stack_overflow_survey_pt-br.ipynb

{
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  {
   "cell_type": "markdown",
   "id": "b171292f-d930-44d8-9289-c6aab65badfc",
   "metadata": {},
   "source": [
    "# Stack Overflow Surveys"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3af6c4c3-e02a-4f86-9ab4-6bed3b085698",
   "metadata": {},
   "source": [
    "## 2. Data understanding"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c457a231-2a39-4368-a4d1-994c78657f91",
   "metadata": {},
   "source": [
    "### 2.1. Load datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "197dd2aa-da82-49ae-b4b4-460d175f1079",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.ticker import StrMethodFormatter\n",
    "plt.style.use(\"./style/minimal.mplstyle\")\n",
    "%config InlineBackend.figure_format=\"retina\"\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "e00ca74c-daa7-40e1-9006-7d7de6618788",
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.set_option(\"display.max_colwidth\", None)\n",
    "pd.set_option(\"display.max_columns\", None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "75f0d085-0e80-4bf9-9fc7-781a5ca4e119",
   "metadata": {},
   "outputs": [],
   "source": [
    "root = \"data/zipped_folder/survey_results_public_\"\n",
    "\n",
    "df_11 = pd.read_csv(root + \"2011.csv\", encoding=\"latin-1\", header=1, dtype=str)\n",
    "df_12 = pd.read_csv(root + \"2012.csv\", encoding=\"latin-1\", header=1, dtype=str)\n",
    "df_13 = pd.read_csv(root + \"2013.csv\", encoding=\"latin-1\", header=1, dtype=str)\n",
    "df_14 = pd.read_csv(root + \"2014.csv\", encoding=\"latin-1\", header=1, dtype=str)\n",
    "df_15 = pd.read_csv(root + \"2015.csv\", encoding=\"latin-1\", header=1, dtype=str)\n",
    "df_16 = pd.read_csv(root + \"2016.csv\", encoding=\"latin-1\")\n",
    "df_17 = pd.read_csv(root + \"2017.csv\", encoding=\"latin-1\")\n",
    "df_18 = pd.read_csv(root + \"2018.csv\", encoding=\"latin-1\")\n",
    "df_19 = pd.read_csv(root + \"2019.csv\", encoding=\"latin-1\")\n",
    "df_20 = pd.read_csv(root + \"2020.csv\", encoding=\"latin-1\")\n",
    "df_21 = pd.read_csv(root + \"2021.csv\", encoding=\"latin-1\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "0bbebd41-f6c6-4e41-92be-586015d096d5",
   "metadata": {},
   "outputs": [
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       "      <th>Age</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Trans</th>\n",
       "      <th>Sexuality</th>\n",
       "      <th>Ethnicity</th>\n",
       "      <th>Accessibility</th>\n",
       "      <th>MentalHealth</th>\n",
       "      <th>SurveyLength</th>\n",
       "      <th>SurveyEase</th>\n",
       "      <th>ConvertedCompYearly</th>\n",
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       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>I am a developer by profession</td>\n",
       "      <td>Independent contractor, freelancer, or self-employed</td>\n",
       "      <td>Slovakia</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Secondary school (e.g. American high school, German Realschule or Gymnasium, etc.)</td>\n",
       "      <td>18 - 24 years</td>\n",
       "      <td>Coding Bootcamp;Other online resources (ex: videos, blogs, etc)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Developer, mobile</td>\n",
       "      <td>20 to 99 employees</td>\n",
       "      <td>EUR European Euro</td>\n",
       "      <td>4800.0</td>\n",
       "      <td>Monthly</td>\n",
       "      <td>C++;HTML/CSS;JavaScript;Objective-C;PHP;Swift</td>\n",
       "      <td>Swift</td>\n",
       "      <td>PostgreSQL;SQLite</td>\n",
       "      <td>SQLite</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Laravel;Symfony</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>PHPStorm;Xcode</td>\n",
       "      <td>Atom;Xcode</td>\n",
       "      <td>MacOS</td>\n",
       "      <td>Call a coworker or friend;Visit Stack Overflow;Go for a walk or other physical activity;Google it</td>\n",
       "      <td>Stack Overflow</td>\n",
       "      <td>Multiple times per day</td>\n",
       "      <td>Yes</td>\n",
       "      <td>A few times per month or weekly</td>\n",
       "      <td>Yes, definitely</td>\n",
       "      <td>No</td>\n",
       "      <td>25-34 years old</td>\n",
       "      <td>Man</td>\n",
       "      <td>No</td>\n",
       "      <td>Straight / Heterosexual</td>\n",
       "      <td>White or of European descent</td>\n",
       "      <td>None of the above</td>\n",
       "      <td>None of the above</td>\n",
       "      <td>Appropriate in length</td>\n",
       "      <td>Easy</td>\n",
       "      <td>62268.0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>I am a student who is learning to code</td>\n",
       "      <td>Student, full-time</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bachelorâs degree (B.A., B.S., B.Eng., etc.)</td>\n",
       "      <td>11 - 17 years</td>\n",
       "      <td>Other online resources (ex: videos, blogs, etc);School</td>\n",
       "      <td>7</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>JavaScript;Python</td>\n",
       "      <td>NaN</td>\n",
       "      <td>PostgreSQL</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Angular;Flask;Vue.js</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Cordova</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Docker;Git;Yarn</td>\n",
       "      <td>Git</td>\n",
       "      <td>Android Studio;IntelliJ;Notepad++;PyCharm</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Windows</td>\n",
       "      <td>Visit Stack Overflow;Google it</td>\n",
       "      <td>Stack Overflow</td>\n",
       "      <td>Daily or almost daily</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Daily or almost daily</td>\n",
       "      <td>Yes, definitely</td>\n",
       "      <td>No</td>\n",
       "      <td>18-24 years old</td>\n",
       "      <td>Man</td>\n",
       "      <td>No</td>\n",
       "      <td>Straight / Heterosexual</td>\n",
       "      <td>White or of European descent</td>\n",
       "      <td>None of the above</td>\n",
       "      <td>None of the above</td>\n",
       "      <td>Appropriate in length</td>\n",
       "      <td>Easy</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 code sometimes as part of my work</td>\n",
       "      <td>Student, full-time</td>\n",
       "      <td>Russian Federation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bachelorâs degree (B.A., B.S., B.Eng., etc.)</td>\n",
       "      <td>11 - 17 years</td>\n",
       "      <td>Other online resources (ex: videos, blogs, etc);Online Forum</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>Assembly;C;Python;R;Rust</td>\n",
       "      <td>Julia;Python;Rust</td>\n",
       "      <td>SQLite</td>\n",
       "      <td>SQLite</td>\n",
       "      <td>Heroku</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Flask</td>\n",
       "      <td>Flask</td>\n",
       "      <td>NumPy;Pandas;TensorFlow;Torch/PyTorch</td>\n",
       "      <td>Keras;NumPy;Pandas;TensorFlow;Torch/PyTorch</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IPython/Jupyter;PyCharm;RStudio;Sublime Text;Visual Studio Code</td>\n",
       "      <td>IPython/Jupyter;RStudio;Sublime Text;Visual Studio Code</td>\n",
       "      <td>MacOS</td>\n",
       "      <td>Visit Stack Overflow;Google it;Watch help / tutorial videos;Do other work and come back later</td>\n",
       "      <td>Stack Overflow;Stack Exchange</td>\n",
       "      <td>Multiple times per day</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Multiple times per day</td>\n",
       "      <td>Yes, definitely</td>\n",
       "      <td>Yes</td>\n",
       "      <td>18-24 years old</td>\n",
       "      <td>Man</td>\n",
       "      <td>No</td>\n",
       "      <td>Prefer not to say</td>\n",
       "      <td>Prefer not to say</td>\n",
       "      <td>None of the above</td>\n",
       "      <td>None of the above</td>\n",
       "      <td>Appropriate in length</td>\n",
       "      <td>Easy</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>Austria</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Masterâs degree (M.A., M.S., M.Eng., MBA, etc.)</td>\n",
       "      <td>11 - 17 years</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Developer, front-end</td>\n",
       "      <td>100 to 499 employees</td>\n",
       "      <td>EUR European Euro</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Monthly</td>\n",
       "      <td>JavaScript;TypeScript</td>\n",
       "      <td>JavaScript;TypeScript</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Angular;jQuery</td>\n",
       "      <td>Angular;jQuery</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>Windows</td>\n",
       "      <td>Call a coworker or friend;Visit Stack Overflow;Go for a walk or other physical activity;Google it</td>\n",
       "      <td>Stack Overflow</td>\n",
       "      <td>Daily or almost daily</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Daily or almost daily</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>No</td>\n",
       "      <td>35-44 years old</td>\n",
       "      <td>Man</td>\n",
       "      <td>No</td>\n",
       "      <td>Straight / Heterosexual</td>\n",
       "      <td>White or of European descent</td>\n",
       "      <td>I am deaf / hard of hearing</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Appropriate in length</td>\n",
       "      <td>Neither easy nor difficult</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>I am a developer by profession</td>\n",
       "      <td>Independent contractor, freelancer, or self-employed</td>\n",
       "      <td>United Kingdom of Great Britain and Northern Ireland</td>\n",
       "      <td>NaN</td>\n",
       "      <td>England</td>\n",
       "      <td>Masterâs degree (M.A., M.S., M.Eng., MBA, etc.)</td>\n",
       "      <td>5 - 10 years</td>\n",
       "      <td>Friend or family member</td>\n",
       "      <td>17</td>\n",
       "      <td>10</td>\n",
       "      <td>Developer, desktop or enterprise applications;Developer, full-stack;Engineer, data;Other (please specify):</td>\n",
       "      <td>Just me - I am a freelancer, sole proprietor, etc.</td>\n",
       "      <td>GBP\\tPound sterling</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bash/Shell;HTML/CSS;Python;SQL</td>\n",
       "      <td>Bash/Shell;HTML/CSS;Python;SQL</td>\n",
       "      <td>Elasticsearch;PostgreSQL;Redis</td>\n",
       "      <td>Cassandra;Elasticsearch;PostgreSQL;Redis</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Flask</td>\n",
       "      <td>Flask</td>\n",
       "      <td>Apache Spark;Hadoop;NumPy;Pandas</td>\n",
       "      <td>Hadoop;NumPy;Pandas</td>\n",
       "      <td>Docker;Git;Kubernetes;Yarn</td>\n",
       "      <td>Docker;Git;Kubernetes;Yarn</td>\n",
       "      <td>Atom;IPython/Jupyter;Notepad++;PyCharm;Vim</td>\n",
       "      <td>Atom;IPython/Jupyter;Notepad++;PyCharm;Vim;Visual Studio Code</td>\n",
       "      <td>Linux-based</td>\n",
       "      <td>Visit Stack Overflow;Go for a walk or other physical activity;Google it;Watch help / tutorial videos;Do other work and come back later</td>\n",
       "      <td>Stack Overflow;Stack Exchange</td>\n",
       "      <td>Daily or almost daily</td>\n",
       "      <td>Yes</td>\n",
       "      <td>A few times per week</td>\n",
       "      <td>Yes, somewhat</td>\n",
       "      <td>No</td>\n",
       "      <td>25-34 years old</td>\n",
       "      <td>Man</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>White or of European descent</td>\n",
       "      <td>None of the above</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Appropriate in length</td>\n",
       "      <td>Easy</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ResponseId  \\\n",
       "0           1   \n",
       "1           2   \n",
       "2           3   \n",
       "3           4   \n",
       "4           5   \n",
       "\n",
       "                                                                      MainBranch  \\\n",
       "0                                                 I am a developer by profession   \n",
       "1                                         I am a student who is learning to code   \n",
       "2  I am not primarily a developer, but I write code sometimes as part of my work   \n",
       "3                                                 I am a developer by profession   \n",
       "4                                                 I am a developer by profession   \n",
       "\n",
       "                                             Employment  \\\n",
       "0  Independent contractor, freelancer, or self-employed   \n",
       "1                                    Student, full-time   \n",
       "2                                    Student, full-time   \n",
       "3                                    Employed full-time   \n",
       "4  Independent contractor, freelancer, or self-employed   \n",
       "\n",
       "                                                Country US_State UK_Country  \\\n",
       "0                                              Slovakia      NaN        NaN   \n",
       "1                                           Netherlands      NaN        NaN   \n",
       "2                                    Russian Federation      NaN        NaN   \n",
       "3                                               Austria      NaN        NaN   \n",
       "4  United Kingdom of Great Britain and Northern Ireland      NaN    England   \n",
       "\n",
       "                                                                              EdLevel  \\\n",
       "0  Secondary school (e.g. American high school, German Realschule or Gymnasium, etc.)   \n",
       "1                                      Bachelorâs degree (B.A., B.S., B.Eng., etc.)   \n",
       "2                                      Bachelorâs degree (B.A., B.S., B.Eng., etc.)   \n",
       "3                                   Masterâs degree (M.A., M.S., M.Eng., MBA, etc.)   \n",
       "4                                   Masterâs degree (M.A., M.S., M.Eng., MBA, etc.)   \n",
       "\n",
       "      Age1stCode  \\\n",
       "0  18 - 24 years   \n",
       "1  11 - 17 years   \n",
       "2  11 - 17 years   \n",
       "3  11 - 17 years   \n",
       "4   5 - 10 years   \n",
       "\n",
       "                                                         LearnCode YearsCode  \\\n",
       "0  Coding Bootcamp;Other online resources (ex: videos, blogs, etc)       NaN   \n",
       "1           Other online resources (ex: videos, blogs, etc);School         7   \n",
       "2     Other online resources (ex: videos, blogs, etc);Online Forum       NaN   \n",
       "3                                                              NaN       NaN   \n",
       "4                                          Friend or family member        17   \n",
       "\n",
       "  YearsCodePro  \\\n",
       "0          NaN   \n",
       "1          NaN   \n",
       "2          NaN   \n",
       "3          NaN   \n",
       "4           10   \n",
       "\n",
       "                                                                                                      DevType  \\\n",
       "0                                                                                           Developer, mobile   \n",
       "1                                                                                                         NaN   \n",
       "2                                                                                                         NaN   \n",
       "3                                                                                        Developer, front-end   \n",
       "4  Developer, desktop or enterprise applications;Developer, full-stack;Engineer, data;Other (please specify):   \n",
       "\n",
       "                                              OrgSize             Currency  \\\n",
       "0                                  20 to 99 employees    EUR European Euro   \n",
       "1                                                 NaN                  NaN   \n",
       "2                                                 NaN                  NaN   \n",
       "3                                100 to 499 employees    EUR European Euro   \n",
       "4  Just me - I am a freelancer, sole proprietor, etc.  GBP\\tPound sterling   \n",
       "\n",
       "   CompTotal CompFreq                         LanguageHaveWorkedWith  \\\n",
       "0     4800.0  Monthly  C++;HTML/CSS;JavaScript;Objective-C;PHP;Swift   \n",
       "1        NaN      NaN                              JavaScript;Python   \n",
       "2        NaN      NaN                       Assembly;C;Python;R;Rust   \n",
       "3        NaN  Monthly                          JavaScript;TypeScript   \n",
       "4        NaN      NaN                 Bash/Shell;HTML/CSS;Python;SQL   \n",
       "\n",
       "           LanguageWantToWorkWith          DatabaseHaveWorkedWith  \\\n",
       "0                           Swift               PostgreSQL;SQLite   \n",
       "1                             NaN                      PostgreSQL   \n",
       "2               Julia;Python;Rust                          SQLite   \n",
       "3           JavaScript;TypeScript                             NaN   \n",
       "4  Bash/Shell;HTML/CSS;Python;SQL  Elasticsearch;PostgreSQL;Redis   \n",
       "\n",
       "                     DatabaseWantToWorkWith PlatformHaveWorkedWith  \\\n",
       "0                                    SQLite                    NaN   \n",
       "1                                       NaN                    NaN   \n",
       "2                                    SQLite                 Heroku   \n",
       "3                                       NaN                    NaN   \n",
       "4  Cassandra;Elasticsearch;PostgreSQL;Redis                    NaN   \n",
       "\n",
       "  PlatformWantToWorkWith WebframeHaveWorkedWith WebframeWantToWorkWith  \\\n",
       "0                    NaN        Laravel;Symfony                    NaN   \n",
       "1                    NaN   Angular;Flask;Vue.js                    NaN   \n",
       "2                    NaN                  Flask                  Flask   \n",
       "3                    NaN         Angular;jQuery         Angular;jQuery   \n",
       "4                    NaN                  Flask                  Flask   \n",
       "\n",
       "                  MiscTechHaveWorkedWith  \\\n",
       "0                                    NaN   \n",
       "1                                Cordova   \n",
       "2  NumPy;Pandas;TensorFlow;Torch/PyTorch   \n",
       "3                                    NaN   \n",
       "4       Apache Spark;Hadoop;NumPy;Pandas   \n",
       "\n",
       "                        MiscTechWantToWorkWith     ToolsTechHaveWorkedWith  \\\n",
       "0                                          NaN                         NaN   \n",
       "1                                          NaN             Docker;Git;Yarn   \n",
       "2  Keras;NumPy;Pandas;TensorFlow;Torch/PyTorch                         NaN   \n",
       "3                                          NaN                         NaN   \n",
       "4                          Hadoop;NumPy;Pandas  Docker;Git;Kubernetes;Yarn   \n",
       "\n",
       "      ToolsTechWantToWorkWith  \\\n",
       "0                         NaN   \n",
       "1                         Git   \n",
       "2                         NaN   \n",
       "3                         NaN   \n",
       "4  Docker;Git;Kubernetes;Yarn   \n",
       "\n",
       "                                      NEWCollabToolsHaveWorkedWith  \\\n",
       "0                                                   PHPStorm;Xcode   \n",
       "1                        Android Studio;IntelliJ;Notepad++;PyCharm   \n",
       "2  IPython/Jupyter;PyCharm;RStudio;Sublime Text;Visual Studio Code   \n",
       "3                                                              NaN   \n",
       "4                       Atom;IPython/Jupyter;Notepad++;PyCharm;Vim   \n",
       "\n",
       "                                    NEWCollabToolsWantToWorkWith        OpSys  \\\n",
       "0                                                     Atom;Xcode        MacOS   \n",
       "1                                                            NaN      Windows   \n",
       "2        IPython/Jupyter;RStudio;Sublime Text;Visual Studio Code        MacOS   \n",
       "3                                                            NaN      Windows   \n",
       "4  Atom;IPython/Jupyter;Notepad++;PyCharm;Vim;Visual Studio Code  Linux-based   \n",
       "\n",
       "                                                                                                                                 NEWStuck  \\\n",
       "0                                       Call a coworker or friend;Visit Stack Overflow;Go for a walk or other physical activity;Google it   \n",
       "1                                                                                                          Visit Stack Overflow;Google it   \n",
       "2                                           Visit Stack Overflow;Google it;Watch help / tutorial videos;Do other work and come back later   \n",
       "3                                       Call a coworker or friend;Visit Stack Overflow;Go for a walk or other physical activity;Google it   \n",
