diff --git a/analysis_and_scripts/Analysis_07MAY2019_new.ipynb b/analysis_and_scripts/Analysis_07MAY2019_new.ipynb index 435c9e6dc50f52f2552efa21d23be697d438e897..0945b1a36cf2fbdbf07cffcc2a5375f03892dc97 100644 --- a/analysis_and_scripts/Analysis_07MAY2019_new.ipynb +++ b/analysis_and_scripts/Analysis_07MAY2019_new.ipynb @@ -56,7 +56,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 78, "metadata": {}, "outputs": [], "source": [ @@ -127,7 +127,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 90, "metadata": {}, "outputs": [], "source": [ @@ -137,11 +137,12 @@ " return 1 / (1 + np.exp(-x))\n", "\n", "\n", - "def generateDataWithUnobservables(nJudges_M=100,\n", - " nSubjects_N=500,\n", - " beta_X=1.0,\n", - " beta_Z=1.0,\n", - " beta_W=0.2):\n", + "def dataWithUnobservables(nJudges_M=100,\n", + " nSubjects_N=500,\n", + " beta_X=1.0,\n", + " beta_Z=1.0,\n", + " beta_W=0.2,\n", + " add_noise_T=True):\n", "\n", " df = pd.DataFrame()\n", "\n", @@ -163,12 +164,17 @@ " # Calculate P(Y=0|X, Z, W)\n", " probabilities_Y = sigmoid(beta_X * df.X + beta_Z * df.Z + beta_W * df.W)\n", "\n", + " df = df.assign(probabilities_Y=probabilities_Y)\n", + "\n", " # Result is 0 if P(Y = 0| X = x; Z = z; W = w) >= 0.5 , 1 otherwise\n", " df = df.assign(result_Y=np.where(probabilities_Y >= 0.5, 0, 1))\n", "\n", " # For the conditional probabilities of T we add noise ~ N(0, 0.1)\n", " probabilities_T = sigmoid(beta_X * df.X + beta_Z * df.Z)\n", - " probabilities_T += npr.normal(0, np.sqrt(0.1), nJudges_M * nSubjects_N)\n", + "\n", + " if add_noise_T:\n", + " probabilities_T += np.sqrt(0.1) * npr.normal(size=nJudges_M *\n", + " nSubjects_N)\n", "\n", " df = df.assign(probabilities_T=probabilities_T)\n", "\n", @@ -227,11 +233,11 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 80, "metadata": {}, "outputs": [], "source": [ - "def generateDataWithoutUnobservables(nJudges_M=100, nSubjects_N=500, beta_X=1.0):\n", + "def dataWithoutUnobservables(nJudges_M=100, nSubjects_N=500, beta_X=1.0):\n", "\n", " df = pd.DataFrame()\n", "\n", @@ -252,15 +258,20 @@ " df = df.assign(probabilities_Y=sigmoid(beta_X * df.X))\n", "\n", " # Draw Y ~ Bernoulli(sigmoid(beta_X * x)) = Bin(1, p)\n", - " df = df.assign(\n", - " result_Y=npr.binomial(n=1, p=df.probabilities_Y, size=nJudges_M * nSubjects_N))\n", + " results = npr.binomial(n=1,\n", + " p=df.probabilities_Y,\n", + " size=nJudges_M * nSubjects_N)\n", + "\n", + " df = df.assign(result_Y=results)\n", "\n", " # Invert the probabilities. P(Y=0 | X) = 1 - P(Y=1 | X)\n", " df.probabilities_Y = 1 - df.probabilities_Y\n", "\n", " # Sort by judges then probabilities in decreasing order\n", " # I.e. the most dangerous for each judge are first.\n", - " df = df.sort_values(by=[\"judgeID_J\", \"probabilities_Y\"], ascending=False)\n", + " df.sort_values(by=[\"judgeID_J\", \"probabilities_Y\"],\n", + " ascending=False,\n", + " inplace=True)\n", "\n", " # Iterate over the data. Subject is in the top (1-r)*100% if\n", " # his within-judge-index is over acceptance threshold times\n", @@ -298,7 +309,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 81, "metadata": {}, "outputs": [], "source": [ @@ -378,12 +389,19 @@ "F(x_0) = \\int P(x)~\\delta(P(Y=0|T=1, X=x) > P(Y=0|T=1, X=x_0)) ~ dx = \\int P(x)~\\delta(f(x) > f(x_0)) ~ dx.\n", "$$\n", "\n", - "NB: in code the direction of inequality was changed." + "NB: in code the direction of inequality was changed. CDF changed to `bailIndicator` function.\n", + "\n", + "**Rationale for `bailIndicator`**\n", + "\n", + "* Bail decision is based on prediction $P(Y=0|T=1, X=x)$.\n", + " * Uniform over all judges\n", + "* Judges rationing: \"If this defendant is in the top 10% of \"dangerousness rank\" and my $r = 0.85$, I will jail him.\"\n", + "* Overall: this kind of defendant $(X=x)$ is usually in the $z^{th}$ percentile in dangerousness (sd +- $u$ percentiles). Now, what is the probability that this defendant has $z \\leq 1-r$?" ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 82, "metadata": {}, "outputs": [], "source": [ @@ -411,33 +429,72 @@ " return f_values[:, model.classes_ == class_value].flatten()\n", "\n", "\n", - "def cdf(x_0, model, class_value):\n", - " '''\n", - " Cumulative distribution function as described above.\n", - " \n", - " '''\n", - " prediction = lambda x: getProbabilityForClass(\n", - " np.array([x]).reshape(-1, 1), model, class_value)\n", + "# def cdf(x_0, model, class_value):\n", + "# '''\n", + "# Cumulative distribution function as described above.\n", "\n", - " prediction_x_0 = prediction(x_0)\n", + "# '''\n", + "# prediction = lambda x: getProbabilityForClass(\n", + "# np.array([x]).reshape(-1, 1), model, class_value)\n", "\n", - " x_values = np.linspace(-10, 10, 40000)\n", + "# prediction_x_0 = prediction(x_0)\n", "\n", - " x_preds = prediction(x_values)\n", + "# x_values = np.linspace(-10, 10, 40000)\n", "\n", - " y_values = scs.norm.pdf(x_values)\n", + "# x_preds = prediction(x_values)\n", "\n", - " results = np.zeros(x_0.shape[0])\n", + "# y_values = scs.norm.pdf(x_values)\n", "\n", - " for i in range(x_0.shape[0]):\n", - " \n", - " y_copy = y_values.copy()\n", - " \n", - " y_copy[x_preds > prediction_x_0[i]] = 0\n", + "# results = np.zeros(x_0.shape[0])\n", + "\n", + "# for i in range(x_0.shape[0]):\n", + "\n", + "# y_copy = y_values.copy()\n", + "\n", + "# y_copy[x_preds > prediction_x_0[i]] = 0\n", + "\n", + "# results[i] = si.simps(y_copy, x=x_values)\n", + "\n", + "# return results\n", + "\n", + "\n", + "def bailIndicator(r, y_model, x_train, x_test):\n", + " '''\n", + " Indicator function for whether a judge will bail or jail a suspect.\n", + " \n", + " Algorithm:\n", + " ----------\n", + " \n", + " (1) Calculate recidivism probabilities from training set with a trained \n", + " model and assign them to predictions_train.\n", + " \n", + " (2) Calculate recidivism probabilities from test set with the trained \n", + " model and assign them to predictions_test.\n", + " \n", + " (3) Construct a cumulative distribution function of the probabilities in\n", + " in predictions_train.\n", + " \n", + " (4)\n", + " For pred in predictions_test:\n", " \n", - " results[i] = si.simps(y_copy, x=x_values)\n", + " if pred belongs to a percentile (computed from step (3)) lower than r\n", + " return True\n", + " else\n", + " return False\n", + " \n", + " Returns:\n", + " --------\n", + " (1) Boolean list indicating a bail decision (bail = True).\n", + " '''\n", "\n", - " return results" + " predictions_train = y_model.predict_proba(x_train)[:, 0]\n", + "\n", + " predictions_test = y_model.predict_proba(x_test)[:, 0]\n", + "\n", + " return [\n", + " scs.percentileofscore(predictions_train, pred, kind='weak') < r\n", + " for pred in predictions_test\n", + " ]" ] }, { @@ -451,11 +508,11 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 83, "metadata": {}, "outputs": [], "source": [ - "def fitLogisticRegressionModel(x_train, y_train, x_test, class_value):\n", + "def fitLogisticRegression(x_train, y_train, x_test, class_value):\n", " '''\n", " Fit logistic regression model with given inputs. Checks their shape if \n", " incompatible.\n", @@ -497,7 +554,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 88, "metadata": { "scrolled": false }, @@ -506,12 +563,12 @@ "name": "stdout", "output_type": "stream", "text": [ - "1| 0 1 2 3 4 2| 0 1 2 3 4 3| 0 1 2 3 4 4| 0 1 2 3 4 5| 0 1 2 3 4 6| 0 1 2 3 4 7| 0 1 2 3 4 8| 0 1 2 3 4 " + "[1] 0 1 2 3 4 [2] 0 1 2 3 4 [3] 0 1 2 3 4 [4] 0 1 2 3 4 [5] 0 1 2 3 4 [6] 0 1 2 3 4 [7] 0 1 2 3 4 [8] 0 1 2 3 4 " ] }, { "data": { - "image/png": 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\n", + "image/png": 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eHyu9DH1s4pk5A3zaX8aY09je6LrZPIV0KeyQyY1JL1wdKW1vPE5A4WXZFuwQ26zoOY/CHgcDsT0qawGMMXuxF81hzutX49tMq6m1e1Y6g73mcRvW5kxXXj0zBTttdASo4wwv9BTq/PU2hNnboz4S03Z6LjDGJBhjvnd+mIpwkhO/XxKP46z+vvblOzAjx2yidO2DRJk5H9PYj0plOQ24lMoZh4GSTu8FYJ/NhZ3BL8M9z85/dL8CoZLkeVMiUhr762N6fYwdZjVYREI8F4p9fsptyT+Wboedv57/MT8LeHuGTeJ/6N4Cy43YKaz7ikg7z4Ui4i9pPM/MwyLssJiezisBO8wmaZmlnXsCPCX+ShuTJG8BEaktIteltWIR8QN6Y4cwdTfG9PV8YScsOA10ln+edfO+U8/RIlLGo8y8ztTRGGN+xwZs9QBvz9xKun8nOmVO9CzTyVtGRLzdB9RO3J/plgd41Xmb9KIttTb1enyISBPsbHWZ9Ql2CNPDInK750KPQOVdbKAxQbw8A01EbhQfn0+XisQZE2927l1LWo9XU/jMKbwEFEnqLMA0574XzzpXFR+eT+eIcv4+iw3W1yVZtg57QV4d33u3Umv3rPSd87d3YoITnI7CzlKZWR8CBbBT9Ls4Q9jaYycR2ezlc0PE/Zl01YB+2KGMyxPTnF5zT27fL859bp9gH33xsGdmsc+rCvVM90Ga34Fk7JhNlOY+SIXP56Ov+1Gp7KBDCpXKGROww242icgC7H9gLbEXTD8AN2Si7HHOa7OILMZeTNyNvTm4anoKMsbEiEhn7Hj8b0Tkc+w9NP7YcfOh2Huu2meivmCfkfR/2Gcq3YkN8m7F3gT+GeAZOO3G3nfQU0QuOvkTjDFjjDFGRLphf3lf6QyH2YHdx5Www6D+xA4nSZMx5m8RWYm9RysBiHIClaSuA74VkR3Ouo5ih6d1wgZL45PkvR17/94X2DZPTbhTzlKT5JlRHvW7JCLzsM9F6wzMMMZ8JyKDsfde7BWRj7EXROWddY7CHoMAA7D74g0RuQ97nARgA926OBcjxpjtIvIkdvrln0TkM2xwXxw7QUIz7DN7kt6MD/Z+vP85x/kxbC/STdjnKiUNuFJsU2wQvR2IcC7gvsP2et2Nndbe54ekeuMc592xQxbXi8gKpz4lsL0FPwP3O9knYNuwD9BCRNZij6dy2MC1Pva49TZ5gq/1iROR94HHge3Ovi6OfV5VFN57ZNZig51FIrIae/G73hiz0RizTETewJ5j+53z+Ddsr8T12Ek1umBnnUvLd9hZ60pih5WdTLIsCuia5N++2Ii9mH9aRIphp5k/bYx538fP+2oa8Azwmog0xG5/U+zEDj9i90NmvIa9J+gxEbkJex5VwO7XGOA/XoYyxmPPiR9E5BNswNYd21P0gDHmrJPvJmy7bsI+P+8v7Hd5R+xw5aT7qj92coz3naBrC3YYYEXsaIFiJJ9wJlW+fAdm8JhNzz5ISXrOx/TsR6WyVnZMfagvfV2LL/6ZFj7NZzw5+btjL84vYP/DmY69AEptiuJUp4VPsuwZ4CD2ousn7L1Eic9t8jYt/P406loJ28NxEHtxdAo7lfg7QIgP25o4TfeaVPLcjA1Czjiv/zppybbdyd/U2VfnneWe+6wk9oG8e7AXPNHOv6di70lLT9veyz/T+/fxsrwY9lkzG5y2vITtlVkM3OKRN7HdUtwXSfIuwodHCmBnGzTABo/0NthJWU5jZxH8BftL/PUe+Yo7++pnp+4nsb/GP+llXU2AJfzzi/Yx7MxrQ0hhum/sg0x3OHX4A3gT78/rSbFNsVNef4gNZi9gh0N283YepHa8pbHseuzMj0edbfsDG/C39cgn2PvGopxj9SI2WFmFveBNtm1e1uX1uE6yPMA5pvY75e/HTliS31v9sdOkj8Wez3Ge+8TJcxf2vDrhbN/vzjY8jZcp41Op+yq8PHoBOxtc4nlSycvnkk3r7aTfg+2VjnGW70+yLMXvp9SWpZD/VuwPRDHOMT6bdHznprUMO0x2NHDA2b8nsOdKXS9lfOW0UxD2e/QPp523Afd55K2IPT+3YIOEi9jv4hl4f5xHQewDtXdgz6Vz2HP7Izy+S3zdh6TxHZjBY9bnfZDG8ePT+Zje/agvfWXlK/EZMkoppVSWEZG+2OeB9TLGpHrPm1JKKfVvpvdwKaWUUkoppVQ20YBLKaWUUkoppbKJBlxKKaWUUkoplU30Hi6llFJKKaWUyibaw6WUUkoppZRS2USfw+VFcHCwqVy5ck5XA4Dz588TFBSU09VQHrRdch9tk9xJ2yX30TbJnbRdch9tk9wpN7XLd999d8IYUzKtfBpweVG5cmW2bt2a09UAICoqirCwsJyuhvKg7ZL7aJvkTtouuY+2Se6k7ZL7aJvkTrmpXUTElwfG65BCpZRSSimllMouGnAppZRSSimlVDbRgEsppZRSSimlsokGXEoppZRSSimVTTTgUkoppZRSSqlsogGXUkoppZRSSmUTnRY+g6Kjozl+/DixsbHZup4iRYqwZ8+ebF2HSj9tF9/4+/tTqlQpChcunNNVUUoppZTKERpwZUB0dDR//vkn5cuXJ3/+/IhItq3r7NmzFCpUKNvKVxmj7ZI2YwwxMTH8/vvvABp0KaWUUuqapEMKM+D48eOUL1+eAgUKZGuwpdTVTEQoUKAA5cuX5/jx4zldHaWUUkqpHKEBVwbExsaSP3/+nK6GUleF/PnzZ/vQW6WUUkqp3EoDrgzSni2lfKPnilJKKaWuZRpw5RJhM8MImxmW09VQSimllFJKZSENuJRSSimllFIqm2jAdY0TkTRflStXzulqAvDCCy+kWMdGjRplyzr37t2LiDB//vxsKR9g8eLFjB8/Pln6qlWrEBE2b96cbetWSimllFLZS6eFv8Zt2rTJ7X2nTp2oX78+kZGRrrSAgIArXKuU+fn58dVXXyVLv5qnaF+8eDFbt27liSeecEtv3LgxmzZt4sYbb8yhmimllFJKqczSgOsa59kzFBAQQHBwsM89RpcuXbriAVl29WblNkWKFLlmtlUppZRS6t9KhxQqn3Xr1o3q1auzfv16GjVqRP78+Rk6dCgXL15ERBg9erRb/pSG461Zs4awsDAKFixIwYIFueuuu9izZ0+W1PHDDz9ERPjpp5+SLbvjjjvcApixY8fSqFEjihUrRrFixWjSpAmff/55muto1KgRnTp1SpZepkwZBgwY4Hp/9OhR+vXrR40aNShQoAAVK1akd+/eHDt2zJWnW7duLFiwgAMHDriGR9auXRvwPqQwISGBMWPGUKNGDfLly0f58uV58sknOX/+vCtPYnu88sorvPXWW1SqVIlChQpx5513sm/fvjS3TymllFJKZR0NuFS6nDhxgl69etG7d2/++9//cv/996fr8x9//DHh4eEEBwfz0UcfMXv2bP766y+aN2/O0aNHfSojLi4u2SshIQGA++67j6CgIObMmeP2mSNHjrB+/Xp69erlSjt06BD9+/dnyZIlzJs3jxtvvJE2bdqwdu3adG1TSk6cOEGhQoV4/fXXWbVqFaNHj+aHH36gefPmrudSvfLKK7Rs2ZIKFSqwadMmNm3axIIFC1Is89lnn+X555+nffv2rFixgkGDBjFlyhTuvvtujDFueadOncqXX37JhAkTmDp1Kj/99BOdOnVy7SullFJKKZX9dEhhFnlq1VPsOLYjw59P/Kzn1PDx8fH4+fn5VEaDMg0Y12Zchuvgi7///psFCxYQHh7uSrt48aJPn01ISODJJ58kPDycxYsXu9JDQ0OpWrUq77zzTrJeMk/x8fH4+/snS3/mmWd48803CQoKolOnTsyZM4fhw4e7ngE1d+5c/Pz86Nq1q+sz48b9s68SEhJo2bIle/bsYfLkydxxxx0+bVNq6taty9tvv+16HxcXxy233ELNmjVZs2YNbdu2pXr16pQoUYKAgIA0hw8eO3aMd999l/79+zN27FgAWrduTdGiRenXrx//+9//aN26tSt/UFAQy5Ytcx0/sbGx9OrVix07dtCwYcNMb59SSiml1BUVFkaDM2dgR8avuXOC9nCpdClQoIBbsJUeu3bt4rfffiMiIsKtd6pw4cLccsstrF+/Ps0y/Pz8+Pbbb5O9nnrqKVeeXr168csvv/D111+70ubMmUO7du0IDg52pX3zzTe0bduWUqVK4efnh7+/Pxs2bMiyYXfGGMaPH0/dunUpWLAg/v7+1KxZEyBD69i4cSNxcXFERES4pffs2RMRYd26dW7p4eHhbsF63bp1ATh8+HC6162UUkoppTJGe7iySGZ7lhJ7tqIejHJLP3v2bK6aga9MmTIZ/uzx48cBGyD07Nkz2fLEYCQtISEhqS5v2bIl5cqVY/bs2TRt2pRt27axa9cuhg8f7spz8OBBWrZsScOGDZk4cSIVKlQgb968PP/88/z+++/p2KqUvfnmmzz//PM899xz3HnnnRQtWpSYmBhCQ0N97hVM6tSpUwCULVvWLT1//vwULlzYtTxR8eLF3d4nTm6SkXUrpZRSSuW4q/S2CA24VLokDtFLyt/fHz8/Py5fvuyWfvLkSbf3JUqUAOCtt96iefPmycoJDAzMkjrmyZOHHj16MG3aNMaPH8+cOXMoVqwY7du3d+VZuXIl586dY8mSJW69XufOnUuz/MDAQNc9WIkSEhI4c+aMW9r8+fNp166d2zDJzEwOkhhAHTt2jGrVqrnSY2JiiI6Odu1fpZRSSql/nU2b4Jtv8KtYMadrkm46pFBlmp+fH+XLl+fHH390S1+5cqXb+7p161KuXDn27NlDSEhIsldWPm+qd+/enD59mqVLlzJv3jy6dOniNn39hQsXAMib95/fHH788Ue2bt2aZtmVKlXip59+Ij4+3pW2Zs0aLl265JbvwoULye43mzFjRrLyAgICiImJSXO9t99+O3nz5k026+NHH32EMYbQ0NA0y1BKKaWUuups3Ajh4eDnR4KXe/lzO+3hUlmiW7duvP3227z++uuEhISwdu1aFi1a5JbHz8+PCRMm0LlzZy5cuMB9991HiRIlOHbsGF9//TU1a9bkscceS3NdSadJT+Tv78/NN9/sel+3bl3q16/P008/zbFjx9xmJwQ72cTgwYOJiIjgySef5LfffmPYsGFU9OFXk27duvHhhx/St29fevbsyf79+xk/fjxBQUFu+dq0acO7777LmDFjaNiwIatXr+bTTz9NVt4NN9zAhx9+yLRp06hXrx4FChSgTp06yfKVKVOGxx9/nHHjxhEYGEjr1q35/vvvGTp0KC1atKBly5Zp1l0ppZRS6qry1VfQti2UKwfFi2N8+JE6t9GAS2WJYcOGcfbsWcaOHcuFCxfo0KEDM2fOpGnTpm75OnXqxNq1a3nttdd46KGHiImJoWzZsjRu3DjZZBDexMfH07hx42TpJUqU4MSJE25pvXr14tlnn6Vq1ao0adLEbdlNN93ErFmzGDFiBB06dKBGjRqMHTuWRYsWsSONmW/atm3LmDFjmDx5MvPnzyckJIR58+Ylm0xk5MiRnDt3jjfeeINLly7RokULVq5cSa1atdzyDRw4kK1bt/LMM8/w999/U6tWLfbu3et13W+++SZlypRhypQpvPPOOwQHB9O3b19ee+01r8M9lVJKKaWuWuvXQ7t2UKECrF0L3bvDVRhwieezexSEhISY1IaW7dmzh+uvvz5L13m1TJqhLG2X9MmOc8ZTVFQUYWFh2boOlX7aLrmPtknupO2S+2ib5LC1a6F9e6hUCb78EsqUgbAwzpw5Q9FcMi28iHxnjEl9Nje0h0sppZRSSimVm3zxBXToAFWr2n+XLm3To6LYERVFWI5WLv004MolPHu2lFJKKaWUuuZ8/jl07Ag1asCaNVCqVE7XKNN0lkKllFJKKaVUzlu1Cu6+G2rWtMMI/wXBFmgPl1JKKaWUUiqnffYZdOoEN9xge7Y8ni+aYBK4/r3rCYwNZGfYzhyqZMZoD5dSSimllFIq56xYYYOtunXtPVsewdaluEv0WNKDn07+xN9xf+dQJTNOe7iUUkoppZRSOWPpUujcGRo0gNWroVgxt8XRl6K5d8G9fPF7oRFXAAAgAElEQVTLF1QtWpVC5uqbJVoDLqWUUkoppdSV98kn0KUL3HyzvX+raFG3xX+e+5O2c9vy/Z/fM+ueWfSu35uoqKicqWsmaMCllFJKKaWUurKWLIFu3SAkxAZbRYq4LT5w6gDhc8I5eu4oy7svp22NtjlU0czTgCu3CHP+RuVgHZRSSimllMpuCxdCjx5w223w3/9C4cJui7cd3UbbuW2JT4jny95fcluF23KoollDJ81QSimllFJKXRnz5tlgq3Fj27PlEWx9cfALQmeGEpg3kK//8/VVH2yBBlwKmDlzJiLC/v37M11WWFgYTZs2zYJaWQ8++CCVK1fOsvIiIyMRkSwrLz3r/fLLL6/4epVSSimlco05cyAiApo0sT1bhdwnwFjw4wLazm1L5aKV2fifjdQKrpVDFc1aGnApdQUMHz5cAy6llFJKXbs+/BB694bQUPvMrYIF3Ra/+827dF/SnUYVGrGhzwbKFy6fQxXNehpwKaWUUkoppbLPjBnw4IPQooV95lZQkGuRMYbBXwzmiVVP0LF2R1ZHrKZoYNGUy7oKacClfPLtt99y//33U6FCBfLnz0+tWrUYPHgwMTExXvMvXbqUG2+8kYCAAGrXrs3ChQuT5dm5cyd33303xYoVI3/+/DRp0oQNGzakWZcLFy7w/PPPU6VKFfLly0eVKlV49dVXSUhIcMu3fft2mjVrRmBgIOXLl2fkyJEYY3za3tjYWIYMGULlypXJly8flStXZsiQIcTGxrryREVFISLJpidNHKL566+/AriGML766quICCJCZGSkK/+6deto1aoVRYoUISgoiPr16zNt2rR01eXXX39FRJg8eTIvvvgiZcqUoVChQkRERHDhwgX2799PeHg4BQsWpHr16syaNSvZNvvSHt9++y2tWrWiRIkSFChQgKpVq/LII4/4tE+VUkopdQ2aNg0eeghatYLly6FAAdeiuIQ4+i7ry6ivRvFww4dZ3Hkx+f3z52Bls4fOUqh8cvjwYRo0aMCDDz5IoUKF2LVrFyNGjODgwYPMnz/fLe/+/ft54okniIyMpFSpUkyaNIlu3bpRsmRJ7rjjDgC2bdtGs2bNuOmmm5gyZQoFChRg8uTJtGzZko0bN3LzzTd7rUdcXBzh4eHs3r2bl19+mbp167J582ZGjhzJqVOneOuttwA4ceIELVq0oEyZMsyaNYuAgADeeOMNDh8+7NP2PvDAAyxcuJDBgwfTtGlTNm3axCuvvMLBgwf56KOP0rXvNm3aROPGjXnwwQfp378/ABUqVABsYHrffffRpEkT3n//fYKDg9m1axeHDh3KUF1GjRpFWFgYs2bNYvfu3Tz33HPkyZOH7du3069fP5599lkmTZpEnz59CAkJoU6dOj63x7lz5wgPD+fWW29l5syZFCpUiF9//ZWNGzema38opZRS6hrxwQfQvz+0aWOfuRUY6Fp0IfYCXRd3ZcVPKxgWOoxhocNy5D77K8IYoy+P180332xSs3v37uSJTxpjQjPxKuK8PNJjm8b6XsaTqVY7RTNmzDCA+fnnn33Kn5CQYGJjY83s2bONiJgTJ064loWGhhrAbNq0yZUWFxdnatWqZZo2bepKa9Gihaldu7a5dOmSW77atWubjh07utIeeOABU6lSJdf7Dz/80ABm3bp1bnV65ZVXjL+/v/nzzz+NMcYMHjzY+Pv7m0OHDrnynDt3zpQoUcLYwz5lP/zwgwHMsGHD3NJHjhxpALNz504THR1t1q5dawCzdu1at3yJ+/OXX35xpQHmpZdecsuXkJBgKlWqZG6++WYTHx+f4boYY8wvv/xiAHPHHXe45evUqZMBzOzZs11pp06dMn5+fiYyMtKV5kt7fPvtt27rTA+v50wW82wHlTtou+Q+2ia5k7ZL7qNtkkkTJxoDxrRrZ0xMjNuikxdOmsZTGxuJFDPp20npKjY3tQuw1fgQW+iQQuWT6Ohonn/+eapVq0ZAQAD+/v706tULYww///yzW97rrruORo0aud77+fnRuXNntmzZQkJCAjExMaxbt47OnTuTJ08e4uLiiIuLwxhDy5YtWb9+fYr1WLVqFZUqVeL22293fS4uLo7WrVsTGxvL5s2bAdur1KhRIypWrOj6bFBQEB06dEhzWxPXHxER4Zae+H7dunVpluGLffv2cejQIfr27UuePN5PxfTWpW1b94cC1q5dG4Dw8HBXWrFixShVqhRHjhwB8Lk9atSoQdGiRenfvz9z5sxxfV4ppZRSys1778Ejj0CHDvDxx249W0f+PkLT6U357uh3LOq8iAEhA3KwoleGDinMKuMy+fkw52+Ue3LM2RgKeUyZmRP69OnDmjVrGDFiBA0aNCAoKIgtW7bw6KOPcvHiRbe8pUuXTvb50qVLc/nyZf766y/i4uKIj49n5MiRjBw50uv6EhISvAYhx48f59ChQ/j7+3v93MmTJwE4evQoN954o9d6pOXUqVMAlC1b1i29TJkybsszK7GuicMLs6IuxYoVc3ufL1++FNMT2+3UqVM+tUeRIkVYu3YtI0eO5JFHHuHs2bPUqVOH4cOHc99996W6rUoppZS6RowfD08+CR072gccO9ciALuO76LN3DZEX4rm84jPCa0cmoMVvXI04FJpunjxIkuXLiUyMpInn3zSlf7DDz94zf/nn396TcuXLx8lS5YkJiaGPHny8Oijj9K7d2+vZaTU41OiRAmqVKnidRIOwPXMrrJly6ZYj7QUL14cgGPHjlGtWjVX+rFjx1x1AAh0fq25fPmy2+cTA6m0BAcHA/D7779nui6ZUbRoUZ/bo0GDBixZsoS4uDi2bt3KqFGj6NKlCzt37vQa4CqllFLqGjJ2LDz9NHTqBPPnuwVbG49spP1H7QnIG8D6B9dTv0z9dBcfFgZnzjRgx44srPMVoAGXStOlS5eIj49P1qs0c+ZMr/mPHDnC5s2bXcMK4+PjWbRoEbfeeit58uQhKCiIZs2asXPnTho2bJhicOVNmzZtWLJkCQULFnQNl/OmcePGvPHGGxw5coTrrrsOgPPnz7N8+fI01xEaan9tmT9/Pi+99JIrfe7cuQA0b94cgEqVKgHw448/0rp1a1e+zz77LFmZ+fLlSzajY82aNalcuTJTp07l4Ycf9nqjqK91yYyMtEfevHlp1KgRI0eOZNmyZezZs0cDLqWUUupa9uab8H//B/ffDx99BEmuG5fvW06XxV24rvB1rI5YTZViVXKwoleeBlzKZdWqVa6haomKFClCq1ataNSoEW+99RZly5YlODiY6dOnp9gzU7p0abp27crw4cMpWbIkkyZN4qeffmLSpEmuPG+//TbNmzcnPDychx56iLJly3LixAm2bdtGfHw8o0eP9lp2z549mTFjBnfeeSfPPPMM9evX5/Llyxw4cIBly5bx6aefUqBAAQYNGsTEiRNp3bo1kZGRrlkK8+dPe6rROnXq0L17dyIjI4mLi+P2229n06ZNjBw5ku7du1OvXj3Onj1L2bJlCQ0NZdSoUQQHB1OqVCnmzJnDgQMHkpV5ww03sHLlStq0aUOxYsUoV64c5cqVY9y4cdx77720aNGCAQMGULJkSfbs2cPx48cZPny4T3XJCr60x4oVK/jggw+45557qFKlCufPn2f8+PEUKlSIxo0bZ0k9lFJKKXUVev11eOEF6NIF5sxxC7amb5/Ow8sfpmHZhqzssZKSQSVzsKI5xJeZNa61V4ZmKcysUOflITo6OuvX5SFxVj1vrzp16hhj7Cx4bdq0MQULFjQlS5Y0jz76qFmxYkWyWfpCQ0NNkyZNzNKlS02dOnVMvnz5TM2aNc38+fOTrXf37t2ma9eupmTJkiZfvnymfPnypkOHDmblypWuPJ6zFBpjTExMjBk2bJipVauWyZcvnylWrJgJCQkxw4YNM7Gxsa583333nWnatKkJCAgw5cqVMyNGjDBDhw5Nc5ZCY4y5fPmyeemll0zFihVN3rx5TcWKFc1LL71kLl++bIz5p12OHDli2rdvb4oUKWJKly5tXnzxRTNlypRksxR+9dVXpmHDhiYgICDZrINffPGFCQsLM0FBQSYoKMjUq1fPTJ8+3ee6JLYPYKZMmeK2HcOGDTOA234xxphKlSqZnj17pqs99u7da7p06WIqV65sAgICTHBwsGnbtq3ZvHlzmvtTZym8dmm75D7aJrmTtkvuo23io1desbMRdu9uTJLrjYSEBPPq+lcNkZjw2eHm7KWzmV5VaKgx9eufznQ5WQUfZykUm1clFRISYrZu3Zri8j179nD99ddn7UrDnL9R7slnz57NFZNmKHfaLumTLeeMh6ioKMLCwrJ1HSr9tF1yH22T3EnbJffRNvHBiBEwbBj07AkzZ0JeO3guwSTw1KqneHfLu0TUi2Da3dPI55cv9bJ8YO/hOsOOHUUzXVZWEJHvjDEhaeXTIYVKKaWUUkop3xkDw4fbV+/eMH06+PkBcCnuEr0/7c3CXQt5pvEzjGk1hjxybT+JSgOu3CIqpyuglFJKKaVUGoyBoUPhlVegTx+YMsUVbEVfiqbTgk58+cuXvNHqDZ69/dkcrmzucMXDTRG5TkQWi8jfIhItIh+LSEUfPldJRJaKyCERiRGREyISJSJtveQNFJE3ROSok3eTiGR+OjellFJKKaWuVcbASy/ZYKtvX5g61RVsHTt3jLCZYaw/tJ4P7/lQg60krmjAJSIFgC+B2sADQC+gBrBWRILS+HhB4AQwBGgHPAScAz4TkXs98k4D+gFDgfbAUWC1iDTIok1RSimllFLq2mGMnYlw1Cjo3x/efx+cR8nsP7WfJtObsO/kPpZ3X06v+r2yfPW7d8P330NsbPLH6OR2V3pIYT+gKlDLGLMfQES+B34G+gNvp/RBY8wubJDlIiIrgV+APsDHTlp9oAfwH2PMDCdtHbALGAHcnbWbpJRSSiml1L+YMfYZW2+9BQMHwoQJrmBr29FttJ3blviEeL7s/SW3VbgtS1cdFwdvvAGRkZCQAMWLX333g13pGt8NbE4MtgCMMb8AXwMd01uYMSYO+BuI9VhHLLDAI998IFxEAjJWdaWUUkoppa4xxsDTT9tg67HH4L33XMHWmoNrCJ0ZSv68+fn6P19nebD1ww/QqBEMHgwdO8Itt0DBgvFZuo4r4UoHXHWAH72k7wJu8KUAEckjInlFpIyIvAzUBN7zWMcvxpgLXtaRD6ie/morpZRSSil1jTEGnnoKxo2DJ5+E8eNB7JC++T/Op93cdlQpWoWND22kVnCtLFttbKydcf7mm+HwYVi0CBYuhHyZn1k+R1zpIYXFgdNe0k8BxXwsYwzwjPPvc0A3Y8wXPq4jcXkyIvIw8DBA6dKliYqKSrECRYoU4ezZsz5WN3Pi4+Ov2LqU77Rd0ufixYupnlNZ4dy5c9m+DpV+2i65j7ZJ7qTtkvtc822SkECN8eMpv3QpRzp35kDHjrBuHQBLflvChAMTqFekHq/WeJWfvvuJn/gpS1a7f39BRo+uzYEDBWnR4k+eeGI/RYrEEhUFZ840ID4+/qprl5yYFt7bk5bTc/fbOOzwwDJAb+AjEbnfGLMiSVnpXocx5gPgA7APPk7tQXd79uzJ+ofeJq7P4wDSB+zmTtou6RMYGMhNN92UrevQB1TmTtouuY+2Se6k7ZL7XNNtkpAAjzwCS5fC//0f173+OteJYIxh8BeDmXBgAp1qd+Kj+z4iMG9glqzy8mU7+eGoURAcDJ9+Ch07lgZKu/IULWoffHy1tcuVDrhO472HqRjee6WSMcb8BvzmvF0hIlHAm0BiwHUK8DbNfLEky5VSSimllFKeEhLsLIRTp9pZCV97DUSIS4jj4eUPM2PHDPrf3J/32r2HXx6/LFnl1q32kV4//mifozx2LBT3Oibt6nSl7+Hahb3HytMNwO4MlrkV9/uydgFVnCnoPddxGdiPcjNz5kxEhP37k++auLg4RITIyMgrX7F/sezep1FRUURGRpKQkOCW/uuvvyIizJw5M9vWrZRSSqmrVEIC9Otng62XXnIFWxdiL9BpQSdm7JhBZGgkk+6alCXB1sWLdkKMRo3g1ClYsQJmzfp3BVtw5QOuZUAjEamamCAilYEmzrJ0EZE8QFPggMc6/IHOSfLlBboCnxtjLmWk4kpdTaKiohg+fHiygKts2bJs2rSJu+66K4dqppRSSqlcKT4e/vMfmD4dhg6FkSNBhJMXTtLyw5Z89vNnTLprEsPChiGS+WdhffMNNGxohxA+8ADs2gX/1suTKz2kcArwGLBURIZg77UaCRwB3k/MJCKVsEHUCGPMCCctEjsc8WvgGPYeroeAW7HP3QLAGLNDRBYA40TEH/ucroFAFaBnNm+fUrlaQEAAjRo1yulqKKWUUio3iY+3Y/pmz4bhw23ABRz5+wjhc8I5ePogizov4t7r7830qmJibPFvvw3ly8OqVRAenulic7Ur2sNljDkPtAB+AmYDc7EBUQtjzLkkWQXw86jfNuBG4F3gc+xshReBZsaY+R6r6gPMAF4BVgLXAW2MMduyepuuRZGRkV5/2XjwwQepXLmy633i8LXJkyfz4osvUqZMGQoVKkRERAQXLlxg//79hIeHU7BgQapXr86sWbPcytu/fz+9evWiSpUq5M+fn6pVqzJw4EBOnz6dbL0VKlRg+/btNGvWjAIFClCjRg0mT57s0/acOHGCgQMHUr58eQICAqhduzYffPCBa/mWLVsQEZYvX57sswMHDqRkyZLExtpHwc2fP58WLVpQsmRJChYsyE033ZRsu7zx3HeJwsLC3G4MvXjxIoMGDeLGG2+kYMGClClThg4dOrB3715XnsjISIYPHw6Av78/IuJqr5SGFM6ZM4f69esTGBhIcHAwvXr14ujRo255KleuTEREBPPnz+f6668nKCiIkJAQvvrqqzS3TymllFK5VFycvXFq9mw7a4UTbO06vovG0xrz+9nfWR2xOkuCra+/hgYN4M03oW9fe89WeoKtqCgYN25HputxpV3xWQqNMYeB+9LI8yseswoaY5bh47BDY0wM8LTzUj6Kj48nLi4uWVpmjRo1irCwMGbNmsXu3bt57rnnyJMnD9u3b6dfv348++yzTJo0iT59+hASEkKdOvY2vz/++IMKFSowbtw4ihUrxsGDB3nttddo164dmzZtcltHdHQ0PXr04KmnnmLo0KHMmDGDgQMHUqtWLe64444U6xYdHU2TJk2IiYkhMjKSKlWqsHr1agYOHMilS5d4/PHHufXWW6lVqxazZ8+mQ4cOrs9evnyZhQsX0qNHD/z9/QE4ePAg999/Py+88AJ58uRh/fr19O3bl5iYGAYMGJDpfXnp0iXOnj3LkCFDKFu2LKdOnWLixIk0atSIvXv3UqZMGfr27ctvv/3GtGnT+Oqrr/DzS32M9QcffED//v3p2rUro0aN4o8//mDw4MF88803bNu2jYIFC7rybtiwgX379jFy5EgCAwN5+eWXad++Pb/++itFixbN9PYppZRS6gqKi4NevWD+fDu274UXAPj68Ne0n9ee/Hnzs6HPBuqVrpep1Zw/D0OGwDvvQKVKsGYN3HlnVmzA1SEnpoX/d3rqKdiRiYg78bMe01zmj4+HNC6YXRo0sA+my6DatWtn+LOpqVatmquXJzw8nA0bNjB79mxmz55NREQEACEhISxbtozFixe7Aq7mzZvTvHlzVzm333471atXp1mzZmzfvt1tmvGzZ88yceJEV3DVvHlzPv/8c+bNm5dqwPXOO+9w6NAhfvjhB2rUqAFAy5YtOXPmDMOHD2fgwIHkzZuXXr168corr/D3339TpEgRAD777DNOnTpFr169XOUNHjzY9e+EhATCwsI4evQokyZNypKAq0iRIkydOtX1Pj4+nvDwcEqXLs28efMYNGgQFSpUoEKFCgDcdttt5M2b8mkeHx/Pyy+/TFhYGPPn/9NRXLt2bZo1a8b06dN54oknXOnR0dHs2LGDYsXspJ9lypThlltu4bPPPqNHjx7JyldKKaVULhUbCz172qcKjxkD//d/ACzbt4yui7tSsUhFVkespnLRyplazbp18NBDcOAAPPoojB4NSX7LvSZc6UkzVC72ySef8O2337q9Nm/enOly27Zt6/Y+MbALT9KHXKxYMUqVKsWRI0dcaZcvX+a1116jdu3a5M+fH39/f5o1awbAvn373MosUKCAW2AVEBBAjRo1OHz4cKp1W7VqFbfddhtVqlQhLi7O9QoPD+fkyZPs3m0nz4yIiODSpUssWrTI9dnZs2dTq1Ytbr31Vlfazz//TPfu3Slfvjz+/v74+/szderUZPXNjIULF3LbbbdRtGhR8ubNS1BQEOfOncvQOvbt28fx48fp2dP99samTZtSqVIl1jkPOEzUuHFjV7AFULduXYA097NSSimlcpHYWOje3QZbb73lCrambZtGpwWdqFe6Hl/1+SpTwda5c/DYY7YvwRhYuxYmTLj2gi3QHq6sk4meJSDFBx/HXMEH7N54441Ur17dLc1ziGFGJL1AB8iXL1+K6RcvXnS9f/HFF3n33XcZOnQot99+O4UKFeK3337j3nvvdcvnrSywQZdnPk/Hjx9n//79riGBnk6ePAlApUqVaN68ObNnz6Zv376cOXOGlStX8vLLL7vynjt3jlatWlGgQAFGjx5NtWrVyJcvH5MmTWL69Omp1sNXy5cvp2vXrjzwwAMMGzaM4OBg8uTJQ7t27dLcVm9OnbKPpStbtmyyZWXKlHEtT1TcY57WgIAAgAytWymllFI54PJl6NrVPll47Fh46imMMby24TWGrB1CeLVwFndZTMF8GY+MvvjC3qN16BA8+SS8+ioEBWXhNlxlNOBS6RYYaJ8ofvnyZVfwBP8EJ1ll/vz59O7dmyFDhrjSzp07l8on0q9EiRKUKlWKd955x+vyWrVquf7dq1cv+vXrx6FDh1i6dCmXL1926xnatGkThw4dYsOGDTRt2tSV7kvQGhgYyOXLl5Olnzx5khIlSrjez58/n+rVq7tNehEbG5ssMPJVYgB17NixZMuOHTtGSEhIhspVSimlVC506RJ07gzLl8P48fD448QnxPPUqqeY8O0EIupFMP3u6fj7ef8hOi3R0fDcc/D++1CjBmzYAE2aZPE2XIV0SKFKt0qVKgHw448/utLOnDnDxo0bs3Q9Fy5cSNbzNGPGjCxdR5s2bdi7dy8VK1YkJCQk2Stp72Lnzp0JDAxk7ty5zJ8/n+bNm7vNLHjhwgUAtzqfPn2apUuXplmPSpUq8eeff3LixAlX2oEDB5INE7xw4UKye7Jmz56dbHKTxJ6nmJiYVNdbq1YtSpcu7Xb/FsDGjRs5dOgQoaGhadZdKaWUUleBixfhvvtssPXee/D441yKu0T3Jd2Z8O0Enm38LLPumZXhYOvzz+HGG2HKFHj2Wdi5U4OtRBpwqXRr27YtRYoUoV+/fqxYsYIlS5a4pnfPSm3atGHWrFlMnDiRzz//nAEDBmR5UDdo0CBKlSpFs2bNmDx5MmvXrmXFihW8+eabdOzY0S1v4cKFufvuu3nvvffYvHmz22QZYCf1KFy4MI8++igrV65k4cKFhIaGEhwcnGY9OnfujIjQs2dPVq9ezdy5c+nYsWOyzyYGiIMGDeKLL75gzJgxDB06NNkMgTfccAMAb731Ft988w1bt271ul4/Pz9GjBjBmjVriIiIYNWqVUybNo17772XGjVq0KdPnzTrrpRSSqlc7uJF6NQJVq6EyZPhkUeIvhRNu4/asWj3It5s9SZvtH6DPJL+0ODMGTspRni4HTb49dfwxhuQP382bMdVSgMulW5FixZlxYoV5MmThy5duvDiiy/y+OOPpzobYEa8++673H333bz00kt07dqVs2fPMm/evCxdR5EiRdi4cSPt2rXj9ddfJzw8nP/85z8sXbrU6/b06tWLP/74g4CAAO6//363ZSVLluSTTz4hPj6e+++/nxdffJG+ffu6ZmJMTfXq1Vm8eDG///4799xzD2PGjOHtt9+mZs2abvn69evHSy+9xIIFC+jQoQMrV65k+fLlrpkTE7Vv355HHnmEiRMn0rhxY2655ZYU1/3www8ze/ZsfvjhBzp27Mhzzz1Hq1atWLduXZYH0UoppZS6wmJioGNHWL3adj/178+xc8cInRnK+kPrmd1pNs/c/kyGil650vZqzZxpZ5Tfvh0aNcra6v8biDEmp+uQ64SEhJiUegQA9uzZw/XXX5+1K01h0oyzV3DSDOU7bZf0yZZzxkNUVJTbQ6JV7qDtkvtom+RO2i65z7+iTS5csMHWF1/AtGnQpw/7T+2n9ezWHD9/nMVdFtOmept0F3v6tH0i0ocf2oBrxgy4Urd956Z2EZHvjDFpbrlOmqGUUkoppdS/zfnzcPfddj72GTPggQf47o/vaDu3LQbDlw98ya3lb027HA9Ll8KAAfDXX/ZhxkOGgHPruEqBBly5hUfPllJKKaWUUhly/jy0bw/r19tuqIgI/nfgf9y78F5K5C/B570+p2aJmmmXk8SJE/DEEzBvHtSvD599BjfdlE31/5fRe7iUUkoppZT6tzh3Dtq2tcHW7NkQEcH8H+dz10d3UbVYVTY+tDHdwdaSJVCnjn1O8vDhsGWLBlvpoT1cSimllFJK/RucPWuDrc2b4aOPoGtXxm0ex6DVg2heqTlLuy2laGDRtMtxHD8Ojz1mA62GDeF//4N69bKx/v9S2sOllFJKKaXU1S462s7NvnkzzJuH6dKFF9a8wKDVg7j3+ntZHbHa52DLGFiwwPZqLV0Kr75qi9VgK2O0h0sppZRSSqmr2d9/22Dru+9g4UJiO3ag39I+zNo5iwE3D2BCuwn45fHzqahjx+CRR+CTT+DWW2H6dBt4qYzTHi6llFJKKaWuVmfOQKtWsG0bLFrE+fbh3L+U8AEAACAASURBVLPgHmbtnMXwsOFMvGuiT8GWMTBnjg2uPvsMxoyxDzHWYCvztIdLKaWUUkqpq9GpU9C6NXz/PSxZwsk7b+euD+/k2z++ZfJdk+kf0t+nYv74A/r3hxUroHFj26tVu3Y21/0aogFXLpHCc4+VUkoppZRK7uRJ27O1axd88gmHm9YlfEZTfjn9C4s7L6bT9Z3SLMIYmDULBg2CS5fg7bft1O9+vo0+VD7SgEsppZRSSqmryYkT0LIl7N0LS5fyY8MKhE9rzPnL5/m81+c0r9Q8zSKOHLG9Wv/9LzRrBtOmQY0aV6Du1yC9h0u5bNq0iS5dulCuXDny5ctHiRIlaNWqFbNmzSI+Pj5b1hkVFUVkZCQJCQnZUn5axo0bx8cff5wsPTIyEhHJgRolFxYWRlhiF6hSSimlrm1//QUtWsC+fbBsGRuuD6LZjGYYY9jQZ0OawZYxMGWKvTdr3ToYP96OsNJgK/towKUAG3g0adKEU6dO8frrr7NmzRqmT59OzZo1GThwICtWrMiW9UZFRTF8+PBcF3D17duXTZs25UCNlFJKKaVScPy4Dbb274fly1laMYbWc1pTKqgUGx/aSN3SdVP9+KFDdjLDhx+GkBD44Qd4/HHIoxFBttIhhYr169fz9NNP89hjjzF+/Hi3ZR07duTpp5/m/PnzOVS7f8TGxpI3b94r0vNUoUIFKlSokO3rUUoppZTyyZ9/2mDrl19gxQqmFDnAgIUDCCkXwsoeKwkuEJziRxMS4P334bnn7PtJk2zQpYHWlaG7WTF69GiKFy/OmDFjvC6vVq0a9ZI86W7Lli20bNmSggULEhQUxJ133smWLVvcPvPggw9SoUIFtm/fTrNmzShQoAA1atRg8uTJrjyRkZEMHz4cAH9/f0TEFUz9+uuviAgTJ07kueeeo1y5cgQEBHDmzBn++usv+vfvT82aNSlQoADXXXcdPXr04Pfff09W9507d9KpUydKlChB/vz5qVWrFqNGjQKgcuXKHDp0iLlz57rW/eCDD7rq5hnYRUdH89hjj1GuXDmCg4OpVasWY8eOxRjjyhMVFYWIsGzZMh577DGCg4MpWbIkERERnDlzxtcmSdO+ffvo1KkTRYsWJX/+/DRq1IhVq1Ylyzdv3jxq165NYGAgdevWZdmyZTpEUSmllLraHD1qZ1j79VfMZ58x0u9rHl7xMK2rtebL3l+mGmwdPAh33mmfrdW4Mfz4IwwYoMHWlaQ9XNe4+Ph4oqKiuOeeewgMDEwz//fff09oaCg33HADM2fOREQYPXo0oaGhbN68mfr167vyRkdH06NHD5566imGDh3KjBkzGDhwILVq1eKOO+6gb9++/Pbbb0ybNo2vvvoKPy9T4rz66qvccsstfPDBB8THxxMYGMjhw4cJDAxk1KhRlCxZkj/++IO33nqLJk2asHfvXtd2bNmyhbCwMKpXr87YsWOpUKECP//8M99//z0An3zyCe3ataN+/fpERkYCULJkSa/bnZCQwF133cW2bdsYMWIE1apVY+3atTz99NP89ddfvPb/7N13fI7X+8Dxz4kMIvamIlp7q01LYtUeJWpTs9QM0RixN0FrU0WN2r5K1BZ7a6gRNRKjZhIhiSzJ+f3xkJ9E8IQkT8L1fr3yktz3uc99PbnzeOXKOec6EyfGaN+/f38aNWrE6tWruXLlCkOGDCFVqlQsX77cqOfyNnfv3uWrr74iXbp0zJkzhwwZMjB37lwaNmzItm3bqF+/PgC7d++mXbt2NGnSBDc3N3x9fRkwYAChoaEUKlTog+MQQgghRBK4exccHOC//4jc7k6/oPXMOz2PDqU6sKTJEixSWcR5WVQUzJ0LLi5gbm5Yt9W1KySTJeqfFEm4EsiAAeDp+f7Xv7w29sBDZGQao0tzlikDs2bF776+vr6EhISQL18+o9qPHTsWKysr9u7dS8aMGQGoU6cOdnZ2jBkzJsZ6qMDAQObNm4eDgwMA1atXZ9euXfzxxx84ODjEmLZXqVIlzM1f/3HMkSMHmzdvjjHaVLhwYX7++eforyMjI6lWrRq2trb89ddfNG9uKIM6ePBgsmTJwvHjx7G2tgagZs2a0deVLVsWKysrsmbNSuXKld/6urdv387hw4dZunQpnTt3JjAwkGbNmhEcHIybmxtOTk5kzfr/f12qXr06s2fPBqBu3bpcuXKFX3/9NTpJ/RAzZszg8ePHHDt2jAIFCgDQoEEDihUrxvDhw6MTrlGjRlGsWLEY37+SJUtSrlw5SbiEEEKIlODOHcM0wnv3CHP/k/YP57Lh0gacqzozufZkzFTcw1RXrxqSq0OHoH59w3TCvHmTOHYRTQYTRbwcPHiQRo0aRSdbAOnTp6dJkyYcOHAgRltra+voZAvAysqKggULcuvWLaPv16xZszgTlPnz51O6dGlsbGwwNzfH1tYWMEy1A3j27BlHjhyhXbt20cnWhzh48CBmZma0adMmxvH27dsTHh7+WoGNhg0bxvi6ZMmShIWF8eDBgwSJpXLlytHJFkCqVKlo06YNnp6ePH36lMjISE6fPk2LFi1ifP++/PJL8ufP/8ExCCGEECKR3b5t+Ev8/fsE/bmRej7j2HBpA2513ZhaZ2qcyVZkpGEvrVKlDAUxli4Fd3dJtkxNRrgSSHxHlmJ708bHgYEhpEuX7sM6f4uXa5tu3rxpVHt/f39y5cr12vGcOXPy+PHjGMcyZcr0WjsrKytCQ0ONji+ue82ePZt+/frh5OTEtGnTyJQpE1FRUVSuXDm678ePHxMVFZVghS/8/f3JnDkzVlZWMY7nzJkz+vyrMmfOHOPrl9fF57W/LZayZcu+djxnzpxorXn8+DEhISFERESQPXv219rlyJHjg2MQQgghRCK6edMwjdDPD9/Nq6l9ZQgXH11kZfOVtCvVLs5LvLygSxc4dgwaN4YFCyB37iSOW8RJEq5PnLm5Ofb29uzevZuwsLDXEorYMmfOzP379187fv/+/deSjIQQ1+jWmjVrqFWrFm5ubtHHvL29Y7TJlCkTZmZmcRbSeB+ZM2fG39+f8PBwLC0to4+//F5kyZIlQe5jbCxvegZKKTJnzoy1tTUWFhY8fPjwtXYPHjyIHhEUQgghRDLj42NIth4/5taGJdS40JdHwY/Y1mYb3xT45rXmz5+DmxuMGgVp08LKldC2razVSk5kSqHAxcUFPz8/nJ2d4zzv7e0dXWiiRo0auLu7ExgYGH0+MDCQrVu3UqNGjXjf+2WCFxISYvQ1z549w8Ii5gLRpUuXxvja2tqar776ipUrV761bysrK6PuXaNGDaKioli/fn2M46tWrcLS0vKda8AS0ssCJT4+PtHHIiMjWbt2LWXLliVdunSkSpWK8uXLs3HjxhhVFM+cOfNaciqEEEKIZOLGDahRA5484dKa2ZT37E1QeBD7O+2PM9m6eBGqVjUUxmjQwPB1u3aSbCU3knAJqlevzowZM5gzZw516tRh1apVHDp0iD///JP+/ftTokSJ6F/SXV1dCQkJoVatWmzcuJFNmzZRu3Ztnj17xsiRI+N972LFigHg5ubGiRMnOH369DuvqVevHjt37mTixIns2bOHYcOGsWbNmtfaTZ8+HT8/P6pUqcKKFSvYv38/S5YsoW/fvjHuf+jQIbZt28bp06djJDGvql+/Pl999RU//PADs2bNYt++fQwcOJBff/2VQYMGxSiYYazOnTu/VwGNgQMHkjFjRurUqcPq1avZtm0bjRs35t9//2XChAnR7caMGcPFixdp3rw527dv5/fff8fR0ZGcOXNiFqsWrLm5OV27do13LEIIIYRIINevG9aYBAVxbNl4Kp7tRVrLtBzpcoQKeSrEaBoRARMmwJdfGrblWrsWNm6EFysdRDIjCZcAYMCAARw+fJiMGTMyePBgatasSefOnbl8+TILFy6kcePGAJQqVQoPDw/Sp09Pp06d6NChAzY2Nhw4cCBGSXhjNWrUiN69ezNv3jyqVKlChQoV3nnNyJEj6dmzJzNnzqR58+acP3+enTt3vtauQoUKHDlyhLx589K3b18aNGjAtGnTYqzrmjRpEoULF6ZVq1ZUqFAhujx8bGZmZri7u9OpUyemTJmCo6Mj7u7uzJgxI0aSEx/BwcHvtZ4qd+7cHD58mOLFi9OrVy9atmyJv78/7u7u1KtXL7rdy+T58uXLNG/enClTpuDm5kbOnDnJkCFDjD4jIyOJjIx8r9chhBBCiA909aphZOvZM7YvHEz1c/35IvMXHO1ylEJZYlYWPn8eKlWCESOgWTO4dAlatZJRreRMvTrdSBiUL19ev22k5fLlyxQtWjRB7/nmohmBiVo0Q7yfhHguefLkoX///gx5ue17Erhz5w4FChRg+PDhuLq6Jtl9E+M9E5uHh4ds6JwMyXNJfuSZJE/yXJKfJHsmV64YSr+Hh7NiRmc63phOjXw12NJ6CxlS//8fSMPDYdIkGD8eMmeGefOgRYvEDy+5SU7vFaXUGa11+Xe1k6IZQpjA1atXCQ0NpXfv3ol2j5CQEJycnKhduzZZs2blxo0bTJ06FWtra7p165Zo9xVCCCGEkby8wMEBHRnJzAmNGXRjOi2KtmDltytJbZ46utnZs/D994bRrbZt4ZdfIAnrdYkPJAlXMhF7ZEt83AoWLIifn1+i3iNVqlTcv3+fPn364OfnR9q0afn6669Zv359nOX2hRBCCJGELl2CmjXRwDDXKky+t5Re5Xsxu/5sUpmlAiAsDMaNg8mTIVs22LIFmjQxbdgi/iThEuIjZWlpyebNm00dhhBCCCFiu3ABatUiykzxg1MhFvv/yVj7sYyoPiK6oNapU4ZRrYsXoVMnmDkT4tjiVKQAUjRDCCGEEEKIpHL+PDg4EGmmaP1jDpaEHGFho4W41nBFKUVoqKHMe+XKEBAA7u6wbJkkWymZjHAJIYQQQgiRFDw9oXZtnltZ0LBrGg5whY2tNtKsSDMAjh2DLl0MS7u6djVsaByrsLBIgSThEkIIIYQQ4hX29hAQUAZPzwTs9OxZqFOH8NQWOHSK4qK1P7va7KJ6vuqEhICrK8yYAXnzws6dULduAt5bmJQkXEIIIYQQQiSmM2egdm1C01pRqe0zfLOm41C7PZTMUZLDhw2jWlevwg8/wJQpkD69qQMWCUnWcAkhhBBCCJFYTp2CWrUITmtJ6e8eE2abm6NdjvK5TUn694fq1SEiAvbuhfnzJdn6GEnClUzY29snm03chBBCCCFEAjhxAmrX5qmNBSVaPSJT0bIc7nIYb898lCpl2E/rxx/hn38Mex+Lj5MkXEIIIYQQQiS0Y8fQdergb2NO8Va+FC1Xj/8138so56w4OIBScOAAzJ4NNjamDlYkJkm4RLRjx47RqlUrcufOjaWlJVmyZKFOnTosX76cyMhIU4f3Vj4+PiilWLZsmalDeaNly5ahlMLHxyfe1yqlGD16dILHJIQQQohEcOQIum5dHqYzo9R3/tSs3pF+Wf+kcrm0zJ8PAwYYqsNXr27qQEVSkIRLADBr1iyqVauGv78/U6ZMYc+ePfz2228UKlSIXr16sW3bNlOHKIQQQgiR/B06hP7mG+6mg7Ktn9CyuiuW7suoX88cKys4dMiwibG1takDFUlFqhQKDh48iJOTE3369OGXX36Jca5p06Y4OTkRHBxsouiEEEIIIVIIDw90w4bcygCV2wbTOM9GNvb9lrt3wdkZxoyBNGlMHaRIajLCJZg8eTKZM2dm6tSpcZ7/4osvKFWqFACPHj2iZ8+eFCpUCGtra/LmzUvbtm3577//YlzTuXNn7OzsXusrdnGQoKAg+vbti62tLVZWVuTIkYPatWvj5eUV3WbOnDlUqVKFzJkzkzFjRipXroy7u/t7vdbRo0ejlMLLy4tvvvmGtGnTYmtry9KlSwFYsWIFRYoUwcbGBgcHB65fvx7j+oiICEaMGEGJEiWwtLTEzs6OESNGEBEREaPdjRs3aNiwIdbW1mTLlo3+/fsTFhYWZ0yLFy+mdOnSpE6dmqxZs9K1a1f8/f3f6/XFxdfXl169epEnTx6srKwoUqQIixYtitHm5XTHgwcP0qxZM2xsbMiSJQs//vgjISEhCRaLEEII8dHatw/doD43MkRSpWVqCl27xmKnb0mXDo4ehalTJdn6VMkI1ycuMjISDw8PmjVrRurUqd/Z3t/fn9SpUzNp0iSyZcvG3bt3cXNzo1q1anh5eRnVx6sGDhzIn3/+ycSJEylYsCB+fn4cOXKEgICA6DY+Pj5069YNOzs7nj9/ztatW2nUqBHbt2+nfv368X7NAI6OjnTv3p3Bgwczb948unTpwtWrV/Hw8GDy5MlERETQv39/2rZty4kTJ6Kv69SpE+vWrWPQoEHUqlWLY8eOMX78eG7cuMHq1asBCA8Pp06dOoSEhDB37lyyZ8/OwoUL2bRp02txuLi44ObmRr9+/Zg2bRr//fcfI0aM4MKFCxw9epRUqVK91+t76enTp1SrVo2QkBBGjx5N/vz52blzJ7169SIsLIy+ffvGaN++fXtatWpF7969OXnyJGPHjiU4ODhZr40TQgghTG7PHqIaN+JqxiiqV2tM5LpVHPFNzdChMHIkxPPXI/GRSfKESymVF5gJ1AEUsAcYoLW+9Y7rygM9gOqALeALHAJGaK29Y7X1AfLF0U1zrfX/PvQ1xGXAgAF4fsB25C+vjV0aPjIy0uhfusuUKcOsWbPidV9fX19CQkLIly+ub9frChcuzM8//xwjvmrVqmFra8tff/1F8+bN43X/Y8eO0a5dO7p27Rp9LHYf06dPj/48KiqKWrVq8e+//7JgwYL3TricnZ3p2LEjAOXLl2fr1q0sXLgQb29v0r/YAOPevXv079+fmzdvki9fPi5cuMAff/zBqFGjGDRoEOnSpaNu3bqkSpUKV1dXXFxcKFWqFMuXL+fGjRscO3aMypUrA1C/fn1KliwZIwYfHx+mTZvGqFGjGDlyZPTxQoUK8dVXX7F161aaNWv2Xq/vpZ9//pmbN2/yzz//ULBgQQBq165NQEAAY8aMoVevXpib//9/Aw0aNIj+ftetWxelFCNHjmTYsGEUKlTog2IRQgghPkq7dhHVpAnHM6Sjfra5PN3QihIlYKc7lCtn6uBEcpCkUwqVUtbAPqAI0AnoABQE9iul0r7j8tZAceAXoD7gAnwJnH6RxMW2E6gS6+NAAryMT978+fMpXbo0NjY2mJubY2trC8CVK1fi3VeFChVYtmwZEydO5PTp03FWQzxz5gyNGjUiR44cmJubY2Fhwe7du9/rfi+9mqhlypSJ7NmzU7ly5ehkC6BIkSIA3L59GzCsdQPDKNCrXn594IDhx+vYsWPkzZs3OtkCMDMzo1WrVjGu2717N1FRUbRr147nz59Hf1SqVIn06dNH3+9D7Nixg0qVKpE/f/4Y9/jmm2/w8/Pj0qVLMdrHjrF169ZERUVx8uTJD45FCCGE+Ojs2EFk40b8kqYBNZ5d5NllR0aOhDNnJNkS/y+pR7i6A58DhbXW1wCUUueBq0BPYMZbrp2itX706gGl1BHA+0W/I2O199VaH0+owN8lviNLsb0c2fLw8IhxPDAwkHTp0n1Q32+TJUsW0qRJw82bN41qP3v2bPr164eTkxPTpk0jU6ZMREVFUblyZUJDQ+N9/9mzZ5MzZ05+++03hg8fTubMmenYsSMTJkzA2tqa27dvU6tWLYoVK8bs2bOxtbXF3NwcV1dXLl++HO/7vZQpU6YYX1taWsZ5DIh+XS/XVeXKlYuoqKjodjlz5oxx/t69e+TIkeO1e8Y+9vDhQwAKFCgQZ4x+fn7GvZi3ePjwIdeuXcPCwsKoe8SO8eXXsdfoCSGEEJ88d3ceNOtKJ/Pl7AxoQ/FSEaxcrihTxtSBieQmqROuJsDxl8kWgNba+0Xi1JS3JFyxk60Xx24qpR4BeRIj2E+Bubk59vb27N69m7CwMKysrN7afs2aNdSqVQs3N7foY97e3q+1S506NeHh4a8d9/PzI0uWLNFf29jYMGnSJCZNmsTNmzfZsGEDLi4uWFpaMmXKFHbs2MGTJ09Yt24dn332WfR1z549e5+X+0EyZ84MwP3798mePXv08fv37wNEv65cuXJx8eLF165/8OBBjK9ftt+1a9dryd6r5z9ElixZyJ49e4xpoK8qXLjwazEWL148xtcAefLIW0wIIYSItnUra5utpBfnCYjIxLCRoYwekZo3/H1TfOKSukphceBCHMcvAsXi25lSqiiQHYhrqKOxUuqZUipMKXVcKfVhi2E+Yi4uLvj5+eHs7BzneW9vb86fPw8YEp3YoyUvK/y9Kl++fDx48ABfX9/oY9evX3/rNMB8+fIxaNAgSpYsyYULF6LvB8S457///suRI0eMfHUJp0aNGoAh6XzVqlWrAKj+YvfCKlWqcPv2bY4f//8B1qioKNatWxfjujp16mBmZsatW7coX778ax/58+f/4Jjr1auHl5cXtra2cd4j9uhp7BjXrFmDmZkZFStW/OBYhBBCiI/B/WXutGwaRuuotZjZPuXkqSgmjJFkS7xZUo9wZQYex3HcH3j9T/xvoZQyBxYAj4AlsU5vBU5hmG6YA+gDbFZKddBar4xv0B+76tWrM2PGDJycnLh8+TKdO3fG1taWx48fs3fvXn799VdWr15NqVKlqFevHlOmTGHixIlUrFiRffv2sWHDhtf6dHR0xNXVlXbt2uHk5ISvry+TJk0ia9asMdpVqVKFJk2aULJkSWxsbDhw4ADnzp2jU6dOgKHAg7m5OR07dmTQoEHcu3ePUaNGYWtrG2NaX1IoXrw4bdq0YfTo0QQHB+Pg4MCxY8cYN24cbdq0iS6d36lTJyZPnsy3337LxIkTyZ49OwsWLODp06cx+vviiy/46aef6NOnD1euXKFGjRqkTp2a27dvs3v3brp164aDg0Ocsfj4+JA/f35GjRrF6NGj3xjzwIEDWbt2LV9//TUDBw6kcOHCBAcH4+XlxaFDh9iyZUuM9tu3b8fZ2Zm6dety8uRJxowZQ8eOHaVghhBCiE+e1rBq4DEG/FyJp6Tjq9Yb2bO8GVaWH1ZRWHz8TFEWXsdxTL1HP3OAqkBDrXWMJE5rHaPWtVJqM3AcmATEmXAppXpgqIJIjhw5XltL9aoMGTIQGBj4HiG/2ctiEbH7jYyMTPB7xaVr166UKFGCuXPnMmjQIPz8/LCxsaFs2bLMmjULe3t7AgMDGThwII8ePWLGjBmEhYVRrVo1Nm7cSKlSpQgLC4uONUeOHKxYsYJx48bRrFkzChQowPjx43Fzc4vxmipXrsyaNWuYPHkyz58/x87OjkmTJtGlSxcCAwOxtbXl119/ZcKECTRp0iQ6ydizZw+HDx+O7icoKAgwrLd62/fr5V5YgYGBMarzaa2JiIiIce3L0bVnz55FH58zZw558uRhxYoVTJs2jVy5cjFgwACGDh0a49rNmzczePBgevfujbW1NY6OjtSqVYsBAwYQFBQU3Xbo0KHY2dmxePFi5s6di1KKPHnyUKNGDXLlyhWjz1e/vy/Xf2XMmPGtr9fMzIydO3cyZcoUJk+ezN27d8mQIQMFCxakSZMm0de+XKe2aNEiZs+ezfz587GwsKBTp05MmDDhg38GQ0ND3/qeSghBQUGJfg8Rf/Jckh95JsmTPJfkJSCgTPTWOQB+fpbMGZ4RjytVKGZ5nNoum+hpX59jRw+ZNtBPUEp8ryit48p/EulmSj0A/qe17hnr+DzAUWudzch+JgE/AZ201iuMvGYIMAXIrbW+97a25cuX16dPn37j+cuXL1O0aFFjbms0UxXNEO/H1M9l0aJFDB8+nJs3b2Jtbf3B/S1btozvv/+eq1evvrGIx4dIjPdMbB4eHq9tqyBMT55L8iPPJHmS55K82NtDQEAAf/+dkZUroV+vUEKCoWvGEZTbZEcXhz6mDvGTlZzeK0qpM1rr8u9ql9QjXBcxrOOKrRhwKY7jr1FKDcdQEr6fscnWy0tf/Jt0GaYQieTAgQMMHDgwQZItIYQQQsTi6YlFuKJx44y4u0MVztAnd1fS/zmKRuXamDo6kcIkdcL1JzBdKfW51voGgFLKDqiGIYl6K6VUP2A8MFxrPdvYm75Y7+UI3NJa33+PuBNdShsaFab1slCHEEIIIRLeg/BMXA3Jg8WuCNxwppzdPMzdt1Kt2DemDk2kQEldpXAx4ANsUUo1VUo1AbYAt4GFLxsppfIppZ4rpUa+cqw1MAvYAexTSlV+5aPYK+3aKKXWKKU6KqUcXly3HyiHYRqiECKWzp07o7VOlOmEQgghREoREQH9+oFXSD5yWdzgXERRKhWYT9Z9hyXZEu8tSUe4tNbBSqmawExgBYZpfnuBAVrroFeaKiAVMRPCei+O13vx8aoDgP2Lz70xlIqfhqEq4jMMFQvraa13JuTrEUIIIYQQH4cHD8DREQ4dgqo2m9gf1IpTha3Iu+8ctrmLmDo8kYIleZVCrfUtoMU72vgQq3Kh1roz0NmI/o8DNd87QCGEEEII8Uk5cQJatAB/vyhm5unHgP/mst3WhopHLpE1S15ThydSuKSeUvjRSMrqjkKkZPJeEUIIkZwtXgzVq2ssgv04GPElHf3m0rfMlwz33SzJlkgQknC9BwsLC0JCQkwdhhApQkhICBYWFqYOQwghhIghLAx69oQePeBr80OcCSjIjeIX2P/XPP7xXkJaldHUIYqPhCRc7yF79uz8999/PHv2TP56L8QbaK159uwZ//33H9mzZzd1OEIIIUS0//4D+6+fs2gR/MRkFps74PKDNcV3n6OFfS9Thyc+Mkm+hutjkD59egDu3r1LREREot4rNDSU1KlTJ+o9RPzJczGOhYUFOXLkiH7PCCGEEKZ2+DC0bBxK0JNI1vEddyttYlTvZsz97nfSWaUzTi8ogAAAIABJREFUdXjiIyQJ13tKnz59kvwS6eHhQdmyZRP9PiJ+5LkIIYQQKYvWMG/yUwYMtya/vsXirK2Y3PwCrbrMYnmlfij1Sr22MmUICggwXbDioyIJlxBCCCGE+KiFPNP0qn2V5ccK0VBto1iNzvRpaMkfrQ9SNW9VU4cnPnKScAkhhBBCiI/WTQ9vWjQO50xQYX7MNp2drYYQWrEmp1qsJntaWWMsEp8UzRBCCCGEEB+fiAj2dV1FeQcbrgblpE2Nrszr5cx33w5jZ/udkmyJJCMjXEIIIYQQ4qOiT5xkZrMDON934ou0t4ho14Idn/uwtfk2GhZqaOrwxCdGEi4hhBBCCPFxCAoi+KexdJtXljU4U67occ40q8OXdoXY53iG/JnymzpC8QmSKYVCCCGEECLl276dG4XrUXVeO9byHYWaLuRMqyr0rNqOI12OSLIlTEZGuIQQQgghRMr18CEMGMCOP/xpa+ZOpI0VGVu357bd/1jeaDkdS3c0dYTiEycjXEIIIYQQIuXRGpYtQxcpysR1X9CAv0hjF0ZQ15JkLXWa492OS7IlkgUZ4RJCCCGEECnL9evQsyeBe0/QOctWNkXa81m1Q9ypUY9vS9fjtya/kSF1BlNHKQQgI1xCCCGEECKleP4cpk6FkiW5cvwxlXLeZEtADbI2n8jdOg5MbziWDY4bJNkSyYqMcAkhhBBCiOTvzBno1g08PdlaaTztLw1Fh4WTqlN9LIqdx6Plfr7O97WpoxTiNTLCJYQQQgghkq/gYBg8GCpWJOr+Q0Y5XqLJieFY5rhNYKdCVK0extmeZyXZEsmWjHAJIYQQQojkadcu6NkTfHwI6DyADvemsm29BZmrbMW3Zitc7AcwruY4zM0S9ldaDw/w8PAE7BO0X/FpkoRLCCGEEEIkL76+4OQEK1ZA4cJcXHaK5hPKc8M7ijRNnXleaTFbvl1Lk8JNTB2pEO8kCZcQQgghhEgetIZVq2DgQHjyBFxd2VBkBJ17WIBlIJEd6lO4UjAbHM/wReYvTB2tEEaRNVxCCCGEEML0vL2hfn3o0AEKFCDy1FmGRozFsZ0lqXJeJvj7InRtVoSjXY5KsiVSFBnhEkIIIYQQpvP8OfzyC7i6gpkZzJ6NX6tetO2Qil27wLrKCsK+6cNvTWbxfdnvTR2tEPEmCZcQQgghhDANT09DqfczZ6BRI5g3D0+/vDSvpLn933PMmv5Izpp72NjqAGVyljF1tEK8F0m4hBBCCCFE0goJgTFjYPp0yJIF1q4FR0dW/6Ho1k1DGn8iOzWgaa1cLGt2hoypM5o6YpEM2NvbExAQgKenp6lDiRdZwyWEEEIIIZLO3r1QsiRMmQKdOsHlyzz/thVOgxTt2gG5TxPatQRTOrdg83ebJdkSAAQGBnLr1i2ioqJMHUq8ScIlhBBCCCESn78/dOkCtWuDUrBvHyxZwsPnmalTB2bOBPMq80jXvTn7ev/BkGpDUEqZOmphYpGRkSxevJiCBQvi7e1NYGCgqUOKN5lSKIQQQgghEo/WhimD/fsbkq6hQw0FMtKk4dQp+LaF5t6DCGjelSqNb7K25Slypctl6qhFMrB7924GDRrEP//8Q7Vq1cidO7eMcAkhhBBCCBHt1i1DMYw2bSBfPjh9GiZOhDRpWLoUvvpa8zD4PpGdKzP4h5zs7bhXki3B5cuXadiwIXXr1iUoKIj169dz6NAh0qdPb+rQ3ouMcAkhhBBCiIQVGQlz5sDw4YYRrpkzoW9fSJWK8HDDvsbz5oF5gYOkbt2ZNW1n0Lxoc1NHLUzs0aNHjBkzhgULFpA2bVqmTZtG3759sbKyAsDDwwMPDw/TBvkeJOESQgghhBAJ559/DKXeT56EevVg/nywswPg3j1o6ag5ekRB1WkUbfsHG1vvomCWgqaNWZhUWFgYs2fPZvz48QQFBfHDDz8watQosmXLZurQEoQkXEIIIYQQ4sOFhsL48YbqgxkzwqpVhqmELwpfHDsGzb+N5JF/BLTsRKd2aZjX8DDWFtYmDlyYitaajRs3MmTIELy9vWnYsCHTpk2jaNGipg4tQckaLiGEEEII8WEOHIDSpWHCBGjXDry8oG1bUAqtYeFCqF4jCt+IO6TqXo1FLrVZ2nSpJFufsJMnT/L111/j6OiIjY0Nu3btYtu2bR9dsgWScAkhhBBCiPf1+DF07w729hARAbt2wbJlhs2MMQx6deum+eEHiLTbSe5BTTg2bBHdy3WXku+fqFu3btG+fXsqVarEtWvXWLx4MX///Td16tQxdWiJRqYUCiGEEEKI+NEaNm40FMJ4+BCcnWH0aLD+/xGr27cNUwjPnE4FX4+nQc9TrPjWg0xpMpkubmEygYGBTJkyBTc3NwCGDx/OTz/9RLp06UwcWeKThEsIIYQQQhjvzh348Uf4808oWxbc3eHLL2M0OXAAvm35nICgUFTrjkzoXYGfvtqMmZLJVZ+ayMhIli5dyogRI3jw4AHt2rVj4sSJ2Nramjq0JCM/9UIIIYQQ4t2iogy13IsVg927Ydo0QyXCV5ItreGXX6BmrSgec4MMP37Dnol9GPr1UEm2PkF79uyhbNmydO/enQIFCnDixAlWrlz5SSVbICNcQgghhBDiXS5dMqzVOnoUatc2VMH4/PMYTZ49g+49Ilm9KhUU/pOKfeeyqcM68qTPY6KghalcvnwZZ2dn3N3dyZ8/P+vXr6dFixaf7Lo9SbiEEEIIIUTcwsJg0iSYOBHSpYPly6FDh+hS7y/5+ECjJuFcvGAODq4McH7G1LrbsUhlYZq4hUn4+voyevTo6I2Lp06dSt++fUmdOrWpQzMpSbiEEEIIIcTrDh+GHj3g8mVDqfeZMyGOjWh374YWrcIJCg0hTceu/D6kNS2LtTRBwMJUYm9c3LNnT0aPHv3RbFz8oWQyrRBCCCGE+H9PnkCvXvD114Z5gtu3w8qVryVbWsOUKVF8Uy+KQMsrfPFTa/6ePkGSrU+I1poNGzZQtGhRnJ2dqVatGufPn2fu3LmSbL1CRriEEEIIIYTB5s3Qpw/cvw8DB8LYsWBj81qzoCBo3zmMLRutoNg6vhu+iyUtN5DWMq0JghamcPLkSZycnDhy5AglSpRg586d1K1b19RhJUsywiWEEEII8am7exdatIBvv4WsWeH4cZgxI85k69o1KFP+GVs2mZPqm6HMW+bPH20WS7L1iXh14+KrV6+yaNEiPD09Jdl6CxnhEkIIIYT4VEVFwa+/wpAh/18gY9AgsIi72IW7u8axTTghz0PI1rM77iMGUCFPhSQOWpjCqxsXa60ZNmwYLi4un8TGxR9KEi4hhBBCiE+Rl5ehKMahQ+DgYCj1XrBgnE2jomDU2HDGjzWHHJeoMeQXNvb8hSzWWZI4aJHUYm9c3LZtWyZOnEi+fPlMHVqKIQmXEEIIIcSnJDwcpkyB8eMhbVpYsgS+//61Uu8vPX0K37YOZO9f6aDUCkZMvcOYuktkI+NPwJ49exg0aBDnz5+natWqbNmyhUqVKpk6rBRHEi4hhBBCiE/FsWOGDYwvXoTvvoOff4YcOd7Y3MsLajV4yt2b1lg3Gcpmt5rULdAhCQMWpuDl5YWzszPbtm3Dzs6OdevW0bJly0924+IPJX+aEEIIIYT42AUGQt++UK2aoez71q2wZs1bk60Nm55T+stQ7j4Ipdigfnj93pu6BeokYdAiqfn6+tK3b19KlCjBwYMHmTp1KpcvX8bR0VGSrQ+Q5AmXUiqvUmqDUuqJUuqpUmqTUsrWiOvKK6UWKaW8lFLPlFK3lFKrlFL542hrppQaqpTyUUqFKqXOKaVaJM4rEkIIIYRIxrZuhWLFYO5cQ8n3S5egUaM3No+MhP7OT3FsYU54pvN0nj+HvyfNIm+GvEkYtEhKYWFhuLm5UaBAAebPn0/Pnj25du0azs7OpE6d2tThpXhGJ1xKqVJKqXVKqftKqXCl1Jcvjo9XShlVB1IpZQ3sA4oAnYAOQEFgv1LqXbVEWwPFgV+A+oAL8CVwWikV+3+AccBoYM6LtseB9UqpBsbEKYQQQgiR4t2/b5g22KQJZMgAR4/CL7/AW6rKPX4MVWv58sv09JiXW8byP31Y2nEslqkskzBwkVS01mzcuJFixYoxePBg2bg4kRi1hkspVRXYC9wCNgE9XzltBvwA7DKiq+7A50BhrfW1F32fB66+6HPGW66dorV+FCuuI4D3i35HvjiWHRgMTNZaT3/RdL9SqgAwGdhuRJxCCCGEECmT1rB0qaG8+7NnMG6coey75duTpnPno6jZIAD/++nJ2Xo0e3/+jmLZiyZR0CKpnTp1CicnJw4fPiwbFycyY0e4pmBIuIoC/YBXJ3GeBsoZ2U8T4PjLZAtAa+0NHAGavu3C2MnWi2M3gUdAnlcOfwNYAitjNV8JlIxrCqIQQgghxEfh6lWoVQu6doVSpeD8eRgx4p3J1m8rgyhXMRz/J6HUGTuBq8sHS7L1kbp9+zYdOnSgYsWK/PvvvyxatIi///5bkq1EZGzCVQ6Yq7WOAnSsc77Am1dcxlQcuBDH8YtAMSP7iKaUKgpkBy7HukcYcC1W84sv/o33fYQQQgghkrWICMOmxSVLwtmzhj219u+HwoXfetnz59Cx9326drAhKvtZxq/dwc6ho7GxtEmiwEVSCQoKwtXVlUKFCrF+/XqGDRvG1atX6d69O+bmUrg8MRn73Q0D0rzhXE7giZH9ZAYex3HcH8hkZB8AKKXMgQUYRriWxLpHgNY6dmLo/8p5IYQQQoiPw8mThlLv58/Dt9/C7NmQO/c7L3v0SFO90X94nfwMm2rL+ev3onz1eZckCFgkpcjISJYtW8aIESO4f/++bFxsAur1vCSORkptBdIBNTFMJ4wAymmt/1ZK7cCQ4LQ2op9wwE1rPTTW8QnAT1pro9NrpdQCoCvQUGu965Xji4FGWutcsdoXBP4FOmqtV8TRXw+gB0COHDnKrVmzxthQElVQUBA2NvJXpuRGnkvyI88keZLnkvzIM0me3ue5pAoJwe633/hs0ybCM2fmav/++H71lVHXXvCyxHn4F4Q+yYBdq6nM+r40GSwyvE/oH62P4b1y5swZ5s2bx40bNyhevDi9e/emWLGUPdkrOT0XBweHM1rr8u9sqLV+5wdQFggGzgEjgEjADdgNBAJFjeznAbAwjuPzgEfG9PGi/SQgCugQx7kpQCgvkslXjlfEMB2y4bv6L1eunE4u9u/fb+oQRBzkuSQ/8kySJ3kuyY88k+Qp3s9l+3at8+XTGrTu1UvrgACjL506755WFiGa9Dd19wUL9fPI5/G79yciJb9XLl++rBs1aqQBbWdnp9euXaujoqJMHVaCSE7PBTitjchdjFrDpbX+G7AHAjCUW1fAACA14KC1vvzGi2O6iGGNVWzFgEvGdKCUGo6hJHx/HcdI1Yt7WAFfxHEPjL2PEEIIIUSy8/AhtGsHDRpAmjRw6BDMm2co+/4OERHQsMM1hvTOSaq8p/hj1zUW9exBKrNUSRC4SAqxNy6eMmUKly9fplWrVrJxsQkZvQ+X1vqU1roGkB6wAzJqrb/WWp+Ox/3+BCorpT5/eUApZQdUe3HurZRS/YDxwHCt9ew3NNsBhAPtYh1vD1zQhqqIQgghhBAph9awfDkULQrr18OoUeDpCUZOIbxzN4LPy11n+8oC5Ki9Gq8TtrSuVDORgxZJ5dWNi+fNm0ePHj24evUqQ4YMkY2LkwGjEi6l1KIXiRFa62da61ta68AX52yVUouMvN9iwAfYopRqqpRqAmwBbgMLX7lfPqXUc6XUyFeOtQZmYUio9imlKr/yET0ZVWv9EJgJDFVKOSml7JVS8zGsPxtmZJxCCCGEEEnD3p4yAwa8+fz161C3LnTuDEWKwN9/w+jRYGVlVPfu+x/xRYnH3Lmci9qDl3LzrxZ8kVUKJnwMdKyNi6tWrcr58+eZN28e2bNnN3V44gVjR7i6YSi/HpdsGIpXvJPWOhhD4vMvsAJYhWHj4ppa66BXmiogVaz46r04Xg84FutjXqxbDccwEtYf2IlhBK2V1nqrMXEKIYQQQpjc8+cwbZqh1PuJEzB3rmEKYfG4VmfEzXnyFRrVSU8EwUxY7cHuad9jZW5coiaSt1OnTlG9enVatmxJmjRp2LFjB9u3b6d4PH4+RNJIiKL7OYAQYxtrrW8BLd7RxoeYmyujte4MdDbyHpEYEq7xxsYlhBBCCJFsnD0L3boZRrOaNDEkW599ZvTlIaFR2H93npN/lsG6yGF2/y8rVQs3SMSARVK5ffs2w4YNY+XKlWTPnp2FCxfSpUsX2UsrGXvjk1FKNQWavnLIVSn1KFazNEAN4GwixCaEEEII8Wl59sywPmvGDMie3bBeq0ULiEfBg8s3nlCt3j0eXy1DkWabObaqNhmt0yVi0CIpBAUFMXXqVKZPn05UVBRDhw7FxcWF9OnTmzo08Q5vS4U/B+q8+FxjKKseHqtNGHAa+CnhQxNCCCGE+ITs3g09e4K3t2Ej4ylTIFOmeHWxdMtVunfISGTYZ3Se4M5vQ5tJdboULjIykuXLlzN8+HDu379PmzZtmDRpkmxcnIK8MeHSWs/EUHwCpdRtDJsJn0uqwIQQQgghPgkREVjfumUojFGoEHh4QI0a8epCa+gw9CirplUgVebbrNh0h/a1GyZOvCLJ7N27l0GDBnHu3DmqVKnC5s2bqVy5sqnDEvFk1GRPrXXexA5ECCGEEOKTs2ULnDqFRUQEDB8OI0ZAPMt4+z8NoXLzM1zd9xVZSh/nmPsXFMzz+bsvFMnWlStXcHZ2ZuvWrdjZ2bF27VocHR1ltDKFitfqOqVUeqAAhg2PY9BaH02ooIQQQgghPmrBweDkBIsWgY0Ngfnzk358/Gt9HTp/k28aBxNy6yu+7riPvUtqYGEuGxmnVH5+fowZM4b58+eTJk0apkyZQr9+/WQvrRTOqIRLKWWFYQ+tNry5lLy8u4UQQggh3uX0aWjXDq5ehSFD4Ngxop4+jXc345cfYeSPhdHPM+E67xRje8lGxilVWFgYc+fOZdy4cTx9+pSePXsyevRo2UvrI2HsPlwjMBTQ6IahXHt/4AfgOHCdmNUMhRBCCCFEbJGRMGkSVKliqEa4d6+hMIaZsb+OGUREPqdmz224fl8Jq/RP2XPwKWN7VUikoEVi0lqzadMmihcvzqBBg6hSpYpsXPwRMvYd7giMBVa++Pqo1nqx1roacAGolRjBCSGEEEJ8FG7ehJo1YdgwaN4czp8HB4d4d3Pj4X0+q+bB/kWNyF/5PLcu5qZWReP35xLJx+nTp6lRowYtWrQgderUsnHxR8zYhMsWuPhiQ+EIIO0r537FMNVQCCGEEELE9scfULq0YTPjZctg7dp4l3sHWHvoFIXL+PHwZE1a9j3L9SNfki2TrO1Jae7cuUPHjh2pUKECV65cYeHChXh6evLNN9+YOjSRSIxNuPwAmxef3wFKvXIuE4YNkIUQQgghxEtPnkD79tC2LRQrBufOQadO8drEGAzTzrrP3EDrb74g6kke5q26yfpfvoxvN8LEgoKCGDlyJIUKFWLdunW4uLhw9epVevTogbl5vOrYiRTG2Kd7AigNbAc2AeOUUtbAc2AIcCRxwhNCCCGESIEOHYIOHeDOHRgzxjCV8E2/VHt44OnhgX0cpwJCnlCty1YurWlLBttbHNiRmdJF8ydm5CKBxd64uHXr1kyaNAk7OztThyaSiLEJ11Tg5XbW44FCwCQMI2Sngd4JH5oQQgghRAoTEQGjR8PkyWBnB4cPwzs2qrW3h4CAMnh6xjx+7PoF6rS4Q/C59pSp7cWhzYWxsZFhrZRk3759ODk5ce7cOSpXrsymTZuoUqWKqcMSScyoKYVa65Na6/UvPn+itW4KpAOyaK0raq19EjFGIYQQQojk799/oVo1mDjRMHXQ0/OdydabTNmymWpVzQg+X4cfR9zg7K4ikmylIFeuXKFJkybUqlWLgIAA1qxZw9GjRyXZ+kS9M+FSSlkqpU4qpeq8elxrHaK1fpx4oQkhhBBCpABaw+LFULYsXLsG69fDb79BunTx7ir0eSjfuM7B5buamIfkZv3WJ8wZ97ms10oh/Pz86NevHyVKlMDDw4PJkyfj5eXFd999h5KH+Ml655RCrXW4UqoQEJkE8QghhBBCpBy+vtC9O/zvf4ay78uXw2fvV6b9up83X3Xexf1tfchZ8A6Hd+bki/xSTCElCA8PZ86cOdEbF/fo0YMxY8bIXloCMH4N1x6gNrAvEWMRQgghhEg5du0yTB3094fp02HgwHhvYgzged+TkCxHKPLVFzz36knNZrfYttqWNFIDOtnTWrN582aGDBnC9evXqVevHtOnT5e9tEQMxiZcM4DVSikz4H/APUC/2kBrfSuBYxNCCCGESH5CQ8HFBX7+GYoWhb/+gjJl3qur8MhwntltIOJURwjIz6gpjxjlbCtTCFOAM2fO4OTkxMGDBylevDh//fUX9erVM3VYIhkyNuE6/OLfIYDzG9qk+vBwhBBCCCGSsX/+MeyrdeEC9OkDU6fyvkNRHj4etB/3JxH7x4DZc3bviaK2Q7YEDlgktDt37jB8+HB+//13smXLxoIFC+jatavspSXeyNifjB7EGtESQgghhPhkREXBL78YRrYyZAB3d2jQ4L26ehD0gIHbf+KPGWXgxAzM0t/FKtMjajuUTuCgRUIKCgpi2rRpTJs2jaioKFxcXBg6dCjp06c3dWgimTMq4dJa/5rYgQghhBBCJEt370LnzrB7NzRqBEuWwHsUQ4iMimThmYW4bJpD0KolcLsKP/aLYMWOh0RGPk/4uEWCiIyM5Pfff2f48OHcu3dPNi4W8SZjn0IIIYQQb/K//0G3bvDsGcyfDz178j4LrM7cPUMv916cOpwOi81HSBOVnqVroVUrCy7YlyEgICARghfvy97enoCAAGbMmMGgQYPw9PSkcuXKbNy4UfbSEvEW/1I6QgghhBAfu6AgQ7n35s0hXz44exZ++CHeyVZAaAB9tveh/MKKXN7UDLVyNwXzZuTM6VS0apVIsYsPFhwcjLe3N7Vq1eLx48eycbH4IDLCJYQQQgjxqlOnoF07wybGP/0EY8eCpWW8utBas/qf1QzaNYgHvuHY7ffE52RJ2rSBRYvAxiaRYhcf5MKFC4wfP57Tp09jZmbG5MmT6d+/P6lTpzZ1aCIFk4RLCCGEEAIgMhImT4bRoyFXLti3D+zt492Nl68Xvd17s99nP0Uj2mH+xxL+u2fF7Nnw44/vNSNRJDJPT0/Gjx/Pxo0bsbGxIW/evKRPn56ffvrJ1KGJj4BMKRRCCCGE8PExJFcjRkCLFnDuXLyTrWcRzxi+dzil5pfi7L2ztIvYx43pK1BRVhw8aKgiL8lW8nL69GmaNm1K2bJl2b17N66urvj4+PD5559LmXeRYOL9k6SUSgNkBh5oraWkjhBCCCFStlWroHdv0Bp+/x3at493ZrTt3230/asvPgE+tCncBe0+h1Ur01CnjqH7bG/ZXsvDAzw8PAH7D3kVIh6OHz/OuHHj2L59O5kyZWLMmDH069ePjBkzAuDh4YGHh4dpgxQfDaNHuJRS9ZVSJ4FA4CZQ6sXxhUqp1okUnxBCCCFE4ggIMGxi3L49lCxpGNXq0CFeydatJ7dovrY5jf9oTBrzNKy0P8alyUtYszINrq7w119vT7ZE0jp8+DB169alSpUqnDhxgokTJ+Lj48PIkSOjky0hEppRI1xKqcbA/wAPYAQw8ZXTt4HOwJoEjk0IIYQQInEcPGhIrv77z1AUY+hQiMcUsvDIcGYem8nYg2PRWjO51mS+eOREt6YWmJl90L7IIoFprfHw8GDs2LF4eHiQPXt2pk6dSq9evbCR6iUiCRg7wjUa+F1rXQuYHuvcP0CJhAxKCCGEECJRhIfDsGGG9VkWFnDkCLi6xivZOuBzgLILy+Ky14U6n9fhn56XebztJxy/taBAAUMFeUm2TE9rze7du6levTo1a9bEy8uLmTNn4u3tjbOzsyRbIskY+79LMcDlxec61rnHQNYEi0gIIYQQIjFcuWIo937mDHTtCrNmxas++8Pghzjvdub3c7+TL0M+/mz9JxUzNqa1o2EdVs+ehi6lgrhpaa3566+/GDt2LCdOnOCzzz5j9uzZdO3alTRp0pg6PPEJMjbhCgSyvOFcPuBRwoQjhBBCCJHAtIbFi2HgQEM2tHEjfPut0ZdH6SgWnVnE0L1DCQ4PZuhXQxn+9XD+PpmWsg6GpWDLl0PHjon4GsQ7aa3ZunUrY8eO5cyZM+TLl48FCxbQuXNnrKysTB2e+IQZO6VwL+CilEr/yjGtlLIEfgR2JnhkQgghhBAf6tEjaN7cMPxUtSqcPx+vZOvsvbNUWVKFXu69KJOzDOd+OMeEmhNZNDct9vaQNi0cPy7JlilFRUWxceNGypYtS9OmTXn8+DFLlizh6tWr9OzZU5ItYXLGjnANA04CXoA7hmmFzkBpDCNfLRMlOiGEEEKI97VjB3z/Pfj7g5sbDBgAZsb9rflJ6BNc97sy99RcslpnZUXzFbQr2Y7AQEWrVrBhAzRrBsuWQYYMifsyRNwiIyNZv34948eP5+LFixQqVIjly5fTtm1b2UNLJCtG/a+jtfYGygO7gcYvDtcBzgKVtNZ3Eic8IYQQQoh4CgmB/v2hfn3IkgVOngQnJ6OSLa01f/zzB0XmFmHOyTn8UO4HrvS5QvtS7bl4UVGhAmzeDNOmwaZNkmyZwvPnz1m5ciXFixenTZs2REVFsXr1ai5dukTHjh0l2RLJjrFl4dMCd7XWnRI5HiGEEEKI93f+vGFvrYsXoV8/mDwZjCyUcMX3Cj9u/5G93nspl6scW9tspXzu8oBh8+IePSBdOti7F2rUSMwXIeISERHBypUrmThxIteuXaNqjffYAAAgAElEQVRkyZKsW7eOFi1aYGbkyKUQpvDOn06llAXwBKif+OEIIYQQQryHqCiYORMqVABfX8OOwz//bFSyFRIRgus+V0otKMXpu6eZ22AuJ7qdoHzu8oSFwY8/GvZGLlcO/v5bkq2kFh4ezuLFiylUqBBdunQhXbp0bN68GU9PTxwdHSXZEsneO0e4tNYRSqmHwPMkiEcIIYQQIn7u3oVOnWDPHmjSBH79FbJlM+rS7Ve302d7H7wDvGlfqj3T6kwjp01OAG7dAkdHw4zEwYNh4kTD1l0iaYSGhvLbb78xefJkbt++TcWKFZkzZw4NGjRAKWXq8IQwmrGTXFcD3wPbEzEWIYQQQoj42bQJunc3rNtasMAw78+IX8ZvP7lN/x392ey1mSJZi7Cv4z4c8jtEn9+507BlV3h4vKvIiw8UEhLCokWLmDp1Knfv3qVq1aosXryYunXrSqIlUiRjE65/ge+UUseALcA9Ym2ArLX+PYFjE0IIIYSIW1CQoergkiWGuX6rVkHhwu+8LCIyglnHZzHmwBiidBQTa05kUNVBWKayBAwzE8eNgzFjoEQJQzXCQoUS+8UIgODgYBYsWMC0adN48OABNWrUYMWKFTg4OEiiJVI0YxOuBS/+zQNUiuO8BiThEkIIIUTiO3nSMPx0/ToMHQqjR4Ol5TsvO3TzEL3ce3Hx0UUaF2rML/V/wS6jXfR5Pz/DWq0dOwz7as2fD9bWifcyhEFgYCBz587Fzc0NX19fatWqxdq1a6khi+XER8LYhKtgokYhhBBCCPEukZEwaZIhwcqdG/bvN6qCxaPgRwzZM4RlnsuwzWDL/777H02LNI3R5tQpaNkS7t+HhQsNsxRlUCVxPXnyhNmzZzNz5kz8/f2pV68erq6uVK1a1dShCZGgjEq4tNbXEzsQIYQQQog38vaGDh3gyBFo0wbmzYOMGd96SZSO4tezv+Kyx4XA8EBcqrkwovoI0lqmjW6jtSHB6t8fcuUydF++fGK/mE+bv7///7F33/E9XX8cx183Q2LEiN0atUoVtbeKTVVRWjVKjSgxyk+tWrXVKBIjErGC2rO2kNqi9qq9Z4TInt/z++NEY1aQ5JvE5/l45FHu937vPbffSvN2zvl8mDp1KlOnTuXx48c0atSIwYMHU758eXMPTYgEIZ3hhBBCCJF0KaX3Zzk56SmnhQv1csLXOHrnKF03dOXgrYNUz1udGQ1nUDRr0WfOCQ6GLl30JRs0AE9P3SdZJIwHDx4wefJkXFxcCAwMpGnTpgwePJjSpUube2hCJKi4Nj6+wHNFMp6nlJItpUIIIYSIP/7+0LUrLFkCVavqRPTRR//5loDwAIbuHIqLjwuZU2dmQZMFtCnR5oWiC+fPQ7Nmuj/yiBEwaBBIO6eEce/ePSZNmsSMGTMICQnhm2++YfDgwRQvXtzcQxMiUcR1husgLwauzEBFIADYFZ+DEkIIIcR77q+/9BLCO3dg1CgYMAAsLV95ulKKZaeX0XtLb+4G3aVL2S6MrjmaTKkzvXDuypXQvr2us7F5M9Stm5AP8v66c+cOEyZMwNXVlfDwcL777jsGDRpE0aJFX/9mIVKQuO7havOy44Zh2AObgQ3xOSghhBBCvKciImDYMPjtNyhYEPbtg3Ll/vMt5/3O021jN7Zf3k6ZnGVY+91ayn344nsiI3VRw0mToEIFWLYM8uRJqAd5f928eZPffvsNd3d3oqKiaNOmDb/88gsfS3198Z56pz1cSqmHhmGMB0YAS+NnSEIIIYR4L507B61awZEj0KkTTJ4M6dK98vTQyFDG7hnLb3t/w9bKFpcGLnQt2xVLixdnwm7fhhYtYM8e6N5dh644VJIXb+DatWuMGzeOOXPmYDKZaNeuHQMHDqRAgQLmHpoQZhUfq5VDgDj//ZBhGLkNw1hhGMZjwzACDMNYZRhGnN5vGMYYwzC2GobhZxiGMgzjh1ec5x3z+vNfveI6TiGEEEIkEqXA1RVKlYJr12DVKnB3/8+wtenCJorNLMbIXSNpXrQ557qfo3v57i8NW3/9BaVL6xy3aBG4uEjYik+XLl2iU6dOFCxYEA8PDzp06MDFixeZPXu2hC0heIcZLsMwLICiwFDgbBzfkwbYAYQD7dD7wkYBOw3DKKGUCn7NJXoAx4A/gbavOfcE8ONzx67GZZxCCCGESCS+vtCxI6xfD3XqwLx5usfWK9wMuEmvzb1YeXYlhTMXxqutFzXz1XzpuUrBhAnwyy96daKXF3z6aQI9x3vo/PnzjB49mkWLFmFlZUWXLl3o168fuXPnNvfQhEhS4lqlMJIXi2ZYAAYQBDSM4/0cgfxAYaXUxZhrnwAuoMPR7695fwallMkwjIK8PnAFKqUOxHFcQgghhEhsmzbp6hWPHunlgz17vrJUYGR0JM4HnRnmPYxoFc3omqPpU6kPNlY2Lz3f3x9++AHWroVvvgEPD7CzS8BneY+cOXOG0aNHs2TJEmxsbOjZsyd9+/YlZ86c5h6aEElSXGe4fuPFwBUGXAM2KKUexfE6XwEHnoQtAKXUFcMw9gKNeU3gUkqZ4ngfIYQQQiRVoaHQrx9MmwbFisHWrVCixCtP33t9L103dOXk/ZM0LNQQlwYu5MuU75XnHz+uS75fu6Zz3E8/6RZe4t2cOHGCUaNGsWLFCtKkScPPP/9Mnz59yJYtm7mHJkSSFtcqhYPj6X6fAmtfcvw08E083eOJUoZhPAbSoJc8TlVKecTzPYQQQgjxJo4f14UxzpzRSWjcOLC1fempD0Ie0H9bf+Ycm0Pu9LlZ3WI1jQs3fqGn1tPmzdOtu+ztwdsbqlRJmMd4nxw9epSRI0eyevVq7OzsGDhwIL179yZLlizmHpoQycI7VSl8C/bAy2bDHgIvNsp4e7uARcB5ICN6+eFswzByKqVGxeN9hBBCCBEXJpOebvrlF52GNm+GevVefqoyMefoHPpv709AeAD9KvdjaPWhpE2V9pWXDwvTKxLd3aFGDd0rWSZe3o2Pjw8jR47kzz//JEOGDAwbNoyePXtib29v7qEJkawYSj2/UjDmBcNwe4PrKKXU8wUqXnbNCGCSUmrgc8dHA/2VUnHdU1YQve+rvVJqXhzfsxqoD2RVSgW95PXOQGeA7Nmzl1myZElcLpvggoKCSPcfVZqEecjnkvTIZ5I0yeeS9JjjM0nl68sn48aR6cgRHlSpwrm+fYnMkOGl514MusiUC1M4HXCaEhlK0KtQL/KlffXyQYA7d2wZNuxTLlywo1Wra3TocBVLy5f/fJNUJaU/K6dOncLT0xMfHx/Sp09P8+bNadq0aZIZX2JJSp+JiJWUPpcaNWocVkqVfd15/xVwvuDFfVuvEtfzHqFnuZ6XiZfPfMWnP4AmQHFg//MvKqXcADeAsmXLKgcHhwQeTtx4e3uTVMYiYsnnkvTIZ5I0yeeS9CT6Z7JyJXTpoqeg3NzI0qkTWV6yJDAwPJBh3sNwPuKMfWp75jeZz/clvv/P5YMAGzaAk5OuSLhuHTRqlBfIm0APk3CSwp+Vv/76i5EjR+Ll5UWWLFkYN24cTk5O2L2n1UaSwmciXpQcP5dXBi6lVK4EuN9p9D6u5xUFziTA/Z725Dt28vorLyGEECI5CgrSe7TmzIGyZXUDrI8/fuE0pRTLzyyn95be3Am8w49lfmR0rdHYp/7vZWvR0TBsGIweDSVL6lyXP39CPUzKpZRix44djBgxgl27dpE9e3YmTpxIly5dSJv21Us4hRBxFx+Nj9/EOqCiYRj/fks0DOMjoErMawmpFRAKnEzg+wghhBDvt4MHdQqaOxcGDYJ9+14ati4+vEj9RfVpsaIF2dNmZ3/H/cz8cuZrw5avr97+NXq0buG1b5+ErTellGLLli1UrVqV2rVrc/HiRaZOncqVK1fo06ePhC0h4tErZ7gMw/gAuK+Uior59X9SSt2Ow/3cge7AWsMwBqNnm0YCN4BZT907L3AJGKGUGvHU8epAViBHzKGyhmEExdx/Rcw51YABwCp0o+MM6CbLXwED4tBcWQghhBBvIyoKxoyBESMgVy746y+oVu2F08Kiwhi3Zxzj9ozDxsoG5/rOdC3XFSuL12/l3r9f99Xy89O9tTp0SIgHSbmUUmzYsIERI0Zw6NAhcufOzYwZM2jfvj22r6gWKYR4N//1ne0GUAnwAW7y+qV4lq+7mVIq2DCMmsBkwBO9zM8L6PVcIQsj5nrPz8ANB6o/9ftuMV9P3gNwJ+Z9I4AsQCRwAmillPrjdWMUQgghxFu4cgXatNHTTa1bw/Tp8JLCGFsubqHbxm5cenSJlsVaMqnuJHLavb5hrlLg4gJ9+kCePPo2pUolxIOkTCaTibVr1zJy5EiOHj3KRx99hJubG+3atSNVqlTmHp4QKdp/Ba7O6FmmJ7+Ol71PSqnrQLPXnHOV2AD19HGHOFz/ItDgLYcnhBBCiDehFHh6QvfuurvwokW6z9ZzbgXcoteWXqw4s4KPM3/M9u+3Uyt/rTjdIigIOnWCpUuhUSOYPx8yxWczmRTMZDKxcuVKRo4cycmTJylYsCBz586ldevWWFtbm3t4QrwX/qtohsdTv56dOMMRQgghRLLx6JGuQLhsmV466OkJeZ+tEBhlisLloAtDvYcSZYpiZI2R9K3cFxsrmzjd4uxZaNYMzp2DsWOhXz+wSOwd6MlQdHQ0S5cuZfTo0Zw5c4YiRYrg6enJd999h5VVYrdhFeL9Jn/ihBBCCPHmvL3h++/h7l1dvaJ/f7B8dnfBvhv76LqhKyfuneCLQl/g0sCF/JniXt1iyRI9s5U2LWzfrhsai/8WFRXF4sWLGT16NOfPn+fTTz9lyZIlNG/eHEvL1+7+EEIkgDgHLsMwsgAtgMLA87sq49T4WAghhBDJXEQEDBkCEyZAwYK6ikXZZ/t++oX40X97fzyOepArfS5WfbuKJkWavLan1tO3+PlnvWercmU9gfbhhwnxMClHREQEnp6ejBkzhsuXL/PZZ5+xYsUKmjZtioVMCQphVnEKXIZhfIxuFmwb8/UIyIguTvEYCEyoAQohhBAiifjnH10Q48gR6NwZfv9dTz/FMCkT847No9+2fjwOf0zfyn0ZWn0o6VKli/Mtbt7UVQgPHIDeveG330C2Gr1aeHg48+bNY+zYsVy7do0yZcqwdu1aGjVqFOeAK4RIWHH9K48JwBF0SXYDqAukBbqgw1bDBBmdEEIIIcxPKZg5E0qXhmvXYM0amDXrmbB14t4Jqs2tRsd1Hfkk6ycc/fEo4+uMf6OwtX27rjx46pSe1fr9dwlbrxIWFsa0adMoWLAgXbp0IUeOHGzcuJFDhw7x1VdfSdgSIgmJ65LCcoATEBbzewulVDjgZhiGPTAFiFupISGEEEIkH/fv6+7Cf/6puw3PnQs5Y8u4B4YH8qv3r0w9OJVMqTMxt/Fc2n3W7o1+4DeZdEGMIUPgk09g5UooUiQhHib5CwkJYdasWUyYMIE7d+5QtWpV5syZQ+3atSVkCZFExTVwpQf8lFImwzAC0P2tnvABBsf7yIQQQghhXhs3Qvv28PgxTJ2qS7/H7AdSSrHy7Ep6be7F7cDbdC7TmTG1xmCf2v6NbvHoka69sWGDriY/axaki/uk2HsjKCiImTNnMnHiRO7fv0+NGjVYvHgx1atXl6AlRBIX18B1Fcge8+tz6D5am2N+3wDwj99hCSGEEMJsQkOhb1/dvLh4cfDygmLF/n354sOL9NjUg80XN1MyR0lWfLuCirkqvvFtDh+G5s3h1i19q65ddSsvESsgIIDp06czadIk/Pz8qFOnDkOGDKFatWrmHpoQIo7iGri2A7WBFcBkYLFhGJWBKKAYMDZhhieEEEKIRHXsmJ5qOntWV60YMwZsdXHisKgwxu8dz5jdY0hlmYqp9afiVM4JK4s36zKjFMyeDT16QLZssHs3VKiQEA+TfPn7++Ps7MyUKVN49OgRX3zxBUOGDKFixTcPtkII84rrd8gBQGoApdQSwzDC0SXi0wCzANeEGZ4QQgghEoXJpKtU/PILZMkCW7dCnTr/vrzt0ja6bezGhYcX+K7Yd0yqO4kP7D5449uEhEC3bjBvHtStC4sW6dsJzc/PjylTpuDs7ExAQACNGzdm8ODBlH2u9L4QIvmIU+BSSoURWzADpdRqYHVCDUoIIYQQiejmTWjXDnbsgKZNwc3t3xR0O/A2vbf0ZtnpZRSyL8TWNlupU6DOay74chcv6iWEx4/D0KH6S3rxgoODAw8ePKBRo0ZMmzaNoKAgmjVrxuDBgylZsqS5hyeEeEevDFyGYdQEfJRSQYk4HiGEEEIkphUrdE+t8HC9zq9DBzAMokxRTPeZzpCdQ4iIjmCEwwj6VumLrZXtW91mzRqd6aysdC2OBg3i+TmSqevXr3Pp0iVu377NmTNnaNGiBYMGDaLYU3vmhBDJ23/NcG0DKqGrEGIYhgXgDXRUSl1I+KEJIYQQIl45OFDS31/v0woMhJ499dq+cuX02r5ChQA4cPMAXTd05djdYzQo2ACXBi4UsC/wVreMioJBg2D8eChbFpYvh48+ir9HSo6UUuzevRtnZ2dWr16NyWQiU6ZM7Nu3jyJSD1+IFOe/AtfzdYIMoCpgl3DDEUIIIUSC278f2rSBq1dh8GC9ts/amoehDxmwfQDuR9zJlT4XK79dSdMiTd+67Pjdu9CyJXh7Q5cuMGUK2NjE65MkK6Ghofzxxx84Oztz/Phx7O3t6du3L97e3oSFhUnYEiKFerOyQkIIIYRIvpTC5u5dqFYNcuWCv/6CqlUxKRPzj86l3/Z+PAp9RJ9KffjV4VfSpXr7hli7d0OLFuDvD/PnQ9u28fgcyczNmzeZMWMGbm5u+Pn5UaxYMdzd3WnVqhVp0qTBwcGBsLCw119ICJEsSeASQgghUjql9Caqv/8mdUiInt2aNg0yZODkvZM4bXRiz/U9VMldhZkNZ1I8e/F3utXkydCvH+TPD1u26FZe7xulFPv27cPZ2ZmVK1eilOKrr76iZ8+eODg4PDNr6O3tjbe3t/kGK4RIUK8LXB8ahpE/5teWTx17odGxUupyvI5MCCGEEO9GKZ14Bg/WXYZTpyY4b17SenoSFBHE8K19mXxgMhltMzLnqzm0K9kOC8PirW8XEKBrbqxcqYsdzp0LGTLE4/MkA2FhYSxduhRnZ2eOHDlCxowZ6d27N05OTuTLl8/cwxNCmMHrAteKlxxb84pzpbCrEEIIkVTs2qWD1u7dukrF3Lkwdy4Rj/3ZcnYVP23+iZsBN3Es7cjYWmPJnCbzO93u5Elo1gwuX4aJE+F//4O33PqVLN2+fZuZM2cya9YsfH19KVq0KK6urrRp04a0adOae3hCCDP6r8DVPtFGIYQQQoj4ceiQDlpbt0LOnDB9OnTqBKlScXHpTJyKXmHbsmZ8lv0zljVfRqXcld75lgsX6sryGTLoVl6ffx4Pz5EMKKU4cOAAzs7OrFixgujoaBo1akTPnj2pWbPmWxcbEUKkLK8MXEqp+Yk5ECGEEEK8g1OnYMgQvVcrc2aYMAGcnCBNGu4G3WXEthG4VjyEgcHkepPpXr47VhbvtpU7PBx694aZM3XIWroUcuSIp+dJwsLDw1m+fDnOzs4cOnSI9OnT06NHD7p3707+/PlffwEhxHtFimYIIYQQydnFizBsGPzxB9jZwfDh0KsXpE/P47DHTNgxmMkHJhMRHUHXsl2pZV2Lryt+/c63vXYNvvlGT6j16wejR+umxinZ3bt3cXV1xdXVlXv37lG4cGGmT59O27ZtSZfu7Ss6CiFSthT+rVEIIYRIoa5fh5Ej9d4sGxvo3x/69gV7e8Kiwpi5fzKjd4/GL9SP74p9x8gaIyloXzBequFt3gytW+umxqtW6QIZKdmhQ4eYOnUqy5YtIzIykoYNG9KzZ09q166NhcXbFxkRQrwfJHAJIYQQycnduzBmDMyapX/frRsMHAg5chBtimbhsfkM9R7K9cfXqVugLmNrjaV0ztLxcuvoaJ3xRozQpd5XrIBCheLl0klOREQEK1euxNnZmQMHDmBnZ4eTkxPdunWjUEp9aCFEgpDAJYQQQiQHDx/C+PHg4qI3T7Vvr/ds5cmDUoo/z63nlx2/cOr+Kcp9UI65jedSM1/NeLv9gwd6VmvrVt3EeOZMSJMm3i6fZNy7dw83NzdmzpzJnTt3KFSoEC4uLrRr1w47OztzD08IkQxJ4BJCCCGSsoAAmDIFJk2CwEBo2RJ+/fXfqaW91/fSf3t/9t7Yy8eZP2b5N8tp9kmzeK2Q5+MDzZvDvXt6Ys3RMeWVfD98+DDOzs4sWbKEiIgI6tevj4eHB/Xq1ZNlg0KIdyKBSwghhEiKQkN1Sfdx48DPT2+UGj5cr+UDTt0/xS9ev7D+/HpypsvJrC9n0b5ke6wtreNtCErpmaxeveDDD2HfPihTJt4ub3aRkZGsXr0aZ2dn9u7dS7p06ejcuTPdu3encOHC5h6eECKFkMAlhBBCJCURETB7NowaBXfuQL16+tdlywJwzf8aw7yHseD4AtLbpGdsrbH0rNCTNNbxu74vOBh+/BEWLYIvvgBPT7C3j9dbmI2vry/u7u7MmDGDW7duUaBAAaZMmcIPP/xAhgwZzD08IUQKI4FLCCGESAqionSqGT5c11yvVg2WLPm3i/CDkAeM2T2G6YemY2DQp1IfBlYbiH3q+E9B585Bs2Zw5owukvHLL5ASVtUdO3YMZ2dnFi9eTHh4OHXq1MHV1ZUGDRpgaWlp7uEJIVIoCVxCCCGEOZlMsHy57qV17pxeszdrFtStC4ZBcEQwkw9MZsK+CQRFBPHDZz/wq8Ov5M6QO0GGs2KFrsdhawtbtkCdOglym0QTFRXF2rVrcXZ2ZteuXaRJk4YOHTrQvXt3ihYtau7hCSHeAxK4hBBCCHNQCv78U1caPH4cPv1UN7Vq0gQMg8joSNyPuDPirxHcC75HkyJNGFNzDJ9k/SRBhhMZqVt5TZ4MFSvCsmWQO2EyXaLw8/Nj9uzZTJ8+nRs3bpAvXz4mTZpEhw4dyJgxo7mHJ4R4j0jgEkIIIRKblxcMHgwHDkCBArBwIXz3HVhaYlImlp1ayuAdg7n06BKf5/2c1S1WUyl3pXe+rYMD+PuX5NixZ4/fugUtWsDevdCjB0ycCKlSvfPtzOLEiRO4uLiwcOFCwsLCqFWrFtOmTaNhw4aybFAIYRYSuIQQQojEsn8/DBoEO3dCrlzg5gY//ADWurLgtkvbGOA1gCN3jlAiewk2tNpAg4IN4rXE+/N27tRZLzgY/vhD/zq5iY6OZt26dTg7O+Pt7U3q1Klp27YtPXr0oFixYuYenhAivjhASf+ScOy1ZyYpEriEEEKIhHbsmJ7R2rABsmXTfbV+/FFvlAIO3TrEQK+BeF3x4qOMH+HZ1JNWxVthYSRcpQqTSfdRHjQIPv5YB6/ktqXp0aNHeHh4MG3aNK5du0aePHkYP348HTt2xD6llFQUQiR7EriEEEKIhPLPPzB0qC6KkSkTjB2r1+ylTQvAeb/zDNoxiBVnVpA1TVam1p/Kj2V+xMbKJkGH5e8P7drBunXw7be6Cr2dXYLeMl6dPn0aFxcXPD09CQkJwcHBgcmTJ9OoUSOsrORHGyFE0iLflYQQQoj4duWKLu/u6Qlp0ujCGP/7H8QUa7gdeJvh3sPxOOpBauvUDKs+jD6V+mBnk/CpJzTUkjJl4Pp1mDpV578EXLEYb6Kjo9mwYQPOzs54eXlha2tL69at6dGjB5999pm5hyeESGjRQABgMvdA3pwELiGEECK+3LqlmxTPng1WVtC7ty79lzUrAP5h/ozfO54pB6YQZYrCqZwTgz8fTLa02RJ0WBERuiDGpUtw61Y6PvgA/voLKldO0NvGC39/f+bOncu0adO4fPkyuXLlYuzYsXTq1IksWbKYe3hCiIR0H9gCbAK2An5glS/5xZfkN2IhhBAiqfH1hXHjYMYM3cDY0VFvjvrwQwDCosKY5jONMbvH4B/mT6virRhRYwT5M+VPsCFdvKj7aG3erPdnBQfrmSw7u0iOHElFtoTNeO/sn3/+wcXFhfnz5xMcHEy1atX47bffaNKkiSwbFCKligJ80AFrE3A45nhW4Avgb4i2iDbT4N6efMcSQggh3pa/P0yapItghITA99/rBsb58gEQZYpiwfEFDPMexs2AmzQo2IAxtcZQMkfJeB9KYCDs2KFD1pYtcPmyPp4/P7RtC/XqwYQJEBQUQrZsSbPmu8lkYtOmTTg7O7N161ZsbGxo1aoVPXr0oFSpUuYenhAiIdwFNqMD1jbgEWABVARGAg2AUjHHHED5K/OM8x1I4BJCCCHeVHAwODvrBPPoEXzzjd6z9YluSqyUYu25tfzi9QtnH5ylwocVWNh0IdU/qh5vQzCZdPHDJwFr7149uZY2LdSsqbeM1asHBQvGvmfy5Hi7fbwKCAhg3rx5uLi4cPHiRT744ANGjRpF586dyRqzHFMIkUJEAfuJncV6UuI9B9AYHbBqAymo0KgELiGEECKuwsLA1VVXG7x/Hxo2hJEj4anZl13XdjFg+wD239xPkSxFWPXtKpoUaRIvvbTu3YOtW3XA2rZNDwGgZEno00cHrCpVkk/T4vPnzzNt2jTmzp1LUFAQlStXZtSoUXz99ddYx/QmE0KkALeIncXaDjwGLIHKwBh0yCqBnsVKgSRwCSGEEK8TGQlz5+pwdfMm1KgBa9ZApUr/nnLi3gkGeg1k44WNfGj3Ie6N3Pmh5A9YWbz9/2ojImDfvthZrKNH9fEsWXS4qlcP6tSBHDne9QETj8lkYuvWrTg7O7Np0yZSpUrFd999R48ePShbtqy5hyeEiA8RwD50wNoMnIg5/gHQHB2wagEZ3/C63nDM+xgOOMTPOBOJBC4hhBDiVaKj4Y8/4NdfdYm/iqngr0sAACAASURBVBVh/ny9Zi/GVf+rDNk5hEUnFpHRNiPja4+ne/nupLZO/Va3vHRJF7rYskUXuwgK0gUPK1eG0aN1yCpVCiyS2d8EBwYGsmDBAlxcXDh37hw5cuRgxIgRdO7cmezZs5t7eEKId3WD2GWCXkAgOmlUBX4D6gPFgWTQhiK+SeASQgghnqcUrF6tmxafPg2ffQbr1+slhDFLA32DfRm1axQz/56JpYUl/av0p1+VfmRKnemNbhUYqIPVk1msS5f08Xz5oE0bqF9fT6ilTx/fD5k4Ll68yPTp05kzZw4BAQFUqFCBxYsX06xZM1Ill7WPQogXhQN7iA1ZZ2KO5wZaogNWLSCZfu+KTxK4hBBCiCeU0qln8GA4fBgKF4alS6F583+nlALDA/l9/+9M3D+R0MhQOpTqwLDqw/gw/YdxuoXJBMePx5Zs37dPr1hMm1YHq169YotdxHdDYm9v8PY+Bgm8HEcpxfbt23F2dmbDhg1YWVnx7bff0qNHDypUqJCg9xZCJKCrxAasHUAwYA18DnRAh6yivJezWP9FApcQQggBsGuX7p21Zw989JHes9WmjV7PB0RERzDr71mM3DUS3xBfmn3SjNE1R1M4S+HXXvr+/dhiF1u3xha7+Owz3Rv5SbELG5sEfL5EEBQUhKenJy4uLpw9e5Zs2bIxdOhQfvzxR3LmzGnu4Qkh3lQYsIvYvVj/xBz/CGiL3otVA0hnjsElHxK4hBBCvN8OHdIzWlu3Qs6cunlxx47/lvozKRNLTi1hyM4hXH50mRof1WBc7XGU/7D8Ky8ZEQH798fuxXq62EXdujpg1a2bvIpd/JcrV64wffp0Zs+ezePHjylTpgwLFizg22+/xSa5p0gh3jeXiA1YO4EQwAaoDvyInsUqjMxivQEJXEIIId5PJ0/qPVpr1kDmzDBxIjg5QWpd7EIpxeaLmxnoNZDj945TMkdJNrfeTN0CdV9a4v3Spdh9WDt2xBa7qFQJRo3SIat06eRX7OJVlFLs3LkTZ2dn1q1bh6WlJc2bN6dnz55UrFgxXsrgCyESQSjgTWzZ9gsxxwsQu0zQAUhrhrGlEIkeuAzDyA1MBuqgs/F2oJdS6noc3jsGKAuUQbdDa6+UmveKcx2BPkA+9IrTyUop13h4BCGEEMnZhQswbBgsWQJ2djBihN44ZWf37ykHbx6k//b+/HXtL/Jnys/irxfTolgLLIzYtBQUpItdPJnFer7YRb16uphhci128SohISEsXLgQZ2dnTp8+TdasWRk0aBBdunThww/jto9NCGFGCh2qnsxieaOXDtqilwd2Ry8VLGSm8aVAiRq4DMNIg95iFw60Q3/ko4CdhmGUUEoFv+YSPdD9qP9Erxx91X0cgVnAWHSgqwXMMAzDUErNfOcHEUIIkfxcv67D1bx5erNU//7Qty/Y2/97yj8P/mHQjkGsOruKbGmzMa3BNBzLOJLKMhUmExw9FjuLtXevLnaRJo0udvHTT7qiYEIUu0gKrl27xowZM3B3d+fRo0eUKlWKefPm0aJFC2xtbc09PCHEfwlGLw98Mot1Oeb4x8QuE6wOvF03C/EaiT3D5QjkBworpS4CGIZxAp2zfwR+f837MyilTIZhFOQVgcswDCtgNOCplBoUc3inYRgfACMNw5itlIqMh2cRQgiRHNy9C2PGwKxZ+vfdusHAgc9soLoVcItfvX9lzrE5pLVOywiHEfSu1JsQ/3QsXxJb7OLePX1+Sit28SpKKXbt2oWzszNr1qzBMAy+/vprfvrpJypXrizLBoVIqhS6wMWTWaxd6OmONEBN4H/oWaz85hrg+yWxA9dXwIEnYQtAKXXFMIy9QGNeE7iUUqY43KMSkBVY+NxxT6A9uv3azjcZtBBCiGTo4UMYPx5cXCA8HNq3hyFDIE+ef095FPqIcXvG4ezjjEmZ6Fa6F7WshnBwS0aq/w+OHNHnZckCderEFrtI6QX3QkNDWbx4Mc7Ozpw4cYLMmTPTv39/unbtSu7cuc09PCHEywShGw4/mcW6FnP8E8AJHbCqoZcOikSV2IHrU2DtS46fBr6Jx3sAnHrJPUB3B5DAJYQQKVVAAEyZApMm6a7CLVvCr79CodgNCSGRIbgcdGHc3nH437anQrgr6W98w7zxaXAJBEtLqFw5ZRa7+C83btxg5syZuLm54efnR4kSJfDw8KBly5akTi1rjYRIUhT6p9sns1i7gUh0cYtawAD0UsGPzDQ+8S9DKZV4NzOMCOB3pdSA546PAgYopeIUAGOWFF7gJUUzDMP4Bb2kMLVSKuyp41bo/wyHKqVGvuSanYHOANmzZy+zZMmSN3m0BBMUFES6dNLcIKmRzyXpkc8kaUrMz8UiPJwP16whz+LFWAcE4FutGlfbtyc4X75/z4lW0ay96sW8ndcI/KcStlcbE+arZ2xy5AilXLlHlCv3kFKlHpEuXXSijDuxPf+ZKKU4deoUK1euZPfu3QBUqVKFZs2aUaJECVk2mEjke1jSkxQ/E8tgSzIdzoS9jz32h+yxva+nq4LyBfGw/EMeln/I4+KPUdaJ9/N9YktKn0uNGjUOK6XKvu48c5SFf9l/AfH53fzJtd7ovzSllBvgBlC2bFnl4OAQj0N6e97e3iSVsYhY8rkkPfKZJE2J8rlERMDs2Xo66s4dPSU1ahRZy5YlK6AUHDummOR5itV/BhNy6VcwpcI2dTQ1a1hSv75+S6FCqTGM1MAHCTteM3vymYSFhbFkyRKcnZ05evQomTJl4ueff8bJyYm8efOae5jvHfkelvQkic9EASeIXSa4F4gC7ND1vuvrr3S505GOdOQhzysvlVIkic/lDSV24HqELuf+vEwxr8WHhzH/tAfuPHXc/rnXhRBCJCAHB/D3L8mxYwl0g6go8PSE4cPh2jWoVk2Xev/8c3x9YdtiXbL9z03hPHpgAxTH5sNzNPnhGt1aFqRaNcsUW+ziVRwcHPD19aVp06bMmjWLBw8eUKxYMdzc3GjdujVp0qQx9xCFEP7oGttPlgrejjn+GbrhUQOgMmBtltGJt5DYges0sXusnlYUOBOP9yDmPk8HrqIx/4yv+wghhDAHkwmWL9e9tM6dgzJliJzuxv50ddiyxWBLTLELpcA63WMiP9qIfe1DDGpfnp9qf4OlhaW5nyDRmUwmvLy8OHPmDL6+vpw9e5bGjRvTs2dPHBwcZNmgEOZkAo6jA9YmYD8QDWRAz2I1QM9kpezJ9xQtsQPXOmCiYRj5lVKXAQzD+Aiogt7aFx/2Aw+A1ui/H3iiDXp2a2883UcIIURiUgr+/FNXGjx+nCuF6rLlxz/Ycq8kXi0NAmOKXZQqF0qxFus5aTeBdPmvMujzAXQrPwZbq/evNNedO3eYO3cus2fP5sqVK1hZWZE1a1YOHjxIvqf2tgkhEtlDYBuxs1gxLScoBfRHh6yKmGfzj4h3if0xuqP7V681DGMwemXqSOAGulExAIZh5AUuASOUUiOeOl4dXfL9SfOUsoZhBAEopVbE/DPSMIwh6EbHt9ChqybQAeihlIpI2EcUQggR77y8CBowCu+/07Il/f/YkqMJFy6khwuQN68uRFjhc3/2pxrFvH+mYm1hzS8Ve9OvSj8y2GYw9+gTVXR0NFu3bsXNzY3169cTHR1NzZo1GTt2LNOnTycgIEDClhCJzQQcIXYW62DMsUxAXXTAqkfsT7giRUnUwKWUCjYMoyYwGd0Xy0B3DOillAp66lQDsASeL8I7HN0H+4luMV9P3vPkPq6GYSj0Ste+wHWgu1JqRjw+jhBCiASkFJxYcIwtIw6y5XJBdrOFSFKROlJRo7RB93q62EWOvAH8vn8SPfdPIiwqDMfSjgytPpScdim8WdZzbt68yZw5c/Dw8OD69etky5aNn3/+mU6dOlGwYEEAWrRogbe3t3kHKsT74gGwFR2wtgC+McfLAoPQIascMov1Hkj0j1gpdR1o9ppzrvKSyoVKKYc3uM8snpo1E0IIkfT5+sK2bbDlDz+2bjO4G14SKEnxnA/4qYUF9RpC1aoGtrYQHhWO69+ujFo3igchD/j2028ZVWMUhTIXeu19UoqoqCg2btyIu7s7GzduRClFnTp1+P3332nUqBGpUqUy9xCFeH9EA38TO4t1CL2WKzN69qoBejYrm7kGKMxFMrUQQgiziYyEAwdgyxb9dfiwQikDe6COtTf1m9tQd2wNPiiY5d/3RJui8Ty+mKHeQ7nqf5Xa+WszttZYyn7w2lYoKca1a9fw8PDAw8OD27dvkzNnTgYOHEjHjh1luaAQiek+evZqE3o2yw89ZVAeGIYOWWXQ67bEe0sClxBCiER19aoOV5s3w44dEBAAlpaKivYXGM5C6qXeRZn/Vcfy596QMeO/71NKsfHCRgZ6DeTk/ZOUyVkG90bu1M5f23wPk4giIyNZv3497u7ubNmyBcMwaNCgATNmzKBhw4ZYWcn/0oVIcFGAD7GzWIdjjmcFvkAHrDpAlpe+W7yn5LuzEEKIBBUcDN7esbNY58/r43nyQIsvg6n/YCE1vQaRMTAY/tcN+i+HrFmfucb+G/vpv70/u6/vpqB9QZY2X0rzos2xMJ7f6pvyXLp0idmzZzN37lzu3btHrly5GDZsGB06dCB37tzmHp4QKZMDlPQvCceAu8Q2Ht6G7hxrga4iOBIdskrxYuUBIWJI4BJCCBHvIiPh1i24ezct9vYQEQGpU+tmyE5OUK/cQwqvGI0xcwZER0PnTjB4MHzwbKOZM75n+MXrF9aeW0uOdDmY2XAmHUt1xNoyZXf8jIiIYM2aNbi5ueHl5YWlpSVffvkljo6O1K9fH0tLWZ8kRIKJBPzB9o6tDlJPmrfnABqjA1ZtwN5M4xPJjgQuIYQQ8eqff6BNG7h4EdIYkfT4nzX16kG1amAb5g+TJkG9KRASAm3bwtCh8Ny+oxuPbzDMexjzj88nXap0jK45mp8q/ETaVGnN9FSJ4/z587i7uzNv3jwePHhA3rx5GTVqFO3bt+eDD6TrqRAJ5gZ6FmszuqFQANhgA4WBMeiQVQKZxRJvRQKXEEKIeKEUTJ8OfftC2rRQNM0VMhl+TJxYFoKCYLILjB8P/v7w7bcwfDgUKfLMNfxC/Bi7ZyzTfKYB0LtibwZWHUjmNJnN8UiJIiwsjFWrVuHm5sZff/2FlZUVjRs3pnPnztSuXRsLC/kJT4h4FwbsIbbx8JmY47mAb4F9EGARQIZd71cfP5EwJHAJIYR4Z7dvQ4cOeo9W/fowZw60/OQxFpHhMGUKjB0L9+/Dl1/CyJFQsuQz7w+OCGbqwan8tvc3giKCaPdZO351+JU8GfKY6YkS3pkzZ3B3d2fBggU8fPiQAgUKMG7cOH744QeyZ89u7uEJkfJcJHYWaycQAqQCPgc6APWBougqgw6g/JV5xilSHAlcQggh3smKFfDjjxAaqme4unYFIyyURuEraBPuDr3vQ82aMGoUVKr0zHsjoyPxOOrB8L+GczfoLl8V/ooxNcfwabZPzfQ0CSskJITly5fj7u7O3r17sba25uuvv6Zz5844ODjIbJYQ8SkYHayehKxLMccLEhuwHICXrVT2hmPex3DAIcGHKVI+CVxCCCHeyuPH0LMnLFgAZcvCwoVQ2O42DJ0Jrq70CXvAKYviZN/+hw5cT1FKsfzMcgbvGMyFhxeomqcqK75ZQZU8Vcz0NAnrxIkTuLm5sXDhQh4/fkzhwoWZOHEibdu2JetzFRmFEG9JAaeJDVi7gQggDVAD6I1uQFzQXAMU7ysJXEIIId7Yrl263sWNGzBkCAz54jDWIyfDsmUQFQVffUWv7Q35W5VkT81yz7x3++XtDNg+gMN3DlMsWzHWt1xPw0INMQzDTE+TMIKCgli6dClubm74+PhgY2ND8+bN6dy5M9WqVUtxzyuEWfgDXsSGrJsxxz8FeqBnsaoCtmYZnRCABC4hhBBvIDxcFxWcMAHy51fsHbmTihuHwsi9YGena7736AEFCnAs4zEdvmIcvn2YAV4D2H55O3kz5GV+k/m0Lt4aS4uUVeL8yJEjuLm5sXjxYgIDAylatChTpkzh+++/x95e6kgL8U5MwFFiA9Z+IBpIj244PAw9iyUt6kQSIoFLCCFEnJw6pcu9Hz8OjuWP8/vt70g36B/In18XxmjfHtKnf+F9F/wuMHjnYJadXkbm1JmZXG8yXct2xcbKxgxPkTACAgL4448/cHNz48iRI6ROnZoWLVrg6OhIpUqVZDZLiHfhC2xFB6wtMb8HKAMMQM9iVQBSdns+kYxJ4BJCCPGfTCaYOhUGDjCR3jKYtak68JXPCt3FeNo4XXnwJY14I9I84Ep5V4rOWIuNpQ1DPh/Cz5V/Jr3Ni6EsOVJK4ePjg7u7O0uWLCE4OJgSJUowffp0WrVqRcaMGc09RCGSpyjgILGzWIfR+7Myo2evGqBns6SYp0gmJHAJIYR4pRvXFT80fsiOY5lpxJ/MtnYiW5u60PPoC6Xdnzh29xguB13Y33ERWETRrUwXhnw+hOzpUsZPR/7+/ixatAg3NzdOnDhB2rRpadmyJY6OjpQrV05ms4R4G7fQs1ebgW3ovVkWQEVgOHoWqzSQslYgi/eEBC4hhBAvCgnhj577cZpblkiTDe52/6Njn4wYXQ7DS3pERUZHsvqf1bj4uLDn+h7SWKch5712ZDjdhWnDS5nhAeKXUop9+/bh7u7OsmXLCA0NpUyZMsyaNYvvvvuO9C9ZSimE+A/hwF5iZ7FOxhz/APgaHbBqA5nMMjoh4pUELiGEELFu3uTRJA+cZhRjSUQzKqY5geevlyjYcyzYvLjn6n7wfdwOu+H6tyu3Am+RP1N+JtWdRPuS7cmUOhPe3t6J/wzxyM/PD09PT9zd3Tlz5gx2dna0a9cOR0dHSpcube7hCZG8XCY2YO1A98myBqoB49Ehqxi68bAQKYgELiGEEHDwIEyZgtcyP9qZ5nDPyMHIjlcZMLM4VtYlXjjd55YPLj4uLDu9jIjoCOoWqIvrl640KNgg2VcdVEqxa9cu3NzcWLlyJeHh4VSoUAEPDw++/fZb0qVLZ+4hCpE8hAB/AZvQIetCzPF8QDt0wKoByB8pkcJJ4BJCiPdVZCSsXAlTpxJ24CgDU01iiqkbhfNHsGapFWXLfvTM6eFR4Sw/sxwXHxd8bvmQLlU6OpfuTPfy3SmcpbB5niEe+fr6Mn/+fNzd3Tl//jwZMmTA0dERR0dHSpR4MXQKIZ6jgH+IncX6C7100BYdrLqjQ1YhZBZLvFckcAkhxPvGzw/c3WHaNLh1i2O5G9Em5y1O38lMt24wfnwq0qSJPf124G1c/3Zl1uFZ3A++T+HMhXFp4ELbz9om+4qDJpOJnTt34ubmxurVq4mMjKRq1aoMGjSI5s2bk+bpfxFCiBcF8Gzj4esxxz8BnNABqxqQ2iyjEyJJkMAlhBDvizNnwNkZFiyA0FCia9VlYu1tDFlchCxZDDZtgvr19alKKfbe2Ms0n2msPLuSaFM0DT9uSI/yPaidvzYWhoV5n+Ud3b17l3nz5uHu7s7ly5ext7enW7duODo6UrRoUXMPT4ikSwHHiV0muA9dxt0OXeRiELp0e15zDVCIpEcClxBCpGQmE2zZohsTb92qC198/z1Xm/Wh7Zgi7J4PzZrBrFmQOTOERobyx6k/cPFx4djdY2S0zUjP8j1xKudEAfsC5n6adxIdHc22bdtwd3dn3bp1REVF4eDgwMiRI/n666+xtbU19xCFSJr80KXanzQevhtzvCTQFz2LVQlpPCzEK0jgEkKIlCg4WM9kTZ0K585BzpwwahTKsTMLNmWlx7f6tPnz4fvv4UbAdSZsn8HsI7PxC/Xj06yf4trQlTYl2pA2VVrzPss7unXrFnPmzMHDw4Nr166RJUsWevfuTadOnfj444/NPTwhkp5o4BCxywR90DNb9kBddMCqC+Q01wCFSF4kcAkhREpy/brem+XuDv7+ULYsLFoEzZvzICAVXbroOhnVqsH8+YqreNNsmQtrz60FoEmRJnQv1x2HjxySdQPfqKgoNm/ejJubGxs2bMBkMlG7dm0mTJhA48aNSZUqlbmHKETScofYxsNbgUfowhYVgGHokFUWaTwsxFuQwCWEEMmdUrBvn57NWrVKH/v6a+jVCypVAsNg82Zo317Xyxg5OoLMtebx1WYXTt0/RebUmelXuR9dy3UlT4Y85n2Wd3T9+nU8PDzw8PDg1q1bZM+enf79+9OxY0cKFEjeSyKFiFcRwH50wNqE3pcFkANoTGzj4cxmGZ0QKYoELiGESK4iImD5cr0/6++/IWNG6NMHunWDPDo4hYRA374wYwYUKhJBrSHOTAwYxePNjymVoxRzvprDd8W+I7V18i0hFhkZyYYNG3Bzc2Pz5s0A1KtXDxcXF7788kusrWVjiRAAXCV2FssLCET/JFgFGAs0AEogJduFiGcSuIQQIrnx9QU3N5g+He7cgcKFdaJq2xbSxu63OnQI2rRRnD9vkK/BGi6UbskVvyiaF21O93LdqZy7crJeNnjlyhVmz57NnDlzuHv3Lh9++CGDBw+mY8eO5M0rJdKEIBTYRexerH9ijucBWqFnsWoCybu7gxBJngQuIYRILk6e1MsGFy6E8HCoVw/mzIG6dcEitkx7VBT8OjKMsaOtsbC7D23bEFL8NEPL9OPHsj/ygd0HZnyIdxMREcG6detwc3Nj27ZtWFhY