{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Model SIM "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Model SIM is introduced in chapter 3 of {cite:t}`GodleyLavoie2006MonetaryEconomicsIntegrated` \"Monetary Economics: An Integrated Approach to Credit, Money, Income, Production and Wealth\" and represents the \"simplest model with government money\". That is, this is a model with only _outside money_ (from the government)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Module Contents\n",
    "\n",
    "As with all `MacroStat` models, SIM is divided into Variables, Parameters (fixed constants), Scenarios, and the Behavior (model initialization and steps). The module-level documentation, such as all variables/parameters/scenarios and their notation or the behavioral equations associated with each function of `BehaviorSIM.py` can be seen in:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```{eval-rst}\n",
    ".. toctree::\n",
    "    :maxdepth: 2\n",
    "\n",
    "    Variables <GL06SIM/variables.rst>\n",
    "    Parameters <GL06SIM/parameters.rst>\n",
    "    Equations <GL06SIM/behavior.rst>\n",
    "    Scenarios <GL06SIM/scenarios.rst>\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    ":::{Note}\n",
    "The remainder of this page gives an introduction to the model, notes on how it is implemented in `MacroStat` and then shows some of the model dynamics by replicating the relevant graphs of Godley and Lavoie (2006).\n",
    ":::"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model Overview"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Behavioral Equations"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The SIM model is introduced in Chapter 3, and consists of the following 11 equations and 11 unknowns:\n",
    "\n",
    "1. Consumption good supply equals demand\n",
    "```{math}\n",
    ":label: gl06_sim_eq301_consumptionClearing\n",
    "C_s(t) = C_d(t)\n",
    "```\n",
    "2. Governmend good supply equals demand\n",
    "```{math}\n",
    ":label: gl06_sim_eq302_governmentClearing\n",
    "G_s(t) = G_d(t)\n",
    "```\n",
    "3. Tax supply equals demand\n",
    "```{math}\n",
    ":label: gl06_sim_eq303_taxClearing\n",
    "T_s(t) = T_d(t)\n",
    "```\n",
    "4. Labour supply equals demand\n",
    "```{math}\n",
    ":label: gl06_sim_eq304_labourClearing\n",
    "N_s(t) = N_d(t)\n",
    "```\n",
    "5. Disposable income is wage income minus taxes\n",
    "```{math}\n",
    ":label: gl06_sim_eq305_disposableIncome\n",
    "YD(t) = W(t)\\cdot N_s(t) - T_s(t)\n",
    "```\n",
    "6. Tax demand is a fixed proportion of wage income\n",
    "```{math}\n",
    ":label: gl06_sim_eq306_taxDemand\n",
    "T_d(t) = \\theta\\cdot W(t)\\cdot N_s(t)\n",
    "```\n",
    "7. Consumption demand is a share of disposable income and deposits\n",
    "```{math}\n",
    ":label: gl06_sim_eq307_consumptionDemand\n",
    "C_d(t) = \\alpha_1\\cdot YD(t) + \\alpha_2\\cdot H_h(t-1)\n",
    "```\n",
    "8. The change in government stock of money is demand minus tax\n",
    "```{math}\n",
    ":label: gl06_sim_eq308_governmentDeposits\n",
    "\\Delta H_s(t) = H_s(t) - H_s(t-1) = G_d(t) - T_d(t)\n",
    "```\n",
    "9. The change in household deposits is disposable income minus expenditure\n",
    "```{math}\n",
    ":label: gl06_sim_eq309_householdDeposits\n",
    "\\Delta H_h(t) = H_h(t) - H_h(t-1) = YD(t) - C_d(t)\n",
    "```\n",
    "8. Total national income is consumption of households and government\n",
    "```{math}\n",
    ":label: gl06_sim_eq310_nationalIncome\n",
    "Y(t) = C_s(t) + G_s(t)\n",
    "```\n",
    "8. Labour Demand is national income over wages\n",
    "```{math}\n",
    ":label: gl06_sim_eq311_labourDemand\n",
    "N_d(t) = \\frac{Y(t)}{W(t)}\n",
    "```\n",
    "\n",
    "With the redundant equation being\n",
    "```{math}\n",
    ":label: gl06_sim_eq312_redundant\n",
    "\\Delta H_s(t) = \\Delta H_h(t)\n",
    "```\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Transaction Flow Matrix\n",
    "\n",
    "The accounting of transactions for model SIM is as follows:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```{csv-table} Accounting Transaction Matrix for Model SIM\n",
    ":file: GL06SIM/transaction_matrix.csv\n",
    ":header-rows: 2\n",
    ":stub-columns: 1\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Balance Sheet Matrix"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```{csv-table} Balance Sheet for Model SIM\n",
    ":file: GL06SIM/balance_sheet.csv\n",
    ":header-rows: 2\n",
    ":stub-columns: 1\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Implementation in MacroStat"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Transposing these eleven equations to the `MacroStat` framework, we consider that there are:\n",
    "\n",
    "1. Three parameters (fixed constants): $\\alpha_1$, $\\alpha_2$, and $\\theta$ (see [Parameters](GL06SIM/parameters.rst))\n",
    "2. Two scenario variables : $G_d(t)$ and $W(t)$ (see [Scenarios](GL06SIM/scenarios.rst))\n",
    "3. The remaining 14 tracked series are variables (see [Variables](GL06SIM/variables.rst))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Behavioral Modeling"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For the implementation of the behavioral equations (see [Behavior](GL06SIM/behavior.rst)), most prior implementations have made use of some form of linear solver or iteration until the system is solved. To simplify the implementation in Macrostat, we can note that the system can be solved analytically for a given timestep as follows:\n",
    "\n",
    "Substitute into Eq. {eq}`gl06_sim_eq311_labourDemand` to obtain\n",
    "```{math}\n",
    "N_d(t) =\\frac{1}{W(t)}(C_d(t) + G_d(t))\n",
    "```\n",
    "where we can already note that $W(t)$ and $G_d(t)$ are exogenously given (they are scenario variables). This leaves us to solve for $C_d(t)$, where we can use Eq. {eq}`gl06_sim_eq307_consumptionDemand` and Eq. {eq}`gl06_sim_eq305_disposableIncome` to obtain\n",
    "```{math}\n",
    "N_d(t) =\\frac{1}{W(t)}(\\alpha_1(1-\\theta)W(t)N_s(t) + \\alpha_2 H_h(t-1) + G_d)\n",
    "```\n",
    "now noting from Eq. {eq}`gl06_sim_eq304_labourClearing` that supply=demand, we can rewrite the above as\n",
    "```{math}\n",
    ":label: gl06_sim_eq13_solutionLabourDemand\n",
    "N_d(t) =\\frac{\\alpha_2 H_h(t-1) + G_d}{W(t)(1-\\alpha_1(1-\\theta))}\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Therefore, for a given period $t$ we can solve the system by solving, in order:\n",
    "1. Eq. {eq}`gl06_sim_eq302_governmentClearing` given the scenario variable\n",
    "2. Eq. {eq}`gl06_sim_eq13_solutionLabourDemand` for labour demand based on prior information $H_h(t)$ and scenario variables $W(t)$ and $G_d(t)$ (this replaces the need to run Eq. {eq}`gl06_sim_eq311_labourDemand`)\n",
    "3. Eq. {eq}`gl06_sim_eq304_labourClearing`\n",
    "4. Tax demand, given labour, Eq. {eq}`gl06_sim_eq306_taxDemand`\n",
    "5. Tax supply, given demand, Eq. {eq}`gl06_sim_eq303_taxClearing`\n",
    "6. Disposable income, given labour supply and tax demand, Eq. {eq}`gl06_sim_eq305_disposableIncome`\n",
    "7. Consumption demand, given disposable income, Eq. {eq}`gl06_sim_eq307_consumptionDemand`\n",
    "8. Consumption supply, given demand, Eq. {eq}`gl06_sim_eq301_consumptionClearing`\n",
    "9. Government stock of money, Eq. {eq}`gl06_sim_eq308_governmentDeposits`\n",
    "10. Household stock of deposits, Eq. {eq}`gl06_sim_eq309_householdDeposits`\n",
    "11. National income, Eq. {eq}`gl06_sim_eq310_nationalIncome`\n",
    "\n",