       "4  Visit Stack Overflow;Go for a walk or other physical activity;Google it;Watch help / tutorial videos;Do other work and come back later   \n",
       "\n",
       "                      NEWSOSites             SOVisitFreq SOAccount  \\\n",
       "0                 Stack Overflow  Multiple times per day       Yes   \n",
       "1                 Stack Overflow   Daily or almost daily       Yes   \n",
       "2  Stack Overflow;Stack Exchange  Multiple times per day       Yes   \n",
       "3                 Stack Overflow   Daily or almost daily       Yes   \n",
       "4  Stack Overflow;Stack Exchange   Daily or almost daily       Yes   \n",
       "\n",
       "                        SOPartFreq           SOComm NEWOtherComms  \\\n",
       "0  A few times per month or weekly  Yes, definitely            No   \n",
       "1            Daily or almost daily  Yes, definitely            No   \n",
       "2           Multiple times per day  Yes, definitely           Yes   \n",
       "3            Daily or almost daily          Neutral            No   \n",
       "4             A few times per week    Yes, somewhat            No   \n",
       "\n",
       "               Age Gender Trans                Sexuality  \\\n",
       "0  25-34 years old    Man    No  Straight / Heterosexual   \n",
       "1  18-24 years old    Man    No  Straight / Heterosexual   \n",
       "2  18-24 years old    Man    No        Prefer not to say   \n",
       "3  35-44 years old    Man    No  Straight / Heterosexual   \n",
       "4  25-34 years old    Man    No                      NaN   \n",
       "\n",
       "                      Ethnicity                Accessibility  \\\n",
       "0  White or of European descent            None of the above   \n",
       "1  White or of European descent            None of the above   \n",
       "2             Prefer not to say            None of the above   \n",
       "3  White or of European descent  I am deaf / hard of hearing   \n",
       "4  White or of European descent            None of the above   \n",
       "\n",
       "        MentalHealth           SurveyLength                  SurveyEase  \\\n",
       "0  None of the above  Appropriate in length                        Easy   \n",
       "1  None of the above  Appropriate in length                        Easy   \n",
       "2  None of the above  Appropriate in length                        Easy   \n",
       "3                NaN  Appropriate in length  Neither easy nor difficult   \n",
       "4                NaN  Appropriate in length                        Easy   \n",
       "\n",
       "   ConvertedCompYearly  \n",
       "0              62268.0  \n",
       "1                  NaN  \n",
       "2                  NaN  \n",
       "3                  NaN  \n",
       "4                  NaN  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_21.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0af03354-b99c-4199-8107-8d2cf27f09ca",
   "metadata": {},
   "source": [
    "### 2.2. Exploratory data analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ec6e3216-dad9-44ff-b4d6-47c1f1218fa3",
   "metadata": {},
   "source": [
    "Selecting questions:\n",
    "\n",
    "1. How many caffeinated beverages per day?\n",
    "2. Tabs or spaces? (2015 and 2017)\n",
    "3. How much do you agree or disagree with the following statement? I want to go to Mars right now, even if there's a chance I never come back.\n",
    "4. Star Wars or Star Trek?\n",
    "5. Dogs or cats?\n",
    "6. Do you believe in aliens?\n",
    "7. How do you pronouce \"GIF\"?\n",
    "8. Are you the \"IT support person\" for your family?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "eb022e24-11d0-42d9-8df7-9bb2a1584d77",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0               3916\n",
       "2               3587\n",
       "1               2844\n",
       "3               2492\n",
       "4               1535\n",
       "5               1099\n",
       "6                456\n",
       "More than 10     219\n",
       "8                170\n",
       "7                154\n",
       "9                 38\n",
       "Name: How many caffeinated beverages per day?, dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# How many caffeinated beverages per day?\n",
    "q1 = df_15[\"How many caffeinated beverages per day?\"].value_counts()\n",
    "q1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "15520417-80e0-4f3f-af50-af805eb7cb8f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Tabs          11604\n",
       "Spaces         8663\n",
       "It depends     4391\n",
       "Huh?           1149\n",
       "Name: Tabs or Spaces, dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Tabs or spaces?\n",
    "q2_15 = df_15[\"Tabs or Spaces\"].value_counts()\n",
    "q2_15"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "53335e48-3ec8-4cba-8435-e2b7b30b68cd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Tabs      16682\n",
       "Spaces    14667\n",
       "Both       7502\n",
       "Name: TabsSpaces, dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Tabs or spaces?\n",
    "q2_17 = df_17[\"TabsSpaces\"].value_counts()\n",
    "q2_17"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "d1df0db3-ccd2-4d06-ba75-e377fb844b59",
   "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>2015</th>\n",
       "      <th>2017</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Tabs</th>\n",
       "      <td>11604.0</td>\n",
       "      <td>16682.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Spaces</th>\n",
       "      <td>8663.0</td>\n",
       "      <td>14667.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>It depends</th>\n",
       "      <td>4391.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Huh?</th>\n",
       "      <td>1149.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Both</th>\n",
       "      <td>NaN</td>\n",
       "      <td>7502.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               2015     2017\n",
       "Tabs        11604.0  16682.0\n",
       "Spaces       8663.0  14667.0\n",
       "It depends   4391.0      NaN\n",
       "Huh?         1149.0      NaN\n",
       "Both            NaN   7502.0"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q2_15.rename(\"2015\", inplace=True)\n",
    "q2_17.rename(\"2017\", inplace=True)\n",
    "\n",
    "q2 = pd.concat([q2_15, q2_17], axis=1)\n",
    "q2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "b7c9daa4-ad4f-4e91-9b16-843b88f30c72",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Disagree completely    21567\n",
       "Disagree somewhat       6463\n",
       "Neutral                 5217\n",
       "Agree completely        4977\n",
       "Agree somewhat          4461\n",
       "Name: agree_mars, dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# How much do you agree or disagree with the following statement?\n",
    "# I want to go to Mars right now, even if there's a chance I never come back.\n",
    "q3 = df_16[\"agree_mars\"].value_counts()\n",
    "q3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "1d67ea6a-f920-42ba-bec1-6fc979e37e06",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Star Wars               22410\n",
       "Star Trek                8148\n",
       "Star Wars; Star Trek     3840\n",
       "Name: star_wars_vs_star_trek, dtype: int64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Star Wars or Star Trek?\n",
    "q4 = df_16[\"star_wars_vs_star_trek\"].value_counts()\n",
    "q4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "d111feb9-b526-4d66-a1b1-3cb0f4a337eb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Dogs                      22101\n",
       "Cats                      15740\n",
       "Other (please specify)     7398\n",
       "Name: dogs_vs_cats, dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Dogs or cats?\n",
    "q5 = df_16[\"dogs_vs_cats\"].value_counts()\n",
    "q5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "63feaadc-5375-432b-9f21-194fc543f72f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Yes                       25742\n",
       "No                        17243\n",
       "Other (please specify)     6192\n",
       "Name: aliens, dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Do you believe in aliens?\n",
    "q6 = df_16[\"aliens\"].value_counts()\n",
    "q6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "6227c7f7-0a99-4757-9966-e363b68f2ba0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "With a hard \"g,\" like \"gift\"              33484\n",
       "With a soft \"g,\" like \"jiff\"              13408\n",
       "Enunciating each letter: \"gee eye eff\"     3085\n",
       "Some other way                             1031\n",
       "Name: PronounceGIF, dtype: int64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# How do you pronouce \"GIF\"?\n",
    "q7 = df_17[\"PronounceGIF\"].value_counts()\n",
    "q7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "eebf7026-fa46-47ed-9da0-6c96be8dccab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Yes                                         46370\n",
       "SIGH                                        21819\n",
       "Also Yes                                    12313\n",
       "Fortunately, someone else has that title     6639\n",
       "Name: ITperson, dtype: int64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Are you the \"IT support person\" for your family?\n",
    "q8 = df_19[\"ITperson\"].value_counts()\n",
    "q8"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "26b15b57-694d-4bff-8a53-34369de790c5",
   "metadata": {},
   "source": [
    "### 2.3. Null values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "804dd12a-83fe-4d92-8974-0a9bd26c2466",
   "metadata": {},
   "outputs": [],
   "source": [
    "dfs_columns = [\n",
    "    (df_15, \"How many caffeinated beverages per day?\"),\n",
    "    (df_15, \"Tabs or Spaces\"),\n",
    "    (df_17, \"TabsSpaces\"),\n",
    "    (df_16, \"agree_mars\"),\n",
    "    (df_16, \"star_wars_vs_star_trek\"),\n",
    "    (df_16, \"dogs_vs_cats\"),\n",
    "    (df_16, \"aliens\"),\n",
    "    (df_17, \"PronounceGIF\"),\n",
    "    (df_19, \"ITperson\"),\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "a997ef97-9159-4955-9d8c-8f220e4bfacf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Respondents:   Not nulls (abs):   Nulls (abs):   Nulls (per):   Question:\n",
      "      26,086             16,510          9,576         36.71%   How many caffeinated beverages per day?\n",
      "      26,086             25,807            279          1.07%   Tabs or Spaces\n",
      "      51,392             38,851         12,541         24.40%   TabsSpaces\n",
      "      56,030             42,685         13,345         23.82%   agree_mars\n",
      "      56,030             34,398         21,632         38.61%   star_wars_vs_star_trek\n",
      "      56,030             45,239         10,791         19.26%   dogs_vs_cats\n",
      "      56,030             49,177          6,853         12.23%   aliens\n",
      "      51,392             51,008            384          0.75%   PronounceGIF\n",
      "      88,883             87,141          1,742          1.96%   ITperson\n"
     ]
    }
   ],
   "source": [
    "space = \"   \"\n",
    "print(\n",
    "    \"Respondents:\"\n",
    "    + space\n",
    "    + \"Not nulls (abs):\"\n",
    "    + space\n",
    "    + \"Nulls (abs):\"\n",
    "    + space\n",
    "    + \"Nulls (per):\"\n",
    "    + space\n",
    "    + \"Question:\"\n",
    ")\n",
    "\n",
    "for df, column in dfs_columns:\n",
    "    respondents = df.shape[0]\n",
    "    null_per = df[column].isnull().mean()\n",
    "    null_abs = respondents * null_per\n",
    "    not_null_abs = respondents - null_abs\n",
    "\n",
    "    print(\n",
    "        f\"{respondents:>12,}\"  # 12 is the length of \"Respondents:\"\n",
    "        + space\n",
    "        + f\"{not_null_abs:>16,.0f}\"  # 16 is the length of \"Not nulls (abs):\"\n",
    "        + space\n",
    "        + f\"{null_abs:>12,.0f}\"  # 12 is the length of \"Nulls (abs):\"\n",
    "        + space\n",
    "        + f\"{null_per:>12.2%}\"  # 12 is the length of \"Nulls (per):\"\n",
    "        + space\n",
    "        + f\"{column}\"\n",
    "    )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9cfe997b-4a15-433e-b9ef-90a1c2922d2b",
   "metadata": {},
   "source": [
    "Some questions have a relatively high percentage of null values, like Star Wars vs. Star Trek, with 38% of nulls. However, the absolute number is still high enough (34,398 respondents, for the previous example) to provide representative descriptive statistics. Since any input method for the missing data would add a bias, the null values will just be removed."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6a30b841-e0e4-4ad3-afd0-4efe38982c76",
   "metadata": {},
   "source": [
    "## 3. Data preparation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cfda5ce5-ceb9-43f1-81bd-739a0b4b0dd3",
   "metadata": {},
   "source": [
    "### 3.1. Adjusting labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "50851fe4-be29-4258-88ff-4e834656cc37",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Dropping uncomparable items (2017 survey doesn't have 'Huh?')\n",
    "q2.drop(labels=[\"Huh?\"], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "d506a951-b026-472b-8f3f-8540cb0f43c0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Standardizing and simplifiyng labels\n",
    "q2.rename({\"It depends\": \"Both\"}, inplace=True)\n",
    "q4.rename({\"Star Wars; Star Trek\": \"Both\"}, inplace=True)\n",
    "q5.rename({\"Other (please specify)\": \"Other\"}, inplace=True)\n",
    "q6.rename({\"Other (please specify)\": \"Other\"}, inplace=True)\n",
    "q8.rename({\"SIGH\": \"Sigh\"}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "462fa690-bcc4-4d01-bfd1-34acd8667315",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Combining rows with same label to remove NaNs\n",
    "q2 = q2.groupby(q2.index).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "ec630348-6238-447f-8f71-dffc7197dde0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Ordering in a more intuitive way\n",
    "q1 = q1.reindex([\"0\", \"1\", \"2\", \"3\", \"4\", \"5\", \"6\", \"7\", \"8\", \"9\", \"More than 10\"])\n",
    "q2 = q2.reindex([\"Tabs\", \"Spaces\", \"Both\"])\n",
    "q3 = q3.reindex([\"Disagree completely\", \"Disagree somewhat\", \"Neutral\", \"Agree somewhat\", \"Agree completely\"])\n",
    "q8 = q8.reindex([\"Yes\", \"Also Yes\", \"Sigh\", \"Fortunately, someone else has that title\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "debabdba",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Breaking label lines to fit on the charts and translating to brazilian portuguese\n",
    "q1.rename({\"More than 10\": \"Mais\\nque\\n10\"},\n",
    "          inplace=True)\n",
    "\n",
    "q2.rename({\"Tabs\": \"Tabulações\",\n",
    "           \"Spaces\": \"Espaços\",\n",
    "           \"Both\": \"Ambos\"},\n",
    "          inplace=True)\n",
    "\n",
    "q3.rename({\"Disagree completely\": \"Discordo\\ncompletamente\",\n",
    "           \"Disagree somewhat\": \"Discordo\\num pouco\",\n",
    "           \"Neutral\": \"Indiferente\",\n",
    "           \"Agree somewhat\": \"Concordo\\num pouco\",\n",
    "           \"Agree completely\": \"Concordo\\ncompletamente\"},\n",
    "          inplace=True)\n",
    "\n",
    "q4.rename({\"Star Wars\": \"Star\\nWars\",\n",
    "           \"Star Trek\": \"Star\\nTrek\",\n",
    "           \"Both\": \"Ambos\"\n",
    "          },\n",
    "          inplace=True)\n",
    "\n",
    "q5.rename({\"Dogs\": \"Cães\",\n",
    "           \"Cats\": \"Gatos\",\n",
    "           \"Other\": \"Outro\"},\n",
    "          inplace=True)\n",
    "\n",
    "q6.rename({\"Yes\": \"Sim\",\n",
    "           \"No\": \"Não\",\n",
    "           \"Other\": \"Outro\"},\n",
    "          inplace=True)\n",
    "\n",
    "q7.rename({'With a hard \"g,\" like \"gift\"': 'Com um \"g\" de gato',\n",
    "           'With a soft \"g,\" like \"jiff\"': 'Com um \"g\" de girafa',\n",
    "           'Enunciating each letter: \"gee eye eff\"': 'Enunciando cada letra:\\n\"gê i efe\"',\n",
    "           \"Some other way\": \"Algum outro jeito\"},\n",
    "          inplace=True)\n",
    "\n",
    "q8.rename({\"Yes\": \"Sim\",\n",
    "           \"Also Yes\": \"Também sim\",\n",
    "           \"Sigh\": \"Suspirando\",\n",
    "           \"Fortunately, someone else has that title\": \"Felizmente, outra\\npessoa tem esse título\"},\n",
    "          inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8eba8cdb-2443-43e8-81c7-b8b55392532d",
   "metadata": {},
   "source": [
    "### 3.2. Getting x and y values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "5940f07e-a84f-451b-bfcb-b547b69e5284",
   "metadata": {},
   "outputs": [],
   "source": [
    "q0_x = list(range(2011, 2022))\n",
    "\n",
    "surveys = [df_11, df_12, df_13, df_14, df_15, df_16, df_17, df_18, df_19, df_20, df_21]\n",
    "q0_y = []\n",
    "for survey in surveys:\n",
    "    rows = survey.shape[0]\n",
    "    q0_y.append(rows)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "3be896c4-1c6f-4fbe-a7d0-166ec1738e0a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# The convention used is labels as x and values as y\n",
    "q1_x = q1.index.tolist()\n",
    "q1_y = q1.to_list()\n",
    "\n",
    "q2_x = q2.columns.tolist()\n",
    "q2_y_t = q2.loc[\"Tabulações\"].tolist()\n",
    "q2_y_s = q2.loc[\"Espaços\"].tolist()\n",
    "q2_y_b = q2.loc[\"Ambos\"].tolist()\n",
    "q2_l = q2.index.tolist()  # Legend\n",
    "\n",
    "q3_x = q3.index.tolist()\n",
    "q3_y = q3.to_list()\n",
    "\n",
    "q4_x = q4.index.tolist()\n",
    "q4_y = q4.to_list()\n",
    "\n",
    "q5_x = q5.index.tolist()\n",
    "q5_y = q5.to_list()\n",
    "\n",
    "q6_x = q6.index.tolist()\n",
    "q6_y = q6.to_list()\n",
    "\n",
    "q7_x = q7.index.tolist()\n",
    "q7_y = q7.to_list()\n",
    "\n",
    "q8_x = q8.index.tolist()\n",
    "q8_y = q8.to_list()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1ea09b08-5081-4e16-8eea-b61c21150be3",
   "metadata": {},
   "source": [
    "### 3.3. Transforming into percentages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "79ca3407-e251-4017-bd05-de5ba4d0aed0",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_percentages(abs_values):\n",
    "    \"\"\"\n",
    "    Transform a list of absolute numbers into percentages of the total sum.\n",
    "    \n",
    "    Parameters:\n",
    "        abs_values (list of floats): A list with absolute numbers.\n",
    "    \n",
    "    Return:\n",
    "        per_values (list of floats): A list with the percentage of each\n",
    "            absolute number regarding the total sum.\n",
    "    \"\"\"\n",
    "    \n",
    "    np_abs_values = np.array(abs_values)\n",
    "    total = np.sum(np_abs_values, axis=0)\n",
    "    per_values = list(np_abs_values/total)\n",
    "\n",
    "    return per_values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "6cd322b0-6013-45a9-85fa-b23500017518",
   "metadata": {},
   "outputs": [],
   "source": [
    "q1_y_per = get_percentages(q1_y)\n",
    "q3_y_per = get_percentages(q3_y)\n",
    "q4_y_per = get_percentages(q4_y)\n",
    "q5_y_per = get_percentages(q5_y)\n",
    "q6_y_per = get_percentages(q6_y)\n",
    "q7_y_per = get_percentages(q7_y)\n",
    "q8_y_per = get_percentages(q8_y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "8810f14d-5732-49fe-8d17-d725954d5779",
   "metadata": {},
   "outputs": [],
   "source": [
    "q2_y_t_abs = np.array(q2_y_t)\n",
    "q2_y_s_abs = np.array(q2_y_s)\n",
    "q2_y_b_abs = np.array(q2_y_b)\n",
    "\n",
    "total = np.sum([q2_y_t_abs, q2_y_s_abs, q2_y_b_abs], axis=0)\n",
    "\n",
    "q2_y_t_per = list(q2_y_t_abs/total)\n",
    "q2_y_s_per = list(q2_y_s_abs/total)\n",
    "q2_y_b_per = list(q2_y_b_abs/total)\n",
    "\n",
    "q2_y_per = [q2_y_t_per, q2_y_s_per, q2_y_b_per]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c39452c7-42f2-481d-9a13-9593ab023951",
   "metadata": {},
   "source": [
    "## 4. Descriptive statistics"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "999c5dc2-409d-48a0-97b4-3ab3ee7da97c",
   "metadata": {},
   "source": [
    "### 4.1. Support functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "e71f4546-e71a-4b5f-b06e-338cd655f3f0",
   "metadata": {},
   "outputs": [],
   "source": [
    "def calc_bar_positions(classes, space=1/2):\n",
    "    \"\"\"\n",
    "    Calculate the coordinates and size of bars, given a desired space.\n",
    "    \n",
    "    Parameters:\n",
    "        classes (list of strings): A list of the major tick labels for the x\n",
    "            or y axis. In other words, the classes.\n",
    "        space (float): The space between bars, in terms of the size (width or\n",
    "            height) of them.\n",
    "    \n",
    "    Return:\n",
    "        coords (list of floats): A list with the x or y coordinates to\n",
    "            position the bars.\n",
    "        size (float): The width of the bar (x axis) or the height of the bar\n",
    "            (y axis).\n",
    "    \n",
    "    Example:\n",
    "        Let's say there are 2 classes in the y axis, and we want to generate y\n",
    "        coordinates to position them, with spaces with 1/4 of their height\n",
    "        between them and the axis limits. First, we need to calculate the\n",
    "        space unit, with the following equation:\n",
    "        \n",
