FinalProject_group081.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Cogs 108: Final Project Group 081\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Group Information\n",
    "\n",
    "| Names | Year | Major |\n",
    "|-------|------|-------|\n",
    "| Makoto Ikeda | 4th | Cognitive Science, Machine Learning\n",
    "| Errick Santos | 3rd | Data Science\n",
    "| Trish Lam |  2nd | Computer Science\n",
    "| Subin Yoon |  2nd | Cognitive Science, Machine Learning\n",
    "| Nathaniel Swadai | 2nd | Computer Science Engineering\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Overview\n",
    "\n",
    "In this project, our team will explore a 2019 Stack Overflow Annual Developer Survey dataset with questions that 88,883 developers from 170 countries and dependent territories have answered. We hope to use their answers to see if learning how to program at an earlier age has a huge effect on the coder. In this dataset, we will focus on cleaning and visualizing featured variables such as the age when they’ve first coded, the amount of years they coded, salary, job satisfaction and career satisfaction.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Research Question\n",
    "\n",
    "This project will explore whether learning code at an earlier age gives him/her/them an advantage in income, number of programming languages, job satisfaction, technological innovation, etc. over those who learn code at an older age.  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Background and Prior Work\n",
    "\n",
    "You can't teach an old dog new tricks is a popular idiom exemplifying the fact that it is more difficult to teach an older individual something new, especially because they are used to their own mindset, habits, and traits for so long. It’s a widely-used proverb that has lasted around five hundred years, with its earliest citation in print in The boke of husbandry (1534) by John Fitzherbert (1). Although this saying has prevailed for about five centuries, is it really true? Do old people learn slower than younger people?\n",
    "\n",
    "On the other hand, there is a psychological idea that childrens’ brains are like sponges, soaking up a vast amount of information from their surroundings in a short amount of time. According to Abdul Malik Muftau at the Teachers College graduate school at Columbia University, children in youth sport teams tend to learn very fast compared to adults who are learning the same thing in their respective sport (2). It’s interesting to see how this could be possible. In “early stages of neuronal development, the brain exhibits more plasticity, and as a result children seem to absorb everything around them (language being one of the most notable examples)” (3). More specifically, by age two or three, infants enter a period called “Exuberant Synaptogenesis, where they have more than twice as many synaptic connections than adults” (3). Because “long-term memories are stored in the brain in the form of synapses”, memory formation happens when these connections are formed or strengthened (4). However, the “brain actually goes back and reduces the number of connections after [the Exuberant Synaptogenesis] because a functioning adult, set in [his/her/their] ways, doesn't need as many” (3). Although psychology and biology shows how children form memories more effectively and rapidly, does it matter whether one learns something earlier or later in life? More importantly to us, does this matter if you want to become a successful software engineer?\n",
    "\n",
    "With the rise of technology and its company counterparts, the potential occupation as an engineer has increasingly become appealing in recent years. According to the U.S. Bureau of Labor Statistics, “employment of software developers is projected to grow twenty-one percent from 2018 to 2028, which is faster than the average for all occupations” (5). Many prospective college and university students see Computer Science and its equivalents as a fast and reliable route to gaining a stable job and income. As the competition in technology and the demand of software engineers increases, tech companies have accommodated accordingly by providing extra benefits, such as “relocation assistance, tuition reimbursement, wellness stipends” (6) to even micro kitchens to attract the “best and brightest” employees and maintain a “strong employer brand” (7). The stable income, the huge job market, and the emphasis on work culture and employee satisfaction have driven people from different backgrounds and ages to study towards becoming a software engineer, including the current youth.\n",
    "\n",
    "Many companies such as iD Tech and FunTech are using this logic (the job market and benefit factor) to encourage parents to sign their children up for programming related courses and camps that many public schools do not offer in their curriculum. Even huge tech corporations such as Google host and encourage coding programs for younger audiences, ranging from elementary to high school students. Although many parents buy into these camps and programs, how does coding at an earlier age really affect the future of these potential software engineers?\n",
    "\n",
    "Not many studies have been done on this topic. A notable study that relates the most with our question is research done by Amanda Strawhacker and Marina Umaschi Bers with the Association for Educational Communications and Technology. In 2018, they “investigated cognitive domains and computer programming knowledge in young children” to see what children learn when they begin learning how to code (8). In their research, they created a six-week learning intercession in which children engaged with Scratch Jr., a programming environment made for younger audiences, on an iPad, and then tested them on their programming knowledge with a numerical scored response form. Through their method, Strawhacker and Bers concluded that “children in [their] study demonstrated a range of mastery and creativity through coding, but none showed a complete lack of understanding about the most foundational programming concepts after the intervention” (8). Although it is not known from this research whether coding at an earlier age affects the student in the long-term scope of career success and happiness, it does support the fact that coding for children helps cognitive development in general.\n",
    "\n",
    "Considering this developmental benefit, the extreme push towards teaching people how to code at a younger age and the mass assumption that learning earlier is more beneficial than learning later in life, we hope to realize through this data science project whether or not learning programming earlier really has an edge, not only in knowledge and industry, but in life and their happiness.\n",
    "\n",
    "\n",
    "\n",
    "### References\n",
    "\n",
    "\n",
    "1. https://quod.lib.umich.edu/e/eebo/A00884.0001.001?view=toc\n",
    "2. https://edlab.tc.columbia.edu/blog/10822-Do-Kids-Learn-Faster-than-Adults\n",
    "3. https://www.seeker.com/why-do-kids-learn-faster-than-adults-1792717450.html\n",
    "4. https://www.discovermagazine.com/planet-earth/do-synapses-really-store-memories\n",
    "5. https://www.bls.gov/ooh/computer-and-information-technology/software-developers.htm\n",
    "6. https://www.techrepublic.com/article/12-tech-companies-with-impressive-benefits/\n",
    "7. https://hired.com/page/brand-health-report\n",
    "8. https://tessais.org/children-learn-languages-faster-adults/\n",
    "9. https://insights.stackoverflow.com/survey\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Hypothesis\n",
    "We predict that there is a strong correlation between those who code earlier and those who succeed in the tech industry as software engineers.\n",
    "We believe this as our hypothesis because we have seen personally that people who start earlier in their hobbies are more skillful at them, such as drawing, dancing, sports, etc. We believe this is also the case with coding, especially because with the people we see who code in college right now, those who started earlier seem to have an advantage in homework assignments and tests because they have been exposed to the concepts and syntax before.\n",
    "\n",
    "## Dataset(s)\n",
    "This dataset consists of over 88,883 developers that were surveyed from 170 countries and dependent territories during 2019 by StackOverflow. Each row includes information about the respondents in terms of their personal background, background as a developer, income, job and career satisfaction, etc. In this dataset, we will focus on featured variables such as the age when they’ve first coded, the amount of years they coded, salary, job satisfaction and career satisfaction.\n",
    "### Dataset Link:\n",
    "The data set can be found [here](https://insights.stackoverflow.com/survey). It contains 8 years of developers' surveys. In this project, we are focusing on the 2019 dataset and if time allows we can apply our hypothesis towards the other datasets. The 2019 dataset surveyed 88,883 developers throughout the world.\n",
    "\n",
    "### Size of Dataset:\n",
    "\n",
    "\n",
    "The files have the following columns:\n",
    "\n",
    "|Header | Definition |\n",
    "|-------|------------|\n",
    "|Respondents|The developer being surveyed|\n",
    "|MainBranch|Which best describes the repsondents today|\n",
    "|Employment|Current employment status|\n",
    "|Country|The country the respondents resides|\n",
    "|EdLevel|The Highest level of formal education|\n",
    "|EduOther|The certificates of non-degree education|\n",
    "|OrgSize|Approximately how many people are employed by company/organixation you work for|\n",
    "|DevType|Type of Developer, that best suits respondents|\n",
    "|YearsCode|Including any education, number of years coding|\n",
    "|Age1stCode|Age, where respodent written their first line of code|\n",
    "|YearsCodePro|Years coded professionally|\n",
    "|CareerSat|How respondent are satisfied with their career|\n",
    "|JobSat|How respondent are satisfied with their job|\n",
    "|CurrencySymbol|Currency respondent use day-to-day|\n",
    "|CurrencyDesc|Currency respondent use day-to-day|\n",
    "|CompTotal|Respondents current total compensation|\n",
    "|CompFreq|Is compensation weekly,monthly,yearly|\n",
    "|ConvertedComp|Salary converted to annual USD salaries (exchange rate on 2019-02-01)|\n",
    "|WorkWeekHrs|Respondents total working hours per week|\n",
    "|LanguageWorkedWith|Type of programming languages respondents knows|\n",
    "|LanguageDesireNextYear|Language respondents wants to learn next year|\n",
    "|DevEnvirson|What development environments respondents uses day-to-day|\n",
    "|OpSys|Primary operating system respondents use|\n",
    "|Age|Age of respondents|\n",
    "|Gender|What respondents currently identify|\n",
    "|Trans|Does respondents identify as transgender|\n",
    "|Sexuality|Sexual preference of respondents|\n",
    "|Ethnicity|Ethnicity of respondents|\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setup\n",
    "### Importing Packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline \n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import os\n",
    "import patsy\n",
    "import scipy.stats as stats\n",
    "from scipy.stats import ttest_ind, chisquare, normaltest\n",
    "import statsmodels.api as sm\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "# set defaults\n",
    "plt.style.use('default')   # seaborn custom plot style\n",
    "plt.rc('figure', dpi=100, figsize=(7, 5))   # set default size/resolution\n",
    "plt.rc('font', size=12)   # font size"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Converting .csv File Into Pandas DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [],
   "source": [
    "stack_overflow_survey_2019 = 'updated_survey_2019.csv'\n",
    "\n",
    "#covert csv into pandas data frame\n",
    "data_2019 = pd.read_csv(stack_overflow_survey_2019)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Cleaning"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Dropping unnecessary columns "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\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>YearsCode</th>\n",
       "      <th>Age1stCode</th>\n",
       "      <th>YearsCodePro</th>\n",
       "      <th>CareerSat</th>\n",
       "      <th>JobSat</th>\n",
       "      <th>ConvertedComp</th>\n",
       "      <th>LanguageWorkedWith</th>\n",
       "      <th>Age</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>HTML/CSS;Java;JavaScript;Python</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>17</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>C++;HTML/CSS;Python</td>\n",
       "      <td>19.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>22</td>\n",
       "      <td>1</td>\n",
       "      <td>Slightly satisfied</td>\n",
       "      <td>Slightly satisfied</td>\n",
       "      <td>8820.0</td>\n",
       "      <td>HTML/CSS</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>16</td>\n",
       "      <td>Less than 1 year</td>\n",
       "      <td>Very satisfied</td>\n",
       "      <td>Slightly satisfied</td>\n",
       "      <td>61000.0</td>\n",
       "      <td>C;C++;C#;Python;SQL</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>16</td>\n",
       "      <td>14</td>\n",
       "      <td>9</td>\n",
       "      <td>Very dissatisfied</td>\n",
       "      <td>Slightly dissatisfied</td>\n",
       "      <td>NaN</td>\n",
       "      <td>C++;HTML/CSS;Java;JavaScript;Python;SQL;VBA</td>\n",
       "      <td>30.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  YearsCode Age1stCode      YearsCodePro           CareerSat  \\\n",
       "0         4         10               NaN                 NaN   \n",
       "1       NaN         17               NaN                 NaN   \n",
       "2         3         22                 1  Slightly satisfied   \n",
       "3         3         16  Less than 1 year      Very satisfied   \n",
       "4        16         14                 9   Very dissatisfied   \n",
       "\n",
       "                  JobSat  ConvertedComp  \\\n",
       "0                    NaN            NaN   \n",
       "1                    NaN            NaN   \n",
       "2     Slightly satisfied         8820.0   \n",
       "3     Slightly satisfied        61000.0   \n",
       "4  Slightly dissatisfied            NaN   \n",
       "\n",
       "                            LanguageWorkedWith   Age  \n",
       "0              HTML/CSS;Java;JavaScript;Python  14.0  \n",
       "1                          C++;HTML/CSS;Python  19.0  \n",
       "2                                     HTML/CSS  28.0  \n",
       "3                          C;C++;C#;Python;SQL  22.0  \n",
       "4  C++;HTML/CSS;Java;JavaScript;Python;SQL;VBA  30.0  "
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# List all columns in the data frame\n",
    "var_19 = list(data_2019.columns)\n",
    "\n",
    "# Drop columns that is not relevant to our hypothesis\n",
    "df_19 = data_2019.drop(columns=['Respondent', 'MainBranch', 'Employment', 'Country', \n",
    "                                'EdLevel', 'EduOther', 'OrgSize', 'DevType', \n",
    "                                'CurrencySymbol', 'CurrencyDesc', 'CompTotal', \n",
    "                                'CompFreq', 'WorkWeekHrs', 'LanguageDesireNextYear', \n",
    "                                'DevEnviron', 'OpSys', 'Gender', 'Trans', 'Sexuality', \n",
    "                                'Ethnicity'])\n",
    "\n",
    "# Show the first 5 index of our updated dataframe\n",
    "df_19.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Dealing with Na and Null Values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "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",
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       "    }\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>YearsCode</th>\n",
       "      <th>Age1stCode</th>\n",
       "      <th>YearsCodePro</th>\n",
       "      <th>CareerSat</th>\n",
       "      <th>JobSat</th>\n",
       "      <th>ConvertedComp</th>\n",
       "      <th>LanguageWorkedWith</th>\n",
       "      <th>Age</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>22</td>\n",
       "      <td>1</td>\n",
       "      <td>Slightly satisfied</td>\n",
       "      <td>Slightly satisfied</td>\n",
       "      <td>8820.0</td>\n",
       "      <td>HTML/CSS</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>16</td>\n",
       "      <td>Less than 1 year</td>\n",
       "      <td>Very satisfied</td>\n",
       "      <td>Slightly satisfied</td>\n",
       "      <td>61000.0</td>\n",
       "      <td>C;C++;C#;Python;SQL</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>13</td>\n",
       "      <td>15</td>\n",
       "      <td>3</td>\n",
       "      <td>Very satisfied</td>\n",
       "      <td>Slightly satisfied</td>\n",
       "      <td>366420.0</td>\n",
       "      <td>Java;R;SQL</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>12</td>\n",
       "      <td>11</td>\n",
       "      <td>4</td>\n",
       "      <td>Slightly satisfied</td>\n",
       "      <td>Slightly satisfied</td>\n",
       "      <td>95179.0</td>\n",
       "      <td>Bash/Shell/PowerShell;C#;HTML/CSS;JavaScript;P...</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>17</td>\n",
       "      <td>11</td>\n",
       "      <td>8</td>\n",
       "      <td>Very satisfied</td>\n",
       "      <td>Very satisfied</td>\n",
       "      <td>90000.0</td>\n",
       "      <td>Bash/Shell/PowerShell;HTML/CSS;JavaScript;PHP;...</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   YearsCode Age1stCode      YearsCodePro           CareerSat  \\\n",
       "2          3         22                 1  Slightly satisfied   \n",
       "3          3         16  Less than 1 year      Very satisfied   \n",
       "5         13         15                 3      Very satisfied   \n",
       "8         12         11                 4  Slightly satisfied   \n",
       "12        17         11                 8      Very satisfied   \n",
       "\n",
       "                JobSat  ConvertedComp  \\\n",
       "2   Slightly satisfied         8820.0   \n",
       "3   Slightly satisfied        61000.0   \n",
       "5   Slightly satisfied       366420.0   \n",
       "8   Slightly satisfied        95179.0   \n",
       "12      Very satisfied        90000.0   \n",
       "\n",
       "                                   LanguageWorkedWith   Age  \n",
       "2                                            HTML/CSS  28.0  \n",
       "3                                 C;C++;C#;Python;SQL  22.0  \n",
       "5                                          Java;R;SQL  28.0  \n",
       "8   Bash/Shell/PowerShell;C#;HTML/CSS;JavaScript;P...  23.0  \n",
       "12  Bash/Shell/PowerShell;HTML/CSS;JavaScript;PHP;...  28.0  "
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df_19.dropna()\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Standardize Values in our Columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['3' '13' '12' '17' '10' '5' '14' '8' '35' '2' '4' '6' '30' '9' '26' '40'\n",
      " '15' '7' '20' '28' '25' '1' '22' '16' '11' '33' '50' '18' '34' '19' '24'\n",
      " '23' '42' '27' '21' '36' 'Less than 1 year' '32' '39' '38' '31' '29' '37'\n",
      " '41' '44' '48' '45' '43' '47' '46' '49' 'More than 50 years']\n",
      "---------------------------------------------------------------------\n",
      "['1' 'Less than 1 year' '3' '4' '8' '2' '13' '18' '14' '22' '23' '19' '35'\n",
      " '20' '10' '9' '7' '5' '6' '48' '12' '31' '11' '27' '17' '15' '16' '21'\n",
      " '29' '26' '30' '25' '33' '37' '28' '34' '24' '40' '32' '39' '45' '44'\n",
      " '36' '43' '41' '42' 'More than 50 years' '50' '38' '47' '46' '49']\n"
     ]
    }
   ],
   "source": [
    "# checking if our column has any discrepancy\n",
    "# It does, so will apply standardizing function\n",
    "print(df['YearsCode'].unique())\n",
    "\n",
    "# Separator for easy visualization\n",
    "print('---------------------------------------------------------------------')\n",
    "\n",
    "# This column has some discrepancy as well\n",
    "print(df['YearsCodePro'].unique())\n",
    "\n",
    "#Creating a standardizing function\n",
    "def standardize_Years(string):\n",
    "    \n",
    "    if 'Less' in string:\n",
    "        out = '1'\n",
    "    elif 'More' in string:\n",
    "        out = '50'\n",
    "    else:\n",
    "        out = string\n",
    "        \n",
    "    return out\n",
    "\n",
    "# Apply function two both columns to standardize them\n",
    "df['YearsCode'] = df['YearsCode'].apply(standardize_Years)\n",
    "df['YearsCodePro'] = df['YearsCodePro'].apply(standardize_Years)\n",
    "\n",
    "# Find unique values in this column as well\n",
    "df['Age1stCode'].unique()\n",
    "\n",
    "# Creating a standardizing function\n",
    "def standardize_Age1stCode(string):\n",
    "    \n",
    "    if 'Younger' in string:\n",
    "        out = '5'\n",
    "    elif 'Older' in string:\n",
    "        out = '85'\n",
    "    else:\n",
    "        out = string\n",
    "        \n",
    "    return out\n",
    "\n",
    "# Apply function to column data\n",
    "df['Age1stCode'] = df['Age1stCode'].apply(standardize_Age1stCode)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Fixing numbers in columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([28., 22., 23., 31., 26., 29., 38., 47., 34., 32., 21., 25., 35.,\n",
       "       44., 42., 27., 43., 62., 45., 18., 37., 33., 19., 24., 36., 30.,\n",
       "       39., 64., 41., 49., 54., 40., 56., 58., 46., 51., 48., 16., 57.,\n",
       "       52., 50., 55., 20., 67., 53., 59., 65., 61., 63., 17., 70., 60.,\n",
       "       71., 68., 72.,  1., 75., 66., 69., 99., 15., 12.,  2., 73.,  4.,\n",
       "       74.,  3., 98., 13., 84., 14., 95.])"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Rounds values in column\n",
    "df = df.round()\n",
    "\n",
    "# Prints unique values to see if they are rounded\n",
    "df['Age'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Dealing with Categorical Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Function to convert catagorical data to integers to find means\n",
    "def convertInt(string):\n",
    "    out = string\n",
    "    if string == 'Very dissatisfied':\n",
    "        out = 1\n",
    "    elif string == 'Slightly dissatisfied':\n",
    "        out = 2\n",
    "    elif string == 'Neither satisfied nor dissatisfied':\n",
    "        out = 3\n",
    "    elif string == 'Slightly satisfied':\n",
    "        out = 4\n",
    "    elif string == 'Very satisfied':\n",
    "        out = 5\n",
    "    return out\n",
    "\n",
    "# Create new columns of converted catagorical data to ints\n",
    "df['CareerSatInt'] = df['CareerSat'].apply(convertInt)\n",
    "df['JobSatInt'] = df['JobSat'].apply(convertInt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.JobSat = pd.Categorical(df.JobSat, categories=['Very dissatisfied', 'Slightly dissatisfied', 'Neither satisfied nor dissatisfied',\n",
    "                                                     'Slightly satisfied', 'Very satisfied'], ordered=True)\n",
    "df.CareerSat = pd.Categorical(df.CareerSat, categories=['Very dissatisfied', 'Slightly dissatisfied', 'Neither satisfied nor dissatisfied',\n",
    "                                                           'Slightly satisfied', 'Very satisfied'], ordered=True)\n",
    "df.sort_values(['CareerSat', 'JobSat'], inplace=True)\n",
    "\n",
    "df.CareerSat = pd.Categorical(df.CareerSat, categories=['Very dissatisfied', 'Slightly dissatisfied', 'Neither satisfied nor dissatisfied',\n",
    "                                                           'Slightly satisfied', 'Very satisfied'], ordered=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Standardize Values in our Columns Part 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Creating a standardizing function\n",
    "def standardize_LanguageWorkedWith(string):\n",
    "    \n",
    "    return string.count(';') + 1\n",
    "\n",
    "# Apply function two both columns to standardize them\n",
    "df['LanguageWorkedWith'] = df['LanguageWorkedWith'].apply(standardize_LanguageWorkedWith)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Converting String Types into Integers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['YearsCode']    = pd.to_numeric(df['YearsCode'])\n",
    "df['YearsCodePro'] = pd.to_numeric(df['YearsCodePro'])\n",
    "df['Age1stCode']   = pd.to_numeric(df['Age1stCode'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Renaming Columns into Readable and Understandable Columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Rename columns\n",
    "df = df.rename(columns={'LanguageWorkedWith': 'NumLanguageWorkedWith'})\n",
    "\n",
    "# Resting index values to have it more organized\n",
    "df = df.reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Lets Compare our Modified DataSet with the Original One!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "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>YearsCode</th>\n",
       "      <th>Age1stCode</th>\n",
       "      <th>YearsCodePro</th>\n",
       "      <th>CareerSat</th>\n",
       "      <th>JobSat</th>\n",
       "      <th>ConvertedComp</th>\n",
       "      <th>NumLanguageWorkedWith</th>\n",
       "      <th>Age</th>\n",
       "      <th>CareerSatInt</th>\n",
       "      <th>JobSatInt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>8</td>\n",
       "      <td>23</td>\n",
       "      <td>4</td>\n",
       "      <td>Very dissatisfied</td>\n",
       "      <td>Very dissatisfied</td>\n",
       "      <td>65424.0</td>\n",
       "      <td>4</td>\n",
       "      <td>31.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>35</td>\n",
       "      <td>16</td>\n",
       "      <td>21</td>\n",
       "      <td>Very dissatisfied</td>\n",
       "      <td>Very dissatisfied</td>\n",
       "      <td>157017.0</td>\n",
       "      <td>5</td>\n",
       "      <td>56.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7</td>\n",
       "      <td>17</td>\n",
       "      <td>3</td>\n",
       "      <td>Very dissatisfied</td>\n",
       "      <td>Very dissatisfied</td>\n",
       "      <td>2664.0</td>\n",
       "      <td>4</td>\n",
       "      <td>24.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>20</td>\n",
       "      <td>14</td>\n",
       "      <td>15</td>\n",
       "      <td>Very dissatisfied</td>\n",
       "      <td>Very dissatisfied</td>\n",
       "      <td>110000.0</td>\n",
       "      <td>4</td>\n",
       "      <td>39.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>27</td>\n",
       "      <td>15</td>\n",
       "      <td>25</td>\n",
       "      <td>Very dissatisfied</td>\n",
       "      <td>Very dissatisfied</td>\n",
       "      <td>110509.0</td>\n",
       "      <td>1</td>\n",
       "      <td>49.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53060</th>\n",
       "      <td>15</td>\n",
       "      <td>16</td>\n",
       "      <td>11</td>\n",
       "      <td>Very satisfied</td>\n",
       "      <td>Very satisfied</td>\n",
       "      <td>120000.0</td>\n",
       "      <td>2</td>\n",
       "      <td>36.0</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53061</th>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>5</td>\n",
       "      <td>Very satisfied</td>\n",
       "      <td>Very satisfied</td>\n",
       "      <td>412464.0</td>\n",
       "      <td>3</td>\n",
       "      <td>29.0</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53062</th>\n",
       "      <td>7</td>\n",
       "      <td>19</td>\n",
       "      <td>4</td>\n",
       "      <td>Very satisfied</td>\n",
       "      <td>Very satisfied</td>\n",
       "      <td>2000000.0</td>\n",
       "      <td>4</td>\n",
       "      <td>26.0</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53063</th>\n",
       "      <td>31</td>\n",
       "      <td>18</td>\n",
       "      <td>28</td>\n",
       "      <td>Very satisfied</td>\n",
       "      <td>Very satisfied</td>\n",
       "      <td>2000000.0</td>\n",
       "      <td>8</td>\n",
       "      <td>48.0</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53064</th>\n",
       "      <td>12</td>\n",
       "      <td>14</td>\n",
       "      <td>3</td>\n",
       "      <td>Very satisfied</td>\n",
       "      <td>Very satisfied</td>\n",
       "      <td>130000.0</td>\n",
       "      <td>4</td>\n",
       "      <td>26.0</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>53065 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       YearsCode  Age1stCode  YearsCodePro          CareerSat  \\\n",
       "0              8          23             4  Very dissatisfied   \n",
       "1             35          16            21  Very dissatisfied   \n",
       "2              7          17             3  Very dissatisfied   \n",
       "3             20          14            15  Very dissatisfied   \n",
       "4             27          15            25  Very dissatisfied   \n",
       "...          ...         ...           ...                ...   \n",
       "53060         15          16            11     Very satisfied   \n",
       "53061         14          14             5     Very satisfied   \n",
       "53062          7          19             4     Very satisfied   \n",
       "53063         31          18            28     Very satisfied   \n",
       "53064         12          14             3     Very satisfied   \n",
       "\n",
       "                  JobSat  ConvertedComp  NumLanguageWorkedWith   Age  \\\n",
       "0      Very dissatisfied        65424.0                      4  31.0   \n",
       "1      Very dissatisfied       157017.0                      5  56.0   \n",
       "2      Very dissatisfied         2664.0                      4  24.0   \n",
       "3      Very dissatisfied       110000.0                      4  39.0   \n",
       "4      Very dissatisfied       110509.0                      1  49.0   \n",
