diff --git a/examples/T4-regression.ipynb b/examples/T4-regression.ipynb index 35e9d34..08e1e89 100644 --- a/examples/T4-regression.ipynb +++ b/examples/T4-regression.ipynb @@ -11,6 +11,9 @@ "import matplotlib.pyplot as plt\n", "from matplotlib import ticker\n", "\n", + "from pycircstat2 import load_data\n", + "from pycircstat2.regression import CLRegression\n", + "\n", "%load_ext jupyter_black" ] }, @@ -18,7 +21,9 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Circular-Linear Regression" + "## Circular-Linear Regression\n", + "\n", + "In this section, we replicate the results from Section 6.4 of Fisher (1993), modeling the mean direction of periwinkle movement as a function of distance moved." ] }, { @@ -27,35 +32,153 @@ "metadata": {}, "outputs": [], "source": [ - "from pycircstat2.regression import CLRegression" + "df = load_data(\"B20\", source=\"fisher\")\n", + "X = df[\"x\"].values\n", + "θ = np.deg2rad(df[\"θ\"].values)\n", + "\n", + "data_cl = pd.DataFrame({\"X\": X, \"θ\": θ})" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Circular Regression for the Mean Direction\n", + "\n", + "Call:\n", + " CLRegression(model_type='mean')\n", + "\n", + "Coefficients for Mean Direction (Beta):\n", + "\n", + " Estimate Std. Error t value Pr(>|t|)\n", + "β0 -0.00832 0.00136 6.12 0.00000 ***\n", + "\n", + "Summary:\n", + " Mean Direction (mu) in radians:\n", + " μ: 2.42597 (SE: 0.11192)\n", + "\n", + " Concentration Parameter (kappa):\n", + " κ: 3.22430 (SE: 0.71593)\n", + "\n", + "Model Fit Metrics:\n", + "\n", + "Metric Value \n", + "nLL -27.76148 \n", + "AIC -53.52296 \n", + "BIC -52.08897 \n", + "\n", + "Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1\n", + "p-values are approximated using the normal distribution.\n", + "\n" + ] + } + ], "source": [ - "from pycircstat2 import load_data\n", - "\n", - "df = load_data(\"B20\", source=\"fisher\")\n", - "X = df[\"x\"].values\n", - "θ = np.deg2rad(df[\"θ\"].values)\n", - "\n", - "data_cl = pd.DataFrame({\"X\": X, \"θ\": θ})\n", - "\n", - "# Fit the model\n", + "# Fit the mean direction only model\n", + "# This implmentation is ported from R package circular's lm.circular.cl and we arrive at the same results\n", "cl_reg_mean = CLRegression(formula=\"θ ~ X\", model_type=\"mean\", data=data_cl, tol=1e-10)\n", + "cl_reg_mean.summary()" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Circular Regression for the Concentration Parameter\n", + "\n", + "Call:\n", + " CLRegression(model_type='kappa')\n", + "\n", + "\n", + "Coefficients for Concentration (Gamma):\n", + "\n", + " Estimate Std. Error t value Pr(>|t|) \n", + "α -0.25475 0.50585 -0.50 0.61454 \n", + "γ0 0.03326 0.00905 3.68 0.00024 ***\n", + "\n", + "Summary:\n", + " Mean Direction (mu) in radians:\n", + " μ: 1.32978 (SE: 0.07460)\n", + "\n", + " Concentration Parameter (kappa):\n", + " Index kappa Std. Error\n", + " [1] 27.23391 6.85109\n", + " [2] 3.58005 0.80650\n", + " [3] 2.32321 0.50677\n", + " [4] 7.19881 1.75046\n", + " [5] 44.85424 11.32782\n", + " [6] 7.69401 1.87768\n", + " [7] 3.24004 0.71988\n", + " [8] 2.10257 0.46255\n", + " [9] 1.15536 0.31770\n", + " [10] 1.78040 0.40459\n", + " [11] 2.65383 0.57893\n", + " [12] 7.69401 1.87768\n", + " [13] 0.91536 0.29398\n", + " [14] 12.25746 3.04289\n", + " [15] 7.44229 1.81305\n", + " [16] 2.74359 0.59957\n", + " [17] 1.55860 0.36972\n", + " [18] 0.80133 0.28463\n", + " [19] 8.22329 2.01335\n", + " [20] 5.70344 1.36357\n", + " [21] 8.22329 2.01335\n", + " [22] 8.22329 2.01335\n", + " [23] 5.16176 1.22191\n", + " [24] 4.51870 1.05263\n", + " [25] 2.74359 0.59957\n", + " [26] 7.95425 1.94442\n", + " [27] 0.97833 0.29967\n", + " [28] 3.82633 0.87048\n", + " [29] 0.97833 0.29967\n", + " [30] 1.55860 0.36972\n", + " [31] 1.90288 0.42564\n", + " Mean: 6.36210 (SE: 1.56042)\n", + "\n", + "Model Fit Metrics:\n", + "\n", + "Metric Value \n", + "nLL -30.17278 \n", + "AIC -56.34556 \n", + "BIC -53.47759 \n", + "\n", + "Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1\n", + "p-values are approximated using the normal distribution.\n", + "\n" + ] + } + ], + "source": [ + "# Fit the concentration only model\n", "cl_reg_kappa = CLRegression(\n", " formula=\"θ ~ X\", model_type=\"kappa\", data=data_cl, tol=1e-10\n", ")\n", - "beta0 = cl_reg_mean.result[\"beta\"]\n", - "gamma0, alpha0 = cl_reg_kappa.result[\"gamma\"], cl_reg_kappa.result[\"alpha\"]" + "\n", + "cl_reg_kappa.summary()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As suggested by Fisher (1993), we use the fitted values from the mean and kappa models as initial values for the mixed model." ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "metadata": {}, "outputs": [ { @@ -70,33 +193,71 @@ "\n", "Coefficients for Mean Direction (Beta):\n", "\n", - " Estimate Std. Error t value Pr(>|t|) \n", - "β_0 -0.00376 nan nan nan \n", + " Estimate Std. Error t value Pr(>|t|)\n", + "β0 -0.00376 0.00027 13.84 0.00000 ***\n", "\n", "Coefficients for Concentration (Gamma):\n", "\n", " Estimate Std. Error t value Pr(>|t|) \n", - "γ_0 0.04590 nan nan nan \n", - "\n", - "Intercept for Concentration (Alpha):\n", - " Estimate: -0.41402\n", + "α -0.41403 0.51485 -0.80 0.42130 \n", + "γ0 0.04590 0.00920 4.99 0.00000 ***\n", "\n", "Summary:\n", " Mean Direction (mu) in radians:\n", - " mu: 1.91715 (SE: nan)\n", + " μ: 1.91714 (SE: 0.04552)\n", "\n", " Concentration Parameter (kappa):\n", - " kappa: 16.11628 (SE: nan)\n", + " Index kappa Std. Error\n", + " [1] 89.82281 22.75070\n", + " [2] 5.46322 1.30087\n", + " [3] 3.00825 0.66257\n", + " [4] 14.32354 3.56887\n", + " [5] 178.80833 45.35346\n", + " [6] 15.70063 3.91924\n", + " [7] 4.76046 1.11638\n", + " [8] 2.62129 0.57155\n", + " [9] 1.14739 0.31683\n", + " [10] 2.08376 0.45894\n", + " [11] 3.61450 0.81540\n", + " [12] 15.70063 3.91924\n", + " [13] 0.83211 0.28703\n", + " [14] 29.85278 7.51655\n", + " [15] 14.99629 3.74005\n", + " [16] 3.78426 0.85950\n", + " [17] 1.73426 0.39698\n", + " [18] 0.69254 0.27687\n", + " [19] 17.21012 4.30318\n", + " [20] 10.38763 2.56634\n", + " [21] 17.21012 4.30318\n", + " [22] 17.21012 4.30318\n", + " [23] 9.05141 2.22521\n", + " [24] 7.53325 1.83642\n", + " [25] 3.78426 0.85950\n", + " [26] 16.43806 4.10682\n", + " [27] 0.91211 0.29370\n", + " [28] 5.98847 1.43774\n", + " [29] 0.91211 0.29370\n", + " [30] 1.73426 0.39698\n", + " [31] 2.28409 0.49869\n", + " Mean: 16.11623 (SE: 4.04050)\n", + "\n", + "Model Fit Metrics:\n", "\n", - "Log-Likelihood: 37.81777\n", + "Metric Value \n", + "nLL -37.81772 \n", + "AIC -69.63544 \n", + "BIC -65.33348 \n", "\n", - "Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1\n", + "Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1\n", "p-values are approximated using the normal distribution.\n", "\n" ] } ], "source": [ + "beta0 = cl_reg_mean.result[\"beta\"]\n", + "gamma0, alpha0 = cl_reg_kappa.result[\"gamma\"], cl_reg_kappa.result[\"alpha\"]\n", + "\n", "cl_reg_mixed = CLRegression(\n", " formula=\"θ ~ X\",\n", " model_type=\"mixed\",\n", @@ -112,24 +273,24 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 5, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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ChZW+5Nzc3Hj99ddZtWoVVlZWDBo0iG+++aba5+1O169fp3Xr1lWW+/j4VDrPCne/3hVfvne+3nUxbtw4Dhw4QGJiIjt27KhV8/4bb7xBu3btOHPmDAsWLKgU2Gv6nKelpVFUVFTtsBHVPV/VGTNmDEVFRephHPLz89m9ezejRo1S/0Dr3bs3zz77LB988AFWVlY89dRTrF27lpKSkoc654q+gXv27GHTpk0MGzas2h+daWlpZGdn88MPP1Q5/0mTJgGV/x7Xr1+Pv78/+vr6WFpaYm1tzV9//VXt++ph3huSJDXZi4GER4voM9YEmZiY0LJlSy5dulTnfd1Zw/Ew7vUBpFQqK9W0VWf06NGEhITwxhtv0L59e4yMjFCpVAwePLjaK/PuLOMvv/yi/rCtIGmgH9m9ynznvlUqFQMHDuTNN9+sdttWrVoBcOzYMUaMGEGvXr349ttvsbe3R1dXl7Vr11bp2A0P/xoYGhpW6kDevXt3AgMDeeedd/j666/VZZXJZOzZs6fac6vLeGx3l7fiNfv000+r9L+5+3ijR4+mZ8+e/P777+zfv59PP/2UTz75hO3btzNkyBAAPvvsM4KDg/njjz/Yv38/r732GosXL+bUqVPV9mGrjZq83tWxtLREoVCQl5d335rpESNGIJfLmThxIiUlJffsgH4/cXFx6tAVERFRaV1Nn/OHDUPV6dq1K66urvz666+MGzeOXbt2UVRUxJgxY9TbVIwBdurUKXbt2sW+ffuYPHkyn332GadOnarx+83e3p4+ffrw2WefceLECbZt21btdhXnP378eCZOnFjtNv7+/kD5RSzBwcE8/fTTvPHGG9jY2KCtrc3ixYvVPz7v9DDvjaysLKysrGp0boJQFyKMNVHDhg3jhx9+4OTJk3Tr1k1j+/Xw8ADg0qVLVWpL7mRubk52dnaV5devX8fd3f2ej8vKyuLvv//mgw8+YP78+erlFV86DzJo0CAOHDhQo201zcPDg/z8/HteSVdh27Zt6Ovrs2/fvkpDFqxdu7ZeyuXv78/48eNZuXIlc+fOxdnZGQ8PDyRJws3NTR0Sq1PRdHbt2jX69u2rXq5QKEhISFB/od1PxXvGxMTkgc8NlH/hTp8+nenTp5OamkpgYCAfffSROowBtG3blrZt2/Lee+8REhJC9+7d+f777/nwww/veR5Xrlypsvzy5cuVzrOuvL29gfKrKu/33BgYGPD000/z008/MWTIkIf+wlapVAQHB2NiYsLs2bP5+OOPee655xg5ciRQ8+fc2toaAwODav++qnu+7mX06NF89dVX5Obm8ssvv+Dq6qruWnCnrl270rVrVz766CM2b97MCy+8wJYtW+45EG51xo0bx9SpUzEzM+PJJ5+853kZGxujVCof+J7bunUr7u7ubN++vdKPyAULFtS4TPcSHx+vvqBCEOqTaKZsot58800MDQ2ZOnUqKSkpVdbHxsby1VdfPfR+n3jiCYyNjVm8eHGVK7/u/GXo4eHBqVOnKC0tVS/7888/qx024U4Vvzrv/pV555WI92Nvb8+AAQMq3RrK6NGjOXnyJPv27auyLjs7G4VCAZSfo0wmqzTmV0JCAjt27Ki3sr355puUlZXx+eefAzBy5Ei0tbX54IMPqjzXkiSphxHp2LEjlpaW/Pjjj+ryQ/lQDDVtsuvQoQMeHh4sW7asUr+iCmlpaUB5rendzUI2Nja0bNlSXYOTm5tbqRxQHsy0tLTuW8vz5JNPcubMGU6ePKleVlBQwA8//ICrq+tD9cm7n4ofPqGhoQ/cdu7cuSxYsID333//oY/z+eefExISwg8//MCiRYsICgriP//5j7p/Uk2fc21tbQYNGsSOHTtITExUr4+Ojq72fXwvY8aMoaSkhPXr17N3794qNX1ZWVlV3mcVNXYPWzv33HPPsWDBgmoHzq2gra3Ns88+y7Zt26ptIag4/4ptofJnzunTpyu9V2ojJyeH2NjYOl/RLgg1IWrGmigPDw82b97MmDFj8PHxqTQCf0hICL/99lut5u4zMTHhiy++YOrUqXTq1Ek9vteFCxcoLCxk/fr1AEydOpWtW7cyePBgRo8eTWxsLD/99JP6F/v99t+rVy+WLl1KWVkZDg4O7N+/n/j4+No8DVWUlZVVW3tiYWHB9OnT67TvN954g507dzJs2DD1sBcFBQVERESwdetWEhISsLKyYujQoXz++ecMHjyYcePGkZqayjfffIOnpycXL16sUxnuxdfXlyeffJJVq1bx/vvv4+HhwYcffsi8efPUQ1UYGxsTHx/P77//zssvv8zcuXPR09Nj4cKFvPrqq/Tr14/Ro0eTkJDAunXr8PDwqFF/GC0tLVatWsWQIUPw8/Nj0qRJODg4cOvWLQ4dOoSJiQm7du0iLy8PR0dHnnvuOdq1a4eRkREHDx7k7NmzfPbZZ0D5cA0zZ85k1KhRtGrVCoVCwcaNG9Vfvvfy9ttv8/PPPzNkyBBee+01LCwsWL9+PfHx8Wzbtk1jo/W7u7vTpk0bDh48+MAxtNq1a1erWpPo6Gjef/99goODGT58OFA+3Ez79u2ZPn06v/76a42fc4APPviAvXv30rNnT6ZPn45CoWD58uX4+fnV+P0YGBiIp6cn7777LiUlJZWaKKG8T9a3337LM888g4eHB3l5efz444+YmJjcs3brXkxNTVm4cOEDt1uyZAmHDh2iS5cuvPTSS/j6+pKZmUlYWBgHDx4kMzMTKG9F2L59O8888wxDhw4lPj6e77//Hl9f32qDbE0dPHgQSZJ46qmnar0PQaixhr+AU3gYV69elV566SXJ1dVV0tPTk4yNjaXu3btLy5cvl4qLi9Xb3Wtoi3tdir5z504pKChIMjAwkExMTKTOnTtLP//8c6VtPvvsM8nBwUGSy+VS9+7dpdDQ0BoNbXHz5k3pmWeekczMzCRTU1Np1KhR0u3btyVAWrBggXq76oYBuJ+JEydKQLU3Dw+PSud999AWdw4LUeHuc5Gk8uES5s2bJ3l6ekp6enqSlZWVFBQUJC1btkwqLS1Vb7d69WrJy8tLksvlkre3t7R27Vr1+dyJ/x8OoabuHAbgbocPH67yHG7btk3q0aOHZGhoKBkaGkre3t7SjBkzpCtXrlR67Ndffy25uLhIcrlc6ty5s3TixAmpQ4cO0uDBg9XbVDe8wJ3Cw8OlkSNHSpaWlpJcLpdcXFyk0aNHS3///bckSeXDaLzxxhtSu3btJGNjY8nQ0FBq166d9O2336r3ERcXJ02ePFny8PCQ9PX1JQsLC6lv377SwYMHKx2ruqFVYmNjpeeee04yMzOT9PX1pc6dO0t//vlnpW3udQ7VvU/v5fPPP5eMjIyqDF9Sk9fyQUNbKBQKqVOnTpKjo6OUnZ1d6bEVw2/88ssv6mUPes4rHDlyROrQoYOkp6cnubu7S99//32178f7effddyVA8vT0rLIuLCxMev755yVnZ2dJLpdLNjY20rBhw6TQ0NAH7vd+7+kK93rdUlJSpBkzZkhOTk6Srq6uZGdnJ/Xv31/64Ycf1NuoVCrp448/Vr+/AwICpD///LPKkCIV74FPP/20yvHv/ruSJEkaM2aM1KNHjweenyBogkyS6mmUTUEQmiyVSoW1tTUjR47kxx9/bOziNCk5OTm4u7uzdOlSpkyZ0tjFERpBcnIybm5ubNmyRdSMCQ1C9BkThEdccXFxlf4+GzZsIDMz84FTWz2OTE1NefPNN/n0008f+wm+H1dffvklbdu2FUFMaDCiZkwQHnGHDx9mzpw5jBo1CktLS8LCwli9ejU+Pj6cO3funp2oBUEQhIYhOvALwiPO1dUVJycnvv76azIzM7GwsGDChAksWbJEBDFBEIQmQNSMCYIgCIIgNCLRZ0wQBEEQBKERiTAmCIIgCILQiEQYEwRBEARBaEQijAmCIAiCIDQiEcYEQRAEQRAakQhjgiAIgiAIjUiEMUEQBEEQhEYkwpggCIIgCEIjEmFMEARBEAShEYkwJgiCIAiC0IhEGBMEQRAEQWhEIowJgiAIgiA0IhHGBEEQBEEQGpEIY4IgCIIgCI1IhDFBEARBEIRGJMKYIAiCIAhCIxJhTBAEQRAEoRGJMCYIgiAIj5ng4GBkMhkymQxdXV1sbW0ZOHAga9asQaVS1Xg/69atw8zMrP4K+pgQYUwQBEEQGplKpSIiIoKjR48SERHxUIGotgYPHkxSUhIJCQns2bOHvn37MmvWLIYNG4ZCoaj34wv/EmFMEARBEBpRSEgI48ePZ8KECUybNo0JEyYwfvx4QkJC6vW4crkcOzs7HBwcCAwM5J133uGPP/5gz549rFu3DoDPP/+ctm3bYmhoiJOTE9OnTyc/Px+Aw4cPM2nSJHJyctS1bAsXLgRg48aNdOzYEWNjY+zs7Bg3bhypqan1ej7NmQhjgiAIgtBIQkJCmDt3LmFhYZiZmeHq6oqZmRnh4eHMnTu33gPZ3fr160e7du3Yvn07AFpaWnz99ddERkayfv16/vnnH958800AgoKC+PLLLzExMSEpKYmkpCTmzp0LQFlZGYsWLeLChQvs2LGDhIQEgoODG/RcmhOZJElSYxdCEARBEB43KpWK8ePHExYWhqenJzKZTL1OkiRiY2MJDAxk48aNaGlptu4kODiY7OxsduzYUWXd2LFjuXjxIlFRUVXWbd26lWnTppGeng6U9xmbPXs22dnZ9z1eaGgonTp1Ii8vDyMjI02cwiNF1IwJgiAIQiOIjIwkOjoae3v7SkEMQCaTYWdnR1RUFJGRkQ1aLkmS1OU5ePAg/fv3x8HBAWNjY1588UUyMjIoLCy87z7OnTvH8OHDcXZ2xtjYmN69ewOQmJhY7+VvjkQYEwRBEIRGkJWVRUlJCQYGBtWuNzAwoKSkhKysrAYtV3R0NG5ubiQkJDBs2DD8/f3Ztm0b586d45tvvgGgtLT0no8vKChg0KBBmJiYsGnTJs6ePcvvv//+wMc9znQauwCCIAiC8DgyNzdHLpdTVFRUbdNdUVERcrkcc3PzBivTP//8Q0REBHPmzOHcuXOoVCo+++wzdTPpr7/+Wml7PT09lEplpWWXL18mIyODJUuW4OTkBJQ3Uwr3JmrGBEF4aHl5ecyePRsXFxcMDAwICgri7Nmz6vWSJDF//nzs7e0xMDBgwIABxMTEVNrHyZMnad++Pa6urqxevbqhT0EQGp2fnx8+Pj4kJydzd/dtSZJITk7G19cXPz+/ejl+SUkJycnJ3Lp1i7CwMD7++GOeeuophg0bxoQJE/D09KSsrIzly5cTFxfHxo0b+f777yvtw9XVlfz8fP7++2/S09MpLCzE2dkZPT099eN27tzJokWL6uUcHhmSIAjCQxo9erTk6+srHTlyRIqJiZEWLFggmZiYSDdv3pQkSZKWLFkimZqaSjt27JAuXLggjRgxQnJzc5OKiorU+/Dx8ZG2bt0qnThxQvLw8JASExMb63QEodGcOHFC6tatm+Tt7S316dNHGjJkiNSnTx/J29tb6tatm3TixIl6Oe7EiRMlQAIkHR0dydraWhowYIC0Zs0aSalUqrf7/PPPJXt7e8nAwEAaNGiQtGHDBgmQsrKy1NtMmzZNsrS0lABpwYIFkiRJ0ubNmyVXV1dJLpdL3bp1k3bu3CkBUnh4eL2cT3MnrqYUBOGhFBUVYWxszB9//MHQoUPVyzt06MCQIUNYtGgRLVu25L///a/6MvecnBxsbW1Zt24dY8eOBcDFxYXDhw9jY2NDnz59WL9+Pb6+vo1yToLQmEJCQlixYgXR0dGUlJQgl8vx9fVlxowZBAUFNXbxhAYg+owJgvBQFAoFSqUSfX39SssNDAw4fvw48fHxJCcnM2DAAPU6U1NTunTpwsmTJ9VhbP78+fj4+KBQKPjPf/4jgpjw2AoKCqJr165ERkaSlZWFubk5fn5+Gh/OQmi6RBgTBOGhGBsb061bNxYtWoSPjw+2trb8/PPPnDx5Ek9PT5KTkwGwtbWt9DhbW1v1OoApU6YwduxYSktLG7SDsiA0RVpaWrRt27axiyE0EhG7BUF4aBs3bkSSJBwcHJDL5Xz99dc8//zzD/1L3tDQUAQxQRAeeyKMCYLw0Dw8PDhy5Aj5+fncuHGDM2fOUFZWhru7O3Z2dgCkpKRUekxKSop6nSAIgvAvEcYEQag1Q0ND7O3tycrKYt++fTz11FO4ublhZ2fH33//rd4uNzeX06dP061bt0YsrSAIQtMkrqYUBOGh7du3D0mSaN26NdeuXeONN95AX1+fY8eOoauryyeffMKSJUtYv349bm5uvP/+++q57u7u+C8IgvC4Ex34BUF4aDk5OcybN4+bN29iYWHBs88+y0cffYSuri4Ab775JgUFBbz88stkZ2fTo0cP9u7dK4KYIAhCNUTNmCAIgiAIQiMSfcYEQRAEQRAakQhjgiAIgiDcU58+fZg9e3a9HmPhwoW0b9++Xo/RlIkwJgiCIAiPmeDgYGQyGdOmTauybsaMGchkMoKDgwHYvn27mOi7nokwJgiCIAiPIScnJ7Zs2UJRUZF6WXFxMZs3b8bZ2Vm9zMLCAmNj48Yo4mNDhDFBEARBeAwFBgbi5OTE9u3b1cu2b9+Os7MzAQEB6mV3NlNevnyZFi1asHnzZvX6X3/9FQMDA6KiogDIzs5m6tSpWFtbY2JiQr9+/bhw4UKlYy9ZsgRbW1uMjY2ZMmUKxcXF9XimTZ8IY4IgCIKgIZIkUViqaPBbbQdGmDx5MmvXrlXfX7NmDZMmTbrn9t7e3ixbtozp06eTmJjIzZs3mTZtGp988gm+vr4AjBo1itTUVPbs2cO5c+cIDAykf//+ZGZmAuXhbeHChXz88ceEhoZib2/Pt99+W6vyPyrE0BaCIAiCoCGFpQp85+9r8ONG/W8QLfRqPnRocHAw2dnZ/Pjjjzg5OXHlyhWgPGzduHGDqVOnYmZmxrp16+jTpw/t27fnyy+/VD9+2LBh5Obmoqenh7a2Nnv37kUmk3H8+HGGDh1Kamoqcrlcvb2npydvvvkmL7/8MkFBQQQEBPDNN9+o13ft2pXi4mLOnz9f5+eiORKDvgqCIAjCY8ra2pqhQ4eybt06JEli6NChWFlZPfBxa9asoVWrVmhpaREZGYlMJgPgwoUL5OfnY2lpWWn7oqIiYmNjAYiOjq5y4UC3bt04dOiQhs6q+RFhTBAEQRA0xEBXm6j/DWqU49bW5MmTmTlzJkCl2qr7uXDhAgUFBWhpaZGUlIS9vT0A+fn52Nvbc/jw4SqPMTMzq3UZH3UijAmCIAiChshksodqLmwKBg8eTGlpKTKZjEGDHhwkMzMzCQ4O5t133yUpKYkXXniBsLAwDAwMCAwMJDk5GR0dHVxdXat9vI+PD6dPn2bChAnqZadOndLU6TRLogO/IAiCIDzGtLW1iY6OJioqCm3tB9ewTZs2DScnJ9577z0+//xzlEolc+fOBWDAgAF069aNp59+mv3795OQkEBISAjvvvsuoaGhAMyaNYs1a9awdu1arl69yoIFC4iMjKzXc2zqmld8FwRBEARB40xMTGq03YYNG9i9ezfh4eHo6Oigo6PDTz/9RI8ePRg2bBhDhgxh9+7dvPvuu0yaNIm0tDTs7Ozo1asXtra2AIwZM4bY2FjefPNNiouLefbZZ/nPf/7Dvn0Nf+FDUyGuphQEQRAEQWhEomZMEIQqJEmioKCAvLw88vLyyM/Pr/Tv3cvy8/MpKytDpVJVuWlpaVW56ejoYGRkhLGxsfrfO/9/9zIjIyP11VqCIAiPGlEzJgiPEUmSyMzM5Pbt2yQlJZGUlFTp/3ferxgRWy6X3zM03RmW9PT0qoQulUrF5cuX8fLyQiaTqQNaaWlptWHv7pBXUQZ9fX3s7e0r3Vq2bFnl/5aWliK0CYLQ7IgwJgiPGJVKxY0bN7h69WqV282bNyktLcXY2LhSmLk73Njb22NjY4OxsTG6urq1LktZWRm7d+/mySefrNV+ysrKyMvLIy0t7YHhMTc3F11dXRwcHGjVqlWVm7Ozc406JwuCIDQ0EcYEoZnKy8vj4sWLVQJXTEwMCoUCd3f3SmHEy8sLFxcX7O3tMTQ0bJAy1jWMPYzCwkKSkpJITEwkJiaGK1euqJ+TuLg4tLS08PT0rPSctG7dGn9//xp3XhYEQagPIowJQjOQm5tLeHg4586dU9+uXr2Kra0tPj4+VWqB3Nzc6j381ERDhrEHlSMhIaFKcL18+TJJSUl4eXkRGBhIhw4d6NChA4GBgZiamjZaeQVBeLyIMCYITUxOTg5hYWGVgldMTAyOjo7qoFARGuzs7Bq7uPfVVMLY/aSkpFR5vm/cuIGnp2eVgGZubt7YxRUE4REkwpggNLK0tDSOHDnC4cOHOXz4MJGRkTg5OalDQEUQqBijpzlpDmGsOmlpaepgVhHUrl+/jo+PD3369KFPnz707t27Wb4mgiA0PSKMCUIDS0tL4+jRo5XCV5s2bdRf8j169MDGxqaxi6kRzTWMVSctLY0TJ06oX7eLFy9WCWePyusmCELDEmFMEOpZZmYmhw4dqhS+/Pz86NOnD3379qVXr15YWVk1djHrxaMUxu6WkZFRKVRHRERUCmf9+vXD0tKysYspCEIzIMKYINSDmJgYdu3axc6dOzlx4gStW7emb9++9OnTh169emFtbd3YRWwQj3IYu9ud4ezQoUNERUURFBTE8OHDGTFiBK1bt27sIgpCjfTp04f27dvz5ZdfanTbhrZu3Tpmz55NdnZ2vR0jISEBNzc3wsPDad++fa33I0bgFwQNUCqVnDp1ip07d7Jz507i4uLo27cvo0ePZsOGDTg7Ozd2EYV6ZmlpyTPPPMMzzzwDwM2bN/nzzz/ZuXMn77//Pi4uLowYMYLhw4cTFBSEjo74+BUaT3BwMOvXr6+yPCYmhu3btzfJH0+HDx+mb9++mJmZkZSUhL6+vnrd2bNn6dy5M1A+uDWUz4H55JNPNkpZH5b4NBCEWsrPz2f//v3s3LmTv/76C0mSGDp0KB9++CFPPPEExsbGjV1EoRE5Ojoybdo0pk2bRn5+PgcOHGDnzp0899xzKJVKhg4dyvDhwxk0aJAY50xoFIMHD2bt2rWVlllbWzf64MilpaXo6endc72xsTG///47zz//vHrZ6tWrcXZ2JjExUb3MwMAAAwODei2rpmg1dgEEoTkpKiri119/ZcSIEVhaWvLuu+9iY2PD77//TkpKCuvXr+fZZ58VQUyoxMjIiGeeeYa1a9eSlJTErl27cHBwYOHChVhZWTF06FB+/vlnCgsLG7uowmNELpdjZ2dX6aatrU2fPn2YPXu2ertvv/0WLy8v9PX1sbW15bnnnqu0H5VKxZtvvomFhQV2dnYsXLiw0vrs7GymTp2KtbU1JiYm9OvXjwsXLqjXL1y4kPbt27Nq1Src3Nwq1XhVZ+LEiaxZs0Z9v6ioiC1btjBx4sRK261btw4zMzOgvLZswIABDBo0SF1zlpmZiaOjI/Pnz1c/ZtWqVfj4+KCvr4+3tzfffvttpX2eOXOGgIAA9PX16dixI+Hh4fcta02JMCYID6BUKjl48CCTJk3C1taW+fPn07lzZyIiIoiOjmbp0qX06NGj0X9NCs2DtrY2QUFBLF68mMjISKKioujevTuLFi3CxsaGCRMmsH//fhQKRWMXVaiDwlLFPW/FZUqNblufQkNDee211/jf//7HlStX2Lt3L7169aq0zfr16zE0NOT06dMsXbqU//3vfxw4cEC9ftSoUaSmprJnzx7OnTtHYGAg/fv3JzMzU73NtWvX2LZtG9u3b+f8+fP3LdOLL77IsWPH1LVg27Ztw9XVlcDAwHs+RiaTsX79es6ePcvXX38NwLRp03BwcFCHsU2bNjF//nw++ugjoqOj+fjjj3n//ffVzbn5+fkMGzYMX19fzp07x8KFC5k7d27Nn8z7EM2UglANSZI4f/48mzZtYvPmzahUKp5//nkOHTpEYGCgmIxa0BhPT0/eeecd5s2bp37PBQcHq99zL7zwAh06dBDvuWbGd/6+e67r29qatZM6q+93WHSQortCV4Uubhb88ko39f0enxwis6C00jYJS4bWqox//vknRkZG6vtDhgzht99+q7RNYmIihoaGDBs2DGNjY1xcXAgICKi0jb+/PwsWLADAy8uLFStW8PfffzNw4ECOHz/OmTNnSE1NRS6XA7Bs2TJ27NjB1q1befnll4HypskNGzbU6OImGxsbhgwZwrp165g/fz5r1qxh8uTJD3ycg4MDK1euZMKECSQnJ7N7927Cw8PV/TcXLFjAZ599xsiRIwFwc3MjKiqKlStXMnHiRPV3werVq9HX18fPz4+bN2/yn//854HHfhARxgThDgkJCWzevJlNmzaRmJjIyJEjWbduHf369XtsOlxLkkRpaSnFxcWUlJSgUChQKpUoFIp73pRKJUqlUl39X/GvSqUC4NixY2hplVfEy2QytLS00NHRqfamra1d6b5cLkdfXx89Pb1HOpDIZDICAgIICAjgk08+4fDhw/z000/069ePli1bMn78eMaNG4e7u3tjF1V4RPTt25fvvvtOfb+6OWsHDhyIi4sL7u7uDB48mMGDB/PMM8/QokUL9Tb+/v6VHmNvb09qaioAFy5cID8/v8owL0VFRcTGxqrvu7i4PNRV5pMnT2bWrFmMHz+ekydP8ttvv3Hs2LEHPm7UqFH8/vvvLFmyhO+++w4vLy8ACgoKiI2NZcqUKbz00kvq7RUKhXpqtOjoaPz9/Ss1o3br1g1NeDy+XQThPkpLS/njjz/4/vvvOXbsGE888QTvv/8+I0aMqPSB8yhQKBQUFBRQXFxc5VZSUqL+vyRJ6iB0r9BkYGBQKThVNNPKZDL1TaFQEBoaSqtWrdTrJUlSh7s7Q15JSQkFBQVVgl5FIJTJZOjr66vD2Z03uVyOgYEBhoaGj0Ro1tbWpn///vTv359vv/2WXbt2sWnTJv73v/8RFBTEtGnTeOaZZ9Q1DULTE/W/Qfdcp3XXj4pz7w+o8bbH3+pbt4LdwdDQEE9Pz/tuY2xsTFhYGIcPH2b//v3Mnz+fhQsXcvbsWXV/rLuvvJTJZOofYvn5+djb23P48OEq+654fEVZHsaQIUN4+eWXmTJlCsOHD6/xmH6FhYWcO3cObW1tYmJi1Mvz8/MB+PHHH+nSpUulxzREF5Tm/6klCLUUHx/Pjz/+yOrVqzEyMuKVV17h559/bvajqKtUKgoLC8nPzyc/P5+CggL1/4uLi9VB6s5gY2VlVSnY6OvrayTUlJWVAWBra1unS+UrQtndAbKgoICMjAyKi4spKipCoVCgr6+PkZERhoaGGBkZqf9vaGiorp1rTgwMDBg9ejSjR48mPT2dDRs2MH/+fF599VUmT57Myy+/jIeHR2MXU7hLC72a//3U17aaoqOjw4ABAxgwYAALFizAzMyMf/75R92cdz+BgYEkJyejo6ODq6urRss0YcIEli5dyp49e2r8uP/+979oaWmxZ88ennzySYYOHUq/fv2wtbWlZcuWxMXF8cILL1T7WB8fHzZu3EhxcbG6duzUqVOaOR+N7EUQmgmVSsXevXtZsWIFBw8eZPjw4fz000/079+/2X1RS5JEQUEBOTk5ZGdnk5eXR35+PoWFhchkMnUYMTQ0xNHRUR1MmmNzX0Xt2/1+PVc0r94ZPjMzM7lx4wb5+flIkkSLFi0wMjLC2NgYU1NTzMzMMDQ0bDbPh5WVFa+//jpz5szh0KFDfP/99/j6+tK7d29mzpzJ0KFDxYUkgkb9+eefxMXF0atXL8zNzdm9ezcqlarGgxgPGDCAbt268fTTT7N06VJatWrF7du3+euvv3jmmWfo2LFjrcu2aNEi3njjjRrXiv3111+sWbOGkydPEhgYyBtvvMHEiRO5ePEi5ubmfPDBB7z22muYmpoyePBgSkpKCA0NJSsri9dff51x48bx7rvv8tJLLzFv3jwSEhJYtmxZrct/JxHGhMdCdnY2a9eu5ZtvvqGgoIBp06axatUqWrZs2dhFq5GK4JWdna0OX9nZ2ahUKoyNjTEzM8PGxgZ3d3eMjIwwMDBoNgFDU2QyGXK5HLlcjoWFRaV1kiRRVFSkDml5eXnExsaSm5uLlpYWZmZm6nDWHAKaTCajX79+9OvXj+TkZFatWsX06dPR09Nj+vTpTJ48ucpzIAi1YWZmxvbt21m4cCHFxcV4eXnx888/4+fnV6PHy2Qydu/ezbvvvsukSZNIS0vDzs6OXr16YWtrW6ey6enp1XgqubS0NKZMmcLChQvVV11+8MEH7N+/n2nTpvHLL78wdepUWrRowaeffsobb7yBoaEhbdu2VQ/zYWRkxK5du5g2bRoBAQH4+vryySef8Oyzz9bpPEBMhyQ84q5du8Znn33Ghg0bCAgIYObMmYwcOfK+Awo2BaWlpWRkZJCZmVkpeJmYmFQKDiYmJk26Rq+pT4ekUqnIy8tTP8fZ2dnqgFbxHFtaWmJpadnk3zNlZWXs2LGDFStWcPbsWV544QXmzp0rpmEShGZAhDHhkXT+/HmWLFnCjh07GDNmDLNnz65yOXZTUhG+MjIySE9PJycnByMjIywtLTE3N8fU1LTJB6/qNPUwVp27A1pGRgZ5eXmYmJhgZWWFlZVVkw9nFy9e5Msvv2Tz5s0MGzaMefPm0aFDh8YuliAI9yDCmPBIOXbsGIsXL+bw4cNMmTKFuXPn4uLi0tjFqqKsrEwdvO4MX3d+2T9oFOrmoDmGseoUFxerX6+KcGZqaoqlpWWTDmc3btzg888/54cffqB79+7MmzePPn36NOkmWEF4HIkwJjR7kiSxe/duFi9ezKVLl5gxYwazZs1qUldFSpJEXl4eSUlJpKSkkJWVpQ5fFV/oj0L4utujEsbudmc4S09PJz8/HzMzM/WUMiYmJk0q8KSnp/P111+zfPlyWrduzbx58xg+fHizq2kVhEeVCGNCs6VQKNi6dSuLFy8mJSWFOXPmMG3aNPUAfY1NpVKRnp5OcnIyycnJlJaWYm1tjZ2dHTY2Ns1mAtu6eFTD2N2Ki4tJTU0lOTmZ1NRU9PT01MHM0tKyyVzhmJeXx8qVK/n888+xsLDg7bffZuzYsY/E2GyC0JyJMCY0O0qlko0bN/Lhhx+iVCp58803CQ4ObhLhprS0lJSUFPWXso6OjvpL2crKqsl8KTeUxyWM3UmpVJKRkUFSUhLJycmUlZVha2urvjWFgVqLi4vZsGEDS5cuRalU8u677xIcHCxCmSA0EhHGhGZDkiR27drFO++8Q1FREQsXLuT5559v9C+QsrIybt++zc2bN8nIyMDExEQdwExNTZtUc1VDexzD2J0kSSI3N5fk5GSSkpLIzc3FwsICR0dHWrZs2ej9zBQKBb/99hvz589HW1ubjz76iJEjRz7W71lBaAwijAnNwrFjx3j77be5du0a8+fP56WXXmrULzKlUklKSgo3b94kJSUFExMT9RdsU6ihayoe9zB2t6KiIpKSkrh58yY5OTnY2Njg6OiInZ1do9aalpWVsXr1aj744AOcnZ1ZsmQJfftqbtodQRDuT4QxoUmLiIhg3rx5HD16lDfeeIM5c+ZgZGTUKGWRJImMjAxu3rzJ7du30dPTw9HRUT26vVCVCGP3lp+fz61bt7hx4wYlJSW0bNkSR0dHrKysGq1mqqCggK+//ppPPvmErl27snjx4iY9JIwgPCpEGBOapISEBObPn89vv/3GtGnTeOedd7C2tm6UsuTm5nLjxg1u3bqFUqnEwcEBR0dHzM3NRXPOA4gw9mCSJJGdnc3Nmze5desWMplMHfIb62KUjIwMlixZwjfffMNTTz3Fhx9+KOa/FIR6JK5rFpqUtLQ0Zs2ahY+PDzKZjOjoaL744osGD2IKhYLExESOHj3K0aNHKSoqwt/fn0GDBuHv74+FhYUIYoJGyGQyzM3Nadu2LU888QTt27enuLiYY8eOceTIEa5fv45CoWjQMllaWvLpp59y5coVWrRoQZs2bZgxYwYpKSkNWg5BeFyIMCY0CUqlkm+++YZWrVoRGxvLmTNnWL9+Pa6urg1ajtzcXCIiIti/fz/Xrl3D0dGRQYMG0bFjR+zs7MS4TEK90tLSwtbWlg4dOjBo0CCcnZ2Ji4tj3759XLx4kdzc3AYtj5OTE6tXr+bcuXPcvn2bVq1a8dVXXzV4OBQ0Lzg4GJlMxrRp06qsmzFjBjKZjODg4IYv2GNKNFMKje7kyZPMmDGDvLw8vv76a4YMGdKgx1epVCQnJxMfH09mZiYtW7bE1dVV1H5pgGimrDtJksjKyiIhIYFbt25hbm6Ou7t7o/w4OHjwIDNnzkRPT49vvvmGnj17NujxBc0JDg7mn3/+ITc3l6SkJPWFR8XFxdjb22NiYkLfvn1Zt25d4xb0MSF+5guNJjU1lcmTJzNgwACeffZZIiIiGjSIlZSUcPXqVQ4ePMilS5ewtrbmiSeeoEOHDlhaWoogJjQJMpkMCwsLAgMDGTRoEHZ2dkRGRnLgwAGuXLlCSUlJg5VlwIABXLx4kfHjxzNkyBBefPFFkpOTG+z4gmYFBgbi5OTE9u3b1cu2b9+Os7NzpQs3VCoVixcvxs3NDQMDA9q1a8fWrVvV65VKJVOmTFGvb926NV999VWlYwUHB/P000+zbNky7O3tsbS0ZMaMGZSVldX/iTYDYoQ/ocEplUq+//573nvvPfr27UtUVFSDzh9ZWFhITEwMN27cwNzcnDZt2ogmSKFZ0NPTw9PTEw8PD1JSUoiLi+Pq1as4Ozvj6emJoaFhg5ThzTffZNy4cfz3v/+ldevWfPDBB8ycObPRx/xrEiQJygob/ri6LaAWPyAnT57M2rVreeGFFwBYs2YNkyZN4vDhw+ptFi9ezE8//cT333+Pl5cXR48eZfz48VhbW9O7d29UKhWOjo789ttvWFpaEhISwssvv4y9vT2jR49W7+fQoUPY29tz6NAhrl27xpgxY2jfvj0vvfRSnU+/uRPNlEKDCgkJYcaMGeTn57N8+XIGDx7cYMfOzc0lJiaG27dvY29vj5eXV5OZOulRJZop619jv68PHjzIq6++iq6uLitWrKBXr14NduwmqbQAPm7Z8Md95zbo1TyMBwcHk52dzY8//oiTkxNXrlwBwNvbmxs3bjB16lTMzMxYuXIlFhYWHDx4kG7duqkfP3XqVAoLC9m8eXO1+585cybJycnqGrTg4GAOHz5MbGyseky90aNHo6WlxZYtW2p71o8M8TNGaBBpaWm8+eab/Pbbb8ybN4+5c+c22LQwmZmZxMTEkJqaipOTE3379hXjggmPDBMTEzp06IC3tzfXrl3j2LFjWFlZ4eXlhaWlZb0ff8CAAVy4cIEvv/ySoUOHqpuibG1t6/3YQt1ZW1szdOhQ1q1bhyRJDB06FCsrK/X6a9euUVhYyMCBAys9rrS0tFJT5jfffMOaNWtITEykqKiI0tJS2rdvX+kxfn5+lQY3tre3JyIion5OrJkRYUyod7/99hvTp0+ne/fuREZGNkiTpCRJpKWlERMTQ1ZWFm5ubvj7+4vR8YVHlqGhIe3ataN169bExcVx6tQpTE1N8fLywsbGpl77QN7ZdPn666/j6+vLihUrGDt27OPX91K3RXktVWMct5YmT57MzJkzgfJQdaf8/HwA/vrrLxwcHCqtq/hBvWXLFubOnctnn31Gt27dMDY25tNPP+X06dOVi3hX7bhMJkOlUtW63I8SEcaEepOWlsbMmTP5+++/WbFiBWPGjKn3D2ZJkkhKSuLq1asUFRXh7u5Op06dGn0OQEFoKPr6+vj6+uLl5UV8fDxhYWEYGBjg5eVFy5Yt6/Vv0NHRkV9//ZXt27czbdo0fv31V77//vvHq5ZMJnuo5sKmYPDgwZSWliKTyRg0aFCldb6+vsjlchITE+ndu3e1jz9x4gRBQUFMnz5dvSw2NrZey/yoET2WhXqxdetW/Pz8KCsrIzIyskF+IaelpXH06FEuXryIk5MTAwcOpHXr1iKICY8lXV1dWrVqxRNPPIGzszOXLl3iyJEjpKam3vdxCekF7LpQt5qdkSNHEhUVhVwux9fXl59//hnRPbnp0tbWJjo6mqioqCpzpBobGzN37lzmzJnD+vXriY2NJSwsjOXLl7N+/XoAvLy8CA0NZd++fVy9epX333+fs2fPNsapNFuiZkzQqPT0dGbMmMHBgwcbrJkiOzub6OhoMjMz8fLywt3dXVzVJQj/T1tbG3d3d1xcXIiLiyM0NBRTU1N8fX0xNzcHymuUT8Vlsvp4PH9fTkGuo0UPTyvMDWv/Q8bKyootW7awdetWpk+fztatW/n2228fr1qyZsTExOSe6xYtWoS1tTWLFy8mLi4OMzMzAgMDeeeddwB45ZVXCA8PV7d+PP/880yfPp09e/Y0VPGbPXE1paAx27Zt4z//+Q/du3fnu+++w87Orl6PV1BQQHR0NMnJybi5ueHl5SVqwZoYcTVl01NaWsq1a9eIi4vDytqGRMmKDWdvcenWv6P7921tzcIRfrhYVm1uU6lUREZGkpWVhbm5OX5+fg8cFiYtLY0ZM2bwzz//NFiXBUFoTkQYE+osPT2dV199lf3797N8+XKef/75ev2gLS4u5urVq1y/fh1HR0e8vb1Fx/wmSoSxpqmoVMlPIbH8cDSOtEIlAPo6WjzbwZFJ3d3wtKn+auOQkBBWrFhBdHQ0JSUlyOVyfHx8mDlzJkFBQQ88bsXFPL169eK7777DxsZGo+clCM2V6DMm1MmBAwdo06YNRUVFREZGMm7cuHoLYmVlZURHR3Pw4EGKioro3bs3AQEBIogJQg3lFJWx/O8Yun/yDx/tjSGtUIlFC13G+BqysIOSF1pr42Je/ZAzISEhzJ07l7CwMMzMzHB1dcXMzIzw8HDmzp1LSEjIA48/atQodb8kPz8/du/erelTFIRmSdSMCbWiUChYsGABX331FV999RWTJ0+utxAmSRK3b9/m0qVLtGjRAj8/PywsLOrlWIJmiZqxpiGzoJRVx+LYePI6eSXlk3w7W7Tg5V7uPNfBEX1dbbKysoiKiiIvLw8/Pz8cHR2RyWQolCpkSLz44ouEhYXh6elZ6W9dkiRiY2MJDAxk48aNNZ7JYuPGjUyfPp1p06bx8ccfi/eH8FgTvZyFh3bjxg3GjRtHZmYmp0+fxs/Pr96OlZubS0RERJUvCEEQHiw9v4Qfj8ax8dR1CkvLmyO97Yz5Tx8Phra1R0f73+Bkbm5OUFAQt2/f5mJEBHvDYrlabMzfVzN5v6cF0dHR2NvbV/n7k8lk2NnZERUVRWRkJG3btq1R2V588UU6d+7M6NGjOXbsGFu2bMHV1VVj5y4IzYkIY8JD2bVrF8HBwYwcOZKvvvqKFi1qP9Dg/ZSVlXH16lXi4+NxdXWlc+fO4pezINRQVkEpK4/GsT4kgaKy8hDW1sGUV/t5MsDHFi2t6n/QXEnJ4/eLufwRrktybgFQAMDhmAxKSkru2SXAwMCAlJQUsrKyHqqcrVu35tSpU/z3v/8lICCA1atXM3LkyIfahyA8CkQYE2qktLSUt99+m1WrVvH9998zbty4ejmOJEncunWLyMhIDA0N6dWr130vuRYE4V95xWWsOhbP6uPx5P9/c6S/oymzB3jRt/W9R+G/mVXIyxvOEZX07xWVxvo6DGhtSWuDfOy188nu1InExMRqpxIrKipCLperh8p4GAYGBnz77bf069ePyZMnc+jQIT799FP09fUfel+C0FyJMCY8UFxcHGPHjkWhUHDu3Dm8vLzq5Th3Nkm2adMGBwcH0SQpCDVQXKZk48nrfHP4GtmFZQD42pvw+sBW9PepGsIUShWJmYW4W5cHK1sTfVLzitHT1qKvtzXPBDjQp7UN+rra6h9Ihfl5pKSkEBYWVqkGTJIkkpOTCQwMrFOXheeee47AwEDGjh1LUFAQv/zyS7191ghCUyPCmHBfW7duZerUqUyYMIFPP/20Xib3ViqVXLlyhdjYWNzc3ESTpCDUkFIl8Xv4LT7ff4XbOcUAeFgb8t8nWjPYz65Kc+SNzEJ+OXuDX0NvoKMl49hb/dDWkqGrrcX34zvgaWOEWYvKY/XJZDIcHR1xdnbm4sWLDB8+nIiICMLDw8nPzyc5ORlzc3NmzJhR48779+Lu7s7x48eZN28eHTp0YOXKlTz//PN12qcgNAdiaIt6cvToUYYPH66eC27Hjh2V1i9cuBBvb28MDQ0xNzdnwIABVSZVdXV1RSaTVbotWbKk0jY//vgjLi4uBAQEVHl8XSiVSubOnctLL73EmjVr+Prrr+sliGVlZamnaOnduzdt2rQRQUx4LKlUKiIiIjh69CgREREPnED56NU0hn59jLm/XeB2TjH2pvosfc6ffbN78WRbe3UQU6okDkSlMHHNGXp9eogVh66RmldCiaK8dqxCR1eLKkHsTt27d2f48OEcPHgQW1tbRowYgZGREYGBgSxbtqxG44zVhJ6eHp999hmbNm1i5syZvPbaaygUCo3s+0GWLFmCTCZj9uzZ6mV9+vSp8jk8bdq0So/buXMnrVq1onXr1vz5558NUlbh0SKGtqgne/bs4cSJE3To0IGRI0fy+++/8/TTT6vXb968GRsbG9zd3SkqKuKLL77gt99+49q1a1hbWwPlYWzKlCm89NJL6scZGxtjaFg+KnZiYiL9+/dnw4YN3Lp1i/nz5xMVFVXnsmdnZ/P888+TkJDAzp0766WpoKI2LC4uDi8vL7y8vOr8q1poWJIkoVQqUSqVKBQKFAoFSqVSvQ7KL8Q4ffo0Xbt2VYdsbW1tdHR0Kv37uDdHP8xgqtdS8/jwr2gOX0kDwERfhxl9PZkY5Iq+buV5Bf+OTmH+H5Hcyi5SL+vpZcXYTs4M9LVFT+fh/+ZUKhWXLl0iOTmZ4uJi3N3d8fHxqTKnoSbEx8czYsQIbG1t+fXXX+t1SJuzZ88yevRoTExM6Nu3L19++SVQHsZatWrF//73P/W2LVq0UPdlLSkpwdPTk7Vr1yJJEpMnTyY2NrZZzwbSp08f2rdvr34ONLWtcG+imbKeDBkyhCFDhtxz/d0d4D///HNWr17NxYsX6d+/v3q5sbHxPacVys3NxczMDH9/f+zs7CgqKqp2u4dx5coVRowYgaenJ6dOncLU1LTO+7xbVlYW4eHhaGlpiQ76TYhSqaSkpITi4uIqt5KSEkpLS9Whq+JWQSaToaOjg5aWlrr24E7nz5+vdByFQlFp4mgdHR31TVtbGz09PfT19avc5HI5+vr69fLF31gqBlPNzMzE3t4eAwMDioqK1IOpVtQ6ZReW8sWBq/x0OhGlSkJXW8aEbq7M7OtZaQ5JhVKlHrLC3FCPW9lFmLfQZXRHJ8Z1ca52iqOHoaWlhb+/P/7+/uTl5REeHs7hw4cJCAjQeFhyc3MjJCREPQzGzp078fX11egxAPLz83nhhRf48ccf+fDDD6usb9GixT0/h0tKStDW1qZ9+/ZA+Xu5pKSkyYex4OBg9UTfd4qJiWH79u1NsoXi8OHD9O3bFzMzM5KSkipd5HH27Fk6d+4M0CwnpRdhrAkoLS3lhx9+wNTUlHbt2lVat2TJEhYtWoSzszPjxo1jzpw56kmw27Rpg7+/P6ampujp6fHjjz/WqRz79u1j7NixvPzyy3z88cca/8ITtWGNr6ysjPz8fPLz8ykoKFD/v7CwkLKyMmQymTrwVISfFi1aYGFhgZ6eXqXQdGd4utd7pWLQ1379+lX5cFepVFXCXcWttLRUHQLz8vIqhUJJktDV1aVFixYYGRlhaGiIkZGR+v9N/UvwTiqVihUrVpCZmVlpMFUjIyM8PDyIjY1lxTffcg17Pj8Yo+6c/4SvLe886YOrleH/70fi8NVUVh2Lx9PGiP891QaAACczVr7Ygd6trKvUmmmCsbExPXr0IDY2lpCQENzc3PD29tboZ4exsTHbt29nwYIFdOvWjU2bNjFs2DCN7R9gxowZDB06lAEDBlQbxjZt2sRPP/2EnZ0dw4cP5/3331cP62NiYsKkSZPUY7B9+OGHGBsba7R89WXw4MGsXbu20jJra+tG/7FTWlp6379jY2Njfv/990r9CVevXo2zszOJiYkNUUSNE2GsEf3555+MHTuWwsJC7O3tOXDgAFZWVur1r732GoGBgVhYWBASEsK8efNISkri888/V2+zevVqli5dSosWLWo9LZAkSXzxxRe8//77rFy5kvHjx9f53O52Z21Yz54966XGTfiXQqEgJyeH7OxscnNz1eGr4hd7RXgxMTGhZcuWtGjRQh2+GqrJUEtLCz09vYcKT5IkqYNaQUGBOlCmp6ff8/xMTU0xNTVtkr/0IyMj7zuYqplnAKdNexOys7z7QWtbY+YP96W7Z/nnRIlCyY7wW/x4LJ5rqfkARNzM4Z0nfdDXLW/+HeRXfY2OpmhpaeHl5YWtrW291ZJpaWmxaNEi2rRpw9ixY3n//fd58803NfJe3bJlC2FhYZw9e7ba9ePGjcPFxYWWLVty8eJF3nrrLa5cucL27dvV2yxYsIDZs2ejpaX1bxArLbj3QWXaoHvH0B333VYLdA3uv61e7Wo75XJ5tTV+dzc9fvvtt3zxxRfcuHEDU1NTevbsydatW9Xbq1Qq3nzzTVatWoWenh7Tpk1j4cKF6vXZ2dnMnTuXP/74g5KSEjp27MgXX3yhrnxYuHAhO3bsYObMmXz00Udcv379vn0mJ06cyJo1a9RhrKioiC1btvDaa6+xaNGiSttWXBASGhqKlZUVzzzzDIsXL1Z399m4cSNfffUVV65cwdDQkH79+vHll1+q502tqI07ePAgb731FlFRUbRv3561a9fSunXrh3/S70GEsUbUt29fzp8/T3p6Oj/++COjR4/m9OnT6jfB66+/rt7W398fPT09XnnlFRYvXlypM72lpWWty1BcXMy0adPYv38/hw4dUlfzaookSVy9epWYmBhRG1ZPysrKyMnJUYev7Oxs8vPzkcvlmJmZYWpqipWVVbOsObpbRc2dXC6vNtDfWfNXEdKuXbtGcXExRkZG6uej4t/GDmhZWVnVDqaq0NYn2bYLWeY+ALTQgbee9OOFLs7oaGuRX6Lg59OJrDoeR0puCQBGch2e7+xEcHe3eqkFexATExN69uzJtWvXCAkJwcPDg9atW2v0733MmDF4eXnx1FNPcfHiRVatWlWnuWlv3LjBrFmzOHDgwD3HNXv55ZfV/2/bti329vb079+f2NhYPDw81OuqvB8/bnnvA3s9AS/89u/9Tz2hrLD6bV16wKS//r3/ZVsozKi8zcKcex+rjkJDQ3nttdfYuHEjQUFBZGZmcuzYsUrbrF+/ntdff53Tp09z8uRJgoOD6d69OwMHDgTK5yQ1MDBgz549mJqasnLlSvr378/Vq1fVof3atWts27aN7du3P7Bm7sUXX+TTTz8lMTERZ2dntm3bhqurK4GBgZW2i42NZfDgwXz44YesWbOGtLQ0Zs6cycyZM9U1gmVlZSxatIjWrVuTmprK66+/TnBwcJV5U999910+++wzrK2tmTZtGpMnT+bEiRN1em7vJMJYIzI0NMTT0xNPT0+6du2Kl5cXq1evZt68edVu36VLFxQKBQkJCRpJ5ElJSYwcORKlUkloaCgtW97nw6MWioqKCAsLo6ioSNSGaVBRUREZGRmkp6eTkZFBfn4++vr66oDh4OCAmZnZYzlopq6uLubm5lUGHy0uLlaH1YyMDGJjYykuLsbQ0BBLS0usrKywsrJq8Ennzc3NkcvlFBUVYWRkhARkmbUm2bYbSp3y10/v5jl+mDWCHp1c1Y/77vA1vjkUC4CtiZwpPdwY29kZE/3GDZdaWlq0atUKOzs7QkNDSU9Pp2PHjhp9XgMDAwkNDWXkyJH06tWLHTt24ODgUKt9nTt3jtTU1Epf4kqlkqNHj7JixQp1f7A7denSBSgPD3eGsebozz//rDSI75AhQ/jtt98qbZOYmIihoSHDhg3D2NhYffX+nfz9/VmwYAEAXl5erFixgr///puBAwdy/Phxzpw5Q2pqqroSYdmyZezYsYOtW7eqw25paSkbNmxQX8B2PzY2NgwZMoR169Yxf/581qxZw+TJk6tst3jxYl544QX11bFeXl58/fXX9O7dm++++w59ff1Kj3N3d+frr7+mU6dO5OfnV3puPvroI3r37g3A22+/zdChQykuLtbY56wIY02ISqWipKTknuvPnz+PlpaWuuasLiIiIhgyZAh9+/blhx9+0PiXUGpqKufOncPGxoYuXbqo+7kJD+/O8FXRHGdmZoaVlRV+fn6PbfB6GBV94GxtbdXLSkpKyMrKIiMjg7i4OMLDw2nRokWDhjM/Pz98fHwIDw/H0acDtx16U2BY/qNIXpyBdPZnOrla4OvjTWJGIc6W5f2UJga58s/lNCYFufJUQEvkOk3rggYTExN69epFRESEutnyXh3ga8PW1pZ//vmH//znP3Ts2JHdu3dXCQg10b9/fyIiIiotmzRpEt7e3rz11lvV1tBUXIxib29//52/c/ve62R37feNa/fZ9q6axdkR1W9XC3379uW7775T369ourvTwIEDcXFxwd3dncGDBzN48GCeeeaZSlPh+fv7V3qMvb09qampAFy4cIH8/PwqLThFRUXExsaq77u4uNQoiFWYPHkys2bNYvz48Zw8eZLffvutSo3dhQsXuHjxIps2bVIvkyQJlUpFfHw8Pj4+nDt3joULF3LhwgWysrLUzaOJiYmVLha58xwrXvvU1FScnZ1rXOb7Ed+Q9SQ/P59r1/79A4uPj+f8+fNYWFhgaWnJRx99xIgRI7C3tyc9PZ1vvvmGW7duMWrUKABOnjzJ6dOn6du3L8bGxpw8eZI5c+Ywfvz4Wk05cqdjx44xYsQIXn/9dd577z2N9hFSqVRcvnyZuLg4/P39cXJyeuyHLXhYSqWStLQ0UlJSSEtLqxS+2rRpg6WlZaM3rz0KKvrLVISEsrIyMjMzSU9PrxTOrKyssLOzw8rKSuM/KrS0tJg2fQYzlv9OjHNP0NZBpirD7GYIRef/wtzKFut+k+n16RECXczZMLm8G4GNsT67X+vRpP+2dHR0CAgI4MaNG5w7dw4XFxd8fX011mwpl8vVfWb79OnD77//Tr9+/R5qH8bGxrRp06bSsora0jZt2hAbG8vmzZt58sknsbS05OLFi8yZM4devXpVCSBVPEw/rvra9gEqWmfux9jYmLCwMA4fPsz+/fuZP38+Cxcu5OzZs5iZmQFU+TySyWTqUJOfn4+9vT2HDx+usu+Kx1eU5WEMGTKEl19+mSlTpjB8+PBqu+vk5+fzyiuv8Nprr1VZ5+zsTEFBAYMGDWLQoEFs2rQJa2trEhMTGTRoEKWlpZW2v/McK/7uHjQW4MMQYayehIaG0rdvX/X9iv5fEydO5Pvvv+fy5cusX7+e9PR0LC0t6dSpE8eOHVNPJyKXy9myZQsLFy6kpKQENzc35syZU6kfWW3s2LGD8ePH88UXX1Qav0wTCgsLOXfuHGVlZWLIiodUXFxMSkoKycnJpKWlIZfLsbW1FeGrAenq6mJra6uuPasIZ6mpqURERFBcXIyNjQ12dnbY2tpqpDby0q0clpxTkedW/lmhk34VnfNbkVBg0/sF0i3bsyOmfGT9tLwS8orLMP7/psimHMTu5OTkhLm5OaGhoRw7doyOHTs+9BfvvchkMt566y31VY5r165l9OjRGtk3lA9Ae/DgQb788ksKCgpwcnLi2Wef5b333tPYMZoDHR0dBgwYwIABA1iwYAFmZmb8888/NZrUPTAwkOTkZHR0dHB1ddVomSZMmMDSpUvZs2fPPY8dFRV1z8AZERFBRkYGS5YswcnJCSj/7m4MIozVkz59+tx3rJM7r8SpTmBgIKdOndJomX788UfmzJnDTz/9VGkAWk1ISkoiPDycli1b0qZNG9Es+QCSJJGXl0dycjLJyclkZ2djZmaGnZ0dPj4+GBsbN5sv20fVneGsTZs25OWVz82YmJjIhQsXMDU1VdesmZiYPNTrVapQseKfGL49HItCJWHWQpf5Q31w0XLk94i27IotI7FEBQqJ1rbGzBnoxRO+Vac3ai6MjIzo2bMnkZGR6mZLTfZRnThxIlZWVowZM4a0tDRmzJhR633dWYPj5OTEkSNHNFDC5uvPP/8kLi6OXr16YW5uzu7du1GpVDXutzxgwAC6devG008/zdKlS2nVqhW3b9/mr7/+4plnnqFjx461LtuiRYt444037nkR21tvvUXXrl2ZOXMmU6dOxdDQkKioKA4cOMCKFStwdnZGT0+P5cuXM23aNC5dulTlasyGIr4xHwOSJPHhhx/y+eefs3v3bnr16qWxfatUKiIjI0lMTKRdu3Y4OjpqbN+PooKCAm7evMnNmzcpKirC2toaFxcXOnfuLPp9NWEymQwTExNMTEzw8vKipKREXZMZExODvr4+Tk5OODo6PrDWJ+p2Lq//ep7LyXkAPNnWjv891QYrIzlbzkj8FHUTADcrQ2YP8GK4f8tmG8LupK2tjb+/P1ZWVpw/f560tDTatGmjsTGthg4dyoEDBxg2bBjJycn873//Ez9oNMDMzIzt27ezcOFCiouL8fLy4ueff67xpPAymYzdu3fz7rvvMmnSJNLS0rCzs6NXr16V+nDWhp6eXqXhoO7m7+/PkSNHePfdd+nZsyeSJOHh4cGYMWOA8jHV1q1bxzvvvMPXX3+tntprxIgRdSpXbYjpkB5xSqWSWbNmsX37dvbt20fbtm01tu+SkhJCQ0MpLS2lU6dOla48Ef5VWlrKrVu3uHnzJllZWdjY2ODo6Iidnd0jX4NYMejrk08++cg2tSqVSlJSUrhx4wapqamYmpri6OiIg4NDpSFolCqJ74/E8uXBq5QpJSwM9Vj0VBt6trJSXwVZqlDx4urTPNXegVEdHdHVfjSHgSkoKODs2bNoa2vTqVMnjf4QiY6OVvcD+u677x75vzHh0SDC2COspKSE8ePHc/HiRfbt26fR9vrc3FxOnz6NqakpgYGB4gPvLkqlkuTkZG7evElKSgpmZmY4OTnRsmXLeplwval6HMLYnUpLS7l9+zY3btyoFLzL9Ex4Y9slQq9nATDQ15b/9Pbg+yOxXEvNZ+/sXrWaJ7I5UyqVnD9/noyMDDp37lypM3dd3bx5k0GDBqlrcRp6yBJBeFgijD2icnNzefrppykoKODPP/98qEuGHyQpKYmwsDA8PT1p1aqVaAq4Q25uLgkJCdy4cQO5XF7jpqtH1eMWxu5UWFjIzZs3+e1MAhujyyhWgqGeNm8P8eZmVhFrTsRTppTQksFPU7oQ5Hnv5pZHlSRJXLt2jStXrhAQEFDr8cKqk5mZyYgRI5DJZOzcubPOV6ELQn0S1RmPoMzMTAYNGoSlpSU7d+7UWPPhnaPpBwYGanyQ2OZKqVRy+/ZtEhISyM7OxsHBgW7dumFubi6C6mNMqaXLd+GF/H6pfD7J1pa6+JqUsmxvFDkl5b+Be7Wy5r2hPrSybR5zGWqaTCbDy8sLY2Njzp07R25uLt7e3hr5u7GwsGD//v2MHTuWvn37cuDAAY3+KBUETRI1Y4+YjIwMBg4ciLOzM7/88ovGmsQUCgXh4eFkZWXRpUsXMZo+5YMWJiQkkJCQgJ6eHq6urjg5OTXr6YY07XGtGbt0K4cZm8O4nlGItpaMab3dOROfydmE8mZKmxYynnOHJ9s74+7uXmkAzcdVbm4uZ86cwdjYmMDAQI29X8rKynjhhReIjo7m77//1sig2YKgaSKMPULS0tIYMGAAnp6e/PzzzxoLBYWFhZw5cwYdHR06der0WPV5qk5mZiaxsbEkJydjY2ODm5sb1tbWohasGo9bGJMkiQ0nr/PRX9GUKlU4mBnw1dj2dHAx58XVZzh3PYuZ/TyZ0sOVvOws4uPjSU5OxtbWFk9PzzrNM/soKC0t5ezZs5SUlNClS5fKzfuSBGVFUJwDciOQ17w2UaFQMGHCBC5cuMDff/+t0dkABEETRBh7RKSkpNC/f3/8/Pz46aefNPbFl5mZyZkzZ7C3t6dt27aP7STfkiSRlpZGTEwMWVlZuLq64ubm9tj2BaupxymM5RWX8fa2CP6KSAIg0NmML8e2x9mi/D1yI7MQLS0ZDmaVO5MXFhYSHx9PQkICpqameHl5YWNj8+iHe2UZ5Kf8/y0NClKhIA0pP53spFjKclIw1wfdsjwozobiXFCVN/ny1LcQ8MLDHU6pZNKkSZw5c4Z//vlHdLMQmhQRxh4Bqamp9O7dG3d3d3bs2KGxL73k5GRCQ0Px9fXF3d1dI/tsbiRJIikpiatXr1JUVIS7uztubm6iKbKGHpcwdjUlj2kbzxGXXoC2DLztTYi8ncu4Ls58/EzNhpMpKysjPj6e2NhYDAwM8PLyomXLls0zlKlU5eEqO/HfW+4tyLlV/m9eEhSkA7X4+pFpwZOfQqepD/1QhULBmDFjuHDhAkePHhWBTGgyRAf+Zi49PZ0BAwbQtm1bJk2axOXLl2nTpk2dP8ATExO5ePGixq9wai5UKhU3btzg2rVrKBQKPD09cXFxEUN4CFXsvHCbt7ZepKhMiZmBLkpJIvJ2LloyMJLrIElSjf4edXV1adWqFe7u7iQmJhIZGUl0dDReXl44OjpqbHBUjZEkyL0NGdf+/xYLmbGQlVB+UxQ/eB9aOmBkC4bWYGRT/m8LSzC0AgMLMktkXE5IxsW7HQ7uvqBvAnpGUIvPN0mSuHLlClOnTmXz5s3079+fw4cP13ngUUHQBPHN0oxlZmYyYMAAvL292bx5MyUlJZw4cQKg1oGs4lLzq1ev0qVLl8fu6iOVSkViYiJXr15FS0sLLy8vnJycHtvmWeHeFEoVn+y9zI/H4gGwMNQjs6B8cmFvO2OWPuePv6PZQ+9XR0cHd3d3XF1duXnzJjExMVy+fBkvLy9cXV0b/r0oSZBzA1Kj/72lX4H0GCjNv/fjZFpg4gBmzmDqWH4zcSj/19geTFqCgQXc53wsgNatMjh9+jT5LfJp1ap2NYWSJBEVFcXNmzfp2bMnTzzxBMHBwfTr149Dhw6JTv1CoxPNlM1UVlYWAwYMwNXVlS1btqibgAoKCjhx4gT29vYPHcgkSSIyMpKbN2/StWtXjQ7C2NRVNEdGRUUB4OPj03ybiJqQR7WZMruwlJmbwzl+LR0AuY4WJQoVutoyXu3nxbTeHhobxLXivRkdHY0kSXh7e+Pg4FA/701lGaRdgaQL5beUS+W34pzqt5dpg4UbWHqW3yzcwNyt/F9TJ9DWzGuem5vLyZMnsbOzw9/f/6E/1yqCWPfu3dVD/SgUCl588UUiIyP5559/7jutjiDUNxHGmqH8/Hz69++Pvb09v/76a5X+S7UJZCqVSj10Rbdu3R6rjulpaWlERUVRVFSEt7c3zs7OoiZMQx7FMHYtNY+p60NJyCjEQFebBcN9WbrvCnYm+nw2uh0+9ib1ctyKpvPLly8jl8vx9fWt21W8klTevHgzFG6Hwa0wSI4AZUnVbbV0wKoV2PiAtQ/YeJffN3cDnYbpP1lYWMjJkycxMTEhMDCwRs229wpiFRQKBePGjePatWscPnwYE5P6ee0E4UFEGGtmysrKGD58uPpL7l7DTDxMICsrK+Ps2bOUlpbStWvXx2bC6uzsbKKiosjKysLLywt3d3fRJ0zDHrUwduRqGjM3hZFXosDBzIBVEzviY2/CleQ83K0NG2QuSaVSSXx8PFevXsXU1BRfX9+ajS5fVlQeuBJPwo3TcPMsFGVV3U5uAvbtwM4f7NqCXRuwat1goet+SkpKOH36NNra2nTu3Pm+76kHBbEKZWVljBgxgpKSEvbs2fPYD90jNA4RxpoRlUrFxIkTiYyMrNGvuJoEspKSEk6dOoWOjs4DP9weFYWFhURFRZGcnIybmxteXl7i6sh68iiFsQ0nE1jwR6T6+r8lI9sytrNzo5WnrKyMmJgY4uLisLGxwc/Pr3KNdmlBeehKOF5+uxX279AQFbTl0LI9OHQov7UMKK/tasI1wwqFgrNnz1JcXEy3bt2q/fFY0yBWoaK1wdnZmS1btjS9iyWER54IY83I3Llz2bFjBydOnKjxFUD3C2TFxcWEhISoR7x+1D+AlEol165dIyYmhpYtW+Lj4yMmEK5nj0IYU6okPvormjUn4istf7mXO+886dNIpfpXcXExly9f5taN67QxK8apLBathGPlNV93hy8jW3DuBs5dwbFzec1XE6jxelh3dqvo3r17pb/jhw1iFdLT0+nRowcDBgxg+fLlor+o0KBEm0wzsWzZMjZu3EhISMhDXYptaGhI9+7dq1xlWVxczIkTJzAzMyMgIOCR7yOVkpJCREQEOjo6BAUFYWFh0dhFEpqB4jIlr/0czv6oFPUyUwNdPnm2LYPb2Ddiyf5fzk30Yw7Q/tpB2sUdQVaaV3m9iSO49QTXHuASVF7r9QiEDC0tLQIDAzl//jwnTpxQB7LaBjEAKysr9u3bR1BQEHZ2drz33nv1eAaCUJkIY83Ahg0bWLRoEYcPH8bDw+OhH393IPPw8CAkJAQLCwsCAgIe6V+AhYWFREREkJGRgY+PD66uro/0+Qqak1VQyqR1Zzh/498rCTu4mPP18wFVRtFvMCoV3DoHV3ZDzP7yKx3/nwyQDMwptO1MvMyJMqfutOr8BIYPEUiaE5lMRvv27blw4QLHjx8nKCiIhISEWgWxCi4uLuzdu5devXpha2vLSy+9VA8lF4SqRDNlE7d7925GjRrFrl276NevX532VVBQwPHjx1EoFLRs2ZL27ds/ssHkziZJBwcHfH19RcfcRtBcmylvZhUyYc0Z4tIK1Mum9fbgv0+0apBO+pUoSiH+KETvhKt7y6cPUpOBYyfwGgge/cv7f2lpU1paSnR0NDdu3MDT0xMvL69HthuCJElcvHiRmzdvoqWlRc+ePWsVxO507NgxhgwZwk8//cTTTz+tmYIKwn2ImrEm7NSpU4wZM4a1a9fWOYhBedW+TCZDkqRH9oMZICMjg/DwcNEkWUMqlYrIyEiysrIwNzfHz8/vkW+2vp+rKXlMWH2G5NxiWprqM8DHlt6trenv04AjtStKIPYfiPwdruyFkjvG+ZKbgOcAaD2kPIAZVp1cXE9Pj3bt2uHs7MzFixe5ceMG7du3f2QHcdbW1kaSJLS0tDTy3u3Zsyc//fQT48ePZ/fu3fTq1UsDpRSEexNhrIm6fPkyw4YNY/HixYwePbrO+6voI2ZtbY2XlxchISHIZDKNTJ3UVCgUCqKjo7l+/To+Pj64u7s/MudWX0JCQlixYgXR0dGUlJQgl8vx8fFh5syZBAUFNXbxGlzY9UzGrTpNcZkKLxsjNkzpjL1pAzVJKhUQfwQitsLlvyoHMCNb8B4G3kPBtWeNO92bm5vTq1cv4uPjOX36NE5OTvj5+T0yQ7hU9BG7desWvXv3Ji4ujhMnTtCjR486X5zz9NNP88UXX/DUU09x9OhR2rat2RyjglAbopmyCcrMzKRz586MHj2ajz/+uM77qwhi5ubm6j5idRmpvymqqA2Ty+UEBATUuZnicRASEsLcuXPJzMzE3t4eAwMDioqKSE5OxtzcnGXLltU5kDWnZsrDV1KZsj4UpUqihZ42R97og7VxPY+5J0nlI91f2AKXtpVPrl3BuCX4PQ2+T5Vf+VjHGp+CggLCw8MpKioiICCg2Y84X11nfUmSuHDhAunp6VWusqytDz74gDVr1nD27FkxbZJQb0QYa2IUCgWDBw/G2NiYbdu21bnKvbS0lOPHj2NqakpgYGCl0PUoBLI7a8O8vb3x8PBolufR0FQqFePHjycsLAxPT89Kz5kkScTGxhIYGMjGjRvr9B5sLmFse/hN/vvLBfUYYu886c1LPeuxZjU/tTyAnd8MadH/LjewgDYjoc2z4NRV4+N9SZJEfHw8UVFRODs74+vr2yxrye531aQkSZw/f57MzEx69OhR576ikiTx/PPPc/v2bQ4ePCjGJBTqhQhjTcysWbM4dOgQISEhda7dUSgUhISEIJfL6dSpU7Vfqs05kN1ZG9a+fXuMjY0bu0jNRkREBBMmTMDMzKza91l+fj7Z2dls2LChTs0zzSGM/XA0lo93XwZAV1vGqokd6d2qHmpAVEq49jeErS/viK9SlC/Xlpc3P7YbCx79NDaf4/0051qymgxfIUkS586do6CggKCgoDq/9woLC+nRowcdO3Zk5cqVzepzUmgemt9PokfYqlWr2LRpE2fPnq1zEFOpVISGhqKlpUXHjh3vWbtxr3HImjKVSsXly5eJi4sTtWG1lJWVRUlJyT2bcQwMDEhJSSErq5rpch4hS3ZH8/3ROACM5Dr8MbM7HtYabuLOS4HwDXBuPeTc+He5Q0cIGA9+z4CBmWaP+QAVf/fx8fGcOnUKV1dXfH19m/yFGzUdR0wmkxEQEMDp06c5e/YsXbt2rdO5tWjRgj/++IOOHTvSrl07ZsyYUet9CUJ1RBhrIo4fP86sWbP466+/cHNzq9O+Kqrpi4qK6NGjxwOvnGxOgaywsJBz585RVlZG7969RW1YLZmbmyOXyykqKqr2C62oqAi5XF6zOQ+bqV0XbquDmI2xnH2ze2JuqKHhTyQJbpyBMysh6o9/a8H0zaDd8xA4AWx9NXOsWpLJZLi7u2NjY0NoaCjHjh2jY8eOladUakIedkBXbW1tOnXqxIkTJwgLC6NDhw51+lxzcnLi999/Z+DAgfj4+GjkCndBqNC0fwY9JhITExk5ciSfffYZffr0qfP+oqOjSU9Pp2vXrjWunq8IZElJSVy6dImm2HqdlJTE4cOHMTY2FkGsjvz8/PDx8SE5ObnKay1JEsnJyfj6+uLn59dIJaxfey8lM+eX8wB42Rhx9M2+mgliilK48Av80AfWPFHeKV+lKO+A/8xK+O9lGLKk0YPYnYyMjOjZsyfm5uYcPnyY27dvN3aRqqjtyPq6urp069aN7OxsjXyuBQUFsXz5ckaNGkVsbGyd9iUIdxJ9xhpZQUEBPXr0oFu3bnz77bd13l9sbCxXr16t9cCHTbEPmVKpJCoqisTERNq1a4ejo2NjF+mRUHE1ZVZWFnZ2dg+8mlKSJMrKyiguLq50Ky0tRZIkVCoVkiRVuimVSpKSknBwcEBbWxuZTIZMJlOPeaenp4e+vr76JpfL0dPTq7f3XalCxcqjsXz9dwxlSolnAhxYNqod2lp1PF5RNoSugdMrIT+5fJmOPrQdBZ1fAvt2dS57Q7h9+zbnz5/HwcGBNm3aNInxCOsyxVGFgoICjh07hoeHB15eXnUu05w5c9i/fz8nT57ExMSkzvsTBBHGGpEkSYwePZr09HT2799f506mN2/e5Pz583Tv3r1OzUtNKZAVFBRw9uxZADp27CiGrNCwinHGYmNjMTQ0xNLSktatW9O7d29sbW0rha6SkhJUKhXa2tqVApSenp46XFX8W3GTJInLly/TqlUr9f2K0KZSqSgtLa20f4VCgZaWFnK5vFJAu/N4+vr6tGjR4qH/XgpKFIz94RQRt8rH7xreriVfjmlftyCWextOfgPn1kFpfvkyIzvoPBU6TK52QNamrqCggNDQUFQqFR07dmzUGmhNBLEKOTk5HD9+nDZt2uDi4lKncikUCp