2q+oOisXg3k5pK/lRDYGtnCp4MPtt/dLpJa4FTUKaQXpWNer3kNn7hgAfk+Slue9z6LF1P1eR0eWt1NX5uYsx31WFgkApuMYmEBkFmcCZf9LlBXVseNGTfq310W0A7kkr5L0N+8P748/2WTzBsVlrw8kud16ICS5Ysx9sRY6Krr4p9R/0BZSVmsIT1tPeFo6og119ag0msYGXmuXg1ERUk4eMkQmhiKHmY90EKjRc0Hli0jP4pvv5VPYNW0bUuG4AcPAk9qe184WzjDQt8Cvo98pR6KgBHg1NNTGGo7FDpqOnSQYei1ateO5IyKwubNtLj98kv42HuTVE9WcsaNG5FmqIa4gd1hZ2wnmzmlgE8H8m3a52lGHYiWip6gFopvvoFGTgHWzbAB11RBWqGLiK66Llzbu8I/xl9qlbSPXz1GeGo4RtuPlsr4sqa1TmvqyirFBF5ibiKuJF3B1K5Tm63H1mCbwVDmKON45PGGTxwyhHwGV68G3NyA+HjhJ4mIAPr1A7ZuxWFnQ+R7OAst0Zc706dTAmjZslqeWV1ad8FJn5OIyIjA2JNjUVnVeNVYYm4ivI97g2vExaHRh2pUzdfLokXUuEVRvaLex8EBGDGCqpHyhEsuLe23FIUVhdh2Z5vQ02y9sxU2hjZvvM/qJCgICAyk187UVOixJULHjoCXFyXlimtWl+up64FrxEV4KmtizsIiCdhkFAsLyIyyqKIIJ8eeRMdW9XQ6CQ0lc8MJE6CckYmDow6Cw+Fgst9kqfuByJwFC6j7mK8vdkT4IjIzEgdGHoCprvgLAg6Hg1Uuq6g66vE/5Eugq0tyMwmZq0qKoooi3H55u7Zf1OXLQEgILW719eUSWw2++44WunXIBZU4SpjadSouxl9ESkGKVMO4kXwDaUVpNbvo+fuTX9TKlYrVccnMjCoELlzAoPBctNBoIRup3q1bwLVr2NCzAmO7NoPKggZop98O/cz7YW9KAJnS+/sD169LdpLz54H9+/FzP6BTMzR6fxcvnhee5TxDTHaMVMbfensrNFU0663mbY4M5w7HvbR7YsmohOHAowPggIMpXadIZXxZ0Eq7FTy5njjw+EDDaxAOBzh5khqR3LtHxuO//97w725pKf2udO8OxMbi1faNmOSag5G8kZJ/ItJCRQVYs4aqkw4frvWwh40HdgzbgeC4YHxx7osGk8VFFUUYeWwkqpgq+I/3h566XuPzX7xICZUVK+Trlygqq1ZRImqzcNK7riZdMdR2KDbf3oySypJGz7+Xeg83U25ibs+59Sf0KipI2s/lAl/LqevskiXkobV7d62Hepj1YCujWFgkBJuMYmEBEBAbgDa6beBo6lj3CadPU6cRfX36bzs7WBwNwl9DtuFG8g2svybjEmJpcu4cGUV+9x2YHj3g+9AXTm2c4GHTdGPcGtVRRgaUkLp9G/hDsSQ4V5Ougi/g10xGMQxVgLRpQyX3ioChIS2YAgKA//6r9fAnXT8BA0bqctKTUSehrqz+ts11VRXdyPB45PWgaHzxBdCjB1QWLsLEtkOlL9Xj84F581Csr4W9DiRza+6M7zgekZmRiJzoTrvWixaJJwGqi/x84PPPkW1lip+cUduHrJnhxfMCAKlU+uSU5uDQk0OY1HkSDDUNJT6+vKh+zQJjAyU+NsMwOPD4AFwtXWGuby7x8WXJ9G7TkV6UjuC4BozMAUpIffYZJWYGDKANp3796pbYhoYCXbpQo5FJk4DoaPzTlQNwgBF2I6TzRKTFmDGAoyNV15TX/o6f6TATy/svx+4Hu7H+v7rXcQJGgGlnpiEiIwJHxxwVzrS8qoo8N62sgLlzm/osZEu3bsCoUZSwzM0V6pJl/ZYhqyQLu+/XTty8z9Y7W6Gtqo1p3abVf9KWLUBs7NtKZnnQpw/Qvz95aL3nt+Zo6oiUghS8Knoln9hYWD4g2GQUy/895fxyXIi/gGHcYXWX6+/dSz4zjo7kF/T4MZUyz5mDiXO2Y4neUKy+shq3Um7JPnhJk5tLC9ZOnYDvv8fD9Id4kvEEU7tKJqFQqzpq/HgqhV6+nIwqFYRLCZegrqyOPu36vD0YEEDVLStXkh+FovD115QM+O67WskAa0NrOFs4w/ehr9QkQtUSvcE2g9+2Zz58mOSXP/1Eu9OKhrIysHMnkJGBxefzUVBegAvxF6Q338aNQHg4lo7WQw+eK9rotZHeXDLCu4M3lDhKOJJ4luQ/N29ShZQkWLgQSE/HssmmsDHtAPuW9pIZV0601WsLB1MHqSSj9tzfg1J+KeY5NeK90szo0LIDLFtY4mys5F+z/178h4TcBEzrOk3iY8saT1tPtNJuhX0P9wl3Qdu29Fv2zz90s9+tG1WKVlYCWVm0eTDwtU3BpUuAry9gbAz/GH90bd0V7Vu0l9ZTkQ5KSpRUe/68Tv8fAPjJ9SdM6jwJy8OW4/CT2hVUa6+uxamnp/DLwF+E35Tz9SX5/M8/A+rNr2sqVq0CCgooISUEfc37or95f2y8sREVVRV1nlPGL4N/tD+ORBzB1K5Toa9RT3V5Whr9pgwbRhJTefLdd0ByMnDkSI3Db0zM2eooFpYmwyajWP7vufz8MooqijCcO7z2g5s2AZ9+SouzixcBAwOq9ggNBfbvB549w/rFF7D1ijY+PToBZfwy2T8BSTJ/PpCRQc9NXR2+D32hpqyGcZ3GSWyK6uqotdfWgs9UkZm5ujq9zoIGugLJkNDEUPQ17/u23bdAQB30bGzIh0KR0NKiBNn161TV9h5Tu05FTHYMbr+8LZXpb6fcRkpBytvqlYoKiqd7d9qVVlQcHIB582B+5DzcMnWlJ9WLjARWrUKOpxu2WqRjYueJ0plHxrTWaY0BlgNwNOIomGnTqMPjwoXAixdNGzgkBNizB8Vff4FdSg/e+FM1d0bwRuBG8g3EZsdKbMwqQRW2h2+Hs4UzurTuIrFxFQEOhwMvnhdCE0Il3hF0/6P90FHT+SA8tlSVVTG582QExAQgszhTuIs4HKp4iooif6AVK2izzc6ONhKWL6dNNzeqDM4szsT15OsYwWtmVVHVuLtTYmPFCiCmtlSWw+Fgj9ceuLR3wXT/6bjy/Mqbx85En8EPl3/AlC5TsKD3AuHmKyqiufr0AbybaVVnly4U++bNJFUTgmX9lyGlIAWHHh96c6w6ATX59GS02tgKI4+NhIGGAb7p/U39Ay1dSusIIRNhUmXIEJK1bthQY33a3aQ7OOCwHfVYWCSAzJJRPB6Py+PxbvJ4vNjX/65V58rj8ZR5PN42Ho8Xz+Px4ng83sx3HmvF4/HO8Xi8xzweL5rH423n8XgKuOXO0twIjA2EpoomBlgOeHuw2nx50SIy2g4IIKPeajgc4JNPgOhocD75BHPCChC49jnC9/wk+ycgKS5fBg4coOft4ICKqgocjjiMEbwREpV/VFdHxefGU3WUmRktOq5do8SUnMkozsDjV49rSvROnKDF+erVilnpM2MGYGtLi7j3fEB8OvhAS1ULvg99pTL1yaiTUFNWe5vM3bULSEyk3WhFb//944/gmJpi73lVBEadkXwymc8Hpk0D9PSweYoN1JTVMMZegRN0IjK+43jE58bjXuYj8tXIygKcnMiXRhwKCqgy094eh0bZgAHT7CV61cxynAVNVU38dFVyvxGBsYF4nve88Y5UzZTh3OEoryqXaIOBksoSHI88Du8O3tBW0278gmbA9O7TUSmoxKEnhxo/+V1atwaOHyfrgaws2mh78IB8lt6p/g2MDYSAEWCkXTPyi3oXDof8srS0qPKLX9tfS11FHafHnoa1gTVGHhuJp5lPEZERgSl+U9DTrCd2DtspvNH9L7+Q5+avv9LczZWVKymx9uuvQp3uYe2B7ibd8fP1n+H31A8TT01Ey40tMfLYSATFBWFsx7EInhSM5G+SYWNoU/cgt27RZuiCBbT5J284HLJCiIqiDtOv0VXXJRPzNNbEnIWlqcjyTmEHgG0xMTFcANsA7KzjnEkAbADYAugNYBWPx2v/+rFlAJ7GxMR0AdAZgCOA5r+txSJXGIZBQGwABloNfFsFU1UFzJlDrWRnzaKdwvo060ZGwJ49qAoLBV9NBf1mr1OIhIrIMAz94LZrR8koAEHPgpBVkiUxid67vPGOurqGjFenTQM8PCiGpCSJzycK/yb+CwBvOyry+bQo69SJZIWKiKoqSS0iImqZbeqq62KM/RgcjTiK0spSiU7LMAxOPj2JQdaDqOS+uJikec7O9PdUdPT0gC1bYJ6Yg6nXCiUv1Xstz6v680/sTjmLobZDYaBpINk55Mgo+1FQVVLFsYhjQN++wI0bVOXo7AycFUNetXgx8PIlsHcvjiX4g2fEQ8eW9TSUaGa01mmNuT3n4vCTw3iaWYdPjxhsvbMVbfXaNt8kQSM4WzhDX10fATEBEhvT76kfCisKpfK7Ji86teqEnmY9sffBXvHk2KNGkRTpv//od+49zsScgbm+ObqZdJNAtHLC1BTYvp08Kn/5pc5TDDQNcH7Seagrq2PIoSEYcXQEdNR04DfO7+36sDFSUqiiftw44KOPJPgE5ECnTrQZu2ULJSsbgcPhYGm/pYjNjsXo46NxIf4Cxnccj5DJIUhfmI7dXrvhYeMBVWXVugcQCKhDsKnpm3WoQuDjQ/6cBw/WONzDrAdbGcXCIgFkkozi8XitADgAqBbdHgHgwOPxWr536jgAu2JiYgQxMTGZAM4AqK7RZwDo8ng8JQDqANQASKfNCsv/DREZEUjKT3pb1VFRAUycSH4yy5ZRYklZudFxlF0HYM+euQix4YBZuFCh/I+E4vRp6nz2449vOp/tf7QfrbVbS8S4/H04HA5WfrzybXVU9c4lw9COmBy5lHAJ+ur6b83sDx2i0v4ff1TsSh9vb8DFhaqj3ls4Tus2Dfnl+fCPkZCnz2vupt7Fi/wXb7vobd0KvHpFVVHNZUd49GgIhg7FT/8CoVd9JTfua3kevL1xuacx0orSMKlz8+6i9z6GmobwsPHAschjEDACaod96xb9e+RIakwgzM1xVRXthu/cCSxYgMzO1rj8/DJ8OvgIX43QDFjUdxG0VLXw49UfmzxWVGYUQhNDMafHHKgoKWC1pgRQVVbFYJvBCHxGlTmSYP+j/Wjfoj2cLZwlMp6iML3bdDzJeIL7affFG0BZuc7v7JLKElyMv4gRvBHN/7M4bhwlV1atAh49qvOU9i3a49zEc8gsyURKQQr8xvmJ5vG3YgV9n63/QJra/PADbTIJWR01psMYbB+6HRcmX0DawjTs8tqFQdaD6k9AvYuvLxAeTslCXd2mxS1J1NTovePvDxQWvjnsaOqIl4UvkV6ULsfgWFiaP7JawbQD8DImJqYKAGJiYqp4PF7q6+PvitzNAbxbFvHi9TkA8BOAUwDSAGgD+DMmJkakXtIRERHiRf+BcU9cCcUHyN5newEA7cra4d7du7CZPx/6N24gef58ZIweTYblQtJVuxdmeDGI2ylAlbc3YnbtEiqRJXf4fHRcsACMlRWiOnQA7t1DXkUeAmICMM5yHB49qHvRVh/Cvr9MGVPY6dvh+4vfw77SHipKKjCZNg1ttm9H7LZtKJTTrmJQTBC6teiGhw8eglNZiY7LloFvb4/odu3Elx/JCI0vvkCHCROQPXMmkr7//s1xXUYXJpom2HJ1C2zLhegEJCR/Rv0JFY4KzEvN8fDff9Fp3ToU9euHeA0NqbxW0vruUps9G9xLIRj4+1nc6HId6ioaTRuQz4fdjBlQ09JC1Oef44/Lf0BbRRumRaYf3Pevk5YTAgsCse/SPnQzpMoJzu+/w/L772Ewfz4ybtxA8oIFdcpblYqKYBwQgFZHj0L95UuUcLmIHjkSp0I2Q8AI0IHTQWavl6zm8TH3gW+EL0YajoSNnvgylJ+f/Aw1JTX0Uu71wb2n3qWzWmccKz6GA6EH0Nmgc5PGSi9Nx6WES5hpOxMP7j+QUITCIe2/kR3fDmpKathwYQOWdF4isXEvp19GKb8U9kr2H8T7TPnzz9ExNBSVPj6I3r8fTD1V7zuddqJcUA7VV6q490q4560ZHQ37AwfwasoUvMzJEdprqalI++9iOWgQ9P/4AxFubuAbNF7Z20upF5AHPH74WOg5lAsL0fHbb1HepQti7OwUbq2l7egIu7/+QuJvvyFnGHUN1i2khNmxq8fQr3U/eYYnNT6EzzxLM4BhGKn/w+VyHblcbuR7x6K4XK7De8eecLncnu/8/2Iul7vl9X/P4nK5f3C5XCUul6vP5XJvcLlcb2HmDw8Pbx8eHs6UlZUx/++Eh4fLOwSFovfu3ozjTkf6n0uXGAZgmF9/FWssgUDAdNreiVk905bG2bhRgpFKkR07KN6zZ99pRByYAAAgAElEQVQc2nJrC4NVYB6lPxJpKFHfX2ejzzJYBWbfg310oKyMYWxsGIbHY5jycpHGkgQJOQkMVoHZcmsLHfjrL3ptgoJkHovYLFpEMd+8WePw92HfM0qrlZiU/BSJTCMQCBjLzZbMkH+G0IE5cxiGw2GYBw8kMv77SPu7K3rJTIYBmOfeAxmmsrJpg61fT3+D48eZ0spSRm+9HjPVb6pE4lQ0CsoKGI01Gszcc3NrPsDnM8zChfQ6eHoyTGHh28cSEhjmm28YRk+PHu/bl2FOnHjzursfcGdsttgwAoFAJs9Blr+LWcVZjO46Xcb7uLfYY+SV5jHaa7U/2PfUu+SU5DDKq5WZhSELmzzWuqvrGKwCE5cdJ4HIhEdW768JJycwBj8bMKWVpRIbc9qZaUyLn1swFfwKiY0pdwIC6Htn6VLJjSkQMIyrK8MYGzNMXp7kxm0Emby3nj5lGGVlhhk5kmGqqqQzxzff0PpBUe9RBAKGad+eYdzd3xwqLC9kOKs4zKp/V8kxMOnB3i+yiEpZWRkTHh7OhIeHt2dEyBPJSnOSDKANj8dTBsioHIDZ6+Pv8gKAxTv/b/7OOfMAHHot4csH4A/AVapRs3zQZBRn4FbKrbcSvQMHyENmzhyxxuNwOJjceTJWtnmGYk93KteOipJgxFKguJhMufv2pW4zr9n/aD+6m3SXeoemYdxh6G7SHZtubCKvC3V1kvbExNC/ZUxoYigAwM3KDSgtJf+jvn2bh/9RNd9/D7RpA3zxRQ0z86ldp0LACHDw8cEGLhae+2n3kZiXSAbTly+TpHX+fGoV3gyxWrMNG900YHHyEkkeS8X014qMJI8xb2/Axwfnn51HQXnBByfRq0ZXXRfDuMNwPOo4+b9Vo6xM3il//UXGr/37UyOIMWPImHbrVvrOuX2bvGq8vQEVFWSXZCMsMQze9t7NXxZUB0ZaRpj/0XycjDqJx6+Erxx4l30P96G4sviDNS5/FwNNA/h09MGfd/7Es2zx5e8Mw2D/o/3ob94f1obWEoxQcZjebTpyy3LhHy0ZOTZfwEdATAA8bT2Fk1k1F4YNo6YfGzaQrFgSBAYC//5LEkB9fcmMqSjY2ZFM78wZMreXNJcv0+/BzJnU1VERqe5AGRoKpKUBAHTUdGBnbId7aWz1EAtLU5BJMiomJiYDwEMAE14fmgDgwWtfqHc5AeAzHo+n9NpPaiRImgcAiQAGAwCPx1MDMBAAq7tjEZvzz86DAYPhvOGUlDl1iowKNYU0qqyDiZ0nAhzg75kOgI4OGXPX0blFYfjjD/ph3bDhjV9EREYE7qXdk4nBK4fDwRc9v0BkZiRupbxeFA4dCgwfTh5NqalSj+FdQhNDYapjCntje2DHDpp/zZrm438EkNfCb79RV6QdO94ctja0Rj/zfvB96Cueye17nIw6CWWOMka0HQh8+ilgbS2dhaqMUFVRQ+xXk/HtcHUwZ89SAjIvT7RB3umeh23bAACHnhxCa+3WcLX8cPdOxnccj4zijBot0d8wezbdqMXFAV5edOOxZAl1XDx0COjVq8bp/jH+qGKq4NPRp/ZYHwjffPQN9NX1seryKpGvFTACbLu7Db3b9oajmYLeuEmYXwf9CnUVdcw5N0fs767bL28jJjvmgzIuf58BlgPQTq8d9j3cJ5HxbiTfQHZp9odpkP/770DbttRdr6SkaWNlZAALF1I3ws8/l0x8isZXX9FrtXKleM0p6uPxY2DECOoGvGGD5MaVBpMmkcn60aNvDjmaObLJKBaWJiJLN97ZAObxeLxYUJXTbADg8XjneTxej9fnHASQAOAZgFsAfoyJiUl4/dh8AP15PN4TUGIrFsAuGcbP8oEREBuANrpt0N2kO+34FBcDn3zSpDHb6beDS3sX7Ew5A2b7duDuXcX9gc3Opti8vKj65zX7H+6HipIKJdZkwPhO46GjpoNd99/5OP/+O1BZSd21ZISAESA0IRRuVm7gFBeTAenAgWQK3tzw8aHYly+nhfJrpnWdhpjsGNx+ebtJw+eU5mDPgz0YZD0IRmt/AxISgD17qHV2M8anow9+dSxH+KaFtGPu7CxaQnTTJjJg3b4daNUKeWV5OBd7DuM6jvtgTaYBYKjtUOio6eBoxNG6Txg8mCqg9u+nrl3r1tGNYB2ciDoByxaW9L38gWKgaYAFvRfAL9pPZMPp4LhgxOXE/V9URVVjpmuG9W7rEZoYikNPDok1xv6H+6GpovlBJzmVlZQxrds0XIi/gOT894UHonPg0QGoKavBw7oZVQYLi54eGWbHxgLffSf+OFFRgJMTddHbsYM6236IcDj0/Hr2BCZPBp5KoCNoUhIwZAhtoAUHA0L4UckVe3vAwYE2UV7jaOqI1MJUpBWmyTEwFpZmjiiavub6D+sZ9RZWA0yUVZYxOut0mFkBs+jAoEEMY2EhET387nu7GawCcyflDsOMG8cwqqoM8/Bhk8eVOAsWMIySEsNERLw5VFlVyZhsMmFGHBkh1pDivr8+P/s5o7lGk8krfcdrYcUK8nW4ckWsMUXlUfqjt/5V69bV6bvUrHj6lN57U6e+OZRfls9ortFkZgfMbtLQM87MYFR+VGGenfUln4cvv2xisI0ji++uCn4FY7TBiJl4aiLDXLjAMNra5BMRE9Pwhfn5DHPoEMOoqTGM91svoD339zBYBeZ2ym0pRy5/Jp+ezBj8bMCU88X3esspyWFUflRhFl1YJMHIGkcev4t5pXlMi59bMMMPDxfpusH/DGZMNpk06XVujlQJqhinXU6M8S/GTFZxlkjXllaWMi1+bkGfazkgy/dXfE48g1Vg1lxZ06Rx7qTcYTirOMzXQV9LKDIF5auv6Lc+NFT0ay9eZBh9fYYxMWGYO3ckH5sQyPy7KzmZYVq1YhhbW4bJzRV/nKwshrGzo9fvyRPJxSdtfvuN3i9PnzIMwzDXkq4xWAUmICZAzoFJHvZ+kUVUFN0zioVFobiSdAVFFUUYxh1GMrVLl2i3R6npH4kxHcZAXVkd/zz+h6Q6hoZUcVVRIYHIJURSEvDnn1R23bHjm8MX4y8ivShd5lKGzx0/Rym/tOau99KlgLk5MG+eTKSOoQnkFzXQoAe1Fh42DJBTRz+JYGdH0oH9+8mTB4Ceuh7GdBiDIxFHUMYvE2vYK8+vYO/DvVji8BVsvl0HWFgAP/8sycjlhqqyKkbZjcLZmLModelHkrKiIqBfv9rdfeLigM2bqQLN2JhK+M3M3sjzAODwk8OwNrBGT7Oesn0icmB8x/HILcvFxfiLYo9xNOIo+AI+fDp8uNUr1ehr6OPb3t8iIDYAd1/eFeqa2OxYBMcFY7bjbKgp190F7ENFiaOEv4f/jbyyPCy+KFrF7NmYs8gry8O0rtOkE5wCYWVgBZf2Ltj3cJ/YksYqQRXmnJsDEx0T/Oj6o4QjVDDWrwe4XGD6dCA/X/jrdu+mqp527aiKtueH/x0PgCpaT50Cnj8HJk6s4UspNCUlZMWQmAj4+wOdOkk8TKkxfjzdJ7yujupm0g0ccBCeGi7nwFhYmi9sMorl/5KAmABoqmjCzdINOHyYdOBTpkhk7BYaLTCcNxxHIo6gsoUe8PffpIv/6SeJjC8RVq6ksuvVq2sc9n3kCyNNI3hyPWUajqOZIxxMHbDz3s63C2gtLTLNfPwY2LlT6jGEJobC1tAWbfccJ68gRfp7icuKFbRY/vLLNwm9aV2nIb88XyyT23J+OWYFzoJlC0usDBOQxGH3bvJH+0AY23EsiiqKEBIfAvToAVy/Tu9FFxf6LH/7LSX6bG2Bb74B0tOBBQuAa9eAZ8+AVq0AAGmFaQhLDMOkzpM+SCPu93G3doeBhgGORtYj1WuEmKwYLL60GH3b9UUPsx6NX/AB8JXTVzDUNMTKyyuFOn/bnW1QVVLFrB6zpByZYtKldRcs7L0Qex/urdufrB72P9qPNrptMMBygBSjUxymd5uO+Nx4XHtxTazr/773N+6l3cNvHr9BT11PwtEpGFpatGGTkkJJqaVLKUlSHwIByfo++wwYMIA2eiws6j//Q6RfPzIcDwqihimiwOcDEyZQAu/QIeDjj6UTo7QwNQXc3Ch2hoGOmg7sW9qzvlEsLE2ATUax/N/BMAwCYgMw0GogNFU1gYMHyUSXx5PYHJM7T0ZmSSYuJVwiT6ZPPqEduLvC7YBLlSdPqHPgvHmUqHhNbil14ZnQaYJcdt0/d/gcj189xt3Ud16jMWPoh3/FCiDz/X4HkqOyqhJXkq7Ay7AP+VX5+DTbrnA10Nam6p3Hj99U7LhauqKdXjv4PvIVebj1/61HTHYMjrSdD9XNW2hB7uYm4aDli6ulK4w0jbD3wV46wOUCN24AlpbArFm0CG/fnv6dkABERFBlWL9+gMpbX6ijEUfBgMGEzhPqnugDQ01ZDWPsx8A/2h+llaJ1IiypLIH3CW9oqGjgqPfR/4vkHUCdCBf3WYyguKC3DRzqobC8EPse7oNPRx+Y6JjIKELF44ePf0D7Fu0xK3AWyvnljZ4f9CwIIXEhmNJlCpSVlGUQofwZYz8Gumq6YhmZvyp6haWhS+Fm6YZxHcdJIToF5KOPgLAwoHdvqoq2tqaqJ3//mlXZpaXAuHHktTlrFnDu3IfXOU9YZs0is/b164Hjx4W7hmFoY+zsWWDLFlrfNUcmTaKE5c2bAMg36l4qm4xiYREXNhnF8n9HZGYkkvKTMJw7nG7SHz2SWFVUNUNsh8BQ0xD/PPmHDvzxB2BiQrK4MvHkURJj2TIy71y6tMbh45HHUV5VjmndpsklrAmdJ0BLVQu77r1jZM7h0KKlqIjilhJ3Xt5BUUURPgvNoRLy9yrGmjWjRlFnuB9+ANLSoMRRwtSuU3Eh/gJeFrwUepinmU+x/r/1+MRuHJx+2EmStI0bpRi4fFBRUsGC3gsQEBtAUluAnuv169S6OzubzFbnzqUEVT0cjjgMB1MH2BnbyShy+TOh8wQUVhRiedhykSRCX57/EpEZkTg0+hDa6tVtbP6h8mWvL2GsZdxgdVRRRRE239qMworC/yvj8rrQUtXCX55/ISY7Bhuu198cpIxfhq+DvsbQw0PRoWUHfOX0lQyjlC/aatoY13EcTkSeQGF5oUjXLr60GCWVJdg2dNv/TVIYAFXonDlDFgY//EBrw5EjaeNh9WrqTuvqShK1TZuAv/6qsfnwf8nWrUCfPiRxfPSo8fN//JGqi5cupd/P5sqoUdR1+x9aHziaOiKtKA2phbLt/szC8qHAJqNY/u8IiAkAAJKiHTxIC4rx4yU6h5qyGsZ2GAu/p360GGzRgrqNPX1KCx15ce0atVn/7jvysnoH30e+6NiyIxxMHeQSmp66HiZ0moAjEUdQUF7w9oEOHYCvv6bXT0qVZaGJoTDPA7hHLtKul729VOaRCxwOLRrLyt50J5zabSoEjOBtsqURBIwAswJnQVtVG9vvmVIHoV27Pthd4SV9l+B/7N13eFRl+sbx76Q3agIJJZQgHHpvKRK6gGCXpS2W34osithQd9eC7rquFbG3tayAAio2EBVBek8lwAHpJIQSEEggIWV+f5xEOiSQyZkk9+e65prknTPn3NFDIE/e93ljGsQwbs44th0u3NC1ShVrqV4xliRuztjM2rS1jGwz0rVB3UyvRr0Y33U8k1dO5v559xerIPVR/Ed8nPAxT/R4gv5N+pdBSvcS5BPEo9GP8tPWn1i6aylHc46yeOdiJq+YzKivRtHyzZZUfa4qT/76JNHh0XSr183uyLYbcNUAhrUexrNLnmVzxuZzXl+/fz1d3+/Ka6tfY0K3Cay+azV1qtSxIal97uhwB1m5WczaMKvY71m8czH/S/wfE6MmYoSU3kzxcqV+fZg0ySpKzZ5t9TOaNMnaRS0pySpGPfSQ9fdqZefjY/33qF7dKty9+641637WLOvfmfPnW7/EiYuzZmhPmmT9QvbZZ+1OfmWqVrVWPMycCSdP/rGsXLOjRC6PilFS6Xy3+Ts61elE3YBQa933oEFWA+JSNqrtKE7kneDrTV9bA9dcY01rfukl6y/osuZ0wqOPWrM87jvzt8TmQZOVe1ZyW7vbbP1t6JhOY8jKzeKz5M/OfOHJJyE01PptWkFBqV936aaf+OGrABze3hVrVlSRpk2tQtTUqfDAA1wV1IDo8Gjej3u/WLOjPoz/kCW7lvBR+HgCX3kdbr8dBgxwfW6beHp4MvXGqXg4PBj11SjyCkrWQH968nQcOCrPMpdCDoeDKQOm8GD3B3lt9WvcM/ceCpwX/vOatC+JcXPH0adxH56MtbFIb7NxXcYRGhjKgKkDqP6f6sR+HMuDPz3Irzt+pWlwU56KfYrvhn/HvFHzKtdslYuYfM1kArwDGPv92D+Knk6nkzdWv0Hn9zqzL2sfc0fM5dUBr+Ln5Wdz2rIXWT8SI9go9lK93Pxcxs0ZR8NqDflHj3+4OF054OVlFVjmzYOtW60ekkuXWrNi5JSwMKtol5EBY8daxaahQ60G5f36WcvXO3Wy+isOHGj9EqsifA8bNcr6mn/8kfZh7fFweKiJuchlUjFKKpX9WftZuWeltUTvl1+snfRKeYlekajwKBpVb3RqqR5YhaiGDa0f5rOyXHLdC/roI2uN+6RJVtPO0/wv8X/WD95tR5VtprN0qduFtqFteS/uvTNfqFrV6uWwejX8o3T/oZyVk8n/vbmc5ruPW8XJiyy9KteeeMIqQr76KkRF8a+Gd5B6LJXmbzZn8orJFyy47Mvcx8SfJ9Kn3tVc9/zXVoPuV14p4/Blr2H1hrwz+B1W7FnBPxcVv5n9yfyTTEueRs9GPalXtZ4LE7onh8PBS/1f4tHoR3l77dvc/d3d5y1IHc05yi0zb6GGXw2m3TSt0vTzOZ8A7wDeuvYtBjYdyDO9nmHuiLmkP5TOngf38M2wb3iq51MMbjaYIJ+Ks1HAlQoLCuP5vs+zcMdC/pf4P/Zn7WfwZ4MZ/8N4+kT0IWlsEgObDrQ7pm0cDgd3tL+DpbuW8sqKVy5ZUJ+yagopB1J4feDrBHgHXPTYSiciwupb2dGeWeNur2tXayOPPXusXWaTk61/qy1aBD/+aC1//PpraxaVt7fdaUvHNddAcDBMm0agTyAtQtTEXOSyOZ3OCv9Yu3Zto7Vr1zqzs7Odld3atWvtjmCrj+M/djIJ57q0dU7nqFFOZ/XqTueJEy673uO/PO70eNrDmXY07dTgggVOJzid48e77Lrn2L7d6QwKcjp79nQ68/PPeCkvP89Z/5X6zoFTB17xZUrj/npj1RtOJuFcm3rWuQoKnM6777b+27344hVfp4j54G1OJzjNh+8otXO6tdmznc4aNZzOKlWc6e+/6hw4daCTSTjbvd3OuWL3inMOH/X5n5x/udHTmdOogfXf/ptvbAht3/eu0bNHOz2e9nAu2bnkksdmHM9w9vy4p5NJOGeun1kG6dxXQUGB84kFTziZhPO22bc58/Lzznjt1pm3Oj2f9nQu2rHIxpSWyv73YnmVX5DvjP5vtLPm8zWdoS+GOn3/6et8beVrzoKCArujncGu++tI9pEzvr8v37X8vMftPrLbGfhsoHPI9CFlnFCulL532WjcOKfTz8/pPHLEOXr2aGfoi6Fu973nSujekpLKzs52rl271rl27dpGzhLUaTQzSiqV7zZ/R90qdekQ1BS++sqaTuznuin8I9uOpMBZwOfrT9vuvFcvaye711+3GiK7WkGBNRPL4bBmR3mc+cd+0c5F7Dm6h9va3eb6LMUwsu1I/L38eT/u/TNfcDisHeGGDoWJE62v5Up98w3NXvmEz9o6qPev1678fOXBDTdAQgK0aUPoXfczZ2FdZg+exsHjB4n6bxR3f3c3h04cgpMnWf/sBJ4ZO4P3Z+fjUzMEvvvO6pVQibwx8A0aVW/EqK9GcST7yAWP25yxme4fdGf57uV8euOn3Nrq1jJM6X4cDgfP9HqGZ3o+wyeJnzD669F/zM54c82bzNowi2d7P0uPhj1sTirllYfDg3cHv0vmyUxqBdZizV1rGN9tvJYyFqrqW5U5I+bwxa1fWN/fP4zirm/vIuN4xhnHPfDjAxQ4C5gyYIpNSUXKoZEjrV6cs2fTuY61NFhNzEVKTsUoqTRy8nL4ceuPDG46GMfs2dauaS5aolekeUhzOtftfOZSPbC2w73qKrjzTjhWst1uSuy116zp0pMnWzvDnOXz9Z8T6B3IEGOIa3MUU3W/6gxtNZRpydPIPJl55ouenlbT+f794S9/sXoVXK7kZBg1ipSGAXx4TxSBvpVoCUyDBvDrr/C3v+H48ENuuO3fmL2+4oHuD/Dpmg94bmRDjjWsQ+vHX+NYNT9yv5kNa9fC4MF2Jy9zVXyrMP2m6ew5uodxc8ed95iF2xfS/YPuHM4+zILRC2xf7upOnoh9guf6PMf05OmM+HIEy3cv58EfH2Rws8FMjJ5odzwp51rVbsXW+7ay9q61tAltY3cct+NwOLi55c1svGcjD0U+xEcJH9H8zeZ8FP8RBc4C5v02jy82fMHjPR6ncY0KukRdxBUiI622DlOn0qluJwAt1RO5DCpGSaWxaOciMk9mWkWXTz+1/hKJjnb5dUe1GUXc3jg2HNhwajAwED7+2Nqx5eGHXXfxTZusbXSvvdYqfJ0lNz+XLzd+yXXGdW7VJ2JMpzFknsw8c0ZZER8fa1Zb167WLogLFpT8AgcPwvXXUxAYwDU3H+dqo/Lt4oW3N/z731ZPhwMHCIzuycs/5PP7f2vx4uxM1nsdYsBI+P3XeXhfd0PFaDp6mbrV78aknpOYnjz9nB0IP4z/kP5T+1OnSh1W/WUV0Q1c/z2lvHks5jFe7v8yszbMosdHPahbpS6f3PAJHg79E0SuXP2q9fH18rU7hlur4luFl/q/RNzdcTQLbsad395J7Mex3DP3HpoFN+OhyIfsjihSvjgc1uyoBQvoUBCqJuYil0n/EpRK4zvzO/y9/Onj09xqXv7nP5fJD9jDWg/D0+HJtKRpZ74QHW0Vot57z9qxpbTl5cHo0Vbh64MPzvu1/rL9Fw6dOOR2u35F1o+kVa1W5y7VKxIYCHPmWLvEXX89rFlT/JPn5sKtt0JaGj+/fA+pVaFP4z6lE7w86tcPEhOt+3HKFHwaX0XBj/Mwv/2Qmx54lx6NYu1O6Bb+FvM3YhrEMG7OOLYd3kaBs4BHfn6E//v2/+jduDfL71xORI0Iu2O6rQcjH+T1ga9TK7AWM2+dSU3/mnZHEql02oa2ZckdS/jvdf9l44GNbDu8jTcHvalinsjlGDkSCgrw//IbWtZqqZlRIpdBxSipNOZsmUPfiL74z/wKnE5ra9YyEBoUSr8m/ZiaPPXcXaWeeQZatrSWnP3+e+le+LnnrCLN229b2++ex4yUGVTzrcaAqwaU7rWvkMPhYEynMaxOXU1CesL5D6pZE376CUJCrC2DN20q3sknTIBff8X53ns8dWIuETUi6F6/e+mFL4/CwqwZUqYJS5bg0f8abu9wB2M6jbE7mdvw9PBk6o1T8XB4MPKrkdw882ZeXP4if+38V+aMmEM1v2p2R3R793a9l7QH0+har6vdUUQqLQ+HB3d2uBPzXpMldyyhb0RfuyOJlE/Nm0PnzjBtGp3qdGJt2lqcTqfdqUTKFRWjpFLYl7mP7b9vp2fDWGuJXmSkNaumjIxsM5JdR3axYveKM1/w84NPPrG2xZ0wofQuuG6dVegaPtyaBXQeOXk5zN44mxua3+CWvxUd1XYUvp6+vL/uArOjAOrWhZ9/Bi8va4bPrl0XP+nbb1uPiRNZ3rMJq1JX8WD3Byv1tvJ/8PCAZs0q9XK8S2lYvSHvDH6HlXtW8q35LVMGTOHNQW/i5eFld7RyQ82lRdxDcEAwMQ1i7I4hUr6NHAlxcfTLrsf+rP2kHku1O5FIuaJ/QUulUDS75urDVWH9enjrrTK9/vXG9fh7+TM9efq5PWU6d7b6Ov3rX3DzzVe+W1l2trU8r1YteOONCx7249YfOZJzxO2W6BWp6V+TW1vdytTkqbzQ7wUCfQLPf+BVV1mzemJjrZ0KIyMhKwsyM089ij4/eBAGDYLnnuPlL26lhl8Nbm9/e5l+XVK+DWs9jMMnDtM0uKlmFIiIiFRmw4bBww/Tc+luqAWrU1dTv2p9u1OJlBuaGSWVQlExqs2P8Vbj5qFDy/T6VXyrcJ1xHTM3zCQ3P/fcA554Atq1gzFjYO/eK7vYE0/Ahg3w3/9aS9kuYEbKDGr613TrH6jHdBzD0Zyj529kfrp27eD7763/tytWwNatVgGqShVrBlx0tFXoe/JJ+Owztvy+ja83fc24LuMuXOQSuYC/dvmrW/+5ERERkTIQFgYDBlB39i/4ObzPXQEhIhelmVFSKSTsS6BxlQb4vf2VtT19cHCZZxjRZgQzUmYwf9t8BjYdeOaLPj7Wcr3u3a3CynvvwQ03lPwiS5bAyy/D3XdbfZQu4Hjucb41v2V46+F4e3qX/DplJKZBDO3D2vPPxf9kRJsR+Hv7X+TgmGL3jZo85zG8Pb25t+u9pZRURERERCqd22/HMWcOYw+3YMUeFaNESkIzo6RSSEhP4IacxrBvnzVDxgbXNLmG6n7Vmb5++vkPaNcOVq+GevXgxhvh9tvhyJHindzphMWLreV5jRvDSy9d9PC5W+aSeTLTbZfoFXE4HLzS/xV2HtnJKyteKZVzHjx+kI8TPmZUm1GEBZ2/sbuIiIiIyCUNGQI1ajA6voC1aWs5mX/S7kQi5YaKUVLhZZ3Mwjxo0ndv4ayaGHsadvp6+XJLi1uYvXE2x3OPn/+gNm1g1Sp4/HGr0XqbNrBgwYVPWlAAX38NUVFWz6SsLJg6FYKCLpplRsoMagfWJrZR7BV8RWWjV+Ne3NTiJv699N+kHr3yxpBvr3mbE3kneDDywcV53BsAACAASURBVFJIJyIiIiKVlq8vjBhB25Xb8MvMufAu0CJyDhWjpMJL3p+MEydtf8u0Zh01aGBblhFtRpCVm8X3m7+/8EE+PvDPf8Ly5eDvD336wH33wfHTClgnT8JHH0GrVtYsqvR0q1n5jh1WA++LOJZzjDmb53Bry1vLzS5gL/Z7kbyCPP72y9+u6DzZedm8seYNBl41kFa1W5VSOhERERGptG6/Hc+cXIamoL5RIiWgYpRUeEW/oQhL3Go1srZxa/EeDXtQt0pdpidfYKne6bp1g/h4GD8eXn8dOnSAhQvhlVcgIgLuvNP6bcz06bBlC9xzDwQEXPK0323+jhN5J9x+id7pImpE8GD3B/k06VNW7Vl12eeZmjSV/Vn7eTjq4VJMJyIiIiKVVqdO0LIlY9b7sHzPcrvTiJQbKkZJhZeQnkDr7Kp4pe21ilE28vTwZFirYczdMpfDJw5f+g0BAfDaazB/Ppw4Ab17w0MPQbNmMG+eVawaPhy8ij/DaUbKDOpVqUd0A3v/W5TU36/+O2FBYUyYN4ECZ0GJ31/gLOCVFa/QPqw9vRr1ckFCEREREal0HA64/XY67zjJvnWL7U4jUm6oGCUVXkJ6AkN/r2d9YnMxCqylerkFuXy58cviv6lPH0hOtgpTq1ZZfaSuuabEs7x+z/6deb/NY2iroXg4ytcf/yq+VXiuz3OsSl1VvJllZ/lhyw9sPLiRhyMfxmHj7DgRERERqWBGjaLAw0H/peml0uNUpDIoXz+NipRQfkE+SfuS6JnqA4GB1o51NutYpyNNazYteUGlWjVryV7Xrpd97W82fcPJ/JPlaone6Ua3G03nup15dP6jZJ7MLNF7X17xMvWr1mdoq6EuSiciIiIilVKdOhzpGcmfk2DFzqV2pxEpF1SMkgpty6EtnMg7QcvNh60eTCVYzuYqDoeDEW1G8OuOX8v8Nyefp3xOo+qN6Frv8gtadvJweDBlwBTSjqXx/NLni/2+uL1xLNyxkAndJuDt6e3ChCIiIiJSGQWNuZfwo5Dx/Sy7o4iUCypGSYUWvzeeoByouWWPWyzRKzK89XCcOJmZMrPMrplxPIP52+YztOXQcr1MLSo8iuGth/PSipfY+fvOYr3n5RUvU8WnCnd1vMvF6URERESkMvK+/kaOBXjS6JtFdkcRKRdUjJIKLSE9gavTvHAUFLhVMcoIMehUpxPT15e899Hl+mrjV+QV5DGs9bAyu6arPN/3eRw4eGT+I5c8dteRXcxYP4O7Ot5FNb9qZZBORERERCodPz+Se7emx7qD5GTstzuNiNtTMUoqtIR9CVx/MMRq9N29u91xzjCizQjWpq1lc8bmMrnejJQZNK3ZlPZh7cvkeq4UXi2cR6MfZWbKTJbsXHLRY6esnALAhO4TyiKaiIiIiFRSOaOG458Hez581e4oIm5PxSipsJxOJ/F744nZ4wFt2lgNwN3In1r9CQcOPkv+zOXX2pe5j4U7FlrXLMdL9E43MXoi4VXDmTBvAodOHOK3Q7+xas8q5m6Zy6eJn/Lqyld5YsETvB/3PkNbDaVBtQZ2RxYRERGRCqz5wD+zIQT8pn5udxQRt2d/N2cRF0nPTOfQsQM03eILt11vd5xz1Ktaj56NejJ9/XSejH3SpUWiLzZ8QYGzoEIs0SsS4B3A832fZ8RXIwh+Ifi8xzhw0Kh6I/5x9T/KOJ2IiIiIVDZ1qtbl4+7V+dv322HLFmja1O5IIm5LxSipsOLT42mzH3yO57hVv6jTDW89nDHfjyFubxyd6nZy2XVmpMygVa1WtKrdymXXsMOw1sM4knOEE7knCA4IJtg/+Izn6n7V8XBoAqiIiIiIlI3d18WSP+cbPD/5BP71L7vjiLgtFaOkwkpITyB6V+EnblqMurnlzdwz9x4+W/+Zy4pRWzK2sGTXEp7p+YxLzm8nh8PB2M5j7Y4hIiIiIgJA87a9+anJN/T75CO8nnkGPPSLUZHz0Z8MqbAS0hO4Zl8g1K0LDRvaHee8avrXZGDTgXy2/jPyC/Jdco1nFj9DgHcAYzqNccn5RURERETEElk/ko/bg9eeNFi40O44Im5LxSipsBLSE+i+s8CaFeXGTbtHtB5B2rE0luy6+K5wl2PjgY1MT57OvV3uJTQotNTPLyIiIiIip7QLa8ePrXw5EegDH39sdxwRt6VilFRIx3KOkb19C7UyTrjtEr0iQ4whBHoHMi1pWqmfu2hW1MToiaV+bhEREREROZOPpw9tG3blh87V4csv4ehRuyOJuCUVo6RCStqXRJSb94sqEuAdwNBWQ5maPJUdv+8otfOu37+eGetnML7reEICQkrtvCIiIiIicmGR9SN5yciAEyfgvffsjiPillSMkgopIT2B6N1QEOAP7drZHeeSnu75NB4ODx766aHSO+eipwnyCeKhyNI7p4iIiIiIXFxkeCQr6uZzOLYbPPccHDlidyQRt6NilFRICekJxO7xxNGtO3h72x3nksKrhfOPq//BVxu/4qetP13x+RLTE/liwxfc3/1+ggOCSyGhiIiIiIgUR2T9SAC+vy0SDh2Cl16yOZGI+1ExSiqkzTvX0WpvPg43X6J3uociH+Kqmldx3w/3cTL/5BWda9KiSVTzrcYD3R8opXQiIiIiIlIcoUGhNK7emG8Cd8PQoTB5MuzbZ3csEbeiYpRUOHkFeQTErcfTidv3izqdr5cvUwZMwcwwmbJyymWfZ13aOr7e9DUPRj5IDf8apZhQRERERESKIzI8khV7VuB85hnIzoZnn7U7kohbUTFKKhzzoEmXHbk4HQ6IjLQ7TokMajqIIc2G8MziZ0g7lnZZ55i0aBI1/GowoduEUk4nIiIiIiLFEVk/krRjaewO84c774R33oEdO+yOJeI2il2MMgyjpmEY/zYMY65hGItPf7gyoEhJxafHE70bcppfBdWq2R2nxCZfM5nc/Fwe+fmREr93depqvt/8PQ9HPUw1v/L3tYuIiIiIVARFfaNW7F4BTz4JHh7w1FM2pxJxHyWZGTUdiAS+A/571kPEbSSmxhG5B3x69LI7ymVpUrMJj0Q/wrTkaSzeWbJa71O/PkWwfzDju453UToREREREbmUtqFt8ffyZ8WeFVC/PowfD59+CikpdkcTcQteJTg2CqhlmmaOq8KIlIYj65ZRNQeIudruKJftsZjH+CTxE8b/MJ51Y9bh5XHpP6rLdy9n3m/zeL7v81TxrVIGKUVERERE5Hy8Pb3pUq+LVYwCeOwxeO89ePxxmD3b3nAibqAkM6OSgPquCiJSGpxOJ9XWFf62oRw1Lz9bgHcAk6+ZTNK+JN5Z+06x3vPkwiepFVCLe7rc4+J0IiIiIiJyKVH1o4jfG8+J3BMQHAwTJ8LXX8PKlXZHE7FdSYpRC4B5hmH83TCMO09/uCqcSEmlHkul/dYsskKqQaNGdse5Ijc2v5G+EX15YuET7M/af9FjF+1YxC/bf+GxmMcI9Akso4QiIiIiInIhkeGR5Bbksm7vOmvg/vuhdm3429/A6bQ3nIjNSlKMuhrYA/QD/nzaY5QLcolclvi98UTvghNdO4LDYXecK+JwOHhtwGtknszk77/8/ZzXDx4/yC/bfuGVFa9wz9x7CAsKY2znsTYkFRERERGRs3Wv3x0obGIOEBRkLdP79Vf4+Wf7gom4gWL3jDJNs3x2g5ZKZWvyYoYcgexe/e2OUipa1GrB/d3u56UVL9Gmdhv2Ze0jcV8iCekJpB1L++O4sKAwXh/4OgHeATamFRERERGRIrUDa9OkRpNTfaMAxoyBl1+Gv/8d+va1dtkTqYRK0sAcwzBqAEOAekAq8J1pmoddEUzkcuQvs3af84vtY3OS0vNk7JNMS57G/T/ej5eHFy1CWtC7cW/ahbazHmHtqB1Y2+6YIiIiIiJylsjwSOZvm4/T6cThcICvLzz9NNx+O3z5Jdx6q90RRWxR7GKUYRiRwBxgE7ATGAy8ahjGtaZprrjom0XKSHDcJrJ9PfFr397uKKWmim8VVv1lFRknMmgR0gJfL1+7I4mIiIiISDFEh0czNWkqZoZJ85Dm1uCoUfDCC9aSvRtvBK8SzRERqRBKMifwVWCcaZpRpmkON00zGvgr8JproomUzJHsI7TecpR9LRuAt7fdcUpVeLVw2oe1VyFKRERERKQcGdJsCABfbPji1KCnJ/z737B5M9xyC2Rm2pROxD4lKUY1A2aeNfYFcFXpxRG5fMk7VtE+HXK7d7U7ioiIiIiICPWq1iOmQQwzU876Ufr662HKFPjuO4iOhp077QkoYpOSFKO2AMPOGrsV2Fp6cUQuX+qyeXg5oWaPa+yOIiIiIiIiAsDQlkNJ3p/MxgMbz3zhvvvghx+sQlSXLrB0qT0BRWxQksWp9wPfG4ZxH1bPqEZAU6zeUSK2y163EoAa3XraG0RERERERKTQzS1vZsK8CczaMIsnY58888X+/WHVKrjuOujdG955B+688/Iv5nTCunUwbRr8+KO1W19gIAQEnHou+rh2bbj/fqhW7cq+QJHLUOxilGmayw3DaAJcC9QFvgPmmqZ5yFXhREoiMGULmQFeBDVqZHcUERERERERAOpWqcvVDa9mZsrMc4tRAIYBK1fCsGHwf/8H69dbDc5L0tj8t99g+nSrCLV5M/j4QJ8+4O8Px49DVhakp5/6+PhxyMiwClY//ghVqpTeFyxSDCVq22+a5mFgqouyiFy2AmcB4dszSG9Sj6scDrvjiIiIiIiI/GFoy6Hc+8O9pOxPoVXtVuceUKMGzJkDDz0EkyfDxo3w+ecXnrXkdML+/TBzplWAWrUKHA6IjYWJE+Hmm61zXsxXX8HQoTBokLVcMCjoyr9QkWK6aDHKMIx5pmkOKPx4CeA833GmafZwQTaRYtt9aAet051si2lmdxQREREREZEz3NzyZsb/MJ5ZG2advxgF1kyoKVOgdWsYNw46doTmza3d9jIzrRlNRR9nZkJ+vvW+du2smVTDh0P9+sUPddNN1myq4cNhyBCrGCZSRi41M+p/p338gSuDiFyJXesW0DAXfDp2szuKiIiIiIjIGcKCwohtFMvMlJk8FfsUjout5rjrLmvp3sSJ1uynwECoU8eauRQUZH0eFATVq1uzmlpdoLhVHEOHQl4e/PnPcN11OJ5++vLPJVICFy1GmaY5/bRPN5mmuersYwzD6FrqqURK6NjqJQDUiu5rcxIREREREZFzDW05lHFzx5FyIIXWtVtf/OAePayld2VhxAirIHX77TQ5fhwWLAA/v7K5tlRaHiU49ucLjM8rjSAiV8KRkMRJT6jZKcbuKCIiIiIiIue4qcVNeDg8mJky0+4o5xo9Gj74gGorVlj9pnJy7E4kFdwlG5gbhuEBOACHYRiOwo+LNAHyXJRNpNhqbt7JzrqBNPXxsTuKiIiIiIjIOUKDQunZqCczU2bydM+nL75Uzw533snOrVtp+O9/W8v3Zs2yduUTcYHizIzKA04CgYUf55722AC85bJ0IsXUcMcRDjSta3cMERERERGRCxracihmhkny/mS7o5zXwZtugjffhG+/hWHDrOV7Ii5QnGJUY6wZULuBiNMejYGqpmlOclk6kWI4tH0jYccKyGnVwu4oIiIiIiIiF+TWS/WKjBsHr7wCs2fDZ5/ZnUYqqEsu0zNNc6dhGJ7AdiDdNM3LWjxqGEYz4BMgGMgARpumueWsYzyB14ABgBP4j2maH5z2+lDgCaylgk6gr2ma+y4nj1Qce5fPoybg36W73VFEREREREQuqFZgLXo37s3MlJn8s9c/3W+pXpH774f334fJk2HUKHDXnFJuFauBuWma+VgzoUrS8Pxs7wBvmqbZDHgTePc8x4wErgKaApHAJMMwGgEYhtEZmAT0M02zNRADHLmCPFJBZK1eBkBY9DU2JxEREREREbm4oS2HsuXQFhL3Jdod5cIcDnjgAYiPh8WL7U4jFVBJiktPA28bhtHQMAxPwzA8ih6XeqNhGLWBjkDRHL/PgI6GYdQ669A/Ae+bpllgmuYB4Gvg1sLXHgBeMk0zHcA0zSOmaWaXIL9UUN5JKeyqBuGN2tkdRURERERE5KJuanETng5P916qB9aMqJAQa8meSCkrSTHqA2A0sA2roXkupxqaX0o4kFo4w6poplVa4fjpGgA7T/t812nHtAQiDMNYbBhGnGEYjxfu7ieVXPDmPWxtWBVPD0+7o4iIiIiIiFxUcEAwfSP6MjNlJk6n0+44F+bvD2PHwnffwW+/2Z1GKphL9ow6TWOXpSgeL6At0A/wAeZhFav+V9wTrF+/3jXJypl169bZHaHUOLKzabc3k0UdIirU11We6f+DuIruLXEV3VviSrq/xFV0b5VvXQO78uPWH5m+cDrNqzW3O84ZTr+3vGJiaOPlxcF//IPdjzxiYyqpaIpdjDJNcydA4bK8UGCfaZoFxXz7bqCeYRiepmnmFzYqr1s4frpdQENgTeHnp8+U2gl8UdhAPccwjG+ArpSgGNW6dWt8fX2Le3iFtG7dOjp16mR3jFKTs3wJnk7w7ta5Qn1d5VVFu7/EfejeElfRvSWupPtLXEX3VvnXuGVjnlv/HMkFyYzsNNLuOH847701YgS1Z82i9jvvQI0a9gQTt5WTk3NZE3+KvUzPMIyqhmH8D8gGUoEThmF8YhhGtUu91zTN/UACMLxwaDgQX9gX6nSzgLsKe1HVAm4Avix8bTrQ3zAMh2EY3kAfwI07vklZOLB8PgCBXaJtTiIiIiIiIlI8Nf1r0i+in21L9TJPZjJj/QzunXsv69IuMcvugQfg+HFrdz2RUlKSnlGvAYFAa8AfaAMEFI4Xx1hgvGEYm4HxhZ9jGMbcwp3yAD7F6km1BVgJPGOa5rbC1z4H9gMbsApbKcB/S5BfKqDsdSs54gsN2vWwO4qIiIiIiEixDW01lO2/b2fd3rJZcpl1MotZKbO4ddat1H6xNsO+HMbba9+m5yc9Wbh94YXf2K4d9O4Nr78OucVpGS1yaSXpGTUAiDBN83jh55sNw7gD2FqcN5umuQnodp7xQad9nA/89QLvLwAeLHyIAOC7fiOJodAlxLA7ioiIiIiISLFdb1yPt4c3M1Nm0rlu50u/4TIczz3OD1t+YOaGmXy/+XuO5x4nNDCUOzvcydBWQ4moEcGAqQMYOG0gM2+dST3qnf9EDzwAQ4bAl1/CsGEuySqVS0lmRmUDtc4aCwFySi+OSAkUFFDrt71sa1gVf29/u9OIiIiIiIgUWw3/GvRv0p/pydP5Pfv3Uj//8t3LiZgSwS2zbmHh9oXc1u42Ft62kNQHU3lj0Bv0aNiD+lXrs+j2RbQLa8dNM25i7p655z/ZoEHQrBm88gq48w6AUm6UpBj1AfCzYRhjDcMYaBjGWOBH4D3XRBO5hK1b8cvO43DzBnYnERERERERKbHHYh5jf9Z+bpxxIzl5pTfPY1rSNHp90osgnyB+GvUTaQ+l8da1b9GzUU88PTzPODY4IJj5f55PbKNYnkx4kjdWv3HuCT084P77Yc0aWL681HJK5VWSYtSzwH+AW4CXC59fKBwXKXMF8XHWc9u2NicREREREREpuZgGMXx8w8f8uuNXbv/mdgqcxd2w/vwKnAU8vuBxRs0eRVR4FKv+sop+Tfrh5XHxDj1VfKswZ8QcYkNjGf/DeP656J/nNlYfPdraTW/y5CvKKAIl6BllmqYT+LDwIWK7o6sWE+gBNTpqJz0RERERESmfRrQZwZ6je3h0/qOEVw3nhX4vXNZ5juce57avb+OLDV/wlw5/4c1r38TH06fY7/fz8uP5Ts/zVupbPPnrkxzOPszL/V/G4XBYBwQGwt13wwsvwPbt0LjxZeUUgZI1MMcwjDuB4UBdIA1rh7sPCwtVImXq5Lo17AqBpvXa2B1FRERERETksk2MmsiuI7t4cfmLhFcNZ3y38SV6f+rRVK7//Hri9sbxcv+XeaD7A6eKSCXg5eHFR9d/RDXfakxeOZnfs3/n/SHvn1rad++98NJL8NprmiElV6TYxSjDMF4ArgdeBXYCDYGHAQN4xCXpRC4iIMUkoS4MqtXC7igiIiIiIiKXzeFwMGXAFFKPpTJh3gTqVa3HTS1uKtZ74/bGMeSzIRzNOco3w75hiDHkirJ4ODyYMmAK1Xyr8a8l/6J/k/4Ma124g169evCnP8F//wuTJkG1ald0Lam8StIz6nagj2mab5umOdc0zbeB/sAdLkkmcjH79xN08ChbwgMICQixO42IiIiIiMgV8fTwZPpN0+levzsjvxrJsl3LLnr8kewjvL/ufWI+jMHLw4tldy674kJUEYfDwdO9niaiRgTvrH3nzBcfeACOHbMKUiKXqSTFqGOFj7PHjpZeHJFiSkwE4GjLCJuDiIiIiIiIlA5/b3++Hf4t4VXDue7z6zAPmme8nno0lbfXvM01U6+h1ou1GPP9GNqHtWf1X1bTNrR0N3bycHhwd6e7WbRzERsPbDz1QqdO0KOHtVQvL69UrymVR0mKUa8CXxmG0c8wjBaGYfQHZgGTDcOIKHq4JqbIWQqLUY627W0OIiIiIiIiUnpCAkKYN2oeXh5eDJg2gCU7l/Ds4mfp+n5X6k+uz7i549h+eDv3d7+fZXcuY8kdSwgNCnVJljva34G3hzfvrnv3zBcmTICdO2HBApdcVyq+kjQwn1L43Ous8T7Aa4UfOwHPKw0lcik5a1exvyo0aNLB7igiIiIiIiKlKqJGBHNGzCH241h6fNwDgG71uvFcn+e43rie5iHNL6tBeUnVCqzFLS1v4ZPET3iuz3P4e/tbLwwcCP7+8P330L+/y3NIxVPsYpRpmiWZRSXiUnnx60gIg+Yhze2OIiIiIiIiUuo61+3M/D/PJ+VACoOaDqJulbq25BjbeSyfrf+MmSkzua39bdagvz/06WMVo6ZMgTIojEnFUuICk2EYDQzDiDQMI9wVgUQu6cQJ/LfuVDFKREREREQqtMjwSP7S8S+2FaIArm5wNS1CWvDOurMamQ8eDNu3w6ZN9gSTcq3YxSjDMOoYhrEI+A34CthqGMZiwzDs+1MhlVNKCh75BWyo503Dag3tTiMiIiIiIlJhORwO7u50Nyv3rCQhPeHUC4MGWc9z5tgTTMq1ksyMehtIBGqYplkHqAHEA+9c9F0ipS3B+gZ4tEUEnh5qUSYiIiIiIuJKo9uNxs/Lj3fXntbIPDwc2rWzluqJlFBJilExwEOmaWYBFD4/AkS5IpjIBSUkcMzXQVWjnd1JREREREREKrwa/jUY1noYU5Oncizn2KkXrr0Wli6Fw4ftCyflUkmKUYeBlmeNGcDvpRdH5NIK4uNICHVi1G5hdxQREREREZFKYWynsWSezGR68vRTg4MHQ34+/PSTfcGkXCpJMeoFYL5hGP8xDOOvhmH8B/i5cFykbBQU4ExMJCEMWoSoGCUiIiIiIlIWutbrSvuw9ry99m2cTmfhYFcICdFSPSmxYhejTNN8H/gTEAIMKXwebprmey7KJnKu7dvxzDpOYqh20hMRERERESkrDoeDsZ3GkrgvkdWpq61BT08YOBB++MGaISVSTF7FOcgwDE/gQ2CMaZoLXBtJ5CIKm5cnhkGz4GY2hxEREREREak8RrQZwcM/P8y7696lW/1u1uDgwfDpp7BqFUSppbQUT7FmRpmmmQ/0BwpcG0fkEhISyPdwkNm0If7e/nanERERERERqTSq+FZhZJuRfL7+cw6fKGxa3r+/NUNKS/WkBErSM2oy8LRhGN6uCiNySQkJbA/1pXHds3vpi4iIiIiIiKvd3eluTuSd4NOkT62B6tXh6qtVjJISKUkxajwwEThmGMZuwzB2FT27KJvIOZwJCaypfVLNy0VERERERGzQoU4HutXrxjtr3znVyHzwYEhOhl0qD0jxlKQYNQroC1xT+PGfT3sWcb2MDBx79hBXu0DNy0VERERERGwytvNYNh7cyJJdS6yBa6+1nufMsS+UlCslKUatAPoAHwBzC5/7AqtckEvkXMnJACSGQotamhklIiIiIiJih6GthlLdrzrvrH3HGjAMaNJES/Wk2EpSjHob6A3cB3QpfI4F3nJBLpFzJSUBkByKZkaJiIiIiIjYJMA7gNFtR/PFhi84dOIQOBzWUr0FC+D4cbvjSTlQkmLUDcBg0zR/ME1zg2maPxSO3eCaaCJnSUriWFU/8moHExIQYncaERERERGRSutPrf9EbkEuC7YvsAauvRays62ClMgllKQYlQ4EnDXmD+wtvTgiF5GczOZ6vjTXEj0RERERERFbda3XlSo+Vfh568/WQI8eEBSkvlFSLF4lOPZTYJ5hGK8De4Bw4B7gf4Zh9C46yDRNlUGl9OXnw/r1rO1YQPNgLdETERERERGxk5eHF70a9+LnbYXFKF9f6NfP6hv11lvW0j2RCyhJMeruwue/nzU+tvAB4AQirjSUyDm2bYPjx1lVE1prZpSIiIiIiIjt+kX041vzW7Yd3kZEjQirb9Ts2Va/33bt7I4nbqzYxSjTNBu7MojIRRXupJcUCreoebmIiIiIiIjt+kX0A+DnrT9zd+e7YdAg64U5c1SMkosqSc8oEfskJeF0ONhQC1qEaGaUiIiIiIiI3ZoFN6N+1frM3z7fGggLg86draV6IhehYpSUD0lJHKhXHWeAHw2qNbA7jYiIiIiISKXncDjoF9GPX7b9Qn5BvjU4eDCsXAkHDtgbTtyailFSPiQns7muL0awgaeHp91pREREREREBOgb0ZfD2YeJ2xtnDVx7LTidMG+evcHErakYJe4vMxO2bmVNcA7N1S9KRERERETEbfRp3AeA+dsKl+p17Ggt19NSPbkIFaPE/aWkgNPJ4qqH1S9KRERERETEjYQGhdI2tC0/b/vZGvDwsGZHzZsHubn2hhO3pWKUuL/CnfQSQ9HMKBERERERETfTCdA5RwAAIABJREFUL6Ify3Yv43jucWtg0CA4etTqHSVyHipGiftLSiLX35cd1VWMEhERERERcTf9IvpxMv8kS3YusQZiY63nxYvtCyVuTcUocX9JSaQ3rgUeDpoFN7M7jYiIiIiIiJzm6oZX4+Ppc6pvVHAwtGkDixbZG0zclopR4t6cTkhOxqzrQ6PqjfD39rc7kYiIiIiIiJwmwDuA6PDoU32jAHr0gOXL1TdKzkvFKHFvaWlw6BBrgnNoUUvNy0VERERERNxR34i+JO5LZF/mPmsgNhaysiA+3t5g4pZUjBL3lpQEwC9BB2gerH5RIiIiIiIi7qhfRD8AFmxfYA1cfbX1rKV6ch4qRol7K9xJb13ISc2MEhERERERcVMd63Skhl+NU0v1wsLAMNTEXM5LxShxb0lJnAgL4Xd/7aQnIiIiIiLirjw9POnduDfzt83H6XRagz16wJIlkJ9vbzhxOypGiXtLSmJv41oAtAjRzCgRERERERF31S+iH7uP7mZzxmZrIDYWjhz5Y8WLSBEVo8R9nTwJmzZh1vUhJCCE4IBguxOJiIiIiIjIBfSN6Atwaqlejx7Ws/pGyVlUjBL3ZZqQm8vq4BNaoiciIiIiIuLmmtRsQuPqjZm/bb41EB4OjRqpb5ScQ8UocV+FO+nND9qvJXoiIiIiIiLlQN+IvizcsZC8gjxrIDbWKkYV9ZESQcUocWfJyTi9vVkZ+LtmRomIiIiIiJQD/SL6cTTnKGtS11gDPXrAwYOwcaO9wcStqBgl7ispieNXNSDPU83LRUREREREyoPejXvjwHGqb1RsrPWspXpyGhWjxH0lJZHWKARAM6NERERERETKgeCAYDrW6Xiqb1REBNStqybmcgYVo8Q9HToEqalsquuDn5cfDas3tDuRiIiIiIiIFEO/iH6s2LOCYznHwOFQ3yg5h4pR4p6SkwFYE5yNEWzg4dCtKiIiIiIiUh70jehLXkEei3YWzobq0QPS0mDrVnuDidvQT/jingp30vspMJ0WtdQvSkREREREpLyIbhCNn5ffqaV66hslZ1ExStxTcjLO4GBWF+ymebD6RYmIiIiIiJQXfl5+9GjY41QT8+bNISRExSj5g4pR4p6SksgyGuN0qHm5iIiIiIhIedO7UW82HNjAgawDVt+oHj3UxFz+oGKUuJ+CAli/nrTG1k56WqYnIiIiIiJSvkQ3iAZgxZ4V1kBsLOzYAbt22RdK3IaKUeJ+tm+HrCw21vHGgYOmNZvanUhERERERERKoFOdTnh7eLN893JroEcP61lL9QQVo8QdFTYvX13zBI1rNMbf29/mQCIiIiIiIlIS/t7+dKzTkWW7l1kDbdpA9eoqRgmgYpS4o6QkcDj4JSBd/aJERERERETKqejwaNakruFk/knw9ISYGBWjBFAxStxRcjLOq64iMfM3WoSoX5SIiIiIiEh5FBUeRU5+DnF746yB2FgwTUhPtzeY2E7FKHE/SUkcNyLIzsvWzCgREREREZFyKio8CuDcvlFLltiUSNyFilHiXrKy4LffSC3cSU/FKBERERERkfKpTpU6NK7e+FTfqA4dIDAQFi2yN5jYTsUocS8pKeB0sqmuN4CW6YmIiIiIiJRj0Q2iWb57OU6nE7y9ITpafaNExShxM8nJAKyskUVIQAjBAcE2BxIREREREZHLFVU/ivTMdLb/vt0a6NHD+rkvI8PeYGIrr7K6kGEYzYBPgGAgAxhtmuaWs47xBF4DBgBO4D+maX5w1jEGEA+8ZZrmw2WRXcpQUhIEBLDUK02zokRERERERMq56AbRgNU3KqJGhNXEHGDpUrj+ehuTiZ3KcmbUO8Cbpmk2A94E3j3PMSOBq4CmQCQwyTCMRkUvFhar3gW+dnlasUdSErRpw4aMTeoXJSIiIiIiUs61qtWKqr5VWbarsG9Uly7g56elepVcmRSjDMOoDXQEPisc+gzoaBhGrbMO/RPwvmmaBaZpHsAqOt162uuPAd8Dm10cWezgdEJyMtktmpJxIkMzo0RERERERMo5Tw9PutfvzvI9hTvq+fpC9+5qYl7JldXMqHAg1TTNfIDC57TC8dM1AHae9vmuomMMw2gLXANMdnlasUdqKmRkkNrI6hOlmVEiIiIiIiLlX1T9KJL3JXM056g10KMHxMfD0aP2BhPblFnPqCthGIY38D5wh2ma+VbbqJJbv359qeYqr9atW2d3hPOqtngxVwG/eB+GXMhLz2PdUffMKhfmrveXlH+6t8RVdG+JK+n+ElfRvSWu4op7KyQ7BCdOPl34Kd1rdadKWBjNCgrY8sknHI2KKvXrifsrq2LUbqCeYRiehcUkT6Bu4fjpdgENgTWFnxfNlKoDNAHmFhaiqgMOwzCqmqY5prghWrduja+v75V9JeXcunXr6NSpk90xzm/OHHA42N6yKn4pflwbcy0eDm34WJ649f0l5ZruLXEV3VviSrq/xFV0b4mruOreaprTlPtW38cBvwPW+Q0Dxo+n6f79oHu5XMvJybmsiT9lUowyTXO/YRgJwHBgauFzfGFfqNPNAu4yDOMrrF33bgB6mKa5CwgpOsgwjElAkHbTq2Di4qBZMxKztmIEGypEiYiIiIiIVABVfavSpnYblu0ubGIeFAQdOlg76kmlVJY/7Y8FxhuGsRkYX/g5hmHMNQyjc+ExnwLbgC3ASuAZ0zS3lWFGsVN8PHTowKaDm2hRS83LRUREREREKoro8GhW7llJfkG+NRATA6tWwcmT9gYTW5RZzyjTNDcB3c4zPui0j/OBvxbjXJNKNZzYLyMDdu0id+wYdvw+g9va3WZ3IhERERERESklUeFRvLX2LZL3J9M+rL1VjHr1VWtSQrdzSgVSwWkdlLiH+HgAdkUE48SpmVEiIiIiIiIVSHSDaACW715eOGB9rqV6lZOKUeIeCotRiXWtW7J5SHM704iIiIiIiEgpalitIXWC6pzqGxUWBlddpWJUJaVilLiH+HgIDycpPw0HDpoFN7M7kYiIiIiIiJQSh8NBdIPoUzOjwFqqt3QpOJ32BRNbqBgl7iEuDjp0YOPBjTSu0Rg/Lz+7E4mIiIiIiEgpiqofxY7fd5B2LM0aiImBgwdh82Z7g0mZUzFK7JeZaX3z6djR2kkvRP2iREREREREKpqo8ChAfaNExShxB0lJ4HSS364d5kFT/aJEREREREQqoA51OuDn5XeqGGUYEBwMy5bZG0zKnIpRYr/C5uV7moSQk5+jYpSIiIiIiEgF5OPpQ5e6XU41MXc4TvWNkkpFxSixX1wchISQ4nsEQMv0REREREREKqjo8Gji9sZxIveENRATA1u2wL599gaTMqVilNgvPr6wefkmAM2MEhERERERqaCiwqPIK8hjTdoaayAmxnrWUr1KRcUosdfJk7B+PXToQMqBFGoH1iY4INjuVCIiIiIiIuICkeGRwGlNzDt2BD8/LdWrZFSMEnulpEBuLnTsSOK+RNqFtrM7kYiIiIiIiLhISEAIRrBxqm+Ujw9066ZiVCWjYpTYq7B5eV67NqTsT6FtaFubA4mIiIiIiIgrRYdHs3z3cpxOpzUQE2P1Es7KsjeYlBkVo8Re8fEQFMTmGgXk5OdoZpSIiIiIiEgFFxUexaETh9icsdkaiImB/HxYtcreYFJmVIwSe8XFQbt2JB1YD6CZUSIiIiIiIhVcVHgUwKmlepGR4HBoqV4lomKU2Cc/HxITrX5R6Yl4eXjRolYLu1OJiIiIiIiICxkhBjX9a55qYl6tGrRpo2JUJaJilNjnt9+sNcEdOpC4L5EWIS3w8fSxO5WIiIiIiIi4kIfDg8j6kadmRoG1VG/FCsjLsy+YlBkVo8Q+cXHWc4cOJO1Lol2Y+kWJiIiIiIhUBtHh0Ww6uImM4xnWQEwMZGZCUpK9waRMqBgl9omPBx8fMhqFknosVc3LRUREREREKomivlEr9qywBmJirOdlyy7wDqlIVIwS+8THQ+vWJB3eBKh5uYiIiIiISGXRpV4XvDy8TvWNCg+HBg3UN6qSUDFK7OF0WsWown5RgGZGiYiIiIiIVBIB3gF0COtwbt+opUutnxelQlMxSuyxezdkZEDHjiTtS6J2YG1Cg0LtTiUiIiIiIiJlJDo8mtWpq8nNz7UGYmIgLQ127LA1l7ieilFij/h467lwZpRmRYmIiIiIiFQuUeFRZOdlk5CeYA0U9Y3SUr0KT8UosUd8PDgc5LVuScr+FPWLEhERERERqWSKmpj/sVSvVSuoVk3FqEpAxSixR1wcNG/O5uxUcvJzNDNKRERERESkkqlXtR4NqzU81cTcwwOio1WMqgRUjBJ7FDYvT9qXBGgnPRERERERkcooKjyKZbuX4SxqWh4dDRs2WD2GpcJSMUrK3oEDsGeP1S8qPRFvD29a1GphdyoREREREREpY9Hh0aQdS2PXkV3WQFHfqOXL7QslLqdilJS9oublHTuSuC+RFrVa4OPpY28mERERERERKXPn9I3q0gW8vbVUr4JTMUrKXlExqn17kvYlaYmeiIiIiIhIJdUmtA1BPkGn+kb5+0PnzipGVXAqRknZi4+Hhg3J8HOSeixVzctFREREREQqKS8PL7rV63ZqZhRYS/XWroXsbPuCiUupGCVlLy5OzctFREREREQEsPpGJe1L4ljOMWsgJgZOnoRVq+wNJi6jYpSUrWPHYMuWP/pFAZoZJSIiIiIiUolFhUdR4Cxgdepqa+Dqq8HhgF9/tTWXuI6KUVK2Eq0CVNHMqNqBtQkNCrU3k4iIiIiIiNime/3uOHCcWqpXowZ06AALF9obTFxGxSgpW0XNyzt0IHFfomZFiYiIiIiIVHLV/KrRunbrU03MAXr1ghUr4MQJ+4KJy6gYJWUrLg5q1yYvrDYp+1PUL0pERERERESICo9ixZ4V5BfkWwO9ell9o1assDeYuISKUVK24uOhQwc2H9pCTn6OZkaJiIiIiIgI0eHRHM05yoYDG6yBq68GT08t1augVIySspOdDSkp2klPREREREREzhAVHgVwqm9U1arQqZOKURWUilFSdtasgbw86N6dxPREvD28aVGrhd2pRERERERExGYRNSIIDQw9t2/U6tWQlWVfMHEJFaOk7CwrrHBHRZG0P4kWtVrg4+ljbyYRERERERGxncPhICo86tTMKLCKUbm5sHz5hd8o5ZKKUVJ2li0Dw4BatUhMT9QSPREREREREflDdHg02w5vIz0zvXAgGry8tFTv/9u78/Cqqnv/4++EQABBEEQUZRaWDIqKKBgcKAEVBYc6YLW0eq3a23rV3j5t1Xq1aqvee1unWrWDP2cFHNpY8YpgBRMHEEUFcaGAzCKDCjKT5PfHPiZBRKYkmyTv1/PkOZy19jn5RDewz5e1vrsWshil6lFSklSz8/JYvmY5C1cttHm5JEmSJKnMV32jyrbqNWkCffpYjKqFLEapesQIK1ZAXp7NyyVJkiRJWzh8v8PJrZe7Zd+oyZNh1ar0gqnSWYxS9SgsTB7z8nhnyTsAroySJEmSJJXJzcnliDZHbFmMKi4u/0ypWsFilKpHURHsvTd07cq7S95lnz32oXWT1mmnkiRJkiTtRo5uezRTFk9h3aZ1mYGjoX59t+rVMhajVD2KipLmc1lZvLPkHVdFSZIkSZK2kNc2jw3FG5iyaEoy0Lgx9O1rMaqWsRilqrdkCXz0EeTlsalkE9M/nW6/KEmSJEnSFvq17QdA0fyi8sEBA+Ctt+CLL1JKpcpmMUpV79XMft+8PGYun8n64vWujJIkSZIkbWGfPfahS4suW/aNKimBV15JL5gqlcUoVb3CQsjNhd69y+6k12tfi1GSJEmSpC0d3fZoXp3/KqWlpclA377JZ0q36tUaFqNU9YqKoE8fyM3lnU/eoX52fQ7a+6C0U0mSJEmSdkN5bfNYumYpH634KBlo2BD69bMYVYtYjFLVWrs22dublwfAu5++S7dW3WhQr0HKwSRJkiRJu6Oj2x4NfEPfqKlTYcWKlFKpMlmMUtWaPBk2biwrRr3zyTs2L5ckSZIkbVW3Vt1o3rA5RfO+VowqLYWJE9MLpkpjMUpVqyjzh8fRR7N8zXIWrlpo83JJkiRJ0lZlZ2XTv11/Xp77cvngkUdCo0Zu1aslLEapahUVwUEHQcuWZc3LXRklSZIkSfo2+R3z+WjFR8z9fG4ykJub7LixGFUrWIxS1SkpSYpR/fsDMGXxFAAO3ffQNFNJkiRJknZz+Z3yARg/Z3z54IAB8N57sHRpSqlUWSxGqerMmAGff17WL6pwXiEHtjiQffbYJ+VgkiRJkqTdWfdW3dm3yb6Mmz2ufPD445NH+0bVeBajVHW+6heVl0dpaSmF8wrp365/upkkSZIkSbu9rKwsBnYcyPg54yktLU0G+/SBPfZwq14tYDFKVaeoCFq1ggMPJC6PLF+7nP5tLUZJkiRJkrZtYMeBfLr6U6Z9Oi0ZqF8/aQNjMarGsxilqlNUlGzRy8qicF4hAMe0PyblUJIkSZKkmmBgp4HAN/SNev99WLIkpVSqDBajVDU++QRmzSprXl44r5BWjVvRpUWXlINJkiRJkmqCds3a0aVFl837Rg0YkDy+/HIqmVQ5LEapalToFwXwyrxX6N+uP1lZWSmGkiRJkiTVJPmd8pkwdwIbizcmA4cfDk2bulWvhrMYpapRVAQNG8Lhh7No1SJmfzbb5uWSJEmSpB2S3ymfLzd8yaSFk5KBnBw49liLUTWcxShVjaKi5E4HDRpQNC9ZJWUxSpIkSZK0I47vcDxZZG3ZN2rmTFi4ML1g2iUWo1T51qyBt94q26JXOK+QxvUbc9i+h6UcTJIkSZJUk7Ro1ILebXpv3jfqhBOSxzFj0gmlXWYxSpVv8mTYtKm8efn8Qvoe0Jf69eqnHEySJEmSVNMM7DiQ1xa8xpcbvkwGevSADh2goCDVXNp5FqNU+QoLk8d+/Vi5fiVTP5lK/7Zu0ZMkSZIk7bj8TvlsKtnEK3NfSQaysmDYMBg3DlavTjecdkpOdX2jEEJX4EGgJbAcGBFj/PBrx9QD7gROBEqBW2KMf83MXQsMBzZlvq6OMb5QXfm1A4qKoHt3aNGC12eNpaS0xH5RkiRJkqSdktc2j9x6uYybPY6TupyUDA4bBnfemRSkTj013YDaYdW5Mupe4O4YY1fgbuC+bzjmPOBAoAvQD7g+hNAhMzcJ6BNj7AVcCIwMITSq8tTaMSUl8Nprm/WLys7Kpu8BfVMOJkmSJEmqiRrVb0Reu7zNm5gfeyw0a+ZWvRqqWopRIYR9gMOBxzNDjwOHhxBafe3Qc4C/xBhLYoxLgb8DZwHEGF+IMa7JHPcukEWyykq7k/ffh88/36wYdei+h9I0t2nKwSRJkiRJNVV+x3zeWfIOn67+NBmoXx9OOgn++c9kUYRqlOraptcWWBhjLAaIMRaHEBZlxpdWOK4dMLfC83mZY75uBDArxrhgR0JMmzZth0LXVlOmTKmy9977qadoD7zXvDlrJr/Bq/Ne5Yz2Z1Tp99Tuxf/XqiqeW6oqnluqSp5fqiqeW6oqu+u51WZ9GwD+9tLfGNxmMAB79exJpyee4IOHHmL1wQenGU87qNp6RlWWEMJxwI3AoB19bc+ePcnNza38UDXIlClT6N27d9V9gzvugNatOXjYMCYtmsz6kvWcccQZ9O5ehd9Tu40qP79UZ3luqap4bqkqeX6pqnhuqarszufWoSWHcvmblzO7dHZ5xk6d4PrrOWjmTPjhD1PNV1etX79+pxb+VFfPqPnA/pkG5V81Km+TGa9oHtC+wvN2FY8JIfQDHgFOizHGKk2snVNYmGzRy8oqu9NBXtu8lENJkiRJkmqyetn1GNBxwOZ9o/baK+kdZd+oGqdailExxk+BqcC5maFzgbczfaEqGg38KISQnekndRrwFEAIoQ8wEjgzxvhWdeTWDpo9G+bMSf4wAArnF9J5r87s13S/lINJkiRJkmq6/I75zPl8DrM/m10+OGwYTJ8Os2alF0w7rDrvpncpcFkIYSZwWeY5IYQxIYQjMsc8DMwGPgReB26IMX51lv0JaATcF0KYmvlyU+ju5Ktq9NChlJaWUjivkP7t+qebSZIkSZJUKwzsNBCA8bMrrI4aOjR5fPbZFBJpZ1Vbz6gY4wfAUd8wPqTCr4uBH2/l9X2qLp0qRUEB9OwJnToxc1lk2ZplFqMkSZIkSZUitAzs33R/xs0Zx496/ygZ7NQJevRIPo9ecUW6AbXdqnNllGqzzz6DiROTJZJA4bxCAI5pd0yaqSRJkiRJtURWVhb5nfJ5ac5LlJSWlE8MG5Z8Hv3ss/TCaYdYjFLleP55KC4uK0a9Mu8V9m68N11bdk05mCRJkiSpthjYcSDL1izj3SXvlg8OG5Z8Hn3++fSCaYdYjFLlKCiA1q2hT7Kb8qt+UVlZWSkHkyRJkiTVFl/1jRo3e1z54JFHwj77eFe9GsRilHbdhg1JBXroUMjOZvGqxcz6bBb929ovSpIkSZJUedo0bUO3vbsxfk6FJubZ2cnn0eefTz6fardnMUq7buJEWLmybIte0fwiAJuXS5IkSZIqXX6nfCbOnciG4gqFp2HDks+lEyemF0zbzWKUdl1BATRqBAOT5ZKF8wpplNOIw/Y7LOVgkiRJkqTaZmDHgazZuIbXF7xePpifDw0bulWvhrAYpV1TWpr8Zh80CBo3BpLm5X0P6EuDeg1SDidJkiRJqm2O73A89bLq8cJHL5QPNm6cfC599tnkc6p2axajtGvefRfmzi3bordq/SqmfjLVLXqSJEmSpCrRrGEzjutwHE/OeJLSioWnYcPg449h2rTUsmn7WIzSrikogKwsOOUUAF5f8DolpSUWoyRJkiRJVWZ4j+HMXD6Td5a8Uz6Y+VzqVr3dn8Uo7ZqCAjjqKGjdGkj6RWVnZdP3gL4pB5MkSZIk1VZndDuDnOwcnpj2RPngvvvCkUdajKoBLEZp5y1cCG++WbZFD6BwfiG9Wvdiz9w9UwwmSZIkSarNWjZuSX6nfEZOH7nlVr1Jk2Dx4vTCaZssRmnn/fOfyWOmGLWxeCOvL3idY9odk2IoSZIkSVJdMLzHcD7+/GMmL5pcPvjVYomvPq9qt2QxSjuvoAA6d4bu3QGYsngKazauIa9dXsrBJEmSJEm13WkHnUaDeg0236rXsyd06OBWvd2cxSjtnC+/hPHjk6pzVhYAT894mpzsHPI75accTpIkSZJU2zVr2IwTDzyRUdNHUVJakgxmZSWfU8eNg9Wr0w2orbIYpZ3z4ouwfn3ZEsjS0lJGTR/F4M6DadGoRcrhJEmSJEl1wfAew1m4aiFF84rKB7/7XVi3Dp58Mr1g+lYWo7RzCgpgr70gL9mSN2nhJOZ+MZezu5+dcjBJkiRJUl0xNAylUU4jRk4fWT54zDEQAtx3X3rB9K0sRmnHFRcnzeCGDIH69QEYOX0kDeo14NSDTk05nCRJkiSprmjSoAkndz2Z0e+PZlPJpmQwKwsuvhheew3eey/dgPpGFqO0415/HZYtK9uiV1Jawuj3R3NC5xNo3rB5yuEkSZIkSXXJ8B7D+XT1p0z4eEL54A9+ALm5ro7aTVmM0o4rKEhWRJ1wAgCvzX+NBSsXcE6Pc1IOJkmSJEmqa4Z0GUKTBk0236rXsiWceSY8/LCNzHdDFqO04/7xDzj+eGjWDIBR00eRWy+XoWFourkkSZIkSXVOo/qNGBaG8dSMp9hYvLF84pJLYOVKGDly6y9WKixGacfEmHxltugVlxQz+v3RDOkyhD1z90w5nCRJkiSpLhreYzgr1q5g3Oxx5YP9+0O3bm7V2w1ZjNKOefbZ5HFosgqqaH4Ri79czNk9vIueJEmSJCkdgzsPplluM56Y/kT5YFZWsjpq0iSYOjW9cNqCxSjtmIIC6NUL2rcHki16jXIacUrXU1IOJkmSJEmqq3Jzcjm92+n8/YO/s27TuvKJESOgYUNXR+1mLEZp+338MRQVwWmnAckWvSfff5KTu55MkwZN0s0mSZIkSarThvcYzsr1K3nhoxfKB/faC84+Gx59FL78Mr1w2ozFKG2/u+6C7Gy46CIAJs6dyJLVS7yLniRJkiQpdd/p+B1aNmq5+VY9SLbqrVoFjz+eTjBtwWKUts+qVfDXv8JZZ8EBBwAwcvpI9qi/B0O6DEk5nCRJkiSprqtfrz7f7fZdCmIBqzesLp/o1w969nSr3m7EYpS2z/33J7fEvOIKADaVbOKpGU8xNAylcf3GKYeTJEmSJAmG9xzOmo1reO7D58oHv2pkPmVK8qXUWYzSthUXw513wtFHw5FHAvCvOf9i2ZplnN3du+hJkiRJknYPx7Y/ln2b7MvI6SM3nzj/fGjUCP7853SCaTMWo7Rtzz4Ls2fDlVeWDY2aPoqmDZpyUpeTUgwmSZIkSVK5etn1OLPbmYz5cAwr168sn2jeHIYPh8ceS9rQKFUWo7Rtt98O7duX3UVvY/FGnv7gaU496FQa5jRMOZwkSZIkSeWG9xzOuk3rePL9JzefuOSS5I56jz2WTjCVsRilb/f22zBhAlx2GeTkADB+znhWrF3hFj1JkiRJ0m7n6LZH06t1L24tupXikuLyiSOPhF69kkbmpaXpBZTFKG3DbbdBkyZw0UVlQyOnj6RZbjMGdx6cYjBJkiRJkraUlZXFtcdey8zlMxk1fVTFiWR11Ntvw5tvphdQFqP0LRYvhieegAsugGbNANhQvIFnZjzDaQedRm5ObsoBJUmSJEna0undTqdHqx7c9MpNlJSWlE9873vQuHGyOkqpsRilrfvTn2DTJrj88rKhsbPG8sX6LzinxzkpBpMkSZIkaeuys7K59threX/p+zw94+nyiWbN4Nxz4fHHYcWK9ALWcRaj9M3WroV774Vhw6Bz57LhUdNHsVfDvRjYaWCK4SRJkiRJ+nZndj9yVXSmAAASsElEQVST0DJw48QbN18ddfnlsG4d/OY36YWr4yxG6Zs9+igsWwZXXFE2tHbjWv4R/8EZ3c6gQb0GKYaTJEmSJOnb1cuux6+P/TXvLnmXglhQPnHwwXDxxXD33TB9enoB6zCLUdpSaSncfjsceigcd1zZ8F2T7mLl+pX88NAfppdNkiRJkqTtNLzncA5scSA3TLiB0op30LvxRmjaFK680jvrpcBilLb04otJdfjKK5O7DQAr1q7g5sKbObnLyfRv1z/lgJIkSZIkbVtOdg7XHHMNb3/yNmM+HFM+sffeyTa9F1+EgoKtv4GqhMUoben226F1azinvEn5LYW38MW6L7h54M0pBpMkSZIkacecd/B5dGzekRsmfm111I9/DN27w89+lvSQUrWxGKXNzZgBzz8PP/kJ5OYCMP+L+dz5xp18v9f3Obj1wSkHlCRJkiRp+9WvV5+rj7maSQsnMXbW2AoT9eGOO2D27GRRhqqNxSht7s47kyLUpZeWDV3/8vWUUsoNx9+QYjBJkiRJknbOiF4jaNesHb+Z8JvNV0fl58Opp8JNN8GiRekFrGMsRqlcjPDAA3D++dCqFQDTP53OA+88wE/7/JT2zdunm0+SJEmSpJ3QoF4DfpX3K15b8BovzXlp88nf/x42boSrrkonXB1kMUqJjRvh+9+Hxo3hhvIVUFe/dDVNGjTh6mOuTjGcJEmSJEm75sLDLmT/pvtz48QbN5/o3Bn+8z/hoYfgjTfSCVfHWIxS4ne/g8mT4b77oE0bAArnFVIQC/hV3q9o2bhlygElSZIkSdp5uTm5/DLvl0yYO4EJH0/YfPKqq2C//eCyy6CkJJ2AdYjFKMGkSXDjjcn2vDPPBKC0tJRfjvsl+zXZj8v7Xp5yQEmSJEmSdt1Fh1/Evk323XJ1VNOmcOutySKNhx9OJ1wdYjGqrluzJtme16YN3HVX2XBBLODV+a9y/fHX07h+4xQDSpIkSZJUORrVb8Qvjv4F4+eM57mZz20+ed550Lcv/OpXsGpVOgHrCItRdd0vfgEzZ8KDD0Lz5gBsKtnEVeOvomvLrlx42IUpB5QkSZIkqfJcesSl9Grdi/OfOZ/Zn80un8jOhjvugE8+Se6upypjMaou+7//g7vvhiuvhAEDyoYfnPogM5bN4OaBN5OTnZNiQEmSJEmSKlej+o14+pynySKLM0aewZqNa8onjzwSfvhDuO02KCpKLWNtZzGqrlq+HC68ELp3T5qXZ6zduJbrXr6Oo/Y/itMPOj3FgJIkSZIkVY1Oe3Xise8+xrtL3uXiZy+mtLS0fPJ//gc6doRTToF3300vZC1mMaouKi2FH/8Yli2DRx6Bhg3Lpu6adBcLVy3k1vxbycrKSjGkJEmSJElV58QDT+SGATfw6HuP8sdJfyyf2HtvGDsW9tgDTjgBZs/e+ptop1iMqoseewxGj4bf/AYOO6xs+K3Fb3HTxJsY0mUIx3U4LsWAkiRJkiRVvauPuZphYRg/G/szCucVlk+0b58UpDZsgEGDkj5SqjQWo+qY+p98Aj/5CRx9dNK8PGPap9MY/PBgWjRqwb0n35tiQkmSJEmSqkd2VjYPnfYQHZt35KzRZ7Fo1aLyye7dYcwYWLIkWSH1+efpBa1lLEbVJatX0/G//gs2bYKHHoJ69QCYuXwm+Q/lk5uTy/gR42nbrG3KQSVJkiRJqh7NGjbjmXOeYdX6VZw1+iw2FG8onzzqKHjmGZgxA4YOhTVrtv5G2m4Wo+qKuXMhL48mU6fCvfdC584AzPlsDgMfGkhJaQnjR4ync4vOKQeVJEmSJKl69dinB/efej+vzn+Vn73ws80nBw2CRx9N7q539tmwcWM6IWsRi1F1QWEh9OkDH3/MR7ffDuefD8CClQsY+NBAVm9YzbgR4zho74NSDipJkiRJUjrO7nE2P+/3c+6efDcPvfPQ5pNnnQX33APPPZfcmb6kJJ2QtURO2gFUxf72t+TOeR06wLPPsvLLLwFY8uUSBj40kOVrlzN+xHgOaX1IujklSZIkSUrZzfk3M2XxFC5+9mJWrV/Fv/f59/I7zV9yCSxfDtdcA3vtBbfdVtb+RjvGlVG11aZNcMUVcNFFMGAAvPEGhADA8jXLyX84nwUrFzDme2M4os0RKYeVJEmSJCl9Odk5jD5rNAM6DuCnz/+UEx89kYUrF5YfcNVVcOWVcNdd0K8fvPlmemFrMItRtdFnn8GQIXDHHclvkueeS6q2wKqNqxj8yGA+XP4hz577LHnt8lIOK0mSJEnS7qNl45aM+d4Y7jn5HgrnFXLwPQfzxLQnksmsLPj975MeUvPnw5FHJruRVqxIN3QNYzGqtvngg6Tb/8svJ1v0/vAHyMmhuKSYUdNHcWHRhby35D2ePudpvtPxO2mnlSRJkiRpt5OVlcWlR1zK1Eum0rVlV8596lzOfepcVqxdkRSkvvc9iBEuvxz+8hfo2jX5DG4vqe1iMao2KC6G559PGqodcgh88QX8619w4YVsLN7IA1MfoMefenDOk+dQUlpCwbkFDOkyJO3UkiRJkiTt1rq07ELhhYXcOOBGnnz/SQ6+52DGzhqbTO65Z9I36q23oFu3pE1OXh68/Xa6oWsAi1E12axZ8OtfQ/v2yba8l1+Gn/4Upkxh3VG9uWfyPXS5qwsX/OMCGuY0ZNSZoxh1/ChOPPDEtJNLkiRJklQj5GTn8Otjf83r//Y6zXKbccIjJ3DBPy5gzIdj+HLDl8mikIkT4cEHYfZsOOKIpNn5Cy/AqlVpx98teTe9mmbNGnjqKbj//qT4lJ0NJ54Id94Jp5zCajZy75v38vuRv2fxl4vpd0A/7h5yN0O6DCErK4spU6ak/RNIkiRJklTj9G7TmykXT+Gal67hT5P/xANTH6B+dn36te3HoE6DGPSdQRwx433qXXc93Hsv/PnPyd32Dj8cjj0WjjsO+vcv6+lcl7kyqqYZPBhGjEgapf32tzBvXtKg/IwzoEEDbphwAz9/8ed0a9WNl0a8RNGFRZzc9eTyW1FKkiRJkqSd0qh+I/5wwh/47JefMfb8sVzZ90pWrV/Ftf+6lr5/68vefzmQM/ov5JWpBTB2bHL3vYYNk7vvDRsGLVvCoYfCjTfW6f5SroyqaW66KWmWduyxyePXXNH3Cs475DwOaX1ICuEkSZIkSar9GtVvxKDOgxjUeRC3citLVy9l/JzxjJs9jnGzx3F/w1Ecc+r/g0GDkhesWwdvvJFs55swIen7fM016f4QKaq2YlQIoSvwINASWA6MiDF++LVj6gF3AicCpcAtMca/bmuuTjn++G+d3q/pfuzXdL/qySJJkiRJkmi1RyuG9xzO8J7Dv/mAhg2TbXrHHQfXXlu94XZD1blN717g7hhjV+Bu4L5vOOY84ECgC9APuD6E0GE75iRJkiRJklQDVMvKqBDCPsDhQGZ9Go8DfwwhtIoxLq1w6DnAX2KMJcDSEMLfgbOA/9nG3LbUA9iwYUOl/Dw13fr169OOoFrM80tVxXNLVcVzS1XJ80tVxXNLVcVzSzuiQp2l3o68rrq26bUFFsYYiwFijMUhhEWZ8YrFqHbA3ArP52WO2dbctuwHMHPmzB1PXgtNmzYt7QiqxTy/VFU8t1RVPLdUlTy/VFU8t1RVPLe0k/YDZm3vwXWlgflk4BhgMVCcchZJkiRJkqTaoB5JIWryjryouopR84H9Qwj1Mqui6gFtMuMVzQPaU/5DVFwN9W1z36p3797rgcKdjy9JkiRJkqRvsN0ror5SLQ3MY4yfAlOBczND5wJvf61fFMBo4EchhOwQQivgNOCp7ZiTJEmSJElSDVCdd9O7FLgshDATuCzznBDCmBDCEZljHgZmAx8CrwM3xBhnb8ecJEmSJEmSaoCs0tLStDNIkiRJkiSpjqjOlVGSJEmSJEmq4yxGSZIkSZIkqdpYjJIkSZIkSVK1sRglSZIkSZKkamMxSpIkSZIkSdUmJ+0Aqj4hhK7Ag0BLYDkwIsb4YbqpVNOFEFoCDwOdgfXAR8AlMcalqQZTrRJCuA64Hjg4xjgt5TiqJUIIDYHbgHxgHfBajPHidFOpNgghnALcCGSR/OPv9THGp9NNpZoohPC/wHeBDlT4O9Dreu2qbzq3vK5XdXJlVN1yL3B3jLErcDdwX8p5VDuUAv8dYwwxxkOAWcAtKWdSLRJCOBzoC8xLO4tqnf8mKUJ1jTEeDFybch7VAiGELJIPc9+PMR4KnA88GELwuls74+/AscDcr417Xa9d9U3nltf1qjb+pVhHhBD2AQ4HHs8MPQ4cHkJolV4q1QYxxhUxxpcrDL0OtE8pjmqZEEIuyUX2v5NcIEmVIoTQBBgBXBtjLAWIMS5JN5VqkRKgWebXzYHFMcaSFPOohooxFsYY51cc87peleGbzi2v61WdLEbVHW2BhTHGYoDM46LMuFQpMv/q+2OgIO0sqjVuAB6JMc5JO4hqnc4kW1uuCyG8GUJ4OYTQP+1Qqvkyxc2zgX+EEOaSrD74QbqpVMt4Xa8q53W9qprFKEmV6S7gS+CPaQdRzRdC6Af0Af6UdhbVSjlAJ+DtGOMRwC+Bp0MIe6YbSzVdCCEHuAo4NcbYHhgKjMysxpOkmsLrelUpi1F1x3xg/xBCPYDMY5vMuLTLMk0QuwDnuBVBleQ44CBgTgjhY+AA4IUQwuA0Q6nWmAtsIrPNJcb4BrAM6JpmKNUKhwJtYoxFAJnH1UC3VFOpNvG6XlXK63pVB4tRdUSM8VNgKnBuZuhckn8N9s4I2mUhhN8CvYHTYozr086j2iHGeEuMsU2MsUOMsQOwADghxjg25WiqBWKMy4B/AYOg7M5U+5DcOUjaFQuAA0IIASCE0A3Yl6QRsLTLvK5XVfK6XtUlq7TUfrB1RQjhIJJbwO4FfEZyC9iYbirVdCGEHsA0YCawNjM8J8Z4enqpVBtlVked8tVtraVdFULoBNxPcmv0jcA1Mcbn002l2iCEcB7wK5JG5gDXxRj/nmIk1VAhhDuBM0gKmsuA5THGHl7Xa1d907lF0u/O63pVC4tRkiRJkiRJqjZu05MkSZIkSVK1sRglSZIkSZKkamMxSpIkSZIkSdXGYpQkSZIkSZKqjcUoSZIkSZIkVRuLUZIkSZIkSao2OWkHkCRJUvpCCB2AOUD9GOOmlONIkqRazJVRkiRJWxFCuD6E8MguvsfxIYQFlZWpsoQQPg4h5KedQ5Ik1T0WoyRJkqpICMFV6JIkSV+TVVpamnYGSZKk1IUQfgn8B7AnsAj4GfAMkAWsB2bFGHuFEC4AfgEcACwFbo0x3pd5j+OBR4C7gCuBV4BTgFxgTeZbdY0xLtpKhuuBHpnvdyrwMfDdzNeVmfF/izGOzRzfBrgX6A+syGT5S4X36g6sA04H5gE/iDG+GUJ4GDgv837FwA3AKJJtej8EbgQaA7fFGH+7w/8xJUmSvoUroyRJUp0XQgjAT4E+McamwAnAB8DvgJExxiYxxl6Zwz8lKTDtCVwA3BZCOLzC2+0LtADaAyOAk4BFmfdosrVCVAVDgYeBvYC3gRdIrtn2Jyka3Vfh2MeBBUAb4EzgdyGEgRXmhwFPAM2BAuCPADHG75MUp4ZmMv13hdf0BwIwEPivEEK3beSVJEnaIS4dlyRJSlYH5QLdQwhLY4wfAyQ1qs3FGJ+r8HRCCGEscAzwVmasBLguxrh+a++xDa/EGF/IvHY0cAZwS4yxOITwBPDnEEJzoClJ4eiUGOM6YGoI4a/A94HxmfcqjDGOybzXw8AV2/H9fxNjXAu8E0J4B+gFzNjRH0KSJGlrLEZJkqQ6L8b4UQjhCuB6oEcI4QWSbXpbCCGcBFwHdCVZsdQYeK/CIUszxaGdtaTCr9cCy2KMxRWeAzQhWQ21Isa4qsLxc4EjKjz/pMKv1wANQwg527hb3tdf02RHwkuSJG2L2/QkSZKAGONjMcb+JNvrSoFbM49lQgi5wFPA/wKtY4zNgTEkfaW+8vWGnFXVoHMR0CKE0LTCWDtg4Xa+3sahkiQpFRajJElSnRcS38kUm9aRrEAqJlml1CGE8NU1UwOS7XxLgU2ZVVKDt/H2S4CWIYRmlZk5xjgfeBW4OYTQMIRwCPBvwKPb+RZLgE6VmUmSJGl7WIySJElKCky3AMtItqntA1wNjM7MLw8hvJXZEvcfJHee+wz4Hklj8K2KMX5A0mh8dgjh88wd8CrLuUAHklVSz5D0qnpxO197M/DrTKafV2ImSZKkb5VVWuoKbUmSJEmSJFUPV0ZJkiRJkiSp2ng3PUmSpGoUQngeOOYbpn4XY/xddeeRJEmqbm7TkyRJkiRJUrVxm54kSZIkSZKqjcUoSZIkSZIkVRuLUZIkSZIkSao2FqMkSZIkSZJUbf4/lPmQtC/kfncAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1440x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#distribution of star_month\n",