    "        space_unit = 1/(1 + 2*(space) + (n - 1)*(1 + space))\n",
    "        \n",
    "        Where:\n",
    "        \n",
    "        Space unit: The size of a single space. It's the fraction that a bar\n",
    "            occupies on an axis with a size of 1 and a given ammount of space\n",
    "            between the bars.\n",
    "        Numerator: The total size of the x or y axis, always 1.\n",
    "        Denominator: The number of spaces to divide the axis by.\n",
    "        \n",
    "        This would give us as a space unit of 1/2.75. The details of how to\n",
    "        calculate the denominator are:\n",
    "        \n",
    "        1/4 (from the bottom of the y axis to the bottom of the first bar)\n",
    "        + 1 (height of the first bar)\n",
    "        + 1/4 (space between bars)\n",
    "        + 1 (height of the second bar)\n",
    "        + 1/4 (from the top of the second bar to the top of the y axis)\n",
    "        = 2.75\n",
    "        \n",
    "        Then, we would need to use the space unit to calculate the x or y\n",
    "        coordinate for each bar, with the following equation:\n",
    "        \n",
    "        coordinate = space_unit*(1/2 + space + i*(1 + space))\n",
    "        \n",
    "        To calculate the y coordinate for the second bar, it would be:\n",
    "        \n",
    "        1/4 (from the bottom of the y axis to the bottom of the first bar)\n",
    "        + 1 (height of the first bar)\n",
    "        + 1/4 (space between bars)\n",
    "        + 1/2 (half of the height of the second bar)\n",
    "        = 2\n",
    "    \"\"\"\n",
    "    n = len(classes)\n",
    "    space_unit = 1 / (1 + 2 * (space) + (n - 1) * (1 + space))\n",
    "\n",
    "    # List with the coordinate of every bar\n",
    "    coords = []\n",
    "    for i in range(n):\n",
    "        # Calculate the coordinate to position the bar\n",
    "        coords.append(space_unit * (1 / 2 + space + i * (1 + space)))\n",
    "\n",
    "    size = space_unit\n",
    "    \n",
    "    return coords, size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "db7e8911-3e41-4891-a2c8-ad63123c87f4",
   "metadata": {},
   "outputs": [],
   "source": [
    "def annotate_plot(text, xy, xytext, **kwargs):\n",
    "    \"\"\"\n",
    "    Annotate the point xy with text and offset it.\n",
    "\n",
    "    Parameters:\n",
    "        text (string): The text to be annotated.\n",
    "        xy (tuple of floats): The x and y coordinates to place the text.\n",
    "        xytext (tuple of floats): The ammount of x and y points to offset the\n",
    "            text.\n",
    "        **kwargs: Accepts any keyword argument from the annotate function.\n",
    "\n",
    "    Return:\n",
    "        None.\n",
    "    \"\"\"\n",
    "    plt.gca().annotate(\n",
    "        text,  # This is the text\n",
    "        xy,  # These are the coordinates to position the label\n",
    "        textcoords=\"offset points\",  # How to position the text\n",
    "        xytext=xytext,  # Distance from text to points (x, y)\n",
    "        fontsize=11,\n",
    "        **kwargs\n",
    "    )\n",
    "    return"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "86a61442-a48b-4b83-9c0b-4561575cd1ad",
   "metadata": {},
   "outputs": [],
   "source": [
    "def style_vertical():\n",
    "    \"\"\"Apply a minimalist style to a vertical bar chart plot\"\"\"\n",
    "    plt.gca().yaxis.set_major_formatter(StrMethodFormatter(\"{x:,.0%}\"))\n",
    "    plt.gca().tick_params(bottom=False, width=1)\n",
    "    plt.gca().spines[\"bottom\"].set_visible(False)\n",
    "    return"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "dfaba309-36b7-4e7c-a0ee-57855f149676",
   "metadata": {},
   "outputs": [],
   "source": [
    "def style_horizontal():\n",
    "    \"\"\"Apply a minimalist style to a horizontal bar chart plot\"\"\"\n",
    "    plt.gca().xaxis.set_major_formatter(StrMethodFormatter(\"{x:,.0%}\"))\n",
    "    plt.gca().tick_params(left=False, width=1)\n",
    "    plt.gca().spines[\"left\"].set_visible(False)\n",
    "    return"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "8b709577-9df0-41f5-a66e-b2af336800fa",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_line(x, y, title, xlabel, ylabel, xlim, ylim, **kwargs):\n",
    "    \"\"\"\n",
    "    Plot a line chart with a minimalist style.\n",
    "\n",
    "    Parameters:\n",
    "        x (list of floats): A list with the x values to plot.\n",
    "        y (list of floats): A list with the y values to plot.\n",
    "        title (string): The title of the chart.\n",
    "        xlabel (string): The name of the x axis metric.\n",
    "        ylabel (string): The name of the y axis metric.\n",
    "        xlim (tuple of floats): A tuple with the left and right limits for\n",
    "            the x axis.\n",
    "        ylim (tuple of floats): A tuple with the bottom and top limits for\n",
    "            the y axis.\n",
    "        **kwargs: Accepts any keyword argument from the figure function.\n",
    "\n",
    "    Return:\n",
    "        fig (figure): A figure with the final plot stored.\n",
    "    \"\"\"\n",
    "    fig = plt.figure(**kwargs)\n",
    "\n",
    "    plt.plot(x, y)\n",
    "\n",
    "    plt.title(title)\n",
    "    # Hide the spine inside the 0.1 x axis margin\n",
    "    # Must come before plt.xlim()\n",
    "    plt.gca().spines[\"bottom\"].set_bounds(xlim)\n",
    "    # Add a 0.1 margin to avoid trimming the round end of the line\n",
    "    xlim = (xlim[0], xlim[1] + 0.1)\n",
    "    plt.xlim(xlim)\n",
    "    plt.ylim(ylim)\n",
    "    # Right align the xlabel to the last major tick label\n",
    "    plt.xlabel(xlabel, va=\"top\", ha=\"right\", x=1.015)\n",
    "    # Vertically align the ylabel to the last major tick label\n",
    "    plt.ylabel(ylabel, va=\"bottom\", ha=\"right\", y=1.026)\n",
    "    # Show major ticks as multiples of 1 on the x axis\n",
    "    plt.gca().xaxis.set_major_locator(plt.MultipleLocator(1))\n",
    "    plt.tight_layout(h_pad=4, w_pad=4)\n",
    "    plt.show()\n",
    "\n",
    "    return fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "e57dab86-e91f-43b1-b1d3-75bfbf0647ee",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_bar(\n",
    "    x, y, title, horizontal=False, xlim=(0, 1), ylim=(0, 1), space=1 / 2, **kwargs\n",
    "):\n",
    "    \"\"\"\n",
    "    Plot a bar chart with a minimalist style.\n",
    "\n",
    "    Parameters:\n",
    "        x (list of strings): A list with the name of the labels of the\n",
    "            classes.\n",
    "        y (list of floats): A list with the y values of each class.\n",
    "        title (string): The title of the chart.\n",
    "        horizontal (bool): The orientation of the chart. The default is False,\n",
    "            which is vertical.\n",
    "        xlim (tuple of floats): A tuple with the left and right limits for\n",
    "            the x axis. The default is (0, 1), useful for percentages.\n",
    "        ylim (tuple of floats): A tuple with the bottom and top limits for\n",
    "            the y axis. The default is (0, 1), useful for percentages.\n",
    "        space (float): The space between bars, in terms of the size (width or\n",
    "            height) of them.\n",
    "        **kwargs: Accepts any keyword argument from the figure function.\n",
    "\n",
    "    Return:\n",
    "        fig (figure): A figure with the final plot stored.\n",
    "    \"\"\"\n",
    "    fig = plt.figure(**kwargs)\n",
    "    coords, size = calc_bar_positions(x, space)\n",
    "\n",
    "    if horizontal:\n",
    "        plt.barh(coords[::-1], y, height=size)\n",
    "        plt.yticks(coords[::-1], x)\n",
    "        style_horizontal()\n",
    "    else:\n",
    "        plt.bar(coords, y, width=size)\n",
    "        plt.xticks(coords, x)\n",
    "        style_vertical()\n",
    "\n",
    "    # Styling and showing the chart\n",
    "    plt.title(title)\n",
    "    plt.xlim(xlim)\n",
    "    plt.ylim(ylim)\n",
    "    plt.tight_layout(h_pad=4, w_pad=4)\n",
    "    plt.show()\n",
    "\n",
    "    return fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "2b8016db-f65a-4b2b-ad02-3125482591c9",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_slope(dates, series, legends, title, ylim=(0, 1), **kwargs):\n",
    "    \"\"\"\n",
    "    Plot a slopegraph with a minimalist style.\n",
    "\n",
    "    Parameters:\n",
    "        dates (list of strings): A list with two date labels, always.\n",
    "        series (list of list of floats): A list with other lists inside,\n",
    "            each one with the y values from a specific class.\n",
    "        legends (list of strings): A list with the legend of each class.\n",
    "        title (string): The title of the chart.\n",
    "        ylim (tuple of floats): A tuple with the bottom and top limits for\n",
    "            the y axis. The default is (0, 1), useful for percentages.\n",
    "        **kwargs: Accepts any keyword argument from the figure function.\n",
    "\n",
    "    Return:\n",
    "        fig (figure): A figure with the final plot stored.\n",
    "    \"\"\"\n",
    "    fig = plt.figure(**kwargs)\n",
    "\n",
    "    items = zip(series, legends)\n",
    "    for single_series, legend in items:\n",
    "        plt.plot(dates, single_series, \"o-\", markersize=10)\n",
    "\n",
    "        # Pick the label color from the style sheet file\n",
    "        color = mpl.rcParams[\"axes.labelcolor\"]\n",
    "        labels = zip(dates, single_series)\n",
    "        for i, (x, y) in enumerate(labels):\n",
    "            label = \"{:.0%}\".format(y)\n",
    "\n",
    "            if i % 2 == 0:  # First date label\n",
    "                annotate_plot(\n",
    "                    label, (x, y), (-10, 0), ha=\"right\", va=\"center\", color=color\n",
    "                )\n",
    "                annotate_plot(\n",
    "                    legend, (x, y), (-45, 0), ha=\"right\", va=\"center\", color=color\n",
    "                )\n",
    "            else:  # Second date label\n",
    "                annotate_plot(\n",
    "                    label, (x, y), (10, 0), ha=\"left\", va=\"center\", color=color\n",
    "                )\n",
    "\n",
    "    # Styling and showing the chart\n",
    "    plt.title(title)\n",
    "    plt.ylim(ylim)\n",
    "    plt.margins(x=0.05)\n",
    "    plt.tick_params(left=False, width=1)\n",
    "    plt.gca().yaxis.set_visible(False)\n",
    "    plt.gca().spines[\"left\"].set_visible(False)\n",
    "    plt.gca().spines[\"bottom\"].set_bounds((0, 1))\n",
    "    plt.tight_layout(h_pad=4, w_pad=4)\n",
    "    plt.show()\n",
    "\n",
    "    return fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "6427c011-85ce-4f4d-82ba-1ea3997e0244",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_hor_stacked_bars(\n",
    "    values, legends, title, bar_colors, leg_colors, xlim=(0, 1), ylim=(0, 1), **kwargs\n",
    "):\n",
    "    \"\"\"\n",
    "    Plot horizontal stacked bars chart with a minimalist style.\n",
    "\n",
    "    Parameters:\n",
    "        values (list of floats): A list with the size of each bar.\n",
    "        legends (list of strings): A list with the legend of each bar.\n",
    "        bar_colors (list of strings): A list with the bar colors in the\n",
    "            hexadecimal format, including the #.\n",
    "        leg_colors (list of strings): A list with legend colors in the\n",
    "            hexadecimal format, including the #.\n",
    "        xlim (tuple of floats): A tuple with the left and right limits for\n",
    "            the x axis. The default is (0, 1), useful for percentages.\n",
    "        ylim (tuple of floats): A tuple with the bottom and top limits for\n",
    "            the y axis. The default is (0, 1), useful for percentages.\n",
    "        **kwargs: Accepts any keyword argument from the figure function.\n",
    "\n",
    "    Return:\n",
    "        fig (figure): A figure with the final plot stored.\n",
    "    \"\"\"\n",
    "    fig = plt.figure(**kwargs)\n",
    "\n",
    "    # Store the position from which the bars begin\n",
    "    left = 0\n",
    "    zipped = zip(values, legends, bar_colors, leg_colors)\n",
    "    for value, legend, bar_color, leg_color in zipped:\n",
    "        rect = plt.barh(y=3 / 4, width=value, height=1, left=left, color=bar_color)\n",
    "\n",
    "        # Put the legend in the middle of each bar\n",
    "        xy = (\n",
    "            rect[0].get_x() + rect[0].get_width() / 2,\n",
    "            rect[0].get_y() + rect[0].get_height(),\n",
    "        )\n",
    "\n",
    "        annotate_plot(legend, xy, (0, 5), ha=\"center\", va=\"bottom\", color=leg_color)\n",
    "        left += value\n",
    "\n",
    "    # Styling and showing the chart\n",
    "    style_horizontal()\n",
    "    plt.title(title)\n",
    "    plt.xlim(xlim)\n",
    "    plt.ylim(ylim)\n",
    "    plt.gca().xaxis.set_major_locator(plt.MultipleLocator(0.1))\n",
    "    plt.gca().yaxis.set_visible(False)\n",
    "    plt.tight_layout(h_pad=4, w_pad=4)\n",
    "    plt.show()\n",
    "\n",
    "    return fig"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "baf01708-f194-4f75-bfb9-7495b324cc8c",
   "metadata": {},
   "source": [
    "### 4.2. Visualizations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "f177c1b1-7b00-4502-9ac6-11146fbe94c5",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Titles\n",
    "t0 = \"Quantas pessoas responderam a pesquisa por ano?\"\n",
    "t1 = \"Quantas bebidas cafeinadas por dia?\"\n",
    "t2 = \"Tabulações ou espaços?\"\n",
    "t3 = \"Quanto você concorda ou discorda da seguinte afirmação?\\nQuero ir para Marte imediatamente, mesmo que haja uma chance de eu nunca mais voltar.\"\n",
    "t4 = \"Star Wars ou Star Trek?\"\n",
    "t5 = \"Cães ou gatos?\"\n",
    "t6 = \"Você acredita em extraterrestres?\"\n",
    "t7 = 'Como se pronuncia \"GIF\"?'\n",
    "t8 = 'Você é a pessoa \"suporte de TI\" da sua família?'"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "841b30a0-ba31-4128-96f1-f8b6bab658b5",
   "metadata": {},
   "source": [
    "#### 4.2.1. Survey respondents"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "19f467b9-0435-4c00-b37b-27f21914856d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1000x450 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 427,
       "width": 978
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig0 = plot_line(\n",
    "    q0_x,\n",
    "    q0_y,\n",
    "    t0,\n",
    "    xlabel=\"Ano\",\n",
    "    ylabel=\"Respondentes\",\n",
    "    xlim=(2011, 2021),\n",
    "    ylim=(0, 120000),\n",
    "    figsize=(10, 4.5),\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "99485817-59db-4237-81a5-a4c4b4cca11f",
   "metadata": {},
   "source": [
    "#### 4.2.2. Caffeinated beverages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "e4e22e37-b7de-4cb5-980d-9d30b059495d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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33E8oKSnR5s1btHnzFn3z7Xdq166dpk3503S70+F9zl12u12/T56sjz7+VJmZmZXaJjs7R3PmzNWcOXPVpXNnvfzSi3UiaDrZ0qXL9NwLL1bq/E9PT9eob77VxEmT9PFHH+ryyy5zen9JSUn65LPPtXjxEtPA8FTZ2TlaumyZli5bpk/OOkuvvvKSS204VVFRkb748it9+933pjf8SkpKtHr1Gq1evUZdOnfWxx99qOho9yf9rkvHJSMjQ2++9bZmzprt9LZpaWlKS0vTjJmz9PIrr2rRgvlVcnzclZ9foLfeflsTJk6S3W6vcN2ioiItXLRICxctUv/+/fT2m2+43RPOZrPpo08+1fjxEyr92SUzM1Pjxk/Q+AkTdc2gq/XC889Xee+Y/Px8vfve+xo3foJKSkqqtG5XZWVl6YUXX1b8nDmm6+bl5WnGzFmaOWu2htxys1568UX5+dVurzCr1aZ33ntPc+bMqXQQd0JRUZE2bNyoDRs36utR3+ihBx+ole++o8cYH8QLCQlRl86Vn9wZAABX1I07i6gS8fGOP8zddNON1bbPG2+8wWH5rNnx1bbP6jRu3HiXbrKcrKioSL/9PlnX33iz9u6t+GlsZ+3es0eDr7+hUmHCyex2u8aO/VWPPPpYnfkSUlxcrF9Gj3H6puSp8vLy9O133+uOO4crM/OIS+146uln9PY77zp9U9KR/Px8t+uoCqPHjNVDIx6p1E3zk+3fv1+33zlMf/41xa39r169Wv0HDtLvkx0HnWYKCgr0w48/aejtd7j0dy1PbR8Xd/z++2TdcefwSt1MPNmRrCw99PAIh186ncV5W7VsNpseHvGIHnn0cafCBEe2bNlSqfXq+vucuywWi+697wE9/8JLlQ4TTpWQmKgbb75FCxYuquLWuW78+Am6657/OX3+Z2Ud1X33P6hZLtxwXr9ho+bOnef0TfNT7dmzR/f87z598+13btWTl5en++5/UCO/HmUaJpwqITFRN9x4k1JSUtxqg1R3jkvK7t26/sabXQoTTlVcXKziYueOaXXIy8vTsOF3afyEiaZhwqlmzJipG268WWlOniMnS9m9W4Ovv0Fjx/7q0mcXu92uKVOnadC1g7Vp82aX23Eqq9WqW4ferrG/jqszn+P37t2n6264qVJhwsnsdrvGT5ioYcPvUm5ubjW1rnIyj2Tqt99+dzpMOJXFYtG7772vEY88WqO/0++/T9aChQsN5dcNvva0GV4KAHD6oofCGeLQoUP6d9s2Q3lMTBN1uuCCattvpwsuUNOYGO1LTS1TvnHjRh07dkyhoaHVtu+a5OnpqcaNoxUSHHJ86AAPyWa1KXX/fh07dszhNtu3b9ewu+7WtCl/Vkk32IMHD+r2O4YZJr2uV6+eYmJiFBbWQAX5BUo7kKaMjIMO65g5a7Z+/mW07r5ruNvtqU7e3t5q3LixgoODFRwcpJLiElmtVu3bt0+27GyH2yQkJuqBhx7S+F/HOvXE88effKqp0/4ud3lQUJCaNW2qoKAg+fj4yGazyWqzKjV1v9s3E6pL/Jy5evOttw1fxsMaNFB048YKCgrU4UOHlbp/v8MbqUVFRXr2uecVGBCgPn2ucnr/CxYs1IMPj6jw+MTENFF4WLgCAgOUlZWlffv2ORy2YuPGTbp5yBBNnDBeDcPDnW7LyWr7uLjjnxkz9PyLL5V7g8XPz08xTZqoYaOGslltSjuQVuYLst1u15tvva3GjaOrrY2ct87JysrSncPvrjAI8PT0VHR0tMLCGig4OFhWq1VZWVnavz/N6ZttZurC+5y7jhw5ojuH3aWt//5b7jqhoaFqHB2t0Pqhys3JVUZGhsOALDc3V/c/8KA+++Rj9evXtzqbbWrq1Gl65bXXDX/zRo0aKTIyQsHBwTp29Jh279njcOiqwsJCPfvc84qLa+/2kIwnBAcHKzLi+L4DAgKUk5tbei13dCO2pKREH370sYKDgjR06K1O76+kpESPPPqYFi4qP+Q5+Vp+6NAhw/menpGhu+65VyO//MLp/VdWTR2X3NxcDR9+d7kBk4eHhyIjIhQdHa16AfVUXFQsm82mzCNHKhzmr7Y9+dQzSly1qkyZh4eHYpo0UWRUpIqLipWekVHu7528a5eGDbtLv02aoPr16zu17z179urWobfp4MHyJ7Nt3LixIiMi5OXtpYz0DO1PS3N4gz89PV233zFMY0b/rA5xcU6141QlJcW674EHtX7DBsOyE5+l/P39lXHwYOl8StXtcGam7rhzmOH738lOPlYHMw5qX2pqmWtY4qpVevKpZ6p0jr+q5OvrqyZNGisoKEhBQUEqLCyUxWLVnj17yn0IYcbMWfLw9NQXn31a7e2bO2+eXnn1NUN5o0aNNOLhh6p9/wAAECicIdZv2ODw5sJ5Hc+r9n137NjR8IGyuLhYGzZu1GXdu1f7/quDj4+PLrroQvXu1UsXnH+eWrZsWe7EW3v37tPMmTM1bsJEw/jQe/bs0YsvvaLPP/vE7TY99viTZcKE3r16atiwO3Vhp06GiSS379ihUaO+0bS/pxvq+eTTz9SvX181jnZ8Y7FRowhN/m1S6c8LFi7UyK9HlVmnx+WX6+GHHnTn1ynD399fl15ysXr16qWOHTqoRYtYh5Nj2u127dyZrL+nT9eEiZN05EjZJ5vXrFmrTz/7XE8/9WSl9pucnKwff/rZUF6/fn0Nu/MO9evbV+ec08LhtkVFRUpJ2a2169ZpwcKFWrZseaXGIK9uR7Ky9OIpN54HDhigO+64TRecf36ZMaSzs7M1d+48ffHVSO3evbtMPSUlJXrmuefVoUMHp4ZA2LkzWY889rjDm7bnnttKdw0frh6XX2YYhq2goEAJCYn6etQ3hpsJKSm79dxzL+iH77+tdDtOVdvHxR1paWl6/oUXHV7jmzc/W488/LB69+6lwMDA0nK73a41a9bol9FjSp9etdvteuGFlxReRUPgcd66Lj8/X/+774Fyw4ROnS7Qbbfeqm7dLnU4rrnVatXGTZs1b948zZ4d71KPkZp+nxs18ivDdeGGm242rHfy+48j55zjeLLhkpISPfr4Ew7DhKCgIA29dYiuHjhQrVufaxhLPzk5WZN+n6yxY38t08aioiI99/wLatu2rc46q1mF7aouycnJmjFzZun5HxQYqOHDh2nQ1QMNE8Hm5xdo4aJF+ujjj7VrV9kn8W3Z2Xr1tTdcvo42btxYvXr20GXdu6tNm9Zq3Lixw/Vyc3O1avVq/T75D82cOctw3XrrnXd1wQUXOD2c1M+/jNa8+Y57Z149cKDuuOM2nX/eeWX+tjabTXPmztUXX47U3r17JUl79+7VW2+/49S+K1Jbx+XrUd84vJnbsUMHDR8+TJd171buQz1Wq01JSdu0bPkKLVi4UJs2Vd2T9O7486+/lJDwf/OPBAUG6oEH7tc1gwYZ3m9Tdu/W5Ml/6KefflZBYWGZZcm7dunV195w6rN3YWGhHnnsMYdhgp+fn/53z926bvBgw3UgIyND0/6erq9HfSOLxVJmmdVq1YhHHtX0adMUHOx64PrTz6O1Y8eO0p8jIyP0wP3366orrzBMvFxYWKily5YrOqp650948cWXHL7+fH19dc/dd+mG6683HKsDB9I1ddo0jRr1TelDBrPj48udB6KmBQcHq3v3burVs4fi2sepefOzHc5xUlxcrK3//qtp0/7WpN9+MzwM888/M9S1SxfdOuSWamvr7NnxeuzxJwyvfV8fH335+WdOh2kAALjCw17Vj7ihVjia9FOSnn/u2Wofz/GHH3/Su++9byg3G5O6Lk7KfMONN+uKK3rrlptvcvrDWG5urt57/wP9Om68YdnUKX9WelJkqeJJKYMCA/XZZ5+qZ4/LTesZPWas3njzLUP5iIcf0mOPPlKptlRmkkhXFBUVqd+Agbrzjtt13eDBTo/DffToUb3w4suaHV92eC1fHx8tXrRAjRo1Mq3jw48+Ngw1cPbZZ+vXMaOdvllstdo0+Y8/FBwc7PQk4K5ydA6dzNfXV198/qmuvOKKCuvJy8vTK6++rj/+NI6/3rNHj0rfgMrLy9O1191Q5ouvdPzG5dNPPVnpnjG/jB6jt9951/DU3+uvvaLbhg413b6uHRd3J2Uefvc9Wrx4iaH8+uuu05tvvCY/P78Kt585c5aeePIpwxfPk1V20ljO26rx1tvv6OdfRhvKg4OD9f677zjVA6akpETx8XP0zXffacqff5iuX1fe56SqmUzzhC+//EqfffGlobx792765KMPKzXh7I4dO3XXPf8z9AQ8r2NH/f7bxErNQVTVkzKf7Pzzz9c3X39lOi9Wdna2/nfv/YZ2eHh4aP7cOWrWrHKTdU6e/IfmzJunu4YNU5cuzo/HvWbtWo145FFDr8nevXrqu2+/qXQ9e/fuU/+BVxuGEqnstTw3N1cvvfyKpkydVu46TZo00eKF8yvVnto+Lna7Xd26X24IEm+/baheefklp+fK2rFjp0aPGaMRDz9kuEFdXRx9Xj9Z2zZt9O03X5cb0JyQtH277r7nXoc9Fr77ZpR69+5VqfZ88OFH+va77w3l57RooW+++VrNzz67wu0zMjL08COPau3adYZl1wy6Wp98/FGl2mF2XAYOGKD33n273PC3Jvw9/R899vgThvKmMTH64fvvyg30T0hLS9N99z9YYU8yZ75nuPM+snvPHj362OMaPuxO9e/Xz+FDERVJO3BATzzxlFatXl2mPCwsTEsXL6qWOSKmTp2mZ5573jDsm5eXlz779GP179evyvcJAIAjzKFwhjjx5NWp2rVrW+37Lm8fpz7Zezr4/beJuv++e116sqNevXp6/bVXdfttxhuejm4cucLX11djRv9SqTBBku6843YNGNDfUD75D/OJO6ubt7e34mfN1G1Dh7o0qWf9+vX15Ref6YpTviwWFBY6vNnlyJIlSw1lb735uktPngcHB2n4sDtr9KZkRTw9PSt1o0U6/qT5e+++rX59+xiWLVi4UIuXGG9mO/LlVyMNYYKXl5dGfvmFU8NsDbvzDr36ykuG8q9GjnJ7uJraOC7uWLBwkcMwoX+/vnrv3bdNwwRJ6tevrz795GPDU9mu4Lx135YtW/XL6DGG8oYNG2ri+F+dHk7L09NTffv2qVSYINX99zlX7NixU1+O/NpQPmBAf/384w+VChMkqWXLczRpwjg1aFC/TPn6DRucnruoqp1//vkaN3a0aZggSYGBgfr8s08Mk9Pa7XZN/qNyrxNJuv766/TtqK9dumkuHR8Wc/y4X48PoXWSBQsXabcT83h8+NFHhjDBmWt5vXr19MH77+mqK92fmF6q/eOSlJRkCBOaNW2ql158wekwQTr+un/rzTdqLEww06xZM/3884+mYYIknduqlcb88pPhnJWkN956q1LzDaSlpemHH38ylDdp0kSjf/nZNEyQpMjISP30w/dq26aNYdnUaX9r3br1pnWYGTCgvz795KNaDROKior07nvGG/3h4eEa/cvPpmGCdLxXz88//6izzjqrOprolLOaNdPUv/7Utddc43SYIEmNo6P1808/qEOHssNaHTlyRNOmlR9gumrSb7/rqWeeNYQJ3t7e+vSTjwgTAAA1ikDhDHGgnPFQG4ZXzdAWFQkvZ1zz9HT3Ju2sDVVxw+3ZZ55WZGREmbIZM2YqP9/9cbuffupJdezYwaltHh3xsKHswIEDhmEraoO7x9vLy0tvvvG6YeKxKVOnVmr7U59oCwgIqNRTpKeDG2+8oVI3Wk7w9PTUO2+/5fDG27jxE0y3t1ptDtd77NFHKv2E4MluGzpUvXqWHVf30KFD+nv6P07XdbKaPi7uGufgJntYWJjefutNp24c9e3bR9dfN7hK2sR5657PPv/CMNyJh4eHPvnoQ7Vu7dwwMK6o6+9zrvj+hx8N49Ofe24rffj++07/vo0bN9Zbb7xhKP/p51/caaJbggID9cVnn1QqQDyhUaNGGnKLcUip1WvWVLqOqnitnH3WWYbeWCUlJZpWwRwoJzt06JDmzJ1nKHf2Wu7l5aV333nL4Y1nZ9X2cTlwwPiZ/7LLujs1D01d9u47bzk1Z1JsbKyee+YZQ3lq6n4tWrTYdPsx5UzA/N67byvKiaGDgoOD9cnHH8nHx8ewzFGI7IzIyAi99cbrLgVGVWnOnLkO52l76YXnnRoWrmF4uN575+2qbJpLquJcrlevnt5+801D+V+V/ExTWb+OG6cXX3rZEJL5+flp1MivNKC/8QEyAACqE4HCGaK8CRNDQoIdllelkOAQh+VHsrKqfd91Ub169Qwf6goKCrR161a36o2IaKTbXJjIsEWLFmrj4CZVXRkz110RERGGuTpSU/fr0KHyJ9U7wWqzlfk5MDCwSr5c1DZ/f3899cTjTm8XEhKiRxwEUAsWLHR4A+NkEydNktVqLVPWNCbGrSHXRowwTir32++/u