8MUXX9C5c2caNGiAlZX8b028xxRwntiA5Q2EATaAA/AjOmQVRmaxhEhE8n8mIYRIykwm2LhRLxv08oLUqeGHH6BnT3hJv6hthy7Tti3c/Sc/FFtMqU5z6V2jA82LNsfGyibxxx9PLly4wOzZs5k7dy6+vr7kyZOH4cOH06FDB3LlymXu4QlhPoHATmJD1pWY44WJDVifA9LDWwizkcAlhBBJUWAgzJunGxVfvAi5csG4ceDoCPb2z5wabYpmw/mNDJxwiTOencAykqq9Z/B7n3KU+3CbecYfD8LDw1m1ahXu7u7s3LkTS0tLvvrqKxwdHalbty6WllIuTbyHFHCS2IC1B4gE0gK1iO2Llc9cAxRCPE8ClxBCJCVXruiy7rNnQ0AAVKwIo0bpqoPPFX94FPqIOUfn4LJzKdc8B8G5XuQvfYUVi+0oVdjJTA/w7s6ePYu7uzsLFizAz8+PfPnyMXr0aNq3b0/OnNL4R7yHHgLbiW08fDvmeAmgNzpgVQGk24EQSZIELiGEMDelYPduvWxw7Vq9H+ubb+Cnn6BChRdOP3nvJNN8prHw5EJCTtXE+s8tWIenZ8zEaP7XO9/T27mSjdDQUFasWIGbmxt79uzB2tqaJk2a4OjoSK1atbBIjg8lRFw5QEn/knAs5vcm4DC6XPtm4GDMsYzENh6uByTf7ZhCvFckcAkhhLmEh8PSpTpoHT2qlwr27w9OTnoJ4VOiTFGsO7cOFx8XvK96YxOdmY8ObuTc1uoU/UzX0ShWzEzP8Q5OnjyJu7s7np6e+Pv7U7BgQcaPH0+7du3Ili2buYcnRKIxIg3wJLbx8AN0YYtywGB0yCqH/OQmRDIkf2yFECKx3bsHrq4wc6b+ddGiusx769aQ5tmd7Q9CHjD7yGxmHJrBjYAb5M2QF6ccnmwa35LzVyzp1w9GjACbZFQPIzg4mGXLluHm5saBAwdIlSoVzZo1o3PnzlSvXj1Zl6oXIk5MwDnAJ+brMGQIygBtgWzoflj1gTpAVrONUggRTyRwCSFEYjl2TJd1X7xYNy3+4gvo1Qtq14bnQsaRO0dw8XHhj5N/EB4dTs18Nfm9tgtHlzZi3FgLcucGb2/4/HPzPMrbOHr0KO7u7ixatIiAgACKFCnC77//zvfff0+WLFnMPTwhEs4d9LLAJwHrEBAQ85odYAWhOUJJvSE1lARkBa0QKYoELiGESEjR0bB+vQ5a3t56BsvREXr00A2LnxIZHcnKsytx8XFh3419pLVOS4dSHehWrhtWjz6lTRv4+29o105fLkMG8zzSmwgJCcHNzQ13d3f+/vtvbG1t+eabb+jcuTNVqlSR2SyR8gSi9189HbBuxrxmhS500RooH/NVBKgJ4f7hpC6dOvHHK4RIcBK4hBAiIQQE6KbEzs668mCePDBhAnTsCJkyPXPq3aC7uB12w/VvV+4E3aFApgJMrjeZH0r+QAabjMycCT//rFtwrVgBzZqZ6ZniKDw8nB07dtChQwfu37+PyWSiWLFiODs706ZNGzI99/xCJFuRwCl0qHoSsM6gS7cDFACqARXQ4aokIJlKiPeOBC4hhIhPFy+CiwvMnat7aVWtqoNW48ZgFfstVynFwVsHcfFxYfnp5USaIqlfsD6zy8+mfsH6WBgW3LkDLTvA5s1Qv77Ob0m1KnpAQAAbN25kzZo1bNy4kcDAQCwtLcmQIQMbN26kQoUKMpslkjeFbirs89TXESA05vUs6FD1DbGzV5njeG1vOOZ9DAcc4nHAQoikQgKXEEK8K6X0csEpU/TyQSsraNFCl3UvW/aZU8Ojwll6eikuPi78fftv7FLZ0bVsV7qV78bHmT/+97xVq6BzZwgJ0W25nJxe2OZldnfv3mXdunWsXr0aLy8vIiMjyZYtGy1atKBp06aMGzeOgIAAKlasaO6hCvHm/NB7rZ5eGvgg5jVboAzQhdhwlQ9dVVAIIZ4jgUsIId5WWJgugDF1Kpw4AVmywODB0LXrC1NRNwNu4vq3K26H3fAN8eWTLJ8w/YvpfF/ie+xs7P49LyAAevaE+fN1VvP0hCJFEvvBXu3ChQusWbOGNWvWsH//fpRS5M+fn549e9K0aVMqVqyIpaUlAF988QXe3t7mHbAQcRGK7oH19NLASzGvGUBRoBGxSwOLAdYvXkYIIV5GApcQQrypO3d0SXdXV/D1heLFwcMDWrUCW9t/T1NKsef6CEma1QAAIABJREFUHlx8XFh1dhUmZaJR4Ub0KN+DWvlqvbDEbvdu+P57uHFD57ahQ8HazD/UKaU4cuQIq1evZs2aNZw+fRqA0qVLM3z4cJo0aUKxYsVkuaBIPkzAPzy7NPA4EBXzei50qHKM+WdZdCVBIYR4SxK4hBAirg4f1rNZS5ZAVBQ0aqSXDdao8cx6v5DIEBafXMw0n2kcv3ecTLaZ6F2xN07lnMiXKd8Llw0Ph2HDYPx4yJ8f9uyBSpUS88GeFRkZye7du/+dybpx4wYWFhZ8/vnnTJ06lcaNG5M3b17zDVCIN3GbF0uyB8a8ZoduJtyX2KWBH5hhjEKIFE0ClxBC/JeoKFi7Vu/P2rMH0qXTSwZ79ICCBZ859ar/VWYcmoHHUQ8ehj6keLbiuH3pRusSrUljneallz99Wvc7Pn4cOnWCyZP1LRJbSEgIW7ZsYc2aNaxfv55Hjx5ha2tLvXr1GDFiBF9++aX0yhJJXwC6JPvTSwNvxbxmBXwGtEEHqwpAYaTnlRAiwUngEkKIl/H318sEXVzg2jXIl0+nofbtn2mApZRix5UduPi4sP78egwMmn7SlB7le1AtT7VXLrUzmXTF+AEDIH16nem++iqxHu7/7d15fNTVvf/x10lI2AMJJIBCBBK2BBABEQhUQEQESYK41gVbhWut/rS9rWvb69rWbvbWblq9YtXe9mJLiKh1QYOyRBBZAwJh3wlhCyGELOf3x5nJTCYBApnJQt5PH9/HkJnznTnffM0k7znnfL5Ofn4+77zzDhkZGXz44YcUFRURHR3NlClTSE9PZ8KECbRu3bpuOyVSUyXAGnwjV18A6/GVZE8ErsQ3cnUZrtiFiEgdU+ASEfG3caNLQrNmQWEhXHmlG92aMgU8xSAAjp86zhur3uD3y37Purx1dGzVkUdTHuXeoffSrV23M77Erl1w110wfz5cdx288gp06hTaw/Lavn07c+fOZc6cOXz++eeUlZXRtWtX7r77bqZOncro0aOJqO+FYyKB/Euye0euvgJOeh73lmS/2XN7OTUvyS4iEmIKXCIi1rr089vfwrvvQmSkK4Dx4IMwaFClprmHcvnD0j/w2srXOFp8lCFdhjArbRY397+ZFs3O/vH53//uZiSWlMDLL7tphKGsN2GtJScnp6LoxVdffQVAcnIyjz76KOnp6QwZMkRFL6RhOYhba+UfsPI9j3lLsn8HX9XA7qgku4g0WApcItJ0FRXBm2+6Qhg5ORAXB08+CffeW2nIqdyW80HuB7y49EXez32fiLAIbky+kQeGPcAVF9fsgr6HD8P997sq8sOHu3LvAUvAgqasrIzs7OyKkLV582aMMQwfPpxf/OIXpKen06tXr9C8uMi5KgJWUHlq4BbPY96S7Gn4pgaqJLuINDJ1HriMMd2AF4CrcW+lHwMPWWt31GDfFsAzuCWv7XFXzXjEWvtZQLttQHUltKZaazNqdQAi0vjt3g1//CO89BLk57tRrNdfdxcrbt68otnRk0eZtXIWf1j2BzYd2kTnNp158sonmTlkJl3adjnDC1T2yScwfbqrJv/00/DYY+7ayMFUXFzM/PnzycjIYO7cuRw4cICIiAiuuuoqHn74YaZMmUKXLjXvs0hIeEuy+1cNXE3Vkuz/4bkdgkqyi0ijV6eByxjTCvgEKAam42ZlPwt8aowZaK0tPMtTvApMxhVw3QJ8F/jAGDPCWrsyoO0HwJMB922o3RGISKO2dKmbNjh7NpSVQXo6PPQQjB5daV7f+rz1/H7p73l91esUlhQyousInhrzFNOSphEZHlnjlzt5Eh5/3NXa6NMHliyByy8P3uEcPXqU9957j4yMDN577z2OHz9O27ZtmTRpEunp6UyaNImoqKjgvaDIudpN5ZGrL/GVZI9CJdlFpEmo6xGuGUBPoI+1NhfAGLMa2IT7POs3p9vRGHMp8E3g29ba1zz3LQBygKeBwPpeB6212UE/AhFpXEpL4V//ckFryRJXEvCBB9z8vp49K5qVlZcxb+M8Xlz6IvO3zqd5eHNu6X8LDwx7gCEXDTnnl121ypV7z8mB++6DX/4SWlVfGf6c7N27l8zMTObMmcMnn3xCSUkJcXFx3HrrrUydOpVx48bR3G+UTqTOHMMFKv+AtcfzmLck+x34wpVKsotIE1HXgSsVyPaGLQBr7VZjzCLcDO3TBi7PviXAP/z2LTXG/B141BjT3FpbHKJ+i0hjc+gQ/OUv8Pvfu7KACQmu+uBdd0Fb3xylQ0WHePWrV/njl39k25FtdI3qynPjnmPG4BnEto4955ctK4Nf/xp+9CPo0AHeew+uvbZ2h7Jx40YyMjKYM2cO2dnuc6SEhAQefPBBpk6dyhVXXEG4XwVFkZDzlmT3nxoYWJJ9DL6iFoNQSXYRabLqOnAlA3OruT8HuLEG+2611p6oZt9I3Nt7jt/9U4wxJ4Bw3HLcn2v9lsgFaswYBh05AitXwvr1Lli9/rorinHVVfCnP8GkSRDm+zh99f7VvPjFi7y15i2KSou48pIr+dXVvyKtbxrNws7vrXHbNrdW67PP4Prr3RKx87lWsLWWL7/8koyMDDIyMli3bh0AgwcP5plnniE9PZ3k5GRVFpS6YXGT+P1HrlZQuST7Fagku4jIadR14IoBDldz/yEguhb7eh/3egdXUHYr0Am4H5hjjLnDWvvmOfVYRBo+a2l27BhMnAgffOAKX9x+uyvrPmBARbPS8lIyvs7gxaUv8tn2z2jZrCW3D7yd+4fdz8BOA2vz8rzxhpulCO4SXnfeeW7l3ktKSvjss8+YM2cOc+fOZdeuXYSHh/ONb3yDe++9l7S0NOLj48+7jyI1dhBfuPJugSXZ78M3NbA7KskuInIGxlp79lbBejFjTgG/ttY+FnD/c7hqg6cNgMaYj4A21toRAfdfDXwIfMNa+/lp9g0HsoHO1tpqr0hqjJkJzATo1KnTkL///e81P7AQOn78OG3atKnvbkgAnZcGoLycqHXriF2wgIvnziWspITiDh3Yk5bGnilTKGnfvqLpkVNHmLd3Hpl7M8krzqNzi86kX5TOtZ2vJSqidkUljh5txgsv9GbBgjgGDDjCY499TZcuJ8++I1BUVMSyZctYuHAh2dnZFBQU0Lx5cy6//HJSUlIYMWIE7dq1q1X/6pt+Vhoe/3MSVhxGm01tiFofRduv2xL1dRQt97QEwBpLYfdCCvoWcKzvMQqSCijsXohtVnd/NzQl+llpeHROGqaGdF7Gjh273Fo79Gzt6nqE6zCVR6K8oql+9MrfIaC6j3ej/R6vlrW2zBgzG3jeGNPFWru3mjYvAy8DDB061I4ZM+Ys3akbWVlZNJS+iI/OSz0pL4cvvoD/+z94+223NisyEqKiKGzdmtabNtEjMpIenuZf7vmSF5e+yN/X/p1TZacY33M8Dwx7gMm9JhMeVvs1Tx984C5ifPAg/Pzn8IMftCc8fPgZ9zl48CDvvPMOGRkZfPjhh5w8eZKYmBiuv/560tPTmTBhAq2CUV2jgdDPSgNyEhgFJw6coNXkVm5q4Boql2QfQcXIlRliaNO2DW1oQxd0SYFQ089Kw6Nz0jA1xvNS14ErB7cWK1ASsK4G+041xrQKWMeVBJwCcqvfrYJ3woM+mhNpTLwha/Zst3lD1sSJLuVMmQKpqZQcOQKRkZwqO8Xb697mxaUvkr0rmzaRbZgxeAbfvfy79IvtF5QunTgBjzzi6nEkJcG778Jll52+/bZt25g7dy5z5szh888/p7y8nG7dujFjxgymTp3K6NGjaRbsC3NJ01WK+424NmDbBJRDK1rB33BrrR7Gt+5KJdlFREKirn/DZwK/Msb0tNZuATDGdAdSgEdrsO9TuOIar3v2bYZbpvvhmSoUetrdCOyw1u6r5TGISKj5h6y334adO30h62c/cyHLf6pdVhbzP/gna7Ke5KXlL7Hv+D56xfTivyf+N9MvnU67FsGblrd8uVse9vXX7hJeP/sZtAiovmatZc2aNRVFL1asWAFA//79efzxx0lPT2fw4MEqeiG1Uw7soGqwWo/7GBLcR42JQH/gJuBtOFZ+jKh1USrJLiJSR+o6cP0FV8BirjHmR7jRpmeAncBL3kbGmEuAzcDT1tqnAay1K40x/wB+a4yJwBXE+A7QA7jNb99bcSXm3/M8byfcBZKHALeG+gBF5DxZW3m6oDdkXXMN/PSnVUMWsKdgD/M2zuOx+Y9xqOgQBsO1va7lgWEPMCFhAmEmeH9Rlpa6AbWnnoJOneDjj10BRK+ysjKWLFnCnDlzyMjIYMuWLRhjGDFiBL/85S9JS0ujV69eQeuPNCEW2EfVYJUDFPq164YLVhM8t/2BvoD/DNWn4ausrxgTNibUvRYREY86DVzW2kJjzDjgBeAN3Gdv84GHrLXH/ZoaXDn3wL+WvgU8BzwLtAdWAROttV/5tdkKxAG/xK0XO4GrWDjRWvtB0A9KRM6fN2R5pwv6h6znnoPU1Eohy1rL2gNrydyQydwNc1m2ZxkALZq1IDYylsX/sZjEmMSgd3PzZrjjDnfd5FtugT/+EaKj4eTJk8yfP585c+aQmZlJXl4ekZGRXHXVVTz66KNMmTKFzp07B70/cgE7TNVgtZbKq5Q7AgOAb+MLVslA466vIiJywarzRQPW2h3AtLO02UY1RWattUXA9z3b6fbNBsbVrpciEjLWwtKlvpGsHTvOGLJKykpYuGMhczfMJXNDJluPbAVg2MXDeG7cc6T2SSU5NpkFCxYEPWxZC6++6qYONmsGb70FkyYd4b333iMjI4P333+f48eP07ZtWyZPnkx6ejrXXnstUVG1q3woTUAhbuVyYLDa49cmChempuELVv1xHymKiEijoVXaIhJ63pDlHcnasQMiIlzIevbZKiHrWPEx/p37bzI3ZPLupnc5cvIIzcObM77neB4d9ShTek+hS9vQVk07cABmzIDMTBg5cg+TJ8/l9dczuOuuTykpKaFz587cdtttpKenM3bsWJo3bx7S/kgjdQrYQNVgtcWvTQtc+afxVA5WXdH1rURELgAKXCISGv4h6+23Yft2X8h65hkXsvyulbXz6E4yN2SSuTGTT7d+Skl5CR1bdSS9bzqpvVOZkDCB1pGt66Tr8+bB9OkbOHo0g/j4OSxe/AWLF0NiYiIPPfQQU6dO5YorriAsTFUHxKMMF6ICg9VGfGXXw4E+wFDgLnzBqqfnMRERuSApcIlI8FgLy5b5pgt6Q9aECfD005VClrWWlXtXVKzHWrHPVfLrFdOLB694kLS+aYzoOiIo18uqifLycj7/fDkPPTSHlSszcKXeIDZ2CDNnPkt6ejpJSUmqLNjUWVw5puoqA/pf77onLkyl4wtWvQENhIqINDkKXCJSO96Q5Z0u6B+ynnoK0tIqQtapslMs2PxRxXqsncd2YjCM7DaS58c/T2qfVPp27FtnXS8pKWHBggXMmTOH2bPnkpe3GwgnPv5Kvve9+5g2LY1u3brVWX+kgTlA9ZUBj/m1uRgXpsbhClf0x00PrJvBWBERaQQUuETk3J1DyDpcdJj31/yNuRvm8u/cf3Os+Bgtm7VkQsIEnhrzFJN7Tyaudd1VATh+/DgffPABGRkZzJs3jyNHjtCsWUtKSycSE5POrFnXMWVKTJ31RxqAo7ggFRiu8vzaxOAqA95B5cqA0XXaUxERaYQUuESkZqyFL7/0haxt21zIuvpqF7JSU12tdGDr4a1kZr9O5sZMPtv+GaXlpXRq3Ymbkm4itU8q43uOp2VEyzrrel5eHu+88w4ZGRl89NFHnDx5kpiYGMaOTWfNmnRyc6/mzjtb8bvfVbnUl1xIinBT/wKD1U6/Nm1wQSqVygUsOqECFiIicl4UuETk9KoLWc2auZGs//ovN5IVHU25LWf5nuVkrnDrsdYcWANAUmwSPxz5Q1L7pDLs4mFBvRDx2WzdupWMjAwyMjJYuHAh5eXlxMfHM3PmTNLTp5KTM4qHH25Gy5bu0G64oc66JqFWAmyiarDKxa3BAogE+gHfoHKwiqfqFSBFRERqQYFLRCqzFpYvd4Uv/EPW1VdXClknS0/yydZPyFyUyTsb32FPwR7CTBij40fz6wm/JrVPakguQlydMWPg8OFL+etfV5GRkcGcOXNYtWoVAAMGDOCJJ55g6tSpDBo0iH37DHffDe+/7wom/s//wEUX1Uk3JdjKcZe6DwxWG3ChC1x46g1cCtyGbypgIvoNKCIidUK/bkTEF7K8I1lbt/pC1k9+4kJWTAwHTxzkvU3vMPejuXyQ+wGFJYW0iWzDxMSJpPZOZVKvSXRo1aGOumzZsmULixYtYsmSRykpOcSgQcUYYxg5ciS/+tWvSEtLIzHRF/r+9S+YORMKC+HFF+G73wUVHWwELO6CwIHBah1wwq9dd1ygug7fiFUf3HWuRERE6okCl0hTdaaQ9eMfV4SsTfmbyPz6NTI3ZrJwx0LKbTkXtb2IOwbeQVrfNMZ0H0OLZqH/i7akpISVK1eycOFCFi1axMKFC9m/f7/n0XDCw6P4059eJDU1lU6dOlXa99gxePBBmDULhgyBN9+EvnVXDFHORT5Vg9Va4Ihfm864MDUTX7BKAtrWaU9FRERqRIFLpCmxFr76yjdd0Buyxo+vCFnl0e35YtcXzP3qF2RuyGT9QXc9qoGdBvLE6CdI7ZPKkC5DQn49qqNHj7JkyZKKcLV06VJOnHDDGd27d2f8+PGMGjWKlJQU7r8/maNHjzFjRvsqz/P553DnnbBjBzzxhBuwi4wMadelJgpwI1SBwWqfX5v2uDB1C5UrA3as056KiIjUigKXyIXOG7K8I1lbtvhC1o9+BOnpnGjbgo+3fEzmwod5Z+M7HCg8QLOwZlx5yZXcO/ReUvuk0r199xB20bJjx46K0atFixaxZs0arLWEh4czaNAg7rnnHlJSUkhJSeHiiy+utH912e/UKbfk7PnnoUcPF7xGjgzZIchphJ0Kg1VUDVbb/Bq1wgWpa6lcwKILqgwoIiKNngKXyIXIWlixwjeS5Q1ZV13lhnnS09kfWcK8jfPI/PBbfLT5I4pKi4hqHsWkXpNI7Z3Ktb2upX2LqiNGwVBaWsrq1asrRq8WLVrE7t27AWjbti3Dhw9n2rRppKSkcMUVV9CmTZtzev6cHLj9dli5Eu65B37zG2ir6WahVY4LUauBNZ7tXRh9YrSvTQTQFxgBzMAXrLqjyoAiInLBUuASuVB4Q9bs2S5o+Yesxx/HpqXxtc0jc0Mmc+dcR/aubCyW+Hbx3H3Z3aT1TeMbl3yDyPDgz7crKCggOzu7YvQqOzub48ePA9C1a1dGjx5NSkoKo0aNYsCAAYSHh5/X65SXu2IYjzwCUVGQkeGWokmQ5eMLVd6AtRYo9DxugJ5ASyhuW0yL37VwwaoXLnSJiIg0IQpcIo2Zf8iaPRs2b4bwcDdd8PHHKU29jiUnNjJ3w1wy//d5Nh3aBMDgLoN5csyTpPZJ5dJOlwZ9PdauXbsqjV6tWrWK8vJyjDEMHDiQ6dOnV0wPjI+PD8prnjpluOYa+PhjuO46eOUVCKidIeeqGHehYP9gtQZXMdCrAzAAuNtzOwA3PdAzKJmdlc2YMWPqqsciIiINjgKXSGNjrZsr550u6A1ZV10Fjz3G8Unj+fDIcjI3ZDLvtUfIL8onIiyCcT3G8b3h32NKnyl0jeoatO6UlZWRk5NTqXrgjh07AGjVqhXDhw/niSeeYNSoUQwfPpyoqKigvG5eHqxb56YPbtoE+/e3Zft2eOklmDFD5d7PiQW2UzVYbQDKPG2a4yoBjseFqoGe285onZWIiMgZKHCJNAbekOWdLugfsh59lH3jhzP34CIyN/6L+a9+l+KyYqJbRDO592RSe6dyTeI1RDUPTtApLCxk6dKlFQFryZIlHDt2DIAuXbowatQovv/975OSksKll15KRETt5pAdOOALVv63eXm+NuHh0KpVGcuXh9GrV61e7sJ3GF+g8gastbiqgV49cGFqKr5g1Qv9xhARETkP+vUp0lD5h6zZsyE31yWLceOwjzzC+pQ+zDn4OXM3vMyy12cA0KN9D74z9Duk9U0jpVsKEeG1XzCzd+/eirVXCxcuZMWKFZSVlWGMITk5mVtvvbWiPHv37t3Pa3qitS5A+Ycq778PHvS1a9cOkpPduqzkZEhKcrff/CYcPVpIr16hKfLRKJ0CvqbqWqtdfm2icWFqOr7pgP3R9axERESCSIFLpCGxFlat8o1k+YWs0h/8J0uGduKfeQvI3PAzts7eCsAVF1/Bc+OeI61PGkmxSbVaj1VeXs769esrrb/asmULAC1atGDYsGE88sgjpKSkMGLECKKjo8/58A4cqDpalZMD+fm+du3buyA1dWrlYNWlS/VTBZv09EEL7KTqdMCvgVJPmwigHzAGX7AaCFyEpgOKiIiEmAKXSH3zD1mzZ7sFSeHhMHYsRd97gA8GtmL2gU95b9NjHJl3hObhzRnfczyPjXqM63pfR5e2Xc77pYuKili2bFnFCNbixYs5fPgwAHFxcaSkpHDfffcxatQoLrvsMiJreMVga2H//uqD1aFDvnbeYDVtmi9UJSWdPlg1eUdx0//8g9Uaz/1e8bgwNQVfsOqNqgOKiIjUEwUukfpgLaxe7St84ReyDn3328zpC/+X9ymfbv0BJfNL6NiqI+l900ntncqEhAm0jmx9Xi+bl5dXafRq+fLllJSUANC3b9+Ka1+NGjWKhISEs46WWQv79lW/xso/WEVHuzB1442Vg1XnzgpW1SrBFawIXGu1w69NO1yg+ia+dVb9PfeLiIhIg6HAJVJXvCHLO11w0yYIC8OOG8fOGTfxj16n+N/9H7Ni32OQDb079Oah4Q+R2ieVEV1HEB52btemstayYcOGSuuvNm1yZeEjIyO5/PLL+d73vseoUaMYOXIkHTp0OGPX9+6tPlh5BsQAiInxBSv/qYCdOilYVcsCu6m6zmo9LnSBe5fuC6QA38E3JbAbmg4oIiLSCChwiYSSf8iaPRs2boSwMMrHXMn66ZN4o2cBf9v3ETuPfYxZZRjZbSTPj3+etD5p9OnY55xeqri4mOXLl1eMXi1evJiDnooTHTp0ICUlhXvuuYdRo0YxZMgQmjdvXm139+6tfirgkSO+dh06uCB1882Vg1VcnILVaRXgpgMGrrXyC6x0xY1WXYsvWPUFgn8tahEREakjClwiwWYtrFnjmy7oCVklV45mxc2j+MslB/nHgU8pOPUpLbe05JrEa3hqzFNM7j2ZuNZxNX6Z/Px8Fi9eXDF69eWXX1JcXAxAr169uO666yqqB/bp06fS9EBrYffuqsFq3brqg9Wtt1aeCqhgdQalwCaqrrPa6temLS5M3YRvnVV/XNVAERERuaAocIkEgzdkeacLekJW0agrWJx+I3/ouofMwwspswvodLgTNyffTFrfNK7qcRUtI1rW4OktmzdvrrT+av369QBEREQwZMgQ7r//flJSUkhJSSEuLq6iW7t3w0cfVQ1XR/0KLXTs6CuvHhis5DQssI/KwWo1bjpgsadNONAHGAbcjW+t1SVoOqCIiEgTocAlcr6shbVrfSNZGzZgw8IoGDGYTydN5IUu21lQtASApPAkHk55mNQ+qQy7eBhhJuyMT33q1ClWrFhRsf5q0aJF7N+/H4D27dszcuRI7rjjDlJSUrj88stp0aIlu3a5IPXmm5WDleeaxADExrowddttlacCxsaG7LtUJ7KyICtrJa7ueQgcB3KoutbKr5Q9F+HC1NX4pgP2A6rO3BQREZEmRIFL5FwcOQLjxjF8zx5X09wTsvKHDeCD+0bzfNxG1vAlYSaM0XGj+U2fGUzpM4XEmMSzPO0RlixZUjF6tXTpUoqKigDo2bMnEyZM8IxejaJt236sXx/GunXw+uvwyCNVg1VcnAtSd9zhC1ZJSY0/WIVcGZBL1XVWW3AjWgCtcdP/rscXrAYAp685IiIiIk2YApeIv9JS2LkTtmxx2+bNvn9v2VJRkq85sDc+hsx7BvF87Ea2Nl9Fm8g2TEycyA97pzKp1yQ6tKr+L3BrLdu2batUPTAnJwdrLeHh4Vx22WXMnPkf9OmTQlRUCvv2dSEnB157DX74Qygo8D1Xp04uSN15Z+WpgB071sH3qrHbT9VglQOc9Dwehrt+1WBgOr61Vt09j4mIiIjUgAKXND1Hj1YNUt5wtX07lJVVNLUREZTFd+PIxR3YPTaZDe1OsXjfl/yjXzn7otZzUduLSO19J2l90xjbfSzNm1WdP1ZaWsqqVasqRq8WLVrEnj17AIiKimLQoBHcdttNtG49isLCYWzc2JpXX4Xjx33P0amTC1N33VU5WJ2hkrt4naD66YB5fm064wLVffjWWfUDzr68TkREROSMFLjkwlNaCrt2nX6Uyv+KvOCGg3r25OTggeybOILN0ZZVrQtYFLGXBSW55J/agptTBh1adqC0d1ua05xld77LkC5Dqlwc+NixY2RnZ1eMXn3xxRcUFhYCEBsbz8UXjyE+PoWCghS2bevPZ5/5rq/VubMLU9/6VuWpgApWNVCGqw4YGKxy8U0HbAUkA1PwBasBgKZaioiISIgocEnjdOzYmUepSkt9bZs1g+7dISEBLr+cwq6d2NYhnJw2J1ja/CDLCzex9sBaDp5YWrFL+7D2JMckMy32JpLjkukf15/k2GTiWsdhjCErK4uhFw0FYOfOnZVGr1avXk15eTnGhBEdfSmtW3+L0tJRFBenkJfXlbw86NLFBaqrrqocrGJi6vj72JicBHYBO4Cdns3778/gypNXQrmnrQEScaHqNnzTAXvgKgeKiIiI1BEFLmmYysrOPEqVn1+5fYcO0LMnDB0KN90ECQkc7xrHhqgSvgo/wNr89eTk5ZCTN4d9x/e5ct5A28i2JMclk9YnjeTY5IrJl2EjAAAdgklEQVRw1aVNlyojV+CKW4wbt4n9+5cxePBLZGcv4uDBnQCEhbUGRlBe/mMgBWuH06JF20pTAL230breUmWlwF6qBin/f+dVs18c0A1