    "This is implemented as such in the [Behavior](GL06SIM/behavior.rst) class. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model Dynamics"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Preparatory Steps"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The autoreload extension is already loaded. To reload it, use:\n",
      "  %reload_ext autoreload\n"
     ]
    }
   ],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "\n",
    "from matplotlib import pyplot as plt\n",
    "from macrostat.models import get_model\n",
    "from macrostat.util import latex_model_description\n",
    "\n",
    "plt.style.use(\"../../macrostat.mplstyle\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Convergence to the Steady State"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In {cite:t}`GodleyLavoie2006MonetaryEconomicsIntegrated` models are initialized with almost all of the variables set to zero. For model SIM the only non-zero item is that in period 0 the government demand is 20, i.e. the government creates 20 monetary units of demand. Thereafter the system converges to a steady state. We can see this by simulating the default parameters and checking that total national income is 100. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "GLO6SIM = get_model(\"GL06SIM\")\n",
    "model = GLO6SIM()\n",
    "model.simulate()\n",
    "output = model.variables.to_pandas()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The consumption demand is a function of the disposable income, the propensity to consume income, and the propensity to consume savings. Equation (3.7) in the book.\n",
      "In the model it is assumed that the supply will adjust to the demand, that is, whatever is demanded can and will be produced. Equation (3.1) in the book.\n",
      "The disposable income is the wage bill minus the taxes. Equation (3.5) in the book.\n",
      "The government money stock is a function of the government demand, and the tax supply. Equation (3.8) in the book.\n",
      "In the model it is assumed that the supply will adjust to the demand, that is, whatever is demanded can and will be produced. Equation (3.2) in the book.\n",
      "The household money stock is a function of the disposable income, the propensity to consume income, and the propensity to consume savings. Equation (3.9) in the book.\n",
      "We can resolve the labour demand from the national income equation, together with the consumption demand (+ disposable income) and the government demand knowing that labour demand is equal to labour supply.\n",
      "The labour income is the wage rate times the labour supply. This is an intermediate variable used to calculate the disposable income, but is computed explicitly here to compute the transaction flows.\n",
      "In the model it is assumed that the supply will be equal to the amount of labour demanded. Equation (3.4) in the book\n",
      "The national income is the sum of the consumption demand, the government demand, and the tax supply. Equation (3.10) in the book.\n",
      "The tax demand is a function of the tax rate, the labour supply, and the wage rate. Equation (3.6) in the book.\n",
      "In the model it is assumed that the supply will be equal to the amount of taxes demanded. Equation (3.3) in the book\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'\\\\documentclass{article}\\n\\\\usepackage{amsmath}\\n\\\\usepackage{amssymb}\\n\\\\begin{document}\\n\\\\title{BehaviorGL06SIM}\\n\\\\maketitle\\n\\\\section{Step Equations}\\n\\\\subsection{Consumption Demand}\\nThe consumption demand is a function of the disposable income, the propensity to consume income, and the propensity to consume savings. Equation (3.7) in the book.\\n\\n\\\\begin{align}\\\\label{eq:consumption_demand}\\nC_d(t) = \\\\alpha_1 YD(t) + \\\\alpha_2 H_h(t-1)\\n\\\\end{align}\\n\\n\\n\\\\subsection{Consumption Supply}\\nIn the model it is assumed that the supply will adjust to the demand, that is, whatever is demanded can and will be produced. Equation (3.1) in the book.\\n\\n\\\\begin{align}\\\\label{eq:consumption_supply}\\nC_s(t) = C_d(t)\\n\\\\end{align}\\n\\n\\n\\\\subsection{Disposable Income}\\nThe disposable income is the wage bill minus the taxes. Equation (3.5) in the book.\\n\\n\\\\begin{align}\\\\label{eq:disposable_income}\\nYD(t) = W(t) N_s(t) - T_s(t)\\n\\\\end{align}\\n\\n\\n\\\\subsection{Government Money Stock}\\nThe government money stock is a function of the government demand, and the tax supply. Equation (3.8) in the book.\\n\\n\\\\begin{align}\\\\label{eq:government_money_stock}\\nH_s(t) = H_s(t-1) + G_d(t) - T_d(t)\\n\\\\end{align}\\n\\n\\n\\\\subsection{Government Supply}\\nIn the model it is assumed that the supply will adjust to the demand, that is, whatever is demanded can and will be produced. Equation (3.2) in the book.\\n\\n\\\\begin{align}\\\\label{eq:government_supply}\\nG_s(t) = G_d(t)\\n\\\\end{align}\\n\\n\\n\\\\subsection{Household Money Stock}\\nThe household money stock is a function of the disposable income, the propensity to consume income, and the propensity to consume savings. Equation (3.9) in the book.\\n\\n\\\\begin{align}\\\\label{eq:household_money_stock}\\nH_h(t) = H_h(t-1) + YD(t) - C_d(t)\\n\\\\end{align}\\n\\n\\n\\\\subsection{Labour Demand}\\nWe can resolve the labour demand from the national income equation, together with the consumption demand (+ disposable income) and the government demand knowing that labour demand is equal to labour supply.\\n\\n\\\\begin{align}\\\\label{eq:labour_demand}\\nN_d(t) =\\\\frac{\\\\alpha_2 H_h(t-1) + G_d}{W(t)(1-\\\\alpha_1(1-\\\\theta))}\\n\\\\end{align}\\n\\n\\n\\\\subsection{Labour Income}\\nThe labour income is the wage rate times the labour supply. This is an intermediate variable used to calculate the disposable income, but is computed explicitly here to compute the transaction flows.\\n\\n\\\\begin{align}\\\\label{eq:labour_income}\\nW(t) N_s(t)\\n\\\\end{align}\\n\\n\\n\\\\subsection{Labour Supply}\\nIn the model it is assumed that the supply will be equal to the amount of labour demanded. Equation (3.4) in the book\\n\\n\\\\begin{align}\\\\label{eq:labour_supply}\\nN_s(t) = N_d(t)\\n\\\\end{align}\\n\\n\\n\\\\subsection{National Income}\\nThe national income is the sum of the consumption demand, the government demand, and the tax supply. Equation (3.10) in the book.\\n\\n\\\\begin{align}\\\\label{eq:national_income}\\nY(t) = C_s(t) + G_s(t)\\n\\\\end{align}\\n\\n\\n\\\\subsection{Tax Demand}\\nThe tax demand is a function of the tax rate, the labour supply, and the wage rate. Equation (3.6) in the book.\\n\\n\\\\begin{align}\\\\label{eq:tax_demand}\\nT_d(t) = \\\\theta N_s(t) W(t)\\n\\\\end{align}\\n\\n\\n\\\\subsection{Tax Supply}\\nIn the model it is assumed that the supply will be equal to the amount of taxes demanded. Equation (3.3) in the book\\n\\n\\\\begin{align}\\\\label{eq:tax_supply}\\nT_s(t) = T_d(t)\\n\\\\end{align}\\n\\n\\n\\\\end{document}'"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "latex_model_description.make_latex_model_description(GLO6SIM().behavior)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### National Income"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "steady_state_income = model.scenarios[(0,\"GovernmentDemand\")][0] / model.parameters[\"TaxRate\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(1, 1, figsize=(5, 3))\n",
    "axs.plot(output.index, output['NationalIncome'], color='k', label='National Income (Y)')\n",
    "axs.axhline(y=steady_state_income, color='r', linestyle='--', label=r'Steady State Income $Y^\\star=\\frac{G}{\\theta}$')\n",
