{ "cells": [ { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "# Weighted cost functions\n", "\n", "In this notebook we show different ways to weight the cost function when combining multiple objectives and output variables" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import pybamm\n", "import numpy as np\n", "import pandas as pd\n", "import ionworkspipeline as iwp\n", "import matplotlib.pyplot as plt" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## Generate data\n", "\n", "First we generate some synthetic data using a variant of the Robertson model. We add an activation energy term to the rate constants of the reaction so that we can run the simulation at different temperatures (assuming isothermal conditions). To keep things simple we ignore units and assume the system is written in a suitable non-dimensional form." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "class Robertson(pybamm.BaseModel):\n", " def __init__(self):\n", " super().__init__()\n", " x = pybamm.Variable(\"x\")\n", " y = pybamm.Variable(\"y\")\n", " z = pybamm.Variable(\"z\")\n", "\n", " k_1 = pybamm.Parameter(\"k_1\")\n", " E_1 = pybamm.Parameter(\"E_1\")\n", " k_2 = pybamm.Parameter(\"k_2\")\n", " E_2 = pybamm.Parameter(\"E_2\")\n", " k_3 = pybamm.Parameter(\"k_3\")\n", " E_3 = pybamm.Parameter(\"E_3\")\n", " T = pybamm.Parameter(\"T\")\n", "\n", " arr_1 = pybamm.exp(-E_1 / T)\n", " arr_2 = pybamm.exp(-E_2 / T)\n", " arr_3 = pybamm.exp(-E_3 / T)\n", "\n", " self.rhs = {\n", " x: -k_1 * arr_1 * x + k_2 * arr_2 * y * z,\n", " y: k_1 * arr_1 * x - k_2 * arr_2 * y * z - k_3 * arr_3 * y**2,\n", " z: k_3 * arr_3 * y**2,\n", " }\n", " self.initial_conditions = {x: 1, y: 0, z: 0}\n", " self.variables = {\"x\": x, \"y\": y, \"z\": z}\n", "\n", "\n", "model = Robertson()\n", "true_inputs = {\n", " \"k_1\": 5,\n", " \"E_1\": 0.5,\n", " \"k_2\": 3,\n", " \"E_2\": 0.25,\n", " \"k_3\": 1.5,\n", " \"E_3\": 0.2,\n", " \"T\": pybamm.InputParameter(\"T\"),\n", "}\n", "true_params = pybamm.ParameterValues(true_inputs)\n", "true_params.process_model(model)\n", "solver = pybamm.IDAKLUSolver()\n", "t_data = np.linspace(0, 10, 1000)\n", "data_dict = {}\n", "for T in [1, 10]:\n", " solution = solver.solve(model, t_eval=t_data, inputs={\"T\": T}, t_interp=t_data)\n", " x_data = solution[\"x\"].data\n", " y_data = solution[\"y\"].data\n", " z_data = solution[\"z\"].data\n", " data = pd.DataFrame({\"t\": t_data, \"x\": x_data, \"y\": y_data, \"z\": z_data})\n", " data_dict[T] = data\n", "\n", "# Plot the data\n", "colors = [\"tab:blue\", \"tab:orange\", \"tab:green\"]\n", "for i, (T, data) in enumerate(data_dict.items()):\n", " plt.plot(data[\"t\"], data[\"x\"], \"-\", color=colors[i])\n", " plt.plot(data[\"t\"], data[\"y\"], \"--\", color=colors[i])\n", " plt.plot(data[\"t\"], data[\"z\"], \"-.\", color=colors[i])\n", " if i == 0:\n", " plt.plot([], [], \"-\", color=\"k\", label=\"x\")\n", " plt.plot([], [], \"--\", color=\"k\", label=\"y\")\n", " plt.plot([], [], \"-.\", color=\"k\", label=\"z\")\n", " plt.plot([], [], \"o\", color=colors[i], label=f\"T = {T}\")\n", "plt.xlabel(\"t\")\n", "plt.legend()" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## Fit model" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "To fit this model we set up a custom `Objective` class which defines how the error function is calculated from the solution. Here we will compare the values of x, y, z between model and data. The cost function used to make the comparison can be specified later." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "class Objective(iwp.objectives.Objective):\n", " def process_data(self):\n", " data = self.data[\"data\"]\n", " self._processed_data = {\"x\": data[\"x\"], \"y\": data[\"y\"], \"z\": data[\"z\"]}\n", " \n", " def build(self, all_parameter_values):\n", " data = self.data[\"data\"]\n", " t_data = data[\"t\"].values\n", "\n", " model = Robertson()\n", " all_parameter_values.process_model(model)\n", " solver = pybamm.IDAKLUSolver()\n", "\n", " def run(inputs, full_output=False):\n", " sol = solver.solve(model, t_eval=t_data, inputs=inputs, t_interp=t_data)\n", " return {\"x\": sol[\"x\"].data, \"y\": sol[\"y\"].data, \"z\": sol[\"z\"].data}\n", "\n", " self.run_ = run" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "We create a dictionary of objectives to fit the data at each temperature. When we do this, we pass in the known temperature as a `custom_parameter` to the objective. This is a parameter that is not fitted, but is passed to the model when the objective is evaluated." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "objectives = {}\n", "for T, data in data_dict.items():\n", " objectives[T] = Objective(data, custom_parameters={\"T\": T})" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "We choose to use the RMSE as our cost function. We can pass weights for both the objectives and variables to the `Cost` class. `objective_weights` should be a dictionary with the same keys as the objectives and the values are the weights for each objective. `variable_weights` should be a dictionary with the same keys as the variables and the values are the weights for each variable. If no weights are passed, the default is 1 for all objectives and variables." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "objective_weights = {1: 1, 10: 1}\n", "variable_weights = {\"x\": 0.1, \"y\": 0.1, \"z\": 0.8}\n", "cost = iwp.costs.RMSE(\n", " objective_weights=objective_weights, variable_weights=variable_weights\n", ")" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "We can then specify which parameters need to be fitted, which parameters are known, define bounds, and pass this to the standard `DataFit` class to fit the unknown parameters. Let's assume we know $k_2$ and $E_2$ and fit the remaining parameters. " ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "fit_parameters = {\n", " \"k_1\": iwp.Parameter(\"k_1\", initial_value=1, bounds=(0, 10)),\n", " \"E_1\": iwp.Parameter(\"E_1\", initial_value=0.1, bounds=(0, 1)),\n", " \"k_3\": iwp.Parameter(\"k_3\", initial_value=1, bounds=(0, 10)),\n", " \"E_3\": iwp.Parameter(\"E_3\", initial_value=0.1, bounds=(0, 1)),\n", "}\n", "known_parameters = {\"k_2\": 3, \"E_2\": 0.5}\n", "\n", "optimizer = iwp.optimizers.ScipyMinimize()\n", "data_fit = iwp.DataFit(\n", " objectives, parameters=fit_parameters, cost=cost, optimizer=optimizer\n", ")\n", "new_parameter_values = data_fit.run(known_parameters)" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "Let's compare the fitted and true values of the parameters." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "k_1: 4.9935 (fit) 5.0000 (true)\n", "E_1: 0.5970 (fit) 0.5000 (true)\n", "k_3: 1.5005 (fit) 1.5000 (true)\n", "E_3: 0.2390 (fit) 0.2000 (true)\n" ] } ], "source": [ "for key, value in new_parameter_values.items():\n", " print(f\"{key}: {value:.4f} (fit) {true_params[key]:.4f} (true)\")" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "We can plot the trace of the cost and the parameter values to see how the fit progressed" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/Users/robertwtimms/Documents/Ionworks/battery-parameter-pipeline/src/ionworkspipeline/data_fits/data_fit.py:568: UserWarning: The figure layout has changed to tight\n", " fig.tight_layout()\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAABKUAAAKyCAYAAAAEvm1SAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy80BEi2AAAACXBIWXMAAA9hAAAPYQGoP6dpAAD7fklEQVR4nOzdeXxU1dkH8N+dPftCSMISCEJQFgUFQXABLYq4VLQqoq8gKiqGqkVqxVaRasVqS7EapVoVa92KrSuICwqooGyCyh5ICCRkXybrLHfu+8fMnWQy9062WTO/76d8auaeuXPmZDJn5rnPeY4gSZIEIiIiIiIiIiKiINKEugNERERERERERBR9GJQiIiIiIiIiIqKgY1CKiIiIiIiIiIiCjkEpIiIiIiIiIiIKOgaliIiIiIiIiIgo6BiUIiIiIiIiIiKioGNQioiIiIiIiIiIgo5BKSIiIiIiIiIiCjoGpYiIiIiIiIiIKOgYlCIiIqKIMXXqVEydOjXU3SAiIiIiP2BQioiIKMwdOXIEd955J0455RSYTCYkJibi3HPPxTPPPIPm5ma/P15TUxMeffRRbNy40e/npuB4/vnnsXr16qA+5hNPPIH3338/qI9JREREkU0X6g4QERGRurVr1+K6666D0WjEnDlzMHr0aFitVnzzzTf47W9/i7179+LFF1/062M2NTVh2bJlAMCspAj1/PPPIy0tDbfcckvQHvOJJ57Atddei5kzZwbtMYmIiCiyMShFREQUpgoKCnDDDTdg8ODB+PLLL9GvXz/3sdzcXOTn52Pt2rUh7GF0a2xsRFxcXKi7ETR2ux0OhwMGg6HH54q2sSMiIiJlXL5HREQUpp566ik0NDTg5Zdf9ghIyYYNG4Z7773X/bPdbsdjjz2GoUOHwmg0Ijs7Gw899BAsFovH/Xbs2IHp06cjLS0NMTExGDJkCG699VYAQGFhIfr27QsAWLZsGQRBgCAIePTRR1X7WV1djcWLF+P0009HfHw8EhMTMWPGDOzZs8ej3caNGyEIAv7zn//gT3/6EwYOHAiTyYRf/OIXyM/P9zrviy++iKFDhyImJgYTJkzA119/3emxEwQBCxcuxBtvvIFTTz0VJpMJ48aNw+bNmz3aHTt2DHfffTdOPfVUxMTEoE+fPrjuuutQWFjo0W716tUQBAGbNm3C3XffjfT0dAwcOLBb5/jmm29wzz33oG/fvkhOTsadd94Jq9WK2tpazJkzBykpKUhJScEDDzwASZI8zuFwOLBy5UqMGjUKJpMJGRkZuPPOO1FTU+Nuk52djb1792LTpk3u31/bjLfa2lrcd999yMrKgtFoxLBhw/DnP/8ZDofD3aawsBCCIOAvf/kLVq5c6X5N7du3T3W8Gxsb8dprr7kfU87SevTRRyEIAvbt24cbb7wRKSkpOO+88wAAP/74I2655Rb30tTMzEzceuutqKqq8nqM4uJi3Hbbbejfvz+MRiOGDBmCBQsWwGq1dum5ERERUfhgphQREVGY+uijj3DKKadg8uTJnWp/++2347XXXsO1116L+++/H99//z2WL1+O/fv347333gMAlJeX45JLLkHfvn3x4IMPIjk5GYWFhfjf//4HAOjbty9eeOEFLFiwAFdffTWuueYaAMAZZ5yh+rhHjx7F+++/j+uuuw5DhgxBWVkZ/vGPf2DKlCnYt28f+vfv79H+ySefhEajweLFi1FXV4ennnoKN910E77//nt3m5dffhl33nknJk+ejPvuuw9Hjx7FL3/5S6SmpiIrK6tT47Fp0ya88847uOeee2A0GvH888/j0ksvxbZt2zB69GgAwPbt27FlyxbccMMNGDhwIAoLC/HCCy9g6tSp2LdvH2JjYz3Oeffdd6Nv37545JFH0NjY2K1z/PrXv0ZmZiaWLVuG7777Di+++CKSk5OxZcsWDBo0CE888QTWrVuHp59+GqNHj8acOXPc973zzjuxevVqzJs3D/fccw8KCgrw3HPP4YcffsC3334LvV6PlStX4te//jXi4+Px+9//HgCQkZEBwLk0c8qUKSguLsadd96JQYMGYcuWLViyZAlOnjyJlStXevT11VdfRUtLC+644w4YjUakpqYqjvXrr7+O22+/HRMmTMAdd9wBABg6dKhHm+uuuw45OTl44okn3MG2zz//HEePHsW8efOQmZnpXo66d+9efPfddxAEAQBQUlKCCRMmoLa2FnfccQdOO+00FBcX491330VTUxMMBkOXnxsRERGFAYmIiIjCTl1dnQRAuuqqqzrVfvfu3RIA6fbbb/e4ffHixRIA6csvv5QkSZLee+89CYC0fft21XNVVFRIAKSlS5d26rFbWlokURQ9bisoKJCMRqP0xz/+0X3bV199JQGQRowYIVksFvftzzzzjARA+umnnyRJkiSr1Sqlp6dLY8eO9Wj34osvSgCkKVOmdNgnABIAaceOHe7bjh07JplMJunqq69239bU1OR1361bt0oApH/961/u21599VUJgHTeeedJdrvdo31XzzF9+nTJ4XC4b580aZIkCIJ01113uW+z2+3SwIEDPZ7r119/LQGQ3njjDY/HWr9+vdfto0aNUhynxx57TIqLi5MOHTrkcfuDDz4oabVaqaioSJIk5+8PgJSYmCiVl5d7nUdJXFycNHfuXK/bly5dKgGQZs+e7XVMaezeeustCYC0efNm921z5syRNBqN4utWHsvOPjciIiIKH1y+R0REFIbMZjMAICEhoVPt161bBwBYtGiRx+33338/ALhrTyUnJwMAPv74Y9hsNn90FUajERqN8yOFKIqoqqpCfHw8Tj31VOzatcur/bx58zzqEp1//vkAnBlXgHN5YXl5Oe666y6PdrfccguSkpI63a9JkyZh3Lhx7p8HDRqEq666Cp9++ilEUQQAxMTEuI/bbDZUVVVh2LBhSE5OVuz7/PnzodVqPW7r6jluu+02dwYQAEycOBGSJOG2225z36bVajF+/Hj3mADAmjVrkJSUhIsvvhiVlZXuf+PGjUN8fDy++uqrDsdkzZo1OP/885GSkuJxjmnTpkEURa/ljb/61a/cyzl76q677vK6re3YtbS0oLKyEueccw4AuMfO4XDg/fffx5VXXonx48d7nUMey64+NyIiIgo9Lt8jIiIKQ4mJiQCA+vr6TrU/duwYNBoNhg0b5nF7ZmYmkpOTcezYMQDAlClT8Ktf/QrLli3D3/72N0ydOhUzZ87EjTfeCKPR2K2+OhwOPPPMM3j++edRUFDgDvgAQJ8+fbzaDxo0yOPnlJQUAHDXRZL7mpOT49FOr9fjlFNO6XS/2t8fAIYPH46mpiZUVFQgMzMTzc3NWL58OV599VUUFxd71HCqq6vzuv+QIUO8buvqOdo/fznQ1n5ZYlJSkketqMOHD6Ourg7p6emKz7e8vFzx9rYOHz6MH3/8UTXQ1P4cSs+3u5TOVV1djWXLluHtt9/2emx57CoqKmA2m91LLtV09bkRERFR6DEoRUREFIYSExPRv39//Pzzz126X9sMHLXj7777Lr777jt89NFH+PTTT3Hrrbfir3/9K7777jvEx8d3ua9PPPEEHn74Ydx666147LHHkJqaCo1Gg/vuu0+xwHT7TCOZ1K6odzD8+te/xquvvor77rsPkyZNQlJSEgRBwA033KDY97aZPd09h9rzV7q97Zg4HA6kp6fjjTfeULx/ZzKaHA4HLr74YjzwwAOKx4cPH+7xs9Lz7S6lc11//fXYsmULfvvb32Ls2LGIj4+Hw+HApZde2uXi5F19bkRERBR6DEoRERGFqSuuuAIvvvgitm7dikmTJvlsO3jwYDgcDhw+fBgjRoxw315WVoba2loMHjzYo/0555yDc845B3/605/w5ptv4qabbsLbb7+N22+/vcPAVnvvvvsuLrzwQrz88sset9fW1iItLa1L55KfC+DMfLnooovct9tsNhQUFGDMmDGdOs/hw4e9bjt06BBiY2PdAZx3330Xc+fOxV//+ld3m5aWFtTW1na6v/44R2cMHToUX3zxBc4999wOg0Vqv8OhQ4eioaEB06ZN82vffD2mmpqaGmzYsAHLli3DI4884r69/e+tb9++SExM7DBAG8jnRkRERIHBmlJERERh6oEHHkBcXBxuv/12lJWVeR0/cuQInnnmGQDAZZddBgBeO4ytWLECAHD55ZcDcAYC2mckjR07FgBgsVgAwL1bXGeDKlqt1uuca9asQXFxcafu39748ePRt29frFq1Clar1X376tWruxTo2bp1q0dNp+PHj+ODDz7AJZdc4s5KUur7s88+67EEsSP+OEdnXH/99RBFEY899pjXMbvd7jE2cXFximN1/fXXY+vWrfj000+9jtXW1sJut3e7f2qPqUb+HbQfu/avYY1Gg5kzZ+Kjjz7Cjh07vM4j3z+Qz42IiIgCg5lSREREYWro0KF48803MWvWLIwYMQJz5szB6NGjYbVasWXLFqxZswa33HILAGDMmDGYO3cuXnzxRdTW1mLKlCnYtm0bXnvtNcycORMXXnghAOC1117D888/j6uvvhpDhw5FfX09XnrpJSQmJroDWzExMRg5ciTeeecdDB8+HKmpqRg9erRqTZ8rrrgCf/zjHzFv3jxMnjwZP/30E954440u1X9qS6/X4/HHH8edd96Jiy66CLNmzUJBQQFeffXVLp1z9OjRmD59Ou655x4YjUY8//zzAIBly5Z59P31119HUlISRo4cia1bt+KLL75QrIWlxh/n6IwpU6bgzjvvxPLly7F7925ccskl0Ov1OHz4MNasWYNnnnkG1157LQBg3LhxeOGFF/D4449j2LBhSE9Px0UXXYTf/va3+PDDD3HFFVfglltuwbhx49DY2IiffvoJ7777LgoLC7uV3SY/5hdffIEVK1agf//+GDJkCCZOnKjaPjExERdccAGeeuop2Gw2DBgwAJ999hkKCgq82j7xxBP47LPPMGXKFNxxxx0YMWIETp48iTVr1uCbb75BcnJyQJ8bERERBUiIdv0jIiKiTjp06JA0f/58KTs7WzIYDFJCQoJ07rnnSs8++6zU0tLibmez2aRly5ZJQ4YMkfR6vZSVlSUtWbLEo82uXbuk2bNnS4MGDZKMRqOUnp4uXXHFFdKOHTs8HnPLli3SuHHjJIPBIAGQli5dqtq/lpYW6f7775f69esnxcTESOeee660detWacqUKdKUKVPc7b766isJgLRmzRqP+xcUFEgApFdffdXj9ueff14aMmSIZDQapfHjx0ubN2/2OqcaAFJubq7073//W8rJyZGMRqN05plnSl999ZVHu5qaGmnevHlSWlqaFB8fL02fPl06cOCANHjwYGnu3Lnudq+++qoEQNq+fbvXY/X0HEuXLpUASBUVFR63z507V4qLi/N6vBdffFEaN26cFBMTIyUkJEinn3669MADD0glJSXuNqWlpdLll18uJSQkSAA8xqy+vl5asmSJNGzYMMlgMEhpaWnS5MmTpb/85S+S1WqVJKn1d/L00093NNRuBw4ckC644AIpJiZGAuB+7mrPT5Ik6cSJE9LVV18tJScnS0lJSdJ1110nlZSUKL7mjh07Js2ZM0fq27evZDQapVNOOUXKzc2VLBZLl54bERERhQ9BkkJQVZSIiIgogARBQG5uLp577rlQd4WIiIiIVLCmFBERERERERERBR2DUkREREREREREFHQMShERERERERERUdBx9z0iIiLqdVgyk4iIiCj8MVOKiIiIiIiIiIiCjkEpIiIiIiIiIiIKOgaliIiIiIiIiIgo6BiUIiIiIiIiIiKioGNQioiIiIiIiIiIgo5BKSIiIiIiIiIiCjoGpYiIiIiIiIiIKOgYlCIiIiIiIiIioqBjUIqIiIiIiIiIiIKOQSkiIiIiIiIiIgo6BqWIiIiIiIiIiCjoGJQiIiIiIiIiIqKgY1CKiIiIiIiIiIiCThfqDoQzh8OBkpISJCQkQBCEUHeHiCjoJElCfX09+vfvD40meq9jcD4gomjGuaAV5wMiimaBmA8YlPKhpKQEWVlZoe4GEVHIHT9+HAMHDgx1N0KG8wEREecCgPMBERHg3/mAQSkfEhISADgHPDExsUv3FUURR44cwdChQ6HVagPRvajAcew5jqF/ROs4ms1mZGVlud8PoxXng9DiGPoHx7HnonUMORe06u58EK2vHX/jOPYcx9A/onUcAzEfMCjlg5ySm5iY2K0vIfHx8UhMTIyqF6m/cRx7jmPoH9E+jtG+RIHzQWhxDP2D49hz0T6G0T4XAN2fD6L9teMvHMee4xj6R7SPoz/ng+heFE5ERERERERERCHBoBQREREREREREQUdg1JERERERERERBR0DEoREREREREREVHQMShFRERERERERERBx6AUEREREREREREFHYNSREQUUTZv3owrr7wS/fv3hyAIeP/99zu8z8aNG3HWWWfBaDRi2LBhWL16dcD7SUREgcX5gIgo8ulC3YFA+/jjj3H//ffD4XDgd7/7HW6//fZQd4mIiHqgsbERY8aMwa233oprrrmmw/YFBQW4/PLLcdddd+GNN97Ahg0bcPvtt6Nfv36YPn16lx7barXCarV63a7RaKDT6TzayURRdN9Pq9VCEATo9XrFtu21b2uz2SBJUlDbAoDBYOhWW7vdDofD0eO2oih6PGZH59Xr9RAEocttRVGEKIp+aavT6aDRaMKmrcPhcL8O5ddiW1qt1n2bw+GA3W5XPW8w2kqSBJvN5pe2bf8+e9q27d+zXq9X/bv3dd6O2obre0Q4iqT5oP1cAITv75rzQfTMB+3nAoDzQWfbcj7wn14dlLLb7Vi0aBG++uorJCUlYdy4cbj66qvRp0+fgD/2aY98CpsoATjidcyo0+DPvzoDM88cEPB+EBH1NjNmzMCMGTM63X7VqlUYMmQI/vrXvwIARowYgW+++QZ/+9vfVL+EWCwWWCwW989msxkA8PTTT8NoNHq1z8nJwY033uj++c9//rN70pYkCdXV1UhNTYUgCMjOzsbcuXPdbVesWIGmpibFfvTv3x/z5893//zss8+itrZWsW3fvn1x9913ezzviooKxbbJycm499573T+//PLLKCkpUWwbGxuL3/72t+6fX3/9dRQWFiq21ev1eOihh9w/v/XWWzh8+LBiWwBYunSp+7/fffdd7Nu3T7GdJEn41a9+5f7A/eGHH2L37t2q5128eDHi4uIAAOvWrcOOHTtU2957771ITk4GAHz22WfYunWratsFCxYgPT0dgDPbYtOmTaptb7/9dgwY4Jznv/32W3zxxReqbefOnYvs7GwAwLZt2/DJJ5+otp09ezaGDx8OANi9ezc++OAD1bbXXnstRo0aBQDYu3cv1qxZ4/FabOuqq67C2LFjAQCHDh3CW2+9pXreGTNmYMKECQCAwsJCvPbaa6ptp02bhnPPPRcAUFxcjH/+85+qbadMmYKpU6cCAMrLy/HCCy+otp00aRIuueQSAEBtbS2eeeYZ1bbjx4/H5ZdfDsAZxPjLX/6i2nbs2LG46qqrADg//C9fvtzjeNu/51GjRuG6665zH3v88cdVz+vrPaK9cHyP+Ne//qXYLtQiaT5oPxcA4fm75nyQDKD3zwcvvfSS4lwAcD6QcT5wCsZ80KuDUtu2bcOoUaPcbwIzZszAZ599htmzZ4e0Xxa7AxsOlDMoRUQUBFu3bsW0adM8bps+fTruu+8+1fssX74cy5Yt87q9pqbG42qurLS01OPDdlVVlfsKoCRJaG5uRnV1NQRBQExMjEfbyspKtLS0KPZDp9N5tK2oqEB9fb1iW0mSPNqWl5ejpqZGsa3NZvNqW11drdi2qanJo21ZWZlq2/b9LS0tVW0LwKPtyZMnVdtKkoSamhrk5+dDo9GgpKTE53nz8/MRGxsLAB22PXLkCBITEzvV9ujRo6irqwPg/EDtq21BQYH7g+OJEyd8ti0sLHR/ID1+/HiHbeUvEUVFRT7bHjt2zP16PXbsGKqrqz1ei20VFRW5v7gVFhb6PO/x48eRkpICoONxOHHihPv37Ou1I59LbltVVeWzbUlJibut2WzudNumpqZOt7VarV5t2/49nzx50uM17Ou8vt4j2gvH9wi1LyuRJpTzQfu5AAjP3zXng94/HxQVFanOBfJxzgecD2TBmA8EyVfOZYht3rwZTz/9NHbu3ImTJ0/ivffew8yZMz3a5OXl4emnn0ZpaSnGjBmDZ5991h2tfffdd7Fx40Y899xzAJxXNARBwOLFizv1+GazGUlJSairq3O/QXVWWV0TCo4exZBTTvFIi3x35wk8+ckBTB+VgX/cPL5L54xGoiji8OHDyMnJUUwvpY5xDP0jWsexJ++DwSAIguLc0Nbw4cMxb948LFmyxH3bunXrcPnll6OpqQkxMTFe91G6Mp6VlYXS0lLFceho+V5+fj6GDRvG5XvdbCuKIo4dO+b+++Nyje4t17BYLB6vxba4XKNzbdv+PUfTco2qqipkZGSE7VwAhP980H4ukPscbr9rzge9fz6w2Ww4cOCA4lwAcD7obFvOB/6bD8I6U6qjdeLvvPMOFi1ahFWrVmHixIlYuXIlpk+fjoMHD7rTKbtCLT23oz9yJSkxOlQZNUiJ0Xn8safEOIfcYnN0+ZzRSBRFOBwcq57gGPpHtI5jtD1fmdFoVFyWERMTo/ilRamdTBRFmEwmxMTEKH7468z5ZF0JiPamtqIouj90tv3wGcw+9Ia2Go3G52uxbdu2H0A7Om8g2gLw+NAeLm19/T135W85UG0D9foxmUydbtvb+Gs+6GguaNu2M8LlfSXYbTkf9LwtgE7NBfJ5OR8ot+V84D9hHZTqaJ34ihUrMH/+fMybNw+Acy3k2rVr8corr+DBBx9E//79UVxc7G5fXFzszqJSopaee+TIEcTHx3ep7w6HA9XV1e7UUll1pTOFrra+wee6anJSG0fqPI6hf0TrODY0NIS6Cz2WmZmJsrIyj9vKysqQmJjYpcmdiIgiG+cDIqLwE9ZBKV+sVit27tzpkX6r0Wgwbdo0d1G6CRMm4Oeff0ZxcTGSkpLwySef4OGHH1Y955IlS7Bo0SL3z3J67tChQ7ucmqaUogsAR62lAMqhNRiRk5PTpXNGI7VxpM7jGPpHtI6jnDEaySZNmoR169Z53Pb5559j0qRJIeoRERGFAucDIqLwE7FBqcrKSoiiiIyMDI/bMzIycODAAQDOFLu//vWvuPDCC+FwOPDAAw/43HlPLT23q6mhMo1G43Vfk8E55Fa7FFVfbHtCaRypaziG/hGN4xiOz7WhoQH5+fnunwsKCrB7926kpqZi0KBBWLJkCYqLi927g9x111147rnn8MADD+DWW2/Fl19+if/85z9Yu3ZtqJ4CERH5AecDIqLIF7FBqc765S9/iV/+8peh7oabUef8gme1qxfZIyIidTt27MCFF17o/lnOcJ07dy5Wr16NkydPoqioyH18yJAhWLt2LX7zm9/gmWeewcCBA/HPf/5TdftvIiKKDJwPiIgiX8QGpdLS0qDVahXXhWdmZoaoVx0z6Jy1aCz26CweTETUU1OnTvW528/q1asV7/PDDz8EsFdERBRsnA+IiCJfxFbrNRgMGDduHDZs2OC+zeFwYMOGDWG9LtygdQ45M6WIiIiIiIiIKJqFdaZUR+vEFy1ahLlz52L8+PGYMGECVq5cicbGRvdufOHIqHcFpUQGpYiIiIiIiIgoeoV1UKqjdeKzZs1CRUUFHnnkEZSWlmLs2LFYv369V/HzrsrLy0NeXh5E0f9L7ORMKYuNQSkiIiIiIiIiil5hHZTqaJ04ACxcuBALFy706+Pm5uYiNzcXZrMZSUlJfj23Ue8sdG5hphQRERERERERRbGIrSkVqdrWlOoo4EZERERERERE1FsxKBVkck0pgHWliIiIiIiIiCh6MSgVZHKmFABYuAMfEREREREREUUpBqWCzKhrkynFoBQRERERERERRSkGpYJMEITWHfgYlCIiIiIiIiKiKMWgVAjI2VLMlCIiIiIiIiKiaMWglIK8vDyMHDkSZ599dkDOb9DJmVJiQM5PRERERERERBTuGJRSkJubi3379mH79u0BOT8zpYiIiIiIiIgo2jEoFQIGBqWIiIiIiIiIKMoxKBUCrcv3GJQiIiIiIiIioujEoFQIGHVaAMyUIiIiIiIiIqLopQt1B6JRpBQ631FYjW2F1YrHYvRazBw7AClxhiD3ioiIiIiIiIh6AwalQsAYAcv3RIeEW17djgaLXbVNmdmCB2ecFsReEREREREREVFvwaBUCERCTSmb6HAHpK4+cwB0GsF9bH+pGT8Xm1HbZA1V94iIiIiIiIgowjEopSAvLw95eXkQxcAsrzNGwO57okNy//fya06HSa91/7xq0xH8XGyGvU0bIiIiIiIiIqKuYKFzBbm5udi3bx+2b98ekPMbXIXOwzlTqm3ASdsmSwqAO2tKZFCKiIiIiIiIiLqJQakQiIRMKbvY2jet4BmUkoNUzJQiIiIiIiIiou5iUCoEImH3PTkLSiMAGo1yUEp0hG9QjYiIiIiIiIjCG4NSIRARmVKuoJRO4/0S0XL5HhERERERERH1EINSIWCIgKCUHHBqX08KYE0pIiIiIiIiIuo5BqVCwKiVl++Fb1CqNVPKOyildWVPsaYUEREREREREXUXg1IhYNQ7d98L70wpZ9+0WmZKEREREREREZH/MSgVAgZt+Bc670xNKbvIoBQRERERERERdQ+DUiFg1LtqSonhmyklB5yUl+8xU4qIiIiIiIiIeoZBKQV5eXkYOXIkzj777ICc350pZQvfoJSvQufuoJTEoBQRERERERERdQ+DUgpyc3Oxb98+bN++PSDnj4hMKXn5no+aUix0TkRERERERETdxaBUCBi0zkLnEZ8p5Qjf/hMRERERERFReGNQKgSMOtfyvbDOlHL2TammlFz8nIXOiYiIiIiIiKi7GJQKAYMclLKF7+57rZlS6rvvsdA5EREREREREXUXg1IhIGdKRURNKe6+R0REREREREQBwKBUCMiZUlZ7+AalRLHjmlIsdE5ERERERERE3cWgVAi4l++FcVDKV6aUjplSRERERERERNRDDEqFgFHn3H0vrDOlOrX7HoNSRERERERERNQ9DEqFgHv3PXv4Fjp3776nVciU0nL5HhGFVl5eHrKzs2EymTBx4kRs27bNZ/uVK1fi1FNPRUxMDLKysvCb3/wGLS0tQeotEREFCucDIqLIxqBUCBjb1JSSpPAM7NhF9d33WpfvhW+mFxH1Xu+88w4WLVqEpUuXYteuXRgzZgymT5+O8vJyxfZvvvkmHnzwQSxduhT79+/Hyy+/jHfeeQcPPfRQkHtORET+xPmAiCjy6ULdgWgk15RySM5sI71CNlKoiT5333P2n5lSRBQKK1aswPz58zFv3jwAwKpVq7B27Vq88sorePDBB73ab9myBeeeey5uvPFGAEB2djZmz56N77//XvUxLBYLLBaL+2ez2QwAEEURoti1LFdRFOFwOLp8P2rFMfQPjmPPResYhuvzjaT5IFpfO/7Gcew5jqF/ROs4BuL5MiilIC8vD3l5eQF7gck1pQBntpReG34Ja3ZfNaUE1pQiotCwWq3YuXMnlixZ4r5No9Fg2rRp2Lp1q+J9Jk+ejH//+9/Ytm0bJkyYgKNHj2LdunW4+eabVR9n+fLlWLZsmdftR44cQXx8fJf67HA4UF1djfz8fGgUsk+pYxxD/+A49ly0jmFDQ0Oou+Al0uaDaH3t+BvHsec4hv4RreMYiPmAQSkFubm5yM3NhdlsRlJSkt/PL2dKAc4d+OKMfn+IHpOX5ilmSmkZlCKi0KisrIQoisjIyPC4PSMjAwcOHFC8z4033ojKykqcd955kCQJdrsdd911l8/lGkuWLMGiRYvcP5vNZmRlZWHo0KFITEzsUp9FUUR+fj6GDRsGrVbb8R3IC8fQPziOPRetYyhnB4WTSJsPovW1428cx57jGPpHtI5jIOYDBqVCQKsRoNMIsDuksN2Bz1emlI677xFRBNm4cSOeeOIJPP/885g4cSLy8/Nx77334rHHHsPDDz+seB+j0Qij0fuKgVar7dYHD41G0+37khPH0D84jj0XjWPYW55rqOeDaHztBALHsec4hv4RjeMYiOfKoFSIGHQa2K1i2O7A57umVOvue5IkQRDCryYWEfVOaWlp0Gq1KCsr87i9rKwMmZmZivd5+OGHcfPNN+P2228HAJx++ulobGzEHXfcgd///vdRlXJNRNRbcD4gIuod+M4bIm134AtHcqaUTqHeVdtAFZOliCiYDAYDxo0bhw0bNrhvczgc2LBhAyZNmqR4n6amJq8vGvJVnnDdAZWIiHzjfEBE1DswUypE5LpSljANSnUmUwoA7A4HtJroSVckotBbtGgR5s6di/Hjx2PChAlYuXIlGhsb3bsvzZkzBwMGDMDy5csBAFdeeSVWrFiBM888071c4+GHH8aVV14ZVenWRES9DecDIqLIx6BUiIR7UMou+th9r81trCtFRME2a9YsVFRU4JFHHkFpaSnGjh2L9evXu4vdFhUVeVwJ/8Mf/gBBEPCHP/wBxcXF6Nu3L6688kr86U9/CtVTICIiP+B8QEQU+RiUChGjznk15tpVW9A+7KPVCPj1RTm45xc5we+Yi8/d9zwypRiUIqLgW7hwIRYuXKh4bOPGjR4/63Q6LF26FEuXLg1Cz4iIKJg4HxARRTbWlAqRCUNSAQCS5KzL1PafTZSw7qeTIe1f6+57SjWlWm9zMChFRERERERERN3ATKkQeeLq07Ho4uFwtCuquLuoFne8vjPky/rcNaW03plSbZOnmClFRERERERERN3BoFQIpcUbvW7LTDIBAFpsYrC746E1U8o7KCUIAnQaAXaHxJpSRERERERERNQtXL4XZmL0zlpToQ5K+dp9D2gNVjFTioiIiIiIiIi6g0GpMGNyBaWaQ54p5Vw+qJQpBbQGq0SRQSkiIiIiIiIi6joGpcKMUe/8lbTYHJCk0AV8OsqU0rgzpUJb+4qIiIiIiIiIIhODUmFGXr4HIKTFzu2i+u57QGuwqn2hdiIiIiIiIiKizmBQSkFeXh5GjhyJs88+O+iPbWoTlAplXamOa0o5XzqsKUVERERERERE3cGglILc3Fzs27cP27dvD/pj67Uadx2nFlvoMqVsPnbfA1qDVXbWlCIiIiIiIiKibmBQKgzFhEGxc9FVK0qn9b37nshMKSIiIiIiIiLqBgalwpDJXew8dEGp1ppSKplSWrnQOYNSRERERERERNR1DEqFIbmuVFjXlBKYKUVERERERERE3acLdQfImykMlu/ZHb5335MzqOyO0NW9IiIiIvKnbw5X4p/fHFW96HbNmf0xIjbInSIiIurFGJQKQ/LyPUsIC513vPue83bGpIiIiKi3eO6rw/juaLXq8SMVDXhl5oAg9oiIiKh3Y1AqDMWEwfI9eweFzltrSjEqRURERL1DbZMNALBg6lAMz4h3317daMNjH+9DTaMtVF0jIiLqlRiUCkPhsHyv40wpjUc7IiIiokhnbnYGnS4dlYkxWcnu2+uanEGpZpsIq8jPPkRERP7CQudhyKiTM6VCl4XUUU0pnYa77xEREVHvYm6xAwASY/QetyeYdHDt8YIGS+guGhIREfU2DEqFoRhD6JfvdbamFDOliIiIqDewiw40WFxBKZPnYgKNRkCiyRmoarCydAEREZG/MCgVhkw6568lpLvviXKmlEpQSmCmFBEREfUeckAKABJMeq/jybHO2+qZKUVEROQ3DEqFIbmmlCWMM6XkQucOBqWIiIioFzA3O4NSMXotDDrvj8hJMcyUIiIi8jcWOg9D7uV79u5/6Cmpbcbsl75DudmieHxASgzW3DkJKXEGxePyrnqqmVKsKUVERES9iLnFWeQ8MUb547EclKq3MChFRETkL8yUCkPu5XvW7mdKbT1ShWNVTWi2iYr/8ssbsPt4rer93ZlSWpVMKXdNKX4wIyIiosgn77yXqLB0D2ibKcXle0RERP7CTKkwZNT3vNC5XBfhwlP74o9XjfY4lvvmLvx4og4Wu/r5O9p9j5lSRERE1Ju0ZkopB6Vaa0rxghwREZG/MCgVhmJcQameFDqvd32wSk8wISs11uOYfAXQ4mN5YIc1pVzBKu6+R0RERL2BXFOq/c57MvfyPdaUIiIi8hsu3wtDJnemVPc/9NS3OD9YJSh8sDK6lgdafJy/NVNKOSilkTOlRAaliIiIKPJ1mCkV46zDyd33iIiI/IdBKQV5eXkYOXIkzj777JA8vknvChr5WF7XkXqLHJTy/mBl7MT5O86Ucu2+JzEoRURERJGv8zWlmClFRETkL1y+pyA3Nxe5ubkwm81ISkoK+uO7l+/1oJCmnCkVr5gp1XEmlk3k7ntEREQUPiRJwsvfFKCgslHxeJ84A+6aOhSxhu59vDW7Pjup7r7nrinFTCkiIiJ/YVAqDLmX7/UkU8qVgq60fK8zmVitmVLKyXStu+8xKEVERESBt7fEjMfX7vfZZlCfOFw7bmC3zt/pTCkWOiciIvIbBqXCkD9qSjW0qBfrlDOlfBU6d9eU0naQKcWaUkRERBQEctAoLd6Am8/J9jj22b5S7C0xo7LB0v3zd3b3vR5kshMREZEnBqXCkJzJ5Jfle0aFmlKuQuctPnb362xNKdHBq4VEREQUeHIGeb+kGNw7LcfjWG2zFXtLzO7AVXe07r7XcaaUxJqaREREfsFC52FIzpTqUaFzH8v33LvvqWRKSZLkDkp1uPsel+8RERFREMgZ5PLFu7bkQFJdT4JS7kwp5Wu28u57ogQ0MluKiIjILxiUCkMxfli+17r7nkJQSg56qZy/bZ2ojjOlGJQiIiKiwJMzvOWLd23JWUxysfLu6KimlEmvgcFV1qAnGVlERETUikGpMCR/2Gr2sbzOF4dDQoPF1+57vgudt81+0mmVXyJaVwF0BqWIiIgoGOSLdfLnmLbkOlA9y5SSd99TDkoJgoAkV7ZUbRODUkRERP7AoFQYktPSRYcEm9j1bKlGqx1yqQOlq33GDjKxupIpxeV7REREFAzyxTSjr0ypbgal7KLDfUFPaZOY1sdxHqtrYVCKiIjIHxiUCkNt09J9FSNXI3+o0msFxauJXcmUUqsppeXyPSIiIgoid00pnXdQSg4kdTcoJX92AoAEleV7AJDk2oGvjplSREREfsGgVBgy6jQQXLGg7izha915TwdB8A4qtRZS7zhTSqtwf4CZUkRERBRcrTWl1JfvmbuZwSTvvBej18KgcEFPluSHgupERETUSj0/mUJGEJwZTi02h2oxcl9ad95TvtLX0e57dofzdo3Qustee1qtnCnV/WLsRERERJ3VIi/fU8iUal2+Z4ckSYoX5XzpaOc99+O4MqWWrz+IZ7864nX8rEEp+PvsM1UzzYmIiMgTM6XCVOsOfN3PlFLaeQ9oDUqpnVvOlNJp1F8ecgYVM6WIKBTy8vKQnZ0Nk8mEiRMnYtu2bT7b19bWIjc3F/369YPRaMTw4cOxbt26IPWWiPxBvlDnK1PKKjq6tXtxRzvvyUb3TwTg/Kx1sq7F69/an05izY7jXX586j7OB0REkY2ZUmHKucTO1uPle0rkK4yqmVKiM9Dk6yqffMzBoBQRBdk777yDRYsWYdWqVZg4cSJWrlyJ6dOn4+DBg0hPT/dqb7VacfHFFyM9PR3vvvsuBgwYgGPHjiE5OTn4nSeibpNrYZoUCp3HGbTQagSIDgnmFhtiDN5tAGDdTyfx0Z4S94YwsvL6FgCtGVdq5k4ajEH6RqT3Hwit1vMxPttXhr9vOIynPz2IC09LR6xCH2L0WtWdjanrOB8QEUU+BqXClKmDHfJ8ac2UUv5gJV9hVCt03poppR6UYk0pIgqVFStWYP78+Zg3bx4AYNWqVVi7di1eeeUVPPjgg17tX3nlFVRXV2PLli3Q653vi9nZ2T4fw2KxwGKxuH82m80AAFEUIYpdu1ggiiIcDkeX70etOIb+Eenj2Gx19tugFRSfQ6JJh5omG6obWpAWp/wZ6A/v/4zqRqvqYwxINvkcH4fDgQGJOgzLjPcKSg1Ni8XHe0pwtLIRE5/YoHj/eKMOsydk4ezBKVBaYRhj0OKsrGTFHQZDKVxfM5E0H0T631+44Dj2HMfQP6J1HAPxfBmUClNyUKo7mVINFjkFvYNMKZWAlxxokutGKdG6rvJx9z0iCiar1YqdO3diyZIl7ts0Gg2mTZuGrVu3Kt7nww8/xKRJk5Cbm4sPPvgAffv2xY033ojf/e53Xl8qZcuXL8eyZcu8bj9y5Aji4+O71GeHw4Hq6mrk5+dD42NZNKnjGPpHpI9jZU0dAMBcU4XDh+1ex2O0QA2AfYcLIJhjvI432xzugNRdE/p4XXzTagRMGmTE4cOHVfvQ0RjeMS4RS79ogkVU/nzUYLHjpa8L8NLXBaqPYdQJ6J+ghwQAEiBBavPfgOTx/87HaXsbADhc/9G2vXz/gUl6/GXGANXHV+x3Q0OX2gdDpM0Hkf73Fy44jj3HMfSPaB3HQMwHDEqFKTmbqSc1peLVglIdnJuZUkQUriorKyGKIjIyMjxuz8jIwIEDBxTvc/ToUXz55Ze46aabsG7dOuTn5+Puu++GzWbD0qVLFe+zZMkSLFq0yP2z2WxGVlYWhg4disTExC71WRRF5OfnY9iwYapfesg3jqF/RPo46raYATQiq38mcnIGeh3vk1iBknobEtMykZPjvXTrUFk9gAIkmnT47VVnd6sPHY1hTg5w9bmnQzEmJUn49kgV3tx2XDVbq8zcglKzBQU16tlcPdU3MQY5OTlduo+cHRROIm0+iPS/v3DBcew5jqF/ROs4BmI+YFAqTJl0gS903tHue52pKcVMKSIKdw6HA+np6XjxxReh1Woxbtw4FBcX4+mnn1b9EmI0GmE0Gr1u12q13frgodFoun1fcuIY+kckj6NVdH4+iTXqFPufFGMAADRYRcXjpWZnoGdASmyPnn9HY+jr3BeP6oeLR/VTPS5JEvafrEdlgwWCAAgQXP/v3J25U/8NQBAAjWt9YNvzaFw7PHf1+Ufi60VJqOeDSP77Cyccx57jGPpHNI5jIJ4rg1JhSi7Q+W1+JWwKl9vOGpSMU/oqpwx3XFOqtdC50rbJ3H2PiMJVWloatFotysrKPG4vKytDZmam4n369esHvV7vMYmOGDECpaWlsFqtMBgMAe0zEfmHfKFOLkPQnlyk3NzsvbQPAE7UNgNw1o0KV4IgYGT/rmVjRivOB0REvUP0LH6MMPLOef/ZcQKL1+zx+nf9P7bCqpLpVN9i8zhHe3KmFKCcLWXrxO57Oq2cKdX1QuxERN1lMBgwbtw4bNjQWkTY4XBgw4YNmDRpkuJ9zj33XOTn58PR5v3q0KFD6NevH7+AEEUQefMXucRBe4kxzs89dc02xePFNXJQyrveFEUezgdERL0Dg1Jh6rbzhuDikRmYMryv178Eow6VDVZ8m1+peN+Ol++1Xh1SCkp1pqYUl+8RUagsWrQIL730El577TXs378fCxYsQGNjo3v3pTlz5ngUvl2wYAGqq6tx77334tChQ1i7di2eeOIJ5ObmhuopEFE3tNh9Z0olujOllINSJXKmVAqDUr0F5wMiosjH5XthakxWMl6aM17x2CMf/Ix/bT2GtT+dxIWneRfybLA4g1KJKsv39FpnXQFJAix2EYBnu87UlNIxKEVEITJr1ixUVFTgkUceQWlpKcaOHYv169e7i90WFRV57IKSlZWFTz/9FL/5zW9wxhlnYMCAAbj33nvxu9/9LlRPgYi6wdJRppTrc49qppR7+V5sAHpHocD5IPp8urcMW/dXo89x7x3PkmP1uG5clrsMChFFBgalItDlp/fDv7Yew6d7S/HE1afDoPN8Q3Yv31PJlBIEASadFs020f0Bry050OS70LnzMVlTiohCYeHChVi4cKHisY0bN3rdNmnSJHz33XcB7hURBZLFlSkl18Zsz11TqqWD5XvMlOpVOB9Ej+LaZtz95g+un2oU2xh1Gsw6e1DwOkVEPcagVAQan52K9AQjyustWPrhXvRL8izYWVFvAaC+fA8AjHqNMyhl997dTw40yXWjlDBTioiIiIKptaaU7+V7SplSVrsDZfUtAFhTiihS1TQ6d9A06gRcfeYACELrhfnvC6pwtKIRlQ3WUHWPiLqJQakIpNUIuOz0fli9pRBvbStSbZcap16wUS523qKUKeUudO5j9z1XUMqusDMgERERkb/Ju++pL99zfqxV2n2vtK4FkgQYdBr08fH5iIjCl3zhPMmoxZ9mjvbYRfH37/2EoxWNqhtBEVH4YlAqQi28aBh0GgGNVu9MJwA4Y2AS0hPUtzyWi4QqFTqX3/D1LHROREREYcAuOtyfT9QKnftavneitgmAM0tK4+PzDRGFL7vo/N6itBmTXM7EKjIoRRRpGJSKUGnxRvzhipHdvr98lVFp+V7nakq5glISg1JEREQUWG0voqlmSrmCUrVNNhRUNnoc++lEHQAu3SOKZFZ3UMr7mByUsjFTiijidCso9cc//hGLFy9GbKzn7iXNzc14+umn8cgjj/ilc6GSl5eHvLw8iKJyFlJv4M6UUli+J+++x5pSREREFA7kpXsAYOogU6rBYseFf9mo2IZBKaLIJZcNUcqUMmqZKUUUqdSLBvmwbNkyNDQ0eN3e1NSEZcuW9bhToZabm4t9+/Zh+/btoe5KwMg1pXxnSnWippSDb/xEREQUWC2u7AeDVqO6/K5PnAEXj8xAgkmn+C8j0Ygrx/QPZreJyI/k7x1Kqzncy/eYKUUUcbqVKSVJEgTB+81gz549SE1N7XGnKPCM7uV76jWllK5CyHSugJXIQudEREQUYHKmlFFp3Y6LIAh4ac74YHWJiILMape/o3gfY1CKKHJ1KSiVkpICQRAgCAKGDx/uEZgSRRENDQ246667/N5J8j859b1tOrysKzWl7Fy+R0RERAEmlxsw6pWX7hFR7+cuMaKUKeVavmfh8j2iiNOloNTKlSshSRJuvfVWLFu2DElJSe5jBoMB2dnZmDRpkt87Sf7X00wp7r5HREREwdLiKjegVuSciHo/XzWlDK4L7syUIoo8XQpKzZ07FwAwZMgQnHvuudDpuHlfpPJV6FwU1ddry5gpRUT+UlNTg48++ghz5swJdVeIKEzJmd0mZkpFPEmSUFhYiKysLOh0OlitVrz33nuwWCy47LLLkJaWFuouUpiyiT4ypbh8jyhidetyU0JCAvbv3+/++YMPPsDMmTPx0EMPwWq1+q1zFDi+Cp13rqaU85iDQSki6qGioiLMmzcv1N0gojDmXr7no6YUhb+DBw9iyJAhGDZsGEaMGIGCggJMnjwZt912GxYsWIARI0bg8OHDoe4mhSmbKJcY8T7GoBRR5OrWzH7nnXfi0KFDAICjR49i1qxZiI2NxZo1a/DAAw/4tYMUGPKVxhalTKku7b7HoBQR+WY2m33+q6+vD3UXiSjMMVOqd/jd736HMWPGYPfu3bjiiitw+eWXY+DAgaipqUF1dTUmTZqEP/7xj6HuJoWpztSUsrKmFFHE6db6u0OHDmHs2LEAgDVr1mDKlCl488038e233+KGG27AypUr/dhFCoQeZ0ppWVOKiDonOTlZccdWmdqOrkSy2iYrNhc0YH9TCTTtLphoBAGThvZBWrwxRL2jYJBrYLKmVGTbsmULPvvsM5x++ul4/PHH8cwzz+DFF1+EXq8HADz44IOYPXt2iHtJ4crmo6aUkZlSRBGrW0EpSZLgcEWqv/jiC1xxxRUAgKysLFRWVvqvdxQwrUEphULncmqstjM1pfjGT0S+JSQk4Pe//z0mTpyoePzw4cO48847g9wriiRL3tuLz/aVAShTPH7OKal4+w5utNKbuTOldMyUimQNDQ1ITU0FAMTFxSEuLg79+vVzH8/KykJZmfLfOZHdXVPK+5hey6AUUaTqVlBq/PjxePzxxzFt2jRs2rQJL7zwAgCgoKAAGRkZfu0gBYa8pbJioXMfqbEynetKtUNy1pXS+GhLRNHtrLPOAgBMmTJF8XhycjIkKUKyLhsbAa3Cl2KtFjCZPNvJRBFCU1PrfTUaICZGuW177ds2NQFqYyUIQGxs99o2NwO+LjLExXWvbUsLIHpn5Ha1bXV5NSBJGNEvEanxBuhsVmgdIupb7Pi52Izq8hrPcYyNdT5HALBYALtdvQ8xMc5xBgCrFbDZ/NPWZGp9rXSlrc3mbK/GaATkjWa60tZuB5qaPF+LbRkMgCtbBXa7c9zUtG0ris7fnRq93tm+q20dDudrzcVurkeMtQWJotXZfx9tveh0zrEAnH8TTU3db9v279lgUP+7b8/Xe0R74foe4Qf9+/dHUVERBg0aBAB46qmnkJ6e7j5eUVGBlJQUvzwW9T42H5sxuWtKcfkeUcTpVg70ypUrsWvXLixcuBC///3vMWzYMADAu+++i8mTJ/u1gxQYcqZUi4/lez5332uz1EaMlC+TRBQSN954I0xtv4y1k5mZiaVLlwaxRz3Qvz8QH+/971e/8myXnu4+pk1KwqnjxkGblOS8bcYMz7bZ2crnjI8HLrjAs+3Ikeptzz7bs+3ZZ6u3HTnSs+0FF6i3zc72bDtjhnrbNl8uATjHRa1tfLxn25tvVm337m+nI8ZmwYMzTsUbt5+D175/Ba8svAhrFl+C/X+7Fp89fLnnfdpmbS9a5LsPRUWtbX//e99t22zygiee8N12167Wts8847vt11+3tn3xRd9tP/20te0bb/hu+957rW3fe8/7tdj23xtvtLb99FPf533xxda2X3/tu+0zz7S23bXLd9snnmhtu3+/x7H/u3g09v/tWvzt9vOct/3+961ti4p8n3fRota2lZW+27bN2mxq8jruMYY33+z5GvZ1Xh/vEV7/wvE9on2fumnatGk4cOCA++cFCxYgISHB/fNnn33mvpBB1J68fE/P3feIepVuZUqdccYZ+Omnn7xuf/rpp6FVuoJMYcd3plTHNaXaLu0THRJYd5SI1MyfP9/n8YyMjMgJSlFI+ZqXiCj8rVq1yufxWbNmYe7cuUHqDUUauWyIYqaUVr00CRGFt24FpWQ7d+7EftdVw5EjR/LKRgTpTKFzX7vvtf1iwGLnRORPp59+OtatW4esrKxQd8VbSQmQmOh9e/sLMuXl7v8URRH5+fkYNmyY88JN+/fWwkL1x2vfdt8+38tt2tq+vfNtN2/2vSSvrU8+6Xzb//7X9/K9tl5/HVi9WvHQJX/bhOZ6h7tmCP7xDyAvD0VVjZi+8mvEGrTY+fDFrXdou+xoxQrgqafUH7ft0qc//Ql49NHOtX3oIeC3v1Vv2zY78N57gbvv7lzbO+4AbrlFva2xTUH3m24Crruuc22vvhpiXZ3na7EteSkcAEyfDjQ0qJ+3bdvzz/fdVl7mBwBnndX5tiNGeLRd8flBvLS5ADdPGoSHLhvp2XbQIN/n1bX5uJuW1vm2sbFebT3+ntuOA+D7vD7eI7yE43vEJ58AmZnq/fCTIUOGePwc1vMBBZ3dXejc+1hrplQn5xwiChvdCkqVl5dj1qxZ2LRpE5KTkwEAtbW1uPDCC/H222+jb9++/uwjBYCvQuedypRqc8zOoBQR+VFhYSFsvurvhFJcnGcdJF/tZKIIKTbWeZtSNnFnzidrG2zxZ9u2wRZ/tvWxbLMrbeu1RkBoaQ1KGY2A0Qi9XYNmgwk2jaA+jq62nWIweAZcQtFWr/cMuPirrU4HxMX5fi22bavr5EdErbbzr+GutNVoPNrWa41oNpigTUjwPke7tj4JPl4rnWnr6++5K3/LgWobDu8RfhTW8wEFndVHTSn5u428xI+IIke3akr9+te/RkNDA/bu3Yvq6mpUV1fj559/htlsxj333OPvPlIAmFzr7eTdbNrylRor86gpxaAUEREFkFzcVt9uV1ijayc2u0PiXNTLtbjKDRiVUiSIKCrYO1NTioXOiSJOtzKl1q9fjy+++AIjRoxw3zZy5Ejk5eXhkksu8VvnKHA6kynV/sN/WxqNAI3g3H3P3tllHERERN3gLm6r9QxIGNoEKKx2B2IMLHDYW1lcF9FMLGJJFLU6U1NKdF2k8HVxnYjCS7cuNzkcDugV0sX1ej0cDFBEBPnqslJQSr4K4aumlPO4882eV6eJiCiQ7O5MKc95qW3WjFKNROo95M8rJmZKEUUtWydqSgHcgY8o0nQrU+qiiy7Cvffei7feegv9+/cHABQXF+M3v/kNfvGLX/i1gxQYRr3zjbum0Yp3d57wOHa0shFAx7scaTUCbKLkDmIREREFgtryPZ1GgCA4azXzS0jv1sJMKaKoZ/NRU4qZs0SRq1tBqeeeew6//OUvkZ2d7d4N4/jx4xg9ejT+/e9/+7WDFBjxRuevvqrRisVr9ii2kQNXanQaDQAHHGo7t/RQi03EPzYdwZHiSiQftEEjePZnUGos5p2bDaH9DjFERNRrSJIEq8ryPUEQYNRp0GJzcBvwXq7FzqAUUbTzVVOq7UUKiygC6OQmEEQUct0KSmVlZWHXrl344osvcODAAQDAiBEjMG3aNL92jgInJz0ed1xwCg6V1SseT4k1YMbofj7PIV+lCNTue5/uLcXfvjjs+qlOsc2EIakYPSApII9PRP5x2WWX4a233kJSkvNv9cknn8Rdd93l3r21qqoK559/Pvbt2wcA+Mc//oGMjIxQdZfCTNsl4kq1Dg1aBqWiAQud9w6cD6gnWjOlvI8JggCDVgOL3cHMWaII06Wg1JdffomFCxfiu+++Q2JiIi6++GJcfPHFAIC6ujqMGjUKq1atwvnnnx+QzpL/CIKAhy4b0XFDH3QBrilV2WAFAGQnG3DZ2IEemVJvbz+OygYLapqsAXlsIvKfTz/9FBaLxf3zE088geuvv979JcRut+PgwYPu4zfeeGOwu0hhrO323u0zpQDAqNcCLXbWlOrlLMyU6hU4H1BPyEEptRIjBh2DUkSRqEtBqZUrV2L+/PlITEz0OpaUlIQ777wTK1asYFAqSrgzpQJUU6qhxQ4AGJluwv0XD4dW2/pB9NsjlahssKDZyi8hROFOarfEt/3PRL603d5bpxCUkndc4peQyJdf3oAbXvwO1Y0Wr2Py9a+OSgtQeON8QD0hr85Q21nPqNOgHp7zBhGFvy7N7Hv27MGll16qevySSy7Bzp07e9wpigyB3n2vvsUGAIgzeL9MY1xXSpttDEoREfVm9jZfLpTqiMhBCi7fi3zfHK5AZYMFDgle/wAgOVaPUzMSQttJIgoZ96YXKkEpPS9SEEWkLmVKlZWVQa9XLxqn0+lQUVHR405RZJCDUr/774/uwukyjQaYd+4QTB+V2e3zN1icmVKxCldF5fR9i42TDlG4EwTBa0MCblBAnSUv39MKgEZpxyV+Cek1KhqcGVLXjx+IxdNP9TqeaNJz+V6E43xAPSGvzlCqKQW07sDH+YAosnQpKDVgwAD8/PPPGDZsmOLxH3/8Ef36+S6OTb1H/+QYnKhpxr6TZsXjx6ubccnIjG5/2KiXg1LMlCKKaJIk4ZZbboHRaAQAtLS04K677kJcXBwAeNQXIWqvoxoiRvkiBb+ERLyKeud7waDUWKQnmELcGwoEzgfUEx3WlAqDixTl9S24/z973LVx2xuYEoNnZ5/JADtRG10KSl122WV4+OGHcemll8Jk8vyw0NzcjKVLl+KKK67wawcpfK36v3HYVlCF9uUAJAC/XbMHxbXN2HOiDmOzkrt1frmmVKzee+IxMShFFDHmzp3r8fP//d//ebWZM2dOsLpDEcbaUVAqDL6EkH/IQam+CcYQ94QChfMB9YScOeur0DkAWEJYU+rL/eX4+nCl6vH9J834+nAlLh7JXSWJZF0KSv3hD3/A//73PwwfPhwLFy7Eqac6U6sPHDiAvLw8iKKI3//+9wHpKIWf1DgDLh2tnBn3yc+l+GhPCdb+WNLtoJS7ppTClYQYV/YUC50Thb9XX3011F2gCCYv19CpXFRurSnF+SDSycv3GJTqvTgfUE/YHfJFCuXj4bB8r6bJ+f3l/Jw03HHBKR7H/vl1ATYdqsDBUjODUkRtdCkolZGRgS1btmDBggVYsmSJe8cMQRAwffp05OXlISODf2AEXH56Jj7aU4J1P5XioctGdGsJn7umlEEhU8r17aSFX0KIiHq1jgrbhsNyDfIPd6ZUPJfuEZE3e0eZUq75wBbCTKnaZueyveEZCTg/p6/Hsb0lZmw6VIEDpfWh6BpR2OpSUAoABg8ejHXr1qGmpgb5+fmQJAk5OTlISUkJRP8oQk09NR2xBi2Ka5tx4V82Khan/dVZA5F7oXJ9MqDt8j2FmlIGV1CKmVJERL2avHxPdQtw7r7XKzgckrsGS3oiM6WIyJt7PlC52B0OmVJ1rkyp5BjvzcFOzXTuHnqQQSkiD10OSslSUlJw9tln+7Mv1IuY9FpccUY//GfHCRRWNSm2WbXxiM+gVH0ndt9jTSkiot6ts1fGmSkV2aqbrBAdEgTBWR6AiKi91uXcKhcpwiEo1ewMSiXFegelTnMFpY5WNsJiF2FUW5dOFGW6HZQi6shjM0dj1tlZ7glE1mQTMe/V7ai32FXfkB0Oyb18L87n7nv8EkJE1Jt1tHxPnkNYUyqyyUv3UmMN0Kvt905EUa3TNaVCuXzPlSmVpJAplZloQqJJB3OLHfnlDRjVPynY3SMKSwxKUcAYdVqMG5zqdbskSdBpBNgdEqobreiXFOPVpskmunf187l8j5lSRES9WuvyPeXj8vI9ZkpFNu68R0Qdce++p7Z8LwwyZ2tdmVLJsd4Zn4Ig4LR+idhWUI2DpfUMShG58FIUBZ0gCEhxpeZXuepHtCfXk9JpBBgUUnRNri8hDEoRRae8vDxkZ2fDZDJh4sSJ2LZtW6fu9/bbb0MQBMycOTOwHSS/kbNtOyp0HuqaUgWVjXh35wnFfx/uKXHvKEvKGJSi7uJ8ED1sHdQYlDOlQjkf1DU5v9so1ZQCWpfwsa4UUStmSlFI9IkzoKLegupGlaCUxfnhPd6oU9y5z718j4XOiaLOO++8g0WLFmHVqlWYOHEiVq5cienTp+PgwYNIT09XvV9hYSEWL16M888/P4i9pZ6Sv4So1hAJg0LnkiThhhe3osxsUW0zZ9Jg/PGq0UHsVWSpaJB33mNQijqP80F0cV+kUJkPwqHQeWumlHJQSi52/vm+MkDhaaTGGjB74iAkmpTv3xk20YGaRiskleNGrXPeIgoXDEpRSPSJd2VKNSp/gDe7MqUSTMovURY6J4peK1aswPz58zFv3jwAwKpVq7B27Vq88sorePDBBxXvI4oibrrpJixbtgxff/01amtrg9hj6gl3UEo1U0quKRW6LyEtNoc7IHV+TprHVfyaJhv2HK/FrqKaUHUvIjBTirqD80H0kCQJNoe8+55yG3k+CFVNKYtdRJPrgnlyjPKGDaNdS/aOVjbiH5uOKrZ5f3cJ/vF/4xSLpR+vbsI/Nh/FnuO1ivcVHRLKzC2wO3wHnTQCoBEKFI/Fm3QYlBoLk0oh9hiDFqf0jVOsmwU4s8SuHZ+FeCNDDdQ5fKVQSKTGOT90drR8T+3NTM6U4vI9ouhitVqxc+dOLFmyxH2bRqPBtGnTsHXrVtX7/fGPf0R6ejpuu+02fP311x0+jsVigcXSGjQ3m80AnF9mRLFr7zuiKMLhcHT5fuRkcb3PawUojqFrOoDFZg/ZGFc3tABwLil5de44jwzfY1VNuGjFZhwqa4DFaoMuhEW8w/m1WG52jmGfOH1Y9k8WzmMYSOH4fCNtPojW146/2EWHu96sBlJYzgc1roxPQQBi9YJiH0b1i8djvxypuDu5BAkf7jmJ/SfNuODpr3rUF2fQyTt6J8EZuHJIgEMlW6q2yYbapjqf5990qMLn8X9sPoqbzxmkuHFFjF6LX47ph7gID1pF6990IJ5vZL8SKGL1cdWUUl++5wpKdZAp1cLd94iiSmVlJURRREZGhsftGRkZOHDggOJ9vvnmG7z88svYvXt3px9n+fLlWLZsmdftR44cQXx8fJf67HA4UF1djfz8fGg0LOXYVcUnnV8AJdGmOIbmmloAQFWNGYcPHw529wAABTXOLyLxBgH5+fkexxySBJNOQIvdgU279mNQsvLV82AI59diUbkzk0xsrMHhw/YQ90ZdOI9hIDU0NIS6C14ibT6I1teOv7TNhjXX1SqOY31dLQCgvKomJPPBsVrn95p4gwZHjuSrtjs7FTg7VTkL6fzMTDz2ZSmO1ih/R9IIwPmD4zHj1AQYFQI+ggD0idWhT6xWMSgFAC02O46XVSM5OdlrDCUJMFtElDXYIapkW9VbHTheZ4XFrnx8Z3ETTta14KlPDykeB4Afjxbj1nF9VI9Hgmj9mw7EfMCgFIVEh0GpjjKlDFy+R0Qdq6+vx80334yXXnoJaWlpnb7fkiVLsGjRIvfPZrMZWVlZGDp0KBITE7vUB1EUkZ+fj2HDhkGrVf4QSuq+qzoGoAIxRoPiGA6oKQJQBUNMLHJyckLSx+qCagAn0Cc+RrEPI/pV4YfjdWgxpSInp1/wO+gSzq/FhrWlAIDRwwYjZ2j4flEJ5zEMJDk7KJKFej6I1teOv9S32AE4l5ulp6UojmPmiSMAahAblxiS+aCusAbAcaTGm7r9+DkAPjtzhOryO40gqBZ67yxRFGHQBu612GS14+VvCnG0stHrWE2jFV/nV2HLCQuemDVMsXZwpIjWv+lAzAdREZS6+uqrsXHjRvziF7/Au+++G+ruEIBUV02pSpXle2bXLkVqNaVY6JwoOqWlpUGr1aKsrMzj9rKyMmRmZnq1P3LkCAoLC3HllVe6b3O4alLodDocPHgQQ4cO9bqf0WiE0ehd20ar1Xbrg4dGo+n2faOdfHFcr1UeQ5PeOU9YRSlk42tucdUQidUr9uG0fkn44XgdDpU14pdjQ/saCOVr8URNE57feERx6f2JmmYAQGZSTNj/nUTj33M4PtdInA+i8bXjLxJa3zf0rjH0mg9cF61tjtDMB2aLPBcYevz4gf6SHsjXYkKMFvddfKrisWariLMe+xwnapqxv7QRpw9M8vvjB1M0/k0H4rlGRVDq3nvvxa233orXXnst1F0hl9ZMKeVC5+7leyqZUu7le3YRkiRFdJSdiDrPYDBg3Lhx2LBhg3sbb4fDgQ0bNmDhwoVe7U877TT89NNPHrf94Q9/QH19PZ555hlkZWUFo9vUA/LVYrVC50bXfBDK3ZbMrt2W1Iq+jujn3G3pQGnkZ5v0xJ/W7scnP5eqHjdoNchMMgWxRxTJOB9EF3nTC0GAaqaQQRva3fdqm5wX25NV5gJyrna58LS+WPdTKdb9fDLig1LkH1ERlJo6dSo2btwY6m5QG31cWz53d/meybUFuCQ515jLQSoi6v0WLVqEuXPnYvz48ZgwYQJWrlyJxsZG9+5Lc+bMwYABA7B8+XKYTCaMHj3a4/7JyckA4HU7hSeb68uF2tu8/CXEYg9d5mxts+uLSKxyvajTMp1LfPafrA9an8JNcW0zPt3rDEjdNy0HsQbvX+jpA5KR0INt0Cn6cD6IHjbXBQq9j6VrBl1od2Otc12gSFbYNY9azRjdD+t+KsX7PxQjVmFy1+s0uGpsf/RLiglB7ygUQh6U2rx5M55++mns3LkTJ0+exHvvvee+2iHLy8vD008/jdLSUowZMwbPPvssJkyYEJoOk1+kujKlVHffc2VKOZfveU8sbYNQLTaRQSmiKDJr1ixUVFTgkUceQWlpKcaOHYv169e7i90WFRVFVcHJ3k6