oCcWtimnxfAsXrJJwo1kiIiIi9UyBS+rPsWOwdWvVMOUdpSop8bVt1gwuucSNUt14owtXnq3g4ljWndpNTl4Oaw+sJSdvOTkH/sruXbsrdm8V0Yqk2CQmJk50wcoTrrpFdQu4ILAlPz+fL3K+IDc3l02bclm1Kpevv97Mrl25FBYerGi7Z89FwCjgB8TGjmLgwIEMGNCsIlj166dgBbjpfAepGqT8v96DmxLoLwoXpuKBoZ5/e7/uBnQFWviaZ2dlM2bMmJAdhoiIiMj5UOCS0Ckrc1fdDQxT3n8fPFi5fUyMC1GDB8MNN7hw5Q1WXbtSWF7M+oPryTmQ4wlXn5KzIIcdR3dUPEWLZi3o17EfY3uMpX9sf5LjXLi6pP0lFde+stayb98+clfnMj93Prm5ueTmbmb9+ly2bMmlsNDvisAY3F/4icA0oqISKCtLIDIymeef701ysiEpyVWIb7IKOH2Q8m4nA/Zpji9AjaVykPJu7eqg7yIiIiIhpsAltVNQUP0o1ZYtsG0bnDrla+sdperZE6ZNqzRKRc+eFamlqKSIrw9+7aYAHviInCUuYG09vBXrqX4QGR5J3459SemWwszBM90aq7hkerTvQXhYOOXl5ezatYvc3Fw+XvCxJ1TlVoxaFRWd8DuIcIzpgbWJwHAgkZiYRPr2TWTw4B5cemnzijVW7dvDmDFuauGMGVWnHF5winHrps401e9owD5huIsAdwMuA9KoOjoVi8uyIiIiIhc4BS45s/LyM49S5QUsrImOduHp0kvh+usrB6pu3Vzo8iguLWZj/kY3DfCrf3kCVg6bD2+m3LrqB83CmtGnQx+GXjSU6ZdOJznWrbFKiEmActixY4cLUp/ksiB3QUWo2rJlC8XFxRWvFRYWSWRkT0pKEikrG4cbsUokLi6RAQPi6d8/guRk3xqrM41YZWVBVtZKYEywvsv1owy3lu10QWon7lpVgTriQlMC7lsQODp1EXpnEREREfHQn0XiLvh0ulGqrVsrj1KFh0N8vJvuN3Vq1VGqahYtlZSVsOnQJnI2zPGssXIjVpvyN1Fm3cKdcBNOYkwiAzsN5Nb+t1ZMBYxvE8+enXtckFqZS1ZuFq/kvkJubi7btm2j1K8aYURES9q0ScTavpSXX4c3VLlgdTH9+4dXClUXdPEKCxzi9EFqJ7AbV6zCXxt84WkQVaf5dUXFKERERETOgQJXU1BeDnv2nH6U6sCByu3btXOBasAASEurvJaqWzeIiKj2ZUrLS9l8cEPFSJW3iMXG/I2UlLsCGAZDQkwCybHJTOs3jeTYZHq26UnE0Qh2bPONVi3KXURubi47d+6kvLy84jVatYoiOjqRiIjBxMbexKFDiRQXu1BVUtKZFi1MpYqAF2xVwOOcfs2U999FAftE4gJTN+AbVA5S3mDVDk31ExEREQkiBa4LRWHhmUep/KbXERbmW0uVllZ5hCoh4azppKy8jK1HtlaEKm/A+vrg1xSX+V6nR/seJMclc13v6+jZsidtC9tSnl/ugtXKXD7P/ZxZm2exe/fuSs8fHd2BuLhEYmJGER2dyLFjiezdm0hRUQInTnTkxAlTcYHgwBGrC+I6Vqdwo09nmup3OGAfA3TBhaZLgeuoOtUvDre+SkRERETqjAJXQzZmDIOOHIGVK90o1d69px+l2h+w2CYqyoWn5GRITa0cquLjTztK5a/clrPj6A43DdAvXK3PW09RqW/4JL5dPMmxyYzqOIqYkzFEHImgOK+YHct3sHnzZl7LfY0DAaNonTt3plu3RPr1u5oBA1yYystLZPv2BA4fjubwYW87dwiTJ1cOV402WJXj1kWdLkjt8DxuA/aLwYWnS3CV6P2DVDxu3dTZT6mIiIiI1DEFroYsP5/W27e7hLF1K5z0q60dFuam9yUkwJQp1Y9SVXPh3upYa9l1bFfFSNXaPBew1uWto7CksKJdlzZd6N2iN1NaTqHN8TbYQ5aCvQVs37qd7Nxs3j/8fqXn7datG4mJiVx1VRotWiRQVpbI0aOJ7N6dwIYNbVi2zNe2UycXpq66qvJFghtVsLK4kafTrZnagRu5KgnYrzW+8DSZqtP8unraiIiIiEijo8DVkJWVYUpK3BV0J0+uvJYqPh4iI8/p6ay17D2+1zda5QlX6/LWcaz4mGtUDh3LOtKtvBtXnLiCyKORnDxwkvxd+WzdspUFxxdUPF9YWBjdu3cnISGBm2++hdjYRMLCEjlxIpH9+3uwYUNLvvzSVY738gar6dMrj1h16BCMb1iIWNy1pvJ9W+f5nWEBVYNVYcC+EcDFuPCUQvXXm4pG66ZERERELlAKXA1ZXBzHIyNp/89/nvOuBwoPVJkKmHMgh8MnD7tpbUch6kQUnYo70aOgBzbfUrCvgL079nLw5EEO4i5KHBERQY8ePUhMTGTsmLEkJCQSHZ1ISUkiBw9ewoYNkaxbB3/7Gxw7VqnrlYKVd8Sq3oPVSVz1Pr/wVOXrwPsOUaWaX1/6upDUGReakoGJVJ3q1wmtmxIRERFpwhS4GrKsLFZmZZ3xak/5J/IrqgH6h6uDBQfhCHAIWh5rSfui9rQ90paIAxEc2nuI0pJSjnn+a9GiBQkJCQzsN5Drp1xPYmIiCQmJtGmTyOHD3diwIZycHFi6FGbNqhqskpLgjjsqj1h17Bjabw1luOM7U1Cq7usT1T2ZR0vcWqkOni054GvvFgPZO7IZPm24q/wnIiIiInIaClyNxJGTRyqVWs/Jy2Ht7rUc2HXAhYpDEHE0glYFrSg/VE5YXhjlZa6cehFFhLcJJzExkcRhie7WsyUkJGJtF9avDyMnB3Jy4K9/hXXr4OhR3+vHxrowdccdlUuu1zpYWVyJ83MddTpC1cISXmFUDkrea0oFhqfAr1vWvNsnS04qbImIiIjIWSlwNWDvbnyXHy/7Mbvm7SJvZ15FsAo7Ekazw804deRUpdDRun1revXqReKl/oEqgcTERGJj49i715CT48JUdja8+mr1wSopCW67rfKIVWxsDTp8irMHpeqm652q7sk82lI5FPXk7MEpCk3jExEREZEGQYGrAbvn5nvYt3Jfpfs6xHagT68+JI6qHKgSExOJiYnBWneN43Xr3GjV55/7/u0frDp2dGHqttsqj1jFxlKxxqsiFC2jZqNOx89wMJFUDkV9OHtwikGlzkVERESkUavzwGWM6Qa8AFyNKzvwMfCQtXZHDfZtATwD3A60B1YCj1hrPwtoFwY8AvwHrqzBBuBpa+25V5+oR/Nemcef//xnJkyYUBGuoqKiALDWXZYrJwcWL4ZXXqFi9OrIEd9zdIiB5F7wzQmQ3BmSoyGpNcSV4AtK7wNv+X19GBe6qmNwVfW8oagLbq1TNeucKn3dClXiExEREZEmp04DlzGmFfAJUAxMx02Iexb41Bgz0FobWFQ70Ku4KxX9ENgCfBf4wBgzwlq70q/dM8APgCeA5cAtwGxjzHXW2veCeUyhNGTIEL75zdvo02cM61bDZ+9CzmrIWQ/rtsIRv+9Wh+aQ3BZubQVJLSH5FCQXQNwh4AvPFqg1lUNRN84enNoB4SE7ZBERERGRC0pdj3DNwK3C6WOtzQUwxqwGNuFGo35zuh2NMZcC3wS+ba19zXPfAiAHeBpI9dwXhwtbP7fW/sqz+6fGmETg50CjCVzXd4FP9l2J30xAYnADSrd4bpOBpHCIawemI9WHpNNN12teV0ciIiIiItI01XXgSgWyvWELwFq71RizCEjjDIHLs28J8A+/fUuNMX8HHjXGNLfWFgPX4FYMvRmw/5vA/xhjelhrtwbncEIrohWMjCzn2hHhJHeH5D4Qd4lfsPJubdB0PRERERGRBqiuA1cyMLea+3OAG2uw71ZrbeCVlHJwASvR8+9k3JTF3GraASQBjSJw/WMzZGV9zpgxY+q7KyIiIiIich7qunh2DK4kQ6BDuFIM57uv93Hv7RFrbeBVmgLbiYiIiIiIhFR9lIWv7nK1NZkQZ2q4b03bVX7QmJnATIBOnTqRlZVVgy6F3vHjxxtMX8RH56Xh0TlpmHReGh6dk4ZJ56Xh0TlpmBrjeanrwHWY6keYoql+9MrfISD+NPt6H/feRhtjTMAoV2C7Sqy1LwMvAwwdOtQ2lGl8WVlZmlLYAOm8NDw6Jw2TzkvDo3PSMOm8NDw6Jw1TYzwvdT2l0LvGKlASsK4G+/bwlJYP3PcUvjVbObj6ewnVtKMGryMiIiIiIhIUdR24MoHhxpie3juMMd2BFM9jZ9s3Ar/iGsaYZsDNwIeeCoUA/8YFsNsC9r8dWNtYKhSKiIiIiEjjV9dTCv8C3A/MNcb8CLfW6hlgJ/CSt5Ex5hJgM/C0tfZpAGvtSmPMP4DfGmMicJUGvwP0wC9cWWsPGGNeAB4zxhQAX+FC2Thc6XkREREREZE6UaeBy1pbaIwZB7wAvIErZDEfeMhae9yvqQHCqToC9y3gOeBZoD2wCphorf0qoN0TwHHgQaAzsAG4yVr7TnCPSERERERE5PTqvEqhtXYHMO0sbbZRTVVBa20R8H3Pdqb9y3Ch7Nnz7qiIiIiIiEgt1fUaLhERERERkSZDgUtERERERCREFLhERERERERCRIFLREREREQkRBS4REREREREQkSBS0REREREJEQUuEREREREREJEgUtERERERCREFLhERERERERCRIFLREREREQkRBS4REREREREQsRYa+u7Dw2OMSYP2F7f/fDoCBys705IFTovDY/OScOk89Lw6Jw0TDovDY/OScPUkM7LJdba2LM1UuBq4IwxX1prh9Z3P6QynZeGR+ekYdJ5aXh0ThomnZeGR+ekYWqM50VTCkVEREREREJEgUtERERERCREFLgavpfruwNSLZ2XhkfnpGHSeWl4dE4aJp2XhkfnpGFqdOdFa7hERERERERCRCNcIiIiIiIiIaLAVU+MMd2MMW8bY44aY44ZY/5ljImv4b4/NcZ8aIzJN8ZYY8xdIe5uk3C+58QYM9QY87Ix5mtjzAljzA5jzFvGmB510e8LXS3OyyXGmLnGmO3GmCJjzEFjTJYx5tq66PeFrDbvXwHP85jnPWxhKPrZlNTyd4o9zTYo1P2+0NX2Z8UY088YM9vz/lVkjNlgjHkwlH2+0NXid8qTZ/hZOVkXfb+Q1fI9LN4Y87rn768TxpiNxphnjTGtQ93vmtKUwnpgjGkFrAKKgR8BFngWaAUMtNYWnmX/AmAlsAW4E/iWtXZWKPt8oavNOTHG/AoYAbwF5AAXAz8G4oBB1tqdoe39hauW5yUZ+D6QBewCooAZwGRgmrX2XyHt/AWqtu9ffs/TE1gNFAKbrLWjQtPjC18QfqdYYBbwUsBDq621J4Le4SYiCOdlKPAJ7j3sf4CjQC+gjbX2N6Hr+YWrlr9TugJdA+5uDfwbmGOtvSkknW4CanleWgMrgAjgSWAHcDnwFJBprb05pJ2vKWuttjregAeBMiDR774eQCnw/RrsH+a5TcT9T3lXfR9TY99qc06A2GruuwQoB56u72NrzFttf1aqeb5mwE7gnfo+tsa6BeucAB/g/sDPAhbW93E15i0Iv1Ms8Gx9H8eFttXy90oY7gO8OfV9HBfSFoLfKXd4fn4m1/exNeatlj8rEzznYELA/T/37N+qvo/PWqsphfUkFci21uZ677DWbgUWAWln29laWx7CvjVV531OrLV51dy3HcjDjXbJ+avVz0oga20p7lPikqD1sOmp9TkxxnwTGAw8FpIeNj1B/TmRoKnNeRkDJAEayQquYP+sTAf24z5AkvNXm/MS6bk9FnD/EdwHFyZYnawNBa76kQysreb+HNwbrNS9oJ4TY0w/3JTC9bXsV1NX6/NijAkzxjQzxnQ2xvwY6A38IYh9bGpqdU6MMdHAC8DD1tpDQe5bUxWM96/vGGOKPesfPjHGjA5e95qs2pwX7xTbFsaYbGNMiTHmgDHmd8aYlkHtZdMStN/1nimGY4G3PB/myfmrzXn5GNgEPG+MSTLGtDHGjMONmv3Z1nCae6gpcNWPGOBwNfcfAqLruC/iBO2cGGOaAX/GjXC9WvuuNWnBOC+/wI1o7QUeBm6x1s4PTveapNqek18CG3FrhiQ4antO3gTuA8YDM4EOwCfGmDHB6mATVZvzcpHn9h/Ah8DVuPeye4C/BauDTVAw//66A/d39Ou17ZSc/3mx1p7EfUDhnYZbAMwH5gH3B7eb569ZfXegCauuWkmDGPZswoJ1Tn4PjMTN6a7uDUTOTW3Py2+BvwOdcUVm/maMucFaOy8YnWuizuuceEZN7gQGW88kewma8/45sdbe4ffl58aYubhPm5/FN9Ii5+d8z4v3A/E3rbU/8fw7yxgTDvzcGJNkrV0XlB42PcH6XX8nsMJau7qW/RHnfH+vtMB9MBGHC8E7gGHAT3BruL4TxD6eNwWu+nEYl+YDRVN9wpfQC8o5Mcb8DPcJ8XRr7YdB6ltTVuvzYq3dhatSCDDPGJMF/Ar36Zecu9qck5dwo767jDHtPfc1A8I9XxdZa4uD1tOmI6i/U6y1BcaYd4G7a9uxJq425yXfc/tRwP0f4ooBDAIUuM5dsH7XDwP6Ag8FqV9NXW3Oy924NY+J1trNnvs+M8YcBV42xvzZWrsqaD09T5pSWD9ycPNVAyWhN9D6UutzYox5AngUeNBa+0YQ+9aUheJn5UtchU85P7U5J/2Ae3G/QL1bCjDc8+8G8UlkIxSKnxND9Z84S83V5rzkeG4Dz4H3E38Vzzo/wfpZmY4bPdH0zuCozXkZABz2C1teSz23/WrZt6BQ4KofmcBwz3VoADDGdMf94ZFZT31q6mp1Towx/w83/eYJa+2LIepjUxTUnxVjTBhuilTgG7PUXG3OydhqtlW46WtjgbeD390mIdg/J1G469V9EaT+NVW1OS/v465JNDHg/ms8t18Gp4tNTq1/VowxkcAtwHvVVSmW81Kb87IPiDbGBH6QeoXndneQ+lg79V2XviluuAvl5QJrcOUuU3F/dGzBXdDQ2+4S3CcoPwnY/0rgBtxiQItbM3QDcEN9H1tj3WpzTnBvvOW4X5DDA7ak+j62xrzV8rw8CfwOuNnzM3MzbjpOOa5wRr0fX2Pcavv+Vc3zZaHrcNXbOQF+APwF+CZuWs50z/OcAkbX97E15i0Iv+v/y3P/T3EFTR4FioBZ9X1sjXULxvsXcL3nb6/r6/t4LpStlu9h3XEl4Td63r/GAj/03PclnmvX1vemNVz1wFpb6ClZ+QLwBm6KwHzgIWvtcb+mBgin6kjkU7g/IL2+69m8+8g5quU5mei5fyJVP41cgPsjRs5DLc/LV7j59bcA7XCfgq3C/RG5qA66f0EKwvuXBFktz8kGYKpna4f7I2URcLe1dily3oLws/I0ruLafbhgvBdX5fOZEHf9ghWk96/puOp5WgccJLU5L9babcaY4bgPWZ8FOgI7gZeB52wDuXat8aRDERERERERCTJ98igiIiIiIhIiClwiIiIiIiIhosAlIiIiIiISIgpcIiIiIiIiIaLAJSIiIiIiEiIKXCIiIiIiIiGiwCUiIufEGPOKMcYaY35T3305F8aYJz3XemnSjDHdPd+LnvXdFxGRpkCBS0REaswY0xK40fPlbcaYZvXZn3P0X0CTD1xAd9z3QoFLRKQOKHCJiMi5mApEAe8BccDE+u2OABhjmtd3H0REpHoKXCIici6mA4eBu4Ai4M7qGhljLjXGzDHG5BtjiowxG4wxjwW0mWqMWWSMOW6MOWaMWWqMSfV7vJkx5jFjzNfGmGJjzB5jzK+NMS382nT3TG+8zxjzG2PMAWPMCWPMPGNMd7921vPPJzztrTHmSc9jlxtj3jbG7PLr6089o3n+/c0yxiw0xow3xnzleZ21xpj08zz+640x2Z7nOWKMmW2MiT/bCfDrxxRjzApjTDFwn+ex+40xS4wxhzzPmW2Mmey37xjgU8+XH/l9L8b4tZlhjFlljDlpjDlojHnVGBNztn6JiEj1GtNUEBERqUfGmIuA8cDL1to8Y0wGcL0xJtpae9iv3TAgC8gFvgfsAnoBA/3aPAD8DsjAhbjjwGDcdDevN4EpwPPAYqAf8IynzbSA7j0GrAS+hRt5+ynwoTEm2VpbAowAlgCzgJc8++zy3MZ79p0FFADJwE9wU+5uCXidBOC/gZ8BB4H/BN42xvS11uaew/HfC/wJeA14GmgLPAksMMYMtNYWcGa9cd+/Z4AtwCHP/d2BV4BtuN/xU4B5xphJ1tr3ga+A7wJ/AP4fsMyz3zpPv37uOabfAT8ELgaeBfobY0Zaa8vO0i8REQlkrdWmTZs2bdrOugGPABYY4fn6Gs/X9wa0+wzYCbQ6zfNE4YLNv87wWqM9z31nwP23ee4f5Pm6u+frdUCYX7sUz/13+91ngWfPcowGF1RuB8qBDn6PZQElQC+/++KAMuDxczj+NsBR4H8C7u8OnAIeOksfszx9G3SWdmGeY/kQmOt3/xjP92J8Na9fBvwk4H7v9zK9vv8f1KZNm7bGuGlKoYiI1NSdwCZr7RLP1x8De/CbVmiMaYX7A/0ta+2J0zzPSFzoePkMrzURFz7+6Zla2MxToONDz+PfCGj/trW23PuFtXYRbmRpxNkOyhgTZYx53hizGSjGhao3cOGrV0DzTdbaTX6vcwA4gBslq+nxj8CFzrcCjm0X8HU1x1adbdbaldUcyxDPdMr9QKnnWK4G+tTgOa/GhbTAfn0BHKthv0REJICmFIqIyFkZYy4HkoDnjTHt/R76F3C/Maa3tXYjEI37o31XNU/j1cFze6Y2cUAkbqrhmZ7Da381bfbjpsSdzWu4qZI/wU0tLASG4abdtQhoe4iqiv3a1eT44zy3H5/m8cOnud/f3sA7jDHdgPm40b4HgB240PUMbjrm2Xj7lXuaxwO/5yIiUgMKXCIiUhPTPbePeLZAdwI/woWFcs4cdA56bi8G1p6mTT5wEje1sDp7Ar7uVE2bTrgAdVqeAhxpwJPW2v/2u3/AmfY7g5ocf77n9i4gp5rHz7Z+C9wUv0ATgXbATdbaisDnGXWrCW+/JlB96Muv5j4RETkLBS4RETkjY0wkrnjEF8Cj1TR5AbjDGPNja+0JY8xC4HZjzNPW2qJq2i/GjVzNBD44zcv+Gxfs2llr59egmzcYY570Tis0xqQAXXGFMrxOAS0D9msOhOOm3vm7qwavWcU5HH8BkGitff18Xuc0vMGq4liMMb1xUxz9R9yKPbeB34uPcGEx3lr7URD7JSLSpClwiYjI2VyHm072n9barMAHjTEv4SrujcGVHP8BsABYYoz5Ne6P/Z64Ig8PWGsLPCXSXzTG/BN4CxdABgEnrbUvWmuzjDH/i6sA+BtgKS4MdAcmAY94pjB6tQUyPH2JxVUR3AT81a/NOmCyMebfuBGcPdbaPcaYbOA/jTF7caNv36ZmUxFP52zHf8wY80PgD8aYWOB9XBGNi4ErgSxr7d/O43U/xk0h/KvndbsAT+GmFvqv2d7oafdtY8whXADbYK3dbIx5Hvi9MaaP5xhOAt1w67tesdZ+ioiInBMVzRARkbOZjgtEs0/z+P/irsk1HcBauww3qrITeBF3keQf4jfKYq39PXAjbhTqLeCfwA3AVr/nvR1XKv0GYC7wNnA/LkgFrtn6GW7t0Szgj7jy59dYVxLe637c+qx3cOXQZ3ruvxVYjluzNQvYBzx42u/GWdTw+F8CUnHFLN7Aha6ncB+EnnEa5BleNwdXxfESIBN4GDci+VlAu3zc9+JSXKhaBgzxPPY47vvyDeD/cN/3R3ABdRMiInLOjLXVTQMXERFp+DwXN94KzLDWvlK/vREREalKI1wiIiIiIiIhosAlIiIiIiISIppSKCIiIiIiEiIa4RIREREREQkRBS4REREREZEQUeASEREREREJEQUuERERERGREFHgEhERERERCREFLhERERERkRD5/2g5RvvQ57elAAAAAElFTkSuQmCC\n", "text/plain": [ "<Figure size 1008x576 with 1 Axes>" ] @@ -525,56 +582,18 @@ "name": "stdout", "output_type": "stream", "text": [ - "[[0.005544 0.0022 0.01027108 0.00470851 0.00425303]\n", - " [0.02112 0.008248 0.02691527 0.02059184 0.01725623]\n", - " [0.046616 0.018488 0.04842042 0.03653877 0.03691361]\n", - " [0.082656 0.031824 0.08504799 0.06495903 0.06255394]\n", - " [0.126216 0.04844 0.12745866 0.12681319 0.0954118 ]\n", - " [0.181 0.06864 0.18465026 0.18324289 0.13430768]\n", - " [0.244616 0.086416 0.24131455 0.25093638 0.17210743]\n", - " [0.321824 0.10564 0.32405645 0.31731251 0.21823937]]\n" + "[[0.005576 0.002368 0.00975484 0.0024027 0.0050152 ]\n", + " [0.019912 0.0086 0.02109956 0.01658424 0.01691919]\n", + " [0.045936 0.01832 0.04945307 0.03069707 0.03660539]\n", + " [0.082064 0.033352 0.08653878 0.08995609 0.06328502]\n", + " [0.127528 0.047936 0.13063434 0.11355927 0.09697531]\n", + " [0.179456 0.065944 0.19077157 0.17911279 0.13350704]\n", + " [0.244872 0.089856 0.24493377 0.24659278 0.17521346]\n", + " [0.321696 0.113984 0.32884645 0.30272122 0.22299695]]\n" ] } ], "source": [ - "def bailIndicator(r, y_model, x_train, x_test):\n", - " '''\n", - " Indicator function for whether a judge will bail or jail a suspect.\n", - " \n", - " Algorithm:\n", - " ----------\n", - " \n", - " (1) Calculate recidivism probabilities from training set and assign to\n", - " predictions_train.\n", - " \n", - " (2) Calculate recidivism probabilities from test set and assign to\n", - " predictions_test.\n", - " \n", - " (3) Construct a cumulative distribution function of the probabilities in\n", - " in predictions_train.\n", - " \n", - " (4)\n", - " For pred in predictions_test:\n", - " \n", - " if pred belongs to a percentile (computed from step (3)) lower than r\n", - " return True\n", - " else\n", - " return False\n", - " \n", - " \n", - " Returns a boolean array indicating a bail decision.\n", - " '''\n", - "\n", - " predictions_train = y_model.predict_proba(x_train)[:, 0]\n", - "\n", - " predictions_test = y_model.predict_proba(x_test)[:, 0]\n", - "\n", - " return [\n", - " scs.percentileofscore(predictions_train, pred, kind='weak') < r\n", - " for pred in predictions_test\n", - " ]\n", - "\n", - "\n", "failure_rates = np.zeros((8, 5))\n", "failure_sems = np.zeros((8, 5))\n", "\n", @@ -582,7 +601,7 @@ "\n", "for r in np.arange(1, 9):\n", "\n", - " print(r, end=\"| \")\n", + " print(\"[\", r, \"]\", sep='', end=\" \")\n", "\n", " f_rate_true = np.zeros(nIter)\n", " f_rate_label = np.zeros(nIter)\n", @@ -594,20 +613,25 @@ "\n", " print(i, end=\" \")\n", "\n", - " train_labeled, train, test_labeled, test, df = generateDataWithUnobservables(\n", - " )\n", + " # Create data\n", + " train_labeled, train, test_labeled, test, df = dataWithUnobservables()\n", "\n", - " logreg, predictions = fitLogisticRegressionModel(\n", + " # Fit model and calculate predictions\n", + " logreg, predictions = fitLogisticRegression(\n", " train_labeled.dropna().X,\n", " train_labeled.dropna().result_Y, test.X, 0)\n", + "\n", + " # Attach the predictions to data\n", " test = test.assign(B_prob_0_logreg=predictions)\n", "\n", - " logreg, predictions_labeled = fitLogisticRegressionModel(\n", + " logreg, predictions_labeled = fitLogisticRegression(\n", " train_labeled.dropna().X,\n", " train_labeled.dropna().result_Y, test_labeled.X, 0)\n", + "\n", " test_labeled = test_labeled.assign(B_prob_0_logreg=predictions_labeled)\n", "\n", " #### True evaluation\n", + " #\n", " # Sort by failure probabilities, subjects with the smallest risk are first.