    "plt.figure(figsize=(20,8))\n",
    "plt.title('Distributions of start_month')\n",
    "plt.ylabel('proportion')\n",
    "\n",
    "sns.distplot(df_successful['start_month'],color='green',hist=False)\n",
    "sns.distplot(df_failed['start_month'],color='red',hist=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fa985530550>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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cigUq8krLV6hbui6PzX+Mc3HnHN972DDYuRM2bsxi8CK3jr+u/MWiqEU8cccTPH7H43jZbvwSt2zBsrzU4iVm7J3B+sPr3RiliFxPySgRERERkWvFxcHs2dCrF/j7Z3j5pthNdJjYgaIBRQkfEk7VYlUB8PP248e7f+TE5RO8uORFx/cfMADy57eqo0TkpqbtnkZSShKD6g5y6Prnmj1H2YJleWHpC9hVfSjiMUpGiYiIiIhca/FiuHDBoRa9jbEb6TixI8UCihH+YDhVilb5x/sbl2/MC81eYNy2cSw/sNyx/QsXhv794bff4OLFLDwAkVvH5J2TqV2qNvXK1HPo+oJ+BXmnzTusO7yOWftmuTg6EbkRJaNERERERK41dSqUKAHt29/0sg1HNtBxYkdK5C9B+JBwKhetnO51I9qMoHrx6gybN4zLCZcdi2HYMLh8GaZMyWz0IreMmHMxrD28lkF1B2Gz2Ry+76EGD1GrVC1eWfYKicmJLoxQRG5EySgRERERkTRXrsDcuXDvveDre8PLthzdQqdJnSiVvxThD4YTWCTwhtfm883H+J7jiT4XzWthrzkWR5MmUKeOWvVEbmLKTitZO6DugEzd5+Plw0cdPiLyTCRjt4x1RWgikgElo0RERERE0oSGWhVJGbTojVg5gnw++QgfEk6lIpUyXLZV5VY8eceTfLHhC9YdXpdxHDabVR21eTNs3+5o9JKHbYrdRKeJndhwZIOnQ8kR7HY7k3dOpkWlFv9qj3VE1+pdaVOlDW+vfJsL8RecH6CI3JSSUSIiIiIiaaZOhdKl4a67bnjJhfgLLNm/hIF1B1KxcEWHl/6w/YdUKlKJh+c+TFxSXMY3DB5sDVAfN87hPSRvSkxOZOjcoSw9sJSWP7Vk0oFJt/zw7R0ndrD71G6HB5dfz2azMabjGE5dOcWoNaOcHJ2IZETJKBERERERgEuXYMEC6NMHfHxueNn8iPkkJCfQu2bvTC1fyL8QP/T4gX1/7eO9Ve9lfEPx4nDPPdYg84SETO0lecuXG79k18ld/NjzR7rX6M5nez7j7t/u5szVM54OzWMm75yMj5cPfWv3zfIajco3YmDdgXzyxyccuXDEidGJSEaUjBIRERERAZg3D65ezbBFb8beGZQrWI5mlZpleotOQZ0YUn8II9eMZPtxB9rvBg+G06etE/7klhR7IZa3wt+iW/VuDKk/hJn3zeSF2i+wKGoR9b+r71jbZx6TYk9hyq4pdA7qTMn8JbO11vvt3ifFnsLotaOdFJ2IOELJKBERERERsFr0ypeHli1veMnlhMssjFzIvTXvxcuWtR+lP+70MSXyl+Ct8LcyvrhzZ+tkv0mTsrSX5H7PLXmOpJQkvujyBTabDZvNRv+q/Vn38Dp8vX1p/VNrRq0ZRYo9xdOhus3qg6s5cuFIllv0rlWlaBU6B3VmXsS8W771UcSdlIwSERHJI5JTkolPivd0GCK50/nzsHAh9O0LXjf+EXlh1EKuJl3NdIvetYrnK06fmn1YfmB5xl+zvr7Qv791wt/581neU3KnZQeW8fvu3xnecjjVilX7x/sal2/M1v9spVfNXryy/BW6/9qdU5dPeShS95q8czIFfAvQ0+jplPVCgkOIPhdN1Jkop6wnIhlzWzLKMIwahmGsNwwjIvXP6ulc08kwjM2GYcQbhjHmuvd5G4bxtWEY+w3DiDIM4xF3xS4iIpLTJack0+3XbgR/GawfpkWyYs4cay6TAy16JfOXpFXlVtnarkv1LlxOvMyaQ2syvnjwYIiLg5kzs7Wn5C7xSfE8GfokQcWCeKnFS+leUySgCL/3+Z1vun5DWHQYTcc3JSE5b88Xi0+KZ/qe6fSq2YsCfgWcsmbnoM4ALIpa5JT1RCRj7qyM+g742jTNGsDXwPfpXHMAGAak17A7CAgGqgPNgBGGYVRxTagiIiK5y8g1I1m8fzGnr5ym3YR2xJyL8XRIkgccPn+YIbOHMHXX1Dz/ApepUyEwEJo2veElcUlxzI+YT6/beuHjdeMB545oW6Utft5+LIxamPHFTZpAUJBa9W4xY9aNIeJ0BF91/YoAn4AbXmez2Xj8jsf5tfevHDh7gNDIUDdG6X6LohZxNu4sA+sMdNqaQcWDCC4ezOL9ms0m4i5uSUYZhlEaaAhMSX3TFKChYRilrr3ONM0o0zS3AUnpLNMP+ME0zRTTNE8Bs4GsH50gIiKSR6w+uJo3w99kYN2BrB26losJF2k3oR2Hzx/2dGiSy7207CUm/DmB/jP6U+nTSryy7BUOnD3g6bCc78wZWLIE7rsPbLYbXrZ0/1IuJVzKVotemgJ+BWhdubVjySibzaqOWrECYmOzvbfkfDHnYnh/9fv0rtmbkOAQh+7pafSkdIHSTNwx0cXRedbknZMplb8UHYM6OnXdzkGdWRGzQu3uIm6SvV/pOK4SEGuaZjKAaZrJhmEcTX27o43NgcDBa/7/UOr9Dtu1a1dmLs/TtmzZ4ukQJI/Sc0tcRc+t9J1LOMegVYOokK8Cj1Z4lJSjKXze+HOe+OMJWv7QkrHNxlIyIHsnDeV1em6lb++5vfy26zceCn6IBsUbMPPgTMasG8OotaNoWqopvQN706pMq2xXCOUEJWbPpkpSEnvr1ePKTZ4P32//nkK+hShytohDz5uMrqkTUIdlB5axYM0CyuYre9Nr/W+/nTp2O0dGj+bE/fdnuLfkbs9teg7s8FD5h274PErv7e1Lt2e6OZ0V61dQ2K+wq8N0u0uJl5i7by53B97Nn9v+dOrawQRzJfEKPy7/kTtL3unUtXMb/bso7pD7f3rIhDp16uDv7+/pMDxuy5YtNGrUyNNhSB6k55a4ip5b6bPb7fT8rSdnE8+y/uH1NCzXEIBGNCK4RjCdJnbi2e3PEj4knNIFSns42pxJz60bGz5xOCXyleDT3p9SJKAIT/M0sRdiGb9tPD9s/YEXt7xIuYLleLbps7zQ/AVsN6koyvGGD4dq1ag5ePANK6MSkhNYu2wtvWr1oukdN27lS+PIcyt/YH4+2/MZsfli6dao280XbNQImjShYng4FT/7LMP9c4X162HECOv0wtdeu+ng+FvJ/Ij5rDqxilEdRtGtRfrPixs9v54v9zxTfphChG8EjzZ61NWhut2E7ROIT4nn2fbP0qiic793GwkGL215iQO2Azze6HGnrp2b6N9Fyaz4+PgsFf646zv+YaCCYRjeYA0jB8qnvt1Rh4DK1/x/YCbvFxERyVM+3/A58yPmM7rj6L8TUWmaV2pO6KBQYs7F0OGXDpy+ctpDUUputHT/UpYeWMrrrV+nSECRv99eoXAF3rzrTaL/L5q5/edSs1RNXlr2EuuPrPdgtNl06hSEhVmDy2+SUFsRvYJzcefoU7OP07a+reRtBBYJdKxVD6xWvT//hJ07nRaDR8TEWCcENm9uJaTefBN69oRz5zwdmcddSbzC0wufpmbJmjzT9JlM39+wXENqlqyZZ1v1Ju+cTLVi1WhSoYnT1y7oV5BWlVtpbpSIm7glGWWa5klgOzAg9U0DgG2ps58cNQ0YZhiGV+qsqXuAGc6NVEREJHfYfHQzLy19ibuNu3n6zqfTvaZ15dbMHTCXiNMRdJzYkbNXz7o5SsmNUuwpvLL8FSoXqczjjdOvDvDx8qGH0YM5/edQyK8Q323+zs1ROtGMGZCcnOEpetP3TKegX0Gnzqmx2Wx0Ce7C8gPLHRsQ368feHvD5MlOi8GtLlywqtBuuw3mzrWSUEePwtdfw+LF0Lhx7k+0ZdOHqz8k5lwM33T7Bj9vv0zfb7PZuL/e/aw9vDbPzXc7fuk4y6OXM7DOQJdVYoYEhbDz5E5iL2g2m4irubMW9jHgacMwIoCnU/8fwzBCDcNonPr3loZhHAGeAx41DOOIYRidU++fiHXaXiTwB/COaZp56zusiIiIA87Hnaff9H6UK1SOH+/+8aY/lHeo1oFZ/Wax+9RuQiaHcCH+ghsjldxo2u5pbD22lXfbvou/z83HGxT0K8gDtz/A77t/z73Vd1OngmFAvXo3vCQpJYnZ5my61+h+01PNsqJLcBcuJlxk3eF1GV9cqhSEhFjJqJQUp8bhUklJMHYsVK8OI0dag+IjIuDtt6FgQXjiCQgPh8uXrdMMf/vN0xF7xKHzh/ho3UcMqjuINlXaZHmdQfUGATBpR946fXHqrqmk2FP+fnyu0DnYeump6igR13PbzCjTNPcB/6qnNE2z6zV/XwNUvMH9ycCt27wrIiKCNSfq0fmPcvDcQVY9tIri+YpneE+X6l2Y1ncavX/vzaPzH2VK7ykZ3iO3poTkBF4Le416ZeoxsK5jx6Y/1vgxvt70NT9v/5nnmz/v4gidLDYWVq60KnRuktRdfXA1f135y6ktemnaVW2Hr5cvCyMXOpaAGDwYFiyAVaugjQPXe1p4ODz9NOzaBa1aWbE3bvzv61q0gK1boW9fGDAANm+2Elc+t86I29n7ZpOQnMCINiOytU5gkUDaVGnDxB0TeaP1G7l7nts1Ju+cTMNyDbmt5G0u26Nu6bqUK1iOxfsXM7TBUJftIyLurYwSERGRbBq3dRxTd0/l3bbv0rxSc4fv62n05PHGjzNr7yxVR8kNjds6jv1n9zOy/Ui8vbwduqdO6Tq0DGzJd1u+I8Wei6p1wKqKstth4M0Tb9P3TCefTz5CgkOcHkIh/0K0DGzp+Nyonj2taqJJuaDqZedO6NQJrlyB6dOtxF96iag05cpZ87ueego+/ti691RmpnrkbqGRoRglDIKLB2d7rfvr3U/UmSg2xG5wQmSeF3k6kk1HNzGwjmNJ8qyy2Wx0Du7M0v1LSU5JduleIrc6JaNERERyid0nd/PfRf+lY7WOvNzy5Uzff1/t+4hPjmd+xHwXRCe53aWES7y98m3uqnxXppMujzV6jKgzUYRFh7koOhf59VfrlLoaNW54SYo9hVn7ZtGlehcK+BVwSRhdgrs4Pqcmf37o3RumTYO4OJfE4xSJifDgg1CsGGzYYMXsSIWOnx98+SX8/LM13LxRo1tijtSVxCuEx4TTJbiLU9brU6sPAT4BTPwzbwwy/33379iw0b9Of5fvFRIUwtm4s2w6usnle4ncypSMEhERySVGrxuNn7cfE3tNxMuW+X/Cm1dqTvlC5Zm2Z5oLopPc7pP1n3Dy8klGdRiV6bae3rV6UyJfidw1yDwiArZsybAqav3h9Ry7dMwlLXppulS3EhCLohY5dsPgwdYw8Pk5OLH84YewbRt89x2ULJn5+x98ENatg4QEePRRq4ItD1sRvYL45Hi6Vu+a8cUOKOxfmHtuu4ffdv/m2HD8HG559HLql61PhcIVXL5Xh2od8LJ5Of71KCJZomSUiIhILpCUksS8iHn0NHpSpmCZLK3hZfOiT80+LIxcqFY9+YdTl08xet1oetfsTZOKmT8yPcAngKENhjJ732yOXjzqgghdYMoUq1Ing1P0ZuydgZ+3H91qdHNZKLVL1aZCoQqOt+q1bWu1tOXUVr3t2+Hdd61EX69eWV+nQQMYMcKqkFqyxGnh5UShkaHk981P68qtnbbm/fXu58zVM4RGhjptTU+4mniVdYfX0a5qO7fsVyJ/Ce4of4eGmIu4mJJRIiIiucDqg6s5c/UM9xj3ZGudvrX7qlVP/uW9Ve9xNfEq77d7P8tr/KfRf0i2JzN+63gnRuYidrvVonfXXVDhxpUWdrudGXtn0CmoE4X9C7ssHJvNRpfgLiw9sJTE5MSMb/D2thI9oaFwOoedYpiQYFU1lSxptdtl19ChEBhoJaXyaHWU3W4nNCqU9lXbZ3iCZWZ0CupE6QKlmbgjd7fqrTu8jvjkeNpXbe+2PUOCQ9gYuzH3nhIqkgsoGSUiIpILzN43mwCfgGwPUFarnlzvwNkDfLv5Wx5u8DBGSSPL6wQXD6ZTUCfGbh1LUkqSEyN0ga1brTa9DFr0Nh/dzKHzh+hds7fLQ+pSvQsX4i/wx5E/HLth8GBrLtO0HPa1/O67sGMHjB0LxTM+7TNDfn7w2mvwxx+wOG9WqpinTWLOxTitRS+Nj5cPA+oMYH7EfM5ePevUtd1pefRyfLx8aBnY0m17dg7qTIo9hWUHlrkU7E+nAAAgAElEQVRtT5FbjZJRIiIiOZzdbme2OZuO1Tpme4Cyl82L3jV7szByIRfjLzopQsnN3lzxJj5ePrzV5q1sr/VYo8c4cuFIzm8LmjIFfH2todo3MWPvDHy8fOhp9HR5SO2rtsfHy8fxVr3bb4fatXNWq97mzdasqAcfhB49nLfukCFQuTK89VaerI5K+3px1vDya91f734SkhP4fffvTl/bXcKiw7izwp0U8i/ktj3vqHAHxQKKqVVPxIWUjBIREcnhth3fxqHzh+h1WzZmr1yjby216okl6kwUk3dO5pmmz1C+UPlsr9fD6EH5QuVz9iDz5GQrGRUSctPKHbvdzvQ902lXtR3F8zmhwicDRQKK0LxSc8eHJttsVnXU2rVw4IBrg3NEfLyVhCpTBj77zLlrp1VHbdwICx1M1uUiC6MWUrtUbSoXrez0tRuWa0jNkjVzbave+bjzbDq6ya0temBVlXWo1oHF+xdjz4MJUJGcQMkoERHJUfae2ku1z6tR6dNKBH0RRK2vazFw1UCajmtK659a03FiR4bMHkJcUg4+0tzJZu+bjZfNi+41ujtlvRaBLShXsBy/78m9vykX55hrzgXg0UaPOmU9Hy8fhjUcxqKoRUSfjXbKmk63ejUcPZphi96OEzvYf3a/W1r00nQJ7sK249s4fum4YzekPYacUB01YgTs2QPjxkHRos5ff8gQqFIlz82OupRwiZUxK11SFQXWPLL7693P2sNrOXA2ByQtM2nVwVWk2FPcNrz8WiHBIRy9eJRdJ3e5fW93Onv1rBJu4hFKRomISI7yzqp3OHXlFB2rdaRZxWbULl2bMvnKUCSgCF42L87FnWPCnxP4adtPng7VbWbtm0WrwFaUKlDKKet52bzoU6uPWvWA41eP8/zi5yk+qjjfbvrW0+G43YLIBU6vyHik4SN42bwYu2Ws09Z0qilToECBDNvI5kXMA+Ce27J3aEBmpM2Ec7g6KjAQOneGr7+GK1dcGFkG/vgDPvoIHn4YurgmqYKvL7z+OmzaZA1uzyOWH1hOYkqi0+dFXWtQvUEATNqRA5KWmRQWHUaATwBNKzZ1+96dgzoDmfh6zIU2xm6k/CflGTZvmKdDkVuQklEiIpJjRJyOYOquqTx5x5P8ePePTLp3EtP6TuPTOz5l8eDFhA8JZ+MjG2lasSmj1o5y7NSpXC7qTBS7Tu5y+gviW71Vb8vRLQycMZC7w+7m8w2fU8i/EC8te4kjF454OjS3uRB/gVUHV9GtejenrluxcEV6GD0Yv2088UnxTl072xISrIHfd99tJaRuIiw6jPpl61O6QGk3BQe3l7mdcgXLZe7F7+uvw8mT1sBwT7h61apaqlABPvnEtXs98ABUrZqnqqMWRi2kkF8hWgS2cNkegUUCaVOlDRN3TMx1FTBhMWG0DGxJgE+A2/euULgCdUrXybNzo45dPEavqb2w2+2M3zY+VyYrJXdTMkpERHKMkWtGEuATwHPNnrvhNTabjddbvc7B8weZvHOyG6PzjNn7ZgPOr85Ia9W7lU7VS7GnsCBiAW0ntKXxD42ZHzGfgVUHEv1/0ax4cAVJKUk8u/hZT4fpNkv3LyUpJclp7Z/XeqzRY5y6copZ+2Y5fe1sWbwYzp7NsEUvLimOdYfX0a6Ke1uDbDYbIcEhLNm/xPETCVu2hDZtrMqkOA+0L7/xBpgm/PgjFC7s2r3SqqM2b4b5uT+RbrfbCY0MpUO1Dvh5+7l0rwfqPUDUmSg2xG5w6T7OdPLySXac2OH2r8NrhQSFsPrQai4lXPJYDK4QnxTPvb/fy7m4c6x/eD2tAlvx2PzHiDgd4enQ5BaiZJSIiOQIB88dZOKOiQxrOCzDSoSu1btSv2x9PlzzIckpyW6K0DNm75tN/bL1qVK0ilPX/btVL2phnvshOz2z9s6izjd16D6lO1FnohjTcQyHnz3M/9X6PyoVqUS1YtV4vdXrTN8zPU+3ZFxrQeQCigUUo1mlZk5fu2NQR6oVq5bzBplPmQIlSkCnTje9bP3h9cQnx9O2als3BfY/XYK7cDbuLBtjNzp+05tvwrFjMH686wJLz4YNVjXUo49Chw7u2fP++6FatTxRHbX71G4OXzjs0ha9NL1r9SbAJ4CJf+aeQebhMeEAHpkXlaZzcGcSkhP+jiUvsNvtPBn6JH8c+YMJ90ygQbkG/Nr7VwJ8Aug3vR/xyTmsolXyLCWjREQkR/ho7UfYsPFiixczvNZms/Faq9eIOB3B9D3T3RCdZ5y4dIJ1h9c57RS96/Wt1Ze4pLg836p3/NJx+k3vh5fNi0m9JnHgvwd4vvnzFAko8o/rXmj+AkYJg6dCn+Jq4lUPReseKfYUQiND6RzcGR8vn5tfPGmSVUn0n//As89alTCjRllziiZMgBkz4Mg/2xu9bF482uhRVh5cyZ5Te1z4SDLh0iWYMwf69LEqbG4iLDoMb5s3rSu3dlNw/9OhWge8bF4sjMzEqXFt2lgVUiNHWqfauUNCAgwbBuXLW1VZ7uLraz0Ht26FefPct68LhEZas69cNbz8WoX9C3O3cTfT9kwjxZ7i8v2cISw6jML+hWlUvpHHYmgZ2JL8vvlZHJV3WvW+2fQN47eN57VWr9GnVh/Aaq/++Z6f2X58O5/tcfJpmCI3oGSUiIh43LGLxxi/bTxD6g+hYuGKDt1zb817ua3kbXyw5oNcNwPDUXPNudixu2yA8t+n6u3O26fqjd0ylsSURGb2m8mgeoPw9U4/EeHv48/XXb9m/9n9jFo7ys1RutfWY1s5cflExvOipk2zKlFWrLDaosaPh/ffh1degaeesmYF9ekDt98Ou/554tRD9R/Cz9uP7zd/77oHkhlz51pDvjNo0QNYEbOCxuUbU9jfxW1n6SiWrxjNKjZj0f5MVOjZbFaC5sgRK0HoDqNHw86d8M03rm/Pu97gwRAUlOuroxZGLaRemXpUKFzBLft1r9GdU1dOse3YNrfsl13Lo5dzV+W7Mk6Yu1CATwBtq7TN3NdjDrYyZiXPLH6G7jW6807bd/7xvu41uvNc0+eYdnAaM/fO9FCEcitRMkpExANS7Cl8vfHrnFMx4GEfr/+YxJREXm7xssP3eNm8GN5yODtO7MizlT2zzdlUK1aNuqXrumR9L5sXvWv2ztOtegnJCXy3+Ts6B3WmRokaGV7fvlp7BtQZwIdrPiTydKQbIvSMBRELsGH7+/S2dP3xhzUwukULiI6Go0fhwgVITobLl+HECdi/H1avhoAA6NgRIv/3MStVoBS9a/Zm4o6Jjs8/cqUpU6BiRauC6CYuJVxiQ+wG2lZxf4temi7BXdh8dDMnL590/KaOHaFJE/jwQ0h08eEO+/bBO+/AffdBz56u3Ss9Pj5W8m3bNqvaLRc6H3eeNYfW0DXY9S16aToFWe2puaEV+dD5Q0SdiaJ91faeDoXOQZ2JOhPF/jP7PR1Kthw8d5A+0/oQXDyYSb0m4WX7dyrgww4fUqtILYbOGUrMuRj3Bym3FCWjRETczG6383To0zy18Ck6TuzI0YtHPR2SR/115S++3fwtA+sOJKh4UKbuHVBnAFWLVuW91e/lueqoC/EXWHZgGfcY92Cz2Vy2T9/aebtVb9beWRy7dIyn73za4Xs+7vQxAT4BPLXwqTz3vEqzIHIBTSs2pWT+kulfEBNjnThXvjzMmmUlm9LYbJA/P5Qubc3uadkSli2DpCRo3x4OHvz70ntr3svZuLOsP7zetQ8oI6dPw6JF0L8/eN38x981h9aQlJLk0Tk1aUnCTLUGpVVHxcRYrZWukpJitWwWKABffOG6fTIyaBAEB8Pbb+fK6qhlB5aRlJLklnlRaUoXKE2jco1yRZVPWHQY4Nl5UWn+/nrMxafqXUm8wj1T7yExOZE5/ef8q009jZ+3Hx80/AA7dvpP739LnFosnqNklIiIG9ntdl5e9jLfbP6GB25/gPNx5+k1tVeen09zM5//8TlXEq8wvOXwTN/r6+3Lyy1eZmPsRpZHL3dBdJ6zKGoRCckJLmvRS9OiUt4+Ve/LjV9SrVi1m1cAXadcoXK81/Y9luxfkic/LicunWDT0U03btE7dw66dbNmAi1YAKVKZbxozZqwZIlVOdWhgzVMG+hYrSM+Xj4siFzgxEeQBdOnW8kyR1r0olfg6+VLi8AWbggsfQ3KNaBk/pKExYRl7sauXaFhQ/jgA+vxusK4cVY13JgxUKaMa/ZwRFp11PbtMHu25+LIooVRCyniX8QlBwjcTEhwCOsPr+dc3Dm37ptZYdFhlMpfitqla3s6FIKLBxNYJJAVMSs8HUqW2O12hs4Zyp/H/+TX3r9mWCVcsUBFxvUYx4bYDbwW9pqbopRbkZJRIiJu9M7Kdxi9bjRP3vEkP9/9M5PuncTG2I0Mmzcsz1Zg3Mz5uPN8ufFLetfsTa1StbK0xpD6QyhfqDzvrXrPydF51qx9syiVvxTNKzV36T7eXt70rtmb0MjQPNeqt+3YNtYeXsuTdzyJt5d3pu594o4naFC2Ac8seoYL8RdcFKFnLIyyBmN3q5FOMioxEfr2hYgImDkTbrvN8YUbNICFC61EVMeO8NdfFAkoQqvAVn8PavaYKVOsx1K/foaXhsWE0bRiU/L75ndDYOnzsnnRMrAlqw+uztyNadVRUVHw22/OD+zoUXjxRWjXDh56yPnrZ9bAgVC1qmcrtLLAbrcTGhlKp6BObp+HFBIcQrI9mWUHlrl138yw2+2ERYfRrmq7dFvJ3M1ms9GmShvCY8JzzfD3a41eN5qpu6fyQfsPHK7E61u7L481eozR60Zn7jAFkUzw/Fe3iMgtYsy6MYxYOYIh9YfwRZcvsNls3HPbPbzX9j0m75zMR2vdeBpRDvH1pq85H3+e11pl/Tdv/j7+vNj8RVYeXMnaQ2udGJ3nxCfFsyBiAT2NnplOomRFWqvegggPV6842VcbvyK/b36GNhia6Xu9vbz5rvt3HL90nLdWvOWC6DxnQeQCKhSqwO1lbv/nO+x2ePJJq+Xuhx+gbRZmJjVrZp1wtn8/hITA+fN0rd6VnSd3cuj8Iec8gMw6fBhWrYIBA6xkzU2cizvH1mNbc0RrUKvAVuw/u59jF49l7saePaFePWvQfHKyc4N66imrYu777zP8WLqFj491ol94uJVAzSX+PPEnxy4dc2uLXpqmFZtSxL9Ijp4bFXE6gtiLsTni6zBN2ypt+evKX+w+udvToWTKpYRLvL3ybe657Z5MzeUE+KTzJ9QrU48HZj/A8UvHXRSh3MqUjBIRcYNvN33Li0tf5L7a9zGux7h//Kbv1Vav0r9Of4YvH848M3cfU50ZlxMu88n6T+havSsNyjXI1lrDGg6jZP6SvL/6fSdF51krYlZwMeEivW7r5Zb9WlRqQdmCZfl9T945Ve/0ldP8uutX7q93P0UDimZpjTsr3MmjjR7li41fsP34didH6BkJyQks2b+ErtW7/nsW2ZgxVhLq1VetU/Kyqm1bmDEDduyAbt3oXt5Kannst+tTp1qJtgEDMrx01cFVpNhTcsSL4JaB1qD1NYfWZO5GLy94/XVryPj06c4LaOZMa37Y229bs5pyiiFDwNvbah/MJdK+FjLTPuwsPl4+dAzqyKKoRTm2IjsnzYtKk3agQW5r1Zu9bzZXEq/wfLPnMz1/Mp9vPibfO5m/rvzFlJ1TXBSh3MqUjBIRcbEJ2yfwROgT9KjRg0m9Jv2r0sVmszG+53galmvIwJkDc91v3bJq7JaxnL56OltVUWkK+BXguabPsTBqIVuObnFCdJ41e99sCvoVpH0195wilBdb9cZtHUdcUhxP3vFkttb5oP0HlMhXgscXPJ4r2zOut+bQGi7EX/j3vKiZM+Hll6FfP3j33exv1LUr/PorrF+PMewVahQI9MzcqORk+PFHaNwYqlfP8PKw6DACfAJoUqGJG4K7uQZlG5DfNz+rD2WyVQ+gd2+oVQvee88aOJ5d585ZVXMNGsBzz2V/PWcqV86qBvv5Z6tqKxcIjQqlYbmGlC1Y1iP7hwSFEHsxlt2ncubPG2ExYQQWCSSoWOYONXGlykUrU7VoVcJjwj0dSqZM3jmZKkWrZLnlv07pOlQrVi1r34dEMqBklIiIC/2++3eGzh1Kx2od+b3v7/h6+6Z7XX7f/MzpP4eCfgXp+VtPTl857eZI3SsuKY7R60bTpkobp81EeuKOJyjiX4QP1nzglPU8JcWewhxzDl2CuxDgE5DxDU5yX+378kyrXnJKMt9s/oY2VdpQt0zdbK1VLF8xxnQawx9H/mD2vtw3JPl6CyIW4Oft989E56ZNMHgwNGkCP/2U4WlzDuvTB378EduyZUyZ48vyA8uIS4pzztqOmjgR9u6Fl15y6PKw6DBaBrbE38ffxYFlzNfbl2YVm2XtRaCXF7z2Guza5Zzh3i+9BKdOWdVHPu6dceSQYcOs+ObM8XQkGTp79SzrDq+ja7D7W/TSdA7uDJAjW/VS7CmsiF5Bu6rtXHqSbFa0qdKGlQdX5ppfTJy4dIIl+5cwsM7AbM3eal25NasOrsqxlXSSeykZJSLiIvMj5jNo5iCaV2rOrH6zMkwsVChcgdn9ZhN7IZY+0/rk6eN0f97+M8cuHeP1Vq87bc0iAUX4b5P/MnPvzFxdXbbhyAaOXzru8lP0rteiUgtKFyjNHDPnv5jLyLyIeRw6f4in73zaKesNrDuQUvlLMXX3VKes50kLIhfQpkobCvoVtN6QkmK1OZUubb2Qz5fPuRs++CCMGkXDNft5YP1VVsasdO76NxMXB2++aVVF9emT4eWnLp9i58mdtKuSc1qDWgW24s/jf3I+7nzmb+7XD2rUsCrdsvMiMjzcat987jnrpL6cqFMnCAy04szhlh5YSoo9hS7Vu3gshoqFK1KndJ2/DzPISXac2MHpq6dz1NdhmrZV2nLm6hl2nNjh6VAcMnX3VFLsKQyqNyhb67QKbMXpq6fZ+9deJ0UmYlEySkTEBZJTknlk7iPULV2XBQMXUMCvgEP3NanYhHE9xxEeE87/Lfo/F0fpGUkpSYxaO4omFZo4fR7E/zX5Pwr4FuDDNR86dV13mr1vNr5evv9uo3Ixby9vOlTrQFh0WK7/7edXG7+iUuFK9DR6OmU9Hy8f7q15L/Mj5nMl8YpT1vSE/Wf2Y542//ncmjED9uyBUaOshJQrvPACySGd+HQxbFsywTV7pOfbb63h5SNHOjRsO639pm3VLAxud5GWgS2xY2f9kfWZv9nb26qO2r7dasPMik2b4P77oVo1GDEia2u4g7c3PPwwLF0KBw54OpqbCo0MpXi+4h5vBQ0JCmH1wdU5rjV7+YHlQM6aF5Um7XvDiujcMTdq8s7J1C9bP8unFadpXbk1QOZP9xTJgJJRIiIusPrQak5cPsGrrV6lsH/hTN07uN5gXmr+Et9u/pY5+3J/lcr1Vh9cTcy5mCwN08xIifwlGNZwGL/t+o0zV884dW13sNvtzNo3i7ZV21IkoIjb9+9QtQMnLp/IsXNEHLHn1B6WRy/n8caPO/XI9L61+nIl8UquPuI6bWbT38molBSraua22xyqHMoyLy+8J0zkckF/+rwzHfslN7z4PX/eOk2uY0do79jstbDoMAr5FaJx+cYuDs5xTSs2xcfLJ+svAgcOhJo1oX9/q0rM0ZlKKSnWQPvmza2Wv2nTIH/+rMWQjjWH1vDxuo95a8VbPLf4OR6Z+wj3TbuPkEkhtPixBQ2/b5j5xzx0qBVrDh5knmJPYWHUQjoHdXbLSak3ExIcQmJKYo5LrITFhGGUMKhQuIKnQ/mXioUrElw8mPCD4Z4OJUORpyPZGLuRQXWzVxUFEFQsiHIFy7Hq0ConRCbyP0pGiYi4wPQ908nnk48uwVkrw/+g/QeUL1Sen7b/5OTIPG9+xHz8vP1c1qIwoO4Aku3JhEaGumR9V9r7114iz0S67RS966XNEVp2YJlH9neGrzZ+hb+3P480fMSp695V5S5K5i/JtD3TnLquOy2IXIBRwiCoeOpQ4DlzYOdO6+Q1bxe/MC5dmjXvP0q1E4mcf+wh1+4FViLl9Gn40PEqyRUxK2hdubVTk5jZVcCvAA3LNcz68GAfH1i71kpKvfuu1bK4devN7zl5Erp1gxdfhB49rMoqJ7bn7Tm1h7t+vosXlr7AO6ve4YetP7AwaiE7T+7kbNxZ8vnkI/ZiLE+GPklySrLjC1esaMX900+QmDPb3Hed3MXJyyfpHNTZ06HQMrAlBXwL5Ki5UYnJiaw6uCpHVkWlaVO5DStjVmbuuekBk3dOxoaNAXUyPkU0IzabjdaVW7MyZmWur5yWnEXJKBERJ0uxpzBj7wy6Vu/qcHve9by9vOlfuz+hkaGcvXrWyRF61ryIebSt0vZ/M2ucrHH5xpQrWC5XDptOGx7eo0YPj+wfWCSQ6sWrszx6uUf2z67zcef55c9f6F+nP6UKlHL8Rgd+uPbx8uHe26xWvauJV7MRpWdcSrhEeEz4/6qi7HYrOREcbM0WcoP6A5/jg1ZQdPJ0mOLCY8KPH4dPPoH77oNGjRy6JfZCLOZp8+/j23OSVoGt2Bi7kfik+KwtUKwYTJgA8+bBX3/BnXfCG29AfDrrLV8Ot98OK1bAN99YbZzFimXvAVzn1eWvUsC3AIeeOUTym8lcHH6R2Odi2fvkXjY8soFlDyzjqy5fsfPkzsz/QmbYMOvzP3++U2N2lrRW0DZV2ng0DgB/H3/aVW3HwqiFOSbBsOnoJi4lXKJ9VfecJJsVbau25Xz8ebYf3+7pUG7Ibrczeedk2lZt67QKs9aVWxN7MZaYczFOWU8ElIwSEXG6dYfXcfzScfrUyl7by8C6A0lMSWTG3hlOiszzIk5HEHkm0qXJFi+bF3cbd7MoapH7T+7KpqUHllK7VO3M//B46pT14n7zZriSvZlG7au2Z2XMylw5QP/n7T9zOfGy44PLDx2i7LhxEBRkDXr+88+bXt63dl8uJ17OkUN/M7L8wHISkhPoViM1GbVgAWzbZs0UctPpaJWLVmZa31rsql4EHn0U9u93zUbvvmu1o733nsO3rIixWpVyYkVGq8BWxCfHs/no5uwt1L077N5tnZz43ntWldSWLdb7EhOt50LHjlbyaeNGePxxh2ZtZca6w+uYY87h5RYvU6lIpRue8NWnVh+aV2rOGyveyNxMoy5doEKFHDvIPDwmnKpFq1K5aGVPhwJYrXrR56KJOhPl6VAAq1UWckay7kbSEtZp3zNyok1HNxF1JsopLXpp0uZGrTqoVj1xHiWjREScbPqe6fh7+2d7AHXDcg2pUaIGv+781UmRed78COu31X+/IHaRu2+7m8uJl/8ehJobxCXFsfrQajpW65i5G0+fhlatrDacO+6AggWtxEqfPvD22zBrFkRFWTNgHNChWgcuJlxk09FNWXgUnpNiT+GrTV/RrGIzGpW/STVMXBxMnQqdO0OVKlT47juoWhWuXoUWLW56NHybKm1ybavegsgFFPYvTMvAllZV1DvvWI97kPNerDii823duKfHZeze3jBggOMzjBwVFQVjx8Ijj0D16g7ftiJ6BcUCinF72dudG48TtAhsAZD1Vr1rFSsGP/9sVQ6dOQNNmsDLL0ObNvDBB9bcpU2boF697O91HbvdzivLXqFswbI80/SZm15rs9n4uNPHHL90nNFrRzu+iY+P9RgWLYKDB7MZsXOl2FNYeXBljkq0hASHAOSYBHtYdBj1y9anRP4Sng7lhsoVKodRwsjRyajJOybj7+1P75q9nbZmrVK1KBZQTMkocSolo0REnCitRa9zcGcK+RfK1lo2m42BdQYSHhPO0YtHnRShZ82LmEed0nWoUrSKS/dpW6UthfwKMcfMPQPg1x5aS1xSHB2DMpGMunLFqnaIibHaaWbMsIYU161rVfm8/Tbce6/1otwwrAqqDLSt2hYbtlyVyANYsn8JUWeieOrOp9K/YNs2ePppKF/eGua8bx+8+SY75861WpM2boRataBXL+tkuXTaVny8fOh1Wy/mmfNyVaue3W4nNDKUTkGd8PP2g8WLrYTDq6+Cr69bY+lWvRv7Cyex8e3/WDG89ppzN3jjDfDzs74OMiEsJow2VdrcsFLHk0rmL0nNkjWdk4xK060b7NplnZT30UfW7LApU6zh3wWy1l6ekQWRC1h9aDVv3fWWQy3sTSs2pV/tfoxeN5rYC7GOb/Tww9afP/6YxUhdY9fJXZy5eibzyaidO2HJEqt1cu1a63vVtm0E7N8PERFw5EiWY6pWrBrVi1fPEXOjriZeZd3hdTm6RS9NmyptWH1wNUkpSZ4O5V+SUpL4bfdv9DB6OPUgFC+bF60qt3Lu9yG55eW8f3FFRHKxTbGbOHLhCH1qptOid+4cxMZaR40fPAjR0VabSmSk9cL42LF/3TKg7gDs2Jm6a6obonetc3HnWH1wtVvmIfn7+NOlehfmmHNy/JDRNEsPLMXXy/fvUvgMJSVZs342brReRN57r/XfiBFWUioyEi5ehA0brNkvhw/Dgw9mWCFVPF9xGpZryLLo3DXE/JtN31C2YNn022P/7/+sAcw//AAhIdbx79HRMGIECeXLW9eUKwcrV1pzhl55BR56KN2ZOn1rWa16OeHFm6P+PPEnsRdjrWrNtKqowEB44AG3x9K8UnOK+BfhhyqnrTawMWNgoZOqMrZuhd9+g2eesT6fDoo+G03MuZgc2aKXplVgK9YeWuvc72fFilnDvteutRJT/fs7b+3rJKckM3z5cKoXr87DDR52+L4P239Isj2Z11e87vhmlStblY/jx1vfJ3OIlTErAbir8l2O3zRhglWl1rkztGsHLVta1WwNG1K7Xz/rlwyVKsFzz2U5rpDgEMJjwj2eYF97eC3xyfE5+uswTdsqbbmYcJGtxzI4DMADlh1YxsnLJ8hyokEAACAASURBVJ3aopemdWBrIs9Ecuziv39eFckKJaNERJxo+p7p+Hr50sO4LuHy++9QqpR12k9gIFSpAtWqWcODa9Swjt6uWNFKIlyjRokaNC7fmF935f5WvcVRi0m2J9O9Rne37HePcQ8nL59kQ+wGt+yXXcsOLKNZpWaODXa3260X8vPnw1dfWdU86SlQwBpW/Pjj8PHH1ov+Tz7JcPn2Vduz/vB6LidczuSj8IyL8RdZvH8xA+oMsCp/rhUaCl98YQ02PnoUfv0VOnSwjoC/Xr58VmLvrbesF4EdOvyrmqxt1baUyFciV7XqpQ3G7xLcBcLCYP16GD7cqiByM19vXzoFdSI0MhT7mDFWFd+DD6abjM+04cOheHF46aVM3ZaT50WlaVW5Fefjz7Pr5C7nL968ufXvkgtN2jGJXSd38V679/D1drwar2qxqvz3zv8yYfuEzA2M/s9/rF/+LMo5SePwg+FUKVrF8XlRM2daLYcdOsCaNVZl1JIl1ry3WbPYP3IkTJ5sff18+il8912W4uoS3IWrSVc9XvESGhmKn7ef47+Q8aC06rYV0TmvVW/yzskUDSia5dOcbybtc+Pp54rkHUpGiYg4id1uZ/re6XQM6kjRgKL/e8fBg9YPxg0awPffW9UZ48dbv5H+5ReYNMl6gdy4sVWNERn5j3UH1BnA5qObiTgd4eZH5FzzIuZRMn9JmlRo4pb9ulTvgo+XD3P25fxWvdNXTrP12FY6VO3g2A0jRljtNK+/biWaHPHEE1bl1PDhVrXUTbSv1p7ElMRc8wPn4v2LSUhO4G7j7n++48wZa3ZQnTrw5ZdWoiIjNpv18U0bCH/nndbQ51R/t+pF5J5WvQWRC7ij/B2UKVjGqoqqUMH6XuMh3ap349ilY2w/b1rzuy5fhh49stVuRFiY9UL91VehSOZaU8KiwyhToAw1S9bM+v4u1jKwJQBrDq3xcCSZF5cUx5vhb9K4fOMsHezxWuvXKJ6vOM8ved7xU9+6d4cyZaz5YTlAij2FlTGZmBe1ZIlVqdakCcyebc2za9PGGjDftSvccw/nOnSwZgWOH2+97amnYFnmK1rvqnIX/t7+Hq/2nB8xn3ZV27nspF1nKlOwDLVK1cpxc6MuJ1xm1t5Z9K3VF38ff6ev36BcAwr4FtDcKHEaJaNERJxk67GtxJyL+WeLXnKy1QqTkmK1j/znP9aL46FDYcgQa17HoEHWIN9p06z5LX36WMOUU/Wr3Q8bNqbsdOFR6C6WlJLEwqiFdK3eFW8vb7fsWTSgKG2rtGW2Odst+2VHWHQYduyOzYv6/nsroTB0qPWno2w260VLhQrWi5xz5254acvAlvh5++WauVFzzbkUz1f870HPf3vySauy6ZdfwD+TP5j372+17cXFQbNm/6iw6Fu7L5cSLrF4/2InRO9ap6+c5o8jf9C1etf/Z++845o6vzD+JGxkLxGRoUKYbqsVFVDqAhXFCdpa2zpatUu7HFVbrT9Hh1btcNQqWgciiFbFUpC6Ki522FNREATZkNzfH8coKiMJWdj7/Xz8qMl73/cQbpJ7z3ue59DPc+ECGVZL+nrIEJFp8qn0U1QVevgwwOcD/fsDsVIkQBmGpJXdutHvXKJDGURlR5FXmow7x8kSW0NbWBtYd5gEcVN2XNuBvPI8bBi5QSpPLiNtI3zp+SWisqPonBEHDQ36jDx1iiqklEzS/SQ8qHkAL1uvtgdfvEjVri4uVNnZloeXmholz52dgalT6b0kAboauvC081SqiTm/hI/00nT4OSimcloWeNt545+8f1Sq82wYPwxVDVVykegBtBnjYePBJqNYZAabjGJhYWGREceSj0Gdq46JTk2qMzZtopu/bdtIltcaNjZUJRUfT0bLj+lq0BVedl44mHhQ/F1hFeNy/mWU1pQq/ELT38kfaQ/SkFqSqtB1JSUyKxKGWoYYYDWg9YEnTlCFk58fJaUkvXk2MqKkaEEBydZaOJ90NXQxpNuQDuEb1ShsxKn0U/B18IU6V/3pE0eO0M/65ZdUlSgNr7xCnlzdu1OS+HHljredN0x0TDqEVO981nkwYCgBtHYtYGlJCXEl0lmvMwZaDcTp9NP0gJ8fVesZGpIvzo4dLZ6bzRISQmboa9YA2toSxZL2IA13K+9ihJ3qSvQAamgxzIbMgzvS90B5bTnWxa7DqB6jMLK79MbUCwYsgKOpI5ZFLhPfNPrtt2kjSAWMzKNzogFQFVKr3LxJ5vLW1lQdZWTU+ngRBgbAyZOUhPPzoy6rEjCmxxiklqQi52GORMfJClGnXZnL+EUm/WFhkn2miIGXnReqGqoQdydOpvO2h+CEYHQz6IZhtsPktsZwm+FIuJ+A0ppSua3B8t+BTUaxsLCwyACRRG+E/QiY6DyWAl2/Tp2dpkwR3yh47FiSmezeTZ41jwl0D0TagzSVNMsUh4i0CKhz1TG652iFrjuBNwEAcCJVdaujGIZBZFYkvO29n02mPM8//1AF3cCBlGRRb2VsawweDKxbBxw71qrHiI+9D24V3UJJdYl06yiIi3kXUVpT+qxE7+5dki++8gpVzLSHbt2A0FCqcvz4YwDkeyTqqlfbWNu++eXM2cyzMNY2xsDsepKyffIJeWMpmXEO43Cl4MrT88vFhRJ/o0dTddNbb1FVWmskJJDcMCiIjpfCkD0qOwoAeYGpOsNshuHOozvIfpit7FDEZtOlTSitKcWGkRvaNY+GmgY2+mxEakkqfr3+q3gHde9Ofku7dtH7V4nE5MbA1tC29U6yfD6d/wYG1GTBwkKyRezs6LMqL4+uO+rrxT5UVK14NkM51Z4R6RFwt3AX30+rLRobgW++oWrL4GDA3x8YNYqSUzLiiW+Uikj1iquKcTbjLALdA+XaFVSU6OqIkmEW1YNNRrGwsLDIgPh78cgozUCAcwA9UF1NN0idO0tewbJmDXlDLFxIN1sAApwDoMHVwMGEjmlkHpEeAU9bTxhoGSh0XWsDawywGoAwvur6RmWVZSHnYU7rflGpqeSpY2NDpuXtbb2+dCl1lfvwQ+D27WaHiKoYRDfrqkoYPwyaapoY1WMUPcAwVPVVXU0JXWmTdk2xtyevrSNHnniyTHWZikf1j5R28yYODMPgXOY5+HT3gdq69XRzO3++ssMCQL5RDJhnXz8jIyA8nJL4e/cCw4e/6CPFMMDZs3Rj2asX/U7eeYdklGqSS4CjcqLQzaAbehj3aOdPJH86mm/U3Ud38e3lbzHTbSb6dpGyOrEJE3gT4GnriS+jv0RFXYV4B82bR8mZc+favb60CBkhYnLb8IvKzaXEGYdDnzHSGsp7eNBmVnQ0VdGKWQ3kZOYEG0MbnMlUvG9UWU2ZbDvtJieTKf8XXwATJ5JMc+tW8gDs04e8tSSsHGsOM10zuFu4q0wy6kjSEQgYgdwkeiJe6foKNNU0EZvb8STDLKoHm4xiYWFhkQHHko+By+HC38mfHli6lHY59+0TzzS5Kerq5P9gaEj+D48ewVjHGOMcxuGPpD9k29pbAWSVZSG5OFlhXfSeZyJvIq4UXFHZVsSRWZEA0Lpf1AcfUPe3s2cBM7P2L8rlko+SiQkwfTpQWfnCkAFWA2CgZaDSvlEMwyCcH46R9iOhr6VPD+7ZQz4xGzYATk6yW+yTT6jSYvFioL7+SRWkKkv1kouTUfioEEHVPencWboU0NVVdlgAgP5W/WHRyeJFDyAul+SEx48DKSlPfaTq6uh36+5OidTERGD9eiA/nzpKdusmcQxCRojonGiMsB+h0n5RIlwtXGGsbdxhbgLXxqxFg7ABX3l/JZP5OBwOtozaguLqYnwT+414B02cSJtC27bJJAZpSC5ORkl1ScvJqHv3KBFVWUkVUY6O7Vtw1ixg+XJKSonRPRWg13ZMjzH4K+sv1AvEr6iSBWczZdRpVyAANm4E+vUDsrLIi+7IEaBLF/rcTk+nZPzOnYCDA31uNIop+WwBbztvXMy7qPDXrDkOJByAu4U73Du7y3UdbXVtDOo6CBfyWN8olvbDJqNYWFhY2gnDMDiafBSetp6w6GRBlSs7d5KkZ6SUHhmWliTFSk8n3wuGQaB7IO48utPhDGxFXhAy2/WUEFGC8GTaSaWs3xbns87DxtAGDiYOzQ+4fJkSCZ99RjIMWWFuTvKFtLRmTZ/VuerwsvNSad+o5OJkZJZlPpFjIieHEnfe3s/4rskEbW3aXU9NBb7//olUL5wfrrJSPZHB+qg/rgGmpuJ3XlQAXA4XY3uOxZmMM80n2CdNItmekRH5SNnYkHRPTY2S/Dk5VK0mabK/CYn3E1FSXQJvO9WX6AH0mnnYeHSI74C0B2n49cavmN9/PnqYyK7qrL9Vf8zqNQvfXfkOBRVidF/U1ASWLAH+/JP8GJWAyC+q2WRUTQ1J8+7eJbPyXr1ks+jatSTVW7aMvKTEYKzDWDyqf4TL+ZdlE4OYnEw7CXNdc7zS9RXpJ0lNBYYOpeYMvr7UAXXatGfHmJkB27cDt26Rj+DixVQpFRkp9bJedl6oaazBv4X/Sh+7DMgszcSVgityr4oSMdx2OK7fuY7K+hc3slhYJIFNRrGwsLC0k+TiZPAf8Kll9b171MGnVy/y5WkPnp40x5EjwPbt8HP0g56mXoeT6kWkRcDJzEmmNySS4Gruiu7G3VXSN0ogFCAqOwo+9j4tV2asXk0X0e++K/sAvL1JEvX77/TnOXzsfZBVloXsMtX0qBHJL8c7jiej4jlzSOaydy9V2MgaX19gwgS60cvPfyLVO5epPAlQa5zLPIfx9fbQOXOebsj1VKtluq+DL8pqy3Cl4ErzA5ydKSEVEEBeaZGRdCP5+uuUZGgnokS5WF0sVYRhNsPAf8DH/ar7yg6lVVb9vQra6tpYOXylzOde67UWdYI6/H77xc+sZlm4kKTNmzfLPBZxiM6Jbtkv6uuvSSp95Ah17ZQVXC4lbfv1I6/BpKQ2DxlhPwLqXHWFdtVrFDbiz/R2dNplGKr+6tOHNlYOHSI/xM6dWz7G3Z2kkKGhlAwcNYqax0iBp50nOODg72zlSvVE14WB7oEKWW+47XAIGIHCE5csLx9sMoqFhYWlnYSkhIADDibx/CkRVVEBHDwom9bpn3xCnXE++gi6NxMxyWkSjiUfQ11jXfvnVgAVdRWIzolWartmDocDf54//sr+C4/qHiktjua4fvc6ymrLWr4ZvnSJvE4++aT9PlEtsWoVJT7few8oLn7mKZFv1F/ZqinVC+eHY4DVAHQ16EpVSzExwPffA7YyMsFtju+/f2JmrspSvZqGGsTkxmDFVW2S5jVT/aZsXuvxGtQ4ai9K9ZpiaEhVohERTz11ZERoaigGdR0EK30rmc0pb4bZkHnwxbyLSo6kZUqqSxCSEoL5/eejs14rSQEpsTe2x1CboQhOCBavs6CxMfmKHTpE/lEKhGEYxOTGNN9FLz6eZGVz5gDjxsl+cV1d8mDT0iKJbhsYaBlgmM0whKaGKqxj46X8SyirLZNeonfwIFWhjx5NCbcZM8T7jOBwyNRc5C/1wQdAieTNOkx0TNDbsrdSfaMYhsHBxIMYbjsc3QwllytLw6vWr0KNo4YLuaxUj6V9sMkoFhYWlnZyLPkYhtoMRZfgMCqz37gRcHWVzeSi3U0rK2DqVMy2m4iy2rIn8htVJzIzEg3CBoznKUeiJ2Ki00TUC+pxJkPx5qytcT6LJHAj7FtoK796Ncnp5FEVJUJNjbrqVVeTz1ITnM2c0UWvi0omo+4+uourhVepi15qKkm2/Pyou5o8sbcnY9yjR6Hxdwz8ef4I54erXII4Ni8WZg9qMSAmjW7ETU2VHdILGGkbYZjtMITzwxW+dn55PuLuxGGS0ySFr90e+lv1h7a6tkpL9Y4mHUWjsBGv95a8u6G4BLoFIrk4GQn3E8Q74MMPqYrm++/lFlNzPPGLsvV69gmBgN6XxsbyrdiysiLp2pkz1JG1DWa4zVBo596ItAhocDWeNqCQhLIy4KOPqGvq8eNkbyApWlrUZKa8nCSNUuBt543LBZeVJte+VXQLqSWpCHRTTFUUAOhr6aNvl76sbxRLu2GTUSwsLCztgF/CR8L9BMw19Hq6O7dokWwXMTF5sqM7IiIJ5rrmHUaqdzLtJIy1jTGk2xClxjGk2xCY6ZrhBF+1pHqRWZHoY9mHvMae5+JFkiXJsypKhJMTMHs2sGMHdR56DIfDwcjuI/FX1l8QMkL5xiAhIonVRN5E8v7Q1QV+/VWmlTMtsmwZ0KMHsGgRpjn4o6KuQuWkeucyz2HpVS44DOiGTUWZ4jwFScVJSLrftoxIlohku5OcO1YySlNNE4O6DlLpZNSBhANwNXdFr84y8j9qhqmuU6HOVUdwfLB4B9jYkFztl18oiaEgWvSL2r6dJKjffy//RPGiRZSo+eKLNrvrTXGZAg2uBoITxHxd28nJtJPwtJOy0+7nn1M1008/SdVJ8wlubvSZ/ttvwN+SVzh52XmhtrEWVwuuSh9DOziUeAjqXHWyilAgw22G42rBVZXbiGHpWLDJKBYWFpZ2EJISAgAIiCykriy7dsnHq+bVVwFfX6j9sBWzulMlhqpJzp5HIBTgdPppjHUYC3WuulJjUeeqw8/RD6fSTqFB0KDUWERU1VfhUv4l+Nj7ND9gzRrAwkJxptNffkm79c95nfnY+6C4uhiJ9xMVE4eYhPHDYGdkB7fkEvL/WLFCup1xadDWBn74AeDz4ROWAGNtY5WT6l2OP4V51zngzJwpfZt4BTDFZQq4HC4OJx1W6LqhqaFwNnOGo2k7O5cpgWE2w3Dz7k2VNA/OLsvGpfxLCHIPkmuHQjNdM4zuMRqHEg+JnyhftgyoqqIGIwoiOjcaNoY2z/pF5eVRYmjMGEqQyRtdXfp8jI0l2XcrmOiYUOfeRPl37s0ozUBqSap0zU0uX6aKpvffJzPy9rJyJXVLXbAAqJWswmm47XBwOVylSPWEjBB/JP6BUT1GwVRXsdWvw22Ho05Qh2t3ril0XZaXCzYZxcLCwtIOjiUfg7fZQOgfPAZMnQpYW8tvsRUrgAcPsPiGBmoaa56YN6sq1+5cQ3F1sVL9opriz/NHeV05YnJjlB0KAJJR1Qvqm/eLUmRVlAh7e+rc+OuvQPZTw/InvlFZqiPVq6qvwvms85joOAGclStJirJggWKD8PUFJk6E2rr1eNPUB2H8MJXZIS6sKIT36VTo1AnoHFJhOut1hpedFw4nHVaYT82D6ge4kHuhw0n0RAyzHaay5sGKNFIOdA9EfkW++P5ZvXpRAuiHHyROOEgDwzCIyYmBl53X08Qcw5B/G8NQUkwRlZwASQJtbek6oo33WZB7EO5W3pV7ckVU3SqxX1RDA33eW1vTpo0s0NGhCqu0NOCbbyQ61EjbCH0t+yolGXUp/xLyK/Ix000BSc3nGGozFABY3yiWdsEmo1hYWFikJLM0EzeLbuLzXBsyLZe3QfDgwYCPD+x2h8BRp5vKS/VO8k9CjaOGMT3HSD8JwwD//AO7VavIF+L8eamneq3Ha9BR10FYqmok8c5nnYeWmtYTQ+JnWL2aqqIUnWBZvhxQV3/mAt/awBo8Ux7OZ0v/2suac5nnUCeow5x7XShxt3Il3Uwomsdm5kuP30VFXcUTDzBlE5V8CkuuAhUjh1HnKBVnhiv51NwquqWQ9SLSIiBgBB1OoidisPVgcDlc/JPXtgeQImEYBgcSDmCYzTDYGsmxicBjJvImQldDVzJJ2SefAPfvN9s9VNaklKSguLoYnrZNzMuPHiUz/q++Auzs5B7DEzQ1qfo1Lg440bpc3c/RD/qa+nKX6kWkRcDF3AXdjbtLduAPP5D5+9atgL6+7AJ67TUgKIiSUampEh3qbeeNKwVXUNNQI7t4xOBQwiFoq2uTXF3BmOqaws3CjU1GsbQLNhnFwsLCIiUhKSEAA3ieSqS2wrJsy9wSK1eCc+8eNufycC7zHIqrits+RklEpEdgqM1QGOsYS35waSldcLq5AcOGwSgmhjq9vfYaSS3qJK9A0dXQxageo3CCf0JhFRitEZkVCQ8bD+hoPJdE+ecfSrp9+qniqqJEdO1KZun79wMpKU8eHmk/EjE5MSojcQxPC4eRliF6/XiUbujmzlVOIHZ2wPLl6PLnP5iYp/tEtqts6vf8AotqQH/lV8oORSwmO0+GOlddYVK90NRQdDPohv5d+itkPVljoGWAPpZ9VM436mbRTaSWpCLIPUgh63XS7AR/J38cTT6KekG9eAd5eQEDBpBpuEC+MrQX/KLKyoAlS4D+/elvRTN7NsDjUfK+lZ9dR0MHAS4BCEkOkVtypaKuAjG5MZJXTuflUVJt/Hjqhidrvv0W0NMD5s8HhOL7JHrZeaFeUK/QBHGjsBFHk49ivON46GvJMCknAcNthuNi/kU0ChuVsj5Lx4dNRrGwsLBIycm0k5hb5QjNZD5VRSmi3H74cGD4cIwOjYdag0ApXajEIa88D/H34iUrv2cY8rSYPZtkVx98QBeFu3cj/swZatu8cCHdRAwe/EyyRFwm8iaioKJAYZ2CWuJe5T3E34vHa92bkegpqypKxGefkcfI6tVPHvLp7oOqhipcLVSOQWtTBEIBItIi8GVpL3Cv36A4NTWVF9DSpUCPHthxVh2nkk8oPWEnqK/DiJCbyHA0A2f4cKXGIi6muqbw6e6jEKleVX0Vzmaehb+Tv1w9jeTNMJthuFJwRfwkjAIIjg+GBlcDU12nKmzNQLdAlNaU4myGmB1mORza0EhPB8Ll+/0ZnRONbgbdYG9kTw988gkZbv/6K1WgKhpR1WtSEvDHH60ODXQLxKP6RziVfkouoZzNOItGYaPknXYXL6a/t22TzzWXhQWwaRNw4QIZmouJt703Oml0Uqh34F9Zf6G4ulgpEj0Rw2yHobK+UmFVrSwvH2wyioWFhUUKqhuqcbXgKhZf4wJGRkCg4lrqYsUKaN69j4/5pirXHU6ExF4QN24Arq6UbAsPB956C7h5E7h6FZg7F0IdHUqQ7NhBzxcUAP36keeGBDevfo5+4HK4Svfb+iub/Jd8uj9nXh4bC/z1F1VF6eoqITIA5uaUCDxyBLhFF5hedl7gcrgq4Rt1ueAySitL8GZoNu3yBymmCqNFtLWB77+HVWEFZsaUKd2TLGf3FtiXCnFn4SzF+dHIgBmuM5DzMAf/Fv4r13XOZp5FbWNth/WLEjHMZhhqGmuUnlgXIRAKcCjxEMY6jIWJjonC1h3VYxRMdUxxMFEC2frkyWRW/b//SfT9IQkMwyAmt4lfVEwMNTj56CPZGG5Ly9SpQO/eVF3U0HLifIT9CFjqWcpNqheRHgETHRMMth4s/kFhYfT9v3o1+V/JizffBIYNo42G+/fFOkRXQxeTnCfhWPIxhXkHHko8BAMtA4x1GNu+iaSoNBchshmIzVWtKk2WjgObjGJhYWGRgisFV2Ba3oBeF9PpwkWRiQMfH2DQIHx8oQF/p51TyY5KEWkR6GnSEzxTXtuDS0vp5qCiAtizB7hzh9pe9+nT/Pjx44GEBMDTkyRlEyaIfcFo3skcHt08EJoaKsFPI3sisyJhomOCvpbP3ZSsXg107qy8qigRH39MSdaVKwEAxjrG6N+lv0r4RoWlhmFWkhoMMwqAtWuVU2HwPL6+EIzyweoY4Mzl/cqLg2HQ6bsfkWoKOL31qfLikAJ/J39oqmnKXaoXmhoKEx0TDLNtxqutAyGKXxUSxABVAd2tvKswiZ4IDTUNTHOdhrDUMPG/C9XV6TPu6lWSRcuB1JJU3K+6TxK92lpg3jxKgDWpOFUKXC7w9ddAZmarlT9qXDXMcJ2B0+mnUVZTJtMQnnTa7SlBp93KSqqKcnenzRJ5wuVSp77KSjpPxCTQLRBltWU4mylmlV47qG2sRWhqKCY7T4a2urZ0kyQm0rWXnh5w6JBUU3Q16Ioexj1wIY/1jWKRDjYZxcLCwiIFMTkxmHeDA26jgKRjioTDAVauhOm9Cky5WY9zma23alY0lfWViMqOgp+DX9syGIahZN6dO8Dx4/RvcXySLC2B06fJVyoykroknTkjVnxTXKYg8X4iUooll/nJAoZhcD7rPEbYj4AaV+3pExcuAFFRyq2KEmFkRFKWiAjgyhUA5Bt1peCKUpOfDMPgVPIJrP9Hi3b3p0xRWizPwOFA7fut0K/nwP3HI3Jvid4i58/DMv0ujoyzgYW+pXJikBJDbUOM6TkGR5KOQMiI79UiCQ2CBkSkRWC843jxb4JVFItOFhhoNVBuMipJOZBwAPqa+hjvKKHsSgYEugeiprEGJ1IlqBSeMwcwMwM2bpRLTCK/KE9bT0r+pKVRtzZlf7YD1Al08GBK5rfSVTCoVxDqBfU4lnxMpstfLbyKkuoSyc6VL78E8vPpNdTQkGk8zeLsTJL1AwfoGkMMfLr7wEzXTO7G7wBwOv00KuoqEOgmRVV+WhpV8/fqRZXYPB69Hy5Il1AabjscsbmxcvvcZnm5YZNRLCwsLFIQmxmF926qA6NHAw4Oig9g3DgwfftgxUUuwpOVW+XzPJGZkagT1GECb0Lbg7/9lsruN2+mbnmSwOWSCey1ayQt8/WlzmptEOAcAA44CvV2aAr/AR8FFQUv+kWtWUNJNmVXRYlYsoT8M5YvB0AX2o3CRqV2zuE/4GNIVAa63qumblRcFbqMcXZG5szRmHW1FrfO7lNKCI0b1uOOPtAwc7pS1m8vM1xnoPBRIS7mtf0+loaY3Bg8rH3Y4SV6InwdfHGl4IrSG1nUNNQgJDkEAS4BLzZkUABDug2BjaGNZB1mdXWp0iYigjyUZEx0bjSsDazRPbGQ5ICzZ1MDDlWAwwHWrSO5+08/tTisf5f+cDR1lHly5ST/JNS56hjdc7R4B9y6RRtP77wDDBki01ha5Ysv6Ppu4UKgpm0jUtpxQQAAIABJREFUdw01DUx3nY5wfjge1T2Sa2iHEg/BopMFvO29xT8oJ4csEFxcSPL42WdAdjbZA/ToAUycKJUX5zCbYXhQ8wCpJZJ1IGRhAdhkFAsLC4vE1DbWovP5K7B42EDG5cqAwwFnxUr0LBFC41ioSnUyCU8Lh5G2EYbaDG194KVLVAUUEPDUlFQa3N1pLhsbqqyqrm51eFeDrhhqM1RhnbueJzKTdlmf8YuKjX1aFaWj+Ju5ZtHTAz7/nOKKioKHjQd0NXSf+IEpg4j4EKyKAer79wH8JOzCpAC6bP4ZZTqAwWer5OZF0yLXr0M9KhrfDwJGOo9T7NoyYjxvPHTUdeT23gxNCX3SVfNlwM/RDwwYnMkQrypUXkSkReBR/SOFS/REcDlczHSbKXmH2ffeo6TU5s0yjYdhGETnRGOS/ivgTJ0K2NuT4bYqMWIE/Vm/nuRozcDhcBDkHoSY3Bjkl+fLbOmI9AgMsxkGI22jtgcLhbRBY2ICbNggsxjEQlubknWZmcDWrWIdEuge+ERCJy8q6ioQkRaBaS7TxKvwvHOHznVHRyA4mK63srLod29iAhgbU6W5lhYwbhxw755E8fTtQnYDSfdln9Rleflhk1EsLCwsEnK14CrmXW1EtZUFfXErC39/lDvY4IO/qhCbrVzTZBGiTmfjHMZBQ62VUvqSEmD6dDIh3b27/UbL+vo0T3o6sGJFm8Onu05HcnGyUi6ezmefR3fj7uhu3P3pg19/TV5R8+crPJ5WWbAA6NoVWLEC2mpaGOcwDqGpoUorx1fbvRs2FYDmhk0qac6tb2mDozPc4RBfCGGIbKUtbbJxI2p0NRE8pBOGdFNg9YAM0dPUg6+jL44mH5V5gl3ICHGCfwJjeo5RSvWOPOjbpS+66HVBRLryEsQAEJwQjC56XeBtJ0GVhowJcg+CgBHgSNIR8Q8yNaVKkeBgqhKSEaklqXhYfh8rfrhFmyMnTgCGhjKbX2asWwcUF7eaaAl0JxnYH4mtd98Tl5yHOUi8nyh+c5ODB8nba/NmSpwomhEjgLFjSc5ZUdHm8FetX4WdkZ1kVXoSEpYahtrGWsx0F6OL3qVLQM+ewC+/0LmekQF89x1dbzTFzo6qBO/fB/z8wBWjEkyEo6kjOOAgpUQ51gcsHRs2GcXCwsIiIcnRR+GdAyrdVlNra7j84HKhtWoNXIuB7L3fKi+OJoi8ICY4tiLREwqB11+ni56jR2V3kT5iBP1Ovv++TVPaABeS6kl04yIDGgQN+Dv772cletevA+fOUZclVamKEqGtTSbmly8Dp08jwDkARZVFuJx/WeGh3LuXhZlh2cjpbQeMHKnw9cVF790PEW8B1H/0fqt+LDIlMxM4dgy/v6qL/k4joKmmqZh15cAM1xm4X3UfMTmyTbBfK7yGO4/uvDQSPYAqgsY5jMPZjLNoELTcGU2elNaU4nT6acx0m/msB56Cce/sDjcLN8m66gH0uSsUAosWAQLZeL3F5MZg65+ARWIWmYS7uMhkXpkzeDA1BNm0CXj4sNkhPU164pWur8hMqieqrBXLL6q2ljaX+vYFZs2SyfpSsXYtNVr54Yc2h3I4HAS6BSIyKxL3KiWrMBKXQ4mHYGtoi1etX219YFUVXWtZWgJ8PnUftrZuefyAAcDhw8CNG7D/4gugUbwNAV0NXdga2bIyPRapYJNRLCwsLBJideAE6tQ50F2wSNmhQHvmbBR06YRBv0WCESrfPDKcHw51rjrG9BzT8qCNG4E//6TduX79ZBvAxo1UbdWGXM9SzxKedp44knwEjALlVJcLLuNR/aNnJXrffEOG4ariFfU8c+dSF6jlyzGu+2hoqmkiJCVE4WHkrf8UllVAw5pVKlkVJcLPxR8fj+NCO/8ueaIpgvXrwairYXWfhx1egjbOYRz0NPVkLtULTQ2FOlcdvg6+Mp1X2fg5+qG8rhwX8+Xjs9UWR5OOokHYgKBeypHoNSXQLRCX8i8huyxb/IPs7IAtW8hD5913ZSKv5e7ajfnXAUYkQ1dlvvqKElGbNrU4JMg9CLfv3ZZJJfHJtJNwNHWEg6kYXps7dwK5ueS5pUx/wAEDyE9pyxagrO3OgkG9giBkhHLZ7CqpLkFkViRmuM1ou0HMZ5/RRsXevfQdLg5+fsC2bTCKjQXef1/s94OTmRNbGcUiFWwyioWFhUUC6kqLMSK2ELc9nagTj7JRU0Pm/GlwLWxAdvB2ZUeDcH44PG09YajdQrVTbCztdE6fLp8uhHp6dOGVkfHEeLslprlMQ2pJKhLvJ8o+jhY4mHAQuhq6T5N1qanURfC99wADA4XFIREaGiTnuH0bBvuPYFSPUTieclyhSTyUl4O3JwzRTtroOWGO4taVAmMdY6iNfA1ne+mCWb+e/DrkSWQksGcPbk8djiJ9YHQPMU2BVRQdDR1M4E1ASEqIzKp9GIZBaGoovOy8YKxjLJM5VQWf7j7QVNPEqTTldNULTgiGk5kT+lr2Vcr6TRHJlg4lStim/v336cb9l1+okUQ7EF65jDd2xSG+tyU469a1ay6F0Ls3MHMmVRQXFTU7ZLrrdKhx1NpdHfWo7hGic6LFq4oqLyf5+muvqYbx+9q1FJMYGwwu5i7o3bm3XLrqHUs+hkZhI2a6tSHR++sv4Mcf6dz29JRskXffRdHs2cCOHZSAEwNnM2fwS/hsRz0WiWGTUSwsLCwSULD9G+jXA9XvzFF2KE9wfv8rZBkBmuv/p3jT5CakP0hHSklKy1307t8HZsygHbpffpFfdYuXFyV3fviBkl8tMNl5MrgcrsKkevWCehxNPgp/J3/oaerRg//7H0nh3n9fITFIzfTpdEH7xRcI7DIaueW5uHH3hsKWr1y/BgaVDUhaLMZusAoQ4ByAhV7VYBrqyQReXjx8SFWAzs5YN0oH9kb26GnSU37rKYjprtNRWlOK81nnZTJfakkq0h6kvVQSPRF6mnrwsvNSim9U7sNcxObFIsg9SCXel3ZGdvDo5oHghGDJk+Xr19N7ac0aqsiRhqIiNEyaiEJ9IO3HNcqV8UvC2rVAfT0lf5qhs15n+HT3wcGEg+1KNqyLXYd6QT2muExpe/DGjSSNU7RpeUv06gVMnUpJu5KSNocHugfiauFVZJZmyjSMQ4mH4GzmjF6de7U8qKKCKpodHem8loLCxYuBadOAZcuAI21fIzmZOaGmsUamRvcs/w3YZBQLCwuLuDAMDHYfwDUrwG38XGVH8wQLo644OqEHrFMLgbNnlRbHybSTAFrwghAIyPOhtJR8ouRdBbRhA8kv3nyTfBOaobNeZ3jbeeNw0mGFVPmcyTiD0prSpx2n8vKAAweoXbW5udzXbxccDu2ylpdj0v5rUOOoKU6ql5IC7e+24qAb4D11mWLWbCf+Tv7INeXin4CBwO+/kwGvPFiyBCgqQuPePThbGINRPUapRFKgvYzuMRqGWoYyk+qJOltN5E2UyXyqhq+DL1JLUmV+49sWIpNmkcm1KhDoHojk4mQk3E+Q7EAOhzZJ/PxoM+OYhA0IGhqAadPAKSvDtEB1jBo4Q7LjlUnPnmRu/csv1GWtGYLcg5BbnotL+ZekWuJa4TVsurQJb/V9C4OtB7c+uLCQZPwzZ8peyt8eVq+m64lWJI0iRJVLsjQyL6goQGxuLGa6zWz9c/6jj8iQf98+6hYpDVwuHT90KDB7NlWbt4KzmTMAsFI9Folhk1EsLCws4hIdDfPcYpzw6QozXRWQ6DVBY+7byDYC6r74VGnVUeH8cLhbuMPe2P7FJ7duJTnR1q0kC5A3enrAnj3kl/DFFy0Om+Y6Deml6bh977bcQwpOCIaZrtlT83JRO/GPP5b72jLBzQ1YvBjae/djPtMfISkh8k/iCYXA/Pmo1gD2vuEOF3MVNQJ+DvNO5vC09cRH/UvIPPb99+lnkSWhocD+/cCKFbhkWY9H9Y86vERPhJa6FiY5T0JoaijqGuvaPV9oaigGdR2ErgZdZRCd6iHywTqVrjipHsMwCE4IxpBuQ57tDKpkprpMJUlZvBQSKXV1MnB+9VUgKAj4+2/xj/34YyA2FkunGsHSYzQMtFRUdt0Sq1ZRJdeXXzb7tL+TP3TUdaR6XesF9ZgbPheWepbYPGpz2wesWUPm2S1UaikNFxcgMBDYtq1FSaOIbobdMNx2uHRVei1wOPEwGDCtd9E7fZo6Cy9bRgb17UFbGzh0iBKth1qXvjqZOQEAa2LOIjFsMoqFhYVFTIQ/bkOJLlA9SQy/AwUz3i0AXw0HtG7GAydPKnz9B9UP8E/eP81L9AoK6EJ33Djg7bcVF5SXF3VI2roVuHCh2SGTnCZBjaMmd6leRV0FwvnhmO46HRpqGtROe9cu2nG0sZHr2jJl9WrAwgKrjt5HenEakouT5bvenj1AbCw+9BHAd6jqVCOKQ4BzAK5XpqHwi8VUGXVQhq2+798H5s8H+vcHli/HucxzUOOoYYT9CNmtoWSmu05HRV0FzmScadc8+eX5iLsTB38nfxlFpnr0MOkBJzOnJ53KFEH8vXgkFSc9rfRUEcw7mWN0z9E4lHhIOkmZri59h/bsSabVN2+2Pp5hyKdw2zbceycQ23qWIMBZxU3Lm8PKiiotg4OBhBeryvS19DHRaSKOJB9BvaBeoqnXx65H4v1E/Oz3M4y0jVofnJpKyZSFC8U33VYkX35JkkYx5INB7kHgP+DjVtEtmSx9KPEQBlgNaFmKXVpK11iuru32PnuCtTXg4dFmpaCZrhlMdEzYZBSLxLDJKBYWFhZxKCwEJywcu/sCHo6q11bewdQBcT7OKOisQ4kfBXfW+zPjTwgYQfPJqI8+ol3ObdsU3wVtwwa6oG1BrmfeyRwj7EfgSJJ8u+qFpoSitrH26Y3bDz9Q2+pPP5XbmnLB0BDYtAmdk3Lw1k3IV6pXVAQsW4asXjbY14/btmGrijHJmfyJ9rg1AAMH0o3eDRn4bDEMMG8e+YL8/jugoYEzGWcw2Hpwy40DOiAj7UfCVMe03VK9E6knAOCl9Itqip+DH2JyY/Co7pFC1gtOCIY6Vx3TXKcpZD1JCHIPQn5FPqJzoqWbwMSEJO9GRsDYsc9K12prgUuXqLJ18mSgSxfy5/HywrYp3aDGUWvZN1HV+fRTktCvWNHs00HuQSitKcW5zHNiT3m76DbWxa5DkHsQ/Bz92j7g88+BTp1ajEHpODgAr78O/PQTbbS1whSXKdDgasjEyDz9QTqu373e+vfgkiW00fX774CWVrvXfMKUKUB8PJCW1uIQDocDZzNnVqbHIjFsMoqFhYVFHPbuBUcgwM/9geG2w5UdTbP4ufjjC49a4PZtkvAokHB+OCz1LDHAasCzT5w9Sx5Ry5crZ5ezUyeqrsnKatFIerrrdGSWZeJmURs74O0gOCEY3Y27k1dGRQX5L02eDPB4cltTbsyaBQwdik1/qyMyTjaePs3ywQdgqqvxlm8DRvUcjc56neW3lhyw0rfCkG5DEMIPJQNYAwPAx6f9Canff6c29OvWAS4uiL8Xj+t3r2Oy82TZBK4iaKhpIMA5AOH8cFQ3VEs9T2hqKJzNnMEz64DvNQnwdfRFvaBeZqbvrVHXWIffbv0GXwdflZOsA5R4NNQyxO6bu6WfxNqavr8aGoBRo0j25OFBCXkPD/p/fDw9t3MnmLAwHE0Lhbe9N0x1TWX3wygSExPgk0+A8HBKuD3HqB6j0LlTZyw8tRDx9+LbnK5B0IA3w96EiY4JfhjzQ9vrX7oEnDhBMaiyj+LKleSD2YY5uImOCcY6jMWhxEMQCAXtWnLf7X3ggIPprtObH3D8OFW1LV8ue5+tyY+/W0Ja33xyMnNiK6NYJIZNRrGwsLC0hVAI7NmDWy4m0HZ0hkUnC2VH1Cz+Tv4IdmNQbm9FpeSC9l38iEu9oB5nMs5gvON4cDlNvlZqa0km5+hIF+7KwtMTWLyYKrMuXnzhaX8nf6hz1XE4UT6JlaLKIvyV/RcC3QLJdHTnTmoRLc8ua/LksZm5QbUAM/9IRkZp68amUnH6NHD4MHLeC0K01l3M7jVb9msogADnANy+dxuZBgIgOrr9Cam8PNr9HjYM+OADAMDOazuhra6NOX3myCxuVWG623RUNVThVJp0Xkg5D3NwIffCS18VBQAe3TxgqGWoEN+okJQQFFcX492B78p9LWnQ0dBBkHsQQpJDUFZTJv1Ezs5ARARw7x7JvQF6/x0/Dty9S6bOv/8OLFiApNo8pD1Iw2SnDp4Ufv99oHNn8lp8rlpYU00TZ2adgZARYuieoW1KaDdf2oybRTexY9yOthN0DEOVWZaWwIcftvenkC/29mT4vmsXkJvb6tBAt0DceXQHF3KbtwoQh5TiFGy+tBkBLgHN+94VFwMLFgB9+1IyStZ06wYMGtSmVM/JzAn3q+6jtKZU9jGwvLSwySgWFhaWtoiOBrKzsdWtCl52XsqOpkUGWA2ApaEVdk+wBpKSxGrHKwticmLwqP7Ri9KE//2PLta3b5dtybg0rF9P3kzz5pHfQxNMdU3h090HR5LlI9X7I/EPCBkhgnoFATU11CVo1Cjy++mo9O6NyrffwII44OKJbbKdu7ISePddwMUF3wwRQl+TvEo6IqJqpZCUEOruGB1NlRUjRwLXr0s2mVBIciCBAPjtN0BNDRV1Fdgfvx8z3GbARMdE1uErHU9bT3TR64KvLnyFiroKiY6trK/ExD8mQk9TD2/1e0tOEaoOGmoaGN1zNE6ln5LOK0kCdlzbgR7GPeDT3Ueu67SHt/u9jTpBXfslUq++SsmoigrazNi0CZg0iZImTQhJDgEHnCfy3A5Lp05U+RMTA5x7UY7Xx7IPrr59Fd2Nu8PvoB9+jvu52WlSilOwOmY1prhMQYCLGB5aJ08C//xDvoSdOrXzh1AAy5fTxsxXX7U6bDxvPPQ09aTuqicQCvBm2JvopNkJP4798cUBDEOJqPLyJ7JtuTBlCm2iZGe3OETUUY+tjmKRBIUlo3g8niOPx7vM4/HSHv/t0MwYNR6Pt53H42XyeLwMHo/3dpPnLHg83ikejxfP4/FSeTzeDh6Pp66o+FlYWP7D7NmDRkN9HHKog6etp7KjaREuh4sJjhPwpVkihG5udFHX2Cj3dcP54dBR18FI+yZeWhkZwDffADNmUCWIstHTA3bsAJKTgY0bX3h6mss05DzMQdydOJkvHZwQjH5d+lG3mb176camo1ZFNcHgf9+hTF8d/dbtlq1H2ZdfArm5qNuxDYczQhHgEgBdDSnbUysZOyM79O/S/6m3lp0ddegyMqL3RZwE59uOHcBffwHffvtE8rr/9n5UNVTh3QGqWaHSXtS4atjnvw8pJSmYcmQKGgQNYh0nZISYc2IOEu8n4lDAIZXq9iZP/Bz8UFRZhJt35Sc5jr8Xj4v5F7FwwMJnK2FVjL5d+qKvZV/surGr/ZsMurptbqgcTz0ODxsPWOpZtjquQ/DOO1T98/nnzX62WxtYI/bNWIzuORoLTi3AsnPLnkmACoQCzA2fC31N/eYTKM/T2EhrOTpSwr0j0K0bNZH47Te63mkBXQ1dTHKahGMpx6TqDLrl8hZcLbyKH8f+2LxU/fBhqtRbs4Y63sqLgMcJxVakemxHPRZpUOS3yE8AtvP5fEcA2wE0l0oPAtATgAOAVwGs5vF4do+f+wJACp/P7wXAHUB/AB28FpaFhUXlefgQCAlBwgg31GoAnnaqm4wCSHJWKajGjQUTyGxSlh28moFhGISnhWNUj1HQ0dARPUjyPE1NYMsWua4vEb6+wLRp1C76OSNOfyd/aHA1ZN5Vj1/CR9ydODIub2igXfVXXyXpYEfHyAiXF02Ee1YVSnd+J5s5r18Hvv8eWLAAJ0yLUVFX0WEleiICnAPwb+G/yC/PpwdEFVJGRsBrr4mXkEpNJR+VsWPpRhH03tsZtxP9u/THwK4D5Ra/snmtx2v4dfyviMyKxDsn3xErsbA2Zi1CUkKw0WcjxjqMVUCUqsGYnmPAAUeuXfU6kiz07X5v4/a927hxVwaNA1ohozQD8ffiO2YXvebQ1KTkxs2bLUqz9LX0ETYjDO8NfA+bL2/G1KNTn3i7bb26FVcKrmDr2K3ief39/jttFK1fL7/KHnnw+ecU79q1rQ4LdA/Ew9qH+DPjT4mmTylOwaq/V2GS0yTMcJvx4oD79+laa+BAYOlSieaWGHt7quZuRapnZ2QHLTUtpBSzJuYs4qOQZBSPx7MA0A/AoccPHQLQj8fjPe9ONx3Ar3w+X8jn84sBnAAw9fFzDAB9Ho/HBaAFQBNAodyDZ2Fh+W9z8CBQW4vf+qvB0dRR5Xc9vey8oK+pj5+t75GJ5Zo1lASRE/H34pFXnvesRC8khIxfv/6a2kWrEj/8AGhrU1l7k5taYx1jjOoxSuZSveCEYHA5XLqQ/OMPICeHLmAV3VVQTjh++DUuWQPaK1cDZe3wZgFod/yddwALC+Cbb7A/fj+sDaxVWhorDiKJyvGU408ftLWlhJSxcfMJqbt3SWa7aBHQuzfg4kLn7a5dT86d2LxYJBUnqaxvjyyZ02cOVnuuxr7b+7AmpvWW5ceSj2FNzBq80fsNfPTqRwqKUDUw72SOwdaD5eYb1VQW2hFMugPdA6Gtrt0+I3MxCEmmapGXqolAYCBV2qxY0eI1hDpXHdvGbsP3o79HaEoovPd542LeRSyPWo7xjuPF64D66BF1AB406KlRdkehSxfgvffIODwpqcVhPt19YK5rLpFktFHYiDlhc6CnqYedvjvJb/J5Fi2i12/vXkBdAWKhgADg6lUgP7/Zp9W4dJ2c+oCtjGIRH0VVRnUDUMjn8wUA8PjvO48fb4oNgKZOcHlNxnwFwBHAXQBFAM7y+fwXnWhZWFhYZMmePWB698Zv3NvwsvVSdjRtoqWuhXEO4xCefhKC1V9SF7l9++S2Xjg/HBxw4OvgSw88ekTGyn36kO+PqmFpSV5Wf//9wusyzXUa8srz8G/hvzJZimEYBCcEY4T9CFh1sgQ2bKCLe19fmcyvCjiaO+HbWd2h9bCyWcNbidi6lXbit23DfQ0yxQ90C1RpKZA4OJo6ws3C7alUT0TThJSPD1WEzZ1LrcOtrIDp00kC0rkzJZUvX34mubszbieMtI2a3zF/CVnluQpz+8zFmpg12HNzT7NjbhXdwhsn3sBg68H4ye+n5m/gXnL8HP1w7c41FFUWyXzujiYLNdI2whSXKQhOCG5XR8a2CEkJwUCrgbAxtJHbGgpHTY06dqan0+dQC3A4HLw/+H2ETg9F4v1EDN07FJpqmi0nUJrCMPSZd/cuyY874vv1s8/oM/ytt1psGqPOVcd01+k4yT+JrLIssabdcmkL/i38Fz+Oa0GeFxJCnYpXrQJcXdvzE4iPSKp3/HiLQ5zMnNjKKBaJ6EieS1MBxAMYCUAfwJ88Hm8Kn89v3dq/CYmJifKKrcNxXVLjVBYWMXmZzi2dtDS4XL+OuEWvo6L+NmwYmw7x87lruuNw1WHs0yrGNDc3aKxciSRXVzCamjJf64+bf8Dd2B0F/AIUoADW330Hizt3wP/6a1Tdvi3TtWT22vfrB17v3tD+4AMkWVuj0dgYAGDTYAMNrga2Rm3FR67tr6hIKEtAVlkWZtvMRubmzeiRnIysr79G2U35+bkoAxP3kdj+ShaW/PQTytLTkfvFFxAYGko0h+adO3BZvhyPhg1Dpp0d/vhzEwSMAP3U+ynkPSfvNTyMPPBL2i84/Pdh9DTo+cxzGtu2gTd/PrQ+/BCNhoao7NMHj/z8UNm3L6p5vKc73pWVT0zPS2pLcCzpGKbaTUVK/H/nwn+e1TwkFyZj3sl5qC6qxqsWrz557kHdA7we+zr01fSx2mk1km63XKmgSBT9nWHfaA8A2Hl+JyZ0m9DGaPFhGAbfxn4LF0MXcIu4uF6k+t+FADBUdygO1B3A5tOb4Wst+42AopoiXLtzDYucFinl+kCua1pZgderFzRXrECiiwsYbe0Wh1rDGj8P+hlrb6/FnJ5zUJRehCK0nhDtvH8/rI8dQ8GSJbinpSV5UwcVwfijj9B9+XIUfPQR7r3+erNjhusOx17OXvTa0QufuX2GsdYty4ezHmVhZexKeFt6o2dtzxd+x2oPH8J13jw08HhI8fGR2+vW3Lnl7OAAwW+/IW3o0GaPMWowQnZZNi79ewlaakpuXMPSMWAYRu5/HB0dLRwdHR86OjqqPf6/2uP/mz837pSjo+OUJv//0dHRcdnjfyc6Ojq+0uS5Tx0dHbeLs35cXJxdXFwcU1tby7AwTFxcnLJDYHlJeenOrcWLGUZTk9l+5isGq8EUlBcoOyKxeFjzkNFYq8F8cu4Thjl7lmEAhtm+XebrFJQXMFgNZv2F9fTA7dsMo6bGMPPmyXwtmZ9bSUkMo6HBMLNmPfPw+IPjGetvrRmBUNDuJRadWsRof63NVBRkMYylJcO4uTFMQ0O751U1bhfdZrirwFxZNIlh1NUZxsqKYSIjxTu4vp5hfvyRYczMGEZPj2Hy8hiGYZgBvwxg+vzUR45RP0URn1slVSWM0QYjZsyBMc0PqKxkmNRUhhGId959HfM1g9VgUotTZRhlx6C8tpzpvbM3o7dej7lx5wbDMAxT11jHeOz2YHS+1mGu37mu5AifoozvRKFQyFh/a81MPjxZpvNGZ0czWA1mz409Mp1X3giFQqbn1p7M8L3D5TL/d5e/Y7AaTFpJmlzmbw2FnF/R0XQNsWABwwiFsps3KophuFyGCQiQ7bzKQChkmEmTGEZLi2FSUlocll2WzXjs9mCwGsys47OY8tryF8Y0CBqYgb8MZEz/Z8oUPSpqfqLAQPquvXVLVj/BC7R4bq1dyzAcDsMUFjb79MH4gwxWg0m4lyC32FhUk9raWiYuLo6Ji4uzYyTIEymk9p3P598HcAuASDw8E8BubGcwAAAgAElEQVTNx75QTTkK4B0ej8d97CflD0BU154NYAwA8Hg8TQA+ANhSJxYWFvlQWwscOABMmoSzZdfQw7gHuhp0VXZUYmGobQgvOy+EpoaC8fEBhg6lcvvaWpmuIzLJncCbQB13Fi6kcvX162W6jlxwcaHy+gMHgMjIJw9Pd52OgooCXCm40q7pGwQNOJx0GOMd/KC/ZClQWkprKcLXQcG4W7jD3rQHVg2qAq5cAfT1yQfp44+Buha6BzEMtfJ2dyffCzc3auvdrRtSS1IRdyeuwxuXN8VU1xQrhq3AmYwzOJf5Yrt0dOoE8HgAt+3LMoFQgJ+v/4yR9iPBM+PJIVrVxkDLAKeDTsNY2xi+B32RV56Hd0+9i4v5F7F34l7069JP2SEqFQ6HZNPnMs+hXlAvs3l3xO2AsbYxprtNl9mcioDD4WBun7m4kHsB6Q/SZT5/SEoI3C3c4WD6QpPwlwNPT+DTT4GffmrTqFtsCgpIhuzoSH5HHVGe1xQOh7qdduoEvPlmi3I9OyM7RM+JxhqvNTiUcAh9fuqDy/mXnxmz5dIWXLtzrWV5Xng4eZkuX05+gopmyhT6/g4NbfZpUUc9VqrHIi6KNGJYAGAxj8dLA7D48f/B4/FO83i8AY/H7AeQBSAdwBUAa/l8vkhc+wGAYTweLwGU2EoD8KsC42dhYfkvERYGlJVBOPdNxObGwtO2Y3U/m+w8Geml6fj3zjXgq6+AO3eAn5trYio94Wnh6G7cHS7mLuR3c+kSsHEjYKr6xrYAyOPI0ZHMzKvJT2Q8bzy01LRwIP5Au6Y+n3UexdXF+DyjC/krfP21ci4cFQCHw0GAcwCisqNQ5tIduHGDEpPffgu88grwvET+xg1g5EhgwgS6qA0LA6Kinrw+B+IPgMvhimd+24FY9Moi2BvZY+m5pRAIm79ZEYdT6aeQX5H/nzAubwkrfSv8GfQnqhuq0f+X/th9czdWDFvR4RIl8sLP0Q+V9ZW4kHtBJvMVVRbheMpxzOkzB7oaujKZU5G80ecNqHHUWvQak5aiyiJczLv48nTRa4lvviFvp9WrKenSHurqKKFRU0Pfjfr6MglR6VhaAtu20YbMdy13l1XnqmOV5ypcePMCGDAYtncYvor5CgKhAMnFyVgVvQqTnSdjumszn2VlZXS90qsXXb8oA2dn+tNCVz3RBklqCWtiziImkpRRddQ/rEzvWV46KRWLyvBSnVujRjGMjQ1zq/AGg9Vgfr/1u7IjkoiK2grG8BtDZsqRKfSAtzfDdO7MMGVlMpn/Ud0jRusrLeaDPz9gmPBwKtsOCBBbZiQpcju3oqJIgvDZZ08eejvsbYa7hsv8k/uP1NMGhQQxfZYZMEI9PYbx9GSYxkYZBKu6XC24ymA1mH239j198ORJhjE3J+nC99+TBO/11+lcMTVlmG3bSKbXBIFQwNh+Z8uM3j9aYbEr8nPrcOJhBqvB7Lq+S+o5xhwYw1htsWIaBC+f5FNSorKiGI21Goz/H/4ykdbKGmV9J1bVVzHaX2vT57MM+CqGpOr8Er5M5lMG4w+OZyw3W8r0fbPz2k6lSpIUen41NDDMhAn0+X34sPTzLFxI37lHj8ouNlVBKGQYf/825XoiHtY8ZIJCghisBjN0z1Cm/8/9W5fnvfEGWSFcl78UudVza+VKkljeu9fs07bf2TKBIYFyioxFVVFpmR4LCwtLhyI3l6Rbb76JmPxYAICnXceqjNLX0sfCAQtxPOU4MkszqZNbaSng7y8TuV5kZiTqBHUIbHQGZs4EBgwAfv9dLJmRSuHtTWX1mzYB8fEAgC2jt8DW0BazQ2ejoq5C4imr6qtwMikURyN0wFFTo9dFTU3WkasUA6wGwNrA+tmOcX5+QEICdYr74APAzg744w9g6VIgI4PkeRoaz8zzT94/yC3Pfakkek2Z6jIVg60HY+XfK1FZXynx8ZmlmTiTcQbz+s2DOvflk3xKire9N/I+zMOxqcc6fNdFWaKroYsR9iMQkR7R7rkahY34+frPeK37a3A0dZRBdMrh7X5vo6iyCKfTT8tszpCUEDiaOsLVXEHdzJSJujp9fnt4ALNmAefPSz7Hvn3Azp3AsmVUHfWyweHQz6erS5VkLcj1RBhqG+LA5AM4MOkAbhfdxvW717F93Pbm5Xl//kmv36efAv2ULEWeMoWsGU6caPZpZ3NnVqbHIjbsNzcLCwvL84jaGL/5JqJzomFnZNchWzYvGbQEahw1fHv5sVxq3z4gJoYuJNu4SGqLk2kn4VxngAHz15AsLzycLsA6Ips2kdfVO+8ANTUw0DLA/kn7kVueiyV/LpF4ujB+GBZFV6Nnyj1g+3bApuOdO5LC5XAx2WkyzmacfTbJ0rkzeUP9/DO1vk5NJSmnkVGz8+y/vR+dNDrB38lfQZErFg6Hgy2jtuBu5V1svrRZ4uN/ivsJahw1vNP/HTlE1zGx1LOEGvflTvZKg6+DLzJKM3Cr6Fa75olIi0BBRUGHl4WOcxgHSz1L7LqxSybzPah+gL+z/0aAcwA4Hd3zSFx0dOjz3MmJNrauXRP/2Js3SWLm7d0xfCWlRSTXu3yZ7AvEIKhXEOIXxuPY1GOY5jrtxQHl5XR94uICrFol44ClwN0dcHBoUarnZOoE/gM+hIxQwYGxdETYZBQLCwtLU4RCMtT08YHQphsu5F7ocH5RIrrod8GsXrOw99ZelFSXUAXTt98CISHAkiXk1yMFxVXFOH3zCE4fVgfn0SMgIoIuwDoqpqbkg3HtGjBmDFBeDg8bDywfthz7bu/D0aSjEk13NWw7VkcDzPRpQGCgfGJWQaa6TkWdoA7rLqx79gkOB5g3D/jlF8DevsXjaxtrcTT5KAJcAtBJs5Oco1UeQ7oNwVSXqdh0aRPuPLoj9nE1DTXYc2sP/J38YaVvJccIWV4GprlOg5muGd4OfxsNggap59lxbQesDazh5+gnw+gUjzpXHXN6z8Hp9NMSve9aIpwfDgEjePn9op7HyAg4exYwNwfGjQP4/LaPKS0FAgIAMzOqrnoJG3k8Q2AgeSKuWCHe6wMyNw9waSGxuWwZcPcuXZtqack4WCngcKg6KioKePDghaedzJxQ3VCN/PJ8JQTH0tFgk1EsLCwsTYmKIpne3LlILk7Gg5oH8LLzUnZUUrN0yFLUNNZgx7XHpqMffkgXNjt2UIc9KfhfzHr88kcVbHMeAocP0y5ZR2fqVOpQc/kydQ8qKsLK4SvxStdXMD9iPgoqCsSaJuzGISz84RKqTPXB2flTx+8SJAEe3TzwTr93sOHiBhxOPCzx8UeSjqC8rhyz3GfJITrV4puR36BB0ICVUSvFPuZo8lGU1pR2+AoVFsVgpmuGn/1+xvW71/H1ha+lmiPtQRoisyIxv//8l0IWOrfvXAgYAfbd2tfuuUJSQmBraPvf7N7YpQtw7hzJ8keNAgoLn32eYSgBFRdH1whTplAHvWPHAAsL5cSsSDgc6j6ooyOWXK9FBAIyjf/1V+pO+8orMg2zXQQEUHzh4S885WzuDIA1MWcRDzYZxcLCwtKU3btJsuXvj5icGADosJVRAOBi7gJfB1/8+O+PqGmooQc3bABmzwZWrgR2SSZZyC/Ph/W6bZjABzhbtwJjx8ohaiUxYwZVeWVkAB4e0MjJQ/DkYNQL6vHGiTdaLTkXMkKsjl6N/AWBcCoBOHt/o/PoPwSHw8GP436ERzcPvBn2pkTyoJicGCyIWIC+ln0xwn6EHKNUDXqY9MDiVxZj7629iL8XL9YxO67tAM+UB287bzlHx/KyMNl5Ml7v/TrWxa7Dv4X/Snz8T3E/QZ2rjrf7vS2H6BSPg6kDPG09sefWHjBSVgYDQEVdBSKzIjHZefJ/R6L3PA4O5GNUVkYJqU8/pU2dfv3ou8/UFBg4kL5XL1ygDbBBg5QdteLo0gXYupW6DG/dKvnxhYXUdXbNGuD114G1a2UfY3vo1498IJuR6jmZOQFgk1Es4sEmo1hYWFhElJYCoaFAUBCgrY2onCjYGNrAzshO2ZG1i6VDlqK4uhi/3/6dHuByKek2Zgwwf36zO1stEfP5THxwSYCK+XOA996TT8DKZNQo4K+/yKPBwwM98yrxw5gfEJUdRd5bzVBZX4kpR6bg6q41WHQNaHx/MQx9Jys4cNVAU00TIdNCYKpriol/TMT9qvttHnMx7yJ8D/rC3tgeZ2ed/c/4/ywfvhxG2kZYem5pmzfGN+7ewNXCq1g4YOF/9+aXRSq2jtmKrgZdMTt0NqobqsU+rrqhGr/d+g2TnSfDUq8Dy7Cf462+byGjNAMXci9IPceptFOoF9T/9yR6z9OvHxAWBuTlkT9SQgJJ9mfNArZsIYPr+Hjg4UPg7ZcjoSkRQUHA+PHAF19QdZO4zWNOnwb69KHKsn376I+2tnxjlRSRVC8ykn6/TTDXNYextjFSSlgTc5a2YZNRLCwsLCIOHgTq6oC33oJAKEBUdhR87H06/M2fp60nBlgNwJbLWyAQPi4X19AAjh4F+vcHpk8HLl5sc57CY3sx4+eLSBxoB4PtsjGBVUkGDQJiYwFNTcDTE3MremCS0yR88dcXuF10+5mh2WXZGLLrVaTFnsCxM/pg3NygvmGjkgJXDTrrdUbo9FDcr7qPKUemoF5Q3+LYfwv/xdjgsbDSt8L52edh3slcgZEqFxMdE6zyXIXIrEicyTjT7Ji6xjpEpEVgyZ9LoKOugzf6vKHgKFk6Oobahvht4m9Ie5CGTyI/Efu47f9uR1ltGd4d8HLJQgNcAmCoZYhdN6X7DmMYBgcSDqCLXhe82u1VGUfXAfH2BkpKgOpqalBx+jTw44/ARx8BEyeSjF9PT9lRKgcOh5p3uLmRb6KNDVU6FRc3P76+nrrN+voCVlaUjHr9dcXGLAlTpgANDWRq3wQOhwNnc2e2MopFLNhkFAsLC4uI3btpp69PH8TdicPD2ocY1WOUsqNqNxwOB8uGLEN6aTrC+U2qoPT0gFOngG7daPcuKYker6khqVp0NLB/P/DNN8B778H4jflIseDAPCwSUHvJq1ecnSlB17UrOGPG4DdMgpmuGQKPB6KmvhrIzETqhmWIG+mEPz9PQuJ2Bp2qGsA5cED1djCVwACrAdg1fhdi82LxwZkPmh1z8+5NjD4wGuadzBH1RhS66HdRcJTK592B76KHcQ8sjVyKRmHj/9m77/Aq6rSN499z0iGU0EIogRDIQAqdELpUe0NFWbErYhd1Xde1d99V1FWXVSwIqIhtWVxFgq4YSgihJpQBEiD0XkN6zvvHhEgJkHJOJuX+XFeuIXMmMze7RyBPnt/zA6xB7jPXzWTMd2No9kYzLv/yclL3pPLasNdo6F/yLoQi5zI4bDDj48bz/pL3mZM255zX5hXk8fDsh3l87uOMCB/BwDYDKyll5ajjU4cbY27kq9SviE+LL/PXv5LwCj9u+JH7Y+/H6dC3UYA1VLum/5ugvEJCICnJmkcaG2vNgAoNtbrS151UrNm0CQYMsDrK7rkHEhOtXQursthY69+PJS3Va9xRxSgpleo/jVBExB2WLIEVK6yf6AHx6fE4cDC03VCbg7nHyE4jCWsYxhuL3uDqTlf/8ULTptbOOH37Wh++vtZPOU+TH9SApU3yWPjaffwlpH0lJrdR69ZWh9Sll1L/T7cy/67rSEj8iqznggnYe4yOQJN6XvgNvRguusJa9timjd2pq4wbO9/Iyt0r+fvCv9MluAt397y7+LWU3SkMnzqc+n71+fXmX2lVv5WNSe3j6+XL68Ne59qvr+WRnx9h3/F9zFo/i2O5xwjyD+LaTtdybeS1DG03FF8vX7vjSjX28pCXmb1xNrfNvI2Ue1JoFNDojGt2H9vNqG9G8fuW33m498P83/D/q/adwSV5achLzN86n6u+uoo5Y+bQL7Rfqb5u8orJPPW/p7i5y838tf9fPZxSagyHw+ogGzwY1q6Ft96ylt59+CFcdhkMGWJ1TIFV2Lmmmiz/dDhg5EhrWPvRo1CvXvFLnZp24pMVn3Aw6yBBAbVrfqaUjUr6IiJg7SzXsKE16wCrGNUtpBtN6jSxOZh7eDu9GR83noVbF7Jw68JTXwwLs3bGuewyq+36pZesfyj98ou1LXFmJle/P4Ar7m3I2KtetOc3YJfGjWHuXBg+nHYffMU1mwL4pekx7r0E7vn7IHz37Kfe9/+1fsqpQtQZXh36Khe1v4j7f7qfhC0JgDXUdNjUYfh7+/Przb/SpmHt/t9tZKeR9Gvdj3eT3mVO2hxuiLqBn8f8zO7HdvPxlR9zcYeLVYiSCgvwCWDayGnsydzDfT+eOe9v8bbF9PiwB0u2L2Ha1dN466K38PHysSGp5wUFBDFnzBxa1mvJpV9cyvKdy8/7NT9t+Ik7/3MnI8JH8NHlH9XIIp1Ugk6drCJURgY8+6zVAfXII2AYsHx59SlEnXDlldZ4i4SEU05riLmUlopRIiLLl1tDOMePhwYNOJZ7jEVbFzG83XC7k7nV7d1up1FAI/6+8O9nvhgTA59/DhMnwt/+Zs0pGDIEIiJYuH8FP6z/gcf7Pl47f8IVGGjNwdiyBe+9+5j29BU0fewZ3nvkF+r7N7A7XZXm5fTii5FfENYwjGtmXMOvm35lyGdDcODgl5t/IbxRuN0RbedwOPh21Lf8fuvv7HpsF5OumMSI8BE1thAg9uke0p1nBz3L9NTpTE+dXnx+0tJJDJw8EF8vXxbesZAbO99oY8rKERwYzNyb51Lfrz4jpo045zfNyTuSue7r6+gc3JlvrvtG/21KxTVrZi3Zy8iA+fOtYk5YmN2pyq5XL2tTnKRTd+s8UYzSEHM5HxWjRESef97qinrwQcDaZj6vMK/GFaPq+tbl3p73MnPdTNbvX1+qr3G5XDz5y5M0q9uMB3s/6OGEVZjTCaGh+PvWYeYNM3l+8PO1Zte3igoKCOI/o/9DTkEOQ6cMJa8wj19u/gWjiWF3tCojODCYAW0G4O3U9ATxrCf6P0Fcqzju+e89pB9MZ+yssYz9YSwXtL2A5LHJdG3e1e6IlSa0QShzb56L0+Fk2JRhbD60+Yxr0g6kcekXl9K0blN+vPFH6vnVO/NGIuUVEAD9+lkjEqqjwECIioLFi085HdYwDF8vX3VGyXmpGCUitdvJXVENreHA8enx+Hv7l3qORHVyf+z9+Hr5MmHRhFJdPzd9LvO2zOOpAU9R17euh9NJTdWxSUemXzOdXi16MfemuUQ1i7I7kkit5O30ZspVU8gtyCXy/UgmLZvEk/2f5Mc//VjiHKmaLqJxBPE3xZOZl8nQKUPZcXRH8Wt7M/dy0ecXkV+Yz+wbZ9M8sLmNSUWqqNhYqzPK5So+5eX0IqJxhIpRcl4qRolIhRzJOULyjmQyczPtjlI+L7wADRoUd0WBVYwa2GYg/t41b1e04MBgbu5yM5NXTGZP5p5zXutyuXjy1ydp06ANY3uMraSEUlNd3OFiku5KokvzLnZHEanVOjTuwLsXv0sD/wZ8N+o7Xh76cq3u9Owc3JnZN85m97HdjJg6gv3H95OZm8llX17GtiPb+GH0D+rkFDmb3r3hwAFITz/ldKcmnbRMT85LxSgRKbdCVyFXfHkFvSb1Yti9gRwa0585w8L49xNXMeen99i4fwOFrkK7Y57dihXw73+f0hW17cg21uxdU+OW6J3s0T6PkluQy3tJ753zuu/XfU/yjmSeu+A5/Lz9KimdiIh42u3dbmfXo7tO3V21FuvdqjezRs9i44GNXPT5RVz/zfUk70hm+jXT6dO6j93xRKqu2FjreNpSvY5NOpJ+MJ2c/BwbQkl1oeEEIlJu7yS+Q8KmeczZOoihnyVwuG4BXlsyqP/LZnh9JvsCYHaoE1efPlx684vWX1h1q9BSrxNdUQ89VHxqbvpcgBpdjDKaGFxhXMGLv7/Il6lf0rtlb2JbxhLbMpauzbvi7+1PQWEBT/36FB2bdGRM5zF2RxYRETfTjnCnGhw2mK+v+5qRM0aSX5jPxEsncmXHK+2OJVK1RUVBnTrWUr0//an4dMcmHSl0FbLxwEYtzZezUjFKRMpl7d61vP/dE6z8oRHR6+bBDTewedw4ug0YQNaqZeyK/57cBb/TeclKWk1eAJOHWAMaJ0yA+87cVrrSrVgB339vba1b1BUF1hK9ZnWbERMcY2M4z/vkyk/4cOmHLNmxhN82/8bnKZ8D1jyRLsFdCKkXwtp9a/n6uq81VFlERGqFy43L+WH0D+w8tpNbu95qdxyRqs/bG3r0OGNHvU5NOgHWjnoqRsnZ6DsMESmz/MJ8Jj99OUum5NHAKwc++wxuuonCZcvA6SSga0/CuvaEP0NuQS793+pKmLmbT7b1xOf++6115X//u7VDmV1OdEU9/HDxqUJXIXPT5zKs3TCcjpq9irlRQCOe6P9E8efbj2xnyY4lJG1PIml7Er9v+Z2+rfsystNIG1OKiIhUrgvbX2h3BJHqJTYW3nsPcnOLdwaMaBwBoCHmck4qRolI2WRmknL9IF7/bxoHosNxfj8b2rc/6+W+Xr68Nfoz4j6OI/CyNkzs8IDVHbV5M0ydarX2VraVK0vsikrZncKezD01eone2bSs35KW9VtyVcerAKsw58ChZRwiIiIicnaxsZCTAykpVpcUUNe3LqENQjXEXM6pZv/oX0Tca9kysrtE0eXHpcy8OpJGy9aesxB1Qq+WvRgfN55/rZjEvEeugbfesopBQ4bAnnPv6OYRL7wA9eufMisKrCV6ULPnRZWW0+FUIUpEREREzq13b+tYwlI9dUbJuagYJSKls2QJrj59OLx/O6PubsSAzxPAx6fUX/7C4BdoF9SOO2fdSdZ9d8O338KqVRAXB+sq8S+qVavgu++s5XlBQae8FJ8eT6cmnWhZv2Xl5RERERERqa5CQ6FZsxJ31Fu3b13V3llbbKVilIicX04O3HYbR+r7EX1XPrc/MpVGAY3KdIs6PnWYdPkkNh7YyPPznoerr4bffoPMTOjbF+bN80z2053oijppVhRAdn42v2/5XV1RIiIiIiKl5XBYS/VK6Iw6nnecbUe22RRMqjoVo0Tk/F55BVav5qYRx7iq/51c0uGSct1mSNgQ7uh2B28sfINlO5dZf3ElJkJwMAwfDp9/7ubgp1m1yurIeuihM7qiFmQsIDs/m+HhKkaJiIiIiJRa797WSofDh4tPdWzSEdAQczk7FaNE5NxWrsT1yiv8u2c9VvUK5c0L36zQ7d4Y8QbN6jbjjv/cQV5BHoSFwcKF0K8fjBkDL70ELpebwp/mxRdL7IoCa4met9ObQW0GeebZIiIiIiI1UWys9e/35OTiUyeKUWv3aoi5lEzFKBE5u7w8uO02jgb6cvuQo0y+ajL1/epX6JYN/Rvy/iXvs2LXCt5cVFTYCgqC2bOtYtTTT8Mdd1jPdqcff4RvvrG6ohqducQwPj2ePq36UM+vnnufKyIiIiJSk/XqZR1PWqrXrG4zgvyD1BklZ6VilIic3d//DsuXc+uI49w8+CEuaHuBW257daeruabTNTz323OY+0zrpJ8fTJkCzzwDn34KF18Mhw655Xl8/jlceSV06waPPnrGy/uO72P5zuWaFyUiIiIiUlZBQRARcUoxyuFwWEPM96sYJSVTMUpESrZmDTz/PAviWrCwVzCvDH3Frbd/75L3CPAJ4K5Zd/2xy4bDAc8/D5MnWwPN+/eHLVsq9qB//MPquOrf3xqY3qDBGZf8kv4LLlyaFyUiIiIiUh6xsdaOeieN2+jYpKOW6clZqRglImcqKIDbb6cwMJBRA3czpvMY6vjUcesjmgc2Z8KICSRkJDBp6aRTX7zlFmvZ3rZtEBcHS5eW/QEuFzz1lLUs7+qr4aefrHlRJYhPj6eBXwN6tuhZjt+JiIiIiEgtFxsLO3fC9u3Fpzo26cjuzN0cynbTagepUVSMEpEzvfMOLF7MnIcuZUedAm7pcotHHnNr11sZ2GYgz817jqy8rFNfHDoUFiwAX18YOBBmzSr9jQsKYNw4ePlluPNOmDED/P1LvNTlchGfHs+QsCF4O70r8LsREREREamleve2jict1WvfqD0A6QfT7UgkVZyKUSJyqg0b4G9/g8sv52/BqXRr3o2Y4BiPPMrhcPDCBS+w69guJi2bdOYFUVFWu29kJFx1Fbz7LuTnn/umOTlw/fXw4Yfw179aR++zF5k2HNhAxuEMzYsSERERESmvLl3Ax8f6t3uR8KBwANIOpNmVSqowFaNE5A+FhVYnkZ8fa198iGW7lnNr11s9+shBbQcxqM0gXl/wOtn52Wde0Ly5NevpssvgwQehXj3rJy/33AOTJllL+HJyrGuPHoVLLoFvv4UJE+CVV6w5VOcQnxYPoHlRIiIiIiLl5ecHXbue0hnVLqgdAGkHVYySM6kYJSJ/mDgRfv8d3nqLj3f/hLfTm9HRoz3+2GcGPcOOozv4eNnHJV9Qty589x189RXcey/UqQNffAFjx0LPnhAYaO2U16uXNfh8yhQYP75Uz45Pj6dtw7bFP7kREREREZFy6N0bkpOtkRlAPb96NK3TVMv0pEQqRomIZds2+MtfYMQI8m8ew7RV07i0w6U0rdvU448e3HYw/UP789qC18jJzyn5Ii8vGDUK3nwT/vc/OHgQNm605kE99hg0a2Ytx5s5E266qVTPzS/M53+b/8fwdsNxnKeDSkREREREziE2Fo4dg7V/7KAX3ihcnVFSIhWjRMTy1FOQlwf/+hdz0uPZnbnb40v0TnA4HDw76Fm2HdnGJ8s/Kd0XOZ0QHg7XXQevvgo//wypqXDppaV+btL2JI7kHNG8KBERERGRioqNtY6nLdXTzCgpiYpRIgIrV1pL2x58EMLCmLxiMo0DGnNJh0sqLcLQsKH0bd2XV+e/evbuKDebsXoG3k5vhoQNqZTniYiIiIjUWJ6tyx8AACAASURBVB06QMOGpxSjwoPC2XpkK7kFuTYGk6pIxSgRgT//2fqL48knOZh1kJnmTP4U8yd8vXwrLYLD4eCZgc+w9chWJq+Y7PHnHc4+zMfLP+aG6BtoXKexx58nIiIiIlKjOZ3WDNfTdtQrdBWy5dAWG4NJVaRilEht9/PPEB8PTz8NQUF8tforcgtyK22J3slGhI+gd8vevDL/FY//9OSjZR9xLPcY4+NKN+hcRERERETOIzYWUlLg+HFAO+rJ2akYJVKbFRRYXVFhYdYudcBnKz8julk03Zp3q/Q4J2ZHZRzOYMrKKR57Tn5hPu8sfocL2l5A95DuHnuOiIiIiEit0ru39T3G8uWANcAc0I56cgYVo0RqsylTrJ9cvPoq+Plh7jNJ3JbILV1usW13uYvaX0SvFr14OeFl8gryPPKMb9d8y9YjW9UVJSIiIiLiTr16WceipXohgSH4e/triLmcQcUokdrq+HFraV5sLIwaBVhdUU6HkxtjbrQtlsPh4JlBz7D50Gamrprq9vu7XC7eXPQm7Ru157KIy9x+fxERERGRWqt5cwgNLR5i7nA4aBfUjvRD6oySU6kYJVJbvf02bN8Ob7wBDgcFhQVMXTWVi9pfREi9EFujXdrhUnqE9PBId9TCrQtZsmMJ4+PG43Toj0AREREREbfq3fuMHfXUGSWn03diIqW1apXVdnrFFfDZZ3DwoN2Jym/PHnjtNbjyShgwAIBfN/3KtiPbuKXLLTaH+6M7Kv1gOl+kfOHWe09InECQf1CV+H2KiIiIiNQ4sbGwaRPs3QtYxaj0g+m4XC6bg0lVomKUSGksWQIXXADbtsGKFXDrrdCsGVx8MXz0EezbZ3fCsnnhBWuZ3uuvF5/6bOVnNPRvyBXGFTYG+8PlEZfTrXk3Xkp4ifzCfLfcM+1AGt+v/Z5xPcdR17euW+4pIiIiIiIniY21jkXdUe2C2pGZl8mezD02hpKqRsUokfNJSIChQ6FhQ1i4ELZssQbyjR8P69fDXXdZa6OHDoWJEyEry+7E57Z+PXzwAYwdC4YBwJGcI3y39jtuiLoBf29/mwNaTnRHbTywkU+Xf+qWe/5j8T/wdnpzf+z9brmfiIiIiIicpkcPcDqLi1EndtRLO6ilevIHFaNEziU+Hi68EFq2tIpSYWHgcFjV/v/7P9i4EZYtgyeesOYv3XuvtYwvO9vu5Gf3xBPg7w/PPlt86ps135CVn8UtXavW0rUrjCsY2GYg438ez7p96yp0r0PZh/h4+cfcEH0DLeq1cFNCERERERE5Rd26EB1dvKNeu6B2AJobJadQMUrkbP7zH7jsMoiIgHnzrILU6RwO6NYNXnoJ1q6FTz+FuXPh2mshN7fyM5/P/Pnw/ffwl79AcHDx6ckrJhPROILeLXvbGO5MToeTL0Z+QYBPANd9fR3H846X+16Tlk4iMy+T8XHj3ZhQRERERETOEBtrdUa5XIQ1DMOBg/SD2lFP/qBilEhJpk+HkSOtQtP//mfNhzofh8OaJfXBB/Df/8Lo0ZDvnllHbuFywZ//DC1awCOPFJ9OP5hOQkYCt3a5FYfDYWPAkrWs35JpV09j9Z7VPPjTg+W6R15BHv9I+geD2w6mW0g3NycUEREREZFT9O5tbfi0cSN+3n60qt9Ky/TkFCpGiZzuk0/gT3+Cfv2sZXpBQWX7+rFj4Z134Lvv4OaboaDAMznL6sMPITHR6uKqU6f49PTU6QDc2PlGu5Kd14XtL+TJAU/y8fKPmbpyapm//ps137DtyDYe6fPI+S8WEREREZGK6Vb0A+BVqwBrqZ6KUXIyFaNETvbee3DHHdacqJ9+gnr1ynefBx+E116DL7+0BpwXFro3Z1mlpcGjj8KwYXDLqXOhZqyeQd/WfQltEGpTuNJ57oLnGNhmIOP+O461e9eW+utcLhcTEicQ0TiCSzpc4sGEIiIiIiICQKdO1sqRlBQAwoPCtUxPTqFilMgJa9bAAw/AlVfCv/99SvdQufzlL9aQ8E8/hfvvt5bJ2aGgwFo+6O1tdX05//jP3txnsnL3SkZFjrInWxl4O7358povqetTl1HfjCr1/Kj5GfNJ3pHM+LjxOB36I09ERERExOPq1IH27f8oRjUKZ9exXWTmZtocTKoKfWcmcsK//gW+vjBpEvj5ueeezz4Ljz8OEydanUl2FKQmTLAGl7/7LrRufcpLM1bPwIGDayOvrfxc5dCiXgumjbTmRz3w4wOl+poJiRNoFNCIm7vc7OF0IiIiIiJSLCYGUlOBP3bU23Rok52JpArxLu2FhmE0Ah4DugKBJ79mmuZAN+cSqVyZmfDZZ9YueE2buu++Doe1XC87G956CwIC4OWX3Xf/80lNhaeegquvhjFjznh5xpoZ9A/tT8v6JewUWEWNCB/B3wb8jZcSXmJQ20ElFplcLhdr9q5hpjmTmetm8uSAJ6njU8FONxERERERKb3oaGvFSVYW4UHhAKQdSCO6WbTNwaQqKHUxCvgC8ANmAOXfX12kKpo+HY4cgXvucf+9HQ54+22rIPXKK1ZB6qmn3P+c0+XmWgPUGzSwdvg7bae8NXvXkLonlXcvftfzWdzs2QueJSEjgXv+ew89W/QksmkkuQW5zNs8j1nrZ/HD+h+Kf+rSt3VfHuxdvl34RERERESknGJirNm5a9cS3qmoGKUh5lKkLMWovkBT0zRzPBVGxDYTJ1qV+379PHN/h8N6RnY2PP20VZB69FHPPOuEF1+E5cvh++9L7Pb6evXXOHBwTadrPJvDA07Mj+r6QVdGfjWSmOAYft74M0dzj+Lv7c+wdsN4ov8TXNrh0mrV9SUiIiIiUmPExFjHlBSCunWjgV8DDTGXYmUpRq0CWgEqZUrNsmQJLF1q7aR3WvfQCWkH0vho2Uc8FPcQzQObl+85Tid8/LFVkHrsMfD3h/vuq0Dwc0hKgldftXbOu+qqEi+ZsWYGA9sMJKReiGcyeFhIvRCmXT2Niz+/mKO5RxkdPZrLjcsZEjZES/JEREREROwWHm7N4k1JweFwEN4oXJ1RUqwsxahfgdmGYXwK7Dr5BdM0P3FrKpHKNHEi1K0LN91U4surdq9ixNQR7M7czeSVk/li5BcMDhtcvmd5e8O0aZCTY+2w5+cHd95ZgfAlyMqylue1aAHvvFPiJav3rGbN3jW8f8n77n12JRsePpw9f95DkH8QjrMUEkVERERExAbe3hAZecoQ85W7VtocSqqKsuymNwDYBgwHbjrp48ypyCLVxcGD1ryoG2+E+vXPeHnR1kUMmjwIb6c33476lob+DRk2dRgvzHuBgsKC8j3Txwe++gouugjGjrWKU+7017+CacKnn1rzokowY/UMnA4nIzuNdO+zbdAooJEKUSIiIiIiVVFMDKSkABAeFM7mQ5vL/32U1Cil7owyTbOcrSAiVdiUKVYnUQmDy+PT4rnqq6sICQxh7s1zaduwLSPCR3DPf+/h2d+sAdrTrp5GcGBw2Z/r5wfffQeXXmotpfP3t3byq6hff7W6oe6/H4YOLfESl8vFjDUzGNRmUPmXHIqIiIiIiJxPdLT1PdeBA4QHhZNXmMe2I9to07CN3cnEZmXpjMIwjCDDMG42DOOvRccgTwUT8TiXC/71L4iLg65dT3npu7XfcdmXlxEeFM782+fTtmFbAAJ9A5ly1RQ+uvwj5mfMp+sHXflt82/le35AAPznP9CnD4weDbNmVez3s2oV3HordOgAr79+1stS9qSwbt86RkWNqtjzREREREREzuXEEPPUVNoFtQO0o55YSl2MMgyjD9bw8nFAZ+BuIK3ovEj189tvsG4djBt3yunJKyZz3dfX0SOkB/NunXdG95DD4eCO7neQdGcSDfwaMHTKUF76/SUKXYVlzxAYCD/+CN26WZ1Rc+aU/R5Hj8Ijj0D37laX1+efQ52zD/CuSUv0RERERESkCouOto4pKYQ3CgfQjnoClK0z6m3gXtM0+5qmOdo0zX7APcA/PBNNxMMmToSgIBj1R4fQ24lvc9vM2xgaNpT4m+IJCjh7819McAzJY5MZHT2ap//3NJd9cRn5hfllz1G/PsyeDZ06wZVXwrPPQlopflrgcsGMGdCxI7z9tjUI3TShV69zfImLGatnMLjtYJrVbVb2rCIiIiIiIqXVsiU0bAgpKbSu3xpvpzdpB9QZJWUrRkUAM0479w3Q3n1xRCrJzp3w/fdw220QEIDL5eK5355j/M/jGdlpJLNGz6Kub93z3ibQN5CpV0/l7Qvf5qeNPzFp6aTy5WnUCOLjYfBgePFFaN8e+veHDz6whqyfbv16uPBCuP56aN4cEhOtJYeNGp3zMSt3r2TDgQ1aoiciIiIiIp7ncFhL9VJT8XJ60bZhW9IPqTNKylaM2gDccNq567CW7olUL598Avn5cPfdACRkJPD8vOe5teutfHXtV/h5+5X6Vg6Hgwd7P8igNoN4+n9PczCrhOJRaTRtai3Zy8iA116zilDjxlnFpuuus2ZKHTkCzzxj/YG+eDG89x4kJUFsbKkeMWP1DLwcXlqiJyIiIiIilSM6GlJTweUiPChcnVEClK0Y9TDwnmEYiYZhfGUYxmLgn8CDnokm4iEFBfDhh9ZucxERAHy24jPq+dbj/Uvex9tZ6k0mizkcDt6+6G0OZB3ghXkvVCxfq1bwl79Yf2AnJ1s7/c2bB1dcYS0rfPFFa2mhacJ994GXV6lue2KJ3tB2Q2lSp0nFMoqIiIiIiJRGTAwcPgxbt1rFKA0wF8pQjDJNcyEQDrwHLAXeBdoXnRepPk50H91zDwBZeVl8s/Ybrom8hjo+Zx/8fT5dm3flru538d6S91i3b13Fczoc0KOHNQ9q+3arM+q+++DXX2HqVKtjqgyW71pO2sE0RkVqiZ6IiIiIiFSS03bUO5R9qPyrSaTGKFMLiGmaB4FpHsoiUjkmToSQEKvTCJi1fhZHco4wJmZMhW/94pAXmb56Oo/8/Ag/3vhjhe9XzMcHLrvM+iinGatn4O305qqOV7kvl4iIiIiIyLlERVnHlBTCrzQASDuYRs+AnjaGErudsxhlGMZs0zQvKvp1AuAq6TrTNAd6IJuI+23aZO1c9/TTVoEHmLZqGi3rteSCthdU+PbN6jbjmYHP8Fj8Y/y04Scu7nBxhe/pDieW6A1rN4zGdRrbHUdERERERGqLoCBrFElqKu1utb4/SjuQRs8WKkbVZufrjJpy0q8/qsiDDMOIAD4DGgP7gZtN09xw2jVewD+Ai7AKX6+ZpvnRSa+PAp4GHEWvDzNNc3dFckkt8+GH1vK3u+4CYN/xffy08SfGx43Hy1m62Uvn80DvB/hg6Qc8MucRhrUbho+Xj1vuWxFLdy5l06FNPD3wabujiIiIiIhIbRMdDSkptAtqB0D6Qe2oV9udc2aUaZpfnPTpOtM0Pzv9A1hbymf9C3jfNM0I4H3ggxKuuRFoD3QA+gDPGYbRFsAwjJ7Ac8Bw0zSjgf7A4VI+WwTy8uDjj+Hyy63KPPBV6lfkF+YzpnPFl+id4Ovly4QLJ7Bu3zr+ueSfbrtvRXyV+hU+Th8t0RMRERERkcoXEwNr1xLo8CO4brCGmEuZdtOLP8v52ef7QsMwmgHdgS+LTn0JdDcMo+lpl14PTDJNs9A0zb3Av4Hril4bD7xhmuYuANM0D5ummV2G/FLbLV4Me/fCTTcVn5qWMo3OwZ3pHNzZrY+6tMOljAgfwXPznmPf8X1uvXdZuVwuZqyZwfDw4QQFBNmaRUREREREaqGYGMjNhY0baRfUTp1Rcv4B5oZhOLGWxTkMw3AU/fqEcCC/FM9pDWw3TbMAwDTNAsMwdhSd33vSdaHAlpM+zyi6BiAS2GQYxu9AIPAd8LJpmiXOsSpJampqaS+t8ZYuXWp3hEoXMmUKIU4nKxs1omDpUjKOZZC4LZEHOz3okf897mx1J7+k/8I9M+7hiZgn3H7/0krel0zG4Qxub3t7pfz/XhvfW1I59N4ST9F7SzxF7y3xJL2/xFM88d4KcDqJBNJnzqRhk4Ys371c7+FarjS76eVjzWdycGbhqRB42d2hzsIb6AwMB3yxOrIyOHWu1TlFR0fj5+fnmXTVyNKlS+nRo4fdMSrf6tXQsyddBw8GYNZvs3Dg4PGLHqdl/ZZuf1wPevD78d/5Z/I/eebiZ4gJjnH7M0rj+S+fp0mdJjx+6eME+AR49Fm19r0lHqf3lniK3lviKXpviSfp/SWe4rH3VlQU3HIL7TIziY2LZfa82UR3icbPW9+fV3c5OTnlavwpzTK9MKwOqK1Au5M+woD6pmk+V4p7bAVaFg0oPzGovEXR+ZNlAG1O+jz0pGu2AN+YppljmuZRYCYQW4pni8CRI9YyveHDAWvp2rRV0xgSNsQjhagTnh/8PA39G/Lwzw/jcpW6ic9t1u9fz6z1s7i3570eL0SJiIiIiIiUyN8fOnSwdtQLaocLF1sObzn/10mNdd5ilGmaW7AKQpuAXaZpbin6yDBNM6s0DzFNcw+wAhhddGo0sLxoLtTJvgbuMgzDWTRP6irg26LXvgBGGIbhMAzDBxgKrCzN80X47TcoKIBhwwBI3JZI2sE0tw4uL0mjgEY8f8Hz/LrpV2aaMz36rJK8tegt/Lz8uLfXvZX+bBERERERkWJFO+qFB4UDkHZAQ8xrs1INMC+a9RRW2uvPYhzwgGEY64EHij7HMIwfi3bKA5gKpAMbgETgBdM0T0w2mw7sAdZgFbZWAx9XII/UJnPnQp060KcPANNWTSPAO4CRnUZ6/NHjeo4jsmkkj815jJz8HI8/74R9x/cxeeVkxnQeQ3BgcKU9V0RERERE5AwxMZCeTrhvcwDtqFfLlWZm1AnPAxMNw3gW2IY1RwoA0zQLz/fFpmmuA3qXcP6Sk35dANxzlq8vBB4p+hApm/h4GDgQ/PzILchl+urpXNnxSur71ff4o72d3rx14VtcOO1C3ln8Do/3e9zjzwSYuGQi2fnZPNJH/8mIiIiIiIjNYmLA5SI4Yz91fOpoR71ariydTh8BN2N1LuUCeVgDzfM8kEvEfbZtg3XriudFzd44mwNZBxgT49kleicbET6CyyIu46XfX2L3sd0ef152fjbvLXmPi9tfTGTTSI8/T0RERERE5JyiowFwFM2NUmdU7VaWYlRY0cfpQ8zbeSCXiPvMnWsdi+ZFTVs1jaZ1mjIifESlxnhzxJtk52fzt1//5vFnfZHyBXsy9/Bon0c9/iwREREREZHzatcOAgIgJcUqRmlmVK1W6mLUicHlWMPMc4GtJ50TqbrmzoVmzSAmhkPZh/iP+R9uiL4BHy+fSo0R0TiCB3s/yCfLP2HZzmUee47L5WLCogl0Du7MkLAhHnuOiIiIiIhIqXl5QWQkpKYSHhRO+sF0W3Ycl6qh1MUowzDqG4YxBcgGtgNZhmF8ZhhGA4+lE6kol8sqRg0bBg4H3675lpyCHG7qfJMtcZ4e+DRN6jThodkPeewP3p/Tfmb13tU82udRHA6HR54hIiIiIiJSZjExxTvqZeVnsevYLrsTiU3KskzvH0BdIBoIAGKAOkXnRaqm1FTYvbt4id7UVVOJaBxBzxY9z/OFntHAvwEvDXmJ+Rnz+XrN1x55xoRFE2hRrwU3RN/gkfuLiIiIiIiUS0wM7N5NR1djAA0xr8XKUoy6CLjJNM31pmnmmKa5Hrit6LxI1RQfbx2HDSPjcAbztsxjTMwYWzuG7uh2B12Cu/Dn+D+TlZfl1nuv2r2K+PR4Hoh9AF8vX7feW0REREREpEKKhphH7MwF0BDzWqwsxahsoOlp55oAOe6LI+Jmc+eCYUDr1nyR8gUAN3a+0dZIXk4v3rnoHTIOZ/DGwjfceu8JiyZQx6cOY3uMdet9RUREREREKiwmBoCQzftw4NAQ81qsLMWoj4B4wzDGGYZxsWEY44CfgQ89E02kgnJyYN48GD4cl8vF1FVT6de6H+2C7N8AclDbQVzT6RpeW/Aa249sd8s9dxzdwRcpX3B719tpFNDILfcUERERERFxm+bNoXFjvNeso3WD1qQf0jK92qosxaiXgdeAa4E3i47/V3RepOpJTITjx2HYMDYd2sSavWuq1Bylvw//OwWFBTzxyxNuud/7Se+TX5jPw3EPu+V+IiIiIiIibuVwWEv1ioaYqzOq9vIu7YWmabqAT4o+RKq++Hhr+9ALLiBh078BuKDtBfZmOklYUBiP9nmUV+a/wn297iOuVVy575WZm8nE5Ilc3elqwhuFuzGliIiIiIiIG8XEwOTJhDcYxX82/mB3GrFJWTqjMAzjdsMw4g3DWF10vMMwDO0dL1XT3LkQGwsNGpCQkUCQfxCRTSPtTnWKvw74KyGBITw0+yEKXYXlvs/kFZM5mH2QR/s86sZ0IiIiIiIibhYdDceO0S23MXsy93As95jdicQGpS5GGYbxf8BfgO+APxcdHwNe90w0kQo4eBCWLIHhwwFIyEigX2g/nI4y1V89LtA3kFeHvkrS9iSmrpxarnvszdzLm4vepHfL3vRp1cfNCUVERERERNyoaIh5zF6rryX9oOZG1UZl+c78VmCoaZoTTdP80TTNicAI4DaPJBOpiN9+g8JCGDaMPZl7WL9/PQNCB9idqkQ3dbmJuFZx3DnrTt5c+CYul6vUX7tk+xJ6fNiDHUd38PKQl3E41KgoIiIiIiJVWHQ0AGFbrY4ozY2qncpSjDpa9HH6uSPuiyPiJvHxEBgIcXHMz5gPUGWLUU6Hk59u/InLIy7nsfjHuGL6Few/vv+8X/fxso/p/2l/HA4HC25fwNB2QyshrYiIiIiISAXUrw+hoTTbtBtQZ1RtVZZi1NvAd4ZhDDcMo5NhGCOAr4G3DMNod+LDMzFFymjuXBg0CHx8SNiSgL+3Pz1a9LA71Vk19G/It6O+5d2L32VO2hy6fdCNhVsXlnhtTn4Od8+6mztn3cnANgNZOnZplf69iYiIiIiInCImBt81JkH+QaQdVGdUbVSWYtQ7wGDgZ2A1MBsYCvwD2Fj0scHdAUXKbMsW2LABhg0DYP7W+fRu2RtfL1+bg52bw+Hg/tj7WXj7Qny9fBn46UBen//6KYPNtx7eysDJA/lw2Yc80e8JZt84myZ1mtiYWkREREREpIxiYmDdOiLqtVVnVC3lXdoLTdOsWpOfRc5m7lzrOHw4x3KPsXzncv7a/6/2ZiqDHi16sHTsUsb+MJYnfnmCeVvm8dlVn5G6J5Xrv7merPwsvh31LSM7jbQ7qoiIiIiISNlFR0N+Pv2zmzGzQJ1RtVGpi1EnGIYRCrQEtpmmudX9kUQqKD4eQkIgMpJF6XMpcBUwoE3VnBd1Ng38GzD9mukMbjuYh2c/TNQ/oziQdYAOjTvw/fXf07FJR7sjioiIiIiIlE/REPMeB/x5x28z+YX5eDvLXJ6QaqzU3U6GYYQYhjEPazned0CaYRi/G4bRwmPpRMqqsBB++cVaoudwMD9jPk6Hk7hWcXYnKzOHw8G4nuNIvDOR5oHNuTbyWpLuTFIhSkREREREqjfDAKcTY3cB+YX5bDuyze5EUsnKsvRuIrASCDJNMwQIApYD//JEMJFyWbkS9u0rnheVkJFA1+Zdqe9X3+Zg5de1eVdW3bOK6ddOp55fPbvjiIiIiIiIVIy/P4SH02rrYQDSDmipXm1TlmJUf+BR0zQzAYqOjwN9PRFMpFxOzIsaNozcglwStyUyILR6LdETERERERGp8aKiCErfDqAd9WqhshSjDgKRp50zgEPuiyNSQfHxEBkJLVqwbOcysvKz6B/a3+5UIiIiIiIicrKoKLzTt1C30Fs76tVCZZkQ9n/AXMMwPga2AG2A24CnPRFMpMxyciAhAe6+G4D5GfMB1BklIiIiIiJS1URF4SgoYEhuG3VG1UKl7owyTXMScD3QBLi86DjaNM0PPZRNpGyWL4fsbBhgFZ8SMhLo0KgDwYHBNgcTERERERGRU0RFAdD3aEPNjKqFStUZZRiGF/AJMNY0zV89G0mknBYtso59+lDoKmR+xnyuNK60N5OIiIiIiIicqWhHvS77fXj14HpcLhcOh8PuVFJJStUZZZpmATACKPRsHJEKSEyE0FBo0YJ1+9ZxIOuAluiJiIiIiIhURX5+0L497XfmcCTnCAeyDtidSCpRWQaYvwU8bxiGj6fCiFTIokUQFwdAwpYEAAa0UTFKRERERESkSoqKImTLfgANMa9lylKMegD4M3DUMIythmFknDh6KJtI6W3fDlu3Qp8+gDUvKrhuMOFB4TYHExERERERkRJFRVE3Yxd+eWiIeS1Tlt30xngshUhFLV5sHYs6o+ZnzGdAmwFacywiIiIiIlJVRUXhKCzE2I+GmNcyZemMWgQMBT4Cfiw6DgMWeyCXSNksWgS+vtCtG1sPb2XL4S2aFyUiIiIiIlKVFe2o1+9IAy3Tq2XKUoyaCAwBHgR6FR0HAf/0QC6RsklMhO7dwc+PhIyieVEqRomIiIiIiFRdERHg5UXvw/W0TK+WKcsyvauAcNM0DxV9vsYwjMXARuB2tycTKa3cXEhOhnHjAGt4eT3fenQO7mxzMBERERERETkrPz/o0IGovZkqRtUyZemM2gXUOe1cALDTfXFEymHVKsjOLh5ePn/rfPq27ouX08vmYCIiIiIiInJOkZGE7chk+5HtZOdn251GKklZOqOmArMNw3gX2Aa0Bu4DphiGMeTERaZp/ureiCLnkZhoHePiOJB1gNQ9qdwQdYO9mUREREREROT8oqII+vf3+Oa52HxoMx2bdLQ7kVSCshSj7i46Pnna+XFFHwAuoF1FQ4mUyaJFEBICrVuzYP0PAPQP7W9zKBERERERETmvqCichS467oP0g+kqRtUSpS5GmaYZ5skgIuWWmGgt0XM4mJ8xHx+nD7EtY+1OJSIiIiIiIudTtKNe1F5IO6C56QdUnQAAIABJREFUUbVFWWZGiVQ9e/ZAejrExQGQkJFAr5a9CPAJsDmYiIiIiIiInFdEBC5vb7ru99EQ81pExSip3k7Mi+rTh6y8LJJ3JNO/tZboiYiIiIiIVAu+vjg6dKDnQX/SD6bbnUYqiYpRUr0lJoK3N3TvTtL2JPIK8xjQZoDdqURERERERKS0oqIw9hSqM6oWUTFKqrdFi6BLF6hTh4SMBAD6te5ncygREREREREptchImu/OZMeeNApdhXankUqgYpRUX/n5sGSJNbwca15UdLNoggKCbA4mIiIiIiIipRYVhdMFbXflsOvYLrvTSCVQMUqqr9WrITMT4uIodBWSuC1R86JERERERESqmxM76u3Rjnq1hYpRUn0tWmQd+/Rhw/4NHMk5QmzLWHsziYiIiIiISNl06IDL25uovWhuVC2hYpRUX4mJ0LQphIWRvCMZgJ4tetocSkRERERERMrE1xdXRAei96Id9WoJFaOk+lq0COLiwOEgeUcyAd4BdGraye5UIiIiIiIiUkbOqGg67/NWZ1QtoWKUVE/798P69cXDy5N3JtMtpBveTm+bg4mIiIiIiEiZRUXR+kA+23dtsDuJVAIVo6R6SkqyjnFx5Bfms2znMnq16GVvJhERERERESmfyEicLvAyVYyqDVSMkupp0SJwOqFXL9btW8fxvOOaFyUiIiIiIlJdFe2o12LrIY7mHLU5jHiailFSPSUmQkwMBAZqeLmIiIiIiEh116EDhd5eRO3REPPaQMUoqX4KC2HxYmt4OZC8I5lA30AiGkfYHExERERERETKxceHnPC2RO1FQ8xrARWjpPpZuxaOHPljePmOZHqE9MDp0NtZRERERESkuvKK7kzUHkg7oGJUTafv3qX6SUy0jnFx5BXksWLXCi3RExERERERqeZ8O3el3SHYttO0O4p4mIpRUv0sWgRBQdChA6v3rianIEfFKBERERERkequaIh5/ppUm4OIp6kYJdVPYqI1L8rp1PByERERERGRmiIyEoCA9RpgXtOpGCXVy+HDsGZN8fDyJduX0NC/IeFB4TYHExERERERkQpp3558byfBm/eRX5hvdxrxIBWjpHpJSgKX64/h5TuT6dmiJw6Hw+ZgIiIiIiIiUiE+PhxpG0KnPS4yDmfYnUY8SMUoqV4SE8HhgNhYsvOzSdmdQs8QLdETERERERGpCfI7RhC1F9IPaqleTaZilFQvixZBp07QoAEpu1PIK8zTvCgREREREZEawq9zd8IOwZZtq+2OIh6kYpRUHy4XLF78xxI9DS8XERERERGpUep1t+YDZ65KtjmJeJKKUVJ9bNwIBw5A796AVYxqUqcJoQ1CbQ4mIiIiIiIi7uCMjrGOa9banEQ8ScUoqT6SkqzjiWKUhpeLiIiIiIjULOHh5Hk7Cdy41e4k4kEqRkn1kZQEdepAZCTH846zes9qDS8XERERERGpSby92dMqiJCM/bhcLrvTiIeoGCXVx+LF0KMHeHuzctdKClwFmhclIiIiIiJSwxzrEIqxq4D9WfvtjiIeomKUVA+5ubB8efESvSU7lgDQq2UvO1OJiIiIiIiIm7kiI2l7GDZtTbE7iniIilFSPaxaZRWkYmMBa3h5SGAILeq1sDmYiIiIiIiIuFOdrtb3fQeSE2xOIp6iYpRUDyeGl59UjNISPRERERERkZqnWZ9hAOSvWGZzEvEU78p6kGEYEcBnQGNgP3CzaZobTrvGC/gHcBHgAl4zTfOj064xgOXAP03TfKwysksVkJQEzZpBaChHc46ybt86boi+we5UIiIiIiIi4mb+HTpyzM+B3xrT7ijiIZXZGfUv4H3TNCOA94EPSrjmRqA90AHoAzxnGEbbEy8WFas+AP7t8bRStSxebHVFORws37UcFy51RomIiIiIiNRETiebWgXSdOMOu5OIh1RKMcowjGZAd+DLolNfAt0Nw2h62qXXA5NM0yw0TXMvVtHpupNefwL4AVjv4chSlRw+DOvWFQ8vT96RDECPkB52phIREREREREP2d+hJW0zjoLLZXcU8YDKWqbXGthummYBgGmaBYZh7Cg6v/ek60KBLSd9nlF0DYZhdAYuBAYDT5cnRGpqanm+rEZaunSp3RFKrV5SEhHA+qAgji5dypzUOQT7B7PN3MY2ttkdT05Tnd5bUr3ovSWeoveWeIreW+JJen+Jp1SV99beliE0yF7Hwu+n49cmwu444maVNjOqIgzD8AEmAbcVFbLKdZ/o6Gj8/Pzcmq06Wrp0KT16VKOuojlzAIgYPRoaNSJ9YTp92/atXr+HWqLavbek2tB7SzxF7y3xFL23xJP0/hJPqUrvrexhF8PH/6PRoW10HDna7jhyFjk5OeVq/KmsmVFbgZZFM59OzH5qUXT+ZBlAm5M+Dy26JgQIB340DGMz8DBwl2EYH3o2tlQJSUnQoQM0asSh7ENsOLBB86JERERERERqsOZ9hgNwfOkim5OIJ1RKZ5RpmnsMw1gBjAamFR2XF82FOtnXWEWm77B23bsKGGiaZgbQ5MRFhmE8BwRqN71awOWyhpcPGQLA0h1Wy2ivFr3sTCUiIiIiIiIe1LZ1DOlB4JW6xu4o4gGVuZveOOABwzDWAw8UfY5hGD8ahnGizWUqkA5sABKBF0zTTK/EjFLVbN8OO3eeOby8RdVoHRURERERERH383J6sSm0Ho03aE5wTVRpM6NM01wH9C7h/CUn/boAuKcU93rOreGk6kpKso6xsQAk70ymXVA7GgU0sjGUiIiIiIiIeNr+Dq1osWotHD8OderYHUfcqDI7o0TKLikJfHygSxfA6ozSvCgREREREZGaryA6CqcLclcsszuKuJmKUVK1JSVZhSh/f/Yd38fmQ5vpGaJilIiIiIiISE1Xt1dfAPYm/mJzEnE3FaOk6ioogCVLiudFnRhers4oERERERGRmq9VlwEc9YWsZYvtjiJupmKUVF3r1sGxY3/MiyoaXt49pLudqURERERERKQSRDTtSEoz8Elda3cUcTMVo6TqKmF4eUTjCBr4N7AxlIiIiIiIiFSGQN9A0lvXpcnGHeBy2R1H3EjFKKm6kpKgfn2IiABgyfYl9GrRy+ZQIiIiIiIiUlkORoRSNzMXtm61O4q4kYpRUnUlJUGvXuB0svPoTrYf3a55USIiIiIiIrVIQXQUAK6VK21OIu6kYpRUTVlZsGrVH8PLd2p4uYiIiIiISG0T2KMPAEeSEmxOIu6kYpRUTcuXQ37+KcPLnQ4nXZt3tTmYiIiIiIiIVJbwtt1IbwhZy5LsjiJupGKUVE2nDy/fkUynJp0I9A20MZSIiIiIiIhUpk5NO7EqGPxWa0e9mkTFKKmakpKgVSsICcHlcpG8I1lL9ERERERERGqZ4LrBmC39aLB1Lxw/bncccRMVo6RqSkoq7orafnQ7uzN3qxglIiIiIiJSyzgcDg5FhOIsdMHq1XbHETdRMUqqnn37IC2teHh58o5kQMPLRUREREREaqOCztHWL1atsjeIuI2KUVL1LFliHU+aF+Xt9KZLcBcbQ4mIiIiIiIgdGkf14pgP5CxbYncUcRMVo6TqSUoChwN69ABgyY4lRDeLJsAnwOZgIiIiIiIiUtk6NoskJVjFqJpExSipepKSIDIS6tX7Y3h5iJboiYiIiIiI1EYdm3S0dtRbY4LLZXcccQMVo6RqcblOGV6++dBmDmQd0LwoERERERGRWqpdUDtSQ5z4HcmEbdvsjiNuoGKUVC2bNlkDzDW8XERERERERAAfLx8OdmhtfaIh5jWCilFStSQlWceThpf7evkS3SzaxlAiIiIiIiJiq5gY67hypb05xC1UjJKqJSkJ/P0h2io+Je9MpnNwZ/y8/WwOJiIiIiIiInYJDY1hU0MoXLnC7ijiBipGSdWSlATdu4OPD4WuQpbuWKrh5SIiIiIiIrVcxyYdWRkMecuX2h1F3EDFKKk68vJg2bLiJXppB9I4nHNY86JERERERERquU5NOrEqGHzTNkNWlt1xpIJUjJKqY8UK6w+VPn0AWLJjCQC9WvayM5WIiIiIiIjYzGhisCoYHIWFsHq13XGkglSMkqpj4ULr2LcvYA0v9/f2J7JppI2hRERERERExG71/eqzK7yZ9Yl21Kv2VIySqmPBAggNhVatAKsY1a15N7yd3jYHExEREREREbsFGFFk+Tq1o14NoGKUVA0ul1WM6tcPgILCApbtXKZ5USIiIiIiIgKA0SyS1GAHLnVGVXsqRknVsGUL7NhRXIwy95tk5mWqGCUiIiIiIiKAtaPe8qYFuFautBoapNpSMUqqhhPzooqKUck7kgFUjBIRERERERHAKkatbA7Ogwdh+3a740gFqBglVcOCBRAYCNHRgFWMqutTF6OxYXMwERERERERqQo6NunIquCiT7RUr1pTMUqqhgULIC4OvK1h5ck7kuke0h0vp5fNwURERERERKQqaFmvJemt61qfaIh5taZilNjvyBFISSleopdfmM/yXcu1RE9ERERERESKORwOWrTqxK4m/uqMquZUjBL7LV4MhYXFxajVe1aTnZ9Nrxa9bA4mIiIiIiIiVUnxUj11RlVrKkaJ/RYsAKcTevcGNLxcREREREREStaxcUcWN87GZZqQnW13HCknFaPEfgsWQEwM/9/enUdXWd37H3+HhElAQOYwqQw74MQQCojzjDjbapUWW/1pq610FHu9bfV6r722Vr1qaaWtWrWtWqpXUMBgvQ4QRAGFCtYNygwVAZlUiCQ5vz+eYxocQch5SPJ+reUK2c9J8qHr6fLk497fh333BZIyqmXjlvTYr0fKwSRJkiRJe5OitkXM7Qh5lZUe1avFLKOUrvJymDmz6ogewOx/zmZg4UAa5Hl7SpIkSZL+pU+7PrzYOfvJCy+kmkWfn7/tK13z58M771SVUWXlZcx7cx7FnTyiJ0mSJEnaUY/WPfhnywZsbtMi2digWskySukqLU0+Hn44APPfms/2yu3Oi5IkSZIkfUTjgsYcuF8PXu2xr2VULWYZpXSVlkJhIXTvDji8XJIkSZL06YraFlHauRwWL4a1a9OOo8/BMkrpKi1Njujl5QFJGdWmaRv2b7V/urkkSZIkSXulPm37MGm/9cknzo2qlSyjlJ6VK2H58h2Gl89aPYviwmLysuWUJEmSJEnVFbUtYmaHcjL5+R7Vq6Uso5SeGTOSj9l5UVu3b2X+W/M9oidJkiRJ+kRFbYvY2gg2Fe1vGVVLWUYpPaWlsM8+0K8fAPPWzKMiU2EZJUmSJEn6REVtiwBYEtrDiy9CRUXKibSrLKOUntJS+MIXoGFDwOHlkiRJkqTP1rppazo068CcrgWwZQv84x9pR9IusoxSOt59F+bO/ci8qA7NOtC5RecUg0mSJEmS9naHdTyMx/bLPknPo3q1jmWU0vHBVsrsvCiA6cunc3jXwx1eLkmSJEn6VMWdipnMIjKtW1tG1UKWUUpHaWnycehQAFZvWc3iDYs5otsRKYaSJEmSJNUGgzoPojxTwcZ+RZZRtZBllNJRWgoHHQStWwPJriiAI7sdmWYqSZIkSVIt8MGs4YU9W8Orr8LmzSkn0q6wjFLuVVbC88/vMC9q2rJpNGvYjP6d+qcYTJIkSZJUG3Ru0ZkOzTrwXOH7kMnArFlpR9IusIxS7r36KmzatOO8qBXTGdJlCAUNClIMJkmSJEmqDfLy8iguLOaR5iuTBY/q1SqWUcq9D+ZFZXdGbdq2iXlvzvOIniRJkiRppxUXFvPiewupLAqWUbWMZZRyr7QU2reHHj0AmLFiBhkyDi+XJEmSJO204sJiKjOVrD3kwKSMymTSjqSdZBml3JsxI9kVlZcHJMPL8/PyGdJlSMrBJEmSJEm1xQdDzF85oBmsWweLF6ecSDvLMkq5tWYNvPHGDvOipi2fxoBOA2jWqFmKwSRJkiRJtUnH5h3psm8XnurwbrLgUb1awzJKufWheVFl5WW8uOpF50VJkiRJknZZcWExE/Jfh2bNLKNqEcso5VZpKTRuDAMGADB79WzKKso4srtllCRJkiRp1xR3KuYfGxdRPrC/ZVQtYhml3JoxAwYNSgopknlRAMO6DkszlSRJkiSpFvpgbtSqvl1h7lzYujXlRNoZllHKnXffhTlzqo7oQTIvqqhtEe2atUsxmCRJkiSpNvqgjJrTvSGUl8PLL6ecSDvDMkq589xzsH07HHccAJWZSkpXlHJE1yNSDiZJkiRJqo3a7NOGA1odwJQ2G5IFj+rVCpZRyp2SEmjSBI5M5kMteGsBG7dtdF6UJEmSJOlzKy4s5qn35kP37pZRtYRllHKnpASOPhqaNgWSI3oAR3RzZ5QkSZIk6fMpLixmycYllA1yiHltYRml3Fi+HF57DU4+uWpp+vLpFLYo5IBWB6QYTJIkSZJUm30wN2pJ6AArVsCqVSkn0mexjFJuTJ2afDzpJAAymQzTlk/jyG5HkpeXl2IwSZIkSVJtNqDTAABmdskuvPBCemG0UyyjlBslJdC5M/TtC8CyTctYuXmlR/QkSZIkSbulVZNW9G7Tm0nNV0OjRh7VqwUso1Tzysvhb39Ljuhld0FNXz4dgCO7ObxckiRJkrR7iguLmbn2Zejf351RtYBllGre7NmwcWPVET2AacumsW/jfTm4/cEpBpMkSZIk1QXFnYpZuXkl7w48BGbNSjZFaK9lGaWaV1KS7Ig64YSqpekrpjOs6zDyG+SnGEySJEmSVBd8MMQ89mwNW7fCK6+knEifpiBXPyiE0Bu4F2gDrAdGxRgXfeg1+cDtwClABrgxxvj77LWfAF8GyrP/XBNjLMlVfu2GkhIYNAjatAFg/XvreXXtq3zlkK+kHEySJEmSVBf079SfPPKY1vF9BkAyN6p//7Rj6RPkcmfUncDYGGNvYCww7mNeMxLoCfQChgLXhRD2z157ERgUYzwMuBh4KITQtMZTa/ds3Jic1612RO+DeVEOL5ckSZIk7QnNGzWnT7s+/C3zOrRv7xDzvVxOyqgQQntgAPBAdukBYEAIod2HXno+8LsYY2WMcS3wKPAlgBhjSYzxvezr/g7kkeyy0t7sqaegsjIZXp41ffl0GuU3YlDnQSkGkyRJkiTVJYMKBzFr9WwyQ4ZYRu3lcnVMryuwKsZYARBjrAghrM6ur632um7AsmqfL8++5sNGAW/EGFfuSoj58+fvUui6bM6cOTn5Od3+9Cf2a9aMuQ0bQvZnPvGPJ+izbx8WzFuQkwzKrVzdW6p/vLdUU7y3VFO8t1STvL9UU2rzvdW+vD1r3l3Dwo6tCRMXMvepp6ho1SrtWPoYOZsZtaeEEI4G/hM4cVe/9uCDD6Zx48Z7PlQtM2fOHAYOHFjzPyiTSQqok05i4ODBALy3/T1em/waPxz6w9xkUE7l7N5SveO9pZrivaWa4r2lmuT9pZpS2++t7R22c9OCm1hzdCD8Fvq9/TYcf3zaseq0srKyz7XxJ1czo1YAnbMDyj8YVF6YXa9uOdC92ufdqr8mhDAU+CNwVowx1mhi7b6FC2H58h3mRb2w8gXKK8udFyVJkiRJ2qMO63AY+Xn5/K3dFmjdGiZPTjuSPkFOyqgY41vAXOCC7NIFwMvZuVDVjQcuDSE0yM6TOgt4GCCEMAh4CPhijPGlXOTWbirJPuzwQ/Oi8shjWLdhKYWSJEmSJNVFTRs25eD2B/PimpeSTRFTpiQzjLXXyeXT9L4JXBlCWAhcmf2cEMLkEEJx9jX3A4uBRcBM4PoY4+LstV8DTYFxIYS52X8OyWF+7aqSEujVCw44oGpp2vJpHNLhEFo18dyuJEmSJGnPSoaYzyIzfDisWQMvv5x2JH2MnM2MijG+Bgz+mPVTq/25Arj8E77eR6/VJmVl8Mwz8PWvVy2VV5bz/MrnGXXoqPRySZIkSZLqrOLCYn7/8u9ZPrRvMgNoyhSoxXOw6qpc7oxSfVJaCu+9t8MRvXlvzuOd99/hyO5HphhMkiRJklRXFRcmB69e3L4UBg1ybtReyjJKNaOkBBo2hGOPrVp6btlzAA4vlyRJkiTViIPbH0yj/EbMXj0bTj0VZs6EdevSjqUPsYxSzZg6FQ4/HJo3r1qatGgSRW2L6LJvlxSDSZIkSZLqqsYFjTm0w6HM/udsGD4cMpnk91PtVSyjtOetWQNz5+5wRG/jto08u+xZzgxnphhMkiRJklTXFXcqZs7qOVQOHABt2yZzo7RXsYzSnvdB61ytjJqyaArlleWcEc5IKZQkSZIkqT4Y1HkQm8o28fqmJXDKKfDEE1BRkXYsVWMZpT2vpATatYN+/aqWJi6cSPtm7Rnc+SMPVJQkSZIkaY/5YIh51dyodetg9uyUU6k6yyjtWZWV8OSTcOKJ0CC5vd6veJ/JiyZzWq/TyG+Qn3JASZIkSVJd1rddX5o1bMa0ZdPgpJOS3019qt5exTJKe9a8efDWWzsc0Xt26bNsLtvMmUXOi5IkSZIk1ayCBgWc2ONEJr8+mcx++8HgwZZRexnLKO1ZJSXJxxNPrFqaGCfStKApJxx4QkqhJEmSJEn1yYheI1i+aTkL1i5IjurNnp08bEt7Bcso7VlTp8Khh0KnTgBkMhkmxAmc2ONE9mm4T8rhJEmSJEn1wam9TgXg8YWPJ2UU/GvzhFJnGaU9Z8MGmD59hyN689bMY8XmFZwZPKInSZIkScqNwhaF9O/Yn0mLJiUP1+rY0aN6exHLKO0548fD9u1w/vlVSxNem0AeeYzoNSLFYJIkSZKk+mZErxHMWDGDt8s2wvDhyc6o8vK0YwnLKO1J990HffrAgAFVSxMXTmRo16F0aN4hxWCSJEmSpPpmRO8RVGYqKXm9JCmjNm6EmTPTjiUso7SnLF4MpaUwahTk5QGwYtMKXvrnS5zR+4yUw0mSJEmS6ptBhYNou0/b5KjeiSdCfj5MmZJ2LGEZpT3lj39MSqiRI6uWJsaJAJxZ5LwoSZIkSVJu5TfIZ3jP4Tzx+hNU7NsChg1zbtRewjJKuy+TSY7oHXssdO1atTxx4UR6t+lNUduiFMNJkiRJkuqrEb1GsH7rel5Y9ULyVL25c2HVqrRj1XuWUdp9M2fCG2/AV79atbRp2yaeXvK0R/QkSZIkSak5uefJ5OflM2nhpKSMAnjiiXRDyTJKe8B990HTpnDuuVVLJW+UsL1yu0f0JEmSJEmpadWkFcO6DUvmRh18MHTu7NyovYBllHZPWRk89BCcfTa0aFG1PCFOoO0+bRnaZWiK4SRJkiRJ9d2IXiOYt2YeK7esSnZHTZ0K27enHates4zS7pk8GTZs2OGI3vaK7UxeNJnTep9GfoP8FMNJkiRJkuq7Eb1GADB50eSkjNqyJXkavFJjGaXdc9990LEjnHBC1dK05dPYuG2j86IkSZIkSanr264v3Vt2T47qHX88NGzoU/VSZhmlz2/9epg0CS68EAoKqpYnvDaBJgVNOKnHSSmGkyRJkiQJ8vLyGNFrBH9b/De2NW0IRx1lGZUyyyh9fg89lJyzrXZEL5PJMHHhRE448ASaNWqWYjhJkiRJkhIjeo/gve3v8ezSZ5OjegsWJE+FVyoso/T53X8/HHIIHHZY1dIrb73C0o1LPaInSZIkSdprHLv/sTQtaJoc1Tv/fMjPh3Hj0o5Vb1lG6fNZtAhmzkx2ReXlVS1PjBMBOD2cnlYySZIkSZJ20LRhU44/8HgmLZpEprAQzjoL7roLtm5NO1q9ZBmlz+f++6FBAxg5coflCXECgzsPpmPzjikFkyRJkiTpo0b0GsHiDYuJ6yNccQW8/TaMH592rHrJMkq7rrIyKaOOPx4KC6uWV21exezVszkznJliOEmSJEmSPurUXqcCMGnhJDj2WCgqgrFjU05VP1lGadeVlsLSpTsMLgd4cP6DAJxZZBklSZIkSdq7dGvZjUPaH5LMjcrLS3ZHvfgizJ6ddrR6xzJKu+7++6FZMzj77Kql8spybn/xdo7qfhR92/VNMZwkSZIkSR9vRK8RTFs+jU3bNsGoUcnvtr/+ddqx6h3LKO2abdvgL3+Bc86B5s2rlv/3H//L8k3L+d6Q76UYTpIkSZKkTzai9wjKK8uZ+sZUaNkSvvIVeOCBZH6UcsYySrvmscdgU7ZBruaWmbfQo3UPTu/tU/QkSZIkSXunIV2G0LpJ6+SoHiRH9bZtg3vuSTdYPWMZpV1z//3J0PJjj61amrlyJjNXzuQ7g79DfoP8FMNJkiRJkvTJChoUcErPU5jy+hQqM5Vw6KFwxBHwm98kD+tSTlhGaee98QZMnpxsY8z/V+l068xbadm4JV/v//UUw0mSJEmS9NlG9BrBW+++xaxVs5KFK65Ift+dOjXdYPWIZZR23k9/Co0awXe/W7W0fNNyHn71YS4dcCnNGzX/lC+WJEmSJCl9w3sNp0lBE34757fJwrnnQvv2DjLPIcso7Zy//z0Z6vad70CnTlXLd7xwBwBXDr4yrWSSJEmSJO20/ZruxyX9L+H+v9/Pqs2rkk0Xl14Kjz8OS5emHa9esIzSzvn3f0+eNDBmTNXSlrIt/Pal3/LFvl+kW8tuKYaTJEmSJGnn/WDoD6jMVHLrzFuThW98A/LyYNy4dIPVE5ZR+mylpUlDPGYMtG5dtXzP3HvYXLaZ7w35XorhJEmSJEnaNQe0PoDzDz6fcXPGsWHrBujaFc44A37/eygrSztenWcZpU+XycA110CHDjB6dNVyRWUFt71wG0O7DGVwl8EpBpQkSZIkadeNOXwM77z/Dr+elZ0V9a1vwbp1MH58usHqAcsofbqSEnjuOfjJT6BZs6rlxxY+xuINi90VJUmSJEmqlQ7reBjDew7nthduY+v2rXDccdC7t4PMc8AySp+ssjLZFXXAAckwt2puef4Wurfsztl9zk4pnCRJkiRJu+fqYVez9r213DP3HmjQAK64Ap5/Hl5dyw6QAAAQ+0lEQVR+Oe1odZpllD7ZX/+a/B/wP/4jebpA1pzVc5i2fBqjB4+moEFBigElSZIkSfr8jup+FEO6DOGmGTdRXlkOF10E++zj7qgaZhmlj1denhzNO+gguPDCHS7dOvNWmjdqziX9L0kpnCRJkiRJuy8vL4+rh13N0o1LGb9gPLRqBSNHwp/+BGvWpB2vzrKM0sf7wx9g4UK44QbIz69aXrV5FQ8teIhL+l9CyyYt08snSZIkSdIecEY4g6K2Rfy89OdkMhn4wQ+gogKuvDLtaHWWZZQ+atu25GjekCHJoy2rGTtrLBWVFYwePPoTvliSJEmSpNqjQV4Dxhw+hnlr5lHyRgmEANdemzxV75FH0o5XJ1lG6aN+8xtYuRJ+9jPIy6tafvf9d7lz9p2cVXQWB7Y+MMWAkiRJkiTtOSMPHUnnFp25cfqNycJVV0H//slA87ffTjdcHWQZpR1t2ZKUUCecAMceu8OlMU+OYcO2DVx1+FUphZMkSZIkac9rlN+I7w/9Ps8ue5aZK2dCw4Zw992wfj1873tpx6tzLKO0o1tugXXrkkKqmscXPs6vZ/+a7w/5PkO7Dk0pnCRJkiRJNePSAZfSuklrfl7682ShXz/40Y/gvvtgypR0w9UxllH6l/nz4aab4JxzYNCgquU176zh4gkXc2iHQ/nZ8T/7lG8gSZIkSVLt1KJxC7416Fs8+tqj/GPtP5LFH/8Y+vaFyy6DzZvTDViHWEYpsXYtnH467Lsv3HZb1XImk+HiiRezuWwzfz7nzzQuaJxiSEmSJEmSas7owaNpWtCUm2bclCw0bpwc11u9GsaMSTdcHWIZJSgrS3ZDvfkmTJgAXbpUXfrN7N8wedFkbjrxJg5qf1CKISVJkiRJqlntmrXj4v4X88e//5FF6xcli4MHJ3Ojxo2Dp59ON2AdYRlV32Uy8M1vwvTp8Ic/7HA879W1r/KDqT/glJ6n8O0vfDu9jJIkSZIk5cjVw66mReMWnPngmWzatilZvP566NkT/t//g3ffTTdgHWAZVd/dfHNSQl17LZx/ftVyWXkZIx8ZSfNGzbnnzHvIy8tLL6MkSZIkSTnStWVXHj7vYRa9vYgLHr6AisoK2GcfuOsuWLw4mSOl3WIZVZ899lhy5vVLX4Kf/nSHSz95+ifMfXMud59xNx2bd0wpoCRJkiRJuXfM/scw9tSxTHl9Clc9eVWyeNRRcMUVyZzlGTPSDVjLWUbVV6+8AhdeCAMGJDujGvzrVvi/Jf/HL2f8km8O/Canh9PTyyhJkiRJUkouG3gZo78wmltn3spdL92VLN54I3TtChdfDBs2pBuwFrOMqocK3n47eXJeixbJwPJ99qm69vbWtxn1v6Po3aY3N598c4opJUmSJElK180n38zJPU7m8kmX89yy55Lfo+++G5YsgcMPTz5ql1lG1TdlZfS46ipYswYmToTOnasuVVRWcNljl7Hm3TX86Zw/sU/DfT7lG0mSJEmSVLcVNCjgwS8+yIGtD+Tcv5zLkg1L4Pjj4cknk9+rhwyBWbPSjlnrWEbVJ9u2wcUX03zePLj3Xigurrq07r11nPrnU3n4Hw9zw3E3MLBwYIpBJUmSJEnaO7Rq0orHLniMisoKTn/gdDaXbU7mR82YkZw0OuaYZLOHdpplVH0xaxYMHAh//jOrLr8czjuv6tLMlTPpP64/zyx9hnGnjeOqw69KMagkSZIkSXuXXm168dfz/spr617jwocvTJ6wV1QEM2dC375w9tkwdmzaMWsNy6i6rqwMrrkGhg6FzZthyhTevOQSADKZDHe8cAdH3XMUBQ0KmHHxDC4beBl5eXkph5YkSZIkae9y3AHHccfwO5i0aBJjnhxDJpOBDh3gmWfgtNPg29+GH/4QKivTjrrXs4yqy2bPTnZD/fd/w0UXwfz5cMopAGwp28IFD1/A6CdGc3LPk3npspc8midJkiRJ0qe4fNDlfGvQt7hl5i0MvWsoM1bMgGbN4JFH4Mor4eab4fzzYevWtKPu1Syj6qKyMvjxj5NBahs2wOTJcNdd0LIlAG9seYNBvxvE+FfHc+PxNzLhyxNo3bR1yqElSZIkSdr73T78du458x6Wb1rOsLuHcd7481i8eRncdhvccgs8/HAyR+qJJ9wl9Qkso+qSTCY5rzpoENxwA3z1q7BgAQwfDsDGbRu5c/adXDT9IjZu28hTo57i6iOupkGet4EkSZIkSTujQV4Dvtbvayy6chHXHn0tkxZNos/YPlz15Bg2Xv51+OtfYcmS5Hfxnj3hxhuTJ++pii1Ebbd+PTz0EFx8MXTtmsyGWr8eHn+czN138+r21dxUehNH/+Fo2v6iLZdPupw+Lfvw8jde5pj9j0k7vSRJkiRJtVKzRs247pjrWPjthYw8ZCQ3P38zPW/vya+6rGb70sXw4IPQvTv8278lv69/+cvJfKlMJu3oqStIO4B20fbtye6nkhKYOjWZC5XJQOvWcMIJbD/uGJ79QnsmvPkEj9/+bZZuXArAYR0O4+phVzOi9wgarmlIpxadUv1rSJIkSZJUF3TetzN3n3k3oweP5vsl3+fKKVfy+MLHeeIrTyTzo157DcaNg3vvTTaThABjxiSbSuopy6ja5sQT4dlnIT8/mQl13XVw8slQXAz5+Vz66Ne497F7aVrQlBMOPIEfDfsRp/Y6la4tu1Z9izlvzUkvvyRJkiRJdVC/jv14atRTTF40mS3vb/nXhaIiuPVW+NnPYPx4uPPOZM7zqFFQUD9rmfr5t67NrrkGRo+G446DVq0+cnnMsDFccPAFHNX9KJo2bJpCQEmSJEmS6qe8vDxG9B7x8RebNk0KqFGjkhNOeXm5DbcXyVkZFULoDdwLtAHWA6NijIs+9Jp84HbgFCAD3Bhj/P1nXatXTjrpUy/3bdeXvu365iiMJEmSJEnaZfW4iILcDjC/ExgbY+wNjAXGfcxrRgI9gV7AUOC6EML+O3FNkiRJkiRJtUBOdkaFENoDA4ATs0sPAL8KIbSLMa6t9tLzgd/FGCuBtSGER4EvATd9xrXPkg/w/vvv75G/T11QVlaWdgTVUd5bqineW6op3luqKd5bqkneX6op3lvaFdV6lvxd+bpcHdPrCqyKMVYAxBgrQgirs+vVy6huwLJqny/Pvuazrn2WTgALFy7c9eR11Pz589OOoDrKe0s1xXtLNcV7SzXFe0s1yftLNcV7S59TJ+CNnX1xfRlgPgs4EvgnUJFyFkmSJEmSpLogn6SImrUrX5SrMmoF0DmEkJ/dFZUPFGbXq1sOdOdff4nqu6E+7dqnGjhwYBkw/fPHlyRJkiRJ0sfY6R1RH8jJAPMY41vAXOCC7NIFwMsfmhcFMB64NITQIITQDjgLeHgnrkmSJEmSJKkWyOXT9L4JXBlCWAhcmf2cEMLkEEJx9jX3A4uBRcBM4PoY4+KduCZJkiRJkqRaIC+TyaSdQZIkSZIkSfVELndGSZIkSZIkqZ6zjJIkSZIkSVLOWEZJkiRJkiQpZyyjJEmSJEmSlDOWUZIkSZIkScqZgrQDKHdCCL2Be4E2wHpgVIxxUbqpVNuFENoA9wM9gDLgdeAbMca1qQZTnRJCuBa4Djgkxjg/5TiqI0IITYBbgROAbcDzMcbL0k2luiCEcBrwn0AeyX/8vS7G+Ei6qVQbhRB+CZwL7E+1fwf6vl676+PuLd/XK5fcGVW/3AmMjTH2BsYC41LOo7ohA/wixhhijIcCbwA3ppxJdUgIYQAwBFiedhbVOb8gKaF6xxgPAX6Sch7VASGEPJJf5r4aY+wHfAW4N4Tg+259Ho8CRwHLPrTu+3rtro+7t3xfr5zxX4r1RAihPTAAeCC79AAwIITQLr1UqgtijG/HGJ+ptjQT6J5SHNUxIYTGJG+yryB5gyTtESGE5sAo4CcxxgxAjHFNuqlUh1QCLbN/bgX8M8ZYmWIe1VIxxukxxhXV13xfrz3h4+4t39crlyyj6o+uwKoYYwVA9uPq7Lq0R2T/q+/lwMS0s6jOuB74Y4xxSdpBVOf0IDnacm0IYXYI4ZkQwhFph1Ltly03zwMmhBCWkew+uCjdVKpjfF+vGuf7etU0yyhJe9IdwDvAr9IOotovhDAUGAT8Ou0sqpMKgAOBl2OMxcDVwCMhhH3TjaXaLoRQAPwbcGaMsTtwOvBQdjeeJNUWvq9XjbKMqj9WAJ1DCPkA2Y+F2XVpt2WHIPYCzvcogvaQo4EiYEkIYSnQBSgJIZyUZijVGcuAcrLHXGKMLwDrgN5phlKd0A8ojDGWAmQ/vgv0STWV6hLf16tG+b5euWAZVU/EGN8C5gIXZJcuIPmvwT4ZQbsthHADMBA4K8ZYlnYe1Q0xxhtjjIUxxv1jjPsDK4GTY4xTU46mOiDGuA54GjgRqp5M1Z7kyUHS7lgJdAkhBIAQQh+gI8kgYGm3+b5eNcn39cqVvEzGebD1RQihiOQRsK2BDSSPgI3pplJtF0I4CJgPLAS2ZpeXxBjPTi+V6qLs7qjTPnistbS7QggHAneTPBp9O/DvMcYp6aZSXRBCGAn8iGSQOcC1McZHU4ykWiqEcDtwDkmhuQ5YH2M8yPf12l0fd2+RzLvzfb1ywjJKkiRJkiRJOeMxPUmSJEmSJOWMZZQkSZIkSZJyxjJKkiRJkiRJOWMZJUmSJEmSpJyxjJIkSZIkSVLOWEZJkiRJkiQpZyyjJEmSakgI4Q8hhP9KO8enCSEsDSGckHYOSZJUf1hGSZIk1RO1oRyTJEl1n2WUJEmSJEmScqYg7QCSJEl7mxBCIXAHcBTwDnBrjPH2EMJ1QF9gG3A2sBy4KMY4O/t1/YG7gF7AZCCzEz/rGOCPwO3AD4EK4HLgfeB/gLbAL2OMP8u+vjHwc+C87Lf4C3B1jLGs2ve6Fbg6+72uiTHeE0K4DBgJZEII3wWejjGenv0e/UIItwDdgSeyf6dtu/g/myRJ0k5xZ5QkSVI1IYQGwGPAPKAzcDzw3RDCydmXnAE8CLQCJgK/yn5dI+BR4H5gP2A8cO5O/tiOQJPsz/sp8DvgK8BA4EjgpyGEA7Ov/XdgCNAPOAz4AvDjD32vltnvdQkwNoTQOsb4W+BPwC9ijM2rFVGQFFunAAcAhwJf28nckiRJu8wySpIkaUeDgHYxxutjjO/HGBeTlENfzl6fHmOcHGOsICmeDsuuDwEaAv8TY9weY/wrMGsnf+Z24IYY43aSoqstcFuMcUuMcQGwgKQkgmR30/UxxrdijGuB/wC++qHvdX02w2SSnV3hM37+7THG1THGt0mKuH47mVuSJGmXeUxPkiRpR92BwhDCxmpr+cA0YBnwZrX194AmIYQCoBBYFWOsfjRv2U7+zPXZcgtga/bjmmrXtwLNs38u/ND3XZZdq/69yj+UsTmf7sN/p8JPeqEkSdLusoySJEna0QpgSYyx14cvZGdGfZJ/Ap1DCHnVCqluwBt7ON9qksJsQbWfsXonv/YzZ1hJkiTVNMsoSZKkHb0IbA4hXE0yVPx9oA/Q9DO+7nmgHBgdQhhLMlvqC8DTezjfA8CPQwizSMqln5IMLd8Za4ADP/NVkiRJNciZUZIkSdVkj8udTjI3aQmwDvg9yVDwT/u694FzSIZ/bwDOBx6pgYj/BcwG/g68AryUXdsZdwF9QwgbQwiP1kA2SZKkz5SXybhbW5IkSZIkSbnhzihJkiRJkiTljDOjJEmSalgI4Rrgmo+5NC3GODzXeSRJktLkMT1JkiRJkiTljMf0JEmSJEmSlDOWUZIkSZIkScoZyyhJkiRJkiTljGWUJEmSJEmScub/A8+CNspMoncUAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1440x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#distribution of end_month\n",
    "plt.figure(figsize=(20,8))\n",
    "plt.title('Distributions of end_month')\n",
    "plt.ylabel('proportion')\n",
    "\n",
    "sns.distplot(df_successful['end_month'],color='green',hist=False)\n",
    "sns.distplot(df_failed['end_month'],color='red',hist=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Upon these initial visualization of data, we can see that comics, dance, and music seem to have the highest success rates while food, journalism, and technology seem to not do that well. When we compare the overall number of kickstarters in each category, we can see that dance is the least and music is the most popular category, both being the most successful categories. However, it seems that the amount of kickstarters did not effect the rate of successes and failures in each category. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For the next part of our analysis, we will try to search for differences between successful/failed kickstarters to help distinguish what attributes the successful starters had that the failed didn't."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "check how many unique main categories and sub categories there are："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "159"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df_kickstarters['sub_category'].unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "15"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df_kickstarters['main_category'].unique())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will drop some more columns:\n",
    "- For data on start/end dates of projects, we agreed that observing trends at the month level is best, so we will drop the more specific dates in \"launched_at\" and \"deadline\" columns. In addition, some of the columns have redundancy with regards to project funding start and end date. Start and end month is the most balanced.\n",
    "- The names of the Kickstarters are difficult to quantify and analyze sentiment with nltk as they often contain catchy phrases or made-up words to try to catch consumers' attention, so we will drop the \"name\" column as well.\n",
    "- Finally, as shown above, there are 159 sub categories which is a bit excessive to analyze; but there are only 15 main categories which is good for analysis（And also our hypothesis is on main_category）. So we will drop the sub categories."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_kickstarters.drop(columns=['launched_at', 'deadline', 'name', 'sub_category'], inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, we will create a function that will change our status (successful, failed) column into binary variables, with 1.0 being successful and 0.0 being failed. We believe that doing this will make data analysis a little faster."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "def convert_status(label):\n",
    "    if label == \"successful\":\n",
    "        return float(1.0)\n",
    "    else:\n",
    "        return float(0.0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_kickstarters['status'] = df_kickstarters['status'].apply(convert_status)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>main_category</th>\n",
       "      <th>duration</th>\n",
       "      <th>goal_usd</th>\n",
       "      <th>city</th>\n",
       "      <th>state</th>\n",
       "      <th>blurb_length</th>\n",
