{ "cells": [ { "cell_type": "markdown", "id": "e98f84a0", "metadata": {}, "source": [ "# Notebook 10: A hyperparameter search\n", "\n", "### Goal: Show an example of hyperparameter tuning \n", "\n", "#### Background\n", "\n", "If you look at any of the ML method documentation, you will find there are alot of switches and nobs you can play with. See this page on ```RandomForestRegressor``` [click](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestRegressor.html). Most of these switches and nobs are considered *hyperparameters*. In otherwords, these are parameters you can change that may or may not influence the machine learning model performance. Since every machine learning task is different, you often can *tune* your choice of these hyperparameters to get a better performing model. This notebook sets out to show you one way to do a hyperparameter search with random forest. \n", "\n", "# Import packages and load data for Regression\n", "In the paper we do this hyperparameter tuning with the random forest regression example. So let's load in the regression dataset. " ] }, { "cell_type": "code", "execution_count": 1, "id": "ffdf6ca6-e815-4448-8cfc-3c48183ca635", "metadata": {}, "outputs": [], "source": [ "###################################### Load training data ######################################\n", "#import some helper functions for our other directory.\n", "import sys\n", "sys.path.insert(1, '../scripts/')\n", "from aux_functions import load_n_combine_df\n", "import numpy as np\n", "(X_train,y_train),(X_validate,y_validate),_ = load_n_combine_df(path_to_data='../datasets/sevir/',features_to_keep=np.arange(0,36,1),class_labels=False,dropzeros=True)\n", "\n", "#remember since we have all 36 predictors we need to scale the inputs \n", "from sklearn.preprocessing import StandardScaler\n", "#create scaling object \n", "scaler = StandardScaler()\n", "#fit scaler to training data\n", "scaler.fit(X_train)\n", "#transform feature data into scaled space \n", "X_train = scaler.transform(X_train)\n", "X_validate = scaler.transform(X_validate)\n", "################################################################################################\n", "\n", "#import other packages we will need \n", "import pandas as pd \n", "import matplotlib.pyplot as plt\n", "\n", "import matplotlib.patheffects as path_effects\n", "pe1 = [path_effects.withStroke(linewidth=2,\n", " foreground=\"k\")]\n", "pe2 = [path_effects.withStroke(linewidth=2,\n", " foreground=\"w\")]" ] }, { "cell_type": "markdown", "id": "502f2a05-a55f-4105-b105-9789bb9bebf7", "metadata": {}, "source": [ "# Determine what parameter 'sweeps' you wish to do \n", "\n", "Right now I would like you to go check out the random forest document page: [here](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestRegressor.html). \n", "\n", "We will go ahead and systematically vary some of these hyperparameters. More specifically, we will play with\n", "\n", "1. Tree depth (i.e., number of branches).\n", "2. Number of Trees \n", "\n", "While one could always do more hyperparameter tests, for now this will get you started on generally how to do it. Let's vary the depth of trees from 1 to 10, and we will incrementally increase it. Then for the number of trees lets do 1, 5, 10, 25, 50, 100. Note we did 1000 in the paper, but something you will notice is that the deeper the tree and the more numerous trees it takes longer to train your models. So for it not to take forever in this tutorial, we will cut it to 100. \n" ] }, { "cell_type": "code", "execution_count": 2, "id": "0af679aa-4122-48b9-b782-68d9742949a2", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[[1, 1], [1, 2], [1, 3], [1, 4], [1, 5], [1, 6], [1, 7], [1, 8], [1, 9], [1, 10], [5, 1], [5, 2], [5, 3], [5, 4], [5, 5], [5, 6], [5, 7], [5, 8], [5, 9], [5, 10], [10, 1], [10, 2], [10, 3], [10, 4], [10, 5], [10, 6], [10, 7], [10, 8], [10, 9], [10, 10], [25, 1], [25, 2], [25, 3], [25, 4], [25, 5], [25, 6], [25, 7], [25, 8], [25, 9], [25, 10], [50, 1], [50, 2], [50, 3], [50, 4], [50, 5], [50, 6], [50, 7], [50, 8], [50, 9], [50, 10], [100, 1], [100, 2], [100, 3], [100, 4], [100, 5], [100, 6], [100, 7], [100, 8], [100, 9], [100, 10]] 60\n" ] } ], "source": [ "#vary depth of trees from 1 to 10. \n", "depth = np.arange(1,11,1)\n", "#vary the number of trees in the forest from 1 to 100 \n", "n_tree = [1,5,10,25,50,100]\n", "\n", "#build out the parameter sets we will test. \n", "sets = []\n", "#for each number of trees, set their depth\n", "for n in n_tree:\n", " for d in depth:\n", " sets.append([n,d])\n", " \n", "print(sets,len(sets))" ] }, { "cell_type": "markdown", "id": "0a87faab-1f13-49fc-ab21-53275bb3882c", "metadata": {}, "source": [ "As you can see, we have built out 60 different parameters to try out! \n", "\n", "To make the code a bit more concise, let's define a functiont that will calculate all our metrics for us. " ] }, { "cell_type": "code", "execution_count": 3, "id": "c6a60be5-ce6d-4219-b725-8d2a7f65937d", "metadata": {}, "outputs": [], "source": [ "from gewitter_functions import get_bias,get_mae,get_rmse,get_r2\n", "#define a function to calcualte all the metrics, and return a vector with all 4. \n", "def get_metrics(model,X,y):\n", " yhat = model.predict(X)\n", " mae = get_mae(y,yhat)\n", " rmse = get_rmse(y,yhat)\n", " bias = get_bias(y,yhat)\n", " r2 = get_r2(y,yhat)\n", " return np.array([bias,mae,rmse,r2])" ] }, { "cell_type": "markdown", "id": "9057a519-8ac4-4abe-b79c-aa6e1cabc2a7", "metadata": {}, "source": [ "Okay, now we are ready to do the hyperparameter sweep. \n", "\n", "WARNING, this took 20 mins on my mac with n_jobs set to 4 (also made the jet engines fire up [the fan]). So if you dont have that kind of time, go ahead and jump past this cell, and just load the pre-computed metrics I have. " ] }, { "cell_type": "code", "execution_count": 4, "id": "49d1781e-7464-400d-94d4-b006fd4392f0", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 60/60 [12:48<00:00, 12.80s/it]\n" ] } ], "source": [ "# import the progress bar so we can see how long this will take\n", "import tqdm \n", "\n", "#import RandomForest \n", "from sklearn.ensemble import RandomForestRegressor\n", "\n", "#do our hyperparameter search!\n", "# for each set of parameters,train a new model and evaluate it \n", "for i,s in enumerate(tqdm.tqdm(sets)):\n", " #initialize the model \n", " reg = RandomForestRegressor(n_estimators=s[0],max_depth=s[1],n_jobs=4)\n", " #train the model\n", " reg.fit(X_train,y_train)\n", " #get the metrics on both the training dataset and the validation dataset. \n", " met_train = get_metrics(reg,X_train,y_train)\n", " met_val = get_metrics(reg,X_validate,y_validate)\n", " \n", " #this if statement lets us stack the observations up. \n", " if i ==0:\n", " #if the first loop, rename things\n", " all_scores_val = met_val \n", " all_scores_train = met_train\n", " else:\n", " #otherwise, stack it on \n", " all_scores_val = np.vstack([all_scores_val,met_val])\n", " all_scores_train = np.vstack([all_scores_train,met_train])\n", " \n", " del reg \n", "\n", "#import pandas for easy writing and reading functions \n", "import pandas as pd\n", "\n", "#this takes a hot min to run, so lets save them when we are done. \n", "df_val = pd.DataFrame(all_scores_val,columns=['Bias','MeanAbsoluteError','RootMeanSquaredError','Rsquared'])\n", "df_val.to_csv('../datasets/hyperparametersearch/validation_metrics.csv',index=False)\n", "df_train = pd.DataFrame(all_scores_train,columns=['Bias','MeanAbsoluteError','RootMeanSquaredError','Rsquared'])\n", "df_train.to_csv('../datasets/hyperparametersearch/train_metrics.csv',index=False)" ] }, { "cell_type": "markdown", "id": "e807a37b-032e-4561-b3c8-0351bec0405c", "metadata": {}, "source": [ "Since that took about 30 mins, we dont want to do that EVERY time we load this notebook, so lets save the results out to a file (i.e., a comma separated values file format) to allow for quick and easy reading later on. (this dataset is already made for you in the ```datasets``` folder in the repo.). " ] }, { "cell_type": "code", "execution_count": 5, "id": "1b736d69-c2b8-46ae-a5eb-e04d998d62d1", "metadata": {}, "outputs": [], "source": [ "df_val = pd.read_csv('../datasets/hyperparametersearch/validation_metrics.csv').to_numpy()\n", "df_train = pd.read_csv('../datasets/hyperparametersearch/train_metrics.csv').to_numpy()" ] }, { "cell_type": "markdown", "id": "e7678c3f-a5d8-4b57-808d-aae467d053d1", "metadata": {}, "source": [ "And there we go, we have successfully trained 60 models with various different configurations to see if any one particular configuration does better than another. So, how do we check which one is doing best? Well we can look at the validation dataset results, here I named it ```all_scores_val```. This will show us the general performance on the validation data. So lets take a look at that now. In the next cell is some code to plot up that matrix we saved out in the last cell. \n", "\n", "The figure I want to make has a metric on each panel. The x-axis will be the tree depth, then each color will be the number of trees. " ] }, { "cell_type": "code", "execution_count": 7, "id": "993cd862", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/var/folders/ph/fm42qdjd6vq_mxy6l2ts8sp80000gn/T/ipykernel_1802/3826817153.py:63: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\n", " plt.tight_layout();\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "image/png": { "height": 351, "width": 422 } }, "output_type": "display_data" } ], "source": [ "#matplotlib things\n", "import matplotlib.pyplot as plt \n", "import matplotlib\n", "from matplotlib.ticker import (MultipleLocator, FormatStrFormatter,\n", " AutoMinorLocator)\n", "\n", "#make default resolution of figures much higher (i.e., High definition)\n", "%config InlineBackend.figure_format = 'retina'\n", "\n", "#plot parameters that I personally like, feel free to make these your own.\n", "matplotlib.rcParams['axes.facecolor'] = [0.9,0.9,0.9] #makes a grey background to the axis face\n", "matplotlib.rcParams['axes.labelsize'] = 14 #fontsize in pts\n", "matplotlib.rcParams['axes.titlesize'] = 14 \n", "matplotlib.rcParams['xtick.labelsize'] = 12 \n", "matplotlib.rcParams['ytick.labelsize'] = 12 \n", "matplotlib.rcParams['legend.fontsize'] = 12 \n", "matplotlib.rcParams['legend.facecolor'] = 'w' \n", "matplotlib.rcParams['savefig.transparent'] = False\n", "\n", "#make a 2 row, 2 column plot (4 total subplots)\n", "fig,axes = plt.subplots(2,2,figsize=(5,5))\n", "#set background color to white, otherwise its transparent when you copy paste it out of this notebook. \n", "fig.set_facecolor('w')\n", "\n", "#lets ravel the 2x2 axes matrix to a 4x1 shape. This makes looping easier (in my opinion). \n", "axes = axes.ravel()\n", "\n", "########### colormap stuff ###########\n", "# I want to color each line by the number of trees. So this bit of code does that for us.\n", "#get func to plot it\n", "from aux_functions import make_colorbar\n", "#grab colormap\n", "cmap = matplotlib.cm.cividis\n", "#set up the boundaries to each color \n", "norm = matplotlib.colors.BoundaryNorm(n_tree, cmap.N, extend='both')\n", "#make a mappable so we can get the color based on the number of trees. \n", "scalarMap = matplotlib.cm.ScalarMappable(norm=norm, cmap=cmap)\n", "######################################\n", "\n", "titles = ['Bias','MAE','RMSE','$R^{2}$']\n", "for j,ax in enumerate(axes):\n", " for i,ii in enumerate(n_tree):\n", " color_choice =scalarMap.to_rgba(ii)\n", " ax.plot(np.arange(1,11,1),df_val[(i*10):(i+1)*10,j],'o-',color=color_choice,ms=3)\n", " # ax.plot(np.arange(1,11,1),df_train[(i*10):(i+1)*10,j],'o--',color=color_choice,ms=3)\n", " ax.set_title(titles[j])\n", " ax.set_xlim([0,12])\n", " ax.grid('on')\n", " # ax.xaxis.grid(True, which='minor')\n", " # For the minor ticks, use no labels; default NullFormatter.\n", " ax.xaxis.set_minor_locator(MultipleLocator(1))\n", " ax.yaxis.set_minor_locator(MultipleLocator(2.5))\n", " \n", "axes[2].set_xlabel('Tree Depth')\n", "axes[3].set_xlabel('Tree Depth')\n", "\n", "########### draw and fill the colorbar ###########\n", "ax_cbar = fig.add_axes([1.025, 0.4, 0.015,0.33])\n", "cbar = make_colorbar(ax_cbar,1,100,cmap)\n", "cbar.set_label('# of trees')\n", "##################################################\n", "\n", "plt.tight_layout()" ] }, { "cell_type": "markdown", "id": "9b30fa3a-cccf-473b-a237-bdc65ae8e591", "metadata": {}, "source": [ "A reminder that each x-axis as the tree depth (i.e., number of decisions; branches) and the y-axis is the metric that is indicated in the title. The color corresponds to the number of trees used in the random forest, with 1 being the darkest color and 100 being the lightest. \n", "\n", "As we can see, and noted in the paper, basically beyond using just 1 tree, which means its a decision tree, the number of trees doesnt have a large effect on the overall performance, while the number of trees seems to have a more appreciable effect. While this is helpful to find generally which models are performing better than others, there is a group of models that all seem to have similar performance with a tree depth greater than 5. \n", "\n", "In order to truly assess which one is best to use, we need to include the training data metrics. This is where we will diagnose when a model becomes *overfit*. Overfitting is when the training data performance is really good, but the validation performance is not good. To diagnose this, you compare on the plot when the training data continues to improve its performance while the validation performance starts to degrade or worsen. So lets add the training curves to the same plot as above." ] }, { "cell_type": "code", "execution_count": 8, "id": "a6c771a6-d5b9-4aac-9718-b986e58bc6e5", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/var/folders/ph/fm42qdjd6vq_mxy6l2ts8sp80000gn/T/ipykernel_1802/3040232818.py:45: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\n", " plt.tight_layout()\n" ] }, { "data": { "image/png": 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YQFpaWqX1n3/+OQDdu3evEkwB3H///bz44osUFhayZMkSHnzwwXrXoVOnThQVFfHTTz/V+xiieSQkJADQp0+fZq5J84uJifE9by1/y63x85s4cWKV7sniwsg1t/Vqjf/PNhW55l4ccs0Vza1FJKU4ny1btgBU6fqxbt06ACZMmFBtOaPRyBVXXAHA2rVrm7CGQgghGqq4uJi0tDTS0tJwOBy43e7mrpIQQghxXi22haqkpIQTJ07w/vvv89VXXwHw8MMP+7Z7PB4OHz4MQO/evWs8Tq9evVi+fDkHDx6s03kHDRpU7fpDhw4RExPju3MjWo/y7gvy2VXWWt6P1vj5WSwWuVtaD2+88QYvvfSSbzkkJKQZayOEEELUTYsKqFJSUoiLi6uy3mAw8Kc//Ynf/va3vnVFRUWUlpYClZvUz1W+LT09vZFrK4QQojE9+eST3H///QBMmjTJd40XQgghWrIWFVCp1WoiIyMByM/Px263o9FoePbZZ/nd735Xad+zv2hrGzjp5+cHeFu86qI8/fq5Bg0aRFFRUavqUyy8WmN/8IuhtbwfrfHza02DuVsSs9mM2WwGQKvVolK1il7pQggh2rgW9W0VHR1NRkYGGRkZWCwWjhw5wsyZM3nxxRcZMGAABw4caO4qCiEuIrvdwbETKezel8jO3QewOxzNXSXRilltDtZsSmDBks2s2XwAm13+noQQQjRci2qhOptKpSI+Pp6PPvqIoKAg/vWvf3HXXXexY8cOVCoVJpPJt2/5GIvqlJWVAfjmthJCtA6nk9P4cN4iiku8rdG79h7B7G/ivrtn0D6u5m6+QlTn8PE0XpiziPzCit4NwYEmXn5qBj26yN+TEEKI+mtRLVQ1eeSRRwDvvFO7d+8GICAgwBdUnZtO/Wzl26Kjo5u4lkKIxmJ3OCoFU+WKS0r5cN4iaakSF8Rmd/DCnEU4HUX8/qY8Xn84nUdm5OGwF/PCnEXSUiWEEKJBWmwL1dliY2N9z48fP86gQYNQFIWePXuyY8eOWrsClmf369WrV5PXU4iWrrabDy3J/oTEKsFUueKSUvYnJDJoYM3ZPYU426btiQzunsXffncUo6EieJo5Tctz/+nGpu2JjB8pf0+i8bWWa64QomFaRQvVyZMnfc/P7ro3duxYAFatWlVtOavVysaNGwEYP358E9ZQCNFYnE4X23fuq3Wf3LyCi1MZcUnIykrnbw9XDqYAjAYHf3v4KFlZkgVWCCFE/TV7QOVyufB4PLXuM2fOHAA0Gg0jRozwrb/tttsAOHz4MMuXL69Sbu7cuRQWFmI0Gpk+fXoj1loI0RQOHznB629+yJGjSbXuFxoSdFHqIy6upprYt3fsDoz66rv1GfUOesfuaJTzCCGEaJuaPaBKTk5m8ODB/O9//yMlJcW33u12s2fPHu644w4+/PBDwDuWKjg42LfPwIEDufnmmwG4++67WbFiBeAN0j755BOefvppAB5//HEiIiIu1ksSQlyg3LwC/vfJYt7/31dk5+TVuq/Z30TfPvEXqWYtU3FxMd999x0vvPAC11xzDWFhYSiKgqIovgnPq2O1Wlm8eDH33Xcf/fr1w9/fH71eT/v27bnllltYv359nc6/evVqpk2bRkREBAaDgS5duvDoo4+SmZnZoNf1xhtvEBsbS2xsLPv376egoKBBxyvXLjyrQduFEEKI2rSIMVS7du3i3nvvBbyT+Pr7+1NcXIzNZvPtc/fdd/P6669XKTt37lyOHz/Ozp07mTJlCn5+frhcLl/ZqVOn8tJLL12cFyJECzdo0CDf85rmXLuY7A4Ha9dvZe36rTicTt96g17P8KH92Ld/Pz07pRIRYiMzV8/hpFhm3TkDnVbbjLVufmvWrKlXq/u0adNYvXq1b1mv16PVaklOTiY5OZmvv/6aRx99lLfeeqvGY7z66qs8//zzgDcbq7+/PydOnOCdd97hiy++YO3atfWeM6ypJva1OwwN2i5EfbW0a64Qomk0e0AVExPDV199xZo1a9i2bRvp6enk5ub67nqOGDGCe+65h5EjR1ZbPiAggC1btvDmm2/yxRdfcOzYMfR6PQMHDuSee+5h9uzZKIpykV+VEC1TenrLGCvi8XhIOHiUb5atJi+/sNK2oYP7MXXSlQSb07h32mdolIrtTk8uBZ6pOM89YBsUERHB4MGDGTJkCLGxsb5ApDYOh4Nu3boxe/Zspk2bRo8ePQBvsp9nn32WhQsX8vbbbxMfH89vf/vbKuVXrFjhC6aefPJJXnzxRcxmMwcOHODOO+9kz549XHfddRw8eBC9Xn/Br6mpJvYtcw3B4TyKVuOqss3hVFPmGtIo5xHiXC3lmiuEaFqK53wDmATgvctUVFTEhg0bmrsq4gIlJCQA1Puu+aUkJqZivp3GzT5lw8BW1GThIhIrw4Dqf1BnZeey9LvVHE484VunKB56xQdx/eS+tIsCNemYlMWolKrjXpxuMzl8UOPxW4KJEyei1Wqb7I60y+VCrVb7lpOSkujUqRMAhw4d8gVK59qyZQvDhg2rVLacx+PhqquuYu3atXTq1IkTJ05U2WfAgAHs3buX6dOns2TJkkrbUlJS6NmzJyUlJbzzzju+6S7qqzGvuQ67heLTL9Ct86lKQZXHA4eOdsTc/lW0OmODzyO85JpboemuuU2nNX5+TX3NFeJ8mr2FSgjRumk4SrDyN9RntSS5PIHke57DSbcza2y47Ons3fszaSn76NvJytiBdsKC7YQHOwgNsqNSuYHV1Z6j0vlUxeicW7CrxjbNC2oFqguI6uLyyy+vcZuiKMycOZO1a9dy8uRJ8vLyCAkJ8W0/cOAAe/fuBeCpp56qUr5du3bcdtttzJ07l88++6zBAVVj0uqMOIwz2XvwKyLDCoiNykCl8qAocDhJT/8YFVpdc9dSCCFEayUBlbikedx2DEoSaqUEa5ELvX8vFFXbHH9jtVVu7bHZHeh1DX0vbAR6/opaVXmsi1opJITncNEeFXneYMsAscOAYQ08JWArPYRibrsBVVMJDQ31PXe5KnePW7duHQCBgYEMG1b9hzhx4kTmzp3Ltm3bKCkpqTTNRXOLjO2HI7wbKSfXodctISLMm/xkWP8sfticwNSrB53nCEIIIUT1JKASLYLdmkdJ9qdoVZnYXVGYI2ei0wc16JgOSwpFafPoEJKBVuvAXrqJvOxoAmJmoTW2a3CdrTYHm7cfIT2rkOjIIEYNiW+EAKVpHD6exgtzFlVad+fv3+Xlp2bQo0tMDaXO5URNFhpSUZOGRklD40lAq64+cYBKcaHiZLXbquNwqLE7tNgdWlQqN4HmmhMSlJTqODPURjSin3/+GYDIyEjCwsIqbSufJL1nz541jm0qn0Dd4/Fw+PBhBg8e3IS1vXBanZFO3Sdz+shJIsLWABAdkc+JYxtAAiohhBD1JAGVaHZ56d/TNWIeug7ld8QPY3ds5Fj63YRET7ng43k8LtzOUuw5/yW+U+WB6A5nJqdTy9DE/qVBLVWHj6fx1zcX0i2mkIhgD4mHFT76PJA/P3HTBQQoF4fN7uCFOYuwWIoqrS8rK+aFOYtY8M5DZwWCHlTkoyYdDalolDRv8EQaajJRlHMG9dcx34vHA44zwZLDocXh1Piel//r8VT8SFcUN35dj9WYRMBii0DiqcaVmprKe++9B3izqp6bzKd8cP3ZY0LOdfa2ug7GPzsL2tkOHTpETEyMbzxHo3IPorRsCyY/CyoFrr/iJD+s2kRcdFDjn6sNslgsAE3z2bVireX9aI2fn8ViQdvGs7+K5iUBlWhWdluBN5jSVv7hrNO6iI/6mJzSNNSKGo/HjcftxO12gceJ2+3E43HicTvPrHd4n3uceNwuFMVNh3apaNSVJwbValy0j00k8cRrqLShqNT+qNQmFI2/97nGu6w6s6yo/VCUynfjbXYHH37yBS/dk0+Qf0VOl4KSbN7/5Ate/dPvW1RL1drNB4gNy+T//niUiLNyFax5dw/zv48kL+1denRynQma0lAplkY7d2Z2GHkFQTidGuocfQEej4pTyXF0iEs+JyBWcyo5DoNBEgg0JqfTyR133EFJSQnt27fn2WefrbJPeQpzo7Hm997Pz8/3vKSkpPEr2lhU/pxMiaJPvLcFtW98FgtWHSUuWrL9CSGEuHASUNWiuLiY4uJiwJtu2O12n6eEuFDFGfNo36lqKwSARu0myvxDo59Tq3ERG3mMgqJsrDY9VoeWmn/sKyhqP1weIxabhvxiSE4v5dEbizGck2QuyN/Dg9fms3n7QcaN7F/v+nncdmwlB3E58lFrQ+o97svj8bB5RyKfLfmRb+Yk4u9X+X0OMrt49NY0oO6Zp+wODXa7Dptdh82mx+7Q0C46A00NLUmHTsRQXGLA4QS7Q8HuVLA7wGZXcDgVPB4Ftwc8HgWPx9uS5fYoRIdZuawHHDnWlQBzMTqtA7tDS1GxGY9HRYnVSUDkBb8logaPPPIIP//8Mzqdjs8//5zAwMCLdu6asnKVZ/lrqkxjeem34HTOQaNxYTTYGdTtKF263oHRINkpGqo1Zom7GFrL+9EaP7/abvQIcTFIQFWLN954o9KkwGdnvBKNQ01Ks5w3KLCYoEBvsOxyK9hsem9wZdP7nntbVcDjKkVFKSYtmEKg3Zk/A0VxE2gu9o7POvNjP9BfRWfNt+Se2oVWF4haG4BKbUalqfxQlOqztDksKRSmfILHXTF+qERtIjB2Zp3HfanIo6xoF8eOraZHWAo//bsM9QVM5+NyqbwBk13nDZ5set+yx6PC5VYotWgotWgps2qw2nR06Xi6SkvS8aT2ZBR0oVuvMbhcHhwOBw67HbvvX3ulZYfDgd1ux+Gwk5JTTC9bGQY9FBZV/nFvtanIswfRqe4vSdTiueee47333kOtVvPZZ5/VOOefyWQCKroDVaesrMz3vCUlpKhOcNRgsnKDiYnIAWDiiAxWbE5g8vjLmrlmQgghWhsJqGrx5JNP+ibLnDRpkq/Li2g8Vlvtf4JFxX5YbGeagjyA4ql46turotudcma7QW8nwN9apzqoVR78jFb8jJX3dzjV3mDinGDL5VZjNFhq7I4G4LYew1bL6T0YUTT+aHVBqMuDLLWJkuzVKNgr7+sqJf/0PEI7P4qi1p153cqZhxuNkozGfQjFdRCDOhGDNh+CoGMd8wGUlhnJLwz0tjjZdThdas5+d11uKLPqKLUaKSw1kp2vIq/ASqnFhckAEInFqic0uMjXkpSbH8Cp9CAMpihiY9vXrSJnSUw8wqZflzOqfwEGfUXLsNWmYtPeIAYNk5sbjeHVV1/l