From eacef8109a35180e181aec27bb770fbcc77df863 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Pawe=C5=82=20Sk=C3=B3rzewski?= Date: Thu, 24 Nov 2022 07:22:33 +0100 Subject: [PATCH] =?UTF-8?q?Wyk=C5=82ad=206.=20Problem=20nadmiernego=20dopa?= =?UTF-8?q?sowania?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- lab/04_Reprezentacja_danych.ipynb | 24 +- lab/05_Ewaluacja.ipynb | 4 +- wyk/05_Metody_ewaluacji.ipynb | 67 +- wyk/06_Problem_nadmiernego_dopasowania.ipynb | 1832 ++++++++ wyk/bias2.png | Bin 0 -> 125272 bytes wyk/curves.jpg | Bin 0 -> 96290 bytes wyk/data-metrics.tsv | 50 + wyk/data_flats_with_outliers.tsv | 4186 ++++++++++++++++++ wyk/ex2data2.txt | 118 + wyk/fit.png | Bin 0 -> 141779 bytes wyk/learning-curves.png | Bin 0 -> 6018 bytes wyk/polynomial_logistic.tsv | 100 + 12 files changed, 6330 insertions(+), 51 deletions(-) create mode 100644 wyk/06_Problem_nadmiernego_dopasowania.ipynb create mode 100644 wyk/bias2.png create mode 100644 wyk/curves.jpg create mode 100644 wyk/data-metrics.tsv create mode 100644 wyk/data_flats_with_outliers.tsv create mode 100644 wyk/ex2data2.txt create mode 100644 wyk/fit.png create mode 100644 wyk/learning-curves.png create mode 100644 wyk/polynomial_logistic.tsv diff --git a/lab/04_Reprezentacja_danych.ipynb b/lab/04_Reprezentacja_danych.ipynb index 0491bea..97cd2ca 100644 --- a/lab/04_Reprezentacja_danych.ipynb +++ b/lab/04_Reprezentacja_danych.ipynb @@ -199,18 +199,6 @@ "Jak widać powyżej, tutaj oprócz liczb pojawiają się pewne tekstowe wartości specjalne, takie jak `parter`, `poddasze` czy `niski parter`." ] }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Takie wartości należy zamienić na liczby. Jak?\n", - "* Wydaje się, że `parter` czy `niski parter` można z powodzeniem potraktować jako piętro „zerowe” i zamienić na `0`.\n", - "* Z poddaszem sytuacja nie jest już tak oczywista. Czy mają Państwo jakieś propozycje?\n", - " * Może zamienić `poddasze` na wartość NaN (zobacz poniżej)?\n", - " * Może wykorzystać w tym celu wartość z sąsiedniej kolumny *Liczba pięter w budynku*?\n", - " * Może w ogóle odrzucić przykłady, w których występuje ta wartość? (jeżeli tych przykładów jest bardzo mało)" - ] - }, { "cell_type": "code", "execution_count": 8, @@ -251,6 +239,18 @@ "alldata[\"Piętro\"].value_counts()\n" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Takie wartości należy zamienić na liczby. Jak?\n", + "* Wydaje się, że `parter` czy `niski parter` można z powodzeniem potraktować jako piętro „zerowe” i zamienić na `0`.\n", + "* Z poddaszem sytuacja nie jest już tak oczywista. Czy mają Państwo jakieś propozycje?\n", + " * Może zamienić `poddasze` na wartość NaN (zobacz poniżej)?\n", + " * Może wykorzystać w tym celu wartość z sąsiedniej kolumny *Liczba pięter w budynku*?\n", + " * Skoro `poddasze` pojawia się tylko w nielicznych przykładach, może w ogóle odrzucić te przykłady?" + ] + }, { "cell_type": "markdown", "metadata": {}, diff --git a/lab/05_Ewaluacja.ipynb b/lab/05_Ewaluacja.ipynb index 6fec839..783a83f 100644 --- a/lab/05_Ewaluacja.ipynb +++ b/lab/05_Ewaluacja.ipynb @@ -98,7 +98,6 @@ "data = preprocess(data) # wstępne przetworzenie danych\n", "\n", "# Podział danych na zbiory uczący i testowy\n", - "split_point = int(0.8 * len(data))\n", "data_train, data_test = train_test_split(data, test_size=0.2)\n", "\n", "# Uczenie modelu\n", @@ -252,7 +251,6 @@ ")\n", "\n", "# Podział danych na zbiór uczący i zbiór testowy\n", - "split_point = int(0.8 * len(data_iris))\n", "data_train, data_test = train_test_split(data_iris, test_size=0.2)\n", "\n", "# Uczenie modelu\n", @@ -283,7 +281,7 @@ "metadata": { "celltoolbar": "Slideshow", "kernelspec": { - "display_name": "Python 3.10.6 64-bit", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, diff --git a/wyk/05_Metody_ewaluacji.ipynb b/wyk/05_Metody_ewaluacji.ipynb index 80bce1d..fd75c2f 100644 --- a/wyk/05_Metody_ewaluacji.ipynb +++ b/wyk/05_Metody_ewaluacji.ipynb @@ -67,7 +67,7 @@ } }, "source": [ - "Czasami potrzebujemy dobrać parametry modelu, np. $\\alpha$ – który zbiór wykorzystać do tego celu?" + "Czasami potrzebujemy dobrać (hiper-)parametry modelu, np. $\\alpha$ – który zbiór wykorzystać do tego celu?" ] }, { @@ -306,7 +306,7 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 7, "metadata": { "slideshow": { "slide_type": "notes" @@ -328,7 +328,7 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 8, "metadata": { "slideshow": { "slide_type": "notes" @@ -347,7 +347,7 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 9, "metadata": { "slideshow": { "slide_type": "notes" @@ -419,7 +419,7 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 12, "metadata": { "slideshow": { "slide_type": "notes" @@ -443,7 +443,7 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 13, "metadata": { "slideshow": { "slide_type": "subslide" @@ -452,14 +452,12 @@ "outputs": [ { "data": { - "image/png": "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", + "image/png": "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\n", "text/plain": [ - "
" + "
" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -469,7 +467,7 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 14, "metadata": { "slideshow": { "slide_type": "notes" @@ -516,7 +514,7 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 15, "metadata": { "slideshow": { "slide_type": "notes" @@ -544,7 +542,7 @@ }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 16, "metadata": { "slideshow": { "slide_type": "subslide" @@ -574,7 +572,7 @@ }, { "cell_type": "code", - "execution_count": 42, + "execution_count": 17, "metadata": { "slideshow": { "slide_type": "notes" @@ -596,7 +594,7 @@ }, { "cell_type": "code", - "execution_count": 43, + "execution_count": 18, "metadata": { "slideshow": { "slide_type": "subslide" @@ -610,7 +608,7 @@ }, { "cell_type": "code", - "execution_count": 44, + "execution_count": 19, "metadata": { "slideshow": { "slide_type": "notes" @@ -630,8 +628,9 @@ }, { "cell_type": "code", - "execution_count": 45, + "execution_count": 21, "metadata": { + "scrolled": true, "slideshow": { "slide_type": "subslide" } @@ -640,7 +639,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "165999bd4b234b55b10cdc34e64e8244", + "model_id": "99f3351da36340ca8c6d117c625f3ed4", "version_major": 2, "version_minor": 0 }, @@ -657,7 +656,7 @@ "" ] }, - "execution_count": 45, + "execution_count": 21, "metadata": {}, "output_type": "execute_result" } @@ -726,7 +725,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 22, "metadata": { "slideshow": { "slide_type": "skip" @@ -804,7 +803,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 23, "metadata": { "slideshow": { "slide_type": "subslide" @@ -859,7 +858,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 24, "metadata": { "slideshow": { "slide_type": "subslide" @@ -904,7 +903,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 25, "metadata": { "slideshow": { "slide_type": "subslide" @@ -949,7 +948,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 26, "metadata": { "slideshow": { "slide_type": "subslide" @@ -1054,7 +1053,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 27, "metadata": { "slideshow": { "slide_type": "notes" @@ -1163,14 +1162,12 @@ "outputs": [ { "data": { - "image/png": "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", + "image/png": "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\n", "text/plain": [ - "
" + "
" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -1246,14 +1243,12 @@ "outputs": [ { "data": { - "image/png": "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", + "image/png": "iVBORw0KGgoAAAANSUhEUgAAA10AAAH0CAYAAADG90dQAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8o6BhiAAAACXBIWXMAAA9hAAAPYQGoP6dpAAA+HElEQVR4nO3de3TU9Z3/8ddMJpkEkwkikosNKmLBCnIRwQACVhSBw3Lpbi1yRFmLi4ILhlZlf66stbspuwp0Wy66PUrt1movAq3XhSBIEEEusWAtR6kKYhJQNENCCEnm+/vjS4ZMkplMkvnMJXk+zpmTzHe+38knYQjz4vN5vz8Oy7IsAQAAAACMcMZ6AAAAAADQmRG6AAAAAMAgQhcAAAAAGEToAgAAAACDCF0AAAAAYBChCwAAAAAMInQBAAAAgEGELgAAAAAwiNAFAAAAAAYRugAAAADAoIQJXYWFhbruuuuUkZGhXr16adq0aTp06FCr1/3ud79T//79lZqaqoEDB+rVV1+NwmgBAAAAwJYwoWvbtm2aP3++3nnnHW3atEm1tbW65ZZbVFVVFfSat99+WzNnztTdd9+t/fv3a9q0aZo2bZoOHjwYxZEDAAAA6MoclmVZsR5Ee5w4cUK9evXStm3bNGbMmBbPue2221RVVaWXX37Zf+z666/X4MGDtXbt2mgNFQAAAEAX5or1ANqroqJCktSjR4+g5+zcuVMFBQUBxyZMmKANGzYEvaampkY1NTX++z6fTydPntRFF10kh8PRsUEDAAAAiGuWZenUqVPKzc2V0xmZhYEJGbp8Pp8WLVqkUaNGacCAAUHPKysrU1ZWVsCxrKwslZWVBb2msLBQjz32WMTGCgAAACDxHD16VN/4xjci8lwJGbrmz5+vgwcPqri4OOLPvWTJkoDZsYqKCvXu3VtHjx6Vx+OJ+NcDAAAAED+8Xq/y8vKUkZERsedMuNC1YMECvfzyy3rrrbdaTZ7Z2dkqLy8POFZeXq7s7Oyg17jdbrnd7mbHPR4PoQsAAADoIiJZWpQw3Qsty9KCBQu0fv16bdmyRZdffnmr1+Tn56uoqCjg2KZNm5Sfn29qmAAAAAAQIGFmuubPn6/nn39eGzduVEZGhr8uKzMzU2lpaZKk2bNn65JLLlFhYaEkaeHChRo7dqyefPJJTZ48WS+88IL27Nmjp59+OmbfBwAAAICuJWFmutasWaOKigqNGzdOOTk5/tuLL77oP+fIkSMqLS313x85cqSef/55Pf300xo0aJB+//vfa8OGDSGbbwAAAABAJCXsPl3R4vV6lZmZqYqKCmq6AAAAgE7OxPv/hJnpAgAAAIBEROgCAAAAAIMIXQAAAABgEKELAAAAAAwidAEAAACAQYQuAAAAADCI0AUAAAAABhG6AAAAAMAgQhcAAAAAGEToAgAAAACDCF0AAAAAYBChCwAAAAAMInQBAAAAgEGELgAAAAAwiNAFAAAAAAYRugAAAADAIEIXAAAAABhE6AIAAAAAgwhdAAAAAGAQoQsAAAAADCJ0AQAAAIBBhC4AAAAAMIjQBQAAAAAGEboAAAAAwCBCFwAAAAAYROgCAAAAAIMIXQAAAABgEKELAAAAAAwidAEAAACAQYQuAAAAADCI0AUAAAAABhG6AAAAAMAgQhcAAAAAGEToAgAAAACDCF0AAAAAYBChCwAAAAAMInQBAAAAgEGELgAAAAAwiNAFAAAAAAYRugAAAADAIEIXAAAAABhE6AIAAAAAgwhdAAAAAGAQoQsAAAAADCJ0AQAAAIBBhC4AAAAAMIjQBQAAAAAGEboAAAAAwCBCFwAAAAAYROgCAAAAAIMIXQAAAABgEKELAAAAAAwidAEAAACAQYQuAAAAADCI0AUAAAAABhG6AAAAAMAgQhcAAAAAGEToAgAAAACDCF0AAAAAYBChCwAAAAAMInQBAAAAgEGELgAAAAAwiNAFAAAAAAYRugAAAADAIEIXAAAAABhE6AIAAAAAgwhdAAAAAGAQoQsAAAAADEqo0PXWW29pypQpys3NlcPh0IYNG0Kev3XrVjkcjma3srKy6AwYAAAAQJeXUKGrqqpKgwYN0qpVq9p03aFDh1RaWuq/9erVy9AIAQAAACCQK9YDaIuJEydq4sSJbb6uV69e6t69e1jn1tTUqKamxn/f6/W2+esBAAAAQIOEmulqr8GDBysnJ0c333yzduzYEfLcwsJCZWZm+m95eXlRGiUAAACAzqhTh66cnBytXbtWf/jDH/SHP/xBeXl5GjdunPbt2xf0miVLlqiiosJ/O3r0aBRHDAAAAKCzSajlhW3Vr18/9evXz39/5MiROnz4sFasWKFf/epXLV7jdrvldrujNUQAAAAAnVynnulqyfDhw/XRRx/FehgAAAAAuoguF7pKSkqUk5MT62EAAAAA6CISanlhZWVlwCzVxx9/rJKSEvXo0UO9e/fWkiVLdOzYMT333HOSpJUrV+ryyy/X1VdfrTNnzugXv/iFtmzZov/7v/+L1bcAAAAAoItJqNC1Z88e3Xjjjf77BQUFkqQ777xT69atU2lpqY4cOeJ//OzZs1q8eLGOHTumbt266ZprrtHmzZsDngMAAAAATHJYlmXFehDxzOv1KjMzUxUVFfJ4PLEeDgAAAACDTLz/73I1XQAAAAAQTYQuAAAAADCI0AUAAAAABhG6AAAAAMAgQhcAAAAAGEToAgAAAACDCF0AAAAAYBChCwAAAAAMInQBAAAAgEGELgAAAAAwiNAFAAAAAAYRugAAAADAIEIXAAAAABhE6AIAAAAAgwhdAAAAAGAQoQsAAAAADCJ0AQAAAIBBhC4AAAAAMIjQBQAAAAAGEboAAAAAwCBCFwAAAAAYROgCAAAAAIMIXQAAAABgEKELAAAAAAwidAEAAACAQYQuAAAAADCI0AUAAAAABhG6AAAAAMAgQhcAAAAAGEToAgAAAACDCF0AAAAAYBChCwAAAAAMInQBAAAAgEGELgAAAAAwiNAFAAAAAAYRugAAAADAIEIXAAAAABhE6AIAAAAAgwhdAAAAAGAQoQsAAAAADCJ0AQAAAIBBhC4AAAAAMIjQBQAAAAAGEboAAAAAwCBCFwAAAAAYROgCAAAAAIMIXQAAAABgEKELAAAAAAwidAEAAACAQYQuAAAAADCI0AUAAAAABhG6AAAAAMAgQhcAAAAAGEToAgAAAACDCF0AAAAAYBChCwAAAAAMInQBAAAAgEGELgAAAAAwiNAFAAAAAAYRugAAAADAIEIXAAAAABhE6AIAAAAAgwhdAAAAAGAQoQsAAAAADCJ0AQAAAIBBhC4AQHRVV0vl5fZHAAC6AEIXACA6ioulGTOk9HQpO9v+OGOGtGNHrEcGAIBRCRW63nrrLU2ZMkW5ublyOBzasGFDq9ds3bpVQ4cOldvtVt++fbVu3Trj4wQANLFmjTRmjPSnP0k+n33M57Pv33CDtHZtbMcHAIBBCRW6qqqqNGjQIK1atSqs8z/++GNNnjxZN954o0pKSrRo0SJ9//vf1xtvvGF4pAAAv+Jiaf58ybKkurrAx+rq7OP33ceMFwCg03LFegBtMXHiRE2cODHs89euXavLL79cTz75pCTpqquuUnFxsVasWKEJEyaYGiYAoLHly6WkpOaBq7GkJGnFCmnUqOiNCwCAKEmoma622rlzp8aPHx9wbMKECdq5c2fQa2pqauT1egNuAIB2qq6WNm4MHbgk+/H162muAQDolDp16CorK1NWVlbAsaysLHm9XlUH+Ye9sLBQmZmZ/lteXl40hgoAnZPXe76GqzU+n30+AACdTKcOXe2xZMkSVVRU+G9Hjx6N9ZAAIHF5PJIzzH9qnE77fAAAOplOHbqys7NVXl4ecKy8vFwej0dpaWktXuN2u+XxeAJuAIB2SkuTpk6VXK2UELtc0vTp9vkAAHQynTp05efnq6ioKODYpk2blJ+fH6MRAUAXVFAg1deHPqe+XnrggeiMBwCAKEuo0FVZWamSkhKVlJRIslvCl5SU6MiRI5LspYGzZ8/2nz9v3jz97W9/04MPPqi//vWvWr16tX7729/qAf5hB4DoGT1aWr1acjiaz3i5XPbx1avpXAgA6LQSKnTt2bNHQ4YM0ZAhQyRJBQUFGjJkiB599FFJUmlpqT+ASdLll1+uV155RZs2bdKgQYP05JNP6he/+AXt4gEg2ubNk7Zvt5caNtR4OZ32/e3b7ccBAOikHJZlWbEeRDzzer3KzMxURUUF9V0AEAnV1XaXQo+HGi4AQNwx8f4/oTZHBgB0AmlphC0AQJeSUMsLAQAAACDRELoAAAAAwCBCFwAAAAAYROgCAAAAAIMIXQAAAABgEKELAAAAAAwidAEAAACAQYQuAAAAADCI0AUAAAAABhG6AAAAAMAgQhcAAAAAGEToAgAAAACDCF0AAAAAYBChCwAAAAAMInQBAAAAgEGELgAAAAAwiNAFAAAAAAYRugAAAADAIEIXAAAAABhE6AIAAAAAgwhdAAAAAGAQoQsAAAAADCJ0AQAAAIBBhC4AAAAAMIjQBQAAAAAGEboAAAAAwCBCFwAAAAAYROgCAAAAAIMIXQAAAABgEKELAAAAAAwidAEAAACAQYQuAAAAADCI0AUAQLiqq6XycvsjAABhInQBANCa4mJpxgwpPV3KzrY/zpgh7dgR65EBABIAoQsAgFDWrJHGjJH+9CfJ57OP+Xz2/RtukNauje34AABxj9AFAEAwxcXS/PmSZUl1dYGP1dXZx++7jxkvAEBIhC4AAIJZvlxKSgp9TlKStGJFdMYDAEhIro5cfPr0aR05ckRnz54NOH7NNdd0aFAAAMRcdbW0ceP5JYXB1NVJ69fb56elRWdsAICE0q7QdeLECc2ZM0evvfZai4/X19d3aFAAAMSc19t64Grg89nnE7oAAC1o1/LCRYsW6euvv9auXbuUlpam119/Xb/85S915ZVX6o9//GOkxwgAQPR5PJIzzH8mnU77fAAAWtCuma4tW7Zo48aNGjZsmJxOpy699FLdfPPN8ng8Kiws1OTJkyM9TgAAoistTZo61e5S2LSJRmMul30es1wAgCDaNdNVVVWlXr16SZIuvPBCnThxQpI0cOBA7du3L3KjAwAglgoKpNaWzNfXSw88EJ3xAAASUrtCV79+/XTo0CFJ0qBBg/TUU0/p2LFjWrt2rXJyciI6QAAAYmb0aGn1asnhsGe0GnO57OOrV0ujRsVmfACAhNCu0LVw4UKVlpZKkpYuXarXXntNvXv31n//93/rP/7jPyI6QAAAYmrePGn7dnsJYUONl9Np39++3X4cAIAQHJZlWR19ktOnT+uvf/2revfurZ49e0ZiXHHD6/UqMzNTFRUV8lAkDQBdW3W13aXQ46GGCwA6KRPv/zu0T1eDbt26aejQoZF4KgAA4ldaGmELANBm7Qpd9fX1WrdunYqKinT8+HH5muxjsmXLlogMDgAAdCHMJALopNoVuhYuXKh169Zp8uTJGjBggBwOR6THBQAAuoriYmn5cmnjRnuj6YaaucWLaVICoFNoV01Xz5499dxzz2nSpEkmxhRXqOkCAMCgNWuk+fOlpKTA/dBcLrsd/+rVNCsBEFUm3v+3q3thSkqK+vbtG5EBAACALqq42A5cltV8A+q6Ovv4ffdJO3bEZnwAECHtCl2LFy/WT3/6U0Wg8SEAAOiqli+3Z7hCSUqSVqyIzngAwJB2LS+cPn263nzzTfXo0UNXX321kpOTAx5/6aWXIjbAWGN5IQAABlRXS+npdg1Xa5xOqbKS5hoAoiJuWsZ3795d06dPj8gAAABAF+T1hhe4JPs8r5fQBSBhtSt0Pfvss5EeBwAA6Eo8HnsGK9yZLlabAEhg7arpkqS6ujpt3rxZTz31lE6dOiVJ+vzzz1VZWRmxwQEAgE4qLc1uC+9q5f9/XS5p+nRmuQAktHbNdH366ae69dZbdeTIEdXU1Ojmm29WRkaGli1bppqaGq1duzbS4wQAAJ1NQYG0YUPoc+rrpQceiMpwAMCUds10LVy4UMOGDdNXX32ltEb/8zR9+nQVFRVFbHAAAKATGz3a3ofL4Wg+4+Vy2cdXr2aDZAAJr12ha/v27XrkkUeUkpIScPyyyy7TsWPHIjIwAADQBcybJ23fbi81dJ57W+J02ve3b2djZACdQruWF/p8PtXX1zc7/tlnnykjI6PDgwIAAF3IqFH2rbra7lLo8VDDBaBTaddM1y233KKVK1f67zscDlVWVmrp0qWaNGlSpMYGAAC6krQ0KSuLwAWg02nX5sifffaZJkyYIMuy9OGHH2rYsGH68MMPddFFF2n79u3q1auXibHGBJsjAwAAAF2Hiff/7Qpdkt0y/sUXX9R7772nyspKDR06VLNmzQporNEZELoAAACArsPE+/921XQVFhYqKytL//iP/6hZs2b5jz/zzDM6ceKEHnrooYgMDgAAdDHUdQHohNpV0/XUU0+pf//+zY5fffXV7NEFAADarrhYmjFDSk+XsrPtjzNmSDt2xHpkANBh7QpdZWVlysnJaXb84osvVmlpaYcHBQAAupA1a6QxY6Q//Uny+exjPp99/4YbJP5DF0CCa1foysvL044W/udpx44dys3N7fCgAABAF1FcLM2fL1mWVFcX+FhdnX38vvuY8QKQ0NpV0zV37lwtWrRItbW1+va3vy1JKioq0oMPPqjFixdHdIAAAKATW75cSkpqHrgaS0qSVqyw9/ICgATUrpmuH/7wh7r77rt13333qU+fPurTp4/uv/9+/fM//7OWLFkS6TEGWLVqlS677DKlpqZqxIgR2r17d9Bz161bJ4fDEXBLTU01Oj4AQBRUV0vl5fZHJK7qamnjxtCBS7IfX7+eP28ACatdocvhcGjZsmU6ceKE3nnnHb333ns6efKkHn300UiPL8CLL76ogoICLV26VPv27dOgQYM0YcIEHT9+POg1Ho9HpaWl/tunn35qdIwAAINottC5eL3na7ha4/PZ5wNAAmpX6GqQnp6u6667TgMGDJDb7Y7UmIJavny55s6dqzlz5uhb3/qW1q5dq27duumZZ54Jeo3D4VB2drb/lpWVZXycAAAD4qHZwsmT0sGD9kd0nMcjOcN8K+J02ucDQALqUOiKprNnz2rv3r0aP368/5jT6dT48eO1c+fOoNdVVlbq0ksvVV5enqZOnar3338/5NepqamR1+sNuAEAYizWzRZWr5Zyc6WLLpIGDrQ/5ubaQRDtl5YmhfufodnZ7NsFIGElTOj64osvVF9f32ymKisrS2VlZS1e069fPz3zzDPauHGj/vd//1c+n08jR47UZ599FvTrFBYWKjMz03/Ly8uL6PcBAGiHhmYLoTQ0W4i0mTPtwNd0S5TSUjvo3X575L9mV1FdLQX5N7yZ0lJqugAkrIQJXe2Rn5+v2bNna/DgwRo7dqxeeuklXXzxxXrqqaeCXrNkyRJVVFT4b0ePHo3iiAEAzcSy2cLq1dILL4Q+5ze/Ycarvbxee5YyHJZFTReAhJUwoatnz55KSkpSeXl5wPHy8nJlZ2eH9RzJyckaMmSIPvroo6DnuN1ueTyegBsAIIZi2Wzhxz+O7HkIRE0XgC6iXft0xUJKSoquvfZaFRUVadq0aZIkn8+noqIiLViwIKznqK+v14EDBzRp0iSDIwUAdFh1tR2ePJ7zb8zDCV6RfGN+8mTzJYXBfP65fX6PHpH52l1FWpo0dardDCXUTKbLZZ9HTReADrIsS2dqfTp1plbeM7WqqK6T90ytTp2pk7faPnb8y68j/nUTJnRJUkFBge68804NGzZMw4cP18qVK1VVVaU5c+ZIkmbPnq1LLrlEhYWFkqQf/ehHuv7669W3b199/fXX+q//+i99+umn+v73vx/LbwMAEExxsV2/tXGjHbKcTvvN9ujR0ttvR/eN+eeft/18QlfbFRRIGzaEPqe+XnrggagMB0B8syxLlTV1dkg6UytvtR2WTtWc/9wfohoebxKqautDL2v21ZyO+LgTKnTddtttOnHihB599FGVlZVp8ODBev311/3NNY4cOSJno2UKX331lebOnauysjJdeOGFuvbaa/X222/rW9/6Vqy+BQBIHI1nm6Ixw7Bmjd2wIimpeUv41uq5pMi/Mc/NNXt+LET7zzQco0fbtXP33Wf/2Tf+s3a57D/X1aulUaNiN0YAEVPvs1R5LhBVnAtB3uq6czNPTUJT48drzp/nC7MUNJ44LCvcCtauyev1KjMzUxUVFdR3Aegags02LV5s7o1vcbG9B1c4/yS5XMHfmM+bF9lx5eaGt8QwN1c6diyyXzuSYvFn2lY7dtjdJ9evPz/G6dPtIB0vYwSgs3W+1gNS0MfrVFkTxn+iRZjTIWWkJsuT5pInNVkZqfZHT1ry+ftpyfKc++isrdYtQ/pE9P0/oasVhC4AXUrj2aZoBRtJmjEjvLqeUaOknj2j98Z89Wr75xHOeffeG/mvHwlt+TONh5mweBgD0EmFU8/U2qzTmdowGxtFUHKSo1FIcgUEKE9asjLc50KTP1QFPn5BSpIcDkfYX8/E+39CVysIXQC6jHBnm159VZo4MXJft7paSk8Pv1FGZaX9ebTemN9+u90WPpiZM6Xnnzc7hvYK58/U4ZB+/nNp8+b4ngkDIMuyVHW2voWA1Li2KTBAtbWeyYTUZOf5gBQwy9RCgDr3eGajY26Xs02hqaMIXTFA6ALQZYQz29QgJ0f613+NzOxOebkU5tYfkuzNdM/V8koKPTMSqVmTNWvstvCNm2vk5kqPPBK/M1xSeH+mDZ0ho7lsE+iiWqpnarz0zlvduAFE84YQsapnSne7/Evvwg1NjR9PcSXMLlWSCF0xQegC0CW0ZbapsUjM8rRnpistLXSdkmWZqWE6edIOXrm58d+psL1/pk05HPYs2NVXs+QPXV6i1zNluFsPSA2PZ56rd0pPdSnJGb1ZpnhA6IoBQheAhNOe2Z22zjY11t56psbjnDUr/L2afv/70HVKDfe7+sxNR/5MG3M4zi9PZNkhEphlWaqp8/nDUEUrAcmedQp8PNb1TOdDUgsNIfyhKvDxC1Jccnax0NRRhK4YIHQBSBgd6VDXkVmRtnbua2mco0dLb70V+jqHQ9q+3Q4A4XY6DPU8nT00RGqmq6muFl4RN9pTz9Q0NMWynul8h7wQAerc45mNGkKkJke3nglm3v8n1D5dAIAgQu1xtWGD9JOfSPffH3zma+9eu04qnPboTX3+ub3sLpzldsHG+fbb588JNUM1apRdp9R0hqstkpLs1uSdPXSlpdmhO9w6vXA1PNd990kDB8b3zzGRloN2AU3rmQJrl84FpOr4rWcKXrvUcse8jFSXMlJdcruSoj9oxB1mulrBTBeAuBdu10GHQ5o2rfnMV0MQcjjaPyty4IA0YEBkxjl2rD0T1VJL+EjN3jSuDevM2rL/WVs1Xu4Zb1avthufNP5PhEg2f+mimtYztdjwIWhDiNjUMzkcarIML3hA8jSpZ8pIdSnd7ZIrKbGaQKDjmOkCADS3fHl4Mz+WZc96rF8vLVtmz3zt3WsHLsvq2Bvzo0dbD13hjNPlsvfhqqxsuS7N643Mcjmfz36uzh66Ro+2A8h99wWvf2voXthWdXX2a6m6Or5+jjNnSi+80Px4aan9c9i+PX5b/BvUtJ7J20pAipd6JpfT4Q9A55fmtdIQIu3crBT1TIgjzHS1gpkuAHEhWHOMjsz8OJ32ksLjx+3lex3VEORaegPe3g6FHXme9n6NzmjHDntJZcOm0pI0ZYp0663SggUdC9xNW/jHQsPfj9/8xp4VbU08b2YdRNN6prZ0zGsIVWfrox+aUpOd/gDUEJqaBagmj2f6j1HPhNigkUYMELoAxFRrzTEi1aEuUoI17+joXlyNtWU/sZbE87I4k1avlh5/3P7ZNsjJkcaNs2eG2lMnF+vw2vTvR7ja2vwlAtpaz+R/PA7qmUI1fPA0CkhNH6eeCYmK0BUDhC4AMROqLXp9vbRypfR3fyddcUXkO9R1REvd7SI10yV1vE6pq3QvbCzYkrsG48dLmZmBM2GtiXV4Dfb3I1xfftmm5hqN65mCBqQQAepUjOqZMtzhBaTGxxo+p54JXRWhKwYIXQBioq3BovFeSvGiabgJZ4Yq3Dfya9eGrlNq+nnD/a7Y6nz1ajuchHPeXXfZy/QOHpRuvjn0a6ql8NqePeLao41/PyxJNa4Ued0XyJt6gf3x2V/Jm3VJiNAUuDSvujYCS3DbyOV0+DetDViaFzQ0Nb5PPRPQXoSuGCB0AYiJji6hiwcNAerpp+223a+9Jj34YOhr2jIL1bROqXGnQyn4Y11phkuyl9KFsxVA0yV3oYJt0/DakT3iwtC4nunUmTp5Cx6Ud2+JvK5UnWocpFLT5XVfoFPubvK60/3HT7kv0FlXcofH0VZulzMgNAWvbWoUnBp9Tj0TEBuErhggdAGIOlOb2sYzp9OetWjPLFSo2ZVozbzEq5MnpYsuCv/8pkvuQgXbhjDV2jLY1atVf88/+euZvEGX5tWdawDR6PFGDSFiUc90QUpSyIYPoRpCUM8EJC5axgNAVxCptuiJxOczs+wvLa1rhq0Gn3/e9vMbh65Ro6RRo3S2skqnTnylUylp8lpJdig6UKpTBz6Qd90meUfPsmeazs0qnZ95ukCnDl2gU//yamS/rzA4LJ8yak7Lc6ZSnpqqgM89I4crY/i1gTNM1DMBMIjQBQDR0DDjkpws1daGnnnxeNq/d1KicrmkoqLgbbxbmrEyvKStU8jNDaxnarIU71RKt3P37aV4p/ZWyvvu7mYNIULWM914t5GhN61n8tcyJTvkeXq1Ms5UnQ9RZ6qUUVPl/9xTU6kLzp6RUy1Mj82cKf2/mUbGDADBsLywFSwvBNAhDcFgw4bAov/WAkJnqOlqq5a6FgYLVn36SE8+2byBSMP9NWs6TbOMZvVM/iYPLe/F1KwhREWVzibFoJ6ptsYOQQ2zTDfky3OBu/lGto3rmvzHWqlnas/fj9xc6ZFHEm5/LgDRR01XDBC6ALRbQ62Lw9HyrFWoOqaOtkVPVAcO2C3w09KC1wolJYW3mXNxcVzMeDXenymwdqmlzW2bPH7uY30MCpoa1zM1bfiQkeqSp65Gnv/3kDxnKu1QVVPVaClfldz1TQJRJDdRDufvh8MhvfKKlJdnB642tIcH0LURumKA0AWgXdoSmoJ17Fu7tmv+r7zTKY0eLb31VseeZ+xYaevWDg+ntt7XesOHFh8/N/sU4/2ZMlKT5fn4Q3mO/O38rFNN5blleOduI0fI8+N/a1s9UyT3XmuPtnRXBIA2oJEGACSK5cvD37TV4ZCWLJF+8xvpkkvsY8XF9pvKrsjns0NoR23bJuv0adUku1vtmBdqg9tY78+U0aTJQ/NZp0ZL9M7NQqU325/pBnvm8Mc/Dmyu0ZEld2lp9lLPcPdei3RDk3nzpIEDm3dXnDq1a24NACCuMdPVCma6ALRZdbXUrVv7rnW77VmeoqLIjilBWZKqUtLO77vU0BGvSVOIgI557nT7/NQL5M24UGdj0I+kYX+mprVLGanJ8mx6TZ6SPeeW4p1blndu5imj5rQ8fzdRaf/7nLn9mU6etINXJJbchbvML9y919qrq28NACCiWF4YA4QuAG1SUGAva6qpifVIOqZhidagQdLBg+1u6FHvcKoyJa1RQDrXJa+FzWtbClGn3Beo3hn9vY4a6plaDE1p54+19HhGqkupyUHGvHq1XafWmtWrE2dpKcv8AHQyhK4YIHQBCNuwYdLevbEeRWTk5koPPaTa3pfp1KzZ8vpbizeeVToXoFK6yZuaHjQ0RVvD/kwZ/vbhdoOHjNpqeaor5blprDyjrw/cm6lRgMpINbg/U26uVFoa3nnHjpkZgwnhbKIMAAmC0BUDhC4AYSkosN90xpkzSckBAanZrFJqhr3hbWrjpXvnl/JVp6RGfcyu+jp/B7zGzR6ahagmDSEaHk8/W93y/kwNorHcrSUnT0oXXRT++V9+mXgd91jmB6AToJEGAMSr1asj/pSWpNPJqedDk/tcIEoNXtvUdCbqrCs2+zP5A1GLG9c2/fxcgDq3qW1abY0MVTPZkpLsgBzt0NW4gUW45yda6EpLI2wBQAsIXQDQUceOtVjD5ZPj3KzR+RDkb/Dgr206H5aahqiY1TPVnFbG2fMhyN/goemsUqPglNEoXKXW10Z9zG1SV2cvg6uujm5AyM01ez4AIG4RugAgiNp6X8AGti1vZlsn7yefyTvjX+Omnindv1FtC8vyas51zAsIVOcDVPrZ00r2Rb9FetT5fPYyuGiGrh49pJyc8Gu6Em2WCwAQFKELQKd1pra+xc1qA0NT8MfbtD/TlSMiMuYkX/25VuJVrc4qtTQL1Wo9E2xOp113FG2PPBJe98JHHjE/FgBA1BC6AMQly7J0+mzT0NTKBrdn6nSqUWg6Wx/9DZpS6s6eD0Q15wJRkxAVPFBFoZ4J5jbrDcd999l7W/3mN8HPmTkzcdrFAwDCQugCYITPZ+lUTUtL8+qaBKZGjzeZdar3RX/GpltKUkAr8YxU17k9mOxjGanJLT9e+GNl/Pfy+K9ngr131AMPxO7rP/+8dMMN0o9/HNhcIzfXnuEicAFAp0PL+FbQMh5dVdj1TA3HGoep6lpVnq1TtH+7OBxSuruljWvPfWwlQKWnupTckf2ZhgyRSkoi9v0gwuJxs96TJ+3gRQ0XAMQNWsYDCFvjeqamAam1AHXqTJ1On41+M4UkpyMgGDUNTRlBNrP1pNnXpKe45HTGcHHe229L3brF7uujOYdDsiy7hmvq1PjbrLdHD8IWAHQBhC4gDjWtZ2qt4UOzeqYzdTpbF4N6piSnHZj8s0iNZpb8n7uaBKbzAatbSpIcjgSuaEpLk6ZPlzZsUMhpPodDGjNG2rYtakPrMJfLbrVuUlKSPRMVCQ11W7/6FZv1AgBijtAFGNC4nimwdqmuWTOIeK1nahqaWq5tCnw8NTn6e0rFnYICO3S15t//XfrZz6QXXzQ+JElSUZG0Z4/00ENtDzeNZ4kOHLCbQSQlBYYwp9Nuw94RPp/0gx9ITz7Z/Pkbh75wxt9Qt8VmvQCAOEDoAlrQuJ6pxYYP1Y2X4zXvpldZE/16Jkn+2aOmAalpPVNLASqjo/VMsI0ebdcMtRRMGtcUjRpl3778Utq82eyY1qyRvv1t+zZqlLRihfTSS6Fn4xpC1LJl0v33nw8uo0ZJAwfaz7F+vX2O02nP8FVUhP5ehg2T9u4N/XOZN0+aNq358zeEPin0+Jv+jAEAiAM00mgFjTQSU6LXM/mX3rXWMa/R4+lul5JiWc+EQDt2tBxMWqopWrNGevzx4Jvm5uZKZWXNZ5IcDik5WTp7tuXrvvOd4DVM1dV2QHrmGemPfwx8bodDmjGj9fqn6urmS/fWrAndla8tP5eWnj/U+EM9FwAAYTLx/p/Q1QpCV/Q1rmcKt2Pe+Xome6YppvVMqS5lpDWpYfLXLrmCNoNI+HomtCxUcGiqcSe7tLTA6xo/jxT4WKjr2jLG5GSptjYy9U+tdeVry8+lNZF8LgBAl0foigFCV9u1pZ7J/3iTUBXLeqaMMBo+tPQ49UwAAACJj5bxiIqGeqagASmgjinO65nCDFDUMwEAAMAUQlcn1FDP1LThQ2sNIRoej2U9U8DSuzA75nnSqGcCAABA/CJ0xZmGeqbWO+bFYz3TuZmmgDqmIBvZNtnolnomAAAAdFaErghrqGcKvjSvYR+mxpvaBoaqWNQzpSUnhQxIzZfmBc5KUc8EAAAAtIzQFaaX9n6mOldq/NYzuRvVLLWhYx71TAAAAIBZhK4wPfrH9+V0dzPy3E6HAuuW3IEBqbWOetQzAQAAAPGL0BUBrdUztdwMgnomAAAAoCsgdIXpX6dcpeyLerRY70Q9EwAAAIBgCF1hum1YbzZHBgAAANBmdE8AAAAAAIMIXQAAAABgEKELAAAAAAwidAEAAACAQYQuAAAAADCI0AUAAAAABhG6AAAAAMAgQhcAAAAAGEToAgAAAACDCF0AAAAAYBChCwAAAAAMInQBAAAAgEGELgAAAAAwiNAFAAAAAAYRugAAAADAIEIXAAAAABhE6AIAAAAAgwhdAAAAAGAQoQsAAAAADEq40LVq1SpddtllSk1N1YgRI7R79+6Q5//ud79T//79lZqaqoEDB+rVV1+N0kgBAAAAIMFC14svvqiCggItXbpU+/bt06BBgzRhwgQdP368xfPffvttzZw5U3fffbf279+vadOmadq0aTp48GCURw4AAACgq3JYlmXFehDhGjFihK677jr9/Oc/lyT5fD7l5eXp/vvv18MPP9zs/Ntuu01VVVV6+eWX/ceuv/56DR48WGvXrg3ra3q9XmVmZqqiokIejycy3wgAAACAuGTi/X/CzHSdPXtWe/fu1fjx4/3HnE6nxo8fr507d7Z4zc6dOwPOl6QJEyYEPV+Sampq5PV6A24AAAAA0F4JE7q++OIL1dfXKysrK+B4VlaWysrKWrymrKysTedLUmFhoTIzM/23vLy8jg8eAAAAQJeVMKErWpYsWaKKigr/7ejRo7EeEgAAAIAE5or1AMLVs2dPJSUlqby8POB4eXm5srOzW7wmOzu7TedLktvtltvt7viAAQAAAEAJNNOVkpKia6+9VkVFRf5jPp9PRUVFys/Pb/Ga/Pz8gPMladOmTUHPBwAAAIBIS5iZLkkqKCjQnXfeqWHDhmn48OFauXKlqqqqNGfOHEnS7Nmzdckll6iwsFCStHDhQo0dO1ZPPvmkJk+erBdeeEF79uzR008/HctvAwAAAEAXklCh67bbbtOJEyf06KOPqqysTIMHD9brr7/ub5Zx5MgROZ3nJ+9Gjhyp559/Xo888oj+5V/+RVdeeaU2bNigAQMGxOpbAAAAANDFJNQ+XbHAPl0AAABA19Gl9+kCAAAAgERE6AIAAAAAgwhdAAAAAGAQoQsAAAAADCJ0AQAAAIBBhC4AAAAAMIjQBQAAAAAGEboAAAAAwCBCFwAAAAAYROgCAAAAAIMIXQAAAABgEKELAAAAAAwidAEAAACAQYQuAAAAADCI0AUAAAAABhG6AAAAAMAgQhcAAAAAGEToAgAAAACDCF0AAAAAYBChCwAAAAAMInQBAAAAgEGELgAAAAAwiNAFAAAAAAYRugAAAADAIEIXAAAAABhE6AIAAAAAgwhdAAAAAGAQoQsAAAAADCJ0AQAAAIBBhC4AAAAAMIjQBQAAAAAGEboAAAAAwCBCFwAAAAAYROgCAAAAAIMIXQAAAABgEKELAAAAAAwidAEAAACAQYQuAAAAADCI0AUAAAAABhG6AAAAAMAgQhcAAAAAGEToAgAAAACDCF0AAAAAYBChCwAAAAAMInQBAAAAgEGELgAAAAAwiNAFAAAAAAYRugAAAADAIEIXAAAAABhE6AIAAAAAgwhdAAAAAGAQoQsAAAAADCJ0AQAAAIBBhC4AAAAAMIjQBQAAAAAGEboAAAAAwCBCFwAAAAAYROgCAAAAAIMIXQAAAABgEKELAAAAAAwidAEAAACAQYQuAAAAADCI0AUAAAAABhG6AAAAAMAgQhcAAAAAGEToAgAAAACDCF0AAAAAYBChCwAAAAAMSpjQdfLkSc2aNUsej0fdu3fX3XffrcrKypDXjBs3Tg6HI+A2b968KI0YAAAAACRXrAcQrlmzZqm0tFSbNm1SbW2t5syZo3vuuUfPP/98yOvmzp2rH/3oR/773bp1Mz1UAAAAAPBLiND1wQcf6PXXX9e7776rYcOGSZJ+9rOfadKkSXriiSeUm5sb9Npu3bopOzs7WkMFAAAAgAAJsbxw586d6t69uz9wSdL48ePldDq1a9eukNf++te/Vs+ePTVgwAAtWbJEp0+fDnl+TU2NvF5vwA0AAAAA2ishZrrKysrUq1evgGMul0s9evRQWVlZ0Otuv/12XXrppcrNzdWf//xnPfTQQzp06JBeeumloNcUFhbqsccei9jYAQAAAHRtMQ1dDz/8sJYtWxbynA8++KDdz3/PPff4Px84cKBycnJ000036fDhw7riiitavGbJkiUqKCjw3/d6vcrLy2v3GAAAAAB0bTENXYsXL9Zdd90V8pw+ffooOztbx48fDzheV1enkydPtqlea8SIEZKkjz76KGjocrvdcrvdYT8nAAAAAIQS09B18cUX6+KLL271vPz8fH399dfau3evrr32WknSli1b5PP5/EEqHCUlJZKknJycdo0XAAAAANoqIRppXHXVVbr11ls1d+5c7d69Wzt27NCCBQv0ve99z9+58NixY+rfv792794tSTp8+LAef/xx7d27V5988on++Mc/avbs2RozZoyuueaaWH47AAAAALqQhAhdkt2FsH///rrppps0adIkjR49Wk8//bT/8draWh06dMjfnTAlJUWbN2/WLbfcov79+2vx4sX6zne+oz/96U+x+hYAAAAAdEEOy7KsWA8innm9XmVmZqqiokIejyfWwwEAAABgkIn3/wkz0wUAAAAAiYjQBQAAAAAGEboAAAAAwCBCFwAAAAAYROgCAAAAAIMIXQAAAABgEKELAAAAAAwidAEAAACAQYQuAAAAADCI0AUAAAAABhG6AAAAAMAgQhcAAAAAGEToAgAAAACDCF0AAAAAYBChCwAAAAAMInQBAAAAgEGELgAAAAAwiNAFAAAAAAYRugAAAADAIEIXAAAAABhE6AIAAAAAgwhdAAAAAGAQoQsAAAAADCJ0AQAAAIBBhC4AAAAAMIjQBQAAAAAGEboAAAAAwCBCFwAAAAAYROgCAAAAAIMIXQAAAABgEKELAAAAAAxyxXoA8c6yLEmS1+uN8UgAAAAAmNbwvr8hB0QCoasVp06dkiTl5eXFeCQAAAAAouXLL79UZmZmRJ7LYUUywnVCPp9Pn3/+uTIyMuRwOGI9nE7L6/UqLy9PR48elcfjifVwEGd4fSAYXhsIhdcHguG1gVAqKirUu3dvffXVV+revXtEnpOZrlY4nU594xvfiPUwugyPx8MvPwTF6wPB8NpAKLw+EAyvDYTidEau/QWNNAAAAADAIEIXAAAAABhE6EJccLvdWrp0qdxud6yHgjjE6wPB8NpAKLw+EAyvDYRi4vVBIw0AAAAAMIiZLgAAAAAwiNAFAAAAAAYRugAAAADAIEIXAAAAABhE6ELMnDx5UrNmzZLH41H37t119913q7KyMuQ148aNk8PhCLjNmzcvSiOGSatWrdJll12m1NRUjRgxQrt37w55/u9+9zv1799fqampGjhwoF599dUojRTR1pbXxrp165r9jkhNTY3iaBEtb731lqZMmaLc3Fw5HA5t2LCh1Wu2bt2qoUOHyu12q2/fvlq3bp3xcSI22vr62Lp1a7PfHQ6HQ2VlZdEZMKKmsLBQ1113nTIyMtSrVy9NmzZNhw4davW6jr7vIHQhZmbNmqX3339fmzZt0ssvv6y33npL99xzT6vXzZ07V6Wlpf7bf/7nf0ZhtDDpxRdfVEFBgZYuXap9+/Zp0KBBmjBhgo4fP97i+W+//bZmzpypu+++W/v379e0adM0bdo0HTx4MMojh2ltfW1IksfjCfgd8emnn0ZxxIiWqqoqDRo0SKtWrQrr/I8//liTJ0/WjTfeqJKSEi1atEjf//739cYbbxgeKWKhra+PBocOHQr4/dGrVy9DI0SsbNu2TfPnz9c777yjTZs2qba2VrfccouqqqqCXhOR9x0WEAN/+ctfLEnWu+++6z/22muvWQ6Hwzp27FjQ68aOHWstXLgwCiNENA0fPtyaP3++/359fb2Vm5trFRYWtnj+d7/7XWvy5MkBx0aMGGH90z/9k9FxIvra+tp49tlnrczMzCiNDvFCkrV+/fqQ5zz44IPW1VdfHXDstttusyZMmGBwZIgH4bw+3nzzTUuS9dVXX0VlTIgfx48ftyRZ27ZtC3pOJN53MNOFmNi5c6e6d++uYcOG+Y+NHz9eTqdTu3btCnntr3/9a/Xs2VMDBgzQkiVLdPr0adPDhUFnz57V3r17NX78eP8xp9Op8ePHa+fOnS1es3PnzoDzJWnChAlBz0dias9rQ5IqKyt16aWXKi8vT1OnTtX7778fjeEizvF7A+EYPHiwcnJydPPNN2vHjh2xHg6ioKKiQpLUo0ePoOdE4veHq33DAzqmrKys2ZS9y+VSjx49Qq6fvv3223XppZcqNzdXf/7zn/XQQw/p0KFDeumll0wPGYZ88cUXqq+vV1ZWVsDxrKws/fWvf23xmrKyshbPZ+1959Ke10a/fv30zDPP6JprrlFFRYWeeOIJjRw5Uu+//76+8Y1vRGPYiFPBfm94vV5VV1crLS0tRiNDPMjJydHatWs1bNgw1dTU6Be/+IXGjRunXbt2aejQobEeHgzx+XxatGiRRo0apQEDBgQ9LxLvOwhdiKiHH35Yy5YtC3nOBx980O7nb1zzNXDgQOXk5Oimm27S4cOHdcUVV7T7eQF0Dvn5+crPz/ffHzlypK666io99dRTevzxx2M4MgDxrF+/furXr5///siRI3X48GGtWLFCv/rVr2I4Mpg0f/58HTx4UMXFxca/FqELEbV48WLdddddIc/p06ePsrOzmxXC19XV6eTJk8rOzg77640YMUKS9NFHHxG6ElTPnj2VlJSk8vLygOPl5eVBXwvZ2dltOh+JqT2vjaaSk5M1ZMgQffTRRyaGiAQS7PeGx+NhlgstGj58eFTejCM2FixY4G/k1tpKiEi876CmCxF18cUXq3///iFvKSkpys/P19dff629e/f6r92yZYt8Pp8/SIWjpKREkr0sAIkpJSVF1157rYqKivzHfD6fioqKAmYsGsvPzw84X5I2bdoU9Hwkpva8Npqqr6/XgQMH+B0Bfm+gzUpKSvjd0QlZlqUFCxZo/fr12rJliy6//PJWr4nI74/2dvoAOurWW2+1hgwZYu3atcsqLi62rrzySmvmzJn+xz/77DOrX79+1q5duyzLsqyPPvrI+tGPfmTt2bPH+vjjj62NGzdaffr0scaMGROrbwER8sILL1hut9tat26d9Ze//MW65557rO7du1tlZWWWZVnWHXfcYT388MP+83fs2GG5XC7riSeesD744ANr6dKlVnJysnXgwIFYfQswpK2vjccee8x64403rMOHD1t79+61vve971mpqanW+++/H6tvAYacOnXK2r9/v7V//35LkrV8+XJr//791qeffmpZlmU9/PDD1h133OE//29/+5vVrVs364c//KH1wQcfWKtWrbKSkpKs119/PVbfAgxq6+tjxYoV1oYNG6wPP/zQOnDggLVw4ULL6XRamzdvjtW3AEPuvfdeKzMz09q6datVWlrqv50+fdp/jon3HYQuxMyXX35pzZw500pPT7c8Ho81Z84c69SpU/7HP/74Y0uS9eabb1qWZVlHjhyxxowZY/Xo0cNyu91W3759rR/+8IdWRUVFjL4DRNLPfvYzq3fv3lZKSoo1fPhw65133vE/NnbsWOvOO+8MOP+3v/2t9c1vftNKSUmxrr76auuVV16J8ogRLW15bSxatMh/blZWljVp0iRr3759MRg1TGto8d301vB6uPPOO62xY8c2u2bw4MFWSkqK1adPH+vZZ5+N+rgRHW19fSxbtsy64oorrNTUVKtHjx7WuHHjrC1btsRm8DCqpdeFpIDfBybedzjOfXEAAAAAgAHUdAEAAACAQYQuAAAAADCI0AUAAAAABhG6AAAAAMAgQhcAAAAAGEToAgAAAACDCF0AAAAAYBChCwAAAAAMInQBAGDYJ598IofDoZKSklgPBQAQAw7LsqxYDwIAgHgxbtw4DR48WCtXrozYc9bX1+vEiRPq2bOnXC5XxJ4XAJAY+M0PAEAbWZal+vr6sANUUlKSsrOzDY8KABCvWF4IAEhY48aN0/33369FixbpwgsvVFZWlv7nf/5HVVVVmjNnjjIyMtS3b1+99tpr/msOHjyoiRMnKj09XVlZWbrjjjv0xRdfSJLuuusubdu2TT/96U/lcDjkcDj0ySefaOvWrXI4HHrttdd07bXXyu12q7i4WIcPH9bUqVOVlZWl9PR0XXfdddq8ebP/azVc1/R21113RftHBQCIIUIXACCh/fKXv1TPnj21e/du3X///br33nv1D//wDxo5cqT27dunW265RXfccYdOnz6tr7/+Wt/+9rc1ZMgQ7dmzR6+//rrKy8v13e9+V5L005/+VPn5+Zo7d65KS0tVWlqqvLw8/9d6+OGH9ZOf/EQffPCBrrnmGlVWVmrSpEkqKirS/v37deutt2rKlCk6cuSIJGnkyJH+5yktLdWWLVuUmpqqMWPGxORnBQCIDWq6AAAJa9y4caqvr9f27dsl2bVTmZmZmjFjhp577jlJUllZmXJycrRz505t3rxZ27dv1xtvvOF/js8++0x5eXk6dOiQvvnNb7ZY07V161bdeOON2rBhg6ZOnRpyTAMGDNC8efO0YMGCgONffvmlhg8frokTJ+rnP/95hH4CAIBEQE0XACChXXPNNf7Pk5KSdNFFF2ngwIH+Y1lZWZKk48eP67333tObb76p9PT0Zs9z+PBhffOb3wz5tYYNGxZwv7KyUv/2b/+mV155RaWlpaqrq1N1dbV/pqtBbW2tvvOd76hPnz4RbdABAEgMhC4AQEJLTk4OuO9wOAKOORwOSZLP51NlZaWmTJmiZcuWNXuenJycVr/WBRdcEHD/Bz/4gTZt2qQnnnhCffv2VVpamv7+7/9eZ8+eDTjv3nvv1bFjx7R79266FwJAF8RvfgBAlzF06FD94Q9/0GWXXRY0/KSkpKi+vj6s59uxY4fuuusuTZ8+XZI98/XJJ58EnLN8+XL9/ve/1zvvvKMLL7ywQ+MHACQmGmkAALqM+fPn6+TJk5o5c6beffddHT58WG+88YbmzJnjD1qXXXaZdu3apU8++URffPGFfD5f0Oe78sor9dJLL6mkpETvvfeebr/99oDzN2/erAcffFArV65U9+7dVVZWprKyMlVUVBj/XgEA8YPQBQDoMnJzc7Vjxw7V19frlltu0cCBA7Vo0SJ1795dTqf9T+IPfvADJSUl6Vvf+pYuvvjiZvVZjS1fvlwXXnihRo4cqSlTpmjChAkaOnSo//Hi4mLV19drzpw5ysnJ8d8WLlxo/HsFAMQPuhcCAAAAgEHMdAEAAACAQYQuAAAAADCI0AUAAAAABhG6AAAAAMAgQhcAAAAAGEToAgAAAACDCF0AAAAAYBChCwAAAAAMInQBAAAAgEGELgAAAAAwiNAFAAAAAAb9f3ntuvpIGYyMAAAAAElFTkSuQmCC\n", "text/plain": [ - "
" + "
" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], diff --git a/wyk/06_Problem_nadmiernego_dopasowania.ipynb b/wyk/06_Problem_nadmiernego_dopasowania.ipynb new file mode 100644 index 0000000..8f025a2 --- /dev/null +++ b/wyk/06_Problem_nadmiernego_dopasowania.ipynb @@ -0,0 +1,1832 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "### Uczenie maszynowe\n", + "# 6. Problem nadmiernego dopasowania" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "## 6.1. Regresja wielomianowa" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "### Wprowadzenie: wybór cech" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "Niech naszym zadaniem będzie przewidzieć cenę działki o kształcie prostokąta.\n", + "\n", + "Jakie cechy wybrać?" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "notes" + } + }, + "source": [ + "Możemy wybrać dwie cechy:" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + " * $x_1$ – szerokość działki, $x_2$ – długość działki:\n", + "$$ h_{\\theta}(\\vec{x}) = \\theta_0 + \\theta_1 x_1 + \\theta_2 x_2 $$" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "notes" + } + }, + "source": [ + "...albo jedną:" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + " * $x_1$ – powierzchnia działki:\n", + "$$ h_{\\theta}(\\vec{x}) = \\theta_0 + \\theta_1 x_1 $$" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "notes" + } + }, + "source": [ + "Można też zauważyć, że cecha „powierzchnia działki” powstaje przez pomnożenie dwóch innych cech: długości działki i jej szerokości." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "notes" + } + }, + "source": [ + "**Wniosek:** możemy tworzyć nowe cechy na podstawie innych poprzez wykonywanie na nich różnych operacji matematycznych." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "### Regresja wielomianowa" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "notes" + } + }, + "source": [ + "W regresji wielomianowej będziemy korzystać z cech, które utworzymy jako potęgi cech wyjściowych." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "slideshow": { + "slide_type": "notes" + } + }, + "outputs": [], + "source": [ + "# Przydatne importy\n", + "\n", + "import ipywidgets as widgets\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "import pandas\n", + "\n", + "%matplotlib inline" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "slideshow": { + "slide_type": "notes" + } + }, + "outputs": [], + "source": [ + "# Przydatne funkcje\n", + "\n", + "\n", + "def cost(theta, X, y):\n", + " \"\"\"Wersja macierzowa funkcji kosztu\"\"\"\n", + " m = len(y)\n", + " J = 1.0 / (2.0 * m) * ((X * theta - y).T * (X * theta - y))\n", + " return J.item()\n", + "\n", + "\n", + "def gradient(theta, X, y):\n", + " \"\"\"Wersja macierzowa gradientu funkcji kosztu\"\"\"\n", + " return 1.0 / len(y) * (X.T * (X * theta - y))\n", + "\n", + "\n", + "def gradient_descent(fJ, fdJ, theta, X, y, alpha=0.1, eps=10**-5):\n", + " \"\"\"Algorytm gradientu prostego (wersja macierzowa)\"\"\"\n", + " current_cost = fJ(theta, X, y)\n", + " logs = [[current_cost, theta]]\n", + " while True:\n", + " theta = theta - alpha * fdJ(theta, X, y)\n", + " current_cost, prev_cost = fJ(theta, X, y), current_cost\n", + " if abs(prev_cost - current_cost) > 10**15:\n", + " print(\"Algorithm does not converge!\")\n", + " break\n", + " if abs(prev_cost - current_cost) <= eps:\n", + " break\n", + " logs.append([current_cost, theta])\n", + " return theta, logs\n", + "\n", + "\n", + "def plot_data(X, y, xlabel, ylabel):\n", + " \"\"\"Wykres danych (wersja macierzowa)\"\"\"\n", + " fig = plt.figure(figsize=(16 * 0.6, 9 * 0.6))\n", + " ax = fig.add_subplot(111)\n", + " fig.subplots_adjust(left=0.1, right=0.9, bottom=0.1, top=0.9)\n", + " ax.scatter([X[:, 1]], [y], c=\"r\", s=50, label=\"Dane\")\n", + "\n", + " ax.set_xlabel(xlabel)\n", + " ax.set_ylabel(ylabel)\n", + " ax.margins(0.05, 0.05)\n", + " plt.ylim(y.min() - 1, y.max() + 1)\n", + " plt.xlim(np.min(X[:, 1]) - 1, np.max(X[:, 1]) + 1)\n", + " return fig\n", + "\n", + "\n", + "def plot_fun(fig, fun, X):\n", + " \"\"\"Wykres funkcji `fun`\"\"\"\n", + " ax = fig.axes[0]\n", + " x0 = np.min(X[:, 1]) - 1.0\n", + " x1 = np.max(X[:, 1]) + 1.0\n", + " Arg = np.arange(x0, x1, 0.1)\n", + " Val = fun(Arg)\n", + " return ax.plot(Arg, Val, linewidth=\"2\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "slideshow": { + "slide_type": "notes" + } + }, + "outputs": [], + "source": [ + "# Wczytanie danych (mieszkania) przy pomocy biblioteki pandas\n", + "\n", + "alldata = pandas.read_csv(\n", + " \"data_flats.tsv\", header=0, sep=\"\\t\", usecols=[\"price\", \"rooms\", \"sqrMetres\"]\n", + ")\n", + "data = np.matrix(alldata[[\"sqrMetres\", \"price\"]])\n", + "\n", + "m, n_plus_1 = data.shape\n", + "n = n_plus_1 - 1\n", + "Xn = data[:, 0:n]\n", + "Xn /= np.amax(Xn, axis=0)\n", + "Xn2 = np.power(Xn, 2)\n", + "Xn2 /= np.amax(Xn2, axis=0)\n", + "Xn3 = np.power(Xn, 3)\n", + "Xn3 /= np.amax(Xn3, axis=0)\n", + "\n", + "X = np.matrix(np.concatenate((np.ones((m, 1)), Xn), axis=1)).reshape(m, n + 1)\n", + "X2 = np.matrix(np.concatenate((np.ones((m, 1)), Xn, Xn2), axis=1)).reshape(m, 2 * n + 1)\n", + "X3 = np.matrix(np.concatenate((np.ones((m, 1)), Xn, Xn2, Xn3), axis=1)).reshape(\n", + " m, 3 * n + 1\n", + ")\n", + "y = np.matrix(data[:, -1]).reshape(m, 1)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "Postać ogólna regresji wielomianowej:\n", + "\n", + "$$ h_{\\theta}(x) = \\sum_{i=0}^{n} \\theta_i x^i $$" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "outputs": [], + "source": [ + "# Funkcja regresji wielomianowej\n", + "\n", + "\n", + "def h_poly(Theta, x):\n", + " \"\"\"Funkcja wielomianowa\"\"\"\n", + " return sum(theta * np.power(x, i) for i, theta in enumerate(Theta.tolist()))\n", + "\n", + "\n", + "def polynomial_regression(theta):\n", + " \"\"\"Funkcja regresji wielomianowej\"\"\"\n", + " return lambda x: h_poly(theta, x)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "notes" + } + }, + "source": [ + "Najprostszym przypadkiem regresji wielomianowej jest funkcja kwadratowa:" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "Funkcja kwadratowa:\n", + "\n", + "$$ h_{\\theta}(x) = \\theta_0 + \\theta_1 x + \\theta_2 x^2 $$" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAAA1IAAAH+CAYAAACWZz+7AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8o6BhiAAAACXBIWXMAAA9hAAAPYQGoP6dpAACEnUlEQVR4nO3dd3hUZd7/8c+UNCAJhpIQCB0B6SAg0hUbrgtixbp2FAuwxeW3++w+W1zXZxXcIrDrqqy62FBAxAYISKgConTpNQk9ISF1Zn5/HDIppMwkM3OmvF/XNVdyJmdmvimE88l939/b4nK5XAIAAAAAeMxqdgEAAAAAEGoIUgAAAADgJYIUAAAAAHiJIAUAAAAAXiJIAQAAAICXCFIAAAAA4CWCFAAAAAB4iSAFAAAAAF4iSAEAAACAlwhSAAAAAOCliA5SX3/9tW666SalpqbKYrFo/vz5Xj+Hy+XSiy++qEsvvVQxMTFq2bKlnnvuOd8XCwAAACBo2M0uwEx5eXnq1auXHnzwQY0bN65Oz/HMM8/oyy+/1IsvvqgePXro9OnTOn36tI8rBQAAABBMLC6Xy2V2EcHAYrFo3rx5Gjt2rPu+wsJC/epXv9I777yjs2fPqnv37nrhhRc0YsQISdKOHTvUs2dPbd26VZ07dzancAAAAAABF9FT+2rz5JNPas2aNXr33Xf1/fff67bbbtP111+v3bt3S5IWLlyo9u3b65NPPlG7du3Utm1bPfzww4xIAQAAAGGOIFWNQ4cO6Y033tAHH3ygoUOHqkOHDvrZz36mIUOG6I033pAk7du3TwcPHtQHH3ygN998U7Nnz9bGjRt16623mlw9AAAAAH+K6DVSNdmyZYscDocuvfTSCvcXFhaqSZMmkiSn06nCwkK9+eab7vNee+019evXT7t27WK6HwAAABCmCFLVyM3Nlc1m08aNG2Wz2Sp8rFGjRpKkFi1ayG63VwhbXbt2lWSMaBGkAAAAgPBEkKpGnz595HA4dPz4cQ0dOrTKcwYPHqySkhLt3btXHTp0kCT98MMPkqQ2bdoErFYAAAAAgRXRXftyc3O1Z88eSUZwmjZtmkaOHKmkpCS1bt1a99xzj1atWqWXXnpJffr00YkTJ7R06VL17NlTN954o5xOp/r3769GjRrp5ZdfltPp1MSJE5WQkKAvv/zS5M8OAAAAgL9EdJBavny5Ro4cedH9999/v2bPnq3i4mL98Y9/1JtvvqmjR4+qadOmuuKKK/S73/1OPXr0kCQdO3ZMTz31lL788ks1bNhQN9xwg1566SUlJSUF+tMBAAAAECARHaQAAAAAoC5ofw4AAAAAXiJIAQAAAICXIq5rn9Pp1LFjxxQfHy+LxWJ2OQAAAAD8yOVy6dy5c0pNTZXV6rtxpIgLUseOHVNaWprZZQAAAAAIoMOHD6tVq1Y+e76IC1Lx8fGSjC9kQkKCJKmg2KGRLy7TuQKHYqKsWv6zEYqPjTKzTACITPn5UosWkid9kCwWKSNDiovzf11AmJq9ar9e/NLYA3PC8A568qqOJlcE+F5OTo7S0tLcOcBXIi5IlU7nS0hIcAepBEk3D+ykt9ceUrGkVQfP6/b+jFoBQMAlJEhjx0oLF0olJdWfZ7dLY8ZIyckBKw0IR5//kCNrTANJ0p2DL1VCQiOTKwL8x9fLemg2ccGt/cqC09yNR0ysBAAi3JQpksNR8zkOhzR5cmDqAcLUrsxz2p6RI0nqldZY7ZsRogBvEKQu6NUqUR2bG79A1h84rQMn80yuCAAi1JAh0owZxtQ9e6WJE3a7cf+MGdLgwebUB4SJ+ZuPut+/uXeqiZUAoYkgdYHFYtGt/coWn320iVEpADDNhAnSypXG9L3SDktWq3G8cqXxcQB15nS6tOBbI0jZrBb9qBdBCvAWQaqcm/u0lPXC1MkPNx2V0+nBYmcAgH8MHizNnSvl5kqZmcbbuXMZiQJ8YN3+0zqWXSBJGtapqZo2ijG5IiD0EKTKSU6I1bBLm0mSjp7N19p9p0yuCACguDijqQTd+QCfmf9t2bS+sX1amlgJELoIUpWUn95H0wkAABBuCood+nRLhiSpYbRN116WYnJFQGgiSFUyqmuyEmKNxc2fbs3QuYJikysCAADwna92Hte5QmN7geu7t1BctM3kioDQRJCqJDbKph9f6FxTUOzUZ1syTa4IAADAd+aVm9Z3M9P6gDojSFWBPaUAAEA4OpNXpOW7jkuSmsfHaFCHJiZXBIQuglQV2FMKAACEo0VbMlTsMLoSj+mdKltpu2IAXiNIVYE9pQAAQDiaR7c+wGcIUtVgTykAABBODp06r40Hz0iSLk1upMtaJJhcERDaCFLVYE8pAAAQTuZvLt9kopUsFqb1AfVBkKoBe0oBAIBw4HK5KmzCO+ZCh2IAdUeQqsGorslKjIuSxJ5SAAAgdH1/JFv7LjTPuqJ9klIbx5lcERD6CFI1iI2y6ce9yvaUKt0FHAAAIJSwdxTgewSpWjC9DwAAhLJih1MLvzsmSYq2W3V99xYmVwSEB4JULXq2SlSnC3tKfXPgDHtKAQCAkJK++6RO5RVJkkZ1be5etgCgfghStai8p9SH7CkFAABCSIW9o3ozrQ/wFYKUByrsKbXxCHtKAQCAkJBbWKIvt2dKkho3iNKIzs1NrggIHwQpDzRPiNXwC3tKHcsu0Br2lAIAACFg4XfHVFDslCTd2KOFou1c+gG+wr8mD93aL839Pk0nAABAKHh3/SH3+3f0T6vhTADeIkh56OpyizM/Y08pAAAQ5LYdy9Z3R7IlSd1SE9SjZaLJFQHhhSDlIfaUAgAAoeTd9Yfd7985oLUsFouJ1QDhhyDlBfaUAgAAoSC/yKH5m41ufXFRNo3pnWpyRUD4IUh5gT2lAABAKFi0JUPnCkokSTf2bKGEWPaOAnzN1CD1/PPPq3///oqPj1fz5s01duxY7dq1q8bHzJ49WxaLpcItNjY2IPWypxQAAAgF5ZtMjB9AkwnAH0wNUitWrNDEiRO1du1aLV68WMXFxbr22muVl1fzSE9CQoIyMjLct4MHDwaoYvaUAgAAwW131jltOHhGktSpeSP1bX2JyRUB4clu5ot//vnnFY5nz56t5s2ba+PGjRo2bFi1j7NYLEpJSfF3eVUq3VNq2a4T7j2lBndsakotAAAAlb37DU0mgEAIqjVS2dlGi86kpKQaz8vNzVWbNm2UlpamMWPGaNu2bdWeW1hYqJycnAq3+mJPKQAAEIwKih366MLSg2i7VeP6tDS5IiB8BU2QcjqdmjRpkgYPHqzu3btXe17nzp31+uuva8GCBXr77bfldDp15ZVX6siRqgPN888/r8TERPctLa3+84TZUwoAAASjL7Zl6sx547rkhu4puqRhtMkVAeEraILUxIkTtXXrVr377rs1njdo0CDdd9996t27t4YPH66PPvpIzZo10z//+c8qz586daqys7Pdt8OHD1d5njdiy7URLSh2atH37CkFAADMV2HvqP6tTawECH9BEaSefPJJffLJJ1q2bJlatWpV+wPKiYqKUp8+fbRnz54qPx4TE6OEhIQKN19gTykAABBMDpzM05p9pyRJ7Zo21BXta14qAaB+TA1SLpdLTz75pObNm6evvvpK7dq18/o5HA6HtmzZohYtWvihwur1aJmoS5ONPaU2HDyj/ewpBQAATFS+ycQd/dNoMgH4malBauLEiXr77bc1Z84cxcfHKzMzU5mZmcrPz3efc99992nq1Knu49///vf68ssvtW/fPm3atEn33HOPDh48qIcffjigtV+0pxSjUgAAwCTFDqd7hozdatEtfb2b4QPAe6YGqZkzZyo7O1sjRoxQixYt3Lf33nvPfc6hQ4eUkVG2BunMmTN65JFH1LVrV40ePVo5OTlavXq1LrvssoDXP7Z3S9kubCr14aYjcrCnFAAAMMHSHVk6mVsoSbrmsmQ1i48xuSIg/Jm6j5TLVXvwWL58eYXj6dOna/r06X6qyDule0p9tfO4MrILtGbvKQ3pxJ5SAAAgsN5ZX3HvKAD+FxTNJkJZxaYT9e8ICAAA4I0jZ87r690nJEktG8dpaEf+qAsEAkGqnsrvKfX5tkzlsKcUAAAIoPc3HFHpJJ87+6fJaqXJBBAIBKl6irFX3FPqU/aUAgAAAVLicOr9C936rBbptsvTTK4IiBwEKR9gTykAAGCGFT+cUGZOgSTpqi7NlZIYa3JFQOQgSPkAe0oBAAAzVGgy0Z8mE0AgEaR8gD2lAABAoGXlFGjZruOSpOSEGI3o3MzkioDIQpDyEfaUAgAAgfTBhsPu643bL0+T3cZlHRBI/IvzkdI9pSS595QCAADwB6fTpfc2GNP6LBYjSAEILIKUD7GnFAAACIRVe0/q8Ol8SdLQTs2UltTA5IqAyEOQ8iH2lAIAAIHwbrkmE+P7MxoFmIEg5UPsKQUAAPztZG6hvtyeKUlq2ihaV3dNNrkiIDIRpHzstn5lfxX6gO59AADAxz7ceETFDqPJxC39WinazuUcYAb+5flY95YJ6pwcL0naePCM9p3INbkiAAAQLlwul977hr2jgGBAkPKxyntKzWVUCgAA+Mi6/ae172SeJOmK9klq17ShyRUBkYsg5Qdj+qS695Sau/GIih1OkysCAADh4N31h9zvjx/AaBRgJoKUHzSPj9Wors0lScfPFWrx9iyTKwIAAKHu7PkifbrVaDLRuEGUruuWYnJFQGQjSPnJPVe0cb//1pqDJlYCAADCwbxvj6qoxJjlMq5PK8VG2UyuCIhsBCk/GdyhqXve8pp9p7Tn+DmTKwIAAKHK5XJV3DtqAHtHAWYjSPmJ1WrR3QPL5i6/vfZQDWcDAABU79vDZ7Ury/ijbL82l6jThQ7BAMxDkPKj2/qlKTbK+BJ/uPGIzheVmFwRAAAIReWbTNzZn9EoIBgQpPwosUGUftwrVZJ0rrBECzYfM7kiAAAQas4VFGvhdxmSpPgYu27s2cLkigBIBCm/u/eKtu7331pzUC6Xy7xiAABAyFmw+Zjyix2SjC1WGkTbTa4IgESQ8rserRLVK62xJGl7Ro42HTpraj0AACC0vPsNe0cBwYggFQD3lmuF/vZaWqEDAADPbD2ara1HcyRJPVslqltqoskVAShFkAqAH/VsocYNoiRJi77P0KncQpMrAgAAoeCdCk0mGI0CgglBKgBio2y6/XKjw06Rw6n3NxwxuSIAABDszheVNapqEG3Tj3unmlwRgPIIUgFSfk+pOesPyuGk6QQAAKjeJ99nKLfQ2Drlpp6pahRDkwkgmBCkAqRNk4YafmkzSdLh0/n6+ocTJlcEAACCWYW9owawdxQQbAhSAXRPuaYTb9F0AgAAVGNX5jl3p98uKfHqfaEDMIDgQZAKoKu6NFfLxnGSpGW7juvw6fMmVwQAAIJR+SYT4we0lsViMbEaAFUhSAWQzWrRXRfWSrlc0n/XHarlEQAAINIUFDs079ujkqQYu1Vje7c0uSIAVSFIBdjtl6cpymb8Ven9DYdVcGGncgAAAEn6fGumsvOLJUk39mihxAtbqAAILgSpAGsWH6MbureQJJ3OK9JnWzNMrggAAASTCntHDWDvKCBYEaRMcO+gck0n1tB0AgAAGPadyNW6/aclSR2aNVT/tpeYXBGA6hCkTHB5m0vUJSVekrTp0FltPZptckUAACAYvPfNYff7d/anyQQQzAhSJrBYLBVaof93HaNSAABEuqISp+ZuPCJJirJZNK4vTSaAYEaQMsnYPi3dO5TP//aYcgqKTa4IAACYacmOLJ3KK5IkXdstRU0axZhcEYCaEKRM0ijG7v5LU36xQx9d+AsUAACITOWbTNxFkwkg6BGkTFR+et9baw/K5XKZWA0AADDL4dPntXL3SUlS66QGGtS+ickVAagNQcpElybHa0C7JEnS3hN5WrPvlMkVAQAAM5RvMnFH/zRZrTSZAIIdQcpk95YblXp7LU0nAACINCUOpz7YaAQpm9Wi2/q1MrkiAJ4gSJnsum4panphMekX27KUlVNgckUAACCQlu06oaycQknS1V2aq3lCrMkVAfAEQcpk0Xarxg9IkyQ5nK4KC00BAED4e7fc//3jaTIBhAyCVBAYP6C1SqdCv7P+kIodTnMLAgAAAZGRna9lu45LklITYzXs0mYmVwTAUwSpIJDaOE6juiZLkrJyCrVke5bJFQEAgED4YMMROS807b29f5psNJkAQgZBKkjcO6hc04l1NJ0AACDcOZwud7c+q0W6/fI0kysC4A2CVJAY3KGp2jVtKElateeU9hzPNbkiAADgTyt3n9DRs/mSpOGXNlNq4ziTKwLgDYJUkLBaLbp7YNkC0/8yKgUAQFh7d33Z3lF30mQCCDkEqSByW780xUYZ35K5G4/ofFGJyRUBAAB/OHGuUEt2GGuim8XH6KouzU2uCIC3CFJBJLFBlH7cK1WSdK6gRB9vPmZyRQAAwB/mrDukkgtdJm7r10pRNi7JgFDDv9ogc88VZU0n3lxzUC6Xy8RqAACArxWWOPTWWmMKv81q0d3l/u8HEDoIUkGmZ6vG6tUqUZK0PSNH3x4+a25BAADApz75LkMncwslSdd3S1FLmkwAIYkgFYTKj0q9vYamEwAAhAuXy6XXV+13Hz84pK15xQCoF4JUELqpV6oS46IkSZ98n6HTeUUmVwQAAHxh/f7T2nYsR5LUq1Wi+ra+xOSKANQVQSoIxUbZdPvlrSRJRQ6n3t9wuJZHAACAUFBxNKqdLBaLidUAqA+CVJC6e2DZ9L7/rjsop5OmEwAAhLJDp87ry+1Gy/PkhBiN7tHC5IoA1AdBKki1bdpQwy5tJkk6fDpfK3afMLkiAABQH/9Zc0ClzXjvG9SWludAiONfcBC7l6YTAACEhXMFxXrvG2OqfozdqrsGtDa5IgD1RZAKYld1ae5uifrVruM6fPq8yRUBAIC6+GDDEeUWlkiSxvVtpUsaRptcEYD6IkgFMZvVorsGGn+xcrmkOesPmVwRAADwlsPp0uzVB9zHDw5ua1otAHyHIBXkbr88TVE2o6PPe98cVmGJw+SKAACAN5buyNKhC7NKhnZqqk7J8SZXBMAXCFJBrll8jG7obnT1OZ1XpM+2ZJpcEQAA8EbllucAwgNBKgTcU67pxFtraToBAECo2HYsW2v3nZYktW/WUMM7NTO5IgC+QpAKAf3bXqLOF6YBbDx4Rtsv7IgOAACC2xurDrjff2BwO1mtbMALhAuCVAiwWCy6Z1C5VujrGJUCACDYnThXqI83H5MkJcTadUvfliZXBMCXCFIh4uY+LdUw2iZJmv/tUeUUFJtcEQAAqMl/1x1UkcMpSRo/sLUaRNtNrgiALxGkQkSjGLvG9W0lSTpf5NC8TUdNrggAAFSnsMShty+sa7ZZLbp/UFtzCwLgcwSpEFK56YTL5TKxGgAAUJ2F32XoZG6RJOmG7ilKbRxnckUAfI0gFUI6p8RrQLskSdKe47nuLkAAACB4uFwuvZ5Oy3Mg3BGkQsy95Ual3qYVOgAAQWftvtPanmF02O2d1lh9W19ickUA/IEgFWKu65aipo1iJElfbMtUVk6ByRUBAIDy2IAXiAwEqRATbbdq/IA0SVKJ06V31x82uSIAAFDq4Kk8LdmRJUlKSYjVDd1TTK4IgL+YGqSef/559e/fX/Hx8WrevLnGjh2rXbt21fq4Dz74QF26dFFsbKx69OihTz/9NADVBo/xA1qrdD+/OesPqvhCa1UAAGCu2asPqLQX1H1XtlGUjb9ZA+HK1H/dK1as0MSJE7V27VotXrxYxcXFuvbaa5WXl1ftY1avXq3x48froYce0rfffquxY8dq7Nix2rp1awArN1dq4zhd3TVZkpSVU6ilF/7yBQAAzHOuoFgfbDgiSYqNsmp8/9YmVwTAnyyuIOqhfeLECTVv3lwrVqzQsGHDqjznjjvuUF5enj755BP3fVdccYV69+6tWbNm1foaOTk5SkxMVHZ2thISEnxWe6B9/cMJ3ff6eknSkI5N9fbDA02uCACAyPZa+n794ZPtkqS7BrbWn27uYXJFACT/Xf8H1Xhzdna2JCkpKanac9asWaNRo0ZVuO+6667TmjVrqjy/sLBQOTk5FW7hYEjHpmrbpIEkKX3PSe09kWtyRQAARC6H06XZq8uaTDxwZVvzigEQEEETpJxOpyZNmqTBgwere/fu1Z6XmZmp5OTkCvclJycrMzOzyvOff/55JSYmum9paWk+rdssVqulwga9/117yMRqAACIbEt2ZOnw6XxJ0rBLm6lTcrzJFQHwt6AJUhMnTtTWrVv17rvv+vR5p06dquzsbPft8OHw6XJ3a79WirEb38IPNhzWuYJikysCACAyVdiAd3Bb8woBEDBBEaSefPJJffLJJ1q2bJlatWpV47kpKSnKyqrYXCErK0spKVW3F42JiVFCQkKFW7ho3CBaN/dpKUk6V1iid9YzKgUAQKBtPZqtdftPS5I6NGuoYZ2amVwRgEAwNUi5XC49+eSTmjdvnr766iu1a1f7pnWDBg3S0qVLK9y3ePFiDRo0yF9lBrVHhrWX5UIr9NfS96uohFboAAAEUvkNeB8Y3E7W0j1KAIQ1U4PUxIkT9fbbb2vOnDmKj49XZmamMjMzlZ+f7z7nvvvu09SpU93HzzzzjD7//HO99NJL2rlzp/73f/9XGzZs0JNPPmnGp2C6Ds0a6ZpyrdAXbD5qckUAAESO4+cKtPC7Y5KkxLgo3dK35pk1AMKHqUFq5syZys7O1ogRI9SiRQv37b333nOfc+jQIWVkZLiPr7zySs2ZM0f/+te/1KtXL82dO1fz58+vsUFFuHtseAf3+//6ep+czqDpaA8AQFh7e+0hFTuM/3fvGthacdE2kysCEChBtY9UIITLPlKV3TZrtb45cEaS9Nr9l7s37AUAAP5RUOzQ4D9/pVN5RbJZLUp/dqRaJMaZXRaASiJiHynU3WPDykal/rlin4mVAAAQGT7+7phO5RVJkkb3aEGIAiIMQSpMXNWluTo2byRJWn/gtDYdOmNyRQAAhC+Xy0XLcyDCEaTChNVq0aPD2ruP/8WoFAAAfrNm3yntzDwnSerTurH6tL7E5IoABBpBKoyM6Z2q5IQYSdIX2zO170SuyRUBABCeXk8/4H7/wcG1b98CIPwQpMJIjN3m/mXuckmvrtxfyyMAAIC3DpzM09KdWZKkFomxur57iskVATADQSrMjB/YWvExdknSh5uO6Pi5ApMrAgAgvMxefUClPY/vG9RWUTYup4BIxL/8MJMQG6W7rmgtSSoqceo/qw+YWxAAAGEkp6BYH2w4LEmKjbJq/IA0kysCYBaCVBh6cHA7RdkskqS31hxUbmGJyRUBABAe3v/msPKKHJKkW/q2UuMG0SZXBMAsBKkwlJwQq5v7tJQk5RSU6N31h0yuCACA0FficOqNVQfcxw/QZAKIaASpMFW+Ffpr6ftV7HCaWA0AAKFvyY4sHT2bL0ka0bmZe/9GAJGJIBWmOjaP16iuyZKkjOwCLfzumMkVAQAQ2mh5DqA8glQYmzC8bFTqnyv2yVXaYggAAHhly5FsrT9wWpLUsXkjDe3U1OSKAJiNIBXGLm+bpH5tjJ3Wd2Wd0/IfTphcEQAAAZCfL2VlGW995I1VZXszPji4nSwWi8+eG0BoIkiFuceGlR+V2mtiJQAA+Fl6ujRunNSokZSSYrwdN05atapeT3s8p0ALvzemyDduEOVu6AQgshGkwtyorslq36yhJGntvtPafPisuQUBAOAPM2dKw4ZJCxdKzgsNlpxO43joUGnWrDo/9dtrD6rYYUyPv2tAa8VF23xRMYAQR5AKc1arRY8OLRuV+tfXjEoBAMJMero0caLkckkllfZOLCkx7n/iiTqNTBUUO/T2OmMbEbvVonsHtfFFxQDCAEEqAozt01LN4mMkSZ9tzdSBk3kmVwQAgA9NmybZahklstmk6dO9fuqPNx/T6bwiSdLoHi3UIjGuLhUCCEMEqQgQG2XTA4PbSjL+KPfqyn3mFgQAgK/k50sLFlw8ElVZSYk0b55XDShcLpdeL99kYggtzwGUIUhFiLsHtlHDC3O6P9h4RCfOFZpcEQAAPpCTU7YmqjZOp3G+h1bvPaWdmeckSX1bN1bvtMZ1KBBAuCJIRYjEuCjdNbC1JKmoxKk31xwwtyAAAHwhIUGyeng5Y7Ua53vo9XRGowBUjyAVQR4c0k52q7HvxZtrDiqvsJZpEAAABLu4OGnMGMlur/k8u126+WbjfA/sP5mnpTuPS5JSE2N1fbeU+lYKIMwQpCJIi8Q4jelt7H2RnV+s9745bHJFAAD4wJQpksNR8zkOhzR5ssdPObvc2qj7r2wru41LJgAV8VshwjxaboPe19L3q9jh4bxyAACC1ZAh0owZksVy8ciU3W7cP2OGNHiwR0+XnV+sDzYekSTFRdl0Z//Wvq4YQBggSEWYzinxuqpLc0nS0bP5WvR9hskVAQDgAxMmSCtXGtP8StdMWa3G8cqVxsc99P43h3W+yBjhurVfKyU2iPJHxQBCXC0TihGOHhvWXl9dmPc9a8VejemdKovFYnJVAADU0+DBxi0/3+jOl5Dg8ZqoUiUOp2avPuA+/smF7UMAoDJGpCLQgHZJ7hauOzPP6evdJ80tCAAAX4qLk5KTvQ5RkvTFtiwdPWvsNTWyczN1aNbI19UBCBMEqQhksVg0YXjZWql/rthrYjUAAAQHp9Olv3+1231My3MANSFIRahrLktRu6YNJRkbDn5/5Ky5BQEAYLIlO7LcG/D2apWoIR2bmlwRgGBGkIpQNqtFjwwtNyr19T4TqwEAwFwul0t/Kzca9fTVnVg/DKBGBKkINq5vSzVtFC1J+mxLhg6eyjO5IgAAzLF81wltPZojSeqWmuDucAsA1SFIRbDYKJseGGzM/3a6pH+v3F/LIwAACD8ul0t/XVo2GvXUVYxGAagdQSrC3TOwjRpE2yRJ7284rFO5hSZXBABAYK3cfVKbD5+VJHVJide1lyWbWxCAkECQinCJDaI0foCxY3thiVP/WXPQ5IoAAAgcl8ulv1UajbJaGY0CUDuCFPTgkHayX/hP4801B3S+qMTkigAgwuXnS1lZxlv41Zp9p7Th4BlJUqfmjXRD9xSTKwIQKghSUMvGcfpxr1RJ0tnzxXr/m8MmVwQAESo9XRo3TmrUSEpJMd6OGyetWmV2ZWGr/GjUk1d1ZDQKgMcIUpAkPVpug95XV+5XicNpYjUAEIFmzpSGDZMWLpScF34HO53G8dCh0qxZ5tYXhtbvP621+05Lkto3bagf9Uw1uSIAoYQgBUlSl5QEjejcTJJ09Gy+Fm3JMLkiAIgg6enSxImSyyWVVJpeXVJi3P/EE4xM+djfy+0bNXFkR9kYjQLgBYIU3B4b1sH9/j9X7JPL5TKxGgCIINOmSTZbzefYbNL06YGpJwJsPHhGK3eflCS1TmqgMb0ZjQLgHYIU3K5on6SerRIlSdszcpS+56TJFQFABMjPlxYsuHgkqrKSEmnePBpQ+EjF0agOstu4JALgHX5rwM1isVw0KgUA8LOcnLI1UbVxOo3zUS/fHzmr5btOSDIaLt3cp5XJFQEIRQQpVHB99xS1TmogSUrfc1Jbj2abXBEAhLmEBMnq4X/HVqtxPurlb0v3uN9/fEQHRdu5HALgPX5zoAKb1aJHhpV18PvX14xKAYBfxcVJY8ZIdnvN59nt0s03G+ejzrYdy9aSHVmSpJSEWN12OaNRAOqGIIWL3NavlZo0jJYkLdqSocOnz5tcEQCEuSlTJIej5nMcDmny5MDUE8b+8VXF0agYey1NPgCgGgQpXCQ2yqb7r2wrSXI4XXotfb+5BQFAuBsyRJoxQ7JYLh6ZstuN+2fMkAYPNqe+MLEr85w+25opSWoWH6M7+qeZXBGAUEaQQpXuvaKN4qKMv9K9+80hnc4rMrkiAAhzEyZIK1ca0/xK10xZrcbxypXGx1Ev5Tv1PTasvWKjGI0CUHcEKVTpkobR7r/UFRQ79daagyZXBAARYPBgae5cKTdXysw03s6dy0iUD+w5nuvebL5po2jdPbCNyRUBCHUEKVTroSHt3Lu8/2fNAeUX1TJ/HwDgG3FxUnIyjSV86JVle1S6z/wjQ9srLprRKAD1Q5BCtdKSGuhHPVtIkk7nFWnuxsMmVwQAgPf2n8zTgs1HJUmXNIjSPVcwGgWg/ghSqNGj5Vqhv7pyv0ocHm4aCQBAkJixbI+cF0ajHh7aXg1jamk1DwAeIEihRt1SEzW0U1NJ0qHT5/X5tkyTKwIAwHOHT5/XR98ao1EJsXbdN4jRKAC+QZBCrSYM7+B+f9aKvXKVTjIHACDIzVi+R44Lw1EPDmmn+NgokysCEC4IUqjVlR2aqHvLBEnS1qM5WrLjuMkVAQBMlZ8vZWUZb4PY0bP5mrvxiCQpPsauB65sZ3JFAMIJQQq1slgseuqqTu7jl77cJaeTUSkAiDjp6dK4cVKjRlJKivF23Dhp1SqzK6vSrOV7Veww/r/6yeC2SmzAaBQA3yFIwSPXXpasXq0SJUk7M8/pkwt7cQAAIsTMmdKwYdLChZLzQuMhp9M4HjpUmjXL3Poqycwu0HvfGN1mG0bb9OBgRqMA+BZBCh6xWCz66bWd3ccvL/6BDn4AECnS06WJEyWXSyopqfixkhLj/ieeCKqRqVkr9qrowv9T9w5qq0saRptcEYBwQ5CCx4Z2aqqB7ZIkSftO5umjTUdNrggAEBDTpkm2Wjawtdmk6dMDU08tjp8r0DvrD0mS4qJsengoo1EAfI8gBY9ZLBb9/LqyUam/Lt2twhKHiRUBAPwuP19asODikajKSkqkefOCogHFq1/vU2GJMRp198DWatooxuSKAIQjghS8cnnbJI3o3EyS0Q3pnXWHTK4IAOBXOTlla6Jq43Qa55voVG6h3l5r/N8UY7dW2FgeAHyJIAWv/azcWql/LNur80W1/JUSABC6EhIkq4eXC1arcb6J/p2+X/nFxmyJ8QNaq3lCrKn1AAhfBCl4rXvLRN3QPUWSdDK3UP9ZfdDkigAAfhMXJ40ZI9ntNZ9nt0s332ycb5IzeUV6c/UBSVK0zVphQ3kA8DWCFOpkyjWXymIx3p+1Yq9yCorNLQgA4D9TpkiOWtbEOhzS5MmBqacar6/ar7wio87b+7dSSiKjUQD8hyCFOumUHK+b+7SUJGXnF+vfK/ebXBEAwG+GDJFmzJAslotHpux24/4ZM6TBg82pT8b/RbNXHZAkRdksenxER9NqARAZCFKos0lXXyq71RiWem3lPp3OKzK5IgCA30yYIK1caUzzK10zZbUaxytXGh830exVB3Su0Fize2u/VmrZ2LwphgAiA0EKdda6SQPd0T9NkpRX5NCsFXtNrggA4FeDB0tz50q5uVJmpvF27lxTR6Ik6VxBsV5L3ydJslktenw4o1EA/I8ghXp56qpOirEbP0b/WX1AWTkFJlcEAPC7uDgpOdnUxhLlvbnmoHIKjNGom/u0VOsmDUyuCEAkIEihXlISY3XvFW0kSYUlTv39q90mVwQAiCR5hSX690pjNMpqkSaOZDQKQGAQpFBvj4/ooIbRNknSu+sP6/Dp8yZXBACIFG+vPagz543OsT/ulap2TRuaXBGASEGQQr01aRSjh4a0kySVOF16eQmjUgAA/8svcujVC6NRFov05FWMRgEIHIIUfOLhYe2VGBclSZr37RHtOX7O5IoAAOFuzvpDOplrdIy9sUcLdWweb3JFACIJQQo+kRAbpceGt5ckOV3S9MWMSgEA/KeguGK3WEajAAQaQQo+85Mr26ppoxhJ0qItGdp6NNvkigAA4eq9bw7rxLlCSdL13VLUJSXB5IoARBqCFHymQbRdE0d2cB9PW/yDidUAAMJVYUnF0ainrmY0CkDgmRqkvv76a910001KTU2VxWLR/Pnzazx/+fLlslgsF90yMzMDUzBqddfA1kpNjJUkfbXzuDYePG1yRQCAcDN34xFlZBv7Fo7qmqxuqYkmVwQgEpkapPLy8tSrVy+98sorXj1u165dysjIcN+aN2/upwrhrRi7TU9f3cl9/JcvdsnlcplYEQAgnBQ7nJqxrGw06mlGowCYxG7mi99www264YYbvH5c8+bN1bhxY98XBJ+4pV8r/fPrfdp/Mk9r953Wqj2nNKRTU7PLAgCEgXmbjuro2XxJ0ojOzdSzVWNzCwIQsUJyjVTv3r3VokULXXPNNVq1alWN5xYWFionJ6fCDf4VZbNq0qhyo1JfMioFAKi/EodT/1i2x3381FWdajgbAPwrpIJUixYtNGvWLH344Yf68MMPlZaWphEjRmjTpk3VPub5559XYmKi+5aWlhbAiiPXTT1T1SXF2M/ju8NntWTHcZMrAgCEugWbj+nQ6fOSpCEdm6pfm0tMrghAJLO4gmSowGKxaN68eRo7dqxXjxs+fLhat26tt956q8qPFxYWqrCw0H2ck5OjtLQ0ZWdnKyGBVqn+9OW2TD361kZJUpeUeH369FBZrRaTqwIAhCKH06Vrpq3QvpN5kqT3HxukAe2STK4KQCjIyclRYmKiz6//Q2pEqioDBgzQnj17qv14TEyMEhISKtwQGNdclqxeaY0lSTszz+mTLRnmFgQACFmffH/MHaKuaJ9EiAJgupAPUps3b1aLFi3MLgNVsFgs+tm1l7qPpy/+QSUOp4kVAQBCUUGxQ3/5Ypf7+GnWRgEIAqZ27cvNza0wmrR//35t3rxZSUlJat26taZOnaqjR4/qzTfflCS9/PLLateunbp166aCggL9+9//1ldffaUvv/zSrE8BtRjSsamuaJ+ktftOa//JPH246Yju6N/a7LIAACHkP6sP6MgZo1Pf0E5NNahDE5MrAgCTR6Q2bNigPn36qE+fPpKkKVOmqE+fPvrNb34jScrIyNChQ4fc5xcVFemnP/2pevTooeHDh+u7777TkiVLdPXVV5tSP2pnsVj08+s6u4//tnSPCkscJlYEAAglp/OK3J36LBbp/43uKouF9bYAzBc0zSYCxV+LzVCzB95Yr2W7TkiS/vemy/STwe1MrggAEAp+u2Cr/rPmoCTpjsvT9MKtPU2uCECoodkEQtpPry0blfrHsr06X1RiYjUAgFCw90Su/rvOmJnSINqmn5ZbdwsAZiNIISC6t0zU6B4pkqSTuYX6z+qDJlcEAAh2z3+6UyVOY+LMY8M6qHlCrMkVAUAZghQCZso1l6p0G6lZK/Yqp6DY3IIAAEFr9d6TWrIjS5KUnBCjR4YxJRxAcCFIIWA6No/XzX1aSZKy84v176/3mVwRACAYOZ0uPbdoh/v4Z9d2VoNoUxsNA8BFCFIIqEmjOinKZgxLvZa+X6dyC02uCAAQbD769qi2HcuRJF3WIkG39G1lckUAcDGCFAIqLamB7uifJknKK3Jo1oq9JlcEAAgm+UUOvVhu891f39hVVivtzgEEH4IUAu6pqzopxm786L255qCycgpMrggAECxeXblPmRf+X7i6S3Nd2bGpyRUBQNW8DlL333+/vv76a3/UggiRnBCr+wa1kSQVljj19692m1wRACAYHM8pcM9UsFktmjq6q8kVAUD1vA5S2dnZGjVqlDp16qQ//elPOnr0qD/qQph7fERHNYy2SZLeXX9Yh0+fN7kiAIDZpi3+QeeLHJKkuwe2VsfmjUyuCACq53WQmj9/vo4eParHH39c7733ntq2basbbrhBc+fOVXEx7azhmaSG0XpoaHtJUonTpZeXMCoFhJz8fCkry3gL1NPOzBy9v+GwJCk+xq5nru5kckUAULM6rZFq1qyZpkyZou+++07r1q1Tx44dde+99yo1NVWTJ0/W7t1cFKN2Dw9tp8S4KEnSvG+PaM/xcyZXBMAj6enSuHFSo0ZSSorxdtw4adUqsytDCHtu0Q5d2HtXE6/qqCaNYswtCABqUa9mExkZGVq8eLEWL14sm82m0aNHa8uWLbrssss0ffp0X9WIMJUQG6UJwztIkpwuY0oHgCA3c6Y0bJi0cKHkdBr3OZ3G8dCh0qxZ5taHkLR813Gt3H1SktSycZx+cmVbcwsCAA94HaSKi4v14Ycf6kc/+pHatGmjDz74QJMmTdKxY8f0n//8R0uWLNH777+v3//+9/6oF2Hm/ivbqOmFvzp+uiVTW49mm1wRgGqlp0sTJ0oul1RSUvFjJSXG/U88wcgUvFLicOpPn5ZtvvvsDV0UG2UzsSIA8IzXQapFixZ65JFH1KZNG61fv14bNmzQhAkTlJCQ4D5n5MiRaty4sS/rRJhqEG3XkyM7uI9f+nJXDWcDMNW0aZKtlgtcm01iRgK88N6Gw/ohK1eS1DutsW7q2cLkigDAMxaXy+Xy5gFvvfWWbrvtNsXGxvqrJr/KyclRYmKisrOzK4Q/mKewxKGrXlyho2eNBesfPj5I/dokmVwVgAry8421UKXT+WpitUq5uVJcnP/rQkg7V1CskS8u18ncIkn8/gfgH/66/vd6ROree+8N2RCF4BRjt+npqzu6j//yxS55me8B+FtOjmchSjLOy8nxbz0IC7NW7HWHqNE9UghRAEJKvZpNAL5yS99Wate0oSRp7b7TWrXnlMkVAaggIcEYafKE1WqcD9Tg2Nl8/XvlfklSlM2iZ6/vYnJFAOAdghSCgt1m1eRrLnUf/+WLnYxKAcEkLk4aM0ay22s+z26Xbr6ZaX2o1V++2KXCEmOU8/5BbdWmSUOTKwIA7xCkEDR+1KOFuqTES5K+O5Ktj787ZnJFACqYMkVyOGo+x+GQJk8OTD0IWd8fOat53x6VJDVuEKWnrmLzXQChhyCFoGG1WvTsDWVTO/706Q7lFpbU8AgAATVkiDRjhmSxXDwyZbcb98+YIQ0ebE59CAkul0t/XFTW7vyZqzspsUGUiRUBQN0QpBBURnZurlFdkyVJWTmF+tvS3SZXBKCCCROklSuNaX6la6asVuN45Urj40ANvtyepfX7T0uS2jVtqLsHtjG5IgCom1omuwOB99ubLtPXu0+oqMSp19P367Z+rdQpOd7ssgCUGjzYuOXnG935EhJYEwWPFJU49efPdrqPf3lDF0Xb+ZsugNDEby8EnbSkBnp8uLFJb4nTpd9+vI3GE0AwiouTkpMJUfDYf9cd1P6TeZKkAe2SdO1lySZXBAB1R5BCUHp8RAelJRkXZ6v3ntKiLRkmVwQAqI/s88X6a7np2r++sassFouJFQFA/RCkEJRio2z6zY+6uY+fW7RDeTSeAICQ9fevduvs+WJJ0s19Wqpnq8bmFgQA9USQQtAa1bW5RnZuJknKyC7QP5btMbkiAEBdHDyVp/+sOSBJirFb9fPrOptbEAD4AEEKQctisei3N3VTtM34Mf33yn3aeyLX5KoAAN564fOdKnYYa10fHtpOqY1ZVwcg9BGkENTaNm2oR4e1lyQVO1z6XxpPAEBI2XDgtD7dkilJatooWo+P6GhyRQDgGwQpBL2JIzuq5YW/Xq7cfVJfbMs0uSIAgCcqb7475ZrOahTDzisAwgNBCkEvLtqm//lRV/fxHz7Zofwih4kVAQA8sfD7DG0+fFaSdGlyI91+eStzCwIAHyJIISRc1y1FQzs1lSQdPZuvGctpPAEAwayg2KEXym2++/9Gd5XdxmUHgPDBbzSEBIvFot/9uJuibMaeI/9csU8HLmzqCAAIPrNXH9DRs/mSpKGdmmpE5+YmVwQAvkWQQsho36yRHh5qNJ4ocjj1u4U0ngCAYHQqt1CvfGXMHLBapF/d2LWWRwBA6CFIIaQ8ObKjWiTGSpKW7TqhJTuOm1wRAKCyl5fs1rkLm6jffnmauqQkmFwRAPgeQQohpWGMvcJfNn+3cJsKimk8AQDBYs/xc5qz/pAkqUG0TVOuvdTkigDAPwhSCDk39mihKzs0kSQdOZOvWSv2mlwRAKDU85/ulMNpTLueMLyDmsfHmlwRAPgHQQohx2Kx6PdjusluNRpPzFy+V4dPnze5KiAC5edLWVnGW0DS6j0ntXSnMeU6JSFWj1xY1woA4YgghZDUsXm8HhzSTpJUWOLU7xZuN7kiIIKkp0vjxkmNGkkpKcbbceOkVavMrgwmcjgrbr77s+s6Ky7aFpgXJ9QDMAFBCiHr6as7qXl8jCRpyY4sLdtJ4wnA72bOlIYNkxYulJxO4z6n0zgeOlSaNcvc+mCajzYd0faMHElS95YJGtenpf9flFAPwEQEKYSsRpUaT/wvjScA/0pPlyZOlFwuqaSk4sdKSoz7n3iCi9gIdL6oRC9+uct9/KvRl8l6Yfq13xDqAZiMIIWQ9uNeqRrYLkmSdPDUef175T6TKwJ8JBinKk2bJtlqmapls0nTpwemHgSNV7/er6ycQknSqK7JGnShIZDfEOoBBAGCFEKa0Xiiu2wX/vL5j2V7dOQMjScQwoJ1qlJ+vrRgwcUXrZWVlEjz5gVXAIRfZeUUuLun2q0WTR3dxf8vSqgHEAQIUgh5nVPidf+gtpKkgmKn/vjJjpofAASrYJ6qlJNTVlNtnE7jfF8JxtE5uL3w2U7lX5hWfffA1urQrJF/X5BQDyBIEKQQFiZd00lNGxmNJz7flqmvfzhhckWAl4J9qlJCgmT18L8Mq9U4v76CdXQObit+OKGPvj0qSYqPteuZUQHYfNfMUA8A5RCkEBYSYqM09Yay6ST/+/E2FZbQeAIhxNdTlU6flrZuNd76QlycNGaMZLfXfJ7dLt18s3F+fQTz6BwkSbmFJfp/H21xH/9qdFclNYz2/wubEeoBoAoEKYSNcX1b6vI2l0iS9p3M02vp+02uCPCQL6cqzZghpaZKTZpIPXoYb1NTjWBSX1OmSI5a/kDhcEiTJ9fvdYJ9dA6SpBe/2KWjZ42fxSs7NNEd/dMC88KBDvUAUA2CFMJGaeOJ0o67f1+6RxnZzI1HCPDVVKXx440AkpFR8f6MDCN43HVX/eocMsQIahbLxRexdrtx/4wZ0uDB9XsdGgkEvQ0HTus/aw5IkmKjrPrzuJ6yWPzc7ry8QIV6AKgBQQph5bLUBN17RRtJUn6xQ39cROMJhABfTFWaMUN6992aH/vOO/UfmZowQVq50hgRKK3ZajWOV640Pl4fNBIIegXFDj374fdyuYzjn13bWa2bNAhsEYEK9QBQA4IUws6UazuryYV5+ou+z9CqPSdNrgiohS+mKv3xj569lqfn1WTwYGnuXCk3V8rMNN7Oneubi1YaCQS9f3y1R3tP5EmSeqU11gOD25lTiL9DPQDUgiCFsJMYF6VnyzWe+O3H21RU4uGFGWCWKVM8G4WpaqrS6dMXT+erzrFjvm1AkZzs2zUoNBIIatuOZbv3jIqyWfR/t/R07+NnCn+GegCoBUEKYenWvq3UO62xJGnP8VzNXk3jCYSxY8f8e34g0UggaJU4nHr2w+9V4jTm9E0c2VGdU+JNruoCf4R6AKgFQQphyWq16A9juqt07fNfl+xWVk6BuUUBNZk2zbPwUFWDhdRU717L2/MDjUYCQenVlfu19agxlbJzcryeGNHR5IoAwFwEKYStHq0SddeA1pKkvCKH/vQpjScQpOrbYCEpSWrRwrPXSk01zg9mNBIIOvtO5Gr6kh8kSVaL9MKtPRVt5xICQGTjtyDC2s+v66xLGkRJkhZsPqa1+06ZXBFQBV80WPj1rz17vKfnmY1GAkHD6XTplx9uca81fXBwO/fUaQCIZAQphLXGDaL1i+vLNZ5YsE3FDhpPIMj4osHCE08Y+0jVZPx46fHHva/PLDQSCAr/XX9I6w8YDUpaJzXQlGsvNbkiAAgOBCmEvdsvT1PPVomSpF1Z5/TmmoMmVwRU4qsGC3PmGFPeKq+BSk017p8zxzf1BhqNBExz9Gy+/lxuWvSfx/VQg+hafk4BIEIQpBD2bFaLfl+u8cTLi3/Q8XM0nkCQ8VWDhccfl44elU6dkrZsMd4ePRpaI1EICi6XS7+at0V5RcbP5Z3903Rlx6YmVwUAwYMghYjQO62x7rg8TZJ0rrBEf/5sp8kVAZX4usFCUpLUvXvwN5ZA0Fqw+ZiW7zohSWoeH6Opo7uaXBEABBeCFCLGL67vosQ4o/HER5uOasMBH21KCvgKDRYQJE7mFup3C7e5j/84trv79ycAwECQQsRIahitn13X2X38Pwu2qYTGEwg2NFhAEPjdwu06c75YknRjzxa6tluKyRUBQPAhSCGi3DWgtbqlGh3PdmTk6L/rDplcEVANGizAJIu3Z2nhd8ckSY0bROl/b+pmckUAEJwIUogopY0nSr345S4aTwDABTkFxfr1/C3u49/86DI1i48xsSIACF4EKUScfm0u0a39WkmSzhWU6JcfbpHL5TK5KgAw3/Of7lRWTqEkaXjHJN2capfy802uCgCCE0EKEWnqDV3UtJHxV9avdh7XnPVM8QMQ2VbvPal3LvwubOgs0nM/v1mWFi2kRo2kceOkVatMrhAAggtBChGpSaMY/d+tPdzHf/xkh/adyDWxIgAwT36RQ1M/KpvS9+yyN9TqbJZx4HRKCxdKQ4dKs2aZVCEABB+CFCLWVV2Sdc8VrSVJ+cUOTX5vs4rp4gcgAk1f8oMOnjovSbr8yDbds+GTiieUlEgul/TEE4xMAcAFBClEtF+NvkztmzaUJH13JFt//2qPyRUBQGB9d/is/r1ynyQpuqRIL3z2N1lVzbpRm02aPj2A1QFA8CJIIaLFRds0/Y7eslstkqR/fLVbGw+eMbkqAAiMohKnnv3wezkv5KZnVr2jDqePVv+AkhJp3jwaUACACFKAeqU11jNXd5IkOV3SlPc3K6+wxOSqAMD/Zi7fq52Z5yRJl2Xt1aPrP6r9QU6nlJPj58oAIPgRpABJj4/ooL6tG0uSDp46rz98st3cggDULD9fyspiZKQefsg6p38s2y1Jslks+r/P/64op6P2B1qtUkKCn6sDgOBHkAIk2W1WTb+jtxpG2yRJ735zWF9syzS5KgAXSU83WnE3aiSlpFTdmruqkBUMwcvfNXjx/A6nS7+Y+72KHcacvseGt1f3QT0ku73mB9rt0s03S3FxvqgYAEIaQQq4oE2ThvrtTd3cx1M/2qLj5wpMrAhABTNnSsOGGa24nRc6bJZvzf2zn10csoYPN241BS9/8yT8Bfj5Z68+oM2Hz0qS2jdtqKev7iRNmSI5ahmRcjikyZN9UzcAhDhTg9TXX3+tm266SampqbJYLJo/f36tj1m+fLn69u2rmJgYdezYUbNnz/Z7nYgct13eStdelixJOp1XpGfnfi+Xq5ruVYg8wTCqEanS06WJE40W3CWV1jCWtuZ+6SXp448rhqyvvzZuVQWvQOyJVFv4q28NdXj+Q6fO68UvdrmPX7i1p2KjbNKQIdKMGZLFcvHIlN1u3D9jhjR4cP1qBoAwYWqQysvLU69evfTKK694dP7+/ft14403auTIkdq8ebMmTZqkhx9+WF988YWfK0WksFgsen5cDzVtFCNJWrbrhN5ed8jkqmA6f48ooHbTphmtt2tT24iKFLg9kTwJf/WpoQ7P73K5NHXe98ovNr5O9w1qo/5tk8oeN2GCtHKlNGaMsRZKMt6OGWPcP2FC3WoFgDBkcQXJn9stFovmzZunsWPHVnvOs88+q0WLFmnr1q3u++68806dPXtWn3/+uUevk5OTo8TERGVnZyuBxbKoxrKdx/XA7G8kSbFRVi16eqg6NGtkclUwxcyZxsWqzVbxYtVuNy7aZ8zg4tLf8vON8Or08YbZNpt0001GO29/GDfOGBmqHHLKs9uNkDJ3bkCe//1vDusXH34vSUpNjNWXU4arUUw166Ly843ufAkJrIkCENL8df0fUmuk1qxZo1GjRlW477rrrtOaNWuqfUxhYaFycnIq3IDajOzSXPde0UaSVFDs1OT3NqvY4eOLOAQ/f48owDM5Ob4PUZIRhOfPN4KGr7+H+fnSggU1hxyp7vsy1eH5s3IK9IdFZR1JnxvXo/oQJRnhKTmZEAUA1QipIJWZmank5OQK9yUnJysnJ0f51fwn9PzzzysxMdF9S0tLC0SpCAP/b3RXtW/WUJL0/ZFs/W3pbpMrQsB5Mp3MZpOmTw9MPZHK37MHFi3y/Zopb8JfXfZl8vL5XdnZ+p/5W3WuwAhe4/q01MjOzb17TQBABSEVpOpi6tSpys7Odt8OHz5sdkkIEXHRNr18R2/ZrRZJ0ivL9mjjwdMmV4WA8feIAjzn76+tw+H70cWEhLI1RrWpy75MXj7/Z0cL9eX2LElSk4bR+p8fXebd6wEALhJSQSolJUVZWVkV7svKylJCQoLiqpl6EBMTo4SEhAo3wFM9WzXWpFGdJElOlzT5ve+UW1jLhTXCg79HFOC5Y8cC8zq+HF2MizOmDPprXyYvnv/sLXfoN5/94L7rd2O66ZKG0d69HgDgIiEVpAYNGqSlS5dWuG/x4sUaNGiQSRUhEkwY3kH92lwiSTp0+rx+v3CbyRUhIPw9ogDPpaYG5nV8Pbro732ZPHz+Pwz7iU7mFkmSrrksWTf2aFG31wMAVGBqkMrNzdXmzZu1efNmSUZ7882bN+vQIaPd9NSpU3Xfffe5z58wYYL27dunX/ziF9q5c6dmzJih999/X5PZHBB+ZLdZNf323moYbayVeX/DEX2xLdPkquB3/h5RgOeSkqQWAbr49+Xoor/3ZfLg+Ve89Lo+PFIsSYqPteuPY7vLYrHU7fUAABWYGqQ2bNigPn36qE+fPpKkKVOmqE+fPvrNb34jScrIyHCHKklq166dFi1apMWLF6tXr1566aWX9O9//1vXXXedKfUjcrRu0kC//XE39/EvP/xex3MKTKwIAeHvEQV47te/Dszr+Hp00d/7MtXw/LnLvtb/K2ztPvVXo7sqOSG2fq8HAHALmn2kAoV9pFBXLpdLE97eqC+2Gev0RnRupjd+0p+/7oa7WbOMJgTsI2W+u+6S3nnHf89fnz2dPOHvfZkqPf+v52/R22uNP0YOat9Ecx4ZyO8rABGJfaQAk1ksFj0/rqeaxcdIkpbvOqG31x40uSr4nb9HFOC5OXOM4OqvNVP+Hl30975M5Z7/4++OuUNUbJRVf76lByEKAHyMESnAS8t2HdcDb3wjybhA+eSpoerYvJHJVSEg/D2iAM/t2SN16uSb57LZjLVRYTK6uDvrnMa8skrni4xpqc/d3F13D2xjclUAYB5GpIAgMbJzc903yLgoKSh2avJ7m1VU4mGbbIQ2f48owHMFdVyjWFUnRodD+ulPwyJE5RaWaMLbG90halzflrprQOtaHgUAqAuCFFAHU2/oqg7NGkqSthzN1t+W7ja5IiAE5OdLWVm+aS9e1+l91e0N9tJLvtuM1yQul0vPfvi99p7IkyR1SYnXc2OZ0gcA/kKQAuogLtqml+/oI7vVuECZsXyPNhw4bXJVQJBKT5fGjZMaNZJSUoy348bVL7j4uiV65c14vQl9vgyI9TB79QEt+j5DkhQfY9fMe/op7sK2DQAA3yNIAXXUo1WiJl9zqSTJ6ZImv79Z5wqKTa4KCDIzZ0rDhkkLF5aNBjmdxvHQoUZXxLryZUv00s14ly71PPT5IyDW0caDp/Xcoh3u4xdv76V2TRsGvA4AiCQ0mwDqweF06Y5/rtGGg2ckSbf1a6W/3NbL5KqAIJGeboSomv6bsViM7od13ZTWHy3R7fbaW93PnClNnBgUbfFP5hbqxr+tVFZOoSTpsWHtNXV014C8NgCEAppNAEHIZrVo+h291fDC9JkPNh7R51szTK4KCBLTphlBoyaVp9R5q7QletOmdX+OysoHo9Jjl8vYT2zVKiMgTpxo3FfbuX5W4nDqqTnfukPUgHZJ+vl1nf3+ugAAghRQb2lJDfS/P+7mPp760RYdz6ljRzEgXOTnSwsWXBw0KiudUlef9UWPP25ME6yqI5+nPGnIUBr6AhEQPTRt8Q9as++UJKlZfIz+cVcf2W381w4AgcBvW8AHbu3XStd3S5EknTlfrJ/P/V4RNmsWqCgnp/oOeZU5ncb5dVUa2jx9vap48u+1NPTNnx+YgFiLJduzNGP5XknG6Pgrd/VV8/hYv70eAKAighTgAxaLRX8a10PN4mMkSSt+OKG31h40uSrARN7OQa/PnHVvQltldrtno1GlnE7PQlfpufUJiDU4dOq8Jr+/2X089YYuGtAuyS+vBQCoGkEK8JGkhtF6sVyjiecW7dCe4+dMrAgIEH+3/67t+aOivAtDpVMArVZpzBhpyRLPpwVarZ6/ltVav4BYjYJihya8vVHnCoxRsRu6p+ihIe18/joAgJoRpAAfGn5pM90/qI0kqbDEqUnvbVZRST2mGwHBqDTY1NQq3NuRmKrOr629eOnHmzXzbJTIbpduuUXKzZUyM423c+dKV11lBCq7vfbH33yzNHas5+fGxdVel5d+s2CrtmcYX6/2TRvq/27tyaa7AGAC2p8DPpZf5NCP/r5Se0/kSZImjuygn1/XxeSqAB9ITzcaLZRfj2SxVAwxpe2/X35ZmjzZsyl3VqsRasqHjtrai99xh/Teexd/vCY1tVr3plW7y+X/tu7VeO+bQ3r2wy2SpLgom+ZPHKzOKfE+fQ0ACDe0PwdCRFy0TX+9s4/sVuMvxDOX79U3B06bXBVQT1VtrCtdHCZK239PmiQNGVK3kRtP2ou/+27VH6/uNSwWo016dcFmyBDj4xbLxTVXfrw35/rQ1qPZ+p8F29zHz4/rQYgCABMRpAA/6N4yUZOvuVSS5HRJk9/brHMFxSZXBdRRTcGmOjabESgcjprPcziMkavyPGkv7qnSdVArV9a+Qe6ECcZ5Y8ZcvI6q8uO9OdcHss8X6/H/bnRPFb73ijYa26elT18DAOAdpvYBfuJwunTnv9bomwNnJElXdWmuV++7XDYraxkQYsaNM0aiPA1RpaxWYy+lSZOqn6I3Y0bF0JGfb6yFqk8r8/Kvf+KElFSHbnb5+ca6rYSE2tc5eXNuHTidLj3y5gYt3XlcktQrrbHef+wKxdh9FDYBIMwxtQ8IMTarRdNu763EuChJ0lc7j+uPi7abXBXgJU831q2K02msZfJm5KY+rcyrev3iOo4Ex8VJycmeBSNvzq1ODZ0JZ67Y6w5RlzSI0oy7+wY+RPm7MyMAhCCCFOBHaUkNNPOevu71Um+sOsD+Uggt9Qk2pe2/Bw82uuNV7pZX1RqihATPW5F7+vrBrJbOhKv2nNRLX+6SZMyUfPnOPmrZ2PejXnWtDwAiGUEK8LMrOzTVczd3dx//78fbtOKHEyZWBHihrsGmqiYSnozcxMUZo1X1beftx/bjPlNVAw+n0zgeOlQZ/3hVT7/zrZwXJuBPuvpSDb+0WdDUp1mzAlcLAAQhghQQAHf0b63HhrWXZKydevK/m/RDFpv1IgSUBpvauu9VVlUTCU+VNraoj8qvH2xT02rpTFhksWniumydyiuSJI3o3ExPXdUxaOqTyyU98QQjUwAiGkEKCJBnr++iay9LliSdKyzRg7O/0cncQpOrgimC7aK+NlOm1N59r5Qv2n937177OZ6+frBOTaulM+GfRj6oTS27SpJaNo7T9Nt7yxrIRjWedE602YxmIgAQoQhSQIBYrRa9fGdvdW9prNk4ciZfj765QQXFHl6gIvQF60V9bUr3TaqNxeKb9t8JCd5N7auuiUWwTk2rpYHHx12HafblP5YkRZcUa+Zt3XRJw+igqc+tpESaNy90/iAAAD5GkAICqEG0Xf++r7+SE2IkSZsOndWzH36vCNuFIDIF60W9pzwZJXK5jOl09d2IduNGz6b22WzSLbdU3cQimKem1dDAY0+TVvrl9U+5j3+75J/q2ShQhV3gTYMRp9M4HwAiEEEKCLCUxFi9dn9/xUUZ02YWbD6mvy3dY3JVuIgvp98F80W9p6ZNq32dlN3um6lef/mLZw0uStdBVdXEwhdT0/w1BbOaBh650XF67OZf6Xy08XmM27JUd235MvCdB71pMBIKnREBwE8IUoAJurdM1F/v7O2evTR9yQ/6+Ltj5hYFgz+m34X6epOjR40pXP6e6pWebkzN+/hjz0ZELBapb9+L76/v1DR/T8GsooGHS9Ivr39Ke5ukSZK6HN+v5776pyzVdR705zo7TxuMhEJnRADwI4IUYJJru6Vo6g1d3Mc/++A7bTx4xsSK4Jfpd6G83mTGDCk1VWrVyvPH1HWqV+nXftEizx/jclX9WvWZmhaoKZiVGnjM7neTPuk6TJIUX5inmfOfV1xh/sWdDwO1zs6TBiP16cwIAGGAIAWY6JGh7XXH5cZfoItKnHr0zQ06fPq8yVVFKH9NvwvV9Sbjxxtfj4wM7x5Xl6le5b/2nnYHrOm16jo1LZBTMEsbeFgs2ti6m54b+ZD7Q3/5/G9qdzbj4s6HgVxnV66+i0amfNGZEQDCAEEKMJHFYtEfxnbXoPZNJEmn8or00H++UU5BscmVRSB/Tb/zxXqTQLdLnzFDevdd7x9X16lennztvXmtuk5NC/QUzAkTdHLJCk287TcqsRm1Prb+I13fLeXizodmrLObMMGoY8yY6jsjAkAEs7girF1YTk6OEhMTlZ2drQQWyCJIZJ8v1s0zVmnfyTxJ0rBLm+n1+y+X3cbfOgIiP9+YIuXJyJHVanSH8yYsjBtnjBrUNL3PbjcuUOfOLbsvPd24uF+wwKit9CL2pz/1bCQgP98Y4UpI8K7e1FTvR6IkY5Ri5UrvRim8+dp781rp6cboTW3/xaWnG8/h75+BKjicLt372jqt3ntKkjSgeYzm3NdH9qZNLj65rj9DvlLXnyUACAL+uv7nKg0IAokNovT6T/qrcYMoSdLXP5zQ7z/ZbnJVEcTf0+/qst6kPtO46rOO5vRp70NUXad6pacb7cu9DVGSdOedNb9WTVPTSlks0ksvGV8XE6ZgTlu8yx2imuWe1j9+c5vsyc0v/l4Fwzq7qjojAkCEI0gBQaJt04b65z39FGUzWvm9ueagZq/ab3JVEcLf7Z69XW9Sn2lc9V1Hc6wO3SPrMtWrtM4vv/T+9SRj6mFtwbD81LSqNvh1ucq+Lu+9F9CW30u2Z+mVZXslSTanQ68seEHN885W/b0K1XV2ABDmCFJAEBnYvomeH9fTffz7T7Zr2a7jJlYUITxdU2OzSTfcULfX8Ga9SV3X6vhiHU1qquefkyQdOVK2Ca6n6tpcojxP1yoNHixNmlT9x0u/LpMmGYE3AC2/D506rynvbHAf/3L5bA04su3imkq/V+zrBABBiSAFBJlb+7XSEyM6SJKcLumpOd9qV+Y5k6uKAJ5Ov1u0qO4tpwcPNkJHbq6UmWm8rRxC6jONyxfNEpKSpBYtav9cJCN0tWzp2bnl1aW5RGXeTGPz9Otisfi95ffZ80V69K0NyrnQT+b6Xav08Dfzqq9p+nT2dQKAIEWQAoLQz67trNE9UiRJuYUlenD2NzpxrtDkqsKcJ2tqStW35XRN603qOo3Ll+tofv1rz17f0/PK87ROT3gyjc2br8vKldLLL/ut5fe5gmLd//p67bzwh5F2p4/qL5++rComHZbVVPq9Yl8nAAg6BCkgCFmtFr10W2/1apUoSTp6Nl+PvLlBBcV1nAYFz1Q1/a46/mo5XddpXL5cR/PEE8Y+UjUZP156/HHPXq88b+qsjdVqhIyaQqG3X5c77vBLy+/8Iocemr1B3x3JliQ1zT2j1+f+TvFFtYyolX6v2NcJAIIOQQoIUnHRNr163+VqkRgrSdp8+Kx+9sF3cjojaseCwCs//W70aM/WTflqXyHJu/VaN95YNqrl63U0c+YYF+aV10ylphr3z5nj2WtV5k2dtXE6pXbtqp9qOWOG1Lu3589X+nXxZAqmFwpLHHr0rQ1af+C0JOmSuCj994P/UbszHjT2KP+9Yl8nAAgq7CMFBLntx3J066zVOl9kjEY9fVVHTbm2s8lVRQAT9hVy83QPJMlYz/Q//2OMDnm715CnewOdPm1087vkEuPx9d1LaNy4sr2xfMVuN6a2zZhhBIrx473bVNhPezAVO5x64r+btHh7liQpPsauOY9coR5PP1C/faHY1wkAPMY+UkCEuiw1QX+7s4+7e/Pfvtqjed8eMbeoSGBmy2lv1mtlZBhT8e66y/N1NFdd5d0+U9u3S7/5jdS6ddn5Y8YYQaAuexaNGuXbECVVnGo5ZYp3IUryy/oih9OlKe9/5w5RcVE2zX6wv3q0Sqz/mif2dQIA0xGkgBAw6rJk/Wp0V/fxs3O36JsL04TgJ95OlYuKkrKyfLcZam17IFX2zjvSli21r6O54w7pyScv3mfq44+rbp5R3b5UH38s/fjHUsOG3ncwXLLEd9P7KrPZjJq9OV/y+foip9OlqR99r4XfGdP3ou1W/fv+y9WvTZJxAmueACDkEaSAEPHQkHa6a2BrSVKRw6nH3tqoQ6fOm1xVGPNmrVJKitSsmWejO94oXauTnOzZ+X/8Y83raP7xD2Pj2ar2mXI4jPsff7wsiNS0L1Upl6v6EFaV0i56vh6RKlVSIhUUeH6+w2F8fb780mdNQ1wul37/yXa9v8EYObZbLZp1T18N7ti04omseQKAkMYaKSCEFDucenD2N1q5+6QkqWPzRvrw8SuVGBdlcmVhKj3dCAi1sdkqTtOqvF6nPk6flpo08fz8U6eMvaCki9fReLKGqtTMmUa48PR8yRhFWbmy5lGUrCwjcAYbH33PXC6X/u+LXZq5fK8kyWqR/j6+r27sWcveXKx5AgC/YY0UAEXZrPrHXX3VsXkjSdKe47l6cs4mFTv89Nd9eKbyWhdftkY/5kFnt+rOL7+Oxtv9mx5/XJo/37v9njzpYJiQ4NlUxUDz0ffslWV73CFKkv5ya6/aQ5TEmicACEEEKSDEJMZF6fX7+yupYbQkaeXuk/rfj7cpwgaXA2PatNqn9tXEF63RK7cfr+v53u7fZLV61jWwvNo2+01Pl+6+2/vn9YbdLsXG1v3x9fievZa+Xy9++YP7+A9ju+uWfq3qXgsAIKgRpIAQ1LpJA/3r3n6Kthn/hP+77pBeX3XA3KLCjbcjOFWpLVh4IinJaHHuidTUsml9lXm7f1Nd1zBV18GwfNMKf3I46rZRcKk6fs/mrDukP3yy3X38q9Fdde8VbepWQ36+bxuXAAD8giAFhKjL2ybp/27t6T7+46LtWrojy8SKwoy3IzjV8UVr9F//2rPzJk2Stm6Vjh69+EK8tHlGaZc6T3l7flWb/XrStKJUace6mTOlDh08f93yne6mTZNuu827usvz8ns279sj+tX8Le7jSaM66ZFh7b1/3fR079rSAwBMRZACQtjYPi319FUdJRnXqE+9862+P3LW3KLChbcjONWpKlh464knjA1maxIbK/3iF1KPHlKrVsaFeOXW5FOmeD+9r7a9jsqz26Wbb754nc+0aZ4HstLugl9+Ke3b59ljLJayTnfduxuf84cfel53ZV58zz7fmqGfffC9e7biY8Pa65mrO3n/mtW1mV+40POOiACAgCJIASFu0qhL3YvZzxc5dPer67Ru3ymTqwoDnrY/r0l1waIu5swxRlsqr4GKiTHeVtXy2+UyGkaUXoiX7l3kCYvF2CfqhReMY0+CUOkGsuWnpnkzRdJqNWot3eeqprVUpSNQL7wg5eUZbeK///7iMFIXKSnSpk21nrZs13E99c63cjiNOu+9oo1+eUMXWbxtplHTiJ0vG5cAAHyK9udAGCgodui+19Zr/YVNemPsVs28p6+u6uLh/kOoWnq6cWFe11+TnrQDr4tPPzVGeZYurVstd95p7CflyWNcLiPgpKRU30GwtHX4lCnGKFLpPlFWq9S6tXTggOd1esJqNQLq5MllX9v6fq/Ks9mM+mtohb5m7yn95I31KiwxAtut/Vrp/27pKau1Dh0JPWlLb7cbwX7uXO+fHwAinL+u/wlSQJjIL3Lo8f9u1PJdJyQZm4C+dHsvjend0uTKQtysWcZogM1W8ULXbi87Lv9+6bGv9pGqbOZMY/Sicj21KX8h3rSpsd+UN0o/pzFjpHXrpIyMso+lphoh5r33vK+rssp7clX18ZtuMhpClOfNHlmeqiYIbzx4Rve+tk7ni4w6b+zZQn+7s49sdQlR+fnGWihPRtCsVik3lxbpAOAlgpSPEKQQzopKnJry/mZ98r1xkWuxSL8f073u3cNgWLXKaIk9b17ZSEvpiIhU/cd8PRJV31EXq1U6dMhYQ1UfVmvFC//awo8nKofR2l6/fKA4fVpq1sw3zUEq11RpFGjr0WyNf3WtzhUYtV7dpblm3tNP0fY6zpT3doPizExjvykAgMf8df1fj8n/AIJNtN2qv97ZRwlxUZqz7pBcLul/5m9VTn6xnhjRwfu1GzAMHmzc8vONbm4JCRVHBWr6mC+VNm2o66iL02l09auvyoGlviHK2+co7aq3caPxNak8OuUr5Vuhx8Vpd9Y53ff6eneIGtyxiV65u2/dQ5RU1tTE0xEp/gAIAEGDZhNAmLFZLXpubHc9PqKsdfRfvtilP3+2k0176ysuzhgNqCoo1fQxX/DFvlZWa/COZvzhD553SbRapXffNUbnFizwb10XQtuBk3m6+9/rdDqvSJJ0eZtL9Op9lys2ysv28JV52tTEl41LAAA+QZACwpDFYtGz13fRs9d3cd/3z6/3aepHW9wdxhBg3m6yWvn8+u5rVXoh3rlz3Z/Dn6ZM8TxQDB1qTJ10uXw/na8yq1VHXdG6+9/rdPxcoSSpR8tEvf5AfzWI9tGkjilTah+RK+2ICAAIGgQpIIw9PqKD/nRzD5XO6Hv3m8N6+p1vVVTi54tPlPF2k9Xqzt+2rX77WpVeiMfFSYmJdX8efxg92giKEyd6FihKOwnWVWlYq+057HYdv/Uu3f3WZh09awTazsnxevPBAUqIjar761dW2pbeYrk4SJbfaNjXa+4AAPVCkALC3F0DW+tvd/ZRlM1IU4u2ZOjhNzfofJEPu5uhat5uslrT+aNGST17er+vlcVS8UK8dC1XMPn0UyM0Xnut1KuXcV/lz9NmMz6Pp56Svv66fuuyfvQj6ZVXam3acTq6oe7peZcOnDovSWrftKHeeniALmkY7dnreDMKOWGC0SFwzJiygGe1lm007OvujwCAeqNrHxAhlu86rglvb1RBsXGB3q/NJXr9J/2VGOfDv6yjjCcd9sq3105PN8KVL1ksxmhW+Q6C3naJC7TSxgt9+kjffeefqXulne9qaG2fY4vRXb94S1uLjNDUsnGcPpgwSKmNPVijlJ5uNMEov5/WmDHST3/q2ahSIBqXAEAE8df1PyNSQIQY0bm53npooOJjjL/0bzx4Rnf+a61OXFj3AR8r7bBXE5vNaJ2eni7dfnvtz2m3GwGjuilgkvTrX0tHjhhhIS/PaN1d/uI92P+AVBqcvv3WeL+2r6G3yne+q2YUKG/sLXrgd3PdISo5IUZzHhnoWYjydhSyKv5uXAIA8AlGpIAIs/Votu5/fb1OXeg+1rZJA7398EC1uqSByZWFEW82WS1dwObpr2KrVVq82JiqV3nvqocektLSjA1yk5KqfvzMmcYoTKS65ZYK+0K5XRgFKmjQUA++u1Wr9xobFic1jNb7j12hjs3ja39ub0chAQABwYgUAJ/o3jLRmKKUGCtJOnDqvG6duUZ7jp8zubIw4k2HPZfLuw12nU6pWzcjDOTmGiNPL71kNK8YPVrq0UNq0sQIUzNnVnxsenrdQtRHH3n/mGB19dVV3x8Xp6ImzfTEhzvcISoh1q63HhrgWYiSvBuFBACEPIIUEIHaN2ukuY9fqfbNGkqSMnMKdPs/12rLkWyTKwsTpZus+kP5qWlxcdLddxtroDIzK56XkWGEprvuMo7z86U//alsBMwbnTrVr+ZgYbVKS5dW+aH8IoeeemeTvtp5XJLUMNqm2Q8OULdUDzscerrPV/lNfgEAIY0gBUSo1MZx+uCxQere0rgoP51XpPGvrtXafadMriyIedqFzdNNVr1ls1XclPXOO6sNBm7vvGOsq2rUSPrsM+9Gv0qlpvovGAaS01lliDl8+rxumblaX2zLkiTF2K167Sf91bf1JZ4/tzejkBc2+QUAhLYw+J8RQF01aRSjOY9coQHtjPU0uYUluv/19Vq6I8vkyoKMt3tBSZ5tsuqt8puypqdL773n2eM2b65797s+fYz1Vj171n6uzWa0L7dYfN8kwldKQ8yePdJHHyl9xXe66R/p2p5hBJuG0Tb9677LdUX7JhUfV1uI9mYUsvyoIgAgZBGkgAiXEBulNx8coKu6NJckFZY49ehbGzX/26MmVxYk6tqFrbZNViXvp9lZLFLfvsb7f/6zd4+tq2+/NT6PzZtrP9fhkLZsMb4uQ4b4vbQ6a9FCrk6d9Oqf39Z9iw7q7PliSVK7pg01f+JgDb+0Wdm5noZoT0ch7faKo4oAgJBFkAKg2Cib/nlvP/24V6okyeF0afL7m/XWmgPmFma29HRp4kRjOlzltS8lJcb9TzxR/chUTZuspqdLY8d6N3LjchmjKfn5xjS9QLDbpeee83yaotMprV5tbJr79NP+ra2O8m3Reuamn+m5qx6S02p8/a/as17zZz6mTjpfNurkaYguHa2aOLH2Ucjyo4oAgJBG+3MAbk6nS7/5eKveXnvIfd/Prr1UE0d2lKUuTQpC3bhxxkVzTQ0E7HYjGFXVUru8qjZZ9aRddnlWq9GpLycnuDfVLWWxSM88I738svF+EPx3czgxWY/e/CvtSG7vvu/pVe9oUvocWXWhPqvVGFH7+uvan3DYMOP7WNqGvmdPY/TObr9ok185HMbo3oQJvv2kAAA18tf1P0EKQAUul0svfrlLryzb677vkaHt9P9Gd42sMOXNXlClAacu07VmzZIef7z288oHNm9qCwbDhpXtn2RGzRdCXHqbXnpyzLM6G2f87m9YeF4vLZqu63evqfYxnj63W2mA6tNH+u67ivt8TZ7M/lEAYAJ/Xf/7uKUUgFBnsVj08+u6KDEuSn/6dKck6dWV+5WdX6znx/WUzRohYaouXdjqEqQ8/VtW+SlhcXHSDTdIixZ5/3pmWLXK+Bq9/LL04x9L7dv7ZnQqMdH4uttsFUd/KoUbl8ulVwfcrD8P/4l7Kl/7U0f0z3nPqdOpw1U/t6f1VT6vtI7Nm6UlS4w9v8qPQgIAwgZrpABU6dFhHfTncT1Umpve33BET87ZpMISH3eiC1aB6MJWugbLE716VTx+9FHvX88sDocROCZNMppR+GoixNSpRlipvAZt3DgjtEnKt8fomZt+pj+NLFsPdfWe9Zr/5pTqQ5Qv2GzGNL7kZEIUAIQpghSAat05oLX+cVdfRdmMNPXZ1kw9/J8NOl9Uy6aj4SAQXdimTfO82cTWrRUbHFxzTd021zWTzSa9/rrv9qT65S+Nr4PTKS1eLO3YIa1bJ/3rX9KKFTqc1ELj7vmLPr5shPshT696R69++AclFJ33TQ3VYeNdAAh7rJECUKsVP5zQY29tUEGxMdWtb+vGev0n/dW4QbTJlfmZp80ghg2T/vQnozV55YYS1anrOqfStUaDB0utWklHQ6xNvdVa/2mJVmvFr1vlY0kr2/bWUz/+RYX1UNMWTdN1u9fW/XXrIjPTGJWqrKrmIwAAv/DX9T8jUgBqNfzSZnr7oYGKjzVGZzYdOqvrX16pr384YXJlPlZ509Wa9oIqb9Uq49yGDT3fsNebNVjluVzS7bcbzx1qIUoyPufbb6//c1Rz7JL0zwHjdP9tv3OHqPanjmjBW1MCH6KqmvJZl82dAQBBKSiC1CuvvKK2bdsqNjZWAwcO1Pr166s9d/bs2bJYLBVusbGxAawWiEyXt03Se48OUtNGMZKkzJwC3ff6ev16/pbQn+pX08Vt6V5QNXVbK907qHTkypMNe71Zg1XZsWPBveFtbV57zS9Pez4qRk/f9HM9P/LBi9ZDdTx1xC+vWaOUlIqjTXXd3BkAEJRMD1LvvfeepkyZot/+9rfatGmTevXqpeuuu07Hjx+v9jEJCQnKyMhw3w4ePBjAioHIdVlqghY+NVhDOjZ13/f22kMa/deV2njwtImV1YMnF7eDB0tJSd5tnlvbhr2ersEKR57sz+Slw4nJGnfPi1p42XD3fU+vmuOb9VBNmtTtcceOlY1u1ndzZwBA0DE9SE2bNk2PPPKIHnjgAV122WWaNWuWGjRooNdff73ax1gsFqWkpLhvyVXNPwfgFy0S4/TmgwP0+zHdFBtl/Ao5cOq8bpu1Ri98vjO0uvp5enH71VfSggVlI0/esNmkF1+sOGWw1JQpdXtOVLCybW/ddP907WzeTpLUqPC8/vnRHzWl/Ca79ZGdXffH5uQYbz1pLGKzSdOn1/21AAABZWqQKioq0saNGzVq1Cj3fVarVaNGjdKaNVVskHhBbm6u2rRpo7S0NI0ZM0bbtm2r9tzCwkLl5ORUuAGoH6vVovsGtdWnTw9Vn9aNJUlOlzRz+V6N+ccqbT8WIv/OPL24nTat7hvJlpRI8+dXvR6m/BoseK269VDzfbEeqlOnsvcrh2xvlJQYAXrBgtqfh05/ABBSTA1SJ0+elMPhuGhEKTk5WZmZmVU+pnPnznr99de1YMECvf3223I6nbryyit15EjV89+ff/55JSYmum9paWk+/zyASNW+WSN98Ngg/fy6zu4W6Tszz2nMK+l6ZdkelTjqGD4CwZuL20WLfNOy2+k0LpSHDClbDzNhgrEXErxyPipGT/34FxXWQ43ava5+66EsFunGG6WlS6Xu3X0z7fLMmbpt7gwACHqmtj8/duyYWrZsqdWrV2vQoEHu+3/xi19oxYoVWrduXa3PUVxcrK5du2r8+PH6wx/+cNHHCwsLVVhY6D7OyclRWloa7c8BH9t+LEdT3t+snZnn3Pf1bd1YL93eW+2aNjSxsmpkZRmjRJ6Kj5fOnav9PG+kpxvrrw4ckNq18+1zh7FDicl6dNyv3VP5JOmZ9Dl6ZtU7dZ/Kt3691KGDVFwsRUVJzZrVfRSyvFOnjPVwnra6t1ql3FxaogOAD4Vl+/OmTZvKZrMpKyurwv1ZWVlK8fACJyoqSn369NGePXuq/HhMTIwSEhIq3AD43mWpCVrw5GA9PqKDrBdmqm06dFaj/7pSb605oKDbss7brnm+DlGS9OSTvn/OMGesh3q5wnqof334B01eVc/1UL/+tRGeUlJ8F6JSU40mJYHY3BkAEHCmBqno6Gj169dPS5cudd/ndDq1dOnSCiNUNXE4HNqyZYtatGjhrzIBeCjGbtOz13fRBxMGqU2TBpKk/GKH/mfBNt33+nplZAfR2o9g6Jq3ebMxxZA/8NTKJWnWgFt0/22/U3ZcvCSp/anDmv/mFF27p/bZC7VaurRi10Zf+PWvy973pLGIwyFNnuyb1wYA+J3pXfumTJmiV199Vf/5z3+0Y8cOPf7448rLy9MDDzwgSbrvvvs0depU9/m///3v9eWXX2rfvn3atGmT7rnnHh08eFAPP/ywWZ8CgEr6tUnSp08P1T1XtHbft3L3SV07/Wt9tOlI8IxOBUPXvIMHjelk3oiw5hTno2L05I9/oT+PfKDceqi1mv/mT9XxtI/2h/L1z8H48dLjj5cd17S5s91u3D9jRs37lQEAgorpQeqOO+7Qiy++qN/85jfq3bu3Nm/erM8//9zdgOLQoUPKyMhwn3/mzBk98sgj6tq1q0aPHq2cnBytXr1al112mVmfAoAqNIyx649je+g/Dw5QcoKxie+5ghJNef87Pf72Jp3KLazlGQKg9OLWTLm53k8zbN7cf/UEmRXt+urH903Xoq7D3PdNSv+v/vXRc/XfH8oXmjateJyaavxMzZlz8bmlmzuPGVP2/bZajeOVK42PAwBChqnNJszgr8VmAKqXfb5Yv/14q+ZvPua+r2mjaD0/rqeuuczkfeBmzjT2ijLLqVPGOppx44yOfpAkbW/WTs+PfEAr2/V139eo8Lymf/Kirtmz3sTKZLTEdzqNwDRhgnT6tLH5bumaKE/k5xvd+RISWBMFAH7mr+t/ExcHAIgUiQ2i9PKdfXRttxT9at4WnTlfrJO5RXrkzQ26tV8r/eamy5QQGxX4wko35DVT6UV027amlhEsMuKb6KWh9+jD7lfLZSkbpet17Ae9tGia76by3Xij0da+LpKTpfffL5uGl5TkeYAqFRdHgAKAEEeQAhAwo3u00OVtL9HUD7do6c7jkqS5G49ozd5T+sttPXVlh6a1PIOPlW7IW58NV+srJ8e4oH73XfNqCALnouM0a+Cteq3/GBVExbrvb3U2Uz//+k3dtGNl/bryVTZypPTZZ3VrLJGZKfXtW/t5AICwxtQ+AAHncrn0wYYj+v0n25VbWBZiHhjcVs9e30WxUTb/F5Gf7/nePv5SumdQfr7UpIl5dZio2GrTu72u08uD79Kpho3d9ycU5Oqp1e/pvk0LFePwQ9C1WKShQ6XVq+sWpDMzjZEpAEDQY2ofgLBhsVh0e/80DerQRD/74Dut239akvTGqgNa8cMJTbu9t3qnNfZvETk55oYom026/nrj/WPHaj43DLkkfdnpCr0w/Cfa16SV+/4oR7Hu27RIT61+V40Lcv1XgM1mhKm6dOuzWmlZDwBgRAqAuZxOl95YfUAvfL5TRSVGsLFZLZo4ooOevKqTou1+ai6any81aOCf5/aG1Spde630+edmVxIw37a4VM+PfFDr07pXuP9HO77WL1b8R62zs6p5pI9ZrdL06dKkSZ5P8bTbjS57c+f6vTwAgG/46/qfIAUgKOw5fk5T3v9O3x/Jdt/XLTVBvx/TTf3aeLmQ3xNHj0qtWtV+XiBYLFIE/Co+lJis/xt+vz4p18pckvof3qb/t+w19cn4IfBFZWZKe/YYgWrevNpHKS0Wo1U5+z0BQMggSPkIQQoIXsUOp15Ztkd//2qPHM6yX0290xrrwSHtdEP3FEXZfDRCtXy50XAAfnc2tpH+fuWderPvjSq2lXVnbH/qiJ5dMVvX7l4rU7YYLl2jVto9Lz9f+vvfpWefNUaeyo9Q2e3GNMDSlucAgJBBkPIRghQQ/LYcydbk9zdrz/GKa2RSEmJ135VtNL5/a13SMLp+LxJMI1JhqtBm15t9b9Lfr7xDObGN3Pcnnc/W5PT/6s7vvlCUsw5rlHyhpil6q1ZVHKGyWqWbb5YmT2YkCgBCEEHKRwhSQGgoLHHo483H9PqqA9qRkVPhY7FRVo3r20oPDm6rjs3j6/4isbFSYWE9K0VlTlm0sOtQ/WXYfTrSOMV9f0xxoR7+Zr4mrJur+KJ8EyuUZ1P02DQXAMICQcpHCFJAaHG5XFq777ReX7VfS3ZkXbSUaNilzfTg4LYa1qmZrFYvJ4hNmWKMPMBn1rXqpj+NfEjfpV7qvs/icmrc1q/005VvK/XcSROrkxGgpMBM0SOIAUBQIEj5CEEKCF0HT+Vp9uoDev+bw8orqjglrEOzhnpgcDvd0reV4qK92IeqXz9p0ybfFlp5fU0E2JPUSn8e8RMt6XRFhfuHHPhWU5e9rm7H95tUWRWWLpWuusp/z5+ebmz2vGBB2dTAMWOkn/6UqYEAYAKClI8QpIDQl1NQrA82HNHs1ft1+HTFKWKJcVG6a2Br3TeojVokejgKkJwsHT/uh0rD38kGiXp58F16p/f1cljLAmznEwc0ddnrGr5/kzmNJGriyWa6dR1NmjlTmjjx4nbqNKsAANMQpHyEIAWED4fTpcXbs/T6qv1af2FT31I2q0Wje7TQg4Pbqk/rS2p+ovR0aehQP1YaXlySdjdtrU+6DNVrl49RXkzZflzJ507ppyvf1i1bl8rmMnHD4+pU7tRXWX1Gk9LTpWHDam5lT/t0AAg4gpSPEKSA8LT1aLZeX7VfC787pmJHxV9rfVo31oOD2+n6mtqn+2OKXxgpttr0TavLtKTjQC3pOFCHLmlR4eMNC8/rsfUf6eFv5qlBcZA28KhtM936jiaNGyctXFjztE429AWAgCNI+QhBCghvx88V6O21h/TftQd1Kq+owsdaJMbqvkFtNX5Amho3KNc+PT1duukm6ezZwBYb5HKiG2hF+35a0nGglnW4vEIL81I2p0N3fveFJqXPUbPzZwNfpDdqGg2q72hSfr7UqFHtG/pKtY+KAQB8iiDlIwQpIDIUFJe2T9+vnZnnKnwsLsqmW/q11E+ubKeOH74lPfGESVUGn8MJzbWk00At7ThAa9N6qMRmv+gcu6NEAw5v06g963Tt7jVqlXPChEq9ZLHUPKJU39GkrCwpJeXi+6vjyTotAIBPEKR8hCAFRBaXy6U1e0/p9VX7tXTn8YsGHEbs3aAHNyzQkAObZVVE/TqUZOz59H2LTlrScYCWdByonc3bVXlefEGuRu7boFF71mv4vo1KLMwLcKX1MHy49Nxz1a9L8sVoEiNSABC0/HX9f/GfGgEgjFgsFl3Zsamu7NhU+0/m6T+rD+j9DYd1/kL79OUdLtfyDperYeF5dT2xX92y9qlb1j5dlrVXnU4dUowj/NqYF9ijtapNrwvrnQboRKOkKs9LO5upUXvW6Zrd69T/yDZFOR1Vnhf0+vWrublDTo5nAUgyzsvJuTgExcUZo1WejmoRogAg5DEiBSDiZOcX64M1+/TGB6t0NLH66VVRjmJ1PHlY3Y7vvRCu9umy4/sUX5Rf7WOC1YkGjbWsQ38t7jhAK9v1UUFUbJXn9T62U9fsXqdRe9br0pMHg691eV3ExEgFBdV/3FejSXTtA4CgxNQ+HyFIAZAkbd6skr79tLjTFZp/2QhtTelQY6gqr82ZY0awOr7vwgjWXjXPO+Pngr3jkrSnSZoWdxyoJZ0G6tvUznJZLu5YGFtcoCEHNuuaPes0cu83ap53NuC1BsSpU1JS1SNvkowAtHJl7c8zfLi0fHn1H581y1hzxz5SABA0mNoHAL70ww+yu5y64YfVuuGH1ZKks7GNtL15e21Pbq9tzdtrW3IH7WnSSs5yG81K0sFLUnXwklR92mWI+76muWfU7fheXZa13z2C1eZMhk/XXRVbbToX01C50XHKiWmo3JgGOhfT4MJ9pe830Nm4BK1p3UMHL0mt8nma5p7RqL3rNWr3Og0++J3iSoK0Xbkvbd8uDRlS/cctPhp7mzBB6tFDmj5dmjev4l5UkyczEgUAYYQRKQCR6S9/kX7xi1pPK7BHa2ezttrevJ22JXfQtuT22tmsbbVT48q7aN3V8X2KKSlSTkxDnYtpcCEIlYUgIxzF6Vx0WUjKjW7gPr8wKqbOn27nEwc0avc6jdqzTr0ydkdeY43Fi6VRo6r+mL8aReTnG+upEhJYEwUAJmJECgB86bPPPDottqRIvTN+UO+MH9z3OSxW7U9K1bbmRrAqDVhn4yr+cs6LaaANrbppQ6tuPi3dE+VblI/as06ts7MCXkNQadq0+o/5otlEVeLiCFAAEMYIUgAiT35+zetcamFzOdXx1BF1PHVEY3askGSsScqIb1oWrJq31/bkDjqa2LzOr2N1OtSoKF/xhXmKLzyv+MLzalR03n3cqPC8Egrz3Oc0unBOfNF5tT6ToYSi83V+7bATW8MIYkKCMdLk6YgUsxkAACJIAYhEOTk1d1arA4uk1HMnlXrupK7Zs959f+m6q23JHbSrWWtZXDJCT9F5JVwIQ+5gVHQhGBUawahBcUF4dM0LBjUFKVqXAwDqgCAFIPLUdLHsY40LcnXloe915aHvA/aaqEJyLR0Zp0yR5s+v+RyHw2gYAQCApIt74QJAuDsTXK3K4WfDh9c+ijRkiNGa3GIxRp7Ks9uN+2fMoOseAMCNIAUg8qRW3RYcYeq55zw7b8IEYy+pMWOMtVBSWevylSvZ/wkAUAFT+wBEnqQkY4QiP9/sSuBvf/2rd6NIgwcbN1qXAwBqQZACEJmKisyuAP42fLj09NN1eyytywEAtWBqH4DIc/So0TgA4cti8XxKHwAAdUCQAhB5PvrI7ArgLzYbjSEAAAFBkAIQeT791OwK4A8WizR2LI0hAAABwRopAJElP1/68kuzq4A/LFkiXXWV2VUAACIEI1IAIktOjuR0ml0FfM1qNabzAQAQIAQpAJElIaFsjyCED6dTmjePlvYAgIDhagJAZImLMzZYtTOzOew4ncaIIwAAAUCQAhB5pkzxX/tzu93Yvyg11T/Pj5pFRZldQe3y86WsLEbPACDEEaQARJ4hQ4z1NBaL70emHA5j/6L33vPt88IzxcVmV1C99HRp3DipUSMpJcV4O26ctGqV2ZUBAOqAIAUgMk2YYLTJHjPGCFT1ZbdX3L9o0qT6Pye8Y7EYa+CC0cyZ0rBh0sKFZc1OnE7jeOhQadYsc+sDAHiNIAUgcg0eLM2dK+XlSaNHezc6VT58Wa1GICvdv2jKFGnjRt/Xi+pZrcboTlyc2ZVcLD1dmjhRcrmkkpKKHyspMe5/4glGpgAgxBCkACAuTpo61fN1U6UX7UuXSpmZUm6u9NZbUseOxroX2nAHnsslTZ5sdhVVmzZNstlqPsdmk6ZPD0w9AACfIEgBgFTzuqnSaXt//WtZcJo719j8dfdu6e67y9a9NGggFRaa8zmEsvqsVSs/pTLY5OdLCxZcPBJVWUkJ7dsBIMQQpACgVPl1U6V7TZWftvf001Jyctn0sarWvUS6Pn2kmBjPz7dajZG98l9zb4wdWzalMhh5swE07dsBIKRYXC6Xy+wiAiknJ0eJiYnKzs5WQrAuSgZgvvx846I2IaHqdTfp6UaIiqxfobWzWo31QH//e+3nWizGFMm5c43j/Hxp716pRw/PXy8z0wi3wSo/3xit9CRMWa3GaGcwrvMCgBDmr+t/RqQAoCpxcRVHnyrzZN1LJHI6pV/9SurSxbPzy69riouTOnTwfGTKag3eLn2lPN0A2m6Xbr6ZEAUAIYQgBQDe8nTdSyQqDTc7dkhXX131ORZL9euawjF4eLIBtMMRvM0yAABVIkgBgLe8WfdSX8GwH9XYsUZo8TbcLFliTIEcPbqsXXxpx8Oa1jWFW/DwpJFJsDbLAABUizVSAOAtb9a91FXpxfWECb7ZMLg+0tONtWC1rQmzWIyAVFUgqG3NWWWzZhl7K9lsFUf+7HYjRJV+bULJqlVGi/N584yfHavVCJ6TJxOiAMCPWCMFAMHC0+lndTV8eNmIzdat/nkNT82caVzk13dUpbY1Z5XV1kEx1EKUVLYBdG5uxTb6hCgACEkEKQCoC0+mn9XFM89Iy5eXXVyvX+/716isSZOL7xs+3BiJKh9YAh1uwjV4eBsqAQBBial9AFBXs2ZJjz/uu+e7807pnXcq3rd1q3ftwOvCapVOnCjbw8iTi3xvp+oBAGASpvYBQLCZMMEYtUlNrf9z2WzSe+8Z4ay87t3r/9y1cTql4mKpbVvj5kkwYlQFABDhCFIAUB+DBxsBqL4NIRwOo5HDE08YTQnKGzmyfs9dm1DYjwkAgCBDkAKA+qqpEYO3bDajs1t5X30lxcfX73mrU9f9mPLzpaws4y0AABGIIAUAvlBdI4bUVO9Gq0pKjPbYlQPKqFG+q7U8b/djSk839oFq1EhKSTHejht38SgaAABhjmYTAOBrlRsx5OdLe/d61zQiM9NYg1T6fL7et8pqNaYSerMf08yZ0sSJ4bW3EwAg7NFsAgBCReVGDHFxUocOZSNVtam8Ziknx7chymIxpvN507I8Pd0IUS5XxRAlGcfVre8CACBM+Wk3SQBABaWb+C5ceHEQKc9uN84rv2YpIcEIV3UNUxaLtG+f8TzFxXVrWT5t2sUjUZWVru8K9X2eAADwQMQFqdKZjDml+6UAQKA89pix/qkmJSXSo4+W7elUavRo6bPP6rYJcOkokt1u3IqLjZun8vOl+fON56lJSYn00UdGEwraogMAgkTpdb+vVzRF3BqpI0eOKC0tzewyAAAAAATQ3r171b59e589X8QFKafTqWPHjik+Pl6W+u77AlPl5OQoLS1Nhw8fpnFIhONnARI/ByjDzwJK8bMAScrOzlbr1q115swZNW7c2GfPG3FT+6xWq1q1amV2GfChhIQEfjlCEj8LMPBzgFL8LKAUPwuQjBzg0+fz6bMBAAAAQAQgSAEAAACAlwhSCFkxMTH67W9/q5iYGLNLgcn4WYDEzwHK8LOAUvwsQPLfz0HENZsAAAAAgPpiRAoAAAAAvESQAgAAAAAvEaQAAAAAwEsEKQAAAADwEkEKIeX06dO6++67lZCQoMaNG+uhhx5Sbm5ujY8ZMWKELBZLhduECRMCVDF85ZVXXlHbtm0VGxurgQMHav369TWe/8EHH6hLly6KjY1Vjx499OmnnwaoUviTNz8Hs2fPvujffmxsbACrhb98/fXXuummm5SamiqLxaL58+fX+pjly5erb9++iomJUceOHTV79my/1wn/8vbnYPny5Rf9TrBYLMrMzAxMwfCL559/Xv3791d8fLyaN2+usWPHateuXbU+zhfXCQQphJS7775b27Zt0+LFi/XJJ5/o66+/1qOPPlrr4x555BFlZGS4b//3f/8XgGrhK++9956mTJmi3/72t9q0aZN69eql6667TsePH6/y/NWrV2v8+PF66KGH9O2332rs2LEaO3astm7dGuDK4Uve/hxIUkJCQoV/+wcPHgxgxfCXvLw89erVS6+88opH5+/fv1833nijRo4cqc2bN2vSpEl6+OGH9cUXX/i5UviTtz8HpXbt2lXh90Lz5s39VCECYcWKFZo4caLWrl2rxYsXq7i4WNdee63y8vKqfYzPrhNcQIjYvn27S5Lrm2++cd/32WefuSwWi+vo0aPVPm748OGuZ555JgAVwl8GDBjgmjhxovvY4XC4UlNTXc8//3yV599+++2uG2+8scJ9AwcOdD322GN+rRP+5e3PwRtvvOFKTEwMUHUwiyTXvHnzajznF7/4hatbt24V7rvjjjtc1113nR8rQyB58nOwbNkylyTXmTNnAlITzHH8+HGXJNeKFSuqPcdX1wmMSCFkrFmzRo0bN9bll1/uvm/UqFGyWq1at25djY/973//q6ZNm6p79+6aOnWqzp8/7+9y4SNFRUXauHGjRo0a5b7ParVq1KhRWrNmTZWPWbNmTYXzJem6666r9nwEv7r8HEhSbm6u2rRpo7S0NI0ZM0bbtm0LRLkIMvxOQHm9e/dWixYtdM0112jVqlVmlwMfy87OliQlJSVVe46vfifYvS8PMEdmZuZFw+92u11JSUk1zm++66671KZNG6Wmpur777/Xs88+q127dumjjz7yd8nwgZMnT8rhcCg5ObnC/cnJydq5c2eVj8nMzKzyfObBh666/Bx07txZr7/+unr27Kns7Gy9+OKLuvLKK7Vt2za1atUqEGUjSFT3OyEnJ0f5+fmKi4szqTIEUosWLTRr1ixdfvnlKiws1L///W+NGDFC69atU9++fc0uDz7gdDo1adIkDR48WN27d6/2PF9dJxCkYLpf/vKXeuGFF2o8Z8eOHXV+/vJrqHr06KEWLVro6quv1t69e9WhQ4c6Py+A4DZo0CANGjTIfXzllVeqa9eu+uc//6k//OEPJlYGwAydO3dW586d3cdXXnml9u7dq+nTp+utt94ysTL4ysSJE7V161alp6cH5PUIUjDdT3/6U/3kJz+p8Zz27dsrJSXlokXlJSUlOn36tFJSUjx+vYEDB0qS9uzZQ5AKAU2bNpXNZlNWVlaF+7Oysqr9vqekpHh1PoJfXX4OKouKilKfPn20Z88ef5SIIFbd74SEhARGoyLcgAEDAnbRDf968skn3Y3Iapt14KvrBNZIwXTNmjVTly5darxFR0dr0KBBOnv2rDZu3Oh+7FdffSWn0+kOR57YvHmzJGOIH8EvOjpa/fr109KlS933OZ1OLV26tMJoQ3mDBg2qcL4kLV68uNrzEfzq8nNQmcPh0JYtW/i3H4H4nYDqbN68md8JIc7lcunJJ5/UvHnz9NVXX6ldu3a1PsZnvxPq0g0DMMv111/v6tOnj2vdunWu9PR0V6dOnVzjx493f/zIkSOuzp07u9atW+dyuVyuPXv2uH7/+9+7NmzY4Nq/f79rwYIFrvbt27uGDRtm1qeAOnj33XddMTExrtmzZ7u2b9/uevTRR12NGzd2ZWZmulwul+vee+91/fKXv3Sfv2rVKpfdbne9+OKLrh07drh++9vfuqKiolxbtmwx61OAD3j7c/C73/3O9cUXX7j27t3r2rhxo+vOO+90xcbGurZt22bWpwAfOXfunOvbb791ffvtty5JrmnTprm+/fZb18GDB10ul8v1y1/+0nXvvfe6z9+3b5+rQYMGrp///OeuHTt2uF555RWXzWZzff7552Z9CvABb38Opk+f7po/f75r9+7dri1btrieeeYZl9VqdS1ZssSsTwE+8Pjjj7sSExNdy5cvd2VkZLhv58+fd5/jr+sEghRCyqlTp1zjx493NWrUyJWQkOB64IEHXOfOnXN/fP/+/S5JrmXLlrlcLpfr0KFDrmHDhrmSkpJcMTExro4dO7p+/vOfu7Kzs036DFBXf//7312tW7d2RUdHuwYMGOBau3at+2PDhw933X///RXOf//9912XXnqpKzo62tWtWzfXokWLAlwx/MGbn4NJkya5z01OTnaNHj3atWnTJhOqhq+VtrGufCv9/t9///2u4cOHX/SY3r17u6Kjo13t27d3vfHGGwGvG77l7c/BCy+84OrQoYMrNjbWlZSU5BoxYoTrq6++Mqd4+ExVPwOSKvwb99d1guVCAQAAAAAAD7FGCgAAAAC8RJACAAAAAC8RpAAAAADASwQpAAAAAPASQQoAAAAAvESQAgAAAAAvEaQAAAAAwEsEKQAAAADwEkEKAAAAALxEkAIAAAAALxGkAABh7cSJE0pJSdGf/vQn932rV69WdHS0li5damJlAIBQZnG5XC6ziwAAwJ8+/fRTjR07VqtXr1bnzp3Vu3dvjRkzRtOmTTO7NABAiCJIAQAiwsSJE7VkyRJdfvnl2rJli7755hvFxMSYXRYAIEQRpAAAESE/P1/du3fX4cOHtXHjRvXo0cPskgAAIYw1UgCAiLB3714dO3ZMTqdTBw4cMLscAECIY0QKABD2ioqKNGDAAPXu3VudO3fWyy+/rC1btqh58+ZmlwYACFEEKQBA2Pv5z3+uuXPn6rvvvlOjRo00fPhwJSYm6pNPPjG7NABAiGJqHwAgrC1fvlwvv/yy3nrrLSUkJMhqteqtt97SypUrNXPmTLPLAwCEKEakAAAAAMBLjEgBAAAAgJcIUgAAAADgJYIUAAAAAHiJIAUAAAAAXiJIAQAAAICXCFIAAAAA4CWCFAAAAAB4iSAFAAAAAF4iSAEAAACAlwhSAAAAAOAlghQAAAAAeIkgBQAAAABe+v+WWHs2oN9IZAAAAABJRU5ErkJggg==", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plot_data(X2, y, xlabel=\"x\", ylabel=\"y\")\n", + "theta_start = np.matrix([0, 0, 0]).reshape(3, 1)\n", + "theta, logs = gradient_descent(cost, gradient, theta_start, X2, y)\n", + "plot_fun(fig, polynomial_regression(theta), X)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "notes" + } + }, + "source": [ + "Innym szczególnym przypadkiem regresji wielomianowej jest funkjca sześcienna:" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "Funkcja sześcienna:\n", + "\n", + "$$ h_{\\theta}(x) = \\theta_0 + \\theta_1 x + \\theta_2 x^2 + \\theta_3 x^3 $$" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[ 