    "axs.legend(loc='lower right', frameon=False)\n",
    "axs.set_xlim(0,40)\n",
    "axs.set_title('Figure SIM.0: Convergence of National Income\\nto the Steady State')\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Disposable Income and Consumption\n",
    "\n",
    "Corresponding to Figure 3.2 \"Disposable income and consumption starting from scratch\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "steady_state_consumption= (model.scenarios[(0,\"GovernmentDemand\")][0] * (1-model.parameters[\"TaxRate\"])) / model.parameters[\"TaxRate\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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OMxXUtWtXGBkZcafi7t+/jy5duqB27dplWq65ubnUsJ+fH3Jzc7Fx40bupaCgUOz8Hz16BMYYzMzMMH/+fJw/fx5v376FoaEh1q5dW6p4hg0bBrFYjNOnTwOQfNiKOyVdkZo0aYKIiIhip/n48SNycnJw9+5dZGZmypyeqlevnszjGkZGRtzf+ddR8/LyuHHGxsbo3LkzDh06BAA4efKk1JeYn58fwsLCpPZRmzZtpH5QmJmZycQ6YsQIvH37lnv048GDBxg8eLDUfEuy7z+PPz/25ORkBAYGolGjRly5oaEhZsyYUar5F3T16lWZbaqtrQ0lJSWZ7folvr6+aNiwYanqAJKEtmHDBmhpaaF169YIDw/nEkdRmjdvzl1rLGwd6tWrh5ycHNy5cwdz585FcHAwTExMYGJigr///hvW1tYAJNv6r7/+wvnz57F8+XIcPnwYAJCbm1vs8o2NjSEWi+Hr61touZ+fHxISEqT2hZGRUaE/8EuiqPcEAHh7e0u9JzQ1NeHg4AB5eXlcvXoVdevWlbmfoCSfGz09PS5p54/LT3j+/v4Qi8W4ePEit36+vr5o3rx5setR0htB83+M29raQl5evkR1PpeUlARA9jsYALS0tGQe0apqvrtr0o0aNZJ6IxdFU1MTv/zyC3x9fXHr1i0Aki+Bsvr8Q8nj8VC7dm2ZO7OLc/78edSuXVvqOpm+vj6WLl2KdevWlSoedXV1DBw4EIcOHUKvXr0q9ZrMqFGjMGfOHISFhRV5XfrIkSOYMWMG9+WQnZ0tVZ6VlSX1hVVS9vb2WLNmDZycnJCUlCR1lMTj8dCiRYti91FhX7ZmZmYYPXo0PDw8kJeXh7Fjx2Ls2LFS8y3tvi8o/wuuqLMPZZm/SCSS2aZisRg5OTll2q4qKiqlrtOpUydERUXBy8sLV69exZgxY6CkpIQBAwYUWUcgEHCJp7B1yMrKAiD5caajo4Pg4GB4e3vD19cXGzZsQHJyMtavX48XL15g4MCBmDNnDpydnREZGYnVq1d/Meb8+RdMYgXxeDyYmpqWeV+XhlgsLvI9Udi2ASTxlzX5Af+9B0eOHFloEiyKjo4OkpOTvzhd/lHw19w1/+zZMwAo9H0kEomKvC5eVXx3R9IllZiYCD6fD0dHRyxfvhyOjo4yN0IU9sb5/JGBonTp0gWhoaEyp2A+vwPxc/l3phekrq4udUNRSY0dOxY3btzAzp070bdv31LXLy/Tp09H48aNi7wpRCgUIjIyEqqqqujQoQMEAgE+fvwoNU1YWFiJz5IUNHToUHz8+BF//fWXzJ2mXbp0QVBQkNS4xMREhIaGFjvPO3fuoEePHlixYgVWr14tlaDz51uWfZ9PW1sblpaWCA4OlhofGxuLDx8+lGn+nTp1ktmm79+/h1gsLvV27dSpE8LCwkpVBwBmzZoFNTU1DBs2DLt27cKmTZtw5cqVYus8ePCAaxClsHUICwuDQCBA+/btMX/+fOTm5qJ79+5YuXIl7t69Cy8vLwCAg4MDOnbsiF9//RVycnJSP0z++eefIpf/5s0bACiyUZbC3kO5ubl4+PBhsetVFj/++KPMeyIrKwtBQUHo1KkTYmJiZH5wlfVzk69jx44QCAQy6/il97K+vj4SEhLKvNzS2LlzJ3788Uf06NFDpiwpKUnm0kJVU+OTNGOs0GsRhU3HCjzapKqqCi8vL7x9+xYxMTHcL+aCzM3NwefzkZiYCEByyjg0NJQbzp8vIHt6Z9q0adDQ0MCpU6e4cefOnfviI2Fr1qyRanYwOzsbf/75J9dqT8Flss8e1UpMTORO/QCSR5vq1q2L9+/fc9f8CtsWALBr1y6Ym5sjJiZGJiaxWFzo6avi6hSkpKSE8+fP4/bt21iwYIFUq1SpqamYP38+dz3KwMAA8+bN405RA0B8fDxu3rwpdeTz+ToUtU00NDQwYMAArF27Vuaa/MqVK+Ht7S3V0tnmzZu508aMsULXW1tbG4cOHUJUVBRiY2NlTpl+ad8XFuvn67N27Vp4enpKbdutW7dCU1OzTO+tpUuXIjg4WCq5Hjx4EMOGDUP79u2l4vnSqcrFixfj2bNnePLkCTfuzJkzACD1xfz5Ot2+fZs76gEARUVFqevaALjLMwDg4+OD58+fw9nZGQDg6uqK69evSx2hHTx4EHPnzoWBgQEyMzO5u+8/n39qaqrUZ+DKlStQUFCAUCjEy5cvufHPnj2T2ua7du3CzJkzudP7n++7xYsX48OHD7h//75UnYLLKkxJ3r+fT7Ny5Upcv35dKlHv3bsXSkpKGDJkCFq3bo2TJ09yZb6+vpCXl+cuk5RkGZ+P09XVxfz586Xu9UlKSsLly5eLXT9LS8tCfzQUth0+j6m46QoSiURYsWIFAgICcOTIkULrxcfHc/cLVFkVeVdaZbpw4QKztbVlcnJyjM/nMxsbG+bg4FDotPv27WNNmzZlPB6P9e/fnyUnJzPGJC0iAeBeWlpabNasWdydj4xJ7mCeOHEiW7NmDduxYwebPXs2q1u3LhszZgx78uQJ69q1KwPAmjZtyhYtWiS13KioKDZ27Fg2e/ZstmjRInbo0KFi18nNzY29ePGCubu7sxEjRjB7e3s2cOBAdvLkSW4aR0dH1q5dOwaAaWpqsiFDhrDAwEC2Zs0aZmpqygQCAevduzd78+YNY4yxZcuWsdu3b8tsMwUFBdavXz/uTvatW7eyunXrssjISG5ZixcvZj/99BPj8/lMTU2NDRgwgB08eJArL6xOcdLT09nKlStZ165d2ciRI9nUqVPZokWLWGxsrNR0YrGYeXh4sBkzZrC5c+eyCRMmcHe4Z2dns0GDBjEFBQWmp6fHli1bxq5fv85tk3bt2rGrV69Kzc/Ly4vNnTu30Jju3bvHhg0bxhYuXMgWLFjA/Pz8GGOMeXh4cNuzT58+7NKlS1yd3NxcZm5uzr1veDweMzY2Ztu3b+emKWrfX716VSrW69evs2XLljE9PT2mqKjIBg8ezLKzsxljkpaZ+vbty+bPn8+WLl3K/P39vzj/4oSGhrJJkyaxhQsXspkzZzJHR0eWk5PDxdW2bVsurs2bNxc7r+fPn7MRI0YwFxcX5urqyt093bJlS3b16tVCP3N2dnbM1dWVrVmzhrm4uDBHR0epu/EBsBUrVjBnZ2fm7OzMhgwZInUHOWOMBQQEsIkTJ7IFCxawqVOnMg8PD+4O7blz57K1a9cyFxcXtmbNGjZ79mz26dMnLt7evXuzRYsWsXXr1rHz58+z6dOns0GDBnF3yTs7O7MHDx4wDw8PtmbNGvbbb78xV1dXJhKJZPZdt27duNiCg4PZiBEj2Lx589iiRYvYhQsXit12Y8aMYerq6kxfX5+5urpKfY9YWVmxo0ePsk2bNjEzMzPG4/FY3759uc/YnTt3WL9+/dicOXPYsmXLpN6XqampzMHBgc2ZM4f9/vvvbMaMGdz6l2QZ79+/Z4MHD2aKiopMT0+Pu9NeLBazdevWMXt7e7Z48WK2fPly7omI4gwbNow9fPiwyHJ3d3fWvn17BoDp6OiwYcOGyXyXFPzO0tDQYKNGjWLjxo1jI0aMYO3bt2ezZs1i8fHxRS7D3Ny8yrc6xmPsCz9RvlNz5syBlpYWFi5cCCUlJWRnZ+Pdu3eYM2cORo4cifHjx1d2iKQKysvLQ+fOneHs7IwePXqAz+cjLS0NT58+hb29PW7evFns8+CkaDweD97e3lLPRZPq6/Lly7h9+zZcXV0rZfkRERGwt7eHj49PpSy/pGr86e6yevLkCaytraGkpARAckq2SZMmsLKyqvI3GpDKIxQK8e7dO7Ro0YK7oUlNTQ3t27eHkZFRiZpbJbLoWKLm6dOnDwIDA5GZmVkpy/f09MTMmTMrZdmlQUfSRYiNjcWWLVuQkZEBTU1NCAQCJCQk4IcffpB6TIeQzz179gy7du2ChoYGlJSUwOPxkJiYiJEjR3LPLpOSCwwMxJw5c+Dj4wMrKyssW7YMI0aMqOywSDl48uQJzpw5AxcXl2+63NzcXPTr1w+XL1+u8s3cUpImhBBSaa5cuQJ5eXmpxnsq2vLly9G7d+9CG9mpaihJE0II+W4EBQUhODi42pwRpSRNCCGEVFFV+2Q8IYQQ8h2jJE1INbJ9+3apxl4IITUbJenvyJUrVzBgwICvagaQVJ6dO3eiWbNmxfbTW5yVK1ciOjq6nKP6evHx8Xj48CHXRn5NdejQIfTr1w92dnaVHQqpRr67Dja+Z7169UJubi769+9f2aFUax07dkSDBg1w8ODBb7bM/KYlp06dKlOWnp4ODw8PeHt7Q19fH4qKirCwsMDcuXOxdOlS/P7776hfvz5mz56N6dOn49ChQ1/VYUF5e/ToEVasWIGoqCiEh4eX67wZY9i4cSMeP34MZWVl5OXl4ddff8X69eu5nq6+lTFjxiA1NbXUneEUJS0tDcuWLUNWVhYYY1BWVsb8+fOxatUq7Ny5s1yWQaqASmnnjFSazzulJ0U7c+YM8/b2lhnftWtXNm7cuG8ay5QpU6Sa/cz36tUrZmZmxhYuXMiEQiE3/vnz52zo0KGMz+ezsLAwbvzx48eZh4dHiZe7YcMGqfpfKzk5mTk5OcmMv379OjM2Ni635eT7888/2YwZM7jhnJwcNmvWLJnPQFH7urx5e3uX23r269ePHT9+nBuOiYlhP/74I7OxsZGabvbs2WVextfUJeWDTncTUoTbt28XOt7b2xv79+//ZnFkZGTA39+f6+giX1ZWFvr374+uXbti7dq1Ui3hWVlZYcqUKTKdYQwZMgTHjx8v8XXtorZBWRV1Sruijuw3bdqEX3/9lRuWl5eHu7s7tLW1paYr7/WsaO/evUNAQAB++eUXblzdunWxfv16mWnLum7x8fEyvWqRb4+SNCGfycvLw8WLF7F9+/bKDgWA5Eu2VatWMuO3b9+O0NBQLF++vNB6PXv2RLNmzaTGCQQCtG3b9otdQGZnZ2P//v04d+5c2QP/TFBQEObPn19u8yuJ5ORkPH/+XGqcsrIyd8mnqu3rkkpOTkZiYqJM15zt27fn+ptPT0/HmjVr8Pjx41LPPzo6GtOmTaObFKsAuiZdRT1+/Bjnzp2DkpISnj9/zvV1C0iaSZw+fTqCgoJw/fp1XLt2DYwx+Pj4wMPDAy1atODm8+TJE2zevBnm5uYQi8Wl6pbt0KFDuHr1KoyNjcEYQ+vWrbmbXqKiouDi4oLatWsjJycHampqWLZsGQQCATw9PbFy5Urk5eXh+PHjuHLlClJTU/HixQt4enpCQ0MDALBv3z6kp6dDXl4eUVFRePPmDY4cOQIXFxesX78eWlpaCA8PR25uLmxsbHDv3j04OTnB2dkZV69excKFC/H69Ws8efIEJ06cQG5uLm7duoUDBw7g4cOHeP36NZ4/fw5NTU1s2bIFAHD48GG4uroiPj4eGzZsQGhoKJKSkvDhwwds3rwZxsbG8PPzw8mTJ5GZmQk3Nzfs378f3bp1w7hx47B582bs3r0bDRs2lOoKMiQkBOvWrYOhoSFSUlJgbm6O3377DQDg4eGBv/76C2ZmZliyZAkePnyIjx8/IikpCfv374ecXPEfw9u3bxfanOjRo0dRp06dYjvssLGxkWkvvGPHjrh8+TIGDBhQZL1Lly7hwoULEIlEmD9/PlRVVTFs2DCu3/Hi9n9hYmNjsW7dOqSkpODs2bMIDw+Hvr4+1qxZIzXdnTt34Ovri7S0NAQHB+PQoUNQV1fnyj08PPDmzRvo6OggKioK69ev595PhenevTtmzJiB5ORk9O3bl3v/53d9Wty+BoDXr19j5cqVMDMzw/v37zFw4EAMGjQIgKQv5j179kBFRQWvX7+GkZERnJycpJqZvHnzJjw9PWFmZobc3FyZWAcNGoQLFy5AW1sbW7duxdChQ/Hnn39iwYIFaNasGa5duwZdXV2Z9WrSpAnq1q2LPn36wMXFBd26dePmnb9uR44cga+vLwBwHQLNmDED7du3h1gsxvr165GXl4eMjAyEhoZi3bp1XIJ3d3fH27dvER0dzdXdtGkTt4zS7gfyFSr7fDspXPv27dmvv/7KGJN0MVevXj129OhRrjwpKYkBYJMnT+a6zlyxYgXr3bs3N83z58+Zrq6uVPdu27ZtK9E16T179jBra2upedepU4cxxlhiYiIzMzNj4eHh3PTr1q1jEydO5IbPnDnDtLW12fr167lx3bp1Y25ubowxybXxQYMGcWUZGRlsyJAh3PDff/8tc+2ubdu2Utcznzx5wgAwZ2dnbtyECRNYhw4d2OXLlxljjAmFQqakpMTu3LnDTXPp0iUGgHl5eXHjNm7cyMzMzFh6ejo3DkCh1ynd3d2lrvu9efOGWVhYsMTERG7crFmzmIuLCze8YcMGZmpqyvbu3cuNMzU1ZceOHZOZ/+fGjRsnde0xn4qKCrO2ti62blpaGtdVY76goCDWoUOHLy43//6Fz69Jl2T/F8XGxqbQa9Le3t5MW1ubbd26lRvXtWtX7v3CmGS79+/fnxvetGkTGzNmTLHL+/DhA7O0tOS6DTUxMWHOzs5S1+8ZK3xfJyUlMQMDA66ryszMTFa/fn0WGhrKGGNs+PDhXDy5ubnM2tqarVmzhqt/9epVZmpqKtVt46JFi2Te1/Pnz2c//fST1Ljhw4dLddNZmOvXrzM1NTUGgPH5fNa6dWvm6ekpNY23t3ehn/f8rkM/fPjAGGNs/fr1zNLSUuq94uTkJHN9m7Gy7QdSdnS6u4oaNWoU166smpoaOnfujBs3bnDlmpqaAIAuXbpwR2KGhoZ4/fo1N83SpUthY2MDAwMDblxJ2qrNzc3F4sWLMWnSJG7eQ4cOxYYNGwAAa9asgZWVFYyNjbk6EydOxN69e/HixQsuvsTERAwbNoybpmB8ycnJ8PPzw9WrV7k7U6dMmcJNq6ysLBPX5+Pyt0HBNn8NDQ0RGxuL3r17AwAUFBRQp04dvHv3jpumVq1aACR3u+ebOnUqPn78iH379n1x+9SpU0dqeMmSJejVqxe0tLS4cZMmTcKqVauQmJjIxRoVFQV7e/tCt0dx4uLiijxK+VKvWqqqqjLTaGtr4+3bt19cblFKsv/LIikpSWr7GBkZcdtHKBRi9erVmDBhAleef31dJBIVOU8jIyM8f/4cZ8+exa+//golJSU4Oztj7NixX4xn+/btqF27NncWo1atWujZsydOnDgBABg8eDB69OgBAJCTk0PPnj2lPqPz5s3DsGHDoKamxo0r7PM3ZcoU+Pj4cPvE398fo0eP/uJ1+p9//hkfPnzA7t27MWrUKERGRmL06NElOnXftGlTjBw5knvP2traIiQkBFFRUcXWK+t+IGVHp7urqN9//x1BQUFcX6vv3r1DkyZNZKYzMjLi/ubz+cjLy+OGfX19uVOupREUFIS4uDg0atSIG9ekSRNu+VevXpW5iUlbWxtKSkq4efMmrKysvhhfy5YtMWjQIPTq1Qtqamro3bu3zKnPkvp8GQWH88d96QukVq1aaNiwIfz8/KRuNCqJq1evYtGiRVLj6tWrh5ycHNy5c4c7raynpyd1avvz/VWUz2/+ytekSZMvPrL08eNH1KlTR+qmMi0tLaSkpHxxuUUpzf4vDW1tbaiqqnLDBbdPUFAQUlJScPv2bbx//x6A5PGqn3/+GRkZGVKnxAt68OAB2rZti4EDB2LgwIEAJKdq582bBycnJzRu3LjIePz8/JCbm4uNGzdy4xQUFFC7dm0AwPDhwxEWFoY///wTWVlZCAwMRG5uLgDJD47nz5/j999//+J6N2rUCJ07d8aePXvg6uqKS5cuwcnJqdg6nz59gkgkgqGhISZNmoRJkyYhOzsbY8eOhbOzM6ZPn15sfSMjI/z11184e/YsgoKCuPH58RelrPuBlB0dSVdR8+bNw+TJk/HLL79g6dKlhSboklBRUSl1nfykUNRRmkgkQnZ2tkydnJycEiUdQPJlsGXLFoSEhMDd3R3h4eHo1q0bMjIySh1veREIBEV2W1dcQxuFbY+srCwAKPH2KI6Ojg6Sk5Nlxo8aNQpxcXEICwsrsu6RI0eQk5MjE29Z+kTP3wblsf8BSZeeJf2xkP9e7Nu3LxwcHODg4IA5c+bg8uXLxSaGv//+W2bc3LlzYWxsXORRf/568ng81K5dm1ueg4MD/v77b8yYMQOAJNn369cP3bp1g6OjIzp06CAzr5J+/qZMmYL9+/cjMTERKioqXzyKDg0NxfXr16XGKSkpwd3dHTExMYiLiyt23V68eAErKyskJCTA2dkZkydPLnZ5KSkpePbsWZn3Ayk7StJV0J07d+Dh4YHDhw+jQYMGAP77svf19S3yA/i5Tp06FfsFXpSmTZtCU1NT5vGLN2/eIDk5GZ06dZK5q/T9+/cQi8Ulbs3Mz88PR44cgYWFBaZPn46AgADUq1cPL1++BFD4IzklXe+ySE1NxatXr9ClSxduXMEj8IKnMT9X2PYICwuDQCCQOeIsC319fSQkJMiMnz59Oho3boxVq1YVWk8oFCIyMlLq6BSQHOV9fsq+MPn74PNt8DX7XyAQcPO7f/8+0tLSvhgHIHlPamtrSx31AZIbLIu7A9nb2xuZmZky49XV1VG/fn1uuLB93aVLF4SGhsqchfHz80NERATmz5+PzZs3o3Xr1gD++4y+fPkSnz59QpMmTUr8+RsyZAiEQiHGjRuH4cOHl6jOhQsXCl0vNTU17lJQUfvQwcGBuxlVTk5O6sfVP//8w9XNrxcXF4dnz56VeT+QsqMkXQWlpqYC+O/aaXJyMgIDAyEUChESEgKxWAz2/87LWIFOzBhjUsMuLi64cOECPnz4wI07c+YMABT6pZ9PUVERLi4u2LZtm9QX3I4dO6Curo6lS5ciODhY6gvo4MGDGDZsGJeUvhQfYwzbt2+XOmrX1NTkTrE3bNgQKSkp3JdEYGAgkpKSuGu8JVlGceMA4PTp09zfGzZsQIMGDbi7egHAwsICb968kan3+fxcXV1x/fp1qaPdgwcPYu7cudz9AKWJ63M//vgjnj59KjNeSUkJ58+fx+3bt7FgwQKpL8nU1FTMnz+fu9O3oPj4+BLd5a+vrw91dXW8efMGjDHuLENJ9n9RCm7Tjx8/ol69egC+vH0UFBSwevVq7Nmzhzslm52dDU9Pz2KbSf3w4QN+++03qSP2s2fPQkNDQyrWwvb1tGnToKGhIXUX/7lz55Ceno60tDQwxrjPaE5ODvz8/CAUChEREcE9/nTgwAGZZRd8X+dTUlKCvb09cnNzuTusv+Ty5ctYv3691OUQFxcX/P7775CXlwcANGjQAAKBAG/evEFKSgqXvFNTU7nYAUmTwQoKChAKhdwPZQsLC+46+cuXL9GkSZMy7wdSdtRVZRXEGIOrqyvu37+Pjh07QiQS4eeff8a4ceMwfvx49O7dG3PmzIGPjw+srKywbNkyxMbGYtOmTQgLC4OtrS127NgBAwMD3L59G1u3bkWzZs3A4/FgamqKqVOnomnTpti2bRtatmxZZBx79+7F2bNn0aRJE/D5fIwfP55Loq9evYK7uztq166N9PR01K5dG46OjpCXl4enpyfWrFmDoKAgdOvWDZs2bcLmzZtx8uRJAICdnR0mTJiAkydPQk1NDWpqakhMTESXLl3Qr18/bvkuLi6Ii4uDgYEBTE1NcezYMTx48ACjR49G9+7dsXz5cty/fx/t2rWDq6srvL29sWfPHiQlJcHW1hYbN27EzJkzcenSJZiamuLXX3/ltlu3bt2wb98+fPz4EcnJyYiPj8eff/7JXW8EAB8fH7i4uMDa2hqjRo1C69at4e7uju3bt+PTp08YOHAgjh07BkByVLhjxw7Url0bKSkpsLS0hIODA3g8HjZs2IC//voL4eHhsLW1xdatW+Hg4IBLly5BS0sL48ePL/Z6fGpqKmxsbPDkyZNCyzMyMrBhwwbcuHED+vr6UFNTg5aWFubNm1foEfOePXsQFhZW5BF4QSdOnMCuXbvQtGlTzJs3j7veX9z+L05kZCTGjx+PZs2aoX379hgxYoTU+6VXr17YvHkzXF1dcebMGfB4PNjZ2WHv3r0AgAMHDsDLywsmJiZgjGH27NnQ19cvcnnjx4/H/Pnz4eHhgczMTMjJyUFeXh7r16+XatCksH0NSK79Ll68GFpaWlBSUoKVlRXGjBkDANi1axf++ecfdO3aFSKRCP3798fw4cNhZ2eHFStWQF5eHmfPnsXJkydhZWUFxhi0tLSwdOlStGzZEocPH5a6qfPy5cvIzMzEkCFDvrhfbt++jVevXkFHRwfHjx8Hj8dDTk4OrKys4OjoKHXZZtOmTbh+/ToaNGgAFxcXqKmp4cWLF1iwYAFatGgBHR0dWFpa4uLFi4iOjsayZcvQpk0biEQiTJgwAXJycjA3N8eyZcu4eZZ2P5CyoyRNvjv5Sbo6vfVHjhwJZ2dnWFhYfPW8Jk2aBHt7e3Tt2vXrAyNf5ePHj6hbty7k5eXh5OSE5cuXf/GHDvm+0Olu8t2pTsk5n6OjIzZv3vzV88nMzMSbN29gY2NTDlGRr9W8eXMcOnRIKlkTUhAlafJd8fT05B5L+/nnn2WajKyqmjRpAl1dXTx8+PCr5nPgwAHMnDnzi89Xk29j+vTpiIiIwKFDh7742BT5PtHpbkKqEScnJyxZsgRKSkqlrhsZGYmlS5fiwIEDlKQJqSYoSRPynfDw8MCUKVOkWsAihFRtlKQJIYSQKoquSRNCCCFVVKW23S0WixEVFQU1NTW6RkYIIaTGYIwhLS0N9erVK7K54ZKo1CQdFRUl0xkCIYQQUlNERESUqIW/olRqks6/gSUiIqJEjbMPHz4cx48fL9G8aVqalqalaWlamraypk1NTYWRkdFX36hZqUk6/xS3urp6iZK0vLx8iXtaoWlpWpqWpqVpadrKnBb4cp/vX1KtbhwbOXJktZq2NKpCvLRupVcV4qV1K72qEC+tW+lVhXgrat2KUqmPYKWmpkJDQwMpKSk1si/SAQMG4N9//63sMCoErVv1ROtWPdG6VT/lld+q1ZE0IYQQ8j0p9TXpsLAwXL58GUpKSoiOjkafPn1gbW2NBw8ewNPTE9bW1rh79y6WLFkCU1PTioi52vjWp0W+JVq36onWrXqidft+lfp096JFi7B27VpueMyYMdizZw8sLCwQEBAAXV1d3Lt3D0uWLIGPj0+x86rpp7sJIYR8n8orv5X6SPr06dMYNWoUWrRoAQBQVFTErVu3oK6uDl1dXQBAu3bt4O/vj5iYGG5csQIDAVXV/4a1tABTUyA7G3j5Unb6Vq0k/4eGAhkZ0mUmJoC2NhAXB0RESJepqQENGwIiEfD0qex8mzUD5OWBt2+BlBTpMgMDQFcXSEoCwsKky2rVAho3lvz95Anw+e+exo0l07x/DyQkSJfp6krmnZYGvH4tXSYvL4kJAJ4/B3JzpcsbNpSs08ePQEyMdFnt2oCxMZCVBQQHS5fxeIC1teTv4GDJNAWZmkr2QUyMZN4FaWgA5uaSWArrQapFC0AgkKxLWpp0mZERUKcOkJgIhIdLl6moAPl9JT9+LDvfJk0AJSXJtk9Kki7T15e8UlOBN2+kyxQVgaZNJX8/ewbk5UmXN2okee9FRgKxsdJlOjpA/fpAZiYQEiJdxucDLVtK/n75UvJeLcjMDNDUBKKjgago6TJNTUl5Tg7w4oXsurZsKZn/q1dAerp0Wf36krji44EPH6TLVFUl6yMWSz5Tn7OyAhQUgHfvgORk6bJ69QA9Pcn4d++ky5SUJNsfkMxXLJYut7QElJUl8cTHS5fVrQsYGkrW49Ur6TI5OaB5c8nfQUGAUChd3qABoK4OfPokeRVE3xESFfwdwRiDOCgI4owMiMVi7pVXvz5Eampg0dHgRUVBJBJJphWLkaeighwjI+RlZ0EuOBgisUjyYiKIRCKkmJsgj8egEP4eSE+DSCySzJeJkVZbC1nqKhCkpKDWpxhJHbEITMwgVJBDgr4OxEyM2m/fQ8zEYIxBxCTLjtGrjVx5AdRjE6CQngHGmCQmiJGirowUdWXIZ2ZBJzYZYoghZgyMiZEj4CFKTwsMDPU+xoP3/3VhjIGBIUpHFdkKctBMSodaRpakq1sGMDCkKisgTrMW5IW5MIhLA4NkeYwxZOeKZN8/ZcFKaePGjUxOTo7NmTOHOTs7s8DAQLZz505mY2MjNZ2Ojg67ceNGsfNKSUlhAFiK5C3LvbwNDNiRI0cYe/1aajz3ytehg2zZoUOSsi1bZMt69sxfcOHzjY2VlPfvL1u2fr2k7MQJ2TJr6/9iUlCQLX/xQlI2aZJs2eLFkjJvb9kyA4P/5mtgIFvu7S0pW7xYtmzSJEnZixeyZQoK/83X2lq2/MQJSdn69bJl/ftLymJjC9+GKSmS8p49Zcu2bJGUHTokW9ahw38xFTbf168lZaNHy5Y5OUnKvLxky8zN/5uvjo5suZ+fpGzOHNmymTMlZY8eyZapqf033yZNZMvPnZOUubrKlg0dKimLiCh8XbOzJeU2NrJlu3ZJynbtki3L/wxmZxc+34gISfnQobJlrq6SsnPnZMuaNPlvXdXUZMsfPZKUzZwpWzZnjqTMz0+2TEfnv/mam8uWe3lJypycZMtGj5aUfePvCHFMDMvNzWW5trYyZZ8WLGCPHz9mrwrZ50mmpuzYsWNs78G9LE9OTqbc9bfRbMaKGcy3ZSOZsqNtTFjX37qyXwdZyS5TWY41mNiAmU4wZVHKApny/r3UmOY4TbbeSvZ7aW9DPpOfKM+a28nWy+aDYQYYZoI9qiO7HYb2B8MCsDndZMvONQKDM5jOgkL2C8DUFkvKvcxly2baSspGD5Yt8zOUlMG58Pma/yYpO9RMtszJRlLWc4xs2Wut/+Ybqyxb3mGSpGx9B9myLW3B4ARmPUW2LEIeDABLyf9OLKNSn+6OiYnBvHnzEBAQgPT0dHh6eiIgIAC+vr7w8vLipjMyMsKmTZtgZ2dX5Ly40wG+vlCnI2k6kqYjaQk6kpYo5kg6V1UVmbq6yEhIgOj5c2RlZSE7OxvZ2dnIyclBjIEBsrKyoBAWBlFqKoRCIYRCIbKF2YhQFCCWnwdBSiJUU5KQnZeNHFEOhCIhkvkivFJmyM3LRqOULOQiFyKIkIc8iCFGoLoYeQqAWTagwQAIILn9Vg74qAbEqgOaeYBpxv/HCySvLEUgRE8Se8tPAO+zr4jgOkC2PFA/GaidKV0WowpEqQOqQqDh/78++IwHHuNBxOfjZV0B+IwPq1gGRREffPDBAw988BGuLY8sJTkYpAK6mZJndgUQgM/jI01ZATFaSlDO48E8PgcCnmS8gCcAj8/HO0MNyPHkYBKXhVp5kJTxJdMk1tFAtmotaKXnQCdZKBnPl9TNUamFJH1tKIh5MPyYJFVPwBcgwcwQfHl51P6UCKXsXPB5AsgJJOVZujrI1daEckY21KITwOfzIceXA5/PB1NWRpZpfQgEAmgGvwNfwJesC58PPp+PHIsG4CnVQq3IaMinpYPP40uWKRBArKcL6OtDkJ4BxfAISax8AXjggaekBNa0CXjgQe7FS/BEIvDAg+QfD7xGFuCpqYEX+RG8uDjJOB5P8n+dOkV+R6RmZkKjc+evPt1dqiSdlpaGsWPHwtPTE3w+H25ubtiwYQNcXV3x77//4sqVK9y0WlpaOHfuHLp06VLk/OiaNCE1X05ODlJSUpCamsr9n56ezr3S0tIKHU5LT0NqVirSctKQkZeBzLxMZImykM2yIRKIAEUACvjv/4Iv+f/+5ynyuL+ZHANK2LYEj/EgD3nI8+ShwFOAPE8e8nx5KPAVoChQhAJfAUpySlCUU4SSnBJqydWCopwiasnXgpK8kmScguTvWgq1oKygLPlfURm15GtBQaAARTlFKAgUJPMVKHAvecFnw3x5yAvkJQmLRw/lVAeVck362rVrsLGxgbKyMgDA2dkZubm5qFOnDmILHIUIhUKkpaXB2Ni4zIERQqqGnJwcJCUlISkpCYmJidzfBYeTk5NlEnFKSgqSM5KRw88BlAHU+v9LSfolpyIHgYoAPGUeoAQwNQaRvAh5grxiEyoPPCgLlKEspwxVeVWoyKtAVUEVqoqqUFNUg7qSOtRqqUnKFFSgIq/C/a8srwxleUmyVJZXRi25Wtxw/t/yAvlvsXkJKVapknSDBg1kHjoXiURo3749YmNjERkZCUNDQ/j6+qJt27aUpAmpYnJzc5GQkIC4uDjEx8cjPj6+yL/j4+ORmJiIzMz/n38VAFD5/0sZkNOUQ63ataCgpQCBmgC8+jyIlcTIk89DriAX2fxs5CGv0DjUFNSgoagBrVpa0FDSgIaiBjSVNKGhqAENJem/1RTUoKaoJvN/Lbla1HseqfFKlaSbN2+O4cOHY968eTA0NIRQKET37t1hbGyMAwcOYPXq1ejQoQN8fX3h6elZUTETQgoQi8VISEhAdHT0F1+JiYnSlXmAQEMALSMtqOipQElHCXKN5MBaMygrKUNOTg6ZvEyki9ORKZa+WJqHPDAFBg0VDego66B2