1xfbRwXd6QdOKBFi403Qx595GHDk8eV8fTTTzl1Q7I6/VfP2/379zucVPbmm27SpZdeUgstck11vc+5IiMjQ3//bbwJ+8Jzz7k83ETfvn107rmtypQlJCRqzx7HvUGr280331Spp7VPNXDAAEPZli1bq3xCbzODr73GcLN77Trj0DCO/D75DxWeMlybq9fy+vXra8TDxmt5bXH1uJz6XiupTkyKXhWuvPIKlwLi66+/zmHvgAkTJ1a4XX5+vn6fbOy10+eqq3TJxRc73Y6WLc/R0FuHGMpnzZ6tgweNN+Ir656773bpfb+qTZz0m6GsQ4c4DRp0tdN1de58kfpc5VyPvLqqbds2ate2bI/9TZs2OwyqXDFj5ky99vqbhmt3YGCAfvzhuzo7sTUA4MxGoHCGyMvLd1h+anfq6lDeRGP5eXnVvu+6Ki4uzlC2fv16t+q8bvBgl7rjHm9Pe0NZymk4JFV5Tu1qLEnr1m8w3e7U8+Pw4cNKdTDJ3Onmit69Kz3Ex6muGXS14XVWXFyspUuNw8yczFHPgVtvHeLya1aSOsTF6ZwWZbvPb9y4yeWnoGvjuLhjyZKlhifRfH19dc2gQS7V1zA8XL3r0JfO/+J5O2t2vOFv6uHhoXvurvyQYHVFdbzPuWLW7HjD/CDntGihbt0udateR+fZqeNk15Rbbr7Jpe1atWppuG7ZbLZKBXdVqX79+mraNKZM2caNmyoVbDgK4Ny5ll97zSC33peqkqvHJdjBjeV1tXDuVYebbrjBpe08PDx0vYOh65YsXVbhUIkbNmx0OCmwo949leVoMt6ioiItX7HCpfp8fXw0+NprXG5PVcnLy9PKhARD+Y0u/s2k4z2NzhSnvifm5OQoKWm72/Xu3rNHzz3/guG6EBQYqJ9/+lEXd+3q9j4AAHAFgcIZoqScJyBq4ktTefuoaALQM52jYaD27NvnVp2dO1/k8raOxil19ITb6So83Hhjobx5RU7WsuU5ZX622+168aVXlJ/vOKA7XfTv19flbUNCQtTdwY24dRvKv9Frtdq0bds2Q3nfPsa5B5x14YUXlvm5oKBAmzZvcqmumj4u7nJ0c7Z7t0vdCorr0vi6/8XzdomDAKpz54vUvHnzWmiNe6rjfc4ViYmrDGV9Hcx74qyLLrrQULZm7Vq363VWw4YNFRsb69K23t7eiolpYiivjff/U18vx44dc3gj92SFhYXassXY68Wda3loaKguvaTu9AZy5bi0OuUaKB3vQeNOD766ICgoSN27d3N5+4EO5gwrKCjQv/8aP5+c4KhHSFhYmFs9xlq0aKH27Y0T1DuasLkyWrdprQYNGrjcnqqyefNmw9j9khzOM1VZ3btdWid6XlQFVz/TmPnoo4+VnZ1TpszHx0fffPO1Ol1wgdv1AwDgqjNjsE2UO4yFzWZzaeJFZ9hOGX7ihICA2ps0rKoUFRVp5coErd+wQUnbtys5OVkWi1XZ2dnKzs52qiur1WJxqy0tW7Z0edugoEBDWV0MFPLz87Vk6VJt3rxFSUnblbJ7t6wWi2zZ2crJyanU5HonWCpxvHv26KGEhMQyZUuXLVPf/gP1wP33akD//goMNB67ui7OwZPfzmjfvr3mzS87AemGCm6cr16zxnAuNGhQX82aNXWrHZIMT29KUtK2JF3YqZPTddX0cXHX+g0bDWWOngp3hqNeAe7ivK28zZuNQ811vsj1sLgq1KX3OVc46jXQsYNzcw050jTG8bWnpp0aoDnL0VA4Vqvjz22VkXbggBYvXqKkpO1K2p6k9PQM2Ww2ZWdnK8/JnqkWi7XCG6XbkpIc1unutbxDhzgtWLjQrTpOVZPHpUmTJmrZsqV27NhRpvz5F17SggWLdNfwYbrwwk6nzVBwJ7Rt08bh/AOV1bBhQ0VHRxvm2Vm/YUO584856tnRIS7O7bkKzj/vPG3evKXsvlycmDmuvbGXcW1w9JmkWdOmboUd3t7eatOmteE9vTZZrTYtXrJYW7f+q6Sk7dq7d69s2TbZbDbl5OQ6NWScxeree2JeXp7mL1hoKH/owQfomQAAqHUECmeIeuXcvLdYrNUeKFgsjm9Mn87juR48eFBff/Ot/vlnho4cOVIldR475t6HyvqhoS5v6+9vfH3U1uSZjqTs3q1Ro77V7Pj4cgMqZ1XmxuSQW27Wd999b5jvY+/evXr+hZf02utv6uKuXXXJJRfrogs7qY2bX3ZrQmhoqBpHR7tVh6OJYVNTy5/Ee/t2Y5fuhg0bufzl+WSO/o5ZJk9vOlIbx8Vd+/cbh/Fp08a9SXubNGmikJCQSp0fZjhvnXPs2DFlZR01lHfs2LHmG6O6+T7nrMOZmcrMzDSU5+Tmun39cfQkrivXHne5894vSfUcvv8735tnxsyZGjPmV61es6bK5mA4ZnE8/9cJ+x1cX6vrWu6q2jgukvTgA/fr8SeeNJTHz5mj+DlzFBUZqct7XK4uF12kCy/spCZNjD1V6pqq+Lu0ad3aEChU9JS4o9dY27bGuRicdep4+pK0Py3Npbqi3Xy9V5XU/cZjVVV/s7oQKGzavFnffvud5i9YWGU9Ht19T1y1arWhLR4eHrrzjtvdqhcAgKpAoHCGaNSwocNyd5+MqAyrrZxAIfD0DBRGjxmrTz75VLbs7CqtNyc3x3ylCgQEBFRRS46r6UkZHSkpKdGnn32uH374scqHyMrJyTVdJygoSJ999qnuvud/hkkfpeM3XRYuWlQ6hrO/v7/i2rdXly6d1bVrF1104YWGCRVrm6Mu11VRh81mU3Fxsby8vAzLHA3PsGPHDt1wk+tjEFekvEnoK1Ibx8UdRUVFhi7ukhQeZhxmxllhYWFuBQqct65Jz8hwWB4dFVnDLam773POOuogoJGkRx9zfsLeynDl2uOuevWq9r1fkuyq/Pv/vn379OzzL1TLDb9ck/P9mIPrVHVdy51Vm8dFkgZdPVDLli3T5D/+dLg8PSNDkyb9pkn/fxLdRo0a6aILO6lLl8669NJL1fzss6uyyVUiIqKR23U0bGT8PlTeg0+S49dYZGSE2+2IcFCH1WpVSUmJ070fypurrqZZHFz/quZ8dP9zjTvy8vL01tvvaNJvvzvVo7IycnPNz+WKHEg/YChrGhNzxgwTBQA4vdWtO2FwWePGjR2Wp6TsVvt2xnE8q9KuXSkOyx0NVVLXvf/Bh/ru+x+qp/Lav39fpxQVFempp5/V39OnV0v9lQ1MLr3kYo0d/YseffxxZWQcrHDdvLw8rVq9WqtWr9ZXI79WWFiYBgzor2F33qGzHcxTURuqomdQeWP0WywWh13bzcZ7rmquDNdVG8fFHeXd8K+a38P1OjhvXZfjICCSpBA3n0B31pn0Pnf0aJb5SlWoLg4VWJ1SUlJ02+13lhuGucss2HB0HazOa3ll1fZxOeHdd95WZGSkvvn2O9OhyQ4dOqQZM2dpxsxZkqT27dvp+uuu00033iB/f3+321wVquRv66AOSwU9PhzdJK+u11hJSYlsNpvTN4Md9TKuDY6CmbpwProjJydH/7vvfq1caZxsuiq4+/CWo16NtR3AAABwAoHCGaLlOY7H2N20ebOuHjigWvftaExoSWrlxpj/tWH8hInl3mTx9vbWueeeq/PP66gmTZooKipKwcHB8vPzlZ+fnzw9yj5ttGXrFr362hs10ezT1qeffV7uTUlfX1+1b99OHeLi1LhxY0VFRSowMFB+fn7y8/OTh8qOC7xg4UKN/HqUy2256KILNW9OvEaPGatx4ycorZLd0o8cOaKxY3/V+PETdOMNN+iF55+t9bHbq2Jol3InWi9wPExWTd9kKy52/gmy2jgu7igocPzkv49v9f0elcF56zpHQ+hIkn85cyBVhzPtfc6duQBcUdVPr9ZleXl5Gn7XPeXeNA8PD9f555+nc1u1UlRUlCIiGsnP9/i57uh6++prr2vLVuMEyxVxdG2tzmt5ZdSF43KCp6ennnj8MV0z6Gp9NfJrzY6fU+mhWjZv3qLNm7fo61Hf6Plnn9E11wxyqQ1Vyc/P9b/L/9VhvJ7m5pY/h0Weg+Pl7+d+wFJeHTk5uaft0+V18Xx01/MvvFRumBAQEKAOHeLUvl07RUdHKyoyUvUC6h3/TONrfJ399vvv+u33yVXaPkfzr9SFIRwBAJAIFM4Y7cuZsGvTxk3Vvu9Nm8oJFFqdPoHCkSNH9NHHnxjK/fz89MD99+nWIUOc6tabk1Ozwz6cbpKTk/XjTz8bykNCQvToIyN0/XXXOfUU9fZTJiZ0Rb169XT/fffqvnv/p4TERC1ZslQJCYnavGWLw2FVTlZcXKyJkyYpITFB438dq4gI97vLuyq7CoYwKW88/PK+BHtW8XA/1aE2jos7ynv9Z9uq7/cww3nrnvJumths2QoLc3/YCDNn4vucp5d7E6eifKO++Vb7Uo3zuFxwwfl6dMQIdet2qVP1+ddz/iatoyeXq/NaXhl14bicqkWLFvr0k49ltVo1d948rViRoMTERIftPNWhQ4f0xFNPa/2GjXr1lZfcbos7HA3z53wdxtdHRU/ABwUFGXpZVsVQcOW9TuvK8EWuqIvnozuWr1ih6f/8YyiPiorS4489qqsHDnQq5Jq/YEFVNq9cp9tk6wCAMxeBwhmiXbu2Cg4ONjwpvGHjRh07dkyh1TSkgsVi0YaNGw3lAQEBiouLq5Z9VqSoyLXxvKdMnWYYG9nPz08Txv2qjh07OF1fZSbU+y8bN36C4WZfWFiYJv82SWed1czp+qpyXGsPDw917dJFXbt0kXT86aANGzYqcdUqrV69RomrVpX7RHpKym7977779efk36t8TP3Kqoondh31OPDx8VG9eo673Tvq8j548LX66IP33W5LVamN4+KOwMBAeXt7G55qL2/OGme4eiw4b90TEuo4eKqJuY6kM/N9ztG1x8vLS1s2beApTjcUFxfr13HjDeUDBvTXJx996NIcJBYXJicNCTHewKyua3ll1JXjUp7g4GANvvZaDb72WklSRkaGVq9Zo1WrVmtlQqJ2VBDijhk7Vs2aNdXwYXdWWXucVRU3lm0OQndHr6P/WxZiDBSqoB3lfV6o7V6s7qhr56O7Ro8eYyhrERurCePHuTQ3hDtzUwEAcDri0a4zhLe3t7o7eCoqPz9fU6f9XW37nTrtb4fdq7t36+aw2/HJvB3cuCkqdjwkRGVluTiW+9x58wxlDz34gEs3WSQp60jNjut8upk/3/gUz0svPO/STUlJysqqvuPt7++vLl06a8TDD2n0Lz9pzaoEffXF57r0kkscrr958xb9NWVqtbXHTHp6usMu0s5ISdltKGvQoH6560dHRRnK9u7d61YbqlptHBd31a9vrHv37j1u1Zmbm6sMF8f95rx1T3RUlMMnCx29rqrDmfg+Fx0dbSgrLi7W/koOfwXHVq9eY7jJWr9+fb395psuT2h+xIXz3dHcNNV1La+MunJcKisyMlID+vfXa6++olkzpmvRgnl66sknHJ43kvTFl1/V6k3RffvMe1SYSXXQK6Oih6pCHQS9VfH5Zc8e43v16TrU0QmOzsfde3a7XW9NvQeeLC8vT8uWrzCUv/POWy5PNF2d5zIAAHURgcIZ5NprrnFY/nsVj+dYmbqvuuoK020DA41PFrrbdTY93bUbZY7mgbhu8GCX27GpnHklcPwm4qnd8AMDA9S3bx+X66zJ4x0QEKB+/fpqzOif9c2okQ4nM5wytfYCheLiYiUlbXerjn///ddQ1qZNm3LXdzSHy44dO8sdM7421MZxcVebNq0NZVtdHGv7hG3bkkwn73SE89Z9/v7+atq0qaF83bp11brfE87E97noqCiHvRS2/butFlpz5nD0t73qyitcHq7lwIF0ZWZmOr1dWwfX16q4lrt6Ha0rx8VVMTExeuD++zQ3fpZuuvEGw3KLxaJ58+fXWHtO5eg91uk6thnP/VatWpW7/jkOPr9s3ep+O7Y4+F3OOaeF2/XWJkefd7ZtS3J7bpmt/7r3ucYVO3buVG5ubpmyZs2a6cJOnVyuc3M5QwC7497/3aNVCSvK/Pv2m6+rfD8AALiCQOEM0qPH5WrcuLGhfOu//2r6PzOqfH//zJjhcCK5hg0bql/fvqbbO/oCdvDgIZfbY7FYtHPnTqe3y83NNYzbGhQYqOho41PXlbVq9RqXt61rqnqszsOHjV+eY2JiTHu0lKegoEAbNhiH3aoJV15xhR59ZIShfM2atbLb7bXQouOWLV/u1vbLV6w0lJ3XsWO565933nmGMovFolWrV7vVjqpW08fFXY7qXr7C+ESdM1w9Bpy3VeP884x/02XL3HtdVsaZ+j7n4eHh8DyZW4s3Rc8Ehw8fNpQ5uvFaWatWrXJpu0aNGjn8XFsd1/LKqCvHxV3+/v5668031Lr1uYZltXle79i5062h8JKSkhz2sDivgl5YF5x/vqFs85Ytbj3gZLfblZho/NtecMEFLtdZFzg6jjk5OVq3fr3LdaYdOFArPRQcfaZp6Ubgk5GRob379rnTJIfq1aunsLCwMv8qmhMEAICaRKBwBvHy8tKDD9zvcNmbb71dpeNVWywWvfnWOw6X3TV8WKVuMjVs2NAwXvWRI0d06JBrocLcefNduhnk6MtHQGCAS22QpMTEVdq9e7fL29c1jiYSdXWuCsnxeOEBAa6PKTv9nxm1Ojno1QMHGsoKCgqq9Hxz1tSp01zedv36DQ5fv50q+CIcFRWpdm3bGsr//HOKy+2oDjV9XNzlqO6UlN1u3YifOs21Y8B5WzV69OhhKNuZnKwVK127wVlZZ/L7XM+ePQxlc+fOYzxrN1gcjGkeEOD662XS77+7vK2j66A71/K169Y5HI6mMurScXGXl5eXw4d/Drv4GbwqFBYW6p8ZM13e3tEQr6GhoWrevHm523TqZHx95ebmatbseJfbkZCYqP379xv35SC8OJ00bdpUkZERhnJ3zsepU6fVygM4VkfviW58pvntt9o7lwEAqC0ECmeYG2+4Xi1btjSUHz58WC+98mqVfWh79bXXHd74b9SokYbeOqRSdfj7+ys2NtZQvmjxEqfbY7fb9eNPPzm9nSSHT3pkZR0tdwJPM99+971L29VVQQ4mkMs5pZuwMxwdb1fHdC8qKnL5715VwsIcj7VaXOxeF3B37ExOdjheemV88913hrKoqCh17dqlwu0GD77WUDZl6lQlbXdvaIqqVBvHxR2XXHKxoiIjjW351tiWypg9O167dqW4tC3nbdW4oncvh0P0fPnVyGq9qXImv88NHDjAEHxbrVaN+ubbWmrR6S/YwWvU1fN948aNWrkyweW2XHvtIEOZW9dyN14Xdem4VAVH18Ha/OwiSb+OG+fSsHw2m01//PmXoXzggP4V9rRt1bKlzmlhfDJ99OgxLg/l8+OPPxvK6tevr4sv7upSfXXJNYOM5+OUqVNdOg+ys7M19tdfq6JZTqvKzzQ2m03jJkx0t0kAAJx2CBTOMN7e3nr/3XcMT/5L0owZM/XmW2+7fdPinffe17S/pztc9u7bbzm8WVKejh3iDGUTJ05yuk3ffve9tm1Lcno76fjTZae2ubCw0KVhKCZP/kMLFy1yqR11VYiDCev2pxqfvKqsiEaNDGVpaWnavmOH03V9NfJrl//uVcXR5H2+Pj4KCzNOXleT3n77XaefAF+wcJHmzJlrKL/lphsdXlNOdsP11xsmES4pKdGTTz4tm83mVDuqU00fF3d4eXnpRgfjXMfPmaMFC527zthsNr397nsut4XztmoEBATolptvMpQnJCTqp59/qdb9nqnvcw3Dw3XttcY5pH7+ZbTDSTdhLtJBkOnK3zwvL09PPf2sW225rHt3xcQ0MZS7ci2fO2+e5jmYXL6y6tJxqQqOroORUcbfsSYlJW3XhInO35z98quRDoekGnLLLRVu5+HhodtvH2oo37J1q8aNn+B0O+bOm6f5C4yvsVtuvsnh3D2nmyG33GIIaLKzc/TWO+86Xddnn3+hjIyDVdU0p0REGHtarF+/3qVeiq+98abLvevNPP3Mc2rR8twy/y7r0ata9gUAgLMIFM5AHTt20HPPPuNw2egxY/XQw4+49IHJarXp0cee0I8/On6y9Oabb3I49EBF+jrobr1u/XqNd+JJj2l/T9enn33u1H5P1aXzRYayTz//wqmnN5csWarX3njTrXbURY4m3N2ZnCyrg67/lVG/fn2de65xgryPPvrYqbDrjz//0tejvnGpDZKUkpKiDz78yOUnkk74efRoQ1n7uPZVPveEs/bu26cHHny40q/hLVu26rHHnzCUBwcHa8iQir+QH18vSI8/9oih/N9t23TfAw8qKyurUu2oSEJCotvjzdf0cXHXrUNucdhL6PEnntSWLZWbyDA/P1/33v+AwyEYKovzturcf9+9hvBNkt7/4EP95sYQKGbH5Ex+n3v80UccBiYPPTxCKxPcfwo8IyND48aNd7ue00VnB6+VTZs2a+bMWZWuIz8/XyMeeUzJu3a51RZPT0/dc/fdhnJnr+UbN23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      "text/plain": [
       "<Figure size 800x450 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 428,
       "width": 778
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig1 = plot_bar(\n",
    "    q1_x,\n",
    "    q1_y_per,\n",
    "    t1,\n",
    "    ylim=(0, 0.25),\n",
    "    space=1/3,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "57eda195-837c-46ff-ad72-d7ed000876f9",
   "metadata": {},
   "source": [
    "#### 4.2.3. Tabs or spaces"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "d18161f0-92ac-462d-a94b-b45d6735defb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 400x450 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 427,
       "width": 494
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig2 = plot_slope(\n",
    "    q2_x,\n",
    "    q2_y_per,\n",
    "    q2_l,\n",
    "    t2,\n",
    "    ylim=(0, 0.5),\n",
    "    figsize=(4, 4.5),\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1707f5e3-c66c-47f4-ad2a-4dc1ddeb6eb2",
   "metadata": {},
   "source": [
    "#### 4.2.4. Desire to go to Mars"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "ff5ba6e2-55a3-4088-9f05-42174bb152f9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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FwMAguHu4I8A/ADExMUiXSGBjYwNbWxsUK1o0V7T9UlNT4evnh8+fPiMkNBSxsbFISkqChYUFrK2sYGtriwoVyue6Z3x1UFXbIaP4+Hi8ev0aXl5fEB0VhXSJBFZWVihduhTKu5aHkZGhXPnFxMTgzdu38PL6gpjoaOjq6aFAgfz/3zapoJZ6HdDOdkhkZCTevX+PAP8ARERGIikpCUZGRjA3N4eDgwNKligOJycnlZ2T2NhYfPbywpcv3oiOjkJsbBx0AFhZW8PK0hLOLs4oV7Ys9PT0VHK87OSWvmGxsRhTU1MNlISIiIiIiIhIPrm3ZzODr18DceHiRUG6qakp/pw9S+XHmz17Jm7cvIG4uHip9BPHT2DSxInZDrY8dHNDn779pdJq1ayJ/fv2KFymP6ZMw/ETJ6TSFi9aiK5dOsuVz9u373D7zh24uT3C02fPEB8fn+0+xYoVRcMGDTBo4AA4OTnJdbyMipcsLUj79EF6KY/bd+5g+46dePDgoWjHDPBtSaB6dX/B2LFjUN7VVaZj+/n5oWHjplluc/zECcF5zkzGcmclLS0N585fwLFjx+H26FGWb+3r6emhSpXK6NSxIzp17Ch3B6wq/D5pMk6dPiOV1rx5M2xcv04l+S9YtBjbtm2XSqtSuTKOHjkkVz5PnjzBgYOHcPXadcTGxma5bfFixdCuXVv06d1bLQOmHp6eOHLkKK5evQZfP79st7e3t8Mvv/yCpo0bo2nTJjA0VOzvLJFIcPPWbRw/fhy3bt8W1Fs/09fXR5XKldGmTWv07NFd4WOqm6bOpY+PL/bu24fzFy7i69evWW5ra2uLVi1boE+f3jIvhy5Glro9ICAAW7dtx5kzZxEeEZFpXqVLl8KA/v3RtUtnlXbySyQS3L17DydPncLNW7cRGRmZ7T4lS5RA3bq/oFXLlqhRo7rCx9bEPd6gURP4+/tLpd26cQ3Ozs4//n3z1i3s3bsf9x88QFJSkmg+zZo2yXZg7u7de9i2Ywfu3buPtLQ00W2MjY3RpHEjDBs6BBUrVpTvy8gg4OtX3Lh+Aw8fPcKjR48RKsNsEQUKFEDtWrUwoH8/VKlSWeVlUhVN3NOytHPkcfTYcUydNl0qrXOnTli6ZJHCeapCYGAQtmzdipOnTmdZJ7iWK4c+fXqjc6eOCg9UZ6SqNrGfnx+OHjuO02fOwtvbW6Z9rKysULFiBdSuVQstW7ZA0SJF5Drmz1i3sm7NKDfUrampqTh2/AT27t2Hd+/fZ7qdjY0Nfu3QHoMHD4JjwYIqL4emn2lVTdP1UWpqKi5cvIRTp05nef8BgKGhIWrVqolfO7THrx06qCwwViKR4MLFi9i9ey+ePH0KiUQiup2JiQkaN/7/e7dChR/pyvxerlq9BqvXrJVKGzd2DMaPGyv39/hOljpPHeUR6/NwcnLC7ZvXf/xbIpHg/IUL2LV7D549e57puTY3N0fTJo0xbtxYmQOpxPrCMlq9Zq3g+4nJWG5Z+Pj44sDBg7h48RJ8fH2z3NbF2RmNGzfGkMEDZfq75ASJRIKnz57h7t17cHN7hBcvXyI5OTnLfXR1dVGqVEk0a9oU/fv1k/u3WqztmpG/v3+224ld38r2jaqr7dC7Tz+4PXoktc2+vbtRu1atH/9+/PgJtm7bhtt37mb6N7C0tESXzp0wZvQo0Vn4fnb/wQNs27YD9+7fz7Q/sECBAujatQtGjRiudECatrZD/Pz8cOjwEVy5chUfPn7Mdntra2v8Uqc2GjZsiNatWsLMzEzmY8XExOLmrVt4+NANbo/c4OX1Jdt9zMxMUaVyFXTr1hWtW7VUefBkbusb9vLyEn1WKOTikuNlISIiIiIiIpJXngmYPHrsmOhgV5vWrZA/f36VHy+/rS3atG6NI0ePSaUnp6TgxMmTGDpksMqPqW7rN2zE0WPHZR6A+dnnz174/NkLe/buQ+dOHTF71ky1vE0aFhaOadNn4PqNG9lum5iYiKvXruPa9Rvo27cP5syamWOzmMjr3v0HmPPnX/jy5YtM26elpeHJk6d48uQp1qxZi9mzZqJVq5bqLWQGXTp3FgRM3rx5C+Hh4bCxUS7YMC0tDacz5A0AnTt3kjkPb28fzPnzL9y9d0/mfT59/oxVq9dg0+YtGDVyBH4bNlQlwRteX75g0aLFuHpNvsGcoKBgnDhxEidOnES+fNZYs3oV6tSuLVcejx8/wdy/5+G9u7tM26empuLxkyd4/OQJduzYiWlTp6BlyxZyHVOdNHUuY2NjsWz5CuzffyDTwIqMwsLCsG//Aew/cBC/dmiPGdOnqyUQd/uOnVi+YiUSEhKy3dbDwxMzZs7Czl27sXnjeriooBP73r37+GfhQnh4eMq134ePH/Hh40fs3LUbRYsWweGDB+SqO7TpHv/Z16+BmDJtGu7ff6BUPhEREZgxczYuX7mS7baJiYk4f+EiLly8hF49e2DWzJkqGSy5dPkKtmzdhhcvXmQ6UJ6ZkJAQnDl7FmfOnkWtmjWxcME/KFy4kNJlUhVtvqfzgt179mLJ0mUy1Utv373DjJmzsHvPHqxY/i9KlSyZAyXMWlJSMtauW4et27ZnG4SQUVRUFO7cuYs7d+5i6bJ/sXLFcrRv11buMrBulca69Rttr1vd3d0xcdIf8PTM/roNDw/Hjp27cOjwEUyfOgW9e/dSSRlywzOtPLShPrpy9Sr++WehTC8pAd9moPx+3G3bdmD2rJmoVaum3Mf9mY+PLyZPmYKnT59lu21CQgLOn7+ACxcuonevnpg5Y4ZGgkhyK29vH0yeMgXPnj3PdtvY2FicOn0G5y9cxLixYzBq5IgcKKFiwsPDsWTpMhw/cVLmtp+vnx9279mDg4cOoX+/vhg/bqzG6gSJRIL5/yzAxYuXEBgUJNe+6enpcHf3gLu7B7Zu244B/fvh94kTcvXsoLJQVdsho/j4eMz5ay5OnDiZ7bbR0dHYsXMXTp06jbVrVovWhREREZg2YyauXr2WbX4hISHYsGEjTp48hc0bN6BcubJyl19b2yHBwcFYumw5Tp0+LfM9CnybhfL8hYs4f+Ei/p43D/P//hsdOrTPch8PDw8sX7kKt2/fkfu3NS4uHnfv3cPde/ewvHBh/DlnFho2aCBXHpnJjX3DO3ftFqTp6emhcWPVrfRFREREREREpC7aGT2mgMuXxQe9unfvprZjduvWVTT94qXLajumOu3bt1+hgaWfpaam4vCRo+jSrQd8fLJ+W19eX7y90alLV5mCJX8mkUiwZ89ejBs/Aenp6SotkyqsXrMWAwYOkrlDLKPAoCCMHjsOf839W65ORWXVqVMbjo6OUmkpKSk4feas0nnfunUbISEhUmlGRkYyD/Bdv34DHTp2kmuw/2eJiYlYvmIl+vUfiPDwcIXy+O7wkSNo1/5XuQP8MoqIiIS/f4DM20skEixfsRK9+vSVOVgyIx9fX4waMxarVq9RaH9V09S59PryBZ26dMWePXsVusckEglOnjqNDh074fWbN3Lvn5n09HRM+mMK/lmwUKagpJ95enqie89e+PTpk8LHT0lJwV9/z0P/gYPkDujJyMvri0wzP32nTff4z9zd3fFrp85KD8r5+Piic9fuMgX0/EwikWD/gYMYOGiw3NeEmEuXLuH588xnFZKV26NH6NSlK+7cuat0mVRBW+/pvCA9PR3TZ8zE3L/nyX0Nurt7oHuPXnj6LPtgGHWKj4/H0N9+w/oNG+UeQBWT1SxsYli3CrFuFadtdevNW7fQtXtPmYIlfxYfH4/Zf/6FhYsWq6Qc2v5MKw9N10dJScmYPmMmRowcLXOwZEbv3d3Rb8BAHD5yRKH9AeD58xfo3LWrTMGSP5NIJNi3/4DK7t3/gm/nuptMwZI/S0lJwb/LV+CfBQvVVDLlPHnyBG3adcCRo+IvWmcnOTkZW7dtR59+/REWprrfN3mkpaVh567dcgdLZpSYmIhNm7eg/4BBGvsuOUFVbYeMoqKi0KtPX5mCJX8WHhGBgYMGw81NetZKf39/dO7STaZgyZ99/foV/QYMxPv38vf1aGM75MaNm2jTrj2OnzihVL9mXFw8vGToW33x8hWuXr2m9G+rt7c3hg4bjo2bNiuVD5A7+4bv3buP/QcOCtIbN26EggUdcqQMRERERERERMrIE68Th4SEiAYEOTs7oVrVqmo7brWqVeHi7CwYPHj16hWioqJgZWWltmPnJF1dXTg6FoSlhSUsLCwAHSA2JhZ+/v6IiooS3cfT0xMDBw/B6ZPHYW5urnQZgoOD0a//QAQESAc5mZiYwNnZGTY2+ZCclIyArwEICgoWzePCxUvYsXMXhgwepHR5VGXR4iXYsnVbpp+bmZnC0dEJNjb5EBUVBX//AMTExIhuu2fvPkRHR+PfZUuho6OjriL/oKuri04df8W69Ruk0o8fP4GBA7JeYis7x44Llzxv0bz5t+svG1evXcPoMeMyXardwMAAjo6OsLezQ2JSIgIDAxEcHCK67eMnT9C3/wDs37sn2+WTxIgtlZZRvnzWKFDA7ts1nJyM6Kho+Pn7IzExUe7jfZeeno4p06Zn2YlvZGSEQi4usLa2hgQShISEwsfHR7TTfPWatYiOjsbsWTMVLpOyNHUuvb190LtP30yvEQA/ric9fT0EBQbBPyBANDg7MDAQ/foPxO5dO6SWB1TUrDl/4uTJU1JpOjo6cHF2hq2tLQyNDBEeFo7PXl6iHebBwSGY+PtkHD92RO7ZRRITEzFy9Bjcvn0ny+0cHBxga2sLS0sLxMfFIyIyEv7+/kp14GvTPf6zwKAgjBk7HmFhYYLyODs7wdbWFmlp6QgKCkJQUFCm5yA0LAz9BwzMMjDh52suOCgYvn5+Uvfuo8ePMWnyFDRpor5ZHQoUKAAbm3wwNzeHkZERYmNjERwcgsDAQNHto6Ki8NuIkTh25LBCM6Goijbf03nB3L/n4fCRo5l+bmlpCSdHR1hZWyEsLBz+/v5SAX0xMTEYPmIkThzLPA91mzZjZpaD69bW1nB2doKZqRl09XQRGxuL6OgY+Pv7Z1ovyYp1qxDr1txRtz558gSjRo/NNCDPwMAATk5OsLezQ3xCPAIDgwQvR23dtl3wMpYqacMzrbw0XR8NHzEqywBqczMzODk7wdraGsnJKQgJCYafn79gu7S0NEyfMQtxsXEYNGigXOX48OEjBg8dhujoaNHPdXR04OzkhPwFCkBPTxchIaHw9fWV+t1+9Pgxfp/0B5o2bSLXsf9rPD98ED3XFhYWcHJyhLW1NeLj4+Hn559pUPz2HTtRvVo1rVqh4MaNmxg1ZmyWgVHOzk6wtbGFqZkpIiIi4Ovri7g44QsHr169Ro9evXDwwH7kt7VVZ7Hloq+vD0dHR1hYWMDCwhzpaemIiYmBr68vYuPiRPdxe/QII0ePxv69e/LcTJOqajtklJqSit9GjMSbN2+l0k1MTODi4gIbm3xIiE+Aj68PIiIiBfsnp6Rg9NixuHzxAmxsbBAZGYm+/QYIloY3NzeHk5Mj8uXLh9jYWHh7+4j2A0ZGRmLipMk4c+qEymb21kQ75PCRI5g5a06WL7hbWFjAwd4eNjY2SEtPQ1RUNL4GBGR6fSvDwsIC9nZ2sLCwgKmpKeITEn7UC2LXSnp6OpYu+xcW5ubo06e3QsfMjX3DL168xKgxYwV/N1NTU0yfNlVtxyUiIiIiIiJSpTzRK/bi5UvRIJ/KlSqr/diVKlUSDLylpaXh5atXaFC/vtqPrw4GBgaoUaM6mjZpgqpVKqNkyZIwMTER3dbHxxcXLlzAvgMH4e8vPTji7e2NmbPmYNXK5UqXacLESVLBkk2bNMbAgQNQvVo1GBpKL6/l+eEDNmzYKDrT4fIVK9G6dSs4FiwoepwCBexw9PChH/++cfOmICCwUcOGGDN6lDJfBwBw6dLlTDvEqlSujOHDh6FB/QZSy4elpaXhwYOH2L5zJ27dui3Y79TpM6hYsaLSAYuy6tK5s+D8vH33Du7u7ihTpoxCeUZGRuL6deEMgl1kWI7bz88PkyZPER0gdLC3x5gxo9G6VUvB4P379+44dOSI6NKs35Ywno316+SbZXHX7j2ZBvjZ2Nhg0MABaNqkMUqXLi34PDU1FR8/fsSDBw9x7vyFTOu4zKxdt140WFJPTw+tW7VC7149UblyZcHSdKGhoTh3/gLWrd8gGFzYuWs3qlWrijatW8tcDlXR1LlMSUnBuAkTRANCjIyMMGzoEHTu1EmwBFVQUBBOnzmL9Rs2CgYcY2JiMHbceJw9fRoWFooPvB8/fgJuj/43O4WLszNGjhyBpk2bCAbvoqKicPz4CaxZt14QEPD23Tvs2LkLw4YOkfnYEokEkyZPyTSgp1SpUhg0sD8a1G8ABwd7wefx8fF49/49bt68hfMXLso1C5Q23eMZzZr9p1TwR8WKFTDit99Qt+4vgiCLmJgYnDt/QXRga+bMWaIBPYaGhhg6ZDC6dukiuOa+fg3EqdOnsWHDxh+DRpcuX0ZkZKRS3+ln5cqWRZMmjVGnTm2ULlUK+fLlE90uIiIC12/cxIEDB/H8xQupz5KTkzFm3HicOXUCZmZmKiubrLT5ns4LLl2+gr379ot+Vr9ePQwbOgS1a9eCnp7ej/SkpCTcvHUb69atx9t37wB8mwV46rQZOVLmjO7du49z584L0h0cHDB08CC0aNEcTk5OovsmJyfj06fPePT4MW7cuAk3Nzckp6TIfGzWreJYt36jzXVrTEwsxk+cJBosaWdXAGPHjEGb1q0E18/bt++w/8BBHDp8+EfbbNHiJShXVjWBn9r4TCsPTdZHADDnz7miwZJGRkbo3KkjunXtClfXcoJAK39/f5w4eQpbtmwVBLIsXLwElSpXQtUqVWQqQ2pqKiZN/kM0WNLc3ByjRgxH+w7tBc/2YWHhuHjxIlavXYfQ0FAAwOUrVzINjKVvv8djxoz7ca51dXXx668d0KdXL1SsWEHqt1sikeDly1dYuXq16Mxys//8Cw0a1M/0fnMt5yrV53L4yBHByxbdu3VF927ZrxaTsS8oo48fP2HchImiwZKlS5fC4EGD0KhhA+TPn1/qs+TkZLi5PcL6DRvx6PFjqc+8vL5g2rQZ2LplU7blUxdjY2PU/aUOmjRpgkoVK6J48WKi50IikeDjx084c/YsDhw8JAh0ffr0GVasXIU/Jk/K8ng//70AIDgkBKNGj5FKK1CgADasy/oFxwIF7LL8XFVU1XbIaM26dXjy5OmPf9eqWRPDhw9D7Vq1pfpW0tPT8fjxEyxeshQvX72SyiMiIhIrVq7CvL/nYsLvk6SCJZs1a4ohgwahatUqUnVrSkoKbt++g4WLF8PL64tUfh8+fMD27TswfPhv2ZZfjKbbIZevXM00WNLMzBT9+vZFi+bNUaFCeejqSi+SJZFI8PnzZzx6/ATnL1yAm9sjhV4eKliwIJo0boQGDeqjbJkymf62JiQk4PGTJzhy9BguXLgo6Feav2AhqlatirJl5esLzY19w0+fPcPgIcMQGxsrla6jo4MF/8xHkcKF1XJcIiIiIiIiIlXTkSi7BocWyGzmsenTpmLokMFqPfbWbdtFlw/7Y/IkjMiiw+qhmxv69JXuuKhVsyb279ujcFn+mDINx09Iz8y3eNFCdO3SWab9u3brgWbNmqJnj+5yzwaTkJCARYuXiA6Unzp5HOVdXWXOq3hJYdDTd+ZmZli5cgUaN2qYbT67du/B3/PmC9LHjhmNCePHyVSWo8eOY+q06VJpnTt1wtIli2TaPzNBQUFo066D6IDrpN8nYsTw3wSdgRkdPnIEs2b/KegQNDIywonjR1G6VCmlyiirnr364PGTJ1JpQwYPwozp0xTKb8/effhr7t9SaQ4ODrhz60aW5yQtLQ29+vQVXaqtZYsWWLxoYbbBLC9evMRvI0YKggUBYME/89Gje/aDNgDw6vVrdOveUzTwoG+f3pg8aZJcgTWfP3/Gps1bUPeXX9ChQ/sst33w8CH6Dxgk6HAuXLgw1qxaCVfXctkeLyYmBiNHj8GDBw+l0i0tLXHh3FnRQA110eS5XLJ0GTZt3iJIL1G8ODZuXI+iRYpkuX9QUBDGjBsvuqTdrx3aY/m/y2Qqs1jd/rPevXpizuxZ2Q7yfP78GX37DxDMwuvs7ISb16/JPPvAjp27MP+fBYJ0QwMDzJ49Cz17dM+2/vrZvXv3sWHTJixeuCDTwQlAu+7xBo2aCAIqvtPR0cH0aVMxeNBAuWd0OHP2HCZM/F2Q7uLsjK1bNqNEieJZ7h8QEIDhI0bh3fv3mW4jz2/YrNlzoK+vjwED+md7vYs5dPgI/vxrLlIyBGnMmD5NI7M9a8s9LdbO+fTBQ6Z9xairrSKPqKgotGzdVjBjnI6ODub+OSfb2VZSU1Px7/IV2Lxla5bbyXqeFG0Tj5/wO86eOyeVVqVKFWzfuhmWlpYyHfu70LAwHDx4CK6urjK1W1m3sm6VlbbVrbNmz8GBg4cE6Q0bNsCKf5dlu+rCo0ePMXzkqExnEARy5zOtsjRZH504eRKT/xDODlWhQnmsWbUSLi4u2eYRGBiEocN+E6wE4uLsjPPnzsDU1DTbPNasXYeVq1YL0suXd8XmjRtgb5/1M0l0dDQm/D5JNJjkO1nvXbE+p3Fjx2D8uLHZ7psZsTrv1o1rcHZ2Vmt5/Pz80LBx00w/L1CgADZtWI9KlSpmm9eCRYuxbdt2QfrihQvQtWuXbPcH1HNugW+zpHbs3BUfPnyQSjcwMMAfkyfJXF/u3LUb/yxYKHi+nvvXHPTt00epMsojNTUVrdu2w4D+/dC5UyeZ7qGfRUZGYsbM2bh0+bJUuqGBAW7fuoECBQrInJfYNeTk5ITbN4UvvmZH2b5RdbUdevfpJ/WC4s/09PTw15zZ6N27V5Z5JCcnY/jIUYKXYYyMjDBxwngsWrwEwLcZKleu+BfNmmZ+XwLf6rQ+ffsL2iNOTk64dUP253ltaYcEBASgTbsOojMltmrZEnPn/inXTK5fvwZi2/btsLe3z/aF0KNHj+HK1asYOHAA6tSuLfMxvnv67BnGjhsv6Ftp2qQxNm/aKHM+ubFv+P6DBxg+YpTUKgHfaaotSkRERERERKQo2UfdtJiPj49ouiyBQcrK7BhfvnxR+7FV7cjhgxgx/DeFls4zMTHB3L/+RL++wg7jHTt3qaB032YP2L1rp0yDPAAwoH8/tG3bRpB+9NhxlZRHGStXrxHtEPt94gSMGjlCpgHx7t26YcE/woDQpKQk0SBedRGb+fHU6TMKLwN37Ljw79OpU8dsz8nZs+dEB/sbNmyAVSuXyxRUV7lyJezasV106e/FS5YiISEh2zwkEglmzf5T9PtPmTwJc//6U+5ZyIoVK4bFixZmG+CXkpKCP6ZMEwzmFCtWFMePHpa5TrSwsMCObVtRrVpVqfTo6Ghs2y4cEFMXTZ7LgIAAbBUZ/HNycsKunTtkGliwt7fH9q1bRGdKOnX6DJ4/fyFrsTM1aOAAzPt7rkwzYhQrVgwLF/wjSPfz88f9DMGxmQkODsa/y1cI0k1NTbFt2xb07tVTroAeAKhb9xfs3b0ry4AeQHvu8ez89edsDBk8SO5BudTUVCxcJBywt7W1xa6dO7IN6AG+LSe7Y8c2FFbRjA7z/p6Lv/6co9BAGgD06N4NK0SCCHfv2aPU0sGKyC33dG61YeMmQbAkAMyZPUumpen09fUxdcofGNC/nzqKJ7M7d6VnytLR0cG/S5fIHZwEAPltbTFm9CiZ2q2sW7PHuvV/tKlu9fzwAQcPHRakV69eDevXrsk2WBIAatasga1bNsHIyEglZdL2Z1pZaao+ioiIwJ9/zRWk16heHYcOHJApWBIAHBzscWD/XsF94+vnJ5hNUEx0dHSmLzns2rE922BJ4NvLXhvWrUXNGjVkKjN9W+b9yKEDMgVLAsD0qVNQRWTG0CPHjqm6aHJbs3adIFhST08P69asliugZ+CA/vhzzixB+tp1G7Jc5lvV9PX1cfniBfTt00fuYEng2992zeqVaJZhafrklJRMZwjP7RRtO2RnwT/zsw2WBL71YS5dvEgwq2VSUtKPYEk9PT1s3bIp22BJ4FudtnTJIqkZX4FvM/s+eCjb8zygPe2Qv+f/Ixos2a9vH6xZvVLuZe8LFnTArJkzZFo9o0uXzti0cYNCwZIAUK1qVezft1fQ9r1x8xa+yDHLe27rG75x4yaGDhvOYEkiIiIiIiLKM/JEwOTXwEDR9Py2+UXTVck2kw6cwMAgtR9b1VTRiTh1yh+wt5deZuf8+QtISlK+I/mPyZNk7rj/bvzYMYK0r1+/ZvoGek6IiIjA6dNnBOk1a9TA6FEj5cqra5fOaN+unSD97t17+PTpk8JllEebNq0FHfahoaFZzuSRmQ8fPuL16zeCdFmW4961WzgDgbW1NZYtWSxTMNl3ZcuWwdQpfwjSo6KicOLkqWz3v3TpMt6+fStI79jxV4WXSZLV6TNn8fXrV6k0Y2NjbN28We5BYwMDA6xcsVywlNrhI0cFy+6oiybP5e49e0U7+xct/EeuGTYtLCyw/N9lotfgzl27lSpj+fKuotdqVho2aIDKlSoJ0p8+fSqytdD6jZtEA1/mzJqJX+rUkass8tKWezwrjRo2VHimmStXrgpmqACAWTOmC5aJzUp+W1ssEgmMVYQq2gWtW7dC8+bNpNL8/PyllrPLCbnhns6tkpKScVQkMKJe3bro36+vXHlNmzoFxYoVVVXR5JKQkCBYrrVE8eJy3X+KYt2aNdatQtpSt+7ff0CwJKWRkRGWLl4MY2NjmfOpVrUqRqqobaftz7Sy0GR9tGfvPsTFSQdCFChQABs3rJNaDlQWFhYWWLniX8HfZNfuPaLLr/7s2PETgnpRR0cHCxbMl+u5xsjICIsXLZTrevwvW/DPfJmDYoFvf5OxY0YJ0l+9fJWjwYQZxcTEYt/+A4L0CePHoWmGgEFZ9O3TB00aN5ZKCwkJwZmz5zLZQz2Urd/09PQw7++5gvvh5Cnlfqe1kTJth6y0a9tW5hmPASB//vzo1PHXTD//7bdhqF2rlsz5lSlTBvXq1RWkP378RGRrcdrQDnn95g2uXLkqSK9VsybmzJ4l94tC8lLFOShSuLBgJtz09HTR/l4xua1v+MrVqxg1egySkpKk0nV1dTF/3t8MliQiIiIiIqJcKU8ETGYcTPjO0lI4y4mqWVqIz/AQHhGh9mNrIxMTE7RtIz2rY3JyMt69e6dUvnZ2BdBXhhmKMipevDjKlikjSBcLysspR44eQ2JioiBdbNYCWcyYPlUwI4tEIsGevfsUyk9eZmZmaNmyhSD9+ImTcuclFnBRrVrVbN98f/XqFV6+eiVIHzd2DGxsbOQuR88e3eFaTjgb4+49e7Pdd+9+4ewMNjY2+GvOHLnLIS+x2dMGDRqo8OCqY8GCgsGA2NhYnL9wQaH85KWpc5mUlIQjR4XXYssWLRQKXClZsgT6iMxAcfHSJQQHC4M4ZDVuzBi5glm+aycy864sdWJ8fDxOiNzX9evVQ7duXeUuhzy06R7Pyu8TJyi8r9gMXRUrVsh2NlQxNWvWQMsWwnpZU8QGFZ+/eJFjx88t93RudenSJURERArSZ86cLtw4G4aGhpg2ZYoKSiU/seWAM84IpA6sW7PHulWcpuvWhIQEnDx1WpDev19fFCoke8DVd7/9NkwQpKgp6nqmlZWm6qPExETRZ8gJ48cpNGMnAFSsUAGNGkrPbOnj44MHD92y3O/Q4SOCtBbNm6Na1aoiW2etUCEX9O7VU+79/mvKl3dFyxbN5d6vXt26gusjOSUFHp6eKiqZ/A4eOiSYuc7F2RlDhwxWOM+xY0