       "...                  ...            ...                    ...   ...   \n",
       "53060     Very satisfied       120000.0                      2  36.0   \n",
       "53061     Very satisfied       412464.0                      3  29.0   \n",
       "53062     Very satisfied      2000000.0                      4  26.0   \n",
       "53063     Very satisfied      2000000.0                      8  48.0   \n",
       "53064     Very satisfied       130000.0                      4  26.0   \n",
       "\n",
       "       CareerSatInt  JobSatInt  \n",
       "0                 1          1  \n",
       "1                 1          1  \n",
       "2                 1          1  \n",
       "3                 1          1  \n",
       "4                 1          1  \n",
       "...             ...        ...  \n",
       "53060             5          5  \n",
       "53061             5          5  \n",
       "53062             5          5  \n",
       "53063             5          5  \n",
       "53064             5          5  \n",
       "\n",
       "[53065 rows x 10 columns]"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Our groups modified table\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "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>Respondent</th>\n",
       "      <th>MainBranch</th>\n",
       "      <th>Employment</th>\n",
       "      <th>Country</th>\n",
       "      <th>EdLevel</th>\n",
       "      <th>EduOther</th>\n",
       "      <th>OrgSize</th>\n",
       "      <th>DevType</th>\n",
       "      <th>YearsCode</th>\n",
       "      <th>Age1stCode</th>\n",
       "      <th>...</th>\n",
       "      <th>WorkWeekHrs</th>\n",
       "      <th>LanguageWorkedWith</th>\n",
       "      <th>LanguageDesireNextYear</th>\n",
       "      <th>DevEnviron</th>\n",
       "      <th>OpSys</th>\n",
       "      <th>Age</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Trans</th>\n",
       "      <th>Sexuality</th>\n",
       "      <th>Ethnicity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>I am a student who is learning to code</td>\n",
       "      <td>Not employed, and not looking for work</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>Primary/elementary school</td>\n",
       "      <td>Taught yourself a new language, framework, or ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4</td>\n",
       "      <td>10</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>HTML/CSS;Java;JavaScript;Python</td>\n",
       "      <td>C;C++;C#;Go;HTML/CSS;Java;JavaScript;Python;SQL</td>\n",
       "      <td>IntelliJ;Notepad++;PyCharm</td>\n",
       "      <td>Windows</td>\n",
       "      <td>14.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>No</td>\n",
       "      <td>Straight / Heterosexual</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>I am a student who is learning to code</td>\n",
       "      <td>Not employed, but looking for work</td>\n",
       "      <td>Bosnia and Herzegovina</td>\n",
       "      <td>Secondary school (e.g. American high school, G...</td>\n",
       "      <td>Taken an online course in programming or softw...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Developer, desktop or enterprise applications;...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>C++;HTML/CSS;Python</td>\n",
       "      <td>C++;HTML/CSS;JavaScript;SQL</td>\n",
       "      <td>Atom;PyCharm</td>\n",
       "      <td>Windows</td>\n",
       "      <td>19.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>No</td>\n",
       "      <td>Straight / Heterosexual</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>I am not primarily a developer, but I write co...</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Thailand</td>\n",
       "      <td>Bachelor’s degree (BA, BS, B.Eng., etc.)</td>\n",
       "      <td>Taught yourself a new language, framework, or ...</td>\n",
       "      <td>100 to 499 employees</td>\n",
       "      <td>Designer;Developer, back-end;Developer, front-...</td>\n",
       "      <td>3</td>\n",
       "      <td>22</td>\n",
       "      <td>...</td>\n",
       "      <td>40.0</td>\n",
       "      <td>HTML/CSS</td>\n",
       "      <td>Elixir;HTML/CSS</td>\n",
       "      <td>Vim;Visual Studio Code</td>\n",
       "      <td>Linux-based</td>\n",
       "      <td>28.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>No</td>\n",
       "      <td>Straight / Heterosexual</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>I am a developer by profession</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>United States</td>\n",
       "      <td>Bachelor’s degree (BA, BS, B.Eng., etc.)</td>\n",
       "      <td>Taken an online course in programming or softw...</td>\n",
       "      <td>100 to 499 employees</td>\n",
       "      <td>Developer, full-stack</td>\n",
       "      <td>3</td>\n",
       "      <td>16</td>\n",
       "      <td>...</td>\n",
       "      <td>80.0</td>\n",
       "      <td>C;C++;C#;Python;SQL</td>\n",
       "      <td>C;C#;JavaScript;SQL</td>\n",
       "      <td>Eclipse;Vim;Visual Studio;Visual Studio Code</td>\n",
       "      <td>Windows</td>\n",
       "      <td>22.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>No</td>\n",
       "      <td>Straight / Heterosexual</td>\n",
       "      <td>White or of European descent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>I am a developer by profession</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>Ukraine</td>\n",
       "      <td>Bachelor’s degree (BA, BS, B.Eng., etc.)</td>\n",
       "      <td>Taken an online course in programming or softw...</td>\n",
       "      <td>10,000 or more employees</td>\n",
       "      <td>Academic researcher;Developer, desktop or ente...</td>\n",
       "      <td>16</td>\n",
       "      <td>14</td>\n",
       "      <td>...</td>\n",
       "      <td>55.0</td>\n",
       "      <td>C++;HTML/CSS;Java;JavaScript;Python;SQL;VBA</td>\n",
       "      <td>HTML/CSS;Java;JavaScript;SQL;WebAssembly</td>\n",
       "      <td>IntelliJ;Notepad++;Vim</td>\n",
       "      <td>Linux-based</td>\n",
       "      <td>30.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>No</td>\n",
       "      <td>Straight / Heterosexual</td>\n",
       "      <td>White or of European descent;Multiracial</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88878</th>\n",
       "      <td>88377</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Not employed, and not looking for work</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Primary/elementary school</td>\n",
       "      <td>Taught yourself a new language, framework, or ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>HTML/CSS;JavaScript;Other(s):</td>\n",
       "      <td>C++;HTML/CSS;JavaScript;SQL;WebAssembly;Other(s):</td>\n",
       "      <td>Atom;Visual Studio;Visual Studio Code</td>\n",
       "      <td>Windows</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Man</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88879</th>\n",
       "      <td>88601</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88880</th>\n",
       "      <td>88802</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Employed full-time</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88881</th>\n",
       "      <td>88816</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Independent contractor, freelancer, or self-em...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88882</th>\n",
       "      <td>88863</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Not employed, and not looking for work</td>\n",
       "      <td>Spain</td>\n",
       "      <td>Professional degree (JD, MD, etc.)</td>\n",
       "      <td>Taken an online course in programming or softw...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bash/Shell/PowerShell;HTML/CSS;Java;JavaScript...</td>\n",
       "      <td>C;C++;C#;HTML/CSS;Java;Objective-C;SQL;Swift</td>\n",
       "      <td>Android Studio;Atom;Eclipse;NetBeans;Notepad++...</td>\n",
       "      <td>Linux-based</td>\n",
       "      <td>18.0</td>\n",
       "      <td>Man</td>\n",
       "      <td>No</td>\n",
       "      <td>Straight / Heterosexual</td>\n",
       "      <td>Hispanic or Latino/Latina;White or of European...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>88883 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Respondent                                         MainBranch  \\\n",
       "0               1             I am a student who is learning to code   \n",
       "1               2             I am a student who is learning to code   \n",
       "2               3  I am not primarily a developer, but I write co...   \n",
       "3               4                     I am a developer by profession   \n",
       "4               5                     I am a developer by profession   \n",
       "...           ...                                                ...   \n",
       "88878       88377                                                NaN   \n",
       "88879       88601                                                NaN   \n",
       "88880       88802                                                NaN   \n",
       "88881       88816                                                NaN   \n",
       "88882       88863                                                NaN   \n",
       "\n",
       "                                              Employment  \\\n",
       "0                 Not employed, and not looking for work   \n",
       "1                     Not employed, but looking for work   \n",
       "2                                     Employed full-time   \n",
       "3                                     Employed full-time   \n",
       "4                                     Employed full-time   \n",
       "...                                                  ...   \n",
       "88878             Not employed, and not looking for work   \n",
       "88879                                                NaN   \n",
       "88880                                 Employed full-time   \n",
       "88881  Independent contractor, freelancer, or self-em...   \n",
       "88882             Not employed, and not looking for work   \n",
       "\n",
       "                      Country  \\\n",
       "0              United Kingdom   \n",
       "1      Bosnia and Herzegovina   \n",
       "2                    Thailand   \n",
       "3               United States   \n",
       "4                     Ukraine   \n",
       "...                       ...   \n",
       "88878                  Canada   \n",
       "88879                     NaN   \n",
       "88880                     NaN   \n",
       "88881                     NaN   \n",
       "88882                   Spain   \n",
       "\n",
       "                                                 EdLevel  \\\n",
       "0                              Primary/elementary school   \n",
       "1      Secondary school (e.g. American high school, G...   \n",
       "2               Bachelor’s degree (BA, BS, B.Eng., etc.)   \n",
       "3               Bachelor’s degree (BA, BS, B.Eng., etc.)   \n",
       "4               Bachelor’s degree (BA, BS, B.Eng., etc.)   \n",
       "...                                                  ...   \n",
       "88878                          Primary/elementary school   \n",
       "88879                                                NaN   \n",
       "88880                                                NaN   \n",
       "88881                                                NaN   \n",
       "88882                 Professional degree (JD, MD, etc.)   \n",
       "\n",
       "                                                EduOther  \\\n",
       "0      Taught yourself a new language, framework, or ...   \n",
       "1      Taken an online course in programming or softw...   \n",
       "2      Taught yourself a new language, framework, or ...   \n",
       "3      Taken an online course in programming or softw...   \n",
       "4      Taken an online course in programming or softw...   \n",
       "...                                                  ...   \n",
       "88878  Taught yourself a new language, framework, or ...   \n",
       "88879                                                NaN   \n",
       "88880                                                NaN   \n",
       "88881                                                NaN   \n",
       "88882  Taken an online course in programming or softw...   \n",
       "\n",
       "                        OrgSize  \\\n",
       "0                           NaN   \n",
       "1                           NaN   \n",
       "2          100 to 499 employees   \n",
       "3          100 to 499 employees   \n",
       "4      10,000 or more employees   \n",
       "...                         ...   \n",
       "88878                       NaN   \n",
       "88879                       NaN   \n",
       "88880                       NaN   \n",
       "88881                       NaN   \n",
       "88882                       NaN   \n",
       "\n",
       "                                                 DevType YearsCode Age1stCode  \\\n",
       "0                                                    NaN         4         10   \n",
       "1      Developer, desktop or enterprise applications;...       NaN         17   \n",
       "2      Designer;Developer, back-end;Developer, front-...         3         22   \n",
       "3                                  Developer, full-stack         3         16   \n",
       "4      Academic researcher;Developer, desktop or ente...        16         14   \n",
       "...                                                  ...       ...        ...   \n",
       "88878                                                NaN       NaN        NaN   \n",
       "88879                                                NaN       NaN        NaN   \n",
       "88880                                                NaN       NaN        NaN   \n",
       "88881                                                NaN       NaN        NaN   \n",
       "88882                                                NaN         8         11   \n",
       "\n",
       "       ... WorkWeekHrs                                 LanguageWorkedWith  \\\n",
       "0      ...         NaN                    HTML/CSS;Java;JavaScript;Python   \n",
       "1      ...         NaN                                C++;HTML/CSS;Python   \n",
       "2      ...        40.0                                           HTML/CSS   \n",
       "3      ...        80.0                                C;C++;C#;Python;SQL   \n",
       "4      ...        55.0        C++;HTML/CSS;Java;JavaScript;Python;SQL;VBA   \n",
       "...    ...         ...                                                ...   \n",
       "88878  ...         NaN                      HTML/CSS;JavaScript;Other(s):   \n",
       "88879  ...         NaN                                                NaN   \n",
       "88880  ...         NaN                                                NaN   \n",
       "88881  ...         NaN                                                NaN   \n",
       "88882  ...         NaN  Bash/Shell/PowerShell;HTML/CSS;Java;JavaScript...   \n",
       "\n",
       "                                  LanguageDesireNextYear  \\\n",
       "0        C;C++;C#;Go;HTML/CSS;Java;JavaScript;Python;SQL   \n",
       "1                            C++;HTML/CSS;JavaScript;SQL   \n",
       "2                                        Elixir;HTML/CSS   \n",
       "3                                    C;C#;JavaScript;SQL   \n",
       "4               HTML/CSS;Java;JavaScript;SQL;WebAssembly   \n",
       "...                                                  ...   \n",
       "88878  C++;HTML/CSS;JavaScript;SQL;WebAssembly;Other(s):   \n",
       "88879                                                NaN   \n",
       "88880                                                NaN   \n",
       "88881                                                NaN   \n",
       "88882       C;C++;C#;HTML/CSS;Java;Objective-C;SQL;Swift   \n",
       "\n",
       "                                              DevEnviron        OpSys   Age  \\\n",
       "0                             IntelliJ;Notepad++;PyCharm      Windows  14.0   \n",
       "1                                           Atom;PyCharm      Windows  19.0   \n",
       "2                                 Vim;Visual Studio Code  Linux-based  28.0   \n",
       "3           Eclipse;Vim;Visual Studio;Visual Studio Code      Windows  22.0   \n",
       "4                                 IntelliJ;Notepad++;Vim  Linux-based  30.0   \n",
       "...                                                  ...          ...   ...   \n",
       "88878              Atom;Visual Studio;Visual Studio Code      Windows   NaN   \n",
       "88879                                                NaN          NaN   NaN   \n",
       "88880                                                NaN          NaN   NaN   \n",
       "88881                                                NaN          NaN   NaN   \n",
       "88882  Android Studio;Atom;Eclipse;NetBeans;Notepad++...  Linux-based  18.0   \n",
       "\n",
       "      Gender  Trans                Sexuality  \\\n",
       "0        Man     No  Straight / Heterosexual   \n",
       "1        Man     No  Straight / Heterosexual   \n",
       "2        Man     No  Straight / Heterosexual   \n",
       "3        Man     No  Straight / Heterosexual   \n",
       "4        Man     No  Straight / Heterosexual   \n",
       "...      ...    ...                      ...   \n",
       "88878    Man     No                      NaN   \n",
       "88879    NaN    NaN                      NaN   \n",
       "88880    NaN    NaN                      NaN   \n",
       "88881    NaN    NaN                      NaN   \n",
       "88882    Man     No  Straight / Heterosexual   \n",
       "\n",
       "                                               Ethnicity  \n",
       "0                                                    NaN  \n",
       "1                                                    NaN  \n",
       "2                                                    NaN  \n",
       "3                           White or of European descent  \n",
       "4               White or of European descent;Multiracial  \n",
       "...                                                  ...  \n",
       "88878                                                NaN  \n",
       "88879                                                NaN  \n",
       "88880                                                NaN  \n",
       "88881                                                NaN  \n",
       "88882  Hispanic or Latino/Latina;White or of European...  \n",
       "\n",
       "[88883 rows x 28 columns]"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Original Table\n",
    "data_2019"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Visualization & Data Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Lets see that Averages,Maximums,Minimums of each columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "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>YearsCode</th>\n",
       "      <th>Age1stCode</th>\n",
       "      <th>YearsCodePro</th>\n",
       "      <th>CareerSat</th>\n",
       "      <th>JobSat</th>\n",
       "      <th>ConvertedComp</th>\n",
       "      <th>NumLanguageWorkedWith</th>\n",
       "      <th>Age</th>\n",
       "      <th>CareerSatInt</th>\n",
       "      <th>JobSatInt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>8</td>\n",
       "      <td>23</td>\n",
       "      <td>4</td>\n",
       "      <td>Very dissatisfied</td>\n",
       "      <td>Very dissatisfied</td>\n",
       "      <td>65424.0</td>\n",
       "      <td>4</td>\n",
       "      <td>31.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>35</td>\n",
       "      <td>16</td>\n",
       "      <td>21</td>\n",
       "      <td>Very dissatisfied</td>\n",
       "      <td>Very dissatisfied</td>\n",
       "      <td>157017.0</td>\n",
       "      <td>5</td>\n",
       "      <td>56.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7</td>\n",
       "      <td>17</td>\n",
       "      <td>3</td>\n",
       "      <td>Very dissatisfied</td>\n",
       "      <td>Very dissatisfied</td>\n",
       "      <td>2664.0</td>\n",
       "      <td>4</td>\n",
       "      <td>24.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>20</td>\n",
       "      <td>14</td>\n",
       "      <td>15</td>\n",
       "      <td>Very dissatisfied</td>\n",
       "      <td>Very dissatisfied</td>\n",
       "      <td>110000.0</td>\n",
       "      <td>4</td>\n",
       "      <td>39.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>27</td>\n",
       "      <td>15</td>\n",
       "      <td>25</td>\n",
       "      <td>Very dissatisfied</td>\n",
       "      <td>Very dissatisfied</td>\n",
       "      <td>110509.0</td>\n",
       "      <td>1</td>\n",
       "      <td>49.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53060</th>\n",
       "      <td>15</td>\n",
       "      <td>16</td>\n",
       "      <td>11</td>\n",
       "      <td>Very satisfied</td>\n",
       "      <td>Very satisfied</td>\n",
       "      <td>120000.0</td>\n",
       "      <td>2</td>\n",
       "      <td>36.0</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53061</th>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>5</td>\n",
       "      <td>Very satisfied</td>\n",
       "      <td>Very satisfied</td>\n",
       "      <td>412464.0</td>\n",
       "      <td>3</td>\n",
       "      <td>29.0</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53062</th>\n",
       "      <td>7</td>\n",
       "      <td>19</td>\n",
       "      <td>4</td>\n",
       "      <td>Very satisfied</td>\n",
       "      <td>Very satisfied</td>\n",
       "      <td>2000000.0</td>\n",
       "      <td>4</td>\n",
       "      <td>26.0</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53063</th>\n",
       "      <td>31</td>\n",
       "      <td>18</td>\n",
       "      <td>28</td>\n",
       "      <td>Very satisfied</td>\n",
       "      <td>Very satisfied</td>\n",
       "      <td>2000000.0</td>\n",
       "      <td>8</td>\n",
       "      <td>48.0</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53064</th>\n",
       "      <td>12</td>\n",
       "      <td>14</td>\n",
       "      <td>3</td>\n",
       "      <td>Very satisfied</td>\n",
       "      <td>Very satisfied</td>\n",
       "      <td>130000.0</td>\n",
       "      <td>4</td>\n",
       "      <td>26.0</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>53065 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       YearsCode  Age1stCode  YearsCodePro          CareerSat  \\\n",
       "0              8          23             4  Very dissatisfied   \n",
       "1             35          16            21  Very dissatisfied   \n",
       "2              7          17             3  Very dissatisfied   \n",
       "3             20          14            15  Very dissatisfied   \n",
       "4             27          15            25  Very dissatisfied   \n",
       "...          ...         ...           ...                ...   \n",
       "53060         15          16            11     Very satisfied   \n",
       "53061         14          14             5     Very satisfied   \n",
       "53062          7          19             4     Very satisfied   \n",
       "53063         31          18            28     Very satisfied   \n",
       "53064         12          14             3     Very satisfied   \n",
       "\n",
       "                  JobSat  ConvertedComp  NumLanguageWorkedWith   Age  \\\n",
       "0      Very dissatisfied        65424.0                      4  31.0   \n",
       "1      Very dissatisfied       157017.0                      5  56.0   \n",
       "2      Very dissatisfied         2664.0                      4  24.0   \n",
       "3      Very dissatisfied       110000.0                      4  39.0   \n",
       "4      Very dissatisfied       110509.0                      1  49.0   \n",
       "...                  ...            ...                    ...   ...   \n",
       "53060     Very satisfied       120000.0                      2  36.0   \n",
       "53061     Very satisfied       412464.0                      3  29.0   \n",
       "53062     Very satisfied      2000000.0                      4  26.0   \n",
       "53063     Very satisfied      2000000.0                      8  48.0   \n",
       "53064     Very satisfied       130000.0                      4  26.0   \n",
       "\n",
       "       CareerSatInt  JobSatInt  \n",
       "0                 1          1  \n",
       "1                 1          1  \n",
       "2                 1          1  \n",
       "3                 1          1  \n",
       "4                 1          1  \n",
       "...             ...        ...  \n",
       "53060             5          5  \n",
       "53061             5          5  \n",
       "53062             5          5  \n",
       "53063             5          5  \n",
       "53064             5          5  \n",
       "\n",
       "[53065 rows x 10 columns]"
      ]
     },
     "execution_count": 115,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Averages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The average years coded of a surveyed developer is: 12\n",
      "The average age when a serveyed developer first coded is: 15\n",
      "The average number of years a developer coded professionally is: 8\n",
      "The average Career Satisfcation among the surveryed data set is: 3.995910675586545 -> Slightly Satisfied (Rounded up)\n",
      "The average Job Satisfcation among the surveryed data set is: 3.702647696221615 -> Slightly Satisfied (Rounded up)\n",
      "The average annual salary from all surveyed developers is: 126728\n",
      "The average number of programing a single developer know is: 5\n",
      "The average age of a surveryed developer is: 31\n"
     ]
    }
   ],
   "source": [
    "print('The average years coded of a surveyed developer is:',int((df.YearsCode.mean())))\n",
    "print('The average age when a serveyed developer first coded is:',int(df.Age1stCode.mean()))\n",
    "print('The average number of years a developer coded professionally is:',int(df.YearsCodePro.mean()))\n",
    "print('The average Career Satisfcation among the surveryed data set is:', (df.CareerSatInt.mean()), '-> Slightly Satisfied (Rounded up)')\n",
    "print('The average Job Satisfcation among the surveryed data set is:', (df.JobSatInt.mean()), '-> Slightly Satisfied (Rounded up)')\n",
    "print('The average annual salary from all surveyed developers is:',int(df.ConvertedComp.mean().round()))\n",
    "print('The average number of programing a single developer know is:', int(df.NumLanguageWorkedWith.mean()))\n",
    "print('The average age of a surveyed developer is:',int(df.Age.mean()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Maximums"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The maximum years coded of a surveyed developer is: 50\n",
      "The maximum age when a servyed developer first coded is: 85\n",
      "The maximum number of years a developer coded professionally is: 50\n",
      "The maximum Career Satisfcation among the surveryed data set is: 5 -> Very Satisfied (Rounded up)\n",
      "The maximum Job Satisfcation among the surveryed data set is: 5 -> Very Satisfied (Rounded up)\n",
      "The maximum annual salary from all surveyed developers is: 2000000\n",
      "The maximum number of programing a single developer know is: 28\n",
      "The maximum age of a surveyed developer is: 99\n"
     ]
    }
   ],
   "source": [
    "print('The maximum years coded of a surveyed developer is:', int(df.YearsCode.max()))\n",
    "print('The maximum age when a servyed developer first coded is:', int(df.Age1stCode.max()))\n",
    "print('The maximum number of years a developer coded professionally is:',int(df.YearsCodePro.max()))\n",
    "print('The maximum Career Satisfcation among the surveryed data set is:', (df.CareerSatInt.max()), '-> Very Satisfied (Rounded up)')\n",
    "print('The maximum Job Satisfcation among the surveryed data set is:', (df.JobSatInt.max()), '-> Very Satisfied (Rounded up)')\n",
    "print('The maximum annual salary from all surveyed developers is:',int(df.ConvertedComp.max().round()))\n",
    "print('The maximum number of programing a single developer know is:', int(df.NumLanguageWorkedWith.max()))\n",
    "print('The maximum age of a surveyed developer is:',int(df.Age.max()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Minimums"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The minimum years coded of a surveyed developer is: 1\n",
      "The minimum age when a servyed developer first coded is: 5\n",
      "The minimum number of years a developer coded professionally is: 1\n",
      "The minimum Career Satisfcation among the surveryed data set is: 1 -> Verey Dissatisfied (Rounded up)\n",
      "The minimum Job Satisfcation among the surveryed data set is: 1 -> Slightly Dissatisfied (Rounded up)\n",
      "The minimum annual salary from all surveyed developers is: 0\n",
      "The minimum number of programing a single developer know is: 1\n",
      "The minimum age of a surveyed developer is: 1 -> less than 5 year\n"
     ]
    }
   ],
   "source": [
    "print('The minimum years coded of a surveyed developer is:', int(df.YearsCode.min()))\n",
    "print('The minimum age when a servyed developer first coded is:', int(df.Age1stCode.min()))\n",
    "print('The minimum number of years a developer coded professionally is:',int(df.YearsCodePro.min()))\n",
    "print('The minimum Career Satisfcation among the surveryed data set is:', (df.CareerSatInt.min()), '-> Verey Dissatisfied (Rounded up)')\n",
    "print('The minimum Job Satisfcation among the surveryed data set is:', (df.JobSatInt.min()), '-> Slightly Dissatisfied (Rounded up)')\n",
    "print('The minimum annual salary from all surveyed developers is:',int(df.ConvertedComp.min().round()))\n",
