{ "cells": [ { "cell_type": "markdown", "id": "ed5cfd16", "metadata": {}, "source": [ "# Hurricane multiverse (non-neuroimaging)\n", "\n", "The Comet toolbox is developed primarily for fMRI brain network analyses. However, we here showcases how the versatile multiverse workflow can also be applied outside of neuroimaging.\n", "\n", "This script is a re-implementation og the famous *“Female hurricanes are deadlier than male hurricanes”* multiverse analysis originally presented in [Simonsohn et al. (2020)](https://www.nature.com/articles/s41562-020-0912-z). Their study revisited [Jung et al. (2014)](https://www.pnas.org/doi/full/10.1073/pnas.1402786111), who reported that hurricanes with more feminine names caused more fatalities. Simonsohn and colleagues systematically explored how robust this conclusion is across a large range of reasonable analytic specifications.\n", "\n", "The Comet toolbox provides a Python-native multiverse framework that allows the entire hurricane multiverse analysis to be expressed with two simple objects:\n", "\n", "- A dictionary of forking paths\n", "- A single analysis template function containing placeholders for all decisions\n", "\n", "Existing examples (R implementations) of this example can be found here:\n", "\n", "- multiverse package: https://cran.r-project.org/web/packages/multiverse/vignettes/example-hurricane.html\n", "- mverse package: https://mverseanalysis.github.io/mverse/index.html" ] }, { "cell_type": "code", "execution_count": 1, "id": "488e043d", "metadata": {}, "outputs": [], "source": [ "from comet.multiverse import Multiverse\n", "\n", "forking_paths = {\n", " \"death_outliers\": [2, 1, 0], # Drop n hurricanes with the most deaths\n", " \"damage_outliers\": [3, 2, 1, 0], # Drop n hurricanes with the most damage\n", "\n", " \"femininity_rating\": [\"fem_likert\", \"fem_binary\"], # Femininity rating (11-point likert or binary)\n", " \"damage_functional\": [\"ln\", \"linear\"], # Damage functional (ln or no transformation)\n", "\n", " \"effect_type\": [\"femininity * damages\",\n", " \"femininity * damages + femininity * zpressure\",\n", " \"femininity * damages + femininity * zwind\",\n", " \"femininity * damages + femininity * zcat\",\n", " \"femininity * damages + femininity * z3\",\n", " \"femininity + damages + z3\"], # Interactions or main effect only)\n", " \"year_interaction\": [\"\", \" + post1979:damages\", \" + year:damages\"], # Interactions with year\n", " \"model\": [\"log_linear\", \"neg_binomial\"] # Model (negative binomial or log-linear)\n", "}\n", "\n", "def analysis_template():\n", " import comet\n", " import numpy as np\n", " import statsmodels.api as sm\n", " import statsmodels.formula.api as smf\n", "\n", " # Load hurricane data\n", " df = comet.utils.load_example(\"hurricane\")\n", "\n", " # Create derived predictors\n", " df[\"post1979\"] = (df[\"elapsed_years\"] > 1979).astype(int)\n", " df[\"zcat\"] = (df[\"category\"] - df[\"category\"].mean()) / df[\"category\"].std()\n", " df[\"zpressure\"] = -((df[\"pressure\"] - df[\"pressure\"].mean()) / df[\"pressure\"].std())\n", " df[\"zwind\"] = (df[\"wind\"] - df[\"wind\"].mean()) / df[\"wind\"].std()\n", " df[\"z3\"] = (df[\"zpressure\"] + df[\"zcat\"] + df[\"zwind\"]) / 3.0\n", "\n", " # Decisions 1 & 2: Exclude outliers\n", " top_deaths = df[\"deaths\"].nlargest({{death_outliers}}).unique()\n", " top_damage = df[\"damages\"].nlargest({{damage_outliers}}).unique()\n", " df = df[~df[\"deaths\"].isin(top_deaths) & ~df[\"damages\"].isin(top_damage)]\n", "\n", " # Decision 2: Choose femininity rating\n", " df[\"femininity\"] = df[{{femininity_rating}}]\n", "\n", " # Decision 3: Transform damage variable\n", " if {{damage_functional}} == \"ln\":\n", " df[\"damages\"] = np.log(df[\"damages\"])\n", "\n", " # Decision 4 & 5: Effect type & account for year\n", " formula = \"deaths ~ \" + {{effect_type}} + {{year_interaction}}\n", "\n", " # Decision 6: Model type and fitting\n", " if {{model}} == \"log_linear\":\n", " df[\"deaths\"] = np.log(df[\"deaths\"] + 1)\n", " fit = smf.ols(formula, data=df).fit()\n", " else:\n", " fit = smf.glm(formula, data=df, family=sm.families.NegativeBinomial(alpha=1)).fit()\n", "\n", " # Results: Set femininity for male vs female and predict deaths at the sample means\n", " if {{femininity_rating}} == \"fem_likert\":\n", " fem_male = df[\"femininity\"][df[\"fem_binary\"] == 0].mean()\n", " fem_fem = df[\"femininity\"][df[\"fem_binary\"] == 1].mean()\n", " else:\n", " fem_male = 0\n", " fem_fem = 1\n", "\n", " base = df.mean(numeric_only=True).to_frame().T\n", "\n", " base_male = base.copy()\n", " base_male[\"femininity\"] = fem_male\n", "\n", " base_fem = base.copy()\n", " base_fem[\"femininity\"] = fem_fem\n", "\n", " if {{model}} == \"log_linear\":\n", " # Predict and back-transform (slightly simplified)\n", " pred_m = np.exp(fit.predict(base_male)) - 1\n", " pred_f = np.exp(fit.predict(base_fem)) - 1\n", " else:\n", " pred_m = fit.predict(base_male)\n", " pred_f = fit.predict(base_fem)\n", "\n", " # Get the additional deaths as multiverse outcome measure\n", " extra_deaths = pred_f.values - pred_m.values\n", " # The p-values mix interaction with main effect only so its a bit hacky, but good enough for illustration\n", " p_val = fit.pvalues[\"femininity:damages\"] if \"femininity:damages\" in fit.pvalues.index else fit.pvalues[\"femininity\"] \n", " \n", " comet.utils.save_universe_results({\"extra_deaths\": extra_deaths, \"p_val\": p_val})" ] }, { "cell_type": "code", "execution_count": 2, "id": "c2925495", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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UniverseDecision 1Value 1Decision 2Value 2Decision 3Value 3Decision 4Value 4Decision 5Value 5Decision 6Value 6Decision 7Value 7
0Universe_1death_outliers2damage_outliers3femininity_ratingfem_likertdamage_functionallneffect_typefemininity * damagesyear_interactionNaNmodellog_linear
1Universe_2death_outliers2damage_outliers3femininity_ratingfem_likertdamage_functionallneffect_typefemininity * damagesyear_interactionNaNmodelneg_binomial
2Universe_3death_outliers2damage_outliers3femininity_ratingfem_likertdamage_functionallneffect_typefemininity * damagesyear_interaction+ post1979:damagesmodellog_linear
3Universe_4death_outliers2damage_outliers3femininity_ratingfem_likertdamage_functionallneffect_typefemininity * damagesyear_interaction+ post1979:damagesmodelneg_binomial
4Universe_5death_outliers2damage_outliers3femininity_ratingfem_likertdamage_functionallneffect_typefemininity * damagesyear_interaction+ year:damagesmodellog_linear
................................................
1723Universe_1724death_outliers0damage_outliers0femininity_ratingfem_binarydamage_functionallineareffect_typefemininity + damages + z3year_interactionNaNmodelneg_binomial
1724Universe_1725death_outliers0damage_outliers0femininity_ratingfem_binarydamage_functionallineareffect_typefemininity + damages + z3year_interaction+ post1979:damagesmodellog_linear
1725Universe_1726death_outliers0damage_outliers0femininity_ratingfem_binarydamage_functionallineareffect_typefemininity + damages + z3year_interaction+ post1979:damagesmodelneg_binomial
1726Universe_1727death_outliers0damage_outliers0femininity_ratingfem_binarydamage_functionallineareffect_typefemininity + damages + z3year_interaction+ year:damagesmodellog_linear
1727Universe_1728death_outliers0damage_outliers0femininity_ratingfem_binarydamage_functionallineareffect_typefemininity + damages + z3year_interaction+ year:damagesmodelneg_binomial
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1728 rows × 15 columns

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" ], "text/plain": [ " Universe Decision 1 Value 1 Decision 2 Value 2 \\\n", "0 Universe_1 death_outliers 2 damage_outliers 3 \n", "1 Universe_2 death_outliers 2 damage_outliers 3 \n", "2 Universe_3 death_outliers 2 damage_outliers 3 \n", "3 Universe_4 death_outliers 2 damage_outliers 3 \n", "4 Universe_5 death_outliers 2 damage_outliers 3 \n", "... ... ... ... ... ... \n", "1723 Universe_1724 death_outliers 0 damage_outliers 0 \n", "1724 Universe_1725 death_outliers 0 damage_outliers 0 \n", "1725 Universe_1726 death_outliers 0 damage_outliers 0 \n", "1726 Universe_1727 death_outliers 0 damage_outliers 0 \n", "1727 Universe_1728 death_outliers 0 damage_outliers 0 \n", "\n", " Decision 3 Value 3 Decision 4 Value 4 Decision 5 \\\n", "0 femininity_rating fem_likert damage_functional ln effect_type \n", "1 femininity_rating fem_likert damage_functional ln effect_type \n", "2 femininity_rating fem_likert damage_functional ln effect_type \n", "3 femininity_rating fem_likert damage_functional ln effect_type \n", "4 femininity_rating fem_likert damage_functional ln effect_type \n", "... ... ... ... ... ... \n", "1723 femininity_rating fem_binary damage_functional linear effect_type \n", "1724 femininity_rating fem_binary damage_functional linear effect_type \n", "1725 femininity_rating fem_binary damage_functional linear effect_type \n", "1726 femininity_rating fem_binary damage_functional linear effect_type \n", "1727 femininity_rating fem_binary damage_functional linear effect_type \n", "\n", " Value 5 Decision 6 Value 6 \\\n", "0 femininity * damages year_interaction NaN \n", "1 femininity * damages year_interaction NaN \n", "2 femininity * damages year_interaction + post1979:damages \n", "3 femininity * damages year_interaction + post1979:damages \n", "4 femininity * damages year_interaction + year:damages \n", "... ... ... ... \n", "1723 femininity + damages + z3 year_interaction NaN \n", "1724 femininity + damages + z3 year_interaction + post1979:damages \n", "1725 femininity + damages + z3 year_interaction + post1979:damages \n", "1726 femininity + damages + z3 year_interaction + year:damages \n", "1727 femininity + damages + z3 year_interaction + year:damages \n", "\n", " Decision 7 Value 7 \n", "0 model log_linear \n", "1 model neg_binomial \n", "2 model log_linear \n", "3 model neg_binomial \n", "4 model log_linear \n", "... ... ... \n", "1723 model neg_binomial \n", "1724 model log_linear \n", "1725 model neg_binomial \n", "1726 model log_linear \n", "1727 model neg_binomial \n", "\n", "[1728 rows x 15 columns]" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "mverse = Multiverse(name=\"example_mv_hurricane\")\n", "mverse.create(analysis_template, forking_paths)\n", "mverse.summary()" ] }, { "cell_type": "code", "execution_count": 3, "id": "f2112fe1", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Starting multiverse analysis for all universes...\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "8f492b0ac54240d3843db15a9fc2ff26", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Performing multiverse analysis:: 0%| | 0/1728 [00:00" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "mverse.specification_curve(\"extra_deaths\", figsize=(12,9), height_ratio=(1,2), line_pad=0.05)" ] }, { "cell_type": "markdown", "id": "b1568b1c", "metadata": {}, "source": [ "However, for large multiverses this type of visualisation can become difficult to interpret. A better alternative is a multiverse plot, which visualises the results as a density function and groups the specifications into bins. \n", "\n", "Here it becomes easily visible how most effects are close to 0 and not significant:" ] }, { "cell_type": "code", "execution_count": 5, "id": "3f93b28c", "metadata": {}, "outputs": [ { "data": { "image/png": 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QH1dSTuXw+eqK/wEgIiLVy/Hjx+nduzeff/45W7duJTExke+++45XXnmFm2666Zzt77zzTsxmM6NGjWLXrl38+uuvvPbaawBVevsyV1dXJk6cyOOPP85nn31GQkICq1evZubMmUBRkE1KSuLrr78mISGBt99+m9mzZ1e4TlhYGGvWrOHAgQMcO3ZMo60XoKAqIlJDhIWFWS95X1JaZh7L9hwFYFDbmjntt5iLowOP9mkCwPtLE8jILbBzRyIiNUBeLuRkV/1X3sWv2ns2T09POnXqxPTp0+nRowetWrViypQpjBw5knffffec7b29vfm///s/Nm/eTNu2bXnyySeZOnUqQKnzVqvClClT+Ne//sXUqVNp3rw5t912m/X80htvvJFx48YxZswY2rZty8qVK5kyZUqFa0yYMAEHBwdatGiBv7//Oee4yt8Mi8Wi+wCIiNRgX65J4onZ22gR7M3P/7za3u1ctoJCM33fWMaB41k81q+ZdTqwiIicJScblv8MGadtV9PTC3pcV3RfVRv54osvuPfee0lPT7/ouaRy5XC0dwMiIlI+R48e5dtvv2Xo0KH4+/tbl/+8regiSje0CbZXa5XK0cHE2L5NGfvNZj5avp+7uzTC29Xp4juKiNQ2rm5FoTE/7+LbVhYn5yoPqZ999hkRERHUr1+fLVu2MHHiRIYOHaqQWssoqIqI1BB//vknY8aMoUuXLtagmpaZx6r9x4Gi29JcKQa2CeG9JfvYm5rBzN8TGXdNU3u3JCJSPbm62XR00xZSUlKYOnUqKSkpBAcHc+utt/Liiy/auy2xMZ2jKiJSg/26I4VCs4WWId40quth73YqjYPJYGzfonD6yYpETmTacLRARETs6vHHH+fAgQPk5OSQmJjI9OnTcXd3t3dbYmMKqiIiNVjxtN/rrqDR1GIDWgURFeTF6dwCPvp9v73bERERERtSUBURqaHSMvNYmXDlTfstZjIZjD8z5TfujwMcy6j41SZFRESkZlJQFRGpIby8vLj22mvx8vIC4Lcz035bBHsTVu/KmfZb0jUtAmkd6kN2fiEfLk2wdzsiIiJiIwqqIiI1RJMmTfj1119p0qToPqPzzkz7vb71lTeaWsww/h5V/e/qgxw5lWPnjkRERMQWFFRFRGqIwsJCTp06RWFhISdKTPu9Es9PLalnU3/aN6pDboGZ95fss3c7IiIiYgMKqiIiNcSWLVvw8fFhy5YtLNh5hEKzhebB3oRfodN+ixmGwb/OjKp+tfZPDp3MtnNHIiIiUtUUVEVEaqDfdh4BoH/LIDt3YhtdI+vROcKPvEIz7y7ea+92REREpIopqIqI1DC5BRZW7DsKFF1sqLb417XNAPhu/V8kHc+yczciIiJSlRRURURqmC1HcsnJN1Pf143mwV72bsdmOob50aOpPwVmC28t0qiqiIjIlUxBVUSkhll7qOjKt9e0CMQwDDt3Y1vFVwCevekvEo5m2LkbERERqSoKqiIiNUR0dDTJKUfYfLQAgGtr0bTfYm0b+NK3eQBmC7y5UKOqIiIiVyoFVRGRGsLJyYk/sx1Jy8zH29WRjuF+9m7JLsadGVWdu/Uw8Smn7dyNiIiIVAUFVRGRGiIhIYF/vPAhAL2jAnByqJ2/wluG+DCgVRAWC0xfsMfe7YiIiEgVqJ1/5YiI1EAnT54k2VQPgL61cNpvSeOuaYphwPwdKWw/lG7vdkRERKSSKaiKiNQQh04X4ORXH0cT9Gzqb+927KppoBc3tgkBNKoqIiJyJVJQFRGpIdYeygWgVYALXq5Odu7G/v7ZpwkmAxbtTmVj0gl7tyMiIiKVSEFVRKSGWHu46LY0V4W42LmT6iHC35ObY0IBjaqKiIhcaRRURaTW279/v71buKjU0znsPZ4PwMD2YfZtphr5Z58mOJoMft97jLWJafZuR0RERCqJgqqI1HqRkZH06tWLzz//nJycHHu3U6bFu1KxAK1DfYhu3MDe7VQbDfzcGdqx6P147bd4LBaLnTsSERGRyqCgKiK13saNG2ndujXjx48nKCiIBx98kLVr19q7rVIW7DwCQLD5KCdO6HzMksb0isTZwcTaxDT+2Hfc3u2IiIhIJVBQFZFar23btrz11lscPnyYTz75hOTkZLp3706rVq144403OHr0qF37y8orYMW+YwB8+vw4EhMT7dpPdRPi68adnRoC8PoCjaqKiIhcCRRURUTOcHR05Oabb+a7777j3//+N/v27WPChAk0aNCAe+65h+TkZLv0tXzPMXILzAR6OJB/7KBdeqjuHoptjIujiU1JJ1kab98PFkREROTyKaiKiJyxfv16HnroIYKDg3njjTeYMGECCQkJLFiwgMOHD3PTTTfZpa/iab8dQ1ztUr8mCPB25Z4ujQB4Y8EejaqKiIjUcAqqIlLrvfHGG0RHR9O1a1cOHz7MZ599xsGDB3nhhRcIDw/n6quvJi4ujo0bN9q8t4JCM4t3FwXVq+rrtjQXMrpnY9ydHdh2KJ3fzoR7ERERqZkUVEWk1vvggw+48847OXjwIHPmzOGGG27AZCr96zEgIICZM2favLcNB09wIisfHzcnYhr40K5dO9zc3GzeR01Q19OFe7uFAfDGb3swmzWqKiIiUlMZFs2PEpFa7sCBAzRs2PCccGqxWPjzzz9p2LChnTqDF+bu5D8rEhncrj7Tb2trtz5qipNZeVz97yWczi3gnTvaMbBNiL1bEhERkUugEVURqfUaN27MsWPHzlmelpZGeHi4HToqYrFYWLCraArrNS0C7dZHTeLr7sz9Vxf9zN5cuIdCjaqKiIjUSAqqIlLrnW9iSUZGBq6u9ruA0d7UDA4ez8LZwUSPpv5s2rQJFxcXNm3aZLeeaoL7uofj4+ZEwtFMftx8yN7tiIiIyCVwtHcDIiL2Mn78eAAMw2Dq1Km4u7tb1xUWFrJmzRratm1rp+7+vtpv18i6eLo4YrFYyMvL0xVtL8Lb1YlRPSJ49dd43lq0l4FtQnBy0OeyIiIiNYmCqojUWsUjkxaLhW3btuHs7Gxd5+zsTJs2bZgwYYK92rMGVU37rbgRXcP4ZEUiB49n8b8Nf3H7VfY7z1hEREQqTkFVRGqtJUuWAHDvvffy1ltv4e3tbeeO/pZ6KofNf54EoG9zBdWK8nBx5B+xjXlh3i7eWrSXm9rWx83Zwd5tiYiISDlpLpSI1HqffvpptQqpAAt3pQLQpoEvgd72O0+2JrurcyPq+7qRnJ7DJ38k2rsdERERqQCNqIpIrXTzzTcTFxeHt7c3N9988wW3/eGHH2zU1d8W7EwB4NoS036bN2/O9u3biYiIsHk/NZGrkwOP9WvG2G828/6SfQzt0AB/Lxd7tyUiIiLloBFVEamVfHx8MAzD+vhCX7aWmVvAHwnHgdLnp7q5udGyZUvc3Nxs3lNNdWObEFqH+pCZV8j0hXvs3Y6IiIiUk2HR5SNFRKqVX7Yl848vNtLQz51lj8VaA/XBgwd5/vnnmTJlCo0aNbJzlzXHmv3Hue2j1ZgMmD+2B00DvezdkoiIiFyERlRFpNbLzs4mKyvL+vzgwYO8+eab/Pbbb3bp57czV/u9tkWgNaQCHD9+nJkzZ3L8+HG79FVTdYqoy7UtAjFbYNrPu+zdjoiIiJSDgqqI1Ho33XQTn332GQAnT57kqquu4vXXX+emm27igw8+sGkv+YVmFu8uupDStS2DbFr7SjZpQBSOJoMl8UdZsfeYvdsRERGRi1BQFZFab+PGjVx99dUAfP/99wQFBXHw4EE+++wz3n77bZv2si4xjfTsfPw8nGnfqI5Na1/JIvw9uatz0XTpF+btpNCss15ERESqMwVVEan1srKy8PIqOm/xt99+4+abb8ZkMtG5c2cOHjxo016Kp/32iQrAwWRcZGupiEf7NMHL1ZHdKaf5fsOf9m5HRERELkBBVURqvcjISObMmcOff/7Jr7/+yrXXXgtAamqqTe+varFYWFB8fmoZ034DAwOZNGkSgYGB56yTi/PzcObR3k0AeGV+POnZ+XbuSERERM5HQVVEar2pU6cyYcIEwsLC6NSpE126dAGKRlfbtWtnsz52HD7FoZPZuDqZ6B5Z75z19evXZ9q0adSvX99mPV1phncNo7G/B8cz85i+QLerERERqa4UVEWk1rvllltISkpi/fr1zJ8/37q8T58+TJ8+3WZ9FI+m9mjij5uzwznrT58+zdKlSzl9+rTNerrSODuaeObGlgB8tuoAu5JP2bkjERERKYuCqogIEBQURLt27TCZ/v61eNVVVxEVFWWzHn67wLRfgL1799KrVy/27t1rs56uRFc38WdAqyDMFnj6px3oduIiIiLVj6O9GxARsbfMzExefvllFi1aRGpqKmazudT6/fv3V3kPf6ZlsSv5FCYDekcFVHm92u7J65uzJD6VtYlp/N/WZG5sE2LvlkRERKQEBVURqfUeeOABli1bxt13301wcDCGYfur7RZP++0Y5oefh7PN69c2oXXceTg2ktcX7OHFeTvpExWAh4v+SRQREaku9K+yiNR6v/zyC/PmzaNbt2526+G3nSkAXNNCV/S1lZE9Ivhuw18kpWXx9qK9TL6uub1bEhERkTN0jqqI1Hp16tTBz8/PbvVPZOax7sAJAK5tUfb5qQBOTk7Ur18fJycnW7V2RXN1cuCZG1sA8J8View4nG7njkRERKSYgqqI1HrPP/88U6dOJSsryy71F+9OpdBsISrIi4Z13c+7XXR0NH/99RfR0dE27O7K1jsqkOujgyk0W5j8wzYKzbqwkoiISHWgqb8iUuu9/vrrJCQkEBgYSFhY2Dkjlhs3bqzS+sXnp16rab928fTAFizfe5Stf6Uza+UB7usebu+WREREaj0FVRGp9QYNGmS32tl5hSzbcxSAay4w7Rdg27ZtDBgwgF9++UWjqpUowNuVyQOa88Tsbbz2WzzXtgwktM75R7ZFRESk6imoikit9/TTT9ut9rI9qWTnFxJax41W9b0vuG1+fj6HDh0iPz/fRt3VHrd3bMCcTYdYeyCNqT/uYObwDna5+rOIiIgU0TmqIiLAyZMn+c9//sPkyZNJS0sDiqb8Hjp0qErrzttWdLXf66Ltc1scKWIyGbx0czTODiYW707lx82H7d2SiIhIraagKiK13tatW2natCn//ve/ee211zh58iQAP/zwA5MnT66yujn5hSzeVXR+6oBWF572K1UvMsCTR3pHAjD1x+2kpOfYuSMREZHaS0FVRGq98ePHM2LECPbu3Yurq6t1+XXXXcfy5currO7yPUfJzCskxMeVtg18q6yOlN8/YhvTJtSHUzkFTPzfViwWXQVYRETEHhRURaTWW7duHQ8++OA5y+vXr09KSkqV1f15WzIAA8o57bdJkyYsWbKEJk2aVFlPtZ2jg4nXh7bB2dHEsj1H+Wrtn/ZuSUREpFZSUBWRWs/FxYVTp06ds3zPnj34+/tXSc3cgkIW7koF4Lro8k379fLyIjY2Fi8vryrpSYpEBnjxeL9mALwwbydJx+1zf10REZHaTEFVRGq9G2+8keeee856NV3DMEhKSmLixIkMGTKkSmqu2HuMjNwCAr1daNegTrn2OXToEJMnT67yCzwJ3NctnKvC/cjKK2TCd1soNGsKsIiIiC0pqIpIrff666+TkZGBv78/2dnZ9OzZk8jISLy8vHjxxRerpOa84mm/rYIxmcp3td8jR47w8ssvc+TIkSrpSf5mMhm8dksbPJwdWHsgjbcX7bV3SyIiIrWK7qMqIrWej48PCxYs4I8//mDLli1kZGQQExND3759q6ReXoGZBTuLwuZ10cFVUkMuX8O67rw4OJqx32zm7cV76RThR9fG9ezdloiISK2goCoitZrZbCYuLo4ffviBAwcOYBgG4eHhBAUFYbFYquTepn8kHON0TgH+Xi60b1S+ab9iH4Pa1WdlwjG+Xf8XY7/ezM//vJp6ni72bktEROSKp6m/IlJrWSwWbrzxRh544AEOHTpEdHQ0LVu25ODBg4wYMYLBgwdXSd15W4um/fZvGYRDOaf9iv08c2NLIgM8ST2dy7++3YJZ56uKiIhUOQVVEam14uLiWL58OYsWLWLTpk189dVXfP3112zZsoWFCxeyePFiPvvss0qtmZNfyPztRbe8uaF1xab91q1bl/vvv5+6detWak9yYe7Ojrx3ZwwuZ25Z88GyBHu3JCIicsUzLLqbuYjUUtdeey29e/dm0qRJZa5/6aWXWLZsGb/++mul1fx5WzIPfbGREB9XVkzsXe4LKYn9fb02iUk/bMMw4JMRHenVLMDeLYmIiFyxNKIqIrXW1q1b6d+//3nXDxgwgC1btlRqzTmbim4tc2Pb+hUOqdnZ2ezYsYPs7OxK7UnK57aODbjjqoZYLPDoV5vYfzTD3i2JiIhcsRRURaTWSktLIzAw8LzrAwMDOXHiRKXVS8/KZ2n8UQAGtQup8P67du2iVatW7Nq1q9J6kvIzDINnb2xJh0Z1OJ1TwKj/buB0Tr692xIREbkiKaiKSK1VWFiIo+P5L37u4OBAQUFBpdX7ZXsyeYVmooK8iAryrrTjiu04O5p4/64Ygrxd2ZeawSNfbaKg0GzvtkRERK44uj2NiNRaFouFESNG4OJS9u1GcnNzK7XenM1F035valu/Uo8rthXg5cpH97Rn6IxVLI0/ypOzt/PykOgquZWRiIhIbaWgKiK11vDhwy+6zT333FMptZLTs1mTmAbAwDYVu9qvVD+tQ315544YHvzver5Z/ydBPq6Mu6apvduyG4vFwp9p2Ww7lE7C0QyS03M4ciqH7LxCCs/czsfH3Ym6Hs6E+LoRFeRF82BvQuu4KeCLiEiZFFRFpNb69NNPbVbr/7YcxmKBq8L8CK3jfknHMAwDZ2dn/WFfTVzTIpDnB7XiydnbeWvRXgK9XbmzU0N7t2UzR07lsDQ+leV7jvFHwjFOZlX8fN1gH1eublKPXs0C6BUVgKuTQxV0KiIiNZFuTyMiYgPXvfU7O5NP8eLgVgzr1Mje7UgleuO3eN5evA/DgFdvacMt7UPt3VKVOZWTz/ztKczZdIhV+49T8i8IZwcTzYK8iAryIsTXjSAfVzxdHHE0GZgtcCIrj7TMPA4cz2R38mn2pWaQV+L8Xi9XR25oHcxtHRvStoGv7V+ciIhUKwqqIiJVzGKxMG9bMj9tPsy/h7SmjoezvVuSSmSxWJj64w7+u/oghgGv3dKGIVdYWN175DSfrjzADxv/Iif/73DZtoEvPZv606OpP9H1fXB2LP81GnPyC1mbmMbyPUf5ZXsKh07+fdulq8L8GNkjgj5RAbrXsIhILaWgKiJSQ+zatYthw4bxxRdf0Lx5c3u3IyWYzRam/LidL9YkYRjw+q1tuDmmZodVi8XC8r3H+Hj5flbsO2Zd3tjfg5tjQrmxTQgN/C5tGvvZzGYLaxLT+G79n/zf1sPkFxb9adI61IdJ/aPoGlmvUuqIiEjNoaAqIlJDbNy4kfbt27NhwwZiYmLs3Y6cxWy28NSP2/nyTFidekML7u0Wbu+2KsxisbB0z1HeWriXzX+eBMBkFJ2Te2+3cDqF+1XpedIp6Tl8ujKRz1cdJDOvEIAeTf156vrmNA30qrK6IiJSvSioiojUEAqq1Z/ZbOHZ/9vBrFUHAXiwZwQT+0XViOmrxQH1zYV72XImoLo6mRjWqREjuoZV2uhpeR3LyOWdRXv5Yk0SBWYLjiaDkT0ieLR3E9ycddElEZErnYKqiEgNoaBaM1gsFj5YlsAr8+MBuD46mFduaY2HS/W80L7FYmFp/FHeXLiHLX+lA0UB9e7OjRjVozH+XmXfZ9hWDh7P5IV5u1iw8wgAoXXceHFwND2b+tu1LxERqVoKqiIiNYSCas3yvw1/MemHreQXWmgS4MmMu9sT4e9p77asLBYLS+JTeWvhXmtAdXNy4O4ujRh5dYTdA+rZftuRwjM/7eBweg4Awzo15Mnrm+PuXD0/ABARkcujoCoiUkOcOHGChQsX0rdvX+rUqWPvdqQcNhxM4x+fbyT1dC6eLo48PbAFt7QPteu9cC0WC4t2pfL24r1sLRFQ7+nSiJE9IqjnWb0CakmZuQW8+ms8cSsPANCorjtvDG1L+0b670FE5EqjoCoiIlKFUk/nMOaLTaw9kAZAn6gApt0cTYC3q037MJstLNqdyluL9rD90CngTEDtWjSCWp0D6tlW7D3GY99vITk9B5MBD8VGMrZvExwdyn97HBERqd4UVEVEaogjR47wxRdfMGzYMAIDA+3djlRAodnCR8v3M33BHvIKzXi6OPJwr0ju7RaGq1PVXhgoJ7+QHzYeYuaK/SQczQTA3dmBe7qEMfLqcOrWoIBaUnp2Ps/+tIMfNh0CoEOjOrx9RztCfN3s3JmIiFQGBVURkRpC56jWfLtTTvH491utU25D67jxUGwkN8fUr/TAuv9oBt9v+Iuv1iZxIisfAE8XR+7q3IhRPSLw83Cu1Hr2MnfrYSb9bxsZuQX4ujvx+q1t6NNcH+SIiNR0CqoiIjWEguqVwWy2MHvTIV75dTdHTuUCUNfDmWGdGnJTu/o0vowLLh06mc3iXUf4YdMhNiWdtC4PrePGvd3CGdohFC9Xp8t9CdXOweOZjPlyE9sOFX0A8ED3cB7vH4Wzo6YCi4jUVAqqIiI1hILqlSUrr4Av1yTx6R8HOHQy27q8ebA33SPr0im8Ls2CvKjv61bmfVhz8gv560QW2w6ls+XPdFbvP87ulNPW9Q4mg55N/RnaIZRrWgThUAPu5Xo5cgsKefmX3Xz6xwEA2jTw5d072tn8/q8iIlI5FFRFRGoIBdUrU0Ghmfk7Uvjfhr9YvvcYhebS/yy7OJqo5+mCl2vRbVjyC82kZ+dzLCPvnGOZDIhpWIf+rYK4sW0IAV62vWBTdfDrjhQe+24Lp3IK8HJ15JUhrRkQHWzvtkREpIIUVEVEaoiEhATGjRvH9OnTady4sb3bkSpwPCOXFfuOsSrhOJuSTrL/WAb5hef/Z9rd2YGoIC/aNPClXcM6XB1ZjzpXyLmnl+OvE1k88tUm6/Tnuzo35KnrW1T5hatERKTyKKiKiIhUU/mFZpJP5pCWlcep7HwcTAYOJgNPF0dC67jh4+Zk13uyVmf5hWZe/20PHy5LACAqyIt374whMuDSzwEWERHbUVAVEakh8vPzOXnyJL6+vjg5XXkXxBGpCsv2HGX8N5s5npmHm5MDz93Uklvahyrgi4hUc7ocnohIDbFt2zYCAgLYtm2bvVsRqTF6NvXnl39eTbfIumTnF/LY91sZ/+0WMnIL7N2aiIhcgIKqiIiIXNECvF357L5OPNavGQ4mg9mbDnH927+z/kCavVsTEZHzUFAVERGRK56DyeDhXpF8PaozIT6uHDyexa0zVvHivJ3k5Bfauz0RETmLgqqIiIjUGh3D/Jg/rge3tg/FYoGPf0/k+rd/Z1PSCXu3JiIiJSioioiISK3i7erEq7e2YebwDgR4uZBwNJObP1jJlDnbSc/Kt3d7IiKCrvorIlJjFBYWkpmZiYeHBw4Ouh+kSGU4mZXHc/+3kx82HQLAz8OZSQOiuCUmFJNJVwYWEbEXBVURERGp9VYlHGfqj9vZm5oBQOtQHx7vF0X3JvXs3JmISO2kqb8iIjXE3r176devH3v37rV3KyJXnC6N6/LzP6/mieui8HB2YOtf6dw1cw13fryaDQd1dWAREVvTiKqISA2xceNG2rdvz4YNG4iJibF3OyJXrKOnc3lvyT6+XJNEXqEZgJiGvozqEcE1LYJw0JRgEZEqp6AqIlJDKKiK2NZfJ7J4Z9E+Zm86ZA2soXXcGBITyi3tQ2ng527nDkVErlwKqiIiNYSCqoh9pJ7O4bOVB/nv6oOkZ/99VeCrwvy4tmUgfZoHEl7Pw44diohceRRURURqCAVVEfvKzivk1x0pfL/hL/5IOEbJv6Ai6nlwVbgf7RvVoUOYH2F13TEMTREWEblUCqoiIjXE0aNH+fbbbxk6dCj+/v72bkekVjt0Mptft6ewaPcR1uxPo8Bc+s8pb1dHmgZ60STQiyYBnjT0c6d+HTdCfN3wdnVUiBURuQgFVREREZHLcConn9UJx9mQdIINB06w9a906zmtZfF0cSTYx5UgH1cCvV0J8nYl0Kfoe9FjF+p6uOiiTSJSqymoiojUEGlpafz8889cd911+Pn52bsdETmP3IJC9h/NZM+R0+w9ksG+1AwOnczm0Mls0jLzynUMR5OBv5eLNcgWh9qGfu40DfQkrJ4HTg66y6CIXLkUVEVEagidoypS82XnFXI4PZvDJ7M5ciqXI6dySEnPIeVUDkfOfB09nYv5In+dOZoMwut50DTIi+j6PrRt4EvrUB/cnR1t80JERKqYfpuJiIiI2IibswON/T1p7O953m0KCs0cy8gj5UyITT19Jsym57D/WCb7UjPIyC1gb2oGe1MzmLc1GQAHk0HTQC9iGvrSpXFdukTUpa6ni61emohIpVJQFREREalGHB1MBJ05h5UG5663WCwcTs9hz5HTxKecZsufJ9mUdJKUUznsSj7FruRTfLEmCYDmwd50a1yXbpH16BxRFzdnBxu/GhGRS6OgKiIiIlKDGIZBfV836vu60atZgHV5cno2m5NOsu7ACVYmHGN3ymlrcP3PikRcHE10bVyX3s0D6R0VQH1fNzu+ChGRC9M5qiIiNUR8fDwjRowgLi6OZs2a2bsdEanmjp7OZdX+46zcd4zf9x7j0MnsUuujgrzo0zyA3lGBtG3gq6sMi0i1oqAqIiIicoWzWCzsOZLBot1HWLI7lQ0HT5S6YJOfhzOxTf3p3TyAq5v44+PmZL9mRURQUBURERGpdU5k5rFsz1EW7U5lWXwqp3IKrOscTQYdwurQJyqQ3s0DiKjngWFotFVEbEtBVUSkhtDtaUSkKuQXmtlw8ARLdqeyaHcq+1IzSq1vVNed3lEB9IkK5KpwP5wddf9WEal6CqoiIjWEgqqI2ELS8SwW7z7Cot2prNmfRl6h2brOw9mB7k3q0T2yHl0a16Oxv0ZbRaRqKKiKiNQQCqoiYmsZuQWs2HuMJbtTWRyfytHTuaXWB3i50KVxXbo2rkvXxvUIreOm4CoilUJBVUSkhlBQFRF7MpstbD+czrL4o6zaf5z1B0+QV2AutU2AlwsxDevQrqEv7RrWIbq+j+7dKiKXREFVRKSGUFCtYhYLmM1gLvz7e/EyixksFH0v3raYYQBG0XfDAMMEpjOPTQ5gMhV9d9Af63JlyckvZFPSSVYlHGNlwnE2/3mSAnPpPysdTQbNg72JDvWhebA3LYK9iAryxsPF0U5dV0/5hWZO5xSQnp1PZm4BeYVm8grM5BYUfy+koLDovS36VWNgFD/GwNHBwMXRhKuTw5kvE66Ofz92d3bUucVS4yioiojUEDk5Ofz111+Ehobi6upq73aqp8JCyM+F/DzIzy/6KjjzuODMV35+0TZ5xdudWV+YfyaUWooCqdlyJpCe+W7h78dnM878AVj8l2NxcDWdCa6GURRYHZzA0REcncHZCZycwckFnJzA0QkcHM+sP/O81GOnou1MCrxSPWXnFbLtUDqbkk6wKekkG5NOkHrWVOFiYXXdaR7sTbMgLyL8PYmo50FYPQ88r5AAazZbSMvKI/VULqmnc0g9ncvR07mknip6fDwjj/TsfE7l5HMqO5/MvMIq78nVyYS3qxNero54uzmVeuzl6kgdd2f83J3x83CmjkfRdz8PZ7xdHTWdW+xCQVVERKo3c2FRqMwtDpdnvhcvy86E7CzIySpaV1gIhQV/f7eYKUqQZ1gsf49wGqYzI55nvkqGSsMo/VV8jLL+YCv+p9Rydri1lBF+i0dsLX+P3lrMfx/XYjkTeEuMxBZ/d3AoCrcubuDsCq5u4OJStMzRqezvxSFYf2iKjVksFg6n57Ap6QQ7Dp9iV3LR15FTZYdXgEBvF8LreRBez5NGdd0J9nGlvq8bIb5uBHi54Ohg/1HBzNwCUk7lcCQ9h+T0nKLHp3JISS/6fuRULscycs8ZXS4PTxdH3J0dcHEy4exgwtnRARdHE86OJpwciv4btlg/O7NYP0MrKDSTk28mp6CQ3HwzOfmFRV8FZgovoY+SHE1GUXB1d6aOhxN1PVyo4+FUKtT6ujvj6+aEr7sTvm7OeLk6YjLpd45cHgVVEZEaIjExkSlTpvD8888THh5u73Yu39kBNC/nzOOcotCZlQFZmZCbDQUFZ77yiwJoyb9/HByKRiKtXw6lv5vs/4ftJSmeflxYeP7vhQV//9VqDaLGWe/BmaDr7FIUbIsDrrNz6dHaUiO4jn+P/hYfR6SSHM/IZVfyaXYln2Jv6mkSj2Wy/2gmxzPzLrifg8kg0MuFYF83/D1dzoz6ORWNBJ4JTN6ujrg6OeDm5ICbs4N1+mvxr4GSf/XmFZrJziskO6+QrLxCsvOLHp/IyuNEVh7HM4q+p2UWfaWezuVIeg6ncwvKbrAMdT2c8fdyIcDblUAvFwK8XQjwcqWepws+bk74uDnh7eZoHd2siiCeX2gmK7eQUzn5pGfnczqngFM5Z76feZ6enc/J7KLXeSIzj7SsPNIy8i55pNcwwMfNCV83J3zcnf9+7OaEu3PRz6bouyNuTg7WZa6ODjg5GDiYDBxNpqLvDgaOxc8dDEwGmAzjzKQV48xX0XTo4nUOprLXS82ioCoiUkPUmHNUC/L/HvEsnl5bHEBzsyEzoyiE5uacmY57JoCaCwCjaHjAMEoEpzNhqfi5yUGjgxdSMuAWh9mSz4sfU8Y//9YR3DOjuSaHounLDmemHVtHaJ3/DrrFQda6/ZnR6ZIj1taRa+Pvx/D3+byUGLW2Tp+G0p9IlFSi97KmZZ89sl38vljXlTjn2HrusaXEshIj4pRcVqLOOVPBLWW+pWUyKP2aocT7QOmR/ZLvk+Fw7vnPJdc5nHl+9myBGiI9K5/9xzKswfXQyWwOnczm8MlsUtJzLmmEsqp4ODsQ5ONKkI8rgd6uBHmXfhzg7UI9TxecqsEI8OXIyS/kZFa+NaynZRUF2eNnBdr07KIQfDLr0sOtLZhKhNe/g2yJ4Gs6N/i6Ojng7lw00u3u7ICHsyPuLmd9d3bAy9URL9dzp1R7uzrp/OBLdGWcCCAiIlXDYjnr3M68c79yc/6eepudeeZ8z+LRzzNTcI2SAbTEeZhOzuDm8XcYlctXHE4cnSq2n8VS+kJShcWPzX+Pchc/t5RYV54PDUwmSl9wqnga9dnn9hY/oXzHLRkSrd9KBsazwqv1e4mgCUXTsEulTAt/f2hy8TYqn0Gp12R9a4rPeebvMFvqy1T6e/EUdkenovBq/WDBEZxKjpqXmF5eHIBLPj7nA4yS38tYdokfJPm4O9GuYR3aNaxzzrpCs4VjGbkcPpnN4ZM5pGXmkpaZbx3xLP6ekVtQNEp6ZuprfuGFw61hgLtT0checRDxcXP6+zxN97/P1azn6UKQjwuB3q54uVbwv68aytXJgSCfolBeXnkF5jPBNY+TWflFX2dC7KnsfLLyCsnKLx7JLiA730x2XgFZeUU/s0KzhQKzpfT3wqIpzPnmov92zRbLma+KvR7zmX3L/6lS5XBxNJUKrn+fJ+x4TrC9qU19TZs+Q38ViIhcqc4eVbN+PzONtuTjgoIzFx06M/qZm31mWm5OiX3Pmm5aavptiam3jg5F51B6eGnaaE1iGGd+XpV8XOvoZFkjlWeFxpIBs8S3svs950GJAHzmf4yz1501Ynv2ucfVeaS+5Ht3vve01HNz0X+vFnPRf8vF68xnfS++knWZigNziQuDlTp/uzgQnxWSTWdGd88+x/qcc8NLjAKffV54yZ+fYeBgGAQCgRi0cwXcgHrFfTqd+fI46/8zRcEmJ9+MpcT/586c6YmTCVyKy5Q6p9wM5lwg58xIvAXyzZBmgWMWoPg9LDFqb31c8mfAmfevxGj9361dXMn/j5d6Xyj9Myj18yneruS598Uj8MZZI+7F+3Nmpgqlz9UvuY2pxDLrhyBlr3c2mfA3Gfh7msDbDQz3svevJBZLUZgtDqGWs4KsxfL3utLriy56daHtC80WcguKpoZn5hYF68y8QrJyi4J18fPM3AIyyphSXTxNPLfAzNEzF9S6EEeTwaC29SvtvanpFFRFRC7Txo0by7fh6VOQfvysKYMl/8gBKHG12bP+8Ny1PxGAXXN/gK1rS0/pNJ81hbH4Qj3WxyUv6GP++48xixkKzX8HB4NzR0ccHP6eVlhyuqGI1A6WM+Gs5O+mc56fHdjOWn7OdOmzl9tYiUHrc5bDeT7MKLXBuaPtxtnrztqgrGXlcvZ7dNaMgJJn8ZW1/Jyrl1+EcVYY5uwPeYy/p6pTYruSQbrUDArOeh9LjLqbSrxnlNy+eLsSYbg44FpnaJhKH784tFufA5SodU4vJXso8fMs9e9b0ZRgDww8Sn7IVXJ7ZwOcAa+S64sUWiCrwEJmgZmsPDOZ+WYy88xkFZjJyC+xLN9MZl4hZgcnNm3adNEfUbU+/acS6RxVEZHLpAs0iIiIiK3UlvimEVURkcu0YcOG8m2Yd2ZKbclPjkVERKR6KXUea4mRacvZ25xZXyo4njXCfU6mLGMkvHiZm0fRaTMCaERVREREREREqhmdZCQiIiIiIiLVioKqiIiIiIiIVCsKqiIiIiIiIlKtKKiKiIiIiIhItaKgKiIiIiIiItWKgqqIiIiIiIhUKwqqIiIiIiIiUq0oqIqIiIiIiEi1oqAqIiIiIiIi1YqCqoiIiIiIiFQrCqoiIiIiIiJSrSioioiIiIiISLWioCoiIiIiIiLVioKqiIiIiIiIVCsKqiIiIiIiIlKtKKiKiIiIiIhItaKgKiIiIiIiItWKgqqIiIiIiIhUKwqqIiIiIiIiUq0oqIqIiIiIiEi1oqAqIiIiIiIi1YqCqoiIiIiIiFQrCqoiIiIiIiJSrSioioiIiIiISLWioCpSTcTGxmIYBrGxsTarGRcXh2EYGIZhs5qXqqxei9+zESNG2K8xEREREal0CqoitUBNCnQV6bVFixZ06tSJxo0bV31jIiIiImIzjvZuQETkUr3//vuVdqy8vDycnZ0r7XgiIiIicuk0oipiBydOnGDo0KG4u7vTsGFDPvzww3O2yc3N5emnn6ZJkyY4OzsTEBDAfffdx7Fjx6zbbN68mT59+hAcHIyLiwseHh507NiRzz//3LqNYRgsW7YMgFmzZlmnzx44cKBUvZUrV9KxY0fc3d2JiYlh9erV5X49K1asoF+/fvj4+ODi4kLz5s159dVXKSwstG4TFhaGYRg888wz1mUjRowoNd25vL0WK2v0NT09nX/+8580atQIZ2dnQkNDGT9+PFlZWWXWfeWVVwgNDcXV1RWA1atX06dPH+rWrYurqythYWEMGjSIhISEcr8fIiIiInJ5FFRF7OCBBx7gu+++Izs7G3d3dyZMmMD69etLbXPzzTfz3HPPkZiYSPPmzcnNzeXTTz+lZ8+eZGdnA3DgwAGWLl2Ki4sLLVu2xMXFhfXr13P33Xczb948ADp16oSXlxcA9erVo1OnTnTq1AkXF5dS9a655hpOnz5Nfn4+mzZt4vbbb6egoOCir2Xp0qX06tWL3377DQcHBxo1asTu3bt5/PHHGT16dIXel/L2ej55eXnExsby9ttvk5qaSvPmzTl+/DjTp09n4MCBWCyWUtuvWrWKyZMn4+3tjZ+fH2azmRtuuIHFixfj5ORE8+bNycrK4scff+TPP/+s0GsRERERkUunoCpiYwkJCfzwww8ATJw4kd27d7NhwwZyc3Ot2yxbtoyff/4ZgMWLF7NlyxZ2796Nm5sbO3fu5MsvvwSgc+fOHD58mAMHDrBx40YOHz5MZGQkAF9//TVQNEIYExMDwPXXX8/q1atZvXo1wcHBpfp6+eWX2b17N6+//joABw8eZN++fRd9PU8//TQFBQU0atSI/fv3s2fPHv75z38CMHPmTPbv31/u96a8vZ7PV199xebNm3F2dmbr1q1s2bLFOjK8ePFiFi9eXGr7vLw85s6dy86dOzly5AgnTpzg+PHjAGzYsIFNmzaRmprK9u3badGiRblfh4iIiIhcHgVVERvbsWOH9fGQIUMAaNasGa1bt7YuX7t2rfVxz549MQyDkJAQ60hqcfgyDIN//etfhISE4OjoiJubmzVcHj58uEJ93X333QClAtmRI0cuut+6desAuO666/D19QXgzjvvBMBisbBhw4YK9XE5it+3vLw8mjZtimEYtG3b1rr+7OnMzZo1Y8CAAQA4ODhQt25dunTpAkBkZCTR0dHccccdbNq0iXr16tnmRYiIiIiILqYkUt116tTpnGVBQUEA3HXXXSxcuBDDMGjRogWenp7s3LmT06dPlzo/tDyKQ6aj49+/Fs6eKns5im8rU7Kv9PT0Sjt+Sc7OzrRr1+6c5XXq1Cn1PDAw8JxtFi1axJdffskff/zBzp07+f777/n6669JTk7mscceq5J+RURERKQ0BVURGys5Yjl79mw6duzInj172Lp1q3V5x44drY8nT57MTTfdBEBBQQELFy4kKioK+HuEcOTIkcyYMYO0tDRatWrF6dOnS9V0d3cHIDMzs9JfT8eOHVm+fDk///wzJ0+exNfXl6+++gooCqft27cHICAggAMHDrBnzx4Ajh07xtKlS8853uX0Wvy+FRYW8v7771unEefk5DBv3jz69OlTavuz7x9rsVhYuXIlI0aM4P777wdg9OjRzJgxg+XLlyuoioiIiNiIpv6K2FhkZCSDBg0CYNq0aTRv3pyYmBgcHBys28TGxtKvXz8ABg0aRFRUFC1btsTX15cBAwZYr4JbPF34P//5Dy1btqRx48bk5OScU7M42P7www/ExMTQv3//Sns9zz77LI6Ojhw8eJCIiAiaNm3Km2++CcD9999PREQEgDUkfvvtt1x99dVER0dz6tSpSu31jjvuoHXr1hQWFtKxY0datWpFs2bN8PX15ZZbbuHkyZMX3L+wsJC+fftSp04dWrZsSXR0NB9//DFAqanZIiIiIlK1FFRF7GDmzJkMGTIEV1dX0tPTee655+jcuXOpbebMmcPUqVNp0qQJ+/fvJyUlhebNm/PUU0/RqlUrAOLi4ujVqxeurq5kZWXx5ptvlhmoJkyYQN++fXF3d2fTpk3nXGH4csTGxrJkyRKuueYaCgsLOXDgAFFRUfz73/8uddudyZMnc9ddd+Hr68uePXu45557uP322yu1VxcXF5YtW8ajjz5KgwYN2LNnDydOnKBDhw68+OKLZU71LcnBwYHRo0cTHh7OoUOH2LdvH2FhYUyYMIGpU6eW/00RERERkctiWCrzJDQRERERERGRy6RzVEXkgp5//nnrPVnPNmXKFK6//nobdyQiIiIiVzoFVRG5oISEBNasWVPmuqNHj9q4m5rtzo9XX3yjSnBPlzCb1NmbmmGTOgDh9TxsUufz1QdtUmfWfVfZpE5mboFN6vh5ONukTl6B2SZ1nB11ZlR1Fjap7A9PK9uBl/VBrIg9KaiKyAXFxcURFxdn7zZEREREpBbRR4YiIiIiIiICwB9//EF0dDROTk7WO1XYg4KqiIiIiIjIFWDEiBEYhoFhGDg5OREeHs7jjz9e5u0Lz2f8+PG0bduWxMREu86qU1AVESlh2rRpdOzYES8vLwICAhg0aBDx8fH2bktERESkXPr3709ycjL79+9n+vTpzJgxg6effrrc+yckJNC7d29CQ0Px9fWtukYvQkFVRKSEZcuW8fDDD7N69WoWLFhAfn4+1157LZmZmfZuTUREROSiXFxcCAoKokGDBgwaNIi+ffuyYMECAMxmM9OmTSM8PBw3NzfatGnD999/D8CBAwcwDIPjx49z3333YRiGXUdUdTElEZES5s+fX+p5XFwcAQEBbNiwgR49etipKxEREZGK2759OytXrqRRo0ZA0cyxzz//nA8//JAmTZqwfPly7rrrLvz9/enevTvJyck0a9aM5557jttuuw0fHx+79a6gKiJyAenp6QD4+fnZuRMRERGRi5s7dy6enp4UFBSQm5uLyWTi3XffJTc3l5deeomFCxfSpUsXACIiIlixYgUzZsygZ8+eBAUFYRgGPj4+BAUF2fV1KKiKiJyH2Wxm7NixdOvWjVatWtm7HREREZGL6tWrFx988AGZmZlMnz4dR0dHhgwZwo4dO8jKyuKaa64ptX1eXh7t2rWzU7fnp6AqInIeDz/8MNu3b2fFihX2bkVERESkXDw8PIiMjATgk08+oU2bNsycOdP6ofu8efOoX79+qX1cXFxs3ufFKKiKiJRhzJgxzJ07l+XLlxMaGmrvdkREREQqzGQy8cQTTzB+/Hj27NmDi4sLSUlJ9OzZ096tXZSu+isiUoLFYmHMmDHMnj2bxYsXEx4ebu+WRERERC7ZrbfeioODAzNmzGDChAmMGzeOWbNmkZCQwMaNG3nnnXeYNWvWefePiopi9uzZNuy4iEZURURKePjhh/nyyy/58ccf8fLyIiUlBQAfHx/c3Nzs3J2IiIhIxTg6OjJmzBheeeUVEhMT8ff3Z9q0aezfvx9fX19iYmJ44oknzrt/fHy89eKStmRYLBaLzauKiFRThmGUufzTTz9lxIgRl3XsOz9efVn7l9c9XcJsUmdvaoZN6gCE1/OwSZ3PVx+0SZ1Z911lkzqZuQU2qePn4WyTOnkFZpvUcXbUhLPqLGzSPJvUOfDy9TapIyJl04iqiEgJ+uxORERExP70kaGIiIiIiIhUK5r6KyJiI/tsNFV2x+FTNqkT6G27S9nn2mjKZ1hd20wx/mb9nzap4+HsYJM6pvNMma9sZhv9yZKRY5sp03mFtvn/9a3tbXPl8vk7UmxSZ2zfpjap8/AXG21SB6Chn7tN6jQO8LRJnVts9P85W/2M3hsWY5M6UppGVEVERERERKRaUVAVERERERGRakVBVUREREREpJZ58cUX6dq1K+7u7vj6+pZrH8Mwyvx69dVXrduEhYWds/7ll1+ucH8KqiIiZ1m+fDkDBw4kJCQEwzCYM2eOvVsSERERqbDY2Fji4uLKXJeXl8ett97KP/7xj3IfLzk5udTXJ598gmEYDBkypNR2zz33XKntHnnkkQr3rtvTiIicJTMzkzZt2nDfffdx880327sdERERkUr37LPPApw3yJYlKCio1PMff/yRXr16ERERUWq5l5fXOdtWlEZURUTOMmDAAF544QUGDx5s71ZEREREqqUjR44wb9487r///nPWvfzyy9StW5d27drx6quvUlBQ8aupa0RVREREREREKmTWrFl4eXmdM/vs0UcfJSYmBj8/P1auXMnkyZNJTk7mjTfeqNDxFVRFRERERESuAC+99BIvvfSS9Xl2djarV69mzJgx1mU7d+6kYcOGl13rk08+YdiwYbi6upZaPn78eOvj1q1b4+zszIMPPsi0adNwcSn/PdgVVEVERERERK4Ao0ePZujQodbnw4YNY8iQIaVGPUNCQi67zu+//058fDzffPPNRbft1KkTBQUFHDhwgGbNmpW7hoKqiIiIiIjIFcDPzw8/Pz/rczc3NwICAoiMjKzUOjNnzqR9+/a0adPmottu3rwZk8lEQEBAhWroYkoiIiIiIiK1TFJSEps3byYpKYnCwkI2b97M5s2bycjIsG4TFRXF7NmzS+136tQpvvvuOx544IFzjrlq1SrefPNNtmzZwv79+/niiy8YN24cd911F3Xq1KlQfxpRFRE5S0ZGBvv27bM+T0xMZPPmzfj5+VXKOR0iIiIi9jZ16lRmzZplfd6uXTsAlixZQmxsLADx8fGkp6eX2u/rr7/GYrFwxx13nHNMFxcXvv76a5555hlyc3MJDw9n3Lhxpc5bLS8FVRGRs6xfv55evXpZnxf/ch0+fHiF7jUmIiIiYk9Lly4977q4uLiL/l1jsVjOWTZq1ChGjRpV5vYxMTGsXr26Ii2el4KqiMhZYmNjy/zFLCIiIiK2oXNURUREREREpFrRiKqIiI34uDnZpI6zo20+gzTbcND56Olcm9RpGuhlkzr1PJxtUgfDNmVs9fNxdXKwSR1vdxv9t+pgm/9Wx367xSZ1+rcMtEkdW7mudbDNaiWlZdmkzqr9x21S55b2oTapY6ufUdikeTapc+Dl621Sp6bQiKqIiIiIiIhUKwqqIiIiIiIiUq0oqIqIiIiIiNQyL774Il27dsXd3R1fX99y7ZORkcGYMWMIDQ3Fzc2NFi1a8OGHH5baJiEhgcGDB+Pv74+3tzdDhw7lyJEjFe5PQVVEpAzvvfceYWFhuLq60qlTJ9auXWvvlkREREQqJDY29ry3oMnLy+PWW2/lH//4R7mPN378eObPn8/nn3/Orl27GDt2LGPGjOGnn34CIDMzk2uvvRbDMFi8eDF//PEHeXl5DBw4ELPZXKHeFVRFRM7yzTffMH78eJ5++mk2btxImzZt6NevH6mpqfZuTURERKRSPPvss4wbN47o6Ohy77Ny5UqGDx9ObGwsYWFhjBo1ijZt2lg/0P/jjz84cOAAcXFxREdHEx0dzaxZs1i/fj2LFy+uUH8KqiIiZ3njjTcYOXIk9957r3VKi7u7O5988om9WxMRERGxm65du/LTTz9x6NAhLBYLS5YsYc+ePVx77bUA5ObmYhgGLi4u1n1cXV0xmUysWLGiQrUUVEVESsjLy2PDhg307dvXusxkMtG3b19WrVplx85ERERE7Oudd96hRYsWhIaG4uzsTP/+/Xnvvffo0aMHAJ07d8bDw4OJEyeSlZVFZmYmEyZMoLCwkOTk5ArVUlAVESnh2LFjFBYWEhhY+n6AgYGBpKSk2KkrERERkYt76aWX8PT0tH79/vvvjB49utSypKSkSz7+O++8w+rVq/npp5/YsGEDr7/+Og8//DALFy4EwN/fn++++47/+7//w9PTEx8fH06ePElMTAwmU8Wip+MldykiIiIiIiLVxujRoxk6dKj1+bBhwxgyZAg333yzdVlISMglHTs7O5snnniC2bNnc/311wPQunVrNm/ezGuvvWadjXbttdeSkJDAsWPHcHR0xNfXl6CgICIiIipUT0FVRKSEevXq4eDgcM5l1I8cOUJQUJCduhIRERG5OD8/P/z8/KzP3dzcCAgIIDIy8rKPnZ+fT35+/jkjow4ODmVe0bdevXoALF68mNTUVG688cYK1dPUXxGREpydnWnfvj2LFi2yLjObzSxatIguXbrYsTMRERGRypOUlMTmzZtJSkqisLCQzZs3s3nzZjIyMqzbREVFMXv2bAC8vb3p2bMnjz32GEuXLiUxMZG4uDg+++wzBg8ebN3n008/ZfXq1SQkJPD5559z6623Mm7cOJo1a1ah/jSiKiJylvHjxzN8+HA6dOjAVVddxZtvvklmZib33nuvvVsTERERqRRTp05l1qxZ1uft2rUDYMmSJcTGxgIQHx9Penq6dZuvv/6ayZMnM2zYMNLS0mjUqBEvvvgio0ePtm4THx/P5MmTSUtLIywsjCeffJJx48ZVuD8FVRGRs9x2220cPXqUqVOnkpKSQtu2bZk/f/45F1gSERERqc6WLl163nVxcXHExcVdcH+LxVLqeVBQEJ9++ukF93n55Zd5+eWXy9vieSmoioiUYcyYMYwZM8bebYiIiIjUSjpHVURERERERKoVw3L2eK6IiIiIiIiIHWlEVURERERERKoVBVURERERERGpVhRURUREREREpFpRUBUREREREZFqRUFVREREREREqhUFVREREREREalWFFRFRERERESkWlFQFRERERERkWpFQVVERERERESqFQVVERERERERqVYUVEVERERERKRaUVAVERERERGRakVBVURERERERKoVBVURERERERGpVhRURUREREREpFpRUBUREREREZFqRUFVREREREREqhUFVREREREREalWFFRFKkFsbCyGYRAbG2vvVq5YBw4cwDAMDMNg6dKlADzzzDMYhkFYWJhdexMRERGRyqWgKiLVSkXCZ2hoKJ06daJdu3ZV35iIiIiI2IyjvRsQEblUDzzwAA888EClHMtisVBQUICTk1OlHE9ERERELp1GVEUq6MSJEwwdOhR3d3caNmzIhx9+eM42kyZNomXLlvj6+uLk5ERISAjDhw8nOTnZuk3xyKFhGPzyyy80bdoUDw8Phg0bRmZmJi+88AL+/v4EBwfz9NNPlzr+8OHDadKkCV5eXjg7O9OoUSMeffRRTp06Zd3GYrEwZcoU6tWrh6+vL2PGjOGJJ56w1izp888/p2PHjri7u+Pl5UX//v3ZvHlzud+TpKQk7rnnHoKCgnByciI0NJSHHnqItLQ06zYjRow4Z3p0XFxcqX5iY2N59tlnATh48KB1XVxcXJl1yxp9NZvNvPXWW7Rq1QpXV1fq1KnDrbfeSmJiYpl158+fT8uWLXFycuKPP/4gJSWFYcOGERwcjIuLC0FBQfTu3Zuff/653O+HiIiIiFwejaiKVNADDzzADz/8AIC7uzsTJkw4Z5v58+dz6NAhGjRoQEFBAfHx8Xz22Wfs2rWLtWvXnrP90KFDqV+/PllZWXz55Zds2rSJAwcOEBwczP79+3nuuefo2rUr/fr1A+DHH3/E0dGRxo0bc/r0afbv388777xDcnIy3333HQDvvvsuL7zwAgD169fnu+++IzMz85zar7zyChMnTgSgadOmZGRk8Ouvv7JixQrWrVtH8+bNL/h+pKam0qVLFw4fPoyLiwtNmzZlz549fPDBB/z++++sW7cOV1fXcr23LVq0YN++fRw6dAhnZ2frlF5/f/9y7Q8wZswYPvjgAwBatmxJSkoK33//PStWrGDLli0EBASU2v6mm24iJCSEBg0aAPDQQw8xe/ZsPD09adWqFUePHmXp0qX06NGD6667rtx9iIiIiMil04iqSAUkJCRYQ+rEiRPZvXs3GzZsIDc3t9R2//3vf0lLS2Pbtm3s2rWLjz76CIB169aRkJBwznE//PBDdu/eTbdu3QDYtWsXCxYsYO/evTRq1AiAJUuWWLdftmwZx44dY/PmzSQkJPDkk08CMGfOHHJycoCiAArQpUsXEhMT2b9/P6GhoaXqZmVlWUcwn332WeLj4zl48CAdOnQgMzOTl1566aLvyXvvvcfhw4cxmUysXLmSHTt2WMPy9u3b+eqrry56jGLvv/++dSpvcHAwq1evZvXq1Vx//fXl2j8xMdE6wj1r1iy2b9/OgQMHCA0NJSUlhXfeeeecfcaNG0diYiKJiYlcffXV7N27Fyj6mWzYsIGkpCQOHTrE7bffXu7XISIiIiKXR0FVpAJ27NhhfTxkyBAAmjVrRuvWrUttt3nzZjp27IinpyeGYTBy5EjrusOHD59z3IEDBwJYp7DWqVOHbt26YTKZrEH1yJEj1u0XLlxIq1atcHNzwzAMXnzxRQAKCgo4evQop06d4q+//gJg8ODBODk54eHhcU7g27FjB1lZWQA8/fTTGIaBk5MT69evB2D16tUXfU/WrVtnfR9iYmIAGDRoEO7u7gDWY9nC+vXrsVgsQNH0aMMw8PLysr4XZb2esWPHWh87ODhYfxbDhw8nMjKSG264gc8//5yQkJCqfwEiIiIiAmjqr0ilW7FiBcOHD8disVC3bl1atGhBRkYGu3btAqCwsPCcfby9vQFwdHQs9Rywnr9ZHMC++OIL63Tj4OBgGjRowLFjx9i/f/95j18ezZs3L1UXoG7dupd0rLIUv46S/aWnp1fa8c/Wtm1bXFxcSi0rDv0lBQYGlnr+4osv0q1bN3799Ve2b9/O8uXLmTdvHkuXLmXevHlV1q+IiIiI/E0jqiIV0KJFC+vj2bNnA7Bnzx62bt1qXb5mzRprqNy2bRtr167lnnvuqbQeikcFvby8SExMZM2aNVx77bWltvH29raeczl37lwKCgrIyso6J2i1bNkSNzc3APr378+qVaus020/+OAD65TiC+nYsSMA8fHxbNy4ESiaglw8UtuhQwcA67mhiYmJFBQUUFhYaH0PSyoeic3KyrK+j+XVvn17ayAeMWKE9bWsWrWKV199lUcfffScfc6+sNQff/xBz549efvtt1m8eLF12vby5csr1IuIiIiIXDoFVZEKiIyMZNCgQQBMmzaN5s2bExMTg4ODg3WbktOAo6Ojad68Oa+++mql9VB8/NOnTxMREUFERATffvvtOds99thjQFHAioiIIDw8nD///LPUNu7u7kyZMgWA6dOnExoaStu2balbty4xMTH89ttvF+3n4YcfJjg4GLPZTNeuXWnVqhW33norAK1ateKOO+4AoE+fPgAcOnSItm3bEh0dze+//37O8aKiogA4evQozZo1o3PnztbR4ouJiIiwTrMeO3YsERERtG7dGl9fX3r06GEN0hcyadIk6tatS2RkJO3bt+e+++4DOGd6t4iIiIhUHQVVkQqaOXMmQ4YMwdXVlfT0dJ577jk6d+5sXX/NNdfw73//m5CQELKzs4mKirJehbYy3H///YwfP5569epx+vRpYmNjee65587ZbsyYMTz11FP4+fmRnp7O4MGDuf/++wFKXYV38uTJzJo1i44dO3LixAn27dtHQEAAo0eP5uabb75oPwEBAaxevZq7774bX19f4uPjCQwMZPTo0Sxbtsxa69prr+WFF14gJCSEAwcO0KpVK+tViUu64YYbGDlyJHXr1mXv3r2sWbPGOjpbHh988AHTp08nOjqaw4cPc/DgQcLCwhg/fnypW+Ocz2233UaHDh04deoU27Ztw9fXl9tvv71CF4USERERkctjWCo6t05EaoT09HRyc3OtU25zcnLo2LEj27dvp3PnzqxatcrOHYqIiIiIlE0XUxK5QiUmJtK5c2euuuoqfH192bBhA4cPH8bBwcF6S5rymDdvHs8//3yZ666//nrr1GERERERkcqioCpyhfL396dHjx5s2rSJkydP4uPjw3XXXcekSZO4+uqry32co0ePsmbNmjLXFZ9PKuV0YIVt6mSl2aaOg5Nt6gAERdumTmG+beok2WhGg1eQbeqk/2WbOjGVd2G6aiH7hG3q7PnVNnXa6H7Tl2z/UtvUMdnoT/+w7rapI1c0BVWRK1T9+vXLdTGkixkxYgQjRoy4/IZERERERMpJF1MSERERERERoOhWfdHR0Tg5OVnvdmEPCqoiIiIiIiJXgBEjRmAYBoZh4OTkRHh4OI8//jg5OTnlPsb48eNp27YtiYmJxMXFVV2zF6GgKiJSwgcffEDr1q3x9vbG29ubLl268Msvv9i7LREREZFy6d+/P8nJyezfv5/p06czY8YMnn766XLvn5CQQO/evQkNDcXX17fqGr0IBVURkRJCQ0N5+eWX2bBhA+vXr6d3797cdNNN7Nixw96tiYiIiFyUi4sLQUFBNGjQgEGDBtG3b18WLFgAgNlsZtq0aYSHh+Pm5kabNm34/vvvAThw4ACGYXD8+HHuu+8+DMOw64iqLqYkIlLCwIEDSz1/8cUX+eCDD1i9ejUtW7a0U1ciIiIiFbd9+3ZWrlxJo0aNAJg2bRqff/45H374IU2aNGH58uXcdddd+Pv70717d5KTk2nWrBnPPfcct912Gz4+PnbrXUFVROQ8CgsL+e6778jMzKRLly72bkdERETkoubOnYunpycFBQXk5uZiMpl49913yc3N5aWXXmLhwoXWv2siIiJYsWIFM2bMoGfPngQFBWEYBj4+PgQF2egWZ+ehoCoicpZt27bRpUsXcnJy8PT0ZPbs2bRo0cLebYmIiIhcVK9evfjggw/IzMxk+vTpODo6MmTIEHbs2EFWVhbXXHNNqe3z8vJo166dnbo9PwVVEZGzNGvWjM2bN5Oens7333/P8OHDWbZsmcKqiIiIVHseHh5ERkYC8Mknn9CmTRtmzpxJq1atAJg3bx7169cvtY+Li4vN+7wYBVURkbM4Oztbf8G3b9+edevW8dZbbzFjxgw7dyYiIiJSfiaTiSeeeILx48ezZ88eXFxcSEpKomfPnvZu7aJ01V8RkYswm83k5ubauw0RERGRCrv11ltxcHBgxowZTJgwgXHjxjFr1iwSEhLYuHEj77zzDrNmzTrv/lFRUcyePduGHRfRiKqISAmTJ09mwIABNGzYkNOnT/Pll1+ydOlSfv31V3u3JiIiIlJhjo6OjBkzhldeeYXExET8/f2ZNm0a+/fvx9fXl5iYGJ544onz7h8fH096eroNOy5iWCwWi82riohUU/fffz+LFi0iOTkZHx8fWrduzcSJE8+58MAlObDi8o9RHllptqnj4GSbOgBB0bapU5hvmzpJq2xTx8tGV2xM/8s2dWLusU0dW8k+YZs6e2z0QVub221T50q0f6lt6phsNEYV1t02deSKphFVEZESZs6cae8WRERERGo9naMqIiIiIiIi1Yqm/oqI2ErSatvUSd1lmzoNO9umDoB7XdvUOZlkmzqZqbapY9jo8+g6Ybaps/kr29TpcK9t6tjqfbOVZ3zs3UHlesb25+RVuaXTbFMndrJt6sgVTSOqIiIiIiIiUq0oqIqIiIiIiEi1oqAqIiIiIiJSy6SlpTFs2DC8vb3x9fXl/vvvJyMj44L7fPTRR8TGxuLt7Y1hGJw8efKcbfbs2cNNN91EvXr18Pb2pnv37ixZsqTC/SmoioiUMG3aNDp27IiXlxcBAQEMGjSI+Ph4e7clIiIiUmGxsbHExcWVuW7YsGHs2LGDBQsWMHfuXJYvX86oUaMueLysrCz69+9/wfuu3nDDDRQUFLB48WI2bNhAmzZtuOGGG0hJSalQ7wqqIiIlLFu2jIcffpjVq1ezYMEC8vPzufbaa8nMzLR3ayIiIiKVYteuXcyfP5///Oc/dOrUie7du/POO+/w9ddfc/jw4fPuN3bsWCZNmkTnzmVfUPHYsWPs3buXSZMm0bp1a5o0acLLL79MVlYW27dvr1CPuo+qiEgJ8+fPL/U8Li6OgIAANmzYQI8ePezUlYiIiEjlWbVqFb6+vnTo0MG6rG/fvphMJtasWcPgwYMv6bh169alWbNmfPbZZ8TExODi4sKMGTMICAigffv2FTqWgqqIyAWkpxfdnsDPz8/OnYiIiIhUjpSUFAICAkotc3R0xM/Pr8JTdEsyDIOFCxcyaNAgvLy8MJlMBAQEMH/+fOrUqVOhY2nqr4jIeZjNZsaOHUu3bt1o1aqVvdsRERERuaCXXnoJT09P69fvv//O6NGjSy1LSqq6e4ZbLBYefvhhAgIC+P3331m7di2DBg1i4MCBJCcnV+hYGlEVETmPhx9+mO3bt7NixQp7tyIiIiJyUaNHj2bo0KHW58OGDWPIkCHcfPPN1mUhISEEBQWRmppaat+CggLS0tIICgq65PqLFy9m7ty5nDhxAm9vbwDef/99FixYwKxZs5g0aVK5j6WgKiJShjFjxlivgBcaGmrvdkREREQuys/Pr9TpSm5ubgQEBBAZGVlquy5dunDy5Ek2bNhgPXd08eLFmM1mOnXqdMn1s7KyADCZSk/cNZlMmM3mCh1LU39FREqwWCyMGTOG2bNns3jxYsLDw+3dkoiIiEilat68Of3792fkyJGsXbuWP/74gzFjxnD77bcTEhICwKFDh4iKimLt2rXW/VJSUti8eTP79u0DYNu2bWzevJm0tDSgKADXqVOH4cOHs2XLFvbs2cNjjz1GYmIi119/fYV6VFAVESnh4Ycf5vPPP+fLL7/Ey8uLlJQUUlJSyM7OtndrIiIiIpXmiy++ICoqij59+nDdddfRvXt3PvroI+v6/Px84uPjraOkAB9++CHt2rVj5MiRAPTo0YN27drx008/AVCvXj3mz59PRkYGvXv3pkOHDqxYsYIff/yRNm3aVKg/w2KxWCrhdYqIXBEMwyhz+aeffsqIESMu7+BJqy9v//JK3WWbOg3LvodalXCva5s6J6vuAhOlZKZefJvKYNjo8+g6Ybaps/kr29TpcK9t6tjqfbOVZ3zs3UHleibd3h1UvqXTbFMndrJt6sgVTeeoioiUoM/uREREROxPU39FRERERESkWtHUXxERW9n7m23q+DW2TZ1Th2xTByDDRlNlTQ62qWOrKZ8Fubap4+RumzoFObapc3ClberknbZNnd5TbFPnSvPdcNvViuhlmzrtR9imjq3Y6md06yzb1JFSNKIqIiIiIiIi1YqCqoiIiIiIiFQrCqoiIiIiIiK1TFpaGsOGDcPb2xtfX1/uv/9+MjIyLrrfqlWr6N27Nx4eHnh7e9OjR48yb+OXm5tL27ZtMQyDzZs3V7g/BVURkbMsX76cgQMHEhISgmEYzJkzx94tiYiIiFRYbGwscXFxZa4bNmwYO3bsYMGCBcydO5fly5czatSoCx5v1apV9O/fn2uvvZa1a9eybt06xowZg8l0bqx8/PHHCQkJueTedXsaEZGzZGZm0qZNG+677z5uvvlme7cjIiIiUql27drF/PnzWbduHR06dADgnXfe4brrruO11147b8AcN24cjz76KJMmTbIua9as2Tnb/fLLL/z222/873//45dffrmkHjWiKiJylgEDBvDCCy8wePBge7ciIiIiUulWrVqFr6+vNaQC9O3bF5PJxJo1a8rcJzU1lTVr1hAQEEDXrl0JDAykZ8+erFixotR2R44cYeTIkfz3v//F3f3SrwqvoCoiIiIiIlKLpKSkEBAQUGqZo6Mjfn5+pKSklLnP/v37AXjmmWcYOXIk8+fPJyYmhj59+rB3714ALBYLI0aMYPTo0aVC8KVQUBUREREREbkCvPTSS3h6elq/fv/9d0aPHl1qWVJS0iUd22w2A/Dggw9y77330q5dO6ZPn06zZs345JNPgKLpw6dPn2by5MmX/Vp0jqqIiIiIiMgVYPTo0QwdOtT6fNiwYQwZMqTUNTdCQkIICgoiNTW11L4FBQWkpaURFBRU5rGDg4MBaNGiRanlzZs3t4bfxYsXs2rVKlxcXEpt06FDB4YNG8asWbPK/VoUVEVERERERK4Afn5++Pn5WZ+7ubkREBBAZGRkqe26dOnCyZMn2bBhA+3btweKQqbZbKZTp05lHjssLIyQkBDi4+NLLd+zZw8DBgwA4O233+aFF16wrjt8+DD9+vXjm2++Oe9xz0dBVUREREREpBZp3rw5/fv3Z+TIkXz44Yfk5+czZswYbr/9dusVfw8dOkSfPn347LPPuOqqqzAMg8cee4ynn36aNm3a0LZtW2bNmsXu3bv5/vvvAWjYsGGpOp6engA0btyY0NDQCvWooCoicpaMjAz27dtnfZ6YmMjmzZvx8/M75xewiIiISE30xRdfMGbMGPr06YPJZGLIkCG8/fbb1vX5+fnEx8eTlZVlXTZ27FhycnIYN24caWlptGnThgULFtC4ceNK78+wWCyWSj+qiEgNtnTpUnr16nXO8uHDh5/3ptnlsve3S9+3Ivwq/x+LMp06ZJs6ABmpF9+mMpgcbFOnTpht6hTk2qaO06XffqBCCnJsU+fgStvUyTttmzq9p9imzpXmu+G2qxVx7r85VaL9CNvUsRVb/YxuLf95lVJ5NKIqInKW2NhY9BmeiIiIiP3o9jQiIiIiIiJSrWhEVUTEVlx9bVPHwdk2dSxm29QByLTR1F9bTcn18LdNnaw029TJPWWbOoaNPl9387VNHVdv29SZ/aBt6gyeYZs6ttJisL07qHwHVtimTlh329Sx1c/oGR8b1Um3TZ0aQiOqIiIiIiIiUq0oqIqIiIiIiEi1oqAqIiIiIiJSy6SlpTFs2DC8vb3x9fXl/vvvJyMj44L7pKSkcPfddxMUFISHhwcxMTH873//K7XNjTfeSMOGDXF1dSU4OJi7776bw4cPV7g/BVURkTK89957hIWF4erqSqdOnVi7dq29WxIRERGpkNjY2PPeWm/YsGHs2LGDBQsWMHfuXJYvX86oUaMueLx77rmH+Ph4fvrpJ7Zt28bNN9/M0KFD2bRpk3WbXr168e233xIfH8///vc/EhISuOWWWyrcu4KqiMhZvvnmG8aPH8/TTz/Nxo0badOmDf369SM11UYX9BERERGpQrt27WL+/Pn85z//oVOnTnTv3p133nmHr7/++oKjnytXruSRRx7hqquuIiIigqeeegpfX182bNhg3WbcuHF07tyZRo0a0bVrVyZNmsTq1avJz8+vUI8KqiIiZ3njjTcYOXIk9957Ly1atODDDz/E3d2dTz75xN6tiYiIiFy2VatW4evrS4cOHazL+vbti8lkYs2aNefdr2vXrnzzzTekpaVhNpv5+uuvycnJITY2tszt09LS+OKLL+jatStOTk4V6lFBVUSkhLy8PDZs2EDfvn2ty0wmE3379mXVqlV27ExERESkcqSkpBAQEFBqmaOjI35+fqSkpJx3v2+//Zb8/Hzq1q2Li4sLDz74ILNnzyYyMrLUdhMnTsTDw4O6deuSlJTEjz/+WOEeFVRFREo4duwYhYWFBAYGlloeGBh4wV/cIiIiIvb20ksv4enpaf36/fffGT16dKllSUlJl3z8KVOmcPLkSRYuXMj69esZP348Q4cOZdu2baW2e+yxx9i0aRO//fYbDg4O3HPPPVgslgrVcrzkLkVERERERKTaGD16NEOHDrU+HzZsGEOGDOHmm2+2LgsJCSEoKOica28UFBSQlpZGUFBQmcdOSEjg3XffZfv27bRs2RKANm3a8Pvvv/Pee+/x4YcfWretV68e9erVo2nTpjRv3pwGDRqwevVqunTpUu7XoqAqIlJCvXr1cHBw4MiRI6WWHzly5Ly/uEVERESqAz8/P/z8/KzP3dzcCAgIOGdqbpcuXTh58iQbNmygffv2ACxevBiz2UynTp3KPHZWVhZQdEpUSQ4ODpjN5vP2VLwuNze3Qq9FU39FREpwdnamffv2LFq0yLrMbDazaNGiCn0KKCIiIlJdNW/enP79+zNy5EjWrl3LH3/8wZgxY7j99tsJCQkB4NChQ0RFRVlv0RcVFUVkZCQPPvgga9euJSEhgddff50FCxYwaNAgANasWcO7777L5s2bOXjwIIsXL+aOO+6gcePGFf47SkFVROQs48eP5+OPP2bWrFns2rWLf/zjH2RmZnLvvffauzURERGRSvHFF18QFRVFnz59uO666+jevTsfffSRdX1+fj7x8fHWkVQnJyd+/vln/P39GThwIK1bt+azzz5j1qxZXHfddQC4u7vzww8/0KdPH5o1a8b9999P69atWbZsGS4uLhXqT1N/RUTOctttt3H06FGmTp1KSkoKbdu2Zf78+edcYElERESkOlu6dOl51/n5+fHll1+ed31YWNg5F0Bq0qQJ//vf/867T3R0NIsXL65wn2VRUBURKcOYMWMYM2aMvdsQERERqZU09VdERERERESqFcNS0RvaiIiIiIiIiFQhjaiKiIiIiIhItaKgKiIiIiIiItWKgqqIiIiIiIhUKwqqIiIiIiIiUq0oqIqIiIiIiEi1oqAqIiIiIiIi1YqCqoiIiIiIiFQrCqoiIiIiIiJSrSioioiIiIiISLWioCoiIiIiIiLVioKqiIiIiIiIVCsKqiIiIiIiIlKtKKiKiIiIiIhItaKgKiIiIiIiItWKgqqIiIiIiIhUKwqqIiIiIiIiUq0oqIqIiIiIiEi1oqAqIiIiIiIi1YqCqshFWCwWHnvsMUJCQjCZTBiGwYEDB6q0pmEYGIZBXFxchfZ75plnMAyDsLAwm9WsbmJjYzEMgxEjRti7FRERERG5RI72bkCkupszZw6vvfYaAM2bN8fb2xsXF5cqrdmpUycA/P39K7RfaGgonTp1Ijg4+LJrHjhwgPDwcACWLFlCbGxshY9ZVS7UW4sWLcjJyaFx48Z26k5ERERELpeCqshF7NixA4Dg4GB27txpk5qrV6++pP0eeOABHnjgAZvWrCx5eXk4Oztf9nHef//9SuhGREREROxJU39FLiA2NpYpU6YAkJycbJ0eazabeeutt2jVqhWurq7UqVOHW2+9lcTEROu+cXFx1u2/++472rVrh5ubGwMGDODo0aN8/PHHNGjQgLp16/LQQw+Rn59v3ffsabglj7VkyRJiYmJwc3MjJiamVMAsa+pvWFgYhmEwceJExowZQ926dQkICOCf//wnBQUFZdaMi4uzjlgC9OrVC8MwrO+HYRg0bNgQs9ls3WbIkCEYhkH//v3L9b4ahsHdd9/NY489RkBAAM2aNQNg+vTptG3bFj8/P5ycnPD39+fmm29mz5491vfifL2VPHbx1N8DBw6Uem033HAD7u7uhIeHM3PmzFJ9LV26lOjoaFxdXenevTvz5s27YqZEi4iIiNQkCqoiF9CiRQvq168PgLOzM506daJTp06MGTOGsWPHsmPHDiIjI3FwcOD777+na9eupKamnnOc4cOHk5OTQ25uLvPnz6dnz548/PDDuLu7k5aWxgcffMAnn3xSrp4GDBhAVlYWBQUFbNq0idtvv71U4Dyf6dOn89VXX+Hm5sbRo0d5++23+fTTT8vc1t/fn7Zt21qfN2/enE6dOtGiRQtGjRqFg4MDf/75JwsXLgQgKyuL+fPnW19reX377be89dZbBAYG4u3tDcCyZcvYt28fQUFBREVFceLECWbPnk2fPn3Iycm5YG8XM2rUKHbs2IGTkxMHDhxg1KhR7N69G4CUlBRuuOEGtm/fjslk4vjx49x2223lfi0iIiIiUnkUVEUu4P3337dOpQ0ODmb16tV89dVXfPjhhwDMmjWL7du3c+DAAUJDQ0lJSeGdd9455zhPPvkku3bt4s477wRg165dfPrpp8THx9O9e3eg6FzL8nj11VfZvXs3r7/+OgAHDx5k3759F90vNDSU/fv3s2/fPkJCQgBYtGhRmdtef/31zJ49u9T7sHr1at5//30aNGjA9ddfD2AN17/88gtZWVl4e3szaNCgcr2OYuvWrWPbtm1s3LgRgJdeeokTJ06wc+dOtm3bZg3Af/31F3/88ccFe7uYm266if379/P7778DYDabWbp0KQDvvfcemZmZmEwmVq9eza5duxg3blyFXouIiIiIVA4FVZEKWr9+PRaLBSgaPTQMAy8vL/766y+g7HM9Bw4cCFBqSm7xsoiICACOHDlSrvp33303QKkRxPLse+ONN+Lj44Orq6t16mx5a57tH//4B1B0oakTJ07wv//9D4Bbb70VNze3ch+nV69etGnTBgAHBwegKHj36tULb29vTCYT11xzjXX7w4cPX1K/xYYNG4ZhGGW+d8XnIkdFRdG6dWsAhg4deln1REREROTS6GJKIpehbdu251wBuFGjRudsVzyt1dHR8ZxlhmEAWMPvxfj6+p5zrPLsW7xfyX3LW/Ns/fr1o3HjxiQkJPDpp58yd+5coGLTfgECAwNLPd+/fz+DBg0iLy8PLy8v2rdvT0FBAZs3bwagsLDwkvotdqnvnYiIiIjYlkZURSqoffv21nA5YsQIVq9ezerVq1m1ahWvvvoqjz76qJ07rBzu7u7Wx5mZmaXWGYbBgw8+CMDUqVM5ffo04eHh1mnM5VX8PhbbtGkTeXl5APz666+sW7eOiRMnVqi3S9WqVSsA4uPj2bVrF1B0Dq2IiIiI2J6CqkgFRUREMHLkSADGjh1LREQErVu3xtfXlx49eljPtazp/P39qVu3LlA03bhTp06lzr+97777cHFxsQbFe+6555zgWVEtW7a0TgHu378/0dHRPPLIIxXu7VI89NBDeHh4UFhYSMeOHWnevDlvvPHGZR1TRERERC6NgqrIJfjggw+YPn060dHRHD58mIMHDxIWFsb48eOtt0mp6QzD4OOPPyYyMpJTp06xdu1aDh48aF1ft27dUudw3nPPPZddMyoqik8++YTw8HDy8vKoV68eX331VYV7uxRBQUHMnTuXli1bkp+fj6+vL//5z3+s6yty7q2IiIiIXB7DohO0ROQSvfzyy0yePJmrr76a5cuX27udy7Z3716aNGliff7iiy/y1FNPAUVXao6KirJXayIiIiK1ii6mJCIV9sMPP/Dll1/yyy+/APDYY4+VWj948GCSk5PL3Hf27NkEBwdXeY+X4tZbbyUvL48mTZpw+PBh1q9fD8Bdd92lkCoiIiJiQwqqIlJhW7du5X//+x/+/v48+eST1lvtFNu0adN5p+Lm5ubaosVLMmDAAL799lt+++03DMOgTZs23HPPPVfMBbJEREREagpN/RURsZGVh1fapM7GVNtc0MtsNtukDoAF2/xTdfDU5Z3rXF49G/S0SZ09aXtsUie30DYfQIX7hNukjq3+G2pWp5lN6jg7ONukTlZ+lk3qPNT2IZvUiZ4VbZM6AK/3fN0mdbILsm1S56bIm2xS5/3N79ukjq3Y6v/bNYUupiQiIiIiIiIA/PHHH0RHR+Pk5MSgQYPs1oeCqoiIiIiIyBVgxIgRGIaBYRg4OTkRHh7O448/Tk5OTrmPMX78eNq2bUtiYiJxcXFV1+xFKKiKyAVZLBZGjRqFn58fhmGwefNmm/cQGxvL2LFjrc/DwsJ48803rc8Nw2DOnDk270tERESkuunfvz/Jycns37+f6dOnM2PGDJ5++uly75+QkEDv3r0JDQ3F19e36hq9CAVVEbmg+fPnExcXx9y5c0lOTqZVq1b2bol169YxatSoKq1x4MABuwVzERERkUvl4uJCUFAQDRo0YNCgQfTt25cFCxYARdeXmDZtGuHh4bi5udGmTRu+//574O+/fY4fP859992HYRh2HVHVVX9F5IISEhIIDg6ma9eu9m7Fyt/fv0qPn5eXV6XHFxEREbGF7du3s3LlSho1agTAtGnT+Pzzz/nwww9p0qQJy5cv56677sLf35/u3buTnJxMs2bNeO6557jtttvw8fGxW+8aURWR8