       "      <th>name_length</th>\n",
       "      <th>status</th>\n",
       "      <th>start_month</th>\n",
       "      <th>end_month</th>\n",
       "      <th>start_Q</th>\n",
       "      <th>end_Q</th>\n",
       "      <th>usd_pledged</th>\n",
       "      <th>goal_minus_pledge</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>games</td>\n",
       "      <td>16.0</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>Menasha</td>\n",
       "      <td>WI</td>\n",
       "      <td>14</td>\n",
       "      <td>7</td>\n",
       "      <td>1.0</td>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "      <td>Q4</td>\n",
       "      <td>Q4</td>\n",
       "      <td>6061.0</td>\n",
       "      <td>-4061.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>fashion</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>NY</td>\n",
       "      <td>21</td>\n",
       "      <td>7</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>Q2</td>\n",
       "      <td>Q3</td>\n",
       "      <td>1110.0</td>\n",
       "      <td>-10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>music</td>\n",
       "      <td>45.0</td>\n",
       "      <td>3500.0</td>\n",
       "      <td>Nashville</td>\n",
       "      <td>TN</td>\n",
       "      <td>15</td>\n",
       "      <td>6</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9</td>\n",
       "      <td>11</td>\n",
       "      <td>Q3</td>\n",
       "      <td>Q4</td>\n",
       "      <td>4807.0</td>\n",
       "      <td>-1307.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>technology</td>\n",
       "      <td>60.0</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>Troy</td>\n",
       "      <td>MI</td>\n",
       "      <td>15</td>\n",
       "      <td>4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>11</td>\n",
       "      <td>1</td>\n",
       "      <td>Q4</td>\n",
       "      <td>Q1</td>\n",
       "      <td>40368.0</td>\n",
       "      <td>-10368.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>music</td>\n",
       "      <td>30.0</td>\n",
       "      <td>7500.0</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>WA</td>\n",
       "      <td>11</td>\n",
       "      <td>4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Q1</td>\n",
       "      <td>Q1</td>\n",
       "      <td>7770.0</td>\n",
       "      <td>-270.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  main_category  duration  goal_usd       city state  blurb_length  \\\n",
       "0         games      16.0    2000.0    Menasha    WI            14   \n",
       "2       fashion      30.0    1100.0  Manhattan    NY            21   \n",
       "3         music      45.0    3500.0  Nashville    TN            15   \n",
       "4    technology      60.0   30000.0       Troy    MI            15   \n",
       "5         music      30.0    7500.0    Seattle    WA            11   \n",
       "\n",
       "   name_length  status  start_month  end_month start_Q end_Q  usd_pledged  \\\n",
       "0            7     1.0           10         11      Q4    Q4       6061.0   \n",
       "2            7     1.0            6          7      Q2    Q3       1110.0   \n",
       "3            6     1.0            9         11      Q3    Q4       4807.0   \n",
       "4            4     1.0           11          1      Q4    Q1      40368.0   \n",
       "5            4     1.0            1          2      Q1    Q1       7770.0   \n",
       "\n",
       "   goal_minus_pledge  \n",
       "0            -4061.0  \n",
       "2              -10.0  \n",
       "3            -1307.0  \n",
       "4           -10368.0  \n",
       "5             -270.0  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_kickstarters.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, we will analyze the means of failed and successful kickstarts for the quantitative variables (duration, goal, blurb length, name length, start and end months, and money pledged) using the groupby function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>duration</th>\n",
       "      <th>goal_usd</th>\n",
       "      <th>blurb_length</th>\n",
       "      <th>name_length</th>\n",
       "      <th>start_month</th>\n",
       "      <th>end_month</th>\n",
       "      <th>usd_pledged</th>\n",
       "      <th>goal_minus_pledge</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>status</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0.0</th>\n",
       "      <td>34.601601</td>\n",
       "      <td>81020.575093</td>\n",
       "      <td>19.247716</td>\n",
       "      <td>5.252334</td>\n",
       "      <td>6.442516</td>\n",
       "      <td>6.715932</td>\n",
       "      <td>1061.582359</td>\n",
       "      <td>79958.992734</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>30.845921</td>\n",
       "      <td>9380.515233</td>\n",
       "      <td>18.849873</td>\n",
       "      <td>6.073439</td>\n",
       "      <td>6.470154</td>\n",
       "      <td>6.804175</td>\n",
       "      <td>22060.336532</td>\n",
       "      <td>-12679.821299</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         duration      goal_usd  blurb_length  name_length  start_month  \\\n",
       "status                                                                    \n",
       "0.0     34.601601  81020.575093     19.247716     5.252334     6.442516   \n",
       "1.0     30.845921   9380.515233     18.849873     6.073439     6.470154   \n",
       "\n",
       "        end_month   usd_pledged  goal_minus_pledge  \n",
       "status                                              \n",
       "0.0      6.715932   1061.582359       79958.992734  \n",
       "1.0      6.804175  22060.336532      -12679.821299  "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_grouped = df_kickstarters.groupby('status').mean()\n",
    "df_grouped"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From this we get some key observations:\n",
    "- We see clearly that the goals of failed kickstarters were set exponentially higher than their successful counterparts.\n",
    "\n",
    "- There isn't any discerinble difference between start and end times, and blurb length.\n",
    "\n",
    "- Successful kickstarters had shorter durations\n",
    "\n",
    "- Obviously the successful kickstarters had a much higher pledge\n"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "calculate standard deviation of each factor's data(both failure and success):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>duration</th>\n",
       "      <th>goal_usd</th>\n",
       "      <th>blurb_length</th>\n",
       "      <th>name_length</th>\n",
       "      <th>start_month</th>\n",
       "      <th>end_month</th>\n",
       "      <th>usd_pledged</th>\n",
       "      <th>goal_minus_pledge</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>status</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0.0</th>\n",
       "      <td>12.701759</td>\n",
       "      <td>1.659378e+06</td>\n",
       "      <td>5.204079</td>\n",
       "      <td>2.666351</td>\n",
       "      <td>3.306609</td>\n",
       "      <td>3.328290</td>\n",
       "      <td>5577.869893</td>\n",
       "      <td>1.659339e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>10.607315</td>\n",
       "      <td>2.811928e+04</td>\n",
       "      <td>4.883005</td>\n",
       "      <td>2.640535</td>\n",
       "      <td>3.308368</td>\n",
       "      <td>3.336141</td>\n",
       "      <td>120522.291961</td>\n",
       "      <td>1.071039e+05</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         duration      goal_usd  blurb_length  name_length  start_month  \\\n",
       "status                                                                    \n",
       "0.0     12.701759  1.659378e+06      5.204079     2.666351     3.306609   \n",
       "1.0     10.607315  2.811928e+04      4.883005     2.640535     3.308368   \n",
       "\n",
       "        end_month    usd_pledged  goal_minus_pledge  \n",
       "status                                               \n",
       "0.0      3.328290    5577.869893       1.659339e+06  \n",
       "1.0      3.336141  120522.291961       1.071039e+05  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_std = df_kickstarters.groupby('status').std()\n",
    "df_std"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's take a further look into the differences in goal_usd between successful and failed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'Status')"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "my_colors = list(['r', 'b'])\n",
    "df_grouped.goal_usd.plot.bar(stacked=True, color=my_colors, figsize=(10,5))\n",
    "plt.title('Mean of goal_usd for Successful/Failed', fontsize=30)\n",
    "plt.ylabel('goal_usd', fontsize=18)\n",
    "plt.xlabel('Status', fontsize=18)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Compared to the successful kickstarters, the failed kickstarters had an increase of 763.71%\n",
      "in there USD goal amount\n"
     ]
    }
   ],
   "source": [
    "fail = df_grouped.loc[0, 'goal_usd']\n",
    "success = df_grouped.loc[1, 'goal_usd']\n",
    "percent = ((fail - success) / success) * 100\n",
    "\n",
    "print(\"Compared to the successful kickstarters, the failed kickstarters had an increase of \" \n",
    "      \"{0:.2f}\".format(percent) + \"%\\nin there USD goal amount\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we can see, a 736.38% increase in goal_usd for the failed kickstarters is a huge difference compared to the successful kickstarters.\n",
    "\n",
    "This clearly shows that part of what makes a successful kickstarter is likely setting a realistic goal for funding.  If people who are looking into kickstarters notice that you've set your goal for funding unreasonably high especially with respect to the details of your project, why would they waste time and effort into funding your kickstarter if they know your funding goal likely won't be met?  Perhaps it can also be an indicator that shows that you are naive to the business side of things, which can be seen as a red flag."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_success = df_kickstarters[df_kickstarters['status'] == 1 ]\n",
    "df_fail = df_kickstarters[df_kickstarters['status'] == 0 ]\n",
    "\n",
    "                  #len(df.goal_usd.unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fa984a70b70>"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_kickstarters.boxplot(column=['goal_usd'],by='status',showfliers=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It seems that the distributions are too nonnormal for statistical tests to work effectively. So instead, we decided to group the data by state and take the mean of the data by state to be analyzed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"8\" halign=\"left\">blurb_length</th>\n",
       "      <th colspan=\"2\" halign=\"left\">duration</th>\n",
       "      <th>...</th>\n",
       "      <th colspan=\"2\" halign=\"left\">status</th>\n",
       "      <th colspan=\"8\" halign=\"left\">usd_pledged</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>...</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>state</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AK</th>\n",
       "      <td>390.0</td>\n",
       "      <td>18.507692</td>\n",
       "      <td>4.900416</td>\n",
       "      <td>4.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>19.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>31.0</td>\n",
       "      <td>390.0</td>\n",
       "      <td>31.158974</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>390.0</td>\n",
       "      <td>6956.510051</td>\n",
       "      <td>16554.923549</td>\n",
       "      <td>0.0</td>\n",
       "      <td>228.2500</td>\n",
       "      <td>2462.530</td>\n",
       "      <td>6890.500</td>\n",
       "      <td>207289.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AL</th>\n",
       "      <td>867.0</td>\n",
       "      <td>19.269896</td>\n",
       "      <td>5.365492</td>\n",
       "      <td>3.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.00</td>\n",
       "      <td>31.0</td>\n",
       "      <td>867.0</td>\n",
       "      <td>32.076125</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>867.0</td>\n",
       "      <td>7154.891557</td>\n",
       "      <td>35664.385770</td>\n",
       "      <td>0.0</td>\n",
       "      <td>25.5000</td>\n",
       "      <td>801.000</td>\n",
       "      <td>4532.000</td>\n",
       "      <td>839145.79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AR</th>\n",
       "      <td>525.0</td>\n",
       "      <td>19.047619</td>\n",
       "      <td>5.589625</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.00</td>\n",
       "      <td>29.0</td>\n",
       "      <td>525.0</td>\n",
       "      <td>32.097143</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>525.0</td>\n",
       "      <td>5471.507886</td>\n",
       "      <td>21405.237878</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.0000</td>\n",
       "      <td>427.000</td>\n",
       "      <td>3031.000</td>\n",
       "      <td>413530.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AZ</th>\n",
       "      <td>2461.0</td>\n",
       "      <td>19.145469</td>\n",
       "      <td>5.075924</td>\n",
       "      <td>1.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.00</td>\n",
       "      <td>30.0</td>\n",
       "      <td>2461.0</td>\n",
       "      <td>32.576595</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2461.0</td>\n",
       "      <td>10063.050459</td>\n",
       "      <td>48958.919352</td>\n",
       "      <td>0.0</td>\n",
       "      <td>95.0000</td>\n",
       "      <td>1218.000</td>\n",
       "      <td>5562.000</td>\n",
       "      <td>902043.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CA</th>\n",
       "      <td>24826.0</td>\n",
       "      <td>18.967091</td>\n",
       "      <td>4.956358</td>\n",
       "      <td>1.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>31.0</td>\n",
       "      <td>24826.0</td>\n",
       "      <td>32.537420</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>24826.0</td>\n",
       "      <td>25430.887529</td>\n",
       "      <td>154740.272898</td>\n",
       "      <td>0.0</td>\n",
       "      <td>416.0000</td>\n",
       "      <td>3375.000</td>\n",
       "      <td>11998.000</td>\n",
       "      <td>8596474.58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CO</th>\n",
       "      <td>3188.0</td>\n",
       "      <td>19.141154</td>\n",
       "      <td>4.785007</td>\n",
       "      <td>3.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>30.0</td>\n",
       "      <td>3188.0</td>\n",
       "      <td>31.898369</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3188.0</td>\n",
       "      <td>10986.838416</td>\n",
       "      <td>47896.341427</td>\n",
       "      <td>0.0</td>\n",
       "      <td>215.0000</td>\n",
       "      <td>2012.515</td>\n",
       "      <td>6926.000</td>\n",
       "      <td>1027985.58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CT</th>\n",
       "      <td>1178.0</td>\n",
       "      <td>19.162988</td>\n",
       "      <td>4.977665</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.00</td>\n",
       "      <td>31.0</td>\n",
       "      <td>1178.0</td>\n",
       "      <td>32.618846</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1178.0</td>\n",
       "      <td>13395.562479</td>\n",
       "      <td>140074.210283</td>\n",
       "      <td>0.0</td>\n",
       "      <td>203.5000</td>\n",
       "      <td>1604.000</td>\n",
       "      <td>5546.000</td>\n",
       "      <td>3317658.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DE</th>\n",
       "      <td>290.0</td>\n",
       "      <td>19.093103</td>\n",
       "      <td>4.786980</td>\n",
       "      <td>3.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>30.0</td>\n",
       "      <td>290.0</td>\n",
       "      <td>34.179310</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>290.0</td>\n",
       "      <td>83808.959759</td>\n",
       "      <td>236211.091159</td>\n",
       "      <td>0.0</td>\n",
       "      <td>115.5000</td>\n",
       "      <td>2095.500</td>\n",
       "      <td>16013.750</td>\n",
       "      <td>1432637.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FL</th>\n",
       "      <td>6325.0</td>\n",
       "      <td>19.010435</td>\n",
       "      <td>5.291612</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.00</td>\n",
       "      <td>33.0</td>\n",
       "      <td>6325.0</td>\n",
       "      <td>33.317154</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6325.0</td>\n",
       "      <td>9701.414493</td>\n",
       "      <td>108594.669550</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.0000</td>\n",
       "      <td>475.000</td>\n",
       "      <td>3520.000</td>\n",
       "      <td>5333792.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GA</th>\n",
       "      <td>3449.0</td>\n",
       "      <td>19.140910</td>\n",
       "      <td>5.304791</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.00</td>\n",
       "      <td>33.0</td>\n",
       "      <td>3449.0</td>\n",
       "      <td>33.153958</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3449.0</td>\n",
       "      <td>11965.563224</td>\n",
       "      <td>101057.627966</td>\n",
       "      <td>0.0</td>\n",
       "      <td>27.0000</td>\n",
       "      <td>800.000</td>\n",
       "      <td>4792.000</td>\n",
       "      <td>3352208.89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HI</th>\n",
       "      <td>593.0</td>\n",
       "      <td>19.175379</td>\n",
       "      <td>4.838570</td>\n",
       "      <td>3.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>29.0</td>\n",
       "      <td>593.0</td>\n",
       "      <td>33.067454</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>593.0</td>\n",
       "      <td>8291.153002</td>\n",
       "      <td>16326.815229</td>\n",
       "      <td>0.0</td>\n",
       "      <td>117.0000</td>\n",
       "      <td>1643.000</td>\n",
       "      <td>8300.000</td>\n",
       "      <td>137385.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IA</th>\n",
       "      <td>689.0</td>\n",
       "      <td>19.174165</td>\n",
       "      <td>4.817166</td>\n",
       "      <td>3.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.00</td>\n",
       "      <td>30.0</td>\n",
       "      <td>689.0</td>\n",
       "      <td>31.748911</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>689.0</td>\n",
       "      <td>6974.418897</td>\n",
       "      <td>30204.374559</td>\n",
       "      <td>0.0</td>\n",
       "      <td>73.0000</td>\n",
       "      <td>1053.000</td>\n",
       "      <td>4151.000</td>\n",
       "      <td>595676.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</th>\n",
       "      <td>671.0</td>\n",
       "      <td>18.891207</td>\n",
       "      <td>4.988802</td>\n",
       "      <td>1.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>29.0</td>\n",
       "      <td>671.0</td>\n",
       "      <td>31.493294</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>671.0</td>\n",
       "      <td>7774.701326</td>\n",
       "      <td>23393.910169</td>\n",
       "      <td>0.0</td>\n",
       "      <td>135.5000</td>\n",
       "      <td>1250.000</td>\n",
       "      <td>5192.500</td>\n",
       "      <td>325952.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IL</th>\n",
       "      <td>5164.0</td>\n",
       "      <td>18.841402</td>\n",
       "      <td>4.959435</td>\n",
       "      <td>1.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>32.0</td>\n",
       "      <td>5164.0</td>\n",
       "      <td>32.339659</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5164.0</td>\n",
       "      <td>10094.629231</td>\n",
       "      <td>37210.331242</td>\n",
       "      <td>0.0</td>\n",
       "      <td>210.0000</td>\n",
       "      <td>2030.000</td>\n",
       "      <td>6746.250</td>\n",
       "      <td>1021583.52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IN</th>\n",
       "      <td>1553.0</td>\n",
       "      <td>19.007083</td>\n",
       "      <td>5.103120</td>\n",
       "      <td>2.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.00</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1553.0</td>\n",
       "      <td>32.529298</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1553.0</td>\n",
       "      <td>7163.167006</td>\n",
       "      <td>41132.131602</td>\n",
       "      <td>0.0</td>\n",
       "      <td>40.0000</td>\n",
       "      <td>656.000</td>\n",
       "      <td>3297.090</td>\n",
       "      <td>958792.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KS</th>\n",
       "      <td>614.0</td>\n",
       "      <td>19.141694</td>\n",
       "      <td>5.006142</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.00</td>\n",
       "      <td>30.0</td>\n",
       "      <td>614.0</td>\n",
       "      <td>32.778502</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>614.0</td>\n",
       "      <td>7078.960993</td>\n",
       "      <td>45961.090448</td>\n",
       "      <td>0.0</td>\n",
       "      <td>50.0000</td>\n",
       "      <td>792.000</td>\n",
       "      <td>4100.750</td>\n",
       "      <td>784577.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KY</th>\n",
       "      <td>989.0</td>\n",
       "      <td>18.952477</td>\n",
       "      <td>5.221682</td>\n",
       "      <td>2.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.00</td>\n",
       "      <td>31.0</td>\n",
       "      <td>989.0</td>\n",
       "      <td>32.509606</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>989.0</td>\n",
       "      <td>7135.818028</td>\n",
       "      <td>34872.945609</td>\n",
       "      <td>0.0</td>\n",
       "      <td>50.0000</td>\n",
       "      <td>1065.000</td>\n",
       "      <td>5411.000</td>\n",
       "      <td>823704.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LA</th>\n",
       "      <td>1163.0</td>\n",
       "      <td>19.361995</td>\n",
       "      <td>4.981083</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.00</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1163.0</td>\n",
       "      <td>32.346518</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1163.0</td>\n",
       "      <td>6092.371745</td>\n",
       "      <td>15689.588587</td>\n",
       "      <td>0.0</td>\n",
       "      <td>76.0000</td>\n",
       "      <td>1382.000</td>\n",
       "      <td>5759.270</td>\n",
       "      <td>276502.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MA</th>\n",
       "      <td>3869.0</td>\n",
       "      <td>18.795296</td>\n",
       "      <td>4.861629</td>\n",
       "      <td>1.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>30.0</td>\n",
       "      <td>3869.0</td>\n",
       "      <td>32.493926</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3869.0</td>\n",
       "      <td>17834.403913</td>\n",
       "      <td>86167.419780</td>\n",
       "      <td>0.0</td>\n",
       "      <td>680.0000</td>\n",
       "      <td>3128.000</td>\n",
       "      <td>9162.550</td>\n",
       "      <td>2344134.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MD</th>\n",
       "      <td>1902.0</td>\n",
       "      <td>19.241851</td>\n",
       "      <td>4.729770</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.00</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1902.0</td>\n",
       "      <td>32.927445</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1902.0</td>\n",
       "      <td>7366.308880</td>\n",
       "      <td>79843.410308</td>\n",
       "      <td>0.0</td>\n",
       "      <td>101.0000</td>\n",
       "      <td>1431.000</td>\n",
       "      <td>4810.500</td>\n",
       "      <td>3401361.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ME</th>\n",
       "      <td>701.0</td>\n",
       "      <td>19.269615</td>\n",
       "      <td>4.861811</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.00</td>\n",
       "      <td>30.0</td>\n",
       "      <td>701.0</td>\n",
       "      <td>31.831669</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>701.0</td>\n",
       "      <td>6907.744879</td>\n",
       "      <td>18378.617019</td>\n",
       "      <td>0.0</td>\n",
       "      <td>280.0000</td>\n",
       "      <td>2080.000</td>\n",
       "      <td>5912.000</td>\n",
       "      <td>348449.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MI</th>\n",
       "      <td>3048.0</td>\n",
       "      <td>19.054790</td>\n",
       "      <td>5.119954</td>\n",
       "      <td>1.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.00</td>\n",
       "      <td>32.0</td>\n",
       "      <td>3048.0</td>\n",
       "      <td>31.897310</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3048.0</td>\n",
       "      <td>6000.261522</td>\n",
       "      <td>31563.809588</td>\n",
       "      <td>0.0</td>\n",
       "      <td>95.0000</td>\n",
       "      <td>1127.000</td>\n",
       "      <td>4431.255</td>\n",
       "      <td>1509506.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MN</th>\n",
       "      <td>2567.0</td>\n",
       "      <td>19.273471</td>\n",
       "      <td>4.571508</td>\n",
       "      <td>3.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>33.0</td>\n",
       "      <td>2567.0</td>\n",
       "      <td>31.867160</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2567.0</td>\n",
       "      <td>13235.380651</td>\n",
       "      <td>126998.972606</td>\n",
       "      <td>0.0</td>\n",
       "      <td>461.0000</td>\n",
       "      <td>2550.000</td>\n",
       "      <td>7303.000</td>\n",
       "      <td>5764229.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MO</th>\n",
       "      <td>2022.0</td>\n",
       "      <td>19.216617</td>\n",
       "      <td>5.136779</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.00</td>\n",
       "      <td>30.0</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>32.454006</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2022.0</td>\n",
       "      <td>10448.566083</td>\n",
       "      <td>75586.059002</td>\n",
       "      <td>0.0</td>\n",
       "      <td>66.0000</td>\n",
       "      <td>1047.000</td>\n",
       "      <td>5004.000</td>\n",
       "      <td>2069100.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MS</th>\n",
       "      <td>359.0</td>\n",
       "      <td>19.181058</td>\n",
       "      <td>5.215799</td>\n",
       "      <td>1.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.00</td>\n",
       "      <td>28.0</td>\n",
       "      <td>359.0</td>\n",
       "      <td>31.771588</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>359.0</td>\n",
       "      <td>5613.886407</td>\n",
       "      <td>35237.227228</td>\n",
       "      <td>0.0</td>\n",
       "      <td>27.0000</td>\n",
       "      <td>455.000</td>\n",
       "      <td>2974.000</td>\n",
       "      <td>468281.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MT</th>\n",
       "      <td>497.0</td>\n",
       "      <td>18.989940</td>\n",
       "      <td>4.860752</td>\n",
       "      <td>3.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>31.0</td>\n",
       "      <td>497.0</td>\n",
       "      <td>30.478873</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>497.0</td>\n",
       "      <td>20571.721952</td>\n",
       "      <td>170294.407149</td>\n",
       "      <td>0.0</td>\n",
       "      <td>364.0000</td>\n",
       "      <td>2525.000</td>\n",
       "      <td>7699.000</td>\n",
       "      <td>2650310.88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NC</th>\n",
       "      <td>3032.0</td>\n",
       "      <td>19.209103</td>\n",
       "      <td>5.100036</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.00</td>\n",
       "      <td>34.0</td>\n",
       "      <td>3032.0</td>\n",
       "      <td>32.318931</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3032.0</td>\n",
       "      <td>6725.831046</td>\n",
       "      <td>23462.381878</td>\n",
       "      <td>0.0</td>\n",
       "      <td>51.0000</td>\n",
       "      <td>1156.000</td>\n",
       "      <td>5430.250</td>\n",
       "      <td>502188.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ND</th>\n",
       "      <td>153.0</td>\n",
       "      <td>18.699346</td>\n",
       "      <td>5.355869</td>\n",
       "      <td>4.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>29.0</td>\n",
       "      <td>153.0</td>\n",
       "      <td>31.209150</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>153.0</td>\n",
       "      <td>5238.114314</td>\n",
       "      <td>10447.875309</td>\n",
       "      <td>0.0</td>\n",
       "      <td>56.0000</td>\n",
       "      <td>970.500</td>\n",
       "      <td>5000.000</td>\n",
       "      <td>84258.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NE</th>\n",
       "      <td>418.0</td>\n",
       "      <td>18.576555</td>\n",
       "      <td>5.574877</td>\n",
       "      <td>3.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>30.0</td>\n",
       "      <td>418.0</td>\n",
       "      <td>31.708134</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>418.0</td>\n",
       "      <td>2595.624426</td>\n",
       "      <td>5416.120662</td>\n",
       "      <td>0.0</td>\n",
       "      <td>41.2500</td>\n",
       "      <td>637.000</td>\n",
       "      <td>2703.000</td>\n",
       "      <td>55731.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NH</th>\n",
       "      <td>580.0</td>\n",
       "      <td>19.179310</td>\n",
       "      <td>4.564516</td>\n",
       "      <td>3.0</td>\n",
       "      <td>16.75</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.25</td>\n",
       "      <td>30.0</td>\n",
       "      <td>580.0</td>\n",
       "      <td>31.356897</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>580.0</td>\n",
       "      <td>7988.041397</td>\n",
       "      <td>37667.224719</td>\n",
       "      <td>0.0</td>\n",
       "      <td>201.7500</td>\n",
       "      <td>1741.000</td>\n",
       "      <td>5084.000</td>\n",
       "      <td>609902.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NJ</th>\n",
       "      <td>2134.0</td>\n",
       "      <td>18.989222</td>\n",
       "      <td>5.130859</td>\n",
       "      <td>2.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.00</td>\n",
       "      <td>29.0</td>\n",
       "      <td>2134.0</td>\n",
       "      <td>32.970478</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2134.0</td>\n",
       "      <td>6453.470984</td>\n",
       "      <td>25476.758292</td>\n",
       "      <td>0.0</td>\n",
       "      <td>70.2500</td>\n",
       "      <td>1109.000</td>\n",
       "      <td>5243.000</td>\n",
       "      <td>687827.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NM</th>\n",
       "      <td>783.0</td>\n",
       "      <td>19.035760</td>\n",
       "      <td>5.012644</td>\n",
       "      <td>3.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>30.0</td>\n",
       "      <td>783.0</td>\n",
       "      <td>32.376756</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>783.0</td>\n",
       "      <td>6982.592286</td>\n",
       "      <td>23875.850831</td>\n",
       "      <td>0.0</td>\n",
       "      <td>160.5000</td>\n",
       "      <td>1501.000</td>\n",
       "      <td>5101.000</td>\n",
       "      <td>383153.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NV</th>\n",
       "      <td>1828.0</td>\n",
       "      <td>19.430525</td>\n",
       "      <td>4.646577</td>\n",
       "      <td>3.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.00</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1828.0</td>\n",
       "      <td>28.915755</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1828.0</td>\n",
       "      <td>11382.829092</td>\n",
       "      <td>85020.082995</td>\n",
       "      <td>0.0</td>\n",
       "      <td>102.7500</td>\n",
       "      <td>985.000</td>\n",
       "      <td>4013.750</td>\n",
       "      <td>2052791.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NY</th>\n",
       "      <td>15838.0</td>\n",
       "      <td>18.944437</td>\n",
       "      <td>4.885577</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>32.0</td>\n",
       "      <td>15838.0</td>\n",
       "      <td>32.548428</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>15838.0</td>\n",
       "      <td>14433.598141</td>\n",
       "      <td>66485.740477</td>\n",
       "      <td>0.0</td>\n",
       "      <td>700.0000</td>\n",
       "      <td>3728.505</td>\n",
       "      <td>10678.000</td>\n",
       "      <td>2950874.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OH</th>\n",
       "      <td>3462.0</td>\n",
       "      <td>19.088677</td>\n",
       "      <td>5.166675</td>\n",
       "      <td>1.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.00</td>\n",
       "      <td>35.0</td>\n",
       "      <td>3462.0</td>\n",
       "      <td>32.449451</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3462.0</td>\n",
       "      <td>6631.649393</td>\n",
       "      <td>23709.044263</td>\n",
       "      <td>0.0</td>\n",
       "      <td>50.0000</td>\n",
       "      <td>959.000</td>\n",
       "      <td>5044.000</td>\n",
       "      <td>598999.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OK</th>\n",
       "      <td>902.0</td>\n",
       "      <td>18.941242</td>\n",
       "      <td>5.273632</td>\n",
       "      <td>1.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.00</td>\n",
       "      <td>31.0</td>\n",
       "      <td>902.0</td>\n",
       "      <td>31.355876</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>902.0</td>\n",
       "      <td>3806.358914</td>\n",
       "      <td>9527.843897</td>\n",
       "      <td>0.0</td>\n",
       "      <td>51.0000</td>\n",
       "      <td>620.500</td>\n",
       "      <td>3095.000</td>\n",
       "      <td>117240.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OR</th>\n",
       "      <td>3468.0</td>\n",
       "      <td>18.839389</td>\n",
       "      <td>4.998054</td>\n",
       "      <td>2.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>29.0</td>\n",
       "      <td>3468.0</td>\n",
       "      <td>31.171857</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3468.0</td>\n",
       "      <td>11415.914625</td>\n",
       "      <td>46186.124336</td>\n",
       "      <td>0.0</td>\n",
       "      <td>481.0000</td>\n",
       "      <td>2852.000</td>\n",
       "      <td>8896.330</td>\n",
       "      <td>1559525.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PA</th>\n",
       "      <td>4324.0</td>\n",
       "      <td>19.002313</td>\n",
       "      <td>4.912229</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>31.0</td>\n",
       "      <td>4324.0</td>\n",
       "      <td>32.204672</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4324.0</td>\n",
       "      <td>8129.586075</td>\n",
       "      <td>38583.997256</td>\n",
       "      <td>0.0</td>\n",
       "      <td>180.7500</td>\n",
       "      <td>1651.000</td>\n",
       "      <td>5621.270</td>\n",
       "      <td>1193255.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RI</th>\n",
       "      <td>493.0</td>\n",
       "      <td>19.318458</td>\n",
       "      <td>4.907478</td>\n",
       "      <td>2.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.00</td>\n",
       "      <td>29.0</td>\n",
       "      <td>493.0</td>\n",
       "      <td>32.261663</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>493.0</td>\n",
       "      <td>13679.657890</td>\n",
       "      <td>85563.552444</td>\n",
       "      <td>0.0</td>\n",
       "      <td>365.0000</td>\n",
       "      <td>2013.000</td>\n",
       "      <td>6285.500</td>\n",
       "      <td>1363381.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SC</th>\n",
       "      <td>1072.0</td>\n",
       "      <td>18.798507</td>\n",
       "      <td>5.314434</td>\n",
       "      <td>2.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.00</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1072.0</td>\n",
       "      <td>31.969216</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1072.0</td>\n",
       "      <td>5308.228517</td>\n",
       "      <td>26935.085575</td>\n",
       "      <td>0.0</td>\n",
       "      <td>35.0000</td>\n",
       "      <td>933.330</td>\n",
       "      <td>4475.000</td>\n",
       "      <td>668343.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SD</th>\n",
       "      <td>169.0</td>\n",
       "      <td>18.508876</td>\n",
       "      <td>5.225986</td>\n",
       "      <td>2.0</td>\n",
       "      <td>15.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>31.0</td>\n",
       "      <td>169.0</td>\n",
       "      <td>30.390533</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>169.0</td>\n",
       "      <td>9194.031006</td>\n",
       "      <td>45544.630898</td>\n",
       "      <td>0.0</td>\n",
       "      <td>30.0000</td>\n",
       "      <td>1608.000</td>\n",
       "      <td>5051.000</td>\n",
       "      <td>513422.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TN</th>\n",
       "      <td>2647.0</td>\n",
       "      <td>19.178315</td>\n",
       "      <td>5.318284</td>\n",
       "      <td>1.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.00</td>\n",
       "      <td>32.0</td>\n",
       "      <td>2647.0</td>\n",
       "      <td>32.402720</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2647.0</td>\n",
       "      <td>10506.428285</td>\n",
       "      <td>61886.213042</td>\n",
       "      <td>0.0</td>\n",
       "      <td>196.5000</td>\n",
       "      <td>2157.000</td>\n",
       "      <td>7869.000</td>\n",
       "      <td>1806651.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TX</th>\n",
       "      <td>7780.0</td>\n",
       "      <td>18.936504</td>\n",
       "      <td>5.176790</td>\n",
       "      <td>1.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.00</td>\n",
       "      <td>32.0</td>\n",
       "      <td>7780.0</td>\n",
       "      <td>32.015810</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7780.0</td>\n",
       "      <td>11127.420251</td>\n",
       "      <td>66260.230068</td>\n",
       "      <td>0.0</td>\n",
       "      <td>62.0000</td>\n",
       "      <td>1251.000</td>\n",
       "      <td>6014.250</td>\n",
       "      <td>2045463.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UT</th>\n",
       "      <td>2248.0</td>\n",
       "      <td>18.750890</td>\n",
       "      <td>5.064185</td>\n",
       "      <td>1.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>31.0</td>\n",
       "      <td>2248.0</td>\n",
       "      <td>31.270018</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2248.0</td>\n",
       "      <td>24324.313732</td>\n",
       "      <td>93645.927138</td>\n",
       "      <td>0.0</td>\n",
       "      <td>330.0000</td>\n",
       "      <td>2391.000</td>\n",
       "      <td>10075.750</td>\n",
       "      <td>1500975.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VA</th>\n",
       "      <td>2602.0</td>\n",
       "      <td>19.029593</td>\n",
       "      <td>5.012661</td>\n",
       "      <td>1.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.00</td>\n",
       "      <td>31.0</td>\n",
       "      <td>2602.0</td>\n",
       "      <td>32.110300</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2602.0</td>\n",
       "      <td>8193.324939</td>\n",
       "      <td>56720.079190</td>\n",
       "      <td>0.0</td>\n",
       "      <td>72.5000</td>\n",
       "      <td>1090.000</td>\n",
       "      <td>5375.250</td>\n",
       "      <td>2232933.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VT</th>\n",
       "      <td>592.0</td>\n",
       "      <td>18.986486</td>\n",
       "      <td>4.876459</td>\n",
       "      <td>1.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>29.0</td>\n",
       "      <td>592.0</td>\n",
       "      <td>31.641892</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>592.0</td>\n",
       "      <td>9184.474611</td>\n",
       "      <td>33265.776705</td>\n",
       "      <td>0.0</td>\n",
       "      <td>967.6675</td>\n",
       "      <td>3315.000</td>\n",
       "      <td>9224.770</td>\n",
       "      <td>547566.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WA</th>\n",
       "      <td>4557.0</td>\n",
       "      <td>18.768269</td>\n",
       "      <td>4.899412</td>\n",
       "      <td>1.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>31.0</td>\n",
       "      <td>4557.0</td>\n",
       "      <td>31.349133</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4557.0</td>\n",
       "      <td>22585.231957</td>\n",
       "      <td>160678.453723</td>\n",
       "      <td>0.0</td>\n",
       "      <td>428.0000</td>\n",
       "      <td>2841.000</td>\n",
       "      <td>8761.000</td>\n",
       "      <td>3948547.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WI</th>\n",
       "      <td>1745.0</td>\n",
       "      <td>18.966189</td>\n",
       "      <td>5.060245</td>\n",
       "      <td>2.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.00</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1745.0</td>\n",
       "      <td>32.260172</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1745.0</td>\n",
       "      <td>6174.004436</td>\n",
       "      <td>24259.838146</td>\n",
       "      <td>0.0</td>\n",
       "      <td>120.0000</td>\n",
       "      <td>1250.000</td>\n",
       "      <td>4443.500</td>\n",
       "      <td>472897.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WV</th>\n",
       "      <td>306.0</td>\n",