    "print('The minimum number of programing a single developer know is:', int(df.NumLanguageWorkedWith.min()))\n",
    "print('The minimum age of a surveyed developer is:',int(df.Age.min()), '-> less than 5 year')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, '# of Developers')"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 700x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "num_lang = df.NumLanguageWorkedWith\n",
    "plt.hist(num_lang, bins=28)\n",
    "\n",
    "plt.title(\"Number of Developers That Worked With Number of Programming Languages\")\n",
    "plt.xlabel(\"# of Programming Languages\", fontsize=16)  \n",
    "plt.ylabel(\"# of Developers\", fontsize=16)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Number of Developers That Worked With Number of Programming Languages Analysis\n",
    "We can see that the average number of programming language that the average number of developers knows are 5 languages. There are few to no developers who has knowledge of knowing more than 15 programming languages."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, '# of Developers')"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 700x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "job_sat = df.JobSat\n",
    "\n",
    "plt.hist(job_sat, bins=5)\n",
    "\n",
    "plt.title(\"Developer's Job Satisfaction\")\n",
    "plt.xticks(rotation=45)\n",
    "plt.xlabel(\"Job Satisfaction\", fontsize=16)  \n",
    "plt.ylabel(\"# of Developers\", fontsize=16)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  Developer's Job Satisfaction Analysis\n",
    "We are now examining how many developers are satsified with their jobs. Looking at this, we can tell that most developers surveyed are either 'Slightly Satisfied' or 'Very Satisfied' with their currect occupation.  Although we can see that it is almost a perfect left-skewed histogram, there are many that's 'Slightly Dissatisfied'. This can mean that some developers had accepted a poor job or the working enviroment was not enjoyable. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, '# of Developers')"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 700x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "career_sat = df.CareerSat\n",
    "\n",
    "plt.hist(career_sat, bins=5)\n",
    "\n",
    "plt.title(\"Developer's Career Satisfaction\")\n",
    "plt.xticks(rotation=45)\n",
    "plt.xlabel(\"Career Satisfaction\", fontsize=16)  \n",
    "plt.ylabel(\"# of Developers\", fontsize=16)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Developer's Career Satisfaction Analysis\n",
    "Now looking at the overall satisfaction of the surveyed developers' career as a programmer, this is very similar to the histogram about job satisfaction. We can see that most surveyed developers are very satisfied with their career. Comparing to the previous histograms, some developers shifted over to the satisfied side in the Career Satisfaction histogram. This is probably due to enjoying their career, but ended up with a poor job due to some underlying factors. Overall, we can assume that if a developor is very satisfied with their job, they can also be satisfied with their career choice. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, '# of Developers')"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 700x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "age_1st_code = df.Age1stCode\n",
    "age = df.Age\n",
    "\n",
    "plt.hist(age_1st_code, bins=29, histtype='bar', stacked=True, color='red', label='Age 1st Coded')\n",
    "plt.hist(age, bins=29, histtype='bar', stacked=True, color='blue', label='Age')\n",
    "\n",
    "plt.legend(loc='upper right')\n",
    "plt.title(\"Number of Developers Based On Age\")\n",
    "plt.xlabel(\"Age\", fontsize=16)  \n",
    "plt.ylabel(\"# of Developers\", fontsize=16)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Number of Developers Based On Age Analysis\n",
    "We ploted both the age and age first coded in the same graph to see if there are similarities. Just by looking at the graph we can see that the average age first coded is about 10 years old and the average age of develpers is around 20-25 years old. This falls in our idea that learning code at an early age will possibly lead to someone being a developer. In this case we can assume that if someone who is 10 years old and started to first code can lead to them being a developer around the ages 20-25 years old "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, '# of Developers')"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 700x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "years_pro = df.YearsCodePro\n",
    "plt.hist(years_pro, bins=30)\n",
    "\n",
    "plt.title(\"Developer's Years of Coding Professionally\")\n",
    "plt.xlabel(\"Years\", fontsize=16)  \n",
    "plt.ylabel(\"# of Developers\", fontsize=16)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Developer's Years of Coding Professionally\n",
    "This histogram depicts the number of years that developers that has coded professionally. Coding professionally excludes classes taken and courses learned. This is when a developer works for a certain company and/or sells their code/algorithms/services to help them increase their recognition and income. Above, we can see that the average years a developer coded professionally is around 5-7 years. We can assume that the reason for this is becuase most developers are either early middle aged (i.e. 20-35 years old). There are a smaller amount of developers as years increase, but those can be seen as older aged developers (i.e 50-60 years old) who has been coding for decades. There is the large amount of developers who have 1 had one year of coding professionally which can mean that they have just graduated and/or entering the field of being a developer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Annual Salary')"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 700x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "annual_salary = df.ConvertedComp\n",
    "\n",
    "a1, b1 = np.polyfit(age, annual_salary, 1)\n",
    "\n",
    "age_range = np.arange(0, 100, 1)\n",
    "pred_age  = a1*age_range + b1\n",
    "\n",
    "plt.scatter(age, annual_salary, color='blue')\n",
    "plt.plot(age_range, pred_age, color='red')\n",
    "\n",
    "plt.title(\"Annual Salary Impacted By Age\")\n",
    "plt.xlabel(\"Age\", fontsize=16)  \n",
    "plt.ylabel(\"Annual Salary\", fontsize=16)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  Annual Salary Impacted By Age Analysis\n",
    "These graphs are points that compare age and salary, and adding a linear regression we can see that it is in increasing regression line. This tells us that the older you are, the higher your annual salary. There are some developers who's age is close to 0 in the graph. This would suggest that they have indicated their age as null or left the response blank."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Annual Salary')"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 700x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "a2, b2 = np.polyfit(age_1st_code, annual_salary, 1)\n",
    "age1st_range = np.arange(5, 86, 1)\n",
    "pred_age1st  = a2*age1st_range + b2\n",
    "\n",
    "plt.scatter(age_1st_code, annual_salary, color='blue')\n",
    "plt.plot(age1st_range, pred_age1st, color='red')\n",
    "\n",
    "plt.title(\"Annual Salary Impacted By Age First Coded\")\n",
    "plt.xlabel(\"Age First Coded\", fontsize=16)  \n",
    "plt.ylabel(\"Annual Salary\", fontsize=16)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Annual Salary Impacted By Age First Coded Analysis\n",
    "\n",
    "Comparing this graph, we can see that the younger you are when you first learn to code, the higher your salary will be in the future. Versus learning how to code in later years (such as 30 years old) will yield a smaller salary. This can be supported with the idea that, leaning to code early will be able to learn more langauges thus giving you a sligt edge when applying for job in the tech field."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Income')"
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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DcvnyZRVtVFQUkclkJDQ0VJBeUFBA+vbtS1xcXMjLly8JIYQ8fvyYBAUFkSVLlgi0GRkZxMXFhXTq1EmRxo9DZ2dn8tdffwn0Y8aMITKZjGRkZAjSY2NjyejRo8m///6rsW2vX78mDRs2JF27dqXqi5IcOnSIyGQysmDBAkG6XC4nPXr0II0bNyZpaWmEEEKOHTtGZDIZmTt3rkD7999/K8Y3/3eal5dHWrVqRfr166cYgzyhoaFEJpOR3377TVGWh4cHad26NcnOzhbU4bPPPlM77tTh5eVF3NzcNF7fvHkzkclkZM2aNYLPODs7k/Xr1wu0qamppFGjRqR3796koKBAcG3u3LlEJpORY8eOKdL4cfrkyRNF2saNG4lMJiO///674PPZ2dnE29ubtG3bVpE37f3/7rvviEwmUxkP//zzDwkMDCRnzpwhhLwZayX7bfbs2Sr1JoT7fnJ1dSU9evRQpPHfSz4+PiQvL0+R/vTpU9KwYUPi5+enSLt+/ToJDAwUfIcRQsjt27eJTCYjo0aNUqSdPXtW5R4MGjSINGrUSPF//jv/5s2bgvzCw8PVfocaE7a0zRDAH7KpVasW2rRpAwCQSCTo27cvXr58iZMnT6r9XPPmzeHi4iJI4/+v7ALiww8/RIcOHQRprq6uACBYCtWHGTNmIDw8HHZ2diguLkZ2djaysrJQp04dANwsmL58+OGH2LlzJ1q2bImbN2/ip59+Qu/eveHh4YGxY8di7969Kksbnp6e2LZtm+IXdm5uLrKyshQzFY8fPxa9HV27dhX8v1u3bqhYsSIOHDggSD969CgAoG/fvnr0giq9e/dW/NvGxkaxqb5Pnz4CXcOGDVFYWIj09HRBur29PTp37ixI69ixIwDgypUrirSff/4ZmzdvhpWVFQoLCxV9UbduXQBv+iI5ORk3b95E+/btUblyZUHdNmzYgK1bt2ptT3R0NACgS5cuyMrKUrxyc3PRsWNHFBQU4K+//gLALacBQPfu3QV5uLi46O26IyIiAh4eHoqXn58fFixYAC8vL6xYsUIxIwQAAwYMAAC199TOzk7Rf7qoV68exo8fj1u3buGLL75AbGysYhuFMvy2AOV+ycvLU/QLf79q1qyJX3/9FdOmTQPA7ZXLysqCRCJB9erV1Y77Dz/8EO7u7oI0fn9mQkKCIN3b2xubNm1Co0aNNLYtIyMDxcXFpZqlOXHiBABu1rYk1tbW6NmzJwoLCxXLk/zsoPIYaNq0qYpbsfPnzyMjIwOdO3fG69evBf3o7+8PiUSiWGK+efMmMjMz4ePjI9jDam1trfK3RUPJsjIzM5GYmIjQ0FCsXLkS1atXF2wnALgZSeUVllOnTqGoqAj9+vVDuXLCBcx+/foBAGJjY7XWIzo6Gvb29mjdurWgTsXFxWjfvj1evHiBxMREAPT3n9cpbydo3LgxtmzZojKjWJI//vgDVatWVVmVqV27Nlq3bo07d+6ofM/269dPMBPu4OCA6tWrC55Xrq6u2LJli2IG8dWrV8jKykKNGjVgZWWl9zOI/5tXt4XL3t5e5RlqTNjSNkPA8ePHkZ6ejqFDh0IikSjS+/Tpg9WrV2PPnj1qN3GrO7XMb2IvLCwUpPNGUUn45RZlLS05OTnYtGkTIiMj8eTJExQVFQmuK/+fFplMhh07diAxMRFnzpzBX3/9hcuXLyM2NhaxsbFYs2YN1q5dKzAioqOjsX37dty4cQOvX7/Wqx6laYeyawtbW1t07doV+/fvx40bNxRGenR0NOrVq6fy8NYHqVSqsoTKGzzKy3p8uvISWv369VUOdPBteP78uSItLS0NmzZtwrFjx/Ds2TOVfWJ8X9y9excA4OjoqFJfJycnnW1KSkoCAPj7+2vU8IZQSkqKxrLq16+Pf/75R2d5PL6+voIl2NevX+PBgwfYvXs3unbtiiVLlqB9+/YAgFatWuHjjz9GZGQkZs6cCRsbG8USV79+/fQ6fRsUFITo6GjExcWhVq1a+L//+z+1Or5fNO0RBiDYl3nt2jX8+uuviI+PV9n7p+4AjzqXLKNHj0Z8fDzGjx+PFi1aoH379oq9ciW/j7RRXFxMpStJUlISJBKJ2vHC/1C6f/8+AO1jwMnJSXFymc8XAJYuXYqlS5eqLVt5bKnrF31PQOfl5cHDw0MlXSKRoF27dvjuu+9QtWpVlWvKf8N8/dWdbq9Xrx4AqN07X5Lk5GSN9eF58uQJnJ2dqe//0KFDERkZiR9//BEHDx6Ej48P2rZtixYtWmg9LPby5UtkZGTAw8ND7XiqV68e4uLicP/+fcFWFU3PLOXn1ZkzZ7B161ZcvnxZsMcU0P8Z1LZtW9SqVQtHjhzB9OnTYW1tjefPn+PSpUsYPHiwSR0SY4YkQ8CePXsAcPsYV61aJbj2/vvvIz4+Ho8ePVL5Ei05e6ILsf8ACCGKjdKenp6KPVdSqRSRkZGKNr0NTk5OcHJyUvzavHbtGrZt24bIyEhMnjwZ0dHRkEql2Lt3L+bMmYOaNWviq6++gpOTEypUqIDMzEydLmdK2w5bW1uVtAEDBmD//v04ePAgXF1dkZSUhNu3b2Pq1Klv1Q9SqVTjXlPa+6ruRCc/A5OVlQUAin1V9+/fR/fu3dGhQwe8//77sLKyQmhoKGJiYhSf5Y11fcZgSfLy8iCRSBAaGqqxbfzDnT9coK6t+rpSqVGjBlq3bq2S3rdvX/Tr1w/Tpk3DH3/8AXt7e0gkEvTr1w8hISGIjY1Fp06dcPz4cRQWFuo9w1yuXDkMHToUc+bMwYABA9SOH4DrFysrK60zuvz3wK1btzB06FBYWVkpDlHx93TatGmKg0MlUVduixYtEBERgV9//RWnTp3C5cuX8csvv8DR0RHTp09Xmckuyfvvv49y5crpnPVXR15eHsqXL6/WCOF/5PKGAT/e1O3lVh4D/Ge++OILtGvXTm3Z/EwXP7Zo8tVF+fLlVfYmv/fee3B0dFQxIEvWQ7n9fP3V/c3ydVJ38I2HEIK8vDzUqFFDoyENvDFUae9/vXr1EBERgS1btuD48eNYu3Yt1q5di2rVqmHChAkYPHiw2nL49mjaZ6upTTTfbadPn8bYsWNhb2+P0aNHo1GjRooxXhqXWvzf/MqVK/Hnn3/C398fx44dQ3FxcalmqA0JMyQZCpKSkhRLBfv27dOo27dvn8ZZjLJAeZbv2rVruHz5Mlq1aoVNmzYJjAF9T8vR0rRpUyxbtgxPnjzB5cuXcf/+fTg5OWHLli2QSqUIDQ1V/GIH3vyy14aY7XB3d0eDBg1w9OhRfP311zh69CikUqnGk6xliboHDz+DZW9vD4BbUrt//z4+++wzLFmyRKDdvXu34P8ffPABgDdGqL7Y2tqCEAKZTKbISxP8g0Yul6tcy83NLVX5ylSqVAm+vr4IDQ3F1atXFTOCffr0wYoVKxAZGYlOnTohOjoa9evXh5ubm95l8AaDttkbW1tbFBcXw9nZGVWqVNGa3/bt2yGXy/Hzzz8Ltj4A+q8yODk54aeffkJRURFu3LiBEydOYMeOHZg0aRJ27NiBFi1aqP2cjY0NGjVqhOvXr6v9sVsSuVyOgoICxYO+YsWKePz4MQoLC1WWcPnxymt5Q095WwugOgb4z1SpUkXtj4aS8GOLJl9dSKVSneXRwBuQ6srnjTJNP0QAzhiqWLEicnNzqetDe/8/+ugjzJkzB3PmzMGtW7cQExOD7du347vvvoOdnR169OihsT3Ks4U8yvdaH7Zu3QpCCFavXi2Yfc3LyyvVLDnALamvXr0akZGR8Pf3R3R0NGQyGZo0aVKq/AwF2yPJUMDPeIWEhOD27dsqrytXrsDW1hYRERGlXiqmhZ9dUvcHzy8x8fBLQupOVivvtaHl5cuXWLp0KdasWaNVx89U8cZtSkoKatasKTAiAVCFTBO7Hf3798eLFy9w4cIFREVFoV27diZxyi85OVllmfrRo0cAoDi9y/eF8l6nwsJCFTdK/BJUSbcfPH/99Rf27t2rsk+zJPxsCL8PsiRZWVkCQ4hf+uPrWxJ15ZcW3pgpaVTUqFED7du3R2xsLJKSkpCQkGDQmQlt/ZKZmSnoF/5+tW3bVqBLTEzEy5cvS1W+VCpFs2bNMHXqVCxatAiEEMVeRk3ws7Pr1q3TqluzZg06dOiAGzduAOCMF0KI2nvIp/HL3vx4UzcG+G0WPNr6kBAiGJf82OL7Ulu+ZQXfZt4VWkmU+0UTn3zyCXJzcwVL/jzp6ekaXRvpc/8bNmyIL7/8Ehs3bgTAuRBSR9WqVVG1alXcu3dPrXHHt6k0ztRTUlJgbW2tsoRf2mcQwO0j9vT0RExMDBITE3H58mWTm40EmCHJ+B/8IZsqVapo3LhfsWJF9OjRA2lpaTo3WL8t/DLV7du3BV80jx8/Vvky4WeRlDczR0REKGYClWcxdVGpUiUcPHgQ69at0+h6Izk5GadPn0a1atUgk8kAANWqVcPLly8Fs25PnjxBWFiYznqI3Y5evXrB2toaK1euRFJS0lsfshGL9PR0lXt4/PhxAG98KPJ9ofxQXbduHXJycgC86Yu6deuiQYMGOHfunGC/VmFhIb799lv8+OOPihkG3kAvaaDxh5W2bdsmeLgQQjBt2jR4e3sryuQfEsqhI69cuaL2YVsasrOzFVslmjVrJrjWv39/5Ofn45tvvoFEIjHoDDPfL/xMC09xcTGmTJkCHx8fxUyVuvuVn5+PH374AXZ2digqKlLZK6vMq1ev0L9/f3z99dcq1/hlcl1LjP3794eLiwv279+P0NBQtZo9e/Zg48aNqFmzpsLFEr/vm/czWrINhw4dwnvvvafYr6ppDFy6dEll5aFNmzZ4//33ERMTo7KX8MiRI/D09FQcgnNxcYGtrS3+/PNPwQ9ouVyOgwcPam23oejQoQOsra2xb98+lfvHrwzociXGjyPl+/H69WsMHz4cvXr1AiGE+v6T/7maCgoKUjEGacZJly5dkJGRoXL/EhMTkZCQADc3t1L94P7ggw9QUFAg8O2YkZGB1atXo3z58no/g3j69++PV69eYfbs2ZBKpSYZGIQtbTMAcA/yjIwMjBw5Uusf4YABAxRREbQdTnhbbGxs0LlzZ0RFRWHKlCnw9vZGWloatm/fjs6dOwscRbu7u6NmzZo4cuQIHBwcUK9ePVy8eBHnzp3Dt99+iylTpuDAgQN4//33VU44ayt/6dKl+PLLLxEUFAR/f3+0a9cO9vb2yMzMxM2bN3H06FEUFBRg1apVihnUrl27YvPmzZg4caLC6P7tt9/wzTff4KeffsLNmzexc+dO+Pj4qJQpdjuqVq0KPz8/HD9+3KRO+bm4uGD+/Pm4cuUKZDIZbt++jd9++w21atVSGEbe3t6oWLEitmzZAhsbG1SvXh2nTp1CSkoKvvrqK3z//ffYvn27QjtnzhyMGTMGgYGBCAoKQsWKFXHkyBHcuXMHc+fOVYxpfgb522+/Rf369TFy5Ej4+/ujY8eO+OOPPzBy5Ej06tULhYWFiIqKwoULF/Dll18qHlAdO3ZE/fr1FbP3bm5uSE1NxZ49e9CmTRvFqW4aUlJSBA+zgoICpKam4sCBA0hJScH06dNVHmg+Pj6oXr06rly5Am9vb4POMHfs2BG+vr6IiYlBYGAgevbsiYKCAkRFReHixYuYOHGiwkDv1q0bIiMjMXv2bAQFBUEul2Pv3r3w8PBA5cqVER0djeXLl6N79+4alw0rVKiAxo0bY/fu3UhPT4evry9sbW2RkpKCHTt2wNbWVnFSWBM2NjZYv349vvjiCyxatAhHjx5F586d4eDggGfPnuHUqVNISEiAu7s71q5dq5j57dKlC7y8vLBr1y68fv0arVq1Qk5ODo4cOYL79+9j3rx5im0XnTt3xurVq7Fr1y4UFxejWbNmSElJwZ49e9C6dWtcuHBBUJ958+Zh6tSpCAgIwMiRI1GtWjXcuHEDu3fvRv369RUGqo2NDUaOHIk1a9Zg1KhR6NmzJ4qLixEVFYVatWopTjaXJQ4ODpg4cSJCQkIwYsQIdO/eHeXKlUN8fDyOHTuGrl27wsvLS2se/MGYAwcO4NWrVwpH8Pv378edO3fw448/QiKRUN9/iTCkVk4AACAASURBVEQCDw8PhISEICAgAN26dYO9vT2ePXuG3bt3w9raWuMeSQCYMGECTp06hW+++Qb//vsvGjRogMePH2Pnzp2wsbHBnDlzStVX3bp1w5UrV/DVV19h4MCByMrKwvbt2xX+U69du4bNmzdT+5Lk8fPzQ9WqVXHlyhX4+fmp+AY2BZghyQDw5tcl73JAE02aNEHjxo3x559/UkWaeBvmzJmD8uXL48yZMzh16hScnJwwd+5cyOVygSFZvnx5bNiwAQsXLsRvv/2G9957D23btsWOHTtQo0YNHDlyBPHx8Vi/fj21IQlwswmRkZEICwvDuXPncPbsWbx69QoVKlRA7dq10a9fPwwbNkywF2vixImQy+X4/fffMX/+fHzyySeYP38+/P39kZeXh8WLFyMkJETtKUhDtKNPnz44fvw4evToYTKn/N5//338+OOPWLx4MXbu3AmJRIL27dvjm2++UexhqlatGjZs2IAlS5Zg3bp1sLOzg4+PDxYuXAgrKytERUXh/PnzKFeuHLy9vdG2bVuEhYVh9erVWLFiBV6/fo1PPvkEq1atEsyYjB49GtevX0dkZCSqV6+O4cOHAwCWL1+OrVu34tChQ5g/fz4kEglkMhmWLl2qcOUEcFsutmzZgp9++glRUVE4dOgQGjZsiMWLF+PixYt6GZJnz57F2bNnBXk7ODhAJpNh7ty58PT0VPlMuXLl0LNnT2zZssXgM8wSiQSrVq1CaGgojhw5ougXZ2dnhISECNzf+Pv7Y+7cuQgLC8PChQtRs2ZNfP755wgMDMT169dx7do1hIWFoVq1alofpN999x2cnJxw6NAhLF26FPn5+fjwww/Rvn17jBkzRu3pWWVq1KiBvXv34uDBg4iKisLmzZuRlZUFW1tbNGrUCCEhIejcubNgL6REIsHatWuxceNGHDlyBFFRUbCxsYGLi4uKI2kbGxvFGIiMjMTBgwfRqFEjLFu2DGfPnhUYkgBnYHzwwQfYuHEjNmzYgLy8PDg4OGDEiBEYPXq0wNXPhAkTIJVKsW/fPvz000+oUaMG+vXrhy5duuDPP/+kum9iM3bsWNSsWRNhYWFYvHgxCCGoW7cuZs6cqeIsWx02NjbYtm0bNm7ciGPHjuHkyZOwtrZG06ZNsXnzZsE4p73/Y8eOhYODA3bv3o2VK1ciNzcXNWrUQLNmzbBs2TIVV3Ql+eCDD7Bnzx6sXLkShw4dwsuXL1G5cmW0atUK48ePV6wu6cuQIUOQkZGBgwcPYv78+ahbt64i8ELdunUxe/ZsrF69GjVr1tS557gk1tbW6NGjB3777TedP6SMhYRo2qDAYDDMng0bNiAkJARHjhwp9RekWKSkpMDf3x+enp7YvHmzUetizgQFBeH27duIiYkp9Ul1BoNhPowYMQL379/HyZMnVQ6DmQJsjySDYaE8ffoUW7Zsgaenp9GNSIY4/Pnnnzhz5gyGDx/OjEgG4x0gJiYG58+fx/Dhw03SiATY0jaDYXGcP38eiYmJ2LJlC+RyOb799ltjV4nxlhw9elRxT52dnXXGkmYwGOYLIQTR0dG4e/cuQkND0bhxY6ptBMaCGZIMhoWxadMmnDt3Do0aNcKaNWuo9pUxTJuZM2dCIpHAx8cHCxYsYLORDIYFU1xcjBkzZsDKygq+vr5YsGCByc5GAmyPJIPBYDAYDAajlLA9kgwGg8FgMBiMUsEMSQaDwWAwGAxGqTDdRXeGgpYtW0Iul6N69erGrgqDwWAwGIx3gGfPnsHGxkZniF9mSJoB+fn5Bo9tzWAwGAwGg8FTWFioMRZ6SZghaQbUqFEDAHDy5Ekj14TBYDAYDMa7AG0YZLZHksFgMBgMBoNRKpghyWAwGAwGg8EoFcyQZDAYDAaDwWCUCmZIMhgMBoPBYDBKBTMkGQwGg8FgMBilghmSDAaDwWAwGIxSwQxJBoPBYDAYDEapYIYkg8FgMBgMBqNUMEOSwWAwGAwGg1EqTNqQPHjwIPr27Qt3d3f4+vpi7ty5ePnypeL63bt3MXr0aLi7u8Pd3R1jxoxBYmKiII+srCzMnj0b7dq1Q5MmTdCnTx/ExMQINIQQbNiwAR06dICrqyv8/f2xceNGlfqcPHkSffv2RZMmTdCmTRvMmTMHOTk5Ao1YdWIwGAwGg8EwdUzWkNy6dSu+/vpr9OnTB4cOHcL8+fMRFxeHr776CoQQpKenY/jw4ZBKpdi2bRvCwsJQrlw5jBgxAllZWYp8JkyYgISEBCxevBgHDx5E+/btMX78eFy+fFmhWbNmDdauXYvx48fjyJEjmDhxItauXSswJs+fP48JEybA09MTBw4cQEhICBISEjB58mSFRsw6lSU9ewISyZtXz57qdQEBQl1AgHpdUJBQFxSkXhcYKNQFBqrXzZwp1M2cqV534IBQd+CAet2aNULdmjXqdaGhQl1oqHodAFy/DlhZcTorK+7/6vjhB2GeP/ygXvf0KfDhh8B773HvT5+q1507J8zv3Dn1uqtXhbqrV9XrMjMBT0+gTh3uPTNTve7ffwGplMtLKuX+r46XL4EmTYAPPuDeS/wOFJCaClStClhbc++pqep1tP2ckwP06QM0bcq9K/3eU3D6tLBfTp9Wr6PtF9r20upoywWAZ8+AevWASpW492fP1OuKioDYWGDnTu69qEi97tUrYMIEoHNn7v3VK/U62r6mRex2yOXA8uXAxIncu1z+du2gLZcWsfuPtn5i6xjvMMQEKS4uJp9++imZOXOmIH3Pnj1EJpORBw8ekFWrVpFmzZqRzMxMxfXMzEzSrFkzsn79ekIIIRcvXiQymYzExcUJ8hk4cCAZNWoUIYSQvLw84ubmRpYtWybQLFu2jDRv3py8fv2aEEJIQEAAGThwoEATFxdHZDIZ+euvvwghRLQ6KePn50f8/Py09FjpATS/mE63zhB5VqyoXlOxomHLdXJSr3FyKl1+Dg7qNQ4OQp2NjXqdjU3pyvXwUK/x8DBsv9C2l1ZHWy4hhNjbq9fa2wt1+/cTUru2UFO7Npdekl691OfXq1fp+poWsdsxfTohUqlQJ5Vy6aVpB225tIjdf7T1E1vHsExobQ/oVBiJ9PR0gUFGCCGxsbFEJpORy5cvk4EDB5LAwECVzwUEBJAhQ4YQQggJCQkhTZs2JQUFBQLNqlWrSOPGjUl+fj45c+aMIs+S8AZffHw8ef36NWnUqBFZt26dQCOXy4mrqytZvnw5IYSIVidlDGVIanuQlnygMp16nSHy1GRE8i/emBS7XE1GC//ijRfa/DQZS/yLN5o0GZH8izcmacvV9GDmX/wDWux+oW0vrY62XEI0G1/8izfC9u8nRCJRvS6RcC/eONBkRPIv3pik7WtaxG7H9Ona8+ONSdp20JZLi9j9R1s/sXUMy4XW9jDZpe0qVaqgcuXKgrQTJ06gYsWK+OSTT5CcnIzatWurfO7jjz9GUlISACA5ORk1a9ZEuXLlVDSFhYV4+PAhkpOTAQCOjo4CTZ06dQAASUlJePDgAYqKilQ01tbW+OijjwTliVGnskDT8rUyFSvS6WrWpNPVqkWn++QTOl337nS6ESPodP360elCQzUvqyozdiydbvp0IC9PuyYvT/OSvTKbN9PpTp8GlLbxqpCYqHnZXJkzZ4D//tOu+e8/rv80LTPyyOXAsWN05Z47ByQkaNckJABRUXT5HT5M1y/JyXTtvXePTpecTFduZia37KttuRvgrj99CkyaxJkCyvBpkydzy6qHDmnP79AhrlyavqZdphW7Ha9eASEh2vMLCeG2FNC0IzOTrlzaZd+cHHH7r6iIrn5yubg6tszNAEx4j6QyJ06cwN69ezF27FjY2dkhNzcXtra2KrpKlSohOzsbAJCTk6NRAwDZ2dmKwzLKOl6Tk5OjUcOn8dfFqlNZEBlJp9O0L0oZTXv4lHn8mE537x6d7uhROt1vv9HpIiLodKNGAc2a0WnVnNtSy9KldLq+fel0o0fT6Xx86HTt2tHpvLzodLT917UrnY62fj160Ol69aLTNW5sHF337kCrVnRaNzcgJUXzdUKAR48073tWhrZcsfOjbcf06bqNnKIiwNubrtzu3enKjYujy4+2X2h1cXF09Vu7VlwdbXsZlo1ZGJJHjx7F5MmT0bNnT4zVMb1D1P2EMpCGlrIuj1E2sFv2dlhK/+Xn0+kKCsTN7+FDzQdRlMnIoNPpmgnloS1X7Pxo23H3Lp2O9oct7ULRkyd0Otp+odWZerkMy8bkDckdO3Zg6tSpGDRoEH7++WdIJBIAUMxKKpOTkwN7e3uFRtk9D68BgMqVK8POzk6QxsPnXblyZcUSu6a8+Oti1YlhHvxvKDJKiaX0X/nydDpra3Hzq1MHqF6dTlulCp3OyYlOR1uu2PnRtoN2a8xHH9Hp/rfTSSe0W3xo+4VWZ+rlMiwbkzYk9+7di++//x5TpkzBnDlzYGX1prr169fHgwcPVD5z//59OP3vr6B+/fp48uQJCpSmAu7fvw9ra2vUqVMH9evXBwCVvYn83skGDRqgTp06KFeunEp5crkcjx8/FpQnRp3KAtrlvQoV6HQffkino/3ipv0i69KFTjdsGJ2Odtl4yxbg77/ptMHBdLpp0+h0tMvvv/5Kp4uNpdPFx9PpaJe7aPsvOlrccnXtAdRXp8n1kaF1UVH0+1YvXwZq19ZsvEskgKMjEBZGl9/Fi3Q6sfO7epWuHUuWcG6ptCGVanb3pExUFF25tNs6aPuFVuflRVe/cePE1dG2l2HZmKwhefHiRXz77beYNWsWxowZo3Ld29sbV65cQXp6uiLt+fPnuHr1Kvz8/AAAPj4+yM/PR7zSE/DkyZPw8vKCtbU1WrRoATs7O5w6dUqgOXHiBKpUqQI3NzfY2Nigbdu2Kk7DT58+jYKCAkV5YtWpLDhyhE6n6/AHD+0Shyb/gMrQGkGdO9PpNPmyVGb/fjpdYCDn/4+GDRvodEuW6D7cVLEi52uOBto2e3vrNtydnIC2beny8/QEHBy0axwcuP6zsdGus7Gh/7FQWEino530/+wzun6pV4+uvQ0a0Onq1aMr194euHVLu47n7l1gxQru38rGAf//5cs534269ob26sXNIHp4aNd5eHD50VC9Otcebdjbcz9YadpRoQIwZYr2/KZM4XyW0rTD3p6uXF3GK0+lSuL2n1RKVz8bG3F1tO1lWDiGPTxeOoqLi0n37t3J4MGDSVpamsorJyeHZGVlES8vLzJq1Cjy999/k6tXr5IRI0YQX19fkpubq8hr7NixxNfXl5w+fZrcuXOHLFy4kLi4uJAbN24oNJs3byaurq5kz549JDExkezevZu4uLiQ7du3KzRXrlwhjRs3JosWLSJ3794lsbGxxMfHh0ycOFGhEbNOJTGE+5/CQlX/YMovR0dOR4h2XUnE0oWHa9fwrwkT6HTh4YZphyHyZH4kuZe+fiRpx4y+Y8GU/Ujq22Z1fgEdHS3Dj6S6dpSFH0l15dJSFn4k1dVPbB3DMjFrP5IpKSlEJpNpfK1cuZIQQsj9+/dJcHAwcXNzI+7u7mTcuHHk0aNHgrxycnLIvHnzSJs2bYirqysZMGAAOX/+vEqZoaGhxN/fn7i4uJCOHTsKjEieuLg40qdPH+Lq6kratWtHvv/+e/Lq1SuBRsw68RjCkIyJoXsAxcS8+cywYcJrw4apz3vUKKFOg591MnKkUDdypP71++UX/duxerXw2urV6uu3ZYtQt2WL5v68du2NzzWJhPu/OhYuFOa5cKF63ZMnnGFRvjz3/uSJel18vDC/+Hj1uitXhLorV9TrMjII+fRT7mHx6afc/9Xxzz+EWFlxeVlZcf9Xx4sXhLi6ElK1Kvf+4oV6XUoKIe+/T0i5ctx7Sop6nbZ+Ls2Yjo0VXouNfbt+oW0vrU5XuaVpc2Eh9//wcO6d/7GoTF4eIePHE9KpE/eel6del51NSO/ehDRpwr1nZ6vX0ZKWRkjduoTY2nLvaWnqdbTtyM/nvicmTODe1bjq1asdtOXSInb/0dZPbB3D8qC1PSSEEGLsWVGGdvz9/QFwy99isXMnMGSIbl14ODB4sGjFUlNUBNStyy2FqxuhEgm3h+fePW6ZT5cuOZktw1g6tGPGksbCu9hmBoNRNtDaHia7R5JhWGhP2xnrVJ7Ye37YQ9TyoR0zljQW3sU2MxgM04IZku8otKf8jHkqr29fYN8+1Wg4tWtz6fwJa1odw/J5F8fCu9hmBoNhOrClbTPAEEvbAOdGpn9/7t8lRwFvXCo/hIqKOBcrT55wM5VeXmUz0yGXc5EWEhO5Zexx49Sf9jVW/YzJu9hmGt7FfrGUNltKOxgMc4fW9iin9SrDouFnMiZNEobDql2bWw4raURGRKjXrVhh2BkPdeUuW6a+XKmUPtyfJWCse2IOvGtjAbCMNrMxzWCYH2xG0gww1Iwkj64ZAH7mUnmkaJq5FAtjlWsOsL5hWBpsTDMYpgWt7cEMSTPA0IakNvhToSVnCEpiqFOhxirXHGB9w7A02JhmMEwPdmqbIQpxcZq/3AFu9uDRI/rwdKZerjnA+oZhabAxzWCYL8yQZGiFNvQhrc7UyzUHWN8wLA02phkM84UZkgytGMvfpKn7uTQmrG8YlgYb0wyG+cIMSYZWjOVv0hz8XBoL1jcMS4ONaQbDfGGGJEMrhoycUVQExMZy4RpjY7n/l0W55g7rG4alwcY0g2G+MEOSoRNDRM6IiOBOafr6cjG/fX25/0dEGLZcS4H1DcPSYGOawTBPmPsfM8CY7n9KIlbECX39xdFGtnkXETsKCG1+LPoIw1Cwv3cGwzRgfiQtCFMxJMVAl784gNsLxfuLY5Euyg7avmb3hGEo2NhiMEwH5keSYZLo8hcHvPEXx89cKutTU7n0ksvghkDbHk5Lg7avNelSUsrmnjA0Y+7j1dh/7wwGo3QwQ5JRpqSm0ukePeJmJtTNl/Npkycb7mFJs4fTUigqoutruVyzjtca8p4wNGPu45V2DLKxxWCYHsyQZJQpz57R6S5cMF6ki4gIoF8/9bNu/fqZz8OZFtqoImvX0s8mM8oOS5jJY5FtGAzzhRmSjDKlenU6He3OXbEjXRQVAcHB2jXBwZY1M0Lbh3fv0uloZ50Zb4+lzOSxyDYMhvnCDElGmaLs2kMTn3xCpxM70kVsLPDihXbNixeczlKg7UNNzqKVoZ11NgXMfV+hpczkscg2DIb5wgxJRpnCR7DQhqMj5/LDGJEuaA1ESzIkaaOKtG5Nlx/trLOxMfd9hYDlzOSxyDYMhvnCDElGmcJHsND2wFi+nPMbxyJdlA20UUUcHenyo511NiaWsK8QsJyZPBbZhsEwX5ghyShz+AgWyjOTjo5CZ+TGiHTh4yOuzlyg6Wva2WRTnzWylH2FgGXN5LHINgyGecIckpsBluSQvCSmGEWlqAhwcNC+T/KDD4D//rPM2RFdfc3P5AFCQ0xTVCJTJDaWW8bWRUyMefxgsIR7UhIWNYnBMA1obY9yZVEZhmljrC/unBxgzhzg4UOgTh0gKgqwt1dfv6tX34RMa9fu7QxObTqpFNi4kXPzo4mNG0vfP8YKaUiLVKrdeOJnjZSjj9Sq9XbRR8ryR4Wl7Cvk4e/JV18JT8xruiembqjpGoOMssXUxwvDBCAMk8fPz4/4+fkZJO/9+wmpXZsQbi6De9WuzaUbEicnYZn8y8lJqJs+nRCpVKiRSrn00rSDVjd9OiFWVrrL1Qex+9pY927/fkJq1RKWW6uW4dshVntjYtSPPeVXTEzp2mMMyroPGe8GbLy829DaHsyQNAMMZUju30+IRKL6AJVIuJehviw0GZHKxuT06dp1vFFH2w6xdfogdp7GunfGaoeY5RYWElKpkvaxVakSpzMHjDmuGZYLGy8MWtuD7ZE0AwyxR7KoiHN1oskHnUTCbXJPThZ3GSMzE6hSRbcuLY1bRtF24EEqBbKzAZlMdzvu3eOWxcXS6dMvYve1se6dsdoh9j2Ry4EKFYDiYs0aKyvg1SvOe4ApY6w+ZFg2xvqOYZgWtLYHO7X9jmIsR8bdu9PpWrXSfWq2qAiYPl2c8H766vTpF7H72lj3zljtEPuerF2r3YgEuOtr19LlZ0yM1YcMy8ZSHN0zygZmSL6jGOvAwcOHdDra6Ci0YfsSE8XV6dMvYve1se6dseon9j0ReywYE2P1IcOysbQDaQzDwgzJdxRjOTKuU4dORxsdhTaUopOTuDp9+kXsvjbWvTNW/cS+J2KPBWNirD5kWDaW4uieUTaY/B7JrVu3YunSpejYsSN++eUXRbqfnx9SS/q6KEGrVq0QFhaGrKwseHh4qNVMmjQJ48aNAwAQQrBx40bs3bsXT58+hYODAwYOHIjg4GDBZ06ePIk1a9bg7t27sLW1RYcOHTBr1ixUqlRJobl79y5+/vlnXL58GQDQsmVLzJo1C04lvsmzsrLw888/IyYmBtnZ2WjQoAG++uor+GpwbmfIPZKpqdwyhTKG2gPz8iXnh1EXT55w5dPukdTVDn6PmFi60uyRFCtPY907Y7VD7HsilwMVK+oeW3l55rNH0hjjmmG5GOs7hmFaUNsehj3zU3rS09PJ2LFjiaenJ2nevDmZPHmy4PqLFy9IWlqa4PXw4UPStm1bsm7dOkIIIampqUQmk5GoqCgVbW5uriKvVatWkaZNm5KIiAiSlJREDhw4QJo1a0Y2bNig0Jw7d440bNiQLFu2jNy9e5ecPXuWdOrUiQQFBSk0L1++JG3atCHBwcHk77//JtevXydffPEF+fTTT0lmZqZCFxAQQDp27Eji4uLIvXv3SEhICGnUqBG5dOmS2r4w9Klt5ZN5mk7l5ecT8ssvhEyYwL3n5+tfpj6uV/Q9ta2rHWLrDNnXtPmp65eyOLUtdjvK+p7Qji1zwJjjmmG5sPHCMHv3P2FhYSQgIIA8f/6c+Pr6qhiS6li6dCnp2LEjyf+fhXP79m0ik8nI5cuXNX4mLy+PuLm5kWXLlgnSly1bRpo3b05ev35NCOGMv4EDBwo0cXFxRCaTkb/++osQwhmkzZo1ExiNmZmZpFmzZmT9+vWEEEIuXrxIZDIZiYuLE+Q1cOBAMmrUKLV1NKQfyV691D9Ie/US6mj9OeoiPJzOkAwP169cdf7OHB3p/Oi9jU4fxM5TrHuiL2K3w1j3xFj9ZwiMOa4ZlgsbL+82Zm9IPnz4kBT+z5EbjSGZmJhIXFxcSGxsrCLt0qVLRCaTkZs3b2r83JkzZ9Qam7zBFx8fT16/fk0aNWqkmOnkkcvlxNXVlSxfvpwQwhmDgYGBKmUEBASQIUOGEEIICQkJIU2bNiUFBQUCzapVq0jjxo0VRnBJDGVI0s7K6Dt7U1jIzSiGh3PvJf3xlcYZNO1MaF4eIePHE9KpE/eel6dep61+pdHpgxizuoTo7+NNrHJ5xO4b2vxo2yF2fuaAMcc1w3Jh4+XdxewNyZLQGJJTpkwhn3/+uSAtNjaWyGQy8vDhQ42fCwsLIzKZjKSlpQnSnz59SmQyGdm+fbtiZjMyMlLl8506dSJfffUVIYSQVq1akblz56po5syZQ9q0aUMIIWTixImkc+fOKprDhw8TmUxG7t69q3LNEIZkfr7qbIzySyolJDubTsc/gHVFQqAtV98HujnMLokVJaKwUDUfZWPS0fHNF7459A0NLHoLg8FglB20todFxNp+8OABoqOjsXr1akF6Tk4OAGDHjh04d+4cnj17htq1a6Nfv34YMGAArKysFBpbW1vBZ/kDNDk5ORo1fBp/PTc3V62mUqVKyM7OVuSnSQNAoTM0a9fS+WkMCKDTrV3Lncju3597dJckNZVL37cPqFqVLr/4ePp4uzNmAEuWqM+HT1+8mC4v5c+LFWM2IkJ339DGqdbHx9vRo4bpm7KGtv/07WcWR5jBYDDeDotw/7Nt2zY4OjqqnHouKipCtWrVkJ+fj/nz52PDhg349NNP8d1332HFihVa8yTKT6K3gCYvMcujQWxfenfvApMmqT7AgTdpkycDDx7Q5ffoEZ1OLgdCQrRrQkI4nT5ERHCnFn19gSFDuPe6dbl0fSkqousbXQY2D63vtkePDNM3ZQ1t/8nl+vWzmPeYwWAw3lXM3pAkhOD333+Hn58fJBKJ4Npnn32Gs2fP4ttvv4WbmxuaNGmCSZMmoV+/fti8eTPy8vJgZ2cH4M3sJU9ubi4AoHLlyqhcubJaDZ/GX7ezs1N8Tlljb2+v0GjKhy+vLBDbl55EQjdLdvAgXX4XLtDpaGdW9YlSws9qKbeHn9XS19AQO0oEre+2CxfE7xtjYIjoLWLfYwaDwXhXMXtD8urVq3j27Bn8/PyoP9OwYUMUFBTgxYsXqF+/PgDgoVLIleTkZABAgwYNUKdOHZQrVw4PlKbT5HI5Hj9+rPARWb9+fRUNANy/f1+gefLkCQoKClQ01tbWqEPrsfstGTdO9xKeVAqEhdHpWremK1eNna0W2glasWdWxZ49BMSPEuHlxflwU/rdpEAiARwdxe9DYyF29JbUVPHvMYPBYLyrmL0hef78eUilUjRr1kzlWkREBBYsWKCSfv36dVSsWBEODg5o0aIF7OzscOrUKYHmxIkTqFKlCtzc3GBjY4O2bdsiJiZGoDl9+jQKCgoURqy3tzeuXLmC9PR0heb58+e4evWqQuPj44P8/HzEx8cL8jp58iS8vLxgbW1duo7QExsbYMoU7ZopU4BKleh0jo505cpkdDpjRawxRIxZsaNESKUAvzND2Zjk/798ufh9aCzEjt7y7BmLI8xgMBiiYeBDP6UmPT1d4Ty8ffv25Msvv1T8/9WrVwrdlClTiL+/v9o8YmJiiLOzM5kzZw65efMmSUxMJOvXrycNGzZUuOwhhJDNmzcTV1dXsmfPHpKYmEh2795NXFxcyPbt2xWaK1eukMaNG5NFixaR1r6DowAAIABJREFUu3fvktjYWOLj40MmTpyo0GRlZREvLy8yatQo8vfff5OrV6+SESNGEF9fX4ED9LFjxxJfX19y+vRpcufOHbJw4ULi4uJCbty4obYdhvQjSXuiV5eOP0mszUm2oyPnkkfMU9tinwLX188lDbR9o69bDV0+3gx1Qr6soe2//Hw63fbt4t9jBoPBsDTM3v3PsGHDiEwmU/vaX8KPx6hRo0jv3r015hMTE0MGDx5MPDw8SIsWLUjfvn3JgQMHSHFxsUAXGhpK/P39iYuLC+nYsaPAiOSJi4sjffr0Ia6urqRdu3bk+++/Fxi1hBBy//59EhwcTNzc3Ii7uzsZN24cefTokUCTk5ND5s2bR9q0aUNcXV3JgAEDyPnz5zW2wZCGJCH0vvR06fbv1/5g5m+b2FFFxMyvNH4uaTBUlAhdPt4sJYKLmNFbDHWPGQwGw5Iwe0OS8QZDG5JiQWtIEiK+b0Ox8jPU7CEhxosSQRu9yNQRK3qLIe8xg8FgWAq0toeEEEKMvbzO0A514HQDI5dzJ2MTE7n9aOPGcXstAe5gQt26mveeSSTcAZHk5DeHd169AqZP51wHffIJ59ewQgXVz9L6+tNWP33gT/QCnGlRsg2Aep+PYteRNj9dOk1+Ffn26OO/0hQQu18A+nssZv0YDAbD1KG2PQxu0jLeGlOYkdQ146fvcqGpRynRZ/ZQ7LaIpdMVAYdv07s68+bgoL5PHBxKlx+LqMNgMCwJtrRtQRjbkKTZZ6fPIRXaONH6xpM2Rvxnsdsipo7tBdSMk5P2PnFy0i8/fccqg8FgmDpsaduCMObStlwOVKyo3aeeVMqF4uvcWXd+J04AI0fqXgK/d49b+qVdKo+I4HwDltTXrs25yTHU0i3tcr6utgCc+yTaNtPqfvgBGD5cdzu2bweGDtWtsxQyM4EqVXTrMjKA/8UR0EpptnUwGAyGqUNre5i9H0mGYaGNHHP9Op2TbMByopSIFXEF0K/NtDra6EDPntHpLIXu3cXVGcL3qClQVATExgI7d3LvzEE7g8FQBzMkGVqhjRZy/z6dk+y0NHHL1RWlhBDVKCViPSBpI67cvSuujrZvaNcaqlen01kKSkGs3londuQiU4DFIWcwGLQwQ5KhFX0ix/Tty512rVVLeK127TenYMs6SgkgnA0S8wFJ2xZNs7Sl1dH2DW1kG+X7ZenQRiGl1YkducjYsDjkDAZDH9geSTPAHPZI5uUJXQFpcoHC7ydLTdXskqbkPkBdOn32AVaooN4VTmldvtC25fvvuX2huti6FZgzR7y+od2b+a7t3TPUHkld98Mc+pnt92QwGDxsjyRDFGhjcpf0hSiVAj4+wODB3HvJB07JONGaWL6cy49mqfzFC5pWAE+fal8CB1SXwHVBG/O6ROh1raSn0+VH2ze8TiJRr5NION27ZhDY2+ue1XVyojMiAfpxYA79bKn7PRkMhuFghiRDJ4sXc47DlR+EUimXvnixfvn17QtMm6Y+v2nT3swK0iyV0+7ve/nSMA9IMetYvTpdfrTl6qN71+Bna9Xh5MRd1wdL6WdL3O/JYDAMC1vaNgNMJbKNWJFoNEVb0bTErC2/2Fhun6Mu5swBFi7UrQsP52ZSadpB22baOsbEcDO4QNlHwDEUph7p5eVLwNsbePwY+Ogj4PRpoGrV0udn6u3VRWnGKoPBsExYZBsLwtgOyQkx3WgrtPmdOKGfc24xo5To22ZLiZBi6u0w9foZAxaHnMFg8NDaHmxpm6ET2lOcNDpde7AA/ZaYpdI3M4iaGDSImz2h8XPp5SX+qVWpFGjRQrumefM3jtUt4cSsqbfD1OtnLCxpvyeDwSgbmCHJ0EpREd0hFbmcTvfgAV25jx7R12/nTu2aXbu4d5oHJCD+oRy5HIiM1K6JjOS2DohdtjGgHTPGaoep18/YWMp+TwaDUTYwQ5Kh1UG3WNFbeN3Bg3R1oo3Kos8Mp6YHZK1abx6Qhji1ShsdaPp0yzgxa+onf029fqZA375ckIGYGG7fcEwM5/KHGZEMBkOZcsauAMO46IpRTXs6kzbaSm4unY72CFhpTpkq513y/4Y4tUrbN7SRbUz9xKypn/w19fqZCrwbLwaDwdAGm5F8h6HZJyZ2JBqZjE5HG5VFn6gifHtTU4XXHj/Wv736RCkROxKNqUdIMfVIL6ZePwaDwTAnmPsfM8AQ7n9oI1joG0VFl+72bcDOTr9IOTTteNsoL/q2Q5/IHnI55yapuFizxsoKyMnhDG19yjZFdzOmHunF1OvHYDAYpgCLbMPQCu0+sfh4caOtVKigf6QcbdCeMo2PF7e9+hgYUikXZlIbFSu+6UNNP+0IEZYtZtxwMTH1k7+mXj8Gg8EwJ5gh+Y6izz4xsaOo8JFyrJRGn5VV6SPl6CrXEO2lJS6Om23URk6Ofoc7TN19jamf/DX1+jEYDIa5wA7bvKPou0+sb1+gVy/dy6i0ujZtuGsl9yvWrMmllwZd5RqqvTTQGrGpqcCsWZqvSyScW5oePbS7r+F1vXoZd1ZNzD40BKZePwaDwTAHmCH5juLlxc2+6Non5uUlftmaQiTyh16UZ4RycoCAgDfhAsPCgEqVVPPVdsrUmO2lNWKfPRPX1VJcnP6nbsUOuWjqJ39p62eKe1EtFdbXDIaZYfAYO4y3xlAhEvfv1x62r2SoOGOFSPTwUK/x8DCN9tJA2+bt2+nCOE6YQKcLD9e/f8S4x5bGu9ZeY8L6msEwHViIRIZoGCtEYqtWQEKCek1CAnddH86fp7turBCJyvv1NEHrTkgf9zVi3mNLwpzaqy2wgDlgTn3NYDDewNz/mAGm4P5HLN333wMjR+qu38aNQHCwbl12tvplbmXkcu5ktC63Q9nZnAseXe3Q1/2PPmWL5WqJto5ijwVLcZtD2y+m0F5dgQVMHXPqawbjXYG5/2FoRezQh2KHSPzxRzpdQACdzphhCmnL3rBBXFdLtA9csceCOYUWFCM8qLHbawkzeebS1wwGQxVmSL6jiB36UOwQiZmZ4pZrzDCF+tRRbFdLNIg9FswltKAuP5zmEEqxqEj7CX6AO8Fv6svc5tDXDAZDPezU9juK2KEP9QmR+McfunW1agHp6eKVq0+Ywt9/160zRIhEXie2qyVdiD0WzCG0oCbPASkpbzwHmEMoRX1m8kz59Lw59DWDwVAP2yNpBhhyj6RY+/HEDpGYlgZ88IHudoi9RzIjA6hSRbwQjvqUrU+eYiL2WDD1fWy69uMBgKOjebR3505uNlUX4eHA4MGGr09pYWErGQzTg+2RZGiFNkwc7X48sUMkVq0KeHho13l40BmRAFc/mnIvXaLbzxgfT1euPmUbw4gExB8Lpv6gp/UcYIhwmWJjKTN5LGwlg2HGGNgN0VsTGhpKXFxcyOTJk1XSZTKZ2teTJ08UusePH5NJkyaRli1bkiZNmpDBgweTv/76S5BXfn4+WbRoEfHy8iIuLi6kS5cuZN++fSp12bNnD+natStxcXEhnp6eZNGiRUQulws0CQkJZMiQIaRp06akRYsWZNKkSeTp06cCDU2dSmIoP5KEqPfb5uhI5zvwbXTTpxMilQp1UimXXhIx/UjSlBsebhgfjfq02ViIfY9NFVp/ndu3c3pTbi/vo1QiUd8GiUTol9XUMeW+ZjDeNWhtD5Nd2s7IyMCsWbPwzz//IC8vD+3bt8cvv/yiuL569Wrs3LkTB9UcA/7ggw9gZWUFuVyOXr16oVKlSpg5cybs7OwQFhaGqKgoHD58GI6OjgCAr7/+GrGxsViwYAGcnJxw5swZ/PTTT1i2bBm6desGADh48CBmzZqFWbNmoX379khKSsK8efPQsWNHzJ8/HwCQlJSE3r17o0ePHhg+fDhyc3OxePFi5OXlISIiAtbW1tR1KokhlrZL8uoVd1r57l1uj+CSJdzMYWl1tJEpaPOjjWxDW65czp1A5vMbN+7NbGBsLHfoQhcxMcI9Z2KUbUhoyxU7so0psnw58H//p1v3yy/cQRXAtNvL7/cEhMvC/EyeucUON9bfCIPBEEJtexjcpC0lYWFhJCAggDx//pz4+vqqzEguWrSIdOrUSWseBw4cIDKZjCQmJirSCgsLibe3N5k7dy4hhJCUlBTi7OxMdu3aJfjslClTBPn7+/uTKVOmCDS7du0iDRs2VMw4zpo1i3h7e5OCggKFJikpichkMnLkyBHqOiljyBlJ2lkysWfTxI5gIVZ++kbeMURbxMbUZ0LLGn1nJM0BS5nJM/W/JQbjXcLsI9t4e3sjNDQUH2g4cZGdnY2KFStqzSMuLg5169ZF/fr1FWlSqRRt27bFn3/+CQA4e/YsCCHwUTrS6OXlhfv37+PRo0eKd3Wa4uJixP3PudmZM2fg5eWFcuXeHIavV68eateurSiPpk5lxYwZ3Cyg8p7AoiIufcYM/XS0iO33Tt/8tPkOpI1Cw89GmboPP7HvnSVAG0GIVmcK9O0L3L/PzZSHh3PvycnmNRNp6n9LDAZDPSZrSDo6OkKqZe0oJydHpyGZnJyM2rVrq6R//PHHePLkCV69eoXk5GSUL18eDg4OAk2dOnUAcMvVycnJijqVpGbNmrC2tkZSUhJyc3ORlpamdmn6448/RlJSEnWdygK5HAgJ0a4JCeGWlWl0cjlduWL7vdM3P12+A+VyIDJSe5mRkZzO1H340d5j2ntnKbRrp3tZWirldOaEVMpttxg8mHs3laV3Gkz9b4nBYGjGZA1JXWRnZyM7OxtTp06Fv78/fH19MW7cONy8eVOhyc3Nha2trcpnK/1vg112drZGg1RZA0AlL4lEAltbW+Tk5GjU8HllZ2dT16ksoI22EhBAp1u7lq5csSNY6JMfzYwHbb+sXWv60Tj0acu7RHy8+CfzGW+Hqf8tMRgMzZitIWltbY3Xr1+jdevWWLduHX744QdkZ2dj4MCBuHPnjtbPEorzRTQaWsq6PBrEjggjdtQTsXWpqXQzHrSRbRITTT8ah9j3zlIw9fv2LsLuCYNhvphtZJv169cL/i+TydCsWTP4+vpiw4YNWLZsGezs7JCrJiYfP3toZ2enU1O5cmWFkcen8RBCkJubi8qVK8POzk6thk+zt7dXlKmrTmWBPtFWrl8XLz+x/d7R6p49o5vxUPZhpwknJ9P34Sd21B9LwdTv2/+zd+bRUVRpG3+SJhHCKgjIEsCAIRD2RRYJkCA4LkMg4rgg6jAOSoBhGcLBZdw3GAH9EBTOCAiIuCQsDupoIGgQQREXFEQChCUEAkEwIZClud8fl0o6ne6qp9LV6e7k/s7JadP9eG/dqgr19nvfpSairolCEbgErEfSFXXr1kXr1q1x6tQpAEBERASOHDlSQZeZmYnWrVujTp06iIiIQFFREbKdvupmZmYCADp06FCaGOM81vHjx1FcXIwOHTogLCwMLVq0cDtf+ytPa+aYqoLERC5ObNUqTpeYyM1rdXxaTIzseOHOAAwKkl1KmjblxuvXj18vO3dMDDe31bDXmL121QXtuunhy+tWE/H3vyWFQuGegDQki4uL8eSTT+Ljjz8u935eXh4yMzPRrl07AMDQoUNx7NgxZGRklGqKioqQnp6O2CvFAmNiYhAcHIwtW7aUGys1NRUdO3ZEy5YtER4ejoiICKSlpZXTbN68GbVq1ULMlX/dhgwZgvT0dBQXF5dq9u7dixMnTiAuLo4+pqqA7bZSr561XVmsjk9jO2KwGbjh4fx6/b0bh7931PEVNptxu8C77w6sZJVAx9//lhQKhQ7erEHkCb///rvIyckROTk5YvDgwWLixImlv1+8eFFMnTpV9OrVS6xbt04cPXpUfP/99+LBBx8U3bp1E/v37xdCCFFcXCzi4+PF6NGjxTfffCP27t0rpk+fLvr06VOu+82zzz4rbrjhBvHJJ5+IjIwM8eabb4qOHTuKLVu2lGo++eQT0bFjR7F06VKRkZEhNm3aJPr06SNefvnlUs3Ro0dFz549xcyZM8W+ffvEzp07xciRI8Wdd94p7Ha7qWNyxJt1JOPjXdfQi48vr7OqFqG3OscY1dEz2wHEzHr9vYafqiNZnsrUClVUDf7+t6RQ1CQCvrPNuHHj8M0337j87KWXXsJtt92GJUuWYNOmTcjOzkajRo3QtWtXTJ8+HR06dCjVnjlzBi+99BK+/PJLFBUVoWfPnpg9ezaioqJKNSUlJVi4cCHWrVuHs2fP4rrrrkNiYiJuueWWcvNu3LgRS5YswZEjR3DNNddgzJgxSExMRHBwmWN3z549mDNnDn766SfUrl0bsbGxmD17Nq6++mpTx+SItzrbaFnMzneAu44YbMcJvU40lekcY1XXGHfr1dbsvN7z54HbbgOOHgXatAE2bQKuhLpWwOpuPizsNWHn9VVXEas7A+mN5817UOE5qrONQuEfBHxnG0UZ3vBIessrY9Qbu7CwonfM+cdmkzoh+E4XrI71zrGeWjNYPSa7FqvPjdVYfXxG45n1iqtuK1WHOtcKhf/A2h7KkAwAvGFIpqVxD9O0NH5Md0akozFpZt7kZNdb0UFB8kd7uFitc2fweWL4WT1mUpL+eJpxxa6ZHc9qrD4+Zjxv3IMKz1HnWqHwLwJ+a1tRhje2tletAu6/31i3cqXcpjYiPx9gKhctWwaMH2+sW70amD3bfcmeoCCZ5ZmRIbe/rNLt3cuto6CA35K+eBEwaMJkasyiIjmeXtKSzQbk5QGRkcZr3r9frtlovIICa7cY7XbZVciq42PXy17jvDygUyfj8Q4fVtvcnsLeC+pcKxRVB2t7BGTWtsJzdu60VscYmwDw1lucjq37uHixtTp2HUlJnM6MltWxHWuSkrg1JyX5pgMO282EPT52vbNnc8en90XGcTzVbcVzVGcbhSJwUYZkDYX1Q7M6tjvK+fPW1n30VYcetgOOGa2Zrjr+PC8L26XE6nVYrVPdVjxHdbZRKAIXZUjWUK6/3lod2x2lQwdr6z5a3b2F1bHnxYzW6nPtq3lZ2C4lVq/Dap3qtuI5qrONQhG4qBjJAMAbMZJsnB0bF8fGSOblyVJAKSnAP/4he2BrtG4tjcyEhLKYqaws115R59hHq3SBECPJjqfF+Bmt2dcxklYdnxYjWdXj+UvcXiCXKGLvBX851wpFTUDFSCp0sbrrSb16QN+++pq+fcvqSQL6fa3ZThehodbq6tUD4uP11xEfb672Y5061o7Jxq3u2sWtuU4d33TAYa8xe3x16vhmPH8wbFJSpCEWGwvce698bddOvh8IqM42CkUA4+XscYUFeKuzTXKyfvkTs+U22PHMlPlgO114onNVp86f60haUQfR1bnxpzqSnhyfr8bzFdWpbI6/n2uFoiahyv9UI7yxtW11uQ12PKMyPIBMtnGcl92yY3SuttRbtQL+7//Kd7UBrO9CY9WYvuwO5C2qsrONRkoKMGUKcOJE2XstWwILF1a8F/x127g6ls3x13OtUNQ0WNujVlUcjML/MFNuQzNGrBjPqAwPUHFem407BiPctUg8cUK+79wi0WaTyUFBQdJo0XuYsQZOaKicS3tIVsZIi4mRxoFRPFlMTPm1MOcwNBSYNs1YZ/XD3urjMxrP3b2Qne3+XrDiHrQaq/+O/QF/PdcKhcI1KkayhmJ1uQ2rS7k4egwZjGLE7HZg6lTXhpe2iTZtWlkCxqxZMqFl+nTg9dfla1iYfN8ZVmtVHJsWT+ZuL0EI78aTBXo8ntG9AJS/F/wZVTZHoVD4GuWRrKFYXW6D1ekl2Dhy+jSnA9x7l7KyyrxLjRvzntCPP5Zbzs7Y7WXvz50rX2fN4rTMMTpvp1qJVR5Eb62jKrczq5MXT5XNUSgUvkZ5JGso2vaoUWFwx+1RPfr143S9e3M6x4LkdruMC3z3Xfnq6ClivUvHjnHzHjkCzJ+vr5k/X25lFxVx2osXrfWAaWt2R1BQ+fGs8iB6y5NX1R7O6uTFs/rvWKFQKMyiDMkaitXlNpYs4XTffcfptILkRkYG611iS+asX8+3C7S6VSHb/s2MR03zIDrrNQ+iGWPNG23srDw+R/S+fFQnL54qm6NQKHyNMiRrMAkJcivSuYtM69bmtyjZ9nlCyPH10DwojJHBeo3Y2gQXLnC6gwetb1VotacsK8taD6LVx+crD2d18+JZ+XesUCgUZlGGZA0nIQHIzJSlYtaska+HD5t/+Jhp2/faa/oP8Vdflf/NGBnNmvHzMkRGcrr27a1vVejoAbPCo3b6tLUeRKs9eb7ycFZHL55Vf8cKhUJhGq9XtFR4jLcKkltJQQFXJLugQOqNCg+npXHjpaZWHMf5JzxciMJCTldQULFItfOPzSbHKywUIjhYXxscLMds3dp10WitcHR4uBAlJe7PjWPR9JISbrzVq7lzqBUuN4KdV1uHEWYLq7PH524c5jyr4tcKhUIhYW0P5ZFU0Oh5ydgYRE1n5EFht0dzcoB77tHX3H13WYtEI0+omXaBNptxz+u6dfn2jDabtR41561Od7AeRKs9eb72cCYkyPCEBQuAyZPla0aG8uIpFAqFKarAqFV4iD94JI28ZFZ7l6z2SJr1QjHt89hjTEvj5rbao2a1B1HvXqiMJ8/XHk62XaZCoVDURFjbQ9WRVBjW8HNXO/D48bLagZXxLum1C2S7t2jHoYdjTcCEBOD224270MydCzzzjH47Q7PJJwkJwIgRwLhxZXOvWgXUqyc/N1vf0GgtmgdxzBh5vhzPozsPItPCMSEBuOUWz1s9Vub49O5VM/egr+t6egPVWlChUPiEKjBqFR7iTY8kG49n5PFjYxA171J8vGtNfHz5Y9MbLznZe14oRmfWI2m05qpciysPInNNhOC8tWZgj8+q2FGje7WynlpforyrCoXCaljbQxmSAYC3DMnkZNcP3aAg+ZOcbM5Y6ttXX9O3r5zXncHibLgkJenrkpLMHR+zXva8CCENjSZN9Odt0kTqmDV7Yy0aJSXy/1uzRr46G0lWXpPKYHR8Zq+ds7ay93QgYPZeUCgUCgZlSFYjvGFIsvF4K1dyD91lyzhdbi6nO3eOy57OyeHnZdZrxlvFGpJ5edwx5uX5xqPGZtyz16Sw0NJb1fLYUavjeX2J2XOjUCgULCprW6GL1R1h3nqL0w0Zwuluu43rGhMXx403ciS33sWL+TjF9HQgN1d/3txcGRPJMHs2lxW9fbu19ReTkjgde00WL+bGY6lMNrZeRYDq1NnGG7U4FQqFwgzKkKyhWN0R5vx5TnfiBKc7etQ347HdarKz+XNopgMO06XE6g4zbOcdq88hS2XWa7PJhKR77pGvjkkn1amzTXXqG65QKAITZUjWUNiOMBERnK5DB07XsiWna9PGN+Ox3WpatOA9VmY74FS1R43tvGP1OWSxer3VqbNNdfKuKhSKwCRICNbnpPAVw4YNAwBs3rzZsjE/+wy4+WZj3ccfAxMm6G+fhYcDe/cC9esbj5ebCzRpYqw7d07q9LZSbTbpaWGM4pwc+TA1Gu/cOaBRI2NdQYF8bdfOuEQRe24KCrgSOnY7N+/hw5wxdPGicWF1gL8mBQUVyyl5gtXr1UhJkW04He/t8HBpRAZK6R9vnRuFQqFgbQ/lkayhsDFT27eXdYRx5b3ROsLUqwfEx+uPFR8PNG7M6Ro25DrM/PKL8RoA4J13uPi+//yH023fznu22HPD1mG02qNWp46118RKIxLwngexOvSnrk7eVYVCEaB4Pe1H4THeyNp+4gkuc/WJJ6Te6lqEVtUsZDNwExOt1Tlm9Fp9blis7hXtqzqSLKo3tnvUuVEoFFbD2h5qazsA8MbW9ubNwE03GetSU4Er06OoyLgjDADk57vv3uII00XFaN6tW4HYWON1TJoELFpknS4tTSZxaLBdRdg1s+Ox14TF6mtnNVZ3b7H6/FmNmfWqzjYKhcJKaNvD6yathyxfvlxER0eLadOmVfjsu+++E3/961/FDTfcIPr37y/+/ve/i3379pV+fv78eREZGenyZ9GiRaW6y5cvizfffFMMGzZMREdHi7i4OLFkyZIK86WmporRo0eLLl26iH79+onHH39c5OXlldP89ttv4m9/+5vo0aOH6NGjh3jooYdERkZGOc358+fFY489JgYMGCC6dOkiRo0aJbZs2eL2HHirjiRbTFsIazvCWL0OpqMOWw9z5UpzHXq8ga/Otb9eY2/hK88qS3U5zwqFIjAJ+ILkv//+u3j44YfFoEGDRK9evSoYkj/++KOIjo4Wjz32mMjIyBB79uwR48aNE/369RNnzpwRQgiRlZUlIiMjxaZNm0ROTk65nwsXLpSOtXDhQtGtWzeRkpIiDh06JNatWye6d+9ezpj8+uuvRVRUlJg3b544cOCA+Oqrr8SIESPE3/72t1LN2bNnRf/+/cWECRPEjz/+KPbs2SMeeeQRceONN4rz58+X6saNGyeGDx8u0tPTRUZGhpg/f77o1KmT2LVrl8tz4a3ONmw3E6s7wpjFqOuJ1R1w2PPiDXx1rn19jasab3XosYrqcp4VCkXgEvCG5KpVq8S4cePEmTNnRGxsbAVDcurUqWLYsGHCbreXvpeZmSkiIyPF+++/L4QQYv/+/SIyMlJ89913bucpKCgQPXr0EPPmzSv3/rx580SvXr3EpUuXhBDS+LvrrrvKadLT00VkZKTYvXu3EEIapN27dy9nNJ4/f150795dvPnmm0IIIb755hsRGRkp0tPTy4111113ifHjx7s8Rm8YkoWFXJeSggLrO8KYoap7gRcU+KZ7C7MWb51rX83rK9h73xvXmEF1q1EoFP5AwHe2GTJkCJYvX44mbmrFvPjii3jvvfcQHFy2hGZX6sDkXmk3kpeXBwAI06ltsnv3bhQUFGCoY8AbgJiYGOTn52P37t0oLCzErl27Kmj69euH0NBQfPnllwCAbdu2oVevXmjQoEGppkGWrKwxAAAgAElEQVSDBujWrVs5Te3atdG/f/9yYw0aNAg7duxAUVGR22O1ksWLuezkpCTrO8KwpKQAY8ZUHDcrS76fkmLc2QOQ87LZ50uW+KZ7C8B3KbH6XPtqXl/B3vveuMYMqluNQqEIJPzWkAwPD4dNJ1I8LCysgpGZmpoKAOjevTsAID8/HwBQt25dt+McPny4dD5H2lypvnzo0CEcOXIEdru9giYkJAQtW7bEoUOHSsdq3bp1hTnatm1bTtOiRQvUqlWrgqakpARH2fYhHmKm24qV47EdNux2WeNPiIqfae9NmyaNSnZepmsMuw6ru7dox2jl3FZ3PbF6Xl/hy2vMoLrVKBSKQKKWsSQwOHbsGJ5//nkMGjQIAwYMAFBmSL7zzjv4+uuvcfr0abRu3Rp33HEH7rzzTgQHB7s1NutdSVXNz8/XNUjr1q1b+vmFCxdcaurVq1fqHc3Pz3erAcq8qN7GTLeVzz6zbjzHDht6WaasV+b0aXPzJiTImoju5mXX4ayzImPW6k45Vnc9sXpeX1HZa1xVqG41CoUikPBbj6QZMjIycO+996JZs2aYN29e6ft2ux3XXHMNCgsL8cwzz2DJkiW48cYb8fTTT+M1rYqvG4QrV1glYcaycj6GxERjQ8dmk2VdmL7EDz/MjTdwoPzvlBTZkSM2Frj3Xvnarp18H+C9LU2bmu+brNeH+eGHuXkddUZrYWF7QCcmWtsr2lfz+gr23k9MrJrjcaY69QJXKBTVn4A3JHfv3o17770X4eHhWL16NRo1alT62ciRI/HVV1/hqaeeQo8ePdC1a1dMnToVd9xxB9566y0UFBSg/pXedZpXUePChQsAZIyjFvPorNHe0z6vX79+6f/nrGnYsGGpxt042nxVQWgo16WkTh2uc8bOnXxHGCb2kfW2tGplbWePnTvN6Zi1sLBdSkJDza/Zbpc1N999V746XitvzuuPhIYCt9+ur7n9dt/Vk1TdahQKRSAR0Ibk3r178dBDD+GGG27AihUrSo01I6KiolBcXIzc3FxEREQAQIXYRC12skOHDmjTpg1q1aqFI0eOlNMUFRXhxIkTaH9lDywiIqKCBgAyMzPLabKzs1FcXFxBExISUhqbWRXMnSuTaZwfSDabfH/uXPk7E1vIehCzsrjYx4EDea8Mc3wsLi6fWx0bx2lkYDvCrsXMmhmPqTfm9VfsduC77/Q1u3ebu25WUx3Os0KhqBkErCF59uxZTJgwAQMHDsRrr72GUBfug5SUFDz77LMV3t+zZw/CwsLQvHlz9O7dG/Xr18eWLVvKaVJTU9GoUSP06NEDoaGhGDBgANLS0sppvvjiCxQXFyMuLg6AzDT//vvv8fvvv5dqzpw5gx9++KFUM3ToUBQWFmL79u3lxtq8eTNiYmIQEhJSuRNSSebOBQoKgAULgMmT5WtBQZkRqWHUl5j1IJ4+zcU+alnWAOeVsapv8vr1vM5b2bXsWhidGY+plfP6M2ymv6+zogP9PCsUipqB3ybbnDt3rtRrZ7fbUVhYiNNXMivq16+P//u//8OlS5cwc+ZMnD17ttz/GxISgkaNGqFx48ZYs2YNiouLMXbsWISGhuLzzz/Hxo0b8cgjj5Qan4mJiViwYAGuu+469O7dG7t27cLatWvx6KOPlhp2kydPxtixYzFnzhzccccdyMrKwosvvoibb74ZnTt3BgDcc889WL16NWbOnImpU6dCCIEFCxagWbNm+Mtf/gJAZpTHxsbimWeewdNPP40WLVrg/fffx8GDB/Hiiy9WybmtLHY78MMPZe3kBg4sM+S0uK6sLNceuqAg+XnTptxc2dkyhvHDD4F//KN8dra2ne38QNU7Pmedu8QYF5EJLrlwoXLZtefPA7fdBhw9CrRpA2zaBLhypGtxnJ5g5DENCpIe0/h489uk7PGxSUhW6/QIpKxoK+6DQEO1elQoAgwv17OsNPfdd5/b9obJyckiNjbW7ef33Xdf6ThpaWninnvuEX379hW9e/cWCQkJYt26deLy5cvl5lu+fHlpi8Thw4eL1atXVzim9PT00haJAwcOFM8995y4ePFiOU1mZqaYMGGC6NGjh+jZs6dITEwUx44dK6fJz88XTz75pOjfv7/o0qWLuPPOO8WOHTvcngtvdbYRgm8Tx+iSk/WLPCcnm+swo80bHFz+s+Dgyh2fdox6Bc4nTeKOb9Ik82tp39715+3bV+7aGa3F7PH5e8tFq47P7HlRVB2qLaRC4T8EfGcbRRneMiTZNnFW6kpKhAgJ0deFhkqd1cfHtJ0rKOCMjIKCsg4krsbUxtU6kLgzIitrTDJrWbOGW8uaNf7fctGdTtM6H59eW00z101Rdai2kAqFf6EMyWqEL1sk5uVZq8vN5Yyb3Fxr52VbPbKGpNY+T3v4OT8AHR9+585xY547x107toVeaio3b2qqf7ZcBMzptONjvFrMdVNUHaotpELhfwR8i0SFd2HbxI0bZ61uyBDu+IYMsXZettVjUhJ3fFr7PC271jnZqGXLsuza227jxmR1bJIPwGW+A/7ZchEwp0tP55OLVFa0f6HaQioUgYsyJGsoVreJY3UnTlirs7rVY2VaQu7YAZw6Vf7zkyfl+4BMrGFgdWwSSE6OTEoSwvXnQsjM95wca+dldey53r+f0x07Zq4ck8qK9h8CKQFKoVCUxxJD8vjx41iyZAmmTJmCu+++G99++23pZzu0p6nCr7C6TRyra9nSWp2ZVo9W6rR5Z82S3X+cvaJ2u3x/1iyZnc3A6qxuoecrnTtPqTMnT3K6nTvNe7X0uhwpqg7VFlKhCGA83UN/++23RdeuXUVUVJTo2LGjiIqKEqmpqUIIIc6dOyc6deokpk2bViFLWsETCDGSbBxgTo61unPnzMVIGiVYFBRw4xUW8ufQzFoY2GQRo9hCZ51VySfs8a1cyZ2XiRM5XWIip1uzpvJ/NwrvoBKgFAr/o0piJNPT0/Hiiy/iqquuwsMPP4znn38eQohymsGDB+PTTz/Fe++955HBq7AWtk1cvXpcK8Xvv+fm/eUXYy9i+/ZSx/D99+ZbPbrj1Veljm2fx8aZvvOO61qRjjRsaKzR0FroOf2plSKEXMv27d4p/s4en9F4WnymEZGRnI71JvuDV0uvZWVNRLWFVCgCF48Mybfffhv16tXDhg0bMG3aNAwYMKDc5w0bNsTrr7+ONm3aYD3bMkRRJZhpE8e0UjTTIrGwUF9TVFS+ALke2dnmWj3OnOlaN3Om/NzMeWHjM3/7DXDRXr0c+fly3VZiJu7M6uQTZjytiL0e4eFAYqI5HdNW05cwLStrIioBSqEITDwyJH/++WfceuutaKkT0FarVi0MGzYMB9jIekWVYLZNnFErRataJGrzXmliZIg2L9PqMSUFeOWVit6fy5fl+ykp5s4LG5+Znc15LrVMcCO0jjXu0DrWNGvGjaedQzPJJ0VF0kM0ZYp8dWUEG42neaH0DL9XX5XeX03nylvlrNPed9YBFb1aVe0ZNNOysiaiEqAUigDEk/3z6OhosWjRotLfjx8/Ljp27FgaI6nxxhtviC5dungyVY3GGzGSq1dz8WQuGvy4xKgOHCBjnMzMa6Z2oKfHZzZub/VqPkby4Yf5GD8GtjOLVh/S6rgztosQi6u6j+HhXGcbq3Xe7KKiaiUqFIpAokpiJJs2bYr9RG2OX375Bddcc40nUykshvX4sTqbTWa+6nH33RW3rdzRqpWxl/Paa/mYKbZO3c6d3HinT/NxprXIjvZsFrPZ8j+uxq5s3BmTpW4W1gtlpc4XnkFVK1GhUFRHPDIk+/fvj9TUVHz99dduNe+++y5SU1MrxE8qfEvTptbq7Ha5PajH2rVAnz7ceN26AQ5VpFzy7bfAxYvceKzxdfkyp2vShI+n7NmTG7N3b05nplSKlXFnRUXA/Pn6mvnzKxfryZbhsUKnhQa4SlbS3nOsN2kVqlaiQqGojpC+Etc8/PDD+PTTT/HQQw8hLi6uNFYyNTUVu3btwtdff439+/ejTp06mDBhgiUHrLAGM55BBja2cPZsbryRIzldUhLw+uvyv+12eRzZ2dKIiokpMyBY4yuY/GqVm8uv+b//5cb87jvgr3811mlJKllZro2hoCD5uZZUkpAAxMe7PzcsbJb64sXSEPNXzHgGhw61bl5VK1GhUFRHPDIk27Vrh2XLlmHmzJn4/PPPS99fv359aRmgli1bYu7cuWjXrp1HB6qwFs0Y0XugmslwtbqbCdvlRRsvJUV6mRzX07q13Np1zBA2Mr769QMWLTKet2lTfs0XLnA6d+V8nNGSVMaMkcft+P+527LWPHSeYHWXI1/hK8+g2S8ACoVCEQh4ZEgCQM+ePfHZZ59h27Zt+OGHH5Cbm4ugoCA0bdoU3bt3x8CBA2FTxb/8DkdjBOCMET3YDOGICE7Xpk1Zv2g9rr++LN7N+eGsxbtpW7iO63XFq68CjRtzx8d6agFZB9Hhe5Zb2DqIQNmWtSvj+dVXvZPlanWXI1/hK89gZb4AKBQKhb8TJATrB1H4imHDhgEANm/ebPnYrjx54eGujZGiIrltefCgNBYSE2XCiTw24KabjOf7+GOZgKIXixgcDJw9CzRqZDxeXh7QqZN7z6rm5Tl8WD6gZ82ScXyOW7Q2myxaPneufL9dO2NP7eHD8r/btTP2MO3fD9Svr78tbLPJckXa+dTbpneE1VlBUREQFmZuHf6Ido2Nrpt2z1iNmb85hUKh8BWs7WFJr21F4MJmws6aJY2I6dNlTOL06fJ3LUs3J4eb7+xZYyMjNFR2mAkJ0deFhJjrr8zUkWRrG9psfDeOOnW47jvaeTFTsLoqe0WHhppbh7/i6y4qqlaiQqGoTni8tb1x40Z88sknOHr0KAoLCyu0SNQICgpCamqqp9MpvIBR/JxW8sUZreQLANx6KzfXyZPApUv6mkuX5IO+uFhfV1wMbNnCzZuVJRN93GXqakW84+Pdbxu78hqxW8xaYXQ9byjAb9P7CnYd/o4vQgMcsSJmVaFQKPwBj7a2ly5digULFrg1Hp359ddfKztVjcabW9uALKGTlCQTV66/XhqHderIz9jtzLw8GQtotF14zz2csTFwoOwBbcS990qvjhGvvCLbIBqRllb2gDezbcxq9c610ba6t7dczaC3jkCiKkMDAg11bhSKmg1re3jkkdywYQPCwsLwwgsvYNCgQahXr54nwyl8wKhRwIYNZb9/9pnMWo6PB9av50u+LFkivYh33OFaI4T09LzxBndcJ05wOraI99mznM4xU9eM14jROsfGffaZPPdaZrmvytKYxWgdgYTyDLrGqAqCQqFQaHgUI5mVlYUxY8bgT3/6kzIiAxBnI9KRDRvk52ZKvqxcqa9ZuRKoW5cbj82YbduW07H1Ib1Vw4/ppBIIBatVr+jqj7rGCoXCDB4Zks2aNUPt2rWtOhZFFXLxonsjUmPDBr6sT9Om3Hh9+3LjjRjB6bp04XQ9expvy9lsckvdathOKuy59lXBal91hFFUHeoaKxQKs3hkSMbHx+Pzzz9HYWGhVcejqCKSkjjd2rXW6nbs4HQffMDp/v53Tvfkk9wWPROXaRZ2yxqQ24d6GeNmisRbjeoVXf1R11ihUJjFoxjJiRMn4tSpU7j77rsxfvx4dOjQAQ0bNnSr11ooKnwP22Hm5ElOd+oUpztyxNp5re617Y1tY3bMnBz/LlgdCFvvCs9Q11ihUJjFI0Py0qVLKC4uxoEDBzBLKyjohqCgIOzdu9eT6RQWcv31MknCiJYtuUQVVte+PbBnj7GuQQNuPJtNv7i52fEct42tylo100ll6FDXZWlatfJ9ooPqFV39UddYoVCYxSND8rnnnsP69eths9nQqVMn1GUzKRQ+5+WXuZ7Sn3/OPTS2bOFi/Fatkp1ojMoEzZ4NPPKI8XhjxgDvvmuse+wx4Nln+T7HVmatVqbHsrPOH/pPqV7R1R91jRUKhVk8MiS/+OILtG3bFqtXr8Y111xj1TEpqoCdOzndqlWc7vvvgdq19YuN16kjf5jt28xMbl6mjSIgPbDstnFlioLreS/N9Fh2N/eJE74vSK56RVd/1DVWKBRm8SjZ5uLFi7jllluUERmAbN3K6YwysTVWrTLuWHPxojS2tK4irVqV/7x16zJDKTeXm7dRI/n/6aElqDDzViZrlWlp6K25qxpmHYrARl1jhUJhBo88kh06dMC5c+esOhZFAJOfz+m0IP2EBGDYMOC224CjR4E2bYBNmwAtV4ut++joQXG3FefoQUlIAG65xX1XFrNFwc14LxMSgNtvl0XeDx6U8aKJiWW9qStTkJyN47SyS0lCgixYr7qeVF/UNVYoFDTCA7Zu3SpuuOEG8euvv3oyjMKAuLg4ERcXZ+mYqalCSNNE/2fuXE73yiucLi1Nzt+3r+vP+/Y1d3ypqVIfH+/68/j48utOShLCZiuvsdnk+0IIsWYNN++aNUKUlAjRurV7TVCQEOHhUieEEMnJFfWtW8v3zc7NjKfB6hQKhUKh0GBtD496bW/evBnffPMN1q5di9jYWERGRuqW/xk7dmxlp6rReKPXtt0ONG+uv4XcpImMzWvYUH/bunZt4Px5mbltNN6pU8CAAcC337rX9e0LfP01d3ynTgGPPiq9iu5ISpL9vWfNMtbdeqvcmjYiLU2+stqzZ117LrW4sw8/BBo3tna8hAT3HlNnnUKhUCgUjrC2h0eGZFRUFIKCgqANEeSmkrIQAkFBQdi3b5/pOVasWIFXXnkFw4cPx4IFC8p9tmvXLixYsAA///wzQkJCMGjQIDz66KNo3rx5qSY7Oxtz5szBV199hcLCQnTp0gVJSUno2bNnqaaoqAgLFizApk2bcPbsWYSHh+Ohhx7CHU6Noz/44AMsX74cR48exdVXX43bb78dM2bMQEhIiOXH5Ig3DElAGhnuemMDQHKy3IqtXVs/azgoCLhwQcYiGhl+Bw9yCTJ5ebI8EXN8YWH6cYM2G3DunJzXSJeTI4+TOb6PPpIxkUasXi2z0N1tW2uZsPv3A/XrGx9jXh4QGWk8XkaG3D430h0+rLYsrcLKEAKFQqHwJazt4VGyzahRozBq1CiMHj0ao0ePLv3d+Uf7zAznzp3DI488grfeegtXXXVVhc8PHTqE8ePHo23btnjvvfewZMkSZGdn46GHHkJxcTEAaSCOHz8eWVlZeOONN/DBBx8gIiIC48ePxzGtlQiAp556CuvXr8e//vUvbNy4Effccw+eeOIJfPzxx6Ua7fO//OUv2LhxI5566ils2LABzz//vFeOqSpISJDGmPPpveoq+X5CArBwoXHpGSGAGTOME2Ryc2VMJMO4cZxu8WKuY824cZxu5Ehu3tmz+Vp6p09zsY9LlnDHuGQJN97ixea7lOzZI+NTg4Lkq7uan1u2SI32s2WLa11GhowBDQqSrxkZrnVHj0oj2maTr0ePutb98EP5eX/4wTPdO++U173zjmvd2bNA167yS0bXrq5rkqakSK+8Y9JVy5aue1OfPg1cdx1Qr558PX3a9bz5+cDo0UC3bvJVLxaZPYdFRTJueMoU+VpU5NncFy8CkycDN98sX901CWDnZdfBws7LYrfLZMV335Wv7v5mzVw7K+f1lU5RdfjdNfHqBrsHrFq1SowbN06cOXNGxMbGimnTppX7fPbs2WLIkCGiuLi49L1Dhw6JyMhI8dFHHwkhhFi3bp2IjIwUBw8eLNWUlJSIIUOGiH/9619CCCGOHz8uOnbsKNauXVtu/BkzZogRI0aU/j5s2DAxY8aMcpq1a9eKqKgocfLkSUuPyRlvxEhq6MXiCSHEqFFc3F7v3pxOL6bQ8adLF2NteLgQiYn8eFYe34gRxjGS2jGuXs2NOXmyb3RazKXRvcDeMxpBQa41QUHldbVqudbVqlW5ea3WNW/uWtO8eZkmOVl/PMd41IYNXWsaNiw/r1EccWXOoVGMsNm5rYpNNrsOFnZeFjbe2My1s3JeX+kUVUdVXhPW9vDII+lNhgwZguXLl6OJm33Gbdu2ISYmBrVqlSWeX3fddWjdujW+/PJLAEB6ejratWuHiIiIUo3NZsOAAQNKNV999RWEEBiqpcFeISYmBpmZmTh27FjpqyvN5cuXkX7FpWPVMVUV7no6O35erx43lhCcjq372LChvjcNkN40ozWYpRZZx+D666XH5MQJfV1WVsUyKu5o3943uhYtuHvB8dVIFxzs/p4QoiwrPyQEKClxrSspkZ+bmddq3bXXum//eeqU/Nxu1w/BAOTndru8/8+fd605f77s7+OGG9zHEX/7rfxcgz2HWoyws/fCbpfva83J2LlHjXJfHmzDBvm5mXnZdbCw87Jo8cbO/y5pFRo0z7OZa2flvL7SKaoOf70mlhiSH3/8MRITEzF06FB0794dPXr0QFxcHKZOnYpt27ZVaszw8HDY3AQXXbhwATk5OQgPD6/wWdu2bXHo0CEAwOHDh9HaRZHBtm3bIjs7GxcvXsThw4dx1VVXlYthBIA2bdoAkNvVhw8fLj0mR1q0aIGQkBAcOnTI0mOqCj7/nNMZ1YbUuLJzbwgTfwjwBuJ333E61vXfuDGni4+XW25G7RkvXwbWrePG/PFHTseea3cGizP793O6JUs43fLlxl8shJDb4e4MB42SEmDjRm5etnj+Cy9wuiVLjHvInzoFvP02N96KFcbX5Px5GbOql4wGyM/z8+U9yJzDjAxg/nx93fz5csuemfv0aeMasxs2yPUw82ZkcOtgt7mLirh52W1utsbr+fP8tbNy3qIi3+h8vqVag/DnOsMeGZJ2ux2TJ0/GP//5T2zZsgUnT55EYWEhLl26hBMnTuB///sf/v73v+OZZ56x6ngBAPlX/gpdtWSsV68e8vLyAEiD050GAPLy8pCfn4+wsDBDjav5goKCULduXeTn51t6TFXBiBGc7sMPOR3TPxsAvviC07HfP3bs4HRsntfu3ZxuxAggOprT/t//cboVKzgd60l5+mlOx7SiNKMbP57TXYnjNiQ+ntPdfz+ne+IJTseu929/43QPPcTpOnfmdOPG8fdg585c/O2QIdx4rFftttu4edk1s+tlY6cXL+bGY2u8Wh0Dzs7LxkNbrXOMr1Z4FzN1hqsajwqSv/vuu0hNTUXnzp3x4IMPolu3bmjcuDEuX76Ms2fPYvfu3Vi2bBnWrl2L3r174/bbb7fquN0iiD1WqzQsVT2fomooKPD1ESiqI4WFnO7gQf4eZL3YRqEaGu6Sg5xhPYjs8bHrPXjQWp3WSMEIdr1Wz2v1eq0+PoXnsOfaF9fEI0Ny48aNiIiIwNq1axGqtee4QqNGjRAREYE//elPiI+Px3vvvWeZIVm/fn0AZZ5JR/Lz80trWdavXx8XLlxwqdE+N9I0aNCg1Mhznk8IgQsXLqBBgwaWHpMiMAgL8zwTUxH4OPek9pSrruJCStq3l92ZGK3Nxm15tWzpOiPdmaZNZckvI9q0kV4SI0JCOGPSxeaRSyoTR6xXuomt0MCu10z8MoMv46sVVQN7rn1xTTza2j506BBiYmIqGJGO1KtXD7Gxsfj11189maocYWFhaNGiBY4cOVLhs8zMTLS/8lcQERHhVtO6dWvUqVMHERERKCoqQraTGZ+ZmQlAtoHUEmOcxzp+/DiKi4vRoUMHS4+pKpg3j9O5KW1ZATahhN3CYmMpr4SyGjJ4MKfr35/TLVwI/PILp2XPIRsXyj5Me/XidNOmcbq77+Z0Dz7I6diyqDExnI7dbu3ShdP16cPp2NjW//yH0y1bxulWrZKF9hn+/W/jepY2Gx968s03nG7TJm7evXu58di/ucREbt7ERPnfKSlAu3blSze1a1eWvBATI2uuuvsbDQqSdXQ3beKOj43nZedNTPSNjv3bVHgOey/44pp4ZEgWFhZSHrRGjRrhEpu1QTJkyBCkp6eX1mcEgL179+LEiROIi4sDAAwdOhTHjh1DhkPxuqKiIqSnpyP2SguRmJgYBAcHY4tTIbzU1FR07NgRLVu2RHh4OCIiIpCmtTO5wubNm1GrVi3EXLlyVh1TVTB5Mqfr14/TRUVxOtYpzcbPscbNhAmcTnuwGDFxojRijbK8a9Xi46bY+K8ePTgdayCy14Q17rt353Rxcdz5Y2Man3uO07G1QkeMkN2V9GjeXNaVZLLA2S8AgOzuZPR5vXpyboaePWWtVz1mzJDJZszcTZsax67Gx8vqC8y8HTqUZfK7IziY/+IYGsrNGxrKZcLabMBrr8n3na+19vurr8r1steOgZ03NNQ3OlVsv+pg7wWfXBNPagzFxsaKiRMnGuqmTJkiYmNjTY39+++/i5ycHJGTkyMGDx4sJk6cWPr7xYsXxdGjR0XPnj3FzJkzxb59+8TOnTvFyJEjxZ133insdrsQQoji4mIRHx8vRo8eLb755huxd+9eMX36dNGnTx+RnZ1dOtezzz4rbrjhBvHJJ5+IjIwM8eabb4qOHTuKLVu2lGo++eQT0bFjR7F06VKRkZEhNm3aJPr06SNefvnlUo2Vx+SIN+pIpqXp173TfiZN4nRsvcl77+V0/ftzujFjON1HH3G6Tz91X/9Q+wkKEqKwsOxcGtW+Y+d+/HFO98ILnG79ek63bBmnmziR061YwdXX1HqQG52/khIh6tXTH69ePXlNmHk3beLW8ckncn6juo8FBfy9xejS0vi6lIWFQgQH62uDg8vuV6vrSLI6o3nZmqzaPcPi6bxBQeXndVXDLzzcN3UkXc3rK52i6qjKa8LaHvBkkscff1x07txZvP/++241a9euFZ07dxZPPPGEqbHvu+8+ERkZ6fIn+coZ++mnn8TYsWNF165dRd++fcWsWbPE2bNny41z+vRpMWPGDNGnTx/RrVs38cADD4h9+/aV0xQXF4v58+eLmJgYER0dLW6//Xbx8ccfVzEp4xsAACAASURBVDimDRs2iFtvvVVER0eLIUOGiIULF5YaiBpWHZMj3jAkV67kHmpLl3K6+fM53cCBnK5FC07XpAmn69eP0/3975xu3rzy5/PAASFCQuRnISHyd41bb+XG7NjR2mMcMIDT3Xgjp2O/VLC6tLSyc3TokBC1a8sHd+3a8ndHGMOK/XLEGsTz5slx9QqrJyfz6504UT4A9MYLDzc2iB2Nm9RUbu7U1LJzWVgoxIIFsmD9ggXlvxQ5kpcnvyB27Spf8/IqXhOjc+OI3rzstXO8Z1isnpc9f+fOyb+t8HD5eu6c+WN3pKREHseaNfLVnVHN6th1sOMpqo6quiZVYkgePXpU9OnTR0RFRYm4uDjxz3/+U7zwwgvi+eefFzNmzBCxsbEiKipK9OvXT2RlZXkyVY3GG4Yk+/BjjQwjj5HjA4bR1a7N6TTjzeinbl1Od/31nG7kyLJzaeT1aNzY2rVERnK6pk05ndZFyMjAYb98sN2GtI46ZrpstGpVXteqVZluzRpu3hEj+HUwXrLhw/l5rTSI09KEeOIJTmvye7whZj15RrDXTrtnrMLsvNWlI4y/H5/CP2BtD4+ytsPDw/H222/jsccew6+//oqsrKwKmu7du+P5559Hy5YtPZlKYTFCcDq2qDWTwWlmXjbxhM32ZONG2DKe2q2udc9wRuueARjHfmkYFTfXYMvDNGzIlWlp317WYBwzpmIGsmPsDVus/frrOV2LFmXxac73hRaf9uGHsuc7IF/j4z3PrL3+euCzz4x1QUFcd6Xevfl5Gfy5zIeGmZp2Tg3BXOKrjFQz87L3qpl72hf4+/EpAhCrLNd9+/aJDz74QCxZskQsWbJEfPjhh2L//v1WDV+j8YZHcsEC7pv4yJGcjvWmsR7J7t05XVyctTp2C3zkSLkV5OyJdP6x2fg+5M2acbrBgznd/fdzOi2Kw5XHz9FLce4cN15urvVbuAzs9cjN5dbxn/9wOjbGNC+PWy+7XZ2WJq+dmWtsFVZ7EDUPp9E9Y/UWHjsve69afU9bjdWeZEX1psp7bUdFRWHMmDGYMGECJkyYgDvuuAPXs1/BFVXOww9zugce4HQuOkO65NprOR1buiY3l9OxnW1Y7+HgwXz3DLZ4M+vxY2tX7trF6RzrBup5gtluHA8+yGUXbt9ubaeG7du56/Hkk9x4//0vpzt/nstg3rWLWy/Al/n4+WfuGFkdi9UeRF9lpLLzsveqv3eE8efuKIrAxWNDMisrC1OmTMHbLhrOTp8+HY888ojLLW+Fb9m5k9O98QanY7e2dUqOloPt/2zUC1mDNb7YMp6JiXz3B3a7vFYt4xI7TZrw2/5//MHpTp/mSqCYMVoSEuQWmXNES6tWZVtnVm/hsrrffuN07HVr2hRYv969MRkfLz9njy8nhzeqtm/nxmR1LN6oaafdM841aVu39u52KzOv1R1mfBWWEAhhE4rAwyND8uTJkxgzZgxSU1Nx2o3bZevWrRgzZgxyWdeRokqwuuUXC+t1+/13TueibblLWI8pO962bXz3h3btOF3XrsDSpfqapUv5wtvshsDVVwNTp0pvhDPae9OmAY0a8eNp6Bm9Vnu1WB17jdkmU5oBsn69bOE3aZKsQTlpkvx9/Xpzx9eiBW9UsfUIWR2LtzyICQlAZiaQlgasWSNfDx/2zIi024GtW4F335WvrrzWRvNa3WHGVx1h/Lk7iiKA8WT//PHHHxedOnUSq1evFhcvXqzwud1uF+vWrRPR0dHiX//6lydT1Wi8ESPJxmH16sXpevTgdA89xOlatuR07dtzOram4l13cbpx4/iYPLaO5P/+x2X1snULX36Z07EZ/C++yOk++sh9aZigoLLSMJWJi9Mre8HWImRjGpctM1/bkDk+q9YrhLxn2HvLG3ijpp2VpU2syk42G0tZ1bGeVq9DxUgqhKii8j833nijmDFjhqFuxowZ4sYbb/RkqhqNNwxJ9gH0l79wOjYphy0N07attbo1a4SIj9fXxMfzhdVHjZLnMSlJX5eUZF1Bbcd/5Jm1rF5t7TVZvZoznM2sw0wtQsYoYK4Hm2i2YIH1x6eN5zymo4FtBvbe8qZh4I+GnzaW0ZeZyoxndO2svsYaVp1nbx2fovpRJYZkdHS0ePPNNw11b7zxhujSpYsnU9VovGFIsvXnxo7ldPPm8Q9nRhcdba1OKyjszoPZvr38nF2HY0Fyd0ZdfHyZhjFwzBZHNuqewY7HXpPUVOP6nnXqmMs6Zs+fGQ+n3pxm6mGuXl02t5HXzYzRYrUXj+2C4+9YuQ5vZSf7qiOM1XUfVccaBUOVGJJDhw6lOtYkJSWJwYMHezJVjcYbhuRjj3EP01mzuJaBbEmVnBxON24cp3vwQePuNk2ayAcGY8yx28YFBfI8Mg8/xmtUvz7vQVyzhjesmHPDbsd98gl3fI8+yq+D9ehaWTaHNZwdu5l4sqVemS1rsyQnVwwHcSzW7u+w9yp7nrzZKcfqDjNGWO1Ztfr4FNWXKilIPnDgQGzcuBG33norBgwY4Cr+EuvWrcPHH3+MP//5z55MpbAYNunl/Hn5z5YeQvClYdjbYMsWTvfLL5yuqAiYP19fM38+EBvLjbd9uyy0PGGCvm7CBJncYZQ1npcHnDjBzd2smSyx4+q6aO9Nmwbcfrtx8fLCwrLEiTvucK0RQiZOrFnDHR9bdqhJE+6aDB/OlSzZupWfNzhYvwB8cDAwcGDZ7zab+8LalSnOrTdeZWGz+f2RrVuNS3nl5krdsGHG43kzO5m9dlZcY7tdPxEuKEj+rcfHm09s8sY9qKiZeGRITp48GZ999hnGjx+PqKgoREVFoWHDhigqKsLZs2exa9cu5Obmon79+pg0aZJVx6ywALae48mTnI6tO/bjj9bOu3evcemh3FwgKYmrMWhk2GhoRgvz8HPV+cYVP/4os3Kzslw/OIKC5OcA13Fl4UJjAzY/nzfA2HI4YWHcOvbs4a7JqlXcvCw5OcZdhC5flve0ZrTY7e476vi6pIq7TiUnTgROpxL2HmQNyeqSnWx1ByGFwht4VP6nRYsWWLt2Lbp27Yp9+/Zh3bp1WLFiBdasWYNPP/0UZ86cQefOnbFy5Uq01p6ACr+ANSTZsiElJZzOyHDQYNsFFhVxul9/5XSOxbn1uHyZf/hpRaaNuHChrKSKO1591XrjfssW6fVwh+b16N+fG+/GG7nSMJmZ3HisATt0KFfbkL3G2vVNSZElnGJjgXvvla/t2sn3Ad8aLUYeK0BeO/bvLpDQK+vjjTqXvsDXX1IUCgaPC5K3b98e77//PjZt2oTnnnsO06ZNw4wZM/DCCy9g48aNSE5ORlRUlBXHqrAQ1lDr2pXTsTULWQO2QQNOx9b6KyjgdGzB9MaN+XPoXAvQHTfeKD1HI0e6/nzkSPk52ymHLRJ/7Bjn9WC7/nTvztVBZGvu3Xij8badzSaNAsaAZbl8mSvU7kujpbp0KmHPjaYzMu591SnHaqqLZ1VRvbGsRWL79u1x55134pFHHiltkRgZGWnV8AqLYb1pv/9uHHsVFAT07s2Nx/6D586YcobdzmGNPjZ2tFkzXssaTF27ArNmARs2uP58wwb5uVH3Gw32mrDF2lkPomboGhV5TkzkDMTu3bkt8O3bOQOWvW6NGnHePsB3Rkt18Vix58Zm44x7wHedcqykunhWFdUbywxJRWBx5Ain+/ZbLtmGTXq5dInTNWvG6dgtOzaR5cABTnfqFHDNNZzWKJ5R47PPgHnz9DXz5skHJkPDhsZexOBgYMgQbjzWGHfcetcC+u+5R746GgyhocCMGfpjzZgBnDnDzasZS0YGLHtvnT3Le/sSEoCZMyue7+Bg+b63jBZ2LazOV7B/n8ePm9vK90annKqkunhWFdUbj5JtAODtt9/G+vXrkZmZiUs6VkJQUBD27t3r6XSKKobtZb1vH6dje9Fu3MjpPv2U07Fxhex28A8/8C0D2T7HK1dySSDvv8+Nt3kzN57NxiXHsOtlYxABYO5c+Tp/fvkvBTabNCLnzuW956y3OyeH07GxrdnZ0gv2yisVz5/dLt/v3z9wjBdfsHMnp1u/3j8y5KsSzbM6dWr5tbduLY1IdV8pfI1HhuTSpUuxYMECCCOXFUBpFFVH27acrmFDTseWHmG9WqwXyqi8jQbruWzQgPOO5Ofz8Zns3EYZ1hrsNuX585wuJ0d6PcaMkdfR8U/V0evx/ffceGwspcbcucDzzwOLF8svGu3by21vLV5V294zMnQd4+dcPXRfe00+dM0Yugx65Zg0KluixQj2CxKr8xXs44H9oufvW/lmSUiQ94+7ygEKhS/xyJD88MMPcdVVV+HZZ59FbGws6rNPVoXPiYsDXnzRWNelC+dRa9QI+OMPY11YGHDxorGONThZQkI4o5M1iFu25A2m0FDuARgaym39t2zJGQZ9+nA1HVu0kB6bDz8E/vGP8lvnrVqVGWANG0qDz4jKeH9CQ8viDZ3RtveMDF3H+Dlnw+T48bJSOCxt2lhTjsmVl0yvnJAZ2MQrVucr2GS9yEjg88+NddUx+STQPauK6otHMZLZ2dkYPXo0Ro4cqYzIAKNnT07XqxenGz6c0917L6dr3pzTXXcdp+vQgdOxhuSAAUC/fpy2Wzd+TIZnnuF0L7/MJbM4Ft7WW//QocaJPk2aeOdh5y5xolWrssQJvVI4gHx/2jTg6qu5Oa+5RhqweuO9+iq/Va55yYwyjs3QtKm1Ol/BJl79+98q+USh8Dc8MiQbNmyIJmwKqcKvYLOijeoaarCZycXFnM7qLTt2S4w1MsLD+WxndsyICOO6nfXrA3XqcOMtX85nOzOZsDYbsHSp/nhLl3p3u83ZqHP83agUDiA9g7//zs3VvDmwY4e+ZscOcyVa2IxjFra0FKvzFWziVZ065pNP9OpNKhQKz/HIkOzXrx92795t1bEoqhA2a/vwYU63bRunYzOY2ULj7BZ47dqc7oEHuEzngQOl14Px0I0axc09YAAwcaK+5pFHeA8Ym9iUlcVnwq5cqT+W0eeVJSVFtnB0zljPypLvp6Tw2ewsTZtyWfT9+nFesoEDrS8ersWP6hEoHrq5c2UHKucvIjabfF9LzDJT1sdK769CoXCNR4ZkUlISDh8+jEWLFqGYdTUp/ALWa8ReVra/8p49nC4kxFodW5B8506+fR4La8SGhgLLlulrli3juw2x4QEnTnAxfp9/7r7GpcaGDVwMrBnsdq6nOVtCplEjzvj66SfuXli8mPOSbd9uffFwm02WVtLj7rsDJylj7lz5t7pgATB5snwtKCgzIjWYsj5We38VCoVrPEq2WblyJQYOHIg33ngDa9asQfv27XG1m328oKAgvGqmrYTCq1x7LeeVDAvjWtSx24Vm2gUysB5JtoVjaiqn27JFPpyZXtt67QcdmTqVG49JkgLkVh4D2/+c7UOelAS8/jqnZdi6lTsvbFb5uXPS+NLrgX733cBXX3HjbdsG/POfxiVa2OthJuPYbjced+1a4KWXyoxJqxJ9vIVe4pUjesknRq0jtbaf3sikVyhqGh4ZksuWLUNQUBCEEMjNzUWuzr/2QWwWg6JKqEVe+agoWZScGY/xXrKGn9W9tlkdWxrm8GH+gX/unLVzs1vWVsePsl8W2KLuLGwdyaNH+TEZ42vwYG4szUNsVKLFG+3u2LhQLWPcqDRSdcFM60iVCa1QeIZHhuRLL71k1XEoqpiuXTmPC9sbmy3r41y+xVMaNpSGml5cmc0m15uWZjwe6504fZp/4IeFcaWHQkI4Y7xRI66cS8uWnHEaEyNDE4zK3LDlhNjEK6tp25a7p5s04YyvHj2Ad94xHm/cuLL/1vOSma2HyWCmRaK70kjaVm+gtA1kqC6tIxWKQMAjQ3L06NFWHYeiiunfH3jzTWMdm+3Zvz+waZOxrkMHzmM1YADw9dfGusWLpXGjt005Y4YMsmcMyago40xdAKhbVyZP2GzGRuyddxpnOwOyhJJRDCIg18ok8HzxhSyWbXR8kyfLBIQxY9zrXn1VGsTMPcNWBGAZOpSrX/nAA8D//qe/Dd6kCR872qKF9DbqFYqvVw8YNqzsd71tYzP1MFnYLzN6RdM93eq1equ8qMh9cXqW6tI6sjL4e+hCTaS6XxPVa7uGYhRzpsF6D1kvCluX0igZQqNhQxmI784L1r69/NzxYa8HawTdeKNMnmDK67CJSH/8wWWMjxhh/I9QrVry3LRrp69r104+pBMS3K995Ej5Obu1zepY2PqVw4Zx5YnMlMx5+219zdtvl10LJkPYTMYxg+blNMoYB6xP9AGsz4qeNUt+YZk+XcbZTp8uf581q3Lj1TRUlrr/UROuiWlD8uLFi5X+UfgPrCHJxvexBmeDBpwuI4PTvfOO9M65ixs8eFB+zva7ZrvVdOnCl5thOv4Asq85myVsZMCWlEjvnFE85cGDMiRh1iz33tANG+Tn3ojx09Cr9WezAePH6///48fz3/BjYowz6WvXlrqEBCA5WYYJONKqlXxfM/zMZAgnJMjz7piZnJFRuW1lzcsJ6GeMmy2azmB1VvSsWdLb7nxv2+3yfTPGJLteVhcIqCx1/6PGXBNhkqioqEr9dOrUyexUiivExcWJuLg4S8d87DEhpPmn/9OpE6e74QZOd8stnK5tW043fDinW7yY040YwekefVSIBQs4bbNmnK5FC053++2crmdPTvfII0IEB+trgoOFKCgQonVrfV14uBAlJebuxeTkiuO2bi3fF0KOx8xbWKivCwqSurw87rwUFJQdY0mJEGlpQqxZI18d12h0fNq82v9jtN7K4GrM8PCyMdPSuDWnpXHzmV2zEYWFQths+sdms0kdg9Xr9Xesvh4Kz6kO14S1PUx7JIUQlfq5bHXzZIVHsB0t2cLlbF16duuMLRPEehoff5zTsSVfdu0y3m7VsNobtH8/p8vM5HSpqbwn1Oqahcw3djYzefFibvt27Fju2P75z7L/1pJo7rlHvjqu0UyGsLc8FEZ1FdktcDZExcyaGRgvu90udQxWr9ffsfp6KDynJl0T08k2v/76qzeOo1IcP34cw3SC3yZPnoxOnTph0qRJLj9/55130KdPHwDAH3/8gTlz5iAtLQ15eXno0KED/vGPfyA2NrZUL4TA0qVL8cEHH+DkyZNo3rw57rrrLkxwqpa8efNmLFq0CAcOHEDdunVx0003Yfbs2ajnUEn6wIEDmDNnDr777jsAQJ8+fTB79my0r6KU182bOR1byJut08iWmhGC07Flfdgt+kuXOF1YmO+2xerW5XTsOWTDHNLTjTsYLVtWvmbhxYuyruSBA8D118stSq3FI1vrjy0OwZZFYoviM2WvAP4LQFYWMHu28XorW9tQL2Pc6kQfq7Oi2ZJRrM4biU3+jMpS9z9q0jUJ6GSbFi1aYNu2bRV+/vOf/yA4OBgDBw5E/pWUy61bt1bQde/evXSsyZMn49tvv8XcuXOxfv16DB48GJMmTSo19ABg0aJFWLx4MSZNmoSPPvoIU6ZMweLFi7HUIcJ/x44dmDx5MgYNGoR169Zh/vz5+PbbbzHNocLu77//jvvvvx82mw1vv/02Vq1ahVq1auGBBx7AH2xAnYewhlV1gY19ZOtrDh7MleDxBmFhnI6NVWR7d+fnc4XBtbqPo0bJY120CPjsM/kaFlaWcc5+Y2fPs1FikQbb+5zVsef59GnfeiisTPSxOl6WLTNsphxxQgIwc2bFv/3gYPl+dSl1BHg3fllROWrUNfHGvrovuXz5srjrrrtEUlKSEEKIVatWiejoaN3/55tvvhGRkZEiPT293Pt33XWXGD9+vBBCiIKCAtGjRw8xb968cpp58+aJXr16iUuXLgkhhBg3bpy46667ymnS09NFZGSk2L17txBCiIULF4ru3buL8+fPl2rOnz8vunfvLt58880Kx+eNGMmJE7kYorp1OZ1RfJP2U7s2pwsL43TXXcfp2BjOO+7gdIWFfHxm48acjo0LnTBBxtfoaYKChLjnHm48NpYyLo7TPfaYEPHx+pr4eBlvyIy3erUQTZroa5o0EeJ//+PGe+klTvfpp2V/L0yMpLtrosVCrV7NzbtmjaV/6hXQW4uZMZg1s2OvXMmdm5Ur+WNMTtY/Pk9iUv0Nq6+HwnOqwzXxWoykv5OSkoLffvsNSUlJAIC8vDyEGbhwtm3bhtq1a6N///7l3h80aBB27NiBoqIi7N69GwUFBRjqtHcUExOD/Px87N69G4WFhdi1a1cFTb9+/RAaGoovv/yydL5evXqhgUMKc4MGDdCtW7dSjbdx7l3rDqZVGQBERnI6tk8060Fkt3nZsj733cfpAL6HNhutcNNNnK5jR+N116snS00wxMVxOrbwwoEDXE9uNk63aVNOx3ouw8ONr12dOmXXw6h8B5s5zZYd8raHQi/e08wYr70mH4muEMLc1rFWosgqnV7YhMa0acZxmYECew9Wl638QKAmXZNqZUgWFxdj0aJFGDt2LJpeefrk5+cbGpKHDx9GixYtUMtpX7Nt27YoKSnB0aNHcfjwYQBAuNO/ZG3atAEAHDp0CEeOHIHdbq+gCQkJQcuWLXHo0KHS+Vq7KJTYtm3bUo23YWsb/vADp9Mr2uwI+w83G5vJJgPt3Mnp5szhdAsX8tts7Llp356rI9m1q/GYeXl8Ug57rpnuPADf85op0g7IXuDMljprSLZqBUyZoq+ZPFn+A88mxzDbxjUtAcQM2rnRw5fJQIGA2dAFvZJbCmuwum6sv1KtDMkNGzYgNzcXDz74YOl7eXl5sNvtePLJJ3HzzTcjJiYGf/vb37DDoX1Jfn4+6rpw8WjJMXl5eaWxls46TZOfn+9Wo72nfX7hwgW38+Xl5ZlZcqVhA3x/+YXTsQ9xdnlskj/rJfvpJ07HJmxs21axtqA72GPcudM4/rFuXT7Jh83aZgkJ4XSs4fzzz5yOzcxv0sT4273NBvTrJ5OC9Fi2TCZy6SUDAeW9WkaZ09XJQ6F5/NyhJQ6xxol2bvSMbF8mAwUKRvegRk0oku0vsNckkKlWhuSKFSvw5z//GU0c6rLYbDbYbDa0a9cOr732GubPn4+6deviwQcfxFcGtV6E3r6ICQ2LlWMZwbYGY3o/A3z2NPtgYbe22dZpbLY4ayzVrcs/1MwcI+NpPHGCG++Ks9wQ9lyz9wK7Zd24sbXj5eZyJWTeeIPzcL7+unmvltG2sTc9FFXpYfKGx087N86eyfBw3ycDBRJG92CNKZLtR1gRTuLPVBtD8uDBgzhw4ABucgo0e+qpp7B161aMHz8eUVFR6Nu3LxYsWIB27dph4cKFAID69euXegsd0d5r0KAB6l95mjnrLlyxUBo0aFAa8+huLO3z+vXrl/5/zpqGDRuaWre3YWOS2Exi1lDr1InTde7M6VhjpF8/ThcdzWtvvpnTdenC6dianZcvc9uF7DrYtpXx8ZzumWc43dix3JY/W9eTNW5YnVmvljc8FGY8TFYYnN7y+FnV9UeFEbjGqOQWUL1iRxVVQ7UxJFNTU1GnTp0KCTOusNlsiIyMxKlTpwAAERERyM7ORrGTyyUzMxMhISFo06YNIiIiAABHjx4tp9FiJzt06IA2bdqgVq1aOOIUuFdUVIQTJ06U1oiMiIiooNHmq6o6kuz26HXXcTrWCGKTbdjtYLaMEesxZWMuf/mFN7LZeNT//Y/TsVvCO3ZwBcTZdQwaxOmGDzc2JuPjgT/9ieuhHRTEFUxn72k2QYvVOXq1WCPNSg+FGQ+TVVua3vL4paTIWGHHXtvt25s/Pn8II/DHGMSaGDuq8D7VxpDcsWMHoqOjUdspHfPf//43Vq9eXe69kpIS7N27F+2uFJ4bOnQoCgsLsd0pGGvz5s2IiYlBSEgIevfujfr162PLli3lNKmpqWjUqBF69OiB0NBQDBgwAGlpaeU0X3zxBYqLixF3JT12yJAh+P777/H777+Xas6cOYMffvihVONt2IckW5tv+HBOx/baPnuW07Fb1uxWPhtdkJ8PDBzIxeSxW9Fs7272GOvWlQ8xPdauletgPJc9enDz2mzA+vXujcn4ePm5zWaccLN0Kf9QO3uW80J168aN162buQQQX8SdmfEwWbml6Q2PX0oKcMcdFY/v+HH5vtnz6MtEB3+NQayMJ9kfDWKFn+HtOkRVxaBBg8Sjjz5a4f25c+eK6OhosWLFCnH48GHxyy+/iBkzZoioqCixbdu2Ut3DDz8sYmNjxRdffCF+++038fzzz4vo6Gjx888/l2reeust0aVLF/H++++LgwcPivfee09ER0eL1atXl2q+//570blzZ/Hyyy+LAwcOiK1bt4qhQ4eKKVOmlGr++OMPERMTI8aPHy9+/PFH8cMPP4gHHnhAxMbGigsXLlRYgzfqSA4cyNVta9CA0zVvzunq1OF0bF1Kdt4//5nT9e/P6SZO5Pv5tmrF6erV43TDhnG6uXM5XVqaEElJ+pqkJL7uo2MdxIICISZNkj3MJ00q379aw6j39BNPcPM+8URZ7UDn2m3ae8nJfJ/5xx7jzou2Blf14hzn9QbsPZiaan3fX+Zcs5SUcLVCK1vz0tO6mWbw1b3AYLYHuTf6wisCB9b2QBUcS5UQHR0tXnzxxQrv2+12sXz5cnHbbbeJ7t27i4EDB4q//vWvpcXBNfLz88WTTz4p+vfvL7p06SLuvPNOsWPHjgrjLV++XAwbNkxER0eL4cOHlzMiNdLT08Xo0aNFly5dxMCBA8Vzzz0nLl68WE6TmZkpJkyYIHr06CF69uwpEhMTxbFjx1yuzRuGpN5DxfkfP0ZXq5a1OvaHXcf06Zzu1ls53cqVfIHpfv04XVQUp5s929jorFePP77Vq43PY3i4EJ99xo2Xmmr+ftQzOFNTzc3r6uEXHl728GMNydmzufNSWGjeSLPKuGGNEgh2gwAAIABJREFUe9YY1wwIFqNzzWL2GvsrWhFqM/eCL46PKZLtzwaxomqocYZkdcYbhmSnTtw/3KxnMDiY01n9w3bA6dWL0/XuzT9wFyzgtDfdxOnYTjSpqfIfcT1NcjL/cJ43z1qd2Yd9UlLF+yc4uMzbVxlvlZ6hxnpqJ0zgdOx94A0vD+thYg3JynTVscIoNuN19mfMevx8AeNJ9neDWFE11NjONgqO6GhOx/aeZmFLzbCwxbSv5FUZ0rIllyE8cCDfcaVXL043bhyXfDJ0KLBypb7O6HNHjErhaFzJKzOETXoBgFmzgH//u2IyzeXL8v1Zs2Qs5fjx+uOMH18+XlUvmYVN0GLvGbb2aHa29aVX2FhFp2ZbbqlMOZzqXtrEDIFQv5KJHVVJOQozKEOyhnLsGKcrKbF2Xl89ZNh5r72WyxBOT5daBjaxqaiIM5iKirgWhGyTJPYas4lXbGJTUREwb56+Zt48mcHPFBBnkwCE4HRWJ6Q1aWJ96RU2O3noUP8uh8MauqzOVwRK/UqjElSBYBAr/AdlSNZQMjI4HftQYzvRWG2YsrDFr9muLGayF9lWgElJXJb1jBnceC++yOn27eOMjK5dufFYXn+dM9qnT+cKiG/dWva7XqYp65Fs0MDa87Jnj3e8PIyHyR/K4egxdCjvjfdnAql+pZ4nOVAMYoV/oAzJGgrbpcRqWG8QC9vvml0vW78SMFeWhiEnR9/QAKShwdal/OMPTnfpkjQy3F0bIaSRwW6Bs1vb7PlzqqblFs2QNCq9wt4zwcGc8cWeF7ZlZWW8PEyRc3/u+8uWgvL3bXN/N9hZAskgVvgeZUjWUJo353Rsez82lpL9B9Tq9oNsZxuinj0A+Q2e9cJefTWnY2MuGzXidOzWO1sDvzJeCj3PIHtN2GsMcLUIr/QWMCQiwr3x1apVmfHFnherz7MzTKyiP/f9TUiQXnnnGGWbTb7vD8fI4M8GO0t1MYgVVYMyJGsoc+ZwOrabCdsBh32IswbdDTdwOpbLl409VkFB8ps4u10+YgSne+ABTjd1Kqd7+mlOd9tt+mMGBcnYPa1wOeulMPIMjhvHHd9993G6mBhgwgR9zYQJfFtNxy1rZ2+t4++s9yYx0T+8PGxyTFUXok5JAV55xXXi1Suv+L6Ytxn82WBnqQ4GsaJqUIZkDYX1ILLeIPYhw3rn2Exn1phjM3A/+sh4+10IuS3LJpWcPs3p8vM5Q6NOHW48tif3V19xsXvbt5d5KdyheSmY7OS4OOOWmfXryxhJtpUiE0u5bZu+xlGrrcO569CJE2XrcPTeuOPVV+XfUqB4eaq6M0t17AFdHbLZq4NBrPA+ypCsobDeqk8/5XRshvA333A6tnzNf//L6dge2r/+yum2bOENxP37Od1333GGBhuDyMZSsrrsbPkAGTnS9ecjR8rPWaMAAN5+W3/OFSukAcbEz335pb5Gg61Y0KwZb9wkJAAzZ1Y0Fmw2+b724NV0ztu3wcHldb7E6hJFDKrcjP9SHQxihXdRhmQNhe3/7CvY7Gmrs8rZZKAjR/gkCza5o25dbjuJjaFjy9ewuhYtZF1Hd6WHNmyQn5sxChISgORk1+tNTi5vgDE6hvBwzvML8OvQtmWd70fnbVl3OrvdP7ZvfeUZVOVmFIrARRmSNRQ20cFXhIRwOvbbccOGnM5oC1WDNUwBabQw3HijfDXaTrI6o5Idr18/YP58/bHmz+c9fppRkJAgDXPH9WZmVjQOExKk53vBAmDyZPl68GCZji0NExdnrec3K4szvoqK3Os0nI20qo5T9JVnUJWb8V+q+h5UBB7KkKyh3HYbp2vZ0tp5WcOvUydON3gwp3vjDU7Xpw+nCw7m4zPZbF3H5A697SQ2o3LKFK5Lz5Qp3HhLlhg/ROx2YOdOfY2Go1HAbJ+lpMhzOX26rEE5fbr8XfPimalFqHl+ne/vymRjnz7NGV+LF5sz0qo6ThGonGfQCkPDm+VmlCFUeXxxDyoCD2VI1lAuXeJ0bC1CFjbJh93aZtcBGJc8at6czypv0wa45hpOy4YRfPEFpwOkodOnj+ts4j59yopQh4XpjxMWJnXMljrbClAIzqAzYxQwcXuVaaWoF3bAGjds2SazrRSNyhh5A7OewZQUoG3b8oZG27bmj89b5WaUIVR5fBErqwhMlCFZQ2FjAdne2Gx2d5s21s5bVMTpwsKMM7dPnQKuuoobr359me3M8MMPnI5NegGAUaOAb791/dm338rP09ONDfL8/DIPmNGWOutZZY1xFjZur6iI6wxkt/OGKWPcOBvf7mDPX7NmXBkjb3jWzHgGNWPXOaM9K6tyxq7V5WaUIVR5qmMWvcJ7KEOyhsJ6ydhOL6xBxyaosFnWe/ZwOrZu5pIlnO7zz2U5HAa2s82FC5zu4kWu1zbrAWNjGh9+mNN17syV4XGMs9PbfmTj9oy2jgGp27rVXDa2kXFjdR3Jy5fNt4S0CtZ4Brxj7FpVbkYZQp6hsugVZlCGZA2FNeisbqXIGlXsljVrwLK9xc+c4XQHDvDnhk3McVyznmGVlMSNt2ABp/v6a/lqtA3Ixj6yBrYWZ2c0Lxu3xxrOW7eae0gaGTes8aXVkTRqRcmWMfKGIQlwxvPWrd4zdq0oN6MMIc9QWfQKM5ARawqFfxIczBlqjRpxdR/ZLfVataTB89tv3NxMBnDt2vI1JUV6UxwfhK1bSyMkIUEasQxsEfasrLJtSme0mLzkZKCwkBuPpUWLsu1HZ+NK23788EPrWxCyOD4kNePGHVp9yPnzyxv9wcHAjBn+UR/SDAkJQHy8NLSys+U1iIkpM+pYA3HrVmDYMG8dpXuUIeQZKoteYQblkayhsP2afQUbq8hmbb/4IqdjWy7ecIOs+8fAHmNEBBfXdf313HiaYWpEQQG3Tcl28hk61LjkUXi4bLnIbD+yrRmtbkHIrhfg6kNq263u0FpRssfHljuqLIFciFoZQp7hzSx6RfVDGZI1lMxMTscW02Zhs7ZZz2BeHqdjvXhGLfs0Gjfmk2PYkkJ3380ZVi+/zI/H0LQpt015+TL3cNGMD6Nj277dfGtGZuvYSGe1QaQXj6cxbRq/pW6z8WWMnI+jqsrcsEast41ddyhDyDO8lUWvqJ4oQ7KGUlLC6djsbqvnZWMkf/mF061Zw+nYItTBwRWzVd3x/fec7r//5QyNXbvktqMe8fHA8OHcvCxffsnF+AFc9jR7/rTWjExGL6NjrzGrY+Px2O3gnByuJaTjQ7yqy9yYqdnpC5Qh5DlWZ9Erqi/KkKyhsP/Asx5Eq2ENWFbHJuWwW/4REcDJk5yWzSx3V87Hmexs4P779TX3388/JFnvL4uRYQVIw4rtVa5tP7IZvUY6q7c9rY6za9HCXEtIX5S5sdnMG7tVjTKEPMeqLHpF9UYZkjWUP/+Z07EP0zp1OB3bDYZtVdixI6cbMoTTsYkBXbvyHis2E5wt/s7WGWQN3bZtOV1MDBfjx3oamzY1v/3Ixu3p6fr1446P1bF/I47JKu6w2WRMKMC1jvRlmRvN2HWOh61M/3NvoQwhzzETK6u6CNVMlCFZQ2GLaRt1RtFgvVpsrUR2C5ztY822hGSNudxcYPduTstu019zDWdY2e1cTCNbK5TdprTZuC1c1tPYqpVvth/Zdpmsjo3Hs9m4FpOO5ZOMHuLeLHPDGAWuDDVXfdJ9SSAnDQUSqotQzUUZkjUUrXagEWy9SbY0DGsgsrUXjbZQNd57j9OxhdCbNeOLtYeEcLr27csMK3e8+ipvFLCxmUJw25SsB9aMp9Hs9qMVHg+2TiOrY+Px2PNnpo+1t8rcmDEKrDbUlFcr8FBdhGo2ypCsofz0E6c7d87aedmYRtZIY7PP2ThFtvai3S4frAzdu3O6Bx4o66HtCq2HNsvRo5wuPb2sbqAr4uPl5+wWruZpNErK0QwOdvvRKo9HQYG1OoAziCvTx9povd4oc+NLo8Cq3t2KqkN1EVIoQ7KGwiafsJ5BNkaSLa/D1pFke3w3aMDpWM9qejowdiynnT7d2CsZGgrExXE9tNlEKdbQBYBZs9y3XdywQX4eE2O8jpAQqduxQ1/n/LmRV8tK44Ytx8TqNIwMYrN9rJn1Wl3mxpdGgdW9uxVVg+oipFCGZA2laVNOx9aRZLezGjbkdPXrW6tr2ZLTNW/O6S5fNldj0+jBW1IC5OdzPbS7dePmZL2X/frJjix6zJ8PnD9v3BayuFjqmPHYLzNWGzdsgXhW54ieQWymjzW7XqvL3PjKKLDbvdO7W+F9VBchhTIkayhs1xP2H252C5zdsmZjM9mYRiMDTYNNQmrcGHjnHU779NPGnt3Ll4FbbuHGYz2SK1Zwuk2buCQQNvN9yBBuvMWLufGsNm727rVWZwZmC9zseq0sc+Mro8CbvbsV3kV1EVKoXts1lPx8/57XyPOlwW69s+Oxx3fttXxXHdYozsjgdMeOcbpDhzjdwYOcjs0CZ3XsvFYbN4cPW6szi1Ef68qs12hMFl8ZBf7eu1vhHi28IivLtRc9KEh+rroIVV+UIVlDsbrQeHAwZ9T5amuKPb7QUK5EUbNm/HY5W0KJze6+6ireiGWoW5fTNWgAnD1rna59e25etue1o85ud29UXXcdNx6rqwzaFrgrKmvM6Y3JoowChVm08IoxY+T94XjfqC5CNQO1tV1D6dSJ03XowOl69uR011zD6djkHTbmki1czq53zx5gwABOyya9aIWojWCNBdYQGjWKK5T92GPceLNnc7qHH+Z0ZjHKdu7alRuH1VlNTAxX19MbxpyvWgv6e+9uhT6qi1DNJuANycTERHTs2LHCz3CHRsO7du3C2LFj0b17d/Tp0wfTpk3DKac6L9nZ2Zg2bRr69u2Lbt264d5778X3ToX4ioqKMGfOHAwePBhdunTBLbfcguTk5ArH9MEHH+DWW29Fly5dEBMTgzlz5qDYaW+VOSZvwmYnsyVQ2ELjbJLP1VdzOtabxnoP2Wzxw4dlNiwDm1TCPpxZA5E1stu2BWbM0NfMmAFcfz03HhsHu3Nn2X/r1Q5kO/ScPMllO5sZrybiC6PA33t3K4xRXYRqLgFvSObn52P48OHYtm1buZ/3rlSgPnToEMaPH4+2/8/emYfHdLZ//JtMEiQSWSyViNg6ofatFCFCLd2UqmpRfZXqT2lV7a+lVLUo+lJV3q721mutUoogllLdtKgt9i1igixkfX5/HGcyM5nlO3Emk+X5XNdc4cyd5zxnyZzv3M+9RETg22+/xaJFi3D16lUMHDjQKO4yMjIwYMAAXL58GQsXLsTq1atRo0YNDBgwABdNAtImT56M9evXY+LEidi4cSNefPFFTJgwAZs3bzbaqO/36tULGzduxOTJk7FhwwZMmzbNaMPMqbDAdmVhC4OznWNY0cIue3bowHndbNVStKRmzdxlQHuEh/Pi+eRJzu74cc6ubl1uflFRwMyZ9utIzpyp/fGqMX5r1wJVq5p7EKtWzfUgsp1yrl/nsp3ZYvymQvfuXWDoUKBzZ+WnLbGsRTHtuDgu8cSV5VQKWhQUht7dshD6gyO7CJVQRBGne/fuYsKECTbfHzt2rGjXrp3IzMw0bouPjxd6vV58//33Qggh1q1bJ/R6vThz5ozRJisrS7Rr105MnDhRCCHEpUuXRGRkpFi1apXZ+CNGjBCdOnUy/r9Dhw5ixIgRZjarVq0StWvXFteuXaPnZEpMTIyIiYlxeC6c4emnhVAer/ZfFSpwdt7enJ2PD2fXvDln9/zznN2YMUKMGmXfZtQoIZKTufGSk5XzuGaNfbs1a4R48UVuzIcf5uxq1eLsevXijlk9Dg8P6zYeHsr77PFu387Nb/t2brwlS7jxxo3j7Lp14+yGDFGO2ZZ9t27mf1Nr1ggRFmZuExaWe+5YVqzg5rdiRf7//gsra9YIUaWK+XFWqeL8OSwq+5VICjOs9igWHklfO9kMe/fuRVRUFLxMskuqV6+OKlWqYM/9HmhxcXGoVq0aatSoYbTR6XR47LHHjDb79u2DEALRFmsrUVFROHfuHC5evGj8ac0mJycHcfddCMycXM1DD3F2bA9ttjA4+y3/1CnOjvXi/for0LKlfZuWLZ3vw+xs4W17sDUx2USbo0cV74o9Vq1Slt5tefJUXFGEOjtb6eZjj/79+SVmtpMPW5z+4YeV+FF7hdqffVb5t5bFtPOTXFRccEfvbtneTyJ5MIq1kExNTUVCQgLCrQSzRUREIP5+fZSzZ8+iipU1u4iICFy9ehV3797F2bNnUapUKVSyqFhdtWpVAMpy9dn79UIs91e5cmV4e3sjPj6enpOruX2bs2Pj3diONWwGMxvDyZbCSU5WxJItPDwUsbR+PTfe+vWKAGMKb9sTaKawiT4REZydEI5DDi5eVOo5MnULd+3iziEr/GJjHZdbSkkBDh/mxmP7uL/0Ehfm8K9/cQXiU1JkMe2iiis7+cilcklJocgLyeTkZJw4cQIDBgxAmzZt0LVrV0yePBmJiYlIuf+U8rOSkVG2bFkk33ftpKam2rRR92FLsFraWNufh4cH/Pz8kJKSQs/J1dhqw2cJW1eRTcphhSTrCWVjOG/e5MQSWwPxzh1FgDGFt9kYP7b8D9t9hy0jw9Zz3LWLO4fs8bIC8dAhzo6t1+ntzSUX/fvf3Hh9+2pbTDshQVu7ooRW/dRZXNXJp6CPQyJxJ0VaSGZlZaFcuXIwGAzo06cPvvzySwwdOhRxcXHo46ARsiDcRFrZsGg5liO0riOpdY4Q6+FkywSxsOKrXj1egLHHwnoa2Qx0tlc0W8+RpUIFrv8zm3HPhk2w4yUkKMlDo0bl9UzqdMr2mTP58IojRzg7VkiW1E4h7lhidkUnH7lULilpFGkh6eXlhb1792LVqlXo0KED9Ho9nnzyScyaNQvnzp3Djz/+CABGL6ApKSkpKHe/Poq/vz9SrdSvUX/P39/foU1AQAAC7gdfWe5PCIHU1FQEBATA/34gnKM5uRo2K5rNutNaA9+PGHAIK6pYkcHW12zcmJ9jixaOPayennxvZ7abT7ly3BLu4MFcNjZbeiUsjKtFyNZBbN+es2PHUwXYzJmKJ33uXCUTe+5c5f8zZyrvs38jbKkq9rqp2fGOhLjl8RblpVRXLjHbQ2vR7q7jkGhLUf5bcgdFWkjaonbt2gCA27dvo3LlyjhvpSHzuXPnUPO+K6ZGjRo2bapUqYIyZcqgRo0ayMjIwFWLr6bnzp0DANSqVcuYrGM51qVLl5CZmYlatWrB19eXmpOrYb1kLGytxKQkzo5dpmTrV7JL9GzvbjbGVB2T6bV99Cg3HusJ3bmTW3o/eFAp12GP3r0VIckKHKYW4bBhtscyHXPuXK7G4LBhzgswHx/lwT5/vvLT1Ps5a5b9far07MnZBQdzdvkpCl7Ul1JdtcTsiPyKdlu46zgk2lHU/5bcQZEWkvHx8RgzZgxOWqTu/vXXXwCAatWqoV27doiLizOrz3js2DFcuXIFMTExAIDo6GhcvHgRp02aHWdkZCAuLg7t77tDoqKi4OnpiZ07d5rta/v27YiMjERoaCjCw8NRo0YNxMbGmtns2LEDXl5eiLr/acTMydWwooVdsmY9kqzgZDNwWWHK7vfWLc7O05OfI5s/xS6lsiKWPZbLl7nsbsA5gdOjh5JV/8YbQKdOys8TJ3IzcHU6x55iPz9F3DE1Bn18tO3KUqaM47qi3brxnmm2UgJgW4iHheUtCm5rKfXSpaKzlOqKJWYGrTv5uOs4JNogwxLyR5EWkpUrV8bhw4cxYsQI7N27FxcvXkRsbCwmTJiAatWqoXPnzhg4cCBSU1Mxfvx4/PPPPzh06BDGjRuHhg0bokOHDgCATp06oU6dOhg9ejR++eUXHD9+HGPHjkVmZiYGDhwIAKhUqRJeeuklzJs3Dz/++CPOnDmDRYsWITY2Fm+//bZxTm+99Ra2bt2K//73vzhz5gw2b96MBQsW4OWXX0bIfbcKMydXw3ro3AWbgcsWOGezwNml8uhoPraQTTBiHy5ax0jeuMFld8fFKQJm5Mi8S/Wensp2U4EzerRS0mjBAmDbNuWnv7+yHVDGY7K2nfHeODM/hvXr7RdqX78+r9izBWtniuUXNMv/21tKVe2LwlKqO+NCtezkU1LjW4sDMizhAXBpNcsC4MqVK2Ls2LGibdu2on79+uLxxx8XU6dOFUlJSUabI0eOiD59+oj69euL5s2bi9GjRwuDwWA2zo0bN8SIESNEs2bNRIMGDUT//v3F8ePHzWwyMzPFnDlzRFRUlKhbt6546qmnxObNm/PMacOGDeKJJ54QdevWFe3atRPz588X2dnZZjbMnFRcUZA8MpIrelzYXzodZ1epEmc3ZowQISH2bUJChMjKEiI9XQhPT/u2np7KmMy+2SLxX37J7TctTSmqbK/QeHi4EMuWcftdsYIvXM4UQmcLby9blrdYtOUrPFy5Juz8nCUtTYg33hCiUyflZ1pa7ntZWfz8TH8nNlY5B7Gx5u8JYfs4PDzMjyM2ljuHsbH5O+6CIj3d8d+yTqfYuQpH14Qdg/mby8/YEtdSXP6WtITVHiiAuUgeEFcIyYAA7o+msL98fTm7atU4uwkTuG4rQigPg7Jl7dv6+wsxfjy3744dObvZs53rWOPoWNhONFu32hdM6kMyLY0TBVu3cvudO5ez277deUGnFc4IWEddVBwJU1Mxwn4JWLZM+2PWkuL0EFfvBcv7wfJLgKRwUZI7StmixHS2keQPITg7tp6j1uWE2OXgatU4Ozb0NDpaWcpasybv8lNoqLJdXepilmaTk/kkC7ZTyc2bXJcerfnrLy6RYNQoLsnnzz+5rHI2K3rnTn6J3nQeWmRnqsujltnv4eHmy6NMDJYzCRtszU7Wzl0Up9hCLZfKJQWHDEvIP1JIllBYocbCClNWcLJ2WnfeadFC+fnzz8D16+bvXbtm3vLQsh2eLSpWdLx/f39eFANcJxW19aEtnO1Ec79AgUPYpKH9+znByRbPZzPu1eumdXamtfZ+Z8/mCgc2Bou9r65eVWp2MrB27qIwPMS1LPnSo4dSXcG0tNTp01JEFma0zuAvSWjsR5IUFZo0AbZscWzH1r5jP3QdlXtRYZNt2E40//sfZzd2rCKyrZV+ycnJ3T5zJu/lSUgASpWy77308QHatOHGCwjgOql88om2nWjY5KKHH1aSaxzBinv2SwrLjRu5nkHLsVXPYH49Rzqd7XqbrKeRvR7OiKr8JPoUJOpD3N75ceVDfO1aReSb7r9KFSWjOz/3gbXxZs/O/3gS16Nm8PfsqTynTD8b8pPBX5KQHskSCpvFrDVslxJWwLLlidjOkydOKB/49pg9W/H2OaptqJKYyAm/Y8e48f78k7Pbs4ezUzvR2CM8XClczhRW//BDbsm6Xz9ufmxhcLYzUEiI89mZWnir2GVZtjNQVBTQqhV3rlu1cm6uBY1Ox9UydcVDXOuSL7KETNFFhiXkDykkSyisx49dAmf7RLPCjxWSrIeTJS2NKx4+fz5fNP3iRc6OrTfJ1q9k+5+HhXEP8f37uXNz8CDXy7pDB04wDRnCCV02Dpbtu67GUjqzBG5PcLIeRLYzkE7Hhwfs38/t211kZ3O1TLUuvaJ1yRdZQqbo4yhERZIXKSRLKCdOcHasUAsM5OxYgcgue7IeTtaOTYzZu5ePO2OPmbVjYymbNeM6wrRqBXz5pX27L79UklkYdu3K7WVt6cE07WXNFoP28QGaNrW/zyZNcjvv2CM8nL9uV686V+zbkeBs1Yrz6LZqxXtGXJmkUpBt4hwt+wOu6QijdSea/Iyn9Xlmx5NtAG2jhqi8+KLyUy5n20cKSYld3PXhwmbqsoKzVCnHXlNvbyXphaFMGec6lTAEBnJCiF0SbtvWcQhDRobyEGGW3tlkG5WWLfN64R56yDyjnBFMGRnApk3297Vpk3Kv/uc/igi1Jkw9PBRhysYLVqzIF/teuxZ47jnrgvO553KzsRmPrioymIQNNtOftVMp6DZxbIIRa8eitRB31k7r88yOJ9sASrRECskSSunSnB3rkWSXeVmvG7t8m5jI2fn7O15Wz8zkYyn9/XmRzR6zpye3xMxmtP/1F1eeaMkSbjz2XoiOzvXkWT74r1zJ68lztJT06afc8u2nn3KtBaOiHH8BUd9nvGS7dnFZ9M54dAHlHNWsCbz9tpI49fbbyv9d/bB3R4yfu8oYaZ0t7oydu2IzZQynRGukkCyhsBm4bEIJm1nLihGte3yzMZysgAWA3bs5O9aL4uPDxYmx5Xr27uXs2NhM1gPbrJm2cWJsGIapneW+Tf+fnQ2kptofKzWVvxd++onz6J49y42Xk8M/7BMSuDFN7ewtaborxo9dgWDtWLQu+cKO16qVe2Iz1ZJgMoZToiVSSJZQatTg7Ng6jVoXONcaViydPs3ZHT3KC43ff+fs/vtfzgNmWd/SFo7GUmG9ugcOcHavvKJtMgsrnK9d4zyh8+c7vl+FAD7/nNvvTz/x82MIDLT/sDddUnfWU+boXGsdM8jC1gpl7VjYOF02Ro4db/9+98Rmfvqpe66vpHgjhWQJhfWS3b7N2bECMTRU2/FY2PFYj2mpUkDVqpwtmyF/6xZnx4YRlCrF2bFxpnfucHZnznB29pJZTD1vrCfUXkyjqbeFLYvE1ih1FD6gcu8eZ2cw8IknznjUmDhOd3WYYb+Ial1TFNC+5AsznrtiM53525RIWKSQLKGwXjJWBLFCjRUjLKzwK1OGs2M9D3fv8uVm2JhGrUsZsXGwjhJ8VGrV4uzYsAlW+LHnJSGB87awnlo2HIL9QuHnx9mx5aIuX871gNlLCPr4Y+XfTBwnm5SjdYcZtlYoa+csWpd8cTSeu2Iz2b9N2QZQ4gxSSJZQ2AQQVgSVK8fZsWWC2FgodjzWzpme4dHRXHmB8nqdAAAgAElEQVQdNs40OJgbjy1RxIr7Rx7h9vv119x4X3/NeckATvix9xbruWQ9tQ0bcsW+33mHG69ZM86OxZnEEzYzPyfHPW3ihgzhzvWQIc6PzZa50brki73x3BWbqdZklW0AJVoihWQJhS00znok2eLXrJeH9ZKx4yUlcXbOxHrqdMDixfbtFi/m6xaWL8/ZsV4jdslap3NcJig9HTh8mBvv99+5ODE2UYQV95GRnB3rGfTx4Qqrx8Rw9SHbt+f2y3boqVAhN8nCFmo/dTZjfM+e3GtnC1e0iWPPNVsPVsUVZW4yMpRzMGyY8jMjw7qdPQFrGktpC8vzzI7nqCarljGhEgkAQEgKPTExMSImJkbTMf391bD9gn35+HB2jzzC2YWEcHbVqnF2Xbtydh9+mHsuu3WzbtOtm/L+pk3cmNOnc3Zz53J2H33E2c2cydmNHcvZLVumHPeoUULodObv6XTKdiGE2L6dG2/bNiHKlrVvU7asEOnpQlSpIoSHh3UbDw8hwsOFGDeO2+/48dxxxMZy423frszPnk14OH9eYmP5fffty9lNmMDd065Cy/2uWWP9XvDwUF5r1jg/pqN7wXTflte6SpW8+9R6PGt24eH5t5OUbFjtgQKYi+QBcYWQ9PbmHizuetWuzdk9/DBn16sXZ7d+PWf344/KeRw1yr7dqFFCZGVxY379NWf3+eecXXKyYwHm768IJma8jh05u7lzbT/EgdyHOCuYNm+2PZbpmOnpufu1tDcVD9u2cfvdti337yU9XTmuoUOVn+npue8tW8aNt2wZd7+kpwvh6WnfztNTsVuxgts3e423b+fm6AqcFX5ZWYqQXrFC+ZmVZf6ePdGufqkw/R1HsOeFPQ6t7Zjzkh87SclFCslihCuEZJky3IPFXS8/P86ufHnObuBAzu7FFzm7CROUB7mlN8HypdMJcfUqN2a/fpxdkyac3aRJnCdv5EhuvCee4Oy+/przvLECrE8fzu6jj5R725H3ZutWbrytW7m/JWc8xI486CEh/Py2b+fF+Nat3L7T0rh72lRIa4Gzws/RNWY9tbGx3PzYv/W0NO44VO+5VnZSBBZuiqpoZ7WHjJEsobAJG2x8GhtTw2bgOioYrcKWzDl6lLM7coSzA/iOK40aceOxcVtsxv2HHzouTZOSAuzbx43Htkj85ReufA2bLMLu17QAuxDm75n+35nafCr24tPYGNjERC7h5ZtvuPHUDjgMbDzvokV8FyEtcaZ+JVMySuuyOezf+qhR2tZzdGXdR9lru2AoCe0opZAsoVg+aG2hdUkadr8sbPY5WxOQHa9VK74mG1vwm60zyJ5DW0kAlrCFstl7gX0ghYRwGaTVqnHjlS3rXGtGFkcPArZ3N1t26Px5fm7OdLbp0QNYs8Z6fcM1a3J7ezOwdiysoLt8mSsZpXUZI/Z4T53SdjxX1X0sCeKmMFBS2lFKIVlCYTvWsLirYw1byoWFzVI/doyvycZmmrK1LlkvMXtN2FJL7PGy3umbN7kM0pdf5sbr04cTGW3bcuOZ9gy39yBQS6/YIzycrzfJCufoaOfrDPbooQhV0/qG587l1jdkrzFrx8Iex40bnIcO0LbMDXu8bJ1Lrc+zM3UfS4q4cTfuajfqFgpgmV3ygLgiRjI8nIshKl2as2NjLlk7dr+lSnF2ej1n17AhZ/d//8fHTbHZzmPGcEklzzzDjdeyJWc3cSJnt24dF/vIJg0tWaLci44ySNPSuPE2b+bstm7lzjMb75aVpczV3njOJBdt28bFM2Zl8fcgG9OYnMzNMTlZ048j+jiWLOHmt2IFl3jFwt6Dyclc5QC2wgBrx8bcuSIJSWIdreN03YGMkZTYha0xyH5bEoKzY4tLs143dr9sW0FnltjY2ne7d3Njfv+94+MRgq/ZyS5t//ADZ7dmjeJBtOfl+fhjvmanek0cdQFh4/GWL+fsdu/mzrPW8WlRUVy9yXbtgAED7NsNGKB4fvfv52L39u/n5sj2F2ftWNjjYP+OK1fWtvXhwYOc3eHD2tZz1Lruo7t6qZdE3NVu1B1IIVlCYZe22ZhBFrZFYmYmZ8cWVmfHc/a8tGxp365lS+D0aW5MtjUeuwSutci+cyf34Wy5lBYamvtwZpNPWDv2oRYfz9mxyTvsfi9f5toPxsU5/nvKyVHsVq60b7dqlSKs8vOwspdkUdhjJCtUcG7J2pnWh/bOizPnWf0bCQ01fy8szFzAskLXlp3leFofBzOeqynKCUFat7cszEghWUJhPYOsaGHjALX2prFt51gPLCu+7t7lu4qw59rZrh2OYJN3WDuVDz/M+0C6ckXZDvCtClU7R4H/ycnceOxxsAkqbOWAa9e4bGy2u8yuXVzWe1yc8w8rR+e6sMdIhoU576FjWh+uXat0FDI9LxERueclP6KASU5zRuhafjZZ+6xydH21vl9cSVFPCNK6DWahpgCW2SUPiCtiJNn4ubAwzq5iRc6OfTmKYVNfbOHyHj04O0cxgOrrxRf5GBi2/mLbtpwdGyPJFmuvWpWze/11IZo3t2/TvDkfC7h9O1e4PCaGG69OHc7u6ac5u9GjuVhFttg3Wyd0wgTObsWK3Jg3JoaOKWztTDF0LcnK4uNChdC2MwsT36rFeTa9p52dn1aFy7W+X1yFO/etJVrG6boDGSMpsYuj+oLO2rEeRHYpmi01wy5T/vMPZ1e6NGdXqRK/TMR61Ni+4Y76Yquwy/mBgZxdaKhSI9Iev/zCL+VfuGA7qxFQtg8fzocbsB5E9p5m70E2058tSdOiBT+e2mPZ3jn8+GPl30wGKeD4b9TX1/29mNVSRXPnAkOHKj9Pn3Yu7hFQVhWYsASA84QC3D3NLtGymb8ZGfz1fdDjMB3PFUvNxSnbWcs43UJNAYhayQPiCo9kq1ac18ORd0J9sS0Xg4I4O61f7HF4eXF2ERG8R5LNQGfnqPWL9Uiy/c8rVeLsWrfm7Bo35uzYLkfseWYrArB/S3Xrcnavv87Zbd+u/C0zrfvYe5Xt0qN1pqmzGa5s72kh7HcVccZ7bmu/pp5QrTN1XXXdCvo4nKE4ZDtbQne2ycgQ4vp1IY4fF2L/fiE2bVJKFXz8sdKqbOhQIV56SYguXYR49FGlZVtOjsvmzWoPMjdWUtxo2ZLL5GS9MmxSDptsozXs/FjvksGgxLZ4e9v3/Pn48N+ctU5sYmE9pmzhctbjd/s2Z8d6idkYU/Y8s1529p5mj5dNGkpIUOY4Z459uzlzgPr1uTFdVQBbq/GuXs2tgyiE+XtqHURTT8/atcCbb5oXqA8LA+bNU2zY7kC7dgEdOii/07Wr0sHm1CmlbuSsWbmx5JaF8G3B2rHnxdnr1qMH0K2bEmd79aoSExkVletpdmfGcZHPdhZCWUYxGJRXUhJ0BgOi1f8fMQCrknLfN32xH8YqR48qNzObzOAipJAsobCiwMeHW1rUuuuJu/D05IRG2bLKeXG0fJyRAZQvz3e3KcywS+8VKnDLzP7+3HhsOMRDD3EdjNhr7OPDhRHUqAH8/bdju7AwrruNo+LmKhUr8q372PI1riiAreV4FSsCr7ySV0QCyjY1wa1bN2DDBuC55/LaXb6sbF+zxvl5jh6tCHP1nG/bBnz2mVLma+ZMvu0na8eel/xcNzUJ6UH264qM40KT7ZyTo3xLNBV6STYEoOX7bPyRLcqVU1p/BQcrr6Cg3H+bvpo0cbuIBKSQLLGwgq5ePcdxcYD7Otuw6HTcMYeEcB/yDRoomYQMAQGckCxThhPtpUpxn1OPPw789JNjuwYNuFqXnTsDS5Y4tvvpJ67Dx6OPAgcOOLarVMmxDaAc72+/ObZr1Iiz69pV8djYy8gOCVFi6DZudDwe29+e/ZIHACdPcnbZ2YpAvXzZugjz8FDeHzIEmDjRvlfZ31/7TFM1w9XR/ACuDuKuXVzs44oV3PyioxUROWtW3veys3O3N2zIjceWvmLPy5AhwOzZju3Y68bu1xUZx5rvOzPTKPCyE5NwNM6A1IsGlPc0oGaQAZ63bIjEpKQHWyby8sorBIOCzAWiNZEYGOj+IGQnKRZCcv369ViyZAnOnj2LwMBAtGnTBm+//TaCg4Oxfft2vPHGG1Z/b/ny5Wh2v37MnTt3MGPGDMTGxiI5ORm1atXCm2++ifbt2xvthRBYvHgxVq9ejWvXrqFSpUp44YUX8JrFJ9aOHTuwYMECnDp1Cn5+fujYsSPGjh2LsiY1aE6dOoUZM2bg119/BQA0a9YMY8eORU2t62rYgO0J+9dfnB27DKg1Hh7WP2ys2TGwiR3Z2UrxYQa2dzK7rB4UxIkNttUe2yLRYODs+vXj7Ng6jRERymevI0EXEwPMmOF4PNZZwHqNbt3i7NiEr+PHObuEBH5579o1JcmiZ8+8fzOWSRaOSnSlpir3v5bPOjVpyNH82NJNO3dyJZkA7t5q1Ur5ImWPOXOALVu4+bH92dnzohYud2THXjN1v9Y8uoAyvjPjOYP1YxYog7sIgQHBwoD5Aw3QbXDgJVS3mywX6wA0cHZCvr7WvYG2xKG6vWxZ/sFTxCnyQvLrr7/GjBkzMH78eLRr1w7nzp3DpEmTcPbsWSxduhQp979a79q1C14W7VICTdJVhw4dimvXrmHmzJmoXLkyNm7ciDfeeANLly5F06ZNAQALFizAf//7X7z77rto1KgR/vzzT7z77rsAYBSTP//8M4YOHYpBgwZh5syZSEhIwJQpUzB8+HB8fr8dRFJSEl5++WU0aNAA33zzDTw9PbFgwQL0798fmzdvRkBAgKtPm+bZ2FrDCkSdjhNgWsd6+vpq3+fby4vLtGZrYl6/ztk98wywfr1jOzZ2j/3ywYYDlS8PtGmjLFXaok0bbixAWR49etSxXZkynBhhzzP70GW7OlWu7FzNTjWD1DJmMDQ0N2bw44+5oumffpqbBZydbTvWzhRHdur8hg0zD1EwnR8b08h+edu9G1i82LZgApT3Fy3iQgj++osTps548mxdN7Wmpmnh8pEjzZfeAWW1aMQI64XLmeumKZbLxTZEYA+DAQm1Dbh5Kgn+WQYEw4DSMPkGONn5XSchEAYEIwlBUEYMvv//YDzdPxgNoi1EoioI2SDtkozL0n0KgJycHNG6dWsxZswYs+3fffed0Ov14vz582Lp0qWibt26dsc5dOiQ0Ov1Ii4uzmz7Cy+8IAYMGCCEECItLU00atRIzJ4928xm9uzZokmTJuLevXtCCCH69esnXnjhBTObuLg4odfrxW+//SaEEGL+/PmiYcOG4vbt20ab27dvi4YNG4rPPvssz/xckbXdoQOXGcdmY7N2vr7ajsdm1rI9vtl6mKNHCzFgAGfL1uKsV4+ze/RRzi46mrObPp2zCw3l7AICOLuOHTm7r7/mahuOG8eN17s3ZzdyJGc3Zgxn16sXZzd8OGeXlibErFmc7axZyt/9qFHWa9qNGqW8P2QIN96QIYo9mz3N2nXrZn1/3bop7zvqFQ0o2ccvvsgdR58+3H6HDuXPizP1MIVQanLOnavsY+5c6zU6mfPnTP1KR+M5quvphQwRGXRdZP19XIh9+4T4/nshvvlGOYCJE/NmF9eqpQz4gKUpcry8lA/p2rWVcglPPSXEyy8rfzRTpggxf74Qy5cLsWWLEAcPCnHypMi6niiqhmU5vGdkf/G8lIisbQ8PD2zatAmeFgF6Fe8XbEtMTERycjJ8HUTr7927F6VLl0ZLi353bdq0wcKFC5GRkYHffvsNaWlpiLaITo6KisKiRYvw22+/oUmTJjh8+DDefPNNM5sWLVrAx8cHe/bsQePGjbF37140adLEzPMYEBCABg0aYM+ePRg8eLCzp8Jphg8HduxwbOfvzy1pBgRwrfbq1AHur+bbpVQpvg4ig5oc44hq1bjlM52Oj3MKDeWyNNk4UzZDk42f++47zo5dwvX35zKZhw0Dtm93bHfwIOclY2J5AX7Jn83GZuItAaBWLc6O7dCzaBHvQc/JsR3jJ0TudtZz7+HBZ0+zds8+a9vrvGGD8v769UqHGmvHodK7N5d0pTJ6tP39jh7NJ7N4eHBe7Li43LhLSw/iyJG5yTsAd/66dbNfvxIwT0JSxlOWi1XfXMglA5Y/Z0DE/yUhIMuAd26a+u3MX/5IAZIA1OPOSx58fc2XhG0lk5guHQcFwSMfy8Vxu4ALDj5/1U5RtpKPJPYp0kISMF+eVtm+fTt8fX3x8MMPY8eOHQ6F5NmzZ1G5cuU8S98RERHIysrChQsXcPbsWQBAeHi4mU3VqlUBAPHx8QgJCUF2dnYeG29vb4SGhiL+/trg2bNn0dlKwE1ERAS2M09WDWCXMNhMXTZxjF0qZ5fe2Xg3drmQjcG6eJF/iLPC7/4t5hD2mLUu68Pul+3d/ccfnN2JE5wdK3RZ2OVRNsSBLTTO3lenTvH3zI4djkX77NnA/egbhzRvbr9otJo9/dRTnF2nTvZDFwDl/ZQUrg/5Cy9wx1GpElc+KSEBePttx+M1bszt9/JlLnnngw8cn7+338pBiOdteF9KQlMbwi9IJCH4ogHJjQyo+48Bl4UBQUgyXy5WWaj8GOfgGHLggfTS5VAm1LbwsyoKg4IKdLlY65JMkrwUeSFpyfbt27F69WoMHz4c/v7+SE5ORnZ2NiZNmoSDBw8iLS0Ner0egwYNMnogU1JS4Ofnl2csNTkmOTnZGGtpaafapKSk2LRRt6nvp6am2txfsrN1pPKJvW/0prBla5iyJgAfP6c1bFIC2ynnf/8DWrfmbNkkFfbSsyKb9Wyxnl8205/dL3sPskk5R45ou9/YWM6OFc5qL3JHsMeRk8OX9YmL09arm5TEZU9/+ilnx1ZAeOklrg85++XjwAEu9vHVV7nxNm3i7K5ezStgvZCJICQZxd+J2QYcEwY8d8lgtt3sJQwIvHQLuu45oEKY/wYsXS+Z8MozclCNYByOt4wlDMJNJd0FBgTjNsph/Egd3nuPO2Z3oXVJJkleipWQ3Lx5M0aPHo2nn37auDys0+mg0+lQrVo1vPTSS0hOTsbSpUvxyiuv4IsvvkBrO2pA2FsncMKGRcuxHME+rAp73Ud3kZ7OZ3i7C9az5e/PiyEtYVsastnsWgti1nvO3gdspQT2WgQG8l5Ydo6XLnHJImxYB+uNZwUsa8ceL/vljT2OlGTz5eJgWBeBjeYZsDXb/P0AWEwmB8BHwMfcrpECPzPRZyn8khCE6O7B+HyduThMQVkA5svF415QvKGOKApLwey9ytqZ4paEpUJIsRGSy5cvx7Rp09CnTx+MHz8eHvfjKCZPnozJkyeb2TZp0gRPPvkk5s+fj9atW8Pf3x+Xrfi1VQ9iQEAA/O9XT05JSTFbKk+9/zQMCAgwxjymWHEZpaSkICIiAgDg7+9v/D1Lm3Llyjl97PnBUYkPiX08PYtPMh/bcUVr2Mx8NpudtdMaNpaS7bzDhpN4eWnfDYn9XGAfutWrc3ZseAD7XZutbFCrlvVi8h7IQQDuGIXfU/4GPGK5XGxFIIbEJsHH2nKxJRdtv6VmFxsQDF2FYJy4EWxXIBoQjG82BOHJHqXsfknS6QB9KyB2nePpBQc7Ltzv6emaOpKmaFERgC21xNqprF2rhB2YesirVDHPpC8pFAshuXr1arz33nt45513MGjQIIf2Op0Oer0ef91fZ61RowZiY2ORmZkJb5NP8XPnzsHb2xtVq1ZFwv3guQsXLhiTeQAYYydr1aqFqlWrwsvLC+ctgqsyMjJw5coVPPPMM8b9Wdqo+yuoOpJBQXzHmgJ0lLoMrY/D07PwnxfW88Z6tdhzWLo0t7wdGMgt+1euDFy4oJ2d1rBCkvVUREQAx445touOVuIamb9jtiB/xYpcsggb31qnDldcum5dLib1oYe4cktqSSvL5WJLETi2ggH/s7JkHIhb0MFERRHtZAFA/RXT5WJV+JmWnUn3DcbFNPO9JiEItxCIHOTeKI/VAg4QS65/neSW6Nkwm5s3uVCI/ftd55VkhZojO7XAub2QiPBw50SxM206SwJFXkgeOnQIkydPxtixY/HKK6/keX/WrFmoXLky+vbta9yWlZWFY8eOodr99M3o6Gh8+umn2L9/P9q1a2e027FjB6KiouDt7Y2mTZvC398fO3fuNBYxB5SYzMDAQDRq1Aje3t547LHHEBsba1YEfffu3cjMzERMTAwAoF27dvjkk0+QlJSEoPvVoBMTE/HHH39g5MiRWp4emzRqxGU2lilTPLyXWou+zEw+FrCww54b1k7rhCo2dsldnlU2jviiHS+UKQaDY9Hu4aE8+KpW5eIBH3qISyZgPYhMJx9ASYxhCltv3WpvFAFfpCEYBkSVM/XX2fYQ1hxhQE81u9ge/wX62Hk7BX5IQhDC6gfj7K1g/HHRXPiZzuDpl4Oxalswjl2zvlxsShkBMKvvbILbvn2cHftFi71XXdXvWuuKAGqBc8DcNj/F2rOzuQSybt1KzjJ3kRaSQghMnToVjRo1wpNPPokbFk8cdQn6ww8/RHZ2Ntq1a4e0tDR88cUXuHz5MqZMmQIAaNiwIdq3b48pU6bg3XffReXKlfHdd9/hzJkzmD59OgDAx8cHQ4YMwdy5c1G9enU0bdoUhw8fxqpVqzBu3DijJ3Po0KHo06cPZsyYgeeeew6XL1/G9OnT0blzZzzyyCMAgBdffBHLli3DyJEj8dZbb0EIgblz56JixYro1atXgZy7OnWAzZsd2wUHFw8h6QpYIVTSYJdbtY5BdJeQ1JoTJxyLdiGUpTz2QRUQoJwfe/ds2bJKd6D7H3maYBqDaLlcrL5q/GhAVJwBelsJJTCgFO7fLHvIHVt42ZMQaHVJOLBaEH49l9czqHoQM6Csuc8doHzxtpeo1awSkBoCpBBVEPz9ufuabatpJXfTKuyXQfZv2GRxTjNYocZWBOjWLbeouzXP5ccfO+c9jIvjEshKUjmhIi0kr1y5glP3I9jbWGltMXToULzzzjuoUKECVq9ejblz58LPzw+RkZFYsWIFGpvUapg9ezZmzpyJMWPGICUlBXXq1MEXX3yBunXrGm0GDBgAT09PLFq0CNeuXUNoaCjGjRuHPn1yv9M2atQIixYtwpw5c7Bs2TIEBASga9euZp5Gf39/LF26FNOnT0f//v3h4eGBxx57DEuWLHFYqkgr/vyTs2OX7Uoi7lhGlRR/2DjPnTv5WEB/f8ferfR0rkSRNzLQMyoJN/fZjhVUtzf81YB7Gw1ItLZcrPJfoBFxDBnwRmqpYGSUDcapm7YTSmJ6BuNCcjBWbM3NLjZdLjZF7wMw5VZPngQ++8y+zUcfAVOmAJMmOR5vyBBg6lTHMYgdO3K1Vk0eU3Zhw13ym8GsRfIJK9TYigCqoOvRQxGVDzo/1gvrKm9tYaRIC8mwsDCcINZ1XnnlFavL3qb4+flhypQpRi/lg4zVpk0bq8LWlIiICCxatMiujSthY2WkkLSNPDcSV8AWpr9wgS+8feaMpUDNm10cnGnA2icMGOUgocQfKcCHwHBmx1aWSFPhm0d2+lQKxrHrtpeNDQhGKvzQ40kP7N4N2Avj3BYLPP44wCRas568S5c4L/Hevdx4Xl5K8pW98BgfH6WZAQNbVo1t58nWBTatQatV8gkrwNhMetPxdLoH9xKyXlhTu+Ke3V2khaQk/7irnmNxorAn20iKJqzXqEoV4OaNHATitt14wWAYEHQzryA0LhebQtbszIEHbplEK1oTfgYEw7tCEP6xyDpWl4tNCbgLMN/L4uK07X/OFslgRcuBA5zdihWOY6zv3eMbJLCf52wBe/azTfVcapl8UrkyZ8fmpZqO5w5B54zALqqCUwrJEgpbm08ikbgeb2QYxV+F9CQE2IgVNBWJVeYZ8H56EjyR/280mfAyyyi+owtGQrb1ItSmYjGjdDmk3nP8hPO/B8vqiFZha4qyKylstyY2/pZdfWCTY1iBaDBwdT1ZQcx+SWG7EIaEaJ98EhXFHfOQIUrVAkcVAdRsbK08puy1S0hQ9mkt0ezSJWX7mjW5+y7K5YSkkCyh+PjwH3oSiYQhN7vYUb1By21m2cVsEwCTJDi1GLUt4Wf5f9UuFX4wzS4OrcQtlweVAVKJqgVBQVzRb7Y8EespY5dH2ezkihW57l2VKnFjVqrEZ/szPPkkl7n98MPccbACW+0brnXyCRPPq9PlZmNbVjmwzMZ2h8e0YkXHrTpfe82y//mDz88dSCFZQmnXDti2zd2zkEgKHx7IQTmT5WKb7emsiEOry8Uk9paLrWUclwkNxt9XgmwuF+eHhx7ihGTNmsDhw47toqOBJUsc2wUEcMKqVClO5LArLqxgio4GfvvNsd2//qUk0TiiWzfg6FHHdkzXKWe6UsXEcK0/mzXjknwqVNA++WTXLscVMVJSFDsmG9uRxxRw3mPK1EbNyeGu3Y4dRb+ckBSSJZTdu909A4nEtdgqRs14Cx9kuTgD3laziS33bpl1bC+72Cpkoo0zWOvyYnXX5L6ZIuMA751jhV9QEFeeiy1zk5TE2bHJNl9/zdn99BNn98MPnN2xY9yycceOXG94Z7rBsJ68nTt5uw4dHGdjO/KYAs55TFlP6B6yVNXSpUW/nJAUkiUUuawtKRpotFycD0x7FztKKjF9pcEX9opRF2bY2p6sd+n06fzP5UGoWJFbYmbbUbJCjRVBrBBnl97ZGqoXLgADBtivhzlggCJYGMGpxh86Ywso99mnnypJTDVrKvGOagtR9phZO6YQvzN2AOcJ/f13biy2HrHp31xhS8qRQlIikbgc0+ViZqnY1Ear5WJ7ItBaPKFWy8XFEa27HGlNfDxnx3ok2SQfrWHLE+n1nDc5NBRYuNC+zcKFwLRp3H7zw+jRSpKM6bl/5x3lNXOm0q6QQbVzlKTC1sR0tnamI09odDR3Htu0Udp5OkL16BbGpBwpJJFNwjQAACAASURBVCUSCY1pdrEzHkKbxahJMuCdR+hZ9i+2JgidXi6WaIq7hCTbP55JBAJ4wcnC9q1n93v8OGeXmsrFH/7nP1x8X1xc7r8Z282brXtDc3Jyt3fuzHVXionhkmgqVHA8FsDbmWKvLiXr1R02DPjgA86jW1h7fEshKZGUOPIuF7NeQi2Xi23FDVomlSQhKE92sYQXI+6E7dKjNex5Yeen02krJtmqGVp70+43gnPIunWc3cWLSnF11nb2bPs2s2cr3YHYpfKaNR0nqXz1FTc/Z+I9GXQ6LoygOPT4lkJSIimiWGYX2xOGlv/XYrmYTSgx/SmXi7WjsItIgE+OKeyw3YZYcc/GqLMZ2Wx9SNZTywrOXbuAl17ibPftcyzGc3KUpXVGgO3fzyWpAMrSrz3b8HDzGE4tyM4GVq60b7NqleKBZTy6zraELEikkJRI3Iwzy8Wmr0DceuDsYiZe0PJ1G+UgQD5ZJSWaoiB2GdhyQlofL+sxZQV7WppjG4DPUv/hB6B3b872yBHObs8e4Ndf7dusWgU0bMiNl5CQm2Vtq1yPWm9SS9hs8V27uPHy0xKyoJBCUiLRBAE/pNIZxabbXJFdbCuBxPT/crlYIuFgPX5awwpTR+0WVbT2EN+7xwshtjtQaionwNg2mBUrKmWCRo4E5swxv5Y6HTBihGviCrUWdPlpCVlQSCEpkZhgb7nYkafQB/kPCLMsRm0ZL2jLS5iEIGTCR8MzIJFICgtax8GyY4WGcuV1atdWSgox+JAfUxUrcnbOFGJfuxb46KO8x5+To2xv2VJ7MckKuuhopa6oowLngwcrme32wgM8PYFWrfIz2wdDCklJscQH6UbB5yheUOvlYkfZxNZiC2V2sUQisSQggK8RycAK08ce44RkzZpA1arcvkNDudqKVapw47Fxq9euAWPHFnySCtsBJzqaK3C+fz8XYxoXp3hgCxIpJCWFGGW52Nm6g8EwoCxSH2jPyShrlihimUlsa+lYLhdLJBKtqFCBE5Jsr/LSpbk4yU2bHNuodqtXc+V6WJF265YiEh153tq25ca7ccM9SSrO9AJnCpyPH8/td8cOKSQlxRBnsou1Xi62zBo2FX32BKJcLpZIJO6GXb4tV44rmt6kCdfGkc0qv3uXF4jssvrVq5znTQiuTBBbH9IVSSqMQDS1tVfgnOlt74ydlkghKaHxRgaVPGL5fy16F1tbLrb1Uu1kdrFEItECd9XsZBNUWOHHZoF7kIsq3t5KVjQDmxDEtipkk3weeoizc1WSiiOBaIq9Aue+vtz+WDstkUJSAgBohl8Qg512vYQPulxsL7vYnlAsyr2LJRJJ0cddZYzYbHE2G5v1uvn5cUvqgYFA+fLcmI0bAz/95NiuFFlq9vBhrv4iwMUqal1H0hR7ApGlbVtgwwbOrqCRQlICQGArOiMYjouHqdnFtoSfraQSuVwskUgk7oWtI8kK0zt3gD/+4GzZ2pTh4cCBA47t2Cxw0zqSjmIVnSU7m/M0asHQocCoUY5jR4cOdc3+7SGFpASAB0ZjJtpgr8OEErlcLJFIJAUDm0RTtiy3DB4QACQmOrZje6Tfu6dkEzMcPcrZMdniAC9MK1dWvIHW6kh6eua/juTatdZjH//zn7zjaSE4fXyU8j/2Ov688w4vsLVECkkJAOALDMQXGOjuaUgkEonESVjxwIoXNibUy0tZBmfHZEhO5uzKlHEstHU6pa6irTqS2dn5qyO5dq31TjmXLyvb//e/3PGcEZyOmDlT+Tl7trln0tNTEZHq+wWNdC1JJBKJRFIIYcWXF+kSqlaNsytdmrMLDORbFer1nF1EBGdXtqxjb63qCXzrLfvCePhwPh41O9v2eOo2dTxVcFqWH1IF59q13D5NmTkTSEkB3ngD6NRJ+ZmS4j4RCUghKZFIJBJJoSQoiLNjl6L//JOzc1R+R8XTUyk0znD+PGfHJjaxwnTnTr6OJIOjHtrqeLt28YLTGdauVY59wQJg2zblp16fP1GqFVJISiQSiURSCClblrNjxRdbTogVN97eQFgYZ8t26GFbLrIZ6FqPx9rt2qWtgAVc4+HUAikkJRKJRCIphLC1F8uV4+y0XioPDMxtBWiP8HBecLLHEh7O2bH7ZXt8a11vkhWmziypFzRSSEokEolEUgjx8XEs/jw8gJgYbjy25iOblJOZmdsK0NY8PTzydnGxx6uvcsI0JIQbj/XCsqjC2d7xhofzdSNZYcouqTvj4dQKKSQlEolEIilAWI9f9eqOl62F4NsAsl68MmU4u4AA5afaCtBSAIaH52Yws0k01asDL75o36Z3b75jDeuFZTv0qMLZ2timdSmjoznByRZC13rpXUukkJRIJBKJxA6eGj8pWSFZqRJnx9Ze7NaNs6tRg7MzFbA9egDnzgGxscCKFcrPs2dzPZFRUY69iCEhSrmelSvt261axQvJhx/m7JxZslaFs+WyeZUqucKZFZys95edn6taPdpDCkmJRCIpgqjeIHfA1i309nbtPAoKVtCxglMIbsn6xg1uvOvXueXgBg248dglcEvRorYCfPFF5Wd+urw4WsIFcoUzc8xDhmjrGVRxJJxVG0eCk4WNRXVlq0dbSCEpkUgkRRBXtGJjx2TLzWRm5n8uhQnW+8XWX9TpuCVrdrn13j0uTnHfPm6806c5O3Z+gCIQmd7Yu3bx+2aWwH18tPUMmsIIZ0ZwsvtijtdVLRrtIYWkG1m9ejWeeOIJ1KtXD1FRUZgxYwYyi8snr0QicSm3bmk/JhtPVtjReik6MNDxA1qnA+rU4cZjM4RZr3O1aoowGTky77HrdMp2Z4QLW3aIFdiA9rF7FStyS+DZ2dp6BvODFp7a7Gzgyy/t23z5pczaLlGsX78eEydORK9evbBx40ZMnjwZGzZswLRp09w9NYlEUgRgawc6A1uIurDDCiG2vd+9e1wXFVbcsx7devU4u/79lRqCs2blvYbZ2cr2tWv5TOLmzTm7WrU4O4CP3WOTVABuCVzNYtbKM+gudu3S1qOrJVJIuolPPvkETz75JF555RXUqFEDHTt2xFtvvYXvvvsO169fd/f0JBKJ5IHR2jPIwnZbYT2Ivr75n4s12C8BbGebNm2A116zb/Paa0r8nKPl99Klgaee4vb7yCOcHeBc2RxmKZpdVjf1hGrhGXQXO3Zoa6clUki6gXPnzuHixYuItvh6GBUVhZycHMS5oxCURCIpUrAJL87AevLYrGO2jIzWsOVwWKHLLkWzApFdfmS7ssyfz3mrduxw7A3NyOC9Wrt3c3aAc1nMzFJ0Yc5idgWHDmlrpyVSSLqBs2fPAgDCLYp6Va5cGd7e3oiPj3fHtCQSSRHCFUvb1atzdqwnqmnT/M/lQThzhrNjvVrVq3PetJQUbjx2aZvN2l66lLObM8dx+EJODvDtt9x427dzdirOxCoy5YRckY1dWLl2TVs7LZFC0g2k3P+08bMI0PHw8ICfn5/xfYlEIrEFG9/nDBERXFma6dO58Vq14uy0XgJncxZZb1VMDOdNY4+jVCmupiJ7jVlhysZwpqdzdvnBmVhFe0vRWtdpLOywrSNZOy2RQlIikbiF4pIhrDVsJmybNkDt2pwtu9Tbtq2S4WuPkSOBLl0cL4OXLQt07Mjtl334seV12CSQ7t05QRcdzXnTmjXj9tu8ObB4sX2bxYt5bxrbIpGdH1vE+9FHOTtLtIpVdHc2dkHy7LPa2mmKkBQ4u3btEnq9Xvz2229m23NyckTdunXFrFmzzLbHxMSImJgYTeegLIyVnJdez9nFxHB2n30mxOrVnG3nzpxd376c3YoVnN3atZzd0aOc3e+/c3b79xfu/cbFcXYHD2o73uHDnF1CAmeXnCzEzZuc7dWrQnh62rfx9BQiPV35fBg1Kq+9TqdsV1mzxv54a9YIkZUlRJUqQnh4WLfx8BAiPFyIS5e444iP5+xu3eKPlzkOU7KyhIiNVf4OY2OV/6skJ/PXTj2HVaqYv1elSu4+09O540hLEyIkxL5dSIhip9PZt9PplPPHHEdamqaPpXxj75oUF9LTbf8dmf49qX/DWsBqD2i3SwnLhQsXhF6vF+vWraO2u0JICsF9UEg723auGJN5aDgznq+vfRtfX8WuUiX7dpUqKXZeXvbtvLwUOx8f+3Y+PopdzZr27WrWdO68sMfLfCA7c17Y69Gtm32bbt0Uu+bN7ds1b557D7JzHDXKvp2pSBRCeSDNnSvE0KHKT2sPqDVrhAgLMx8nLMxcfK1Zo5xPy3OublNt2WvHnkNnjtfacZgKOmdw5toJ4VgEscfBCmJ2PPY8SwoOZ/+GHxQpJAs5Xbp0EW+++abZtq+++ko88sgjIjEx0Wy7q4SkEI4ffNLOvp0rxrQlmlSx5Ox4th7Q6oNZxZYgUYWIii0xqYpIFVtiUhWRKrbEpCoinT0v7PHa85Ll57yw18PWA9rywWxLkFgKEWfmOGpUXo+UpafRWRhvkDXPW3h4XqHGXjv2HDpzvFp6tZy5dgyMh1gIXhCz54U9z5KCg70XtEAKyULOli1bRGRkpFi8eLE4ffq0+OGHH0SzZs3Ehx9+mMfWlUJSCMcPPnfbVaxoblOxonW7V14xt3vlFet248eb240fb93us8/M7T77zLqdEHmXuVevtm43YoS53YgR1u3i44UoXVoRNaVLK/+3huVy7v791u2uXlVERalSys+rV63b3bwpRL16QgQHKz9v3rRud/68EGXLKh9oZcsq/7fGpUtCBAUpIjMoSPm/NW7dEqJ1a0VctG6t/N8a7Hlhj/fUKSG8vZVz5+2t/N8a7Hk5ejT3Q97TU/m/NdLShHjjDSE6dVJ+2loiTE4W4tlnhahfX/mpLok+yBwZT6MrYIUae+3Yc+iu43Xm2jGwx8GeZ3Y89jxLCo6CuqdZ7eEhhBBuCM2UANi4cSMWLVqE8+fPo3z58ujZsyeGDBkCT4vUvw4dOgAAdrij0qhEIpFIJJISB6s9yLKyElfwzDPP4JlnnnH3NCQSiUQikUjyhSz/I5FIJBKJRCLJF1JISiQSiUQikUjyhRSSEolEIpFIJJJ8IYWkRCKRSCQSiSRfSCEpkUgkEolEIskXUkhKJBKJRCKRSPKFFJISiUQikUgkknwhhaREIpFIJBKJJF9IISmRSCQSiUQiyReys00RICEhAdnZ2cZ2RRKJRCKRSCSu5OrVq9DpdA7tpEeyCFCqVCl4eUnNL5FIJBKJpGDw8vJCqVKlHNp5CCFEAcxHIpFIJBKJRFLMkB5JiUQikUgkEkm+kEJSIpFIJBKJRJIvpJCUSCQSiUQikeQLKSSLMatXr8YTTzyBevXqISoqCjNmzEBmZqa7p1Wi+Prrr1GvXj28/fbbed47fPgw+vTpg4YNG6JZs2YYPnw4rl+/7oZZlhzWr1+PHj16oHHjxmjfvj0mTpwIg8FgfP/UqVMYOHAgGjdujMaNG2PQoEE4c+aMG2dcfMnJycGXX36Jp556Cg0aNECLFi3w1ltv4dKlS0YbeT3cy4ABAxAZGWl2TeTnVsExZMgQREZG5nk9/vjjRpvCcD2kkCymrF+/HhMnTkSvXr2wceNGTJ48GRs2bMC0adPcPbUSwa1bt/D666/jiy++sJr1Fh8fjwEDBiAiIgLffvstFi1ahKtXr2LgwIFS7LuIr7/+GuPGjUP37t2xYcMGTJkyBXFxcXjzzTchhEBSUhJefvll6HQ6fPPNN1i6dCm8vLzQv39/3Llzx93TL3bMmDED8+fPx6BBg/DDDz9gzpw5OHr0KF577TVkZGTI6+Fm/ve//+HgwYNm2+TnVsGSkpKCxx9/HHv37jV7ffvttwAK0fUQkmJJhw4dxIgRI8y2rVq1StSuXVtcu3bNTbMqOSxdulT069dPJCYmivbt24vhw4ebvT927FjRrl07kZmZadwWHx8v9Hq9+P777wt6usWenJwc0bp1azFmzBiz7d99953Q6/Xi/PnzYv78+aJhw4bi9u3bxvdv374tGjZsKD777LOCnnKxJjMzU7Rv31588sknZtvXr18v9Hq9OHLkiLwebuT69euiWbNm4t133xV6vV5cvHhRCCE/twqa7t27iwkTJth8v7BcD+mRLIacO3cOFy9eRHR0tNn2qKgo5OTkIC4uzj0TK0G0a9cOX331FUJCQqy+v3fvXkRFRZnVB61evTqqVKmCPXv2FNQ0SwweHh7YtGkTxo8fb7a9YsWKAIDExETs3bsXTZo0QUBAgPH9gIAANGjQQF4TjfHy8sLOnTvxxhtvmG338PAAAHh7e8vr4UamTp2Khg0bokuXLmbb5edWwZKSkgJfX1+b7xeW6yGFZDHk7NmzAIDw8HCz7ZUrV4a3tzfi4+PdMa0SRXh4uM2OAKmpqUhISMhzfQAgIiJCXh8XERgYaCZKAGD79u3w9fXFww8/jLNnz6JKlSp5fk9ek4Lh2LFjWLhwIdq1a4fatWvL6+EmtmzZgn379mHq1Klm2+XnVsFjT0gWpushhWQxJCUlBQDg5+dntt3DwwN+fn7G9yXuwdb1AYCyZcsiOTm5oKdUItm+fTtWr16NwYMHw9/fH6mpqfKauIFZs2ahXr16eO6559CqVSt88sknACCvhxu4desWpk2bhpEjRyI0NNTsPfm5VfAkJyfjxIkTGDBgANq0aYOuXbti8uTJSExMLFTXQ/bdk0gKEUI2mioQNm/ejNGjR+Ppp5/G4MGD7drKa+JaXn31VfTo0QMnTpzAf/7zH5w8eRKff/65TXt5PVzH9OnTERERgZdeesmp35PXRHuysrJQrlw5GAwGDBo0COHh4Th16hRmz56Nn3/+GUuWLLH5uwV9PaSQLIaoy3eWnkchBFJTU/Ms70kKFn9/fwB5r4+6rVy5cgU9pRLF8uXLMW3aNPTp0wfjx483xuWpXklL5DVxLcHBwQgODkbNmjVRv359dOrUCd999528HgXMnj178NNPP2HNmjXGvwlT5OdWweLl5YW9e/eabdPr9XjooYfw0ksv4ccffwRQOK6HFJLFkBo1agAAzp8/j8aNGxu3X7p0CZmZmahVq5a7piYB4Ovri8qVK+P8+fN53jt37hxatmzphlmVDFavXo333nsP77zzDgYNGmT2Xo0aNWxek5o1axbUFEsEBoMBP//8M5o1a2ZMeAKU2GJfX1+cOnVKXo8CZsuWLbh79y6eeuop4zbVs9WpUyc0b95cfm4VAmrXrg0AuH37dqG5HjJGshgSHh6OGjVqIDY21mz7jh074OXlhaioKDfNTKLSrl07xMXFmdX6OnbsGK5cuYKYmBg3zqz4cujQIUyePBljx47NIyIB5Zr8/vvvSEpKMm5LTEzEH3/8Ia+Jxty7dw9vv/021q5da7b90qVLSElJQWhoqLweBczw4cOxceNGrF+/3vhS6w4vXrwY06ZNk59bBUh8fDzGjBmDkydPmm3/66+/AADVqlUrNNdD9+67775bYHuTFBjly5fHggULUKpUKQQGBuLnn3/GzJkz8eKLL5pVxZe4hlu3biE5ORlpaWn49ttvERwcjEcffRRpaWnQ6XSoXbs2lixZgrNnz6Jq1aqIj4/H5MmTERYWhtGjR1tdWpLkHyEEXn/9dURERODNN99EWlqa2QsA6tWrh7Vr1+LXX39F9erVce3aNUydOhVZWVl4//334e3t7eajKD74+/vj4sWL+PbbbxEUFAR/f3+cPn0akyZNQmZmJqZPn46GDRvK61GAlC1bFiEhIWav5ORkrFu3Dm+99RbCw8NRq1Yt+blVQJQuXRofffQRdu7ciapVq8LDwwO//fYbpkyZguDgYEycOBGRkZGF4np4CBklW2zZuHEjFi1ahPPnz6N8+fLo2bMnhgwZAk9P6Yh2Nf369cOhQ4esvvfBBx+gR48e+OuvvzBjxgwcOXIEpUuXRvv27TF27FgEBQUV8GyLP5cvX7b7DX3o0KEYNmwYzp8/j+nTp+PQoUPw8PDAY489hnHjxlktQyN5MDIyMvDVV19h9erVuHbtGoKDg9GoUSMMHz7cLDxHXg/3cfDgQbz88svYsWOH8ZzLz62C4+rVq5g3bx7279+PpKQkPPTQQ4iKisKwYcMQGBgIoHBcDykkJRKJRCKRSCT5QrqmJBKJRCKRSCT5QgpJiUQikUgkEkm+kEJSIpFIJBKJRJIvpJCUSCQSiUQikeQLKSQlEolEIpFIJPlCCkmJRCKRSCQSSb6QQlIikUgkEolEki+kkJRIJBIN+eijjxAZGYnFixe7bB+9evVCZGQk/vjjD5ftwxWkp6fj3XffRfPmzfHII49gxowZ7p6SGXv27EFkZCReffVVd0/FLmfOnEFkZCS6dOlid5tEUhB4uXsCEokk/xw/fhzPP/88dDodNm7ciIiICJu2cXFxGDhwIEJCQrBp0yYEBwcX4EwLhuzsbGzZsgVbt27FX3/9BYPBAB8fH1SsWBH169dHt27d0KpVK3dPs0DZs2eP1d7iAODt7Y0KFSqgSZMmeOWVV1C/fn2XzmXVqlVYuXIlKlWqhP79+6NevXou3Z+z1KhRA6NHj5adcyQSJ5BCUiIpwtSpUwevv/465s+fjwkTJmDJkiVW+6umpqZi8uTJAGDs1VrcOH/+PIYOHYqTJ08iODgY0dHRqFKlCtLS0hAfH49NmzZh/fr16Ny5M6ZPn46yZcu6e8oFSlhYGPr06WO2LSkpCf/88w82bdqELVu24P3330f37t1dNofjx48DAAYPHpxnLoWBKlWqFHpvpERS2JBCUiIp4gwePBjbt2/HoUOH8O2336J37955bObMmYPLly/jqaeewuOPP+6GWbqWmzdvom/fvkhISMDLL7+MESNGoEyZMmY2V65cwbBhw7B161ZkZmZi4cKFbpqte6hUqZJNkbRr1y68/vrrmDJlCtq2bYuQkBCXzCE9PR0AjH2CJRJJ0UfGSEokRRxvb298+OGH8Pb2xqxZs3Dt2jWz93/77TesWLECFSpUwMSJE/P8fnZ2NpYvX46ePXuicePGaNiwIbp06YK5c+ciJSXF6j7Xr1+Pvn37GmPdWrRogVdffRUHDhzIY6vG8505cwb//ve/0bx5c4wePdpsfkOGDEHr1q1Rt25dtGzZEr169cLy5cuRk5NDnYMZM2YgISEBPXv2xL///e88IhIAQkND8eWXXyI4OBgGgyHPeTpw4AAGDx6Mli1bGufx2muvYe/evVb3uXHjRnTv3h0NGjRAixYt8Prrr+PkyZN25/n999+jb9++aNq0KerXr48OHTrgvffew40bN/LYZmRkYP78+ejYsSPq1auHqKgoTJo0Cbdv36bOiTNER0ejVatWuHv3Lnbt2mXc7uja5eTkGL+8NG3aFPXq1UN0dDTGjh2L+Ph4o50ae7h582YAwIgRIxAZGYlJkyYZbW7duoVZs2ahS5cuqF+/Ppo2bYpevXrh22+/tXofxMbG4tVXX0WLFi1Qt25dtG7dGv369cPGjRvz2LL3mL0YyS1btqB///549NFHUa9ePbRp0wZvvvkmjhw5YmaXnp6OyMhItG3bFtnZ2fjss8/QuXNn1K9fHy1atMA777yDhISEPOMnJSVhxowZ6Nq1Kxo0aIB69eqhQ4cOePfdd5GYmGjtstll9erViIyMxJAhQ2za9OjRA5GRkTh48KDT40skKtIjKZEUA2rXro3/+7//w7x58zB58mQsWrQIgCJGJkyYgJycHEydOjWPJygnJwdvvPEGYmNjER4ejpdeegk6nQ4HDx7EZ599hp9++gkrV65EuXLljL/zySefYP78+ahQoQKeffZZBAUF4cyZM9i8eTP27duHBQsWoEOHDnnm+M033+DPP//Ev/71L1SvXh2AIt4GDhwIPz8/dOnSBaGhoUhJScGOHTswdepU/P333/jggw/sHrvBYMAPP/wAb29vvP3223Zty5Urh9jYWJQuXdps+/Lly/Hee+/Bz88PnTp1QlhYGK5du4atW7di9+7dmDRpktlS7HfffYeJEyfC19cXTz75JCpXroyTJ0+iT58+eOyxx6zue+rUqVi+fDnKly+P5557Dn5+fvjzzz+xbNkybN26FStXrkR4eLjRfty4cdi0aRNCQ0PRu3dvlClTBocPH0b//v2thi88KNWrV8e+fftw9erVPO9Zu3aAIgi3bNmC8PBwdOvWDUFBQTh16hQ2btyIrVu34ptvvkGDBg2MsYfff/89jh8/jqeffhp16tRBnTp1AACJiYno3bs3Ll68iKZNm+KJJ55AcnIyduzYgUmTJuHgwYOYM2eOcb/r16/HmDFjULFiRTz99NOoUKECDAYDtm7dilGjRuHChQsYOnQoAG3usVmzZuHzzz9H+fLl0aVLF1SsWBHnz5/Htm3bsGPHDsybN8/qPa/OvWPHjvD29sa2bduwadMmXLhwAatXrzbapaamon///jhx4gSaNWuGrl27Ijs7G3v27MHKlSsRFxeHDRs2OBWO0bVrV7z//vvYvXs3EhMTUb58ebP3L1y4gKNHjyIsLAyPPvooPa5EkgchkUiKBZmZmaJ79+5Cr9eLjRs3CiGEmDNnjtDr9WLMmDFWf2fZsmVCr9eLQYMGiYyMDOP2nJwcMWnSJKHX68XUqVON2+/cuSPq1q0rHnnkEXHp0iWzsb766iuh1+vFs88+a7b9+eefF3q9XnTo0EHcvHnT7L033nhD6PV6ceDAAbPt6enpomfPnqJ58+bixo0bdo97y5YtQq/Xi379+tm1s8Xly5dF3bp1RcOGDcXp06fN3jt9+rSoX7++qFevnkhISDDO7dFHHxV6vV788ssvZvabNm0Ser1e6PV6sWjRIuP22NhYodfrRffu3UVycrLZ7yxatEjo9XoxePBg47YjR44IvV4vWrVqleecTZw40biP33//3eHx7d69W+j1etG7d2+7dsOGDRN6vV4sW7bMSsOCrQAADrVJREFUuM3etfvhhx+EXq8XTz31lEhNTTV7b+3atUKv14tnnnnGbPvw4cOFXq8XmzZtsrrvhQsXmm1PTU013tM//vijcfuzzz4r9Hq9uHDhgpl9cnKyaN++vWjfvr1IT08XQjh3j6nnasCAAUa733//Xej1etG6des89+KBAwdEZGSkeOyxx4z7u3fvntDr9aJOnTriueeeM7vet2/fFo0aNRJ6vd7sXlu+fLlxvzk5Ocbt2dnZxuP/5ptvjNtPnz4t9Hq96Ny5s91to0ePFnq9XnzxxRfCkoULFwq9Xi8+/vjjPO9JJM4gl7YlkmKCl5cXPvjgA3h7e+P999/H/v378cUXX6BSpUoYP3681d9ZtWoVAGDMmDHw9vY2bvfw8MDIkSON2eDZ2dnGfXz11VdYtGgRwsLCzMZSYy9tLe927NgxT5KPukyr0+nMtvv4+GDlypU4dOhQHk+KJRcvXgQA1KpVy66dLTZt2oTMzEw888wzqFmzptl7NWvWRKdOnZCRkYFt27YBAA4fPoxbt26hbt26aNasmZn9k08+iRo1auTZh3qehw8fnser9Oqrr6J8+fLYvXs3DAYDAGD79u0AgGeeeSbPORs2bJjmHsnr169j37598PT0ROvWrfO8b+3arV27FoASo+vr62v23rPPPouHHnoI//zzD06fPm133waDAdu2bUOFChXw2muvmb3n6+uLYcOGAQDWrVtn3K7eN56e5o+wsmXLYtu2bdi5cyd8fHzMbPN7j6n77devXx67li1bonHjxrh582aesI7s7GwMGzbM7HoHBASgSZMmAIBz584Zt0dHR+Pzzz/H+PHjza6tp6cnYmJiAAAnTpywOUdb9OjRA0DutTLlhx9+AKBcK4nkQZBCUiIpRqgxUUlJSRg4cCAyMzMxbdo0BAQE5LFNTU3FqVOn4O3tjVKlSuHSpUtmr9u3byM8PBx37tzB+fPnAQBlypRB8+bN0aZNGwBASkoKrly5gkuXLhkTKbKyspCVlZVnf+oypint2rUDoIijxYsX48yZM8b3vLy4yJvU1FQAyCNmWP7++28AMD7gLWnQoAEA4NixYwCAU6dOAQAeeeQRq/YNGzbMs02t9xgYGJjnPF+9ehW1atVCTk4Ojh49CgBG8WXtnFWoUAGhoaH08alkZGTk2fexY8ewdu1a9OnTBykpKejbty+qVauW53etzcPeefPw8DCWElKPyRZHjhyBEALVqlUz3kumr0qVKpntD8i9b/r164elS5fi0qVLxvcs75sHvcfY+8PacVq7R/z9/QHkJh4BSvxuVFQUatasiezsbNy8edN4/KoANrVnefTRRxEeHo5Tp07hzz//NG4/c+YMTp48icaNG9stGSaRMMgYSYmkmPHaa69h69at+Oeff9C9e3e0bdvWqp3BYIAQApmZmVbju0y5ceOG0dP2zz//YN68eThw4ADS0tLoeQUFBeXZNnDgQKSmpuLLL7/E7NmzMXv2bFSoUAFt2rRBz54983j8rKE+mO/cuUPPxRTVC2htfgCMnrikpCQASlIIYDvz2Focqvo7zz//vN25qEk3zD4uX75sdyxL/v77b5vXOTAwEKNGjbKZ1W15bkyPyVYpKcvzZoubN28CAH755Re792FiYiKEEPDw8MD48eORnZ2NNWvWYNq0aZg2bRrCwsLQtm1b9O7dG7Vr1zb+3oPeY+r9kZ/jtHZPqR5HIYTZ9tWrV2Pp0qU4deoUnWTmCA8PD3Tv3h3z5s3DmjVrjF9y1KQnV5Z6kpQcpJCUSIoZXl5eqFOnDv755x+7BZ/VB5qvry9mzZpld0x12fjkyZPo3bs37t69i1atWqF9+/YoX748fHx8kJmZieHDh9udlzXeeustvPzyy9i9ezf27duHAwcOYN26dVi3bh369u1rNdPcFFXgOvJ82cLRMrH6ULcUALZ+z1IEmNrNnj07T6KPKaoAcnYfDDVr1sSIESPMtnl5eaF8+fKoXbu2Xe+cvfcsBZHlHB2dX/X9Ro0a2SycbrovDw8PeHt7Y+rUqcZEsf379+Pnn3/GypUrsWrVqjyi+EHuMVvCz9njtMe8efOwYMEC+Pr64oUXXkD9+vXh7+8PT09PxMXFGUMj8kP37t3xySefYPPmzfj3v/+NUqVKYfPmzShVqhS6du2a73ElEhUpJCWSEkpISAg8PT1x9+5dtG3b1hhTZo+vvvoKd+/exfPPP49p06aZvff/7d1/TMx/HMDxZ9q6r4q6q3Xy6w+z2DB/pKyNKaGfco6SH/2h3ZrJzDL+QGzM5sfC5McQ/yihMqcaN5pqyRYyP2JZCxVjiZBVp7rvH+0+1F2/Tvt+t7wef97Pz316t3vd6/16vT72RtgMllqtRqfTodPp6Orqori4mF27dpGZmUlERES/WaM5c+agUqmoqqqitrbWbo3i76xbqdbsjDWjZM2M9WbNSFlnK1rLBPoaw9P7dZycnPDy8uLTp0/MnDnT7tZxbwO9hyPjYDw8PFi0aNGQn2fPqFGjUKvVfP78maamJrtXgul93vpirTt0cnIa8vFptVri4+OJj4/HbDZTWFjI3r17SUtLIzw8vEcdr6NrTKPR8O7dO5qamuzW4Q72c/alvb2dCxcuAHDu3Dmb4/h9jJIjxo8fT1BQEPfu3aO0tBRfX19qa2uJiIiwW/IixFBJjaQQf6nRo0fj5+eHxWKxO/8RukeE/J6Jsdai2fvC/33+4GA1Nzfz/v37HrdZGwzWrFkD/LoaSl/GjBnD8uXLsVgs7N+/v99s3ffv39m6dStxcXFUVlYCKLV8jx49svucx48f93ictSGnr+YHe9e/tgat5eXldp9TX1+vNDTBryyrvfdoaGj4o6B9uPR33rq6upT5igNddnHmzJk4Ozvz8uVLu9vDHR0dPWogoftHS+9z4OLiwvLlywkPD6ezs1M5d3+6xoa6PoaqsbGR1tZW1Gq13WDWkf+r3qxNNwUFBeTn5wOyrS2GjwSSQvzFrDV7x44dU2rerO7fv09YWBgGg0G5zdr40Lsz++nTp2RkZCid34OpV/zy5Qvz58/HYDDw/ft3m/utTRG+vr4DvlZKSgoTJkygrKyMLVu2KFmi3719+5aEhATq6urQ6/VK80RMTAwqlYqCgoIejRjQvV1eVFSEu7s7YWFhAAQEBODq6sqTJ09shlHn5eXZBD3w6zyfO3fO5v7q6mpiYmJYunSpEgQHBwcDYDQabc5Nenr6gOfjv2D9TBkZGTa1spcuXaKxsZGAgIABmzk0Gg2LFi2ira2NQ4cO2fwQOHXqFKGhocps1FevXjFv3jxSUlIwm809HtvZ2cnr16+B7nUzHGts5cqVODk5kZWVZZMJvnv3Ls+ePWPixInMnTu338/ZFx8fH5ydnfn69SsfP35Ubu/q6iI9PV2ZSuBoDTB0T1QYO3YsJSUlFBYWKjWiQgwH2doW4i+2evVqSkpKKC0tRa/XExkZyejRo6murqaoqAg3N7cedY8rVqwgPz+f9PR0Ghoa8PX1paamhjt37pCWlsbp06d5/vw5O3bsIDIykpiYmD7fW61WYzAYOHXqFFFRUYSGhqLVamlvb+fhw4dUVFQwe/Zspeu2Px4eHmRmZrJp0yZMJhNlZWUEBwczZcoUzGYzNTU1lJSU0NHRQWJiItu2bVOe6+PjQ2pqKqmpqcTHxxMREYFWq6W+vh6TyYTFYunR+e7q6kpycjKHDx8mMTGR8PBwtFot1dXVlJeXo9frbcathISEEBcXx9WrV4mNjWXp0qV4enry5s0bTCYTnZ2dbN++XRlnExgYyIIFCygpKUGv1xMSEoJKpeLBgwe0tLQQGBhIRUXFkP7Ww23x4sXodDquX7+OTqcjJCQENzc3Xrx4QXFxMV5eXuzdu3dQr7Vz506eP3/OtWvXqK2tZf78+fz8+ZOKigoqKyvx8/Nj1apVAPj5+bFs2TKMRiPR0dEEBwfj7e1NS0sLZWVlVFVVsWTJEqXT/E/X2IwZM9i4cSMnT55Ep9MRFhaGWq1W1r2rqysHDx60GS80WC4uLkRHR2M0GklISCAqKgqLxUJpaSk/fvzg6NGjrF27lvLyco4cOUJkZGSPUV2DoVKpiIqKIjs7m9bWVhITEx0+XiF6k0BSiL+Ys7Mzp0+f5vLlyxiNRrKysvj58yfe3t7ExMSQlJTU40omQUFBHD9+nDNnzpCfn49KpWLWrFmcP3+eOXPm4O7uzs6dOykvL0ej0fQbSEJ3E4Sfnx+5ubncvn2b5uZmPDw8mDBhAikpKSQkJAz6S3P8+PHk5uZy69Ytbt68SWVlpTKP0dfXl9jYWBISEmxmRUJ3dm3SpElcuHABk8lES0sLnp6eSjbLOuLFymAw4O7uTlZWFkajkX/++YfZs2dz8eLFPgO8ffv2ERAQQE5ODteuXVO2M4ODgzEYDDZbo8eOHePEiRPcvHmTS5cuKcezbdu2PueC/tcOHDiAv78/ubm55OTkYDabGTduHGvXriUpKUnJYA9Eq9WSl5dHRkYGRUVFnD17FovFwqRJk9iwYQMGg0HpzofuS2L6+/tz48YNCgoK+PbtG2q1msmTJ7N7924l6IThWWObN29m2rRpZGZmYjQaaWtrw8vLi+joaJKSkgasyx3Inj170Gg03L59m/Pnz+Pt7U1oaCjJycl4enqyfv16cnJyuHLlCv7+/nZrUgei1+vJzs4GYNmyZX90vEL8zsnSVyuaEEIIIUaEb9++ERQUxPTp08nLy/u/D0eMIFIjKYQQQoxw2dnZdHR0sG7duv/7UMQIIxlJIYQQYgSrqakhLi4ODw8PTCbToEZ9CTFYUiMphBBCjECZmZnU1dWRm5tLW1sbR48elSBSDDvJSAohhBAj0MKFC/nw4QNTp05l69atg5qAIMRQSSAphBBCCCEcIs02QgghhBDCIRJICiGEEEIIh0ggKYQQQgghHCKBpBBCCCGEcIgEkkIIIYQQwiESSAohhBBCCIdIICmEEEIIIRwigaQQQgghhHCIBJJCCCGEEMIh/wL+6WBVzUDaZwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 700x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "a3, b3 = np.polyfit(years_pro, annual_salary, 1)\n",
    "years_pro_range = np.arange(1, 51, 1)\n",
    "pred_years_pro  = a3*years_pro_range + b3\n",
    "\n",
    "plt.scatter(years_pro, annual_salary, color='blue')\n",
    "plt.plot(years_pro_range, pred_years_pro, color='red')\n",
    "\n",
    "plt.title(\"Annual Salary Impacted By Years Coded Professionally\")\n",
    "plt.xlabel(\"Years Coded Professionally\", fontsize=16)  \n",
    "plt.ylabel(\"Income\", fontsize=16)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Annual Salary Impacted By Years Coded Professionally Analysis\n",
    "We ploted a developers annual salary versus the number of years they have coded professionally and found that, the more years you have coded professionally will lead to an increase in annaul salary. This is becuase, gaining more experience, in this case coding professionally, will give you advatage over those who had less years coding professionally. Looking at this graph we can see that the average amount of years coded professionally ios around 10-15 years."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Annual Salary')"
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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s1atXwuv+/fts165dzMHBgQ0dOlT0Wfvyyy+ZUqlkt27dEunir3Xu8ZabNWvWMKVSyRITE1l2djbr27cva9WqFXv69KlILvdnjt9P3Tl17txZ1Jf8eTVv3lz4zDPG2PHjx5lSqWRNmzZl//77r9D+xx9/MKVSyaZPn65yvE6dOrF3794J7enp6axjx47MxsaGvXz5kjGm23XLy7a8ePv2LXN2dmbt27dX+Sz+9NNPTKlUss2bN0vqp9zMnDmTKZVKdv36dbXbo6OjmVKpZEOHDlXZZ8SIESryXbp0YXZ2diwxMVHUfuLECaZUKtm8efOEto8//pg1a9aMxcbGCm3v3r0T7tU5j8mfU5cuXYTPD8/WrVvZoEGDRHoYY2zZsmVMqVSy0NBQFduHDx8ukh09ejRTKpVs4MCB7P3790L7ggULRN8FjMl378k5tnm7fH19WWZmptB+8+ZNplQq2eDBg4W2RYsWMaVSyfbv3y86ztdffy3c07TB9+fRo0e1yh48eJANHTpUZTwFBQWp9AOv183NjaWmpgrtT548Yc2bN2ceHh5C27Zt25hSqWQrV64U6d2wYYNwHvw44j8za9asUbFv7ty5KuNd6v06MzOTtW7dmrVs2ZK9ePFCkHvx4gVr166dynVatGgRa9q0Kbtx44ZI76NHj1jLli1Z9+7dhbbu3bszJycnlpWVJZI9cOAAGzt2LEtKSlI5l5xo+2zmZOzYsczR0ZElJCSI2qOjo1mzZs3YZ599JrTl53qq+9zx31/jx48XtfOf9Zz3Ul367dtvv2VKpZIdPHhQJLt9+3bJ4zsnpTbEgl+cV79+fbRp0wYAYGBgAF9fX7x48QKnT59Wu5+TkxNsbGxEbfz/T548EbV/8MEHwq8cHltbWwAQPRbThRkzZiAoKAgmJiZ4//49Xr9+jZSUFDRo0AAA8vWo4IMPPsCePXvQqlUrREdH4/vvv0evXr3g7OyMsWPHIjg4WOXXlaurKwICAtC9e3cAwJs3b5CSkiLMVj148ED28+jSpYvo/65duwozQzk5fvw4AMDX11eHXlClV69ewt/GxsawtLQEAPTu3Vsk17RpU2RlZSE5OVnUXq1aNXTu3FnU5uPjAwC4fv260LZkyRJs3boV5cqVQ1ZWltAXjRo1AvBfX8THxyM6Ohru7u6oWrWqyLbNmzdjx44dGs/nxIkTALhH2ykpKcLrzZs38PHxQWZmppC2KyIiAgDQrVs3kQ4bGxs0b95c43FyExISAmdnZ+Hl5eWFb775Bm5ubli9ejWMjIwE2X79+gGA2mtqYmIi9J8UypUrhwULFiA1NRVLlizRyWYpODk5iWaj+Jlwe3t7WFlZqbSr+8z37t1b9CTJ2NgY3t7eomuhy3XjsbOzkzRTFhkZiVevXqFLly7CEw0e/vNz9uxZrXo0kZaWJrI7KSkJJ0+exMSJE6FQKFRCtwCoxKzHxsYiNjYWrq6uKpkzfHx8YGJiItj54sUL3L59G3Z2dsJnFuBmq4cNG5annR07doSxsbGobeTIkQgKCoKlpSUYY0hNTUVKSorQt+rucz179hT9z1//3r17i2b1NI2Lgt571DFw4EAYGv73UNjGxgblypUTHT8iIgIKhULlcy/3GgGenj17IjAwEC4uLgAg9C8/y6iuf319fVG5cmXh/zp16sDU1FTlPACorCcaNmxYvp7c5kTq/To6OhovX76Eu7s7atSoIexfo0YN4T6Xk5MnT8LKygoffvih6PNSsWJFtGrVCjExMUL4hKGhId68eYO//vpLpMPX1xebNm3S+tRIKmlpaQgPD0fLli1RvXp1kV316tVDkyZNRCFS+bme6j53PEOHDhX9r85/0qXfLl++DENDQ5Xv5T59+uRrxr3UhlicOnUKycnJGDJkiKhjevfujXXr1mH//v1qVwOry+LAX9ysrCxRO+/s5YT/cOaWlUpqaiq2bNmCo0eP4uHDhyrxY7n/l4pSqcTu3bsRGxuLCxcu4Nq1a7h69SrOnj2Ls2fPYv369diwYYPIOTpx4gR27dqFP//8UyX+S5sd+TmP3F+MlStXRpcuXXDgwAH8+eefwofnxIkT+PDDD+Ho6KhTH+REoVCoPMrnHbncNx++PfcjSEtLSygUCrXn8OzZM6HtyZMn2LJlC06ePImnT5+qPALm++LOnTsAoNbxyemQ5UVcXBwAwNvbO08Z/gbGx+epO5alpaXKjVkTnp6e+OSTT4T/3717h4SEBOzbtw9dunTBsmXL4O7uDgBo3bo1GjZsiKNHj2LmzJkwNjbGixcvEBkZiT59+ogeRUvBxsYGgwYNwu7du9G3b1/hxi0HuccjPw5yP0LM6/4AQG32htzOly7XjUdqGAyvW12oRI0aNVC9enXcvXtXkq68yHntc2JpaYmNGzcKExQ5yd23/LoQdXYqFArhUem7d++EvlB3/829WFDTMQHuM71jxw6EhoYiISFB5Rqqu0/l7ntt943cOuW496gj93dXuXLlYGhoKDp+UlIS6tSpg0qVKolkGzRogBo1akhyxHWBMYb9+/dj3759uHPnDjIyMkTb1fVvXt/BOc8jrzFQuXJlNGnSBH/++We+bZZ6v9ZlHKakpODp06d4+vQpnJ2d8zz2w4cPUa1aNYwbNw6ff/45BgwYgLZt28LV1RXt27eXPUacH/Pnz5/XaNfr169hYmKSr+upKVVk7r7L7T/p2m/3799HnTp1VL5HTExMULduXTx+/DhPHeootQ7y/v37AajPF1ujRg1cunQJiYmJKg5CztkubeT1qyi/MMYwZswYXL16Fa6urpg0aRLq1q0LhUKBo0ePCudUEKysrGBlZYXhw4cD4GIZAwICcPToUUyZMgUnTpyAQqFAcHAw5syZAzMzM0yePBlWVlaoWLEiXr16pTW1WH7PI+esAU+/fv1w4MABHDx4ELa2toiLi0NMTAy+/PLLAvWDQqHIM5Zb6nXN/SUDQIhX5HP0vnv3Dn5+frh79y66deuGjh07okaNGihXrhy2b98uWqDE/wjRZQzmJC0tDQYGBti+fXue58bfrPjFJurOVVcntW7dumodU19fX/Tp0wfTpk3Dr7/+imrVqsHAwAB9+vSBv78/zp49i06dOuHUqVPIysrK9xOBKVOm4NSpU1i4cCEOHTqU7/7LTV56dNGvbkzzXwL89dblumnSq460tDQAeWelqFChgsZ80lKYN2+e6IeAoaEhTE1NNX4x5rafj1PWZCfAnQ/fb+pkc8+SazomAHz11Vc4cuQI7O3tsWDBApiZmcHIyAgRERGiWNOc5HV/kDou5Lj35Hffd+/eoW7dumq3mZiYyO4gr1q1Cps2bYKVlRVmzZoFCwsLlC9fHv/++y+++eYbtftIOY+3b9/CyMhINGPOo2kMaEOX+zV/D1U3DnPHrfOfw6ZNm2L27Nl5Hp//8eXj44O9e/di27ZtOH/+PC5evAiAm+j6+uuv1f7ozA/8545P/5oX/D0rP9dT071K27XWtd80jW9dv9eAUuogx8XFCY8Ffv755zzlfv75Z3zxxRdFZZYKuWdlb968iatXr6J169bYsmWL6CZ64cKFQrGhRYsWWLFiBR4+fIirV6/i7t27sLKywrZt26BQKLB9+3Z8+OGHgjw/I6UJOc/D0dERjRs3xvHjx/HVV1/h+PHjUCgUKo85iwN1K5pfv34NgAu/AIAzZ87g7t276NGjB5YtWyaS3bdvn+j/WrVqAUC+HZbKlSuDMQalUinoygv+ZpF7BgCA2kVV+aFKlSrw9PTE9u3bcePGDSGLSu/evbF69WocPXoUnTp1wokTJ2Bpaalx9k8TVatWxfTp0zFz5kxs375d58fFhVk8KPdnPGcbfw10uW66wv+I479ocvP27VvJznZe2NjY5Pva8fA2aLKTl+O/VNVdt9TUVMnHfPLkCY4ePYpGjRph586doi9QdZmOSgPGxsZqP/OAbn0nhaysLAQGBqJatWrYtWsXatasKWzLywap8DPK79+/V/mxoct55B5DutyvNY3D3PdQfnxnZmZKfsrVokULrFq1CpmZmbhx4wZOnTqFvXv34tNPP8WxY8dkqVnAO/LlypXTaldhXs+80LXfKlSokOf9PD/fa6UyBpmfofT390dMTIzK6/r166hcuTJCQkLyHbIgFX5WQd2NP/ejTf6xt7pME1FRUfk6/osXL7B8+XKsX79eoxw/28N/ed+/fx9mZmYi5xjgsixoQ+7z6Nu3L54/f47ff/8dx44dQ7t27YTV7MVJfHy8yuO3xMREABB+xfJ90b59e5FcVlaWSro8/ldwzjSBPNeuXUNwcLDGGR5+Fk9deeCUlBTRI0r+US5vb07UHT+/8DM8OW9adevWhbu7O86ePYu4uDhERUWpxF7qSq9evdC6dWts2LBBbXw7b0fuz+G7d+9kr/aXE3Vpkvg0gPzTK12um67wuvlUjzl59uwZXr16JYrjLS74ECJ1dmZlZSEhIQHm5uYoX7688NlXF++oLntAXjx48ACMMTg5OanMLuX3fqvv8LG8uR2axMREUco/OUhOTsabN2/QtGlTkTMFSPse0YSpqSkYYypj4O3bt0KoGk9en30g7+9gKfdrXcahiYkJTE1NkZCQIKS9zImmvjcyMoKzszPmzJmDGTNmIDMzs8DrBngaNWoEIyMj3Lp1S20YT067CvN65oWu/VavXj08ffpUZWIiOTlZFPYolVLnIPOL86pXr57ngp9KlSrh448/xpMnT2QbaHlRo0YNGBoaIiYmRuRMPXjwAL/99ptIlp89yv0FHxISIszcqpuR0kSVKlVw8OBBbNy4Mc8ct/Hx8Th37hxq164NpVIJAKhduzZevHghmiV9+PAhAgMDtdoh93n07NkTRkZGWLNmDeLi4gq8OE8ukpOTVa7hqVOnAPyXA5jvi9x5XDdu3CjMdPB90ahRIzRu3BiXL18WzWBlZWVh/vz5+O6774Rf1PwPj5yOJ7/IMSAgQJQbmDGGadOmwcPDQzgmH8+VM78ywC0uVOek5IfXr18LITv29vaibX379kV6ejpmz54NAwMDWZ4IzJs3D1lZWVi8eLHKNj7V4T///CNq37Vrl6Q8yvnl0KFDImfk7du3OH36NIyNjeHk5ARAt+umK61bt0bNmjVx/Phxlfype/fuBQCVBS3FwYcffghra2tcvHhR5UfbkSNH8ObNGyGlo6mpKerXr4/r16+Lfty8e/dOuD9JIa/P5uXLl4VH2rreb/UdR0dHZGZmqty3pKSR0xX+u4//IcITExMj5PfOb//y60/4Ba48O3fuVNHJT1bk/uzfvHlTxZHV5X7dvHlzVKhQAefOnRPNTiYnJ6vN5dulSxdkZWUJudR5Xr58iV69euHTTz8FwKVY7d69O1auXKmig5/xlSu8s0KFCujQoQOSk5Nx8OBB0bbExER4eXkJ1UoL83pqQmq/Adz3WlZWlsr4zm94aqkLsTh16hRevnyJESNGaBxE/fr1w759+xAcHKxxcUxBMTY2RufOnXHs2DFMnToVHh4eePLkCXbt2oXOnTuLCgE4OjrCzMwMR44cgampKT788ENERkbi8uXLmD9/PqZOnYrQ0FDUqFFDJeODpuMvX74c48aNw6hRo+Dt7Y127dqhWrVqePXqFaKjo3H8+HFkZmZi7dq1wox3ly5dsHXrVkyaNEn4MbFz507Mnj0b33//PaKjo7Fnzx615WjlPo+aNWvCy8sLp06dQrVq1VQyhxQXNjY2WLhwIa5fvw6lUomYmBjs3LkT9evXFxw+Dw8PVKpUCdu2bYOxsTHq1KmDM2fO4P79+5g8eTIWLVqEXbt2CbJz5szB6NGj8cknn2DUqFGoVKkSjhw5gtu3b2Pu3LnCmOZn/OfPnw9LS0uMGDEC3t7e8PHxwa+//ooRI0agZ8+eyMrKwrFjx/D7779j3Lhxwg3Wx8cHlpaWwo3DwcEBSUlJ2L9/P9q0aSOsEpfC/fv3RY52ZmYmkpKSEBoaivv372P69OkqM/4dOnRAnTp1cP36dXh4eMjyRKBJkyYYNmwYtm7dqrLN29sb3377reAImJmZ4dq1a4iIiICjo6Mo64icmJqaYsCAAejVqxeMjIxw4MABJCUlYcyYMTgBSSIAACAASURBVMK10OW66YqxsTHmzp2LL7/8EkOGDEHfvn1hYmKCP/74A8HBwXBwcFC74r44mDdvHj755BMMGzYMgwYNQp06dRATE4OgoCA0aNBAVDRo5MiRWLRoEUaOHCnkcA0ODoatrS2io6MlHc/c3BwtWrRAZGQkFi9eDDs7O0RHR+PQoUP44YcfMHbsWPzyyy9QKpWS77f6zrBhw3Ds2DHMnz8fcXFxMDMzw9mzZ5GcnIxGjRrptGDzjz/+UFmkzOPo6AhTU1N07NgRJ0+exLRp0+Du7o6EhAQEBQVh+fLlGDt2LC5fvoyQkBBRsSMpDBgwAAEBAVizZg1evnwJKysrXL16FVeuXIGzs7PoCYCFhQUcHR1x+fJlLFiwAA4ODkhMTERQUBA++ugjkZOt6/168ODB2LZtG0aOHIkePXoIYQgeHh4qTvK4ceNw+vRpbN68Gc+fP4ezszOeP3+OvXv34vnz50JxG1NTU5iZmWHTpk1ISkqCi4sLKlSogPj4eAQGBqJOnTqSy43//vvveT4ha9++PUxMTDBjxgxcuXIFCxcuRFxcHJo1a4akpCTs3r0bBgYG6N+/PwBuJr6wrqcmpPYbwI3v0NBQLFiwAHFxcTA3N8etW7dw+fJlncc3UAodZD5OSNtN387ODs2bN8f58+cL9RErAMyZMwfly5fHhQsXcObMGVhZWWHu3LnIyMgQOcjly5fH5s2bsXjxYiEmrm3btti9ezfq1q2LI0eO4NKlS9i0aZNON+w2bdrg6NGjCAwMFGZH3r59i4oVK8Lc3Bx9+vTB0KFDRQsWJ02ahIyMDPzyyy9YuHAhmjRpgoULF8Lb2xtpaWlYunQp/P391a7SL4zz6N27N06dOoWPP/5Y9sWR+aVGjRr47rvvsHTpUuzZswcGBgZwd3fH7NmzhdjP2rVrY/PmzVi2bBk2btwIExMTdOjQAYsXL0a5cuVw7NgxREREwNDQEB4eHmjbti0CAwOxbt06rF69Gu/evUOTJk2wdu1aUVGUTz/9FLdu3cLRo0dRp04dIb3VqlWrsGPHDhw6dAgLFy6EgYEBlEolli9fLqTsA7jHdtu2bcP333+PY8eO4dChQ2jatCmWLl2KyMhInRzkixcvCjNuvG5TU1MolUrMnTsXrq6uKvsYGhqie/fu2LZtm6xPBCZOnIjjx4+rVOOrUaMGfvzxR6xYsQJbtmyBkZERXFxcEBAQIBTsKAy++OILXLx4EYGBgXj06BFq166NSZMmYdy4cSI5qdctP3Tt2hXVqlXD5s2bsWbNGmRkZKB+/foYM2YMxo4dqzefp1atWiEoKAjr1q3DTz/9hLS0NNStWxf9+/fH+PHjhbh+gEsPlZ6eLnw5169fHwMGDEC3bt0QHBwsqZiSgYEBVq1ahUWLFuHw4cM4cuQIHB0dERAQAKVSiQEDBuDw4cPw9/fXKf2gPmNjY4P169dj1apV2Lx5M6pVqwZvb298//336NOnj05FqAICAoQiELlZv349TE1NsWDBAhgbG+PixYs4e/YsbGxssG7dOrRq1Qrjx4/H1q1bsWzZMrRs2VKn8zA1NcX27dvxww8/IDAwEJUrV0a7du2ESRwAIud9xYoV+P7773Hq1CnhXrdmzRpcv35d5CDrer+eOnUqFAoFDh06hCVLlqBhw4aYOHEiGjZsqDIOq1evjv3792P9+vUICwvDwYMHUbFiRbRs2RJLly4VxfHzn4ETJ07gzJkzeP/+PT744AP07t0bo0aNEqWV04S/v3+e2w4ePIhmzZqhQYMGCA4Oxvr163HkyBHs3LkTJiYmaN++PcaPHy/KoFRY11MTuvSbpaUltm7diuXLl+Onn36CsbExWrdujZ9++gkzZ87U2UE2YLmDKAlCD9m8eTP8/f1x5MgRIQykuLh//z68vb3h6uqqdraSkMaoUaMQExODsLAw2TJPEGWbmJgY9OjRA126dMGqVauK25wShYuLCxQKBS5dulTcphQIX19f/P3337h+/XqeWVEKmzNnzmDcuHH49NNPMX369GKxgSg4pS4GmSh9PHr0CNu2bYOrq2uxO8eEPJw/fx4XLlzAsGHDyDkmdCYwMBDDhg3DvXv3RO38Ezl+DQAh5vLlyxgzZoxQbInn3LlzePnyZYnpt3/++Qfjxo1TmcG+c+cOoqOj0bx58yJxjletWoURI0YI2Yt4aByWDkpdiAVReoiIiEBsbCy2bduGjIwMzJ8/v7hNIgrI8ePHhWtqbW2dZ5EJgtBEgwYNcOXKFYwcORJDhw5F9erVhUwvDRo0KHBWlNKKpaUlbt26haioKNy+fRuWlpa4d+8eduzYgfLly4vivPWZhg0bIjY2FufPn0dSUhJsbW3x+PFjwWGePHlykdhhZmaGjRs3YujQoejfvz8qVqyI8PBwnDhxAo6OjkKBJKJkQiEWhN4yatQoXL58Gc2aNcO3334rlG4tbijEIv/Y2dnBwMAAHTp0wDfffIPq1asXt0lECeXy5cv46aefEB0djZSUFNSuXRvu7u6YPHkyateuXdzm6S13797Fxo0bERkZiadPn6Jy5cpwcnLChAkThGqlJYGnT59i48aNOH/+PB4/fozy5cvD1tYWY8aMQbt27YrMjhMnTiAwMBCxsbF48+YNzMzM0LFjR0yYMCHfi2sJ/YAcZIIgCIIgCILIAcUgEwRBEARBEEQOyEEmCIIgCIIgiBzQIr0SQKtWrZCRkSFUAyMIgiAIgihMnj59CmNj40IrJa3vkINcAkhPT0d2dnZxm0EQBEEQRBkhKysLZXmZGjnIJQC+lvzp06eL2RKCIAiCIMoC3t7exW1CsUIxyARBEARBEASRA3KQCYIgCIIgCCIH5CATBEEQBEEQRA7IQSYIgiAIgiCIHJCDTBAEQRAEQRA5IAeZIAiCIAiCIHJADjJBEARBEARB5IAcZIIgCIIgCILIATnIBEEQBEEQBJEDvXaQDx48CF9fXzg6OsLT0xNz587FixcvhO137tzBp59+CkdHRzg6OmL06NGIjY0V6UhJScHXX3+Ndu3awc7ODr1790ZYWJhIhjGGzZs3o2PHjrC1tYW3tzd+/PFHFXtOnz4NX19f2NnZoU2bNpgzZw5SU1NFMnLZRBAEQRAEQRQPeusg79ixA1999RV69+6NQ4cOYeHChQgPD8fkyZPBGENycjKGDRsGhUKBgIAABAYGwtDQEMOHD0dKSoqgZ+LEiYiKisLSpUtx8OBBuLu7Y8KECbh69aogs379emzYsAETJkzAkSNHMGnSJGzYsEHkJEdERGDixIlwdXVFaGgo/P39ERUVhSlTpggyctpUlFy9ChgY/PfKrxnz54v1zJ+ff5s++kis66OP8qfH3l6sx94+f3rMzcV6zM3zp8fDQ6zHwyN/egDg44/Fuj7+OH96tmwR69myJX96jh0T6zl2LH96Ll8W67l8OX96AODePcDEBFAouPd79/Kn59UrwNUVaNCAe3/1qnj1ZGQAq1YBkyZx7xkZ+dMjp67sbODsWWDPHu49Ozv/NhGaob4miCKA6SHv379n7du3ZzNnzhS179+/nymVSpaQkMDWrl3L7O3t2atXr4Ttr169Yvb29mzTpk2MMcYiIyOZUqlk4eHhIj0DBgxgI0eOZIwxlpaWxhwcHNiKFStEMitWrGBOTk7s3bt3jDHG/Pz82IABA0Qy4eHhTKlUsmvXrjHGmGw25cbLy4t5eXlp6LH8A+T9Kg49+miTvunRR5v0TQ9jjBkaqtdjaKibHisr9XqsrIpHz/TpjCkUYh0KBdeuK3LpOnCAMXNzsR5zc66dkBfqa6KoKEzfoySglzPIBgYGOHr0KGbPni1qr1u3LgDg2bNnuHDhApycnFC1alVhe9WqVdGiRQucP38eAHDhwgVUqFABbdq0EelxdXVFREQEMjIycO3aNaSlpaFDhw4iGTc3N6SmpuLatWtIT0/HlStXVGRcXFxgbGwsOp4cNhUVBgYF2y63Hjl1lVY9cuoqrXoAwMgIyMpSvy0ri9suhcaNgVwRUgKxsdz2otQzYwawbJnqjGF2Ntc+Y4Y0PXLqCgkB+vYF7t8Xtyclce0hIdJtIjRDfU0QRYdeOsgAUL16dZGjCQC//fYbKlWqhCZNmiA+Ph7map5zN2zYEHFxcQCA+Ph4mJmZwdDQUEUmKysL9+7dQ3x8PADAwsJCJNOgQQMAQFxcHBISEpCdna0iY2RkhHr16omOJ4dNRYHUMAptclLDKKTISQ2j0CYnNYxCm5zUMAptclLDKKTISQ2j0CYnNYxCm5zUMAptclLDKKTI3buXt3PMk5WlPdzi1au8nVqe2FjtYRJy6cnIAPz9Ncv4+0sLkZBLV3Y28Pnn3Dxmbvi2KVMoBEAOqK8JomjRWwc5N7/99huCg4MxduxYmJiY4M2bN6hcubKKXJUqVfD69WsAQGpqap4yAPD69WthkV1uOV4mNTU1Txm+jd8ul01FQatW8sh98400PVLkTp2Spkub3M2b0vRok0tKkqZHm9z/Hx5oRYqcXA7pmDHS9GiTk8thb9dOmh4pcjY20nRpk+vWTZoebXJy6dmwQbvzk53NyWlDLl3h4aqzmTlhDEhM5OSIgkF9TRBFS4lwkI8fP44pU6age/fuGDt2rEZZpu7ndSHJSKWoj0cQZZm0NHnkpD7M0SYnlx5ts9C6yMml6+FDaXqkyhF5Q31NEEWL3jvIu3fvxpdffomBAwdiyZIlMPh/ICI/i5yb1NRUVKtWTZDJnYaNlwG4+GATExNRGw+vu2rVqkKoR166+O1y2UQQRP6pVEkeuf9HWWlFm5xceqyspOmRIieXLjMzaXqkyhF5Q31NEEWLXjvIwcHBWLRoEaZOnYo5c+agXLn/zLW0tERCQoLKPnfv3oXV/+/qlpaWePjwITIzM1VkjIyM0KBBA1haWgKASuwvH5vcuHFjNGjQAIaGhirHy8jIwIMHD0THk8OmouDKFXnk5s2TpkeKXOfO0nRpk5PrEXv9+tL0aJNzd5emR4qcXI/rN22Spkeb3NGj0vRok7t0SZoeKXJ//SVNlzY5ucJZ5NIzfjyXrk4TCgUnpw25dLm5/ZcCUR0GBoCFBSdHFAzqa4IoWvTWQY6MjMT8+fMxa9YsjB49WmW7h4cHrl+/juTkZKHt2bNnuHHjBry8vAAAHTp0QHp6Oi7l+lY9ffo03NzcYGRkhJYtW8LExARnzpwRyfz222+oXr06HBwcYGxsjLZt26oU8zh37hwyMzOF48llU1HQsqU8cgsXStMjRe7kSWm6tMnlSjaSbzlN8X66yJ07J02PFDm5HFJra2l6tMnJ5bC3bStNjxS5Bg2AXGtgVTA01D5jW62a9hlUKytOrij0GBsDU6dqlpk6lZPThly6FApg9Wru79yOG///qlXanXFCO9TXBFHEFGuSuTx4//4969atGxs0aBB78uSJyis1NZWlpKQwNzc3NnLkSPbHH3+wGzdusOHDhzNPT0/25s0bQdfYsWOZp6cnO3fuHLt9+zZbvHgxs7GxYX/++acgs3XrVmZra8v279/PYmNj2b59+5iNjQ3btWuXIHP9+nXWvHlz9sMPP7A7d+6ws2fPsg4dOrBJkyYJMnLalBPKg6ybrk6dNOvgX506adaTlaWabzT3y8KCkyuK85JTV1CQtD4KCirac6M8yNopKXmQLSwoN29hQH1NFBVlPQ+yXjrI9+/fZ0qlMs/XmjVrGGOM3b17l40ZM4Y5ODgwR0dHNn78eJaYmCjSlZqayubNm8fatGnDbG1tWb9+/VhERITKMbdv3868vb2ZjY0N8/HxETnHPOHh4ax3797M1taWtWvXji1atIi9fftWJCOnTTyFPUivXBHfbK9cyZ+eefPEeubNy79NnTuLdXXuLH3fCROkOX8TJmjWExYmTU9YmHTb3N3F+7q7S983N926iXV16yZ938I4t6NHxfseParrGXFcuiTWc+lS/vQwxlhCAmNVqjBWrhz3npCQPz0vXzLWvj3niLRvz/1fnHrS0xlbuZKxiRO59/T0/OmRU1dWFjdegoK4d6k/HAndob4mioKy7iAbMMZYcc9iE5rx9vYGwIVhENp5+1baQq20NKBixby379kDDB6sXU9QEDBokHT79IHsbKBRIy5Fnbo7AF9OOz6eHtkSBEGURcq676G3McgEkV8qVgR69tQs07OnZucYKN2rximekSAIgiDyhhxkolRy8GDeTnLPntx2bZT2VeO+vsDPP6tm4TA359p9fYvHLoIgCIIobrSs9SYI6WRnc1WcHj7kZlXd3Ip3BvLgQSA1FfDz4woeWFkBgYHA/4sWaoWfZe3bl3OGc4Yi5HeWVd/6yNeXq3K3YcN/fTR+vLRMCARBEARRWqEZZEIWQkK4mFZPTy5u19OT+z8kpHhtataMc5Rv3eLemzXTzSY5Z1n1tY+srIAvvgDWrePerayK1yaCIAiCKG5okV4JQN8D5UNCuFnW3COJn2Utjsf1cttU0JnfstBHBEEQROlB332PwoYc5BKAPg9SPhtCXsUyiiMbgr7ZpG/26KtNBEEQhP6gz75HUUAhFkSBCA/XXEmOMSAxkZMrqzbpmz36ahNBEARB6AvkIBMF4uFDeeXkQN9s0jd7dDlWUdpEEARBEPoCOchEgdDHXMH6ZpO+2aPLsUpijmeCIAiCKCjkIBMFQh9zBeubTfpmj77aRBAEQRD6AjnIRIEorIps2dnA2bNcueezZ7n/i9um/KJv9uirTQRBEAShL5CDTBQYuSuyyZEvWN+qxOmbPfpqE0EQBEHoA5TmrQRQ2KlW5KruJocefctfLDdv3wLTpwN37gBNmgDLlgEVKxafPYB+XX859RAEQRD5p6yneSMHuQRQmIM0JAT4/HNxyi9zc+7xe1HPIJb23LwzZgD+/uJwEYUCmDoVWLq0+OySA7nGkT6NR4IgiLJMWXeQKcSiDMPP1uZ2SJOSuPaiLjesz7l5CxITDXDO8bJlqvtlZ3PtM2bIZWnRI9c40rfxSBAEQZRdyEEuo2RnczN16p4f8G1TpujuCBYEfc3NW9CY6IwMbuZYE/7+nFxJQ65xpI/jkSAIgii7kINcRtHH2Vp9zM0rx6zmhg3SHMQNG/JvZ3Eh1zjSx/FIEARBlF3IQS6j6ONsrb7l5pVrVjMmRtrxpMrpE3KNI30cjwRBEETZhRzkMoo+ztbqW25euWY1HzyQdjypcvqEXONIH8cjQRAEUXYhB7mMom+ztTy+vsC0aUC5XCOzXDmuvSgzGdCspnbkGkf6Oh4JgiCIsgk5yGUUfZut5QkJAZYvV5/tYfnyos1kINesZtWq0vRIldMn5BpH+joeCYIgiLIJOchlGH2rpKYp5penKDMZyDWr6ecn7XhS5fQNucaRvo1HgiAIouxChUJKACWlkl5BOXuWS6GmjbAwoEOHwraGg89iAYgdd10q+2VnA9WrA6mpectUqQK8fFmyZ0ipkh5BEETpoawXCjEsbgOI0kNBHZvCiPnNyODSp8XGAlZWwPjxgLGx9P35Wc0JE4BHj/5r/+ADYN06abOaCgUQEAD06ZO3TECA7k5gQc+NJzWVm73m9QQGcg67rigU8vxwkUsPQM42QRAEkU8Yofd4eXkxLy+vQtF94ABj5uaMcfOj3MvcnGsvaj1hYeL983qFhUnTN306YwqFeF+FgmvXBVNT9XaYmuqmx9lZvR5nZ930MCbfuclpk74h19gmCIIoixSm71ESoBjkMoy+lQh2cwNq1dIsU6uWtEwGcpV2/uAD4PFj9dseP+a2S6FXLyAqSv22qChuu1TkOrfWrTXb1Lq1dJv0DSpbTRAEQRQEikEuARRGHFB2NlcuOa88vwYG3OKo+HjNj6Tl0sPrMjUFnj/PW6ZWLc4x1aQrIwOoVEnzYj6FAkhL0xyS8OKFdocd4OytWTPv7W/fcvZoIy0NqFhRs4xc55aaCpiYaLfp9ev8hVsUJ3KOSYIgiLJKWY9BphnkMoo+lggOD9fsHAPcdm265Crt7OGhebtUuenTpemRIifXuRVGZo3sbG6h5Z493HtRZRvJDZWtJgiCIAoKLdIro+hjiWC5dMXGStOjTU6uCnh37kjTI0VOrnOTSw9PSAiXoi+nY2puzuU2Lur0bFTghSAIgigoNINcRtHHEsFy6bKykqZHm1y9etL0aJNr0kSaHilycp2bXHoA/Yv3pbLVBEEQREHR+xjkHTt2YPny5fDx8cHKlSuFdi8vLyQlJandp3Xr1ggMDERKSgqcnZ3Vynz++ecYP348AIAxhh9//BHBwcF49OgRTE1NMWDAAIwZM0a0z+nTp7F+/XrcuXMHlStXRseOHTFr1ixUyRGkeefOHSxZsgRXr14FALRq1QqzZs2CVQ5PIyUlBUuWLEFYWBhev36Nxo0bY/LkyfDMIwlwYcYgJyWpL8yhawxyQfXIqYtikIsuBlkf433lHJMEQRBlFYpB1lNevnyJzz77DFu3bkX58uVVtv/888+4cOGC6PXbb7+hVq1aaN++PQAg9f+VGVauXKkiO2LECEHX+vXrsWHDBkyYMAFHjhzBpEmTsGHDBvz444+CTEREBCZOnAhXV1eEhobC398fUVFRmDJliiCTnJyMYcOGQaFQICAgAIGBgTA0NMTw4cORkpIiyE2cOBFRUVFYunQpDh48CHd3d0yYMEFwqosCfSwRLJcuY2Ng6lTNMlOnas8ZXLMmt2hQE6ammp1jgHN6e/bULNOzp3bnGJDv3KpUAfL47Sjg7Kx9gZ4+xvtS2WqCIAiiwBRrkjkNBAYGMj8/P/bs2TPm6enJpkyZonWf5cuXMx8fH5aens4YYywmJoYplUp29erVPPdJS0tjDg4ObMWKFaL2FStWMCcnJ/bu3TvGGGN+fn5swIABIpnw8HCmVCrZtWvXGGOMrV27ltnb27NXr14JMq9evWL29vZs06ZNjDHGIiMjmVKpZOHh4SJdAwYMYCNHjlRrY2HmIpQrn27Pnurz6fbsqbtN6vLXWljonr9WrnOrVk39uVWrppue0pgHOShIWu7qoCDdz7GgyDWOCIIgyiKUB1lP8fDwwPbt21FLyjNuAHFxcdi+fTu+/vprGP9/+uz169cAgEoanm9fu3YNaWlp6JCrdJebmxtSU1Nx7do1pKen48qVKyoyLi4uMDY2xvnz5wEAFy5cgJOTE6pWrSrIVK1aFS1atBDJVKhQAW3atBHpcnV1RUREBDIyMiSdrxyEhADLl6vPp7t8ufTY0RkzgEOH1G87dEh6Xl4eX1/g9m2uel2nTtx7TIzui72WLuVCDVauBCZO5N7T0rh2qYSEADkm/0WkpOiWK/rKFfXbrlzRPU536VKuNHWvXoCdHff+8qVu5wYAkZHcfu3bAxYW3PvLl1y7FAoj3leubBi+vsDdu1xp8qAg7j0+vugXDRIEQRAlD711kC0sLKDQ4Rno+vXrYWNjA48cObf4EIvKlSvnuV98fLxwvJw0aNAAAOd4JyQkIDs7W0XGyMgI9erVQ1xcnKDL3Nxc5RgNGzYUyZiZmcHQ0FBFJisrC/fu3ZN0vgUlO5vLOqApAn3KFO3OSUYG4O+vWcbfn5OTyowZXHzs+vXAL79w7yYmujvaABdqMGUKsHYt965LKWZtfcSYtD6SS09OZswAqlcHDh4Ebt3i3qtX172PQkIAW1vg4kUuFOLiRe5/qQ57u3bSwnDatZNuT6NGgKcnMHgw996oUf4X+vFlqwcN4t4prIIgCIKQgt46yLqQkJCAEydOYOzYsaJ23kHevXs3evbsiXbt2qF///7Yt28f3r9/L5LJ7UTzC+9SU1M1OtqVK1cWtr9580atTJUqVYTZ7NTU1DxlgP9mvQsbuWJH5crLyyNXlTg50NZHgDy5oqXq4ZGrj+TIPnHpkrTrf+lS0dhDEARBEHJQKhzkgIAAWFhYqGSByM7ORu3atZGeno6FCxdi8+bNaN++PRYsWIDV/CqePGAyJveQokvO40lBrlyxMTHS9EiRK4zZ6IKQR5IUneXk0gPI10eaZrX5Nimz2nKNI7nsIQiCIAg5KPEOMmMMv/zyC7y8vGCQa8l6jx49cPHiRcyfPx8ODg6ws7PD559/jj59+mDr1q1IS0uDyf9zXfGzwDxv3rwBwMUQ8zHFuWX4Nn67iYmJsF9umWrVqgkyeenhj1cUyBU7+uiRND1S5OSejS4oT5/KIyeXHkC+PpLrCYJc40gfs2EQBEEQZZcS7yDfuHEDT58+hZeXl+R9mjZtiszMTDx//hyWlpYAoBL7y8cmN27cGA0aNIChoSESEhJEMhkZGXjw4IGQ49jS0lJFBgDu3r0rknn48CEyMzNVZIyMjITY58LGzY3LBZs7DRaPgQG3aMvNTbMeORdpyV3draBIXB+qVU4uPYB8fSTXzK9c44iq3xEEQRD6RIl3kCMiIqBQKGBvb6+yLSQkBN98841K+61bt1CpUiWYmpqiZcuWMDExwZkzZ0Qyv/32G6pXrw4HBwcYGxujbdu2CAsLE8mcO3cOmZmZgnPu4eGB69evIzk5WZB59uwZbty4Ich06NAB6enpuJQrKPP06dNwc3ODkZFR/jpCR+TKFatUSjueFDk5q7vJwfPn8sjJpQeQr4/k+mEj1zii6ncEQRCEPqG3DvLLly/x9OlTPH36FNnZ2UhPTxf+f/funSD377//ol69ekJqt5zUrFkTQUFBmDt3Lv755x/ExcVh8+bNOHz4MEaMGAFjY2MYGxtj/PjxCAwMRHBwMOLi4rB//37s3bsXkydPFhzWiRMnIjo6GkuWLMG///6Lc+fO4bvvvkPnzp3RvHlzAMCgQYNQvXp1TJs2DTdv3sQff/yBadOmoW7duujfvz8AwN7eHp6enli4cCHOnz+PO3fu4Ntvv0VsbCwmTpxYBD37H76+wM8/A/Xri9vNzbl2Kemwxo+XlsXg/0ULM+IkjwAAIABJREFUi0yXHNSpI4+cXHoA+fpIrplfQJ5xJKc9BEEQBFFgijcNc94MHTqUKZVKta8DOTL9jxw5kvXq1StPPWFhYWzQoEHM2dmZtWzZkvn6+rLQ0FD2/v17kdz27duZt7c3s7GxYT4+PmzXrl0qusLDw1nv3r2Zra0ta9euHVu0aBF7+/atSObu3btszJgxzMHBgTk6OrLx48ezxMREkUxqaiqbN28ea9OmDbO1tWX9+vVjEREReZ5DYSfrzspiLCyMK+YQFsb9rwvTp2suEqFL8Qo5dRWUsDBpRTDCwopGD49cfXTgAGMGBtwr5/58m64FNQo6jnh71J1TfuwhCIIg8k9ZLxRiwFgRp08gdKYk1EOfMYPLnpBzAZlCwZU91rV4hZy6CkJ2NldKWlPoQ61awOPHmmd1s7O5XL6aFqFZWHBFLKTm6ZWrj0JCuOwROW2zsODCIoqjoIa+XHuCIIiyTknwPQoTcpBLACVlkL59C0yfDty5AzRpwuXkrVgxf7pSUwE/P26xmZUVEBgI/D9VdJHpkctBBv7L8avu02ZgID0UISdy9XdGBpf1gu+j8eN1K6giF3n1ER92kZ8+IgiCIPJHSfE9CgtykEsAJWGQqpuJNDfnFnDp6tTINYvYujUQFaXa7uwsrZTy2bNcJTdthIVxVdoK256cyNXfcl63glAYs+wEQRBE/ikJvkdhoreL9IiSg5wV0OSqEpeXMwpw7a1ba9chZ+qxXr0029Orl7RjAfL1tz5VrpO72iBBEARBFARykIkCIWcFNLmqxKWm5u2M8kRFcXKaqF1b83apcm/fAocOaZY5dIiT04Zc/a1vlevkrDZIEARBEAWFHGSiQMhZAU2uKnF+ftqPJUXu1i1perTJTZ8uTY8UObn6W98q18lZbZAgCIIgCgo5yESBkDMMQa4qcf/+K02PNjm57LlzR5oeKXJy9be+Va6TM1c0QRAEQRQUcpCJAiFnBTS5qsRVqyZNjza5vIpW6CrXpIk0PVLk5Opvfatcl7vISEHlCIIgCKIgkINMFAgXF/nk5KoSN2qUNJu0yTk7S9OjTW7ZMml6pMjJVXFO3yrX8fZogirpEQRBEEUFOchEgdAWD6yLnLExl8pNE1Onas/R++GH0mzSJpecLE2PNrmKFYGePTXL9OwpLYexQsGlYANUnVv+/1WrpP3QkEOPXPD2aHLYi9IegiAIomxDDjJRIC5ckFdu6dK8ncmePaXlQZZrNlLOuNiDBzWf18GD0o4FcPmJf/5ZNdzA3Fy3Yhpy6ZEL3p7c187CgoqEEARBEEWLYXEbQBQ/2dlctoKHD7mYUzc36TN1UqvSSZULCQEOH1ZtNzDg2kNCtDtK/Gykpsp1UmYj5Y6LPXgQePEC8PAAHjwA6tUDzp0DataUtn9OfH2BTp0KXm3Q1xfo0kW+CogFxdcX+Phj/ajsRxAEQZRhGKH3eHl5MS8vr0LRfeAAY+bmjHGuJPcyN+fapXDqlHjfvF6nTmnXlZWlakvul4UFJ5ffc7OwkH5uctvTs6d6HT17Stu/MHRNn86YQiHWoVBw7cVBQccjQRAEIQ+F6XuUBCjEogwjRyU1b2/ts5ZVqnBy2pC7mpqvL3D3LlcKOiiIe4+Pl/6oPmdcrLo4XV3iYnv1yrtYyKFDulXSk0uXXFUL5UKfKvsRBEEQZRsDxtQ9hCb0icKoh56dDTRqlLdDamDAxYLGx2t3AENCgD598t5+4IA0p3T3bmDoUO1yu3YBQ4Zol5OLkBCu6lzOvrKw4JxjKef19i1QqZJ2ubQ07aENcunKyOD0aCrMolBweooivEHO8UgQBEEUnMLwPUoSNINcRpGzkpqvL+cE16snbq9fX7pzDBRONbXsbODsWWDPHu49P6WTCzoTLWclPbl0yVW1UC70rbIfQRAEUbahRXplFLkrqcmxuEruamrqZn7NzbmwCV0zIigUQIcOuu3DI2clPbl0yVUlUC70rbIfQRAEUbahGeQyityV1EJCOKf4iy+Adeu4dysr3eJG5cwaoU/xrHJW0pNLl1xVC+VC3yr7EQRBEGUbikEuARRmDHJSUt6p0HSJQVaXUo1f2CY1h622OFSAi/3VZlNhxLNmZOR/dlzOGOTUVMDERLuu1681L57U1xhkOcYjQRAEUXAoBpkok8hVSS07mwtjUOfU8G1TpkiL/ZWrmprc8awzZnDOZM7Z8UqVpGd5kLOS3pUr0o6pTU6uqoVyoW+V/QiCIIiyDTnIZRg5KqnJ7YzKUU1NznhWuVKhyVVJT85zW7qUW8yX2+lUKLh2KVUL5UTfKvsRBEEQZRdapFfG8fXlHLT8VtIrjMVVBbVJrnjWjAzA31+zjL8/sHixtJnWYcO4md2kpP/a6tfn2qUid6zu0qWc/fpSua6g154gCIIg5IBmkIkCUViLq7KzgRs3gEuXuHdd0rO5uXGzjppCNSwsODlNyJkKjY/TzukcA1zJaV0WDcp1bjlRKAAHB6BdO+6dnFH9R470hQRBEETekINcxgkJ4RZHeXoCgwdz740aFa/DVtCYXz6eNa/lp4xJi2eVKxWatjhtxnSP0y7oufEU9PrLjb7Zo49QHxEEQRQ+5CCXYeRIhSb34iq5Yn537izYdkC+VGhyl9CW49wA/UqFp4/25ERfZmz1uY8IgiBKE5TmrQSg76WmgYKXYwbkSz0mV1q1Fy+AWrW063n+HKhZM+/tgYHS4ox37gT8/DTLyHVu+lbaWd/syYmcBWcKgj73EUEQpQ9K80aUSQoj+0RsLLByJTBxIvf+77+6ORByxfzKVY551ChperTJ/f67ND1S5OQ6N30r7axv9vDo04ytvvYRQRBEaYQc5DKK3Nkn5KikJ1fMr76VY5b6jEaKnFznpm+lnfXNHkDeHN9yoI99RBAEUVohB7mMImf2Cblm2eSK+dW3csz6WGpa30o765s9gP7N2OpjHxEEQZRWKAa5BKDPpabljIvUtxhkfSzrLNe5Ualp7ezZw2WJ0EZQEDBoUOHbo499RBBE6YVikIkyiVzZJ+ScZZOr/HHFioCzs2YZZ2ftpZ2rVJGmR5NzDMhb1lmustWXLkmL9750SbtNcqCPpab1bcZWH/uIIAiitKL3DvKOHTtga2uLL774QqXd2tpa7evRo0eC3MOHDzFlyhQ4OzujRYsWGDx4MK5fvy7SlZGRgSVLlsDd3R22trbo0qULDhw4oGJLcHAwunbtCltbW7i5uWHJkiXIzMwUyVy5cgVDhgyBvb09WrVqhSlTpuDx48ciGSk2FQVylPaVOy5SjvLH2dnaj/fokbTY0cjIvJ1kZ2duuxTkLOssR9lqfYxn1bdS04WR47ug6FsfEQRBlFqYnpKcnMzGjh3LXF1dmZOTE5syZYpo+9q1a1m7du3YkydPVF7Z2dmMMcbS09PZRx99xPr27cuioqLYP//8w77++mvm4ODA7t27J+iaNWsWa9OmDfvll19YbGwsCwgIYE2bNmXHjh0TZEJDQ5m1tTXbvn07i42NZb/++itr27YtmzdvniATGxvL7Ozs2FdffcWio6PZlStXWP/+/dnHH3/MMjIydLIpJ15eXszLy0u2vs1NVhZjYWGMBQVx71lZ0vcNC+NLXWh+hYXpZlNaGmMTJjDWqRP3npZWvDY9f86YrS1jNWty78+f63Y+PE+eMNaoEWOVK3PvT57kTw9jjL1+zVivXozZ2XHvr19L37ewrpscFGQ8ys2BA4wZGHCvnP3Ctx04UDx26VMfEQRROils30Pf0VsHOTAwkPn5+bFnz54xT09PFQf5hx9+YJ06ddKoIzQ0lCmVShYbGyu0ZWVlMQ8PDzZ37lzGGGP3799n1tbWbO/evaJ9p06dKtLv7e3Npk6dKpLZu3cva9q0KXv06BFjjHO0PTw8WGZmpiATFxfHlEolO3LkiGSbcqPPgzQrizFzc1UHIqcjYWGh2xf4gQOczpx6zM2lOyNBQdKcv6AgafqmT2dMoRDvq1Bw7bpgZaXeDisr3fQwVvA+KozrVlpR19cWFsXnHBMEQRQF+ux7FAV6G2Lh4eGB7du3o1YelRpev36NSlpWK4WHh6NRo0awtLQU2hQKBdq2bYvz588DAC5evAjGGDp06CDa183NDXfv3kViYqLwrk7m/fv3CP9/gO2FCxfg5uYGQ0NDQebDDz+Eubm5cDwpNpUk5I6LlCMjhpyxo3JV9mvcOO90cLGx3Hap6GMFxNKMry9w9y4QFsYtyAsL4xbCUTgDQRBE6UVvHWQLCwsoNHw7p6amanWQ4+PjYW5urtLesGFDPHz4EG/fvkV8fDzKly8PU1NTkUyDBg0AAHFxcYiPjxdsyomZmRmMjIwQFxeHN2/e4MmTJyoy/PHi4uIk21TSkCsuUq68s46O0o6nTS4jA/D31yzj78/JaeLVK+25kmNjOTltyJmbl+JZpaNQAB06cNkqOnSgHw4EQRClHb11kLXx+vVrvH79Gl9++SW8vb3/x965x0VVbv//M4xgiqhpXgMxRNS8YN7KC+El7WtaGpomphk/s0JT85hp2Sm/+dW01Mq0sGOZmpc6klp5KkVU1GNqatrROolgiPcbclEHhv37YzMTt9nPmmENzuB6v168JmZ/+Oxn9oyxWHs9a6FHjx6IjY3FsWPH7Jrs7Gz4+/uX+NlqBW0HMjMzHQbaxTUASniZTCb4+/sjKyvLocbmlZmZSV6TN8KRZePqiDFqFO18Kh3XZL9+/WjroejcMQFRsqOCIAiCUJRKaoln4uvrixs3buD+++/Hc889h4sXL+Kjjz7C0KFD8c9//hNhYWEOf1YjtH6maKiU9/luFbYsm6twdVbgmoDH5XPyJM2HonNH94myvm+CIAiCUNHw2gD5448/LvJ9WFgYwsPD0aNHD8TFxWHevHkICAhAdnZ2iZ+1ZXsDAgKUmurVq9uDV9tzNjRNQ3Z2NqpXr46AgokSxTW252rUqGE/p2pNtytctcNNmgBHjqh9VBPwuCbp1axpnPUtrFPhab15BUEQBKEi4rUlFqXh7++PwMBAe9/hkJAQnCwlLZeamorAwEBUqVIFISEhsFgsOFMs5ZaamgoACA0NtW+oK+516tQp5ObmIjQ0FFWrVkWDBg0cnq9JQRRFWdPtClff2WXLaOdT6WJj1bWmZrOuM2LiRNp6KDpP7M0rCIIgCBUNrwyQc3Nz8fe//x2bNm0q8nxmZiZSU1PRuHFjAED37t2RlpaG48eP2zUWiwVJSUno0aMHAL0ThY+PD7Zu3VrEa8uWLWjWrBkaNmyIoKAghISEIDExsYgmISEBlSpVQkRBNBIZGYmkpKQiw0OOHj2K06dPo2fPnuQ1eStWK7Btmz6id9s22kaxwhTurOAISmcF6swVlY5rAh5XJhqQ7hOCIAiCUB54bIB89epVXLhwARcuXIDVasXNmzeLfH/t2jW8/vrrWL9+PdLS0nDo0CGMHz8eVqsVI0eOBAD06dMHLVq0wJQpU7Bv3z4cO3YMU6dORW5uLkaPHg0AqFevHqKjo/HBBx/g+++/R3JyMuLi4pCYmFhket+ECRPwww8/4JNPPkFycjI2bdqERYsWYeTIkfZWdKNHj0Z2djZeffVV/Pbbb9i7dy+mTZuG8PBw+0xzypq8kfh4oHFjoEcPIDpaf2zcmNZyrDBRUcDkyaVPnJs8mbZ5LD2ddi6KjmMCni3ra4QzWV/pPiEIgiAI7sWkeejusBEjRmCvgzm+s2fPRr9+/RAXF4fvvvsOZ86cQc2aNdG6dWu89NJLCC3UVPbixYuYPXs2duzYAYvFgvvuuw9Tp05F8+bN7Zq8vDwsXLgQX3/9NS5fvox77rkHsbGx6Nu3b5Hzbty4EXFxcTh58iTuuusuDB48GLGxsfDx+evvjCNHjmDOnDk4fPgw7rjjDvTo0QNTp07FnXfe6dSaCmMLrhMSEpy/kOWArS9v8U+SLaPpTNDmyMvmR/F67z2g2GTyUlmwgF7+cOEC0KmT/linjj5iuk4d2s8CPK+rOJcvA5GRwOnTQMOGwPbtQK1aznkAeqY/KUnf2NeggR6ou5KBtlj0jh7JyXo2PDZWnV2/3ZBrJAiCt+DpsYe78dgAWfgLT/6QWq16pthoE1pQkN46TBV0cXl98QXw1FPG5wKAlSuB4cPVOkdDPpo0AQpVyijp1AnYt6/k8x076gG3M3CtKT5e76tc+JoHBuplHM4E7FOm6D2hC5fVmM16CQoly347INdIEARvwpNjj/LAY0ssBO9A1ZcXoPfl5fIqXnpQFh3XBLyBA0sPjgH9+YEDaT6ca+KYyAfwTRusyMg1EgRB8C4kQBbKRFoan47Lq2VLmo9KxzUB7/p1YMMGY82GDbpOBdeauCbycU0brMjINRIEQfA+JEAWysRPP/HpuLwKGoYoUem4JuC9/DLNh6LjWhPXRD6uaYMVGblGgiAI3ocEyEKZoFawU3RcXqdP03xUuj//pPmodH/8QfOh6LjW5GlTCysyco0EQRC8DwmQhTLRtCmfjsurYUOaj0rXqBHNR6XjvEZca+KcWkiBqquIyDUSBEHwPqSLhRfg7p2kZWnzZbEAVasa30I2m4GcHHU7Ky6vy5eBgtbUhly6ZNwWjcvn+nX9danIyQFUgxQzMmgjqa9eBQqmm5eKrWNIerrj1nOBgeqOIZzvf0VFrpEgCN6IdLEQbmvKOuCDa9ocp1etWkC9esaaevXUPYMPHzY+TtVVqQIMGGCsGTBAHRwDetCryjQ2aWIcHAN8E/k43/+KilwjQRAE70MC5NsYrjZfHNPmbDzwQNmO2zh71nGQXK+eflwFV50uABQMd3T5eGGOH3ccJDvTB9nRRL6773ZucAnn+19RkWskCILgXUiAfJvC1ebLxty5+i3iBQuAceP0x5wc537x29bkCJPJuTUtXlwySK5Xj94toG5dHh336wL0IPjqVaBrV314Steu+vfODAmxUfwz4ErRFcf7X9GRayQIguA9VLrVCxBuDc60+ereneZpNgNt2+pBaIMGzo8r5lyTo9HO587pz7sy2tlV3HGtAaBaNWDmzL9qx6tVc25djq6R7Q6Cs9fIz48+uvt2Ra6RIAiCdyAZ5NsUzvIBoOy1zJxrMsqOA/rzlIwtpQyDouO+1kDZrzfXNRIEQRCEiohLAXJkZCTmz5+PZGnc6bVwtfkC+GqZudbENbL6wgXaelQ6zmsN8FxvzhHhgiAIglDRcClAPnfuHD755BP0798fTzzxBL744gtcvXqVe22CG4mI0Nt4Fe9gYMNk0mtbIyKMfThrmbt0UZdlmM26zoiTJ9XnouhUnSCoOq7XBfBd7/R09bmc0QmCIAhCRcKlAPnHH3/E+PHjERoaiiNHjmDmzJmIiIjA+PHjkZCQgLy8PO51CsxwtfniGlkMALt300by7t5trFm/Xn0uim7jRpqPSsf1ugC+682VHRcEQRCEiohLm/QaNWqEF154AS+88AKSk5Px3XffYdOmTfjxxx+xefNm1KxZE/3798fAgQPRsmVL7jULTERFAZMnA/PnFw3gfHz0vqyUDVqc9bVcXtnZNB+VLjOT5qPSeeI1qlOH5kPVAWUbOCMIgiAInkSZN+k1adIE48ePx/fff4/169dj1KhR8PPzw8qVKzF48GD0798fy5YtQyY12hDKjfh44N13S2Y3rVb9eUotK2d9LVdbtbAwmo9Kd+MGzUel47xGXF7Fex+XVcexSVO4NVitwLZtwOrV+qNszBQEQWDuYtG8eXO89NJLePXVVxEYGAhN03D8+HG8/fbbePDBBzF79mxkZWVxnlJwEVUXA4BWy8pZX8vFO+/w6Fq3pvmodLZ6byMo9d6FvcpaO865Jq5NmkL5I3/YCIIglA5bgLxv3z5MmzYNXbt2xcSJE5GWlobatWvjmWeewVtvvYWgoCB8/vnnGDRoEM6dO8d1WsFFuGpZOetrz59Xayg6rtHOzZrR1qPSmc3AsGHGmiefpJUjFK4ddwSldtzmYzKVXoNuMtF8uAfOCOWH/GEjCILgmDIFyOfOncNHH32EPn36YOTIkfj6669x/fp19OjRAx9++CF27NiBV155BU888QQ2btyIyZMn4+TJk/i///s/rvULLsJVy8pZX8tZirB+veMgecAA2ka+2FhaoBkba6yxWvXb10asWUMPIm2146WNLZ48mT7cw9Go6cBA+pAQzk2aQvkhf9gIgiAY49ImvU2bNmHdunXYs2cP8vPzoWkaQkNDERUVhQEDBqB27dql/tzo0aNx6NAh7Ny5s0yLFsoOVzDKGdTabvunp5f+i9tk0o9TbvsDehCckQH06wf8+SfQqBHw3Xf09m1+fkD//sCGDY41/fvrOiOc6TlMmaRnqx0vfo1steMPPOBckNy/vz5+OzkZaNJED/hVr8mGO4ageCKetgGxrOtx13RHQRCEioJLGeRJkyZh165dqFq1KoYMGYIvv/wS3377LWJiYhwGxzbatGmDG9TdT4Lb4KpB5aqJBf667W803Y1y29/GlClA7drArl36L/tdu/Tvp0yh/bzVCvz8s7HmwAF1lo0ziOSegBcfrwfFL70EfPih/tikSfkPd/FkPK1O15OmVgqCIFRUXAqQO3fujHnz5mHXrl2YMWMG2rRpQ/7Z/v37Y+XKla6cVmCEqy6Wq5+yDVXwSg1up0zRN+GV1qHjnXdoPlzT5jiDSM4JeBw1qBERQLVqxppq1ehZf0/D0+p0PW1qpSAIQkXFpQC5ZcuWCAgIgB/1PmwhGjZsiHbt2rlyWoERzrpYjlpWQC+HUE0vT07WdUZYLHpvZyPmz9d1qnNRUOmaNqX5UHRpaTQvlY6rBtVqBXJyjDU5Od5Zy+qOOt2ytFTjXA/nnR9BEISKiEsB8urVq/Hbb79xr0UoRzgzkYAeBCcnAwsWAOPG6Y/Hj9ODY0CvFebQLV5MC+wWLzbWvPcebT0qXfv2NB+K7qefaF4qHdfmusWLgfx8Y01+vvpaeyLcGxDLWhrBuR7uOz+CIAgVDZcC5G7duiEhIUFqib0Y7hrEstayAvpGOg4dV+b36lWaj0rH5QMY9612Rsf1/nNda0+E898IR2kE979Zrjs/giAIFRGXuli88cYbeP/99xEdHY3+/fujRYsWuPPOO1GpUul2oaGhZVqkwA9nDaLtl3/xoMz2y5/6y7ZRI1oJQaNGxsebNFF7UHTBweosu01nRM2aAKX1d82aag1XuQbX+891rT0RrmukKo0wmfTSiAEDjDO27qgbjorSz+tJHToEQRA8AZOmUXNSf9GiRQv6CUwmHD161NlTCIXo1asXACAhIYHN02rVb++qWqqlpBj/srT5OAokqT6AXltMCRKvXjVu1Xb9OlC1qtonJ8d4WAjXetLT1R1DAP0aqkY7Wyz6azMqITGb9ddmtEWA6/3nWo8nwvXatm3TyylUJCYat1Tjes8EQRAouCP28CZcKrFo0KAB+at+/frcaxYY4KpB5KyLrFFDnWls0kTdx5irTpdrPX/8QVsPRWfrzWwEpTcz1/vv5wdMmmSsmTTJ+4JjgG9KJFdphNQNC4IglB8ulVhs3bqVex3CLcBWgzhhQtEgNzBQ/0VLKYvgros8fhwIDS29ZrVJE/14ea7J09bjTG9mVaDE8f4DwNy5+uP8+UUDSrNZD45tx70NrveNszSC6z0TBEEQjHEpQKaSkJCAw4cP46WXXnLnaYQyUNYaRHfURR4/Dly4AHTqpD/WqQPs3as/3oo1HT8OXL4MREYCp08DDRsC27cDtWqV/3q4p/JFRQG9erk+bdDG3LnAzJmuT+TzRLjeN+4JkVI3LAiC4H5cKrGgkJ+fj02bNmH58uVl8lm2bBlatWpVapB94MABxMTE4P7770fnzp0xZsyYIu3nrl27hmbNmpX6tbhQ3ylN0xAXF4eHHnoIrVq1Qq9evbBkyZIS50tISEBUVBRat26NBx54ANOnT0dWVlYRzR9//IHRo0fjvvvuw3333Ydnn30WycXSj9euXcNrr72GLl26oHXr1nj88ceRmJhYputUFsxmPZgaNkx/dOYXrTv6qU6Zov/ST00FsrP1xwYN6ENCuKYE2oiPB8LDgV9/1QPlX3/Vv6d26OBcD3fGvlMnvc668LTBmjX1553Fz0/fbLZwof7ozcExwPfZdkdpRFn+zQqCIAhqXA6QDx06hOeeew7du3dH586dS3y1bdsWmzZtQg1nU1EFXL16Fc8//zyWLl2KypUrlzh++PBhjBw5Eg0aNMCqVavwySef4MaNGxg1ahQuXboEAPbgdcGCBdi5c2eRr1GjRtm9Fi1ahMWLF2Ps2LH45ptv8OKLL2Lx4sVFguQ9e/Zg3Lhx6NatG77++mvMnz8f+/btw8SJE+2aK1euYOTIkTCbzfj888+xYsUKVKpUCU8//TSuXbtm140bNw779u3D3LlzsX79ejz44IMYO3YsflbdO/dA3DFJr6wT8MxmdU/hdu1oa3LUnuvUKXp7Lq6phQBvNrpTJ2DfvtKP7dvnWpBckeD8bEtLNUEQBC9Dc4FffvlFa926tdasWTPDr8jISO3HH3905RTaihUrtBEjRmgXL17UevTooU2cOLHI8QkTJmi9evXSrFar/bnU1FQtLCxM+/LLLzVN07Tff/9dCwsL037++WeH58nJydHatm2rzZs3r8jz8+bN09q1a6fduHFD0zRNGzFihDZ06NAimqSkJC0sLEw7cOCApmmatnDhQi08PFzLyMiwazIyMrTw8HDt448/1jRN0/bu3auFhYVpSUlJRbyGDh2qxcTElLrGnj17aj179nT4GjyBdes0LTBQ0/SbyPpXUJD+PJWbNzXNbC7qUfzLbNZ15eGTl1fyNRX/CgrSdeXho2madvWqsY/t6+pVY5/MTJpPZqZ6TRUdjs+2jbw8TUtM1LRVq/RHynsuCIJwK/CG2MOduJRBjouLg8XGwd0bAAAgAElEQVRiwbPPPosvv/wSK1euBAC89dZbWL9+PcaPH4/g4GDMnz8fvXv3dilwj4yMxGeffYbatWuXenzWrFlYu3YtfHz+egl169YFAHsGOTMzEwBQ1aDn14EDB5CTk4PuxQo2IyIikJWVhQMHDuDmzZvYv39/Cc39998PPz8/7NixAwCwc+dOtGvXDtWrV7drqlevjjZt2hTR3HHHHXjggQeKeHXr1g179uyBRTX/2EOJitJLIRITgVWr9MeUFOcyY1wT8Lh8uKYNck4tLHTjo0y6ESNoPlRdRYbjs21DSiMEQRC8A5c26R08eBC9e/fG3/72NwBAeno6AKBWrVpo3rw5mjdvjrZt22L06NFYvXo1mjVr5vQ5goKCDI9XrVq1ROC7ZcsWAEB4eDiAv0os/P39HfqkpKSUer5GBdMoTpw4gdq1a8NqtZbQ+Pr6omHDhjhx4oTd6+GHHy5xjuDgYPvaUlJS0KBBgxJDVYKDg5GXl4c///zTawer2H75uwrXVDYun4KPtRKVjrNu2NOu0e1CWT/bgiAIgnfhUgY5IyMD9957r/17U0FBnrVQ2q5Lly7o2rUrFi1aVMYl0khLS8PMmTPRrVs3dO7cGcBfAfIXX3yBAQMGoEuXLhgyZAjWrl2L/Pz8IpriQXS1atXsx40CbX9/f/vx7OzsUjXVqlWzZ7OzsrIcaoC/st63I1xT2bh8Llyg+ah0nHXDnnaNCmO16kMxVq/WH1VZ/PLAE9ckCIIgeD4uBchVqlQp0r0hICAAwF+lDTbuvfdeHDhwoAzLo3H8+HFER0ejbt26mDdvnv15q9WKu+66Czdv3sSMGTMQFxeHrl274s0338T7tt03DtCcHzBYJi/O83krsbHqW85ms64z4rnnaOdT6aht5VS6Ll1or6tLF/W5VqygrUml4/KxER+vT3nr0QOIjtYfGzemd/pwB564JkEQBME7cClADg0NxY8//mjvzBAQEIDKlSvj3//+dxHd5cuXkZ2dXfZVGnDgwAFER0cjKCgIK1euRM1Cs4Efe+wx7Nq1C2+88Qbatm2L1q1bY8KECRg0aBCWLl2KnJwce3BfvF2bbd3Vq1e31xQX19iesx0PCAgo9fVmZWXZu3kEBAQ49LGd73aFa0oc1yQ91dhnqo5rIhsAVKtGyw4X3JAw9OnY0VjTsaPaB+Dp9MGNozWlp9+6NQmCIAjeg0sB8qOPPoq0tDT07t0b+/fvBwB06NABmzdvxgcffICjR49i/fr1WLdunb2W1x0cPXoUo0ePRqdOnbBs2TJyS7nmzZsjNzcXly5dQkhICADgzz//LKKx1SaHhoaiUaNGqFSpEk6ePFlEY7FYcPr0aTQpiFhCQkJKaAAgNTW1iObMmTPIzc0tofH19XXr9fJ0nJkSZwRXzS9X5perlhnQX/vNm8Yai4VWSrB3r+MguWNH/ThlPRMmlD4AA9CfnzixfEsbjNZke6681yQIgiB4Fy4FyMOGDcOTTz6JjIwMe2nA2LFjYTab8dFHH2HQoEGYNm0acnJyMHLkSNYF27h8+TLGjBmDLl264P3334dfKWnF+Ph4/O///m+J548cOYKqVauiXr16aN++PQICAkqMz96yZQtq1qyJtm3bws/PD507dy4xzGP79u3Izc1Fz549AeidNw4ePIgrV67YNRcvXsShQ4fsmu7du+PmzZvYXSxdmJCQgIiICPj6+rp2QSoAXN0euGp+uTK/XLXMAG9HDEAPgjMzgYEDgdat9cfMTFpw7I71cKBak6aV/5oEQRAE78KlLhY+Pj548803MXr0aHtJQ7t27fDZZ59hyZIlOHXqFOrXr49Bgwahv+qeuQOuXr1qz7JarVbcvHkTFwoiiICAAHzwwQe4ceMGJk+ejMuXLxf5WV9fX9SsWRO1atXCqlWrkJubi+HDh8PPzw+bN2/Gxo0b8fzzz9uD6tjYWCxYsAD33HMP2rdvj/3792PNmjWYNm2aPWAdN24chg8fjjlz5mDQoEFIT0/HrFmz8PDDD9s3LA4bNgwrV67E5MmTMWHCBGiahgULFqBu3boYMmQIAL3DRo8ePTBjxgy8+eabaNCgAb788kskJydj1qxZLl0rT+H6deDll4E//gCaNtUHe1SpQv95rswv12hfrvVw1TJTzuWsDtDfowkT/hpb7Mx7xpkd58Id10gQBEG4vXApQLYRWGx+bseOHdFRVdhI5MUXX8TeQmmss2fPIiEhAQAwe/Zs7NixA5mZmaW2VevUqRNWrFiB7t274+OPP8aSJUswcuRI5OfnIzg4GLNnz8aAAQPs+piYGPj4+CAuLg5nz55Fw4YNMW3aNAwfPtyuadu2LeLi4jB//nysXLkS1atXR9++fTF58mS7JiAgACtWrMCsWbPw9NNPw2QyoXPnzli+fHmRlnTz5s3D3Llz8corryArKwstWrTA0qVL0bJlS5ZrdysYOBDYsOGv73/8EVi0CBgwAFi/nubBlfm1TUAbNKj045pGm4DGtR6uWmbKuZzVxcfrwXHhjGtgoH79KH1+ObPjXHBfI0EQBOH2w6RJ+wSPp1evXgBg/wPB0ygeHBeHGiRbrfoGvIIOfKXi46PX2KqC25o1gYwMx8dr1ACuXlWvp3Jl4zKLSpWAGzeM12O16pvdbtxwrLnjDiArS/26OL1sG9kcZdkpI5C/+AJ46iljDQCsXAkU+nvTrVitercK1R2ElBQZ1CEIguAIT4893A0pgzxt2jSXT2Aymby+dEBwzPXrxsExoB+/fl196z4jwzg4BvTjGRlArVqONRcuGAfHtnNduGBc1pCVpa5BzsvTdUb7Qy0W44AW0I9bLOprxOVF3Vw3YIBxEMmZHefCdgdh8GA9GC78GgtatpPuIAiCIAi3L6QA+euvv3b5BBIgV2xefpmu+/BDY01kJM0rMhI4csTx8U6daD6dOulZREf060fz6dcP2LnT8XHOa8Tl5czmOqMJcrZ6byOvoCB1vTc3UVF6Bry08pH33nNtTLQgCIJw+0AKkGfPnu3udQheyh9/8OlOn6Z5qXRcdbHFOv+5rOO8Rv/9L81LpePaXFc4Wwt4VrY2KkrPgCcl/bUBMSJCMseCIAiCGlKA/Pjjj7tkfvXqVdxUNW0VvJqmTfUNeRSdioYNgWINSRzqjKhWDaDMp1ENwWjUSM+iqlC1rua8RqVMKXdJx7m5TrK1giAIQkXDpT7IVFavXo1hw4a58xTCLeadd/h027fTvFS6GTNoPirdqlU0H5WO8xoNHEjzUuk4W88BehCcmgokJurXIzFRL1+5lcGxjJoWBEEQXKVMbd6OHDmC33//vdQs8bVr17B69WpkZmaW5RRCOWC1un4bukoV/Ta2qosFpbdurVpAvXrAuXOONfXqGW/QA4BmzdTnouiio2k+0dHGNchVquiT6fbtc6zp2JF2jYKDaWtS6dyxuc5sNq5XLk8cdeiwjb+mdOgQnMNiARYvBpKT9XHnsbHqsfCCIAieiksBssViwfjx47FdkcrTNA3dPeU3plAqZe2DC+gt3By1enOmDzIAnD0L1K9fepBcr55+XIVtRLRRBwrKiOhSpoa7pLNa1UMpzp7Vdao/TLhem6duruOAq0OHQGfKFGD+/KKfy8mTgUmTgLlzb926BEEQXMWlEoulS5di27ZtqFq1Krp164bevXtD0zR06tQJPXv2RI0aNVC3bl3MnDkT7733HveaBSZsWbbiQVJ6uv68M7ei168vfWSxM8GxjbNngfPn9dvh/v764/nztOAY4BsRbdS6zRkd5zhmrtdm21xnMv21mc6G7TlvbYXmieOvKzJTpujlQcU/l1ar/vyUKbdmXYIgCGXBpQB506ZNqF+/PjZv3oxPPvkEUwr+Dzhy5EgsWrQImzdvRps2bZCYmGgf5yx4FkZZNttzEyeqgzEb8fFAixZ6QHzkiP7YooVr9Z7x8UC7dnpNa3a2/tiuHd2La9Rw3740H5WOc/Qx52jnqCg9y+dT7P8CPj76895aguCJ468rKhaLnjk2Yv58XScIguBNuBQgp6WloV+/fqhVUAxqKpaCCggIwNtvv41jx45h2bJlZV6kwI8qy6Zp9CwbZyaaw4tr1PAdd9B8VDrO0cec3Sfi44F33y098/fuu967mc0Tx19XVBYvpt3RWLy4fNYjCILAhUsBstVqRUBAgP17X19fAEB2od5a/v7+ePjhh8s0ZERwH1xZTc5MNJeXrU7XCEqdbocOxsepOq71AMCdd9LWpNKp6nQB5+4gcGK1Atu2AatX64/OrqF2bV6d4JjkZF6dIAiCp+BSgFynTh389ttv9u/vLPhtnFJsLFlAQABOqYoBhVsCV1aTMxPN5cVVp8vVno1rPYBxJwxndJzvGyccrdkuXeLVCY5p0oRXJwiC4Cm4FCB37NgRmzdvxocffojLly/D19cXDRs2xPr163Gp4LdOfn4+du3aVSTTLHgOti4GxTdo2TCZaF0MOOtruby4fLgm6XFeI6OMrzM6zjVxwVWqw93jWXBMbCzt7khsbPmsRxAEgQuXAuTnnnsO/v7+WLRoEY4cOQIAeOyxx3DmzBk89thjeOGFF9C3b18cOHAAHTt2ZF2wwIOtiwFQehcDgNbFgLO+lsuLy0c1IY+q47xGlGl7FB3nmjjgLNVxR49noXT8/PRWbkZMmiT9kAVB8D5MmkbNSRXlxIkTWLJkCUaPHo3Q0FBYLBa88MIL2LVrl13TtGlTfPLJJ6hfvz7bgm9HevXqBQBISEhg9y6tD3JQEH1EsNWq3wJPTy89uDGZ9Ex1Soo62LZ5qXrzqrwsFqBqVXWv4Jwc41/cGRlAzZrGawaAq1eNW71ZrXoPZ6Nb+rVr672fVdfIYtEHiuTnO9b4+ADXrxu/Ns73jYNt2/RyChWJiephJFyfI4FOaX2QzWbpgywI3ow7Yw9vwOVJeiEhIXj77bft3/v5+WHp0qU4fPgwTp06hXr16iE8PByVKpVpWJ/gZqKi9IEJrk7Ss2WiBw/Wg6rCwZYzmWib17BhxjW9Tz6p9nKm5tco2KpRgzbZj9ovmQOzWQ/+s7Ica6pWpd32fv99YNCg0o9rWvn2QeYs+VC9NsB7ezx7KnPnAjNnyiQ9QRAqDuzRa5s2bdCmTRtuW8GNlHVEcFSUPrq3tIl81Ew0oAetq1cba9asAWbPNg5uuPrgWq1AXp6xJi9PPQEvKUm9IezSJV2neh+SkoyDY0A/TvHas0d9vLx6IXtayYfgPH5+ehmMIAhCRcClGuSbN2+W+vy2bduwePFifPbZZ0hLSyvTwoTyo6xttQA9kPrvf4GxY4E+ffTH3393LsDimoDG1Qd32zZaYLttm7GGc3AFl5enDXjg2jQK/FXP7AiT6da1sBMEQRC8A6cC5F9++QVRUVFYtWpVkeetViueffZZvPDCC1i4cCHmzp2Lfv364bvvvmNdrMAPR1stQK9BDAgAFi0CfvxRfwwIcG7MLNdtdq4uBqrAl6rjHFzB5eVpAx64No0CntvCThAEQfAeyAHy6dOnERMTg2PHjuHkyZNFjn366adISkqCv78/hg8fjqFDh8LX1xevvfYaTp8+zb5ogQeutlpTpuh1w6VNZHvnHXqQzHWb3dO6GHC2HePy8sQBD7ZSneLvS2Cg/jz1boQntrATBEEQvAtygLxixQpkZ2dj1KhReO211+zPa5qGFStWwGQy4eOPP8b06dPx5ptv4tNPP8XNmzexdu1atyxcKBtcbbU4b9Xfd59aQ9Hdfz/NR6Vr357mo9JRW4FTdHXr0rxUOq4WdtxERQGpqXq3ilWr9MeUFOdKdbiukSAIgnD7Qg6Qf/rpJ4SEhOCVV16xj5YGgF9//RXnz59H8+bN0aHQzN3w8HC0a9cO//73v3lXLLDAdRua81b9qFFqDUUXF0fzUem4JunNmUPzoegK2o6z6TwR26bRYcP0R+k2IQiCIJQ35AA5LS0N3bp1K/H83r17AfzVL68wbdq0KVGOIXgGXLehOW/VHz9O81LpuNbENUmPul+Vois2zd1lHddr80TOn+fVCYIgCLcf5AA5JycHd911V4nnf/75Z5hMJrRr167EsTvvvBPZ2dllW6HgFrjqfZs0oflQdNR+wiod15ooQ0IoOs5yBq7Xxvm+2eDohsKBtIwTBEEQygo5QA4ICEBubm6J5w8dOgQfHx+Eh4eXOJabmwuz3B/1SLp0oQ2T6NLFWBMbS/OJjVWv6Zln1BqKLjZWnyZnhI+Pek3Unq4qHbWZC0X33HM0L5WO830D+LqhcMDZMk4QBEG4PSEHyHXq1MHxYve2Dx48iMuXL6NZs2bw9/cv8TMpKSmoXbt22VcpsOPMtDkj/Pz0cbJGTJpEm6iVmanWUHS2aXNG+PurA8TGjWnrUemqVaMFo9Wqqc+lej+oOs73jasbChecLeMEQRCE2xNygNyiRQts374d6YUmEMTFxcFkMqF3794l9Dk5Odi6dSvCwsJ4ViqwwtkKa+5cfVx1aQwYoB+nwNXCjDJtLjNTvQGRWiKg0iUl0f4YofTl5erNDOjvy8svlwwUzWb9ecr7xtUNhRuulnGCIAjC7Ql51PQTTzyBjRs34oknnkCvXr2Qnp6O3bt3o0qVKhg6dGgRbVZWFiZPnozr16+XGjwLtx7OOs34eGDjxpLPm0z68/HxtICEq38xV/BPHSSRlKRPD3T3etzB3LnAa68B/frpG/IaNdJLPaj14M50Q6GOM7f9sXDmjP75i4hwLdsbFQX07693UElO1uupY2NpWXFBEATh9oacQe7YsSNeeOEFXL58GV999RV2796NypUrY9asWahVq1YR7cMPP4zt27cjLCwMjz32GPuihbJjq9M0glKnqcogaho9g8i1Jk/bpMW5HmqQSdUNHKhvMty1Sw9kd+3Svx84kPbz3ME/Zy1zfLweFL/0EvDhh/pjkya3pi5aEARB8C6cGjU9YcIE/POf/8Qrr7yCGTNm4LvvvkPfvn1L6AIDA9GpUyf84x//KNIzWfAczGb1gIt27dSZO1UGEaCP9TWb9d63Rjz5pHpNXJu0uILRiAh1fXG1arRNY927O35dNkwm2toHDgQ2bCj92IYNtCCZ+04EVy2zp9VFC4IgCN6FUwEyALRq1QrPPPMMhg4dikAH6b4lS5bg888/Rx1qUakBy5YtQ6tWrfDSSy+VOLZ//34MHz4c4eHh6NChAyZOnIhz584V0Zw5cwYTJ05Ex44d0aZNG0RHR+PgwYNFNBaLBXPmzMGDDz6IVq1aoW/fvli3bl2J83311Vd45JFH0KpVK0RERGDOnDklOntwrcndWCzAt98aa779Vj0Bj7PHr9WqtwgzYs0adTaaa5NW9+6Aao9p7drqYNRqBXJyjDU5ObQse0ZG6dn6wmiarjPi+nXHwbGNDRt0nRFcf4xw1jJ7al20IAiC4D04HSBTqEEtYDTg6tWreP7557F06VJUrly5xPETJ04gJiYGwcHBWLt2LeLi4nDmzBmMHj3aHrRaLBbExMQgPT0dH330Eb766iuEhIQgJiYGaYUitjfeeAPr16/H66+/jo0bN2LYsGGYPn06Nm3aZNfYjg8ZMgQbN27EG2+8gQ0bNmDmzJluWZO74ZqA99NPtPNRdJzZaNsmrdI2oFE3aZnNwJIlxpolS9SB9uLFQH6+sSY/nzZtkNqaTKV7+WWaj0pX+I8RR1D+GOGa7MjtZePCBeCee/RM/z336N+7Alev6OvXgXHjgIcf1h9Vf8iUx5q44FqPp70uQZDPtpeheSgrVqzQRowYoV28eFHr0aOHNnHixCLHp06dqkVGRmq5ubn2506cOKGFhYVp33zzjaZpmvb1119rYWFhWnJysl2Tl5enRUZGaq+//rqmaZp26tQprVmzZtqaNWuK+E+aNEnr06eP/ftevXppkyZNKqJZs2aN1rx5c+3s2bOsaypOz549tZ49eyqumHOMG2erEDb+GjfO2Cc2luYTG6te08qVNK+VK2mv0cjDGcrq88ILtNf1wgtqr4AAmldAgLFPnz40n0L/BAwp6zVatYq2nlWrytdL0zStRo3Sf75GDdrP21i3TtPuvruox9136887w4ABpa9nwADnfGxrCgws6hMY6PyauOBaj6e9LkHwxs+2O2IPb8ItGWQOIiMj8dlnnznso7xz505ERESgUqW/GnHcc889CAwMxI4dOwAASUlJaNy4MUJCQuwas9mMzp072zW7du2CpmnoXuw+eUREBFJTU5GWlmZ/LE2Tn5+PpIJUFNeaygOuSWpNm9J8KDpqVo6io9TpUuDwKdQZscy6Um6muKTjfN84rhFnLTOnV82ajstVMjLo0xbj44FBg0q+x+np+vPUmmiOuvHCa/KkOm2u9Xja6xIE+Wx7Jx4bIAcFBTmcwpednY3z588jKCioxLHg4GCcOHECgD6opLQ66eDgYJw5cwbXr19HSkoKKleujHr16hXRNCqY+3vixAmkpKTY11SYBg0awNfXFydOnGBdU3nQoQOP7tIlmg9Ft3w5zUul69mT5qPS9ehB81HpfvyR5kPRqbp8UHWqDZpU3fbtNB+Vrm5dmg9FxxX8X7igruXOyFD/wWa1AmPGGGvGjFHfJuWqG7etyZPqtLnW42mvSxDks+29eGyAbERWwRSI0qb3VatWDZkFo9ays7MdagAgMzMTWVlZqFrK2LXimtLOZzKZ4O/vj6ysLNY1lQdctayFSrDLrKPuU1TpEhNpPiod11COGzdoPhTdoUM0L5UuJobmo9Jxdfpo04bmQ9FxBf+dOtF8VLpt29R/IF66pP4ccdWNA+6p0y4LXOvxtNclCPLZ9l68MkA2Qivtzys3aaiU9/kEwdvgmloIAFev0rxUOq6SH64/tP74g+ZD0Xna8Bqu9Xja6xIE+Wx7L14ZIAcEBAD4K5NcmKysLHsXjYCAAGRnZ5eqsR1XaapXr47q1auXej5N05CdnY3q1auzrkkQbjeok/IoOmpdsEp31100H6qurHDWjVfUYTqe9roEQT7b3gspQD59+nSZvripWrUqGjRogJMnT5Y4lpqaiiYFO8tCQkIcagIDA1GlShWEhITAYrHgTLE/u1JTUwEAoaGh9g11xb1OnTqF3NxchIaGsq6pPBg5kkenGuzhjI5r41xFZvp0Ht2rr9J8VLqEBJqPSvef/9B8KDquMpR33qH5qHRcZShc6wH4+ldzwbUeT3tdgiCfbe+FFCD37NkTvXr1cunroYcecsvCIyMjkZSUVGRQx9GjR3H69Gn0LNh91b17d6SlpeH48eN2jcViQVJSEnoU7KyKiIiAj48Ptm7dWsR/y5YtaNasGRo2bIigoCCEhIQgsVjRakJCAipVqoSIgk8k15rKA64Aedkymg9Fx1VjWb8+zUela9mS5qPScfkAwFtv0bxUuv/9X5qPSketDFLpmjWj+VB09esDhRrJlEqlSur3Py+PtiaVjmvgTJUqwIABxpoBA3SdClv/akfvi6bR+ldzwTXch8tHELiQz7b3QgqQGzZsiAYNGrj0VZ8arRTj6tWruHDhAi5cuACr1YqbN2/av79x4wZGjx6N7OxsvPrqq/jtt9+wd+9eTJs2DeHh4ejVqxcAoE+fPmjRogWmTJmCffv24dixY5g6dSpyc3MxevRoAEC9evUQHR2NDz74AN9//z2Sk5MRFxeHxMTEItP7JkyYgB9++AGffPIJkpOTsWnTJixatAgjR460t6LjWlN5cP/9PDquDXEA0KULzUul4wqQVcM9qLonnqD5UHTUJicqndVKa8+mqvndvJm2HopOFURTg3GLhealmhLJdUuTa+AMAKxf7zhIHjBAP+6t2Ib73H130ecDA+nDfTh9BIEL+Wx7KbewB7MhTz31lBYWFlbq17qCjtiHDx/Whg8frrVu3Vrr2LGjNmXKFO3y5ctFfC5cuKBNmjRJ69Chg9amTRvt6aef1o4dO1ZEk5ubq82fP1+LiIjQWrZsqfXv31/btGlTiTVt2LBBe+SRR7SWLVtqkZGR2sKFCzWr1VpEw7WmwrijWffYsbRhCmPHGvv07k3z6d1bvab776d53X+/sc9999F87rvP2CcoiOYTFFQ+r0vTNG3MGJrXmDHGPvPm0XzmzTP26dCB5tOhg/q1rVunaSZT6T9vMtEb4S9YQFvTggXGPnl5egN+ozUFBek6CpwN/nNy9H+bffrojzk5zv287bU5ujbOvjZObt7U35tx4/THmzdd88nL07TERH0gTGLirXktglAYrs9keX22b/dBIW4NkLds2aLNnz/fnae4LXDHh5Rrklr79jSf9u3Va6pcmeZVubKxj48PzcfHx9jHUWBUWjBhRPXqNJ/q1dXXKCyM5hUWZuwzcCDNZ+BAY5927Wg+7doZ+6gCNoAesHFNidS0v4L24p8F23POBreeErQlJtKuUWJi+a5LJuAJgudwuwfIbutikZ+fj02bNmE5dfqDUK5w7Yhv2JDmQ9FxbdLjKo3QNJqPSsfZocHPj+al0lGbpah0XINLVD0+AXqPT64pkQD/LU2zWa81HjZMf7xV9YKe2DJKpoQJguBJuBwgHzp0CM899xy6d++Ozp07l/hq27YtNm3aZG9vJngWb7/NowsOpvlQdKUMIXRJxxWQ+vrSfFS6Bx+k+VB00dE0L5XOmZq38vDhHMcdG0vb8BIbSztnVBSQmqrX0a9apT+mpHh3vZ+ntYySKWGCIHgaLgXIhw8fxsiRI7F9+3acPXsWV65cKfFlsVhQr149vPbaa9xrFhjYv59H9/XXNB+K7soVmhdVV1a42nMdOEDzoehat6Z5qXSffkrzUem4/kDiGsoB6NnzSZOMNZMm0bPxgOdkfrnwtJZRMiVMEARPw6UAOS4uDhaLBc8++yy+/PJLrFy5EgDw1ltvYf369Rg/fjyCg4Mxf/589O7dm3XBAg9ct1hVnQCc0ZUyY/8Os44AACAASURBVMUlHVeJRePGNB+V7tw5mg9F98EHNC+V7tdfaT4qXUQEUDAl3SHVqqkDrTp1aOuh6ubO1dsBFg9kzWb9+blzaT4VFU9rGeWJJR+CINzeKLqFls7BgwfRu3dv/O1vfwMApBfc96xVqxaaN2+O5s2bo23bthg9ejRWr16NZtQmp0K5wXWLNTSUltULDVVratQAbtyg6VTHKeOGVT7UGTcqXaVKtD8QVL17AeDyZdqaVDrKuSg6qxXIyTHW5OToOqNgi6s1X2HmzgVmzgQWLwaSk/Wa49hY5zLHFRlbffWECUWzt4GBenBcniUknlbyIQiC4FIGOSMjA/fee6/9e1NBysFaqECsS5cu6Nq1KxYtWlTGJQrugOsW67/+RTsfRffoozQvlW7ECJqPSpeSQvNR6ai3qSk6rkCibVuaj0q3eLE6E5+fr+tuBX5+eu3qwoX6owTHRfGU+mpPK/kQBEFwKUCuUqUKsgrd5w4o2Op+6dKlIrp7770XB6gFmEK5wjVJq0YNdTeAJk3U2VoA6NZNraHouDo0XLtG81HpOMdxF/q7tEw6SkafoktOpvmodGfP0nyoOoGOJ9RXe1rJhyAIgksBcmhoKH788UdcK4gMAgICULlyZfz73/8uort8+TKys7PLvkrBo1HVc1LrPS9e5NGpxvpSdVx1sZy3j7navN11F81HpeNqqca5SU/wTmRKmCAInoRLAfKjjz6KtLQ09O7dG/sL2hx06NABmzdvxgcffICjR49i/fr1WLduHRo1asS6YIEHqxUYM8ZYM2aMuq2S1Qo8+aSxZtgwWnsmrgC5Xj2aj0rXowfNR6U7dIjmQ9FxlWtwZdmfeYbmo9Jxb9ITvBNPKfkQBEFwKUAeNmwYnnzySWRkZEAruEc/duxYmM1mfPTRRxg0aBCmTZuGnJwcjBw5knXBAg/btgHFKmJKcOmSrjPihx+A3FxjjcWi61ScOKHWUHRcGeRjx2g+Kt2GDTQfio6ra4jtdrYKlW7qVJqPSlc8a1hWneC9eELJhyAIgksBso+PD958801s2bIFLVq0AAC0a9cOn332Gbp164bGjRvjgQcewLvvvotBgwaxLljgYetWHt3rr9N8KLrdu2leKt3GjTQflW7fPpqPSsfVDQPgC2y5Ws9x9dO2bdIyQjZpCYIgCOWFS23ebAQW+43WsWNHdOzYsUwLEsqHP//k0aWm0nwoOkqLN4ruv/+l+ah0N2/SfFS6qlVpPhQdpX0dRVe5Ms1HpaMOylTpbJu0Bg8ufeOoySSbtARBEITyw+VR04J3o8rWUXXVq9N8KDqujWNcHRFUAzCoulataD4UXYcONC+VrmtXmo9KFxlJ86HobJu0in/mgoJkk5YgCIJQvriUQZ7rxBgqk8mEl19+2ZXTCG6EKxgdPRqYPl3tM3q0WtOqFfDbbzSdEVxDMGrUoE3uUmVHuQJtAHj7beDjj2k6I0JCaGtS6XbsoPlQdVFRQP/+MtxDEARBuLW4FCB/+umnMJlM9g16hTEVamKpaZoEyB4KV4DMNXACKDrNqyy6zEyaj0rHNfr68GGaD0X3ySc0r08+ASZPdny8Zk2aj0rHNdnPRnx8yclu8+bp5ReSQRYEQRDKC5cC5HHjxjk8dvHiRRw9ehRHjx7FM888gxBqqkooV376ia57+mnHx1evpvmsXg3062esSUujeal0BZPPlah0XG3nONu8OdMRwyhA3rKF5rNlC/DKK46P33EHzYeii48vvQY5PV1/XsosBEEQhPKCPUC28f333+P111/HypUrXTmF4Ga4OitwtWYD+EojKD2XKTpV+zqqTjWK2Rmdo8mHzuq4Nvu1bk3rPtK6tfFxq1XPHJe2bk3TN+lNnAgMGCAb9QRBEAT347ZNev/zP/+Dbt26Yf78+e46hVAGuDbXcXV6AAB/f5qXSse1AdGH+K9DpeMKagFg4ECal0pHbTaj0jVtSvNR6ZKSjEtnNE2/c5CURDufDatV7+W9erX+SP3jSRAEQbi9cWsXi6ZNm+IQ9f6yUK4MH86jq1+f5kPR3XMPzUul++47mo9KFxRE81HpuFqhAcDzz9O8VLrZs2k+Kt2999J8VDrKZkhndIBestG4sT7pMDpaf2zcWH9eEARBEIxwa4Ccnp6OvLw8d55CcBGucgaufsoAX1ZbVetM1fXuTfNR6TgD5H/8g+al0n32Gc1HpeMa7tKgAc2HqrPVMxfPStvqmSVIFgRBEIxwqQb5tKIw9dq1a9ixYwc2bNiAsLAwlxYmuJfz53l0nPW1XO3QuDbpvfUWEBen9nnrLePjzZoBJ0+qfZo1U2t+/12toeiSk2k+VF1ZiYjQR38bjT+vXZs2SU/qmQVBEISy4lKA3LNnzyLt3ByhaRqeffZZV04huBmujF1AAM2HouMKbM1m2gY7VXAUHU1bT3Q0sHmz4+O//krzoei4NkXWrUvzUem6dKH5UHUcOFPP3L17uS1LEARB8CJcCpAbNmzo8JjJZELlypURFBSEQYMGoU+fPi4vTnAfXBk7zk16e/fSvFS6GjVoY6tVJQ0JCbT1qHRXrtB8KDquwRxr1tB81qwBXn/d8XFngv++fR0fT0oy/iwC+nFKUOuOemZBEATh9sKlAHnr1q3c6xC8lIwMPt316zQvlY6rawSXD1fbOYCv9RzXOO5du2g+u3YBRvOCOINa7npmTqxWPcg/c0Y/f0SElHkIgiB4Im7dpCd4Ls5k7IxQjX12RkcdJ6zScW6K44BrQyTANwHR4CaQU7qcHJqPSscZ1EZE6C38HFWBmUx65xFKPTMn0lVDEATBeyhzgHz58mWcOXMGp0+fdvgleB5cGbsVK2g+FJ1qmARV9z//Q/NR6Vq2pPmodFzdOQC+qXzbt9N8VLoOHWg+Kp2t5McI6iY9s1kfTQ2UDJJt37/3XvlmbqWrhiAIgnfhUomFxWLBu+++iw0bNuDatWuGWpPJhKNHj7q0OMF9cG3SOniQ5nPwoLp2lCuLuG8fzUele+QR4D//Ufs88ojx8fr1aSUNlF7RdeqoNRRdjRr6gBOj7iI+Puose69etJ7KvXqpNZxERemjtufPL1q64uMDTJpUviOrpauGIAiC9+FSBvm9997D8uXLkZGRgWrVqqFBgwYOv+pTJ0kIXglX5wlOfvuNR8cVjDZpQvOh6LZto3mpdElJ6tZ7+fnqEpuICPUkQR8fdeaXq+THRnw88O67Jeu6rVb9+fLM2LprSqAgCILgPlzKIP/rX/9CjRo1sHjxYrRv3557TUI5QK18Uek4B4WkpdG8VDquuliu4J8rYAeA77+neX3/vXHWlqvEZvduWqC9e7fxHQTOP7SMMrY2yjNjK101BEEQvA+XMsgXL17E448/LsGxF/PTTzy6tWtpPhTdnj00L5XOYqH5qHRc0+aoFUYU3apVNC+VTlXvS9VxBbYXLtB8KDpPy9h6clcNQRAEoXRcyiDXrl0bVapU4V6L05w6dQq9DNJk48aNQ4sWLTB27NhSj3/xxRfoULB76Nq1a5gzZw4SExORmZmJ0NBQjB8/Hj169LDrNU3DkiVL8NVXX+Hs2bOoV68ehg4dijFjxhTxTUhIwKJFi/DHH3/A398fDz30EKZOnYpqhUbA/fHHH5gzZw5+/vlnAECHDh0wdepUNKHejy8jXC3MuAZXALxT+ThQlNeTdVzXGlCXIVB1v/xC8/nlF8ColTlXYMtVzgJ4XsbW1lUjPb3099hk0o+Xd1cNQRAEwTEuZZC7d++O3bt3c6/FaRo0aICdO3eW+PrHP/4BHx8fdOnSBVlZWQCAbdu2ldCFh4fbvcaNG4d9+/Zh7ty5WL9+PR588EGMHTvWHsACwKJFi7B48WKMHTsW33zzDV588UUsXrwYS5YssWv27NmDcePGoVu3bvj6668xf/587Nu3DxMnTrRrrly5gpEjR8JsNuPzzz/HihUrUKlSJTz99NPKTY9cNG3Ko+Ps8auqZXVWVxHh6oPsTP9iI7gy0XffTfOh6Lg2oHLhiV01BEEQBAWaC1y7dk17/PHHtddee027fPmyKxZuIz8/Xxs6dKj28ssva5qmaStWrNBatmxp+DN79+7VwsLCtKSkpCLPDx06VIuJidE0TdNycnK0tm3bavPmzSuimTdvntauXTvtxo0bmqZp2ogRI7ShQ4cW0SQlJWlhYWHagQMHNE3TtIULF2rh4eFaRkaGXZORkaGFh4drH3/8cYn19ezZU+vZsyfl5ZO5eVPTfHw0Tc9plf7l46PrjGjUyNjD9tWokXpNffrQvPr0MfapW5fmU7eusY/ZTPMxm4197ryT5nPnneprVLUqzatqVWOf3r1pPr17G/ssWEDzWbDA2CcvT9MCA409goJ0nYotW2hr2rJF7VV4fYmJmrZqlf5IWUdx1q0r+RqDgvTnBUEQPA13xB7ehEu5uOnTp6N+/fpYv349IiIi0KtXLwwePLjUryeeeII7pjckPj4e//3vf/FywdiuzMxMVK1a1fBndu7ciTvuuAMPPPBAkee7deuGPXv2wGKx4MCBA8jJyUH3YjuNIiIikJWVhQMHDuDmzZvYv39/Cc39998PPz8/7CiY/7tz5060a9cO1Qs1vq1evTratGlj17gbsxlQXBZUrarOat1/P+18FB21pF2lCwmh+ah0/v40H5WOc5hKWBjNS6Vr147mo9JxZZALZ1kdQc2ynj9PWxNVxzXgIyoKSE0FEhP1GvHERCAlpXxbzgmCIAg0XKpB/uGHH4p8n56ejnQHu3BMjsZZuYHc3FwsWrQIw4cPR52CYsWsrCxlgJySkoIGDRqgUrFRZsHBwcjLy8Off/6JlJQUAEBQUFARTaNGjQAAJ06cQO3atWG1WktofH190bBhQ5woKMRNSUnBww8/XGIdwcHB2LJlixOv2HWSkoCC6hOHZGXpOqPuA+3bA199pT4fJfhdvFitselmzXJ8/MABmo9Kd+MGzUelu3iR5kPRDR5MGxYyeLDxca6JfFw10ZxwboqzDfgoXjtsG/Dxz386F+Cazep+4IIgCMKtx6UAefny5dzrYGHDhg24dOkSRo0aZX8uMzMTVqsVf//73/HTTz8hJycHYWFhePbZZ+0Z46ysLPiXkga0barLzMy01zIX19k0WVlZDjW252zHs7OzHZ4vMzPT2ZftElwbma5coflQdBkZNC+VjquLRV4ezUel4wyQuVrYcWVZuTLIttZsjnBmmIZtU5xRJwvKqGkZ8CEIgnD74lKA3KlTJ+51sLBs2TI8+uijqF3ot7HZbIbZbEbjxo0RHR2NzMxMrFixAqNGjcLSpUvRtWtXh34aoa0ARUOF00sFV5aNK1vLiclE6wihurlBvfmh0tWsSev2ULOmWsO1kTEhgeaj0nFlkJ1pzabKwJrNwLBhwDvvONY8+aQ6qOVckyAIguBdVJh+AMnJyfjjjz/w0EMPFXn+jTfewLZt2xATE4PmzZujY8eOWLBgARo3boyFCxcCAAICAuzZ3cLYnqtevToCAgKKPGcjOzvbrrHVFDvysh0PCAiw/1xxTQ3VbF8munRRBwhms64zgtrtj6KjDl1U6QreKiUqXaGufGXSDRtG86HoqIGYSke9UaHScbVn42zNZrUCq1cba9asUXdW8bR2cYIgCEL54VIGGQD+85//YOPGjUhNTcWNGzccZj9NJhM+//xzlxdIZcuWLahSpUqJjXalYTabERYWhiNHjgAAQkJCkJiYiNzcXPj6+tp1qamp8PX1RaNGjXC+4F7zn3/+ibqF+kPZapNDQ0PRqFEjVKpUCSdPnixyPovFgtOnT+Oxxx6zn6+4xna+8uqDvHu3OkCwWtUT0DjrPbmyo1yt5ypXpvmodDt30nwouogIdYbcZCq/nrpc7dk4P0eqzC9Ay/zKgA9BEITbF5cyyAkJCRgyZAiWL1+O7du346effsLevXsdfpUHe/bsQcuWLXHHHXcUef6dd97BypUrizyXl5eHo0ePonHjxgD0vs43b94s0ds5ISEBERER8PX1Rfv27REQEICtW7cW0WzZsgU1a9ZE27Zt4efnh86dOyMxMbGIZvv27cjNzUXPnj0BAJGRkTh48CCuFCrMvXjxIg4dOmTXuBuu7BhXpwcAuHmT5qXScZVGcAXIpfwt5LIuKUldPqJp6ilxXN0wuO5E2OqGHb0nJhOtbhjg+2xzrkkQBEHwLlzKIH/00UewWq0YPHgwunfvjoCAgHLtVlEax48fR4SD31Rvv/02rFYrIiMjkZOTg6VLlyI9PR0zZswAAISHh6NHjx6YMWMG3nzzTTRo0ABffvklkpOTMaugXYKfnx9iY2OxYMEC3HPPPWjfvj3279+PNWvWYNq0afbM87hx4zB8+HDMmTMHgwYNQnp6OmbNmoWHH34Y9957LwBg2LBhWLlyJSZPnowJEyZA0zQsWLAAdevWxZAhQ8rhavFlx779lubz7bfAvHnGGq7NdVwT+bjKEDjHKBf7+8xQZzBkki1bz3UnwtbmbfDgkhlyZ4dpcH22OdckCIIgeBcuBcj//e9/0adPH8ycOZN7PS5z5coVe51wYf72t7+hTp06+Oqrr7BgwQL4+/ujWbNmWLVqFe677z67bt68eZg7dy5eeeUVZGVloUWLFli6dClatmxp18TExMDHxwdxcXE4e/YsGjZsiGnTpmH48OF2Tdu2bREXF4f58+dj5cqVqF69Ovr27YvJkyfbNQEBAVixYgVmzZqFp59+GiaTCZ07d8by5cuVLem44Bp/y5X1BfhKI6gBS3kFNpyjpv/8k+al0nFl2R10d3RJFxWlt02bMKFoiURgoB6IUtupcY525lqTJ2O16ncczpzR/2iIiJCgXxAEwaUA+Y477kDz5s2511Imfv3111Kf9/HxwahRo4q0fisNf39/zJgxw55VdgTFq1u3bujWrZuhJjg4GHFxcYYad2LLjg0aVPpxTaNlx7g2xAF8ATJX5perDzKXD6AHZhRUOq7SGM7sOKAHnAMGlC1g4878cqzJU4mPLz34f//9ihH8C4IguIpLAfK9995r35wm3N507gw4+NukhE4F121/LioR/3WodFwlHwDfgA+uP2y4ulgUhmOYBnfmtyIO+OAegiIIglCRcCnUGDduHLZs2YJ9+/Zxr0coJ6xWYMwYY82YMepsLWfwR60uKacqFLYyBE4ovZIpOq73zR0BMhdRUUByMrBgATBunP54/LgEfYB6CAqgD0Gh3tURBEGoaLiUQc7OzsbIkSMRExODyMhING/eHHfeeadDfeEaXcEz2LZNPbzh0iVdZ7TZa/t22vkoOq6hE5Uq0abgqTK/XJP0zGZaoEG5Zb90KW1NS5cC/+//OT6+Zw/NR6U7fJjmc/gw0KcPTctFaeUD8+ZJ+QAgQ1AEQRBUuBQgP/fcczCZTNA0DVu2bEGCg3FbmqbBZDJJgOyBbNtG1xkFyNw1qJ4EV8lHbi7Nh6I7cYLmRdWVlV276LpC+1TdTkUvHyjrxjoZgiIIgmCMSwHywIEDb3lbN6FscN1ir1sXyMhQ+xSareIQHx/aulQBadWqwLVrah9VqUarVsBPP6l9WrUyPl6pEi34pdQ8+/mpNRRdaCitdjw01Pg417RBTqjlAwMGeOdGO46NdTIERRAEwRiXAuS3336bex1COcNVyzp3LvD442qfuXPVmlmzgKlTaTojunYF/vUvtU/XrsbHX31VD6JUvPqq8fEmTYDfflP7lNMQRQDAihW0jXorVhgfj44Gis3hcagrL7gm6XkiXJlxzlZ4giAIFRG39gNITk72qF7Jwl8UGuJXJt2xYzQfio4SRFJ01avTfFS6tDSaj0pHDXwpuuvXaV4qXZUqQKGp6qXi56frjHBHz2mLRe808eKL+iN1gIwNzt7MngTnxjpbKzyg5CZTGYIiCILghgA5Ly8PmzZtwogRI9C/f3988cUX3KcQGFBl2Kg6SvaQqvvnP2leKt3atTQflY6SzaboKNlsqs5gL6xTuqQkddmHxaIeWa067qxuyhQ9KH/pJeDDD/XHKlX056lU1Lp4ZzbWUbC1wrv77qLPBwZ6f422IAhCWXGpxKI0Tp8+jbVr12LdunW4dOkSNE1DrVq1MHDgQK5TCIwEBfHozp+n+VB0nFP5OMjJ4dFxtsIbNQp47TWazghP3KQ1ZQrwzjsln8/P/+t5SqlO7dq081F1noI73rOKPARFEAShLJQ5QN6+fTtWr16NpKQk5Bf8hu/cuTOeeOIJPPTQQ/BV3ccVbgmUwR0UHWfvYl9f2ma28vpImc20oFUVTFSpQiuNUJUzAEBwsFpD0XFt0ureHaBUUalqfS0WvQWbEfPm6edSbUDkahfoabhrY11FHIIiCIJQVlwqsbh8+TLi4uLQq1cvPP/889i2bRvq1KkDTdMwcOBAfPrpp+jbt68Exx7Md9/x6Lh6BQN8tbohITQflY6rQwO1vRlFV78+zUuls23SMiIoSL1Jq3t3dSa2dm11ALZwofqPkfx8XafCHcNLrFa95eHq1frjrRigYXvPHDUQMplo75kgCIKgxqkAed++fZg0aRIiIyOxYMECnDt3Dr1790ZcXBy2bt3qrjUKboCrny71byCKjtIKjqLztAl4nH2QuTCbgWHDjDVPPqnOjpvNQLduxppu3dQ+O3caH3dGV7ymtqy6+HigcWOgRw+9G0ePHvr38fG0n+fCtrGutE16gP68bKwTBEHggVxi0a9fP5w4cQKapiE0NBRRUVEYOHAgatWq5c71CW6CK8vaoAFw8qTah3Lbt317wMHMmRI6Iyh9mSk6ruD/+HGaD0WXmkrzUumsVj0basSaNcDs2cYBl8UCfPutsc+33+o6o9IIzn7Ktkyr0YY2aqa1og8cEQRBEEqHnEFOTk5Go0aN8Nlnn+Hbb79FTEyMBMdeTO/ePDrODVEffkjzUum4NtdxBdqcXSxUdbpUnTO9go1YvFhdbmC16jojRowwPu6MzpZpNZlKb2FmMtEyrZxt1TiwrccRJlP5rkcQBKEiQw6Q77rrLpw8eRLPPvssYmNjkZCQAKv8n9hrUQUsVN3339N8KDquHr9c3TC4fLKzaT4UHVc2mqsjQnIyzUel69VLnR2uVs147HlhOFqYcbdVKyueth5BEISKDLnEYtu2bfjhhx+watUqbN26FYmJiahduzYGDhyIwYMHo3Hjxm5cpsDN77/z6Kh/I1F0Pj50XXn5cIy+9kS46r25NlaazcDnnwODBjnWfP65c/W1ZW1h5mmt8DxtPYIgCBUZ8q/2SpUqoV+/fvjiiy/wzTffYMiQIcjJycE//vEP9O3bF9HR0TCV164nocxwTZvj8gGAsDCal0pHGaFM0dWrR/NR6TjLUFq0oHmpdFy9mZ97juZD0UVFAevWlcz63n23/rwrtb62FmbDhumPzgTY7mqr5ipcf9QIgiAIalzKfTVt2hQzZsxAUlISpk+fjpCQEBw4cACapuGHH37Am2++id+oc4OFW0KXLjy6xx6j+VB0NWrQvFQ6R7v8ndVlZtJ8VDqjrKizOsqGSIpuxw6aj0q3ezfNh6qLitLXnpgIrFqlP548eWs2wklbNUEQhNuXMt0c9vf3x1NPPYXvvvsOy5YtQ58+fWCxWLBmzRo8/vjjGDp0KOLLuxeSQOKuu3h0nJP0uAJbrrZqXDXR69bRfCi6a9doXlRdWdm2jVcHlC3ry4ltsx9Q+mY/oHzbqnH+WxMEQRCMYauefOCBB/DBBx9g69atGDt2LOrUqYNffvkFr1Hm4grlTiVi9blK17QpzYei48rYUmuCVTpq4KPScb0ugO+1USenqXScY7Q9EY7Nflx4WsmHIAhCRYZ9e1HdunXx4osvIjExEQsWLEDHjh25TyEwwFVi8cYbNB+KTjVCmKqjjGym6Lh6RXMOU3n0UZqXSsc1Aa9mTdp6qDpPJCpK7ytduOwjJaX8yz6k5EMQBKH8cNv+e7PZjL59+2L58uXuOoVQBo4e5dHFxNB8KDqutmoXL9J8VDqu4RWcm6seeIDmpdJxTcC7coW2HqrOU/GEsg9PK/kQBEGoyHhhgyqBA66JbLt20XwoOq4aZC64eg5zdvrgGl5isQDffGOs+eYbXWcE1+dIoOFJJR+CIAgVGQmQb1O4+tdy1cQCfJvr7riD5qPScW2I43pdAPDnnzQvlW7hQnVdcH6+rjNCNo6VP55S8iEIglCRkQD5NiU2lkfXqRPNh6K7cYPmpdKFhtJ8VDqu2mGugJ2TnTt5dFxlKIJzeELJhyAIQkVGAuTbFK4JeJwb0Pz9aV4qHVepBlfXAK7NhwBfr2iu941rs2dhrFa9Ldzq1fqjTLQXBEEQyhsJkG9TJk3i0f34I82Hojt3jual0qWk0HxUOq6hHD/9RPOh6FavpnmpdKdO0XxUOurwTKouPh5o3Bjo0QOIjtYfGzfWnxcEQRCE8kIC5NuUfft4dFxlEZxeqo1lVB1XJppz82FODs1LpeOqr+aqiQb0IHjw4JJBeXq6/rwEyYIgCEJ5IQHybQpX0MY1TAPgK/vgKkPggvMaeVrf4Xvu4dFZrcCECaV/3mzPTZwo5RaCIAhC+SAB8m3KQw/x6Lg2xAF8tbpcAz4CAmg+Kt3f/kbzoegOHaJ5qXRcgW3r1jQflS4pybicQ9OAtDRdJwiCIAjuxusD5NjYWDRr1qzEV+/eve2a/fv3Y/jw4QgPD0eHDh0wceJEnCtWyHrmzBlMnDgRHTt2RJs2bRAdHY2DBw8W0VgsFsyZMwcPPvggWrVqhb59+2LdunUl1vTVV1/hkUceQatWrRAREYE5c+Ygt1gPL8qa3EmfPjy6p56i+VB0XN0euIagcGVrjx2j+VB0tWrRvFQ6riw711CWM2doPlSdIAiCIJQFrw+Qs7Ky0Lt3b+zcubPI19q1awEAJ06cQExMDIKDg7F27VrExcXhzJkzGD16flk8PgAAIABJREFUtD1otVgsiImJQXp6Oj766CN89dVXCAkJQUxMDNLS0uzneuONN7B+/Xq8/vrr2LhxI4YNG4bp06dj06ZNdo3t+JAhQ7Bx40a88cYb2LBhA2bOnGnXUNbkbrhGDXNt9gL4stFcNciVK9N8VDrOAHnxYpqXSte2Lc1HpePq9MHlc7sgnT4EQRDcjOblPP7449r06dMdHp86daoWGRmp5ebm2p87ceKEFhYWpn3zzTeapmna119/rYWFhWnJycl2TV5enhYZGam9/vrrmqZp2qlTp7RmzZppa9asKeI/adIkrU+fPvbve/XqpU2aNKmIZs2aNVrz5s21s2fPktdUmJ49e2o9e/ZUXgtnGTBA0/Sb16V/DRig9njoIWMP29dDD6m9OnWieXXqZOxTpw7Np04dYx9fX5qPr6+xT8OGNJ+GDdXX6PnnaV7PP2/ss3IlzWflSmOfmzc1zcfH2MPHR9cZkZenaYGBmmYyle5hMmlaUJCuc4a8PE1LTNS0Vav0R2d/3hNZt06/VoWvT2Cg/rwgCAIX7oo9vIUKkUGuWrWqw+M7d+5EREQEKlWqZH/unnvuQWBgIHbs2AEASEpKQuPGjRFSqCjVbDajc+fOds2uXbugaRq6F0upRkREIDU1FWlpafbH0jT5+flIKiigpKzJ3VgswMaNxpqNG9VZ1uxs2vkoOq42b1z9lPPyaD4qHdfmQwA4fZrmpdIVH1Xsqi4piTaRT1U7bDYD77+v/3fxlnC27997z7mBGJ7YMq6smV/p9CEIglA+VOgAOTs7G+fPn0dQUFCJY8HBwThx4gQAICUlBYGBgf+/vfMOi+rM/vh3aNLFLlZEHVSwoDGWiIAlxK5oNOoqxhJdSyy4trVEY4oxscToL2jM2mJcW9AoqxEjih0sSRRbpAgWjGJhKALD/f0xzmT6fQdemML5PA+PO/d+58x7h7vhO2fOe45ezcOHD5GXl4eUlBRUqlQJtWrV0tA0aNAAgKJsIuV1Y13t1/P29oajoyOSk5OZ11TWrF3L1p5MaVoMIWaOTNG5uLDFEtPxqmfl1eO3ShW2OKw6HnTuLD7+285OfMAHzz7Y4eHA3r1AnTqax+vWVRw3ZZSyJRrJ0hp26vRBEARRfli9Qc7OzsatW7cwduxYdOnSBb169cKSJUvw5MkTyGQyAICbnlShu7s7srOzASiMtCGN8jUMGXFtjb7Xk0gkcHNzg0wmY15TWXPgAB8dr6wvALx4wRZLTPfqFVscMZ2YgWTV8cpEA4CnJ1ssMR2vzG9sLNt6WHUA+wcTQ4gZSUEofyPJw7BTpw+CIIjyw6oNclFRESpXroysrCyMHDkS33//PaZOnYr4+HiMHDnS6HMFhkbAvDSs8IxVXhipbjFZx2tQCK/ML6/+xbxMLQCI3NbMurg4tjisOh7wyvqKGUmgfI0kr8wvdfogCIIoPxzEJZaLg4MDTp8+rXFMKpWidu3aGDFiBI4cOQIAqqytOjKZDJVf97Dy8PBAjp4iWeXzPDw8RDWenp4qg6v9eoIgICcnB56envB43TRXbE1lTZ8+wJkzbDpj1KrF1lZNqzJFL7y6RlStCjx9Kh6HpRXa48ficcR+ZQEBwOXL4nECAsQ1llYXXbcu27WJ1TKzmsgBA8Q/kNy/L74eU3SlxZTMr7GuMdTpgyAIovyw6gyyIZo1awYAePHiBby9vZGWlqajSU1NRePGjQEAvr6+BjX16tWDi4sLfH19UVBQgIda6ZnU1FQAQJMmTVSb/LRjZWRkoLCwEE2aNIGrqyvTmsoaB8aPRmI6XmUIANC1K1ssMZ12DWtJdbzGMf/6K1scFp1YTTirLiuLLY6YbvBgtjhiOp5Z37/+YlsTq6608Mr8BgUB9eoZ/uZDIgHq11foCIIgiNJh1QY5OTkZc+fOxe3btzWO//HHHwAAHx8fBAcHIz4+XqO/cFJSEh48eIBu3boBAEJCQpCeno4///xTpSkoKEB8fDxCQ0MBKDpR2NnZ4VctFxMbGws/Pz/UqVMH9evXh6+vL06cOKGhOX78OBwcHBD0+i8Xy5rKmnv3+Oh4dYwAgFat2GKJ6Viyxyw6XiUfPOu0nz1jiyWm49UNQ8/e1hLpeGZ9a9Rgi8WqKy28Mr9l0emDIAiC0I9VG2Rvb28kJiZi1qxZOH36NNLT03HixAksXLgQPj4+CAsLw/jx45GTk4MFCxbg5s2buHjxIubPn4/WrVuje/fuAIC3334bzZs3x5w5c5CQkIAbN25g3rx5KCwsxPjx4wEAtWrVwogRI/D111/jyJEjuHv3LqKionDixAnMnDlTtabp06fj6NGj2LRpE+7evYuYmBisX78eo0ePRrXXkzlY1lTWsCaqxXQ8v/bVM5SwRDqWsghTdKWFV000wC87bmllCLwMO8CvhR0veGZ+lZ0+tNder57pnT4IgiAII5ixBzMXHjx4IMybN0/o2rWr0LJlS6Fnz57CsmXLhGfPnqk0v//+uzBy5EihZcuWQvv27YU5c+YIWVlZGnH++usvYdasWcIbb7whtGrVSoiIiBBu3LihoSksLBRWrVolBAUFCf7+/kLfvn2FmJgYnTUdOHBA6N27t+Dv7y8EBwcL69atE+RyuYaGZU1KyqJZN68BD3PmsA2cmDNHfE01a7LFqlnTeBxDwyb0DZ8ojzhNmrDFadJE/D3asoUt1pYtxuP068cWp18/43F27mSLs3On8TgjR7LFGTlS/D1SDh0xFqckQ0dKw759ivtE+55SHjN1yIctDkAhCMKyqOiDQqx6kx6gyCJ/9tlnRjUtW7bEjh07jGqqV6+Or776yqjGwcEBM2fO1MgY66N///7o379/qddUltjbA05OxssDnJzEv65Vm8Rdah2vrhGszUDKq2kIa+c+Fh2vkgZeWVZe3yDwHDijLEUYMkT/71giKf9SBGXmd/p0zVrrevUUazE182tvLz4GniAIgig5Vl1iQZScuDjx2tn8fPE2Xzzrax0d2WKJ6XiVNPAaXMKrvzPAr/uE2AAQVh2vgSNdurCth1UXHg7Mnq1rgu3tFcdNNaSlnYCnXFNqKnDiBLBzp+LflBQqiyAIgrBEyCBXUI4f56PLy2OLw6LLzWWLJaZzdmaLw6orLTxrkHl1xNAzyLFEOl4DR6ZNYzPa06YZ1yjZvx/48ktdI1tcrDhuyiQ9SxxZTRAEQZQtZJArKImJfHQ8zSivoSO8WtjxMuw8R03z+mDTubN4iYG9vXjml9fAEScnIDLSuCYyUqETg+dIZp4jq8loEwRBWA9kkCsovIxtzZpscVh0Xl5sscR0rLNWymkmC7e6YUA8W8uqO3tW3CDK5QpdeawHADp2LN15JbxGMluq0SYIgiDKHjLIFRReX/vzLB8oKGCLJaZTay/NRVdaeNUyA/w2xfFq88YrOy6XAx98YFzzwQdsZpTXYI7yMtqCwG60CYIgiPKBDHIFhVcXA55Ty3gNweCVHWf5Op9Fx7PHL6/BLLx+b7x+Z3Fx4oNbnj5lK+ng9SGivIw2wD4lUAmPTYMEQRCEYcggV1B4fe3Psz2XuztbLDGdpydbHDEdr/IRnhnt339niyWm41kXzQNetdXA34M5jMEymOP1XB9RxHS8h7JQLTNBEETZQwa5gnLoEB/dkydscVh0vDK2jx6xxRHT8cqy85p+BwBq09BLpUtIYIsjpqtalS2OmI7XplFAsblQLDtcu7b4JsXXE+tFEdPx/JaFapkJgiDKBzLIFZR79/joeG7S4tV9QiZjiyOm47We9u3Z4rDoiorYYonpXr1iiyOm47Wxkmeddl6euLFPSBBvPZiayrYmMV2NGmxxxHQ8Nw0SBEEQxiGDXEHhNZRDbNiIKbqbN9liiel4bfY7f54tjpju8GG2OCw6sV7BrLrTp9niiOn+8x+2OGK62rXZ4rDo/vUvtlhiusaN2eKI6Xh9E8Fr0yBBEAQhDhnkCkqPHnx0PPsg88qOVqrEFkdMx2tqHa/NXgDg4cEWS0wntmmMVcdrSiCvUg0AuHOHLZaYbvJktuElkycb1/CqieZ5HxEEQRDGIYNcQeGVQbbEGmRexpYXvMoZAH5dLHi152vUiC2OmI5XOQsA+PqyxRLT2duLD6Vxc2MbuLJ2reH3UiIB1qwRj8OrOwdBEAQhDhnkCgqv2lFeRhvgl0Xk1Q2DV6cPnuaPl0Fu0YItjpiuUye2OGK6kBC2OCy6/v3ZYonp4uPF69Szs9lKGsLDgb17de+V+vUVx8PDxWMoM9HGjDZLJpogCIIQhwxyBUUsW8Wq4zlJj1dPXV4lFryMNs9hKi9fssUS002cyBZHTMerVCMoiK2cgcX8PX/OtiYxHe/2bOHhig19J04AO3cq/k1JYTPHwN+ZaED3XlE+ZslElxXUm5kgCFuCDHIFhVfGrlcvtjgsOl6lCLxqmXnBs9MHr016DRqwxRHT8Rx9LaYpLhYffQ3wK0Xg2Z5Nib294v9Tw4cr/jXVzCoz0dob+urVY89ElwXUm5kgCFuD8ctfwtYIClJknfS1jFIikYhn7HjVDQPG12KKjpfR5lVfzcvUAuI1sabqSguvrD/PbG1QkCKrb6w8wt1d/N7m1Z6NN+HhwIABitKOhw8VRj8oyHyZY2VvZu3/Xyp7M5vTuBMEQZQUMsgVlPh4caMpCApd9+6GNZmZbK/HquMBr9ZzvNrF8cxo86r55jX++vp1tjhiOp7juOVy8cmNOTkKnTFTybP1HG+UmWhzI9abWSJR9GYeMMB8Bp4gCKIkUIlFBSUujo/uxAm2OKw6HvDKIPMaOMLTIPNq9cVSqsCi4zXW+7ff2OKw6NatY/vwt24d22sShqHezARB2CpkkCsovEwbr01jlgiv+lqem/TEpr+x6nhtrhs4kC2OmE4s42uKjtcQlMeP2eKw6gDb28hGvZkJgrBVyCBXUJ4+5aOrUoUtDouOp5G0JHjWDfMazMKrpGH6dLY4YrrOndnisOh4dR/h3XfYFjeyUW9mgiBsFTLIFRRetaMtW7LFYdHxGu3Lq38xL3gNrgCAgAC2WGK6OnXY4ojp7O3Fjaa7u3j9aZs2bOth0Y0axRZLTMez77ByI5t2Rl65kc1aTTL1ZiYIwlYhg1xB4VUaceECWxwWHa8NaLzKB3jV1966xRaHRcerawSvbD3LMA2ZTLwGledExu7dxTPozs7GN58C/PoOi21kAxQb2ayx3MLSezMTBEGUFDLIFRReAz6ystjisOiys9lisepKC6/SCF7dMAB+dbG8suy