xoxYgSPPPIISUlJGIZBWFjYBT+JA1i6dCmGYfDrr7/Srl073Nzc6N27N6mpqfzyyy80b94cb29v7rzzTrKyLu0KkWdP/T3b008/TXBwMFu3bgVgxYoVXH311bi5udGgQQMeffRRMjMzSx3v+eef55577sHb25tRo0YRHl50ddF27dphGAaxsbGX1KuIiIiILc2dOxdPT09cXV2Jjo4mNTWVxx57jNzcXF566SU++eQT+vXrR0REBCNGjOCuu+5ixowZODg4EBQUhGEY+Pj4EBQUhJubm91eh0ZUReS83nrrLRo3bsxHH33EunXrcHBwuOAncT17/n3LjWeeeYZ3330Xd3d3hg4dytChQ3FxceHLL78kIyODwYMH88477zBx4sRK69disfDoo48yd+5cfv/9dyIjI0lISKB///688MILfPLJJxw9epQxY8YwZswYPv30U+u+r732GlOnTrWew/Hwww9z1VVXsXDhQlq2bImzs21u7yAiIiJyOXr16sUHH3xAZmYm06dPx9HRkSFDhrBjxw6ysrK45pprSm2fl5dHu3bt7NTt+Smoish5+fj44OXlZf2ErfiTuIULF9KlSxcAIiIiWLFiBTNmzCgVVF944QW6desGwP3338/kyZNJSEggIiICgFtuuYUlS5ZUWlAtKCjgrrvuYtOmTaxYsYL69esDRVNchg0bZr0YU5MmTXj77bfp2bMnH3zwAa6urgD07t2bf/3rX9bjOTg4AFC3bl2CgoIqpUcRERGRqubh4UFkZCQAn3zyCW3atGHmzJnW64zMmzfP+ndSMRcXF5v3eTEKqiJSbvv27Sv3J3GtW7e2Pg4MDMTd3d0aUouXrV27ttJ6GzduHC4uLqxevZp69epZl2/ZsoWtW7fyxRdfWJdZLBbMZjOJiYk0b94cgA4dOlRaLyIiIiLVgclk4oknnmD8+PHs2bMHFxcXkpKSSg0uVFcKqiJSbhkZGUD5PolzcnKyPi6+l1dJhmFgNpsrrbdrrrmGr776il9//ZVhw4aV6vnBBx/k0UcfPWefhg0bWh97eHhUWi8iIiIi1cWtt97KY489xowZM5gwYQLjxo3DbDbTvXt30tPT+eOPP/D29mb48OFl7h8VFcW0adMYPHiwTftWUBWRcmvRokW1/STuxhtvZODAgdx55504ODhw++23AxATE8POnTutU2DKq/ic1MLCwkrvVURERMRWHB0dGTNmDK+88gqJiYn4+/szbdo09u/fj6+vLzExMTzxxBPn3T8+Pp709HQbdlxEQVVEys3Ly+uSPomzlcGDB/Pf//6Xu+++G0dHR2655RYmTpxI586dGTNmDA888AAeHh7s3LmTBQsW8O677573WAEBAbi5uTF//nxCQ0NxdXW16yXaRURERC7mfPc9nTRpEpMmTQLgn//8J//85z/Pe4yTJ0+Wem6xWCqrvQpRUBWRCnn++ecr/EmcLd1yyy2YzWbuvvtuTCYTN998M8uWLePJJ5/k6quvxmKx0LhxY2677bYLHsfR0ZG3336b5557jqlTp3L11VezdOlS27wIERERkVrOsNgrIouI1DIrD6+0SZ2NqRttUqcyzzG+GAu2+afq4KmDNqnTs4Ftps7vSdtjkzq5hbk2qRPuE26TOrb6b6hZnWY2qePsYJvba2XlX9q9sSvqobYP2aRO9Kxom9QBeL3n6zapk12QbZM6N0XeZJM6729+3yZ1bMVW/9+uKUz2bkBERERERESkJE39FRG7SkpKokWLFuddv3PnzlJX563JZu2YZZM6MQExNqljcrLdZ50Ghk3qDAgfYJM6y/5cZpM6Tf2a2qSOi4Nt7r+XmJ5okzr9GvWzSZ34E/E2qXM677RN6rg5utmkjq1GOrcN32aTOgD/Wvavi29UCdwcbPMzstWIqlzZFFRFxK5CQkLYvHnzBdeLiIiISO2iqb8iYleOjo5ERkae98vRUZ+niYiIiFwKi8XC1KlTCQ4Oxs3Njb59+7J3794L7jNt2jQ6duyIl5cXAQEBDBo0iPj40jNAYmNjMQyj1Nfo0aMrtXcFVZFazGKxMGrUKPz8/DAM44Ijm1UlNjaWsWPHXnCbsLAw3nzzTZv0IyIiInKleOWVV3j77bf58MMPWbNmDR4eHvTr14+cnJzz7rNs2TIefvhhVq9ezYIFC8jPz+faa68lMzOz1HYjR44kOTnZ+vXKK69Uau8aqhCpxebPn09cXBxLly4lIiKCevXq2bulMq1btw4PDw97tyEiIiJSY1gsFt58802eeuopbrqp6Lzhzz77jMDAQObMmcPtt99e5n7z588v9TwuLo6AgAA2bNhAjx49rMvd3d0JCgqqsv41oipSiyUkJBAcHEzXrl0JCgqqttNs/f39cXd3r9IaeXl5VXp8EREREVtKTEwkJSWFvn37Wpf5+PjQqVMnVq1aVe7jpKenA+Dn51dq+RdffEG9evVo1aoVkydPJiurcm9RpaAqUkuNGDGCRx55hKSkJAzDICwsDLPZzLRp0wgPD8fNzY02bdrw/fffW/dZunQphmHw66+/0q5dO9zc3Ojduzepqan88ssvNG/eHG9vb+68884K/bIqKChgzJgx+Pj4UK9ePaZMmULJWzyfPfXXMAz+85//MHjwYNzd3WnSpAk//fSTdX1hYSH333+/9XU0a9aMt95665zXP2jQIF588UVCQkJo1qwZzz33HK1atTqnv7Zt2zJlypRyvx4RERERe0tJSQEgMDCw1PLAwEDruosxm82MHTuWbt26lfob6c477+Tzzz9nyZIlTJ48mf/+97/cddddldc8mvorUmu99dZbNG7cmI8++oh169bh4ODAtGnT+Pzzz/nwww9p0qQJy5cv56677sLf35+ePXta933mmWd49913cXd3Z+jQoQwdOhQXFxe+/PJLMjIyGDx4MO+88w4TJ04sVy+zZs3i/vvvZ+3ataxfv55Ro0bRsGFDRo4ced59nn32WV555RVeffVV3nnnHYYNG8bBgwfx8/PDbDYTGhrKd999R926dVm5ciWjRo0iODiYoUOHWo+xaNEivL29WbBgAVD0KeOzzz7LunXr6NixIwCbNm1i69at/PDDD5fyNouIiIjYxBdffMGDDz5ofT5v3rzLPubDDz/M9u3bWbFiRanlo0aNsj6Ojo4mODiYPn36kJCQQOPGjS+7LiioitRaPj4+eHl54eDgQFBQELm5ubz00kssXLiQLl26ABAREcGKFSuYMWNGqaD6wgsv0K1bNwDuv/9+Jk+eTEJCAhEREQDccsstLFmypNxBtUGDBkyfPh3DMGjWrBnbtm1j+vTpFwyqI0aM4I477gDgpZde4u2332bt2rX0798fJycnnn32Weu24eHhrFq1im+//bZUUPXw8OA///kPzs7O1mX9+vXj008/tQbVTz/9lJ49e1pfm4iIiEh1dOONN9KpUyfr89zcXACOHDlCcHCwdfmRI0do27btRY83ZswY5s6dy/LlywkNDb3gtsV19+3bV2lBVVN/RQQo+sWSlZXFNddcg6enp/Xrs88+IyEhodS2rVu3tj4ODAzE3d29VJALDAwkNTW13LU7d+6MYRjW5126dGHv3r0UFhaed5+SPXh4eODt7V2q5nvvvUf79u3x9/fH09OTjz76iKSkpFLHiI6OLhVSoegKdl999RU5OTnk5eXx5Zdfct9995X7tYiIiIjYg5eXV6lb/LVo0YKgoCAWLVpk3ebUqVOsWbPGOihRFovFwpgxY5g9ezaLFy8mPDz8orWL7xxRMhBfLo2oiggAGRkZQNE0kfr165da5+LiUuq5k5OT9bFhGKWeFy8zm81V1Om5PZxd8+uvv2bChAm8/vrrdOnSBS8vL1599VXWrFlTap+yriQ8cOBAXFxcmD17Ns7OzuTn53PLLbdU3QsRERERqQKGYTB27FheeOGF/2fvzsOiKt/Hj78HEBiYAYKQRRRQAXHHMBU3JAzcl1K+aukouKS4Ru4LblAWpWauJbimttjmVpJaghKWlJaZEkQmarmGpCLM7w9/nI8ju+KIer+ua67LOedZ7jlzQO7zPOc5eHl54enpyYwZM3B1daVnz55KuWeeeYZevXoRGRkJ3Jruu3HjRj799FO0Wq1yP6utrS1qtZr09HQ2btxI586dcXBw4KeffmL8+PG0a9fOYCDhXkmiKoQAoH79+lhYWJCVlWUwzdcY7kwgDx48iJeXF6ampnfVXlJSEgEBAYwcOVLZdueocEnMzMwYNGgQ8fHxmJub83//93+o1eq7ikMIIYQQ4kGaOHEiV69eZdiwYVy6dIk2bdqwc+dOLC0tlTLp6en8888/yvtly5YBt551f7v4+Hh0Oh3m5ubs3r2bhQsXcvXqVWrWrMlzzz3H9OnTKzV2SVSFEMCt6SJRUVGMHz+egoIC2rRpw+XLl0lKSsLGxoZBgwbdt76zsrKYMGECw4cP54cffuDtt98mLi7urtvz8vJi7dq17Nq1C09PT9atW0dqamq5pq4ARERE4OvrC9xKeoUQQgghHkYqlYo5c+YwZ86cEstkZmYavL/9yQvFqVmzJvv27auM8EoliaoQQjF37lwcHR2JjY3l999/x87OjmbNmjF16tT72u/AgQP577//ePrppzE1NWXs2LEGq8lV1PDhwzl8+DBhYWGoVCr69evHyJEj2bFjR7nqe3l5ERAQwIULFwwWJRBCCCGEEMah0peVMgshxGNGr9fj5eXFyJEjmTBhQqW1O/yr4WUXqgTNqjczSj8mJsZbj0+FquxClcDdxt0o/ez78/5fiQbwtvc2Sj8WphZlF6oEGZczjNKPsX6Gjl88bpR+buTfMEo/ajPj3Cax7MdlRunnyKAjRukH4OV9LxulH7Wpcb6jeW3mGaWfpWlLjdKPsYxsOrLsQo8RGVEVQojb/P3332zatIkzZ84wePDgBx2OEEIIIcRjSUZUhRD3TVZWFvXr1y9x/y+//EKtWrWMGFHZVCoVTz75JIsWLaJ///4POhwhhBBCiMeSJKpCiPvm5s2bRW7Qv52HhwdmZjKxQwghhBBCGJJEVQghhBBCCCFElWK8lTCEEEIIIYQQQohykERVCCGEEEIIIUSVIomqEEIIIYQQQogqRRJVIYQQQgghhBBViiSqQgghhBBCCCGqFElUhRBCCCGEEEJUKZKoCiGEEEIIIYSoUiRRFUIIIYQQQghRpUiiKoQQQgghhBCiSpFEVQghhBBCCCFElSKJqhBCCCGEEEKIKkUSVSGEEEIIIYQQVYokqkIIIYQQQgghqhRJVIUQQgghhBBCVCmSqAohhBBCCCGEqFIkURVCCCGEEEIIUaVIoioeW4GBgahUKgIDAx90KA/EyZMnCQ4OxsbGpkoeB51OVyXiUqlUqFQqEhISHmgcQgghhBCPE0lUhXhMvfzyyyQmJpKXl0fz5s2pX7/+A4mjpESwTp06tGjR4oHFJYQQQgghHhyzBx2AEOLB+PnnnwEYN24csbGxDziaombMmMGMGTMedBhCCCGEEOIBkBFV8Vi4ePEiffv2xcrKilq1arF8+fIiZSZPnkyDBg2ws7OjWrVquLq6MmjQILKzs5Uy0dHRygjgjh078Pb2xtramgEDBnD16lXmzZuHo6MjLi4uzJo1y6D9QYMG4eXlhVarxdzcHHd3d8aMGcOVK1eUMnq9nhkzZvDkk09iZ2dHZGQkU6dOVfq83fr162nevDlWVlZotVpCQ0NJS0sr81hkZmaiUqlIT08H4NVXX0WlUqHT6di7d6/SV2ZmplLnzlHPhIQEZduePXto1qwZarWaZs2acfDgQYP+Dh06RI8ePXBwcMDCwoLatWsTFxen9FVo8ODBqFQqPDw8gOKn/v73339MmzaNunXrYm5ujr29PT179uTIkSNKmfLGlpaWxjPPPIOLiwsWFhZYW1vTvHlz1q9fX+YxFEIIIYQQ95leiMdA79699YAe0Pv4+Oitra311tbWekDfvn17vV6v1zdp0kRva2urb9iwob5evXp6lUqlB/TNmzdX2pk1a5bSjkaj0fv4+CjvfX199Wq1Wl+7dm1l286dO5W6tra2egcHB32TJk0Myjz//PNKmcWLFyvba9Sooa9evboS5+0/rq+99pqyzdvbW+/q6qoH9NbW1vpffvml1GNx+vRpfYsWLfTm5uZKPy1atNDPmTNHv2fPHqXdjIwMpU7htvj4eL1er9fHx8cr2ywsLPQ+Pj56MzMzPaB3d3fX5+Xl6fV6vT4pKUnpx9zcXN+gQQO9g4ODvkePHvrvv/9e36JFC6Wd2rVr61u0aKHv2bOnXq/X6wcNGmTw/ej1en1wcLAe0KtUKn29evX0Go1G+S6OHTtWodi2bt2qNzEx0bu7u+v9/Pz0TzzxhFLviy++KPGzCyGEEEKI+08SVfHIO3nypJJsTJo0Sa/X6/W//vqrkrwUJkI//fSTPj8/X6m3atUqpd7Jkyf1er1horp+/Xq9Xq/Xt27dWtm2f/9+fX5+vt7d3d2gP71er09LSzOIa9q0aXpAb2Zmpv/vv//0er1e7+bmpgf0rVq10t+4cUOfk5NjkAzr9Xr91atX9VZWVnpAP3v2bL1er9fn5eXp/f399YD+hRdeKNdxKYxx1qxZyra7SVQXL16s1+v1+kWLFinbCpPGDh066AG9nZ2d/vjx43q9Xq/Pz883OBYlJYJ3Jqpff/21Uvatt97S6/V6/Z9//qkkqwMHDqxQbNnZ2fozZ84o/f3333/6unXrFjmGkqgKIYQQQhifTP0Vj7zCezEBnnvuOQB8fHxo3LixQbm0tDSaN2+ORqNBpVIxdOhQZd/p06eLtNutWzcAZarqE088QevWrTExMcHd3R2As2fPKuV3795Nw4YNUavVqFQq5s+fD8DNmzf5+++/uXLlCqdOnQKgV69eVKtWDWtra7p06VLk8+Tm5gIwa9YsVCoV1apV49ChQwBFpt7eby+++CKAwaJHhZ87JSUFgOeffx5vb28ATExMaNKkSYX7SU1NVf7dv39/ANzc3Gjbti2A8vnLG5tKpeLll1/G1dUVMzMz1Go1J0+eBIr/voUQQgghhPHIYkpCAPv372fQoEHo9XocHByoX78+OTk5HDt2DID8/PwidWxsbAAwMzMzeA8o917q9XoANmzYQFRUFAAuLi7UrFmTf/75h99//73E9svD19fXoF8ABweHu2oLMLhntDCmy5cvl1rHzs4O+N9xgP997gettNheeOEFdu/ejUqlon79+mg0Gn755Rf+/fffu/4+hBBCCCFE5ZARVfHIu300bevWrQD89ttv/PTTT8r2lJQUJYE5cuQI3333HQMHDqy0GApHObVaLRkZGaSkpPDss88alLGxsaFmzZoAfPHFF9y8eZPc3Fy2bdtmUK5Bgwao1WoAQkNDOXDgAAcPHuTgwYMsW7aMadOm3XWc1atXV/7922+/AfDBBx/cdXstWrQA4KOPPlJGK/V6vcGxL/wsV69eLbWt5s2bK//euHEjAKdOneLbb78FwN/fv0KxFX4nQ4cO5ejRo2zfvh2NRlOhNoQQQgghxP0hiap45NWtW5eePXsCEBsbi6+vL82aNcPU1FQpc/s04EaNGuHr68vrr79eaTEUtv/vv/9Su3ZtateuzZYtW4qUe+WVVwD45ptvqF27Np6envz5558GZaysrJTHtrz11lu4ubnRtGlTHBwcaNasGV9++eVdx+nl5UWtWrWAW9NrO3TowKhRo+66vXnz5mFubs7Fixdp0KABjRo1onr16sycOVMpU69ePeDWqstPP/00U6dOLbatDh06EBwcDMCECROoX7++MvKt0WiYMmVKhWIr/E7effddGjRoQJ06dbh27drdfEwhhBBCCFHJJFEVj4X33nuP5557DktLSy5fvsycOXNo2bKlsr9jx4689tpruLq68t9//1GvXj2WLVtWaf2Hh4czYcIEnnzySf79918CAwOZM2dOkXKRkZFMnz4de3t7Ll++TK9evQgPDwfA0tJSKTdlyhTWrFlD8+bNuXjxIidPnqR69eqMGDGC3r1733WcZmZmbN68GT8/P65du8aFCxeUUei7ERAQQFJSEt26dUOj0XD8+HE0Gg1t2rRRyixevJhGjRpx48YNUlNTlZHc4nz22WdMnToVT09PTpw4gZmZGT169CA5OVlJeMsrISGBDh06YGlpSW5uLgsXLixy37IQQgghhHgwVPqqcjOZEILLly9z/fp1ZQrutWvXaN68OUePHqVly5YcOHDgAUcohBBCCCHE/SeLKQlRhWRkZNCyZUuefvpp7Ozs+P777zl9+jSmpqbMnj273O1s27aNuXPnFruvS5cuytRhIYQQQgghqiJJVIWoQhwdHWnXrh2HDx/m0qVL2Nra0rlzZyZPnqw8hqU8/v77b+XRMHeq6BRZUXkyw/7PKP1U+/+Lct1vNiEhRukHAH2BUbq5+fc/Runn38REo/SjN9IK1tVcXIzSj6lWa5R+NB06GKUfdeNGRunH5BFbKO5YPV+j9OP76zGj9COEKJ4kqkJUITVq1LinxZAK6XQ6dDrdvQckhBBCCCEeK0lJSYwYMYJff/2VLl268MknnzyQOGQxJSGEEEIIIYR4BOh0OlQqFSqVimrVquHp6cnEiRMr9GSDCRMm0LRpUzIyMkhISLh/wZZBElUhxGMvMDCQcePGPegwhBBCCCHuWWhoKNnZ2fz++++89dZbrFixglmzZpW7fnp6OkFBQbi5uWFnZ3f/Ai2DJKpCCCGEEEII8YiwsLDA2dmZmjVr0rNnT4KDg/nqq68AKCgoIDY2Fk9PT9RqNU2aNOHDDz8EIDMzE5VKxfnz5xkyZAgqleqBjqjKPapCCCGEEEII8Qg6evQoycnJuLu7AxAbG8v69etZvnw5Xl5efPPNN7zwwgs4OjrSpk0bsrOz8fHxYc6cOYSFhWFra/vAYpdEVQghbuPh4cGwYcM4efIkH3zwAU888QTTp09n2LBhDzo0IYQQQogyffHFF2g0Gm7evMn169cxMTFhyZIlXL9+nZiYGHbv3k2rVq0AqF27Nvv372fFihW0b98eZ2dnVCoVtra2ODs7P9DPIVN/hRDiDnFxcfj7+3P48GFGjhzJSy+9xPHjxx90WEIIIYQQZerQoQNpaWmkpKQwaNAgBg8ezHPPPcfJkyfJzc2lY8eOaDQa5bV27VrS09MfdNhFyIiqEELcoXPnzowcORKASZMm8dZbb7Fnzx58fHwecGRCCCGEEKWztrambt26AKxevZomTZrw3nvv0bBhQwC2bdtGjRo1DOpYWFgYPc6ySKIqhBB3aNy4sfJvlUqFs7Mz586de4ARCSGEEEJUnImJCVOnTmXChAn89ttvWFhYkJWVRfv27R90aGWSqb9CCHGHatWqGbxXqVQUFBQ8oGiEEEIIIe5enz59MDU1ZcWKFURFRTF+/HjWrFlDeno6P/zwA2+//TZr1qwpsX69evXYunWrESO+RUZUhRBCCCGEEOIRZWZmRmRkJAsWLCAjIwNHR0diY2P5/fffsbOzo1mzZkydOrXE+sePH+fy5ctGjPgWSVSFEEIIIYQQ4hFQ0nNPJ0+ezOTJkwEYO3YsY8eOLbGNS5cuGbzX6/WVFV6FyNRfIYQQQgghhBBVioyoCiEee3v37lX+nZmZWWR/Wlqa0WIRQgghhBAyoiqEEEIIIYQQoopR6R/UpGMhhHjM/Pfjj0bpJ+/PP43Sz5Vdu4zSDwAq41xXNXN80ij9aJ95xij9qExNjdJPXna2UfrJ//dfo/STs2ePUfr576cjRumnICfHKP0Yi++vx4zSz7F6vkbp51Ek39HdMdZxe1jIiKoQQgghhBBCiCpFElUhhBBCCCGEeMzMnz+fgIAArKyssLOzK1cdvV7PzJkzcXFxQa1WExwczIkTJ5T9e/fuRaVSFftKTU2tUHySqAohqqTAwEDGjRsHgIeHBwsXLnyg8QghhBBCPGwCAwNLfGTNjRs36NOnDy+99FK521uwYAGLFy9m+fLlpKSkYG1tTUhICNeuXQMgICCA7Oxsg1dERASenp74+/tXKHZZ9VcIUeWlpqZibW39oMMQQgghhHhkzJ49Gyj52at30uv1LFy4kOnTp9OjRw8A1q5di5OTE5988gn/93//h7m5Oc7OzkqdvLw8Pv30U0aPHo1KpapQfDKiKoSo8hwdHbGysnrQYZCXl/egQxBCCCGEeCAyMjI4c+YMwcHByjZbW1tatGjBgQMHiq3z2Wefcf78eQYPHlzh/iRRFUJUeXdO/VWpVLz77rv06tULKysrvLy8+OyzzwzqHD16lE6dOqHRaHBycuLFF1/kn3/+Ufbv3LmTNm3aYGdnh4ODA127diU9PV3Zn5mZiUqlYvPmzbRv3x5LS0s2bNhw3z+rEEIIIURVdObMGQCcnJwMtjs5OSn77vTee+8REhKCm5tbhfuTRFUI8VCaPXs2ffv25aeffqJz584MGDCACxcuAHDp0iWCgoLw8/Pj0KFD7Ny5k7Nnz9K3b1+l/tWrV5kwYQKHDh0iMTERExMTevXqRUFBgUE/kydPZuzYsRw7doyQkBCjfkYhhBBCiIqIiYlBo9Eor2+//ZYRI0YYbMvKyjJKLKdOnWLXrl2Eh4ffVX25R1UI8VDS6XT069cPuPVLefHixXz33XeEhoayZMkS/Pz8iImJUcqvXr2amjVr8ttvv+Ht7c1zzz1n0N7q1atxdHTkl19+oWHDhsr2cePG0bt3b+N8KCGEEEKIezBixAiDC/MDBgzgueeeM/hbxtXV9a7aLrz39OzZs7i4uCjbz549S9OmTYuUj4+Px8HBge7du99Vf5KoCiEeSo0bN1b+bW1tjY2NDefOnQPgxx9/ZM+ePWg0miL10tPT8fb25sSJE8ycOZOUlBT++ecfZSQ1KyvLIFGt6Ap1QgghhBAPir29Pfb29sp7tVpN9erVqVu37j237enpibOzM4mJiUpieuXKFVJSUoqsHKzX64mPj2fgwIFUq1btrvqTRFUI8VC685eeSqVSks2cnBy6devGa6+9VqRe4RXAbt264e7uzqpVq3B1daWgoICGDRty48YNg/Ky2rAQQgghHkVZWVlcuHCBrKws8vPzSUtLA6Bu3brKxf569eoRGxtLr169UKlUjBs3jnnz5uHl5YWnpyczZszA1dWVnj17GrT99ddfk5GRQURExF3HJ4mqEOKR06xZMz766CM8PDwwMyv6a+78+fMcP36cVatW0bZtWwD2799v7DCFEEIIIR6YmTNnsmbNGuW9n58fAHv27CEwMBCA48ePc/nyZaXMxIkTuXr1KsOGDePSpUu0adOGnTt3YmlpadD2e++9R0BAAPXq1bvr+CRRFUI8ckaNGsWqVavo168fEydOxN7enpMnT7Jp0ybeffddnnjiCRwcHFi5ciUuLi5kZWUxefLkBx22EEIIIUSl2rt3b4n7EhISynyGql6vN3ivUqmYM2cOc+bMKbXexo0byxtiiWTVXyHEI8fV1ZWkpCTy8/N59tlnadSoEePGjcPOzg4TExNMTEzYtGkT33//PQ0bNmT8+PG8/vrrDzpsIYQQQgjx/8mIqhCiSrr9CmBmZqbBvjuv7sGtR9LczsvLi48//rjE9oODg/nll19KbNfDw6PYfoQQQgghxP0nI6pCCCGEEEIIIaoUlV6GDIQQQgghhBBCVCEyoiqEEEIIIYQQokqRRFUIIYQQQgghRJUiiaoQQgghhBBCiCpFElUhhBBCCCGEEFWKJKpCCCGEEEIIIaoUSVSFEEIIIYQQQlQpkqgKIYQQQgghhKhSJFEVQgghhBBCCFGlSKIqhBBCCCGEEKJKkURVCCGEEEIIIUSVIomqEEIIIYQQQogqRRJVIYQQQgghhBBViiSqQgghhBBCCCGqFElUhRBCCCGEEEJUKZKoCiGEEEIIIYSoUiRRFUIIIYQQQghRpUiiKoQQQgghhBCiSpFEVQghhBBCCCFElSKJqhCPsUOHDtGqVSusrKxQqVTodLpStwshhBBCCGEMkqgK8RgLDw/n4MGDVKtWjaeffpo6deqUur0yJCQkoFKpUKlUFaoXGBgoSbMQQgghxGPC7EEHIIR4cH7++WcAFixYwPDhw8vcLoQQQgghhDHIiKoQj6iCggIWLVpEw4YNsbS05IknnqBPnz5kZGSwd+9eVCoV+fn5AIwYMQKVSqWMWt65PTo6GoBff/2VPn364OjoiLm5Ob6+vixbtsygX71ez9KlS/Hz80OtVqPVann66adJS0tDp9MxePBgpWzhyGph+yVRqVTs27cPgDVr1ij1Tp48iYmJCSqVit27dyvlP//8c1QqFaampvz1118Go7h79+7Fz88PS0tLGjdurLRbKCUlhc6dO2NnZ4elpSXNmjXjww8/vKvvQAghhBBC3B1JVIV4REVGRjJu3Dh+/vln6tati6mpKR9++CEBAQFYWVnRokULpWzt2rVp0aIFnTt3Lna7m5sbJ06coGXLlnz44YcUFBTg4+PD8ePHGTlyJHPmzFHqjBkzhlGjRpGWloa1tTXu7u78+OOPZGZmUqdOHWrXrq2UbdGihdJ+aVq0aIFWqwXgySefVOpZW1sTHBwMwOrVq5XyH330EQDBwcHUqFHDoK0uXbpw/fp1TExMOHLkCF26dOH06dMAJCUl0bZtW3bs2IFarcbDw4PDhw/Tp08f1q5dW6HjL4QQQggh7oFeCPHI+f333/UqlUoP6NesWaPX6/X6f//9V+/m5qYH9NOnT9fr9Xo9oAf08fHxBvWL267T6fSAvmHDhvqrV6/q9Xq9fuHChXpAr1ar9VeuXNFnZGQo/fbq1Ut//fp1vV6v1587d07/559/6vV6vT4+Pl5pvyLat2+vB/SDBg0y2P7xxx/rAb2lpaX+4sWL+hs3buifeOIJPaBfv359kT6XL1+u1+v1+qNHj+rNzMz0gH7SpEl6vV6vDwwM1AP6jh076vPy8vR6vV4/btw4PaB3c3OrULxCCCGEEOLuyT2qQjyCDh06hF6vB2DQoEEMGjTIYP/Bgwcr3OZ3330HwNGjR7G2tjbY999///HTTz9x+vRppd+XX34Zc3NzABwdHSvcX3l169aNGjVq8Ndff7Fx40bq1q3LxYsX0Wq19OrVq0j5fv36AdCgQQMaNWrE4cOHOXLkiMFn/Oqrr6hWrZpBvVOnTvHXX38VGaEVQgghhBCVTxJVIR5xTZs2xcLCwmCbu7v7Xbf35JNPFrsKsKmp6V23eS/MzMwYNmwYs2bNIj4+nmbNmgHQp08frKys7qrNGjVqFDsd+ebNm/cUqxBCCCGEKB9JVIV4BD311FOoVCr0ej06nY6xY8cCtxY62r9/P7a2thVus3nz5vzyyy/Y2tqyfft27O3tAfjnn39ITEykZcuWODs7K/0uXLiQ5s2bY25uzvnz5/nvv/9wc3MzSB6vXr1aZHS2JIX1rl69WmRfREQEc+fO5dChQxw7dgyAgQMHFtvO5s2bGTp0KMeOHVNGUhs1aqR8xn379uHu7s7u3btRq9XArdHU77///p4SfCGEEEIIUX6ymJIQj6DatWszdOhQAMaNG0ft2rVp3LgxdnZ2tGvXjh9++KHCbU6ZMgUbGxvS09OpWbMmfn5+uLu74+zszKRJkwDw8PBg1KhRAHz44YfUqFGDRo0aUaNGDQ4dOgRAvXr1lDbr169Py5YtSUpKKrP/wnoff/wxzZo1IzQ0VNnn6upKjx49gFuJrIeHB+3atSu2naioKBo0aIC/vz83b97EysqK0aNHAzBnzhzMzMxITk7GxcUFPz8/3NzcqFWrFm+99VZFD5kQQgghhLhLkqgK8YhatmwZb731Fo0aNeL06dP88ccfeHh4MGHCBAIDAyvcno+PDwcOHFCm1P78888UFBQQGhrK3LlzlXKLFy/mnXfeoWnTpuTk5JCRkUHjxo3x8PAAoHHjxsyYMQMnJyeysrJISUnh4sWLZfYfFRVFcHAwVlZWHD58WEl8C40cOVL594svvohKpSq2nR07dmBpacnNmzdp2LAhn3/+uXLfabt27fjmm2/o1KkTKpWKX375hWrVqvHcc88RFRVV0UMmhBBCCCHukkpfuPKJEEI8xM6cOYOLiwsqlYoTJ04Y3EebkJCgPL9VfuUJIYQQQlR9co+qEOKBy87OLnaFXgAXFxe2bt1aYt1//vmHsWPHKiOsvXr1KnaxJyGEEEII8fCQRFUI8cBdv36dlJSUYveVtYBRTk4OGzduxNLSktDQUJYvX34/QqwUl87mGqWfvOv5RumnmoXxVno21kh4Qb5x+nGooTFKP8Y650zNjHMnkdbB0ij95F6+YZR+TMyKv0WhsllaVyu7UCU4+f05o/RT96nqRunHWJ8H4NSvF4zSz0Uj/U7oNaGZUfp5Z8TXRunHWEYtD3rQIVQpco+qEOKB8/DwQK/XF/vKzMwsV93//vuPHTt2FPvMVp1Op7QnhBBCCCFKlpSURKNGjahWrRo9e/Z8YHFIoiqEEEIIIYQQjwCdTodKpUKlUlGtWjU8PT2ZOHEi165dK3cbEyZMoGnTpmRkZJCQkHD/gi2DJKrikabX6xk2bBj29vaoVCrS0tLuW1+BgYGMGzeu3OUzMzMrHFN0dDRNmzatcGz32918FiGEEEIIUflCQ0PJzs7m999/56233mLFihXMmjWr3PXT09MJCgrCzc0NOzu7+xdoGSRRFY+0nTt3kpCQwBdffEF2djYNGza8b319/PHHBo9pKUvNmjUrHFNUVBSJiYnKe51OV6lTMnQ6XZlTbYUQQgghRNVlYWGBs7MzNWvWpGfPngQHB/PVV18BUFBQQGxsLJ6enqjVapo0acKHH34I/G/g4fz58wwZMgSVSiUjqkLcL+np6bi4uBAQEICzszNmZvdv/TB7e3u0Wm25y5uamlY4Jo1Gg4ODw92EV6ILFy7wzjvvGNy/mZ6ezoYNGyq1HyGEEEIIYVxHjx4lOTkZc3NzAGJjY1m7di3Lly/n559/Zvz48bzwwgvs27dPGUSxsbFh4cKFZGdnExYW9sBil0RVPLJ0Oh2jR48mKysLlUqFh4cHUPqVJIC9e/eiUqnYtWsXfn5+qNVqgoKCOHfuHDt27MDX1xcbGxv69+9Pbu7/Vs+7c+qvh4cHMTExDBkyBK1WS61atVi5cqWy/87psoX9JiYm4u/vj5WVFQEBARw/flypc/vU3+joaNasWcOnn36q3Iuwd+9egoKCiIyMNDgWf//9N+bm5gajsYUsLS3566+/CA0N5dSpUyxfvhydToenp2eJx/a7777Dz88PS0tL/P39OXz4sMH+/Px8wsPDlWPs4+PDokWLinw/PXv2JCYmBicnJ+zs7JgzZw43b97klVdewd7eHjc3N+Lj4w3qTZo0CW9vb6ysrKhduzYzZswgLy/PoMy8efOoXr06Wq2WiIgIJk+eXGTK9Lvvvouvry+WlpbUq1ePpUuXKvtu3LhBZGQkLi4uWFpa4