397519.38046962]\n", + " [-841341.14146733]\n", + " [2253713.97125102]\n", + " [-244009.07081946]]\n" + ] + }, + { + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAAA1IAAAH+CAYAAACWZz+7AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8o6BhiAAAACXBIWXMAAA9hAAAPYQGoP6dpAACEN0lEQVR4nO3dd3yV9fn/8fcZWRAChJEQCHvvoSAbFAcuhlrFWatWFFsRW1t/9Wtrl61V0FoB2zrqHiggThBkhKks2XtmsRMSMs85vz9ucpJAxjnJObnPeD0fjzyS+5z7nHNlEO4r1+dzXRaXy+USAAAAAMBjVrMDAAAAAIBgQyIFAAAAAF4ikQIAAAAAL5FIAQAAAICXSKQAAAAAwEskUgAAAADgJRIpAAAAAPASiRQAAAAAeIlECgAAAAC8RCIFAAAAAF4K60Rq+fLluuGGG5SUlCSLxaJ58+Z5/Rwul0vPP/+8OnfurKioKLVs2VJ/+ctffB8sAAAAgIBhNzsAM+Xm5qpPnz762c9+pokTJ9boOR599FEtXLhQzz//vHr16qVTp07p1KlTPo4UAAAAQCCxuFwul9lBBAKLxaK5c+dq/Pjx7tsKCgr0u9/9Tu+//77OnDmjnj176u9//7tGjRolSdqxY4d69+6trVu3qkuXLuYEDgAAAKDOhfXSvuo88sgjWr16tT744AP9+OOPuuWWW3TNNddoz549kqQFCxaoffv2+vzzz9WuXTu1bdtW999/PxUpAAAAIMSRSFXi8OHDeuONN/Txxx9r+PDh6tChg371q19p2LBheuONNyRJ+/fv16FDh/Txxx/rrbfe0ptvvqn169fr5ptvNjl6AAAAAP4U1nukqrJlyxY5HA517ty53O0FBQVq0qSJJMnpdKqgoEBvvfWW+7zXXntNAwYM0K5du1juBwAAAIQoEqlK5OTkyGazaf369bLZbOXui42NlSS1aNFCdru9XLLVrVs3SUZFi0QKAAAACE0kUpXo16+fHA6Hjh07puHDh1d4ztChQ1VcXKx9+/apQ4cOkqTdu3dLktq0aVNnsQIAAACoW2HdtS8nJ0d79+6VZCRO06dP1+jRoxUfH6/WrVvrzjvv1MqVK/XCCy+oX79+On78uBYvXqzevXvruuuuk9Pp1KWXXqrY2Fi9+OKLcjqdmjJliuLi4rRw4UKTPzsAAAAA/hLWidTSpUs1evToi26/55579Oabb6qoqEh//vOf9dZbbyk1NVVNmzbVZZddpmeeeUa9evWSJKWlpekXv/iFFi5cqPr162vs2LF64YUXFB8fX9efDgAAAIA6EtaJFAAAAADUBO3PAQAAAMBLJFIAAAAA4KWw69rndDqVlpamBg0ayGKxmB0OAAAAAD9yuVw6e/askpKSZLX6ro4UdolUWlqakpOTzQ4DAAAAQB06cuSIWrVq5bPnC7tEqkGDBpKML2RcXJwpMSzclqFpH22WJN08oJX+cGMPU+IAgICTlye1aCF50gfJYpHS06WYGP/HBYS5Jz/5UQt+TJck/WlcD03o77uLUcDfsrOzlZyc7M4DfCXsEqmS5XxxcXGmJVLXDqinp77cp/wip5YfzFH92AayWVlmCACKi5PGj5cWLJCKiys/z26Xxo2TEhLqLDQgXJ3KLdSivWdljaqnhjERunVoF0VH2MwOC/Car7f10GzCBPUi7RrZuZkk6UROob4/eMrkiAAggEybJjkcVZ/jcEiPPVY38QBh7qMfjqjQ4ZQk3TKgFUkUcB6JlEnG9mzh/vjrrRkmRgIAAWbYMGnmTGPpnv2ChRN2u3H7zJnS0KHmxAeEEafTpXfXHnIf33FZGxOjAQILiZRJLu/WXBE2o7z49dYMOZ3MRQYAt8mTpRUrjOV7JR2WrFbjeMUK434Afrdsz3EdOZUnSRreqanaNa1vckRA4Ai7PVKBIi46QsM6NtV3u44rIztfm46eUf/Wjc0OCwACx9ChxltenpSdbeyforEEUKfeWV1ajbqTahRQDhUpE7G8DwA8EBNjNJUgiQLq1JFT57Rk1zFJUouG0bqia3OTIwICC4mUia7snuDu1vfV1nS5PGn3CwAAUAfeX3fYPYng9oGtZbdx2QiUxb8IEzWuH6nL2sdLko6cytO2tGyTIwIAAJAKih368PsjkiS71aJbByabHBEQeEikTHYNy/sAAECA+Xprhk7mFkqSru6ZqOYNok2OCAg8JFImu7pHgkpmg321Nd3cYAAAACS9s6a0ycRdNJkAKkQiZbLmDaJ1SRujW9++47nak3nW5IgAAEA425mRre8PnpYkdWoeq0Ht4k2OCAhMJFIBoOzyvq9Y3gcAAExUthp152VtZClZOgOgHBKpAHBNz0T3xyRSAADALGfzizR3Q6okqV6kTRP6tzQ5IiBwkUgFgJaNYtSnVUNJ0o70bB06mWtyRAAAIBzN25iq3EKHJGl8v5aKi44wOSIgcJFIBQiW9wEAADO5XC69s+aw+/jOQTSZAKpCIhUgxrK8DwAAmOj7g6e163zTqwFtGqt7UpzJEQGBjUQqQLRtWl9dExtIkjYfOaO0M3kmRwQAAMLJ27Q8B7xCIhVAxjKcFwAAmOD42QJ9fX6eZXz9SI3tlVjNIwCQSAWQsr+0SKQAAEBd+eiHIypyuCRJP7kkWVF2m8kRAYGPRCqAdGoeq/bN6kuSvj90SsfO5pscEQAACHUOp0vvnl/WZ7FIdwxqbXJEQHAgkQogFovF3XTC5ZIWbss0OSIAABDqluw8prQs44+3ozo3U3J8PZMjAoIDiVSAYZ8UAACoS++UbTIxmCYTgKdIpAJMj6Q4tWocI0lavf+kTucWmhwRAAAIVYdO5mrZ7uOSpFaNYzSyc3OTIwKCB4lUgCm7vM/hdGnRDpb3AQAA/3h3bekA3jsGtZHNajExGiC4kEgFoGtY3gcAAPwsv8ihj344IkmKtFn1k0tamRwREFxIpAJQv+RGSoiLkiSl7Dmhs/lFJkcEAABCzRc/puvMOeMa49peiWoSG2VyREBwIZEKQFarRdf0MJb3FTqcWrLzmMkRAQCAUPM2TSaAWjE1kXr22Wd16aWXqkGDBmrevLnGjx+vXbt2VfmYN998UxaLpdxbdHR0HUVcd8ou7/tqC8v7AACA72xNzdKmI2ckSV0TG6h/68bmBgQEIVMTqWXLlmnKlClas2aNFi1apKKiIl111VXKzc2t8nFxcXFKT093vx06dKjK84PRwHbxalI/UpK0dPcxnSssNjkiAAAQKi5seW6x0GQC8JbdzBf/+uuvyx2/+eabat68udavX68RI0ZU+jiLxaLExER/h2cqm9Wiq3ok6P11R5Rf5NSyXcc1tleL6h8IAABQhay8Is3blCpJio2ya3zfliZHBASngNojlZWVJUmKj4+v8rycnBy1adNGycnJGjdunLZt21bpuQUFBcrOzi73FizKLe+jex8AAPCBTzccVX6RU5I0sX9L1Y8y9e/qQNAKmETK6XRq6tSpGjp0qHr27FnpeV26dNHrr7+u+fPn65133pHT6dSQIUN09OjRCs9/9tln1bBhQ/dbcnKyvz4Fnxvcvonioo1fbkt2HlNBscPkiAAAQDBzuVzlmkzceRlNJoCaCphEasqUKdq6das++OCDKs8bPHiw7r77bvXt21cjR47Up59+qmbNmunVV1+t8Pwnn3xSWVlZ7rcjR474I3y/iLRbNaZ7giQpp6BYKXtOmBwRAAAIZqv3ndT+48Ze9EHt4tU5oYHJEQHBKyASqUceeUSff/65vvvuO7Vq5d0wuIiICPXr10979+6t8P6oqCjFxcWVewsmY1neBwAAfOSdtVSjAF8xNZFyuVx65JFHNHfuXC1ZskTt2rXz+jkcDoe2bNmiFi1CsxHD8E5NVS/SJklatD1TRQ6nyREBAIBglJmdr2+2ZUqSmsZG6eoeod24C/A3UxOpKVOm6J133tF7772nBg0aKCMjQxkZGcrLy3Ofc/fdd+vJJ590H//xj3/UwoULtX//fm3YsEF33nmnDh06pPvvv9+MT8HvoiNsGt21uSSjy86a/SdNjggAAASj99cdlsPpkiRNGpisSHtALEwCgpap/4JmzZqlrKwsjRo1Si1atHC/ffjhh+5zDh8+rPT0dPfx6dOn9cADD6hbt2669tprlZ2drVWrVql79+5mfAp1YmzP0r8YsbwPAAB4q8jh1PvrDkuSrBZp0sDWJkcEBD+Ly+VymR1EXcrOzlbDhg2VlZUVNPulcguK1f9Pi1RQ7FTT2Eit/X9jZLMyOA8AAHjm663pmvzOBknSld0T9J+7LzE5IqDu+Ov6n5puEKgfZdeIzs0kSSdyCvXDwVMmRwQAAIJJ2Zbnd9FkAvAJEqkgUXZ539fbWN4HAAA8s+94jlbuNfZYt21ST8M6NjU5IiA0kEgFiSu6JSjCZizn+2ZrhsJsRSYAAKihd9ccdn98x6A2srI9APAJEqkg0TAmQkM6GH9BSsvK1+ajWSZHBAAAAt25wmLNWX9EkhRlt+rmAd7N6wRQORKpIFK+e196FWcCAABIn2xIVXZ+sSTp+t5Jalw/0uSIgNBBIhVEruyeoJJq/Ncs7wMAAFVwOl16I+WA+/jeoW3NCwYIQSRSQaRJbJQGtWsiSTp08px2pJ81OSIAABCovtt1TPtP5EqSLmsfr54tG5ocERBaSKSCzNheZbr3sbwPAABU4r8rSqtR9w9rb2IkQGgikQoyV/cou0+KNugAAOBi29KytHq/0fK8XdP6urxrc5MjAkIPiVSQSYiL1oA2jSVJe47laO+xHJMjAgAAgea1Mnujfja0LS3PAT8gkQpC5YbzsrwPAACUcSw7Xws2p0kyxqfcRMtzwC9IpIIQy/sAAEBl3lp9SEUOo7Pv7YNaq16k3eSIgNBEIhWEkuPrqdf5zjvb0rJ1+OQ5kyMCAACBIK/QoXfWHpIk2a0W3TO4rbkBASGMRCpIXVN2ed82lvcBAADp041HdeZckSTphj5JSmwYbXJEQOgikQpSZfdJsbwPAAA4na5yTSbuG9bOxGiA0EciFaTaN4tVl4QGkqSNh88oPSvP5IgAAICZlu4+pv3HjQG8g9oxgBfwNxKpIFZ2ed83VKUAAAhrZatR9w9nAC/gbyRSQWxsL5b3AQAAaXtatlbuNQbwtm1ST1cwgBfwOxKpINYloYHaN60vSVp38JTSzrC8DwCAcPT6yjIDeIe1YwAvUAdIpIKYxWLRjX2TJEkulzRvU6rJEQEAgLp2LDtf889fA8RF23VTfwbwAnWBRCrITexX+sty7oZUuVwuE6MBAAB17e01ZQfwtlH9KAbwAnWBRCrItW5ST5e2bSxJ2nMsR1tTs02OCAAA1JX8IofeWVNmAO+QNiZHBIQPEqkQMLFMCf+TDUdNjAQAANSlTzek6vT5AbzX9W6hFg1jTI4ICB8kUiHg2l4tFGk3vpWfbU5TkcNpckQAAMDfjAG8+93HDOAF6haJVAhoGBOhK7slSJJO5RZq2a7jJkcEAAD8bdme49p3fgDvwLbx6t2qkbkBAWGGRCpETOzf0v3x3I107wMAINS9tqK05fl9w6lGAXWNRCpEjOjcTE3qR0qSFu3IVNb59dIAACD07MzIVsreE5KkNk3qacz5lSkA6g6JVIiIsFndM6UKi536Yku6yREBAAB/KVuNundIW9kYwAvUORKpEFJ2ptSndO8DACAkHTubr/mb0iRJDaLtuuWSZJMjAsITiVQI6dkyTp2ax0qSfjh0WodO5pocEQAA8LV31hxW4fkOvbcPas0AXsAkJFIhxGKxlJspRdMJAABCS9kBvDarRfcMbmtuQEAYI5EKMeP7Jclyfpn0pxtS5XK5zA0IAAD4zNyNqTqVWyhJuq5XCyU1YgAvYBYSqRDTomGMhnRoIkk6fOqc1h86bXJEAADAF1wul15LKdPynAG8gKlIpEJQuaYTLO8DACAkLNt9XHuP5UiSLm3bWH2SG5kbEBDmSKRC0DU9ExUTYZMkfb45TflFDpMjAgAAtVW+GtXexEgASCRSIal+lF1jeyZKkrLzi7Vk5zGTIwIAALWxK+OsVuwxBvC2jq+nK7szgBcwG4lUiCrbvY+ZUgAABLfXUva7P753KAN4gUBAIhWiBndoooS4KEnS0l3HdTKnwOSIAABATRw/W6B5DOAFAg6JVIiyWS0a36+lJKnY6dKCzWkmRwQAAGrinTWHVFhsDOCdNLC1YhnACwQEEqkQRvc+AACC20UDeIe0NTcgAG4kUiGsS2ID9WwZJ0n68WiW9mSeNTkiAADgjfmbUnXy/ADesT0T1ZIBvEDAIJEKcROoSgEAEJQuHMB7/3BangOBhEQqxN3YJ8nd2WfexlQ5nS6TIwIAAJ5YseeEdmcaA3gvadNYfRnACwQUEqkQ16xBlEZ2biZJSs/K15r9J02OCAAAeOK/5QbwtjMxEgAVIZEKAxP7t3R//MkGlvcBABDodmee1fLdxyVJyfExuqpHoskRAbgQiVQYGNMtQQ3Ot0r9amu6zhUWmxwRAACoyutlqlH3DmnHAF4gAJFIhYHoCJuu691CknSu0KFvtmWYHBEAAKjMiZwCd4OoBlF2/eRSBvACgYhEKkxM7F+mex/L+wAACFjvrjnsHsB728BkBvACAYpEKkxc0qaxkuON2RMr955QRla+yREBAIAL5Rc59Paag5Ikq0UM4AUCGIlUmLBaLe6ZUk6XMeAPAAAEls82pelEzvkBvL1aqFXjeiZHBKAyJFJhZEK/0u59n25IlcvFTCkAAALFRQN4aXkOBDQSqTDSrml99W/dSJK0K/OstqdnmxsQAABwS9l7Qrsyz0qS+rdupH6tG5scEYCqkEiFGZpOAAAQmP67okw1anh7EyMB4AkSqTBzfe8WirQZ3/b5m1JV7HCaHBEAANiTeVbLzg/gbdU4Rld1TzA5IgDVIZEKM43qReryrs0lSSdyCrVizwmTIwIAAK+vLK1G/XRIW9ltXKIBgY5/pWFoYv8yTSc2srwPAAAzncwpcC+3j42y61YG8AJBgUQqDI3q0lyN60VIkhZuy1B2fpHJEQEAEL7eXXtYBecH8N56abIaREeYHBEAT5BIhaFIu1U39kmSJBUUO/XVlnSTIwIAIDwVFDv01upDkowBvD9lAC8QNEikwtSEMt37PqF7HwAApjAG8BZIksb2bKHkeAbwAsGCRCpM9WnVUO2b1ZckrTtwSkdOnTM5IgAAwsuFA3h/xgBeIKiQSIUpi8Wim8pUpebRdAIAgDq1cu9J7cwwBvD2a91IA9owgBcIJiRSYWx8v/Ld+1wul4nRAAAQXl5L2e/++P5hDOAFgg2JVBhr2ShGg9s3kSQdOJGrjUfOmBsQAABhYu+xs/pulzGAt2WjGF3dgwG8QLAhkQpzE8rOlNpw1MRIAAAIHzO/2+f+mAG8QHDiX22YG9szUdERxo/B5z+mq6DYYXJEAACEtsMnz2n+5jRJUqN6EZo0qLXJEQGoCRKpMNcgOkJX90iUJJ05V6Tvdh43OSIAAELb7OX75HAa+5LvHdJOsVF2kyMCUBMkUtDEMt37WN4HAID/ZGTla84Pxv+1sVF2BvACQYxEChraoYmaNYiSJH2365hO5RaaHBEAAKHp38v3q9DhlCTdNbiNGtaLMDkiADVFIgXZbVaN75skSSpyuPT5j2kmRwQAQOg5kVOg99YdkiRFR1h1HwN4gaBGIgVJFy7vYzgvAAC+9nrKAeUXGdWoSQNbq2lslMkRAagNEilIkrq1iFO3FnGSpE1Hzmjf8RyTIwIAIHRknSvSW6uNalSEzaKfj2AALxDsSKTgNrFf6UypuVSlAADwmf+tPqicgmJJ0s0DktWiYYzJEQGoLVMTqWeffVaXXnqpGjRooObNm2v8+PHatWtXtY/7+OOP1bVrV0VHR6tXr1768ssv6yDa0Deub5KsFuPjuRtT5TzfmhUAANRcbkGxXl95QJJks1r00MgOJkcEwBdMTaSWLVumKVOmaM2aNVq0aJGKiop01VVXKTc3t9LHrFq1SpMmTdJ9992njRs3avz48Ro/fry2bt1ah5GHpuZx0RreqZkkKfVMntYdPGVyRAAABL931x7SmXNFkqQb+ySpdZN6JkcEwBcsLpcrYMoOx48fV/PmzbVs2TKNGDGiwnNuvfVW5ebm6vPPP3ffdtlll6lv376aPXt2ta+RnZ2thg0bKisrS3FxcT6LPVTM35SqRz/YJEn6ySWt9NzNfcwNCACAIJZf5NDw577T8bMFslikhVNHqFNCA7PDAsKKv67/A2qPVFZWliQpPj6+0nNWr16tMWPGlLvt6quv1urVqys8v6CgQNnZ2eXeULmruie6J6x/uSVDeYUOkyMCACB4ffTDER0/WyBJuqZHIkkUEEICJpFyOp2aOnWqhg4dqp49e1Z6XkZGhhISEsrdlpCQoIyMjArPf/bZZ9WwYUP3W3Jysk/jDjUxkTaN7ZkoScopKNbC7RV/XQEAQNWKHE69umy/+3jK6I4mRgPA1wImkZoyZYq2bt2qDz74wKfP++STTyorK8v9duTIEZ8+fyhiphQAALU3d2OqUs/kSZJGd2mmni0bmhwRAF+ymx2AJD3yyCP6/PPPtXz5crVq1arKcxMTE5WZmVnutszMTCUmJlZ4flRUlKKiGHjnjUHt4tWyUYxSz+RpxZ7jOnY2X80bRJsdFgAAQcPhdGnW0n3u40cupxoFhBpTK1Iul0uPPPKI5s6dqyVLlqhdu3bVPmbw4MFavHhxudsWLVqkwYMH+yvMsGO1WjTh/Ewpp0v6bFOayREBABBcvtiSrgMnjC7Eg9s30YA2le//BhCcTE2kpkyZonfeeUfvvfeeGjRooIyMDGVkZCgvL899zt13360nn3zSffzoo4/q66+/1gsvvKCdO3fqD3/4g3744Qc98sgjZnwKIWtC/9LhvJ+wvA8AAI85nS69smSv+5hqFBCaTE2kZs2apaysLI0aNUotWrRwv3344Yfucw4fPqz09HT38ZAhQ/Tee+/p3//+t/r06aM5c+Zo3rx5VTaogPc6NItVn+RGkqQd6dnakU63QwAAPPHtjkztyjwrSerXupGGdGhickQA/MHUPVKejLBaunTpRbfdcsstuuWWW/wQEcq6qX9LbT5yRpKxYbZbC+ZuAQBQFZfLpVe+K1ONGt1RFovFxIgA+EvAdO1D4Lm+d5IibMYv/7kbU1XscJocEQAAgW3FnhPafNSYi9mtRZwu79rc5IgA+AuJFCoVXz9So7oY/wEcP1uglftOmhwRAACB7V9Uo4CwQSKFKt1UpunEpxuOmhgJAACBbd2BU1p34JQkqX2z+rqmZ8WjWQCEBhIpVGl01+ZqGBMhSfpmW4ZyCopNjggAgMBUtho1ZVRH2axUo4BQRiKFKkXZbbqhTwtJUn6RU19tSa/mEQAAhJ8fj57R8t3HJUmtGsfoxr5JJkcEwN9IpFCtif1buT/+lJlSAABc5F9l5kY9NKqDImxcYgGhjn/lqFa/5EZq17S+JGn1/pM6dDLX5IgAAAgcuzLOauH2TElSQlyUbh7QqppHAAgFJFKolsVi0S2XlP6n8M6aQyZGAwBAYCk7N+qB4e0VZbeZGA2AukIiBY/cekmyIs8vU/jw+yPKK3SYHBEAAOY7cCJXn/+YJskYG3L7oNYmRwSgrpBIwSNNYqN0/fmmE9n5xfpsM3ulAACYtXSvnC7j4/uGtVO9SLu5AQGoMyRS8Njdg9u6P/7fqkNyuVzmBQMAgMlSz+S5mzA1iLbrrsFtTI4IQF0ikYLH+iY3Uu9WDSVJ29OzteHwaZMjAgDAPP9etk/F58tRPx3SVnHRESZHBKAukUjBK2WrUm+tpukEACAA5eVJmZnGez85djZf739/RJIUE2HTvUPb+e21AAQmEil45freLdS4nvEXty+3pOv42QKTIwIA4LyUFGniRCk2VkpMNN5PnCitXOnzl3ptxQEVFjslSXde1lrx9SN9/hoAAhuJFLwSHWHTrZcaHYmKHC59sO6wyREBACBp1ixpxAhpwQLJaSQ4cjqN4+HDpdmzffZSp3ML9fb5USCRdqseGN7eZ88NIHiQSMFrdwxqLYvF+PjdtYdV7HCaGxAAILylpEhTpkgul1RcXP6+4mLj9ocf9lll6o1VB3Xu/BiQWy9JVvO4aJ88L4DgQiIFryXH19MVXZtLkjKy87Xo/DR3AABMMX26ZKtmCK7NJs2YUeuXOptfpDdXHpAk2a0WPTiSahQQrkikUCM0nQAABIS8PGn+/IsrURcqLpbmzq11A4q31xxSdr7xWhP6tVSrxvVq9XwAgheJFGpkWMemate0viRp9f6T2p151uSIAABhKTu7dE9UdZxO4/wayit06LUVRjXKapEeGtWhxs8FIPiRSKFGrFaL7rqsdPDg21SlAABmiIuTrB5ezlitxvk19P66wzqZWyhJurZXC7VvFlvj5wIQ/EikUGM3DWilmAhjTfqnG47qbH6RyREBAMJOTIw0bpxkt1d9nt0uTZhgnF8DBcUO/Xv5fvfxlNEda/Q8AEIHiRRqrGFMhMb3aylJyi106NMNqSZHBAAIS9OmSQ5H1ec4HNJjj9X4JT7dkKqM7HxJ0phuCerWouaVLQChgUQKtXL34NLlfW+tPiiXy2ViNACAsDRsmDRzpmSxXFyZstuN22fOlIYOrdHTFzucmrV0n/v4kcupRgEgkUItdWsRp4Ft4yVJ+47natW+kyZHBAAIS5MnSytWGMv8SvZMWa3G8YoVxv01tODHNB0+dU6SNLxTU/VNbuSDgAEEu2oWFAPVu3tIG607eEqSUZUa2rGpyREBAMLS0KHGW16e0Z0vLq7Ge6JKOJ0uvfJdaTWKvVEASlCRQq1d3SNRzRtESZIWbc9U6pnazegAAKBWYmKkhIRaJ1GS9M22DO09liNJurRtYw1qF1/r5wQQGkikUGsRNqsmDWwtSXK6pPfW0godABD8XC6X/vXdXvfxlNEdZbFYTIwIQCAhkYJP3D6otexW4z+XD9YdUUFxNd2TAAAIcEt3Hde2NGOAb6+WDTWyczOTIwIQSEik4BMJcdG6umeiJOlkbqG+3JJuckQAANScy+XSy0v2uI+pRgG4EIkUfOaewW3dH7+1muV9AIDgtXr/SW04fEaS1DkhVld1TzA3IAABh0QKPnNp28bqmthAkrTx8BltOZplckQAANTMKxfsjbJaqUYBKI9ECj5jsVh01wUDegEACDYbDp/Wyr3GXMQ2Terpul4tTI4IQCAikYJPje/bUg2ijfFkn21O0+ncQpMjAgDAO68sKa1GPTyqg+w2LpcAXIzfDPCp+lF23TyglSSpoNipj9cfMTkiAAhCeXlSZqbxHnVqW1qWFu88JklKahitCf1amRwRgEBFIgWfu+uy0uV9b685JIfTZWI0ABBEUlKkiROl2FgpMdF4P3GitHKl2ZGFjekLd7s//vmI9oq0c6kEoGL8doDPtW8Wq+GdmkqSjpzK07Ldx0yOCACCwKxZ0ogR0oIFktNp3OZ0GsfDh0uzZ5sbXxj44eApdzWqRcNo3XZ+2DwAVIRECn5xd5lW6P9bRSt0AKhSSoo0ZYrkcknFxeXvKy42bn/4YSpTfuRyufT3r3e6j6eO6aToCJuJEQEIdCRS8IvLuzZXy0YxkqRlu4/r4IlckyMCgAA2fbpkq+ai3WaTZsyom3jC0NJdx/X9wdOSpPbN6uum/uyNAlA1Ein4hc1q0Z1l9kq9s4aqFABUKC9Pmj//4krUhYqLpblzaUDhB06nS899s8t9/KurutCpD0C1+C0Bv7n10mT3Jt2PfjiivEKHyREBQADKzi7dE1Udp9M4Hz614Mc07Ug3vq69WjbU2J6JJkcEIBiQSMFv4utH6obeSZKk7Pxizd+UanJEABCA4uIkq4f/HVutxvnwmcJip14o06nvN9d0lcViMTEiAMGCRAp+dffg0uV9/1t9SC4XrdABoJyYGGncOMlur/o8u12aMME4Hz7z4Q9HdPjUOUnSkA5NNOx811kAqA6JFPyqT3Ij9UluJEnakZ6t9YdOmxsQAASiadMkRzXLnx0O6bHH6iaeMJFX6NA/F+9xHz9xTVcTowEQbEik4Hd3l2k68dZqmk4AwEWGDZNmzpQslosrU3a7cfvMmdLQoebEF6LeWHVAx88WSJKu6ZGovuf/8AcAniCRgt9d17uF4utHSpK+2pquY2fzTY4IAALQ5MnSihXGMr+SPVNWq3G8YoVxP3wm61yRZi/dJ0myWqRfXd3Z5IgABBsSKfhddIRNt16aLEkqcrj0wbojJkcEAAFq6FBpzhwpJ0fKyDDez5lDJcoPZi/fp+x8o+X8Tf1bqWPzBiZHBCDYkEihTtwxqLWs55sgvbf2sIocHrb6BYBwFBMjJSTQWMJPMrPz9cbKA5KkSJtVU6+kGgXAeyRSqBOtGtfTFd0SJEkZ2flatD3T5IgAAOHqn4v3KL/I+IPenZe1UctGJKwAvEcihTpTthX6W6sPmhcIACBsHTyRqw+/N5aY14+0acroDiZHBCBYkUihzgzt0FTtm9aXJK3Zf0q7Ms6aHBEAINxMX7RbxU5jpuEDI9qrSWyUyREBCFYkUqgzVqtFd5WpSr295qB5wQAAws62tCx9tjlNkhRfP1L3D29vckQAghmJFOrUTQNaqV6kTZL06YZUZecXmRwRAMBreXlSZqbxPoj845td7o+njO6o2Ch7FWcDQNVIpFCn4qIjNKFfS0nSuUKHPl1/1OSIAAAeS0mRJk6UYmOlxETj/cSJ0sqVZkdWrbX7T2rpruOSpJaNYnTHoNYmRwQg2JFIoc7dPbit++O31hySy+UyLxgAgGdmzZJGjJAWLJCc50dYOJ3G8fDh0uzZ5sZXBZfLpefKVKMeHdNJ0RE2EyMCEApIpFDnuiQ20MB28ZKk/cdztXLvSZMjAgBUKSVFmjJFcrmk4uLy9xUXG7c//HDAVqYW7zim9YdOS5I6No/VxPMrIwCgNkikYIp7ylalaIUOAIFt+nTJVk0Fx2aTZsyom3i84HC6yu2N+tVVXWS3cfkDoPb4TQJTXNUjQQlxRsvZb3dkKvVMcG1YBoCwkZcnzZ9/cSXqQsXF0ty5AdeA4rPNqdqVaYzb6JPcSFf3SDA5IgChgkQKpoiwWXX7QKMVutMlvbvmkMkRAQAqlJ1duieqOk6ncX6AKCx2avqi3e7j31zdRRaLxcSIAIQSEimYZtLAZNmtxn9oH35/RAXFDpMjAgBcJC5Osnp4uWC1GucHiA++P6wjp4wK2fBOTTWkY1OTIwIQSkikYJrmcdG6pmeiJOlkbqG+3JJuckQAgIvExEjjxkn2amYu2e3ShAnG+QEgt6BY/1y8133866u7mBgNgFBEIgVT3TOkrfvj/61ieR8ABKRp0yRHNasGHA7pscfqJh4PvLHygE7kFEiSru2VqN6tGpkbEICQQyIFU13SprG6JjaQJG06ckY/Hj1jbkAAgIsNGybNnClZLBdXpux24/aZM6WhQ82J7wKncwv16rL9kiSb1aLHr6IaBcD3SKRgKovFUq4q9dZqqlIAEJAmT5ZWrDCW+ZXsmbJajeMVK4z7A8TsZft0tsDoMnhz/1bq0CzW5IgAhCISKZhuXN8kNYg2/sK5YHOaTucWmhwRAKBCQ4dKc+ZIOTlSRobxfs6cgKlESVJGVr7eXHVQkhRpt+rRMZ3MDQhAyCKRgunqRdp1y4BkSVJBsVMf/XDE5IgAAFWKiZESEgKmsURZLy3eo4Jio137PYPbKKlR4MUIIDSQSCEg3DW4jfvjt9ccksPpMjEaAEAw2n88x/3HuAZRdj08qqPJEQEIZSRSCAjtmtbXiM7NJElHT+dp6a5jJkcEAAg2Lyza7f5D3AMj2qtx/UiTIwIQykikEDDuKVOV+h9NJwAAXtiamqUvfjTmETapH6n7hrUzOSIAoY5ECgFjVJfmatXYWMu+fPdx7T121uSIAADB4rlvdrk//sXlHVU/qpoBwgBQSyRSCBg2q0X3DG7rPn7lu33mBQMACBqr9p3Q8t3HJUktG8Vo0qDWJkcEIByQSCGgTBrUWo3qRUiS5m9K1cETuSZHBAAIZC6XS899XVqNmnZlZ0XZbSZGBCBckEghoMRG2XXfUGNdu9MlzVy61+SIAACBbNH2TG06ckaS1DkhVuP7tTQ3IABhw9REavny5brhhhuUlJQki8WiefPmVXn+0qVLZbFYLnrLyMiom4BRJ+4Z2tY9oPfTDak6cuqcyREBAAKRw+nSP8rsjfrVVV1ks1pMjAhAODE1kcrNzVWfPn30yiuvePW4Xbt2KT093f3WvHlzP0UIM8RFR+jeIW0lScVOl2YvY68UAOBiczemas+xHElSv9aNdGX3BJMjAhBOTG1pM3bsWI0dO9brxzVv3lyNGjXyfUAIGD8b1k6vpRxQbqFDH/9wVL+4vJMSG0abHRYAIEAUFDs0Y9Fu9/Fvrukqi4VqFIC6E5R7pPr27asWLVroyiuv1MqVK6s8t6CgQNnZ2eXeEPga1YvUXec7+BU6nFSlAADlvLf2sFLP5EmSRnRupsvaNzE5IgDhJqgSqRYtWmj27Nn65JNP9Mknnyg5OVmjRo3Shg0bKn3Ms88+q4YNG7rfkpOT6zBi1Mb9w9spOsL4EX1/3WEdO5tvckQAgECQU1Csfy0pbUb0xNVdTIwGQLgKqkSqS5cuevDBBzVgwAANGTJEr7/+uoYMGaIZM2ZU+pgnn3xSWVlZ7rcjR47UYcSojaaxUbpjUBtJUkGxU/9dccDkiAAAgeD1lAM6mVsoSbq+dwv1bNnQ5IgAhKOgSqQqMnDgQO3dW3mL7KioKMXFxZV7Q/B4cER7RdqNH9N31hzSqfP/cQIAwtOp3EL9e/l+ScYg98evohoFwBxBn0ht2rRJLVq0MDsM+EnzuGhNutRYjnmu0KHXUvabHBEAwEwzv9urnIJiSdJPLklWu6b1TY4IQLgytWtfTk5OuWrSgQMHtGnTJsXHx6t169Z68sknlZqaqrfeekuS9OKLL6pdu3bq0aOH8vPz9d///ldLlizRwoULzfoUUAceHNlB7607rCKHS/9bdUg/H95BDetFmB0WAKCOpZ3J01trDkmSouxWPXpFJ5MjAhDOTK1I/fDDD+rXr5/69esnSZo2bZr69eunp59+WpKUnp6uw4cPu88vLCzU448/rl69emnkyJHavHmzvv32W11xxRWmxI+6kdQoRjcPMKpSOQXFemMVe6UAIBy99O0eFRY7JUk/HdKWsRgATGVxuVwus4OoS9nZ2WrYsKGysrLYLxVEjpw6p1HPL5XD6VJctF0rf3u5GkRTlQKAcLH3WI6umrFMTpfUINquFU+MVqN6kWaHBSAI+Ov6P+j3SCE8JMfX04R+LSVJ2fnFemv1IZMjAgDUpWe/3CHn+T/9Th7ZgSQKgOlIpBA0pozuKOv5ofWvpRzQucJicwMCANSJJTsztXjnMUlSQlyU7h3a1tyAAEAkUggi7ZrW1w19kiQZ7W/fXXO4mkcAAIJdfpFDzyzY7j7+f9d2U71IU3tlAYAkEikEmUdGd5TlfFXq1eX7lV/kMDcgAIBfvZZyQIdOnpMkDWwXrxvP/0ENAMxGIoWg0imhgcb2TJQkncgp0PvrqEoBQKhKO5Onfy0xxqRYLdIzN/aQpeSvaQBgMhIpBJ1HRpfODXl12X4VFFOVAoBQ9Jcvdyjv/MqDuwe3VbcWdNsFEDhIpBB0uifFaUy3BElSRna+Pv7hqMkRAQB8bdW+E/rix3RJUnz9SD02prPJEQFAeV4nUvfcc4+WL1/uj1gAj/3yio7uj2ct3acih9PEaAAAvlTkcOoPn21zH//mmi5qWI/ZgQACi9eJVFZWlsaMGaNOnTrpr3/9q1JTU/0RF1Cl3q0aaWTnZpKk1DN5mruBn0MACBVvrz6k3Zk5kqQ+rRrqlgHJJkcEABfzOpGaN2+eUlNT9dBDD+nDDz9U27ZtNXbsWM2ZM0dFRUX+iBGoUNmq1CtL96qYqhRQt/LypMxM4z3gI8fPFmjGot3u42fG9ZTVSoMJAIGnRnukmjVrpmnTpmnz5s1au3atOnbsqLvuuktJSUl67LHHtGfPHl/HCVxkQJt4DenQRJJ06OQ5LfgxzeSIgDCRkiJNnCjFxkqJicb7iROllSvNjgwh4Lmvd+psgTFw/SeXtFLf5EbmBgQAlahVs4n09HQtWrRIixYtks1m07XXXqstW7aoe/fumjFjhq9iBCr1i8tLO/j9a8leOZwuE6MBwsCsWdKIEdKCBZLzfBXY6TSOhw+XZs82Nz4EtQ2HT+vj9UYDoQbRdj1xTVeTIwKAynmdSBUVFemTTz7R9ddfrzZt2ujjjz/W1KlTlZaWpv/973/69ttv9dFHH+mPf/yjP+IFyrmsfbwubdtYkrTveK6+2ppuckRACEtJkaZMkVwuqbi4/H3FxcbtDz9MZQo14nC69Pv5pQ0mpl3ZWU1jo0yMCACq5nUi1aJFCz3wwANq06aN1q1bpx9++EGTJ09WXFzpbIfRo0erUaNGvowTqJDFYrmoKuWkKgX4x/Tpks1W9Tk2m8SKBNTARz8c0ZbULElSl4QGuuuyNiZHBABVs3v7gBkzZuiWW25RdHR0pec0atRIBw4cqFVggKeGd2qqPsmNtPnIGe3MOKtFOzJ1dY9Es8MCQktenjR/fulyvsoUF0tz5xrnx8TUTWwIemfOFeq5r3e6j58Z10N2G6MuAQQ2r39L3XXXXVUmUUBds1gserRMB7+Xl+yRy0VVCvCp7Ozqk6gSTqdxPuCh6Yt26/Q5o/PvDX2SdFn7JiZHBADV4889CAmjuzRXz5bG8tKtqdlauuu4yREBISYuTrJ6+F+G1WqcD3hge1q23llzSJIUE2HT/7uWBhMAggOJFEKCxWLRI6NL90r9k6oU4FsxMdK4cZK9mhXhdrs0YQLL+uARl8ulP3y2TSVbW39xRUe1aMjPDoDgQCKFkHFV9wR1SWggSdp4+IxW7j1pckRAiJk2TXI4qj7H4ZAee6xu4kHQ+2xzmtYdPCVJate0vu4b1s7kiADAcyRSCBlWq0WPXF66V+qfSxgMDfjUsGHSzJmSxXJxZcpuN26fOVMaOtSc+BBUcgqK9ZcvdriPn76hu6Ls1XSFBIAAQiKFkHJtrxZq36y+JGndgVNau5+qFOBTkydLK1YYy/xK9kxZrcbxihXG/YAHXl6yR8fOFkiSxnRrrtFdmpscEQB4h0QKIcVmteiR0WU7+O01MRogRA0dKs2ZI+XkSBkZxvs5c6hEwWP7jufo9RRjTEqk3ar/u767yREBgPdIpBBybuyTpDZN6kmSUvae0PpDp02OCAhRMTFSQgKNJeCVkgYTRQ6jw8SDI9qrTZP6JkcFAN4jkULIsdusenhUB/fxy+yVAoCAsXB7plbsOSFJatkoRg+P6ljNIwAgMJFIISRN6NdKLRsZfyVfuuu4fjx6xtyAAADKL3LoT59vdx8/dV03xUTSYAJAcCKRQkiKtFs1uVxVir1SAGC22cv26ejpPEnS0I5NdE3PRJMjAoCaI5FCyLplQCslxEVJkhZtz9SO9GyTIwKA8HXk1DnNWrpPkmS3WvSHG3rIYrGYHBUA1ByJFEJWdIRND44orUr9i6oUAJjmz19sV0GxU5L00yFt1en8AHUACFYkUghpkwa2VtPYSEnSl1vTtffYWZMjAoDws3z3cX2zLVOS1DQ2So+O6WRyRABQeyRSCGkxkTY9MLy9JMnloioFAHWtsNipPyzY5j5+cmxXNYiOMDEiAPANEimEvDsva6PG9Yz/tD/bnKYDJ3JNjggAwsebqw5o/3Hj9+6ANo01oV9LkyMCAN8gkULIqx9l133D2kmSnC5p5ndUpQCgLmRm5+ulb41ZfhaL9MyNPWS10mACQGggkUJYuHtIW8VF2yVJczem6sipcyZHBACh729f7VRuoUOSdPvA1urZsqHJEQGA75BIISzERUfop0ONqlSx06VZy/aZHBEAhLbvD57S3I2pkqRG9SL0q6u6mBwRAPgWiRTCxs+GtlX9SJskac4PR5WelWdyRAAQmhxOl56eX9pg4ldXdVHj+pEmRgQAvkcihbDRqF6k7hnSVpJU6HDq1WX7zQ0IAELUe2sPuYeg90iK06SBrU2OCAB8j0QKYeW+Ye0UE2FUpd5fd1jHzuabHBEQxPLypMxM4z1w3qncQj2/cLf7+Jkbe8hGgwkAIYhECmGlSWyU7rzM+MtoQbFT/1lOVQrwWkqKNHGiFBsrJSYa7ydOlFauNDsyBIB/fLNLWXlFkqSJ/Vrqkrbx/n9RknoAJiCRQth5YER7RdmNH/131hzWiZwCkyMCgsisWdKIEdKCBZLTadzmdBrHw4dLs2ebGx9MteVolj74/rAkKTbKrt+O7erfFySpB2AiEimEneYNot3r9fOKHJqxaHc1jwAgybhonTJFcrmk4uLy9xUXG7c//DAXsWHK6XTp6c+2yuUyjh+9opOax0X77wVJ6gGYjEQKYenh0R3cHfzeX3dY29OyTY4IuEAgLlWaPl2y2ao+x2aTZsyom3gQUD7dmKqNh89Ikjo2j9VPh7b134uR1AMIACRSCEvNG0TrF1d0kiQ5XdIfFmyTq+TPqICZAnWpUl6eNH/+xRetFyoulubODawEEH6XnV+kv321w338hxt6KMLmx0sMknoAAYBECmHr3qFt1bZJPUnSugOn9MWWdJMjQtgL5KVK2dmlMVXH6TTO95VArM6hnJe+3aMTOYWSpLE9EzWsU1P/vRhJPYAAQSKFsBVlt+mp67q7j//6xQ7lFTpMjAhhLdCXKsXFSVYP/8uwWo3zaytQq3MoZ3fmWb256qAkKTrCqt9d182/L2hmUg8AZZBIIaxd0a25RnRuJklKy8rX7GX7TI4IYcvXS5VOnZK2bjXe+0JMjDRunGS3V32e3S5NmGCcXxuBXJ2Dm8Pp0v/7dIscTmNp9MOjOqpV43r+fVEzknoAqACJFMKaxWLR09d3l/38sMjZy/bp6OlzJkeFsOPLpUozZ0pJSVKTJlKvXsb7pCQjMamtadMkRzVVW4dDeuyx2r1OoFfn4PZ6ygH9cOi0JKlNk3r6+Yj2/n/Ruk7qAaASJFIIex2bx+qeIW0lGUN6n/1qp7kBIfz4aqnSpElGApJ+wX6/9HQj8bj99trFOWyYkahZLBdfxNrtxu0zZ0pDh9budWgkEBT2HsvRPxbukmR86/9xcx9FR1TzffOVukrqAaAKJFKApF9e0UlN6kdKkr74MV1r9p80OSKEFV8sVZo5U/rgg6of+/77ta9MTZ4srVhhVARKYrZajeMVK4z7a4NGAkGh2OHU4x9vVmGx8QeAnw1tp4Ht4usugLpK6gGgCiRSgKSGMRH69dVd3MfPLNjuXvMP+J0vlir9+c+evZan51Vl6FBpzhwpJ0fKyDDez5njm4tWGgkEhX+v2K/NR85Ikto3rV/u92ed8XdSDwDVIJECzrvlkmT1SDL+0r8jPVvvrztsckQIK9OmeVaFqWip0qlTFy/nq0xamm8bUCQk+HYPCo0EAt6ujLN6cdEeSZLVIj3/kzpc0nchfyb1AFANEingPJvVoj/c2MN9/MLCXco6V2RiRICH0tL8e35dopFAQCtyODXto00qdBhVw5+P6KD+rRubHJX8k9QDQDVIpIAyLm0brxv7JEmSTp8r0oxvd5scEcLG9OmeJQ8VNVhISvLutbw9v67RSCBgzfxun7alGcspOzWP1dQxnUyOCADMQyIFXODJa7sq5vwylbfXHNKujLMmR4SQV9sGC/HxUosWnr1WUpJxfiCjkUBA2pqapZeXGEv6bFaLXjBzSR8ABAASKeACLRrG6OFRHSQZwyb/+Pk2uVw0noAf+aLBwlNPefZ4T88zG40EAkphsVO/+nizit2Ddzuod6tG5gYFACYjkQIq8MCI9mrV2Fhrv3LvSS3cnmlyRAhpvmiw8PDDxhypqkyaJD30kPfxmYVGAgHjn4v3aOf56ny3FnH6xeUs6QMAEimgAtERNj11XTf38Z+/2K78omr2bAA15asGC++9Zyx5u3APVFKScft77/km3rpGIwFTbT5yRrOW7ZMk2a0WvXBLH0XauXwAAH4TApW4ukeiBrdvIkk6cipPr6UcMDkihDRfNVh46CEpNVU6eVLassV4n5oaXJUoBIz8Ioce/3ize67eL6/opO5JtJwHAIlECqiUxWLR72/sLqvFOH7lu73KyMo3NyiELl83WIiPl3r2DPzGEghoMxbt1t5jOZKkXi0b6qHz+0cBACRSQJW6JsbpzsvaSJLOFTr0t692mBwRQhoNFhBA1h86pX+v2C9JirRZ9cJP+ijCxmUDAJSoZkE+gGlXdtZnm9N05lyR5m1K012D22hAG/7KDz8ZOtR4y8szuvPFxbE3CHUur9ChX338o0oalj52ZWd1TmhgblAAEGD40xJQjUb1IvX4lZ3dx88s2C6nk3bo8DMaLMBEz32zUwdO5EqS+iY30gPD25kcEQAEHhIpwAOTBrZW10Tjr7E/Hs3SnPVHTY4IAPxjzf6TemPlQUlSlN1Y0mdnSR8AXITfjIAH7Darfn9DD/fxc9/sVHZ+kYkRAYDv5RYU69dzNruPfz00SR1ibSZGBACBi0QK8NDgDk10ba9ESdKJnEK9vHiPyREBgG/97audOnIqT5J06dFtuve6/lJsrDRxorRypcnRAUBgIZECvPDk2G6KOj+I8o2VB7XveI7JEQGAb6zce0JvrzkkSYopytc/vnhRNpdTcjqlBQuk4cOl2bNNjhIAAgeJFOCF5Ph6enBEe0lSsdOlP32+3eSIAKD2zuYX6Yl317mPf7v0TbU9k156QnGx5HJJDz9MZQoAziORArw0eVQHtWgYLUlauuu4vtt5zOSIAKB2/vLFDqXmGd1IBx/arLs2fFHxiTabNGNGHUYGAIGLRArwUr1Iu568tpv7+E+fb1dhsdPEiACg5r7bdUwffH9EklS/4Jye+/IlWVXJiIfiYmnuXGPOGQCEORIpoAZu6N1CA9saQ3n3n8jVm6sOmBwRAHgv61yRfvvJj+7j3333mpKzq6myO53GsGgACHMkUkANWCwWPX1Dd1ksxvE/F+/VsbP55gYFhJO8PCkzk8pILT3z+TZlZhdIkoYf2KBJm7+p/kFWqxQX5+fIACDwkUgBNdSzZUPddmlrSVJOQbH+8fUukyMCwkBKitGKOzZWSkysuDV3RUlWICRe/o7By+dftD1Tn25IlSQ1iLLr767dstjtVT/IbpcmTJBiYmobLQAEPRIpoBZ+dVVnNYg2Ljw+Xn9Um4+cMTcgIJTNmiWNGGG04nae35dYtjX3r351cZI1cqTxVlXi5W+eJH91/Pyncwv15Kdb3MdP39BdSb98UHI4qn4th0N67DHfxA0AQc7URGr58uW64YYblJSUJIvFonnz5lX7mKVLl6p///6KiopSx44d9eabb/o9TqAyTWKjNHVMZ/fxHxZsk9NZySZtBL9AqGqEq5QUacoUowV3cXH5+0pac7/wgvTZZ+WTrOXLjbeKEq+6mIlUXfJX2xhq+PxPf7ZNJ3KMJX1XdG2umwe0koYNk2bOlCwWo/JUlt1u3D5zpjR0aO1iBoAQYWoilZubqz59+uiVV17x6PwDBw7ouuuu0+jRo7Vp0yZNnTpV999/v775xoM13YCf3D24jTo2j5UkbTx8RvM3p5ocEXzO3xUFVG/6dKP1dnWqq6hIdTcTyZPkrzYx1PD5v9ySrgWb0yRJDWMi9OzEXrKUbPicPFlasUIaN87YCyUZ78eNM26fPLlmsQJACLK4XK6A+PO5xWLR3LlzNX78+ErP+c1vfqMvvvhCW7dudd9222236cyZM/r66