       "      <td>19.281046</td>\n",
       "      <td>5.205870</td>\n",
       "      <td>3.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.00</td>\n",
       "      <td>31.0</td>\n",
       "      <td>306.0</td>\n",
       "      <td>33.464052</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>306.0</td>\n",
       "      <td>4487.371111</td>\n",
       "      <td>10744.044558</td>\n",
       "      <td>0.0</td>\n",
       "      <td>39.7500</td>\n",
       "      <td>720.500</td>\n",
       "      <td>3702.500</td>\n",
       "      <td>84707.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WY</th>\n",
       "      <td>163.0</td>\n",
       "      <td>18.883436</td>\n",
       "      <td>4.468536</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>26.0</td>\n",
       "      <td>163.0</td>\n",
       "      <td>32.877301</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>163.0</td>\n",
       "      <td>12653.748589</td>\n",
       "      <td>27134.015227</td>\n",
       "      <td>0.0</td>\n",
       "      <td>282.5000</td>\n",
       "      <td>3805.000</td>\n",
       "      <td>14463.750</td>\n",
       "      <td>179019.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>50 rows × 72 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      blurb_length                                                      \\\n",
       "             count       mean       std  min    25%   50%    75%   max   \n",
       "state                                                                    \n",
       "AK           390.0  18.507692  4.900416  4.0  16.00  19.0  22.00  31.0   \n",
       "AL           867.0  19.269896  5.365492  3.0  17.00  20.0  23.00  31.0   \n",
       "AR           525.0  19.047619  5.589625  1.0  17.00  20.0  23.00  29.0   \n",
       "AZ          2461.0  19.145469  5.075924  1.0  16.00  20.0  23.00  30.0   \n",
       "CA         24826.0  18.967091  4.956358  1.0  16.00  20.0  22.00  31.0   \n",
       "CO          3188.0  19.141154  4.785007  3.0  17.00  20.0  22.00  30.0   \n",
       "CT          1178.0  19.162988  4.977665  1.0  17.00  20.0  23.00  31.0   \n",
       "DE           290.0  19.093103  4.786980  3.0  16.00  20.0  22.00  30.0   \n",
       "FL          6325.0  19.010435  5.291612  1.0  17.00  20.0  23.00  33.0   \n",
       "GA          3449.0  19.140910  5.304791  1.0  17.00  20.0  23.00  33.0   \n",
       "HI           593.0  19.175379  4.838570  3.0  17.00  20.0  22.00  29.0   \n",
       "IA           689.0  19.174165  4.817166  3.0  17.00  20.0  23.00  30.0   \n",
       "ID           671.0  18.891207  4.988802  1.0  16.00  20.0  22.00  29.0   \n",
       "IL          5164.0  18.841402  4.959435  1.0  16.00  20.0  22.00  32.0   \n",
       "IN          1553.0  19.007083  5.103120  2.0  16.00  20.0  23.00  30.0   \n",
       "KS           614.0  19.141694  5.006142  1.0  17.00  20.0  23.00  30.0   \n",
       "KY           989.0  18.952477  5.221682  2.0  16.00  20.0  23.00  31.0   \n",
       "LA          1163.0  19.361995  4.981083  1.0  17.00  20.0  23.00  30.0   \n",
       "MA          3869.0  18.795296  4.861629  1.0  16.00  20.0  22.00  30.0   \n",
       "MD          1902.0  19.241851  4.729770  1.0  17.00  20.0  23.00  32.0   \n",
       "ME           701.0  19.269615  4.861811  1.0  17.00  20.0  23.00  30.0   \n",
       "MI          3048.0  19.054790  5.119954  1.0  16.00  20.0  23.00  32.0   \n",
       "MN          2567.0  19.273471  4.571508  3.0  17.00  20.0  22.00  33.0   \n",
       "MO          2022.0  19.216617  5.136779  1.0  17.00  20.0  23.00  30.0   \n",
       "MS           359.0  19.181058  5.215799  1.0  16.00  20.0  23.00  28.0   \n",
       "MT           497.0  18.989940  4.860752  3.0  16.00  20.0  22.00  31.0   \n",
       "NC          3032.0  19.209103  5.100036  1.0  17.00  20.0  23.00  34.0   \n",
       "ND           153.0  18.699346  5.355869  4.0  16.00  20.0  22.00  29.0   \n",
       "NE           418.0  18.576555  5.574877  3.0  16.00  20.0  22.00  30.0   \n",
       "NH           580.0  19.179310  4.564516  3.0  16.75  20.0  22.25  30.0   \n",
       "NJ          2134.0  18.989222  5.130859  2.0  16.00  20.0  23.00  29.0   \n",
       "NM           783.0  19.035760  5.012644  3.0  17.00  20.0  22.00  30.0   \n",
       "NV          1828.0  19.430525  4.646577  3.0  17.00  20.0  23.00  30.0   \n",
       "NY         15838.0  18.944437  4.885577  1.0  17.00  20.0  22.00  32.0   \n",
       "OH          3462.0  19.088677  5.166675  1.0  16.00  20.0  23.00  35.0   \n",
       "OK           902.0  18.941242  5.273632  1.0  16.00  20.0  23.00  31.0   \n",
       "OR          3468.0  18.839389  4.998054  2.0  16.00  20.0  22.00  29.0   \n",
       "PA          4324.0  19.002313  4.912229  1.0  17.00  20.0  22.00  31.0   \n",
       "RI           493.0  19.318458  4.907478  2.0  17.00  20.0  23.00  29.0   \n",
       "SC          1072.0  18.798507  5.314434  2.0  16.00  20.0  23.00  30.0   \n",
       "SD           169.0  18.508876  5.225986  2.0  15.00  20.0  22.00  31.0   \n",
       "TN          2647.0  19.178315  5.318284  1.0  16.00  20.0  23.00  32.0   \n",
       "TX          7780.0  18.936504  5.176790  1.0  16.00  20.0  23.00  32.0   \n",
       "UT          2248.0  18.750890  5.064185  1.0  16.00  20.0  22.00  31.0   \n",
       "VA          2602.0  19.029593  5.012661  1.0  16.00  20.0  23.00  31.0   \n",
       "VT           592.0  18.986486  4.876459  1.0  16.00  20.0  22.00  29.0   \n",
       "WA          4557.0  18.768269  4.899412  1.0  16.00  20.0  22.00  31.0   \n",
       "WI          1745.0  18.966189  5.060245  2.0  16.00  20.0  23.00  30.0   \n",
       "WV           306.0  19.281046  5.205870  3.0  17.00  20.0  23.00  31.0   \n",
       "WY           163.0  18.883436  4.468536  1.0  17.00  20.0  22.00  26.0   \n",
       "\n",
       "      duration                ...     status      usd_pledged                \\\n",
       "         count       mean     ...        75%  max       count          mean   \n",
       "state                         ...                                             \n",
       "AK       390.0  31.158974     ...        1.0  1.0       390.0   6956.510051   \n",
       "AL       867.0  32.076125     ...        1.0  1.0       867.0   7154.891557   \n",
       "AR       525.0  32.097143     ...        1.0  1.0       525.0   5471.507886   \n",
       "AZ      2461.0  32.576595     ...        1.0  1.0      2461.0  10063.050459   \n",
       "CA     24826.0  32.537420     ...        1.0  1.0     24826.0  25430.887529   \n",
       "CO      3188.0  31.898369     ...        1.0  1.0      3188.0  10986.838416   \n",
       "CT      1178.0  32.618846     ...        1.0  1.0      1178.0  13395.562479   \n",
       "DE       290.0  34.179310     ...        1.0  1.0       290.0  83808.959759   \n",
       "FL      6325.0  33.317154     ...        1.0  1.0      6325.0   9701.414493   \n",
       "GA      3449.0  33.153958     ...        1.0  1.0      3449.0  11965.563224   \n",
       "HI       593.0  33.067454     ...        1.0  1.0       593.0   8291.153002   \n",
       "IA       689.0  31.748911     ...        1.0  1.0       689.0   6974.418897   \n",
       "ID       671.0  31.493294     ...        1.0  1.0       671.0   7774.701326   \n",
       "IL      5164.0  32.339659     ...        1.0  1.0      5164.0  10094.629231   \n",
       "IN      1553.0  32.529298     ...        1.0  1.0      1553.0   7163.167006   \n",
       "KS       614.0  32.778502     ...        1.0  1.0       614.0   7078.960993   \n",
       "KY       989.0  32.509606     ...        1.0  1.0       989.0   7135.818028   \n",
       "LA      1163.0  32.346518     ...        1.0  1.0      1163.0   6092.371745   \n",
       "MA      3869.0  32.493926     ...        1.0  1.0      3869.0  17834.403913   \n",
       "MD      1902.0  32.927445     ...        1.0  1.0      1902.0   7366.308880   \n",
       "ME       701.0  31.831669     ...        1.0  1.0       701.0   6907.744879   \n",
       "MI      3048.0  31.897310     ...        1.0  1.0      3048.0   6000.261522   \n",
       "MN      2567.0  31.867160     ...        1.0  1.0      2567.0  13235.380651   \n",
       "MO      2022.0  32.454006     ...        1.0  1.0      2022.0  10448.566083   \n",
       "MS       359.0  31.771588     ...        1.0  1.0       359.0   5613.886407   \n",
       "MT       497.0  30.478873     ...        1.0  1.0       497.0  20571.721952   \n",
       "NC      3032.0  32.318931     ...        1.0  1.0      3032.0   6725.831046   \n",
       "ND       153.0  31.209150     ...        1.0  1.0       153.0   5238.114314   \n",
       "NE       418.0  31.708134     ...        1.0  1.0       418.0   2595.624426   \n",
       "NH       580.0  31.356897     ...        1.0  1.0       580.0   7988.041397   \n",
       "NJ      2134.0  32.970478     ...        1.0  1.0      2134.0   6453.470984   \n",
       "NM       783.0  32.376756     ...        1.0  1.0       783.0   6982.592286   \n",
       "NV      1828.0  28.915755     ...        1.0  1.0      1828.0  11382.829092   \n",
       "NY     15838.0  32.548428     ...        1.0  1.0     15838.0  14433.598141   \n",
       "OH      3462.0  32.449451     ...        1.0  1.0      3462.0   6631.649393   \n",
       "OK       902.0  31.355876     ...        1.0  1.0       902.0   3806.358914   \n",
       "OR      3468.0  31.171857     ...        1.0  1.0      3468.0  11415.914625   \n",
       "PA      4324.0  32.204672     ...        1.0  1.0      4324.0   8129.586075   \n",
       "RI       493.0  32.261663     ...        1.0  1.0       493.0  13679.657890   \n",
       "SC      1072.0  31.969216     ...        1.0  1.0      1072.0   5308.228517   \n",
       "SD       169.0  30.390533     ...        1.0  1.0       169.0   9194.031006   \n",
       "TN      2647.0  32.402720     ...        1.0  1.0      2647.0  10506.428285   \n",
       "TX      7780.0  32.015810     ...        1.0  1.0      7780.0  11127.420251   \n",
       "UT      2248.0  31.270018     ...        1.0  1.0      2248.0  24324.313732   \n",
       "VA      2602.0  32.110300     ...        1.0  1.0      2602.0   8193.324939   \n",
       "VT       592.0  31.641892     ...        1.0  1.0       592.0   9184.474611   \n",
       "WA      4557.0  31.349133     ...        1.0  1.0      4557.0  22585.231957   \n",
       "WI      1745.0  32.260172     ...        1.0  1.0      1745.0   6174.004436   \n",
       "WV       306.0  33.464052     ...        1.0  1.0       306.0   4487.371111   \n",
       "WY       163.0  32.877301     ...        1.0  1.0       163.0  12653.748589   \n",
       "\n",
       "                                                                      \n",
       "                 std  min       25%       50%        75%         max  \n",
       "state                                                                 \n",
       "AK      16554.923549  0.0  228.2500  2462.530   6890.500   207289.00  \n",
       "AL      35664.385770  0.0   25.5000   801.000   4532.000   839145.79  \n",
       "AR      21405.237878  0.0   14.0000   427.000   3031.000   413530.99  \n",
       "AZ      48958.919352  0.0   95.0000  1218.000   5562.000   902043.72  \n",
       "CA     154740.272898  0.0  416.0000  3375.000  11998.000  8596474.58  \n",
       "CO      47896.341427  0.0  215.0000  2012.515   6926.000  1027985.58  \n",
       "CT     140074.210283  0.0  203.5000  1604.000   5546.000  3317658.10  \n",
       "DE     236211.091159  0.0  115.5000  2095.500  16013.750  1432637.11  \n",
       "FL     108594.669550  0.0   17.0000   475.000   3520.000  5333792.84  \n",
       "GA     101057.627966  0.0   27.0000   800.000   4792.000  3352208.89  \n",
       "HI      16326.815229  0.0  117.0000  1643.000   8300.000   137385.00  \n",
       "IA      30204.374559  0.0   73.0000  1053.000   4151.000   595676.11  \n",
       "ID      23393.910169  0.0  135.5000  1250.000   5192.500   325952.00  \n",
       "IL      37210.331242  0.0  210.0000  2030.000   6746.250  1021583.52  \n",
       "IN      41132.131602  0.0   40.0000   656.000   3297.090   958792.00  \n",
       "KS      45961.090448  0.0   50.0000   792.000   4100.750   784577.00  \n",
       "KY      34872.945609  0.0   50.0000  1065.000   5411.000   823704.20  \n",
       "LA      15689.588587  0.0   76.0000  1382.000   5759.270   276502.17  \n",
       "MA      86167.419780  0.0  680.0000  3128.000   9162.550  2344134.67  \n",
       "MD      79843.410308  0.0  101.0000  1431.000   4810.500  3401361.08  \n",
       "ME      18378.617019  0.0  280.0000  2080.000   5912.000   348449.00  \n",
       "MI      31563.809588  0.0   95.0000  1127.000   4431.255  1509506.28  \n",
       "MN     126998.972606  0.0  461.0000  2550.000   7303.000  5764229.38  \n",
       "MO      75586.059002  0.0   66.0000  1047.000   5004.000  2069100.91  \n",
       "MS      35237.227228  0.0   27.0000   455.000   2974.000   468281.01  \n",
       "MT     170294.407149  0.0  364.0000  2525.000   7699.000  2650310.88  \n",
       "NC      23462.381878  0.0   51.0000  1156.000   5430.250   502188.90  \n",
       "ND      10447.875309  0.0   56.0000   970.500   5000.000    84258.42  \n",
       "NE       5416.120662  0.0   41.2500   637.000   2703.000    55731.41  \n",
       "NH      37667.224719  0.0  201.7500  1741.000   5084.000   609902.71  \n",
       "NJ      25476.758292  0.0   70.2500  1109.000   5243.000   687827.00  \n",
       "NM      23875.850831  0.0  160.5000  1501.000   5101.000   383153.00  \n",
       "NV      85020.082995  0.0  102.7500   985.000   4013.750  2052791.18  \n",
       "NY      66485.740477  0.0  700.0000  3728.505  10678.000  2950874.77  \n",
       "OH      23709.044263  0.0   50.0000   959.000   5044.000   598999.00  \n",
       "OK       9527.843897  0.0   51.0000   620.500   3095.000   117240.00  \n",
       "OR      46186.124336  0.0  481.0000  2852.000   8896.330  1559525.68  \n",
       "PA      38583.997256  0.0  180.7500  1651.000   5621.270  1193255.00  \n",
       "RI      85563.552444  0.0  365.0000  2013.000   6285.500  1363381.00  \n",
       "SC      26935.085575  0.0   35.0000   933.330   4475.000   668343.01  \n",
       "SD      45544.630898  0.0   30.0000  1608.000   5051.000   513422.57  \n",
       "TN      61886.213042  0.0  196.5000  2157.000   7869.000  1806651.00  \n",
       "TX      66260.230068  0.0   62.0000  1251.000   6014.250  2045463.20  \n",
       "UT      93645.927138  0.0  330.0000  2391.000  10075.750  1500975.81  \n",
       "VA      56720.079190  0.0   72.5000  1090.000   5375.250  2232933.03  \n",
       "VT      33265.776705  0.0  967.6675  3315.000   9224.770   547566.97  \n",
       "WA     160678.453723  0.0  428.0000  2841.000   8761.000  3948547.00  \n",
       "WI      24259.838146  0.0  120.0000  1250.000   4443.500   472897.00  \n",
       "WV      10744.044558  0.0   39.7500   720.500   3702.500    84707.00  \n",
       "WY      27134.015227  0.0  282.5000  3805.000  14463.750   179019.00  \n",
       "\n",
       "[50 rows x 72 columns]"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## Get statistical data from each state\n",
    "state_describe = df_kickstarters.groupby('state').describe()\n",
    "state_describe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"8\" halign=\"left\">blurb_length</th>\n",
       "      <th colspan=\"2\" halign=\"left\">duration</th>\n",
       "      <th>...</th>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
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       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>state</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AK</th>\n",
       "      <td>247.0</td>\n",
       "      <td>18.283401</td>\n",
       "      <td>4.724165</td>\n",
       "      <td>7.0</td>\n",
       "      <td>15.00</td>\n",
       "      <td>19.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>28.0</td>\n",
       "      <td>247.0</td>\n",
       "      <td>29.481781</td>\n",
       "      <td>...</td>\n",
       "      <td>9.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>247.0</td>\n",
       "      <td>10494.733279</td>\n",
       "      <td>19919.017680</td>\n",
       "      <td>124.0</td>\n",
       "      <td>2313.5000</td>\n",
       "      <td>4775.000</td>\n",
       "      <td>10939.5000</td>\n",
       "      <td>207289.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AL</th>\n",
       "      <td>451.0</td>\n",
       "      <td>18.771619</td>\n",
       "      <td>5.491302</td>\n",
       "      <td>3.0</td>\n",
       "      <td>15.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.00</td>\n",
       "      <td>29.0</td>\n",
       "      <td>451.0</td>\n",
       "      <td>29.649667</td>\n",
       "      <td>...</td>\n",
       "      <td>9.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>451.0</td>\n",
       "      <td>13352.539623</td>\n",
       "      <td>48632.195941</td>\n",
       "      <td>160.0</td>\n",
       "      <td>1595.5000</td>\n",
       "      <td>4014.000</td>\n",
       "      <td>9242.0000</td>\n",
       "      <td>839145.79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AR</th>\n",
       "      <td>244.0</td>\n",
       "      <td>19.057377</td>\n",
       "      <td>5.208886</td>\n",
       "      <td>2.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>28.0</td>\n",
       "      <td>244.0</td>\n",
       "      <td>30.241803</td>\n",
       "      <td>...</td>\n",
       "      <td>9.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>244.0</td>\n",
       "      <td>11384.180902</td>\n",
       "      <td>30354.159709</td>\n",
       "      <td>21.0</td>\n",
       "      <td>1125.0000</td>\n",
       "      <td>3067.500</td>\n",
       "      <td>12175.0200</td>\n",
       "      <td>413530.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AZ</th>\n",
       "      <td>1314.0</td>\n",
       "      <td>18.928463</td>\n",
       "      <td>4.960873</td>\n",
       "      <td>3.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1314.0</td>\n",
       "      <td>30.793760</td>\n",
       "      <td>...</td>\n",
       "      <td>9.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1314.0</td>\n",
       "      <td>18069.792359</td>\n",
       "      <td>65924.982355</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1630.4250</td>\n",
       "      <td>4614.500</td>\n",
       "      <td>12962.2500</td>\n",
       "      <td>902043.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CA</th>\n",
       "      <td>16457.0</td>\n",
       "      <td>18.814061</td>\n",
       "      <td>4.844413</td>\n",
       "      <td>1.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>31.0</td>\n",
       "      <td>16457.0</td>\n",
       "      <td>31.373640</td>\n",
       "      <td>...</td>\n",
       "      <td>9.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>16457.0</td>\n",
       "      <td>37475.627072</td>\n",
       "      <td>188794.532028</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2750.0000</td>\n",
       "      <td>7110.000</td>\n",
       "      <td>20510.0000</td>\n",
       "      <td>8596474.58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CO</th>\n",
       "      <td>1924.0</td>\n",
       "      <td>19.029106</td>\n",
       "      <td>4.801974</td>\n",
       "      <td>3.0</td>\n",
       "      <td>16.75</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>29.0</td>\n",
       "      <td>1924.0</td>\n",
       "      <td>30.768711</td>\n",
       "      <td>...</td>\n",
       "      <td>10.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1924.0</td>\n",
       "      <td>17487.041902</td>\n",
       "      <td>60716.780123</td>\n",
       "      <td>10.0</td>\n",
       "      <td>2012.9925</td>\n",
       "      <td>5107.500</td>\n",
       "      <td>11901.6825</td>\n",
       "      <td>1027985.58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CT</th>\n",
       "      <td>723.0</td>\n",
       "      <td>18.928077</td>\n",
       "      <td>4.914259</td>\n",
       "      <td>3.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>31.0</td>\n",
       "      <td>723.0</td>\n",
       "      <td>31.461964</td>\n",
       "      <td>...</td>\n",
       "      <td>9.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>723.0</td>\n",
       "      <td>21151.267898</td>\n",
       "      <td>178386.866067</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1509.0000</td>\n",
       "      <td>3883.000</td>\n",
       "      <td>10107.5000</td>\n",
       "      <td>3317658.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DE</th>\n",
       "      <td>163.0</td>\n",
       "      <td>18.846626</td>\n",
       "      <td>4.662144</td>\n",
       "      <td>3.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>29.0</td>\n",
       "      <td>163.0</td>\n",
       "      <td>33.969325</td>\n",
       "      <td>...</td>\n",
       "      <td>9.50</td>\n",
       "      <td>12.0</td>\n",
       "      <td>163.0</td>\n",
       "      <td>147042.530368</td>\n",
       "      <td>300419.470336</td>\n",
       "      <td>38.0</td>\n",
       "      <td>2927.0000</td>\n",
       "      <td>10687.000</td>\n",
       "      <td>109066.0000</td>\n",
       "      <td>1432637.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FL</th>\n",
       "      <td>2787.0</td>\n",
       "      <td>19.011123</td>\n",
       "      <td>5.001244</td>\n",
       "      <td>2.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>32.0</td>\n",
       "      <td>2787.0</td>\n",
       "      <td>31.479727</td>\n",
       "      <td>...</td>\n",
       "      <td>9.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>2787.0</td>\n",
       "      <td>21157.089426</td>\n",
       "      <td>162843.876195</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1377.0000</td>\n",
       "      <td>3724.000</td>\n",
       "      <td>10344.3100</td>\n",
       "      <td>5333792.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GA</th>\n",
       "      <td>1671.0</td>\n",
       "      <td>19.047277</td>\n",
       "      <td>5.124280</td>\n",
       "      <td>1.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.00</td>\n",
       "      <td>33.0</td>\n",
       "      <td>1671.0</td>\n",
       "      <td>30.947337</td>\n",
       "      <td>...</td>\n",
       "      <td>9.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1671.0</td>\n",
       "      <td>23897.445919</td>\n",
       "      <td>144165.259766</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1688.1300</td>\n",
       "      <td>4505.000</td>\n",
       "      <td>10996.5000</td>\n",
       "      <td>3352208.89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HI</th>\n",
       "      <td>326.0</td>\n",
       "      <td>18.880368</td>\n",
       "      <td>4.776975</td>\n",
       "      <td>3.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>29.0</td>\n",
       "      <td>326.0</td>\n",
       "      <td>32.279141</td>\n",
       "      <td>...</td>\n",
       "      <td>9.75</td>\n",
       "      <td>12.0</td>\n",
       "      <td>326.0</td>\n",
       "      <td>14227.866104</td>\n",
       "      <td>19981.554828</td>\n",
       "      <td>87.0</td>\n",
       "      <td>2517.2500</td>\n",
       "      <td>7040.500</td>\n",
       "      <td>16303.2500</td>\n",
       "      <td>137385.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IA</th>\n",
       "      <td>394.0</td>\n",
       "      <td>18.850254</td>\n",
       "      <td>4.681229</td>\n",
       "      <td>3.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>29.0</td>\n",
       "      <td>394.0</td>\n",
       "      <td>29.946701</td>\n",
       "      <td>...</td>\n",
       "      <td>9.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>394.0</td>\n",
       "      <td>11611.440330</td>\n",
       "      <td>39270.273711</td>\n",
       "      <td>19.0</td>\n",
       "      <td>1123.5000</td>\n",
       "      <td>2915.000</td>\n",
       "      <td>7834.1250</td>\n",
       "      <td>595676.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</th>\n",
       "      <td>383.0</td>\n",
       "      <td>18.686684</td>\n",
       "      <td>5.078546</td>\n",
       "      <td>1.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>28.0</td>\n",
       "      <td>383.0</td>\n",
       "      <td>29.543081</td>\n",
       "      <td>...</td>\n",
       "      <td>9.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>383.0</td>\n",
       "      <td>12823.824178</td>\n",
       "      <td>29304.216212</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1520.0000</td>\n",
       "      <td>4021.000</td>\n",
       "      <td>10376.0000</td>\n",
       "      <td>325952.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IL</th>\n",
       "      <td>3300.0</td>\n",
       "      <td>18.650909</td>\n",
       "      <td>4.870678</td>\n",
       "      <td>2.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>19.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>32.0</td>\n",
       "      <td>3300.0</td>\n",
       "      <td>30.874242</td>\n",
       "      <td>...</td>\n",
       "      <td>9.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>3300.0</td>\n",
       "      <td>15197.515627</td>\n",
       "      <td>45593.042166</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1769.0000</td>\n",
       "      <td>4492.715</td>\n",
       "      <td>11529.2450</td>\n",
       "      <td>1021583.52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IN</th>\n",
       "      <td>788.0</td>\n",
       "      <td>18.836294</td>\n",
       "      <td>5.100001</td>\n",
       "      <td>3.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.00</td>\n",
       "      <td>29.0</td>\n",
       "      <td>788.0</td>\n",
       "      <td>30.583756</td>\n",
       "      <td>...</td>\n",
       "      <td>9.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>788.0</td>\n",
       "      <td>13600.961713</td>\n",
       "      <td>56991.693127</td>\n",
       "      <td>40.0</td>\n",
       "      <td>1104.5000</td>\n",
       "      <td>2864.500</td>\n",
       "      <td>8310.0000</td>\n",
       "      <td>958792.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KS</th>\n",
       "      <td>292.0</td>\n",
       "      <td>18.996575</td>\n",
       "      <td>4.968283</td>\n",
       "      <td>4.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.25</td>\n",
       "      <td>29.0</td>\n",
       "      <td>292.0</td>\n",
       "      <td>30.948630</td>\n",
       "      <td>...</td>\n",
       "      <td>9.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>292.0</td>\n",
       "      <td>13743.671336</td>\n",
       "      <td>65922.615723</td>\n",
       "      <td>75.0</td>\n",
       "      <td>1225.0000</td>\n",
       "      <td>3351.000</td>\n",
       "      <td>10255.5000</td>\n",
       "      <td>784577.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KY</th>\n",
       "      <td>528.0</td>\n",
       "      <td>18.604167</td>\n",
       "      <td>5.185784</td>\n",
       "      <td>2.0</td>\n",
       "      <td>15.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.00</td>\n",
       "      <td>28.0</td>\n",
       "      <td>528.0</td>\n",
       "      <td>30.979167</td>\n",
       "      <td>...</td>\n",
       "      <td>9.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>528.0</td>\n",
       "      <td>12881.521913</td>\n",
       "      <td>46968.054535</td>\n",
       "      <td>31.0</td>\n",
       "      <td>1538.0000</td>\n",
       "      <td>4755.000</td>\n",
       "      <td>10389.0000</td>\n",
       "      <td>823704.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LA</th>\n",
       "      <td>676.0</td>\n",
       "      <td>19.386095</td>\n",
       "      <td>4.585037</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.00</td>\n",
       "      <td>29.0</td>\n",
       "      <td>676.0</td>\n",
       "      <td>30.721893</td>\n",
       "      <td>...</td>\n",
       "      <td>9.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>676.0</td>\n",
       "      <td>9987.838417</td>\n",
       "      <td>19552.595268</td>\n",
       "      <td>101.0</td>\n",
       "      <td>1848.1700</td>\n",
       "      <td>4303.000</td>\n",
       "      <td>10403.0000</td>\n",
       "      <td>276502.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MA</th>\n",
       "      <td>2814.0</td>\n",
       "      <td>18.681237</td>\n",
       "      <td>4.771832</td>\n",
       "      <td>3.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>30.0</td>\n",
       "      <td>2814.0</td>\n",
       "      <td>31.686212</td>\n",
       "      <td>...</td>\n",
       "      <td>9.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>2814.0</td>\n",
       "      <td>23927.587466</td>\n",
       "      <td>100223.398125</td>\n",
       "      <td>19.0</td>\n",
       "      <td>2097.0000</td>\n",
       "      <td>5265.000</td>\n",
       "      <td>12712.6250</td>\n",
       "      <td>2344134.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MD</th>\n",
       "      <td>1100.0</td>\n",
       "      <td>19.113636</td>\n",
       "      <td>4.456115</td>\n",
       "      <td>3.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>31.0</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>31.285455</td>\n",
       "      <td>...</td>\n",
       "      <td>9.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>12311.022691</td>\n",
       "      <td>104722.730514</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1661.0000</td>\n",
       "      <td>3828.500</td>\n",
       "      <td>8361.5000</td>\n",
       "      <td>3401361.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ME</th>\n",
       "      <td>454.0</td>\n",
       "      <td>18.993392</td>\n",
       "      <td>4.742132</td>\n",
       "      <td>3.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>29.0</td>\n",
       "      <td>454.0</td>\n",
       "      <td>29.876652</td>\n",
       "      <td>...</td>\n",
       "      <td>9.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>454.0</td>\n",
       "      <td>10227.247577</td>\n",
       "      <td>22089.476111</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1906.5650</td>\n",
       "      <td>3841.500</td>\n",
       "      <td>10578.8150</td>\n",
       "      <td>348449.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MI</th>\n",
       "      <td>1786.0</td>\n",
       "      <td>18.913214</td>\n",
       "      <td>4.992069</td>\n",
       "      <td>2.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1786.0</td>\n",
       "      <td>29.823068</td>\n",
       "      <td>...</td>\n",
       "      <td>9.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1786.0</td>\n",
       "      <td>9747.037833</td>\n",
       "      <td>40744.424832</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1254.7500</td>\n",
       "      <td>3140.000</td>\n",
       "      <td>8173.5000</td>\n",
       "      <td>1509506.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MN</th>\n",
       "      <td>1768.0</td>\n",
       "      <td>19.124434</td>\n",
       "      <td>4.572786</td>\n",
       "      <td>4.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1768.0</td>\n",
       "      <td>30.967760</td>\n",
       "      <td>...</td>\n",
       "      <td>9.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1768.0</td>\n",
       "      <td>18689.887839</td>\n",
       "      <td>152707.992699</td>\n",
       "      <td>15.0</td>\n",
       "      <td>1806.5000</td>\n",
       "      <td>4626.000</td>\n",
       "      <td>10796.0000</td>\n",
       "      <td>5764229.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MO</th>\n",
       "      <td>1147.0</td>\n",
       "      <td>18.891892</td>\n",
       "      <td>4.983795</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1147.0</td>\n",
       "      <td>30.906713</td>\n",
       "      <td>...</td>\n",
       "      <td>9.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1147.0</td>\n",
       "      <td>17790.442049</td>\n",
       "      <td>99706.273896</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1262.5000</td>\n",
       "      <td>3375.000</td>\n",
       "      <td>9882.0000</td>\n",
       "      <td>2069100.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MS</th>\n",
       "      <td>172.0</td>\n",
       "      <td>19.284884</td>\n",
       "      <td>4.588978</td>\n",
       "      <td>6.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.00</td>\n",
       "      <td>28.0</td>\n",
       "      <td>172.0</td>\n",
       "      <td>29.209302</td>\n",
       "      <td>...</td>\n",
       "      <td>10.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>172.0</td>\n",
       "      <td>11106.323953</td>\n",
       "      <td>50353.263862</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1448.7500</td>\n",
       "      <td>2850.000</td>\n",
       "      <td>7135.0000</td>\n",
       "      <td>468281.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MT</th>\n",
       "      <td>329.0</td>\n",
       "      <td>18.920973</td>\n",
       "      <td>4.715680</td>\n",
       "      <td>4.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>31.0</td>\n",
       "      <td>329.0</td>\n",
       "      <td>29.562310</td>\n",
       "      <td>...</td>\n",
       "      <td>10.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>329.0</td>\n",
       "      <td>30631.486778</td>\n",
       "      <td>208688.782405</td>\n",
       "      <td>86.0</td>\n",
       "      <td>2018.0000</td>\n",
       "      <td>5416.000</td>\n",
       "      <td>12240.3200</td>\n",
       "      <td>2650310.88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NC</th>\n",
       "      <td>1648.0</td>\n",
       "      <td>19.100728</td>\n",
       "      <td>4.899678</td>\n",
       "      <td>2.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>34.0</td>\n",
       "      <td>1648.0</td>\n",
       "      <td>30.674150</td>\n",
       "      <td>...</td>\n",
       "      <td>9.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1648.0</td>\n",
       "      <td>11760.220170</td>\n",
       "      <td>30724.709363</td>\n",
       "      <td>16.0</td>\n",
       "      <td>1712.7500</td>\n",
       "      <td>4501.000</td>\n",
       "      <td>10850.0000</td>\n",
       "      <td>502188.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ND</th>\n",
       "      <td>86.0</td>\n",
       "      <td>18.267442</td>\n",
       "      <td>5.058306</td>\n",
       "      <td>7.0</td>\n",
       "      <td>15.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>29.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>29.755814</td>\n",
       "      <td>...</td>\n",
       "      <td>9.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>8724.558023</td>\n",
       "      <td>12729.263831</td>\n",
       "      <td>106.0</td>\n",
       "      <td>1098.7500</td>\n",
       "      <td>3602.500</td>\n",
       "      <td>11538.7500</td>\n",
       "      <td>84258.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NE</th>\n",
       "      <td>207.0</td>\n",
       "      <td>18.294686</td>\n",
       "      <td>5.755126</td>\n",
       "      <td>3.0</td>\n",
       "      <td>15.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>28.0</td>\n",
       "      <td>207.0</td>\n",
       "      <td>29.227053</td>\n",
       "      <td>...</td>\n",
       "      <td>9.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>207.0</td>\n",
       "      <td>4517.961787</td>\n",
       "      <td>6863.022028</td>\n",
       "      <td>22.0</td>\n",
       "      <td>758.0000</td>\n",
       "      <td>2185.000</td>\n",
       "      <td>5480.7500</td>\n",
       "      <td>55731.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NH</th>\n",
       "      <td>356.0</td>\n",
       "      <td>18.629213</td>\n",
       "      <td>4.629074</td>\n",
       "      <td>3.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>19.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>29.0</td>\n",
       "      <td>356.0</td>\n",
       "      <td>29.199438</td>\n",
       "      <td>...</td>\n",
       "      <td>10.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>356.0</td>\n",
       "      <td>12571.265787</td>\n",
       "      <td>47510.341551</td>\n",
       "      <td>29.0</td>\n",
       "      <td>1736.7500</td>\n",
       "      <td>4021.000</td>\n",
       "      <td>8075.2500</td>\n",
       "      <td>609902.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NJ</th>\n",
       "      <td>1162.0</td>\n",
       "      <td>18.810671</td>\n",
       "      <td>5.114566</td>\n",
       "      <td>2.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>29.0</td>\n",
       "      <td>1162.0</td>\n",
       "      <td>31.530981</td>\n",
       "      <td>...</td>\n",
       "      <td>9.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1162.0</td>\n",
       "      <td>11230.743477</td>\n",
       "      <td>33715.989904</td>\n",
       "      <td>26.0</td>\n",
       "      <td>1526.0000</td>\n",
       "      <td>4158.750</td>\n",
       "      <td>9948.7500</td>\n",
       "      <td>687827.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NM</th>\n",
       "      <td>458.0</td>\n",
       "      <td>19.248908</td>\n",
       "      <td>4.667412</td>\n",
       "      <td>4.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.00</td>\n",
       "      <td>30.0</td>\n",
       "      <td>458.0</td>\n",
       "      <td>30.637555</td>\n",
       "      <td>...</td>\n",
       "      <td>9.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>458.0</td>\n",
       "      <td>11320.416681</td>\n",
       "      <td>30409.087474</td>\n",
       "      <td>85.0</td>\n",
       "      <td>1652.7500</td>\n",
       "      <td>3596.000</td>\n",
       "      <td>9951.5000</td>\n",
       "      <td>383153.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NV</th>\n",
       "      <td>1082.0</td>\n",
       "      <td>19.408503</td>\n",
       "      <td>4.363824</td>\n",
       "      <td>5.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1082.0</td>\n",
       "      <td>24.655268</td>\n",
       "      <td>...</td>\n",
       "      <td>9.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1082.0</td>\n",
       "      <td>18771.073022</td>\n",
       "      <td>109894.674340</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1010.7500</td>\n",
       "      <td>2756.000</td>\n",
       "      <td>8401.0000</td>\n",
       "      <td>2052791.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NY</th>\n",
       "      <td>11402.0</td>\n",
       "      <td>18.876425</td>\n",
       "      <td>4.747117</td>\n",
       "      <td>1.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>32.0</td>\n",
       "      <td>11402.0</td>\n",
       "      <td>31.502894</td>\n",
       "      <td>...</td>\n",
       "      <td>9.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>11402.0</td>\n",
       "      <td>19509.648022</td>\n",
       "      <td>77710.706077</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2713.2500</td>\n",
       "      <td>6262.500</td>\n",
       "      <td>15214.2500</td>\n",
       "      <td>2950874.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OH</th>\n",
       "      <td>1863.0</td>\n",
       "      <td>18.854536</td>\n",
       "      <td>4.991915</td>\n",
       "      <td>1.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1863.0</td>\n",
       "      <td>31.041868</td>\n",
       "      <td>...</td>\n",
       "      <td>9.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1863.0</td>\n",
       "      <td>11566.984960</td>\n",
       "      <td>31127.239269</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1288.5000</td>\n",
       "      <td>3727.000</td>\n",
       "      <td>10530.5000</td>\n",
       "      <td>598999.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OK</th>\n",
       "      <td>468.0</td>\n",
       "      <td>18.523504</td>\n",
       "      <td>5.157631</td>\n",
       "      <td>4.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>31.0</td>\n",
       "      <td>468.0</td>\n",
       "      <td>28.705128</td>\n",
       "      <td>...</td>\n",
       "      <td>9.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>468.0</td>\n",
       "      <td>6736.753269</td>\n",
       "      <td>12379.886150</td>\n",
       "      <td>21.0</td>\n",
       "      <td>793.7525</td>\n",
       "      <td>2516.000</td>\n",
       "      <td>7643.7500</td>\n",
       "      <td>117240.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OR</th>\n",
       "      <td>2420.0</td>\n",
       "      <td>18.864050</td>\n",
       "      <td>4.886655</td>\n",
       "      <td>2.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>29.0</td>\n",
       "      <td>2420.0</td>\n",
       "      <td>29.919421</td>\n",
       "      <td>...</td>\n",
       "      <td>9.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>2420.0</td>\n",
       "      <td>15610.057174</td>\n",
       "      <td>54395.923915</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2054.9950</td>\n",
       "      <td>5241.000</td>\n",
       "      <td>12710.0000</td>\n",
       "      <td>1559525.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PA</th>\n",
       "      <td>2728.0</td>\n",
       "      <td>18.940982</td>\n",
       "      <td>4.700471</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>30.0</td>\n",
       "      <td>2728.0</td>\n",
       "      <td>30.564883</td>\n",
       "      <td>...</td>\n",
       "      <td>9.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>2728.0</td>\n",
       "      <td>12470.421767</td>\n",
       "      <td>48014.898193</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1570.5000</td>\n",
       "      <td>3919.500</td>\n",
       "      <td>9814.2675</td>\n",
       "      <td>1193255.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RI</th>\n",