73//O4qiMHfuXGbMmFHjvuXjo2qbS+fsbdHR0Y1X0SagKCrS84cSE7ECgMiwApKOrwMJqIQQQlwgCahqYTabMZ9JJabVamvMbCXqx+2yEhOWVeN2h0PNT5v64XRd+J+pWuXi2vE7MOirTgzrcKo4mRJBoL+FQHMpBr2z2mNoNS60mjL8TWWV1pdZ1Rh0Ls79c9BqXHSIS+bIsS54PLXPE6RgAacFhzMbR6X11bd84bGQd+I1VIobo9GCya8MP6MFP6MFtdoNaqAOvQIv62eqsi43P7hSK5DDCSlZak5naiksDeBUqoviUhvgAiqPi1GpICZCh9UeSkCOGZ3Ghd2ppqhUh8UGao/h/JWqRufOXdi8KZDvN2uIDbfi7+eipExNarYBvd5E585d6nVcUeHNN9/k+eefB+Dtt9/mnnvuqXX/8gx+hw4dwu12V3s9LM8EqCgKPXv2bOQaN76IjrdSXLoes6kMRYHrr0ji6MkMunWKau6qCSGEaEUkoBLNwuNxY8mcQ5d2BdVudzjUbN7Vk+j2l6PWBVFYWEBubg75eXlYykrw4D4TfJz1ADjz3KBT+HlbL0YPOYjRUBGyWKxaNmzvRV5hRY44vc5OkLmMQHMZgeZSAs1lBJnL0GqrH9vlZ6h+PXiDql7xidjsGmx2DQ6nBqdLjculwuNWAyoUVLjcapxODS6XGpdL7WsVqq7ly+VSUVxiQq9zYDBYUc6T28HtViizGL2PMj/KrHq6dT6JVuNix8q+ld9np5qCIjPF1hCOJLk5cNRGRq4Kt7v8JGVVT3CGv78fgWZ/tiVkM7SPFo+nYlCZ1e5hW4KDqVPq15Kk0WiYPGUaK75fRnJmxQs2Gv2YPGUaGo1cuhri3Xff5YknngDgtddeq9MkvGPHeuf9KiwsZPv27dXORbVy5UoAhg0b5usi2JJptP6cTm5P766HAejVNYu/L9hMt043NnPNxKWithZdIcSlQ36ViGZRnLmQTlH7fMvpWUFk5oRgNlkoLjVy9FQEHsWfkZcNQ62u3PTi8XgoLi4iNyeHjMxM0lLTyM/Pw26v6GOnKB5MBjPL1g6mXVQu/n5WSsoMpGSEYrOrSUpXoVEr6LQetBoDmbl6tJpgtBoPWo23vJ/BRmBA2ZlgyxtoBfqXoVZ7qI1KBUaDE6Oh+pavmjidCmq1p0rApFa7feO9quNwqCm1+FFWZqS0zA+rzcC5STZqy5i3eY+eDbvKuxlW37LmcoPTraZbl/aMubwfnTq2IyjQjMPp5JXX3mX1r6VEh6nwMyiUWT2k57gx+Zno2yf+gt6Ds0VGRnLXzLvZ8PN6LFYL3brF07lzFwmmGmj+/Pn87ne/A+DPf/4zTz/9dJ3K9erVi/79+7N3717mzJnDokWV5zVLS0vjiy++AOCOO+5o3Eo3IXXAbTidf0WjcWHQO+gRvQOLdZokpxBCCFFn8stEXHSleb8QYfrB9+PeZtewZXdP7I6KH/NanR/9B19fJZgCb3eigIBAAgIC6XSm61dKei4/rNvDrzsOoHhsdInWkJypJi4STqVF+Mo6nZCcqcbhVHA4wWKrHHio1WpUKgW9ToVO648uJxSN2oNG7fY+VE56dE7mst51n7C2rjSa2gM18GbBKyz2IzsvgJz8ALLzAygt01MeQBUUu8nMdZOR66KwxBuc9e7s5NoxNWfMyymo3HVLp9USExOBw6Vmf2Im2QU27E4AF4lpJ9l2MJfbrxvBxCv7odNque/uGXw4bxGpWRVjDM3+Ju67ewa6Bs4LotFoiIj0dr+Kj+/eoGNdanJycnzP8/Pzfc8LCgoqbQsJCfF1z1u8eDH33nsvHo+Hp556qlLSnbr429/+xpQpU1i8eDF//OMfeeGFFzCbzRw8eJC77rqL4uJiOnfuzOzZsxv46i6ewNA+ZGaHEBuVDcD4YRl8v+UA14wb2Mw1E0II0VpIQCUuKlvJUTSWzwkKq5hk9sdNPRl0xcMU5iZhsRRiNAYSFtW12mDqbBarnZ+3HubH9XtJOFI5W6DT5SHAZOBYihqznwetFhwOKC7zpuoOi+7KlIljUKvVqFUqVGo1KpWqymSm1UlL3oXF+o9KXQkr6qTl+/WXoVZ70Osc6LRO9DoHep0TvdaBTuesul7nQKt1ojrPqU8mR7DzQGcczor/bZ0uD2k5brLyFJxuP+wON8UlpbhcAN5U5IeTNIwbYsffT1UlY15JmUJGXhAjR3QnLjaa9nHRREaE+n6A2+wOlq/ezZffbSW/0BswZecW8fb/fuLzb3/hjusvZ+KV/Xjq8ftYunwDmdl5REaEcsPUK/A3+SGaTnh4eLXrR4wYUWn55MmTdOzYEYCnnnoKl/ePg08++YRPPvmkxuMvWbKEyy+/vNK6yZMn8/LLL/PCCy8wZ84c/vWvf2EymSgq8v7/HBYWxrfffoter6/ukOfVHFNVKIpCVskoYlkKQHhIIadPrAEJqIQQQtSRBFTionHasilJ/5juXTJ86w4eiySq0z0YDEYMsecfxO7xeDiQmMqP6/ey/pdDWG1Vg5qgAD+GDOqJPf8QOq1CUWnlSMXu9DBl0lhMfvWbtyIypi+btg9g1GV7qozP2rRrAP2H3o3VWkRZST5lpXkUluRRlJGDQm1dAD10aZ/B0H7Ha9wjPTsIh1NDUamHY6lujqa4OZ3l4boJQ3j4d1f4uih5PB6sVhvFJaUUl5Sxd99hFq7+lZuusvK3N9f7jvfc41eycLWByZPGM2hg72rPqddpuXHyUKaMH8jyNbv56pzA6q2PfmT+oo3Y7A7KLOXdBk+xbN0RXn5qBj26xNTlLRUXydkBSmZmZq372u32atc///zzDB8+nLfeeotff/3V1yo1depUnnvuOSIj6z9BWHNNVRHR4SaKSlYS4F+KosD0MUmcOJ1F5/YR5y8sRC26du3qe37s2LFmrIkQoilJQCUuCpezlJyT79E5LsU3CWxxqY5fD4/nmskdz1s+N7+EVRv38+P6faSk51XZrlIpDL+sK5PG9GfogM5oNGq27Yph84Y16LUVAZXN4WHk6PH1DqYA1GotHXrcww+bFhMVkuwbn5WRF0efy27EHBSJmco/Kj0eDyUlRaxct5Vd+w7gb3ASFqAQEqAiyN9b/6SUCPrGn66x5WvTniB+2mYnM9/bNbBH1xj+/fIkunSofC5FUTAaDRiNBiLCQ4lrF8Ur+w7x34Uqvl99wrdfULvJGI3+dRrnZNBrmTF5KFPHD2TZql18tWwrBUXehBXlAdbZ8gtLef71hXz279+i1zWs25+onsdz/i6i50pKSmqUc1911VVcddVVjXKsszXXVBVqtYHTGZ3o09U7oWn3Tlm89tkmHph1w0U5v7h0nT03mxDi0iUBlWhyHo+TrOPvExaUQYC5Iu320tW9GHv1FACsNgebtx8hPauQ6MggRg2JR6VS8evuY/y4fh/b9hzH7a76A7J9TCiTxvbnqlG9CQmqPJHo0Mv60LtHF75cuIyS0jLat49jwrjLGxRMlQsIimLYmPvJyThGmaUQU3ggw/rW3E1RURTM5kBuvHYiV429gs+/2cKSlbtwOO2oVRBsVhjYTUWguebMhDuPKGTmuzH56bnv1iuZMn4gqvP1E4RK45zOZjT6X/A4J4Ney01ThzH1qoEsW72bBUs2ndUyVVlBURl3PPJfesXH0ikunE5xEXSKC6dddAjqC5lpWLQZzTlVhSF0Jg7ns2g1LvQ6J31it2G1TcOglxsCQgghaicBlWhSHo+HzGMfY9RkEBNZ0cXo130xxHWdgcFg5PDxNF6Ys6hSS4dep0GrVVNSaqtyTD+jjitH9GLSmL707BZb67gnk5+RYYO88+f06dOnEV+Zt6Uqsg7dFM8VaPbjobuuYvqkwXz81QbWbD5ATqGHdbtd9OroX21mwsJSFUeS7Ywb2YsH7xxfJXg8n/ZxMTz/zEN8+O5rvnXPP/NQvZNGGA06bp46jLIyGwuWbq5xv4KiMrbsOMqWHUd967QaNe1jQ+kUF07HuHBvsNU+gvAQc5XP0mpzsCMhhbyCMjILFUYNiZcWL9Ek/AO7kpERRlyM9zo1ZnA63/9ygIlXDmjeigkhhGjxJKASTSoraQlq90liY9O9E9ACuQUGdiUO5/rpPbHZHVWCKQCb3YnNXnnMUb+e7Zl0ZT+uGNr9kkhpHBUexLMPX8uMKUP54PN17E5I4ut1Dm4eq8V1VmbCEouHr9c5mDF1OPfdOrbe5zs3eGpoBj6AuNjQCy7jcLo4fiqL46cqT+ps8tNXBFhx4WjUKj7+eoOva+GKn48QHGiSsVmiyeTbr6Kd5zMUBcJCikk5uQokoBJCCHEeElCJJpOdsh7FtouQ4ALM/t6Aye2BpWt6ctXV16EoCpu2J1Y7Bqecv8nAtVdfxsQxfYmNujgD1C+2bp2ieP25W3n93eWs2pjAf5ba6R6nIsisUFDs4UiyG6cLDLqWF0SOGhJPcKCp2s8wKMCPl5+aQWp6PieTszmZnMXJ09lk51U/p1ZpmY0DR1I4cE7GxrPlF5bywpxFLHjnIWmpEo0uLHYaRcXfEhjg7Zp8/eiTnErJoUO7sGaumRBCiJZMAirRJPKz9uIqXo1RbyfqrK5+W3bHER13jW+cRHpmQa3HufGaIdx146imrGqLoCgKg/t3ZtXGBJwuOJBUNV10dGTQxa/Yeeh1Wl5+akaVVsazW5J6do2tVKak1HomwMrm5Oks3/PSsqrdO6uTX1jKpu2JjB9ZfWZCIepLpdaRnNWNwIDdAHTrmM0/Fqxn9qwZzVwzIYQQLZkEVKLRFeWfxJK9GK3GTbuYNNQqbzKJrDw/th3oz623XebbV6OpfdB5TFRwk9a1JamttSc40MSoIefPxtccenSJYcE7D7FpeyLpmQW+pCI1tSD5mwz07RFH3x5xvnUej4ecvOIzQVY2azYf4MTprGrLw/kDcSHqyxR5D3bHfnRaJzqti34dtmG3X49OJ1+XQgghqieptkSjKi3JoiD5E7QaF2EheZj8LAC43LBkVQ8mTrrWl7mrzGLjh/V7azxWSw4imkJ5a09woKnS+vLWnpbcxU2v0zJ+ZG/uvGEk40f2vuC6KopCeGgAQwd04ZZrh3PLtcNr3b8lttaJhisuLiYtLY20tLSLNrHvuYymdqRnVUyafMVlGfz8S8JFr4cQQojWQ265iUZjtRSTefRDzH529DobkeHZvm0bdnQgJPIKQkO9YxE8Hg//mvsDqen51R6rNQQRTeFCW3suVa21tU40THNN7HuuEs9UPJ65KAqEBJWQfnolMKBZ6iKEEKLlk4CqFsXFxRQXewfQN9fd0tbCYbdw+uBcgv1LAQ/tYtJQnenql5blz9b9PbjrrpG+/b9btYv1vxzyLT9x/zXoddo2HUSUK2/tacvONzarrf5tXOqaa2Lfc4VET6Cg6EuCA73X/2uvOElyWi5xMRee1VIIIcSlTwKqWrSUu6Utncvp4Ni++YSZcwEID83Fz2gFwOlSWLK6BxMmTEGj8f65HT6exrufrPaVnzJ+AJPHDrjo9RYtW3lr3ZdL1pBbUEb/vt3bdKDdFjTnxL5nUxQ1qdm9CA78FYAu7XP4x4K13DfzpmapjxBCiJZNAqpatJS7pS2Z2+3iyN4vCDUlA2DQW4kIz/FtX7u1E/5BA4mNbQdAUYmFl9/6BqfL29rXtWMkv5t59cWveBuVlpbW3FW4IHqdlkF9vH87ffq07VY7cXEFRN+D3b4Lnc6BVuPiss7bsDumo9PK16aou9Z2zRVC1I98M9Siqe+WFhcXsnXzSqyWIgzGQEaMmoi/v7lRz9GUPB43R/Z9S5AhEZUKFMVNu5gMVIq3q19yegC/7u/MzFnjAHC7Pfzjv8vIzCkEvBO5/vmx6ZI9SwjR4uiMEaSmRdKpnXdetBH9M/h+6wGuuqJ/M9dMCCFESyO/ZJvJrh2bKcjaTN/OWZhNFopLjWz7+QRBkSO5bPDI8x+gmXk8Ho4eWIVJtQetxhtARYTlYTR4s/rZHSqWrO7B2HFXo9frAfhq2VZ+3X3cd4ynHpxCTGTbSYsuhGhd7Oob8HjeQVEgOLCU7OQfAAmohBBCVCYBVTMoKSlG7/yJmyYeQqt1+db37naKDdtLKCnp12JbqlwuB9kZx0hL3keg7hBGk7f+RoOF8NCKrn6rtnRG5xdP167dANh78DQff/Wzb/tNU4Yyakj3i1t5IYS4AAERo8kvmEdIcBEAU0clkZKeR7toGU8rhBCigsxD1Qy2/7KM0UMqB1MAWq2L0UMOsf2XZc1Us9oVFWSwdf1c0o5/Q4jhIAEmB+Dt6hfXrhDlTFe/E8lBbE+I4+qrJwCQV1DCq//+BrfHu71393bce+uVzfIa2rp27dr5HkK0NC1hHqqzKYqKtPyKFqlO7XL4adWqZqyRaG3kmitE2yABVTPoEpNQJZgqp9W66BLT8iaRdLkcJO77ik5RacRFlmAyOn3bgoPy0Wu980lZ7Wq+WdOdy0degb+/Py6Xm1f//S15Bd6EHoFmI88/ch0ajbpZXkdb53a7fQ8hWpo33niD2NhYYmNj2b9/PwUFBc1dJYJi7sFm82aW1GjcDI3fjsNZ/fVbiHPJNVeItkECqmYQHGhr0PbmkJN+mJjQbN94qXImv1Jio7J8yz9u7IqibUffvt67uvMXbWTvwdMAKAo89/B1hIcGXLyKCyFajSeffJLU1FRSU1Pp27cvQUFBzV0lNLogUrNifMtD+2aw4ZeWd9NLCCFE85GAqhmYAmpP/+xn7nWRalJ31uIDVYIplcpFu+h033JiUgi7DkYzadI1KIrCr7uP8fk3W3zb77phFIP6dbpodRZCtC5ms5mYmBhiYmKadR6qc7kNt+B2KwAEmsvIT1/ezDUSQgjRkrSMb6s2RvG/BYej+nwgbg/8uqdlTVzqcjmxlZ6usj46IgudzjuOyu5Q8+3a7lw2aAjBwSFkZhfy2n8rxoIN6tuRO25o+dkLhRDiXKaQYeQVVLSsT778FKkZec1YIyGEEC2JBFTNQFGZSEibhd1RdRyRSoHL+2zg8KHdzVCzqjweD4kJP+GnL6q03t9UQkhwgW95086OuAljyJChOJwuXn57KcUlVgDCQsw8+/B1qFvI3WYhhLgQiqKQVTTEt9whNo+Vq35oxhoJIYRoSeQXbjOw2R38/tXjjJ7dnw+XdmD11igOHA/ybY8KzyNCN4/c3Nzmq+QZKSd3oXNtR6/zdvdTFDfBgfm0j0317ZNXYGbDzlgmTpqEWq3m/QVrOHzc2xVQrVbx/O+vJyjAr1nqL4QQjSEwZhZWqw4AtdrNiJ67cEpyCiGEEEhA1Sw2bU8kv7CUEouat76M4LE347jlua4kJgX59unRJYWs42/jcDiarZ652UmUZq/wpUc3Gix073qcdjEZqNXejEUeD6zbFkd8fB+ioqJZ/8shvvlpp+8Ys28bS5/uki5WCNG6qTUmUrIqrmWDemewbvOe5quQEEKIFkMCqmaQnllQzVqFO1/sTHGJHgCVysPllx1h55a5eDyeavZvWpayAtKPf01okLfbnqK46dg+E63GWWk/RYGJo45xxRXDSU7L5Y0PVvi2jRoSz42ThyCEEJcClf9MX3IKs8lCWc6K85QQQgjRFkhA1QyiI4OqXV9mVTPrpa64XN6PRa9zMHbwVvbuXH0RawdOp53j+xcQEVToWxccGoBGbal2f38/OwbVdl56aykWqx2AmMgg/vDAFBRFuSh1FkK0fi1tYt9z+QX1Iyc/yLc86fLTpGfmN1+FhBBCtAgSUDWDUUPiCQ40VbvteIo/h9Nv9C0HmkvoE7eYtJQTF6VuHo+H4/sXEh6QTnkspGijCQqu/U9l+65NJCVnA6DVqvnzYzfgbzI0dXWFEJeQljix77lySyuylbaLyuPHn5bVsrcQQoi2QAKqWjTV3VK9TsvLT82oNqhyud28/YWW46kVc1XFRmWhLvkvpaWljXL+2pw+upYA/SHKE/J5FDPtOsXhp/611nLb91a0Zj08awJdO0Y2ZTWFEJegljix77kCo2/HYvV2zVarPVzRbzcuV8tqSRNCCHFxSUBVi6a8W9qjSwwL3nmIZx++lrtvGs2kK/v5tm3ZcZTP1o0hKy8I8I5T6tM9iaSEt5q0C0x2egJq23o0au+YLbdHQ8eukQSp51Nbz73iUi2JSWEAXHVFHyaP699kdRQNU36DIC0trbmrIkQVLXVi37Op1AZSMjv4lgf0yGTNhl3NWCPRksk1V4i2oeV9W7UgTX23VK/TMn5kb+68YSR/eGAKN00Z6tv29bLt/LB7Jlabd5JftdrN5QMT2LPt80atQ7mSogzKshah13kDNrcHOncNIEBT0Z0lM8ePkrLKkw4Xl2r5bHlfQEPHdmE8+puJMm5KCHFJ0wbe40tO4e9nxVX8fTPXSAghRHPSNHcFWjKz2YzZbAa4KHdL77t9LGmZBWzekQjAGx9uJTrkDq7qPx+VyoPRYGN4zzUcOtKNLt2HNdp57XYL2Sf+h7+xPEW7my5d1PjrNvv2OXoqmK9+6I3brdCzSw4hARbyiowcOh6G06WmxOrkz0/cgNGga7R6CSFES2QI6E5WbjBR4XkAXDUsmfSsfKIjgpu5ZkIIIZqDtFC1IGqVimd+N41unaIAcLs9vPDOMXYcqRgEHRJcSIzpE3JzMxvlnG63m5TDH+Bv9I7PUiluOncqwV9/0LfPviMRfL68L3aHBqdLzf7ESH7e0ZH9iZE4XWpsdjc3T7+a9rGhjVInIYRo6Qps43zPYyPz+emnb5uxNkIIIZqTBFQtjNGg4+U/zCAsxNsyVlpm47n/6Dl2Ota3T4e4dCzpb2K32Rp8vpQjn2HWZwGgVjvp1DELkyHVt33r3lgWr+yJyT+EvgNHYHNUnhPLandjUUUxflTfBtdFNL3y8SkxMTHNXRUhWrXAqJspLfNmMlWpPIwdsBtXC0vzLpqfXHOFaBskoGqBwkLMvPLUTRj03vFKGdlFvPjRAPIL/QBQKdC/5wmO7vtPgyb9zTi1EoNyGACtxkHnDqn4GSrmVFmztSMrNnSlc9fu3DDjZt755Bd+2F7GtiNWDpyys+2IlR93WNh1MBOb3VHTaYQQok5a+jxUZ1NUGlKzO/uW+8Zn8drbX7Fm8wG5HgohRBsjAVUL1bVjJM///jpUZxI87D2cxRtfj8PuUAOg1ToZ1mcXh/fWbw6Uwpx9KGU/oyig19no3OEUBn0Z4E1IsWxdN9Zv68gVo8cxceIkftl1nPzCUtxuSMl2cSTZQUq2C7cbCorK2LQ9sXFeuBCizWoN81CdzRA62zcRu5/RxoSBB9i2ZQX3PP4fDh+XrG5CCNFWSEDVgg2/rBsPzRzvW/5mdSZfrh5JeaOUv6mMXnHfkZZy4IKOay1JpSxrISoVGA0WOnc4hU7nvaPqdCks/LEXOw525Oabb6Nv37643R7WbEqo9ZjpmQUXVAchhDhXa5iH6mweTQwZ2RWJKMYNP8490zK5b7KdeZ9+KS1VQgjRRkhA1cJdP3Ew1024zLf8+jwLm/fG+5Yjw/Pwd86ltDi/uuJVOB3F5J3+CI3ajb+phE7tT6HRuACw2VUsWNaXkxnx/OY39xIeEU5qRh5PvvwZ2/acqPW40ZFBF/7ihBDiLE09D5XL5Wbxim0sXrGtUSbjXbd5Lzl5Zt+yyc/GgF4nuGnSdu6aVMC6zXsbfA4hhBAtnwRULZyiKPx25tUM6V/RV/+ROYGcSqu4K9qlYzI5SW/hdDprPZbH7STr2Lto1TYCAwrp0C4Z9ZlJfEstGv63pD8O1TDunjUTrVbLNz/t4IFn/sf+w8m1Hjc40MSoIfG17iOEEM1tzeYDvPvpGt79dA1rNl9Yy351CtK306tb1eujVuti9JBDFKRvb/A5hBBCtHwtIqA6ffo0b731FtOmTaN9+/bo9XrMZjP9+/fnmWeeIT09vdbydrud119/nQEDBuDv709QUBAjRozggw8+aFDShpZCrVbx/O+vp1NcOAAOJzz4WndKSvXe7SoP/Xsc4fi+D2s8hsfjJvP4R2hVhYQE5xEXk0b5zd+CYj3vfzWQdl2mMm3qNaRnFfDUq5/zf/NWYbV5u6yoVAqTruxLUKBfpeMGB5p4+akZ6HXac08phBAthsvl5vNvNjGkh5ohPdR8/s2mBrdSDetzCq3WVe02rdbFsD6nGnR8IYQQrUOzT+ybnJxMx44dKwU+AQEBlJaWsm/fPvbt28cHH3zA4sWLGTt2bJXyRUVFjBs3jp07dwLg5+eHxWJh69atbN26lWXLlrF06VI0mmZ/qQ1i8tPzyh9v4uHn55NfWEpyposX3uvLPx/biVrtwaC3MyD+Fw4d6UbH7uOrlM9LXoLafYqIsBwiw3N867Py/Ji7sB9XTbyDuHYxfLdqFx98ttYXSAF0bBfGUw9OpXuXaGx2B5u2J5KeWUB0ZBCjhsRLMCWEaPHWbD5AqKmQR27OBuCNz92s2XyACaPrP+VDWHDtY6RCg+z1PrYQQojWo9lbqFwu7929KVOmsHDhQvLy8igsLKSsrIwVK1bQqVMn8vPzuf7668nIyKhSfvbs2ezcuZOQkBCWLVtGSUkJZWVlzJs3D4PBwPLly3nxxRcv9stqEpFhgWdag7zB4aptCp8u7+7bHhhQTFzQQnKzK493KsregNuyi5jIzErBVHKGmfe+HsaNNz+IwejP03//knf+91NFq5SicNt1I/jv3+6he5doAPQ6LeNH9ubOG0YyfmRvCaaEEC1eeevU7GvzuKz3SS7rfZLZ1+bx2dKGtVKZAnvXuv3waVOjjNUSQgjRsjV7QBUcHMzu3btZvnw5M2bMIDjYOzZIp9NxzTXXsGLFCgwGA0VFRbz//vuVyu7evZuvv/4agI8//pipU6eiKApqtZpZs2bx2muvAfDmm2+SlZV1cV9YE+nRJYanfzvNt/zPz81s2x/tW46JykIp+g82awkAlqKD2PJ+IC42ldCQisQViUnBfPrDOGbOvJ/NO05w3x8/ZHdCkm97+5hQ3vnrTO699Up02tbduieEaNvKW6eG9K0Y7zSkbzJh/oUNGkul+N+Cw1H99dHthn9/qePdT1fX+/hCCCFah2YPqAIDA+nfv3+N23v06MHw4cMBfN36yn3++ecAdO/enWuvvbZK2fvvv5/AwEAsFgtLlixpxFo3r9HDenDfbVf6ln/7egwZOf4AKArEdzqFK+dZrOmPoy79Dx3jkgkKKPbtv+tgOKt3TWfy5Ot48c2lvPnhD1is3q4pKkXhlmnDee/vv6FHV5nZXQhx8TTFxL5nt06Z/Gy+9SY/G7OvzWvQWCpFZSLP+SgOZ9WgSqWCB68v5pufdvLdql31rr8QQoiWr9kDqroIDQ0FKroHllu3bh0AEyZMqLac0WjkiiuuAGDt2rVNWMOL75Zpw7lmrDcQtdpVPPBqF6w2b/c7jcZN5/apdIw9RfvYdMz+Zb5y67dFkZj9G4yBcdz/9P/Yue+kb1u76BDe+sudzL59LDqdtEpdilQqle8hREvTFBP7Vtc6VW5I32RCTQ1rpfLoR5LDx2SX3kBuyTAKi/x926ZemUSv9h7+b95Kdu4/WctRxKVKrrlCtA0t/v9wp9PJ5s2bAejTp49vvcfj4fDhwwD07l1zP/ZevXoBcPDgwSas5cWnKAq//81EBvbuAMDxNB1vLuhMbUkNv98QS57rAVZuSeKND1ZQZrGdORbMmDyU91/7Db3i212M6otmkpKS4nsI0dI0xcS+V43qze9mFFdqnSpn8rPxwPX5XDWq9rFQ56OoTLiMd+Lwe5oc+0O+boB6nZOn705DhYeX3/6G5LTcBp1HtD5yzRWibWjxzRD/+c9/yMjIQKVSMWvWLN/6oqIiSktLAYiJqblrWvm286VeLzdo0KBq1x86dIiYmBgSEhLqWvWL4qaJPUjNyCErt5T+3ewoSs37Bvr789hbK7HaKuarCgs2cfu0/nSOC+Vo4pGLUOOLz2KxALS4z07UTWv8/CwWC1qtJGy5UGazGbPZO1FuY03sm5a8j/7da56YfFDv02zZ/wt9+49s8LkA/IKHk5zWkc5xxwAY2DONa4ZFsOwXeH7OQv798iwC/I2Nci4hhBAtQ4tuodq3bx/PPvssAA8//LCvtQnwBVPg7dpXEz8/77xJJSUlTVTL5uVn1HH/LcMwGbW0i7TWum+AqahSMDV6SCf+OHs0neNCm7qaQgjRLMqKNlbbOlXO5GcjK2NVo51PURSUwN9SWub9XlKp4OHbThDsD6kZ+bz81lKczurnrhJCCNE6tdgWqvT0dK6//nosFguDBg3iH//4x0U577mJL8oNGjSIoqKiSt0OW5LQ8Bgyct6iX/ea98nIMQAQHRHEHx6YQv9e7S9S7ZpXectGS/3sRO1a4+dX200ecXG1bz+K/YcqT7kRHppDVIR3PiqrTce+RBV9BhUSGRbYKOc0+nfkdNIAenT6BUWB2Mgi7p1azD+/NLP7wCn+b94qHr13IkptXQqEEEK0Gi2yhSovL48JEyZw8uRJunXrxvfff4/BYKi0j8lk8j0v7xJUnbIyb0IGf3//Gve5FPTtEce+05fjcKir3e5wqHn7y2CumzCID/5xb5sJpkRlMTExvocQbYEhcCDh3V+t9EgtmozL5f36M+jtDOlZyqLvtzXqef2j7yU3L9i3fNPEE/Tp6A2glq/ZzTc/VX/zTlxa5JorRNvQ4gKqwsJCJk6cSEJCAu3bt2f16tVERkZW2S8gIMAXVKWlpdV4vPJt0dHRNe5zqYiI7sbH38RXCaocDjUffxPPiOGX88g9EzAadM1UQyGEaH7RHaeQmV3R1XnC5Snk5WXhqS2rzwXS6kNILxyN0+m9Hpv87Dx0Uzr6M0Pr3v1kNdv2HG+08wkhhGg+LSqgKi0tZfLkyezYsYOoqChWr15N+/bVt6QoikLPnj0BOHCg5pS35dn9zh5/danKyilm7nf+zH6pP2t+6URCYjRrfunE7Jf6M/c7fwx6fXNXUQghmp1KpSG9+Crcbm+LUYC/hVvHZTZ6F7yQdreQmllxQ3DUwBSuG+UNsNweD6+88y2nUnMa9ZxCCCEuvhYTUFksFqZNm8aWLVsIDQ1l9erVdOvWrdYyY8eOBWDVquoHFFutVjZu3AjA+PHjG7fCLVB0ZBAWO+w8pubPH4TxyJx2/PmDMHYeU2Oxe7cLIURL1RQT+9YkuuP1ZOWG+JZ7d96Ny+WspcSFU2sMFDmnUmbxdllXqz3cfk0i3eK8vSvKLDaef30hhcVltR1GCCFEC9ciAiq73c4NN9zAunXrCAoKYuXKlbXOLVXutttuA+Dw4cMsX768yva5c+dSWFiI0Whk+vTpjV7vlmbUkHiCA014PFBYBtlF3n89HggONDFqSHxzV1EIIWrUFBP71kSl1pKSNwa3W8HhVFNS4o/DUfN43PoKjb2aU6kVPS26dsjjxjEF+Bm8ff/Sswp46c2lOCTznxBCtFrNHlC5XC5uv/12fvzxR8xmMz/88AOXXXZZncoOHDiQm2++GYC7776bFStW+I75ySef8PTTTwPw+OOPExER0TQvoAXR67S8/NQMggNNldYHB5p4+akZ6HUyL44Ql4Li4mK+++47XnjhBa655hrCwsK86boVxTfheW3cbjcffPABI0aMICgoCLPZzMCBA5kzZw52u/285Xfs2MGtt95KTEwMBoOB9u3bc99993Hs2LEGva6mmNi3NjGdb+boyQ7sPjgIq+636PX+OJ2uRg1uVCo1+N9IXkFFBsGpVx7mtkkVQda+Q6d5538/NeoYLiGEEBdPs6dN37x5M4sXLwbA4XBw/fXX17hvXFwc27dvr7Ru7ty5HD9+nJ07dzJlyhT8/PxwuVzYbN55R6ZOncpLL73UZPVvaXp0iWHBOw+xaXsi6ZkFREcGMWpIvARTQlxC1qxZU+9W9/LrbPkNKJ1Oh1qtZs+ePezZs4eFCxeydu3aGjOjzp8/n/vuuw+n04miKAQEBJCcnMxHH33El19+yXfffce4cePqVbemmNi3Niq1DlO7FwnQBGCzO/nmp50s/P5Xbrt2BNOurtuNvboIjhjCqcPxBJp3ola7CTJb6d1hK7NumML8Jd7sgj+s20uHdmHMmDy00c4rhBDi4mj2Fqqz+8hbrVYyMzNrfGRnZ1cpHxAQwJYtW3jttdfo378/iqKg1+sZPnw477//Pt999x0aTbPHjReVXqdl/Mje3HnDSMaP7C3BlBCXoIiICCZPnsyLL77IBx98UOdyzz//PCtWrMBgMDBv3jzKysooLS1l2bJlhISEsH37dh544IFqy+7bt4/Zs2fjdDq54447yMzMpKCggKSkJK6++mpKS0u58cYbq71Wt1QabSCKovDDur38Z/4qsnKK+Pr7rbhcjTt+yxx1MxlZ4b7lsUNP4686xlWjKrq3f7BgLVt3NayVTwghxMXX7AHVlVdeicfjqdMjKSmp2mPodDqefvpp9uzZQ0lJCYWFhfzyyy/cf//9MnGiEOKSM23aNDIzM/n+++/5y1/+wtVXX12nchkZGbz99tsA/OMf/2DWrFmo1WoURWHq1Kn873//A+CLL75g3759Vcr/+c9/xuFwMHjwYObPn094uDdA6NChA0uWLCEuLo6CggJee+21RnqlF8/E0X0Y3EPPn+6yM7x7Nut/Odiox/cP6kJaXh8sVm+2Va3Gzaj+u5h4eRy942MBb+a/v/3ft5xMbj0BqRBCiBYQUAkhhLgwanX1E3ifz+LFi7HZbAQGBnL//fdX2X7dddcRHx+Px+Ph888/r7StoKDA103wiSeeqFIHf39/HnzwQcAbkLW28UD5met49bcHuG3qXh648TRfLduC2924ryG8wy2kpEX5lvvGZ5OZvJynH5pMRFgAAGUWOy/MWUhBkWT+E0KI1kICKiGEaCPWrVsHwOjRozEYDNXuM2HCBADWrl1baf2mTZtwOByV9jnXxIkTAUhPT+fQoUONUueLRa3YiI3MByA2Mp8BnVL5dXfjdr8z+IVRaB9MQWGAb93k0UfYs2sLr/zhJt+k6xnZhfzlX4uxOxo3jbsQQoim0bYGFwnRxvn5+TV3FUQzKp/ovLZpKconQT906BAej8fXbbq8bFRUFKGhobWWLd+/LhOqDxo0qNr1hw4dIiYmhoSEhPMeozF43LEUFvkTGFCCosC916Xx8L9W4a+zNmrXcY+7B6dTEzD7l6BWu4kIKSM6YCMppwK5Y1p/Plq4HQ+QcCSFv/zzS26b2r/VdV23WLzp5y/WZ9eS6fV63/PW8n60xs/PYrGg1cp4cdF8JKASog1paFpr0bqlp6cDEBMTU+M+5dtKSkooKSnxZd2rS1mj0UhQUBAFBQW+/VsLRWXkUFJ3hvfbCUD7mFx6xGZx/HQuXTuENeJ59GSX9iIrJ5/oyCwAxg1P4j9f7KF3vyuZNr4X363xBq/b9iUTFuxHSJAfeQVlhAb50bd7NDpt/bp8iotv2bJlzV0FIcRFIAGVEEK0EaWlpYA38KnJ2a2YZwdUdSlbXr6goICSkpI61Wnnzp3Vrh80aBBFRUX06dOnTsdpDHZrO4pLHsbsX4aiwIMz0vnrJ2lcP+XKRj2Py9WT1EMnCA4qwKC3o9e5GDv0MEm5g3nk3muxOTX89LM3KciKn49UKhscmMjLT82gR5eaA9vmVt6ycTE/O9F4WuPnd77rkhBNTcZQ1aK4uJi0tDTS0tJwOByVUrwLIYS4tOgMQZxMq+im2KldDv7qYxw9mdGo51Gr1eiDJpCeGelbN7BnJjkZ68jLy+PReyf6Mv+dK7+wlBfmLMJmdzRqnYQQQtSfBFS1eOONN4iNjSU2Npb9+/dTUFDQ3FUSQoh6M5lMQMUYieqUlVVklzt7ct+6lD27fE0TA7d0gbH3U1rmvdutUnl45JZ0Fn3/a6OfJyx2OJl5sRQWmX3rpoxOZP26lWg1aq66oubWgfzCUjZtT2z0OgkhhKgfCahq8eSTT5Kamkpqaip9+/YlKCiouaskRIPExMT4HqLtKf/c09LSatynfJu/v7+vu19dy1osFt+Np+jo6IZWt1nojWGcTO3uW+7WMYspIxs/mYuiKATFXEtqRgRutzfpRExECXFhezl4IIHCotoD1/TMgkavk2h8cs0Vom2QgKoWZrPZdyHUarWoVPJ2CSFar/KsewcOHKhxn/Jsfj179qy2bEZGBrm5ubWWPXv/1sg/6gEsFm92NrXKQ2zgd01ynqCwHhRZOpCdW5E18arLT7B751rCQ2ofExIdGdQkdRJCCHHhJEIQQog2YuzYsQBs3LgRq9Va7T6rVq0CYPz48ZXWjxo1ypeWePXq1dWWXblyJeC9K39uQNaaGEyRnEzr6lsODyrBarM1ybnCO9xIelYYdrv3vfUzOBk9+ChuSwbBgaZqywQHmhg1JL5J6iOEEOLCSUAlhBBtxA033IBer6egoIAPP/ywyvZly5Zx5MgRFEXhtttuq7QtMDCQyZMnA/Cvf/2rSpKe0tJS3nvvPQBuu+22Vjd30rkMYfeTmxdE4vGOnM65qslSlZsCorF6upN2VoKKIX3SsBbv5rG7R1YJqhTguYevRa+TOXeEEKKlkIBKCCFaoZycHN8jPz/ft76goKDStrMDn6ioKB599FEA/vjHP/Lpp5/icrkAWLFiBffccw/gDYj69etX5ZwvvfQSWq2Wbdu2cffdd5OTkwPA6dOnueGGGzh9+jRBQUE8/fTT9XpNLSmzqp85jgzLbEztXqJd/B2kpBfyxgcrKCwqO3/hCxTV+QZy8gIpLvEGT4oCU8Yc5UTiXub96z6efmgqZpMBAA+w79DpRq+DEEKI+pOASgghWqHw8HDf47LLLvOtHzFiRKVtp09X/vH9yiuvMHnyZCwWCzNnzsRkMmEymZgyZQq5ubkMGTLE19J0rv79+zN37lw0Gg2ffvopERERBAUF0aFDB1auXInJZGLx4sWEh4fX6zW1tMyqodEjUGvNfPTleu596gN+WLeXpT/taPTzGAxm3LrLSMuI8iWoaB9dRJfYY+zbs5urR/fl4buv9u2/+IftTRLYCSGEqB8JqIQQog3RarUsW7aM9957j+HDh6PX61EUhQEDBvCPf/yDTZs2Vcrud65Zs2bxyy+/cPPNNxMZGYnFYiEuLo7f/OY37Nmzh3HjxtW7bi01s2rn9hH4G2DiEIUtv26jzNL446miO08mv9hMTl6Ib93Vlx/n4IFf2bljOwH6UgbEB6FSQZnFzlfLtjZ6HYQQQtSPprkrIIQQ4sJ5PJ56l1WpVDzwwAM88MAD9So/ePBgvvrqq3qfvyZms9kXzLWkzKqdI4t4+4lc+nRL4Ze9MSxfs4ebpw5r1HNotXp0AWPIyv6R4MBCtFonZpODsUOT+HGT96u6cwTEBBn55aCNb1fu5MbJQwkNbp3zfQkhxKWkZXxbCSGEEC1UoP4XhvY7gZ/RzsiBqaz7eRN2h7PRzxPVYRSFZYGkn5WgYlj/FEZedpoxg5PoG5+Jv9HDiF56HE4nX3y7pdHrIIQQ4sJJQCWEEELUQmW8CqfTm+XPoHfwwPQ0Vm7Y3/jnUakxR0wiv9BMSal3MmG1CiaOPMH4EUncNPEQj8/aSud2JcSEqvl+zR4ycwobvR5CCCEujARUQgghRC0CQvuSkhnlWx49KI0fVm7E5Wr8LIThMf0pskaSnhVOdb06zSYHd0zdT4i/B4fTxYIlmxu9DkIIIS6MBFRCtCHR0dG+hxCi7mzaWbhc3q9MP6ONmdck8/PWQ41+HkVRCGt/HRq1k5qm8jKbHAzpkwvATz/vIzUjr9HrIRqHXHOFaBskoBKiDdm5c6fvIYSou8CwwaRlRfiWxw1LZcn3GxqUHKQmwaEdsbtqzxnVLtLbOuZ2e/hk0aZGr4NoHHLNFaJtkIBKCCFEi9CSJvatTqlyh2+eKLPJyozRp/h19/EmOVeJs2et28PCuvier91ygKTk7CaphxBCiPOTgEoIIUSL0NIm9j1XYPjlZGSH+ZavuSIFp6NpJthVqyJwnEmEcS6HU01gQBTDBnqDKo8H5i/a2CT1EEIIcX4SUAkhhGgRWurEvuUURaHIebOvlSrQXIafc0WTnMvlKOJUcly1QVVWdhglBRncfdNo37qN245w9GRGk9RFCCFE7SSgqkVL734ixIWKiYnxPYRoacxms+/vsyVN7Hu2wKhxZOWG+JYHdj+M1WZr9PNodGFYrEaOHOvK6dQYLFa9b1tIcAHpmSV0iA3hiqHdfes//npDo9dDNIxcc4VoG1ret1UL0tK7nwghhLi4FEUh3zYdh1NNZnYYKZld0Wm1jX6e0NgrcbpUeDwqCosCSUqOw3WmZcxosOFvymb3rp3MmnGFLxvgtj3HOZCY0uh1EUIIUTsJqGrR0rufCCGEuPiCoiex5/A48l33067Xc3iAhCONG8hotH4Yw2fgPJOq3enUkp1TMX5r7NAkDh/cSmiQgfEje/vWz5NWKiGEuOhqz8vaxpnNZsxmM0CL7X4ihBDi4lIUFXG9HsLj8fDDur18+d0vpGcWcOt1I7j7ptGo1Y3zXREU3h//oG7kpq6nJD8BcBMSVIBO58DP6GTMkBNs2byJu24cxdotB3G7Pew+cIrdCUkM7NOxUeoghBDi/CRCEEIIIepBURQ2/HqYtMwC+nRSWLn2F1Zt3N+o59Bo/YjsOJl2PX9LbqGZ9LPmwhraN5Xi/N1oVQ4mjunnW//x100zP5YQQojqSUAlhBCiRWiNiYCmj+/A03fY+ffTB5nzaCpLlq/B5Wr8eusN/viHX01OXiAlpX4AqFRwzehjrFmzijumX45W480IePBoKtv2NM38WEIIIaqSgEoIIUSL0BoTAUX5r+DOaXsJCy5haN80Zk7M4Kef9zbJuWI7DiK/rB1pmZGUN0B1iSsgMugIxQXZTBk/wLfvx19vwO2WViohhLgYJKASQgjRIrS2REAul5sjJ92+LHsAk0ef5rNFP1JcYmn08ymKivbx15OZE0BufrBv/TWjjrNxwypumTYMvc47NPpYUiabth9p9DoIIYSoSgIqIYQQLUJrmIfqbKs27sekt1da52e08/ubc3ng2Y/IKyhp9HMGBEXhMQwhPTMC55lJf4MDrQzpfZzEwwlcP3Gwb9/5CzfiagXdJoUQorVr2d9WQgghRAvkcrn5ZsVaJo6qmi596piTRPgX8MgL80lOy230c3fqPo6MvFAyz0qjPmbIKU4c/YVrr+6Pn1EHwKnUHNZvOdjo5xdCCFGZBFRCCCHEBVq1cT93Xp2Ov5+tyja12sMHzx9EpxTw5MufYbU5GvXcWq2B8LhrSE4Lx2LVA6DTurn68mNs2rCeG68Z4tt3/qKNOJ2uRj2/EEKIyiSgEqINGTlypO8hhKi/EJOTSVck17g9wGxl/ktHuPGqjhj02kY/f2RsL4rtXUnLiPStG9AjC60ngZGDO2A2GQBIyyxg5YbGTeUu6k6uuUK0DTKxrxBtyMKFC5u7CkJcEjqEbam2depsEaEl3D5+MfsPdqBXr/6Nen5FUejcawpJCcmEheQTGFAMwNQrj/Hh0pXcPG04H325HoBPl2zmqiv6oNPKV/7FJtdcIdoGuboKIYQQFygwZBT7D2VUuy0iLJvI8BwAwoKLIXEh4A2oCovLMJuMqFRKtWUvhMk/FEPwKE6lFtHHvwSVykNMRAl9Op/AZehLUIAfBUVlZOcW8f2aPUyfNPj8BxVCCHHBJKASQgjRIhQXF1Nc7G1paekT+xoCB2IIHFjtNpfbxum0p4iLTuF0SgyRcdcBUFRi4fG/LKBbpyj+8OAU30S8DdGx6+Xs37qPqPA8IsK8CTAmjTrBnI9/4eapw/ng8/UAfP7NFq4Z279Juh8KIURbJ2OohBBCtAitcWLf6qhUerQR/yTh2BCKuIPQ6CHY7U5e+OciTqflsmbzAZ77x9eUlFkbfC61Wku7rlNIPBmDw+G9R+pndHDV8JO4y9IJCzEDkF9Yyrcrdzb4fEIIIaqSgEqINqR8jp+YmJjmrooQVbS2iX1ro6h0hHV+hvDYEQCo1So6tgvl8r4ugvyd7E5I4omXPiMnr7jB5wqL7IyVvqSelaBixIBUXNYjXDe+t2/dl9/9QmlZ7eO+ROOSa64QbYMEVEIIIVqE1jax7/koinLWc5g81MLrvz/MsjePEBfh5MTpLB758yecSslp8Lm69prA4ZOxlJYZAVCpPFx/1TGy048SHREIQHGJlSU/bG/wuYQQQlTWur+tmlhxcTFpaWmkpaW1+P78QgghWq7007vp1+kbggLKCA4o48u/HaZjlJPs3CIe/cun7D9ccwr2ujAYAwiJHsfxU7F4PN51XeLy6d4+hdGXVbSOLPx+G0UllgadSwghRGUSUNXiUunPL4QQonnFdBhIRk6kL9gJNFv4/NVDdI1xUlJq5Y9/+4INvx5u0DnadRpESk438goCfeuuH3eMwtwTdIgJBqDMYuPrZb826DxCCCEqk4CqFpdSf34hhBDNR1FUBLT/G4knO/qCqgB/K5++cogecS4cDhcvv72UxSu21fscKpWazj2vISGxAy6X9+s90Gxl0uWp9Oqg8+33zU87yC8obdDrEUIIUUECqlpcav35hRBCNB+1Wod/u79z+ERFUGU2WZn30gH6dHLi8cDO/Um4GtC9PCikHW7dMFIzInzrxgw9hZ8mm27tAwCw2hx88d0vDXotQgghKkiEIIQQQlwkao0e/3Z/49CxTr6gyt9k46M/H2TCCD9eePR61A28edelxxj2He2CzeZtldJq3Nx6zUliAp2Uzye8bPUusnOLGnQecemx2hzsSEhh5aZE1mw+gM3uaO4qCdEqyMS+QgghWoTWNLFvQ2i1BkztXuVA4vP0jj+BooDJz8YrD/zC7lOX0SX+Ct++Lpebb37aAcD1EwejVp8/2NLp/YjpeDVHTqbTr8cJAHp0zqJ3lxiyi4M4mFSKw+HiH+8uZ0CvDkRHBjFqSDx6nUz625YdPp7GC3MWkV/o7Q664ucjBAeaePmpGfToImnfhaiNtFAJIYRoEdpSIiC93oCp3V9IOFLRUuVntNMxaB4Z6Sm+/ea8t5x3P13Du5+uYc3mA3U+fnRcX1JyB1BY5A9407bfPOkooSYbhjNx054Dp5i3cAN//7/vuPP373L4eFqjvT7RutjsjkrBVLn8wlJemLNIWqqEOA8JqIQQQrQIbS0RkNHojzHmz+w73Bm3B0rLjJzOiCciwjv+aemP21m9qSKI+mzpZlyuurXaKYpCfO+J7D5YEbCFBZcydXQO7cOr7i8/nNsup9PFh1+srxJMlcsvLGXT9sSLXCshWhcJqIQQQrQIbTERkL9/IIaoZ/llT18OHu9Ph96PoVLryMkr5r0Fayrtm5qRz5pNCXU/dkA4av8rScsM8627akQSnWMUQs1V988vLOWd//3EnoOnyCsowVMeiYlLUlZuEfMWbuCOR/7L0h931LpvembBxamUEK2UjKESog15+umnm7sKQohzBAaGEtDvL+Bxoai8X8vBgSZCAv1wOQr4833ZAPzx31G88/FKLuvbibCQaiKianSKH8meX/YREbYJrcaFXu9g1rXJpP8vjqIyDw5X5f1/+nk/P/28HwCTn5646BDiYkKJiwmlfaz335jIYLQadbXnK09qkFdQRmah0irGZlltDjZvP0J6VmGjjydraddct9vDjn0nWLZ6N7/uOoa7jkFzdGRQ01ZMiFau2QOq4uJi1q1bx/bt29mxYwfbt28nNzcXgEOHDtGjR49ay7vdbj788EM+/vhjDh06hMvlomvXrtx+++08+uij6HS6WssL0ZY8+uijzV0FIUQ1FEUBpeIree2Gzbx072mG90tCp/N28/tTsZYXPwznN09+wHOPXMfwy7qe97gajY64rtdw5EQSfeJPAdC7WwaDekZTYlVTVAZ2JxRZ4Nzf1qVlNg4fT+fw8fRK61UqheiIINqfCbTKHza7ndf+s7xVJTU4NxED0Gh1ttoc9Bk03heo2eyOZgsu8wtL+ennfSxfs4eMrIIq24MD/bBYHVhtVbt8BgeaGDUk/iLUUojWq9kDqjVr1jB9+vR6lXU4HFx//fWsWLECAJ1Oh1qtZs+ePezZs4eFCxeydu1a/P39G7PKQgghRJPJzT5Nl5BlXD7wRKX1k69I49V5oZRZ7Tw/ZyHTrhrIA3eOx6Cv/Ud6eFQ39m0fQaeyTEx+VlQqD3dMPc7+o93x03mjKIcLMgrVDOzXnfTMfE6n5VFmsVV7PLfbQ2pGPqkZ+fyy61it5y4fm7XgnYdaXEtVbYkYnvzrZ0wZNwCDQYdep0Gn1aA7869eV/Fcp9P4tut1GrRaDXqdllMp2bzyzrdNEqjVlcfjYf/hZJat3s3GXw/jrGb83cA+HZl21UAuH9SNY6cyawwuW9pn19r9/PPP/OW5a7nvt//ljjvuaO7qiEbQ7AEVQEREBIMHD2bIkCHExsZy//3316nc888/z4oVKzAYDLz33nvceeedqFQqvv/+e2bNmsX27dt54IEH+Oyzz5r4FQghhBCNY/u+U3Qwa3G74exhZEaDnb/cm8Nz73uTVixbvZs9B0/x8h9m0C46tMbjKYpCt95Xs/NAAqOHeMdgRYYVcs91eSSeMlNQrLDvqIr4WC1PPTgZnVaLx+Mhr6CU5LRc3+N0Wi7JaXlk5RZWac2qTX5hKet/OcTEMf3q9X40BbvDyXufrqkxEYPN7mTJecYVXaj8wlKeeuVznpw9hc4dIoiJDEJTQ9fJhigps7JqQwLLV+/mVGpOle1mk4GJY/oxZfwA4mIq/m56dIlhwTsP8eWSNeQWlNG/b/dW0WWzNfrLc9eyfksRJ0//hptvvhmtVt7j1q7ZA6pp06Zx/fXX+5aTkpLqVC4jI4O3334bgH/84x/MmjXLt23q1Kn873//4/rrr+eLL77g6aefpl+/lnMhF6K5lP8/A9L9T7Q8bWUeqvOZNP4KDibocTqPotM5K22bMiaZXYmdWfJzCW43WG1OggJM5z2mnykYbcA1ZGSnEhWeD8DwAUnEdwzC7tAxZlAAi9bAW/83n0EDe9O1SwfaxUQRGuzPgN4dKh3LanOQmpHH6bRcUtK8/+49eIq8guqDE4B3/vcTqRn5XHv1ZXUe/9UU8gpKWL56N8tW764xmGpMWUnbfM8jOg7FYnXwyr+/AUCtVhETGVQxRi0m1DdmzexvrPW41Y37OpWSw7LVu1m35WC1Xfd6doth2viBjBnRs8YgSa/TMqhPOwD69Oldz1ctarNlyxbWbymiS0c9x5NsfPHFF8ycObO5qyUaqNkDKrW6fndnFi9ejM1mIzAwsNoWreuuu474+HgSExP5/PPPJaASAu/Nh3ISUImW5o033uCll17yLYeEhDRjbZpXu5DNVYIpALXazZ/u3UDPjgP44FsDf/ztNPxNhjods0PnIWzduJFrr9yKSgU6nZOoCG8LRnRkJn6G9vxjHiz/wZsEQ6/X0aVTHF07d6Brl/bExkSiUqkw6LV06RBJlw6RvmOv2XyAv//fdzWe22Z38vk3W/jyu1+4YmgPpk8aTO/4WO/YsYvgyPF0lv60g/VbDlbb9a06Yy/vRfuYUOwOJza7E7vDif3Mv9UtO878W1xiwWb3fnY5p371HS+i49BKx3e53CSn5ZGclgccrbQtKMDPG2DFnhVsxYQSERbA0ZMZVbrmqdWqalPqG/RarhrVhynjB9CtU1Rd3y7RhP7+lynodAo/fdWTUdMO8PdXHvD1sBKtV7MHVPW1bt06AEaPHo3BUP2XyYQJE0hMTGTt2rUXs2pCCCHq4cknn/TdIJs0aRKlpU3fgtASuVxW2of9WuN2rdbFzRN30qtzNClFKbjd7Sr9GDt8LI0eXauO01GpNWi1QXg8ClC5z55W4yK+y2ku7x/M7sN6LDYXNpudg4ePc/DwcQCMRsOZAKs9Xbt0IDoqApXKGxCNGhJPcKCJgqJSAo2g1VQkuwDFl4Ld7fbw89ZD/Lz1EF07RjJ90mDGjuiFTtf4P0ecThcbtx/hmx93cCAxtcr2kCATZRZ7jYkY/vDA5Hp1dztfcNkpLoySMjvZuUU17lNQVEZBURn7DidXWq/VqHG73bjclT+/c4OpjnHhTLtqIFeN6oPJT3/Br0E0jb1797J8VQGz74qgcwcDTzwYzR//eppvvvmGG264odHO09wJ33bs2ME///lPNmzYQF5eHhEREUyYMIFnnnmGrl3Pn0ynNWq1AdXBgwcB6N275ibpXr16Ad4/Ho/Hc9HuhAkhhLhwZrMZs9nbHaytzENVndLMd4ltZ691H0WBvvHpBGf8j0MHdfTuMxiALTuO8uc3FjH28l48+puJVVqvOrXLRq2ufgCUVuPihqtPEB7ckRMp/uQXq7BY3VhsLu/DYiXh4FESDnpbU/z8DHTp5A2uunXpwMOzxrB4yQrUZ31sLjfceP01qLQGlv64g32HTvu2HUvKZM573/PBZ2uZMn4g064aSHhoQH3eskoKispYsXYP363aRU5ecZXtvbrFMn3SYK4Y2r1JEjGUB5fVdSkMDjTxf6/cjV6nxWK1k5Ked9YYNe/zlPQ87I6qrZMADqer2vXl+sTHct/t4y5q65+ou9f+Mh6VCv74O+8NjwdmRvL3d1L520szmT59eqN9Zs2Z8G3+/Pncd999OJ1OFEUhICCA5ORkPvroI7788ku+++47xo0bV+/X1lK12oAqPd2bxjUmpuZsOeXbSkpKKCkp8X1R12bQoEHVrj906BAxMTEkJNR9UkXRMlgsFgD57M7RWt6P1vj5WSwWGWQs6i3hRC927qk+6AkOKGXEwEQCzaW43ArZuZF0794H8I4PeuOD7wFYt+UgCUdSeOa30+jfq72vvFFvrfXcEaEFTJ+wh5JSE+lZwew7Es6JVBOlFj0ul6ciuLK5KSuzsv9AIvsPJAKgABo1+BvVaDQqnE43JRYXa9b+zPPPPMQVQ7tz4lQWS3/awZpNB3xBQ2GxpVG6Ax4/lcnSH3ewZvMBHOdMsKVRq7hyRE+unzS4Upa98kQMm7Ynkp5Z0CjzUOl1Wl5+agYvzFlUaf25gZrRoKNbp6gqXfFcbjdZOUVnJQTJO5MQJPe8474G9+9Cn+7t6l130XSOHj3K19/lcuv1oXTp6L3RYfZX8/v7onnpnymsWrWKCRMmNNr5miPh2759+5g9ezZOp5M77riDN998k/DwcE6dOsXs2bNZtWoVN954I4mJiYSHhzfaa20JWm1AVd4VxGiseeCmn5+f73ldAyohhBCiOV0+aiIwsdptFksZ36xfxGVdtxFoAl3InWi03h9nBr2WEYO68eP6fQBk5xbxh1c+4+Zpw7n7ptFoNWocnvbAgVrPr1IgwL+UAP9SunVMpaTURGpGEPsSIziRasJi83Yhc7s9vuDKYnOBB6LD9WjOaqJyutykZVvYn5DIoIG96dwhgifvn8x9t13Jj+v28e2qnWTlFPmOV1t3wOoSMWjUarbsPFql9atccKCJqVd5W79Cgqq/o67XaRk/snETMJQHap2+e823rq6p49UqFdERQURHBDF0QJdK275fs5s3P/yxxrIyAW/L9frrr+N2wzOPxFZa/8i9Ufzzv2n87S8zmDCh5m6gF6K5Er79+c9/xuFwMHjwYObPn+/Lk9ChQweWLFlCr169SE5O5rXXXuONN95o2ItsYVptQNVUdu7cWe36QYMGUVRURJ8+fS5yjURDlbdsyGdXWWt5P1rj51fbjR4hGsJo9GPiNTNJS5+EEqIhVF+RuKM4P4k7xidw9QAP//7KSFK6FY8HvvpuKzv2nuS5R67FqAzDaluNQV913JDDqaKkzEBwQJlvnUrlIcBcQoC5hO5dUikuNZGaEcKew2EkpZlQqTSYzvy5V9e1XqNWEROuZ/+BIwzs39PXjTPQ7Mct1w5nxpShbNl5lG9+2sHegzV3B+zVLYY3PvihUguN0aDFqNeRV02rTXznKG6YNITRw3ug0zbPT51zg6fGSD9+1RV9mLdwY43dCWUC3pYpOTmZ+fM/4rpJwfTp6VdpW0iwhgdnRfLGu+ls3ryZkSNHNvh8zZHwraCgwNdN8IknnqhSB39/fx588EH+9Kc/8cUXX/DPf/7zkuqW2moDKpPJREFBga87UHXKyiq+FGRyXyGEEJeKmOiISst2u4WMU0u5esR2VPEeerQP5f0l/fl+SzEut7c73EPPfswDd4whO/gyLh+wC6OhIqiyWLVs3jUAnf9Q7JZEwgMS6dgum0Bz5eAq0FxCoLmEHl2SKSrxJzXT2y3weIofdocag97BmEHphARZySswsH5HNNi1pJw+wWtvfMD4K0cwaGAf3/xLarWKK4Z2P293wOpYrA4s1orXoFarGD20O9MnDaZnt0tzDNHZ3QllAt7W44033sDh8PDM76sfpvLEg9H83/8y+NuLU/l+df5Frl2FhiR827RpEw6Hw7dPdSZOnMif/vQn0tPTOXTokC/XwaWg1QZUMTExFBQUkJaWVuM+5dv8/f2lu58QQohLVtrpffSPP4JK5R171SE2lz/P3sTA+N78Z7GBnEJveu9/z1vDVSPaUVBsIjo0BX8/KyVlBjLy4uhz2Y0EBEUB47HbyjiVl4wlJQGzbjvtIpIJMFfcwFSpPAQFFBMUUEzPLskUFZspKDIQG5WLVlsxfmlov1N8s7oX+4+F4vHY2LRxLRs2/Eyvnj0YM2Yk/qaKObRq6w5YG6NBy/RJQ5p9jquLpSnGfYmmk52dzQcf/JvxVwQw7LLq/z6jI3Xcc2sE783PZM+ePQwYMODiVvKMhiR8Ky8bFRVFaGj1E42fHUAdPHhQAqqWoFevXhw8eJADB2ruC17+4fbs2fNiVUsIIUQ9ycS+9de+8xB270xlsHoZ4SGFABgMdmZM2E3frtG89VVPNu8txgP8sjebrl1H8PVXpQSZFUYNG8C4K8eiVlf8INfp/YiI7g7R3YEbybMUkZK2GyMbCAs8gtlUueUqKLCIoMCqwY9W6+L6qw5yNHkYVpsOo97bMnXq5GHmnziE0ehPt/hudOzYkaioaLRabaXugL/sOsp7n64hI7uwxtc+Y/JQZt00unHeyFaiKcZ9iabxn//8B4vFzbOPxta631O/jWbugkzGjRtHp06dqt2npmEpjaUhCd/qUtZoNBIUFERBQYFv/0tFqw2oxo4dy6JFi9i4cSNWq7XapslVq1YBMH78+ItdPSGEEBdIJvatP5VKxcAhN5CTdwXJB96gf49jqNVuFAV6dElnzu8LWbiqD+9/A7+/ZwKfLN5EaoY3YE3KPsG4K6+q9fgGYwAG4xhgDCUeDwUlB1HbfyTIbw9+htozz2m1Ln4z/TAJibGcTPWnsESLxabgcILVWsr+fXvYv28PKpWKiMhIYmPaERMbS1RUNKOGdMdmd/L3//sOtQpiQtX4GVSUWt2k5bpwu6FdTPV3w4VoCZKSktBoFMaOrH1KgE4dDPToaiQppfYpE5pSQxK+1aVsefmCggJKSkoaWt0WpdUGVDfccANPPPEEBQUFfPjhhzz88MOVti9btowjR46gKAq33XZbM9VSCCFaJrfbzfz58/nss8/Yu3cvBQUFmEwmunfvzrXXXsvvf//7GrtK2+123nrrLT7//HOOHTuGRqOhZ8+e3HPPPcyePbveY1dkYt+GCw4JJzjkNbYeWkrf9osJODMGyuxfxqxrd9C/W3u2HD5JWkY+/Tp5fwLsP5nPU69+zk1ThjF0YBfU55n/S1EUtH69wa83RUCp6xR6y18J8K957EdUeB5R4Xk4nGpKSv3IKzCTlhXIsdNBFJVqsdjAavOQkZ5ORno6O3du9wVYkZHR9O5komOEi/AgBa0WHA7ILvCw/5RaEjGIFk9RQPF4wFP9dAhn79evXz+2bKl+3KBouVpEQJWTk+N7np9fcUEuKCiotC0kJMSXISgqKopHH32U119/nT/+8Y8EBgZy++23o1arWbFiBffccw8At912W5W0jkK0VbWNORRtR1lZGdOmTas0qDgwMJCioiK2bdvGtm3bmDt3LmvXrqVz586VyhYVFTFu3Dhf1xM/Pz8sFgtbt25l69atLFu2jKVLl6LRXPjXi0zs23i69JxOTuk4MpJeoluHJBQF1Go3g/okERG6jJRTnbltcgoAr82PYd+hZPYdSiYqPJCpVw3kmiv7Exjgd56zeLmUDuSX9ifAf/1599VqXAQHFhMcWEyXDmmMHKRQWmYkr9CfjJxATqQEk1+ox2JTsNg8ZKSnkZGeTv9OHjrGOOnYLhd/o3fcV1JKKGFBetSqlpl8wm53sOz7leTmFRIaEoTd4UAn89O1XecJplqChiR8M50ZD1lb2bPLX2rJ4lpEQFXT5F4jRoyotHzy5Ek6duzoW37llVdISEhgxYoVzJw5k9mzZ6NWq30f1pAhQ3jvvfearN5CCNEavfzyy6xduxZFUfjb3/7GQw89RGBgIHa7nSVLlvDQQw9x6tQp7rvvviqZnGbPns3OnTsJCQlh/vz5TJkyBbfbzYIFC3jwwQdZvnw5L774Iq+++mozvTpRzs8UCKZ/se/UYuKjFmI02PF4oKjIzPXjshjQMxmAR27W8OA/wvAAGdmFfPjFeuYv2siVw3ty3YRB9Oha85iIcuqgmTgcGyslpCjncilYHDEYtZmo1c5K21QqD2b/Msz+ZXSIzWJYf7BYdeQVmsnKDSQlI5CMXD/aRZZw5dCDlTITDuylZd3WXnyzdBFdu8YTGRVFeHjEBQfzdruD/QeO+AKfvn3iGxz4nE5O48N5iyguqWhlNfubuO/uGbSPO//72VzsdgfHTqRQXFKGzaE0ynshvDzuOgRUzRxzNSThW/nYqdrKWiwWCgoKAIiOjm6EGrccLSKgqi+tVsuyZcuYO3cu8+bN4+DBg7hcLgYMGMBtt93GY489hk6na+5qCiFEi/L5558DcM899/DMM8/41ut0Om699VasViv33HMP69atIz8/n+DgYAB2797N119/DcDHH3/M1KlTAe+cJ7NmzaKgoIDHHnuMN998k0cffZSIiAhE84tsfyM59qtQMp9HjY3Fa0L44737fdsH9U5lUHwEu455cJ/50edwuFi1MYFVGxOI7xzFdRMGceWInjVmktNog0jNv4fYgI8rBVUOh5rUonswBE+mBDdq5ylUzl/QevahVyej11W9m2002Ik15BIbmcvAXt75sdQqjy+DYcV+DsaNOMixhSa2bMkEFFQqFaGhYURGRRF5prtgYGBgjd1Q6xP4uFwubDY7drsDm92BzX7muc2O3W6ntMzK8h/WYbNVHgtTXFLKex99xSMP3kloSBC6BmTluxhB4K69R1pFENhaeDwtv8W9IQnfyjP2ZWRkkJubW22mv/KyZ+9/qWgRAZWnAc2gKpWKBx54gAceeKARaySEEJeuzMxMAAYOHFjt9kGDBvmel5WV+QKq8kCsfJzVue6//35efPFFCgsLWbJkCQ8++GBjV13Uk1YXyMpD9zP302957Xd5GPQVP/YNejvv/HE/v+zpyM97Y0lM1XL4RLZve+KJDOa89z3vLVjDnx65jsH9Old3CgzBk8l0XE7hiXfx0+eh0sShDpqJITjozB4qXKpOuHSdcHA7ZQCODFT2jWg8+zGoT2HQl1QJnLSamrM9GvQOrh93hGOnI8nM8SOvyIDNmsGxI5kcSACPR0FRqdDqjOh0RnR6P3R6I2q1BpfLzdbte8FjZ1BPN0FmDwXFCvuOlvDOuwvoEBeN0+nCZrdjszmw2+3Y7A5crqqtcNVRFPA3qtFoVDidbkosLiwWK6+/+aG37gY9gQH+BJj9CQjwPgJ9z80EmE0EBPijP+fGcH1bv9xuDzabDavVhtVmx2K1YbPasFhtlJaV8f0PP2N32DH7nVXn0lI+nLeI5595SFqqGqguAVVzdwpsSMK3UaNGodVqcTgcrF69mltuuaVK2ZUrVwLe1qxLLQN3iwiohBAXx0033eR7vnDhwmasiWhOHTt25MiRI+zevbva7eXjoyIjI4mNrUj1Wz7pY02TNhqNRq644gqWL1/O2rVrJaBqYSaM7ou7LIVBvedX2RZgLmPiFQe5fGASR05GsXFPJ05mB7NxVzIOhzegKS2z0bFd9V30y2m0QaSXTIMS6NOnz/krpY7CbbwJOzdhB/IdOahsm9F49qJTJWEyFqPR1B7AtI/JpX1MLgAul4oyq57SMgPFJUbyCv3IzDWRmmmiqKyIolIVThfYHR6sNhddYp1MGVVCZFgRWq0Du0PLmEEBLFrjz4mklPPXvwZ6nYqYcD0rf1rpWzdh4gTSsm3Y7N7302r1BjeZWbm1Hsug1/sCLrO/HwkHj+F0OqoEPv/3/mcM7NfT22pm8wZKVqv9TABlq9JiVl2dO8UaCDZXJP7IL/aQmmVhf0IigwZKmvaGcNephap5xwM2JOFbYGAgkydP5ttvv+Vf//oXN910U6VxsKWlpb5hOLfddtslN/G2BFRCtCGbN29u7iqIFmD27Nn84Q9/4OOPP6Zbt26VxlAtXbqUxx9/HEVR+Oc//+kr4/F4OHz4MHD+SR+XL19eqWuHaBkcDifxUWsqtU6dy+xfxuC+J+jbPZlTqeH0jYvjZHYc2w8W0LVTTJWJc9My89m0PZFJV/YjwN+Iy+Vm/bYTAPTs2Qu1+sK6Oam1YaC9DhfXUebxUGzPwpb2Ol3an6xbebUbs8mC2WQhKrwiyZXbA3abjjKrgdIyAwXFRnLzjUSHW+jcIQXtWUFbdGQmJmN7Pv0+FpfL+6PPc+Y/5S0IKsXbvVBRKagUFSpVxcPpdOBxO9BpPezavcd33GnTJtAuwkCp1ftZuNxuyhO/eTwe33O3x4OHivUul528vDxyc3PxeECnVdExTk/3Dnb8/RyUlKk5ckpPapaTPfsSUBQFlQIqlYKieOtq0IKfXutbVimcqTu+dUEBCu0j3Wg0Fe0kkSFg0OnIzsm7oM9RVHWxu/w1R8K3l156iRUrVrBt2zbuvvtu/vWvfxEWFsbp06eZPXs2p0+fJigoiKeffrqpXnazkYBKCCHamMcee4yTJ0/yn//8h2effZZnn32WwMBAiouLcbvdDB8+nD/96U++MVLgze5Xnsa8LpM+1nXSxrO7F57t0KFDxMTEkJCQUNeXJc5j//69PDSj5lYXj8f74xpAr3MQ3ymNLu0zyMw5zi9dY9mTqGXXrl2VxiZ/u/oA6349wcdfrWdgr1hCAo38uDERAD+DlqH94hpc7+K8PrSPOV0p6CnncinkFgTiZ7Rh1NtQq6vvHqhSvBMdGwx2QoKKqK1WWo2L7l1OcdcUF0WlfpRZtFjtGhxOFQ6ngsOhYHcq2B0q7E4VdruC1aFgdyi4nCoUFKLCHFzeP4+/nHXca0dnsWVvCJl5OqD+3eciQ+xc3j+HsOCKVrVenQPOHLtqFy3wnAmazqTvPvu5ClSKB5XiITrMjV7npFuHLMwmC8WlRo6eiqBjtIac3LQW/f+ixWJB28K7JNYpoGrEPn/NkfCtf//+zJ07l/vuu49PP/2UBQsWEBAQQGGhd2Juk8nE4sWLa6xbayYBlRBCtDFqtZq33nqLzp078/TTT+N0On1feADFxcVkZ2dXKnP2nFB1mfTxUpu08VIw8fKTtbZOKQrkFoQQ6F/o62anVruJiczhhqtzGNY3jY17TYTHDADA7nDy615vpkCH0822fcmVjvfTxkQG9Yk977xW52MM6MfhYwn06Fo5qHI41Rw+1p7UstvRaHQo2DFosjAb0jDps/DT5+CnL8CoL0Gnc9RyhqrUaje94k/7lt1uBadTg9Ol9v571nPHWcsOhzfw8vez0rF95fejT4+jmIxxnEoPxONR4fYouN3ecV7elqmKZbfnzL9u7/rydeBhcK8sOnc4XaVVzWhoz6/7YwDlnICpbq85OryAkZcdqpRUpHe3U2ze1RNnZuQFvX+iKo+nLh9E83eDa2jCt1mzZtG7d2/mzJnDhg0byMvLIy4ujquvvppnn32Wrl27XsRXc/FIQCWEEG1MRkYG1113Hdu2bWPWrFk88cQTdOnShfT0dBYtWsRf//pXfvOb35CYmMjf//73Jq1L+Xitcw0aNIiioqK6jcMRddSHjJrzO3gFQC5WVKVf46/5CaPem4VPUcDp1DFw8FiCQrzj6ixWCzOuyWLrruMknirwHSL0TK/A3IIy/vXxFq6+oi9D+nemW6coVPWcMyo5ScWu/YuIjihEd6ZVJj0rEFXgDAbEV59cBcBy5oGrDLXnBCrnURTnMdRKCkZdOjqts8ayZ1OpPOh0DnScPzBzuytags6m1bjo2ukUYSEBeMp/OHuUyo0S5yyf+yPc44Gw0DzUVRJ3uIjvnERocD7lP8oVpXwfz5m6eHzrzv7Xu81NgL+lap21LkZedgjLzv4t+v/F2m7ytBQXOylFcyZ8Gzx4MF999VW9z98aSUAlhBBtzMyZM9m2bRv33nsvH374oW99165deeaZZ4iNjWXmzJm8/vrr3HnnnfTu3ds3aSPUPnHjpTppY1viwYDLOJNC7qTEugG96wv02gJOZ3Yh/rKKJCWnj25kbO+fiNAFsyPQxNFUOw6Hi/uu9UZtH3yrIjUjn3kLNzB/0QYWvf8ogea6TRZ8rriOA7HZunP8yDrs1hx0hjA69xiLXl/H4yl+uJQ+uHR94MzN9bzcBXQKX1JjkTKrCbVaQaO2oFbVLbMfQG0NciqVh5Dgwpp3aACVykN4aEGjH1erddGzU2qjH7etcbnVzV0F0YQkoKpFcXExxcXFADgcDtzu893aE0KIlu3gwYO+tLePP/54tfvcddddPP744+Tm5rJs2TJ69+5NQEAAJpOJ0tLSOk36eKlN2tg2qXDprqSMKylzF9K1X8UPQofdgsqxkSGDTzKodxKTRwexfX8seYU6rhzi/fFdZo3lrUXeMt07R1cJpo6ezGDjtiMM6d+Znl1j0Ghq/8Gp1/vRs9+URnt1uqDpWG3LMOirtjpZbVry1e+hVpsAD4rbioqCM49CVOSjVgrPWXfmuWJrtDq2FGZTWR3a5kRtWkuXP1E/ElDV4o033uCll17yLYeEhDRjbYQQouEOHTrke96pU6ca9+vcuTO5ubkkJSUBoCgKPXv2ZMeOHXWa9PFSm7SxzVMFVmp5KS7Monsnb4ILlcpDRFg+U8bmY7HqMBq847TGDdPw3YZoskt0jB7eo8ohN20/wuffbOHzb7bgZ9RzWd+ODO7XiSH9OxMZFlhlf5fLzTc/7QDg+omDLziD4LnUahOZZY8TyVuVxpZZbToyrY+hN5e3yip4MOLCiIuzbhTU0KNK5/yBEO3cGs9b4hyNS9UTcJ/5+ew+c7DKD4Xym7gV29We4/ipt9dy7OE4ifdlDcTj8Y7R4sykzb5sgm48bg8ejwe3x41eOUB40KEaj+tW2tW4TdRNnQKq5p6IStSbBFS1ePLJJ7n//vsBmDRpUqVB2UII0RqdPS/I6dOn6dGj6g9dgFOnTgFgNlekyR47diw7duzwtXCdy2q1snHjRqDqpI/i0hIS3h6V/UZKLQsxGYt968uDKYD2MRk8clMQX61ScerEEWB4pWNs33vC97zMYmPTtiNs2nbEWzY2lCH9OzOkf2f69WiPTqdhzeYDvPvpGgDM/kYmjO7b4NehNw8n1/URztxlqDxpuJUYNAHTzgqmLpxdPQ6n63M06qq/GZwuEyWqhwB9/Q6u2NC57qvl2I/W+djKmYcKcLpLcTjvQaupOqbM4dTg1E+XtpMGag0T+4r6u7hJ8VsZs9lMTEwMMTExaLXaSj9EhBCiNerfv7/v+dy51d9FX7ZsGVlZWQAMGzbMt758IsfDhw+zfPnyKuXmzp1LYWEhRqOR6dOnN2a1RYuj4NRNpVg/jyz7n8jKi+TcMfAajYurrjjA608e4oo+pyk9J/PjHdePZMr4AUSEBVQ5+unUXBav2M4zf/+K6bPfZN2WA3y2tGIevc+Wbsblapxu+Gq1CX3wrWhDnkAffOuZbn4NoadA+TMuT+VWNpcnkALlz9Q7mGrCYysqE3mOR3E4K99ndzg15DkeRVE19D1p4zzl2Rxrf4jWSyIEIYRoQzp37syECRMAeOutt3j22Wd9wVNJSQnz5s3j7rvvBqBjx45ce+21vrIDBw7k5ptvBuDuu+9mxYoVALhcLj755BPfZI2PP/44ERERF1y34uJi0tLSSEtLk3GrrYaCQxnITxs74HBUnQdIUSAooJjwYCd+ZyU28Xg8WEpymTiqG5++9SAf/XM2D901nsH9OqHVVh5LZbM7ScssIDWjYnLS1Ix8vlq2tUGZzJqSk25keyrP1ZPteQ8n3Rrt2AXuxyh230aB+7FGObZHP5IcPubI6TGczuxDdukN5PAxHv3IBtdZSEB1qZMuf0II0cbMmzeP8ePHc+jQIV577TVee+01zGazLwkPQGRkJEuWLKky38jcuXM5fvw4O3fuZMqUKfj5+eFyubDZvAPxp06dWmns6YWQcaut045duxk5MLXGuZ4sVgNZRe3pciYnt8fj5uD2d4jzT/5/9u47Pqoya+D4707NpBeSQCK9996kg3RQQGXFVbFiW9uylvW1r3XVddV1F7GABRuK0hEIvXdI6BBqGqRPkplkyn3/iBkIaQNkMplwvn7ux5nb5swMczNnnuc5D+vX1WPe/GB69+zCDf07c/OYXlgLbew7eJod+06wY28ieQVWfl8bX+a8X/64lgUrdjGwV2sG9G5Du1ZXP+dV9bq0tehqWqbKntvKwGo8XzFFE8CZ7OLuuh0iO0g3v2rklKIUdZokVEJcQyqrziauHQ0aNGDnzp3MnDmTefPmkZCQQE5ODsHBwbRo0YKxY8fy2GOPlTubfXBwMJs2beKDDz7g+++/59ixYxiNRrp27co999zDAw88gHLpZDZuknGrvilUv5/Y+ucq3K7X2QkPuvBvIuPcSRo3OEyLxmn073GKcxmhbI9P4d8fbaBhoxb069ONHp2a0atLcwAWrtjFh1/+Xu650zPNzFu2g3nLdhAWEkC/Hq3o36sVXdo1rrJqYE2Qa64o4VSr/vdYSxtchRskoRJCiGuQyWTiiSee4IknnrjsYw0GA88++6yri191CQoKchXBkHGrvqNzl4YYNRUX1TYY7HTu1hTrH/ez0g/Tp+15ALRaJw2iMrlxWCbD+xlJPHOWJesPMW9+GL16dqNH1w78vGSb61yuSYPNlJGVk8+iuN0sittNUIAffbu3pH/P1vTo1BSDQb7uCO+SLn11m1xhhBBCCHHFrAwh1TnEdT8hIQGADh06lLt/y3aDyDAfJcRvCyY/q2u9ya+Q9i2TaNciiYysYHYfPMV/PllLkaV4LF10iJN/Pp4GwDMfRZOWU5xwd2nXiJNn08nOLXCdy5xvZfm6eJavi2fcDV158r5R1fukhbhMMg9V3SYJlRBCCCFqjuIPwY+Tw2Nk5a9HX/Qz4cHJaLXFiZOiQL3wXIb3y2VQLx0LV3en9+C/cTL+Wbp3KJ776tUHDTTt9E/XXFQOp5MDR5JYv/UQ67cf4XxGruvhru9etljDnv2naN44iqBAU7XPbyVEeaSFqm6ThEqIa0j37t1dt3fu3OnFSIQQQkFjGojDNJBzDjOO7K8I8dtGUMCF8upFRQbCwiLZtXsXI7qcda3v0eEs3/y+grGjRqDRKGg1Gjq2aUjHNg15+K4bOJyYwoZtR9iVcIKuHZqUelSLtYj/++dP2B1OurRvTERYIMv/KHpRXfNblZBrrighCVXdJgmVENeQlJQUb4cghBBlKNogdGF/IR/IzduJxvoD9UJOkZkdQmTsYAwp/8XPeGHSYD9jEb1aLOKf7x+la9cu9O7RidDQ4vmsFEWhTfMY2jSPAQaXeaztexMpLCqewHbnvhOltn323Sr69WhFgH/1VOSTa64o4U5CJTUpfJckVEIIIYSoNbT+3cG/O+lqIYSc5cT+jFKtUyU6t0ni5QbZ7DpwhhkzNxMWEUPf3j1o37YFWm3FFdX0Oi2tmzfg8PGyyU5WTgG3PvQRIwZ2ZNSQTrRu1uCKq1YKcTG3yqZLRuWzJKESQghRK5jNZtdcWDKxr1AUI1pjU8J1/yvVOnWxsJB8hvU9Sv/uJzl+OpJlG06xeEkAbdq05fo+3YmOiihzTN/uLenbvSXJaVk89uJX5JgtpbYX2eyuaoEjB3Xk6YfGeeT5iWuLdPmr2yShEkIIUSvIxL7iUjt37Sy3depSRoONdi2SadMshXMZIWzdl87XX++jV6++DBrYr9xjEg6fLZNMXapT20ZXFLcQpSk4ne4UO5Gky1dJKRshhBC1wvTp00lKSiIpKYmOHTsSGhrq7ZCEl7WMXl5h61QJh+PCl1CNRqV+ZDY3DdvPC9PiMajHS+2rqiqqquJwOJnz68YKz+nvZyA02J+BvduUWu90qvz1tTnM+mktyWlZV/CMxLVKVZWqF28HKa6YtFAJIYSoFWRiX3GpsEb/R2oVPT/tjlwc6bOICNxBYEC+a32Rzch1DVuX2vdY4mkWLFxGYEgkqeeKEyIF6Ni0+OtQ/Ak7KlBgLeKRqTdg8jOUOn7fwdOuZc6vm+javjGjBneif6/WGA36q36+ou5SJVuq0yShqoT05xdCCCFqN50uGF3kE5hVlfSMlQQo8wkPSSU1oyExzXu49jt7cg9Bzm8YP0DLup153NDNj4jwaPxNeiL8jwEwfGA3Ro8aWeFjrd58oNT93ftPsXv/KQJnr2Do9e0YNbgTLZvWR1EUHA75ziAuUKU7X50mCVUlpD+/EEII4RsURcEvbDgOhnPOmU+9JlZXtT9VVck+t54b+hSXSe/d+RSnkiJZt8OCosCwPmcAWLIebLZh6PXlfz36y90j6N6xKcvW7GPH3kScfzQ75OVbWbBiFwtW7KJ54yhGDe6MRiNfoMUFbhWlkFYsnyUJVSWmT5/OtGnTABg1ahT5+flVHCGEEEIIb1M0AWgNAa77ebnnaBh9yHXfaLDRqmkyLRqnUGDxIzCguDjF4J46Pv9yFrf96U+E/TGv1cX0Oi0De7dhYO82nM/IZfm6eJat2UfKuWzXPsdPneOTr1YQFOhX6liHw4lWK91Yr1VS5a9uk092JYKCgoiJiSEmJkb68wshhBA+KigkGr96fyE5vSV2+4U5qjQa1ZVMATSOTaNFTBqff/4Fx48nVnrOyIhg/jyxH1998BDvvXg7N/Rvj+Gili1znrXU/nEb95dKvMS1xZ2iFFLlz3dJC5UQQohaQcatCk8yBrSFgHdIs5uxn/+WcNNGggILSu2j19v50+i9NL2uCXk5qUCzKs+r0Sh0adeYLu0a85e7rcRtSODLn9aRX1BYar/Zc9dxLj2X1s0bMHxAB4b0bUdIsH91PkVRiznd6M4nPf58lyRUQlxDkpOTvR2CEBWScauiJmh1QTiDH+DHBVncNWEPBr291HaDwUFUqA1tZNtS63ftOYBer6N925YVjo8KDPDDZDK6kql2gx5zbTuXngvA4eMpHD6ewoxv4ujdtQXDB3agd9cW6HXacs8pfJ8K7s1DJRmVz5KESgghRK0g41ZFTVkZF8fgnillkqkSer2NNRu2uSr+JZ/azaYNK7FYtSxd5s+ggX3p3rU9Ol3pr1FVzW91MbvDycYdR9i44whBgX4Mvb4dwwd0pHXzBiiKdP2qa2QMVd0mCZUQQohaQeahEjVlcJ9wYgLPVbg9pn46gwOLW0gtBdnYzd/xyqMnSEmLYOXWxqxbG8eKuLX069ubvr274OdnBIrHSSWlVj7h7/ABHTibmsnBoxd6DJjzrMxfvov5y3fRKCaCR6beQI9OVXc3FL7DnXmopIHKd0lCJYQQQohrikY9gtFgq3C70WBDox4BenLmxHa6tTiLTuukYcx5pt6UTlp6GOu2N2Tr9g2sXreRXj26MbB/D0YM7MiIgR3diuFsSgYr1iewYn2CqzsgwOnkDAID/Co5srgl7LffdwAwYWQPqR7oA2QeqrpNEiohriEtWrRw3T527JgXIxFCCO8xhv2ZVOefq9in+P8N6kegKDqgeFyURqPSICqTyWMyGdY3hE17GrJ2x042b91O544dGDKoN5H1wnE4nLRs1bL4GEUpc829rkEE90wexNRbBrLv0GlWrEtg3dZDRIYH0bpZg1L75pgL+PTbVdwwoAOd2zUibuN+/vdNHABBgSa3kzjhPdLlr26ThEqIa0hBQUHVOwkhhHAJiuiGma/Iyv6VUP0CAgOKK1EqCtQLz+HGoTkM7BHI9viG/L5pP9sDDIwZNYydu+OxWixVnL10lcDH7hlB2vmcMmOo1mw+yPJ18SxfF0+9sECsRRfGfs35dSPD+rWXVqpazr2ESpIuXyWfPiGEEEKISmnQBd9Mnmk2SeZHyDFHlNoaGpzH8H4H+b9p+/BTTuJwONmwYU2pfRyOqqcB8DPqaXxdvTLrV6xPcN1Oz8ojL//CHFdJqVnEbUgoc4yoXVS16kX4LkmohBBCCCHcoqANuAFLwGckF/ydzJwGpb4I22xG2rZtz87d8dw0+HSpIxcsjkO9wm/Nj98zgomjehAcWP7Yqn9/sYzNu45e8fmF5zmdSpWLvH2+SxIqIYQQtYLZbCY5OZnk5GSZ2FfUehq/nhQFfUJq4ZukZzfB7tCQfL4pkTE92bBhDd3bJ5Xaf3/CLt7/aBYJBy4/8WnVrAGPTh3OtD8PLXd7kc3Bi+/+zKMvzOZsSsYVPyfhOaqqVLkI3yUJlRBCiFrh/fffJzY2ltjYWOLj48nOzvZ2SEJUSTG0wR78L847Z1Kvyf3s2pPATYNP42csKrXfs/ceQ3FkMPubX/jXx7MvO7FyOJx8P39zpfskp2URHhp4Rc9DeJYkVHWbJFRCCCFqhenTp5OUlERSUhIdO3YkNDTU2yEJ4TZFG46iq1du6xRAw5gMXn54N3eMzaPIksGXX//M+x/NIn7/EbcSK3fmuOravgn+JmOpdbl5FhzS2ut1TjcW4bukyp8QQohaQSb2Fb6uZOzUpa1TJQIDrIwaeIAeHUJYubkZ63Zl8OXXvxAbE82IYf3o2L5VmQp/Jaqa4yojKw+Tn77M+n9/vowTZ84x5abrpRqgF0kLVN0mnyohhBBCiGoQHKCW2zp1qXrhOUwevYfn7j3OoO4KuTnprFm39aoeOyIssEzr1Kmz6azfdogzyZn883+LuPuvn7Jk1R5sdsdVPZa4fO50+ZPJf6tXYmIi27Zt49y5cx5/LEmoKiEDpIUQQgjhrmb1VlfYOnUpjUalUew57r9lJ49NSaJBRPUnOaeS0kslWSnnsvnXZ0uZ+tQMFqzYRZHNXsnRojq5VTZdqvy5JT09nZkzZzJz5kxycnLKbE9MTKRnz560bNmSvn37EhMTw+TJk8vdt7pIl79KvP/++7z66quu++Hh4V6MRgghhBC1mSHyKVKdT120JsZ1K9U5DwClaAOB6ucEmHIB0OkctGh8juwCW6nufg6Hk9nfzqN71/Z06tAGjebyWy8G9m5Dtw5N+O33nfyydBvmvOL5q86l5/LRl78z59eN3HZjH8YM7YLRoMfhcLJmWyIAbdu2k+6B1Ui6/FWfefPm8dBDD9G8eXOmTZtWapvNZmPMmDEcPXqh6Iuqqvzyyy9kZGQQFxfnkZjkk1IJGSAthBBCiOqkGvpjNs7iXMEUiooMACSlRHNdi5td+xQVWdi2fTMHDh7lqzm/8e6/P2f33gOunjIOh5O167exdv22KicMDgzw445J/Zjz0SPcP2UwocH+rm0ZWXl88tVK7nj8f6zbeoi4jfv5bUXxErdxvwee/bXLnXmoqoOiKG4va9euLXXsyZMn3Tpux44d1RLrlfr9998BmDBhQpltX3/9NUeOHAFg5MiRvPPOO4wYMQJVVVmzZg3z5s3zSEzSQlUJGSAt6prk5GRvhyCEENeMiq+5Ck6/W8lQx6PL/xklsCmmgAjX1lPHNtMiYj6ThkWyea+JlPPpfP3dfKKjNjBiWH/sdju/LSr+pd3f30TP7hUXqyjhbzJy2419uWlEdxav2sNPC7eQmZ0PQFZOPoEBfnzxwxrX/nN+3ShFLKqRO735qqPHX3R0dKXbc3NzsVgsGAwGOnTocEXn0evLFj+pSYcPH0ZRFHr37l1m23fffQfAgAEDWLp0KQB/+9vfGDZsGGvXruW7775j0qRJ1R6TJFRCCCFqBbPZjNlsBpBxq+KaoCh+OEx3EGC6sM5SkIPOtpKOHc7QruVZerSPYvX2xuw6qOPc+Qy++X4+Wq2G0KDir3DL4zbQrYv7iY/Jz8AtY3ox/oauLF29lx8XbKF+VCjpmeZSZdmTUrOI27i/0sqCwn011eUvNTW10u1dunRh7969jBs3joiIiAr3q+o83nT+/HkAGjduXGp9YWEhmzZtQlEUHnzwQdd6RVG4//77WbNmDTt37vRITJJQCSGEqBVk3KoQADa6tDsNgFaj0vi6NG6PzqB3xxhWbb2OhOMqqqoyrJcNgJVbzezas9+tVqqLGQ16JozswZihXcjIyuO5t34os4+0UlWfy5jD2WP27NnD3r17AZg6daqXo7lyWVnFib9OVzqN2b59O4WFhSiKwvDhw0tta9asGQBpaWkeiUk+IUIIIWoFGbcqBJj865GvPIS1KMi1zqC307bFae6ZtIt7b0pnZF8b13c5w/VdzjCgq51lK9ZVOZaqIga9jvhDZ8qdNLiklUpcPXfKpnu6yt9XX30FQFRUFGPGjPHsg3lQQEAAQJly6OvWrQOgdevW1KtXr9Q2o7G42mVF87xdLUmohLiGXHfdda5FiNomKCiImJgYYmJiZNyqqBOu9Jpr1/UnW/clmYW3YbNfGK/ib7LSs/NRRg7YT0z9NGLqp9G3SwoOWz679lxZ4uNwOJnz68YKt8/5deMVJ2viArfKpnuQ3W53jS+6/fbby7Tu+JIWLVoAsGrVqlLrf/vtNxRFYeDAgWWOKUm+qhpjdqXkr5UQ1xCn0+lahBBCeNbVXXO1FOknk6HMIts6uFQVOH+T1XU7tv45BnS1szxugyvxuZzHi9u4v9zWqRLSSlU93Gqh8qClS5e6kgp3uvv17duX4OBgTCYTTZs25Y477mDDhg0ejdFdJVX7ZsyYwZIlS8jLy+Pjjz92VR+86aabyhxT0tUxJiamzLbq4LvpqRBCCCFEXaf4YzU8zo74LlwX+BVtmpdOfowGG327pLB+t45de/bTskUT/jPjW0YO70+Prh2q7OI0YmDHUoUnEhISACqtACcun9ONhElFYd++fXTv3r3c7VdTUGH27NkAdO7cmS5dulS5/5YtWwgJCQGKy6mfPHmSOXPm8MQTT/DBBx94rOucOx5//HH+97//kZOTw/jx40tt69ChA6NHjy5zzJIlS1AUha5du3okJmmhEkIIIYSo5dq178/+4+0ospX9LTy2/jmG99XSqlkkixb9hsOWzw9zFzHjix9Iz6i49UnUHG92+cvMzGTRokVA5a1Tfn5+PPLII6xbtw6z2Ux2djYFBQXs3LnTlbh8+OGHvPXWW54L1g3R0dEsXLiQBg0aoKqqa2nRogVz584ts/+xY8dcrWs33HCDR2KqMy1UqampvPXWWyxatIikpCRCQkLo1asXTz75JMOGDfN2eEJ4nfSBF0II33X48H66tjmJQW8vs81osNG1zUn27pnL6D7HiA+vz4ETJs6nJfHuB58zavhABvbvKdX6vMXdhEmFTp06sWnTpmp9+O+//56ioiJ0Oh1//vOfK9yvfv36fPLJJ6XWKYpCt27dWLBgAZMnT2bu3Lm8+eabPPLII14tHNSvXz9OnDjBhg0bSE1NJSYmhn79+pU7Niw1NZUXX3wRKO4u6Al1IqHat28fQ4cOJSMjA4Dg4GDS09NZtGgRixcv5s033+S5557zcpR1g8Ph5Lffi/uoThjZQy7OPsSTfeBtNjsLFy4GYPz4sej1deLSImqYzEMlRMXC/U4QW/9chdtj659Dr7PSMCaDFo3SaH/iOtbtakBSmpY1a9exa+9+Jt88hoax9WswalGipuahKk9Jdb/Ro0cTFRV1xed55513mDt3Lvn5+cTFxXHzzTdXV4hXRK/XM2TIkCr369+/P/379/doLD7/bdhisXDjjTeSkZFB165dSUhIICcnh6ysLKZPn46qqjz//PMsX77c26GWYbfZWRP3K2vifsVuK/uLU20UtyGeHdvXsGP7GuI2xHs7nCo5HE7WbEtkzbbEa7qFxuFw8v38dWXWVZe4VSvo2XoVPVuvIm7Vimo7b0G+mQjd50ToPqcg31xt5xW10/vvv09sbCyxsbHEx8eTnZ3t7ZCEqDUaNw3CaLBVuN1osNEwpviHZaOxiI5tErl9bDzDemfTOEaP1pnLzM+/Yf6iOIqKKj6P8Axvdfk7ePAg27dvB65+7qmmTZsSGRkJQGJi4lXHVpf4/M/In376KadOnSIwMJCFCxcSGxsLFLdSvffeexw/fpzffvuNv//97x5r5rtS27b8Tpdmq/+4beD6AWOr5bx2WwGWtH8AYIp+EZ3ev1rO63A42bptHVNuKL4Qz9+0jmH9O1ZLK1VhYSFrVn4BwOAb7nPNF3C1Vm3aR6A+7o/bjRg+oEu1nBfA4bDizPonAJqwZ9Bq/arlvIXWfPKSXwYgMOZVjH4BV3yujKw8ggL9WLP5IMO7n+T37y9su+3R/9CkYSRREUHUCw8iMiKYqIhgIiOCiYwIItDfD4fDgdVqwelUCQoKKnXuvXv3cujQIQoKCujbcT89O54BIN8SxzffpGMymfAzmQjwDyAqKor27dtddvznEt+kT+fiCS637H2TJh29229beNb06dOZNm0aAKNGjSI/P9/LEQlRe1gZQqqzsl/jHfg5FxCkfI9WW/wjbVhILoN776dl4yg27GrEkVMmjh3Zx/sHD3HrpHG0aN64ZoIXqLhTlKL6lRSjCA8PL1PAoa44fvw4mzdvJjU1lYKCAh555JEy81B5ms8nVHPmzAGKa+qXJFMXe/rpp/ntt9/YtWsXhw8fpnXr1jUdYrnsNjtN6q2iTfOzABRYV1FUOByD0XDV5zYnf0DbpocBOHjiA8Ia/99ln0NVVRz2Iuz2ImxFVvIL8tl3MJkhXXLo0DIJgNyCWCY/9AGhIf4YjUYCTH4E+BvxNxkJ8DdeuG0y0ig2go5tGpZ6DLvdgUajQaNRWLfmW4b3LG7xilvzLcNH3ldljA6HE5vdgd3hwGF3Ync4cTid2O0OHA4nhUV2kk/9yHNTi7/ovzdnLg5Hp2rrpmjL/C9NovcAcDLtv2gj/1ot5808/Q5d2xT/8rP70Ds0aPWae/HYHRw/lcaho2c4mniaxNNJmPOy+b/HRrNl22refuQsf/vbhf0Nmlya1UtFrwOtBcypCoUZkKZT0OtAp1XQakFBRa830W/YhX9HSamZnD29k3aNDqHVOujX9bRrW7+upzDq7SiKgkajotGo5Fv8gHdKxbtr839pEh2PRqOg1ajF/9eCRgNaDWg0Tnp2SHft36XNCZLzzfgHlE7sRN0RFBTkStxlHiohLpcWq2YiRQzBv+g/BBp2Fa/VOmkUm8rEiCwOHW/Iht3RnM+ys2vnVpo3a+TVam3XEk/PM1Ueh8PBt99+C8CUKVMwGK7uO+aJEyc4f/48UNxa5W179uzhiSeeKFPO/ZZbbimVUP3nP//htddeIyQkhAMHDqDX6y891VXz6YTKbDa7SkiOHDmy3H369OlDSEgIOTk5xMXF1ZqEatuW3xnTJ8l1v0OrM2yPfxGnU/NH06+C06lcuK0qOJ0aOvZ9udSXjJPHt5ORvBRUBVQFRaMyrE+Ca3uzmH2s3vAeiqJH1QbQpc/9peJIOrWdrLQdqKqK0+nA6XDgcDhwOOx/fPj/iAGwZCsM6FM8kSBA9yIdw3vE0rFpHnaHGUsRWApVrEUqlkIoSFfJKgJrkUpWWjQNIwcRGtHC9diffb+ajVu20qCewiv3J7vO27ftLl54MxunA5xOFbvqYNSgDgwd0BeNLtx1/HNv/UBq2hGCA+woCui06h9fxlV0WhW9zsm/njrp2n/aTceZv2mfq5Xq3RmLCPU/QoMIJwEmPf5+WvxNGvyMGkwGBaNeg14Pei3odKALHITW2Aoobp2qH7rNde7Y8M2cSX2t+PcnVQVUUFQUVMAJqOhC7kJnuvDvz1ZkwZH5CgoOFEUF1YmKg44tUlz7dGx5gHPp09BoVBwBr6A1XvjR4NiRzXRt9DEajRONxolW4yS2ucrglpdetfcxpC1lPHdXGsOvTyq7oRx2u4aS1MbhdHLP9Jk8d0cWw/sdK7OvXu+g70UJFkCBxY/cP24fPp7C2/9dwIt3HaNdizS3Hh/Az1jEuUPSSiWEEJVxEkqe7gUKHXsJdH6IUZ8NgMmvkK7tj9GoQTprdzRB9etcJplyOp2cPVv8I2S7du3kR41q5I2EauXKlSQnJwPudfdTVbXSBPv5558HwGQyMXTo0OoJ8gotXbqUm2++mcLCQtSLXtzy4r/rrrt47rnnyMjIYNGiRUycOLHa4/HphOrgwYOuF7F9+/bl7qPRaGjdujXbtm3jwIEDVZ6zotr/Bw8eJCYmxjU/w9VwOIpbp/yMRa51Br2dft2OVnqc06mwKqH0c9AWrmHsoD0VHmM02hg1sLhajLVQz4aEPqW2+zsWMKTnweJmZlUp838oTqZUVSE/34/AQIvr2Jj655gyEhrHni9OJJTi98L1T1lRS91OS99KQsLjruPPJqXy0fTTtGl2nov//bdoksLnL1xIKopt5djpJZzMfti1xmIp4KuXThETnVPh879YcGARSSd/YG+IBq1Gw74DJ/nlrV0EBxW4dXz8sSzSCsYA0CDwV2KbXXj/9HoHzWL2VHr81gNrMdsv9Fs352Zy4/XH0GoqvsrqtE5ioopTmdV7d+BQisvf/rRkH2phIv1ftlZ4bFX6da14cHMZyoW5SbJzi7sAXs4fB0VRXcefOJvJmeTMKxqg26XNCVbt2orBcOXdIGuCxWLxyC9gQgjhLpvSmSztp5jscwnSzEOjKR43GxGeTbe253AEtSy1/8lTSZxLSyLxePF3kcOHGtO23eV31Rblczjd+JtXzUlXSTGKdu3a0bNnzyr3Hzx4MKNGjWL8+PG0bdsWrVaLqqrs2bOH1157jd9++w2AZ599lvDw8MpP5kFpaWncdtttWK1W2rZty/vvv0///v0JDg4ud//g4GDGjx/PTz/9xNKlSyWhulRKyoUv3ZXNfFyy7eL9vens6QQGjXKvZeBi5X0BVdXLKSxQ9nhFcaDVun+OiwfEGg02IsPNpRLDyui0jlL37XYnfobiLl7uUCgdp16nRau9vC/lD006xf8WnKFnx8bkW4oo7zWpSF5+XvHuahHNYy+/Yl5RUaGrDIzd4WT5pkRu7Kvg9hVULXSFGxkewMmTFb9wTqfyR2unAoqKXlf82t9/x4XqPv4mGxarAbtdXyqBdj2c64aCw3nhsayFdiJC/UnJsGDOMxF0UZJ9sezcAPLyTaiqQqHtQgKk+6PL5e7D/kSHx7hmiHc4i/+NO1SFeiFmGkSXnTvFz1hEiGYeFu6s8LkLIYQooceiuZ0ibiDA9iH++oPk5ftTqBlDSPCFHg85ORl88908woOcrl/4N23eSOs2baSVqprU9Biq3NxcVwLkbjGKU6dO8fzzz/P888+j1+sJDg6moKAAi+XC3/nHHnuMl156qRojvXz//ve/MZvNNGzYkA0bNhAWFlblMYMHD+bHH3+8qsmRK+PTCdXFA5ZNJlOF+/n7FxdlyMvLq/KcFb3Q3bt3Jzc396pnDrfb7IRrZ1WYhORbjDgcJcUNiruOFV/bnDid2jKPn3xiPxbrbhRFRad1oNOVnxypKtjsmlLH55gL2L2pkL5d3IvdoC9bFSg40P1B4w6nUurx3+nQgcKUDeXue6HqjVJ8EVIVnKq+1PEfdOhAYcpWLFbjH8corv9rtY5yX+PQoEL0bKJt29G8/1I02blHcKqa4jki4I//l5znwn0VcBBNhw4dsJ7/V4XvX3auP7l5pj+6SSqu86qqgqJvTIe2xfFn5eSzafdiDp2IQqMUP1a9sHyiIsqvZHcmJZz6sd0Ji2gOgGII5bUdB/lpaXtUtIABjUaHih5V1aAofywaJ6P7bXQlVDPfa1bqvE6nwqGUuzGZgtDq9IAGp6pxJTnFXU9VdHoTHToUH9sBuGFIX35f+gt6/ZFy4wXwM9qYs2wQfXv3xeQfTIeGxWPoWray0b5dWxTFjlkDBoMRg8GISa9Dr9NiteQRZpxW4Xm7tz9FclHjWj2WqrLrkRDi2lHS3crbHESRq30Dq2MLBbYsgqMvzM9ptZg5svtTBnSGxCQjYwYWd9mev6oJhw8dklaqalLTXf5++uknLBYLGo2GO+64w61j3n33XVasWMG2bdtITU0lMzMTg8FA69at6devH9OmTaN3794ejrxqy5YtQ1EU/vrXv7qVTAG0bVs89uHkyZMeicmnEypfdOnYqUtpNSq/b7vF7Yp/MU3/RA5/wm4roJ7jXnS68r/oFxYZiE97k2ZNLqwLCfJnwZYOfDQ3FI2meAxSyyZRdO/YiI6t6hMW6ofNZiU3M5GmESu5LqZsFzGdzsHZ5Cj2HO+BqgnFqYLqVHGq4HSCU1VxOor75dZv0IS2kRfFVFiI3V5+tyhFgcTTsazf0xWNVoeiKDSIbU2H0nUt2Hv6VvISSloyFBQFMrNzuHPsCvwqKBR4/42JLPxjLNUvv44kz5yHw6HicNhxOp2lFlV1umbg7t//+jJjpy7lZ7Tz+qetKbJpsTtVbHaVIruTDq0bM3hQD9d+eflWHE64//WG2O2gUZys/bziMvSR4Xk4HRfmDmnTIoY5/3kanU5b4TEAmUlfE2CquAUxwL+QAL8kwmPuqvQ85Rk1MLfS1kk/YxG3jNaiBpTujms06GkUG1HhcedPvEXzzpWfV8ZSCSHE5StS+qC7pFfU8UNxDOq1Hz+jjeycIKLqFf9NtVj1rJJWqmpT0wnV/fffz/3331/1jhe59dZbufXWWz0UUfU5ceIEUFwnwV0hISEArrkOq5tPJ1QBARe6EVksljJlnUsUFBSPkQkMDKyRuCrTscXRKr+ENouJJ/5QJ9e6kuZ3jUahXcvSlQzzCwo5nZxOGJ9xXavKz6vJ+wx4o9T6Ab07EOAfyPU9WtGnawvCQsuOTQk02okMLtv9qkRkvSzaGjoREN6rwn3Ks27Nt0well7h9usanEN7QGX4yIq/7PfsPazMOp1tOUHGwgqPCQ0qZHSfc9iBmy+zH631/L/wi678df7LXRr8Ip9yrbPbHWi1mlIDJUOC/Xny/lHk5VvJyy9kUNulVf67yLyo4p9Wo3FrFrmkZHDklVOR4iKpuRBetkBmlZZviUFXWPlEeXZjDMPLvkWVatLxLVIvamgtGXt1cetkk46Xd07hG2RiXyFqltPpoEn9gwT/0XW7JJkC6NruLMs3xUorVTXx5sS+dU1RkXtDTS5W8rfl4tyhOvl0QnXxuKnk5OQKK/iVNLk3aNCgRuKqTFCDJ0l1PsnydfH883+LKthLBb4ts9bPqGfR7L+VWnfsZBrT/zGH0AAjDSMqH3BoUYOY8c/S6yaO6snEUZUfl5S0jeb1Kp9MMClpG60uM6Hq1MpS5SSFnVqVPz6nMpu3JNIkqvIk4uS5RHoOuOxTs3Bje84nVf6xiYxtza0TLtwvrxUpONDEuGFdXfcdjoGMfGImSanlJ66x9cP48r2Ku8FVpGPPqlueIqvco3zDh40Eyq+uKcSVeP/993n11Vdd97056FmIa4FGoyUsuh/Wwj34GUv/PfYzFjHi+iRppaom3qjyV1dFR0dz+vRpEhMT3e6CWDKkp7wplqqDTydUbdq0QVEUVFVl//795SZUTqeTw4eL52RqV0t+YXE4nMz5dWO1njM7v3ipSGz9MPr1aIXD4bzseZhadfwLqc6/VLHPZZ0SgOimVZ83+gqmOeg54KFS98tr4Yi8wur5TRrGsGnzrsofv0/FBVIqErdxf4XJFEBSahZxG/czYuDVNc1c+iOEEIcPH+Y///kPy5cv5+zZs+h0OmJiYujbty9Tp05l0KBBZY4pKiri3//+N9999x3Hjh1Dp9PRtm1b7rnnHh544IErntdGJvYVdY0vXHP3HqrH1i3d+ds929BdUqRKWqmqR/FYavf2E1Xr27cvp0+fZuHChUyZMqXK/R0OB5999hmKojBw4ECPxOTTCVVQUBA9evRg+/btrFixgkmTJpXZZ+vWreTkFJfVHjbsMvseeUhlX55j64cRFhJwUYU11fU/g77s2+VvMtCmeQNUICe3gNTz5ZcQ//PEflf9ZVxAz+4d6dm9+l/HEQM7yvsjatxHH33E008/7eo+ERgYSFFREYcOHeLQoUNoNJoyCVVubi5Dhw51/drn7++PxWJhy5YtbNmyhYULF/Lrr7+i013+nxeZ2FeImpdncdCzfXKZZAqKW6n6dztFnsVRzpHicrhT5e9yKg9fy+644w5++OEHfvrpJ5544olKW6lUVeXRRx/lwIEDKIrC3Xff7ZGYfDqhArj99tvZvn07c+bM4aWXXirTre+9994Diqv01YZJfd1pnXr/xT+73YrUsml9/vP63TgcTu7928wK95vz60aG9Wt/2a1TQoi66dNPP+WJJ55Ao9Hw7LPP8sgjj9CoUSMAUlNTWbFiBTZb2S65DzzwADt37iQ8PJyvvvqKsWPH4nQ6+fbbb3nooYdYtGgRL7/8Mm+88UaZY4UQtU+3Li2JcKZWuL1ft1QyNC0r3C7c49aQUGmicsuYMWMYMWIEy5cvZ8SIEbz88svccsstru35+fkkJiayYcMGPv74Y3bt2oWiKPzpT3+iV6/LG57iLp//dv3ggw/SuHFjzGYz48aNc03eazabeeaZZ5g3bx4Ab775pjfDdHG3a1dtOa8Qou45efIkf/3rXwGYMWMGb7/9tiuZAqhfvz533nkn9957b6njdu/ezU8//QTArFmzGDduHIqioNVqmTp1Km+//TYAH3zwAefOXcbE0UIIr3Fk/q/KokiOzP/VYER104XpYCpehPt++uknunfvjtls5umnn6Zp06au7uZ9+vShZcuW3HPPPezatQtVVenbty+ff/65x+Lx+RYqk8nE/PnzGTZsGLt27aJ9+/YEBweTl5eH01k8Qd2bb77JiBEjvB0q4LmuXdJlTAjhrg8//JCCggJ69+7NAw884PZx3333HQCtW7fmxhtvLLN92rRpvPzyy+Tk5DBv3jweeuihMvsIIWoXQ+RTpDovVKYtb9yx4UqrFwkXqfJXvYKDg9m0aROvvfYa//nPf1zDey4VEBDAY489xquvvopeX/5UPdXB5xMqgM6dO5OQkMBbb73FokWLSEpKIiIigl69evHUU0/VmrFTQghRG5QkRu4M5r3Y6tWrASr8gcpkMjFgwAAWLVrEqlWrJKESQog/uNMAJY1Ul0ev1/OPf/yD5557jrVr17Jjxw7OnTuHw+GgXr16dO3alWHDhrnmoPKkOpFQQXEXlQ8//JAPP/zQ26EIIUStdfz4cVd3vK5du7JlyxbeeOMNNm3aREFBAY0bN2b8+PE8/fTTREVFuY5TVZVDhw4B0L59+3LPDcXVVBctWuTqfi2EEEK69HlSQEAAY8aMYcyYMV6Loc4kVEIIIap29OhR1+01a9bw2muv4XA4CAoKQlEUDh8+zOHDh5kzZw4rVqxwJU+5ubmuMuYXl4K+VMm2lJQUt+Lp3r17uesPHjxITEyMq/uR8B0WS/H8gfLeleYrr4cvvn8Wi8Wj3bmqg1sJlSRdPsvni1IIIYRwX3Z2tuv2q6++SqtWrdiyZQu5ubnk5eWxZMkSoqKiSElJ4eabb8ZutwOUmhPKZDJVeH5/f38A8vLyPPMEhBDCB6mqUuUirozVamXDhg38/PPPfP311+Tm5tZ4DNJCJYQQ1xDnRbV7FUXh119/dU0podFoGD16NF9++SXjxo3j8OHDzJs3j8mTJ3ssnpL5rC7VvXt3cnNzSw2MF76hvKIGwndeD198/yr7kae2cErrU7U7e/Ys//d//8ePP/5YapqPHj160O6iiai/+OILPv30U0JCQli+fPkVTz5fGUmo3HTixAkKCgoYOXKkt0MRl6mk+4IvXHBrkq/8W/bF9+/o0aO1Nt7AwEDX7VGjRpU7P9/YsWNp1aoVR44cIS4ujsmTJxMQEODaXvKelKegoKDM41wJueb6Ll/8zNYEX/m37IvvX22+5pZwp8uf5Fzu27FjB2PGjCEjIwP1ohe3vGRp3LhxPPLII9jtdpYvX+6Rz6IkVG7Kz8/H4XBUex9dp9NJWloa0dHRaDTV1wPTU+f15Lk9dd5jx44B0LZt22o7Zwlfey26dOnic/8uPPX+efIz4ufnh9PpxGw2ExQUVK3nvloXj3+qbLLz1q1bc+TIEc6cOQMUl6gNCAggPz+f5OTkCo8r2XbpJOuXS665nj+3r31mwfdeC7nmXnCtXnNLSJe+6pObm8uNN95Ieno60dHRvPTSSwwYMIBOnTqVu390dDQjR45k8eLFLFmyRBIqbypp+q6oe8qVSk5OJjY2lh07dlQ60Lu2nNeT5/bUeUsGvVf3ewe+91r44r8LT71/NfFa1MY/7u3atUOj0ZTq+leZkl/7FEWhbdu27Nixg/37K54kvKS638XdLa6EXHM9f25f+8yC770WvvjvQq65niFV/qrPf/7zH1JTU4mIiGDz5s00adKkymOGDx/OokWL2Lp1q0dikqIUQghxDfH396dv374AHD58uML9SrZd/IdqyJAhAKxYsaLcY6xWK+vXrweQ+f+EEOIiqhuLcM+CBQtQFIUnn3zSrWQKLvxIl5iY6JGYJKESQohrzF133QXAsmXLyk2qFi9ezJEjRwBKzetRMhHwoUOHWLRoUZnjPvvsM3JycjCZTEycONEToQshhE9S1aoXyarcU/L3afDgwW4fExYWBkBOTo4nQpKEytuCgoJ4+eWXq72J2lPn9eS5PRmzp/jaa+GL/y485Vp+Le69917atWuHw+Fg0qRJbNu2DSge47Bs2TLuu+8+APr06VMqoerataur4t/dd9/NkiVLAHA4HHz99dc8++yzADz11FOlJgWuTeSz5fnzepKvvRa++O/CU67118KdhEryKfeUFD8yGo1uH1NSbMXPz88jMSmqKr063eHJPuHCs+S9823y/nlGYmIigwcPdhWdCAoKwuFwuP5QtWvXjuXLlxMbG1vquNzcXIYOHep6P/z9/XE4HBQWFgLF1ZR+/fVXdLqrG6Ir77vvkvfOt8n7V73uvvtuvv32G/77wdNV7vvqW1/QuElLNm3aVAOR+a6GDRuSnJzMjz/+yC233OJar9FoUBSF+Pj4MuN4Z86cyUMPPUTLli0r7e5+paSFSgghrkHNmjUjPj6e//u//6Ndu3bY7XYURaFbt2689dZbbNu2rUwyBcXV/jZt2sTbb79N586dURQFo9FInz59+PTTT1mwYMFVJ1NCCFHXONWqF+GeHj16ABAXF+f2MbNmzUJRFK6//nqPxCQtVEIIIYQQQnhASQvVx+9X3UL1+jvSQuWO77//nj//+c8YDAYSEhJo0aIFUHEL1RtvvMGLL76IoigsW7aM4cOHV3tM0kIlhBBCCCGEB7lVlEK45bbbbqNbt24UFRUxZMgQ5s2bh91ud21XFAWbzca6deuYOHEiL730EoqiMHToUI8kUyDzUAkhhBBCCOFR7iRMklS5R1EUfvvtNwYMGMCpU6e49dZb0ev1rnkTr7/+evLy8lzzLaqqSsuWLfn+++89FpO0UAkhhBBCCOFBKkqVCyjeDtNnXHfddezatYs///nPaDQaioqKUFUVVVXJycnB4XBQMqrptttuY+vWrdSrV89j8UgLlRBCCCGEEB4krU/VLywsjG+++YY33niDRYsWsWPHDs6dO4fD4aBevXp07dqV8ePH07JlS4/HIgmVEEIIIYQQniQJVbVZsGABAE2aNKFTp040atSIRx55xKsxSZc/IYQQQgghPEjKplefCRMmMHHiROLj470dioskVEIIIYQQQniQVPmrPsHBwQC0bdvWy5FcIAlVJVJTU3niiSdo3rw5fn5+REdHM378+MuaSEzUvNmzZ6MoSqVLYGCgt8O8ZpnNZhYsWMCLL77I6NGjqVevnut9OXToUJXHO51OZs6cSd++fQkNDSUoKIiuXbvy7rvvUlRUVAPPQHiSXHd9j1xzaze55tYO7iRUklO5p2HDhgDk5eV5OZILZAxVBfbt28fQoUPJyMgAirPh9PR0Fi1axOLFi3nzzTd57rnnvBylqIxeryc8PLzcbQEBATUcjSgRFxfHxIkTr+hYm83GhAkTWLJkCQAGgwGtVsuePXvYs2cPc+fOZdWqVfLlzUfJdde3yTW3dpJrbu3gVguUZFRuGT9+PAcOHGDFihUMHDjQ2+EA0kJVLovFwo033khGRgZdu3YlISGBnJwcsrKymD59Oqqq8vzzz7N8+XJvhyoqcf3115Oamlrucvz4cW+Hd02LiopizJgxvPzyy8ycOdPt41544QWWLFmCn58fs2fPpqCggPz8fBYuXEh4eDjbt2/nwQcf9GDkwlPkuuv75Jpbe8k11/tUNxbhnieeeIKIiAg+/PBD9u7d6+1wAEmoyvXpp59y6tQpAgMDWbhwIe3btweKfy197733mDBhAqqq8ve//93LkQrhe8aPH09aWhqLFy/mlVdecXvW8tTUVD788EMA3nnnHaZOnYpWq0VRFMaNG8eXX34JwPfff8++ffs8Fr/wDLnuCuEZcs2tHWQMVfWJjo5m0aJFhISE0L9/f15//XVOnDjh1ZgkoSrHnDlzALj99tuJjY0ts/3pp58GYNeuXRw+fLhGYxPC12m12is67pdffqGwsJCQkBCmTZtWZvtNN91Eq1atUFWV77777mrDFDVMrrtCeIZcc2sHSaiqT7NmzbjtttsoLCwkPz+fl19+mRYtWhASEkLjxo1p1qxZhUvz5s09EpOMobqE2Wxm586dAIwcObLcffr06UNISAg5OTnExcXRunXrmgxRiGvS6tWrARg4cCB+fn7l7jNixAiOHDnCqlWrajI0cZXkuitE7SPX3OolCVP1OXnyZKn76h8vrtlsxmw2V3qsoigeiUkSqkscPHjQ9caUdDm5lEajoXXr1mzbto0DBw7UZHjiMuzfv5/27duTmJiITqejcePGDB8+nMcff5ymTZt6OzxxmUo+axV9LgHatWsHXPgce+rCKaqXXHfrBrnm1i1yza1e7swzJTmXe6ZOnertEMqQhOoSKSkprtsxMTEV7ley7eL9Re2Snp5ORkYGYWFh5Obmsn//fvbv38+nn37K559/zu233+7tEMVlKPmsufO5zMvLIy8vj6CgoBqJTVwdue7WDXLNrVvkmlu9VNWNZFMyKrfMmjXL2yGUIWOoLpGfn++6bTKZKtzP398fqF018EWxmJgYXn31VRISErBarWRkZJCXl8fixYtp164dFouFqVOnsm7dOm+HKi5DyWfTnc8lyGfTl8h117fJNbdukmtu9ZIxVHWbtFCJOmfEiBGMGDGi1Dqj0ciYMWPo168fPXr04NixYzz33HNs2rTJS1EKIUTdINdcIaom+VL1KflxpmfPnpUm/BezWq1s27YNwCNzV0kL1SUunnzQYrFUuF9BQQGATGbnY0JCQnj++ecB2LJlC+np6V6OSLir5LPpzucS5LPpS+S6W3fJNdd3yTW3ernTQlVdSdfs2bNRFKXSpbL3y+l0MnPmTPr27UtoaChBQUF07dqVd999l6KiomqK8soNHjyYoUOHXlap9KSkJNdxniAtVJe4uK9wcnJyhZWkkpOTAWjQoEGNxCWqT+/evYHiqjAnTpygXr16Xo5IuCMmJobs7GzXZ688JdsCAwOlL78Pketu3SbXXN8k19xq5KUufXq9nvDw8HK3XfxD1sVsNhsTJkxgyZIlABgMBrRaLXv27GHPnj3MnTuXVatWeT2BVq/wBb3S46oiLVSXaNOmjatKzf79+8vdx+l0uuZBKalwI4TwrJLPWkWfS7hQlapt27Y1EpOoHnLdFaL2kWtu9VJVtcqlul1//fWkpqaWuxw/frzcY1544QWWLFmCn58fs2fPpqCggPz8fBYuXEh4eDjbt2/nwQcfrPZYPc3pdAJXPi9bVSShukRQUBA9evQAYMWKFeXus3XrVnJycgAYNmxYjcUmqsfWrVtdt5s0aeK9QMRlGTJkCADr16/HarWWu0/JZ1Y+l75Frrt1m1xzfZNcc6uP6ubibampqXz44YcAvPPOO0ydOhWtVouiKIwbN44vv/wSgO+//559+/Z5M9TLdurUKaC4G7InSEJVjpLSrnPmzCm3PO97770HQPfu3WVyyVqmql94cnNzefvttwHo1asXkZGRNRGWqAaTJk3CaDSSnZ3N559/Xmb7woULOXz4MIqiMGXKFC9EKK6GXHd9k1xz6y655lYvp7PqxdtZ1S+//EJhYSEhISFMmzatzPabbrqJVq1aoaoq3333XY3Fdfr06VJLiZSUlDLbLl2OHj3KsmXL+Pvf/46iKJXOq3Y1JKEqx4MPPkjjxo0xm82MGzfO1aRtNpt55plnmDdvHgBvvvmmN8MU5Th16hR9+vThiy++KPWhKyoqYtmyZfTr148jR46g0Wh46623vBjptS09Pd21ZGVludZnZ2eX2lbSRA9Qv359nnjiCQCeeeYZvvnmGxwOBwBLlizhnnvuAWDKlCl06tSpBp+NqA5y3fVNcs31DXLNrQV8oIlq9erVQHEVPD8/v3L3KanouWrVqhqLq2nTpqUWKP4xZ8SIEWW2Xbq0adOGsWPHsmvXLgDuuusuj8QoRSnKYTKZmD9/PsOGDWPXrl20b9+e4OBg8vLycDqdKIrCm2++WaZMrKgdtm7d6upi4ufnR0BAALm5udhsNqB43owZM2Z4rNKLqFpFv1L37du31P0TJ06U6iL0+uuvk5CQwJIlS7jrrrt44IEH0Gq1rkpTPXv2ZMaMGR6LW3iOXHd9l1xzaz+55nqfO/lSdedU+/fvp3379iQmJqLT6WjcuDHDhw/n8ccfdyUmFyv5IauyVpySsXUHDx5EVVXX+FdPqqgl/HLGnfn5+fH4449z7733VldYpUhCVYHOnTuTkJDAW2+9xaJFi0hKSiIiIoJevXrx1FNPSX/hWio6OpqPPvqIDRs2sHfvXs6fP09OTg4BAQG0bNmSYcOG8fDDD9O4cWNvhyqugF6vZ+HChXz22WfMnj2bAwcO4HA46NKlC1OmTOHJJ5/EYDB4O0xxheS663vkmlu3yTW3+rj73X/fvn1079693G07d+68rMdMT08nIyODsLAwcnNz2b9/P/v37+fTTz/l888/d3W1LlHS3friyquXKtmWl5dHXl5ejVR3nDVrVqn799xzD4qi8I9//IPY2NgKj1MUBT8/Pxo0aEDXrl09WplQUT1VP1AIIYQQQohr2N13380333zD3597psp9Z372BQUFBRWOE3U3oVq+fDlbtmzh5ptvpmXLlhgMBgoLC4mLi+Ppp5/mwIED6HQ64uLiSk1yazAYsNlsfPbZZ9x///3lnnvFihWungLJyclemcZCo9GgKArx8fG1puqrtFAJIYQQQgjhQe62XnTq1IlNmzZd1WONGDGiTPdoo9HImDFj6NevHz169ODYsWM899xzV/1Y3lAy1qu8boveIkUphBBCCCGE8CD35qHyfKexkJAQnn/+eQC2bNlCenq6a1vJZL8Wi6XC40vGzwFem9x30KBBDBo0CJPJ5JXHL48kVEIIIYQQQniQO2XTa2oQTu/evYHiJO/EiROu9SXjo5KTkys8tmRbYGBgjYyf8hWSUAkhhBBCCOFRtb9uesl4pP3791e4T0klwLZt29ZITL5CEiohhBBCCCE8SFWrXmpKyTQHQKky+UOGDAFg/fr1WK3Wco9dsWIFgFRdvYQkVEIIIYQQQniQe2OoqudxKpObm8vbb78NQK9evUrNUTZp0iSMRiPZ2dl8/vnnZY5duHAhhw8fRlEUpkyZUi3x1hWSUAkhhBBCCOFBNdVCderUKfr06cMXX3zB6dOnXeuLiopYtmwZ/fr148iRI2g0Gt56661Sx9avX58nnngCgGeeeYZvvvkGh8MBwJIlS7jnnnsAmDJlCp06daqegOsIKZsuhBBCCCGEB9XkCKmtW7e6uvX5+fkREBBAbm4uNpsNAH9/f2bMmMHQoUPLHPv666+TkJDAkiVLuOuuu3jggQfQarWu6n49e/ZkxowZNfdkfIS0UAkhhBBCCOFB7nT5q46kKzo6mo8++ojJkyfTunVr/P39ycnJwd/fnx49evDss89y4MAB7rzzznKP1+v1LFy4kBkzZtCnTx+MRiOKotClSxfeeecdNmzYINX9yiEtVEIIIYQQQniSO9lSNWRUJpOJxx57jMcee+yKz6HRaHjwwQd58MEHrz6gq3DvvfeiKAqvv/46DRo08GosVZEWKiGEEEIIITzIqapVLqK02bNnM3v2bLKyskqt12g06HQ6Vwn32kBaqIQQQgghhPAgyZeqV3VVRawu0kIlhBBCCCGEB9Wmeah8RUBAAADp6elejqRqklAJIYQQQgjhQaob/9VsLcDar2XLlgDMmjULp9Pp5WgqJ13+hBBCCCGE8CB3WqAknSpt4sSJ7Nmzh6+//prff/+d5s2bo9frXdvvueceVyuWuxRFIS4urrpDlYRKCCGEEEIIj5Js6bI9/fTTLFu2jM2bN5Oamkpqaqprm6qqbN++3e1zKYqCqqooiuKJUCWhEkIIIYQQwpMkn7p8fn5+rF27lrlz57Jy5UqSkpIoLCxk7dq1KIpC9+7dL7uFylMkoRJCCCGEEMKD3KpKJ1lXGTqdjilTpjBlyhTXOo2muATE7NmzadeunbdCK0USKiGEEEIIITyoltdUEFdJEiohhBBCCCE8SBqfqs+JEycAiI2N9XIkF0hCJYQQQgghhAe50+VPki73NG7c2NshlCEJlRBCCCGEEB4kE/d6zubNm1mxYgXx8fFkZmYCEB4eTseOHRk+fDh9+/b1eAySUAkhhBBCCCF8yt69e7n//vvZtWtXudvnzZvHq6++Svfu3fn888/p1KmTx2LReOzMQgghhBBCCFS16kW4Ly4ujj59+rBr1y5UVUVVVXQ6HdHR0URHR6PT6Vzrd+zYQe/evVm9erXH4pGESgghhBBCCA9yK6GSpMotGRkZ3HLLLRQWFqIoCvfeey9btmwhPz+f5ORkkpOTyc/PZ+vWrdx3331oNBoKCwu5+eabXV0Cq5skVEIIIYQQQniQU1WrXCSfcs9HH31ETk4Oer2e+fPn8/nnn9OrVy90ugsjmXQ6HT179uSzzz5jwYIF6HQ6cnJy+OijjzwSkyRUQgghhBBCeJB0+as+ixcvRlEUHn74YcaOHVvl/mPGjOGRRx5BVVUWLVrkkZgkoRJCCCGEEMKDJKGqPomJiQBMmDDB7WNK9i05trpJlT8hhBBCCCE8SPKl6mOxWAAIDg52+5iSfUuOrW7SQiWEEEIIIYQnSRNVtYmMjAQgISHB7WNK9o2KivJITJJQCSGEEEII4UFS5a/6XH/99aiqynvvvUdhYWGV+xcVFfHee++hKIrHJvmVhEoIIYQQQggPUt1YhHvuvvtuAPbv38/w4cM5ceJEhfueOnWKUaNGuVqo7r33Xo/EJGOohBBCCCGE8CB3evRJUuWeUaNGceuttzJ37lw2btxIq1atGDx4MH369CEqKgpFUUhLS2Pr1q2sWbMGh8MBwOTJkxkxYoRHYpKESgghhBA+LykpiV9++YUlS5Zw8OBBUlNTCQ4OplevXjz11FPccMMN3g5RXMOcTm9HULd88803aLVafvjhBxwOB6tWrWLVqlVl9lP/yGSnTJnCrFmzPBaPdPkTQgghhM/7+OOPeeKJJzh27BjDhw/nr3/9K4MGDeL3339n+PDhfPDBB94OUVzDVDf+E+4zGAx89913LF68mDFjxmAymVBVtdRiMpkYM2YMS5YsYc6cORgMBo/FIy1UQgghhPB5vXr1Yt26dQwYMKDU+vXr1zNs2DCeffZZbrvtNho0aOClCMW1TIr4ecbo0aMZPXo0DoeDxMREMjMzAQgPD6dZs2ZotdoaiUMSKiGEEEL4vEmTJpW7fsCAAQwZMoTly5ezadMmbr755hqOTAhJqDxNq9XSsmVLrz2+dPkTQgghhNd8++23KIpS7mIymWjevDlTp05lx44dV/wYOl3x78c19Wu1EBdzp8KfVPrzbZJQCZ+yZs2aSv/wXnfddYwePZr//ve/5OXlVXquJk2alDp+5syZbsXwxhtvlDquT58+le6/Z88eHn/8cbp160ZYWBg6nY7AwECaNm3K8OHDefbZZ1myZAkFBQXlHl/R861oCQ0Ndet5CCFEbbB79+4Kt1mtVhITE/n666/p3bs3H3744WWf//Tp08TFxWEymcp0BxSixkhGVadJQiXqDKvVSlJSEsuWLePRRx+lQ4cO7N271+3jv/nmG7f2+/rrr93az+Fw8Je//IVu3brx8ccfs3v3brKzs3E4HOTn53Py5ElWrlzJP//5T8aOHctrr73mdqxCCFFXlCRUer2evXv3Eh8fT3x8PLt372bevHmMGjUKAKfTyVNPPVVpAnYpm83GnXfeSWFhIS+88AIREREeeQ5CVMWtiX2Fz5IxVMJnPfzwwzzyyCOu++np6Rw+fJh//etfHDlyhFOnTjF69GgOHz5MUFBQhefx8/PDarWyceNGTpw4QdOmTSvcd8uWLRw5cqTUcRV57LHH+N///gdAdHQ0Dz74INdffz1RUVEUFhZy+vRptm3bxsKFC13nrEyPHj3cKvkpXVqEEL6k5IevNm3a0KlTp1LbunTpwsSJE5kwYQLz589HVVW+/PJLPv744yrP63Q6uffee1m3bh0TJkzgueee80j8QrjDKQlTnSYJlfBZUVFRdOjQodS6wYMHc8899zB69GhWrVpFSkoKM2fOZPr06RWep1OnTpw7d46TJ0/yzTff8NJLL1W4b0nrVJ8+fUhJSeHUqVPl7peQkMCMGTMA6Ny5M6tWrSI8PLzUPn369GHy5Mm89957bNmyxVWZpiIBAQFlnq8QQviyU6dOua59lyZTF3vssceYP38+APv376/yvKqq8sADD/Dtt99y44038uOPP6LRSKcc4T3SAlW3ydVF1DkGg4FXXnnFdX/FihWV7q8oCnfccQdQebe/oqIifvjhBwDuvPPOSs+5YMEC12Ryb7zxRplk6lJ9+vRhzJgxle4jhBB1zZ49e1y3K0uoGjdu7Lpts9kqPafT6eS+++7jyy+/5MYbb2Tu3LkenX9GCHdcOkdSeYsMovJdklCJOqlbt26u22fOnKly/7vuuguAY8eOsXnz5nL3WbhwIVlZWRgMBm677bZKz3f69GnX7ebNm7sTshBCXHMuHg9VWUJ1/vx51+1mzZpVuJ/T6eT+++9n1qxZTJgwgZ9//lmSKVErSE2Kuk0SKlEnXTyOSK/XV7l/y5YtXdX6Kio6UbJ+7NixVbY4GY1G1+2DBw9W+fhCCHEtcreFat68ea7bEyZMKHefkpapWbNmMWnSJH766Se3rv9C1AQpSlG3yRgqUScdOHDAdbtJkyZuHXPXXXexZcsWfvrpJz788MNSv2qeP3+epUuXuvarysUtZM888wydO3eu9FdVIYS4FpW0UNWrV4+YmJhy91m/fr2rCEXfvn256aabyt3vtddeY/bs2QQGBtK2bVveeOONMvsMHjyYwYMHV0/wQrjL3YRJkiqfJQmVqJPee+891+3Jkye7dcxtt93Gk08+SWZmJosWLWLSpEmubd9//z02m42IiAjGjh1b5bluueUWnn/+eZKTkzl27BitW7fmhhtuYNiwYfTs2ZNu3bpVWnmwPPn5+SQkJFS5X1RUFFFRUZd1biGEqGmZmZmu7tEdO3Ystc1ms5GYmMh3333HO++8Q2FhIR07duTXX3+tsLjEyZMnAcjLyys3mSohCZXwBsmV6jZJqESdkZGRwcGDB3nzzTddrUn9+/d3O6EKCwtj3LhxzJs3j2+++aZUQlXS3e+2225zqwtJQEAA8+fP58YbbyQlJQW73c6yZctYtmwZABqNhs6dOzN69Gjuvfdet8ZZ7dixo8yXjvK8/PLLpYpyCCFEbXRxd7/Vq1ejKEq5+3Xs2JGpU6fy6KOP4ufnV+H5Zs+ezezZs6s5SiGqh3Tpq17r1q0DoFevXpVeF2qKjKESPuvVV19FURTXUq9ePQYMGMDSpUsxGAzcd999LF26FJ3O/d8NSqr3LVmyxFXK98CBA+zcubPUdnf06NGDAwcO8Morr5Tpduh0Otm9ezdvvvkmbdq04dlnn8XhcLh9biGE8HXuTtCbmZnJ4MGDa8WXJiGulFOteqmunOv06dP8+9//Zvz48TRq1Aij0UhQUBCdO3fmueeeIyUlpdzjTp48Wep7VUXLjh07qinSKzd48GCGDh1aqgiYN0kLlaiTWrduzZNPPklgYOBlHTd27FgiIiLIyMjghx9+4JFHHuGrr75ynbN3796Xdb7Q0FBefvllXn75ZQ4fPsymTZvYtWsXmzdvZteuXaiqit1u55///Cfnz5/nyy+/rPBcgwYNYs2aNZf1+EIIUVtd3EL1+++/u8ZQWa1WEhMT+fjjj9mwYQNJSUlMnjyZw4cPX9YPZELUJjXVQnXmzBmaNGnimroFIDg4mPz8fPbt28e+ffuYOXMmv/zyC0OGDKnwPNHR0RVuqy3FXtQKXtShQ4eiKApffvllqSkXPElaqITPevjhh4mPjyc+Pp7du3ezePFiHnzwQfR6PfHx8QwaNIjDhw9f1jn1er2rJPo333yD0+lkzpw5wOW1TpWndevW3HPPPXz88cfs2LGDU6dOcd9997m2z5o1i40bN17VYwghhK8oaaEKDg5m+PDhdOjQgQ4dOtCjRw8mT57MmjVrGDBgAACJiYmuiX2F8EU1VeWvpLfL2LFjmTt3LpmZmeTk5FBQUMCSJUto2rQpWVlZTJgwgdTU1ArPk5qaWuHSuXPn6gnWDT///HOlcZZnzZo1rFmzhvz8fA9FVZYkVMJnRUVFuf4Ad+nShTFjxjBjxgzXoOXMzExuv/32y+5KV1LFb8uWLcyYMYOkpCQURbnqhOpSDRs25PPPPy81p9XcuXOr9TGEEKI2slqtrh+8OnfuXO74Ka1Wy2uvvea6X/LjlhC+qKbmoAoLC2P37t0sWrSIW265hbCwMAAMBgOjR49myZIl+Pn5kZuby6efflpNj+o5kydPJjY2lhYtWnD33XfzxRdfcOjQIW+HVYYkVKLOGTt2LA899BAAu3btuuxByr169aJNmzYATJ8+HSjubteoUaNqjbPEAw884Lp99OhRjzyGEELUJvHx8djtdgC6dOlS4X6DBg3iuuuuA2Dp0qUUFBTURHhCVLuaaqEKCQmptAWpTZs2rnk3S8aH12aNGzdGVVUSExP5+uuvmTZtGu3bt3dtnzt3LvHx8V6MsJgkVKJOevnllwkICACKi1cUFRVd1vElrVFWqxVwb+6pK3Xx3CsVVbkSQoi65OKCFF27dq1wP0VRGDduHFB8PV6xYoXHYxPCE9xJqGpqnFVERASATxTDOnHiBGfOnOG7777joYceol27dsCF70svvfQSXbp0ISwsjLFjx1Y6ZYInSUIl6qSoqCgefPBBoHiAZklhCXfdcccdmEwmjEYjoaGh3HLLLZd1fEUDJctzcbUcmfxXCHEtuLggRWUtVIAroQJYuHChhyISwrNqSzJlt9td47U7dOhQ4X59+/YlODgYk8lE06ZNueOOO9iwYUPNBHmJ2NhYbrvtNv773/8SHx/P+fPnXd+zWrVqhUajIScnh6VLl/LSSy+5jrv//vt5+eWXWbVqlesHck+RhErUWU8//bSrzO5bb73l6l7ijkaNGlFQUIDVaiUrK+uyJ+F99dVXefrppzl79myl+508eZLnn3/edX/ixImX9ThCCOGLSlqo9Hp9qe475Rk6dCgmkwmARYsWXdYPVkLUFu6Oodq3bx/du3cvd6kOn3zyCampqWg0GqZOnVrhflu2bHFNon3y5EnmzJnDgAEDePLJJ73+GQwPD3fdnj9/PtnZ2axYsYJXXnmFG264wbVty5YtvP766wwfPpzQ0FD69+/PCy+84JGYpP6oqLPq16/PfffdxyeffMKJEyeYM2dOpReP6pSXl8f777/Pv/71L4YMGcLQoUPp2rUrUVFRKIrC2bNnWbVqFV988QV5eXkA3HzzzZWWMM3PzychIcGtx2/dunWtKWsqhBAXczqdrjEP7dq1w2AwVLq/yWRi2LBhLFq0iLS0NLZt23bZU1gI4W1Op7cjKE7W/v73vwPwl7/8xdV9roSfnx+PPPIIt912G127diUwMBBVVdm9ezevvPIKCxcu5MMPPyQqKqrUj8GelJaWVmkJd4CAgACGDRvGsGHDAFyJ4OOPP05iYiIbNmwgOzubTZs2sXnzZl5//fVqj1MSKlGnPfvss3z22WcUFRXx5ptvcuedd7o+aJ7UoEEDtFotDoeDuLg44uLiKt3/7rvvZsaMGZXus2PHDjp27OjW4584caLMZMJCCFEbHDlyxFXOuKrufiXGjx/PokWLAFiwYIEkVMLnuNum06lTJzZt2lTtj5+SksKECROwWCx0796dd955p8w+9evX55NPPim1TlEUunXrxoIFC5g8eTJz587lzTff5JFHHiE0NLTa47xUTEwMLVq0oF+/fgwYMIABAwbQokULt46dNm0a7dq1Q1VV9u3bx5o1a1i/fr1H4pQuf6JOa9iwoatV6siRI/z444818rjTp08nJSWFb775hgceeIBevXoRGRmJXq/HaDQSFRVFv379+Nvf/saePXuYNWsWRqOxRmITQghvatOmDaqqoqqq21VYp02b5jrGW4POhbgabhWl8NBjZ2ZmMmLECE6cOEHLli1ZvHixa0jE5ShJwvLz86v8obi6qKrK0aNHmT17Nvfffz+tW7emQYMGru1Hjx6tsguioih07tyZJ554gp9//tkjcUoLlfApgwcPvuy+uzNnzmTmzJll1p88efKqYqnq+MjISO644w7uuOOOq3ocb/dVFkIIIcTVcetPuQf+3Ofk5DBy5EgSEhJo1KgRK1eurLILXUWaNm1KZGQk58+fJzExsZojLd+pU6fYsGGDa9m/fz9paWkoioKqqtx4440EBQVx/fXXM3DgQPr3718jcV1KEiohhBBCCCE8yBs/jebn5zNmzBh27NhB/fr1Wblypcfm1PSUhg0bMmXKFKZMmQIUJ4gbN25k3LhxKIqCoijk5uaybNkyfv/991LHzpgxgwkTJtC3b19XYRtPkYRKCCGEEEIID6rpziYWi4Xx48ezadMmIiIiWLlyJS1btryqc544cYLz588Dxa1V3hASEsKYMWNc97dv3052djbr169n/fr1bNmyxTUB+CeffMInn3yCXq+ne/fuDBw4kIEDBzJ69Ohqj0sSKiGEEEIIITyoJhOqoqIiJk2axOrVqwkNDWX58uVVTk8AxUMMSibMLU9JZT+TycTQoUOrLd6rERAQQNeuXV1Vku12OwaDAUVR6NevH/v37ycrK4vNmzezefNm3n333cuaRsddUpRCCCGEEEIID3KqVS/VkXM5HA5uv/12li1bRlBQEEuXLqVbt25uHTt48GDeeustEhIScDgcAK6y6RMnTuSHH34AiisoXzwXVG2i011oK5oxYwbp6ens2bOHDz/8kIkTJ3osbmmhEkIIIYQQwoOcNdRCtXHjRn755RcAbDYbEyZMqHDfhg0bsn37dtf9U6dO8fzzz/P888+j1+sJDg6moKAAi8Xi2uexxx7jpZde8lj81U1RFDp16kSnTp147LHHPPY4klAJIYQQQgjhQTXV5c950QzCVqsVq9Va4b6Xlk5/9913WbFiBdu2bSM1NZXMzEwMBgOtW7emX79+TJs2rdbMATdr1iyAUiXUvUkSKiGEEEIIITyopoZQXcn0MiVuvfVWbr311mqOyDNK5hgtT6NGjVAUBYPBUGPxSEIlhBBCCCGEB6lqxcUeLmcfUbWrnWf0SkhCJYQQQgghhAfVdNl0UbMkoRJCCCGEEMKDJJ+q2yShqoTZbMZsNgPQu3dv8vLyaNasmZejEkLUdidOnCA4ONgr3Q7qiiZNmpCbm+u1ySOFEL7DF665NVXlT3iHJFSVeP/993n11Vdd97VaLTabzYsRiStRUu7TZDJ5ORLvi4+Pd93u2LGjFyNxny++fxeXmBVXJjc3l4KCArnm+iBf/Mx6ilxza4YvXHPdSagk5/JdklBVYvr06UybNg2AUaNGkZ+fz++//+7lqMTlSkhIAKBDhw5ejsT7YmJiXLd95d+yL75/I0eORK/XezsMn9a0aVNyc3N95t+puMAXP7OeItfcmuEL11xpoarbJKGqRFBQEEFBQQDo9Xo0Go2XIxJCCCGEEL5ERYpS1HWSUAkhhBBCCOFBKlISvS6ThEoIIYQQQggPcmsMlbRi+SxJqCpxcZU/m82G0+n0ckRCCCGEEMLXSLJUt0lCVYlLq/yFh4dX6/mzs3NYsXIZhZYc/PxDGDF8NMHBwdX6GEIIIYQQ7nHQsN6mP263BbTeDKZOkaIUdZskVJUor8pfdVm7fj22nE0M6HCeoAAL5nwTW9eexBB6PYMGDKi2xxFCCCGEcIfBuZrWMcsAyLQ3o0hzg5cjqjscUja9TpOEqhKeqvKXm5tLuG45g0cfQq93uNa3b3mKNdvyyM3tLC1VQgghhKhBDgKc37juBTi/pUgzBGmlqh6qKkUp6jKpA+4Fq+LmM7hX6WQKQK93MLjXIVbFzfdSZKKuS05Odi1CCCE8y5euuQZnHEaD2XXfaMjF4FztxYjqFqcbi/Bd0kJVCU8VpejYNKFMMlVCr3fQsWlCtTyOEEIIIURVFPIJ0XxWZr20UlUfqfJXt0kLVSXef/99YmNjiY2NJT4+nuzs7Go5b1iI9aq2CyGEEEJUBwUz4UxHqyn7Q6+0UlUfp1r1InyXJFSVmD59OklJSSQlJdGxY0dCQ0Or5byKrslVbRdCCCGEuFoa0glX/o5ec67CfQKc3wLl96oR7pOEqm6TLn+V8FRRiqDoe7HZNpXb7U9V4UhSI3o3rJaHEqKU7t27u27v3LnTi5EIIUTdV5uvuRoyCFf+jk7JqHQ/oyEXg321VPy7Sk6qLkohOZXvkoTKC3SGEE6cv5em4V+WSaoUBfq1WciZ1OtpUL+BlyIUdVVKSoq3QxBCiGtGbb7m2h1BZJgDiQ7PwKnC2eQYcnJDyt3XabAS3bSGA6xjpAWqbquWJpfTp0/z73//m/Hjx9OoUSOMRiNBQUF07tyZ5557rsoLSlFREf/85z/p0qULgYGBhIaG0rdvX2bOnInqxgi9lStXMn78eKKiovDz86N58+Y88cQTpKWlVcfT84jgyNGkOT7naNIQTqa05VTyheSpXnguZL+NwyE1X4QQQghR/VRVYdfB7pxNDefg0absPdyYuSujmLsy2rXsODGYyNZvEN10nLfD9Xk2tepFci7fddUtVGfOnKFJkyalEp/g4GDy8/PZt28f+/btY+bMmfzyyy8MGTKkzPG5ubkMHTrU1RTu7++PxWJhy5YtbNmyhYULF/Lrr7+i05Uf6htvvMELL7wAgEajITAwkMTERD766CO+//57Vq1aRYcOHa7ouXmqyl8JnSGEoAaPAaCqDk4nP0qjmOJ+zF3anmHeynfoN+zv1fqYQgghhBBanZ4O3W9m5xYHBr9wtu9PhEu6pR07ehDbsCHo9dKh6Wq5M7Gv8F1X3ULlcBR3WRs7dixz584lMzOTnJwcCgoKWLJkCU2bNiUrK4sJEyaQmppa5vgHHniAnTt3Eh4ezsKFC8nLy6OgoIDZs2fj5+fHokWLePnll8t97CVLlriSqenTp5OdnU1OTg4JCQl06dKF8+fPc9NNN1FYWHhFz81TVf7KoyhaCH2NvHzTH/dh3KDdbNiw2GOPKYQQQohrgz9L8Lf9E3PafNeP4HqDie59b+PIKRuXJlMAWg2sjJMqf9XBrla9SNl033XVCVVYWBi7d+9m0aJF3HLLLYSFhQFgMBgYPXo0S5Yswc/Pj9zcXD799NNSx+7evZuffvoJgFmzZjFu3DgURUGr1TJ16lTefvttAD744APOnStbgeb5558HYOLEibz33nuuAhLt27dn4cKFrtaqmTNnXtFz81SVv4oY/KI4lXU3dnvxfA9Gg51BHeZy1gcmBBRCCCFEbaQSqPxAsOZzgo1bCNIuoSAj7qKtWs6lnq3w6GNHD2Kz2Wsi0DrNgVLlIvmU77rqhCokJITOnTtXuL1Nmzb06dMHKFvh5rvvvgOgdevW3HjjjWWOnTZtGiEhIVgsFubNm1dq2/79+9m7dy8ATz/9dJljr7vuOqZMmQLAnDlzLuMZXRAUFERMTAwxMTHVWuWvMhExw9mf2NV1PzI8FyXnHWx2uZgJIYQQ4nI4COJTApWfXGuCA/PIz9yJpSAXKG6B0lby9UZaqaqHOy1UwnfVSKfYiIgI4EL3wBKrVxd/QEeMGFHucSaTiQEDBrBo0SJWrVrFQw89VObYkJAQevfuXe7xI0eO5LPPPmPbtm3k5eURGBh41c+lJkQ1f44zKY/QsEFxq1y3dmeYu+KfDLzheS9HJoQQQgjfYCNE+QCTssW1xpwXwKHjTVmx2UC96DjGjruR0aOGA8Nd+yQkJABc8fhzUT7pzle3ebzJxW63s3HjRqD0h1NVVQ4dOgQUd9GrSLt27QA4cOBAqfUl99u2bVthy1HJsRc/li9QFA1K2BulxlPdNHgvq1Yv8HJkQgghhKjtFCyE8VqpZCo7J5j4w82I2xaO1abl7Nkz7Nyx3YtRXmtUNxbhqzzeQvXJJ5+QmpqKRqNh6tSprvW5ubnk5+cDEBMTU+HxJdsuLb1ect+dY8s7viIXT8J3sYMHDxITE+P65aYm6Bxj6d9pHjqtE6PBxg1d5rFydShRkeE1FkNdYLFYAGr0vfMFvvJ6+OL7Z7FY0Ov13g5DCHEN0pBNKP/AoDnhWpeeGcb+o41ZvzuYIlvxj9AFVgc5eTKcoMZIvlSnebSFat++ffz978Vlv//yl7+4WowAVzIFxV37KuLv7w9AXl5eqfUlx7tzbHnH+wK7thO7D15o1YuKyKV19C/YL+k6KYQQQgih5Rxh/L1UMpV6LpLdB5qwdueFZConz0bSOSsHDiWWGY4hPER1VL0In+WxFqqUlBQmTJiAxWKhe/fuvPPOO556qGp1aeGMEt27dyc3N7fG+xSrarvS46nan+GHZYsYMvL/ajQOXyb9wcvnK6+HL75/lf3QI4QQnuEkVHkLvZIGFI/ZSUqpz55D17HjYABOp4KqqqRnF5FtttO8aUPuv+dWtFqtl+O+Rrg1iEqasXyVR1qoMjMzGTFiBCdOnKBly5YsXrwYPz+/UvsEBAS4bpd06SlPQUEBQJmCEiXHu3Nsecf7CkXRQGjp8VSThu1j+fJ5VRwpRFnJycmuRQghhGfV7DVXw55DnbDbNTidCifPxrJ1XyO2HyhOphxOleTzhWSb7bRs3pgH7p2Mn9FYA3GJYk43FuGrqj2hysnJYeTIkSQkJNCoUSNWrlxJdHR0mf2Cg4NdSVFlF5qSbQ0aNCi1vmR8lDvHlne8L9EbI0jOewC7o/jtMhpsjOq5gGPHT3s5MiGEEELUFn4h/Vm/ox2bd7dh857r2HvUhKoqFNmcnEm1UGB10KZVM+6/51aMBoO3w722qE43Fm8HKa5UtSZU+fn5jBkzhh07dlC/fn1WrlxJo0aNyt1XURTatm0LFM8pVZGSan4Xj7+6+P7BgwdxOsvP6kuOvfixfFVw5GAOnezhuh8VkYux8H0Ki2xejEoIIYQQNU1Vi9AVfITB8i8ctizX+sj6LQmpfwsOw3DO5cYCCgVWB2fSLNjsKu3btuC+qTdjkKI5Nc+dhEoyKp9VbQmVxWJh/PjxbNq0iYiICFauXEnLli0rPWbIkCEArFixotztVquV9evXAzBs2LByj83JyWH79vLLfi5fvhyA3r17l+pi6C6z2exqqrfZbBUmbjUloskznE2Nct3v0f4M6+J8Y2yaEEIIIaqHzjKHeoFrCA/YgCbn/7AXprq2xTTqRKv2g9EYQsnMKSLpnBWnEzp1aM3dd0xCp6uRKUhFGdLlry6rloSqqKiISZMmsXr1akJDQ1m+fHmlc0uVmDJlCgCHDh1i0aJFZbZ/9tln5OTkYDKZmDhxYqlt7dq1o3PnzgC8++67ZY5NTk7m+++/B+DPf/7zZT8ngPfff5/Y2FhiY2OJj48nOzv7is5TXRRFA2FvlRpPNfmGeBYu+tmrcQnf0aJFC9cihBDCszxxzVXVQsJMS1z360emYj77Xxy27FL7dencgdz84haPrp3bctftE9DppACF17jVQiV81VUnVA6Hg9tvv51ly5YRFBTE0qVL6datm1vHdu3alcmTJwNw9913s2TJEtc5v/76a5599lkAnnrqKaKiosoc/+abbwLwyy+/8Mwzz2A2m4Hirn7jx4/HbDbTrFkzHnjggSt6btOnTycpKYmkpCQ6duxIaGjoFZ2nOun0YaTkT7swnspo46brF7P/0HEvRyZ8QUFBgWsRQgjhWdV/zXUQ6nganfZCiW1FAZ0ug6NHT5bas1WLJtxz1yT69OzMHbfdiFbr0ZlyRGVU3CybLl3+fNVVt/tu3LiRX375BQCbzcaECRMq3Ldhw4Zluud99tlnHD9+nJ07dzJ27Fj8/f1xOBwUFhYCMG7cOF599dVyzzdmzBj+8Y9/8OKLL/Luu+/yr3/9i4CAAHJzcwGoV68e8+fPx3iFVWyCgoIICgoCQK/Xo9HUjotRUL1BHDm1hXZNtwIQVS+H4OSPsVjewWSSij1CCCFE3VNIiPoOJsPZMlsaNsjg+1lrCQ2Ppn79C0W42rZuTtvWzWsySFERaYGq0646Q7h4XJHVaiUtLa3C5fz582WODw4OZtOmTbz99tt07twZRVEwGo306dOHTz/9lAULFlTa3/eFF15gxYoVjB07lrCwMAoLC2nWrBmPP/44CQkJPjV3zeUIa/Q0SReNp+re4TTrVpbt+iiEEEII36aQT6j6EibtnnK3+/kVMaRXCigyPqrWkqIUddpVf/IGDx6M6tZkZRUzGAw8++yzri5+l+uGG27ghhtuuKoYfI2iaFDD3ia/4FEC/C1oNHDbqHg+/+1Hbp7wJ2+HJ4QQQohqoCGLUPUFDNqUSvfr0f4kz374I488cBehocE1FJ1wn7RQ1WW1ow9bLVXbqvxdSqcPJSX/IRwXjae6ZeAy9iQc9nJkQgghhLhaWlIJU6dXmUwBmPyKuKHnMfbsO1QDkYnLpqpuLN4OUlwpaRuuxPvvv19q/FZ4eLgXoylfYMQAjpzeTNsmWwCIrpdDWNJ/yct/m8AAk5ejE0IIIcSV0tmWojdmA8Xft0+djWH3wUZYi8r/+mbTNmX4iJ41GKFwm4yhqtMkoarE9OnTmTZtGgCjRo0iPz/fyxGVL7Th0ySlPUxs9DkAenY8w/5jf6NIoyE7L5jQ2IcIj2jo5SiFEEIIcTn2Hb6OxhH1aNggg8STDVm5tSEp6TpAKbOvXm/kvvtvQlHKbhPeprqZUEkTla+ShKoStbXK36UURcEZ8tYf46msaDTQsVVJ94AkbLa/snbnMDp0f8ircQohhBDCfS3aDmHf9nMcTjzBgcQAsnIrnkfKZivkyJHDtGnTtgYjFO6TZKkuk4SqjtAbwkg88yc6NPqKS3+c0usdDOoSx9GMsdJSJYQQQtRSOvtGstLPERg9HkXRodXqaN9tEoWWXLQh59gXv5/te06UOa5eRBjPTZ8mc03VZk67GztJ0uWrJKGqQ8xZ21Aal79Nr3eQnTSD8Ig3ajYoIYQQQlTJWPQlYX6LUEyhpCfbCI65FUVRMBhMGAwm9GkF5SZTAOkZWezas5+e3TvWcNTCPSqc21P1bnarxyMRniEJVSXMZjNmsxmgVlb5u1RoYO5VbRdCCCFETVPxK3yPUNNmACLCsimwrCY3qwch4c1ce7Vo3hij0UBhYVG5Z1ket5FuXdpLK1VtZT7l7QiEB8mnrhLvv/8+sbGxxMbGEh8fT3Z2trdDqlR2XuXzTmSZZV6Ka13JNADJycneDkUIIeq8qq65qmrHZH3elUwBmPP9WbGpEcuWb8FWdCF52rVnf4XJFFxopRK1y+zZs1FV1e1l06ZN3g5ZXAFpoaqEr1T5KxEa+xA221/R6x1lttntGmYtacKLbW0YDXovRCeEEEKIEqpqIbDwbwT5X5hjKisniF+Wt+d0qhFFm0u+xUKowQBAz+4dpUufELWUtFBVIigoiJiYGGJiYmp1lb8S4RENWbtnGDZb2SpAFqueI4npvP7hb9jtZRMuIYQQQtQQZxbBhY+WSqbOpYfx9fxOnE71I6/AydGTWfy+YqMXgxRCuKt2ZwjisnXo/hBHs//Fpj1tOZ1cD/WPgjFBgYX8dUoWm3cd472ZS3A6pZKMEEIIUdNU22lC7I8R4J/tWnc6KYov53UgI0dPRnYRKelWVBV27t5PZmZ2hecSQtQO0uWvEr5WlKJEeERDwiPeQFVV0s4/TP2o4gl/Rw04xU9xYaxcn0BQgB+P3HWDTAB4jbnuuutct8+ePevFSIQQou679JqrOM4SpjyL0VjoWn/oeCw/LW+OzaYhNcNKXkFxL5IG9SO5c8pNhIeH1li8DoeTNdsSAWjbtp0UuBDCTfJJqYSvFaW4lKIo5GnuxWYv7gLoZ7Tx1z8nY9TDr8t28O086UpwrXE6na5FCCGEZ116zT1+eC2qWnxbVWFnQlN+WNoCa6HC2TSLK5ka0K8HT/3lbhrUj6zReOM27ue3FcVL3EYpcCGEuyShqsT06dNJSkoiKSmJjh07Ehoa6u2QLltgeC/OpjZ13e/WLplRPYsv2F/9vJ5fl+3wVmhCCCFEneVwlJ1TqF7MMNZu74S1UM+6ba2Yv7oRlkKVM6kWrEVOAgP8uf/uW5l043D0+prtRORwOJnz64UfWuf8uhGHQ358E8IdklBVwteKUlREDXqYAosfABqNyrRbT1A/rPi5fPLVClauT/BmeEIIIUSd48j8X5l1waH1iWn2Jzbsv4fF66PJtzg4k2bB7lBp3bIpTz91H+3btvBCtMWtU0mpWa77SalZ0kolhJt8M0MQl8U/qCmnUzu77jeOyeL24fmUDJ/654xFbN551EvRCSGEEHWLw2ElKnRrmXUAkfVb0K7TCIz+kSSfL0Sj0XLTuGFMu/dPBAcFeiPcMq1TJaSVSgj3SEJ1jQiIfoDMrBDX/ZtHHKN/B38AnE6Vf3z4G3sPnPZWeEIIIUSdYc/8CD9jUZl1JTQaDX++7UaaNI7lyUfvYvCAXmg0NV8kymItIis7v0zrVAlppRLCPZJQVcJsNrtmOPelKn/l0fuFk5zVH4ej+C0PCbIyYcgZmsYGA1Bks/Pie3M5eiLVm2EKIYQQPq3QvIeGkVvLrI8O3VVqXFVoaDCPP3wn18XWr8nwXLbsOsp9T3/Gu58uqrRIlbRSCVE1Sagq4etV/i4Vdt3tpJ6/UDFoaK9TDOoMEaEBABRYivj72z9yJjnDWyEKIYQQPqswZzGxAa+j0ZSd69HPWIQt87+l1nlj6pL0TDOvfjCPF979mXPpuWzbk0hyWtnWqRLSSiVE1WQeqkpMnz6dadOmATBq1Cjy8/O9HNHV0epMpBeOpl7hdxiNRej1Dm7ovZ/IBn/ifz/sIi/fSnZuAc+8+QMfvnonURHB3g5ZCCGEqPVUVcWe9SENw9dRWf2q+qHbyHBY0Wr9ai64PzicThau2MWXP66lwHKhO2JwoIkn7x/FwN5tAEhIKC5U1aFDhxqPUQhfJS1UlagrVf4uFh47hjMpsa77nVunUpC5kVeevBE/ox6A8xm5PPvm92TnFngrTCGEEMInOJ2FaHOm07Be5ckUFLdSlVf9z9OOnUzj8Ze+5j+zV5RKpkYO6sSs96e5kikhxJWRFqprjEajw268mdy8/xEcWFzp76ahh/lt3R5e+eskXvjnXOwOJ2eSM3n+7R9594XbCfA3ejtsIYQQotZx2tMJLPobweG5rnUFFiM/LO5A0nl/YItr/Wv/HYBWH8g999xXDY9ciB9b0HIOB9FY6Q2U/VttsRbx9c/r+WXpdpzOC90QG8aE8+R9o+ncrlGp/VVnEX7KSbRKHtZcB8bAdigafTXEK0TdJgnVNSgkqi9njv9O25bxaBSIiTITFbSTqLCe/P0vN/L6R7+hqnDkRCovvvczbz03GaNBLqhCCCHqIveSk0s5HXaSjs2iZ7sLydT5zBC+/LU9IYFWnpq6hTPHo1zb/nr3Fr5d2JHDhw7Rtl27K45Wx1HClDfRKjmudQ41hCz1eey0dK0z51l48O9fci79Qnx6nZbbJ1zPn27sg+GSiYNtlrPkJs+mcXgqer2NovwNZJ5vQHDMVPSm6644XiGuBZJQVcJsNmM2mwF8vsrfxRRFwRgxmYzMJCIjMgEYPeA4H3+/iDvvepAn7xvNB58vBWDfwdO8/tF8XnlqElqt73d5vNYlJyd7OwQhhKg13E1OyqPR6rApfTl4/BRtmiVz4mwUKzc3IKZeDreMPITJz8HM95pddISNuyfs4fi5CPw5gYoGLlou3NdWss1BCO+jVaylYtEqOYSqr5DF66iqAdXpINBgY0x/f/YfPo9Rr9KicQTD+rcmJKCIouyVFDoLUR2FqE4rTocFPUdp1fQUep3jQsT2NE4nFaCLfUVaqoSohCRUlXj//fd59dVXXffDw8O9GE31CgxrT9KRtoSGbEGvcxDgb+P6zofZvHkTY4cNIC/fymffrwZg886jvPfpYp5+aJxX5skQQgghql8hoepraDWlC05plRzC1JfI52Y0ShEKBWgoQPlj0ZCHggUNBUS3KUBRihOQZg3PMa3huUof0c/opH3DFR55NjqNhUim//EkAD38bcqle61x3VJVUFXFdVujUbm06KBe56BR7BGS8/ZiDO7hkbiFqAukyaES06dPJykpiaSkJDp27EhoaKi3Q6pWobF/IjXtQneEfl3PcubEJnJycvjTjX340419XNtWrE/gf9+sRFXLloIVQgghfIFCATrnPoz2Hwm2/x2dtvzqvVpNIcGa7whUfiZAWYJJWYOfsg2jkoBeOYlOSUOjmF3JlC9SlOIkSqNR0WrLJlMl9DoHfpodNRucED5GWqgqERQURFBQEECdqfJ3Mb+A60hJ7kKEJQt/kxWtVmX0gGMsXbKEP912G/ffNhhznpUlq/YA8OuyHfj7GWgUG0HKuRwaRIfSv2crGV8lhBDC44qsmeSd/wa9Jo0iR32Cou/CYAwtd1+n04LGdgit8zA6TqLXJGPQZWDQW6r9p2SnU8Hp1OBwanA4tGgUJ35+RRXub84LoKjIAIqKAu7/H9DrbJWe22bT4lQ1pY5TFBWU4gRKQUVRipfLYdDbKLysI4S4tkhCdY2LbHQrSSkHadnsJABtmmWwdd9hDh8+RJs2bXnivpHk5VtZt/UQAHN+21Tq+LCQAP7x9C20aR5T06GLKxATc+F9kvFUQghfkZmymBZRszE0LmkROkSRbT3Hkm8mKLgpGudR9JzCoE3DoM/Cz1CAxnR1PSrM5gAKrCYM+iJCQ3JdLTiqCmeSG5CfH4jdocHp1KCiUNKBQ1EctG99DL3OwbS/JbrON/O9ZtjsWg4fb0SRXe/qcuf6P1SwTgMoqKoGf2MhvbvFlxrnVMJm17Jqc2cyc01A5d3ztTo9/gFhBASGEBAQQoN6J2gYPr/iAwwyJ5UQlZGE6hqnM4ZSoPYmMzuL8NDiQbljBx3lfz/G0bRpM4xGI889Oh5zvoXdCafKHJ+Vk8+L7/7Mtx89LC1VQgghql2hNb04mdKXTiIMegdtY3+qsKtaeVQVrIVGCix+FBQYaVA/HZ22bMEpm13L6q2taNkkmbYtLlTJczg07DnYhFVbG4BSnOhc+vABJid+xiKaNznN599eGFP1ydstOX6yEVsTIjAXaHGqgApOtSSR+mPhwu1LEyOt1ki98EY0b3L6kuIRWo6fbMTJ5ECMfjr0WgeK4qgwrXLYbZhzzmHOKY7v5DEHkcP0+BltZfa1Fuop0PRCq634dRXiWicJVSXqapW/S0U2uonkxD2EBJnRap3UC7PQo/0p1q5ZzYiRozDodQy9vn25CRUUJ1Ubth9hWL/2NRy5EEKI2qWQ+qF7MRmy8CPT7RLkLmo+GsdRsB1E4zyJjmRC9efLJFMlKkumimw68gv8MOf5k20OIDMngJRzAWSa9VisGgptKjcPCyg3OTl5OpbeXY4TXe9CMmUtNBC3qTVbEyIAcDghOjoKnU4LKqiqiqqq5FkLSDhmx2I1Ahtdxyccasnxs6Gcy9K6ikFcLodDQ9zWBlisRiLCcjHobRTZ9GRkBbNpbzhpmRrACSgoihaDDgx6FYMBjHq1+LYeLi3a63BqWbutHQN7HsDkdyGpslj1rNvejshGJ4lpKH/jhaiIJFSVqMtV/i6m0fqhmAZzLj2LBtHFv1YN7X2Sf3+dQGpqZ+rXb0BGVl6l50hJy66BSIUQQtRWJSXI6zcqKUG+qpwS5CoKuehIRUsqGvUsWucJtCSj02Si0xYVV6gzuP+4TifkF5jIzfMnOzeA9OxAMrIDsVgNWArBUqhQYFWwFCo4nRcSGUuhg5Vb65dJTgosehpfl1wqscjODWLe8jacTAkAIDO3CJ0hmM5detHwugb4+5tc+9rtdn787gushaWbdPYfjyAtK5D77r+neD+bDZvdhs1mx263kV9QQHZ2LuZcM+a8fPLy8ikoKMBitZKfb8HpsGPQa0jLNLBgXRQtrgsm0N9BXoGWY2f9cDhKZ0mqqlBog0KbAgWltqDVglH/R7KlVwk0qWTmBLFwVQ+uq59BoL+VvAI/zqZG4HBqsSWdkIRKiEpIQlWJ6dOnM23aNABGjRpFfn751YDqgvDYG0g7tIXw0GyMxiKMBgc39E3k99+Xcccdd9EgOrTS46vaLoQQoi4rJJTX0SrmUmu1Sg7hvEghXdFxDi0paC6ZQ4mr7Eq273BTDh6PxenUUGCFfAsUFCpYC6F0lzkFP1MABr8gDEZ/zqfnsOPAGdKzwpkwLB+9TkOOWUfvLqfQaooHRKkqJKVG8uOyluTkFWd557MKyTbbgQxmfPEjAIGB/kRH1SMqMoLoyHAi6rfi0JG9peI8dEpL23btSDhwjKzsXLKzc8jKznUtFsslr0s5FAWaxJgADYdP+ZfaZnc4OZtqRaNR0GhAq1HQaBS0GgWDXou/vxGjQY9Op0GjAafTSZ7Fht1sxxrgJDbKicOp5VRyVJnHtdndfTeEuDZJQlWJul7l72KKosVUbxTJaZk0bXQGgG7tUtkWn8zu3bvo37MLYSEBZOWUTSrDQgLo37NVTYcshBCiljA416PTmcvdplGKMLHVrfM4nQpFRXoKrEbyCvzINfuTk2ekV+fj5RdisGnZfaA+See1FNng0jFHRqORxo2b0LRpMxo2aozBcKHpq8hm4/W3/0fb5qfp0rb4715Gtr8rmXI4NBw63ohfVzWkyKZFVVVSMwrJKygbR15eAXl5pzmeeNq17tLuiIlnLRw/s8Gt16Eidgckny8kJtKI7qJ+e3aHk+TzhdgcKjjKK8Zhg8zyEza9Tkf9SH+iwwvRlfOt0G6H4LBGVxW3EHWdJFTCJbheL1IOrSXCnEVwUB6KUlyg4otfgmnVqhX/ePoWXnz35zJJ1a3jeklBCiGEuMYoWNA5tqO1ryfIsMft4xwODUU2PUVFBgqLDOQXGMnNM5GZ609Wjj+FNh3FVe1UnKoOo9GPjTsN9Ot2EP1FY6lsNi0bd7UlI0dPke1C9hIUFESTps1o2rQZDRrEoK2gmoJBr+e+qTfRPuo51zo/o4PcPD/0OpUd8c1YuTUKVVVwOFXSMooY0P96IuuFc+58BufOZZB2PoPz5zOx2cs24Vw6bWNV0zhqtVpCggMpsDqIjYmkeZMYwsNCCA0NJiw0mCI7hAX7886/PuNkcj6BJi06nQa73UmexYG/v4l77ryR7Bwz6RlZpGdkF/8/PQtrYcVFz212O2dTcwky+dGkgVoqqbLb4WSKQqgU8hWiUpJQeZHdZmfZioUAjBo+Hp3eu2+HoiiExNxEStp5AgPz0CjQqEEuHVulsCoujpsmTOTbjx5mw/Yj/LpsB4eOFZfdXhy3h4mjeqLXSQkgIYSoq1RVpchyBqVwLf663YQFnkard4Ibv6dlZIWSnRNCvsUPc76RInsgdjWErDwDp89mYc4rwlqkYi0qbjmKjoqkdYumqHYbiWdPY7WE8tvKnrRsfI6gAAvmfBNHT0VhLdRhLlCoVy+Sps2Kk6iIiHoobpb+qx+4jkD/C8lGgKmQvYdasedYG46fyAEU7A4n6dlO7rrjVlq1aFLmHE6nk6zsXFeCtWv3fs4kpVb4mNFREbRu2ZSw0BDCwoqTpYDAAFasO8B38zdTYCkkvcDEw/f3R1tOz5j7776Fz2f/jDkvHyhOMIMCA7j/7lto1LBs5qOqKvn5lj+SrIuW9CzSM7PIz7egqnD8bBHWIgNhQQp6PdhskGVWSTpXROMW5bc+CiGKSUJVCU9X+Vu1dhn9267+47aeETeMq9bzX4mAkNakpDYiIyObyHoZAIzol8hH39Tj+PFjtGjRkmH92tOjY1PuemoG+QWFJKVmsWjlLiaO6unl6IUQQrjD4bBxPvUYVksOJlMI9eq3QKvVX7KPnbzcc1jMBzBpthEeeJzosCw0geWfU1XLr7pns2s5ldqJoKgbCa3fgHo6IwcPJ7Jk6WrSziVjNGjwM2gwGnQE+uvRalSctnwOHkxwneOMXUvDaDiYeCFhsNvhTJqWTp270a/fgMt8BewYCv9LvbB1Zba0bHyGXSdGkJO3G5NRi9mi5aEHbiemQdmxRQAajYaI8FAiwkNp26Y5QYEBfPvDggofefjQfnTvWlzgQVVV1m87zMzv5pN6Ltu1z4kz2hnwxQAAowtJREFU59m66zjX92hZ5vhGDWN44bmHiU84QkZmNhHhoXTs0AqDvvzMVlEUAgP9CQz0p0nj2DLbLRYr6zftZOnydZxIsnL+kpYvVYWI8NAKn48QQhKqSnmyyp/dZqd9zGraND8LQL5lNXbbKK+3UgGEN7yFtLNJhIZmo9c5CA4oYmCP06xZs4qGDRthNBoJCfbnzxP7MXPOKgC+/mUDN/TvQFCgqYqzCyGE8Kbc7FT27/qF6IgzBJqs5J334/jhhrTuOAanw05OVhLOokOEBRzmuuh0wppUXJDJYjWSaw4i1xyEojhp3PBsmRLkp840JDR6APqAhuw/eIiNG7dizs3BaNDS/Dr/S1qTyu8XZy1SOHZWS5C/6mo9MRcoqKpCWNjl/W1WnCkE2F4m0JRe7nZ/k4WhPZPIyGpJatp5Hn90MiHBQW6fv2OHVgQFBvzRglRaUGAAHTsUjzk+kpjC/76JI/7QmVL7NIwJ58E/D6N31+YVPoZBr3clZVfLZPJj8MBebNi0E3NePuYCByUtX5fGLIQon/e/vddinqzyt2rtMiYPSnLdb98yiR/XLGXk8PHV9hhXyujfgCxNa1LPmWkYkwLA9V3PsOtAfTZv3sTgwUMAmDCyOwtW7CL1XDbmPCtzft3EQ3cO82boQgghKuFw2Dhz5CtG9d91yXxDJ4g/cpLgQAtdmmQQGFD+mBtVhQKLyZVE2RzBGAJaoQ9tTm7aEg4f8yM4yOwqQZ5rDqLIZmDthniysovnZFKA4MCK+wkqikJYeDhRkdFERkVy7FQOJ47uws+gITe/dBOYtchJUoaDdm4+f8W6mAjjbHSm8ue1KhEZsIw/TfoCh6rgZ7yMebQoTnZKuuVdrKRbXq7Zypc//s7ydfGXbPfjrpsHMP6GrsVzW9Wgi2O+OBEsibmi1i8hRDFJqCrhqSp/Ja1TfsYi1zo/YxEdYldjKxqFvhYUeKjX6GYyjh8jIiwLf5MVnVZlVP/jfLfYnwB/fxSNQnBwCPf9aQBvfFw8Duy333cwfnhXYuvXzfm66oK6XKlSCFG1jLSD9Ou6Cz+jrdR6k5+NXp2Ol3uM06mQV+BPrjkIszkIiy2C/KJIzNZwcvJNFBXZsVpPYc0L5PpORahqiOtYa6HChr3BZOXmlntuRVEICwsjMiqayMgooqKiiIioh/6PL/BJqZl8/8laVEchfdsZ8TNcuIZZi5xsPlBIVOOqx/coWNHlv05E0IEq94XiVqrz6T/jF36HW/tfqlHDGJ5/+kG+mPEOxZPswgvPPczW3Ym889/vsBZeeP21Wg03jejOnZP6ebWXR0lXwqXL4sg1F9CubetKuxIKIS6oloTKbDazevVqtm/fzo4dO9i+fTsZGcXjbw4ePEibNm3KPe7uu+/mq6++cusx7r77bmbNmlVq3eDBg1m7dm2lxz366KP85z//cesxasqlrVMlOrU+wzvffMv9d9/jhahK0xmC0fh3IznVQoumJwFo0yyDFo0y2L79Qvlbk8lE93bR7DyQht3h5PPv1/DyU5O8FLWoytmzZ70dghDCi/yUrWWSqfI4HBrMeYHkmoPIyg0gNd1ESrqRlHQjlkItYP5juZiOxRsjiY20uiacTTrv55pMV1VViuwq/v6BdGjflmbNmlKvXqQrebrUxh1H+Of/FpFfUNxatmyHhZgILQF+GvKtTpIzHDidEB0ZUu7xLrb9BKtvYQq6MLttYZGeM0mxWKwVJzBB9a+uS926bUdoO/AvADzz8DgMej0tmkTjcFwYj923e0se/PMQrmsQcVWPVV0Mej3Nm14HQIcOMpGvEO6qloQqLi6OiRMnXvZxISEhREdHV7jdZrORmZkJQLdu3SrcLzg4GJOp/IticHDwZcdVwhNFKcprnSqh1zu4bdg2NmzvS/+e5SehNSniunGcO7KPzOwQwkNzABg98Bj//S4Mh7P4V0KLxUKzKD27DxXPVr9+22HiD52hY5uG3gxd1BHWQhs7Es6SmV1AWo5C/56tpES/EFdBr5yudHuBxY+085GkpQeRfN6PlAwj57MMrqSoKk6nwpm0sn+Pc/Js+AfWY8KEYTRtcl2l53A4nHz501p+XLDlknPD2fOlx/cAbN5xhCF925bTTU4F86dEBa1Ao7kwNiszO5jFa1tx9HQF1TWAIUNuIDLE3Y6E5T+HOb9udN2f8+tGhvVrT4OoUCaN6cn2PYk8dOcwunVocsWPIYSoPaqty19UVBQ9evSgZ8+exMbGusYeVebDDz/kww8/rHD7Bx98wF//+lcMBgO33357pee5++67ryTsSnmiKEVFrVMlmjdK4/fN35MY9SjNGpdfUaimaLRGjKEDSTu3nJAgM1qtk8gwCxOGHSI9y5/MXBMHj9fDbocb+jRk+abigbUzvo3j49emotG49wdYiPIcOp5cat6zJWsPExYSwD+evoU2zWVSFCGuhMVa+Z/9Y6ei+H1jIwoKDRgMRgwGAxERxf83GAzo9QYcTieFhXYs1kLy8izkmPOwFOQRFmyo8LyNGzdhyp8mVVnOPCs7n9c//o29By4kftH1Qph6ywA++351uZPLr9t2GOfH8/m/x25yTd+hqk7sWf+mYb0LE+k6nQqHE2P5Na4J1qLKX4dNmzfSuk2bK+4mvXDFLpJSs1z3k1KziNu4nxEDOzL15gHc+6dB5ZZEF0L4pmpJqMaPH8+ECRNc90+ePFkdp3V1Bxw7diwRETXfHO6JohQdGu0tt3WqhKLAA5MO8OT7X/GXBx8mPLTiX9BqQmj9waQe2sy59Ho0iD4HQOc251zbzfl65izqSJHSEL1ei83m4PDxFFZv2s+w/h28Fbbwcecycnn2zR9cXX1KZOXk8+K7P/PtRw9LS5UQl0lVVc6d96Nt04rLm+fZB3H7XeNxOFXOn88k7Vw6qWnppJ3LIDUtmfSMrHJ7aygKBAXo0GnLJgl2h5PwiKgqk6mEw2f5x79/JSM7z7WuV5dmPPfojQQHmhjUtw0bth8hJS2b+pEhJBw+w6K4PQBs2HaYVz+Yx0tPTMRg0OGw/z979x0X1ZU2cPx3pw+996ooomLvGmPvmmZM3fS2m82W+Ca76ZvNpiebdZON6aaZZo0lMSp27B0RRBQQ6Z0BBqbd948JgxOKqEjR8/18SGZuPQPOzH3uOed5zCSlqAkYrkKrsWA0atmwsyf7j/tgT4vRsrpaIydSU4nrfWG9VFarjZW/7OODrzc3WlffS6XRiOnrgnClaZN3dXNVyC/FkSNHOHLkCMBl6X1qjcuRlCKk5zPk/+a7SJZlik6/Rd/uu1EoZDQaKy89ksST//ua5//v/g69cJQkJW4B0yktWUJQQGGjL2F3VzN3zEpi8S99uGn6ML5btQuAT77byphhseKit5MJCWno2cnNze3AljgrLKkkKTWbpNRsjqVmk3m26XTGYA+qduxLY+JoMb5fEC5EXnYSUaEZzQZTJ09FsnlfHflrPqaktBy56QzmTZJlyC2qI8Rf6xRUWaw2covqGH1N8yM8ZFlm+c/7+OibzY75RZIEd8+9htuvH+0Y7aDVqJ3e9xPH9EGn1bD0p70AHDh6khf+/QMv/PVmdFot3eJuZPfhQsKDS1mREE2Fwd6DVme2UVphoaqm5blkQ40tZwL8raTUbN5dtJ7TZxpuOh7f+m7DBtc+5uilEgThytJpb5PU9075+/szffr0Dm7N5SVJEv7dHict8xl6dUsDwNe7imfuOshbC3146rGbO3T4nJvPIKqrv23ySxjsQdWw/tV4Bs5g3ZYjlFfWUFRSybKf9nH79aPat7FCpyfLMmdySxzBU1LqWQqKKy7oGHkF5ZencYJwhTKZjJTmrmXgyIaL/aISb6xWFSazmoJiD5YmuHEmL+O8x/L29iQowJfAAD+CAv0IDPDDx9uTtxZ8RmZuNW6/KQzr5tp8HaMaYx1vffgT2/akOpZ5uOl5+rE5DOnXrcV2SJLEw3dOQK1Wcjp9E3+aV8qPW008+8YSXnpiLl4+ocjygySdLiWvaDNajUxphYnobj24954JeHld/Bzrc5WWV/HRN5vZuP3Yebet76VSNtGTJwhC19UpAyqLxcLixYsBuP3225vNAFTvrbfe4umnn6a4uBhPT0/69evH3Llzuffee9HpdO3R5EsmSUrcw57nTO4TRPxa+6lbRDG/m7iLOtMc9B34OiRJwtMvEjjd7DZRYWBSa7l77jUs+OwXAL79cRfTx/XH28u1nVoqdJTaOjOJ+06QV1hBcKCXU/IIq9VGemZBQw/UiWwqDMYWjydJEnILt8eDA73asvlXrPz8fF599VXWrFlDTk4Onp6eDBs2jL/85S9MnHhpNeNycnJ49913Wbt2LVlZWdhsNoKDgxk6dCi33HIL1113XRu9CqEtnD6xjcF9Uhw3xioMLnyzNgpXPZQbJI6eVGC2NNw1kyQJXx8vR8AUGOhLUIAfAf6+aLVNz5VyrmNk791pqY5R1tli/vHOMrJzSx3LenUP5rm/3ECg33ky99WTrfxu0lFC5qWgVFpx1ap56bNM/v7a97zy5Dy8fSMY6h3Orr2HqLNY+d0dN9Itum2SJtmH9+3ni6U7qDE2Xbfrt86dSyUIwpWjUwZUP//8M4WF9rtorRnul5ycjFarxdXVleLiYjZt2sSmTZtYuHAha9asISIiotXnHjx4cJPLU1JSCAkJ4dix89+BuhSS7XZcdJ/i51MOQJ+YAjYn7UWn79jaTsFuVfi3MJ3rTOYpiuuOERGoIsjPjfziKoy1Jv790UpumdG//RraBKPRfvF+uf92XU1b/T7O5Jbz8Q97MVQ3XFDodWoGxAVTWl5DZk4ZdaaWh85o1EqiQr3pFu5DtwhfQvzdef3jrU7HrOfuqsXbxdKp/55Go/G8N4Iut6NHjzJhwgRHCQsPDw+Ki4tZs2YNa9eu5ZVXXuHvf//7RR17yZIl3H///Y4sqC4uLkiSRHp6Ounp6RQWFoqAqhOpKMvFRdqEt6d9bpIsw/IN0exOanwJ0D++F1Mmjsbfzwe1+sIuES6kjtGmxGT+/fHPTvWY5kwexCO/m4imlec1GzPR1b1OcECBY1l4aC5DewXw4eqz/O2Vb3n177fg7qbn/rvm4eqqb7NafAXFFTz7xhIysouclo8d3ouH75zgCAhDQhqG/G389qk2ObcgCJ1Pp+xzrh/u169fPwYMGNDsduPGjePLL78kLy8Po9FIWVkZBQUFvPLKK2i1WpKSkpgxYwYmU/NJIDobWeHJ0TO3UFXtgqHKlX0pE9HpvTu6WZSWuWO2ND1XzmpVkJ2jxGq1olQomDOxYRLv7sNnyCtsuqCj0PWZzNZGwRSAsdbMrkNnOJFR3GQw5aJX07dHIHMm9uYv94zh1fnT+MMdI5k2NpaeUX64uWp5cN4w3F21Tvu5/7pco277eZtXEqPRyJw5cygpKWHgwIEcO3aMiooKysrKmD9/PrIs8/TTT7N+/foLPvZPP/3EbbfdhsFg4L777iM1NZXq6mqqqqooLi5m2bJlzJgx4zK8KuFiyLKNUynr6B+b6ViWmeNHwp6mRw7ExXYnJDjggoOpevV1jAb268nggX0aBVNmi5V3F63nlfdWOYIpnVbNU4/O5k/3TW0xmLJaazEX/xNz8T+pKfwKP8VT+Ps0BFN1JhVrNsdSWOpK92AVqafyeOLlb6kw1ODu7tqmhc19vdyw2Rp60cNDfHj9qVt5/kJ61wRBuGJ0uh6q0tJSVq9eDcDdd9/d4rb/+Mc/Gi0LCAjgqaeeol+/fsyaNYvk5GQ+//zzVqVxBzhw4ECTywcPHkxlZSV9+7ZH5rq+ZOfrQNLRa+Bwx1JZlqk21uHm0v7D/woyz5CVfZrI8GzUKucLZFmGOpPM2YxMbrj+Ovr06cOBlCIOHM1AliFhzxlee+rWdm9zvfqejPb523Udl/r7MFQZef/LjU32Iv2Wv68H8b3CiI8NJ75XOBGhfuedF9i3L0wcN5zvlidQUl5D//jYLlOHqrm6eO3lww8/JCsrCzc3N1avXk1oaChg76V66623OHXqFCtXruSpp55iypQprT5uZWUlDzzwAFarlaeffpqXX37Zab2vry833igKe3cmOVlHiI04gPbXYr4Wi4JFyyOx2hoPqTVbITO/mmGyfN6MfBejsKSSlxasIOVkQ0KcsGAfXvjrjUSH+593f0vpQiIDDwNgsx3m3Pgov8iTr1f3pqJKQ7nBTGmlBYD0zAL+76VveOPp29p0+LlKpeSxe6fw7JtL+N2NY7hxxlBHynZBEK4+nS6g+u677zCZTKhUKu68886LPs7MmTMZO3Ys27ZtY/Xq1a0OqDoL76BrnZ5bLFbe+3wd6aezeO3Z+9o9qPINHUfRyV2cSI/Bw92AVlOHr3cZKpUNlcpG7x7ZfLvWnRNp6cT2jOHhOybwSNJn2GSZ/Ucz2Hv4FMMGdG/XNgttT5ZljqZk89Omw2zbm4rZ3PJQvmuGxfLInRMJ9L+4O7ZajZrBfe1FQPv2FVn9WuvcOaj1wdS5nnjiCVauXMnBgwc5ceIEsbGxrTruokWLyMvLIywsrMkbWkLnYqqrpizvFwaOaOjF2X0knFNnFciyc+p0sxWyiiD1my2s/OUgA3pHMKBPJAN6R170+/dcB5IyeOXdH53mT14zLJb/e3gmri7aFva0s1hqCPJqKPRbH0zZbBK7D0exLjGcmloZk1XF7NnTGFho5J1PfkaWISO7iPkvLeaNZ27Dz8f9gtt+5PgZEhKT+esD05wCzQF9IvnmvUfxcOvYGyiCIHS8ThdQ1Q/3mzZtGgEBl1bYdvjw4Wzbto3Tp5tPptAVyLLMK+8u4caRB3hkZjkv/edb/vm3u9s1S5BK7YLefy7GoqVUVNq/XGuMLkRH2Iv59u5eTP/YItb/so7IiAfpFhHAtPH9+WnTYQA+WryJwfHRIrNRF1VWXs36bUn8tPmwU7HK8xkzLLZNLsaE1jMYDI6e9qlTpza5zYgRI/D09KSiooKEhIRWB1T1gdrcuXM7fI6YcH7pqZsZGJeGUmlPRW6o1vHtT0HYZBslVVBTBxoVmCxQacSRJr2opJIN24+x4desdUEBXvYAq3ckA/pEXlBQYrPJfPvjTj5fss1xfIVC4qHbJ3DTjKGt7wmreBWtv3Oa8zqTisWr4zl5xp0yg5WRw4cxftwINGo1/QCtRsXr76/B9mtm0cf/+TVvPnt7q4fkFZca+HDxJjbvPA5A/7jwRvUVRTAlCAJ0soAqJSWFvXvt9STON9zvaiLLVv4wZyd9e5wF4M9zD/DuIn/+8sCsdm2Hl39/3Lx6UJKzBbMxA7kql5IyL3y9ywGYee1JMnK8+O77pdxz9x3cc/M1bN55HGOticyzxfy85QizJg5s1zYLF89qs3HgaAY/bT7CrgMnHfVhztU9MpC8wjJqjI3nKXp7ujJmaNOpkoXLJyUlxZEhsU+fpnv1FAoFsbGx7N27l+PHj7fquLW1tRw+fBiAgQMHkpqayosvvkhCQgKVlZWEhIQwdepU/va3vxEVFdUWL0W4BOWlZ3FX7nAkOAJYmdCdskobZgsUlMNvR/2pVEpUSoVTogiA/MJy1hWWs27LUQBCg7wZ2CeK/n0iGBAX6TSUrrbOzP5jZyktryGrwMyOfSfYd6QhFbuPlyvP/fkG4nu1PtOe2VRNgGdao+WyLHE4VUtoeAR33TURb2/nQGnimL6oVEpeeW8VVquN3IJy5v9zMW8+ezvBAV6O7eqz9QFcP3WIvS7Wuv18tWwHxtqGz7Yvl+1g/Kg+HVrGRBCEzqlTBVT1vVM+Pj7MmTPnko+3Z88eAKKjoy9qf4PB4MhiZTabm6wO3x4UChXeHg0f6v165ZJTuIVlPwVw04xh7doWldqFwCj7hPP800vIL7Ti7lqNRmNGr7Nw/cRUvlipZvvOvVwzahi3zhnBoh+2AfD5D9sYP7J3q4Z3CB2noLiCX7YcZd3WoxQWN04o4qLXMnF0b2ZMGECP6CBST+Xy3JtLKauodmzj7enKS0/M7RLzna40eXl5jsfnFnL+rfp1527fkszMTMxm+4V2WloajzzyCEajERcXF9RqNRkZGXzwwQd88803/Pjjj4wbN65Vx+3ozKpXIlm2YSzZwsQRZxzLsnK92H7QAxkLOaWNg6n6hC+hQR5k51WQnlXMyawSMrJLMf1maG9Ofhk5+WWsSTgEQJCfGzGRfnh56Niy5zRVNfbvq5+2nnDar3uED3ffMBjJUsGxY+erPWcDJEAixH0F4dGNi/DqtGbuvamKElNPcnKyycnJbrSNrxvce+NgFi0/gNVqI7+ogseeXcSjd47E38eeunbv0Wy+WX0YgBPpWSSfzKeguMrpOAN7h3DdxN4cP558nnY3r6v8W+6KmXE7Q2ZV4erWaQIqm83G119/DcCtt96KRtN0nYt68nkmza5bt45t2+wX8jNnzryoNr399tu8+OKLjuc+Ph2Xutzq9gIVhr/h6W7/kJ86JoMPl6xizyEfhg+M6ZA2BUTdRE5KFtm5dXSLzEKSoEdkGcPi89m2K5Hu0VHcNGMYazYeoqjUQHllDd+v3s19t1x7/oML7cpisbLrYDo/bz7MviOnaaoEVJ/YMGaO7881w3uh1zW8P3t1D+Hr//6eHfvSyCsob1SHSmhf1dUNgW1LyTFcXFwAqKqqanabc5WXlzsev/rqqwQFBbFy5UomT56MJEns3LmTe++9l7S0NG6++WZOnDjRoZ+ZVzOjIZM+3dNxdakF7POMvv85BkO1BVmhxVBrTyQTE+FLz2g/fL1ciI8NdmTPjAr1JirUm0mjemCx2jiTW+4IsDLPlmK2ON9czC+uIr+45X9H1w6LZs7E3ihbkWlPQTX+uk1U1PWh1hZGt5Dmg5i46DR2pJpAav6aoW/PIB64eSifLtmHxWqj3FDLu1/u5A93jMTf15X1O046tt20K91p3yA/N26aGk+PKL/ztlsQhKtXmwVUxcXFjsdlZQ1zLMrLy53W+fj4NJm6dOPGjeTk5ACtG+732muvcfLkSW677TZGjBiBu7t9THdRURGLFi1yTJiOjY3lvvvuu6jXNH/+fEcyi2nTpjldqLQ3jT6Y4vLH0dS+jl5Xh0Ih88CNJ3j2/cUE+P2hVRmS2ppCoSCg232UnP4PxaU++PvaizNOuyadU9nefPPdMh77w/3cf+s4Xnvfnrlx6dq9zJw4QKSV7QC1dWa0Wu2vk9El6kxmikoM/Lz5CL9sPUp5ZU2jfTzc9EwZG8/0Cf2JDG3+gkKrUTNxtEgacSU7t4feZrPx5ZdfOhUHHjVqFEuXLmXAgAEUFxfzySef8OSTT573uJ0js+qVo67WQMbRlUSE5DuW7U0KJS1ThVar5PApezAlSfD0n24iItT3vMcccE4pQZPJwvH0HI4kZ3H4+BlSTuZgaWI48G+NGhZP/37n/4yoqzyAOx/h5VHOiVNl6Fy90GmbL32i05roEbQVrf9fWzxu377QvXs3nntzCXUmC5XVdXzw3V5umDqE4rLG3+16nYa7bhrDDdOGoLqE7H31Ny7sbega/5a7Ymbcjs6sKghtFlD5+zd9QT9y5Ein5xkZGU2Or68f7hcXF8ewYecfxlZXV8eiRYtYtGgRkiTh4eGBJElOd1Hj4+NZtWoVWu3FDTFzd3d3BGpqtbpNa1hcDFevAZzJv53uAV+iUllRq608/+AJHnt9EU/8+dE2TQnbWlq9D1rf68grXIq7WxU6rQmN2sYNk1L5eGk/liz/idvmzWH5un2knc7HZLbw2XdbeeqPlz6kU2i9+mF53Uc0ZLu87r5/N3shNDg+iunjBzBqSI9WF9kUOgdX14bPAaPR6PgM+62aGnsA7ebWQsXuc5y7XZ8+fZyCqXrx8fFMmjSJ9evXk5CQ0KqASmhbGanriOuehVptTxturFWzZnM41bUWPP2CsNjsNy5HDe7ZqmDqtzQalT05Re9I7sZ+oyY57SyLVyRyNKXxkLt6eQXlLR5XtlmoLfmUEO9NaDX24X1RYdms3BTIomXjWtx3/PhJxLXinuKgvlG8+vdbeOaNJRhrTZRX1vD50u2NttPr1HzyxgNtklAnPT39/BsJgtDldYqUa5WVlaxYsQJofTKKm2++mWeeeYbx48cTHh6OxWKhpqaG4OBgpk+fzqeffsq+ffuuuMnRnkGzSc8Zh81mH+7o6lLLa386zsv/+QKTydIhbfINGkytrQ9nc0McQ8WiQiu4ZnAu2WdOse/AUR65s+HiKyExmdT03GaOJrQlQ5WRoyln+NvL3znNcQIaBVO+3m7cccMovlrwe15/+jbGjYwTwVQXdO68qdzc5t9n9euCg4Mv+LgtZQWsX5ed3fzFtXB5lBRl4ak56BgtAPDzjm7kFNmICA9h95GGfw+3zB7e1CEumE6rZnB8NDPPk3AoONCr2XWWunyk8vlEBfziCKYAcgo9SD8jcbbAyMkz1c3+VBlbLt9wrn5xEbz+9K2OubxyE+ObjbVm1m092upjCoIgtNnVUlMfSq3l4eHhuFvaWn369OFf//rXRZ+zK/MM+wOnc/KICbdn5wrwreS5e49y5Hg6Qwf06pA2hfa4hTPJObgXVxHobx/iOWnEaU5m+bD25438/qG7GDMslh177ZOUP/g6gXdeuPOyFI/s6mrrzCTuO0FeYUWr5iNVVddyNr+U3F8niufkl3I2v4zc/DIqq4zN7lcvJjqQe+Zew9D+3UVa+ytAr169kCQJWZZJTk5uMvix2WycOGF/L/bu3btVx/Xz8yMwMJCCgoLzbwzivd3ObFYLhZnLGRSXi0Jh/z7OK3Ij8YAfFpsVld4Xi9UeUPWNDaN3z7A2Pf+YoT3x9nRtdOMGWs74WVe+ET/d57j6NVwDWCwKEnb3YOv+AMoM8Ogj9xAaEnjJbSwtr+LLZTu466YxvPb3W/jTC181e+2yeEUiN88choteJFESBOH8xO3nFnSWLH+/JUkSrsEvcDb/L4QF2TN09YwqJLt4D9AxAZVSpcY/+i7OnvkfHu4G9Lo6VCqZmyankFc0gM+/XsZd825g94GTWKw2jp04y/a9Jxg7vGPa21k1lzHvmceuw0WvcQRMOecET+cWyrwYY4bEMmJQj0ttutBJuLu7M2TIEPbt28eGDRu48cYbG22zZ88eKirsWdaaGrrXnEmTJrF48WJHMNaU1NRUgCtudEBnd/b0DsIDsvD0MDiWrd4cQ3G5mWuvGcmH3+93LL91zog2P79Wo+alJ+a2OuOnbDNhLX2LMN+DjjpZAKXlbixe25szeVqsuPLoIzfj5+t9SW0zmSws/Wkv3/64C2OtCYvFSr+4iBZvBNtsMk+//gP33XItUeH+ot6UIAgtEgFVCzpTlr/fkhRqJO9XKS3/M57uBk5kxBDX74YObZObRzCVrpM5c9ZIj26ZKBQyIQFVTBqZzbINoezYsZs5Uwax/Gf7F/sn325mxKAYMazsV3Umc6OLEYCyimr+71/fXNQxtRoVHm56ikrtF1nHt77rWNf72seAlofiCF3T7bffzr59+1i8eDHPP/98o2F9b731FmBP/NDaor4Ad911F4sXLyY5OZmNGzcyadIkp/VJSUkkJCQAMGPGjEt8FUJrGWsqsFZtIbRPQ+/hkdQAkk+54uvnSXmN0lFPKTLUj2EDLk9m2PqMn98tT6CkvIb+8bFN97DLVWir/w+fgMKGRTIcTgnnx83RlFVY8Q8K487b5qC7yDnQ9mPKbN97go8WbyK/qCFN+y9bj3LbdSO55+axfL5kW7P7Hztxlsf/aS9m7ePlSlSYP1FhfkSF+xMV7k9kqF+LZUBq68x0i450PM/IzBLZTwXhCiWuZFvQmbL8NUWp9qDK/A9yM1fhG/UwksKeNtZksrBw0UokCR6553o0mvb7MwdHjSX9yEk8iqoJDrR/WY4beoYTp33ZnZTK5EnjcHfVYaiuJbegnFXrDzJ3ZvvW0uqsduxLa3K4zPmo1UpCA70JDfIhNOjc/3vj6+2O2WLhzj8tvOChOELX9fDDD/Of//yHrKwsZs2axVdffUXv3r0xGAy89NJLLF++HIBXXnml0b71Q/VeeOEFR7bUelOmTGHy5Mls2LCBu+++m88//5xJkyYhSRK7du3innvuwWazER0dzb333nvZX6dgd/bkUrqFFKLX2TP4mc0K1iV2o6zSzIP3TeHpN1c6tr1l9vDLWphWq1EzuK99OGHfvo2z+smyzJnUrxjWuyGYMtZqWLExjuOnvSgqNTFixHCmTrrmktp5MiOfhV9u5Giq81y+qDA/fv+7SYQG+VzQzaTS8mpKy6s5eCzTaXmAn4c9yDon2IoI9SPzbBHPvbnUads7/7SQl56YS6/uzdeHEwShaxIBVQs6W5a/pmhcIvGLfsxp2Xuf/MCkgfZeoMVLtdx7++x2a48kSUTG3U76sQI83A24uhhRKGTmTUvhTP4g1q3fxg1TBvPlir0AfL0ikclj++Lp7nKeI1+c2joz+4+dpbS8hoIKqVPXRzqW2vIkfk93Pb17hhH2a9AU8mvQ5O/j0eKFx7lDcc4liu9eufR6PT/++CMTJ07k4MGD9OnTBw8PD6qqqrDZbEiSxCuvvMKUKVMu+Njffvst48ePJykpiSlTpuDi4oJSqXQMjw4JCWHVqlVO6aKFy6c4PxlPXTqB/kWOZVv3R5Kdr2D4sAGcyCxx3Ezx83FnfAeXN5AkCUk7lJRTKfSOOcuZXF+++SmWCoOK4nILN90wiwH94i76+KXlVXz2/VZ+2XrUqZ6eh5ueu2++hlkTBzrmirY070uvUzNiUA+yc0s4k1OCydx00qfC4koKiyvZe/i003KFQsL2m+rJZRXVPPfmUr7+7+/F564gXGFEQHWFWbfpEDOG7mPc8CwADNXbMZmmt2svlUbrgnfYzaRnfkp8r3QUChlfbyOzx2fx5Y/hZGWkERbkxdn8cqqqa/l6eSKP3j25zdvx2/lIP2094QgiOtsdwu17T/Dz5iMtbvOHuydfdK2n+qE40atecywTX+pXtv79+3Ps2DFeffVV1qxZQ05ODr6+vgwbNoy//vWvFzR36ly+vr7s27ePBQsW8N1333Hy5EksFgt9+vThuuuu4/HHH8fX98LTcQsXzmo1U5n/Iz2jClGp7Jnuyiq1bD8Qig0106Zcwx+e/sKx/U3Th6K+hJpKF8tszESWbWhcugEQHj2YpAOZnNl5moREFTISRrOKRx687ZKST/y8+QgLv9pIjbGhbpVSqeC6KYP53Y2jcf/NPKjzzfuq/56w2mzkFZSTebaIzOxi+//PFpOdW4K1mdITvw2m6pVVVLNjX5qo2ycIVxgRUF1hdJafGTssy/F86phsXv1iOY89OK9d2+EX2JP04mvIyTcQ/muByZH9z3LspC/bD1jpGx3M2fxyAFZtOMh1UwYRFtx2F2FVNbU89dr3GKpqnZZ3tjuEsizz3ardfPrdlha3a4uheb99vZ3h9QuXV1BQEAsWLGDBggWt3qc1GVu1Wi1PPvmkqDPVwXJOrcHPsxRf7zLHsnU7Yigqs3HjDdM4mHSGnHz7OlcXLTMnDrjsbbJaa4nyss/5tFieRar6hAC3nWRkx6EM+ytKtb1mZPzgm7BabWw7+DUKScEjv7sJN7dL69V0c9U5BVPDB3bnkTsnEh7S/HdL/c2mHfvSyCsobzKzqlKhICzYh7BgH8YMbZhzaLFYyckvIyO7yBFkZWYXkZNXSkvvojUbDzGoT1SH1I4UBOHyEAFVCzprlr/mmEwWRsSf4tzRX24udQyK3seajTHMnDiwXVMZR/eayvH9GXh5GHB3q0aS4LYZqZzOHkRWTi7x3b1IOlWO1Wrjo28288/5cy/6XEUllaSk55JyMofj6bmkpuc2e+ews9whNJkt/OeTdazfluRY5ufjhslkdUp3LobmCYLwWzWGfFTmAwSHFVD/sX4624ukEz6ER0TQJy6Gx55r6J2aM3lQu6QAt5YuJCbCnumxqvph3HzsPT+hgekcSvqYHgMftw/7kyRUKiX33zMPrUaDqhU9Z1arjZW/2IezXz91SKMyD2OG9qR/7wjKK2p45HcTGdq/W6varNWoL+r7QKVSEhnmR2SYH9AwTPGXrUd584O1ze6XlJrNHX96n2nj+jFv9nCC/L0u+NyCIHQuIqBqQWfO8teUxUt/5rEbG9fzum5CBjc9/jPJaTn86b6p6HWadmmPUqkmOu5WktKKGN7/OEqlDXfXOm6feZr/Lo7GWFeJXgNGE+zcf5LDx7MY0DvyvMetM5lJO53vCKBS0nMpLjWcd79zHU8726EBVUVlDf94ZzlJ58yb6tcrnBcevxGdVt3i3VJBEK5usixTmPktQT6VuLvZAxabDX7eHkNlDdx971SOpmSTespeVkOtVnLDtCGXvV1Way0BXnscz91cG4bRqVRmjqRaMMj7GTx4qGO5q0vr05EnJCaz8Ct7FsnE/WnMmzXcqeSDJEk8+9j1eLjrO7Sm3riRcXzy7ZYWkwyZzBZWbTjImoRDTBjVm1vmjCQ63L8dWykIQlsSAVULOnuWv3OZTBZ6Bm7HzaWu0TqVysaif6Zyx9MSjz6bx3N/vqHdPrjdPPwpdZ9NRnY5MVFnAegXW8C4IX78vMOFnqFqjmWZsdrgzYVrmDauPyFB3o4gQpZlcgvKSDmZS0p6Diknczl1prDZ3qfWWr3hEL7e7twye0S7f/Fm5RTz7BtLyCssdyybem0//vLANMf8ho7uPRMEofMqztmOm7aQ4MCGNOn7j4WQne/ChPHX4unhxverG3pIpoyNx8fL7bK3y1q6EF2gqdHynHwfFq+No6pGTXVSMoMGDbng0RJWq42vl+9wPD+akk1xqYHB/bo5zQvrDMPoWkoEdOP0oWzfk0pahn0ovM0ms3FHMht3JDNyUAy3XTeyzYsuC4Jw+YmAqgVdIctfPXvvVPNZ4ny8qln0zzR+/y/447Of88Qjsxg38uIzKV2I8G5DSNqXhp9PBV6/Fp2cOzWNY+kDycozE+4LmUVQUFzJF0u3A6DTqomJCiQ7t6RVhWt1WjW9uocQ1yOEuJhQukUE8NjzXzR7h9Amy3z2/VZ27k/jyd/PJiK0fSbRHziawT8XrKC6xh74ShI8cOt45s0e3q7DMQVB6JospmpMFQmEBJSh1ZgBMNaq2LQnCpXWgxHDBnA6q9CRdU6S4OZ2KE1hsVQR4pfYaLnZrOLTZb2x2FSUVpiosVixWq2oVK2//LDZZN79fD25BeVOy3MLytl14GSnLBDfUiKgW+eM4GBSJt+t2sWh5IY5z7sOprPrYDr9eoVz63UjGdq/m/heEIQuQgRUV4gZIzOb7J06V5BfJZ/8I5XHXoslwNe9nVpmH4YR2+869h3OZvywA6hUVnRaM4/MS+fFD3oANvzcoficUXu1dWaOnTjb7DEjQn2JiwklrkcIvWNCiQz3Q/mbgLep7E0ebnq8PV3IyikBIPVUHo889Rn33XItN0wf0ugYbWn1hoO8+/l6R/YnnVbNU4/OYbSoAyUIQivlZ3yLq7aWAL9ix7JNe6IorVRxxx1zUCgkfljbMOxuzNDYNk340xTZWom35Q+oNI1HDqjVFiaNzGHRykC6dY/h9nmzLiiYOnw8iw+/TuBkRkGjdb7ebowe0nk/P5tLBCRJEoP7RTO4XzQp6Tl89+NuEvenObY7mprN0dRsYqICuXXOSK4ZHntZv5sEQbh0IqC6Qnj6jCEpJb+JNTKB/kUE+NkDCF+vKhY+c5zNSelA+w0r0OrcCIq6ieMni+gXlwFAVFgpN04s49ufPAnyAoUEMmCyQKURRw0Rd1cdvWJCiIsJoXfPUGK7BTdKf9uU+juE3y1PoKS8hv7xsYwZ2hOVUsn3q3fz5dLtWKw2TGYLH3ydwI59J3jikZmEBrXtXDmrzcaHXyWwfN1+xzI/H3de+r+59IgOatNzCYJw5aosTUYjZxAYUIhSaQ9eCktc2HcshG7dYwkM8KOguILNO4879pk3e/hlbZNsq8Td/CdcXRrP3603qE8O6cWzmDRhXKuL9WadLebjbzez+2B6s9uUlFWRkJjMlLHxF9zuziIuJpQX599E1tlivlu1i007jzuGtKdnFvCv/64kNMibebNGMHlsXzRqcdkmCJ2ReGe2oCtl+dN5DkTnObDJdRariTN5fyMi2D60wGLR0KeXc/KHopJK/H09Lmsb/YN6kFo0haKS7/H3LQdg2jWnOJgygNQMBecWrTdbIasIpk0Ywu9/N6nVX8K/pdWoGdzXHjj27dswL+n260cxYlAMbyxcQ3qm/c7nsRNnefjvn/HAbeOYM3nwRZ/zXNU1dbz87o/sPXzKsaxndBD//L+5+Pm0Xy9hveDg4HY/pyAIl85mM1OVvxwPVyM+XhWO5T9vj8FkVjFrhr1I87Kf9jkuyPvFRRAXE3pZ25V1+ji9gpoueltPpzUxrv9hFIrxrTpmwo5jvP7+GmytSOG/eEUiE0f36dAkFC1p7WduZJgff/vDbO65eSxL1u7h581HqDPZf685+WW888nPfLlsO3NnDGPmxAEoFAoS950gr7BCJC8ShE5ABFQt6GpZ/pqjUGpQB7xFRs6zeLvlUmB8FJ+gaMf6/KJyHnlqEaOH9OCxe6ei016+D+WYuPEc2JvOhOFb0agtqFVW/nDLSZ74d0/qTA0BjFoJUf7QPdK/TQKbpnSLCOC9l+5m8cqdfLNyJ1arjdo6M+99voEde9P4v0dmXFI62/yicp59cymZ2UWOZdcMi+Vvf5h9WX/HLTlw4ECHnFcQhEtTlLUCtdLolIgi5bQv6We8GTd+HCqVksoqIz9tOuxYf+ucEZe9XeHRg9m5dzJD4zZxJteXVZsjkHEObsaPn0Rc796tPuaAPlFoNCpq68zn3TYnv6xT91Jd6GduoL8nf7xnCnfeOIYV6/bx4/qDVFXb6ymWlFXx4eJNfLVsBzZZdvr9dNai9YJwtZDk1lRxvEqd20NVn+Vvx44d59mr85JlG+bas2j0EY5lZouVv/7jK0d63agwP5778w2/1tW4PCrL8ynJfJeRg1Icy3YfjmTB4oAmt/fx8cLf1xt/P2/8/Hzw+/Wxr48XSmXLtUtMJjM/rUvAUFVD77hY4vv2RKNuHMyczMjn9YVrnIIfvU7Dw3dOYOaEARc8Mfh42lmef3sZ5ZUNw2Buv34U99w89rIFiFeqY8eOAdC3b98ObknrTZ06FbVaLQLYSzB48GAqKyvZtm1bRzelQ1nM1RRlr0FpOoqXZwURobn25VaJ9xYPpcYUxH333QPA18sT+XyJ/fcVHe7PR6/ffxmSGsiYak6h1kUhKez3ZGuNBtb8+DmFJTag8fm0Oj333nt/k4mdrL8Ou/5tOY8vlm4n+cRZHrpjAjFRgW38GrqO6po61iQcYtlPeyktbznTsLena5sUrRefuYJw4UQPVQu6Upa/1pAkhVMwBWCoKOIf9+5n0x4fPlqtJ/NsMY8++zl/um/qZbvj5+EVRJnbdZzNKyIs2D6xemj8GebfZQHJRn6xlhUJPtTU2oOl0tJySkvLOXEyw+k4CoWEj7cnfr72QMvfzxt/Xx/8/Lzx8fYkJ7eATz5fiqHK/iV08MgJ3N1ceeCeuUSEO9/F6xEdxPsv38NXy3bw/ard2GQZY62J/3yyjh17TzD/oRmtHhKZkJjMWx+uxWy2AqBSKnj8oRmd9g6qIAidU3nREYxFS1EpbUgKG8EBhY51uw6HUVLuwrxbZgL2+nz1RW8Bbpk94jIEU1Y0NS+gNuVRVDYJz5BbkSSJjIxsCktkmgqmAOpqjZxITXXqpZJlmT2H0vn4my0M7BvJH++Z4rTPnTeORvFrAeCrmauLlltmj+CGqUNYvy2Jz5dsc7pRd66yimre/GAtd9wwmqgwv6v+dycI7UkEVFexmuoyFIZ/0btHLnHd8nFzieM/P7hQW2fmjYVrOJpyhj/eM+WyDE+L6D6Eo/tO4OezFp3WhFIpMyQ+x7F+yuhsPvyhJzsPN187xWaTKS4pp7ikHNKcg62GLxIZdxclKpUCi8VGVXU1n3y+lGf//vtGPVUatYr7bx3HqCE9eGPhGrJzSwHYfzSDB578hEfvmsTksfHNfknJssyXS7fz1fKG1MGe7nr+8fhNxPcKv4DfjiAIVzuLucYRTAEE+BWjVtvn1JjNSnYcDCc0LBJ/f3tNwV+2JjkutP19Pdq8LIZsM+BSOx9PN/tNsDrTNs6m6wnvcT1VRisnz7TcezLUaHU8Tjudx4eLN3Hk+BkAzuaXcv3UIYQFNwyrF1ntnGk0KmZNGkhZRbWjvEhTtuxKYcuuFAL8PBg2oDsjBnZnQJ+oDhtmLghXCxFQtaArJaW4GLVVp+gRYR+Pr1TauOf647i7xPLKl+6YrbBuy1FS03N57i83EBnatkMAJUlBbPx17D2azjVDkvhtjKJRW3lkXhr9Bz+N2aLDUGWkosJAWbmBktIKikvKKK8wNH1w7MGNVqMgxF+H6pzJyharjdwiI0nH0hg8sOniuXExoXzw6n0s+n4by37eiyzbh1288cFatu89wV8fnN6oSGadycybH6xly66GYYwRob7864mbCQn0vojf0OUREtLQM5ebm9uBLREEoSUlOVvsPVOSDR+vMvx8ShzrCooCiAi0MmriZMCeSXTJmoZU6XNnDEWlank49IWQzWfwlJ/Gxa2hZ0SpqmPDtixu8Ctl6OB4hg5u6IFvbshYflE5n32/lU2Jx52Wa9QqMrKLnAKqK0Vbf+aGBLXu+6SwuJI1Gw+xZuMh1GolA3pHMnxgd4YN6N6pvpME4UohAqoWXClJKZrjEziEjLybiApYjkZtQaGQmTs1FVd9D57/xItaE/YhgM98zl/un8aka9p2PLVO74Gfn65RMFVPrbbip1zEvpQQCks1GGqUgIQEBPuqCA/yQ6lQgiRhs4HFasVkslBbZ6K21oynm6rRfCWVUkGIv5Zduw/Sq2c0rq4uTZ5bq1HzyO8mMnpoT978YI2joOSug+kce+Jj/nTvVEYMimHn/jROnyli295U8s4pOjm4XzTP/fl63Fx0l/6LEgThqmMxFeOpMxIZno1a1dC7I8tQW6chKECPXm///Nqx9wR5heWAvczEjAkD2qwdttq9+KvfcvSOAWSeDeTLVT2pM0N+QRHe3i1/NxqqjHzz4y5WrtuP2dLwWhQKiVkTB/K7m8bg7enaZm2+ko0Z2hNvT9cmi9a76DUM7BvFoWNZ1Bgb6lKazVb2HTnNviOngQ1EhPg6gqu+vcJRnxN819aZ2X/sLKXlNRRUSCJ7oCC0kgioWjB//nweeughoCEpxZXGI/hWMvJciPJbjFZrRpJgxrUncdF349kPAymvslBbZ+a191cTHuJLTFSgY5z+9VOHXHKqWr2mrMX1sd1yCPY3YKh2pbjUndwiFwpKNRSWajAaG6fqlQC9BvQtfAGolApqaor4z38/pGdsDOPHjsLPr+nCl/G9wvnwtfv55NvN/Lj+IACGqlpefvdH1Cql08VBvTmTB/Ho3ZM7bRpfQRA6P7XWs1EwBSBJEBl+lirbWMDeG//9qt2O9XOmDGqU4OFiydXLCHL9BoXCnrvKJkPSiQiWbYiitk7GKunx9XUevWC12tiy9zQA3WN6snbTYRYvT8Twa6a6eqOH9OSB28YRHnJ5iw5fabQadZNF68/N8mexWElOy2HPoXT2Hj5F5tlip2OcyS3hTG4JS9buxUWvYXB8NMMHxuDj5cqbH6x1HPenrSdE9kBBaCURULXgSktK0RzP4DlkFuiJ8P4Mvc5+V2vcsNO8rTPz+uKepGVWct2UwcR2D2b9tiQWfpUAgLub/pITLdTUtlyLSamU8faqwNurgvAQ6FWrw1DlRlW1KwUlbhSWaiks1VBYpsFkbvz3USpkQgNqcdVbqapRklOkw2aTcNGpcNFBUV4GP3yfgUKpIjAwkKDAIHx9ffH188PLyxulUolep+Gxe6cyemgsb324lsLiSgBsNivh/kpcdAqqa23klljRauyZAUUwJQjCpQjwMzQKpuqpVVbCI9wxA4eTs0jLsBd116hVXD91SBucXUYyLCDIsyHDosWiZMeBHmzaG0hFlYVuMXHcMGdyo7moCYnJrNyQbD+KpOPH9c5Z13rFhPDwHRPEvNJLUF+0fse+NPIKyhvVoVKplPTvHUH/3hE8dMcE8ovK2XPoFHsPn+LQsSxM5oabkTVGE9v3nmD73hNNnqusoprn3lzaJtkDBeFKJgIqAQDPwMlkF7kSavsfri5GAIb3y+YfWgsrd03lntsmYLXaWLyiIeFCWxRUNKmmYzYfRa1ufOEgyzgNB5QkcNHX4qKvJdC/mKhwBVXVrhiq3DBUu1JnCcBMELUWP7JyLRTln2BM/zJ02obKALV1BnYc8aas0vmLwWa1kJebQ15uQ2IMhUKBt7cPvn5++Pr64efry39fuJ1XF67lzJkcRvbWotM0vPZak41dx+vYsS+NiaObnp/VkUwm55ouJrO5yRTynYnJZCb99FkMVTXUmaVm094LwpXGZjwELdxvUkrFmIHvVjf0Tk29Nr4Nhs6ZUVc9h69nmmNJbZ2GtVviOHzCizKDjZkzpjOwf+O6Ur/9jth35DQ9ogM5mVFAcIAX9986jmtH9BLZ59qAVqNu9fdMkL8X100ZzHVTBlNnMnM4OYu9h0+x59Ap8osqzrt/WUV1p/1eE4TOQgRUgoOH/yhySnQEWd/Bw93e5d8vNg/4BYtpIlsOnCYnv2GIXk5+GV8t38E9N4+96HMGhPRn1+F+jBzgHFSZzUoSD8Uh446vRw7BAWX4eRucAiyl0oanhwFPD3tyitrabAy/Blheaj22MIV9G3cDarUZk1mNZHDnmgHlFJpmkZF5lty8PCTZ2mRtKJvNRklJMSUlzsMluvsqifLSofzNPjqNgpG9teTml1707+NyOZOdyyefL3Va9q/XFjaZQr6zqG9za9LeC8KVxFxXimyqa3Gb01kWaqQCDhy1ZzhVSBI3zxp+yefOydhEn7DTjueGKhe+X9eH09l6bEpXfv/wXHx9vBrtZ7PJrEk45PQdkVtQxu3Xj2LSmL7MnjwIjVpccnQ0rUbN8IExDB8Ywx/vkTmTU8Kew6dYtf5Ai8HVuXOEBUFoTHy6teBKz/LXFA/fQRSWPYO14lW8PQ1YrAostjA0Wh2LVyQiAd1C7P9sTuda+Hp5IgXFFTx02wS8vS78zqhSqSao+4Os2baE6OAs3F2NGKr1ZORF0mfgzXh4BWGqq6GwooDM9Cw0HMHDJZ1AnyJc9CanY+l0deh0dfj7lmKzSdQYdeh1dSiVDX83s0VJVnY4Lsp8esdNQK31IOXEKTYmbKekpASNRoFWrUCrUaBWNdPzJltRKiQkScbdRUatBrMZDDUSOo0CF3Vt0/t1EJPZ7BSY1DNUNZ9CviNZLFaKikv54NPvMRqdf5edtc2C0JbKcn/BRdH8v29DtZq9R1w5frahd+qa4b3aJHubm1c82w/0ZcLwI5SUefH1mjhyi5R079mb2dMnNpk9sKC4gjcXruH4ycZZ7LbuTuGztx4Sw6A7IUmSiAzzIzLMD19vN159b1Wz2wYHerVfwwShCxIBVQuu9Cx/zXHz7kVJxQuYi18lvySM4B5PsGHHcXLyy4gKUvLIDfbikv9b5k9mvpUN246RuO8kd900huumDnbKGNQaHl5BDBv7CMX56RQZK9C7ezKsRwxKpf2CQqN1wTcgGt+AaGAcAEW1BkxFR1HL+3HTnsDbvQClomFon0Ih4+ZqbHQutcpKdGQWeXnrqS3eQkWNFl2tG1NHumKs9eBsgYmiklrqzGAyy9hsErKswMfHCxe9nsrKSsxmMzqNTFSIiaiwEtz0tVTV6Mg860tmnobCs6ms+rGK8IhIIiIi8fHxadchLiazmZKScopLyiguLuP4iVONgql6hqpqFn78LdFRYXh6uOPp4Y6XpxueHu54eLihVLbub2kymUlKPkFJaQW+Pl4tDs2zWm1UVFRSUlZBaWkFpWXllJZV2H9KK6ioNCDL9r+lJIGb/pw6YkYrhqrqFtPeC0JXJtvM2GpT8A0tb3K9oVrN4jXxmCTZqUzDvAvsnbLZzFjKPwFA6XkfSqUWAE/vEAIi5rFpXyCrEirQqNXMmDmDPnE9GrdVllm/LYn/fbHRKavcuXLyy0hITBaFzTu5lrIHenu6MmZozw5olSB0HSKgasHVkOWvOW6e3bBY3sHfS4NNVjh6p+6cWsL0sacAqKhS8PIXXshAjbGOD75O4KdNh/nD3ZMY0q/bBZ1PqVQTGNr6QpRanTta3WhgNBagSDYi1R5AadmNq/o4em158+dSyISF5jmeyzKYzGrMZjUmsxqjUYuhRoehWk9ZpZ6KSj0WWyVQiZ+7hEJS4+1RwrXDjqPXNcxLGthbzebdvdlzzIuzZ7M5ezabXTt34Orq6giuwsLC0elaTqXemuDEZDLbA6aSMoqKyxyPi4tLW6zP1ZTMrBwys3IaLZckcHNz/TXIcsfTww1PT/dzAi93PD3dKSwqsQ8ntNU6Ap8VqzcwY8q1qNRKSksrKCursAdQZRVUVFRis8lNtMSZVqMgNECDt7vk6AUsM8jkFJooKS2/oNcoCF1FeeEOtJpaPD0bhl8l7I4EWaK0Uk/KKT8sViVWtcXxPhrYJ5LY7sEXdJ660m+JDtgAQEHRccps9+PlPwCAwJBeBATHUmk7RN/ePfD0aDyZq6y8mn9/8jO7Dpw877naYr6tcHmdL3ugSEghCC0TAVULrpYsf81RqOzFaxO2JTl6p+aMz3Ssnzn2DF//4ktmfsPcpzO5Jfz91e8ZNaQHj9w5sf0KCEp6ZM0YLJoxVACGyjcJ8NjVul0l0GrMaDW/BkdezuttMphMGmprNVQbtVTV6OgWnt8okYZeZ2bCyOPklwyhtEKNsU7CbIHq6mpSU46TmnIcSZIICAwkItweYPkHBDj9u3LMdTonOFm28hcGDeyDxWJ1BE0VlVUX/iuSGj+XW4hrZBkMhmoMhmrO5uQ3u529gLIWlbIhULRYbaxau546U+uGySoke00apUJCqQSdVkOwn0RkkA2VqqGRgT6g02jw9mw5O6QgdEWyLFNbtouwwDLqp2hm5XqydV+003ZqjZafE7Mcz2+ZM+KCzmOzmQlw+9nxPMAvh+K0xVRpPHHztJ9LkiRGjxjU5P7b9qSy4NN1VBgajwJoiuil6hrqswd+tzyBkvIa+sfHijpUgtBKIqASzmvK2Hgmju7NmWNP4qJv6JFxd6vjwesq6T/yeVZvOMRXy3dQY7TPa9q5/yT7jpzmkTsnct2Uwe3eZpXLEKD5gKrOFoMkySjlApSKloMThQQ6rQmd1oSXZ8vb6rRmRg7I5GRmKNVGLRarRG2dhLEOjHX2xwX5+RTk57Nv3x5kGSw2BSaLRK1JpqamhmA/TaPgZP+Bw60OTiRJwsfbE38/b/x8vfH28mDr9l34ejrfEIgK0VNSKTN18jiqq41UVBqoqDBQXmGgotJAVVV1iwGX/Vz8Gkw5H1ulVBAaoKO0woRCIdmDpV+DJoVCQq1SolJJ9iCviZMolTYig238dvSoSgVRwTIu+lb9KgShSzEa0tCoKvHxbkjskHjQOb24Xq8HfTjGukMAdI8MYHC8c8B1PnWli3ENaBiiJ0kQHZHDzzvWM3L8g83ePDRUGXnv8w0kJCY7Lb9uyiAeuG28o/7VsWPHAOjbt22LwQuXn1ajZnDfMAD69hXDqgWhtURAJbRKWkoSo/pkN1o+89pUFn6/kAmT72DimD58+t0WftmaBNirswcHeLVzS+1MilFYbJ+jUjQe/maxuVPGSyDb5wxgq0NJEUoKUcp5SLZMFLYcVFIRKmUlKqW50TFaEtc9j7jueVh/TYxRXa2nskpPucGF0gpXCktcqKlTOgKsWpMVtVLCVQs+blr0OgvXDj6Lj1ctpeU6tuwPJsRfR06BkfrQQ6FQ4OXpjreXB16e7nh5e+DtaX/s5uaKUqFARkaWwWqxcCpNj2yrY94Nw3FzVVBVbUOrgVB/LXq1DZ2nBk9XT8z+LlgtvlgsFkxmM7W1tdTV1mEymTCZzVgtFqxWKzbZBrLs6PVqKkGHUiHh761t5rcko1TKaFSgUctoVPZ97Y+hpalbKhVUlp0B+l3Q30UQOruK/I0EeZc7EukUl+k5keFL//4D0eq0eHh4EhIawV1/+dCxz7zZIy5ojqbVWkO475om1tg4W+LZ7H77jpzm7Y9+ori04TPV38ed/3tk5gUHdFeT0aNHd3QTBEFoByKgasHVmOWvKTabDUPpcrQaS6N1KqWNP9yyjS17symunclfH5jGrEkDee/zDfh4ujJsQPcOaDGAlnKexVt+BaXUMBfBKntSztOA1mlbK2FYCQMJUP7649ipGkxpSJaTKGyZqEjG2/P885SUChl3VyPurkaCAhqW22wStXUaaow6qqr1VFTpKSpzJb/YBV+PaiaNTnUaTjisXxYrN/ZGpfT9zRnMWOtKKCksoaSw5bYE+pgY1b+Ue68LdaSQLykrZOcRH3btSmx55yZIjv+ATiMTHVpHXLdCR5bGlFMBZORqsNgkNCoZjRrUv/6//nlrRtAqFVbCghsSf5zN98VqUyKyLwtXGrOpDKUtB1+fhrILiYfC8fTyYdToMY6gaeUv+6mssg+1C/TzZNyI1s89tdlq8TA9gsq18XeZi97EnPF1zfZO7TmU7hRMTb6mL4/ePRk315bnhF7tlixZ0tFNEAShHYjLkhZcrVn+fistNZnxQ5qfeKxUykwceZqS8kUs+3E//YfczLv/vLvJrE/b9qRy5HgWd988Fg+3yztuy0IPiuQPKMpehoumFN+AftQyHOdgqhUkV9AORNYOxAocT/qRUX2+Rq1qXIy4Pl27Vmtqcj3YMxC66Otw0dfh59MQ7NWPfPvtzWa12soNk5OJiYjCbNZgsSmxWpTYZAlkkJHs+9Y/PudYsmyfKBURUka3yGynNgUHFuCiD+dEhh82m4RNlrDJNDy2d0Jhtdkf1y+r38Zqs/+/T/cyrhniHAT26ZHFjgNx5Bd7XdjvmvrfgQJvjwrGDnVO/GGsVbNtX2/8Q8UdceHKUpazHi/PSjRq+42rqho1R1IDmTBxuCOYslptLF2717HP3JnDWp3owWqpxLXuL7i7Nz9sOcD9Fypst6NoImX7A7eNZ//RDKqqa/nrA9MZLbK+CYIgOIiAqgVXc5a/c3noD+Du1nKRSQBfryoeuGk3h1Oy2bhhMlOmznZaX1tn5oOvEygsrmTzzhTuu+Vapk/oj/KyJvvQUlBuHxrmGtA24/mjek4mNX07vWKynAIUs0VJanok7hH/QG21INdmo5RPoZKzUCnyUCtL0KorUauaHkLY0qgdlcrGwD6nnZbZbBI2mwKrTWH/v1WJrf6x0zKJQP9ip3pcYE8h3z3qjD0Zh6wASf6156k+Zflvnv/62Pn/NgL9ilEqnedBqdVWxg5LJr/Qp35PGrawP1JIEgqlCqVSiUKpRqlUoVSpUCpVKBQyGo6jUDgfV68zc+2w45Qoopr/ZQlCFyPbLNhqj+EfWuJYtvdoKDq9F926xziWbd2d4ii+6uGmZ9q41g17NZuK8bTMx8O95Z51V5daCgu/Rel5OyazBTeXht4nnVbNP/56I54eLnh7XnjNQUEQhCuZCKhacLVn+aunxI+klKaHlUiSjQC/Yvx9S5Ake+9Lv9g8amyNsz9t3Z1CYXElAJVVRv7z6TpWbzzEH++ZTO8eoaz8ZT8A108d0qnT62q1LtRq7uBg0lKCAyrQ/DqELq/QE4XnXPx19uyIqL2AeKyAFagDqgAs5Sisqb8GW2dQSbmolSVoLrAgsEIho1BYUdF0T1hrqJQ2osIbp0xvC0qFTGhQyfk3vEA6rRkX617qGN/mxxaEjlBRuAMPNwN6nf3GldmsYG9SCCNGj3B878iyzPer9zj2uW7qYEcSiJaYagvxsj2Bh1tDMJVf6E9RiV+T2yefMfP1+kVEhPrx3J+vd5qfFRXuf1GvTxAE4UonAirhvAKjZwGzml1vspg5lvEF3YI24epSy6kzoXSLu6nRdlPGxuPqouWDrxIcd1lPZRXw1xe/Jq5HCCkncwFwd9N3+vS64VEDqauL5dSJzZhqi9Ho/OjWazxarcv5d1Z4YVOMwMYIzu2rMhX+m4iAHc3uZjLrkBQaFFIdCsmEJJ2/llOjUwftdjy25V9YquVOxXQMtCKgEro+WZapKdtFaGTDzYeDKUHIkhc9ejQMqzuYlMmprAIAtBoV17cye+rZrBPU6t0cAdWJU6H8sKEPd9x5Ny7npMu0Wm18++Muvlq+A6vVRubZYjbtPM7E0SLT26UICQlxPM7Nze3AlgiCcDmJgEq4ZCqVGv+oBygwzELK+xK1z00oFA1ZHYw1FRw5sIIKYwiTJk5kaP9uLFmzh29/3EWdyT5foD6YAvhq2Y4uUQRSq3Uhrt/MNjuewvM+zOZdjepbAZjNSgpt76NSetkXyDKSXIeE8defGhRNPZZqUMlp6BTHmj2vyRaGLPkjo8A+PE8BKH59rnQsk39dfu5zyXwCF83pZo9dWdMNixSDbLMhy9Zz/m/FVv9/mwVZtiDbrMg2MzabBVe9gQC/0maPazKrL3gqnCB0RsbKdNz0xbi72YeUyzLsOhzGsGHDUZ6T7vK71Q03Q6aN64+nRytu3gBRPUaTfKgEpWIdeYUubDvcl7vv+R1KpZJlP9nnYw3qG81bH63lxKmGgudajQqTqXEiIkEQBKExEVC1QGT5uzAu7kHg/qTTMlmWyU77nOvGbqWwxIulS4/Sb/D13HnjGCZfE8+HizexbU+q0z55heV8sXQ7991ybXs2v8Op1F7klN1LqMcip6DKbFaSU3kvOm+vc7aWkNEhowNaKJ4sA9ThZ30AlbLxHECL1ZVS6c2GFPIXSFZUo7bci1rV+MLLbFFRrXkRSdH0fAuJhvDtt2oq9mC2vNVkYg+zRUmtbYiIp4QrQkXBBqKCGm4eHD/lR5XRm15xDcOs007ncehYJmCv5TZ35rAWj2k1lyMp9SgUWhQKBb0HzKSibDAVUgV33x2HUqlk/bYkFn6VAIBSqcBqbfh+690jlCd/P4uw4KszEZMgCMKF6txdAB3s7bffJjQ0lNDQUJKSkigvL+/oJnU5JQWpDIrdgyRBoF85D9+8G33d//j2u69xd1XxzGPX4eft1mi/zTuPO33BXy103jMosH1MVsE4coriyCoYR4HtY3TeMy7hqFrKpeexys41ZqyyJ+XS81xKV4+kcKXU/GfMFud7M2aLilLzn5sNps5H6z6IMzk9MVucC1KZLUrO5PRE49b/otssCJ2FxVSOVpGJp2dDts/Eg+EMGToMpdL+nqqtM/PfResd68cMjW2xvl9N6Xo01X8nL+0DZJv9RodSqcbHL5zBA/uiVCqxWm18uXS7Y5/6z1qVUsH9t47jnX/cKYIpQRCECyB6qFogsvxdOhdXN6qNHri52hMuqFQ2hsRn0SOqmNWbMsipjKe4rHEa37zCchISkx1zqbJzS6gxmojtHtyu7e8IKrUXKv8/Ac7lsC5FfQp5aEg3bn9+6f08snY0xbYBqKpXoCAXGyFYtDcgaS8+E5ikUKPx+z1pGV/g7pLnSPxhqAnGI+RupCbSOgtCV1Oau54gnzIUv+Z9yMr1IL/Ej+nX2TOSpp7K5enXf6DS0JDk51ByJqmncunVPaTR8crOfkWPkB9RqWwoJBPpKZ8Q2eeRRtstWbvHMY+1nr+POy8/OY9ukQGNthcEQRBaJgKqFogsf5fOxT0cm7yQ9PyvCPNei05rT8Pg6V7N7bMOcyorn4qSSHYmWXjjz/kA/P61QOosChavSHTMpVr0wza27UllYN8obp09gkHxUU7Zp4TW+G3w1HaD5iSFK1b9nY58g23xl1Hrw/CJfpJTKb+glKoIDovDJ7C3CKaEK4IsW6DuKL7eZY5liYfCGThoMGq1mjqTmefeXOoUTAEYqmp57s2lfP3f36PVqH89lkxZ9vvEhm92lEfw9Kgk9VQxroFF+Pk1ZOezWm18taxx8hu1WklkWNOZ/wRBEISWiQhBuOwkScIt4C6KbO+TW9TNUXRWoZDpEZ3Hsw8d5uPnshkWf5Zh8Wd5/Y/2bFc5+WUkJCZzNq+U7Xvt86wOHcvkb69+xx+e+Zwtu1KwinltVzRJoaZWjqLa1hedR38RTAlXjIqCnfj5NNSHKynXczIzkP797cNZd+xLo6yi6VERZRXV7NiXBoDNZqMs6016RWxyHMtiUfL9T33xDJjkFEwBJCQmO5IBnSu3wD4qQBAEQbhwbRJQGQwGVq1axXPPPcf06dPx8/NDkiQkSSI1NbXFfeu3a+ln6dKlLR5j//793HrrrYSEhKDT6YiIiOCBBx4gPT29LV6e0EbUWl8Uvm+RVf4YVTUNGapc9LXERBQ4no8ZlMvaRX9i47dPMWVsPAqFxPhRvVEoGvo9Tmbk86//ruTexz9kzcZDIhuVIAhdSk3ZDvx8GpJRJB4MJ77fADQae89x1tniFvfPKyjHYjFReeZFekXvdhTBNplVfL6yH37hNzBihHNpBKvVxuIVic0ec/GKxKty7qogCMKlapMhfwkJCdxwww2XdAw/Pz+nFLHn0ul0TS4H+OKLL3jggQewWCxIkoSHhwfZ2dl8+umnfPfdd6xatYoJEyZcVJtElr/LQ+c5HoM8mvLidwjx2YtCIXPu6D2d1kRp6usE9/wnACGB3jz9x+u4d961LF27h583H8VktgdQuQXl/OfTdXyxdDs3TBvCnMmDcHNt/t+LIAhCR6upTMfPKxeN2v45VmNUc+REML+7e4hjm8PHs1o8RrC/nprc54iNPun4/KytU/Pp8v70HXgTsT1jAftwwBOn8+jVPYSExGRy8suaPWb9qIDOXgdQEAShs2mzOVQBAQEMGTKEoUOHEhoa6kjm0Fr79u0jKirqgvY5evQoDz74IBaLhTvuuIN33nkHf39/srKyePDBB9mwYQM33XQTaWlp+PtfeIX3t99+mxdffNHx3MdHZD1qK5KkQeXzN7IMh4l0f8lxd7VeXHQap0tyWbJ8IyOGDaZfv94EB3jx2L1T+d1N17Dyl/38+MsBDNX2ZBdlFdV89v1WTpzK48X5DUWFrVYbW/ba6yTFxfXu9LWtBEG48pXnrycuqqGQ7+4jocT07Oe4eZiw4xjH03Ka3T8yWM+IqK/oHtkQdNUYNXy0ZAAjr7mNyMhIACwWK//++Gc2bj/GP//vJqaMjRfBkiAIwmXQJleXs2fPpqCggLVr1/KPf/yDyZMnt8Vhz+v555/HbDYzZMgQvvjiC0fQFBkZyfLlywkPD6e8vJzXXnvtoo4/f/58cnJyyMnJIT4+Hi8vrzZsvQBQnre8UTAF9l4qb57l3tmJnExew//e/5iU1JMAeHm4cM/NY/nmvUd55HcT8fdxd+x3w7QhTsdJSExm5Qb7j5gfIAhCR7OYKvDUpaHX1dmfWyT2JoUyfPhwAPKLylnwWUOadI3a+b5ndKgLLz5Q4BRMGap1LPx+GNdOvMsRTNUY63j2zSWs35aETZZ5acFKMrOLLvfLEwRBuCq1SQ9Vc0P1Lqfy8nJ++uknAB5//PFGbXBzc+ORRx7hmWee4dtvv+Wtt9664KxwIsvf5VVXW01cdFqz64P8ypEkeOiWMpLTwli5ycCmzV5MnTKJmO6R6HUa5s4YxnVTBrMpMZlDxzLp3zvCsb/VauPr5Q3ZrM7NGni1+tvf/tbRTRCEq1pJznq6BTb0Th08HkxwWB9cXFywWm28+r/V1BjtwVZIoBcLXvwdB49lkVdQTnCgF4Pi/Mg8/jm1dWp0WjNllS58vHQoM2bd7khAUVpexTNvLOFkRr7jPBNG9yE8xLd9X6wgPnMF4SrRZdOm79ixA7PZnoJ7ypQpTW4zdepUnnnmGfLy8khJSaF3797t2UThPErPvE5kL1Oz6+vjX43awsA+mcREFrJ5TzfWrF6GVu/D9GmTiIoMQ61SMvXafky9tp/T/gmJyeQWlDue5+SX8eaHa3n0rkm4u+kvx0vq9P785z93dBME4aoly1Y08n7c3ap/fQ47D4cx6/rRAHz74y6ST5wFQKGQeOqPc3DTKxgc9jWEgWvwc6g1Lij6/I6t+2QiQ9JZs20Qc66/DS8vb8Bes++p1753qjN1101j+N1NY0SpiQ4gPnMF4erQaQKqefPmcfLkSWpqavD392f48OHcd999zJw5s8ntjx8/DkBQUBC+vk3fdTs3gDp+/HirAqrBgwc3uTwlJYWQkBCOHTt23mMIrTWPjUfnNbNOJshtMz3Ddzgmbru71TB7wjEG9/FjZUJ3li1bgkLlysD+vfHz9XLa22qz8dl3mxsddeP2Y2xOTGZAXAjD+4cTE+WHQlxkdGpGo70OT1d67xmNRtRqkeJdcFZesJNAv0LH89QMP1w8euPm5k5Keg5fLtvuWHfXTWOIiwmlKOMl4rufACDp1Nv4Rz+Hp3cIfYfNx2qD2+5QOEZoHE87y7NvLqWyyv6eUSgk/nL/NGZMGNB+L1IQBOEq1GnGPu3btw+r1YparSYnJ4fly5cza9Ys5s2bh8nUuBcjLy8PgJCQxtXi6+n1ese8p/rtha5CIr9qAomp/8eZ/O6O2lWSBKFBxTx0y37umHEGV001+/fvp7auzmnvA8dyKC6rafLIVpvMgeQc3v9mNy+/v4lftqdRVmlscltBEIS2YjFswcuzoedo+4Fwrr12LMZaE6++twqbzf5B1yc2jNuuG4XZVEOPsIa5nz3CkjGb7J9rSpUajUbtCKYS96fxf//61hFM6bRq/jl/rgimBEEQ2kGH91Ddfffd3HbbbQwfPtwR/KSmpvLGG2+waNEilixZgpeXFx999JHTftXV9iETen3LQ7dcXFwoLy+nqqqqVe05cOBAk8sHDx5MZWUlffv2bdVxhLY0jPzaY7ha38HDzZ7yV62yMqB3FjGRhaxIGMCggQMdc9ysVhtvfrqjpQM6lJTX8PO2E6zbfoI3nr6NgX2jLteL6BQWLFjgeNxVhqLU90x1pffe+T6XhKuPsfIUgb5nqC+nl1PggUmOw9PTi7c+XOsYnuyi1/LUo7NRKhWUZ71GeEzDDUWd1kT5yTfx7/6C07HXJBziv5/+gu3XO0+e7npefnIevWKav+EotI+u+JkrCMKF6/CA6vPPP2+0rFevXnz22Wf4+fnx5ptv8sknnzB//nxiY2Pbv4FCpyBp+1LDJ1RVfIeffiUajX3+nEppI7bXIKeEIQmJydRWlaFRgckCvr8mASwxNBxvYN8o0jPyHWnXXV109OkZ5nROWZavuDkHr7/+uuOx+HIXhPZTUfAzETENNaC27gtnwvgJbNuTyrotRx3L/3zfFIL8vag1GugZmdLoOD0iUigy1aDWNBRH12nUjmAqJNCLV/9+C6FBosxHZyA+cwXh6tDhAVVLXnjhBd577z2MRiNr1qxxCqhcXV2BhvkVzampsQ+PcHNzu3wNFdqJhML9Nkpss1GUvYm/5zFySwYSETPRaate0d4M7qmlptaKr08gpWUFAEyfNoVhQ/o7tjOZLOzYd4J1W44SEeqLRuP8dth35DRfLt3OtHH9GTcqDjcXUTBYEIQLZzFX4u+ZjFJpLw5fYdBRUBGHFRXvfPyzY7vxo3ozcYy9J9Zc/DzqSGujY+m0Jsp/nUtVb9I1fSkpq2LrnhRefnIe3p6ul/kVCYIgCOfq1AGVq6srffv2Zd++fZw+fdppXf3cqdzc3Gb3NxqNlJeXAxAcHHzZ2im0L0nhhuz5IoWWHLT+7k7rykuz8VO8zIRh/uw95ofZUoq/txaAzVu2M3hgvCNtukajYsLoPkwY3ccxd+Fc67YcJfVUHqmn8lj41UbGDu/FtHH96RcXjiRJWK02Vv6yH4Drpw65qtOxC4LQvJKz64iLaEiVvnVfGOOuncAbC9c4eskD/Dz4831TASgtSiY2/Eyzx+sRltyol2re7OHcMH1Io7pVgiAIwuXXZT956zP25efnU1JS0mSmv/pMgOdufyEMBgMGg32cmNlsxmazXWRrhctCFcq51cdsNhs1RZ/TK66QbuGFDO7jzapN3Rje355Va+n6CL7+7kfuuGUOKpVz3TKFwnloX22dmf1HG4L4OpOFDduPsWH7MUKDvJl6bT90WjULv0oAwN1Nz5Sx8ZfndQqC0GXJshVPTaIjW2ltnYr0nDgyq7I4lGwvzquQJJ56dA5urjqsVgv+qrdRNlHwvJ5Oa6I07S0CY553LJMkSQRTgiAIHaRTf/pWV1c7JqRHR0c7rRszZgxqtRqz2czGjRu55ZZbGu2/fr292nxISAhxcXEXfP63336bF1980fHcx0eMSe/Mao1lxEU3BNHBAWU8OO8gil8vTIy1apZtkHjznY+54bop9OrZrdlj6bRqvlrwezYlJvPz5qOcPtOQ6jgnv4zPvt/qtP3Xy0XRYEEQGisv2EmUX5Hj+Z4joUTFDOSf7/7iWHbrdSOJ7xUOQFHW58RHVzrWHT0RxNL1vRodN9/gyrOPWxoNVRYEQRDaX4de/cly83fgAF566SWMRiOSJDFjxgyndZ6eno5l//73vxv1HlVXV/PBBx8AcNttt11UcoH58+eTk5NDTk4O8fHxjiyEQufk4upLmfwi5ZX+jmWKc+7yDu57Bg83GTddHd//sIxPPl/SKN36uTzdXbhh2lA+fO0+/veve5g1aSAuem2T2+YWlJGQmNzkOkEQrl6KunXo9fZhfVarxP7UnnyyZC8Wq/07K7Z7MHfdNAaAytI0YoK3OOZaVdVoScqcQWD0CGS3ODYcsrJ8RzXLd1SzO6mIpNTsjnlRgiAIgpM2C6iKi4sdP2VlDZmMysvLndadG/jMmzePZ555hv379zvVmjpx4gQPPvigIzvO3Xff3eSQvRdffBG1Ws3evXu55557KC4uBuDMmTPceOONnDlzBi8vL/72t79d1Gtyd3cnJCSEkJAQ1Gq1UyY5oXNSaHtSrV/Iio29MZmdh/Vp1BaevH8vo/sX4e+tpq66AJVS2cyRGkiSRGz3YP5y/zR+WPgYTz4ys8m7wotXJGL99SLJZLKc94aBIAhXthpDBsH+DXOhktICKazy40yOfT6VTqvmqUftQ5BtNiuy4WPcXO2JlGQZlm3sj1kdxsKvElixbr9jvlV9janB/aIbn1QQBEFod202VsDf37/J5SNHjnR6npGRQVRUFABFRUUsXbqUV155BaVSiaenJ3V1dY4aUwBz58519DT9Vv/+/fn444954IEH+Oqrr/j666/x8PCgosJeONHV1ZVly5Y12zbhynTgUBL7j3kz/RoF4JwlS6c1M2PccYb1d2fdnutRqS7sLaDTqkGSMJksjdbl5Nt7qaaMjeeLpdvZfTCdWZMGMnlsX5EhUBCuQrXFy/Hobv8+k2XYvK8ba7emO9Y/evdkwoLtQ8kL89LQ2mod6/Ynh9Fv8D089o/vnY7p4abjlb/dImpMCYIgdCId2uXy9NNP89hjjzF06FACAgKorq7GZrMRHR3Nbbfdxi+//MKSJUvQapseZgX23qtdu3Yxb948AgMDMRqNhIeHc99993H48GEmTJjQjq9I6Aw83DTMujYPndbc7DYWi4bRY8Y5LbNarXy7ZC25eYVN74S9aPDiFYnNrl+8IhGj0cS6LUfIyinmf19s4NY/vMe/P/6Zkxn5F/xaBEHomixmA0E+DcOAM3N82Hq4oUd8zNCeTBvXz/E8MKQXRtVDbN7bj/QzvmRXzGXVpmTKK2ucjnvLnJEimBIEQehk2qyH6mKGN02ZMoUpU6Zc8rmHDBnC999/f/4NL5DI8tc19egRja/tbLPrZRlq5OtwcfF2LDObjOzevZbC3Gw++SyF3r37Mn3qtbi66J32TUhMJie/7LeHdMjJL+OHNXswmRt6xmrrzPy06TA/bTpMr5gQ5kwexLgRcWIyuSBcwSryfyQkotzxfO22cNJz7D1Qvt5u/PXB6U5zeyVJIiQ8Hl//KFRqF4KsJbzw7meNjvvTpsPMnTFMJMARBEHoRMQVXQtElr+uyVq6EF2gqdn1kgQqOc1pWV7WRm4c+y2j47xYs7U7p7NSeWdBKuPHjWXk8AGO+XNTxsa3Kj36zbOGsXFHMqs3HCQjuyHDV2p6LqnpuSz8aiPTru3HrEkDCQ0S/64E4UoiyzZ89dupr8ZQXOrGz7v01A9BfvL3s/B0t9eQqjMcQ6WPQKnyAECrc6e8soYnXv62yRuV5w4tFgRBEDoHEVC1YP78+Tz00EMATJs2zWlul9B5afz/Sr7tr47n9an3+/bte842DdvX1VUT4PoTSoVMSGAZD968nzO5fqzd2o1dO7eye+8BbpgzjW7R4a1ug4tey5zJg5g9aSDJaTms2nCA7XtOYLbYL6gMVbUsWbuXA0mZfPT6/U77Xs6CwS0VwhYEoW1UFm4lJqChkO8vO8PIKrS/92+eOYzB8fZkEjUVKbhZF1CQF4BrwFxcvAbalxvrqDY2n4F08QpRpqGrEJ+5gnB1EAFVC9zd3XF3dwcQWf6uYBIyHh4NwzklCSJDi3nk1hIyzvqzeksU333/A6Hh0Vw3azJenu6tP7Yk0Tc2jL6xYZTfVcO6LUdYs/EQ+UX2xCkzJw5otM+G7cdEwWBB6ML08ipH6vPqGi3LNnkCNrpHBnDvLdcCYLXU4WL+DwEBJXh7lZN6ajEmORIvbx+OnTiLxWJt9viil0oQBKFzEQGVcNXTaN2o1bzPmZIleGt/wt2tCrDXsOoeUcif7iwiLSOQ1VutvPd+JqNHjmL8uBFYrTZ27LT3JI0Zdf6eJC8PF26dM5KbZw1n/5HTrNtylElj+jptY7FYWfDpOsdzUTBYELqWGsMpwvwaeiV2HAwlLceGRq3iqUfnoFHbv3YNue8SG2kfDqxWWckvkegeas8GWj+0WJbli6qhKAiCILQvEVAJAiBJSjTet1Jlu5HSwq/xdduEm4s9u5ZCIdOrez49ogo5djKYX3Z7ACM4cPAQ3qrvADhwUMmwoYNbdS6lQsHwgTEMHxjTaN3Xy3c4hgWCvWDwgs9+4bF7p6BWnb9mliAIHUuu/BKNpz3DqMms5Is1foDMw3dOICrcPtbYULKP6JB91MdKBcUe1ChuwcXFxelYIpgSBEHoGkRA1QKR5e/qIyk0aP3uo9J6CyUFi/D32ImL3p6ZS6m00TOqmCq5N1arDalmKVPGZwKwevNSrNaBl9STZLXa+HHDwUbLf9p0mF0H0rhuyhBmTxqIp4dLE3u3zs033+x4vGTJkos+jiAIjVnMVQT7nXQ8P3oiiGOZMsMGdGfO5EEAWC1GvBQfotXYgy6LRcF3G4bzzfpt/L5G45RKXej6xGeuIFwdREDVApHl7+qlULqi9f8jZeY7KSr4iADPQ+h1dZw+G0F0jxHsP3CICcMzHduPH57JVz+t57qZU1EoLu6uckJiMoaq2ibXlVXU8PmSbXyzcieTx/blxulDiQz1u+BzJCY2X0NLEIRLYyz+ApdQ+3vYZpP4eHkQHu4uPPHwTEdvU3X+O4RGlDr2+SUxhhVbTVTX1PHWh2upqqll7oxhHdJ+oe2Jz1xBuDqIiRktmD9/Pjk5OeTk5BAfH4+Xl1dHN0loZ0q1F1r/JymW3+FMwUg8gh9FlkGqWYqbS0MWLjeXOiI9N/Hmv//H1h17qa1tPkNXU85XMLieyWxhbcJh7v+/jx2ZAAVB6FhWcyl1xQsI99vuWHY62489KQr+7+GZeHu5AmAoTiQ6+LBjm7P5Xnz1SwTFZfbhxe6uOkY0MRRYEARB6NxED1ULRJY/oZ5aGwT+TwCwd98Bp96petPGnsJiU7HrwA527EikV684rr1mOH6+3o22/a3zFQwGCPTzpKC4wvF8SL/oC3sRgiC0udqynwj1WIQ6oGHuoyzDkTR3Zk4axIhB9gDJYq7GV/0parUFsM+v+t/3fTh2yv6eVioVvPD4jYQFi5EQgiAIXY0IqAThAtTPnTq3d6qeQiEzZ0Iqowe58fP2GFJOp/LRx8kEBIZy7TUjiOke2ewk89YUDJZlmaMp2Sz7eS+yDGHBvk7ry8qrWb3xILMnD8Lb0/XiX6QgCK1iMZfbgym1c4pzSYI547IYWNuQqKamYCFhEeWO5z9u6sGanQ0FyP9y/zQG9I687G0WBEEQ2p4IqAThAhw4eKjJ3qlz+XpVcefsw+QWeLNqcww5hQWsWLEclcadx/5wD2q1+qLOLUkS/XtH0L93BFZr4wQpqzYe5KtlO/h21S4mjbHPs4oO92/iSIIgtIW6ks9QhzRdL0qttiIXfQmuj1NtKEHJKce609m+LPjeAxkZgHmzhjN9fP92abMgCILQ9kRA1QKR5U/4rUi/nU32TjUlJLCMh+btJ/NsAKs2R1NaWYssy23Sjt9mEzSZLKz+NUOg2Wzl581H+HnzEQbHR3HTjGEM6detzc4tCIKduTarVev1rl5k5d1J0eHVxEZn8/LH0ZRX29+Po4b04P7bxl3upgqCIAiXkQioWiCy/Am/5ekzhqSU/GbXazV1BPoX4+lRCdiHAXaLKODRO4pZtW0mGo3GaftDR47j4+1JZEToJbVLqVTw6N2TWfrTXk6cynMsP5CUyYGkTCJCfekVE3JJ5xAEwVlRqZ5e3Vpe7xUFCoWS6J6jOXUqgLtfWEVGnn2oX/fIQJ56dA5KMT9XEAShSxMBVQvmz5/PQw89BMC0adOorq7u4BYJHU3nORCd58AWt6mRbVSULMFXvxrXX4sDV1R60KffVKftTGYzGzduwGKx4OLmzTWjR9A/PhabTWb16rUAzJ49E7X6/G9TpVLB+FG9GTcyjuS0HJb9tJfEfWnYfu2VOpNTwpmcEqd9rFbbJdXNEoSr3Z6UPowedBKFonHvr9msJCWrG90H1KFQaAE4U2Amq9CCDPh6ufGvJ+ai12ka7SsIgiB0LSKgaoHI8idcDElSoPG+hUr5JspKFuHruoUq23V4+QQ7trFYTBzdvxgPFxtWmxqoYlPCL6z7JQF/Py/MtfaMfxsTNjN92uQLOLdE39gw+saGkVdYzop1+1m35Qg1RlOjbRMSk8+bCEMQhOZNH2tpNphavbkn00cepTDtDXzC70Dj2o3xo3rj6eHC6++v5p/z5+Lv69EBrRYEQRDamogQBOEykSQVKu8HKVd/gdZrutO6/DPbmTZiLX+56xCjBxSiUNhw0SnxcpMxGRuKfqafTMFstlzU+YMDvPjDXZP4asHv8XDXN1q/eEWiI7lFYUklFkvTk+sFQWhMls1E+CY4nlcYXEg5FULigW68+vFQ+veqJjwkl17dkzHkfkBNTRUAg/pG8dV/fk9s9+DmDi0IgiB0MSKgEoTLTJJUSIqGzH6muhp8tMtRKW14ulcxZcxx/njbUQbHlaFQ2FApbdw46RQ3TjqFRmVl6fIfL+n8ew6dotJgbLQ8J7+MhMRkAF7+70ru+NP7LF6RSHllzSWdTxCuBpW5/8Pdzf5esdngk2W9+WLNALYcHc5Ns8KJDssGQKc1UWupwXhOL7FGIwaHCIIgXEnEp3oLRJY/4XJQqdToPTyR5TwkyV6zxs+nnNkTKhgW70tppZY+PXIAMNaqWbNNwY6d+xgzaugFn8tqtbF4RaLjee9rH3Nav3hFImFBPiSn2c+36IdtfL0ikQmj+nDDtCHERAVewisVhCuT1VJFhP8ex/OMswFMm/1HfL09MNcV4iP/1TEU0FCtY+vRa7n9FpHU6GqUm5vb0U0QBKEdiB6qFrz99tuEhoYSGhpKUlIS5eXlHd0k4QqgUKqxur9CQd0rVFQFNSxXyAQHFtM7JsexbGDvs2hUNs5kpV/UuRISk8nJL2t2fU5+GZt3HcfHq6EQsNls5ZetR3nkqc94/MWv2b73RJN1rwThalWT/yZ6nb18gtWqYOX2Ifh6eyDLNqTKl3F1sfcI22wSH/7Qgx+35HI6q7AjmywIgiBcRqKHqgUiy59wWWl6YdS8T61xJ258hKvenmpdkho20WlNTL8mmx83KzGbLa3K+HeuKWPjW5V44qE7JrBtdwrL1+13Srt+NDWbo6nZBPh5cN2UwcwY3x93t8bzsQThamGpKyQyOMXx/NjJYK6bPQ/D2adw0VQSEnhO2YJjofywWYenpwZfb7eOaK4gCILQDkQPVQvc3d0JCQkhJCREZPkTLhtZO4ofNt/O6k09aKr2br/YHDQqKxsTNjuWrU/YQUbm2TZrg1qlZOKYvrz30t3898XfMX5knFNK9cLiSj7+ZjOLftjWZucUhK7IVPI6GrU9UYzJrGJr0njMJe/SI+IEoUF5KH69IVJe6cK/PglGUmr515M34+nh0oGtFgRBEC4n0UMlCJ3A9GlTMBUlI0knG63Tac3cOxc0/vb06cdT0zl6eB+7du1iwIBBzJh6bat7rgYPHux4fODAgUbrJUmid88wevcM4+FSA6s2HGTNxkNUVtmHMF03ZXCjfcA+V2vlL/sBuH7qEFHfSrgi1VWlERGc5Xi+NymM62dNJUDxg9N2Vhu8+00MWcXwryevJzLUr72bKnQS5/vMFQThyiACqhaIpBRCe7Faawnw2tPs+gCvPZRYa6k11pB2bBmuei0uOi0nTxzl3yfSuW3ebCLCQ857nry8vPNuU8/Px537brmWO24YxabE46RnFhAZ5nxhWFFZw//96xu6RfqTsOM4AO5uelHfSrgiKar/g8rD/j1grNVwquQ6fPP/gy7auc5bboE3a3Zq+cPdUxnSr1tHNFXoJC7kM1cQhK5LBFQtePvtt3nxxRcdz318RJYm4fKwli5EF9i4+G49ndaEpWAhJcUKHpq7l5x8f1YkdKe4XIvVVsunixYzfPgwpkwcg0qlbNO2aTVqpo/v3+S6tZsOk5FdREZ2kWPZl0u3M3F0H9FLJVxRasp2EhVY4Hi+eW8UE8cOxY+Fjbb196lm+vj+zJk8qD2bKAiCIHQQccXTgvnz55OTk0NOTg7x8fF4eXl1dJOEK5TG/6/k25a3+FNumkDfbrtRKGTCQwp5eN4BpozMQaWUCfTVknTkAO+8t4ic3ILzn7ANyLLMpp3HGy3PL6rgmTd+oKSsql3aIQiXmyzLuMqfOVKhV1a5YHO7G0PuO+i0jW+E6LQm5o072N7NFARBEDqICKhaIJJSCJ2Jf4AfVrkhw55Wa2LMkJP88bajhAdW4+6qQiNVsfCjL1m/cQdWq/WytkeSJP7zwp1NTrbffzSDO/70P977fD1FJZWXtR2CcLkZin4kwLfU8fynHd0Z0CeS6JCkZvfpFnIMi1kUyRYEQbgaiAhBELoIhTqUat0n5FXMxGJteOv6+5Zz740HuWFiBlqNTIi/ln379rBi1frL3qadB05SUdn0RaPFYmPlLwe46y8fsODTdVRV11729ghCW5NlK/76FY5yBsWlHkT1eqTZ3ql6Oq0JQ+477dRKQRAEoSOJOVSC0KUokNzvp8gyE231y/h42IsAq1RWBvbOont4EWu29iQ1w4tAv8tb98ZqtbF4ReJ5tzNbrOw6mM7v75p0WdsjCJdD+dnPiIu0JyeSZfhxa29mXhfM3n3TOXTMxO4kNUVlTc9bvHXuTIZHtmdrBUEQhI4gAqoWiCx/QmclqYIwub1LTuVq/HSL0Wrsd8o93Gu4dcYR9h/rTkivPzjtY7W27b/fhMRkcvLLWtwmONCLvIJybpk9As1vUrtbbTaUYhit0InJtlrC/bY4np/N92HEtY8A4KPbzrXXZjKkjx9rE935dI220f7TjVKjZYIgCMKVRwRULRBZ/oTOTuk2m1LbBBSlrxDgneIYluTh3R+Vyvnt/fW3P7bpuaeMjT9venRZljl4LJO+sWGN1j3/1lI83PTcccMowoJ927RtgtAWyrLfITjaXoPNZpNYu3MI19/ggc1WR3y3A3i6V+HpYaCiuhvzbn1eZLYUBEG4SolP/xaILH9CVyApXJG9Xia36gmqa9woLI3GM+QWp22yzpyltPC007K27rFqsm2SxOD4aLQatdPylPQc9hw6xYbtx7hv/se88t6PZOUUX/b2CEJrWc3ldAs54nienhXAtBn3A1BdsAhPd3sWS1mGwyfDRDAlCIJwFRPfAC0QWf6ErkTpOpJK7afYPJ5Dkhp6p8wmI+rqt3ng5jSn7T9e9ANGY8ckithz6JTjsU2W2ZR4nAee+Jh//XelU00rQegoVbmvO5JOWKwKtiaNR6dVY7MaCfJsmDuYnedLNQM7qpmCIAhCJyCG/AnCFUSS1EgqT6dlOaeXMywuC4UCBvVzBaCuzkZZcTYvv/kBs6aNZ9iQfigU7Tff456bxzK0fze+Xp7IviP2njNZhi27UtiyK4VrhsVy542jiQrzZ8te+/q4uN6iF0BoF6aabLqFNQT9SSdCmDnjZgCq8j8jJLwasP+b/WRFGJOnxXZIOwVBEITOQQRUgnAFs1hMRPhtpb5zdf/6hjlPP28rZl1iAD8s/4nE3Qe5cc5koqMaz3W6XPr0DOPVv99CanouX69IZPfBdMe67XtPsH3vCWKiAknPtBcq7hkTfd45W4LQFixlb6IOtwBgMqlIzb+e4F4SNks1wd67HNtl5viRZ+hJj+igjmqq0Mnl5uZ2dBMEQWgH4nZvCwwGA7m5ueTm5oosf0KXJEkqPlvRE4ul8Vt9yuhTRARZiAzWU1xcyH8XfsXX362irq752jqXQ6+YEP71xM28//I9jBrSw2ldfTAFsHhFYrvM+xKubtXlh4kMabgI3n00gvHjJgBQlf8x7m72ums2GT5eFsK9t07skHYKgiAInYcIqFrw9ttvExoaSmhoKElJSZSXl3d0kwThghw4lMTA2CJUqsaBiFJp47E79zOodzlhAVp8vdQUF5eiVqubONLl17NbMP+cP5cPXr2Pa4Y1HkKVk19GQmJyB7RMuFrIsozWtBCl0v5+qTFqqVbeBYDVUkGI7z7HthnZ/pSaetMtIqBD2ioIgiB0HiKgaoHI8id0dR6uEtcOO9Pseo3ayk2TjzJ3ciZ+Xkp6xQS161yqpsREBfLsn64nwNej0TrRSyVcThWFGwgJaMg2uXlfNwb27wdAdf7HuLk2pFD/cGkI994yoUPaKQiCIHQuYg5VC9zd3XF3dwcQWf6ELik68ChuLnWO5x991TCE7qHfBQKgUED/uDP4eNVg8XjQaX+r1caKVesZM2oIQYF+7dNo7EWDC0sqGy2v76USc6mEtibLVnw136FQyABUVLriG1FfHFvG1+OYY9vT2X5U0YfIsPZ7TwhdU0xMjONxenp6C1sKgtCViYBKEK5gsrIPSSkpjuePPLHb8fjakaOICM1Br69FlsFojsVD7+a0/+69h0ncfYhdew8zeuRgpk0ag4uL/rK22Wq1sXhFYrPrF69IZOLoPiLjn9CmSrK/oU9kueP5L7tiGTs5FACLxUzS8e7063kaP59KFv4Qwj23ju+glgpdSU1NTUc3QRCEdtAmVyQGg4FVq1bx3HPPMX36dPz8/JAkCUmSSE1NbXa/2tpali1bxgMPPEC/fv1wc3NDq9USERHBLbfcwpYtW1o877hx4xznae7nj3/8Y1u8REHoknSeA/GPfdnxcy7Pbm9Srv6IkopuFJRE4Bb8qNN6s9lEYuJ2PN1U2Gwy2xP388qbH7Jz96HLmqAlITGZnPyyZteLuVRCW5NtJsJ8NiD9Otq1sMST+KF/cqxXqTR8s7kbz38Qx8Lv+mPW9CMi1LeDWisIgiB0Nm3SQ5WQkMANN9xwwfvNnj2bjRs3Op5rtVrUajXZ2dlkZ2fzww8/8Oc//5n//Oc/LR7Hw8MDvb7pu+YeHo3nYbSWwWDAYDAAiCx/whVJUrhhdn8Lm9WIQqlzLLdZLaQffZe+3c1k5upx1SspKDVRXWNkyYp17NxziBtmT6J7t4g2b9OUsfFOQ/qOHbMPterbt2+bn0sQAAoz/0f/mCrAXlvqlz0DmTyt4btDlmWmTxjMl0tr2LW6hM/eurajmioIgiB0Qm02ZiYgIIAZM2bwwgsv8NFHH7VqH7PZTI8ePXjjjTdISUmhtraWqqoq0tPTuflmexHFBQsW8P7777d4nAULFpCfn9/kzyuvvHLRr0lk+ROuFgql8w2JnIyfGTNgN3fMOsyEYUV4uimICnHBzUVpX59bwHsfLuaLxSspK6vAarWxdftetm7fK5JGdCL5+fn8+c9/pnv37uh0OgIDA5k9ezYJCQltdg6r1cqQIUMcowL+8Y9/tNmx24PVYiAmpCF7X3aeL9eMfxgAc20B1aU7AStjh/fio9cfYMGLvyMs2KeDWisIgiB0Rm3SQzV79myuv/56x/PMzMxW7ffKK68wfPhwlEql0/Lu3bvz/fffU1JSwqZNm3jrrbf4wx/+0MxRLp/58+fz0EMPATBt2jSqq6vbvQ2C0N5sVhM9g5ejVlsBK2OHphAWGMLabVEoJB3VRiv5JbXYbHD4aArJKSfp3SuGI0n24b0uLnqGDhZJIzra0aNHmTBhAiUlJYC9t764uJg1a9awdu1aXnnlFf7+979f8nneffddDhw4cMnH6SilWW8R2qMWsGfv23L0GqZM0QJQU/gJrtocCk9swjP0ZnTuscTFhHZkcwVBEIROqE16qH4bELXWqFGjmt1XkiTuuste/yMjI4PS0tKLbt/Fcnd3JyQkhJCQEJHlT7hqKJQazOobsFrt/94VCpmYqBx+NyeJ+Jgq3F0UxIR74KKzv3fNZgtp6ZmO/dcniNTmHc1oNDJnzhxKSkoYOHAgx44do6KigrKyMubPn48syzz99NOsX7/+ks5z9uxZnnvuOSIjIwkMDGyj1refOmMePSMa5vmmZQYyceKd9nU12UQEHSMsOJ+4mCROp2/tqGYKgiAInVynjhB8fRsm/Vqt1g5siSBcXSyaOZTIb1Nr8nQs8/GqZM6Eo0wbXYCL1kxogI6oME/0Oi1GYy1e7iq83FUUl5Rx8LBIGtGRPvzwQ7KysnBzc2P16tX06dMHsPdSvfXWW1x//fXIssxTTz11Sed57LHHqKqq4r///S86ne78O3QyxoK30GrNAFgsCpKyZzqyR5pKPkSvs5ccUCqtVNSEdVg7BUEQhM6tUwdUW7fa7wgGBgbi59d8vY+33nqLkJAQNBoN/v7+TJw4kYULF1JbW9teTRWEK45NEUm56gMq6wY7lmm1Job1P8G8qelEBteiVpjx81Lj7qrC31uLv7cWd1cV6xN2UFdn6sDWX90WL14MwO23305oaOMhak888QQABw8e5MSJExd1jlWrVrFy5UpmzZrFnDlzLr6xHaSqPJnuEQ1Fr4+cCOOaa2YCUFedQXhQQ82g4+mB+AYPaO8mCoIgCF1Ep61DlZOTwwcffADAPffcg1Sfz7YJycnJaLVaXF1dKS4uZtOmTWzatImFCxeyZs0aIiJan4ls8ODBTS5PSUkhJCTEkXFM6DqMRiOA+Nv9Rut/H9cR7BVKr7A1KBU2FAqZ6IhcbvCoZuu+bixPUBEaoMPbwz7Mz2RWkZVXzstvLmT21DHo9dpLamdX/PsZjUbUanWHnNtgMDjmNE2dOrXJbUaMGIGnpycVFRUkJCQQGxt7Qeeorq7mj3/8I3q9nnffffeS29zeZFlGWf0+ah/7yIc6k5oi0x3Uh56m0o/QRdpvCFisCt79PpjHfu/WzNEEQRCEq12n7KGyWCzccccdVFVVERER0eywlHHjxvHll1+Sl5eH0WikrKyMgoICXnnlFbRaLUlJScyYMQOTSdwpF4RLkVc+hD0n/0C18dwhgBVEhpSi1ykJ9JGZPuY008ecJtBHxt1VhcFQw8qftlFSWtGBLb/6pKSkIMsygGOo328pFApHEHX8+PELPsdzzz1HdnY2Tz/9NFFRURfd1o5Smr+ViJACx/PdR6IY0H8oAEZDGuFBGY51x9KC8Q8dir/vxZfgEARBEK5snbKH6rHHHmPr1q1oNBq++eYbPD09m9yuqfS8AQEBPPXUU/Tr149Zs2aRnJzM559/7sjWdz7NZasaPHgwlZWVohZOFyTqGDXtYn4fBkYjW/6Lm2oXxaU+fPCDHz6easYNPUuv7mcBMNaqKSoPw1Btoaamlp827OLOW+cQ36fnRbWzK/79mquL1x7y8vIcj0NCQprdrn7dudu3xqFDh/jvf/9Lz549efLJJy+ukedoz1EBNmsd5uoUhsRuQam096hW1+jIq5yM+dgxQCbC/XN00b/2TlkUvPt9EDMm+3apHtKO1hV7ldtDV/l9dMW/X0eOChAE6IQ9VE8//TQffPABSqWSxYsXM3r06Is6zsyZMxk7diwAq1evbssmCkKXlZub6/i5OFqqFE9QZp1Pre55br/lRgJ9ZOJichxbxMXk4O8lExGkR6EAk8nMoq+WsXHzLkfPiXD5nFveoaXAzsXFBYCqqqpWH9tms/Hwww9jtVp577330Gg0F9/QdmaqPoOvcjkDY3bg79eQNXb30Uj8/IMAUNnOEhl61rHu6IlgtG7d8XTvegk3hM5h/fr1jh9BEK5cnaqH6uWXX+bVV19FkiQ+/vhj5s6de0nHGz58ONu2beP06dNt1EJBEADqpNEoNDYO7P+SCUNz0GkbhtXqtCYmDD/Lso2RRIe4kltkxFhnY+26LRQUFjPvxumo1Z3qo0dopf/973/s27ePefPmMXny5DY5ZnuMCjCbjBjOfE6PblmoVQ0ZY20yBPuYcI/ojkqtoyZnEVqNPeuf2aLk3R+CefLPs/H2cr3kNlxNumKvstCgK/79OnJUgCBAJ+qheuedd3j22WcBWLBgAffee28Ht8g+ubv+br7ZbMZmE7V1BKFeWtoJFLZSp96per1jztK3ew0KhUxYoB4/Lw0SsP/gMf730WIMBlEk+3JxdW24+K8futOUmpoaANzcWpdsITc3l2effRZ3d3feeeedS2tkO8tK+6lRMAWgkKBHtzNkpf2EzVZLsH/Dv+XDKcFEdh8ugilBEAThvDpFQLVw4UIef/xxAF577TUee+yxNjnunj17AIiOjr6o/d9++21CQ0MJDQ0lKSmJ8vLyNmmXIFwJevaMZcroIqfeqXpqtYUpo1MZ1seASmnD20NNWJAOtUoi60wu/373c/Lyizqg1Ve+c+dNtTS0s35dcHBwq4771FNPUVlZyZNPPomHhwdVVVVOP/XDOU0mk2NZZ6FT7G0UTNVTq6zoFHsx1xk4nR2I2aLAZFby3g9B3DpnZDu3VBAEQeiKOjyg+uKLL3j00UcBeP755/nb3/7Wqv3ONxdj3bp1bNu2DbDPp7oY8+fPJycnh5ycHOLj4/Hy8rqo4whCZxEWFub4uVSFOUl0j8hodr2Xp4ExQ9IYP7QUN70NnUZJRJAeDzcVNpsVvV7MS7kcevXq5SgzkZzcdIFlm83mqD/Vu3fvVh03KysLsGf4c3d3b/Rz5oy9ptOrr77qWNZZqFUt1yRUq2pRaX155/tefPjDYJZv6EWPXqPw8nBppxYKV6q2/MwVBKHzarOAqri42PFTVlbmWF5eXu607txhc8uWLeP+++9HlmWeeOIJXnzxxVaf77XXXuO+++5jw4YNGAwGx/KioiLeeOMNbrzxRgBiY2O57777Luo1ubu7ExISQkhICGq1GoWiw+NPQbgkNpvN8XOpQv0ONdk7dS4vjyqGxp9k2qg8gv3MKBQQ6KNl+KAYvDw7zwX3lcTd3Z0hQ4YAsGHDhia32bNnDxUV9nT2EydObLe2dZSC8pZ74QrKgzGZLPgGRPHxGgXvLvPi5lnD2ql1wpWsLT9zBUHovNpsZri/v3+Ty0eOdB4ykZGR4ahb8sQTT2C12odhfPnll3z55ZfNHn/58uWMGjXK8byuro5FixaxaNEiJEnCw8MDSZKchuXFx8ezatUqtNpLKywqCEJjVv095NvuaWKNBXc+w1WxDgCdro4+sadwdaljX3IwqRl6Bg8a1GgvWZZbLOAttN7tt9/Ovn37WLx4Mc8//3yjYX1vvfUWYE/80Nqivlu2bGlxfVRUFFlZWbzwwgtNlrToSNG9HsBYdwi91txoXW2disiYG3HRa3n8wencOmcEp88U4ukueqcEQRCE1unQLpdz79gUFBS0+PPb4rw333wzzzzzDOPHjyc8PByLxUJNTQ3BwcFMnz6dTz/9lH379nXJopOC0LWpMPAQFbY/YpOVACiVNrpFnmHc0NOMG+VDYFCQ0x4n0jJ494OvqTR0nnk3XdnDDz9MZGQkBoOBWbNmOYr3GgwGnnzySZYvXw7AK6+80mhfSZKQJKnTBUWXwt3Djx3JczHWOtepMdaqySsMQC77mJIz32GzVBES6M2Yoa0LMgVBEAQB2rCH6mLqy2RmZl70+fr06cO//vWvi96/NQwGg2M4ocjyJwgXxsgEzHI4XvKrqBTlSBK4utTQPfZap+0Ki0r4bslKqmvqeOfdz7n/7rmEhQY1c1ShNfR6PT/++CMTJ07k4MGD9OnTx5FIwmazIUkSr7zyClOmTOnoprab+AE3c7ZyPBmHP8NFW0JNnS8BQb3pE/olKpWFkrIScovjCQjq09FNFQRBELoYMSmoBSLLnyBcGgs9KOXf1NliMZn1lFkeRq0Pd9om7eRpfDwURATpsVmNvLvwa44eO9FBLb5y9O/fn2PHjvGnP/2Jbt26UVdXh6+vLzNnzmTDhg38/e9/7+gmtjt3Dz/6DXuSmP6vEz/0cXzU61CrLUgSuLlWY5NFinRBEAThwonqmi2YP38+Dz30EADTpk2julrUzhGEC2XDizJeQqEoQeMR6LSuuOAU5sp9qJQgyxKBPlqqaix8sXg50yaPZfzYERxLsRfmjovrjVIp7gFdiKCgIBYsWMCCBQtavc/FjDaASxtx0BFK8zbRM6jA8fxAcgRBPVuXQl4QBEEQziUCqhacm/pXZPkThEuhwiY5B1M1VaWojO8ybrCRQK8wEo+6YzYrcHNRodMo2LxlB8kpJ6kos9erOnAokmFD+ndE44UrjGwz46FY6ahNVVun5n/LAnnpqQ5umCAIgtAliYBKEIQOYa5cSa9u9tpFLvpa3FwiSDziRVmlGpVKQVignmpjKf7e9iydW7ftYPDAeNFLJVyy0txfiA1pKCy981AYQ4eMxtVFZIQVBEEQLpy4MhEEoUNEhOQ6Hnt6GOgXd5IpI/LpEWEB7MPOXPUN93zUCjMHDiW1dzOFK4gsW6kp2YqXZg2qX3unjLUaPl4VzPVTB3dw6wRBEISuSgRULTAYDOTm5pKbmyuy/AlCG6vg71TbZjqe67QmesVkMGZgJiP7mZEk5/ebRq1g67YdWK3ifShcnJqyA+jlbwjyb+idSjwUxsgR16DXaTqwZYIgCEJXJgKqFogsf4JwOakwcD/ltj9hk+09UUqljajwswzqncb4IeXoNRb69aiiX48qJMkmeqmEiybLVqSabwgOKEKptPeA1hg1fLY6hDmTGxeaFgRBEITWEnOoWiCy/AlXmtzc3PNv1M5qGYfFUa+qFEmCQP9idLpaPN1CCPSrAMBsiSAlw1XMpRIuSk3ZAcKC8pyWJZ0IYvSoMei06mb2EoRL0xk/cwVBaHviiqQF7u7uhISEEBISIrL8CcJlZKE7JbxNna2hqKqnexV9Yk8RElRASFABw/vlil4q4aLYe6e+RasxOy339rAwc2K/DmqVIAiCcKUQEYIgCJ2CjCdl/IPsktGOZfVprQFCgwrpFWVEo1bg4SbmuwitV1N2gNCgxj0FkWFFWKuPdkCLBEEQhCuJGPInCEInokTtPZ9Sy0C8FO9xbqewVmNmRP98xk59C6VSDNESWsfRO+VnbrROqzEj1XyL7D0YSVJ2QOsEQRCEK4HooWqByPInXGnqh7CGhIR0dFNalJ1VhdnSOGgKCcyn+MzPHdAioatqrneqXmhQLjVlB9qxRcLVpKt85v5/e/ceHFV5/3H8s4FcySY04WITJKCABoJcwkUYCxOpoHiLdKyFQtG26PBHRxkLWGoJWmstMlWHGeoISsCKZWpHLglMgISLEsQQhBBERzHwq4EgSTAk5NKw+/z+yGTNZbNsDtlsNrxfMztzkuc8z/nu2Zzv2W/ODcD1oaDygLv8AZ3P4ahXVEh2q+tdpIYjClEh2XI4WrcB7hR/e9jt31Kj0JB6FX97uBMjAgB0N5zy5wF3+QM6X+n/7dTtN5e02R7Xv0Rf/N9O9R/8UCdGhUAV2TtF72d4LsBvS0rppGgAAN0RBZUHdrtddrtdkrjLH9BJEgbbFRrk+YhCwmC7ajsxJgSuwjNGK9+t8zjPkoVGcQM7KSAAQLdDQQWgS6lVikqcPxwxKCwslCQlJSX5KyQEsOlTRmr6lJH+DgMA0I1xyAUAAAAALOIIlQeVlZWqrKyUJO7yBwAAAKAVjlB5wF3+AAAAAHhCQeXBs88+q+LiYhUXF2vkyJHq3bu3v0MCAAAA0IVwyp8H3OUPAAAAgCc2Y4zxdxCBICYmRtXV1Ro2bJi/Q0E71dTUSJLCw8P9HIn/nThxwjU9cmRg3PksED+/r776SuHh4SovL/d3KAGLnBu4AnGb9RVybucg58LfOELlpStXrsjhcCg4OLhDx3U6nbpw4YL69+/foUfAfDWuL8f21bhff/21JCkxMbHDxmwUaOti9OjRAfd34avPz5fbSFhYmJxOpyorK11HudE+5Fzfjx1o26wUeOuCnPsDci66M45QeSk5OVmSlJ+f36Hjnjt3TvHx8SouLlZcXFyXH9eXY/tqXF99dlLgrYtA/LsItG3P12PfKALtcw/Ev6dA22alwFsXgfh3EWjbnq/HBrzBRUEAAAAAYBEFFQAAAABYREHlZ3a7XWlpaR1+zq+vxvXl2L6M2VcCbV0E4t+Fr7AubkxsW74f15cCbV0E4t+Fr7Au0J1xDZWXfHlOOHyLzy6w8fndmPjcAxefXWDj8wPajyNUAAAAAGARR6gAAAAAwCKOUAEAAACARRRUAAAAAGARBRUAAAAAWERBBQAAAAAWUVABAAAAgEUUVAAAAABgEQUVAAAAAFhEQeVBSUmJnn76ad16660KCwtT//799eCDDyo7O9vfocGD9PR02Ww2j6/IyEh/h3nDqqys1LZt2/SnP/1J9913n/r06eP6XL744otr9nc6nXrrrbc0adIk9e7dW3a7XWPGjNGrr76q//3vf53wDuBL5N3AQ87t2si5gO/19HcAXVVBQYHuvvtulZWVSZKioqJUWlqqjIwMZWZm6uWXX9Zzzz3n5yjhSXBwsGJiYty29erVq5OjQaPs7Gw98sgjlvrW19crNTVVO3bskCSFhISoR48eOnbsmI4dO6Z///vfysnJ4ctbgCLvBjZybtdEzgV8jyNUbtTU1Oihhx5SWVmZxowZo8LCQlVUVOjSpUt69tlnZYzRsmXLtGvXLn+HCg8mT56skpISt6/Tp0/7O7wbWr9+/TRz5kylpaXprbfe8rrf888/rx07digsLEzp6emqrq7WlStXtH37dsXExCgvL09PPfWUDyOHr5B3Ax85t+si5wI+ZtDKa6+9ZiSZyMhI8+2337ZqT01NNZLM2LFj/RAdrmX9+vVGkpk6daq/Q4EbV69ebfZzUVGRkWQkmVOnTrXZ7/z58yY0NNRIMm+88Uar9i1bthhJxmazmePHj3d43PAt8m7gIud2beRcwPc4QuXGe++9J0maM2eO4uPjW7UvXrxYknT06FF9+eWXnRobEOh69Ohhqd9//vMf1dXVKTo6Wk8++WSr9ocffljDhg2TMUabNm263jDRyci7gG+QcwHfo6BqobKyUvn5+ZKkGTNmuJ3nzjvvVHR0tCRxoTTQSfbu3StJmjJlisLCwtzOM336dElSTk5Op8WF60feBboeci7gPQqqFk6dOiVjjCRpxIgRbucJCgrSbbfdJkn6/PPPOy02tM/Jkyc1YsQIhYeHy263KykpSYsWLVJRUZG/Q4MFjdtaW9ulJA0fPlxS8+0YXR95t3sg53Yv5FzAexRULZw/f941HRcX1+Z8jW1N50fXUlpaqlOnTikiIkK1tbU6efKkXn/9dY0YMYLTEwJQ47bmzXZZVVWlqqqqTokL14+82z2Qc7sXci7gPQqqFq5cueKaDg8Pb3O+iIgISSKBdEFxcXF64YUXVFhYqNraWpWVlamqqkqZmZkaPny4ampqNH/+fB04cMDfoaIdGrdNb7ZLiW0zkJB3Axs5t3si5wLeo6BCtzN9+nQtX75cI0aMUEhIiCQpNDRUM2fOVG5uroYMGaKrV6/yPBsA6ADkXAA3OgqqFpo+fLCmpqbN+aqrqyWJh9kFmOjoaC1btkyS9Mknn6i0tNTPEcFbjdumN9ulxLYZSMi73Rc5N3CRcwHvUVC10PRc4XPnzrU5X2Pbj3/8Y5/HhI41ceJESZIxhoulA0jjtunNdhkZGSm73d4pceH6kXe7N3JuYCLnAt6joGrh9ttvl81mk9RwxyJ3nE6n6zkojXe4AeBbjdtaW9ul9MNdqRITEzslJnQM8i7Q9ZBzAe9RULVgt9s1btw4SdLu3bvdznP48GFVVFRIkqZNm9ZpsaFjHD582DU9aNAg/wWCdklJSZEkffTRR6qtrXU7T+M2y3YZWMi73Rs5NzCRcwHvUVC5MWfOHEnSe++95/b2vKtWrZIkJScnu56Lgq7hWs/BuHz5sl555RVJ0oQJE9S3b9/OCAsdYNasWQoNDdX333+vdevWtWrfvn27vvzyS9lsNs2ePdsPEeJ6kHcDEzm3+yLnAu1g0Ep1dbVJSEgwkszYsWPNyZMnjTHGXL582SxevNhIMpJMVlaWnyNFS0VFRWbixIlm3bp15uzZs67f19XVmZ07d5qkpCQjyQQFBZns7Gw/Rnpju3jxout19OhR1zZ16NChZm0Oh6NZvyVLlhhJJjw83GzcuNFcvXrVGGNMZmamiY2NNZLMnDlz/PGWcJ3Iu4GJnBsYyLmAb9mM4dHW7hw/flzTpk1TWVmZJCkqKkpVVVVyOp2y2Wx6+eWXuQVsF3TmzBkNHjzY9XNYWJh69eqly5cvq76+XlLDczPefPNNzZs3z19h3vAar5e5lqKiomanCNXX1ys1NVU7duyQ1HBr5h49erjuNDV+/HhlZ2dzcXSAIu8GHnJuYCDnAr5FQeVBSUmJ/vrXvyojI0PFxcWKiorShAkTtGjRIs4X7qJqamq0bt06ffzxxzp+/LguXryoy5cvq1evXho6dKimTZumhQsXKiEhwd+h3tCs7tylhpsTrF27Vunp6fr888/lcDg0dOhQzZ49W88884zrOTgITOTdwELODQzkXMC3KKgAAAAAwCJuSgEAAAAAFlFQAQAAAIBFFFQAAAAAYBEFFQAAAABYREEFAAAAABZRUAEAAACARRRUAAAAAGARBRUAAAAAWERBBQAAAAAWUVABAAAAgEUUVAAAAABgEQUVAAAAAFhEQQXAa+np6bLZbLLZbDpz5oy/wwGAbo+8C3R9FFRo5syZM67EfT2v7pT0m+7Mmr569uyp2NhY3XLLLUpJSdHixYu1detW1dfX+ztkAAGEvNsaeRdAIKGgAixyOBwqLy9XUVGR9u3bp1WrVik1NVUDBw7UypUr5XA4/B2iV5p+mUtPT/d3OADQJvIugK6op78DQNcSHx+vEydOtNk+Y8YMnTt3TnFxccrKyvI4Tnf00ksv6eGHH3b9XFlZqUuXLunYsWPKzs5WTk6OSkpKtHTpUm3dulXbt29XTEyMHyMG0NWRdz0j7wLo6iio0ExwcLCSkpI8tnszX3cVHx/v9n3PnDlTy5YtU0FBgebNm6eCggLl5ubqZz/7mXbt2uVabwDQEnnXM/IugK6OU/6ADnTHHXfo0KFDGjVqlCRp3759evPNN/0cFQB0X+RdAP5GQYUO8/jjj8tms2nQoEGSpJKSEi1btkxJSUmKjo6WzWbTli1bmvVxOp3atGmTUlNTNWDAAIWGhupHP/qRJk6cqL/85S+qqKjwatmZmZmaPXu2Bg0apPDwcEVHR2v06NF67rnnVFJS0sHv1LOIiAi9++67stlskqRXX31VV69ebXP+ixcvasWKFZo4caJiY2MVEhKiuLg4paamtlpfLTWeg79ixQpJUk5Ojh555BHFx8crLCxMCQkJWrBggU6fPt1m/8GDB7t+fuKJJ1pdBN44tjtOp1Nvv/227rrrLsXGxioiIkLDhw/XH//4R68/OwDWkXcbkHfJu4BfGaAdEhISjCSTkJDQqm3+/Pmutk8++cT07dvXSGr2+vDDD13z//e//zXJycmt5mn6uummm8ynn37aZjzff/+9mTFjhscx7Ha7yczMtPye169f7xpr/fr1Xvf76U9/6uqXm5vrdp7Nmzcbu93uMf6HHnrIVFVVue3fOE9aWpp58cUXjc1mcztGeHi42bp1a5v9Pb3S0tLcrouTJ0+ae+65p81+iYmJ5rvvvvN6fQFwj7y73ut+5F3yLuAPFFRoF2927LGxsSY+Pt706tXL/OEPfzB79+41eXl5ZuPGjeazzz4zxhhTVlZmBg0aZCSZ4OBgs2DBArN582Zz+PBhc+DAAfPiiy+amJgY13hnz55ttby6ujozbtw4I8nYbDbz85//3Pzzn/80ubm5Jjc31/z97383AwYMMJJMaGioyc/Pt/Sere7YV65c6er3t7/9rVX7Bx984NoR33zzzWblypUmMzPT5Ofnm23btplf/OIXrv6PPvqo22U0to8fP95IMkOGDDFr1641eXl5Zu/evWbRokUmODjYSDIhISHm2LFjzfqfOHHCZGVlucZ56aWXzIkTJ5q9Lly44HZdTJ482dhsNvPLX/7SbNu2zRw9etRkZGQ0+6I1d+5cr9cXAPfIu+u97kfeJe8C/kBBhXbxZscuyURERHjckc6dO9dIMnFxceaLL75wO88333xj+vfv3+YO4vnnnzeSTGRkpDl48KDbMcrKykxiYqKRZO666y7v3mQLVnfse/bscfX7zW9+06yttLTUREdHG0lm9uzZpq6uzu0Ya9ascY2xZ8+eVu1N/zM5atQoU1FR0WqenTt3mqCgINfOuKWioiKv31/TddHW/A6Hw0ybNs31pe3ixYsexwTgGXl3vdf9yLvkXcAfuIYKPrFkyRKNHTvWbdvZs2f1/vvvS5Jef/113XbbbW7nGzx4sJYvXy5J2rx5s6qrq11tVVVVWr16tSRp+fLlmjx5stsxYmJitGrVKknSxx9/rK+++sraG7IgNjbWNV1eXt6s7R//+IcqKirUt29frVu3TiEhIW7HWLhwocaPHy9Jeueddzwub+3atYqKimr1+3vvvVfz58+XJOXm5uqzzz5r1/toS2pqqh5//PFWvw8KCtLvf/97SVJ9fb1yc3M7ZHkAPCPvkncl8i7gDxRU8Im5c+e22ZaRkSGHw6Hg4OBmzxZxZ8qUKZIadhBHjhxx/X7//v2ui28fffRRr8aQpEOHDl0z9o4SGRnpmq6srGzWtnXrVkkNt/2NiIjwOE5j/J5iT0pKcn0BcOfXv/61a3r37t0el+ctT5/xuHHjXNPffPNNhywPgGfkXfJuI/Iu0Ll4DhU6XGRkpG699dY22xt30PX19QoNDfV63KZ3jWq6k296t6T2jOFrTXfmTf+D6XA4dOzYMUnShg0btGHDBq/G8xT7hAkTPPYdN26cgoKC5HQ6VVBQ4NXyriUxMbHNtqYP1Wz5pQZAxyPvNiDvNiDvAp2LI1TocL179/bY/t1331kat+mpJx0xhq+Vlpa6ppvu6MrLyz3ezrctNTU1bbb169fPY9+wsDDXl4uysrJ2L9sdT//hDQr6IbU4HI4OWR6AtpF3G5B3G5B3gc7FESp0uB49enhsb0z0UVFROnjwoNfjDhgwoNUYUsMpGU1P8/DkWjvAjnT06FHXdNPrFZrGPm/ePC1ZsuS6l9X47BUANybybgPyLgB/oKBCp+vTp4+khguchw4d2q7TT1qO0Tg9ZMiQDouvo+zatcs1/ZOf/MQ1HRsbK5vNJmOMnE6nkpKSrntZFy5c8NheW1ury5cvu5YP4MZC3iXvAvAdTvlDpxszZoykhqe9W71YuXEMqeEuUl1NQUGBcnJyJEkDBw5UcnKyqy04OFgjRoyQJB08eFDGmOte3qeffuqxPT8/X06nU5I0cuTIZm38lxXo/si75F0AvkNBhU734IMPunYmr732mqUxpk2bpl69ekmSVq9e3aXOF6+urtavfvUr18+LFy9Wz57NDwY33mXrzJkz2rJly3Uvs7CwUPn5+W22N7317z333NOsLSwszDVdV1d33bEA6HrIu+RdAL5DQYVON2zYMD322GOSpG3btunPf/6zx/lLSkq0bt26Zr/r3bu3fve730lqOGd+4cKFHi84rqiocD0/xZcKCgo0adIkHT9+XJKUkpKip556qtV8Tz/9tOti5SeffLLZef/ufPTRR9q/f7/HeRYsWKCqqqpWv9+1a5fS09MlSXfeeWer59TExsa6nsdy+vRpj8sAEJjIu+RdAL7DNVTwizVr1ujIkSP6+uuvtXz5cmVmZuqJJ57QyJEjFR4erkuXLqmwsFC7d+9WVlaW7rjjDv32t79tNsYLL7yg/fv369ChQ1q7dq0OHjyoBQsWKDk5WXa7XRUVFTp16pT27dun7du3Kzw83PVlwKri4mIVFha6fq6qqlJ5ebmOHz+uPXv2uE43kaTJkyfrgw8+UHBwcKtx+vbtq40bN2rWrFkqLS3VpEmTNHfuXD3wwAMaOHCgHA6Hzp8/r7y8PG3ZskUnT57U6tWrNXXqVLdxjRs3TkeOHNHYsWO1dOlSjRo1SleuXNG2bdu0evVqOZ1OhYSEaM2aNa369uzZU+PHj9fBgwf1zjvvaMyYMRo9erQr7piYmGZ3ywIQmMi75F0APmKAdkhISDCSTEJCQqu2+fPnt9nmzoULF8zdd99tJF3zlZKS4naMyspK89hjj3k1xuDBgy295/Xr13s1fuPrpptuMq+88oq5evXqNcfeuXOn6dOnj1fjbtiwoVX/xra0tDSzYsWKNvuGhYWZDz/8sM04MjIyjM1mc9s3LS3N7booKiry+N7c9QfQfuRd8i55F+jaOEIFv+nXr5+ys7OVlZWlTZs2KTc3VyUlJaqtrVV0dLRuueUWTZw4UTNnztT06dPdjhEZGal//etfeuaZZ5Senq4DBw6ouLhYV65ckd1u16BBg5ScnKz77rtPDzzwQIfG36NHD9ntdkVHR7uWM2XKFN1///2tzt1vy7333quioiK9/fbbyszMVGFhocrKyhQUFKR+/fopMTFRU6dO1axZs5rdAtidtLQ0TZ48WatXr1ZeXp7Ky8vVv39/TZ8+XUuXLtXQoUPb7Hv//fcrOztbb7zxhvLy8nTx4kXV19e3a30A6PrIu+RdAB3PZkwH3OoGgF80XmSelpamFStW+DcYALgBkHcBtMRNKQAAAADAIgoqAAAAALCIggoAAAAALKKgAgAAAACLKKgAAAAAwCLu8gcAAAAAFnGECgAAAAAsoqACAAAAAIsoqAAAAADAIgoqAAAAALCIggoAAAAALKKgAgAAAACLKKgAAAAAwCIKKgAAAACwiIIKAAAAACyioAIAAAAAiyioAAAAAMAiCioAAAAAsIiCCgAAAAAs+n/MdvyAyNuwOgAAAABJRU5ErkJggg==\n", 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" ] }, "metadata": { "image/png": { "height": 351, "width": 426 } }, "output_type": "display_data" } ], "source": [ "#make a 2 row, 2 column plot (4 total subplots)\n", "fig,axes = plt.subplots(2,2,figsize=(5,5))\n", "#set background color to white, otherwise its transparent when you copy paste it out of this notebook. \n", "fig.set_facecolor('w')\n", "\n", "#lets ravel the 2x2 axes matrix to a 4x1 shape. This makes looping easier (in my opinion). \n", "axes = axes.ravel()\n", "\n", "########### colormap stuff ###########\n", "# I want to color each line by the number of trees. So this bit of code does that for us.\n", "#get func to plot it\n", "from aux_functions import make_colorbar\n", "#grab colormap\n", "cmap = matplotlib.cm.cividis\n", "#set up the boundaries to each color \n", "norm = matplotlib.colors.BoundaryNorm(n_tree, cmap.N, extend='both')\n", "#make a mappable so we can get the color based on the number of trees. \n", "scalarMap = matplotlib.cm.ScalarMappable(norm=norm, cmap=cmap)\n", "######################################\n", "\n", "titles = ['Bias','MAE','RMSE','$R^{2}$']\n", "for j,ax in enumerate(axes):\n", " for i,ii in enumerate(n_tree):\n", " color_choice =scalarMap.to_rgba(ii)\n", " ax.plot(np.arange(1,11,1),df_val[(i*10):(i+1)*10,j],'o-',color=color_choice,ms=3)\n", " ax.plot(np.arange(1,11,1),df_train[(i*10):(i+1)*10,j],'^--',color=color_choice,ms=3)\n", " ax.axvline(8,ls='--',color='k')\n", " ax.set_title(titles[j])\n", " ax.set_xlim([0,12])\n", " ax.grid('on')\n", " # ax.xaxis.grid(True, which='minor')\n", " # For the minor ticks, use no labels; default NullFormatter.\n", " ax.xaxis.set_minor_locator(MultipleLocator(1))\n", " ax.yaxis.set_minor_locator(MultipleLocator(2.5))\n", " \n", "axes[2].set_xlabel('Tree Depth')\n", "axes[3].set_xlabel('Tree Depth')\n", "\n", "########### draw and fill the colorbar ###########\n", "ax_cbar = fig.add_axes([1.025, 0.4, 0.015,0.33])\n", "cbar = make_colorbar(ax_cbar,1,100,cmap)\n", "cbar.set_label('# of trees')\n", "##################################################\n", "\n", "plt.tight_layout()" ] }, { "cell_type": "markdown", "id": "ddd5faa3-c318-43e3-9235-f0219caa62d9", "metadata": {}, "source": [ "Okay, now we have the training curves in the dashed lines and triangle markers. I have also drawn a vertical dashed black line on the tree depth that seems to maximize performance before overfitting. We can see at a tree depth of 8, the $R^{2}$ value for the training data now out performs the validation data, while the other metrics are effectively the same as 5,6, and 7. Thats why we suggest random forest of > 1 tree and depth of 8 is likely a good model to continue on and use. \n", "\n", "I hope this was enough to give you an example of how to do hyperparameter tuning. I encourage you to go ahead and try it with the other models!" ] } ], "metadata": { "kernelspec": { "display_name": "waf_tutorial_part1", "language": "python", "name": "waf_tutorial_part1" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.2" } }, "nbformat": 4, "nbformat_minor": 5 }