\n", " test.sort_values(by='B_prob_0_logreg', inplace=True, ascending=True)\n", "\n", @@ -620,6 +644,7 @@ " test.result_Y[0:to_release] == 0) / test.shape[0]\n", "\n", " #### Labeled outcomes only\n", + " #\n", " # Sort by failure probabilities, subjects with the smallest risk are first.\n", " test_labeled.sort_values(by='B_prob_0_logreg',\n", " inplace=True,\n", @@ -631,6 +656,7 @@ " test_labeled.result_Y[0:to_release] == 0) / test_labeled.shape[0]\n", "\n", " #### Human evaluation\n", + " #\n", " # Get judges with correct leniency as list\n", " correct_leniency_list = test_labeled.judgeID_J[\n", " test_labeled['acceptanceRate_R'].round(1) == r / 10].values\n", @@ -645,19 +671,20 @@ " released.result_Y == 0) / correct_leniency_list.shape[0]\n", "\n", " #### Contraction, logistic regression\n", + " #\n", " f_rate_cont[i] = contraction(test_labeled, 'judgeID_J', 'decision_T',\n", " 'result_Y', 'B_prob_0_logreg',\n", " 'acceptanceRate_R', r / 10)\n", "\n", " #### Causal model - empirical performance\n", " #\n", - " f_rate_caus[i] = np.sum(\n", - " (test_labeled.dropna().result_Y == 0)\n", - " & bailIndicator(r * 10, logreg, train.X.values.reshape(-1, 1),\n", - " test_labeled.dropna().X.values.reshape(-1, 1))\n", - " ) / test_labeled.dropna().result_Y.shape[0]\n", + " recidivated = test_labeled.dropna().result_Y == 0\n", "\n", - " #print(\"diff: \", f_rate_caus[i] - (np.sum((test_labeled.dropna().result_Y == 0) & (cdf(test_labeled.dropna().X, logreg, 0) < (r /10))) / test_labeled.dropna().result_Y.shape[0]))\n", + " released = bailIndicator(r * 10, logreg, train.X.values.reshape(-1, 1),\n", + " test_labeled.dropna().X.values.reshape(-1, 1))\n", + "\n", + " f_rate_caus[i] = np.sum(recidivated\n", + " & released) / test_labeled.dropna().shape[0]\n", "\n", " failure_rates[r - 1, 0] = np.mean(f_rate_true)\n", " failure_rates[r - 1, 1] = np.mean(f_rate_label)\n", @@ -719,7 +746,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 92, "metadata": { "scrolled": false }, @@ -728,12 +755,12 @@ "name": "stdout", "output_type": "stream", "text": [ - "| iteration: 1 ,0 1 2 3 4 | iteration: 2 ,0 1 2 3 4 | iteration: 3 ,0 1 2 3 4 | iteration: 4 ,0 1 2 3 4 | iteration: 5 ,0 1 2 3 4 | iteration: 6 ,0 1 2 3 4 | iteration: 7 ,0 1 2 3 4 | iteration: 8 ,0 1 2 3 4 " + "[1] 0 1 2 3 4 [2] 0 1 2 3 4 [3] 0 1 2 3 4 [4] 0 1 2 3 4 [5] 0 1 2 3 4 [6] 0 1 2 3 4 [7] 0 1 2 3 4 [8] 0 1 2 3 4 " ] }, { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "<Figure size 1008x576 with 1 Axes>" ] @@ -747,14 +774,14 @@ "name": "stdout", "output_type": "stream", "text": [ - "[[0.015672 0.015672 0.02077658 0.0168399 0.03213019]\n", - " [0.04256 0.04256 0.04143341 0.04854146 0.07905376]\n", - " [0.075808 0.075808 0.07616197 0.06881769 0.13324914]\n", - " [0.11696 0.11696 0.11272757 0.12694184 0.1941261 ]\n", - " [0.163664 0.163664 0.16585906 0.16208214 0.2442222 ]\n", - " [0.215816 0.215816 0.214522 0.22351695 0.28915824]\n", - " [0.27644 0.27644 0.28466479 0.28419799 0.32621678]\n", - " [0.341944 0.341944 0.34848206 0.34073762 0.34775226]]\n" + "[[0.015 0.015 0.01962992 0.01439704 0.0297739 ]\n", + " [0.04148 0.04148 0.04322212 0.04912637 0.08153246]\n", + " [0.075696 0.075696 0.07457801 0.07281473 0.13389142]\n", + " [0.115016 0.115016 0.11908461 0.12088559 0.18920554]\n", + " [0.16228 0.16228 0.16279339 0.14916862 0.24129177]\n", + " [0.214056 0.214056 0.21129612 0.22366353 0.28695953]\n", + " [0.276344 0.276344 0.27453313 0.28847544 0.32376534]\n", + " [0.343248 0.343248 0.3449349 0.37472556 0.35145913]]\n" ] } ], @@ -766,7 +793,7 @@ "\n", "for r in np.arange(1, 9):\n", "\n", - " print(\"| iteration:\", r, \",\", end=\"\")\n", + " print(\"[\", r, \"]\", sep='', end=\" \")\n", "\n", " s_f_rate_true = np.zeros(nIter)\n", " s_f_rate_gs = np.zeros(nIter)\n", @@ -778,38 +805,20 @@ "\n", " print(i, end=\" \")\n", "\n", - " s_train_labeled, s_train, s_test_labeled, s_test, s_df = generateDataWithoutUnobservables(\n", + " s_train_labeled, s_train, s_test_labeled, s_test, s_df = dataWithoutUnobservables(\n", " )\n", "\n", - " s_logreg, predictions = fitLogisticRegressionModel(\n", + " s_logreg, predictions = fitLogisticRegression(\n", " s_train_labeled.dropna().X,\n", " s_train_labeled.dropna().result_Y, s_test.X, 0)\n", " s_test = s_test.assign(B_prob_0_logreg=predictions)\n", "\n", - " s_logreg, predictions_labeled = fitLogisticRegressionModel(\n", + " s_logreg, predictions_labeled = fitLogisticRegression(\n", " s_train_labeled.dropna().X,\n", " s_train_labeled.dropna().result_Y, s_test_labeled.X, 0)\n", " s_test_labeled = s_test_labeled.assign(\n", " B_prob_0_logreg=predictions_labeled)\n", "\n", - " s_f_rate_cont[i] = contraction(s_test_labeled, 'judgeID_J',\n", - " 'decision_T', 'result_Y',\n", - " 'B_prob_0_logreg', 'acceptanceRate_R',\n", - " r / 10)\n", - "\n", - "# s_f_rate_caus[i] = np.sum(\n", - "# (s_test_labeled.dropna().result_Y == 0)\n", - "# & (cdf(s_test_labeled.dropna().X, s_logreg, 0) < r /\n", - "# 10)) / s_test_labeled.dropna().result_Y.shape[0]\n", - " \n", - " s_f_rate_caus[i] = np.sum(\n", - " (s_test_labeled.dropna().result_Y == 0)\n", - " & bailIndicator(r*10, s_logreg, s_train.X.values.reshape(-1,1), s_test_labeled.dropna().X.values.reshape(-1,1))) / s_test_labeled.dropna().result_Y.shape[0]\n", - "\n", - "# s_f_rate_caus[i] = si.quad(\n", - "# lambda x: getProbabilityForClass(np.array([x]), s_logreg, 0) * (\n", - "# r / 10) * scs.norm.pdf(x), -np.inf, np.inf)[0]\n", - "\n", " #### True evaluation\n", " # Sort by estimated failure probabilities, subjects with the smallest risk are first.\n", " s_sorted = s_test.sort_values(by='B_prob_0_logreg',\n", @@ -852,6 +861,21 @@ " s_f_rate_human[i] = np.sum(\n", " released.result_Y == 0) / correct_leniency_list.shape[0]\n", "\n", + " #### Contraction\n", + " s_f_rate_cont[i] = contraction(s_test_labeled, 'judgeID_J',\n", + " 'decision_T', 'result_Y',\n", + " 'B_prob_0_logreg', 'acceptanceRate_R',\n", + " r / 10)\n", + " #### Causal model\n", + " recidivated = s_test_labeled.result_Y == 0\n", + "\n", + " released_for_bail = bailIndicator(\n", + " r * 10, s_logreg, s_train.X.values.reshape(-1, 1),\n", + " s_test_labeled.X.values.reshape(-1, 1))\n", + "\n", + " s_f_rate_caus[i] = np.sum(\n", + " recidivated & released_for_bail) / s_test_labeled.dropna().shape[0]\n", + "\n", " f_rates[r - 1, 0] = np.mean(s_f_rate_true)\n", " f_rates[r - 1, 1] = np.mean(s_f_rate_gs)\n", " f_rates[r - 1, 2] = np.mean(s_f_rate_human)\n", @@ -902,6 +926,44 @@ "\n", "print(f_rates)" ] + }, + { + "cell_type": "code", + "execution_count": 148, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(0.38130401665687785, 2.6503789913005405e-09)\n" + ] + } + ], + "source": [ + "def f():\n", + " N_bootstraps = 100\n", + "\n", + " N_sample = int(s_train.X.values.shape[0]*0.05)\n", + "\n", + " res = np.zeros((N_bootstraps, 101))\n", + "\n", + " percs = np.arange(101)\n", + "\n", + " for i in range(N_bootstraps):\n", + "\n", + " sample = npr.choice(s_train.X.values, size=N_sample)\n", + "\n", + " predictions_sample = s_logreg.predict_proba(sample.reshape(-1, 1))[:, 0]\n", + "\n", + " #predictions_test = y_model.predict_proba(s_train.X.values.reshape(-1, 1))[:, 0]\n", + "\n", + " res[i, :] = np.percentile(predictions_sample, percs)\n", + "\n", + "#%timeit bailIndicator(50, logreg, train.X.values.reshape(-1, 1), test_labeled.dropna().X.values.reshape(-1, 1))\n", + "\n", + "print(si.quad(lambda x: logreg.predict_proba(np.array([x]).reshape(-1, 1))[:, 0] * bailIndicator(99, logreg, train.X.values.reshape(-1, 1), np.array([x]).reshape(-1, 1)) * scs.norm.pdf(x), -np.inf, np.inf))" + ] } ], "metadata": { diff --git a/analysis_and_scripts/derivation_validation.ipynb b/analysis_and_scripts/derivation_validation.ipynb index ef80f9f11cda7302b9f8db33571cb09838ce5c69..c94f83bb5af6d0c702f8e277a17e9b363cae9c80 100644 --- a/analysis_and_scripts/derivation_validation.ipynb +++ b/analysis_and_scripts/derivation_validation.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 7, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -62,7 +62,7 @@ }, { "cell_type": "code", - "execution_count": 117, + "execution_count": 2, "metadata": { "scrolled": false }, @@ -71,16 +71,16 @@ "name": "stdout", "output_type": "stream", "text": [ - "Bias: (0.07408376336924696, 8.2249499843419745e-16)\n", - "Bias: (0.03499978223514582, 3.8857564094325414e-16)\n", + "Bias: (0.07558160888120039, 8.391244241812189e-16)\n", + "Bias: (0.03647337206409673, 4.0493577451280163e-16)\n", "Analytical: 0.03709585053394618\n", - "Estimated: 0.03908404387660974\n", - "Difference: -0.0019881933426635634\n", + "Estimated: 0.03910840191792689\n", + "Difference: -0.0020125513839807097\n", "\n", "Values for P(y=0|do(r=1)) and P(y=0|do(r=0))\n", "\n", "Analytical: 0.14973849934787756 0.11264264881393138\n", - "Estimated: 0.15038208197340258 0.11129803809679284\n" + "Estimated: 0.15185984231839383 0.11275144040046695\n" ] } ], @@ -176,6 +176,170 @@ " analytic_R_on_Y(0, a, b, c, d))\n", "print(\"Estimated: \", r1[0], r0[0])" ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0.0\n", + "0.0006666666666666666\n", + "0.00125\n", + "0.0015833333333333333\n", + "0.0025833333333333333\n", + "0.0035\n", + "0.004583333333333333\n", + "0.006333333333333333\n", + "0.007416666666666667\n", + "0.007833333333333333\n", + "0.008916666666666666\n", + "0.00925\n", + "0.009916666666666667\n", + "0.010833333333333334\n", + "0.012333333333333333\n", + "0.0135\n", + "0.01425\n", + "0.015166666666666667\n", + "0.016\n", + "0.017\n", + "0.017666666666666667\n", + "0.01875\n", + "0.02\n", + "0.021083333333333332\n", + "0.022416666666666668\n", + "0.0235\n", + "0.024083333333333335\n", + "0.025166666666666667\n", + "0.026166666666666668\n", + "0.02775\n", + "0.029\n", + "0.029916666666666668\n", + "0.03158333333333333\n", + "0.03283333333333333\n", + "0.03383333333333333\n", + "0.034833333333333334\n", + "0.036\n", + "0.037\n", + "0.03808333333333333\n", + "0.03941666666666667\n", + "0.04058333333333333\n", + "0.042083333333333334\n", + "0.043666666666666666\n", + "0.044583333333333336\n", + "0.046\n", + "0.04716666666666667\n", + "0.04841666666666666\n", + "0.050166666666666665\n", + "0.0515\n", + "0.053\n", + "0.05491666666666667\n", + "0.05575\n", + "0.05708333333333333\n", + "0.058166666666666665\n", + "0.059416666666666666\n", + "0.06091666666666667\n", + "0.06233333333333333\n", + "0.06383333333333334\n", + "0.06491666666666666\n", + "0.06575\n", + "0.06725\n", + "0.06891666666666667\n", + "0.07\n", + "0.07141666666666667\n", + "0.07283333333333333\n", + "0.07425\n", + "0.07691666666666666\n", + "0.07791666666666666\n", + "0.07933333333333334\n", + "0.0805\n", + "0.08225\n", + "0.08425\n", + "0.08541666666666667\n", + "0.08666666666666667\n", + "0.08841666666666667\n", + "0.08975\n", + "0.09141666666666666\n", + "0.09266666666666666\n", + "0.09391666666666666\n", + "0.095\n", + "0.09633333333333334\n", + "0.09791666666666667\n", + "0.09916666666666667\n", + "0.10066666666666667\n", + "0.10158333333333333\n", + "0.10358333333333333\n", + "0.10466666666666667\n", + "0.10608333333333334\n", + "0.1075\n", + "0.10908333333333334\n", + "0.11033333333333334\n", + "0.11216666666666666\n", + "0.1135\n", + "0.11525\n", + "0.1175\n", + "0.12008333333333333\n", + "0.12133333333333333\n", + "0.12308333333333334\n", + "0.12475\n", + "0.12741666666666668\n", + "0.12941666666666668\n" + ] + } + ], + "source": [ + "r_, x_, t_, y_ = generateData()\n", + "\n", + "\n", + "def bailIndicator(r, y_model, x_train, x_test):\n", + " '''\n", + " Indicator function for whether a judge will bail or jail a suspect.\n", + " \n", + " Algorithm:\n", + " ----------\n", + " \n", + " (1) Calculate recidivism probabilities from training set with a trained \n", + " model and assign them to predictions_train.\n", + " \n", + " (2) Calculate recidivism probabilities from test set with the trained \n", + " model and assign them to predictions_test.\n", + " \n", + " (3) Construct a cumulative distribution function of the probabilities in\n", + " in predictions_train.\n", + " \n", + " (4)\n", + " For pred in predictions_test:\n", + " \n", + " if pred belongs to a percentile (computed from step (3)) lower than r\n", + " return True\n", + " else\n", + " return False\n", + " \n", + " Returns:\n", + " --------\n", + " (1) Boolean list indicating a bail decision (bail = True).\n", + " '''\n", + "\n", + " predictions_train = y_model.predict_proba(x_train)[:, 0]\n", + "\n", + " predictions_test = y_model.predict_proba(x_test)[:, 0]\n", + "\n", + " return [\n", + " scs.percentileofscore(predictions_train, pred, kind='weak') < r\n", + " for pred in predictions_test\n", + " ]\n", + "\n", + "\n", + "recidivated = y_ == 0\n", + "\n", + "for r__ in range(101):\n", + " released_for_bail = bailIndicator(r__, lr_y, np.array([t, x]).T, np.array([t_, x_]).T)\n", + "\n", + " print(np.sum(recidivated & released_for_bail) / y_.shape[0])" + ] } ], "metadata": {