cL0g4fEV6n2s7Ozg4N6teXSvPz8xedKTw3U6btkBkdHR2ME7kOstO8WTPRdFNTUwxT4JoUy0/sRVN1U6Ydsk9kVlNDAwMsXbJI7cGSqtSp46/Q19eXSnv2/LlM++amvuEnT59i/ITfkZxhGXZ9fX38u2wpevXsofQxiIiIiIiIiDQh9/RCZCExMUk0XWxZOFXLbJm6JJFOj/+KChUqCNJeKDl417lTJxgayjejxf/KU16Q5qXBJdNv3RbOvFilShWUEQnslIWdnR2aNRMu33Pr9h2F8lOE2AyQ169fF11aJjNpaWk4fUb4dnWXztm/vS82m6WRkRE6d+oo8/F/pqOjg549ugvSP3z4gK9fxWe0BYDw8HC4uT0SpPfs0V3upaPl5eHhAc8Mg1K6uroYIOfsXhl16thRkPb4sfpnL9LkuXz58pXotatMJ7DYIG1qairuP3igUH52dgXQpEnj7DcUIV4nemW73507d0VnF5VlyStlacs9npXy5V1lXvY+o8TERDx0EwYOdOuqeLCUugOt5FFRpF2Qk0E9ueGezs1u3rolSKtSuTJKlSypUH6NGjVEgQIFlC2W3MSWDvb84Cm65JwqsW7NGuvWzGm6bn327LnoUprdunZRKD8jIyN0aC9/IKu6qOOZVlaaqo/u3buP8PBwqTRLS0uF64TvOnUSzq725Enms6GFhoUJllIGZFt1IDPyzAj3X9Wju7D+loWenh7KlSsrSPfy+qJkiRQnNvNj7969FO5TAr7VuSWKF5dKe/XqdY7NPKtKFSuK/X681EBJ1EOZtkNWqlatguIZrgFZlC5TWjS9RfNmovV9dsReCv/slf3zvKop2g5JTU3FZZHZJVu3bgUnJydVFC3HWFtbw8XFWSrt1avXgtm3xeSWvuHIyEiMGz9BMLOkvr4+Vq9cgQ7thTNbEhEREREREeUWeSJgMl1kiUUASnWGyiqzY2R86/K/RGyZcm9fX6XyrFmzhsL7Fi5cWJAmNriXE9LS0vD69WtBevt2bZXKt2OHDoI0Hx8fhIaFKZWvrGrXqgUXZ+lOwuSUFJw+c1bmPG7fuYvgYOlZDUxMTNCmdets930q8gZ3o4YNlQqabteuLfT09ATpz54/y3Sfe/cfiC4vJxY8oGpujx4L0qpVrap00ImraznBkutPn2V+DlRFk+dSbEYAGxsb1K37i8J5Fi9eHOXLuwqP9Uy22QcyqlGjhsLLSInXidkvs37n7l1Bmouzs1LnRVbaco9npU7t2gqX5c2bN0hNTRWkt27VUuE869erC0tL8Vmwc5pYu8DHR7l2gTxywz2dm4kNsLdu3Urh/PT09NBKZOZqdTM2Noazs/QgbVxcPP786+9sl45VBuvWrLFuzZym61axoIjSpUspFEzyXZs22bf7c4o6nmllpan6yO2x8HmiSZPGSver1KheXZD29GnmdYJYYKqhgQHq16+ncBlKly4tOKckrZYyfS6FhCsaxGqozyUmJhbu7u6C9FYtFa/7v6ue4VpOTk7G6zfC/h1tZ2srnEXax8dHAyVRD2XaDlmpWUOxeyS/rS1MTEwE6RmvJ1k5ZwjQA2R7nlc1Rdshr1+/EV0pStGgbU3LeB6ioqKyfXk8N/UNb9i4CUFBwlUUFi9aILraEBEREREREVFuop/9Jtov45IT38XGxiq8dJSsxGaEAQBTU2FnWG6TmpqKhw/d8OLlS3h4euLTp0+Ijo5BXFwc4uLikJZJoKqYGJFlxeRRUsFZigDA3NxMkKapgEkPD0/ExQlnBqlSuZJS+VbOZP/nz59nuvyPKuno6KBTp45YvWatVPrxEyfQX8YZDo8fPy5Ia9miebazCUokErx8KVxOMrNzIitLS0sUK1ZMMLvJ8+cvBEv0fff6jXBZY0dHxxx5S/6xyABnxUoVlc5XX18fDg72+Pz5fzMWeHt7IyEhQbTTX1U0eS7FAgAqVqig9NJQVSpXxps30ktlPX8uPJYsSpYooXA5xJZ0lKVOFPubVK+h2CCPPLTpHs+K2Mydsnoh8v0KubggX758Cuepr6+PsmXLiM7Uqoy3b9/h0aNH8PD0hKfnB4SFh31rF8TGyfWyiNhyo+qSG+7p3CoiIkJ0gF1sxhl5iM3slhMaN2okWLbu+IkT8PDwwPDhw9CsaTMYGan2hSzWrVlj3aq9davY9aPsvV+2TBkYGhio9OVDbXqmlYcm6iOx54lKFZV/nrCzs4OhoSGSk/83E5+7h0em22f8bQWAkqVKKR24Wa5sOfj5+SuVR16lp6eHYsWKKby/os8X6vDk6VPBfZ0vnzUKFXJROu+MM8kBgIe7B6pXq6Z03opISkrCnbt38ebNW3h4eMLryxfEREcjNi4O8fHxcgVY5+Tvh7op03bISokSir8QYGpqioSEBKm0kgrmZ26m+j7OnGyHiLV9DQ0MlG6DKivg61fcvn0HHh6e8PD0QGBgEGJjYxEXFye6dHZWoqNjsmxv5qa+4QsXLwnSunXtgo6/CmePJiIiIiIiIspt8kTApEkmwYnR0TFqD5iMjhbvlBLrMM4tgoODsX7jJpw7d16wJJeioqKU63y1VmCZmu+MjYXXh6aWTfLzFw7Q6OnpoXRp8SV6ZGVjY4OCBQvi69evUun+/gFK5SuPLp07Yc3adVJLz7x+/QaeHz5kuyxnVFQUrl67LsxThqXTYmJiRDtlXcspvwSTq2s5wYB/VufUW2Sp98oqCFqUhaencNk6PV1dlQTv6OsbCNIiI6PUGjCpyXPpLzKQKrbMnLzErkn/AMXuUWV+28T+bhmXVxLz5Yu3IC0n/ibadI9npWDBggqXQ+y3QdGluH5WtoxqgnqSkpKwc9duHD12TCp4Whk5OSibG+7p3Ers2gWUv37FlhrMCUOHDMahw0ekgnoA4O27dxg3fiLMzcxQr1491K5dCzVrVEfJkiWVDrxl3Zo11q3yycm6VR3n18DAAMWLF8d7kdnh5KWNz7Ty0ER9JPY8kZaaqpLnCTMzU6nvIja72HchIaGCNEUDi35WokRxXL5yRel88iIrS0uFZ68HMnm+SNZMn4unp6cgLX/+Aiq5jsXq2IhsZpJTB68vX7BhwyZcunw505e45ZWXAiaVaTtkxcrKWuF9jY2NVZafWF6yPM+L7aOJdsgXkb6eMmXLZDoZgrqdv3ABu3fvxZOnT2VaSlsWUdGZ/8YBuadv2MvLC/4iZR04oL9C+RERERERERFpmzwRMFkgf37R9OgY9Xf4xcRmEjBpljsDJnft3oPly1cgNi5OpfnGJwjfnJVHxiWBlaWqTjB5RYsMDFlZWamkY9Dezk7QKZaTnd7Ozs6oWbOGYAD52LHjmD5tapb7njl7VjAY6OTkJNNSSpkNttnZ2WW7b3bsRfLIquMzMChIkObg4KB0OWQhNlCzectWbN6yVS3Hi4qKRMGC6vtumjyXUSL3jb298teTnUgeMTExSE9Pl3uAW53BqmLi4uJEB+Ny4m+iTfd4VizMFV/CVuy3QWypPHmJLZMmr/sPHmDmzNnwUfEypPHxyrUL5JEb7uncKlokeMjQ0DDb2aGzo4rrXxHOzs6YP+9vTJk6TfTz2Lg4XLx0CRcvfZtpxdzMDJUrV0atWjVRp3ZtVK5cSa6AE9at2WPdKp+crFvFz6/y50YVeWjrM608cro+SkxMFJ1Ba/6ChYp9gWykpqYiJiZW9PdCrB/HwtJS6WNaqiCPvMpExf0tgOb6XMSWwv3w4QO6du+hluNlFfyraunp6VixchW2bt2m0pl4ASA+PiH7jXIJZdoOWTExEQYqalN+8tBkO0RseWcH+5zp6/mZr68vpk6fofJZwwEgIZv7Kbf0DQd8DRSkGRoYoIQSK54QERERERERaZM8ETDp6Ogomu7l9QXlXV3VeuzM3sIVW6pH2y1eslRtwVXQTF+51hEL2lDVbKQWFsJO4ZzsvAeALp07CzobT50+gyl/TIaenl6m+x07fkKQ1qnjrzIN8omdU0A151XsnIoFh3wn1jmcUwNzOf23jolRzUwWmdHkuRTrvFbX9ZSeno7Y2FitH8DNbODDylLx2X9lpU33eFaUGfASm61aXd9PHpevXMX48RNUPiCb03hPq4/Y4Js2XLvK6NK5E8zNzDBtxsxsBxdj4+Jw99493L13D8C3Z5IO7dthQP9+MgUesm7NHutW7RUtsvynas6vcnnkpWfanKyPIiIiVVFkucTExoj+vWO09N6l3EEsYFKdcmrp8dTUVEz+YyrOnD2rlvw1FeCqDpoMRMwNNN0OiYsXvsxgZZWzz05eXl7o22+A6Iu6qiDJpsGQW/qGIyMjBGlW1tbQ188Tw0lEREREREREeSNgsmQmbza+fvMG7du1Veux37x5I5qe3RLE2mb/gYOZDizp6+ujdOnSqFK5EpycnODg4AALCwsYGRnCyMgIujrSsyi9ffcWf/71d04UO9cRm7VDbDkdRRgZC99Ejk/I2VkCWrdqibl//424uP8FAISEhOD2nbto3Kih6D4fP37Cq1evpdJ0dHTQuVMnmY4pdk4BwFjkfMjLWOTt7qzOaWpKqkg51N9ZHx8fj9RU4bHVKS09Ta35a+pcAkCiyHJWxkbKHzuzPOLjE7Q+uColk+tLrN5RNW26x9Ul4wy7wLdlSZVlaGio8L4enp4YN34CUjIZSCtcuDCqVq2CIoULw8HBAbY2NjA0NISRsRH0dIUB8uqa1UcWvKfVR+zaNdTwtasKLVu2QK1aNbF5y1YcOXpM5uV8AwICsHHTZuzYuQuDBw3E+HFjs7yXWbeqF+tW9dLG+z8vPtPmVH2U2coZ6pSeJv48oasnnKU5TQXPOqmpuTtImWSTUwGM36WlpefIcVasXJVpsKShoSHKl3dFxQoV4OjoCAcHe5iZmcHIyAhGRkbQgfSLqDdu3sS69RtyotikZbShHSLWd5VTfT3AtzbwoMFDMw2WtLW1RZUqlVG6VCk4ODjAzq4AjAy/3Utiv6N//jUXb9+9k7sMGWlj33BCgrCcqmhLExEREREREWmLPBEwWb58edH01xmCsNTh9etMAiZL5Z6AyfDwcCz7d7kg3cjICCNHDEfvXr3kWr4uJ5eCy23E3hiOU9FScWL55PQsGqampmjdqhWOHjsulX78+PFMAyaPHT8uSKtRvToKFy4k0zEtMnkLOy4uDvny5ZMpj8yILeOX1aw3YgO8YkttqlpWs3fmVpo6l8C3+zTjzCSqWNIxs3td2ZmUckJmwQs58TfRpntcXcTqalX8Nijz9/nzz7miA2mdOnXE8GHDULKk7Mtw5XRAd0a8p9VH7NpVxbnNqfo+K9bW1pjyx2RMnDAed+/dx7179/Do0WO8d3dHenrWwRFJSUnYsHETHro9wq4d22BmZia6HetW9WLdql4WFuaCWQk1ef/n5WfanKiP9HSFQYqaYiXy0oEq6sXYWNUu0U7aSTcPPht/+vQJ27bvEKRbWlpi/Lix6NK5s1y/s54fPqiyeJSLaEM7RKz9G5ODbf8NGzfB189PkF61ahWMHzsW9erVlSs/YwVmNM3NfcOyrARERERERERElFvkiYBJV9dysLCwELxJ/vLVK0RFRcHKSj3L2kVHR+Plq1eCdFNTU1SoUEEtx8yKojMmnDx1WrA8h5GREQ7s24tKlSrKnV9UdM4uDZybiC0zo6pBcbGZFKzVdO1npWuXLoKAyavXrovei2lpaTh1+rQgjy5dOst8PMtMlq1UxXkV67S1trLOvCwif1+x5SBVzcjICIYGBoIllfbu2YU6tWur/fjqoKlzCXwbeBIEV6niehK5Rw0MDDIduNYmlhYW0NHRESzVJrZkosqPrUX3uLpYWgoHMFSx7L2iM+y8ffsOj588EaTPmT0LA/r3kzu/KAWX4lWVvH5PazJoSuzajY+PR3p6OnSVCL7J6dmhsmJgYIDGjRr+ePEjJiYWz188x+PHT/D48RM8f/Ei07/B8+fPMemPKdi4fp3o56xb1Yt1q3pZWFgKAiZVce8q+jf6LzzTqrM+ymwp0JvXr8LFxUU1X0BGYv034eHCZUHlJevsnDmFM16qh9i13KlTRyxbslgDpVGNffsPCILcbGxscPTwIZlfNP2ZosvzUu6mLe0QsaD4GJElqtUhLS0Ne/ftF6S3bdsGy5ctVWip6WgFzsN/oW+YiIiIiIiIKDfQnmkElKCvr4/6Im+AJiUl4dTpM2o77qnTZ5Akssxj/Xr1YCSyFN3P9EXeek9NU27AOyJDMICsrl67JkgbPWqkQgNLABChgsGMvMpKZHA6KipKJR3Wvr7CN6TFOiLVrUaN6ihUSLrTPjk5GWfPnhNse+fuXQQFBUulfZulsqXMxxPraAQAbx9fmfPIjLe3tyBNLJDvO8eCjoI0ry9eSpdDFg4ODoI0HxWcA03R5LkUu6Z8fHyUzlf0esoly/YaGhoif/78gnSvL1/UfmxtusfVRWw2ty/eX5TO18tLsTyuXb8uSKv7yy8KDaQBQESEZtsF2nZPi80KrEzQY8Zg0Jwkdu2mp6fDW8nzmxN1i6IsLMzRoH59TPp9Ig4e2IdHD+9j8aKFqFhR/GWpK1eu4qGbm+hnrFvVi3WretmInl/h315eil7//8VnWlXWRwUKFBBdZlMTzxMFCxYUpL13d1c6X2XyUPVvNwBERjJoTR0Kij4XK9/u06Tr128I0mbNmK5QsCSg+d8P0gxtaYc4Oor19XxRKC95PXnyVPDsZG1tjX/mzVMoWBIAwhU4D/+FvmEiIiIiIiKi3CBPBEwCQMdffxVNP3LkqNqOmVneLVo0y3ZfMzPVL78RGBik0H5v3giXFe/cqZPC5Xgtkh99U6JEcdH0t+/eKZWvr6+vaMdaiRKyL6ejSp07dRSkHT9xUpB27PgJQVqrli3lmp3L1NRUtMP1nZLn9Fse7wVpJbM4p2LLF718+Uowc5Q6iP2tVTGwqCnadi7FrgV5vX0vzCOzOkEbif1Nnj9/rvbjatM9ri5ly5YVpLm7e2S7zGZ23r1X7By9fi3SLujcUeFyvH7zWuF9VUHb7mmx3zhl2oCBgYEK76usIkWKwNTUVJCu7P2pir9PTrGyskLXLp1x4thRzPt7rujMmidPnsp0f9at6sO6Vb3Kli0jSFP2+gkNDUVISIhC+/KZVrn6SFdXF0WLFhWka+J5onKlSoI0Hx8fpV4QSEtLw9u3il+fqv7tDg8PF335lpQn9nvz4cNHjc7IrYyIiAjB8sFmZqZoJcdLphnlxvqNlKct7RCxtq+X15cceQlM7Npv0byZXEva/+zr10CEhYXJvV9u6Rtu364dHrs9kPrvzClhPy4RERERERFRbpVnAiYbNWooPuj3/j3Onjuv8uOdO39etCMjf/78aN2qVbb7i3XGBAcrNjgEfFse/OPHj3Lvl5CQgLi4eKk0czMzFCwofCtfVo+fPFV4X22jo6Oj0vxcXFxgZ1dAkO7m9kipfB8+FM4Uoq+vn+nsIurWpXMnwQDdi5cv8enTpx//jo6OxrVrwjfcu8qxHPd3VatUEaQpe059fHwREBAg07G+q1K5siAtOjoaL1++UqossqhSRXhssZkocgtNnkuxv/Gbt2+VGhSVSCR49Oix8FhVqyqcZ04TG7x+/ORpjgz2ass9ri6VRWa/io+Px/MXLxTOM+DrV4VnQQsNCxWkKROAr+l2gbbd0xYWwmWClWkDPn36TOF9laWnp4fyrq6C9Hv3HyiV773795XaX1N69+qJ3r16CtKzugdYt6oP61b1Ert2nz59ptS1e/fePYX24zOtkCL1kdjzhNjzmrpVrFhBMNOXRCLB+fMXFM7zzt27Ss3cJfbbrWhwLwA8faa5325to+o+l8qZPEeKLUWcG4SGCoOxnJ2ds13VJjPJyck58kxN2kdb2iFi96hEIsHde+pv/4eGqvgcPBY+D8oit/QNGxkZwsbGRuo/Ky7vTURERERERHlIngmY1NPTw6iRI0Q/mzf/H5Usa/FddHQ05s1fIPrZ4EEDZeq4zJ8/v2BZp/DwcIU73a9eu67QzGvR0dGCNFMz4UxBsnr06DG+aPEyivIyNDQUpKWmpiiVZ9UqwmCKU6dOKzVz3gmRmULKli0DExMThfNUhqOjI2rXriVI/3lGybNnzwkGVF2cnVGzZg25j1etmvCcPnn6FH5+wqVoZHXi5ElBmq6uLiqJDA5/V6NGdZiLzD6yd/9+hcshqyaNGwnS/P39M112T9tp8lyKXU8JCQm4eOmywnm6PXoEf39/4bE0EECiqMaNGwnSoqKicObMWbUfW1vucXVxcXGBvb2dIP3UqdMK56nM70p0dIwgzUxkFkFZxMXFKRXgoAradk/b2Qn/1u4eHgqVw9fXV+F9VUXs/F64cBFJSckK5RcYGCQ62JdbtG/XVpAWmkX7vnHjRoI01q2qwbpVvcSun9jYWNGlsWV18qRifxs+04qTtz4Se554+uwZvL1zdjljExMT1KpZU5B+8PARhe+/AwcPKVUmexX+dgPA1auK3yd5jVifS4oSs0E6ONjDtVw5Qfrx4ycVzlOTomNE6jdT2VfkyOjsufOIj4/PfkPKc7SlHVKkcGEULVpEkL5vn/r7eqJjhOdAbLZ8WR06ckThff8LfcNERERERERE2i7PBEwCQLeuXVCyZElBemhoKGbN+VNlS7n++ddc0cDGAgUKoE/vXjLlYWxsjGLFignSb92+I3d5JBIJtm3fLvd+gPhMCRERkUhOVmyQe9PmLQrtp63EArbiExKUylNs6SRfPz9cvnJVofxevXqFRyJvNcsy06k6de0snCny1KnTP5ZBFFuOu0vnTgrNMNG8WTPRWUi279gpd17At8Heg4eEg2r169fLcqkeQ0NDtGnTWpB+7tx5qdk11aFMmTIoJ7L05NKl/6r1uOqiyXNZqmRJlCguXCJp167dCi/juW3bDkGatbU16tSprVB+mlClcmUUKVJEkL5pyxa1z4SmLfe4Ov3aoYMg7eSpUwgKCpI7r7i4OOzZu1fhsoidg0AFygEA+/YfQIzIwFRO0rZ7uryrcBD/tgLtPwDYvmOX0ssLK6vjr78K0qKjo3Hg4EGF8tu0eYvGv5MybGxsBGlpWXwf1q3qxbpVfYoWLYpKFYWzeG7eslWhe/jV69cKzy7LZ1px8tZHDerXR/78+aW3T0vDsuXLVV627IjNjvn27VscOix/cMrdu/eUDlB0Ffnt/vzZC76+vnLnFRwcjNM5EBSfW4gtd56gZEBfp04dBWknT52Ch6enUvlqglj9pshvGACkpqYq3HdIuZ82tUPEnh8ePX6MBw8fKpynLCzMhedA0fvp1atXSr3k9V/pGyYiIiIiIiLSZnkqYFJfXx+LFy4QzNwIAOfPX8C8+f8oHTS5YNHiTDu3F/4zH+YinS+ZqSSyJMZBBWY+2LR5C9zdFZvdwNTUVFDmlJQU3FNgKZSjR4/h5q1bCpVDW1laWQrS/P2EM0rJo3WrlqKz3fyzYCES5AzGTEtLw5y/5gquaxMTE/To3k2pciqrZcsWgmsrMCgId+/dw6dPn/Di5Uupz3R0dNC5cyeFjlWwoANaNG8mSN+7bz/ev3eXO79Vq9eILo86cED/bPcdOKC/IOgzOTkZv0/+Aykpys1Omp2hQwYL0l68fIk1a9aq9bjqoqlzqaOjg379+gjS3757h337D8id39Vr13D9hnB59J49usPY2FihMmqCjo6O6D3w+bMXFi1eqtZja9M9ri69evYUXO9xcfGYv2Ch3HmtXLUaQUHBCpdFbBalmzfl/33/8OEjVq1eo3A5VEXb7umKIgFGly9fRnh4uFzlePL0KfYfkL/8qlaiRHHUrCGcHXrlqtUIDpbvOnz79h325cBMwurk7SMMnrG3t890e9at6sW6Vb3EgtrevHmLAwfkC5hOTU3FX3/9rXCwNJ9pxclbHxkaGqJ/v76C9PPnL+D4iZOqLFq2mjVrioIFCwrSFy5cJNdywt7ePpgybZrS5bGxsYGLs7Mg/eChw3LlI5FIMG3GTIWDefMiK0thn4ufyCze8ujapQusra2l0tLT0zFp0h+IjY1VKu+cZldAuGxvQEAAPD98kDuvtevWK9x3SLmfNrVDevbsITqz45Sp00VnjVYVsd9ARX7zExMTMfmPqUqVJTf0Da9avQbFS5YW/EdERERERESUV+SpgEkAqFSpIqZNnSL62a7dezB6zDiFlueOiYnF+Am/Y9s28bexe/ToLrqkXlZaibzl+fzFC+yXY4Dp9JmzWLFylVzHzaiWyBLIK1atlqsT/86du/jr73lKlUMblSxRQpD28dMnpd6k1tfXR/9+/QTp/v7+GDtugsyBYBKJBDNnzcbr128En3Xp3EkwQJDTjI2NRWcIPHbshOjskrVq1YSTk5PCxxs0aKAgLS0tDSNHjZbrjfFjx09gx85dgvSSJUuifr162e5funRpdOwofFv+zZu3GDFytNwdn9+lpqYiLCzrYJoOHdqjssiSlytXr1F4tqifJSQkYN++/Tk2o5Emz2Wnjh2RL5+1IH3BwkW4/+CBzMd6/94df0wRDtIaGhqiT5/eMuejLXp07yY6E9ruPXuwWonA3KioKCQmJma5jbbc4+pSqJALWrVsIUg/f/4CVq5aLXM++w8cVPp+rymyDOb+AwflWqbXz88Pw0eOyvbvmlO06Z5u2qQxjIyMpNJi4+Lw97x/ZC6Hu7s7xo4bj1QllqxUpd+GDRWkxcTEYPCQYTIPevr6+mLY8OFIS0tTdfFk8vjxE2zYuEmh54TvJBIJdu3aLUivWKF8lvuxblUf1q3q1a5dWzg6OgrS5/+zALfvyDZzrkQiwR9TpuLlK9mD4MTkpWdaTdZHQwYPEn0mmzFzFs6eO69web6LioqS6V7S19fHX3/OFqTHxsVh4OAhuHTpcrZ5uLk9Qp9+/X8EOiuyksHPxGYD2759B9zdZQswT09Px9/z/sGtW7eVKkdeU0Kkz+XFi5dKvexsYWGOiRPGCdLfu7tj+MhRiIiIUDjv79zcHikUlC0va2trlC5dSpC+bNm/cp2jY8dPYP2GjaosGuUy2tQOyW9riyGDBwnSAwICMGDQ4Gz7azIjkUhEV4T6rqZIW+H16ze4cOGizMdISkrC2HET8OnzZ4XK+N1/pW+YiIiIiIiISJvluYBJABg8aCD69RXOJAQAly5fRotWbbB7z17Ey7DMT2JiIg4eOoxWrdvg7Llzots0aFAff80RduZnp2GD+qKzJvw192/s27c/y87PiIgIzP9nAX6fNPnHYLmJiYncZQC+LceX0du3bzFm7LhsA6NSUlKwbfsO/DZ8xI/gJbEZPnMrS0tLFHJxkUpLSUnBho2blMp38KCBcC0nXNbrxs2bGDZ8BL5+Dcxy/8jISEyYOAlHjh4TfObk5ITJk35Xqnyq0rWLcFnuK1evis5QIratPKpWqSJ63/v6+aFXn3549vx5lvunpqZiw8ZNmD5jpuDe09fXx5JFC2QeZJs1Y7rom+I3b91C9x698OiRcJmczERERGDnrt1o3LQ5bty8meW2Ojo6WLZ0seib+v8sWIjfho+QezlriUSCly9fYeGixahbvyHm/DU3RwfpNXUuzczMMG/uXEF6cnIyRowchaMi915GV65eRf+Bg0SDhaZMngRHkfpf2xkaGmLxIvGZnFetXoPRY8bBR2Q2o8x88fbGwkWLUb9hI4SGhma5rTbd4+oyZ/YsWIrMsrNm7TpMnjI1y8CJ+Ph4zJv/D/7863/XrVhdIIumTZtAV1e6iRgfH4+Bg4fIVIfcuHET3Xv2gre3NwDtaBdo0z1tZWWFli2aC9LPnD2L6TNnZdk+TUlJwd59+9CjZ+8fM/kp2v5TpcaNG6Ft2zaC9Pfu7ujSrTuePnuW5f6XLl9Btx69fgS1KHrtKiMiMhLL/l2Oeg0aYfacP/HQzU2u2e4SEhIwfcZM3Ll7V/DZr78Kl4X+GetW9WLdqj7GxsaYP0+kbk1JwfARo7Bp0+Ysg6D9/f0xcNAQqRUcFD2/eemZVpP1kbGxMZYtWSz4/ikpKRg/YSKmTZ+BgK9fZS4L8C0I+6GbG2bNnoO69Rti6bJ/ZdqvWdOm+LVDe0F6dHQ0Ro0Ziz79+uPwkSPw+vIFsbGxSEhIgI+PL06fOYvhI0ehd99++Pr/ZdXT0xOdEVUeYrN0JaekoP/AwXj8+EmW+378+AmDhw7D7j17AAC6urowNDRUqjx5RcmSJQQvkoSGhso9U21GfXr3Fg3Yf/jQDe3a/4pLly7LPattUFAQ9u8/gA6/dkLvvv3w+o0wQEkdxOq3a9dvYObsOUhKyjooPD4+HkuX/Yup06b/qI+14feDcp62tUNGjRyBMmWEsxW+evUaXbt1x5Wrsi9NHRcXh6PHjqN1m3ZZTkLgWq6c6EsBf0ydhuvXhSsIZOT54QP69BsgtdqAMufhv9I3TERERERERKSt9DVdAHX568850NPTw06RWRVCQ0Mx9+95+Pff5ahbty6qVq2CokWK/BhIi4mJgbe3N569eIG7d+9lOTNOrVo1sWHdWoU6u3V1dTF50kRMmiw9I+b3pTT2HTiANq1bo0yZ0rCytEJsbCy+BgbiwcOHuH3rNmLj4n7sU6dObdjb2+PkyVNyl6Njx1+xbv0G+GZ4q/ja9Rto3rI1+vTqiQYNGqBYsaIwMTFBZGQk/P0DcPv2bZw4dfpHZxnwLWBrxPDfsG79BrnLoa1atWqJzVu2SqVt2rwFL168RPPmzVC0aBGYm5tDT1fYSValSmXRPA0NDbFi+TJ06NhZEHx2585dtGrdBh07/opWrVqiWNGiyJcvH6KiouDj64vLl6/g+ImTokt36urq4t+lS2BhYaH4F1ahalWromjRIvDy+vIjLSkpSfDGt7mZGVq1FM7YIa9pU6fg4UM3fPj4USrd29sbPXr2RovmzdG+XVu4upaDnZ0dEhMTERgYiFu37+D48ROC/b4bP26s6BKqmbG2tsaGdevQu28/wd/33fv36NWnL2rVrIkmTRqjVq2asLezg7W1NVJSUhAVHY0vX77gzZu3uP/gAR48eCjXDGJFixbF6lUrMWLkKMF+167fwPUbN1GvXl00qF8fVSpXRsGCBWFlZQl9fX3ExMQgJiYWfv7+8PTwwHt3D9y9d1ep5SeVpclz2bp1K3Tp3BnHjh+XSo+Li8fU6TNw8NBhdOr4K2rXrgU7O3vo6ekiKDgYz549x+nTZ3D33j3RfOvXq4eBAwfIfzK0RPVq1TBr5gzMFZmB6eKlS7h+/TqaNWuKhg0aoFKlSrC1tYGlpSXi4+MREREJzw+eeP36DW7euo23b9/KdWxtucfVxc7ODnNmzxRd3uvEiZO4cvkKmjVrijp16sDezg66enoIDg7C4ydPcenSZURGRv7Y3sLCAkOHDFZoFuoihQujfbu2OHX6jFS6l9cXdOjYGZ07dUSrli1RpkwZWFlZIi4uDkHBwXBze4Rz587j8RPpoIFRI0dgzdp1cpdD1bTpnh43biwuX7kqqNcOHz6CGzduol3bNqhWtSpsbGyQnJyM0LBQPHv2HNdv3ERg4P8GzvLnz49BAwfIHHyiTn/Ong03t0eCAL3Pn73Qo2dvVKtWFS2aN0ehQi6wsrRCeHg4Pn76hAsXLwqWh/xj8iTROiYnxMfHY/+Bg9h/4CBsbW1Rv15duLq6wrVcOTg6FoSVlRXMzMyQnJz84zvcu/8AJzJpm9WrWxeNGjbM9risW9WHdat6NWzQAN26dhEM1icnJ2PJsn+xe+8+tG3TGuXLl4edXQEkJCTi69evuHX7Nm7fviM1A2SlihVRtGgRnDx1Wu5y5MVnWk3VRzVr1sDfc//CzFnCl0KPHD2GEydPoWmTJvjll9qoXLky7AoUgJWVNQAgJjYGMTEx8PHxgbu7B969e4+79+5J3Ufy9J38PfcvfPz4CW/fvRN89vChGx4+dJMpn0m/T4StrS327T8gla6rK3tAd9GiRdG9W1ccPnJUKj0sLAw9e/dB/fr10LRJExQq5AJTE1OER0TA29sbd+/ew0M3N6ng4bFjRuPosePwV3Lp6bzAwMAATZs2wfnzF6TSZ//5F27euoWGDRrApZALzMzMoKsjHexlaGgIV1dhsBHw7T5etXI5evbuC09PT6nPAoOCMGrMWBRycUGbNq1RrWpVlChRAtbW3+6p+PgExMTGICwsDJ6eH+Dh4YEnT57i1evXSs18qahBAwdg567dguXEDx06jAcPHqJvn974pU4duLg4w8jICOHh4fDx8cWNmzdx8tQpqed5IyMj9O/XF1u2bsvpr0Eapm3tEENDQ2xcvw6du3YX/Gb5+PpixMjRcHV1RYvmzfDLL3VQ0KEgbGzyIT09HVFR0fDz98Pr12/w+PET3Lp9+8dzlXCdm//R0dHB6FEjMWPmLKn0hIQEDBs+Ak0aN0bnTh1RqXIl2NrYIi0tFaGhYXj1+jUuX7mCixcvSdXltWrVRHpauuDcyHMO/gt9w0RERERERETaKs8GTALA7FkzUapUKcz9ex6SkpIEn8fGxeHS5cu4dDn75ZzEDBo4AFOn/AEDAwOFy9jx119x6dIVXL5yRfCZh4cnPDw8RfaSVrp0Kaxbsxrz/1moUBkMDAywYMF8DBo8VBBMFBISgpWr12Dl6jUy5fXHpN9RqXIljQ8uqVKvnj2xa/cewTXk9ugR3B49ynLfTx88Mv2sePHiWLNqJUaPGYvkDEutxMbFYe++/di7b7/M5dTR0cGC+fNQo0Z1mffJCV06d8ayf5dnuU2bNq1VMkOWsbExNm3cgN59+0kFlADflkC7eOkSLl66JFeeXTp3xsgRw+UuS6VKFbFt62YMHz5SKrj5O1muH0U1btQQG9evw7gJEwUzlUkkEty5cxd37ghnnNFWmjyXf8/9EwFfA/DgwUPBZ89fvMDzFy/kys+1XDmsWrlc47NtKat/v75ITEzE4iVLBZ8lp6Tg/IWLOC/Hslay0qZ7XF06deyIz5+9RJfMi42Lw8lTp7MNJNHX18fqVSt+zECoiGlTp8DN7RECMyzJm5iY+CN4QxZNGjfGmNGjtCKoB9Cee7pokSL4Y/IkzJsvXIY7JCQEO3buEl3e+Gfm5ubYumWTTG3FnGBra4OtWzahX/+BgtncJBIJnjx5iidPnmabT8dfO6B/v74aC5j8WVhYmEz3XGacnJywaOECmbdn3ao+rFvVa+5ff8HP31+0bg0MDMS27TuyzcPOrgDWrl2NFSvkD0YF8v4zbU7XRz17dIeOjg7m/PmX4HympqYq1Y8iD3Nzc+zetQPDR46S6TdEzKiRIzD8t2E4fOSI4DNTUzO58poxfTruP3gAPz9hoKOsz1gdO/76I2CSvhnQvx8uXLgoCEa8dv0GrmUx65uTkxNu37ye6edWVlbYu3sXhv72G169ei343MfXFxs3bVa84DnE2toaf86ZjT+mCAP/fXx8sGDhIpny0dHRwaKFC6QC1em/RdvaIS4uLti7ZxcGDBwsupT227dv8fbtW4VeVMlM1y6dcf78BdGX4a7fuCE1e2RWXJydsXL5v5gwcZJS5fmv9A0TERERERERaaM8uST3z3p074YL586iQYP6KsvT2dkJmzaux6yZM5QKlvxu5Yp/0axpE4X2rVmjBvbu3gUrKyulyvBLnTpY8M986OsrFkOro6ODyZN+x/DhvylVDm1UqJALZs2coZa8mzRpjF07dyB//vxK5WNubo4N69eiW7euKiqZ6nTq2FGw7E9GXTp3UtnxChcuhKOHD6FixQpK5aOrq4uxY0ZjsRJLSdauVQtHjxxGqVKllCqLIho3boTjR4+ILu+jDB0dHeiKzKaqbpo6l8bGxti2ZTO6dFZuyXgAaNqkMfbt3aN0fa0tfhs2FBvWr4O1tXWOHleb7nF1mfT7REyfNlWh32QTExOsW7saDeor1+6xs7PDls2bYGNjo3AeLVu0wJrVKxVuW6iDNt3TAwf0x+8TJyi0r4ODA/bv3YMK5csrtL+6VChfHgf27RVd6k4WXbt0liugR5u5urri6OGDKFjQQa79WLeqD+tW9TEyMsS2LZvRrm1bhfYv5OKC/Xv3wLFgQaXKwWdacYrWRz26d8O+vbtRyMVFpeUxMJDv72NtbY19e3Zj/Lixcr1kZ2dXAOvXrsGk3ycCAKKjhUuzW1iYy1UWCwtz7N+7B0WKFJFrv+8G9O+HJYsWal39qGnVq1XD8N+GqSVvW1sbHNy/DwP691P5ec/Jerhzp44KtxsBwNDAAEsWL0KH9u1UVyjKdbSxHVK6VCmcPH4MNWvUUEl+2dHT08PaNatQoYLiz1ElS5TAnt07YWdnp5Iy/Rf6homIiIiIiIi0UZ4PmAS+DQDu2LYVRw8fQps2rWFsbKxQPuZmZpg9ayauXLqIZk2bqqx8RkZGWLd2DaZPmyrzoLu1tTWmT5uKvXt2KdXR9bMunTspNCBSrFhR7Nq5Q6tmkVG13r16YuOGdXCwt1d53jVr1sClC+fQu1dPGMoZgKunp4dfO7THpQvn0bxZM5WXTRUcHOxR95dfMv28cOHCqF5dtW8+FyzogCOHDmL6tKmwyZdP7v2rVq2CI4cOYsL4cUoPqpQsWQKnTx7HjOnTYGdXQKE8TE1N0a1rF9SuVVPuY584fhQLF8xXeFDvR14lSmDS7xNx+9YN2Nqqps6RuwwaOpdGRkZYsnghNm/cgBLFi8t9TGdnJ/y7bAk2b9oo96CstmvRvBmuXLqAfv36Kvzbam9vh1EjR8g1OKBN97i6DB0yGIcPHkCVKlVk3qd+vXo4c/qkytoo5cqVxZlTJ1GnTm259rO0tMRff87BurWrFb4u1Emb7unRo0Zi08b1KFasqEzbGxgYoFfPHjh/9nSmS1BqWtmyZXDuzCn069dX5heLChYsiOXLlmLxooUqeRlJERUrVMCwoUMUuiZ+ZmNjgz/nzMaJY0cUHkRl3ao+rFvVx8jICKtWLsfyZUvh6Ogo0z6GBgbo26c3Tp86iaJFZasHs5MXnmm1qT6qXq0aLl44j2lTpyj9LFyhQnnMnjUTN65dk3tffX19jBs7BjeuXcHvEyegfHlX6OkJX+IyNTVFvbp1seCf+bh5/Rpatmzx47Po6GjB9paWlnKXxcnJCUcOHUDvXj1lDhgqWrQItm7ZjDmzZ4mWm4A/Jk/C/Hl/q+WFASMjI8yZPQunThxH0yaNs32hMyuWlpbo1rUL9u/dgyGDB6mwlNkbPWokNqxfJ3dQVaWKFXHkyCF07tRRPQWjXEUb2yEODvbYv28PFi9aiEKFCimUh4GBAVq2aCFT36iFhQUOHTiAvn16y1Un6+npoV+/vjh65BBcVPwyQV7vGyYiIiIiIiLSRjqSjGve/AfExsbiwcOHePLkKdzdPeDr54fw8HAkJCQIlpv6ma6uLlatXI42rVurrWzR0dG4fOUqbt+5A/f37giPCEd0dAyMjY3gYO+AMmXLoFHDhmjVsgVMTU3VUoa0tDScPXsOZ86ew5OnTwXLKgLfBmFr1ayJtm3boElj6Q7nwMAgwRLj9vb2aNmiuVrKm5PS0tJw+85d3Lt3D+/ev4evrx9iY2MRHx8veu1ktSS3mODgYJw+cxY3b93Cq1evEBcXL9jGyMgI5cu7okH9+uj4awc4Ozsr/H1yyvPnL3D7zh3RzypWrIjGjRqq7dgJCQm4eOkSLl++imfPnyM0NFSwja6uLkqUKIFf6tRG+3btULlyJbWUJTk5GTdu3sKVq1fx9Okz+Pr6CpYdA77NgFakSGFUrlQZDerXQ926v8DcXLmgHIlEgsePn+DqtWvf6j4PD8Ey89+Zm5ujWLGiKFmiJGrWqI5ffqkj88B3TtHUuZRIJLh37z7OnT8Pt0eP4ePjI3pcR0dH1KxRHa1atUTjRo20ahYodYmMjMSFi5dw8+ZNPH/xEmFhYaLbWVlZoXjxYqhZowbq16+HGtWrKzVwrE33uLo8e/4cFy5cxNOnz+Dt44OYmBjo6+vD2toKRYsWRfVq1dC6VUuUKVNGbWV4/PgJDh4+jIcP3QRL9gLfBp2qVq2CZk2b4tcO7WFmJr3E5e49ewX79O/XV23llZW23NOpqam4des2bt2+jWfPniM0LAyRkZHQ09ODjY0NSpYsgV/q1EG7tm3h4KD6lzfUJTQ0FKdOn8G9+/fh6fkBYWFhSE9Ph5mZGZydnODqWg6NGjVC0yaNtaqe9Pf3x5MnT/H8xQu8efsO3t7eCA8PF93WwMAAxYoVRYXy5dGyRQvUr19PpUGfrFvVh3Wr+qSmpuLateu4dv0GXr1+ja8BAYhPSICxsTHy29qiZMkSqFOnDtq2aa2y2ZkyyivPtNpUH6WmpuLuvXu4fv0Gnj17jo+fPiElw/Kh3+XLZ42iRYuidKlSqFWrFurUqY38trYqKwsAJCUlIyDAHzGxsTDQN4CVtRUKOjhkGrA9YtRoXLlyVSptxb/L0KFDe4XL4Ovri8tXruLO3bvw9vZBeHg4EhMTv/3OOTujYoXyaNasKRrUr69UkN5/SVJSMq5dvwY3t0d47+4Ofz9/xMbFISEhAWlpaVLbZrckd2b8/f1x6fIV3Lt3H6/fvMn0t1VfXx8uLs4oXrw4KlWsiF/q1EGFCuU1HvSalJSEo0eP4eLly3j+/AUSEhKkPtfR0YGzkxPq/FIH7du1xS916kh9/unTJ9y7/0AqrXjx4qj7i/R2mQkNDcXkDMuD58+fH8uWLFbg25AmaWM7JD09Hffu3cely5fx5MlTfPr8Genp6YLtDA0MUKhQIZSvUB716v6CBvUbKPRyr4+PL/bs3Ys7d+/h48ePgmdBQ0NDuJYrh4YN6qNr166C2ZovXb6CoAxLnLdo3lypZ7a82jdMREREREREpG3+kwGTsrh37z6GDvsNyRkGAAwNDLBl8ybUq1dXQyXLWenp6QgNDUVEZCSSkpJgZmoKOzv7PDdLmrYKCQlBWFgYkpOTYWBgCGtra9jb23GwRQnR0dEICgpGQmICdHV1YWFuAUfHghqZ0SopKQlfAwMRFxuHtPQ0mJmawtzcHHZ2dmqfmUkikSAkJOTbvZ2YCAMDQ5iZmcHCwhz5FJhVStM0dS4TExPx9etXxMbFAQBMTUzg4OAgGEj4L4qJiUVwcBDiExKgq6MLUzNTWFtZqf360qZ7PK+KiIhAREQEYuPiYGRkBFsbG6WXD9MWvKcpM3FxcQgLC0d8fBySU1JgavLtd8bGJh8MDQ1zrBysW/OuvFy3alpee6bVlvooLS0NwcEhiI6OQlJSEoyMjGBmZgZLS0uFZm5Utzp16yE4OEQq7cqlCyhWrJiGSkTaIjY2FsHBwYhPSIBEIoGZqSnMzMxgY2Oj9b9zqampCA0NQ2RkBFLTvj0HOzg4yLV8PRGgve2QlJQUBAYG4sHDh5g+Y9aP9J3bt6F+/XoqPdb339eo6CgY6OvD0tISDg4OGu+DZd8wERERERERkXowYDILp0+fwe+T/xC8XWpqaoo9u3bmullUiIiIiIiIiIj+Sx4/foKevftIpZmbm+PFsydqf1GNiIhUY978f7Bz124AgK2tLS5fPA9ra2vNFoqIiIiIiIiIci2+ipiFDh3aY9rUKYL0+Ph4DP3tN3z48FEDpSIiIiIiIiIiIlls37FTkFajenUGSxIR5SJjRo+CkZERACAsLAzL/l2u4RIRERERERERUW7GgMlsDB0yGIMHDRSkR0REYuCgwfD398/5QhERERERERERUZbOnT+Py1euCNJ79OimgdIQEZGi8uXLhyaNG/3494mTpxAVFaWx8hARERERERFR7saASRnMmD4N7dq2FaQHBgVhwKDBCAsL10CpiIiIiIiIiIjypvT0dJw5ew7p6ekK7X/z1i3MmDFLkO7g4IAmjRsrWzwiIsphjk5OP/4/MTERr1691mBpiIiIiIiIiCg3Y8CkDHR0dLB0ySLUqVNb8JmX1xcMGjIUMTGxGigZEREREREREVHek56ejgkTf0fzlq2xc9duBAcHy7RfSEgIFixchGG/jUBsXJzg8ymTJ0FPT0/VxSUiIjV78eKF1L+joqM1UxAiIiIiIiIiyvV0JBKJRNOFyC1iYmIxc/ZsRIt0xtSuVQsjhv+mgVIREREREREREeUtqampKF3W9ce/dXV1UaliRVSsWAFly5SBra0tLCwskJycjMioSHz54o3Hj5/A7dEjJCcni+bZrm1brFq5PKe+AhERyWnosOFo164NqlerhgIF7ABI4OPji23bt+PI0WNS2546eRzlXV3FMyIiIiIiIiIiygIDJomIiIiIiIiISKtkDJhUVp06tbFh3TpYWJirLE8iIlKtUmXKIS0tLdvtypUti9OnTkBHRycHSkVEREREREREeQ2X5CYiIiIiIiIiojyrZ48e2LFtK4MliYjyABdnZ6xevZLBkkRERERERESkMH1NF4CIiIiIiIiIiOhnenp6GP7bMFy8dBne3t5y76+jo4OmTRpj9OhRqFihghpKSEREqjZq5Ai8e/cOHz99RnR0FGJj46CjowObfPlQslRJNG3SBN26doGxsbGmi0pEREREREREuRiX5CYiIiIiIiIiIq31+fNnPHv2HC9fvYKPjy/8A/wRERGJxMREpKSkwMzMDNZWVrDOZ43SpUqhVq2aqFWrFhwLFtR00YmIiIiIiIiIiIhIyzBgkoiIiIiIiIiIiIiIiIiIiIiIiIjyPF1NF4CIiIiIiIiIiIiIiIiIiIiIiIiISN0YMElEREREREREREREREREREREREREeR4DJomIiIiIiIiIiIiIiIiIiIiIiIgoz2PAJBERERERERERERERERERERERERHleQyYJCIiIiIiIiIiIiIiIiIiIiIiIqI8jwGTRERERERERERERERERERERERERJTnMWCSiIiIiIiIiIiIiIiIiIiIiIiIiPI8BkwS5VINGjVB8ZKlpf7z8/PTdLGIiEgNHrq5Cer83n36abpYpEarVq8R/M1XrV4j075+fn6CfRs0aqLmEhMRERHRf5Ey7da87Oix44Lz8seUaZouFhHJqHeffoJ7+KGbm6aLRZRrZLx/ipcsrekiERERyYTPcgSwr+O/Ql/TBdCk2NhYfPjwEb6+vgiPiEBCQgIkEglMTExgky8fXAq5oGSJErCwsNB0UYmIiIiIiIiIiIiIiIiIiIiIiIhICf+5gMmPHz/hzNmzuHHjJtw9PJCWlpbl9rq6uihTujQaN26EDu3bo0SJ4jlSTiIiUl52b64uXrQQXbt0VtnxIiIi8Evd+khOScmxYxIRERERERERERERERERERGRbP4zAZMvXrzE6rVrcevWbbn2S09Px7v37/Hu/XusW78BDRs2wIRxY1GxYkU1lZSIiHLKkaNHVRq8ePLkqSyDJUkoMDAIHp4eUmkO9vYoXZrLtBD910VGRuLlq1dSadZW1qhUie1wyp34m0dERERERERERERElLfdui2MS2vYoIEGSkJZyfMBk3FxcVi4aDEOHjoMiUSidH63bt3GnTt30btXT0ybOgUmJiYqKCUREWnCkydP4fXlC4oWKaKS/A4fPaaSfP5L7t67h6nTpkulde7UCUuXLNJQiYhIW7h7eGDwkGFSabVq1sT+fXs0VCIi5fA3j4iIiIiIiIiIiIgob8s4tgUAnz54iGxJmqSr6QKok9eXL+jStTsOHDyUZbCkuZkZypUti1q1aqJOndpwdXWFhYVFptunp6dj77796Nq9B3x9fdVRdCIiyiFHVRTk+PLlK3h6eqokLyIiIiIiIiIiIiIiIiIiIiJSvTw7w6SHpyf69R+IsLAw0c8d7O3Ro0d3NG/WDGXKlIaOjo5gG88PH3D16jUcPHQY/v7+gs/d3T3Qo1dv7Nu7R2WzkxHJ6vbN65ouAlGecPzECfw+cQL09PSUyufwkaMqKhGRUO1atfjmEcnM2dmZ1wsRERERkQZ17dIZXbt01nQxiIiIiIiISA58liP678iTM0wGBASg/4BBosGShgYGmPT7RFy/dgXjxo5B2bJlRIMlAaBUyZIYNXIErl6+iGlTp8DIyEiwTVBQMPr2G4CQkBCVfw8iIlK96tWrSf07ODgEt27dVirPhIQEnD13TiqtRvXqSuVJRERERERERERERERERERERKqV5wImk5KSMWLkaISGhgo+s7GxwcED+zFq5AjR4MfMGBoaYtjQIThy6CAKFCgg+DwwMBCjxoxFamqqUmUnIiL169SxIwwMDKTSjii5LPeFi5cQGxsrldatW1el8iQiIiIiIiIiIiIiIiIiIiIi1cpzAZNr1q7F23fvBOlWVlbYv3cPKlWqqHDerq7lcGDfHuTLZy347Nmz59iydZvCeRMRUc6wsbFB40aNpNJu3LyJUJFZiWV1JMNy3OZmZmjTupXC+RERERERERERERERERERERGR6uWpgMnPnz9nGrS4bMlilCxZQuljFC1aFMuWLhH9bM3adQgICFD6GEREpF7dM8z+mJKSgpMnTymU1xdvbzx6/FgqrW27tjAxMVG4fERERERERERERERERERERESkevqaLoAqrVq9VnRZ7DZtWqNJk8YqO06jhg3Rrm1bnD13Tio9KSkJa9dvwIL581R2LG0SExODt+/ewc/XDxGRkUhOToaVlSVsbWzh6OiI8uVdoaenl8NlisXbd2/h7e2DqKgoJCcnw8TEBAULOqBN69Yy5yORSPD582d8/PgJAV+/Ij4+Hrq6ujAzM4OjY0GUKV0azs7Oavwm2u3jx0/4+PEjvgYG/jg3VlZWqFOnNooWKaLp4iExMRGvX7/BZy8vREZGIjU1FZaWlihSuDAqV64ECwsLtR07MjISn7284OPjg+joGMTGxkJfXx/W1lawsrRC0WJFUbJECejo6KitDJlJT0+Hh4cnPn76hJCQEMTHx8NAXx/W+fKhUcMGsLe3lymf1NRU+Pr54fOnzwgJDUVsbCySkpJgYWEBaysr2NraokKF8rC0tFTzN1KdBg3qw97eDkFBwT/Sjh49hqFDBsud11GR5by7d1Xvctz/hesuJ4SHh+P9e3f4+vkhOjoaqampsLa2hq2tLQq5uKBMmdIaOYeaFhkZiTdv3sLb2xsxsbHQAZDPJh/KlCmDcmXLQl9fvuZjeHg43r59B28fb8TExMLIyAj58+dH6VIlUbp0afV8iZ8kJCTg3fv38PHxQVhYOBITE2FhYYH8+W1hb2+PihUqwNDQUK1lCA0Lw8sXL+Hj64u4uDgYGRkhX758KFG8OFxdy8HAwECtx1eVxMREeHl9gdcXL0SERyA2Lg7p6emwsrSElbUVChYsiPKurmo/n+qSnp6OgIAAfPr8GYGBQYiLi0NCQgLMzMxgZWUJGxsblHctD1tbG42ULyQkBG/evoOvr++Pet/W1hblXcuhVKlSctdXQUFBePv2Hfz8/REbGwtTU1MUKJAfrq6uKFK4sJq+xf9o47NFdHQ0Xr9+A68vXoiJiYWBgQHy5csHR8eCqFqlCoyMjHK0PKrE37ysJSUl483bN/j06RMiI6P+/3nCAsWLF0elihVhamoqV34JCQl4++4dPn36jMjISABA/vz5UcjFBVWqVJb7t1ReaWlp8PT8AK8vXggKDEJ8QgKMjY1ha2uD/Lb5UbFiBbW13dPT0+Ht7Q1Pzw8Ij4hATEwMkpOTYWxsDBNjY+TPnx9Ozk4o5OKi9ueHtLQ0vH33Dh8+fER4eDiSk5NhYWGBwoULoXKlSrCyspIrv+TkZLi7u8PT8wMiIiORlpYGWxsbODo6onr1amqvI4KCgvDuvTv8/f0QGxuH1NRUmJqawt7eDsWLFUOpUqWgq5s73ouOiYnB8xcv8OWLN2JiYv7/WcYaxYoWRYUK5WFsbKzpImpcYGAQ3D3cEeAfgJiYGKRLJLCxsYGtrQ2KFS2KYsWKabqICvPw9ISHuwdCQkORmJgIayurb+2s8q5wcXFR23G1+TlaHnnle+QWEokEnp6e8PDwREhoKBISEmBubg4nJ0dUqVwZ+fPnlyu/730mHp4eCAsLR1JSEmxsbGBvb48a1avB3NxcLd8jLz/LxcbG/mjnhod/e+Y3MDCAhbk5CtgVQIkSJVDIxUWtzxbJycl48/YtPn38hPCICEgkEuTLlw8F8udHlSqVkS9fPrUdOzAwCJ8+f0bA/z/XxSckwNTEBJZWVshnbY2yZcuiYEEHtR0/KwkJCXj16jU+e3khKioKOjo6sLWxgZ29HapWqaK26/1nKSkp8PD0hLe3N4KDQ5CQkAAdHR2Ym5vD2toaxYsVQ7FiRdXS9sgrz2Df29Senh8QFhaGtLQ0mJmZwcXZGeXKlYODg2b6en18fPHhwwcEfP2KuLg46ACwtbWFra0tSpUqCScnJ42US1F5ue2nTfJyv4+ytOHcJCYmfqs3fX0RGhaGhIQE6OvpwczcDLY2tiheojiKFC6ssvZKcnIyvL198NnLC2FhYYiNjf3RH2RlZQ27AgVQsWKFXD05Sl7pF4mNjcVnLy98+eKN6OgoxMZ+q/etrK1hZWkJZxdnlCtbNsf7kuURHx8PDw9PfPH+gpiYWMTGxkJHRwfGxsYwMzNFQYeCcHZ2grOzc64ZL9IUX19feHh6IiDgWxtAIpHA1NQUBR0cULJkif/sb2ZoWBg+f/oMXz8/xMTE/BiLtLaygpW1FUqWLJkj4z5iUlJS8P79+/+vb8ORkJAAAwMD2NrYoGXLFmqN5clOngmY/Po1EBcuXhSkm5qa4s/Zs1R+vNmzZ+LGzRuIi4uXSj9x/AQmTZyY7UDqQzc39OnbXyqtVs2a2L9vj8Jl+mPKNBw/cUIqbfGihejapbPCecbExODI0WM4e/YcXr95g/T09Ey3tba2Rv169dCndy/UqFFd4WMWLykMnvj0wePH/6enp+Pc+Qs4cPAgnj59Jhoka2FhIVPApLu7O/bu249Ll68gPDw8y20dHR3RpnUr9OvbRyuCJxs0agJ/f3+ptFs3rslUtlWr12D1mrVSaePGjsH4cWN//NvX1xe79+zF2XPnEBwcIprPrBnTUXTQQPkLLwNZrueXL19hy9atuHHzFhITE0Xz0dfXR726dTF06GDUqV1b6XKFhYXjxs2beOjmBje3RzLNKmttbY3q1auhd6+eaNiggVLHl+W8eHh4YOfuPbh8+cqPAdqMNqxfhxbNxTszJBIJnj57hrt378HN7RFevHyJ5OTkLMulq6uLUqVKolnTpujfr5/Ggklkpaenh86dOmHDxk0/0j58/Ijnz1+gSpXKMueTlpYm+HuULFEClStXUlVRAeSt665c2RQ0bNw0y+MdP3FCcLzM/Pz7IIuQkBAcPHQY5y9chKenZ5bb2tkVQKOGDTFwQP8cCezLirLtBll+M65du44du3bh0aPHSEtLE83Hzq4Aevbogd+GDc2yo0AikeDy5SvYtXsPHj95kmn7wdnZCX379MHAAf1V+hCYlJSEEydP4fSZM5m2Fb4zMzPFL7/8gq5dOqNZ06yvTXmdv3ABu3bvwdOnzyCRSES3MTc3R+tWLTFs6BAUL15cJcf18/MT3GdOTk64ffO6XPkkJSXh9p07ePDgIdwePYKHh2em3+M7IyMjVKxQAb/+2gGdO3WCkZF8HVhi7cCfuT16lO0238nSLnr79h1u37kDN7dHePrsGeLj47PcHgCKFSuKhg0aYNDAAUp3wMvS7j195gx2796LV69fZ3r+C7m4oH//fujXt0+WgVipqak4ceIk9h04gNev32S6XckSJTB0yGB06dJZpQM42vhsAQC379zB9h078eDBw0zrC2NjY9Sr+wvGjh2D8q6uMh1b7F7MiL956iNL+8Xd3R2bt2zFlavXMr3/TUxM0LZNa4wfPw6OBQtmeczXb95g85atuHHjJhISEkS3sbKyQvt2bTFh/DiVDp5LJBLcvHUbx48fx63btwV9FT/T19dHlcqV0aZNa/Ts0V0lgw137tzFiZMncfXatSyP/bMiRYqgcqWKaNiwIZo0biTToLksz7I+Pr7Yum0bzp47j6ioKNF8DAwM0LRJE0wYPy7b1Ui8vLywectWXLx0GdHR0aLbmJqaonmzppg86Xc4Ojpm+z1kFRISgn37D+DsuXPw8vqS5bYWFhZo2rQJevfqiWpVq6qsDKp07/4DbNu+HXfv3su0vWlsbIwmjRth2NAhqFix4o/0o8eOY+q06VLbdu7UCUuXLMr2uLJcN/JSpk8mMz4+vjhw8CAuXrwEH1/fLLd1cXZG48aNMWTwQK3oo8pOeHg4du7ajWPHjiMwKCjT7QoXLoyePbpjQP9+Sg+2afo5Wplr9mea/h6qoG394LL8bUJDQ7F9x04cP3ESISHi/aK6urqo+8svGDduDKpWqZLlMYOCgrBl6zacOXsOoaGhotsYGhigfv16mDx5EkqVLJnt98iKJp7lclJoWBiOHj2Gi5cu4e3bd1k+VwCAuZkZatasiYYN66Nd27awtrZWSTk+fPiILVu34dKlS4iNixPdRldXFxUrVMCwoUPQqlVLpY/5+fNn3Lx1G25ubnj85GmmbZ2fOTk5oW7dXzBo4AClry1Zfv+eP3+Brdu248bNm0hKShLNx8DAANWrV8PoUSNV0mf/s6SkJJw5ew7nzp/Hw4du2fZr6+vro1Kliqhfty7atW+n1AQReekZLDAwCFu2bsXJU6cz7esFANdy5dCnT2907tRR7QEe7u7uOHjoMC5dvpzpmNV3JUuWRLOmTTBo4ECtHavI6bafOsaQZelzUTdN9vtkpOpnBGXbUNp0bjITExOL4ydO4OLFS3j2/HmW/fjAt/ZK9WrVUL9+PbRv106uoO3U1FQ8fOiGe/fvw83tEd6+e5ft8fT19eFarhxat26FXj175Eiwf3b+C/0iMTGxuHnrFh4+dIPbI7ds+0OAb+M8VSpXQbduXdG6VUulgidV9SwXExOLU6dP4eTJ03j56lW2bVbg2zVerlw5VK9WFc2bN0PVKlXU+oLFocNHMGOmdCyVjY0N7t+9rZLf9evXb2DY8BFSaUZGRnh4/65cL1L7+Phi7759OH/hIr5+/Zrltra2tmjVsgX69OmN0qVKKVRuRfTu0w9ujx5luY2sY1uy/D4HfP2KG9dv4OGjR3j06HGmz5k/K1CgAGrXqoUB/fvJFQ8hRuz77tu7G7Vr1frx76fPnmHX7j24efNmpv3F5cqVQ7lyZZUqizLyTMDk0WPHRDtb27RuJfebnrLIb2uLNq1b40iGmcWSU1Jw4uRJhWYp0yYpKSnYvmMn1q/fkOnDfkaRkZE4c/Yszpw9ixbNm2PG9KkqfzPcw9MTf0yZhrdv3yqVT2hoKObNXyCYJTQrAQEB2LptO3bu2o1+ffvg94kT5J5pJDdIT0/HunXrsX7jpmw7EzQlKSkZ8//5BwcOHsq2sy81NRU3b93CzVu30KZNa/wz72+FZjJ59Ogx1q5bj4dubpkO7GQmMjISV69ew9Wr11CubFn88888VKxQQe4yZCcpKQkLFy3Gvv0HZGp0ZSSRSDD/nwW4ePFSlgMYYtLT0+Hu7gF3dw9s3bYdA/r3w+8TJ6h99hxldO3aRSpgEgCOHDsmVwPh1q3bUrNUAkC3bqqbXfK/cN3llPj4eKxZuw47d+2WuW4LDg7B4SNHcfTYcXTt0hmTJ03S2g42ZYSFhWPylCm4fftOttsGB4dg9Zq1OHHiJDZt2iD6sOHn54ffJ/+Bp0+fZZufn58/Fi1egmPHT2D71s1KP0hLJBIcOXoUy/5dgbCwMJn2iYuLx5UrV3HlylXUqlkTs2fNRNmyZZQqh7+/PyZNnoLHT55ku21sbCyOHD2Gk6dOY+SI4Rg3dozGZxgI+PoVS5cuw7Xr12UOevkuKSkJj588weMnT7B6zRpM+WMyOnXsqJ6CKmH9ho04euw4vL295d7382cvfP7shT1796Fzp46YPWumWtqE3t4+mPj7JLx89SrbbX18fTH/nwXf7s2NG0RnEHn/3h0Tf5+EDx8/Zpvfh48fMXX6DBw9dhybNq6X+23jjLT12SIsLBzTps/A9Rs3st02MTERV69dx7XrN9C3bx/MmTVTa2dy429e9lJTU7F02b/YsXNXtm2shIQEHD12HOcvXMSihf+gbZs2otvM+2cBDh06nO2xo6KisHfffpw9dx6rVixHvXp1Ff4e3z1+/ARz/56H9+7uMm2fmpr6o67esWMnpk2dgpYtWyh07M+fP2POX3Px4MFDuff98uULvnz5gpOnTsPQ0BDv375WqAw/27J1G1asXJXp4Px3KSkpuHjpEq5eu4ZpU/7AIJEXAVNTU7F6zVps3LQ52+skPj4ep06fweUrVzHv77+U/u1LTk7Gxk2bsXHT5my/y3cxMTE4efIUTp48hYYNG+Dvv/7UmkC6qKgozJw1GxcuXsp228TERJy/cBEXLl5Cr549MGvmTK0O2lGF8PBwLFm6DMdPnJT5uc/Xzw+79+zBwUOH0L9fX4wfN1Zr+6hOnz6DufPmZxls8Z23tzcWL1mK3Xv2YuOGdQoNyOaG52hZ5JXvkRudPHUKc/+en+lg8Hfp6em4c/cu7t67h6FDBmPKH5NF24e79+zF4iVLM33Z+7vklBRcu34Dt27fwe8TxmP48N/kLntef5aLiYnBmrXrsGfvPrn6rWPj4nD9xg1cv3ED/yxYhN8nTsCwoUMULkdqaiqWr1iJbdt3ZBtokZ6ejhcvX2L02HGoWaMG1q9bo9BLMwcPHcaevXvh7i5/IJK/vz8OHz6CI0eOolmzppg/72/kt7WVO5/sxMfH4+958wVjZmJSUlLw4MFDPHjwEK1btcSypUuUnuUxPT0dBw4cxKo1a2XuEwK+/T2fPn2Gp0+fYeXqNWjRvDk2rF+b/Y4/yWvPYLv37MWSpcsyfQnsZ2/fvcOMmbOwe88erFj+r9JBuWL8/f0x/5+FuHzlisz7fPjwAR8+fMCevfswYvhvGDZ0iNaMVeT1tp82yav9Pqqg6XOTlJSErdu2Y/PmLTL3FX7f7979+7h3/z6WLvsX/fr2wexZM7PcJyYmFgsWLcKVK1cQEREpVzlTU1Px8tUrvHz1Cus3bMToUSO1PgYkN/eLeHh4YPnKVbh9+47cMQpxcfG4e+8e7t67h+WFC+PPObM0+vLYyVOnsHDREpmC2H6WlJSE58+f4/nz59iydRt69eyB+fP+VlMpgTatW2Pe/H+kfvPDw8Nx89YtNG/WTOn8jx0XThTQvFkzmWM1YmNjsWz5Cuzff0Dm38ywsDDs238A+w8cxK8d2mPG9Ola08ZShUuXr2DL1m148eJFtnEyGYWEhPwYc6lVsyYWLvgHhQsXUnkZo6OjMXP2HJw/f0Hleatanvmlv3xZvKHcvXs3tR0zs6CYi5cuq+2YOSEwMAi9evfFkqXL5Gqk/OzylSvo3LU7XskwwCure/fuo1v3HkoHS7548RLtf+0oV7Dkz1JTU7Fj5y507todPj5Zv/WV26SkpGDkqNFYuXqN1gZLJiYmYuCgwdh/4KDcPwLnz19A1249EJDNmwdi7ty9i3v378vdSZ3Ru/fv0bNXHxw/cVKpfDKKiYlB7z79sGfvPoWD1tLS0rBz1265gyUzSkxMxKbNW9B/wCCEhWU9c6smFSlcGDVr1JBKO3fuvEwdQd8dPnpU6t8GBgbo+OuvKikf8N+47nLChw8f8Wunzti8ZatCdVt6ejoOHzmKrt17wNvbRw0l1Bx/f3906dpNpmDJn/n6+aFnrz74+PGTVPrbt+/QqXNXmYIlf/bhwwf06tNXofr5u+joaPw2fCSmz5glV8f4z9wePUK3Hj1x4+Ythcvx+s0bdOzcVaZgyZ+lpKRg9Zq1GD/xd43fT16fvXD6zFm5B9gyCg4OweQ/pmLu3/OVrsdUbd++/QoFS/4sNTUVh48cRZduPVTeJnzz9i26dusuU7Dkz96+e4fuPXsJOmLu3LmLrt17yBQs+bPHT56g34BBiImJkWu/n2nrs8UXb2906tJVpo7hn0kkEuzZsxfjxk/Q+L0qhr952UtKSsZvI0Zi67btctVN8fHxGD/hd5w+fUYqPTIyEr379pMpWDLjfr+NGIl79+7Ltd/PJBIJlq9YiV59+socLJmRj68vRo0Zi1Wr18i97/PnL9ClWw+FgiUzUvb5UyKRYPqMmVi0eInMAYbAt7p8/oKFghepkpKSMGLkaKxbv0Gu6yQhIQFTpk5Xqt0dGhqK3n37Y9XqNXJ9l5/dunUb7X/thNt35GvjqYO/vz+6dOsuU7DkzyQSCfYfOIhBg4dkG2SUmz158gRt2nXAkaPiL4JnJzk5GVu3bUeffv218vn73+UrMHHSZJmCJX/29etX9OnTD0/kbFMD2v8cLau88j1ymzVr1mLS5CnZBkv+TCKRYMvWbZg95y+p9PT0dMyYNRtz/54nVz2WmpqKJcv+xdp162Xe57u8/Cz3/PkLtG3/K7Zt36FUuyE5ORmenh8U3j8xMRFDhv6GTZu3ZBssmdGjx4/Rs1cfuQfOgW8z0ysSLPkziUSCK1euomOnLnj9JvMVBxQRFhaOHj17yxQsmdGFi5cwYNBgufpkMwoJCUHffgMw56+5CvcJfff23Tu5ts9Lz2Dp6emYPmMm5v49T+6/h7u7B7r36IWnz+TrE8zOpctX0KZdB7mCJX8WGxuLZf8ux/ARo5S6xlQlr7f9tEle7fdRBU2fGy8vL3Tu2g3LV6xUuK8Q+Dam+f599n0hYeFhOHz4iNzBkhlFR0dj4aLFGDtuvFbUJxnlhX6RFy9f4erVa0r3EXl7e2PosOHYuGmzUvkoaumyfzFp8hSF2nwZJSWpN17DwsIcLVs0F6QfP35S6bwjIyNx/bpw1TNZZzb2+vIFnbp0xZ49exX6zZRIJDh56jQ6dOyk8ravJl26dAnPnz+XO04mI7dHj9CpS1fcuXNXRSX75uvXQHTq0i1XBEsCeWSGyZCQENHBAWdnJ7UuQ1StalW4ODvD189PKv3Vq1eIiopSeiYWTfDx8UWffv2zXN7F1tYWDvb2sLSyRExMDAICvoouZx0eHo6+/Qdg+9YtqF5d8WX0gG9T7Y8cPVrQ2WNsbAxnJyfY2NggKSkJQUFBCAoOziSXb8GSAwYOynKJDGcnJ9jZ2yEtNQ1BwcGZnovvwR0H9+9V+Ww3mjJtxkxcvSb84XKwt0cBuwIwNTVFaEgoAoMCle54U9SkyVPw6PFjqTQdHR04OznB3sEeaalpCAwKynQ65k+fP2PgwME4fOiAypZfyZfPGvnzF4CFhTlMjE0QFxeHsLAw+Pn7i/5YJSUlYcrUaciXLx8aN2qo9PHT09MwfOQovHj5UvCZs7MTbG1sYWxsjKDgYAQGBio02KSvrw9HR0dYWFjAwsIc6WnpiImJga+vb6b3k9ujRxg5ejT2792jNW9vZtStW1ep6yk2NhbnL1xEl86dst03NCwMNzMEVTVp3DjH3lL5L1x3qvDq1SsMHDw0yyWKvtdx5ubmiI6Khq+fn+jgiI+PD7r37IUD+/agWLFi6ix2joiJicXY8eMF7RgLCws4OznBOp81YmJi8OWLN2JjYwX7R0dHY8SoUTh35gyMjAzh7e2D/gMHCQZDra2t4ViwIKysrRAdFY3PXl6iHQp+fv6YPn0mdu3cLvd3CQ8Px4CBg/Hu/ftMt7GysvpRjoT4BAQFBYkGiCckJGDEyFFYufxftG7dSq5yfP78GQMHDcl0QPjndkZqSiqCgoMFv1fnzp2Hg709zMzM5Dp2TjExMYFjwYIwNzeHmbkZEhMTER0VDW8fH6SkpIjus3vPHhgbG2HqlD9yuLTy09XVhaNjQVhaWMLCwgLQAWJjYuHn759pPeLp6YmBg4fg9MnjKlmWxd/fH4OHDEN4RIRUuk2+fChYsCAsrSwRHRWNT58/i9atAQEBGDdhIvbv/bY8z/PnL/DbiJGCjqb8+fPDwcEe5ubmiIyMxKdPn0X/hm/fvsWCRYux8J/5cn8XbX22CA4ORr/+AwXlMjExgbOzM2xs8iE5KRkBXwMEM0l/d+HiJezYuQtDBg9SqiyqxN882fwxdSpu3botlWZoYIBChQrB1tYWycnJ8A/wF13iTSKRYOr0GXB1LYfixYsjKSkZQ4b+hlevpGdGNDY2houLC2xs8iExIRG+vr6Cexr41j6bOGkyrly6IHf/QXp6OqZMm44TWXRAGxkZoZCLC6ytrSGBBCEhofDx8RFtK65esxbR0dHZzszwXUhICAYPHZZpQImenh4KFnRAgQJ2MDExRkpyCmJjYxEaFpbp0qbKWLrsXxw+Iv0yk56eHgoVckF+2/xIl6QjMDBIsDzad/8uX4HKlSuhTu3akEgkGD/xd9y4eVNqGwMDAxQuVAg2NjZISU2Fv7+f6HWSnp6O2XP+RLWqVeV+SzsiIgJ9+vbHx0+fMt3Gzq4A7O3tYWJs8qPPQqz+jo6OxvDhI7F+3Vo0btxIrnKoSkREBPoPHIwvX75kuo2joyPs7eygq6eL4KBgwfOM26NHmPzHFDRq1Ej9Bc5hN27cxKgxY7McDPr+bGVqZoqIiAj4+vqK9se8evUaPXr1wsED+9Uya5gi1m/YiPUbNgrSHR0dUSB/fpiYmiAyMhKfP31Gssg1HBsXh/ETJ+Hi+bPf2mUqoOnnaFXJK99D2+zffwArM7xAoKOjAxdnZ+QvkB/6evoIDgnJtE47eOgQqlSp/GMAcL7I7NO6urr/3+awgY6ODr5+Dcz0t2nlqtWoXaum0m3f73Lzs9yNm7cwZuy4LPuWTE1N4eBgDxsbG+jq6CIqOgpBQcFyB2xnJS0tHSNHj8Hde/ek0r+3OWxsbKCnq4fgkBB4e3uL3o8fP33CjJmzsHmTsH5UlIODA/JZW8Pc3Bz6BvqIiYlBYGBQpoP0X79+xaDBQ3Dm1CnR1QnkFZ+QgFGjxwr6ZL63sW1sbJCWnoagoCD4+Ylf70+ePMWSpf/izzmzRD/Pio+PL/oPGCjo3/qZgYEBCjo4wMbGBiamJoiOjkFYaKjSEwfktWewuX/PE7Spf2ZpaQknR0dYWVshLCwc/v7+iI//X7skJiYGw0eMxIljmechj4OHDmPW7DmZBgTo6up+e+7Klw+GRoYID4+At7e3aNvq5q1b6DdgEPbu3qn0bKaKyuttP22SV/t9VEHT5+bV69cYPGRolsGLRkZGcHBwgK2tDQwNDREdFY3gkBCVBJ9lZGhoCCcnR5ibm8Pc3BwpKSmIjo6Bt7d3pkGH5y9chI6uLlavXKHy8igjr/SLZMbCwgL2dnawsLCAqakp4hMSftSTYsF06enpWLrsX1iYm6PP/7F319FRXG0YwJ/dJLtxA2K4u7sEd7fiDkVLkVKg/dqiLdpipTgUL+7u7k5wl5BAiHuyu98fadJsZjZZTTbL8zun59C7OzN3Nrsz995573t79jBKHbSxadPmdAM17e3tkSdPHrg4O0MmkyE6OhoRERF47++fZYG4HTt2xO49e9XKTp0+jeDgYLi76//Me+++/YK+vpeXF2rXrpXhtq9fv0GPnr1Ev1/JkseTrKytEBgQiPf+/qLB3AEBAejdpx/WrV1j8Ssv5MqVC+7ubnB0dIRcLkdkZCQ+fvyEgIAA0feHhYVh8NBh2LFtq1GWxY6Oika//sJxwJQ2m7s7rK2sEBAQgMDAQNGxoMxmnhEsOrp9545og7lC+QomP3b58uUFHTGFQoE7d++irq+vyY9vTDExMRg8dJjoA82cOXOib5/eaN6sqaCzplKp8ODBQ6xbvx47d+1WuxBFRUVj1JjvcGDfHoOC00aPHafWKahTuzYGDOiHGtWrQy6Xq7036PNnHBXJ8hkeHo6Ro0aLBnc5Oztj+LChaNumNTw9PdVee/36DXbs3ImVq1YLGkcBAQEYNXostm7ZbLYBYdo6dPgInj79b3ats7Mzhgz+Gi2aNxc0ZpRKJa5fv5HZVcTOXbtw5crVlP93dHDAsGFD0a5tW8HgzstXr7B9+w6sXr1GcLF9/uIFJk2eigXz/9CrHgULFkDDhg3hW7s2ihcvBg8PD9H3RURE4uLFi9i8ZYsgOl+lUuH78eOxf+9eeHl5im6vrdVr1qr97Tw9PTBs6FA0bdJY8H1OSEjA+QsX4Z3BMW1tbVG7Vk00bNgQ5cuVQ+HChSCTCZdBU6lUePbsOfbt34/N/2wRBDjcuHET8+YvwPfjvjPgDE2nRfNmmDJ1mlow2PbtO7QKmNy1a7dgQPmrzp2MXsdklvK9y5XLA9u3bkl57dTp01j81xK199evVw/fjBhuUP2ApOw8g4cOFx20zJsnDwYM6I/GjRoKloFWKBS4dfs2VqxchePHTwj2OWr0WOzYvlX0N5GdTJ46FS9fvkr5/yZNGmNg//6oVKkirKysUsoTEhJw9uw5zJw9Gy9evFTbx8uXr/D333+jf/9+GDZiRMqDCKlUio4d2qNnj+4oW7as2hLTcXFxOHT4MGbNniPo7Jy/cAH7DxxE61bC5U41USqVGDVmrGiwpKOjI3r26I42rVujRInigqWunz9/ji3btmP9+g1qg5WJiYmY+MOPKFWqlNYd+sTERIweK549x8nJCcOHDUW7tm0Ev4+XL19i2/YdWLPm75T71eo1f6OqkR6KGcrd3R0N6tdH/fp1UapUKeTLm1d0yZX4+HjcuXMXO3fvFr0+rli5CjVqVM9wGYzU1we/B36YNFl9uYnSpUphyuRJWtU9Vy7x62RqNjY2qFq1Cho1bIhKFSugaNGisLOzE33vmzdvcejQIWzc/I9gYOn169f430+/6N22SG3suO9TMmKk/JZ69kDZMmXUvsOxsbE4dPgw5sz9XTCAeeXKVew/cBC1a9XEiJH/DcbLZDL07tUTnTp1RPFixdS2iYiIxM5duzBv/gJBRslt27ajS+fOqFixgtbnYdZ9izHfqdWrUcMG6NevL6pUriy4tj95+hRLlizF3n37Bfv5Y958tGjRHD7e3qLH4T3P/Gzbvl2tH1OyRAmMGD4Mdev6CgLV7/v5Ye7vfwjaU/Hx8Zj+2wysWbUSU6dNV5s8Ur1aNQwePAg1a9RQ66cm959mzJolCK78/Pkz5v7+B6ZNnaLTufy5+C/RYEkrKyu0aN4cPbp3Q4UKFQRLGQcFBeHAwUNY/NcSQfadv9euQ+XKldCyRYsMjz9j5izRB711atdGn969ULNmDY1LxIWEhODBw0c4d+4cTp8+o3P227QuXLyImzdvpfx/vrx5MWLEcDRu1FBwrXj58iUWLvpT8JtWqVSYMmUaDh7Yh2XLV+DYseMpryV/T3x96wgC4+/7+WHu3D9w7rz69yQ2NhaTp07FmlUrdTqXiT/8KBosaWVlhZ49eqBrl84oUaKE2muhoaE4dPgIFv35p+B+EJ+QgLHjvseBfXsEv//M8NPPk0QDi2Q2Nhg4cAA6d+6EAvnzq73m/+EDdu/egyVLl6U8gD90+AhCjBjwYg6ePXuOb0ePEX1gXrx4MQzo3x/169VFzpw51V6Lj4/HlStX8deSpYLJpC9fvsLEiT9i5Qr1zCBZ4dKly2oZpnLkyPHvGFMzwXcxKioKhw4fwbx58wWBKwEBAfj9j3mYPOkXvephbv1ofVnKeZizp8+eqq1GlCNHDgwfNhQtWzQXfN4fPgRg+YqV2LBRuNrGrNlz0KJ5M5w4eQpr161PKc+XNy9GDB+GRo0aCpZjTu/e9NPPk3Do4H5BX1Ybmd2XM5Xbt+9oDJaU2digS5ev0LJFC1SuXEl0fP7Nm7e4eesmDh06jLPnzhuUsWjx4r9w5ep/Y9MlShTH0CFDUK+ur2BZwU+fPmHjps1YsXKVoO4nTp7CoUOHdZ6kCST1EcuXL4/GjRqiatUqKFa0GJycxCfuBQYG4uix49i4abPaGB4AhISEYtSYMdi8cYPaGJA+Jk+eqpaVsWqVKvh60EDR9uC7d++wcvUa0WUV12/YgA7t26JcuXJaHzskJAT9Bw7SGCzZoH59fPVVZ9SuVVN0guPnz8G4e/cujh47hmPHj+uUfczS+mBHjh7Dho2bRF/zrVMHXw8aiBo1qqt9X+Li4nD6zFksXvxXyncgJCQUEyb+aHB9Ll2+jJ9/mST67Ldy5Uro37cvatWqKZh4Fh0djXPnzmPhn38KsrLeunULM2bO0npcyZgsve1nbjJr3Cc7ysrP5s2btxg48GvRa61UKkWb1q3Qrl1b0Wf/QNIqNrdv38bhI0dx8tRJvRL7ODk5wde3Dho2qI+yZcqiYMECovdBhUKBBw8fYu/efdiydavgWAcOHESN6tXRo3s3netgCpY0LpLMx8cHDRvUR11fX5QsWULjmEZMTAyuXb+Obdt34NChw4L7xvTfZqBSpUooWbKE6PbGFBISgtlzfxeU29nZoWeP7mjbpg1KlSop2rZXKpV48/Yt7ty+g1Onz+DsuXPpTsgwplo1ayB37txqzzwSEhKwd99+9OvbR+/97ti5U1DWoX070T5JagkJCfh29GjRYEm5XI6vBw1Exw4dBM/uAgMDsXfffvy1ZKlgzDIiIgIjvx2F/Xv3amw7G2rK5Elq8Qadu3QVvCf1s4L05Mun3XPJUiVLomHDBqhZswaKFysm6GsmCwkJwclTp7F58z+4dfu22mvx8fH45ttR2Ldnl8GJXGbP/V1tXLNgwQIYPmwYGtSvJ6hbTEwMTpw8BVc3V4OOaajsHeH1rwcPxLMJlS1bxuTHLlu2jOjSzg8ePMx2AZOTp0wVdJwBoEOH9pg6eZLGhx0SiQSlS5fCrJkz0KljRwwdPkLtAh4QEICff5mERQsX6F235HrJbGwwa9ZMtG3TWuN7c+bIgR49ugvKf/5lsugD2ypVKmPRgvkaBxvz58+HsWNGo327thgybLggWOTO3btYsHARvhs7RpdTMjup//bVq1fD4kULNV5UpVIpqlWrKvqaKaUOlixVsiSWLf1LYwOpYIEC+H7cd2jbtg0GDhosyOC1/8ABtG3TGo0aNdTq2DKZDO3bt0P/fn1RpnRprbZxcnJEs2ZN0axZU5w4cRJjx32vdqMMCQnFsuUr9Jo5m1rqv13rVq0wc8avGoM9bGxs0s0mUKhQQfTt0xsdO3TQ+JtPTSKRoGjRIhg7ZjQG9O+HH//3M44cVQ9YXr16Dfr17YNcuXJpeUaZx87ODq1btcI/W/5roFy9dg2vXr8WPLhLa3uaJWY8PT1Qt65xr/uW+r1LHXDz/MULwfvd3d11CsoRo1QqMfa77wUZjCQSCQYNHIBx343VGOhuZWWFKpUro0rlyjh06DC++368WsD8g4cP8ce8+Zg4YbxBdcxqyQEjtra2mD/vdzRp3Fj0fTY2NmjUqCGqVauKnr37ws/PT+31v9etQ0RUFB4/fgIg6e+3fOkSjX9DuVyO9u3aoVrVqujSrYfg+rxhw0adAiYXL/4LFy9eEpT7+tbBH3PnpDsDrnDhwvhx4gR81akTBgz6Wq2dEBkVhbHfjcO2rf9k2IEDgJWrVgs+GwAoU6Y0li1ZovGhZMGCBTH++3Fo164tBn09BP7+/lCpVIJB0EwlkaBGjero368vGjZooNX5y2QyVK1aBVWrVsGAfv0w8ttRagEwKpUKs+fMzfAhW+rvTVy8cBavo6OjwdcHAPD29kbv3r3QrWsXrQPv8uXLiyFDBqNPn96YOWu24EHC/gMH8PXXA7W+XmuS/Nt0d3PDsmVLUKliRdH32draokP79qhevTq6de8pCOJcuWoVzpw5mxI8ky9fPqxeuRwFCxYU3Z+TkyP69umNqlWqoEev3mpBkyqVChs2bdLpszfnvkXyQ05HBwfMnz8v3bZRsaJFMe+P31GhQgVMnaaeZTM2NhZbt27D6FHfim4rl8t4zzMzqYMlRwwfhtGjvtV4jStTujTWrFqJH//3k2CG/tmz57Bu/YaUNqSVlRWmTJ6E7t2EA2HAf/2nfzZtwpChwwSDyLt278GE8d9rnaX20uXLWPTnYkF5/vz5sWjBfJQuXUrjtskByx07tMewEd8IltP+30+/oFLFSukG00RERIourzz++3EYMvjrDOvv5uaG2rVqonatmpg4YTxu3bqtFlSiqxs3/gvK6tSxI6ZPm6LxAXPBggUx74/fUahQIcxfsFDttafPnmHN32uxcNGfKWUjvxmBb0d+k/73ZPVKTJj4o2Ag+OzZc3j9+o3Wky82bdosuuJDrly5sHzpXxqDB1xdXdG9W1e0btUS48ZPEDx4Dw8Px3fjxmPjhnVa3dON5cjRYzh8RPg98fHxwcoVywSB+ymve3tj+LChaNO6FYYMG57Sxrx8+YpJ65uZYmNj8c23o9QyMgFJ7e7vx32XbqYWmUwGX9868PWtg7/XrsOvv81QC9g6dfo0NmzciF49e5qs/tq4lmop7caNG+GPuXM0Drw7ODigc6eOqFfXF7379BMEUe/ctQvjvhur9TXSnPvRurCU88gu7t37b4m2unV9sWjBfI3fOW9vL0z65SeULVsG34+foPZacHAwVq1eg/XrN6SUfdW5E6ZOmZzhvalAgQJq9yAg6d506fJl1KpZU7sTycK+nClERETi29FjRIMlq1WtitmzZmS48lO+fHmRL19etG/XDiEhIVi3fgOi9Fz+M7kfIZFIMHrUtxgxfJjGYNZcuXJh9Khv4etbBwMGDBIkcVi3foNOAZNubm4YNnQIevXsqXXQs6enJ3r36onu3bpi6bLlmDdfvQ9148ZNHD9+As2aNdW6HmKSPxcbGxtMmzIZX33VWeN78+TJg8m//Iya1avj29Fj1JY1V6lUWLdhI+bO1j5g8of//SQ6OcPL0xPz/vg9w2cYOXK4o0GD+mjQoD6mTpmM3bv34MChjJcPtLQ+WFhYGCZNFk7gkkgkmDLpF42ZueRyOZo1bYJGDRvg9z/mYfmKpKCY1IHF+gj6/Bljxo4TBKU7ONhj+rRp6T4ftLe3R7NmTdGkSWPMmft7Sp2Sbdi4CfXr1cvUDOxfQtvP3GTWuE92lFWfTWJiIkaNGSO6+kbRokUx/4+5gsmBaXl5eaJ582Zo3rwZoqOj8c+WraLj8WLKlCmN/v36omWLFloFpFtZWaFsmTIoW6YM+vfvh7Fjx6n1cQBg3vwF6NSxo2CialawlHERK6kUjRs3woB+/VC9ejWttrGzs0NdX1/U9fXFjb43MfLbUWqTSePj4zFv/nyjZvfW5NDhI4JEBO5ubti4cT2KFS2a7rZSqRQF8udHgfz50a5dW8TFxWHfvv2ZMnlUIpGgQ/t2+HPxX2rlO3ft1jtg8snTp7h/X/j71CZh0bz5C0S3LVK4MJYu/QsFCxQQ3c7T0xNfDxqItm1a45tvR6kFEQNJq9xNmjwZf/w+V7uT0FHRokUyfI8xnm3Z29ujd6+e6Nu3j8bPIi03Nzd06tgBnTp2wJat2zBp8hS1iXKvX7/GP1u2GpxVOfXzoIED+mP89+M0tomTYjS0fxZsKpk3UmpCb968ES1P7yGBsWg6RnrLDZmjs+fOYfsOYZT314MGYu7sWVoFTgFAtWpVsW7tGsFN+OChw3j4ULhsui4kEgkW/7ko3c6QJtdv3BANbC1dujRWLl+uMVgytUKFCmHt32vgLTJbZvmKlfjwQTyVbXZTtUoVrFm1UmOwpDnIly8f1qxZpVWGjOLFimHd36vhJhKdPnX6dNHUzGK+GTEcv8+ZrXcQRKNGDbFm9UrBTWHHzh2CxpO+WrVqiXl/zNUYtJYRa2trHD18CL169tT6N5+aq6srFi2cj8ZpglDjExI0zk41B2JZIdMGQ6Z14+ZNQeaXjh06GDwjO60v4XtnKv9s2YoLFy8KyidP+hkTJ4zXOitwixbNsXjRQsEA+Np16xGUJitTdiSVSrFi+VKNwZKpOTk5Yc7smYLv+cePn7Dk36X2HBzssXnjBq0a/T4+Ppg2ZbKg/Nr163j9Wrxtl9bTp8+wKE0nDkj6Xq5ZtVLr5QKKFi2CLZs3Cu4Vt+/cwclTpzLcPiQkRPBgC0gKQl+zaqVWDzOS71fuZnD/rVWzBjauX4fGjRrpFVhRtGgRbNywHnny5FYrf/ToMS5eEga3ZoVtW//B0CGD9cpSaGdnhymTJ6F3L+Fg9Jq/1xqhdkmd3o0b12sMlkzNx9sb06ZOFpTfu3cfO3ftApAU1L9ty2aNwZKplSpVUnQi0JEjR7V+sJgd+hYymQzr1v6t9bKUffv0RiuRDrzYeWY23vN0N+rbkRg7ZnSG1ziJRILJk34RXM+ApOXqks2a+ZvGYMnU5HIZ5syeCcc0QUMxMTE4dOiwVnVPSEjA9+MnCvoxhQoVxM7tW7UeB3FycsKaVStRuXIltfLw8HCsWr063W2vXL0iyIxSrWpVrYIlxVSsWAHz5wln4OuqU8eOmD1rhlYPP74ZMRwVRa6xv82YmXJuY0aPSjeoNplEIsHUKZNE+6fJ1+GMREdHY87vwizFLi4uWLtmlVaZlpycnLBowXz41qkjeO3qtWs4cDDjh//GolAoMP3X3wTlbm6uWLtmlcZgydTy5s2Lv1evQt48eUxRxSy16M/FgkkFVlZWWLxooU6D0/369hENfPtz8RKDMqgZU/NmzbBk8Z9aZSnIlSsXFsz/Q3DfioqKxkEtgleSZYd+tDYs5Tyym9q1amHFsqVaBeh27NBetH24YOGilGCALl91xswZv2l1b/p25DcoL3K937FTu3sJYHl9uQULF4ouG9m0SRP8vWZ1hsGSabm5uWHUtyPx4w8TDarX/378Ad+MGK5V5s/KlSqJLml+9do1rcc+AGDpX4sx7ruxemWItba2xjcjhosG4BmrDyuRSLBwwfx0gyVTa9asqeg979Chw1r3O48dP66W/SpZoUIFsW3bFp0TPtjY2OCrrzrj79WrMnyvpfXBlixdJgj+BIBffv5Jq2VMra2tMWH89+jbp7dR6jNt2q+C+tjZ2WHDurVaPx+USqWYMP57fD1ooOC1tMHDpvYltf3MiSWN+xhbVnw26zdsFKy4AQCVKlXEls0bMwyWTMve3h4D+vfD73PnZPje/PnyYc+unWjfrp1e2Xt9vL2xZvVKlCunvpRvcHAw9u7dq2GrrJGdx0UAoFOnjli25C+tgyXTqlypEjZt3AAnJye18lOnz+DV69d67VMXabP8A8CE8d9nGCwpRi6Xo3PnTqL3MVPo1LGjoD3i5+eHx48fa9gifTtErg+VKlXM8PmEv78/Vq4Sjkvmzp0ba/9eo1WAoKenJ1avXIFSJYVLTO/Zuw+3bt3OcB/mbNrUKZg86RetgyXT6trlK8wTCRpdt3696PL2+hg0cAB+/GFitlih1yICJj9oWHM9Z46couXGlCNHDtHygIBA0XJztXTZckGZr28d0c58RsqULi36kNXQznfPHt3RsGEDvbZdu3adoMzGxgbzfp+jU9pdH29vzPztV0F5YmIiNmzcqFfdzIm9vT3mzJ4pmurcnMz4bTpyavjtiSlUqBAmjhcOCL179x5nzpzVah/6LH2TVqWKFQXBFVFR0TgqMrCjK09PD0yfOsXgjCGGnqeVlRWmTZ0CW1tbtfLde/YYtF9TqlChPIqmaazu2rU73UaBWEBlZxMsx/2lfO+MTalUYsVK4eBm165d9Jpt26BBffRK8xnGx8dj06bNetbQfAz+epD2mSqQFNSXXgbtH3/4AUWKFNZ6fw0a1EeRwsL3p52tqcmKlasEv9XixYthzqxZOv9+fHx8MH3qVEH56jV/Z7jt9h071bIBAEm/3xm//ap10CaQNLvzBwMf3BiDMa49OXK446f/CZdg2r3bPAaRjHGOE8Z/D09P9Uk3Bw8eQlyc4YPUP0ycoNNASr26dQX3stRmz5wpWNYpPV27fCVYUi4mJgb37t/XsIW67NC3+H7cdyhfXvvMJQAwauQ3grIPHz6IPsTNLLzn6a5y5Uo6LYMul8vT/SzbtmmNDu3ba72/XLlyoV27toLyq9e0u/ft3bdfkJ3Z1tYWK5cv1zkI3MbGBvPn/SGY+LJ123a1jGRpiU0WbNCgvk7HNrZ8+fJhymTtl+yVSCQY2L+fxterVKmM4cOGar0/W1tb9BJ5mHxNy7/rzl27RJc4/2HCeBQvXlzreshkMsydO1twDQfEx0VM5fTpM6IrfPwwcSIKFSqk9X48PDzw6/RpGb8xG4mIiMRGkWvq6FHfar0CRmq9evZEwwbqY2WfPn3Cvv3CScOZzdvbGzNn/KpTf7F48eKimc6uX78p8m5x5t6P1palnEd24uLigt/nztbpoc6ggQM0vpY/f3788rP22TwlEgkGDhQGzmh7L0neh6HMpS/38eNHbBSZgF2oUEH88fucLMvm1LhRQ/Tv11enbbp16yroOwJJSR60ZYy/7cAB/VE6TRD2tevXjdKf6dO7F5o2yXgybmpDhwwWPIeIjY0VzSgkRizoTS6XY/Gfi0y6fK6l9cHi4uKxfYdwrLtO7dro07uXTvuaOGE8ChXKeKJmet68eYtDh4WTyX6bPk2n5dqTjftuLEqXUp9U5vfggdpqZqb0JbX9zI2ljPuYQmZ/NnFxcfhriTC7n7ubG5Ys/hMuLi461UVXxriH2tnZ4ddpwr7pLjN69pndx0WS62SoAvnzY9S3I9XKlEol9u7dZ/C+M/Ih4IOgrEED/WJbMlu+fHlRtUoVQbkuk7eSKRQK7N0n/Lw7d8r4Ofq69RtEn8/PnPGrThOHnJyc8Mfvc2FjYyN47e9MHB8zBWP8Tlq0aI4madru7969V1udSV8lS5TAuO/GGryfzGJeEQ56Sr1EW2rOzk6i5cbk7CQchAYgmlLaXN29d0/QObCyssJPP/6o9w+uV88eggCBffv3IyYmRq/92djYYKRIY0wbgYGBogOBfXr3QmGRII2M1KlTG40bNxKUb9m61SgPyLPSV5076TwzN7M1adIYNapX13m7Tp06is4k2PzPP8aoltY6d+ooKLt165bIO3UzaOBA0YdiWcHDw0MQUPXu3XvRWarmokua2c8BgYE4KzITCEjK/nLg4EG1surVqmW4hHdW+hK+d6kdOXJUkH3a0dER40QCbrQ1bMhgyNI0rLds3ab3/syBnZ0dBn89SOft0jaik/n4+Ih+1/TZn5/fgwy3CwwMxD6RTtePEyfq/eCkefNmKF5cPePRlStXM8z68M+WrYKyFs2boUrlyjrXoUP7dihTxrAlnc1FwwYNBBkzb902/NpjLuzs7NCqpfrs6vj4eDx4kPH3Nz3e3t6C+5I2moi0T4GkmZt16tTWaV8ymUx0yT1tfpvZoW/h4ZFLdAAvI4ULF0ZJkRnvqZdwzGy85+lu5IgROk/20HTvk0gkGPnNCJ3rIJbZ2e+Bdg+GxWZZ9+/fT+vljdLy8fYW3L8jIyPTzeYmlplM26VyTWXw14N0znjeoEF9jUEx+nxPxIIE/B48gEqlynDbDRuEASFlypTWa1JWzhw58K3I9/LW7du4e0+Y0cMUNv+zRVBWulQpdOzQXud91a5dS/BQODv7Z8sWwW8ob5486QZdZWTkSOHfe+u2rL9ufz1ooCCzhzZat2olKNN20oYxmaofndks5TwyQ4/u3ZArVy6dtilXtiy8PMUf3Olzb2rYoIHg3vT+/XuEZPKzBnPoy23Zug3xqZaJSzZr5owsXeVkzOhROm8jlUrRorlw+e3MvrZJpVLRe/FNA7PsyOVyDB8+TOftnJ2d4esrzIytzedy7dp1PH78RFA+8psRemVx0oWl9cGOHDmCkJBQQfn//veDzvuSyWSiiSt0sXrNGkGgRKVKFdG2bRu99mdtbY1hQ4cIyjOrrfQltf3MiSWN+xhbVnw2Bw8dQnBwsKD8559/0mmCd1YrVaqkIAD73r37RsvIZqjsPi5iTB3atxOc181M6ANFRAgnH2f1eJkuxJbL3rN3HxITE3Xaz9mz5/Dxo3pMgK2tLVq2aJHudnFxcdgmkrCoWdOmOiV+SVa0aBH07NFdUH74yBF8/PhRZIsvi+hYwe3bBu935MhvRANVzZVFBEzGxsaJluszKKcrTdkJ42JjTX5sY9kvMvPIt04dnTJEpWVra4sWzZuplcXHx+PO3bt67a9Rw4Y6ZRRM7cLFS6IXcm2WTNOkR/dugrKQkFDcu6ff+ZmLrl27ZHUVMtSls+4BBEDSw8xOIhf+c+cvZOpyBSVKlBCkQr99+45B+5TZ2KBD+3YG7cPY0qamB4BbBp6nKbVv11Zw89a0LPeBAwcRFRWtVmaK7JLG9KV875KJzaht366tTpn+0vL09ETNWuoN8oCAALx7907vfWa1pk0a6zV7s4SGLEdinVCt9icy0PLy5csMtzt85Kjg4UmRwoV1DgxLq11bYdav9DJevnr9Gq9evRKUa7sMVVoSiQRfmfk1RVtWVlaC7BUvX77SONkpOypbVni/u21gp1L/35L4b1Pf71NJkf29eJHxbzM79C06duig1xI8AFC2bBlB2UuRa0Bm4T1PN15eXqIPZTOSP18+0aXkK1eupFO2vGQlS4rc+7T4fT1+/BhPnqg/GJZKpeirY+aXtMQyZF67pnlGsdjkVEPbloaQ2digvUjWzozY2tqKTnry9vbWqz1RoEABwfckMjIyw4lj/v7+ePrsmaC8W9euegead+rUUXTliLNnz+m1P13ExcXjwoULgvLOnTvpfT5duujXrjJHYtftHj26631fApICttJmbb97916WTuq1trYWfdiijbJlhPfaV1r0D4zNFP3orGAp55EZ9B3bKS7SbpbZ2KCdHsE9dnZ2yJ9POAkis9ub5tCXE8swV7lyJVQSWToys1SsUEHnJUOTifUjXr18ZWCNdCc2ZmtoH7ZJ48Z6P7sRu+a/1OJzOXhI+P2wt7cXfShubJbWBzt95oygrGKFCnoHntavX0/n4PNkKpUKBw4cFJTrmtU1raZNm8DRwUGt7JoRMihp40tp+5kbSxr3Mbas+GwOiVyzfXx80Kpl+sFT5ijtWHB0dLRoAH9my+7jIsbm6uqKvHnzqJXdvXvP5IGb4uNlt016TGNq0aK54O8XFBSk81jSjp3C5bibNW2S4aqvd+7cRWhoqKDc2DE9iYmJuHjpkt77tBTlRJ5tGRowmTNnTjTSc8XgrGIRAZNKDZH7hjQ4taXpGGKzH83VlavC1PPNRZa/0VUVkbS9N25ov4ROajVr6p5RMNnNm8Jjli5dGgUL6r80QJ3atUWXY79xM/vO0HZ3d0fxYsUyfmMWcnR01OsBZ7LWrVoKyuLj4/Hw4SNDqqWztIMnb96mn7ksIyVKloBbmlnfWS1HDuEAUdqZt+bE3d0djRqqL4Fx4uRJfP4snPW2dft2tf93dHQUBHGYoy/he5dMLLhNbFk3XYmlo9f3vmYOqlatqtd2efLkES0X+3y0kVdkf2KZq9K6evWaoKy5EX6LVauK/J1F2hLJxDq8Li4uqF2rlt51yGimXXaS9n6gUqnw5u3bLKqN8Ym1B18beH7V9Pxtiv2WAP1/m3nyivw2IzP+bWaHvkW1avp9xkDS0oppaXPNMhXe83Sj7+9BIpEgt4+P0faXM2dO2NraqpXFJyQgLk58MmiyKyL3vsqVKun9QDJZ6dKlBAOi6d37ihYRPjzds3cvzp4zfTCemNJlyuidaUqsXaNPhmgg6XsitvxjRtcIsXEEKysrgx4eOTs7o0H9+oLyzMio8ODBA9ExsZYthJm1tFW/Xj3BQ+7sKCIiEo8eCccfmjczvA2b9j4ZHx+Pe/czJ6OomDKlS+udScPb20sw3qrNNdIUjN2PziqWch6m5OGRS++VQ8Ta4Qbdm8Ta4VnQ3szKvtynT59Egw+6dsnayf4G9SPymUc/Ioe7sA/75o1hf9fqxu5fadHvPH9BuDJQi+bNM2UlHEvrg4klOWhhQLvNyspK7zGAJ0+fClbvk8vlqF+vnt71Sa5TxTTB1u/fv0dAQKBB+83Il9T2MzeWNO5jbJn92SgUCly6fEVQ/lXnTrCystK7LlnFXJ99ZvdxEVNIO24fFhYmGoxnTGLjZdOm/2ry4xqLg4OD6D1Kl2W5w8LCcOLkKUF5Jy2W4xYbs3J3d0ft2vo/aytcuLDoim43s3FMj7GIPdsytF9QrWoVvZKBZKXsVVsNxGbNA0kR666uriY9dmSkMLUuANjbZ92yELqIjIwUDRYrV76cwfsWGyx69PixXvsqW0YY4awtsVnTFSuU13t/QFIHq1zZsjh1+rRauTHS1GYVsZlB5qZUyZIGpfDNmTMnvL298eHDB7Xy23fuoLwe3/mXL1/i/IWLePz4MR4/eYKgT0GIjIpCZGSkTlkro6KikZiYqPcNRGwmrrHExcXh3PnzuH/fD48fP8HLV68QER6OyKgoREdHQ6lUar2v8PBwk9XTGDp37oTDR46k/H9CQgL27N2LAf37pZS9ePFC0Ihq3apVpi4F9CV87wzx9Okz0eUdxGbK6Eqs4/jo8WOYZ57NjBXVM9ubg4MwwxYAFClSRM/9CR9+a9OBFhugLl/ONO2Xx480t19u3xFmuCtVqqRBAz7u7u7Ikyc33r17r/c+jC04OBinz5zFo0eP8PjxE7x7/x5RUVGI+vd+oIvwcPMbZExMTMTly1dw+84dPH7yBM+fP0d4eETKOeqytEqEgfc7fX9L9vbC35K1tbXek4T0+W1ml75FUQOWaHN01O+aZQq85+nOkEynYhkmDdmfg4MDYtOsTBEREaFxfAMArl0TBkwa4/dlbW0NLy9PtSyyr1+/RkxMjGg7t2LFCnB1dVUb8E1MTMTAQYPRqWMH9O7VC6VLlxJsZyr6tmkAwF6kXWPo3zUtsSWZUhObfFGoYEGDH/hXqFBerX+TdCzTZ5W7fUd4DB8fH4OWWrOxsUGJkiVwPZMyAZnK9Rs3BG0KNzdX5MuX1+B9p82eASS1YfV90GWookX1a88kc3R0FNzjMrpGpsdc+tGGspTzMEf6tsEB8TaCIfcmfe4l6cmOfTlNy3tWE5ngmJkMubaJBZEb0o9QqVS4cfMmbty4iSdPnuDp02cIDQtDZGQkoqKidFo6MTzCsD6sYf0r3T+XyMhI0SyUmfH9sLQ+WEhIiGigj6HnI7YahzbE+jtFixYRvc7qKk+e3IKyR48fwcvL0+B9a/Iltf3MjaWM+5hCZn82z54/F21viCUtyEwREZE4e+4sHjx4iMePn+DNmzeIjIpEZGQkoqNjdMpEaOh91Biy+7hIevw/fMDZs+fw+PETPH7yGAEBgSntnbTjahkJD48waSKYBvXrCbIrPnz0CM1btsbgrwehQ/t2ZpuIJlmnTh2wc5d6gOTJkycRGhqqVdzVvv37BX1THx8f1KpZI8NtxeJsypUtq/PS8GlVrFAB9+/7qR/rlvBY2Zmf3wNcvXoVj588wZMnT/E5+HNSny8ySqdEf4bGcpQx09iB9FjEqIidhuDE8PAIkwdMahok0HcWdWZ7/vyF6APg0JBQgy8U/h/8hfvVM4Le29tL73q8ey8MNihVyvCHN6VLlxIETPq/F55zduHtJZzxYW70XfIktZIlSggCJnWZ/aNQKLB123Zs/mcL/Pz8Mt5AS+Hh4Xov2+EtMlvHUC9fvcKSJctw5OhRjYHhujL3gMm6vnXg5emJgMD/ZpZu275DLWBy67btgu266Lnsri6+lO+dMTx5KsxA4OrqiqdPhcsc6iooKEhQll1mholxcXHVa7u0GbGSubrqvrx30v6EDz3j4tPPHhP0+TM+f/4sKI+OiTG4/SL2UCEknb/ze5GgxpJGuF+VKFHCLAImL1y4iFVr1uDChYs6PXBJT7gZLcn98eNH/LV0GQ4cOCj60EMfYWGG3e+M+VsyJNhG7LeeUWan7NK3cHXR7zMGAFtbYd8zq5a94j1Pd/r+vgDx34S+91JN+8voN/bkyVNBmZVUapRBPmtr4cS00NAw0YBJmUyGQQMHYO7vf6iVK5VKbNu+A9u270C+fPlQv149VK9WFZUrG54FMz0uhvym5cK/g7G/Jxn9XcXHLErqXYdkYkGrYWFhiIiIzHAZJEOIzUYvKbJcra5KliyZ7QMmnzwRXrdz5sxllN+wWH87vTasqRnyuwQgeu3RNcOkOfaj9WEp52HuDGsfirURjHtv0ifDanbuy716/VpQ5u7ujrx5DQ8yMoSrAW0/OzuRv2sGYx9iIiIisGzFSuzevUcwxq0vQ/uwLga0nUQ/lwy+769fvxENZClf3rAkGdqwtD6YWDsUMPw5jL7jYmL9HRdnF6O0lWJFvlem/ny/pLafubGUcR9TyOzP5tUr4T1dKpUaJdBcH/fu38eyZctx8tRpo2WwN/Q+agzZfVxEzMFDh7Bu3QZcv3HDaEtph4Wbti3brFlTFClcGM+eP1cr//TpE379bQZmzZ6DypUroU7t2qhWtQrKli2r96RAU6lerRry5c2rllk+PiEB+/YfQO9ePTPcXiwbZccO7SGRSDLcVuxZm1HGx0Tigt77Z9+YnmRxcXH4e+06bN+xQ20SvCEMjeUw19iB9FhEwGQuDbPUMyOiX9PyAI4O2SNgMiQ0RLS8R6/eJjleWKh+NyInJye9tlMqlaLBXh4eHnrtLzVPkX2Y+kZrSqZ8YGIsHh6GP2TLmUt4vdB2dvSDBw8xYeIPePDwocH1SCsmJkbvbY35t1MqlZg3fwFWrlyl04wDbURH63+OmcHKygodOnbAkiVLU8qePHmCO3fuonz5ckhMTMSu3XvUtilatKhe2Ul18SV874wpNCRUWBYais5duprmeHre18yB2KC0YfszXqbVjPq/Yn9nABg1eozR6pBaWDoPhcTu/WKp7HVljH0YIjg4GD//MlmQmcoYog249hjT2nXr8ccf8xAZFWXU/UbH6JalJS1j/paMngE5g99mdulbGCM7RWrGGrTTFe95uhMb3DeEse+lGX2XxB6ALV+xEstXrDRqPZKFhYVqnLz49aCBuHz5Cs5fuCD6+ps3b7Bu/XqsW78eAJA7d25UrVoFNapVQ506dQyaFJmWsa91xv6eqDK4eIaLPFwx1ZgFAISHh5m0LS82Fpcrl+Hno2nsLzsReyj/9OlTk12302vDmpqx77WAbvdbc+1H68pSziM7MH4bwcj3Eh2+/5bQl0s9mTmZt5fx2g760pS4Q1+6diP2HziIqdOmi04gNUSMgX1Y+0zudwaKfD8AwCsTviOW1gcTa4fKZDKD24piS9ZqQ6y/c+HiRVy4eNGg+mhi6s/3S2r7mRtLGfcxhcz+bMSu2U5OTqJZCE0pNjYW03/9DVu2btNp5TxtmEO7OruPi6T29u1bTPjhR1y5ctWodQCAGBM/p5ZKpVi4cD66dOkm+swhMTERV65cTTk3GxsblCpZEtWqVUWNGtVRs0aNLA+glEgk6NChPRYsXKRWvmPnzgwDJp89e467d+8Jyjt26KDVscNEgvU8PQ0fT/IQ2UdERASUSqXB2SuzysVLl/C///2sFthqDLquQJCWvjFdWSl7fgPS8PHxES0XS8tvbJqidcXSoZujzM4Som/acn1v9OHh4aKNNSeRtOG6chT5wZvDLBJ9ZeaSwvoyRuZWJ5F9hGsR6Hrz1i306NXbJIPUgGEdLmM1XBMTEzH2u+/x15KlRg+WBLJHp/KrTp0Es1y2bU/KKnny1GnBTF9TZ5f8Er53xpbZM2k1TZwg0wrVEJRlKum1X8SC7sWWJ9GV2P0qswQFBaFn774mecAGmMf9YNbsOZg6bbrRgyUBZPhwx5Jll76FpeA978uT2Q/A0lsyydraGsuXLUGXLl9pta/3799j9+49mPjj/+Bbrz669+iFnbt2Gy3jVXYmNvnCKH1fDYOUph63iBAZ4DZG2yi7rOSSHt4nM4c596N1YSnnQZnLUvpy0SL9NGcX/bPnW4L1GzZi9JixRg+WBHQP3MxqUSIPcq2srIzS3siIpfXBxLIImbIdmhFLaytZ2vkQ6UMs+MbFgBVx9K3DwK8HY/M/W4weLAmwXW1ML1++RLfuPU0SLAnoFripr+LFimHbti0oXKhQhu9NSEjAnbt3sWLlKgwcNBjVatTC+Ak/wM/vgcnrmR6xjJD37t3PMKP29h07BGVVq1RB/vz5tDquWDZ7U7VLNCVdyw6OHjuOgQO/NnqwpDEYO7lAZrCIDJNFixQRLb93/z7atG5l0mPfv39ftLxY0aImPa6xpPcAxBQUJmiIpCc2VjzFs1zDcqK6EEspbQ6zSCyZXC4zwj6EMzNiYmLT3SYoKAgDBw3W2OH09vZGpUoVUbhQIXh5eSFnjhyQy+WQy+WwthZeZoeN+AafPn3S7wRMaN78Bdi3f7/oazKZDGXKlEa5smXh4+MDLy9PODg4pJynBOoNp1OnT2PxX0syo9pGlT9/PlSrWhVXrv7XGN9/4CB++t+P2L5dfTluGxsbtGvb1mR1+VK+d8aW2QNDSkXm3tcoSWa3X9IbSImPFy47YmNj+P1KJjN8H/pQqVQYNuIb0WWDgKQlnitUKI9SJUvCy8sLHh4esLOzhVwmF63zn4v/wukzZ0xdbZ1s2vyPxmxs1tbWKF68OCpWKI/cuXPDy8sLTk5OkMtlkMvlkErU55v5PfDDpMlTM6Pa2YKl9y3MDe95X5bo6OhMDy5UKBXpvi6XyzHj1+no1qULFv/1F86cPadVHVUqFa5eu4ar165h0Z+LMXXyJPj61jFWtbMdsXELsfEGXWnah6GZkDMidj7GyJBgjM8kq2X2dVvxBV63LaUfbSnnQZnLkvpyYu0JseUivxRnzp7F5Cni/U6JRIIiRYqgYsUKyJc3L7y8POHq6gaZTAZbW2Ef9uOnTxg+4pvMqLbJJCYKJ/rL5XKtlno0lKX1wcTGtGQ2NgbvV98xrUz/fE08psC2H1FSQFhaxnhGr4sffvwJly9fEX3N3t4e5cqVRZnSpeHt7Q0vT0/Y2dslta1lwn7s1m3bsHXbdpE9kaFiY2PRf8Ag0UzjQNKKXBUrVkDxYsX+bcvmglyW1AeyEbl3TZo8BX4PsibwsFjRojiwfy+2bduOv9euw/MXL7TaLjIyEjt27sSOnTvRvFkzTJkyCTmzYCWyPHnyoHr1aoLfzY6dOzFxwnjRbRQKBfbs3Sso79ypo9bHjRVZut0YfQBN+4iOjoFzJgdwG+rxkyf4dtRo0WsrAOTPnx+VKlVEgfz54eXlhRzu7pDJZJDbymEltRK831RZr7MTiwiYLFOmjGj5PZGUr8Z2756GgMli2SNg0iqbppnVlqZZhVFGyCYUFSV8IGyuS9Raiqgowx/siP3tM5rxOGPWbNHZlg0bNMCI4cNQoUJ5nepgjr+758+fY9XqNYJyZ2dnjPp2JDp17KjT9/vJ06fGrF6m+uqrTmoBkxEREVi7bj3OnD2n9r5GDRvqvbyINr6E750pWFkJG3xkeaRW5vN9Frs2GqOdERlpgsyHWti+fQdu3rwlKC9apAjGjB6Fxo0b6fQ7czGzLCDBwcGY+/sfgnK5XI5hQ4egR/fuOl3bDV2iwNJ8Kfcac8F73pfFnP/e5cuXw/JlSxEUFIRjx0/g8uUruHb9GgIDP2a47Zs3b9B/4CBMGP89vh40MBNqa37EZssbpS2hYR+mXh5HbGk1Y9wvjfGZZDWpGf+OLYWl9KMt5Twoc1lSX04s2Cq7ZoAxVFxcPKZMnS4ol0ql6Ne3D/r17YPcuXNrvb9Xr18bs3pZQuz7ER0dDYVCYfI2szm3yfUh1i40xkoc+v5exR7kZ2ds+xFl/T394qVL2H/ggKDcy8sLY0aPQpvWrXVK1nPy1CljVo9SWbJ0Gd6+eycor1SpIkaNHIk6dWrrtD/bLM50Z2Njgx49uqNHj+64e/cuTp85i8tXruDOnbuIjU0/kRMAHD5yBDdu3sS6tWuyJFFbp44dBQGTe/buxffjvhNtD507fx4fP6pP0rO3t0eLFs21Pqajo6MgO7Mx2iWaxpOyY1zPpElTRIMlO3RojyFff42iRcUTDYrhqj9JLCJgsnTpUnBychLM1rlz9y7CwsLg4uJikuOGh4fjzt27gnJ7e3uULVvWJMdMj9jMuoyIDcz7+Pjg3BnLuOE7OjrC2tpa8IM3RmNMLIOOi4urwfslzYzxdxMLQHF21vzAKCQkBPv2CbMuDhw4AD9OnKBXHcJEBr2z2sZNmwU3WHd3d2zfukXrVNmpZfZygcbUonlzTJ4yTe379se8+YLrSOfOnUxWhy/le2cKYve1alWrYvOmDVlQGzIVsb+zlZUV/O7dEZ1NaEpiM9CMMYM8q5a+/XvdOkFZtapVsWrlctjb2+u8P1Mv+6mr3Xv2Cu5RcrkcmzduQPny5XTen9gyql8yS+9bmBve874scrkcMhsbxKdps29YvxY1a9TIolqpy5kzJ7p364ru3ZJmJ7958xbXb9zAtevXcfnSZY1LxahUKsyaPQf58+dH0yaNM7PKZkEsIMU4YxbibQlXE42RJRPrXxunL29egTLGGoPr0KE95s6eZYwqffEspR9tKedhavr8Bi2dJfXlnEXuVeERlvc91sbpM2fwOk2Qo0QiwV+LF6FJY93bTWJLHWY3Ls7ibZmIiAi4urqa9NiW1gcTa7dFR0dDqVRCakCwvb7jYmKf78hvRmD0qG/1rktWsvS2n6bsVmQ8iQnZP5hFLEYjIhPbpmvXCttHhQsVwuZNG/VKiCI2qYkMp1AosGHjJkF5q1Yt8cfcOaJZ9DMSbkbPJcqVK4dy5crh25HfICEhAffv++Ha9eu4fv06Ll+5ojFh1KdPnzBw0GAc3L8v04P7WjRvhilTpqoFLH78+Annzp9H/Xr1BO/fsXOXoKx5s2aik2o1cXZ2FgZMmmh8zMbGRqe6mQM/vwe4dv26oPyXn39C3z69dd6fuT27yyoWMb3U2toaviJR5XFxcdizd5/Jjrtn7z7EiaSG9a1TJ8PlhqxFIq8TFYY1fELSXEC04e3tLSgLCAhAXJwwFX925SwyS+7NG/EHNbpIO1ABAC7ZLG1vdvP2rXBmia7eicxOSS+o+uSp01Ao1JeiK1yoEMaP+06v48fGxprl0u0nTwoDGX768Qe9giWBpAH+7MrW1hZtWrdSK0sbLOnl6Ym6Jlw28Ev53pmCt7eXoOzNmzdZUBMyJbH2i0KhwHt//0yvi5ubm6Ds1atXBu/31UvD96Gr9+/f49Gjx2plVlZWmDtnll4P2ADzux8cP3FCUDZi+DC9giUBICTYvM4vq30JfQtzwnvel8fLS+xvbnjf1lTy5cuLjh3aY8av03Hq5HEcOXQQw4YOgbvIvVOlUmHGzFlf5OxmsXEEY/yWX78W34epJhWn7F8kUEFTsKwuDNmHWPYDQ79roaG6B5x4i/6Ged02FkvpR1vKeaRmLuPglszS+nI+Iv2Kt2/fCX4bX4ITJ04Kyr76qrNewZIAEGxmfXR9+PgIvx8A8DITxlEsrQ8mNqalVCrx2sBzeqnnuJilfb7m1vazthbejw25rqYNaiEN/Q4DPmNLaO+IXbMjo6Lw6dMnkXcbV2xsLC5cvCQo/+236XqvHmcJ91FzdP36DcE1xdXVFb9Om6ZXsCRgvn8rGxsbVKxYAYO/HoTly5bi+tUrWLVyOZo1bQqJRCJ4v7+/P1avEa4QaWp2dnai2SHFAiPDw8NF26ydOnXQ6ZhiE4qNMz4mjOnJbktxA8CJk8LPuHatWnoFSwLm9+wuq1hEwCQAtG/XTrR827btJjumpn03bZpxZ9XBwfhLLgUEBOq8TZEihQVlSqUST54+Magu5qRIEWHqWb8HDwze74MHD7U6FhnPw4fCz1znfTx6JCgrVqyYxvffu39fUNa2bRu9G2j37gn3l9VCQkIEac4dHOzRvHkzvfcp9rllJ12+6pzu6x07djDpEixfwvfOVMSuw4EfPyI4ODgLakOm4u3lJTpL+9FD4TXe1EqVLCkoE2sj6EKpVOLR48cZv9HIxK4V1atX02l5r9QSEhLw+Il5tSnvi1xfO3bQreOeWna/3xnbl9C3MCe85315xP7mYv0bc1WkSGGM+24sjh87ggb16wtef/PmDW7dup3p9cpq4mMWhvd9H4iMe+TJkxu2tqZdlkpsqai0QTz6MGQ8QCxrgCFjcMHBwaITqDNSVORv/fTpsy8yUNgULKUfbSnnkZq5jINbMkvryxUTWUouOjraKPeT7EbsmtCpQ3v992cG1wRD5cuXTzRhya3bt01+bEvrgxUoUEA0qFqsHakLfcfFxPs72fd3b25tP2O3iT8EBBhSHYvkKPYZi6x6p60AC/iMixYRX0r4Zib0/Z8+eyaYOJQvXz5UqVxZ733et4D7qDkSa+80bdJY76yKHz4E4PPnz4ZWK1PIZDLUr1cPfy1ehK1bNotOMt69e08W1CxpWe60jh8/Ici0um/ffsEYSd48eVC9WjWdjifWDjD0WRsA+ImMJ4k9xzB3Yu34jh3b67+/+/cMqI3lsJiAyfr168HHx0dQ/uDhQ+w/cNDoxztw8KBo0F3OnDnRorkw2jotsQv8x4/6z6YIDw/Hs2fPdN7Ozc0NBQoUEJSLRYFnV5UqVRSUXb16DSqVSu99RkVFid68xY5FxvP02TODlnp+/PixaLr0CulklfocFCQoE+voakssVXJWCwoSNhrz5MmTYaZcTeLj43Hnzl1Dq5WlypUrpzGQViKRoHMn0y3HDXwZ37tkYjOmDFGieHHY2dmplalUKtEsqpR9SSQSVChfXlB+XGSGlamJZSZ88fIlPnzQf0Dr5s2bWZIFJuiz8NpTpLD+15679+4hNjZW7+0lMO71ISYmRrC8haODg2gGA21du37D0GpZlC+hb2EI3vPIUBUrVhCUZce/t4uLCxbM/wM5c+YUvGbO7VZTERtH+PDhg8HZQy9fviI8VkXTj1mItdHCwsIMCrwJCQnBs2fP9d7eSWTlEUMymty4eVOv7SpUqCAoCw8P/yK/96ZgKf1oSzmP1MxlHNySmVtfzlClSpWCzMZGUH7+/PksqE3WChK5JhiStOG6BfRhra2tUaZMaUH5uUz4flhaH8zKygplSgs/S7GMbLq4cPGiXtuJ9XeePHli1ln102NubT+xNvHHjx/13t+NG/q1iS2Z6GecBf0Oc+Lt7QUvT09BeWbc08WefRY1IEgqMDDQKKsnkJCx2zvXrl0zpDpZplLFipgyZZKg/M3btwgMzPwJY1WrVkH+/PnVyuLj47F//wG1sp27dgu27dixg85j4WJjVvf9/AwK7lepVLh6Vfh9qFSpkt77zCqifT6Dxgqyf7/AGCwmYNLKygrDhw0VfW3a9F8NCrJKKzw8HNOm/yb62oD+/bQKMsqZM6cgO1lwcLDeA7bHT5zUOwCwYYP6grI9e/dZzAz3yiIXPH9/f9GLo7YOHT4iGsjAgEnTSkhIwIGDh/Tefs/efYIyFxcXFCxYUOM24eERgjJ9l7JRKpXYvmOnXtuaUniEMIjU3l44E05b+w8cRHR0dMZvNHNdOosHRVarVlXvpcq19SV875LJZDJBWWJigt77s7GxgW8d4XLpYg12yt4aNKgvKBOb3WZq5cqWFTzIUSqV2LtPeM/R1q7dew2tll7Erj0ODvpdewBg69ZthlRH9PqQYMD1Qey7YW/A+V29es0oy69bGkvvWxiC9zwylNjv6/3797h8RRgYZ+4cHBxEz+fTJ+Hgn6WrWKECpFLh8NzuPfpnEHj79i2u3xAOfGbGgHDhwoVElzbaK9If19aBgwcNuo94engIygzJ5n38+Am9tvPy8kTpUqUE5Tt37ta7LvQfS+lHW8p5pGZO4+CWytz6coayt7dH9erVBeWb/9kCpVKZBTXKOhERxrsmvHv3DpcuXza0SmZBLFv5+fMX8Pq1aZc7tsQ+WOXKwvbhoUOHERcXr9f+AgICRSfuaKNC+fJwdxcuk7tr92699pfVzK3t52HsNvEJ/drElkzsM36s52ccGRmJS5cs45pdX+SavWfvXkRERJr0uBFiY8EGPPvM6vaRJQs3YnsHALZsy75/qyaNG4vGGn0SCSrNDB1FMpunXpb7+fPnuH3njtrrEolEdLuMiLVJYmJicPjIUZ33lezK1at4//698FiZMKFY9PlWgiHPt0T6fHr+TqKionDQgJgbS2IxAZMA8FXnTigqsvRPUFAQfvplktEGUiZNniI6oJMrVy707NFdq33Y2tqiUKFCgvIzZ8/pXB+VSoVVq1frvF0ysWUI37x5gy1btuq9T3NSs2YNuLi4CMpXr1mj1/4UCgX+/nutoLxokSKiS0+RcW3YuBEKhULn7SIjI9Vu4Mlat2qZ7gwHsVnw+s7iOHzkCF6/fq3XtqYkNutN33NMTEw06HpkTjp37owlfy0W/Dd96hSTH/tL+N4lE1umItrAzHpiKcivXL2K02fOGLRfMi+tW7cSdDgiIiKwZOmyTK2Hg4MDGjdpLChft36DXsHj/h8+GBRsaQix+0GAntce/w8fsC/NTENdOTgKrw8x0fpfH8TOLyQkFPHx+j0EWLZ8hd51sWSW3rcwBO95ZKgSJUqgVMmSgvI5c37PgtoYTuxhqFKpe18vu3NyckLt2rUE5f9s2aL3LPpVq9cIxsCsra3RpLGwzWJsEokELVu0EJTv2LkLkZG6PxBLTEzEho2bDapT6dLCB9UvXrzEWz2yg3z8+BF79+3Xuy4dRB4a7N6zJ0uXvrUUltKPtpTzSM2cxsEtlbn15Yyhffu2grK3795l68A0fTg5Gu+asGLlKr3G1c1R2zatBRNOlEol/lz8l8mPbWl9sPbt2gnKwsPDsfmff/Ta37LlK/QObLayskK7tm0E5atXr0FQNllaNS1zavuJtYlv3Lip1/jlfT8/vQNjLZnYZ3xWj/YOAGzZuk2v/pM56iByT4+Kitb7Ob22jPnsMzIyEhs363ddpIwZs71z9+7dbH19srGxEZ2EqsyiNlzHjh0Eba7bd+7gxYsXACAae1G9ejXkyZNH52MVK1oURQoLs8CuXbtO77bFqlXC64yrqytq1qyh1/50IfYswJCV5cTGCvTt823ctFl0YtaXyKICJq2trTFrxm+CGasAcPDgIUyb/qvBQZO/zZylcWB0xq/T4ShyQdekfLmygrJ//tmic52WLV+BR4/0nwVUsmQJ1K4lHJyfPfd3ixiwtbOzQ5evOgvKj584iVOnTuu8v/UbNuLho0eC8j59eutTPdLR48dP9OqsL/pzsWhK7+7duqW7ndiMMH0GP4KCgjB5yjSdt8sMHrlyCcr8/f3x5OlTnff15+K/DLoemRMnJ0c0bdJY8J/YIL+xfQnfu2TOLsKG//t3wtk+umjUsCEKFRJmjv3p50lZkraeTCNnjhxo3144qLvm77UGLx2kqx7dhfeSgIAALPpzsc77mj79tyzL0it27blw4YLOGZ2USiW+Hz8BcXFxBtXHRWRg4L2/v977s7e3F7TVExIScOGC7ktFbd++I9s+DDE1S+9bGOJLuef16NkbhYsWF/xHxjFo4ABB2e07d7Bo0Z9ZUBvDvHkjzADkKbJU15egb58+grLAwI9YqMff1c/vATaJPMhp3qwZvLwy5/Pt3r2roOzTp096BTGs37ART/Xom6bm7u6OvCKD9f/oGMyvUqkw8cf/6T3ZAgA6d+oEV1dXtTKlUonvvvveYh6IZhVL6UdbynmkZS7j4JbK3PpyxtCieQvRJTynTf8V7969y4IaZQ0PT7Frwlmd93Px0iVs3GTYBARzkjt3bjRr2kRQvnPXLhwxIAuRNsyxD2aIIkUKo1rVqoLy+QsW6rxcs5/fA2zctMmg+vTt01uwkktkVBTGjRufLVeuMKe2X4nixQWTz6Ojo7F7j24r3cTFxeOHH/5nzKpZjPLlygnKrl67hmfPnuu0n1evX2PhwkXGqlaWq1KlCsqWLSMo/2vJUty5c9dkxxVrH92+fVuvVUknT52md3Z0ypjYWJA+faDY2FiM+36CMaqUZSIiIhEcHCwoz6rxMh9vb9SsIQwu3LFzF5RKJfaI3EM6deyo17EkEgl69+4pKPd78ECvduzxEydw8tQpQXm3rl1ga2urVx114SyS0O2dAc8CxFZPOX1a99/J06fPsMDM7jF16zcUPEuoW79hphzbogImAaB8+XKYOGG86Gtr163HiG++1etGGBERiVGjx2LVKvEZrF27dhFdGjI9zZs3F5Tdun1bdGBbk7379mPe/AU6HVfMDxMnwNraWq0sMjISAwZ+jUciwYG6evnqVZbO/uzdq6egkwUA48ZP0OnB7fnzFzBr1mxBububGzqIBG2QacyYORvXr1/X+v0HDh7E6jV/C8qrV6+GkiVLpLtt9WrVBGVHjh7TqREfGhqKwUOG4bOZzoJ0dXVF8eLFBOVz5/6uU5D5jp278NeSpcas2hfrS/jeJStapIig7Nnz5wbNbJFKpfjxhx8E5R8+fED/gYNE06/rys/vgckHYCljY0Z9KxoAN+KbkUZZnjQwMBAbN2Y80FuzRg2UE3kAuHzFSmzbtl3r482Z+zuOHM2671XVKpUFswU/fvyENSKZtTVRKpX4+ZfJRpnF6enpKcgSHh4ervMgY2rVqwkfAsxbsFCnwIdz585j8lTzefhsjiy9b6Ev3vPIGNq2bYMK5csLyucvXCTa59FVTEwMNm7clO73csnSZTh+4oRBE1Jfv36DEyeFg5blygrvp1+C+vXqorDIxKxVq9eIDj5r4v/hA4YOHyHIHiWRSDCgfz9Dq6m1MqVLo0qVyoLyVavX4OAh7Zf8uXzlCmbPmWuUOjVv3kxQtnr1Gq3vS0qlElOn/YozegSppObk5Igxo78VlD989AhDhg1HSEiIQfsHgCtXruo1ISS7s5R+tKWcR1rmNA5uicytL2cMcrkMY0aPEpRHRkaid9/+Bi29nJ2C2qpVFV4Tli5bjnCRZUY18fN7gFGjx1rcUvZjx4wWfebz3ffjcUqPh8fJMvp+WGIfbPDXgwRlERERGDDwa62/a2/fvsXXQ4YYnMU0b9686NtXOJno3Pnz+G7ceIMyMwFJ17oTJ07i7r17Bu1HW+bU9pPJZGjcSBh88Me8eVpfF+Pi4jD2u3F48PChzvX8ElSuXAmeaQLdVSoVfv5lktbLsPr7+2PIkGGI1HO1AXM1Yfz3grLExEQMGjwEd+/qHzSZ3ne3RInigkx98QkJOrcn/1z8F3Zlw3HI7KSayJj9vXv3cejQYa33ERcXh5HfjsbzfzMfZrbIyEj8MmkyXr56ZdB+1m/YILiXenl6igYAZ5ZOHYUrSu3evQdnzp4TZDh0cLBH82ZN9T5Wh/bt4ebmKij/bcZMXLykfaKUhw8f4fvxEwXlMpkMPXv20Lt+uihSRJgt89atW3rvr5rIWMGmzf/oNJns3bt3GDJsOGJjY/Wuh6WxuIBJABjQvx969xJGHwPAkaNH0bR5S62XSYyNjcU/W7aieYuW2H9AfCmKunV9MfmXn3WuZ726vvD29haUT54yFRs3bkq3AxsSEoLpv/6Gsd+NS5lVZWdnp3MdkpUsWQKjvh0pKA8ICEDHzl2wfMVKnZeCioqKwqFDh/H14KFo0rR5li0vCSTNOBw7doygPDQ0FH369sdJkQc1aW3Zug1Dh49AvEij9tdfpxv0+ZN2kgf+YmNjMWjwUOw/cDDd96tUKqxdtx7jxo0XpGqWyWSYOnlyhsesVasWHBzs1cqUSiW+HjIUt27dznD7Gzdvomu3HriTqsEvlgU3q4ktzXbi5Cn87+dfEBeXfhBJdHQ05sz9HRMm/pDSiDPHc8xOvpTvHQA4OzsjX968amUJCQkGL6vcoH49dO3aRVD++PETtG7bHlu3bdM5M0xoaCh27tqN7j16oW37Djh3/rxBdSTDeXh4YNqUyYLyiIgI9O7TD7PnzNV54DEuLh6nTp/BmLHfoV6DRvh73Tqttpvx63TYiAzU//jTz/ht5qx0OyDBwcEYM/Y7LF22PKXM3t5e4/tNxd3dHZUrVRKUz5n7u1YZmPz9/TF02HD8s+W/TDGGXntKlRIuPbv4r7/0XoJB7H7n5+eHb0Z+m2HQWkJCAlatXoPBQ4amDNCb67U1q1l630JfvOeRMUgkEsydM0v0PvHrbzMweMhQPH+uW2C5SqXCnTt3MWPmLNT2rYdfJk9J9751+84dDBk6HE2aNcfyFSt1Xtb48ePHGDDoa0H2Kg+PXJmyJI45kkgkmDVzhiDYXKVSYfzEH7Bs+YoMHz5fv34dPXv2hr9INua+fXqjfHlhthNTmjZ1iiCIITmbzrr1GzIM2tizZy+GDBmWcv1KGwikq65dvhKUxSckoE+/Abh2Lf0Jmc+ePceAQV9j3fr1KXVJm51HFz179IBvnTqC8suXr6B1m3Y4cuSozm2dwMBAbNq0GW3bdUCPXr1x7/59veuXXVlKP9pSziMtcxoHt0Tm2Jczhs6dO6FuXV9B+Zs3b9C5S1ds37FT6+tlXFw8Dh8+gs5fdcXc3+cZu6om06RJI0FZQEAABgz8OsMAJ5VKhZ27dqNHr94pmYrM4e9qLIUKFcKoUcJAtJiYGAwdNhx/zJuPiAjtMvipVCrcuHkTI0eNRrfu4s8WU7O0PliDBvXRqlVLQfnDR4/Q6asuuHHzZrrbHzl6DF917Y7AwKSMlIaOaY0ZPUo0wcP+AwfQvkMnvVaWefPmLVauWo3GTZtj8NBhBgVd68qc2n5duwi/tyEhoejRqw8eP04/g/Pt23fQrUdPHD5yBADvxWKsrKzQUSSz2tVr1zDim5GiWeOSqVQq7Nt/AB07d8Gzf/v0lvQZ16xRA927CVciCA4ORs/efbFq9ZoMn0UmUygUOHfuPPoNGIgx343T+D4rKys0bNhAUL5+w0YsXPRnhr+7kJAQTPzhR7UAS0u6j5qT0qVKIXfu3ILy7ydM1CqG48nTp+jZu69aNsHM/lsplUps3LQZTZu1wJChw3Dw0CGdVhJTqVTYsHGjaOa/tm3bQCKRGLO6OmnWrKlgifuAwEBMmTJV8N6WLVoY1A5wcHDAtClTBOXx8fEYOmw4tm/fkeE+jh0/jj79+otO+hg/7jv4iPRLTaFM6dKCsr/XrdM7eUKjRg0FY2PR0dHoN2CgVmPBp06dRpdu3fH69WsAvJ4ls874LdnT5Em/wMrKCn+vFT7kDgoKwpSp0/D773+gdu3aqFSpIgoWKJAyyyAiIgKvX7/Gzdu3cf78hXRnUFWvXg1LFv+p10CpVCrFuO/G4Ltx6hkxFQoFfpk8BRs3b0bLFi1QokRxuDi7IDIyEh8CAnDp8mWcPXNWbXZJzZo14Onpid279+hcj2TDhg7B8+fPBenX4+LiMGv2HCxZugytWrZA1SpVUKZMabi5ucHZ2Rnx8fGIjIxEaFgYnj97jkePH+PuvXu4fPmKQcsUGduggQNw9tw5XEzTmQoKCsLXQ4bCt04dtG3bBpUqVYRHrlxQKJT4+DEQly5fxq5de3D7zh3R/Xbt2gVNmwgfvpPx9ezRHZs2/wOFQoGIiAiMGj0GmzZvRscOHZJmbnl4QKFQIjAwEBcvXcL2HTvh5+cnuq+R34wQjexPy8nJEX379BFkTvz8+TO6du+BVi1boE3r1ihTpjRcXV0RFxePoKBPuHHjJg4fOYpTp0+rbdehQ3tcvXrNKDNNjal/v774e+06wTIQW7ZsxaVLl9GrZw/UqlkTefPmgVwuR3BwMN68eYtTp09j9549KYMhACCXy9Gndy+sWLkqs0/DYnwp37tkzZs3w/IVK9XKli1fgdu376BJk8YoWLAAHB0dYSUVNt4qVqygcb+Tfv4Zr1+/FmRHCA8Pxw8//oQ/5i1Aq5YtUKVyZZQoWQJurq5wcnJCbGwsIiIiERISgqdPn+Lxkye4des2rt+4YfAsaTK+tm3b4MmzZ1iS5veiVCqxbPkKrF23Hs2bN0ONatVQrlxZ5MiRA87OzlAqlYiIiEB4eDhevnqFR48e476fHy5evIioKN2XxC5RogRGDB+G+QsWCuqxatVq7Nq5C82aNUWVKpXh4eEBRaICgYGBuHDxIk6cPKl2zDx5cqNZs2YaM5ub0shvRqBPv/5qZQqFAv/76Wfs3r0HXbt+hcqVKsPDIxeApOvSw0ePcOLESezdt18twKZwoUIoXqI4Dh7UPpNUWi2aNcOlS5fVyvbu24/nz1+gVauWKFqkCJycnAQBJgBQqlQpyOXqbfT27dth8V9L8DbNrLsTJ0+hSbMW6Nm9G+rWrYtChQrCzs4OoaGheP/eH2fPnsWuPXtTOpNAUnDL0CGDsfivJXqfnyWz9L6FvnjPI2MoWLAgFi6Yj6HDhguWpTtx8hROnjqNOnVqo66vLypWqABvb2+4uDjD2toaERERiIiIxLv37/Hk8WM8fPQY5y+cV2vPa+vly1eYNXsOZs2eg9KlS6NqlcooXbo0ShQvDnd3d7i4OMPGxgYxMTHw9/fHg4cPcezYCRw7flz0wcTE8eO/6MG6ihUrYMTwYYLB8cTERMyeMxe7du9Bp44dUNe3Dry8vGBra4uPHz/i/n0/7Nt/AEePHRMNOCpWrBjGfy/M5mFqxYoWxbBhQwXnE5+QgClTp2HHzp3o3KkTatWsAQ8PT1hZSRH48SOuX7uOnbt24+q1aynbWFlZoUf3bli/YaPe9SlYsCC6fNUZW9Nk//78+TO69egJX986aNSwIfLlywt7O3sEh4Tg9evXOH/+Ai5fuaJ2TRz5zQhs37FT7/6VRCLBgvl/oFuPXniSZtWTgMBADP9mJPLlzYuWLVugcqVKKFKkCFxdXeDg4IDo6BhEREbg8+fPePLkKR4/fozr12/g7r17Fpc5TFeW0o+2lPNIy9zGwS2RufXljGXe73PRuUtXvHz5Sq08ODgYEyb+gGXLl6NZs2bwrV0befPmgZubG6RSKcLCwvDhQwDu37+PGzdv4sTJUynjngULCpdTNle1atZElSqVcf36DbXyW7dvo3nL1ujyVWc0btQIRYsWgaOjI8LDwxEQEIjzFy5g3779gixww4cNxaI/F2fmKZjUkMFfw8/PDwfTZKBKTEzE4r+WYNPmzWjRvDnq1vVFsaLF4O7uBltbW0RERCDo82c8ePAAd+7cw7Hjx/HhwwcAEA3YEGNpfbBJP/+MK1euIigoSK38xYuX6NqtBypXroSmTZogX768cHF2QXBwMJ49f45Dhw/j0SP1QLvvx32HKQaszCGXy7Fi2VJ81bWboJ/y7Plz9OnbDyVKFEfTJk1QuVIlFCxYAM7OLrC3t0NUVBQiIiLw8eMnPH7yBI8eP8aVK1cFba7MZE5tvzp1aqNO7do4f+GCWvmrV6/Qpl0HNGncGHXr+sLH2xsymQwhISF49vw5zp47hxs31ANnp0yehPEThNm7vnQD+/fDtm3bBb+lEydPoVGTZmjVsgWqVasGD4+k59CfP3/GvXv3cPLUabxKlZnOzs4OEyd8j0mThQFJ2dXPP/2EJ0+fCr5L0dHR+G3GTKz5ey1aNG8GX986KFigANzd3WFjY4PwiAh8DPwIPz8/3Lx9G8ePn0gJPhXLzp7aiGFDsW/ffsH1dcHCRTh69Bh6dO+G6tWrwdvbG1ZW1vgc/Bkvnr/AiZOnsHvPHrUYEXd3dzRv1lSnDOmkHYlEghHDh+HH//2kVh4TE4OvhwxFwwYN0LFDe5SvUB453HNAoUhEUNBn3L13D0ePHcPhw0fU/sbVq1eDUqHENR1WqzQWpVKJ4ydO4viJk7C1tUXtWjVRtmxZlCldGgUK5IeLiwucnZ1TYh1evXqF6zduYveevXj69Klgfzlz5hTNBJ2ZbG1t0bJlC2xJMxEr7TMWQP/luFNr0aI5OnXsiB07d6qVR0VFY8IPP+KfLVvRoX071KhRXW086ebNW9i7d5/gHpfMt04d9OvX1+D6aatF8+aC54UvXrxE8xat0L59O5QpXRpu7m6Qy+SCbfPly4ccOdzVygrkz482rVthz171RBIvX75C2/Yd0bFDezRv1gwlSpSAi4szoqKiEPjxI65cuYoDBw4Kfg+W1i/Ql8UGTALAzz/9D8WKFcOUqdMEmQsAIDIqCkeOHtV76cP+/fpiwvjvRbMJaat9u3Y4cuQYjh47Jnjt8eMnePw440Z88eLFsHjRQkz/dYbe9QD+y2ggk8kEA8hAUkdv8z9bsPmfLSJbmz+JRIIF8/5Arz59RT/Xc+fP6zxrz7dOHUz6WffsoqSfMmXKYPz34zBj5qyUsitXruLKlas67ad5s2YYOmSw1u8fOmQwTpw8KfjeKBQK7N23H3v37ddqP2XLlsGUSb+gRas2OtU3M7i6umLSLz/j+/ETBK+9efMGv82YqdV+JBIJZs74zSICGrLal/C9S9a9WzesXbdecK++cvUqrlxN//f9/Knmma9yuQwrli3FyG9H4/QZ4VI8nz59wt9r14lOrqDsZdzYMbCxtsbCRX8KXouNjcXu3Xsy5WHaNyOG49WrV4IAMQAIDgnRqh3l4GCPJYsX49jx46aqZrpq166Fzp06YvuOnYLXrl2/rvUgg6urKxb/uUgQGKartm3bYv6ChQhOkynU78ED+D14kO62Z06dQJ48edTKbGxs8Ntv09F/wCBBkNGnT58wf+EizBeZxSnm++/GonyF8gyY1MDS+xb6+hLueWLtQEcHB5Mf90vToH49LP1rMb4dPUYwY12lUuHcufM4dy7zstL4+flpnKymjS5fdUa7dm2NWKPs6ZsRw/H69WvRtsTTp08xc9ZszJw1W+v95c6dGyuWLRFMIMgs34wY/m+grLBdc/++H+7f1+47M2H893BxcTG4Pj/+8AMuXrqEd++EgWPa/mbat2+XEjBpCBcXF2xYtxaDBg/G3bvCJSHfvH2rln2ctGMp/WhLOY+0zGkc3BKZW1/OWFxdXbF+7Vr07ddfdInFFy9eYsmSpYJJlJZk6pTJ6NKlm2B51vDwcKxctRortZxs2aN7N3Tu1NGiHoxKJBL8PncOFAql6HO+kJBQbNr8j0mCW8ypD2YMOXK4Y+WKZejdp58g85FKpcL16zcEgbti2rdriz69exkUMAkktWM3bdyA/gMG4c0bYTbIR48eCwI1zZk5tf1m/DYdrdq0EyQLUigUOHzkSEoGyfQMHzYUnTp2YMCkCDc3N0ybOgXDR3wjCGrVdizMxsYGixYugJ2drSmrmunkchlWrViOgV8PFgRNAsCHDx+wes3fWL3mb6Mds1ChQhg5YrjoeO/DR4/w86TJWu1HJpPhz4ULcPnKlYzfTHrp3KkjDh48JBrsdvLUKbXskenJmycP5v/xO0aP+c7YVdRZbGwsTpw8hRNaZMkUI5fL8fuc2XBzczNyzXTXuVNHQcBkWvnz50fVqlWMcrypUybB/4O/IJkGkDRx6Nbt2zrtr3SpUlgw/49MzdRZpEhh0UkKAYGBGd7zZ82cgc6dhMGnEyeMx5UrVwVLocfGxurU5m3YoAG+GTHcovoF+rLIJblT69rlKxw6sF906QZ95cmTG8uW/oWf/vejQcGSyebP+x2NGzXUa9tqVatiw7q1Rhk4BgBra2vM+O1X/Dp9mmD5F0PZWBv+WRnK3d0dmzduQL16dQ3eV9euXbA8Cx88fKkGDRyAb0YM13v7dm3bYP6833VazsvBwQErly9Dvnz59D5ulSqVsWbVSjiY8cPijh3aY+yY0XpvL7OxwexZM9G2TWvjVeoL9qV87wAgX768+Ol/P5pk3/b29li+bAnGjB4lWBLQUNZG3h8ZZtS3I7F0yWLkyJHDqPu11qH9IpFIMGf2LAwc0D/jN4twd3PD2jVrRJehzkzTp01Fg/r19d7ey9MTa/9ejaJFixhcFycnR8yePcuoGcdq1ayJ336dLpqVUhsSiQTjvhuLITpMvvhSWXrfQh+Wfs+Li4sTZLEBktrwZHwNGtTHzu3bULpUKaPuVyKRQCqS5dQUkrP1/vbr9Ew5nrmTSqWYM3sWhg0dYvAgbsWKFbFty2bB5IHMJJVKsXD+PLRprX8f8ZsRw/VuW6Xl5OSITRvWo0CBAnpt37dPb8yeOcNoA+w5crjjn00b0bdPb6MP2uvbzsnuLKUfbSnnIcacxsEtkTn15YzJ29sL27dtQbOmTbO6KlmieLFi+HPRQoOWN+zVswemTJ5kxFqZD5lMhj8XLcCob0dm+v3PHPpgxlS2TBls3rhB6yybaXXu1BEzZ/xmtPoUyJ8fu3duR+tWrYy2z2Q2WdBWMpe2n4+PDzasW6vXGKpUKsX4cd/hu7FjdN72S9K0SWPMnjVTr2uSs7MzVi5fhgb165mgZlnPyckJ69euRc8e3TPtmCNHfoOuXYXL0WvLyckJy5cuQfXq6WezJMNYWVnhz0ULULZsGb33UbRIEaxf9zc8PDyMWLOs4e7ujnV/r0adOrWzuioAgEoVK6JQofSztHfs0N5ox7O1tcWqFcuNkrGyUcMG2LhhfZb0I2fO+A3u7u4Zv1FLHh4eWLF8mUH7bNa0KRYtnP/FjhulZfEBkwCQP38+rFm1Etu3bkHLli1ga6vfjAxHBwf8/NP/cOzIYTRu1Mho9ZPL5Vj85yL8MHGC1j9UV1dX/DBxAjasX2vUH1mybl274MSxo+jdq6dBHXGZjQ3q16uHBfPn4c9FC4xYQ/25uLhg9coVmDVzBnx8fHTevlixYli1cjl+mz5Nr6XYyXBjRo/C4kULkStXLq23cXNzxa/Tp+GP3+fqFejs4+ODvbt3omXLFjptZ2tri1HfjsT6tX+bxQyQjIwYPgxL/lqMnDlz6rRd+XLlsG3bFqM2hujL+d4BSbPcly5ZDC9PT6Pv28rKCt+MGI7Dhw6ifbu2Bg1g2tnZoWXLFli5fBl++vEHI9aSjKFJ48Y4cewohg8bCldXV733I5VKUb1aNcz4bTq2/rNZ521//GEi1qxeiaJFtHvIJJVK0bpVKxw8sC/dJXczi42NDZYvW4LR346EXC5cDkATiUSCtm1aY8/unShTurTR6tOgfj1s2rg+ww65Ljp17ICNG9YhX968Om1XqFBBrP17DYYNHWK0unwJLLlvoQ9Lvuddv35DkD3T3d0d/fv307selL6iRYtg187tmPHbdL2DwFL2VaQIvhs7BmfPnBIs+5Jarx490KZ1a4MHGitXroSd27fi+3HfZeoMb3OXtGztWPyzeSMqlC+v8/Y5cuTATz/+gC2bN8LTBNcZXclkMsyf9zumT5uqU/ssV65cWLxoIcaMHmXU+uTOnRvbtmxGj+7dtB4cLliwAFauWI5ffv7J6MvGy+Vy/PLzT9izaycaNWyg0+TOtJydnfFV507YtGG90YJMsyNL6UdbynmkZY7j4JbE3PpyxuTs7Iy/Fi/CsqV/oWSJEnrtQyqVol69uviqcycj1870fH3r6DVRxtPTAwvmz8OUyZMMuseYO6lUim9HfoO9e3ahYYMGerctS5UsiZE6JmvI6j6YsZUsWQIH9u1B7969tH6O4u3tjT/mzsGsmTOMkmQmNRcXFyyY/wc2rF+b4dK7GcmZMyf69umNXTu3o3nzZkaqoW7Mpe1XunQp7NqxDa1atdT691K2bBls/WczJxBrqWOH9ti4fi3KlSur1fslEglatmiOQwf2m02AlKnI5TJMnTIZWzZvRLWqVfXeT5UqldG/v3bL6/42fRqmTZ0CR0dHnY7h61sHe3bthK9vHX2qSDpycnLCls2b0atnD5363lZWVujduxe2b9uCvDqO9xuLvb09xo/7DlWqVDZo3EAmk6Fvn944cewIqlQxTrZGY+nYoYPG16RSqdFjBORyOWbPmoHlS5egSOHCOm+fJ09u/D53NpYvWwonJ91++8bi7e2Fvbt3GfUaUqpUSezbsxs1a9bQaTtnZ2dMnvQLFv+5UO94OUskUaXNB/0FiIyMxKXLl3H9+g08evQYb9+9Q3BwMGJiYgRL86UmlUqxYP4faNlCt4EqXYSHh+PoseM4e+4cHj18hOCQYISHR8DWVg4vTy+UKFkC9evVQ/NmTQ162KiLiIgIHD9xAmfOnMOdO3fw9t07QRpxIKkx5+npicKFCqF06VKoUaM6qlapkmn11EdCQgJOnjqNw4cP49r1G/jw4YPgPRKJBPnz50f16tXQqmVL1KpZgw9zMsH34ydi565damVp0w/HxsZi1+49OHToMG7euoWYmBi199vY2KBs2TJo2aIFOnfqZLSb4cOHj7Bx0yZcuHhJdDkIe3t7lC1bBg0bNECnjh0EA9Q7d+1GZGSkWlnHDu11bqibUlxcHLZv34HDR4/i1q3bgs9WIpEgT+7cqFmrJtq0boVaNWuqvf78+XNcuHhJraxw4cKoXUv9faS9L+F7ByQt/XH23HlcuHABDx4+xNu37xAZGYno6GjRe3R6y5NqEvT5M44ePYZz587j7r17CAgIEH2fVCpFbh8fFCpcCGXLlEGtmjVRsWIFBstnE3FxcTh16jROnT6NW7du49Xr11AoFKLvzZkzJwoXKoQSJYqjRo0aqFG9GpydnQ2ug0qlwvnzF3D02DHcuXMXb96+RXR0NGQyGdzc3FC4UCFUr14NLVu0QP78+mePMaWgoCCs37ARp8+cwcOHjwSfobW1NYoVLQpf3zro3KkjChUqpPb6hYuX8Pz5c7Wy2rVqorAeHVwAuHr1Gk6dPo2HDx/h5auXiIyMQlRUFBISEgTvFVuSOy2FQoH9+w9g3/4DuH7jhmDZKSDpAVP1atXQqlVLNGygPpgdEBAoWFLQ09MTzZo20ev8vgSW3LfQlSXe82bPmYtly1eolf304w8MmMwkKpUK165dx/ETJ5LGOx4/FgSwJnN0dEShQgVRtEhRVKtaBbVq1dR5QqFCocC9e/dx69Yt3Lx9G0+fPMXbd+8QGxsr+n4XFxeUKF4cVapURpvWrc0ue5W5unnrFvbtO4BLly/j+fPnUCqVgvfkypULlStVQtMmjdGsWVOzHfiMiIjA9u07cODQYdy7d09wrbO3t0elihXRvHkzdGjfTu08tu/YiQkT1QMHOnbogDmzZ+pdn7dv3+LoseM4d/48Xr9+g+DgYMTGxsLBwQF58uRBubJl0LhxI9T19c20IJP379/jyNFjuHDhIu7dv4/Pnz+Lvs/a2hp58+ZB4cKFUb5cOdSqWRNly5YxekBndpeV/Wix72ynjh0xe5buS0lb6niAOY6DWxJz68sZ2/UbN3D48BFcvXoNT54+Fe0TWllZIU+ePChduhR869RGvbp1zWIygSFUKhVOnTqNnbt24crVawgODha8x93NDVWqVEHzZk3RokVztTZ9ZGQkdu7arfZ+R0dHi5sE/+r1axw4cBAXLlzEfb/7iIqKFn2fp6cHihUrhlo1a6JeXV8UL17c4GNb0rhjUFAQ9uzdhwsXL+LJk6f4/PkzlEplUlspd26ULl0K9evXR6OGDTItS9Hz589x5OgxXLp8GX5+DxAWFib6PplMhvz586NI4UKoVKkSataogRIlipvdsz1zaPs9efoUx44dx4WLF/H+/XuEhIQgLi4eTk6OKJC/ACpUKI9mTZsabZnVL41KpcKly5dx+vQZXL12DZ8+fkJwSAiApEQvhQsXThl3LGjgJMjs6uHDRzhw6BAuX7qMBw8fio5jSCQS+Pj4oGSJ4qhdO+mers94ekREBDZt/gcnTp7Evbv3EJ+m/SCVSlGwQAHUrl0bHTu2R9ky6tkO79y5izt376qVlS9XDuXLl9O5LpS+N2/eYv2GDTh3/gKePXsmGD+WyWQoXaoU6tX1RefOneHt7aX2+pGjxxCYZtnipk2awMvL9G3BsLAwXL9+A7fu3MGdO3fw8uUrBAYGio7nJD9vL1WqFOrXr4sWzZvDycnJ5HXUx6dPnzQu+Zwjhzt69expsmOrVCpcuHARBw4exJWr1/DmzRvRZwo+Pj6oVrUKmjdvhgb165tVFsWXL1/i4KHD8PN7gKfPniI0NAxRUVGi1zxNS3Knde3adfyzdSsuX74i2uZ0cnJCpUoV0bhRI7Rr20awAsW69RsE2/Tp3UuHs8r+vsiASW1cuHARg74eLLhRymxssGL5Mouf3ZGeuLh4BAYGIjIyEomJCbCzs4eDowPcXF1hZ2eX1dUzSFRUFAICAhD9b3CYo4MDfHx8dJqRS8ahTcBkaiqVCh8CAhAWGoZERSKcnJyQ28fH6DMa0woPD8fn4GBERERALpPB1dUVHh4eZtfxNkRiYiKCgj4jNDQEiQoFHOzt4eXlle1/79nZl/C9y0wxMTEICAxEdFQ0FMqk77iDgyPc3Nwgl5vPICUZJjExEYGBgQgPj0BCQjzktrZwcnSEs7Nzlj8ozC5iY2MRFBSE0LAwSCVSODk5wtvb26w6nYZQKpUICgpCSGgo4uLi4GBvDw8PzyybffilsOS+hTky9T2vXYeOuH/fL+X/fXx8cPzoEd5Ps4hKpcKnT5+SrmuxsbCxkcHBwQFOTo4myzqmUqnw+fNnREREICo6GhJI4ODoAGcnJ2YFM4L4+Hh8+BCAiMgIKJVK2NnawcvL02wH09OTkJCAd+/fIyIiAjbWNnBxdYG3l5fGPo0pAiazg8jISHz8+BHRMTFQqVT/Xrcd4O7ubvLxDkuT2f3of7Zsxf9++lmtrHu3rpg+bapB++V4AOnD0vtyCoUCgYGBCAsLR0JCPGzt7ODo4ICcOXOaVfCZsalUKnwODkZoSCiiY6JhZ2uHXLlyGrTihqUKCgpCcEgIYmNiIJPJYG/vgBw53AUPjU2B446mFRYWhk+fghATGwOJRAIHBwc4/ttWyo4TSdj2oy+dSqXCx48fERISgvj4IbldkAAAtPFJREFUeMjlcjj8e0839sTAuLh4fP4chNDQsKTfm6MDvL28eW02Q1FRUfj8ORhh4WGwsbaGs7MzvLy8slX27Pj4eAQFBSEyKgqxsbGQy+VwcnSEq6srJ4fpITY2Fh8+fEBkVBQAwN7ODl5eXpnStjNXISEhCAkJQWRUFORyOXK4u+u8ouiXiAGT6di7dx/GjvteEJ1sb2+P9Wv/RoUKui+NRETa0TVgkoiIiIiIsk5YWBiqVKuhNlt61ozf0DkbLnlIRObnSw2YpOzr77XrMG36r2plgwYOwA8TJ2RRjYiIiIiIiIiIKFn2CbvOAm3btsHECeMF5dHR0Rg0eDCePn2WBbUiIiIiIiIiMi+XLl1WC5YsUrgwOljY0n5ERETaChJZUjM7ZoMlIiIiIiIiIrJEDJjMwKCBAzCgfz9BeUhIKPr1H4D3799nfqWIiIiIiIiIzMiFixfV/n/smNHZcgk0IiIiY3j18qWgrFChgllQEyIiIiIiIiIiSosBk1r48YeJaN2qlaA8IDAQffsPwOfPwVlQKyIiIiIiIiLzcPHS5ZR/ly1bBs2aNc3C2hAREWWd+Ph4XL5yRVBeonjxLKgNERERERERERGlZZ3VFcgOJBIJ5syeic/Bn3Ep1UMgAHj58hX6DxyEjevXwcnJMYtqSERERERERJR1Thw7ktVVICIiMguL/lyMkJBQtbK8efKgYEFmmCQiIiIiIiIiMgcMmNSSTCbDksWL8b+ff0Z4eLjg9Y2bNmHokMFZUDMiIiIiIiIiIiIiymwvX75EaGgYoqKi8Or1Kxw8dBhXrlwVvK99+3aQSCRZUEMiIiIiIiIiIkqLAZM6cHJyxML587K6GkRERERERERERESUxWbOnoPjx0+k+x4Pj1wY0L9f5lSIiIiIiIiIiIgyJM3qChARERERERERERERWRpbW1vMmTULzs7OWV0VIiIiIiIiIiL6FwMmiYiIiIiIiIiIiIiMqGiRItiwbi3q1Kmd1VUhIiIiIiIiIqJUuCQ3EREREREREREREZGebGxs4OTkhFy5cqJihYqoV68uGjdqCKmU+QqIiIiIiIiIiMyNRKVSqbK6EkREREREREREREREREREREREREREpsQprkRERERERERERERERERERERERERk8RgwSUREREREREREREREREREREREREQWjwGTRERERERERERERERERERERERERGTxGDBJRERERERERERERERERERERERERBaPAZNEREREREREREREREREREREREREZPEYMElEREREREREREREREREREREREREFo8Bk0RERERERERERERERERERERERERk8RgwSUREREREREREREREREREREREREQWjwGTRERERERERERERERERERERERERGTxGDBJRERERERERERERERERERERERERBaPAZNEREREREREREREREREREREREREZPEYMElEREREREREREREREREREREREREFo8Bk0RERERERERERERERERERERERERk8RgwSUREREREREREREREREREREREREQWjwGTRERERERERERERERERERERERERGTxGDBJRERERERERERERERERERERERERBaPAZNEREREREREREREREREREREREREZPEYMElEREREREREREREREREREREREREFo8Bk0RERERERERERERERERERERERERk8RgwSUREREREREREREREREREREREREQWjwGTRERERERERERERERERERERERERGTxGDBJRERERERERERERERERERERERERBaPAZNEREREREREREREREREREREREREZPEYMElEREREREREREREREREREREREREFo8Bk0RERERERERERERERERERERERERk8RgwSUREREREREREREREREREREREREQWjwGTRERERERERERERERERERERERERGTxGDBJRERERERERERERERERERERERERBaPAZNEREREREREREREREREREREREREZPEYMElEREREREREREREREREREREREREFo8Bk0RERERERERERERERERERERERERk8RgwSUREREREREREREREREREREREREQWjwGTRERERERERERERERERERERERERGTxGDBJRERERERERERERERERERERERERBaPAZNEREREREREREREREREREREREREZPEYMElEREREREREREREREREREREREREFo8Bk0RERERERERERERERERERERERERk8RgwSUREREREREREREREREREREREREQWjwGTRERERERERERERERERERERERERGTxGDBJRERERERERERERERERERERERERBaPAZNEREREREREREREREREREREREREZPEYMElERERERERERERERERERERERER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",
      "text/plain": [
       "<Figure size 1100x300 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 275,
       "width": 1318
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Defining a color pallete to plot the chart\n",
    "bar_colors = [\"#888888\", \"#B4B4B4\", \"#E0E0E0\", \"#F69B51\", \"#F2740E\"]\n",
    "\n",
    "# C2C2C2 is darker and more readable than E0E0E0\n",
    "leg_colors = bar_colors.copy()\n",
    "leg_colors[2] = \"#C2C2C2\"\n",
    "\n",
    "fig3 = plot_hor_stacked_bars(\n",
    "    q3_y_per,\n",
    "    q3_x,\n",
    "    t3,\n",
    "    bar_colors,\n",
    "    leg_colors,\n",
    "    ylim=(0, 2.2),\n",
    "    figsize=(11, 3),\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e343fcc7-b58c-4718-815e-a2401f63a481",
   "metadata": {},
   "source": [
    "#### 4.2.5. Star Wars or Star Trek"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "69b55f14-1fff-4e59-8297-4a55c2cadee6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 340x450 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 428,
       "width": 392
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig4 = plot_bar(\n",
    "    q4_x,\n",
    "    q4_y_per,\n",
    "    t4,\n",
    "    ylim=(0, 0.7),\n",
    "    figsize=(3.4, 4.5)\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9de027b7-47b0-4141-8978-b604fe67c185",
   "metadata": {},
   "source": [
    "#### 4.2.6. Dogs or cats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "c6c55dd8-764a-453d-8528-7f3eb2b5d259",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 340x450 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 427,
       "width": 318
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig5 = plot_bar(\n",
    "    q5_x,\n",
    "    q5_y_per,\n",
    "    t5,\n",
    "    ylim=(0, 0.5),\n",
    "    figsize=(3.4, 4.5),\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "22f55935-e9d0-47fa-b921-a6611b19c0e9",
   "metadata": {},
   "source": [
    "#### 4.2.7. Aliens belief"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "02153483-14ea-460c-8bd8-043fe169d668",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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wMKWnp4/Z3jfsePLkibxer3E+VNejt7fX7/UhPT09xnFISIjftebmZt26dUuStH37dkVFRU3ujQAAAAAAgGkzo8KO+vp64zgpKWncbWFTUlKM456eHrW3txvnc+bMkTS4HOXZs2cj7i0vL5ckBQUF+e3m4vV6debMGXk8HiUnJ2vVqlVTei8AAAAAAGB6zKiwo6mpyTgebTtZX+Hh4QoNDQ14/+LFi2W1WiVJZ86c0ZMnT9Tb26v29nZdvnzZCDsWLlwom81m3FdQUKDa2lpZrVbt27dv3MAFAAAAAAC8WTNqNxbf2hkTXToSFRWl3t5eSTK2mZUGi5Bu2rRJ169fV0dHh77//vsR99psNm3fvt04d7lcunz5siRp06ZNxuyQ1y0vL2/cLW8D1REBAAAAAAAzLOxwu93G8fA6GqPxbed7vyRt3rxZVqtVN2/eNGqBDImPj9fPfvYzxcXFGa/9+OOPcrvdmjt3rnJzcyUNLmt59OiRCgoK1NjYKK/Xq7i4ONntdq1evXrETjETfZ++wcxPQdS/to/fCJgCfrcwnfj9AgAAeDfNqLBjaMtZScYSlPH4tvO9f0hubq5WrVql6upquVwuWa1WxcfHKzEx0W+JyuPHj/XkyRNZLBbt27dPVqtVXq9Xp06dUnFxsV+fL1++1MuXL1VRUaEjR45MeKxDbDabIiMjx2zT1dWlkJCQcdsBAAAAAPBTM6PCjqEdVKTBwqIT4dvO935fYWFhysrKGrWPnp4enT9/XpK0Zs0aJSUlSZIePnxoBB3r1q1Tbm6ugoODVVBQoMuXL6uyslI3btzQ1q1bJzTWIRs2bNCGDRsmdQ8AAAAAABg0owqU+hYKHb7sZDS+7Xzvn4xLly6ps7NT0dHRRnDh9Xp1+/ZtSYO7vuzatUsREREKDQ3Vxo0blZ2dLUm6f//+iOUzAAAAAABg+syosCMiIsI4drlcE7rHt91UlnxUV1ersLBQkvTBBx8YgUlLS4uxlW1OTs6I+4Zec7vdqqurm/RzAQAAAADA1MyosGPu3LnGcWtr67jtu7q6jJ1Yht8/Ef39/Tpz5owkafny5Vq4cKFxraWlxTj2LWI6xHdr3Obm5kk9FwAAAAAATN2MCjsWLFhgHNfV1cnr9Y7Zvra21jgOCwtTTEzMpJ53/fp1tba2atasWdq1a5ffNd+lKYGWx4SGhgZsCwAAAAAApteMCjvS09ONrWR7enpUVVU1ZvuysjLjePHixX67q4ynoaFBd+/elSTt3LlT4eHhftd9t7QNtE2s7/KZqdYKAQAAAAAAkzejwg6bzea3a8rNmzdHnd3R1NSkx48fG+dDBUMnYmBgQKdPn9bAwIDS09MD3uu7dCVQ6FJdXR2wLQAAAAAAmF4zKuyQpC1btshqtUqSampqdOHCBQ0MDPi1aW9v1/Hjx43XFy5cqNTU1Ak/4969e6qvr1dISIj27dsXsM2cOXOMZTEFBQV+Mzl6e3uVl5cnaTCgSU5OnvgbBAAAAAAAr8TiHa/wxTuosLBQp0+fNs5jY2O1ePFihYWFqaWlReXl5caWs1FRUfr8888VHR09ob7b2tr0P//zP+rr69POnTu1fv36UdsWFBTo7NmzkgZ3isnOzpbValVpaalRQHXTpk3GdrUAAAAAAGD6zciwQ5IePnyoixcvjln8c/78+Tp48OCklpH86U9/0vPnz5WQkKDPP/9cQUGjT37xer06deqUiouLA17PyMjQkSNHjJkoAAAAAABg+s3YsEOSnE6nHj58qIqKCjmdTrndboWHh2vevHlaunSpli9fPmZYMVxxcbFOnjypoKAg/fKXv9S8efPGvcfr9erRo0cqKChQY2OjvF6v4uLilJ2drTVr1kzq+QAAAAAA4NXN6LADAAAAAABgOKYdAAAAAAAAUyHsAAAAAAAApkLYAQAAAAAATIWwAwAAAAAAmErw2x4AAGB0z549U3t7u5KSkvx2iHI6nSotLVVMTIyWLl36FkcIAAAAvHsIOwDgHXX69GkVFhYa5+vWrdPOnTtlsVj04sULXb58WcuXLyfsAAAAAIYh7AAm4fr167px44Yk6cMPP5Tdbn/LI4JZNTU1+QUdknTv3j11d3dr165dKi8vlyTNmTPnbQwPAAAAeKcRduAno6enR6WlpaqsrFRDQ4O6u7vV19enkJAQzZo1S7GxsYqPj1dCQoLS0tIUERHxtoeMd9i///u/y+l0GudZWVk6fPjwuPf19PTot7/9rXH+m9/8JmC7iooKSVJmZqYOHDigoqIiXblyRY8ePdKjR48kSVarlcBtBqqurtazZ89UXV2tjo4OdXV1yWq1Kjw8XHFxcUpPT1dWVpZiYmLeyviKiorU3t4uaXA2UVhY2FsZBwAAwKsg7MBPQkFBgS5fvqze3t4R19xut9xut9rb21VVVWW8/umnnyozM/NNDhMzWHl5uWpra5WcnPxa+nO5XJKkhQsXKiwsTOvXr1dqaqouXbokh8Oh8PBw7dy5U1FRUa/leZh+tbW1xs9vOI/HI7fbrba2Nj179kyXL19WTk6O3n//fYWHh7/RcRYVFammpkaSZLfbCTsAAMCMRNgB07tx44auX79unAcHBys1NVXx8fEKCwtTf3+/Ojs79fLlS718+VIDAwOSpP7+/rc1ZMxQly9f1ueff/5a+tq9e7d2797t99r8+fN19OjR19I/3qwHDx7o/Pnz8nq9xmvx8fFKSUlRRESE+vv75XQ6VVlZqa6uLg0MDCg/P1+VlZU6cuSI5s6d+xZHDwAAMPMQdsDU6uvrjRobkrRs2TLt3r171G9Ke3t7VVFRocLCQlkslhHX33//fb3//vvTNl7MTBaLRV6vV3V1dSorK9OSJUve9pDwDrl//77Onz9vnCcmJmrPnj1asGDBiLZer1eFhYW6fPmyenp61NbWpj/+8Y/65S9/+daWtQAAAMxEQW97AMB0evjwofFNakJCgg4cODDmlPDQ0FAtX75cR48e1aJFi97UMDHDrVy50ji+evWqMTsIcDgcunjxonGelZWlX/ziFwGDDmkwOMvJydHf//3fKzIyUpLU3d2t48ePy+PxvJExAwAAmAEzO2Bq9fX1xvHSpUsDztYYTaC2E9mN5eTJkyouLpYkffbZZ0pNTVVzc7MxJb2jo0NBQUGKi4vTypUrlZ2dLavVatw/MDCgsrIyFRUVqampSV1dXZo1a5ZSU1OVm5ur+Pj4Cb8HvBk5OTmqqalRS0uLWlpaVFBQoDVr1rxSn21tbaqoqFBNTY2amprkcrnU398vm82m6OhoJScna+XKlZo/f/6E+/R6vSovL1dZWZkcDoe6urokSeHh4UpMTNTSpUu1ePHiSf07wdguXrxohF9xcXH66KOP/P69j2bu3Ln66KOPdOzYMUmDf8uKi4uVk5Pj1y7Q35uxjNV+eNFdSfqP//iPgP38+te/NmaatLe3G+1SUlL0i1/8QgMDAyotLVVpaakaGxvV2dkpj8cTcIxOp1MPHz5UZWWl2tvb1dPTo7CwMMXGxio9PV2rVq2iNg0AAJg0wg6YmtvtfttDUGFhoX788ccRNUAcDoccDodKS0t15MgRhYSEqLOzU//7v/+rFy9e+LXt6OhQSUmJHj9+rAMHDmjp0qVv8i1gHEFBQdq2bZv+8pe/SBqsE7NixQqFhoZOqT/fUG24np4e9fT0qKGhQQ8ePNCqVau0e/fucT9At7e36/jx434BoO+19vZ2lZaWKiEhQYcOHVJ0dPSUxo6/qampUV1dnXG+a9cuhYSETPj+tLQ0LV26VI8fP5Yk3blzRytXrnznwyin06m//vWvAQuxDpeXl6dr166N+PvY1dWlrq4uORwO5eXladu2bVq3bt10DRkAAJgQYQdMLSIiQi0tLZKkZ8+eacOGDW/0+c+ePVNeXp68Xq/S09OVkJCg4OBgNTQ0qLy8XF6vV1VVVbpw4YJ27dqlb7/9Vg0NDYqMjNSiRYsUHR2t7u5uPXnyRG1tbRoYGNDJkye1YMECxcbGvtH3grFlZWUpKSlJdXV16urq0p07d7R169Yp9dXd3S1psJhuYmKi5s6dq/DwcAUFBRkfAIc+SBYUFMjr9Wrfvn2j9ud0OvX73/9eHR0dkgbDmczMTM2bN0+S9PLlS1VWVmpgYEAvXrzQ7373O33xxRd8m/6KysrKjOPY2FhlZGRMuo81a9YYYUdra6saGxuNn9vrtmnTJvX29qqgoEBtbW3Ga4FCu9F2aOnv79df/vIX1dfXa9asWVq4cKFiY2PV39+vly9f+gU1V69e1a1bt4zzmJgYLVq0SBEREers7NTTp0/V3t6u/v5+XbhwQT09PdRMAgAAE0bYAVNLT083tlCsqqrSuXPntHnzZkVERLyR59+5c0cRERH65JNPlJiY6Heturpaf/rTnzQwMKCioiL19vaqoaFBa9as0Y4dOxQc/Ld/ntu2bdP333+vZ8+eqb+/X3l5efrggw/eyHvAxO3YsUO///3vJUn37t3TmjVrjLoLkzF//nx9/PHHWrhw4agzARwOh44fPy6Xy6WHDx/KbrcrKSkpYNsffvjBCDpiYmJ05MiREcuhGhoa9N1338nlcqmjo0MnTpzQZ599Numx42+G/vZIg7M0pjIjIykpSSEhIerr65M0+HdjusKOVatWSZIqKiqMsCMnJ2dShVGHZqUtW7ZMe/fuHXV20/Pnz/2CjtzcXG3ZskVBQX8rJbZjxw5dvXpVeXl5kgZnTKWmpo67VAcAAECiQClMbu3atX7fTufn5+vf/u3f9Ic//EGXLl1SSUmJmpqa/LaDfJ0sFkvAoEOSUlNTlZ2dLWmwTsfjx4+1aNEi7dmzxy/okCSr1eoXbvh+Y4x3R1JSkrKysiRJfX19unbt2pT6WblypZYuXTrmkofExEQdPnzYOC8oKAjYrrKyUrW1tZIGZ4r8/Oc/D1j3Zd68efr000+N5TDV1dWqqqqa0vgxqLm52TgerSDpeIKCgvx+Xk1NTa88rumWmJioAwcOjLmMy3c7cLvdrm3btvkFHdLg370dO3Zo+fLlAe8DAAAYC2EHTC00NFRHjx7V3LlzjdcGBgZUW1urvLw8/fDDD/rv//5v/fa3v9V3332nR48evdYdDxYtWhQw6PC97mvLli2jto2JiTG+0e3q6pLL5Xo9g8Rr5fuhbajI7HRJSEhQXFycJP9ZBL6GilFKg9/SD7UPJD4+3q/oblFR0Wsa6U9Pb2+v39+SsXaBGo/vvUNLnN5lmzdvHnMWS2trq1HLZKjezVi2b99u9FdTU6PW1tbXN1gAAGBaLGOB6cXFxenLL79USUmJCgsLjW+5ffX29qqiokIVFRW6evWqPvjgAy1cuPCVnz3eGn3fuhsRERHjTk+PjY1VQ0ODJKmzs5OaCu+guLg4rVq1Sg8ePJDX69Xly5f1d3/3d1Puz+12q7GxUa2trXK73erv7/ebiTT0gXqotsHwWUG+v+8TKWy7bNkyY5ZIoH8rmJjhxZFtNtuU+/K9t7e3d8r9vAnBwcFKT08fs41vMJeSkjLussKoqCilpKSourpa0uDv5ezZs195rAAAwNwIO/CTYLVaZbfbZbfb1d3dLYfDofr6ejU0NMjhcBj1DKTBYo7fffedDhw44Dd9eirGW+vuu0xhIrtf+H7oGVrDj3fP5s2bVVxcLLfbrYqKClVXV0+6zkBjY6OuX7+uioqKCc826unp8asR0t/f77eV6ERqPfhuZdve3i6PxzOhrVLhb3i48So7Q/neO9Udft6U2bNnj1iOMpzvzIyJbp08f/58I+xgZgcAAJgIwg785AztEOA7c6OxsVH3799XYWGh8a35mTNnlJaW9krFTId/yz6c71Tv8doON111RvDqwsPDtXHjRqNmx+XLl/UP//APEy5QWVJSopMnT2pgYGBSzx0eivT09BjHwcHBE5pdEBoaKqvVavTV09Pzxgr6mkloaKiCgoKMn2FXV9eU+/K9d9asWa88tuk0kTDG9/dyou9npi3lAQAAbx9hB6DBWgX79u1TSkqKTpw4IWlw5kRxcbE2btz4lkeHmWj9+vXKz89XR0eHXrx4odLS0gnNFGppadGpU6eMD8lpaWlasWKFFixYoMjISIWEhPgFY3/84x9HrdeBt2vOnDlqbGyUNLi971QMDAwYfUjyqz/0LprsjjNT2aFmKvcAAICfHgqUAj5WrFjhN9V/aBtFYLJCQkL0/vvvG+fXrl2b0HKUBw8eGO1Wr16to0ePym63Kz4+XrNmzRoxA8j3W/LhfL817+/vn9BSCrfb7TfOsLCwce9BYL5Ll54/fz6l2Vh1dXV+S9bGWg41kf7fheVvvr9TE53x4tuO30kAADARhB3AMHPmzDGO3/VigHi32e1245v4trY2PXjwYNx7HA6HcZybmztmW4/HM2b9AqvV6lcLZqi47Vjq6+uN45iYGOp1vIIlS5YYx21tbaqsrJx0H/n5+cbx7NmzR2wbPNk6Pr41XN4W3x2BJjrjxbfdWDsKAQAADCHsAIaZSevj8W4LCgrS9u3bjfNbt26NG6D5ztQYr1bGkydP1N/fP2ab5ORk4/jx48djth3exvdeTF5KSorf1tMXLlwY9+flq6amRqWlpcb5xo0bRyzh8P0daW5uHrO/jo6OCYULvgVGp6M2kO/vVU1NjTo7O8ds39HR4bczEL+XAABgIgg7YGpVVVUT3slCGvyw4Fv/wPeDCjAVCxcuNJYedHd36/bt22O29w3Yxvpg2tvbqytXroz7fLvdbhw/fPhQLS0to7ZtampSYWFhwHsxNTt27DDCg5aWFp04cWJCf5Oam5v1f//3f8b5ggULlJ2dPaKd724m5eXlY/Z57dq1CRW99S0yOh3FQGfPnq2kpCRJgzVJxvs9vnz5sjHulJQUvy27AQAARkPYAVO7cuWK/vM//1M3btwY80OeJFVXV+vbb781/k91aGioli1b9iaGCZPznd3x8OHDMdumpKQYxz/++KNcLteINm1tbTp27Jja2trGfXZ6errRZ39/v/785z/7Fbwc0tjYqD//+c/GB/HU1FSlpaWN2z/Glpyc7PfzLysr0zfffDNqkOX1elVYWKg//OEPxpbYYWFhOnToUMAlRWlpaUYNC4fDoTt37oxo4/F4dOXKFb8gayy+S/mqqqomdM9k+dazKSoq0tWrV0cEMQMDA7p8+bIePXoU8D4AAICxsBsLTM/lcun69eu6fv26YmNjtWDBAsXExCgsLEwej0cul0u1tbV+U8AtFov27t3Llpt4LRISErRs2TKVlpaOuyxg7dq1ys/Pl9vtVn19vf7rv/5LWVlZmj17trxerxoaGlRZWSmPx6O0tDR5PB6/Kf6BfPTRR/rd736njo4OtbW16euvv1ZmZqYxK+Dly5d69uyZ8WEzMjJSH3300et589D69etlsVh08eJFeb1e1dXV6euvv9a8efOUnJysiIgI9ff3y+l06vnz537LOmJjY3XkyBHFxMQE7Ds4OFibNm3SpUuXJA3OgigrK1N6erpCQkLkdDpVUVEhl8uluXPnKi4ubtwZIAsXLtStW7ckDc4GaW5u1ty5c/2K42ZnZ09om9nRpKena9OmTcZzbt26pdLSUi1cuFARERHq7OzU06dP1d7ebtyzefPmMQu0AgAA+CLsgKmlpKSoubnZ2IWira1t3G/DZ8+erd27dyszM/MNjBA/FVu3blV5efm4SxiioqJ0+PBhHT9+XL29verv71dJScmIdpmZmTpw4IC+//77cZ8dHR2tzz//XMePH1d9fb0GBgb09OlTPX36dETbhIQEHTp0SFFRURN/cxjXunXrNH/+fF26dMnY5amhoWHUorFBQUFauXKltmzZovDw8DH7Xr9+vZqbm42ZGy9evBixk9TQz/XatWvjjjUpKUnZ2dkqLi7WwMCAiouLR7RZtGjRK4Ud0uC/idDQUF2/fl39/f1qa2vT/fv3R7QLDg7W1q1btX79+ld6HgAA+Gkh7ICp7dixQ1u3blVtba1qa2tVX1+vlpYWdXZ2yu12y2q1ymazKTY2VvPmzdOiRYuUnp7ODhR47WJjY7V69Wrdu3dv3Lbp6en6x3/8R927d0+VlZVqb2+X1+tVRESE5s+fr+XLl/vt9DERMTEx+uKLL1RWVqaysjK9ePHCKMYbHh6uxMRELVmyRFlZWSOKYOL1SElJ0RdffKHq6mpVVFSopqZGLpdL3d3dslqtCg8P1+zZs5WRkaGsrKxRZ3MMZ7FYtH//fi1evFgPHz7Uixcv1N3drVmzZikuLk7Lly+X3W6f1N+1Dz/8UOnp6SopKVFDQ4O6u7snVf9oojZu3Khly5apoKBAz58/V1tbm3p7exUaGqrY2FhlZGRo1apVhG8AAGDSLN7pKLUOAAAAAADwllCgFAAAAAAAmAphBwAAAAAAMBXCDgAAAAAAYCqEHQAAAAAAwFQIOwAAAAAAgKkQdgAAAAAAAFMh7AAAAAAAAKZC2AEAAAAAAEyFsAMAAAAAAJgKYQcAAAAAADAVwg4AAAAAAGAqhB0AAAAAAMBUCDsAAAAAAICpEHYAAAAAAABTIewAAAAAAACmQtgBAAAAAABMhbADAAAAAACYCmEHAAAAAAAwFcIOAAAAAABgKoQdAAAAAADAVAg7AAAAAACAqRB2AAAAAAAAUyHsAAAAAAAApkLYAQAAAAAATIWwAwAAAAAAmMr/Azybc1pIPFAuAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 340x450 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 427,
       "width": 541
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig6 = plot_bar(\n",
    "    q6_x,\n",
    "    q6_y_per,\n",
    "    t6,\n",
    "    ylim=(0, 0.6),\n",
    "    figsize=(3.4, 4.5),\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5ae03a53-d2c7-41c5-ab87-a507afc9e5f7",
   "metadata": {},
   "source": [
    "#### 4.2.8. GIF pronunciation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "247c4074-a28b-4636-bfa3-90e97fd33746",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 800x400 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 377,
       "width": 777
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig7 = plot_bar(\n",
    "    q7_x,\n",
    "    q7_y_per,\n",
    "    t7,\n",
    "    horizontal=True,\n",
    "    xlim=(0, 0.7),\n",
    "    figsize=(8, 4),\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d9f11d62-b37c-45f4-ae1d-bb5a260f8713",
   "metadata": {},
   "source": [
    "#### 4.2.9. IT support person"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "115146b5-a235-4b43-8f8f-8377af2e0442",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x400 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 377,
       "width": 879
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig8 = plot_bar(\n",
    "    q8_x,\n",
    "    q8_y_per,\n",
    "    t8,\n",
    "    horizontal=True,\n",
    "    xlim=(0, 0.6),\n",
    "    figsize=(8, 4),\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "19cce682-304d-4d54-82fc-11214f15a455",
   "metadata": {},
   "source": [
    "### 4.3. Export images"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "c6759dea-ddc2-4b79-a50f-743bbc626402",
   "metadata": {},
   "outputs": [],
   "source": [
    "figures = [fig0, fig1, fig2, fig3, fig4, fig5, fig6, fig7, fig8]\n",
    "\n",
    "file_names = [\n",
    "    \"q0_survey_respondents\",\n",
    "    \"q1_caffeinated_beverages\",\n",
    "    \"q2_tabs_or_spaces\",\n",
    "    \"q3_desire_to_go_to_mars\",\n",
    "    \"q4_star_wars_or_star_trek\",\n",
    "    \"q5_dogs_or_cats\",\n",
    "    \"q6_aliens_belief\",\n",
    "    \"q7_gif_pronunciation\",\n",
    "    \"q8_it_support_person\",\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "b1390e0d-d1c9-4a7b-86c1-00286fcedf3e",
   "metadata": {},
   "outputs": [],
   "source": [
    "for fig, file_name in zip(figures, file_names):\n",
    "    fig.savefig(f\"images/pt-br/{file_name}.png\", bbox_inches=\"tight\", dpi=500)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.3"
  },
  "toc-autonumbering": false,
  "toc-showcode": false,
  "toc-showmarkdowntxt": false,
  "toc-showtags": false
 },
 "nbformat": 4,
 "nbformat_minor": 5
}