       "      <td>334.0</td>\n",
       "      <td>19.314371</td>\n",
       "      <td>4.729941</td>\n",
       "      <td>5.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>28.0</td>\n",
       "      <td>334.0</td>\n",
       "      <td>31.188623</td>\n",
       "      <td>...</td>\n",
       "      <td>9.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>334.0</td>\n",
       "      <td>19790.783114</td>\n",
       "      <td>103430.593647</td>\n",
       "      <td>15.0</td>\n",
       "      <td>1577.5000</td>\n",
       "      <td>4010.860</td>\n",
       "      <td>7859.5000</td>\n",
       "      <td>1363381.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SC</th>\n",
       "      <td>581.0</td>\n",
       "      <td>18.211704</td>\n",
       "      <td>5.324789</td>\n",
       "      <td>2.0</td>\n",
       "      <td>15.00</td>\n",
       "      <td>19.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>28.0</td>\n",
       "      <td>581.0</td>\n",
       "      <td>29.958692</td>\n",
       "      <td>...</td>\n",
       "      <td>9.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>581.0</td>\n",
       "      <td>9379.109518</td>\n",
       "      <td>36046.764297</td>\n",
       "      <td>20.0</td>\n",
       "      <td>1215.0000</td>\n",
       "      <td>3550.000</td>\n",
       "      <td>7454.0000</td>\n",
       "      <td>668343.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SD</th>\n",
       "      <td>81.0</td>\n",
       "      <td>18.407407</td>\n",
       "      <td>4.705788</td>\n",
       "      <td>7.0</td>\n",
       "      <td>15.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>27.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>29.037037</td>\n",
       "      <td>...</td>\n",
       "      <td>9.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>18079.428642</td>\n",
       "      <td>64746.551540</td>\n",
       "      <td>359.0</td>\n",
       "      <td>2300.0000</td>\n",
       "      <td>4298.000</td>\n",
       "      <td>10317.0000</td>\n",
       "      <td>513422.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TN</th>\n",
       "      <td>1700.0</td>\n",
       "      <td>19.184118</td>\n",
       "      <td>5.360757</td>\n",
       "      <td>1.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.00</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1700.0</td>\n",
       "      <td>31.090000</td>\n",
       "      <td>...</td>\n",
       "      <td>9.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1700.0</td>\n",
       "      <td>15905.971300</td>\n",
       "      <td>76662.622062</td>\n",
       "      <td>20.0</td>\n",
       "      <td>2030.8875</td>\n",
       "      <td>5238.500</td>\n",
       "      <td>12156.5000</td>\n",
       "      <td>1806651.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TX</th>\n",
       "      <td>4356.0</td>\n",
       "      <td>18.588843</td>\n",
       "      <td>5.130683</td>\n",
       "      <td>1.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>32.0</td>\n",
       "      <td>4356.0</td>\n",
       "      <td>30.015152</td>\n",
       "      <td>...</td>\n",
       "      <td>9.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>4356.0</td>\n",
       "      <td>19281.195638</td>\n",
       "      <td>87664.485893</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1652.4225</td>\n",
       "      <td>4790.500</td>\n",
       "      <td>12576.0000</td>\n",
       "      <td>2045463.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UT</th>\n",
       "      <td>1423.0</td>\n",
       "      <td>18.486297</td>\n",
       "      <td>4.994053</td>\n",
       "      <td>3.0</td>\n",
       "      <td>15.00</td>\n",
       "      <td>19.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1423.0</td>\n",
       "      <td>30.394238</td>\n",
       "      <td>...</td>\n",
       "      <td>10.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1423.0</td>\n",
       "      <td>37577.903823</td>\n",
       "      <td>115538.246198</td>\n",
       "      <td>10.0</td>\n",
       "      <td>2037.5000</td>\n",
       "      <td>6012.000</td>\n",
       "      <td>21011.0000</td>\n",
       "      <td>1500975.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VA</th>\n",
       "      <td>1441.0</td>\n",
       "      <td>18.887578</td>\n",
       "      <td>4.936105</td>\n",
       "      <td>2.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.00</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1441.0</td>\n",
       "      <td>30.188064</td>\n",
       "      <td>...</td>\n",
       "      <td>9.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1441.0</td>\n",
       "      <td>14193.243727</td>\n",
       "      <td>75666.031917</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1290.0000</td>\n",
       "      <td>4090.000</td>\n",
       "      <td>10454.0000</td>\n",
       "      <td>2232933.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VT</th>\n",
       "      <td>456.0</td>\n",
       "      <td>19.089912</td>\n",
       "      <td>4.627988</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>29.0</td>\n",
       "      <td>456.0</td>\n",
       "      <td>30.804825</td>\n",
       "      <td>...</td>\n",
       "      <td>9.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>456.0</td>\n",
       "      <td>11430.921250</td>\n",
       "      <td>37527.285949</td>\n",
       "      <td>20.0</td>\n",
       "      <td>2224.7500</td>\n",
       "      <td>5028.500</td>\n",
       "      <td>10734.2500</td>\n",
       "      <td>547566.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WA</th>\n",
       "      <td>3161.0</td>\n",
       "      <td>18.558368</td>\n",
       "      <td>4.871237</td>\n",
       "      <td>1.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>31.0</td>\n",
       "      <td>3161.0</td>\n",
       "      <td>30.284087</td>\n",
       "      <td>...</td>\n",
       "      <td>10.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>3161.0</td>\n",
       "      <td>32054.196134</td>\n",
       "      <td>192159.906946</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2051.0000</td>\n",
       "      <td>5253.000</td>\n",
       "      <td>13345.0000</td>\n",
       "      <td>3948547.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WI</th>\n",
       "      <td>1052.0</td>\n",
       "      <td>18.829848</td>\n",
       "      <td>4.984900</td>\n",
       "      <td>2.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>29.0</td>\n",
       "      <td>1052.0</td>\n",
       "      <td>31.052281</td>\n",
       "      <td>...</td>\n",
       "      <td>9.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1052.0</td>\n",
       "      <td>9672.878935</td>\n",
       "      <td>30616.704367</td>\n",
       "      <td>13.0</td>\n",
       "      <td>1223.3000</td>\n",
       "      <td>3016.000</td>\n",
       "      <td>7943.5000</td>\n",
       "      <td>472897.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WV</th>\n",
       "      <td>161.0</td>\n",
       "      <td>18.850932</td>\n",
       "      <td>5.140782</td>\n",
       "      <td>3.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>28.0</td>\n",
       "      <td>161.0</td>\n",
       "      <td>31.962733</td>\n",
       "      <td>...</td>\n",
       "      <td>8.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>161.0</td>\n",
       "      <td>7851.266211</td>\n",
       "      <td>13735.209890</td>\n",
       "      <td>11.0</td>\n",
       "      <td>1077.0000</td>\n",
       "      <td>3125.000</td>\n",
       "      <td>7618.0000</td>\n",
       "      <td>84707.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WY</th>\n",
       "      <td>101.0</td>\n",
       "      <td>18.970297</td>\n",
       "      <td>4.302221</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>25.0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>32.594059</td>\n",
       "      <td>...</td>\n",
       "      <td>11.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>20085.416040</td>\n",
       "      <td>32332.843346</td>\n",
       "      <td>78.0</td>\n",
       "      <td>4101.0000</td>\n",
       "      <td>11273.000</td>\n",
       "      <td>21220.0000</td>\n",
       "      <td>179019.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>50 rows × 64 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      blurb_length                                                      \\\n",
       "             count       mean       std  min    25%   50%    75%   max   \n",
       "state                                                                    \n",
       "AK           247.0  18.283401  4.724165  7.0  15.00  19.0  22.00  28.0   \n",
       "AL           451.0  18.771619  5.491302  3.0  15.00  20.0  23.00  29.0   \n",
       "AR           244.0  19.057377  5.208886  2.0  17.00  20.0  22.00  28.0   \n",
       "AZ          1314.0  18.928463  4.960873  3.0  16.00  20.0  22.00  30.0   \n",
       "CA         16457.0  18.814061  4.844413  1.0  16.00  20.0  22.00  31.0   \n",
       "CO          1924.0  19.029106  4.801974  3.0  16.75  20.0  22.00  29.0   \n",
       "CT           723.0  18.928077  4.914259  3.0  16.00  20.0  22.00  31.0   \n",
       "DE           163.0  18.846626  4.662144  3.0  16.00  20.0  22.00  29.0   \n",
       "FL          2787.0  19.011123  5.001244  2.0  17.00  20.0  22.00  32.0   \n",
       "GA          1671.0  19.047277  5.124280  1.0  16.00  20.0  23.00  33.0   \n",
       "HI           326.0  18.880368  4.776975  3.0  16.00  20.0  22.00  29.0   \n",
       "IA           394.0  18.850254  4.681229  3.0  17.00  20.0  22.00  29.0   \n",
       "ID           383.0  18.686684  5.078546  1.0  16.00  20.0  22.00  28.0   \n",
       "IL          3300.0  18.650909  4.870678  2.0  16.00  19.0  22.00  32.0   \n",
       "IN           788.0  18.836294  5.100001  3.0  16.00  20.0  23.00  29.0   \n",
       "KS           292.0  18.996575  4.968283  4.0  16.00  20.0  22.25  29.0   \n",
       "KY           528.0  18.604167  5.185784  2.0  15.00  20.0  23.00  28.0   \n",
       "LA           676.0  19.386095  4.585037  1.0  17.00  20.0  23.00  29.0   \n",
       "MA          2814.0  18.681237  4.771832  3.0  16.00  20.0  22.00  30.0   \n",
       "MD          1100.0  19.113636  4.456115  3.0  17.00  20.0  22.00  31.0   \n",
       "ME           454.0  18.993392  4.742132  3.0  17.00  20.0  22.00  29.0   \n",
       "MI          1786.0  18.913214  4.992069  2.0  16.00  20.0  22.00  32.0   \n",
       "MN          1768.0  19.124434  4.572786  4.0  17.00  20.0  22.00  30.0   \n",
       "MO          1147.0  18.891892  4.983795  1.0  17.00  20.0  22.00  30.0   \n",
       "MS           172.0  19.284884  4.588978  6.0  16.00  20.0  23.00  28.0   \n",
       "MT           329.0  18.920973  4.715680  4.0  16.00  20.0  22.00  31.0   \n",
       "NC          1648.0  19.100728  4.899678  2.0  17.00  20.0  22.00  34.0   \n",
       "ND            86.0  18.267442  5.058306  7.0  15.00  20.0  22.00  29.0   \n",
       "NE           207.0  18.294686  5.755126  3.0  15.00  20.0  22.00  28.0   \n",
       "NH           356.0  18.629213  4.629074  3.0  16.00  19.0  22.00  29.0   \n",
       "NJ          1162.0  18.810671  5.114566  2.0  16.00  20.0  22.00  29.0   \n",
       "NM           458.0  19.248908  4.667412  4.0  17.00  20.0  23.00  30.0   \n",
       "NV          1082.0  19.408503  4.363824  5.0  17.00  20.0  22.00  30.0   \n",
       "NY         11402.0  18.876425  4.747117  1.0  16.00  20.0  22.00  32.0   \n",
       "OH          1863.0  18.854536  4.991915  1.0  16.00  20.0  22.00  35.0   \n",
       "OK           468.0  18.523504  5.157631  4.0  16.00  20.0  22.00  31.0   \n",
       "OR          2420.0  18.864050  4.886655  2.0  16.00  20.0  22.00  29.0   \n",
       "PA          2728.0  18.940982  4.700471  1.0  17.00  20.0  22.00  30.0   \n",
       "RI           334.0  19.314371  4.729941  5.0  17.00  20.0  22.00  28.0   \n",
       "SC           581.0  18.211704  5.324789  2.0  15.00  19.0  22.00  28.0   \n",
       "SD            81.0  18.407407  4.705788  7.0  15.00  20.0  22.00  27.0   \n",
       "TN          1700.0  19.184118  5.360757  1.0  16.00  20.0  23.00  32.0   \n",
       "TX          4356.0  18.588843  5.130683  1.0  16.00  20.0  22.00  32.0   \n",
       "UT          1423.0  18.486297  4.994053  3.0  15.00  19.0  22.00  30.0   \n",
       "VA          1441.0  18.887578  4.936105  2.0  16.00  20.0  23.00  30.0   \n",
       "VT           456.0  19.089912  4.627988  1.0  17.00  20.0  22.00  29.0   \n",
       "WA          3161.0  18.558368  4.871237  1.0  16.00  20.0  22.00  31.0   \n",
       "WI          1052.0  18.829848  4.984900  2.0  16.00  20.0  22.00  29.0   \n",
       "WV           161.0  18.850932  5.140782  3.0  17.00  20.0  22.00  28.0   \n",
       "WY           101.0  18.970297  4.302221  1.0  17.00  20.0  22.00  25.0   \n",
       "\n",
       "      duration                ...     start_month       usd_pledged  \\\n",
       "         count       mean     ...             75%   max       count   \n",
       "state                         ...                                     \n",
       "AK       247.0  29.481781     ...            9.00  12.0       247.0   \n",
       "AL       451.0  29.649667     ...            9.00  12.0       451.0   \n",
       "AR       244.0  30.241803     ...            9.00  12.0       244.0   \n",
       "AZ      1314.0  30.793760     ...            9.00  12.0      1314.0   \n",
       "CA     16457.0  31.373640     ...            9.00  12.0     16457.0   \n",
       "CO      1924.0  30.768711     ...           10.00  12.0      1924.0   \n",
       "CT       723.0  31.461964     ...            9.00  12.0       723.0   \n",
       "DE       163.0  33.969325     ...            9.50  12.0       163.0   \n",
       "FL      2787.0  31.479727     ...            9.00  12.0      2787.0   \n",
       "GA      1671.0  30.947337     ...            9.00  12.0      1671.0   \n",
       "HI       326.0  32.279141     ...            9.75  12.0       326.0   \n",
       "IA       394.0  29.946701     ...            9.00  12.0       394.0   \n",
       "ID       383.0  29.543081     ...            9.00  12.0       383.0   \n",
       "IL      3300.0  30.874242     ...            9.00  12.0      3300.0   \n",
       "IN       788.0  30.583756     ...            9.00  12.0       788.0   \n",
       "KS       292.0  30.948630     ...            9.00  12.0       292.0   \n",
       "KY       528.0  30.979167     ...            9.00  12.0       528.0   \n",
       "LA       676.0  30.721893     ...            9.00  12.0       676.0   \n",
       "MA      2814.0  31.686212     ...            9.00  12.0      2814.0   \n",
       "MD      1100.0  31.285455     ...            9.00  12.0      1100.0   \n",
       "ME       454.0  29.876652     ...            9.00  12.0       454.0   \n",
       "MI      1786.0  29.823068     ...            9.00  12.0      1786.0   \n",
       "MN      1768.0  30.967760     ...            9.00  12.0      1768.0   \n",
       "MO      1147.0  30.906713     ...            9.00  12.0      1147.0   \n",
       "MS       172.0  29.209302     ...           10.00  12.0       172.0   \n",
       "MT       329.0  29.562310     ...           10.00  12.0       329.0   \n",
       "NC      1648.0  30.674150     ...            9.00  12.0      1648.0   \n",
       "ND        86.0  29.755814     ...            9.00  12.0        86.0   \n",
       "NE       207.0  29.227053     ...            9.00  12.0       207.0   \n",
       "NH       356.0  29.199438     ...           10.00  12.0       356.0   \n",
       "NJ      1162.0  31.530981     ...            9.00  12.0      1162.0   \n",
       "NM       458.0  30.637555     ...            9.00  12.0       458.0   \n",
       "NV      1082.0  24.655268     ...            9.00  12.0      1082.0   \n",
       "NY     11402.0  31.502894     ...            9.00  12.0     11402.0   \n",
       "OH      1863.0  31.041868     ...            9.00  12.0      1863.0   \n",
       "OK       468.0  28.705128     ...            9.00  12.0       468.0   \n",
       "OR      2420.0  29.919421     ...            9.00  12.0      2420.0   \n",
       "PA      2728.0  30.564883     ...            9.00  12.0      2728.0   \n",
       "RI       334.0  31.188623     ...            9.00  12.0       334.0   \n",
       "SC       581.0  29.958692     ...            9.00  12.0       581.0   \n",
       "SD        81.0  29.037037     ...            9.00  12.0        81.0   \n",
       "TN      1700.0  31.090000     ...            9.00  12.0      1700.0   \n",
       "TX      4356.0  30.015152     ...            9.00  12.0      4356.0   \n",
       "UT      1423.0  30.394238     ...           10.00  12.0      1423.0   \n",
       "VA      1441.0  30.188064     ...            9.00  12.0      1441.0   \n",
       "VT       456.0  30.804825     ...            9.00  12.0       456.0   \n",
       "WA      3161.0  30.284087     ...           10.00  12.0      3161.0   \n",
       "WI      1052.0  31.052281     ...            9.00  12.0      1052.0   \n",
       "WV       161.0  31.962733     ...            8.00  12.0       161.0   \n",
       "WY       101.0  32.594059     ...           11.00  12.0       101.0   \n",
       "\n",
       "                                                                               \\\n",
       "                mean            std    min        25%        50%          75%   \n",
       "state                                                                           \n",
       "AK      10494.733279   19919.017680  124.0  2313.5000   4775.000   10939.5000   \n",
       "AL      13352.539623   48632.195941  160.0  1595.5000   4014.000    9242.0000   \n",
       "AR      11384.180902   30354.159709   21.0  1125.0000   3067.500   12175.0200   \n",
       "AZ      18069.792359   65924.982355    2.0  1630.4250   4614.500   12962.2500   \n",
       "CA      37475.627072  188794.532028    1.0  2750.0000   7110.000   20510.0000   \n",
       "CO      17487.041902   60716.780123   10.0  2012.9925   5107.500   11901.6825   \n",
       "CT      21151.267898  178386.866067    6.0  1509.0000   3883.000   10107.5000   \n",
       "DE     147042.530368  300419.470336   38.0  2927.0000  10687.000  109066.0000   \n",
       "FL      21157.089426  162843.876195    1.0  1377.0000   3724.000   10344.3100   \n",
       "GA      23897.445919  144165.259766    1.0  1688.1300   4505.000   10996.5000   \n",
       "HI      14227.866104   19981.554828   87.0  2517.2500   7040.500   16303.2500   \n",
       "IA      11611.440330   39270.273711   19.0  1123.5000   2915.000    7834.1250   \n",
       "ID      12823.824178   29304.216212   30.0  1520.0000   4021.000   10376.0000   \n",
       "IL      15197.515627   45593.042166    5.0  1769.0000   4492.715   11529.2450   \n",
       "IN      13600.961713   56991.693127   40.0  1104.5000   2864.500    8310.0000   \n",
       "KS      13743.671336   65922.615723   75.0  1225.0000   3351.000   10255.5000   \n",
       "KY      12881.521913   46968.054535   31.0  1538.0000   4755.000   10389.0000   \n",
       "LA       9987.838417   19552.595268  101.0  1848.1700   4303.000   10403.0000   \n",
       "MA      23927.587466  100223.398125   19.0  2097.0000   5265.000   12712.6250   \n",
       "MD      12311.022691  104722.730514    1.0  1661.0000   3828.500    8361.5000   \n",
       "ME      10227.247577   22089.476111   52.0  1906.5650   3841.500   10578.8150   \n",
       "MI       9747.037833   40744.424832   10.0  1254.7500   3140.000    8173.5000   \n",
       "MN      18689.887839  152707.992699   15.0  1806.5000   4626.000   10796.0000   \n",
       "MO      17790.442049   99706.273896    1.0  1262.5000   3375.000    9882.0000   \n",
       "MS      11106.323953   50353.263862   10.0  1448.7500   2850.000    7135.0000   \n",
       "MT      30631.486778  208688.782405   86.0  2018.0000   5416.000   12240.3200   \n",
       "NC      11760.220170   30724.709363   16.0  1712.7500   4501.000   10850.0000   \n",
       "ND       8724.558023   12729.263831  106.0  1098.7500   3602.500   11538.7500   \n",
       "NE       4517.961787    6863.022028   22.0   758.0000   2185.000    5480.7500   \n",
       "NH      12571.265787   47510.341551   29.0  1736.7500   4021.000    8075.2500   \n",
       "NJ      11230.743477   33715.989904   26.0  1526.0000   4158.750    9948.7500   \n",
       "NM      11320.416681   30409.087474   85.0  1652.7500   3596.000    9951.5000   \n",
       "NV      18771.073022  109894.674340    1.0  1010.7500   2756.000    8401.0000   \n",
       "NY      19509.648022   77710.706077    2.0  2713.2500   6262.500   15214.2500   \n",
       "OH      11566.984960   31127.239269    2.0  1288.5000   3727.000   10530.5000   \n",
       "OK       6736.753269   12379.886150   21.0   793.7525   2516.000    7643.7500   \n",
       "OR      15610.057174   54395.923915    6.0  2054.9950   5241.000   12710.0000   \n",
       "PA      12470.421767   48014.898193    1.0  1570.5000   3919.500    9814.2675   \n",
       "RI      19790.783114  103430.593647   15.0  1577.5000   4010.860    7859.5000   \n",
       "SC       9379.109518   36046.764297   20.0  1215.0000   3550.000    7454.0000   \n",
       "SD      18079.428642   64746.551540  359.0  2300.0000   4298.000   10317.0000   \n",
       "TN      15905.971300   76662.622062   20.0  2030.8875   5238.500   12156.5000   \n",
       "TX      19281.195638   87664.485893    1.0  1652.4225   4790.500   12576.0000   \n",
       "UT      37577.903823  115538.246198   10.0  2037.5000   6012.000   21011.0000   \n",
       "VA      14193.243727   75666.031917    1.0  1290.0000   4090.000   10454.0000   \n",
       "VT      11430.921250   37527.285949   20.0  2224.7500   5028.500   10734.2500   \n",
       "WA      32054.196134  192159.906946    1.0  2051.0000   5253.000   13345.0000   \n",
       "WI       9672.878935   30616.704367   13.0  1223.3000   3016.000    7943.5000   \n",
       "WV       7851.266211   13735.209890   11.0  1077.0000   3125.000    7618.0000   \n",
       "WY      20085.416040   32332.843346   78.0  4101.0000  11273.000   21220.0000   \n",
       "\n",
       "                   \n",
       "              max  \n",
       "state              \n",
       "AK      207289.00  \n",
       "AL      839145.79  \n",
       "AR      413530.99  \n",
       "AZ      902043.72  \n",
       "CA     8596474.58  \n",
       "CO     1027985.58  \n",
       "CT     3317658.10  \n",
       "DE     1432637.11  \n",
       "FL     5333792.84  \n",
       "GA     3352208.89  \n",
       "HI      137385.00  \n",
       "IA      595676.11  \n",
       "ID      325952.00  \n",
       "IL     1021583.52  \n",
       "IN      958792.00  \n",
       "KS      784577.00  \n",
       "KY      823704.20  \n",
       "LA      276502.17  \n",
       "MA     2344134.67  \n",
       "MD     3401361.08  \n",
       "ME      348449.00  \n",
       "MI     1509506.28  \n",
       "MN     5764229.38  \n",
       "MO     2069100.91  \n",
       "MS      468281.01  \n",
       "MT     2650310.88  \n",
       "NC      502188.90  \n",
       "ND       84258.42  \n",
       "NE       55731.41  \n",
       "NH      609902.71  \n",
       "NJ      687827.00  \n",
       "NM      383153.00  \n",
       "NV     2052791.18  \n",
       "NY     2950874.77  \n",
       "OH      598999.00  \n",
       "OK      117240.00  \n",
       "OR     1559525.68  \n",
       "PA     1193255.00  \n",
       "RI     1363381.00  \n",
       "SC      668343.01  \n",
       "SD      513422.57  \n",
       "TN     1806651.00  \n",
       "TX     2045463.20  \n",
       "UT     1500975.81  \n",
       "VA     2232933.03  \n",
       "VT      547566.97  \n",
       "WA     3948547.00  \n",
       "WI      472897.00  \n",
       "WV       84707.00  \n",
       "WY      179019.00  \n",
       "\n",
       "[50 rows x 64 columns]"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "state_describe_succ = df_successful.groupby('state').describe()\n",
    "state_describe_succ"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"8\" halign=\"left\">blurb_length</th>\n",
       "      <th colspan=\"2\" halign=\"left\">duration</th>\n",
       "      <th>...</th>\n",
       "      <th colspan=\"2\" halign=\"left\">start_month</th>\n",
       "      <th colspan=\"8\" halign=\"left\">usd_pledged</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>...</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>state</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AK</th>\n",
       "      <td>143.0</td>\n",
       "      <td>18.895105</td>\n",
       "      <td>5.184909</td>\n",
       "      <td>4.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>143.0</td>\n",
       "      <td>34.055944</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>143.0</td>\n",
       "      <td>845.033566</td>\n",
       "      <td>2009.590111</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>54.00</td>\n",
       "      <td>493.00</td>\n",
       "      <td>12557.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AL</th>\n",
       "      <td>416.0</td>\n",
       "      <td>19.810096</td>\n",
       "      <td>5.178267</td>\n",
       "      <td>4.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>21.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>416.0</td>\n",
       "      <td>34.706731</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>416.0</td>\n",
       "      <td>435.806755</td>\n",
       "      <td>1637.321347</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>175.25</td>\n",
       "      <td>16002.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AR</th>\n",
       "      <td>281.0</td>\n",
       "      <td>19.039146</td>\n",
       "      <td>5.909608</td>\n",
       "      <td>1.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>21.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>281.0</td>\n",
       "      <td>33.708185</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>281.0</td>\n",
       "      <td>337.371886</td>\n",
       "      <td>958.518379</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20.00</td>\n",
       "      <td>161.00</td>\n",
       "      <td>8003.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AZ</th>\n",
       "      <td>1147.0</td>\n",
       "      <td>19.394071</td>\n",
       "      <td>5.195638</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>21.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1147.0</td>\n",
       "      <td>34.619006</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1147.0</td>\n",
       "      <td>890.549276</td>\n",
       "      <td>2861.919188</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>70.00</td>\n",
       "      <td>505.00</td>\n",
       "      <td>44996.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CA</th>\n",
       "      <td>8369.0</td>\n",
       "      <td>19.268013</td>\n",
       "      <td>5.156488</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>8369.0</td>\n",
       "      <td>34.825905</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>8369.0</td>\n",
       "      <td>1745.826152</td>\n",
       "      <td>9739.369974</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>100.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>607628.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CO</th>\n",
       "      <td>1264.0</td>\n",
       "      <td>19.311709</td>\n",
       "      <td>4.755893</td>\n",
       "      <td>3.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1264.0</td>\n",
       "      <td>33.617880</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1264.0</td>\n",
       "      <td>1092.541337</td>\n",
       "      <td>3662.253808</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>100.50</td>\n",
       "      <td>677.00</td>\n",
       "      <td>54681.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CT</th>\n",
       "      <td>455.0</td>\n",
       "      <td>19.536264</td>\n",
       "      <td>5.059808</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>21.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>455.0</td>\n",
       "      <td>34.457143</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>455.0</td>\n",
       "      <td>1071.661341</td>\n",
       "      <td>3535.945484</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>60.00</td>\n",
       "      <td>419.50</td>\n",
       "      <td>28441.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DE</th>\n",
       "      <td>127.0</td>\n",
       "      <td>19.409449</td>\n",
       "      <td>4.943096</td>\n",
       "      <td>6.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>21.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>127.0</td>\n",
       "      <td>34.448819</td>\n",
       "      <td>...</td>\n",
       "      <td>10.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>127.0</td>\n",
       "      <td>2650.912441</td>\n",
       "      <td>11231.890385</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>60.00</td>\n",
       "      <td>597.50</td>\n",
       "      <td>80760.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FL</th>\n",
       "      <td>3538.0</td>\n",
       "      <td>19.009893</td>\n",
       "      <td>5.510282</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>3538.0</td>\n",
       "      <td>34.764556</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>3538.0</td>\n",
       "      <td>677.399220</td>\n",
       "      <td>3539.926851</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>27.00</td>\n",
       "      <td>226.50</td>\n",
       "      <td>95572.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GA</th>\n",
       "      <td>1778.0</td>\n",
       "      <td>19.228909</td>\n",
       "      <td>5.468991</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1778.0</td>\n",
       "      <td>35.227784</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1778.0</td>\n",
       "      <td>751.740962</td>\n",
       "      <td>4922.872433</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>30.50</td>\n",
       "      <td>286.25</td>\n",
       "      <td>144453.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HI</th>\n",
       "      <td>267.0</td>\n",
       "      <td>19.535581</td>\n",
       "      <td>4.897603</td>\n",
       "      <td>5.0</td>\n",
       "      <td>18.00</td>\n",
       "      <td>21.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>267.0</td>\n",
       "      <td>34.029963</td>\n",
       "      <td>...</td>\n",
       "      <td>10.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>267.0</td>\n",
       "      <td>1042.581948</td>\n",
       "      <td>3082.640922</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>100.00</td>\n",
       "      <td>606.00</td>\n",
       "      <td>29025.46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IA</th>\n",
       "      <td>295.0</td>\n",
       "      <td>19.606780</td>\n",
       "      <td>4.968057</td>\n",
       "      <td>5.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>295.0</td>\n",
       "      <td>34.155932</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>295.0</td>\n",
       "      <td>781.244508</td>\n",
       "      <td>2482.605976</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>53.00</td>\n",
       "      <td>328.00</td>\n",
       "      <td>24894.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</th>\n",
       "      <td>288.0</td>\n",
       "      <td>19.163194</td>\n",
       "      <td>4.862331</td>\n",
       "      <td>3.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>288.0</td>\n",
       "      <td>34.086806</td>\n",
       "      <td>...</td>\n",
       "      <td>8.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>288.0</td>\n",
       "      <td>1060.069201</td>\n",
       "      <td>7440.305970</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>73.00</td>\n",
       "      <td>433.50</td>\n",
       "      <td>122876.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IL</th>\n",
       "      <td>1864.0</td>\n",
       "      <td>19.178648</td>\n",
       "      <td>5.096677</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1864.0</td>\n",
       "      <td>34.934013</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1864.0</td>\n",
       "      <td>1060.549238</td>\n",
       "      <td>5331.711575</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>56.00</td>\n",
       "      <td>471.25</td>\n",
       "      <td>186540.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IN</th>\n",
       "      <td>765.0</td>\n",
       "      <td>19.183007</td>\n",
       "      <td>5.103687</td>\n",
       "      <td>2.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>765.0</td>\n",
       "      <td>34.533333</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>765.0</td>\n",
       "      <td>531.817686</td>\n",
       "      <td>2058.496167</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>35.00</td>\n",
       "      <td>256.00</td>\n",
       "      <td>30465.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KS</th>\n",
       "      <td>322.0</td>\n",
       "      <td>19.273292</td>\n",
       "      <td>5.044336</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>322.0</td>\n",
       "      <td>34.437888</td>\n",
       "      <td>...</td>\n",
       "      <td>10.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>322.0</td>\n",
       "      <td>1035.186398</td>\n",
       "      <td>4160.863087</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>61.00</td>\n",
       "      <td>435.75</td>\n",
       "      <td>54387.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KY</th>\n",
       "      <td>461.0</td>\n",
       "      <td>19.351410</td>\n",
       "      <td>5.239705</td>\n",
       "      <td>3.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>461.0</td>\n",
       "      <td>34.262473</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>461.0</td>\n",
       "      <td>555.055228</td>\n",
       "      <td>1849.002027</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>35.00</td>\n",
       "      <td>200.00</td>\n",
       "      <td>21264.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LA</th>\n",
       "      <td>487.0</td>\n",
       "      <td>19.328542</td>\n",
       "      <td>5.488378</td>\n",
       "      <td>2.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>487.0</td>\n",
       "      <td>34.601643</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>487.0</td>\n",
       "      <td>685.112053</td>\n",
       "      <td>2679.459996</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>43.00</td>\n",
       "      <td>301.00</td>\n",
       "      <td>27864.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MA</th>\n",
       "      <td>1055.0</td>\n",
       "      <td>19.099526</td>\n",
       "      <td>5.083230</td>\n",
       "      <td>1.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>1055.0</td>\n",
       "      <td>34.648341</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1055.0</td>\n",
       "      <td>1582.064085</td>\n",
       "      <td>8725.995962</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>105.00</td>\n",
       "      <td>834.50</td>\n",
       "      <td>232822.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MD</th>\n",
       "      <td>802.0</td>\n",
       "      <td>19.417706</td>\n",
       "      <td>5.078789</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>21.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>802.0</td>\n",
       "      <td>35.179551</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>802.0</td>\n",
       "      <td>584.282456</td>\n",
       "      <td>1754.578814</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>51.50</td>\n",
       "      <td>346.25</td>\n",
       "      <td>22151.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ME</th>\n",
       "      <td>247.0</td>\n",
       "      <td>19.777328</td>\n",
       "      <td>5.044821</td>\n",
       "      <td>1.0</td>\n",
       "      <td>18.00</td>\n",
       "      <td>21.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>247.0</td>\n",
       "      <td>35.425101</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>247.0</td>\n",
       "      <td>806.310769</td>\n",
       "      <td>2212.829658</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>96.00</td>\n",
       "      <td>500.50</td>\n",
       "      <td>21700.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MI</th>\n",
       "      <td>1262.0</td>\n",
       "      <td>19.255151</td>\n",
       "      <td>5.291191</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1262.0</td>\n",
       "      <td>34.832805</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1262.0</td>\n",
       "      <td>697.771434</td>\n",
       "      <td>3058.858466</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>46.00</td>\n",
       "      <td>283.00</td>\n",
       "      <td>45754.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MN</th>\n",
       "      <td>799.0</td>\n",
       "      <td>19.603254</td>\n",
       "      <td>4.554217</td>\n",
       "      <td>3.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>799.0</td>\n",
       "      <td>33.857322</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>799.0</td>\n",
       "      <td>1165.832829</td>\n",
       "      <td>3777.193502</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>100.00</td>\n",
       "      <td>668.00</td>\n",
       "      <td>43557.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MO</th>\n",
       "      <td>875.0</td>\n",
       "      <td>19.642286</td>\n",
       "      <td>5.303493</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>21.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>875.0</td>\n",
       "      <td>34.482286</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>875.0</td>\n",
       "      <td>824.415531</td>\n",
       "      <td>3520.605751</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>37.00</td>\n",
       "      <td>303.00</td>\n",
       "      <td>68551.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MS</th>\n",
       "      <td>187.0</td>\n",
       "      <td>19.085561</td>\n",
       "      <td>5.742986</td>\n",
       "      <td>1.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>21.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>187.0</td>\n",
       "      <td>34.128342</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>187.0</td>\n",
       "      <td>562.018717</td>\n",
       "      <td>2309.065873</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>31.00</td>\n",
       "      <td>155.00</td>\n",
       "      <td>20008.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MT</th>\n",
       "      <td>168.0</td>\n",
       "      <td>19.125000</td>\n",
       "      <td>5.144833</td>\n",
       "      <td>3.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>168.0</td>\n",
       "      <td>32.273810</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>168.0</td>\n",
       "      <td>871.349167</td>\n",
       "      <td>2276.152949</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>85.00</td>\n",
       "      <td>543.00</td>\n",
       "      <td>17381.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NC</th>\n",
       "      <td>1384.0</td>\n",
       "      <td>19.338150</td>\n",
       "      <td>5.327709</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1384.0</td>\n",
       "      <td>34.277457</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1384.0</td>\n",
       "      <td>731.124921</td>\n",
       "      <td>4009.162038</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>40.00</td>\n",
       "      <td>300.00</td>\n",
       "      <td>129045.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ND</th>\n",
       "      <td>67.0</td>\n",
       "      <td>19.253731</td>\n",
       "      <td>5.705774</td>\n",
       "      <td>4.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>21.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>33.074627</td>\n",
       "      <td>...</td>\n",
       "      <td>10.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>762.977612</td>\n",
       "      <td>2558.331008</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>45.00</td>\n",
       "      <td>183.50</td>\n",
       "      <td>15093.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NE</th>\n",
       "      <td>211.0</td>\n",
       "      <td>18.853081</td>\n",
       "      <td>5.391548</td>\n",
       "      <td>4.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>211.0</td>\n",
       "      <td>34.142180</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>211.0</td>\n",
       "      <td>709.729479</td>\n",
       "      <td>2197.641901</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>50.00</td>\n",
       "      <td>540.00</td>\n",
       "      <td>20371.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NH</th>\n",
       "      <td>224.0</td>\n",
       "      <td>20.053571</td>\n",
       "      <td>4.328111</td>\n",
       "      <td>7.0</td>\n",
       "      <td>18.00</td>\n",
       "      <td>21.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>224.0</td>\n",
       "      <td>34.785714</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>224.0</td>\n",
       "      <td>703.988348</td>\n",
       "      <td>1913.062360</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>53.25</td>\n",
       "      <td>628.00</td>\n",
       "      <td>19822.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NJ</th>\n",
       "      <td>972.0</td>\n",
       "      <td>19.202675</td>\n",
       "      <td>5.144771</td>\n",
       "      <td>2.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>972.0</td>\n",
       "      <td>34.691358</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>972.0</td>\n",
       "      <td>742.369506</td>\n",