u7uTmxsbInHQwghhBCiqvjiiy/QaDRYWlrSqFEjzp07xyuvvML169eJiYlh9erVhISEULt2bXQ6HS+88AIrVqxQBlFUKhW2trY4OzujVqsf2OeQx9OIR9aiRYuoU6cOK1euJDU1FVPTW4/SiI2NZf369SxfvhwvLy+++eYbXnjhBRwdHWnfvr1SPzo6miVLlmBlZUXfvn3p27cvFhYWbNy4kZycHHr16sXbb7/NpEmTSowhLi6OuXPnMnXqVD788ENeeukl2rdvj4+PT4l1pk2bRlxcHI6OjowYMYIhQ4aQlJRUpFxUVBTHjh3jypUrSjJnb29PREQEkZGRxMXFYWFhAcD69eupUaMGQUFFlz23srIiJiaG7du30717d27evMnXX39NtWrFP84gJyeHrl270rFjR9avX09GRgZjx441KFNQUICbmxsffPABDg4OJCcnM2zYMFxcXOjbt69S7uuvv8bNzY1vvvmGpKQkwsPDSU5Opl27dqSkpLB582aGDx9Ox44dcXNzA0Cr1ZKQkICrqytHjhxh6NChaLVaJk6cCMCGDRuYP38+S5cupXXr1mzatIm4uDiDxHvDhg3MnDmTJUuW4Ofnx+HDhxk6dCjW1tYMGjSIxYsX89lnn7FlyxZq1arFn3/+yZ9//lnidyaEEEIIUVV06NCBZcuWcfXqVd566y3MzMx47rnn+Pnnn8nNzaVjx44G5W/cuIGfn98DirZkkqiKR5atrS1arVa5OgQoV5J2795Nq1atAKhduzb79+9nxYoVBonqvHnzaN26NQDh4eFMmTKF9PR0ateuDcDzzz/Pnj17Sk1UO3fuzMiRI4FbI4FvvfUWe/bsKTVRnT9/vhLH5MmT6dKlC9euXcPS0vD5gRqNBrVazfXr15XPB9C7d28iIyP59NNPlaQwISFBWQXuTteuXSMmJoaUlBQCAwPx9/cnODiY119/naeffrpI+Y0bN1JQUMB7772HpaUlDRo04NSpU7z00ktKmWrVqjF79mzlvaenJwcOHGDLli0Giaq9vT2LFy/GxMQEHx8fFixYQG5uLlOnTgVgypQpvPrqq+zfv5//+7//A2D69OlKfQ8PD6Kioti0aZOSqL799tuEh4czePBgAGbOnMmXX35JTk6OUm/WrFnExcXRu3dvJb5ffvmFFStWMGjQILKysvDy8qJNmzaoVKoyn+UqhBBCCFFVWFtbU7duXQBWr15NkyZNeO+995R1UbZt20aNGjUM6hQOblQlMvVXPFZOnjypXEnSaDTKa+3ataSnpxuUbdy4sfJvJycnZarp7dvOnSv9YeC3t6FSqXB2dq5QHRcXF4Ay69zO0tKSF198kdWrVwPwww8/cPToUXQ6XbHlc3NzcXJyYufOnbi5uTFixAhWr17Nb7/9Vmz5Y8eO0bhxY4PEuTDpv90777zDU089haOjIxqNhpUrV5KVlWVQpkGDBpiY/O/XkJOTE40aNVLem5qa4uDgYPD5N2/eTOvWrXF2dkaj0TB9+nSDdo8fP14kwb79/dWrV0lPTyc8PNzgHJg3b55yDuh0OtLS0vDx8WHMmDF8+eWXxR4LIYQQQoiqzMTEhKlTpzJ9+nTq16+PhYUFWVlZ1K1b1+BVs2bNBx1qETKiKh4rhaNq5bmSdPvU18JnUd1OpVJRUFBQan/3WqdwBLSsOneKiIigadOmnDp1ivj4eIKCgkocFbS3t2fUqFEG2+rUqUOdOnUq1OftNm3aRFRUFHFxcbRq1QqtVsvrr79OSkqKQbnijk9px+zAgQMMGDCA2bNnExISgq2trTK1t7wKz4FVq1bRokULg32F08ObNWtGRkYGO3bsYPfu3fTt25fg4GCDe5mFEEIIIR4Gffr04ZVXXmHFihVERUUxfvx4CgoKaNOmDZcvXyYpKQkbGxsGDRpUbP169eoRGxtLr169jBq3JKrisXL7laTbp/k+rMzNzcnPzy+yvVGjRvj7+7Nq1So2btzIkiVLytVeeZYg9/X1Zd26dQbTkQ8ePGhQJikpiYCAAGXaM1BkxPpuJCcn4+7uzrRp05Rtf/zxh0EZHx8fUlNTGThwoLItNTVV+beTkxOurq78/vvvDBgwoMS+bGxsCAsLIywsjOeff57Q0FAuXLiAvb39PX8OIYQQQghjMTMzIzIykgULFpCRkYGjoyOxsbH8/vvv2NnZ0axZM+W2q+IcP36cy5cvGzHiWyRRFY8VrVZ7V1eSqioPDw927drF8ePHcXBwwNbWVhmRLFxUydraulKvgPXv359p06YxdOhQpkyZQmZmJm+88YZBGS8vL9auXcuuXbvw9PRk3bp1pKamlrqScHl4eXmRlZXFpk2baN68Odu2bWPr1q0GZUaPHs3QoUPx9/cnICCAzZs389NPPxlM2549ezZjxozB1taW0NBQrl+/zqFDh7h48SITJkzgzTffxMXFBT8/P0xMTPjggw9wdnZ+oA+9FkIIIYQoS0mDDpMnT2by5MkAjB07tshCmLe7dOmSwfvbH2FoTHKPqnjszJ07lxkzZhAbG4uvry+hoaFs27btnpOoB2Ho0KH4+Pjg7++Po6OjwerA/fr1w8zMjH79+hVZiOleaDQaPv/8c44cOYKfnx/Tpk3jtddeMygzfPhwevfuTVhYGC1atOD8+fMGo6t3q3v37owfP57IyEiaNm1KcnIyM2bMMCgzYMAApkyZQlRUlDKFV6fTGRyDiIgI3n33XeLj42nUqBHt27cnISFBOQe0Wi0LFizA39+f5s2bk5mZyfbt2w3upxVCCCGEEPePSv+gUmQhxH2VmZlJnTp1SE1NpVmzZg86nAeqY8eOODs7s27dugcax6WzuWUXqgR514tOB78fqlmYGqUfMN7V3IJ84/TjUENjlH6Mdc6ZmhnnIo7WofIuupUm9/INo/RjYlZ0Jfb7wdK6+MeNVbaT35d/4b97Ufep6kbpx1ifB+DUrxeM0s9FI/1O6DXBOH93vDPia6P0Yyyjlhd9jODjTKb+CvGIycvL4/z580yfPp2WLVs+dklqbm4uy5cvJyQkBFNTU95//312797NV1999aBDE0IIIYQQ5SSJqhCPmKSkJDp06IC3t/djuUqtSqVi+/btzJ8/n2vXruHj48NHH31EcHDwgw4N02rGGXUy1oiqMefjGKsvM3PjjBL/cfS8UfopKDDOgfNo6GCUfozl6uXrRunnCRdro/RzPOWMUfrJ/Okfo/RjrBHV9B+MN6LqVs84C/V5NXcySj/GIiOQjzZJVIV4xAQGBj6wm96rArVaze7dux90GEIIIYQQ4h7IyiBCCCGEEEII8QjS6/XMnDkTFxcX1Go1wcHBnDhxotQ60dHRqFQqg1e9evUMyly7do1Ro0bh4OCARqPhueee4+zZs5Uae4USVb1ez7Bhw7C3t0elUpGWllapwdwuMDCQcePGlbt8ZmZmhWOKjo6madOmFY7tfrubzyIMRUdH4+TkhEql4pNPPrlv/eh0Onr27FmhOhWNKSEhQR6LIoQQQgghKmzBggUsXryY5cuXk5KSgrW1NSEhIVy7dq3Ueg0aNCA7O1t57d+/32D/+PHj+fzzz/nggw/Yt28fp0+fpnfv3pUae4Wm/u7cuZOEhAT27t1L7dq1efLJJys1mNt9/PHHyvMgy6NmzZpkZ2dXKKaoqChGjx6tvNfpdFy6dKnSEhudTkd0dDQeHh6V0p4on2PHjjF79my2bt1Ky5YteeKJJ+5bX4sWLarwNNvs7OwKxRQWFkbnzp2V99HR0XzyySeVdiEjOjqawMBAAgMDK6U9IYQQQgjx4On1ehYuXMj06dPp0aMHAGvXrsXJyYlPPvmE//u//yuxrpmZGc7OzsXuu3z5Mu+99x4bN24kKOjWfcLx8fH4+vpy8OBBWrZsWSnxV2hENT09HRcXFwICAnB2dsbM7P7d4mpvb49Wqy13eVNT0wrHpNFocHCo3AUgLly4wDvvvGOQvKSnp7Nhw4ZK7edxUpjwl1d6ejoAPXr0wNnZGQsLi/sUGdja2lZ4tLOiManVaqpXr9yFI/Ly8oiLiyMvL0/Zdu7cOVasWFGp/ZTmxg3jPP6hIqpiTEIIIYQQdyMjI4MzZ84YLChpa2tLixYtOHDgQKl1T5w4gaurK7Vr12bAgAFkZWUp+77//nvy8vIM2q1Xrx61atUqs92KKHeiqtPpGD16NFlZWahUKmWUsKCggNjYWDw9PVGr1TRp0sRgpdG9e/eiUqnYtWsXfn5+qNVqgoKCOHfuHDt27MDX1xcbGxv69+9Pbu7/nu1059RfDw8PYmJiGDJkCFqtllq1arFy5Upl/53TZQv7TUxMxN/fHysrKwICAjh+/LhS5/apv9HR0axZs4ZPP/1UmYu9d+9egoKCiIyMNDgWf//9N+bm5iQmJhY5TpaWlvz111+EhoZy6tQpli9fjk6nw9PTs8Rj+9133+Hn54elpSX+/v4cPnzYYH9+fj7h4eHKMfbx8WHRokVFvp+ePXsSExODk5MTdnZ2zJkzh5s3b/LKK69gb2+Pm5sb8fHxBvUmTZqEt7c3VlZW1K5dmxkzZhgkLwDz5s2jevXqaLVaIiIimDx5cpEp0++++y6+vr5YWlpSr149li5dquy7ceMGkZGRuLi4YGlpibu7O7GxsSUej3sRHR1Nt27dADAxMUGl+t8z6kqLsfD82bJlC23btkWtVtO8eXN+++03UlNT8ff3R6PR0KlTJ/7++2+l3p1TfwMDAxkzZgwTJ07E3t4eZ2fnIkn27VN/C/v9+OOP6dChA1ZWVjRp0sTgh/z2qb8JCQnMnj2bH3/8UTlPExISGDJkCF27djXoJy8vj+rVq/Pee+8VOU6FxyUoKIiff/6ZrVu30q1bN9zc3Io9rgkJCUXuVVCpVMpnKzwOs2fPxtHRERsbG0aMGGGQ+AUGBhIZGcm4ceN48sknCQkJAeDo0aN06tQJjUaDk5MTL774Iv/887+VIz/88EMaNWqEWq3GwcGB4OBgrl69Ctz6OX/66aextrbGzs6O1q1b88cffxT73QCMGzfOYOT4bmMSQgghhKjqzpy5teK3k5Phas9OTk7KvuK0aNGChIQEdu7cybJly8jIyKBt27b8+++/Srvm5uZFBmvKareiyp2oLlq0iDlz5uDm5kZ2djapqakAxMbGsnbtWpYvX87PP//M+PHjeeGFF9i3b59B/ejoaJYsWUJycjJ//vknffv2ZeHChWzcuJFt27bx5Zdf8vbbb5caQ1xcnJLIjRw5kpdeeskg8SzOtGnTiIuL49ChQ5iZmTFkyJBiy0VFRdG3b19CQ0OVudgBAQFERESwceNGrl//31L169evp0aNGspQ9+2srKyIiYlh7Nix7N27l4MHD/L1118TEBBQbL85OTl07dqV+vXr8/333xMdHU1UVJRBmYKCAtzc3Pjggw/45ZdfmDlzJlOnTmXLli0G5b7++mtOnz7NN998w5tvvsmsWbPo2rUrTzzxBCkpKYwYMYLhw4dz6tQppY5WqyUhIYFffvmFRYsWsWrVKt566y1l/4YNG5g/fz6vvfYa33//PbVq1WLZsmUG/W7YsIGZM2cyf/58jh07RkxMDDNmzGDNmjUALF68mM8++4wtW7Zw/PhxNmzYcN+mQ0dFRSnJeOH3WJ4YC82aNYvp06fzww8/YGZmRv/+/Zk4cSKLFi3i22+/5eTJk8ycObPUGNasWYO1tTUpKSksWLCAOXPmlPkMz2nTphEVFUVaWhre3t7069ePmzdvFikXFhbGyy+/bHDfQFhYGBEREezcuVP5vABffPEFubm5hIWFFWnHzMyMl19+mcWLF7N9+3a+/PJLvvzyS7p06VJsfGFhYQb3Kbz//vuYmZnRunVrpUxiYiLHjh1j7969vP/++3z88cfMnj27yLExNzcnKSmJ5cuXc+nSJYKCgvDz8+PQoUPs3LmTs2fP0rdvX+DWd9ivXz+GDBmitN27d2/0ej03b96kZ8+etG/fnp9++okDBw4wbNgwg4sT5VHRmIQQQgghqqINGzag0WiU152DT+XVqVMn+vTpQ+PGjQkJCWH79u1cunSpSO5xv5V7nqytrS1arVaZYgtw/fp1YmJi2L17N61atQKgdu3a7N+/nxUrVtC+fXul/rx585Q/asPDw5kyZQrp6enUrl0bgOeff549e/YwadKkEmPo3LkzI0eOBG6NBL711lvs2bMHHx+fEuvMnz9fiWPy5Ml06dKFa9euYWlpaVBOo9GgVqu5fv26wXzs3r17ExkZyaeffqr8oZqQkIBOpyv2D+Jr164RExNDSkoKgYGB+Pv7ExwczOuvv87TTz9dpPzGjRspKCjgvffew9LSkgYNGnDq1CleeuklpUy1atUM/uD39PTkwIEDbNmyxeCPZ3t7exYvXoyJiQk+Pj4sWLCA3Nxcpk6dCsCUKVN49dVX2b9/vzInffr06Up9Dw8PoqKi2LRpExMnTgTg7bffJjw8nMGDBwMwc+ZMvvzyS3JycpR6s2bNIi4uTrmB2tPTk19++YUVK1YwaNAgsrKy8PLyok2bNqhUKtzd3Uv8vu6VRqNRru7c/j2WFWOhqKgoZVRt7Nix9OvXj8TERINzNyEhodQYGjduzKxZswDw8vJiyZIlJCYm0rFjxxLrREVFKUni7NmzadCgASdPniyywpparUaj0RS5byAgIAAfHx/WrVunfHfx8fH06dMHjUZTpL/8/HyWLFnChx9+SOfOnXF1dSU0NJRZs2YRGhpapLxarUatVgO3plaPGjWKmJgYg89kbm7O6tWrsbKyokGDBsyZM4dXXnmFuXPnYmJiohyPBQsWKHXmzZuHn58fMTExyrbVq1dTs2ZNfvvtN3Jycrh58ya9e/dWzptGjRoBt6bZX758ma5du1KnTh0AfH19SzzGJaloTN7e3hXuQwghhBDifuvevTstWrRQ3hcOtJ09exYXFxdl+9mzZyu0oKydnR3e3t6cPHkSuPU39o0bN7h06ZLBqOrZs2dLvK/1btzT42lOnjxJbm4uHTt2NMje165dq9wnWKhx48bKv52cnJSpprdvO3eu9Acr396GSqXC2dm5QnUKv6Cy6tzO0tKSF198kdWrVwPwww8/cPToUXQ6XbHlc3NzcXJyYufOnbi5uTFixAhWr17Nb7/9Vmz5Y8eO0bhxY4PEuTDpv90777zDU089haOjIxqNhpUrVxrMFYdbq3MVJgRw65gW/lEPt+7jdXBwMPj8mzdvpnXr1jg7O6PRaJg+fbpBu8ePHy+SYN/+/urVq6SnpxMeHm5wDsybN085B3Q6HWlpafj4+DBmzBi+/PLLYo9FoTuvBm3YsIGYmBiDbd9++22pbdyuPDEWuvM8BQyOYUXPU7h13t3v8xQgIiJCGU0+e/YsO3bsKHEGQUFBAXl5eSQmJtKgQQN69erFJ598QmZmZql9FCaGXbp04ZVXXjHY16RJE6ysrJT3rVq1Iicnhz///FPZ9tRTTxnU+fHHH9mzZ4/B91KYnKenp9OkSROeeeYZGjVqRJ8+fVi1ahUXL14Ebl2Y0el0hISE0K1bNxYtWmQwolxeFY1JCCGEEKIq0mq11K1bV3nVr18fZ2dng9sVr1y5QkpKSrH5RklycnKUtYrg1t9O1apVM2j3+PHjZGVlVajdstzTakiFo2rbtm2jRo0aBvvuXCzm9hV8VSpVkRV9VSoVBQUFpfZ3r3UKR0DLqnOniIgImjZtyqlTp4iPjycoKKjEUUF7e3tGjRplsK1OnTrKiM/d2LRpE1FRUcTFxdGqVSu0Wi2vv/46KSkpBuWKOz6lHbMDBw4wYMAAZs+eTUhICLa2tmzatIm4uLhyx1Z4DqxatcrgCg7cSowBmjVrRkZGBjt27GD37t307duX4OBgg3uZb3fn1aBJkyZRo0YNxowZo2y783y71xgLFXe+3Lmtqp6nAwcOZPLkyRw4cIDk5GQ8PT1p27Ztif3dOcXcycmJESNGlNh+fn4+YWFh2NjYGNwfXhHW1tYG73NycujWrRuvvfZakbIuLi6Ympry1VdfkZycrNweMG3aNFJSUvD09CQ+Pp4xY8awc+dONm/ezPTp0/nqq69o2bIlJiYmRVZkLm4KTEVjEkIIIYR4GKhUKsaNG8e8efPw8vLC09OTGTNm4OrqarCOxzPPPEOvXr2UdXmioqLo1q0b7u7unD59mlmzZmFqakq/fv2AWzNtw8PDmTBhAvb29tjY2DB69GhatWpVaSv+wj0mqvXr18fCwoKsrCyDab4PK3Nzc/Lz84tsb9SoEf7+/qxatYqNGzeyZMmScrVX1hRRuDVVcd26dQbTkQ8ePGhQJikpiYCAAGXaM1TOyE5ycjLu7u5MmzZN2Va4EE0hHx8fUlNTGThwoLKt8P5kuJXcuLq68vvvvzNgwIAS+7KxsSEsLIywsDCef/55QkNDuXDhAvb29kXKarVagxWftVot9vb21K1b964+Z3ljfFiUdJ46ODjQs2dP4uPjOXDggDJduyzlXVF5/PjxHDlyhEOHDhWZOg+3RiL/++8/ZYrwwYMH0Wg01KxZs8Q2mzVrxkcffYSHh0eJK3arVCpat25N69atmTlzJu7u7mzdupUJEyYA4Ofnh5+fH1OmTKFVq1Zs3LiRli1b4ujoyNGjRw3aSktLK/OxV+WJSQghhBDiYTBx4kSuXr3KsGHDuHTpEm3atGHnzp0Gf8ulp6cbLBp56tQp+vXrx/nz53F0dKRNmzYcPHgQR0dHpcxbb72FiYkJzz33HNevXyckJMRgodLKcE9/hWm1WqKiohg/fjwFBQW0adOGy5cvk5SUhI2NjcG9fw8DDw8Pdu3axfHjx3FwcMDW1lb5ozYiIoLIyEisra3p1atXpfXZv39/pk2bxtChQ5kyZQqZmZm88cYbBmW8vLxYu3Ytu3btwtPTk3Xr1pGamlrqSsLl4eXlRVZWFps2baJ58+Zs27aNrVu3GpQZPXo0Q4cOxd/fn4CAADZv3sxPP/1kMG179uzZjBkzBltbW0JDQ7l+/TqHDh3i4sWLTJgwgTfffBMXFxf8/PwwMTHhgw8+wNnZucKPdbkXZcX4MPHw8CAjI4O0tDTc3NzQarXKDIaIiAi6du1Kfn5+pf78xcfHs3TpUrZu3YpKpVJWdCucGgu3VncODw9n+vTpZGZmMmvWLCIjIw2mo99p1KhRrFq1in79+ikrJZ88eZJNmzbx7rvvcujQIRITE3n22WepXr06KSkp/P333/j6+pKRkcHKlSvp3r07rq6uHD9+nBMnTigXVYKCgnj99ddZu3YtrVq1Yv369Rw9ehQ/P79SP2tZMd05Ci+EEEIIUVWpVCrmzJnDnDlzSixz561fmzZtKrNdS0tL3nnnHd555517DbFE93SPKsDcuXOZMWMGsbGx+Pr6EhoayrZt2+45iXoQhg4dio+PD/7+/jg6OpKUlKTs69evH2ZmZvTr16/Y0aS7pdFo+Pzzzzly5Ah+fn5MmzatyJTD4cOH07t3b8LCwmjRogXnz583GF29W927d2f8+PFERkbStGlTkpOTmTFjhkGZAQMGMGXKFKKiopQpvDqdzuAYRERE8O677xIfH0+jRo1o3749CQkJyjmg1WpZsGAB/v7+NG/enMzMTLZv315qAlPZyorxYfLcc88RGhpKhw4dcHR05P3331f2BQcH4+LiQkhICK6urpXW5759+8jPz6d79+64uLgor9svqjzzzDN4eXnRrl07wsLC6N69e5mjta6uriQlJZGfn8+zzz5Lo0aNGDduHHZ2dpiYmGBjY8M333xD586d8fb2Zvr06cTFxdGpUyesrKz49ddfee655/D29mbYsGGMGjWK4cOHAxASEsKMGTOYOHEizZs3599//zWYGXC3MQkhhBBCiPtPpb/zJi5RrMzMTOrUqUNqairNmjV70OE8UB07dsTZ2Zl169Y96FDEHXJycqhRowbx8fHKCsfGoNPpuHTpkvJ8WFG8fy9cM0o/13Lubjn6ijIzN97osrH+qzI1M87FiEtnc8suVAkKCoxz3DwaOhilH5VJxR4/dbf+zvrXKP084WJddqFKkP5DxRbnu1uZPxnnedMhQxsapZ9dq46WXaiSuNUreivU/WDnpDZKPzW8nzBKP+LRJjdglSEvL4/z588zffp0WrZs+dglqbm5uSxfvpyQkBBMTU15//332b17d5nPBRXGVVBQwD///ENcXBx2dnZ07979QYckhBBCCCHEXZNEtQxJSUl06NABb2/vElepfZSpVCq2b9/O/PnzuXbtGj4+Pnz00UcEBwc/6NDEbbKysvD09MTNzY2EhARZBKiKys+r2ErOd8vCyjjff0G+8Sbk3DTSsdMbaQSyuruNUfrJvXLdKP1kHj1vlH5sHCrv1pvSZJ+8bJR+TKsZZwS/pq9xRut8WlTe8xNL886Ir43Sz6jlQUbpRwhRPPlrtgyBgYFGm3JWFanVanbv3v2gwxBl8PDweKDnaXlWuBZCCCGEEKK8ZGUQIYQQQgghhHgE6fV6Zs6ciYuLC2q1muDgYE6cOFFqnejoaFQqlcGrXr16BmWGDx9OnTp1UKvVODo60qNHD3799ddKjb3KJqp6vZ5hw4Zhb2+PSqUiLS3tvvUVGBjIuHHjyl0+MzOzwjFFR0fTtGnTCsd2v93NZxGGoqOjcXJyQqVS3dfFhHQ6ncHDmcujojElJCQY9bFB99vevXtRqVRcunTpntq5m2MvhBBCCPGgLViwgMWLF7N8+XJSUlKwtrYmJCSEa9dKX+CxQYMGZGdnK6/9+/cb7H/qqaeIj4/n2LFj7Nq1C71ez7PPPkt+fn6lxV5lV/3dsWMHPXr0YO/evdSuXZsnn3zyvt13d+HCBapVq4ZWqy1X+fz8fP7+++8KxZSTk8P169dxcLi1MmJlr5Kq0+mIjo7Gw8OjQvUyMzPx9PTk8OHDVTKRruqOHTtG/fr12bp1Ky1btuSJJ55Qnmla2S5fvoxer69QInnmzJkKxfTff//x77//Ur16deBWEv7JJ59U2oWM6OhoAgMDCQwMrJT2ynLjxg0uXLigXEi4W5X182qslV5NTI2zMqox71HNu1F5//GVxsRIq8pa2dyf3xN3MtY9qlfOG2dFa2Pdo/rX8UtG6cfN1zgro1paVzNKP1Y25kbpR+5RFaJ89Ho9rq6uvPzyy0RFRQG3/p50cnIiISGB//u//yu23t38/ffTTz/RpEkTTp48SZ06dSoj/Ko7opqeno6LiwsBAQE4Ozvf18Vh7O3ty52kApiamlY4Jo1GoySpleXChQu88847Bvcmpqens2HDhkrt53FSmPCXV3p6OgA9evTA2dn5viWpALa2thUe7axoTGq1WklSK0teXh5xcXHk5f3vkSnnzp1jxYoVldpPcczNzXF2dr6nJFUIIYQQ4mGUkZHBmTNnDBZBtbW1pUWLFhw4cKDUuidOnMDV1ZXatWszYMAAsrKySix79epV4uPj8fT0pGbNmpUWf5VMVHU6HaNHjyYrKwuVSqWMEhYUFBAbG4unpydqtZomTZoYrMRbOM1v165d+Pn5oVarCQoK4ty5c+zYsQNfX19sbGzo378/ubn/G9m4c+qvh4cHMTExDBkyBK1WS61atVi5cqWy/87psoX9JiYm4u/vj5WVFQEBARw/flypc/vU3+joaNasWcOnn36qzPveu3cvQUFBREZGGhyLv//+G3NzcxITE4scJ0tLS/766y9CQ0M5deoUy5cvR6fT4enpWeKx/e677/Dz88PS0hJ/f38OHz5ssD8/P5/w8HDlGPv4+LBo0aIi30/Pnj2JiYnByckJOzs75syZw82bN3nllVewt7fHzc2N+Ph4g3qTJk3C29sbKysrateuzYwZMwySF4B58+ZRvXp1tFotERERTJ48uchI77vvvouvry+WlpbUq1ePpUuXKvtu3LhBZGQkLi4uWFpa4u7uTmxsbInH415ER0fTrVs3AExMTAySodJiLDx/tmzZQtu2bVGr1TRv3pzffvuN1NRU/P390Wg0dOrUib///lupd+f008DAQMaMGcPEiROxt7fH2dm5SJJ9+9Tfwn4//vhjOnTogJWVFU2aNDH4RXX71N+EhARmz57Njz/+qJynCQkJDBkyhK5duxr0k5eXR/Xq1XnvvfeKHKfC4xIUFMTPP//M1q1b6datG25ubsUe14SEhCL3RahUKqKjozl69CgmJibKcblw4QImJiYGVwTnzZtHmzZtgKJTfws/365du/D19UWj0RAaGkp2drZSPz8/nwkTJmBnZ4eDgwMTJ058rBdUE0IIIcTD6cyZMwA4OTkZbHdyclL2FadFixYkJCSwc+dOli1bRkZGBm3btuXffw2fMb106VI0Gg0ajYYdO3bw1VdfYW5eeTMrqmSiumjRIubMmYObmxvZ2dmkpqYCEBsby9q1a1m+fDk///wz48eP54UXXmDfvn0G9aOjo1myZAnJycn8+eef9O3bl4ULF7Jx40a2bdvGl19+ydtvv11qDHFxcUoiN3LkSF566SWDxLM406ZNIy4ujkOHDmFmZsaQIUOKLRcVFUXfvn2VP5Czs7MJCAggIiKCjRs3cv36/6ZqrV+/nho1ahAUVHT6iZWVFTExMYwdO5a9e/dy8OBBvv76awICAortNycnh65du1K/fn2+//57oqOjlWkAhQoKCnBzc+ODDz7gl19+YebMmUydOpUtW7YYlPv66685ffo033zzDW+++SazZs2ia9euPPHEE6SkpDBixAiGDx/OqVOnlDparZaEhAR++eUXFi1axKpVq3jrrbeU/Rs2bGD+/Pm89tprfP/999SqVYtly5YZ9LthwwZmzpzJ/PnzOXbsGDExMcyYMYM1a9YAsHjxYj777DO2bNnC8ePH2bBhQ4WnQ5dXVFSUkowXfo/libHQrFmzmD59Oj/88ANmZmb079+fiRMnsmjRIr799ltOnjzJzJkzS41hzZo1WFtbk5KSwoIFC5gzZ06Zz7idNm0aUVFRpKWl4e3tTb9+/bh582aRcmFhYbz88ssG9yiEhYURERHBzp07DZK7L774gtzcXMLCwoq0Y2Zmxssvv8zixYvZvn07X375JV9++SVdunQpNr6wsDCDeyLef/99zMzMaN26NQ0aNMDBwUH5mf/2228N3gPs27ev1KnFubm5vPHGG6xbt45vvvmGrKwsg5+DuLg4EhISWL16Nfv37+fChQts3bq11GMqhBBCCPGgbdiwQUkcNRpNkQGh8urUqRN9+vShcePGhISEsH37di5dulQkHxgwYACHDx9m3759eHt707dv3zLvfa2IKpmo2traotVqlSm2jo6OXL9+nZiYGFavXk1ISAi1a9dGp9PxwgsvFJlCOG/ePFq3bo2fnx/h4eHs27ePZcuW4efnR9u2bXn++efZs2dPqTF07tyZkSNHUrduXSZNmsSTTz5ZZp358+fTvn176tevz+TJk0lOTi72y9JoNKjVaiwsLHB2dsbZ2Rlzc3N69+4NwKeffqqUTUhIQKfTFTt18dq1a8ycOZNFixYRGBhIy5YtCQ4O5rvvvis2vo0bN1JQUMB7771HgwYN6Nq1K6+88opBmWrVqjF79mz8/f3x9PRkwIABDB48uMiJaW9vz+LFi/Hx8WHIkCH4+PiQm5vL1KlT8fLyYsqUKZibmxvceD19+nQCAgLw8PCgW7duREVFGbT79ttvEx4ezuDBg/H29mbmzJk0atTIoN9Zs2YRFxdH79698fT0pHfv3owfP145B7KysvDy8qJNmza4u7vTpk0b+vXrV+zxuFcajUYZfSz8HssTY6GoqChCQkLw9fVl7NixfP/998yYMcPg3C3rnGvcuDGzZs3Cy8uLgQMH4u/vX+zo+539dunSBW9vb2bPns0ff/zByZMni5RTq9VoNBrMzMyUz6dWqwkICMDHx4d169YpZePj4+nTpw8ajaZIO/n5+SxatIgxY8bQuXNnnn32WUJDQ9m5c2ex8anVaqW/q1evMmrUKGJiYujYsSMqlYp27dqxd+9e4NaI6eDBg7l+/Tq//voreXl5JCcn0759+xI/f15eHsuXL8ff359mzZoRGRlpcMwWLlzIlClT6N27N76+vixfvhxbW9tSj6kQQgghxIPWvXt30tLSlNeTTz4JwNmzZw3KnT17Vvm7tTzs7Ozw9vYu8veira0tXl5etGvXjg8//JBff/21Ui/uV8lEtTgnT54kNzeXjh07GlwpWLt2rXKfYKHGjRsr/3ZyclKmmt6+7dy5c6X2d3sbKpUKZ2fnCtVxcXEBKLPO7SwtLXnxxRdZvXo1AD/88ANHjx5Fp9MVWz43NxcnJyd27tyJm5sbI0aMYPXq1fz222/Flj927BiNGzfG0vJ/i1G0atWqSLl33nmHp556CkdHRzQaDStXriwyL71BgwaYmPzv9HFycjJIKk1NTXFwcDD4/Js3b6Z169Y4Ozuj0WiYPn26QbvHjx/n6aefNujn9vdXr14lPT2d8PBwg3Ng3rx5yjmg0+lIS0vDx8eHMWPG8OWXXxZ7LArdeeVpw4YNxMTEGGz79ttvS23jduWJsdCd5ylgcAwrep7CrfPufp+nABEREcpo8tmzZ9mxY0eJMwgKCgrIy8sjMTGRBg0a0KtXLz755BMyMzNL7ePy5ct07dqVLl26GFxQad++vZKo7tu3j6CgICV5TU1NJS8vj9atW5fYrpWVlcFN/rcfs8uXL5OdnU2LFi2U/WZmZvj7+5caqxBCCCHEg6bVaqlbt67yql+/Ps7OzgYX5K9cuUJKSkqxOUBJcnJylPWDSqLX69Hr9QYzQ+/V/VuhqJLl5OQAsG3bNmrUqGGw787FYqpV+9/qdiqVyuB94baCgoJS+7vXOoUjoGXVuVNERARNmzbl1KlTxMfHExQUhLu7e7Fl7e3tGTVqlMG2OnXq3NNKW5s2bSIqKoq4uDhatWqFVqvl9ddfJyUlxaBcccentGN24MABBgwYwOzZswkJCcHW1pZNmzYRFxdX7tgKz4FVq1YZJBJwKzEGaNasGRkZGezYsYPdu3fTt29fgoODDe5lvl337t0N2po0aRI1atRgzJgxyrY7z7d7jbFQcefLnduq6nk6cOBAJk+ezIEDB0hOTsbT05O2bduW2N+dU8ydnJwYMWJEie3n5+cTFhaGjY2Nwf3h8L97yk+cOMEvv/xCmzZt+PXXX9m7dy8XL15U7hMvSXHHTO5BFUIIIcSjRqVSMW7cOObNm4eXlxeenp7MmDEDV1dXg3VPnnnmGXr16qWslRMVFUW3bt1wd3fn9OnTzJo1C1NTU2WW4u+//87mzZt59tlncXR05NSpU7z66quo1Wo6d+5cafE/NIlq/fr1sbCwICsrq9RpfQ8Lc3PzYp8z1KhRI/z9/Vm1ahUbN25kyZIl5WovISGhzDK+vr6sW7eOa9euKaOqBw8eNCiTlJREQEAAI0eOVLbdORJ4N5KTk3F3d2fatGnKtj/++MOgjI+PD6mpqQwcOFDZVnh/MtxKblxdXfn9998ZMGBAiX3Z2NgQFhZGWFgYzz//PKGhoVy4cAF7e/siZbVarcGKz1qtFnt7e+rWrXtXn7O8MT4sSjpPHRwc6NmzJ/Hx8Rw4cIDBgweXq73yrqg8fvx4jhw5wqFDhwxmAMCtn5EnnniCefPm0bRpUzQaDYGBgbz22mtcvHjxnh59Y2tri4uLCykpKbRr1w6Amzdv8v3339OsWbO7blcIIYQQ4kGYOHEiV69eZdiwYVy6dIk2bdqwc+dOg7+v0tPT+eeff5T3p06dol+/fpw/fx5HR0fatGnDwYMHcXR0BG7NAv32229ZuHAhFy9exMnJiXbt2pGcnFypT494aBJVrVZLVFQU48ePp6CggDZt2nD58mWSkpKwsbFh0KBBDzrECvHw8GDXrl0cP34cBwcHbG1tlZGeiIgIIiMjsba2plevXpXWZ//+/Zk2bRpDhw5lypQpZGZm8sYbbxiU8fLyYu3atezatQtPT0/WrVtHampqqSsJl4eXlxdZWVls2rSJ5s2bs23btiJz2EePHs3QoUPx9/cnICCAzZs389NPPxlM2549ezZjxozB1taW0NBQrl+/zqFDh7h48SITJkzgzTffxMXFBT8/P0xMTPjggw9wdnau8GNd7kVZMT5MPDw8yMjIIC0tDTc3N7RarTKDISIigq5du5Kfn1+pP3/x8fEsXbqUrVu3olKplFXpCqdRF96numHDBmWktnHjxly/fp3ExMR7PsZjx47l1VdfxcvLi3r16vHmm28qqwYLIYQQQjxMVCoVc+bMYc6cOSWWufN2rE2bNpXapqurK9u3b6+M8Er10NyjCjB37lxmzJhBbGwsvr6+hIaGsm3btntOoh6EoUOH4uPjg7+/P46OjiQlJSn7+vXrh5mZGf369SsymnQvNBoNn3/+OUeOHMHPz49p06bx2muvGZQZPnw4vXv3JiwsjBYtWnD+/HmD0dW71b17d8aPH09kZCRNmzYlOTmZGTNmGJQZMGAAU6ZMISoqSpnCq9PpDI5BREQE7777LvHx8TRq1Ij27duTkJCgnANarZYFCxbg7+9P8+bNyczMZPv27Qb3095vZcX4MHnuuecIDQ2lQ4cOODo68v777yv7goODcXFxISQkBFdX10rrc9++feTn59O9e3dcXFyU1+0XVdq3b09+fr4yempiYkK7du1QqVSl3p9aHi+//DIvvvgigwYNUqa/V+YFIyGEEEIIUTaVXm7OqnIyMzOpU6cOqampj/10w44dO+Ls7GywwqyoGnJycqhRowbx8fHKitWidJfO5pZdqBKYmBZdJfx+KMg33n8feTeKTkG/H0xMjHPsrGwsyi5UCXKvVN6iFqW5cr7yHkdQGhuHyrt4W5q/jl8ySj9uvk8YpR9L62plF6oEVjaV9/zE0rwz4muj9DNqedFHAwohjOehmfr7OMjLy+P8+fNMnz6dli1bPnZJam5uLsuXLyckJARTU1Pef/99du/eXeZzQYVxFRQU8M8//xAXF4ednR3du3d/0CEJIYQQQohHjCSqVUhSUhIdOnTA29u7xFVqH2UqlYrt27czf/58rl27ho+PDx999BHBwcEPOjRxm6ysLDw9PXFzcyMhIQEzM/k1UtUYa56MMUdUjcXUzDi3CeRdv2mUfoz1eRxcrY3Sz4nUs2UXqgTVPWyM0k/eNePMFNAXGOdn1VgjqjLSKcTjQab+CiGEkRhr6q/KSNNX8/Mq9lije+or3zh9VTM3LbtQJXjUpmcb6/M8aomquaVxLvSZmRvpgkUNjVH6EUI8Hh6qxZSEEEIIIYQQQpSPXq9n5syZuLi4oFarCQ4O5sSJE6XWiY6ORqVSGbzq1atXYvudOnVCpVLxySefVGrsj0SiqtfrGTZsGPb29qhUKtLS0u5bX4GBgYwbN67c5TMzMyscU3R0NE2bNq1wbPfb3XwWYSg6OhonJ6f78sN8O51OZ/Ag5/KoaEwJCQlGfeyPEEIIIYSomAULFrB48WKWL19OSkoK1tbWhISEcO1a6YvgNWjQgOzsbOW1f//+YsstXLgQler+zKp5JBLVnTt3kpCQwBdffEF2djYNGza8b319/PHHzJ07t9zla9asWeGYoqKiSExMVN7fTdJRGp1OV+R5SeL+O3bsGLNnz2bFihVkZ2fTqVOn+9bXokWLSEhIqFCdisYUFhbGb7/9pryv7Ass0dHR7N27t9LauxuSjAshhBDiYaXX61m4cCHTp0+nR48eNG7cmLVr13L69OkyByfMzMxwdnZWXk8++WSRMmlpacTFxbF69er7Ev8jkaimp6fj4uJCQEAAzs7O93VxF3t7e7RabbnLm5qaVjgmjUaDg4PD3YRXogsXLvDOO+9w+y3J6enpbNiwoVL7eZzodDqio6PLXT49PR2AHj164OzsjIXF/Xs8ha2tbYUTrIrGpFarqV69egUjK11eXh5xcXHk5eUp286dO8eKFSsqtR8hhBBCiEddRkYGZ86cMViY1NbWlhYtWnDgwIFS6544cQJXV1dq167NgAEDyMrKMtifm5tL//79eeedd3B2dr4v8T/0iapOp2P06NFkZWWhUqnw8PAAbj1CIzY2Fk9PT9RqNU2aNDFYSXfv3r2oVCp27dqFn58farWaoKAgzp07x44dO/D19cXGxob+/fuTm/u/BVDunPrr4eFBTEwMQ4YMQavVUqtWLVauXKnsv3O6bGG/iYmJ+Pv7Y2VlRUBAAMePH1fq3D4yFR0dzZo1a/j000+VOeJ79+4lKCiIyMhIg2Px999/Y25ubjAaW8jS0pK//vqL0NBQTp06xfLly9HpdHh6epZ4bL/77jv8/PywtLTE39+fw4cPG+zPz88nPDxcOcY+Pj4sWrSoyPfTs2dPYmJicHJyws7Ojjlz5nDz5k1eeeUV7O3tcXNzIz4+3qDepEmT8Pb2xsrKitq1azNjxgyD5AVg3rx5VK9eHa1WS0REBJMnTy4yovfuu+/i6+uLpaUl9erVY+nSpcq+GzduEBkZiYuLC5aWlri7uxMbG1vi8bgX0dHRdOvWDQATExODKRKlxVh4/mzZsoW2bduiVqtp3rw5v/32G6mpqfj7+6PRaOjUqRN///23Uu/OUfjAwEDGjBnDxIkTsbe3x9nZuUiSffvU38J+P/74Yzp06ICVlRVNmjQx+KV2+2hjQkICs2fP5scff1TO04SEBIYMGULXrl0N+snLy6N69eq89957RY5T4XEJCgri559/ZuvWrXTr1g03N7dij2tCQkKReyhUKpXBZ1u9ejUNGjTAwsICFxcXg5+bN998k0aNGmFtbU3NmjUZOXIkOTk5wK2f1cGDB3P58uVi2xVCCCGEqMrOnDkDgJOTk8F2JycnZV9xWrRoQUJCAjt37mTZsmVkZGTQtm1b/v33X6XM+PHjCQgIoEePHvcneB6Bx9MsWrSIOnXqsHLlSlJTUzE1vbViY2xsLOvXr2f58uV4eXnxzTff8MILL+Do6Ej79u2V+tHR0SxZsgQrKyv69u1L3759sbCwYOPGjeTk5NCrVy/efvttJk2aVGIMcXFxzJ07l6lTp/Lhhx/y0ksv0b59e3x8fEqsM23aNOLi4nB0dGTEiBEMGTKEpKSkIuWioqI4duwYV65cUZI5e3t7IiIiiIyMJC4uThkFW79+PTVq1CAoqOiy7VZWVsTExLB9+3a6d+/OzZs3+frrr6lWrfiHgOfk5NC1a1c6duzI+vXrycjIYOzYsQZlCgoKcHNz44MPPsDBwYHk5GSGDRuGi4sLffv2Vcp9/fXXuLm58c0335CUlER4eDjJycm0a9eOlJQUNm/ezPDhw+nYsaOSkGi1WhISEnB1deXIkSMMHToUrVbLxIkTAdiwYQPz589n6dKltG7dmk2bNhEXF2eQeG/YsIGZM2eyZMkS/Pz8OHz4MEOHDsXa2ppBgwaxePFiPvvsM7Zs2UKtWrX4888/+fPPP0v8zu5FVFQUHh4eDB48mOzs7HLHWGjWrFksXLiQWrVqMWTIEPr3749Wq2XRokXKuTtz5kyWLVtWYgxr1qxhwoQJpKSkcODAAXQ6Ha1bt6Zjx44l1pk2bRpvvPEGXl5eTJs2jX79+nHy5MkiMwTCwsI4evQoO3fuZPfu3cCtK3be3t60a9eO7OxsXFxcAPjiiy/Izc0lLCysSH9mZma8/PLLBAUF0aZNG2rVqsXBgwextbUtNr6wsDBCQ0OV93v37uXFF1+kdevWACxbtowJEybw6quv0qlTJy5fvmzwc2ZiYsLixYvx9PTk999/Z+TIkUycOJGlS5cSEBDAwoULmTlzpnIhSaORFS2FEEIIUTVt2LCB4cOHK++3bdt2V+3cfitY48aNadGiBe7u7mzZsoXw8HA+++wzvv766yKDWJXtoU9UbW1t0Wq1yhRbgOvXrxMTE8Pu3btp1aoVALVr12b//v2sWLHCIFGdN2+e8kdteHg4U6ZMIT09ndq1awPw/PPPs2fPnlIT1c6dOzNy5Ejg1kjgW2+9xZ49e0pNVOfPn6/EMXnyZLp06cK1a9ewtLQ0KKfRaFCr1Vy/ft1gWL13795ERkby6aefKklhQkICOp2u2Buar127RkxMDCkpKQQGBuLv709wcDCvv/46Tz/9dJHyGzdupKCggPfeew9LS0saNGjAqVOneOmll5Qy1apVY/bs2cp7T09PDhw4wJYtWwwSVXt7exYvXoyJiQk+Pj4sWLCA3Nxcpk6dCsCUKVN49dVX2b9/P//3f/8HwPTp05X6Hh4eREVFsWnTJiVRffvttwkPD2fw4MEAzJw5ky+//FIZDYNbyV1cXBy9e/dW4vvll19YsWIFgwYNIisrCy8vL9q0aYNKpcLd3b3E7+teaTQaZfTx9u+xrBgLRUVFERISAsDYsWPp168fiYmJBuduWfekNm7cmFmzZgHg5eXFkiVLSExMLDVRjYqKokuXLgDMnj2bBg0acPLkySIrv6nVajQajXI/Q6GAgAB8fHxYt26d8t3Fx8fTp0+fYpO+/Px8lixZwocffkjnzp1xdXUlNDSUWbNmGSSkt/erVquBW1OrR40aRUxMjPKZ5s2bx8svv2xwkaV58+bKv++cHTFv3jxGjBjB0qVLMTc3x9bWFpVKdd+mtAghhBBCVJbu3bvTokUL5f3169cBOHv2rDJgUPi+IuuK2NnZ4e3tzcmTJ4Fbg1Dp6elFbjN77rnnaNu2baWtMfLQT/0tzsmTJ8nNzaVjx45oNBrltXbtWuU+wUKNGzdW/u3k5KRMNb1927lz50rt7/Y2Cv+orUidwhOnrDq3s7S05MUXX1RuXv7hhx84evQoOp2u2PK5ubk4OTmxc+dO3NzcGDFiBKtXrzZYDOd2x44do3HjxgaJc2HSf7t33nmHp556CkdHRzQaDStXriwyh71BgwaYmPzvVHNycqJRo0bKe1NTUxwcHAw+/+bNm2ndujXOzs5oNBqmT59u0O7x48eLJNi3v7969Srp6emEh4cbnAPz5s1TzgGdTkdaWho+Pj6MGTOGL7/8sthjUWjDhg0GbW3YsIGYmBiDbd9++22pbdyuPDEWuvM8BQyOYUXPU7h13t3v8xQgIiJCmQ1w9uxZduzYwZAhQ4otW1BQQF5eHomJiTRo0IBevXrxySeflLn41+XLl+natStdunThlVdeUeI8ffo0zzzzTIn1du/ezTPPPEONGjXQarW8+OKLnD9/3mC6vxBCCCHEw0Cr1VK3bl3lVb9+fZydnQ1uC7xy5QopKSnF/l1fkpycHGVNILg1yPbTTz+RlpamvADeeuutIrfz3YuHfkS1OIWjatu2baNGjRoG++5cLOb2qa8qlarIVFiVSkVBQekPmr/XOoUjoGXVuVNERARNmzbl1KlTxMfHExQUVOKooL29PaNGjTLYVqdOHerUqVOhPm+3adMmoqKiiIuLo1WrVmi1Wl5//XVSUlIMyhV3fEo7ZgcOHGDAgAHMnj2bkJAQbG1tlam95VV4DqxatcrgyhKgTA9v1qwZGRkZ7Nixg927d9O3b1+Cg4MN7mW+3Z1XqSZNmkSNGjUYM2aMsu3O8+1eYyxU3Ply57aqep4OHDiQyZMnc+DAAZKTk/H09KRt27Yl9hcVFWWwzcnJiREjRpTYfn5+PmFhYdjY2BjcH1440lqSzMxMunbtyksvvcT8+fOxt7dn//79hIeHc+PGDaysrCrwKYUQQgghqhaVSsW4ceOYN28eXl5eeHp6MmPGDFxdXQ3WMnnmmWfo1auXso5HVFQU3bp1w93dndOnTzNr1ixMTU3p168fgLIS8J1q1apV6vo3FfVIJqr169fHwsKCrKwsg2m+Dytzc3Py8/OLbG/UqBH+/v6sWrWKjRs3smTJknK1V57Hlvj6+rJu3TqD6cgHDx40KJOUlERAQIAy7RkoMhJ4N5KTk3F3d2fatGnKtj/++MOgjI+PD6mpqQwcOFDZlpqaqvzbyckJV1dXfv/9dwYMGFBiXzY2NoSFhREWFsbzzz9PaGgoFy5cwN7evkhZrVZrsOKzVqvF3t6eunXr3tXnLG+MD4uSzlMHBwd69uxJfHw8Bw4cUKZrl6W8CxeNHz+eI0eOcOjQIYMZAFqtFg8PDxITE+nQoUORet9//z0FBQXExcUpI/5btmwp12cSQgghhHgYTJw4katXrzJs2DAuXbpEmzZt2Llzp8HfTOnp6fzzzz/K+1OnTtGvXz/Onz+Po6Mjbdq04eDBgzg6Oho19kcyUdVqtURFRTF+/HgKCgpo06aNsoiKjY2Nwb1/DwMPDw927drF8ePHcXBwwNbWVhnpKlxUydraml69elVan/3792fatGkMHTqUKVOmkJmZyRtvvGFQxsvLi7Vr17Jr1y48PT1Zt24dqamp93wlxcvLi6ysLDZt2kTz5s3Ztm0bW7duNSgzevRohg4dir+/PwEBAWzevJmffvrJYNr27NmzGTNmDLa2toSGhnL9+nUOHTrExYsXmTBhAm+++SYuLi74+flhYmLCBx98gLOzs1Gfm1lWjA8TDw8PMjIySEtLw83NDa1Wq8xgiIiIoGvXruTn51fqz198fDxLly5l69atqFQqZQW7wmnU0dHRjBgxgurVq9OpUyf+/fdfkpKSGD16NHXr1iUvL4+3336bbt26kZSUxPLly4t8ppycHBITE2nSpAlWVlYy0iqEEEKIh4ZKpWLOnDnMmTOnxDJ33mK1adOmCvdz+yMwK8sjeY8qwNy5c5kxYwaxsbH4+voSGhrKtm3bKnU42liGDh2Kj48P/v7+ODo6Gqxa2q9fP8zMzOjXr1+RhZjuhUaj4fPPP+fIkSP4+fkxbdo0XnvtNYMyw4cPp3fv3oSFhdGiRQvOnz9vMLp6t7p378748eOJjIykadOmJCcnM2PGDIMyAwYMYMqUKURFRSlTeHU6ncExiIiI4N133yU+Pp5GjRrRvn17EhISlHNAq9WyYMEC/P39ad68OZmZmWzfvt3gftr7rawYHybPPfccoaGhdOjQAUdHR95//31lX3BwMC4uLoSEhODq6lppfe7bt4/8/Hy6d++Oi4uL8iq8qDJo0CAWLlzI0qVLadCgAV27duXEiRMANGnShDfffJPXXnuNhg0bsmHDhiKPJwoICGDEiBGEhYXh6OjIggULKi12IYQQQghRMpX+fqS/wmgyMzOpU6cOqampNGvW7EGH80B17NgRZ2dn1q1b96BDEXfIycmhRo0axMfHKyscP44unTXOIk0qk6Irf98P+XkVu1/5nvrKN05f1cxNyy5UCUxMjfMdFeQb5794Y32eE6lnjdJPdQ8bo/RjbmmciW1m5sa5AOtQQx7hJYSoPI/k1N/HQV5eHufPn2f69Om0bNnysUtSc3NzWb58OSEhIZiamvL++++ze/duvvrqqwcdmrhNQUEB//zzD3FxcdjZ2dG9e/cHHZIQQgghhHgISKL6kEpKSqJDhw54e3uXuErto0ylUrF9+3bmz5/PtWvX8PHx4aOPPiI4OPhBhyZuk5WVhaenJ25ubiQkJGBm9nj/yjHWBBa9kdZ/MuaEHAu1cc6dK+evGaUfK625UfqxtrMou1AlOH8qp+xClcCxlrbsQpWgpm/RBfXuh7MZV4zSjxBCPIxk6q8QQhjJxTNXjdSTsaaVGm/qbzUL40zJlUT17hgrUb2ZZ5yrMLUaOBilH2MlqjL1VwjxMHpkF1MSQgghhBBCCPFwemwTVb1ez7Bhw7C3t0elUpGWlnbf+goMDGTcuHHlLp+ZmVnhmKKjo2natGmFY7vf7uazCEPR0dE4OTmhUqn45JNP7ls/Op3O4OHP5VHRmBISEoz6+B8hhBBCiMeZXq9n5syZuLi4oFarCQ4OVp6AUBIPDw9UKlWR16hRowC4cOECo0ePxsfHB7VaTa1atRgzZgyXL1+u1Ngf20R1586dJCQk8MUXX5CdnU3Dhg3vW18ff/wxc+fOLXf5mjVrVjimqKgoEhMTlfd3k3SURqfTFXnGkrj/jh07xuzZs1mxYgXZ2dl06tTpvvW1aNEiEhISKlSnojGFhYXx22+/Ke8r+wJLdHQ0e/fuvac2Pv74Y/z9/bGzs8Pa2pqmTZvKStJCCCGEeCgtWLCAxYsXs3z5clJSUrC2tiYkJIRr10q+1SU1NZXs7GzlVbhYaZ8+fQA4ffo0p0+f5o033uDo0aMkJCSwc+dOwsPDKzX2xzZRTU9Px8XFhYCAAJydne/rIi/29vZoteVfAMLU1LTCMWk0GhwcKveemgsXLvDOO+8YLJiSnp7Ohg0bKrWfx4lOpyM6Orrc5dPT0wHo0aMHzs7OWFjcv/vNbG1tKzzaWdGY1Go11atXr2BkpcvLyyMuLo68vDxl27lz51ixYsVdtWdvb8+0adM4cOAAP/30E4MHD2bw4MHs2rWrskIWQgghhLjv9Ho9CxcuZPr06fTo0YPGjRuzdu1aTp8+XeqMOEdHR5ydnZXXF198QZ06dWjfvj0ADRs25KOPPqJbt27UqVOHoKAg5s+fz+eff87NmzcrLf7HMlHV6XSMHj2arKwsVCoVHh4ewK1HacTGxuLp6YlaraZJkyYGK+ru3bsXlUrFrl278PPzQ61WExQUxLlz59ixYwe+vr7Y2NjQv39/cnP/97zEO6f+enh4EBMTw5AhQ9BqtdSqVYuVK1cq+++cLlvYb2JiIv7+/lhZWREQEMDx48eVOrePTEVHR7NmzRo+/fRTZah+7969BAUFERkZaXAs/v77b8zNzQ1GYwtZWlry119/ERoayqlTp1i+fDk6nQ5PT88Sj+13332Hn58flpaW+Pv7c/jwYYP9+fn5hIeHK8fYx8eHRYsWFfl+evbsSUxMDE5OTtjZ2TFnzhxu3rzJK6+8gr29PW5ubsTHxxvUmzRpEt7e3lhZWVG7dm1mzJhhkLwAzJs3j+rVq6PVaomIiGDy5MlFRvTeffddfH19sbS0pF69eixdulTZd+PGDSIjI3FxccHS0hJ3d3diY2NLPB73Ijo6mm7dugFgYmKCSvW/BXJKi7Hw/NmyZQtt27ZFrVbTvHlzfvvtN1JTU/H390ej0dCpUyf+/vtvpd6do/CBgYGMGTOGiRMnYm9vj7Ozc5Ek+/apv4X9fvzxx3To0AErKyuaNGnCgQMHlPK3T/1NSEhg9uzZ/Pjjj8p5mpCQwJAhQ+jatatBP3l5eVSvXp333nuvyHEqPC5BQUH8/PPPbN26lW7duuHm5lbscU1ISCh2OkvhZwsMDKRXr174+vpSp04dxo4dS+PGjdm/f3+x7QkhhBBCVEUZGRmcOXPG4KkYtra2tGjRwuDvs9LcuHGD9evXM2TIEIO/Re90+fJlbGxsKnXw77F8VsSiRYuoU6cOK1euJDU1FVPTW6tJxsbGsn79epYvX46XlxfffPMNL7zwAo6OjsoVBLiVQCxZsgQrKyv69u1L3759sbCwYOPGjeTk5NCrVy/efvttJk2aVGIMcXFxzJ07l6lTp/Lhhx/y0ksv0b59e3x8fEqsM23aNOLi4nB0dGTEiBEMGTKEpKSkIuWioqI4duwYV65cUZI5e3t7IiIiiIyMJC4uThkFW79+PTVq1CAoKKhIO1ZWVsTExLB9+3a6d+/OzZs3+frrr6lWrVqx8eXk5NC1a1c6duzI+vXrycjIYOzYsQZlCgoKcHNz44MPPsDBwYHk5GSGDRuGi4sLffv2Vcp9/fXXuLm58c0335CUlER4eDjJycm0a9eOlJQUNm/ezPDhw+nYsaOSkGi1WhISEnB1deXIkSMMHToUrVbLxIkTAdiwYQPz589n6dKltG7dmk2bNhEXF2eQeG/YsIGZM2eyZMkS/Pz8OHz4MEOHDsXa2ppBgwaxePFiPvvsM7Zs2UKtWrX4888/+fPPP0v8zu5FVFQUHh4eDB48mOzs7HLHWGjWrFksXLiQWrVqMWTIEPr3749Wq2XRokXKuTtz5kyWLVtWYgxr1qxhwoQJpKSkcODAAXQ6Ha1bt6Zjx44l1pk2bRpvvPEGXl5eTJs2jX79+nHy5Mkiv7jCwsI4evQoO3fuZPfu3cCtX57e3t60a9eO7OxsXFxcAPjiiy/Izc0lLCysSH9mZma8/PLLBAUF0aZNG2rVqsXBgwextbUtNr6wsDBCQ0OV93v37uXFF1+kdevWRcrq9Xq+/vprjh8/zmuvvVbiZxZCCCGEqGrOnDkDgJOTk8F2JycnZV9ZPvnkEy5duoROpyuxzD///MPcuXMZNmzYXcdanMdyRNXW1hatVqtMsXV0dOT69evExMSwevVqQkJCqF27NjqdjhdeeKHIFMJ58+bRunVr/Pz8CA8PZ9++fSxbtgw/Pz/atm3L888/z549e0qNoXPnzowcOZK6desyadIknnzyyTLrzJ8/n/bt21O/fn0mT55McnJysfPLNRoNarUaCwsLZcje3Nyc3r17A/Dpp58qZRMSEtDpdMVeIbl27RozZ85k0aJFBAYG0rJlS4KDg/nuu++KjW/jxo0UFBTw3nvv0aBBA7p27corr7xiUKZatWrMnj0bf39/PD09GTBgAIMHD2bLli0G5ezt7Vm8eDE+Pj4MGTIEHx8fcnNzmTp1Kl5eXkyZMgVzc3ODUa7p06cTEBCAh4cH3bp1IyoqyqDdt99+m/DwcAYPHoy3tzczZ86kUaNGBv3OmjWLuLg4evfujaenJ71792b8+PHKOZCVlYWXlxdt2rTB3d2dNm3a0K9fv2KPx73SaDTK6GPh91ieGAtFRUUREhKCr68vY8eO5fvvv2fGjBkG525Z51zjxo2ZNWsWXl5eDBw4EH9//2JH3+/st0uXLnh7ezN79mz++OMPTp48WaScWq1Go9FgZmamfD61Wk1AQAA+Pj4G94XGx8fTp08fNJqijz7Iz89n0aJFjBkzhs6dO/Pss88SGhrKzp07i41PrVYr/V29epVRo0YRExNjkHxfvnwZjUaDubk5Xbp04e233y41ORdCCCGEeNA2bNiARqNRXnfOLLwb7733Hp06dcLV1bXY/VeuXKFLly7Ur1+/Qre3lcdjmagW5+TJk+Tm5tKxY0eDL3jt2rXKfYKFGjdurPzbyclJmWp6+7Zz586V2t/tbahUKpydnStUp3Ckqaw6t7O0tOTFF19k9erVAPzwww8cPXq0xCskubm5ODk5sXPnTtzc3BgxYgSrV682WAzndseOHaNx48ZYWloq21q1alWk3DvvvMNTTz2Fo6MjGo2GlStXkpWVZVCmQYMGmJj87/R0cnIySCpNTU1xcHAw+PybN2+mdevWODs7o9FomD59ukG7x48f5+mnnzbo5/b3V69eJT09nfDwcINzYN68eco5oNPpSEtLw8fHhzFjxvDll18WeywK3fkLY8OGDcTExBhs+/bbb0tt43blibHQnecpYHAMK3qewq3z7n6fpwARERHKbICzZ8+yY8cOhgwZUmzZgoIC8vLySExMpEGDBvTq1YtPPvmkzMW/Ll++TNeuXenSpUuRCyparZa0tDRSU1OZP38+EyZMuOdFmoQQQggh7qfu3buTlpamvJ588kng1t9Stzt79qwyAFKaP/74g927dxMREVHs/n///ZfQ0FC0Wi1bt24tcdbl3Xosp/4WJyfn1sPKt23bRo0aNQz23blYzO1fgkqlKvKlqFQqCgoKSu3vXusUjoCWVedOERERNG3alFOnThEfH09QUBDu7u7FlrW3t1eWoS5Up04d6tSpU6E+b7dp0yaioqKIi4ujVatWaLVaXn/9dVJSUgzKFXd8SjtmBw4cYMCAAcyePZuQkBBsbW2Vqb3lVXgOrFq1ihYtWhjsK5we3qxZMzIyMtixYwe7d++mb9++BAcHG9zLfLvu3bsbtDVp0iRq1KjBmDFjlG13nm/3GmOh4s6XO7dV1fN04MCBTJ48mQMHDpCcnIynpydt27Ytsb+oqCiDbU5OTowYMaLE9vPz8wkLC8PGxsbg/vBCJiYm1K1bF4CmTZty7NgxYmNjCQwMrNDnEEIIIYQwFq1Wa7CAq16vx9nZmcTERGVNlitXrpCSksJLL71UZnvx8fFUr16dLl26FNl35coVQkJCsLCw4LPPPjMYqKoskqj+f/Xr18fCwoKsrCyD+1EfVubm5uTn5xfZ3qhRI/z9/Vm1ahUbN25kyZIl5WqvPI8t8fX1Zd26dVy7dk05WQ8ePGhQJikpiYCAAEaOHKlsu3Mk8G4kJyfj7u7OtGnTlG1//PGHQRkfHx9SU1MZOHCgsi01NVX5t5OTE66urvz+++8MGDCgxL5sbGwICwsjLCyM559/ntDQUC5cuIC9vX2Rsnf+wtBqtdjb2ytJUEWVN8aHRUnnqYODAz179iQ+Pp4DBw4wePDgcrVX3ikn48eP58iRIxw6dKhcv1gLCgq4fv16udoWQgghhKgKVCoV48aNY968eXh5eeHp6cmMGTNwdXU1WEDzmWeeoVevXgaLrhYUFBAfH8+gQYOKrDNy5coVnn32WXJzc1m/fj1XrlzhypUrwK0Vg+8cPLlbkqj+f1qtlqioKMaPH09BQQFt2rTh8uXLJCUlYWNjY7BIzcPAw8ODXbt2cfz4cRwcHLC1tVVGugoXVbK2tqZXr16V1mf//v2ZNm0aQ4cOZcqUKWRmZvLGG28YlPHy8mLt2rXs2rULT09P1q1bR2pqaqkrCZeHl5cXWVlZbNq0iebNm7Nt2za2bt1qUGb06NEMHToUf39/AgIC2Lx5Mz/99JPBtO3Zs2czZswYbG1tCQ0N5fr16xw6dIiLFy8yYcIE3nzzTVxcXPDz88PExIQPPvgAZ2fnCj/W5V6UFePDxMPDg4yMDNLS0nBzc0Or1SozGCIiIujatSv5+fmV+vMXHx/P0qVL2bp1KyqVSllMoHAadWxsLP7+/tSpU4fr16+zfft21q1bV+qiU0IIIYQQVdHEiRO5evUqw4YN49KlS7Rp04adO3caXKhPT0/nn3/+Mai3e/dusrKyir316ocfflBmQ945+JKRkaE8UeVeyT2qt5k7dy4zZswgNjYWX19fQkND2bZt2z0nUQ/C0KFD8fHxwd/fH0dHR4PVgfv164eZmRn9+vWr1GF6jUbD559/zpEjR/Dz82PatGlFVkodPnw4vXv3JiwsjBYtWnD+/HmD0dW71b17d8aPH09kZCRNmzYlOTmZGTNmGJQZMGAAU6ZMISoqSpnCq9PpDI5BREQE7777LvHx8TRq1Ij27duTkJCgnANarZYFCxbg7+9P8+bNyczMZPv27Qb3095vZcX4MHnuuecIDQ2lQ4cOODo68v777yv7goODcXFxISQkpMQb+O/Gvn37yM/Pp3v37ri4uCivwosqV69eZeTIkTRo0IDWrVvz0UcfsX79+hLvzxBCCCGEqKpUKhVz5szhzJkzXLt2jd27d+Pt7W1QJjMzs8istGeffRa9Xl+kLNx6lJ9ery/2VVlJKoBKr9frK6018VDIzMykTp06pKam0qxZswcdzgPVsWNHnJ2dDVaYFVVDTk4ONWrUID4+Xlmx+mF38cxVI/VU8nPOKlNBfsXuPb4X1SwqZxpRWa6cL7qS+v1gpTU3Sj/WdhZlF6oE50/lGKWfm3lFbxW4H2o1cDBKP2czrhilHzNz41xMdahRdGV2IYS4WzL19zGSl5fH+fPnmT59Oi1btnzsktTc3FyWL19OSEgIpqamvP/+++zevZuvvvrqQYcmblNQUMA///xDXFwcdnZ2dO/e/UGHJIQQQgghjEwS1cdIUlISHTp0wNvbu8RVah9lKpWK7du3M3/+fK5du4aPjw8fffQRwcHBDzo0cZusrCw8PT1xc3MjISGhyA38D7P/rtz788zKw1JTucvDVwUF+caZ/GPvYm2Ufs6kXzZKPyamxhldN9Y5p3ni0Rqxu/7fTaP0Y2ZunBF8IYSoTDL1VwghjOT0b5eM0o+xkgZj/vdhamacqYvmauNcGDFWomrvapzE21gXEjRPGGcqs7HOg6xfLhilH2tb4ySqMvVXCFGZZDElIYQQQgghhBBViiSq4q7p9XqGDRuGvb09KpWKtLS0+9ZXYGAg48aNK3f5zMzMCscUHR2tPAy5qnuYYhVCCCGEEA+GXq9n5syZuLi4oFarCQ4O5sSJE6XW+ffffxk3bhzu7u6o1WoCAgJITU01KHP27Fl0Oh2urq5YWVkRGhpaZrsVJYmquGs7d+4kISGBL774guzsbBo2bHjf+vr444+ZO3duucvXrFmzwjFFRUWRmJiovNfpdAYPQxaPh48//hh/f3/s7OywtramadOmsiq0EEIIIR5KCxYsYPHixSxfvpyUlBSsra0JCQnh2rWSV7mPiIjgq6++Yt26dRw5coRnn32W4OBg/vrrL+BW8tuzZ09+//13Pv30Uw4fPoy7uzvBwcFcvVp5TziQRFXctfT0dFxcXAgICMDZ2fm+Lnpjb2+PVqstd3lTU9MKx6TRaHBwuP+PJIiOjkan0933fh4nKpWKzMzMSmnL3t6eadOmceDAAX766ScGDx7M4MGD2bVrV6W0L4QQQghhDHq9noULFzJ9+nR69OhB48aNWbt2LadPn+aTTz4pts5///3HRx99xIIFC2jXrh1169YlOjqaunXrsmzZMgBOnDjBwYMHWbZsGc2bN8fHx4dly5bx33//8f7771da/JKoirui0+kYPXo0WVlZqFQq5eG+BQUFxMbG4unpiVqtpkmTJgYrDO/duxeVSsWuXbvw8/NDrVYTFBTEuXPn2LFjB76+vtjY2NC/f39yc3OVendO/fXw8CAmJoYhQ4ag1WqpVasWK1euVPbfOfW3sN/ExET8/f2xsrIiICCA48ePK3Vun04bHR3NmjVr+PTTT1GpVKhUKvbu3UtQUBCRkZEGx+Lvv//G3NzcYDS2sr366qs4OTmh1WoJDw8vchUsNTWVjh078uSTT2Jra0v79u354YcfDMqoVCpWrFhB165dsbKywtfXlwMHDnDy5EkCAwOxtrYmICCA9PR0pU56ejo9