+Oq52ZdzoukgRqi3AAedORYB6ptSpmc5MqeLaZnx5oMy9bblMIwBnDkpx10vsjV7fegwOCZg8tA/umzY81N2hXoLzQfSwi/IFCvXfp0HnPGYL0XwgzwXMlPLtotPSYdJrcLKuBX/9XLkY+oGTZqy84cwg94xCJeRBqcbGRowZMwa33norrrnmGq/j77zzDhYtWoRVq1Zh4sSJWLlyJaZPn46DBw8iPT0dADB27FjY7d47tXz22Wfo379/wJ8DdZ28fK/eYofFLsKo8/wgXu+RKeUduNJrNdBrBdhECc02EcmB7jARhZWFCxcqLs8A0GFm7OrVq/3fIQqYjq6Oy7sPWUK4G2ttB1fHk2L0GJAcg+LaZty6eodim0GpsXj9tgkY3CdO8fjPxXV474dixXpMEoDKegvyyxtUMwR0WsF5QchmQezXtV7L3jUaAX3jjUiM0bm3XZckCRKcWckSJNf/w3Xc9bPrmOgASs3NKDNbIClsMy7XjLplcrZi/4i6i/NBdLCJrqXcnQhKhWz5nitrNkkla5ac4ow6PDf7LGw4UO51rKS2GZsOVaCwqikEPaNQCXlQasaMGZgxY4bq8RUrVmD+/PnuNNxVq1Zh7dq1eOWVV/Dggw8CQJe2dfXFYrHAYmmtcSRXlhdFEaLYtWUBoijC4XB0+X7RIk6vgU4jwO6QUGlu8aohIRc6jzVoVMfRpNfCJtrR2GKDGM83fzV8LfpHtI5jtD1fCj/y8j31mlKhz5Sq66CmFADc84theG3LMTgUAjbl9RYUVTfhqrxvcUqad1DKYndgb0nP61Edc3/Ib+7xubpjWHo8fjEiIySPTUSRTc5+UpsLgDY1pZgpFfamjczAtJHe88EPRTXYdKgCFfXKdYepdwp5UMoXq9WKnTt3YsmSJe7bNBoNpk2bhq1bt/r98ZYvX45ly5Z53X7kyBHEx8d36VwOhwPV1dXIz89n2rCKBKMGNc0iftifj2F9PHc1qax11t2or65AtdWiOI46wfnB/tCRAthrvHdFISe+Fv0jWsexoaEh1F2gKNe6fE/5uLwULpSZUnVNHdcRmXX2IMw6e5DisfL6Fsx9ZTv2nzRjV1GtYhuNAFx+Rn8M7aucSZVg0uPUjATVXWstdgcqzM0oKi5BZmam1/uY1e5Aeb0FjRY7BAEQILj+H4AgQHD+n8ftggB3xpVGEJCeYES/JBM0Kl8aR2Qm9ngrcyKKTnZXppRep/4ZzBjiTCnWlOq5jERnokJ5fQscDkl1PqHeJayDUpWVlRBF0b0uXJaRkYEDBw50+jzTpk3Dnj170NjYiIEDB2LNmjWYNGmSV7slS5Zg0aJF7p/NZjOysrIwdOhQJCYmdqnvoigiPz8fw4YNi6otIrsiPbEMNc0NiO+TiZycNI9jdqEMgAXDs7OQ6qhWHMeEmBLUNDejb78ByBmUEsSeRxa+Fv0jWsdRzhglCpUOl++FQaaUu9B5TPeydtMTTHjv7sn47miV6pep0zITMahPbLf7CDjfxw4b65GT0z+q3seIKPLZHK6aUj4LnYd69z0GpXqqb4Iz0cAmSqhpsro3x6LeLayDUv7yxRdfdKqd0WiE0ej9wtdqtd368KbRaLp932jQJ94IlDWgttnuNUZyofPEWAM0TcrjGKN3vnytIjjGHeBr0T+icRyj6blSeOpo+Z579z2FWkvB4i503oMvIia9FlNPTfdXl4iIehW7u6ZUJ4JSPi5SWOwiDpU2wFkxz5NGEDA8I8F9nq5y15Tq5gUKctYNTos3oLLBijKzhUGpKBHWQam0tDRotVqUlZV53F5WVobMzMwQ9Yr8RX6T2X281qumlJz+Gm/Uwa5S587k2qVIqegrERH1Dh3VEQmHTKm6DnbfIyKinmmdC3wUOtd2nCl1+2s78PXhStXjl5/eD3k3naV6vLLBgle/LUCLwpLxcrOzDhLngp7pm2ByBqXqWzASXVutRJEprINSBoMB48aNw4YNGzBz5kwAzrouGzZsUN1lgyKHvAPf6i2FWL2lULFNgkmHGpX7m1xXMZoZlCIi6rXk5XtqV8flLyE2UQpJ/Qm76EC9K7uXxW2JiAJDDkoZOrH7ntoupA0WO77Ndwak+ieZvHYhLa5txvq9pSg3tyA90aR0Cjyxdj/+90Oxah+0rp1MqfsyEo3YfxIoN7eEuisUJCEPSjU0NCA/P9/9c0FBAXbv3o3U1FQMGjQIixYtwty5czF+/HhMmDABK1euRGNjo3s3Popc15w1ALuKatDo+jDf3oQhfZAWb1QNSsW4MqWarQxKERH1Vq3L95SPG/WtS0ytogMmTXCXnJpbWucwXh0nIgqMLi3fsyt/N9h1rAYOCRiYEoNvfneR1/Frnv8Wu4pq8f7uYtxxwVCv4+XmFnz0YwkAYO6kwYg1en+VHpuV3KOl3ARkJDgDgmVm7sAXLUIelNqxYwcuvPBC989yofG5c+di9erVmDVrFioqKvDII4+gtLQUY8eOxfr1672Kn/tTXl4e8vLyuBV6gJ0xMBkfLjzPZxtfv4MYPZfvERH1dvLVcbXitm2vmltsDpj0wQ1K1TY5a4gkGHXQ+biCT0RE3Wd3FTr3GZTS+l7Ovb2wGgAwITtV8fi147Kwq6gW/91ZjPnnn+KVSfXv74tgEyWMG5yCZVeN7vJzoM7JSHRmmpXXM1MqWoQ8KDV16lRIknehubYWLlwY1OV6ubm5yM3NhdlsRlJSUtAel7qmNSgVujoiREQUWDbX1XGtSlBKrxUgCIAkARZRBBDcK9S1rhqIicySIiIKGKucKeWrplQHu+/JQanxKkGpy8/oh0c/2ouDZfWYvnIzNO2CUoVVjQCAW88d0rXOU5fISyeZKRU9Qh6UIuoueckGa0oREfVeHWVKCYIAg1YDi90BSwguUsgbc3ALcCKiwLG7a0p1nCnlkJzt22avWu0O/FBUCwCYMCRF8f5JMXr8ckx/vLvzBA6VNSi2ye4Ti+mjArdih4AMV1CKNaWiB4NSFLFiGJQiIur1Otp9DwCMOmdQKhQ78Mk77zEoRUQUOK01pTrOlAKA9XtLPZZ3H69phsXuQEqsHkP7xque4/GZo3HduIGwO5RX8ozsl8il2gEmL99jplT0YFCKIlaMwbX7HgudExH1Wq3L99TbGHRaAPaQZErJNaWSYwxBf2wiomhh7eQFCnk598I3f1BsMz471atWVFsmvRYTT+nTs85Sj8iZUhUNFogOSXX5PvUeDEpRxJIzpSwqO2wQEVHkcy/f87Fkw6jzXdw2kOSaUtxtiYgocOzuuUD9CoVOq8H9Fw/HlwfKFY8bdVosmOq9qx6Flz5xBmgEQHRIqGq0IN21Gx/1XgxKUcSSd1hiphQRUe/V2eV7AGBRWc5d2WDB3z4/hPoWu+LxYenx+PVFw1SvnlvtDtz17504WFrvdUyuKZXEQudERAEjL6fzdYECABZelIOFF+UEo0sUIDqtBmnxRpTXW/DermL0T47xOK4RBJxzSir6xBtD1EPyNwalKGKZWFOKiKjXs7l3XPJR3LaDTKl/bT2GN74v8vk4Zw1KwXk5aYrHvjxQrnrlXTaqf6LP40RE1H22TtSUot4jM8mE8noLln9yQPH4Oaek4u07JgW5VxQoDEopyMvLQ15eHkSRwY5w1lroPPjLNYiIKDjs7kwp9TatmVIq24AXOLcBv+bMARg9IMnj2FcHy/H14Ur8b9cJ1aDUR3tKAADXjx+ImyYO9jqeGKPHkLQ430+EiIi6rTNZs9R73HNRDlZvKYTYruB8g8WOn4rrcLy6OUQ9o0BgUEpBbm4ucnNzYTabkZSU1PEdKCRiDM6gVItKppQkSfj3d8ewvbBG8bhJr8HCC3MwqE9swPpIREQ9Y+1EppRRp3W19Q5K2UQHfjjunAcWTB2KnIwEj+NjByXj68OV+OTnUjw20444o+dHo/oWG77YXwYAmDMp2yuoRUREgSdfoDAwUyoqTBuZgWkjM7xuP1BqxqUrv+ZKmV6GQSmKWCa9c1JSC0o9v/EInv70oM9zWOwOPHPDmX7vGxER+Udnro7Ly/eUNr7YW2JGi82BZJVtwM/MSsaQtDgUVDZi9ZZCTB7quevSliNVsNgdGNo3jkv0iIhCxOaQl+8xUyqaxeqd4QvWFO5dGJSiiCXXlMovb8BN//zO45jokPDdUedyjVsmZyMr1TMbqqrBguc3HsGG/eVosYnucxERUXjpSqFzq907U2pHoXMuGD84BRqFcwiCgGvOHIC/fn7I54WMX44Z4HMbcSIiChz3Um5mSkU1eaVMs02EwyEpzusUeRiUoog1MNkZaGqyivg2v0qxza3nDsEjV470ut3hkPC/XcUoNbfg68OVuFghPZSIiELPLna841JrppR3UGq7HJTKTlW9/+yJg7DxUAXK61sUj6fFGzF7Ylan+0xERP7VmU0vqPeLNbQmErTYRcQaGM7oDfhbpIg1qE8s3s89F8eqGhWP900wYtIpfRSPaTQCZpyeiVe/LcQnP51kUIqIKAxJkuSuE9WZQudvfl+ErUc8L1J8c7gSgDNTSk1avBH/XTC5h70lIqJAsXnUlJJ8N6Zeq+3qliYrg1K9BX+LFNHGZiVjbFZyt+57+en9nEGpn0tR1bjN67heK2D++adgokpgi4iIAsveZtcdX1fHMxJNAIADpfU4UFrvdTzBpGOBciKiCCZnzTprSjEoFa20GgFGnQYWu4N1pXoRBqUoap01KAUDU2JwoqYZmw5VKLaxihKDUkREISJ/CQF8B6VyLxqGYenxaFFYvgcAZw1KZu1AIqIIZnO0rSml/F5P0SHWoHUGpbgDX6/BoBRFLY1GwFvzz8G2gmqvYwfL6vHi5qOoarCEoGdERATAvXQP8B2USjTpcd141nwiIuqt5JpSetaUinqxBh1qmmxoYqZUr8GglIK8vDzk5eVBFPlC7+2yUmO9duYDgB+KavDi5qOobbKFoFdERAS01hABfNeUIiKi3k3efU/P3feinknvfA00We0h7gn5C/+qFeTm5mLfvn3Yvn17qLtCIZISawAA1DRZQ9wTIqLoZW+z25Ig8Oo4EVG0snnUlKJoJhc3b+HyvV6DQSkiBXJQqskqwmLnGx4RUSjYeGWciIgA2N01pRiUinYxBmeNSC7f6z34KY9IQYJJB3nJOpfwERGFhlxTil9CiIiim/sihYZfX6NdLINSvQ7/qokUaDQCkl3ZUtWNXMJHRBQK8vI9ZkoREUU3G+cDcolx7abL5Xu9BwudE6lIjtWjutHKulJERCEiXxk3MFOKiCgqlNa1oFJh92tzs3PlAjNnqbcs32u02PFNfqX7Alx72WmxGNkvMSpqajIoRaQiNdaAo2jk8j0iohBpXb7HK+NERL3d3pI6XPHsN5CUv6MDYKYU9Z7le0s/3It3d57w2WZQaizS4g0QBAECADk+JUCA638QBOfPguD53wAU7ud526yzB+HikRmBeYJdwKAUkYpk7sBHRBRSNrtc6Lz3XyUkIop2PxfXQZIAo07j3nSorf7JJowblIyyE7XB7xyFDXn3vWarXbWNJEk4XN6Aumbl5IKslFhkJpkC0r/OqG+x4aM9JQCAswYle118czgk/FRch6LqJhRVNwWsH5OGpgXs3F3BoBSRipRYPQAWOiciChW7gzVEiIjChcMh4Vh1ExwKqUwaQcDg1FhoNN2/iFDd6PzMfcUZ/fHX68cothFFEWXdfgTqDeSaUs0+akqt/7kUC97YpXrcpNfg6wcuQt8Eo9/71xnrfjoJi92BYenx+O+CyYpL9BosduworIbF7nBlD0qQJED+63P+d+ttkuvv0uN2j/YSXKdxHz9zUErAn2tnMChFpCIlzpUpxULnREQhIS/fY1CKiCj0Fr+7B//bVax6/JqzBmDF9WO7ff7qRmctqdQ4fbfPQb1fZ2pK7TtpBgAkmnRIi/cMPJXUNaPF5sCuohpMH5UZuI768N+dzr+ja84aoFozKt6ow9RT04PZrZBhUEpBXl4e8vLyIIqRvU6VeibZlSlVw0wpIqKQ4PI9IqLwsbuoFgAQZ9BC2yYjSnRIaLSK+MF1vLvkTKnUuNBkr1BkkGtKNfsISsm7p9963hDcN224x7HfrtmDNTtPYG9xXUCDUnlf5ePVbwvgUKiRVt1ohSAAV585IGCPH0kYlFKQm5uL3NxcmM1mJCUlhbo7FCLyWvZa1pQiIgoJLt8jIgof5hZn0Oi/d0/GaZmJ7tsPldXjkr9t7nEdVvn+zJQiX+Tle74ypVpfS961yUYPSMKanSfwc4k5MB2Ec6nri5uPqta0AoDpIzPRLykmYH2IJAxKEamQa0pVMyhFRBQSNi7fIyIKC5Ikub9gJ5o8g0bJMc6f65ptcDikbteVqnJltygVOSeSuQud+6gpVe3jtTR6gDOg+nNxXQB653SovB51zTbE6LV4P/dctP+TEAQB2X1iA/b4kYaf8ohUJLszpbh8jyjc5OXlITs7GyaTCRMnTsS2bdtU27700ks4//zzkZKSgpSUFEybNs1newofVtfyPV0PCucSUe/G+SA4WmwO2ERn9mpijGdQKsl1IVeSWrOpukOu49onnkEpUhdjcIYwOrN8TylTakS/RAgCUF5vQbm5JSB93F5YAwA4a3AyTs1MQE6G579h6fFeO+5FM2ZKEamQ38R6mopMRP71zjvvYNGiRVi1ahUmTpyIlStXYvr06Th48CDS070LQm7cuBGzZ8/G5MmTYTKZ8Oc//xmXXHIJ9u7diwEDuJY/HCxeswf/23XC63a5DoOBH9yISAHng+CRg00awVlTqi2jTotYgxZNVhG1TTb3hd2u8pXdQiSL0TtDGE1Wu2obuT6Z0msp1qDD0L7xyC9vwN4SM9ITTX7v4/aCagDA2dmpfj93b8SgFJEKudB5XbMNokPyKOhIRKGzYsUKzJ8/H/PmzQMArFq1CmvXrsUrr7yCBx980Kv9G2+84fHzP//5T/z3v//Fhg0bMGfOnKD0mdRJkoQPdhcrFgKVjctOAaD+4ZOIolNI54PGRkCr9b5dqwVMJs92ACCKEJqaPO+n0QAxMd5tlbRv29QE1z7x3gQBiI3tXtvmZsDh8GpWX1mPGGsLjMkJrbuFtWnbTyeipKEFdZU1gNzNuLjWE7S0AD42kbIYTWiwON/n+2gl9bEQRc/nYrEAdh/zQ2ys8zl2pm1MjHOcAcBqBWw+sr660tZkav2dd6WtzeZsr8ZoBHS6rre1271fi20ZDIBe724Li0X9vG3biqLz96xGr3e272pbh8P5WnOJt7cgxtoCqcH1OmnXVmpqQkutGTEOCX1g83wt6XSA0YjR/RORX1aPA/kncWFWm9dpW662AJyvuaYmz+Nt/6YNBvffvSRJ+OlQMWKsFpyTbvR+Lau9RygJ1/cIP2NQikhFcozzzU2SAHOzDSkK6Z9EFFxWqxU7d+7EkiVL3LdpNBpMmzYNW7du7dQ5mpqaYLPZkJqqfvXKYrHA0uZDmNnsLIYpimKXd2YVRREOh4M7uqowN9vcS0I2L54Cg84zK0qnFZBo1CI/P59j2EN8LfZctI5hOD7fUM8H6N9fsb00YwYcH33U2qf0dAhNTdACOLV92wsugOPLL1vbZmdDqKxUPu/48XB8911r25EjIRw7ptx25Eg4fvyxte3ZZ0PYt0+57eDBcBw50tr2ggsg7Njh1W4YgG9iEnH1o++5Xw+aSy+FsHkzAGCD3PBvrvPGxsJhbi0krbnmGgiffKLYBwCoqm4AAGg1AhLmzwP+91/FdloA0vbt7j4Id9wBzb/+pXpe8eRJoG9fZ9vf/AaaF15Qb5ufD2RnO9suWQLNihXqbffsAUaNcrZ9/HFoHntMve3WrcDZZzvb/u1v0CgETN1tv/gCmDrV2XbVKmjuuUe97QcfAJdf7mz7+uvQ3Habetu33wauvRYA4Pjf/3DqjTeqtnW8/DKkuXOdP6xbB+1VV6m3/fvfId19t/OHjRuhnTZNve2TT0JavNj5w/bt0E6apN724YchLV3q/GHvXmjHjHEfOx3AfvmHRwHHokWQnnrK+XNhIbTDhuFn+fjf2p13wQJIzz6Lkf0SsHmLGQuuHKvah+bZN8Hw+mvOHxoboW23AVrbv2nrzKvR+PqbAICT5hZ89eiVio8PqL9HKAnH9whpxgzFdj3BoBSRCoNOg3ijDg0WO2qarAxKEYWByspKiKKIjIwMj9szMjJw4MCBTp3jd7/7Hfr3749pPj44LV++HMuWLfO6/ciRI4iPj+9Snx0OB6qrq5Gfnw+NhsvQ2jtR57yyG6sX0FR5Akofy8o5hn7B12LPResYNjQ0hLoLXkI9H6hpbGzEicOH3T8PlySo5do3NzejqE3bYaKo+uWspaUFx9q0HWqzQW2POqvFgoI2bYdYLDCqtLXbbDjSpu3glhb42g/MIIg47Go/qLkZaqWaJUlytwOAgY2N8DV77t6fDwBIMGjQ0NiARB9ta2pq3H+D/cxm+Nor/ejRoxBrawEAGbW1SPHRtrCwEDZXFlPf2lr08dH22LFjsLqyc9Kqq5Hmo+3x48fRkpwMAEitrIT3wtJWxcXFaHKNW3J5OTJ9tC0pKUGjq21SWRn6+WhbevIk6l1t40pLkeWjbVlZGerktiUlPtuWl5ej1tU2trgYg3y0raysRLWrren4cWT7aFtdXY1KV1vDsWM4xUfbmtpaVLja6ouLMdRH27raWpQdPowsg0X171J2tKwWWtd5haYmr6ByW5/vL0fu4+7QLAp9tI3094gUXxlu3SRIklqeFpnNZiQlJaGurg6Jib7eGr2JovMNOycnB1qltEjqlFCP43l//hInaprx3wWTMW6wr2ksfIV6DHuLaB3HnrwPBkJJSQkGDBiALVu2YFKbK2wPPPAANm3ahO+//97n/Z988kk89dRT2LhxI8444wzVdkpXxrOyslBdXd2t+SA/Px/Dhg2LqtdOZ+0orMGsl77HoNRYfHX/BYptOIb+wXHsuWgdQ7PZjNTU1LCZC4AwmA+OH1ceC5WlOaIo4siRIxg6dGjraydcl+YoLN9b+9NJ/O6/P2Psaf3x79smeLW9f82P+HRvGR68dDj+75zBzuNdWL73bWkL5ryyHTnp8Vh/53jVtqIoIr+kBMPkz2NcvtfltqLFgiP79nm+FtsK8+V7VY1WTHl6EwBgzyPToDUaPNruOXQSN728HQNSTPj03vM9z9tmSd7J2mZUldd4PfQb3x/HRz+exE3nDsGSma4MrXbL9yrrLZj6183unx0aDSy61gSGBLsFD112Gq4fP9D7uUX48j1zWRlSBwzw63zATCkiH1JiDThR04zbXtsOY7slJQIEXDd+IO6/xFfcnIj8KS0tDVqtFmVlZR63l5WVITPT1/VE4C9/+QuefPJJfPHFFz6/gACA0WiE0eh9zUir1Xbri6hGo+n2fXu7GtcW430TjD7Hh2PoHxzHnovGMQzH5xry+SAxEdrOfCGT24gihPh45/3UxrMrX/ASEgLTViUbuE5TjWaDCUkxhtb+t2kbl5qEZkMdqgSj8rjEqdTtcaktcGbjpcYZoPXVVhShKStr/RuMVcvVUtCVtjExnl/wQ9G2ffDCX22Nxo5fi23Pq/D6V21r6OTKkq621bfm/CSYRDQbnM/VGhOHeKPOo22NxohmgwmxKUk+/0YH9onHwD7er/eDDcB/DtTgQI3Nc3zanOtAaQWaDSYMSNRjw+ILvcZRADq/u15X/u7D4D1C28UVA50RPXnHRN1wxkBnQnBtkw1lZovHv1JzC17YeAS13J2PKGgMBgPGjRuHDRtaU6QdDgc2bNjgcaW8vaeeegqPPfYY1q9fj/Hjxwejq71KXZMNJ2qaFP/52pK5MyobXFuAc4k0EXUB54PgMrc4M4wSY5RzGuRdzuq6+bm4xrXzXp94zgXkm0nfGsJQ+gzS010cczKcQZdDZfWqbfaVOOulDUs1Qq/VeP3rdECKADBTisinx64ajTmTsmFXSGP+zTu7caisAZ/tK8P1432ttiYif1q0aBHmzp2L8ePHY8KECVi5ciUaGxvduy/NmTMHAwYMwPLlywEAf/7zn/HII4/gzTffRHZ2NkpLSwEA8fHxXa4PFY22F1Zj9ovfwa6yPV5SjB5fLZ6K1G4GlarkoFR8J6/EEhG5cD4IHrMrqzXRpFylRt61uqbJx9I0H3oaSKDoIQgCYvRaNNtEn0Gp7n4uyclwZg2V11tQ22RFssJrcv9JZ1BqSCpfr/7AoJSCvLw85OXlheVOIxRcGo2AUzOV0xmvOKM/Vnx+COt+OsmgFFEQzZo1CxUVFXjkkUdQWlqKsWPHYv369e5it0VFRR4FiF944QVYrVZc69p1RrZ06VI8+uijwex6RNpRWAO7Q4JGAPTtrvxZ7A7UNduw/6QZ5w7zVeZVXVWjs1ZFGq+OE1EXcT4IHnOLKygVoxaUcr6H1zb3LCjV3UACRZdYgzMo1WTzrhFW3dSzAGe8UYcByTEorm3GobIGTBjivTvnPldQaiiDUn7BoJSC3Nxc5Obmugv8Eim57PR+WPH5IXxzuBJ1TTYkxartb0BE/rZw4UIsXLhQ8djGjRs9fi4sLAx8h3qxqgZn0Oj280/BQ5eN8Dg2+8XvsPVoFSrqfRRB7fD8XL5HRN3H+SA4zM2u5Xsm5a+Pya5gVXfLWsiBBAalqDNiDFqgEWhSyJSqcQc4u//d7NTMBBTXNuNgWb1XUKrFJuJohbMG2impzPL2BwaliLppWHo8Ts1IwMGyeox97DPFrTzPHZaGf906AYLQ0aajREThydfV6/RE54ex8vrubw9c6Qp6cfkeEVH4kjOl1C7CpsTJQaluZko1MChFnRdrcBYWb1Fcvud8Dab04LWUkxGPLw+U47BCXalDZfVwSM7XampM+G0CEYkYlCLqgZsnDcYf3v8ZkgQoVVv5+nAlyswWZCZ1cjcMIqIwU9monsmUnuAKSpl7kCnF4rZEREFhEx2oUclkitFrkaBSLwrouKZUUozzPVzt/B2pYaYUdUGMwRnGUMyUaup5BvaprrpSO4/VYPOhCo9j3+ZXAgBGZCYw8cBPGJQi6oH/O2cwrjyjPywK9ceufWEriqqbcLSygUGpCGC1O9BiV64jF6PXcqtSilrVjXImk1JQyvneVt6j5XtyTSlmShERBUqLTcQv/roJxbXNise1GgH/+L9xmDYyQ/F4XbPvmlIprgyq+hY77KJDcfexY1WNeHztfjRZvesAHa1sdJ2HQSnqWIxrB74mm/ryvZ68loa7glJ7S8yY88o2xTan9VOuO0xdx6AUUQ8505i9J+ihfeNQVN2EwsomTB4a/H5R5x2paMDM575FvcX7QxLgvGq3duHkIPeKKDy01nzyDhr1dPmeXXS4d2piTSkiosDJL29wB6TaJ3dIEiA6JGw4UKYalDK3yDWl1DKlWm+va7YpLsletekIPt9XptpHg06DgSkxPp8HEQDEujKlmhUCnP6oTzayXyKuHTcQ+0rMisfjTTrMGj8QjtqT3X4MasWgFFGAZKfFAQcrUFDZEOquUAd2HatRDUgBzpo6e0vMGMhl4xRlJElyL69T+nDX17V8r7uFzuUPjhoBilsuExGRf5ysc148OGNgEj5ceJ7HsY9/LMHCN3/AvpPe9XMA51zgXr4Xo/z1UafVIMGkQ32LHbUKQSnRIeGzvc6A1KKLh2Nwn1ivcwzPSOBcQJ0S46op9dWBCtS3eH6Gl7P6elJTSqMR8JfrxvhsI4oiDtd2+yGoDQaliALklLQ4AEBBZVOIe0IdaXAFpGaMzsTKG8Z6HJvz8jZ8X1CNBqsI8OIdRZkGix1WuwOA2vI9OVOqe0GpqjaFbbUa1mUgIgqU0jpnllRmondJiRH9EgEAB0vNEB2S1/txs02E3eGsnqqWKQU4l0vVt9gVd+DbUViNqkYrkmL0WDB1KPQKy/uIOkvOzFu/txTr95Z6HddrBfeOkBT+GJQiCpBsd1CKmVLhrtEVlEow6WDUeaZDJbi2Pm602BmUoqgj77wXa9C6U+Xb6uuqKVXfYkeLTYRJ37V0Ql9LA4mIyH/kTKl+CnVOs/vEwaTXoMXmQGFVI4b2jfc4bm52fk7SagT3rmdKkmP1KKpW3oHvU1eW1C9GpDMgRT12+3lDIIqSaj3YKcP7KtY1o/DEoBRRgGT3cQaliqqbFK86UfhosDgntDij91uifFujj+V9RL1VZQdbdCeadDDqNLDYHSg3WzBIYTmGL1U+iqgTEZH/lLqCUplJ3lfYtBoBp2YkYM+JOuw/afYOSrXIO+/pfO42Ji+9+8fmo/jkZ8/slS8PlAMALh2V2f0nQeRySt94/PnaM0LdDfITBqWIAqR/cgwMOg2sdgeKa5q7/GWNgsedKeUzKKV8JYaoN5MzpZQK1gKAIAhITzTieHUzKhpaVN/nJEmCa+WHB7kWldr5iYjIP0pcy/f6JyvvCD2iXyL2nKjDgZP1uKLdd31zBzvvyeQi5dsKqrGtoNrreIJRhwuG9+1q14mol2NQiihAtBoBg1Njcbi8AQVVjQxKhTE5KKWUKRXvuq3BagfASucUXaoaXEEjH8VC0xNMOF7djHKzcl2pFpuIa57fgn0nlXew6ej8RETUc+5MKYWaUkBrXan9Cu/VrZlSvoNSiy4ejmF942EVHYrHJw5J7fIybyLq/RiUIgqg7LQ4Z1CqogFTeGUobDX4CErFGdou3+MHKYou8s57voJGfeN9FzvfeLDCZ0BKpxEweWifHvSSiIh8kSSpTU0p5QKZclBqb4kZ+eWeu/AdLnPWR1XbeU+WFm/ErecN6Wl3iSjKMChFFEDyDnx//zIfb24r8jpu1GnRN8GIGJWrRnqtgH7JMUg06SEIgABAXsovQEDbZf3yGn/PNs4PIhUVdUivOgatRiM3huC+n/Ncrf/tebtOK8Co08Kk10Cv1aB9KYGkGD1G9EuM6KKVjVZnUCpecfme83fTZOXyPYo+7t3xfNR8Sk+Ug1Itisc/+rEEAHDL5GzcNy3H67hBp1Esok5ERP5R22SDxbWTakaS8nLp0/olAABKzS2YtmKzYpuOMqWIiLqDnwIV5OXlIS8vD6LIL6HUM2cNTgHgrMsi12YJncqAndmo07i3Zm2vT7wR//i/cWG9fJGFzqk3+3BPCZ7/Kh+iUlEnADPPHIDcC4cpHqt2FSJP87E7XnqC81iFQqZUo8WODfudOy796qyB7iK4REQUPHI9qbR4g9cuw7JEkx6zJ2RhfbsC5TKDToOrxvYPWB+JKHoxKKUgNzcXubm5MJvNSEpKCnV3KIJdMjIDa+85D3UKW+MCQLNNRHm9BVa78tr7FpuIktpmNFpFSBIgwfWlUoL8X5Akqc1/e98uSRLq6+sRHx8PQRCcbdynkdr8t3y75HEum+iAxe6AxSbCKnp/qT1Z14zaJpvq0p3yegsWr9mDt+44J2x3IGytKeX9QU0OSjWw0DlFqGc3HMbh8gbV43/7/BCuGz8Q6QnedUbk5Xtqu+8BcN/vUFkDvj5c4XFs17FatNgcyO4Ti9EDErvTfSIi6qHWnfeU60nJll9zBpZfwx3NiCi4GJQiCiBBEDCqf2gDm6Io4vDhw8jJyYFW6/+aSA6HhKLqJsXlbeYWG25bvR3bCqtx/392Y3CfOK82CSYdZk8YpJilFCxyUEpp+V68K1DFTCmKRDWNVndA6tVbzvYqMPvEuv34qbgO/91ZjAVTh3rdv7JB3n2v4+V7u4/X4uaXtym2uXJMf5/biBMRUeCcdBc5V64nRUQUSgxKEVGPaDQCstO8g02yh68YiQf/9xPe312i2sYhSbjjAu8vxMHSqULnVgalqOuqG604VtmA45UtaI6pg7Zd7bW+CUbVorP+sONYDQBgaN84XHhautfxm88ZjAf++yPe2V6Eu6ac4hU4kpfv9fGxfO+cU/pg2ogMnKhpUjyeGmfA/50zuLtPgYioVzhS0YBDKnMBAAxJi0NCgGo2lbqLnPvOlCIiCgUGpYgooGadnYVmm4ijFY1exw6V1eP7gmrsOVEXgp45SZLkM1OqtaYUl+9R1315oByL1+xx/VTsdVwQgLmTsnHDhCxoFDKJ4ow6DEjuftBqe2E1AGDCkFTF45ef0Q/LPtqLwqomzH11O2L0nl+UOpMpZdJr8c+547vdRyKiaPDQe3tdFwq85wLAWbPp3KF9VGt0jstOxf9NHOQz6/Tn4jpUNHiXU9hzohYA0C+ZQSkiCj8MShFRQAmCgHnnKm8P/PXhCnz/8jbsL1HfLj7Qmm0i5PrPSplS8Sx0Tj0Qa9CiX5IJdrsdOp0Obb9KSHAuqVi9pRCrtxSqnuPvs8/EL8d0r7jstgJnUOrsbOWgVJxRh6vPGoB/f1eEzYcqFNvEG3U+g1JERNSxPvEG9I3Tec0FAGAVJVQ2WPDVQeX3YQB4f3cJfjpRq5hZLjokPL8xHx/4yEoHmClFROGJQSkiCpkR/ZyFjwuqGtFktYdkW3h56Z4gALF69ULnjVYRDkl59zIiNZed3g/TR6ar1nX75nAlln+y3720oi2b6IC5xY5HP9yL84elIcVHsXElzVYRPxc7sxDVglIA8OCMERiblQKLXTkbcMzAZNXdmoiIqHOev/FM1blAkiQcKK3H90erYFfYKbWywYoXNx/Bf3acwH92nFB9DI3g/GyllEyVnmDCRadm9Ph5EBH5G4NSRBQyafFGpCcYUV5vwYHSepw1KCXofZCX5cUZdNAo7A7Ydklfi51BKfKv83LSsDbnfMVjVrsDVz77DQ6W1eP2f+3AaZkJXm2arSJ+LK7Dydpmr2MOCbA7JGQmmjAwRX0JYLxRh2vHDez+kyAioh4RBAEj+iW6L9YpOWtQMh5fux91zco7Og9KjcWyq0aF5LMUEVFPMChFRCE1ol8iyusrsK/EHKKglFzkXDkTxKTXQCM4v+A32xzB7BpFOYNOgyeuOR3XrtqCncdqsNNVtLyrLj+jH3e+IyKKcJeMysQlozJD3Q0iIr9jUIqIQmpk/0RsOlSB/SdDU1fK1857gPPqZZxBh3qLnUEpCrpxg1Pw8tzx+FFlMwCdRsBpmYkYlh6vWChdqxXQnzVEiIiIiChMMShFRCElp6rvC1FQytfOe7I4oxyU4vI9Cr6LTsvARaexDggRERER9T4MShFRSI3s56yTs7fYjFtXb/c6rtMIWDB1KM4M0NI+d6aUjyLr8tK+JmZKERERERER+Q2DUkQUUkPS4pEaZ0B1oxVfHihXbHOwrB6f/eaCgOwA5i507iNTSs6iarYzKEVEREREROQvDEoRUUhpNQL+c+ck7CpSKOIsAU9/dhDHqprwry3HMP+CU/z++K3L99QDXnLAijWliIiIiIiI/IdBKSIKuWHp8RiWHq96/IH//oinPzuIt7YVeR0TBOC2807BjRMHdeux6zsodN72GJfvERERERER+Y8m1B0gIvLl2nEDMSYrGVa7A0crG73+HaloxIrPD0GSuleEvDOFzt3L91jonIiIiIiIyG+YKUVEYU2jEfDm7ROx/6QZ7UNCDoeEW17djsoGCw6U1rt38uuKxk5lSjmX9nH5HhERERERkf8wKEVEYS/OqMP47FTFYxNPScXGgxX4+nBFt4JSDZ3IlOLyPSIiIiIiIv/j8j0iimjn5/QFAHx9uLJb9+/M8r04g/NYC3ffIyIiIiIi8hsGpRTk5eVh5MiROPvss0PdFSLqwAU5aQCAbQXVaLGJXb5/o8V5n84VOmdNKSIiIiIiIn/h8j0Fubm5yM3NhdlsRlJSUqi7Q0Q+DEuPR0aiEWVmC37x100w6Lxj7VNP7YtHrhgJQRC8jjW4a0ppVR8jnjWliIiIiIiI/I5BKSKKaIIgYMbofli9pRDFtc2KbQoqGzF5aBouHpnhdazR2vmaUgxKERERERER+Q+DUkQU8X5/+QjMPHMAbKJ30OjD3SV4/btjePTDvRiSFgutxjOTytxsA9DZ5XsMShEREREREfkLg1JEFPH0Wg3GZiUrHhvVPxEb9pehuLYZ01ZsVj2Hr0wp+djJehvue2eP1zLAeJMOiy85Falxhq53noiIiIiIKEoxKEVEvVqsQYcnf3UGFq/Zg2aVQuhjs5IxIDlG9RyZiSYAzkLnH/14UrGNSafFI1eO7HmHiYiIiIiIogR33yOiXu+C4X2x7ffT8NOj0xX/vX7bRGg03kXQZVmpsXhl7jjceXYf/OGy0/DwFSPd/+644BQAwJqdx9HoKppOgZeXl4fs7GyYTCZMnDgR27Zt89l+zZo1OO2002AymXD66adj3bp1QeopEREFEucDIqLIxqAUEVEnTBneF1ePSsa8c7Nx23lD3P8evPQ0DEmLQ32LHe/9UBzqbkaFd955B4sWLcLSpUuxa9cujBkzBtOnT0d5ebli+y1btmD27Nm47bbb8MMPP2DmzJmYOXMmfv755yD3nIiI/InzARFR5BMkSZJC3YlwZTabkZSUhLq6OiQmJnbpvqIo4vDhw8jJyYFWq77VPPnGcew5jqF/+BrHV74pwB8/3oekGD2y+8R63VerEXDmoBScNSgFWpWMrL4JBqQnmFSP+0OfeAOMuq69BnryPhgoEydOxNlnn43nnnsOAOBwOJCVlYVf//rXePDBB73az5o1C42Njfj444/dt51zzjkYO3YsVq1a1anHlMehoqJCcRw0Gg10utYV8Var1f3f7V87giBAr9crtm2vfVubzQa1aTtQbQHAYDB0q63dbofDob5BQGfbiqKIwsJCDB8+HFqttsPz6vV6d+23rrQVRRGiqLzMt6ttdTodNK6NFcKhrcPhgMViUX0f02q17tscDgfsdvXMz2C0lSQJNpvNL23b/n32tG3bv2e9Xq/6d+/rvB21Dcf3iKqqKqSlpYXVXABE1nyg9DkiHH/XnA96/3xgs9mwf/9+1e8GnA8615bzgf/mA9aUIiLqoWvHD8QzGw6jrtmGPSfqFNvsKqrFyygIcs88/XfBJIwbnBrSPvSU1WrFzp07sWTJEvdtGo0G06ZNw9atWxXvs3XrVixatMjjtunTp+P9999XfRyLxQKLxeL+2Ww2AwCefvppGI1Gr/Y5OTm48cYb3T//+c9/dn94kSQJ1dXVSE1NhSAIyM7Oxty5c91tV6xYgaamJsV+9O/fH/Pnz3f//Oyzz6K2tlaxbd++fXH33Xe7f161ahUqKioU2yYnJ+Pee+91//zyyy+jpKREsW1sbCx++9vfun9+/fXXUVhYqNhWr9fjoYcecv/81ltv4fDhw4ptAWDp0qXu/3733Xexb98+xXaSJOFXv/qV+wP3hx9+iN27d6ued/HixYiLiwMArFu3Djt27FBte++99yI5ORkA8Nlnn6m+jgBgwYIFSE9PBwBs3LgRmzZtUm17++23Y8CAAQCAb7/9Fl988YVq27lz5yI7OxsAsG3bNnzyySeqbWfPno3hw4cDAHbv3o0PPvhAte21116LUaNGAQD27t2LNWvWeLwW27rqqqswduxYAMChQ4fw1ltvqZ53xowZmDBhAgCgsLAQr732mmrbadOm4dxzzwUAFBcX45///Kdq2ylTpmDq1KkAgPLycrzwwguqbSdNmoRLLrkEAFBbW4tnnnlGte348eNx+eWXAwAaGxvxl7/8RbXt2LFjcdVVVwFwvt8sX77c43jbv+dRo0bhuuuucx97/PHHVc/r6z2ivXB8j/jXv/6l2C6UIm0+aD8XAOH5u+Z8kAyg988HL730kuJcAHA+kHE+cArGfMCgFBFRDyWa9Fh7z3k4WFqveLzBYse3+ZU4WtGoeNwhSSivt6Ci3oLApq4GLgsrWCorKyGKIjIyMjxuz8jIwIEDBxTvU1paqti+tLRU9XGWL1+OZcuWed1eU1PjcTW37WO0/bBdVVXlvgIoSRKam5tRXV0NQRAQExPj0bayshItLS2K/dDpdB5tKyoqUF+v/DqTJMmjbXl5OWpqahTb2mw2r7bV1dWKbZuamjzalpWVqbZt39/S0lLVtgA82p48eVK1rSRJqKmpQX5+PjQaDUpKSnyeNz8/H7GxzqzFjtoeOXLEfaWvo7ZHjx5FXZ0z8FxcXOyzbUFBgfuD44kTJ3y2LSwsdH8gPX78eIdt5S8RRUVFPtseO3bM/Xo9duwYqqurPV6LbRUVFbm/uBUWFvo87/Hjx5GSkgKg43E4ceKE+/fs67Ujn0tuW1VV5bNtSUmJu63ZbO5026ampk63tVqtXm3b/j2fPHnS4zXs67y+3iPaC8f3CLUvK6EUafNB+7kACM/fNeeD3j8fFBUVqc4F8nHOB5wPZMGYD7h8zwcu3ws9jmPPcQz9I1rHMdyW75WUlGDAgAHYsmULJk2a5L79gQcewKZNm/D999973cdgMOC1117D7Nmz3bc9//zzWLZsGcrKyhQfR+nKeFZWFkpLS7u1fC8/Px/Dhg3j8r1uthVFEceOHXP//XG5RveX77V9LbbF5Rqda9v27znalmtkZGSEzVwARN580H4uAMLzd835oPfPBzabDQcOHFCcCwDOB51ty/mAy/eIiCgKpaWlQavVen15KCsrQ2ZmpuJ9MjMzu9QeAIxGo+KyjJiYGMTExHTYz7ZtRFGEyWRCTEyM4oe/zpxP1pWAaG9qK4qi+0Nn2w+fwexDb2ir0Wh8vhbbtm37AbSj8waiLQCPD+3h0tbX33NX/pYD1TZQrx+TydTptsESafNBR3NB27adES7vK8Fuy/mg520BdGoukM/L+UC5LecD/+Hue0REFDEMBgPGjRuHDRs2uG9zOBzYsGGDx5XytiZNmuTRHgA+//xz1fZERBT+OB8QEfUOzJQiIqKIsmjRIsydOxfjx4/HhAkTsHLlSjQ2NmLevHkAgDlz5mDAgAHugpT33nsvpkyZgr/+9a+4/PLL8fbbb2PHjh148cUXQ/k0iIiohzgfEBFFPgaliIgoosyaNQsVFRV45JFHUFpairFjx2L9+vXu4rVFRUXuugkAMHnyZLz55pv4wx/+gIceegg5OTl4//33MXr06FA9BSIi8gPOB0REkY9BKSIiijgLFy7EwoULFY9t3LjR67brrrvOY6teIiLqHTgfEBFFNtaUIiIiIiIiIiKioGNQioiIiIiIiIiIgo5BKSIiIiIiIiIiCjoGpYiIiIiIiIiIKOhY6NwHSZIAAGazucv3FUURDQ0NMJvN0Gq1/u5a1OA49hzH0D+idRzl9z/5/TBacT4ILY6hf3Acey5ax5BzQavuzgfR+trxN45jz3EM/SNaxzEQ8wGDUj7U19cDALKyskLcEyKi0Kqvr0dSUlKouxEynA+IiDgXAJwPiIgA/84HgsRLHqocDgdKSkqQkJAAQRC6dF+z2YysrCwcP34ciYmJAeph78dx7DmOoX9E6zhKkoT6+nr0798fGk30rvjmfBBaHEP/4Dj2XLSOIeeCVt2dD6L1teNvHMee4xj6R7SOYyDmA2ZK+aDRaDBw4MAenSMxMTGqXqSBwnHsOY6hf0TjOEb7VXGA80G44Bj6B8ex56JxDDkXOPV0PojG104gcBx7jmPoH9E4jv6eD6L7UgcREREREREREYUEg1JERERERERERBR0DEoFiNFoxNKlS2E0GkPdlYjGcew5jqF/cBypu/ja6TmOoX9wHHuOY0jdxdeOf3Ace45j6B8cR/9hoXMiIiIiIiIiIgo6ZkoREREREREREVHQMShFRERERERERERBx6AUEREREREREREFHYNSREREREREREQUdAxKERERERERERFR0DEoFSB5eXnIzs6GyWTCxIkTsW3btlB3KWw9+uijEATB499pp53mPt7S0oLc3Fz06dMH8fHx+NWvfoWysrIQ9jg8bN68GVdeeSX69+8PQRDw/vvvexyXJAmPPPII+vXrh5iYGEybNg2HDx/2aFNdXY2bbroJiYmJSE5Oxm233YaGhoYgPovQ6mgMb7nlFq/X5qWXXurRJtrHkHzjXNA1nA+6jnOBf3A+oEDjfNB5nAu6h/NBz3EuCA0GpQLgnXfewaJFi7B06VLs2rULY8aMwfTp01FeXh7qroWtUaNG4eTJk+5/33zzjfvYb37zG3z00UdYs2YNNm3ahJKSElxzzTUh7G14aGxsxJgxY5CXl6d4/KmnnsLf//53rFq1Ct9//z3i4uIwffp0tLS0uNvcdNNN2Lt3Lz7//HN8/PHH2Lx5M+64445gPYWQ62gMAeDSSy/1eG2+9dZbHsejfQxJHeeC7uF80DWcC/yD8wEFEueDruNc0HWcD3qOc0GISOR3EyZMkHJzc90/i6Io9e/fX1q+fHkIexW+li5dKo0ZM0bxWG1traTX66U1a9a4b9u/f78EQNq6dWuQehj+AEjvvfee+2eHwyFlZmZKTz/9tPu22tpayWg0Sm+99ZYkSZK0b98+CYC0fft2d5tPPvlEEgRBKi4uDlrfw0X7MZQkSZo7d6501VVXqd6HY0i+cC7oOs4HPcO5wD84H5C/cT7oGs4FPcf5oOc4FwQPM6X8zGq1YufOnZg2bZr7No1Gg2nTpmHr1q0h7Fl4O3z4MPr3749TTjkFN910E4qKigAAO3fuhM1m8xjP0047DYMGDeJ4+lBQUIDS0lKPcUtKSsLEiRPd47Z161YkJydj/Pjx7jbTpk2DRqPB999/H/Q+h6uNGzciPT0dp556KhYsWICqqir3MY4hqeFc0H2cD/yHc4F/cT6g7uB80D2cC/yL84H/cC7wPwal/KyyshKiKCIjI8Pj9oyMDJSWloaoV+Ft4sSJWL16NdavX48XXngBBQUFOP/881FfX4/S0lIYDAYkJyd73Ifj6Zs8Nr5eh6WlpUhPT/c4rtPpkJqayrF1ufTSS/Gvf/0LGzZswJ///Gds2rQJM2bMgCiKADiGpI5zQfdwPvAvzgX+w/mAuovzQddxLvA/zgf+wbkgMHSh7gDRjBkz3P99xhlnYOLEiRg8eDD+85//ICYmJoQ9o2h3ww03uP/79NNPxxlnnIGhQ4di48aN+MUvfhHCnhH1TpwPKFxxPiAKHs4FFK44FwQGM6X8LC0tDVqt1msHiLKyMmRmZoaoV5ElOTkZw4cPR35+PjIzM2G1WlFbW+vRhuPpmzw2vl6HmZmZXgU27XY7qqurObYqTjnlFKSlpSE/Px8Ax5DUcS7wD84HPcO5IHA4H1BncT7oOc4FPcf5IDA4F/gHg1J+ZjAYMG7cOGzYsMF9m8PhwIYNGzBp0qQQ9ixyNDQ04MiRI+jXrx/GjRsHvV7vMZ4HDx5EUVERx9OHIUOGIDMz02PczGYzvv/+e/e4TZo0CbW1tdi5c6e7zZdffgmHw4GJEycGvc+R4MSJE6iqqkK/fv0AcAxJHecC/+B80DOcCwKH8wF1FueDnuNc0HOcDwKDc4GfhLrSem/09ttvS0ajUVq9erW0b98+6Y477pCSk5Ol0tLSUHctLN1///3Sxo0bpYKCAunbb7+Vpk2bJqWlpUnl5eWSJEnSXXfdJQ0aNEj68ssvpR07dkiTJk2SJk2aFOJeh159fb30ww8/SD/88IMEQFqxYoX0ww8/SMeOHZMkSZKefPJJKTk5Wfrggw+kH3/8UbrqqqukIUOGSM3Nze5zXHrppdKZZ54pff/999I333wj5eTkSLNnzw7VUwo6X2NYX18vLV68WNq6datUUFAgffHFF9JZZ50l5eTkSC0tLe5zRPsYkjrOBV3H+aDrOBf4B+cDCiTOB13DuaB7OB/0HOeC0GBQKkCeffZZadCgQZLBYJAmTJggfffdd6HuUtiaNWuW1K9fP8lgMEgDBgyQZs2aJeXn57uPNzc3S3fffbeUkpIixcbGSldffbV08uTJEPY4PHz11VcSAK9/c+fOlSTJufXrww8/LGVkZEhGo1H6xS9+IR08eNDjHFVVVdLs2bOl+Ph4KTExUZo3b55UX18fgmcTGr7GsKmpSbrkkkukvn37Snq9Xho8eLA0f/58rw+Q0T6G5Bvngq7hfNB1nAv8g/MBBRrng87jXNA9nA96jnNBaAiSJEmBzcUiIiIiIiIiIiLyxJpSREREREREREQUdAxKERERERERERFR0DEoRUREREREREREQcegFBERERERERERBR2DUkREREREREREFHQMShERERERERERUdAxKEVEREREREREREHHoBRRL5CdnY2VK1eGuhtERBRinA+IiIhzAUUSBqWIuuiWW27BzJkzAQBTp07FfffdF7THXr16NZKTk71u3759O+64446g9YOIiDgfEBER5wKintKFugNEBFitVhgMhm7fv2/fvn7sDRERhQrnAyIi4lxA0YSZUkTddMstt2DTpk145plnIAgCBEFAYWEhAODnn3/GjBkzEB8fj4yMDNx8882orKx033fq1KlYuHAh7rvvPqSlpWH69OkAgBUrVuD0009HXFwcsrKycPfdd6OhoQEAsHHjRsybNw91dXXux3v00UcBeKfoFhUV4aqrrkJ8fDwSExNx/fXXo6yszH380UcfxdixY/H6668jOzsbSUlJuOGGG1BfXx/YQSMi6oU4HxAREecCou5hUIqom5555hlMmjQJ8+fPx8mTJ3Hy5ElkZWWhtrYWF110Ec4880zs2LED69evR1lZGa6//nqP+7/22mswGAz49ttvsWrVKgCARqPB3//+d+zduxevvfYavvzySzzwwAMAgMmTJ2PlypVITEx0P97ixYu9+uVwOHDVVVehuroamzZtwueff46jR49i1qxZHu2OHDmC999/Hx9//DE+/vhjbNq0CU8++WSARouIqPfifEBERJwLiLqHy/eIuikpKQkGgwGxsbHIzMx03/7cc8/hzDPPxBNPPOG+7ZVXXkFWVhYOHTqE4cOHAwBycnLw1FNPeZyz7Rr07OxsPP7447jrrrvw/PPP/3979x7fVJXvffybpE16b7m2BSvlKoLIVTjIOOrYAS/DwMw4InIQOYpHhVHsUUd8FHS81MvIgzooj46KzoyKOmfUow6OVsGDMoIgjspFChQQaKGU3i9pk/380TY0NElvaZImn/fr1deL7P3bydqLJL/kl7XWltVqVXJyskwmk9vjnSo3N1fffPON9u3bp4yMDEnSyy+/rJEjR2rz5s0655xzJDUkqNWrVysxMVGSNHfuXOXm5urBBx/sXMcAQIQhHwAAyAVAxzBSCvCzr7/+Wp988okSEhJcf8OHD5fU8AtEk/Hjx7c49qOPPtJFF12k/v37KzExUXPnztXx48dVVVXV5sffsWOHMjIyXElHkkaMGKGUlBTt2LHDtS0zM9OVdCQpPT1dR48ebde5AgC8Ix8AAMgFgG+MlAL8rKKiQtOnT9cjjzzSYl96errr3/Hx8W778vPz9bOf/Uw33nijHnzwQfXs2VMbNmzQtddeK7vdrri4OL+2Mzo62u22yWSS0+n062MAQCQjHwAAyAWAbxSlgE6wWq1yOBxu28aNG6e//vWvyszMVFRU219iW7ZskdPp1OOPPy6zuWEQ4