rdrQrqXN/V/wVVv5v3EaihoQ8AXfcAsRUn1Rs6CEVGEikQjR0dGIiIhAZGQk93/Bv6P+/whMQRoaGqhbry606mtBuZ4y5HXkwdQZcpRykCWXhVSWiqTcJMRnx0PM/rsRjM/jo65KXeir6kNPVQ+6qrqoo1wHdVXqoq5KXe7vOip1UEe5DmrJ1/rWm4SQaqHSnpMmhJSfvLw8REZGIiwsDO/evcO7d+8QFhaG8PBwRERE4NOnT1IJuFatWjAyMoKhoSFMGpmg6U9NwdfhQ6QiQqZ8JpKRjLicOESmReJ1uvTTAnWV6sJI3Qj11OrBWtUa9dTqQV9NX/K/qj701fRRV6Uu5Pj0tUBIVUFH0oRUsMzMTLx69QqvXr3iknB+Qv7w4QPy/v9YGI/Hg4GBAczMzGBiYgJDI0NoG2iDp81DjmoOUgQpiMqKwtukt3iT+AYxGf89dqckp4T6GvUlL/X6//39/5ehuiEd9RLyDZVXfqMkTUg5YIwhKioKISEhCA0NRUhICPf3hwLPM2toaMDMzIx7mZqawtjUGAIdAVIVU/E6+TVexr1ESHwI3iS+QYrwv+f166rUhbmWORpoN/jvf21zmGmZoY5yHbqJipAqhJI0IZWAMYZPnz7h6dOnePr0KV68eMEl4/T/NzwiJyeHhg0bwsLCApaWlrC0tISFhQVMzE2QwBLwMu4lguOD8TLuJV7GvURoQihyRDkAAE0lTTSt0xSWOpZoqN0Q5tqSZGymZQZ1RfqMEFJdUJImpILl5OQgODiYS8j5r/j/t6qlpqYGKysrNG7cmEvElpaWMDU1RbY4G4HRgXj86TGeRD/B40+PERwfjDyx5NR2HeU6aFKnicxLV0WXjogJqQFqVJLu3bs35OXlMXLkSOq2jFQKoVCIwMBABAQE4OHDhwgMDERwcDB3vdjMzAwtWrRA8+bN0aJFC7Ro0QImJibg8/mIz4zHk09PpBLy60TJTVuKAkU0120Oaz1rtNRriaZ1m6KxTmPUUalTmatLCKkgR48exdGjR5GbmwsvL6+akaTpSJp8S4wxhIWFISAgAAEBAfD398eTJ0+Qk5MDBQUFtGzZEi1btuSScbNmzbj3Z64oF4HRgbgbcRd+EX7wj/RHRKqkjXhVBVVY61nDWs8arfRboZV+K1jqWFLLVYR8h+gRLEJKKD09Hf7+/lxCDggIQFxcHADA3NwcHTp0wOjRo9G+fXu0aNECioqKXN3ErETcjriNuw8kSfn+x/vIysuCokARbQ3aYoTVCLTWbw1rfWs00G5A7SoTQsoVJWlS42RlZeHevXu4efMmvL29cf/+feTl5UFDQwPt27fH9OnT0b59e7Rr1w516kifdg5PDof3S2/4RfjhbsRdBMdLehDTVdHFj/V/xMpuK/Fj/R/RSr8VFAQKlbF6hJDvCCVpUu3l5OTg/v37XFK+d+8ehEIhdHR00K1bN2zevBk2NjawtLQEny99pJuSnQLvcG9ce3sNV99dxZvEN+CBB6u6VrAxtsGSTkvwY/0fYappSjd0EUK+OUrSpNphjOHp06fw8vKCt7c37ty5g8zMTGhqasLGxgZr167FTz/9hKZNm8ok5VxRLu5/vI9r767h6turuP/xPkRMBHMtc/Qw6wH37u7oZtoNmkqalbNyhBBSACVpUi0IhUJ4e3vj/PnzOH/+PCIiIqCqqorOnTtjxYoV6NatG1q2bAmBQLbjhvfJ73Hh1QVce3cNN8NuIi0nDZpKmuhu1h1bW25FD7MeMNUyrYS1IoSQ4lGSJlVWXFwcLl26hH///RdXr15Feno6TExMMHjwYPTv3x9dunSBgkLh14WD44JxOvg0zoScwaNPjyDPl8cPRj9g0Y+L0MO8B1rrt6aemAghVR4laVJlMMYQHByM8+fP499//8W9e/cAAO3bt8eSJUswYMAANG3atNBrw4wxPP70GKeDT+N0yGmExIdARV4FfRv1xYKOC9CnYR9qsYsQUu1QkiaV7v379zhy5AgOHz6Mly9fQllZGT179sTu3bvRt29f6OrqFlpPJBbhbsRd7oj5Q8oHaNfSxkCLgXDv7o4e5j2gJKf0jdeGEELKDyVpUikSExNx8uRJeHp64vbt21BWVsagQYOwdu1adO/eHUpKhSdXxhieRD/B/sD9OB50HLEZsainVg+DLQfDrrEduhh3oa4WCSE1RpX4Nhs+fDg1C/odyMrKwoULF+Dp6YlLly5BJBKhZ8+eOHToEAYNGgRVVdUi68ZlxMHzuSf2Be7Ds5hn0FPVg31zewxtMhTtDNpRIyKEkCqhYLOg5YGaBSUVSiwWw8fHB4cPH8apU6eQmpqKtm3bYsyYMRg+fHiRp7IByeNSl99cxr7Afbjw6gJ44GGAxQBMaDkBvRr0oiNmQkiVRc2CkiotKSkJ+/btw9atW/H27VuYm5tjzpw5GDVqFBo1alRs3RexL7DvyT4cfn4YsRmxsNazxvqe6zGq2SjoKOt8ozUghJDKR0malKunT5/i77//xuHDh5GXl4dffvkFBw8exA8//FBsi13CPCGOPD+CrQ+34mHUQ+go62B0s9GY0HICWui1+IZrQAghVQclafLVcnNzcebMGWzZsgW3b9+GgYEBli5diilTphR7OhsA4jPjse3BNvz94G/EZMTAtqEtTv9yGn0b9aW2sQkh3z1K0qTMoqOjsXPnTuzYsQNRUVGwsbHByZMnMXDgQMjLF989Y0h8CDb6b8SBpwcAAONbjIdDBwdY6Fh8i9AJIaRaoCRNSu3JkydYt24d/vnnH8jLy8Pe3h6zZs1Cs2bNiq3HGINPuA88/D1w4dUF6KroYlnnZZjeZjpdayaEkEJQkiYl9vjxY6xYsQL//vsvzMzM4O7ujvHjx0NTU7PYejmiHBx/cRwe/h4IjA5Es7rNsG/gPoy0GglFOcVi6xJCyPeMkjT5ooLJuWHDhjh48CBGjhwJObni3z7CPCG2P9wOdz93RKVFoXeD3rg65iq6m3Wnbh8JIaQEKEmTIj169AgrVqzA+fPn0bBhQxw6dAgjRoz4YnIWiUU49OwQnHycEJkaibEtxmL+D/PRtG7TbxQ5IYTUDJSkiYyCyblRo0YlTs6MMZwOPg1Hb0cExwdjaJOhuDLmCix1LL9R5IQQUrNQkiacz5Pz4cOHMWLEiEL7aP7c9XfXseTGEjyMeoie5j1xaPAhtK7X+htETQghNVeVSNLUdnflioiIwPz583HixIlSJ+eAyAAsvbkUN8NuooNhB3iP80ZXk64VHzQhhFRB1HY3KTfZ2dn4888/4erqCg0NDbi5uWHMmDElSs5BsUFY7r0cZ0POwqquFVb/tBr9G/WnG8IIIQTUdjf5CowxnD9/HnPmzMGHDx/g4OAAR0fHEr2RkrOTsfTGUmx/uB0mmiY4NPgQRlqNhID/5cROCCGkdChJf2devXqF2bNnw8vLCz179sTFixdhafnlG7sYYzgRdAIOVxyQkZMBj14emNl2JjXdSQghFYiS9HciLS0Nq1atwoYNG2BgYIAzZ85g4MCBJTo9/S7pHWZdmgWvN14Y0ngINvXeBAN1g28QNSGEfN8oSddwjDEcOXIECxYsQFJSEpYvX44FCxagVq1aX6ybK8rF+nvrscJ3Beqq1MW/I/5Ff4v+3yBqQgghACXpGi0oKAjTp0/HnTt3MGTIEKxfvx7GxsYlqusX4YdpF6YhOC4YczrMgVNXJ6gqqFZwxIQQQgriV3YApPyJxWJs3LgRrVu3Rnx8PK5fv45//vmnRAk6KSsJ085Pw497f4SyvDIeTn2IdT3XUYImhJBKQEfSNUxkZCTGjx+PGzduwMHBAa6uriU6tc0Yw7EXx+BwxQHZedn42/ZvTGs9je7aJoSQSlSmJL17925ER0fDyMgIIpEIEydOxIMHD+Dp6Qlra2vcvXsXS5YsgampaXnHS4px9OhRzJw5EyoqKrh27Rq6d+9eonqJWYmY9O8knA05i2FNhmFj742op1avgqMlhBDyJaVO0jt27MC7d++wdu1avH79Gm3atMHo0aMxbNgwBAQEQFdXF40aNcKECRPg4+NTASGTzyUlJWHmzJk4duwYRowYga1bt0JLS6tEdf0i/DDy1EikCdNw+pfTGNx4cAVHSwghpKRKlaSFQiGWLFmCJ0+eAAAaNGiAp0+f4tatW1BXV4euri4AoF27dvD390dMTAw3jlSMGzduYNy4ccjIyMCRI0dK3KyqmImx9s5aOHo7ooNhBxwZcgT1NepXcLSEEEJKo1RJ2s/PD0lJSXj9+jX8/f0REhKCXr16ITw8HNra2tx0AoEAampqCAoKKlGSzm+7uyBqx7t4WVlZWLp0KTZu3IiffvoJ+/fvh5GRUYnqRqdHw/6MPW68u4GlnZfCuasz5Ph0ewIhhJRFfnvdBZVX292l+mb+9OkTAEBBQQHDhw9HfHw8WrRogalTp0JJSUlqWiUlJSQnJ5dovsePH6e2u0vhyZMnGDNmDN6+fYsNGzbg999/B59fshv1r729hjFnxoAHHq7aX0V3s5JdtyaEEFK4wg4q89vu/lqlegQrf4Ft27YFAOjo6EAsFqNOnTr4vJ+O9PR06OjofHWA5D+MMfz1119o3749FBQU8OjRIzg4OJQoQeeKcrHk+hL0OtwLLfVa4un0p5SgCSGkiivVkbS1tTV4PB5EIhE3jsfjwcDAALGxsdw4oVCItLS0EjecQb4sJycHs2bNwu7du+Hg4IC1a9dCQaFk7Wa/T36PkadG4v7H+1jz8xos+HEB+Dx6RJ4QQqq6Un1T16tXDzY2Nrh79y4AIC4uDjweD127dkVsbCwiIyMBAL6+vmjbti0l6XISFxeH7t274+DBg9i3bx82bNhQ4gR9JvgMWu5oiai0KNyecBuLOi2iBE0IIdVEqe8WOnDgAJycnPDy5Uu8ffsW58+fh4aGBg4cOIDVq1ejQ4cO8PX1haenZ0XE+9159uwZBgwYgOzsbHh7e6Njx44lqidmYiy9sRRr766FXWM77O6/G1q1SvZYFiGEkKqBxz6/mPwNlVen2DXVmTNnYG9vj0aNGuHcuXMlvns7Oy8b48+Ox4mgE/iz55+Y02FOiXq7IoQQUj7KK7/Rec8qiDGGVatWwc7ODra2trh9+3aJE3RCZgJ6HOqBc6Hn8M8v/2DuD3MpQRNCSDVFD8dWMZmZmZgwYQJOnDiBFStWwNHRscRJ9m3iW9gesUViViK8x3mjg2GHCo6WEEJIRaIkXYVERERg0KBBCAkJwT///IMhQ4aUuK5/pD8GHB0ATSVN+E/yh7m2eQVGSggh5FugJF1F3Lt3D4MHD4aioiL8/PzQokWLEtc9E3wGo06PQmv91jg34hxqK9euwEgJIYR8K1XimvTw4cMxYMAAmWbVvhcnTpxA165d0bBhQzx48KBUCXqj/0YMOTEEAywG4PrY65SgCSGkEh09ehQDBgzA8OHDy2V+dHd3JTt06BDGjx+PkSNHYu/evSV+/lkkFmHulbnYfH8zFnZciDXd19Dzz4QQUkWUV36j092VaO/evZg8eTImTpyIHTt2QCAQlKheZm4mRp0ahfOvzmNb322Y3mZ6BUdKCCGkMlCSriTbtm3DzJkzMWPGDGzZsqXEHWTEZsSi/9H+CIoNwvmR52Hb0LaCIyWEEFJZKElXgk2bNsHBwQEODg7w8PAo8SNW8Znx+Pngz4jPjMetCbfQSr9VBUdKCCGkMtFFzG/M3d0dDg4OWLRoUakSdFJWEnoe6onYjFh4j/OmBE0IId8BStLf0MqVK7Fo0SL88ccfWLNmTYkTdKowFb09e+NDygfcGHsDljqWFRwpIYSQqoBOd38DjDE4Ojpi9erVWLVqFZYtW1biuuk56ejj2QevEl7h5tibsKprVYGREkIIqUooSVcwxhgWLlyIP//8E+vWrcP8+fNLXDczNxP9j/bH85jnuD72Oqz1rSswUkIIIVUNJekKxBiDg4MDNm/ejE2bNuH3338vcd3svGwMOjYIDz4+wJUxV9DOoF0FRkoIIaQqoiRdQcRiMWbOnIkdO3Zg+/btmDZtWonr5ohyMPTEUNz5cAeXRl/Cj/V/rMBICSGEVFWUpCtA/hH0zp07sXfvXkyYMKHEdXNFuRj+z3Bcf3cd50eeR1eTrhUXKCGEkCqtSiTp4cOHQ15eHiNHjsTIkSMrO5yvtmnTJvz111/YunVrqRJ0njgPY86MwcVXF3Fm+Bn0MO9RgVESQggpb0ePHsXRo0eRm5tbLvOjtrvL2enTpzF06FDMnz8f7u7uJa4nEosw4dwEHHl+BCeHncTgxoMrMEpCCCEVidruroICAgIwevRoDBs2DG5ubiWuJ2ZiTLswDZ7PPXF0yFFK0IQQQgBQki43b9++Rf/+/dGqVSscOHCgxG1xA8DSG0ux98leHBx8EL80/aUCoySEEFKdUJIuBwkJCbC1tYWmpibOnTsHJSWlEtc9/Oww1t5dC4+eHhjTfEwFRkkIIaS6oST9lbKzszFo0CAkJCTA398fOjo6Ja4bEBmAyf9OxoSWE+DQwaHigiSEEFItUZL+CmKxGBMmTMCDBw9w8+ZNNGjQoMR1P6Z+xODjg9FKvxW29d1W4na8CSGEfD8oSX+F5cuX49ixYzh58iQ6duxY4npZuVkYdHwQBHwBTg8/DUU5xQqMkhBCSHVFSbqMdu7ciTVr1mDdunUYOnRoiesxxjD5/GQExQbhzsQ70FPVq8AoCSGEVGeUpMvAy8sLM2fOxMyZMzFv3rxS1V17dy2OPD+C40OPU5/QhBBCikX9SZdSYGAghg0bht69e2PTpk2lupZ8PvQ8lt5YCscujvSoFSGEkC+iJF0KkZGR6Nu3Lxo1aoRjx45BTq7kJyKCYoMw6vQoDLIcBOeuzhUXJCGEkBqjSpzurg5td+fl5WH48OHg8/m4cOECVFVVS1w3ITMBA44NgKmmKQ4OPgg+j34bEUJITURtd1eS5cuXw83NDbdu3SrVndy5olz0OtwLz2Of48GUBzDRNKm4IAkhhFQJ1Hb3N3T9+nW4urpi9erVpUrQADDnyhzc/nAb1+2vU4ImhBBSKpSkvyAmJgb29vb4+eefsWjRolLV3fFwB/5+8Dd29NsBGxObCoqQEEJITUUXR4shFosxbtw4iMViHDp0qFSdZtz5cAe/Xv4Vs9rOwtTWUyswSkIIITUVHUkX488//8SVK1dw5coV6OmVvNGRlOwUjD49Gj8Y/oANvTZUYISEEEJqMkrSRfD398eyZcuwaNEi9OzZs1R1Z3vNRlJWEnzH+0JeIF9BERJCCKnpKEkXIjk5GSNHjkSbNm2wcuXKUtU99fIUDjw9gP0D99ONYoQQQr7KV12TXrRoEW7fvg0AePDgARwcHHDgwAFMnToVYWFh5RLgt8YYw9SpU5GUlISjR49CXr7kR8Kf0j5h2oVpsGtsh7EtxlZglIQQQr4HZT6Svn37Nvbv348+ffpAKBRi2LBhCAgIgK6uLho1aoQJEybAx8enHEP9Nnbu3ImTJ0/in3/+gYmJSYnrMcYw6d9JkBfIY0e/HdT1JCGEkK9WpiPp1NRUPH36FI0bNwYA3Lp1C+rq6tDV1QUAtGvXDv7+/oiJiSm/SL+B58+fw8HBATNmzMCQIUNKVXfHox24/OYy9g7YCx1lnQqKkBBCyPekTEfSO3fuxG+//YZ//vkHABAeHg5tbW2uXCAQQE1NDUFBQVziLk5+s6AFfesmQjMyMjB8+HA0atQI69evL1XdVwmvMO/qPMxoMwN9GvapoAgJIYRURflNgRZUXs2CljpJX7hwAb1794aioiI3Lj4+HkpKSlLTKSkpITk5uUTzPH78eKU3Czp79my8f/8eDx8+RK1atUpcL0+cB/sz9jBQM8C6HusqMEJCCCFVUWEHlfnNgn6tUp3ujoqKQmJiIqysrKTGa2ho4PMmwNPT06GjUz1O+x49ehR79uzBli1buFP4JbX61mo8inqEQ4MPQUVBpYIiJIQQ8j0q1ZH0lStXEB0dDTc3NwDAq1evcOTIEQwcOBCxsbHcdEKhEGlpaTA2Ni7faCvA27dvMW3aNIwaNQrjx48vVd37H+9j5a2VWN5lOdobtq+YAAkhhHy3vqoXLBMTE+zfvx+dOnWCsbExAgICYGhoiKtXr8LJyQn37t0rtn5l94LFGEP37t0RFhaGp0+fQk1NrcR1M3IyYL3DGppKmrg78S41WkIIIYRTqb1gRUZGYvPmzYiOjsb69euRmZmJAwcOYPXq1ejQoQN8fX3h6elZ5qC+lcOHD+PmzZu4cuVKqRI0ACy8thCRqZE4P/I8JWhCCCEV4rvtTzohIQGWlpbo0aMHjhw5Uqq6l19fhu0RW/xt+zdmtp1ZQRESQgiprsorv323vWAtWrQIubm58PDwKFW9hMwETPx3InqZ98KMNjMqKDpCCCHkO227+/bt29izZw+2b99eqt6tGGOYdmEackQ52DtwL7UqRgghpEJ9d0k6JycH06ZNww8//IApU6aUqu7RF0dxKvgUTg47iXpq9SooQkIIIUTiu0vSf/75J169eoXHjx+Dzy/52f40YRrmXZ2HoU2GYmiToRUYISGEECLxXV2Tfvv2LVauXIl58+ahefPmpaq78tZKpGSnYH3P0jUZSgghhJRVlTiSzm+7uyLb62aMYebMmdDV1cUff/xRqrqh8aHY6L8Rf9j8gfoa9SskPkIIIdVffjve5dV293fzCNaxY8cwcuRIXLx4Eba2tiWuxxiD7RFbhMaH4uWsl1CSU/pyJUIIId+1Sm3MpLpJTk6Gg4MDhg4dWqoEDQDnX52H1xsvnB1+lhI0IYSQb+q7uCa9ZMkSZGZmYtOmTaWql52XjTlX5qCXeS8MsBhQQdERQgghhavxR9L37t3Djh07sHnzZtSrV7rHptb7rceHlA+4OOoiPRNNCCHkm6vR16Rzc3PRunVrKCoqwt/fHwKBoMR1I1IiYPm3JWa2mYl1PamfaEIIISVH16RLYOPGjQgKCsKDBw9KlaABYMG1BVBXVIejjWMFRUcIIYQUr8Ym6fDwcDg5OWH27Nlo1apVqer6hPvgeNBxHBh0AOqK374LTUIIIQSooae7GWPo378/nj59iuDgYKiqqpa4bp44D612tIKqgiruTLwDPu+7uLeOEEJIOaLT3cW4ePEiLl68iLNnz5YqQQPA9ofb8SL2BR5MeUAJmhBCSKWqkVnoxo0baNCgAQYOHFiqenEZcXD0dsTkVpPRul7rCoqOEEIIKZkamaRDQ0PRuHHjUtdbfnM5AGD1T6vLOyRCCCGk1KrE6e7ybrs7NDQUdnZ2parzKOoRdj3ehc19NqOOSp2vjoEQQsj3h9ru/oLs7GwoKytj586dmDx5conqMMbw494fkZ6TjsfTHkOOXyV+uxBCqoGsrCzExMTAxMSkskMhVUh55bcad7r7zZs3YIzBwsKixHUOPzuMe5H38FefvyhBE/J/ISEhWLp0KTZu3FjkNJmZmcjIyPh2QVUx2dnZcHV1hb6+foUtY/Xq1UhNTa2w+ZOqrcYl6dDQUACApaVliaZPFaZi4fWFGN50OGxMbCoyNPIdunbtGuzt7cHj8eDg4AA3Nze4uLhg9OjRcHFxQU5ODjdtQEAADA0NkZycXHkBF2BhYYHGjRvj7NmzhZZfvHgRrVq1wrp1pW+Rb8WKFWjevDlq166NZcuW4cOHD18ZbeVwdXXFpEmToKioiFOnTqFv377g8XgYMGCA1DqdPHkSioqKsLOzw+PHj7F27Vo0b94choaGWLNmDdzc3LB48WIMGTIEV69elVrGrFmzsHz58m+9aqSKqHGHjaGhodDS0oKOjk6Jpl93dx1SslOwrgc1/VkdZWZmIiQk5Jsv19LSEsrKyl+crkePHmjYsCEOHz6MxYsXQ09PjytbsmQJBg8ejPPnz4PP56NJkyZYu3YtNDU1KzDykuPxeDAyMiqyvG/fvrh//36Z5u3k5ATGGHx8fLB6dfW8UTMyMhJRUVHcae4hQ4bAzs4OXbp0gVgsRv36//U937p1a6xatQoLFiwAALRq1QpZWVnw9/fHkiVLuOmSkpLQpUsXLF26lLs/R1NTEw0aNMCVK1fQq1evb7eCpEqocUk6JCQEFhYWJeoQIzErEZsCNuHXdr/CSKPoLyNSdYWEhKB162//uNyjR49K3ZLd51auXAkjIyMcPnwYY8eOhZqaGkaPHl1OEX4b33PHM6dPn0b37t2lxvF4POzevRstWrTAyZMnMWzYMADA1q1b4ebm9sV5amlpYc2aNRgzZgz69u3LXcscNWoUJk6cSEn6O1TjknRpHr/acG8DREyE+R3nV3BUpKJYWlri0aNHlbLcryUnJ4dmzZrhyJEjGDt2LJycnLBr1y74+/ujfv36OHbsGIRCIdTU1ODr6ws7OzsoKChg/vz5qF27NgYNGgTGGK5fv47ffvsNHTt2BAD8888/+PjxI3R0dBAUFITJkyfDzMwMAQEBePz4MerWrYtPnz4hPT0dixcvxt27d3Hv3j3o6enh4cOHmDVrFho2bMjFmZiYiN27d0NdXR2BgYHo1q0bevToUeg6/fXXXxCJRNDU1MTDhw/h4eEBBQWFEm2PRYsW4e+//8bx48eRmpqKFy9eQFtbG/PmzQMguRHH0dERDRo0AJ/PR0JCAv744w9kZmZi/fr1MDU1RVZWFhISEjB//nzExcVh9uzZiIyMhIODA/Ly8nD16lWMHDkSnz59gry8PK5du4YlS5Zw97AcO3YMYWFhMDIywq1bt+Du7l7kmY0bN27Aw8NDZryFhQUcHR0xe/Zs9OzZE2fPnsWIESMgJ1eyr9tWrVohJSUFly5dwogRIwAAOjo6+PjxI3JzcyEvL1+i+ZAaglWilJQUBoClpKSUy/zEYjHT0NBga9as+eK0CZkJTH2NOpt/ZX65LJuQooSFhTEA7NOnTzJlI0eOZI0aNeKGDQ0NWVhYGGOMsdatW7OsrCzGGGPPnz9nd+/eZYwxtnfvXmZra8vVefr0KdPS0mLR0dHs5s2bbPDgwVxZbGwss7S0ZEKhkA0YMIC9efOGMcaYSCRiu3btYowxNmrUKLZy5UrGGGP37t1j7du35+p7e3uzhg0bsry8PMYYY7m5uczCwoK9fPmSMcaYk5MTc3JyYowxduLECfbLL79wdR0cHNjWrVuL3C5OTk7MxsZGapyBgQE7ceIEY4yxhIQEpqamxpUNHTqUbdy4kTHGWGBgIFd37Nix7OzZs9x0GzZsYMuXL2eMMfb69WumrKzMwsPDGWOMnTp1iunr67Pk5GTGGGMeHh5s3rx5jDHG/P39WYcOHbj5bNy4kS1cuLDI+Fu1asVSU1MLLcvJyWHNmzdnv/zyC1u1alWR69+rVy+Z8UKhkAFgrq6uUuN79+7NbXdS9ZVXfqtRN47FxsYiJSWlRHd2b/TfiFxRLhb8uOAbREZI4ZKSkqSuUxfsre3nn39G/fr1MWjQIAQGBnJHyjweD3Xq/Pcsf/PmzaGrq4tz585hz549aNmyJVdWp04dZGVl4caNG5gwYQLatGmD7t27w83NjTu1vnnzZrRs2RJ//fUX7t27h+joaKkY1dXVubjk5OTQvHlznDhxQmZdjhw5Ajk5OZw9exZnz56FoaEhatWqVartIScnx11G0NbWRlpaGgDJUfTp06fRs2dPAECLFi3g4+OD7OxsHDlyBNbW1tw8WrZsiZ07d3Lz09bWhrGxMTdPc3NzaGhoAJCcXo6PjwcgOYpWVVXl4ldUVCz23pb09PQi109eXh6rVq3C6dOnMWfOnFJtg6SkJACQel/kx55fRr4fNep0d/6d3V9K0klZSdgUsAkz285EXZW63yI0QmQwxhAUFIRFixYVWj5lyhT8+uuvuHXrFjw8PJCdnV3ks/9ycnIQCATIyMiAUCiUKsvNzUVOTg6srKwQHh6OO3fuYP/+/ZgyZQoOHz6M3377DTo6OnBzc0NsbCw2bdoEkUgEPr/w3/BZWVnIy8uTGS8QCFCvXj0MGjSodBuikPl8jjHGvQrKzs5GXl6e1Drnr29R8yuq21qBQABNTc0Sx6+jo4OkpCSpH0wFqampQSAQlOgGw4KeP38OZWVl9OvXT2p8ZmZmuXZERKqHGnUkHRISAj6fD3Nz82Kn446iO9JRNKkcjDEsXboUFhYWmDZtWqHTzJ8/H0ZGRhg9ejT27t3L/QgFgLi4OO7voKAgxMbGYtCgQRg3bhyePHnClUVEREBOTg49evSAo6MjFBUV0bdvX5w8eRKxsbFITEzE0aNH4erqCmVlZURERAAAbt26xf2dlJTEJWWhUIigoCCMGTNGJt7Jkyfj6tWrEIvFACRJ5cCBA1+5pSQ0NDTQv39/XLhwgRt34cIFyMnJYeDAgVLrfP/+fUycOLHUyxg7diz8/PyQlZUFABCLxdixY0eR0zdu3LjcHx2Ljo7G4sWLsXnzZpnkHx8fDwMDg3JdHqn6qsSRdHk1CxoaGgpTU1MoKioWOU1ydjI2BWzCjDYzoKuqW+ZlEVIS169f5xLV6tWrYWBggJycHAQHB6Np06bw8vLijuxWrFiBmJgYuLq6YsOGDUhLS8OuXbugrKyM169fw8HBgZtveno69u3bh5ycHNy9exdXr17lbiZLSUnB2rVroaGhgbCwMFy7dg3KysqoVasWdu7cidq1ayMmJgZLliyBtrY2HB0dsXHjRjRv3hxycnKwsrLC7du3YWNjg3fv3mHChAk4dOgQlJSU8OTJE+zZswcWFhbw8vLChQsXwOPx0KFDB/Tu3Rvx8fGYO3cuGjdujJycHEyZMqXQ7eLi4oLTp0/j48ePWLZsGaZNm4YDBw4gJiYGq1atwqJFi7hT1gsWLICLiwsOHDiA+fPnY+3atdDV1YWuri5UVVVx6NAhuLm5ISEhAXl5ecjLy4Obmxuio6OxatUqxMTEYMWKFRg2bBi2bNmCly9fYsuWLWjVqhUOHz6M9+/f4+jRoxg5ciT27t2LefPmoVmzZhAKhbC3ty9y39ra2sLX17fQpwtOnz7N7Z85c+Zg/PjxaNGiBVfu7u6OM2fOID4+Hq6uruDz+UhOTkZwcDA8PDzQpUsXqfnl5uaCx+NBS0urZG88UmmoWdBi5J8eKvhr+3POPs5wv+uOd7PfQU9Vr8jpCKmq9u/fDx8fH+zfv7+yQ/mu5eTkYPTo0Th58mSFL+v69et48uQJ95w1qfqoWdBChIaGFns9Ojk7GRv9N2J6m+mUoAkhX0VBQQHjxo3DP//8U+HLyr93gHx/akySFgqFCAsLKzZJb/LfBKFIiIU/LvyGkRFSfgICAnDgwAH4+vrC09OzssP57vXr1w8ikQivXr2qsGUcPHgQM2bMgJKSUoUtg1RdVeKadHl4+/YtRCJRkUk6OTsZGwM2YnprOoom1Vf79u3h7e1d2WGQAoYPH16h82/Tpg2aNGlSocsgVVeNOZL+UscamwM2Izsvm46iCSHVCiXo71uNStIaGhqoW1f2ueeU7BRs8N+Aaa2nQV+t4rqUI4QQQspTjUrSRXWssTlgM7Jys+gomhBCSLVSY5J0fu9Xnyt4FF1PrV4lREYIIYSUTalvHAsICMCdO3eQlpaGe/fuYenSpbCxscGDBw/g6ekJa2tr3L17F0uWLIGpqWlFxCyDMYbQ0FCZZvQA4K/7fyEzNxOLOhXe9CIhhBBSVZUqSWdmZuLs2bNYs2YNAEmXeH369EFwcDCGDRuGgIAA6OrqolGjRpgwYQJ8fHwqImYZ8fHxSEpKkrlpLFWYCo97HpjaeiodRRNSQ2VlZSEmJgYmJiaVHQoh5a5Up7vfvHkDNzc3vHnzBgDQq1cvZGVlwd/fH+rq6tDVlTSz2a5dO/j7+yMmJqb8Iy5EUR1r/BXwFzJyM7DoRzqKJqQmys7OhqurK/T1S35DaHZ2NlatWlVuzTYSUpFKdSTdrFkz3L17l+vAIr9x+Q8fPkBbW5ubTiAQQE1NDUFBQVziLk5+290FlaYd79DQUPB4PDRo0IAblypMxfp76zG11VQYqFOj9KRypaSkwN3dHbGxsTAxMYG8vDwaN26MhIQEmJqawsbGprJD/GoPHz5EmzZtuOGAgAAMGTIEL168gKamZoUs09XVFZMmTZJqr18oFGLjxo14+fIlGjRoAEVFRdSrVw/6+vr49OkTxowZA3t7e6xcuRIuLi4VEhf5vuS3111Qef0ILFWS5vF4XJ+2AODm5gYHBwfk5eXJtIajpKSE5OTkEs33+PHjX9W2aUhICExMTKRi2HJ/i+Qomq5Fk0r26dMndO3aFQsXLsTq1au58YGBgbC3t8fZs2crL7hydOzYMakk3aRJE6xdu7bCEnRkZCSioqKkTnOnp6eje/fu6NOnD/bt28d1txkREYGOHTti5cqVAABjY2NkZWXh5cuX9Bwy+WqFHVTmt939tcrc4tjevXuhp6cHd3d3bNu2Taaf1/T09GI7TC9PoaGhUtej04RpWH9vPSZbT4ahuuE3iYFUjszcTITEh3zz5VrqWEJZvmT9BE+dOhUdO3bEpEmTpMa3bNmyyF6iqpPc3Fx4enri0aNHUuPV1NQwevToClvu6dOn0b17d6lxS5YsQa1ateDk5CQ13sjICIsXL5YaN2LECGzduhVbtmypsBgJ+VplStKXLl2CSCTCunXrkJ2dDSUlJcTGxnLlQqEQaWlpMDY2LrdAixMaGgpbW1tueH/gfqQJ07C40+JiapGaICQ+BK13ynYVWNEeTX2EVvqtvjhdVFQULl68WGSPVYMHD+Yu9fj4+CAgIABGRkYICQnBwIED0bp1axw6dAiOjo6YM2cOtLS0kJ2dDV9fXxw6dAh8Ph+XL1/Gp0+foKmpiaCgIJiYmKBly5Zchww+Pj7w9vbG3Llz0aJFC+zfvx8XL17E4sWLYWdnxz2Fce7cOTg6OuLp06dgjMHPzw87d+4En8/H4sWLsXXrVqxZswba2tp4+fIl0tPTsXbtWrx8+RJ+fn54//493NzcYGlpiUGDBsHJyQm7du2Cv78/6tevj8zMTKxfvx6mpqbIyspCQkIC5s+fj7i4OMyePRuRkZHcmblr167B3t4eP/30U5Hb9saNG/Dw8OCGc3NzsX///iJ7iurXr59Uv9PW1tYyP5wIqXJYKfn6+rJdu3axT58+sU+fPrEzZ86wW7dusXr16rGIiAjGGGNXrlxhHTp0+OK8UlJSGACWkpJS2jA4OTk5TE5Ojm3bto0b1+9IP/bzgZ/LPE9SfWTkZLBHUY+++SsjJ6NE8fn5+TEAzMvLq9jpgoODpT4zQqGQWVhYsJiYGMYYY6NHj2YzZ87kyps1a8YePXrEGGOsU6dOLCkpiTHGWFJSEjt+/DhjjLEbN24wGxsbrs6ePXvYuHHjuOFly5YxW1tbbrh///5Sy2jevDl7/vw5N1y/fn324MEDbnjIkCFs0aJFjDHGvL29pZaVz9DQkIWFhTHGGBs7diw7e/YsV7Zhwwa2fPlyxhhjr1+/ZsrKyiw8PJwxxtipU6dY//79i9haEq1atWKpqanccFRUFAPAtm/fXmy9gho3bswyMkq2LwkpjfLIb4wxVqoj6Xfv3qFfv35IS0uTGp+SkoIDBw5g9erV6NChwzftoeft27fIy8vj7uzOE+fBN9yX7uj+TijLK5foiLaymJiYgMfjFfmkQ05ODoRCIQ4fPozGjRtz4xUUFKCnp4dTp05hxowZkJOTQ6tW/62ntrY2UlNTAUhO25qZmaFDhw6wtbXFjBkzAIC7Hpvv8+HC5llwWEtLC/Hx8dwwj8eTuoQ1bNgwzJkzB25ubkWuv0AgACC5o/rIkSPcNWFAcrp/+PDhWLlyJeTk5KCtrc2dfSu4fkVJT09HrVq1uGEdHR2oqqoW+1RJQkICateuLbWOycnJUFYu2aULQr61Uj2CZWZmhtTUVDDGpF7q6uro3r07tm3bhnHjxmHv3r0wMzOrqJilfP741eNPj5GWk4afTIs+TUbIt6Kvr4++ffsW2XPVrVu3EB0djYyMDAiFQqmy3Nxc5OTkcMP5Ce9zvXr1QkhICCZPnowzZ87IXI/NJxaLZcZ9Ps+illEYOTm5Qqf38/OTGZednY28vDypdSzp+hVFR0cHSUlJ3LC8vDzGjx9f5LZ+8+YNHj9+LDUuMzPzq25aJaSiVftmQUNDQ6GmpsY9J3kz7CZU5FXQpl6bL9Qk5NvYuXMn7t27h71790qNT0lJQUhICBo2bIjRo0cjKCiIuwEzKysL79+/x9ChQ784/4ULF6JOnTqws7PD6dOnuR+uampqUknw2bNnEIlEX7UucXFx3N/Hjx/nbnxTU1NDSkoKACA4OFimnqamJgYOHCh1Tfj+/fuYOHFimWNp3Lgx9xhovjVr1iA7OxsuLi5SP0qEQiEuXLggc407NzcXqqqqZY6BkIpW7fuT/rxjDe9wb3Q27gx5gfwXahLybejr6yMgIADu7u6YMmUKTE1NoaysDE1NTUydOhWApM9gV1dXuLi4QE9PD+/fv8epU6dgYGCAo0eP4u7du4iMjESjRo3w+PFjvHz5Elu2bIGenh74fD62bdsGDQ0NvH//Hn/88QcAyenkFi1aYM+ePZCTk4Oenh7OnTuHw4cPQ0dHBxcuXAAgaXwoKSmp2GXkPz1x8+ZNvH37Fk+fPkWTJk2wbNkyAJKbsJo2bYpNmzahUaNGAIAVK1YgJiYGrq6u2LBhAw4dOgQ3NzckJCQgLy8PeXl5cHNzQ3R0NFatWoWYmBisWLECw4YNw5YtW/Dy5Uts3boVM2fOLHS72trawtfXF61b/3fjoKqqKnx8fLBp0yZMnDgR5ubmUFNTg5KSEiZNmiR1tB4VFVVk//OEVBU8xj57duobyn+OLCUlpcynnDp16gQTExMcPnwYOaIcaK3VgrONMxb8WPgdnoSQsjExMYGPj0+VaX4zJycHo0ePxsmTJ8tUf/fu3dDQ0MCwYcPKOTJCyie/ATXgdHfB3q/uf7yPzNxMdDPtVslREUIqmoKCAsaNG4d//vmn1HVFIhF8fHxKdDmBkMpUrZN0QkICEhISuFNx3mHe0FDUgLWedSVHRkjN4uLigujoaDg7OyMqKqqyw+H069cPIpEIr169KlW9zZs3w9nZudD+5wmpSqrE6e7evXtDXl6+VO11A5K7SH/88Uc8ffoUzZs3R7cD3aCuqI5zI85VYNSEkOosOzsbUVFR3+wJFPJ9yW/HOzc3F15eXl99urtKJOmyrsS+ffswadIkZGRkgCfPg6abJty6u8Ghg0P5B0sIIYSUEF2ThuTO7vr166NWrVq4F3EPQpGQno8mhBBSY1TrJF3wprGbYTdRu1ZtWNW1quSoCCGEkPJRrZN0wd6vvMO90dWkK/i8ar1KhBBCCKfaZrS8vDy8ffsWFhYWSM9JR8DHADrVTQghpEaptkk6LCwMubm5sLCwwN0Pd5EnzkM3E3o+mhBCSM1RbZN0SEgIAEnHGt7h3tBT1YOljmUlR0UIIYSUn2qbpENDQ6GiogIDAwPcDLuJbibdqGECQgghNUq1TtIWFhZIFabi0adHdKqbEEK+E/m9ufn4+Ej1eV5ewsPDcf/+/XKfb1lU216w8pP07Q+3IWZiummMEEJqoLt37+Lx48eoV68eGGN4/vw5evbsCS0tLWRkZEBHRwcZGRnw8fHBxo0bce3atTItJz4+Hjdv3sSnT58wYMAAhIaGwtDQEPXq1SvnNSqdKnEkPXz4cAwYMABHjx4tcZ38JH0z7CaM1I1gpkVN/BFCSE3i7u6OBw8e4LfffsOQIUMwdOhQpKSkoEOHDjh8+DBsbW0BACoqKujbty9yc3PLvKyVK1di6NChMDAwwLVr12BnZ4fdu3eXej5Hjx7FgAEDMHz48DLHUlCVOJI+fvx4qZpNS0pKQmxsLCwsLLA2fC26mdL1aEIIqUmePXuG8+fP4/bt21LjHR0dIRAIkJycXG7f+7du3YJIJMK///6LnTt3YubMmVBRUUFcXFyp55XfB0V+s6Bfq0ok6dIKDQ0FAOiZ6SHwciAc2jtUbkCEEPKdCgsLg6mpabnP98qVK9yRMgDcuXMHp0+fhqmpKX777TdkZ2eXaD5paWk4fvy4zHhjY2P06NEDAODl5YW5c+fCxMQECxcuhI2NDQAgMzOzHNbk61TrJB0lL+kyj/qPJoSQyrFz506sWbOm3OdramqKZ8+eccOdOnXCr7/+Ch8fHwCAvLx8ieajpqaGyZMnFztNcnIyjIyMcP78edjZ2UFLSwsAICdX+Smy8iMog9DQUBgZGeHep3sw0zJDfY36lR0SIVXOkSNH8PjxYwwZMgQ//PBDZYdDqrG8vDyphPXx40dcvnwZWlpaOHLkCNq1a4eUlBQMGTIEampq5bLMoUOH4sOHD9iwYQOMjY3B5/Mxbtw4aGpqAoDUcoRCIU6dOoXw8HAcPXoUdnZ2UFRULPGyhgwZgrNnzyI0NBSrVq0CIOnFysjIqFzW5WtUy64q7ezskJaWhqjBUeho2BG7BuyqwCgJ+XqPHj3Czp07YWFhAbFYDGNjY3z48AHz5s2DSCTC8+fP0bJly3JdZm5uLvr27YtRo0Zh/Pjx5RozgFLHXV7rmZKSAnd3d8TGxsLExATy8vJo3LgxEhISYGpqyp2qrK4K205t2rTBb7/9hnHjxlXYcoVCIXbt2oWXL19CT08PqqqqqFWrFqysrPDw4UPMmTNHavoXL17A3t4egYGBGDhwILZv3w49Pb0Ki+9z9+/fR3JyMnr27Fkh89+zZw/69++PunXrlql+eXVVWW2PpDv83AHX465jWedllR0OIcVKTk7GmDFj8PTpUygoKAAA5s2bx51SCw4ORmBgYLknaXl5+TI/PvKlmIHSx10e6/np0yd07doVCxcuxOrVq7nxgYGBsLe3x9mzZ8s876qisO30xx9/oHXr1hW6zJEjR2LevHnYunUrNz48PByWlpa4deuWTB0rKytoaGhg3LhxUFFR+aYJGgDatWuHCxcuIC4uDnXq1CnXeYeHh8PKyqrMCbo8VYlHsEpDJBLhzZs3EBuLAYAaMSFV3uvXr5GdnQ2BQMCNW7hwIXg8HhISErB06dJKjK5wxcUMoNRxl9d6Tp06FR07dsSkSZOkxrds2RJTpkz56vlXtqK204ABA2BgYFAhy4yMjMRPP/2E+fPnw97eXqrMxMQEHTt2RJs2bWTqvXz5EitWrMD+/fvRqVMnpKSkVEh8xenXr1+5J2hAst7t27cv9/mWRbU7kg4PD0dOTg5iVWJhqWQJfTX9yg6JVLZPnySvgrS0AFNTIDsbePlStk6rVpL/Q0OBjAzpMhMTQFsbiIsDIiKky9TUgIYNSxVes2bNIBaL0aNHD4wbNw4//PADGjVqhBEjRuDSpUv4+PEjLl68iOjoaAwbNgzm5uYAgGPHjiEsLAxGRka4desW3N3doampiU2bNkFNTQ0ikQjv37+Hk5MTdxPN/fv3cfToUbRr1w5isRjv3r1D165dsXfvXixduhSWlpY4efIk0tLS0K1bN3Ts2BEHDx6UuQmnuJgBFBl3UbGVZT0/FxUVhYsXL2L//v2FbufBgwdz6+Hj44OAgAAYGRkhJCQEAwcOROvWrXHx4kUsXrwYdnZ2MDU1BY/Hw9mzZ3H48GGkp6fD09MTRkZGEIlE8PLywv79+3HmzBksWLAAY8aMgbOzM3bs2AFHR0e4u7ujTp06UvMDgHPnzsHR0RFPnz4FYwx+fn7YuXMn+Hw+Ll68iCVLlqBly5bo3r07MjMz4e3tjRUrVsDS0rLQ7RQWFoalS5diyJAhWLRoUZnXT0VFpdDtNnv2bFhaWmLMmDGFli9evBh8vuzxXOPGjdGkSRMAkseOirpympiYiHXr1hVZDgC1atWCk5NTkeXfNVaJUlJSGACWkpJS4joXL15kAJiphymbcWFGBUZHqg0nJ8YA6dfo0ZKy169lywq+7Tt0kC07dEhStmWLbFnPnmUK8d27d2zs2LFMX1+fAWAdOnRgUVFRjDHGxo0bx/bt2yc1vb+/P+vQoQM3vHHjRrZw4UKWnZ3NFBQUWFhYGGOMsWnTprFt27YxxhiLjIxk9erV4+bLGGO9evXi5v3333+zX375hStzdXUtc8yFxV1cbKVdz8L4+fkxAMzLy6vYuIODg6XmKRQKmYWFBYuJiWGMMbZs2TJma2vLlffv35+dOnWKeXh4sN27d3Pjd+zYwf3t6OjInJycuGF7e3tuXQqb38yZM7nh5s2bs+fPn3PDf/zxB5s1axY3fP78eVa/fn2WnZ3NGCt8Oy1fvpxbflnXrzCxsbGMz+ezgwcPFlpOyq4s+a0w1e5IOiQkBEp1lRCWGkZNgRKJadOAAQOkx+VfOzU0BB49Krru/v2FH0kDwC+/AJ/fFV2GO1fj4+NRt25dHDhwAIDknorJkydjwYIFOHz4cKF1jh07BlVVVe4aq6KiInR0dKCoqIiHDx/C19cX169fR1xcHKKjowEAp0+fhqGhIfT1/zu7pKqqyv09ZswYLF++HHFxcUhNTYWVlVW5xlxcbEUpaj0LY2JiAh6Ph5iYmELLc3JyIBQKcfjwYTRu3Jgbr6CgAD09PZw6dQozZsyAnJwcWuWfSQGgra2N1NRU9O/fHz/99BN27NiBH3/8UepGqc+PJAsOFza/gsNaWlpS7UvzeDypdbS1tUVCQgJ8fX2LvAmq4GWHsq5fYd69ewexWAxra+tCy0NDQ9GoUSNqLKoSVbskHRoairrt6+IDPqCrSdfKDodUBfr6kldhlJT+O7VdGAuLosvq1JG8vtKLFy/AGEO3bt3+v0gLrF+/HhMmTJCZ1s/PDx07doRAIICmpiYGDRokVR4WFoZhw4Zh48aN6N27NyIjIwFIHpFhjBV5ShMA1NXVYWdnh/3790NZWRnTp08vl5jz49bX1y8yts+fN/3SehZGX18fffv2hbe3N8aOHStTfuvWLRgbGyMjIwNCoVCqLDc3Fzk5OdxwwaRX0Nu3b3Hv3j1cvHgRP//8M0JDQws91SsWi6WGP59fUfMvDJ/PB5/PL7RO/nYq6GvW73MGBgbg8XhchxUFMcbg5eUFi+I+IyWQkJCAP//8s9Snu6viD4Pi1qGiVIkbx0rTdndoaCgE5gI0q9sMOsqF/+ImpKpZs2aNVLvCoaGh6NKlCwDJ854pKSlgjHEN9YwdOxZ+fn7IysoCIEkKO3bswJkzZ2BlZYXevXsDACL+f83c09MTdnZ2eP36NdLS0gBIvlCioqKkvoCnTZuGXbt2QSAQfPGLvLiYC4u7uNhKu55F2blzJ+7du4e9e/dKjU9JSUFISAgaNmyI0aNHIygoiPtCzcrKwvv37zF06NBi19fT0xNBQUHo0qUL1q5di+bNmyPj/2dZ1NTUpJLg8+fPC01sJVWwuclLly5BX1+/2PdDQWVdv8IYGhpizJgx2LZtm9T4zMxMuLq6cvcgfI3atWtjzZo1cHNzK/JV2PVoxliVe5XEd992d2hoKLK6ZmGA6YAvT0xIFcDn89GnTx9s3LgROTk5SEtLQ0pKCtatWwcAmD59OpydncHn82FnZwcAaN68Ofbu3Yt58+ahWbNmEAqFsLe3R2ZmJh48eICTJ08CAAYOHIiNGzeiZcuWMDQ0xJEjR7Bo0SJ06NABjDEoKipi3759aNKkCX744Qe0bdsW6urq6Nu371fFXFjcYrG4yNhKu55F0dfXR0BAANzd3TFlyhSYmppCWVkZmpqamDp1KgDJM8Wurq5wcXGBnp4e3r9/j1OnTsHAwABeXl64cOECAMkjPElJSbh79y4iIyPRpUsX/Pvvv3jx4gWysrLQu3dvrsGM0aNHY8mSJTh8+DBycnLQqlUr7Nu3D7GxsUXOr1GjRnj8+DFevnyJLVu2QE9PD5aWlgAkjYEcPnwYycnJuH//Pq5evcrd9Pb5drp06RIuXLgAPp+Pnj17omPHjmVaP0tLS3To0EFmm+7evRtr167FhAkT0LBhQ6irq0NRURG///57uTVMUlk+79mqIpov/Vx5t91drRozSUlJgaaJJuAAnB1+FgMtB1Z4jITUNJs3b8bvv/9e2WF8t5ydnaX+JxVn9uzZ2LBhA06fPo3ExETuh9y3UF6NmVSJ090lFRoaCpgCfPBhY1K9WxUi5FtavXo1rl69iuDg4GJvGCOkpvi8Z6uq0DBJWVTLJN1CtwU0lTQrOxxCqg11dXU8efIEgYGB+Okneiqisnh5eeHff//F2bNncenSpcoOp0bL79lqwIABCA8Pr7bNxVaJa9IlFRIaAr45Hz+b/VzZoRBSrfz222+VHQIB0Lt3b+7GOlKxiurZqrqpVkfSj8IeQawipuejCSGEFCu/Z6vnz59zPVtVR9XqSPp5+nPwGA+d6neq7FAIIYRUYT//XDPOuFabI2mRSIToWtEwljOGmmL1fiyAEEIIKYlyTdIPHjyAg4MDDhw4gKlTpyIsLKzc5v3+/XuI64vRQVf2OT9CCCGkJiq3091CoRDDhg1DQEAAdHV10ahRI0yYMAE+Pj7lMv+rgVcBFaBv0+IbYSCEEEJqinJL0rdu3YK6ujp0dXUBSFq78ff3R0xMDDeuKBqrNADFLyyAD0AMDGo9qFziJYQQQqq6ckvS4eHh0NbW5oYFAgHU1NQQFBT0xSStF6QHvrz0mff69evD2NhYapy1sTVUFVVBCCGEVBVHjx6V6XuiYLv3X6PcknR8fDyUlJSkxikpKSE5OfmLdUOPhn5Vs2mEEEJIZclvr7ug8mq7u9xuHNPQ0JDpJSQ9Pb3IvmEJIYQQUrxyS9KWlpaIjY3lhoVCIdLS0mROWX9PStL1ZnVF61Y90bpVT7Ru369yS9JdunRBbGws19G7r68v2rZtS0m6hqJ1