evTAyckJjUZD8+bN2b17t0G72dnZdOnSBbVajaenJxs3bsTDw4OFCxcqZS5dukRERASOjo7Y2NgQFBTEjz/+qOz/8ccf6dChA1qtFhsbG5566ikOHTpUiUfwfxISEpTv9PZX4YOuAwMD6dWrF76+vtSpU4exY8fSuHFj9u/ff1/iEUIIIYS4HzIyMjhz5ozBEy5sbW1p0aIFBw4cKLbOzZs3yc/Px9LS0mC7Wq1W/ha6fv06gEEZExMTLCwsKvXvJUlUxV1ZtGgRc+bMwc3NjezsbGXeemxsLGvXrmX58uX8/PPPjB8/nhdeeIF9+/YZ1I+OjmbJkiUkJyfz559/0rdvXxYuXMjGjRvZtm0bX375JW+//XapMcTFxeHv78/hw4cZOXIkL730kkHiWZxp06YRFxfHoUOHMDMzY8iQIcWWi4qKom/fvoSGhpKdnU12djYBAQFERESwceNG5QcUYP369dSoUYOgoKDyHLoK27JlC9HR0cTExHDo0CFcXFxYunSpQZl///2XQYMGsX//fg4ePIiXlxedO3fm33//NSg3d+5cBg4cSFpaGvXq1aN///4MHz6cKVOmcOjQIfR6vUEinpOTQ+fOnUlMTOTw4cOEhobSrVs3srKylDIDBw7k9OnT7N27l48++oiVK1dy7tw5g3779OmjXIz4/vvvadasGc888wwXLtxa8XLAgAG4ubmRmprK999/z+TJk6lW7f6sXBsWFqZ8p9nZ2bz//vuYmZnRunXrImX1ej2JiYkcP36cdu3a3Zd4hBBCCCHuhzNnzgDg5ORksN3JyUnZdyetVkurVq2YO3cup0+fJj8/n/Xr13PgwAGys7MBqFevHrVq1WLKlClcvHiRGzdu8Nprr3Hq1CmlTGWQRFXcFVtbW7RarTLF1tHRkevXrxMTE8Pq1asJCQmhdu3a6HQ6XnjhBVasWGFQf968ebRu3Ro/Pz/Cw8PZt28fy5Ytw8/Pj7Zt2/L888+zZ8+eUmPo3LkzI0eOpG7dukyaNIknn3yyzDrz58+nffv21K9fn8mTJ5OcnFzsHH2NRoNarcbCwgJnZ2ecnZ0xNzend+/eAHz66adK2YSEBHQ6HSrV/Xle4cKFCwkPDyc8PBwfHx/mzZtH/fr1DcoEBQXxwgsvUK9ePSeJ9IIAAFcXSURBVHx9fVm5ciW5ublFLhAMHjyYvn374u3tzaRJk8jMzGTAgAGEhITg6+vL2LFj2bt3r1K+SZMmDB8+nIYNG+Ll5cXcuXOpU6cOn332GQC//voru3fvZtWqVbRo0YJmzZrx7rvv8t9//ylt7N+/n++++44PPvgAf39/vLy8eOONN7Czs1NG27OysggODqZevXp4eXnRp08fmjRpcl+Op1qtVr7Tq1evMmrUKGJiYujYsaNS5vLly2g0GszNzenSpQtvv/22wX4hhBBCiKpmw4YNaDQa5ZWXd3fPb1+3bh16vZ4aNWpgYWHB4sWL6devHyYmt1LHatWq8fHHH/Pbb79hb2+PlZUVe/bsoVOnTkqZyiCJqqg0J0+eJDc3l44dOxr8kKxdu9ZgOilA48aNlX87OTlhZWVF7dq1DbbdOSp3p9vbUKlUODs7V6iOi4sLQJl1bmdpacmLL77I6tWrAfjhhx84evRoqfecfvvttwbHIyYmpsgvkg0bNpRY/9ixY7Ro0cJgW6tWrQzenz17lqFDh+Ll5YWtrS02Njbk5OQYjHxC0eMO0KhRI4Nt165d48qVK8CtEdWoqCh8fX2xs7NDo9Fw7Ngxpd3jx49jZmZGs2bNlDbq1q3LE088obz/8ccfycnJwcHBweAzZ2RkKOfFhAkTiIiIIDg4mFdffbXI+XKnTp06GbQF0KBBA+V9gwYNSq0Pt5LRrl270qVLF1555RWDfVqtlrS0NFJTU5k/fz4TJkwwSOCFEEIIIaqa7t27k5aWpryefPJJ4Nbfibc7e/Yszs7OJbZTp04d9u3bR05ODn/++SffffcdeXl5Bn+rP/XUU6SlpXHp0iWys7PZuXMn58+fNyhzr4zzRGvxWMjJyQFg27Zt1KhRw2CfhYXhQ9pvn9apUqmKTPNUqVQUFBSU2t+91ikcAS2rzp0iIiJo2rQpp06dIj4+nqCgINzd3Uss7+/vb/CYnMWLF/PXX3/x2muvKdvunJJRUYMGDeL8+fMsWrQId3d3LCwsaNWqFTdu3DAoV9znL+2YREVF8dVXX/HGG29Qt25d1Go1zz//fJF2S5OTk4OLi0uxiZ6dnR1wayp4//792bZtGzt27GDWrFls2rSJXr16FdvmnaO2Xl5ebN++XTnvypo2nJ+fT1hYGDY2Ngb3NhcyMTGhbt26ADRt2pRjx44RGxtLYGBgOT6xEEIIIYTxabVag8VH9Xo9zs7OJCYmKuuwXLlyhZSUFF566aUy27O2tsba2pqLFy+ya9cuFixYUKSMra0tcGuBpUOHDlXoKR1lkURVVJr69etjYWFBVlYW7du3f9Dh3DNzc3Py8/OLbG/UqBH+/v6sWrWKjRs3smTJklLbUavVStIDt1aVvXLlisG20vj6+pKSksLAgQOVbQcPHjQok5SUxNKlS+ncuTMAf/75J//880+52i9NUlISOp1OSRhzcnIMVtf18fHh5s2bHD58mKeeegq4NbJ+8eJFpUyzZs04c+YMZmZmyqJbxfH29sbb25vx48fTr18/4uPjS0xU77wQAuDu7l5q+7cbP348R44c4dChQ0UWCyhOQUGBwX3JQgghhBBVnUqlYty4ccybNw8vLy88PT2ZMWMGrq6uBo9gfOaZZ+jVq5eyTsmuXbvQ6/X4+Phw8uRJXnnlFerVq8fgwYOVOh988AGOjo7UqlWLI0eOMHbs/2vv3uN7rv//j9/eO5/NGBt2MLY5zRgaksgYIudUTnNWLacc+4o5JZJT5VAfbcinQkhOFTlORgtFjMZaGIrInDbb6/eHn/end86Z90b36+Xyvlz2er2eh8fzjbc93s/n6/nqR8uWLWnUqFGexa9EVfKMu7s7gwYNYsCAAeTm5lKnTh3OnTtHYmIiHh4edOnSJb9DvCeBgYF8+eWXpKSkUKRIEQoVKmSeqevRowexsbG4urreMpnKK/369SMmJobq1avz+OOPs3DhQvbt22extCI4OJgFCxZQvXp1/vzzTwYPHoyzs/N99x0cHMzSpUtp3rw5JpOJ119/3WIGuly5ckRFRdGrVy9mzZqFvb09r776Ks7OzubZ2aioKGrVqkXLli2ZNGkSISEhHD9+nFWrVtGqVSsqVqzI4MGDadu2LaVLl+bo0aPs3LmTNm3a3Hf8NxMfH8/MmTNZtmwZJpPJvJnA9WXDEyZMoHr16pQpU4YrV66wevVqFixYYN6SXURERORhMWTIEC5cuECvXr04e/YsderUYe3atRZf1KemplpMcJw7d47hw4dz9OhRvLy8aNOmDePHj7dYsZaRkcHAgQM5efIkvr6+dO7cmddffz1PY1eiKnlq7NixeHt7M2HCBA4fPoynpycRERG89tpr+R3aPevZsycbN26kevXqZGZmsmHDBvPSz+eff57+/fvz/PPP39WM3P1o3749qampDBkyhMuXL9OmTRtefPFFi+d6zp07l169ehEREYGfnx9vvPEGgwYNuu++p0yZQrdu3ahduzZFixZl6NCh5vtXr5s/fz7du3enbt26+Pj4MGHCBPbt22d+X0wmE6tXr+b//u//6Nq1K7/99hs+Pj7UrVuX4sWLY2try+nTp+ncuTMnT56kaNGitG7dmtGjR993/DezadMmcnJyeOaZZyzOjxo1iri4OC5cuMBLL73E0aNHcXZ2ply5cnz00Ue0b9/+gcQjIiIi8qCYTCbGjBnDmDFjblnm78+if/bZZ3n22Wdv227fvn3p27dvXoR4SybDMIwH2oPIIygtLY0yZcqwc+dOi42EBI4ePYqfnx/r1q2jQYMG+R1OgXL84Fmr9OPk9mAe7fN31vzvw9bOOnv/OThb5/vbE6nnrNKPVwlXq/STm2OdvwtuhR3vXCgPWOvvQfpPZ6zSj2shB6v0U6Skm1X6EZF/B82oityD7OxsTp8+zYgRI6hZs6aSVOCbb74hMzOTsLAwMjIyGDJkCIGBgXruqIiIiIj8Y0pURe5BYmIi9evXJyQkxPwM0H+77OxsXnvtNQ4fPoy7uzu1a9dm4cKFd9x599+oRIhnfocgBURQVe/8DkEKAP8KXvkdgohIgaWlvyIiIiIiIlKgWOemHxEREREREZG7pERVREREREREChQlqiIiIiIiIlKgKFEVERERERGRAkWJqoiIiIiIiBQoSlRFRERERESkQFGiKiIiIiIiIgWKElUREREREREpUJSoioiIiIiISIGiRFVEREREREQKFCWqIiIiIiIiUqAoURUREREREZECRYmqiIiIiIiIFChKVEVERERERKRAUaIqIiIiIiIiBYoSVRERERERESlQlKiKiIiIiIhIgaJEVeQRZTKZMJlMJCQk5HcoVpOWlmYe98aNG/M7HBERERH5h5SoijyiIiMjiYyMxNvb+57qbdy40ZzspaWlPZjg7lNcXBwmk4nAwECL846OjuZxe3h45E9wIiIiInLf7PI7ABG5d1lZWTg4ONy2zPbt260UzZ0ZhsHVq1ext7d/oP34+voWqHGLiIiIyD+jGVWRe9SpUydMJhN16tSxOF+tWjVMJhN9+vQhNzeX6dOnU6lSJZycnChcuDDt2rXjyJEj5vJHjx6ladOm+Pn54ezsjLOzM5UqVWLatGkYhmEuFxgYiMlkYvDgwXTr1g1PT0+io6PvGOffl/4mJCSYz23YsIGIiAicnZ2JiIgwJ3dxcXHUr1/f3Ebp0qUxmUzExMQA3NW4/trP2rVrqVixIvb29iQmJrJ7924aNGiAr68vjo6OuLq6UqNGDT766COL2LOyshg/fjzly5fHyckJT09PnnzySY4ePUq9evUYPXo0AL/88ovFOG+19Hfr1q1ER0dTqFAhHB0dKV++PG+99RY5OTk3vM9Dhw4lNjaWIkWKUKxYMfr168fVq1fv+H6LiIiISB4yROSeJCYmGoABGCkpKYZhGMaRI0fM57Zt22a8+OKL5uOKFSsaRYoUMQDDx8fHOHnypGEYhrFr1y4DMEqVKmVUrVrVKFasmLnOu+++a+4vICDAAAwHBwfD2dnZCAsLM5o0aXLHOK+3FR8fbxiGYcTHx5vPOTo6GqGhoYadnZ0BGAEBAUZ2drbxwQcfGOXLlzeXq1KlihEZGWmMGTPGMAzjrsb1134cHByMwMBAIzAw0NiwYYOxbNkyw8bGxggICDCqVq1qFC5c2Fx25cqV5tibNWtmPu/r62uUK1fOsLW1NXbt2mW8+OKLRsmSJc3tR0ZGGpGRkcbKlSst/hw2bNhgGIZhbNiwwTzOwoULG8HBweYyPXr0uOF9tre3N7y8vMx9AMb777//z//CiIiIiMg9U6Iq8g9UrlzZAIyhQ4cahmEYkydPNgAjODjYOHz4sGEymQzAmDdvnmEYhnH+/HmjVKlSBmCMGDHCMAzDOHv2rHHkyBFzmzk5OUbdunUNwKhTp475/PUEqmjRokZ6erphGIZx9erVO8Z4u0R1xowZhmEYxvTp083n9u/fbxjGtcTu+rm/xne34/prP9ffn+sxZ2RkGCdOnDCfu3TpklG2bFkDMDp27GgYhmFs2rTJXD82NtbIyckxDMMw0tLSjNOnTxuGYRijRo0yJ9h/dbNE9fp7GhAQYPzxxx+GYRhGv379DMAwmUxGamqqxftcunRp4+zZs8alS5eMEiVKGIDRvn37O77fIiIiIpJ3tPRX5B948cUXAZg/fz45OTl89tlnAHTu3JnvvvvOvHS3S5cumEwm3N3dOXr0KPC/e0ft7OyYNGkSAQEB2NvbY2try+bNmwE4fvz4DX22adMGPz8/AGxtbe8r/k6dOgFQoUIF87mTJ0/ets7djuuv+vfvb/7Z1tYWk8nEq6++SokSJbCzs8PZ2Zmff/4Z+N+Yk5KSzHWGDRuGjc21j6mAgAC8vLzudajs3LkTgKZNm+Lp6QnACy+8AFy7dzY5Odmi/DPPPEOhQoVwcnKidOnSwJ3fGxERERHJW9pMSeQf6NixI0OGDCEjI4O5c+eyfft2TCYTnTp1YseOHeZyVapUwdHR0aJuQEAAcC2J+89//gNAcHAwXl5epKam8vvvv1vcO3ld8eLF8yz+6wmbnd3/PgKMv9wXeye3G9df/T3mjh07sm7dOkwmExUqVMDNzY2ffvqJ8+fP33TM+eH6ewP/e3/u5b0RERERkfunRFXkH3Bzc6NTp07MnDmTgQMHYhgG9erVIyAggJycHEwmE4ZhEBMTQ79+/YBryc7WrVspVKgQ8L8ZyEaNGvHll19y+fJlatasye+//37TPk0mk1XG5uLiYv75woUL5p+vbxZ1p3H91d9jvj7mnj17MmfOHM6cOUOlSpU4f/68uUxkZKT557feeoupU6diMpn49ddfcXV1xcvLyxzjxYsXMQzjtu9NjRo12Lx5M6tXr+bs2bN4enry8ccfm+OrVq3aXb83IiIiImIdWvor8g9dX/57PZnr0qULAEFBQfTs2RO4NmsaFBRE5cqV8fT0pG7dunz//fcAVK5cGYCvvvqK0NBQ/Pz8+PXXX609jBuUKVPG/BiZqKgoatasyZIlS+56XLdzfcz/+c9/qFixImXKlOHy5csWZerWrUuzZs0AmD59OiVLlqRChQoEBQWRnp4OQLly5QD47bffCA0NpWbNmhw+fPimfY4ePRo7Ozt++eUXgoKCCAkJYdq0aQB0796doKCge3yHRERERORBU6Iq8g9VqlSJJ554Arg2C9m2bVvztVmzZjF16lTCwsI4fvw4v/zyC4GBgQwcOJB69eoBMGXKFFq0aIGbmxvnz59n8ODBNG/ePD+GYqFIkSLMmDEDPz8/Tp48SVJSEidOnADubly3k5CQQP369XFycuLixYtMmzbNnLz+1Weffca4ceMoV64cp0+f5tixY9SqVYuiRYsC0KxZM3r27EmRIkU4dOgQSUlJXLx48aZ91qtXjw0bNtCwYUNycnJIS0ujXLlyTJw4kdmzZ//zN0pEREREHhiToZuvRP6xPn36MGfOHDp16sT8+fPzOxwRERERkUeCElWRf+D9999n1apVrF69mtzcXL7//nvCw8Ot1n9GRgatWrW66TVfX1+WLVtmtVhERERERPKaNlMS+Qe2bdvGihUrKFWqFGPGjLFqkgpw5coVi8e4/NXNdt+VguFA4iar9OPg7HLnQnngysULdy6UR5zd3K3TkZU2LbN3dLJKP1cuZlqln7MnT1ilH5v7fDTX3fItG2qVfo4f3G+Vfi79ZcO6B6mon79V+gmpWccq/RzcvtUq/VjT77+mW6Wf2u1esEo/2xb/1yr9WIu13reHhRJVkX8gISGBhISEfOs/MDBQj0wRERERkUeWNlMSERERERERABITEwkLC8Pe3p6WLVvmWxxKVEVERERERB4BMTExmEwmTCYT9vb2lC5dmiFDhtzwOMDbGThwIFWqVOHIkSP5uoJQS39FREREREQeEY0bNyY+Pp7s7GySk5Pp0qULJpOJiRMn3lX91NRU+vTpQ6lSpR5wpLenGVUREREREZFHhKOjIz4+Pvj5+dGyZUuioqL4+uuvAcjNzWXChAmULl0aZ2dnwsPDWbJkCQBpaWmYTCZOnz5Nt27dMJlM+TqjqkRVRB4Z9erVo2/fvgwZMgQvLy98fHyIi4szX58yZQphYWG4urri5+fHSy+9RGbm/3ZFTUhIwNPTky+//JLy5cvj5uZG48aNycjIyIfRiIiIiNyfvXv3sm3bNhwcHACYMGEC8+fPZ/bs2ezbt48BAwbQsWNHNm3ahJ+fHxkZGXh4eDBt2jQyMjJo3759vsWuRFVEHinz5s3D1dWVpKQkJk2axJgxY8zfItrY2DBjxgz27dvHvHnz+OabbxgyZIhF/YsXLzJ58mQWLFjA5s2bSU9PZ9CgQfkxFBEREZF7tnLlStzc3HByciIsLIxTp04xePBgrly5whtvvMGHH35IdHQ0QUFBxMTE0LFjR+bMmYOtrS0+Pj6YTCYKFSqEj48Pzs7O+TYO3aMqIo+UypUrM2rUKACCg4N59913Wb9+PQ0bNqR///7mcoGBgYwbN44+ffowc+ZM8/ns7Gxmz55NmTJlAIiNjWXMmDFWHYOIiIjIP1W/fn1mzZrFhQsXmDp1KnZ2drRp04Z9+/Zx8eJFGjZsaFE+KyuLqlWr5lO0t6ZEVUQeKZUrV7Y49vX15dSpUwCsW7eOCRMmcODAAf7880+uXr3K5cuXuXjxIi4uLgC4uLiYk9S/1xcREREp6FxdXSlbtiwAH374IeHh4cydO5dKlSoBsGrVKkqWLGlRx9HR0epx3omW/orII8Xe3t7i2GQykZubS1paGs2aNaNy5cp89tlnJCcn89577wHXvkm8XX3DMB584CIiIiJ5zMbGhtdee40RI0ZQoUIFHB0dSU9Pp2zZshYvPz+//A71BkpUReRfITk5mdzcXN5++21q1qxJSEgIx48fz++wRERERB6odu3aYWtry5w5cxg0aBADBgxg3rx5pKam8v333/POO+8wb968W9YvV64cy5Yts2LE12jpr4j8K5QtW5bs7GzeeecdmjdvTmJiIrNnz87vsEREREQeKDs7O2JjY5k0aRJHjhzB29ubCRMmcPjwYTw9PYmIiOC11167Zf2UlBTOnTtnxYivUaIqIv8K4eHhTJkyhYkTJzJ8+HDq1q3LhAkT6Ny5c36HJiIiIpInbvXc02HDhjFs2DAA+vXrR79+/W7ZxtmzZy2O8+sWKJOhm69ERKziQOImq/Tj4OxilX6uXLxglX4AnN3crdORyWSVbuwdnazSz5WLmXculAfOnjxhlX5sbG2t0o9v2VCr9HP84H6r9HPp/Hmr9FPUz98q/YTUrGOVfg5u32qVfqzp91/TrdJP7XYvWKWfbYv/a5V+rMVa79vDQveoioiIiIiISIGiRFVEREREREQKFCWqIiIiIiIiUqAoURUREREREZECRYmqiNy3hIQEPD098zsMEREREfkLwzAYOXIkvr6+ODs7ExUVxaFDh+5Y77333iMwMBAnJyciIyPZsWOHxfXLly/z8ssvU6RIEdzc3GjTpg0nT57M09iVqIrko8DAQKZNm2Zx7vLly8TExBAWFoadnR0tW7a8ad333nuP8uXL4+zsTGhoKPPnz7e4Xq9ePUwm0w2vp59+2lzm5MmTxMTEUKJECVxcXGjcuPFdfXiJiIiISME3adIkZsyYwezZs0lKSsLV1ZXo6GguX758yzqffvopAwcOZNSoUXz//feEh4cTHR3NqVOnzGUGDBjAF198weLFi9m0aRPHjx+ndevWeRq7ElX510hISKBevXr5HcYd5eTk4OzsTN++fYmKirppmVmzZjF8+HDi4uLYt28fo0eP5uWXX+aLL74wl1m6dCkZGRnm1969e7G1taVdu3bAtW/YWrZsyeHDh/n888/ZtWsXAQEBREVFceGC9R47IiIiIiJ5zzAMpk2bxogRI2jRogWVK1dm/vz5HD9+nOXLl9+y3pQpU+jZsyddu3alQoUKzJ49GxcXFz788EMAzp07x9y5c5kyZQpPPfUU1apVIz4+nm3btrF9+/Y8i1+JqsgtXF/Ounz5coKDg3FyciI6Oppff/3VotysWbMoU6YMDg4OhIaGsmDBAvM1wzCIi4vD398fR0dHSpQoQd++fYFrM56//PILAwYMMM92Ari6ujJr1ix69uyJj4/PTWNbsGABvXv3pn379gQFBfHcc8/Rq1cvJk6caC7j5eWFj4+P+fX111/j4uJiTlQPHTrE9u3bmTVrFjVq1CA0NJRZs2Zx6dIlPv744zu+N/7+/ri4uNCqVStOnz5tcT01NZUWLVpQvHhx3NzcqFGjBuvWrbMoExgYyLhx4+jcuTNubm4EBASwYsUKfvvtN1q0aIGbmxuVK1fmu+++M9c5ffo0zz//PCVLlsTFxYWwsLAbYj1//jwdOnTA1dUVX19fpk6dSr169ejfv7+5zJUrVxg0aBAlS5bE1dWVyMhINm7caL7+yy+/0Lx5cwoXLoyrqysVK1Zk9erVt31PRERERAqSI0eOcOLECYuJj0KFChEZGcm333570zpZWVkkJydb1LGxsSEqKspcJzk5mezsbIsy5cqVw9/f/5bt/hNKVEVu4+LFi4wfP5758+eTmJjI2bNnee6558zXly1bRr9+/Xj11VfZu3cvvXv3pmvXrmzYsAGAzz77jKlTpzJnzhwOHTrE8uXLCQsLA67NeJYqVYoxY8aYZz3v1pUrV3BycrI45+zszI4dO8jOzr5pnblz5/Lcc8/h6upqbgOwaMfGxgZHR0e2bv3fQ85jYmIsZqKTkpLo3r07sbGx7N69m/r16zNu3DiLvjIzM2natCnr169n165dNG7cmObNm5Oebvmg8alTp/L444+za9cunn76aTp16kTnzp3p2LEj33//PWXKlKFz584YhgFcWxZdrVo1Vq1axd69e+nVqxedOnWyuG9i4MCBJCYmsmLFCr7++mu2bNnC999/b9FvbGws3377LZ988gk//PAD7dq1s1j2/PLLL3PlyhU2b97Mjz/+yMSJE3Fzc7v1H4iIiIhIAXPixAkAihcvbnG+ePHi5mt/9/vvv5OTk3PbOidOnMDBweGG/Ulu1+4/oURV5Days7N59913qVWrFtWqVWPevHls27bNnBhNnjyZmJgYXnrpJUJCQhg4cCCtW7dm8uTJAKSnp+Pj40NUVBT+/v489thj9OzZE7g242lra4u7u7t51vNuRUdH85///Ifk5GQMw+C7777jP//5D9nZ2fz+++83lN+xYwd79+6lR48e5nPXv/kaPnw4f/zxB1lZWUycOJGjR49aJM2+vr74+/ubj6dPn07jxo0ZMmQIISEh9O3bl+joaIv+wsPD6d27N5UqVSI4OJixY8dSpkwZVqxYYVGuadOm9O7dm+DgYEaOHMmff/5JjRo1aNeuHSEhIQwdOpT9+/ebb84vWbIkgwYNokqVKgQFBfHKK6/QuHFjFi1aBFybTZ03bx6TJ0+mQYMGVKpUifj4eHJycsx9pqenEx8fz+LFi3niiScoU6YMgwYNok6dOsTHx5vLPP7444SFhREUFESzZs2oW7fuXf/5iIiIiFjbwoULcXNzM79uNXnxsFCiKo+s9PR0i3+sffr0YcuWLRbn3njjjdu2YWdnR40aNczH5cqVw9PTk/379wOwf/9+Hn/8cYs6jz/+uPl6u3btuHTpEkFBQfTs2ZNly5Zx9erV+x7b66+/TpMmTahZsyb29va0aNGCLl26ANdmRf9u7ty5hIWF8dhjj5nP2dvbs3TpUg4ePIiXlxcuLi5s2LCBJk2aWLQxYcIEi42a9u/fT2RkpEX7tWrVsjjOzMxk0KBBlC9fHk9PT9zc3Ni/f/8NM6qVK1c2/3z9m7vrM85/PXf95v2cnBzGjh1LWFgYXl5euLm58eWXX5rbPXz4MNnZ2RbjLFSoEKGhoebjH3/8kZycHEJCQiz+LmzatInU1FQA+vbty7hx43j88ccZNWoUP/zwww3vqYiIiEhB8swzz7B7927zq2jRogA37MZ78uTJW06QFC1aFFtb29vW8fHxISsri7Nnz951u/+EElV5ZJUoUcLiH+uYMWOoXr26xbk+ffo80Bj8/PxISUlh5syZODs789JLL1G3bt37/obL2dmZDz/8kIsXL5KWlkZ6ejqBgYG4u7vj7e1tUfbChQt88skndO/e/YZ2qlWrxu7duzl79iwZGRmsXbuW06dPExQUdF/xDRo0iGXLlvHGG2+wZcsWdu/eTVhYGFlZWRbl7O3tzT9fv0f3Zudyc3MBeOutt5g+fTpDhw5lw4YN7N69m+jo6BvavZ3MzExsbW1JTk62+Luwf/9+pk+fDkCPHj04fPgwnTp14scff6R69eq88847/+zNEBEREbECd3d3ypYta35VqFABHx8f1q9fby7z559/kpSUdMMkw3UODg5Uq1bNok5ubi7r168316lWrRr29vYWZVJSUkhPT79lu/+EElV5ZNnZ2Vn8Yy1WrBjOzs4W57y8vG7bxtWrVy0280lJSeHs2bOUL18egPLly5OYmGhRJzExkQoVKpiPnZ2dad68OTNmzGDjxo18++23/Pjjj8C1D4O/Lku9V/b29pQqVQpbW1s++eQTmjVrdsOM6uLFi7ly5QodO3a8ZTuFChXC29ubQ4cO8d1339GiRYtbli1fvjxJSUkW5/6+w1tiYiIxMTG0atWKsLAwfHx8SEtLu/cB/k1iYiItWrSgY8eOhIeHExQUxMGDB83Xg4KCsLe3Z+fOneZz586dsyhTtWpVcnJyOHXqlMXfhbJly1p8C+jn50efPn1YunQpr776Kh988MF9xy8iIiJiLSaTif79+zNu3DhWrFjBjz/+SOfOnSlRooTF4w8bNGjAu+++az4eOHAgH3zwAfPmzWP//v28+OKLXLhwga5duwLXfm/s3r07AwcOZMOGDSQnJ9O1a1dq1apFzZo18yx+uzxrSeQRZG9vzyuvvMKMGTOws7MjNjaWmjVrmpeWDh48mGeffZaqVasSFRXFF198wdKlS8073CYkJJCTk0NkZCQuLi589NFHODs7ExAQAFzb+Xbz5s0899xzODo6mpdo/PTTT2RlZXHmzBnOnz/P7t27AahSpQoABw8eZMeOHURGRvLHH38wZcoU9u7dy7x5824Yw9y5c2nZsiVFihS54drixYvx9vbG39+fH3/8kX79+tGyZUsaNWpkLjN8+HCOHTtmXv7bt29fHn/8cSZPnkyLFi348ssvWbt2rUW7wcHBLF26lObNm2MymXj99dfNs6L3Izg4mCVLlrBt2zYKFy7MlClTOHnypPmLAXd3d7p06cLgwYPx8vKiWLFijBo1ChsbG/PsbEhICB06dKBz5868/fbbVK1ald9++43169dTuXJlnn76afr370+TJk0ICQnhjz/+YMOGDeYvJ0REREQeFkOGDOHChQv06tWLs2fPUqdOHdauXWuxmWZqaqrFHift27fnt99+Y+TIkZw4cYIqVaqwdu1aiw2Wpk6dio2NDW3atOHKlStER0czc+bMPI1diarIbbi4uDB06FBeeOEFjh07xhNPPMHcuXPN11u2bMn06dOZPHky/fr1o3Tp0sTHx5t3yfX09OTNN99k4MCB5OTkEBYWxhdffGFOGseMGUPv3r0pU6YMV65cMe9u27RpU3755RdzP1WrVgUwX8/JyeHtt98mJSUFe3t76tevz7Zt2wgMDLSIPyUlha1bt/LVV1/ddHwZGRkMHDiQkydP4uvrS+fOnXn99ddvKPPXe0tr1qzJBx98wKhRoxg5ciRRUVGMGDGCsWPHmstMmTKFbt26Ubt2bYoWLcrQoUP5888/7+Wtv6kRI0Zw+PBhoqOjcXFxoVevXrRs2ZJz585Z9N2nTx+aNWuGh4cHQ4YM4ddff7X4QI6Pj2fcuHG8+uqrHDt2jKJFi1KzZk2aNWsGXHt/X375ZY4ePYqHhweNGzdm6tSp9x2/iIiIiDWZTCbGjBnDmDFjblnmZqveYmNjiY2NvWUdJycn3nvvPd577728CPOmTMb133xFxEJCQgL9+/e/4UZxebhcuHCBkiVL8vbbb9/0Pl1rOpC4ySr9ODi7WKWfKxcvWKUfAGc3d+t09P9n3h80e0enOxfKA1cuZlqln7Mn8+5xBLdjY2trlX58y4beuVAeOH5wv1X6uXT+vFX6Kernf+dCeSCkZh2r9HNw+9Y7F3rI/P5r+p0L5YHa7V6wSj/bFv/XKv1Yi7Xet4eFZlRF5JGya9cuDhw4wGOPPca5c+fM3yDe7r5bERERESlYlKiKyCNn8uTJpKSkmHeu27Jli/n+3/xk7+RslX7On77xWboPQiHvYlbpB+BMxjGr9GOtRUaXzp21Sj8eVvozKhPx2J0L5YGr2Xe/w/f9+H7NijsXygPVm7W2Sj+FfUtYpR9rzUC+3b6ZVfppPmCYVfqxpkdtxu5RG49YUqIqcgsxMTHExMTkdxhyj6pWrUpycnJ+hyEiIiIi90GPpxEREREREZECRYmqiOSJwMBApk2blt9hiIiIiMj/ZxgGI0eOxNfXF2dnZ6Kiojh06NBt68TFxWEymSxe5cqVsyhTr169G8r06dMnT2NXoioiIiIiIvIImjRpEjNmzGD27NkkJSXh6upKdHQ0ly9fvm29ihUrkpGRYX5t3XrjPeg9e/a0KDNp0qQ8jV2Jqkg+SEhIMD9rtSDLzs7O7xBERERE5B8wDINp06YxYsQIWrRoQeXKlZk/fz7Hjx9n+fLlt61rZ2eHj4+P+XWzTSldXFwsynh4eORp/EpURQq4Cxcu4OHhwZIlSyzOL1++HFdXV87//+fj/frrrzz77LN4enri5eVFixYtLB7gvHPnTho2bEjRokUpVKgQTz75JN9//71FmyaTiVmzZvHMM8/g6urK+PHjbxrTqVOnaN68Oc7OzpQuXZqFCxfeUGbKlCmEhYXh6uqKn58fL730EpmZ/3umY0JCAp6enqxcuZLQ0FBcXFxo27YtFy9eZN68eQQGBlK4cGH69u1LTk6Oud6CBQuoXr067u7u+Pj48MILL3Dq1CmLvlesWEFwcDBOTk7Ur1+fefPmYTKZLJ6Ju3XrVp544gmcnZ3x8/Ojb9++XLjwv+eCzpw509xG8eLFadu27S3+hEREREQKniNHjnDixAmioqLM5woVKkRkZCTffvvtbeseOnSIEiVKEBQURIcOHUhPv/EZvAsXLqRo0aJUqlSJ4cOHc/HixTyNX4mqSAHn6urKc889R3x8vMX5+Ph42rZti7u7O9nZ2URHR+Pu7s6WLVtITEzEzc2Nxo0bk5V17XEO58+fp0uXLmzdupXt27cTHBxM06ZNzYnudXFxcbRq1Yoff/yRbt26kZaWhslkYuPGjeYyMTEx/Prrr2zYsIElS5Ywc+bMG5JFGxsbZsyYwb59+5g3bx7ffPMNQ4YMsShz8eJFZsyYwSeffMLatWvZuHEjrVq1YvXq1axevZoFCxYwZ84ciyQ9OzubsWPHsmfPHpYvX05aWprF7sxHjhyhbdu2tGzZkj179tC7d2/+7//+z6Lf1NRUGjduTJs2bfjhhx/49NNP2bp1K7GxsQB899139O3blzFjxpCSksLatWupW7fuvf3BiYiIiOSjEydOAFC8eHGL88WLFzdfu5nIyEgSEhJYu3Yts2bN4siRIzzxxBMWvzO+8MILfPTRR2zYsIHhw4ezYMECOnbsmKfx6/E0Ig+BHj16ULt2bTIyMvD19eXUqVOsXr2adevWAfDpp5+Sm5vLf/7zH0wmE3AtkfX09GTjxo00atSIp556yqLN999/H09PTzZt2kSzZv97Jt0LL7xA