8alB5DpwBxCcJsk4kNNR3uG5d9vZlZbGRzZJqmS21NzNBEERpIINcQXnzTb46HvCqr+UFL2PLs7aa15oaNWKLI6bjZWx5foiIjxevnX/61DRDqp39Ze3ZDfDfyGaJtcylnRJIEARhaZBBrqD06MFHx3OYgp8fWyxWXWnJzeWj42mQLW1QCC927uSn4zl0RFk7rK01pXaY50Y2S65lLu2UQIIgCEuCDHIFpUMHPrqGDdnisOgszfzx6qfMa0IgwM+0p6ayxRHTJSezxRHTPX/OFodFx6sG3VjtMKA4zlI7zGsjmy3XMhMEQVgaZJArKP/6Fx/dH3+wxWHRsWa/yitLxsvY8uqnDPDrF8zr2j79lC2OmI6XYQeAY8fYYonpxGqHAbbaYV4b2WgoB0EQRPlBBrmCkpDAR8drcAXAnvmqyBkyXmabV4cOSxwUwysbzbNUg8dGNhrKQRAEUX6QQa6g8DJarHWGVI/IB15lKLwGhdSuzRZHTNekCVscFh2vHs9//cUWh1VX2o1sNJSDIAii/CCDXEHx8uKjq16dLQ6rjjAOL0PKq/vEwoVsccR033zDFodFN2gQWywxHc8NqEpKs5GNhnIQBEGUHzZhkKOjoxEeHo7AwECEhoZi0aJFyHrdeDc2NhZ+fn56fxITE1UxXr58iX//+9/o3LkzWrZsiUGDBuHEiRMaryMIAqKiotCjRw8EBASge/fu2Lhxo856jh8/jvDwcLRs2RIdO3bEwoULIdOapnDnzh2MHz8egYGBCAwMxIQJE3D37t0yeHf0w+srdl41sYDtjprmyaNHfHT/+x9bHDHd99+zxRHTDRvGFodF9+IFWywxnXY5RGl1pUVZy2xs0yAN5SAIguCD1RvkLVu2YP78+Rg0aBAOHDiApUuXIj4+Hh9++CEEQVAZ07i4OJw+fVrjp3Xr1qo4U6dORUJCAr744gtER0eja9eumDJlCi5duqTSrF+/Hhs2bMCUKVPw888/Y9q0adiwYYOGST5//jymTp2KLl264KeffsKqVauQkJCAGTNmqDTPnj3D6NGjYW9vj61bt2L79u1wcHBAREQEXpZTsWanTnx0PId7ODiwxWLVWQo8jT+vOm1eA0d41fveu8cWh0XHK/OrzNgagzK2BEEQtolVG2RBEPDdd99hwIABGDVqFBo0aKAytgkJCUhPT4dMJoOjoyO8vb1Ro0YNjR/H1zOLExIScOHCBSxevBhdunRB48aNMXPmTLRq1QobNmwAAOTl5WHz5s2IiIjAoEGD0KhRIwwcOBCjR49GVFQUXr3u9bVhwwa0bt0as2bNQpMmTdC5c2csWrQI8fHxuHLlCgDghx9+QF5eHlauXIlWrVohICAAK1asgEwmw48//lgu7x2vGmSeHRosLWPHy7DzrNN2cWGLJaZzcmKLI6Zr144tjpiO12Q/gN99pMzYSiT6u09IJOWbsZXLgQ8+MK754IOKvYmVIAiCF1ZtkCUSCQ4dOoQFCxZoHK/5unDyyZMnyM7OhqvIjqXTp0/D2dkZHTt21DjepUsXnD9/HgUFBbh8+TJyc3MREhKioQkKCoJMJsPly5fx6tUrJCYm6mg6dOgAJycnnDp1SvV6bdu2hada/YKnpydatWql0pQ1vAYz8MyOFhayxWLVlRZe18bzQwSvDHK1amxxxHQDBrDFEdPNncsWh0XXubP470QiUejE4DFqmhdxcWwTAuPiymM1hDmxpFHjBGGrWLVBBgAvLy8Nowko6o5dXV3RtGlTyGQyUYOckpICb29vOGilAhs2bIiioiLcu3cPKSkpAID69etraBo0aAAASE5ORlpaGuRyuY7G0dERderUQfLraQkpKSmopycV1rBhQ5WmrHn2jI+OV0YTEP/jb6qutPAy7DwNslYpe4l1vDo08BoU8nrLgCgsurg48f7NgmCakdT+3bD+Tnly/DhfnaVC5s84ljhqnCBsEas3yNrExsZiz549mDhxIjw8PJCdnQ25XI7FixcjLCwMQUFBGDduHM6fP696jkwmg5ubm04sd3d3AEB2draqlllbp9TIZDKDGuUx5fmcnByDr5fNWtRbSqpW5aPjZdgAID+fLRarzhbhNeCD14cRXpnf775ji8Oi276dLRaLbv9+YPBg3XZ3Dx4ojpenKbl4ka/OEiHzZxxLHjVOELaGTRnkmJgYzJgxA/369cPEiRMBAPb29rC3t4ePjw/Wrl2LVatWwc3NDWPGjMGZM2eMxhMY3AiLhhWescTg2X2CsD54Zcd53UesDVxYdLw+tMnlQESEcc2YMaZlOEuTHeU5lKcsKG3ml8yfcWjUOEGULzZjkH/44QdERkbivffew4oVKyB5XYS4ZMkSxMXFYezYsWjWrBnat2+P1atXw8fHB+vWrQMAeHh46LRhA6A65unpCQ8PD41jSnJe/+X39PRUlXoYiqU87+HhoXqetqZy5colun5T4dXFgKjY2DH+F4RVxwOW2mIW3a+/ipvo7GyFjoXSZkd5ljPxprTXRuZPHBo1ThDli00Y5D179uDjjz/GrFmzsHDhQtiJ/DW2t7eHVCpFZmYmAMDX1xcPHz5EoVa6LDU1FY6OjmjQoAF8fX0BAPe0+kwpa5ObNGmCBg0awMHBAWlpaRqagoICPHjwAI0bN1a9nrZG+XpKTVljaRviCOuE18AZXoNLAECte2OpdFu3ssVh0fHIjrZvz7YeVh0veFwbmT9xaNQ4QZQvVm+QL168iCVLlmDevHmYMGGCzvmVK1dix44dGseKioqQlJQEHx8fAEBISAhevXqFs2fPauiOHz+OoKAgODo6ol27dvDw8MCvWumi2NhYeHl5oU2bNnByckKnTp10BoycPHkShYWF6NatGwAgODgYV65cwTO1HXBPnjzB1atXVZqyhpexISo2ubl8dDw/sPGqr05NZYsjphPLjgoCW3a0Rw+29bDq1NdX0tIIXplfMn/i0KhxgihfrGzkgiaCIGDZsmVo06YN+vTpg7+0ttwru1d8/vnnkMvlCA4ORm5uLjZv3oz79+9j6dKlAIDWrVsjNDQUS5cuxUcffQRvb2/s3r0bd+/exaeffgoAcHJywuTJk7F69Wo0atQI7dq1Q2JiInbt2oX58+ereipPnToVI0eOxIoVKzB48GDcv38fn376KcLCwtCiRQsAwPDhw7Fjxw7Mnj0b06dPhyAIWL16NWrWrImhQ4eWy3vHa8ADUbHhtbEyPZ0tDouOVzaaV0mDWHYU+Ds7qtUhUoOQEMDd3XjZh4eH8Rja7N+vMLjq66tXT9H/maWFnSmZX2PrIvMnjnJwzf37+j+QSCSK8zS4xgopLFRsHlD+5OZqPjZ07I03gHfeMffqbRarNsgPHjzAnTt3ACh6FmszdepUREZGokaNGtizZw9Wr14NNzc3+Pn5YefOnQgMDFRpv/rqK3zxxReYO3cuZDIZmjdvjs2bN8Pf31+lGTt2LOzs7BAVFYVHjx6hTp06mD9/PkaOHKnStGnTBlFRUVi1ahV27NgBT09P9OrVC7Nnz1ZpPDw8sH37dnz66aeIiIiARCJBp06dsG3bNtGWdLygEgvCkigq4qcrKGCLJaZr2xaIjRWP07at8fP377Oth0VXqZJxg8w6AAb4uzRC22wpSyNY+jzzyvwGBSl6bhvL6lerVrHNn3JwzZAhCjOs/ntT9v2mUeOcKC5mN6o8Hpe0uN7VFXjxwvrGy1oJVv2u1q1bF7du3RLVjRkzBmPGjDGqcXNzw9KlS1VZ5dLE6tKli17Drk7Dhg0RFRVlVFOWODmxZf9M+YNLECWFp0HetIkt1qZNQK9ehs/zykTzMpHx8WyDQsSytYB4aYREoiiNGDDAuOHiNXCGYEM5uEZf1n/NmvIdXFOuCILiDxYvUyqmYf2UXRa4uGj+uLoaPhYcTOa4DKF3toLi5QU8esSmI4iyhucwlQMH2GKJ6WrXZosjprt8mS2OmI5nnS6v0og//mBb0x9/AG+/bXw9vMy/rRMervjgEh+v+F17eysy6+WaORYEzbKAssiqahtac+HkpN+sahvX0j52cQGcndlHuBJlDhnkCoqlTa0jKja8BqAA/Mw2L4Os1fimxDqenT54mW1eGxlpk55p2Nvr+aBQVMTflBo7Zo5xkoAiY1oSw1qSY87OVLNSgSGDXEGhGmTCknB0ZLvXXu+FLRd4lX34+AAiM4lUOmOwlimy6HhtimPtSimms/RNenJ5CTK2yjpWnqbU2DFz/cfazs70TGlpjpXnfwSICg0ZZIIgzE716mzZwerVxTVeXmzdV8TKh7ZtE4+h1IWFGT7/3nvADz+Ix3nvPePnWXsAx8cbL2cAFAZPrCOGu7v4prjJk4HZs42bcnt7hU5sPWXeoUEQgFevTDagNy7n4URMHopkeXBFLu4jD7845yGweR5qexgxvK9elWKxpcTZuWxKAfSdc3SksgDCJiGDTBCE2eH5FfvLl2yxxHS//84WR0wXE8MWJyYG6NuXTVta5HLx3tTKzfXGMqVOToo1G6vn7tvXwGZftTpW+7w8bFqQh8jJuXBBnsaPK3LhIuThw7A82K8uRelAfj57LY8azV//aJAP4IoJQdTrWMs6y+rsXL6jKwnCRiGDTBCETcGrBplXicWff7LFEdOFhADLl4vHYdnEtmGD/uu3g/xvU1qchx+X5CFiqGHTWZyTh84n8tAeuZqGVs3gev0vD0JgLiT6MrRqi3jn9Y9BvhO/Lmbs7UUNZ7GzC/YddsGTXBfkwlXDtufCFflwgWs1F6z7zgX2HiKGl+pYCcLqIINMEIRNYWfHZpLFkmwvXrC9npjOzY0tjl5dcbGqvVWQTy6aGjCh6seCz+UBJ42XDgy6lYeeep7rBK061s9f/xjADsAcsQsrAHDVuESQSBTGU3DRMaLK/w0XV/Qa7AI71xKUAmgfY6hjPRUHDN0jInoKDPWizhoEYYuQQSYIwqaoXh14/JhNZwz9JRgCKuGVhrGs9jwPuGj4K/4FjnlobcTQKn+kCblAE604anWsTgBus7wBi8QlDRnC5MEZRY4u8Khh2JCmZrrg2BldM6ttcKfPdUFIL8Pm9eS5SgjtJlLHmgecGMduRlUb626XrBUaddYgiIoNGWSCIKybwkINU9oCeagnkmV1QR5q5uYBM3INGttzebmopPVcZ+TDDlp1rHkAOhheXvvXP6KITNIrlDgiRzBsQpU/LtVcMfA943Wqy750wYkLhmPlwxkC7NC/l/H64tQ44INQ8Uub/g6AYCOX/kA8BsA+lbC0I7QBy++sQRBE2UIGmSAIrijrWLUNKc4armVdYCCrqs/koqFWDK0WCidYFyoDsNbw6ZYiTy+CvcJMSlxQo4Hhr/QPHnPB/Wf6zaz64zq+LojabrhswK+pPVJSxC+rkScw8Bvjmj8PAnEXxGNVrmz8PK/uE3/9Jb4WVh2PEdpAOXXWIAjCYiGDTBC2jlodq9KUtjJiQrUfY6rhWtZrejK0OnWsSt4yvMRPTLkeYwM1XFzwJM94llX9f8+YZ7iWtVe4C2TFhk1tERR1rPZ2QFGq4SWNcAdyGC7LLROI6mz4fO3aYDLILANORo0Ctm9n0xnD3l6RlR08WP95QVCMQBYrbahRQ3wtLDpeI7SBv69tyBDF89RjKruasVwbQRDWCRlkgih3NOtY1c2lanMKD2MbAAAgAElEQVSVga/9P2MwtMrHqJr3d3srLX4zZbnrDZ/yF3lq/usihVy4om5jw1/5b9ppOLOqfezkBQNxKlUCJBLUMKEl64zPDJ87wtgNQ2wwB69uGOPGAefOiccZN05c062bohuYnltDhYuLQlce1K3LR8drhLaS8HBFxllfucaaNezlGgRBWB9kkAkCUPVjVTelbU3Jsk403Iv1ph69Th2rkhDjy5xnyjU903PM0RFwccGjl8a/7lc/9q9FhutZu/U1XDqgrGNVIhhpY/bBThOu600TtKXAwYHN3DqI/FfUyYltZoTeXsFqPNP3+yyFTgyWlsFyORARYVwTESGesVWWMxgzt/Xri5czlMXGuvBwxfpNnqRHEIRVQwaZsEjU61j11rMeMlzP+qUp9azKSVh60oCXTFnwRsOn/Iw8TQ47DXPZ0M94i6pV3xo2tNqPL9/QE+e1m/M2Icv6r2WGzzHX+1oh1asDjx6x6YxRqRKQnS0ep1Il4+evMA6mYNEdP248ewwozh8/bnwq3/HjxqfxAYrzYnHs7YHhw4GVKw1r3ntP3JSW1cY6e3tq5UYQFQ0yyAQbgqD4i6llSjswft3vgjxgnPHerA/UnlcJBcbX08/wqUhTrkvfH/fXZjI9Szejaqiedf5Sw62wgsIMm9hCOAL4260KN40vN/JbE66tmQlaQgdeGdsCkVuZVcdSf8yqY6k/VuqMGVtTxnEbiyOXAz/+aDzGrl3AZ5+VTyaaIAiCDDIBAJiGrzEIP+k1uHDRX8cKAOdNeZHvjZ82lNTJ12i2pTCZLdsbrmdd8Y3+DVn6jv1xRyvG6zpWAGhgQpZ1/mLD506zhyEsCJayCBZdXh5bHDEdrziAeNaXVZeayhZHTCdWOwyw1Q7zykRro+qpTCUWBFFhIINMAABmYjUaIVX/SW1v/LqOFS4uSMkUN6HKx4s/Nd6btU1n3eflwxnF0P1LJFw0fC3zRFpcadDEBC1BlABem/R4GXYAeOstIDqaTWeM+vXZ1iSm41U7zCsTrQ6PnsoEQVgfZJAJAEB3HEd7JOg1uDdStMys2q4kXxOyrIvnGz9vUmcFgrASWDa7seh4xQGAVq3YYonp3N3Z4ojpeNUO88pEK+HVU5kgCOuDDDIBAEiBL1Lgq/+kT7kuhSAIPTx/zk+XlsYWS0yXmckWR0zHaygH66Q9Fh3PnsoEQVgfduISgiAIwtzwNMgff8wWS0zHy5Aqh3IAfw/hUGLKUA6eE/lM6alMEITtQQaZIAjCCuBZYsGr5lesNZ0pOuVQjjp1NI/XrcteysBrIh9QNj2VCYKwHsggEwRBWAGOjnx1PPDx4avbtk0325yRwd5OjtdEPqDseipbEnI5EBen2NgYFyc+FZIgKhJkkAmCIKwAVvPComvQgC2WmK55c7Y4LLqBA4EDB/SfO3BAcV4MZS2zMVj7ICtjaZd8KJFIrLun8v79ig8uoaHAiBGKf318FMcJgiCDTBAEYRXwbPPGYjZZdCyt4lh0eXmGzbGSAwfEezwra5mNmVqWWmb1WMrnaccB2GNZGsruHNo11sruHGSSCYIMMkEQhFVQXMxPx2tQSFYWWxwx3b/+xRaHRRceDvTvr/9c//6mtWVT1kVrl2TUq2e9Ld7EunMAiu4cVG5BVHTIIBMEQVQweG1Aq12bLY6Y7tYttjgsujlzjJdqzJnD9lpKwsMVkwBPnAB27lT8m5JineYYoO4cBMEKGWSCIAgrwFDZQEl0YsM0WHW8JunxymgXFACrVhnXrFql0FVUqDuH+aBNkdYFGWSCIAgrwI7xv9Ysunzt8fEl1PHqg8zL/G/YIG465HKFjhVb28xWEbpzWCK2dh9VBMggEwRBWAE8+yA/fcoWS0zHy2jzMv9377LFYdXZ4mY2W+/OocSSsrX79wODB+veRxkZiuOm3keWdG22DBlkgiAIK4DnJj1exrZmTbY4YrqAALY4YrrGjdnisOhsdTObLXfnUGJJ2Vq5HPjgA+OaDz5gv48s6dpsHTLIZmTPnj3o3bs3AgICEBQUhBUrVqCwsNDcyyIIwsbhlbFNSmKLI6br0IEtjphu8mRxY2dvr9CJYcub2Sy5O0dps6OWlvWPixP/JubpU4VODEPXlpFhvd9oWDJkkM1EdHQ0Fi1ahKFDh+LgwYNYsmQJDhw4gOXLl5t7aQRB2Di8eiq/eMEWR0x38SJbHDGdkxMwa5ZxzaxZCp0Ytr6ZzRK7c5Q2O2qJWX8W48uiM3ZtgOK4NX6jYcmQQTYT33zzDfr06YMxY8bA19cXPXr0wPTp07F7925kZmaae3kEQdgwvAyyszNbHDHdgwdscVh0X3yh6JesnUm2t1cc/+ILttfiVT5iydjbAyEhwPDhin/NWVbBI/Nry1l/sWsDrPfaLBUyyGYgNTUV6enpCAkJ0TgeFBSE4uJixNMdThCEFjy7WPCqZ54yhS2OmC47my0Oq+6LL4DcXGD1amDqVMW/ubns5hjgO9qbMA6vzK8lZv1ZNzuK6dLS2OKw6ghxyCCbgZSUFABAfa3moN7e3nB0dERycrI5lkUQhAXDc5MeL3jVDvM0/0qcnBSmat06xb8sZRXqsOYpKJ9Renhlfi2xhR1rVl5Mx2usO8EOGWQzIHvd7d7NzU3juEQigZubm+o8QRBEWcDLkPJqF+fuzhaHVUdYF7wyv5bYwu7xYz66nBy2OKw6QhwyyARBEGUIa+ZSTMczy9quHVssMR2vjB2vr6F5olUBV2odYRhe95EltrDjdW1SKVscVh0hDhlkM+Dp6QkAOpliQRCQk5OjOl+WVIQNKIRheJm2Nm3Y4ojpRoxgi8OiW7OGLZaY7sABtjhiujt32OKI6W7dYovDojt2jC2WmI5Xxm7aNHFjb2en0JUXISFAtWrGNdWqkUHmAc/Mr6W1sON1bStXsr0eq44QhwyyGfD19QUApGlV02dkZKCwsBBNmjQp8zWwNsoQ0/Gc7sUrlq3G4RmLVxeDK1fY4ojpfviBLQ6Lbvp0tlhiuv792eKI6Ro0ABwcjGscHBQ6YzRpIj5qWSJR6MSoXFl8WEbjxgqdMXhl7JycgMhI45rISNPriEuDvT2wcaNxzcaN1j1Qw1Lgnfm1pBZ2vK7NxQUYMMC4ZsAAhY7gAxlkM1C/fn34+vrixIkTGsePHz8OBwcHBJXT94iWZhB5xrLVODxj2WocnrF4xSksNGySHRwU51koLjaeiTJlg96ffxo2yY0bK86zwCtjx6s9G0/Cw4F9+xTXok69eorj5uwZbGvwzvxaUgs7XtcWHW3YJA8YQBv0eCMRBFP+7BC8OHLkCGbMmIHIyEh069YNt27dwpIlSzBkyBDMnTtXQ9u9e3cACgNdFtSqpblBoGZN9gyzOvr+cJf07uIVy1bj8IxVqRJQUPD3Yycn9gyzOoGBwNWrfz9u04Y9w6zOyJGKrI+SESPYM8zarF2r6GCgZM0a9gyzOgcPav5hOnCAPcOszr17gL+/ouWYqytw/bp45lgff/4JtGihMNaOjopJdSX94unFC6BPH8XaGjQADh8WzxzrQy5XdBl4+FBRTxkUVDJTUlAAbNgA3L2rMOqTJ5dv5lgfvK6NEMeW32te15aXp/jQeOcO0LSpoqyiLDLHZe09LB0yyGbk4MGDiIqKQlpaGqpXr44hQ4Zg8uTJsNMqxqvoNylBEARBEOVLRfceIpVxRFnSv39/9C9JGoogCIIgCIIoM6gGmSAIgiAIgiDUIINMEARBEARBEGqQQSYIgiAIgiAINcggEwRBEARBEIQaZJAJgiAIgiAIQg0yyARBEARBEAShBhlkgiAIgiAIglCDDDJBEARBEARBqEEGmSAIgiAIgiDUoEl6VsDjx48hl8tVYx8JgiAIgiDKkocPH8Le3t7cyzAblEG2AipVqgQHB/osQxAEQRBE+eDg4IBKlSqZexlmQyIIgmDuRRAEQRAEQRCEpUAZZIIgCIIgCIJQgwwyQRAEQRAEQahBBpkgCIIgCIIg1CCDbMXs2bMHvXv3RkBAAIKCgrBixQoUFhaae1k2x+TJk+Hn56fz07NnT3MvzSbYsmULAgICMHPmTJ1ziYmJGDlyJFq3bo033ngDM2bMQGZmphlWaTsYer+3bNmi9z738/PDo0ePzLRa6yY6Ohrh4eEIDAxEaGgoFi1ahKysLNX5O3fuYPz48QgMDERgYCAmTJiAu3fvmnHF1oux9zo2NtbgvZ2YmGjmlROWCrVGsFKio6OxaNEizJs3D127dkVycjIWL16M3NxcLF261NzLsylkMhl69uyJJUuWaByvyO1vePD8+XPMmzcP169f17tTOjk5GWPHjkXfvn2xaNEi5OTk4IsvvsD48eOxf/9+ODo6mmHV1ovY+y2TyVC9enVER0frnKtWrVp5LNGm2LJlC1asWIEFCxYgODgYqampWLx4MVJSUrB9+3Y8f/4co0ePRqtWrbB161bY2dlh/fr1iIiIQExMDDw9Pc19CVaD2Hstk8kAAHFxcTodoby8vMyxZMIKIINspXzzzTfo06cPxowZAwDw9fXF06dP8dFHH2Hy5MmoVauWeRdoQ8hkMjRs2BA1atQw91JsikOHDiE3NxfR0dF49913dc5v2rQJVatWxbJly1R/1D7//HO88847OHr0KPr27VveS7ZqxN7vnJwcuLu7033OAUEQ8N1332HAgAEYNWoUAKBBgwaYMmUKFi5ciPT0dBw8eBB5eXlYuXKlygyvWLECXbt2xY8//oiJEyea8xKsBpb3WiaTwdHREd7e3mZeLWFNUImFFZKamor09HSEhIRoHA8KCkJxcTHi4+PNszAbRSaTwdXV1dzLsDmCg4Pxn//8x2B28vTp0wgKCtLI+DRq1Aj16tXDqVOnymuZNoPY+52dnU33OSckEgkOHTqEBQsWaByvWbMmAODJkyc4ffo02rZtq5Ep9vT0RKtWrej+NgGW95rubaIkkEG2QlJSUgAA9evX1zju7e0NR0dHJCcnm2NZNgsZ5LKhfv36BstUcnJy8PjxY517HAAaNmxI93gJMPZ+A3Sf88bLy0unTCI2Nhaurq5o2rQpUlJSUK9ePZ3n0f1tOmLvNd3bREmgEgsrRFlP5ebmpnFcIpHAzc1NdZ7gQ3Z2Nm7duoWxY8fi9u3b8PDwwJtvvolp06ahevXq5l6eTWLoHgcAd3d33L9/v7yXZPNkZ2cjOzsbkZGRuHr1KoqLi9G8eXNMmzYNzZs3N/fyrJ7Y2Fjs2bMHM2bMgIeHB3Jycgze39nZ2WZYoe2g/V5nZ2dDLpdj8eLFuHDhAnJzcyGVSjFhwgR07NjR3MslLBTKIBOEEYqKilC5cmVkZWVh5MiR+P777zF16lTEx8dj5MiRyMvLM/cSKxw0/LNscHR0RH5+Pjp06ID/+7//wyeffILs7GwMGzYMt2/fNvfyrJqYmBjMmDED/fr1E60tpvu7dOh7r+3t7WFvbw8fHx+sXbsWq1atgpubG8aMGYMzZ86YecWEpUIZZCtE+VWSdqZYEATk5OTQ7meOODg44PTp0xrHpFIpateujREjRuDgwYMYNmyYmVZnu3h4eADQvceVxypXrlzeS7J5vv32W43HUqkUrVu3RmhoKKKiovDVV1+ZaWXWzQ8//IDly5dj5MiRWLBgASQSCQCossja0P1dcgy910uWLNHpQtS2bVv06dMH69atw1tvvWWO5RIWDmWQrRBfX18AQFpamsbxjIwMFBYWokmTJuZYVoWiWbNmAEA9ecsIV1dXeHt769zjgGKTauPGjc2wqoqHm5sb6tWrR/d5CdmzZw8+/vhjzJo1CwsXLoSd3d9/cn19fen+5oix91of9vb2kEqldG8TBiGDbIXUr18fvr6+OHHihMbx48ePw8HBAUFBQWZame2RnJyMuXPn6nzF/McffwAAfHx8zLCqikFwcDDi4+M1ht8kJSXhwYMH6NatmxlXZnsUFhZi8eLFiImJ0TienZ2N1NRUus9LwMWLF7FkyRLMmzcPEyZM0DkfHByMK1eu4NmzZ6pjT548wdWrV+n+NhGx93rlypXYsWOHxrGioiIkJSXRvU0YhEosrJTp06djxowZ2LRpE7p164Zbt25h/fr1GD16NDX154i3tzcSExNx/fp1zJs3Dw0bNsSff/6JTz75BD4+PggLCzP3Eq2W58+fq8yvXC7Hq1ev8NdffwFQfP08fvx4/Pzzz1iwYAHGjRuHly9f4pNPPkHr1q3RvXt3cy7dKhF7v1++fIlFixahoKAA7dq1w9OnT7F27VrI5XKMHj3anEu3OgRBwLJly9CmTRv06dNH9T4rcXV1xfDhw7Fjxw7Mnj0b06dPhyAIWL16NWrWrImhQ4eaaeXWB8t7DSh6qMvlcgQHByM3NxebN2/G/fv3abAWYRCJQDsCrJaDBw8iKioKaWlpqF69OoYMGYLJkyeLfrVEmMbDhw/x9ddf4+zZs3j27Blq166NoKAgTJs2jaYwlYJRo0bh4sWLes999tlnCA8Pxx9//IEVK1bg999/h7OzM0JDQzFv3jxUqVKlnFdr/Yi933369EFUVBQOHz6Mhw8fwsvLCy1btsTMmTOpbMtE7t+/bzQLPHXqVEybNg1paWn49NNPcfHiRUgkEnTq1Anz58/X2/6N0A/Lez1lyhRs27YNe/fuRUZGBtzc3ODn54dp06YhMDCwHFdLWBNkkAmCIAiCIAhCDUo1EgRBEARBEIQaZJAJgiAIgiAIQg0yyARBEARBEAShBhlkgiAIgiAIglCDDDJBEARBEARBqEEGmSAIgiAIgiDUIINMEARBEARBEGqQQSYIwiDHjx9HWFgY/P398cYbb5h7OUQpmDdvHvz8/LB//35zL4UgCMLioVHTBGElfPXVV0hLS8PXX3+tOnbw4EFs2LABR44c4f56L168QGRkJPLy8jBkyBDUrVtX9Dl+fn56j9vZ2cHT0xP+/v4YPHgw+vTpw3u5hAi9e/dG06ZN0bJlS3MvBQCwf/9+zJ8/H2FhYRr3NEEQhCVABpkgrISEhAT06tVL41hiYmKZZXZTUlKQl5cHqVSKTz75xKTnzpw5E46OjqrHeXl5uHfvHn755RecOXMGJ0+exIoVKyCRSHgvmzBA165d0bVrV3MvgyAIwiogg0wQVkB+fj6uXbuGxYsXaxxPSEjAxIkTy+Q1X716BQDw8vIy+bmjRo2Cm5ubzvHIyEgMHjwYBw4cQPfu3REWFlbqdRIEQRAEb6gGmSCsgKtXr8LZ2RnNmjVTHcvKykJycjLat2/PHOfmzZuYNWsWgoKCEBAQgPbt22PUqFGIjo7W0HXr1g2jR48GAFy8eBF+fn4GyydMoVatWhg3bhwA4H//+5/q+Lp16+Dn54cdO3Zg9+7dCA4ORufOnTWee/HiRfzzn/9Ep06d4O/vjw4dOmDcuHE4efKk3teKiYnB4MGD0bp1a3To0AEzZsxARkYGNmzYAD8/P6xbt86k1z916hQmTJigev127dphxIgR+Pnnn3VeW1nvGxsbi5MnT2LIkCFo06YNOnXqhPnz50Mmk0Eul2P9+vXo2bMnWrdujd69eyMqKgqCIKjiZGRkwM/PDwMGDIBMJsPixYvRpUsXtG7dGgMGDMDx48cBAElJSRg/fjzat2+Pjh07Yvz48bh7967eNanXICuPnThxAomJiYiIiED79u3RsmVLDB48GLGxsTrXlpOTg88//xwhISFo2bIlevbsiW+//RZyuRw9e/aEn58fMjIy9P5OSotcLscPP/yAYcOGoV27dmjRogU6deqEyZMn47ffftPRd+vWDX5+fsjJycHevXsxYMAAtGnTBu3atcMHH3yAO3fu6DwnPT0dM2bMQIcOHdC6dWuEh4fj6NGjePToEfz8/NCtWzeVVvn7UT+mzqhRo1TvrzovXrzAl19+id69e6N169YICAhAt27dsHjxYmRmZurEKSwsxIYNG/D222+jZcuWCA4OxooVK5Cfn48xY8bAz88PFy5c0HhOQUEBNm7ciIEDB6JNmzZo06YN+vXrh2+//Rb5+fk6r/H7779j6tSp6NKli+r/X0OGDMHWrVshl8v1/0IIwoahDDJBWCjR0dFYsGABAEAQBBQXFyMgIEBH17NnTwDAli1b8OabbxqMd+rUKUyZMgWCIKBnz55o3Lgxnj59il9//RVz587FtWvXsHDhQgDApEmTcP36dezatQv169fH8OHDuV1Xo0aNAACPHj3SOXfz5k0cO3YM7777LipXrqw6vmfPHixatAguLi4ICwtDvXr1kJmZiV9++QUffPAB5s2bh/fff1+l37dvHxYsWAAnJycMGjQI3t7eOHv2LN577z3V+6UPQ68fExODWbNmwc3NDX369IG3tzcePHiAgwcPYvbs2Xj8+LHK+Ktz8eJFREdHo1evXnjrrbdw5MgR7N+/H4IgwNHREQkJCXjnnXeQn5+PvXv3YtWqVahVqxYGDhyoE2vatGnIy8vDu+++i4yMDPz888/48MMPsWHDBkRGRiI4OBijR4/GhQsXEB8fj3v37uHIkSOwsxPPg1y5cgXbt29Ht27dEBERgVu3buGXX37BtGnTsHv3blXdsiAImDRpEi5evIiGDRti7NixKC4uxg8//IB79+6VuZH6+OOP8eOPP6JevXoYOnQo3N3dkZSUhNjYWJw6dQrbtm1D27ZtdZ73/fffY+fOnQgLC0P37t0RHx+PkydPIikpCceOHYOLiwsA4PHjxxg+fDj++usvtG/fHp07d8ajR48wZ84cTJgwgcs15OXlYezYsbh27RoCAwMRFhYGQRBw+vRp/Pe//8WpU6cQHR2t8c3NwoULER0djRo1amDUqFFwdnbG4cOHcePGDRQVFem8xqtXrzBmzBhcvnwZUqkUo0ePRlFREc6cOYPVq1cjLi4OW7ZsgbOzMwDg0qVLiIiIgLOzM3r16oW6desiJycHJ06cwKefforffvsNq1at4nL9BGE1CARBWCQvXrwQbt26Jdy6dUt47733hEWLFqke37p1S5g7d64wduxY1eOcnByDsV69eiW89dZbglQqFU6dOqVxLisrSwgKChKkUqlw+fJl1fHz588LUqlU+Mc//sG8ZqlUKkilUkEmkxnU7N69W5BKpcLEiRNVx77++mtBKpUKLVu2FM6ePauhf/z4sdCqVSshICBAuHnzpsa5tLQ0oU2bNoK/v79w//59QRAEoaCgQOjYsaMglUqF2NhYDf3SpUsFf39/QSqVCl9//TXT6wuCIISGhgpSqVTn3MmTJwWpVCq0bdtWKCgoUB2fO3euIJVKhYCAACEpKUnjWlq0aCG0aNFC6N+/v8bvLCYmRud9SU9PF6RSqdC8eXNh+vTpglwuV51btmyZIJVKBX9/fyE6Olp1vLi4WOjbt68glUqFP/74Q2dN+/bt0znm7+8vnDt3TuPaFixYIEilUmH58uWqY8eOHROkUqkQGhoqZGdnq44/ffpUCA0NFVq0aCFIpVIhPT1d5z3UZt++fYJUKhWmTZsmqhUEQbh3754glUqFN954Q8jKytI4t3LlSkEqlQrjx4/XOK78vYWEhAiPHj1SHZfL5cLbb78tSKVS4dixY6rjy5cvF6RSqTB16lSNOJcvXxZatWqlunYlyt+P+jF1/vGPfwhSqVT49ddfVcf27t2r+v+V+u+zuLhYGDZsmCCVSoWNGzeqjiclJanusYcPH6qO5+bmCoMHD1bdz+fPn1edW716tSCVSoW5c+dqvEZRUZEwbdo0QSqVChs2bFAdnzVrliCVSoW4uDiN9RcUFAgjRowQ2rVrJzx48EDvNRKErUIlFgRhoXh6ekIqlUIqlSI5ORndunVTPZZKpUhPT0fnzp1Vj11dXQ3GOnXqlCorFhQUpHGuSpUqeO+99wAAhw8fLtNrEgRBVc6hvQ4AqF+/Pjp16qRxLCYmBvn5+ejdu7dOmUeDBg3Qu3dvFBYW4ujRowCA3377DVlZWfDx8UH37t019LNnz4aTk5PB9el7fblcji+//BLr169Hx44dNc517doVzs7OkMlkePDggU680NBQNG/eXPW4Ro0akEqlKCoqwvvvv6/xO1O+H2lpaTpx5HI5Jk+erJENVpaAeHt7o3///qrjEolEde7evXsGr1WdoKAgnWsLDQ0FAKSmpqqO/frrrwCAYcOGwd3dXXW8atWq+PDDD/VmM3nh5eWFbdu2Yf369ahSpYrGOeW3Ardu3dL73IiICNSqVUv12M7OTrVhMSUlRXVcWQoxduxYjecHBgaid+/epb8IKH5vmzdvxqJFizR+nxKJRFWqoX4dyve8T58+qF27tuq4i4sL5s6di8LCQo34giDgv//9L+zt7TFnzhyN17C3t0dkZCQA4KefflIdf/Hiheq8Oo6Ojti6dSsSExPh7e1dqusmCGuDSiwIwsK5e/cuXrx4ofHVcWFhIa5du4bZs2czxbh27RoA6P36GQBatWoFALh+/XopV6vg4cOHqq9vAcVXvvfu3cO2bduQmJiIZs2aYciQITrPUzeTSljWvnfvXtXa//zzTwDQW47i6uqKN998U6cm1Njr29vba7x2Xl4enj9/rionqFy5MvLz81WbGtWRSqU6x5SbF5s2bar3uL44Dg4OaNy4sV5948aNdbqBGIuljxYtWugcUxpg9XpVZV2zvvc2ODiY6bVKioeHBzp06KB6/PLlS2RnZ0MQBJVJNHS9+n6vHh4eGs/Jz89HRkYGJBIJ/P39dfQhISFcekh7e3urzGZxcTGeP3+O3NxcAH8b1IKCApXe2Hv+xhtvwN3dHTKZTHUsPT0dWVlZqFWrFnJzc1Wxldjb26Ny5cpIS0vDy5cv4enpieDgYMTHxyMyMhJjxoxBjx49VPengwPZBKJiQnc+QVgojx49QlFREU6dOoUGDRrg5cuXePnyJQDgzp07KCoqgpeXFzIyMlCpUjIwIUAAAAuRSURBVCXUqFHDYKysrCwAikyfPpTHnz17xmXthvocOzg4YNCgQZg/fz4qVaqkc147MwiYvvbnz58bjAUAderUMbhuQ8959OgR1qxZgxMnTqjis6CvA4jSzKrXOKsf14e7u7tOdk+pN/YagtqGP2Pou2596zH23lapUgWurq46hownly9fxvr165GQkMBs/pVr00b7PXrx4gUEQYC7u7vebxmM3Tem8tNPP2Hbtm24efMmiouLjWqNvecSiQTe3t4amw2fPn0KAMjMzNT5BkWbv/76C56enhg1ahSys7OxadMmrFmzBmvWrEH16tXRuXNnDBkyROODCUFUFMggE4SFMmLECNy/f1/1WN8fu3feeQcA8Oabb2L79u2iMQ0ZJuUfaV59iVetWqVhgCUSCSpXroxmzZppfDWvjbFsFevalTpD12LsGvW9flZWFoYOHYrMzEz4+/tj/PjxqFOnjur6Fi1apDLxto7Ye1uWJCQkYMyYMSgqKkKPHj3QuXNnVKtWDQ4ODnj69KlOC8SSUpL7xhSioqKwatUqODs7491330WrVq3g6ekJOzs7nD9/Xuf/x6bez8rH3t7eqk23hlAvO5k8eTJGjBiBkydP4uzZszhz5gwOHjyIgwcP4t1338Xy5ctNvlaCsGbIIBOEhbJs2TLk5+fj888/R5cuXdClSxfVua1bt6JSpUqq2mGxXsXVqlUD8Hd2SRulwVPqSktISIjePsglwdS1K786V2bbtdFXK2yMffv2ITMzEx06dMDmzZs1BqAAwPz5802KZ80oP9woa1bVUS8VKAs2btyIoqIiTJo0CTNnztQ4d+PGjVLHV15bbm4uioqKdD4sPXz4UOc5Yqb5yZMnGo+LioqwceNGAMD//d//6bQS1NceT3k/63vPBUHQWVf16tUBKEqBevToYXR92nh5eWHAgAEYMGAABEHAqVOn8O9//xt79uxBnz59dOrzCcKWoU16BGGhdOnSBd26dcOTJ0/Qt29f9OjRQ/WTk5OD0NBQ1WOxaXrKNl2XLl3Se/7KlSsaOkvC1LX7+PgA0L9hKy8vDxcvXjTp9dPT0wEoTL+2OU5MTDRoxG0RZYs+fe+toX7UvFD+HvS16TNUU24Kbm5uqFGjBuRyuaqOXZ24uDidY8pvEfTdAy9fvtQxvM+ePYNMJoOrq6uOOQb0v4fG7udLly4hOztb41i9evVQvXp1PH/+HElJSTrPAXQ3gr548ULj2ypAYf6VrQMBfvsTCMJaIINMEBZMcnIyXr16pbHJqKCgALdv3zbJzAYFBaF27dq4fPkyTp06pXEuMzMTu3btgp2dHQYNGsRt7bzo06cPXF1dceTIEdy8eVPj3O3bt3HkyBG4urqqugy0bdsWrq6uuHHjBhITEzX0X331lc6ufzGUnQO0h0qkp6dj6dKlqtrQimCU33rrLQCKvtTqG8mePXuGDRs26HyA4Imh38PZs2dVnVFycnJK1UlD+S2NdpnD77//jiNHjujoq1atCjc3N2RnZ6s+qClZu3atTn1x1apV4eTkhNzcXA3zLAgCoqKiVMZcPVusfM8PHTqkUf+en5+PlStX6q3lV26AXbFihU5W//Dhw3j77bcxd+5cAEB2djaCg4Px/vvv681SJycnAwB1sSAqHFRiQRAWzLVr1+Dj46NRrnD79m0A0JiqJ4ajoyM+//xzTJw4EVOmTEFYWBgaNWqEzMxMxMbGIisrC7NmzdLbdcHcVK1aFR999BHmzZuHkSNHolevXvD29kZGRgaOHj2KoqIifPzxx6rNeq6urpgwYQLWrl2LiRMnonfv3qhevTouXLiArKwsDBw4EP/973+ZX79v37749ttv8dNPP6GgoABNmzZFRkYGYmJiMHXqVNy4cQMHDx7EypUr0bt3b0RERJTVW2F2+vbti82bN+POnTsYMmQIunbtivz8fBw9ehTh4eHYtWuXSZsYAUWbtc2bNxs837FjR/j7+2Pw4ME4d+4cli1bhuvXr6Nq1apISkrCmTNnsGnTJkRGRuLRo0eYO3cuevXqZXJ5AQBMmDABR48exd69e5GZmYlWrVrh/v37OHbsGCZPnoyVK1dq6JUfKnfs2IFJkyZh0KBBcHFxwcWLF/Hy5Uv07NlTY2Kkvb09Bg4ciN27d2P06NHo378/JBIJTp8+jWfPnmHdunUYNmwYLl26hC+//BLvvPMOOnTogM6dO+Ps2bMYMmQIunfvDjs7Oxw/fhwtW7ZEYWGhTnb3n//8J86dO4fz588jPDwcYWFhcHBwwLVr13Dy5EnUqFEDkyZNAqAo4Zg0aRJWr16NPn36oEePHqhduzYKCgpw6dIlnD9/Hv7+/kYH7BCELUIGmSAsmKSkJJ0WXNevX0fTpk2N9vPVR6dOnbB7925s3LgR58+fx//+9z+4u7sjICAAo0ePLvM2XaVhwIABqFu3Lr777jvExsYiOzsblStXRufOnTFu3DgEBgZq6P/5z3/C1dUVu3btwk8//YRq1aohJCQE06dPx6ZNmwCwb7pq0KABvv/+e6xZswanTp3CyZMnIZVK8fnnn+Ptt9/G3bt3cevWLSQlJcHBwcGmDbKTkxO2bNmClStX4tSpU9i+fTsaNmyIadOmYejQodi1axcA0za03b59G1988YXB8/Pnz4e/vz/69euH/Px8bNu2DXv37oWbmxsCAwOxc+dONG/eHP/+97+xfPlyHD9+HHXq1CmRQW7cuDG2bt2KVatW4dKlS7h69SpatGiBb7/9Fl5eXjoGGQDmzp0LLy8vHDp0CDt37lS1TZs9ezZWrFiho1+wYAE8PT1x9OhRbN68GTVq1EBISAimTp2KqlWrYuLEidi5cyf27NmDNm3aICAgAOvWrcPq1atx9OhR7Ny5E3Xr1sWQIUMwbtw4vPvuuwA033NnZ2ds27YN27ZtQ0xMDLZu3YqioiLUqlULw4cPx8SJEzV6Kk+aNAmNGzfG7t27ERsbi+fPn8PT0xN16tTBhx9+iIiICJP/e0MQ1o5EYO0DRBAEYQMsWbIEu3btwpw5c/SOhyZKTuvWrZGfn49z584ZbMtnrfz2228YOnQomjZtikOHDpl7OSp69eqF5ORk7N271yL3EBCEtUI1yARB2By3b99GTEyMRp2s+jlAMTWPMI3c3FwkJibi3LlzOufS0tKQn58Pd3d3g/2kLZ2nT58iPj5edY+oozxWr169cl1TQUEBfvvtN72bBPPy8lSbF8t7XQRh65BBJgjC5liyZAlmzpyJffv2aRxPSEjAlStX4OLiojNamRDn8ePHGDlyJGbMmIHMzEzVcUEQVKUrISEhZumTzINff/0V48ePx0cffaSx2S8nJwc7duwAANU46PKioKAAERERmDJlik4ni//85z8oLCxEYGCg1X4oIQhLhUosCIKwOS5fvoz3338fhYWFCAsLQ5MmTXDv3j0cPnwYhYWFWLRoEf7xj3+Ye5lWySeffIJt27ahevXq6NevH1xcXHDu3DlcuXIFVapUwd69e602m5mfn4+IiAhcvXoVzZo1Q2hoKF69eoVffvkFGRkZCAwMxPbt28u0W4c+tmzZgs8++wweHh7o168fqlWrhitXruD06dNwcXHBtm3bVOPiCYLgAxlkgiBskps3b2Ljxo24evUqHj9+DFdXV9WGxJCQEHMvz2oRBAE//fQTdu/ejdTUVMhkMtSsWRNdunTBpEmTuI5kNgcymQxbtmzB0aNHkZGRgeLiYjRo0ABhYWEYN24cXFxczLKu2NhYbN++HXfv3sXz589RpUoVvPnmm5g0aRKaNm1qljURhC1DBpkgCIIgCIIg1KAaZIIgCIIgCIJQgwwyQRAEQRAEQahBBpkgCIIgCIIg1CCDTBAEQRAEQRBqkEEmCIIgCIIgCDXIIBMEQRAEQRCEGmSQCYIgCIIgCEINMsgEQRAEQRAEoQYZZIIgCIIgCIJQ4/8Bn/JqK1jW/kUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 700x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "a3, b3 = np.polyfit(num_lang, annual_salary, 1)\n",
    "num_lang_range = np.arange(1, 29, 1)\n",
    "pred_lang_range  = a3*num_lang_range + b3\n",
    "\n",
    "plt.scatter(num_lang, annual_salary, color='blue')\n",
    "plt.plot(num_lang_range, pred_lang_range, color='red')\n",
    "\n",
    "plt.title(\"Annual Salary Impacted By Number of Programming Languages Learned\")\n",
    "plt.xlabel(\"# of Programming Languages\", fontsize=16)  \n",
    "plt.ylabel(\"Annual Salary\", fontsize=16)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Annual Salary Impacted By Number of Programming Languages Learned Analysis\n",
    "Just like the previous graph, both these variable are directly related as one increase the other also increases. In this case as a developer who has knows more langauges will lead to a higher annual salary. In this case, the average developer knows around 5-10 programing langeages, then fewer developes knows more than 25"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Looking at the Correlation Between all Columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 500x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.matshow(df.corr())\n",
    "plt.xticks(np.arange(6), df.columns, rotation=90)\n",
    "plt.yticks(np.arange(6), df.columns, rotation=0)\n",
    "plt.colorbar()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Analysis of Heat Map\n",
    "Looking at the heat map we can see that there is not much correlation between the data set, that is why we can predict that our hypothesis is going to fail. We can see the the variables that does have correlation are: Years coded professionally and number of years coded, Years coded and annually salary, Years coded professionally and annual salary. While the other data sets are might not have any correlation."
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "## Ethics & Privacy\n",
    "\n",
    "### Ethical Consideration\n",
    "There were several things to consider while making up our question and study: the question, the implications, the data, informed consent, privacy, evaluation, analysis, transparency & appeal, and continuous monitoring. Privacy is mentioned below in the next section and continuous monitoring is not applicable in this setting since it is this one time final project with this specific dataset.\n",
    "\n",
    "With our question, we are asking whether age matters when learning how to code and whether learning earlier positively affects the person, and some ethical implications that we thought this question can pose is that people may force children or those under 18 to learn coding or those who are older may be discouraged from learning. This can also affect companies on who they decide to hire. Maybe through a bias from this study, those who are older are discriminated against during their hiring process. For example: if there was a 24 year-old and a 54 year-old who had the same amount of years in experience, and the 24 year-old was chosen based on this bias.\n",
    "\n",
    "With our data, we have answers from those who are different genders, race and ethnicities, ages, sexual orientations, disability statuses, and are from different locations. To remove any biases or ethical issues, we dropped columns that deal with all these identifiers except for age, since it is the main topic of our study. Because there could possibly be children in the study, it may be unethical to use their data without informed consent, although they have volunteered to answer this survey in which we had received the data. The minimum age to engage in the Stack Overflow network is 13 years old. \n",
    "\n",
    "Because this survey data was taken from volunteers and open to the public, we can say that the information is openly available for use and knowledge. However, there is no explicit informed consent to this particular study, which would be difficult since it is from a dataset with no personal identifiers. With our evaluation and analysis, we have made sure to discard any personal biases while analyzing our results, and only used what was shown through our data cleaning and visualizations. With transparency and appeal, it is quite clear how we came up with our model, and it can be appealed if more evidence from specific surveys were given. For biases, we need to consider those who are not a member of Stack Overflow. Does Stack Overflow attract more of a specific race or gender, etc.? Maybe the dataset we have has a bias due to the website culture and community.\n",
    "\n",
    "### Privacy Consideration\n",
    "The survey data that we used is from a public website (Stack Overflow) and the results were uploaded for anyone to see. The information that is provided does not have any identifying information, such as name and address, and it is a voluntary survey done by the users, so we do not violate any privacy issues.\n",
    "\n",
    "We do have each user’s location such as country and state (if they are in the U.S.) from the original dataset, however because it is unnecessary for our research, we decided to exclude it. For demographics, we also have information on race and ethnicity, gender, sexual orientation, disability status, and age. In this case, we only used age in order to factor in finding out when they had started coding and how long they have been coding. There could be possible privacy issues if the users who answered the survey about their age can be identified, but since the topic and hypothesis itself are not related to any specific individuals, we do not have any possible way of identifying individuals. Therefore, we don't have any particular concerns regarding privacy.\n",
    "\n",
    "## Conclusion & Discussion \n",
    "There were many factors that made up much of what answered our question of developers learning coding at an earlier age are given an edge over developers learning coding at a later age. The factors that we picked out from the dataset that we cleaned, visualized and analyzed showed that essentially, when developers do have an edge when they code earlier in their lives. However, we noticed that there is a certain age limit that it reaches where a developer would still be making a higher annual salary up to around the age of 30. Starting this project, we expected to see a correlation between the age one first began programming and their overall success as a programmer. However, it was interesting seeing how multiple other factors were able to play a greater role in determining success. In conclusion, we will have to reject our hypothesis becuase learning code at a early age does not greatly impact someones success in the future. There are so many other factors that can effect someones success and achievements.\n",
    "\n",
    "\n",
    "### References \n",
    "1. https://quod.lib.umich.edu/e/eebo/A00884.0001.001?view=toc\n",
    "2. https://edlab.tc.columbia.edu/blog/10822-Do-Kids-Learn-Faster-than-Adults\n",
    "3. https://www.seeker.com/why-do-kids-learn-faster-than-adults-1792717450.html\n",
    "4. https://www.discovermagazine.com/planet-earth/do-synapses-really-store-memories\n",
    "\n",
    "5. https://www.bls.gov/ooh/computer-and-information-technology/software-developers.htm\n",
    "6. https://www.techrepublic.com/article/12-tech-companies-with-impressive-benefits/\n",
    "7. https://hired.com/page/brand-health-report\n",
    "8. https://sites.tufts.edu/devtech/files/2019/09/Strawhacker_et_al-2019-Educational_Technology_Research_and_Development-2.pdf\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Team Contributions\n",
    "\n",
    "|Name|Contributions|\n",
    "|----|-------------|\n",
    "|Makoto Ikeda| Data Visualization|\n",
    "|Errick Santos|Research Question and Data Analysis|\n",
    "|Trish Lam | Background Context, Ethical and Privacy|\n",
    "|Subin Yoon| Data Cleaning |\n",
    "|Nathaniel Swadai| Data Analysis |\n",
    "\n",
    "## Project Timeline\n",
    "| Date | Time | Completed Before Meeting | Discuss at Meeting |\n",
    "|------|------|--------------------------|--------------------|\n",
    "|1/25/2020 | 11:59 P.M.| Established Group (5 members) | Exchanged contant information | \n",
    "|1/30/2020 | 6:00 P.M. | Created group chat consisted of team members | Agree on what data sets we are going to use |\n",
    "|1/31/2020 | 6:00 P.M. | Finish project Proposal Draft and push into Github | Proofread proposal and strengthen our reasearch question |\n",
    "|2/2/2020 | 11:59 P.M. | Not Applicable | Vote on which research question we are going to pursue |\n",
    "|3/13/20220|2:00 P.M.|Creating New Research Question| Created new research question|\n",
    "|3/15/2020|7:00 P.M. | Think of what part everyone is going to complete| Discussion of research question and assigned parts|\n",
    "|3/18/2020| 11:59 P.M. | Not Applicable | Everyone was Finishing up their assigned parts of project and was able to start putting pieces together|\n",
    "|3/19/2020|10:00 A.M.| Record Ourselves for Extra Credit | Submit Extra Credit|\n",
    "|3/19/2020| 12:46 P.M. | Revisions of Project| Looking over final project and correct small errors\n",
    "|3/19/2020 | Before 11:59 P.M. | Not Applicable | Turn in final project & group Project Surveys |\n",
    "\n",
    "## Team Expectations\n",
    "1. Spread the workload evenly among the 5 group members\n",
    "2. Speak up if there is someone doing completing the task he/she was given \n",
    "3. Get know each other, and hopefully stay in contact as the quarter ends\n",
    "4. Have everyone understand what we're doing in terms of applications from what we learned in class.\n",
    "5. Try our best to determine the best research question and the solution to it.\n"
   ]
  }
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