+uvv97q453qzDPP1MGDB3Xw4EHXLyLbt29XSUmJRowY0eb2AADajnwAACAXAO3H9D2gEzIzM/XFF18oPz9fRUVFcjqdWrhwoYqLizV79mxt3rxZe/bs0QcffKD58+f7TBpDhgxRXV2dnnrqKe3du1d/+tOfXIscNn+8iooK5ebmqqioyOPQ3aysLI0aNUpz5szR1q1btWnTJl199dU6//zzNWHCBL/3AQCAfAAAIBcAHUFRCuiE2267TRaLRSNGjFCfPn104MAB9evXT5999pkcDoemTp2qUaNGafHixUpJSXH9yuHJ6NGjtXz5cj3yyCM666yz9Je//EU5OTluMeeee65uuOEGzZo1S3369GmxGKLUMNT27bffVo8ePfTjH/9YWVlZGjRokNasWeP38wcANCAfAADIBUD7mQzDMILdCAAAAAAAAEQWRkoBAAAAAAAg4ChKAQAAAAAAIOAoSgEAAAAAACDgKEoBAAAAAAAg4ChKAQAAAAAAIOAoSgEAAAAAACDgKEoBAAAAAAAg4ChKAQAAAAAAIOAoSgEAAAAAACDgKEoBAAAAAAAg4ChKAQAAAAAAIOAoSgEAAAAAACDgKEoBAAAAAAAg4ChKAQAAAAAAIOAoSgEAAAAAACDgKEoBAAAAAAAg4ChKAQAAAAAAIOAoSgEAAAAAACDgKEoBAAAA6HY+/fRTTZ8+Xf369ZPJZNJbb73V6jHr1q3TuHHjZLPZNGTIEK1evbrL2wkA8I6iFAAAAIBup7KyUqNHj9bKlSvbFL9v3z5ddtlluvDCC7Vt2zYtXrxY1113nT744IMubikAwBuTYRhGsBsBAAAAAB1lMpn0t7/9TTNnzvQa89vf/lbvvfeevv32W9e2K6+8UiUlJVq7dm0AWgkAOFVUsBsQypxOpw4fPqzExESZTKZgNwcAAs4wDJWXl6tfv34ymyN3cC35AEAkC5dcsHHjRmVlZbltmzZtmhYvXuz1mNraWtXW1rpuO51OFRcXq1evXuQDABGnK/IBRSkfDh8+rIyMjGA3AwCC7uDBgzrttNOC3YygIR8AQPfPBQUFBUpNTXXblpqaqrKyMlVXVys2NrbFMTk5ObrvvvsC1UQA6Bb8mQ8oSvmQmJgoqaHDk5KS2nWsw+HQnj17NHjwYFkslq5oXkSgHzuPPvSPSO3HsrIyZWRkuN4PIxX5ILjoQ/+gHzsvUvswknPBkiVLlJ2d7bpdWlqq008/vUP5AAC6u67IBxSlfGgakpuUlNShLyEJCQlKSkqKqA8t/kY/dh596B+R3o+RPkWBfBBc9KF/0I+dF+l92N1zQVpamgoLC922FRYWKikpyeMoKUmy2Wyy2WwttnckHwBAuPBnPui+k8IBAAAAoI0mT56s3Nxct20ffvihJk+eHKQWAQAoSgEAAADodioqKrRt2zZt27ZNkrRv3z5t27ZNBw4ckNQw9e7qq692xd9www3au3ev7rjjDu3cuVNPP/20Xn/9dd16663BaD4AQBSlAAAAAHRDX375pcaOHauxY8dKkrKzszV27FgtXbpUknTkyBFXgUqSBg4cqPfee08ffvihRo8erccff1x//OMfNW3atKC0HwDAmlIAAAAAuqELLrhAhmF43b969WqPx3z11Vdd2CoAQHswUgoAAAAAAAAB162LUp9++qmmT5+ufv36yWQy6a233nLbbxiGli5dqvT0dMXGxiorK0u7d+8OTmMBAF2CXAAAAAB0T926KFVZWanRo0dr5cqVHvc/+uijevLJJ7Vq1Sp98cUXio+P17Rp01RTUxPglgIAugq5AAAAAOieuvWaUpdccokuueQSj/sMw9CKFSt09913a8aMGZKkl19+WampqXrrrbd05ZVXtvlx7Ha77HZ7i+1ms1lRUVFucU0cDofrOIvFIpPJpOjoaI+xpzo1tq6uzut8+a6KlSSr1dqh2Pr6ejmdTr/Ems3mNsdGR0fLZDK1O9bhcMjhcPglNioqytXmUIh1Op2u52HTc7E5i8Xi2uZ0OlVfX+/1fgMRaxiG6urq/BLb/PXpj9im13R9fb1bP/p6Lft6jzhVqL5H+GpHqAhULpDIB+2N9Vc+cDgcbo9JPiAfBCsfNH89R0dHt/k9PhzyAQAAXaFbF6V82bdvnwoKCpSVleXalpycrEmTJmnjxo0ev4jU1taqtrbWdbusrEyS9Nhjj8lms7WIHzp0qK666irX7UceecSVtA3DUHFxsXr27CmTyaTMzEzNmzfPFbt8+XJVVVV5bHu/fv20YMEC1+2nnnpKJSUlHmP79Omjm266yXV71apVOnbsmMfYlJQU3XLLLa7bzz//vA4fPuwxNi4uTrfffrvr9p/+9Cfl5+d7jI2OjtZdd93luv3qq6/6nBqzbNky17/ffPNNbd++3WvsHXfcIafTKYfDoXfffdd1yV9PbrvtNsXHx0uS3n//fX355ZdeY2+55RalpKRIkv7xj39o48aNXmNvvPFG9e3bV5K0bt06rV+/3mvsddddp/79+0uSPvvsM3300UdeY+fNm6fMzExJ0qZNm/T3v//da+zs2bM1bNgwSdK2bdv09ttve429/PLLNXLkSEnSd999pzfeeMPtudjcjBkzNGbMGEnS999/r1dffdXr/V5yySWaOHGiJCk/P18vvfSS19isrCxNmTJFknTo0CH98Y9/9Bp7/vnn64ILLpAkHT16VM8884zX2MmTJ2vq1KmSpJKSEj3xxBNeYydMmKDLLrtMUsNImt///vdeY8eMGeMqWNjtduXk5LSIaXpNT5kyRbNmzXJtf+CBB7zer6/3iFOF6nvEvn37PMZ2Fx3JBRL5oLlQyAeGYehXv/qVqwDzzjvvkA9EPghGPmj+eh45cqR+/etfu/aFcz54+eWXPcYBANBZYVuUKigokCSlpqa6bU9NTXXtO1VOTo7uu+++FttPnDjh9mtu88do/mH7+PHjrl8ADcNQdXW1iouLZTKZFBsb6xZbVFTkdepIVFSUW+yxY8dUXl7uMdYwDLfYo0eP6sSJEx5j6+rqWsQWFxd7jK2qqnKLLSws9Bp7ansLCgq8xkpyiz1y5IjP2Ly8PFVUVCgvL0+HDx9uNTYuLk6SWo3ds2ePkpKS2hS7d+9elZaWSmr4QO0rdt++fa4Pjj/88IPP2Pz8fNcH0oMHD7Ya2/QF4sCBAz5j9+/f73q+7t+/X8XFxW7PxeYOHDjg+uKWn5/v834PHjyoHj16SGq9H3744QfX/7Ov507TfTXFHj9+3Gfs4cOHXbFlZWVtjq2qqmpzrN1u9xjb9Jo+9XXv6359vUecKlTfI7zFdhcdyQUS+aC5UMgHhmHoxIkTysvLk9lsJh+QD4KWD5q/no8cORIx+cBb8QoAgM4yGb7G4HcjJpNJf/vb3zRz5kxJ0ueff64pU6bo8OHDSk9Pd8VdccUVMplMWrNmTYv78PTLeEZGhgoKClwfWJtrbbpGXl6ehgwZwnSNTsSazWbt2bNHQ4YMkWEYTNdoZ6zT6VRtba3bc7E5pmu0PbbpNT1s2DC3kTLhPl2jtLRUaWlpKi0t9fg+GGr8kQsk8sGpgp0PHA6H9u/fr6FDh8pisTB9j3wQ1Ol7TX0YSdP3jh8/rtTU1G6TC7pSWVmZkpOT6QsAEakr3gPDdqRUWlqapIZf5Zp/ESksLHQNTz+VzWbzOC0jNjZWsbGxrT5m8xiHw6GYmBjFxsa2+OB3amxrPB0fKbEOh0Nms9ntw2eg29DdY81ms8/nYvPY5h9AW7vfroiV5PahPZRim17TNpvNrR/b81ruqtiufP50hzWlfOlILpDIB6EW63A4XHmAfNDxWPJB52N9vZ7DOR/ExMS0ORYAgPbo1lff82XgwIFKS0tTbm6ua1tZWZm++OILTZ48OYgtAwAECrkAAAAACF3deqRU01pDTfbt26dt27apZ8+eOv3007V48WI98MADGjp0qAYOHKh77rlH/fr1c03rAAB0f+QCAAAAoHvq1kWpL7/8UhdeeKHrdnZ2tqSGq9isXr1ad9xxhyorK3X99derpKREP/rRj7R27VqGIANAGCEXAAAAAN1Tty5KXXDBBT4XWzWZTPrd736n3/3udwFsFQAgkMgFAAAAQPcUtmtKAQAAAAAAIHRRlAIAAAAAAEDAUZQCAAAAAABAwFGUAgAAAAAAQMBRlAIAAAAAAEDAUZQCAAAAAABAwFGUAgAAAAAAQMBRlAIAAAAAAEDAUZQCAAAAAABAwFGUAgAAAAAAQMBRlAIAAAAAAEDAUZQCAAAAAABAwFGUAgAAAAAAQMBRlAIAAAAAAEDAUZQCAAAAAABAwFGUAgAAAAAAQMBRlAIAAAAAAEDAUZQCAAAAAABAwFGUAgAAAAAAQMBRlAIAAAAAAEDAUZQCAAAAAABAwFGUAgAAAAAAQMBRlAIAAAAAAEDAUZQCAAAAAABAwFGUAgAAAAAAQMBRlAIAAAAAAEDAUZQCAAAAAABAwFGUAgAAAAAAQMBRlAIAAAAAAEDAUZQCAAAAAABAwFGUAgAAANAtrVy5UpmZmYqJidGkSZO0adMmn/ErVqzQGWecodjYWGVkZOjWW29VTU1NgFoLADgVRSkAAAAA3c6aNWuUnZ2tZcuWaevWrRo9erSmTZumo0ePeox/5ZVXdOedd2rZsmXasWOHnn/+ea1Zs0Z33XVXgFsOAGhCUQoAAABAt7N8+XItWLBA8+fP14gRI7Rq1SrFxcXphRde8Bj/+eefa8qUKbrqqquUmZmpqVOnavbs2a2OrgIAdB2KUgAAAAC6Fbvdri1btigrK8u1zWw2KysrSxs3bvR4zLnnnqstW7a4ilB79+7V+++/r0svvdTr49TW1qqsrMztDwDgP1HBbgAAAAAAtEdRUZEcDodSU1Pdtqempmrnzp0ej7nqqqtUVFSkH/3oRzIMQ/X19brhhht8Tt/LycnRfffd59e2AwBOYqQUAAAAgLC3bt06PfTQQ3r66ae1detW/fd//7fee+893X///V6PWbJkiUpLS11/Bw8eDGCLASD8MVIKAAAAQLfSu3dvWSwWFRYWum0vLCxUWlqax2PuuecezZ07V9ddd50kadSoUaqsrNT111+v//N//o/M5pa/19tsNtlsNv+fAABAUpiPlHI4HLrnnns0cOBAxcbGavDgwbr//vtlGEawmwYACBByAQCEH6vVqvHjxys3N9e1zel0Kjc3V5MnT/Z4TFVVVYvCk8VikSRyAgAESViPlHrkkUf0zDPP6KWXXtLIkSP15Zdfav78+UpOTtbNN98c7OYBAAKAXAAA4Sk7O1vz5s3ThAkTNHHiRK1YsUKVlZWaP3++JOnqq69W//79lZOTI0maPn26li9frrFjx2rSpEnKy8vTPffco+nTp7uKUwCAwArrotTnn3+uGTNm6LLLLpMkZWZm6tVXX+WyrwAQQcgFABCeZs2apWPHjmnp0qUqKCjQmDFjtHbtWtfi5wcOHHAbGXX33XfLZDLp7rvv1qFDh9SnTx9Nnz5dDz74YLBOAQAiXlgXpc4991w9++yz+v777zVs2DB9/fXX2rBhg5YvX+4xvra2VrW1ta7bTZd8dTgccjgc7Xpsh8Mhp9PZ7uPgjn7sPPrQPyK1H8PhfNubCyTyQaihD/2Dfuy8SO3DUD7fRYsWadGiRR73rVu3zu12VFSUli1bpmXLlgWgZQCAtgjrotSdd96psrIyDR8+XBaLRQ6HQw8++KDmzJnjMd7bJV/37NmjhISEdj220+lUcXGx8vLyPC6aiLahHzuPPvSPSO3HioqKYDeh09qbCyTyQaihD/2Dfuy8SO3DcMgFAIDQFNZFqddff11/+ctf9Morr2jkyJHatm2bFi9erH79+mnevHkt4pcsWaLs7GzX7bKyMmVkZGjw4MFKSkpq12M7HA7l5eVpyJAhzFHvBPqx8+hD/4jUfmwaIdSdtTcXSOSDUEMf+gf92HmR2ofhkAsAAKEprItSt99+u+68805deeWVkhou+7p//37l5OR4/CLi7ZKvFoulQx88zGZzh4/FSfRj59GH/hGJ/RgO59reXCCRD0IRfegf9GPnRWIfRtK5AgACK6zHHXu77KvT6QxSiwAAgUYuAAAAAEJTWI+Uarqaxumnn66RI0fqq6++0vLly/Uf//EfwW4aACBAyAUAAABAaArrotRTTz2le+65RzfddJOOHj2qfv366T//8z+1dOnSYDcNABAg5AIAAAAgNIV1USoxMVErVqzQihUrgt0UAECQkAsAAACA0BTWa0oBAAAAAAAgNFGUAgAAAAAAQMBRlAIAAAAAAEDAUZQCAAAAAABAwFGUAgAAAAAAQMBRlAIAAAAAAEDAUZQCAAAAAABAwFGUAgAAAAAAQMBRlAIAAAAAAEDAUZQCAAAAAABAwFGUAgAAAAAAQMBRlAIAAAAAAEDARQW7AYA3hmHoXz+U6psfKvWD85gsZvcaakbPWA3pmxik1gEAAAAAgM6gKIWQ9Vnecf3781803iposd9kktbfdqFO7xUX2IYBAAAAAIBOoyiFkLW/uFKSlGA1a2CfBJlMJte+XQXlqq136uCJKopSAAAAAAB0QxSlELLs9U5J0rh+sXpxwbmyWCyufdOf2qBvDpWqps4RrOYBAAAAAIBOYKFzhKw6R0NRKtpiarEvJrrhqVvbWLgCAAAAAADdC0UphKymkVJRZk9FqYZRU4yUAgAAAACge6IohZDVVJTyNFLKFtVUlGKkFAAAAAAA3RFFKYQsu8OQJEV7HCnV8NRlpBQAAAAAAN0TRSmELNdIKQ9FqaaRUqwpBQAAAABA90RRCiHL7mgYBeVroXNGSgEAAAAA0D1RlELIqqtvnL7nsSjVuKZUPUUpAAAAAAC6I4pSCFl2h6+r7zU8dWtZ6BwAAAAAgG6JohRClq+r78W4rr7HSCkAAAAAALojilIIWU0jpTwudN40UoqFzgEAAAAA6JYoSiFkNY2UivLwLHWtKcVIKQAAAAAAuiWKUghZTN8DAAAAACB8UZRCyHJN3/NQlGqavlfDQucAAAAAAHRLFKUQsup8rCnlmr5Xz0gpAAAAAAC6I4pSCFm+pu/ZGheaqmWkFAAAAAAA3RJFKYQsV1GKkVIAAAAAAIQdilIIWU1rSkX5KEoxUgoAAAAAgO6JohRCls+r77kWOmekFAAAAAAA3RFFKYQsX1ffi4lqHClVz0gpAAAAAAC6I4pSCFl1PtaUsjFSCgAAIOKtXLlSmZmZiomJ0aRJk7Rp0yaf8SUlJVq4cKHS09Nls9k0bNgwvf/++wFqLQDgVFHBbgDgTVtGStU7DdU7nIqyUF8FAACIJGvWrFF2drZWrVqlSZMmacWKFZo2bZp27dqlvn37toi32+366U9/qr59++rNN99U//79tX//fqWkpAS+8QAASRSlEKKcTkN1DkOSFO2h3tS00Lkk1dQ7lUBRCgAAIKIsX75cCxYs0Pz58yVJq1at0nvvvacXXnhBd955Z4v4F154QcXFxfr8888VHR0tScrMzAxkkwEApwj7b/KHDh3Sv//7v6tXr16KjY3VqFGj9OWXXwa7WWhFnfPkWlGeRkrZok4+dZnCB6A15AIACC92u11btmxRVlaWa5vZbFZWVpY2btzo8Zh33nlHkydP1sKFC5WamqqzzjpLDz30kBwO758la2trVVZW5vYHAPCfsB4pdeLECU2ZMkUXXnih/v73v6tPnz7avXu3evToEeymoRX2ZguYR3lYU8psNskaZZa93sli5wB8IhcAQPgpKiqSw+FQamqq2/bU1FTt3LnT4zF79+7Vxx9/rDlz5uj9999XXl6ebrrpJtXV1WnZsmUej8nJydF9993n9/YDABqEdVHqkUceUUZGhl588UXXtoEDB3qNr62tVW1tret20y8hDofD5y8onjgcDjmdznYfhwbV9nrXvy0mw2M/2hqLUlU1djkc1kA2r1vhuegfkdqP4XC+7c0FEvkg1NCH/kE/dl6k9mG4nK/T6VTfvn317LPPymKxaPz48Tp06JAee+wxr0WpJUuWKDs723W7rKxMGRkZgWoyAIS9sC5KvfPOO5o2bZp+/etfa/369erfv79uuukmLViwwGO8t19C9uzZo4SEhHY9ttPpVHFxsfLy8mQ2h/0sSb8rqmwoSllMUsmJEx77McrUsObU93vy5SixBbyN3QXPRf+I1H6sqKgIdhM6rb25QCIfhBr60D/ox86L1D4MxVzQu3dvWSwWFRYWum0vLCxUWlqax2PS09MVHR0ti+Xk2qRnnnmmCgoKZLfbZbW2/JHTZrPJZuNzJgB0lbAuSu3du1fPPPOMsrOzddddd2nz5s26+eabZbVaNW/evBbx3n4JGTx4sJKSktr12A6HQ3l5eRoyZIhb4kPb2IqrJO2XNcqsnj17euzHhJjDOlFdrb79+mvo6UzD8Ybnon9Eaj+Gw9oZ7c0FEvkg1NCH/kE/dl6k9mEo5gKr1arx48crNzdXM2fOlNRQNMzNzdWiRYs8HjNlyhS98sorcjqdrqLi999/r/T0dI8FKQBA1wvropTT6dSECRP00EMPSZLGjh2rb7/9VqtWrfL4RcTbLyEWi6VDHzzMZnOHj410jRfekzXK4rUfm67AV+cUfdwKnov+EYn9GA7n2t5cIJEPQhF96B/0Y+dFYh+G6rlmZ2dr3rx5mjBhgiZOnKgVK1aosrLSdTW+q6++Wv3791dOTo4k6cYbb9Qf/vAH3XLLLfrNb36j3bt366GHHtLNN98czNMAgIgW1kWp9PR0jRgxwm3bmWeeqb/+9a9BahHayl7fUJWyWrwPjW8qStXWsdA5AO/IBQAQnmbNmqVjx45p6dKlKigo0JgxY7R27VrX4ucHDhxwm2aZkZGhDz74QLfeeqvOPvts9e/fX7fccot++9vfBusUACDihXVRasqUKdq1a5fbtu+//14DBgwIUovQVnZHQ6EpOqrllfea2KIaPmTU1IXH4psAuga5AADC16JFi7xO11u3bl2LbZMnT9Y///nPLm4VAKCtwnqFxltvvVX//Oc/9dBDDykvL0+vvPKKnn32WS1cuDDYTUMr7PUNRam2jJSqqacoBcA7cgEAAAAQmsK6KHXOOefob3/7m1599VWdddZZuv/++7VixQrNmTMn2E1DK+oaR0pZo3wVpZpGSjF9D4B35AIAAAAgNIX19D1J+tnPfqaf/exnwW4G2qlppFS0j5FSNteaUoyUAuAbuQAAAAAIPWE9UgrdV219G0ZKRTVN32OkFAAAAAAA3Q1FKYSkpoXOfa0pZYtmoXMAAAAAALorilIISXWuhc69X33PNVKKNaUAAAAAAOh2KEohJNnbsdB5LVffAwAAAACg26EohZBkb8uaUtGMlAIAAAAAoLuiKIWQVOdo/ep7rpFSrCkFAAAAAEC3Q1EKIcl19T1fC527rr5HUQoAAAAAgO6GohRCUtum7zVdfY/pewAAAAAAdDcUpRCS2jZ9r2GkFAudAwAAAADQ/YRUUWrPnj36yU9+EuxmIAS0ZaSUa/oeI6WAbufDDz/UsmXL9PHHH0uSPv30U11yySX6yU9+ohdffDHIrQMAAAAQCCFVlKqoqND69euD3QyEALuj9TWlTk7fY6QU0J38+c9/1qWXXqp3331XM2bM0OrVqzVjxgyddtppGjhwoG644Qa9+eabwW4mAAAAgC4WFcgHe/LJJ33uP3ToUIBaglB3cvqeSZLhMaZppNTuwgpN+7+fttgfa7XoouF9NX5AD5lMphb7q+vq9fXBUh0uqfZ4/1EWk/793wZoZL/kDp4FAE8ef/xxPf7447r55puVm5ur6dOn68EHH9Stt94qSRoxYoRWrFihyy+/PMgtBQAAANCVAlqUWrx4sdLT02W1Wj3ut9vtgWwOQlit2/Q9zyOhBvSKk8Vskt3h1K7Cco8x2w6WdKodP5yo1p+undSp+wDgbvfu3Zo+fbok6aKLLlJ9fb0uuugi1/7LLrtMOTk5wWoeAAAAgAAJaFFqwIABeuSRR3TFFVd43L9t2zaNHz8+kE1CiLK3oSjVLyVW6267QAeLqzzu/6GkWu/964jXkVAWs0lnpidpSN8EnTqQ6niFXc9v2Kfth8s6fA4APIuOjnb7EcJmsykhIcHtdnW159ctAAAAgPAR0KLU+PHjtWXLFq9FKZPJJMPwPFUrqCorJYul5XaLRYqJcY9r4nDIVFV18lizWYqN9Rx7qlNjq6okb/1iMklxcR2Lra6WnD4WCY+P71hsTY3k8LHOUxtiTVWVirXXyGZuVi2qrZXq693iMmxSRnpjX8XFyVVdqq2V0mN1xZk9PbchNrahnyXJbpfq6tx2V9sdevWTHao6UaNjpdXqkxzrNdZNTMzJ50p7YuvqGuK9sdmkqKj2x9bXS1VV7s/F5qxWKTr6ZGxtrff7bR7rcDT833kTHd0Q395Yp7PhueaP2Kiohr6QJMPQ9/sKVVrlud8y+iYrrW+yK1ZVHgqdTa/pmhr357Cv17Kv94hThep7hK92dNCQIUO0c+dOnXHGGZIapm4nJia69u/Zs0ennXaa3x8XAAAAQIgxAui7774zNm/e7HW/3W438vPzA9gi30pLSw1JRmnDV7iWf5de6n5AXJznOMkwzj/fPbZ3b++xEya4xw4Y4D12xAj32BEjvMcOGOAeO2GC99jevd1jzz/fe2xcnHvspZd6jz31KXf55T5jX/9ku7Fjxw6jvr7eMObN832/R4+evN+bbvIdu2/fydjbbvMZu+W9/z0Zu2yZ7/vdtOlk7KOP+o795JOTsX/4g+/Yd989Gfvii75jX3/9ZOzrr/uOffHFk7Hvvus79g9/OBn7ySe+Yx999GTspk2+Y5ctOxn77bc+Y9+48Erj4hWfGhev+NS4+p41vu/3pptcd/vEq5/5jP3b6CyjuKK2IbiiwmfsZ2MvMH719GeuP1+xuyf82Hjwve3Gfe98Z9z86lajxhrjNXbnGeOMa1dvNq57qeGvLDHFa+y+gSOMG/70pXHjnxv+inqne4093H+QseiVrcZvXtlq7Dla3u73iFLJkGSUlpYa/vLf//3fxvr1673uz8nJMe6++26/PZ4/uPJBB/qhvr7+5PsYOoQ+9A/6sfMitQ878x4YbugLAJGsK94DAzpSasSIET73R0dHa8CAAa7bn332mSZMmCBb02gHRJyG6XtGUNuwt6hC44LaAjQ5XmnXjiMNUyrLSyt8xtbWO1RdZdfGPce1+vN83ewjtt5haP33xzRzbP9W23Ciqk5f7j/RpvYeKK7Ss5/udd3OMbw/l09U2fXRjkLX7aYprJ6UVtfp798WuG7fZfc+MrG8pl7/8/VhSdK8czPb0uwu94tf/MLn/jvvvNPtNrkAAAAACE8mw/DxLSnIkpKStG3bNg0aNCgoj19WVqbk5GSVHj6spKSklgE+puY4HA7l5eVpyJAhsnTT6Xvv5JXq87wiSVJUbY1MxsnYmGiL5k3O1Gk9G+/Pz9P35v7xC325/4Qeu3qShsRUaOjQobLU17eYvufm1Ol7vmJbmb4nSU/l7tbT6/Zo+qRBenTWWJ+xLiE4fc9RVeX+XGyuG0zfu+9/vtVrm37Q2NNTdNNPh8toFmuuqdbGPcf1/Ib8FnfrMFtkj2psr2Ho+gmpuuvSloXx5R/u0qoNB3TJhAF64sqxDa+fU6bv3fnXf+ntbYc1ZUCcLj/3DCn25OvIUlWlWodDh05Uq7zG/f/babbIYbXJZDKpV7xVPVUnNbugpNH4D8OQZDKrvvH9xDAkS3VVy5hGhsksR2OBxpBkqamWnE1xhmt7Q6xJ9baG95OfnZ2uvlHOdr1HlJWUKLlfP5WWlnp+HwyAYOcCqVk+6EA/OBwO7d69u+F9zNNUcLSKPvQP+rHzIrUPO/MeGG7oCwCRrCveAwM6Uqq9QqZeFh/vXkjxFdfE4ZARF9ewzdOHlrbcX5PmXxL9Gdu88HWKOodTt73+qewO70Wrupg43fvzkS13NC/UtcZLbFmUTdXWGEVHNes7m+3kGkGtaU+s1XqyKNLMkIGpqv78kHYdq2w1tj33e6qK2nqVVddLMrfYF2e1KCXulPuIjj5ZHGpNVJQUH+/7udg8NqqNbwkWS9ufwxZLw+N7cay8Vmu35OvA8ZbrOBmS/vzNcdVZY/Sb6WM0eXCvFjHnnj1ApoQErVq/R3UOz+8ZPx2Zptt+MU6KatnH543J1JP/PKL13x+Tw2nIYja5nVudw6m/7ytXtTVG00an6afjBkTOF5HYWN+F1QAJmVwAAAAAwK9CuiiF4KmsrXcVpG6bOkymZpen27L/hD7eeVTHK32M1umkk1ffM7US2XXOSGtYePn7wgo5nYbM5o615USlXeU1LUdtOQ1Db2w5qOc+3eez+Df29BSd1S+5xRUCJanK7tDOgjIdK/c8wskkk1LiomVTneI+PeH2/xgoFbX12nO0QpU+ppi1ZtLAnh4LUlLDBRL+a+oZWpw1zGvxIsrSshjVZGxGipJiolRSVadtB09o/AD3xfE37StWaXWdesZbNaJvOwquAAAAAACfKErBo6rGAoLVYtainwx127dm8wF9vPOoKmt9TI/rpLrGIo3VYpY6XsvolAG94mWLMqu6zqE3thxUz/iWI69G9U9WWrL3QsXqz/bpgfd2qN7pe6RHtMUkk1oWjOwOp746UKKvDpS0u/1NCsqaps75mEIXZGNPT9GEAT08Fv6sFrNmnZPR6n1YzCbJQx+2Jspi1o+H9dG7/zqi+/5nu4b0SXDbv7OgXJKUdWbfxscAAAAAAPgDRSl4VGVvKDjF2VpOU4q3NTxtKrqwKNU0Uio6iEUpi9mkYamJ+uZQqX771288xlijzJoz6XQN6t1yKtvh0ho9s26PpIZpeJ7KGekpsbp92hmaOiLV4yimo2U1+nBHoQrLPI+EijKbNCw1Qaf1iPM4ksrplIoqqrVz70Glp6fLbPY+Yqir2KLMGtwnXj1OnYbYyBplVmJMG6cjdpGfjkjVu/86on/9UKp//VDqMeaSs1IllQS0XQAAAAAQzkK6KBWMqUZo0DRSKi7ae1GqK0dKnZy+Z5a6bpZgq26+aKie/XSPx5FOFTX12n20Qi9+lu/zPhacN1B3XXpmh57PfZNiNGfSgNYDfXA4EpSuEg0dmh45ayG10/Sz+6nOYai40nPxLy05VucN6a28vJLANgySyAUAAABAuApKUerVV1/V7NmzPe67/fbb9dhjj0licdtgqqxtLErZWj5FEgMwUso1fc/DwtSB9NMRqfrpiFSP+wzD0Lrvj+ntrw55XRPqnMyeuubcTL5Uhziz2aTLx5/mM8bh64qS6BByAQAAABDZglKUuvHGG5WSkqJLLrnEbfutt96q1157zfVFpLy8PBjNg6Tqusbpe9Ygj5SymNV1j9I5JpNJF57RVxee0TfYTQG6JXIBAAAAENmCMgzlL3/5i2bPnq0NGza4tv3mN7/R66+/rk8++SQYTcIpXCOlPBSlEgIwUqq2+ULnAMISuQAAAACIbEEZKXXZZZfp6aef1s9//nN9+OGHev755/X222/rk08+0bBhw4LRJJyiumlNKWvLp0hTUaqmzql6h1NRHSwc5R0t10Pv7/Q44qr5mlJVHbp3AKGOXAAAAABEtqAtdH7VVVeppKREU6ZMUZ8+fbR+/XoNGTIkWM3BKSrtrU/fkxpGVCXHdawo9coXB/XxzqNe9yfYopQUE8X1zoAwRi4AAAAAIlfAilLZ2dket/fp00fjxo3T008/7dq2fPnyQDULXriuvuehKGWNMstqMcvucKrCXq/kuOgOPcbR8hpJ0uXjT9MFZ/RpsX9EepJsHq7+B6D7IhcAAAAAaBKwotRXX33lcfuQIUNUVlbm2s9VykJDlWuklOenSLzNInuVs1OLnRdV1EqSzhvaWz87u5/HGK54BoQXcgEAAACAJgErSrFobWAVltXo6uc3uUYjnapfSqxeue7fvI5y8jVSSpISYqJ0oqpO5TWdKUrZJUm9E2wdvg8A3Qu5AAAAAECToK0pha61cc9x7Sr0fhn1E1V12pRfrJ+OSPW4v6rx6nvN149qLr5xBJU/RkpRlAIAAAAAIPJQlApTTSOdzh3cS/f9fKTbvrv+9o02559QaXWd9+PrGo6P9bKmU9MV+DpalKpzOFVS1fD4vROsHboPAAAAAADQfVGUClNNa0L1TrBpaGqi27705FhJJ1RSZfd+fGOxKd7mffqeJFV0sCh1vHHqnsVsUo84ilIAAAAAAEQac7AbgK5RU+d9TaiUxnWkfI6UahxpFet1ofPOFaWapu71irfKbGZBYwAAAAAAIg1FqTB1sqjUsiiVHNuWolTjSClvC513ck2pY6wnBQAAAABARKMoFaZcRSkPa0I1FaWa1nTyebyXotTJkVKODrWvqLyxKJVIUQoAAAAAgEgUUUWphx9+WCaTSYsXLw52U7qc7+l7DWs4lbRh+l68l+l7TWtKdX6kFOtJAQisSMoFAAAAQCiLmKLU5s2b9f/+3//T2WefHeymBISvNaHaM33PU1FLkhIaF0Dv8JpS5Q0Lnfdh+h6AAIq0XAAAAACEsoi4+l5FRYXmzJmj5557Tg888IDXuNraWtXW1rpul5WVSZIcDoccjvZNU3M4HHI6ne0+zl+arp5ns5hatCGpsaBUUmX32r7KxqJWTFTL4yUpNrqhnlleU9ehczxWXiNJ6hkf7fP4YPdjOKAP/SNS+zGczretuUAKr3wQDuhD/6AfOy9S+zCUz3flypV67LHHVFBQoNGjR+upp57SxIkTWz3utdde0+zZszVjxgy99dZbXd9QAIBHEVGUWrhwoS677DJlZWX5/CKSk5Oj++67r8X2PXv2KCEhoV2P6XQ6VVxcrLy8PJnNgR+Qdry0XJJUVnxMu3fXuO0rKWkYpVRcUaPdu3e3ONbhNGSvd0qSjhzcr8pjLUdLVZxouP+iknKP99Gag8dKJEn1FSe0e7f30VbB7sdwQB/6R6T2Y0VFRbCb4DdtzQVSeOWDcEAf+gf92HmR2oehmgvWrFmj7OxsrVq1SpMmTdKKFSs0bdo07dq1S3379vV6XH5+vm677Tadd955AWwtAMCTsC9Kvfbaa9q6das2b97cauySJUuUnZ3tul1WVqaMjAwNHjxYSUlJ7Xpch8OhvLw8DRkyRBaL5ylwXerj45KqNfD0/ho6NNVtV3JZjaSDqrQ7NXjwEJnNJrf95TV1kvZKks46c5hsUS0/dB10HJV0VA5ztIYOHdru5lW+XyhJGjXkdA0d0ttrXND7MQzQh/4Rqf3YNEKou2tPLpDCLB+EAfrQP+jHzovUPgzVXLB8+XItWLBA8+fPlyStWrVK7733nl544QXdeeedHo9xOByaM2eO7rvvPv3v//6vSkpKAthiAMCpwroodfDgQd1yyy368MMPFRMT02q8zWaTzdZyjSOLxdKhDx5ms7nDx3ZWdeP0u4SY6BaP3yOhoS+chlRVbyg51v1pUOtoWGvKYjYp1holk8m9aCVJibENC5RX2h0dOr/jlQ2jtfomx7Z6fDD7MVzQh/4Rif0YDufa3lwghVc+CBf0oX/Qj50XiX0Yiudqt9u1ZcsWLVmyxLXNbDYrKytLGzdu9Hrc7373O/Xt21fXXnut/vd//7fVx/E2nRsA4B9hPe54y5YtOnr0qMaNG6eoqChFRUVp/fr1evLJJxUVFRXS8+M7q+nqe7HRLT9ExERbXNtLq1oudt50Rb04q8VjQUqSEmwdv/pevcOpE1UNRaneLHQOoItFci4AgHBVVFQkh8Oh1FT3GQGpqakqKCjweMyGDRv0/PPP67nnnmvz4+Tk5Cg5Odn1l5GR0al2AwDchfVIqYsuukjffPON27b58+dr+PDh+u1vfxuSv/r4y8mr73k+x5S4aFWXOlRSbdfpivN4rLcr70nNi1Lev8xt2V+sFz7Ll8NhuG2vczhlGJLZJPWIs7Z+MgDQCZGcCwAADcrLyzV37lw999xz6t3b+9IRp/I2nRsA4B9hXZRKTEzUWWed5bYtPj5evXr1arE93FS7Ckue/4uTY6N1pLRGpdUtR0o1FaXivRwrSfGNRamK2no5nUaLdakk6f/87VvtLCj3eh+ZveJl8XAcAPhTJOcCAAhXvXv3lsViUWFhodv2wsJCpaWltYjfs2eP8vPzNX36dNc2p7Phwj5RUVHatWuXBg8e3OI4b9O5AQD+EdZFqUhlGIaqfEzfkxqKUpJU4mH6XpW9YUqet1FW0smRUpJUVedwuy1JO46UaWdBuawWs+752ZkepwFO8bHAOQAAAOCN1WrV+PHjlZubq5kzZ0pqKDLl5uZq0aJFLeKHDx/eYtTs3XffrfLycj3xxBOMfgKAIIm4otS6deuC3YQuV+cw5HA2TJnzNX1Pkko6OFIqJtosi9kkh9NQZW19i6LUW18dkiRdOLyP5k7ObPc5AEBXioRcAADhLjs7W/PmzdOECRM0ceJErVixQpWVla6r8V199dXq37+/cnJyFBMT02J0bEpKiiQxahYAgijiilKRoGnqnuR9XaimkVJlPopSvkZKmUwmxVstKqup1/YjZSqvOXk/hiG9ve2wJOkXY09r/wkAAAAArZg1a5aOHTumpUuXqqCgQGPGjNHatWtdi58fOHBAZnNYX9cJALo9ilJhqKquYfpdlNmkaIvnRJzSuMB4SeNV8NyOb5y+F2/zvfhvYky0ymrqNf/FzR73J8VE6cLhfdrcbgAAAKA9Fi1a5HG6ntT6qNjVq1f7v0EAgHahKBWGqtsw0sn3mlJN61H5fnpcMSFDqz/fJ8PDPovJpBsvGCxbFFe1AgAAAAAALVGUCkNVrivvtV6U8nj1vdq2jZS6JWuobska2tFmAgAAAACACMYk6zBU3cqV96S2LXTua6QVAAAAAABAZzBSKgydnL7n/b83JbZhTalDJ6r13r+OuO3bVVguyffV9wAAAAAAADqDqkMYasv0vR7xDSOlDpVUa+ErWz3GJNh4egAAAAAAgK5B1SEMVTdefc/X9L0z05L07/92ur4vrPC4v0dctC4dld4l7QMAAAAAAKAoFYaq7U5JvteEMptNemDmqEA1CQAAAAAAwA0LnYehKnvDSClf0/cAAAAAAACCiaJUGHItdO5j+h4AAAAAAEAwUZQKQ9V1TVffoygFAAAAAABCE0WpMNSWq+8BAAAAAAAEE0WpMMT0PQAAAAAAEOooSoWhk9P3uLgiAAAAAAAITRSlwhDT9wAAAAAAQKijKBWGquvqJTF9DwAAAAAAhC6KUmHItaYUI6UAAAAAAECIoigVhpi+BwAAAAAAQh1FqTDkWuic6XsAAAAAACBEUZQKQ0zfAwAAAAAAoS4q2A1Ax+w4Uqalb3/rmqrXXFFFrSQpzsp/LwAAAAAACE1ULbqpx//xvTbnn/C6P85qUZ9EWwBbBAAAAAAA0HYUpbqhQyXV+nhnoSTpiSvHKCXO2iJmSN8EJdj47wUAAAAAAKGJqkU39OoXB+Q0pMmDemnGmP7Bbg4AAAAAAEC7UZQKUeu/P6ZH/r5Tdoezxb4fTlRJkv793wYEulkAAAAAAAB+QVEqRP35n/u1/UiZ1/2n9YjV1JGpAWwRAAAAAACA/1CUClHHG6+gd9vUYZqQ2bPF/jNSExVtMQe6WQAAAAAAAH5BUSpEFVXYJUn/NqiXx6IUAAAAAABAd8ZQmxDVNFKqV4ItyC0BAAAAAADwP4pSIaja7lCl3SFJ6p1gDXJrAAAAAAAA/I+iVAg6XtkwSsoaZVaCjRmWAAAAAAAg/FCUCkHHG9eT6h1vlclkCnJrAAAAAAAA/I+iVAhqGinFelIAAAAAACBcUZQKQUXlDSOlerGeFAAAAAAACFMUpUJQUeNIqd6MlAIAAAAAAGGKVbRDUNOaUoyUAgA8vS5PG/cc97gvMSZKN180VMPTkgLcKgAAAKDzwnqkVE5Ojs455xwlJiaqb9++mjlzpnbt2hXsZrXqeEXjSKl4RkoBgD9013xQUmXXo2t36X93F3n8e/+bAv3Hi5t1otIe7KYCAAAA7RbWI6XWr1+vhQsX6pxzzlF9fb3uuusuTZ06Vdu3b1d8fHywm+fV8UpGSgGAP3XXfFBY1vAjRaItSvfNGNli/1Mf52lfUaWufWmzJmT2bLE/ymzS5eNP06A+CV3eVgAAAKC9wrootXbtWrfbq1evVt++fbVlyxb9+Mc/DlKrWnesnKvvAYA/dfd8kJ4So1+OO63F/uFpSZr59GfaeqBEWw+UeLyPvKMVevbqCV3ZTAAAAKBDwroodarS0lJJUs+eLX9NlqTa2lrV1ta6bpeVlUmSHA6HHA5Hux7L4XDI6XS2+zjp5JpSPWKjOnR8OOlMP6IBfegfkdqP4Xq+3SUfFJZVS2q48IWn489IjdeaBZP0928LZJyyb//xKv1je6GOVdR2+//HSH39+Rv92HmR2oeRdr4AgMCJmKKU0+nU4sWLNWXKFJ111lkeY3JycnTfffe12L5nzx4lJLRv6oPT6VRxcbHy8vJkNrd96S6nYeh449X3yo8d0u7KwnY9brjpaD/iJPrQPyK1HysqKoLdBL/rLvlAknbsK5Ek2Yxa7d6922NMrKRfDm55v9vizPrHdqm4rNLrsd1FpL7+/I1+7LxI7cNwzAUAgNAQMUWphQsX6ttvv9WGDRu8xixZskTZ2dmu22VlZcrIyNDgwYOVlNS+Kxs5HA7l5eVpyJAhslgsbT7uRJVdTmOvJGncyDNkjYqcDzyedLQfcRJ96B+R2o9NI4TCSXfJB5Jk7N4p6bgG9+utoUOHtuvY6thSSUdkNyztPjbUROrrz9/ox86L1D4Mx1wAAAgNEVGUWrRokd599119+umnOu20lmtyNLHZbLLZWq7jZLFYOvTBw2w2+zy2pq7lUOiCsoape8mx0Yq1Rbf7McNRa/2I1tGH/hGJ/Rhu5xqq+cCbosYLX6Qmxbb72OS4hotlVNTWh8X/YyS+/roC/dh5kdiHkXSuAIDACuuilGEY+s1vfqO//e1vWrdunQYOHBjsJrk88O52/XHDPq/7ufIeAPhPKOcDX5oWOu+T2P4LXyTENKT4itp6GYYhk8nk17YBQChYuXKlHnvsMRUUFGj06NF66qmnNHHiRI+xzz33nF5++WV9++23kqTx48froYce8hoPAOh6YT03bOHChfrzn/+sV155RYmJiSooKFBBQYGqq6uD3TT9Y7vvtaKyzkwNUEsAIPyFcj7wpTNFqcTG0baGIVXZWaQYQPhZs2aNsrOztWzZMm3dulWjR4/WtGnTdPToUY/x69at0+zZs/XJJ59o48aNysjI0NSpU3Xo0KEAtxwA0CSsR0o988wzkqQLLrjAbfuLL76oa665JvANaqa4cUrG+zefpwG94tz2mU0mxVoZJg0A/hLK+cCXo41Fqb4dKErFRJtlMZvkcBqqqK1XvC2sUz6ACLR8+XItWLBA8+fPlyStWrVK7733nl544QXdeeedLeL/8pe/uN3+4x//qL/+9a/Kzc3V1VdfHZA2AwDchfUnVMM49QLZoaGmzqGK2npJUv8esXxRAIAuFqr5wJfaeodKq+skdWyklMlkUoItSqXVdSqvqVdq+9ZnB4CQZrfbtWXLFi1ZssS1zWw2KysrSxs3bmzTfVRVVamurk49e/b0GlNbW6va2lrXbRZ9BwD/Cuvpe6GqaZRUtMWkpBgKUgCAlooqTuaK5NiOXfgiwXZyXSkACCdFRUVyOBxKTXVf8iI1NVUFBQVtuo/f/va36tevn7KysrzG5OTkKDk52fWXkZHRqXYDANxREQmCpqJUz3grC88CADxyrSeVYOtwrkhsWuy8pnsXpXJ3HNWznxxWzIYSj31x+fjTNGNM/yC0DEB39fDDD+u1117TunXrFBMT4zVuyZIlys7Odt0uKyujMAUAfkRRKgiKKhq+aPSMb/90DABAZHAVpZK8f1lqzcmRUnVeY/KLKvXUx3mqrvNcuJo8uLfm/tuADrehswzD0L3vbtfhkhpJnhem/+pAibLOTPU6Hd4wDH1zqFSVtZ4XfB/YO15pyb772V7v1Ikqu8d924+U6cnc3dp+2PO0HrPJpIG94zWoT7wsZs8FxiF9EnTOwJ6KjW65pqShhufDDyeq5HB6nopqizKrZ7xN0RbvBUyn06kjRyqVX1cosznwg+UTbFHqnWhTlJc+SImzqmd8cK8+XOdwaueRcjk8TPk1SRrUOzbwjYJHvXv3lsViUWGh+8WDCgsLlZaW5vPY3//+93r44Yf10Ucf6eyzz/YZa7PZZLPxmR0AugpFqSBoGinVK8gfvAAA7VRZKVk8XIjCYpGa/9JeWXny3w6HTFVVJ481m6XYWM+xzRw/WixbXa36JDT7MlRV1XA5PU9MJikuzi22p6lOsfYaVZ0okyqTPMa++Nk+vfvFHpm93O/6rfn61bj+irM2fmSorpacTs9tkKT4+JP/rqmRHD6u/NeG2J1HynTiaIlsMTF68JejZLGYZbbXytQYu/KTPB04XqH3/pmnKyY0jl6Ii2s4R0mqrdWL677XYx9877EJNdFWWSwW/eGqsbp4WC+prmUBb+v+Yt382lc6VGuSYWoo5kQ76hR1Snubl3lqo6LlNFtcsfv2V2rffs/d0Dw2ylGvaIf3kW32qGg5OhBrcTpkrW86t/wWsXWWKNVbojzEttQ81ux0yOYjtt5iUZ0lus2xfXomKik2WianU9a6Wrf9fRJtWvSTIRqT0UOKjpasjZ+jnE6pulp1Dqe+zC9WYZn7cYbFIqfVJovZpKF94zU43iyzhxF3ecfKlf3Xb7XzRGMbDUOxp7ShV0K0rh3XQ3GxKTJFW91e96bKShWW12jvsUrVO9xfI06zRU6bTZV2h46W1UqVFQ3HNDbDJLlGARoms+ptMTKZJJNMiq6pOiWu8d+mhuejwxbj2hldUyOTDI/xkln1MbHqnWDVNVMGtu/9JASvVGq1WjV+/Hjl5uZq5syZkhoKr7m5uVq0aJHX4x599FE9+OCD+uCDDzRhwoQAtRYA4A1FqSBwFaUSKEoBQLfSr5/n7ZdeKr333snbffs2fOGTZJF0RvPY88+X1q07eTszUyoqanGXV0o6M22oXpvy15MbR4yQ9nupbIwYIX333cnb55yjZ7dvb/j3/z0ldsAAKT9fklRQVqPXX7lTowt2e7zb47FJKl1acLIodckl0vr1ntsQF+deZPvVr6T33/ccK7l/IZ47V3rzzRYhZ0raIWne4+/pF2P7y2KxSNdcI730kiTp502Bzc/x6FGpTx9JUvlNN+s/XnhW/+GlCb+64y/a4kzWole+0nPfrtGF//Nyi5hxkjZImnbtSu3pmylJ+s1nb+jmDa94PbWjuZ+qblzDF97YFcvV8767vca+83//rL/3Hq5vD5dq5mdv6b/eecpr7HN3PKntY8+TJJ2z7h1dtWqZ19jHrv2dPh/3E0nSuVs/1u3PL/Ua++S/36VPJl8qSRr/7ee6+5k7vMY+e8WtWnv+ryRJI7/fqvufuNlr7Eszb9LbP71KhqT0Xd/o6Sdv9Bq7YspsrfjRHB0urdHQY/v19xcWeo1dc/4s/b+f3SBJSi0u0Ks5sxUtabKH2JfHXqalUxset2dVqbY+NcfjfY6QdN1ZF+neX96ulLhoxdir9dHSy7224b0zpmjhzJOLbOc/8jOdJmm8h9iPB03Qf/z6Xtft7ct/pbhTCl5N/plxlq686mHX7S1PXqVe1Z5H4X2dNlQz5p188m945j90WtlRj7Hf9zpdU697WsNSExqKUuecIzW9R5yq2XuEpIbXfQjKzs7WvHnzNGHCBE2cOFErVqxQZWWl62p8V199tfr376+cnBxJ0iOPPKKlS5fqlVdeUWZmpmvtqYSEBCUkJATtPAAgklGUCoKmxWuDPUQdABB8NfVO+Zo41pEr77VHU07ypbymXunJrd+XIamq2aLqNqfhtw8aEzPiWw9q9Ns3/6WKpB6SpKk7CzXDR+zr/zlZ2ZtK9Pa2w/q+sEIX+oh9e9GPFDOmcarPvZsaKlVe9E2MkVIaR8S1ku9/Pqa/fn5BYylj5Q7pHe+xC348SLpsTMON6m3SKu+xt08bLv16SsONNw5Lz3uPvfmiobr5msbY90qkZ7zHXv/jwbr+psbYdXXSE95j552bqXlNsZut0pPeY2+8YLB+dN1k1dY7Fbs7WXrBe2xJdZ32FjUUQO2lVd4DJfVLidH5w/qous6hgt0VrcZ+eseFDZ/RKisl73U8Wcwmj9MtPembaNOlo9Jki7Kob6JN0Su8T5/slxKrhRcOdtVsY5+xeJu5qj6JNi04b6ArNuHFKMnLxeFS4qI1b/KALn9PCaRZs2bp2LFjWrp0qQoKCjRmzBitXbvWtfj5gQMH3KaqPvPMM7Lb7br8cvdi47Jly3TvvfcGsukAgEYmozteJztAysrKlJycrNLSUiUlte9a2g6HQ7t379bQoUMbftVt5o43v9brX/6g26YO06KfDPVnk8OOr35E29CH/hGp/diZ98Fw4uqHw4c994OP6XsOh0N5eXkaMmRIw3On2fS9bw+V6tePf+T1cZ0mk+6ffc7JaWntnL73yPvbtfrz/br2R5m6bdpwj7HnP/aJCgpO6JVrz9H4Ae6XRZ/6f9frYHG1/nTzhZqQ2bjvlOl7RRW1mrlyg45XNEx5qrae7AdbvV1mp1Ox0RbFWlt+Ca+xxiraYta5g3vp3/rFKUru51Zb79Tv/me7TCbp+TnDNHH0iIY+rK2V6k8Wv3775r/0zteHXbero22uOUvW+jrFmg29vXCKMnt7KGzFxqrekN75+rAKi8pkrm85Ha5Pok3TR/dTdEJ8w/+fJNntHqf6ucTEnJzq2Z7YurqGeG9sNikqqv2x9fVyVFW5Pxebs1obpsQ1xqrW8yieFrEOR8PUS2+aT7NrT2zjlLxTHTxepaMVNTKiomU0izXXVCsm2qLhaUkt1+2KimroC0lOh1MVJZ6rNhaTSfHxMa5YGYZrxGMTt9ez1ep92m6LO/cxxfdUbZzi6zG2ne8RbY0tKyxUclpaxOcCibwIILJ1xXsgI6WC4OT0vfD5pQoAIkJ8vPs6SL7imjgcMuLiGradUgjYfrhM1dYYnd4zThed2bfF3fSMs+pnZ6ef3ND8C2Vr4uJkS0lStTVGxSar13YfK69VbbRNvfr2bBFjTU5UdYWh8uZX74t1X+j5Xwcr9IPdIllbFmtroxqKBtWS5KkmU9eQD//7q0P676+8nIc1RmMzktUjLvrkNpvtZOFA0l2/nqCxZx6R3eF5ravRp6UoMyPFywM0fBj65bjTvO733C7ryQKKP2Ojo08WfPwZGxUlxcd7fS62iI1q40dEi6Vtr4n2xprNHmMz4uPVmeuemS1mJfVKaVuwydSyDT5ez20+t66Mbed7RJvFssA7AKBrUJQKAqbvAQAkaffRcknST4b31bLpI/1+/66r79V4Xgy7yl6vKnvDYt29PUzpSbQ1FDzKaryP8impath37uBeeuGac1rstzucOlFpV02d54LR8cpafbT9qPYVeZ5WFWUx67ofZUr2lutuNUmOi9aVE0/3uh8AAAChiaJUEHD1PQCAJO0+2lCIGZraNQvsJsY0FqVqPRelisob8lFMtFnxHkY6NR1f5qWoJUml1Q1FqR7xVsV4WF8nJtqipBhfo3kSde7g3j72N02f9V6UAgAAQPfkfZVFdBmm7wEAJCmvsSg1pE/XFKUSGkc6eRspdayiYd2g3gk21+Xom0uKbTi+vA0jpVJi2ziNDAAAAGhEUSrAauocrl+smb4HAJGryl6vH040LOQ8NDWxSx4joXGkU7m3kVLNilKeuEZKVbc+UioljqIUAAAA2oeiVIA1jZKKtpiUFMPsSQCIVHuPNVxRq2e8tct+pHCtKVXreaRT60Wp1kdKNRWlkhkpBQAAgHaiKBVgTUWpHnFWj1MlAACRoWmR8yF9u2bqntRsTSlv0/fKG4pSfTwsci7J9eNJuY81pUqqGvJaSiyjfwEAANA+FKUCrOlXadaTAoDI5lpPqguLUk0jpSprHR73N+WkPgmeC0pNC5T7vPpe00gppu8BAACgnZg/1kWe37BPR4+VqHfBPpnNJ0dEbT9cJokr7wFAJNhVUK5PdhaqqKhlPvhk5zFJ0tCuLEo1jnSyO5yqrXfIFuV+dbymq+/19jZSKrb1kVJM3wMAAEBHUZTqIo/943vVOQxJxz3u75vESCkACHffHCrVw2t3Nd7ynA/O6KJFziUp3noyzVfU1MuWcEpRyh9rSlWx0DkAAAA6hqJUF/n56H4qKS1VYmKSzKesHWWLNuvaHw0KUssAAIFyes84zRzTT+XlZR7zwWk94/Rvg3p12eNbzCbFWy2qtDdc+fXUqeOdvfqeYRiu6XusKQUAAID2oijVRR791Sjt3r1bQ4cOlcViaf0AAEDYmTiwp8afnhzUfJAQE6VKu8PjFLyiisbpe62sKeVtpFSl3SGH05DE9D0AAAC0HwudAwAQxpoWO6+odS9KVTeOnpK8rynVNFKq0u5QvcPZYn/TlfesUWbFRPORAgAAAO3DSCkAAMJYQuNop6c+3q03vvzBtb2mruGKfLYosxJtnj8ONK0pJTUUtVLi3EdUlTStJxUbLdMpUxMBAACA1lCUAgAgjKUnxehrSZ/leV5ofUCvOK8FpaYRUDV1TpXXtCxKNV15j0XOAQAA0BEUpQAACGNLp4/QhMweqm9c+6k5k6QLh/f1eXxiTLRq6mpVWl2njFP2NRWlWE8KAAAAHUFRCgCAMNYvJVbXndfxK74mxkTpWHmtx4XSm6bvJXPlPQAAAHQAq5ICAACvfF2Br6S6YaFzpu8BAACgIyhKAQAAr5quwFfmYaQU0/cAAADQGRSlAACAV0mx3kdKlTa7+h4AAADQXhSlAACAV0lNI6Wqva8pxfQ9AAAAdARFKQAA4FWijzWlmqbvJTFSCgAAAB3A1fcAAIBXTSOlNu8/oWfW7XHbt6+oUpKUEsfV9wAAANB+FKUAAIBXvRJskqSvD5bo64MlHmP6NMYAAAAA7UFRCgAAeHXZ2enKL6pUcaXd4/5BfRJ0ZnpigFsFAACAcEBRCgAAeJUUE60ll54Z7GYAAAAgDLHQOQAAAAAAAAKOohQAAAAAAAACjqIUAAAAAAAAAo6iFAAAAAAAAAIuIopSK1euVGZmpmJiYjRp0iRt2rQp2E0CAAQYuQAAAAAILWFflFqzZo2ys7O1bNkybd26VaNHj9a0adN09OjRYDcNABAg5AIAAAAg9EQFuwFdbfny5VqwYIHmz58vSVq1apXee+89vfDCC7rzzjvbdB92u112u73FdrPZrKioKLe4Jg6Hw3WcxWKRyWRSdHS0x9hTnRpbV1cnwzACGitJVqu1Q7H19fVyOp1+iTWbzW2OjY6Olslkanesw+GQw+HwS2xUVJSrzaEQ63Q6Xc/DpudicxaLxbXN6XSqvr7e6/0GItYwDNXV1fkltvnr0x+xTa/p+vp6t3709Vr29R5xqlB9j/DVju7EH7lAIh+0N9Zf+cDhcLg9JvmAfBCsfND89RwdHd3m9/hwyAcAAHSFsC5K2e12bdmyRUuWLHFtM5vNysrK0saNG1vE19bWqra21nW7rKxMkvTYY4/JZrO1iB86dKiuuuoq1+1HHnnElbQNw1BxcbF69uwpk8mkzMxMzZs3zxW7fPlyVVVVeWx3v379tGDBAtftp556SiUlJR5j+/Tpo5tuusl1e9WqVTp27JjH2JSUFN1yyy2u288//7wOHz7sMTYuLk6333676/af/vQn5efne4yNjo7WXXfd5br96quvavfu3R5jJWnZsmWuf7/55pvavn2719g77rhDTqdTDodD7777rrZt2+Y19rbbblN8fLwk6f3339eXX37pNfaWW25RSkqKJOkf//iHx+dDkxtvvFF9+/aVJK1bt07r16/3Gnvdddepf//+kqTPPvtMH330kdfYefPmKTMzU5K0adMm/f3vf/caO3v2bA0bNkyStG3bNr399tteYy+//HKNHDlSkvTdd9/pjTfecHsuNjdjxgyNGTNGkvT999/r1Vdf9Xq/l1xyiSZOnChJys/P10svveQ1NisrS1OmTJEkHTp0SH/84x+9xp5//vm64IILJElHjx7VM8884zV28uTJmjp1qiSppKRETzzxhNfYCRMm6LLLLpMkVVZW6ve//73X2DFjxmjGjBmSGt43cnJyWsQ0vaanTJmiWbNmubY/8MADXu/X13vEqUL1PWLfvn0eY7uT9uYCiXzQXCjkA8Mw9Ktf/cpVgHnnnXfIByIfBCMfNH89jxw5Ur/+9a9d+8I5H7z88sse4wAA6KywLkoVFRXJ4XAoNTXVbXtqaqp27tzZIj4nJ0f33Xdfi+0nTpxw+zW3SUFBgduH7ePHj7t+ATQMQ9XV1SouLpbJZFJsbKxbbFFRkWpqajy2Oyoqyi322LFjKi8v9xhrGIZb7NGjR3XixAmPsXV1dS1ii4uLPcZWVVW5xRYWFnqNPbW9BQUFXmMlucUeOXLEZ2xeXp4qKiqUl5enw4cPtxobFxcnSa3G7tmzR0lJSW2K3bt3r0pLSyU1fKD2Fbtv3z7XB8cffvjBZ2x+fr7rA+nBgwdbjW36AnHgwAGfsfv373c9X/fv36/i4mK352JzBw4ccH1xy8/P93m/Bw8eVI8ePSS13g8//PCD6//Z13On6b6aYo8fP+4z9vDhw67YsrKyNsdWVVW1OdZut3uMbXpNn/q693W/vt4jThWq7xHeYruT9uYCiXzQXCjkA8MwdOLECeXl5clsNpMPyAdBywfNX89HjhyJmHzgrXgFAEBnmQxfY/C7ucOHD6t///76/PPPNXnyZNf2O+64Q+vXr9cXX3zhFu/pl/GMjAwVFBS4PrA219p0jby8PA0ZMoTpGp2INZvN2rNnj4YMGSLDMJiu0c5Yp9Op2tpat+dic0zXaHts02t62LBhbiNlwn26RmlpqdLS0lRaWurxfbA7aG8ukMgHpwp2PnA4HNq/f7+GDh0qi8XC9D3yQVCn7zX1YSRN3zt+/LhSU1O7dS7wl7KyMiUnJ9MXACJSV7wHhvVIqd69e8tisaiwsNBte2FhodLS0lrE22w2j9MyYmNjFRsb2+rjNY9xOByKiYlRbGxsiw9+p8a2xtPxkRLrcDhkNpvdPnwGug3dPdZsNvt8LjaPbf4BtLX77YpYSW4f2kMptuk1bbPZ3PqxPa/lrortyudPOKwp1d5cIJEPQi3W4XC48gD5oOOx5IPOx/p6PYdzPoiJiWlzLAAA7RHWV9+zWq0aP368cnNzXducTqdyc3Pdfi0HAIQvcgEAAAAQmsJ6pJQkZWdna968eZowYYImTpyoFStWqLKy0nUFJgBA+CMXAAAAAKEn7ItSs2bN0rFjx7R06VIVFBRozJgxWrt2bYsFbwEA4YtcAAAAAISesC9KSdKiRYu0aNGiYDcDABBE5AIAAAAgtIT1mlIAAAAAAAAITRSlAAAAAHRLK1euVGZmpmJiYjRp0iRt2rTJZ/wbb7yh4cOHKyYmRqNGjdL7778foJYCADyhKAUAAACg21mzZo2ys7O1bNkybd26VaNHj9a0adN09OhRj/Gff/65Zs+erWuvvVZfffWVZs6cqZkzZ+rbb78NcMsBAE0oSgEAAADodpYvX64FCxZo/vz5GjFihFatWqW4uDi98MILHuOfeOIJXXzxxbr99tt15pln6v7779e4ceP0hz/8IcAtBwA0iYiFzjvKMAxJUllZWbuPdTgcqqioUFlZmSwWi7+bFjHox86jD/0jUvux6f2v6f0wUpEPgos+9A/6sfMitQ9DMRfY7XZt2bJFS5YscW0zm83KysrSxo0bPR6zceNGZWdnu22bNm2a3nrrLa+PU1tbq9raWtft0tJSSR3LBwDQ3XVFPqAo5UN5ebkkKSMjI8gtAYDgKi8vV3JycrCbETTkAwAIrVxQVFQkh8Oh1NRUt+2pqanauXOnx2MKCgo8xhcUFHh9nJycHN13330ttpMPAESy48eP+y0fUJTyoV+/fjp48KASExNlMpnadWxZWZkyMjJ08OBBJSUldVELwx/92Hn0oX9Eaj8ahqHy8nL169cv2E0JKvJBcNGH/kE/dl6k9mEk54IlS5a4ja4qKSnRgAEDdODAgZAp0AVSpL4GmnD+kX3+En1QWlqq008/XT179vTbfVKU8sFsNuu0007r1H0kJSVF5JPV3+jHzqMP/SMS+zESP3SfinwQGuhD/6AfOy8S+zDUckHv3r1lsVhUWFjotr2wsFBpaWkej0lLS2tXvCTZbDbZbLYW25OTkyPuOdBcJL4GmuP8I/v8JfrAbPbf8uQsdA4AAACgW7FarRo/frxyc3Nd25xOp3JzczV58mSPx0yePNktXpI+/PBDr/EAgK7HSCkAAAAA3U52drbmzZunCRMmaOLEiVqxYoUqKys1f/58SdLVV1+t/v37KycnR5J0yy236Pzzz9fjjz+uyy67TK+99pq+/PJLPfvss8E8DQCIaBSluojNZtOyZcs8DvdF29GPnUcf+gf9iI7iudN59KF/0I+dRx+GllmzZunYsWNaunSpCgoKNGbMGK1du9a1mPmBAwfcppice+65euWVV3T33Xfrrrvu0tChQ/XWW2/prLPOavNjRvpzgPPn/CP5/CX6oCvO32SE0rVdAQAAAAAAEBFYUwoAAAAAAAABR1EKAAAAAAAAAUdRCgAAAAAAAAFHUQoAAAAAAAABR1Gqi6xcuVKZmZmKiYnRpEmTtGnTpmA3KWTde++9MplMbn/Dhw937a+pqdHChQvVq1cvJSQk6Fe/+pUKCwuD2OLQ8Omnn2r69Onq16+fTCaT3nrrLbf9hmFo6dKlSk9PV2xsrLKysrR79263mOLiYs2ZM0dJSUlKSUnRtddeq4qKigCeRXC11ofXXHNNi+fmxRdf7BYT6X0I38gF7UM+aD9ygX+QD9Bce9+733jjDQ0fPlwxMTEaNWqU3n///QC1tGu05/yfe+45nXfeeerRo4d69OihrKysbp/rOpq7X3vtNZlMJs2cObNrG9jF2nv+JSUlWrhwodLT02Wz2TRs2LCIeg1I0ooVK3TGGWcoNjZWGRkZuvXWW1VTUxOg1vpXa/nQk3Xr1mncuHGy2WwaMmSIVq9e3a7HpCjVBdasWaPs7GwtW7ZMW7du1ejRozVt2jQdPXo02E0LWSNHjtSRI0dcfxs2bHDtu/XWW/U///M/euONN7R+/XodPnxYv/zlL4PY2tBQWVmp0aNHa+XKlR73P/roo3ryySe1atUqffHFF4qPj9e0adPc3iDnzJmj7777Th9++KHeffddffrpp7r++usDdQpB11ofStLFF1/s9tx89dVX3fZHeh/CO3JBx5AP2odc4B/kAzRp73v3559/rtmzZ+vaa6/VV199pZkzZ2rmzJn69ttvA9xy/2jv+a9bt06zZ8/WJ598oo0bNyojI0NTp07VoUOHAtxy/+ho7s7Pz9dtt92m8847L0At7RrtPX+73a6f/vSnys/P15tvvqldu3bpueeeU//+/QPccv9pbx+88soruvPOO7Vs2TLt2LFDzz//vNasWaO77rorwC33j7bkw+b27dunyy67TBdeeKG2bdumxYsX67rrrtMHH3zQ9gc14HcTJ040Fi5c6LrtcDiMfv36GTk5OUFsVehatmyZMXr0aI/7SkpKjOjoaOONN95wbduxY4chydi4cWOAWhj6JBl/+9vfXLedTqeRlpZmPPbYY65tJSUlhs1mM1599VXDMAxj+/bthiRj8+bNrpi///3vhslkMg4dOhSwtoeKU/vQMAxj3rx5xowZM7weQx/CF3JB+5EPOodc4B/kg8jW3vfuK664wrjsssvctk2aNMn4z//8zy5tZ1fpbO6qr683EhMTjZdeeqmrmtilOnL+9fX1xrnnnmv88Y9/bPW9ItS19/yfeeYZY9CgQYbdbg9UE7tce/tg4cKFxk9+8hO3bdnZ2caUKVO6tJ2B4CkfnuqOO+4wRo4c6bZt1qxZxrRp09r8OIyU8jO73a4tW7YoKyvLtc1sNisrK0sbN24MYstC2+7du9WvXz8NGjRIc+bM0YEDByRJW7ZsUV1dnVt/Dh8+XKeffjr96cO+fftUUFDg1m/JycmaNGmSq982btyolJQUTZgwwRWTlZUls9msL774IuBtDlXr1q1T3759dcYZZ+jGG2/U8ePHXfvoQ3hDLug48oH/kAv8i3wQ/jry3r1x40a3eEmaNm1at3xf8kfuqqqqUl1dnXr27NlVzewyHT3/3/3ud+rbt6+uvfbaQDSzy3Tk/N955x1NnjxZCxcuVGpqqs466yw99NBDcjgcgWq2X3WkD84991xt2bLFNcVv7969ev/993XppZcGpM3B5o/3wCh/NyrSFRUVyeFwKDU11W17amqqdu7cGaRWhbZJkyZp9erVOuOMM3TkyBHdd999Ou+88/Ttt9+qoKBAVqtVKSkpbsekpqaqoKAgOA3uBpr6xtPzsGlfQUGB+vbt67Y/KipKPXv2pG8bXXzxxfrlL3+pgQMHas+ePbrrrrt0ySWXaOPGjbJYLPQhvCIXdAz5wL/IBf5DPogMHXnvLigo8Pka6078kbt++9vfql+/fi2+pHYHHTn/DRs26Pnnn9e2bdsC0MKu1ZHz37t3rz7++GPNmTNH77//vvLy8nTTTTeprq5Oy5YtC0Sz/aojfXDVVVepqKhIP/rRj2QYhurr63XDDTd02+l77eXtPbCsrEzV1dWKjY1t9T4oSiHoLrnkEte/zz77bE2aNEkDBgzQ66+/3qYnMdBVrrzySte/R40apbPPPluDBw/WunXrdNFFFwWxZUB4Ih8gVJEPgNY9/PDDeu2117Ru3TrFxMQEuzldrry8XHPnztVzzz2n3r17B7s5QeF0OtW3b189++yzslgsGj9+vA4dOqTHHnusWxalOmLdunV66KGH9PTTT2vSpEnKy8vTLbfcovvvv1/33HNPsJvXLTB9z8969+4ti8XS4mpAhYWFSktLC1KrupeUlBQNGzZMeXl5SktLk91uV0lJiVsM/elbU9/4eh6mpaW1WLCvvr5excXF9K0XgwYNUu/evZWXlyeJPoR35AL/IB90Drmg65APwlNH3rvT0tLC5r2+M7nr97//vR5++GH94x//0Nlnn92Vzewy7T3/PXv2KD8/X9OnT1dUVJSioqL08ssv65133lFUVJT27NkTqKb7RUf+/9PT0zVs2DBZLBbXtjPPPFMFBQWy2+1d2t6u0JE+uOeeezR37lxdd911GjVqlH7xi1/ooYceUk5OjpxOZyCaHVTe3gOTkpLa/IMiRSk/s1qtGj9+vHJzc13bnE6ncnNzNXny5CC2rPuoqKjQnj17lJ6ervHjxys6OtqtP3ft2qUDBw7Qnz4MHDhQaWlpbv1WVlamL774wtVvkydPVklJibZs2eKK+fjjj+V0OjVp0qSAt7k7+OGHH3T8+HGlp6dLog/hHbnAP8gHnUMu6Drkg/DUkffuyZMnu8VL0ocfftgt35c6mrseffRR3X///Vq7dq3bumrdTXvPf/jw4frmm2+0bds219/Pf/5z11XIMjIyAtn8TuvI//+UKVOUl5fnVnz5/vvvlZ6eLqvV2uVt9reO9EFVVZXMZveySlORrmGt8PDml/fA9q/Bjta89tprhs1mM1avXm1s377duP76642UlBSjoKAg2E0LSf/1X/9lrFu3zti3b5/x2WefGVlZWUbv3r2No0ePGoZhGDfccINx+umnGx9//LHx5ZdfGpMnTzYmT54c5FYHX3l5ufHVV18ZX331lSHJWL58ufHVV18Z+/fvNwzDMB5++GEjJSXFePvtt41//etfxowZM4yBAwca1dXVrvu4+OKLjbFjxxpffPGFsWHDBmPo0KHG7Nmzg3VKAeerD8vLy43bbrvN2Lhxo7Fv3z7jo48+MsaNG2cMHTrUqKmpcd1HpPchvCMXtB/5oP3IBf5BPkCT1t67586da9x5552u+M8++8yIiooyfv/73xs7duwwli1bZkRHRxvffPNNsE6hU9p7/g8//LBhtVqNN9980zhy5Ijrr7y8PFin0CntPf9Tdfer77X3/A8cOGAkJiYaixYtMnbt2mW8++67Rt++fY0HHnggWKfQae3tg2XLlhmJiYnGq6++auzdu9f4xz/+YQwePNi44oorgnUKndLa54o777zTmDt3rit+7969RlxcnHH77bcbO3bsMFauXGlYLBZj7dq1bX5MilJd5KmnnjJOP/10w2q1GhMnTjT++c9/BrtJIWvWrFlGenq6YbVajf79+xuzZs0y8vLyXPurq6uNm266yejRo4cRFxdn/OIXvzCOHDkSxBaHhk8++cSQ1OJv3rx5hmE0XAr8nnvuMVJTUw2bzWZcdNFFxq5du9zu4/jx48bs2bONhIQEIykpyZg/f363/RDREb76sKqqypg6darRp08fIzo62hgwYICxYMGCFgWFSO9D+EYuaB/yQfuRC/yDfIDmfL13n3/++a7XV5PXX3/dGDZsmGG1Wo2RI0ca7733XoBb7F/tOf8BAwZ4fO0sW7Ys8A33k/b+/zfX3YtShtH+8//888+NSZMmGTabzRg0aJDx4IMPGvX19QFutX+1pw/q6uqMe++91xg8eLARExNjZGRkGDfddJNx4sSJwDfcD1r7XDFv3jzj/PPPb3HMmDFjDKvVagwaNMh48cUX2/WYJsOIgDFlAAAAAAAACCmsKQUAAAAAAICAoygFAAAAAACAgKMoBQAAAAAAgICjKAUAAAAAAICAoygFAAAAAACAgKMoBQAAAAAAgICjKAUAAAAAAICAoygFAAAAAACAgKMoBYSBzMxMrVixItjNAAAEGfkAAAB0JxSlgHa65pprNHPmTEnSBRdcoMWLFwfssVevXq2UlJQW2zdv3qzrr78+YO0AAJAPAAAAOisq2A0AINntdlmt1g4f36dPHz+2BgAQLOQDAAAQSRgpBXTQNddco/Xr1+uJJ56QyWSSyWRSfn6+JOnbb7/VJZdcooSEBKWmpmru3LkqKipyHXvBBRdo0aJFWrx4sXr37q1p06ZJkpYvX65Ro0YpPj5eGRkZuummm1RRUSFJWrdunebPn6/S0lLX4917772SWk7XOHDggGbMmKGEhAQlJSXpiiuuUGFhoWv/vffeqzFjxuhPf/qTMjMzlZycrCuvvFLl5eVd22kAEIbIBwAAAB1DUQrooCeeeEKTJ0/WggULdOTIER05ckQZGRkqKSnRT37yE40dO1Zffvml1q5dq8LCQl1xxRVux7/00kuyWq367LPPtGrVKkmS2WzWk08+qe+++04vvfSSPv74Y91xxx2SpHPPPVcrVqxQUlKS6/Fuu+22Fu1yOp2aMWOGiouLtX79en344Yfau3evZs2a5Ra3Z88evfXWW3r33Xf17rvvav369Xr44Ye7qLcAIHyRDwAAADqG6XtAByUnJ8tqtSouLk5paWmu7X/4wx80duxYPfTQQ65tL7zwgjIyMvT9999r2LBhkqShQ4fq0UcfdbvP5uuRZGZm6oEHHtANN9ygp59+WlarVcnJyTKZTG6Pd6rc3Fx988032rdvnzIyMiRJL7/8skaOHKnNmzfrnHPOkdTwZWX16tVKTEyUJM2dO1e5ubl68MEHO9cxABBhyAcAAAAdw0gpwM++/vprffLJJ0pISHD9DR8+XFLDr9FNxo8f3+LYjz76SBdddJH69++vxMREzZ07V8ePH1dVVVWbH3/Hjh3KyMhwfQGRpBEjRiglJUU7duxwbcvMzHR9AZGk9PR0HT16tF3nCgDwjnwAAADgGyOlAD+rqKjQ9OnT9cgjj7TYl56e7vp3fHy82778/Hz97Gc/04033qgHH3xQPXv21IYNG3TttdfKbrcrLi7Or+2Mjo52u20ymeR0Ov36GAAQycgHAAAAvlGUAjrBarXK4XC4bRs3bpz++te/KjMzU1FRbX+JbdmyRU6nU48//rjM5oZBjK+//nqrj3eqM888UwcPHtTBgwddv45v375dJSUlGjFiRJvbAwBoO/IBAABA+zF9D+iEzMxMffHFF8rPz1dRUZGcTqcWLlyo4uJizZ49W5s3b9aePXv0wQcfaP78+T6/QAwZMkR1dXV66qmntHfvXv3pT39yLXjb/PEqKiqUm5uroqIij9M4srKyNGrUKM2ZM0dbt27Vpk2bdPXVV+v888/XhAkT/N4HAADyAQAAQEdQlAI64bbbbpPFYtGIESPUp08fHThwQP369dNnn30mh8OhqVOnatSoUVq8eLFSUlJcv3h7Mnr0aC1fvlyPPPKIzjrrLP3lL39RTk6OW8y5556rG264QbNmzVKfPn1aLIwrNUy7ePvtt9WjRw/9+Mc/VlZWlgYNGqQ1a9b4/fwBAA3IBwAAAO1nMgzDCHYjAAAAAAAAEFkYKQUAAAAAAICAoygFAAAAAACAgKMoBQAAAAAAgICjKAUAAAAAAICAoygFAAAAAACAgKMoBQAAAAAAgICjKAUAAAAAAICAoygFAAAAAACAgKMoBQAAAAAAgICjKAUAAAAAAICAoygFAAAAAACAgPv/0Q/zUsl5ZdIAAAAASUVORK5CYII=", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig, axes = data_fit.plot_trace()\n", "for ax, true_value in zip(\n", " axes[1:], [true_inputs[param.name] for param in data_fit.all_fit_parameters]\n", "):\n", " ax.axhline(true_value, color=\"r\", linestyle=\"--\")" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "iwp", "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": "3.11.9" }, "orig_nbformat": 4, "vscode": { "interpreter": { "hash": "6b12f1f625627d6c4a17ef696ddbbbd9bd4b12881121180de40e09e7956aa05c" } } }, "nbformat": 4, "nbformat_minor": 2 }