q55o3aonWrfvV7ldk5aTk8OBAwewevVqdOjQAb6+vlxn74QQQggpvXJtzKR79+7Ytm0bxo0bh71798LMzKw8Z1+qX1xVYdrSqArx0rqVXlWIl9at9KpCvLRupVcV4v3WR/7VpllQoGpsdHrzlV5ViJfWrfSqQry0bqVXFeKldSs/ldrBRv7d4KmpqSWaPjc3l6alaWlampampWmr/LT503z+1FNp8djXzuErREZGwsjIqLIWTwghhFSoiIgIGBoalrl+pSZpsViMqKgoqKmpgcfjVVYYhBBCSLlijCEtLQ316tUDn1/2K8uVmqQJIYQQUrRqdeMYIYQQ8j2hJE0IIYRUUZSkCSGEkCqKkjQhhBBSRVGSJoQQQqooStKEEEJIFVVpSfrBgwdwcHDAgQMHMHXqVISFhVVWKOUuICAAHz58gEgkwsePH+Hv71/ZIX219PR0DBkyBB8+fODG0T6s2gICArB+/Xo4OzujV69e8PX1BUD7rarz8fHB8ePHsXfvXvzyyy94/PgxANpv1cmiRYtw+/ZtAOWw31glyM7OZsbGxiw6Opoxxpifnx+zsbGpjFAqxLhx4xgABoC1adOGhYaGVnZIX2XPnj3sjz/+YABYWFgYY6xm7cO0tDRmZ2fH3r9/z42r7vswIyODLV68mBs+efIkq1WrFgsPD68R+83f35/9+eefzMnJifXs2ZP5+Pgwxqr/fmOMMW1tbbZ//37GGGN//vknMzc3rzGfN29vb3bs2DG2Z88eNmzYMPbo0SPGWM3Yb/lu3brF6taty7y9vctlv1VKkr569Spr1qwZN5yXl8cUFRW5FanunJycWGRkJIuIiKjsUMpVwSRdU/ZhYT9AGKv++/Dp06cMAHv9+jVjjLHU1FQGgB07dqza77eifoBERkZW+/3GGGPPnj1j6enpjDFJktbV1a0xn7fCfoAwVv0/b/lSUlLYX3/9xWxsbJi3t3e57LdKOd0dHh4ObW1tblggEEBNTQ1BQUGVEU6FMDAw+Kr2Wqu6mrIPJ06ciBUrVhRaVp33YbNmzXD37l2Ym5sDAHeZ4sOHD9V+v7158wZubm548+YNAKBXr17IysrC3bt3AVTv/QZI9p2KigoA4Pz581i7dm2N+bz5+Phg6NCh3HB6ejr3d3XfbwCwc+dOTJkyhRsuj/1WKUk6Pj4eSkpKUuOUlJSQnJxcGeGUu4yMDOzbtw9HjhzBxIkTERwcXNkhlTvah1Ubj8dDx44duTbx3dzc4ODggLy8vGq/34r6AdKwYcNqv9/y3b9/H3/88Qfatm2L4cOH15jPW2E/QIDq/3kDgAsXLqB3795QVFTkxpXHfquUrio1NDRkuu9KT0+Hjo5OZYRT7oYOHYr27dsDAOrWrYvBgwfj5cuXX9XIelVD+7D62Lt3L/T09ODu7o5t27ZV+/2W/wMkX/4PEGtra+Tk5NSI/dauXTu0a9cO27dvR+fOnWFvb1/t91u++/fv48KFC9wPEKD6f96ioqKQmJiIfv36SY0vj+/JStkClpaWiI2N5YaFQiHS0tJgbGxcGeGUu9atW3N/N2jQAKGhoXj27FklRlT+aB9WD5cuXYJIJMK6desgFAqhpKRUo/Zb/g8QDw8PANV/v/n7+0NXV5e7A7hr1654+PAh9PT0asx+a9euHVxcXGBubo7OnTsjPT292u+3K1eu4OPHj3Bzc4ObmxtevXqFI0eOwNjY+Kv3W6Uk6S5duiA2NhaRkZEAAF9fX7Rt27ZavuE+5+/vD01NTWRnZwMA0tLSAAAKCgqVGVa5o31Y9d26dQtRUVHo378/oqOj4eXlhYYNG9aY/fb5D5CasN/k5OTQsGFDGBgYAADevXsHeXl5WFtbV/v9VtQPkI0bN1b7/TZhwgQsWbIEixcvxuLFi6GgoIBRo0ahV69eX73fKuV0t5ycHA4cOIDVq1ejQ4cO8PX1haenZ2WEUu4MDQ2xcOFC7jrE3bt30bFjRzRp0qSSIyu7o0eP4tatWwCAxYsXo0uXLpg5cybtwyrs3bt36NevH/eFly8lJaVG7LfPf4D4+/ujdu3a1X6/tWnTBnPnzsXmzZshEAhw584dXLhwAQ0bNqz2+62oHyA2NjYQi8XVer/li4yMxObNmxEdHY3169cjMzPzq/cb9SddAby9vfHo0SOIRCK8evUKa9asQd26dSs7LFKI/B8g27dvx/Dhw7kfILQPq653796hZcuWhf4AefToEe23Kuz06dN49+4d9wNk2rRp6NmzJ33eikFJmhBCCKmiqsetc4QQQsh3iJI0IYQQUkVRkiaEEEKqKErShBBCSBVFSZoQQgipoihJE0IIIVUUJWlCCCGkiqIkTQghhFRRlKQJIYSQKoqSNCGEEFJFUZImhBBCqqj/AXyQFKy6GgU8AAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 500x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(1, 1, figsize=(5, 3))\n",
    "axs.plot(output.index, output['DisposableIncome'], color='k', label='Disposable Income (YD)')\n",
    "axs.plot(output.index, output['ConsumptionDemand'], color='g', label='Consumption (C)')\n",
    "axs.axhline(y=steady_state_consumption, color='r', linestyle='--', label=r'Steady State Consumption $C^\\star=\\frac{G(1-\\theta)}{\\theta}$')\n",
    "axs.legend(loc='lower right', frameon=False)\n",
    "axs.set_xlim(0,40)\n",
    "axs.set_title('Figure SIM.1: Convergence of disposable income (YD)\\nand consumption (C) to the Steady State')\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Wealth and Savings\n",
    "\n",
    "Corresponding to Figure 3.3 \"Wealth change and wealth level, starting from scratch (Table 3.4)\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "alpha3 = (1-model.parameters[\"PropensityToConsumeSavings\"]) / model.parameters[\"PropensityToConsumeIncome\"]\n",
    "steady_state_wealth = alpha3 * (model.scenarios[(0,\"GovernmentDemand\")][0] * (1-model.parameters[\"TaxRate\"])) / model.parameters[\"TaxRate\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(1, 1, figsize=(5, 3))\n",
    "line1 = axs.plot(output.index, output['HouseholdMoneyStock'].diff(), color='k', label='Savings, $\\Delta H_h$ (LHS)')\n",
    "ax2 = axs.twinx()\n",
    "line2 = ax2.plot(output.index, output['HouseholdMoneyStock'], color='k', linestyle='--', label='Household Money\\nStock, $H_h$ (RHS)')\n",
    "line3 = ax2.axhline(y=steady_state_wealth, color='g', label='Target Wealth, $H_h^\\star$ (RHS)')\n",
    "lines = line1 + line2 + [line3]\n",
    "labels = [l.get_label() for l in lines]\n",
    "axs.legend(lines, labels, loc='center right', frameon=False)\n",
    "axs.set_xlim(0,40)\n",
    "axs.set_title('Figure SIM.2: Savings and Household Money Stock')\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Perturbations in the Steady State"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Following the convergence to the steady state, we can introduce a shock in government spending, increasing it by 5 units. Accordingly, the steady state given by $Y^\\star=\\frac{G}{\\theta}$ would shift to $Y^\\star=125$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This kind of scenario can easily be implemented in the `MacroStat` version by adding a scenario:\n",
    "1. Noting that we have convergence to the steady state at period 40, let us set this as the scenario trigger\n",
    "2. We then need a new timeseries for the scenario, where $G=25$ from the trigger period onwards"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "model.parameters[\"scenario_trigger\"] = 40\n",
    "model.scenarios.add_scenario(\n",
    "    name=\"GovernmentDemandIncrease\",\n",
    "    timeseries={\"GovernmentDemand\":25}\n",
    ")\n",
    "model.simulate(scenario=\"GovernmentDemandIncrease\")\n",
    "output_government_demand_increase = model.variables.to_pandas()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### National Income"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "steady_state_income_new = model.scenarios[(\"GovernmentDemandIncrease\",\"GovernmentDemand\")][-1] / model.parameters[\"TaxRate\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(1, 1, figsize=(5, 3))\n",
    "axs.plot(output_government_demand_increase['NationalIncome'], color='k', label='National Income (Y)')\n",
    "axs.axhline(y=steady_state_income, color='r', linestyle='--', label='Prior Steady State Solution')\n",
    "axs.axhline(y=steady_state_income_new, color='g', linestyle='--', label='New Steady State Solution')\n",
    "axs.legend(loc='center right', frameon=False)\n",
    "axs.set_xlim(35,70)\n",
    "axs.set_ylim(95,130)\n",
    "axs.set_title('Figure SIM.3: Impact on national income Y of a\\n permanent increase in government expenditures')\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Consumption and Wealth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "steady_state_wealth_new = alpha3 * (model.scenarios[(\"GovernmentDemandIncrease\",\"GovernmentDemand\")][-1] * (1-model.parameters[\"TaxRate\"])) / model.parameters[\"TaxRate\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(1, 1, figsize=(5, 3))\n",
    "line1 = axs.plot(output_government_demand_increase['HouseholdMoneyStock'].diff(), color='k', label='Savings, $\\Delta H_h$ (LHS)')\n",
    "ax2 = axs.twinx()\n",
    "line2 = ax2.plot(output_government_demand_increase['HouseholdMoneyStock'], color='k', linestyle='--', label='Household Money\\nStock, $H_h$ (RHS)')\n",
    "line3 = ax2.axhline(y=steady_state_wealth_new, color='g', label='Target Wealth, $H_h^\\star$ (RHS)')\n",
    "lines = line1 + line2 + [line3]\n",
    "labels = [l.get_label() for l in lines]\n",
    "axs.legend(lines, labels, loc='center right', frameon=False)\n",
    "axs.set_xlim(35,70)\n",
    "ax2.set_ylim(75,105)\n",
    "axs.set_title('Figure SIM.4: Savings and Household Money Stock')\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "eirindev",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
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