588kn09fXZsWNHk+9rJzR9Iow1okWLFqnHr6nr1UypqamcOXOGzp07a2QsnKYQyG7fvk14eLj6Evym8Cv9UVBWVkZOTg7Z2dnk5OSQlZVFQUEBMpkMHR0dTE1Nq9RW3Xn/YYZCeNirKRUKRaVwdnctXMWysrIyDA0NMTMzw8zMDFNTU8zMzO55jOzCUkZ9f5KY1PLAFOhsxi+vdKv91EaZ8XDiy/KhKZSl5ctsfCHoVWjzXI0HZW2qVCoV0dHRxMfH0759+0apjdZkEKuQlpbG6dOn6dixI3Z2dnXaV1ZWFl26dGHUqFF89NFHdS6b8HgTYayR/P333zz11FOEhITg7+9fp31lZ2dz4sQJ/P39cXJy0lAJGy+QSZLElStXiI2NJSAggJYtWzbIcR9FZWVl6tCVnZ1NdnY2BQUF6OvrVwky+vqaH+C0voa2KC4urnROOTk5FBUVqQNaxTmZmZmRVaRk9MqTJGQUAtDeyYxfXumKXKcW4T4jFo59Vj5GmKQsX+YcBD1fL5+iqAk062tScnIy586dU19t2ZCfAZoOYhVu375NWFiYRqZKu3z5Mp07d2bLli08+eSTGiqh8DgSYawRpKSk0K5dOz788EOmTp1ap30VFxdz5MgR3NzcaNWqlYZK+K+GDmQKhYKwsDBycnLo0qWL6I/xECRJIisri4yMDHVQKSgowMDAoFI4qaj5aggNOc5YSUlJpXCWnZ3N7ewilkfpkFFcvk1rawO2z+yJofwhy5J1HY4shQs//xvCPPpDr7ng8mhPG5WXl8fp06cxMjKiQ4cO9f461mcQqxAbG0tMTAy9e/eu8yj9P/30E7Nnz+b8+fOiP6tQayKMNTCVSsWgQYOwtrZm06ZNdQo3SqWSkJAQWrRoUWV0fU1qqEBWWFjI6dOn0dPTo1OnTmKk6xpQKBSkpaWRnJxMSkoKKpUKS0tLdfAyMzOr8wjkddGYg75mFZQy9Otj3M4pT2ItjbR43V/CUFeGra0tdnZ2WFtb379ceclwdFl5nzBVWfkyz4HQ521w7Fj/J9FElJaWcu7cOQoLC+nSpUu99d1siCBWcZzz58+Tm5tbo+F/HmTy5Mlcu3aNf/75p1nOaCA0PhHGGtjHH3/M2rVrOXfuXJ1qfTT9YfIg9R3I0tPTOXv2rPoqLtEh9t6KiopISUkhOTmZtLQ0DAwMsLOzw87ODgsLiyb13DVmGCsoKaP3p4dJzy/F1kTOzpk9sDGWk5mZSXJyMsnJyRQWFmJlZaV+/tS1JMW5EPJ1eef8svLmTdz7QL/3H6sQdieVSqW+qrljx44an6exoYJYBU3+mC0oKKBTp04899xz/O9//9NgKYXHhQhjDejYsWMMHjyYY8eOERgYWKd9abKavabqK5AlJCRw6dIl2rRpg6urq0b2+SiRJImcnBx1gMjNzcXCwkJdu9OUx1trrDCmUKqY9tM5DkanYmqgw/bp1Y+sn5+fr35eMzMzMTUypHXBKWyiVqNVlFG+kUNHGLAA3Ho1WPmbssTERC5evIiPjw/u7pqZv7Ohg1iFim4e7u7udR7yIiIigq5du7Jz50769++voRIKjwtRn9pAMjIyGDduHJ988kmdg1hqairR0dEEBQU1WBADzY/UL0kSly5d4ubNm3Tt2rVZzY9X31Qqlbr5MTk5mbKyMmxtbXF3d8fW1rZRmx6bstvZRaw8EotSJXEwOhW5jhZrgjvdc4ojIyMjPD098fT0pOzyXtj7BrrZ5YN5Fujbk+Y/Hf2AUVjb2CCu5S3n7OyMkZERZ86cIT8/H39//zp/DjRGEAPQ19enS5cuHD9+HGNj4zpdYdm2bVu+/PJLXnjhBS5cuICtra0GSyo86kTNWAOQJIkRI0agq6vLtm3b6vTBlZ+fz9GjR2nTpg3Ozs4aLGXNaaKGTKlUEh4eTnZ2Nt26dWuyU7A0tPz8fK5fv86NGzeQyWTY29tjZ2eHpaVlsxzaoyFrxlJziytdNQnw3QuBDGlrf/8HZsbB3nfg6p7y+wYWqPq8TbrzMFLSM0lKSkKpVOLk5ISLi0uTrolsSIWFhZw8eRJjY2M6dOhQq/dnYwaxO926dYvz58/Tq1evOr2+kiQxbtw4MjIy2Lt3b5PqMiA0bSKMNYAvvviCr776ivDw8DoNxlpWVsbRo0exs7Nr9Glq6hLIysrKOHv2LGVlZXTt2vWxr+WpGKX++vXrZGZmYmdnh4uLC9bW1k1iBoS6aKgwll1YypiVp7iSkqde9vYQb6b19rhP4Yrg2Ofl44UpS0FLBzq/Ar3fAIN//04lSSI9PZ3r16+TlJSEubk5Li4utGzZslkGZE0qLS3l1KlTaGlp0aVLl4d6jZtKEKsQHR3NrVu36NWrV50uHsrNzSUwMJApU6Ywb948DZZQeJSJMFbPzpw5Q9++ffn777/p2rVrrfcjSRKnT59GkiS6du3aJL6kaxPISkpKOHnypPqKyYbu1N2U5Ofnk5CQQGJiInp6eri6uuLk5PRIhdOGCGMFJQrGrTrNhRvZyAAJGNXBkaXP3af57Op+2D0Xsq+X33fvC0M+AevW9z1WSUkJN2/eJCEhgZKSEhwdHXFzc3usa8sUCgWhoaEUFRXRtWvXGnWdaGpBrKJMZ86cQalU0rVr1zrVaoWFhdGzZ0/27dtHjx49NFhK4VElwlg9KiwspF27dkydOpW33nqrTvu6cuUKN27coHfv3k0qwDxMICsoKODkyZOYmZkRGBj4WFbhS5JEWloacXFxpKWlYW9vj6urK5aWlk0iYGtafYexUoWKKevPciwmHS0ZqCTo5GrOT1O7VD+oa14K7H0LIn8vv2/iAIMXg8+IhxqwVZIkMjMzSUhI4Pbt21hZWeHu7o6Njc0j+To+iEql4vz582RkZNCtW7f7hqumGMQqlJWVcezYMezt7fHx8anTvr766iu++OILIiIiHuuwLtSMCGP1aM6cOZw5c4ajR4/WqTkjPT2dU6dO0bNnT0xNTTVYQs2oSSDLycnh5MmT6qErHrcvLIVCwc2bN4mLi6OkpARXV1dcXV0b9AKMxvCwYUylUhEZGUlWVhbm5ub4+fndN7TP/e0CW8/dVAcxBzMD/pjZHSuju2oXJQnOb4J970BxDsi0oOv08vHC5HX7oiwuLiYhIYGEhAR0dXVxd3fHycnpsRtvqiJkJSYm0rVr12q7ZDTlIFYhNzeXo0eP1nlqOZVKRf/+/fH29ua7777TYAmFR5EIY/WkYhiL8PDwOo2MX1JSwuHDh/Hy8sLd3V2DJdSs+wWyjIwMTp06RatWrfD09HysglhZWRnXrl0jPj4eAwMD3N3dcXR0fGz6Gj1MGKuYtDw6OpqSkhLkcjk+Pj7MnDmToKDqR7k/GZvB5HVnKSpToq+rxdZpQbRxuOsHS85N2PkaxP5dft/OH0Ysh5btNXCG/1Iqldy6dYu4uDgKCgpwc3PD09PzsRu8ODY2Vj1NkLW1tXp5cwhiFa5fv050dDR9+vSp02wVcXFxtGvXjh07dojhLoT7EmGsHlQ0T/7nP//h9ddfr/V+JEni1KlTaGtr06lTpyYfYqoLZOnp6Zw+fRo/P7/HagwxpVJJfHw8V69exdTUlNatWzeppsiHrYGqrZqGsZCQEObOnUtmZib29vYYGBhQVFREcnIy5ubmLFu2rNpAdiAqhZc2hALw5Zj2PB3g8O9KSSqfyHvPW1CaB9py6PsOdJsJ2vVXa1XRhHnlyhWys7PVP6QelwAO/45FVlG71JyCGJS/hmFhYRQXFxMUFFSnv9tvv/2WpUuXiuZK4b5EGKsHs2fPJjQ0lCNHjtTpA7iiRqVPnz5Nqp/Y/dwZyGxtbTlz5gxt27bFxcWlsYvWICRJIjExkStXrqCrq4uvr2+T60dUmxqo2qpJGFOpVIwfP56wsLAqNaeSJBEbG0tgYCAbN25ES0uL4zHp2JnK0dPWZujyY+QVKwgOcmXhiDuuMM5Pg12z4Mpf5fcdO8FT34K15udvvZ/U1FSioqIoKSmhdevWODs7PzZ9JW/cuMGFCxfo1KkT6enpzSaIVSgrK+PIkSM4OTnRuvX9L+y4H5VKxYABA2jVqhXff/+9BksoPEpEGNMwTTVPZmZmEhISQlBQEBYWFhosYf0rKCjg6NGjlJWV0a5du8ciiEmSRHJyMtHR0SiVSnx8fHBwcGhSIQxqXwNVWzUJYxEREUyYMAEzM7Nqv6jz8/PJzs5mw4YN6Fq78Nx3J5HJwNZEzrXUAgKdzdjycjf0dP4/5MQchB3ToCANtHSh37sQ9BpoNU7NlCRJ3L59m+joaGQyGT4+Ptjb2ze590Z9uHnzJmFhYejo6NCrV69mE8QqZGdnc/z4cbp164alpWWt9xMfH4+/vz+///47AwYM0GAJhUfF4/ETrYEUFBQwadIkPvzwwzoFsdLSUkJDQ/H29m52QQzKm2mVSiU6Ojrk5ubyqOf9jIwMjh8/zoULF3B1daV///44Ojo2uS9blUrFihUryMzMxNPTEyMjI7S1tTEyMsLDw4OsrCy++eYbVCpVg5UnIiKCw4cPk5OTc8++OQYGBpSUlHA9OYOp60PJL1FgqKfNtdQCzFvosmJcYHkQU5TA3nmw6dnyIGbjCy8fgh5zGi2IAchkMhwcHOjXrx8eHh5cvHiRo0ePkpaW1mhlaggV03jp6OigUqkoLCx88IOaGDMzM3x9fQkNDaWkpKTW+3Fzc2Pp0qVMmTKF3NxcDZZQeFSImjENmjVrFufOnatT86QkSZw9exaVSkWXLl2a3Bf6g1Rc+env74+lpWW9Ti7e2HJycoiOjiYjIwNPT088PDya9BV0D1MD1bZtW40c8141Y3c2lebk5JCUlISJiQleXl5VrsLLz88nKycXx/GfcCm1BGtjOWl55V+Ma4M70dfbpnwU/d8mQdL58gd1fgUGfgC6D75ataH6z1VQKBTExcURExODubk5vr6+mJmZ1dvxGsPdfcSys7M5f/48Xbp0qdSpvznQ1GeySqVi4MCBeHp6snLlSg2XUmjumu43RzNz5MgRVq9eTXh4eJ36iSUkJJCVlUWfPn2aXXjJzMzk9OnTtG3bVj1VkybnsmwqCgsLiY6O5vbt27i6uhIQENAsBmrNysqipKTknsNpGBgYkJKSQlZWVr2W4+6mUjs7OwoKCsjOziYyMhI/Pz91IKto/jXr9xKXUktooadNUakSgJd7uZcHsaid8McMKMktHzn/6e+h9eAal6Wh+s9V0NHRoVWrVri6uhITE8Px48exs7PDx8fnkZgWrLrO+kZGRuqBq5vbPLQymYyAgAAOHz5MXFwcHh73mdXhPrS0tFi9ejX+/v4899xzDBw4UMMlFZoz0UypAYWFhUyePJkPP/wQLy+vWu+noKCAyMhIAgMDm8WX+51yc3M5deoUvr6+lfqIVUwunpSUxKVLl5p1k6VKpeLy5cv8/fffyGQy+vfvT9u2bZvNa2Vubo5cLqeoqKja9UVFRcjl8jpN2fUg1TWV6ujo4OnpSYsWLSgsLOTq1asoFAry8/OJjY1F7t2LJOPyDtRO5i3IL1HQ1sGUuQM8YP978OuL5UHMqQtMO/5QQey///0vJ0+eBMDS0hJTU1PCw8OZO3cuISEh9fY8AOjp6eHn50f//v3R1tbmn3/+ISoqCqVSWa/HrU/3u2rSycmJtm3bcvr0abKzsxuvkLWgq6tLYGAg0dHR5OXlPfgB9+Dq6qpurszPz9dgCYXmToQxDViyZAlWVla8+uqrtd6HJEmEh4fj5OTU7KrxKyYM9vDwwM3Nrcr6RyGQ5eTkcOTIEZKSkujZsyeBgYG0aNGisYv1UPz8/PDx8SE5ObnKa1BRA+Xr61uv855GRkYSHR1dpQO7hYWFurkuLy9PPSxEQGAgDt1HAtDD05IrKXkY6Gqz/Ckn9DaPhJDl5TvoNhOC/wJTxxqVQ6VSsWDBAiIjI8nMzOTatWtcvHhR3XTYkP3nDAwMCAgIoFevXqSmpnLkyJF6r52sDzUZvsLFxYVWrVpx6tQpCgoKGqGUtWdpaYmrqyvh4eF1+gx75ZVXcHV1ZdGiRRosndDciTBWR9euXWPZsmV88803dWqejI+Pp6ioqNEnAH9YFXNN2tnZ3feiheYayCpqwyqmSOndu3ez7d+jpaXFzJkzMTc3JzY2lvz8fJRKpboGytzcnBkzZtRrf6n7NZVaWFgQGBiIvb09c+bMYcOGDfy0cSO/zx7Iq/08OR2XCcDnvbVw3TYUEo6BnhGMWg+DPgLtmg//smnTJkJCQlAoFOjo6GBgYICOjg45OTlcvnwZAwMDoqKiiIyM1Ni5P4ipqSm9evXCwcGBEydONKtasocZR8zT0xNHR0dOnjxJcXFxA5ay7nx8fCgtLSU2NrbW+5DJZKxYsYLly5cTHR2twdIJzZkIY3UgSRKzZs1iwoQJdOzYsdb7KSgoICoqioCAgCbdAfxuCoWC06dPY2xsjL//fSZl/n/NLZDdWRvWo0cPvL29m/0YUUFBQSxbtoyAgACys7NJSEggOzubwMBAjQ9rUZ0HNZUWFxdjampKnz59aNu2LVpaWshk8Hd0KmUqiTedLzP41ATIuQEW7jD1b/B7+qHKoFKpWL9+PQqFAkNDQ3R0dJDJZOjo6NCiRQtKS0tJTk6muLi4wWuotLS0aN26NT179lTXkjX1Jr2HHdBVJpOp+wWeOnWKsrKyBipp3WlraxMYGMjly5fr1Fzp7+/Pyy+/zKuvvtrkPweFhtF8vvmboF27dnH69Gk2bNhQ631UNE86Ozs3q06tKpWKs2fPoq2tTYcOHWrcMb8ikDXlTv0qlYqrV69y7do1PDw8aN26dbMPYXcKCgqia9euDXoFYYWKptLw8HA8PDyqDPCanJxMYGAgF/KN+XN3NHMHteabQ9eISsrhvwZ/MT11c/nGHv3hudXlHfYfUmRkJDdv3kRXV7fKF6FMJkMul5Obm4uJiUm99p+7n4pasooO/h4eHrRq1arJjeJf25H1KzrFnzp1ijNnztC1a9cmd273YmFhoW6u7NmzZ60/vz744ANat27N1q1bGTVqlIZLKTQ3j843TAMrKipi1qxZLF68uE6DAcbFxVFUVISvr68GS1e/KgJkcXExnTt3fugP0aZcQ5aTk8PRo0fVtWE+Pj6PVBCroKWlRdu2benVq5e6BqqhjvugptIRL05j0V/RrDwax/eHY/n+n8ss1fmBV6X/D2JdpsG4X2sVxKC8qVRLSwsTE5Nqm8m0tbUpKyvDycmpUbsN3FlLlpKS0uRqyeo6xZGWlhadO3dGoVAQFhbWpD4HHsTHx0c972xtmZqa8umnnzJnzhzRmV8QYay2lixZgo2NDVOmTKn1PvLz84mOjm52zZPR0dFkZmbSrVu3Wk/T1NQCmUql4sqVKxw7dgxbW9tm3TesqbtfU+nHn3zKmmiJEoWK3q2sOXopjpXanzJa5wiSTAueXAZDPqnT3JIVTaV2dnbo6elRUFCAUqlEkiR1MNTR0WHChAlNIojf2Zfs+PHjREdHN9jAvPeiqbkmdXR06Nq1Kzk5OVy6dEnDpaw/2traBAQEcOXKlTo1V44fPx43Nzc+/PBDDZZOaI7EoK+1EBsbS9u2bTl69Git+4pJksSJEycwMTHB399fwyWsPzdu3ODixYv06tVLI5PeVje5eEPLyckhPDwclUpFYGCgCGEadL/pkKobbPXDvy6z5kQ8VkZ6TGlvRI8z02irlYCkY4Bs1LoaD1txPxVzYYaHh2NhYUFCQgL5+fmoVCpkMhkymYwuXbqwd+/eJhHG7lTxXpUkiYCAgEZ5r9bHpN8FBQUcOXIEPz+/ZjV9WmRkJBkZGXVqrrx48SJdunQhPDwcb29vDZdQaC5EGKuFYcOG4ejoWKdJX+Pi4oiNjaVv377NplYsKyuLEydO0LlzZ2xsbDS238YMZPHx8URGRjbZPjnNXU3mpqwQci2dcatOA7B8iAVt/wnGVZZMsZ4F+hO3gkMHjZWrYuDZrKwsbG1tUSgUFBQUkJOTg62tLZ999lm9X8xQW3f2afTx8cHd3b3B/mbqI4hVSEtL4/Tp03WeB7IhKZVKDh8+jIuLC56enrXez6xZs4iKimL//v1Nrg+t0DCa1s++ZmDXrl2cOnWKjz76qNb7KC4uJjo6mnbt2jWbIFZUVMSZM2fw9vbWaBCDxmmyVKlUXLhwgStXrtCtWzd8fHxEEGtEecVlvLH1IgCz/FX0OPoCrrJkUrVtkL+8X6NBDCo3lebk5JCZWT5sRrdu3Zp0EIPyvlbe3t4EBQURExPD+fPnG2QIjPoMYgDW1tb4+vpy9uzZZjOPpba2Nu3bt+fy5cv3vEK4Jj744AMiIiLYunWrBksnNCeiZuwhlJSU4OPjw7x583jppZdqvZ9z586hUqno1KmTBktXf5RKJcePH8fY2JiAgIB6++XWUDVkJSUlnD17FoVCQefOnZvd4K3NSU1rxk7FZTB53Vk6t7jFStWHyEsziZEc0Jn4B27utZ/V4kEael5KTav4kaSlpUWnTp3uOdl6XdV3ELvzOBcuXCA7O5sePXo0mx+rmvhM37BhA++++y5XrlwRn0mPoebzqdMErFy5EiMjIyZPnlzrfWRkZJCUlESbNm00WLL6I0kS58+fRyaT0a5du3qtQm+IGrKKqyXlcjk9evQQH3pNRFd3S/4ZZ84q1QfISzO5pHJlf6e19RrEoPGuKtUUAwMD9fu4vq62bKggBuVDXvj7+6Ojo1Pnke4bkp+fH6mpqaSlpdV6H+PHj8fW1pYVK1ZosGRCc9G8PnkaUV5eHh9++CGLFy+udXOWSqXi4sWLtGrV6p6TNTc1sbGxpKen12oIi9qoz0B2+/Ztjh8/jrOzMx07dmw2v7ofC0kXsNsxGp3SHMJVnvzX4EMmP1H7gZQbm0KhYNu2bSxfvpxt27ahUCjq7VgVA5G6u7tz/Phxbt26pbF9N2QQq1BRy5eVlcXVq1fr/XiaoK+vj7e3NxcvXqz1la5aWlosWbKExYsXN8vpsIS6EWGshj777DNat27Nk08+Wet9xMfHo1Qq69TRsyGlpqZy+fJlOnfuXG/NH9XRdCCTJIkrV64QFhZGQEAArVu3Fp1km4jVx+M5H3ocNjwFxdmES15MKH2bOcM7YqDXPPvwrVy5Eg8PD8aPH8/cuXMZP348Hh4erFy5st6OKZPJ8PLyomPHjpw/f57o6GiN/N00dBCrIJfL6dKlCzExMSQnJzfYcevCzc0NmUxWp6mSBgwYQMeOHfnkk080WDKhORBhrAZSU1P57LPP+OSTT2r9JV5cXMzly5fx9/dvFk0hxcXFhIWF0bZt20YZhVxTgUyhUBAaGsr169fp2bMnLVu21HBJhdq6nJzLL7sP4rDreSjKIl7fhwklb9HWw4lBfnaNXbyHolKpiIiIYO7cubz++uskJyejr6+PiYkJ+vr6JCcnM3fu3HoNZAB2dnb07NmTW7ducebMmVpPNdSYQayCqakp7du3JywsrE6d4xuKlpYW/v7+XLlypU7lXbx4McuXL9doDafQ9IkO/DXw2muvcf36df74449a7yMsLEzdYbypkySJkJAQ9PX1CQwMbNRapLp06i8sLOTMmTPo6OjQqVMn5HJ5PZa0aWuIjuoVHyUqlQpJkpAkidLSUg4ePMgTTzyBnp6e+piSBNO/3cGCtNexl2VSYOFHt9uzyZcZ8tdrPfGxN9Fo2epTSEgIK1asIDIyUj25t66uLoaGhuqLFiRJIuf/2Hvv+Lbvav//qeEhL8l7721n2dnObtMWuiHMX3Nbxrel3KSXUgqXUeBeKJcL9EJvaRllFHpLgcuFQkpLV5rtJE5sZ3nvLW/Zlm1t/f5QpNqxndgfS9bbiZ6Phx9NLX3ko/l56YzXGRkhPj6exsZGj5fITSYTZ86cwWg0snHjRoKDg+d9rAhCbCqVlZXo9Xq2bNmyLL7IlpeXY7fbF7Wv+CMf+QgajYbnn3/ejZH5EBmfGLsGzc3NFBYWcvbsWcmrUQYHBzl58iQ33XTTsmgYr6uro6Ojgx07dkh22HcnUgTZ4OAgZWVlJCQkLMvGbHfiFAs1NTUYjUYCAgLIz89n//7987JwsFgsGAwGDAYDRqPR9e+pP0ajcUFZmJq+CT7c8e9kynvQB6Xwadm/cXowkLsKIvjm7dkEBgYSGBgofF+f069saGgIhUJBbW2t6/Upl8sJCQlxvYdMJhMGg4GXXnqJPXv2eDw2pwDv6Ohg/fr1REdHX/MY0YQYOF5/R48eJT4+nvz8fG+Hc00MBgMHDx5kw4YN83rMZ6O+vp5Vq1Zx/vx5cnNz3RyhDxHxibFrsHfvXpRKJb/5zW8kHW+32zl8+DCJiYnk5OS4NzgPMDAwwKlTp9i2bRtqtdrb4bhYiCDr7Ozk3LlzFBYWkp6evoRRisdUsRAfH49KpWJychKtVkt4eDhPPfWUS5DZ7XbGxsbQ6XSMjIyg0+kYHR3FYrEgl8sJCAhwiaSp/3b++Pn5IZPJkMvlLid7q9XKm2++yS233IJCocBmszE6OkL/T29nBU2M+MXw2sof89VSKwEK+MGOYAIxYTQasdlsKJVKQkND0Wg0rp+QkBAhxLXTyb+iooKsrCxaW1uprq5GqVS67rtSqXS9jxz3fZSnnnqKRx55ZMnibGtr4+LFi6xatYqUlJQ5ryeiEHMyOjrK0aNH3W447SmamppobW1l165dkl+rDz/8MAMDAz7vsRsEsb92epnz58/z5z//mdraWsm30d7ejsViITMz042ReQaj0Uh5eTmFhYVCCTF4r4fsxIkTAHMKsvb2di5cuLBsPrQ9ic1m49lnn2VoaIisrCzX4xUSEkJWVhZjY2O89tprBAcHMzo6ysjICODo1VGr1aSmpqJWq1GpVC6hJRU/Pz9HhshqofP3n2IFTegII+CTB/jl73uBcT6zI4u7b3VkAex2O2azmcnJSUZHR9HpdLS1tXHhgsMYNiwsDI1Gg1qtRqPREBoauuQCraqqipqaGuLj45HJZAQGBiKTybDb7S5RarVasVgsKJVKl6hd6r7F1NRUgoKCKCsrw2azkZaWNuM6IgsxcDzfK1eupKKigp07dy7pQJEU0tPTaW1tpa2tTfIXwm984xtkZ2dz5syZZeNJ6UM6PjF2Fb761a/y2c9+VvKuNKvVSl1dHQUFBcK7u9vtdioqKggPD5/1w1oEriXIWltbqaqqYtOmTURFRXkrTGG4UiyEhYWRmppKSkoK0dHR2Gw2enp6GBoaIjMz0yVqPNYjaLej/9sXyNadwGD3o/GWX9LcFUJzfzMRwf48tOO9LywymQx/f3/8/f1Rq9UkJydfvgk7er0enU6HTqejo6ODixcvYrfb0Wg0xMXFERcXR0hIiMd7HYeHhzEajS6bmtjYWPz9/TEaja7M4NT+uYmJCeLj47nnnns8GtdsREdHs2nTJk6dOoXVap325VB0IeYkJSWFgYEBysvLKSkpEXoiWi6Xk5+fz4ULF0hOTpZUbk9ISOBzn/scX/7yl3nnnXeEvr8+Fo9PjM3BsWPHOH78OL/97W8l30ZLSwv+/v4kJia6MTLP0NTUhF6vZ+fOnUK/6ecSZE1NTdTW1rJp06Zls9fO0zhLk5s2bSI1NZXQ0FC6u7tpbm7mxIkTDA0N0dLSws9+9rOrlq/cRtnzhFz4DXZk/DH1m3x048187r+OAvDPOzMJCbj2x5FMJiM0NJTQ0NAZAm1wcBCtVkttbS0qlcolzCIiIjySNQsPDycgIIDJyUlX6TQrK4uamhpXFsyZ4RsfH8ff35+vfOUrXuuDi4yMpKSkhJMnT2Kz2cjOzl42QgzeM4Q9cuQIDQ0Nwrd9OIc1mpubJcf6pS99iYyMDN555x1uueUWN0foQyR8YmwOnnzySf7lX/5FcobFbDZTX1/P2rVrhRY34DC0ra2tpaSkRIiG/WtxpSALCAigsbGRkpISr9hwiITZbKa/v5+enh5GR0fZu3cvra2tnD17ls7OzmnmoxMTEwQEBCzJYyZrehfe+LLj37d8iwe2PML/nGqjSzdJbFgAezdJyz6D4yQdHBxMa2srJpPJlfnr7e3l7Nmz2Gw2YmNjiYuLIyYmxm2v8cLCQvLz86msrCQzMxOZTObKKjc2NroyZBaLhfj4eL7yla/wmc98xi1/Wyrh4eFs2bKF0tJSVwm1q6tLeCHmxM/Pj3Xr1nH8+HFiY2OFa6eYikwmo6CggNOnT5OWloa/v/+Cb0Oj0fCFL3yBJ5980ifGrnN8DfyzUF5ezvbt22ltbZU8DVNTU8Pg4CBbtmwRWozZbDaOHTtGVFSU5GlRbzE+Ps7hw4ex2Wxs27YNjUbj7ZC8gtVqRavV0t7eTn9/P8HBwcTFxREbG8vnPvc5KioqXGLBid1up6mpieLiYv7nf/7HY/1WZrOZI6+8wM3NTyIzjMCavXDPsxitNnb+4DA9Iwb+/e5CHihJk/w3rjYtunnzZoaHh9FqtWi1WvR6PVFRUSQnJ5OQkLDo9gHngMTw8DBxcXGuAYnu7m7sdjt33HEHW7du5Z577hFqMnRkZIRjx44BsHPnzmUhxKZSU1NDb28v27dvF2KY42qcPHmSsLAwyZ+vOp2OlJQU3njjDaEX2PtYHD4xNgsf/vCHSUhI4L//+78lHW8wGHjnnXcoKSkhIiLCzdG5l4aGBtrb29m5c6fwfW1X0tDQQENDA3K5nMTERI8uFxeRsbEx2tra6OjowM/Pj5SUFBISEqadWOcSC7NNU3oC8/gwkz/eSpihkwuyXGpvfZmPbM7i5dPtfPWVi8SGBXDki7sI9JP22lvItCg4BHxPTw9tbW0YjUaSk5NJTU0lLEy6r9lsYrCgoIB9+/YJefJ0libb29ux2+1kZmYuO/sEm83GkSNHSEhIED52nU7H8ePHufnmmyWvwfvXf/1XqqurefXVV90cnQ9R8ImxK6irq2P16tU0NDS4elIWyvnz5zEajcIbvDrHxZeDaLyS5ubmaaVVqcawyw1n031LSwvDw8PEx8eTmppKVFTUnPfba2LBbsf2f59GXvVnhmThvG/ySe7cUsxXb89j138dpmNokm/cWcCntkqbNrvSWmIhmT+73c7g4CBtbW10d3ejVqvJyMggISFBUqZlKUx13cGVPWI2m40TJ06QlZVFdrZnl7K7G6fIEc2GZzbOnj2LQqGgqKhI0vFarZb09HTKyspYuXKlm6PzIQI+MXYFn/rUpwD49a9/Lel4vV7PoUOH2LlzJ6Ghoe4Mza0s5/Kkc2py8+bNLhG5GKf+5YDJZKK1tZWWlhbkcjnp6emkpKTMuw9lMWJB8rFnfw1//zw25HzE+ARVykKO/esuTjQO8Lk/nCMy2J/j/3qT5B2UFy9e5P7773d5j12Jc+ryxRdfvOoJzGQy0dHR4dodm5aWRlpa2nW3sWGuZn2dTkdpaSl5eXlkZGR4OcqFsVzKlePj47z77rvs2LFDchb2n//5nxkZGeF3v/udm6PzIQLiNDEIQEdHBy+//DLnz5+XfBu1tbUkJSUJLcTA0WBssVjIy8vzdigLor29nUuXLk0TYjB/H7LlxsTEBA0NDXR0dBAeHs7KlStdVhULQS6XS/pGLdm9X3sR/uFo2P+p7GOctefxmZJUIoP9+dmRZgA+UZK2qGXgV1pLXIlKpaK3t5fh4eGr3o6/vz+ZmZlkZGTQ29tLU1MT9fX1JCUlkZOTs6BVQqJytalJjUbDpk2bOHnyJHK5XFhrm9nIzc1Fq9VSX18v9GdZcHAwqamp1NTUsHHjRkm38cUvfpH8/Hy+/e1vLzvR7OPaiPtVwgv813/9F3feeafkHoTR0VG0Wq3QHwrgiLO+vp6ioqJl1SfW3d3NhQsX2Lhx46z2Fe5aLi4CJpOJS5cucfDgQcxmM9u2bWPLli0kJCQsmch09mNVVFSg0WhIS0tDo9FQWVnJ448/Tmlp6RzBT8D/fQqsRvoTdvGDyTtQ+cl5aFsGJxoHqekZJchfwT9tlj5BCdOtJWZjcnJyQdOiMpmMuLg4tmzZwo4dO7DZbLz77rtcvHgRo9G4qFi9yXzsKyIiIti0aROXLl2is7PTC1FKQy6XU1RURGNjo8u0WFRycnLo7++/5peDuUhPT+dDH/oQP/jBD9wcmQ8R8JUpLzMwMEBqaipHjx5l7dq1km6jvLwcpVLJ6tWr3Ryd+7Db7Rw/fpyIiIhlVZ509oesXbuW+Pj4q153OZcsLRYLTU1NNDY2EhERQUFBgVf6YRbTj8Wrj0L5CxAaz6dVP+Jgu41PbE7h3+5ZySdeKONwXT+fKEnj3+5e3OvPGeNUa4l5xzhPRkdHqa6uZmBggKysLDIzM5eF/YuTOYWYxQSTQzA5DIZRMI6CeZK+qE2UlZU5+ki73oWBerCawW4DLp8qZHKQKWDnV0BxubjSfARGu8AvCPxDIDAMAtWOH1UEKBdu67AQnOXKHTt2CP1+v3TpEhMTE5L7iS9dusT69etpaWkhLi7OzdH58Ca+MuVlnnnmGbZs2SJZiI2Pj9Pd3c1NN93k5sjcS0dHB5OTk8JPIE3FYDBw+vRpcnNzrynEYHmWLG02G21tbdTV1aFSqdi4caNXtwhc6d4/FWcGqbq6mqqqqunlz/q3HEIM6Nj5Iw7+yYZCZudTW9Jo7NNzuK4fmQw+tWXxO0Plcjn79+/n8ccfp6mpadZp0X379i2qlygsLIxNmzYxODhIdXU1LS0t5OTkkJaWJmZW2W53CKzhVuy6drqba+j0L35PiP3vA9B4EExjM49V+BPz9X7y8/MpKyvjloE/omh8a+6/tfMr7/274rdw6c9zX/fxRgi5bBNU8T/QVQ5hCe/9qFNAnQR+0tYc5eTk0NnZSVtbm9Bl1szMTN555x3GxsYktbKsWLGCW265hR/96Ed873vf80CEPryFT4zhsAj48Y9/zF/+8hfJt9HY2EhCQoLQ/SVms5mqqipWr14tlOfR1bBarZw5c4aoqCiysrLmfdxyEWR2u52uri5qa2tdDuNSesLcjaR+rIkhOHB5AfamfSSvfT+vRA7y+7dOEK8O5Nuv1wGwOz+WlMggt8RZUlLCU0895epr6+3tJSAggOLiYrdOi0ZGRrJ161Z6e3uprq6mubmZvLw8kpKSvP5cUf4baCuFwUbHj8FRrpMBcTI/1I+1vJcRs5rfE2IyOQRqHNmrgFAICAObjYyMDEZHR2kayiBr7aeQK/0vZ8Mui1q7DWxWkE8Ro/GrHX/XNA4mvSPbZhhxZNzsNlBNKRU3H5pbuIXEwmeOQWis4//7asFmhohM8J/7NaNQKFy7K+Pj44UdvlCpVCQlJdHQ0EBxcfGs1zl69Cg/+MEPKC8vp6enh1deeYV7770XcHyGh4WF8dRTT/HjH/8YjUbD7t27+c///M9pO0+HhoZ45JFHePXVV5HL5ezZs4f//u//XnZ+cjcSy+OM7GFeeOEFsrOz2blzp6TjDQYD7e3t7Nixw72BuZmamhrUavW8sksiYLfbuXDhAjabjTVr1iz4pCe6IBscHHT1I+Xl5ZGcnCzMRNiVq36uZNZ+rDe/CnotRGbDzV8HYEViGFti7YwZLPy53NGL9MlFGLzORklJCZs2bfK4tYQzIxgbG0tHRwc1NTU0NjayYsUKyebQ88Jqgf5a6K6A7koYaoZ/+is4X8sNb0Pt36cdYg6MRK+MJCQxj5DAKR/zt34bbvkWBEdCgBpmeYxkwKpVqyjV6xkLCqK4uPja75stn3P8XInNBsaR98qZACs/DJFZMNp9+acLdB1gHncI+uApGeGjP4BL/+eIKjwVovMgJh9iVzh+onJc9yEuLo7IyEhqampYs2bN1eP1ItnZ2Rw6dIi8vDyCgmYKzPHxcVavXs2nPvUpPvjBD067bGJigt7eXnJzc7njjjvYs2cPn/vc57j77rs5e/as63r33XcfPT09vP3225jNZj75yU/y0EMP8fLLL3v8/vmQxg3fM2az2cjLy+Ob3/wm9913n6TbqKqqQq/XS56SWQqcjts7duwQftLTSVNTEw0NDezYsUOyWSKI10NmsVioqamhra2N3NxcMjIyhCt5Lbgfq+Ed+N0eQAaffhtT/Fr8lXLMZjOvv/46w1Er+bdXa8iMDuadx8Tu65kvVquVlpYWamtrSU5OpqCgwH39ZB1lUP8mdJyGrgqHUJnK56scZT2Aqr86MmJR2dgjMqnpNdKhHVj0iiODwcCRI0fIyMjwvAeZs7w62g1xK977/V/3Qd1rjsuuRKaAr3a/V9psP82ETcG7F7vZsnWb0KvRzpw5Q0BAAKtWrbrq9WQy2bTMmJM///nPfOELX6CpqYmKigo2bNhAW1sbKSkp1NTUUFBQwJkzZ1i3bh0Ab7zxBrfffjudnZ3TMmg+xOGGz4y9/fbbjI6O8uEPf1jS8SaTiZaWFiGdtp04M0wZGRnLRoj19fVRU1NDSUnJooQYiJUhGxwcpLKykoCAAKHX0CyoH8s0Dn9/1HHgps+ij17N9u+8xcooOQ9vjMZuhz+UdQBw38bU60KIgaM0lpWVRXx8PJWVlRw+fJg1a9YsPEtmMTpEV9KG94RF1Stw6ifvXcc/FBLWQEKRoyQYMMWrqvBeYEqzvhuEGEBgYCAbN27k+PHjhIaGerZhXCaDoAjHz1TufQ54DvT90F/jKFv2VUNvlaP8ObXH7M2vEtR1ltuVKkYbM7CvuBVZykbH4xo8c/ram2RnZ3P8+HFyc3MllVTvueceHn30Uf7+978THByMTCZzrYM7efIkGo3GJcQAdu/ejVwu5/Tp03zgAx9w193w4UZueDH27LPP8tBDD0la4grQ0tJCeHi40A72zqb9nJwcb4cyL/R6PWfPnmXVqlVue1y9LcimZsPy8/PJyMgQXpTMux/ryPdhpAPUKZwKuoWvPfJthiI3cbRGS+3/fIP7HvkKtb16ApRy9hQnefdOeQDna6ulpYXTp0+TnJxMYWHh1fsyRzodma+Gt6HlCJgn4P4DkHG51SH7VpjUgVNMROfNWlJ0Mh/7CiloNBqKioooLy9n27Zti1obtShCoh0/6dtnv9xudwg5/xDkJj2akSo4UQUnLl+etg0+8ffZj/UCGo2GyMhImpubyc/PX/DxSqWSz372szzzzDPodDo+/vGPu54brVZLTEzMjOtHRESg1WrdEr8P93NDi7Hm5mbeeustfv7zn0s63mKx0NzcLHkCcylYbk37ZrOZ06dPk5qaSkpKiltv21uCbLlkw2bjmv1YfbVw8lkAatI/yWNffoKeVfcDEDNaj0at5lSv47rrYpWog5aPLcRCkMlkZGRkEBsbS2VlJYcOHaKoqGj6ROxoD1S+5Ojv6jk3/QZCYmFi4L3/z9zl+JkHnhJiThITExkdHaWsrIzt27dL/uLqUWQyuO9PjsGCgQZGqt5mtPogifZu5AN10zNudjv85g6IzoWMnQ6Bp1r6kmZ2djanT58mKytLUnn7gQce4Otf/zq5ubn89Kc/9UCEPpYS8c/OHuSnP/0p9957r+QaeltbGyqVyrPNu4ukoaGBsLCwZdG0b7fbKS8vJygoiIKCAo/8jaUUZFOzYXl5eTN6r5YLc7r32+3wxpfBZsGe836+/b9nGbCqsGuSkdmsRIzWExASRsWg4z7rKl/HZrtZmCEFTzA1S3bq1ClSkhMpKFzp+CI01g2Hnrx8TRkkb4Cc2xxZsNgV7zXkLwBPCzEneXl5jI6OcubMGTZv3izucyhXQEwe6pg8qgPXMRIayoqMBMdUp5PBRmg74fg5+2vHlGhCEWTthqxbILF4+qSoh4iMjCQsLIzW1tYF9+SZzWb279+PWq2mpKRkWsYyLi6Ovr6+ade3WCwMDQ35vMkERtB3lOcxGAy88MILfPazn5V0vN1up7m5mezsbGFPsJOTkzQ3N1NQUCBsjFOprq5mfHycdevWeTTepXDqHx4e5vDhwwwPD7Njx44ZxqnXBfVvOGwKFP7UpX+CmpoaAgocPnthY80orUZ0IakYrDKUxlG6Ko9QVVXl5aA9j8w4RsbwUd7f/SNiyr7LoUOHGBoagoRiWP3/wd0/hsfr4dNvwbYvQNxKoYUYODJ/xcXFGI3GZfMcFhQU0NraygSBEJ723gVhCfCx38PGhyEq19F71lUOR74Hv9oNb39jSeKTyWRkZWXR3NyMzWab93Fms5mPfOQjNDQ08Lvf/Y4//elPjI+/N+CxefNmdDod5eXlrt+9++672Gw2oYfMbnRu2MzYn//8Z6KioiTbUWi1Wmw2m9AZp/r6emJiYoSeKnLiNGzcvn37kjicezJD1tHRwfnz58nNzb0+RRg4/KreesLx78376DMHYTBbMUY6VoFFDNcCMBSa6fj/sUb0RoPkVTDCY7dD5xk4+4Kj+d4yiQKIVYUzvvPblJaWsnLlSlI/4J5y0lIKMSd+fn5s3LiRo0ePEhYWRmrq4tZZeRqnjU9tbe10Ty//YMi73fEDMNLl+FLR8Lbjv1PLw+2n4NB/QN4dkHs7aJLdGmNcXByXLl2ip6eHxMREwNEz29jY6LpOS0sL586dIyIigvj4eD70oQ9RUVHB3//+d2JiYkhKSuL5559n3759+Pv7k5+fz/ve9z4efPBBfvazn7myaB/72Md8k5QCc8OKsZ///Oc8/PDDkk+ULS0tpKWlCZuu1+v1tLe3S/ZOW0omJiY4f/48a9euXdJ+KncLMucJsq2tjQ0bNsxoor2uqHjRUe4JioKtjxHe0IY8aRU2ZSB+pjGCx7uwKAIZDXY07Af1VWFewJ7IZcXF/4PjP4LeS+/9LioXiu5DtvIjZIbFE6aJ4MyZM4yOji7aA80bQsxJcHAwa9eupaysjKioKKFNrsFRXn333XfJysqae/hAnQhFex0/Vsv0y2pedQxYtByBf3zJkd0suBvy74bIzEXHJ5PJSE9Pp6WlxSXGzp49y65d7wnCxx57DHD0iP3bv/0bBw4cAJjmpfbYY49RVFTk+rz/3e9+x/79+7n55ptdpq/PPPPMouP14TluSJ+xqqoq1q1bR1dXl6RpvbGxMQ4fPsytt94qrNPzmTNn8PPzE9r8EBwnlpMnT6JSqSgqKvJKDO7wITObzZSXlzM+Ps7GjRuXVZP+gjGNw3+vgfE+eP8PYOND2Gw2PvzAg5wfVRGtDiFquIrB8Hy6E3aQFGxH/+cnKCwsXNSeSGE5+G049hQoA2HFHlj7CUhaP6P0OD4+zunTpwkMDGTdunWSGuG9KcSmcv78ecbGxtiyZYvwmd8LFy4wOTkprUQ33Ao1f3cMXbSfwrWfExwWIx//I4QtrjpiMpl466232LZtm6Q9tKOjoyQkJHD06NE5Xf19iM919qk4P55//nk+8pGPSLZNaGlpISEhQVghNjw87HJpFp22tjbGxsZYsWLFta/sIRbbQ6bX6zl69Ch2u53t27df30IM4MwvHUJMk+oQHjia/L/w2U8T01+B7szf0Ov16C6XKIsjbWg0mkXviRSCgQaHEWnz4fd+t/7TcOt34Au1cO9PHI35swiU4OBgtm3bhkKh4OjRo4yNzbIf8iqIIsQACgsLmZycpKWlxWsxzJfc3Fz6+/sZHBxc+MHhaVCyHz71hqPP784fQcYuh+Gsvs8xBeukrRTGB+a8qbnw9/cnKSlJ8mMZFhbGfffdJ9kVwIcY3HCZMbPZTHx8PH/+858l9YtZLBbefPNNNm/eLKy3WGlpKWq1msLCQm+HclUmJiY4dOgQ69evF6KkJyVD1tfXx9mzZ0lNTV02gxKLwqiH/14FE4Nw709hzf837eLS0lKeffZZqpraGdn5ryCT840iCzmJjt2Oy5beasdqnqpXALvjhHz/XyXdlN1up7a21mWLM58JN5GEmJOBgQFOnTrFrl27hC9X1tbW0t/fz9atW93zHh0fgMEmhw8cOMqbP8xzbArI2g2rPwY575/34nPnhpTbbrtNUs/s6dOnue2229BqtQQGSlu27sO7LPOvqQvnzTffJCgoiG3btkk6vrOzk+DgYGF7X/r7+9HpdJ5fX7JI7HY7586dIyEhQQghBgvLkDlXApWVlbFixQoKCwuvfyEGcPZXDiEWkQkrP+L69XOHGjlwvps16zbw0ksv8U9f/gHI5GSG+xEZyPKd4hpohP/7NPy0BKr+Atgdjdy7vir5JmUyGfn5+axevZqzZ8/S0NBwzdeaaEIMICoqipSUFCorKz0ykexOMjMz0ev19Pb2uucGg6PeE2Lg2MmqTgKbxTFl/KdPwH/lwN8fc0xqXuPxUavVhIWF0dHRISmcDRs2EB0dzWuvvSbpeB/e54YTY7/73e+47777JJdLWltbSUtLE/bEW1dXR2ZmppjGjFMQoTw5G/MRZHa7nfPnz9PQ0EBJSYnbzWlFw2azcfHiRY4degfzsf92/HLbY67lz6MGM0+/U8+//L6Sbt0kcrmc6hHHZXcVe3/izhn/0aNHuXjx4vxtBA59F57bcHlRtd3RtP3wcfj47x2lyEWSlJTE1q1baW5uprKycta4RBViTgoKClwWOiLj5+dHdnY2dXV1cwrHo0ePctddd5GQkIBMJuOvf/3rtMvtdjvf+MY3iI+PR6VSsXv3bhoaGhwXqpPgocPo9r7DX4ey6Bi1g2HE8eXlFzc5sqrXIC0tjdbWVknCViaTcd999/G73/1uwcf6EIMbSoyNjY3xt7/9TfJC8OHhYfR6vWvqRTSGhoYYGRkhIyPD26FclYmJCaqqqigqKloSG4uFcjVBZrPZKC8vZ3BwkB07dghbqnYXpaWl7N27l/vvv593/uvT+BkGGTQHcnL8vRH/Q7V9mK12MqODyYoJZcJk4Xijo3fmlnzvGiJPjf/hhx/m/vvvZ+/evZSWll774PBUsFsh533wmWPw0f9xeIK5EY1Gw44dOxgZGeHs2bPTBJnoQgwca3aKioqoqalBr9d7O5yrkpqayvj4OAMDs/d1jY+Ps3r1ap577rlZL//+97/PM888w89+9jNOnz5NcHAwt912GwaDwXWdjz/yDf7tqJXuj7zJxaInOdASgMkmh9z3v3dD/XWOYYArRFdiYiIGg8HhSSeB++67j9dee+36tY+5zrmhxNgrr7xCTk6O5GxMa2srycnJQgoIcPiKpaWlCRsfOE4wlZWVJCYmClOenI3ZBJnNZuPs2bOMjY2xdevWRS8wF53S0lIef/xxKioqCNeo+XShEYBfXPLnC1/6ikvQHKxxuH3fUuDofTrROIjJYiMpXEV2jPcExNT4NRoNaWlpaDQaKisrefzxx6cLMrsdLv3ZMTnnZNVH4dPvwP/3R4hf5bE4AwMD2bJlCxMTE5SVlWG1WpeFEHPiLFeeO3dO6HKln58fGRkZ72WzruD9738/Tz755KyLtO12O08//TRPPPEE99xzD6tWreLFF1+ku7vblUGrqanhjTfe4Je//CUbN21m5T2P4P/xF4n+/gjdtimLyo//CH59m6P0feaXYHQMcigUCpKTk2ltbZV0/7Kzs1mzZg3/93//J+l4H97lhhJjL730kuSsmMVioaurS1ijw9HRUfr7+8nMXLz3jSdpbW1lfHxc+OECmC7ILly4QFlZGRMTE2zZskXYSVp3YbPZePbZZxkaGiIrK4ttCWZSVJNMWBWU2wsZHh7mueeew2S2cKS+H4Dd+Q5xfajOIc5uyovxWjn/yvhDQkJQKBSEhISQmZnpit9ms0F/Pbx4D/zfp+D1LzqsO8CxEid5/ZLE6+/vz5YtWzCZTJw+fZpLly4tCyHmZLmUKzMyMhgaGlpw9qilpQWtVsvu3btdv1Or1WzcuJGTJ08CcPLkSTQaDevWrXNdZ/fu3Yxb5Jw+ffq9G/MPAaUK+qrhtS/Af+XD61+CgUZSU1Pp7u7GbDZLun979+7lpZdeknSsD+9yw4ixnp4eDh06xMc//nFJx2u1WoKCgiT5wCwFDQ0NpKSkCD1J4yxPrlmzRujs3VSCg4PZvHkz7e3t6HQ6SkpKhO/HcwdVVVXU1NQQHx+PTCbjzuhuAN4eiMNg9yMuLo7q6mr+duwcI5Nm1Co/ilLCsdvtHL0sznbmeq9EeWX8U5HJZMTFxVFfU0X//z0OP9viMPVUBsLaBxy2BV7Az8+PzZs3MzY2RmtrK5s2bVoWQgyWT7nS39+f1NTUObNjc6HVagGIjY2d9vvY2FjXZVqtdka2X6lUEhER4boOAHc85bBBed9/QmQWmMag7Ofw7FrCDn2V0NBQuru7Jdw7+OhHP0ppaSltbW2SjvfhPW4YMfaHP/yB7du3k5SUJOn4zs5OkpKShGzcHx8fp7u7m6ysLG+HMifO8mRSUpLQ5ckrsdlsVFdXExISgkwmu2oD8PXE8PAwRqMRlUpFtL+BtWpHH8tr/Y51KiqVCqPRyIlmR4Zha3YUCrmMloFxOocn8VfI2ZQROeftL2X8s7EqysLLOzqIrf4VWE2OBdH/fAp2fnnedgTuxm63U19fj91uJzQ0lOrqaqxWq1dikcJyma7Mysqit7d3wT5vbkWlgU2fhX1n4J9ecfQlIoOIdJKSkujs7ASbFcyGa93SNGJiYrjlllv4/e9/75GwfXiOG0aMLaZEaTQa6evrkyzkPE1jYyMJCQlCe/20tbUtm/KkE2ez/uTkJFu2bGHr1q0eXS4uEuHh4QQEBDA5OcmtUVrkMqgc1dBjdIibyclJAgIC0FkcU5Pbs6MAONHkMNYsTtUQ5O+9bWtT47+ShIAJflhwgWy1BXNAOOz5Fdz3J4hI90KkDqb2iG3dutVVsryyqV90CgoKMBqNQpcrVSoVSUlJC8qOOb3grrTG6O3tdV0WFxdHX1/ftMstFgtDQ0Nze8nJ5ZB5k6Mv8ZFyWPcpEhMTGRwcxHj+z/D0Csck5sT8m/rvu+8+Xnrppev+M+p644YQYzU1NVRVVbFnzx5JxzvXJgUFBbk5ssVjMBhob28X2lfMbDZTU1PDqlWrlk150pnJGxsbY/Pmzfj7+y/aqX85UVhYSH5+Pn29Pdwc6SixvDXgOKHY7Xa0Wi0FBQX8+qEdlH3tZt6/0rESpvTyFOWWzCjvBH4ZZ/xarXbG89RlUHGgVUXpWAKKR87Cyg/N6pi/VMzWrO8sWU5OTlJeXr5sBJlSqWTVqlXU1dVhMpm8Hc6cZGdn09XVxcTExLyun56eTlxcHAcPHnT9bnR0lNOnT7N582YANm/ejE6no7y83HWdd999F5vNNj+fvchMUIWjUqmIiorCXPF7GO+Hd5+EH62Aun/MK9Z7772X1tZWLly4MK/r+xCDG0KMvfzyy9x1112S+72cJUoRaW1tJTo6eu4luALQ1NRESEjIjH4Lkbl06RLDw8OUlJRMa9a/UQSZXC53LBrO8Cfa38SYWUHpYDh6vZ6mpibCw8PZt28fAKFKO9ZJPT09PZQ2OvrFkgImqa+vd2UfmpqaaGxspLW1lZ6eHoaHhxkfH+fChQsL9/9aQPzh4eE0NTVSEtxGiGzSFf8PG9Nhz6+Qh3hXNF5tatLf39/VQ3bhwoVl81qLiYlBo9EsuC9rKXF+Hk1dQaTX6zl37hznzp0DHE37586do729HZlMxqOPPsqTTz7JgQMHuHjxIvfffz8JCQnce++9AOTn5/O+972PBx98kLKyMk6cOMH+/fv52Mc+RkJCwoLiS0pKojx9vyNrG7sSbGaIXzOvY4ODg7n33nt9nmPLjBtiHdLKlSt54okn+OhHP7rgY/V6PYcOHeK2224TrnHbZrPx1ltvUVRUJKzQMRqNvP3225SUlCwbT662tjaqqqrYsWPHnKVfdywXXw70Pb+HmO53+GtnBL8dXENqairZ2dmkpaWhUCgwGh12F/7+/gxZ/PnaCQN+cnjx3hj8FXLsdjtdXV2uRnqz2YzRaGRsbAy73Y7dbkev16PX67FareTk5LBy5Uo0Go1bhlFOHT2I+a+PsC2si+PaAP7ldAL5BYXs27ePkpKSRd/+YpivfcXExARHjhwhLy+P9HTvlVIXgk6n4/jx49x8883CWsAMDAxQVlbGbbfdhkKh4PDhw+zatWvG9R544AF+85vfYLfb+eY3v8nzzz+PTqdj69at/OQnPyEnJ8d13aGhIfbv38+rr76KXC5nz549PPPMMwsexDCbzbz55pts376dsNBQhzdZTN68j//rX//Kl770Jerr6xf0d314j+tejLW0tLgWxUrJjNXW1jIyMiLkOpfOzk5qa2u5+eabhRUDFy5cYHJyUsjHbzYGBwc5efIkGzduJDr66tOA16sgs1qtDA4OohvoJeMvt6G0jHM8+6sMhxWgUqlITk5meHiY7x4fBoWSb+1Zy+qUCH5f1s5X/nKRjekR/PEzjtKN2Wzm9ddf5/bbb3eVqJ3+X06D4sjISJRKJTKZjPT0dFatWoXVaiUgIACNRoNGoyE8PJyoqCgUigVMOg40wh/3Qn8NdpmC1vT70K/5fxSuWOn1heUL9RFbyOtSFM6cOYOfnx9r1qzxdiizYrfbOXToEJmZmUJaFp09e5agoCAKCgoWfOz4+DiRkZGcP3+e3NxcD0Tnw914r8N2iXj11VfZvn27JCFmt9vp7OyU9GZYCpqbm0lPTxdWBIyPj9PW1iZpIbs3mJiY4MyZMxQUFMzrhOcsWZ44cQJgWQsyo9FIb28vWq2Wvr4+/P39yTDXobSMYw2OZeOHH8XPP4DS0lL+/d//neraOnQ3fQ2UAXzz61/jS5/5Jyq6HFnEdWlz72290v8LHEIDHO+348ePU1xczAsvvMDY2Bg6nQ6dTkdHRwdGo5Ho6Gji4uKIjY29euas7g34y4NgHIWQOGQffoH0VO9mwpxIMXSNjIxk5cqVnDlz5qoZW5HIz893iZ3Q0FBvhzMDmUxGRkYGLS0tpKSkCPfeTUpK4sKFC+Tn5y84tuDgYG6++WYOHDjAF7/4RQ9F6MOd3BBi7O6775Z0rE6nw2g0ClkC1Ol0jI6OuppHRaS2tpbExESh+9mcWCwWysrKiIuLW1ApaDkLMr3e0eel1WoZHh5GrVYTFxdHbm4uYWFhyA78DQBF4b0oLguxxx9/nKGhISIyV6FTBiCzGqktO8LjDeeR3f51AIpT5hZj8/H/qq6upq6ujpUrVxIZ6bDHsNvtjI2NodVqaWtr4/z582g0GuLi4oiPj3/vZG+3Q+kz8PY3ATukbIYP/xZCxXgPL8ZZPzU11dU0vm3bNuGHYUJCQkhJSaGmpoYNGxa/y9MTJCUlUVVVxfDwsHBtFDExMa4sdVTUwnsb7777bl566SWfGFsmXNcN/CMjIxw+fJi77rpL0vHOXpcFlUaWiLa2NpKSkoT9QB4ZGaG7u5u8vPn3OXgL5+SkcxJMyrfQ5dLUb7Va6ejo4Pjx4xw6dIjBwUGSk5O59dZb2bFjB7m5uajVamR2myO7BJB3+4yMlizCsRw9yDBAVmYGQ2MTdI05PLFWJ2vm/PvX8v9y+pdd6ZAuk8kICwsjJyeH7du3c+utt5Kamsrw8DCHDx/m2LFjtLe3YxkfcqyYwQ5rPwkPvHpdCDEnhYWFBAYGUlFRIfTrzElOTg59fX3C7ktUKpWLWkHkSeRyOQkJCXR1dUk6/s477+TkyZNz7uL0IRbXtRh74403JDe9Osf34+PjPRDZ4jCbzXR0dJCWlubtUOakurqa9PR0Ie1ArqS+vp7h4WHWr18vuZdIdEHm3H7w5ptvUl9fT1xcHLfeeiubNm0iLS1tZsmv+xxMDECAGlK3zMhoTQY6yriqyX5kMhma9FUgkxETrCAqZO5VUVfz/4L3/MvCw+fOroFjn2NqaiobN27ktttuIyEhgcbGRt46epqGDd/FdMt34c4fgUKMLyvu2jUpl8tZt24dY2Nj1NbWujlK96NSqcjIyKC6unrO94TVauXrX/866enpqFQqMjMz+fa3vz3t+na7nW984xvEx8ejUqnYvXu326Y109LS6OrqEtKKIz4+nt7eXkmfJ4mJiaxZs4bXX3/dA5H5cDfXtRhbTIlSr9czOTkpZLNsV1cXISEhaDQab4cyKwMDAwwNDQntfeaku7ubhoYGNm7cuOh9kyIKMp1Ox5kzZzh48CDj4+Ns2LCBm266iaysrKvf36bLfkoZO0DhNyOjZQh0lA8DDZf7vTSJAKSEXD2reDX/r6n+ZQsxB/Y3j5Fpa2bXrl1s3LgRnV8sbw4lU3bmjBAZGXcv/fb392fjxo00NzdLzposJdnZ2YyMjNDf3z/r5d/73vf46U9/yrPPPktNTQ3f+973+P73v8+Pf/xj13W+//3v88wzz/Czn/2M06dPExwczG233YbBsDCH+tkICwtDo9HQ0dGx6NtyN5GRkZhMJkZHRyUdf/fdd3PgwAE3R+XDE1y3YsxisfD6669LLlFqtVqio6NRKsVrq2traxM2K+Y88VzzZC8AY2NjVFZWUlxc7Lado6IIMr1ez9mzZzl+/DiBgYHcfPPNbNiwgaioqPmVYZvedfw38yZgekbLDhgCHf01TjE27ufIZOXGXr2xfLr/V5PL0uJK/7J5ZyhHu+GF98HvP46s6V0iIyNZv349N998M8HBwZw4cYIzZ854bV+iu4WYk9DQUNauXUtlZSUjIyNuuU1P4efnR05OzpzZsdLSUu655x7uuOMO0tLS+NCHPsStt95KWVkZ4HgMn376aZ544gnuueceVq1axYsvvkh3dzd//etf3RJjWloabW1tQnyBmopCoZi2/3Kh3HXXXbz55psuCxof4nLdirETJ07g5+cnuXFUq9XOvcLCi4yNjTE6OkpiYqK3Q5kVrVbLxMQEmZmZ3g7lqthsNioqKkhNTV2wIeO18KYgMxgMnD9/nkOHDqFQKLj55ptZuXLlwsrF5knoPOv4d/p2YHpGyypTojIM4GcaI8Ckw263M+6vAWD7qms/7yUlJTz11FMUFRWh0+lobW1Fp9NRXFzMU089NX//L107vPB+GKiHkFhQJ7suCgoKorCwkJtvvhl/f38OHTrEuXPn5iyPegJPCTEncXFxZGZmUllZKbxDf3p6OkajcdZMXklJCQcPHnR5Yp0/f57jx4/z/ve/H3DYE2m1Wnbv3u06Rq1Ws3HjRk6ePOmW+OLj45mYmJCcgfIksbGx9PT0SDp2zZo1aDQaDh8+7N6gfLgd8dI+buLAgQPceeedknqAnA3E69at80Bki6Ozs5PY2FghG/edS7Vzc3OFzChOpampCYvFQn5+vkduf6mnLM1mM42NjTQ1NRETE8POnTul2wl0nnU4fofGQ0QG8F5G6/HHH6e1oZa4MR0qlYqJyUl6evuwFzia5PPj55dhLCkpYdOmTa5JtvDwcAoLC+f/ftW1wwt3wEg7hKc5GvU1KTOuplKpWL16NZmZmdTU1HDw4EHS09PJzs72qImzp4WYk5ycHHp6emhoaBDaT0qhUJCXl0dtbS0JCQnTnucvf/nLjI6OkpeXh0KhwGq18p3vfMe1S9iZFbpyqn0xGaMrUSqVxMfH09nZ6bYsubuIjY11fZFYqIGuTCbjrrvu4sCBA9x2220eitCHO7huM2Ovvvqq5BJlb28varVaOOdop+9ZcnLyta/sBbq6urDZbEIaKE5ldHSUuro6ioqKPDopu1QZsu7ubt58802am5uJjY1l3bp1i/N16jjl+G/K5mk7G+fKaBWs3wZyJSo/BUnh83/PyOVyVq5cyfbt21m5cqYRq81m4+LFizPXJY10wW/vcgixiEz45D9mFWJTCQkJYf369WzZsgWdTse7775Ld3f3vGNdCEslxMAhcoqLi2loaBC+XJmcnIxMJqO9vX3a7//3f/+X3/3ud7z88stUVFTw29/+lqeeeorf/va3SxpfUlISnZ2dwpUqAwICiIiImLGkfL7cfffdvPrqq8LdLx/TETt9IZGOjg6am5u56aabJB0vaolyeHgYs9lMTEyMt0OZgd1up6mpiaysLK+7m18Nm81GZWUl6enpS+Ir5MkMmclk4t1332VsbIzXX3+d06dPExAQQH5+Pvv375e+7qerwvHfpJmZ4ZKSEjZu3Eh1dbUro6WVR/Hg/1SQHhWMXO6e+1ZaWupq6DYaja779ehnHmDDha/BcOt7GbGw+ZeZw8PDKSkpobOzk3PnztHd3c2qVavcliVbSiHmRKPRkJmZSUVFBTt27BD2/SeXy8nKyqKpqYnU1FTX++CLX/wiX/7yl/nYxz4GONbXtbW18d3vfpcHHnjA9Vnc29s7bbq9t7fXre7+0dHR2O12BgYGhBvccmYBpfQKb9++nd7eXtfnsw8xEfNdu0iOHDnC2rVrJZmNWq1W+vr6hBRjHR0dJCQkCOl7NjQ0xMTEhLBZOyeNjY1YLJYl9T/zRIZMq9Xy5ptvUl1dzQ9+8ANaW1tJS0tDo9FQWVnJ448/TmlpqbQbd4qxxLWzXvzZ31Xy0N/7mIhw7JFsGZwAICPaPa7wTnPZiooKNBrNtPv1ha/+G70BaRCW5BBi6oX3TspkMpKTk7npppuwWq1uy5J5Q4g5cZYoRd9FmJSUhNFonDZZOTExMUNAKhQKVyY0PT2duLg4Dh486LrcaX7rTtNruVxOYmIinZ2dbrtNdxEXF0d/fz8Wi2XBxwYFBbFx40Zf35jgXJdi7PDhw+zcuVPSsQMDA/j7+wvnGm+z2eju7iYpKcnbocyK89uuyL1io6Oj1NfXe7w8ORvuEmRms5mKigrKy8s5deoUzz//PDExMYSEhKBQKAgJCSEzM5Ph4WGee+65hTd26/tBrwVkELti1qu0D03QM2IgQOn4+Gi7LMbSIqeLMWcPITh85+YTy5Xmslfer4EhHY8d8cf2/965ZmnyWgQGBrJhwwYKCws5d+4cZ8+elew15U0hBg4hUVRURGNjo9DlSoVCQVpaGs3Nza7f3XXXXXznO9/htddeo7W1lVdeeYUf/vCHfOADHwAc4vnRRx/lySef5MCBA1y8eJH777+fhIQE7r33XrfGl5SURHd3N1ar1a23u1hCQ0NRqVRz2oNci507d/rEmOD4xNgVaLVaYmNjhVtp09fXh0KhcK2HEYmJiQl6e3slmesuFUtdnpyNxQqy0dFRDh8+jNFoJCEhgddff/2aa4WqqqoWFmTf5euHp0HA7IJCO+rwdkrQOPrD2occYiwl8r2JzdLSUvbu3ctnPvMZAD7zmc+wd+/ea2brZl+XZGdHRC8KGZfvVw1Vbe5xFb8yS3b48GF0Ot2CbsPbQszJ1HKlyNOVaWlp9Pf3u+xGfvzjH/OhD32If/7nfyY/P5/HH3+cz3zmM3z72992HfOlL32JRx55hIceeoj169ej1+t54403rr6fVAIajYaAgADJ/VmeJC4uTvLAglOM+frGxOW6E2MdHR20trayZcsWSccPDAwI2ZPV2dlJUlKScCIRHKPnsbGxQrvte6M8ORtSBVlPTw/Hjh0jOTmZTZs2MTY2Jmmt0DXpu+zqHlMw68UGsxXdhBmAuDDHibBr2GEX4Wzen1pmdE6mqdXqeZVPZ1uXdG9MF4+n1/HljGpUqkBp9+saOLNkaWlpHD9+fN5mqqIIMSfLoVypUqlISEigpaUFcGR9nn76adra2picnKSpqYknn3xyWh+fTCbjW9/6FlqtFoPBwDvvvENOTo7bY3OKcxENYGNiYiSvNtq0aRP9/f00NTW5OSof7uK6E2OL6RczGAzo9Xrhsk9Wq5Xe3l63+2G5A4vFQltbGxkZGd4OZU7Gxsa8Vp6cjYUIMrvdTl1dHeXl5RQVFZGXl4dMJnPbWqEZDF3+sI6avdG3f8xhHumvlBOmUmK32+nSXRZjmqAZZcbg4GDXfZ5P+fTK+7U2bIhPJjlKWhfHNExOGqTdr3kgk8nIyclh3bp1nDt3jpqamms+NyIJMZherhTRM8tJRkYG7e3tmM1mb4cyg4SEBPr6+iT1Z3mSiIgIJicnmZiYWPCxvr4x8bnuxNihQ4cklygHBwdRq9Ue9R+SwuDgIEqlUjj/G3DYWahUKuEE7FRqampITk72WnlyNuYjyCwWC2fPnqWtrY1t27ZNE+OeWCsEwOBlMRYxu3nrgN4hxqJDApDJZAxPmDFaHMIqVh0wR5nRwXzKp1PvV6z/BI+n1yKXwRv9cRzoi5d+vxZAXFwc27Zto7Ozk7KysllPyiIKMScajYbU1FRXv56IhIeHExoaKmQGKiQkZFH9WZ5CqVSi0WgkZ8d27drFoUOH3ByVD3dx3YmxxTbviygqnFYbIpYonVN8IsYGjinPvr4+j5Q0FsvVBJnBYOD48eMYjUZ27NgxQ4i7fa2Qk5HLk2Ths3vFDU84Gtwjgh1fWHov949FBPsToFTMWmacyrXKp877FRup5gtJ5whRWqjRh/JfNXE0NTVLv18LJCwsjB07dmCxWDh69Oi0DKTIQsxJTk4Og4ODkk/cS0FqaqqQK4icXxrcZSjrTqKioiQ/p76+MbG5rsRYe3s7bW1ti+oXi4qKcnNUi8OZ5RDRamNkZISxsTFhJzztdjs1NTVkZGQIZ+DrZDZBNjk5yfHjxwkNDaWkpGTOHZ9uWyvkxG6H0cu9UmGzP6eBfgrWp4VTmOBoA+i7XLaMCXXE6I7yaUlJCX/4RDr54RaGjHI+eyiYgeFR6fdLIv7+/mzevJmIiAiOHz/O+Pj4shBi4DAKzcrKmnMfpJOuri727t1LZGQkKpWKlStXcvbsWdfldrudb3zjG8THx6NSqdi9ezcNDQ1uiTExMZGJiYkFD0wsBXFxcfT29gonXKKiohgcHJR07KZNmxgYGKCxsdHNUflwB+L6EEjgeuwXGx0dxWQyCScSwbGwPCEhQcjVTAD9/f2MjIxI3k+6VEw1hjWbzQwODhIdHc3q1auvmXFc9FqhqZj0jh+A0NnFf0lmFCWZ770Wh8YdYiwyxJEpc5YZKysrZ+wndX6xKC4uvnqZcaiFuB6Hp9TIzU/xrfdnL+5+LQK5XM7q1au5ePEix48fJyYmhr6+PqGFmJPMzEzXXsepZqlOhoeH2bJlC7t27eIf//gH0dHRNDQ0TBPK3//+93nmmWf47W9/S3p6Ol//+te57bbbqK6uXvQko1KpJCkpiba2No/0AC6GiIgIbDYbw8PDQrU3TO0bW+jAlEqlYtOmTRw+fJjs7GwPRehDKtdVZmyxJUoR+8W0Wi0xMTFCNJ5PxWq10tnZKezqI2cGIycnR1ixOJXg4GCKi4vp7OxEqVSyatWqeZd+r7VWaN5MXP7GrVTNaWtxJYN6Z9kywBXL1PLp+Pg4AOPj4/Mvn0akw0OH4PanSN/96cXfr0Uik8lYsWIFgYGBtLe3U1RUJLwQA4fYycnJmXMQ4Xvf+x7Jycm88MILbNiwgfT0dG699VaXiLbb7Tz99NM88cQT3HPPPaxatYoXX3yR7u5u/vrXv7olxtTUVDo7O4Vr5JfL5W7dfekuFts35vMbE5frSowtxpF5cHBQyOyTqCXK7u5u1840Eenq6sJoNArtfTaVyclJKisrSUxMxGQyUVVVtfQlEqcYC5r/czoy6TiJhge9J3inlk+dBqQjIyMLKzPGFsKGB+cfuwdxlrsnJydJSUnh3LlzkibavEFaWhpWq3XGPkiAAwcOsG7dOj784Q8TExNDUVERv/jFL1yXO7Nqu3fvdv1OrVazceNGTp486Zb4NBoNISEh87YSWUqcpUrRWEzfWElJCadPn3ZzRD7cwXUjxsbHx6mpqWHt2tlXuFwLEZv3JycnGRkZITY21tuhzKCtrU3Yxn2bzUZNTQ15eXnCZRRnw2g0cuLECaKjoykuLmbr1q0eXy4+eyBjjv8Gzj21+8O369nwnXd47pCj78QpxsICp2cfS0pKeOmll/j5z38OwM9//nP+53/+5+pCrO4f761iEoSpPWJbt25lzZo1xMXFceLEiTn74kRCLpeTn59PXV3dDFf55uZmfvrTn5Kdnc2bb77JZz/7Wf7lX/7FtaDbmRW68vPH3RkjZyO/aMTExDA2NubK7orCYvrGiouLaWpqErJP70bnuhFj58+fJzIyUlIzuaj9Yn19fS5HaJEwGAwMDQ2RmLjwvYBLQWtrK3K5XPg9meAo95aVlaFWq109Yp7YZTkvTJdPOn5z96KMTJjoGzMyaXKc2PUGh+1DaODM9lO5XE5BgcM8tqCg4OplRn0fvPIw/PJmaDkm8Q64l9ma9WUyGStXriQiIoKysjLh1ubMRmJiIn5+fi6TVSc2m43i4mL+4z/+g6KiIh566CEefPBBfvazny15fCMjI8JlG/38/IiMjBQuO7YYv7Ho6GiSk5OpqBDrS4+P60iMlZeXs3btWkmZmqGhIcLCwoTrFxsYGCA6OtrbYcygt7cXjUbj9lUk7sBisVBfX09+fr7Xeozmi91u58KFC1itVoqKiqa9dr0iyMyXMz1+c0+eWmyOOBRyR6zjJocYCw5Y5CzQW0+AQefYh5nivuXPUrna1KRMJmPNmjXIZDLOnTsn3MTdlchkMgoKCqivr5/WmxUfH+8Sy07y8/NdJU1ne8SVYqS3t9etrRP+/v5ERkYK158FDvEiNQvlKZyek0NDQ5KOX7t2rU+MCYjYZ6sF4BRjUtDpdGg0GvcGtEjsdruQVhsgbh8bOMqnKpVq1ukx0Whubqa3t5eNGzfOumB9yQWZ/bIrvnzu0q4zAvll4ThxOUOm8ltEObj1OFz4IyCDu54GhXeHvOdjX6FQKNiwYcOysQqIiYkhLCxsWnZsy5Yt1NXVTbtefX29aygnPT2duLg4Dh486Lp8dHR0Ub25cyF6f5Zogluj0UguNa5du5by8nL3BuRj0fjEGI7mYtHc7ScmJjCZTMKNfFutVvr7+4UUY3a7nebmZjIzM4XsZZtKX18fNTU1bNiw4aoeaEsqyGyXS26yuYXVe6u7HXE43fcDpYoxmxX+8a+Of6/7JCRKew/bbDYuXrzI0aNHuXjxouRF2QvxEQsMDGTjxo3U1dUJmdWZikwmc1ldOB+bz3/+85w6dYr/+I//oLGxkZdffpnnn3+effv2uY559NFHefLJJzlw4AAXL17k/vvvJyEhgXvvvdet8cXGxjIwMCDcVKVGo8FqtTI2NubtUKah0WhcwzELxSfGxOS6EGMTExNUV1dLEmN2u13IzNjAwADh4eGzZky8SX9/PwEBAYSGhno7lBlotVpsNpuQOzynotfrOXv2LKtWrZrXNOqSCTL55deafe4+KOXl8qTtcrnSdFmM+SslfpRU/g/0XnIMDex6QtJNlJaWsnfvXu6//34efvhh7r//fvbu3XvVheSzIcXQVaPRUFRURHl5uXAn7CuJi4tDLpfT09MDwPr163nllVf4/e9/z4oVK/j2t7/N008/zX333ec65ktf+hKPPPIIDz30EOvXr0ev1/PGG2+4vUUhJCSEoKAg4VYQyeVyIiIihNtk4MyMSfksWLt2LQ0NDZLFnA/PcF2IsQsXLhARESGpYXtychKz2SxcZkzE6U4QezVTc3Mz6enpQveKORv2U1JSSElJmfdxSyLIFJcnIq1zZyeUCsdja7I6/r71sihzirQFYRqHQ991/HvHlyF44a/30tJSHn/8cSoqKtBoNKSlpaHRaKisrOTxxx+ftyBbjLN+YmIiGRkZnD59Wrjl0lORyWSkp6fT3Nzs+t2dd97JxYsXMRgM1NTU8OCDD8445lvf+hZarRaDwcA777zjsdViIq8gEq1vLDQ0FJvNJmnSMyYmhqSkJCorKz0QmQ+piHvWWgCLad7X6XSEhoYKZYEgar+YyKuZRkdHGRoaEtaE1kltbS0KhWJG4/R88LggU17OdpjnntKKVweSHx9G1GXHfacYk0sRY3I/2PYFSFwH6z+94MNtNhvPPvssQ0NDZGVlERISgkKhICQkhMzMTIaHh3nuueeuWbJ0x4qjvLw8AgICqKmpWfCxS0lqaiojIyNz7gb1JiKvIBKtb0wulxMWFraovjFfE79YXFdiTAoi9ouNj49jMpmEM1TV6XRYrVYhM3YtLS0kJSUJZwMylaGhIVpaWigqKpKcvfOoIAu4XHo2jM55lf+3LYN/fG4b/29bBvBeQ78klP6w8SH4f++AcuHPW1VVFTU1NcTHx8/4IuZc9lxdXU1VVdWct+GuXZMymYyioiLa2tqEy6JMxc/Pj+Tk5Bk2FyLg/LyTOiXoKXx9Yz6WghtejInYLzY4OEh4eLhQ2TpwlChjY2OFKwNaLBahVzOBozxZWVlJTk6OpN2pU/GYIHOavRrm/wF/uWq5uBgklryHh4cxGo1zDkCoVCqMRuOcWSB3L/0OCQlx7eUUuVyZlpZGd3e3cM3yMplMyBVEoveNScEnxsRDrLOqBCwWCzU1NaxevXrBx9rtdkZGRoQUY6JlxUBcS4uuri6CgoKEmzydSm1tLUqlkqysLLfcnkcEWfBlT7vJofcmK6+B4rKQcpYr54V5En57F5z/I1ili5bw8HACAgLmdMKfnJwkICBg1teFu4WYk4yMjAWXK//zP//TNbnoxGAwsG/fPiIjIwkJCWHPnj1us35Qq9WEhobS2dnplttzJ6L2jUVGRgqXsVOr1ZKb+FevXk19fT0Gg8EDkfmQwrIXY62trYDj295CMRgMGI3GRWcq3I2IAnFiYoKxsTFiYmK8HcoM2traSE1NFXKoANxTnpwNtwuyoEhA5vAbG589C3CmdYib/usw//Qrx347v8upMbN1AVYS534HLUfh3ScXFW5hYSH5+flotdoZ993Z31hQUEBhYeGMyzwhxGB6uXI+mZQzZ87w85//nFWrVk37/ec//3leffVV/vSnP3HkyBG6u7v54Ac/6LY4RV5BNDExgV6v93Yo01hMFspThIWFSW7iT0hIICgoiKamJg9E5kMKy16M1dfXk5WVJamk52zeF8k+wtmbIJoY02q1REZGCrelYHR0lJGREUlrsJYCu93OuXPn3FKenA23CjKFEkIu7yEcnX1xs1wGzf3jtA46TgBOMeb0G7smNhuc/Inj35v3LcrgVS6Xs3//fsLDw2lqakKv12O1WtHr9TQ1NREeHs6+ffumCWBPCjEnznLluXPnrjo8oNfrue+++/jFL34xLXs3MjLCr371K374wx9y0003sXbtWl544QVKS0s5deqUW2JMTExEr9cLJzCUSiVRUVHCZcfUajXj4+NClXblcjmhoaGS+sZkMhk5OTnU19d7IDIfUrguxJjUUWu9Xi+cX9bIyAh+fn5XNQL1BqKWKDs7O4mPjxdOJDppb2/HarW6rTw5G24VZOFpjv8Ot856cWSwo9F+YMyE3W5H5ef4CNH2D1FdXc3Jkyc5dOgQBw8e5K233nK5tx85coRDhw5R/fdnYagJm18I47kfWHQ2r6SkhKeeeoqioiJ0Oh2tra3odDqKi4t56qmnpi0mXwoh5iQ9PR2ZTHbV7NO+ffu444472L1797Tfl5eXYzabp/0+Ly+PlJQUTp486Zb4/Pz8SExM9JUq50lgYCCBgYHCeXOFhoZKziL6xJhYiJMSkshixZgnP5Cl4JzuFKnkZrFYGBgYmFFKEQGtVktubq63w5gVq9VKXV3dtZdkuwGnIDtx4gQAK1askPYaCk+DjlMwNHv5IirE4UU2abZy8GgpI0M6AFq7etgQFU1sbCxBQUHI5XIUCgU2m43S0lLXYxD62tMAdMfsouLYaZRKJRqNBrVaTVRUFNHR0Qt+rEpKSti0aRNVVVUMDw8THh5OYWHhkmfEpiKXy8nPz+fChQskJyfPyL7/4Q9/oKKigjNnzsw4VqvV4u/vPyM77u7m9ri4OKqqqigsLBTq8yYuLo6LFy9iNpvx8/PzdjgunNOLIlkOhYSE+MTYdcJ1IcY+9rGPSTp2fHxcOJsGEac7R0ZG8Pf3Jzg42NuhTGN8fBy9Xi9kHxs47Db8/f1JTExckr/nFkEWffmLTf/0nYVjY2O0t7fT0dGBSgmTFlCERpIS7095fx8JyekUFWXPuDlnWSc6Oho/wyB0HgMg6d6vEx+RxejoKDqdjpGREdfS7aSkJFJSUhZU1pXL5axcuXLWy5ZaiDmJj4+nsbGRpqamaV8YOjo6+NznPsfbb7/tdif7hRAdHc3k5KRwFQKVSkVgYCA6nY7o6Ghvh+NCxL6xkJAQyQI9JyeHQ4cOuTkiH1K54cuUomXGRBRjOp1OuGwdODIIUVFRQn17dmI2m6mvryc/P39JH7dFlyyj8x3/7avBbrfT19fHyZMnOXz4MJOTkxQXF5Ma5Thxy4IjiNY43j+jhnn00pz/g2PVUvJGiM5FoVAQHh5Oeno6a9as4dZbb6W4uBij0cjRo0c5ceLEok1AvSXEwNGXU1BQQGNjIyaTyfX78vJy+vr6KC4uRqlUolQqOXLkCM888wxKpZLY2FhMJtOME39vb69bWwWUSiXR0dHClQRBTOHjnF4UCWdmTMp7xJcZE4tlnRmbmJigo6NDkhgzm80YjUahxJizeV80E1oRpzvBIcbi4+O9HcasNDY2olarvZK1W1SGLG4FAPb+Wo69+zbjJivp6ekUFxe7DHWTwtup1Y7RMTyJWuUQwrqJeYix2ELIugUK7pn1YplMRkxMDDExMRiNRlpbW6moqCAgIIDCwkJiY2Pndx8u400h5iQqKoqIiAjq6+tZscLx2N58881cvHhx2vU++clPkpeXx7/+67+SnJyMn58fBw8eZM+ePQDU1dXR3t7O5s2b3RpfXFwcHR0dZGfPzGp6E7VaLVx/lkajQa/XC1U+DQ4OxmKxYDKZFmx4nZ2dTV9fn5AJgBuRZS3GmpqaCA0NXfCHNDiyYv7+/kI1fo+OjqJUKgkKCvJ2KNPQ6XTCiR6z2czg4CBFRUXeDmUGBoOBpqYmSkpKvJZNlCrIzEFx4K/Bz6QjI3icuB13zeh3yo0LoVs3SbC/wrWTcnjCNNvNTSf7FsfPPAgICCA3N5esrCza2to4e/YsCQkJrFixYl4nQhGEmJOCggKOHTtGZmYmKpWK0NBQlzBzEhwcTGRkpOv3n/70p3nssceIiIggLCyMRx55hM2bN7Np0ya3xhYbG8uFCxcwGo1Cba/QaDR0dHR4O4xpBAYGEhAQwOjoqDDtLUqlksDAQPR6/YKfv/DwcKKjo2loaGD9+vUeitDHfFnWZUpniVLKCW98fFy4HqixsTHCwsKEKgdaLBYhrTZ6e3sJDQ0VTriCw/suMjLS68a9Cy1Z9vf3c+jwYcbCHJnmJFvXrLYvX7wtj9c/t40PFicREez4MjOgn4cYk4BCoSAjI4Ndu3YxOTnJu+++S19f31WPEUmIAa4M6dQF3dfiRz/6EXfeeSd79uxh+/btxMXF8Ze//MXtsalUKtRqtdsMZd2FRqMRzkoCHM+laGuRfE381wfXhRiTgoj9YiLGNDo6ir+/v1cbjWfD3f0z7sJqtdLa2kpmZqa3QwHmJ8jMZjPnz5/n9OnTZGdnE77mTscFbSeuefvRoY5v4/1jxqteT3b+9zAs3WQ0KCiIzZs3k5uby5kzZzh37tysJ2rRhJiTjIwM2tra5lyTdPjwYZ5++mnX/wcGBvLcc88xNDTE+Pg4f/nLXzz2ehfRSiIgIACVSiVcj1ZwcLBwhrQhISGSjF/BJ8ZEYlmLscbGRsn+TSIKHxFjcvYTiJSts9lswoqxrq4u/Pz8hJoCu5og0+l0HD58GL1ez65duxz+WGlbHRe2nrjquiKL1UZUiCMz1j9mxDbHSqRA0yDKvz8Cz6yBSZ3k+yGTyUhLS2PXrl1MTExw6NChaXsnRRVi4Fino1KphPX16uvrw2qd3wqspULEvrHFZKE8xWIEYnZ2Ng0NDW6OyIcUlrUY6+rqkuy8LqLwEbF0KmJz5+DgIHK5XLi4wGFnkZGRIZR4hdkF2eDgICdOnCA1NZWSkpL3XnsJa0AVDsYR6JzpgwVw3y9PUfDNNxkYMyGTgclqY3B89lJl7OgFxz8S14FKs+j74sySZWRkUFpaSn9/v9BCDBxCMiMjg5aWFvctdncTYWFh+Pv7X1eLsD2FiGJsMTElJibS3d3t5oh8SGFZi7Hu7m7JjeUTExNC9RvZ7XYhBaLThFYk+vr6iI2NFU7wjIyMMDY2JuxqpqmCrKysjJMnT1JYWDiz71KugMybHP9ueHPW25Ihw2SxUdc7Rmyoo4TdpZt9YXf0WJXjH1m7Z71cCjKZjKysLFauXMnp06cpKysTVog5SUxMZGJiYlo2TwRkMhmxsbFC9o2JKMYmJiauuuZqqQkODmZiYkKSyI+Pj/eJMUFY1mKsp6eHhISEBR9ntVoxm81CrRyanJzEZrMJlRkTdU+mTqfzenP8bLS1tZGQkCDM2PtsBAcHk5eX59o1mpqaOvsVc293/Lf6AMzyIV+Y6DBkvdg1QlK4433UOTwx83bsdqL0NY5/p29fdPxXkpyc7PLKys3NvaoQ++53v8v69esJDQ0lJiaGe++9l7q66ea2BoOBffv2ERkZSUhICHv27HGbSFEqlSQlJQm5oDsiIkI44SNiE79KpUImkzExMctr3UsEBgZitVrn7Ee8GgkJCfT09HggKh8LZdmKMZPJxMDAgKTMmMFgQCaTCWVrodfrCQ4O9vjanIUg4p5Mu90uZOnUZrPR2dk5t7gRhKGhIS5cuMCKFSsYGxube8oy5zZQBDjWIvVWzbh4dZIGgPMdOlIiHBnmtsFZTlCDDQRYxrArVZC41p13xVWa1Ol0rFixgkuXLl211HbkyBH27dvHqVOnePvttzGbzdx6663Tmp8///nP8+qrr/KnP/2JI0eO0N3dzQc/+EG3xZyamkpXV5dw/VkajYbR0VGhMj4BAQHC7YOUyWTCNfErlUoUCgUGg2HBx8bHx6PX64W6Pzcq4pz5F0hvb6/LJHKhGAwGAgIChCpzidgv5jR7Fe1xstlsQq1vARgYGEChUAiZsXMyOjrKqVOnKCwsJDMz8+pTlgGh73mCXfjDjNsqStEAUKsdI17jKFO2Dsyc6JJ1nQXAnlAESvd9+bmyRywzM9NVspzr5P3GG2/wiU98gsLCQlavXs1vfvMb2tvbKS8vBxyv91/96lf88Ic/5KabbmLt2rW88MILlJaWcurUKbfErVarCQgIoL+/3y235y6cGUXRTsqiliqlTi96AplMRmBgoCQxFh4eTkBAgC87JgDLVox1d3cTExMzqw/StTAYDMJZNYjYL+ZcgyQSOp2OsLAwoTKI4NgGEBcXJ5RwnYrNZqOiooLU1FTS09OBedherP64478X/nfGVGW8WkW8OhCrzY4Mx31unlWMOYSO3Y1Zsbma9VNTU8nMzKS8vHxemSenaHMK6PLycsxmM7t3v9fblpeXR0pKCidPnnRL7DKZTEgrCZlMJuS6H+dybpEQLTMGSBZjztejr2/M+4h1RlsAPT09kpv3RRRjk5OTQpUDQcw1SCLGZLfbhbXacNLQ0IDNZiMvL2/a768qyLJvhaAo0PdC/T9m3OaGdIeIGbo8RdnYN3NHnm37lziZ8QVsqz7ulvtxranJnJwc5HL5jF6wK7HZbDz66KNs2bLF5Xqv1Wrx9/ef8fqKjY11q3hyijHRpipFzEKJGFNQUBCTk7MPq3iLgIAASWIMHKVKX2bM+yxrMSaleR/AaDQKJ8ZEFIiiTZyCmNm6sbExjEYjUVFR3g5lVkZGRmhoaKC4uBiFQjHj8jkFmdIfiv/J8e+yX8w4bmduNO8rjGNLViRyGYxMmmeav4bE0qdeDVHSzJmnMh/7CrlcTnFxMc3NzVedWty3bx+XLl3iD3+YWYL1NJGRkVitVuFEhsjCRyThuhjh4ymkZsbA18QvCstWjC3G1sLZMyYSoglE58SpSDGJ2rzf09NDdHT0rELH29hsNiorK8nMzLzq4zanIFv7SZDJoeUIaC9NO+YDRUn87J/WcseqBNKiHP2ONVrPrIpZiI9YWFgY2dnZVFZWzlqu3L9/P3//+985dOjQNBuSuLg4TCbTDEHi7qynXC53e7bNHajVauGa+BczKegpFiN8PEVgYCBG49W3YMyFz95CDJatGLueypR2u104gWg0GpHJZELF5GzeDwsL83Yo0xC5RFlfX4/dbic3N/ea151VkIWnQsG9jiuc+O85j82Pdzwn1d2j7/2y5zzyI/9JjNP0VSJSDF2zs7NnlCvtdjv79+/nlVde4d1333X1zjlZu3Ytfn5+HDx40PW7uro62tvb2bx586Luw5WI2DfmHIoRqR9qMZOCnsIpfETK1i1GIPrKlGLgE2MCYDabsdlsQsUk4sTpyMgIoaGhQjXvm0wmhoeHiY2N9XYoMxgdHaWxsZGioqJ5P2azCrIt/+K48NKfYbBpxjGtA+OEBjgGaS51T2m2bitFcfwpUgePSL4PUp31p5YrnZmuffv28dJLL/Hyyy8TGhqKVqtFq9W6+n/UajWf/vSneeyxxzh06BDl5eV88pOfZPPmzWzatEnyfZiN2NhYRkdHhRIZIjbxO78QivQ4Ob+gSs1EeQJfz9jyR5yz2gIZGhoiMjJS0rGilQQNBgMKhUIos1DRMnUg5momnU5HUFCQUK8nJ/X19aSkpCz4MZshyOLXQM77wG6Fw/857brHGwbY+dRh3q52GKNe7JwixnQdAEz4R2Gz2bh48SJHjx7l4sWL8yqFLXbFUVhYGOnp6a7s2E9/+lNGRkbYuXMn8fHxrp8//vGPrmN+9KMfceedd7Jnzx62b99OXFwcf/nLXxb0d+eDn58fISEhQgkfEHN6UbSyoEKhwN/fX6iYFvMYRUZGMjQ05OaIfCyUhftCCMLY2Jgkrym73Y7JZBLK8FW0TB04YhJtulOv1wvXJL9UAwU2m42qqiqGh4cJDw+nsLDwqtmuiYkJenp6uOmmmyT9PacgO3HiBAArdn4ZWf0bcPFPUPIIxK8CYF1aOCo/hWsvZfvQBEPjJiKC/WHUsRR70i+CBx98kIsXL2I0GgkICCA/P5/9+/dTUlIy6993167JjIwM3nnnHcbGxuZVVgoMDOS5557jueeek/T3FoKzYV6kEndoaKhwWZLF9EN5CtGydf7+/litVqxW64J7V0NDQxkb80yvp4/5s2wzY3q9XpIYczb0SvEn8xSiZepAzMyYiKJ1Kaw2SktL2bt3L/fffz8PP/ww999/P3v37qW0tBRg1qxTU1MT8fHxizISnpYhG1RiX7EHsMNbX3OtSAr0U7A9xyGQNUGOzG5l++UpRr3D2NTgp+H8+fNoNBrS0tLQaDRUVlby+OOPu+7DVNy59FulUpGYmEhzc7Pk2/AUvizU/BBN+IB4j5PzfCZls0NoaKhQfYI3KstWjI2NjUn6kHZO5YgkxkQUPqIKRNFi8nTptLS0lMcff5yKiopZxczPf/7zGULtgQceoKWlhYyMjEX//amCrC7pY9gVAdByFKr/6rrO+1c4ejetVodAO9vmEGP2cYcYMyrDyMjIICQkBIVCQUhICJmZmQwPD/Pcc89NK1m6U4g5yczMpKOjQ6gdh4Bw/VngEz7zRbRsnTMbJmXqNCQkxJcZE4BlK8akZsYsFgtyuVyoJnCz2SxU2RTEEz52u104gWgymZiYmPCYGLPZbDz77LMMDQ2RlZU1Q8x0dXXxxBNPzBBqFouF/v5+ampq3BKHU5C1j0Jfzv/n+OU/vgwGR1bn5vwY/JVyxoyOE0FZi6P/xKIfBMCsDJ4xCOJ0/q6urubixYtcvHiRI0eOcOTIEbcKMXCInpCQEOHG99VqNQaDQSihERgYiMlkEs7eQqTHCBw9fyKJe5lMhlKplCTGQkNDmZiYEG5f6o2GOIpkAZhMJkwmk2QxJlJWDMSMSTQxZjKZsNvtQsU0MjKCSqXymJCuqqqipqaG+Pj4WadaDQYDY2NjxMTETBNqW7dupaysjJ/85CduO6k6BdlF9W6MwUmg18JbTwAQGujHzXnv7Yg936FjwmRBbnaUPszy2XsPVSoVw8PDfOELX+D+++/nb3/7Gx0dHfz5z3/mwoXF2WFcSUpKCu3t7W69zcUiYhO/iJOCIooxqcLHkyxGjAFC7du8EVmWYsyZUpVaphRN+FgsFuEMQ0UrnRoMBpfnkCiMjo56tHl/eHgYo9E46yDF2NgYk5OTKBSKaR/AKpWKhIQEOjs7qa6upqqqym3xBAcHs3nbLi6kPej4RcWL0PA2AB8oSgRAKZdhsdk50zpM886f8P9OpWLwC5/19rRaLf39/TQ1NXHnnXeybt06/vKXv3Ds2LE5+8mkkpiYyPDwMBMTE267TXfgNFoVBblcTkBAgFDrfkQrCcL1JcacfaW+UqV3WZZiTK/XI5fLJa3qkTJt4mmsVqtQAtFms2EymYTKQomWqQPP7xMNDw+f88RoNptdr+WplihRUVGMjIy4yrpXWwkkheDgYApuf5C2+NsBsP/1szDWy87cGP77Y2u4e7VjRdmJxgEyt+7BFLMGu1w5c2elzUZjYyMKhYJPfOIT5Ofn89prr2GxWObsJ1sMAQEBhIWFCZWFAod4Fkn4gHjiJyAgAIvFIpT4uZ7EmFKpRKVS+Zr4vcyyFGPO5n0phqSiZsZEisn5QSxaZkw0MebpmAoLC8nPz591qbRSqcRqtaJSqaaV66OiohgYGGBycpKAgADCw2fPSi2G4OBgoj76Y8aCUpCN92P/y4P4y+3csyaRHbnRAByt70cul/PQQw8B0NLSgl6vx2q1otfrqa6uxmq18vDDD5Odnc1rr73myhBN7SdzZ2ZPxIZ50YQPiNfE7+/vj0wmEyqm60mMgc/eQgSWpRjT6/WSm3tFEz4gXkzOEqVIQw4iijFPDxTI5XL2799PeHg4TU1N08RMX18fISEhMzJzTjGm1WopKCigsLDwmn9HiiFrsCYKxUdfxCoPQNZyBPvBbwGwLdshxhq0OkYP/hebbaeR28ysWrUKnU5Ha2srOp2OrKwsPvWpT7FmzZppQsyJSqVye2ZPxEXYogkfEK9HSyaTCRfTle0BIrAYMRYSEuLLjHkZcRTAApBq+AriCR8QLyaz2SxUPCCm1cbk5KTHYyopKeGpp57i2Wefpaamht7eXgICAli7di3bt2/nt7/9LU1NTcTFxaFSqYiMjOSNN94gPDycffv2XVNQl5aWum57voasToJSizDc8d8oXn0Y2YmnscfkU6bYSYBSjtViIeyYQ6ApVv6EX/ziF9TX1zM8PIxGo2FwcJDOzk7+9Kc/zXoC8URmT6PRUFNTg91uF2bNl2giA8SMyc/PTyjxI2JmbDEC0ZcZ8z5inXHnyfj4uGQzS9GED4gXk91uFyorBo7MmNT1V55iqQRiSUkJmzZtmtWBf+XKlS4x5XxfREdH88QTT1xTTDk9zIaGhoiPj3f1Lzk9zJ566qlr3kbg2o9j6r2If9lz2P+2H83WX2K0+AFKLChQYkVhN7tidfqImUwmjh07Rm1tLZmZmdPEkd1uR6vVUlxcPK/M3nwJCwvDYrEwOTkpqd/UE0xdOi2SQBTNjFYmkwlltyGiGFtMTMHBwb5pSi+z4DPu0aNHueuuu0hISEAmk/HXv/512uV6vZ79+/eTlJSESqWioKCAn/3sZ9OuYzAY2LdvH5GRkYSEhLBnzx56e3unXefAgQPk5OSQm5vL3//+92mXLabh3WazCSc0RJumFFGMiTZ44WwoXqpsnVPMbN++nZUrV7qen5KSEl566SVefPFFvvvd7+Lv788LL7xwTRF1LQ+zhTTQ+7/vSSw5dyK3mVl74mFW2xz+ZhN2h+WHwmrg9OnTMwxdP/GJT8xagm1qapp3Zm8hKBQKQkNDhSpVBgYGYrPZhPKsErEEJ5fL57XOaqlw9myKxGIeo8Xcn+eee460tDQCAwPZuHEjZWVlrsvq6urYsmULSUlJPPnkk5Ju/0ZhwZ904+PjrF69es7dbY899hhvvPEGL730EjU1NTz66KPs37+fAwcOuK7z+c9/nldffZU//elPHDlyhO7ubj74wQ+6Ljcajezbt4+f/OQnPPvss3z2s5/FZDK5Ll+soBLlG6gT0cSPzWYT7jESLSaj0YhMJhNiubtTqCUnJxMTEzOv19LVPMwW3EAvl6P88C8Z0azAzzrJi6r/IkfWwSiO7LWfdYInnniCt99+e5qhq7MEW1RUNK2frLi4eF5ZOSmo1Wqhsj5OuxaRyoKiCR9wvCZFiul6e4zkcrmkzOMf//hHHnvsMb75zW9SUVHB6tWrue222+jr6wNg//797N27l7/97W/87W9/c6tdzfXGgtNL73//+3n/+98/5+WlpaU88MAD7Ny5E4CHHnqIn//855SVlXH33XczMjLCr371K15++WXXEuMXXniB/Px8Tp06xaZNmzAajSgUCtasWeMIUqnEaDS6zDUXI8ZEewMBQpUoQLx4QDzB6szUifQ4LWSTw9U8zMDRQN/b2zvvBnqbIoDHzibweHQj+eoJfu//JMP2UJCBv0XPunXrGBwc5I477pg2fHO1Eqwn8Pf3Fy7ro1AohCrBiSZ8QMyYRItnMUgVYz/84Q958MEH+eQnPwnAz372M1577TV+/etf8+Uvf5nh4WHWrl3LqlWrSEhIECorLRpu/8QrKSnhwIEDdHV1YbfbOXToEPX19dx6660AlJeXYzab2b17t+uYvLw8UlJSOHnyJODo7fjkJz9JfHw8CQkJfPazn53WsL9YMSbSCRTEe1OL+hiJFJNo8cDCSrlX8zCDazfQXzmBefHiRSqqGvnXSzk0G8KIlI2RKtMCIDOOUFRUxC9/+Uva2tpm3NZcJVhPoFAohCsviSY0ROvPAuliwVOI9pzB0mfGTCYT5eXl087lcrmc3bt3u87l3/rWt9i9ezdBQUHI5XJuu+02SfHdCLi9a/zHP/4xDz30EElJSSiVSuRyOb/4xS/Yvn074HDd9vf3n7HPLzY2Fq1W6/r/b37zmzz66KPI5fIZk5POkpWUPgubzSZcjwY4TqSixOSMQ5R4wPH4iPS8mc1mya9BT+HsPZxPTDk5OaxcuZILFy6g0WhmNNAPDw+zevVqcnJyZtze6dOnef7556mvr3dNYIaHhzMxMYEsKIVvNGr4etYlcgMdOyrpr+KdhiGGhhw/3nzMxsfH0el0Qj1vRqOR8fFxt+3iXCyTk5OMjIwI9RgNDw8TGhoqTEzOoQtR4gHHRhCLxSIpptLSUjZu3LigYwYGBrBarcTGxk77fWxsLLW1tQDcfvvt9Pf3Mzo6SnR09ILjupHwiBg7deoUBw4cIDU1laNHj7Jv3z4SEhKmKej5MNeqGbvdzsjICK+//rrkOGf7hu5Njh496u0QZrCYx9cTVFZWUllZ6e0wpiHaYwTQ2Ng4r+vt2bOHPXv2XPU6b7zxxpzHXo0GmxHzhadYYa/DbjFx7733cu+996LT6YR4zESIYSrl5eXeDmEGoj1Gzc3NNDc3ezuMaYj2GIG0mCYmJjh37pz7g8HhpecTYtfGrWJscnKSr371q7zyyivccccdAKxatYpz587x1FNPsXv3buLi4jCZTOh0umnZsd7eXuLi4ub1d+RyOWFhYdx+++0LjrG2thar1erWkfnF8uabb7qamkWgq6uLjo4ONm3a5O1QXJSWlpKWlkZCQoK3QwEc30JPnz7NLbfc4u1QXFy6dAmlUkleXt68j5kty5Wbm8uDDz4445uyzWbjwQcf5Pz582RkZEzLptlsNkpLS5HJZGzevJn169fTmfo5ymv+l5D1e6k8c4aOjg6ef/55r/b+1dfXYzAYWLVqlddiuJKDBw9SXFzskW0JUujt7aWhoYGtW7d6OxQXZWVlxMfHk5yc7O1QAId4OXLkyFX7p5cap4deQUHBgo/dvXv3tCG6+RAVFYVCoZjhhLCQc7mP93CrGDObzZjN5hkftlMbVNeuXYufnx8HDx50fbuuq6ujvb2dzZs3z+vvOCdZpEyyOWMRYQrOiUwmm7Fj0Js44xAlHnA8b3K5XJiY/Pz8JL8GPYWUmLZu3UpJScm8GuidvWERERGzNsEnJSVRV1dHamoqaWlpvPrqqwwPG/jnEn9yc3PZvn27a7WNN1EqlUI9b+B47kSJSS6XC/VecyLS86ZUKoWZpnaymPOilAEpf39/1q5dy8GDB7n33nsBx5eygwcPsn///gXHcKOzYDGm1+unlUFaWlo4d+4cERERpKSksGPHDr74xS+iUqlITU3lyJEjvPjii/zwhz8EHKXHT3/60zz22GNEREQQFhbGI488wubNm+ediRGtmXOxePvkdCUiNvCK1jArWjzgEKxS9hw6G+ivxbUmMOPi4ti6dSsbNmzg17/+NT09PYSFhQGQkpKC0Wjk0qVLrFixwmuvedH86kA82xbR4gHxBmZEe+/D4h4jqUNxjz32GA888ADr1q1jw4YNPP3004yPj7umK33MnwWLsbNnz7Jr1y7X/z/22GMAPPDAA/zmN7/hD3/4A1/5yle47777GBoaIjU1le985zs8/PDDrmN+9KMfIZfL2bNnD0ajkdtuu42f/OQn845hMWJMxJMoiPXmFvExEi0mPz8/rFarUCf3oKAgBgcHPXb7UycwZyupr1271mXU/PTTTzM8PIxaraa1tZWSkhJMJhMnTpwA8JogGx8fF6qE4hxKma8lyVIgmo0MiGfWLZo4hMU9b1If349+9KP09/fzjW98A61Wy5o1a3jjjTdmNPX7uDYLFmM7d+686kkxLi6OF1544aq3ERgYyHPPPTencey1kMvlksfTRTupg3jj9iI+RqJlQwMCApDJZBgMBsmrudyNRqPh0qVLHjtRFBYWkp+fT2Vl5YwVRuvXryctLY3jx49z3333uT7YzWYzra2tgGPlypYtW7wmyOx2Ozqdjtzc3CX7m9fCmckMCAjwciTv4cuMXRuRvoQ5WcxnttVqlSzk9u/f7ytLugFxvmosgICAAEnlGBBP+IB4e85EEz7g6E+Q+px7AplMtqjXoScIDQ3FZrN5bMecXC5n//79M1YYrVmzhrS0NP74xz/ywAMPXPVD3SnIenp6XMJxqZicnMRsNs85pe0NnGbWIp3YnYMcIiGaGBNtnzAsbk2giM/5jcayFGOL2TAvmvAB8WISUYw5FyqLRGBgoHBrbMLCwjzqcn3lCqO8vDxycnI4ceIEX/va1+a1wshbgkyn0xEaGiqU8DEYDMKdBI1G45LtXJ0vi8nceAIRxdhidhyPjY3N8PP0sbSI9WqaJyEhIT4x5kGcGR+Rvo0GBgZKfs49hUhizGazUVVVxcTEBI2NjSQkJHjs5FVSUsLGjRs5duwYo6OjJCUlTStNzgdvlCxHRkaEyoqBQ4yJJnwMBsMMU25vI1rmZjHCx1MsRiCOjY0JY610oyLOV40FEBoail6vl3SsaMIHxIspMDAQq9UqXEyiCB8nAQEBQsRUWlrK3r17uf/++/n973/PuXPn2Lt3r8eW8trtdmprazEajdx0000UFxdLEn5LnSG70ttQBEQVYyLF5NxOIlpMImbGpMak1+t9mTEvs2zFmNFolLT2QaFQCCUyQDwxplQqUSgUQggNJ6IIn6mIIBBLS0t5/PHHqaioQKPRYLfbSUhI4Ny5czz++ONuF2R2u53q6mo6OzvdYlS8VILM2bwvmhgTsSQoWkwGg8HVoykKIpYppQpEu93uK1MKwLIUY84TgJSylWjCB8SLyfnB522hMRVnz5hIU57BwcFeLZ3abDaeffZZhoaGyMrKIiQkhJGRESwWC9u3b2d4eJjnnnvObf1/7hZiTpZCkDktP0QTY2NjY8JM44LjORYtM+YsUYrSMgFiijGpMU1OTmKz2XxlSi+zLMVYUFAQMplMUqlSNOEDYmbrRMj6TCUwMBC73Y7JZPJ2KC40Gg2jo6NeG3aoqqqipqaG+Ph414nKbrfT2NhITk4OcXFxVFdXU1VVtei/5Skh5sTTgqy9vZ2kpCShmsCdO3ZFEogWiwWr1SqUGBNxyOF6EmPO86gvM+ZdxPlkWgByuVxyVkKpVGK1WoXKsIgoEEWbXnSuixJJIIaEhCCTybyWHZvLEb++vp7U1FTUajVGo5Hh4eFF/R1PCzEnnhJkZrOZ7u5uUlJS3HJ77mJ8fBybzSbUSdBgMKBQKIQSGgaDYc6tD97iehJjY2NjKJVKoYyHb0SWpRgD6U38zherSF5jovlVgXiZMRCvb0wmk6HRaDxqJXE1pjriT2VkZISBgQEyMzMJCAhY1ALqpRJiTjwhyDo7OwkJCRFuklKn0xEWFiZUts6ZhRKpJChiZky06U6bzYbNZpOcGQsNDRXqOb8REedTYIFI9RpzvlhFykSJloUC8YQPiCkQ1Wo1IyMjXvnbTkd8rVY7Q7RcvHiRVatWUVhYSGFhoaTbX2oh5sSdgsxut9PU1ERWVpYbI3QPvoGC+SFaDxuIJxCd5zMpdhu+5n0xWLZiTKrXmFwuR6FQSJrE9BQ+4TM/VCoVExMT3g5jGt7MjM3liK/X63n33Xex2+186lOfkpR58ZYQc+IuQdbT04PNZiMhIcHNES4e0frFwFE6Fa0k6BOI18YpxqSWKX3N+95n2YqxsLAwyRkJ0cqCKpUKo9EolOu9iGLMm1mouVCr1V5t4r/SEb+1tRWdTkdRURHJycnY7fYFl+S9LcScLFaQ2Ww26urqyMzMFKoUCO9ZbYhWOvUZ414bu90unEBcTHl5dHSUsLAwD0TlYyGI1YG4AGJjY+nt7ZV0rGhCw5nunq0Z21uIWDrVaDQ0NDR4O4xpONfrDA8PExkZ6ZUYSkpK2LRpE1VVVQwPDxMeHu4qTR47doza2tp5lypFEWJOFuPUX19fD0B6errH4pOKM5sq2klQp9MJ93iJVhI0m83YbDbhxJjUeLRaLbGxsW6OyMdCEevr4gJISEigp6dH0rGilQXlcjn+/v5CxRQYGIjFYhGqt845HXhlw7o3kclkxMbGotVqvRqHXC5n5cqVbN++nZUrVyKXy5HL5RQVFdHS0sLQ0NA1b0M0IeZESoZsZGSExsZGioqKhMuKwXsnQJFiM5lMTE5OCpUZs9lsmEwm4YSPUqkUappyMWKsp6dHyDL+jYY4nwQLJD4+nu7ubknHipYZA/EyUX5+fsjlcqEeJ6VS6TI2FYm4uDivi7G5CAsLIycnh8rKyquWK0UVYk4WIshsNhsVFRVkZWUJ15PlRKvVEhcX5+0wpqHT6QgKChLK4sD5mShSZky0TB0srq+uu7ub+Ph4N0fkY6EsazEmNTMmmvAB8bJ1MplMSNHqzYb5uYiJiWFiYkK4ReZOsrKyUCqV1NbWznq56ELMyXwFmbM8mZOTs5ThzRvnayUmJsbboUxDxOnOyclJAgIChMogitbDBovPjPnEmPcR5xW+QBYrxkQTGYGBgUKV38DRDyVaFkpEMaZUKomKipLcw+hprlauXC5CzMm1BJlOp6OxsVHy8vKlQKvVEhkZKVQGCsRs3h8dHRXOdkFUMSY1W+cTY2Ig5qfVPHD2jEkZeRdRjAUHBwtn2yDi9KKIYgzELlWCo1yZm5vL2bNnXaJ/uQkxJ3MJMoPBwNmzZ8nKyhJOVExFxBIliJkZEzGm8fFxofaJgq9n7Hpg2Yqx+Ph4yaUh0UqC4PBNk7JRwJOIKHycTfyiPX9xcXEMDQ0JV/6eSlZWFtHR0ZSWlmIwGJalEHNypSAzGo2cPHmS8PBwcnNzvR3enJjNZgYGBoQTYyaTiYmJCeGEj4hebHq9Xrj3i9SeMaPRyNDQkC8zJgDLVoyp1WoCAwMlNfGLOCnoFGMi7czUaDSMjY0J9Tg5m/hFE4kqlYrw8HA6Ozu9HcqcyGQy1qxZQ2hoKIcPH6ajo2NZCjEnTkHW3d3NoUOHCAoKoqioSOi1Lp2dnajVauEyKyI279tsNkZHR4XLcoqWGbPZbJLFWE9PD3K5nOjoaA9E5mMhLFsxJpPJJNtb+Pv7I5PJhMquBAcHY7FYhMqsBAYGEhAQwOjoqLdDmYaIGTuA1NRU2trahBLUsxEUFITZbMbf3x8/Pz9vh7Mo/Pz88Pf3x2w2ExgYKLQQA2hrayM1NdXbYcxARAPa0dFR5HK5UMLHbDZjNBqF+gKzmInTnp4e4uLiJK1R8uFelq0YA+lN/DKZDJVKJVTDvFKpJDAwkPHxcW+H4kImk6FWq4UTPpGRkfT393s7jBkkJCQwOTnJ8PCwt0OZFWePWFdXFzt27CAsLIzjx48L9T5YCAaDgePHjxMcHMzOnTvp7e1123JxT6DT6dDr9SQmJno7lBn09/cTFRXl7TCm4SxRiiSw9Xo9/v7+QmUQJycnCQwMlDSw4mveF4dlL8akeo2J2KMlYkwiZqHi4uIYHh4WKosIDkGdnJxMS0uLt0OZwZXN+mFhYaxdu5bIyEiOHDki9PDBbPT19XHkyBE0Gg3r1q0jNDTUbcvFPUVLSwtJSUnCZSNNJhODg4PC9bGJmK0bHx8XKisGi+th84kxcVjWYiwtLY3W1lZJxwYHBwuVhQIxxZiIE5WBgYGo1WohrSQyMjLo7u4WqgQ+19SkTCZj9erV5OfnU15eTkVFBWaz2cvRXh2z2cy5c+c4c+YMubm50xz23bVc3BMYjUY6OzvJyMjwdigz6OvrIzQ0lKCgIG+HMg0RJyn1er1QZVNYXEwtLS1Cls1vRJa1GMvJyXEZPC4UEYWPiALR2cS/0GXTnkZUK4mQkBCio6Mlf0lwN9eyr5DJZKSmpnLTTTdhNBp59913hRS54BANhw4dYnx8nF27dpGWljajhCWqIGtrayMiIkK4XZQgptWGs3lfRDF2PWXG6uvrhZ4+vpHwiTGBCAkJEc7FXaVS4efnJ1x2LC4ujr6+PuFEIjiyYy0tLV7PMi3ER0ylUrFp0yby8vI4e/YslZWVXo/fydRsWHZ2NiUlJVfN4ogmyFreQZcAAHK/SURBVCwWC83NzWRmZno1jtmw2Wz09vYKJ8bGxsaEa94HMcXYYkqn9fX1wm6quNFY9mKsvb1dUgNySEgIExMT2Gw2D0QmDbVajV6vF8pKQiaTCdk3FhYWhr+/PwMDA94OZQbR0dGEhITQ1NTktRikGLpOzZIZDAbeeecd6urqvNabZzKZqKur4+DBg65sWHp6+rwaukUSZC0tLahUKmJjY70Ww1wMDg6iUCiEy0A5+8VEat63Wq3CWW3Y7XbJZUqLxUJTU5NPjAnCshZjcXFxBAcHSzrpqVQqZDKZUK73TisJ0bJQIvaNyWQyYUuVMpmMgoICGhsbvSJkFuus78ySrV27lsHBQd5++23Onz+PTqdbElEzMjLChQsXeOuttxgYGKCoqOia2bDZEEGQmUwmGhoaKCgoEEpYOHGWKEWLTcR+sdHRUZRKpVC9dZOTk9jtdklirLW1FblcTkpKigci87FQlrUYk8lkkkuVMpmM4OBgoUqVomahRIwJ3usb83YZajYiIyOJioqSXEaXirtWHMlkMmJiYigpKWHbtm3YbDaOHz/O4cOHaWpqcqtBsfPbfXNzM4cPH+bYsWOYzWa2bt3Kli1biI2NlSwWvC3IGhoa0Gg0Qppq2u12IfvFQEwx5tzdKZJw1ev1BAUFSbK1qK+vJysry+cxJghKbwewWK63vjERs1BTnfiVSnFeMlFRUVgsFiFXpgAUFBRw5MgRMjIylqT3xVO7JtVqNUVFRaxcuZLu7m46Ojqorq5GLpejVqvRaDRoNBrUajUhISFXPVnZ7XbGx8fR6XSMjIyg0+nQ6XTYbDbCw8NJT08nISHBrfYPTkF24sQJAFasWLEkJ9TJyUlaWlrYunWrx/+WFMbGxjAYDML5i4nqvC+iQPT1i10/iHNmlUh2drZkMSbq9KIUI1tPolKpUKlUwu3Uk8vlxMTEoNVqhfuQBEdfW2JiIrW1taxdu9ajf2spln4rlUpSUlJISUnBZrMxNjbmElPNzc2MjIwgl8sJDAxEoVAgl8tdouf48ePYbDYMBgM2m42wsDA0Gg1JSUkUFhYSFhYm6dv9fPGGIKurqyM2NlbI1yY4SpQxMTFCfcECGBgYwN/fX7hGeZ1OR3Z2trfDmMZibC18YkwsxHoXSiAnJ4d3331X0rEhISHC7RIUMQs1tT9LJDEGDuPf2tpacnNzhSofOMnLy+PgwYNkZmZ67KS8FELsSpxZMbVa7fIpcgo0o9GI1WrFZrNhMpkYGhoiOzsbf39/AgICCA0N9ajwmoulFGSjo6N0dHSwa9cuj9z+YrHb7XR1dQnpeyZiH5vztS2asNbr9ZI/k+vr6/n4xz/u5oh8SGVZ94zB4sqUYWFhjIyMCNVzJOo+SFH7s+Lj410O4iISFBREVlYW586d88jkrjeE2Fw4BVpMTAzx8fEkJiaSlJQEQGxsLDExMajVaq8IMSdL0UNms9morKwkPT1duOyOE51Ox8TEhHCrmUTtYxsdHUWhUAjVvA+OPjap3nW+zJhYLHsxlp2dTX9/v6R9gGFhYVgsFqEmKkXeB2m1WoWLS6FQkJycTFtbm7dDmZOcnBxsNpvbm/lFEmLLCU8LsqamJiwWC/n5+W69XXfS1tZGUlKSMNl3J6Ojo5hMJuH62ES02picnMRoNErqrZuYmKCjo8MnxgRi2Yux8PBwYmNjqa6uXvCxCoWCsLAw4QRGeHi4cMum5XI5sbGxQlpJpKam0t3djclk8nYos6JQKCguLqaxsdFtwxk+IbY4PCXIRkdHqauro6ioSNgpNbPZTGdnp5BrcJx9bKI9dsPDw8KVKEdGRggJCZEkqGtqatBoNMTExHggMh9SWPZiDKC4uJjy8nJJx4po2xAZGcnAwIBwJUFRfb3CwsJQq9XC9f9NRaPRkJmZSUVFxaLLlT4h5h7cLcimlicjIiLcFKX76erqIiQkRDhxAWKuZgKHOa6I2Tqpz2F5eTnFxcVCZfpudK4LMbZ27VoqKiokHSuilUR4eDgmk0m4Sc+YmBjGxsaEKus6SUtLo6WlRTgBOxXnDrjFlCt9Qsy9uFOQNTY2YrFYyMvLc2OE7sVut9Pa2kpaWpq3Q5mBwWBgZGREuE0Fk5OTTExMCCewFyPGKioqPD7h7WNhXDdibLGZMZFO4kqlkvDwcOGa0v39/YmMjBQyO5aYmIjJZKK/v9/bocyJXC6nqKiIxsZGSWVonxDzDO4QZCMjI9TX1wtdngRHhmdiYsI1WCESWq2W8PBwAgICvB3KNAYGBlCr1W71vnMHi/FXLC8v94kxwbhuxFh1dbWkjI2ziV/KfktPEhUVJeTeRVFLlQqFgrS0NJqbm70dylXRaDTk5eVRVlaGwWCY93E+IeZZFiPIjEYjp0+fJjs7W7jsyZU0NzeTmpoqXOM+QG9vr3BZMXCIMdFKlAaDAYPBIKl532QyceHCBYqLiz0QmQ+pXBdiLCkpicjISM6fP7/gYxUKBaGhob6+sXkSFxfHwMAAZrPZ26HMID09nf7+fuG2KlxJZmYm0dHRlJWVYbVar3l9nxBbGqQIMpvNxpkzZ4iIiBB+Mm1iYoLe3l7S09O9HcoMLBYLfX19vn6xeaLT6SQ371dVVREYGEhmZqYHIvMhletCjMlkMreUKkUiIiJCyL6x4OBgQkJC6Ovr83YoMwgMDCQhIUH47JhMJmP16tUAnDt37qonfZ8QW1oWIsjsdjsXLlzAYrGwZs0a4Zuhm5ubiY2NFc4rCxzZJ5VKRWhoqLdDmYao/WKLLVEWFxd71e/Px0yum2fjehNjCoVCyL4xELdUCY6sU3t7u3Bl5ytRKBRs2LCBgYEBmpqaZr2OT4h5h/kKspaWFrRaLRs3bhSy7DcVo9FIa2srWVlZ3g5lVrRa7aIWwnsKUfvFFjtJ6esXE4/rRoy5w95CtJKgyH1jvb29HnGUXywajYbY2Fjq6uq8Hco1CQwMZMOGDdTW1tLb2zvtMp8Q8y7XEmT9/f1UV1ezfv16VCqVl6KcP3V1dURHRwuX4QFxXfdBzH4xu92+KN8znxgTk+tGjDmb+KVkRNRqNTabTbgVRNHR0fT19QknEsPDw5HL5UIKRYD8/Hw6OjoYGxvzdijXJDw8nDVr1nD27FmGhoYAnxAThbkEmU6n48yZM6xcuZLIyEgvR3ltxsfHaWtrE3YjwNDQEDabTbjH0m6309fXR3R0tLdDmYZer8dsNksSY2azmQsXLvjEmIBcN2IsJSUFjUYjqYlfLpe7GuZFwvkt1nmSFgWZTEZSUhLt7e3eDmVWQkJCSE5Opra21tuhzIukpCTy8/M5deoUw8PDPiEmEFcKspGREUpLS8nJyRHSwX42amtrSUxMlLzD0NM4VzOJ1sM0MjKCxWIRLjM2MDBARESEJAuVqqoq/P39hS1X38iI9epfBDKZjHXr1nHmzBlJx4tYEpTJZEKvIOrp6cFoNHo7lFnJzc2lt7dXuLVSc5GRkUF2djbHjx+nvb3dJ8QEwinIurq6OHbsGJmZmcvmZDYyMkJ3d7ewRrRms5nu7m4hha1zNZNoInEx051nz56lqKhIuPvk4zoSYwDbtm3j6NGjko6NiopicHBQuJKgqM3yoaGhhIeHC7uCSKVSkZGRQXV1tXDP6WzY7XZMJhNyuRybzYbFYvF2SD6mYLFYsNlsyGQyTCbTsnhNgWMHYVpampATlACdnZ2EhoZK8svyNCL2sdnt9kX1sR05coTt27e7OSof7uC6EmM7d+7k8OHDkj4o1Wo1drtdyL6xiYkJIb2zUlNTaW1tFfbElJ2dzcjIiNCu/DC9R2zHjh3k5uZy4sQJ4crTNyrDw8OcOHGCrKwsdu7c6fbl4p5iYGCAwcFBof3P2trahFzNNDk5yejoqHAmtHq9HovFIqlfzG63c/jwYXbu3On2uHwsnutKjK1fv56JiQmqq6sXfKyofWN+fn5ERUUJmR1LSEjAaDQKKxr8/PzIzs4WOjs2W7N+VlYWBQUFlJaW0t3d7e0Qb2i0Wq2rRywnJ8fty8U9hfN1lZWVJdx6ISc6nQ69Xk9iYqK3Q5mBVqslIiICf39/b4cyjYGBAcLDwyX1izU3N9PX18fmzZs9EJmPxXJdiTF/f3+2bNnC4cOHJR0vohiD96wkREOhUJCUlERbW5u3Q5mTjIwMjEajkKLmalOT6enprF27lsrKSmpra4U96V+v2O126uvrOXv2LGvWrJnWI7YcBJlWq2ViYkJol3Vn476IHm0ilihhcVYbhw8fZuPGjcKWrG90risxBu+VKqUgct/Y4OAgJpPJ26HMIC0tja6uLmEb+RUKBXl5eVRXVwvVhzUf+4r4+Hi2bdtGR0cHZ86cESr+6xmr1Up5eTmtra1s3bp11syNyILMarVSXV1NTk6OkEIHHI37HR0dQpYozWYzAwMDwokxu92+qOZ9X4lSbK5bMbaYvrGRkREPRCYdlUpFWFiYkKXKsLAwIiIihM6OpaSkEBAQQE1NjbdDARbmIxYWFsb27dsxmUwcO3aMiYmJJYz0xmNycpJjx44xOTnJ9u3br9qbI6ogq6urQ6FQCCl0nLS3t6NWqyUbl3qSvr4+goKChJtmXmy/2KFDh3xiTGCuOzG2bt26665vDCAxMZGuri5vhzErGRkZtLS0COnIDw6LkKKiItra2ry+XkqKoWtAQAAlJSVERERw5MgR4QcSlisDAwMcOXIEtVpNSUkJgYGB1zxGNEE2PDxMc3Oz0LsH7XY7zc3NZGRkeDuUWens7BSyj62/v19yv1hTUxP9/f1s2rTJA5H5cAdivlsXwWL7xmJiYoTsz0pKSqK/vx+DweDtUGYQFxeHXC6np6fH26HMSWhoKHl5eVRWVnqt3LcYZ325XM7q1avJz8/n9OnTnD9/3le2dBMWi4WLFy9y6tQpcnJyWLNmzYJOeKIIMqvVSkVFBTk5OcIavIKjH8tmsxEfH+/tUGZgMpno6+sjKSnJ26HMoLe3V/J0p69fTHyuOzEGi+sbE7U/S6VSERERIWR2TCaTkZGRMefCa1HIzMz0WrnSXSuO0tLS2LVrF2NjYxw6dMiXJVskg4ODHD58GJ1Ox86dO8nIyJC0rFoEQVZbW4tSqRTekLa5uZn09HQhM3fd3d2o1WrhSpQWi2VRfWy+fjHxEe/d4AYW0zcWFBREaGgofX19HohscSQnJwtrspqSksLo6KjQjvfeKle6e9ek88SfmZnpy5JJxJkNO3nyJGlpaWzdutVtz4s3BNnQ0BAtLS3Cu6uPjIwwPDwsbD9bZ2enkFmxvr4+VCqVpNeoz19seSDuu3YROPvGLl26JOl4UV3vExISGB0dFdIA1s/Pj5SUFOGzYyEhIUtarvTU0m9nNnJqlkyr1Xq9Z0l0nMufDx8+zPDwMDt27CArK0tSNmw2vCHIrFYrlZWVwpcnwZEVS0pKEs6/C2BiYoKhoSEh+8V6e3sll3UbGhp8/WLLgOtSjPn7+7N7925ee+01Scc7fb1Ea0j38/MjNjZW2OxYVlYWPT09wk2jXslSlSs9JcSmMjVLVllZ6XPuvwrDw8OUlpZy9uxZ0tPT2bZtG6GhoW7/O0styJZLeXJsbIzOzk5h4+zs7CQmJkY4k1y73b4o37PXXnuNnTt3+vrFBOe6FGMAd999NwcOHJB0rEajQaFQeH3ybjaSkpLo6OgQMgMSFBREWlqaMBYSczG1XOmpydmlEGJOnFmy3bt3ExkZSWlpKadPn2ZsbMxjf3M5odfrOXPmDCdOnCA8PJxbbrmFzMxMt2XDZmOpBNlyKU+CQzSmpKQI148FjverqCXK4eFh7HY74eHhko4/cOAAd999t5uj8uFuxH73LoI77riDsrIySb1fMplM2FJlbGwsZrNZ2N6snJwcBgcHhRSyUwkJCSE/P5/Kykq3D2sspRCbip+fH/n5+ezevRuVSsXhw4eprKy8Yb3JJicnOXfuHIcOHcLf35+bb76ZgoIC/Pz8luTve1qQmc3mZTE9CQ5B0dvbK+yezNHRUSYmJoQzegXH9GlsbKwksT08PMzx48e58847PRCZD3dy3YqxuLg41q1bJ7lUGRsbK2QPjkKhIDExUViT1YCAALKysoTeB+kkIyMDtVrNmTNn3FaS9pYQm0pgYCCrVq3ipptuwmq1cvDgQc6ePXvDlC+Hh4cpLy/nnXfewWw2s2vXLlavXo1KpVryWDwlyOx2O2fPniUkJITs7Gy33KancL4nMjIyvPIczIe2tjYSEhKE3FiwmBLlP/7xDwoLC0lNTXVzVD7czXUrxgDuuusuyaXK6OhoDAaDkKWe1NRUurq6MJvN3g5lVjIzMxkfHxcyszgVmUxGcXExJpNJ8rDHVEQQYlMJDg5m3bp17Nq1i4CAAE6ePMnRo0dpa2u77qYvLRYL7e3tHDt2jBMnTuDn58euXbtYv369EM+DuwVZdXU1ExMTrF271qPlVnfQ39/PyMiIsKLRYrEIu5ppfHwcvV5PTEyMpON9Jcrlw3Utxu6++27eeustSUapSqWSmJgYIQWFRqMhLCyMjo4Ob4cyK0qlkpycHGpqaoTPjimVSjZu3EhXVxetra2Sb0c0ITaVkJAQVq5cya233kpSUhLNzc28+eabnD9/XshdrPPFbrczNDTEhQsXePPNN2lsbCQhIYHbbruNVatWCfUcuFOQdXR00NbWxsaNG5es5CoV5/siJydH2Fi7uroICgqS3JPlSbRaLVFRUZIeO5PJxBtvvOETY8sE8XKybmTFihXExMTw7rvvcvvtty/4+Li4OFpaWoTsc0hNTXWZJ4r4zTgtLY2mpiY6OjpISUnxdjhXJSgoiPXr13Pq1ClCQ0OJjIxc0PEiC7Gp+Pn5kZGRQXp6Ojqdjra2NsrKygBHWT4uLo7o6GhhT5rgyGL09fWh1Wrp7e3FbrcTHx/P5s2bCQ8PF/K94MQpyE6cOAE4Pp8WGu/Q0BDnz59nw4YNwr7OptLV1YXRaCQ9Pd3bocxJa2sraWlpQr52urq6SE5OlnTssWPHCAoKori42M1R+fAE17UYk8lk3HXXXbz66quSxFhCQgIXLlxgdHRUuAbZxMREqqqqGBoaWrB4WArkcjl5eXnU1NSQmJgoaZ/aUhIVFcWKFSsoKytjx44d8x4DXy5CbCoymYzw8HDCw8NZvXo1Q0NDaLVaampqKC8vJyoqitjYWCIjIwkNDfXqlJ7NZkOv1zM4OIhWq2VgYICgoCDi4uLYsGED4eHhwk8RTmUxgmxycpKysjLy8/Mll62WEpvNRm1tLXl5ecK+/4eHhxkbGxNyinJ8fBydTifZH+zVV1/lrrvuWlbvjxuZ61qMgaNU+cADD/CTn/xkwd98/Pz8iIuLo7Ozk4KCAg9FKA2lUklKSgrNzc1CijFw2HA0NjbS0tIirLfQVNLS0hgZGeH06dNs27btms28y1GIXYlMJiMyMpLIyEgKCwvR6/X09vbS09PjGsJQq9Wo1Wo0Gg0ajcZjAs1mszE2NoZOp2NkZASdTsfo6CjgKM3HxcWxYsUKj3iDLSVSBJnVaqWsrIzY2FhhF2xfSVtbGzKZTHJmZyloaWkhJSVFyGxwZ2cnsbGxkgxy7XY7Bw4c4Mc//rEHIvPhCa57MbZ9+3b0ej0VFRWsXbt2wccnJSVx8eJF8vPzhUtjp6en8+677zI5OSnklJJMJqOgoIDy8nJSU1OF/MC7kpUrV3Ly5EkqKipYv379nM/59SDEZiMkJISQkBAyMzOx2+3o9XqXOOro6ODSpUvYbDZUKhWBgYGun4CAANe/lUolcrkcmUyG1WoFHNYBcrkci8WCwWDAaDRiMBim/UxOTiKTyVzCLz09HbVaTWhoqHDvvcWyEEFmt9s5d+4ccrmcVatWLYvHwmKxUFdXx6pVq4TNzBiNRrq6uoRcE2S32+no6CA/P1/S8VVVVWi1Wm666SY3R+bDU1z3Yszf35/3ve99/O1vf5MkxmJjY6msrBSyHBgcHEx0dDStra2S37SeJiYmhrCwMBobG4WNcSpyuZx169Zx9OhRamtrZ435ehViVyKTyQgNDSU0NNSV3bDb7YyPjzMxMTFNVOl0Otf/WywW7HY7NpvN1ah++vRp5HI5CoVimogLCwsjJiaGwMBA1+695SA23MF8BVlDQwMDAwPs2LFD2HLflTQ1NREUFCR5hc9S0NbWRkREhJCZVp1Oh9FolGxp8be//Y1bbrlFyC/pPmbnuhdjAB/5yEf48pe/zL//+78v+INeLpeTmJhIZ2encGIMHF5Z5eXlZGdnC+mR48yOlZaWkp6eTmBgoLdDuiYBAQFs3LjRZZEwtcR6owixuZDJZK7s2Xwwm828/vrr3HLLLcsiM7rUXEuQNTc309jYyJYtW5bFewccGafGxkY2btworLC2Wq20tLSwatUqb4cyK52dnSQkJEgS33a7nZdffpmvfe1rHojMh6cQM3/sZu644w76+/tdk2MLJSkpia6uLuF2VYLDD02lUtHe3u7tUOYkIiKCmJgYqqurvR3KvAkLC2Pz5s3U19fT3NwM+ISYD88wl+1Fa2srNTU1bNq0CbVa7eUo509tbS0RERFERUV5O5Q56ezsRKlUCum4b7PZ6OrqkjxUcP78edra2rjnnnvcHJkPT3JDiLHAwEA+9KEP8dJLL0k6PiIiAj8/P3p7e90c2eKRyWRkZ2fT2NgopFh0snLlSnp6eoT0bZsLjUbDpk2bqKmpobW11SfEfHiMKwVZe3s7ly5dYtOmTURERHg7vHnT399PR0eHsBkncHypamhoIDs7W8jM3cDAADKZTLKY/d3vfscHPvABgoOD3RyZD09yQ4gxgL179/LHP/5Rkmu9TCYjKSmJzs5OD0S2eBISEpDL5cLGB6BSqVixYgXnz593+y5ITxIREcHGjRu5cOECra2tPiHmw2M4BVlHRwfnzp1jw4YNQrZGzIXZbKayspLCwkKhhUB3dzc2m01IOwtwmPomJiZKEopWq5WXX36ZvXv3eiAyH57khhFj27dvJyAggLffflvS8UlJSWi1WiFXEDmzYw0NDUK7qaekpBAWFuaW1UNLhd1up7e3F6VSid1uZ2BgwNsh+biOGRwcxGazuTLxIr+fr6S6uprg4GAh1wo5cWbFsrKyhJzytFgs9PT0SLYDOXLkCP9/e/cdX3V97w/8dbJ3TnbI3jshOyRkEbYKt9ifreICbR0oVq1W4V7b2qtCpbZqUXCivUhpq1URkSEZkD3IInvvvU7G2ef7+4N7zk0grDO/J3k/H4/zIIScz/d9wsk5r3ymRCLB2rVr1VwZ0TT2PRs1xMDAANu3b8cXX3yh1P2tra1hY2ODvr4+NVemHh4eHpBIJKweBuRwOIiOjtab4cr5c8TS09ORnJyMuro6tLW16bo0sgR1dnaipqYGSUlJSE9PV/vh4po0PDyMnp4eREdHs3LoT254eBh8Pp+1p4L09/fDwsJC6U3Gjx49ivvuu4+Vi7nIjS2bMAZcGar8+uuvlT7828fHB52dnax8cTQ0NIS/vz+am5tZWZ+cfLiyqqqK1cOVi03Wd3BwQEpKCpqamtDS0qLrEskS0tbWhrq6OiQnJ8PJyUkjh4trilgsRlVVFeuHJ4Er24T4+/uzNqyocjQTn8/HV199RUOUempZhbHIyEgEBATgm2++Uer+7u7uiiMq2MjHxwezs7OsH0rz8vICl8tl7XDljVZN2tnZISUlBa2trairq2P1myRhP/lzrampCSkpKQvmiOlLIKurq2P98CRwZQh4amqKtedkTk1NgcfjKT1EefLkSbi6uiq1nybRvWUVxoArvWPKDlUaGRnBw8MDnZ2d6i1KTYyMjODn54empibWvnADV4YrV65cycrhylvZvoLL5SItLQ2Dg4MoLi5m5TxCwn5isRilpaXo7+9Hamoq7Ozsrvkatgey4eFh9PX1ISYmhtXDkwDQ3NwMHx8f1u5319nZCXd3d6XrO3r0KB544AHW/z+QxS27MHbffffh/PnzSocAHx8f9PX1sfYN2N/fH9PT0xgeHtZ1KTdkbm6OyMhIVg1X3s4+YlZWVkhPTweHw8GFCxcwMzOjxUqJvpudncXFixchlUqRnp5+wzlCbA1k8uHJsLAwWFhY6LqcGxoZGcH4+DgCAwN1XcqiJBIJent7le5dHBsbw+nTp7F9+3b1Fka0ZtmFMU9PT6SmpirdOyY/NJmtm6waGxsjMDBQccgzm3l6eoLL5aK2tlbXpSi1oauxsTGSkpLg6uqKCxcusD4AE3YYGRlBXl4enJycsGrVqls6CJqNgUxfhiflP9uBgYFKHbqtDb29vbC0tASXy1Xq/v/4xz8QFxcHf39/9RZGtGbZhTEA+OUvf4mPPvpI6Rc0X19fdHR0sOIFcTG+vr4Qi8WsXfkpJx+uHBoa0ulwpSo763M4HISHhyMyMhKlpaVoa2tj7fOC6BbDMOjo6EBJSYniOXM72yuwKZDp0/DkwMAA+Hw+/Pz8dF3KohiGQXt7O3x9fZX6XjIMg8OHD+MXv/iFBqoj2rIsw9hPf/pTjI6OIi8vT6n7u7m5QSKRsLYnxNDQEMHBwWhoaGD1rvyA7ldXquuII09PT6xevRotLS2orKyEVCpVc6VEn8lkMtTU1KCpqQnJycnw9vZWqh02BLL5qyfZPjwpk8nQ0NCA4OBg1q6gHB0dhVAoVHoT2uLiYnR3d+PnP/+5misj2rQsw5ipqSl27tyJw4cPK3V/AwMD+Pj4oKOjQ82VqY+XlxcMDQ1Zu9hgPk9PT9jZ2aGyslKrby7qPmvSzs4OGRkZmJ6eRkFBAQQCgZoqJfpMKBSisLAQExMTSE9PV3lXfV0GMoZhUFVVBSsrK6UDpTb19PSAYRhW19rR0aF4vVbGBx98gAcffJD124qQG1uWYQwAHnvsMXz99ddK9255e3tjZGSEtRO3ORwOQkND0dzcDIlEoutybojD4SAmJgbT09NobGzUyjU1dei3ubk5UlNTYWlpidzcXPT396ulXaKfBgcHkZOTA1NTU6SmpqqtJ0lXgay5uRmTk5OIi4tj/fCkVCpFY2MjQkNDWbnbPgDMzc1haGhI6e02xsfH8Y9//AOPP/64misj2sbOZ6gWBAYGIi0tDZ9++qlS9zc3N8eKFStYvRu7q6srLCwsWF2jnImJCZKSktDe3q7xuW6aCmJyhoaGiI2NRXh4OKqqqlBeXs6aFaNEO0QiES5duoSKigqEhYUhPj5e7cNk2g5k/f39aG1tRWJiIkxNTTV6LXVob2+Hqakp3NzcdF3KdbW3t8PFxUXpkP63v/0NcXFxiIiIUHNlRNuWbRgDgF27duHw4cNKz+8JDAxET08Pa4ej5JPLW1pawOfzdV3OTVlbWyM+Ph6VlZUa21hX00FMjsPhwNPTE1lZWZBKpcjOzqZesmVicHAQ2dnZEAqFyMrKgpeXl8Z6kbQVyHg8HiorKxETEwNbW1uNXEOdhEIhWlpaEBYWxtoePJFIhM7OTqW325DJZHj//ffx5JNPqrkyogvLOoxt3boVMpkMJ0+eVOr+tra2cHR0RHt7u5orUx8HBwe4urqirq5O16XcEhcXFwQHB6OkpETtIVdbQWw+MzMzJCYmKnrJKioqqJdsiZrfGxYaGopVq1bB3Nxc49fVdCATCoUoKSlBQEAAq3uZ5quvr4ejoyOcnZ11Xcp1tbe3w87ObtHNfm/F2bNnwePxcM8996i5MqILyzqMGRkZ4cknn8Rf//pXpdsIDAxER0cHazeBBYDw8HAMDg6y/pgkuYCAADg6OqK0tFRtqxJ1EcTk5veSSSQSZGdnY2BgQGvXJ5onnxsm7w3z9vbWao+MpgKZTCZDWVkZuFwugoKC1NKmpo2Pj6Ovr4/VQ3cSiQTt7e0qfU8PHjyIxx9/nLV7p5Hbs6zDGAD84he/QH5+PhoaGpS6v4ODA2xsbFi9stLc3BwhISGoqalh/VYXwJXwEh0dDYZhUF1drfIbiy6D2Hzze8kqKyupl2wJmN8bFhISorXesMVoIpDV1tZCIpHoxX5iwJWf9ZqaGgQGBrJ6242uri5YWlrC0dFRqfu3tbXh3LlzNHF/CVn2YczJyQk///nPcfDgQaXbCAoKQnt7O6v3lvLz81NsLqgPDA0NkZiYiOHhYZVqZksQk5P3kq1ZswYSiQQ//vgjWlpaWP3cIdeSSqVobW3F+fPnddYbthh1BrKOjg709/cjMTGRtXt0Xa2zsxMSiQQBAQG6LuW65M+dwMBApZ8v77//PrZt26Y3w8bk5pZ9GAOAZ555Bp999pnSw3jOzs4wNTVFV1eXmitTHwMDA0RFRaGpqUkvJvMDV3r0kpKS0NDQoNQWJGwLYvPJH1t8fDz6+vrw448/oqurSy96LpczhmHQ1dWF8+fPo6enB7GxsTrtDVuMOgLZyMgI6urqkJiYyOoepvmEQiEaGhoQGRmp9J5d2tDb2wsjIyOsWLFCqftPTU3h448/xjPPPKPmyoguURgDEBcXh5SUFKXnjnE4HAQFBaG1tZXVb6ZOTk5wcXFBfX29rku5ZXZ2dli5ciXKy8tva083Ngex+ZydnZGRkYGIiAi0tLQgJycH/f39dKQSyzAMg4GBAeTk5KC5uRmhoaHIzMyEi4uLznvDFqNKIJudnUV5eTkiIyNV3qBWm+rr6+Hg4AAXFxddl3JdDMOgpaVF5V6xlStXIiUlRc3VEV2iMPa/9u7di7/+9a+Ynp5W6v5ubm4wMDBg/XmQ4eHhGBgY0JvJ/MCVHfq9vb1RUlJySwsl9CWIyXE4HLi7uyMrKwt+fn6oqanBhQsXMDIyouvSCICxsTHk5+ejqqoKPj4+WLt2LTw9PVkZwuZTJpCJxWKUlJTAw8OD1bvWX00+aT8yMlLXpdxQf38/ZDKZ0kcf8fl8vP3229izZ4+aKyO6RmHsf2VmZiIoKAgffvihUvfncDgICAhAS0sLq3s15JP5q6qqWL8z/3xhYWGwtLS86QpLfQti8xkYGMDX1xfr1q3DihUrUFpaiqKiIo3tuUZujMfjobi4GEVFRXBycsK6devg5+fH2t3cF3M7gUwqlaK8vBxmZmYIDw/XYpWqkUqlqKysRFBQEKuHVOW9YgEBAUo/hz799FO4ublh06ZNaq6O6Jr+vKpoGIfDwZ49e/DWW29BKBQq1YanpyckEgl6e3vVXJ16+fv7w8TEROkVpLrA4XAQHx8PmUx23UCmz0FsPiMjIwQFBWH9+vWwtrbGxYsXUVRUhKGhIVYH/aWAYRgMDw+juLgYeXl5sLS0xPr16xESEgJjY2Ndl6eUWwlkMplMcVJEQkKCXgXOxsZGGBoasnrSPgAMDAxAIBDAy8tLqfuLxWIcOHAAe/bsYX2vLLl9+vMTpwVbtmyBnZ0dPv/8c6Xub2hoiJCQEDQ2NrJ6dZz8LMiuri6MjY3pupxbZmRkhFWrVkEkEqG8vHzB/LylEsTmMzExQUREBNavX684SP38+fNob2/Xq15NfSCRSNDR0YHs7GxUVFTA1tYW69atQ2RkpF4c/XMzNwpkMpkMFRUV4PP5SE5O1qvQOT4+jo6ODsTGxrI6QMpkMtTX1yMkJETplal///vfYWJigp/+9Kdqro6wAXufvTpgYGCAl19+GW+++abSb3aenp4wNDREZ2eneotTM2tra4SEhKCyslKv3tiNjY2RnJwMPp+PiooKyGSyJRnE5jMzM0NISAjWr1+P4OBgdHd348yZM6iursbU1JSuy9NrPB4PNTU1OHv2LDo7OxEQEIANGzYgNDSUVSsk1WGxQMYwDCorKzE9PY3k5GS92kB0/vCkjY2Nrsu5oe7ubgBQuldMJpNh//79+M1vfsPqlaJEeRyGxj0WEIvFCAoKwr59+3Dvvfcq1cbg4CAqKyuxbt06Vv+WyTAM8vPzweVyWT/x9WpCoRAFBQWwtbWFqakp+vr6lmQQWwzDMJiYmEBXVxf6+vpgbW0Nb29vuLu7s+75JhaLcerUKdxxxx2sqU0ikaCvrw9dXV3g8Xhwc3ODt7c37O3tl8Xwz+zsLAoKCuDq6gqpVIrx8XGsXr0aZmZmui7tttTV1WF0dBRpaWms7hWT7ycYFRWl9L5g33zzDZ566inF4edk6aEwtoj3338fH374ISorK5V6cZaHHCcnJ4SEhGigQvWZmZlBbm4ukpOT9WoZO3BlZVFOTg5kMhkyMjJgbW2t65K0TiwWo7e3F11dXZiZmYGzszNcXV3h4uLCihdttoQxkUiEoaEhDA4OYmhoCJaWlvD29oanpydrQqI2yX/uORwO1qxZw+qJ74sZHx9HYWEh0tPTWd8r1tzcjIGBAaSnpyv9frJq1Sr8/Oc/x/PPP6+BCgkbsPfXCR3auXMnBgYG8MMPPyh1fw6Hg7CwMLS2tiq9GEBbrKysEBoaqnfDlfLTBAwMDGBqaorm5mZW7/GmKcbGxvD19UVmZibS0tJga2uLjo4OnDlzBhcvXkRLSwump6eX5cT/mZkZtLa2Ij8/H6dPn0ZbWxusra2RmpqKzMxM+Pn5LcsgJl/VZ2JiAkNDQ7S1tenV80OfhidFIhFaWloQFhamdK9rTk4OWltb8dhjj6m5OsIm+nHGhZaZm5vjueeew2uvvYbNmzcr9UPk4OAAJycnNDU1ISoqSgNVqo+fnx/6+/tRV1eHlStX6rqcm5o/Ryw1NRVGRkYoKipCeXk54uPjWT1koUm2trawtbVFcHAw+Hy+oieosbER5ubmcHV1haurK+zt7Zfk90gmk2FiYgKDg4MYGBgAn8+Hk5MT3N3dERcXt+TmgClDJpOhsrISk5OTSEtLg0wmQ0FBAQAgIiJCL4Zp6+vrYWRkxPrVkwDQ0tICOzs7ODk5KXV/hmHw2muvYffu3ctiCsZyRsOU1zEzMwN/f3989NFH2Lp1q1Jt8Hg85OXlISsrC5aWlmquUL3m5uaQm5uLlStXwt3dXdflXNf1JuuLRCIUFhbCzMwMCQkJNMl1HolEgpGREcUQnUwmg729PbhcLrhcLmxtbTUWVDQ5TCkQCDA5OYmpqSlMTk5ifHwcABTDtM7OznpzpqI2yLevmJ2dRUpKimIYWz6HbMWKFawPZAMDA7h06RIyMjJYH074fD7Onz+P1NRUcLlcpdo4e/Ys7r33XrS3tyvdBtEPFMZu4ODBgzh8+DCqq6uVfnO/dOkSGIZBXFycmqtTv/7+flRWViIzM5OV4fFmqybFYjGKiopgZGSkV4cbaxPDMIrgMjk5icnJSczMzMDU1HRBOONyuTAzM1P5jVldYYzP5ytCl/wmFAphZWWlqNne3h52dnasDhO6IpVKUVZWBoFAgJSUlGtWTepDIJP/whgVFaX0DvbaJN9YOz4+Xqn7y2QyxMfHY/v27XjhhRfUXB1hGwpjNyASiRAaGopXXnkFO3bsUKqNubk5ZGdnY/Xq1bCzs1NvgRpQU1ODiYkJ1q1QutXtK+THuTAMg8TERFZMYmc7iUSyIOhMTU1henoapqamsLGxgbm5OczMzGBmZgZTU1PFx2ZmZjd9jtxKGJPJZBAIBBAIBBAKhYqP5bepqakFwUsevmxtbZflnK/bJRKJUFZWBqlUesN9xNgcyOTDqdbW1oiOjtZ1OTc1NTWFCxcuYM2aNUr34B0/fhwvvvgiWlpa9G6lK7l9FMZu4tixY9izZw+ampqU/oFoaGjA8PCw0qtptEkqleLixYtwdHRERESErssBcPsbukokEsW8mMTERNja2mqp0qVDHtB4PN6iIUm+MMXExEQR0ExMTMDhcMDhcGBgYAAOhwOGYdDV1QVPT08AUOxtJRaLFW2JRCIAWBD05n9sY2MDGxsbCl5K4PF4KC0thbW1NWJjY2/6PWRrIKuvr8fg4CDS09NZ3+MtX01vb2+v9LFSIpEIYWFh2Lt3Lx555BE1V0jYiMLYTchkMsTGxuLhhx/Gc889p1QbEokEOTk5CAoK0ovDd2dmZpCXl4e4uDi4urrqtBZlN3RlGAbNzc1oaWlBbGys0vv7kMXJZDKIRKIFAU0sFivClnwzXqlUivb2dgQEBMDIyEgR1oyNjReELlNTU1b1xC4Fg4ODqKiogJ+fH0JCQm45WLEtkA0PD6O0tFQvtrEAgJ6eHtTX12Pt2rVKB8f3338fBw8eRE1NDevDJ1EPCmO34IcffsCDDz6ItrY2pXtZBgYGUFVVhbVr1+rFLte9vb2oqanBmjVrdLYKTR076/f39+PSpUsIDAxEUFCQzt9Ylhu27DO2nDAMg9bWVjQ1NSEmJkapBTlsCWQCgQA5OTkICwvTi19kxWIxzp8/j8jISKUXQs3MzCAgIACHDh3Ctm3b1FwhYSv6VfQWbNq0CREREfjTn/6kdBuurq6ws7PTm8O5PTw84Obmds0ZkNqiriOO3NzckJaWhq6uLpSXl+vVXmqE3C6pVIpLly6hvb0dqampSgeCWzlcXNPkZ2Y6OzsrfYyQtjU2NsLa2lqlnvi3334bvr6++MlPfqK+wgjrURi7BRwOB/v378df/vIXDA4OKt1GREQEenp6MDExoeYKNSMyMhJSqRQ1NTVafTFW91mTtra2yMjIgFAoRH5+Pubm5tRUKSHswefzFc/vjIwMlbdC0HUgu3z5MkQiEVauXKkXPdo8Hg9dXV2IiopSut7R0VEcOHAA+/fv14vHTNSHwtgtWrVqFTZs2ID//u//VroNKysr+Pv7az3cKMvQ0BBJSUkYHBxER0eHVq6pqUO/TU1NkZKSAjs7O1y4cAFjY2NqaZcQNhgfH0deXh5sbGyQkpKittV3ugpknZ2d6OvrQ1JSkl7MmWIYBjU1NfD19VXpWLY33ngDq1evRkZGhhqrI/qAwthteP311/Hpp5+iublZ6TYCAwMhFArR3d2txso0x9zcHImJiaivr8fIyIhGr6WpICZnYGCAlStXIjg4GEVFRejq6lJr+4ToQk9PDwoLCxEYGIjo6Gi1b3is7UA2OjqKy5cvIyEhQW/OzOzt7cXs7CyCg4OVbqOzsxOHDh3Cvn371FgZ0RcUxm5DaGgoHnnkETzzzDNKvyAZGRkhMjIS9fX1iiX9bGdvb4+oqCiUlZVhdnZWI9fQdBCbz9fXF0lJSaivr0dtbe2yPNOS6D+GYVBXV4fa2lokJibC399fY0Nb2gpkc3NzKCsrQ0REBBwdHTVyDXUTi8Woq6tDRESESr14zz77LLZv364XR9IR9aMwdptee+01VFRU4JtvvlG6DVdXV3C5XNTX16uvMA3z8vKCl5cXSkpKIBaL1dq2NoOYnJOTE9LT0zEyMoKioiLw+XyNX5MQdeHz+SgqKlLsveXs7Kzxa2o6kEkkEpSUlMDNzQ0+Pj5qbVuTGhoaVJ60f+rUKeTl5WH//v1qrIzoEwpjt8nOzg5//OMf8eyzzyo9EZzD4SAqKgq9vb0YHh5Wc4WaExYWBnNzc1RUVKjthVgXQUzO0tISaWlpsLCwQHZ2Nrq6uvRiLh9ZvhiGQXd3N3JycmBqaor09HSt/8xoIpAxDINLly7BxMQEkZGRamlTG0ZHR9Hd3a3SIgOBQIBnnnkGr7/+utIHihP9R2FMCTt27ICbmxveeOMNpduwtLREeHg4qqqq1N7TpCkGBgaIj4/HzMwM6urqVG5Pl0FMztjYGDExMYiPj0djYyOKi4upl4ywEp/PR0lJCerr6xETE4O4uDid7N2miUDW2NiIqakpxMfH683mv/KTPkJDQ1V67frTn/4EGxsbPP7442qsjugb/XjWs4yBgQHee+89/PnPf0ZLS4vS7fj4+MDS0lItwUZbjI2NsWrVKvT09KC1tVXpdtgQxOZzcXHBmjVrYGpqSr1khFUYhkFPTw9ycnJgbGyMrKwsrFixQqc1qTOQtbe3o6OjA6tWrdKrs2Tr6+thZmYGPz8/pdvo7OzEvn378N5776l94QXRLxTGlBQbG4sdO3aoNJmfw+EgJiYGfX19ejVcaWVlheTkZDQ1NaGnp+e278+2ICZnYmKC2NhYxMXFUS8ZYQWBQIDS0lLU1dUpesPYcoKHOgJZX18f6uvrsWrVKpW2hNA2+fBkTEyMSosmnnvuOdx7771ITk5WY3VEH1EYU8Frr72G8vJyfPvtt0q3YWFhgbCwML0argQALpeLhIQEVFdXY2ho6Jbvx9YgNp+rqyv1khGdkveGZWdnw9DQkBW9YYtRJZCNjIygsrIS8fHxsLe312CV6qWu4ckffvgBubm5NGmfAKAwphJ7e3vs378fv/rVr1Ta1V0fhysBwNnZGdHR0SgvL7+lUwX0IYjJze8la2hoQElJCfWSEa2Y3xsWHR2N+Ph41vSGLUaZQDY5OYnS0lJERUXB1dVVC1WqT319PczNzVUanhQIBNi9ezdN2icKFMZUtHPnTqxYsUKljfr0dbgSuHKGZUhICIqLizE9PX3dr9OnIDafq6srsrKyYGxsjOzsbHR3d1MvGdGIq3vD1qxZo9J2Cdp0O4FsdnYWxcXFCAoK0pszJ+Xkw5PR0dEqDU/SpH1yNQ5D7ywqq6ioQFpaGioqKhAaGqp0O52dnWhqalK8+esTedBKS0uDubn5gn/T1yB2tcHBQVRVVcHW1hbh4eGwsbHRdUmsJxaLcerUKdxxxx1695zWJh6Ph/r6ekxOTiIqKkpvQtjVZmdnUVBQgBUrViAiIuKawCIQCJCfnw9XV1eEh4fr1fmLEokEOTk58PPzg7+/v9LttLW1ISoqCj/++CPNFSMK1DOmBnFxcXjyySexc+dOSKVSpdvx9vaGtbU1amtr1ViddoSGhsLJyQmFhYUQCASKzy+VIAb8Xy+ZlZUV8vLyUFFRQYeOE5Xw+XxUVlYiLy8PFhYWetUbtpgb9ZAJhUIUFRXBzs5O74IYANTV1ak8PCmTybBz507s3LmTghhZgMKYmrz22muYmJjAW2+9pXQb8uHKoaEhvTm7Uo7D4SA6OhpcLheFhYUQCoVLKojJyTelXLt2LTgcDs6fP4/a2loIhUJdl0b0iEgkwuXLl3H+/HlIpVJkZWUhKipKr7Z2uJ7FAplIJEJRURGsrKxUXoGoC319fejr60NsbKxKtf/1r39Fb28vTdon16BhSjUqKirCunXrUF5ertJw5dDQEMrKypCRkaFXy72BK7/5VVRUYHp6Go6OjhgYGFgyQWwx8uGlsbEx+Pv7w9/fn4bj5qFhyoUkEgna29vR0tICe3t7hIaGgsvl6rosjZAPWTo7O2NychIWFhZ6tamr3OzsLHJzcxETE6NSr2VLSwtiYmJw8uRJZGZmqq9AsiRQGFOzF198ERcuXEBBQYFKh8bW1dVheHgY6enpercZoFQqRU5ODubm5pCamqpXy9aVNTY2hvr6eszMzCA4OBg+Pj5696ajCRTGrpDJZOjq6kJTUxPMzc0RFha2LFbRTU5O4sKFCzA3N0dWVpZevpZdvHgR9vb2iIqKUrodmUyGjIwMREdH469//asaKyRLBb1bqNkf/vAHTE1NqTRcCVyZg2VoaIjLly+rqTLtYBgGjY2NkEgkcHR0RHV19bIYwnNwcEBqaiqio6PR2dmJ8+fPo6enh1ZeLnMMw6Cvrw/Z2dlob29HVFQU0tPTl0UQE4lEqKqqgoODA2QyGerr6/Xu56G+vh4AEB4erlI77777Lvr7+2l4klwX9YxpQHFxMdauXYuysjKEhYUp3c7c3Bxyc3OxcuVKuLu7q7FCzbh6jpiFhQUuXboEHo+HlJQUmJmZ6bpErZBvUdDY2AhjY2OEhYXB2dlZ7+bJqMNy7hkbHh5GfX09hEIhQkJC4OnpuWx6S4VCIQoLC2FpaYn4+Hjw+fwbrrJko4GBAVy6dAkZGRkqTbNoaWlBdHQ0Tp06hYyMDDVWSJYSCmMa8pvf/Aa5ubkoLCxUabiyv78flZWVyMzMhKWlpRorVK/rTdaXyWSorKzE5OQkUlJSrtn2YimTSqXo7OxEc3MzLCws4O/vDzc3t2XzhgwsvzAmk8kwMDCAtrY2zMzMIDAwEH5+fno3PKcKPp+PoqIiWFtbIy4uTvF8v9m2F2wi/0U4KioKHh4eSrcjlUqRkZGBuLg4vPPOO2qskCw1FMY0RCAQICYmBg8//DBefvllldqqqanBxMQE0tLSWPlGfrNVkwzDKI5NSk5OXnb7c4nFYvT09KC9vR0SiQS+vr7w8fFZEivnbma5hDGRSITOzk50dHTAwMAAfn5+8PLyWtKPeTHT09MoKiqCo6MjoqOjr3m90odAJpPJUFBQAGtra0RHR6vU1l/+8he89957qK6uZvUv00T3KIxpUElJCbKyslBaWqrSnAP5JFIHBwdERkaqsULV3er2FQzDoKmpCe3t7Vi1atWymNR/NYZhMDQ0hPb2doyNjcHDwwN+fn6wtbXVdWkas9TDGI/HQ3t7O3p7e2FnZwc/Pz+4urqyMmRo2sTEBIqLi+Ht7Y3Q0NDrfg/YHsjq6+sxODiI9PR0lUY1mpubERsbix9++AFpaWlqrJAsRRTGNGzv3r04efIkSkpKVBqim5mZQV5eHlauXKlSt7k6KbOPWEdHB+rq6hAfH693Z9Kp0/w3cRsbG3h7e8Pd3V2lF382WophTCKRoL+/H11dXZicnFwWofpmhoeHUVpaitDQ0FvanZ6tgUw+LSQtLU2lHnyhUIiUlBRkZGTgz3/+sxorJEsVhTENE4vFyMjIQFRUFA4fPqxSW/L9x1JTU3W+N5EqG7r29/fj0qVLiIyMhLe3twarZD/5EGZXVxfm5ubg7u4OHx8fnf//qstSCmNTU1Po7OxEb28vzM3N4e3tDU9PT1Yf4q0NPT09qK6uRnR09G39osi2QDY1NYWLFy8iLi4OK1asUKmtX/3qVygoKEBBQcGymI5AVEdhTAu6uroQExODQ4cO4ec//7lKbbW0tKC9vR0ZGRk6W52ojp31R0dHUVJSgsDAQAQGBur8hVjXGIbB5OQkurq60NvbCysrK3h6emLFihWwsLDQdXlK0/cwxufzMTAwgJ6eHkxPT8Pd3R3e3t6ws7Nb9s9Z4Mo5i42NjUhISICzs/Nt358tgUwoFCIvLw/e3t4IDg5Wqa1vvvkGDz/8MC5duqTSGZZkeaEwpiXffvstHnroIZV/QBmGwaVLlzA7O4vVq1drfZWWOo84mpqaQlFREVasWIHIyEhWLk7QBbFYjP7+fvT29mJsbAzW1tZwdXWFq6sruFyuXoUAfQtjDMNgamoKg4ODGBwcBI/Hg729Pdzd3eHh4aEXj0EbGIZBXV0denp6sGrVKtjZ2Sndlq4DmUwmQ2FhIUxNTREfH6/S9eW/eB8+fBg/+9nP1FglWeoojGnRs88+i/z8fJW7rqVSKfLz82Ftba3Vc940cdbk3NwcSkpKYGJigoSEhGU/5HM1kUiE4eFhDA4OYmhoCIaGhopg5uTkxPotE/QhjEmlUoyOjioCmEQigbOzM1xdXeHi4kLPyauIxWKUl5djbm4OSUlJankd0GUgq66uxsTEBFJTU1Was6nOKSlk+aEwpkVCoRCrV69GWloa/vKXv6jUFp/Px4ULFxAQEKCVrnBNHvotkUgUm8MmJiYuu60vbpVMJsPY2JgiNAiFQjg5OSlCAxs31WVrGBMKhYrv48jICExMTBQh19HRkXppr2N6eholJSWwsrJCXFycWv9PdRHIOjo60NTUhPT0dJWnA7z88ss4deqUyou1yPJEYUzL2traEBsbi//5n//B1q1bVWprYmICBQUFSExMVGq+xq3SZBCbf42mpia0tbUhLi5uWa+0vBUMw2B6eloRKCYnJ8HlcuHi4gInJyfY2tqyoteMLWFMKpViampK0QM2OTkJW1tbRQCzsbHRq+FfXRgeHkZ5eTm8vb0RFhamke+XNgPZyMgISkpKkJycDAcHB5XaOn36NO655x6UlZUhJCRETRWS5YTCmA4cP34cu3btQlVVFby8vFRqq6enB7W1tUhPT9dYSNJ0EJuvr68PlZWVCAoKoon9t0EgEGBoaAiDg4MYHx+HWCyGtbU1bG1tweVyweVyYWNjo/WtM3QRxuTBa3JyUvHn9PQ0jIyM4ODgABcXF7i6urKyJ5GNGIZRTNRfuXIlPD09NXo9bQSy2dlZXLhwAWFhYSqv6O7v70d0dDQOHDiAhx9+WE0VkuWGwpiOPP7447h8+TJyc3NVfpOqq6vDwMAA0tLS1LqMWttBTG5ychKlpaWwt7dHTEwMK3p49AnDMODz+QvCyOTkJEQiEaytrcHlchUhzdbWVqMBTdNhTCKRgMfjKR7j1NQUpqenYWxsvOBxcrlcmJubU7i/TVKpFNXV1RgZGUFiYqJKE/VvhyYDmUgkQn5+PpycnFTeRFsqlWLdunXw8vLC559/rqYKyXJEYUxH+Hw+kpKSsGbNGpXPLGMYRjGhdvXq1Wp5c9VVEJMTCAQoKyuDRCJBfHw8rK2ttXr9pYZhGAgEggWhZXJyEkKhUNGDZm1tDTMzM8XN1NQUJiYmKr0RqhrGGIaBWCyGQCBYcJuZmVH0eJmYmCgClzx8UfBS3ezsLMrKysDhcJCYmKj1eVCaCGQSiQRFRUWKBUOqzg18+eWX8c0336C8vFzrr5FkaaEwpkPt7e1ISEjAm2++iUcffVSltqRSKYqLi8HhcLBq1SqVXmR0HcTkZDIZGhoa0NnZiaioKI0Pjyw38wPa1NQUZmdnFwQeiUQCAwMDmJqaKsLZ/LAmv5mYmMDAwAAcDgccDmfBxxKJBKdOncKmTZtgZGQEmUwGhmHAMAxkMhlEItE1QUsoFC74WCaTwcjICKampjA3N4epqSksLS0VAczMzIyCl5r19fUpplGEhYXprHdanYFMJpOhrKwMYrEYycnJKj+mL774Ak8//TSKi4tV3puMEApjOpaTk4O77roLZ8+exerVq1VqSywWKw64jY2NVeqFiy1BbL6hoSFcunQJrq6uiIyMXHJHBrGVRCK5JhwtFprEYrHS1zA2Nr5uyJv/efo/1w6pVIrLly+jr68PMTExKu9Erw7qCGQMw6CqqkqxhYWq25WUlZVhzZo1+Oqrr7Bx40aV2iIEoDDGCu+//z5effVVlJWVqTyhXyAQID8/H66urggPD7+tFy42BjE5Pp+PiooKCIVCJCQk0PYXLCLv5ZL3eM3/u1gsRk5ODtauXasY8ry6B42ww/T0NMrLy2FoaIj4+HhWnfygaiCTv66lpaWpPNza39+PhIQE/PrXv8bzzz+vUluEyFEYYwGGYfDkk0+ipKQE+fn5sLS0VKm92dlZXLx4Ef7+/ggMDLzlGtgaxORkMpli+4uIiAh4e3vTmznLsWVrC3Jj3d3dqKmpgZ+fH0JCQli5z5qygaytrQ3Nzc1ITU1Vee6pQCBARkYGQkNDceTIEXr9IWrDvp+4ZYjD4eDdd9+FjY0Ndu7cCVXzsaWlJVatWoXm5mZ0d3ff9Ov1IYgBgIGBAUJDQ5GUlITGxkaUl5dDKBTquixC9JZIJEJFRQXq6uqQkJCAsLAwVgYx4Mrr2urVqzEwMIDLly/f0utkb28vGhoakJSUpHIQYxgGjz32GAwMDHD48GEKYkSt2PlTtwyZmJjgyy+/RGlpKV5//XWV2+NyuUhMTERNTQ0GBwev+3X6EsTmc3JyQmZmJmQyGXJyctDf36/rkgjRO4ODg8jOzoZYLEZmZiZcXFx0XdJN3U4gGx4eRlVVFRISEmBvb6/ytf/0pz8hOzsb//73v2mPOqJ2NCuWRZycnHDixAmsXr0a4eHh2LZtm8rtxcTEoLy8HKtWrYKjo+OCf9fHICZnZmaGxMRE9Pb2oqqqCv39/YiKiqJzBAm5CZFIhMuXL2NgYACRkZHw9PTUq14eeSArKCgAgEWHLMfHx1FWVoaVK1eqJWSeOnUKr776KnJzc1mxqIEsPdQzxjJRUVH4/PPP8fDDD6Ompkbl9tzd3REZGYmSkhKMjY0pPq/PQUyOw+HA09MTWVlZkEqlyM7Opl4yQm5gcHAQOTk5EAqFyMrKgpeXl14FMbkb9ZBNTEygqKgIYWFhatkOp6GhAffddx8++ugjxMfHq9weIYuhnjEWuvvuu1FXV4c777wThYWFKr+geHt7g2EYFBcXIzk5GXZ2dnofxOa7updM/hs/9ZIRcoVYLEZtbS0GBgYQERGhtyFsvsV6yKamplBUVISQkBD4+vqqfI3+/n5s3rwZTz/9NO677z6V2yPkemg1JUsxDIMnnngCFy9eRH5+vlrmPHR0dKC+vh6urq4YHR1dEkHsagKBANXV1ZiYmEBERATc3d31/k1Hn9FqSt1iGAYDAwOora2FjY0NoqOjtb6TvqbJV1na29tjeHgYwcHB8Pf3V7ndyclJZGRkICYmhlZOEo2jMMZiUqkU99xzDwYHB/Hjjz+qvO8PwzAoLCzE6Ogo4uPj4e7urqZK2YVhGPT19eHy5cuwtrZGZGQk7UumIxTGdGd6ehq1tbWYmppCeHi43s0Nux0DAwOK82xTU1NVfpwCgQAbN26ElZUVvvnmG3ruEo2jOWMsZmhoiGPHjsHY2Bg/+9nPVNrpXD5HbGZmBkFBQaiqqsL4+Lgaq2UPDocDDw8PrF27Fra2tsjLy8Ply5dV+v4Roi8kEgnq6uqQm5sLKysrxUHWSzWITUxMoLKyEgEBAeDz+be87cX1SKVSbN++HSKRCP/85z8piBGtoDDGcmZmZvj222/R3d2Nxx57TKkXmasn64eGhiIsLAxFRUULJvUvNcbGxoiIiEBGRgYmJydx/vx59Pb2qryPGyFsJO8RPn/+PMbHx5Geno6oqKglHSbGx8dRWFiI4OBghIeH3/Y+ZFdjGAa7du1CQ0MDTp48qfIG3ITcKgpjeoDL5eL06dPIycnB3r17b+u+11s16evri/DwcBQXF2N0dFQTZbOGjY0NVq9ejYiICFy+fBkFBQXg8Xi6LosQtZmenkZRURFqa2sRGhqK1NRU2Nra6rosjRofH0dRURFCQ0MVc8SU2Rh2vldffRXff/89zpw5AwcHB02UTciiaDWlnnBzc1McJu7i4oJnn332pve52fYVPj4+4HA4KC4uRlxc3JLeP0c+dOni4oKmpibk5eXBw8MDISEhS25CM1k+BAIBmpqa0N3dDR8fHyQkJCzpnjC5oaEhlJWVITw8/JpVk7eyD9liDh06hHfffRcXL15U+YxgQm4XTeDXM6WlpVi7di0+/PDDGy61vp19xAYGBlBRUYHIyEh4e3tromzWmZmZQWNjIwYHB+Hr64vAwEDaCkMDaAK/ZojFYrS0tKC9vR0uLi4ICQlR+bgffSE/RzMmJuaGi5Bu5yzLL7/8Ejt27MCZM2ewevVqTZRNyA1RGNNDZ86cwd13340vv/wSmzdvvubfldnQdXR0FKWlpfD390dQUNCSnex7tcnJSdTX12NiYgKBgYHw8/ODkRF1GKsLhTH1kkql6OjoQHNzM2xtbREWFgY7Oztdl6U1ra2taGpqQmJiIpycnG769bcSyM6fP4+tW7fi+PHj2LJliybKJuSmKIzpqX/+85945JFH8PXXX2P9+vWKz6uysz6Px0NhYSHc3NwQGRm5bAIZAIyMjKC+vh58Ph8hISHw8vJi7YHJ+oTCmHrIZDL09PSgsbERpqamCAsLg5OT07L5GWUYBnV1dejt7cWqVavA5XJv+b43CmS5ubnYsmUL3n//fTz44IMaqJyQW0NhTI8dO3YMjz32GE6cOIGsrCy1HHE0NzeHwsJC2NraIjY2FoaGhhqonJ3kG2TW19cDAAICAuDp6bmsvgfqRmFMNfIQ1traCoZhEBISsuw2MpbJZKisrMT4+DiSk5OVel1bLJBdvHgRd9xxB959913s3LlTA5UTcusojOm5v/3tb3jqqafw3XffwcnJSS1HHAmFQhQXF8PIyAiJiYnL7k1UJpOhr68PLS0tEIvF8Pf3h4+PDw1fKoHCmHIkEgm6urrQ2toKIyMjxS8Gy623ViKRoKysDEKhEKtWrYKZmZnSbc0PZDweD5s3b8Zbb72FX/7yl2qsmBDlUBhbAo4cOYLdu3fj1VdfxeOPP66WI47U+SKorxiGweDgIJqbmzE7Ows/Pz/4+fnRRP/bQGHs9ohEInR0dKC9vR3m5uYICgrCihUrllVPmJwmfimcnZ3Fxx9/jFdeeQVvvvkmnnjiCTVUSojqKIwtER999BGef/55fPfdd8jMzFRLm/LhgbGxMSQlJS35fYuuh2EYjI6OoqWlBePj4/D29kZAQABtiXELKIzdGoFAgLa2NnR0dMDOzg6BgYHLak7Y1Xg8HkpLS9U+XaKgoAB33HEHXn/9dTz99NNqaZMQdaAwtoR89tln2L17N7755husXbtWLW0yDIPm5ma0trYiJiYGbm5uamlXX01MTKClpQVDQ0NYsWIFfH19YW9vv2zfNG+Gwtj1MQyDiYkJdHR0oL+/H87OzggMDIS9vb2uS9OpwcFBVFRUwM/PDyEhIWr72bpw4QLuuusuHDhwAI8//rha2iREXWgSzBKyY8cOGBkZ4T/+4z/w73//Gxs2bFC5TQ6Hg+DgYFhbW6OyshLT09PLauuLq9nZ2SExMREzMzPo7OxEcXExLC0t4evrC3d3d5pXRm5KKpWir68PHR0dmJmZgZeXFzIzM5fNPmHXwzCMYuuKm+0hdrvkqybffvttPProo2prlxB1oXeOJeaBBx6AoaEh7r77bvzjH//AnXfeqZZ23dzcYGVlhZKSEvB4PMTExCzr4GFlZYWIiAiEhISgt7cX7e3tuHz5Mjw9PeHj4wMbGxtdl0hYZnp6Gl1dXeju7oapqSn8/Pzg4eFBPYa4ElCrqqowOjqK1NTU29q64mbOnTuHu+++GwcPHsTDDz+stnYJUScaplyivvzySzz88MM4dOgQHnroIbW1KxQKUVZWBrFYjKSkJFhYWKitbX0mH3Lq7OxEX18fuFwuvLy84ObmtqzfbJf7MKVYLMbAwAB6enowPj4ONzc3+Pj40ND2PHw+H6WlpTAwMEBCQoJaFwsdP34cjz76KD766CNs375dbe0Som4Uxpaw7OxsbNu2Df/1X/