       "      <td>2576.435420</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>50.00</td>\n",
       "      <td>375.50</td>\n",
       "      <td>34421.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NM</th>\n",
       "      <td>325.0</td>\n",
       "      <td>18.735385</td>\n",
       "      <td>5.455556</td>\n",
       "      <td>3.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>325.0</td>\n",
       "      <td>34.827692</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>325.0</td>\n",
       "      <td>869.596677</td>\n",
       "      <td>2737.170198</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>97.00</td>\n",
       "      <td>447.00</td>\n",
       "      <td>34408.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NV</th>\n",
       "      <td>746.0</td>\n",
       "      <td>19.462466</td>\n",
       "      <td>5.031371</td>\n",
       "      <td>3.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>746.0</td>\n",
       "      <td>35.095174</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>746.0</td>\n",
       "      <td>666.904249</td>\n",
       "      <td>2959.162379</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>40.00</td>\n",
       "      <td>319.75</td>\n",
       "      <td>55839.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NY</th>\n",
       "      <td>4436.0</td>\n",
       "      <td>19.119252</td>\n",
       "      <td>5.221150</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>4436.0</td>\n",
       "      <td>35.235798</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>4436.0</td>\n",
       "      <td>1386.456404</td>\n",
       "      <td>4891.390164</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>82.50</td>\n",
       "      <td>751.00</td>\n",
       "      <td>107148.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OH</th>\n",
       "      <td>1599.0</td>\n",
       "      <td>19.361476</td>\n",
       "      <td>5.351772</td>\n",
       "      <td>2.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1599.0</td>\n",
       "      <td>34.089431</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1599.0</td>\n",
       "      <td>881.474184</td>\n",
       "      <td>5196.013344</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>40.00</td>\n",
       "      <td>298.50</td>\n",
       "      <td>150670.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OK</th>\n",
       "      <td>434.0</td>\n",
       "      <td>19.391705</td>\n",
       "      <td>5.365489</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.5</td>\n",
       "      <td>23.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>434.0</td>\n",
       "      <td>34.214286</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>434.0</td>\n",
       "      <td>646.394493</td>\n",
       "      <td>2076.472311</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>50.00</td>\n",
       "      <td>305.00</td>\n",
       "      <td>24032.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OR</th>\n",
       "      <td>1048.0</td>\n",
       "      <td>18.782443</td>\n",
       "      <td>5.248222</td>\n",
       "      <td>3.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>1048.0</td>\n",
       "      <td>34.063931</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1048.0</td>\n",
       "      <td>1730.967137</td>\n",
       "      <td>9633.673534</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>125.00</td>\n",
       "      <td>789.25</td>\n",
       "      <td>194635.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PA</th>\n",
       "      <td>1596.0</td>\n",
       "      <td>19.107143</td>\n",
       "      <td>5.254327</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>1596.0</td>\n",
       "      <td>35.007519</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1596.0</td>\n",
       "      <td>709.912036</td>\n",
       "      <td>2451.161495</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>50.00</td>\n",
       "      <td>347.75</td>\n",
       "      <td>42997.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RI</th>\n",
       "      <td>159.0</td>\n",
       "      <td>19.327044</td>\n",
       "      <td>5.276527</td>\n",
       "      <td>2.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>21.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>159.0</td>\n",
       "      <td>34.515723</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>159.0</td>\n",
       "      <td>842.451447</td>\n",
       "      <td>2412.306250</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>70.00</td>\n",
       "      <td>437.00</td>\n",
       "      <td>15294.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SC</th>\n",
       "      <td>491.0</td>\n",
       "      <td>19.492872</td>\n",
       "      <td>5.222933</td>\n",
       "      <td>2.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>21.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>491.0</td>\n",
       "      <td>34.348269</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>491.0</td>\n",
       "      <td>491.157515</td>\n",
       "      <td>2191.581252</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>25.00</td>\n",
       "      <td>171.00</td>\n",
       "      <td>40650.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SD</th>\n",
       "      <td>88.0</td>\n",
       "      <td>18.602273</td>\n",
       "      <td>5.688342</td>\n",
       "      <td>2.0</td>\n",
       "      <td>15.00</td>\n",
       "      <td>19.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>31.636364</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>1015.426364</td>\n",
       "      <td>3096.384292</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>36.00</td>\n",
       "      <td>325.00</td>\n",
       "      <td>22917.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TN</th>\n",
       "      <td>947.0</td>\n",
       "      <td>19.167899</td>\n",
       "      <td>5.243974</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>947.0</td>\n",
       "      <td>34.759240</td>\n",
       "      <td>...</td>\n",
       "      <td>10.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>947.0</td>\n",
       "      <td>813.478838</td>\n",
       "      <td>3266.873290</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>51.00</td>\n",
       "      <td>420.00</td>\n",
       "      <td>67135.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TX</th>\n",
       "      <td>3424.0</td>\n",
       "      <td>19.378797</td>\n",
       "      <td>5.202128</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>3424.0</td>\n",
       "      <td>34.561040</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>3424.0</td>\n",
       "      <td>754.217684</td>\n",
       "      <td>2786.521804</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>43.00</td>\n",
       "      <td>303.25</td>\n",
       "      <td>50443.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UT</th>\n",
       "      <td>825.0</td>\n",
       "      <td>19.207273</td>\n",
       "      <td>5.154124</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>825.0</td>\n",
       "      <td>32.780606</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>825.0</td>\n",
       "      <td>1463.878945</td>\n",
       "      <td>7113.368004</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>125.00</td>\n",
       "      <td>795.00</td>\n",
       "      <td>136147.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VA</th>\n",
       "      <td>1161.0</td>\n",
       "      <td>19.205857</td>\n",
       "      <td>5.102721</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>1161.0</td>\n",
       "      <td>34.496124</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1161.0</td>\n",
       "      <td>746.397313</td>\n",
       "      <td>2472.404181</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>51.00</td>\n",
       "      <td>314.00</td>\n",
       "      <td>23690.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VT</th>\n",
       "      <td>136.0</td>\n",
       "      <td>18.639706</td>\n",
       "      <td>5.635434</td>\n",
       "      <td>4.0</td>\n",
       "      <td>15.75</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>136.0</td>\n",
       "      <td>34.448529</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>136.0</td>\n",
       "      <td>1652.271176</td>\n",
       "      <td>4880.316235</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>78.50</td>\n",
       "      <td>825.75</td>\n",
       "      <td>31866.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WA</th>\n",
       "      <td>1396.0</td>\n",
       "      <td>19.243553</td>\n",
       "      <td>4.931443</td>\n",
       "      <td>2.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1396.0</td>\n",
       "      <td>33.760745</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1396.0</td>\n",
       "      <td>1144.404047</td>\n",
       "      <td>3311.419275</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>105.00</td>\n",
       "      <td>655.00</td>\n",
       "      <td>33188.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WI</th>\n",
       "      <td>693.0</td>\n",
       "      <td>19.173160</td>\n",
       "      <td>5.169276</td>\n",
       "      <td>4.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>693.0</td>\n",
       "      <td>34.093795</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>693.0</td>\n",
       "      <td>862.581674</td>\n",
       "      <td>3565.071705</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>59.00</td>\n",
       "      <td>385.00</td>\n",
       "      <td>60022.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WV</th>\n",
       "      <td>145.0</td>\n",
       "      <td>19.758621</td>\n",
       "      <td>5.253670</td>\n",
       "      <td>4.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>145.0</td>\n",
       "      <td>35.131034</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>145.0</td>\n",
       "      <td>752.287586</td>\n",
       "      <td>2859.980896</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>35.00</td>\n",
       "      <td>148.00</td>\n",
       "      <td>23196.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WY</th>\n",
       "      <td>62.0</td>\n",
       "      <td>18.741935</td>\n",
       "      <td>4.759582</td>\n",
       "      <td>2.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>19.5</td>\n",
       "      <td>22.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>33.338710</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>547.322581</td>\n",
       "      <td>1045.967413</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>107.50</td>\n",
       "      <td>512.50</td>\n",
       "      <td>5044.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>50 rows × 64 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      blurb_length                                                     \\\n",
       "             count       mean       std  min    25%   50%   75%   max   \n",
       "state                                                                   \n",
       "AK           143.0  18.895105  5.184909  4.0  16.00  20.0  22.0  31.0   \n",
       "AL           416.0  19.810096  5.178267  4.0  17.00  21.0  23.0  31.0   \n",
       "AR           281.0  19.039146  5.909608  1.0  16.00  21.0  23.0  29.0   \n",
       "AZ          1147.0  19.394071  5.195638  1.0  17.00  21.0  23.0  30.0   \n",
       "CA          8369.0  19.268013  5.156488  1.0  17.00  20.0  23.0  31.0   \n",
       "CO          1264.0  19.311709  4.755893  3.0  17.00  20.0  23.0  30.0   \n",
       "CT           455.0  19.536264  5.059808  1.0  17.00  21.0  23.0  30.0   \n",
       "DE           127.0  19.409449  4.943096  6.0  17.00  21.0  23.0  30.0   \n",
       "FL          3538.0  19.009893  5.510282  1.0  17.00  20.0  23.0  33.0   \n",
       "GA          1778.0  19.228909  5.468991  1.0  17.00  20.0  23.0  32.0   \n",
       "HI           267.0  19.535581  4.897603  5.0  18.00  21.0  23.0  28.0   \n",
       "IA           295.0  19.606780  4.968057  5.0  17.00  20.0  23.0  30.0   \n",
       "ID           288.0  19.163194  4.862331  3.0  17.00  20.0  22.0  29.0   \n",
       "IL          1864.0  19.178648  5.096677  1.0  17.00  20.0  23.0  30.0   \n",
       "IN           765.0  19.183007  5.103687  2.0  17.00  20.0  23.0  30.0   \n",
       "KS           322.0  19.273292  5.044336  1.0  17.00  20.0  23.0  30.0   \n",
       "KY           461.0  19.351410  5.239705  3.0  16.00  20.0  23.0  31.0   \n",
       "LA           487.0  19.328542  5.488378  2.0  17.00  20.0  23.0  30.0   \n",
       "MA          1055.0  19.099526  5.083230  1.0  16.00  20.0  23.0  29.0   \n",
       "MD           802.0  19.417706  5.078789  1.0  17.00  21.0  23.0  32.0   \n",
       "ME           247.0  19.777328  5.044821  1.0  18.00  21.0  23.0  30.0   \n",
       "MI          1262.0  19.255151  5.291191  1.0  17.00  20.0  23.0  30.0   \n",
       "MN           799.0  19.603254  4.554217  3.0  17.00  20.0  23.0  33.0   \n",
       "MO           875.0  19.642286  5.303493  1.0  17.00  21.0  23.0  30.0   \n",
       "MS           187.0  19.085561  5.742986  1.0  16.00  21.0  23.0  28.0   \n",
       "MT           168.0  19.125000  5.144833  3.0  17.00  20.0  23.0  28.0   \n",
       "NC          1384.0  19.338150  5.327709  1.0  17.00  20.0  23.0  32.0   \n",
       "ND            67.0  19.253731  5.705774  4.0  17.00  21.0  23.0  28.0   \n",
       "NE           211.0  18.853081  5.391548  4.0  16.00  20.0  23.0  30.0   \n",
       "NH           224.0  20.053571  4.328111  7.0  18.00  21.0  23.0  30.0   \n",
       "NJ           972.0  19.202675  5.144771  2.0  17.00  20.0  23.0  29.0   \n",
       "NM           325.0  18.735385  5.455556  3.0  16.00  20.0  22.0  29.0   \n",
       "NV           746.0  19.462466  5.031371  3.0  17.00  20.0  23.0  29.0   \n",
       "NY          4436.0  19.119252  5.221150  1.0  17.00  20.0  23.0  31.0   \n",
       "OH          1599.0  19.361476  5.351772  2.0  17.00  20.0  23.0  30.0   \n",
       "OK           434.0  19.391705  5.365489  1.0  17.00  20.5  23.0  30.0   \n",
       "OR          1048.0  18.782443  5.248222  3.0  16.00  20.0  23.0  29.0   \n",
       "PA          1596.0  19.107143  5.254327  1.0  17.00  20.0  23.0  31.0   \n",
       "RI           159.0  19.327044  5.276527  2.0  17.00  21.0  23.0  29.0   \n",
       "SC           491.0  19.492872  5.222933  2.0  17.00  21.0  23.0  30.0   \n",
       "SD            88.0  18.602273  5.688342  2.0  15.00  19.0  22.0  31.0   \n",
       "TN           947.0  19.167899  5.243974  1.0  17.00  20.0  23.0  30.0   \n",
       "TX          3424.0  19.378797  5.202128  1.0  17.00  20.0  23.0  31.0   \n",
       "UT           825.0  19.207273  5.154124  1.0  17.00  20.0  23.0  31.0   \n",
       "VA          1161.0  19.205857  5.102721  1.0  17.00  20.0  23.0  31.0   \n",
       "VT           136.0  18.639706  5.635434  4.0  15.75  20.0  23.0  28.0   \n",
       "WA          1396.0  19.243553  4.931443  2.0  17.00  20.0  23.0  30.0   \n",
       "WI           693.0  19.173160  5.169276  4.0  17.00  20.0  23.0  30.0   \n",
       "WV           145.0  19.758621  5.253670  4.0  17.00  20.0  23.0  31.0   \n",
       "WY            62.0  18.741935  4.759582  2.0  16.00  19.5  22.0  26.0   \n",
       "\n",
       "      duration               ...     start_month       usd_pledged  \\\n",
       "         count       mean    ...             75%   max       count   \n",
       "state                        ...                                     \n",
       "AK       143.0  34.055944    ...             9.0  12.0       143.0   \n",
       "AL       416.0  34.706731    ...             9.0  12.0       416.0   \n",
       "AR       281.0  33.708185    ...             9.0  12.0       281.0   \n",
       "AZ      1147.0  34.619006    ...             9.0  12.0      1147.0   \n",
       "CA      8369.0  34.825905    ...             9.0  12.0      8369.0   \n",
       "CO      1264.0  33.617880    ...             9.0  12.0      1264.0   \n",
       "CT       455.0  34.457143    ...             9.0  12.0       455.0   \n",
       "DE       127.0  34.448819    ...            10.0  12.0       127.0   \n",
       "FL      3538.0  34.764556    ...             9.0  12.0      3538.0   \n",
       "GA      1778.0  35.227784    ...             9.0  12.0      1778.0   \n",
       "HI       267.0  34.029963    ...            10.0  12.0       267.0   \n",
       "IA       295.0  34.155932    ...             9.0  12.0       295.0   \n",
       "ID       288.0  34.086806    ...             8.0  12.0       288.0   \n",
       "IL      1864.0  34.934013    ...             9.0  12.0      1864.0   \n",
       "IN       765.0  34.533333    ...             9.0  12.0       765.0   \n",
       "KS       322.0  34.437888    ...            10.0  12.0       322.0   \n",
       "KY       461.0  34.262473    ...             9.0  12.0       461.0   \n",
       "LA       487.0  34.601643    ...             9.0  12.0       487.0   \n",
       "MA      1055.0  34.648341    ...             9.0  12.0      1055.0   \n",
       "MD       802.0  35.179551    ...             9.0  12.0       802.0   \n",
       "ME       247.0  35.425101    ...             9.0  12.0       247.0   \n",
       "MI      1262.0  34.832805    ...             9.0  12.0      1262.0   \n",
       "MN       799.0  33.857322    ...             9.0  12.0       799.0   \n",
       "MO       875.0  34.482286    ...             9.0  12.0       875.0   \n",
       "MS       187.0  34.128342    ...             9.0  12.0       187.0   \n",
       "MT       168.0  32.273810    ...             9.0  12.0       168.0   \n",
       "NC      1384.0  34.277457    ...             9.0  12.0      1384.0   \n",
       "ND        67.0  33.074627    ...            10.0  12.0        67.0   \n",
       "NE       211.0  34.142180    ...             9.0  12.0       211.0   \n",
       "NH       224.0  34.785714    ...             9.0  12.0       224.0   \n",
       "NJ       972.0  34.691358    ...             9.0  12.0       972.0   \n",
       "NM       325.0  34.827692    ...             9.0  12.0       325.0   \n",
       "NV       746.0  35.095174    ...             9.0  12.0       746.0   \n",
       "NY      4436.0  35.235798    ...             9.0  12.0      4436.0   \n",
       "OH      1599.0  34.089431    ...             9.0  12.0      1599.0   \n",
       "OK       434.0  34.214286    ...             9.0  12.0       434.0   \n",
       "OR      1048.0  34.063931    ...             9.0  12.0      1048.0   \n",
       "PA      1596.0  35.007519    ...             9.0  12.0      1596.0   \n",
       "RI       159.0  34.515723    ...             9.0  12.0       159.0   \n",
       "SC       491.0  34.348269    ...             9.0  12.0       491.0   \n",
       "SD        88.0  31.636364    ...             9.0  12.0        88.0   \n",
       "TN       947.0  34.759240    ...            10.0  12.0       947.0   \n",
       "TX      3424.0  34.561040    ...             9.0  12.0      3424.0   \n",
       "UT       825.0  32.780606    ...             9.0  12.0       825.0   \n",
       "VA      1161.0  34.496124    ...             9.0  12.0      1161.0   \n",
       "VT       136.0  34.448529    ...             9.0  12.0       136.0   \n",
       "WA      1396.0  33.760745    ...             9.0  12.0      1396.0   \n",
       "WI       693.0  34.093795    ...             9.0  12.0       693.0   \n",
       "WV       145.0  35.131034    ...             9.0  12.0       145.0   \n",
       "WY        62.0  33.338710    ...             9.0  12.0        62.0   \n",
       "\n",
       "                                                                        \n",
       "              mean           std  min   25%     50%     75%        max  \n",
       "state                                                                   \n",
       "AK      845.033566   2009.590111  0.0   1.0   54.00  493.00   12557.00  \n",
       "AL      435.806755   1637.321347  0.0   1.0   22.00  175.25   16002.00  \n",
       "AR      337.371886    958.518379  0.0   0.0   20.00  161.00    8003.00  \n",
       "AZ      890.549276   2861.919188  0.0   1.0   70.00  505.00   44996.00  \n",
       "CA     1745.826152   9739.369974  0.0   2.0  100.00  777.00  607628.38  \n",
       "CO     1092.541337   3662.253808  0.0   3.0  100.50  677.00   54681.00  \n",
       "CT     1071.661341   3535.945484  0.0   1.0   60.00  419.50   28441.00  \n",
       "DE     2650.912441  11231.890385  0.0   1.0   60.00  597.50   80760.00  \n",
       "FL      677.399220   3539.926851  0.0   1.0   27.00  226.50   95572.77  \n",
       "GA      751.740962   4922.872433  0.0   1.0   30.50  286.25  144453.00  \n",
       "HI     1042.581948   3082.640922  0.0   2.0  100.00  606.00   29025.46  \n",
       "IA      781.244508   2482.605976  0.0   3.0   53.00  328.00   24894.00  \n",
       "ID     1060.069201   7440.305970  0.0   5.0   73.00  433.50  122876.00  \n",
       "IL     1060.549238   5331.711575  0.0   1.0   56.00  471.25  186540.00  \n",
       "IN      531.817686   2058.496167  0.0   1.0   35.00  256.00   30465.00  \n",
       "KS     1035.186398   4160.863087  0.0   1.0   61.00  435.75   54387.00  \n",
       "KY      555.055228   1849.002027  0.0   2.0   35.00  200.00   21264.00  \n",
       "LA      685.112053   2679.459996  0.0   1.0   43.00  301.00   27864.00  \n",
       "MA     1582.064085   8725.995962  0.0  10.0  105.00  834.50  232822.00  \n",
       "MD      584.282456   1754.578814  0.0   1.0   51.50  346.25   22151.00  \n",
       "ME      806.310769   2212.829658  0.0  10.0   96.00  500.50   21700.00  \n",
       "MI      697.771434   3058.858466  0.0   1.0   46.00  283.00   45754.00  \n",
       "MN     1165.832829   3777.193502  0.0   4.0  100.00  668.00   43557.00  \n",
       "MO      824.415531   3520.605751  0.0   1.0   37.00  303.00   68551.00  \n",
       "MS      562.018717   2309.065873  0.0   1.0   31.00  155.00   20008.00  \n",
       "MT      871.349167   2276.152949  0.0   6.0   85.00  543.00   17381.00  \n",
       "NC      731.124921   4009.162038  0.0   1.0   40.00  300.00  129045.00  \n",
       "ND      762.977612   2558.331008  0.0   1.0   45.00  183.50   15093.00  \n",
       "NE      709.729479   2197.641901  0.0   1.0   50.00  540.00   20371.00  \n",
       "NH      703.988348   1913.062360  0.0   1.0   53.25  628.00   19822.00  \n",
       "NJ      742.369506   2576.435420  0.0   1.0   50.00  375.50   34421.00  \n",
       "NM      869.596677   2737.170198  0.0   1.0   97.00  447.00   34408.00  \n",
       "NV      666.904249   2959.162379  0.0   1.0   40.00  319.75   55839.00  \n",
       "NY     1386.456404   4891.390164  0.0   1.0   82.50  751.00  107148.74  \n",
       "OH      881.474184   5196.013344  0.0   1.0   40.00  298.50  150670.00  \n",
       "OK      646.394493   2076.472311  0.0   1.0   50.00  305.00   24032.00  \n",
       "OR     1730.967137   9633.673534  0.0  10.0  125.00  789.25  194635.65  \n",
       "PA      709.912036   2451.161495  0.0   1.0   50.00  347.75   42997.00  \n",
       "RI      842.451447   2412.306250  0.0   1.0   70.00  437.00   15294.00  \n",
       "SC      491.157515   2191.581252  0.0   1.0   25.00  171.00   40650.00  \n",
       "SD     1015.426364   3096.384292  0.0   1.0   36.00  325.00   22917.00  \n",
       "TN      813.478838   3266.873290  0.0   1.0   51.00  420.00   67135.00  \n",
       "TX      754.217684   2786.521804  0.0   1.0   43.00  303.25   50443.00  \n",
       "UT     1463.878945   7113.368004  0.0  10.0  125.00  795.00  136147.00  \n",
       "VA      746.397313   2472.404181  0.0   1.0   51.00  314.00   23690.00  \n",
       "VT     1652.271176   4880.316235  0.0  10.0   78.50  825.75   31866.00  \n",
       "WA     1144.404047   3311.419275  0.0   6.0  105.00  655.00   33188.00  \n",
       "WI      862.581674   3565.071705  0.0   1.0   59.00  385.00   60022.00  \n",
       "WV      752.287586   2859.980896  0.0   1.0   35.00  148.00   23196.00  \n",
       "WY      547.322581   1045.967413  0.0  10.0  107.50  512.50    5044.00  \n",
       "\n",
       "[50 rows x 64 columns]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "state_describe_fail = df_failed.groupby('state').describe()\n",
    "state_describe_fail"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will now create plots of the mean durations, grouped by state."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fa9849d8ba8>"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,8))\n",
    "plt.title('Distributions of average duration grouped by state')\n",
    "plt.ylabel('proportion')\n",
    "\n",
    "sns.distplot(state_describe_succ['duration']['mean'],color='green')\n",
    "sns.distplot(state_describe_fail['duration']['mean'],color='red')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Visually, there appears to be a significant difference in distributions; we will use a t-test to confirm."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Ttest_indResult(statistic=-18.101157995571793, pvalue=5.0951022801304901e-33)"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stats.ttest_ind(state_describe_succ['duration']['mean'],state_describe_fail['duration']['mean'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The p-value is much less than alpha value of 0.05; we can thus see that durations of Kickstarters is an important determinant, with failed kickstarters usually taking longer."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next we will compare the distributions of the average start and end months grouped by state."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fa9849d89e8>"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,8))\n",
    "plt.title('Distributions of average start_month grouped by state')\n",
    "plt.ylabel('proportion')\n",
    "\n",
    "sns.distplot(state_describe_succ['start_month']['mean'],color='green')\n",
    "sns.distplot(state_describe_fail['start_month']['mean'],color='red')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fa98493fe80>"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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k+GS344SVnMwcRXujtbJwpdtRAABAGIkORSfGmO6SXpA0UFKtpL2SvmStPXrOcZ0k/Z+kbEkNkr5trX07FBkBALiosjLp1Cm3U5wnvb5eKigISV/JNSc1oT71rNuqEqK0o+Fg0PteX7JetY21mtVvVtD7ijRJsUka33u81hev193D7lZsVKzbkQAAQBgIScFJkk/SL6y1H0qSMebfJf1M0ufPOe7bkk5bawcZYwZLWmWMGWStrQhRTgAAWnbqlLRkidspzlNXUCBlZYWkr8aq46o4uv2s25JuvUcK8nZKPp9PqwpWKbNLprKSQ/NcI830rOnaULpBeaV5uirzKrfjAACAMBCSJXXW2hNnik1+6yS19I7xPkm/8z9mj6SNkm4MekAAANBu5Zfnq/h0saZnTZfH43E7TlganDJYaUlpbB4OAAACJlQznD5ljPFK+rKkt1q4u6+k5usCCiVltqX9bdu2XX64MLJpE5c3jlSMfeRi7IMrvb7emU3UDhWEKFdjbKNOHD9x9m0nT6qgMrj9Ly5erBhPjNIa00L2XC9mZPLIdpFDCuzYj+g8QssOLtOGXRvUK6HXRY892Omgju07FrC+0Xb8zo9cjH3kYuwjV0cd+5AXnCT9l6QKSb8JRuMjR45UXFxcMJruMDZt2qTs7Gy3Y8AFjH3kYuxDIIRL19qioKBAWSHKdbzquFLqUs66LSk5WVk9gtd/dX21du7YqUkZkzRkwJCg9dMWSUlJITvnFxPose+R1kMrDq/Q3vq9mjR00kWPTUtLU1ZX989BpOJ3fuRi7CMXYx+52sPY19bWXtbknpBepc4Y87SkwZLus9Y2tXBIoc5eatdXUlEosgEAgPYnrzRPtY21mt53uttRwl5ibKKy07O1vmS9ahpq3I4DAAA6uJAVnIwxT8m5+twd1traCxw2T9KX/McPljRR0uLQJAQAAO3NqsJVyuicoX5d+7kdJSLM6DtDNQ01yivJczsKAADo4EJScDLGjJD0XUnpktYaYzYbY17337fZGJPuP/TfJXU1xuyV9Lak/2etPR2KjAAAoH0pKC9Q4clCTcuaxmbhITKg2wCld07XysKVbkcBAAAdXEj2cLLWbpfU4jtFa+2G8B2JAAAgAElEQVTYZt9XSpobikwAAKB9W124WjHeGE3uM9ntKBHD4/FoRt8ZemX7KyooL2CfJgAAcNnc2DQcAADgomoaarS+ZL0mpE9Qp5hOZ9/p86lz6XElHD+p+JOVijtZqfjyCsWfrFB8ufPf8kh1SQmqS4xXXVKC6hP/9n11SmeVDUhXbdckd55cOzc5Y7Je2/maVhau1MNdH3Y7DgAA6KAoOAEAgHZnY+nGTzcLj6moVur2fKVu3a/UbQfUa+t+xZ+sPO8xTVFe1SQnqjbZKSTFVFYrtqJasVUtbx1Z2bOrTgxK14lBGToxqI9ODOqjsv691RQbE9Tn1t51iumkSX0mKa8kT/cMu0cJMQluRwIAAB0QBScAANCueBqb5Fm8RC980kk3vvCiUvYflMfnkySdGJCm/JljdXREP1X0TlFNcqJquiappmuS6hPjpRb2evI0Nim6utYpPlVUK/FouVL2lihlT4lS9pZo5Mb3FVXfIElqjI7SwfFDVDhtpAqnjdKpvr1C+tzbi+l9p2tN0RptKN2gmVkz3Y4DAAA6IApOAACgXehcfFTmrTUauHC1vnj0tCo7xej42G46MHu8Do8eqKMj+qmuc6dLN3QOX5RX9UkJqk9KUKWkskF9VJwz4tP7PQ2NSi48rO57StRzR74y127X1F/O09RfzlN531QVXTVKhdNG6eD4wWqKiYy3Tv269lNml0ytKlilGX1nsGk7AABos8h41wQAANqlqJo6DVj+kcxba5S+abeavB5tGNFNv7rGq6u+/JTik5KDnsEXHaXyAekqH5CufXMmat035qpzyTH1Xb1VmWu2athrKzTq5eWq6xSnA7PHy/t4JynV1+JsqnDh8Xg0PWu6Xtr6kvLL89W/W3+3IwEAgA6GghMAAAi52NNVGvendzVswSrFVtboVJ8eyvvy7dp643h95ZOfakyviZodgmLThZzu00Pb77ta2++7WtHVtUrP26V+K7Zo4NKNiln4sLqZTO24e4b23jBJDZ3iXcsZTJP7TNZrO17T6sLVFJwAAECbUXACAAAh42lo1LAFKzXh2YWKO1WlvXMmated03Vw3CDJ69WaojWqaajR9L7T3Y76qYaEOBXOGKPCGWOU+425um7dUSX875814yd/0ZRnXtOemyZrx90zVTaoj9tRAyo+Ol7j0sZp08FNum/kfYqNinU7EgAA6EAoOAEAgJDIXLNNU349X90OHFTJBKN135ir4ybzrGNWF65W76TeGpQyyKWUF1eflKATj96rdbMzlbp1v4bPXynz5hqNmLdCJROM8p64XUdGD3Q7ZsBMyZiidcXr9MnhTzQhfYLbcQAAQAdCwQkAAARVt32lmvLrecrM3aGTmala8vSXVTBzzHl7IJWcKtH+sv2aO3xu+9+k2uPRkdEDdWT0QOV+c67MwrUa/eJ7uuOxX6hg+mjlPXG7TgzOcDvlFTPdjbrFd9O64nUUnAAAQJtQcAIAAEERVVOnyf+1QMPnr1B9p3jlfmOutt8764JXeltVuErR3mhNyZgS4qRXprZrkj55+HrtuGemRr68XGOeX6q7P/Nj7Z0zURsfv02nM3q6HfGyeT1eTe4zWUv3L9Wp2lPqEtfF7UgAAKCDoOAEAAACrkvREV33j8+q+55ibZ87Uxu/dJtquyZd8Pj6xnqtL1mvcb3HKSn2wse1Zw0Jcdr82E3acc9MjXl+qUa9vFwD39uoXbdP00dfvFlVPbu6HfGyTM6YrMX7FmtDyQZdO+Bat+MAAIAOwut2AAAAEF76ffCx7nroKSUeKdOiZ76qNd/5zEWLTZL0yeFPVFVfpamZU0OUMnjquiQq7+/u1MtvPqWdd82QeWuN7rvz+xr1l2XyNDa5Ha/N0junKys5S+uK17kdBQAAdCAUnAAAQEB4Gho1+Zn5uv4ffqfyrF5a8OL3VHTVyFY9dm3xWnWL76ahPYYGOWXoVPdI1prvPKBX5/9IpROMcn41T7d94Rfqur/U7WhtNiVjiopOFankVInbUQAAQAdBwQkAAFyxTkfLdcuXf6kxL7yn7XNn6q0//oMq0rq36rHlNeXafmS7pmRMkdcTfm9NTmf01JJffUXv/9tjSi48orsffErj/viOPA2NbkdrtYnpE+X1eJnlBAAAWi383tUBAICQSttoddeDP1aPnYVa/uPPa813PqOm2JhWP3598Xr55FNORk4QU7rM49HeGyfr1Xk/VP6ssZr4u7d05yM/UfddhW4na5XOcZ01KnWU1pesV5Ov4y0LBAAAoUfBCQAAXLaUd97XzU/8SnWdO+mNPz+pfTdMatPjfT6fcotzNbDbQPVK6hWklO1HTUoXLf/pF7Xk6S8r4cRp3fnoTzXpvxbIW1fvdrRLmpIxRSdrT2rXsV1uRwEAAB0ABScAAHBZem/eq6ynfqPSCUP1+vPfVdnA9Da3kV+er4MVB8Nis/C2KJg1VvPm/VC7b8nR2D8v0W1feFqJh064HeuiRqWOUqeYTsotznU7CgAA6AAoOAEAgDbr/fEeDXl3vU5NGqslv3xC9Ynxl9VObnGuYrwxyk7LDnDC9q+ucyet/P4jWvL0l9W14JDueugppW/Y6XasC4qJitGE9An6+ODHqqircDsOAABo5yg4AQCANknbtFtDFm3Q8UHp2v/zf1JjfOxltVPfWK+80jyNSxunhJiEAKfsOApmjdXrf35S1SmdddPfPaMxzy2WfD63Y7VoSsYU1TfVa9HeRW5HAQAA7RwFJwAA0Grpebs0eEmejg3O0I67ZsgXd3nFJknacniLquqrNDUjspbTteRkv95647l/0oHZ4zX5N6/run98VjEV1W7HOs+ArgOU2ilVC3YucDsKAABo5yg4AQCAVon/cLUGvbdJx4Zkaudd0+SLjrqi9nKLctUtvptMDxOghB1bQ6d4Lf/JF5X79XuUtXKL7nz0p+p64KDbsc7i8Xg0OWOycotzVVBe4HYcAADQjkW7HQAAAHQAS5Yo8c13dXRoX+26/Sr5oq7sb1blNeXafnS7bhh0g7ye8Pr71/DoNHWqbrz8Bu57UHsHj1H/f35adz/6M+X/y9d1cubk8w4bnBin5PrkK0h6eXr3ukkLdy/UX1b9Vt8d/ZXWPahLF6lbt+AGAwAA7QoFJwAAcHHLl0sLFqh23GjtnDNC8l55gWh98Xr55FNORk4AArYvnaobVbFw/hW1USHpxIPXaPiClRrw5M+158ZJOjR20FnHnDx+QlHdU66on8vRVdKUhH56fsvzerJ0oDwez6UfNGcOBScAACJMeP1JEQAABNa2bdK8edK4cap4cG5Aik0+n0+5xbka2G2geiX1CkDI8FTXpZM++cy1KuvfW0PeXa+MdTvcjvSp+2LHyTYe1sZ6ltUBAICWUXACAAAtO3hQ+sMfpIwM6XOfk6KubM+mM/LL83Ww4qCmZrJZ+KU0xUZr+9yZOjIsSwPe/1j9Pvi4XVzB7vaYUYpTtJ6vznU7CgAAaKcoOAEAgPNVVEi//a0UGys98YQUFxewptcWr1WMN0bZadkBazOc+aKitOv2qSodN0h9c3do8KINUlOTq5m6eOJ1R/xYvVydpzpfg6tZAABA+0TBCQAAnK2xUfr976WyMunxx6WUwO0TVN9Yr7ySPI1PG6+EmISAtRv2vF7tvWGSCqeOUNrmvRr2xhp5G69gY/IAeCRhio77KrWodpurOQAAQPtEwQkAAJztr3+VrJUeekgaODCgTW8+vFnVDdXKyQy/zcKDzuNR/qyx2jd7vHruKtSUxZvkrat3Lc51ccPV3ZOoV6o3upYBAAC0XxScAADA33z4obRihXT99VJO4ItCuUW56hbfTaa7CXjbkaJk8jDZW6aoZ8lxjXr5fdeKTjGeKN2TkK23areosqnWlQwAAKD9ouAEAAAcu3Y5s5tGjZLuvDPgzZdVl2nH0R3KycyR18NbkCtxePRA5V07Tl1Kj2vE/JXyNLizvO6B+Imq8tXp7dpPXOkfAAC0X7zbAwAA0pEj0rPPSr16SZ//vOQN/FuE9SXr5ZNPORkspwuE0gG9tfvmKeqWf0hD31zjykbi02IHKd3blWV1AADgPBScAACIdPX10v/8j+TxSF/5ipQQ+M28fT6fcotzNShlkFITUwPefqQ6PHqA9l6brZ62SEMWbZB8vpD2H+Xx6t6EbL1bu03lTVUh7RsAALRvFJwAAIh0r78ulZZKjz0m9ewZlC7yy/N1qOIQs5uCoHTSUBVMG6XeW/ap//sfh7zodH/8RNWpQW/UbA5pvwAAoH2j4AQAQCTbuVNavlyaNUsaOTJo3awtXqsYb4yy07KD1kckK5g+SiXZQ5S5fqcyc7eHtO9JMf3UP6qHXqnJC2m/AACgfaPgBABApKqslJ57ztm36e67g9ZNXWOd8kryND5tvBJiAr9cD5I8Hu27foIOj+in/h9uUdpHu0PYtUf3x0/QstpdOtp4OmT9AgCA9o2CEwAAkerll6VTp5yldLGxQetmy6Etqm6oVk4my+mCyuPR7ltydHxQHw1anKee2/ND1vX9CRPVqCa9VvNRyPoEAADtGwUnAAAi0YYNUl6edMstUr9+Qe1qbfFapSSkyHQ3Qe0Hki/Kq513TtPJzFSZhWuVXHA4JP2Oiu6jYdFpeplldQAAwI+CEwAAkebECemll6QBA6QbbghqV2XVZdp5dKdyMnLk9fC2IxSaYqK1fe5MVXfrrOELVimuvCLofXo8Hj0QP1Gr6vaquLEs6P0BAID2j3d+AABEkqYmZ9+mpiZnKV1UVFC7W1+yXj75uDpdiDXGx2r73JmSz6cR81fKW9cQ9D7vS5ggn3yaV70p6H0BAID2j4ITAACR5P33JWule++VevYMalc+n09ri9ZqUMog9UwMbl84X01KF+26/SolHi2XeTtX8vmC2t+Q6F4aH92Xq9UBAABJFJwAAIgcJSXS669LY8ZIV10V9O4OlB/Q4crDmpoxNeh9oWVlA9N14Oqx6rmrUJlrtwe9v/sTJmhDfb72NRwNel8AAKB9o+AEAEAkaGiQ/vQnKSFBeughyeMJepe5RbmKjYpVdnp20PvChRVPHqYjI/qp34otStlTHNS+7kuYKEn6K7OcAACIeBScAACIBMuWScXFTrGpS5egd1fXWKe80jyN7z1e8dHxQe8PF+HxaPdNk1XRO0VD31yjhGMng9ZV36gUXRUzUK9UbwxaHwAAoGOg4AQAQLg7flx65x1p7FjnKwS2HNqi6oZq5WSyWXh70BQTrR33zFBTdLRGzF+hqJq6oPV1f8JEbW0o0fb60qD1AQAA2j8KTgAAhLtXX3X+vffekHW5tnitUhJSNKT7kJD1iYur7ZKoHXdPV3x5pYa9sdq5UmEQzI3Pllce/bWGWU4AAEQyCk4AAISzrVulzZulm2+WuncPSZdl1WXaeXSncjJy5PXwVqM9OZWZqr1zJihl/0FlrdoalD56RXXRNbFD9XJ1nnxBvjIeAABov3gXCABAuKqrk155RUpLk669NmTdritZJ598yslgOV17dGjcYB0aPUB912xTcsHhoPRxf8IE7W08oo8aCoPSPgAAaP8oOAEAEK4WL5aOHZMeeECKjg5Jlz6fT7lFuRqcMlg9E3uGpE+03d7rJ6g6pbOGvrVW0dW1AW//rvhxilGUXqnmanUAAEQqCk4AAISjw4elJUukSZMkY0LW7f7y/TpceZjNwtu5ptgY7br9KsVUVmvwu+ulAC996+ZN1A1xI/RK9UY1+YKzVxQAAGjfKDgBABBufD7p5ZedWU333BPSrnOLchUbFavstOyQ9ou2q0jrrvyZY9TTFqn3ln0Bb/++hAkqbirTuvoDAW8bAAC0fxScAAAIN5s2STt3SnfcISUnh6zbusY65ZXmaXzaeMVHx4esX1y+4inDVdavtwa+t1EJx04GtO1b40YrTtGaX7MpoO0CAICOITQbOgAAgNCoqZHmzZMyM6WZM4PeXY/YrppQ53y/qHSlahpq9GjvGzWhPjXofbul1/Haiz6/Ht4kVYQwzxXxeGRvzVH2H9/V0DfXaPOjc+SLjgpI0128CZoTN0Lzqz/S074m/soJAECEoeAEAEA4WbhQOnlSevxxyRv8j/gxNXWqeGe+JOn16OXq7UnU0LVWFdod9L7dUt91gCrK91/w/rSbHwlhmitX17mT7M1TNHL+CvVbsUUHZo8PWNv3xI/XW7VbtOHoZk3p1z9g7QIAgPaPPzYBABAuSkqk99+Xpk2T+of2w/0hVegjzyHd2DhAXnlC2jeu3IkhGSodP1iZ63eq2/7SgLV7W/wYxSpa8wreDVibAACgY6DgBABAuJg/X4qPd/ZuCrHFXmdj6BuaBoS8bwTG/tnjVdkjWWZhrmIqawLSZrI3QdfHDdP8/EXyBfhKeAAAoH2j4AQAQDjYscP5uukmKSkppF03yadFUfs03tdbvRXavhE4TTHR2nnHVYquqdOQd9c5VzsMgLnx2SqsLNGGkg0BaQ8AAHQMFJwAAOjompqkBQuk7t2lWbNC3v1mz2Ed8lTqRmY3dXhVqd10YNZYdd9Top47CgLS5m3xYxTjjdH8HfMD0h4AAOgYKDgBANDRbdggFRU5S+liYkLe/bvefUryxWhGU2bI+0bglUw0OpXeXQOXblR01ZUvrevq7aTr06dr3o55LKsDACCCUHACAKAja2iQ3nxT6ttXmjAh5N2fqq/UCm+RrmnqpzgufhsevF7tvmmKomvrNfC9TQFp8p6sG1VwskAbSzcGpD0AAND+UXACAKAD67Jxo3TihHT33ZI39P9bf+vwCtV5GnVT08CQ943gqUrtqqKpI9Rre75S9pZccXu3971eMd4YzdsxLwDpAABAR0DBCQCAjqqyUl3WrpVGjpSGDnUlwiulS9S/KVlDfSmu9I/gKZw6QpU9kjV40QZF1dZfUVvd4pJ17YBrWVYHAEAEoeAEAEBHtWiRvDU10l13udJ9vk7qo5O7dGPTQHnkcSUDgscXHaXdN09R7Okq9f/g4ytub+7wucovz9emg4FZpgcAANo3Ck4AAHREx45JH3ygytGjpT59XImwKGqfoj1Rur6pvyv9I/hO9+mhkolDlf7RHnUpPHJFbd0+9HZFe6O5Wh0AABGCghMAAB3Rm29KHo/KZ8xwpfsGNWmJ94Cu7TFZ3RTvSgaERv7MMapJTtSQd9fJ09B42e2kJKRodv/ZLKsDACBCUHACAKCjKSyUNmyQZs9WY5curkRY5ylRmadG9/eZ40r/CJ2m2GjtvmmyOp04razVW6+orbnD52p/2X59fOjKl+gBAID2jYITAAAdic8nzZ8vJSZKN9zgWoxFUfuV4ovXNd0nupYBoVPeP02HRg9QZu4OJR46cdnt3DH0DkV5ojRvO1erAwAg3FFwAgCgI9m+XbJWuuUWKSHBlQgnVK1cT4mub+qvaG+UKxkQevtnj1ddpzgNeWed1Hh5S+u6d+qu2QNYVgcAQCSg4AQAQEfh80lvvCH16CG5tHeTJL3nzVejx6cbGwe6lgGh15AQp33XT1Dnw2WKX7vhstuZO3yu9pXt0+ZDmwOYDgAAtDcUnAAA6Cg2b5aKipzZTdHRrkTwyad3vfs0vKmH+inZlQxwz7GhfVXWr7cSFr0nnT59WW2cWVbH1eoAAAhvFJwAAOgImpqkt9+WUlOlSZNci7HTc1z53pO6qYnZTRHJ49G+6ybIU1vnzLa7DD069dDV/a9mWR0AAGGOghMAAB3Bxx9LxcXO7KYo9/ZNWuTdpzhflK5pynItA9xV1TNZNTOmSmvWSPn5l9XG3OFztefEHn1y+JPAhgMAAO0GBScAANq7M7ObeveWJrp3VbgqX52Wews0s6mvEhXjWg64r3rONVLnztIrrzivzza6c+idztXqdnC1OgAAwhUFJwAA2rtNm6TSUmd2k9e9/3W/Wb9VlZ56ltNBvvh46a67pAMHpHXr2vz4nok9NavfLJbVAQAQxkL2rtUY87Qx5oAxxmeMGXmBY35ojDlijNns//ptqPIBANAunZndlJYmZWe7GuX5ujz19XXRWF+qqznQTkyeLA0YIC1YIFVXt/nhc4fP1e7ju7X1yNYghAMAAG4L5Z9J35A0Q1LBJY573lo71v/1lRDkAgCg/dq4UTp0SLr1VldnN22tL1FeY6FuaRwkjzyu5UA74vVKDzwgVVRICxe2+eF3DrtTXo+Xq9UBABCmQvbO1Vq72lpbFKr+AADo8BobndlNffpI48a5GuXZqpWKU7RuaBrgag60M337StOmSR984Cz7bIPUxFTNzJrJsjoAAMJUtNsBWnC/MeZ6SYck/cBam9uWB2/bti04qTqYTZs2uR0BLmHsIxdjH1zp9fWqK7jUJN3ASty6VT0OH9aRu+5SddGF/2ZTEORcVarT8zG5usEzRI3HK3VClZ/eV1tbqxPHTwS1//amT0Kfiz7nUJ4Tt879ydiTqjhaIUnyZmcrPS9P9c89p8Of+YzkOX8GXOzBgyo9duy82ycnTdbP8n+mVz98VYO6DAp67nDC7/zIxdhHLsY+cnXUsW9vBaffSXrKWltvjLlO0pvGmGHW2uOtbWDkyJGKi4sLXsIOYNOmTcp2eZ8PuIOxj1yMfQgUFEhZWaHrr7FR+uMfpYwMpV533QWX0xUUFCgryLn+r2qNTp+s1ecTr1Jy96qz7ouLi1NK95Sg9t/eXOo5h+qcnDh+wrVzn5ycrO6duv/thjvvVNTLLyvr+PGW9xpLS1NaC6/TDJOhX2z/hXZoh+7Lvi+IicMLv/MjF2MfuRj7yNUexr62tvayJve0q6vUWWsPWWvr/d+/J6lIUosbjAMAENbWr5eOHHF97yZJerZqlYZFpyknqp+rOdCOzZghZWRI8+ZJtbWtflivpF6akTVD83bMC2I4AADghla/gzXGpBhjfmKMedcYs7L5V6DCGGP6NPt+rKR+kmyg2gcAoENobJTeecfZH2fMGFejbKkv0vr6A/p/nabJ08JSKUDS3zYQLyuTli5t00PvGXaPdh7bqR1HdwQpHAAAcENb/mT6kqQcSQsl/e85X5dkjPlPY0yxpAxJy4wx2/23v2uMmeA/7CfGmG3GmC2S/iDpYWvtoTZkBACg48vNlY4dc2Y3uVzkebZqleIUrUcSclzNgQ5g0CBp/HjpvfekU6da/bC7h98tjzyat51ZTgAAhJO27OE0VVJPa23r50k3Y639e0l/38LtNzX7/tHLaRsAgLDR2Ci9+67Ur580apSrUSqbavVi9XrNTchWijdRx1Xjah50AHfcIW3eLC1cKD34YKse0jupt6ZnTde8HfP0g1k/CHJAAAAQKm2Z4fSJnNlJAAAgWDZskI4fl266yfXZTa/U5Om0r0Zf6jTD1RzoQHr1cvZzWr1aOtT6Sepzh8/V9qPbtfPoziCGAwAAodSWgtP7khYbY75rjHms+VewwgEAEFGamqTFi53Nl0ePdjuNnq1apeHRaboqZqDbUdCR3HKLFBsrLVjQ6ofcPcy/rI7NwwEACBttKThNl1Qs6TpJDzf7eigIuQAAiDybNzuzQm64wfXZTR/XFyqvPl9f6jSDzcLRNp07S3PmSFu2SHv2tOohaZ3TNK3vNApOAACEkVbv4WStvTqYQQAAiGg+n7RokZSaKmVnu51Gv69apXjF6OGEyW5HQUd07bXSihXSa69J3/lOqx5yz/B79LXFX9OuY7s0tMfQIAcEAADB1pYZTjLGdDPGPGKMedL/b7dgBQMAIKLs3CkVFjozQ7xt+t9zwFU01egv1Rt0b0K2unkTXc2CDio2VrrtNunAAemjj1r1kLuH3S1Jmr9jfjCTAQCAEGn1O1pjTI6kfZIelzRa0pck7fPfDgAArsSiRVLXrtJk92cUvcxm4QiEnBwpPV16/XWpru6Sh/fp0kdXZV7FsjoAAMJEW/6E+mtJT1hrp1prH7DWXiXpy5L+MzjRAACIEHv3Srt3S9ddJ8XEuJ1Gz1at1MjodOXEDHA7Cjoyr1e6+27p6FHppZda9ZC5w+fqk8OfaPfx3UEOBwAAgq0tBachkl4957b5kgYFLg4AABFo8WL9f/buO7zJqv/j+Dvdi0JpGWXvW6AM2QhOkCUqDhBEUEBFBMEF7vX4cz4KCIiKuEGWCg5kiosle0vYpezRvUfy+yP4iMoqNjlJ+3ldV66Uu3dzPk3aJHx7zvcQHg6XX246CWvz4lmbt597wy5Xs3D59xo2hEsugbfegpSU855+SwPXsrpZWzXLSURExNcVpuC0E+j9t2M9cS2zExERkYuRkACbN0OHDhAcbDoNkzJ/JZRA+oW2MR1FigObzTXLKSkJXnvtvKdXiaxC2ypttaxORESkGChMwelBYIJlWSsty5phWdZvwERguHuiiYiIlADz50NICFx1lekkJDsymZq1ittCW1DGL8x0HCkuqlWDHj1gzBhXgfU8ejboycajG9l5cqcHwomIiIi7XHDByW63LwdqAxOAtcB4oM6p4yIiIlJYR4/C2rVw5ZWuJXWGfZC5jAxnDsPDrzEdRYqbRx8FhwOee+68p97a4FZAu9WJiIj4uoDCnGy325OAKW7KIiIiUrIsXAgBAdCxo+kkFDgdTMj8kcuD6nBpYDXTcaS4qVIF7r8fxo+Hxx+HevXOemrV0lVpU6UNs7bN4onLn/BgSBERESlK5yw4WZY13263dzn18a+A80zn2e127ZssIiJSGElJsGKFq1F4ZKTpNHyTs5F9BSd5o9StpqNIcfXEEzBpEjz//Hl3revZoCePLHyE3Ym7qV22tmfyiYiISJE635K6T0/7eDLwwVkuIiIiUhiLFoHTCZ06mU4CwFsZS6jmX5YbQ5qYjiLFVfnyMGIETJ/uapR/Dn8sq1PzcBEREd91zhlOdrv99D8/bbfb7b/9/RzLsloVeSoREZHiLC0Nfv0VWrWC6GjTadiQl8fDAOoAACAASURBVMDPuTt4vdTNBNj8TceR4mzkSJg4EZ59FmbPPutp1UpXo1XlVszaNovH2z/uwYAiIiJSVAqzS92isxyfXxRBRERESowlSyAvD7p0MZ0EgHEZSwizBXF3WHvTUaS4i4qCRx6BOXNgzZpzntqzQU/WHV7HnqQ9HgonIiIiRem8BSfLsvwsy/IHbJZl2U79+49LXSDf/TFFRESKiaws+PFHaNoUYmNNp+F4QRqfZ62if2gbovzM75QnJcCDD7pm9j399DlP0251IiIivu1CZjjlA7lA+KmP8067bAMmui2diIhIcfPzz66ik5fMbnov8xdyyGd42DWmo0hJUaqUa6e6BQtcS0vPokaZGrSs1FJ9nERERHzUhRScagK1gQSg1mmXmkCk3W5/3m3pREREipPcXFi8GBo0gBo1TKch15nPxMyf6RTUgPqB5mdbSQly//1QsaJrlpPzjJsgA65ldWsOrWFv0l4PhhMREZGicN6Ck91uj8dVbNoLHLHb7fGnLvvtdnuW2xOKiIgUF8uWuRqGd+1qOgkAX2Sv47AjhRHhmt0kHhYW5io2/fKLqwh7FlpWJyIi4rsuqGm43W4vwDWjqTBNxkVEROQPBQWwcCHUrg1165pOA8BbGT9Qz78CXYIbmo4iJdHdd0O1auec5VQzqibNY5trWZ2IiIgPKkwB6QXgHcuyqluW5X9683B3hRMRESk2Vq2CxETX7CabzXQaVubuYVXePh4Ivxo/m17KxYDgYHjuOdfvxrffnvW0ng16svrQauKT4z0YTkRERP6twrzDnAz0B/bgaiKex59NxEVERORsHA6YPx+qVIG4ONNpAHgrYwmRthDuDG1rOoqUZP37u2b8PfOM6/fkDHo27AloWZ2IiIivKUzBqeapy98bh9dyQy4REZHiY8MGOHLEtTOdF8xuOliQxBfZaxkU1o5SfiGm40hJFhAAL7wAmzbBrDMvm6sVVYtmsc20rE5ERMTHXHDB6Y9m4bgaiOcCCacdExERkTNxOmHePChfHpo3N50GgIkZP1OAk2FhV5uOIgK33eaa+ffcc65eZ2fQs0FPfjv4G/tT9ns4nIiIiFysCy44WZYVaVnWp0A2cBDIsizrE8uySrstnYiIiK/7/XfYvx86dwY/872Sspy5vJf5CzcEN6ZWQDnTcURcvxfPPw92O8yYccZTtFudiIiI7ynMO99xQDgQB4QCjYCwU8dFRETkTObNg6goaNPGdBIAPs9axUlnBiPCO5iOIvKnm25yzXJ68cUzznKqU7YOTSs21bI6ERERH1KYglMXoJ/dbt9ht9tz7Hb7DmDAqeMiIiLyd7t2wY4dcO21rl41hjmcDt5IX0TjgCpcFVTPdByRP/n5wbPPwvbtZ+3l1LNBT1YeWElCSoKHw4mIiMjFKEzBKRv4+9z7GCCn6OKIiIgUI/PnQ0QEtG9vOgkAs7M3sL3gCE9EdMHmBc3LRf7illugYUPXLKcz7FjXs4Frt7ovf//S08lERETkIhSm4DQZWGRZ1n2WZXW1LOs+YAEwyT3RREREfFhCAmzeDB06QHCw6TQ4nU5eSv+euv7l6RniHc3LRf7Czw+eeQa2bYMv/tmrqW50XZpUaKJldSIiIj6iMAWnl4BXgVuBN09dv37quIiIiJxu/nwICYGrrjKdBIAFOVtZn5/A4xFd8LeZb14ucka33gr168N//nPGWU63NriV5QnLOZB6wEA4ERERKYwLbihht9udwIenLiIiInI2R4/C2rXQqROEhZlOA8BL6fOo6hfFHaGtTUcROTt/f9csp9tvh6++chWgTtOzQU+e+fEZvtz2JSPajDAUUkRERC5Eof7EaVnWQMuyFlmWtfXU9SDLstQEQkRE5HQLFriahHfsaDoJAL/k7GBp3i5GRnQiyGa+ebnIOfXqBZdccsZZTlaMRaPyjbSsTkRExAdccMHJsqzXgceAr4CRp64fBV5zTzQREREflJgIK1dCu3YQGWk6DQAvZ8yjvF8p7g7zjublIufk7w9PP+3qgTZnzj8+3bNBT5YlLONg6kED4URERORCFWaG011AB7vd/o7dbv/ebre/A3QCBrglmYiIiC9atAicTtdyOi+wJncfC3K28VB4R0JtQabjiFyY3r2hXr0zznLq2dC1W91Xv39lIpmIiIhcoMIUnNJOXf5+LLXo4oiIiPiwtDT49Vdo3Rqio02nAeDl9HmUsYVxf9iVpqOIXLg/Zjlt3AjffPOXT10Scwlx5eO0rE5ERMTLFabgNBb4yrKsay3Lqm9ZVidgFjDGsqxaf1zcE1NERMQHLFkC+fnQubPpJABsyzvE7JwNPBB+NZF+oabjiBROnz5Qpw688IJr1uBpbq1/K0v3L+Vw2mFD4UREROR8ClNwegu4GlgAbAXmAx2AccCuU5edRR1QRETEJ2RlwY8/wqWXQmys6TQAvJIxnzBbEMPDrzEdRaTwAgJcs5w2bPjHLKdeDXvhxKlZTiIiIl7sgreqsdvthdrRTkREpET5+WdX0alLF9NJANiTf5xpWasZEX4NMX4RpuOIXJy+feHFF12znG64AWyuzZHrl6tP4wqNmb5lOsNbDzccUkRERM6k0EUky7KqWZbV1rKsqu4IJCIi4nNyc2HxYmjQAKpXN50GgNczFuKPH4+EX2s6isjFCwiAp56C9eth7ty/fKpPXB9WHFjBvuR9ZrKJiIjIOV1wwcmyrFjLsn7GtXTuK2C3ZVm/WJZVyW3pREREfMGyZa6G4V27mk4CwMGCJD7KXM7AsMuo5F/GdByRf+eOO1yF3P/7v7/0cuod1xuA6Vumm0omIiIi51CYGU7vABuBKLvdHgtEAeuBd90RTERExCcUFMDChVC7NtStazoNAKMzFlOAg1Hh3tG8XORfCQyExx+H335zNeY/pUaZGrSt0pZpW6YZDCciIiJnU5iCU3vgEbvdngFw6noUcJk7gomIiPiEVasgMdE1u+lUfxmTTjjSeTfzF24PbUXNgBjTcUSKxl13QaVKrllOp+kT14dNRzex7fg2M7lERETkrApTcEoCGvztmAUkF10cERERH+JwwLx5UKUKxMWZTgPAf9MXkOXM43HNbpLiJCQERo6En35yLWE9pVfDXvjZ/Ji2WbOcREREvE1hCk6vA4sty3rVsqwhlmW9Ciw6dVxERKTk2bABjh71mtlNCQWJvJWxhH6hrWkQqBaLUszccw/ExMBLL/3vUIWIClxT8xqmbZmG87T+TiIiImLeBRec7Hb7+8BtQAxw/anrPna7fZKbsomIiHgvp9M1u6l8eWjWzHQaAJ5P+w4n8J+IG0xHESl64eHw8MOu37u1a/93uE9cH3Yn7WbNoTUGw4mIiMjfXVDBybIsf8uyPgGW2e32u+12e7dT10vO+8UiIiLF0ebNsH8/dOkCfoWZMOweW/MO8XHWcoaFX0X1gGjTcUTcY+hQKFPmL7Ocbq5/M0H+QWoeLiIi4mUu6B2y3W4vADoBDvfGERER8QFOJ8yd61re06aN6TQAPJk2hwhbME9GdDUdRcR9IiNh+HCYPRu2bAGgTEgZutbpyoytMyhwFBgOKCIiIn8ozJ9kxwAvWJYV6K4wIiIiPmHrVti3z9W7yd/fdBqW5u7im5yNPB7RhWi/CNNxRNxr+HCIiICXX/7foT5xfTiUdohf9/9qMJiIiIicrjAFpweAkUCaZVkJlmXt/+PaTdlERES8j9MJ330H0dFeMbvJiZPHUr8i1q80I8I7mI4j4n7R0XD//TBjBuzYAcD11vWEB4ZrtzoREREvElCIc+9wWwoRERFf8fvvsHcv9O0LAYV5GXWPRbadLM/bzaTSdxBmCzIdR0qIAoeDk5knL/h8/+wUUpLji2x8v0E9qTzuLTL/8zQnJ/wXgI61OjJz20wevexRgvw987sQGRxJVGiUR8byZklZSaTmpJqOYZR+FkRE/qkw75RXAE8DfYBKwCFgOvDSub5IRESk2PhjdlNUFLRtazoN+c4CXg/4Ecu/AgNCLzMdR0qQ3IIc9pzcc8HnRyTVZ036sSLN0LZHOxpO/5JvbmtKeqUYqkRWITk7mXG/jaNRhUZFOtbZdK7dWUUGIDUnlQW7F5iOYZR+FkRE/qkwS+reAa4BhgMtT11fCUx0Qy4RERHvs3077N7t2pku0HxLw0+yVrDLdpKXS/UgwGa+l5SIJ23q1wmnzUaTTxcC0KBcA8ICw1h1aJXhZCIiIgKFm+HUA6htt9uTT/17m2VZvwG7gIFFnkxERMTbzJ3r2pK9XTvTSch05vJc2rc0dVTippBLTccR8biMClHsuL4t1jfLWD+oG5nlytAsthmrD64mtyDXY8vqRERE5MwKM8PpCBD2t2OhwOGiiyMiIuKlVqyAnTuhc2evmN00PmMJBx3JPF5wNTabzXQcESM23NkFvwIHjacsAqBVpVbkFOSw6egmw8lERESkMDOcPgPmW5Y1HjgAVAWGAp9alnXNHyfZ7fYlRRtRRETEC4wbB6VLw+WXm05CoiODV9Lnc11wI9rkVjcdR8SYtCrl2NW5FfW//IUNd3WhbnRdSgeXZvXB1bSo1MJ0PBERkRKtMDOcBgOlgCdx9W16AogE7gM+OHWZXNQBRUREjPv1V9cMp06dvGJ20yvp80h1ZvNKqZtMRxExbsOALgTk5NHo8x/ws/nRvFJzthzfQmZepuloIiIiJdoFz3Cy2+013RlERETEa/3nPxATA1dcYToJ+/JPMD7jR/qHtqFRYGXiKbqt5kV8UXLNWPZ0aEbDmT+ysd+1tKrUiiV7l7D+yHraVTXfb01ERKSkKswMJxERkZJn+XJYvBgGD4Ygs02InU4nw1KnE2Dz58VSNxjNIuJN1g/sSlBGNg1n/kSNMjWICYth9cHVpmOJiIiUaCo4iYiInMt//gPlykHfvqaTMCdnA3NzNvNCxPVU9S9rOo6I10isV5X4yxvTaNoPBGXm0LJSS7af2E5KdorpaCIiIiVWYZqGi4iIlCzLlsGCBfDaaxD2941aPSvdkc3wlBk0CqjM8PBrzv8FIl4kJqgMLXLdO0bWnX0Jufsxrp25lsge3Zi3ax6HErbRocaNbhuz9NEUSLnIZa2RkRAVVbSBREREvIgKTiIiImfidMITT0DFijBsGBw/bjTOC+nfccCRxPSouwm0+RvNIlJYgdm5pM/9wq1jpAMValSk/MczqRCWQ4PQaL7+fTY9Nudiw+aWMQvKNYSw6Iv74s6dVXASEZFiTUvqREREzmT+fNfudM8+a3x20+a8g4zJ+IG7Q9vTLqiO0Swi3mx/uziCMrKpuHE3XRy12OuXwk5bkulYIiIiJZIKTiIiIn/ncLhmN9WqBYMGmY3idHBfylSi/MJ4NfImo1lEvF1KtfKkVClH1RXb6JBXlSCnH/P89piOJSIiUiKp4CQiIvJ3M2fCxo2uhuGGd6b7KGs5y/N283qpm4n2izCaRcTr2Wzsbx9HcFomdTYfpL2jKj/47SOPAtPJREREShwVnERERE6XlwfPPAONG0OfPkajnHCkMyr1Ky4PqsOdoW2NZhHxFUk1Y0mLLUvV5Vvpkl+dFFsOK2yHTMcSEREpcVRwEhEROd2HH8KuXfDSS+Bn9mXysdSvSHVm8U5kX/xseskWuSA2G/vbxRGanE63rblEO0OZ769ldSIiIp6md68iIiJ/yMx0LaNr1w6uu85olKW5u/gwaxkPh3ekYWAlo1lEfM3JulVIL1eGmsu20bmgBittB0kky3QsERGREkUFJxERkT9MmACHDsErr4DNPduoX4g8ZwFDUqZSzb8sz0Z0N5ZDxGfZbCS0a0jYyVTu2RpKgc3JYr99plOJiIiUKCo4iYiIACQnw6uvQrducPnlRqOMzVjMlvxDjI/sTbhfsNEsIr7q+CXVyCxbihbL9nJJQVkW+O01HUlERKREUcFJREQE4L//haQkV+8mg+z5R3gu7VtuCG7CDSFNjGYR8Wl+fiRc1pCIY0k8vCOaXX5J7LQlmk4lIiJSYqjgJCIicuQIjB0LvXtD06bGYuQ5C7gj+UNCbUG8U/p2YzlEiotjDWuSXTqcW389SaDDxnw/NQ8XERHxFBWcREREXnoJcnPhxReNxvhP+nesyYvn/dJ3UMm/jNEsIsWB09+PhLYNiDqUyLA95Vjkt488CkzHEhERKRECPDGIZVlvALcANYBGdrt9yxnO8QfGAV0AJ/Cq3W6f7Il8IiJSgu3dC++9B4MGQZ06xmIsy93Fy+nzGBB6GTeHNjOWQ6S4OdK4NtWWbmHEr7mMqZPDb7ZDtHdWNR1LRESk2PPUDKc5wBVA/DnO6QvUAeoCbYHnLcuq4f5oIiJSoo0cCYGB8MwzxiKkOrLol/wR1f2jeSvyNmM5RIojZ4A/B9o0oHp8Ml3jg5jnr2V1IiIinuCRgpPdbl9qt9sTznPabcD7drvdYbfbj+MqUvV0fzoRESmxliyBL7+EJ5+EypWNxRiROoP4gpN8VmYApfxCjOUQKa4ON61DblgwL/8SyArbQZLJNh1JRESk2POmHk7V+OsMqP2A5juLiIh75OfD8OFQsyY88oixGF9mrePjrBU8GdGVdkHmlvSJFGeOoAAOtqpP090ZND3kZLHfPtORREREij2P9HDypC1b/tEeqkRau3at6QhiiB77kkuPfeGUmz6dalu3suuNN0jZuvW851fKyyM3/lwrwwvvKGncHfgpjZ2x3JnYiPjEi7v9+CLOdTYFQQUknvzrtvI5OTn/OFbcVQ6tfM7v2ZP3ian7/nz3wd95w89Jas0YKi8P4OWfYUjPnVxzsvy/vs2UoBTSj6df1NcGHT7MoRMnLnpsb3rOzwvL89jzkLc6HHaYE7sv/vEsDG967MWz9NiXXL762HtTwWk/UB1Yferff5/xdEHi4uIIDg4uylw+Z+3atTRv3tx0DDFAj33Jpce+kI4fh8mT4dprqfPww2Cznf9r4uOhevUii+BwOrg3cTw5ufnMLH8fdQIqXtTtxMfHU70Ic53LycyTlM0t+5djwcHBlI0ue5avKJ7O9z176j5JPJlo7L4v7PfoLT8nh1vVp9PSzYQlppIUY6O2M+pf3V7p0qWJDou+uC+OjSX2In93ve05Pz45nuqZnnke8laxsbFUL+P++8DbHnvxHD32JZc3PPY5OTkXNbnHm5bUzQLusSzLz7KsckAP4EvDmUREpDh6+mlIT4e33rqwYpMbvJ35EwtztzE6sifWRRabRKRwDrawyA8K4KlfYb6fmoeLiIi4k0cKTpZljbMs6wBQBVhsWdbWU8e/tyyrxanTPgP2ADuBlcB/7Ha73gmIiEjRWrcO3n8fHngA6tc3EmFr3iFGpX7FdcGNGBx2hZEMIiVRflgwh5vVo+dW2JW0m1wKTEcSEREptjyypM5utw8Hhp/heLfTPi4Ahngij4iIlFBOp6vQVK4cPPeckQhpjmxuS36fUn4hfFC6PzZDM6xESqoDrS6h4prtDF2ax0/d99PJUdN0JBERkWLJm5bUiYiIuNfnn8Py5fDyy1C6tMeHdzqdDEj5hN/zD/N5mUFU8I/0eAaRki4vIpSjTevQbxP8lvq76TgiIiLFlgpOIiJSMqSnw6hR0KIFDBhgJMJrGQv4Mnsdr5W6mY7BZpbziQgcaNMQGzZuWp7EDlvJ2mVRRETEU1RwEhGRkuHll+HQIRg3Dvw8//I3P3sLT6bNoXdISx4Jv9bj44vIn3IjwzjYuCaD1sOv6dtMxxERESmWVHASEZHib9cuePNN6N8f2rb1+PC784/TJ/kDGgVUZnLpfurbJOIFjl7WCH8ntF6+nzRyTMcREREpdlRwEhGR4s3phGHDICgIXn3V48OnO7LpkTQRGzA76j7C/YI9nkFE/im7TAS7G1dl0Dony9K3m44jIiJS7KjgJCIixdsHH8CCBfDKKxAb69GhnU4ng1I+ZVv+YWZE3UOtgHIeHV9Ezi35smb4OaHeCjsOnKbjiIiIFCsqOImISPG1fz88/DBcdRXcf7/Hh/9vxkJmZq/llVI3cW1wA4+PLyLnllMmgo1NKtBnXR6/p+01HUdERKRYUcFJRESKJ6cTBg0ChwM+/NDjjcIX5mzjibTZ9AppzsjwTh4dW0QuXE7blvg5ofzKTaajiIiIFCsBpgOIiBiXlASpqaZT/CuV8vIgPr7objAyEqKiiu72TJg0CRYvhnfegZo1PTr07vzj9E56n4YBlfiw9J1qEi7ixQrKlGZpkyi6r0tiQevjlInU0lcREZGioIKTiEhqqqvHjw/LjY+H6tWL7gY7d/btgtO+ffDoo9CxIwwe7NGhTzjS6Zo4DoDZUUPUJFzEB2S1bYHfxkWErFwNnbqZjiMiIlIsaEmdiIgULw6HaymdzQaTJ7uuPSTTmUv3xAkkFCTxbdmh1FaTcBGfEFGmPPOahnPlet+f8SoiIuItVHASEZHi5d13YckSePPNop31dR75zgJ6J73Pqrx9fB41iHZBdTw2toj8e8cua4KfE4JWrDIdRUREpFhQwUlERIqPPXtg5Ejo1AnuvttjwzqdTu5P+ZxvczYxPvI2bgq51GNji0jRqBtZg5lNA2m24SjBqRmm44iIiPg8FZxERKR4cDhg4EAICPD4Urr/S/+e97OW8kR4F4aGX+2xcUWk6NiwseMyC5sTIlasMx1HRETE56ngJCIixcPbb8PPP8OYMVC1qseG/TBzGc+mf0P/0Da8VKqHx8YVkaLXOrI+nza1UW/Dfs1yEhER+ZdUcBIREd+3bh2MGgVdu8KAAR4b9vvszdybMoXOwQ2YXLo/Ng/OqhKRohdBECvaVcPphPLLN5uOIyIi4tNUcBIREd92/DjcdBOUKwcff+yxpXSrc/fRM3kSTQKqMKvMYAJt/h4ZV0Tcq11kQz68FKps3KNZTiIiIv+CCk4iIuK78vPhttvg6FH46isoX94jw9rzj3Bd0gQq+EUyt+wwSvmFeGRcEXG/2s4ovm4fg9PppPLSTabjiIiI+CwVnERExHeNGgU//giTJkGLFh4Zck/+cTqcHIMNmF92OBX9S3tkXBHxnE4RTXi3BcRu3ENIYqrpOCIiIj5JBScREfFNU6a4GoQPHw79+3tkyP0FiVyTOIYsZx6Lyz5EvYAKHhlXRDyrmbMCX7YvS04AVP9lo+k4IiIiPkkFJxER8T3r1sE998CVV8Ibb3hkyEOZR+lwcgzJjkwWRT9Io8DKHhlXRDzPho3rQhszpg1U2Laf8KNJpiOJiIj4HBWcRETEt5zeJHzmTAgMdPuQxzKO0XFBXw47UphX9gGaBVZz+5giYlZrZyW+blOG5BCo/vMG03FERER8jgpOIiLiOww0CU/MSuTaz65lX/oB5kYNo21QbbePKSLm2bBxY1BjXmsHMbsOEXnguOlIIiIiPkUFJxER8R0ebhKekp1C5ymd2X5iO3OumcSVwfXcPqaIeI92zip80zKS4+E2avy0AZxO05FERER8hgpOIiLiG8aO9WiT8PTcdLp93o0NRzbwRc8v6FT5CrePKSLexQ8bPQMa8cIVTsrsP0bU3iOmI4mIiPgMFZxERMT7jR0LDz0Et9zikSbhGbkZXD/telYeWMm0W6ZxvXW928cUEe90paMaC5qV4kBpP81yEhERKQQVnERExLudXmyaNs3tTcIzcjPoPq07v8T/wqc9PuXWBre6dTwR8W7++NHTFsfTVzkodSSRaHuC6UgiIiI+QQUnERHxXh4uNv2xjO6X+F/47KbP6Nu4r1vHExHf0NFRgx8ah7M7xp8aP28Eh8N0JBEREa+ngpOIiHgnE8Wmqd1Yun8pU2+eyu2NbnfreCLiOwLwo7czjlHXFBB+MpUKW/aZjiQiIuL1VHASERHv80ex6eabPVJsSstJo+vUrixPWM7nN39O77jebh1PRHxPF0dNfr0klK2xAVT/dRO2/ALTkURERLyaCk4iIuJdTi82TZ/u9mJTak4qXaZ2YUXCCqbdMo3b4m5z63gi4psC8ed2R0Me7pBPSEoGsRt2mY4kIiLi1VRwEhER71BQAM8/7/li05QurDq4ihm3zqBnw55uHU9EfNt1jtqsqRXMmupBVPt1M7asbNORREREvFaA6QAiIuLdkrKSSM1JdesYfsdPEDP4IUJ//JX03jdzctxrkHHIrWOm5qRy55w72XxsMxO6TqBFpRbEJ8ef9fyonFTyMk+6NdPFKAgq4KSHcuU68jwyjoi3CiaA3o6GDO68jrWTIHTxT3CbNhcQERE5ExWcRETknFJzUlmwe4Hbbr/i+p10eHIygakZ/Px0P+w3toP9S9w2HkBWXhZv/fYW8SnxDG4+GJvNdt7v8caQS7Ef3+rWXBcj8WQiZXPLemSsWmVqeWQcEW92g6MuM2N/Z07jAm78ZTl06AwxMaZjiYiIeB0tqRMRETMcDpp8PJ/u940mLzSIOR89hr1He7DZ3DpsZl4mY38by/6U/QxuPpimFZu6dTwRKV5CCWBoQTMe6JBLPg6YM8d0JBEREa+kgpOIiHhccHI6nR+eSOsJs9l79aXM/vRJEutVdfu4GbkZjF05lgOpBxjcQsUmEbk4VzuqU75UBca2tcHq1bB3r+lIIiIiXkcFJxER8agKG3dz8x0vUWXlNpaO6s0Pr9xDXkSo28fNyM1g7G9jOZh2kPua30eTCk3cPqaIFE82bIzIb8nL7R2kRATCrFngdJqOJSIi4lVUcBIREY8ove8IHUe9x42DXsfpZ+ObD0axrdfVbl9CB5Cem86YlWM4lHaIIS2G0KhCI7ePKSLFWw1K06/U5Yy8Kg9274b1601HEhER8SpqGi4iIm4VfjSJ5pO+pd63y8kPCWLtPd3Z1LejR2Y1wZ/FpiPpRxjSYghx5eM8Mq6IFH+PhFzNFc03smtVBrW/+gpb48YQoLfXIiIioIKTiIi4SXByOk0/mU/DGT9ic8LWIn/c4AAAIABJREFU265h/cCuZEeV8liG9Nx0xqwYw9GMowxtOZQG5Rp4bGwRKf4ibMG8EXUbw66dxPypx+Gnn6BjR9OxipUCRwFJ2UmczDxJRFAE5cPLE+gfaDqWiIhcABWcRESkSEUcOkG971bQeOpiArJy2HldG9beez3psdEezZGWk8aYlWM4lnGMoS2HUr9cfY+OLyIlw60hzZjUsD4/1LZz9dzv8GvbFsLDTcfyOYlZiexL3seJzBMczzzuus44zsmskzicjv+d52fzIyYshtiIWCpGVPzzulQsIQEhBr8DERH5OxWcRETkX4s4fJJai9dSa/Faym/dB8C+K5qwemgPkmpX8nie1JxUxqwcw/GM4wxtNZT6MSo2iYh72Gw2xpfuze2dXmDNu1kwdy706mU6lk/ILchlw5ENLE9YzvYT23HiarweHhhOTFgM1ctUp3ml5pQLK0fZ0LKk56ZzOP0wR9KOcDj9MFuObaHAWQC4ClEtYlvQpU4XKkdWNvltiYjIKSo4iYjIRQk/kvi/IlOFLa4twY/Xr8ZvD9zMng7NSKtSzkiu1JxURq8YzYnMEzzQ6gGsGMtIDhEpOS4JqEjnWp344NL5DPrpR/yuugrKlzcdyys5nU72p+xnWcIyVh9aTWZeJtGh0XSv151G5RtRLrwcYYFhF3RbBY4Cjmce50j6EXac3MHS/UtZdWgVjco3okudLtQpW8fN342IiJyLCk4iIqYUFEBWFmRmui5ZWa5ttW22M18CAiAkBIKD/7z288Bmo9nZRG/fT9ldBym7+yBRuw9RdtdBIo4lA3DCqspvw25iT8fmxopMf0jJTmHMyjGczDrJ8NbDqRddz2geESk5no7oxhUdVtB3SyohX36B35D7TUfyKpl5maxIWMHyhOUcSDtAoF8gzWKb0a5qO+pG18XPVvjXM38/fypGVKRiREWaVmzKdXWv46d9P/HD3h/47/L/UqdsHbrW6UrDcg2xeWBHVBER+SsVnERE3MHphLQ0OHrUdTlyBI4dg+PH/ywu5eT8+3GCgyE4mEr+/hAR4SpE/XE59TlCQlzFKn//M1/y8115srIgO9t1PWeO63hCAtV27qR6gWvJQkFgAEk1Yznc3OKEVZX4K5uQWtU7/oqfkp3C6JWjScpK4oFWD6jYJCIeFe4XzBOVb+Ol9pN4aclG2LYNGmijggJHAT/H/8x3O74jIy+DGmVq0LdRX1pUanHBM5kuVHhQONfVu46OtTqyLGEZC3cvZPyq8VSJrMJ1da+jWWyzIh1PRETOTQUnEZGikJoKO3eC3Q7x8a4iU1bWn58PCHAtryhXzlUYCg2FsLC/XoeGumYsOZ1nvuTluYpU2dl/Xp+65CYmEujv7zqekuIa/4/zClPYCglx5YiJgehouOQSUrpfy5robBLrVCalanmcAf5Ff//9S8nZyYxeMZrk7GSGtx6uZRQiYsQtIc346CqL3Rt2UG3aFAKffQECS+aOak6nk01HN/Hl719yNOMol8Rcwi31b6Fa6WpuHzs4IJhral7DFdWvYNXBVSzYvYD31r5Hu6rt6B3XmyD/ILdnEBERFZxERC5Oejrs2OEqMO3YAYcOuY4HB0ONGtCqFVSsCBUquC5ly7p1+duJ+HjCq1c/8yedTtfyvbNdAgP/uUSvc2c4dXspyfHs2b3Abdn/raSsJEavHE1qTqqKTSJilM1mY1x0P0Zd9yJffnaS3IXzCLruBtOxPG5/yn5mbZvFjpM7qBhRkWEthxFXPs7jy9oC/AK4rOpltKnShu92fMfcnXPZn7Kfwc0HUy7c7BJwEZGSQAUnEZELlZwMq1fDqlWwf7/rWHAw1K4NrVuDZUG1aq5lat7kj/5PAcXvKT8pK4nRK0aTmusqNtWOqm06koiUcLUDynFPi3v5Ys14rp83D2erttjKlYziRlJWEl/bv2blgZWEB4XTJ64Pl1e7HH8/s6+LfjY/brBuoGaZmny44UNeXvoydzW9iyYVmhjNJSJS3BW//32IiBSlrCzYsAF++w22b3fNFqpRA2680VVgqlHD+wpMJURSVhJvrniTtNw0RrQeQa2oWqYjiYgA0CUkjom3dCbvtQXET3ubesOfNx3JrfIK8pi/az7f7fgOJ0461e5E1zpdCQ0MNR3tLxpVaMRTlz/Fe2vfY+LqiXSp04Ub6t1gvCAmIlJcqeAkIvJ3Dgds3eoqMm3Y4OqdFBMD3bq5ZjJVqGA6YYn3R4PwtNw0Hmz9IDWjapqOJCLyF0Oq3MTnHbfQd95B1qz9lhbNrzcdyS3WHlpL/zn92XZ8G00rNqVng57EhMWYjnVWMWExjLpsFDO2zmD+rvnsTdrL3c3uJjI40nQ0EZFiRwUnEZE/5OXBypWwaJGr6XZ4OFx2mavIVKuWa2maGJeak8qYlWNIyU5hRJsRKjaJiFey2Wz06PYIu9eMImbWXHbVv5Q6YVVMxyoyGbkZPPvjs4z9bSwxYTHc1/w+Lo291HSsCxLoH8gdje+gVlQtPt/8OS/9+hKDmw/WTFkRkSLmvg62IiK+IiUF5s+HJ5+EKVNcfZnuvhv++1+4/XZXjyYVm7xCem46Y1eO5WTWSYa1GqaeTSLi1cKDwgm//U5qJDlZ8M0YUh1Z5/8iH7Bg1wLi3olj9MrR3NvsXhb3W+wzxabTXVb1Mh5r9xiBfoGMXTmWXYm7TEcSESlWVHASkZLr4EEYORLatYPZs6FKFXjwQVfhqWVL9WbyMhm5GYxdOZZjGccY2nIo9aLrmY4kInJeFRu04mhzi0G/pDNy97s4nA7TkS7aicwT9Jvdjy5TuxASEMIvd/3CO93f8enlaFVLV2XkZSMpE1KG8avGsy95n+lIIiLFhgpOIlLynDgBDzwANWvC6NFw9dXw1FMwYgTUr6/ZTF4oKy+Lcb+N43D6YYa0GMIlMZeYjiQicsEq9BqIX0AAN87Zzn/SvjMdp9CcTiefbfyMSyZcwowtM3j2imfZMHgDl1e/3HS0IlE6pDQPtXmIiKAI3vrtLRJSE0xHEhEpFlRwEpGSIycH3ngD6tSBiRNhwADYtQvGj4dq1Uynk7PIzs9m3KpxJKQmMLj5YBqWb2g6kohI4ZQpQ+D1Pei2Czasmcvs7PWmE12wvUl76TK1C/3n9KdedD3WD17PC1e/QHBAsOloRSoqNIqH2jxEsH8wY1eO5VDaIdORRER8ngpOIlL8OZ0wa5Zr9tLIka5G4Js2wXvvuWY5idfKyc9hwqoJ7Evexz3N7qFxhcamI4mIXBTbNdfgqFyJdxb4M+jI+3ywY4bpSOeU78hn9IrRxL0Tx/KE5UzoOoGlA5cW66J/TFgMD7V5CH+bP2NWjuFo+lHTkUREfJoKTiJSvK1cCe3bQ69eEBEBCxfC999Dw+L7hrm4yCvIY+KaiexK3MXASwf6ZENaEZH/8ffH7/a+VExx8OFPkdy9/DGGfT+MvII808n+YcORDbSZ3IZHFj5Ch5od2Hb/Noa2Goqfrfj/16FCRAUebPMgTqeTMSvHcCLzhOlIIiI+q/i/aohIyXT8OPTrB23bwp49MHkyrF8P115rOplcgAJHAe+tfY/tJ7ZzZ9M7aVmppelIIiL/Xp062K6+mh4rknib7ry9+m06ftaRYxnHTCcDIDMvk8cWPUaLSS04kHqAmbfO5OveX1O1dFXT0TyqUqlKjGgzgpyCHMasHENSVpLpSCIiPkkFJxEpXpxOmDoVGjSAGTNczcB37oRBg7TrnI9wOB18tOEjNh/bzO1xt9O2SlvTkUREik6PHhATw/0fbWZa58msOriKFpNasPbQWmOR8gryeH/t+9R/uz6vL3+du5rexe9Df6dnw57YSuhGGlUjqzKi9QjSc9MZvXI0KdkppiOJiPgcFZxEpPhISIDu3eGOO6B2bdeMpv/7P9dSOvEJTqeTqZumsvrQam6+5GaurHGl6UgiIkUrOBjuvBPi4+k9fTPLBi4DoP1H7Zm6aapHo+Q78vlo/UdYEyzu/e5eYiNi+enOn5h8w2SiQqM8msUb1ShTg+GthpOSncLE1RO9cvmjiIg3U8FJRHyfwwFvv+2a1fTTTzBmDCxbpj5NPsbpdDJr2yyWJiyla52udK7T2XQkERH3qFfPVXQaN45muzJYc+8aWlVuxR2z7+DRhY+S78h36/AFjgKmbJpC/bfrM/CbgZQNLcvc2+eyYtAKFfr/pnbZ2gy8dCD7UvYxdfNUnE6n6UgiIj5DBScR8W3bt8OVV8KwYa5+TVu2wIMPavmcD/pu53f8sPcHrq5xNTdaN5qOIyLiXqNGQY0aMGAA5W0RLO63mKEth/Lmijdp9E4jRq8YzfGM40U6ZIGjgOlbphP3Thz9ZvcjPDCcr3t/zep7VtOtbrcSu3zufJpWbEr3ut1ZcWAFS/YuMR1HRMRnqOAkIr7J6YQJE6BpU9i6FT7+GBYsgJo1TSeTi7BozyK+2/Edbau0pVfDXvpPj4gUf+Hh8MEHsHs3PPUUgf6BTOg2gZm3ziQqJIpHFj5C5dGV6TWrFwt3L8ThdFzUMIlZiUzfMp3+s/sT+2Ysfb7sg7/Nny96fsG6weu4wbpBz7kX4Lp619GkQhO++P0Ltp/YbjqOiIhPCDAdQESk0I4dg4EDYe5c6NbN9Ya9YkXTqeQi/Rr/K19s+4Jmsc3o17hfidh2W0QEgKuvhvvvh7fegltugfbt6dmwJz0b9mTLsS18sO4DPt30KbO2zaJ66eoMvHQgA5oOOOdNOp1ONh7dyPc7v+f7nd+z4sAKHE4H0aHRdKnThZvr30yPS3roubaQ/Gx+DGg6gNeWvcaktZN48vIniQmLMR1LRMSrqeAkIr5lwQJX34vkZBg3zrWUTn+Z9VmrD65m6uapNCzXkEGXDsLfT0shRaSEee01+P571x9SNmyAsDAA4srHMabLGF7t+Cpzts9h8vrJPPfTczz303ME+gUStCCIQP9AAvwCCPQL/N/HaTlpHM90LcVrHtucpy5/im51u9GyUks9x/5LoYGhDGkxhFeXvco7q99hVLtRBAcEm44lIuK1VHASEd+QkwNPPOFqCN6wISxaBI0amU4l/8LGoxv5cMOH1Clbh/ta3EeAn16SRKQEiohwzdTt0AGeeQbefPMvnw4OCOa2uNu4Le429ibtZebWmWzbt42YcjHkOfLId+STV5BHvtN1HegfyJXVr6RLnS5UjNDs36JWIaICgy4dxIRVE/hk4yfc0+weLUkUETkLvbsXEe+3bRvcfjts3Oia0fT66xAaajqV/AvbT2xn0tpJVI2sytCWQwnyDzIdSUTEnGuugSFDXH9UuekmaN/+jKfVjKrJY+0fY23oWpo3b+7hkPKHuPJx9LikB7O3z6ba7mp0qdPFdCQREa+kxdsi4t0+/hhatICDB+Hbb2H8eBWbfNyepD1MXD2R8uHlGd56OKGBejxFRHjtNdfGF7ffDomJptPIeXSu3ZmWlVoyZ/scthzbYjqOiIhXUsFJRLxTdjbccw8MGABt28KmTdC9u+lU8i8lpCYwftV4IoMjebD1g0QERZiOJCLiHUqVgunT4cgR12uf02k6kZyDzWajf5P+VImswuR1k9mXvM90JBERr6MldSIlTVISpKaaTnFuCQmupQVbtsDQofDww5CbC/Hx7hkvK8s9tyt/cST9CG+tfItg/2AebPMgpUNKm44kIuJdWrZ0LRt/6CHXxhgjRphOJOcQ5B/EfS3u46VfX2L4vOGsvne1loiLiJxGBSeRkiY11bXTm7favBk+/ND18f33Q+PGsHixe8ds08a9ty+czDzJ2JVjAXiwzYPaSlpE5GxGjIAlS2DkSGjXzrWsXLxWTFgM/Rv359217/LkD0/yRqc3TEcSEfEaWlInIt7B4YA5c2DCBIiOhiefhCZNTKeSIpCSncKYlWPIKchhRJsR2jVJRORcbDb46COoUAFuuw1SUkwnkvO4NPZS7mh0B2+ueJN5O+eZjiMi4jVUcBIR89LS4K23YN48119zR42CcuVMp5IikJ6bztjfxpKak8qwVsOoGlnVdCQREe8XHQ3TprmWkt97r/o5+YCnr3iaRuUbceecOzmcdth0HBERr6CCk4iYtX8/vPwy7N4N/fu7LkHqf1AcZOVlMf638RzLOMaQlkOoHVXbdCQREd/Rvj28+CLMnAnvv286jZxHSEAI02+dTnpuOv3n9MfhdJiOJCJinMd6OFmWVQ/4BIgGTgL97Xb7zr+d8zxwP3Do1KFldrt9qKcyioiHrV4Nn3wCERGuXhXVq5tOJEUktyCXt1e/zf7U/dzX4j7qx9Q3HUlExPc89hj8+KOrr1PbttCokelEcg4NyjVgXNdx3PPtPby+7HUeb/+46UgiIkZ5cobTu8Dbdru9HvA28N5ZzvvUbrc3PXVRsUmkOHI4YPZsmDzZVWR68kkVm4qRfEc+7615j12JuxjQdABNKqgXl4jIRfHzg88+gzJloFcvyMgwnUjOY9Clg+jVsBdPL3malQdWmo4jImKURwpOlmWVB5oB004dmgY0syxLTVpESpqsLJg4EebPh8svd239HBlpOpUUkQJHAR+s/4Atx7fQt1FfWlVuZTqSiIhvq1ABpkwBux0GD1Y/Jy9ns9mY1H0SVUtXpc+XfUjOTjYdSUTEGE8tqasKHLTb7QUAdru9wLKsQ6eOH//bub0ty+oEHAGes9vtKwoz0JYtW4oir89bu3at6QhiyPke+0p5eeTGx3sozV8FnDxJ+VmzCEhOJrFzZ9KbNYODB41kOV3ZuDgSDd0nRSm+CL+HoMOHOXTiBAB5YXkXdNtOp5O5B+eyKWkTHSp2oBrVijSTabk1G5J4MtF0jDPyVK7KoZX/MVZOTo7X3i/ucqb74XSevE9M3ffnuw/+rrj+nKQEpZB+PP2ivvb059nzKlOGioMHU/nddzkQFQV33eVV7/Uu9HWiODscdpgTu/98PJ9r+Bx3L7+bXp/24uVmL2Oz2YpsLG967MWz9NiXXL762Hush9MFehd4yW6351mWdS3wtWVZ9e12+8kLvYG4uDiCg4Pdl9AHrF27lubNm5uOIQZc0GMfH29m+dqWLfDpp+DvDw89RHS9ekR7PsWZRURQyseX9MXHx1O9KL+H2FhiT91efHI81TPPfdtOp5OZW2eyKWkT3et253rr+qLL4iWCgoIoG13WdIx/SDyZ6LFcwcHB/xjrTMeKu/N9z566Tzz52P9dYb/H4vpzUrp0aaLDLvLV7LTn2QvSrBmkpFBlwgRyqlen9qOPXty4bnAhrxPFXWxsLNXL/HkfNKc5R0KO8MQPT9DLrxd3N7u7SMbR+/ySS499yeUNj31OTs5FTe7xVA+nBKCyZVn+AKeuK506/j92u/2I3W7PO/XxolOfj/NQRhFxB6cTliyBCRNc2zw/+STUq2c6lRSxb3Z8w5J9S+hQswPd63U3HUdEpPix2eCDD6B1a2o88wysX286kZzHqHaj6FirI8PnDWf7ie2m44iIeJxHCk52u/0YsAHoc+pQH2C93W7/y3I6y7Iqn/ZxU6AGYPdERhFxg4ICmDYNZsyAJk1g1ChX0UmKlQW7FvD9zu9pX7U9PRv0LNJlAyIicprQUJgzh4LSpeH66+HQofN/jRjjZ/Pj0x6fEhYYRt+v+pJbkGs6koiIR3lyl7r7gAcsy9oBPHDq31iW9b1lWS1OnfOyZVlbLMvaCLwP9LPb7Uc8mFFEikpmJowfDz//DJ06uRqdlvDlrsXRj3t/5KvtX9GiUgv6Nu6rYpOIiLtVrMiusWMhORluvNH1eiteK7ZULO9f/z7rDq/j+Z+eNx1HRMSjPNbDyW63bwdan+F4t9M+vtNTeUTEjY4fh7ffhqNHoX9/aNfOdCJxg1/if2H61uk0qdCEAU0H4Gfz5N8wRERKrqy6dV0ziG+8Ee66C6ZPBz89B3urm+rfxKBLB/Hq0lfpWqcrl1e/3HQkERGP0CuTiBStXbvglVcgNRUefFDFpmJq6f6lTN08lbjycdzT7B4C/LxtDwoRkWLu+uvh9ddh1ix4/nnTaeQ8xnYZS62oWvSb3Y+U7BTTcUREPEIFJxEpOitWwJgxEBEBjz0GlmU6kbjBioQVTNk0hQblGnBf8/sI9A80HUlEpGR65BEYOBBefBE+/9x0GjmHiKAIptw8hQOpBxg2b5jpOCIiHqGCk4j8ew4HzJkDH38MtWu7ik0VKphOJW6w6uAqPtn4CVaMxZAWQ1RsEhExyWaDd96BK6+EAQNg4ULTieQc2lRpwzNXPMOUTVOYvmW66TgiIm6ngpOI/Du5ufD++zBvHrRvDyNGQHi46VTiBmsOreHD9R9St2xdhrYcSpB/kOlIIiISFASzZ0ODBtCjh2uzDvFaT13xFK0rt2bI3CEkpCSYjiMi4lYqOInIxUtJgTfegPXr4dZb4Y47wN/fdCpxg3WH1/HB+g+oXbY2Q1up2CQi4lWiolyzm2rWhOuug+XLTSeSswjwC2DKzVPIK8jjzjl34nA6TEcSEXEbFZxE5OIkJLiagx85AkOGwLXXuqb2S7GzaM8i3l/3PtVLV+eBVg8QEhBiOpKIiPxduXKweDFUqgRdu8KaNaYTyVnUKVuHcV3H8eO+Hxm9YrTpOCIibqOCk4gU3saN8N//uj4eORKaNDGbR9xm9u+zuX/u/VSLrMaI1iNUbBIR8WaxsfDDD1C2LHTqBJs2mU4kZzGg6QBuuuQmnvzhSTYe2Wg6joiIW6jgJCIXzul0Tdl/5x2oWBGeeAKqVjWdStzk882f03NWTxqWb8jw1sMJDQw1HUlERM6nalVYssTVT7FjR/j9d9OJ5AxsNhuTrp9EdFg0t391O1l5WaYjiYgUORWcROTCFBTAlCnw5Zdw6aXw6KNQurTpVOImH+yYwR1f3UH7au2ZctMUwoPUCF5ExGfUrOma6eTvDx06wK5dphPJGcSExfBJj0/Ydnwbjy581HQcEZEip4KTiJxfRga89RYsXQpdusA997h2xZFiaVzGEu5e/hidanfi+77fExEUYTqSiIgUVr16rp5OeXlwzTUqOnmpTrU78UjbR5i4ZiLf2L8xHUdEpEip4CQi53bsGLz2muuN6l13wU03gZ+eOoqrV9PnMyJ1Bj2qdeLr3l8TFhhmOpKIiFyshg1h0SLIzITLLoNVq0wnkjN46ZqXaFqxKQO/HsihtEOm44iIFBn9r1FEzm7HDnj1VUhPh4cegrZtTScSN3E6nTyb9g1PpM2mT0hLZl71NsEBwaZjiYjIv9W0KSxfDhERcPXVMHeu6UTyN8EBwUy7ZRqZeZncOedOHE6H6UgiIkVCBScRObNly2DsWChVytUcvG5d04nETZxOJ4+mfcGL6XMZFNqOz8oMJPD/27vv+Cjq/I/jr930XkkIIQVCGDrSUfEoiojoYcPe9aynVzx/9lO50+POOzuWE/XOLp53AgoWFBARBEQBUYYeAqGmt91smd8fA6EYMOAmS5L38/H4MruzM7OfyZed/e5nvvMdZ1iwwxIRkUDp2hUWLoTu3WH8eJgyJdgRyUG6pXbjidOeYPaG2Ty68NFghyMiEhChwQ5ARI4xfj+89x589BF1+XlUXXkxVrQTaoqDHVmTifG6qW5g/yJDI1v9YNley8fNFW/yz5r53BI9ksfjz8fp0LkIEZFWJz0d5s6F88+3x2IsLIQHHgCHI9iRyR7X9r+WWetmcfendzOq0yj6Z/QPdkgiIj+LEk4iso/bDS+/DN98g+v4wSz5RR5W9QaoDnZgTSvfNYC1u1b9aH7Pdj1bdcKpyu/iwrIpfOBeyV0xp/FQ3Fk49MNDRKT1io2FadPghhtg4kQ76fT88xCmXq3HAofDwQtnvkDf5/py0bsXsey6Za26HSIirZ9OY4uIrawM/v53+PZbmDCB6gnjsUJ0iGittvnKGV78D2a5v+PZ+It5OP5sJZtERNqCsDD7krr777dPMv3yl/ZYjXJMSIlO4dWzX2Vt8Vp+99Hvgh2OiMjPoh5OIgKbN8PkyVBbCzfeCH37tupL6Nq67z1FjC19imJ/NdOTbmZcZO8fL+T1QkEBAAmucgZ60po5ymNPlL4xRSSQ9jvOHqkOHs9Rr1vvqqsgKgruuQf697fbAV27HtWmAvk9kRCTRHl1aUC21ZwSdpRD+c+skz1GOjtzR+8bmLTsWcbE9+fcPhdAUlJAti0i0pzUfBZp6779Fl58EWJi4PbbISsr2BFJE5rjNjm79FmiHGHMS7mNAWE5DS9YXQ2LFgHgqymmqoFLDtsa59k3BzsEEWlN9jvOHqm6ggLIOcTx+0gkJcEtt8BLL8G4cXDhhXDiiUc8rlMgvycyxl3O1g/+E5BtNSdfu54QnRKw7U20evNpWC6/mncbg9v1JStJdwoWkZZH18uItFWWBR9/DM89Bx062HeiU7KpVXutZhFjSp4gMySRRSl3HjrZJCIibUf37nDvvZCXB6++aiefXK5gR9XmhTlCeCPxGjz4uGjerXh8nmCHJCJyxJRwEmmLvF547TV4913o1w9uuw0SEoIdlTQRy7L4c+UHXFb+MieG57Eg5f/ICQ3cWVgREWnhEhLgN7+xx3NasgQeftgeUFyCqktoGi8kXMaCnUu5c/adwQ5HROSI6ZI6kbamtBSefBJME04/Hc48E5zKPbdW1X43N1S8zmu1X3Fp1BCmJFxGhEN3IxIRkYM4nfZldfn59qX2kybB+efDL35xxJfYSeBcGDWIBe09PLroUU7IOoFccoMdkohIo+lXpkhbsmoVjB8P69fbg4WOH69kUytmerczpHgSr9cuZmLsL3kl4Solm0RE5PC6drUvsTMMeOMN+9L70pY3iHdr8o9B9zAkcwhXTbuKgqrADEwuItIc9EtTpK2YMQOOP96+E91tt8HQocGOSJrQ1NqlDNz9MDv8FXyUfCv3xY3DoTPUIiLSGHFx8Otfwznn2Ce3EZH6AAAgAElEQVSr7r8fZs8Gny/YkbVJ4SHhTJ0wlfCQcO74+g5qPDXBDklEpFGUcBJp7SzL7hY/frx91nL6dOjcOdhRSROps7z8pvxtLih7gd6hmSxLvYfRET2CHZaIiLQ0TieMGWMnm/Lz4Z137LGd1q8PdmRtUnZCNq+f8zrrK9dz4wc3YllWsEMSEflJSjiJtGa1tXDJJfYd6C68EObPh4yMYEclTaTQV8Lw4r/zZM1n/CZ6FHNTbiMrJDnYYYmISEvWrp3d2+n666G6Gv72N/tudlVVwY6szRnTZQzX5l/LK8tfYcqyKcEOR0TkJ2nQcJHWassWOOssWLYM/vIXuOMODfrZis13bOR3u2fgsjxMTbyOCVEDgh2SiIi0Fg4H9O8PPXrA++/Dp5/CN9/Yl9wdf3ywo2tTru16LQX+Am6ZdQsDOgygf0b/YIckInJI6uEk0hp9+SUMGmTfiW7aNLjzTiWbWqlqv5vbKt7h8tA3ae+MZ2nq3Uo2iYhI04iMhPPOswcVb9/e7un0wANELP4ah88f7OjahBBHCK+f8zppMWmcO/VcSms1oLuIHLuUcBJpTSwLnnkGRoyAmBhYtAjOPDPYUUkT+cy9mj67J/Jo9Wwu9vdjUcqdGKHtgx2WiIi0dpmZ8Ic/wA03QEQEsW++y6DnptP+m7U4NLB4k0uNTuWdCe+wtWIrl793OX5LyT4ROTYp4STSWrhc5EycCDffDKNHw5Il0LNnsKOSJlDur+W6slc5ueQxnDiZm3wbD/nGEuOMCHZoIiLSVjid0K8f3HMPFddeTl1MJF1nLWbwM9PJWGri8Crx1JSGdBzCo2Me5f017/PHOX8MdjgiIg3SGE4ircHmzXDOOaR+/TXcdx888IDdEJRWZ4ZrOTeUv8F2fzm3x5zKg3FnEuUIp4CCYIcmIiJtkcOBp2c3VrXzkrRxO9lfrCT/46Vkf7mK7cd1YUefzrgSY4MdZat086CbWb59OQ/Nf4jOSZ25ut/VwQ5JROQASjiJtHSffQYXXABuN+v+/ne63HZbsCOSJrDLV8mtFW/zlmsJvUMzmZZ0IwPDc4MdloiIiM3hoLRzBqWd2pNQsIOshd+T/cVKcr5YSVl2Otv7dma3kY0/XD8/AsXhcPDMuGfYXLGZ69+/nqz4LEbnjQ52WCIi9XTEF2mpLAseewxuvx0MA/73P8p1i+JWp9aq45nqeTxcNYtKy8WDsWdyZ+xphDt0+BYRkWOQw0F5bnvKc9sTUV5N+soNpK/cQLcZC/F+tIRd3XPY0aczFR3b6YYmARAWEsY7E95h2EvDOO+d8/jiqi/ond472GGJiABKOIm0TBUV8KtfwdSp9i2J//UviIuDr78OdmQSIB7Lx0s1C5hY9QFF/jLGRPTg73Hn0SssM9ihiYiINIo7IYbNw3qz+cReJBTuJH3FBtK+LyBj+Xpc8dGUdu5ASecMynLb44sMD3a4LVZ8RDwfXPwBQ18cyrg3xrHo2kV0iOsQ7LBERJRwEmlxli+HCRNgwwaYNAn+7/90hrAV8Vt+3nIt5Y+V01nv28UJYXm8kXgNwyO6Bjs0ERGRo+NwUJ6dTnl2OutOHUi71YUkr91Cux8KyPh2HZbDQUVmKiV5HQjNW2v34lbb5ohkJWTxwcUfcNLLJ3HGG2fw+VWfExuusbNEJLiUcBJpKSwLpkyBW26BlBSYMwdOOinYUUmAWJbFDPcK7q2cxkrvVvqGduT9pF9zekQvHGp0i4hIK+EPD2NHn87s6NMZh89PXNFuktcXkbRhG53mLYd5vyYxMpyq9slUZiRTlZ5MVUayPfC4vg8P67j2xzH1vKmc+eaZXPifC3nvwvcIdernnogEj45AIi1BVRXceCO89hqMHm1P09Ka7e3r8LGbGnY4atjpqKaYWrz4sQAL9v3rsB85LQeJRJBsRZJEJElWFElEEk0oDtRY3F+l38VbriU8V/05y7yb6RKSxpuJ13J+5ACcDt1pUEREWi8rxElFVhoVWWlsGnEcYdUuuiV0wTX9XWK3l9Dxq9U4/X4AvBFhVLVPpio9idrkeGqTYnElxuKOj8EK0fflXmPzxzL59Mnc8MEN3DrrViafPlknrkQkaJRwEjnWrVplX0K3ejVMnAh33w0hIU3yVrt8lSzwrGdh3Xq+d29lXeh2djqqKXG4ArL9cCuEZCJpZ0WTZcWTZcWRYyWQZcXTgVhCaRsNRsuyWOop4J8183nTtYRqy02v0A68kHAZV0QdT5ijaepXRETkWOaJicQ1ZhRrvVsAcHh9xOwuJ3ZbCbHbi4ndXkqHr9fg9Pnr17EcDtzx0dQm2gmourho6qIj8MRE4omOpG7P1BsV3mZ6SF0/8Ho2lG7gb1/+jc5JnfnDCX8Idkgi0kYp4SRyrLIseOUVuOkme0Dw2bNh1KiAbd5v+TG9O1jgWc+CunUsqFvPWt9OAMIJJdeZRALh5PkTSbNiSCOaNCuadCuGVKIJ25McckB9r6W9j734KcNFicNFKS5K95uWUMsORzULnVuZuV8iK8Ry0IFYsq0Ecq0E8qxE8vxJdCSu1SSiyv21vF77FS/UfMG33kKiHeFcEDmQ66JPYkhYJ52BFBER2Y8VGmL3amqfDHSxZ/r9RFTVEllaRWTZgSVl3VbCql0N9qW2HA48UeH4IsLxRoThjbSnvogwvBHheCPDDnjNnn/gay2pJ9VfTvkLG8s2cvsntxMTFsONg24Mdkgi0gYp4SRyLCorsy+he+stGDEC3ngDMjJ+9mZrPbXM3DSLqaVTmO1eTYlVDUCKI4YTw7twbfQwTgzPY0BYDtW1Fazateqo3icUJ6lEk2pF2zOshperpI5CRwWb95RCRwWbqWCRcys+h71SmOUk10qgs5VInpW0Z5pIMlFHFVtzW+/dxSfu7/mk7gdmub6jFg/HhWbxTPzFXBw1mARny9gPERGRY4LTiTs+Bnd8DOU56T9+3e8nrMZNWI2b8BoXYdUuwmpchFe7CK2tI9RdR6jbQ4i7juiqWkLddYS4PYTWeX/yrX2hIQ0mo7xREUSl74DUDIiPh4QEexof32S90n+K0+Hk1bNfxeV1cdPMm3B5Xfzu+N8FJRYRabuUcBI51syfD5deCkVF8NBDcMcdP6ux4vK6+GjdR7y96m1mrJlBVV0V7ZxxjI/sy7DwLpwYnkfXkPQf9a6p/rn70QhxhNPDSqWHlXrAfA8+NjsqWO8oY72jlA2OMpY6t/ORY2P9MklWZH3yaW8iKsdKIILgXo5W4q/mU/dqPnF/z+y61Wz07QYgy5nEFdHHc03UiQwIy1FvJhERkabgdOKJjcITG0XNkazn9xPq9tQno0Jdnn3JqP0f7/daqLuOyPIqwmrdhC1b++NtOhx2L/V27eySmmqPwbn3eWzTDoQeERrBf87/Dxe/ezG///j3uH1u7hx2Z5O9n4jIwZRwEjlWeDzw4IPwl79Ap06wYAEMHnx0m/J5+Hj9x7y96m2mmdOocFeQEpXCRb0u4oLUEQxfUU7oMTxOUBgh5FlJ5FlJQKf6+WW42OAoY4OjrD4Z9Z5zLXUOH2BflpdJHJlWLB2sODpYsWRYsXTAnkYG8JBXa9WxzruLNd4drPXtZI13Byu8W1jmKcTCIt4Rychwg9tiTuGUiO4NJvVERETkGOF04o2KwBsVcVSr90wySPGGQXm5XSoq7GlpKezaBaYJX31lD5mwV2QkdOxol6wse5qZCWFhAdopCA8J563z3uKK967grk/vwuV1cf/w+9UmEZFmoYSTyLFg3Tq45BJYvBiuugqeeMI+I3aEStwl/PnzP/Ps0mcpqiwiMTKR87qfx/k9z2dUp1GEhYRBQQGs/KgJdqLpJRJJf6s9/a329fN8+NlKlZ2EcpayyVFOEVUsd+6kxnFg9/gUK4p2VjSxhBFDOLFWGLGEk7MhFLfTJIYwHDhw48ONl0/dxTh9odRaHlyWh2qrjo2+3azx7qDQX3rAtts74+kW2p77Y8cxOqIHg8Nyj+mknoiIiARQaCjEJ0Ny8qGX8Xhg9247AbVrF+zYAVu3wqJFMHeuvYzTCe3b28mnTp0gPx98vp8XmjOUV856hfCQcB6c9yBur5uHT35YSScRaXJKOIkEk2XBv/4Ft95qN1SmTrXvSHeElhYt5anFT/Hmyjfx+D2cmncqz457ltO6nEZ4SHjg4z6GhOAkm3iyrXhG+LLr51tYlONmm6OKIkcVRdjT3Y4aqvGwy1FDlcNDNXW41v/Q8NFwz5jm4YQS5Qgj2hFOdkgyIyIM8kPS6BqaRn5oOvkhacQ5I5tnh0VERKRlCguzx+Q8eFxOvx+Ki6GwcF9Zs8Y+EQn2iciTToKTTiImLQ1694bwI2vfhThDePGXLxIREsGkBZNweV08OuZRJZ1EpEkp4SQSLEVFcP318P77MHw4vPqq3Z26kep8dbz7/bs8tfgpFm5ZSGx4LGdlncXEMybSLbVbEwbeMjhwkEgkiVYk3Q8aI+pgOWMvYvmsl6miDrATTBGEcFxqLzpEpxPiaDl3pREREZEWxuncN65T//775hcXw9q14HLBt9/CzJl0A7j5ZjjxRDj9dLsYRqPGgnI6nDw77lkiQyN5/KvHcfvcPH360zjVzhGRJqKEk0hzsyx45RX47W/tBsSjj9o9nBo5MHh1XTXPLX2Ofyz8B9uqttEluQtPnPYEV/S9gnWr1inZdBTCnWF2cooDeylFWKGU1ZYeYq1jiy/cR3FNccC2F+N1U71ne3V+T8C2KyLSmvj8/qM+9u5/nD3i9w3wMf/n0vdEE0lJscuYMZCTA7t2sf7f/yZv61aYPRtuu80unTrtSz6NGAHR0YfcpMPh4LExjxEREsHfvvwbVXVVPH/G80SFBeauuaW1pVS4KwKyrZYsPiKepKikYIchEnRKOIk0p61b4brrYOZMGDYMXnrJvja/ESrdlUxeMpl/LPwHu2t2M6rTKF785YuM6TJGZ6aaSJ3PzYbiDcEOo1FKiktIrjvMuBFHKN81gLW7VgHQObFzwLYrItKa/Jzvif2Ps0cq0Mf8n0vfE82kXTvKRo6EAQPs55s3w6xZdrvy5Zdh8mR7IPJRo+Dcc+GssxocU8rhcDDplEnEhsfyx7l/5Lud3/Gf8/9D56SfX48V7go+Wt8yxwoNpDF5Y5RwEgH0K1WkOViW3RDo2RPmzLGvxZ83r1HJpjJXGRPnTSTn8Rzu+vQuBnYYyIKrF/Dp5Z8yNn+skk0iIiIibVF2tj08w7Rp9uV3H38MN9wAP/wA11wD6ekwdqx9grOk5IBVHQ4H9w2/jxkXzWBj2Ub6P9+f6eb0IO2IiLRW+qUq0tQKCuwuzldfDX37wooV9iV0zsN//Iprirn3s3vJeTyH++fez0k5J7H42sXMumQWJ2Sd0EzBi4iIiMgxLzISRo+Gxx6D9eth6VL7crs1a/Yln047DV58EcrK6lc7o+sZLLtuGXnJeYx/azx3zr4Tr997mDcSEWk8JZxEmkpdHUyaBN27w+efw1NP2b2bunQ57GrlrnL+OOeP5D6Ry8PzH+bUvFP59vpvmXbhNAZlDmqm4EVERESkRXI47MvuJk2Cdevg66/t5NPatXDttdC+vX1X5BkzwOOhU1InFly9gBsG3MBfF/yVU145he1V24O9FyLSCijhJNIU5syxezPddZd9NumHH+DXvz5sr6bqumomfTGJTk904k+f/4mxXcay8saVvDPhHfq279uMwYuIiIhIq+Bw2He+25t8WrLEvuxu3jz45S+hQwe49VYiv1nJs+Oe4ZWzXmHx1sX0e74f8zbNC3b0ItLCKeEkEkjbt8Oll9qDNbrd8P778N//2tfYH4Lb6+bJr54k78k87vr0Lk7IOoFl1y1j6oSp9Ezr2YzBi4iIiEir5XDAwIHw+OP2jWxmzLDbrP/8JwweDN27c9nMLSw7YwbxEfGc/MrJ3PvZvVTVVQU7chFpoZRwEgkEnw+efhoMA955B+67D1atgnHjDrmKx+dhyrIp5D+Vz28+/A092vVgwdULeP/i9+mX0a8ZgxcRERGRNiUsDM44A95+2z5h+sIL0K4d3H033fqfyqoPcnmsahiPzHmI/Kfyeembl/D5fcGOWkRaGCWcRH6ujz6yuyrfcgsMHQrffQcTJ0JUVIOL+y0/b6x8gx7P9OBXM35Fh7gOzL5sNp9d8ZkGAxcRERGR5pWYaI/tNH++Pcj4nXcSunIVtzwyj6rJCTz+ITz+z2sY+MJA5mycE+xoRaQFUcJJ5GgtXw6nnmqP0VRZCVOnwocfQn5+g4tblsV7q9+j73N9ueS/lxAdFs30C6ez8JqFnNz55GYOXkRERETkIPn58NBD9l2WZ80i7JRTOX9eMSueg3//+Xv+8+tRXDxlLGuK1wQ7UhFpAZRwEjlShYVwxRXQr59914/HHrMHBZ8wwb42/iCWZfHRuo8YPGUwZ799NnW+Ot469y2+uf4bzjTOxNHAOiIiIiIiQRMSYp9UnToVR1ERPPEEvZK7MXkmvHTjhywb2Y1nHj6bzSUbgx2piBzDlHASaazycvuuc1272te73347rF8Pv/0tREQ0uMr8gvkM/9dwTnv9NHZV7+KlX77EqptWcUGvC3A69PETERERkWNcairceivO5cth2TL811zNmRvDueme96BTZ149qxP/++AfVNdVBztSETnGhAY7AJFjXnk5PPWU3ZOppAQuuwz+9CfIyTnkKvML5vOnz//EJxs+oX1se54e+zTX9r+WiNCGE1MiIiIiIse8fv2Ifu5FeHwyO9+YQt1zT3DJ9HU4p/2BeZ3vYMXpAygaPZScDt1b9MlVv+WnxlNDdV01NZ4a+7Fn32Ov34vf8jdYAL4u+prM+Exiw2OJC48jLiKufpoclUxWfBYJkQlB3kuRpqeEk8ihlJTYt4198kk76XTGGfDgg/YA4Q2wLIu5m+Yy8fOJzN00l7SYNB4Z/Qg3DbqJ6LDoZg5eRERERKSJREaSdvWvSbv611ibN7PpyYl0f30qw59eTPkLi3mvbwTfnt4f36AB5CTmEhcRF+yIAbu97vK6KHWVUlpbSqmrlDJXmT2tLat/XO356d5aToezwQLw1davcHldh10/PiKerPgsshOy66fZCdl0Se5Cz7SexEfEB2SfRYJJCSeRg+3cCY8+CpMnQ1UVnHMO3HuvPWZTAyzLYvaG2Uz8fCJfbP6CjNgMHhvzGNcNuE6JJhERERFp1RzZ2eT+fQr87Z8UzHiNLU/8ifO/WM8Vixeyqt1CXj4OpgxJIjqrEzkJOeQm5pKTkENUWMN3dD5aHp+HCndFfdmbPKpPKtXaU7fP/aN14yPiSYxMJCU6hbzkPOIi4ogJiyE6LNqehkfXP48KjSLUGXrYcVjH5I0hMz6TqroqKt2VVNZV1k+La4oprChkc/nm+unSoqXsqtl1wDZyEnLoldaLXmm96J3WG2eFk17eXrpiQloUJZxE9tq82e7R9Nxz4HLBBRfAPfdAr14NLm5ZFh+u+5CJn09k0ZZFdIzvyNNjn+aa/tcQGRrZzMGLiIiIiASR0wnDh7Oqo4s1VbVkfbiQLtM+5++fbGPSp6V83L2a53ov46l88IZAYmQisWGx9cmcgxM7TocTj9+D1+/F6/fi8dmPPX4PXp+XyrpKKtwVVLorqairaLBHkdPhJCEigaSoJDrGd6RXWi+SIpNIjEq0p5GJJEYmEuoM/M/iUGdo/fYbo9ZTS2FFIeZuk+92fsfKnSv5bud3fLz+Yzx+DwAh80Pond6boZlDGdrRLl1TuuomRHLMUsJJ2jbLgnnz7DGa3nvPvsvcxRfD3XdDt24NruLyunhz5Zs8uuhRvtv5HdkJ2Tw37jmuPO5KnXEQERERkTbPExvFhvNGseG8USRu3IYx/UtGzFzE6avqqEyMYvawDrwzOJbvE6DaU82O6h1U11VT7anG6/cecruhzlBCnaGEOcOIDY8lPiKe7MRs4sPjiYuIIz4ivr4kRSYRFxHXYsaSigqLomtKV7qmdOVM48z6+R6fhzXFa5j+1XSqoqtYXLSY11e+znNfPwdAUmQSQzoOqU9CnZB1wjFzCaOIEk7SNtXUwGuvwdNPw8qVkJxs33XuxhsPORj4rupdPLv0WSYvmczO6p30Se/Dy+Nf5uLeFxMeEt7MOyAiIiIicuwr65TBV785l8U3n0X2gu/oOuNLxs9awdnv+9nRuxNrxh3PxpP740qKw7IsPH4P1XXVWFj1yaW9iaa22JMnLCSMnmk9cXVwMWDAAAB8fh+rd69m0ZZFdtm6iAfXPYiFRYgjhEGZgxiZO5KRuSM5MftEDfMhQaOEk7Qt69bBP/8JU6ZAaSn07QsvvggXXQRRDV9H/v2u73l80eO8svwV3D43p+efzu+H/p5RnUa1yS89EREREZEjZYWGUDC8LwXD+xJVXEGXWV9hTF/ASZPe4MRH3qJooMH60QPZNLIf4QlJwQ73mBbiDKFnWk96pvXkmv7XAFDhrmDRlkXM3TSXuZvm8siXj/CXL/5CmDOMIR2HMCJnBCM7jeT4jscHfPwskUNRwklav5ISmDoVXnkFFi6EkBB7IPBbboFhw+zL6A7i9rqZsWYGLyx7gY/Xf0xkaCRXHnclvx36W7qlNnypnYiIiIiI/LTalHhWXjqalZecQvK6reR9vJTOnyxl+J9f5aS/vM6WIT1Yf+pACob3pS5OvXMaIz4inlPzTuXUvFMBqKqr4ovNXzBn4xzmbJrDw188zJ/n/5mIkAiGdhxq94DqNJIhmUM0LIg0GSWcpHWqq4MPP7STTDNm2M979oS//hUuuQQyMxtcbcWOFbz0zUu8tuI1imuL6RjfkYkjJnLjoBtJjU5t5p0QEREREWnFHA5K8jtSkt+RJTeNJ8UsJO/jJXSe/TUjH/gXvtAQtg3oSsEv+lLwiz5UZaQEO+IWIzY8ltO6nMZpXU4DoNxVbiegNtkJqAfnPcgD8x4gMjSSE7JOqL8Eb1DmIA0XIgGjhJO0HnV1MHeuPfj3O+/A7t3Qrh3cdBNcfjkcd1yDvZnKXGW8ufJNXvr2JZYWLSXMGcZZ3c7i6n5XM7rzaEKcIc2/LyIiIiIibYnDQXG3bIq7ZbP4lnNot2oTnT9dRvb8FZz4yFuc+Mhb7O7asT75tLtbtn1nPGmUhMgExnUdx7iu4wAorS3l84LPmbtpLnM2zeG+OfcBEB0WzbDsYYzMHcmoTqPon9G/Se7iJ22D/udIy1ZWBrNmwbRp9rSiAqKjYdw4uOIKOPVUCAv70WqV7kpmrp3Jf1f/l+nmdFxeF33S+/DEaU9wce+L1ZtJRERERCRYHA529erErl6d+Oo355JQsIPs+SvI+Xw5/V6ayYApH1DdLpEtQ7uzdXB3tg7qRm1qQrCjblGSopIY320847uNB6C4pph5BfPqL8G769O7AIgLj+MXOb9gZO5IhucO57j2xykBJY2m/ynSslgWrF4Ns2fD9Ol2jyavF9LSYMIEGD8eTjmlwQHAd1XvYro5nf+u/i+zN8ymzldHWkwaVx93NVf3u5r+Gf01CLiIiIiIyDGmPCedlTmjWXnpaCLKqshe8N2eBNQKjBkLASjJ68CWIXYCalv/fLzRkUGOumVJiU7hnO7ncE73cwDYUbWjvvfTnE1z+GDtBwDEhMVwfNbxDMsaxkk5JzEkcwgx4THBDF2OYUo4ybHNsmD9epgzBz77zE4wbd9uv2YY8Pvf20mmIUPswcAPWNVibclaZq2dxf9W/4/5m+fjt/zkJuZy86CbObvb2ZyQdYIumRMRERERaSHcibGsHTeUteOG4vD5SVlTSOZXP5C5eDU9/jOPPm98ij/Eya4eOWzv24UdfTqzo0+eekAdofTYdC7odQEX9LoAgKLKIuYXzGf+5vl8sfkLHpz3IBYWoc5Q+mf0Z1jWMIZ2HMrgzMFkJ2TrRL4ASjjJsaauDlauhCVL7DvKzZkDhYX2axkZMGoUjBxpl7y8A1a1LIsNpRvqs/BzN82lqLIIgJ7tenLPSfdwdrezOa79cToAioiIiIi0cFaIk93dc9jdPYflV55GiKuO9BXryVy8moxv1tJz6hz6vvYJABWZqfXJpx29O1PaOQN/+I+H3pCGdYjrcEACqsxVxsLChfUJqMlLJvPookcBaBfdjsGZg+vLoA6DSInWgO9tkRJOEjw+n3153JIl+8ry5XbSCewBv0eMgLvushNMhnHAoN9ev5fVu1ezZOsS5hbMZc7GORRW2Mmp9Jh0RuSOYGTuSE7ufDJdkrsEYQdFRERERKS5+CLDKRrcnaLB3QFw1nlINQtJX76e9BUbyFy8mvxZiwHwhzgp7dyB3UYWxV07UtzVntbF6/KwxkiMTGRs/ljG5o8FoM5Xx4odK1iydQmLixazeOtiZq6diYUFQG5iLn3T+9I7rTd90vvQO703XZK7aDyoVk61K03P47Evi/v+e7usWmVPTRPcbnuZuDgYMABuvRUGDbJLbm59gsntdfPdtmUs21O+2f4Ny3csx+V1AZAancqI3BHcmXsnI3NH0i21m3oxiYiIiIi0Yf7wMHb27szO3p1ZCWBZxG4rJm3VJlLWFJJibqHjou8x3l9Yv05lRgpluemU5bSnPCedspx0ynPaU52W2OAdr8UWHhLOwA4DGdhhIDdyIwAV7gqWbVvG4q2L+Xrb16zcsZIZa2bgt/wARIZG0qNdD/qk96FHag/yU/LJT84nLzmPyFCNwdUaKOEkP59lQWkpbNxol02b9j3euNFONnk8+5bPzYUePew7yPXubSeXDAPL4aCosoh1JetYW/Ip69avY23JWtYUr2H17tV4/V4AEiIS6JfRjxsH3kj/jP70z+hPt9RuOB26LaqIiIiIiByCw0FVh1SqOqSyYfTA+tlRxRUkr91C6urNpKzdQkLBDrp9u4CwWnf9Mp6oCMqz06jskEplRjJVGSt1mxoAAA1NSURBVClUZqRQ1d5+7I6PVkLqIPER8YzIHcGI3BH181xeFz/s+oEVO1awcudKVu5cyYfrPuRf3/6rfhkHDrISsshPthNQ+Sn55CbmkhWfRcf4jqTHpuu3XwvRbAknwzC6Av8GUoBi4HLTNNcetEwI8CRwGmABk0zTnNJcMcp+LAtqaqCkBIqLYfdu2LbNLtu3H/i4qAgqKw9cPzEROnWC7t3hrLPwd+9GWecObOkQyxZfKUWVRWyr3EZR5UKKlr/LxrkbWV+6nhpPTf0mwpxhdE7qTH5KPmd2PbM+udQpsZN6L4mIiIiISEDUpsSzNaUHW4f22DfTsojeVUZiwQ4SCnaQWLCdxE3bSdpQRNaX3xHq9hywjbroCKrTkqhNiSch533I6gzt2+8raWmQkgJJSfbVHW3090xkaCT9MvrRL6PfAfPLXGWsLV7L2pK1+6Yla3l71duUukoPWDbMGUZmfCZZ8VlkJWTRMc5OQrWLbkdaTBrtYvZMo9sRERrRnLsnB2nOHk7PAZNN03zNMIxLgeeBUQctcwnQBcjHTkx9YxjGbNM0NzVjnC2DZYHfD17vgcXjIXzrVoiKgtraH5fKykOXsrL6BJNVUoJj71hKB/FFR+Ful0xtuwSqcxKp7NeR4rQ4itpFUJDoYEOin63OakpqSyh1/UBp7ZcUFxTj3ej90bZSo1PpENeBnMQcTul8CvnJ+XRJ7kJ+Sj5Z8Vm6g5yIiIiIiDQ/h4OatCRq0pIoGtTtwNcsi8iyKmK3FRO3rYTYbcXEbi8hZlcZUcUVhC//Dj6Z++OT8nuFhEBysl2SkuwSH28novaW2Nh9j6OiiC8stK8qiYyEiIjDl9CWdyFTYmQigzIHMShz0I9eK64pZnP5ZgorCiksL2RLxRb7cUUhCwsXsrVyK3W+hn+7xkfEkxqdSkJEAomRiSREJpAQkXDA87jwOGLCY4gOi26wRIREEB4SXl9CnaHqANFIzfI/0TCMNKA/MHrPrDeBpw3DaGea5q79Fr0AeME0TT+wyzCM94AJwCONeJsQgLpDJElalLvuggUL9iWRfL6Gp4fQFXAf8tX9RERATAzExrLdqmIL5ZSmQGmmk5KIFMoioSwCyiKhNAp2xsCuGKgOB/ADpXvKPnHeOBKq7A9wZnQmPZJ7EB8RT3JUMukx6aTFpJEem05atJ15Dg8JP2R4Xo8XL4feT2mY2/0Tte/zQfih/+57eXyROKLjAxTVsc2Ls8F99UVGtZi/QYjbH9BY9/+btKS/Q1PywDH5dwh03R9OQ/8XDvX5ac1+6jPRXH+T5qz7gx3pcaG1/j/5OcfHn/M3CWbdNySQ3xMt9f+KJyISdyPaV0fF59s37imNaOsFkc/jI5wm+jscSxzgT4qgIimFih4/fvkX2b8gMz7TPuG/ezfs2mVPy8vtUla2b7r3cWEhVFfvKwfJppG/8QCcTru9Hx5uJ7ecTruEhNg9q0JC7N+CjzwC/fr99PaCLDYklh7JPeiR3MAfG/tu5ZV1lZTUlFBcW1xfSmpK2F2zm1JXKZXuSirrKimrKmNz8WYq6yqpqqs66phCnaGEO8MJDQklxBGCw+HA6XDaBWf986yELN48982jfp+9gv253y/PckQ9QhyWZQU+moMYhjEAeMU0zZ77zfseuNQ0zWX7zVsJXG2a5pI9z/8P6Gia5q0/9R5ff/31MGB+wIMXEREREREREZGTBgwY8EVjF255fe0ObQlwErAN8AU5FhERERERERGR1iAEyMDOuzRacyWcCoFMwzBCTNP07RkcvMOe+fvbDOSwbyeygYLGvMGAAQPcQKMzbSIiIiIiIiIi0ijrj3SFZrmXoGmaO4FvgYv2zLoI+Oag8ZsA3gF+ZRiG0zCMdsBZwLvNEaOIiIiIiIiIiARGsySc9rgBuMUwjDXALXueYxjGTMMwBu5Z5lVgA7AWWARMNE1zQzPGKCIiIiIiIiIiP1OzDBouIiIiIiIiIiJtR3P2cBIRERERERERkTZACScREREREREREQkoJZxERERERERERCSglHASEREREREREZGAUsJJREREREREREQCKjTYAcjRMQwjEngMOAVwAQtN07zuoGVCgCeB0wALmGSa5pTmjlUCq5F1fx9wIeDdU+42TfOj5o5VAqsxdb/fsgbwDfCMaZp/aL4opSk0tu4NwzgfuA9wYB/3TzFNc0dzxiqB1chjfhrwMpAFhAOfAbeapult5nAlQAzDyAXe229WIhBvmmbyQcuprdfKHEHdq63XyjS27vdbXm29VuJI6r6ltfWUcGq5/obd8OxqmqZlGEZ6A8tcAnQB8oEU4BvDMGabprmp+cKUJtCYul8M/MM0zRrDMPoC8wzDyDBNs7ZZI5VAa0zd7/0B8jwHfnFJy/aTdW8YxkDgAWCUaZrbDcNIANzNG6Y0gcZ87u8GfjBNc5xhGGHAF8A5wNRmjFMCaE9b7bi9zw3DeJyG2+1q67UyR1D3auu1MkdQ92rrtTKNrfuW2NZTwqkFMgwjFrgc6GiapgVwiKzmBcALpmn6gV2GYbwHTAAeabZgJaAaW/cHneFagZ0BTwG2NEecEnhH8LkHuBN4H4jdU6QFO4K6/x3wd9M0t+9Zprz5opSmcAR1bwFxhmE4gQjsXk5bmy1QaVKGYYRjJ5bGNPCy2nqt2OHqXm291u0nPvegtl6r9RN13+Laeko4tUx5QDFwv2EYI4Eq4F7TNL84aLlsoGC/55uxu9tLy9XYut/f5cB60zTVAGnZGlX3hmH0wf6CGond3VZavsZ+7nsAGw3D+By78flf4KG9iQppkRpb938C3gW2ATHA06ZpLmjWSKUp/RLYaprmsgZeU1uvdTtc3e9Pbb3W55B1r7Zeq3e4z32La+tp0PCWKRToDHxjmuZA4A7gv4ZhxAc3LGkGR1T3hmEMx/4hclHzhShN5Cfrfs+lNC8AN5im6QtOmNIEGvu5DwX6AKOB4cBY4LLmDFQCrrF1PwG7h0MGkAn8wjCM85o1UmlKVwMvBTsICYqfrHu19VqtButebb024XCf+xbX1lPCqWUqwB4c8E0A0zS/AnYDXQ9abjOQs9/zbKCwOQKUJtPYuscwjOOB14CzTNM0mzNIaRKNqfsM7B4RMw3D2AT8FviVYRj/bNZIJdAa+7kvAP5jmqbbNM1KYBowuDkDlYBrbN3fArxumqZ/T/f6adhnvqWFMwyjA/aPitcPsYjaeq1UI+pebb1W6ifqXm29VqwRn/sW19ZTwqkFMk1zNzAHO7OJYRhdgTRg3UGLvoN9AHIahtEOOAu7y720UI2te8MwBgFvA+c1ohu2tACNqXvTNDebpplqmmauaZq5wOPYY3s0eCc7aRmO4Jj/BnCqYRiOPWdATwaWN2esElhHUPcbse9Stnfsh1OA75ovUmlCVwIfmKZZfIjX1dZrva7kMHWvtl6rdiWHqHu19Vq9Kzn8Mb/FtfWUcGq5bgDuNgxjJfAWcJlpmmWGYczcM3o9wKvABmAtsAiYaJrmhuCEKwHUmLp/BogCnjcM49s9pXewApaAaUzdS+vUmLp/C9gJfA98C6wCXgxKtBJIjan73wIn7VnmW2AN9iUX0vJdyUGXVqit12ZcyeHrXm291utKDl/30npdyeHrvsW19RyWdcyOLyUiIiIiIiIiIi2QejiJiIiIiIiIiEhAKeEkIiIiIiIiIiIBpYSTiIiIiIiIiIgElBJOIiIiIiIiIiISUEo4iYiIiIiIiIhIQCnhJCIiIiIiIiIiAaWEk4iIiIiIiIiIBJQSTiIiIiIiIiIiElChwQ5AREREpCUyDGMTMBm4DMgD3gLuBv4FDAO+AiaYpllqGMZQ4FGgB1AA/MY0zbl7tnMV8H9AR2AX8FfTNJ/f89oI4DXgMeAOwAfcbZrmy82wiyIiIiJHTT2cRERERI7eucBooCtwJjALO+mUit3OutUwjEzgA+DPQDLwB+BdwzDa7dnGTuAMIB64CnjMMIz++71HeyAByASuASYbhpHUxPslIiIi8rOoh5OIiIjI0XvKNM0dAIZhzAd2mqb5zZ7n/wNOBi4FZpqmOXPPOp8YhrEUOB34t2maH+y3vXmGYXwMnAQs2zPPA0w0TdMLzDQMowowgEVNvG8iIiIiR00JJxEREZGjt2O/x7UNPI8FcoAJhmGcud9rYcAcAMMwxgL3Y/eScgLRwMr9li3ek2zaq2bPdkVERESOWUo4iYiIiDStQuBV0zR/dfALhmFEAO8ClwPTTNP0GIbxHuBo5hhFREREAkoJJxEREZGm9RqwxDCMMcBs7N5NQ4F1QDkQgT1YuHdPb6dTge+CFKuIiIhIQGjQcBEREZEmZJpmITAeezDxXdg9nm4HnKZpVgK3AlOBUuBiYHqQQhUREREJGIdlWcGOQUREREREREREWhH1cBIRERERERERkYBSwklERERERERERAJKCScREREREREREQkoJZxERERERERERCSglHASEREREREREZGAUsJJREREREREREQCSgknEREREREREREJKCWcREREREREREQkoP4fNHAcbA8Na7UAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1440x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,8))\n",
    "plt.title('Distributions of average end month grouped by state')\n",
    "plt.ylabel('proportion')\n",
    "\n",
    "sns.distplot(state_describe_succ['end_month']['mean'],color='green')\n",
    "sns.distplot(state_describe_fail['end_month']['mean'],color='red')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There doesn't seem to be much visual difference in these distributions; we ran t-tests to corroborate our visual conclusions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Ttest_indResult(statistic=0.11668212708718963, pvalue=0.9073507397613596)"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stats.ttest_ind(state_describe_succ['start_month']['mean'],state_describe_fail['start_month']['mean'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Ttest_indResult(statistic=1.9461683961465335, pvalue=0.054498627331500078)"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stats.ttest_ind(state_describe_succ['end_month']['mean'],state_describe_fail['end_month']['mean'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Indeed, the t-test of distributions of average start and end months grouped by state did not output p-values less than 0.05 and thus the start and end months of Kickstarters don't seem to affect status significantly."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Lastly, we will test which states Kickstarters are most likely to achieve success in."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,8))\n",
    "plt.title('Count of numbers of Kickstarters per state')\n",
    "plt.ylabel('proportion')\n",
    "\n",
    "ax_state = sns.countplot(x='state',hue='status',data=df_kickstarters)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And a plot of proportions:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fa9706e4ef0>"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1800x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_state = df_kickstarters.groupby(['status','state'])['status'].count().unstack('state').fillna(0)\n",
    "sub_df_state = np.transpose(df_state.div(df_state.sum()))\n",
    "sub_df_state.plot(kind='bar',stacked=True,rot=0, figsize=(25,10))\n",
    "\n",
    "plt.legend(('failed','successful'), loc='center left', bbox_to_anchor=(1.0, 0.5))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Analysis Summary"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1.) Duration\n",
    "- It appears that if your project goes beyond 32 days you have a very high likelihood of having a failed     kickstarter\n",
    "- For successful kickstarters success is determined before the 32 day mark\n",
    "- The average duration for successful kickstarters is ~30, while the average duration for the failed kickstarters is ~34.  The std deviation for successful and failed kickstarters is 10, and 12\n",
    "  \n",
    "#### 2.) USD_Goal\n",
    "- The difference in the total USD goal for failed/kickstarters is massive.  There is an 736.38% increase in goal_usd for the failed kickstarters compared to successful\n",
    "- Failed kickstarters have a average goal of about \\\\$81,020\n",
    "- Successful kickstarters have an average goal of about \\\\$9380\n",
    "- Why the stark difference?  Possibly due to reasonable goals/expectations, a certain level of preparedness and experience.  It probably also matters when someone is deciding whether or not they will pledge to the cause\n",
    "\n",
    "#### 3.) Categories -- Listed below are the top 4 successful categories\n",
    "- Dance has a much lower number of kickstarters at 3,092 (lowest of the top 4).  However, they also have the highest success rate at 86%\n",
    "- Comics has a total of 5,921 kickstarters (3rd in terms of total kickstarters) with a success rate of 84%\n",
    "- Publishing has the second greatest number of kickstarters with a total of 13,590 with a success rate of 74% (which is the 3rd highest success rate)\n",
    "- Music has the greatest number kickstarters at 20,491, and alternatively it has the 4th highest success rate of 70% which is nothing to scoff at\n",
    "\n",
    "#### 4.) Start/end month\n",
    "- Based on the observations we noticed that you're in trouble if your project starts later than October, such as November or December. You're lowering your chances of success by a large margin.  At the same time when we compared start time to end time, the end time of January and early February also has a lowered chance of success which is consistent with our obvservation for start time.  Since on average duration is about a month, the detrimental effects of starting in November/Decmeber are observed in the end time success of January the next year."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Ethics & Privacy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We must decide if Kickstarter and crowdfunding should only be used to fund a project’s minimum requirements or whether these “above and beyond” moments of success should be allowed and celebrated, and we must also decide if Kickstarter’s essential nature is to allow unestablished artists and creators to find success or if people like Braff should be allowed  to use the service despite their previous success.\n",
    "\n",
    "Unique from other creators, Kickstarter creators have a preexisting obligation to their consumers to deliver a certain amount of quality, because many of their consumers will have already paid money and will have a certain expectation for what will be delivered. Does the artist’s vision suffer when they are encouraged to meet a certain expectation? If so, is it okay if their vision is changed to please  their backers, who funded the actual creation? Crowdsourcing offers an interesting dilemma, and begs the question: is the essential nature of creation to please consumers even if some artistic vision is lost, or is it to allow the artist absolute freedom in their creation?\n",
    "\n",
    "Considering using this dataset which is showing the results from each kickstarter projects, then it could be another ethical problem that we are using their information. Although this dataset does not consist of any information regarding to neither personal nor confidential, there is a way to track which project was successful by looking and analyzing all the information here; it could be a risk of revealing personal information as well."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Conclusion & Discussion"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Through our analysis, we found that “music”,”film & video”, and “publishing” have the most common for kickstarter projects’ main categories. Although these main categories are quite common, it did not mean that they have the highest rates of getting better successful rates. From our data visualization, we have found that the category with the most successful kickstarters were dance, publishing, and comics in that order. Although dance had the least amount of kickstarter projects, it still had the highest success rate, compared to technology, which was one of the larger numbers kickstarter projects but was still one of the lower success rate category. \n",
    "\n",
    "In addition, we have also found that duration and USD goals does indeed have an effect on the success and failure of the kickstarter projects, which supports our hypothesis. We have found that projects within 32 days have a higher success rate and failed projects usually had a longer duration. We have also found that projects with smaller amount of USD goals tend to be more sucessful. Failed projects had an average of USD goal of 81020 dollars while successful projects had an average USD goal of 9380 dollars. \n",
    "\n",
    "On the other hand, we have also found that the start and end month of a project does not have an effect on the success and failure of a project. However, we did find that there are more projects that failed around the end of the year, such as starting in November and December and ending in January and February when looking at the data visualization of success and fail rates of each month but this was ratio was not significant enough for us to find that there is indeed an effect to the overall success and failure of projects. Some plausible explanation to these findings could be because backers might be more comfortable in pledging only a small amount of money and in something that they can get quickly, hence the smaller USD goal and duration of successful projects. This is only our speculation and is something that we will have to do further research to prove. \n",
    "\n",
    "We would like to keep in mind that our data consists of datas within the United States from 2014 to 2019. This limits our findings. For someone that wants to start a kickstarter, our findings could be useful to have a higher chance of a successful kickstarter campaign. \n"
   ]
  }
 ],
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