165dzcfHjh0zz3gCHDx4kDVr1rBjxw5q1KgBwNy5cylfvrxF+/379zf/HBgYyLhx4+jTpw8zZ840n8/OzmbWrFmUKVMGgLZt27JgwQJOnjyJm5sbFSpUoH79+mzYsIH27dsD0K1bN3P9oKAgZsyYQY0aNcjMzMTNzY05c+YQGhrKW2+9BUBoaCh79+61mB2eMGECHTp0MMcYHBzMjBkzePLJJ5k1axbp6em4urrSrFkz3N3dCQgIoGrVqnf7xyUiIiJidQsXLqR3797m41WrVv2jdpo0aWL+uXLlykRGRhIQEMCiRYvo3r07AL169TKXCQsLw9fXlwYNGpCammr+ve5+aUZVxArS09Nxc3Mzv/r06cOWLVsszr3xxhu3rP/YY49RsWJF5s2bB8BHH31EQECAeZZvz549/Pzzz7i7u5vb8/Ly4vLly6SmpgJw8uRJevbsSXBwMIUKFcLDw4PMzMwblnJUr17d4rhkyZIcOHCAxx57DID9+/djZ2dHtWrVzGXKlSuHp6enRb1169bRoEEDSpYsibu7O506deL06dMWy0JcXFwsPsyKFy9OYGAgbm5uFuf+OlubnJxM8+bN8ff3x93dnSeffNL8HgOkpKSYE+i/vn9/tWfPHhISEize/+joaHJzczly5AgNGzYkICCAoKAgOnXqxMKFC/N8OYuIiIhIXnrmmWfYvXu3+XX9vtKTJ09alDt58iQ+Pj533a6npychISH8/PPPtywTGRkJcNsy90ozqiJWUKJECXbv3m0+Xrp0KZ999pnFvZ1eXl63baNHjx689957DBs2jPj4eLp27WqePc3MzKRatWo3vVfU29sbgC5dunD69GmmT59OQEAAjo6O1KpVy7w0+DpXV9d/OkyztLQ0mjVrxosvvsj48ePx8vJi69atdO/enaysLPPsrL29vUU9k8l003O5ubnAtft1o6OjiY6OZuHChXh7e5Oenk50dPQN47idzMxMevfuTd++fW+45u/vj4ODA99//z0bN27kq6++YuTIkcTFxbFz584bEnIRERGRgsDd3R13d3fzsWEY+Pj4sH79eqpUqQLAn3/+SVJSEi+++OJdt5uZmUlqaiqdOnW6ZZnrv+f6+vr+o9hvRomqiBXY2dlRtmxZ83GxYsVwdna2OHcnHTt2ZMiQIcyYMYOffvqJLl26mK9FRETw6aefUqxYsVvuuJaYmMjMmTNp2rQpcG3zpd9///2ex1KuXDmuXr1KcnKyeeYyJSXFYqOi5ORkcnNzefvtt7GxubZwY9GiRffc198dOHCA06dP8+abb+Ln5wdcu5/0r0JDQ1m9erXFuZ07d1ocR0RE8NNPP932/bezsyMqKoqoqChGjRqFp6cn33zzDa1bt77vcYiIiIg8aCaTif79+zNu3DiCg4MpXbo0r7/+OiVKlKBly5bmcg0aNKBVq1bmvToGDRpE8+bNCQgI4Pjx44waNQpbW1uef/554NpeH//9739p2rQpRYoU4YcffmDAgAHUrVuXypUr51n8Wvor8pAoXLgwrVu3ZvDgwTRq1IhSpUqZr3Xo0IGiRYvSokULtmzZwpEjR9i4cSN9+/bl6NGjwLX7MBcsWMD+/ftJSkqiQ4cOODs737HfY8eOUa5cOXbs2AFcSwQbN25M7969SUpKIjk5mR49eli0VbZsWbKzs3nnnXc4fPgwCxYsYPbs2ff9Hlyf7bze7ooVKxg7dqxFmd69e3PgwAGGDh3KwYMHWbRoEQkJCQDmGeihQ4eybds2YmNj2b17N4cOHeLzzz83f0CvXLmSGTNmsHv3bn755Rfmz59Pbm4uoaGh9z0GEREREWsZMmQIr7zyCr169TLv6bF27VqcnJzMZVJTUy0mL44ePcrzzz9PaGgozz77LEWKFGH79u3mVXoODg6sW7eORo0aUa5cOV599VXatGnDF198kaexK1EVeYhcXzr71w2F4Nq9nps3b8bf35/WrVtTvnx5unfvzuXLl80zrHPnzuWPP/4gIiKCTp060bdvX4oVK3bHPrOzs0lJSbG4RzM+Pp4SJUrw5JNP0rp1a3r16mXRVnh4OFOmTGHixIlUqlSJhQsXMmHChPsev7e3NwkJCSxevJgKFSrw5ptvMnnyZIsypUuXZsmSJSxdupTKlSsza9Ys866/jo6OwLWNATZt2sTBgwd54oknqFq1KiNHjqREiRLAtXsxli5dylNPPUX58uWZPXs2H3/8MRUrVrzvMYiIiIhYi8lkYsyYMZw4cYLLly+zbt06QkJCLMqkpaURFxdnPv7kk084fvw4V65c4ejRo3zyyScWe4r4+fmxadMmTp8+zeXLlzl06BCTJk3K8+eomgzDMPK0RRF5YBYsWMCAAQM4fvw4Dg4O+R3OQ2P8+PHMnj2bX3/9NV/jSE3eYZV+Ms+ctko/hbzv/EVHXjmTccwq/Vjrv8RL585apR8PK/0ZBYRZZ1fsq9l3fy/6/fh+zQqr9FO9mXVuJSjsW8Iq/RzcvtUq/Xwx9U2r9NN8wDCr9GNNITXr5HcIIndN96iKPAQuXrxIRkYGb775Jr1791aSegczZ86kRo0aFClShMTERN566y3zsl4RERERKfg0oyryEIiLi2P8+PHUrVuXzz//3OLxLXKjAQMG8Omnn3LmzBn8/f3p1KkTw4cPx85O382JiIiIPAyUqIqIiIiIiEiBos2UREREREREpEBRoioiIiIiIiIFihJVERERERERKVCUqIqIiIiIiEiBokRVREREREREChQlqiIiIiIiIlKgKFEVERERERGRAkWJqoiIiIiIiBQoSlRFRERERESkQFGiKiIiIiIiIgWKElUREREREREpUJSoioiIiIiISIGiRFVEREREREQKFCWqIiIiIiIiUqAoURUREREREZECRYmqiIiIiIiIFChKVEVERERERKRAUaIqIo+8evXqYTKZqFev3j3Vi4uLw2QyERgY+EDiEhEREZGbU6IqIiIiIiIiBYoSVRERERERESlQlKiKiNUFBgZiMpno1KkTAwcOpFChQpQsWZL4+HgyMjJ4+umncXV1JTw8nMTERHO9rVu3Eh0dTaFChXB0dKR8+fK89dZb5OTkmMv88ccfPPvss7i4uODv78/s2bNvGsOVK1cYNWoUwcHBODg4UKxYMbp168bvv//+wMcvIiIiIrdnl98BiMi/1+LFi3F3d8fFxYXjx4/Ts2dPypQpw4ULF3BwcOCHH37g+eefJzU1lcTERBo2bMjVq1cpXLgwAQEBHDhwgCFDhnDw4EE++OADAHr06MHSpUsBcHFxYdCgQTftu3Xr1qxevRpbW1sqVqxIWloa8fHxJCUl8d133+Hs7Gy190FERERELGlGVUTyjYeHB4cOHWLLli0A5OTkYG9vT2pqKkuWLAHg119/JTU1lVGjRnH16lUCAgI4fPgwBw8epF+/fgDMnTuXw4cPk5qaak5Shw4dyoEDB0hOTubKlSsW/W7atInVq1cD8M0337Bnzx4OHDiAs7MzP/30E//973+t9RaIiIiIyE0oURWRfFOnTh08PT0tdtVt1KgRjo6OBAUFmc+dPHmSnTt3AtC0aVM8PT0BeOGFFwAwDIPk5GT27dtnrtOmTRsAQkNDqVy5skW/O3bsMP/85JNPYjKZKFGiBJcuXQJg+/bteTdIEREREblnWvorIvnGw8MDADs7uxvOmUwm8znDMB5YDJGRkTec8/HxeWD9iYiIiMidKVEVkYdCjRo12Lx5M6tXr+bs2bN4enry8ccfA9eS2mrVqpGbm2suv2zZMmrUqMHBgwf54YcfbmjruuHDh9OiRQsArl69yrp16yhXrpwVRiQiIiIit6KlvyLyUBg9ejR2dnb88ssvBAUFERISwrRp0wDo3r07QUFBlC1blpYtWwIwYcIEypcvT0REBLa2thZt1atXj+joaABatmxJuXLlqFixIp6enjRp0oS0tDQrjkxERERE/k6Jqog8FOrVq8eGDRto2LAhOTk5pKWlUa5cOSZOnGjxCJq5c+fSpk0bnJycOHfuHGPGjKFmzZo3tLd8+XJGjhxJcHAwhw8f5sSJE5QvX54RI0ZQqVIlaw5NRERERP7GZDzIm79ERERERERE7pFmVEVERERERKRA0WZKIiJWcmzkNqv0Y+NqnY92B183q/QDYOPuYJV+Crcqa5V+RERE5PY0oyoiIiIiIiIFihJVERERERERASAxMZGwsDDs7e3NT1PID0pURUREREREHgExMTGYTCZMJhP29vaULl2aIUOGcPny5btuY+DAgVSpUoUjR46QkJDw4IK9AyWqInJX6tWrR//+/a3SV1xcHFWqVDEfx8TE5Os3eiIiIiIPi8aNG5ORkcHhw4eZOnUqc+bMYdSoUXddPzU1laeeeopSpUrh6en54AK9AyWqIlLgTZ8+PV+/0RMRERF5WDg6OuLj44Ofnx8tW7YkKiqKr7/+GoDc3FwmTJhA6dKlcXZ2Jjw8nCVLlgCQlpaGyWTi9OnTdOvWDZPJlK+/f2nXXxEp8AoVKpTfIQCQlZWFg4N1dp8VERERuV979+5l27ZtBAQEADBhwgQ++ugjZs+eTXBwMJs3b6Zjx454e3tTp04dMjIyCA0NZcyYMbRv3z5ffwfTjKqI3LM//viDzp07U7hwYVxcXGjSpAmHDh2yKPPBBx/g5+eHi4sLrVq1YsqUKf94+cjfl/7Wq1ePvn37MmTIELy8vPDx8SEuLs6iztmzZ+nRowfe3t54eHjw1FNPsWfPHvP11NRUWrRoQfHixXFzc6NGjRqsW7fOoo3AwEDGjh1L586d8fDwoFevXv8ofhERERFrWblyJW5ubjg5OREWFsapU6cYPHgwV65c4Y033uDDDz8kOjqaoKAgYmJi6NixI3PmzMHW1hYfHx9MJhOFChXCx8cHZ2fnfBuHElURuWcxMTF89913rFixgm+//RbDMGjatCnZ2dnAtd3i+vTpQ79+/di9ezcNGzZk/PjxeRrDvHnzcHV1JSkpiUmTJjFmzBjzshaAdu3acerUKdasWUNycjIRERE0aNCAM2fOAJCZmUnTpk1Zv349u3btonHjxjRv3pz09HSLfiZPnkx4eDi7du3i9ddfz9MxiIiIiOS1+vXrs3v3bpKSkujSpQtdu3alTZs2/Pzzz1y8eJGGDRvi5uZmfs2fP5/U1NT8DvsGWvorIvfk0KFDrFixgsTERGrXrg3AwoUL8fPzY/ny5bRr14533nmHJk2aMGjQIABCQkLYtm0bK1euzLM4KleubN4YIDg4mHfffZf169fTsGFDtm7dyo4dOzh16hSOjo7AtYRz+fLlLFmyhF69ehEeHk54eLi5vbFjx7Js2TJWrFhBbGys+fxTTz3Fq6++mmdxi4iIiDxIrq6ulC1bFoAPP/yQ8PBw5s6dS6VKlQBYtWoVJUuWtKhz/felgkSJqojck/3792NnZ0dkZKT5XJEiRQgNDWX//v0ApKSk0KpVK4t6jz32WJ4nqn/l6+vLqVOnANizZw+ZmZkUKVLEosylS5fM3xhmZmYSFxfHqlWryMjI4OrVq1y6dOmGGdXq1avnWcwiIiIi1mRjY8Nrr73GwIEDOXjwII6OjqSnp/Pkk0/md2h3pERVRB5K9vb2Fscmk4nc3FzgWhLq6+vLxo0bb6h3/T7ZQYMG8fXXXzN58mTKli2Ls7Mzbdu2JSsry6K8q6vrA4lfRERExBratWvH4MGDmTNnDoMGDWLAgAHk5uZSp04dzp07R2JiIh4eHnTp0uWm9cuVK8eECRNumIR40JSoisg9KV++PFevXiUpKcm89Pf06dOkpKRQoUIFAEJDQ9m5c6dFvb8fP0gRERGcOHECOzs7AgMDb1omMTGRmJgY84duZmYmaWlpVotRRERExBrs7OyIjY1l0qRJHDlyBG9vbyZMmMDhw4fx9PQkIiKC11577Zb1U1JSOHfunBUjvkaJqojck+DgYFq0aEHPnj2ZM2cO7u7uDBs2jJIlS9KiRQsAXnnlFerWrcuUKVNo3rw533zzDWvWrMFkMlklxqioKGrVqkXLli2ZNGkSISEhHD9+nFWrVtGqVSuqV69OcHAwS5cupXnz5phMJl5//XXzjKyIiIjIw+hWzz0dNmwYw4YNA6Bfv37069fvlm2cPXvW4tgwjLwK755o118RuWfx8fFUq1aNZs2aUatWLQzDYPXq1ebluI8//jizZ89mypQphIeHs3btWgYMGICTk5NV4jOZTKxevZq6devStWtXQkJCeO655/jll18oXrw4AFOmTKFw4cLUrl2b5s2bEx0dTUREhFXiExEREZHbMxn5lSKLyL9Kz549OXDgAFu2bMnvUPLNsZHbrNKPjat1Fss4+LpZpR8AG3cHq/RTuFVZq/QjIiIit6elvyLyQEyePJmGDRvi6urKmjVrmDdvHjNnzszvsPJViRGRdy6UB3IvXLVKP1kZmVbpByD3fNadC+WBo8P+vV+kiIjklVJvPmGVfh61z2xrvW8PCy39FZEHYseOHTRs2JCwsDBmz57NjBkz6NGjBwAVK1a0eND0X18LFy7M58hFREREJL9pRlVEHohFixbd8trq1avJzs6+6bXr95CKiIiIyL+XZlRFxOoCAgIoW7bsTV/u7u75HZ6IiIjII++ZZ57B398fJycnfH196dSpE8ePH79tncuXL/Pyyy9TpEgR3NzcaNOmDSdPnrQok56eztNPP42LiwvFihVj8ODBXL1677clKVEVkfsSExNDy5Ytb1umXr169O/f3yrx3E5aWhomk4ndu3ffdZ27GZ+IiIhIQVSvXr1bPrKmfv36LFq0iJSUFD777DNSU1Np27btbdsbMGAAX3zxBYsXL2bTpk0cP36c1q1bm6/n5OTw9NNPk5WVxbZt25g3bx4JCQmMHDnynmPX0l8ReeCWLl1qfnRNfvLz8yMjI4OiRYvmdygiIiIi+WrAgAHmnwMCAhg2bBgtW7YkOzv7pr+3nTt3jrlz5/Lf//6Xp556Crj2yMLy5cuzfft2atasyVdffcVPP/3EunXrKF68OFWqVGHs2LEMHTqUuLg4HBzufhd/zaiKyAPn5eVVIJb02tra4uPjg52dvqMTERERue7MmTMsXLiQ2rVr33JyITk5mezsbKKiosznypUrh7+/P99++y0A3377LWFhYRZ7jkRHR/Pnn3+yb9++e4pJiarIQ65evXr07duXIUOG4OXlhY+PD3FxcebrZ8+epUePHnh7e+Ph4cFTTz3Fnj17LNoYN24cxYoVw93dnR49ejBs2DCqVKlyT3GMHj3a3EefPn3Iyvrf40T+vvQ3MDCQN954g27duuHu7o6/vz/vv/++RXs//vgjTz31FM7OzhQpUoRevXqRmfm/x6FcX5L7xhtvULx4cTw9PRkzZgxXr15l8ODBeHl5UapUKeLj4811/r70Nycnh+7du1O6dGmcnZ0JDQ1l+vTp9zRuERERkYfV0KFDcXV1pUiRIqSnp/P555/fsuyJEydwcHDA09PT4nzx4sU5ceKEuczfN8a8fny9zN1SoiryCJg3bx6urq4kJSUxadIkxowZw9dffw1Au3btOHXqFGvWrCE5OZmIiAgaNGjAmTNnAFi4cCHjx49n4sSJJCcn4+/vz6xZs+6p//Xr17N//342btzIxx9/zNKlSxk9evRt67z99ttUr16dXbt28dJLL/Hiiy+SkpICwIULF4iOjqZw4cLs3LmTxYsXs27dOmJjYy3a+Oabbzh+/DibN29mypQpjBo1imbNmlG4cGGSkpLo06cPvXv35ujRozeNITc3l1KlSrF48WJ++uknRo4cyWuvvXbbHYtFRERECqo33njD4rF/W7ZsoU+fPhbn0tPTzeUHDx7Mrl27+Oqrr7C1taVz584YhpGPI/gfrX8TeQRUrlyZUaNGARAcHMy7777L+vXrcXZ2ZseOHZw6dQpHR0cAJk+ezPLly1myZAm9evXinXfeoXv37nTt2hWAkSNH8tVXX1nMXt6Jg4MDH374IS4uLlSsWJExY8YwePBgxo4di43Nzb8Pa9q0KS+99BJw7du8qVOnsmHDBkJDQ/nvf//L5cuXmT9/Pq6urgC8++67NG/enIkTJ5q/mfPy8mLGjBnY2NgQGhrKpEmTuHjxIq+99hoAw4cP580332Tr1q0899xzN8Rgb29vkVCXLl2ab7/9lkWLFvHss8/e9fhFRERECoI+ffpY/A7ToUMH2rRpY7HhUYkSJcw/Fy1alKJFixISEkL58uXx8/Nj+/bt1KpV64a2fXx8yMrK4uzZsxazqidPnsTHx8dcZseOHRb1ru8KfL3M3dKMqsgjoHLlyhbHvr6+nDp1ij179pCZmWneQvz668iRI6SmpgKQkpLCY489ZlH/78d3Eh4ejouLi/m4Vq1aZGZm8uuvv95VzCaTCR8fH06dOgXA/v37CQ8PNyepAI8//ji5ubnmWVeAihUrWiTCxYsXJywszHxsa2tLkSJFzO3ezHvvvUe1atXw9vbGzc2N999/3+KbRhEREZGHhZeXl8Vj/5ydnSlWrJjFuVvt1ZGbmwvAlStXbnq9WrVq2Nvbs379evO5lJQU0tPTzYltrVq1+PHHHy1+9/r666/x8PCgQoUK9zQWzaiKPAL+ftO7yWQiNzeXzMxMfH192bhx4w11/n5/gbXdKub7beNe2v3kk08YNGgQb7/9NrVq1cLd3Z233nqLpKSke4pDRERE5GGSlJTEzp07qVOnDoULFyY1NZXXX3+dMmXKmJPOY8eO0aBBA+bPn89jjz1GoUKF6N69OwMHDsTLywsPDw9eeeUVatWqRc2aNQFo1KgRFSpUoFOnTkyaNIkTJ04wYsQIXn75ZfPqvrulRFXkERYREcGJEyews7MjMDDwpmVCQ0PZuXMnnTt3Np/buXPnPfWzZ88eLl26hLOzMwDbt2/Hzc0NPz+/fxR3+fLlSUhI4MKFC+ZZ1cTERPMS37ySmJhI7dq1zUuQAfNMs4iIiMijysXFhaVLlzJq1CguXLiAr68vjRs3ZsSIEeaEMjs7m5SUFC5evGiuN3XqVGxsbGjTpg1XrlwhOjqamTNnmq/b2tqycuVKXnzxRWrVqoWrqytdunRhzJgx9xyjElWRR1hUVBS1atWiZcuWTJo0iZCQEI4fP86qVato1aoV1atX55VXXqFnz55Ur16d2rVr8+mnn/LDDz8QFBR01/1kZWXRvXt3RowYQVpaGqNGjSI2NvaW96feSYcOHRg1ahRdunQhLi6O3377jVdeeYVOnTrdsJPc/QgODmb+/Pl8+eWXlC5dmgULFrBz505Kly6dZ32IiIiI5JebraoDCAsL45tvvrlt3cDAwBs2VnJycuK9997jvffeu2W9gIAAVq9efc+x/p3uURV5hJlMJlavXk3dunXp2rUrISEhPPfcc/zyyy/mhK9Dhw4MHz6cQYMGERERwZEjR4iJicHJyemu+2nQoAHBwcHUrVuX9u3b88wzz1g8Iudeubi48OWXX3LmzBlq1KhB27ZtadCgAe++++4/bvNmevfuTevWrWnfvj2RkZGcPn3aYnZVRERERPKHySgo+w+LSIHRsGFDfHx8WLBgQX6H8kgxsnKs0k/uhatW6Scr4+53hr5fueez7lwoD/yx7Ger9CMi8igr9eYTVunn6LAtVunHWqz1vj0stPRX5F/u4sWLzJ49m+joaGxtbfn4449Zt26d+TmsIiIiIiLWphlVkX+5S5cu0bx5c3bt2sXly5cJDQ1lxIgR5udtubm53bLumjVreOIJffsnIiIiInlLiaqI3NbPP996KWTJkiXNO/2KiIiIiOQVJaoiIiIiIiJSoGjXXxERERERESlQlKiKiIiIiIhIgaJEVURERERERAoUJaoiIiIiIiJSoChRFRERERERkQJFiaqIiIiIiIgUKEpURUREREREpEBRoioiIiIiIiIFihJVERERERERKVCUqIqIiIiIiEiBokRVREREREREChQlqiIiIiIiIlKg2OV3ACIiDzPDMDh//nx+hyEiIiL/Iu7u7phMpvwO44FSoioich/Onz9PoUKF8jsMERER+Rc5d+4cHh4e+R3GA2UyDMPI7yBERB5Wdzuj+ueff+Ln58evv/76yP/HIiJ3ps8EEfmre/1M0IyqiIjclslkuqdfMj08PPRLqYiY6TNBRP5Knwn/o82UREREREREpEBRoioiIiIiIiIFihJVERErcHR0ZNSoUTg6OuZ3KCJSAOgzQUT+Sp8JN9JmSiIiIiIiIlKgaEZVREREREREChQlqiIiIiIiIlKgKFEVERERERGRAkWJqoiIiIiIiBQoSlRFRPLImTNn6NChAx4eHnh6etK9e3cyMzNvW6d3796UKVMGZ2dnvL29adGiBQcOHLAos379emrXro27uzs+Pj4MHTqUq1evPsihiMg9iIuLw2QyWbzKlSt3y/L16tW7obzJZOLpp582lzl58iQxMTGUKFECFxcXGjduzKFDh6wxHBG5R5s3b6Z58+aUKFECk8nE8uXLLa4vXbqURo0aUaRIEUwmE7t3775jm9nZ2YwZM4YyZcrg5OREeHg4a9eutSgTGBh408+Sl19+OQ9Hl3+UqIqI5JEOHTqwb98+vv76a1auXMnmzZvp1avXbetUq1aN+Ph49u/fz5dffolhGDRq1IicnBwA9uzZQ9OmTWncuDG7du3i008/ZcWKFQwbNswaQxKRu1SxYkUyMjLMr61bt96y7NKlSy3K7t27F1tbW9q1aweAYRi0bNmSw4cP8/nnn7Nr1y4CAgKIioriwoUL1hqSiNylCxcuEB4eznvvvXfL63Xq1GHixIl33eaIESOYM2cO77zzDj/99BN9+vShVatW7Nq1y1xm586dFp8lX3/9NYD5s+ShZ4iIyH376aefDMDYuXOn+dyaNWsMk8lkHDt27K7b2bNnjwEYP//8s2EYhjF8+HCjevXqFmVWrFhhODk5GX/++WfeBC8i92XUqFFGeHj4P64/depUw93d3cjMzDQMwzBSUlIMwNi7d6+5TE5OjuHt7W188MEH9xuuiDxAgLFs2bKbXjty5IgBGLt27bpjO76+vsa7775rca5169ZGhw4dblmnX79+RpkyZYzc3Nx7CbnA0oyqiEge+Pbbb/H09KR69ermc1FRUdjY2JCUlHRXbVy4cIH4+HhKly6Nn58fAFeuXMHJycminLOzM5cvXyY5OTnvBiAi9+XQoUOUKFGCoKAgOnToQHp6+l3XnTt3Ls899xyurq7AtX/3gMW/fRsbGxwdHW87Uysij45b/f9/q8+ArKwsPvroI7p164bJZLJGiA+cElURkTxw4sQJihUrZnHOzs4OLy8vTpw4cdu6M2fOxM3NDTc3N9asWcPXX3+Ng4MDANHR0Wzbto2PP/6YnJwcjh07xpgxYwDIyMh4MIMRkXsSGRlJQkICa9euZdasWRw5coQnnniC8+fP37Hujh072Lt3Lz169DCfK1euHP7+/gwfPpw//viDrKwsJk6cyNGjR/XvXuRfIjo6milTpnDo0CFyc3P5+uuvzbcN3Mzy5cs5e/YsMTEx1g30AVKiKiJyG8OGDbvpRgV/ff1986N71aFDB3bt2sWmTZsICQnh2Wef5fLlywA0atSIt956iz59+uDo6EhISAhNmzYFrs2wiEj+a9KkCe3ataNy5cpER0ezevVqzp49y6JFi+5Yd+7cuYSFhfHYY4+Zz9nb27N06VIOHjyIl5cXLi4ubNiwgSZNmujfvci/xPTp0wkODqZcuXI4ODgQGxtL165db/kZMHfuXJo0aUKJEiWsHOmDY5ffAYiIFGSvvvrqHb+dDAoKwsfHh1OnTlmcv3r1KmfOnMHHx+e29QsVKkShQoUIDg6mZs2aFC5cmGXLlvH8888DMHDgQAYMGEBGRgaFCxcmLS2N4cOHExQUdF9jE5EHw9PTk5CQEH7++efblrtw4QKffPKJeZXEX1WrVo3du3dz7tw5srKy8Pb2JjIy0uL2AhF5dHl7e7N8+XIuX77M6dOnKVGiBMOGDbvp//2//PIL69atY+nSpfkQ6YOjRFVE5Da8vb3x9va+Y7latWpx9uxZkpOTqVatGgDffPMNubm5REZG3nV/hmFgGIb5HrXrTCaT+VvSjz/+GD8/PyIiIu5hJCJiLZmZmaSmptKpU6fbllu8eDFXrlyhY8eOtyxTqFAh4No9sN999x1jx47N01hFpGBzcnKiZMmSZGdn89lnn/Hss8/eUCY+Pp5ixYpZPOLqUaBEVUQkD5QvX57GjRvTs2dPZs+eTXZ2NrGxsTz33HPmBPPYsWM0aNCA+fPn89hjj3H48GE+/fRTGjVqhLe3N0ePHuXNN9/E2dnZvLwX4K233qJx48bY2NiwdOlS3nzzTRYtWoStrW1+DVdE/mLQoEE0b96cgIAAjh8/zqhRo7C1tTWviujcuTMlS5ZkwoQJFvXmzp1Ly5YtKVKkyA1tLl68GG9vb/z9/fnxxx/p168fLVu2pFGjRlYZk4jcvczMTIsVFEeOHGH37t14eXnh7+/PmTNnSE9P5/jx4wCkpKQA4OPjY1519ffPiaSkJI4dO0aVKlU4duwYcXFx5ObmMmTIEIu+c3NziY+Pp0uXLtjZPVqp3aM1GhGRfLRw4UJiY2Np0KABNjY2tGnThhkzZpivZ2dnk5KSwsWLF4Fr35Ju2bKFadOm8ccff1C8eHHq1q3Ltm3bLDZmWrNmDePHj+fKlSuEh4fz+eef06RJE6uPT0Ru7ujRozz//POcPn0ab29v6tSpw/bt282rMdLT02+4rywlJYWtW7fy1Vdf3bTNjIwMBg4cyMmTJ/H19aVz5868/vrrD3wsInLvvvvuO+rXr28+HjhwIABdunQhISGBFStW0LVrV/P15557DoBRo0YRFxcH3Pg5cfnyZUaMGMHhw4dxc3OjadOmLFiwAE9PT4u+161bR3p6Ot26dXtAo8s/JsMwjPwOQkREREREROQ6bR0nIiIiIiIiBYoSVRERERERESlQlKiKiIiIiIhIgaJEVURERERERAoUJaoiIiIiIiJSoChRFRERERERkQJFiaqIiIiIiIgUKEpURURERPJZQkICnp6eVukrMDCQadOmWaUvEZF/SomqiIiI/Ott3LgRk8nE2bNn8zuUPGPN5FdEJK8pURURERG5S1lZWfkdgojIv4ISVREREXkk5ObmMmHCBEqXLo2zszPh4eEsWbIEwzCIiooiOjoawzAAOHPmDKVKlWLkyJGkpaVRv359AAoXLozJZCImJgaAevXqERsbS//+/SlatCjR0dEATJkyhbCwMFxdXfHz8+Oll14iMzPzrmNNSEjA398fFxcXWrVqxenTp28o8/nnnxMREYGTkxNBQUGMHj2aq1evmq/fLoaNGzfStWtXzp07h8lkwmQyERcXZ6578eJFunXrhru7O/7+/rz//vvma1lZWcTGxuLr64uTkxMBAQFMmDDhrscmIpIXlKiKiIjII2HChAnMnz+f2bNns2/fPgYMGEDHjh3ZvHkz8+bNY+fOncyYMQOAPn36ULJkSUaOHImfnx+fffYZACkpKWRkZDB9+nRzu/PmzcPBwYHExERmz54NgI2NDTNmzGDfvn3MmzePb775hiFDhtxVnElJSXTv3p3Y2Fh2795N/fr1GTdunEWZLVu20LlzZ/r168dPP/3EnDlzSEhIYPz48eYyt4uhdu3aTJs2DQ8PDzIyMsjIyGDQoEHmum+//TbVq1dn165dvPTSS7z44oukpKQAMGPGDFasWMGiRYtISUlh4cKFBAYG3uOfhojIfTJEREREHnKXL182XFxcjG3btlmc7969u/H8888bhmEYixYtMpycnIxhw4YZrq6uxsGDB83lNmzYYADGH3/8YVH/ySefNKpWrXrH/hcvXmwUKVLkrmJ9/vnnjaZNm1qca9++vVGoUCHzcYMGDYw33njDosyCBQsMX1/fu44hPj7eos3rAgICjI4dO5qPc3NzjWLFihmzZs0yDMMwXnnlFeOpp54ycnNz72o8IiIPgl1+J8oiIiIi9+vnn3/m4sWLNGzY0OJ8VlYWVatWBaBdu3YsW7aMN998k1mzZhEcHHxXbVerVu2Gc+vWrWPChAkcOHCAP//8k6tXr3L58mUuXryIi4vLbdvbv38/rVq1sjhXq1Yt1q5daz7es2cPiYmJFjOoOTk5Fn3cTwyVK1c2/2wymfDx8eHUqVMAxMTE0LBhQ0JDQ2ncuDHNmjWjUaNGt21PRCSvKVEVERGRh971ezNXrVpFyZIlLa45OjoC1+7LTE5OxtbWlkOHDt11266urhbHaWlpNGvWjBdffJHx48fj5eXF1q1b6d69O1lZWXdMEu9GZmYmo0ePpnXr1jdcc3Jyuu8Y7O3tLY5NJhO5ubkAREREcOTIEdasWcO6det49tlniYqKYsmSJfc9LhGRu6VEVURERB56FSpUwNHRkfT0dJ588smblnn11VexsbFhzZo1NG3alKeffpqnnnoKAAcHB+DarOWdJCcnk5uby9tvv42NzbXtPhYtWnTXsZYvX56kpCSLc9u3b7c4joiIICUlhbJly/7jGBwcHO5qPDfj4eFB+/btad++PW3btqVx48acOXMGLy+vf9SeiMi9UqIqIiIiDz13d3cGDRrEgAEDyM3NpU6dOpw7d47ExEQ8PDwoWrQoH374Id9++y0REREMHjyYLl268MMPP1C4cGECAgIwmUysXLmSpk2b4uzsjJub2037Klu2LNnZ2bzzzjs0b97cYpOlu9G3b18ef/xxJk+eTIsWLfjyyy8tlv0CjBw5kmbNmuHv70/btm2xsbFhz5497N27l3Hjxt1VDIGBgWRmZrJ+/XrCw8NxcXG5q9neKVOm4OvrS9WqVbGxsWHx4sX4+PjomawiYlXa9VdEREQeCWPHjuX1119nwoQJlC9fnsaNG7Nq1SoCAwPp3r07cXFxREREADB69GiKFy9Onz59AChZsiSjR49m2LBhFC9enNjY2Fv2Ex4ezpQpU5g4cSKVKlVi4cKF9/T4lpo1a/LBBx8wffp0wsPD+eqrrxgxYoRFmejoaFauXMlXX31FjRo1qFmzJlOnTiUgIOCuY6hduzZ9+vShffv2eHt7M2nSpLuKz93dnUmTJlG9enVq1KhBWloaq1evNs/ciohYg8kw/v8DxUREREREREQKAH01JiIiIiIiIgWKElURERGRPNSkSRPc3Nxu+nrjjTfyOzwRkYeClv6KiIiI5KFjx45x6dKlm17z8vLSzrkiIndBiaqIiIiIiIgUKFr6KyIiIiIiIgWKElUREREREREpUJSoioiIiIiISIGiRFVEREREREQKFCWqIiIiIiIiUqAoURUREREREZECRYmqiIiIiIiIFChKVEVERERERKRA+X+1XfR2PbXjCwAAAABJRU5ErkJggg==", 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