+FF154QW0v/jKZDLW1tejv70diYiIdqHsVkUiEnp4e9PT0YHp6Gq6urvDw8ICzs/Oy27NsOYYxmUyG4eFh9Pb2YmBgANbW1vDw8ICnpydMTU11XR6rjI+Po7S0FC4uLoiKilLrz8c777yDV155Bf/617+wceNGtbVLiCZQGFviKisrsXnzZtx///04cOCAWvcp6ujoQF1d3bI60/J2TU9Po7e3F729vRCLxXB3d4eHh8ey6RlZLmFM3jPa09OD/v5+GBoawsPDAx4eHjRkfR3yMyZDQ0Ph5+entp8HhmGwd+9efPzxx/j++++RmJiolnYJ0SQKY8tAW1sbNmzYgOTkZHz66adq3SdrZGQE5eXlit9sl/M8shtZ7M3a3d0drq6uSzqYLeUwJv8/HRwcRF9fH8RiMdzc3ODp6bmk/09VJZVKFT3r8fHxcHZ2VlvbEokEjz32GLKzs3HmzBkEBwerrW1CNGl5beesJfv27UNCQgKsra3h7OyMn/zkJ2hqalL8+/j4OHbv3o3g4GCYm5vDy8sLzzzzDKampha0w+FwrrkdP358wde8+uqr8PDwQGpqKpqbmxetx9/fH4WFhaivr8fWrVsxMzOjtsfq5OSEzMxMzM3NIS8vDzweT21tLyUcDgf29vZYuXIlNm7ciKioKAiFQpSWluL06dO4dOkS+vv7IZFIdF0quQGJRIKBgQFUVlbizJkzKC4uBp/PR0REBDZu3Ijo6Gg4ODhQELuO6elpxetEZmamWoPY3Nwctm3bhvLychQWFi4axA4dOoSoqCjY2NjAxsYGycnJ+OGHHxT//uGHHyIzMxM2NjbgcDiYnJy8pg0fH59rXpf379+/4Gs++ugjeHt7IyYmBiUlJWp7jGTpop4xDdi0aRPuvfdeJCQkQCKRYO/evbh8+TLq6+thaWmJy5cv43e/+x127NiBsLAwdHV14YknnkBUVBS+/PJLRTscDgdHjhzBpk2bFJ/jcrmKCa4FBQV47rnncOjQIZSUlOCbb77B2bNnr1sXj8fDtm3bMD09je+//x5OTk5qe8wymUyxH1lERAS8vb3pDekWyGQyRe/K4OAg5ubm4OjoCFdXV7i6uur9xrJLoWeMz+djaGgIg4ODGBkZgbm5ueL/x97eftkdUaQs+bCkfP8wdX7fxsfHsWXLFhgaGuLEiRPXXY353XffwdDQEIGBgWAYBp9//jkOHDiAyspKhIeH4+2334ZAIAAA7NmzBxMTE9e05ePjg0cffXTBMUrW1tawtLRUPM61a9fib3/7G/r6+vDb3/5Wcd4tIddDY0oacPr06QV//+yzz+Ds7IyKigqkp6cjIiICX331leLf/f398frrr+OBBx6ARCJZMNTH5XLh6uq66HUmJibg5uaGqKgoSCQSfPbZZzesy8bGBqdOncJDDz2E1NRUnDlzBj4+Pko/zvkMDAwQEhICBwcHVFRUYHR0FCtXrtTbN2BtMTAwgIODAxwcHBAeHo6ZmRnFsFdtbS2srKzg4OAAR0dHODo60gRwLRAKhRgbG8Po6ChGR0cxMzMDOzs7uLq6Ijw8HFZWVvSLxm2QSCSorq7G8PAwEhIS4OLiotb2e3p6sGnTJgQFBeHYsWM3/AVmy5YtC/7++uuv49ChQyguLkZ4eDieffZZAFf2JbsRa2vr674u83g8cLlcREVFwdXVFXw+/7YeD1me6Fc6LZAPP95oZ+2pqSnY2NhcM+fqqaeegqOjIxITE/Hpp59ifkfmxo0bIRAIYGFhgU2bNmHfvn03rcXU1BR///vfsWHDBqSkpKCsrEzJR7U4+bClSCRCXl7eot385PqsrKwQEBCA1NRUbNq0CaGhoTAwMEBzczNOnz6N7OxsVFdXo6+vD0KhUNflLglCoRD9/f2oqalBdnY2Tp8+rZhWEBISgk2bNiEtLQ2BgYGwtramIHYbpqamkJubC4FAgMzMTLUHscrKSqSkpCA1NRVffvnlbfUkS6VSHD9+HLOzs0hOTr6t6+7fvx8ODg6IiYnBgQMHFkwviIiIQFRUFGxtbREeHo7XXnvtttomyxP1jGmYTCbDs88+i9WrVyMiImLRrxkdHcV///d/47HHHlvw+T/84Q/IysqChYUFzp49i127dmFmZgbPPPMMAMDY2BinT5/G8PAwuFzuLU/MNzAwwLvvvgtfX1+sWbMGH3zwAe6//37VHug8ZmZmSE5ORktLC/Lz89W+Wmq5MDExwYoVK7BixQoAV7bMGB0dxdjYGJqbm1FeXg4rKyvY2dnB1tYWXC4Xtra2tIjiBiQSCXg8HiYnJxW36elpWFtbw9HRUdG7Sz2QqmEYBp2dnairq0NgYKBGTu3417/+hUceeQT/+Z//iZdeeumW26+trUVycjIEAgGsrKzw9ddfIyws7Jav+8wzzyA2Nhb29vYoLCzEnj17MDAwgD//+c+Kr/nkk0/w5ptvwsLCQu+nGhDtoDljGvbkk0/ihx9+QH5+Pjw8PK75dx6Ph/Xr18Pe3h4nTpy44bDeb3/7Wxw5cgQ9PT1qq+/06dO499578cQTT+D1119X+z5YY2NjKC8vh62tLaKjo9W6oeNyJxKJMDY2hsnJSUxNTWFychJCoRBWVlbgcrmKm42Njc6Gi3U5Z0wsFiuCl/z7Mz09DRMTE8X3xtbWlsKXmgmFQlRXV2N8fBzx8fFwdHRUa/symQy///3v8c477+CLL77AXXfddVv3F4lE6O7uxtTUFL788kt8/PHHyMvLWxDIcnNzsWbNmkXnjF3t008/xeOPP46ZmRl6HhGlURjToKeffhrffvstLly4AF9f32v+fXp6Ghs3boSFhQVOnjx506Dy/fff46677oJAIFDrD31TUxO2bt2KwMBAHDt2TO37IolEItTW1mJoaAiRkZHw8PCgXjINYBgGAoFgQfiQBzRTU1NYWVkpbpaWloo/NTkBXdNhTCaTYXZ2FrOzs5iZmcHMzIziY/nPiTx0yQOYmZkZPf80pK+vDzU1NXB0dERUVJTaw8nMzAwefPBB1NbW4sSJE7fVo3U969atg7+/Pz744APF524njNXV1SEiIgKNjY20lQZRGo1naADDMNi9eze+/vpr5ObmLhrEeDweNm7cCFNTU5w4ceKWeoyqqqpgZ2en9he44OBglJSU4N5778WqVatw4sQJBAQEqK19ExMTxMXFKebl9Pf3Y+XKldRLpmYcDgfm5uYwNzdXDG0CV3oq5oeV8fFx9PT0YGZmBjKZDJaWlrCwsICZmRlMTU1hZma24GZqaqqToU+pVAqBQLDgJhQKFR/Pzc1hbm4OHA5HES7lw7byj01MTCh4aYFQKERNTQ1GR0cRFRWl1kO+5To6OvAf//EfcHZ2Rmlp6Q3n4N4OmUym0vzLqqoqGBgYqHWbDrL8UBjTgKeeegrHjh3Dt99+C2trawwODgIAbG1tYW5uDh6Phw0bNmBubg5Hjx4Fj8dT7M/l5OQEQ0NDfPfddxgaGsKqVatgZmaGc+fO4Y033sALL7ygkZq5XC6+//57vPTSS0hMTMQ///lPrFu3Tq3XcHNzg4ODA2pra5GdnU29ZFpiamoKU1PTa968GIYBn8/HzMwM5ubmFEFndHR0QfhhGAZGRkYwMTGBkZHRdW+GhoaKYW75/ktSqRQA0NnZCUNDQzAMA5lMBolEsuhNKpVCIpFAKBRCIpGAw+FcExAtLCxgb28PCwsLWFlZwdzcnJ5DOiTvDXNwcEBWVpZGhupyc3Px//7f/8P27dvx1ltvKd3LumfPHmzevBleXl6Ynp7GsWPHkJubizNnzgCAYouZ1tZWAFfml1lbW8PLywv29vYoKipCSUkJ1qxZA2traxQVFeG5557DAw88ADs7O7U9XrL80DClBlzvjeHIkSPYsWOHogt8MR0dHfDx8cHp06exZ88etLa2gmEYBAQE4Mknn8Qvf/lLje9r9Pnnn2PXrl3Yt28fdu/erZE3OnkvmZ2dHfWSsRjDMBCJRBAIBBCJRAsC02I3mUymWPErD14jIyNwdnaGgYEBOBwODAwMrhvm5B+bmJjAzMyMerZY7OreMDc3N438Xx0+fBi//vWv8fbbby/Y20sZjz76KM6fP4+BgQHY2toiKioKL730EtavXw8A+P3vf49XX331mvvJX7svXbqEXbt2obGxEUKhEL6+vnjwwQfx/PPP03wxohIKY2RRxcXF2LZtG+644w4cPHhQIyuChEIhamtrMTw8rBjaoDfepWUpbPpKrjW/NywqKkojv0wJBAI899xz+Oqrr/DVV18hLS1N7dcghC1onzGyqFWrVqGsrAwNDQ1ISkpCY2Oj2q9hamqK+Ph4REdHo7a2FqWlpZidnVX7dQgh6jE3N4fS0lJUV1cjMjISCQkJGgliLS0tSElJQUVFBcrKyiiIkSWPwhi5Lg8PD+Tl5eGOO+5AQkICPv/8c41cx83NDVlZWTAxMUFOTg6ampoUc40IIbonlUrR3NyM7OxsGBkZISsrS2PzPf/+978jLi4Oa9asQX5+Pry9vdV+DULYhoYpyS05ffo0HnroIWzevBnvvfcerKysNHKd8fFx1NTUQCwWIzIy8rpHjhD9QMOU+m94eBg1NTUwNDREVFQUHBwcNHKdubk5/OpXv8K///1vfPbZZ9ccXUTIUkY9Y+SWbNq0CVVVVeju7kZ8fDxqamo0ch17e3tkZGQgICAAly5dQklJCQ1dEqID8iHJsrIy+Pn5ISMjQ2NBrL6+HomJiWhoaEBVVRUFMbLsUBgjt8zNzQ0//vgj7rvvPiQnJ+ODDz6AJjpWORwOfH19sXbtWpiamiInJweNjY00dEmIFlw9JLl27Vr4+flpZBU3wzA4cuQIkpKS8JOf/AS5ubnw9PRU+3UIYTsapiRKycnJwf3334+0tDR8+OGHsLW11di1rh66dHFxoVWXeoKGKfUHwzAYHh5GbW2txockgSsnkOzatQtnz57F0aNHFdtLELIcUc8YUcqaNWtQVVWFqakpxMbGoqCgQGPXkg9dBgYGorKyEgUFBRgfH9fY9QhZbiYmJlBYWIiKigqND0kCQElJCeLj49Hf34/q6moKYmTZozBGlObs7IxTp07hqaeewoYNG/D8889jbm5OI9ficDjw8fHBunXr4ODggMLCQpSUlChOLiCE3L7p6WmUlpaioKAAdnZ2WL9+vcaGJIEre4e99NJLyMrKws6dO3H27FlapEMIaJiSqElTUxN27tyJ0dFRHDlyBKtXr9bo9QQCAZqbm9HV1QUPDw+EhIRoZGNaohoapmQnPp+PpqYm9PT0wMvLC0FBQRr/+SktLcWOHTtgaWmJzz77DOHh4Rq9HiH6hHrGiFoEBwfj4sWLeOyxx7Bhwwb8+te/Bp/P19j1zMzMEBUVhaysLMhkMpw/fx6XL1+GSCTS2DUJ0XcikQh1dXU4f/48xGIx1qxZg5UrV2o0iAkEArz88svIzMzEgw8+iKKiIgpihFyFesaI2jU2NmLHjh2YmJjAkSNHkJKSovFrTk1Nob6+HuPj4wgICIC/vz+MjIw0fl1yY9Qzxg4SiQQdHR1oaWkBl8tFaGioVg62Lisrw44dO2Bubo7PPvsMERERGr8mIfqIesaI2oWEhKCgoACPPvoo1q9fjxdeeEGjvWQAYGtri+TkZCQlJWFoaAhnz55FY2Mj9ZSRZU0kEqGpqQnnzp1Df38/4uPjkZKSovEgJhQKsWfPHmRkZOD+++9HcXExBTFCboB6xohGNTQ0YMeOHZicnMSnn36q8blkwJUl+qOjo2hubsbExAR8fHzg7+9Pc8p0gHrGdEMgEKCtrQ2dnZ3gcrkIDAyEk5OTVraEKS0txc6dO6k3jJDbQD1jRKNCQ0NRUFCARx55BBs2bMAjjzyC4eFhjV6Tw+HAyckJq1evxurVqzE3N4cff/wRlZWVmJmZ0ei1CdGl2dlZVFdX49y5c5iZmUFycjJWr14NZ2dnjQexsbExPP7448jMzMR9992HoqIiCmKE3CIKY0TjjIyM8NJLL6Gurg4TExMIDg7Ge++9p5Ud9e3s7JCYmIjMzEwwDIOcnByUlZVhcnJS49cmRFumpqZQXl6O7OxsSCQSZGRkICkpCfb29hq/tlQqxYcffoigoCD09fWhtrYW//Vf/0U9oYTcBhqmJFr3ww8/4JlnnoG1tTXee+89JCcna+3ac3NzaG1tRXd3NxwcHODv76+14ZvliIYpNYdhGIyMjKC9vR0jIyPw8vJCQEAALC0ttVZDWVkZnnrqKYyMjODdd9+lMyUJURL1jBGt27x5M2pra/HTn/4U69at08rQpZyFhQWioqKwfv16cLlcXLp0CefPn0dbWxvEYrFWaiBEFWKxGO3t7cjOzkZFRQVsbGywfv16rFy5UmtBbP6Q5B133IH6+noKYoSogMIY0QkzMzP853/+J+rr6zE5OanVoUsAMDU1RWhoKNavX4/g4GD09fXhzJkzqK6upl39CSvxeDzU1NTg7Nmz6OnpQWBgIDZs2ICwsDCYmZlppYb5Q5IDAwOora3F73//e1ocQ4iKaJiSsMLp06exe/duWFlZ4d1330VaWprWa5iYmEBHRwf6+/tha2sLHx8fuLm5wdDQUOu1LBU0TKkaqVSKgYEBdHZ2YmJiAm5ubvD19YWdnZ3Wh9aLi4vxzDPPYHR0FO+++y7uuusurV6fkKWMwhhhDaFQiLfeegv79+9HRkYG3njjDURGRmq9DpFIhJ6eHnR2dkIoFMLLywuenp6wsbGhuWW3icKYcng8Hnp6etDd3Q1jY2P4+vrC09MTJiYmWq+loaEBe/fuxblz5/Diiy/iN7/5DfWEEaJmNExJWMPU1BR79+5FW1sb/P39kZiYiIcffhhdXV1arcPExAT+/v7IyspCUlIShEIhLl68iJycHDQ3N2vsMHSyvPH5fLS0tCAnJwcXLlwAn89HQkIC1q5dC39/f60HsZ6eHjzyyCOIjY2Fu7s72tra8Lvf/Y6CGCEaQGGMsI6TkxPefvttNDQ0ALiyo/+zzz6LkZERrdbB4XDg4OCAuLg4bNq0CUFBQRgbG8OPP/6I/Px8dHZ20g7/RCVisRhdXV0oKCjAuXPnMDo6ioCAAGzcuBHx8fFwdHTUem/s2NgYXnjhBQQHB0MgEODy5cs4ePAgXFxctFoHIcsJDVMS1qutrcXevXuRl5eHF154Ac8//zysrKx0Vo9QKERfXx96enrA4/Hg7OwMT09PuLi40Pyyq9Aw5bWkUimGhobQ29uLoaEh2NjYwMPDA+7u7lqbiL+Y2dlZvPPOO3jzzTeRnJyMffv2ITo6Wmf1ELKcUBgjeiM/Px8vvfQSWltb8corr+Cxxx7TyRya+WZmZtDb24ve3l4IhUK4uLjA1dUVLi4uFD5AYUxOLBZjeHgYg4ODGBoagrGxMTw8PODh4QFra2ud1/bxxx/jD3/4A7y8vPDHP/4RmZmZOq2JkOWGwhjRKwzD4OTJk9izZw+mp6fx4osv4pFHHoGFhYXO65qcnMTAwACGhoYwPT0NBwcHuLq6wtXVVasbcbLJcg5jc3NzGBwcxODgIEZHR2FlZaV4PuhiNeTVBAIBjhw5ggMHDsDExARvvPEGtm3bpvO6CFmOKIwRvSSVSvHvf/8bb7zxBvr6+vDss89i165d4HK5ui4NwJUhH3kvCBvfiLVlOYUxeSCXBzC2BnIej4dDhw7hL3/5C5ydnbFnzx7cc889MDIy0nVphCxbFMaIXmMYBmfOnMG+fftQVVWFJ598Es899xyrJhtfPURlYGAAJycnODo6wtHRERYWFks2nC31MDY3N4fR0VGMjo5ieHgYUqlUMVTt7Oys82H0+UZGRvDOO+/g4MGDCA8Px549e3DnnXcu2eceIfqEwhhZMgoLC7Fv3z6cP38eO3bswIsvvghfX19dl7WATCbD+Pg4RkZGMDo6iomJCZiZmcHBwWFJhrOlFsbmh6/R0VEIBAJwuVw4OjrCyckJDg4OMDBg1yL1rq4uvPXWW/jkk0+Qnp6OPXv2IC0tbck8xwhZCqhfmiwZKSkp+O6771BTU4P9+/cjJCQE99xzD15++WVEREToujwAgIGBgSJ0AYBEIsH4+DhGR0fR3d2N6upqmJmZwdHRURHQllI40ycMw4DP5yuC19jYGPh8viJ8RUdHw97enrXDew0NDfjjH/+I48ePY+vWrcjPz0dMTIyuyyKELIKdryKEqCAqKgrHjh1DW1sbDhw4gISEBKSlpeHpp5/GnXfeyartJ4yMjODs7AxnZ2cAi4czIyMjcLlccLlc2NragsvlUkBTM3nwmpycVNympqYgFosV4WvlypWsDl/AlZ7XH374AQcPHkROTg4eeOAB1NTUICgoSNelEUJugIYpyZI3PDyMjz76CIcOHYKxsTF27dqFRx99FPb29rou7aakUil4PN6CgMDj8WBkZKQIZvIbGwMaG4cpGYbB3NwcpqamFoQviUQCa2vrBcHX1taWVeH9eiYnJ3HkyBG89957mJubwxNPPIFf/vKXWLFiha5LI4TcAgpjZNkQi8X49ttvcfDgQZSWluLee+/FE088gYSEBNaFmBuRB7T5YYLH48HAwABWVlawtLSElZXVgo91NZFcl2FMJBJhdnYWMzMzmJmZWfCxTCaDjY3Ngt5GGxsbvQhe81VUVOCDDz7AF198gZiYGOzevRvbtm1j1cIBQsjNURgjy1JtbS0OHz6M//mf/4G/vz+eeOIJbN++XecbcCpLKpVidnZ20fAhFAphYmKiCGaWlpYwNzeHmZmZ4mZsbKyRQKqpMMYwDMRiMQQCwYLb/McvEolgYmKiCKbzw6mlpaXeBS+5mZkZHD9+HIcPH0ZTUxPuv/9+PP744zQfjBA9RmGMLGtXv7Hde++9ePDBB5Gamsq6VXHKEovF1/QMzQ8wUqkUBgYGMDU1XRDQ5H83MjJS3AwNDa/5+41C3M3CGMMwkEqlkEgkkEgkCz6W34RC4YJ65X+XyWQwNDRcUPPVvYJLpYeIYRgUFhbi6NGjOHbsGHx9ffHkk0/q9S8QhJD/Q2GMkP9VXl6OI0eO4B//+AcsLS2xfft2PPDAAwgPD9d1aRolFosXBJ6rP746HEmlUshkMsX95wczAIpwJv9zenpacZao/OVmfuiS43A4C4Ke/CYPhYuFRbbMQ9OUhoYGfPHFFzh27BgmJyfxs5/9DDt27EBSUpJeDa0TQm6MwhghVxGJRDh79iyOHj2Kb7/9FiEhIbj//vtx3333wd3dXdflsYJMJls0pAH/F7gYhoFEIkF5eTkSEhJgZGSkCBBX97AZGRktmZ5IVQ0MDOD48eM4evQo6urqsGXLFjzwwAPYtGkTTE1NdV0eIUQDKIwRcgM8Hg9ff/01jh49itzcXKSnp+OBBx7A3XffDVtbW12Xx3psXE3JRtPT04rnWU5ODtLT03H//ffjpz/9KT3PCFkGKIwRcov6+/tx/PhxfPHFF6ivr8fmzZuxdetW3HnnnXByctJ1eaxEYez6RkdHcerUKZw4cQKnTp1CUFCQogfWw8ND1+URQrSIwhghSqivr8fXX3+NEydOoKKiAklJSdi6dSu2bNmC0NBQms/zvyiMLdTU1IQTJ07gxIkTKCoqQnR0NLZu3Yq7776bNadEEEK0j8IYISoaGBjA999/jxMnTuDcuXNwd3fHli1bsHXrVqSmpi7rELLcw5hEIkFBQQG+++47nDhxAt3d3Vi3bh22bNmCu+66i+YgEkIAUBgjRK3m5uZw/vx5nDhxAidPnoRAIMDmzZuxefNmrFmzZtkNPy3HMNbX14fc3FycPn0a33//PYyNjXHXXXdhy5YtWL9+PSwtLXVdIiGEZSiMEaIhMpkM5eXlih6ziooK+Pj4IDMzU3Fb6uFsOYSxvr4+5OXlITc3F7m5uWhra0NsbCzWr1+PrVu3IjExkVaKEkJuiMIYIVrC4/FQUFCgeNNeDuFsKYax64Uv+f9hamoqrYAkhNwWCmOE6Ig8nOXk5CjCma+vL9LS0hAXF4e4uDisXLkSFhYWui5Vafoexvh8PmpqalBRUYGKigpcvHgRbW1tiImJQWZmJtasWUPhixCiMgpjhLAEj8dDfn4+CgoKcOnSJVRUVGB8fByhoaGKcCYPaPoy70ifwtjc3Byqq6sVwauiogL19fXgcrmK731KSgpSU1PB5XJ1XS4hZAmhMEYISzEMg97e3gXhoKKiAqOjowgJCUFcXBxiY2MREhKCoKAgeHt7s+7wazaGMalUiu7ubjQ3N6OxsRGVlZWoqKhAQ0MD7OzsFgTfuLg4eHl50VYlhBCNojBGiB5hGAZ9fX2KYFZVVYXm5ma0tbXBwMAA/v7+CAoKuubm4uKik0ChqzDGMAyGh4fR3Nx8za21tRUymQx+fn4ICgpCdHS0Inh5eHhQ8CKEaB2FMUKWAIlEgs7OzkXDR09PD6ytrREUFAQvLy+sWLECK1asgJubm+LjFStWwMnJSe2r/jQRxmQyGUZHRzEwMICBgQH09/crPh4YGEB3dzdaWlowNTUFDw+PRcOpj48Pa3rqCCGEwhghS9zc3BxaW1vR3NyM3t7eawJMf38/JicnYWRkBBcXF0U4c3Z2hrW1teJmZWV1w4+NjY1hYGCw4CaVSnHy5Els2rQJhoaGkMlkkMlkEIvFmJmZwfT0NKanpxf9eP7nhoeHFfUODg5CIpGAy+UuCJPycCkPYAEBAXozt44QsrxRGCOEgM/nY3BwcEFQGxkZuWFAkn88Ozur9HUtLS0XDXZXf87Jyemanjxzc3M1fgcIIUR3KIwRQlQik8kwOzsLiUSi6Pmaf7u6t8zAwABGRkawtLSkzVAJIQQUxgghhBBCdIp+LSWEEEII0SEKY4QQQgghOkRhjBBCCCFEhyiMEUIIIYToEIUxQgghhBAdojBGCCGEEKJDFMYIIYQQQnSIwhghhBBCiA5RGCOEEEII0SEKY4QQQgghOkRhjBBCCCFEhyiMEUIIIYToEIUxQsgN7du3DwkJCbC2toazszN+8pOfoKmpSfHvnZ2d4HA4i97+9a9/Kb6uu7sbd955JywsLODs7IwXX3wREolkwbVeffVVeHh4IDU1Fc3NzVp7jIQQoksUxgghN5SXl4ennnoKxcXFOHfuHMRiMTZs2IDZ2VkAgKenJwYGBhbcXn31VVhZWWHz5s0AAKlUijvvvBMikQiFhYX4/PPP8dlnn+G3v/2t4joFBQX4/vvv8e2332L79u14+umndfJ4CSFE2zgMwzC6LoIQoj9GRkbg7OyMvLw8pKenL/o1MTExiI2NxSeffAIA+OGHH3DXXXehv78fLi4uAIDDhw/jpZdewsjICExMTHDy5El8/PHH+Ne//oVLly5h9+7dKC0t1drjIoQQXaGeMULIbZmamgIA2NvbL/rvFRUVqKqqwqOPPqr4XFFRESIjIxVBDAA2btwIHo+Huro6xd8FAgEsLCywadMm7Nu3T4OPghBC2MNI1wUQQvSHTCbDs88+i9WrVyMiImLRr/nkk08QGhqKlJQUxecGBwcXBDEAir8PDg4CAIyNjXH69GkMDw+Dy+XCxMREQ4+CEELYhcIYIeSWPfXUU7h8+TLy8/MX/Xc+n49jx47hlVdeUfoazs7OSt+XEEL0EQ1TEkJuydNPP42TJ08iJycHHh4ei37Nl19+ibm5OTz00EMLPu/q6oqhoaEFn5P/3dXVVTMFE0KInqAwRgi5IYZh8PTTT+Prr79GdnY2fH19r/u1n3zyCbZu3QonJ6cFn09OTkZtbS2Gh4cVnzt37hxsbGwQFhamsdoJIUQf0GpKQsgN7dq1C8eOHcO3336L4OBgxedtbW1hbm6u+HtrayuCgoJw6tQpbNq0aUEbUqkU0dHRcHNzw5tvvonBwUE8+OCD+MUvfoE33nhDa4+FEELYiMIYIeSGOBzOop8/cuQIduzYofj73r17cfToUXR2dsLA4NpO966uLjz55JPIzc2FpaUlHn74Yezfvx9GRjR1lRCyvFEYI4QQQgjRIZozRgghhBCiQxTGCCGEEEJ0iMIYIYQQQogOURgjhBBCCNEhCmOEEEIIITpEYYwQQgghRIcojBFCCCGE6BCFMUIIIYQQHaIwRgghhBCiQxTGCCGEEEJ0iMIYIYQQQogO/X8yTHALclpMBwAAAABJRU5ErkJggg==", + "image/png": 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Wlsb/19fXU1xcTGxsLECLJtbN7r333k457vmEhYUxduxY431XV1cGDBjQov/rN998w9ixY3F0dKS4uNh4mzRpEo2NjWzdutW47unnWFZWRkVFBWPHjm31/OLi4to1hcvhw4dxdXXF1dWVgQMH8uqrrzJ9+vQWU/x9//33GAwGZs2a1aKsHh4e9O/f39isODExkZKSEu666y5MTf9scDNnzhwcHR1bPf7cuXNbnN/+/ftJT09n9uzZlJSUGI9VU1PDxIkT2bp1q7G5tIODA7t37+bUqVOt7ru5xn39+vWtNuc+l59//pno6OgWXS9sbGy4++67ycrKIjU1tcX68+fPbzEYXfNrf6H+ziUlJZiamp53dgRHR0emTp1q7O+9evVqRo0ahb+/f5vPZ9CgQTz33HN89NFHTJkyheLiYj777DPja9TW57yxsZH169czY8YM/Pz8jPsPDQ1lypQpFyyHSqVi5syZ/Pzzz1RXVxuXf/XVV3h7exuf7+bWHevWrUOn07X5PM80e/Zsvv/+exoaGvj2229Rq9VntaYAUBSF7777jmuvvRZFUVq8x6dMmUJFRYXxb02tVhtfa4PBQGlpKXq9nsjIyFb/Hm+++eYW7/3zvTeaPwuEEKKnmzVrFhkZGWi1WvLy8li+fHmLVm4qlYp//OMf5OfnU19fz8aNGwkJCenGEgshOpsE+R7Azs4OaOpvfLECAwNb3M/IyABotS9vZyktLeWhhx7C3d0dS0tLXF1djeU4vR90a2Wsq6sjPz+/xa0znB5ymjk6OlJWVma8n56ezq+//moM0c235r6yp/dPX7duHbGxsVhYWODk5ISrqyvvvffeBc+vLQICAtiwYQPr16/n3Xffxdvbm6KiohYXXtLT01EUhf79+59V3rS0NGNZs7OzgaYxFU5namp6zib+Z5Y3PT0daAr4Zx7ro48+QqvVGs972bJlHDp0CF9fX6Kjo3n22WdbBKTAwEAeffRRPvroI1xcXJgyZQorVqxo9Xk7XXZ2NgMGDDhreWhoaIvzbHbm690c3E5/vS/G7Nmz2bBhAzk5Ofz3v//tUJeUJUuWEBERwZ49e1i6dGmLiz1tfc6Lioqoq6trdWq31p6v1tx8883U1dUZp1qrrq7m559/ZubMmcaLe3Fxcdx4440899xzuLi4cN111/HJJ5+g1Wrbdc7NYyH88ssvfPHFF1xzzTWtXrAsKiqivLyclStXnnX+8+fPB1r+PX722WcMGTIECwsLnJ2dcXV15X//+1+r76v2vDcURemxA2cKIYQQQpxO+sj3AHZ2dnh5eXHo0KGL3tfpNavtca4fr42NjS1q+Fsza9Ys4uPjWbJkCUOHDsXGxgaDwcDUqVNbHQH99DJ+9dVXxh/qzZRO6Dd/rjKfvm+DwcCVV17JY4891uq6zVeut23bxvTp0xk3bhzvvvsunp6emJmZ8cknn5w1CBq0/zWwtrZuMdja6NGjGT58OH/729/417/+ZSyrSqXil19+afXczlejfCFnlrf5NXv11VfP6m985vFmzZrF2LFj+eGHH/jtt9949dVX+ec//8n333/PtGnTAHj99deZN28eP/74I7/99hsPPvggL7/8Mrt27Wq1z35HtOX1bo2zszN6vZ6qqqrztoiZPn06Go2GuXPnotVqzzlY2/kcP37cGNiTk5NbPNbW57y9Qbo1sbGxBAQE8PXXXzN79mzWrl1LXV0dN998s3Gd5jned+3axdq1a1m/fj0LFizg9ddfZ9euXW1+v3l6ejJ+/Hhef/11duzYwXfffdfqes3nf9tttzF37txW1xkyZAjQNODjvHnzmDFjBkuWLMHNzQ21Ws3LL79svHB5uva8N8rKynBxcWnTuQkhhBBCdCcJ8j3ENddcw8qVK9m5c2enjigaHBwMwKFDh86qpT2do6Mj5eXlZy3Pzs4mKCjonNuVlZWxadMmnnvuOf7+978blzcHlguZMmUKGzZsaNO6nS04OJjq6upzjlje7LvvvsPCwoL169e3mFbsk08+6ZJyDRkyhNtuu40PPviAxYsX4+fnR3BwMIqiEBgYeN6mcc3NvY8dO8aECROMy/V6PVlZWcYwdD7N7xk7O7sLPjfQFNbuv/9+7r//fgoLCxk+fDgvvviiMcgDDB48mMGDB/P0008THx/P6NGjef/993nhhRfOeR5Hjhw5a/nhw4dbnOfFGjhwINA0ev35nhtLS0tmzJjB559/zrRp09od9gwGA/PmzcPOzo6HH36Yl156iZtuuokbbrgBaPtz7urqiqWlZat/X609X+cya9Ys3n77bSorK/nqq68ICAgwdoc5XWxsLLGxsbz44ousXr2aOXPm8OWXX3LnnXe2+VizZ8/mzjvvxMHBgauuuuqc52Vra0tjY+MF33PffvstQUFBfP/99y0uQC5durTNZTqXzMxM4+CDQgghhBA9mTSt7yEee+wxrK2tufPOO8+a9xOamsi//fbb7d7v5MmTsbW15eWXXz5rhO3Ta6SCg4PZtWsXDQ0NxmXr1q1rdWqz0zXXdp1Zu3X6iO/n4+npyaRJk1rcLpVZs2axc+dO1q9ff9Zj5eXl6PV6oOkcVSpViznds7Ky+O9//9tlZXvsscfQ6XS88cYbANxwww2o1Wqee+65s55rRVGMU/1FRkbi7OzMhx9+aCw/NE2X1tZm5iNGjCA4OJjXXnutRT/qZkVFRUBTa40zmzK7ubnh5eVlrDmurKxsUQ5oCvUmJibnrV2+6qqr2LNnDzt37jQuq6mpYeXKlQQEBLRrDILzab5olpiYeMF1Fy9ezNKlS3nmmWfafZw33niD+Ph4Vq5cyfPPP8+oUaO47777jP2x2/qcq9VqpkyZwn//+19ycnKMj6elpbX6Pj6Xm2++Ga1Wy2effcavv/56VguDsrKys95nzS0F2tsq4KabbmLp0qW8++67LcYxOJ1arebGG2/ku+++a7VlUvP5N68LLT9zdu/e3eK90hEVFRVkZGRc9MwhQgghhBCXgtTI9xDBwcGsXr2am2++mdDQUG6//XYGDRpEQ0MD8fHxfPPNN63O834hdnZ2vPnmm9x5551ERUUZ528/cOAAtbW1fPbZZwDceeedfPvtt0ydOtU4gMrnn39urCk83/7HjRvHsmXL0Ol0eHt789tvv5GZmdmRp+EsOp2u1VpbJycn7r///ova95IlS/jpp5+45pprjFPT1dTUkJyczLfffktWVhYuLi5cffXVvPHGG0ydOpXZs2dTWFjIihUr6NevHwcPHryoMpxLWFgYV111FR999BHPPPMMwcHBvPDCCzz55JPG6eRsbW3JzMzkhx9+4O6772bx4sWYm5vz7LPP8sADD3DFFVcwa9YssrKy+PTTTwkODm5T/18TExM++ugjpk2bRnh4OPPnz8fb25uTJ0/yxx9/YGdnx9q1a6mqqsLHx4ebbrqJiIgIbGxs2LhxIwkJCbz++utA05RqixYtYubMmYSEhKDX6/nPf/5jDG7n8sQTT7BmzRqmTZvGgw8+iJOTE5999hmZmZl89913mJh0zjXIoKAgBg0axMaNGy84R3pERESHamvT0tJ45plnmDdvHtdeey3QNCXk0KFDuf/++/n666/b/JwDPPfcc/z666+MHTuW+++/H71ezzvvvEN4eHib34/Dhw+nX79+PPXUU2i12hbN6qGpD/q7777L9ddfT3BwMFVVVXz44YfY2dmds1b9XOzt7Xn22WcvuN4rr7zCH3/8QUxMDHfddRdhYWGUlpayb98+Nm7cSGlpKdDUeun777/n+uuv5+qrryYzM5P333+fsLCwVi+CtNXGjRtRFIXrrruuw/sQQgghhLhkLv1A+eJ8jh49qtx1111KQECAYm5urtja2iqjR49W3nnnHaW+vt643rmmnzvXdFE//fSTMmrUKMXS0lKxs7NToqOjlTVr1rRY5/XXX1e8vb0VjUajjB49WklMTGzT9HO5ubnK9ddfrzg4OCj29vbKzJkzlVOnTimAsnTpUuN6rU3VdT5z585VgFZvwcHBLc77zOnnTp+6rdmZ56IoTVOaPfnkk0q/fv0Uc3NzxcXFRRk1apTy2muvKQ0NDcb1Pv74Y6V///6KRqNRBg4cqHzyySfG8zkd/z9lWVudPlXXmTZv3nzWc/jdd98pY8aMUaytrRVra2tl4MCBysKFC8+aUuZf//qX4u/vr2g0GiU6OlrZsWOHMmLECGXq1KnGdVqbAux0SUlJyg033KA4OzsrGo1G8ff3V2bNmqVs2rRJUZSmqe6WLFmiREREKLa2toq1tbUSERGhvPvuu8Z9HD9+XFmwYIESHBysWFhYKE5OTsqECROUjRs3tjhWa9MfZmRkKDfddJPi4OCgWFhYKNHR0cq6detarHOuc2jtfXoub7zxhmJjY3PWFINteS0vNP2cXq9XoqKiFB8fnxbTAinKn1PkffXVV8ZlF3rOm23ZskUZMWKEYm5urgQFBSnvv/9+q+/H83nqqacUQOnXr99Zj+3bt0+59dZbFT8/P0Wj0Shubm7KNddcoyQmJl5wv+d7Tzc71+tWUFCgLFy4UPH19VXMzMwUDw8PZeLEicrKlSuN6xgMBuWll14yvr+HDRumrFu37qxp/5rfA6+++upZxz/z70pRFOXmm29WxowZc8HzE0IIIYToCVSK0gkjiwkhejSDwYCrqys33HADH374YXcXp0epqKggKCiIZcuWcccdd3R3cUQ3yM/PJzAwkC+//FJq5IUQQgjRK0gfeSH6mPr6+rP6N//73/+mtLSU8ePHd0+hejB7e3see+wxXn311VZnWRB931tvvcXgwYMlxAshhBCi15AaeSH6mM2bN/PII48wc+ZMnJ2d2bdvHx9//DGhoaHs3bv3nAOOCSGEEEIIIXoHGexOiD4mICAAX19f/vWvf1FaWoqTkxO33347r7zyioR4IYQQQggh+gCpkRdCCCGEEEIIIXoR6SMvhBBCCCGEEEL0IhLkhRBCCCGEEEKIXqRX95E3GAycOnUKW1tbVCpVdxdHCCGE6HaKolBVVYWXlxcmJnK9XojeqLa2lry8PAoKCqisrKS6upqqqiqqqqqM/z9zmU6nw2AwGG+NjY2oVCpMTExa3MzMzLC1tcXGxqbFv2f+39bWFnd3dzw9PbGysurup0QIcYZe3Uc+NzcXX1/f7i6GEEII0eOcOHECHx+f7i6GEOI0BoOBEydOkJmZSV5eHnl5eZw6dcr4/+b7lZWVmJqa4ubmhr29/QUDt42NDebm5i0Ce2NjI/v37yciIgITExNjwNdqtVRXV7d6ceD0+xUVFRQWFqLX67G3t8fT0xMvLy88PT2Nt+b7gYGB+Pj4yMVDIS6hXl0jb2trCzT9WLGzs+vm0gghhBDdr7KyEl9fX+N3pBDi0lIUhaKiItLT0zl69GiL27Fjx9DpdPj6+rYIxeHh4Vx55ZUtQrKzs/NFBWOdToeNjQ1XXXUVZmZmHdqHwWCgpKTkrIsNeXl57Nixw3jhITc3FzMzM/r3709ISEiLW//+/XFxcZHWs0J0sl4d5Js/EOzs7CTICyGEEKeRH81CdL3a2lr279/P3r172bt3L6mpqRw9epSKigq8vb2NYXb06NHMnz+fkJAQAgMDOxysLzUTExNcXV1xdXUlIiLinOs1NDSQmZnZ4qLFZ599xpEjR8jLy8PBwYGQkBDCwsIYMWIEI0aMICIiQprsC3ERenWQF0IIIYQQ4lKoqalpEdr37t1LWloaLi4ujBgxguHDhzN16lQGDBhA//79sbGx6e4iXzLm5uYMGDCAAQMGnPVYVVUV6enpHDlyhEOHDrFu3Tqee+45ysrKCA0NNQb7ESNGMHToUAn3QrSRBHkhhBBCCCHOkJWVxebNm9myZQt79uzh8OHDuLq6GkPnDTfcwIgRI/D29pYWMOdha2vL8OHDGT58uHGZoiicOHGCvXv3sm/fPn755RdeeOEFiouLCQ0NJTo6mri4OCZMmICfn183ll6InqtXD3ZXWVmJvb09FRUV0rReCCGEQL4bheio5uDefDt58iRRUVHExcUxcuRIRowYgZeXV68J7Tqdjp9//vmi+shfSoqicPLkSfbu3cvOnTvZsmULCQkJ+Pn5MX78eONNgr0QTaRGXgghhBBCXHZOnDjB77//bgzuubm5REVFMX78eFauXMmoUaMuq+bx3U2lUuHj44OPjw/XXXcd0NQsPz4+ns2bN/Pee++xYMGCFsH+iiuukNk5xGVLauSFEEKIPkS+G4VoncFgYO/evfz000+sXbuWlJQUY3AfP358nwvuva1Gvi1OD/abN28mISGBIUOGcO211zJ9+nSGDx/ea1pMCHGxpEZeCCGEEEL0SXV1dWzatImffvqJdevWUVtby7Rp03j88ceZOnUqjo6O3V1E0Q62trZMmTKFKVOmAFBaWsovv/zCTz/9xFtvvYWNjY0x1F9xxRVYWFh0c4mF6DoS5IUQQgghRJ9RWFjI2rVr+emnn9iwYQMeHh5cd911fP7554wdO7bP1E4LcHJyYs6cOcyZM4eGhga2bt3K2rVrWbhwIYWFhUyePJlrr72Wa6+9FldX1+4urhCdyqS7CyCEEEIIIcTFqK6u5vPPP2fq1Kl4e3vz0UcfMXLkSBISEsjIyODNN9/kiiuukBDfh5mbmzNp0iTefvttjh8/zq5du4iKimLlypV4e3tz1VVXsXr1ampqarq7qEJ0CukjL4QQQvQh8t0oLhc6nY4NGzbwxRdf8N///pfg4GBuu+02br31Vnx9fbu7eN2uL/aR76js7GzWrFnDf/7zH7Kzs7n++uuZM2cOkyZNwtRUGiiL3kmCvBBCCNGHyHej6MsURWHPnj18/vnnfPXVV2g0GmbPns2cOXMYMmRIdxevSzU2NtLY2Iher2/1ZjAYUBSF5p/2er2etLQ0wsLCUKvVqFQqVCoVJiYmmJqanvNmYtJ3G+wqisKBAwf44osvWL16NXq9nltvvZU5c+YQGRkpA+WJXkWCvBBCCNGHyHej6Ivy8vJYtWoVn376KUVFRdx0003cdtttjBs3rlcHT71eT319vfGm1Wpb3K+vr6ehoQGdTsfpP9nPFcCbwzo0hdaCggLc3d1RqVTGkG8wGNDpdGddFGimUqkwMzNDo9Gg0WiwsLBocTt9WW+uzW5sbGTLli18/vnnfPvtt3h6ejJv3jwWLFiAu7t7dxdPiAuSIC+EEEL0IfLdKPoKg8HApk2b+OCDD1i7di0TJkzgzjvv5JprrulVo5HrdDpqamqorq42/tv8f51Oh0qlOmdQbr5/emBvrl1vy3Hb2rReUZSzgn1rFxVOX6YoCmZmZlhbW2NjY2O8Nd/vTSG/rq6OtWvX8tFHH7Flyxauu+467r33XiZMmCC19KLH6j1/YUIIIYQQos8rKytj1apVvPfee1RVVbFgwQLS0tIICgrq7qKdl16vp7KykvLyciorK42BXavVYmZm1iLkenh4YG1tjZWVFWZmZt0eFlUqlfFCQVsoikJDQwN1dXUtLk7k5+dTXV2NXq/HwsLCeM52dnY4ODhgb2+PWq3u4rNpP0tLS2bNmsWsWbM4duwYH374ITfffDOOjo7cd999zJ8/HwcHh+4uphAtSI28EEII0YfId6PorQ4ePMjy5cv5/PPPiYyMZOHChVx//fWYm5t3d9HOotfrqaiooLy83PhvVVUV5ubmxsB6eg21ubn5JQ/r3TXYXXPIbw731dXVxgscOp0OW1tb7O3tcXBwwMHBATs7ux5Ze6/Vavnuu+9YsWIF+/fv5y9/+QuLFi1i0KBB3V00IYA+UiPf0NBAQ0PDWcubB/M4fb1zae4P1JF1z+y3dCnWBVp8sbVn3eYBUTpj3dOvInfVus2Du3TGuqcP4tIT1jUYDC36pZ1JrVYbr1z3hHUVRUGn03XKuqf/fXbVunD+v2X5jGh9XfmM6N2fEed7bwrR0yiKwv/+9z9effVVEhISmDNnDvHx8QwdOrS7i9ZCbW0txcXFFBcXG0O7RqMxhnZPT08cHBywsLDo9tr17qZSqYz9652dnY3LFUWhrq7OePGjoKCAI0eO0NDQgK2tLY6Ojjg7O+Pi4oKVlVU3nkGT5oEUZ8+ezb59+1i+fDlRUVHExsby2GOPMXXq1Mv+tRbdq08E+ddffx2NRnPW8v79+zNnzhzj/VdfffWcASAgIIB58+YZ77/11lvU1ta2uq6Xlxd333238f6KFSsoLy9vdV1XV1cWLlxovL9y5UqKiopaXdfBwYGHH37YeP+TTz7h1KlTra5rZWXFY489Zrz/xRdfkJWV1eq6ZmZmPPXUU8b7X331Fenp6a2uC/Dss88a///999+Tmpp6znX/9re/GX/Ur1u3jv37959z3SVLlmBtbQ3A+vXrSUhIOOe6Dz/8sLEJ06ZNm4iPjz/nuvfffz9ubm4AbNu2jc2bN59z3bvuugtvb28Adu3axYYNG8657rx58wgICABg7969/Pzzz+dcd/bs2YSEhACQnJzMf//733OuO3PmTMLDwwFIS0vjm2++Oee6M2bMMP6YOXbsGKtXrz7nuldddRXR0dEA5OTk8Omnn55z3SuvvJLRo0cDTQMIffjhh+dcd/z48YwfPx6AoqIi3n333XOuO2rUKCZPngxARUUFb7311jnXjYqK4uqrrwaafiC9+uqr51x36NChzJgxA2gKpC+99NI51w0LC2PWrFnG++dbVz4jmshnxJ/6wmeEVqs95/pC9BR6vZ5vvvmGl19+mcLCQh5++GF++OEHnJycurtoQMvgXlxcTH19vTFohoaGSmjvAJVKhZWVFVZWVnh5eQFN4b6+vp7y8nLKysrIyspi//79WFpa4uLi0mOC/fDhw1m1ahXLli3jgw8+YO7cuXh7e/PEE09w00039cjuAqLv6xNBXgghhBBC9Hz19fV89tlnLFu2DIPBwGOPPca8efOwtLTs9nIVFhZSXFxMSUkJdXV1xuA+dOhQnJycemTz795OpVJhaWmJpaUlnp6eQNNFntLSUoqLi1sN9m5ubt022KGLiwtPPfUUjzzyCKtWreKxxx7jmWee4bHHHuMvf/lLqxWLQnSVPtFHvqioqNV+gNJstvV1pdls7242253rStN6+Yxo77ryGXFx63bkb7myshJXV1fpIy96lKqqKt5//33eeOMNXFxceOKJJ7j55pu7LRwrikJlZSX5+fnk5+dTUVGBg4MDLi4uuLi49Ing3l195Dvb6cG+qKjI+Fp5eHjg4eGBra1tt7WM0Ol0rFmzhldeeYWKigr++te/cvfdd2NjY9Mt5RGXlz4R5OXHihBCCNFEvhtFT1JSUsLbb7/NO++8w8CBA3nyySe55pprumXud4PBQHFxsTG8NzQ04ObmhoeHB+7u7n2uNrWvBPkz1dfXU1BQQH5+PkVFRWg0GmOod3Z27rb31k8//cRLL71ERkYGDzzwAA8++GCP6Soi+iYJ8kIIIUQfIt+NoieoqanhrbfeYtmyZcTExPC3v/2NuLi4S15zqtfryc/PJy8vj8LCQkxNTY2hz8XFpU/3be6rQf50jY2NFBUVGYO9Xq/H3d0dT09PPDw8LvnrqygKf/zxBy+++CL79u3j8ccf58EHH+z2Pv6ib5IgL4QQQvQh8t0oupNOp+Ojjz7iH//4B/7+/vzzn/8kLi7ukpZBURSKiorIzc3l1KlTWFpa4u3tjYeHB/b29pfNAHWXQ5A/naIolJeXk5+fz8mTJ9FqtXh5eeHj44OLi8slf91///13Hn/8cU6dOsXSpUtZsGBBr++uIXoWCfJCCCFEHyLfjaI7GAwGvvnmG55++mlMTU156aWXmDFjxiULT4qiUFFRQW5uLrm5uQD4+Pjg4+NzWYX3011uQf50zaE+NzeXkydPolKpjO8HOzu7S/q+/Pbbb3nqqadQqVS8+OKL3HjjjZfl+1F0PgnyQgghRB8i343iUlIUhQ0bNvDkk09SUFDAc889x9y5cy9ZzWNtbS0nTpwgNzeXuro6Yw2sq6vrZR+WLucgf7rmsRFOnDhBXl4eVlZW+Pj44Ovre8lmS9DpdKxatYrnnnsOb29vXnnlFSZOnHhJji36LmnfIYQQQggh2m3fvn0sWbKEpKQknnzySRYtWnRJgpHBYKCgoICsrCyKi4txdXVl4MCBuLu7S9NlcRYTExPc3Nxwc3MzjpmQm5vLkSNHcHV1JSAgAHd39y698GNmZsY999zDX/7yF/71r39x4403Eh0dzbJlyxg6dGiXHVf0bZd+WEchhBBCCNFrlZaWct999zFmzBiioqI4fvw4S5Ys6fIQX1dXx+HDh9mwYQPJyck4OTkxadIkYmNj8fb2lhAvLsjU1BQfHx9iY2OZNGkSDg4OHDhwgA0bNnDkyBHq6+u79PhWVlY88cQTHD9+nCFDhjBy5EgWLVpEWVlZlx5X9E0S5IUQQgghxAUZDAY++ugjQkJCyM7O5uDBg7zyyis4ODh02TEVRaGkpISEhAQ2btxIeXk5ERERXHnllQwYMOCSNY0WfY+lpSUDBw7kyiuvZPDgwZSWlrJhwwYSExMpLS2lK3sfOzk58dprr7F//36OHj3KgAED+OSTTzAYDF12TNH3SB95IYQQog+R70bRFRITE1m4cCGFhYW89dZbTJ8+vUubIhsMBnJzczl+/Dg1NTX4+/sTEBCAjY1Nlx2zr5E+8u1XXV1NZmYmOTk5WFtbExwcjLe3d5fOTa8oCt9//z2PPPIIPj4+rFixgmHDhnXZ8UTfITXyQgghhBCiVSUlJdx7772MGzeOqVOnkpqaynXXXddlIV6v15ORkcHGjRs5evQoAQEBTJkyhUGDBkmIF13OxsaGwYMHM2XKFPz9/Tly5AgbN27k+PHjNDY2dskxVSoVN954I2lpaUyYMIHRo0dLc3vRJhLkhRBCCCFECwaDgQ8//JABAwZw4sQJkpOTee6557qsKXtDQwNHjhxhw4YNnDhxgkGDBjFx4kQCAgKk77u45ExNTQkMDGTixImEh4eTnZ3Nhg0bOHr0KDqdrkuOaW1tzYsvvsj+/ftJT0+X5vbigrr9k/HkyZM8/vjj/PLLL9TW1tKvXz8++eQTIiMju7toQgghhBCXnfT0dObPn8/JkydZtWoV1157bZfVwNfX15ORkUFWVhYODg6MGDFCpo4TPYZKpcLb2xsvLy8KCwtJT08nPT2dwMBAgoKCsLCw6PRjhoSE8Ouvv/LDDz/wyCOP8Nlnn7Fq1SqCgoI6/Viid+vWGvmysjJGjx6NmZkZv/zyC6mpqbz++us4Ojp2Z7GEEEIIIS47BoOBt956i2HDhhEZGUlKSkqX9YWvra01jhZeXV3NyJEjGT16NG5ubhLiRY+jUqlwd3dnzJgxxMbGUllZycaNGzlw4AC1tbVdcrwbbriBlJQUwsPDiYiIYPny5VI7L1ro1sHunnjiCXbs2MG2bds6tL0M6COEEEK0JN+NoiOOHTvG/PnzOXXqFJ988gnjxo3rkuNotVqOHj1KVlYWXl5e9O/fX96nXUQGu+taFRUVpKenk5+fT0BAACEhIZibm5+1XrVWzzeJJ4gJdCbMq2Pv9d9//5077riDgIAAPv74Y6mdF0A318j/9NNPREZGMnPmTNzc3Bg2bBgffvjhOdfXarVUVla2uAkhhBBCiI4xGAy8/fbbDB06lGHDhnHw4MEuCfF6vd44cFhNTQ1xcXGMGDFCQrzotezt7YmMjGTs2LFUVVUZ56LX6/UA5JbV8sK6VEa+tInn1qaycmvGWfswGAwkJyezdetWkpOTz1njfsUVV3Dw4EFCQ0OJiIhgxYoVUjsvurdGvrlfyaOPPsrMmTNJSEjgoYce4v3332fu3Llnrf/ss8/y3HPPnbVcah2EEEKIJlIjL9rq2LFjLFiwwNgXPi4urtOPYTAYyMrK4ujRo1hbWxMWFoazs3OnH0ecTWrkL63i4mJSU1M5XFDDrgobthyvotHQFLOCXKy5e1wQt0T7GdePj49n+fLlpKWlodVq0Wg0hIaGsmjRIkaNGnXO42zatIk77riDwMBAVq1aRWBgYJefm+iZujXIm5ubExkZSXx8vHHZgw8+SEJCAjt37jxrfa1Wi1arNd6vrKzE19dXfqwIIYQQ/0+CvLgQg8HA8uXL+dvf/sb8+fN55ZVXsLa27tRjKIpCbm4uhw8fRq1WExYWhru7u/R/v4QkyF86iqIQn1HCe5sz2H6s2Lg80seG+ycOZPwAN0xM/nzvx8fHs3jxYkpLS/H09MTS0pK6ujry8/NxdHTktddeO2+Yr6qqYsmSJXzxxRcsW7aMe++9V/62LkPdOmq9p6cnYWFhLZaFhoby3Xfftbq+RqNBo9FciqIJIYQQQvQ5xcXFzJ07l5SUFNatW8f48eM7/RglJSUkJyfT0NDAwIED8fX1lZAh+iRFUdiUVsg7fxzjwIlyANQmKq4Z4sm1/S1pLM7GpCCNcncznJycgKYLae8sX06xzhz34VOwqToONM1hHxwcTEZGBitWrCA2NhYTk9Z7Qdva2vL+++9z0003MX/+fH799Vc++eQT4zHE5aFbg/zo0aM5cuRIi2VHjx7F39+/m0okhBBCCNE3bd26lVtvvZXY2Fj279+Pg4NDp+6/vr6elJQU8vLyGDBgAEFBQajV6k49hhA9gcGg8FtqPm9vOkZaXtOYXRpTE26J8uXOsUH4OlkB0NjYn4yMDOLj4/Hy8sLCLYD/bElht9OVGCa6kWvQYXc4BxOlqV+9SqXCw8OD1NRUUlJSGDx48HnLMWnSJPbv38/8+fMZOnQoX3755Xlr8kXf0q1B/pFHHmHUqFG89NJLzJo1iz179rBy5UpWrlzZncUSQgghhOgzGhsbefnll3n55Zd59dVXue+++zq1htxgMJCZmcnhw4dxc3Nj4sSJWFpadtr+hegpFEVhfUoBb208yuH8KgCszdX8ZWQAd4wJxNW2ZcthtVqNk5c/mTkGXl2fRXZFXtMDNm6oDI3YVOeiN7XAXFdt3MbS0pKCggLKysraVCZnZ2d+/PFH3n77bSZNmsTSpUtZsmTJOWvzRd/RrUE+KiqKH374gSeffJJ//OMfBAYG8tZbbzFnzpzuLJYQQgghRJ+Qn5/PbbfdRk5ODtu3b2fYsGGduv/i4mIOHjyIoihER0fj6uraqfsXoidQFIXNR4t4/bcjHDrZVANvqzFl3uimAO9gdfa0c82yS2p5fWPTiPVqExWhDgqB6lIK9m2grvLssF5XV4dGo8HR0bHN5VOpVDz88MOMGTOGm2++mT/++IN///vfuLm5tfNMRW/S7ZdqrrnmGpKTk6mvryctLY277rqru4skhBBCiMvc1q1bufbaa/Hy8kKlUvHf//63xePPPvssAwcOxNraGkdHRyZNmsTu3btbrBMQEIBKpWpxe+WVV1qs8+GHH+Lv78+wYcPO2v5ibdiwgYiICNzd3dm7d2+nhvj6+nr27t3Lrl278PX1ZcKECRLiRZ+UmFXKrA92Mv+TBA6drMTaXM2iCf3Y9vgE/jp5gDHEK4rC3uxSHv/2IC//kmbcfrifA9dGePHi9YNIfGoSPzwyGbfaLG667hrGjRvXovWKoijk5+cTFhZGeHh4u8saGRnJvn37sLe3Z+jQoWzevPmiz7+tXnnlFeMFhWbjx48/6zPw3nvvbbHdTz/9REhICAMGDGDdunWXrLx9QbfWyAshhBBC9EQ1NTVERESwYMECbrjhhrMeDwkJYfny5QQFBVFXV8ebb77J5MmTOXbsWItA+49//KNFJYWtra3x/zk5OSxbtowvv/ySkydPMn/+fFJTUy+67Hq9nmeffZa33nqLf/3rX8yfP7/TmtIrikJWVhapqam4u7tLM3rRZx0rrOKVX46wMa0AaOoDP3dUAPfGBeNk/WcNfFlNA98nnWTNnhyOFTY1kbe1MOWRSSFYmKlRqVS8c2vLi2gTJ07kueeeY+zYsdx0003s2rWLpKQk46j1Cxcu7HDTeHt7e7788ktWrlzJ1VdfzZIlS3jmmWe6dLyKhIQEPvjgA4YMGXLWY3fddRf/+Mc/jPetrKyM/9dqtSxcuJBPPvkERVFYsGABkydPxtz83C0cxJ8kyAshhBBCnGHatGlMmzbtnI/Pnj27xf033niDjz/+mIMHDzJx4kTjcltbWzw8PFrdR2VlJQ4ODgwZMgQPDw/q6uouutylpaXcfPPNnDp1it27d3eoVu9camtrSUpKoqamhqioKGm2K3oVg8FASkoKZWVlODo6Eh4e3mpYLqrS8ubGo3y5JweD0tQcflakLw9N7I+HvYVxvYO55Xwan8W6g3k06A0AWJqpuXqIJ7MifdGYnjuIjxo1iqVLl7J8+XIOHDjANddcg7e3N4cPH2b+/PkXPWCdSqXinnvuYeTIkcyaNYvdu3ezZs2aTh/gEqC6upo5c+bw4Ycf8sILL5z1uJWV1Tk/A7VaLWq1mqFDhwJgamqKVquVIN9GEuSFEEIIIS5CQ0MDK1euxN7enoiIiBaPvfLKKzz//PP4+fkxe/ZsHnnkEUxNm35+DRo0iCFDhmBvb4+5uTkffvjhRZUjNTWV6dOnM3jwYHbt2tWi9v9inF4L7+3tTXR0tMxL3g30ej06nQ69Xo9er6exsdH4/+abwWBAURTj+gDp6emo1U01wyYmJpiamp51U6vVmJqaYm5u3idnGoiPj2f58uWkpaWh1WrRaDSEhoayaNEiY2iu1zXy8fZM3v3jGDUNjQBMDnPnsakD6edmc9Y+f07O5/t9JwEI87Rjdowf04d6YWfRtr+NUaNGERsbS0pKCqWlpfj6+jJw4EC8vb1RFKVTWtEMGTKEPXv2MHv2bGJiYvjpp58YMGDARe/3dAsXLuTqq69m0qRJrQb5L774gs8//xwPDw+uvfZannnmGWOtvJ2dHfPnz8fT0xOVSsULL7zQaZ9blwMJ8kIIIYQQHbBu3TpuueUWamtr8fT0ZMOGDbi4uBgff/DBBxk+fDhOTk7Ex8fz5JNPkpeXxxtvvGFc5+OPP2bZsmVYWVldVBP1devWMWfOHB566CGeffbZThuxWmrhu56iKDQ0NFBdXU1dXR319fXU19ej1WqN/6+vrzcGc7VabQzeZ95MTEyMAbA50NfW1mJiYoKiKBgMhrPC/+kXAaCpVtTCwqLFTaPRYGFhgaWlJTY2Npibm3fqzAddKT4+nsWLF1NaWoqnpyeWlpbU1dWRlJTE4sWLefXVV6myD+KF/6WRW9bUKibCx56nrg4jOrBpXvbCqno+35XDmH4uxmVzYvwoqtJyW6wfQ30dOvR8mJiYtJhirqCggP3793Pq1CmGDh3aKd1W7Ozs+PHHH3n66aeJiYnhyy+/ZOrUqRe9X4Avv/ySffv2kZCQ0Orjs2fPxt/fHy8vLw4ePMjjjz/OkSNH+P77743rLF26lIcffhgTExMJ8e2kUpr/ynuhyspK7O3tqaiowM7OrruLI4QQQnQ7+W7sfCqVih9++IEZM2a0WF5TU0NeXh7FxcV8+OGH/P777+zevfucYXfVqlXcc889VFdXo9FoWl2nvRRFYdmyZbzwwgt8/PHHzJo1q9P2m52dTUpKCt7e3oSHh0st/EXS6/VUV1cbbzU1Ncb/6/V6LCwssLKyMobm1oK0mZlZmy/S6HQ6fv75Z6666qo2vXYGgwGdTtfi4sGZFxOaLzSYmppiY2NjvFlbWxv/39zipCcwGAzcdttt7Nu3j379+rUI24qikF5QhcXov1Bh4QmAh50Fj08bwHUR3piYqDhaUMWHW4/z3/0n0TUqTAp146O5UV1aZp1Ox6FDhzh16hSDBg3Cz8+v0y6arF69mrvvvpvnnnuORx999KL2e+LECSIjI9mwYYOxb/z48eMZOnQob731Vqvb/P7770ycOJFjx44RHBzc4WOLJj3nL00IIYQQohextramX79+9OvXj9jYWPr378/HH3/Mk08+2er6MTEx6PV6srKyOqV5a11dHXfeeSfbtm1j69atnTYqfXNtZXV1tdTCd5BOp6OiooKKigrKy8spLy+nuroaMzOzFgHYw8PDGIS7OwCbmJig0WjQaDTY29ufcz29Xt/iIkR1dTUFBQVUV1ej0+mwsbHBwcHBeLO3t++2c0tJSSEtLc3YdLtZo4kpha6RaMMGozVRY2YC947vx33jg7EyNyUhq5T3Nmfw++FC4zbD/Ry4YbhPl5fZzMyMYcOG4eXl1em187Nnz6Z///7MmDGD5ORk3n//fSwsLC68YSv27t1LYWEhw4cPNy5rbGxk69atLF++3Nj//XQxMTEAEuQ7iQR5IYQQQohOYDAY0Gq153x8//79mJiYdEowPnnyJDNmzMDc3JyEhATc3d0vep/QNO/8vn378PT0JCoqSmrh20BRFCorKykuLqa8vJyysjJqamqwsLAwBllvb28cHBw6HJp6ElNTU+zt7c8K+4qiUF9fb7x4UVRURHp6Olqt1hjuHR0dcXFxwdbW9pI0zS8rK0Or1bYIwZW2AZzyGI3OvKkZtzo/hZdvieamyU0X1x75aj8/JDX1fVepYEqYB3eNC2KEf9vnde8M7u7uXHHFFRw8eJDNmzczfPjwTvk7j4qKIjExkeuvv54JEybw/fff4+np2e79TJw4keTk5BbL5s+fz8CBA3n88cdbHWth//79AB06njibBHkhhBBCiDNUV1dz7Ngx4/3MzEz279+Pk5MTzs7OvPjii0yfPh1PT0+Ki4tZsWIFJ0+eZObMmQDs3LmT3bt3M2HCBGxtbdm5cyePPPIIt912G46OFxcIEhMTufbaa7nqqqt49913O6WZvsFgIDU1lezsbCIiIvDx6fqax97q9OBeUlJCcXExBoMBZ2dnnJyc8PHxwd7evk+E9vZQqVRYWlpiaWnZYpTy+vp6ysvLqaiooKCggNTUVNRqNc7Ozri4uHRpsHd0dESj0VBXV4fGwZ1TnmOotAsEwKyhEqfMjWiz9tHvkT/7jEcFOPG/g3ncOMKbu8cFE+hi3enlaiszMzNGjBhBTk4OCQkJBAYGEhoaetFjYHh6erJ582buvvtuoqKiWLt2bbtb9Nja2jJo0KAWy6ytrXF2dmbQoEFkZGSwevVqrrrqKpydnTl48CCPPPII48aNa3WaOtF+EuSFEEIIIc6QmJjIhAkTjPcfffRRAObOncv777/P4cOH+eyzzyguLsbZ2ZmoqCi2bdtmnO5No9Hw5Zdf8uyzz6LVagkMDOSRRx4x7qejfvvtN2666SaWLl160X1cm9XU1JCYmIiiKMTFxWFjc/YI3Ze7uro68vPzKSoqoqSkhMbGRmMQ7devHw4ODp02wGBfY2FhgYeHhzHcGwwGysvLKS4uJj8/v0Wwd3Nzw93dvVOakQOEh4czMDSUxDILGvtdi0FtDkojrsUHcCncS0aVCWYTHuVIgwND/3+bG0d4MzHUDXe7nnMhxs/PD0dHRxITEykpKSEyMrLFfOwdYWFhwWeffcayZcsYP348P/zwA1dccUUnlRjMzc3ZuHEjb731FjU1Nfj6+nLjjTfy9NNPd9oxLncy2J0QQgjRh8h3Y9+1evVq7rrrLj788MOz5rHvqJMnT7J//358fX0JDw/vk1OPdYSiKFRUVJCfn09+fj6VlZU4OTnh5uaGi4tLrwju7R3srrucHuwLCgooKyvD3t7eGP7t7Ow6fMEqs7iG+z7ZzuGSphH/NVWn8D61hVqDmgL3GBQnfwAGetjyy0Nje/xI/I2NjRw6dIiTJ08ydOhQvLy8OmW/n332Gffffz+ffPJJpw2YKbqe1MgLIYQQQvRwb775JkuXLuWHH35g8uTJF72/0wNB88BalzuDwUBRUZExvOv1etzc3AgODsbd3R1zc/PuLmKfZGJigpOTE05OToSEhKDVaikoKCA/P5/09HTMzc2Nod7FxaVNF1AMBoVP4rN4df1h6nUGNGrwKkqg6EgiWf0mYnANAcBcDfNHB3H3uKAeH+KhaerBiIgIXFxcSEpKori4uFMuwM2dOxcXFxduueUWioqKWLhwYSeVWHQlCfJCCCGEED2Uoig88cQTrFq1ik2bNhEVdfFTX9XU1LBnzx7UajXjx4+/6Ca6vZmiKJSWlpKbm8vJkycxNTXFw8ODYcOG4ezsLC0UuoFGo8HPzw8/Pz8aGxuNTfCTkpIwGAx4e3vj4+ODo6Njq+H7RGktf/3mAHsySwEY3c+ZV24Ywvf7+vPmxqa/H1MTmBPjz8Ir+uFm23Oa0LdV8+CJCQkJbNu2jejo6Iv+O7766qvZsGEDV199Nfn5+fzjH//oFRc3LmcS5IUQQggheiCdTsddd93Fli1b2LFjByEhIRe9z6KiIhISEoxN6Xt68/CuUlVVRW5uLrm5ueh0Ory9vYmJicHJyUnCSw+iVqtxd3fH3d2dIUOGUFJSQm5uLjt37kSj0eDj44OPjw82NjYoisI3ibk8tzaFmoZGrMzV/O2qUObENM3DPjLYhbc2pXP9UG8euTIEX6fefQHL2tqacePGkZyczJYtW4iKisLFxeWi9hkbG8v27duZMmUK+fn5vPfee90+LaI4N+kjL4QQQvQh8t3YN9TU1DBr1ixyc3P55ZdfLrrpu6IoZGZmkpqayuDBg/H39++kkvYeDQ0NnDhxghMnTlBVVYWHhwc+Pj64ubn1yZr33tJHviMaGxspKCggNzeXgoICVBa2rMlQsSOrGoAof0fG9nfF0lzNXeOCjNudKK3t9QG+NVlZWRw6dIhBgwYREBBw0fvLzc1lypQp9O/fnzVr1nTa4IOic8klFiGEEEKIHqS8vJxp06Zhbm7Oli1bcHBwuKj9GQwGDh48SH5+PqNGjcLJyalzCtoLKIpCWVkZWVlZnDx5EgcHBwIDA/Hy8upz4fZyolar8fLywsvLiy2H8/nr1wcortWjVilMDLQis0rLGxuPYmFmwjURnnjaNwXRvhjiAQICArCxsSEhIYHKykoGDRp0Ua1tfHx82LZtG9OnT2fKlCmsW7dOLgz3QJdneyohhBBCiB6otLSUSZMm4eLiwvr16y86xGu1Wnbs2EF5eTlxcXGXTYjX6/VkZ2ezefNmdu7ciampKXFxcYwdOxZ/f38J8X2AvtHAq+sPM++zvRTX6vF3smRkkBO/Ha8jvagWazO4J8YdJ8vLo97SxcWFuLg4SkpK2LlzJw0NDRe1PycnJ3777Tesra2ZPHky5eXlnVNQ0Wmkab0QQgjRh8h3Y+9VUlLCpEmT8Pf35+uvv77oUdIrKirYvXs3jo6ODBs27LLo61pbW8vx48fJycnB0tKSoKAgvL29L4tzP1NfblqfV1HHA6uTSMwuA2CEnwOHC6qo0TaiUsGtUb7cHGZFyakc6uvr8ff3Jygo6LJoIq7X69m3bx8VFRXExMSc/T2gKKDXglnbBvmrr6/npptuoqCggN9++w1HR8cuKLXoCAnyQgghRB8i3429U1FREZMmTTL2Sb3Y4HXq1Cn27dtH//79CQkJ6fMDuFVVVZGens7Jkydxd3cnKCgIZ2fnPn/e59NXg/yWo0U8/GUSZbU6bDWmLJ4ygBd/TqNBbyDC14HnrwtniI8D0NS1oqSkhIyMDAoLC/Hx8aF///7Y2Nh070l0Jl0dVOVDTRFUF0BNEUp1EWWnjlFXnIuLtRqNoRbqyqG+ArSV0NgAz5SAum0XuLRaLTfffDM5OTls2LABZ2fnrj0n0SaX3+VJIYQQQogepLi4mPHjx+Pv78/q1asvOnRlZmaSkpLCiBEj8PT07KRS9kxlZWWkp6dTUFCAj48PEyZM6FshTRgZDAr/+j2dtzeloygwyNuOFbOH4+9sTYPegIW5mtnRfqhN/rx4o1KpcHFxwcXFxXix548//sDDw4P+/ftfdNeVLmcwQHU+lGVDeQ5U5ED5Cag8CZWnmm715WdtpgKMnWhKz7FvbSVYta2rjUaj4auvvuLaa6/liiuu4I8//rhsuun0ZFIjL4QQQvQh8t3Yu5SUlDBx4kSCg4NZsGABgYGBhIaGdqgmWVEUjhw5wvHjx4mNje2zP7QVRaG4uJj09HRKS0sJCAggODj4smg23R59qUa+olbHw18l8ceRIgDsLEz5aG4k0YHtrxmura0lIyOD7OxsnJ2d6d+/f/e33qgphqIjUJIOJcegJKPpVp4N+voLb29qATZuYOMO1m5g7QxWLmDlRFWjGYdzCnH3C8G3/yBUlg6gsQONLbTxnBVFISUlhezsbD744ANOnjzJxo0bpZl9N5MaeSGEEEKIblBWVsaVV15Jv379WLNmDfX19ezYsQOg3WFeURQOHDhAQUEBY8aM6bMXcUpKSkhNTaWqqoqgoCAiIyMveiwB0bMdya/i7v8kkl1Si9qkqZK6sl7PO78f4z93tD/IW1lZMXjwYEJCQjh+/Dh79uzBzs6OsLCwrr/4pa2CglQoSIbCtD9vdeeqNgdUarD3Bgd/cPADe9+m+3beYOcFtp5gYX/OUG4LhFRUsHPnTsoLDQwe7N3uz5aUlBROnjxJXFwcV155JTfddBNTpkxhw4YN2Nvbt/NJEJ1FauSFEEKIPkS+G3uH8vJyrrzySnx8fPj666+NNaZVVVXs2LEDPz+/Nof5xsZG9u7dS1VVFaNGjeqTNdMVFRWkpaVRUlJCv379CAoK6vW1zF2tL9TIr0/J55Gv9lPb0IipiQq9oSm23Bzpy9+uDsXe8uLPS6fTkZGRwbFjx3B1dSU0NLRzPjvryuFUEuTth7wDTbfS4+dYWQUOvuASAs79wTkYnILAKbApuKsv/jxramrYuXMn9vb2DB8+HLVafcFtTg/xo0ePNnZb0Wq13HDDDZSWlrJ+/Xr5rukmEuSFEEKIPkS+G3u+uro6pkyZgp2dHd9///1ZNcrtCfM6nY7du3djMBiIjY3tc7XTNTU1HD58mFOnThEYGEj//v3RaDTdXaxeoTcHeUVRWPHHMV777WiL5e52Gl65cQgTBrh1+jG1Wi1HjhwhOzsbb29vBg4ciJVVG+edNzRCQQrk7oETCXAysamJfGtsPcF9ELiHg1souA5sCvDmXT/HvVarZdeuXZiamhIdHX3e98W5Qnyz+vp6rrvuOnQ6Hb/88ov8XXYDCfJCCCFEHyLfjT2bXq9n5syZFBUV8dtvv50zKLQlzNfV1bFr1y4sLS2JjIzsU1OsabVajh49SlZWVvtDlQB6b5Cv1zXyxHcH+e/+Uy2WzxjqxXPTB2Fv1bXn0nzxKC8vj4CAgNYvHum1cHIvZO2AnJ1wYg80VJ29M8cA8BoGnkPBMwI8hjT1X+9Ger2ePXv20NDQQGxsLBYWZ09Dd6EQ36y6upqJEyfi5+fHl19+2aZaftF5JMgLIYQQfYh8N/ZciqJwzz33EB8fz9atWy/YH/d8Yb62tpYdO3bg7OzM0KFDMTEx6eriXxIGg4HMzEwOHz6Mi4tL5zVzvgz1xiBfWtPA3f9OJDG7DLWJimenh5GQWcakMHemR3hd0rJUVFSQmppKWVkZoQNCCNCUozq+GTK3NAX3MwehM7cFn0jwjQafKPAa3u2h/VwMBgNJSUmUlZUxevToFt1x2hrimxUXFzNmzBgmTZrEO++8c1lP+Xip9Z1Lt0IIIYQQPdjSpUv59ddfiY+Pb9OgWra2towePfqsAfBqamrYsWMHHh4eDB48uM/8cC4pKeHgwYMYDAaioqJwc+v85tOi58ouqeH2VXvILqnFRqPm/dsiGdPfhb/EBnRLeeypZqT5UeqLf0a9dxuqxpqWK1i7gv/o/7+NBLcwMOkdNdImJiYMHz6cAwcOsH37dkaPHo2VlVW7QzyAi4sL69evZ9SoUXh6evLUU09dgjMQIEFeCCGEEKLLrVixghUrVrB9+3Z8fHzavN2ZYd7X15f4+Hi8vLwYNGhQnwjx9fX1pKSkkJeXx4ABAwgODu4zLQxE2+w/Uc68VXsor9MBMLqfC2P6u1zaQhgMTc3lj/wM6RuaRpYHmhueN5rZUGg9EL3vaNxjZ2LuNajN07f1RCqVioiICA4ePMj27dsZNWoUWVlZ7Qrxzfz9/fn1118ZN24c7u7u3HnnnV1YctFMgrwQQgghRBf65ptveOKJJ9iwYQOhoaHt3r45zG/bto3jx48TEBBAeHh4rw/xpzejd3NzY+LEiX1yxP22MhgMpKSkUFZWhqOjI+Hh4ZfFBY0/jhRy978T0TU29fZ1sTFn3qjAS3NwfQNkboW0n+DIL1BTeNqDqqam8v0mQfBE1F7DsNc2cOjQIZIPnGCg1prAwMBe/XeoUqkYMmQIycnJbNmyBRMTE8aOHduuEN9s8ODB/PTTT0ybNg1XV1euu+66LiixOJ0EeSGEEEKILvL7778zb948vv76a2JjYzu8H5VKZQwMvTk4NKuoqCApKYnGxkZpRg/Ex8ezfPly0tLS0Gq1aDQaQkNDWbRoEaNGjeru4nWZ7/bmsvibAzQP2BUT6MTy2cNxte3CEdD1DXB8M6R8D4d/Bm3Fn49p7JqCe8jUpn/P6ONuZdU02ntBQQHJycnk5OQwfPjwXj+Og0qlQlGUFp8zHTF27Fg+//xz5syZwy+//MLYsWM7sZTiTBLkhRBCCCG6wIEDB7j++ut59913ufrqqzu8n+Y+8b6+vvj5+REfH49KpWrzPPM9icFg4OjRoxw7dozg4GAGDBhwWdQ6n098fDyLFy+mtLQUT09PLC0tqaurIykpicWLF/Paa6/1yTD/3uZj/PPXI8b798YFsWTKQNQmXfCeNhggewckfw2pP0L9aeHd2g1Cr4GB10DAWDC98BSO7u7uuLi4cOTIEbZu3UpISAj9+vXrde/l5j7xp06dIi4ujszMTOLj44195jtixowZvPnmm0yfPp3t27cTHh7eyaUWzSTICyGEEEJ0ssLCQqZPn86SJUuYO3duh/fTPDq9l5eXsTl9awPg9QbNtfCKojBmzBgcHBy6u0jdzmAwsHz5ckpLS+nXr5/xtbSxsSE4OJiMjAxWrFhBbGxsrwuJ57Pij2O8ur4pxJuaqHjn1mFMG+zZ+QcqOgIH1sDBr6Hy5J/LbdwhbAaEzwDfmA4NUqdWqwkLC8PT05N9+/aRl5fHsGHDek3tfGsD2w0ePBhFUdixYwdjxozpcFeXu+66i9zcXKZPn86ePXtwdu6Zo/f3djL9nBBCCNGHyHdj92toaGDixIl4e3uzZs2aDgft+vp6tm/fjpub21mj07dlnvmewmAwkJ6eTnp6utTCnyE5OZnbb78dBweHVvslV1dXU15ezr///W8GDx7crn33xOnnFEXhjQ1Heef3YwDMjPThrjGBhHh04meVtgoOfQf7/gMnE/9cbmEPYdfB4JlNI8134gjzjY2NHD58mMzMzF5RO3++0ekVReHAgQMUFxczduxYNJqOdXMwGAzMnDmTsrIy1q9f32Peg32J1MgLIYQQQnQSRVFYuHAhtbW1rFq1qsMBW6fTsWvXLhwdHVudYu5cU9P1NJWVlezbtw+DwSC18K0oKytDq9Wes+bT0tKSgoICysrKLnHJOp/BYGD2h7vZlVkKwN+uGsjd44I77wCnkiBxFSR/B7r/nypOpYb+kyHiFhgwDUy7pu+9Wq0mPDwcT09PkpKSyMvLY/jw4dja2nbJ8S7GhaaYax7NPjExkV27djF69GhMTdsfGU1MTPjss88YPXo0jz76KO+8805nnYL4fxLkhRBCCCE6yYoVK1i7di0JCQkd7mPa2NjInj170Gg0DBs27JwBvSeHeUVRyMnJITk5maCgIAYMGIBa3Tvm2L6UHB0d0Wg01NXVtVojX1dXh0ajwdHRsRtK13l0+kauXb6Dw/lVADw8sX/nhHhdfdOgdXtWNgX5Zs79YfhfIOJWsLl0Ayk6OTkxfvx4Dh8+zJYtWxgyZAh+fn6X7PgX0tZ54lUqFcOHD2fXrl0kJCQQExPToRYGNjY2/Pjjj0RFRTF48GDuvvvuiz0FcRoJ8kIIIYQQnWDTpk08/vjjbNy4EV9f3w7tQ1EU9u3bh16vZ/To0Rf88dwTw7xOp+PgwYMUFRURHR192Y9Ifz7h4eGEhoaSlJREcHBwi9dOURTy8/MZPnx4rx4wrLpex1X/2kZOaR0AVw324KFJ/S9up1X5sOdD2PsJ1JY0LVObNzWdHzEf/Ed12xzvzbXzLi4u7Nu3j+LiYoYMGdKhWu3O1NYQ30ytVhMdHc2OHTtISkpi+PDhHfpsCQgI4LvvvmPatGkMHDiQcePGdfQUxBmkj7wQQgjRh8h3Y/fIyMggKiqK119/nfnz53doH4qikJycTGFhYbv7pvaUPvPl5eUkJiZiaWnJiBEjsLCw6JZy9CbNo9aXlZXh4eFhHLU+Pz8fR0fHFqPWK4qCTqejvr4erVZr/NdgMKAoCoqiGP+v1+vJysoiKCgItVqNiYmJcXoxExMTNBoNFhYWxpupqWmnv29KqrVMe3sbhVVaAObE+PHi9e3r699CQQrEvwPJ34JB17TMzgeiFsDwuWDt0gml7jx1dXXs27eP+vp6IiMjsbe375ZytDfEn66+vp5t27bh6enJoEGDOlyGlStX8tRTT5GQkEBAQECH9yP+JEFeCCGE6EPku/HSq6ysZOTIkUyZMoU33nijw/s5evQox48fZ9y4cR1qlt+dYV5RFDIzM0lNTaV///6EhIR0e8uA3iQ+Pp4VK1ZQWFiIlZUVTk5OBAUFER0djaOjozG019fXYzAYUKvVxgBubm6OWq02BvTmsK4oCllZWfj7+xvvN4f8xsZGtFqtcb+NjY2YmJi0CPZnBn1LS0tsbGza/LqeKK1l+vLtlNU2Be47xwTy9DVh7X9yFKVp6rjtb8GxDX8u942F2Puapo1T99xGxoqicOTIEY4dO8agQYOMr8elPH5HQ3yz6upqtm/fTr9+/ejXr1+Hy7Jw4UK2b9/Ojh07OlQO0ZIEeSGEEKIPke/GS8tgMDBjxgy0Wi3/+9//Otx8Njs7m0OHDjFmzJiLqrXrjjCv0+lISkqirKyMyMhImWqqDQwGg3FE+uZbRUUFiqKgUqkwNzfH2dm5RZA+PVy3pfa8raPWN9feN18oOP2iQfP9uro66urqUKlU2NvbY29vj4ODg3G0/da6gMz5cBc7Mpqavd8zLpAnr2pniFcUOLYRtr4GJ3Y1LVOZNDWfH/UAeI9o3/66WVFREXv37sXFxYWhQ4dekqb2nRHim5WXl7Njxw4GDx7c4X7/Op2OyZMn4+TkxLfffisX+y5Sz718JYQQQgjRw73xxhskJyezb9++Dv8wLygoIDk5mdjY2Ituenup+8zX1NSwe/duNBoN48eP7/BUVX2ZwWCgqqrKGNbLy8uprKwEMAbiwMBA7O3tsbW1veThRqVSYWZmhpmZ2XlHWVcUpcV5ZGdnc/DgQQDs7OyMwd7BwYGN6RXGEL9gdDtDvKJA+gbY/DKc2te0TG0Ow25rCvBOQR0+1+7k6urKhAkTSExMZNu2bcTExHR4QMy26MwQD+Dg4EBUVBR79uzBwsKiQ2NfmJmZ8c033zBs2DDeeecdHnzwwYsq0+VOgrwQQgghRAfs2rWLpUuX8scff3R4VPGqqioSExMZOnQoLi6d07/3UoX5oqIiEhIS8PX1JTw8vEfPm30pGQwGSktLyc/Pp7S0lIqKClQqlTHkBgYGGmuye1ONpEqlws7OrkVLn+Zw33yBYldqJhkFVXyYBqBi+kBb7h/phsFgaNv74/hm2PT8n/O/m1pC1B1NAd7WoytO65LSaDSMHDmS5ORktmzZQnR0dJe0YOnsEN/Mzc2NIUOGkJiYyLhx4zq0XxcXF9asWcPkyZMZNWoUkZGRnVK2y5EEeSGEEEKIdiorK+OWW27h+eefJzo6ukP7aGhoYPfu3QQGBuLj49Op5evqMJ+ZmUlKSgqDBw/G39+/0/bbW+l0OgoLC8nPz6egoAATExPc3d0JCgrC3t6+14X2tjo93BcarFn69Uka9CYYUJgc4sDtgy1ISEgAmkKgp6cnrq6uZzf1P7kPNi6FzK1N900tIfpOGPUQ2Lhe4rPqWiYmJkRERGBnZ8fOnTs7/W+oq0J8Mz8/PyorK9m9ezfjxo07b7eNcxkzZgzPPPMMN998M/v27eu2QQB7O+kjL4QQQvQh8t3Y9RRF4cYbb0Sn0/HTTz91KKAZDAZ2796NiYkJ0dHRXRbyOrvPvMFgIDk5mVOnTnVZbWJvUVtbS35+Pvn5+RQXF2NjY4OHhwceHh44Ojp2e3Bvax/5zrA3u5TbPtpDna4RgNH9XPh0fhRmahMURaGsrIy8vDwKCgqorq7GxcUFDw8PPC0asIxfBoe+a9qR2rxp+rixfwVb9y4tc09QXFxMQkIC3t7eDBo06KJbtXR1iG/W/PmlUqmIiYnp8Gfg1KlTcXR05Msvv+z2v5feSGrkhRBCCCHaYcWKFSQkJLB///4O//hMTU2lrq6OsWPHdukP2M6smW9oaGDPnj3o9Xri4uK6tH9vT9QcSJtr3auqqnB2dsbDw4OIiAisra27u4jdIimnjNs//jPEh3nasvIvIzBTN4VSlUqFk5MTTk5OhIeHU11dTdGJY5hteQHznB9B0aOgomHg9ZhPeRaV4+XTwsPFxYVx48axe/dudu7cSXR0dIcvulyqEA9NrQoiIyPZsmULaWlphIW1fzYCExMT/vOf/zB06FA+/PBD7r777i4oad8mQV4IIYQQoo2SkpJ4/PHHWb9+fYdro3NycsjJySEuLq7La0qhc8J8XV0dO3fuxNramtjY2Esy4nZPUVNTQ3Z2NidOnKCxsRF3d3f69++Pu7v7JXn9erJDJyu4fdUeahqaQrynvQWfLojGWnOO94fBgM3RH7DZ9BzUFAFQ7zWSjH7zyaqzwXTPYfz8avHz87tsLoxYW1szduxY9u7dy/bt24mNjcXS0rJd+7iUIb6ZmZkZMTExbN26FTs7uw51D3J3d+eLL75g+vTpjBw5ksGDB3dBSfuuy+dTWAghhBDiIlRVVTFr1iz+9re/MWbMmA7to7S0lIMHDxITE3NJg8rFhPmqqiri4+Nxd3dnyJAhl8Wgdo2NjeTn55OVlUVJSQkeHh4MHToUV1fXy+L82+JYYRW3r9pDVb0eABtzNZ8tiMbN1qL1DU7ug//99c+R6J37w5QXseg/mXCVilCDgcLCQrKzs9m0aRMuLi4EBATg4eHR559zMzMzoqOj2b9/P9u2bWPUqFFtDuPdEeKb2draGkeyt7a27tCgn1dccQWPPvoos2bNIjEx8bK5gNMZpI+8EEII0YfId2PXUBSF2267jcLCQn799VfUanW791FXV8eWLVsICQkhKKh7ptBqb5/50tJSdu3aRVBQEAMGDOjz/VhramrIzMzkxIkTmJmZ4e/vj6+vLxYW5winPVhX95HflFbA3f/eS6OiYKKCT+dHMy6klYHp6srh9xcg4SNAAXNbGP84RN8Dpuat7ru+vp6cnByys7PR6/X4+fkRGBjY57tzKIpCWloa2dnZxMbGXjAYd2eIP92xY8fIyMggLi6uQ38rer2eiRMnEhgYyKefftr5BeyjpEZeCCGEEOICvvzySzZs2MDBgwc7FOINBgOJiYm4u7sTGBjYBSVsm/bUzOfn55OYmEh4eHi3lrmrKYpCcXExx48fp7CwEA8PDyIjI3FxcenzFy6aGQwGUlJSKCsrw9HRsU3TCapNVDT+f33g368Jaz3Ep/4EPy+B6vym+4NnwuQXLjiVnIWFBSEhIfTv35+ioiKysrLYtGmTcSYAZ2fnPvnaqFQqwsLC0Gg07Nixg+jo6HPO195TQjxAcHAwFRUVJCYmMnr06Ha/NqampqxevZohQ4bw3XffceONN3ZRSfsWCfJCCCGEEOeRn5/PokWLWLlyJR4eHZvL+vDhw+h0OgYPHtztAaQtYT4nJ4eDBw8yfPhwvLy8uqOYXa6xsZHc3FyOHz9OXV0dAQEBDBkypN39k3u7+Ph4li9fTlpaGlqtFo1GQ2hoKIsWLWLUqFEt1q1t0FNVr6euoZEH1yQBcEuUL3NHBbTcaVUB/O9ROLyu6b5TMFzzBgSNb1fZVCoVbm5uuLm5UVtbS2ZmJnv27MHKyoqgoCC8vb07dGGtpwsODkaj0bBnzx4iIiLw9fVt8XhPCvHQ9DpFRESwZcsWjhw5wsCBA9u9D29vb9555x3uu+8+xo0bh6tr35p2sCtI03ohhBCiD5Hvxs6lKAo33HADFhYWrFmzpkP7KCwsZM+ePYwbN65HvSbnamZ//Phx0tLSiI6O7pM/phsbG8nKyiI9PR1zc3OCgoLw8fHplgH8OlIT3lZtaVofHx/P4sWLKS0txdPTE0tLS+rq6sjPz8fR0ZHXXnvNGOb1jQbu/s9eUvMqsTA1IaukluF+Dqy5OxaN6f+HaUWB5G+aauHry8HEFEY/DOOWgFnndE/Q6/WcOHGC48ePo9PpCAkJISAgoE/2oy8sLCQhIYGwsDBjq5ieFuJPV1FRwbZt24iJienQZ0fz1J5mZmZ89dVXXVDCvkVq5IUQQgghzmHNmjXEx8eTkpLSoe3r6+vZu3cvQ4YM6VEhHlqvmT9+/DiHDx9m5MiRODk5dXMJO5eiKOTm5nL48GHUajVDhw7F3d2921pItKcmvCsYDAaWL19OaWkp/fr1Mz4PNjY2BAcHk5GRwYoVK4iNjUWlUvHs2hR+P1yIiQoMCrjYaHjvthF/hviaElj3EKStbbrvGQHXvQsegzq13KampgQGBhIQEEB+fj5paWlkZGQQGhqKt7d3t7d46Uxubm7Exsaya9cuFEUhMDCwx4Z4AHt7ewYNGsTevXuZMGECGo2mXdurVCree+89wsPD+fbbb7npppu6qKR9Q7fWyD/77LM899xzLZYNGDCAw4cPt2l7qXUQQgghWpLvxs6Tn59PeHg4H330Eddff327t1cUhfj4eCwsLBg+fHiPDRjNNfO2trZUVFQwcuTIDo0+3VMpikJBQQFpaWnodDoGDhyIr69vt74e7akJ76gL1cgnJydz++234+Dg0GogrK6upry8nH//+98kVNjwj3WpqACFpv7xq++MISbo/6dgTN8A/70fagqbauHjnoAxD4O666fnUxSFnJwcDh8+jEajISwsDFdX1x7799YRpaWl7Ny5E3t7e2pqanpkiG+mKAqJiYno9XrjRaD2+vLLL3nwwQdJSUnpk62COku3t0EJDw8nLy/PeNu+fXt3F0kIIYQQlzlFUbj33nuZMmVKh0I8wNGjR6mrq2PIkCE9OlTY2tri6+tLcXExHh4eODg4dHeROk1paSk7duwgKSkJPz8/Jk6ciJ+fX7e+HmfWhNvY2KBWq4014WVlZaxYsQKDwdClZUhMTKSsrAy9Xk9r9XqWlpZotVo2Hynihf+lAmBi0vS8PTZlQFOI19XDL0/AFzc1hXjXgXDX7xC35JKEeGiqxfX392fSpEn4+PiQmJhIfHw8paWll+T4l4KjoyPu7u6UlJTg5+fXY0M8NL0eQ4cOpbq6mmPHjnVoHzfffDNjx45l4cKFnVy6vqXbm9abmpp2eOAYIYQQQoiusHr1anbt2tXhJvXFxcWkp6czduzYLpn6qzNlZGSQnZ1NVFQUBw8eJC0trV3zzPdElZWVpKWlUVRURHBwMDExMT3mdUhJSSEtLQ1PT8+znmOVSoWHhwepqamkpKQwePDgTj9+c5P+ffv2kZ+fT3FxMfb29gQGBrZoiVFXV4epkzfvHajHoICNxpRqrZ6JA924e1wQlGTAN3MhP7lpg5h7YdJz5+0L35VjAqjVavr164e/vz/p6enEx8fj5uZGaGgotra2nXKM7tDcJ76kpITIyEj279+PhYVFj55JwszMjMjISHbs2IGzs3O7u+moVCreffddwsPD+eabb5g5c2YXlbR36/Ygn56ejpeXFxYWFowcOZKXX34ZPz+/VtfVarVotVrj/crKyktVTCGEEEJcJvLy8njggQdYtWoVzs7O7d6+oaGBvXv3Eh4ejr29fReUsPM094kfNWoUjo6O2Nratmlqup6qrq6Ow4cPk5uba6yl7WlzwJeVlaHVas85Or6lpSUFBQWUlZV1+rFPb9Lv4eFBZWUl5eXllJeXk5qaSlhYGI6OjiiKQn5+PhaTH6FSp+BsbU5JTQOe9ha8NjMCVcr38NOD0FANVs4w4z0ImXLBY1+KMQHMzMwICwsjKCiII0eOsHnzZnx9fRkwYECvm5GgtYHtLC0t2blzJyqVioCAgO4u4jk5OjoSGhpKYmIi48ePx9zcvF3bu7u7s2LFCu6//37i4uLOOQ3f5axbm9bHxMTw6aef8uuvv/Lee++RmZnJ2LFjqaqqanX9l19+GXt7e+PtzKkYhBBCCCEu1n333ce0adOYMWNGh7Y/ePAgDg4OPfpHNsCJEydIS0tr0Se+eQC8nJwc0tLSWm1y3RMZDAaOHDnCpk2bMBgMXHHFFQwZMqTHhXhoCjgajYa6urpWH6+rq0Oj0XT6OAVnNum3tbUlMDAQCwsLVCoV9fX1HD9+nKqqKjIyMnB0dGTZDWGMDHampKYBExW8PTMcx21L4dsFTSHefzTcu71NIX7x4sXs3bsXU1NT7OzsMDU1Zd++fSxevJj4+PhOPVdomos+IiKCCRMmoNPp2LRpE0ePHu3SLgud6Vyj0zs5OREbG8uhQ4c4efJkN5fy/IKCgrC1teXQoUMd2n7WrFnExcXxwAMPdHLJ+oYeNf1ceXk5/v7+vPHGG9xxxx1nPd5ajbyvr68M6COEEEL8Pxns7uKsXbuWefPmceTIEVxcXNq9/alTp9i/fz9XXHFFjwyRzZqnxIuOjm61putcU9P1RBUVFSQlJWEwGBg2bFiPH6jPYDBw2223kZSURHBwcIvnVlEUMjIyGD58OP/5z38uqtn5mYPdnWtwu9LSUrKysqioqECv1xMQEMCIESNYuHAhgeHDmPLmVirr9Tw+xpH7Cp+HnP8P3WMegQlPg/r8DXybz3fHjh3o9Xqqq6sxGAyYmJhgY2ODqakpY8aMuejzvZDS0lKSkpIwNTVl2LBhPfrzsS1TzOXn55OYmNjhqd4ulbq6On7//XdGjBjRoe7UBQUFDBgwgK+//prJkyd3QQl7r24f7O50Dg4OhISEnHNgBI1Gg52dXYubEEIIIURnqKur46GHHuLll1/uUIjXarUcPHiwx9YENysrK2PPnj0MHTr0nM1Ve0PNfHMt/LZt23B3dycuLq7Hh3gAExMTFi1ahKOjIxkZGVRXV9PY2Eh1dbWxJnzhwoWdHmrP1aTfycmJYcOGMWzYMDw8PLj5gae58v4XiImJZck3B6ms13O9RxH3Hr2zKcSb28LNX8CkZy8Y4qFpTIDExETKy8upqKjA1NQUS0tLTE1NqaiooLy8nISEhA6PR9FWTk5OjB8/HhcXF7Zu3dpja+fbOk+8h4cHQ4YMYc+ePZSXl1/aQraDpaUlgwcPZv/+/TQ0NLR7e3d3d55//nkeeOCBFhW6oocF+eYPME9Pz+4uihBCCCEuM8uWLcPZ2bnVVoFtkZycjKOjI97e3p1css5TXV3Nrl27CA0NxcfH57zr9uQwX1lZydatW41hJzQ0FLVa3d3FarNRo0bx2muvMWzYMMrLy8nKyqK8vJzhw4d3ytRzrTlfk36VSoWpqSn27j6sLXbh2bWpPPrNAbYfK+Y6sz28Xv04qsqT4NyvaVT60GvafNySkhIKCgpobGzEysoKU1NT4/GsrKxobGykoKCAkpKSzjzdVqnVasLDwxk1ahQnTpxg27ZtPWrMrbaG+GZ+fn6EhISwa9cuampqLlEp28/X1xcHBweSk5M7tP19992HhYUFb775ZieXrHfr1sHuFi9ezLXXXou/vz+nTp1i6dKlqNVqbr311u4slhBCCCEuM8ePH2fZsmX88ccfHQqEp06dorCwkCuuuKLHNkOvq6sjPj4ef39/goOD27RNc5jvKQPgGQwG0tPTSU9PJygoiAEDBvSqAH+6UaNGERsb22WjuJ8pPDyc0NDQczbpz8svwGLyI5TWNRLgbMVvKXncr/6Rx9RfgR7oNwlu/BgsHdp13JKSEhoaGox98U+nUqkwMzOjvr7+kgT5Zs2184cPH2br1q2EhITQr1+/Lm3afyHtDfHN+vXrh1arZefOnYwZM6ZHtgZSqVRERETwxx9/kJ+f3+4m9qampqxYsYKpU6cyZ84cGSft/3VrjXxubi633norAwYMYNasWTg7O7Nr164e3c9DCCGEEH3Pww8/zJw5c4iOjm73tlqtlgMHDvToJvU6nc74Gys0NLRd2/aUmvkza+HDwsJ6bYhvZmJiwuDBgxk3bhyDBw/u0iB5oSb95oMmU27phYWZCc6Wap5RVvKY2VdNG8fcC7d+1e4QD+Ds7Iy5ufk5m1U3NDRgbm7eoRkiLkZPqp3vaIiHppAcHh6Oo6Mju3btQqfTdWFJO87S0pJBgwZ1uIn9mDFjuPHGG3n00Ue7oHS9U48a7K69ZEAfIYQQoiX5bmy/devWMXfu3A4PcJeQkICiKERFRfXI2nhFUdi1axfQNGNQR8Nidw2A15dq4S+lMwe7a9baNHD+EaNI9ryKRgVuHurM5JQnmKhOQkGFato/IeaeDpcjOTmZG2+80di83sLCAhMTEwwGA/X19ajVatzd3fnuu+8YPHhwZ5x6uzU2NnL48GEyMzMZMGAAwcHBl6x2/mJC/OkMBgO7du1CrVYTHR3dYz+Ldu/ejZmZGSNGjGj39s0D333zzTdceeWVXVDC3qXb55EXQgghhOgu9fX1PPTQQ7z00ksdHqW+uLiYCRMm9MgfztA02FhtbS3jxo27qHDSHc3sa2trSUhIQK/XM3r06F4xmF1Pd2aTfhs7B57cXE5jfhVT+2m45fCDDFMfQW+iwXTmqnb1h29NeHg4kZGRxMfH09DQQE1NjXHUejs7O8zNzYmKiiI8PLyTzrD9mmvnPT092bdvH3l5eURGRmJlZdWlx+2sEA9NLS4iIyPZunUraWlphIWFdWJJO8fpTezz8vLaPS6au7s7//jHP3jggQc4ePBgu+em72t61GB3QgghhBCX0rJly3B0dOTOO+9s97Y6nY7k5GQGDRrUY5vU5+TkkJOTQ0xMTIta2Y66lM3si4uL2bJlCw4ODowfP15CfCc6vUl/hYUHRwuqCLGu5ZnCJQzjCFUqa7j9vxcd4puPtWjRIry8vLCzsyMkJISwsDBCQkKws7PDy8urS0bp7wgnJycmTJiAnZ0dW7du7dJ++50Z4puZm5sTExNDZmYmubm5nVDKzmdpaUl4eDjJycno9fp2b3///fej0Whk4DskyAshhBDiMpWdnc0///lPVqxY0aGm2kePHsXa2vqCo793l9LSUg4ePEhkZGSnhIRmlyLMZ2VlGUfXj4iIkKb0XWjCQDd+/EsgX2lewLvhOIWKAydnfI9pQOeNnN88Sv/w4cPR6/VUVVWh1+sZMWJEl43S31FqtZqIiAhCQkLYuXMn2dnZnX6MrgjxzWxtbYmMjGT//v09dlo6Pz8/LCwsOHr0aLu3bR747vnnn+fkyZNdULreQ/rICyGEEH2IfDe23bx589Dr9Xz++eft3rayspItW7YQFxfXI5/nuro6tmzZQv/+/ds8Qn17dUWfeYPBQHJyMqdOnSIqKqpD3R1Ek3P1kT9LRS7Kp1ejKssiV3Hh67DlPHrztC4pk8Fg6LRR+vV6PT/++COnTp3Cy8uL6667DlPTzu01XFRUREJCAr6+vp02o0BXhvjTHTt2jIyMDOLi4npki6Hy8nK2b9/O+PHjO/QczJo1C0dHRz744IMuKF3vIEFeCCGE6EPku7FtDh06RFRUFKmpqQQGBrZrW0VRiI+Px97enkGDBnVRCTuusbGRbdu2YW9vz9ChQ7u0H3tnhnmtVktiYiINDQ3ExMR0ef/kvu5CQf67vbmMcKwhYO0sKMsi2+DG/abPsXrxTOytLr4bRlf64IMPeOmllygsLDT2t3dzc+Nvf/sb99zT8YH5WlNTU8Pu3buxsLAgMjLyovplX6oQ33ysffv2UVNTw+jRo3tkq5YDBw5QW1tLbGxsuz87jh49SkREBPv372fAgAFdVMKeTZrWCyGEEOKy87e//Y277rqr3SEemga4q6qq6rE/Hg8ePIharWbIkCFdPhhdZzWzb55azszMjLFjx0qI72LHCqt4/fst8Nl0KMviBO7c0vAMt00d02NDfHNrjcWLF/Poo4+Sn5+PhYUFdnZ2WFhYkJ+fz+LFizu9htba2pqxY8eiVqvZunUrVVVVHdrPpQzx0DSw3NChQ1EUhUOHDnXpsToqNDSU8vJy8vLy2r1tSEgIc+fO5emnn+6CkvUOEuSFEEIIcVnZvn07f/zxR4d+AOp0Og4dOkR4eHinDB7X2U6cOEF+fj6RkZGXrAbuYsN8Xl4e27Ztw9fXl6ioqE5vHt2TNIfRrVu3kpycjMFguORlUBSFf363g0/VLxKgyqfU3JNZ9U/j5BXIrEjfS16etoiPj+e2227jtttu4+2336aurg5oCqsmJiaYm5tjb29PQ0MDL7/8cocGUTsfMzMzoqOj8fb2ZuvWreTn57dr+0sd4pup1WqioqI4efJkj+xPbm5uTlhYGIcOHerQa/b3v/+dn3/+mYSEhC4oXc/Xdz8phRBCCCHOoCgKTzzxBH/9619xc3Nr9/Y9eYC7qqoqDhw4QGRkJJaWlpf02B2Zmk5RFI4ePUp6ejrDhw/Hy8vrUhS127Q2f3toaCiLFi1q12BviqKg1WrRarXU19cbbzqdDkVRMBgMKIpCY2Mj0DSPu1qtxsTEBJVKxc7MMhbmPUmIyUnqLdy4ofJx8nDmzWvCUJv0vCkU4+PjWbx4MaWlpajVamNT+sbGRqqrq7GxscHMzAyVSoWVlRUFBQX8+OOP3HjjjZ1aDpVKRWhoKLa2tiQmJjJgwAD69evXpvd5d4T4ZlZWVgwbNox9+/bh4OCAtbX1JT3+hfj5+ZGdnU16ejqhoaHt2tbLy4uHHnqIJ554go0bN/bYKUC7igR5IYQQQlw21q1bx9GjR/nll1/avW1lZSXHjx8nLi6ux/1gbGxsJDExkcDAQDw8PLqlDO0J842NjSQlJVFaWsrYsWOxt7e/lEW95E4Po56enlhaWlJXV0dSUhKLFy8+a+T2xsZGKisrKS8vp7KyskVg12q1KIqCmZkZFhYWaDQaLCwsMDc3R6VSGUNtc8sIjUYDNAXK2vp6Bu19kqEmx6k2seUx1RKyDG4MdlKoSE9kywkLLCwsjE3WHRwcsLOz67b+1QaDgeXLl1NaWkq/fv3IyspCURTUajUqlYrGxkZqa2uN7x9TU1MMBgOnTp3qsjL5+PhgY2PD7t27qaysZNiwYeccBK+7Q3wzT09P/Pz8SExMZOzYsT1iqr9mKpWKIUOGsH37dnx9fdv9HD322GMEBQWxYcMGJk+e3EWl7JkkyAshhBDistDY2MiTTz7J008/ja2tbbu3T0lJISAgoEcOInjo0CFMTEzaXaPV2doS5vV6PXv27EGn0xEXF2cMmn3VmWG0+fmwsbEhODiY7Oxs1qxZg4eHBxUVFZSXl1NVVYWpqSkODg7Y29vj6upqDNjN4f1C4Vqn05Genk5ISEhTNxBF4dCKWxlEMnVYcHzKZ/z8Qz1qExUv3RyFt62p8WJBXV0deXl5pKWlodfrsbOzw97eHgcHh0sa7lNSUkhLS8PT0xOVSoWFhYXxIkVzs/rGxkb0ej2mpqbo9XpMTEy6vHWHg4MDcXFx7Nq1iz179hAVFXXW89FTQnyzsLAwtm3bRmpqao8bpNPBwQFfX19SUlKIiYlp97ZPPvkkTzzxBJMmTepRFym6mgR5IYQQQlwWPv/8c2pqajo0qnVxcTGlpaUMHz68C0p2cU6dOkVubi7jx4/vET9izxfm9Xo9u3fvxmAwMGrUqB45zkBnOzOMNgdNPz8/3N3dcXR0pK6ujmPHjuHj48OAAQNwcHDA0tKyU1t+VPz8HIOKf0GvmJA27h1eTrIE6pkV6cNg/9a7mSiKQm1trfECw+nh3tbWFmdnZzw8PHB2du6SYF9WVoZWqzV2FXF3d8fc3BytVotKpUKlUhm7EjSX1dPTk+uuu67Ty3ImCwsLRo8ezc6dO9m9ezfR0dHG8R16WoiHpv7ykZGRbNmyBWdnZzw9Pbu7SC0MGDCAjRs3UlpaipOTU7u2XbRoEf/617/4+uuvueWWW7qohD2PBHkhhBBC9HkNDQ38/e9/58UXX2x3DbCiKKSmptKvX78eV3tcW1tLUlISw4YN61F9X1sL83q9nl27dmFiYsLIkSP79KB2pysrK0OtVhMREUFAQADe3t40NDSQnZ1NUlISBQUFHDp0iPfff5+wsLCuKcTBr7FPeBOAL90fwcdnPAkbEjA3NeHBif3PuZlKpcLa2hpra2tjLbeiKNTU1JCcnMypU6fIyclBpVLh5uaGh4eHMWx3BkdHRzQaDXV1ddjY2GBiYkK/fv2MFxNMTExQFAWdTkdNTQ3m5uY8+eSTl+y9ZWZmxsiRI9m9eze7du0iJiYGU1PTHhfim9nY2BAREUFSUpLxYlFPYWFhQXBwMKmpqYwePbpdF7EsLS159tlnefrpp7npppsum8+Wy+MshRBCCHFZ+/zzz7GysuLWW29t97b5+fnU1tYSHBzcBSXrOEVRSEpKwtvbu0cOFHd6mG9sbKS0tBRzc3Oio6N75JzWnUlRFKqrq8nPz6euro6nnnqKwsJCcnNzjWMDNKuurkaj0eDo6NglZVGd3As/Lmq6M/ph5kx6huvfjQfgL7H+eNq3L8zt3LnzrEH7Ro4cyfXXX09NTQ1JSUk4OTnh4eGBh4fHRQXZ8PBwQkNDSUpKIjg4GJVKRUBAAADHjh0z1szr9Xo8PT158sknO30e+QsxMzMjNjaWPXv2sHPnTuzt7cnPz+9xIb6Zj48PhYWF7N+/v0Pzt3el5nEQCgsLcXd3b9e2c+fO5aWXXuKrr75izpw5XVTCnqX7218JIYQQQnShxsZG/vnPf/L444+3O0AaDAZSU1MZMGBAj6vlycrKoqamhvDw8O4uyjnZ2toSHR1NZmYmOp2u1b7EfYlWqyU9PZ3ff/+dzZs3U1JSQkhICGvXruWtt946K8QrikJ+fj5hYWFd8jpqdOWov70dGrUw4GqYuJSt6cXsP1GOhZkJ98a17+JU86B9zSOgBwQE4ODgwB9//MHSpUsxNzfnyiuvxNvbm6KiIv744w9+//13Y+huLxMTExYtWoSjoyMZGRlUV1fT2NiIi4sLfn5+9OvXjwcffJDPP/+cY8eOXfIQ38zU1JTo6Gi0Wi3Z2dnExMT0yBDfbPDgwVRWVpKTk9PdRWnBzMyMkJAQUlNT2z2NpampKY899hivvPJKt0zr2B0kyAshhBCiT/vhhx+oq6tj9uzZ7d72xIkTKIqCv79/F5Ss42pqakhJSWHo0KE9up+5TqcjOTkZZ2dndDodR48ebfcP9J5OURQKCwvZs2cPv/32G4WFhQwYMIBp06YRGxtLYGAgd95551lhtLq6moyMDBwdHVm4cGHnj2/QqCMq8x1U1QVkm/ixbfALKCoV72xKB2BOjD+utm3vKnLmoH02Njao1WrjoH1lZWWsWLECjUZDYGAgI0eOZNq0afTv35/8/Hx+++03EhISKCwsbNd7YNSoUbz22msMGzaM8vJysrKyKC8vJzIykk8//ZQ333yTG2+8sVsvtCmKwuHDh2lsbMTJyYnk5OROn8u+M5mZmTF06FAOHTpEXV1ddxenhYCAAHQ6Hbm5ue3edu7cuRQXF7Nu3bouKFnPo1J68adpZWUl9vb2VFRU9MgRZIUQQohLTb4bW1IUhcjISObOncuDDz7Yrm0bGxvZuHEj4eHhPWreeEVRiI+PN/Z37an0ej07d+401lbW1tayY8cO/Pz82jTPfE+n0+nIyckhMzMTvV6Pn58ffn5+56yJbW0e+bCwMBYuXHjBeeQNBgMpKSmUlZXh6OhIeHj4BYN/4y9PoN79HjUqK66pf564kSOZNsiDm1fuwtzUhG2PTcDdzqLN55ucnMztt9+Og4NDq+dYXV1NeXk5//73vxk8eHCrj2dnZ5OTk4O5uTmBgYH4+fm1OYB35Dm4FM4c2M7S0pJdu3YBGPvM91RJSUnU19f3uCb2OTk5HDlyhCuuuKLdLXheffVVvv/+e+Lj43vUOXWFnvvOEkIIIYS4SBs2bCAnJ4c777yz3dtmZmai0Wjw9vbugpJ1XHOT+ujo6O4uyjk1Njaye/duTExMjM3p2zPPfE9WU1PD8ePHycnJwcbGhoEDB+Ll5XXBUDlq1ChiY2PbHUZbuwAQGhrKokWLzn0B4PD/UO9+D4BHtPeQZ+rN/ROCeezbgwDcNMKnXSEezh5B/kyWlpYUFBRQVlbW6uM2NjaEh4czcOBATp06RUZGBmlpafj7+xMUFISVldV5j29iYtLqBYLudK7R6WNiYti5cyd79uwhJiamx3YnGTRoEL///js5OTk9qtWRr68vx44dIysrq91jk9x777289NJLbNmyhfHjx3dNAXuI7r+MJYQQQgjRRV5++WUeeuihC4aEMzU3Aw8LC+tRYbO5Sf2wYcN6bJP6xsZG9uzZg8FgOKtGsjnM5+TkkJaW1qua2dfV1bF//35+//13tFotI0eOJC4uDh8fnzbXDDeH0XHjxjF48OA2hfjW+qQnJSWxePFi4uPjz96o4iT8934AvjaZxm+GKObE+FNWo2PzkSJMVHDPuKB2n//pI8i3pq6urk2D9qnVanx9fYmLiyM2Npa6ujo2bdrEgQMHqK+vb3e5usv5ppgzNTUlNjYWnU5HYmJij+2z3VOb2KtUKkJDQzl69Gi7uyjY2tqyaNEiXn755S4qXc8hNfJCCCGE6JN27drF3r17+f7779u9bVZWFra2tri6unZByTpGURT279+Pr69vjyrX6RRF4eDBg2i1WkaPHt1qs+LeVjOv0+lIT0/n+PHjuLu7M378eGxtbbv8uGf2SW9+jpr7pGdkZLBixQpiY2P/vCBgaIQf7oH6cqqcBvHUqVsxNzXhnnFBvLr+CABTB3ng79z+qQpbG0G+WfOgfcOHD2/zoH0qlQpnZ2ecnZ2pqqoiNTWVjRs3EhwcTL9+/XrshSpowzzxVQWY1Zczys+cQ0m7ySpPIsjXExp1YGoBodf8ue7R36CuDNSmTY+pNWBmCeZWYG4LLv269Fzc3d3x8vLqcaPYe3h4YGVlRXZ2drtr5R988EECAgLYu3cvI0aM6KISdj8J8kIIIYTok15++WXuu+++dk/r1djYSEZGBkOHDu0xP2oBTp06RVVVVY9uUn/8+HEKCgqIi4s7bxDrDWG+sbGR48ePk56ejr29PaNHj+6yKeJak5KSQlpaGp6enmc9NyqVCg8PD1JTU0lJSfmzyfnOFZC1Dcys+Yf5o+gw5dZhXpiYqPhx/ykA7hjT/tp4+HME+cWLF5ORkYGHhweWlpbU1dWRn59/UYP22draEhMTQ2lpKampqWRlZRESEkJAQEDPaZbeUAPlOShl2eQdTsCyMIMr7NWY/fA+WLvBDR/8ue4nU6H0OGbAsOZlO///Xwe/lkH+jxchb3/rx7SwhydOG1n++7uhIAWsXcHGrelm6wV2nmDnAz6R0IG/o/DwcDZt2kR+fj6enp7t3r4rqFQq+vfvT3Jy8jnfB1u3buXVV19l79695OXl8cMPPzBjxgxcXV254447mDNnDmZmZhw/fhx7e3smTZrEK6+80mK6ztLSUh544AHWrl2LiYkJN954I2+//XaPnnWgmQR5IYQQQvQ5hw4d4rfffuODDz648MpnyMnJQaPRtHse466k1+s5dOgQ4eHhPbamsrCwkLS0NEaNGnXOftSn66lh3mAwcOLECQ4fPoxGoyEyMhJXV9dLXrZ290kvTIPfnwegYNRSvllvgQqFO8YEsGZ3Dg2NBiJ8HRjh3/GLEc0jyDf32S8oKECj0TB8+PA2Ddp3IU5OTowePZrCwkJSU1PJyMhg4MCB+Pr6Xrrnv7oIClOagvvAq/9c/s4IqMpDBRhj4Mn//9fBr+U+LB3BwgE0dmBmid7EjMoaLTYOzpg7B7Rc1yeyaf1GXdM0gfp60NVBQy1YObVct+gIFBxqvdzmNvDkaSO9b30NqgvBuV9Trb5LCNh5txr0zc3NCQsLIzk5GVdX1x4zQJ+npydpaWnk5ua22oe/pqaGiIgIFixYwA033NDisXvuuYcVK1bw+uuvM23aNMrKynjooYeYPn06iYmJxvXmzJlDXl4eGzZsQKfTMX/+fO6++25Wr17d5ed3sXrGqySEEEII0YnefPNNbr/9djw8PNq1ncFg4NixYz0mVDY7cuQI1tbWPWr0/NNVV1eTmJjIkCFDcHJyuvAG/6+nhfnCwkKSk5NRFIVBgwbh5eXVbeU5vU96a7WDLfqkGxrhx4XQ2AD9p+Ay7i5WOJ1i7bYkvO0t+GJ3U63uvFEXP6BZRwftayuVSoW7uztubm7k5uZy+PBhjh07xuDBgzu/S0lNMeQmwqkkOLUP8g5CdX7TY/a+LYK84hSIob6KGjMXrDxDMHXyb6oJt/Fo+vd0d/3e4q4pUJWdze7UVMaNG0eLjg1Xv9728s54FyrzoKYIagqbgnrlqaabmWXLkJ7yw9mhX2MHrgP+j70zD2+qTPvwnaT7mm40Ld2hUAqltOxlFVFAZNRRR+cDEXREFHTUQcddRx0XZBxGZXR0RgEVUUdUVMBRkLVQli6UtlDoDm3aQtd0Sdsk3x8xkdIWmnQ5B33v68rVNud9z3nOSZqc3/tsoBlpPu5548PCwigqKuLkyZMMGzas+zb1IRavfG5uLmFhYR3+F+fMmcOcOXM6nTt8+HBuu+02jh8/zgMPPADAm2++ybhx4yguLiYsLIycnBy2bdvGoUOHGDNmDABvvPEG11xzDatWrWrnuZcjQsgLBAKBQCD4RXHu3Dk2bNjAoUOHbJ575ozZxSanG7j6+nry8/OZOnWqrBYXLLS2tpKSkkJ4eDhhYWGXnnABchDzra2tZGVlcfr0aWJjY4mIiJC8tZlNOekpb8GZI+DsDfP+gUql5OrYQNoKjew4UYm2rhk/dyeuieudsOn+qCCvUCgIDQ1l4MCBFBQUkJKSQmhoKMOHD7fPY2wyga4cPM9b3Pvwt1CWceGRwTcSBsSaF0iUKkwmE9mJL3A6+Ky59oMdYdfh4eHU1taSkpLClClT7IusCRxufnSHicuhIhvOnYKzJ6EqH/R1cPoQ6HXtRf9/70ABjPWNJTVdgU7jj4ePPOpwhISEcPz4cUpLS23uIHL//fczZcoUXn75ZdRqNbW1tSgUCtRqNQD79+9HrVZbRTzAzJkzUSqVpKSkcMMNN/TmqfQ6QsgLBAKBQCD4RfHvf/+bCRMmMGLECJvmmUwmTp48SXR0tOQizoKleFxERATe3t5Sm9MBk8nEkSNHcHNzIzY21u79SCnmKyoqSE9Px93dnRkzZtjc4aCv6HZOet1p2PGCedLVz2H0CCQrM5OqqioAPj5kDre+eUwozg4yyTe3AaVSyaBBg9BoNKSlpfHjjz+SkJCAv7//pSc310Lej5C3HfJ3Qr3WnHPu+FO6QugEaG2GgaNhYCIExZsFvPPPQt1a2E57tvPCdjYwYsQI9u/fT2pqKuPGjevb9/io37f/u63FLOorc4Dzjmtog+NboK0JVz5nEmDM/SumoHgUoeMhajoMnd13dl4CpVLJ4MGDOXnypM0RMomJicTHx7N27VqWLl3Kn//8Z37/+9/j5eUFgFarZcCAAe3mODg44Ovri1ar7dXz6AuEkBcIBAKBQPCLwWAw8M9//pO///3vNs/VarW0tLQQGhraB5bZh9wL3GVnZ9PQ0NAr0QL9LebP98IPHz6ciIgI2UU8dCsnfeN8aG2E8EnsbRrMvQ+to6XkKC5FyfzxkcfZe/IsKBTcOlY+72t7cHd3Z9KkSRQUFHDgwAHCwsKIjY3t6J2vKYacr83itHg/mAw/b1M6QOVxCP6pBN3sl+Eii3aXrE5vI0qlkrFjx7J7926OHz/evyHsDk4QGGt+XMitH5lTC86kYTp9CGVDhfnv0lSoLmwv5HO+gdBx5kJ7/URYWBgnTpygoqLC5tol9913H08//TTbt2/HZDLx1ltv9ZGV/Y8Q8gKBQCAQCH4xfP3115hMJn7zm9/YNM/ijR80aJBsqmQbDAaysrJkW+CupKSEoqIipk6d2mv29ZeYl6sXvjMumpN+8ns4/g0oHUgbeBv3v/Qv6uJuRRk5iWhDEQcrFKBQ4FRTSGluBhH+PStGJzUKhYKoqCgCAwPbe+f9/H4OFT+2CX545udJ/kNg8EwYNAPCJrbztveniLfg5OTEuHHj2LNnD15eXjaHi/c6KgcYfKX5AShMJk5nH6A6YxvDvXQoQ8f+PLamBD6Zb/59wHAYdIX5uoZPAkeXPjPRwcGBqKgoTp48abOQ/81vfsPixYtpa2vj8OHDVm88mFvcVVRUtBvf1tZGVVWVzfVVpEAIeYFAIBAIBL8Y3nrrLe6++26bc2jPnTuHTqcjIiKibwyzg4KCApycnGRZ4K66upqMjAzGjRvX622a+lLMt7W1kZWVRUlJiWy98J3RaU66oRW2PQaAafxSXl37NTV+5jE+tSdxUMKhSrNQNeUls2ZNcvue85cx7u7uTEoYxtmdb6N6/88UDV/IwKuXm//vY+bCqR8g5loYMsuc724jfSXiLXh5eTF69GgOHz6Mu7u7NWdbFigUDIydQG55EwXh4e17uDdUgCYOtJnmyv4VWbD/TXBwhcgpMHGZORS/D4iKiuLUqVNUVVV1u6Bma2srCxYswMvLi6FDh+Ln59du+8SJE6mpqWnXb37Hjh0YjUbGjx/f6+fQ21z+/8kCgUAgEAgEQF5eHjt37uTOO++0eW5+fj7h4eGy8Xy3traSm5tLbGys7IRmU1MTKSkpDBs2rEN+aW9hEfPFxcXk5ORgMpl6vM+GhgZ2795NfX09V1xxBZGRkbK7tjZx6D9w7iS4B5AdMI+sU0UYNeZCaL7VOTS4DOCsXoHS2EKwsdLac/6yxmg057x/ejuK12IIOLQSn4Y8PPK/Zc+ePTQ2NoJ/NCz6BiYslaWIt6DRaBg6dCgHDx6kubm5T45hLwqFgtjYWHJzc2ltbf15w8DRsHQvPJwHN70HCQvMfezbmuDk/6Cp+uexdaXmbgC98L8L4OjoSFhYGAUFBdbndDod6enppKenA+bFz/T0dIqLi2ltbeWmm27i8OHDfPDBB+zYsYMjR45YU6jAvEg4e/Zs7rrrLg4ePMi+fftYvnw5t956q6wKnnaFEPICgUAgEAh+Ebz77rv85je/sTkksqmpifLyciIjbb/p7ytOnjyJt7d377fb6iEmk4m0tDQCAgKIiorq02P1ppivrKxk165dBAQEkJSUhLu7+6UnyZnmWtj1ivn3K57gnK6FxoBYUKpwbarARV9NtZfZk6quL8Ld2QG9Xv9zz/nLDaMBkt+EN0fDB9dD9pfmVnuakTD7ZXwWrsfX15ddu3Zx7tw5uw/TXyLewuDBg/H19SU9Pb1XFqt6k8DAQDw8PMjLy+u40d0fRtwI162Bh7LhnmSY+aw5zN5C2ofwznRYHWeOHCnab16I6QGRkZGUlpZaFz4OHz5MQkICCQnmmgcPPfQQCQkJPP3005w5c4bNmzdz+vRpZs+eTWtrK2PGjCEoKIjk5GTrPj/66CNiYmK48sorueaaa5g8eTLvvPNOj+zsL0RovUAgEAgEgsuelpYW3nvvPTZs2GDz3IKCAgYMGCCbPOmmpiby8/OZNGmS7DzGRUVF1NfXM3bs2H6xradh9iaTiYKCArKzs4mLiyM8vOd91GXBvtehqcqc/51wGz7ZORjDzC201DW5mFBQ7WFemPKtz2vfc/5yRKGEY5+bW6g5e8HIWyBxIQSNBMyeyfj4ILy9vdm/fz8jRoywOU2mv0U8mD3fI0eOZMeOHZSUlNjVvrGvsHjl9+/fT2RkJM7Ozl0N7LwtXmsjOLpDbQkc+Kf54RkEsdfDiN9CyNj2LfC6gYeHB/7+/hQVFTF06FCmT59+0QWQ87dt2bKFu+66i6KionapV76+vnZ9b8gB4ZEXCAQCgUBw2fPll1/i7e3NjBkzLj34PAwGA0VFRbLyxufm5hIYGCg70dXY2EhWVhYJCQn9moJgr2feaDSSkZFBbm4uEydO/OWI+IZzcOCnyttXPg0qB9w1ERi8Q8BowLvmFA3uwbQ5uOLuYMKj4QxarZbY2Fhzz/nLgbIM2LTEHHkAZsE3/TGY9w/403GYu8oq4s8nIiKCCRMmkJOTw9GjRzF20wMshYi34OTkxKhRozh27BhNTU39dtzu4OfnR0BAALm5ubZPnvksPJIHt26AkbeaF2DqyyDlLfjgBmi171wjIyMpKCjo9mtrYdasWTg6OvLNN9/YdVw5IoS8QCAQCASCy57169ezaNEimwt5lZaW4uTkJJsQdp1OR3Fxcf+2peoGJpOJ9PR0Bg4c2Gd58RfDVjGv1+tJTk6mpqaGqVOndihydVmT/A9obTD3PI+5FgClQsn0MCdczp6gKPcYZ13NreZG+pooLMj/uee83AvdnUmFj34H/5oKRz+BI+t+3jbkahi9CJwunhbh7+/PtGnTOHfuHPv377fmQ3eFlCLegkajQaPRkJGRIbsQ+2HDhlFYWEhDQ0OXY3bv3s28efOsfd6//PJL8wZHV4iZi+mGt/lL020s3ObEx1kGvip042TRGfMYkwn+ewcNO/7G3bfdjJeXF2q1mjvvvBOdTtfhWIGBgahUKpv7vKtUKm6//XY++OADm+bJGZn/NwsEAoFAIBBcnMrKSv73v/8xf/58m+cWFhbKqnL58ePHCQ0NlURMXIyioiJ0Op2kHt3uivna2lp27dqFs7MzkydPlk3KRE8wGo1kZmaSvP1bDAd+yt+d/rg1NDnC3521917Fe3+YxKiEBHRqc358vJ+J+Ph4Vq1aZe45L1cqcmDjfHj3Cjj5nTmUPu53EH2VXbtzc3NjypQpODo6smvXLurq6jodJwcRb2HEiBHU1tZSUlIimQ2dYWmRd+LEiS7HNDQ0EB8fz5o1azrdvnLlSv7++j+58bF/M/ypZN4rj2XWrFnmXPeyDDj2Oe67n+PNyP9R+MoU9q19mr17drFkyZIO+1IoFISHh7cretdd5s+fzzfffHP51oq4ACHkBQKBQCAQXNZ88sknjB8/3uac2Lq6OmpqaggNDe0bw2xEp9NRVlbGkCFDpDalHZaQ+lGjRkle1f9SYv7s2bPs3buX8PBwxowZY3MbQjmSnJzMggULWLhwIUfeuhuVoYnCZi+Sz3p2GJuUlMSfXnwDk7Mnrg4Q7WXinXfe6VcRb1l02L17N5mZmRcPgTa0wVfL4K0kOP6NWcDH/x6WH4Yb34UB9kemODg4MHbsWEJDQ9mzZ0+HInhyEvFgDrGPj48nMzNTdiH2Q4YM4cyZM+auAJ0wZ84cXnjhBW644YYO20wmE6tXr+bJJ5/kuuuuY+TIkaxfv57S0lKz514dhjbhIQ6XGnBUgm/5Xoan/4WMRQaGaTehPZnWYZ9hYWFUVVV16rG/1HnEx8fz3//+16Z5ckUIeYFAIBAIBJc1H330kd3e+ODgYJycnPrAKts5deoUAwcOlJUH2VKlXqqQ+s7oSsxXVFRw4MABRowYwdChQ2UTZdETkpOTWbFiBampqQzw9WLhULPAeyNVxYqHHyY5OZnU4moySmowGs3X4ccTlQDMiNHgoKRfw+nPX3RYunQpCxcuZMGCBe2qhLdD5QAtjWAywrDfwL0pcMPb4Deo8/E2olAoiImJYfjw4Rw4cICzZ88C8hPxFjQaDUFBQbKrYu/h4UFQUBCnTp2yeW5BQQFarZaZM2dan/P29mb8+PHs378f3HzZci6Uqz5zNFe/n7AMXH1xaaniqanOFCR/2WGfLi4uBAUFUVRUZLM9CxYs4KOPPrJ5nhwRQl4gEAgEAsFly6lTpzhy5Ag333yzTfMMBgOnT5+22YvfVzQ1NVFSUkJ0dLTUprTDkhsrtyJpF4r5srIyDh48yKhRo34xRe2MRiNvvvkmVVVVDB48mGtDG/B2bKNc78xJp+FUV1ezZs0a/va/E1y3Zh8fHDCLmu05FQBcMdS/X+09f9FBrVYTERGBWq0mLS2NFStW/CzmT2wz9xi3cNVzcOf3cMsHENA30SgRERHExcVx4MABysvLZSniLcTFxVFXV0dxcbHUprQjOjqa4uJim3veW3LZAwMD2z0fGBho3abVas0LhYHDYfaL5oKGN73HppNKMhrOW0A8+C7s+wc0VhEeHk5xcbHNRe9uueUW9u3bJ7vraw9CyAsEAoFAILhs2bBhA9dcc43NxczKy8txcnLC19e3jyyzjby8PAIDA/H07BguLRWNjY1kZ2fLIqS+MyxivqCggEOHDpGQkEBISIjUZvUaWVlZ5OTkEBQUhEIB1w4wi99vKgZiUijRaDRknThFSr45ZHxytD/ldc0c19ajUJj/7i8uXHTw8PBApVLh4eHBoEGDqK6u5qO3/4Zp43z4+Bb47omfJ6tDIXRcn9sYFhZGfHw8KSkpFBcXy1LEAzg6Osqyir23tzf+/v7k5+f3/cEcnGHEjSz93hGT4ie52tYCu1+F75+G12Lx3/883s1nKC8vt2nXgYGBzJw5k48//rgPDO9fhJAXCAQCgUBwWWIymfjwww/tCqsvKSkhJCREFuHXLS0tFBYWysobL8eQ+s5obGzEaDSiUqmora2VVThyT6murkav1+Pq6kqMex2Rbg3ojUq+P2f2bLq6utLkGUKbEUJ8XInyd2fPSXPo+MiB3vi591/KSPtFh/b/UwoF3DnKgZdDt6M4/g0oHczi3UZPak8xmUzU1tbi4OCA0WjsMt9bDgQGBsoyxD46OpqCggJaW1u7PUej0QB0ENzl5eXWbRqNhoqKinbb29raqKqqso4BYMZToImDtiYUqetIyvgTbp/Ph5M/mKvfd5P58+fz4Ycfdnu8XBFCXiAQCAQCwWXJ4cOHKS8v59prr7VpXktLCxUVFbLx3ubnm9uDyalvvFxD6s+noqKCQ4cOkZiYyNSpU23uMy93fHx8cHZ2pqmpiTkBZQDsrgqgwWCOjmhqagJNDABTogNQKBTsO2UW8v3pjYf2iw7n4+uo59nBx1gxtBhPRxN1XkPg7t3mcPp+zN0/Pyd+6tSpxMfHc/DgQWvOvByRY4i9n58f3t7eNlWMj4yMRKPRsH37dutzdXV1pKSkMHHiRAAmTpxITU0NR44csY7ZsWMHRqOR8ePHm59wcILE2+DuPbB4K8Reh0mhxPvsEfjoRtj+l27bdP3115Ofn8/Ro0e7PUeOCCEvEAgEAoHgsuTDDz/kxhtv7CAeLkVpaSne3t6yCKtta2sjPz9fVpXqW1tbOX78OCNHjpRlSD2Yq9MfPHiQ+Ph4Bg4caHOf+cuB4cOHM2zYMOrOlpKkNgvO784GAWZhqtVqUQWZq7pPGuyHyWQiOc88btKg/hXy5y86WBjiVsebsUcY7V1Ni1HBa8d8KZr5rjkPuh/prLBdaGgocXFxpKSkUFVV1a/2dBdHR0fi4uLIycmhra1NanOsREdHk5+fj8FgsD6n0+lIT08nPT0dMBe4S09Pp7i4GIVCwQMPPMALL7zA5s2byczMZOHChQQHB3P99dcD5l71s2fP5q677uLgwYPs27eP5cuXc+uttxIcHNzeAIUCwpPgd+tR3J9OSchvMDp6mNsVdhMPDw+uv/76y94rL4S8QCAQCASCyw6DwcAnn3xiV1j96dOnZeONLykpwc3NDX///hVeF+PUqVN4enp2KE4lF+rr60lJSSEuLq5d68BfmphXKpUsX76c3w5V4qIyUtzoTHadGzqdjsLCQgZGDqHRyRzFEezQwPaDmZTX6XFQgvFsvtW7mZaWxpEjR0hPTycnJ4eCggLOnDnDoUOH2LlzJ0ePHrW5YNiFWBYdtFqt9bqfbnaj0aDiZIMH12/z54hzEsNHjOzZRbGRi1WnDw8PJzY2lgMHDtjcxqy/CAoKws3Njby8PKlNsTJgwACcnJw4ffq09bnDhw+TkJBAQkICAA899BAJCQk8/fTTADzyyCPcd999LFmyhLFjx6LT6di2bRsuLi7WfXz00UfExMRw5ZVXcs011zB58mTeeeedixvjE45++jOkTFkPgbE2ncf8+fP5+OOPL+vPicu/uaZAIBAIBIJfHQcPHqSlpYVp06bZNK+xsZGqqirGjh3bR5Z1H5PJREFBAYMGDZJFrj5Ac3MzeXl5JCUlycam82lpaSElJYXIyMhOq9NbxPy+ffsAs6dPjufRXZKSkhh2eABUlZJmjGH8+AmEhITg5+dHZpWCU7mgcQN97VnSSs1iPCbABY2/L0ajkfLycry9vVEoFBgMBpqbmyksLKS8vBwHBwfc3d2pqakhIyODgIAABg8ejFqtxtvb26ZoDMuiw4uP/5G8vFNoNEEYXF15KH0wmcVVeHj78uSyZf3aCq87LeYiIyNpaGggJSWFqVOnyi4CRaFQEBsba33Py6FVpkKhICoqioKCAsLCwlAoFEyfPv2iglihUPDcc8/x3HPPdTnG19eXDRs22GzPwIEDyc7OpqmpyaborJkzZ1JbW0taWhqJiYk2H1cOCCEvEAgEAoHgsmPz5s3MnTsXBwfbbmVOnz7NgAEDcHZ27iPLus/Zs2fR6/WyiQ4AyM3NJSAgQDbV/M/HaDRy+PBhPD09GTZsWJfjLncx39bWRmVlJVqtlrqyfKZWZQDgN20JE5wCqKqqYvPmzaRnZuPs4o/OxY03jjvgNHkxAFOGDWTw4MG0traSk5NDVFSUVaAmJyfz/PPPU1VVZfX2KpVKVCoVgwcPxmQyoVQqaW5uxt3dHT8/PzQaDQEBAZf8X0vyq+XLmadZeyaKNQdqKC8vp8zZmbhRo1m2bBlJSUl9e+HOw5Y+8bGxsdTX13PkyBHGjx8vu/eKv78/vr6+5ObmMmLECKnNASAkJISsrCyqqqps7hjS27i6uuLn58eZM2cYPHhwt+c5OTkxe/ZsNm/eLIS8QCAQCAQCQX/x9ddf88wzz9g0x2QyUVJSwtChQ/vIKtuweLRUKpXUpgDQ0NBAUVGRzVEO/UV2djbNzc1MmTLlkmLrchPzTU1NlJeXo9VqqaysxNXVFY1GQ4LraRSYIDiByfMWkJyczF/+8herENe4GmlqqiQtTUur39XgHsCY8M6LJl7YIu7869HW1sa3335LWVkZH3zwAS0tLdTW1lJZWUlWVhZNTU0EBASg0WjQaDTtQqIxmWDP32DH8zgAd473Yfw9/6S6phYfHx+GDx8uO0/8+SiVSsaMGcOuXbvIyckhNta2EO3+IDY2lt27dxMVFYWbm5vU5uDg4EB4eDgFBQWSC3mA0NBQ8vPzbRLyAL/5zW/4+9//zrPPPts3hvUxIkdeIBAIBALBZUV+fj65ubnMmjXLpnl1dXU0NTW1b2ckEU1NTWi1WiIiIqQ2xcrx48cJCQnBy8tLalM6UFRURHFxMePHj+92+LPcc+ZbW1spLCxk9+7dfP/995w+fRp/f3+mT5/OzJkzGTFiBF6l5oUIYq69aK/2iOgY2twDABg5sPPX7+It4hRoNBqys7PJysrCxcWFwMBARowYwZVXXsn06dPx8/OjpKSE//3vf+zevZuioiLamhvgi7thx/PmHY39A4oFm4gbGc/UqVOJi4uTtYi34OjoyPjx4ykoKGiX+y0XvL29CQ4O5vjx412OMRgMPPXUU0RGRuLq6sqgQYN4/vnn273vTSYTTz/9NEFBQbi6ujJz5kxOnjxpl00RERGUlZWh1+vtmt+bBAUFUV9fT319vU3z5syZQ0ZGhixf8+4ghLxAIBAIBILLiq+//prp06fbLDjLysoIDAy0ORy/LyguLiYgIAB3d3epTQGgtraW0tJS2UQrnE9VVRWZmZmMHTvW5uslRzFfV1dHeno63333HYWFhYSGhjJr1iwmT57M4MGD8fT0NA9saYT8nebfh17TToi3OnlRGjiRWq8oAJpdBwCgbKpGW3Sq0+N21SLOgqurK3q9nurq6nbPKxQKPD09iY6OZsqUKcyaNYuQkBCKTxylds2VcPQTTEoHmPsazP2buU2YBNgr4i14enoyZswY0tPTO1wDORATE8OZM2eoq6vrdPsrr7zCW2+9xZtvvklOTg6vvPIKK1eu5I033rCOWblyJa+//jpvv/02KSkpuLu7M2vWLJqbm222x8PDA19fX1m0x3N0dGTAgAGUlZXZNM/Pz49JkybxzTff9JFlfYsQ8gKBQCAQCC4rNm/ezG9+8xub52m1Wll4400mE0VFRbLyxmdnZxMZGSmLsN3zaWpq4uDBg8TGxhIQEGDXPuQg5k0mE+Xl5ezbt49du3ZhMpmYPHky06dPJzIysvOaDUXJYNCDVwgMGNZOiDe6DuCcfzyVfuYq8E2u5q4HiurTXYrQzlrEnU9TUxPOzs74+HQemm/B2dmZqNBgJp96Eb/6HAwObhwY9CeSW4dRUVEh2fXtiYi3EBgYSExMDAcPHrRL3PYl7u7uhIeHk5OT0+n25ORkrrvuOubOnUtERAQ33XQTV199NQcPHgTM12j16tU8+eSTXHfddYwcOZL169dTWlrKl19+aZdNERERFBYWymKBTKPRoNVqbZ73m9/8hs2bN/eBRX2PEPICgUAgEAguG2pqati9ezfz5s2zaV5TUxN1dXWyaKlmETtysAXMRfeqqqpk1csezDndKSkpaDQaIiMje7QvKcV8VVUVe/fuJTU1FX9/f66++moSEhJQq9UXn5i3w/xz8AxQKNoJ8WYXc16ya7O5B3qzi1nIOzaUdynEO2sRZ8HSlz42Npbhw7vR593RBcXI34GHBtUf/kfCjQ/h5+fH4cOHSU5O7tfe7L0l4i0MGjSIgIAADh482OO2fL3NkCFDqKys7PT6JiUlsX37dnJzcwHIyMhg7969zJkzBzDX5NBqtcycOdM6x9vbm/Hjx7N//3677AkKCsJgMHD27Fm75vcmgYGB1NTU2LwAM2/ePLZv3y7bFoQXQwh5gUAgEAgElw3btm0jNja209ZjF0Or1eLr6yuL9k2WPvb9mTvcFSaTiezsbAYPHiyLa3M+J06cwGQyMXLkyF4pVNffYr6uro6UlBSSk5MJCAhg5syZDB06tPsdEwr3mH9GmosPni/Em53NYt1Z/5OQdzZ3GYhUO3YpxC0t4nx8fMjLy0On02EwGNDpdOTl5eHj48MyW1rETXoA7t0PmjhcXFwYOnQoV111Fb6+viQnJ3Pw4EGbc5ZtpbdFPJhTCeLj42lra7M7f7yvcHFxYdCgQWRnZ3d4/z766KPceuutxMTE4OjoSEJCAg888ADz588HsHqrL1xADAwMtMuTDeb31MCBAykpKbFrfm/i4uKCWq2mvLzcpnlDhgwhMjKS77//vo8s6zuk/wYRCAQCgUAg6CabN2+22RsP8gmrb2tro6ysTDYt58rKymhsbGTQoEFSm9KOmpoa8vLySExM7NUFj74W80ajkbS0NLZu3crOnTtxcXFh5syZVnHVbZprQZtp/j18EtBeiOuU5loBjk3nqG9opNlJDcDS38+76PVKSkpi1apVJCQkUFNTQ2FhITU1NSQmJrJq1aqLt4g7lwefLoTmn3K0FQpwa9+m0NHRkWHDhjFz5kycnZ3ZuXMnaWlpfRKm3hci3oJKpSIxMZGTJ09SW1vba/vtDQYPHkx9fX0Hwfrpp5/y0UcfsWHDBlJTU1m3bh2rVq1i3bp1fWpPSEgIZWVlGAyGPj1Od7B3UWLevHmXZXi99NVeBAKBQCAQCLqBwWBg27ZtbNmyxaZ5bW1tnD17lri4uD6yrPuUlZXh7u6Ot7e31KZgMpk4ceIEQ4YMkUUBQAsGg4HU1FSio6P75Dr1VWu6ffv2sWXLFkaOHMmJEyfYuXMnGo2G5cuX295D/cwRwAQ+EeAVZH06KSmJV1a+ysKvzZ74ilOZOLl6gMoBZxXMmzH5krtOSkpiwoQJZGVlUV1d3aFFnNFo7LittgTWzYO6M+DoDje8ddFjuLi4EB8fz6BBg8jJyWHHjh3ExcUREhLSK9e6L0W8BbVazaBBg0hLS2Pq1KmyiKAB82JJdHQ0J06cIDAw0Ho9H374YatXHiAuLo6ioiJeeuklbr/9dutCZnl5OUFBP7+nysvLGTVqlN32qNVqnJ2d0Wq1DBw40P4T6wWCgoI4efIkBoPBprae8+bN4+abb8ZkMsm6TeWFyOMdCbz88ssoFAoeeOABqU0RCAQCgUAgQ44ePYrBYGDMmDE2zauoqMDNza1PbvZtxRJWLwfOnTtHU1MTYWFhUpvSjtzcXJRKJdHR0X12jN72zO/Zs4eUlBRiYmL47rvvOHDgACaTibS0NFasWEFycrJtOzxzxPxzYMf3ekRsAiaFEkclvP33l7n/yRcAGBzohVLZPRGiVCqJi4vr0CIuOTmZBQsWsHDhQpYuXcrChQu59/abaXp3tlnE+w+Bq/7S7dPw8PBg7NixJCQkkJWV1StF5PpDxFsYMmQIRqNRdiH24eHh6HS6doUNGxsbOyw2qFQqa55/ZGQkGo2G7du3W7db0j8mTpxoty0KhYLQ0FBZtHDz9PTE2dmZyspKm+ZNmDCB+vr6LgsJyhVZCPlDhw7xr3/9i5EjR0ptikAgEAgEApny448/MmXKFJu9x3IJq29ubqayslI2Qj4vL4/w8HBZeeOrq6vJy8sjISGhzz2gvSHmLR0ItFotNTU1fPnll1RWVlr7uw8aNIjq6mrWrFljW+G00nTzz+CEDpuKqxoBCPVzZ/q0aZh+6h8f6d++NZ/leMnJyWRmZl7y+MnJyaxYsYLU1FTUajUREREE+Xlyv+9OXBtLaXYJhIVfgceA7p/HTwQFBTFjxgxUKhU7duygpKTE7uvdXyIe5Bti7+joSHh4OHl5edbn5s2bx1//+le+/fZbCgsL+eKLL3jttde44YYbAKwO0xdeeIHNmzeTmZnJwoULCQ4O5vrrr++RPSEhIZSXl9PS0tKj/fQUhUJBYGCgzXnyTk5OTJo0iR9//LGPLOsbJBfyOp2O+fPn8+67716y3YVer6eurq7dQyAQCAQCwa+DnTt3Mn36dJvmWNp+yUHInzlzBl9f3y77ePcnDQ0NVFRUEBUVJbUpVgwGA2lpaX0WUt8ZPRHzra2tHDx4kMzMTD7//HP27NnTQcgoFAo0Gg3Z2dlkZWV137Dyn8ZqRnTYND7Sl32PzuDtBaMBKKpqACDC72chn5yczF133QXAAw88wMKFC1mwYEGXkQFGo5E333yTqqoqBg8ejIeHB04qBc/HFRPr08bZZiWPH4/F6GH//5GTkxNjxoxh1KhRZGVlcejQIVpbW7s9v79FvIXzQ+zlVMU+MjISrVZrbSf4xhtvcNNNN3HvvfcybNgwVqxYwd13383zzz9vnfPII49w3333sWTJEsaOHYtOp2Pbtm24uLj0yBZ3d3fUajVnzpzp0X56A41GQ1lZmc0LRVdccQU7d+7sG6P6CMmF/LJly5g7d267Vghd8dJLL+Ht7W19hIaG9oOFAoFAIBAIpMZgMLB7926bhXxtbS1Go/GSzoL+4PTp07K5dykoKECj0chiUcHCiRMn+jykvjPsEfM6nY7du3djNBrx8PDg6NGjXV5LV1dX9Hp9l/3dO9DSCNWF5t8HdKxA76BSMlDtypBATwBKqsxCLtTXfHyLZz0jIwOAsLAw1Gr1RcP8s7KyyMnJISgoyJojvDikgNHe1TQblDyRFc2PGUW2LUZ0QXBwMFdccQVtbW3s2bOHhoaGS86RSsRbGDp0KCaTSVYh9u7u7gwYMICCggLA/D5evXo1RUVFNDU1kZeXxwsvvNCuG4VCoeC5554zdz5obuaHH37otbaTISEhsgiv9/f3p62tzeaOCdOnT2fnzp392pqyp0gq5Ddu3EhqaiovvfRSt8Y/9thj1NbWWh9yaHUgEAgEAoGg78nIyMBkMtlclOns2bP4+flJXqiqsbGR2tradkWmpKKtrY2ioiJZeeNramrIz8/v9Sr13cUWMV9RUcHu3bvRaDRMmDABPz8/a3/3zmhqasLZ2bn7i0lV+YAJXNTgEXDJ4aU15uMOVLu186xbXt/uhPlXV1ej1+vbLUb8cC6Qcr0zrxYMo8Tgb9tixCVwdnZmwoQJBAQEsGvXrovmNEst4sFcUyAhIYGTJ0/KKiI4KiqKwsJC2trapDaFgQMHUl1d3ScdCmxBqVTi6+trc2/7MWPG0NjYSHZ2dh9Z1vtI9q1WUlLCH//4Rz766KNuh3M4Ozvj5eXV7iEQCAQCgeCXz86dO5k6darN+dznzp3D39+/j6zqPlqtFj8/P1n0aj99+jTu7u74+vpeenA/YBFqUVFRkt7bXUrMm0wm8vLyOHjwICNGjGD48OEoFIp2/d07m6PVaomNje2yv3sHqvLNP/06bwm4LrmQl7bmkFVqztkuqzULpyC1S6eedQsXC/P38fHpsBhR2OTB0qyxHKz1s30xohtYCu4NHz6clJQUCgoKOr1+Uot4C5a6Ab0RldBb+Pv74+rqKouQdsv7w96e9L2Jv7+/zULekid/OYXXSybkjxw5QkVFBYmJiTg4OODg4MCuXbt4/fXXcXBwkEUvQoFAIBAIBPLA3vz4s2fPykbIyyFPH6CwsJCIiAjZtFmqrKyktra230PqO6MrMW8ymcjIyODkyZMkJSW1q/R/fn/3vLw8dDodBoMBnU5HXl4ePj4+LFu2rPuRBjXF5p/q8E43b8ks41+78smrbKBB34ZOb/bGBnq5dOpZP5+uwvwtixEt1WeIcv05JLnNpLRvMcIGwsPDmThxIidOnODo0aPtrrlcRLyFIUOGUFVVdVGReObMGRYsWICfnx+urq7ExcVx+PBh63aTycTTTz9NUFAQrq6uzJw50+6QfYVCQXh4OEVFRXbN7200Go3Nheb6An9/f86dO2dzmLwlvP5yQTIhf+WVV5KZmUl6err1MWbMGObPn096erpNvf8EAoFAIBD8culJfjwgec/21tZWzp49KwshX1NTg06nk7zfswWTyUR2djZDhgzB0dFRanOAjmLeYDBw5MgRqqqqmDZtWqeRDElJSaxatYqEhARqamooLCykpqaGxMREVq1aZVsf+bpS80/vzl+j2iZzgTgfN0cq6/UAuDmp8HB26NSzfj5dedaVSiXLl93La5N1vDo0jfFuxT1bjLARPz8/pk6dSmVlJampqRgMBtmJeDB7baOjo8nKyupUJFZXVzNp0iQcHR3ZunUr2dnZ/O1vf2t3vVeuXMnrr7/O22+/TUpKCu7u7syaNcvukPSQkBBqa2tlEfKv0WioqKiQPNRfrVZjMBh+8XnykvUb8fT0ZMSI9pU43d3d8fPz6/C8QCAQCASCXy89zY+X2vNcWVmJh4cH7u7ulx7cxxQVFTFw4EDZiOYzZ86g1+uJjIyU2pR2WMT83r17KS0tRaVSMWnSJJydnbuck5SUxIQJE8jKyqK6uhofHx+GDx9uu/jV/RSa7Nl5PYX6ZrNI8nB24FyDWcj7eZhTNiye9bS0NNRqdbt5Fs96YmJip571JEUa+DegNypJK2uj8Gwhzs7OJCYmsmzZMtsWI+zAzc2NyZMnk5yczI8//khbWxuTJ0+WjYi3EBUVRX5+PmVlZQQHB7fb9sorrxAaGsr7779vfe7897bJZGL16tU8+eSTXHfddQCsX7+ewMBAvvzyS2699Vab7XFyciI4OJiioiLi4uLsPKvewcPDA1dXVyorKyWtB3J+nrwt6Tpjx4615sn3RfRJbyN51XqBQCCQGqPRSGZmJrt37+5Wr93eYNGiRSgUChQKBY6OjgQGBnLVVVfx3nvv2XT8tWvXdrhZEwh+aezevZvJkyfbHK0nl/z4srIyWXjj29raOH36NOHhnYds9zdGo5Hjx48TExMjy0hMd3d3vL29aWxsxN/fv1v1DSx531OnTiUuLs4+D3bjOfNPt87fu40tPwv5qgazd97Xzcl6fEuYv6Waebc86+VZsP05ABzn/Y1n12zk7bffZv369XzwwQd9LuItODs74+fnR2NjI97e3rJY/LoQBwcHhg4dSk5OTofv682bNzNmzBhuvvlmBgwYQEJCAu+++651e0FBAVqttl23Lm9vb8aPH8/+/fvttikiIoKSkhLJU5MtdRgu1zx5R0dHJk2axK5du/rIqt5FVkJ+586drF69WmozBALBr4jk5GQWLFjAwoULWbp06SV77fYms2fPpqysjMLCQrZu3coVV1zBH//4R6699lrJw9IEAjlx6NAhxo0bZ9McueTHG41GWfWxd3Nzk0UrPjBHBygUCtm05Dsfk8lEamoqer2eyZMnc+bMGZv7zNtN00/5666dv06NLWax5uKosobZe7v9vMhgCfMfOXIkAMXFxRcP8ze0whdLwdACQ2ajHLO454sRdmDJiddqtUyePJmmpibS0tJkGeYcHh6OyWTq0EErPz+ft956i+joaL777jvuuece7r//ftatWwdgFbiBgYHt5gUGBvZI/Pr6+uLs7Expaand++gtLHnyUr9u9ubJjx07tl1NAzkjKyEvEAgE/Yml125qaqq1Gu2leu32Js7Ozmg0GgYOHEhiYiKPP/44X331FVu3bmXt2rUAvPbaa8TFxeHu7k5oaCj33nsvOp0OMC9+Ll68mNraWqt3/9lnnwXggw8+YMyYMXh6eqLRaPi///s/Kioq+vR8BIK+4siRI4wePdqmOXLJj6+urkahUMhCPJ8+fZqwsDDJUw3AHB1w4sQJYmNjJW8N2BmZmZnU1taSlJSEr6+vzX3me0TLT33VnTuGlJtMJloMZi+ws6OSup+EvKdL+2zZpKQkqyd49erVF/esJ78O2qPmdnfzXgcJ3h8XFrbz9fUlKSmJqqoqWVWJt6BUKhk2bBjHjx9v5wU3Go0kJiby4osvkpCQwJIlS7jrrrt4++23+9QehUJBWFiYLPq4+/r6YjQae61Vob3Ymyc/evRojhw50kdW9S7y++QUCASCfuD8XruDBw/Gw8OjW712+5oZM2YQHx/Ppk2bAPPNwuuvv05WVhbr1q1jx44dPPLII4D5Rm316tV4eXlRVlZGWVkZK1asAMzFtZ5//nkyMjL48ssvKSwsZNGiRf16LgJBb1BfX09ubq7NQv7cuXOyyY8fMGCA5Ha0tLRw7tw5WfSxB8jLy8PNzU0WkQoXUlhYyJkzZ5gwYYI1J96WPvM9pqXR/NOxY+V5owksh3ZUKq1h9p7OHcteWRZIkpKSuvasVxfCrpXm32e/DJ6BHcf0MV1Vp3dxcWHChAkUFxdTXFzc73ZdiuDgYJydncnPz7c+FxQURGxsbLtxw4YNs9pveb9fWNm9N6J2goKCOHv2LK2trT3aT09RKpUEBATYHNbeF3b4+vpy7tw5m+aNHj2arKysLgtGygkh5AUCwa8Se3vt9gcxMTEUFhYC8MADD3DFFVcQERHBjBkzeOGFF/j0008Bc4Ebb29vq70ajcZ6A3THHXcwZ84coqKimDBhAq+//jpbt261evMFgsuFtLQ0NBqNzQK0pqZGFvUjLAX3pKaiogJPT0/c3NykNoXW1lZOnTpFbGys5AscF3Lu3DmOHTvG2LFjO+Rn95uYN/6UWqXsWJBQqYAfHprGDw9NxcvVkYafwuxdneysMeA1EK54HIZeA/G2F1rrKZdqMefh4cGYMWM4evQoVVVV/W7fxVAoFMTGxnLy5ElrOtykSZM4ceJEu3G5ubnWuhSRkZFoNBq2b99u3V5XV0dKSgoTJ07skT0eHh64ublRWVnZo/30Bn5+fpILeTB75WtqamyaExYWhlqt5ujRo31jVC8ihLxAIPhVYm+v3f7AZDJZb25/+OEHrrzySgYOHIinpye33XYb586do7Gx8aL7OHLkCPPmzSMsLAxPT0+mTZsGIEuvhkBwMVJTU232xoM8hLzBYKC6ulryPH2QVx/7kpISPDw8ZLHAcT6NjY0cPHiQ4cOHd/ma9YuYN/0Uqq3sKM4VCgWDB3gweIAnKqUCfas5aszF0U4hr3KESX+EWzfYHFLf00Kx3e0TP2DAAIYNG8bBgwdl5yUNCAjA1dXVGtL+4IMPcuDAAV588UVOnTrFhg0beOedd1i2bBlgfv0eeOABXnjhBTZv3kxmZiYLFy4kODiY66+/vsf2yKnQXFVVVb9HNV6IPUJeoVAwevRoUlNT+8aoXkQIeYFA8KvE3l67/UFOTg6RkZEUFhZy7bXXMnLkSD7//HOOHDnCmjVrAHOYbFc0NDQwa9YsvLy8+Oijjzh06BBffPHFJecJBHLEnvz4trY2dDqd5EK+uroaJycnyStvy6ngnslkIj8/n6ioKFl549va2khJSSE4OPiSrfD6XMwrfhLlxktXIG/5KT/bSWXjLb2hrf3+bXwtelootrsi3kJUVBSBgYEcPHhQ8srs56NQKKzt6EwmE2PHjuWLL77g448/ZsSIETz//POsXr2a+fPnW+c88sgj3HfffSxZsoSxY8ei0+nYtm0bLi4uPbZHLoXmPD09UalUNovo3katVlNfX2/ze+ZyyZMXQl4gEPwqsfTa1Wq1Hb7wLL12Y2Nj+72P6I4dO8jMzOTGG2/kyJEjGI1G/va3vzFhwgSGDBnSoSKtk5NThy+o48ePc+7cOV5++WWmTJlCTEyMKHQnuGyxt9Cds7Nzr9wY9wRL1XypBeu5c+dQqVSSL2yAOcS/ra2NgQMHSm1KOzIzM3F0dOx2H+4+FfOqnyrQG/Sdbl7z4yle2Xac2qZWDEbzcR2UNr7H0tbD25Ph1PZLj72AnhaKtVXEg1kwjxw5EqVSybFjx2y2uS8JCQlBr9dbQ9qvvfZaMjMzaW5uJicnh7vuuqvdeIVCwXPPPYdWq6W5uZkffviBIUOG9Iotvr6+AJKnISgUCrvav/U2rq6uODg4UFdXZ9M8IeQFAoFAxpzfazcvLw+dTte9Xru9iF6vR6vVcubMGVJTU3nxxRe57rrruPbaa1m4cCGDBw+mtbWVN954g/z8fD744IMOlW8jIiLQ6XRs376ds2fP0tjYSFhYGE5OTtZ5mzdv5vnnn++z8xAI+gqdTsfx48dtFvJyCKsH+eTHW8LqpV5QAHORu8jISFlVqtdqtZSWljJ69Gib7OozMW8pctfaecTYWzvzeGtnHtUNLVYhr7RFyLc2wc5XoCIbzp60ybSeFoq1R8RbUKlUjB49mtOnT8tqcVqlUhEREdGu6J1UKBSKHrey6y3kkCevUCjsCq8fPXo0x44do7m5uW8M6yXk8ykqEAgE/Yyl125CQgI1NTUUFhZevNduL7Nt2zaCgoKIiIhg9uzZ/Pjjj7z++ut89dVXqFQq4uPjee2113jllVcYMWIEH330ES+99FKHc1i6dCm33HILAQEBrFy5koCAANauXctnn31GbGwsL7/8MqtWrerTcxEI+oL09HQCAwMJDg62aZ4chLxc8uMtEUZyCKtvaGjg3Llz1sJfcqClpYX09HRGjBjRZc2Ui9EnYt7Fy/yzuXMvoiUfvrHFgAI7FmeOrAWdFrxDYcxim6b2pFBsT0S8BTc3N2JjY0lPT7epOvvLL79szU+30NzczLJly/Dz88PDw4Mbb7yxQzX57hIREUFFRcUl69f0ByJPvj32CPnw8HC8vLzIzMzsG6N6iY69KgQCgeBXRFJSEhMmTCArK4vq6mp8fHwYPnx4n3uL1q5da+0VfzEefPBBHnzwwXbP3Xbbbe3+fuutt3jrrbfaPff73/+e3//+9+2ekzpnTiCwldTUVBITE22eV1tba7P4722qq6txdHSUPD++vr4evV5PQECApHYAFBUVERgYKHnKw/kcO3YMb29vwsLC7N6HRczv27cPMLcb61H0g+tPtVmaOg+P9nRx4KxOj07fhuWrymjs5ud7mx72/cP8+5Q/gYOzTaZ1p1BseXl5h0KxvSHiLURERFBaWkpWVhajRo265PhDhw7xr3/9i5EjR7Z7/sEHH+Tbb7/ls88+w9vbm+XLl/Pb3/7W+jragqurKwMGDKC4uJiYmBib5/cmAwYM4MiRI+h0uh5d555yfp68JeRfCtRqNbm5uTbNOb/g3dixY/vIsp4jPPICgeBXj1KpJC4ujqlTp3bda1cgEPQ7x48f79CT+VK0tbVRX18vuUfesjAodTi7VqslICAAlcrOqua9hNFopLi4mIiICEntOB+tVktZWRmjRo3q8evUq555j596ues6Dx/3cjH74WqbWnH46fuqtbtC/ugnUF8GnsEwav6lx1+APYVie1PEg1lkJSQkcObMmUuG2Ot0OubPn8+7777bzqba2lr+85//8NprrzFjxgxGjx7N+++/T3JyMgcOHLDLrvDwcIqLiyVfNHdwcMDf319yr7xCocDHx0eS7j/n4+3tTV1dnc0F74YNG8bx48f7yKreQdytCgQCgUAgkCW5ubk2F4GSS6G72tpayRcTQD5t58rLy1EqlbKIDABzL/uehNR3Rq+JeYuQry/rdLOPu7kYXnVDC44/VatvaetG+LLJBMlvmn+feC84ONlsmq2FYntbxFtwc3Nj+PDhpKWlWXu4d8ayZcuYO3cuM2fObPf8kSNHaG1tbfd8TEwMYWFh7N+/3y6bAgMDMZlMssjfl0t4vbe3N7W1tZLa4ObmZlfBuyFDhtjsye9vhJAXCAQCgUAgS06ePGmzkK+vr8fLy0tyT7gc8vSbm5upqakhMDBQUjsAiouLCQsLk/x1sXDq1Ck8PDx6FFLfGb0i5tWh5p/VRZ1u9nM3h8OfbdDj6mS+la/VNVJYWEhGRgaHDh3iwIEDpKSkAHD48GEOHTrEqe3r4OwJTI7uGOIX2G4XthWK7SsRbyE8PBxXV1fy8vI63b5x40ZSU1M71JYB8wKXk5NTh//RnhSKUyqVhIWFUVxcbNf83kSj0VBVVSV5y1l78tN7G4VCgZeXF/X19TbNE0JeIBAIBAKBwA6ampooLi62Wcg3NDRImhcKZm9vQ0OD5EK+oqICtVoteXSCwWCgsrJS8roFFpqbm8nLyyM2NrZPFhZ6LOZ9Isw/qws63ezrZk6TyMo7Tdlps2gsOlPGmTNncHBwwMfHp12RSH9/f3x8fNBrRpM96lmyBt7Ct9v3sHPnTtLT0yksLESv77zVXWd0p1BsX4t4MAu02NhYTp061cH+kpIS/vjHP/LRRx/16/s/KCiIiooKyQu8ubq64uXlJXl0gKWP+8WiJvoDDw8PdDqdTXOGDBlCQUGB5IshF0MUuxMIBAKBQCA7Tp06haenp81h4TqdTvJK8TU1Nbi4uODsbFshsd6murpaFu3vKisrcXZ2xtPTU2pTAHPKRkBAQJ8W4OpRATz/oeafVfnQ1gIOThiNRrRaLcXFxQxsrOCvU7wZFOTDAa0RTp5BHaBh0qT2bRpbW1vJzMwkIiICR0dH85Mj4jCZTEQ2NlJTU0NNTQ0lJSUcPXqUwMBAwsLCCAwMvGStmIsViu0PEW/B398fX19fTp48yYgRI6zPHzlyhIqKinbFMg0GA7t37+bNN9/ku+++o6WlpUPkTHl5eY9SUby9vXFwcODs2bMMGDDA7v30Br6+vlRVVRESEiKZDZbPwbq6OkkL3nl4eNicqx8aGoqDgwMFBQUMHTq0jyzrGULICwQCgUAgkB2W/HhbPaY6nU7ygmpyyY+vqalh0KBBUpshqz72DQ0NFBUVMW3atD4/lt1i3isYnL1BX0urNptivSd5eXkoFArCwsL43ciRuLm5AVCaeho4Q31z9z2eCoUCd3d33N3dGThwIGC+LiUlJWRmZnLs2DGioqIIDw/HwaFrqWApFHs+/SniLcTGxrJnzx6ioqKs1+XKK6/s0Dps8eLFxMTE8Oc//5nQ0FAcHR3Zvn07N954IwAnTpyguLiYiRMn2m2LpQWfVquVXMir1WqKijpPz+gvFAoF3t7ekleud3d3p6SkxKY5SqWS6OhocnNzhZAXCAQCgUAg6C72FLozGo2yCK2XQ3680Wikrq5OcjssBdBGjx596cH9QE5ODiEhIXh5efXL8ewS8woFJs0IFEX7yNm+geqIuYwYMaLT3u1qN7OnvabxEj3VN84H/2iYuBzcO0asuLu7ExMTw5AhQygrK+PkyZOcOHGC4cOHd7u2gRQiHsxe8KCgII4fP271wHt6erbz0IP5HP38/KzP33nnnTz00EP4+vri5eXFfffdx8SJE5kwYUKP7NFoNGRkZBAXFyfp4pVarebo0aOYTCbJ7ZA6T97Dw4OGhgabr4Xc8+RFjrxAIBAIBALZYY+Qt7TEsnjlpKK2thZvb29Jbaivr0epVErex76mpgaDwSCLEP+6ujrKysr63btma858U1MTZQpzePdg1zqmTp1KcHCwVYCYTCb+vSefJ77IxOmnqvVVDRfJ463Kg+PfQPIbwMVFjFKpZODAgUybNo2EhARycnJISUnpst2cBalEvIWYmBjOnDljUx703//+d6699lpuvPFGpk6dikajYdOmTT22xd/fn5aWFpuLq/U2ltdAajvUarXklevd3d0xGAw0NzfbNE8IeYFAIBAIBAIbsUfI63Q63N3dJfU+WaICpM4Ht0QFSB3OrtVqu5Vz3R/k5+cTEhIiyUJPd8S8yWSiqKiIHTt20BwwCgC3yvQOr6FCoeDdPfl8lFKMTm8Oqa/U6btcIFAe/9b8S8QUcO/egopCoSAoKIgZM2bg6OjIjz/+2GWPdKlFPJiFWnBwMPn5+V2O2blzJ6tXr7b+7eLiwpo1a6iqqqKhoYFNmzb1SqtGlUrFgAEDKCvrvH1gf6FUKvHy8pJcRFsKzdndjrEXsCxq2lPwTgh5wWWP0WgkMzOT3bt3k5mZKXk1ToHg18T06dN54IEH+vQYzz77LKNGjbrkuKeeeoolS5b0qS3d4dFHH+W+++6T2gxBH5Kbm0t0dLRNc3Q6neRh9Y2NjSgUCsmjAmpqaiSPCoCeFw/rLVpaWjh9+jRRUVGS2XAxMd/U1MSBAwc4fvw4Y8aMIWr6/5k3VOaArrLDvqIHmBeKzunMnviWNiN1TZ3nyStyt5p/GXatzTY7OTkxevRoEhMTyc7OJiUlpZ1XUw4i3kJUVBTFxcW0tl4izaAfCAwMpLy8XGozZBHW7u7ujslkumRUR3/YYY+QP3HiRB9Z1HOEkBdckuTkZBYsWMDChQtZunQpCxcuZMGCBSQnJ0ttmkBwWbJo0SIUCgVLly7tsG3ZsmUoFAoWLVpkfW7Tpk08//zz/Whh52i1Wv7xj3/wxBNPSG0KK1asYN26dRf1vgguX5qamjh79izh4eE2zZODkJdDVADII0+/sbGRuro6yYt+ARQVFaFWqyVf3OhMzOt0Ovbs2YOTkxMzZswgMDDQnMce+FMhufwfO+xnSKBZyOdVNljz5MvqOgolx7Z6FKVHfpo02267NRoNM2bMQKVSsWfPHmu+sVxEPICPjw9eXl6y6eNeU1Njcyh3byMHIa9UKnFzc7NZRPc29rSgCw8Pp6ysTBaLQ50hhLzgoiQnJ7NixQpSU1NRq9VERESgVqtJS0tjxYoVQswLBHYSGhrKxo0b261QNzc3s2HDBsLCwtqN9fX1lTxMF+Df//43SUlJNosrW+lOz1Z/f39mzZrFW2+91ae2CKShrKwMBwcHm9vINTQ0SJ4TLgcb5FLorry8HD8/P5ycnCS1wxKyLnU3Awvni/n09HT27NlDSEgIiYmJP7eJA4ieaf558n8d9jEsyPydkF1WS7C3KwClNR2FfEB9NgqTEQbEgnfP2pA5OTkxZswYgoKC2LNnD6mpqRcV8S+99BJjx47F09OTAQMGcP3113fwbjY3N7Ns2TL8/Pzw8PDgxhtv7JEnOyIigqKiIknDuAGcnZ1Rq9WSe+Ut+elSXw93d3caGhouOxsCAwNRKBSSv45dIYS8oEuMRiNvvvkmVVVVDB48GA8PD1QqFR4eHgwaNIjq6mrWrFkjwuwFssJkMtHY0tbvD1u/JBMTEwkNDW1XWGfTpk2EhYWRkJDQbuz5ofXHjx/Hzc2NDRs2WLd/+umnuLq6kp2dDZg9cX/4wx8ICAjAy8uLGTNmkJGR0W6fL7/8MoGBgXh6enLnnXd2y2uwceNG5s2b1+45vV7P/fffz4ABA3BxcWHy5MkcOnTIun3t2rUdxMSXX37ZzltpCev/97//TWRkJC4uLgD897//JS4uDldXV/z8/Jg5c2a7L+F58+axcePGS9otuPwoKytDo9HYnFfd3NyMq6trH1nVPeQQFSCXQnfV1dWStpyycO7cOVpbWwkKCpLaFCuenp7Ex8dTXFyMp6dn59Xsh8wx/8z9Dtr07TaNGGiOLMg6U8dAtfkz83R1RyHvr8sx/xLZO+32FAoFsbGxuLm5cfr0aeLj47t8v+/atYtly5Zx4MABvv/+e1pbW7n66qvbfY4/+OCDfP3113z22Wfs2rWL0tJSfvvb39ptX3BwME1NTTb3DO8L/Pz8JLfDw8PDGvUhtR1S2+Dq6mpzhISjoyP+/v6S1zvoCtF+rpcxGo1kZWVRXV2Nj48Pw4cPl0WBF3vIysoiJyen03Ynlj6Z2dnZZGVldegjKhBIRVOrgdinv+v342Y/Nws3J9s+Uu+44w7ef/995s+fD8B7773H4sWL2blzZ5dzYmJiWLVqFffeey+TJ09GqVSydOlSXnnlFWJjYwG4+eabcXV1ZevWrXh7e/Ovf/2LK6+8ktzcXHx9ffn000959tlnWbNmDZMnT+aDDz7g9ddfv2juaFVVFdnZ2YwZM6bd84888giff/4569atIzw8nJUrVzJr1ixOnTpl0w38qVOn+Pzzz9m0aRMqlYqysjJ+//vfs3LlSm644Qbq6+vZs2dPuwWTcePGcfr0aQoLC2XjaRP0DqWlpXaJrubmZpydnfvAou6j0+kICemZ57OnWPLj5RDeLwfxXFxcTEhICCqVSmpTrOh0OjIyMoiKiuLMmTPk5OR0FPMhY8EzCOrLIG8HDJ1j3RQ9wAMXRyX1+ja8Xc1e/KJzjR2O06Z0weQ1EEXE5F6x22QykZ2dTVNTExEREWRkZODp6dnpotG2bdva/b127VoGDBjAkSNHmDp1KrW1tfznP/9hw4YNzJgxA4D333+fYcOGceDAAbvawDk4OBASEkJxcbHki0hqtZqTJ09KaoNSqbT2cZcyss/DwwOtVivZ8cEcJWFPqkNwcDClpaV9YFHPuTwVpkz5peWSV1dXo9fru/RuuLq6otfrJV9tFAguVxYsWMDevXspKiqiqKiIffv2sWDBgkvOs4j4BQsWsGjRIsaOHWst/LZ3714OHjzIZ599xpgxY4iOjmbVqlWo1Wr++9//ArB69WruvPNO7rzzToYOHcoLL7xgXQToCku14uDgYOtzDQ0NvPXWW7z66qvMmTOH2NhY3n33XVxdXfnPf/5j07VoaWlh/fr1JCQkMHLkSMrKymhra+O3v/0tERERxMXFce+997bz/FhsKSoqsulYAvlTVlZmswA0GAy0trZaIzqkQvSxN9PW1kZ9fb3kdhiNRsrLyxk4cKCkdpxPS0sL+/fvJyQkhBEjRnRdzV6phOE3mH8/+km7fTiolIwcqEapAMefWtAVnu0YNpw98Fba7suAmLk9tvvCnPiRI0cSFBTE/v37u5VDbKmebhHYR44cobW1lZkzZ1rHxMTEEBYWxv79++22Mzg4GK1WK3k4uVqtpq6uDoPBIKkdFiEvJXIIrXdxcUGv19scSRwUFCQ88r90LLnkVVVVBAUF4erqSlNTkzWXfNWqVSQlJUltpk34+Pjg7OxMU1NTpzclTU1NODs74+PjI4F1AkHnuDqqyH5uliTHtZWAgADmzp3L2rVrMZlMzJ07t9s5we+99x5DhgxBqVSSlZVl9eJkZGSg0+k69GxuamoiLy8PgJycnA6F9iZOnMiPP3YsqHT+fKCdSMrLy6O1tZVJkyZZn3N0dGTcuHHk5OR06zwshIeHExAQYP07Pj6eK6+8kri4OGbNmsXVV1/NTTfd1O7zxrLI2NjY0QsluLwpKytrt2jUHSyeFik98gaDgaamJslD2mtra4mMjJTUhrq6OpydnSVfWLE4G+R0r5KZmYmnpyfDhw9HoVBYc+b37dsH0N4zH38rHPgnHN8CjVXg9rOX+ZWbRuLv4UTm6Vo+PlRCXuVFQpd7GJ3RVWG7uLg49u/fz7FjxzqkhZ2P0WjkgQceYNKkSYwYMQIwF1B1cnLqsNgTGBjYI++tn58fRqORmpoaSV93Nzc3HBwcJF/QUqvVlJSUSHZ8MHvkGxsbMRqNkkUqWz6LLuak7Aw5C3nhke8Ffqm55MOHD2fYsGGdrmqaTCa0Wi2xsbEMHz5cIgsFgo4oFArcnBz6/WFvCOsdd9zB2rVrWbduHXfccUe352VkZNDQ0EBDQ0O7LxidTkdQUBDp6entHidOnODhhx+2y0bAusBgawSOUqns8PnRmefmQuGjUqn4/vvv2bp1K7GxsbzxxhsMHTqUgoIC65iqqiqAdgsAgl8G9njk9Xo9Li4ukoaTNzc3o1AoJF1MMJlM1NXVSV6dXS7h/ZY+9lLbYaGsrIzy8nLi4+Pb2dRlazrNSNDEgUEP6Rva7SvS3x1PF0cGDzCL6uKqRppbz/P+tjZCL3ilL1adXqFQMGrUKEpLSy9aEGzZsmUcO3asX+qaKJVKBgwYIHkot0KhkIU33Nvbm7q6OkltcHFxwWQyodfrLz24j1AqlTg5OdlsgxDyv3BsySW/nFAqlSxfvhwfHx/y8vLQ6XQYDAZ0Oh15eXn4+PiwbNmyy7YGgEAgB2bPnk1LSwutra3MmtW9SIKqqioWLVrEE088waJFi5g/f77VY56YmIhWq8XBwYHBgwe3e1jE+LBhw0hJSWm3zwMHDlz0mIMGDcLLy8taUM/ynJOTk9WLBGaRfujQIWuofkBAAPX19e1C6tLT07t1ngqFgkmTJvGXv/yFtLQ0nJyc+OKLL6zbjx07hqOjo1hM/AViT468HPLjLTZIKRrb2towGAySF/2TQ3g/mIW8HPrYgzmkPiMjw1rE80I6FfMKBYz9g3nAoXfB2DFMO8DTGbWbI0YTnKr42Suv2vowczLvRZH5qd02d6fFnJubGyNGjCA9Pb3Thdrly5fzzTff8OOPP7arH6HRaGhpaekgdMvLy3v8mmk0GsmFPMij/Zurqyutra2ShvhbRLTU7fhcXFxstkHkyP/C+SXnkiclJbFq1SoSEhKoqamhsLCQmpoaEhMTL8t0AYFAbqhUKnJycsjOzu52IaalS5cSGhrKk08+yWuvvYbBYGDFihUAzJw5k4kTJ3L99dfzv//9j8LCQpKTk3niiSc4fPgwAH/84x957733eP/998nNzeWZZ5655EKjUqlk5syZ7N271/qcu7s799xzDw8//DDbtm0jOzubu+66i8bGRu68804Axo8fj5ubG48//jh5eXls2LCBtWvXXvIcU1JSePHFFzl8+DDFxcVs2rSJyspKhg0bZh2zZ88epkyZIrlgEfQ+9njkm5ubJQ/jlosNKpUKBwdpsydra2sljwrQ6XQ0NjbKoo89mEPqfXx8LloMsVMxH3czuPpAdSHkfN1u/MaDxdzwz2R83cwt/nLKzvO8njuJk6EBHO37jLSlT3xYWBheXl4cO3as3fzly5fzxRdfsGPHjg7pHqNHj8bR0ZHt27dbnztx4gTFxcVMnDjRLpstBAYGUl9fL3nqlRw88k5OTigUistSRPc29hS8k7NHXuTI9wK/9FzypKQkJkyY8Iupxi8QyA0vL69uj12/fj1btmwhLS0NBwcHHBwc+PDDD5k8eTLXXnstc+bMYcuWLTzxxBMsXryYyspKNBoNU6dOJTAwEIBbbrmFvLw8HnnkEZqbm7nxxhu55557+O67i1f7/8Mf/sBdd93FypUrrf//L7/8Mkajkdtuu436+nrGjBnDd999Z/288/X15cMPP+Thhx/m3Xff5corr+TZZ59lyZIll7wmu3fvZvXq1dTV1REeHs7f/vY35sz5uWrzxo0befbZZ7t97QSXD0LI98wGqaMCDAaD5HnBYPbs+vv7S76oAT+H1M+YMeOSr02nOfPjlsCuV2DP3yD2OmvOu7aumfSSGiL83ADIKq3j5p/2o6gy10Ux+Q6y2V5bRDz8HGK/Y8cOgoODCQwMZNmyZWzYsIGvvvoKT09Pq4fc29sbV1dXvL29ufPOO3nooYfw9fXFy8uL++67j4kTJ9pVsf58HB0d8fPzQ6vVXrQjS1+jVqupr6+XNDfcku7T3Nwsaf0OS7E5KbHHBjkLeYVJ6pKOPcCSA1ZbW2vTjXBvYzQaWbBgAWlpaQwaNKjdB7TJZCIvL4/ExEQ++OADIX4FAsFli8lkYvz48Tz44IP8/ve/l9SWrVu38qc//YmjR4/K4iZdTsjlu9FejEYjKpWK4uJiQkNDuz0vNTUVNzc3YmJi+tC6i5OdnU1rayvx8fGS2VBSUkJhYSFTpkyRzIaqqipSUlKYPXu2pAsKhw4dwtvbmyFDhkhmA5g/O7dv3050dDTh4eHdnldfX8++ffsICwtjWPgAFP+IhxYd3PIhDJsHQEZJDdet2YezgxJ9m5HR4T58fk8SNNfCy2EA6P+UT25habedMbaK+PPJz8+nsLCQK664ostjvP/++yxatAgwLzz96U9/4uOPP0av1zNr1iz++c9/9ko6xPHjx2loaGD06NE93pe9mEwmtmzZwqRJkyRd2Nq1axeDBw+WtHtDWloarq6ul91ndF5eHjExMbS0tMim1oYFoSp7AZFLLhAIfg0oFAreeecd2trapDaFhoYG3n//fSHif4HodOYcX1t7Hre0tODk5NQXJnUbOXjkLUX/pKS+vh4vLy/Jb3pra2v7TDwZjUYyMzPZvXs3mZmZFy1orNVqMRgMNi1MwQVh9kUVmMb/1G1k+/NgMH8Oxw30JsDTGX2b+fjHztTSajBC7RkAWlTu3LXswW63Ru6JiAdzB5KWlhYqKiowmUydPiwiHswe0jVr1lBVVUVDQwObNm3qtZoGcshPVygUeHl5UV9fL6kdl2tYe1/YYKtH3tPTk7a2NlpaWvrIKvsRyrKXELnkAoHg18CoUaO47bbbpDaDm266ifHjx0tthqAPsAh5WwVEW1ub5As7cim4J7WQl4MNra2tNDQ09EmefnJyMgsWLOhSHF8o8k+dOkVUVJRdDp3zxfwJv6sxufrC2RNw5H0AlEoFV8Wa06YcVQr0bUZznrzOXEG+2VFNRkYGarWaiIgI1Gq1tTXyhWK+pyIezHVfIiMjOXXqlM1zextvb290Op3ki89yENFyCWuX+jo4ODjY/H6wLCpLvRjTGcKV0YuIXHKBQCAQCHpGfX09Li4uNotyOQh5OXjDm5ubJS8yJ4frUFNTg6ura68vrCQnJ7NixQqqqqoICgrC1dWVpqYmqzi+/fbb2bVrFzk5Oej1ekJDQ1myZAkKhYLo6Gi7jnl+zrx3zGKC0v4GO16A2OvBI4BrRgSxIaXYOv5wYTUjvCpRAnoHL6KigqzixdIaOS8vjzVr1jBhwgRrm9CeingLERER5ObmotPperSfnmJ5/Wtra/Hz85PMDrmI6PO7x0hlg9TXwR4h7+LiglKppL6+3tr9Ry4IhdnLKJVK4uLimDp1KnFxcULECwQCgUBgA/X19TaH1YM8hHxrayuOjo6S2iCiAsz0Rfs7o9HIm2++SVVVFYMHD8bDwwOVSmUVx2fOnOHJJ58kNTXV6gEfP348mZmZPPLII12Gs3cHi5g/6jSaJnU0NNfA/54AYEKUL77uTrQazGWvDhZUUVRRz4Gz7tS4RXXZGjkrK4svvviCXbt2sWvXrl4R8WAOX9ZoNBQXF196cB8jh/B6OXii5RDW7uDg0Gl7wv5EpVLZ3IZPoVDg6elpjRaTE0JlCgQCgUAgkA32evEMBoPkQr6tra3bbST7CjmIaDksJvRF+7usrCxycnIICgrqNP+/ubmZ+vp6BgwYgIeHBw4ODgwbNozSUnOhuTVr1lw0l/5SeHp6kjR5KukhizAplHD0EzixFQeVkptGhzBxkNnrfLCwiiLHwdyzL5Dsgbd0uq/m5mYKCgp49NFH2bx5M8XFxXz++eccPXrUbvvOJywsjJKSEqSuqa1Wq6mtrZXUBjmIaDksJtjjDZeLDR4eHrIMrRdCXiAQCAQCgWy4nD3ycrBBLkJeaht0Op1d76OLUV1djV6vx9W1Y1/2+vp6mpqaUKlUVqHg7++PUqmkrKwMjUZDdnY2WVlZPbLB09OTEbNup1AzFwDT5vtBV8Hj1wxj3eJxuDmpqGpooRaPLhdTqqqqyM7ORq/Xc+ONN5KYmMimTZvYs2dPp7nz9hAQEEBbW5vkIloOnlQ5iOjLNaxdLjbI4X3UGULICwQCgUAgkA32CDCTySS5iDYajZhMJkltaGtrw2AwSCqiTSaTLHLk+2IxwcfHB2dnZ5qamjpsa21txWAwoFKprOkV/v7+VFZWAuZ8bb1eT3V1dY/t8PT0xP/m16h3DUXRUIHpi6VgNOLkoGRClNkrX2b6ue3e+V5xk8lEYWEhzc3N/OEPfyAuLo4tW7ZgMBgYNGhQr0QOgDnVVHjDzchFyLe0tPT4de0JDg4OGAwGSaM0eiLkhUdeIBAIBAKB4CLU19fbHFpvyXmUWkRLbUNzczNKpVLSPP3W1laMRqOkQt5oNPbJYsLw4cMZNmwYWq22gxixiBRXV1frQpS/vz/nzp0DoKmpCWdnZ3x8fLq0ubvt7AA8fQeg/N1aDEonFHnbMe18CYDYIPOx1Ufe4L3o7xl+5mMKCgqsrZHLy8s5d+4cixYtYvz48WzZsoW6ujrg59z53ogcAHPVeDnkp+v1eknFo4uLCwaDQdL8cEt0hpQLCpbPRltz1HvbBqPRaPOChoeHh/DICwQCgcB2pk+fzgMPPNCnx3j22WcZNWrUJcc99dRTLFmypFv7tMXu/jjHy4VHH32U++67T2ozJMOe0Ho5iGiLDVLmyLe0tODo6Chp//bm5mZUKpWkr4UlhLi3hbxSqWT58uX4+PiQl5dnFcc6nY6Kigo8PDzahd37+/tz9uxZTCYTWq2W2NhYhg8f3mG/l2pn1xXukWNouXolAIrdK2lK38S7ewoAqKiuw8HQiMqoZ+TIke1aI99+++1MnjyZbdu2WUW8hd6MHJBLoTmj0SipiHZ0dESpVEoa2q5QKHBycpK0F7rlM0HK8Hp7bRAeeYFAIBAAsGjRIhQKBUuXLu2wbdmyZSgUChYtWmR9btOmTTz//PP9aGHnaLVa/vGPf/DEE09Yn7Ocy4WPU6dOycbu7vDOO+8wffp0vLy8UCgUnd58pqamctVVV6FWq/Hz82PJkiUdVui3b99OUlISnp6eaDQa/vznP7e7YThx4gRXXHEFgYGBuLi4EBUVxZNPPtnuJnPFihWsW7eO/Pz8Pjvfzti9ezfz5s0jODgYhULBl19+2W67Tqdj+fLlhISE4OrqSmxsLG+//Xa7Mc3NzSxbtgw/Pz88PDy48cYbKS8vbzdm8+bNDBkyhKFDh/LNN990sKOhoQF3d3ebbG9ra0OpVEraKcYS2i+liDaZTJJ3y5FDfrxer8fJyalPrkVSUhKrVq0iISGhnTgePXo0f/3rXwkODiYvL4+mpibUajXFxcXk5eXh4+PDsmXLOthkaWd3fqX7i/V6vxDXCYtpSbgDAOev72Z5tFmAN5mcAFAaW/nXv/7F+vXreeutt1i5ciWTJk3i888/7yDi4dKRA7agVqupq6uTPJzbwcFBUk+0QqGQRYi/QqGQNDLB8hktpZC3LLTaaoO7u7vdHvk1a9YQERGBi4sL48eP5+DBg9ZtJ06cYNKkSYSEhPDCCy/YvG8h5AUCgUACQkND2bhxY7tcy+bmZjZs2EBYWFi7sb6+vr1etMke/v3vf5OUlER4eHi752fPnk1ZWVm7R2RkpOR22+J5aGxsZPbs2Tz++OOdbi8tLWXmzJkMHjyYlJQUtm3bRlZWVrsFl4yMDK655hpmz55NWloan3zyCZs3b+bRRx+1jnF0dGThwoX873//48SJE6xevZp3332XZ555xjrG39+fWbNm8dZbb9l+0j2goaGB+Ph41qxZ0+n2hx56iG3btvHhhx+Sk5PDAw88wPLly9m8ebN1zIMPPsjXX3/NZ599xq5duygtLeW3v/2tdbter2fZsmX885//5M033+See+7p8DrZk+tuNBolF7ByqFgvh+sgh+4Bfb2YkJSUxIcffsj69et5++23Wb9+PR988AF33323VeRbQrqLi4tJTExk1apVJCUltdvPpdrZdTdf3enaV2mLmonS0MJdxQ8zRFFCI+ZQagejnrvvvpu6ujr8/Pxwc3Nj7969nDhxooOou1TkgK24u7tb+29LiRxEtKOjo6Qh5WAW0lJ3EZC64J1CoUCpVNq8uGRJnbGVTz75hIceeohnnnmG1NRU4uPjmTVrFhUVFQAsX76cBQsW8NVXX/HVV1/ZXGhSCHmBQCCQgMTEREJDQ9m0aZP1uU2bNhEWFkZCQkK7seeHnR8/fhw3Nzc2bNhg3f7pp5/i6upKdnY2YO6f/Ic//IGAgAC8vLyYMWMGGRkZ7fb58ssvExgYiKenJ3feeWe3bnI2btzIvHnzOjxv6Rl8/kOlUnUIl//nP/9JdHQ0Li4uBAYGctNNN7Xbj9Fo5JFHHsHX1xeNRsOzzz7bbvulzsuSHvDvf/+byMhIm27kH3jgAR599FEmTJjQ6fZvvvkGR0dH1qxZw9ChQxk7dixvv/02n3/+OadOnQLMX9gjR47k6aefZvDgwUybNo2VK1eyZs0a641sVFQUixcvJj4+nvDwcH7zm98wf/589uzZ0+548+bNY+PGjd22vzeYM2cOL7zwAjfccEOn25OTk7n99tuZPn06ERERLFmyhPj4eKt3oba2lv/85z+89tprzJgxg9GjR/P++++TnJzMgQMHALOQV6lUjBo1ioSEBBwcHDqEmxqNRskFsT3IwRtuMpkkjQgAeSwmWDzyfYlSqSQuLo6pU6cSFxdnPWeLyH/sscfw8vKyivwLRTxcvJ2dTfnqKgccbllHnddQXAw6PnL8Ky6Y/68c2ho5evQoW7ZsoaCggEmTJrFo0aJO0wMuFjlgDwqFAi8vr049//2JHCq2KxQKSSMT5GSD1IsJ9nxG2iP+AV577TXuuusuFi9ebI1ic3Nz47333gPMnTBGjx7NyJEjCQ4OtjkVRQh5gUDwi6Sxpa3LR3OroVfH2ssdd9zB+++/b/37vffeY/HixRedExMTw6pVq7j33nspLi7m9OnTLF26lFdeeYXY2FgAbr75ZioqKti6dStHjhwhMTGRK6+8kqqqKsAs/J999llefPFFDh8+TFBQEP/85z8velxLu6IxY8bYda6HDx/m/vvv57nnnuPEiRNs27aNqVOnthuzbt063N3dSUlJYeXKlTz33HN8//331u2XOi+AU6dO8fnnn7Np0ybS09PtsrUzOgvVteTC7t271zrmwsUDV1dXmpubOXLkSKf7PXXqFNu2bWPatGntnh83bhynT5+msLCw186hpyQlJbF582bOnDmDyWTixx9/JDc3l6uvvhqAI0eO0NraysyZM61zYmJiCAsLY//+/QB4eXmxePFigoKCCA4O5p577ukQtWGPEJSDgBU2yMcGqReDlEolGo2GgICAdiL/Qi7Wzg4unq9+YXG8NpULf0oN41S9CwHKOu51MEfKGPT13HzzzQwZMoRvvvkGNze3LtMDuooc6AmOjo6StxyzV4T1JnIRsMIGM7baoFKpbH4PtbS0cOTIkXbfiUqlkpkzZ1q/E5977jlmzpyJm5sbSqWSWbNm2XQMm2OfkpOT+eGHH8jPz6exsRE3NzeioqK4+uqru/RkCAQCQX8T+/R3XW67YmgA7y8eZ/179PM/0NTaecjU+EhfPrl7ovXvya/8SFVD+1Dgwpfn2mXjggULeOyxxygqKgJg3759bNy4kZ07d1503r333suWLVtYsGABTk5OjB071locbe/evRw8eJCKigprldpVq1bx5Zdf8t///pclS5awevVq7rzzTu68804AXnjhBX744YeLeuWLi4sxmUwEBwd32PbNN9+0qzI+Z84cPvvssw7z3d3dufbaa/H09CQ8PLxD5MHIkSOtIebR0dG8+eabbN++nauuuqpb5wXmL87169cTEBBw0WtoKzNmzOChhx7i1Vdf5Y9//CMNDQ3WkPmysjIAZs2axerVq/n444/53e9+h1ar5bnnnms3xkJSUhKpqano9XqWLFliHWfBcp2LioqIiIjo1XOxlzfeeIMlS5YQEhKCg4MDSqWSd99917ogo9VqcXJyQq1Wt5sXGBiIVqu1/v3MM8/wwAMPoFQqO029uFyFPNjn6elNRFSAfGzozmLC+e3sOuvU0FW+enJyMm+++SY5OTno9XqcnZ0JCgri1KlTVIQP4fUxhYQ7m73gbq3niIiO4LPPPqOoqIisrCzi4uJISkpiwoQJZGVlUV1djY+PD8OHD+/1948Q0fKxQQ6h9XLAntfCnvfx2bNnMRgMBAYGtns+MDCQ48ePA3DNNddQWVlJXV2dXfct3RbyZ8+e5aabbmLv3r2MGDGC6OhoNm/ezFVXXcXp06d55ZVXmDhxIp988gl+fn42GyIQCAS/NgICApg7dy5r167FZDIxd+5c/P39uzX3vffeY8iQISiVSrKysqw3rRkZGeh0ug6fw01NTeTl5QGQk5PTodDexIkT+fHHH7s8niWXv7Nw9SuuuKJdPndnhcquuuoqwsPDiYqKYvbs2cyePZsbbrgBNzc365iRI0e2mxMUFGTNI+vOeQGEh4f3uogHc9updevW8dBDD/HYY4+hUqm4//77CQwMtN74Xn311bz66qssXbqU2267DWdnZ5566in27NnT4eb4k08+ob6+noyMDB5++GFWrVrFI488Yt1u8dA1Njb2+rnYyxtvvMGBAwfYvHkz4eHh7N69m2XLlhEcHNzO49AdvL29u9xm6cduS5Vpi8dPysrUra2tNtv9S7Xh/J9S0NbWdllchyFDhhAXF8fRo0dRq9XtFh9MJhPV1dXEx8czZMgQ635SUlJ48sknqa6uRqPRWHuU5+XlcfbsWWqDg3nq1Cgei85lmJMWT1MDuXs2WYVLVVVVO5tiYmKsvxsMhl7P4y4rK6O2trZD7Zf+pKKigra2NgYOHCiZDdXV1Zw5c4YBAwZIZkN9fT3l5eW9UsjQXpqbmzl37pyk9XPa2tqora3tMhKmM/7973/j6+vLX/7yl163x9nZ2e77lm4L+bvvvhsnJydKSkoICgoCzKX4X3/9daKiotDpdNx5550sXbq0gydGIBAI+pvs57oOT1Je4Kk58lTXIuTCsXv/fEXPDLuAO+64g+XLlwN0WWSsMzIyMmhoaECpVFJWVmb9XNbpdAQFBXXq1b/QU2oLlgWG6urqDl847u7uDB48+KLzPT09SU1NZefOnfzvf//j6aef5tlnn+XQoUNWuy7sfX1+Pl93z8vWaue28H//93/83//9H+Xl5bi7u6NQKHjttdeIioqyjnnooYd48MEHKSsrw8fHh8LCQh577LF2Y8Bc7BAgNjYWg8HAkiVL+NOf/mT14FnSBfpiUcIempqaePzxx/niiy+YO9ccgTJy5EjS09NZtWoVM2fORKPR0NLSQk1NTbvXpLy8HI1G0+1jKRQKioqK2LJli8122jOntxE2CBvO5/Tp0xfdfuONN3LjjTdedMy2bdva/f3ggw9e8rgn2/SczfwnziqIvGI+iS7mz5aampp+vy6NjY2SvxZVVVWS22ApBisl+fn5/d4R5UKys7OtNX2kIjU11abxQ4YMIT4+3qY5/v7+qFSqDp1bbP1OvBjdFvLfffcdR44csd4sXoiHhwcvvPBCh1BJgUAgkAI3p+5nDvXV2O4we/ZsWlpaUCgU3c6NqqqqYtGiRTzxxBOUlZUxf/58UlNTcXV1JTExEa1Wi4ODQ5ch2cOGDSMlJYWFCxdan7MUI+uKQYMG4eXlRXZ2NkOGDOn2+Z2Pg4MDM2fOZObMmTzzzDOo1Wp27NjRrqp5V3TnvPoLS5jce++9h4uLC1dddVW77QqFwhoa//HHHxMaGkpiYmKX+7P0OD4/FPfYsWM4Ojr2SuXo3qC1tZXW1tYOkQXn5w2OHj0aR0dHtm/fbhUmJ06coLi4mIkTJ3bYZ1colUpCQ0O55ppruj2nrq6OlJSUDq9Ff3Lu3DmOHj3KFVf07mKfLVRUVHDixAmmTJkimQ1nzpyx+TXvbQoLCzl79qzdNT16g/z8fGve+aVISUnhnXfeITc31xoqP3ToUO666y7Gjx9vHZednc3dd9+Nt7d3h0VLk8lEamoqdXV13H///QwdOpTNJZFcd+01ODfr2b37MGfPnuWdd97p1/SLI0eO4OfnJ+nn9sGDBwkKCrIuoEpBcnIykZGRXeqo/mDXrl3ExsZKukC8Y8cOEhISJI0K+O6775g0aVKn6Sxd8dVXX9kcVeLk5MTo0aPZvn07119/PWD+vt++fbvVgdNTun1H6ufnx8mTJxk6dGiXYwoLC/H19e0VwwQCgeDXgEqlIicnx/p7d1i6dCmhoaE8+eST6PV6EhISWLFiBWvWrGHmzJlMnDiR66+/npUrVzJkyBBKS0v59ttvueGGGxgzZgx//OMfWbRoEWPGjGHSpEl89NFHZGVldfAan4+lQMvevXutX0i28M0335Cfn8/UqVPx8fFhy5YtGI3Gi36nnE93zqsnaLVatFqttQJ9ZmYmnp6ehIWFWb/X3nzzTZKSkvDw8OD777/n4Ycf5uWXX27nfX711VeZPXs2SqWSTZs28fLLL/Ppp59aX9uPPvoIR0dH4uLicHZ25vDhwzz22GPccsst7SIS9uzZw5QpU2wK/espOp3Oev4ABQUFpKen4+vrS1hYGNOmTePhhx/G1dWV8PBwdu3axfr163nttdcAc7j8nXfeyUMPPYSvry9eXl7cd999TJw40aYaOhaRcWGExsWwjLVlTm8jbBA2XGiDyWTqlg2TJ08mKSnpkvnqtbW11NXV4evr22nIfnBwMFdffTWRkZF8+umnmEwmjEon/v3vt1m8eDEDBgzAycmpX+sHmEwmnJycJH0twLyQLKUNJpNJchvA/L6U+jpIbQPY936wZwHsoYce4vbbb2fMmDGMGzeO1atX09DQcMnCxt2l20L+0Ucf5fe//z33338/c+fOZdCgQSgUCmprazl16hR79uzhiSee6NAuSCAQCAQXx8vLq9tj169fz5YtW0hLS8PBwQEHBwc+/PBDJk+ezLXXXsucOXPYsmULTzzxBIsXL6ayshKNRsPUqVOtnuRbbrmFvLw8HnnkEZqbm7nxxhu55557+O67rgsEAvzhD3/grrvuYuXKlTZ/oanVajZt2sSzzz5Lc3Mz0dHRfPzxx932OCsUikueV1esXbuWxYsXX7S4zdtvv90u981SwO3999+39oo/ePAgzzzzDDqdjpiYGP71r39x2223tdvP1q1b+etf/4peryc+Pp6vvvqKOXPmWLc7ODjwyiuvkJubi8lkIjw8nOXLl3cIld24cWO/f58ePny4nTf5oYceAuD2229n7dq1bNy4kccee4z58+dTVVVFeHg4f/3rX9vVW/j73/+OUqnkxhtvRK/XM2vWrEt2RLgQpVJpV56uHIo4SW2DaC9lRupe1WCuc2FLjQtLO7uLcanieFdddRWDBg1i69at1iKqACEhIYSFhdHY2EhOTg7Dhg3rNzHf0NBgUyvQvqC1tRUHh96NprMVORSilENrSDlgTzFMg8Fg17W75ZZbqKys5Omnn0ar1TJq1Ci2bdt2yfuW7qIw2fBpu2nTJl588UVSU1OtH9SWCzF69Ggef/xxuzw19lJXV4e3tze1tbU23QhfzhiNxj6vMCoQCASdYTKZGD9+PA8++CC///3vpTan2zzzzDPs2rXrkt0A5MLWrVv505/+xNGjR+26+bzcvxufeeYZSkpKrH12u0N9fT27du3i2muv7UPLLk5NTQ379+9vt3DT35w9e5a0tDRJUwy0Wi05OTmSphjI4To0NTXxv//9j7lz5/aaiDQajSxYsIC0tDSrQ83CuHHjCAsLIzk5mTVr1pCTk0NVVRU1NTXMnj0bZ2dn6uvr2bdvH2FhYf0i5ltbW9myZYv1+FKxbds2xo0bJ2nU8Pbt2xkxYkSvCTh7+O677xg7dqyk1+Hbb79lypQpkn43bd68mSuvvNKmmjq33XYbw4YN4/HHH+9Dy2zHJgX429/+lsOHD1NVVcWhQ4fYvXs3hw4d4ty5cxw8eNBmEf/WW28xcuRIvLy88PLyYuLEiWzdutWmffyaSE5OZsGCBSxcuJClS5eycOFCFixYQHJystSmCQSCXwEKhYJ33nlHck+XrWzdupWVK1dKbUa3aWho4P3335fcgyQVLi4u6PV6m+aoVCoMBoOknmA5eIHl4A13cnKy+fXrbSyV3KW8Fi4uLjg5OVFXV9dr+1QqlSxfvhwfHx/y8vLQ6XQYDAYSEhIICwvjk08+4fbbb8fBwcHaYs4yD8xFRydNmkRxcTE5OTl9fn1qa2txcXGRVMSbTCb0er3kUQEtLS2SXgeQvi2jyWSira1N0u82S1eU7qYyWmhubpb8PdQZdl1JtVrdreIdlyIkJISXX36Z6OhoTCYT69at47rrriMtLU02BX7kQnJyMitWrKCqqoqgoCBcXV1pamoiLS2NFStWsGrVKusHtkAgEPQVo0aNYtSoUVKbYRMHDx6U2gSbuOmmm6Q2QVI8PT2pr6+3aY7lxtBgMEh2k+jg4IDRaJQ0fFWlUkm+mGBZiJFSNDg7O1uLSDo5OUlig0KhQK1WU1NT06se0KSkJFatWmXtI5+YmMjgwYPZt28fTz755CXvBS1ift++fQB96pm/sIOFFFgWlaQU0QaDgZaWFsmFYFtbm80CtjexpExJKeQtn4+22lBfXy9py7yukHS5f968ee3+/utf/8pbb73FgQMHOhXyer2+3Spvb65yyhmj0cibb75JVVUVgwcPtn7genh4MGjQIPLy8lizZg0TJkwQYfYCgUAguKzx8PBAp9PZNMdyUyalt8dyg9zW1iaZeHRxcaG1tRWDwSDZDbtFMEnpBXV0dESlUtHc3CzJa2FJg6yrq6OxsZGIiIhevT9LSkpi/Pjx7Nmzh7q6OkJCQliwYEG3j9FfYr62tlZyId/c3Gx9P0iFHBYTLJ8LUi4m2Cui+8IGW98POp3Opir3/YVsVJ/BYGDjxo00NDR02bLkpZdewtvb2/qQso1Ef5KVlUVOTg5BQUEdPmgVCgUajYbs7GyysrIkslAgEAgEgt7BHo+8UqlEqVRK6o0+fzFBKs4X0VKhUqlwdHSkublZMhvg5/D6/ub8NMh3332XvLy8Xk+DNJlM5OTkoNfrmTFjBomJiTYvFPRHmL0cPPJyCIlubm7G2dlZ0rB2vV6PUqmUtFp8W1ub9bNaShscHBxsfi3k6pGXXMhnZmbi4eGBs7MzS5cu5YsvviA2NrbTsY899hi1tbXWR0lJST9bKw3V1dXo9fou2xC5urqi1+uprq7uZ8sEAoFAIOhdPD09bfbIg/Q56gqFQvLQdoVCgbOz869WRJ+PJQWxP7GkQaamploFrL+/PydPnmTFihW9IuZNJhNZWVmcOXPG5l7YF9KXYr6pqYmGhgbJhXxTU1O/tvHsDLksJri4uEi6mCB1fnxPbBAe+S4YOnQo6enppKSkcM8993D77beTnZ3d6VhnZ2drYTzL49fA+e1GOqOpqQlnZ2d8fHz62bJLYzQayczMZPfu3WRmZkreFkcgEAgE8sbDw8NmjzxIL+TlYoMcRLQ9BQt7Gy8vL2pqavrteBemQXp4eKDX69FqtcycOZPq6mrWrFnTo/ug3hTxFvpKzJeUlBAQECB5gTc5dO+Qi5CX+rWQOke/JzbI1SMveUlcJycnBg8eDJhb2B06dIh//OMf/Otf/5LYMvkwfPhwhg0b1mm7EZPJhFarJTExsU8LBNrT9i45OdlajEWv1+Ps7MywYcNYvny5KMwnEAgEgk6xJ7Qe5FHoTQh5+digVqspKCjot+N1lQZ58uRJRo4c2S4N8lL94jujL0S8hd7OmTeZTBQXFzNs2LDeMtFuampqiI6OltQGOVTNl8NiwuXska+vrxce+e5gNBolX8WVG121G9HpdOTl5eHj48OyZcv6LOfEnrZ3F4aXRUREoFarrVX2Rcs8gUAgEHSGpdidrZ5BBwcHa1VkqXBycqKlpUVSG+TgDZdDeL9araaurq7fIgG7SoMsKCjA3d2dyMhIu9Mg+1LEW+hNz/zZs2dpaWlBo9H0ooW2YzAYqKurkzy8Xw7ecDksJsihBZ/BYLC5TkBbWxvNzc2y9MhLKuQfe+wxdu/eTWFhIZmZmTz22GPs3LmT+fPnS2mWLLG0G0lISKCmpobCwkJqampITEzs09Zz9gjyzsLLVCqVtcp+b4SXCQQCgeCXiaenJ0aj0eb8ZuENFzacj0Xs2lNvwR66SoM0GAwcP36c4cOH25UG2R8i3kJviflTp04RGRkpeRh1XV0dDg4OuLm5SWqHHLzhclhMkIMN9oTWWz5D5OiRlzS+oaKigoULF1JWVoa3tzcjR47ku+++46qrrpLSLNmSlJTEhAkTbA5xtxd7297ZUmXfnvAygUAgEPxysXg9dDqdTTfgjo6OtLa29pVZ3UIu3nCpi9+6ubnR2NgoqQ0KhQJvb29qamr6JUf6YmmQx44d43e/+x3jxo2zKQ2yP0W8hZ6G2dfV1XH27FkSEhL6ysRuU1tbi7e3t6QF3gAaGxtlsZjg7+8vuQ1SL2i0trba7JG3CHl3d/e+MKlHSOqR/89//kNhYSF6vZ6Kigp++OEHIeIvgVKpJC4ujqlTpxIXF9enLRzsbXsnquwLBL8spk6dyoYNG6Q2gwkTJvD5559LbYagj3FycrJLjMohnFsONsjBG+7t7U19fb3kqQ5qtbrf7jUulgaZmZlJdnY2119/fbdFpRQi3oK9nnmLzWFhYZILNpBH+7vW1lZ0Oh3e3t6S2iEHES2H8H57rkNNTY01ulhuyC5HXiAf7BXkl3OVfYGgP1i0aBEKhYKlS5d22LZs2TIUCgWLFi3qf8M6YfPmzZSXl3PrrbdKbQpPPvkkjz76qEjL+YVjWSjWarU2zZODgJWLDVJHBbi6uuLo6Ehtba2kdgQEBFBRUdEnPdI742JpkDNmzEChUHD69OlL7kdKEW/BHjFfXFxMXV1dl22k+xOTyUR5eTkBAQGS2lFbW4uzs/NlKWB/qTbYGt5fVlZGUFBQH1nUM4SQF3SJvYLcEl6m1Wo7fPBbquzHxsb2aZV9gUDuhIaGsnHjxnb/X83NzWzYsIGwsDAJLWvP66+/zuLFi/s0+gfoVoGwOXPmUF9fz9atW/vUFoH0BAcHU1ZWZtMcOQhYOQl5KRe8LGHtUgt5f39/9Hq9XV0Q7CUpKYkPP/yQ9evX8/bbb7N+/Xo++OADJk+eTHx8PJmZmRd9j8hBxFuwRcw3NTVx7NgxRo0aZXPocl9QW1tLW1sbfn5+ktshdVRAW1sbbW1tl6WI7m3siQooLS0lODi4jyzqGULIC7rEXkEudZV9wa8ckwlaGvr/YaPHJzExkdDQUDZt2mR9btOmTYSFhXXILTQajbz00ktERkbi6upKfHw8//3vf63bDQYDd955p3X70KFD+cc//tFuH4sWLeL6669n1apVBAUF4efnx7Jlyy6aU1xZWcmOHTuYN29eu+eLi4u57rrr8PDwwMvLi9/97neUl5d3ONb5PPDAA0yfPt369/Tp01m+fDkPPPAA/v7+zJo1C5PJxLPPPktYWBjOzs4EBwdz//33W+eoVCquueYaNm7c2PWFFfwiCAoKorS01KY5Li4uNhfI623kIOQtN8pSL2qo1ep+7ePeGQ4ODgQEBNgc3dFTukqDDAoKIjAwkIyMjE5FsZxEvIXuiHmTyUR6ejrBwcEEBgZKYGVHtFotAwYMkDwcWg7h/Xq9HoVCgZOTk2Q2mEwm2XjkbbVBzh55yfvIC+SLRZCvWLGCvLw8NBoNrq6uNDU1odVqLyrILeFllj7y5eXlODs7k5iYyLJly0QfeUHf0doIL0qwcvp4KTjZVgjljjvu4P3337d26njvvfdYvHgxO3fubDfupZde4sMPP+Ttt98mOjqa3bt3s2DBAgICApg2bRpGo5GQkBA+++wz/Pz8SE5OZsmSJQQFBfG73/3Oup8ff/yRoKAgfvzxR06dOsUtt9zCqFGjuOuuuzq1b+/evbi5ubXrBWw0Gq0ifteuXcmzHX0AAPW2SURBVLS1tbFs2TJuueWWDnZfinXr1nHPPfdYiyp9/vnn/P3vf2fjxo0MHz4crVZLRkZGuznjxo3j5Zdftuk4gsuPoKCgy9Yjb/F+SdUvWalU4urqik6n6zI1rj9Qq9WcOHFCsuNb0Gg0FBUVMWTIEKlNASAuLo4dO3Zw+vRpQkNDrc/LUcRbuFQBPEtI/ZgxY6QysQNarZZBgwZJbQY1NTUMHDhQUhsshUOlLPrX1taG0WiUVMjbu5gghLzgsqUngry/q+wLBJcbCxYs4LHHHqOoqAiAffv2sXHjxnaCWK/X8+KLL/LDDz8wceJEAKKioti7dy//+te/mDZtGo6OjvzlL3+xzomMjGT//v18+umn7YS8j48Pb775JiqVipiYGObOncv27du7FPJFRUUEBga2+5/dvn07mZmZFBQUWG9C169fz/Dhwzl06BBjx47t9vlHR0ezcuVK69/ffvstGo2GmTNn4ujoSFhYGOPGjWs3Jzg4mJKSEoxGo/gs+QUTHBxMdna2TXOcnZ0lF9FOTk6oVCoaGxv7pVJ6V6jVamprayXND1ar1daCd1J6RS0ecL1eL3lYL5jfI/Hx8aSlpaFWq/H09JS1iLfQlZivq6vj2LFjjBkzRhYh9WAO86+rq5M8OkAuhe7kEBXQ0NCAo6OjZJ/NYH49jEajzZ8DpaWljB8/vo+s6hlCyAsuSU8EuSW8TCDoNxzdzN5xKY5rIwEBAcydO5e1a9diMpmYO3duh/Ywp06dorGxsUNHj5aWlnYh+GvWrOG9996juLiYpqYmWlpaGDVqVLs5w4cPb3dDHRQURGZmZpf2NTU1dVi5zsnJITQ0tJ0nKTY2FrVaTU5Ojk1CfvTo0e3+vvnmm1m9ejVRUVHMnj2ba665hnnz5rX74nd1dcVoNF60EKfg8icoKIjt27fbNMfJyQmFQkFzc7NkQkihUODh4UFDQ4OkQt7Sdk1KXF1dcXBwoK6uTtLiti4uLnh7e6PVagkPD5fMjvMJCgqipqaG5ORkJk+eTEFBgaxFvIULxXxoaCjJyckMHjxYctF8PlqtFl9fX0lDycHcis/Z2Vny76ra2lrJC0w3NDTg7u4uaVRAc3MzKpXK5gUn4ZEXXPYIQS64bFAobA5xl5I77riD5cuXA2YxfiGW/qXffvtth/A8y6ryxo0bWbFiBX/729+YOHEinp6evPrqq6SkpLQbf+GXl0KhuGhBLH9/f7taNymVyg55lJ3l4l/YkzU0NJQTJ07www8/8P3333Pvvffy6quvsmvXLqvtVVVVuLu7S35jJOhb7AmtVygU1hx1KcWQu7u79f9WKtRqNSUlJZLaoFAorHnyUouIgQMHUlJSIhshDxATE0Nrays7d+5EpVIxefJkWYt4CxYxv3fvXgoKCggPD5dN2oKFkpISQkJCpDZDFp5wix2RkZGS2qDT6SR/f9uboy+EvEAgEAg6Zfbs2bS0tKBQKJg1a1aH7bGxsTg7O1NcXMy0adM63ce+fftISkri3nvvtT6Xl5fXY9sSEhLQarXWSBwwh1OWlJRQUlJi9cpnZ2dTU1NjbTkUEBDAsWPH2u0rPT29W6vgrq6uzJs3j3nz5rFs2TJiYmLIzMwkMTERgGPHjnUoBij45WFPsTuQR568h4eHLIR8Q0MDra2tkoY7y6HgHZgXCXNycqivr8fT01Nqc6woFApMJhMKhUJST6WtWOw1Go2ys7uuro66urp2UWNSIQchr9fraWpqktwOOQh5eyrWm0wmWQt5kWAoEAgEEqJSqcjJySE7O7vTPFJPT09WrFjBgw8+yLp168jLyyM1NZU33niDdevWAeZc88OHD/Pdd9+Rm5vLU089xaFDh3psW0JCAv7+/tYwSoCZM2cSFxfH/PnzSU1N5eDBgyxcuJBp06ZZCx3NmDGDw4cPs379ek6ePMkzzzzTQdh3xtq1a/nPf/7DsWPHyM/P58MPP8TV1bWdF23Pnj1cffXVPT43gbwJDg6mtrbW5ir0rq6uNDY29pFV3cPd3Z2GhgZJbbCE88qh/Vt/9nHvCmdnZ4KCgqz1SKTGkhNfWlrKtGnTGDhwIHv27JH89eoONTU17N27l7CwMKZNm0ZJSUm3+8z3B0VFRQQHB0uer28ymaioqJBFH3t3d3fJr4cchHxjY6PN0XyW7yHRfk4gEAgEneLl5XXRfNrnn3+ep556ipdeeolhw4Yxe/Zsvv32W2uo3N13381vf/tbbrnlFsaPH8+5c+faeeftRaVSsXjxYj766CPrcwqFgq+++gofHx+mTp3KzJkziYqK4pNPPrGOmTVrFk899RSPPPIIY8eOpb6+noULF17yeGq1mnfffZdJkyYxcuRIfvjhB77++mtrH+AzZ86QnJzM4sWLe3xuAnnj5+eHo6MjZ86csWmeHLzhcrAB5JEn7+/vT1tbmywEakREBMXFxbS1tUlqx4WF7Tw9PRk+fDiRkZHs2bOHU6dOyUYUn4/RaCQ3N5e9e/cyaNAgYmNj8fLy6naf+f6gtbWV4uJiIiIiJLUDsKalSZ1WUlNTI3mxPZPJZM2RlxJ7FhNKS0txdXWVtObJxVCYpP6v6wF1dXV4e3tTW1sr2wssEAgElzNarZbhw4eTmpoqeX7pn//8Z6qrq3nnnXcktUPu/FK+G2NiYvjHP/7RacpJV5SUlFBYWMiUKVP60LKL09LSwtatW7nmmmsk9YKdOHGC+vp6yVuCHTp0CE9PT2JiYiS1w2QysXPnTiIjIyUTepeqTn/u3DnS0tJwcnIiISGhx2kAra2tbNmypcfvxbq6OtLS0mhrayMhIQFfX9922+vr69m3bx9hYWEdWtP1J/n5+ZSUlDB16lTJQ/6zs7NpamrqUNS1vzl48CA+Pj5ER0dLZoNer2fbtm3MnTtX0qr1u3btYvDgwTa1A9y8eTNPPvkkR48e7UPL7Ed45AUCgUDQJRqNhv/85z8UFxdLbQoDBgzg+eefl9oMQT8xZMgQcnNzbZpjqRgvJU5OTjg5OUnulZdLfrpGo0Gr1UptBgqFgqioKPLy8iTxHHenxZyfnx/Tp0/H19eXXbt2Se6dt3jhd+/ejb+/v9W2C7EUwJPSM28ymcjPzycqKkpyEQ/mRXA55FXLwSOv0+lwcXGRVMRbogJs9cjn5ubKrpjj+YhidwKBQCC4KNdff73UJgDwpz/9SWoTBP2IPULe3d0dvV4veZE3T09PyduueXt7y6LgXWBgIGlpaTQ1NUnebSIkJITjx49z5syZfq1qbkufeAcHB0aMGEFQUBBpaWmUlpYydOhQBgwY0G8C1WQyUV5ezokTJ2hrayMpKalTAX8+XfWZ7y9KSkowmUw2eVv7ioaGBnQ6neT58S0tLbIodFdXVyd5kcmWlhZaW1ttDu+Xu5AXHvnOMBqktkAgEAgEgl819gh54Q3/GRcXF1xcXCTPT3dycsLX11cWXnmVSkVMTAw5OTkXbb3Zm9gi4s/H4p23LIT8+OOPFBUV9WmOf2trK4WFhezYsYP09HSCgoK69MJ3hlSeeYPBwPHjx4mJiUGplF7aaLVa/P39JS8wV1NTg5ubG05OTpLbIfVigr1RAXIX8sIjfyHNdaA9Bs4e4O4Pzl7mntQyCNMRCAQCgeDXgj1CHn4uNielN1ytVvdKC8jesKO2thZ/f39J7bCE10vdyxrMrehOnTpFYWEhUVFRfXose0W8BQcHB4YOHcrgwYM5ffo0+fn5ZGZmEhwcTGhoKD4+Pj0OV25ra6OqqorTp09TWlqKh4cHgwcPJiQkpNNOKpdCCs98QUEBjo6OsugdD/IKq5daQIO58rvUYtjeqvlCyF9uGNugucb8qCkCBxdw8QaPAeafzl6gtP2DTSAQCAQCQfcZMmQIRUVFNDc329T7Vw558t7e3tTV1WE0GiX1EKrVamv1bCnRaDTk5ORIHuYPoFQqiY2NJSMjg7CwsD7L2+2piD8flUpFeHg4YWFh1NbWUlxczJEjR9Dr9Xh4eKBWq60Pb2/vLs+ptbWV2tpaamtrqampoaamxuqpDA4OZsqUKb2ST92fYr61tZWTJ0+SmJgoi9z4lpYWzp07R0JCgtSmyELIGwwG6urqJLfDnvz4+vp6ysrKhJC/LPEMBIUSWpuguRbqy0HlAE4e4BEIrmqzsHdwltpSgUAgEAh+cQQFBeHm5sapU6cYMWJEt+e5u7tTV1fXh5ZdGg8PD5RKJfX19ZIWmvL39yc/Px+TySSpyPHw8MDNzY3KykpZ9GPWaDScPHmSvLw8hg4d2uv7700Rfz4KhcIq2OPi4mhubqampoba2loqKys5efIker0elUqFSqWyLiJ9//33GI1GDAYDzs7O1n0MHDgQb2/vPqld0F9i/tSpU3h6ejJgwIBe37c9VFRU4OnpiZubm6R2GI1GKisrJa1WD+b8eAcHB8nrY+h0um6niFg4efIkPj4+1ha4ckQI+Uvh6Gp+ABhaoaUBzv4U6ufkDm5+5oeLl1nky2A1UCAQCASCyx2FQkF0dDS5ubk2CXkPDw+b+8/3NgqFwtrHXUohb7lxraqqkvxmNDg4mJKSElkIeYVCQWxsLCkpKYSFhfWqyOgrEX8hCoUCV1dXXF1d24VxNzc309raisFgQK/Xc+DAAcaNG4ezszOOjo42Rbf0lL4W842NjeTl5ZGUlCQLbzwgm/f4uXPnUKlUknvCLVEBUr8+Op2OsLAwm+ZYwuqltv1iSF8R4nJC5Wj2xHsPBK8gc4h93Rk4kwrFB+D0QaguhMYqUTBPIBAIBIIeYk+evLe3N/X19RgM0n4Py6HgnUKhIDAwUBaF5sLDwykvL6e5uVlqUwBztEJQUBDp6em9VpStv0T8xXBxccHT0xO1Wm1dyPH29sbT07NfRbyFviqAZzKZSE9PJyQkxGZPa1/R2NhIZWWlzYKxL9BqtWg0GslFaG1treTt79ra2uyKjpJ7fjwIIW8/CiU4e4KnBtQhZu98cx1oM6E4BYqSoTIXdBXQKo8vLYFAILCHqVOnsmHDhm6NVSgUfPnll70+9pfOhAkT+Pzzz6U2Q3YMGTKEEydO2DTHzc0NBwcHycPrLR55qZFLH3c3Nzf8/f0pLi6W2hQrI0aMoK6urldskoOIlyt9IeaLiorQ6XQMHz68FyzsHYqLiwkMDJQ8jNxkMlmFvNTIIU+/rq4OZ2dnmxeycnNzJU9NuBRCyPcWjq7mKvfeIeDuZy6adzYXTh+Cov1Qmg61Z0BfD/3UjkMgEMiTRYsWoVAoWLp0aYdty5YtQ6FQsGjRov43rBM2b95MeXk5t956q/W5iIgIFApFu4elWnBZWRlz5syRylybuP/++xk9ejTOzs6MGjWq0zGffvopo0aNws3NjfDwcF599dUOY9asWcOwYcNwdXVl6NChrF+/vt32TZs2MWbMGNRqNe7u7owaNYoPPvig3Zgnn3ySRx99tN9aYl0uxMXFkZGRYdMcS1i71G3X/Pz8qK2t7dN2Yd0hICCAxsZGyVvygfmzo6ioqN/akl0KJycn4uPjOXbsGE1NTXbvR4j4S9ObYr6xsZGsrCxGjRolefFECyaTiaKiIsLDw6U2hfr6evR6veR97C3FFaWOmLCkONkanZCens7IkSP7yKreQQj5vuD8EHxPDTg4QH0ZnDliDsEvSYGqAnMIvkHaL3iBQCANoaGhbNy4sd3NY3NzMxs2bJBFWJ6F119/ncWLF3eovP3cc89RVlZmfaSlpQFm75+zs3RFQFtaWmwaf8cdd3DLLbd0um3r1q3Mnz+fpUuXcuzYMf75z3/y97//nTfffNM65q233uKxxx7j2WefJSsri7/85S8sW7aMr7/+2jrG19eXJ554gv3793P06FEWL17M4sWL+e6776xj5syZQ319PVu3brXxjH/ZjB49mmPHjqHX622aJ4ewdjc3N1xcXKiqqpLUDkdHR/z9/WXhlddoNBgMBiorK6U2xYpGo+lRiL0Q8d2nN8S8yWQiLS2NgQMHyqbAHUB5eTmALGzSarUEBATY1T6wNzl37hzu7u6SRyjYExXQ0NBATk4Oo0eP7hujegkh5PsahdJcBM9TA+pQc3/6Fh2UHzOL+uJkqDhurorfav9qsEAguLxITEwkNDSUTZs2WZ/btGkTYWFhHdrWGI1GXnrpJSIjI3F1dSU+Pp7//ve/1u0Gg4E777zTun3o0KH84x//aLePRYsWcf3117Nq1SqCgoLw8/Nj2bJltLa2dmljZWUlO3bsYN68eR22eXp6otForA/Lyv/54fItLS0sX76coKAgXFxcCA8P56WXXmq3n7Nnz3LDDTfg5uZGdHQ0mzdvbrf92LFjzJkzBw8PDwIDA7nttts4e/asdfv06dNZvnw5DzzwAP7+/syaNavL87mQ119/nWXLlnXZS/qDDz7g+uuvZ+nSpURFRTF37lwee+wxXnnlFesN6AcffMDdd9/NLbfcQlRUFLfeeitLlizhlVdeaWfjDTfcwLBhwxg0aBB//OMfGTlyJHv37rWOUalUXHPNNWzcuLHb9v8aiIqKwt3dnczMTJvmyUHIgzkP+/z3q1TIJbxeqVQSHh5Ofn6+1Ka0Iy4ujrq6OoqKimyaJ0S87fRUzBcUFNDQ0CCrkHqA/Px8IiIiJG03aUEuYfXnzp3D399fajPsEvIZGRn4+/szcODAvjGql5D+3fZrw8HFXOXeOwQ8AsBkgKq8n0Pwz6RCTYk5316EWAoE9tPS0PXjwroVFx3bdOmxdnLHHXfw/vvvW/9+7733WLx4cYdxL730EuvXr+ftt98mKyuLBx98kAULFrBr1y7ALPRDQkL47LPPyM7O5umnn+bxxx/n00//n733jm/rPu/932dgEyBBUuIQKXGIGpRkSdSWZcnyTLOaVae52Wl7m1u7zajbNP01bdLc69y2SW+Spokzm1EnruOkTdw4y7ZsTWtvUSRFiqS4JwAS+4zfH1+AQ6JkgiIJSML79TovDuAADw8InPP5Ps/zeZ6Z9Dh79uyhubmZPXv28L3vfY/vfve7fPe7371ufPv378fpdLJy5coZ/X1f/vKX+fnPf84zzzxDQ0MDTz31FBUVFZPu85nPfIZHHnmEM2fO8PrXv553v/vdYxlMn8/Hfffdx/r16zl27Bi/+tWv6O3t5ZFHHpn0GN/73vewWq0cOHCAJ598ckaxTkU0Gr2mp87hcNDR0TF2wX+9+xw5cmTKRRLTNHnxxRdpaGhg586dk27bvHkz+/btm7X4bwckSaKuro7jx4+ntF9eXh6BQCDthneFhYUMDg6mNQYQQn5oaCjlipW5oLKykv7+/owo9U9isVhYv349586dY3h4eFr7ZEX8zJmpmB8cHOTChQvU1dVlTEk9iB7swcHBa85v6SA5krCoqCjdoTAwMJB2IZ80uktVyB8/fpwNGzak3SzwtciOn0snsgr2PLGZhhAMwX7wdwjBb3OLmfX2XDHeTsmcD60sWTKeJ24w/qXmIXj3j8d//qelEA9Nfd8lO+CDvxj/+YtrIHTVhfmnZ9aL+573vIdPfvKTY6LwwIEDPP3007z88stj94lGozzxxBO88MILbNu2DRBZyv379/P1r3+dXbt2YbFY+MxnPjO2T2VlJYcOHeKZZ56ZJHq9Xi9f+cpXUBSFFStW8IY3vIEXX3yRP/qjP5oyvra2NoqKiqbMMHziE5/gb/7mb8Z+fuKJJ/izP/uzSfdpb2+npqaGHTt2IEnSlL2DH/jAB3jXu9419hhf/vKXOXLkCK973ev4yle+wvr163niiSfG7v+d73yH8vLySW6yNTU1/OM//uPUB/kmePjhh/nYxz7GBz7wAXbv3s2lS5f4whe+AAgvgIqKCh5++GG+9a1v8Za3vGVMcH7rW98iHo8zMDAwNhbK7/ezaNGisRnPX/3qV3nwwQcnPV9yPJdhGBmR1ckUNmzYkLKQTxrezeQCbjYpLCzk1KlTaJqGqqbvksvhcODxeOjt7aW8vDxtcYBwVS8tLaWlpSWj+k8XLlzIypUrOXz4MLt27bphOXBWxN88qY6mC4VCHD16lFWrVqVdHF5NS0sLZWVlaW0rS9Lb20teXl5aJhRMJB6P4/P50j72MhAIYLVaUz4eSSGf6WSFfKYgycL53uoSP2tRUYLfd0HMprfmgLNQGOnZPGB1pjfeLFmy3DQLFizgDW94A9/97ncxTZM3vOEN11ygXLp0iVAodI3oi8Vik0rw//Vf/5XvfOc7tLe3Ew6HicVi1xi4rVq1alLPXElJyQ1LlsPh8HVPfn/xF38xyZBvqgurD3zgAzz44IMsX76c173udbzxjW/koYcemnSfiRfyLpcLj8dDX18fIErb9uzZM+VFcnNz85iQn6uT7R/90R/R3NzMG9/4RuLxOB6Ph4985CN8+tOfHhPan/rUp+jp6WHr1q2YpklRURHvf//7+cd//MdJYtztdnPq1ClGR0d58cUX+fjHP05VVRX33nvv2H0cDgeGYRCNRtPeU5hJbNiwIeWFmolz3NMp5Cf2yae7dzZZXp9uIQ9iMfLAgQOsXLkyozKrVVVV+P1+jhw5wo4dO6bsMc6K+NljumJe0zSOHDlCSUlJRmS9JxKLxejo6OCee+5JdyhAZpXVZ1J/fKqZ9ePHj/OWt7xlboKaRbJCfiJaDH78AfAsgmUPQd4SIaLTgWoTGwgH/FgIfK0wfFk45NvzRGm+zSO2bPYmS5bJ/HXX9W+Trro4+4tLN7jvVe+tj6bWq/tafOhDH+Kxxx4DhBi/mmT56S9+8YtrerWSq/9PP/00jz/+OF/4whfYtm0bbrebf/qnf+Lw4cOT7n/1BbMkSTd0SS8sLLxumWlhYSFLly694d9WV1fH5cuX+eUvf8kLL7zAI488wgMPPDCpv/9GMY2OjvKmN71pUr95kmSmG8QCwFwgSRL/8A//wBNPPDFmHvTiiy8CjPXVOxwOvvOd7/D1r3+d3t5eSkpK+MY3voHb7Z7kGCzL8tjxWrduHfX19Xzuc5+bJOSHhoYy4sIn09iwYQNnz54lFothtVqnvV9eXl7anethvE8+E4R8c3NzRlR8eL1evF4vly5dmnHrzlwgSRJr167lwIEDnDp1irq6ukkCICviZ5/XEvNJcztVVVmzZk3GlTo3NTWRn5+f9lnpwJiRZCa8p27l/vhQKMSFCxeyGflbjvaDcFn0nHL6h+AphcXbYck2KL4rfaXtsipK6+0eMbouHobQAIx0gWwRBnquIuGUb/eMLwBkyXInY01B3M3VfafB6173OmKxGJIkTWnUVltbi81mo729nV27dk35GAcOHGD79u38yZ/8ydjvmpubbzq29evX09PTw/DwMF6vd0aP4fF4eOc738k73/lO3vGOd/C6172OoaGhaY2jqaur4yc/+QkVFRVpLUtWFGVsEeVHP/oR27Ztu2asj8ViGRvB9/TTT/PGN77xhmIpmXmfyLlz564xOswC1dXVOJ1Ozp07R11d3bT383q9Kc+gnwsKCwtpbW1Ndxjk5uaiqmpGLCqAEGwHDx6ksrIy7WXAE1EUhc2bN/PKK6/Q1NQ0VvmTFfFzx43EfGNjI8PDw+zatSvtC1BXEw6HuXz5Mjt27Eh3KIAwqLXZbLjd7nSHQn9//2su9s8HQ0NDrF69OqV9zpw5Q0FBwdg5PZPJCvmJLKyFBz4N534KffUQ6IJzz4rN4oLyzbB4GyzeIvrW04EkibL6ZGm9HhNmW4MNYCJEhrNAbHaPKMnPsNXLLFmyjKMoCvX19WPfX43b7ebxxx/nYx/7GIZhsGPHDvx+PwcOHMDj8fD+97+fmpoavv/97/PrX/+ayspKfvCDH3D06FEqKytvKrb169dTWFjIgQMHeOMb35jy/v/8z/9MSUkJ69evR5ZlfvzjH1NcXDzt1fFHH32Ub37zm7zrXe/iL//yL8nPz+fSpUs8/fTTfOtb37rp0TqXLl1idHSUnp4ewuEwp06dAsTiidVqZWBggGeffZZ7772XSCTCv/3bv/HjH/94zGQQxEXmkSNH2LJlC8PDw/zzP/8z586d43vf+97YfT73uc+xceNGqquriUajPP/88/zgBz/ga1/72qR49u3bd03rQZbJhnepCPmCggICgQDRaDStvasLFy7k1KlTaY9DkiRKSkro6OjICCGfn5/PggULaGhoYO3atekOZxJ2u50tW7Zw4MABLBYLFRUVWRE/x0wl5ltaWmhubmbHjh0Z0X9+NQ0NDSmd0+aajo4OSkpK0l61EA6HCQQCaZ9jHw6HCQaDKffp3ypGd5AV8pPJWQh174fC5RiWHHpOPo+t+zi5gXrU+Ai07BGbJAvRv2S72NJZgq9YwWEFhxcMXRh2BTphuA0sdiHmXQvFwoPNA0r2Jc+SJdPweDw3vP2zn/0sCxYs4HOf+xwtLS3k5eVRV1fHX//1XwPwx3/8x5w8eZJ3vvOdSJLEu971Lv7kT/7kpmeSK4rCBz/4QZ566qkZCXm3280//uM/0tTUhKIobNq0ieeff37aWZXS0lIOHDjAJz7xCR566CGi0ShLlizhda973Ws+xgc+8AFaW1snGQdezR/+4R9OEuXJbPjly5fH+jC/973v8fjjj2OaJtu2bePll19m8+bNY/vous4XvvAFGhoasFgs7N69m4MHD07q4wwGg/zJn/wJHR0dOBwOVqxYwb//+79Pml/f2dnJwYMH+fd///dpHZs7jQ0bNnDs2LHrGjNOhc1mw+PxMDg4SGnpDcwv5xi73U5ubi49PT1TGj7OJ0uWLGHfvn2sWbMmI3rTa2trefnll6murs44cZyXl8e2bds4dOgQ3d3djIyMZEX8HDNRzPv9foaGhti+fftrniPTwcjICFeuXGH37t3pDgUQvfrd3d2T2rXSRW9vL/n5+WlffBkcHCQ3Nzflz7pbxegOQDJTHeCYQQQCAXJzc/H7/bP3Jg8NUf+b7/LUz16g5XIrsXgMm8XCjuULeNvGIorCzWJc3ETcpaL8fvE2KFmbOe7y8bDI1msRkFSwucC1QIh+e67otc+SJUuWG9DT08OqVas4ceJE2kVIKuzatYvdu3fz6U9/Ot2hTItPfOITDA8P841vfOOmH2tOzo1p5qc//Sl/93d/l/I8+TNnzgCk3R29oaEBv98/aREoXbzyyissXrz4pit2ZouTJ0+i6zobN25MdyjXYJomx44do6urixUrVrB8+fJ0h5QS8Xic559/nte//vUZsXAzXerr62lsbKSsrOwan4JM4ciRI9hstoypJmlubqarqysjTPdeffVVCgoKqKmpSWscp06dQlXVlEvrly9fzhe+8IUZJTDmm8xqNskAjhw9ynf+7TtcvHgRt9tNaUkpOW4PL5zt5K+evcTpZR+B//EfcPdHRam9bBG96ud+As8/Dt//Xfjt30LjryDsS+8fY3GAqzAxs74wMbO+JTGz/mBiZn27iDM7sz5LlixTUFxczLe//W3a29vTHcq08fv9NDc38/jjj6c7lGmzcOFCPvvZz6Y7jIxl586dnD9/nv7+/pT2SxrNpZvi4mL6+vrSPtceRFa+ra1t2rO755oVK1bQ09ODz+dLdyiTSPbEDw0NUVdXx6VLl2hpaUl3WLc9zc3NtLS0sGHDBvr7+1OaMz9fDA0N0dfXlzELO6Zp0tbWlhGL7Zqm0d/fnxHO+TOZY9/V1cWlS5cyYkFkOmTrrCdgGAbf/OY3UUZGKCtfMuZW7XA6KHOU0dHRwTPPPMOav/8s8qq3wKq3iFL2juPQfkhs4WG4vFdsSFBUKzL1S7aDtzJ9JfiTZtabIu7kzHrFmjXMy5Ily3W5FUawTCQ3N5eOjo50h5ESf/7nf57uEDKawsJCVq9ezd69e3n7298+7f0KCgoYGRlJe3+6x+MZ810oKipKWxwAixYt4ty5c/h8vhmbWM4mDoeDyspK6uvr2bZtW7rDAaY2tnO5XBw6dIhoNMqKFSsyMkt8K2OaJvX19bS2trJ9+3a8Xi+5ubnTnjM/XyTjrK6uzhiTxuHhYSKRyDWTbdJBf38/Docj7YZ7M+2Pf/nll6mrq8uIKQTTIZuRn8D58+dpbGwk35t/zYeFJEkUFhRyueUyzS0TSustTqi8B3b9JbznJ/CWJ6HufVBQA5jQex6Ofgue/RD86Pdh/xfhymExJz5dSJIwxctZCHnl4PQK07zBBhFb20HoPgP+ToiOCOGfJUuWLFmypJF77733hp4HUzGxTz6dSJI0Nsc93SQnLLS1taU7lDFqamoYGhpKueJiLrieO31+fj733HMPHR0dHD16FE3T0hzp7UM8Hufw4cNjpeHJBaZkz3x7e3vGZOb7+/sJBAIZ4ciepLW1lbKysps2gJ0NMmmO/Uz6419++eWM8BmYLlkhP4Hh4eEbzqm12WzE4jFGAiNTP4Akw8IVsPFD8PZvwv94BnZ8HBZvFVnv0V648F/wy0+IEvxf/39w8RcQSu8FhjDM84JnEbiLQVaEYV7nCWh/VYj7wRYIDoIeT2+sWbJkyZLljuTee+9lz549Ke9XUFCQMeX1PT09GSFGKioq6OjoIB7PjHO61WqlpqaG8+fPY6Sx1e+1Rsx5PB527dpFPB5n3759hEKhNEV6+xAMBtm3bx+GYbBz585rMrmZJOYNw+DcuXPU1NRkjOdALBajq6trksFqujBNM2OE/EzK6uHWE/LZ0voJeL1erFYrsVgM1GvLZaLRKFaLFbdnmuUiOQuh9s1i0yJCGLclSvBDA9B2QGwAC5aPz6wvqEljCb4CNrfYQMQdG4XgQCKTnwPOQnDmixJ8izM73i5LlixZssw5O3fu5MKFC/T19aU0Pq2wsJCLFy/OYWTTj0PTNIaHh8nPz09rLHl5eeTm5tLW1pYxmcXq6mo6OjpoampKS+/xdOfEW61Wtm3bxrlz53jllVfYtGnTjARDFpHdPnr0KIsXL6a2tva600huNGd+PmloaECWZaqqqub9ua9Ha2srXq83I4xNk5VP6f58AyHkUzW56+zsHBt3eKuQFfITWLVqFcuWLWO4+xi2AvckgWqaJgODA6xYsYLqqurUH1y1j4+rM00YbBoX9f0Xob9BbMf/TQjlxVvFfRfVTbmoMG+o9vHnNzSIhcDXBsOXRR+9PVcsWNg82fF2WbJkyZJlzpjYJ/+Od7wjpf1GRkaIRCJp7WmVZZnS0lI6Ojoy4kK3qqqKCxcuUF1dnRG9x4qisH79eg4cOEBxcfG89qhOV8QnkWWZu+66C4/Hw6uvvsqyZctYunTptEdr3ukYhkFTUxNNTU2sWbNmWiZt6RbzPp+P5uZm7rnnnox5nQ3D4PLly2mfypGko6OD0tLStB+fUChEKBRKuT/+lVdeuaX64yFbWj8JWZb5oz/6I3Jycujo6CAcCmPoBuFQmI6ODjxuD4888giyfJMfHJIEhctgw/vhrU+K3vqdfwkV9wjRHBqAi/8Nv/5r+N6b4Zd/BRd+Jkrz04msiiy8pwQ8paLPPuKHnrPQflhUF/TVw0iPEPxZsmTJkiXLLDKTPnmr1Up+fj69vWk+hwJlZWV0dnamtXw8SUlJCYZhZETffhKv10tVVRUnT56ct2OUqoifSEVFBXfffTdXrlxh3759BAKBOYz09iAQCLB37146OzvZsWNHSk7r6Sqz13WdEydOUFNTk1Eir7u7G1mWM6KUXdd1urq6KC8vT3co9PT0UFBQcNv3x0M2I38Nmzdtwv3BD43NkR8cGsRqsbJixQoeeeQR1s7FqpezAFa8XmxaFLpPid709kNCFF95VWwA+dXCBX/xVli4UpTCpwNJEuPtkrPoDU3MrB+6DGYzWOxgS2Tr7YlsfbpizZIlS5YstwX33nsvf/u3f5vyfkVFRfT09KR9PFNhYSGyLNPf359293pZlqmsrKSlpYWSkpK0xjKR5cuX09PTMy8l9jcj4pN4vV7uvfdeLl68yN69e7PZ+eswMQtfVVXF8uXLZ2TOlo7MfGNjI7Isp30u+tU0NzdTVVWVERU1fX19WCyWjJiE0dvbO6PP1z179vDFL35x9gOaQ7JCfgpWrljB32/YSfPly4wERnB73FRXVd98Jn46qDYo3yK27X8Gw61C0LcdhL4LMNQstlP/Lsray7cIYV+2cbyvPR3IqojHnpsYbxeGyLBYiJBVsLnAtVCMt7N5wOpMX6w3wDAMzp8/z/DwMF6vl1WrVmVPxlmyZMmSIezatWtGffLFxcU0NjaiaRqqmr5LH0mSKCsT42zTLeRBZJQbGxvx+/0Zk2lUFIW6ujr2798/pyX2syHikyiKwqpVqygpKeHkyZN0d3ezfv36jOhbzgT8fv9YlcXdd99902JvPsX88PBwxpXUg4grEAhkzMjGjo4OysrK0r6oEI/HGRgYYM2aNSnt19nZSUtLyy0zPz5JVshfB1kyqUm3AYwkQX6l2Nb9D1HGfuWIEPZXjoifm34jNkmB4jWJ3vptkLs4fSZ0kiSEelKs63GIB8UChGkIgzx7HrgKMypbf/DgQb7yla9QX18/NnN45cqVPPbYY2zfvj3d4WXJkiXLHU9BQQHr16/n17/+Ne9973unvZ/b7cZmszEwMJD2MtSysjL27duX9kUFEG0HixcvpqGhgc2bN6c1lonk5eVRXV3NyZMn2blz56wLqNkU8RPJz88fy86/8sorlJWVsWLFChwOx6w8/q1GKBTi4sWLdHZ2Ul1dPeMs/FTMh5jXdZ2TJ09mXEk9COO9ioqKjHDPj8fj9PT0ZERZen9/P06nM+X39C9/+Uu2bNlyyy2+Zc7SUqagWIS4HO0Tc9RDQ+md+T4Rey7UPAj3/y2877/gTV+Cu34f8paAqYuS/MNPwjPvh6ffDQf/BTqOihnx6USxCOHuKRUj7pI+AN1nRAtB20Hou5jW3vqDBw/y+OOPc+LECfLy8qioqCAvL4+TJ0/y+OOPc/DgwbTElSVLlixZJvPmN7+Z5557LqV9MmmOe25uLk6nk+7u7nSHAsCyZcvo6+tjaGgo3aFMYtmyZRiGQWNj46w+7lyJ+CTJ7Pzu3bvRdZ0XX3yR8+fPi4lIdwjRaJRz587x0ksvYZom9913H7W1tbM+53yue+aTLvWZVlI/ODjI4OBgxsTV1dWF2+2+ZnRgOpjp+LvnnnuON7/5zXMQ0dwimZkw0HSGBAIBcnNz8fv9s7uCoschEoCID0Z6ITYixLxqE+PXLI7MG7kW6Brvq+86BcaE2bCqXZTeJ3vrnam5OM4pyWx9LCRK8i0OsWDhWpAYgzf3TviGYfCe97yHEydOsHTp0kkruqZp0tzcTF1dHT/4wQ8yqqwqS5YsWaZizs6NGcLJkyfZtWsX/f392Gy2ae/X39/P8ePHefjhh9Ne/tnU1MTAwEDGlMXW19czNDTE9u3b035sJuLz+di/fz/bt2+fFaf/uRbxU+Hz+bhw4QLDw8PU1NRQVVU1b5UY8Xic559/nte//vXzkrmNx+O0tLRw6dIlCgoKWLly5bxkskdGRjhw4ACLFy+etcz84OAghw4dYufOnRn1OWqaJvv27aOoqCgtYxqnIjlporp6BlO9ZhHTNPnVr37F5s2bU3KsD4VCFBYWcuzYMWpra+cwwtknW1o/FYoFXAVi81YKIR/xw2i/EPfh4fGZ6lan6AFPN55SWP02scVD0Hk8IexfhdAgtO4XGwjH/MVbxbZgBUhpFKeKBZQ8kbFP9taHhyDQLY6r1SlEvcM7Z3Prz58/T319PSUlJdd8+CezOBcuXOD8+fMp99xkyZIlS5bZZd26deTm5vLKK6/w0EMPTXu/goICdF3H5/Ol3ZCprKyM+vp6QqEQTmf6PWOWLl3KCy+8QF9fX0b07ifJy8ujtraWI0eOsGvXrpsqUU+HiAfxN2zfvp3+/n7q6+tpampiyZIlVFZW4nK55iWGuSYYDNLS0kJ7ezsej4ctW7ZQWFg4b88/22X2oVCII0eOsHr16owS8SAyzqFQKO2iOUkwGGRoaIgNGzakO5SxqqJUF/1efPFFSkpKWLly5VyENadkgALNcGR53MQtb7HIHEcDEBwU5eGjfYlMsl0Ie3X62YE5w+IUo+wq7hE96YOXEjPrXxUz6wcaxXbi+0JAl28Roj7dhnlX99YbGsRGxcz6wWawOkSG3rVAvB42t1gIuEmGh4eJRqPXvUBwOBz09vYyPDx808+VJUuWLFluDkmSeNOb3sRzzz2XkpCXZXnMvT7dQt7hcFBUVERbW1tGXDxaLBZqamq4cOECCxcuzKisfGVlJYFAgMOHD7Njx44ZZbPTJeInsmDBAgoLCxkaGqKlpYWXXnqJBQsWsGTJEoqKim65ir/k6MK2tjYGBgYoKSlh27Zts1I5MRNmS8xrmsbhw4dZtGgRFRUVsxzlzWGaJvX19Sxbtizt/hpJWltbKS4uxm63pzsUenp6KCoqSvl1T5bVZ9Ln3nTJjP+CDCIc07k8MIpNVXBYFewWBZsqY7coKPIEoekunlyCP9onsvZaDFSrmLE+B9njlJFkkYFPzq0PD8OVw0LYdxwTsTf9WmySnDDM2ybEvbcivfHLqlhoSGbrtXCiMqJXmPtZXaJNwJkvRL01Z0bxer1ebDYb4XB4ypN7OBzGZrOl/cIvS5YsWbII3vSmN/HhD3+YL3/5yyldfBUXF9PU1JQR4rmiooKTJ0+yfPnyjBBxyVF0nZ2dlJWVpTucMSRJ4q677uLAgQOcOnWKDRs2pPSaZ4KITyJJEgUFBRQUFBAOh2lvb+fs2bOcPn2aRYsWUVxcTEFBQUb8P0yFYRgMDAzQ09NDV1cXsiyzZMkS1q1blxGGfjcr5k3T5MSJE1itVlavXj1XYc6YK1euoOt6xiww6LpOe3s7GzduTHcomKZJd3d3yqXxhmHw3HPP8dRTT81RZHNLVshfRVTT6fJFMEwT00wkiRUZqyrjtKrk2BWcVnVM3NvsXtRJJfgBCPZD2Cc2SU6If1dmlOA7vLDsdWIzNOg5K/rq218FXzt0nxbb4SfFYkV5ogS/dJ3otU8XkiQWRiwTs/Uh8LeL2fXJioichePZ+mlWR6xatYqVK1dy8uRJqqurr+mR7+npoa6ujlWrVs3FX5YlS5YsWVJk9+7dDA4OcubMGdauXTvt/YqKijh16hSBQCDtJbMLFy5EURR6enooLS1NaywgTNqWL19OfX09paWlGSUmZVlm8+bNvPLKKzQ1NbFs2bJp7ZdJIv5qHA4Hy5cvZ9myZfT399PV1cXx48fRdZ2ioiKKi4tZuHAhVqs1rXHGYjF6e3vp6emhr68PVVUpLi6mrq6OBQsWZFwW82bEfENDA36/n127dmXU/z8I0Xzx4kVqa2szJrbu7m4sFsu8tlFcD7/fTyQSSWksKcCxY8cIh8O33Ni5JBmgLDOTIo8dWZIwTJO4bhDTDHyhGH0jBiYgIQS+RZVxjQl8KzZ1IfbCEmxGBFUbFa73wX7RX28amVWCL6tQul5sW/9k3DDvyqvQdVK4yF/4L7EpViitg8VbhLj3lKQ/drtHbABaBGJB6KsXP1tdYtHCWZAwzXNfd8SdLMs89thjPP744zQ3N1NcXIzD4SAcDo+VYD766KMZ88GZJUuWLHc6drudhx9+mOeeey4lIW+xWCguLqajoyPtpkaSJFFRUcHly5czQsgDLF68mObmZlpbW6mqqkp3OJOw2Wxs2bKFffv24Xa7KSm58XVIJov4iUiSxMKFC1m4cCGmaeLz+ejp6eHSpUucOHGC3Nxc8vLyxja32z1n1yOGYRAIBPD5fPj9/rGvHo+H4uLisTFsmSber2YmYr6rq2tsXny6F0+m4vLly1gsFhYtWpTuUMa4fPkylZWVGfH/0NHRQWlpacotB88999y8mUHOBVkh/xrIkoRNVbCpk0WgaZrEdIO4ZuILxegfMTEwJwl8h9WKx16OI7cMux7Cpo9gj/SjRgKgR0V/95gLfgaIxEmGeWEh5pOGecE+IfCvvAp8SfgFJLP1xWtmpVf9plDt4xUDhi4M/0Z7wHclcZxdCdO8PNFnb51sLrR9+3Y+//nPj82R7+3txWazUVdXx6OPPpqdI58lS5YsGcab3vQmvvrVr/I3f/M3Ke1XVlbGmTNn5mTudKosXryYixcvZkSFAAhRuXLlSk6fPs3ixYszpg83SW5uLuvXr+fEiRPcc8891z1mt4qIvxpJkvB6vXi9XlauXEkoFGJoaAifz8eVK1c4d+4chmHg8XjweDw4HA5sNht2u31ss9ls1xX6hmEQjUaJRCLXbH6/n5GREWRZJi8vj9zcXKqrqykoKMiIsvlUSUXM+/1+Tpw4wYYNGzLifXg18XicxsbGlNtK5pLkIs/WrVvTHQqmadLR0UFdXV3K+/785z/nr/7qr+YgqvkhO37uKoaDUf7rVBerS3OxW1KfdzlR4Ec1nbhuomMgI2FRJKyKjIMobsI4DR+2WAC7GcamSljsTiHsM6EEfyKmKQzn2l8V/fU9Z0V1QRKLAxZtEMK+fLMob88k9Jgow4+Hxo0JbbmQs0CI+gmmeYZhcP78eYaHh/F6vaxatSqbic+SJcstxe0+fi5Jf38/JSUltLe3p5TRNgyDX//612zatCkjSkJPnjyJLMspVRbMJZk43upqLl68yJUrV9i5c+c1IwhvVRE/HUzTJBgM4vP5GBkZmSTEo9Eo0WgUEJWGkiQhSRKapqEoCqZpYhji2i0p/icuAng8HnJzc3G5XBkjFmeD1xpNF4lE2Lt3LxUVFdNu2Zhv6uvrGRwc5O67786Y1yaTPrf6+vo4ceJEyqNF29raWLp0KX19fbesD1ZaFePnPvc5fvrTn3Lx4kUcDgfbt2/nH/7hH9J64ugbifKZ5y4gS1CS66A838HifBflXgdLCpwsynNiVa8v7KSxDD7kTDi8pmkS101imsGIbmNQs2CQA2Ycqx7GEgvi9Ptw04dTNbDZ7dgcLuw2OxYl3YZ5EuRXiW3d/4DoSGK83SG4ckQY6E0cb5dfnSjB3wJFq9K/MKFYwWEV2fgx0zxfwjRPAsu4aZ5sc7Nm1SoxrSBLlixZsmQsCxYs4J577uGZZ57hox/96LT3k2WZRYsW0dHRkRFCvrKykv3797Ny5cqMKOmVJIna2loOHz5MRUXFNUI5E1i+fDkjIyMcOnSIu+++e6ws9nYW8SBem5ycnOv+XcmMu67rIrEUi7F///6xY6Qoyg0z9rcjN8rMx2IxDh06REFBATU1NekM87pEIhGam5vZvn17xoj4aDRKZ2cnO3fuTHcogCirLysrS/n4PP3009x///23rIiHNAv5V155hUcffZRNmzahaRp//dd/zUMPPcSFCxfSNluzLxDFYVEIx3U6fWE6fWFebRkau/1t6xfxwbsrAQhGNY60DrE438miPMcNM/iSJGFVpWsWAYTAdxPTDUZiJQxGgujRINKgD4s+gtUcxG6VyXU5cThd2CwydkXCpkpY0yXwbW6ouldspiFG2V05IoR930UYahbbqR+KkvZFG0UJfvlmIZjTyVSmefEwBDrA1ypEv9UFrgmmeVeV4WfJkiVLlszgPe95D08++WRKQh5Eef2hQ4dYs2YNipJ69d1skpeXh9frpaWlhRUrVqQ1liSFhYUUFBRQX1/PunXr0h3ONUiSxIYNGzh69CiHDh1i27ZtqKp6W4v46SDL8qQy+Hg8DkBOTs4t2wM8G0wl5jVN4+DBg7hcLtavX58xIvlqkiMh0zXWbyqam5spLCzMiIovTdPo6upix44dKe/71FNP8Zd/+ZdzENX8kVGl9f39/SxcuJBXXnllylWeiWVDIMoHy8vLZ7V80BeKcah5AJtFoXM4QvtQkPahMFeGQrQPhfjDHZXcv7IIgLMdPv76v84BwvyuONdOuddJeb6TxfkOVpfmstAzM6d30zTQokGiwVHiIT/RUAAjLv52i82G1ebAblVx22RcFiHsbYqEPZ0CH0Sm+8pRUYJ/5QhEA5NvL6hJzK3fDAtr05+tvxotKkrwYyHxsyUxuz5nAVgTpnlq+jMmWbJkyXI97pTSehB9msXFxZw6dSolEWyaJi+88AKrVq3KCKO5/v5+jh49ykMPPZQxfenBYJA9e/awefPmlJ2g5wtd1zly5AiappGbm0t3d/cdK+KnIh6P8/zzz9/SZl6zSbLMvqysjKGhIaxWK5s3b87YCoXe3l6OHTvGfffdlzE+BfF4nN/85jds3bqVgoI0J+cQ2fiGhgbuu+++lBZjzpw5w7Zt2+jt7b2lPy8y42yRwO/3A1x31elzn/scn/nMZ+Y0htGIRstAkFyHBZdNZcMSL1urC7DIMqosocgSummiSBJIEqtKPbQPhRiJaHT7I3T7IxxpFRn8R+9dyutWFwNwZSjEC/W9CZHvpNzrxGG9UQZfxmJ3Y7G7oaAk0ecdxIz40UaHiEX9hIIGPtmCJtuQFCuqIsS8TZXw2GSclnFxn/z9nGPPg5oHxWbo0H9RCPorr0J/Aww2ie3Uvws/gLKNQthnQrYexDQB1SYc701TZOuvKcPPF5s154Zu+FmyZMmSZW7Jy8vjjW98I0899RSf/exnp72fJEmUlZWNOR2nm8LCQlwuF62trSxdujTd4QDgcrlYtWoVp06dYvfu3RkpBBVFYePGjbz00kv4fD7uueeeW/qiPMvc4na7xyYfJFt6M1XEx+NxTp06xerVqzNGxINwqvd4PBkh4mHmZfVPPfUUb3nLW275z4uMycgbhsGb3/xmfD4f+/fvn/I+85GRbxsM8uOjHRS4rWCCZohxc5ggKxKqLGGRZayqhMOiYLeoKDKE4wa9gTDd/ggdwxGuDIX4wPYKlhW5AfjNhR7+5aVLk55rodtGeULUP1hbxOL8aZZwm7oYtRYLivF28VHQYsQNiZhsF5shoZtgAhYZrAlBn2ORyLHKIoOvStgVCavC/JQUhYcTov4IdBydIlu/dFzUZ0Jv/dUky/BjQdC1yW74Y2X4LiH4s2TJkiVN3EkZeYD//M//5M///M9pbm5O6Vw2MjLCyy+/zMMPP5wRveldXV2cPXuWBx54IO3l/klM0xwrP87EEvtkT3xHRwdOpxNJkti6dWtGLjqkg2xGfjLJnnhZlhkdHWXJkiUZMb1iKk6cOEE0GmXr1q0ZE5+u6/z2t79l/fr1FBUVpTscotEov/71r7n//vtTask2DIMlS5bw9a9/nde//vVzGOHckzFK6dFHH+XcuXPXFfEgXDbny3Qlx6aiXrVKpxsGmmGiGSbBqIE/rGGYESRAQoj88nwXVQtycFgUbKpM/2gEiyJTmGPjd1YX0+kL0z4UwheK0zcSpW8kyvG2YTYu8Y4J+UMtg/zqXDflXieLC5wsTpTru2yJl0tSEm7rHnAXixnq0SCWiA9LxI8r7gNMsFhBdRKXVOKGSVgzCUQNNEMHQJEQvfayhNsm4U4KfCVZqj/LAt/hhWUPi21Stv5wIlt/SWynnhKZ70UbhKjPFCd8WR2fSQ/jbvhDLeLvsdhFlj5nYeL1SYwWzJIlS5Ysc8brX/96PvShD3Ho0KGURoW63W7y8vK4cuUK1dXVcxjh9CgpKaG+vp6Ojg6WLFmS7nAAcQ2wfv169uzZQ2lpaUaV2E80ttuxYwcOh4MjR45w8OBBtm3blhGLM1kyh2g0yqFDh3A4HGzcuJFQKJTSnPn5pKenh+7u7pTLxeea9vZ2bDZbxnwOtLe3k5+fn7Kv2t69e4lGozz44INzFNn8kRFC/rHHHuO///u/2bt3L2VlZWmNRQIUBYZGo6iKgkWRsCgyFkVGkWUUGaZaSjBME80w0HSTaNwgFNXRk9l8QJEltlYVoMoSdouCbhoMjsboTZTjF+fZ0A0DRZZp7BnhRLuPE+2+Sc9R4LJSnu/kf95TRXlC9OsGKKoDVAe4CkGPQzwI0VEIDUJsFIsew6JYcFocYLOPZYw1wySmi6171ODKBIFvTQh8jy2RwU+W6M+WwJcVkXUvWgUbPwhhH3QcGc/YRwPQuldsAN4KIejLNkPJXcKULt1c44YfEce+r17cbnGC3SNeF5tHiPxsf32WLFmyzCo2m41HHnmEp556KiUhD7BkyRKampqoqqpK+wWzJEnU1NTQ2NjI4sWL0x5PEqfTSW1tbUaV2F/PnX7z5s0cO3aMgwcPsnXrVuz2mfkUZbm9CIfDHDp0CLfbzYYNG5BlOaU58/NJLBbj9OnTGVdSbxgGTU1N1NbWZsRxMk2TtrY2Vq5cmfK+//7v/87v//7vZ8Rn2c2S1tJ60zT50z/9U/7zP/+Tl19+OeXRD7NdPugPx/nMz88T1QzKvA48dhWnTUWRJOK6gW6IQ6XI8pjAV2UJVblxf41pmuimiaYbaAbousjsG6YJEsiSNPY4FkXCF4rTMRymNyBEfqcvzFAwNvZ4337fxjETvR8ebuNX53tE730ic5/sw8+1KwnjtlEhlKMjQmyCyBSrdlCuXcvRDZOobhLXIaqbaDogCYFvSfTh51jHM/j2hLi3qRLybLy5DX3cCf/KYZG5nzi3XrVD6Toh6ss3Q256F3+mxDREGX48JAz0JHm8v97hFdl6q3vK458lS5YsN8OdVloPIsPytre9ja6urpQysbqu8+tf/5otW7ZkRM+nYRi88MIL1NbWpj2xMZFMKrF/rRFzhmFw6tQp+vv72bx58y09WupmyZbWw9DQEEeOHKGoqIi1a9de0xP/WnPm55sTJ04Qi8XYsmVL2mOZSHt7O42Njdx///0ZEVdfXx/Hjx/n4YcfTsnnIBKJUFxcPPa5f6uTVhXx6KOP8sMf/pCf/exnuN1uenp6AMjNzU3LKlTrQJCfnuy85vduu8pCt40FOTbyc2zkOlTcNhW33YLDKmMYIsktS1MLfEmSUCXpmlL9JLohsvm6YRKJGaJE3ytm2GOCqkhohslQMMZwMEZU1+kbjWCRZVoGggyH4gyH/Jzp8E963FyHhS++cx2FOcWQU0zfsB+LESFPCiFFfBD2i3571SrKwhW7EOyyhFOWwHJtnDEdYoZJX9Cgc0RHAuSEwLcqEi6LhNsq4bDIiRJ9sKcq8GUFFq4U24b3Q8Qv5tYns/XhIWh/VWwA7lIo3ySEfen6zBgXJ8miX96aKPdJ9tePdMFwmxDwVhc4CkRG3+YWGfsMNV3JkiVLlkxmx44duFwufv3rX/OmN71p2vspikJ5eTmtra0ZIeRlWWbZsmVcvHiR0tLSjDHiypQS++nMiZdlmfXr19Pc3MyBAwdYt25dRi2KZJk/2tvbOXPmDCtXrrxu1U0mZeYztaRe13UaGhpYvnx5xsTV1tbG4sWLU/6M/MUvfsGCBQvYvHnzHEU2v6Q1I3+9f4Z/+7d/4wMf+MBr7j/bWYcrQyF+8Gobp6/48IXi9AQi+MPxG+6jyhIL3DYKc2x4nRY8DgseuwVPQuxbVRlZSop7IfRfK4M/kauz+eLruAFf3DDwheIMjsYYDEYZGI3RG4gwMBpDlSV+8AebsakKFkXmC79p4OXGftw2lfJ8B+W5FhZ7JBbbo5Q7IuSrcfGaWBxC2E/TjV03TOIGiSy+yORjJpLQssjgO60Jga/K2FTGSvUVOcUPBNMUM+qvHBWl+D1nhUhOIqtQtHpc2BdUi0AyDT0+PubOSCymWF3gLBTC3pqT0cZ5hmFw/vx5hoeH8Xq9rFq1KmMuOLNkudO5EzPyAJ/85Cdpbm7mmWeeSWm/pOndQw89NG8+PDfCMAxeeuklli5dSkVFRbrDmURrayuNjY1pKbGfjoi/muT4rsrKyozIts43d2pG3jRNLly4QFtbGxs3bpzWwlO6M/OxWIyXXnqJ2tpaFi9ePK/P/Vo0NzfT1tbG7t27M+I9FA6HeeGFF7jvvvtS7o9/y1vewrp16/j0pz89N8HNMxnjWj8T5uJixReKcax1mAVuG7IkEYpp9AYi9CR62XsS3/cEIvSNRMfK7a9HnsNCQY6VXIeFPKcVj10l124lz6nitqtYFCXRg5+awE+SzOZrhommi+8N0ySuGQTCGsW5NtREhcBTh9s53xVgqohlCZ597zIs8RGI+DjRGcbEpDzPwgK3E8mSem+3YSYy+BMEvoHwIbAmMvhOC+RYZZwWeaw8366KVoNpEQtB10nhgt9xBAJdk293eGHRRijbJEbdOacebZh2kvPr42EwjHHjPGeh6LO35Yie+wz4AD148CBf+cpXqK+vJxqNYrPZWLlyJY899ljK/alZsmSZfe5UId/U1MTq1atpb29P2VH54MGDFBQUsHz58jmKLjW6uro4c+YMDzzwQMbMlQchkJKGYevXr5/X501VxCcZGRnh8OHDuN1u6urq7ihBeycK+Xg8zrFjxwiFQmzZsiXl/5V0ifnjx48Tj8czrqQ+Ho/zwgsvsH79eoqLi9MdDgAXL17E5/OxdevWlPbr7OyksrKSpqamjDEUvVmyQv4qrhbyN0I3TPpHo0LY+yP0JMbPJYV+KKbfcH+bKpPvspLntJKXyOR7nUL4F7hs2C1Jkz1pRm9qwzSF0NfH3fYjcY3BYIyBkSgDwRiDozEGRqMosszfvnGlyN5LOv/7F/U0DYh+eocCZTkm5W6JxXkWFnvtbFo086yFYQpRH9NNYkZC4Au7ACyyEPgOC7itMg5LsgdfGO1Zldc4Dv4OIeqvHIWuE+OeAEkKliZE/SYoXp0ZpnlXY5qgR8UiRTwsfpcU9q6FCef89DjiHzx4kMcff5yhoSFKSkpwOByEw2F6enrwer18/vOfz4r5LFnSzJ0q5AEeeOABHnjgAf7qr/4qpf26u7s5c+YMDz74YEZUF5mmyd69eykpKWHZsmXpDmcSoVCIPXv2sHHjxnkZQXUzIj5JLBbj2LFjRCIRtmzZknIW71blThPyo6OjHD58GJfLxYYNG2b0N6dDzPf09HDixAl2796dUQZ3IERzf38/O3bsyIgFBsMw+M1vfjOjEXh///d/z+HDh/nFL34xR9HNP1khfxWpCPkbYZomIxFtLIPfHYgkHOrD9AQiDI7GpsyMJ5GAXKcFb0Lk5zks5LusFOTYKPbYyLFbUGco8JPoCZd9zTCJaToGYCQU9S/OdI+Z7F1ddLDAbvLVe3VkiwOLzckzDXEkoDxXYbFHpThHTr1kHnHM4kZC4CeEvm6CjGhhsCqi395tk3FapHEnfUXcds2x0OPQey6RrT8mDPQmotqhZJ3I1JdtgrzFGZHxvgbTBC2cMM+bYFZoc4sZ9sn+esvcuvMahsF73vMeTpw4wdKlSycdb9M0aW5upq6ujh/84AcZcSGcJcudyp0s5J999ln+8i//kkuXLqX0OWSaJi+88AKrVq2itLR0DiOcPv39/Rw5coQHH3ww40aptbW1ceHCBXbt2oXTOXe+NLMh4pMYhsGFCxdob2+fdrn1rc6dJOR7e3s5fvw4S5YsuWln9fkU88FgkL1797J69WrKy8vn7HlmQjQa5be//S3btm3LCA8RgI6ODi5evJiy6Z6maVRWVvLVr341JR+VTCdz6rUyDN0wkV8r+3sDJEkS/fIOC8uK3NfcHtMMekciY+Pnrhb8MV30vvtCU/foOywKeU4LeQmxX5hjY0GOlYUeOwUuK8o0LmAmjtMbm1Gf4L1bK9BNg2jcoG8kSk8gTG8gyuBIhByLQUNUxT4awGr08F/1dka18WOlylCao1Ceq1BbaOHNy6e3uihJQpBfnXU3TRMtIfBDcRNfREM3x5/LOoWTvsjgq9hK1iGVrofN/xPCwwnTvKNC3IeH4MqrYgMhiss2ifn1ZRvAnjetuOccSRJl9ZbExZJpCEEf8cNon/hdctSds2DOhP358+epr6+npKTkmg9PSZIoLi7mwoULnD9/njVr1szqc0+XbO9+lix3Nr/7u7/LY489xm9/+1sefvjhae8nSRIVFRW0tLRkjJBfsGABXq+XpqYmVq1ale5wJrFkyRJ8Ph9Hjhxhx44dc1L+P5siHoQJ3urVq/F4PBw5coTy8nJWrVqVUa0LWVInHo+P/Z/cddddsyKG58sALx6Pc/jwYcrKyjJOxAM0NjZSWFiYMSLeNE1aWlqorKxM+fX45S9/CcDv/M7vzEVoaSP76XUVsizhsqkMhWLoujFhPJzoM0/OlLcoN5cNt6oy5V4n5d5rV7IN02Q4GJvUjz/2NRDBF4oTjuuE/Trd/sg1+yuSRG5C5Be4bBTmWFmQY6PIY6Mgx4ZNfW0TO0WWUFCwKgpuu4XqBeMn0KQBX1zTCUeDbK/op98foi+k0xeWiBsS7QGd9oBOf1BjQ5GETRVZ+icOjOKxySzOVVnsUVicp7LIrWBXr38sJUnCoghn/KuL4eK6STwxLm9k1OCKoSeOwVSj8jzYy+7DtuQ+bArIvlbhgt9xFHrOQLAfGp4XGxIU1ohs/aKNKZXhG4ZJc0szI4ER3B431VXVyDOoULj+AZGFM791orAPi4WJkR4h/NXkDPsCMebOlgPqzZk4DQ8PE41Gr1v25XA46O3tZXh4+KaeZ6Zke/ezZMlisVj4gz/4A772ta+lJORBiNOGhgaGhobIz88MP5Xa2lr2799PVVVVxpXcrlmzhoMHD3Ly5Ek2btw4q0JntkX8RBYvXkxBQQEnT55kz549rF+/nsLCwll7/CzzR19fH6dOncLlcrF79+5ZrQ6ZazFvmiYnTpzAbrdn3EIdiEqB1tZWdu3ale5QxhgcHGRkZGRGZoBf+9rX+MM//MPbbuEuW1o/BZG4TlQziGkGcd0gGtcJxjSCUZ24biQ2cdhMk0kCX02Mn5tJafl0Ccf0MVHf4w/TE4iKr/4IvdMw4HPZFPKd1nGR7xGu+wUuGx67OuMPKkmPQizIsN9Pz5Cf3pE4bkVj7QITTbYxalr5369e6xsgAYVOia2LrLx7tXPMnC+mmzgsM4tlbFSebgqzPQMwQZETo/Lkq5z0ieIcOIu15wRy5zHhjD8RxQYld42b5nkrpyzDP33mDM/8xzNcvnyZWDyG1WKlsrKSR975CGvvumtGf0vKGPp4Kb4WEwdYdU0W9lZXyhn7s2fP8r73vY+8vLwpL6pGR0fx+Xx8//vfn/eMfLZ3P0uWce7k0noQI6dqampobGxM2dDo/PnzjI6OZtR84ePHj2MYBps2bUp3KNcQjUbZu3cvixcvnjWjwLkU8Vc/z+XLl7lw4QKLFy+mtrb2trvIv11L65NZ+I6ODlatWkVFRcWclb/PVZl9fX09nZ2d7Ny5M+NaZwAOHz6M1WqdV1PL1+LQoUPk5uZSW1ub0n5JI9TW1lZKSkrmKLr0kBXyKWCawn09pguRn9yCMY1wXCMSGxf5euKwykhjjvQTZ8zP1QeObpgMjkbpTmbxJ/Tl9/gjBF/DgE+VJfJdolS/MEd8LcixUeCyku+yYpmus76hI2lhFC2IHPGhaEG0WJQmv0RnxEpXSKE7BL1Bk1BietzmYpm3LlVRFIm4AX+zL0qeXaI0R6bMo1DmUVicq1CRa8HrUGbUzp4clZd00o/Eoae3m0gojDvHwZJFpbisEnmmj9yBkzh7j2PtOY4cHpr8QI788RL8RRvAtYDTZ87wxf/3RQKBAIWFhdhsNqLRKAODA3jcHj76sY/On5hnQmWA30+uy0LlomJkIz5Z2Dvzp12Kn+yRP3nyJNXV1RnTI38r9e5nS/+zzAd3upAHePvb305NTQ3/9//+35T2S4412rVrV8Ycu0gkwosvvsimTZsysq/b7/ezb98+6urqbrotYb5E/ESCwSAnT54kHA7fdtn521HIT8zCr1+/fk49GpLMtpjv7Ozk1KlT7Ny5E7f72vbbdJP0G7j//vszYiQngM/nY//+/Tz44IMpx/Sxj32M3t5efvjDH85RdOkjK+RnEd0wx8R9VNeJaQaRuE4wqhOK6WiGEPqabo4Z3V1drm9R5Jsy2XstRpMGfIEIXb4wXT7htN83EmEwGONG/w0S4HFYKHAlBf54Vr/AZcNlU6774SbpUeR4EDk2ghL1I2lhJFPHkC0EDBvdYQtOq0ypS0YzDa74db5wLHbdWHaUKbyr1o5NkUCSuOQzWOxRWeBSEhURr30sGpua+O1vXqCrq5OYFke12CkqLefuXfdSvqRyzOTPIkFeuJUFwyfxDp7EOXAGWY9OeiwzbwmH2mO8cmmUYWcFMXN8Vd80TTo6OlixYgWf/fvPzm6Z/XW4YWXA6lVXZewlUJPmeYVC1F/HFT+Z+R4eHqa4uDgjMt+ZXCkwkWzpf5b5ItPOjeng5Zdf5u1vfzsdHR0pl6SfPn0aTdPYsGHDHEWXOs3NzbS2trJ79+6MXPzr6urixIkT3HPPPeTm5s7oMdIh4ic+d0tLC/X19bdVdv52EvLxeJwLFy5w5cqVOc/CT8VsifmkIN24cWPGjHObiK7r7Nmzh+rqaiorK9MdzhhHjx7FZrNxV4oJsdHRURYtWsQvf/nL2/JaKyvk5wnTvCqTn/g+GNUIxkQpv6aJbL6BCabo17dcJfRnMmt+umi6MLbr8oXpTIj8nkCEvpEo/SNRoppxw/1tqjwm7q8W+16nZTx2Q0fSQihaaCxbL2lCGJuqHUO1Y8oqobhJT9CgZ9SgJ2jQPSp+HoqYvLFK5Z4yBd0Qv/vySZHWtyuw0ClRnMjil3sUlnotFDhF20PS66DpUhM/eupHjAaD5OXlYbVaiMXi+Pw+cpwu3vXud7GspmaS0V6yVN/QY3h99RQOn6Rg+BRufxMS48dGN6E1nENTMIfGoJu2sJPRUJSRkRE+8/efoWbp0rl5AROkXBmQ7LGPh4Swh4Qrfg44F4iv1oSwl6QpBWltbS2PPvpoWj4k9+7dy4c//GEqKipQlGv9H3Rdp7W1lSeffJKdO3fOe3yQLf3PMr/cSufGucI0Te666y4+/vGP88EPfjClfYPBIC+99BL33XdfxowpMwyDV155hbKyMmpqatIdzpQ0NDTQ1tbGrl27Us6YpVPET2R0dJRTp04RCoVYvnw5ixcvzoiRWzPldhDyhmHQ3t5OQ0MDOTk5rFu3Lm3vy5sV85FIhFdeeYWqqqqMfh93d3eza9eujPnfHx0dZc+ePdx///0pV2A8+eSTfPOb3+TYsWMZ8/fMJrf+cuMtgiRJ2FTlukZzcX28Jz+mGUQnZPPDMZ2wphGImui6gSmJkn1VHs/iz4YBn6rIlOY5KM1zsPGq20zTZDgUo3NYiPzuRMl+30iUgdEo/rBGVDPo8kXo8l1rwCdJkOewJHrxrWPl+gU55RS6IYcwihZCiQwjx0aQDA23rJKT46Aq1wrS+AkoqpkYgCNhkDcQ1Vno1BkIm0R0aB8xaR/ROdIt2ggeXBLl3nIFRZYIxiWOduu0n79MUMlnUekCZDQwTWx2lSKbjd6+Xn772xdYWl0jFlOuMdpzQG4dvvL19OkmRmSE0bO/JnTueTZ7A5RYRql2iu11C3qIGApNIQ9HeyDYeRGtshJ1CsE5GxiGyTP/8QyBQICy8rKx/weH00GZo4yOjg6eeeYZ1qxeM14ZIMmiZ96a+AuTrvjRERjtT2TsbWBxgbOQ7Wuq2fqdJznf2Mqwz5f2EnGv14vNZiMcDk958RcOh7HZbHi93jREJy5CvvKVrzA0NDSp9D8nJ4fq6mqam5v513/9V7Zu3ZqRmbYsWW5FJEniz/7sz/jnf/5n3v/+96f03nK5XJSUlHDp0iXWrl07h1FOH1mWWbNmDa+++iplZWUZZ3wHsGzZMgKBAEePHmX79u3TPuaZIuJBfC7ffffddHZ2Ul9fT3NzMytXrqS4uPi2FAGZjGmadHd3U19fj2marF69mtLS0rS+DjdjgKfrOkeOHKGwsJClc5zQmSmhUIimpia2b9+eUf/vTU1NLFq0KGURr+s6/+///T8++clPZtTfM5tkM/K3AIaRyOZPyOi/lgGfMpbJHxf6c2XAZ5gmwahGpy9M57AYU9flD9MXEOX6Q8EY2msY8NktciKTb6HQKbPAbrDAEqXIEqZAiaLIYKq2RLZ+6lXluGHSHzTpDooMfm/QoGfU5E01FtYUquimyaneON85O2Gkn2lg10M49FEc+ggFkS6soT6i4RHe9fuPUL5oEaosoSoSipRcLLn2uduvXOHrT34dp9PFohyDlc5hah2DrHIMkKtMLsOPW3IZXbCWWFEdRmkdal4pdlWMzbt69F6qNF26xN/97d/hdrtxOK+90AuHwqlXBkw1x161iZF3zgKw544vBMhzs0BxIzK1dz/JrVL6n+X24U45N74WkUiEyspKvvGNb6Q8NzjZ9/3AAw9gt8/uKM+bIZON70DMat6/fz9er3daiyCZJOKvxjAMWltbaWxsxOl0Ultbe8v1z9+qGfn+/n4uXLhAOBxm+fLlLFmyJKMWulPNzJumycmTJxkZGWHHjh1TVg9mAplocJf0Lbn33ntT9hN49tln+djHPkZzc3NGGgrOBtmM/NVoUXj63cKdfMk2MXrMOvdGGjdCliXssoLdMvUbf2KpfjKjH4ppBGPCgC8U0yYZ8ElwTV/+zRjwyZKE225hRbGFFcXjF41j7QRxg/7RKF3+CJ3DIboDEQZHogwGYwyH4oxGNSJxQywE+MJXPzqy5MBrlym0GyywRVhgG6XAKVHotJDvtuG0iN58iyxR6pYodU/9Ya9IEvkOhVWeEZp7R4jZ8jBkCxE1h4iawzDFODU/DpsNLRLjSGec7zYHWOCUKHJJFLsUSlwS+U4VuyraHJIO+wuLSykpXURbWys220L2B0rZHyhFwmSRZYTFehvbSjRqXX4scT/err3QtRdOQti+kOH8dXQVriO8cB02dyE5ViHsbYqU+Mq0Xp+RwAixeOy6ZY02m43BoUFGAiPTfn2vnWNvgh4Vwn6oWWTwFau43ZEPjqSwzwFl7i8cZFnmscce4/HHH6e5uXnK3v1HH300bRcBmT62L0uW2xW73c7HP/5xPve5z/HGN74xpXNcbm4uhYWFNDc3Z9RoqFWrVvHiiy/S19eXkcZ3qqqyefNm9u7di8fjuWGPbSaLeBDnlqqqKhYvXkxzczOHDx+moKCAlStXztgHIMuN8fl81NfXMzQ0RE1NDVVVVRnpVZBqZr6lpYW+vj527dqVsSK+p6eHwcFB7r///nSHMonm5maKiopSFvGmafK5z32Oxx9//LYV8ZAV8tfSdRIu/VZsALIKJeuEqF+8HRZvFU7fGYRVlbGqMkyh3aYy4IvGhdN+KKYT08X3YwZ8szhOb2I7gdthoSoxi170nZtENYO4ZjASjdORKNnvH4kyOBplKBjHF47hC8XRDJPBsMFgGBqQgYlvyCgOxaTQAYUOmUKXSoFDotApU+iQyLdLk2KvzFN4R6XGT44/j81uB4eHsOImrLoJKW7c8SGMSBjV1AhJTpp8Jk2+ZDWBKNV3WaIscEi8rlKm3C0jIWECKzbvpif4W3pGRnG7HNhUhXg0xrF+jXpnNflveCfS0gocww3k9J8kp/8kjqGLOCJ9OLp+A12/ASDoKmfAu45O71r8+Xch2T1YFQmXRYzLE9l7xkS+OuHvc3vcWC1WIRynyMhHo1GsFituz024pEoSqHaxORLl6lpUZO39bTBsiMy8xSmy9Q5vwhnfddOz7K/H9u3b+fznPz/Wu9/b24vNZqOuri5tvftJMr30P0uW25kPf/jDPPHEE+zduzflecg1NTW8+uqr1NTUZMyFoN1up7a2llOnTrF79+6MzLI6nU42bdrEoUOHsFqtLFq06Jr7ZLqIn4iqqixfvpyKigoaGxvZu3cvpaWlLFu2LCMdx29FAoEAjY2N9PT0UFlZyYYNGzLmPXc9pivmr1y5Qn19Pdu3b8/IlhgQlRunT59m1apVGeNSD+KatbW1lbvvvjvlfX/729/S1tbGH/7hH85BZJlDtrT+akZ6of7n0H4I2g7BSNfk2x/4DOz4qPg+EoCIH/LKZ+e555mpDPjimpko2Rc970mXfd00Rcm+NLfj9JIVBSIWg3BMo9sfpXckwsBolMHRGMOhGL5wHH8oxkj0xuP0JCDfLokMvkOI+wKHxOmDexjpbqEg1zVpSoBpmgwPDVFSWsqO33kbzT4jYbg3brSX5BNb7Sz2KJgG7GmP8VxznDw1jjkyAMEBLFEfDj1IkUdl8/p1LC4rw5JYdLGpIptv1aPk+s+TN3QKz8Ap7P7mxLJAIh4kQp5qhgvWMpi3lgHPajTVgQRYFVGF4LCA2yrjsEhYZPj8/32CSw0XKF9UfM3fNm/u+YaWKMVPOOPLMqjOhIFeQcJAzyXE/iz2LWXieLdML/3PcvuRLa2fzKc+9SmOHj3Kr371q5T3PXToEB6PJ6Oy8qZpcvDgQXJycjKmh38qent7OXr0KBs2bJg0u/lWEvFTEQqFaGhooKOjg4KCAqqrq1m4cGFG9uBmcmm9aZr09vbS3NzM0NAQ5eXlLF++PGPF7vW4UZl9Z2cnJ0+eZPPmzRlZQZPk5MmTRCIRtm7dmlH/x2fOnCEcDrNly5aU9929ezf3338/f/M3fzMHkWUOWSF/I0wTfG3Q/iq0HRTi/ne/CuWJ3rQzz8BP/wg8ZYmM/TZYsh0KlwvhcoujTezLT3ydOE4vrhvEDSH0MQFp7sbpJWOJ6yZRTbj8h6IagbBGf0Lk+4Jh/MEI/lAUX1hnKGoSN2783LIew6YHcRghLLERCA7ikqI8sH09q6oWTcp2gzDa6w0Z9ARN1i1Uxnra/6M+yt4r2tTPIcHHN9oodkkYJvSM6oQ1g0IH2FVR7aDKYmSeywxSNHKBQt8Z3P3H8UR7Jj2WKSmEvMsZLVyLL38tvtyVRLAJN/3EO/lKWyvP/edPCQcDFOTYcKqgRUP4BvvIdTr42EceZf3a+ZtnD4ChgxZJCPvoVQZ6BYmMvVOU46ehz36uycSxfVluX7JCfjL9/f1UVFSMzTpPheSoqPvvvz+jBEYwGGTPnj0ZLxC6u7s5fvw4mzZtoqio6JYX8ROJRCK0tbVx+fJlVFWlsrKS8vLyjMokZ6KQj8ViXLlyhcuXL6PrOhUVFVRUVGRUJjhVphLzV//vZyq9vb0cO3aM++67L+M+41566SV27dqV8nns1Vdf5aGHHqKtre22r3bMCvmbYd8X4KX/A+ZVWWGHF8q3wkP/Gwoz05nyZjFNURqfzJzPZJxesmz/ZhhrHUgY/iVNACPRGPFIkMBoEF9gBF8oij+i449JDMYUhiIS/uuPqQdENj/PLiWy+DKFiax+gUN8dVvH+9Z1w2QgPHFcnjlmuBfV4Z92O3FaxH1/fDHKy+1C9OfZJBY6xbbAKVFgl1BHuzh35jRDg8PkMsJ69yCb80dY7x4mVxucFKMhqwTzVhIsXEto4TpC3hXEsFDfdIkXXtpHd18/cd1AVSwUFy3g3p13s2JpNU6rRI5VwqHK2BTG+vEtN2m2N21Mc4Kwj0zos3eA3QuOvHEDvTkqx59vMm1sX5bbl7SfGzOQj3zkI3R3d/PMM8+kvO+xY8dQFCWjDKAALl++TFNTU8aW2CeZmJXs6+u7LUT8RAzDoLOzk9bWVnw+H6WlpSxZsoSCgoK0ZzczRcibpsnAwABtbW10d3eTl5dHZWUlpaWlt00l2kQxX1BQwNGjR6mrq6O0tDTdoV2XeDzOSy+9xIoVK1iyZEm6w5nE8ePHkSQp5cVXgN/93d9l+fLl/OM//uMcRJZZZIX8zRIdhY6jImvffhA6jol53AB/3gDuYvH9mWdgoFFk7cs3iwzkbUzSSX+sP/+qcXpxY0I2HyGaVXlc3E/M5humQUtzC4GRAB63h6rqKmTpxh/8hjnuDRDXDWKREJFQgEhoFCPiR49FiMZ1hmIKHcNRBiIQkWxEJDtDEZOBkEnMuOFTYJWh0JkQ+VOIfasiYZom/qhJnn083v9sjHG4S2MkNvVbb1X7s2hBH+4cN353BUHJAaMDuOUob91SyVrnAMWBsxSNnMcZH5q0ry5bCeSuIFBwF4H8u2iJeAhHY7hdLkpKy9CBmG4S101i+lghBaosYU0IerdVwmWZbLZnVZiVyoobosfGy/ENDSQFVAfY3cJEb47K8eeTTCz9z3L7kRHnxgyjvb2dZcuWcebMGZYtW5bSvjeTGZpLkiX2LpeLdevWpTucG9Le3s6pU6dQVZWdO3feNiL+agKBAG1tbVy5cgWbzUZpaSnFxcXk5eWlRdSnU8ibpsnw8DC9vb10dnYSj8cpLy9nyZIlt623wMjICPv27UPTNOrq6igrK0t3SDfkxIkTRKPRjCup9/v97N27d0Zz48+dO8emTZtoaWmZ1NJzu5IV8rONHofuM9BzGjZ+aPz3P3gbNL8ovpcUKF4jyvAXbxXiPidzS+Nmm+uN0wvFRcn+xGz+hYv1PP+L5+noaEeLRrCoMkvKy3nkHW+jbgYXLqZpEovH0aKj6OFR9NAwkWCAcCRC3ICoZEGTbBiSSliXCEQN/FEYjpoMRwyGwiLz7ouYvNYbJ9cm+vGTGfzk10KnRK5NIqIxPiYvaNIzqtPaM0xp048pyM9HkiTqc7cybBv/IJJMg6IchSKXTLFT4m0l/Sz0n6XAf44FgXM44r5JMWiylcGcFQzmrsKXfxdh73JUiw1FkVAl4XWgSELQx3SxeBHXTbTEIoYigUWRJpnt2eYri29oE7L2MSHek+74Y+X4iaz9PLjjZ8lyq5CR58YM4IMf/CCyLPPtb3875X1Pnz5NJBKZUa/mXHIrlNgny+nb2towTTOjY50tdF2np6eH7u5uent7URSF4uJiiouLWbBgwbw5l8+3kNc0jf7+fnp7e+np6cEwDBYuXEhJSQnFxcUZ69g+WyR9ISRJorKyMqU58/NNT08Px48fz7iSehDeJDk5OTMayfue97yHnJwcnnzyyTmILPPICvn54vR/CCHfdgj87ZNvs+bAJ9pASQwRCA2J8vwMffPPNclM/v5Dr/K3n/57hgMjLCgqxeJ0E4nrDPkCuNwePvChP2DFihVj2fyrTfimm0GW9BhSbAQ9PIIRGkCPjBKLxQjrEqOmXfSgoxA3TCQkxKOajMYhkBD4g2ESzvom/WGDyNTt8mOoEuQnsvhC4EtYYgFO7HsBtxzHaRXP0uOoJGApEM76Sg6GPD5owq7A5+9zjp0kfng+gj3YwQ61nvXGBWqi53Hp/knPq0kWBnKW0+uupd+9mmFPDZJiw6IkBLpFQZEkIfQVCcmUMEwJDZHFj0/I4os2CbCrEm6bjFOV5jaLP3HsXTxRji8ns/YeMU3CkhD2Fscd+/7JkuWWOjfOIxcvXmTdunU0NDSkXEYaiUR44YUX2L59O/n5mTW55vLlyzQ2NrJ79+6M6s+Ga43thoeHOX36NBs3bqS4uDjd4c0LhmEwODhIT08PPT09RKNRFixYQHFxMUVFRdjt9jl77vkQ8pFIhJ6eHnp7e+nr68PhcIz9bQUFBXdM1VmyJ379+vV4PJ6U5szPN9FolD179rBy5cqMK6kfGBjg8OHDPPDAAyn7Jly6dInVq1dz/vx5qqur5yjCzCIr5NOBvyNRip9wxncXwXv/c/z2f9kI0ZHxbP2SbVC0+rY0AbseSafvEydOsHTp0rEPQRMwkGlpbWfNuvX8vy/9C3HdnDKbb2JgmKDI8vR7800TSQujxEeQo37U8CBGLEQ8HieCSkRyEMZGUJOJaBA3TOITSvBVWYj0uAH+qMFwBAYSAn8gZDAQNhmKjBvTXQ/VECZ8dj2U+BrEogUJj/jYuG0HsnshMd3k4arxi7a/PxCiNzjxgU2WSp3crdZzr6We7Uo9tvhkYa9LFoZyltHnWUVvzkr6nDXoivjglJOCHglVFaMEraosjPkkMCQwE0I/bphophD4E7P4zokj824ii28YJs0tzYwERnB73FRXVQvX/Ynu+Hpc3NliFw75znwh8C3ObNY+yx3FLXtunAfe+973oigK3/3ud1Pet76+nsHBQe6+++6MujA3TZMjR44AsHnz5oyJ7XrGdl1dXZw4cSLj+4fnAtM0GRkZGRP1Pp8Pt9tNbm4ueXl55OXl4fF4Zm12+mwLeU3T8Pv9+P1+fD4fPp+P0dFRvF7vmHh3u90Z8z84XyR9ICZOaLiRm306MU2TV199FVVV2bhxY8bEBSK2ffv2UVRUxPLly1Pe/13vehcul4tvfetbcxBdZpIV8pmAro1n4yN++Kelol94Ila36K2vfTNs+MC8hzjfnD17lve9733k5eVN2Us3OjqKz+fj+9///qTSm4l9+XF9er35ylVO+8JBPvHBZujIWhAlNooSGUKJ+pDiISRM4rKFiOQgKtmJGRJRzSSkmYTjCYGvg26aSJIkxK0soSogJ7L5AyFzLIs/EDboDsToCcTQ1dcqcTLJsyUy+c7xjH5cF+XxgZhJX0iY7fWHxKJBmVvmk1vt5ISukO8/T2/zadYaF1ggXS3sVYZcNfi9qxjwrGIgZzkRyY5hgq4bwrgwQdJtX5bAqirYVHEcJUkSAh/QTTFM7+osvk2VyLFI5FjlRPZeGhP6V2fxT585wzP/8QyXL18mFo9htViprKzkkXc+wtq7rnLfv8ZEz5yctXd4RQWM1XlL99pnyXIjbptz4xxw+fJlamtrOXr0KKtXr05p33g8zgsvvEBdXV3GuVDHYjFefvllqqurMyIT9Vru9D09PRw7dox169ZlfB/xXBKJRBgaGpokjGOxGG63m7y8vDGBn5ubOyNxfzNCPinak3H5/X5GRkaw2WyTYsvPz7+lHedvlvb2ds6cOTOlO30mivmmpiZaW1u59957M84ks7u7m9OnT/PAAw+k/P9+4sQJduzYQWNj4x31mZIV8plIPAydJ0TGvv0QXDkC0YC4re598OZ/Ed/rcXjpf0P5FpG9d2ZWud/NsHfvXj784Q9TUVExZU+Vruu0trby5JNPsnPnzmk95tW9+UmX+1BMn+S0rxkmujnZaT9Zsm9Fw6oHUbQgangQJRZA0iKAiaE6MCxOdNkqRLUB0UQ5eihuEEwIfE0HzTBBEmX6FiUh8iWT//rpT+ju6cNRWEZUdRFVnEQUFxHZSQg7ms2DLt34w02VocAuyvbzEyPuXBZYUaBQ6JBxqPDXr4QJxAyqpG62yPWJ7SIl0mTzPAOZLlsVHa5aRvJWEV9Qi2nzgCkWKXTDQDeEa79umJgJ2S4hi9HxibF6VlWM6jORMBNCX1RXSKiyNJ7FlyWcVtGP77BIXGqo51tf+yqj/mEWFORht9mIRqMMDA7gcXv46Mc+OknMT5m5Nyf02uvxCb32DmGiNzFrf5s45Ge5s7ltz42zxEc+8hEuX77Mz3/+85T3bW5uprW1ld27d2dcyfDg4CCHDh3i7rvvTuvIpemOmOvr6+PIkSMsX758UuXdnYxpmkQikUni2efzEY1GsVgs2O127HY7Nptt7PuJv7NarUiShCyLRXVN0/jlL3/J6173OlRVxTAM4RUUixGNRolEIpO2ib+Lx+Njon2icLfb7dnXCvFaNTY20tTUxJYtW1iwYMGU98skMT80NMTBgwfT/hkxFbqus2fPHqqrq6msrEx5/4cffpi1a9feEU71E8kK+VsBQ4fe86Icv2gVVNwtft95HL553/j9FqxIlOMnTPTyFt+yGceZZuRvBk03iMQ1zpy7wMCQD6c7l8WV1YTjBqGYLpz4DQNdHze6sxoR7HoYuz6KLTaIzQijGDFMWR4T9shixdM0RRm+EPnCNT4cNwnGTSH4DWjv6GLv3r3EIhFynA4siowRjxAa8eNw2Hn44dfhLS4fL9ef+DVkMhx97bJ9hyqEfq5dlLlLgGZAMG7givTygOMib/E0UuA/jzPSe83+TZTTaFnJFWct0cJVLF10rWmRaQpRrRsGuikWLowxoQ8yErIioUiiF1+VJWRJxpQkDCQMU5T2P/P0j+juaGdBgRcFHdWIYTHjSEac3s52ltdU8b//7m+xqvL0M/djvfYJcW/o41l7W2KufdId3+Icr5bJkuUW4Y45N86Qvr4+qqur+eUvf8mOHTtS2tcwDF5++WXKy8upqamZowhnTmNjI21tbWnLtqU6J97n83H48GEKCwtZt27dbW+GNhOSwjscDk8pvieK8Ole0kuSdN0FgeTvHQ7HHZ1pvxGapnHy5EmGh4fZsmULubm5N7x/Joj5ZNVOVVUVS5dm3mjshoYGuru72bVrV8rH56WXXuJtb3sbLS0tGedhMtdkhfytTN9FePWrQuAPNFx7+8NPwLZHxfd6HCT5lumzT/bInzx5kurq6klvatM0aW5upq6ujh/84AezlhWZas73ypUreeyxx9i2bRtRbcJIvcTXUEwnGNXEbZqGGQ0ixUdRo35ssWGsRhiLpCOrViSLC9nqhKkqDAyTaKI0vqH5Mi/vPUj3gJ8YErJqw1u4gLvWrqO0tHRSmb5FFqPjJj7OcEQ46w+GjbGvg4mvI7FrnvoaPFbGSvYr1UE8wxeo1epZa9ZTLXVdc/+gvZih3FqGPLV8+UoVQcciinJkFjplil3CpX9ijCB86nTTEJl8E3TdRDcNGBP6MkNDAzz/i+ewWmyoVisSQoOLIn2TWDRCNBjgQ+9/N2Y8wrNP/YBwYIhCrwe7RUaLhBga6CXX7b4mc38NYw75EdCi4olUK6h2sOeKufYWlyjJVx2QYZm4LFkmcsefG6fBpz/9aV544QX27duX8kXjwMAAr776Kvfff3/GuT2bpsmhQ4ewWCzz3v+aqohPEolEOHLkyJijfaYd01sF0zTRNOG0OzHzvmfPHu6//34sFsvY9ZKqqtms+gwJh8McPnwYVVXZtGnTtBc70inmTdPk6NGjGIbBli1bMu61D4VCvPTSSzMyEzVNky1btvDWt76VT37yk3MUYeaSFfK3C8EBuHJ43ECv+xS87+fj2ftzP4XnPgJlm8YN9ErrhDDJUA4ePMjjjz/O8PAwxcXFOBwOwuEwPT09eL1ePv/5z7N9+/ZZfa6hoSFKSkpSfi4tUbIf10yiuk5MM4hEo0SCAWJBP4SHkMLDEAuBaWDIVkyLE8nqRFXkxBg4YS4H4oOps6OTwOgoNkcOhcWlxE2mX6YvC5F/9Yd1RDMZukrkTxT7Uf3Gx2kBfnZaL7JJbmA9F6mhDfmqQXz9Zi5HjeUcM5ZzxFhOA0vIc6hsKlF5Q/W4OV8gauK2XhsjCKHf0trK8798Hk+eF0mSMSWFZLe9ZBropkHA7+eBBx/m1MlT9PT04s3PA0AxdWQjjmzGGerpYOmSUj7x8Y/hsCT78YWr/g1PZnosIewj40Z6qk2U5Nu9oiQ/mblXbbds9UuW24/sufG1GRkZobq6mm9/+9u86U1vSnn/48ePY5omGzdunIPobo5IJMLLL7/MihUrqKiomJfnnKmIT6LrOqdPn6avr4/NmzffcVm1uSKdc+RvR4aGhjhy5AjFxcXcddddKSeS0iXmW1paaGpqysjJFgCHDx/GarWyfv36lPf9yU9+wp/+6Z9y6dKllGfO3w5khfztSiwk+oCTZcG/+qTI3k9EtkDpOlGGv+V/Qe6ieQ/ztZgqS15bW8ujjz46ayL+eg75MDvZf9MUvfnxWJR4KIAW8mOM9hMLDhOLBInFDWKylZhkR5OsmLIYcqdKwmFfmMqJPv1kaNcr0w9pJlEtcdtVbvoTBb4iTyGeTZNgnGvEfbJ8fygssucTcRNig9zIJlmI+7VSMzZp8uy9UdPOCaOGfvdKFlWvwedZhl+38YmXQ9hVKHLKLHRJFLlEFr/IJbHQKeMb6OMnz/4Eu92O1Tb5xGMC0ZhGNB5j2/a7OXjwVWx2B5bkCco0RXm/JBOLxYnEIrz5DW+guGghNlXGbpVxKhIeu4LHJmFTZGwqYyJ/Slf9pJGeFgUtUZIvySJDb3GMl+RbnSJ7r2beyTLLnUH23Dg9vvzlL/ONb3yD06dPp1zSHYlEePHFF9m8efN1e2PTSbJqYNu2bRQUFMzpc92siJ/4OC0tLdTX17N27VrKy8tnOdI7j6yQnz3a2to4e/YstbW1VFZWzliEz7eYn8/PgpnQ29vL8ePHuf/++1Nu5dA0jdWrV/Oxj32MP/7jP56jCDObrJC/U5jYZ99+UGTtR3vGb//YechNuDw2vQCjvULg51elPdNoGAbnz59neHgYr9fLqlWrZtVkKB39+IDI9kZH0MMBtJFe4uEAejSMZprEsBEyrYSxENdNUXpumMI13hSZZFVOiPyE074qSyCJ8vrYBIE/lZu+gYnJuJu+RQZVEaPzrndSMUwTf9RkIGQyFEmK/XHB74uYWImxRmphs9zARrmBjXIjHik06XE0ZJqlCvbHl3PMWMYxYxn9TDZd2bVY5feWW3n2x8/S2dtPvGQtTiOIXRvFZoTANBkeGqKktJSNGzfy3HPPkZfnFSPpEELflGRAQkdixB9g9wMPUla2CM0Qf7uBhGlIIINFlbHKCnaLGJXntErk2hRybQoOi5Rw1gdbYmFl/KDo48I+WZIvKWIEnjXRb29xjrvkZ0fgZZkHsufG6RGNRlmxYgWf/vSnef/735/y/plsfAciC9fY2MjOnTvnLFM1WyJ+In19fRw7dowlS5ZQW1ubcWXAtxJZIX/zJK9Br1y5wqZNm2Zl4W6+xHwwGGTv3r2sXLly3qpzUiFpcFdVVUVVVVXK+3/zm9/kn/7pnzh//vwd+/+ddXG6U5AVKLlLbFv+pxAcw62iHL/33LiIBzj6TWj8lfjetTBhoJfYiu+adzEiy/LsCuirGB4eJhqNXrcvz+Fw0Nvby/Dw8Ow+scUOFjtKzgKUwips8RBERyESgGA/xIOgjRI3QZNsaKqTOGqihN8gHBej9TTdJBKPixJ7AJNEmb6MS4Fcq4wiyUgyY276MT2RxdcMQnHhrh+JCdM7IUbH++8tsijZlyUJr13Cawe4NnulGSZDEQeD4XUMhe/i6bDJ10IanlA7ldGLrDEb2CRfpFQaYrnZwnK1hT/glwC0GQs5Zi7jhLGc48YyWobK+FmThG35ToJ6PV2edWPPIxka1lgAe84o3sWFDJmgKipaPD6WuZcAyRQlCVo0hmpqLMx1kue0jjnuG4YpTPhMMHQdTY/jSxyDpNDHBFWVsSkyzsSoPLdFweOQcFsVXBYFh8WO1WLH5kiMzkv220f8MNonXhDZIvrtbe7ECDxn1kwvS5Y0Y7PZ+OxnP8v/9//9fzzyyCMp92ZXVlbS1tZGS0tLRppHVVZWEggEOHLkCDt27Ji12eRJ5kLEAyxcuJCdO3dy+PBhAoEAGzduvGMv0rOkl1gsxrFjx4hEIuzatQuXyzUrj+t2u7n77rs5cOAAwJyIeU3TOHLkCIsWLcpIEQ9w6dIlVFWdkUt9MBjk05/+NF/84hfv6M+HbEY+y7Xs/Tw0/Ra6Tlw7z95ZAI83jZvm6fFbPsuYtoz8jTBNiAUhOiIEYWhAtEvoMVHObXWAxYkpW4kbwoQvrglhGteFwI9oOrG4GKcnXOONseoKVZJREm7xqizGwmnmuMCP6iahuElYm5DFF634yClk8ScS00UGPxboJddXT0mwnsroRZYYV67ps/ebTk4YNRw3lnHcXMYpo5ow9sQiw+Tn2lGmELvwIv7OFmwLF3PZsx67NopDH8WujRAb6mRxgYtH3vG26Z0opxD6mqYTTRjzxRNCP3kcrRYJhyrjssq4bDK5NoUcm4zTIieEvoSVOLIeTZTmxyab6dncYM9L9Ns7suI+y02TPTdOH8Mw2Lp1K7/zO7/DZz7zmZT3z2TjOxB/38GDB7HZbLNqfjdXIn4i8XicY8eOEQqF2LJly5w8x+1ONiM/c0ZGRjh8+DBut5u6uro5OX5zlZlPmtvF43G2bduWkRVDN2NwB/DJT36Sffv2zciw9HYiK+SzXJ94BLpOJmbZHx4ff/fB58fv87UdIv1ZPiFrPzG7fwuQDof8GQQJsVGxhX0QGhRC34iLRRXL1KXbugGaIYz4NN0UpnyaQTiuE024708q2wfRn58o25dlMAwZA4mYaY6Z7YU1IfY1HeKmiZQQtlNl8V8LVQuSF2jAPVxPrr+eBcFGrGZ00n00U6beXMxxYxknjGUcN2ropBCY8PimiaxHMVT7FM9i4rXLvG2ZlbpiIZLDmslozCTfLk3pGXBdrhL6ccMkHjeIGiaaAVrCWV+RwSpL2C0yLquCx6bgsUu4rAoOi4xb0XBKGg7CSEbCV0CZmLnPG39ds+I+Swpkz42pcfToUXbt2sXZs2eprq5Oef/jx4+j6zqbNm3KyAvKaDTKK6+8wpIlS1i+fPlNP958iPiJz3XhwgXa2tpYs2YNZWVlGXmMM5WskE8d0zRpb2/n3LlzVFZWznkf+1yI+YsXL3LlyhV27dqVkeZ2pmmOGdzV1dWlvH9DQwPr16/n0KFDrF27dg4ivHXICvks08cwIDwMroRZRtgH/1ABV2VTyS2H8i2w/HdgzTvmOciZMZ8O+bOCoQtRH00I+/CgyNgbmhiNdh1hfzXC+V6I/Lg+Pl4vHDeIaqJsXzNEVj9Zci8jo8gSJiRmvostYpiEr8niiwx6Kr34kqnjHr1MfuAi3kA93sBFHNGBa+43LHs5Ly3jhLGUfbEaTuuVxLjx3+uyQEmOTIFdJqqbnOrTkSXIt0sUu2SKXONme2VuGYdlZidUwxCLIzHNIGZANCH0dXO8qEAY68nYVYk8h0yeXcWl6LjkOA4phkvRcaiSMPCblLl3TsjcZy/MslxL9tyYOh/+8Ie5cuUK//3f/53yhXQ0GuWll14aE5qZiN/vZ9++fWzYsIGSkpIZP858iviJdHd3c/r0abxeL2vXrsVun2rBNsvVZIV8aoTDYU6fPo3f72ft2rUUFxfPy/POppjv7Ozk1KlT3HPPPRn7+d/e3s6FCxe47777Ul5oME2Thx9+mJUrV/KlL31pjiK8dcgK+Sw3R6AbrrwK7YfF1+4zYCZmmK39H/DWr4nvDR32/7MYf7doI9gyr0RuPhzy5wxduzZjHw+J3ytqQtg7XlP4GYZJc0szI4ER3G435RUVGKZEPCHok2X70bhJNK6jmeL3+oT+fDHlXUZnXOhHDXOsF18zkr34QtCqiSz+jRz17ZF+vCMNeAMX8QYu4hltQU7+nyUPgaTS76iiwazgrFHBGXkFV+RSBkMGgxGucdx/LeqKFGoLFQocMqG4SXtAH3PWX+iScc1Q5IM4zjHdIBo3hdDXDKK6mbAglMSihyJht0i4FZ08i4bHopMja9hVcNitOO12LE4PFldBQtg7xkfhZbmjyZ4bU2dwcJBly5bxb//2b7z5zW9Oef+uri5Onz7N7t27M1ZkdnV1ceLEiRmXsqZLxCeJxWKcPXuW3t7ebHZ+mmSF/PQwTZMrV65w9uxZSkpKWL169bxnsmdDzA8ODnLo0KGbXrCbS8LhMHv27GH9+vUzivHZZ5/l0UcfpaGhgby8vNkP8BYjK+Tnkbl2X88IoqPQeVyU4S/aADUPiN93n4Gv3yO+lxQoXp0ox98ivs7C6LvZOL63zWv0msL+2ozu6TNneOY/nuHy5cvE4jGsFiuVlZU88s5HWHvXXdc8hWEg+vMNA00zxVfdJBLXCcd04vq1/fmaYaIbEqYkYyTK0GOGRFQfz+LrmEimKOufODZPlcdL9WU9Su7opYSwFwLfFvdfE2PYWoDPs4wh93I6Hctolivpi1rHXfdDBv0hg+Go8ABIBYsMuTaJQqfEA0ssLMtXRKWCad70xWVcM4noBjHNJKpDTDPRTdH8oMpgRccu6eQocTxKnBybhMum4rTbcThzcLjzsTjdqDYnVrsLyeJI+/SJLPPHrXZuzBS++c1v8sQTT3DhwoUZ9bsfPXoU0zQztsQehJN9Q0MDO3bswO12T3u/dIv4iWSz89MnK+Rfm2QW3ufzsW7dunnLwk/FzYj5QCDA/v37Wbly5YzM4+aDZEm9xWJhw4YNKe8fDAZZsWIF/+f//B/e9773zUGEtx5ZIT9PTJXtXblyJY899ljmZ3tng97zsP//CYHvv3Lt7Q9+Fu7+M/G9HgeklHqC7/jj+1pcT9gbGsgK5xpb+dK/foMh/wiFhYXYbDai0SgDgwN43B4++rGPTinmb/iU1+nPj2o64bgxJvR13UQzxfcxXcI0hfVdzICoDpopTTCZA8lMlOdPyOKrEjgjPXgDDeQFLuIdacQ9ehkZY1JMhqQQcFXi8yzH517GsGc5IXsxBhCImgxFTIYmjNQbiojvB8Lmawp9CSHsFQkCMZMcq3D5L3KJMv3KXJmSHBnrVDPqU0AzTOIaRJNCP7FYYuo6FjOGShybqeGwGLgtCja7FYfdidOTR06OB7szB6vdhcXhwqqqWBV5bGxfltuDW+ncmEkkje9e//rX8+lPfzrl/W+FEnuACxcu0NHRwT333DOtBYtMEvFJYrEYZ86coa+vL5udvwFZIX99kln4c+fOUVRUxJo1azKin3wmYj4UCrFv3z6WLFnCihUr5iHKmXEzJfWQNbibiqyQnweS/ddDQ0OUlJRkfv/1XOPvnFyO33MW3vNTqN4tbr/wc/iv/wVlG0WvffkWUZJvn/o1zh7fGTBB2BvBIf7Pp/6CjpYGykuLMSSJqKEQNWTihkRHRwcrVqzgs3//2VkVfEmHfU0fz+bHNFG6H47rYyI/pon+8pgBui6hmSZxQyKmS2J0HBJ6ovFcYrxU325GKAg1UzDakBD4DdjjvmviiKlufJ5lDLuX4UtsmmXyhaphmozEhOv+UNikN6jTNWrSHzLxR4X533RL9xflSJTkyOQ7ZDBNFBmW5CpU5Qrn+5s9ppqRGDOoGUR1HSMex9TjyEYMBQ1VlrFZFBx2K1ZHDha7B6fLRY4rB7fbjc1mx6LIWBUZqypjUSRU5RasSrmDuVXOjZnIzRrfdXV1cerUKe67776MzRSbpsmpU6cYHh5mx44dN7ygzkQRP5Guri7OnDmTzc5fh6yQn5pMysJPRSpiPhqNsn//fgoLC7nrrrsyVuAmS+rr6upmdLyzBndTkxXyc0zSEf3EiRMsXbo0Mx3R0010FBSrGMcF8Nu/gwNfvOpOknDML98Md38EvBVA9vjOBmfPnuUD73svJQUeCj12XIqGR41jk3VUySQcjjAQCPEXf/23LF1eO29xxQ0TTTPGBH/SiC+SEPvxhPt+W1cvgWAEq92B21tAT/8Qo+EYVrsdb36h+J+QJBRMPFo/RcEmFow2kD/aSO5oC4oZv+a5Rx2lQtR7hLAPuCow5etfBCWF/lDYpCdo0B7Q6Q2Kn0diojx+Oh+0EmBTIMcqkWeXWF2oUOwSoj/fIeFQZ36C1g2TuAGabqJrMWJxDUOLYeoawrBARlJVLFYrFlsOVnsOFrsdm92Fw+HE47DgtluwqkLkWxQZS0LoWxU5Yy8e7kRuhXNjJvPHf/zHdHV18dxzz81o/2PHjqHrOps3b87Y94VhGBw9epRYLMb27dtRFOWa+2S6iE8SjUY5e/YsfX193HXXXSxatChjj/t8kxXyk8nULPxUTEfMa5rGwYMHsdvtGd3Sc7Mu9UmDuxUrVvDlL395DiK8dcnOM5pjzp8/T319PSUlJde8wSRJori4mAsXLnD+/Pn5m1GeaVxtfHf/38Ka35uQtT8MvjboPSe27X82dtf2336djbFDeJcX0mWaaOb4Mc4e3+kxPDxMOBrDsOYwGFcYjNuQMbHJOg5Fx46NUDRAeLgXfB7hiq/aRZ+9ap+z3muLLGGxXntxCcL5/eTp0zz37E9pbb9CXDNE+b1uotqdyBYbss1FQXEpG7Zsp3hRGZG4iV/OZzhnK+ddWzGLJFQ0FkTaWBhqZGGwiYJgI+5INznhLnLCXZT1vQwII71AThU+dw1+9zJ87hqCjhKQxOKQLEnk2iRybVCZp7BtkeWqeIWg7xoxCGkkSvgNLg7qDEWEwAYh9iM6RMImA2GTS8OTWwNkCRwqeKwSBQ6JYpdCmUe47Oc7ZHIs158GoMhiJB6qBLbJWSvdMNF1DT0eQ9c1tNEBRgP9GAYYigqSBcNiR7I4sFjtWGx2VIsDm82C3aLisCi47RacVhmHVRUiX5GwTBD9KY34y5IljTzxxBMsW7aM//zP/+Stb31ryvuvWbOGPXv20NnZmbEl9rIss2HDBg4dOsSxY8fYtGnTpMXuW0XEA9hsNjZu3DhmONjZ2UltbW1KHgBZbn8CgQDnz5/H7/fP2GhtPnG73dx9990cOHAA4Boxn1yMS76XM1XEA1y5cgW/38/u3btntP8zzzzD6dOneeaZZ2Y5slufrJCfY4aHh4lGo9ftQ3M4HPT29jI8PDzPkWUwcsIMr3g1bPpD8buRHrhyBLpPj2XjAVyXfsbHVw8BQ8SMJi6F3NSPerg46uFi0IOePb6vidfrxWazEQ6Hxy7WDCTChkrYUBkdjeMfcSNX3A3lSyASgOCAmGMfGhJpZNUOqgMs9jFxO5ecOXuGf/nSlwgEAhQWFhKLxWhpaSEai2Kz2qioqsRmRBk8f5mDV87xh//zj6lZvoKYZhCM6gSiOhHNJBxXiTiqaHFXcE57CN2QsGgjLAheojh8iYXhSywINWHXRvCONOIdaQR+AUBcdeHLWYrfXYMvsUVtBVPGK0kSHpuExzb1sTEMg4EwNPt0rgQMeoMG/qjJQpfMUNhkKGIQjAtDvmAcgnGT7qDJuYHJQt8qg9ch4VRFRr/UJbHApZBvl8h3iMUGeYqTvRD5Frg6Y2PqmHocI64R1/zo4WG0oIQmKcQkCwHZimlxiIoaxYpisaFY7FgsCqosYbPIOCwKTouCzaLgtCo4LApWizKWybeMbVJGX4hkuXMoKCjgS1/6Ev/rf/0vdu7cSUHB1O/r62Gz2bjrrrs4deoU+fn5OJ3OOYr05lBVlS1btrB//35OnjxJXV0dkiTdUiJ+IqWlpRQUFNDQ0MDLL79MWVkZK1asmJFxYZbbh1AoxMWLF+ns7KSiooINGzZkbBb+aq4n5g3D4Pjx40QiEXbs2DFlRU2mEAwGOXv27IyPe29vL48++ihf+9rXsi71U5AtrZ9jzp49y/ve9z7y8vKmPBmOjo7i8/n4/ve/n80Yz4DOn32Wpue/ytqCGF6rNum2uCHxhv1r6R8OiONbsQBcC8RCQZYxku0JJ0+epLq6enrtCaYpzPKiCQO90ID4Ph4Wt6nW8ZFo8uyuFxqGyac+9SkuXrxIWbnIdjU0NDA6OordbicSiZCTk8Py5csBpuzxN03G+vInjtYTIt9gNKoTiRuENYORqI413It39BILgpdYGG5mQfgyqhm7JraINV9k7XOW4nMvxe9eStwyO59NTUM6l3w6XSMG/SETX3Rc3E8XCXBZoNglUeBQyHdICZEv47WL7y2vZcZnmkimjqTHMPUYhq4JfwNDQpMtxLFiKnZ0iwNkC5Jqw5QtKKoVRZVQJQlFkUSvvirjUBWsFhlVSYh+q4LdomSz+jfBrXBuzHRM0+Qtb3kLLpeLH/7whzN6jFOnTjEyMsLdd9+d0a1dkUiEAwcO4PV6WbduHRcuXLjlRPzVjI6OcvHiRXp6eqisrKSmpuaWEW+zyZ1cWh+NRmlsbKS1tZXS0lJWrFiBy+VKd1gzYmKZ/fLlyzl58iSBQIC7774bmy1zR84ahsG+ffvwer3claJhMojP4Xe84x0oipLNxl+HrJCfY2YkkrJMm/Hje4J7ahexMifAypwAK3ICBDWVdzyfM358v7EThi6LsXhjJnobwOFN95+RdpKGgcPDwxQXF8/MMDAeFln62CgEByEaSAh7XYy5Ux3TmmX/WjRdusTf/e3f4Xa7cTgdBEeDNDY2oqoqsiyj6zq6rrNs2TJcOS7CoTAjIyN85u8/Q83SpdN6jquFflzXCcYMgjEh7IPhKIq/FYevidyRSxSEmsmPtCNP0QkftBXhcy8lkBD2/pylaOrsZOhEyT4EYgZFTpnhiHDa/1ljlK6gML5LFacK+Q6JBU55TOTn24UDf4FDxqFep3zf1JEMDVmPgxEDPdHugIKGhbhsJSo70GUbKBYk1QqKDUmWUWQZVZFQ5YSfgQQWRUaVJayWRMZeFuZ7TquCTZVobWkmOOKn0JvH6lW12CxKtlc/wa1wbrwV6O7uZtWqVXz729+eUYm9pmns3buX4uJiamvnz19kJkQiEfbv348sy8RiMXbs2HHLiviJ+Hw+6uvrGRoaoqamhqqqKlT1zilGvROFvKZpNDc3c+nSJQoKCli5ciW5ubnpDuumGRkZYf/+/WPCPdNFPMC5c+cYGBjgnnvumVHVwNNPP82f/dmfcf78eRYsWDAHEd763DmfZmlClmUee+wxHn/8cZqbm6cUSY8++mhWxM+Qicd334UumoqL+a1jAeFwmIHe7vHja8TB1y5E5uVXxJZkwQpY+Sa472/mNfZMmlm/fft2Pv/5z4+N8Ovt7cVms1FXV8ejjz46Pdf/ZAbeVSjaH7TY5JF34WFRiq/HRZ998v6KLaU++5HACLF4bOwEpmkahmEgJbK1siITj8fRNFGhYbPZGBwaZCQwMu3nkCSEa/vYeUelcMLtQugXoOl1olw/btAcCsJAE/JAI3ZfI55AE+5oD65oL65oL4sGDozt77eVMuSqxu9eyqhnKaPuKvQZiHtRsg8emwh0oUtioQtWbHNimibBOPSHDPpCBv0hg65R0Y+/qURlKGwwHDE50q0R08cfM6RBaMSkY0Sf8jltMnjtUOBUEuJewmuXE99b8FitKPK4ALAYGjYjjmREQA8gayamJqHFVTTTQlS2oSkuYpKVsKRiyBZQbKiJDLw8JuplJBmampr47W9+Q2fHFbR4BKuqUl62iLe8+c2sXbMah0XBYZVxWFQsqjRWum9VxGKBJevAn2WalJSU8C//8i98+MMf5p577qGwsPC1d5qAqqps3LiRvXv3UlhYyMKFC+co0pvHZrNRWFhIe3s7xcXFt2zm8mry8vLYtm0b/f39XLhwgZaWFpYvX86SJUuy1123GYZh0NraSmNjI06nky1btqT8ns1kXC4XXq+Xvr4+KioqMr7CpKenh7a2Nnbt2jUjEd/b28tjjz3Gk08+mRXxNyCbkZ8npppzXltbO32RlOWGTOv4Gjr01QsTvStHoeMIDLWI29b8Hrz9W4n7GfDMe6H4LijfBIs2Xnf03WzGmwlz7+d0cUHXIB4UWfuIPzHLPgxaRChnxTZuoHeD9of5yMjfLKYpRsFFRn1ofY2Y/RdRBhuxDzdii/Rfe38khq2l9DmqGHZV48+pZtRdiWJzYpGVObUdONWr0RMUQr83aNIfMhhNGPnnWGCpVxkz5xu91uD/GmQJ8mwigy9K98fL9pMl/HYFJFND0uNIRgzJ0MA0MZFAUTEkCzHZSVxxEJOsaJKVOAot7Z0899//TXh0FI8nB6uqEotGCAwP4nI5ee97382KmhUgiTYCRREjCccy/oqMRZZwWJVEZl9JjNgTt98uJfy30rkx0zFNk7e+9a04HA5+9KMfzegx2traqK+v5957783I8WgTe+I3btzIyZMn8Xq9Yz3ztwumadLd3c2FCxcA0W9cWlp6W/2NV3MnZORN06Szs5P6+npkWaa2tpbi4uLb6nU1DIMTJ04QCARYu3YtR48eTWnO/HwTDod5+eWXWbNmzYwMP03T5O1vfzsWi4X/+I//mIMIbx+yQn4eyaQM7O3IjI7vaD90HBVZ5PLN4nd99fDVrRPuJMHC2sRc+81QcQ94l8w4zuzc+wSGIfrsk+X4oUHRZ68l+uwVdcpy/LEe+YaLYyeIVHvk00rYh9nfgNZ7EbO/AXmwETU8cM3dTCR8thL67FX02asYcFQw7KoCSw42i4RNBlWVUSV51oV+VBOu+XHDpCJXLKqYpslnD4bpC5pTjtJTJOG6P52efacK3gkl+2Mi32ZSYNXJtegoZhxJFysHpiRhyio/e+6XNHf24cwrIi5ZiJkqUVMljsLA4DBlixbxrne/O5F9F+LcnuixlyQJKSHwkUAykz+YgISqitL+iSX8dosy5bg9iyxnxv/SdbjVzo2ZTk9PD6tWreKb3/wmb3vb21Le3zRNTpw4QSQSYfv27Rl14T2VsV2yZz43N5e6urrb7jrFMAza29tpaGjAZrNRU1NDSUnJbfd3wu0t5A3DoKuri0uXLhGNRlmxYgXl5eW33euYNLYbHR1l+/bt2Gy2lObMzzeGYXDw4EFcLhfr16+f0WP86Ec/4iMf+Ui2pH4aZIV8lixXM9oP538qXPI7joiS/Ins/IvxMvyIHzqPi757+2v3YGXn3r8G8ci4sA8Pi+MbD08ux1ftnL7QyBe/+CUCIwEKCwqJxqJcbrk85lpfWVWJzWpjYHAAj9vDRz/2UdbOwGhl3ggNwUCj2PobMPsbkELXinuAEXsJA45Keu2V9Nkr6bNVElHdqDKoMlilRF+5LInSdFlCGVOwN49mmAyFTfrDBgMhkcEfCJsUOiTettxKIGoyGDb48rEo2gzPLrIEXptw3s93SHhtYIkFaDpxgDwlSp4SwWJqGIBmKmimhD9iMBSM8c53v58FpUuISyoaFjRDxJw81cmyMNpTZZGBt1tl7KoCEshC4QMik6+b44sWMhKqIrL7FlnGZpVwWFScVuWajH66Xfiz58bZ50c/+hEf/ehHOX/+/IzKdePxOK+88grl5eVji4zp5kbu9NFodNJ86tuxr1zTNFpbW2lpEZV5lZWVLFmyJONLllPhdhTy0WiUtrY2Ll++jCzLVFVVUVFRkdHO7TMlHo9z9OhRYrEY27Ztm9QTn6livr6+nu7ubnbu3Dmjz43kwuk3vvEN3v72t89BhLcXWSGfJctrMdIrsvYdR0RJ/q6/gOr7xG0Nv4Qf/T4giV77ZNa+bBMULhficwLZKQYpomtC1MdDYuxdaFB8r8eor6/n57/4FU2tHYxE4sTiBnEtjkW1oKgKVouVyqpKHnnkkcwW8dcjNAQDTTDQkPjaCKO9U941al9AIKeKIWclvfYqemwVDEtekl3uEiaqBKpsYpXlsf5zRQZFEtnl2bwG0A2Tw90ag6FxwT8QFi77AMvyZe5fYhHmfGGDF9q0lNz3ARQjhs0IY9dDOIwgDj2IFOpn+13LqSlfgNehIisWDNWJaXFiKDZMxSqM91DRkdB0E80wMUwh9CUkZIUxoW9ThZO+zaIgy6BIEqYp1kTMxN8pxL4Q/4oksvpJV/6J/frJ/nyrImNRxe1zJfaz58bZJ1nqabVaefrpp2f0GH6/n3379rF169a09+5OZ8RcPB7nyJEj6LrO1q1bbyuBO5FkyX1LSws+n4+ysjKqqqpui/fO7STkA4EAzc3NdHR0kJ+fT1VV1W1XQj+RaDTKoUOHsFqtbNq0acrXL9PEfF9fH0eOHGHnzp0zev+Ypsnb3vY2bDbbjD9n7zSyQj5Llpvh3E/hxc/AcOu1t9k88Hv/BksfED+bJnv37ePDH/7wdVePdV2ntbWVJ598kp07d85t7LciybF3sRDERjGCA7Q2nCPoH8Cd46SsfDHtXf34gzFy8vKprl6a0SXQKRPxJ0R9QtgPNoG/Y8q7GlYPkbxqRtzVDDmq6HdUMmQtJqRLRGIGmm4k5KeJDMiyKbL6CWGvJozmZFmatfL9UFwIelmCMrf4/w/HTf7PoTC+yNQl+8UuiWX5Cr3+CK39AaLWPKYTjAR4rCb5NpN8m4HXauK1mQkXfpXcHDsupwtUO4ZiwZStGLIFHQXNEAJfN8zEcTIxTZAlUeUwsWzfMTYqTxal+5K4n2GCphviMZKnWdMU/fqyNNaz77Ao2C0yeU4rRZ7Z6Z/Onhvnht7eXlavXs3nP/953v/+98/oMS5fvkxDQwO7du1K23zzVObE67rO8ePHGRkZYdu2bTidszNxI1Px+/20tLTQ0dGB1+tlyZIllJaW3rLZ3ltdyGuaRldXF21tbfh8PsrLy6msrLwtXOhvRDAY5NChQ+Tl5b1me0umiPlQKMQrr7xCbW0tS5bMrP30m9/8Jp/61Kc4d+5c2hc7bxWyQj5LltlgtA86jomsfccxUW4fD8Fjx6CwRtzn1a8R3f8Vflvv41LES2u8kNawC53xD+hsRl6Qkt+BFptgoheA8FDCRC8qbletwkBvDmbaZwSxURhsHhf4g01iYcm8dvacqdjQvVXEvEuJeKrxuyrot1UQMKxENINI3CCqmcQNg7iuIyMhSSayYSLJphgPh8hMK7KMLDFr5fvxRMn+wIQM/kDIpNqr8ECFBdM0+eGzP+Ng7oNTP4BpYDWj5LqcDEfMaZX1q5IQ+l6bidcu4bXJ5DlV8lz2xObAZreBYsWULBiQEPcJkW8YibJ9ADOx6CGhJErr7RYFu5rsrRcl+bIESOOGiJpuEIrrLHTb2FiRP/MDOIHsuXHu+NWvfsXv/d7vcfToUVasWJHy/qZpcvr0aXw+Hzt27Jj3kvVURPzEfc6cOUNPTw/btm27I/6notEoHR0dtLa2Eo1GKSsro6Ki4pb7229VIe/3+2ltbaWjowOHw8GSJUsoLy+/batCJuL3+zl06BCLFi1i9erV0xLm6Rbzmqaxb98+CgoKZjQvHkTF6tatW/n5z3/O/fffP8sR3r5khXyWLHOBrkHfBShaPV5e/+yH4NxPJt0tashcCubQEPTw4+4yTjW239k98ry2o7+mafzsZz+jq6uL0tJSfvd3f3fyxXDSRC9ppBcaguhIYqa9BpICFrsQ96o9pdF3twxaFIYvw8AlIewHmsSEBi0yxZ0lzNwyjPylxL3VRHOrCHqqCale/DGTkahOJA5R3SAWN9BNk5hmYpg6mCDJJjImkmkmLh5MJJKl+7Nbvt/c2s6zBy4SwobpLCBmcRNJuNsjSWzwhvnQpkIM06QvKMz5klgVsCTeUpoB0amn612DXTH5/9u79/Am6/v/488kbXpu0wM9UdpCOUMpcqYwTiLIVGCepqLi2SmgyJyn73Q6Dzh1zt8QAZ2Tbeh0uimCqBzkIOfzsVDOLaUnSs9tDk1y//64m7SBlkObNj28H9d1X22SO8knNyXJ635/DqE+qEvs+Xth8Ndj8NcTEuCLwd+PkEA/9NVfkO3OSr7dWdW32hQcE+pptbiMz/fx1uKn11FhthIWoGd0D/csTyafjU3rueeeY8WKFWzbtq1BVXW73c6mTZvw8/Nj4MCBzfaluyEhvvZ9jx49yokTJxg6dCjh4eFN2NKWQ1EUCgsLycjIIDs7m+DgYGJjY4mOjr6q4+cprSXIK4pCeXk5ubm5ZGdnU1ZWRseOHUlISCA0NNTjXcabS0FBAdu2baNbt25069btql63p8K8oijs2LGDqqoqhg8f3qDvrhUVFQwaNIjbbruNP/7xj03QyrZLgrwQzaWyEM7u5syW/3F2+1J6B1cQrFf/+9kUGPTfaPyCw9VZ632Pq/vHDYLYa0DfNtb0vZzLzeg/cuRIvvjiC/Lz87Hb7Wi1WiIjI3nhhRd49NFH639gZ9W+Ug31lYVgrVQn1wN1VnwvXzXg69roGX+7DUrPwvnj1cG+uopvLKp7f18DhCehhCVRZeiCxZCEKbATFrwxW+1UVCmUWRRMVXaMVjvmKqV6zLgdRVGw2xUUxY5agFZAgepO6mjQoNNo0ek06ACtTq3oa6+gqn8mM5OtW7dRcO4cVpsVL50XYZFR9Og/lE5xsYT7qV8izlXa+WivmQKjvc7Q/os4L67r7E2hUSG30s6yYxb01cvVWRV15v4rDfuB3mDw1anVfD9vDP4+GAJ9Mfj7qqHfzxsvndZZxbc5u+2rYb/MXEV0sA/ThiVe2RNehnw2Nq2qqipGjx5NSkoKCxYsaNBjmM1m1q9fT2JiIt27d3dzCy/WmBBf2+nTpzl48CApKSl06tTJza1s2aqqqjh79iw5OTkUFBTg7+9PdHQ00dHRhIaGtsiT7y05yNvtdgoLC8nNzSU3Nxej0UiHDh2Ijo6mY8eOLa69TS0zM5P9+/eTnJzc4K7pngjzR44c4cyZM4wePbrBPSYeeOABTpw4wZo1a9rkxJpNSYK8EB6wefNm5r8/j8oz++kZWE7HYA1bvEbUrHv/4VjI3q3urNGqy991HKgG+46DILJXm6skX25G/507d3L+/Hm0Wi3+/v54eXlhtVqprKxEr9fzzjvvXDrM16YoaoXeUqEGfGOxOv7calJnyIdaVXufttkl36HyvBruz5+o+Vlyps6u+Wh06tKLYUlqyA/tTFVoEhZ9KBY7WGxgsSlUWNSgb7KCyVrTXd/m6Iau2EFRsNvVn2jVarbNOePdxVV9rUYN/xqt+vdwLj+fSqMRfz8/OkRG1vuFRVEUKqpwdtU/b7Rz3qjQK0LHNVHqv2tmqY0/ba2rt4Kqf6SOPh10FJkUCirtZJTYMdvUx62q4zDVJchHi8HPC4OfHkOAvjrkexPs50VObh6BGjO3XRPjlmVJ5bOx6WVkZHDNNdewcOFCbr/99gY9hmPyu4EDBxITE+PmFtZwV4h3yMvLY+fOnSQmJtK7d+92Uy2tzWq1kp+fT25uLnl5eSiKQlRUFDExMXTo0KHFhNCWFuSrqqpcjptWqyUqKoro6Gg6dOjQLkOc3W4nLS2NzMxMBg0aRGRk43pmNWeYz87OZs+ePfziF79o8GfNv/71L5566in27dtHx44d3dzCtk+CvBAecslx4FsXQMZmdax96VnXOwbHwZxDNZczt4EhHoKb7otgc7jUjP52u501a9ZgsVgwGAwuX0gURaGkpISYmBiOHz/e8C8CNmtN1d5SAcbzYK5U17W320Crcw337l68vSVxdM13BvwTagXfUlH3/r4GCO8CoV0gPAnCOkNoIlatDxab4gz4ZpuCqUqhosqOsQosdrWbvtmmVvLtNrV7vpaaqr5dsaEoGmz26svUdFV311h9k1Uho8TOeaO6lF7tn2UWuLm7nmsT1b+5ukJ/gDcEemvw8dIQ7qvBW6tQbLJTaFIoMoHtChqkMZVgWP+2yzCShpLPxubxzTffMH36dHbv3k1SUlKDHsMdX4Qvxd0h3qGsrIxt27YRGBjIwIEDW0RI9BRFUSgqKiInJ4e8vDzKy8uJiIhwVus9OUFgSwjylZWVzqp7QUEBgYGBLj0Z2uOJIIeqqip27txJZWUlQ4cOdev/z6YO8+44EZmens6gQYP4/PPPueGGG9zcwvbBo0F+w4YNvP322+zatYucnBy+/vprpk6desX3ly8rrddVTWbW3pXmwNmdNZPoGeJh6gfqbYoCb3VRJ3gLioW4gWrlvuNAtUu+T5Bn234VNmzYUO+M/jk5OezZswdFUS4K8gAWiwWTycSSJUvcu+6o1Vxdta9e/s5YpAb7KhOg1HTJ96rukt+Wv5AoClTk11TuC6uDfunZeqr3WgjuqIb6sC41W1AMaHXYFTXgm20KVdVh39Flv8KiUGVXqLKpYd9qd3TVV9BoQauoY/IVxe4ch25DuaCqr64G39gZ+M1WdTZ9Xy/13/ZsmZ3vTlicQd9kdd3/V931jK8O/WeqQ3+wj4YgPfh7afDW2kGBikoj50tKsWj9sHgFElRVQPiefzqHkbzzzjsNDvPy2dh8nnzySTZt2sSmTZtc1ni+Gu7omlqXpgrxDk0VQlq7iooKZ3A9f/48/v7+GAwGQkJCMBgMdX6GNZXmDvIWi4WSkhKKi4spLi6mpKSEyspKwsPDneE9IKB9DBW8nKY+GdaUYd4dQ4OMRiPDhg1jwoQJvP32225rW3vj0T4sFRUVpKSk8MADD3DzzTd7simiGV1uMjNxgeAYCL4Jet108W3GIjUYmYqhLBsOZ8PhZdU3aqD/NJg6v2Z/mxV0LbPrWmhoKD4+PhiNxou+EJpMJjXEaeped9vLywu73U52drZ7G+Xlo26EQQg1XfIdE+mZStRjbyoFm0W9j85bnSHfy6dtjbfXaCAwSt0Sav0/tZrUWfLPn1Qn1Cs8qVbvTSVqF/2SM3BqQ83+Oh8IS0Qb2gXfsM74hnWG0M4QGK523a+mVvLVraq6ol9pVbvtm6xUB30FL0U9j2BTFLQadSk9dc49Oyh2quxgsdqw2aHKasdos2HHjqNsr60O+/VNzOfj5fr31jFIyyP91WXiFEWh0opawa9UKDQp9AirOUtw3qieBCgxK5SYAZcF9vzoULyfvpxF6+2D1a5QGRhIUlISJ06cYP78+QwbNkxOcLZwb731FqmpqTz33HP85S9/adBj9OjRg9LSUnbs2MGwYcPcstRZU4d4AG9vb4YOHUpaWhobNmxwS7fgtiAgIICkpCSSkpKwWCwUFRVRXFxMUVERp06dwmg0EhAQ4Az2jp+tbUZ2i8XiEtiLi4uprKzEz8/PecLCMVlde+6xURfH8JTOnTs3WcU8KCiIESNGsGnTJgC3PY/NZmP79u2EhYXRrVu3Bj/Ob3/7W/z8/Hj99dcb3ab2zKPf6CdNmsSkSZOueH+z2YzZbHZeLi0tbYpmiSZU32Rme/bs4emnn25UFapd8g+DxzeDuRxy9qmV+7O74OxuNUAF1FqH01gEf+4FMf0gdkB15X6AWiVtAZXkPn360KtXL/bs2UNSUpLLB46j0qXT6ersOm+1WtFqtcTGxjZtIzUa0Purm+PY2m3Vs+RXj7k3FqkT6hmLa8bbO04IePmqQb8t8fKFDj3VzUFR1F4ihadqhfuTauC3meFcurrV5hOkBvrqYK8P64w+NBH8Ll4v2GZXqLKr1XxH2DdbFSqqFCqd1XwdVXYFbx14VR9yNRKr69hrUNAAFqudKquCxaaGfbPdimKnzi78Gg1q2Ndq0VWfVArwhgBvHfF1FL5TInXMHe3vHJfv+JlTYiKrsIJgXRUauzrBnk5RS/sajYbo6GjS0tI4dOhQu16GsjXw8fHhiy++YODAgaSmpnLbbbdd9WNoNBoGDBjApk2b2L17N4MGDWrUF+7mCPEOWq2Wvn37EhwczPbt2+nevftVz7bdlun1eqKiooiKinJeZzabncG3drivXbn39/fH19cXHx8ffH19PRKEFUXBarViMpkwm82YTCYqKytdKu3+/v7OExEJCQmEhIQ0uGdKe+BY/eHYsWP079+fuLi4Jn0+d4d5x3xFiqLQv3//Bj/Wp59+yr///W/27NnT6k5gtTQtszRXj7lz5/LKK694uhmigex2O++//z6FhYUuk5kFShWq8XwCIXGEujmU5bruk71H7RZ+Zpu6Ofga1EA/+CHo6bkxSlqtlpkzZ/L0009z4sQJoqOjnSd6ysvL8fb2xm63OyvzDoqiUFlZSUxMDFOmTPFAw3VqCHUOY+hcM97eJdyXqxPL2aunQvfyqRlz39Ym09NowD9c3eIG1Vxvt0FptmuwLzypds83l0HufnWrzS8MwhLVkB+qjr3XhSWi0wc6u7vXpihqyK9dyXdU841VdoxVWizV1XybAuh06HXgp1En1NOiDhPQaBUUO1ht9uqu/zasVkVdus5qre7CrwZ9wDkLvxbX8frBPhDso6OzoaaNp0/nsGzntxgMoagLy1/wkv38yMvLo6ionhUFRIvStWtXlixZwl133UXXrl255pprrvoxvLy8GDZsGD///DMHDhwgOTm5QV+SmzPE1xYfH09QUJBzUtIBAwZIoKuHj48PkZGRLr0Xaof7kpIScnNzneHZbrej0+nw9fV1bo6AX/uyVqtFq9U6e65pNBpsNvXzxmKxYLPZUBSlev4RO3a73SWkO7bal202G1qt1vk8fn5+hIaGkpiY2Cp7EXiSyWRi165dGI1GRo4cicFgaJbndVeYVxSFffv2UV5ezi9+8YsGz0e0Y8cOHnnkEb766isSExMb9BiiRouZ7E6j0Vx2jHxdFflOnTrJOMBW4lKTmQGUl5dTXFzMP//5T6lCNQW7Xe3yfHa3WrXP3g05+9UKKcBN/w8G3qf+nncI1r6hBvzYAep4ez9DszSzrqEXvXv3pmPHjixYsACLxdL4Wes9wVZVM97eUqlWrC0V1TPlW1EXGa9VuW9r4f5SrGYozlQn2Cs8pQb8olMXn4yqLSBCDfaGBDXoGxLVGfUvMy+EY2x+Tdd9sNjsVFapFX1Ldbd9q7066KNmbS8t6NCAproLvwJ21KBvtStqZd9mr2O8vhr2NbW68J8vOMeypd/gq/dB7+ONzkuP3VZFWb76ehv7Xihj5D1j7ty5LFiwgB07drhUYK9GZWUlGzZsoEuXLlc99tRTIb62qqoq9u7dy/nz5xk0aBARERGXv5Ool6IoVFVV1Rmya182m83OE92X+1rvCPlardblhEBdJwccvQGkh0Xj5Ofns3v3bjp06EC/fv080sOisWPmjxw5QkZGBqNGjcLPz69BbcjJyWHQoEHMmTOH3/72tw16DOGqVX1T9PHxkTO8rVhRURFms7neNwCpQjUxrRYiuqlbyq/V66wWyD+khvsuY2v2zdwCR5arm0NYUk2w7z0ZQpqmS1hqairDhg2rczLEpKQk3njjDZd15GNiYnj++edbdogHtUu9n8H1hIhjffsqI5grwFRUPfa+AOxWtbLt7dv2w72XT83fZm2WSijOcA33RaegoqBmy9rheh//CDXQhyaqIT80Ub3sq3bR12o0+HpxQTW/Zkyy1a64zLRvsSmYrAqVVepmtUOVTUNV9aR6Cjq0WvD3Ay+tBh2OkSp2FLsGm6KoYd9mr57Yz05ERARhHaLIy8snxC8AjdbLOQxDURRyc3MZMGAAffr0ceNBFk3tueeeY//+/dxyyy389NNPDapW+vv7M3z4cDZu3IiPj88VryfdEkI8qOPmBw0aREZGBlu3bqVr16706NFDgmADaTQa9Ho9er3+ik/KOcK8oihYLBZWrlzJxIkT0ev19c4zI5qG3W7nyJEjnDx5kuTkZOLj4z12/BtTmT916hQnT55k5MiRDQ7xJpOJX/3qV4wfP545c+Y06DHExdrot0LREl1qMjNQZ7D08fEhNDTUA61rp7z0arU99oKuoImjYMJrasDP3l3dBbp6CbIDX0JUn5ogn7UTcvaqjxHVt3pyuMbRarV1ViIfffRRHnzwQZYuXUp2djaxsbFMmTKl9a4966VXN79af/NWc82Y+9rh3lzg2i2/rY65r03vD5G91K02c1mtCv5pNew7An5l9XZ2l+t9fA1qoDckuP70j3CZI8KrepZ7/zoOa33d9k3W6iX1HNV8K1jtGlBAQYNOq8Nb74WfFry16pj4G0cN5osvv6Isu5Cw8Ai0GrUS75i1fsaMGTLEqJXRaDR8/PHHjBo1iscff5yPPvqoQV/aQ0JCGDp0KFu3bkWv1192aaeWEuIdNBoNiYmJhIaGunS1b2gAEFendlh3fDbqdDp5P2lmRqORnTt3UlVVxahRo1pE76iGhPns7GwOHTpEampqg1+Doig88sgjACxatEhOJrlRK/32K1qjS01mJlWoFqZDd3VzqCxUA/3ZPerP2P41tx36Gra8r/6u9VZDfscBNScIOvRy60z5Xl5e7l1irqVxhHSXcG+pCfdVlbXG3BeqlXuotRSeT9tfCs8nSP07i7rgvcJSDkUZ6lZ8uvpnhtpF31QMOcXqpJC1efurSzoaEiA0vub34NiLekBoNBr0OtDr6j62jm77VY7Z9qtDv7F6tn2zFYxWtdu+oWMXJk69nU0bN1FSmI+tvJDi4mIGDBjAjBkzZNLPVsrf359vvvmGQYMG8f777zNr1qwGPU5ERAQDBgxg165dDB8+nPDw8Dr3a2khvraQkBBGjx7N/v37Wbt2Lf369aNjx47yJV60aYqicObMGQ4ePEhMTAzJycktqthwNWG+oKDAOQFnWFhYg5/z3XffZc2aNezcuRNfX98GP464mEfHyJeXl3P8+HEArrnmGt59913Gjh1LWFgY8fHxl72/jANsfRyz1hcVFblMZuaOtZOFh+xZoob5s7vVcd8Xmn0QDJ3U33MPqgEzokeLXQav1bBV1Zotv1INquYytaJvs6gzx3t516rc+7TtcH8pVcbqCn51sC+uDvulZ9Vl6uqi9YLgjjXB3uAI+Z1A37B1kC8cn19lA7PVzvGjaZgtVuJ7D3UOI2kM+Wz0vC1btjB+/HiWLl3K+PHjG/w4p0+fJi0tjZEjR170b9mSQ/yFsrOz2b9/P6GhoaSkpMiX+WbS3OvIt3dGo5F9+/ZRXFxM//79iY6O9nST6nW5MfPFxcVs2rSJvn37XvEQn7p8//333Hbbbaxdu5bBgwc3ttniAh4N8uvWrWPs2LEXXT99+nQWL1582fvLl5XWqb7JzKQK1copihqWsndD9l51lvySLJi1qyZA/vsuSP8OvPwgOrm6at9f/RnRXZ0BXjSczaquTOCo3JtK1DXurSY14IM6V4LOp6Z6356Puc0CJWfVv9vijJqwX3JGPWb18Q+HkE41wd4QDyHxEBjZsONZWaieHIgf1vDXUot8NrYMixcvZs6cOWzfvp2uXbs2+HHS09M5efIkI0aMcP57tqYQ72A2mzlw4AD5+flSnW8mEuSbh6IoZGVlceDAAaKiokhOTm4VM/rXF+ZLSkrYvHkzXbt2bdRa8UeOHGHYsGF88MEH3HXXXe5qtqilxcxa3xDyZaX1stvtdU5mJtoYRXGtAn95PxxbqXaBvpB/ODx9XA2aAKU5ENBBKveNZbe7hntzubrGvdWkbopd/TfS6Wu69eta/heQJqXYoeJcrSp+Zs1WV68TB523GvAdm6F6C+l06dn0Jci3WXPmzGHFihVs3LixUTO4HzlyhNOnTztDe2sL8bVlZ2ezb98+wsPD6devn1Tnm5AE+aZnMpnYt28fRUVFpKSkXHZOi5bmwjDvuJyUlHTVK2fUlp+fz4gRI7j11luZO3euG1ssapMgL4RoXnY7nD+uTpDnqNzn7IOo3vDQ6pr95g9TJ9mLToaYFLVyH9MfOvRo2xO8NQdFqZlUz2qqnlSvWJ1Uz2Z2zqCOzqs62FcHfI2cbMNcpvY0Kc6E4jPqz5JMtbJvr6r/fr6GmlAfElfzMzhWPe4S5Nskm83G7bffztmzZ1mzZg0BAQ0blqEoCocPHyYzM5PIyEjOnTvXKkO8g9lsZv/+/RQUFNCnTx86deok1fkmIEG+6SiKQmZmJocOHWpVVfi6OMJ7dHQ0OTk5dO7cmZ49ezbq8caOHUv37t1ZsmSJFOqakAR5IYTn2W1qVTKwg3rZaoG3u4K55OJ9vXyh541w68c119msUrl3B1tVdeXeqFbxTaVq93ybubp6j1q9d1bufeSkioPdBuV5NQG/pHorPqPOol8vjdrzJLov3PO1W5oin40ti8lkYtKkSfj5+bF06dIGByq73c7PP/9McXExw4cPJzIy0s0tbX7Z2dkcOHAAf39/+vXrR0hIiKeb1KZIkG8axcXF7N+/H5PJRHJycqurwtclNzeXbdu2ERoaysiRIxscvi0WCzfccAMA3333Xas9udFayDdfIYTnaXU1IR7UJdmePe1auc/Zp26WMtdxyHYbvN1FnZAsJqV666/OaK73b97X0drpvNXNt1b4s9vVEO8I95bK6iXxKtVKvnPWfK+ayr1O3/7G3mt1anU9OPbiyrqlUp1YrzhTreaXnKmu6p+BqgqoyFe78os2ydfXl2+++YbRo0fz0EMPsXjx4quuPiuKQlpaGkajkYSEBHbv3s2IESMICrrEkI1WIDY2lsjISNLT0/n5559JSEigZ8+eEjpFi2SxWDh8+DBnzpwhKSmJbt26tagZ6RuqtLSUvXv3kpiYSHZ2NkeOHLmqdeYd7HY706dPp6ioiLVr10qIbwZSkRdCtB52u7peuKJARPXkUflH4IOhF++r0aoT6A2YDsMfb952tgdWS/XYe1Md1XtzzfwIjrH3On3bXxbvaimKOqQhL03taTLkIbc8rHw2tkw5OTmMGDGC2267jT/96U9XfL8LJ7YLCAjgyJEjZGRkNGpt55amrKyMAwcOUFpaSu/evaW7vRtIRd49HN3o09LSMBgMJCcnt9phLRdyTGzXpUsXevTocdnZ7OujKAqzZ89mxYoVbNq0qU30GGoNWv9pJCFE+6HVQniS63UdesCT+2sq9jn71Cp+xTk4dwTMpTX7lpyFxb+E6H4Q0w+iU9SfQS13iZgWy0uvbr61usI6qveOCn6VsWbsvam0Zlk8ra76/u28e75GA36hENmrwUvaidYjJiaGH3/8kREjRhAVFcWcOXMue5/6Zqfv2bMnGo2GTZs2kZqa2ia6pAcFBTF8+HBycnI4cOAAGRkZ9O3bl9DQUE83TbRjhYWFHDx4EJPJ5FxSrq2cYCoqKmLr1q0uE9tdzTrztf3pT3/iP//5D5s3b5YQ34wkyAshWjeNBkIT1K33ZPU6RYGyXMjdD2FdavbN2adOoFd0Gg5/W3N9QKQa6Ic8Ct0nNGfr2xatVh3OcOGQBueyeNXVe3N59bJ4xjq65+uru+jr1bXchWhDunXrxvfff8/YsWOJiopi2rRp9e57qSXmNBoNPXv2RKfTsXHjRoYOHdqoWfFbCo1G4+xuf/ToUTZt2kRUVBS9evVqMxVQ0TqUlZVx+PBh8vPz21Q3eof8/Hx27NhBz549SUpyLZBcbZj/5JNPePPNN1m3bh2dO3du0nYLV23nL1IIIRw0GgiOUbfaEkfCvUshZ78a8nP2w/lj6hjl46sh+faafTO3wqo/VFfuk9UtsrdaRRZXR+cFuqCLl2C7qHt+mdqDwmpWg75iBTTVY/erewDofNrf+HvRpgwcOJD//ve/TJ06lfDwcK6//vqL9rnSdeK7deuGXq9n69atDBgwgNjY2KZufrPw8vKid+/edO7cmfT0dNauXUt8fDzdu3fHz8/P080TbZjRaOTIkSNkZWURHx/P+PHj29wSiVlZWezdu5eUlBQ6depU5z5XGuaXLVvGzJkz+e677+jfv39TNlvUQYK8EKL98A2GLmPUzcFSoY5Rzt0HiSNqrs/aCWe2qpuD1gsieqihPnWWOtO4aLi6uuc7lsZzBnyTGu7NZeplY4m6zrsG0HpXh3sJ+KJ1ue666/j73//ObbfdxrfffsvYsWOdt11piHdISEjAx8eHnTt3Yjab21RFzM/Pj/79+5OUlMSRI0dYs2YNXbp0oVu3bjLmW7iVxWLh2LFjnDp1iujoaMaOHdsme4GcOHGCw4cPM3jwYKKioi657+XC/MqVK7nzzjv55z//yZgxY5qy2aIeEuSbkd1u59ChQxQVFREaGkqfPn1kbUUhPE0fAJ0Gq1ttvaeoy4Ll7ofcA+pPYxHkH1K3IQ/X7Hvwv7D/P2rAj+qr/gztrHY1F1dHowFvX3WrXXhTlFqz51cHfXOZWrmvK+A7K/jSRV+0TL/+9a8xmUxMnjyZ7777jlGjRl11iHeIjo4mNTWVrVu3Yjab6dGjR5sZxwtqoBg8eDBFRUWkpaWxatUqunbtSufOnSXQi0axWCycOnWK48ePO5deMxgMnm6W2ymKwuHDh8nIyGDEiBFXPPdEfWF+zZo13HzzzXz44YfccsstTdl0cQny7aaZbN68mffff5/Dhw9jNpvx8fGhV69ezJw5k9TUVE83TwhxIUMnMPwaUn6tXlYUdQmx3APqFtm7Zt+MzXD0B3Vz0Aeq+0T3hVHPXNzNX1wdjQa8/dStNrtdnSn/woDvrODX7qLvVTN7vpePBHzhcdOnT8dms3HjjTeyYsUKDAbDVYd4h7CwMEaOHMmWLVswmUykpKS0qTAPEBoaSmpqKufOnePo0aMcO3aMxMREkpKS2lz3Z9G0TCYTJ06c4NSpU4SGhjJkyBA6dOhw+Tu2Qna7nX379nHu3DlGjhx51ctWXhjm8/PzmTp1KgsWLOCuu+5qiiaLKyTLzzWDzZs38/TTT1NYWEhMTAx+fn4YjUZyc3MJDQ3lnXfekTAvRGuWe0AdU5+zD/IOQv5htXrs8Mwp8A9Tf988D85sr67e91Er+IZ4WZbN3RwVfKtJDfhV1ZPsmUvVsfk2E9ht6r5a7QUB37t5/z0qC9WeIReuP99AreWzUdT48MMPefrpp3nllVd4+OGHG9Wl12g0snnzZoKCghg4cCA6XdsdclJYWMjRo0c5d+4c8fHxdO3alYAAWQHCQZafu1hFRQXHjh3jzJkzREZG0q1bN8LCwjzdrCZjtVrZuXMnRqORYcOGNWqOibKyMhYtWsTLL7/MvHnzuP/++93YUtEQEuSbmN1u5+6772b37t107drV5ey4oiicOHGCAQMG8K9//Uu62QvRVtisUHhCDfiFJ2H0MzW3/etXcOIn1/19gqtDfR+Y8NrFVWfhPoqiLoPnrOCb1HkSzNVd9G1msFWp+2o0tQJ+9U9NE7xPS5AXwAcffMBzzz3HihUrGDlyZKMey2KxsHWrOr/HkCFD2ny1uqSkhGPHjpGTk0NsbCzdunWTv30kyNfWHv9GjEYj27dvR6fTMXTo0Eb/Daxbt46bbrqJd999l4cffvjydxBNTvoVNrFDhw5x+PBhYmJiLuriptFoiI6OJi0tjUOHDpGcnOyhVgoh3Ernpa5v36HHxbeNegaSxkHuQbV6fy5dDZGZWyA/DX75Ts2+3z0NZTlq1d4R9GXsfeNoNGrVva7VB2xVrgG/yqj+21gq1Gq+zaKeCNCgdst3hHydXp1ZX4hGePzxx/Hy8mLSpEksX76c0aNHN/ix9Ho9I0aMYO/evaxfv54hQ4a06fXYQ0JCGDRoEBUVFRw/fpz169cTFhZG586diY6OlkJJO2W328nNzeXkyZMUFxfTqVMnxo0b1y56bRQWFrJ9+3aioqLo169fo3vmrFmzhqlTpzJv3jzuu+8+9zRSNJoE+SZWVFSE2WyutyuLn58feXl5FBUVNXPLhBAekTBc3RysFnUJvLxDamisfcLv+Cp1zfsjy2uu8w6AyJ7QcRD88q1ma3a7oPOuO5DbbTVd9B3d9c3l6jh8q0X93W5V972wiq/1ltn0xRV75JFH8PLy4sYbb2Tp0qWMGzeuwY+l0+kYMGAAx48fZ9OmTfTv35+4uDg3trblCQgIICUlhZ49e5KRkcHBgwc5ePAgiYmJxMfHt/meCUJlNBrJzMzk9OnTaLVaEhMTGTJkCHq93tNNaxaZmZns37+fXr160aVLl0bPlfHjjz9yyy23sHDhQu6++243tVK4gwT5JhYaGoqPjw9Go7HOMW9GoxEfH582faZcCHEJXvqaavuFJs9Tu+fnpVVX749AVQWc3aXO0F7bPyar3b6j+qiT7EX1hg49pZu+O2h1atd3/QVVHEc3/doh31IJlvKLq/iOx6kd8HV6mRtBXOSBBx5Ap9MxefJk/v3vf3PTTTc1+LE0Go2zC/HOnTspLS2tdz3otsTHx4fu3bvTtWtXcnNzOX36NOnp6URHR5OQkECHDh3a/DFobxRF4dy5c5w+fZrc3Fw6dOhAv379iI6Objf/1oqikJaWRkZGBkOGDCEyMrLRj/m///2Pe++9l48++og777zTDa0U7iRBvon16dOHXr16sWfPHpKSki4aI5+bm8uAAQPo06eOL/FCiPat8yh1c7BZ1TH3+YdcZ1y3WiBjk1oVPrm25nqNFsK6QPfrYeLrNdfb7dI93x0u1U3fpYpfeyx+WfXvRjXkg/rzwpMEol2bPn06AQEB3HHHHcybN48HHnigUY8XFRXFqFGj2LZtG2VlZQwYMKBdjJnWarXExsYSGxtLRUUFp0+fZteuXeh0Ojp27EinTp3a/Djptq6kpISsrCyysrJQFIX4+HiuvfbadtF9vraqqip27txJZWUlo0aNatSEmQ6LFi3it7/9LZ999hmTJ092QyuFu0mQb2JarZaZM2fy9NNPc+LECaKjoy+atX7GjBkyfksIcXk6L+jQXd1q0+rggR/V7vl5h9Sx9nmHwFgI54+r4+wd7DZ4OwlCOtVU7iN7Q2QvCO4oFWJ3qa+KD9Wz5ptdQ74shScucOuttxIREcGUKVPIy8vjueeea1RlMSgoiFGjRrFz505+/vlnhg4d2q7CTkBAgLO4kp+fT1ZWFhs2bCAgIIC4uDji4uIaNaO3aD5Go5GsrCzOnDlDZWUlMTEx9O/fnw4dOrTL79Pl5eVs27YNf39/Ro0a1eiTdIqi8Oqrr/KXv/yFH374odGTb4qmI7PWN5O61pHv3bs3M2bMkKXnhBDupyhQnqcGet8QiBukXn/+BMwbUPd9fIJh8IMw/uWax6g4BwEdJOC3Iq3ps1Fc3t69e5k0aRK33347f/nLXxodVOx2O4cOHeLMmTNcc801xMTEuKmlrU9VVRU5OTlkZWVRUFBAeHg4cXFxREVFtYnx9G1p1nqTyURubi5ZWVkUFhbSoUMH4uLiiImJwcur/Z4Izc7OZs+ePSQmJtK7d+9GDyOw2WzMmjWLb7/9lh9++IG+ffu6qaWiKbTfv/xmlpqayrBhwzh06BBFRUWEhobSp0+fdnnmUAjRDDQaCIpWt9pCE2HWbnWt+3OH1Z95aeqEe+ZS18pwaTb8pTf4hakV+w491Z+RvaBDLwgIb9aXJER71L9/fzZv3syECRPIz89n8eLF+PjUMZzjCmm1WpKTkwkNDWX37t3Ex8e32+8j3t7exMfHEx8fj8lk4uzZs2RkZLBv3z4MBgPR0dFER0cTFBTUbsZZtxSKolBaWkpubi65ubmUlJRgMBjo2LEjgwYNahMnWhrDZrM5T8j179+fjh07NvoxTSYTd999NwcPHmTz5s3Ex8e7oaWiKbW/d20Pcnx4jho1iuTk5Hb5oSmE8DCtDsKToNeNMOp3cOvfYcZWeCEHHt8KA6bX7Ft0CtCoXfQzNsHOj2HF07D4Bni7C6x9o2Zfczmc3qSuiS5EKzd37lwGDx5MUFAQkZGRTJ06lfT0dOfthYWFzJo1ix49euDn50d8fDxPPPEEJSUlLo+j0Wgu2j7//HOXfV555RXi4uIYOXIkR48erbM9nTt3ZtOmTRw7dowbb7yRsrKyRr/GuLg4Ro8ezfnz5/n555+pqKho9GO2Zr6+viQlJTFq1CgmTJhAQkICRUVFbNiwgdWrV3PgwAHOnTuH3W6//IOJBrHb7eTn57N//35WrVrFzz//THFxMYmJiUycOJFRo0aRlJTU7kN8eXk5P//8M0VFRYwZM8YtIb6kpIRJkyaRlZXFxo0b6wzxCxYsoF+/fgQHBxMcHMzw4cP5/vvvnbd/+OGHjBkzhuDgYDQaDcXFxRc9RmJi4kXviW+++abLPh999BEJCQlcc801bNu2rdGvrS2TirwQQgh1JvXIXq7XJY6EF7Kh4Kg6Y37+4eqfaVCcCYaEmn2z98A/blR/D4iEDj2qK/c91Ep+dLLaxV+IVmD9+vXMmDGDwYMHY7VaeeGFF5gwYQJpaWkEBASQnZ1NdnY277zzDr179yYjI4Pf/OY3ZGdn89VXX7k81ieffML111/vvGwwGJy/b9q0ie+++46lS5eybds2Zs6cycqVK+tsU2RkJGvXruWWW25h7NixrFixotGzUgcGBvKLX/yCQ4cOsW7dOrdV9lo7X19fEhISSEhIwGazce7cOXJzc9m1axdWq5Xw8HDCw8OJiIjAYDBIYaaB7HY7xcXFFBQUUFBQQGFhId7e3kRHR5OSkkJERESj1z9va7Kysti3bx8JCQn07t3bLX97OTk5TJo0idjYWJYvX17v3BlxcXG8+eabdOvWDUVR+Mc//sGUKVPYs2cPffr0obKykuuvv57rr7+e559/vt7n++Mf/8jDDz/svBwUFOT8PTMzk7feeovPP/+cs2fPcv/995OWltbo19hWSZAXQghRP70/xPZXt9rM5a7j5i0VYIhXA35Fvrqd/rnm9hvfg0H3q78XnoRjqyCiuxryg6JlDL5oUX744QeXy4sXLyYyMpJdu3YxatQo+vbty3//+1/n7UlJSbz++uvcfffdWK1WlzG7ji7adSkqKiI2NpZ+/fphtVpZvHjxJdsVFBTE8uXLue+++xg2bBjLli1r9Ko3Op2Ofv360aFDB/bs2UNBQQF9+/aVAFVNp9M5u9grikJZWZkzeJ44cQKbzSbB/grVFdx1Oh3h4eFER0fTt29fGcZQD6vVyoEDB8jJyWHgwIH1vqdcrf379zN58mRGjRrFxx9/fMm5FC5cCvP1119nwYIFbN26lT59+jB79mwA1q1bd8nnDAoKqrf9paWlGAwG59KBRqPxql5PeyNBXgghxNXzuWBpmx7Xq5u5HArSIf9Izc9zR1yr/ac3wvfP1HqskOrZ+HtARA/oPQVCExCipXB0mQ8LC7vkPsHBwRdNvDVjxgweeughunTpwm9+8xvuv/9+Z1CZOHEi77//Pv7+/gQGBl5Uza+LXq9nyZIl/PGPfyQ1NZUlS5Y0aq15h5iYGEJCQti5cycbNmxg0KBBLpUyoQ6VcHQr7tKlS53B3mq1EhwcjMFgICQkBIPBQHBwcLsL9zabjdLSUkpKSiguLqa4uJiysjK8vLwkuF+l0tJSdu7cibe3N2PHjnXb6gr/+9//mD59Os899xwvvPDCVf072Gw2vvzySyoqKhg+fPhVPe+bb77Jq6++Snx8PHfddRdPPfWU832zb9++9OvXj5CQEPR6PR999NFVPXZ7I0FeCCGE+/gEQseB6lafwGjo8Us4l66OwzeXQNYOdQOI6VcT5I/+CPv/Ux3yu6tbeFLda7cL0QTsdjuzZ89mxIgR9c7gXFBQwKuvvsojjzzicv0f//hHxo0bh7+/PytXruTxxx+nvLycJ554AlAnW/vhhx/Iz8/HYDCg1+uvqE1arZaXX36Zvn37ctddd/HCCy80enk6AH9/f0aOHMnhw4dZv349vXr1okuXLhK06lFXsK+oqHCG17Nnz3Lo0CFsNpsz3AcFBREYGEhgYCD+/v6t/tja7XaMRiPl5eWUl5dTVlZGcXExpaWleHl5OU9mdOvWDYPB0CZec3NRFIXjx4+Tnp5Oly5d6Nmzp1tOCNntdl577TXeeecd/vWvfzF16tQrvu+BAwcYPnw4JpOJwMBAvv76a3r37n3F93/iiScYMGAAYWFhbN68meeff56cnBzeffdd5z4ff/wxb731Fv7+/rIk5GXI8nNCCCE8p8oEhSfUqv25o2oVf9JbEFg99nf1y7DxL6730ejU2fc79IDrXoWIrur1dju0s6pXXeSz0b0ee+wxvv/+ezZu3EhcXNxFt5eWlnLdddcRFhbGt99+e8muqS+99BKffPIJZ86ccVv79u7dy5QpU0hNTeXjjz/G39/fLY97/vx59uzZg4+PD9dccw2BgYGXv5O4iKIoVFZWOqvSjsBbUVGBRqNx9sZwbH5+fvj6+uLj44Ner29U6HXH8nOKomCxWDCZTJjNZiorK6moqHB5HQABAQHO12AwGCS0N1JZWRl79uzBYrE4g687VFRUcN9997Fz506+/fZbkpOTr+r+FouFzMxMSkpK+Oqrr/jb3/7G+vXrXcL8unXrGDt2LEVFRS5zgtTl73//O48++ijl5eWNWo2jvZIgL4QQouXK2gWnN9SE/HNHwVJrxu7ZB9Sx+QA/vQ67/1Fdue/m+jM4rt2EfPlsdJ+ZM2eydOlSNmzYQOfOnS+6vaysjIkTJ+Lv78/y5csvO5v2d999x4033ojJZHLrl9b8/HxuvvlmTCYT33zzTZ0nHBrCarVy+PBhMjIypDrvZna7/aJQXF5ejslkwmQyYbVa0Wg0+Pr6OoO9r68ver0enU6Hl5dXnZtWq3XOBm61Wlm7di1jxozBy8sLRVGw2+1YrdY6N5vN5gztjuBuMplQFAUvLy98fX3x8/MjMDDQJbj7+fm1u6EDTUVRFE6cOMGRI0dITEykV69ebpuvIiMjgylTpmAwGPjqq6+IiIho9GOOHz+epKQkFi1a5LzuaoL8oUOH6Nu3L0eOHKFHjx6Nbk97I13rhRBCtFxxA9XNQVGgLFcN9QXH1IDuUHAUyvPUrfZEewBefjBzBxg6qZfzD4PVDOFdLx7vL9o9RVGYNWsWX3/9NevWraszxJeWljJx4kR8fHz49ttvr2hJrL179xIaGur2ylNkZCQ//fQTjz/+OIMGDeLrr7++6nGrdfHy8iI5OZmYmBj27NlDdna2VOfdRKvVOoNwVFTURbdbrVaXMF07XNcO3lVVVdhsNud1drsdR43O8XP9+vWAOhRAq9U6Q79Op8Pb29v5u5eXF97e3kRERDhPIDhOIlw494Nwv9pV+OHDhxMeHu62x964cSM333wzt956K//v//2/BvfQuJDdbsdsNjf4/nv37kWr1TZ6BY72Sv5XCiGEaD00GgiOUbcuY1xvmzwPRjyhBvyCo+oY/PPH4fwJUGwQFFOz789/hgNfqr8Hxard8yO6Q3g39ffOo0Hnni86ovWZMWMGn332GUuXLiUoKIjc3FwAQkJC8PPzo7S0lAkTJlBZWcmSJUsoLS2ltLQUgA4dOqDT6Vi2bBl5eXkMGzYMX19fVq1axRtvvMHTTz/dJG12TAz1/vvvM378eObNm8cDDzzglseOiIhg7NixpKWlsW7dOqnONwMvLy9n0G8oR9f6SZMmuS24Cfe7sArfs2dPt504URSFjz76iKeeeop33nmHxx57rMGP9fzzzzNp0iTi4+MpKyvjs88+Y926dfz4448A5Obmkpuby/HjxwF1PH1QUBDx8fGEhYWxZcsWtm3bxtixYwkKCmLLli089dRT3H333YSGhrrl9bY30rVeCCFE22azQll2TRd8gG9nwZEVUFlw8f4aHfw+rybIb/sQynLUbvrhXdXN3z3jFZuCfDY2Xn0B9ZNPPuG+++5zdh2ty6lTp0hMTOSHH37g+eef5/jx4yiKQteuXXnsscd4+OGHm7wb8urVq7nzzjv55S9/yfz5891aQS8oKGDPnj34+vo6Z5cWLZM7xsiLplVcXMz+/fuxWCxcc801bq3Cl5WV8Zvf/IbVq1fzxRdfMGbMmEY93oMPPsiaNWvIyckhJCSEfv368eyzz3LdddcB8PLLL/PKK69cdD/H++bu3bt5/PHHOXLkCGazmc6dO3PPPfcwZ84cGR/fQBLkhRBCtF+VhWrVvuAYnD+m/rRZYNqXNft8dC2c3el6P78wNdB36A6T31d7CgDYbaD17Prb8tkoALKzs7nrrrvIzc3lP//5D/369XPbY1utVtLT0zl58qSzgihBseWRIN9yWSwWjhw5QmZmJl26dKF79+5uHb6we/dufv3rX5OQkMCSJUvctu68aFmka70QQoj2yz8M/IdApyH17zPgHohJqQ76x9XqvrEQsrar4/FrV28X3wglZyCsS031PjwJwpLUJfWku75oJrGxsaxZs4ZXX32V4cOH8+677/LII4+4pTu8l5cXffr0IT4+nv3797NmzRr69OlDXFycdLcX4hIURSEzM5O0tDRCQkIYM2aMW3vMKIrC/PnzefbZZ53LUrprsjzR8kiQF0IIIS5l4H2ul83lUHhSreTbra63nT8GFefUMH9qvetthgSYvb/mctq3oA9Qu+zX7vYvhJvodDpefvllRo0axbRp0/jpp5/48MMP3dYdPigoiNTUVLKzszl48CCnT5+W7vZC1MPRjd5kMpGSkkJMTIxbT3wVFRXx4IMPsn37dr7//ntGjRrltscWLZMEeSGEEOJq+ARCTD91u9DjW9XJ9QpPVE+0Vz3Z3vkTEJrouu+K30F5LkQnw282NkvTRfs0btw49u3bxz333MOAAQP4/PPPGTx4sFseW6PR0LFjR6KiokhPT2fDhg3S3V6IWpq6Gz3A1q1bueOOO+jbty979+51y9JyouWTIC+EEEK4S0CEusUPdb3ebgdLea3LNogbpAb9yD7N20bRLkVGRvL999/z9ttvM2bMGF577TWefPJJt028V1d3+x49epCQkCBrjIt2yW63c/r0adLT05ukG73jOf785z/zhz/8gddee43Zs2fL/7d2RCa7E0IIIdoQ+WwUl7N582buuusuunTpwt///ncSExPd+viKopCTk8Phw4dRFIVevXoRGxsr4+ebmUx25xmKopCVlcWRI0fQ6XT06tWL6Ohot//9nzhxggceeIAzZ87w+eefM2TIJeZ6EW2SnLIRQgghhGhHUlNTOXDgAN27dyc5OZkFCxZgt9vd9vgajYbY2FjGjh1Lt27dOHjwIOvXryc/P59WXD8S4pIURSEvL49169Zx+PBhevTowdixY90+Ft5utzNv3jxSUlJITk5m//79EuLbKelaL4QQQgjRzgQFBbFw4UJuueUWHnzwQf773//y8ccfk5CQ4Lbn0Gq1JCQkEBcXx8mTJ9m5cychISH07t2b0NBQtz2PEJ5WWFhIWloapaWldO/enc6dOzfJbPEnT57kgQceICMjg2XLljF27Fi3P4doPaQiL4QQQgjRTl133XUcPHiQpKQkkpOTWbRokdur5jqdjm7dunHdddcRGhrKpk2b2LFjB2VlZW59HiGaW2lpKdu3b2fz5s2Eh4dz3XXX0bVrV7eHeLvdzvvvv09KSgp9+vThwIEDEuKFjJEXQggh2hL5bBQNtWrVKh588EF69OjB3/72N7dW52szGo0cPXqUzMxMoqKi6N69OwaDoUmeqz2TMfJNp6ioiKNHj5Kfn098fDw9evTA19e3SZ7r5MmTPPjgg5w+fZqPP/6YcePGNcnziNZHKvJCCCGEEMJZne/cuTPJycl88MEH2Gw2tz+Pn58fKSkpjB8/Hj8/PzZu3MjmzZspKCiQMfSixVIUhXPnzrFp0yY2bdpEQEAA48ePJyUlpUlCvNVqdY6F79WrF/v375cQL1xIRV4IIYRoQ+SzUbjDypUreeyxxwgNDWX+/PkMHTr08ndqILPZzMmTJzl16hSBgYF069atSWb5bm+kIu8eiqKQm5vL0aNHqaiooEuXLnTp0gW9Xt9kz7lp0yZmzJhBZWUlCxYs4Nprr22y5xKtl1TkhRBCCCGEiwkTJnDo0CGmTJnCuHHjePjhhykoKGiS5/Lx8aFXr15cd911xMbGsm/fPtauXcuZM2fcOpu+EFfDbreTmZnJ2rVr2b9/P3FxcUyYMIGePXs2WYjPy8vjvvvuY+LEifz617/mwIEDEuJFvSTICyGEEEKIi/j6+vLiiy9y8OBBzp07R/fu3Vm4cGGTdLcH8Pb2pmvXrlx33XV06dKFI0eOsGrVKtLT0zGbzU3ynEJcyGQykZ6ezqpVqzh69ChJSUmMHz+epKQkvLyaZsEvRzf6Hj16UF5eTlpaGs8//zw+Pj5N8nyibZDl54QQQgghRL06d+7MN998w4oVK3jiiSf46KOP+OCDD5qsu71OpyMxMZGEhARyc3M5deoUR48eJTY2li5dumAwGKTbvXArRVEoKiri1KlTZGdnExERQUpKClFRUU3+t+boRm80GvnPf/7DhAkTmvT5RNshFXkhhBBCCHFZv/zlLzl48CC/+tWvGDduHA899BDnzp1rsufTaDTExMSQmprKmDFj8Pb2ZtOmTaxfv57Tp09jtVqb7LlF+1BVVcWpU6dYt24dW7ZsQa/XM3bsWIYPH97k8zRc2I1+//79EuLFVZEgL4QQQgghroivry+///3vOXToEOfPnycpKYk//vGPlJeXN+nzBgUF0a9fPyZOnEhiYiKnT5/mxx9/ZN++fRQVFcls9+KKOarv+/bt48cffyQzM5MuXbowceJEkpOTCQwMbNLnLy0t5aWXXiIpKUm60YtGka71QgghhBDiqiQmJvL111+zceNGnn32WebPn8+LL77II4880qSzeXt7ezu73RcXF3P69Gk2b96Mr68vcXFxxMXFERAQ0GTPL1qv8vJysrKyyMrKwmw207FjR0aMGEFoaGizPL/ZbGbBggW8/vrr9OrVi5UrV5Kamtoszy3aJll+TgghhGhD5LNRNDdFUVi2bBkvvPAClZWVvPrqq9x5551otc3T8dNms5Gbm0tWVhZ5eXkYDAY6depEbGxsu65yyvJzang+e/YsWVlZlJSUEBkZSadOnYiKikKn0zVLG2w2G59++ikvvfQSwcHBvPnmm0yaNEnmeRCNJkFeCCGEaEPks1F4is1m41//+hcvvfQSYWFhzJ07l+uvv75ZA4vZbCY7O5usrCyKioqIjIwkLi6O6OjoJptxvKVqr0HearU6T+zk5+cTFhZGXFwcsbGxTdpb5EKKovDdd9/x/PPPU15e7jzB1VwnEETbJ0FeCCGEaEPks1F4mslkcnYh7tu3L6+//jojRoxo9nZUVFQ4u1JXVlbSoUMHoqOjiY6OxtfXt9nb09zaU5A3Go3k5eWRm5vLuXPnCAgIcA618Pf3b/b2/Pzzz7zwwgukp6fz+9//nkcffbRd9w4RTaNFTHY3f/58EhMT8fX1ZejQoWzfvt3TTRJCCCGEEA3g6+vLU089xYkTJ/jFL37BpEmTGD16ND/++GOzTkoXEBBAjx49GDduHGPGjCE8PJwzZ86wcuVK1q9fT3p6OiUlJTJRXiukKArFxcWkp6ezbt06Vq1axZkzZwgPD2fMmDGMGzeO7t27N2uId1TgR44cyY033si1117LiRMneOKJJyTEiybh8Yr8F198wb333svChQsZOnQo7733Hl9++SXp6elERkZe8r5SdRBCCCFcyWejaGmKi4uZP38+7733Hp06deL555/n5ptv9lgXY7PZ7Kze5ufno9friY6OJioqivDw8DbTBb+tVeSrqqooLCwkNzeXvLw8LBYLUVFRzs1TYdlqtfLVV18xd+5ccnNzeeqpp3jssccICQnxSHtE++HxID906FAGDx7M+++/D4DdbqdTp07MmjWL55577pL3dXxZOXfuXJ1fVrRarcubscViqfexNBqNy5vc1exbVVVV79ncptoXcBnnczX7Wq1W7Ha7W/b19vZ2jn1rqn1tNhs2m80t+3p5eTkn32kJ+9rt9kuug6vT6ZxfdFrCvoqiUFVV5ZZ9a///bKp94dL/l+U9ou595T2idb9HlJaW0qFDBwnyosWprKzk448/5u2338bPz49nnnmGe+65p1nHLV/IZrNRUFDgDPVGoxGDwUBERAQRERGEhYW12mDf2oO8I7gXFBRw/vx5iouL8fPzIyoqiujoaMLDwz063txsNvOPf/yDt956C6vVyjPPPMP999+Pn5+fx9ok2hePvjNZLBZ27drF888/77xOq9Uyfvx4tmzZctH+ZrMZs9nsvFxaWgrAn//85zrPwnXr1o1p06Y5L7/99tv1BoDExETuu+8+5+X33nuPysrKOveNjY3lkUcecV6eP38+xcXFde7boUMHZsyY4bz84Ycfcu7cuTr3NRgMzJ4923n5k08+ITs7u859/f39eeaZZ5yXP/30U06fPl3nvt7e3vzf//2f8/IXX3zBsWPH6twX4OWXX3b+/r///Y+0tLR6933hhRecH8DLly9n79699e77u9/9zrkkzI8//siOHTvq3Xf27NkYDAYA1qxZw+bNm+vd9/HHH3f23vj5559Zt25dvfs+/PDDdOzYEYCtW7eyatWqeve97777SExMBGDXrl2sWLGi3n3vuusuunfvDsCBAwf45ptv6t33tttuo0+fPgAcPnyYL7/8st59p06dSv/+/QE4fvw4n332Wb37/vKXv2TIkCEAZGZmsnjx4nr3ve6665zjFXNycvjoo4/q3XfMmDGMGTMGgHPnzvHBBx/Uu29qaioTJkwAoKSkhPfee6/efQcPHswNN9wAqF/u3n777Xr37d+/P1OnTgXUD/Y33nij3n179+7N7bff7rx8qX3lPUIl7xE12sJ7RO3PSSFaEn9/f2bNmsWjjz7KZ599xp/+9Cf+8Ic/8Nvf/paHH364ydfvrotOp3NWdEH9PCooKKCgoIB9+/a1qWDf0lmtVmdwLygocAb3iIgIOnfuTHh4uEfGu1+orKyMRYsW8e677xIaGsof/vAH7rjjjlZ5skS0bh59JyooKMBmsznfPB2ioqI4cuTIRfvPnTuXV155pbmaJ4QQQggh3Eyv13Pfffdx77338s033zB37lxee+01HnroIR5//HESEhI81jZ/f3/i4+OJj48HXIP93r17MZlMBAcHExISgsFgwGAwEBwcLDORXyWbzUZJSQklJSUUFxdTXFxMWVmZM7gnJiYSERHRIoK7w8mTJ1mwYAF/+9vf6NGjBwsWLOCmm25qtmUWhbiQR7vWZ2dn07FjRzZv3szw4cOd1z/zzDOsX7+ebdu2uexfV0W+U6dO0rX+KveVbrOtu9usJ/eVrvXyHnG1+8p7ROP2la71oj1QFIX169czb948li9fzqRJk5g1axbjxo1rcWttV1ZWOoOnY7NarQQFBWEwGJwBPzg42OOV+5bStd7xvuQ4XiUlJZSVleHt7e1yQsRgMLSo4A7q++rq1auZN28eK1euZMqUKcycOZNf/OIXLe5vU7Q/Hn2HiYiIQKfTkZeX53J9Xl4e0dHRF+3v4+NTZxd6vV5/ReOrrmYM1tXsezVvji1h36v5YGkJ+9b+otrW9tVqtVf8t9YS9tVoNK1qX2i6//fyHtFy9m0J/5db0nuEJ8cbC9EQGo3GOYwrMzOThQsXcscddxAREcGjjz7KvffeS1hYmKebCagVe39/f2JjYwH1JITRaHSG1NzcXNLT07FYLPj5+REYGEhAQACBgYHOzc/Pr81Vce12O5WVlVRUVFBeXu7cKioqMBqN6PV654mO6OhoDAYDfn5+LTYMnz9/nn/84x8sWrSI4uJiHnnkERYsWEBcXJynmyaEU4uY7G7IkCHMmzcPUN8I4uPjmTlz5hVPdidVByGEEEIln42iLTCZTHz55ZcsWrSIXbt28etf/5pHH32UYcOGtdjw56AoCiaTyRlqa4fbiooKAGe49/Pzw9fXFx8fH3x9fZ2bXq9v9Ot0V0VeURQsFgsmk8llM5vNGI3GOl+XY3Nc9vHxaRX/bps3b2bhwoV89dVXDB48mEcffZRbb71Vlo8TLZLHZ+uYM2cO06dPZ9CgQQwZMoT33nuPiooK7r//fk83TQghhBBCeICvry/33HMP99xzDwcPHmTRokVcf/31dOrUiWnTpnHXXXd5dCz9pWg0Gvz8/JzjvWuz2+3O8FteXo7JZKKsrIxz5845A7LVakWj0TjDvY+PD97e3nh5eaHT6fDy8qpz02q1aDQa5+YYllNaWopOp0NRFBRFcQ7DqWuz2WxYrVaqqqowm83OwK4oCt7e3hedcHCMZ2/NPQ1OnTrFZ599xqeffkpOTg733nsvu3btonfv3p5umhCX5PGKPMD777/P22+/TW5uLv379+evf/0rQ4cOvez9pOoghBBCuJLPRtFWVVRUsHTpUpYsWcKqVatITU1l2rRp3HbbbYSGhnq6eW5jtVqdIdoRpC8VumtfBpzzoTgCu2OeEEdFvK6TAXVdd2FPgbY0od/58+f58ssv+fTTT9m2bRsTJkxg2rRpTJkypcWN0xeiPi0iyDeUfFkRQgghXMlno2gP8vPz+eKLL1iyZAl79+7lhhtuYNq0adxwww34+vp6unktQkuZ7K6lMBqNLF++nCVLlvDDDz8wYMAA7r77bm6//XY6dOjg6eYJcdVaX/8XIYQQQgjRrkVGRjJr1iy2bdvGwYMH6devH88++yzR0dE89NBD/Pjjjy4rHYn2yWQy8f333/PAAw8QHR3N73//ewYOHEhaWhpbtmxhxowZEuJFqyVBXgghhBBCtFrdunXj5Zdf5tixY/z444/4+/vz8MMPExERwa233so///lPCgoKPN1M0UzOnTvH4sWLufnmm4mIiOA3v/kNQUFBrF69miNHjvDSSy+RlJTk6WYK0WjStV4IIYRoQ+SzUQh1nPi+ffv49ttvWbZsGXv27GH48OFMnjyZyZMn06NHD083scm1l671iqJw+PBhli1bxrfffsu2bdsYOHAgN910E5MnTyY5ObnFz5gvRENIkBdCCCHaEPlsFOJiZ8+eZfny5SxbtozVq1cTHx/PTTfdxIQJExgxYgSBgYGebqLbteUgX1ZWxqZNm1i5ciXffvstZ8+e5brrruOmm27ixhtvJCYmxtNNFKLJSZAXQggh2hD5bBTi0ioqKli9ejXLli3jp59+4syZMwwaNIgxY8YwZsyYNhPs21KQdwT3devWsW7dOnbu3ElCQgLjxo1j8uTJXHvttTLbvGh3PL6OvBBCCCGEEM0lICCAKVOmMGXKFAAyMjJYv349a9eu5Te/+Q1ZWVkMHjzYGexTU1PbRLBvTeoL7mPGjGHGjBmMHj2a+Ph4TzdTCI+SirwQQgjRhshnoxCNc/r0adavX+8MkVlZWfTt25eBAwc6t379+rX4Ze5aS0XeaDSyf/9+du3a5dwOHjzoDO5jxoyR4C5EHSTICyGEEG2IfDYK4V4ZGRns2LHDJWiWlpbSp08fl3CfkpLSosJ9SwzyRqORffv2uRzLQ4cOYTAYXI7l4MGDJbgLcRkS5IUQQog2RD4bhWhaiqKQkZHhEkZ37dpFcXEx3bp1o3v37hdt0dHRzT5zuqeCvKIo5OTkcPTo0Yu248ePExoa6hLaBw4cSHx8vMwsL8RVkiAvhBBCtCHy2ShE81MUhczMTNLS0i4Kr5mZmQQGBroE+y5duhATE+PcwsPD3R5kmyrIK4rC+fPnycnJITs7m5ycHE6ePOnymisrK4mPj7/ohEbv3r3p1KmThHYh3EAmuxNCCCGEEKIRNBoNCQkJJCQkMGnSJJfbjEYjx48fdwm669evJycnh5ycHMrKytDr9URHRxMTE0NsbKwz4EdHRxMcHExQUBCBgYEuP4OCgvDz82twKFYUhcrKSsrLyykrK6OsrMz5e3l5OaWlpeTm5jrDuiO45+bmUlVVRXBwsLOdnTt3pn///tx+++10796dpKQk/Pz83HFohRD1aNUV+ZKSEgwGA2fOnJGqgxBCCIFake/UqRPFxcWEhIR4ujlCiMuoqKhwqW7X3vLy8igtLb0obFssFgC0Wi2BgYEEBgai1+vRarUum9FoxMfHB7vd7twsFovzcRwxQK/XX3SSICgoiKioqItOLji2gIAATx42Idq9Vh3ks7Ky6NSpk6ebIYQQQrQ4Z86cIS4uztPNEEI0AYvF4hLuy8rKsFqtLoHdZrOh0WguCvfe3t4XVfj1er2nX5IQ4iq16iBvt9vJzs4mKCjIbWNtHJUMqfKr5Hi4kuNRQ46FKzkeruR4uGrO46EoCmVlZcTGxqLVapv0uYQQQgjhGa16jLxWq22yakNwcLB8+axFjocrOR415Fi4kuPhSo6Hq+Y6HtKlXgghhGjb5FS9EEIIIYQQQgjRikiQF0IIIYQQQgghWhEJ8hfw8fHhD3/4Az4+Pp5uSosgx8OVHI8acixcyfFwJcfDlRwPIYQQQrhTq57sTgghhBBCCCGEaG+kIi+EEEIIIYQQQrQiEuSFEEIIIYQQQohWRIK8EEIIIYQQQgjRikiQF0IIIYQQQgghWhEJ8rXMnz+fxMREfH19GTp0KNu3b/d0k5rF3LlzGTx4MEFBQURGRjJ16lTS09Nd9jGZTMyYMYPw8HACAwO55ZZbyMvL81CLm8+bb76JRqNh9uzZzuva47E4e/Ysd999N+Hh4fj5+ZGcnMzOnTudtyuKwksvvURMTAx+fn6MHz+eY8eOebDFTcNms/Hiiy/SuXNn/Pz8SEpK4tVXX6X2nKFt+Vhs2LCBm266idjYWDQaDd98843L7Vfy2gsLC5k2bRrBwcEYDAYefPBBysvLm/FVuM+ljkdVVRXPPvssycnJBAQEEBsby7333kt2drbLY7Sl4yGEEEKI5iNBvtoXX3zBnDlz+MMf/sDu3btJSUlh4sSJ5Ofne7ppTW79+vXMmDGDrVu3smrVKqqqqpgwYQIVFRXOfZ566imWLVvGl19+yfr168nOzubmm2/2YKub3o4dO1i0aBH9+vVzub69HYuioiJGjBiBt7c333//PWlpafz5z38mNDTUuc9bb73FX//6VxYuXMi2bdsICAhg4sSJmEwmD7bc/f70pz+xYMEC3n//fQ4fPsyf/vQn3nrrLebNm+fcpy0fi4qKClJSUpg/f36dt1/Ja582bRqHDh1i1apVLF++nA0bNvDII48010twq0sdj8rKSnbv3s2LL77I7t27+d///kd6ejqTJ0922a8tHQ8hhBBCNCNFKIqiKEOGDFFmzJjhvGyz2ZTY2Fhl7ty5HmyVZ+Tn5yuAsn79ekVRFKW4uFjx9vZWvvzyS+c+hw8fVgBly5YtnmpmkyorK1O6deumrFq1Shk9erTy5JNPKorSPo/Fs88+q4wcObLe2+12uxIdHa28/fbbzuuKi4sVHx8f5d///ndzNLHZ3HDDDcoDDzzgct3NN9+sTJs2TVGU9nUsAOXrr792Xr6S156WlqYAyo4dO5z7fP/994pGo1HOnj3bbG1vChcej7ps375dAZSMjAxFUdr28RBCCCFE05KKPGCxWNi1axfjx493XqfVahk/fjxbtmzxYMs8o6SkBICwsDAAdu3aRVVVlcvx6dmzJ/Hx8W32+MyYMYMbbrjB5TVD+zwW3377LYMGDeK2224jMjKSa665ho8++sh5+6lTp8jNzXU5JiEhIQwdOrTNHZPU1FTWrFnD0aNHAdi3bx8bN25k0qRJQPs6Fhe6kte+ZcsWDAYDgwYNcu4zfvx4tFot27Zta/Y2N7eSkhI0Gg0GgwGQ4yGEuLzLDX88ffo0Go2mzu3LL7907peZmckNN9yAv78/kZGR/O53v8Nqtbo81yuvvEJcXBwjR450fs4JIVouL083oCUoKCjAZrMRFRXlcn1UVBRHjhzxUKs8w263M3v2bEaMGEHfvn0ByM3NRa/XO798OkRFRZGbm+uBVjatzz//nN27d7Njx46LbmtvxwLg5MmTLFiwgDlz5vDCCy+wY8cOnnjiCfR6PdOnT3e+7rr+/7S1Y/Lcc89RWlpKz5490el02Gw2Xn/9daZNmwbQro7Fha7ktefm5hIZGelyu5eXF2FhYW3++JhMJp599lnuvPNOgoODgfZ9PIQQV8Yx/HHw4MFYrVZeeOEFJkyYQFpaGgEBAXTq1ImcnByX+3z44Ye8/fbbzpPMNpuNG264gejoaDZv3kxOTg733nsv3t7evPHGGwBs2rSJ7777jqVLl7Jt2zZmzpzJypUrm/31CiGunAR54WLGjBkcPHiQjRs3eropHnHmzBmefPJJVq1aha+vr6eb0yLY7XYGDRrk/LC/5pprOHjwIAsXLmT69Okebl3z+s9//sOnn37KZ599Rp8+fdi7dy+zZ88mNja23R0LceWqqqq4/fbbURSFBQsWeLo5QohW5IcffnC5vHjxYiIjI9m1axejRo1Cp9MRHR3tss/XX3/N7bffTmBgIAArV64kLS2N1atXExUVRf/+/Xn11Vd59tlnefnll9Hr9RQVFREbG0u/fv2wWq0sXry4uV6iEKKBpGs9EBERgU6nu2jm8by8vIveHNuymTNnsnz5ctauXUtcXJzz+ujoaCwWC8XFxS77t8Xjs2vXLvLz8xkwYABeXl54eXmxfv16/vrXv+Ll5UVUVFS7ORYOMTEx9O7d2+W6Xr16kZmZCeB83e3h/8/vfvc7nnvuOe644w6Sk5O55557eOqpp5g7dy7Qvo7Fha7ktUdHR180gajVaqWwsLDNHh9HiM/IyGDVqlXOajy0z+MhhGicC4c/XmjXrl3s3buXBx980Hndli1bSE5OdukxNXHiREpLSzl06JDzsslkwt/fn+uvv975uSaEaLkkyAN6vZ6BAweyZs0a53V2u501a9YwfPhwD7aseSiKwsyZM/n666/56aef6Ny5s8vtAwcOxNvb2+X4pKenk5mZ2eaOz7XXXsuBAwfYu3evcxs0aBDTpk1z/t5ejoXDiBEjLlqO8OjRoyQkJADQuXNnoqOjXY5JaWkp27Zta3PHpLKyEq3W9W1Tp9Nht9uB9nUsLnQlr3348OEUFxeza9cu5z4//fQTdrudoUOHNnubm5ojxB87dozVq1cTHh7ucnt7Ox5CiMapa/jjhT7++GN69epFamqq87rc3Nw6hz05bgPw9vbmhx9+4OzZs+Tl5XHttdc20asQQriLdK2vNmfOHKZPn86gQYMYMmQI7733HhUVFdx///2eblqTmzFjBp999hlLly4lKCjI+aYeEhKCn58fISEhPPjgg8yZM4ewsDCCg4OZNWsWw4cPZ9iwYR5uvXsFBQVd9OEYEBBAeHi48/r2ciwcnnrqKVJTU3njjTe4/fbb2b59Ox9++CEffvghABqNhtmzZ/Paa6/RrVs3OnfuzIsvvkhsbCxTp071bOPd7KabbuL1118nPj6ePn36sGfPHt59910eeOABoO0fi/Lyco4fP+68fOrUKfbu3UtYWBjx8fGXfe29evXi+uuv5+GHH2bhwoVUVVUxc+ZM7rjjDmJjYz30qhruUscjJiaGW2+9ld27d7N8+XJsNpvzvTUsLAy9Xt/mjocQomldbvij0Wjks88+48UXX2zwc1w4b4cQogXz9LT5Lcm8efOU+Ph4Ra/XK0OGDFG2bt3q6SY1C6DO7ZNPPnHuYzQalccff1wJDQ1V/P39lV/96ldKTk6O5xrdjGovP6co7fNYLFu2TOnbt6/i4+Oj9OzZU/nwww9dbrfb7cqLL76oREVFKT4+Psq1116rpKene6i1Tae0tFR58sknlfj4eMXX11fp0qWL8n//93+K2Wx27tOWj8XatWvrfK+YPn26oihX9trPnz+v3HnnnUpgYKASHBys3H///UpZWZkHXk3jXep4nDp1qt731rVr1zofoy0dDyFE05kxY4YSFxennDx5st59/vnPfyre3t5Kfn6+y/UvvviikpKS4nLdyZMnFUDZvXt3UzRXCNEMNIqiKM143kAIIYQQQghxBRRFYdasWXz99desW7eObt261bvvmDFjiIiI4KuvvnK5/vvvv+fGG28kJyfHWXH/8MMP+d3vfkd+fj4+Pj5N+hqEEE1DgrwQQgghhBAt0OOPP+4c/tijRw/n9Y7hjw7Hjx+ne/furFixguuvv97lMWw2G/379yc2Npa33nqL3Nxc7rnnHh566CHnijRCiNZHgrwQQgghhBAtkEajqfP6Tz75hPvuu895+YUXXmDJkiWcPn36oklZATIyMnjsscdYt24dAQEBTJ8+nTfffBMvL5kuS4jWSoK8EEIIIYQQQgjRisjyc0IIIYQQQgghRCsiQV4IIYQQQgghhGhFJMgLIYQQQgghhBCtiAR5IYQQQgghhBCiFZEgL4QQQgghhBBCtCIS5IUQQgghhBBCiFZEgrwQokFsNhupqancfPPNLteXlJTQqVMn/u///s9DLRNCCCGEEKJtk3XkhRANdvToUfr3789HH33EtGnTALj33nvZt28fO3bsQK/Xe7iFQgghhBBCtD0S5IUQjfLXv/6Vl19+mUOHDrF9+3Zuu+02duzYQUpKiqebJoQQQgghRJskQV4I0SiKojBu3Dh0Oh0HDhxg1qxZ/P73v/d0s4QQQgghhGizJMgLIRrtyJEj9OrVi+TkZHbv3o2Xl5enmySEEEIIIUSbJZPdCSEa7e9//zv+/v6cOnWKrKwsTzdHCCGEEEKINk0q8kKIRtm8eTOjR49m5cqVvPbaawCsXr0ajUbj4ZYJIYQQQgjRNklFXgjRYJWVldx333089thjjB07lo8//pjt27ezcOFCTzdNCCGEEEKINksq8kKIBnvyySdZsWIF+/btw9/fH4BFixbx9NNPc+DAARITEz3bQCGEEEIIIdogCfJCiAZZv3491157LevWrWPkyJEut02cOBGr1Spd7IUQQgghhGgCEuSFEEIIIYQQQohWRMbICyGEEEIIIYQQrYgEeSGEEEIIIYQQohWRIC+EEEIIIYQQQrQiEuSFEEIIIYQQQohWRIK8EEIIIYQQQgjRikiQF0IIIYQQQgghWhEJ8kIIIYQQQgghRCsiQV4IIYQQQgghhGhFJMgLIYQQQgghhBCtiAR5IYQQQgghhBCiFZEgL4QQQgghhBBCtCL/H/lZmnNfA3aJAAAAAElFTkSuQmCC", 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" + "
" ] }, "metadata": {}, @@ -144,8 +305,6 @@ "radii_data = mean_x + (X - mean_x)\n", "\n", "# Compute predicted θ values\n", - "# predicted_θ = angmod(cl_model.result[\"mu\"] + 2 * np.arctan(X * cl_model.result[\"beta\"][0]))\n", - "\n", "predicted_θ = cl_reg_mixed.predict(X[:, None])\n", "X_ = np.linspace(0, X.max(), 100)\n", "fitted_curve_mixed = cl_reg_mixed.predict(X_[:, None])\n", @@ -157,26 +316,114 @@ " X_[:, None] @ np.array([-0.0066])\n", ")\n", "\n", + "se_mu_mean = cl_reg_mean.result[\"se_mu\"] # Standard error of the mean\n", + "se_mu_mixed = cl_reg_mixed.result[\"se_mu\"] # Standard error for mixed model\n", + "se_mu_mixed_fisher = 0.0458\n", + "\n", + "# Compute upper and lower bounds for confidence intervals\n", + "fitted_curve_mean_upper = fitted_curve_mean + 1.96 * se_mu_mean\n", + "fitted_curve_mean_lower = fitted_curve_mean - 1.96 * se_mu_mean\n", + "\n", + "fitted_curve_mixed_upper = fitted_curve_mixed + 1.96 * se_mu_mixed\n", + "fitted_curve_mixed_lower = fitted_curve_mixed - 1.96 * se_mu_mixed\n", + "\n", + "fitted_curve_fisher_mixed_upper = fitted_curve_fisher_mixed + 1.96 * se_mu_mixed_fisher\n", + "fitted_curve_fisher_mixed_lower = fitted_curve_fisher_mixed - 1.96 * se_mu_mixed_fisher\n", + "\n", + "\n", "# Radial position of predicted points: fixed on the mean circle\n", "radii_predicted = mean_x + (X - mean_x) # Same radial framework as observed data\n", "# Plotting\n", - "fig, ax = plt.subplots(\n", - " figsize=(6, 6), subplot_kw={\"polar\": True}, constrained_layout=True\n", + "fig, ax = plt.subplot_mosaic(\n", + " mosaic=[[\"carte\", \"polar\"]],\n", + " figsize=(10, 5),\n", + " per_subplot_kw={\"polar\": {\"projection\": \"polar\"}},\n", + " constrained_layout=True,\n", ")\n", "\n", "# Plot observed data points\n", - "ax.scatter(θ, radii_data, color=\"black\", alpha=0.7, label=\"Data\")\n", + "ax[\"polar\"].scatter(θ, radii_data, color=\"black\", alpha=0.7, label=\"Data\")\n", "\n", "# Plot predicted points on the mean circle\n", - "ax.plot(fitted_curve_mixed, X_, color=\"C0\", label=\"Mixed\")\n", - "ax.plot(fitted_curve_fisher_mixed, X_, color=\"C0\", label=\"Fisher Mixed\", linestyle=\"--\")\n", + "ax[\"polar\"].plot(fitted_curve_mixed, X_, color=\"C0\", label=\"Mixed (pycircstat2)\")\n", + "ax[\"polar\"].plot(\n", + " fitted_curve_fisher_mixed,\n", + " X_,\n", + " color=\"C0\",\n", + " linestyle=\"--\",\n", + " label=\"Mixed (Fisher, 1993)\",\n", + ")\n", + "\n", + "ax[\"polar\"].plot(fitted_curve_mean, X_, color=\"C1\", label=\"Mean (pycircstat2)\")\n", + "ax[\"polar\"].plot(\n", + " fitted_curve_fisher_mean,\n", + " X_,\n", + " color=\"C1\",\n", + " linestyle=\"--\",\n", + " label=\"Mean (Fisher, 1993)\",\n", + ")\n", + "\n", "\n", - "ax.plot(fitted_curve_mean, X_, color=\"C1\", label=\"Mean\")\n", - "ax.plot(fitted_curve_fisher_mean, X_, color=\"C1\", label=\"Fisher Mean\", linestyle=\"--\")\n", + "# Cartesian plot for SE visualization\n", + "ax[\"carte\"].scatter(X, θ, color=\"black\", alpha=0.7, label=\"Data\")\n", + "ax[\"carte\"].plot(\n", + " X_,\n", + " fitted_curve_mixed,\n", + " color=\"C0\",\n", + " label=\"Mixed (ours)\",\n", + ")\n", + "ax[\"carte\"].fill_between(\n", + " X_,\n", + " fitted_curve_mixed_lower,\n", + " fitted_curve_mixed_upper,\n", + " color=\"C0\",\n", + " alpha=0.2,\n", + ")\n", + "\n", + "ax[\"carte\"].plot(\n", + " X_,\n", + " fitted_curve_fisher_mixed,\n", + " color=\"C0\",\n", + " linestyle=\"--\",\n", + " label=\"Mixed (Fisher, 1993)\",\n", + ")\n", + "\n", + "ax[\"carte\"].plot(\n", + " X_,\n", + " fitted_curve_mean,\n", + " color=\"C1\",\n", + " label=\"Mean (ours)\",\n", + ")\n", + "ax[\"carte\"].fill_between(\n", + " X_,\n", + " fitted_curve_mean_lower,\n", + " fitted_curve_mean_upper,\n", + " color=\"C1\",\n", + " alpha=0.2,\n", + ")\n", "\n", - "# Add labels and legend\n", - "ax.set_title(\"Circular-Linear Regression (Mixed vs Mean)\", pad=40)\n", - "ax.legend(loc=\"upper right\", bbox_to_anchor=(1.2, 1.1), frameon=False)" + "ax[\"carte\"].plot(\n", + " X_,\n", + " fitted_curve_fisher_mean,\n", + " color=\"C1\",\n", + " linestyle=\"--\",\n", + " label=\"Mean (Fisher, 1993)\",\n", + ")\n", + "ax[\"carte\"].fill_between(\n", + " X_,\n", + " fitted_curve_fisher_mixed_lower,\n", + " fitted_curve_fisher_mixed_upper,\n", + " color=\"C0\",\n", + " alpha=0.2,\n", + ")\n", + "\n", + "\n", + "ax[\"carte\"].set_xlabel(\"X\")\n", + "ax[\"carte\"].set_ylabel(\"θ\")\n", + "ax[\"carte\"].set_title(\"Circular-Linear Regression (Mixed vs Mean)\")\n", + "ax[\"carte\"].axhline(0, color=\"black\", linestyle=\"--\", alpha=0.5)\n", + "ax[\"carte\"].axhline(2 * np.pi, color=\"black\", linestyle=\"--\", alpha=0.5)\n", + "ax[\"carte\"].legend(loc=\"best\", frameon=False)" ] }, { @@ -188,14 +435,14 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Last updated: 2024-12-17 16:57:18CET\n", + "Last updated: 2024-12-18 13:13:59CET\n", "\n", "Python implementation: CPython\n", "Python version : 3.12.8\n", @@ -204,9 +451,9 @@ "pycircstat2: 0.1.6\n", "\n", "numpy : 2.2.0\n", + "pycircstat2: 0.1.6\n", "pandas : 2.2.3\n", "matplotlib : 3.10.0\n", - "pycircstat2: 0.1.6\n", "\n", "Watermark: 2.5.0\n", "\n" diff --git a/pycircstat2/regression.py b/pycircstat2/regression.py index 7fd9b07..77bb3b6 100644 --- a/pycircstat2/regression.py +++ b/pycircstat2/regression.py @@ -1,10 +1,12 @@ -from typing import Dict, List, Optional, Tuple, Union +from typing import List, Optional, Tuple, Union import numpy as np import pandas as pd -from scipy.special import i0, i1, ive +from scipy.special import i0, i1 from scipy.stats import norm +from .utils import significance_code + __all__ = ["CLRegression", "LCRegression", "CCRegression"] @@ -239,7 +241,7 @@ def _fit(self): beta, alpha, gamma = beta_new, alpha_new, gamma_new log_likelihood_old = log_likelihood - return { + result = { "beta": beta, "alpha": alpha, "gamma": gamma, @@ -248,6 +250,159 @@ def _fit(self): "log_likelihood": log_likelihood, } + se_result = self._compute_standard_errors(result) + + result.update(se_result) + + return result + + def _compute_standard_errors(self, result): + """ + Compute standard errors for the parameters based on the fitted model. + """ + theta = self.theta + X = self.X + n = len(theta) + kappa = result["kappa"] + beta = result["beta"] + gamma = result["gamma"] + alpha = result["alpha"] + + se_results = {} + + if self.model_type == "mean": + # Mean Direction Model + G = 2 * X / (1 + (X @ beta) ** 2)[:, None] + A = np.eye(n) * (kappa * self._A1(kappa)) + XtAX = G.T @ A @ G + cov_beta = np.linalg.solve(XtAX, np.eye(XtAX.shape[0])) + se_beta = np.sqrt(np.diag(cov_beta)) + + se_mu = 1 / np.sqrt((n - X.shape[1]) * kappa * self._A1(kappa)) + se_kappa = np.sqrt( + 1 / (n * (1 - self._A1(kappa) ** 2 - self._A1(kappa) / kappa)) + ) + + se_results.update( + { + "se_beta": se_beta, + "se_mu": se_mu, + "se_kappa": se_kappa, + } + ) + + elif self.model_type == "kappa": + # Concentration Parameter Model + X1 = np.column_stack((np.ones(n), X)) # Add intercept + W = np.diag( + (np.exp(X1 @ np.hstack([alpha, gamma])) ** 2) * self._A1_prime(kappa) + ) + XtWX = X1.T @ W @ X1 + + cov_gamma_alpha = np.linalg.solve(XtWX, np.eye(XtWX.shape[0])) + + se_alpha = np.sqrt(cov_gamma_alpha[0, 0]) + se_gamma = np.sqrt(np.diag(cov_gamma_alpha[1:, 1:])) + + se_mu = 1 / np.sqrt(np.sum(kappa * self._A1(kappa)) - 0.5) + + se_kappa = np.sqrt(1 / (n * self._A1_prime(kappa))) + + se_results.update( + { + "se_alpha": se_alpha, + "se_gamma": se_gamma, + "se_mu": se_mu, + "se_kappa": se_kappa, + } + ) + + elif self.model_type == "mixed": + # Mixed Model + G = 2 * X / (1 + (X @ beta) ** 2)[:, None] + K = np.diag(kappa * self._A1(kappa)) + XtGKGX = G.T @ K @ G + + cov_beta = np.linalg.solve(XtGKGX, np.eye(XtGKGX.shape[0])) + se_beta = np.sqrt(np.diag(cov_beta)) + + X1 = np.column_stack((np.ones(n), X)) # Add intercept + W_gamma = np.diag( + (np.exp(X1 @ np.hstack([alpha, gamma])) ** 2) * self._A1_prime(kappa) + ) + XtWX_gamma = X1.T @ W_gamma @ X1 + + # Check positive definiteness and regularize if needed + eigenvalues_gamma = np.linalg.eigvals(XtWX_gamma) + if np.any(eigenvalues_gamma <= 0): + XtWX_gamma += np.eye(XtWX_gamma.shape[0]) * 1e-8 + + cov_gamma_alpha = np.linalg.solve(XtWX_gamma, np.eye(XtWX_gamma.shape[0])) + se_alpha = np.sqrt(cov_gamma_alpha[0, 0]) + se_gamma = np.sqrt(np.diag(cov_gamma_alpha[1:, 1:])) + + se_mu = 1 / np.sqrt(np.sum(kappa * self._A1(kappa)) - 0.5) + se_kappa = np.sqrt( + 1 / (n * (1 - self._A1(kappa) ** 2 - self._A1(kappa) / kappa)) + ) + se_results.update( + { + "se_beta": se_beta, + "se_alpha": se_alpha, + "se_gamma": se_gamma, + "se_mu": se_mu, + "se_kappa": se_kappa, + } + ) + + else: + raise ValueError(f"Unknown model type: {self.model_type}") + + return se_results + + def AIC(self): + """ + Calculate Akaike Information Criterion (AIC). + """ + if self.result is None: + raise ValueError("Model must be fitted before calculating AIC.") + + log_likelihood = self.result["log_likelihood"] + if self.model_type == "mean": + n_params = len(self.result["beta"]) # Only beta + elif self.model_type == "kappa": + n_params = 1 + len(self.result["gamma"]) # alpha + gamma + elif self.model_type == "mixed": + n_params = ( + 1 + len(self.result["beta"]) + len(self.result["gamma"]) + ) # alpha + beta + gamma + else: + raise ValueError(f"Unknown model type: {self.model_type}") + + return -2 * log_likelihood + 2 * n_params + + def BIC(self): + """ + Calculate Bayesian Information Criterion (BIC). + """ + if self.result is None: + raise ValueError("Model must be fitted before calculating BIC.") + + log_likelihood = self.result["log_likelihood"] + n = len(self.theta) + if self.model_type == "mean": + n_params = len(self.result["beta"]) # Only beta + elif self.model_type == "kappa": + n_params = 1 + len(self.result["gamma"]) # alpha + gamma + elif self.model_type == "mixed": + n_params = ( + 1 + len(self.result["beta"]) + len(self.result["gamma"]) + ) # alpha + beta + gamma + else: + raise ValueError(f"Unknown model type: {self.model_type}") + + return -2 * log_likelihood + n_params * np.log(n) + def predict(self, X_new): """ Predict circular response values for new predictor values. @@ -289,19 +444,19 @@ def summary(self): if self.model_type in ["mean", "mixed"] and self.result["beta"] is not None: print("Coefficients for Mean Direction (Beta):\n") print( - f"{'':<5} {'Estimate':<12} {'Std. Error':<12} {'t value':<10} {'Pr(>|t|)':<12}" + f"{'':<5} {'Estimate':<12} {'Std. Error':<12} {'t value':<10} {'Pr(>|t|)'}" ) for i, coef in enumerate(self.result["beta"]): # Placeholder for standard error and p-values - se_beta = np.nan # Replace with actual computation later - t_value = coef / se_beta if se_beta else np.nan + se_beta = self.result["se_beta"][i] + t_value = np.abs(coef / se_beta) if se_beta else np.nan p_value = ( 2 * (1 - norm.cdf(np.abs(t_value))) if not np.isnan(t_value) else np.nan ) print( - f"β_{i:<3} {coef:<12.5f} {se_beta:<12.5f} {t_value:<10.2f} {p_value:<12.5f}" + f"β{i:<3} {coef:<12.5f} {se_beta:<12.5f} {t_value:<10.2f} {p_value:<12.5f}{significance_code(p_value):<3}" ) # Coefficients for concentration parameter (Gamma) @@ -310,9 +465,21 @@ def summary(self): print( f"{'':<5} {'Estimate':<12} {'Std. Error':<12} {'t value':<10} {'Pr(>|t|)':<12}" ) + # Report alpha as the first coefficient + alpha = self.result["alpha"] + se_alpha = self.result["se_alpha"] + t_value_alpha = alpha / se_alpha if se_alpha else np.nan + p_value_alpha = ( + 2 * (1 - norm.cdf(np.abs(t_value_alpha))) + if not np.isnan(t_value_alpha) + else np.nan + ) + print( + f"α{"":<5} {alpha:<12.5f} {se_alpha:<12.5f} {t_value_alpha:<10.2f} {p_value_alpha:<12.5f}{significance_code(p_value_alpha)}" + ) for i, coef in enumerate(self.result["gamma"]): # Placeholder for standard error and p-values - se_gamma = np.nan # Replace with actual computation later + se_gamma = self.result["se_gamma"][i] t_value = coef / se_gamma if se_gamma else np.nan p_value = ( 2 * (1 - norm.cdf(np.abs(t_value))) @@ -320,34 +487,38 @@ def summary(self): else np.nan ) print( - f"γ_{i:<3} {coef:<12.5f} {se_gamma:<12.5f} {t_value:<10.2f} {p_value:<12.5f}" + f"γ{i:<5} {coef:<12.5f} {se_gamma:<12.5f} {t_value:<10.2f} {p_value:<12.5f}{significance_code(p_value)}" ) - # Intercept (Alpha) for concentration - if self.model_type in ["kappa", "mixed"] and not np.isnan(self.result["alpha"]): - print("\nIntercept for Concentration (Alpha):") - print(f" Estimate: {self.result['alpha']:.5f}") - # Summary for mu and kappa print("\nSummary:") print(" Mean Direction (mu) in radians:") mu = self.result["mu"] - se_mu = np.nan # Placeholder for standard error - print(f" mu: {mu:.5f} (SE: {se_mu:.5f})") + se_mu = self.result["se_mu"] + print(f" μ: {mu:.5f} (SE: {se_mu:.5f})") print("\n Concentration Parameter (kappa):") kappa = self.result["kappa"] - se_kappa = np.nan # Placeholder for standard error + se_kappa = self.result["se_kappa"] if isinstance(kappa, np.ndarray): - print(f" kappa: {np.mean(kappa):.5f} (SE: {se_kappa:.5f})") + print(" Index kappa Std. Error") + for i, (k, se) in enumerate(zip(kappa, se_kappa), start=1): + print(f" [{i}] {k:>10.5f} {se:>10.5f}") + print(f" Mean: {np.mean(kappa):.5f} (SE: {np.mean(se_kappa):.5f})") else: - print(f" kappa: {kappa:.5f} (SE: {se_kappa:.5f})") + print(f" κ: {kappa:.5f} (SE: {se_kappa:.5f})") - # Log-likelihood - print(f"\nLog-Likelihood: {self.result.get('log_likelihood', 'NA'):.5f}") + # Summary for model fit metrics + print("\nModel Fit Metrics:\n") + print(f"{'Metric':<12} {'Value':<12}") + log_likelihood = self.result.get("log_likelihood", float("nan")) + nll = -log_likelihood # Negative log-likelihood + print(f"{'nLL':<12} {nll:<12.5f}") + print(f"{'AIC':<12} {self.AIC():<12.5f}") + print(f"{'BIC':<12} {self.BIC():<12.5f}") # Notes - print("\nSignif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1") + print("\nSignif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1") print("p-values are approximated using the normal distribution.\n") diff --git a/tests/test_regression.py b/tests/test_regression.py index 427c905..cca4336 100644 --- a/tests/test_regression.py +++ b/tests/test_regression.py @@ -24,36 +24,36 @@ def test_cl_regression_against_r(): # Expected values from R expected_beta = -0.008317 - # expected_se_beta = 0.001359 + expected_se_beta = 0.001359 expected_mu = 2.426 - # expected_se_mu = 0.1119 + expected_se_mu = 0.1119 expected_kappa = 3.224 - # expected_se_kappa = 0.7159 + expected_se_kappa = 0.7159 expected_log_likelihood = 27.76 # Assert coefficients assert np.isclose( result["beta"][0], expected_beta, atol=1e-3 ), f"Expected beta: {expected_beta}, got: {result['beta'][0]}" - # assert np.isclose( - # result["se_beta"][0], expected_se_beta, atol=1e-3 - # ), f"Expected SE(beta): {expected_se_beta}, got: {result['se_beta'][0]}" + assert np.isclose( + result["se_beta"][0], expected_se_beta, atol=1e-3 + ), f"Expected SE(beta): {expected_se_beta}, got: {result['se_beta'][0]}" # Assert mean direction (mu) assert np.isclose( result["mu"], expected_mu, atol=1e-2 ), f"Expected mu: {expected_mu}, got: {result['mu']}" - # assert np.isclose( - # result["se_mu"], expected_se_mu, atol=1e-2 - # ), f"Expected SE(mu): {expected_se_mu}, got: {result['se_mu']}" + assert np.isclose( + result["se_mu"], expected_se_mu, atol=1e-2 + ), f"Expected SE(mu): {expected_se_mu}, got: {result['se_mu']}" # Assert concentration parameter (kappa) assert np.isclose( result["kappa"], expected_kappa, atol=1e-2 ), f"Expected kappa: {expected_kappa}, got: {result['kappa']}" - # assert np.isclose( - # result["se_kappa"], expected_se_kappa, atol=1e-2 - # ), f"Expected SE(kappa): {expected_se_kappa}, got: {result['se_kappa']}" + assert np.isclose( + result["se_kappa"], expected_se_kappa, atol=1e-2 + ), f"Expected SE(kappa): {expected_se_kappa}, got: {result['se_kappa']}" # Assert log-likelihood assert np.isclose(