689ep3s7Gw1bNhQWVlZimOzLHxk+e7juvt1Y5hlQlyUljw+SvWjqtlrgOAwa5ZxsWqzlb9YtduNi/aZM7m49Le8PCN5dfp4zIDNJt1wg9HO2x8mTjQqQxcmOWXZ7UaSMmdOnTz/iZwCXTVjuU7lFkqSXrqtr8b1bVnxY/PyjO58cXHsiQIQ1Px1/R9Ue6RWr16tMWPGlLvt6quv1urVqyt9TEFBgbKzs8u9Ab42onMzjemWIEnKzC7QK9/tNTki+IS/KwrwTHa275MoyUiE580zEg1ffw/z8qT586tOcqSaz2WqwfO7XC49NXerO4m6ukeCbuyTVPljY2KkhASSKACoRFAlUhkZGUpISCh3W0JCgrKzs5VXyX9Czz77rBo2bOh+S05OrotQEYb+7/puirQZ/6T+u+KADp3MNTki1Jony8lsNmnGjLqJJ1z5e/XAF1/4fs+UN8lfTeYy1eD5P9ucpq+3ZUiS4utH6i8TyizpAwB4LagSqZp48sknlZWV5X47cuSI2SEhRLVpUl/3DW8nSSp0OPXnL3aYHBFqxd8VBXjO319bh8P31cW4uNI9RtWpyVwmL5//mCVKT8/f5r7pT+N6qmlslHevCQAoJ6gSqcTERGVmZpa7LTMzU3FxcYqpZOlBVFSU4uLiyr0B/jJldEc1b2BcnCzanqkVe46bHBFqzN8VBXguLa1uXseX1cWYGGPJoL/mMnnx/K4JE/Tkl3uUlVckSbq+dwtd17uFd68HALhIUCVSgwcP1uLFi8vdtmjRIg0ePNikiIDyYqPs+s01Xd3Hf1ywXUUOP+ztgP/5u6IAzyVVsY/Hl3xdXZw2zb9zmTx8/k9unqLFO49JkprGRuqP43rW7PUAAOWYmkjl5ORo06ZN2rRpkySjvfmmTZt0+PBhScayvLvvvtt9/uTJk7V//3498cQT2rlzp2bOnKmPPvpIjzEcEAFkQr+W6pvcSJK051iO3llzyNyAUDP+rijAc/HxUos6qqD4srro77lMHjx/+j9f1TM7C903/3VCL8XXj6zZ6wEAyjE1kfrhhx/Ur18/9evXT5I0bdo09evXT08//bQkKT093Z1USVK7du30xRdfaNGiRerTp49eeOEF/fe//9XVV19tSvxARaxWi/5wYw/38YxFu3Xy/OBLBBl/VxTguaeeqpvX8XV10d9zmap4ftfy5fpNvT46m2/s85vYr6Wu6pFYu9cDALgFzBypusIcKdSVX328WXPWH5Uk3T6otf46oZfJEaFGZs82mhAwR8p8t98uvf++/56/NjOdPOHvuUwXPP/76w7ryU+3SDLm2y2cOlIN60X4/nUBIMAxRwoIMk9c00Wx54fyvr/usLYczTI5ItSIvysK8Nx77xmJq7/2TPm7uujvuUxlnn9rapb+8Flpl76/TexNEgUAPkYiBfhJ8wbR+sXlHSUZnZUf+2iT8gqrWSaGwDR0qFGlyMmRMjKM93Pm1HxvC2ruoYek1FRpzx7fPafNVvv9SgHkzLlCTX5nvQqKjUY3tw9qrdFdm5scFQCEHhIpwI/uHdpOPZKMEvLeYzn6y5fbTY4IteLvigI8l59fs8dV1InR4ZAefzwkqosOp0u//GCTjp42Og/2SW6k39/Q3eSoACA0kUgBfhRpt+ql2/oqOsL4p/bOmsNatD2zmkcBISovT8rM9E178Zou76tsNtgLL/huGK+JZizareW7jfl1TepHatYd/RVlt5kcFQCEJhIpwM86Nm+gp64r/Yvwbz75Uceya/jXdCAYpaRIEydKsbFSYqLxfuLE2iUuvm6JfuEwXm+SPl8miLXwzbYM/eu7vZIkm9Wil2/vp6RGVE8BwF9IpIA6cMeg1rqye4Ik6VRuoR7/eLOczrBqmIlwNWuWNGKEtGBBaTXI6TSOhw83uiLWlC9bopcM41282POkzx8JYg3tO56jxz/a7D5+cmxXDenQtM7jAIBwQvtzoI6cyi3U1S8u1/Gzxkyp/7u+u+4b1s7kqAA/Skkxkqiq/puxWIzuhzVt8uCPluh2e/Wt7mfNkqZMCYi2+DkFxRr/ykrtPZYjSbq+dwu9PKmfLBZLnbw+AAQ62p8DQS6+fqSm/6SP+/jvX+3U9rRsEyMC/Gz6dCPRqMqFS+q8VdISvakPqy9lE6OSY5fLmCe2cqWRIE6ZYtxW3bl+5nK59OuPN7uTqC4JDfTczb1JogCgDpBIAXVoeKdmuv98FarQ4dSjH2xUfhEt0RGC8vKk+fMvTjQuVLKkrjb7ix56yFgmWFFHPk95kniUJH11kSB66NXl+/XV1gxJUoNou2bfNUD1Iu1+f10AAIkUUOd+fU0XdWthlJX3HMvRX7/cYXJEgB9kZ1feIe9CTqdxfk2VJG2evl5FPFnlXpL0zZtXNwliNVL2nNBzX+90H794a1+1a1rfb68HACiPRAqoY1F2m/55W19F2Y1/fm+tPqTFO2iJjhDj7Rr02qxZ9yZpu5Dd7lk1qoTT6VnSVXJubRLEKhw9fU6/eH+DSnrWPHpFJ13RLcEvrwUAqBiJFGCCTgkN9NT1pS3Rfz3nRx07S0t0BCl/t/+u7vkjIrxLhkqWAFqt0rhx0rffer4s0Gr1/LWs1toliJXIL3Jo8jvrdfpckSRpdJdmevSKTj5/HQBA1UikAJPcOai1xnRrLsno6Perj3+kJTqCQ0liU1WrcG8rMRWdX1178ZL7mzXzrEpkt0s33STl5EgZGcb7OXOkyy83Eip7NXuL7HZpwgRp/HjPz43x7Rwnl8ulp+Zt1dZU4+vVpkk9vXhrP1mtNJcAgLpG+3PARCdzCnTNSyvcLdGfvr67fkZLdASqlBSj0ULZ/UgWS/kkpqT994svSo895tmSO6vVSGrKJh3VtRe/9Vbpww8vvr8qVbVa96ZVu8vl/7bulXhnzSE9NW+rJCkmwqZPHx7i3nMJAKgY7c+BENQkNkov3FLaEv1vX+3UjnRaoiMAVTRYV7o4mShp/z11qjRsWM0qN560F//gg4rvr+w1LBajTXplic2wYcb9FsvFMV/4eG/O9aH1h07rmQXb3Md/u6kXSRQAmIhECjDZiM7N3IN5aYmOgFRVYlMZm81IKBzV/Cw7HEblqixP2ot7qmQf1IoV1Q/InTzZOG/cuIv3UV34eG/O9YFjZ/P18LvrVeQwEtf7hrXTuL4tffoaAADvsLQPCAD5RQ6Nf2WldmaclSTdM7iNnhnX0+SogPMmTjQqUZ4mUSWsVmOW0tSplS/RmzmzfNKRl2fshapNK/Oyr3/8uBQf7/1j8/KMfVtxcdXvc/Lm3Boocjh1x3/Wat3BU5KkQe3i9c79gxRh42+hAOAJlvYBISw6wqaXJ/Vzt0T/3+pD+m7nMZOjAuT5YN2KOJ3GXiZvKje1aWVe0esXFdXssTExUkKCZ4mRN+dWporOhH/9coc7iUqMi9a/bu9f90mUvzszAkAQIpECAkSnhAZ66rpu7uNfz9nsbkIBmKY2iU1J+++hQ43ueBd2y6toD1FcnOetyD19/UBWTWfCeRtT9cbKg5KkSJtVs+7sr2YNogImPgAIZyRSQAC587I2uqKr0RL9RE6hfj1ns8Js9S0CTU0Tm4qaSHhSuYmJMapV3syF8vT1A01FDTycTuN4+HBt/+dr+u2nP7pP/8ONPdSvdeOAiU+zZ9ddLAAQgEikgABisVj095t7q2ms8RfnpbuO63+rDpobFMJbSWJTXfe9C1XURMJTJY0tauPC1w+0pWnVdCY8E1VfD26X8ouMBObWS5I1aWBywMQnl0t6+GEqUwDCGokUEGCaxkbp+Vt6u4//+tVO7cygJXpICbSL+upMm1Z9970Svmj/3bMWjVYufP1AXZpWRWdCh8WqR2/4lY40SpQk9W7VUM+M6yFLbat0PorPzWYzmokAQJgikQIC0KguzXXv0LaSpMJipx59fxMt0UNBoF7UV6dkblJ1LBbftP+Oi/NuaV9lTSwCdWlaNQ08Xho6ScvaXyJJij+XpVk391B0hI/awfsgPrfiYmnu3OD5gwAA+BiJFBCgfnNNV3VNbCBJ2pV5Vn/7aqfJEaFWAvWi3lOeVIlcLmM5XW0H0a5f79nSPptNuummiptYBPLStCoaeCzqOFD/HDpJkmR1OvSv+X9XS0thXUbnXYMRp9M4HwDCEIkUEKCiI2z6Z5mW6G+uOqjvdtESvc74cvldIF/Ue2r69Or3Sdntvlnq9Y9/eNbgomQfVEVNLHyxNM1fSzAraeCxv3GSpl3/uPv4t8ve1JCjW+u+86A3DUaCoTMiAPgJiRQQwDonNND/u7ZMS/SPN+tEDi3R/cofy++Cfb9JaqqxhMvfS71SUoyleZ995llFxGKR+ve/+PbaLk3z9xLMChp45EZEa/KE3+lsVH1J0nU7V+iBDQsq7zzoz312njYYCYbOiADgRyRSQIC7e3AbXV62JfrHtET3G38svwvm/SYzZ0pJSVKrVp4/pqZLvUq+9l984fljXK6KX6s2S9PqaglmmQYeLklPjP2ldjdrI0nqdOKQnvvyJVkq6nxYV/vsPGkwUpvOjAAQAkikgABnsVj03M291TQ2UpL03a7jemv1IZOjCkH+Wn4XrPtNJk0yvh7p6d49riZLvcp+7T3tDljVa9V0aVpdLsEsaeBhsei/g27SF91GSJIaFOTq1c/+rvrFBRd3PqzLfXZl4ruoMuWLzowAEAJIpIAg0DQ2Sv+4pY/7+C9f7tDuzLMmRhSC/LX8zhf7Teq6XfrMmdIHH3j/uJou9fLka+/Na9V0aVpdL8GcPFmr5i7RsyPvcd80/YsZaj/i0os7H5qxz27yZCOOceMq74wIAGHM4gqzNULZ2dlq2LChsrKyFMcGWQSZP3y2TW+eH9DbNbGB5k0ZWrdtkUNVXp6xRMqTypHVanSH8yZZmDjRqBpUtbzPbjcuUOfMKb0tJcW4uJ8/34it5CL28cc9qwTk5RkVrrg47+JNSvK+EiUZVYoVK7yrUnjztffmtVJSjOpNdf/FpaQYz+Hvn4EKpJ3J0/Uvp+hUrtGV75e9Gmra2O5SfPzFJ9f0Z8hXavqzBAABwF/X/1SkgCDy27Fd1SXBaIm+M+Osnvt6l8kRhQh/L7+ryX6T2izjqs0+mlOnvE+iarrUKyXFaF/ubRIlSbfdVvVrVbU0rYTFIr3wgvF1qeMlmPlFDj30znp3EjVq/w969K6RUrNmF3+vAmGfXUWdEQEgzJFIAUGkpCV65PmW6K+vPKCltESvPX+3e/Z2v0ltlnHVdh9NWpp3n5tUs6VeJXEuXOj960nG0sPqEsOyS9MqGvDrcpV+XT78sE5bfv/hs23afDRLktT6TIZeXPC8bC5nxd+rYN1nBwAhjkQKCDJdEhvo/43t6j7+1cc/0hK9tjzdU2OzSWPH1uw1vNlvUtO9Or7YR5OU5PnnJElHj5YOwfVUTZtLlOXpXqWhQ6WpUyu/v+TrMnWqkfDWQcvv99Ye1gffH5EkRRfla/anf1Gj/JyLYyr5XjHXCQACEokUEITuGdJWo7s0kySdyCnQb+b8SEv02vJ0+d0XX9S85fTQoUbSkZMjZWQY7y9MQmqzjMsXzRLi46UWLar/XCQj6WrZ0rNzy6pJc4kLebOMzdOvi8Xi95bfX29N1//N3+o+/tvX/1L34wcqj2nGDOY6AUCAIpECgpDREr2PuyX64p3H9M4aWqLXiid7akrUtuV0VftNarqMy5f7aJ56yrPX9/S8sjyN0xOeLGPz5uuyYoX04ot+a/n93c5j+sX7G+VwGn/0uO/7eRq/fWnVMZV8r5jrBAABh0QKCFLNGkTpHzeXtkT/8xe0RK+1ipbfVcZfLadruozLl/toHn7YmCNVlUmTpIce8uz1yvImzupYrUaSUVVS6O3X5dZb/dLye9XeE3rwnfUqchhJ1E1bvtXvlrzmWUzZ2cx1AoAARCIFBLHRXZvrp0PaSpIKip365fsbVVBcwz0nMJRdfnfttZ7tm/LVXCHJu/1a111XWtXy9T6a994zLswv3DOVlGTc/t57nr3WhbyJszpOp9SuXeVLLWfOlPr29fz5Sr4unizB9MIPB0/p/rd+UGGxkdBd16O5nvvmX7LKg+W4Zb9XzHUCgIDCHCkgyOUXOTTuXyu163w1amL/lnr+5j6yWivoUgbPmTBXyM3TGUiSsZ/p//7PqA55O2vI09lAp04Z3fwaNzYeX9tZQhMnls7G8hW73VjaNnOmkVBMmuTdUGE/zWD68egZ3fGftTpbYHxPxnRL0Kw7+yvilptrNxeKuU4A4DHmSAGoUHSETS9N6utuif7phlT97eudJkcVAsxsOe3Nfq30dGMp3u23e76P5vLLvZsztX279PTTUuvWpeePG2ckAjWZWTRmjG+TKKn8Ustp07xLoiS/7C/amZGtu19f506ihndqqn/d3k8RNmvt9zwx1wkATEciBYSArolx+udtfVVShPr38v16ddk+c4MKdt4ulYuIkDIzfTcMtboZSBd6/31py5bq99Hceqv0yCMXz5n67LOKm2dUNpfqs8+kG2+U6tf3voPht9/6bnnfhWw2I2Zvzpd8vr9o3/Ec3fnftTpzrkiSNLBdvP591yWKjjj/eux5AoCgRyIFhIhrerbQXyb0ch8/+9VOffTDERMjCnLe7FVKTJSaNfOsuuONkr06CQmenf/nP1e9j+Zf/zIGz1Y0Z8rhMG5/6KHSRKSquVQlXK7Kk7CKlHTR83VFqkRxsZSf7/n5Dofx9Vm40GdNQ46cOqc7/rNWJ3IKJUl9kxvp9Z9eqpjIC1qws+cJAIIae6SAEPPKd3v1j292SZJsVotm3zlAV3b38EIc5aWkGAlCdWy28su0LtyvUxunTklNmnh+/smTxiwo6eJ9NJ7soSoxa5aRXHh6vmRUUVasqLqKkplpJJyBxkffs/SsPN0ye7WOnjYqk91bxOn9By5Tw3oRVT+QPU8A4DfskQLgkYdHddC9Q9tKkhxOlx55b4PW7j9pblCh7sK9Lr5sjZ6WVvPzy+6j8XZ+00MPSfPmeTfvyZMOhnFxni1VrGs++J4dO5uvO/6z1p1EdWweq7fvG1h9EiWx5wkAghCJFBBiLBaL/u+67hrX12hbXVDs1P1v/aDtaT5shhAupk+vfmlfVXzRGv3C9uM1Pd/b+U1Wq2ddA8uqbthvSop0xx3eP6837HYpOrrmj6/h9+x0bqHu+u867T+RK0lq06Se3rt/kJrERtU8FgBAQCORAkKQ1WrRP27uo5Gdm0mSzuYX65431unwyXMmRxZEvK3gVKS6xMIT8fFGi3NPJCWVLuu7kLfzm2q6h6myDoZlm1b4k8NRs0HBJWrwPcvKK9Jdr691jyBo2ShG794/SM3japjQ5eX5tnEJAMAvSKSAEBVpt2rWnf3Vr3UjSdLxswW66/W1On62wNzAgoW3FZzK+KI1+lNPeXbe1KnS1q1SaurFF+IlzTNstkofXiFvz69o2K8nTStKlHSsmzVL6tDB89ct2+lu+nTpllu8i7ssL75nuQXFuveNddqaapzfvEGU3r1/kFo1ruf966akeNeWHgBgKhIpIITVi7TrjZ9eqk7NYyVJh06e0z2vr1N2fpHJkQUBbys4lakosfDWww8bA2arEh0tPfGE1KuX1KqVcSF+YWvyadO8X95X3ayjsux2acKEi/f5TJ/ueUJW0l1w4UJp/37PHmOxlHa669nT+Jw/+cTzuC/k4fcsv8ih+//3gzYcPiNJiq8fqXfvH6S2Tet7/5qVtZlfsMDzjogAgDpFIgWEuEb1IvXWfQOV1NBYZrQ9PVsP/O8H5Rd5cYEcjjxtf16VyhKLmnjvPaPacuEeqKjze3AqavntchkNI0ouxEtmF3nCYjHmRP3978axJ4lQyQDZskvTvFkiabUasZbMuapqL1VJBervf5dyc4028T/+eHEyUhOJidKGDVWeUlDs0INvr9fq841c4qLtevu+geqU0MD716uqYufLxiUAAJ+i/TkQJvYey9Ets1fp9PkBoVd1T9DMO/rLbuPvKZVKSTEuzGv6a9KTduA18eWXRpVn8eKaxXLbbcY8KU8e43IZCU5iYuUdBEtah0+bZlSRSuZEWa1S69bSwYOex+kJq9VIUB97rPRrW9vvVVk2mxF/Ja3Qix1OTXlvg77ZlilJqh9p0zv3D1K/1o1r9nqetKW3243Efs6cmr0GAIQxf13/k0gBYWTzkTOa9J81OldoVKNuuzRZz07sJUsgtqMOFLNnG9UAm638ha7dXnpc9uOSY1/NkbrQrFlG9eLCeKpT9kK8aVNj3pQ3Sj6nceOktWul9PTS+5KSjCTmww+9j+tCF87kquj+G24wGkKU5c2MLE9VkAg7nC5N+2iT5m8yksroCKv+d+9ADWrvxayvsvLyjL1QnlTQrFYpJ4cW6QDgJeZIAai1PsmN9OpdAxRhMxKnD74/oucX7jI5qgA3ebJxMT1uXOmeKavVOE5JMd4qum/FCt8nUd40bbhQSTe61FTvk6iSx5csFczMLH9fZqb0wQc1i6tEyRLK6vZkORzSZ5+Vb6Rx6lTtOyxW5IJW6E6nS//v0y3uJCrSZtV/7r6k5kmU5F1TE180LgEA+AwVKSAMff5jmn7x/kb3Kqj/u7677hvWztyggkFennEhGxd3cVWgqvt8xRdVl6+/lq65xncx+UrJMkJPZWRIe/YYSxwvrE750vkqkCs6Ws8s2K43Vx2UJNmtFs2+c4DGdE+o3fNTkQIAv6MiBcBnru+dpD/e2MN9/KfPt2vuxqMmRhQkYmKkhISKL2Srus8XfDHXymo1YgxEf/qT510SrVajAjZihPE18SenU66sLP3t653uJMpqkV68rW/tkyjJ86YmvmxcAgDwCRIpIEzdNbitHr2ik/v41x//qO92HjMxohDn7ZDVC8+v7VyrkgvxLl1q/hz+NG2a5wnF8OFGowmXyzezvqpiteqfm07p1WWlrdifu7mPru+dVMWDvDRtmmdLGh97zHevCQCoNRIpIIxNHdNJd13WRpJU7HTpoXfXa/2h0yZHFWK8HbJa2fnbttVurlXJhXhMjNSwYc2fxx+uvdZIFKdM8SyhKOkkWFMlyVp1z2G369/3/p9mLD3gvunP43vq5gGtav7aFSlpS2+xXJxIlh007OvujwCAWiGRAsKYxWLRH27soet6t5Ak5Rc59bM3v9fuzLMmRxYivB2yWtX5Y8ZIvXt7P9fKYil/IV6ylyuQfPmlkTRedZXUp49x24Wfp81mfB6/+IW0fLl3g4IvdP310iuvVLsn6+1eV+uvTS91Hz91XTfdef4PDx7xpgpZVVMTfzQuAQDUGs0mAKig2KH73vxBKXtPSJIS4qL0yUND1KpxPZMjC2KezDUq2147JcVIrnzJYjGqWWXnLWVmGklLoLJajeSxXz9p82b/LN3LyDD2ilXR2v7jbqP062unum96/MrO+kWZpbBVSkkxmmCUnac1bpz0+OOeVZXqonEJAIQRmk0A8Jsou02z7xqgPq2MJV+Z2QW6+7V1OplTYHJkQWz6dOMCvSol7bVTUqSf/KT657TbjQSjsiVgkvTUU9LRo0aykJtrzI0qe/Ee6H9AKkmcNm40Pq7ua+gtq7X0a1BJFeizO6bqN2WSqIdGddAjl3f07Pm9rUJWxN+NSwAAPkFFCoDbyZwC3fLqau0/nitJ6t2qod574DLFRnm5nCzcedPSumQYsqe/iq1WadEiY6ne3LmlFY8JE6T77pOSk40BufHxFT9+1iyjChOubrrJSC4vdL4KtDCtQA99vFUOp/H9+OmQtvr9Dd09G1rtbRUSAFAnqEgB8LsmsVF662cDlRgXLUn68WiWHnz7BxUU12I/SjjypsOey+Xd/CSnU+rRw0gGcnKMytMLLxjNK669VurVS2rSxEimZs0q/9iUlJolUZ9+6v1jAtUVV1R8e0yMlmVZ9cicbe4katLAZM+TKMm7KiQAIOiRSAEop1XjenrrvoFqGBMhSVq596SmfbjZfXEJD8TF1a6rXFXKLk2LiZHuuMPYA5WRUf689HQjabr9duM4L0/6619LK2De6OTh3qBAZ7VKixdXeNcH6w7r/v99r0KHkQCP75ukP4/v5XkS5emcr+Jio5LoaRt8AEDAIpECcJHOCQ30+k8vVXSE8Sviiy3penr+VoXZSuCLedqFzdMhq96y2coPZb3ttkoTA7f33zf2VcXGSl995V31q0RSkv8Sw7rkdF6UxBQWO/V/87bqt59uUZHD+Npc0yNRz9/SRzarF0mnN1VIpzPwOicCALwWAv8zAvCHAW0aa9adA2Q/fzH57trDevHbPSZHZRJvZ0FJng1Z9VbZoawpKdKHH3r2uE2bat79rl8/Y79V797Vn2uzGe3LLRbfN4nwlZIkZu9enfjwU935r6V6e80h990/HdJWL9/eT3bbBf89VpdEe1OFLFtVBAAELRIpAJUa3aW5nr+lj/v4pcV79Nbqg+YFZIaadmGrbsiq5P0yO4tF6t/f+Phvf/PusTW1caPxeWzaVP25Doe0ZYvxdRk2zO+h1ViLFto67BrduCxL6zKMxCjS5dBzN/fWH27soYiySZSnSbSnVUi7vXxVEQAQtEikAFRpfL+Wevr67u7j33+2TQs2p5kYUR1KSZGmTDGWw12496W42Lj94Ycrr0xVNWQ1JUUaP967yo3LZVRT8vKMZXp1wW6X/vIXz5cpOp3SqlXG0Nxf/tK/sdXQ/K4jdNMdzyktrrkkqfnZk/rgnSf0k4lDy1edPE2iS6pVU6ZUX4UsW1UEAAQ12p8D8Mg/vtmpV77bJ0mKsFn0yu39dVWPAB7s6gsTJxoXzVU1ELDbjcSoopbaZVU0ZNWTdtllWa1Gp77s7MAeqlvCYpEefVR68UXjY5P/u3FYrPr7yHv070E3uW/rl7pTr879i5rnni490Wo1KmrLl1f/pCNGGN/Hkjb0vXsb1Tu7/aIhv3I4jOre5Mm++6QAANXy1/U/iRQAj7hcLv2/uVv0/rojkozr4qlXdNYvLu8oqzeb8oOFN7OgShKcmizXmj1beuih6s8rm7B5E1sgGDGidH6SGTFbLDoTVV+/uPEJrWjX333zrZu/0R8XzVKUo4JE2dPE78LzShKofv2kzZvLz/l67DHmRwGACfx1/c+UTQAesVgs+vP4XsotcOizzWlyuaQZ3+7WltQsTb+1j+KiI8wO0bdq0oWtJomUp3/LKrskLCZGGjtW+uIL71/PDCtXGl+jF1+UbrxRat/eN9Wphg2Nr7vNVr76c0Fys6tJa/184u90qHGSJMnuKNbvF/9bd278UpX+CcDT+C48rySOTZukb781Zn6VrUICAEIGe6QAeMxmteil2/rqiWu6qKQI9e2OTI3/10rtyTxrbnC+Vhdd2Er2YHmiT5/yxz//ufevZxaHw0g4pk41mlH4aiHEk08aycqFe9AmTjSSNklfdxqsCXc9706i4s9l6Z0Pn9JdVSVRvmCzGcv4EhJIogAgRLG0D0CNLN99XL/8YKPOnCuSJNWPtOn5W/pobK8WJkfmQ77cI1XT5y/7OmX32OTlSfXrm77vyCt2u3T99dJnn/luiV9J845HHjHmXeXkSO3by3n//XrpRD29NGSS+9QeGXv16ty/qFX2cd+8tiex1XTJJwDAZ9gj5SMkUoDvHDl1Tj9/e712pJcOF31oVAf96qou3g0zDVSeNoMYMUL661+N1uQXNpSoTE33OZXsNRo6VGrVSkpN9e7xZrNaa78s0Wot/3W74PhsZIymXTdNizoPdt924/al+vtXLyumuKDmr1sTGRlGVepCFTUfAQD4hb+u/1naB6DGkuPr6dOHhmh83yT3bbOW7tNP31in07mFJkZWQxcOXa1qFlRZK1ca59av7/nAXm/2YJXlckk/+Ynx3MGWREnG5/yTn9T+OSo5PtA4SRPuesGdRFmdDj353et6acHzdZ9EVbTksybDnQEAASkgEqlXXnlFbdu2VXR0tAYNGqR169ZVeu6bb74pi8VS7i06OroOowVQVkykTTNu7aunr+/urkKt2HNCN/wrRdvSskyOzkNVXdyWzIKqqttayeygksqVJwN7vdmDdaG0tMAeeFud117zy9Mubddf4+6err1NW0uS4vJz9MacZ/Tguk/9ux+qMomJ5atNNR3uDAAISKYnUh9++KGmTZum3//+99qwYYP69Omjq6++WseOHav0MXFxcUpPT3e/HTp0qA4jBnAhi8Winw1rp3fvH6Qm9SMlSUdP5+mmWas0b2OAV008ubgdOlSKj/dueG51A3tjYoy9PZ4Oug0lnsxn8oJL0uyBN+lnN/9e2dGxkqROJw7ps/89ppEHNtT+BZo0qdnj0tJKq5u1He4MAAg4pidS06dP1wMPPKB7771X3bt31+zZs1WvXj29/vrrlT7GYrEoMTHR/ZZQ0fpzAHXusvZN9Pkvh6lPciNJUn6RU1M/3KRnFmxTkSMAZx55enG7ZIk0f35p5ckbNpv0/PPllwyWmDatZs8Jtzx7lB694Vf62+h75bQaie6Vu1dr7tu/Utsz6b55kaxaVFazz+8fnD69+kTcZpNmzKj5awEA6pSpiVRhYaHWr1+vMWPGuG+zWq0aM2aMVq9eXenjcnJy1KZNGyUnJ2vcuHHatm1bpecWFBQoOzu73BsA/2nRMEYf/vwy3XZpsvu2N1Ye1J3/XavjZ+t4j0p1PL24nT695l3mioulefMq3g9Tdg8WvHY0rpluuvM5fdZ9lPu2qSnv6tW5f1VsYV7lD/REp06lH3vSVbEyxcVGAj1/fvXPU1wszZ17ccINAAhIpiZSJ06ckMPhuKiilJCQoIyMjAof06VLF73++uuaP3++3nnnHTmdTg0ZMkRHjx6t8Pxnn31WDRs2dL8lJydXeB4A34mOsOlvN/XWXyf0UoTNSBLWHjilG15O0aYjZ8wNroQ3F7dffFHz/UxlOZ3GhfKwYaX7YSZPNmYhwSurk3vpxnte1PaEDpKk+gXn9Oqnf9bUle/Lqho2o7VYpOuukxYvlnr29M2yy9OnazbcGQAQ8Extf56WlqaWLVtq1apVGjy4tE3tE088oWXLlmnt2rXVPkdRUZG6deumSZMm6U9/+tNF9xcUFKigoPSv4NnZ2UpOTqb9OVBH1h86rYffXa/MbOPfYaTNqj+N76FbL21tbmCZmUaVyFMNGkhnfTx0OCXF2H918KDUrp1vnztEuSS91f96/fGKB+Q4v5Sv7ak0/Xvun9X5xOGaP/G6dVKHDlJRkRQRITVr5ptZVydPGvvhPG11z+wpAPC5kGx/3rRpU9lsNmVmZpa7PTMzU4keXuBERESoX79+2rt3b4X3R0VFKS4urtwbgLozoE1jLfjFMF3atrEkqdDh1G8+2aL/N3eLCopN3B/kbdc8XydRkjFEFh4rsNn1m7G/1O+vnOxOooYf2KD5bz1WuyRKkp56ykieEhN9l0QlJRlNSjxtLGK3SxMmkEQBQJAwNZGKjIzUgAEDtHjxYvdtTqdTixcvLlehqorD4dCWLVvUokULf4UJoJaaN4jWu/dfpnsGt3Hf9t7aw7rt32uUkZVvTlCB0DVv0yZjiSF/4KlWZmy8bpv0N33U+yr3bQ+u/URvfvwHNSzIrf0LLF5cvmujLzz1VOnHnjQWcTikxx7zzWsDAPzO9K5906ZN03/+8x/973//044dO/TQQw8pNzdX9957ryTp7rvv1pNPPuk+/49//KMWLlyo/fv3a8OGDbrzzjt16NAh3X///WZ9CgA8EGm36plxPfX8LX0UZTd+9Ww8fEbXv5yi7w+eMieoQOiad+iQsZzMG2HWnGJDUhfdcPcMbWzZVZIUVVSglz77h55c+oZsLh8lPb7+OZg0SXroodLjqoY72+3G7TNnVj2vDAAQUExPpG699VY9//zzevrpp9W3b19t2rRJX3/9tbsBxeHDh5WeXtrC9vTp03rggQfUrVs3XXvttcrOztaqVavUvXt3sz4FAF64eUArffLQELVsZCxfOpFToEn/XqP/rTqoOt+yWXJxa6acHO+XGTZv7r94AsiJeg31u6se1s13PKdjDYxZTi2zjumTd5/QuB3LTI7uvKZNyx8nJRk/U++9d/G5JcOdx40r/X5brcbxihXG/QCAoGFqswkz+GuzGQDvnMot1C/e36CVe0+6b5vYv6X+OqGXoiO8GHxbW7NmGbOizHLypLGPZuJEo6MfVGCz640B4/TKkJ/obFR99+0DD2/RzPl/U9NztZjr5As2m7H8b+ZMI/k5dcoYvluyJ8oTeXlGd764OPZEAYCf+ev638TNAQDCWXz9SP3v3oF67ptd+vfy/ZKkTzekanfmWc2+c4BaNa7n/yBKBvKaqeQium1bU8MIBC5JX3YZqr+NuldHGpU2HKpfcE4Pr/lYP1/3qSKcPlqCd911Rlv7mkhIkD76qHQZXny85wlUiZgYEigACHKmL+0DEL7sNqv+37Xd9PKkfoo5X4XampqtG15O0cq9J/wfgCcDef2tZGbQBx+YG4fJNid20i13/F1Txj/pTqIsLqdu2/yNvvvPzzVlzce+S6IkafToms8Gy8iQ+vf3XSwAgKDE0j4AAWFnRrYefHu9Dp08J0myWqTfXNNVPx/RXhZ/NFfIy/N8to+/lMwMysuTmjQxLw4TpTVoqn+MuFtze15e7vahBzfpd0teU/fjB/zzwhaLNHy4tGpV9UOZK5KRYVSmAAABj6V9AEJa18Q4fTZlmKZ+uFHf7Toup0t69qud+m7XMU27sosGtvNy6VR1srPNTaJsNumaa4yP09LMi8MkuRHRenXQTfr3wAnKj4h2397+5BH97rvXdfm+7+XX3oQ2m5FM1aRbn9VKy3oAABUpAIHF6XTpxW93659Lyg/ZHtqxiR4b01mXtPVRQpWXJ9Wrg31Y1bFapauukr7+2uxI6oTDYtUnPS/X88Pvcnfik6RGedmamvKe7tj0lW+X8FXFapVmzJCmTjUSK08qU3a70WVvzhy/hwcA8A1/Xf+TSAEISIt3ZOpPn2/XwfNL/UoM79RUU8d00oA2tUyoUlOlVq1q9xy+YrFIYfCreFXrXvrz5fdre0IH9212R7Hu2fC5frHqAzXKz6n7oDIypL17jYRq7tzqq5QWi9GqnHlPABA0SKR8hEQKCB7FDqfmbUrTy0v2uPdOlRjeqakeu7Kz+rduXLMnX7rUaDgAvzvQOEl/HXWvFnUeXO72q3av1pNL31C70yYtbSzZo1bSPS8vT3r5Zek3vzEqT2UrVHa7sQywpOU5ACBokEj5CIkUEHyKHE7N3Ziql5fs0ZFTeeXuG9m5maaO6aR+3iZUgVSRClFZUfX10tBJeqv/9Sq2lW7J7Z65T08t+a+GHN5iXnBVLdFbubJ8hcpqlSZMkB57jEoUAAQhEikfIZECgleRw6m5G1L1zyV7dPR0+YRqVJdmmjqms/omN/L8CaOjpYIC3wYJFVlteqfftXpp6CSdiSn9Pdv87En9asXbumnrEtlcJjb6kDxbosfQXAAICSRSPkIiBQS/IodTn6w/qpeX7FXqmfIJ1eVdm2vqmE7q3apR9U80bZpReYBPuCQt7jBQfx39M+1vUlrtiy7K18/XzdWDaz9R/aJ88wKUjARKqpsleiRiABAQSKR8hEQKCB2FxU7NWX9Ur3x3cUI1pltzPXpFZ/Vq1bDqJxkwQNqwwbeBXbi/Jgxsb9ZOf7n8Pq1s27fc7RO2LtGvl7+lpLN1MGDZU4sXS5dfXv15NZWSYgx7nj+/dGnguHHS44+zNBAATEAi5SMkUkDoKSx26uP1R/TKkr1Kyypf8RjTLUFTx3RSz5ZVJFQJCdKxY36OMjQdq99I04ffpQ97XymXxeq+/ZKj2/R/i/+rPhl7TIyuEp4M061pNWnWLGnKlIvbqdOsAgBMQyLlIyRSQOgqKHboox+OauZ3e5V+QUJ1VfcEPTqmk3okVZBQpaRIw4fXUZShYW98K33WfYReu2S8cqNK53Eln8nQk0vf0NhdK/07ULemLuzUd6HaVJNSUqQRI6puZU/7dACocyRSPkIiBYS+gmKHPvz+iGZ+t08Z2eUTqqt7JGjqmM7q1uKCf//+WOIXQpyyaFNSZy3sdJkWdrpM+5skl7u/QUGuHln1oe5Zv0DRjiKToqxGdcN0a1tNmjhRWrCg6mWdDPQFgDpHIuUjJFJA+MgvOp9QLd2rzOzy3fnG9kzUo2M6qWtinFFJuOEG6cwZcwINUAU2u1a16aOFnS7Ttx0H6XjsxUOQrU6Hbt/0taaufE9Nz2WZEKUXqqoG1baalJcnxcZWP9BXqr4qBgDwKRIpHyGRAsJPfpFD7687rFlL9+nY2fIJ1XX1cvXLl59QlxOHTIousGRF1dfS9gO0sNNlWtr+knLL9kpYnQ5dkrpDV+1Zo6t3rVJydhDsL7NYqq4o1baalJkpJSZ6Ho8n+7QAAD5BIuUjJFJA+Movcui9tYc1a9k+HS+TUFlcTvVN263+aTvVP3WH+qftVIuzJ02MtG6lN2iibzsO0sJOl2l1697lhueWiCoq0PCDG3XVnjW6Yu86NcnLNiHSGho5UvrLXyrfl+SLahIVKQAIWCRSPkIiBSC/yKF31hzS7E/W6kR0xb8HWmQfV/+0neqXtkv9UneqZ+ZeRTlCo6W5S9Kepq3d+51+bNG5wvMa5WXrir3rdOWetRpxcIPqFQXp8OJp06QXXqj8fl9Vk9gjBQABiUTKR0ikAEiS8vKUF9dY7/Ybq/f6XFNugGxFIouL1CNzX9BWrRwWqzYkddXCzpdpUcfLdDA+qcLzWp3J0JV71+qq3Wt06dFtsrs8qLAEuqgoKb+KQcC+qibRtQ8AAhKJlI+QSAGQJG3aJPXr5z48FROnjUldtCGpqza07KrNLTrrXGTVS6/cVavUneqftlM9MvcFVNUq3x6plWWaRZys36jC87pn7tNVe9boqt1r1O34gcBsW15bJ09K8Rc3y3AbMcJIcKozcqS0dGnl98+eLT38MHOkACCA+Ov6/+KF8AAQDnbvLncYn5etK/Z9ryv2fS/JqODsatpGG1p21YakrtrYsqsOxLcs95j0uGb6Iq6ZvuhqzKCKLC5Uz8x96n8+seqfulOJOb6vWjllUW5ktM5FxignMka5kTHKjTj/PjJGWdGxWtWmt5a1G6C8yOiLHm9zOjTwyFZdtWeNxuxZGxzNImpr+3Zp2LDK77f4KH2cPFnq1UuaMUOaO7f8LKrHHqMSBQAhhIoUgPD0j39ITzzh1UNqUrVKyj7mrlj1S9ul2MI85UZEKzcyRjmR9XQusuTjGHdidC4i+nyCZNxv3FaaNFWUHFUnpjBfIw+s11V71ujyfd+rUX6O188R1BYtksaMqfg+fzWKyMuTsrOluDgaSwCAiahIAYAvffWV1w+5sGpVbLFqV7M22phUedUqLa650uKa64tuI3wStjea5J7RmL1rdeWetRp2aJOiiwvrPIaA0bRp5fdlZ3uWREnGednZniVGMTEkUAAQwkikAISfvLyq97l4yO5yqsexA+px7IDu3GQkZjWpWlUnsrhI9YryVL8wT/UL8433RXmqX5BX+vEF93U4eVT90nbJFgrNInwhuooqXlycUWnytCLFagYAgEikAISj7OyqO6vVQlVVq62JHeW0WFSvMF+xhecuTowKyyZE59z3RToDp4FF0KoqkYqJMfYwedq6nCoTAEAkUgDCUVUXyz5WtmoFE1U096msadOkefOqPsfhMBpGAAAgyWp2AABQ506fNjsC1KWRI6uvIg0bZrQmt1iMylNZdrtx+8yZdN0DALiRSAEIP0kVD6NFiPrLXzw7b/JkY5bUuHHGXiiptHX5ihXMfwIAlMPSPgDhJz7eqFDk5ZkdCfztpZe8qyINHWq80bocAFANEikA4akwjFuBh4uRI6Vf/rJmj6V1OQCgGiztAxB+UlONxgEIXRaL50v6AACoARIpAOHn00/NjgD+YrPRGAIAUCdIpACEny+/NDsC+IPFIo0fT2MIAECdYI8UgPCSlyctXGh2FPCHb7+VLr/c7CgAAGGCihSA8JKdLTmdZkcBX7NajeV8AADUERIpAOElLq50RhBCh9MpzZ1LS3sAQJ3hagJAeImJMQas2lnZHHKcTqPiCABAHSCRAhB+pk3zX/tzu92YX5SU5J/nR9UiIsyOoHp5eVJmJtUzAAhyJFIAws+wYcZ+GovF95Uph8OYX/Thh759XnimqMjsCCqXkiJNnCjFxkqJicb7iROllSvNjgwAUAMkUgDC0+TJRpvsceOMhKq27Pby84umTq39c8I7FouxBy4QzZoljRghLVhQ2uzE6TSOhw+XZs82Nz4AgNdIpACEr6FDpTlzpNxc6dprvatOlU2+rFYjISuZXzRtmrR+ve/jReWsVqO6ExNjdiQXS0mRpkyRXC6puLj8fcXFxu0PP0xlCgCCDIkUAMTESE8+6fm+qZKL9sWLpYwMKSdHevttqWNHY98LbbjrnsslPfaY2VFUbPp0yWar+hybTZoxo27iAQD4BIkUAEhV75sqWbb30kulidOcOcbw1z17pDvuKN33Uq+eVFBgzucQzGqzV63skspAk5cnzZ9/cSXqQsXFtG8HgCBDIgUAJcrumyqZNVV22d4vfyklJJQuH6to30u469dPiory/Hyr1ajslf2ae2P8+NIllYHImwHQtG8HgKBicblcLrODqEvZ2dlq2LChsrKyFBeom5IBmC8vz7iojYureN9NSoqRRIXXr9DqWa3GfqCXX67+XIvFWCI5Z45xnJcn7dsn9erl+etlZBjJbaDKyzOqlZ4kU1arUe0MxH1eABDE/HX9T0UKACoSE1O++nQhT/a9hCOnU/rd76SuXT07v+y+ppgYqUMHzytTVmvgdukr4ekAaLtdmjCBJAoAggiJFAB4y9N9L+GoJLnZsUO64oqKz7FYKt/XFIqJhycDoB2OwG2WAQCoEIkUAHjLm30vtRUI86jGjzeSFm+Tm2+/NZZAXnttabv4ko6HVe1rCrXEw5NGJoHaLAMAUCn2SAGAt7zZ91JTJRfXkyf7ZmBwbaSkGHvBqtsTZrEYCVJFCUF1e84uNHu2MVvJZitf+bPbjSSq5GsTTFauNFqcz51r/OxYrUbi+dhjJFEA4EfskQKAQOHp8rOaGjmytGKzdat/XsNTs2YZF/m1rapUt+fsQtV1UAy2JEoqHQCdk1O+jT5JFAAEJRIpAKgJT5af1cSjj0pLl5ZeXK9b5/vXuFCTJhffNnKkUYkqm7DUdXITqomHt0klACAgsbQPAGpq9mzpoYd893y33Sa9/37527Zu9a4deE1YrdLx46UzjDy5yPd2qR4AACZhaR8ABJrJk42qTVJS7Z/LZpM+/NBIzsrq2bP2z10dp1MqKpLatjXePEmMqKoAAMIciRQA1MbQoUYCVNuGEA6H0cjh4YeNpgRljR5du+euTjDMYwIAIMCQSAFAbVXViMFbNpvR2a2sJUukBg1q97yVqek8prw8KTPTeA8AQBgikQIAX6isEUNSknfVquJioz32hQnKmDG+i7Usb+cxpaQYc6BiY6XEROP9xIkXV9EAAAhxNJsAAF+7sBFDXp60b593TSMyMow9SCXP5+u5VVarsZTQm3lMs2ZJU6aE1mwnAEDIo9kEAASLCxsxxMRIHTqUVqqqc+Gepexs3yZRFouxnM+bluUpKUYS5XKVT6Ik47iy/V0AAIQoP02TBACUUzLEd8GCixORsux247yye5bi4ozkqqbJlMUi7d9vPE9RUc1alk+ffnEl6kIl+7uCfc4TAAAeCLtEqmQlY3bJvBQAqCsPPmjsf6pKcbH085+XznQqce210ldf1WwIcEkVyW433oqKjDdP5eVJ8+YZz1OV4mLp00+NJhS0RQcABIiS635f72gKuz1SR48eVXJystlhAAAAAKhD+/btU/v27X32fGGXSDmdTqWlpalBgway1HbuC0yVnZ2t5ORkHTlyhMYhYY6fBUj8HKAUPwsowc8CJCkrK0utW7fW6dOn1ahRI589b9gt7bNarWrVqpXZYcCH4uLi+OUISfwswMDPAUrws4AS/CxAMvIAnz6fT58NAAAAAMIAiRQAAAAAeIlECkErKipKv//97xUVFWV2KDAZPwuQ+DlAKX4WUIKfBUj++zkIu2YTAAAAAFBbVKQAAAAAwEskUgAAAADgJRIpAAAAAPASiRQAAAAAeIlECkHl1KlTuuOOOxQXF6dGjRrpvvvuU05OTpWPGTVqlCwWS7m3yZMn11HE8JVXXnlFbdu2VXR0tAYNGqR169ZVef7HH3+srl27Kjo6Wr169dKXX35ZR5HCn7z5OXjzzTcv+rcfHR1dh9HCX5YvX64bbrhBSUlJslgsmjdvXrWPWbp0qfr376+oqCh17NhRb775pt/jhH95+3OwdOnSi34nWCwWZWRk1E3A8Itnn31Wl156qRo0aKDmzZtr/Pjx2rVrV7WP88V1AokUgsodd9yhbdu2adGiRfr888+1fPly/fznP6/2cQ888IDS09Pdb88991wdRAtf+fDDDzVt2jT9/ve/14YNG9SnTx9dffXVOnbsWIXnr1q1SpMmTdJ9992njRs3avz48Ro/fry2bt1ax5HDl7z9OZCkuLi4cv/2Dx06VIcRw19yc3PVp08fvfLKKx6df+DAAV133XUaPXq0Nm3apKlTp+r+++/XN9984+dI4U/e/hyU2LVrV7nfC82bN/dThKgLy5Yt05QpU7RmzRotWrRIRUVFuuqqq5Sbm1vpY3x2neACgsT27dtdklzff/+9+7avvvrKZbFYXKmpqZU+buTIka5HH320DiKEvwwcONA1ZcoU97HD4XAlJSW5nn322QrP/8lPfuK67rrryt02aNAg14MPPujXOOFf3v4cvPHGG66GDRvWUXQwiyTX3LlzqzzniSeecPXo0aPcbbfeeqvr6quv9mNkqEue/Bx89913Lkmu06dP10lMMMexY8dcklzLli2r9BxfXSdQkULQWL16tRo1aqRLLrnEfduYMWNktVq1du3aKh/77rvvqmnTpurZs6eefPJJnTt3zt/hwkcKCwu1fv16jRkzxn2b1WrVmDFjtHr16gofs3r16nLnS9LVV19d6fkIfDX5OZCknJwctWnTRsnJyRo3bpy2bdtWF+EiwPA7AWX17dtXLVq00JVXXqmVK1eaHQ58LCsrS5IUHx9f6Tm++p1g9z48wBwZGRkXld/tdrvi4+OrXN98++23q02bNkpKStKPP/6o3/zmN9q1a5c+/fRTf4cMHzhx4oQcDocSEhLK3Z6QkKCdO3dW+JiMjIwKz2cdfPCqyc9Bly5d9Prrr6t3797KysrS888/ryFDhmjbtm1q1apVXYSNAFHZ74Ts7Gzl5eUpJibGpMhQl1q0aKHZs2frkksuUUFBgf773/9q1KhRWrt2rfr37292ePABp9OpqVOnaujQoerZs2el5/nqOoFECqb77W9/q7///e9VnrNjx44aP3/ZPVS9evVSixYtdMUVV2jfvn3q0KFDjZ8XQGAbPHiwBg8e7D4eMmSIunXrpldffVV/+tOfTIwMgBm6dOmiLl26uI+HDBmiffv2acaMGXr77bdNjAy+MmXKFG3dulUpKSl18nokUjDd448/rp/+9KdVntO+fXslJiZetKm8uLhYp06dUmJiosevN2jQIEnS3r17SaSCQNOmTWWz2ZSZmVnu9szMzEq/74mJiV6dj8BXk5+DC0VERKhfv37au3evP0JEAKvsd0JcXBzVqDA3cODAOrvohn898sgj7kZk1a068NV1AnukYLpmzZqpa9euVb5FRkZq8ODBOnPmjNavX+9+7JIlS+R0Ot3JkSc2bdokySjxI/BFRkZqwIABWrx4sfs2p9OpxYsXl6s2lDV48OBy50vSokWLKj0fga8mPwcXcjgc2rJlC//2wxC/E1CZTZs28TshyLlcLj3yyCOaO3eulixZonbt2lX7GJ/9TqhJNwzALNdcc42rX79+rrVr17pSUlJcnTp1ck2aNMl9/9GjR11dunRxrV271uVyuVx79+51/fGPf3T98MMPrgMHDrjmz5/vat++vWvEiBFmfQqogQ8++MAVFRXlevPNN13bt293/fznP3c1atTIlZGR4XK5XK677rrL9dvf/tZ9/sqVK112u931/PPPu3bs2OH6/e9/74qIiHBt2bLFrE8BPuDtz8Ezzzzj+uabb1z79u1zrV+/3nXbbbe5oqOjXdu2bTPrU4CPnD171rVx40bXxo0bXZJc06dPd23cuNF16NAhl8vlcv32t7913XXXXe7z9+/f76pXr57r17/+tWvHjh2uV155xWWz2Vxff/21WZ8CfMDbn4MZM2a45s2b59qzZ49ry5YtrkcffdRltVpd3377rVmfAnzgoYcecjVs2NC1dOlSV3p6uvvt3Llz7nP8dZ1AIoWgcvLkSdekSZNcsbGxrri4ONe9997rOnv2rPv+AwcOuCS5vvvuO5fL5XIdPnzYNWLECFd8fLwrKirK1bFjR9evf/1rV1ZWlkmfAWrq5ZdfdrVu3doVGRnpGjhwoGvNmjXu+0aOHOm65557yp3/0UcfuTp37uyKjIx09ejRw/XFF1/UccTwB29+DqZOneo+NyEhwXXttde6NmzYYELU8LWSNtYXvpV8/++55x7XyJEjL3pM3759XZGRka727du73njjjTqPG77l7c/B3//+d1eHDh1c0dHRrvj4eNeoUaNcS5YsMSd4+ExFPwOSyv0b99d1guV8AAAAAAAAD7FHCgAAAAC8RCIFAAAAAF4ikQIAAAAAL5FIAQAAAICXSKQAAAAAwEskUgAAAADgJRIpAAAAAPASiRQAAAAAeIlECgAAAAC8RCIFAAAAAF4ikQIAhLTjx48rMTFRf/3rX923rVq1SpGRkVq8eLGJkQEAgpnF5XK5zA4CAAB/+vLLLzV+/HitWrVKXbp0Ud++fTVu3DhNnz7d7NAAAEGKRAoAEBamTJmib7/9Vpdccom2bNmi77//XlFRUWaHBQAIUiRSAICwkJeXp549e+rIkSNav369evXqZXZIAIAgxh4pAEBY2Ldvn9LS0uR0OnXw4EGzwwEABDkqUgCAkFdYWKiBAweqb9++6tKli1588UVt2bJFzZs3Nzs0AECQIpECAIS8X//615ozZ442b96s2NhYjRw5Ug0bNtTnn39udmgAgCDF0j4AQEhbunSpXnzxRb399tuKi4uT1WrV22+/rRUrVmjWrFlmhwcACFJUpAAAAADAS1SkAAAAAMBLJFIAAAAA4CUSKQAAAADwEokUAAAAAHiJRAoAAAAAvEQiBQAAAABeIpECAAAAAC+RSAEAAACAl0ikAAAAAMBLJFIAAAAA4CUSKQAAAADwEokUAAAAAHjp/wNbOR/4QlAxWwAAAABJRU5ErkJggg==", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plot_data(X3, y, xlabel=\"x\", ylabel=\"y\")\n", + "theta_start = np.matrix([0, 0, 0, 0]).reshape(4, 1)\n", + "theta, _ = gradient_descent(cost, gradient, theta_start, X3, y)\n", + "plot_fun(fig, polynomial_regression(theta), X)\n", + "\n", + "print(theta)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "Regresję wielomianową można potraktować jako szczególny przypadek regresji liniowej wielu zmiennych:\n", + "\n", + "$$ h_{\\theta}(x) = \\theta_0 + \\theta_1 x + \\theta_2 x^2 + \\theta_3 x^3 $$\n", + "$$ x_1 = x, \\quad x_2 = x^2, \\quad x_3 = x^3, \\quad \\vec{x} = \\left[ \\begin{array}{ccc} x_0 \\\\ x_1 \\\\ x_2 \\end{array} \\right] $$" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "notes" + } + }, + "source": [ + "(W tym przypadku za kolejne cechy przyjmujemy kolejne potęgi zmiennej $x$)." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "Uwaga praktyczna: przyda się normalizacja cech, szczególnie skalowanie!" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "Do tworzenia cech „pochodnych” możemy używać nie tylko potęgowania, ale też innych operacji matematycznych, np.:\n", + "\n", + "$$ h_{\\theta}(x) = \\theta_0 + \\theta_1 x + \\theta_2 \\sqrt{x} $$\n", + "$$ x_1 = x, \\quad x_2 = \\sqrt{x}, \\quad \\vec{x} = \\left[ \\begin{array}{ccc} x_0 \\\\ x_1 \\end{array} \\right] $$" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "notes" + } + }, + "source": [ + "Jakie zatem cechy wybrać? Najlepiej dopasować je do konkretnego problemu." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "### Wielomianowa regresja logistyczna\n", + "\n", + "Podobne modyfikacje cech możemy również stosować dla regresji logistycznej." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "slideshow": { + "slide_type": "notes" + } + }, + "outputs": [], + "source": [ + "def powerme(x1, x2, n):\n", + " \"\"\"Funkcja, która generuje n potęg dla zmiennych x1 i x2 oraz ich iloczynów\"\"\"\n", + " X = []\n", + " for m in range(n + 1):\n", + " for i in range(m + 1):\n", + " X.append(np.multiply(np.power(x1, i), np.power(x2, (m - i))))\n", + " return np.hstack(X)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "slideshow": { + "slide_type": "notes" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "matrix([[ 1. , 0.36596696, -0.11214686],\n", + " [ 0. , 0.4945305 , 0.47110656],\n", + " [ 0. , 0.70290604, -0.92257983],\n", + " [ 0. , 0.46658862, -0.62269739],\n", + " [ 0. , 0.87939462, -0.11408015],\n", + " [ 0. , -0.331185 , 0.84447667],\n", + " [ 0. , -0.54351701, 0.8851383 ],\n", + " [ 0. , 0.91979241, 0.41607012],\n", + " [ 0. , 0.28011742, 0.61431157],\n", + " [ 0. , 0.94754363, -0.78307311]])" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Wczytanie danych\n", + "import pandas\n", + "import numpy as np\n", + "\n", + "alldata = pandas.read_csv(\"polynomial_logistic.tsv\", sep=\"\\t\")\n", + "data = np.matrix(alldata)\n", + "\n", + "m, n_plus_1 = data.shape\n", + "n = n_plus_1 - 1\n", + "Xn = data[:, 1:]\n", + "\n", + "Xpl = powerme(data[:, 1], data[:, 2], n)\n", + "Ypl = np.matrix(data[:, 0]).reshape(m, 1)\n", + "\n", + "data[:10]\n" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "slideshow": { + "slide_type": "notes" + } + }, + "outputs": [], + "source": [ + "def plot_data_for_classification(X, Y, xlabel, ylabel):\n", + " \"\"\"Wykres danych (wersja macierzowa)\"\"\"\n", + " fig = plt.figure(figsize=(16 * 0.6, 9 * 0.6))\n", + " ax = fig.add_subplot(111)\n", + " fig.subplots_adjust(left=0.1, right=0.9, bottom=0.1, top=0.9)\n", + " X = X.tolist()\n", + " Y = Y.tolist()\n", + " X1n = [x[1] for x, y in zip(X, Y) if y[0] == 0]\n", + " X1p = [x[1] for x, y in zip(X, Y) if y[0] == 1]\n", + " X2n = [x[2] for x, y in zip(X, Y) if y[0] == 0]\n", + " X2p = [x[2] for x, y in zip(X, Y) if y[0] == 1]\n", + " ax.scatter(X1n, X2n, c=\"r\", marker=\"x\", s=50, label=\"Dane\")\n", + " ax.scatter(X1p, X2p, c=\"g\", marker=\"o\", s=50, label=\"Dane\")\n", + "\n", + " ax.set_xlabel(xlabel)\n", + " ax.set_ylabel(ylabel)\n", + " ax.margins(0.05, 0.05)\n", + " return fig\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "notes" + } + }, + "source": [ + "Przyjmijmy, że mamy następujące dane i chcemy przeprowadzić klasyfikację dwuklasową dla następujących klas:\n", + " * czerwone krzyżyki\n", + " * zielone kółka" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "outputs": [ + { + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAAA1wAAAHvCAYAAABAJN42AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8o6BhiAAAACXBIWXMAAA9hAAAPYQGoP6dpAABpKUlEQVR4nO3df3hU1b3v8c9MQkI0TpALJFCHatSAtigKNYYgckuuYOkxQs9psDYqh+pB0VagKvTWeMS2WH/gfWr50VpFm1ZJ9RGRaqkGxSYBQUEqKhBRbKKSWOWQAYyZJLPvH9OMmclkMpPMr73n/XqeeZS91wxrNntm9nd/1/oum2EYhgAAAAAAUWdPdAcAAAAAwKoIuAAAAAAgRgi4AAAAACBGCLgAAAAAIEYIuAAAAAAgRgi4AAAAACBGCLgAAAAAIEbSE90BK/B4PPr444910kknyWazJbo7AAAAAGLIMAwdPXpUo0aNkt0eOodFwBUFH3/8sZxOZ6K7AQAAACCOGhsbdcopp4RsQ8AVBSeddJIk7wF3OBwJ7g0AAACAWHK5XHI6nb44IBQCrijoGkbocDgIuAAAAIAUEc50IopmAAAAAECMEHABAAAAQIwQcAEAAABAjBBwAQAAAECMEHABAAAAQIwQcAEAAABAjBBwAQAAAECMmCrg+tvf/qZ/+7d/06hRo2Sz2fTMM8/0+ZwtW7bo/PPPV2Zmps444ww9+uijPdqsXLlSp556qgYPHqzCwkLt2LEj+p0HAAAAkHJMFXAdP35c5557rlauXBlW+4MHD2rmzJn63//7f2v37t26+eab9YMf/EB//etffW2qqqq0aNEi3XHHHdq1a5fOPfdcTZ8+XZ988kms3gYAAACAFGEzDMNIdCf6w2azaf369br88st7bXPbbbfpueee01tvveXbNmfOHB05ckSbNm2SJBUWFuob3/iGfv3rX0uSPB6PnE6nbrrpJi1ZsiSsvrhcLuXk5KilpUUOh6P/bwoAAABA0ovk+t9UGa5Ibdu2TSUlJX7bpk+frm3btkmS3G63du7c6dfGbrerpKTE1yaYtrY2uVwuvwcAAAAABLJ0wNXU1KTc3Fy/bbm5uXK5XGptbdWnn36qzs7OoG2ampp6fd3ly5crJyfH93A6nTHp/4C53QPbDwAAAGBALB1wxcrSpUvV0tLiezQ2Nia6Sz1VVUnjxkm99a2x0bu/qiq+/QIAAABSiKUDrry8PDU3N/tta25ulsPhUFZWloYNG6a0tLSgbfLy8np93czMTDkcDr9HUnG7pYoKqb5emjq1Z9DV2OjdXl/vbUemC0CikZEHAFiUpQOuoqIibd682W/biy++qKKiIklSRkaGJkyY4NfG4/Fo8+bNvjamlJEhVVdL+fnS++/7B11dwdb773v3V1d72wNAopCRBwBYmKkCrmPHjmn37t3avXu3JG/Z9927d6uhoUGSd6jfVVdd5Ws/f/58vf/++7r11lu1b98+rVq1Sn/605+0cOFCX5tFixbpoYce0mOPPaa9e/fq+uuv1/HjxzV37ty4vreoczqlLVv8g66tW/2DrS1bvO1SBXfQgeRDRh4AYHGmCrhef/11nXfeeTrvvPMkeYOl8847TxUVFZKkQ4cO+YIvSTrttNP03HPP6cUXX9S5556r+++/X7/73e80ffp0X5uysjLdd999qqio0Pjx47V7925t2rSpRyENUwoMuoqLUzfY4g46kJzIyAMALM6063Alk6Rfh2vrVm+w1aWuTpo0KXH9iTe32xtM1dcHDza7X9QVFEh79nBRB8RbYHBVWSmVl6fuTSIAQA+t7a1ytbnkyHQoa1BWQvvCOlz4UmOj96Klu/Ly3jM9VsQddCD5kZEHAPSitqFWs6tmK3t5tvLuz1P28mzNrpqtuoa6RHctLARcVhYYTNTVBQ86UgFz2oDk53R6M1vdVVbyuQSAFLb6tdWasnaKNtZvlMfwSJI8hkcb6zfqorUXac3raxLcw74xpDAKknJIYWCw1RVM9LY9VXR//11S8TgAyYjPJwCgm9qGWk1ZO0WGeg9XbLKpZm6NikcX99omFhhSmOrcbqmkJHhQFZjpKSlJrapf3EEHkhMZeaQaKucCfVqxbYXS7Gkh26TZ0/TAqw/EqUf9Q8BlRRkZ0rJl3gIQwe4MdwVdBQXedqk0Z4k5bUDyCZZ5nzSp5zBgPqewCirnAn1qbW/Vhv0b1OHpCNmuw9Oh9fvWq7W9NU49ixwBl1WVlXmr7fWWuXE6vfvLyuLbr0TiDjqQfPqbkSc7ALNi7TkgLK42l2/OVl88hkeuNleMe9R/BFxW1lfmKtUyW9xBB5JPfzLyZAdgZlTOBcLiyHTIbgsvVLHb7HJkJkkdhSAomhEFSVk0A19iHS4g+bndoT93Xfv5PMMqWHsO6NPsqtnaWL8x5LDCdHu6SseU6qnvPhXHnlE0A/DHnDYg+YWbkSc7AKtg7TmgT4uKFqnT0xmyTaenUwsvXBinHvUPGa4oIMNlEuHeQQeQ/MgOwCq2bvUGW13q6rxD3gFIkta8vkY3PHeD0uxpfpmudHu6Oj2dWjVzleZPnB/3fpHhAoJhThtgHWQHYAVUzgX6NH/ifNXMrVHpmFLfnC67za7SMaWqmVuTkGArUmS4ooAMFwBEUSTZaLIDMCuytEDEWttb5WpzyZHpUNagrIT2hQwXAMCcIqlASHYAZkXlXKBfsgZlKTc7N+HBVqQIuAAAySGS9YmWLpUuvph19WA+/V17DoBpEXABAJJDuBUIR4+WOjulgwfJDsB8qJwLpBzmcEUBc7gAIIpCzW057TTJZut9ngvrcMEsqJwLmBpzuAAA5hWqAuErr0i/+AXZAZgflXOBlEGGKwrIcAFADISqQEh2IPnxbwTAwshwAQDMra8KhGQHklsk1SYBwOIIuAAAySVwDhcVCM0lkmqTFRVU4QNgeQRcAIDkwfpE5hdutcn8fG87spHm01eQTBAN+CHgAgAkB9Ynso7Af6+pU71z8gKD6cCiJ0h+DBcFIkbABQBIDqxPZC2hqk0SbJkTw0WBfqFKYRRQpRAAoojqdtYSqtokzCfYsF+ns/ftgEVRpRAAYF5UILSOvqpNwnwYLgpEjIALAABEH9UmrYvhokBECLgAAEB0UW3S+pxOqbLSf1tlJcEWEAQBFwAAiB6qTaYGhosCYSPgAgAA0UO1SetjuCgQEaoURgFVCgEACEC1SWuiSiEgiSqFAAAg0ag2aT0MFwX6hYALAAAAfWO4KNAvDCmMAoYUAgCAlMFwUYAhhQAAAIgRhosCESHgAgAAAIAYIeACAAAAgBgh4AIAAACAGCHgAgAAAIAYIeACAAAAgBgxZcC1cuVKnXrqqRo8eLAKCwu1Y8eOXttOnTpVNputx2PmzJm+Ntdcc02P/TNmzIjHWzGfvhYxZJFDAAAAwMd0AVdVVZUWLVqkO+64Q7t27dK5556r6dOn65NPPgna/umnn9ahQ4d8j7feektpaWn6j//4D792M2bM8Gv3xBNPxOPtmEtVlTRunNTYGHx/Y6N3f1VVfPsFAADMi5u5sDjTBVwrVqzQtddeq7lz5+rss8/WmjVrdMIJJ+iRRx4J2n7o0KHKy8vzPV588UWdcMIJPQKuzMxMv3Ynn3xyPN6OebjdUkWFVF8vTZ3aM+hqbPRur6/3tuPLEQAA9IWbuUgBpgq43G63du7cqZKSEt82u92ukpISbdu2LazXePjhhzVnzhydeOKJftu3bNmiESNGaMyYMbr++uv12Wef9foabW1tcrlcfg/Ly8iQqqul/Hzp/ff9g66uYOv99737q6tZ9BAAAITGzVykCFMFXJ9++qk6OzuVm5vrtz03N1dNTU19Pn/Hjh1666239IMf/MBv+4wZM/T73/9emzdv1i9/+Uu98soruvTSS9XZ2Rn0dZYvX66cnBzfw+l09v9NmYnTKW3Z4h90bd3qH2xt2eJtBwAAEAo3c5EibIZhGInuRLg+/vhjfeUrX9HWrVtVVFTk237rrbfqlVde0fbt20M+/7/+67+0bds2vfnmmyHbvf/++zr99NNVXV2tadOm9djf1tamtrY2359dLpecTqdaWlrkcDgifFcm1P1LsAvBFgAA6I/A4KqyUiov52YukprL5VJOTk5Y1/+mynANGzZMaWlpam5u9tve3NysvLy8kM89fvy41q1bp3nz5vX59+Tn52vYsGE6cOBA0P2ZmZlyOBx+j5TidHq/DLurrOTLEAAARC5wBE1xMcEWLMVUAVdGRoYmTJigzZs3+7Z5PB5t3rzZL+MVzJNPPqm2tjZ9//vf7/Pv+fDDD/XZZ59p5MiRA+6zJTU2eu88dVde3vuEVwAAgFC4mQsLM1XAJUmLFi3SQw89pMcee0x79+7V9ddfr+PHj2vu3LmSpKuuukpLly7t8byHH35Yl19+uf7X//pfftuPHTumW265Ra+++qo++OADbd68WaWlpTrjjDM0ffr0uLwnU+iaqBqY9q+rCz72GgAAIFzczIWFmS7gKisr03333aeKigqNHz9eu3fv1qZNm3yFNBoaGnTo0CG/5+zfv1+1tbVBhxOmpaXpzTff1GWXXaaCggLNmzdPEyZMUE1NjTIzM+PynpJeV8nW7dt7FsiYNEl6/HFp0CCCLgAAEDlu5sLiTFU0I1lFMmnOdNxub7BVX+8Nqtrb/cdUd/+S7NpfUCDt2UM1IQAAEFpgsBXs+oK5XEhCli2agQToXrK1vd0bVD3+ePAvw5oab7C1bBnBFgAACM3tlkpKggdVgYU0SkpYhwumRcCFvnX/0mtvl773veDrbxUWejNbZWUJ7jAAAEh6GRnem7QFBcEzWF3XH9zMhckxpDAKLD2ksDvW3wIAANHmdocOpvrab7V+wBQYUojYoGQrAACItr6CmHgEOV0Fwnor0NHY6N1fVRX7vsByCLgQPkq2AgAAq3G7pYoKb4GwYFURu0b41Nd72zGXDBEi4EJ4KNkKAEG1treq+VizWttbE90VAP3RvUBY4HVN4PVPdTXDChExAi70LVhp1kmT/KsHEXT56+vuF3fHANOrbajV7KrZyl6erbz785S9PFuzq2arrqEu0V0DEKnAqohTpwYvEMY0CvQDARdCo2Rr5BgHDlje6tdWa8raKdpYv1EewyNJ8hgebazfqIvWXqQ1r69JcA8BRCzwuqa4mGALUUHAhdCClWztHlQFK9maykEX48ABy6ttqNWC5xfIkKEOT4ffvg5PhwwZuuG5G8h0AWaUqgXCGJkTUwRc6FtZmXd9LaczePbG6fxy/a1Uz94wDhywvBXbVijNnhayTZo9TQ+8+kCcegQgalKxQBgjc2KOgAvh6cpc9Za9ycgge9OFceCAZbW2t2rD/g09MluBOjwdWr9vPYU0ADNJxQJhjMyJCwIuhI/sTfgYBw5YkqvN5Zuz1ReP4ZGrzRXjHgGIilQtEMa1XVwQcCEyZG/Cl6rjwAELc2Q6ZLeF99Npt9nlyHTEuEcABizVC4RxbRdzBFyIHNmb8KTiOHDA4rIGZal0TKnS7ekh26Xb0zVr7CxlDcqKU88A9FuwAmHdBSsQZjVc28UUARf6h+xNaKk4DhwwiwFW41pUtEidns6QbTo9nVp44cJIewYgUboXCAume4Ewq+LaLmYIuNA/ZG96F+9x4JRyBcIXhWpck0dP1qqZq2STrUemK92eLptsWjVzlYpHF0ez5wBira/MlRUzW91xbRczBFyIHNmb3sV7HDilXIHwRbEa1/yJ81Uzt0alY0p9c7rsNrtKx5SqZm6N5k+cH7v3AQDRxrVdTNkMwzAS3Qmzc7lcysnJUUtLixwOi0+QDpa9cTp7356Kqqq8F2vV1cGPQWOjN9hatmxgQxPcbm8wVV8f/Jh3/zcpKPAOhbD63TmgLzH4Dmttb5WrzSVHpoM5WwDMh2u7fonk+p+AKwpSJuDiAj98bnfo997X/nDxJQlELvDzUVnpHTbD5wVAquHart8iuf5nSCHCRxWf8MVrHDilXIHIRbsaF/MoAZgV13ZxQYYrClImw9UlXtkbhK/7HaguBFtAaFu3eoOtLnV13gI3kYjXEGIAiCWu7SJGhguxlepVfJIRpVyByESjGlcUi3AAQEJxbRdTBFyAFVDKFQhftKpxZWR4M1vBnhv4d1RXc8ECACmKgAswO0q5AuGL9jp5zKMEAPSBgAsws3gvsgyYWazWyYt2EQ4AgKUQcAFmFe9FlgGzi2U1LuZRAgB6QZXCKEi5KoVIHlRIAyIXi2pcVAoFgJTCwsdxRsCFhKKUK5BYLKQMACmHsvBAKqGUK5A4zKMEAPSBgAsAgP5gHiUAIAwEXAAA9Ecsi3AAACyDOVxRwBwuAEhhJp9H2dreKlebS45Mh7IGZSW6OwBgCszhSjV9DVNhGAsAxI5J51HWNtRqdtVsZS/PVt79ecpenq3ZVbNV11CX6K4BgKUQcJldVZU0blzvE7IbG737q6ri2y8AQNJa/dpqTVk7RRvrN8pjeCRJHsOjjfUbddHai7Tm9TUJ7iEAWAcBl5m53d41mOrrg1fB6qqeVV/vbUemCwBSXm1DrRY8v0CGDHV4Ovz2dXg6ZMjQDc/dQKYLAKKEgMvMMjK8C94GKz0cWKq4ujpph7UAAOJnxbYVSrOnhWyTZk/TA68+EKceAYC1EXCZXWDp4alTpa1be64Lw6KbAJDyWttbtWH/hh6ZrUAdng6t37dere2tceoZAFgXAZcVBAZdxcUEWwCAHlxtLt+crb54DI9cba4Y9wiApVDILSgCLqtwOqXKSv9tlZUEWwAAH0emQ3ZbeD/9dptdjkyWOgEQJgq59YqAyyoaG6Xycv9t5eW9n/SwNu4wAQgia1CWSseUKt2eHrJduj1ds8bOYl0us+A7H4lGIbeQTBlwrVy5UqeeeqoGDx6swsJC7dixo9e2jz76qGw2m99j8ODBfm0Mw1BFRYVGjhyprKwslZSU6N13343124iewAIZdXXBC2kgNXCHCUAIi4oWqdPTGbJNp6dTCy9cGKceYUBS+TufQDN5UMgtJNMFXFVVVVq0aJHuuOMO7dq1S+eee66mT5+uTz75pNfnOBwOHTp0yPf4xz/+4bf/nnvu0a9+9SutWbNG27dv14knnqjp06friy++iPXbGbjAk3jLFmnSpJ6FNAi6UgN3mAD0YfLoyVo1c5VssvXIdKXb02WTTatmrlLx6OIE9RBhC/zOf+89//2B3/nHjiWil7GRyoFmsgqnkNsLL4Se7mLV6xLDZC644AJjwYIFvj93dnYao0aNMpYvXx60/dq1a42cnJxeX8/j8Rh5eXnGvffe69t25MgRIzMz03jiiSfC6lNLS4shyWhpaQnvTURLW5thFBQYhmQY+fmG0dDgv7+hwbtd8rZra4tv/5AY3f/du58XvW0HkJJq/1FrfKfqO4b9Truh/5Zhv9NufKfqO0btP2oT3TVEovt3+6BBhvHqqz235+d7txcUGMa6dYntbzRw/ZPcuh//rkd+vmH8+tfef4/erj8aGkx1jkZy/W+qgKutrc1IS0sz1q9f77f9qquuMi677LKgz1m7dq2RlpZmjB492jjllFOMyy67zHjrrbd8+9977z1DkvHGG2/4PW/KlCnGD3/4w6Cv+cUXXxgtLS2+R2NjY2ICLsPwnpQWOnkRJYE/tHV1BFsAgvrc/bnRdLTJ+Nz9eaK7gv46cMAbbEmGkZ5uGE8/3TPYsloAws3F5FZX5x9wbdkSOkg+cCD0OZqE52wkAZephhR++umn6uzsVG5urt/23NxcNTU1BX3OmDFj9Mgjj2jDhg36wx/+II/Ho0mTJunDDz+UJN/zInnN5cuXKycnx/dwJrISYFmZtGdP7+lZp9O7v6wsvv1C/HVPw7NUAIAwZQ3KUm52LgUyzOz006WaGik9XerokGbP/vI7//HHpe99z3rzZ1iHNHkFK+T2n/8p/f73wae7rFwpnXVW7+eoBYaHmirg6o+ioiJdddVVGj9+vC6++GI9/fTTGj58uH7zm9/0+zWXLl2qlpYW36Mx0fOj+vritMIXK0ILNpY92FIBV1/Njw8AWFFhofSnP/lvu/VW/2DLagEINxeTT6hCbt/7nvcGQPeg65VXpIULpfZ27w2Dxx/3/3ezyNxzUwVcw4YNU1pampqbm/22Nzc3Ky8vL6zXGDRokM477zwdOHBAknzPi+Q1MzMz5XA4/B5AwvRWKCPYHaaf/aznpGoAgPk1Nko//rH/tvnzrR+AsA5p8ginkFuwoKsr2Oro8O63YHVDUwVcGRkZmjBhgjZv3uzb5vF4tHnzZhUVFYX1Gp2dndqzZ49GjhwpSTrttNOUl5fn95oul0vbt28P+zWBhApWinX79i+/pNL/VYUsPd37pXbJJVStBAArCbwwXbPGf/9991k3AGEd0uTgdkslJcED/MBM5FVXSY884v/8P/3J2sND4zCnLKrWrVtnZGZmGo8++qjxzjvvGNddd50xZMgQo6mpyTAMwygvLzeWLFnia3/nnXcaf/3rX4333nvP2LlzpzFnzhxj8ODBxttvv+1rc/fddxtDhgwxNmzYYLz55ptGaWmpcdpppxmtra1h9SlhVQqB7rpPFE5P9/9v4KRpJhIDgDUEq0YYWCEuPf3L6oVWQoGo5BJuIbdf/zp4FcNg524S/ztatkphlwcffNAYPXq0kZGRYVxwwQXGq92+RC6++GLj6quv9v355ptv9rXNzc01vvWtbxm7du3yez2Px2PcfvvtRm5urpGZmWlMmzbN2L9/f9j9IeBC0uheqSrYlxWlcgHAOgLLowfeWHv66S9vvA0a5P2NsAqqFCanvq4rulcjDBYkP/20/zVMXV18+t0PkVz/2wzDMBKbYzM/l8ulnJwctbS0MJ8LibdsmXTHHV/+ua7OO4a6S2OjN+2/bBnVKwHA7KqqvPN4f//74AUytm+XLrrIO6TcCkOzJO/wtXHjvHOXg72n7kMsCwq81ZpNOvfHUoLN8XI6/bd3zeXqksTnbCTX/6aawwWgD42N0mOP+W8LHMvOUgH++qp4ZNKKSABSRFmZtHOnd15MsPkuhYXS3r1fzo8pKTH/91pGhvemYUFB8IvxrjlDBQXedgRbidfXHK/HH/8y2Bo0qGfJf5PPySPgAqwiVCnWwC8rfny8gpXT784Ca38ASAHZ2aEDkNNPt14Awjqk5hIqSG5s9GZnu4KtBx6QLr7YUkEXQwqjgCGFSLhw0vRJnJZPCIakALAatzv091Rf+4FYCzwHA3+LX3jBe4OgSxL/FjOkEEglkZRitcJQkmgJVk7fgmt/AEghfX1P8T2GRAs8BwMzX92DLckyw0PJcEUBGS4kXNek6erq4BksCmX0LjC4qqz0znsjKwgAQHyYMDsbyfU/AVcUEHAhKcTry8qEX4p96h50dSHYAgAAvWBIIZCK4jGUxKpFJpxOb2aru8pKgi0ACAfVXoGQCLgAhMft9g5brK8PXi2oK0tUX+9tZ6Yf2MZG7zDC7gLL6QMAeurrRtx774W+EWem3wqgnwi4AITHqkUmIimnDwD4Ul834laulM46q/cbcWYdFQFEiIALQPgCqx5OnSpt3Wre0vPByuZPmmSptT8AIGZC3Yh77z1p4UKpvd27oO3vf+9/I87MoyKACBFwAYhMYNBVXGzOYIty+gAwcL3diLvkki+DrY4O78K2VhgVAfQDAReAyFmhyESoVe8ly6z9AQAxF+pGXG2tdUZFAP1EWfgooCw8Uo6Vyqhbscw9ACTC1q3eYKtLXZ13mLaVfjOAf6EsPIDYsVqRiXiU0wcAqwtV7dUKoyKAASDgAhA+ikwgzlrbW9V8rFmt7a2J7gqA3vR1I277dpbeQEoj4AIQHopMII5qG2o1u2q2spdnK+/+PGUvz9bsqtmqa6hLdNcAdBfOjbjJk60zKgLoBwIuAOGhyATiZPVrqzVl7RRtrN8oj+GRJHkMjzbWb9RFay/SmtfXJLiHACT1fSPu8ce/rFI4aJD0wguMikBKomhGFFA0AymFIhOIodqGWk1ZO0WGev9pssmmmrk1Kh5d3GsbAHFSVeVdR6u62v9GnNvtXdS4vt4bbD3wgLRgwZf7u2fGCgqkPXv47YCpUDQDQOxQZAIxtGLbCqXZ00K2SbOn6YFXH4hTjwCEVFbmDZYCRz10HxWxd69/sCUxKgIphQxXFJDhAoCBa21vVfbybN8wwlDsNruOLT2mrEFZcegZgH5jVAQsigwXAMB0XG2usIItyTuny9XminGPAAwYoyIAAi4AQHJwZDpkt4X3s2S32eXIZEQBACD5EXABAJJC1qAslY4pVbo9PWS7dHu6Zo2dxXBCAIApEHABQDB9rSPGOmMxsahokTo9nSHbdHo6tfDChXHqEQAAA0PABQCBqqq85Yx7WxumsdG7v6oqvv1KAZNHT9aqmatkk61Hpivdni6bbFo1cxUl4QEApkHABQDdud3eNWXq64MvyNm1dkx9vbcdma6omz9xvmrm1qh0TKlvTpfdZlfpmFLVzK3R/InzE9xDAADCR1n4KKAsPGAx3RfkzM/3rhXjdPa+HTHT2t4qV5tLjkwHc7YAAEmDsvAAMBBdC3Lm53uDq6lTpa1bCbYSIGtQlnKzcwm2AACmFboUFACkqq6gqyvIKv7XnCGCLQAAEAEyXADQG6dTqqz031ZZSbAFAADCRsAFAL1pbJTKy/23lZf3Xr0QAAAgAAEXAAQTWCCjrs5/ThdBFwBEF+sfwqIIuAAgULBqhJMm9SykQdAFANHB+oewMAIuAOjO7ZZKSoJXIwysXlhSwh1XABgo1j+ExRFwAUB3GRnSsmVSQUHwaoRdQVdBgbddRkYiegkA1pGRIVVXBx9BEDjioLqa712YDgsfRwELHwMW5HaH/lHvaz8AIDKBwVVlpbdQEesfIglFcv3POlwAEExfwRTBFgBEF+sfwqIYUggAiJrW9lY1H2tWa3trorsCwIxY/xAWRMAFABiw2oZaza6arezl2cq7P0/Zy7M1u2q26hrqEt01AGbC+oewIFMGXCtXrtSpp56qwYMHq7CwUDt27Oi17UMPPaSLLrpIJ598sk4++WSVlJT0aH/NNdfIZrP5PWbMmBHrtwEAlrD6tdWasnaKNtZvlMfwSJI8hkcb6zfqorUXac3raxLcQwCmwPqHsCjTBVxVVVVatGiR7rjjDu3atUvnnnuupk+frk8++SRo+y1btuiKK67Qyy+/rG3btsnpdOqSSy7RRx995NduxowZOnTokO/xxBNPxOPtAICp1TbUasHzC2TIUIenw29fh6dDhgzd8NwNZLoAhMb6h7Aw01UpLCws1De+8Q39+te/liR5PB45nU7ddNNNWrJkSZ/P7+zs1Mknn6xf//rXuuqqqyR5M1xHjhzRM888068+UaUQQKqaXTVbG+s39gi2uku3p6t0TKme+u5TcewZANNwu72LGtfXBy+Q0T0YKyiQ9uyhcBESLpLrf1NluNxut3bu3KmSkhLfNrvdrpKSEm3bti2s1/j888/V3t6uoUOH+m3fsmWLRowYoTFjxuj666/XZ5991utrtLW1yeVy+T0AINW0trdqw/4NIYMtyZvpWr9vPYU0AATH+oewOFMFXJ9++qk6OzuVm5vrtz03N1dNTU1hvcZtt92mUaNG+QVtM2bM0O9//3tt3rxZv/zlL/XKK6/o0ksvVWdnZ9DXWL58uXJycnwPJ5VzAKQgV5vLN2erLx7DI1cbN6cA9KKszJu56u2ayun07i8ri2+/gChIqXW47r77bq1bt05btmzR4MGDfdvnzJnj+/9x48bpnHPO0emnn64tW7Zo2rRpPV5n6dKlWrRoke/PLpeLoAtAynFkOmS32cMKuuw2uxyZDLkGEALrH8KiTJXhGjZsmNLS0tTc3Oy3vbm5WXl5eSGfe9999+nuu+/WCy+8oHPOOSdk2/z8fA0bNkwHDhwIuj8zM1MOh8PvAQCpJmtQlkrHlCrdHvreXbo9XbPGzlLWoKw49QwAgORhqoArIyNDEyZM0ObNm33bPB6PNm/erKKiol6fd8899+iuu+7Spk2bNHHixD7/ng8//FCfffaZRo4cGZV+w2Tc7oHtB1LIoqJF6vQEH37dpdPTqYUXLoxTjwAASC6mCrgkadGiRXrooYf02GOPae/evbr++ut1/PhxzZ07V5J01VVXaenSpb72v/zlL3X77bfrkUce0amnnqqmpiY1NTXp2LFjkqRjx47plltu0auvvqoPPvhAmzdvVmlpqc444wxNnz49Ie8RCVRV5a2U1FvZ2cZG7/6qqvj2C0hSk0dP1qqZq2STrUemK92eLptsWjVzlYpHFyeoh0CK4aYhkHRMF3CVlZXpvvvuU0VFhcaPH6/du3dr06ZNvkIaDQ0NOnTokK/96tWr5Xa79e///u8aOXKk73HfffdJktLS0vTmm2/qsssuU0FBgebNm6cJEyaopqZGmZmZCXmPSBC3W6qo8JalDbbWR1dZ2vp6bzt+tABJ0vyJ81Uzt0alY0plt3l/Vuw2u0rHlKpmbo3mT5yf4B4CKYKbhkBSMt06XMmIdbgsJNjCi05n79vRb63trXK1ueTIdDC3x0L4dwUShLWsgLiy7DpcQMx1rfXRfVX7rVsJtqKotqFWs6tmK3t5tvLuz1P28mzNrpqtuoa6RHctulJ0WE/WoCzlZucSbAHxlpEhVVf7/351ZboCbxpWVxNsAXFEwAUECgy6iosJtqJk9WurNWXtFG2s3+grJe4xPNpYv1EXrb1Ia15fk+AeRgnDegAkAjcNgaTEkMIoYEihRW3d6g22utTVSZMmJa4/JlfbUKspa6fIUO9fOTbZVDO3xtwFFhjWAyDRun/PdCHYAqKKIYXAQDU2SuXl/tvKy3vPWKBPK7atUJo9LWSbNHuaHnj1gTj1KEYY1gMg0ZxOqbLSf1tlJcEWkCAEXECgwIviurrgF88IW2t7qzbs36AOT0fIdh2eDq3ft16t7a1x6lmMMKwHQCJx0xBIKgRcQHfBqhFOmtTz4pkfrYi42ly+OVt98RgeudpcMe5RHDAXEEAicNMQSDoEXEAXt1sqKQl+URx48VxSYtkqc7HgyHT41mfqi91mlyPTInMhGdYDIJ64aQgkJQIuoEtGhrRsmbeQQbAMRFfQVVDgbcfcm7BlDcpS6ZhSpdvTQ7ZLt6dr1thZ1ikpzrAeAPHCTUMgaRFwAd2VlXmrxvWWgXA6vfvLyuLbLwtYVLRInZ7OkG06PZ1aeOHCOPUoxhjWAyCeuGkIJC3KwkcBZeGB8Kx5fY1ueO4GpdnT/ApopNvT1enp1KqZqzR/4vwE9jBKgg3rcTp73w4A0eJ2hw6m+toPICyUhQeQlOZPnK+auTUqHVPqm9Nlt9lVOqZUNXNrrBFsMawHQCL1FUwRbAFxR4YrCshwAZFrbW+Vq80lR6bDOnO2ulRVSRUV3nW2gmWwGhu9wdayZQxPBQDAhCK5/ifgigICLgA9MKwHAADLYkghAERRa3urmo81R7YgM8N6AACACLgAoFe1DbWaXTVb2cuzlXd/nrKXZ2t21WzVNdQlumsAAMAkCLgAIIjVr63WlLVTtLF+ozyGR5LkMTzaWL9RF629SGteX5PgHsZHv7J7AADAh4ALAALUNtRqwfMLZMjwK18vSR2eDhkydMNzN1g600V2DwCA6CDgAoAAK7atUJo9LWSbNHuaHnj1gTj1KL7I7gEAED0EXADQTWt7qzbs39AjsxWow9Oh9fvWW26oHdk9AACii4ALALpxtbl8WZ2+eAyPXG2uGPcovlI9uwcAQLQRcAFAN45Mh+y28L4a7Ta7HJnWWXsv1bN7AADEAgEXUpPbPbD9sKysQVkqHVOqdHt6yHbp9nTNGjtLWYOy4tSz2Ev17B4AALFAwIXUU1UljRsnNTYG39/Y6N1fVRXffiFqBlrKfFHRInV6OkO26fR0auGFC/v1+skqlbN7AADECgEXUovbLVVUSPX10tSpPYOuxkbv9vp6bzsyXaYSrVLmk0dP1qqZq2STrUemK92eLptsWjVzlYpHF0ez+wmXytk9AABihYALqSUjQ6qulvLzpfff9wu6Wg++q+YZk9Xa8L53f3W1tz1MIdqlzOdPnK+auTUqHVPqy/rYbXaVjilVzdwazZ84P+rvIRmkanYPAIBYsRmGYSS6E2bncrmUk5OjlpYWORwMsTGFrkzW+++r9sJRWlF+pjY0vyKPXbJ7pNLTZmjxN39quQyGVdU21GrK2iky1PvXmU021cyt6de/aWt7q1xtLjkyHSmR1Vnz+hrd8NwNSrOn+RXQSLenq9PTqVUzV1k24AQAIByRXP+T4UJqcjqlLVu0esYwTZn+sTY2eYMtSfLYpY2N1SzwaiKxLmWeNShLudm5KRFsSamb3QMAS6FAWNIgwxUFZLjMyZsVuShETmRgWRHER2t7q7KXZ4dVXc9us+vY0mMpEzhFQ6pl9wDAEqqqvHPRq6u9N5kDNTZKJSXSsmVSWVn8+2cBZLiAMKx46edK6+ManQVekx+lzGMr1bJ7AGB6FAhLOgRcSEmtB9/VhoOb1NHHJ4AFXpMfpcwBAOgmRIGw7nPYKRAWPwRcSD2NjXJ9u8Q3Z6svZEWSG6XMAQAI8K+56n5B19at/sHWli3Bhxsi6gi4kFrcbqmkRI76BtnDG4VGVsQEKGUOAECAwKCruJhgK0EIuJBaMjKkZcuUlV+g0tNmWC8rkqIViVJ1oWIAAEJyOqXKSv9tlZUEW3FGwIXUU1Ym7dmjRd/8v9bKilRVSePG9Zwc26Wx0bu/qiq+/YoTSpkDABCgsVEqL/ffVl7e+7UCYoKy8FFAWXjzsswCr263N5iqrw8+VKD7JNmCAmnPHktPkqWUeXRwHAHAxAILZFRWeoMthhVGBWXhgTBZJitCRSI/lDIfmNqGWs2umq3s5dnKuz9P2cuzNbtqtuoa6hLdNQBAOAJ/+7dskSZN6llIg0xXXJDhigIyXNZgibv53M3CAK1+bbUWPL/A/FlfAEhVjHqJCzJcQD9YIitCRSIMQG1DrRY8v0CGDL9gS/KuSWfI0A3P3UCmCwCS2b8KhKmgIPhvf9e1QkGBtx3BVswRcAFWQ0Ui9NOKbSuUZk8L2SbNnqYHXn0gTj0CAPTLvwqE9frb73R695eVxbdfKapfAVdra6s++uijHtvffvvtAXcIwABRkQj90Nreqg37N/TIbAXq8HRo/b71am1vjVPPAAD90lfmisxW3EQccD311FM688wzNXPmTJ1zzjnavn27b1954EVejKxcuVKnnnqqBg8erMLCQu3YsSNk+yeffFJjx47V4MGDNW7cOD3//PN++w3DUEVFhUaOHKmsrCyVlJTo3XffjeVbAGIjcA5XXR2TYxEWV5tLHiO81cA9hkeuNleMewQAgDVEHHD97Gc/086dO7V7926tXbtW8+bN0+OPPy7JG7jEWlVVlRYtWqQ77rhDu3bt0rnnnqvp06frk08+Cdp+69atuuKKKzRv3jy98cYbuvzyy3X55Zfrrbfe8rW555579Ktf/Upr1qzR9u3bdeKJJ2r69On64osvYv5+gKihIhEGwJHp8FXq7IvdZpcjkwJBAACEI+IqhV/72tf8hg4ePnxYs2bN0rRp0/TMM89o165dUe9kd4WFhfrGN76hX//615Ikj8cjp9Opm266SUuWLOnRvqysTMePH9ef//xn37YLL7xQ48eP15o1a2QYhkaNGqXFixfrxz/+sSSppaVFubm5evTRRzVnzpwer9nW1qa2tjbfn10ul5xOJ1UKkThUJEIUzK6arY31G0MOK0y3p6t0TKme+u5TcewZAADJJaZVCkeMGKE333zT9+ehQ4fqxRdf1N69e/22x4Lb7dbOnTtVUlLi22a321VSUqJt27YFfc62bdv82kvS9OnTfe0PHjyopqYmvzY5OTkqLCzs9TWXL1+unJwc38NJMQIkGhWJEAWLihap09MZsk2np1MLL1wYpx4BAGB+YQdcR48elSRVVlZqxIgRfvsyMjL0xBNP6JVXXolu7wJ8+umn6uzsVG5urt/23NxcNTU1BX1OU1NTyPZd/43kNZcuXaqWlhbfo5EhWkgGVCTCAE0ePVmrZq6STTal29P99qXb02WTTatmrlLx6OIE9RAAAPMJO+C66KKL1NTUpFNOOUV5eXlB2xQXp8aPcGZmphwOh98DSApUJMIAzZ84XzVza1Q6ptQ3p8tus6t0TKlq5taw6DEAABFK77uJ13nnnafCwkL99a9/1dixY33bd+/erZ/85Cc9Kv/FwrBhw5SWlqbm5ma/7c3Nzb0GgXl5eSHbd/23ublZI0eO9Gszfvz4KPYeAMyheHSxikcXq7W9Va42lxyZDnMvCA4AQAKFneFau3atrrnmGk2ePFm1tbWqr6/Xd7/7XU2YMEFpaaEXyoyWjIwMTZgwQZs3b/Zt83g82rx5s4qKioI+p6ioyK+9JL344ou+9qeddpry8vL82rhcLm3fvr3X1wSAVJA1KEu52bkEWwAADEDYGS5JuvPOO5WZman/83/+jzo7OzVt2jRt27ZNF1xwQaz618OiRYt09dVXa+LEibrgggv0//7f/9Px48c1d+5cSdJVV12lr3zlK1q+fLkk6Uc/+pEuvvhi3X///Zo5c6bWrVun119/Xb/97W8lSTabTTfffLN+9rOf6cwzz9Rpp52m22+/XaNGjdLll18et/cFAEBvyDYCgHmFHXA1NzfrF7/4hR566CGdffbZ2rdvn6655pq4BluSt8z7P//5T1VUVKipqUnjx4/Xpk2bfEUvGhoaZLd/mbibNGmSHn/8cf30pz/VT37yE5155pl65pln9PWvf93X5tZbb9Xx48d13XXX6ciRI5o8ebI2bdqkwYMHx/W9AQDQXW1DrVZsW6EN+zfIY3h88+kWFy2meAmsye0OPd+4r/1AEgp7Ha4TTjhBY8aM0c9+9jPNnDlTmzZtUllZmX7605/qlltuiXU/k1okdfgBAAjH6tdWa8HzC5RmT/NbGy3dnq5OT6dWzVxFERNYS1WVVFEhVVcHr7jb2CiVlHiXN6HiLhIskuv/sAOudevW9VgEeNeuXfr2t7+tWbNmaeXKlf3vsckRcAEAoqm2oVZT1k6Rod5/om2yqWZuDZkuWIPbLY0bJ9XXS/n5PdeUbGyUpk6V3n/fu6bknj1kupBQMVn4ODDYkqTzzz9fW7du1UsvvRR5LwEAQFArtq1Qmj10Qao0e5oeePWBOPUIiLGMDG9mKz/fG1RNneoNsiT/YCs/39uOYAsmEnbA1ZtTTz1VW7dujUZfAABIea3trdqwf4PfMMJgOjwdWr9vvVrbW+PUMyDGnE5vZqt70LV1q3+wFZj5AkxgwAGXJJ188snReBkAAFKeq80lj+EJq63H8MjV5opxj4A4Cgy6iosJtmB6UQm4AABAdDgyHbLbwvt5ttvscmQydxgW43RKlZX+2yorCbasxO0e2H6TIeACACCJZA3KUumYUqXbQ6/ckm5P16yxs1iXC9bT2CiVl/tvKy//ck4XzK2qylsgpbd/z8ZG7/6qqvj2K4YIuAAASDKLihap09MZsk2np1MLL1wYpx4BcRJYIKOuLnghDZiT2+0t/V9fH/zfs+vfv77e284imS4CLgAAkszk0ZO1auYq2WTrkelKt6fLJptWzVxFSXhYS2CwtWWLNGlSz0IaBF3mlaLVKAm4AABIQvMnzlfN3BqVjin1zemy2+wqHVOqmrk1LHoMa3G7vYsaByuQEVhIo6TEMpmPlJSC1SjDXvgYvWPhYwBALLW2t8rV5pIj08GcLSRMzM/DqirvMLLq6uAX242N3mBr2TKprCz6fz/iq3tGq4uJgq1Irv8JuKKAgAsAAFhVbUOtVmxboQ37N8hjeHyZ1sVFi6M/rNXtDj2MrK/9MJetW72l/7vU1XmHkZpAJNf/DCkEAATV2t6q5mPNLKwLpLDVr63WlLVTtLF+o299OI/h0cb6jbpo7UVa8/qa6P6FfQVTBFvWkULVKAm4AAB+ahtqNbtqtrKXZyvv/jxlL8/W7KrZqmuoS3TXAMRRbUOtFjy/QIYMdXg6/PZ1eDpkyNANz93AdwMil2LVKAm4AAA+cb+bDSBprdi2Qmn2tJBt0uxpeuDVB+LUI1hCClajJOACAEjibjaAL7W2t2rD/g09vgsCdXg6tH7feoYeIzwpWo2SgAvx19eHxyIfLsBsuJsNoIurzeXLcvfFY3jkanPFuEewhIwMb5XJgoLg1Qi7gq6CAm87i8zZI+BCfFVVSePG9Z4mbmz07q+qim+/gBTH3WwA3TkyHb713/pit9nlyKRKM8JUVibt2dN76Xen07vfQqX/CbgQP263d32N+vrgY3O7xvTW13vbkekC4oa72QC6yxqUpdIxpUq3p4dsl2ZL02UFl7E+HCKTYtUoCbgQPxkZ3sUMg02IDJxAWV1tuQ8bkMy4m504lN9HslpUtEidns6QbTqNTm3Yv4FKpkAIBFyIr8AJkVOnehe9C6xWY4IVxgErCfdudro9XbPGzuJudhRQfh/JbvLoyVo1c5VssoX8bjBkUMkUCMFmGIaR6E6YXSQrTeNfume0uhBsAQlV21CrKWunyFDvPws22VQzt0bFo4tDvlZre6tcbS45Mh0EZ0Gsfm21Fjy/QGn2NL95c+n2dHV6OrVq5irNnzg/gT0EvlTXUKcHXn1A6/et73PocbjfEYDZRXL9T4YLieF0SpWV/tsqKwm2gAQKdTc73Z4um2xaNXNVyAspsjZ9o/x+arHCkNHi0cV66rtP6dtnfltpNiqZApEi4EJiNDZK5eX+28rLLbXIHWBG8yfOV83cGpWOKfXN6bLb7CodU6qauTUhsy4smhweyu+nBqvdfGhtb9Wf3/2zOo3Qc7qoZAr0xJDCKGBIYYQCC2RUVnqDLeZwAUklkmGB0RyOaGWt7a3KXp4dVkVIu82uY0uPMSTThKw4ZLT5WLPy7s8Lu33T4iblZufGsEdAYjGkEMkrMNjaskWaNKlnIQ0yXUDCZQ3KUm52blgX/GRtwkP5feuz6pBRKpkC/UfAhfhxu6WSkuCZrMDqhSUlrMMFmASLJoePi1brs+rNByqZAv1HwIX4yciQli2TCgqCDxvsCroKCrztWIcLMAWyNuHjotXarH7zIax1uTydWnjhwjj1CDAHAi7EV1mZtGdP73O0nE7v/rKy+PYLQL+RtYkMF63WZfWbD9GoZAqkIgIuxF9fmSsyW4CpkLWJDBet1pUKNx8GUskUSFWhfx0BAAjDoqJFembfMyHbkLX50vyJ8zVuxDi/xWS7LloXXriQYMukum4+bKzfGHJYYbo9XaVjSk1786F4dLGKRxezwDkQJsrCRwFl4QFAWvP6Gt3w3A2WKoUdD1y0WgtLJACpgbLwAIC4Y6hR/0RSfh/JjyGjAAKR4YoCMlwA4I+sDVJdXUNdjyGjs8bOYsgoYBGRXP8zhwsAEHVZg7IItJDSmOcEoAsBFwAAQIxw8wEAc7gAAAAAIEYIuAAAAAAgRgi4AAAAACBGCLgAAAAAIEZMFXAdPnxYV155pRwOh4YMGaJ58+bp2LFjIdvfdNNNGjNmjLKysjR69Gj98Ic/VEtLi187m83W47Fu3bpYvx0AAAAAFmeqKoVXXnmlDh06pBdffFHt7e2aO3eurrvuOj3++ONB23/88cf6+OOPdd999+nss8/WP/7xD82fP18ff/yxnnrqKb+2a9eu1YwZM3x/HjJkSCzfCgAAAIAUYJqFj/fu3auzzz5br732miZOnChJ2rRpk771rW/pww8/1KhRo8J6nSeffFLf//73dfz4caWne+NNm82m9evX6/LLL+9X31j4GAAAAEgdkVz/m2ZI4bZt2zRkyBBfsCVJJSUlstvt2r59e9iv03VQuoKtLgsWLNCwYcN0wQUX6JFHHlGoOLStrU0ul8vvAQAAAACBTDOksKmpSSNGjPDblp6erqFDh6qpqSms1/j0009111136brrrvPbvmzZMn3zm9/UCSecoBdeeEE33HCDjh07ph/+8IdBX2f58uW68847+/dGAAApq7W9Va42lxyZDhbDBYAUkfAM15IlS4IWrej+2Ldv34D/HpfLpZkzZ+rss8/Wf//3f/vtu/3221VcXKzzzjtPt912m2699Vbde++9vb7W0qVL1dLS4ns0NjYOuH8AAOuqbajV7KrZyl6erbz785S9PFuzq2arrqEu0V0DAMRYwjNcixcv1jXXXBOyTX5+vvLy8vTJJ5/4be/o6NDhw4eVl5cX8vlHjx7VjBkzdNJJJ2n9+vUaNGhQyPaFhYW666671NbWpszMzB77MzMzg24HACDQ6tdWa8HzC5RmT5PH8EiSPIZHG+s36pl9z2jVzFWaP3F+gnsJAIiVhAdcw4cP1/Dhw/tsV1RUpCNHjmjnzp2aMGGCJOmll16Sx+NRYWFhr89zuVyaPn26MjMz9eyzz2rw4MF9/l27d+/WySefTFAFABiQ2oZaLXh+gQwZ6vB0+O3r+vMNz92gcSPGqXh0cSK6CACIsYQPKQzXWWedpRkzZujaa6/Vjh07VFdXpxtvvFFz5szxVSj86KOPNHbsWO3YsUOSN9i65JJLdPz4cT388MNyuVxqampSU1OTOjs7JUkbN27U7373O7311ls6cOCAVq9erV/84he66aabEvZeAQDWsGLbCqXZ00K2SbOn6YFXH4hTjwAA8ZbwDFck/vjHP+rGG2/UtGnTZLfb9Z3vfEe/+tWvfPvb29u1f/9+ff7555KkXbt2+SoYnnHGGX6vdfDgQZ166qkaNGiQVq5cqYULF8owDJ1xxhlasWKFrr322vi9MQCA5bS2t2rD/g2+YYS96fB0aP2+9Wptb6WQBgBYkGnW4UpmrMMFAAjUfKxZefeHnmPcXdPiJuVm58awRwCAaLHkOlwAAJiJI9Mhuy28n1m7zS5HJjfsAMCKCLgAAIiBrEFZKh1TqnR76NH76fZ0zRo7i+GEAGBRBFwAAMTIoqJF6vR0hmzT6enUwgsXxqlHAIB4I+ACAMRUa3urmo81q7W9NdFdibvJoydr1cxVssnWI9OVbk+XTTatmrmKkvAAosPtHth+xAQBF2KPDz+QkmobajW7arayl2cr7/48ZS/P1uyq2aprqEt01+Jq/sT5qplbo9Ixpb45XXabXaVjSlUzt4ZFjwFER1WVNG6c1NgYfH9jo3d/VVV8+wWqFEYDVQpDqKqSKiqk6mrJ6ey5v7FRKimRli2Tysri3z8AMbH6tdVa8PwCpdnT/Bb8Tbenq9PTqVUzV6VkoNHa3ipXm0uOTAdztgBEj9vtDabq66X8fGnLFv/rrsZGaepU6f33pYICac8eKSMjUb21hEiu/wm4ooCAqxd8+IGUVNtQqylrp8hQ7z8vNtlUM7eGoXQAEC3dr6u6X3f1th0DQll4JIeMDG9mKz/f+yGfOvXLNHfgh7+6mmALsIgV21YozZ4Wsk2aPU0PvPpAnHoEACnA6fQGU92vu7ZuJdhKAmS4ooAMVx8Cg6vKSqm8nA8/YEGt7a3KXp4tj+Hps63dZtexpcdMO7SO4YEAklL3664uXG9FHRkuJJfAOy7FxQRbQJLrb2VBV5srrGBLkjyGR642V3+6l1AUAwGQ1JxO783t7iorud5KIAIuxAcffsAUBhpMODIdvkp8fbHb7HJkmmtUwOrXVmvK2inaWL/RF1h6DI821m/URWsv0prX1yS4h0ACUI04uTQ2ekcSdVde3nv1QsQcARfigw8/kPSiEUxkDcpS6ZjSHmtOBUq3p2vW2FmmGopX21CrBc8vkCHDr/KiJHV4OmTI0A3P3UCmC6mFUuTJJXAaR11d8Ln0iCsCLsQeH34g6UUzmFhUtEidns6QbTo9nVp44cIB9TneKAYCBHC7vUu/1NcH/z3v+v2vr/e2s1KmKxmzesGqEU6a1LOQBtddcUfAhdjiww+YQjSDicmjJ2vVzFWyydYj05VuT5dNNq2aucpUJeFb21u1Yf+GHsFooA5Ph9bvWx/x3DfAlFK1GnEyZvXcbu+6psHmyAfOpS8psVbwawIEXIgdPvyAKcQimJg/cb5q5taodEypb06X3WZX6ZhS1cytMd2ix6lQDASx199iNEkt1UqRJ2tWLyNDWrbMu65psOPd9e9UUOBtZ5Xg1yQoCx8FlIUPoarK+4VTXR38y7ax0RtsLVsmlZXFv38A1HysWXn354Xdvmlxk3Kzc8Nub4Xy6alU7h7RV9tQqxXbVmjD/g3yGB7fzYfFRYtNlekNKZVKkSfzAsNud+hgqq/9CBtl4ZE8ysqkPXt6/8JxOr37CbaAhIl1ZcGsQVnKzc41dQBi5WIgCMMA5uukTGXLVKpGnMxZvb6CKYKthCDgQuzx4QeSGsFEeKxaDAR9GMB8nZSqbJlq1YhZYxQRIOACABBMhMGKxUDQhwHO10mZypapWo04lbJ6GBACLgAAwUSYrFYMBH0YQBW+lKlsmcrViFMtq4d+o2hGFFA0A4BV1DXU6YFXH9D6fet9k/tnjZ2lhRcuTPlgK5AVioEgTIFBRWWl98I6xBCyWBejSQput3c4ZX198OPQ/bgVFHjnbFtlGkE/zglYSyTX/wRcUUDABcBqCCaAABFW4UuZypapWI04masUIm6oUggAGBArVBYEoirC+TopU4wm1aoRs8Yo+oGACwAAoC/9mK+TMsVoUqkaMQsMox8IuAAAAELpZxU+itFYVKpl9TBgBFwAAAC9GWAVPipbWlQqZfUwYBTNiAKKZgAAYEFRrsJHMRrAOiiaAQAAMFBRnq9DMRogNZHhigIyXAAAWJjbHTqY6ms/AMshwwUAABAtzNcBMAAEXAhPX+tIsM4EAAAA0AMBF/pWVeWdNNzbWiONjd79VVXx7RdgRdzcAADAUgi4EJrbLVVUeCs0BSt721Whqb7e246LQaD/uLkBAIDlEHAhtIwMqbo6+FojgWuTVFczjh3oL25uAABgSQRc6FtX2dvuQdfWrT0XguxtxXUAfePmBgAAlkTAhfAEBl3FxQRbQLRxcwMAAMsh4EL4nE6pstJ/W2UlF39ANHFzAwCQbCjoNCAEXAhfY6NUXu6/rby89wn+APqHmxsAgGRBQacBI+BCeALnkNTVBZ9rAmDguLkBAEgGFHSKClMFXIcPH9aVV14ph8OhIUOGaN68eTp27FjI50ydOlU2m83vMX/+fL82DQ0Nmjlzpk444QSNGDFCt9xyizo6OmL5VswlMNjaskWaNKnnXBMuBoGB4+YGAEBKjmF8FHSKClMFXFdeeaXefvttvfjii/rzn/+sv/3tb7ruuuv6fN61116rQ4cO+R733HOPb19nZ6dmzpwpt9utrVu36rHHHtOjjz6qioqKWL4V83C7pZKS4HNIAuealJRwZyMVJcMPglVwcwMAICXXMD4KOg2cYRLvvPOOIcl47bXXfNv+8pe/GDabzfjoo496fd7FF19s/OhHP+p1//PPP2/Y7XajqanJt2316tWGw+Ew2trawupbS0uLIcloaWkJq73prFtnGAUFhtHQEHx/Q4N3/7p18e0XEo9zI3ra2rzHSjKM/Pyex7Shwbtd8rYL8/sJAGAyyfp70P3v7XoE61+KiOT63zQZrm3btmnIkCGaOHGib1tJSYnsdru2b98e8rl//OMfNWzYMH3961/X0qVL9fnnn/u97rhx45Sbm+vbNn36dLlcLr399ttBX6+trU0ul8vvYWllZdKePb3fuXA6vfvLyuLbLyQW47qjKyNDWrZMKigIfqew6w5jQYG3HcM2AMCaknUYHwWd+s00AVdTU5NGjBjhty09PV1Dhw5VU1NTr8/73ve+pz/84Q96+eWXtXTpUlVWVur73/++3+t2D7Yk+f7c2+suX75cOTk5voczFU60vj7MXPylnmT9QTAzbm58iaGqAFJZMg7jo6BTvyU84FqyZEmPohaBj3379vX79a+77jpNnz5d48aN05VXXqnf//73Wr9+vd57771+v+bSpUvV0tLiezRyoiFVJeMPgtlxcyO55i4AQKIk07qMFHQakPREd2Dx4sW65pprQrbJz89XXl6ePvnkE7/tHR0dOnz4sPLy8sL++woLCyVJBw4c0Omnn668vDzt2LHDr01zc7Mk9fq6mZmZyszMDPvvBCyt6weh64u4uNi7nWAL/RE4VDXwHOr+o19RIc2alRpBKIDU1DWMr+u3VYr/ML5gBZ0Cf/uDfV/DJ+EZruHDh2vs2LEhHxkZGSoqKtKRI0e0c+dO33NfeukleTweXxAVjt27d0uSRo4cKUkqKirSnj17/IK5F198UQ6HQ2effXZ03iRgdYzrRrQwVBUAvhSvYXy9DdOmWnVUJDzgCtdZZ52lGTNm6Nprr9WOHTtUV1enG2+8UXPmzNGoUaMkSR999JHGjh3ry1i99957uuuuu7Rz50598MEHevbZZ3XVVVdpypQpOueccyRJl1xyic4++2yVl5fr73//u/7617/qpz/9qRYsWEAWC9YQj7kwA/1BYL4OukuGoaqckwASLV7D+EIN487IkH74Q2nQIGnRIgo69VccqiZGzWeffWZcccUVRnZ2tuFwOIy5c+caR48e9e0/ePCgIcl4+eWXDcMwjIaGBmPKlCnG0KFDjczMTOOMM84wbrnllh7lGz/44APj0ksvNbKysoxhw4YZixcvNtrb28Pul+XLwsO84lG2vXuZ2Px8w6ir8/9zX+ViKS2P3iSqBDHnJIBEC/xt7fo+6m17f0WrBH0KLlUSyfW/zTAMI8Exn+m5XC7l5OSopaVFDocj0d0BvNxu7x2r+vrgGYHud84KCrzV7yK9M9XbuO7etieijzC3rVv95y7U1XkXg44VzkkAiRbv76GB/panqEiu/00zpBBAhGI9FyYa47qZr4NQElGCmHMSQKLFe13GZBjGbXFkuKKADBeSWuBFYmWl96I1Gl+iVVXeSnHV1cFfo7HRG2wtWxZ67ahY9hHmlOhzItF/PwC43aGDqb72R6r7914Xvu96Fcn1PwFXFBBwIenF8ks0Wj8IfNGjS7IMb+GcBJBq4j2M28QYUgjAXyzLtkdroV5Ky0NKrhLEnJNIBlTMRLwkYhh3iiDgAlKBGb5EKS0PKf5zF0Ixw+cG1haqXLfk3T5unLcdrCeev2vxKkGfogi4AKszw5foQPvIRYm1lJV5q271lklyOr37Q80LHCgzfG5gbW63d45sfX3wc67rHK2v97bjppK1xPN3Ldhw7UmTehbS4Huv/2JaoD5FsA4Xkla81vFIZB+jtYYI0MUMnxukBs7F1BTP3zV+Q/stkut/MlyAVSXTXJhY9pEy3ogmM3xukDoo152a4vm7lkzDuC2MgAuwKjN8iUarj1yUIFrM8LlBagn8fisu5nstFcTzdy0ZhnFbHGXho4Cy8Ehq8V7Hoz8oLY9kY4bPDVIL5bpTE79rSYuy8AC+FK2y7bFEaXkkGzN8bpA6qJiZuvhdswQCLgDWwUUJAKuhYmZq43fNEgi4AFgDFyUArIZy3amN3zXLIOACYH5clACwGipmpjZ+1yyFgAuAuXFRAsCKqJiZuvhdsxwCLgDmxkUJAKuiXHdq4nfNcigLHwWUhQeSAGW8AQBWwu9aUqMsPIDUQxlvSH0PrWHoDQCz4HfNMgi4AADWUFUljRvX+yTyxkbv/qqq+PYLAJDSCLgAIBHIxESX2y1VVEj19cErd3VV/Kqv97bj+AIA4oSACwDijUxM9GVkSNXVwcslB5ZXrq5mKA4AIG4IuAAgnsjExE5gueSpU6WtW3uuZdNbxTcAAGKAgAsA4olMTGwFBl3FxQRbAICEIuACgHgjExNbTqdUWem/rbKS4wkASAgCLgBIBDIxsdPYKJWX+28rL+99zhwAADFEwAUAiUImJvoCh2XW1QUfvgkAQJwQcAFAopCJia7AYGvLFmnSpJ7DNzm+AIA4IuACgEQgExNdbrdUUhJ8WGbg8M2SEqo/AgDihoALAOKNTEz0ZWRIy5ZJBQXB58B1BV0FBd52VH8EAMSJzTAMI9GdMDuXy6WcnBy1tLTI4XAkujsAkpnb7V3UuL4+eIGM7sFYQYG0Zw/BQSTc7tDHq6/9AACEIZLrfzJcABBPZGJiq6/jxfEEAMQZGa4oIMOFhOOuvvnwbwYAgGmR4QJSSVWVd4hab/N9Ghu9+6uq4tsvhEYmBgCAlEDABZiZ2y1VVHjnAwUrstA1H6i+3tuOymwAAABxRcAFmFlGhlRdHbyyXWAlvOpqsiYAAABxRsAFmF3gGkNTp0pbt/YsOx5YnAEAAAAxR8AFWEFg0FVcTLAFAECi9DWEnyH+KYWAC7AKp1OqrPTfVllJsAUAQDxRzAoBCLgAq2hslMrL/beVl/f+hQ8AAKKLYlYIgoALsILAAhl1dcELaQAAgNihmBWCMFXAdfjwYV155ZVyOBwaMmSI5s2bp2PHjvXa/oMPPpDNZgv6ePLJJ33tgu1ft25dPN4SMHCBX+BbtkiTJvUspEHQBQBA7FHMCgFshmEYie5EuC699FIdOnRIv/nNb9Te3q65c+fqG9/4hh5//PGg7Ts7O/XPf/7Tb9tvf/tb3XvvvTp06JCys7MleQOutWvXasaMGb52Q4YM0eDBg8PqVyQrTQNR5XZ7x4HX1wf/Au8ejBUUSHv2cDcNAIB46P4b3CXVgi23O/R1R1/7k1gk1/+myXDt3btXmzZt0u9+9zsVFhZq8uTJevDBB7Vu3Tp9/PHHQZ+TlpamvLw8v8f69ev13e9+1xdsdRkyZIhfu3CDLSChMjKkZcu8wVSwL/Cuu2wFBd52Jv1SAwDAdFK9mBXFQ3xMk+F65JFHtHjxYv3P//yPb1tHR4cGDx6sJ598UrNmzerzNXbu3KmJEyeqrq5OkyZN8m232WwaNWqU2tralJ+fr/nz52vu3Lmy2WxBX6etrU1tbW2+P7tcLjmdTjJcSBwL30ECAMCUUjnDlQIjcCyZ4WpqatKIESP8tqWnp2vo0KFqamoK6zUefvhhnXXWWX7BliQtW7ZMf/rTn/Tiiy/qO9/5jm644QY9+OCDvb7O8uXLlZOT43s4rf6hQfLr60vKLF9irFsCALCCVC9mRfEQPwkPuJYsWdJrYYuux759+wb897S2turxxx/XvHnzeuy7/fbbVVxcrPPOO0+33Xabbr31Vt177729vtbSpUvV0tLiezRa/UMDxANDDwAAVkAxKy+Kh/gkfEjhP//5T3322Wch2+Tn5+sPf/jDgIYUVlZWat68efroo480fPjwkG2fe+45ffvb39YXX3yhzMzMPt8DRTOAAUqBoQcAgBTA71lPFh1aGcn1f3qc+tSr4cOH9xkASVJRUZGOHDminTt3asKECZKkl156SR6PR4WFhX0+/+GHH9Zll10W1t+1e/dunXzyyWEFWwCioGvoQdcX8tSpX34Rp+DQAwCASXUVs6qo8P5e9VbMqqQk8cWs4jX/u6t4SHHxl9tSqXiIkmBIYbjOOusszZgxQ9dee6127Nihuro63XjjjZozZ45GjRolSfroo480duxY7dixw++5Bw4c0N/+9jf94Ac/6PG6Gzdu1O9+9zu99dZbOnDggFavXq1f/OIXuummm+LyvgD8C0MPAABWUFbmzVz19nvldHr3l5XFt1/dxXMYf2OjVF7uv6283PpDKrsxTcAlSX/84x81duxYTZs2Td/61rc0efJk/fa3v/Xtb29v1/79+/X555/7Pe+RRx7RKaecoksuuaTHaw4aNEgrV65UUVGRxo8fr9/85jdasWKF7rjjjpi/HwABAoOu4mKCLQCA+SRzMSu325uBq68PPpesa2RJfb233UAKVqV68ZB/SfgcLitgDhcQZVu3+g89qKvzTjgGAAADF6ywR7Bh/AO52RmPvyOBLFkWHkCKYOgBAACxFeth/G63d55asNcK/LtLSiy/7AsBF4DkwdADAADiI5bD+LuKhxQUBH+trr+7oCDxxUPigCGFUcCQQiAKLD70AACApBTLYfzxqoSYAAwpBGAuDD0AACD+Yj2MP5mLh8QRAReAxGPoAQAA8cUw/rhhSGEUMKQQiBILDz0AACBpMIx/wBhSCMCcGHoAAObX17BvhoUnFsP4446ACwAAANFRVSWNG9f7cLTGRu/+qqr49gtfYhh/3DGkMAoYUggAQBJimHJ8ud3eYKq+PvhwtO7D1QoKpD17OP6JxOdjQBhSCAAAUhuZlvjLyJCqq4MXXgicG1RdzcV8ojGMP24IuAAAgLW43VJFhTfTEqzaWtfFf329tx1zVKIncA7Q1KnedZ4oxIBIWWguIAEXAACwFjItiRUYdBUXE2whMhbLUBNwAQDiy0J3LZHEyLQkltMpVVb6b6us5HijbxbMUBNwAQDix2J3LZHkyLQkTmOjVF7uv628nMV00TcLZqgJuAAA8WHBu5YwATIt8Rd4UVxXF/ziGeiNxTLUBFwAgPiw4F1LmACZlvgK/Cxv2SJNmtTz4pnjj75YKENNwAUAiJ9kv2vJ/DJrIdMSX263VFIS/LMc+NkvKeHzhL5ZJENNwAUAiK9kvWvJ/DJrIdMSfxkZ0rJl3kWNg32Wuz77BQXedmSx0ReLZKhthmEYie6E2UWy0jQA4F+2bvUGW13q6rwXxIngdnuDqfr64IFf94v3ggJpzx4uFsPldoc+Vn3t7+/fyb9n4kT73zwR5xASL/CmSWWlN9hKhht0iuz6nwwXACD+ku2uJfPLYiNRWUMyLYnV1/GM5HiTeU5NFstQk+GKAjJcABCBZL5rmcx9M5tkyDKRGTG3ZDiHEH8m+XcnwwUASE7JftcyWeeXmVEyZA2jmWlB/CXDOYT4s2CGmgxXFJDhAoAwmOSupaTkml9mdmQNMVCcQ6kpyTPUZLgAAMnHLHctk21+mdmRNcRAcQ6lJgtlqMlwRQEZLvQpye/SAHGVzJ8H7qTHDllDDBTnEJIIGS4gmVBhCfCXrHctk31+mZmRNcRAcQ7BxAi4gFhyu6WKCu+clWAXal0XePX13nZudyJ6CcDtlkpKgmeyAoczlZTwWY1EYCBbV0cAi8hwDsHkCLiAWKLCEmAOZplfZjZkDTFQnEOwAOZwRQFzuNAn5oUA5pDM88vMxkxVKZGcOIeQxJjDBSQbKiwB5pCs88vMiKwhBopzCBZBhisKyHAhbFRYApBqyBpioDiHkITIcAHJiApLAFIRWUMMFOcQTI6AC4gHKiwBAACkJAIuINaosOTVVxltymwDAAALIuACYom1fbxY/BkAAKQoAi4glqiwxOLPAAAgpVGlMAqoUog+pXqFpWDDKp3O3rcDAAAkMaoUAskm1SssBQ6fnDrVWyKfYAsAAFhceqI7ACBFdAVdXUFW13pkBFsAAMDCTJPh+vnPf65JkybphBNO0JAhQ8J6jmEYqqio0MiRI5WVlaWSkhK9++67fm0OHz6sK6+8Ug6HQ0OGDNG8efN07NixGLwDAHI6pcpK/22VlQRbAADAskwTcLndbv3Hf/yHrr/++rCfc8899+hXv/qV1qxZo+3bt+vEE0/U9OnT9cUXX/jaXHnllXr77bf14osv6s9//rP+9re/6brrrovFWwDA4s8AACDFmK5oxqOPPqqbb75ZR44cCdnOMAyNGjVKixcv1o9//GNJUktLi3Jzc/Xoo49qzpw52rt3r84++2y99tprmjhxoiRp06ZN+ta3vqUPP/xQo0aNCqtPFM0AwhBYIKOy0htsMYcLAACYDEUzJB08eFBNTU0qKSnxbcvJyVFhYaG2bdsmSdq2bZuGDBniC7YkqaSkRHa7Xdu3b+/1tdva2uRyufweAEJg8WcAAJCiLBtwNTU1SZJyc3P9tufm5vr2NTU1acSIEX7709PTNXToUF+bYJYvX66cnBzfw8ldeaB3LP4MAABSWEIDriVLlshms4V87Nu3L5FdDGrp0qVqaWnxPRq5Kw/0jsWfAQBACktoWfjFixfrmmuuCdkmPz+/X6+dl5cnSWpubtbIkSN925ubmzV+/Hhfm08++cTveR0dHTp8+LDv+cFkZmYqMzOzX/0CUlJZmTRrVu/BlNMp7dlDsAUAACwnoQHX8OHDNXz48Ji89mmnnaa8vDxt3rzZF2C5XC5t377dV+mwqKhIR44c0c6dOzVhwgRJ0ksvvSSPx6PCwsKY9AtIWam++DMAAEhJppnD1dDQoN27d6uhoUGdnZ3avXu3du/e7bdm1tixY7V+/XpJks1m080336yf/exnevbZZ7Vnzx5dddVVGjVqlC6//HJJ0llnnaUZM2bo2muv1Y4dO1RXV6cbb7xRc+bMCbtCIQAAAAD0JqEZrkhUVFToscce8/35vPPOkyS9/PLLmjp1qiRp//79amlp8bW59dZbdfz4cV133XU6cuSIJk+erE2bNmnw4MG+Nn/84x914403atq0abLb7frOd76jX/3qV/F5UwAAAAAszXTrcCUj1uECAAAAUgfrcAEAAABAEiDgAgAAAIAYIeACAAAAgBgh4AIAAACAGCHgAgAAAIAYIeACAAAAgBgh4AIAAACAGDHNwsfJrGspM5fLleCeAAAAAIi1ruv+cJY0JuCKgqNHj0qSnE5ngnsCAAAAIF6OHj2qnJyckG1sRjhhGULyeDz6+OOPddJJJ8lmsyWkDy6XS06nU42NjX2udo3IcGxji+MbWxzf2OL4xg7HNrY4vrHF8Y2dZDm2hmHo6NGjGjVqlOz20LO0yHBFgd1u1ymnnJLobkiSHA4HH+wY4djGFsc3tji+scXxjR2ObWxxfGOL4xs7yXBs+8psdaFoBgAAAADECAEXAAAAAMQIAZdFZGZm6o477lBmZmaiu2I5HNvY4vjGFsc3tji+scOxjS2Ob2xxfGPHjMeWohkAAAAAECNkuAAAAAAgRgi4AAAAACBGCLgAAAAAIEYIuAAAAAAgRgi4AAAAACBGCLhM4uc//7kmTZqkE044QUOGDAnrOYZhqKKiQiNHjlRWVpZKSkr07rvv+rU5fPiwrrzySjkcDg0ZMkTz5s3TsWPHYvAOklukx+GDDz6QzWYL+njyySd97YLtX7duXTzeUlLpz3k2derUHsdu/vz5fm0aGho0c+ZMnXDCCRoxYoRuueUWdXR0xPKtJJ1Ij+3hw4d10003acyYMcrKytLo0aP1wx/+UC0tLX7tUvXcXblypU499VQNHjxYhYWF2rFjR8j2Tz75pMaOHavBgwdr3Lhxev755/32h/M9nEoiOb4PPfSQLrroIp188sk6+eSTVVJS0qP9Nddc0+M8nTFjRqzfRtKK5Pg++uijPY7d4MGD/dpw/n4pkmMb7PfLZrNp5syZvjacu1/629/+pn/7t3/TqFGjZLPZ9Mwzz/T5nC1btuj8889XZmamzjjjDD366KM92kT6fR5TBkyhoqLCWLFihbFo0SIjJycnrOfcfffdRk5OjvHMM88Yf//7343LLrvMOO2004zW1lZfmxkzZhjnnnuu8eqrrxo1NTXGGWecYVxxxRUxehfJK9Lj0NHRYRw6dMjvceeddxrZ2dnG0aNHfe0kGWvXrvVr1/34p4r+nGcXX3yxce211/odu5aWFt/+jo4O4+tf/7pRUlJivPHGG8bzzz9vDBs2zFi6dGms305SifTY7tmzx5g9e7bx7LPPGgcOHDA2b95snHnmmcZ3vvMdv3apeO6uW7fOyMjIMB555BHj7bffNq699lpjyJAhRnNzc9D2dXV1RlpamnHPPfcY77zzjvHTn/7UGDRokLFnzx5fm3C+h1NFpMf3e9/7nrFy5UrjjTfeMPbu3Wtcc801Rk5OjvHhhx/62lx99dXGjBkz/M7Tw4cPx+stJZVIj+/atWsNh8Phd+yampr82nD+ekV6bD/77DO/4/rWW28ZaWlpxtq1a31tOHe/9Pzzzxv/9//+X+Ppp582JBnr168P2f799983TjjhBGPRokXGO++8Yzz44INGWlqasWnTJl+bSP/NYo2Ay2TWrl0bVsDl8XiMvLw849577/VtO3LkiJGZmWk88cQThmEYxjvvvGNIMl577TVfm7/85S+GzWYzPvroo6j3PVlF6ziMHz/e+M///E+/beF8cVhdf4/vxRdfbPzoRz/qdf/zzz9v2O12vwuE1atXGw6Hw2hra4tK35NdtM7dP/3pT0ZGRobR3t7u25aK5+4FF1xgLFiwwPfnzs5OY9SoUcby5cuDtv/ud79rzJw5029bYWGh8V//9V+GYYT3PZxKIj2+gTo6OoyTTjrJeOyxx3zbrr76aqO0tDTaXTWlSI9vX9cTnL9fGui5+8ADDxgnnXSScezYMd82zt3gwvntufXWW42vfe1rftvKysqM6dOn+/480H+zaGNIoUUdPHhQTU1NKikp8W3LyclRYWGhtm3bJknatm2bhgwZookTJ/ralJSUyG63a/v27XHvc6JE4zjs3LlTu3fv1rx583rsW7BggYYNG6YLLrhAjzzyiIwUW2t8IMf3j3/8o4YNG6avf/3rWrp0qT7//HO/1x03bpxyc3N926ZPny6Xy6W33347+m8kCUXrM9zS0iKHw6H09HS/7al07rrdbu3cudPvO9Nut6ukpMT3nRlo27Ztfu0l7znY1T6c7+FU0Z/jG+jzzz9Xe3u7hg4d6rd9y5YtGjFihMaMGaPrr79en332WVT7bgb9Pb7Hjh3TV7/6VTmdTpWWlvp9d3L+ekXj3H344Yc1Z84cnXjiiX7bOXf7p6/v3mj8m0Vbet9NYEZNTU2S5Hcx2vXnrn1NTU0aMWKE3/709HQNHTrU1yYVROM4PPzwwzrrrLM0adIkv+3Lli3TN7/5TZ1wwgl64YUXdMMNN+jYsWP64Q9/GLX+J7v+Ht/vfe97+upXv6pRo0bpzTff1G233ab9+/fr6aef9r1usPO7a18qiMa5++mnn+quu+7Sdddd57c91c7dTz/9VJ2dnUHPqX379gV9Tm/nYPfv2K5tvbVJFf05voFuu+02jRo1yu8iasaMGZo9e7ZOO+00vffee/rJT36iSy+9VNu2bVNaWlpU30My68/xHTNmjB555BGdc845amlp0X333adJkybp7bff1imnnML5+y8DPXd37Niht956Sw8//LDfds7d/uvtu9flcqm1tVX/8z//M+Dvm2gj4EqgJUuW6Je//GXINnv37tXYsWPj1CNrCff4DlRra6sef/xx3X777T32dd923nnn6fjx47r33nstcdEa6+PbPQAYN26cRo4cqWnTpum9997T6aef3u/XNYN4nbsul0szZ87U2Wefrf/+7//222flcxfmc/fdd2vdunXasmWLX2GHOXPm+P5/3LhxOuecc3T66adry5YtmjZtWiK6ahpFRUUqKiry/XnSpEk666yz9Jvf/EZ33XVXAntmLQ8//LDGjRunCy64wG87525qIeBKoMWLF+uaa64J2SY/P79fr52XlydJam5u1siRI33bm5ubNX78eF+bTz75xO95HR0dOnz4sO/5Zhbu8R3ocXjqqaf0+eef66qrruqzbWFhoe666y61tbUpMzOzz/bJLF7Ht0thYaEk6cCBAzr99NOVl5fXo+JQc3OzJJn+/I3HsT169KhmzJihk046SevXr9egQYNCtrfSuRvMsGHDlJaW5juHujQ3N/d6LPPy8kK2D+d7OFX05/h2ue+++3T33Xerurpa55xzTsi2+fn5GjZsmA4cOJBSF60DOb5dBg0apPPOO08HDhyQxPnbZSDH9vjx41q3bp2WLVvW59+Tquduf/T23etwOJSVlaW0tLQBfx6ijTlcCTR8+HCNHTs25CMjI6Nfr33aaacpLy9Pmzdv9m1zuVzavn27745WUVGRjhw5op07d/ravPTSS/J4PL6LWzML9/gO9Dg8/PDDuuyyyzR8+PA+2+7evVsnn3yyJS5Y43V8u+zevVuSfD/8RUVF2rNnj1/A8eKLL8rhcOjss8+OzptMkFgfW5fLpUsuuUQZGRl69tlne5SCDsZK524wGRkZmjBhgt93psfj0ebNm/2yAN0VFRX5tZe852BX+3C+h1NFf46vJN1zzz266667tGnTJr+5ir358MMP9dlnn/kFCKmgv8e3u87OTu3Zs8d37Dh/vQZybJ988km1tbXp+9//fp9/T6qeu/3R13dvND4PUZeQUh2I2D/+8Q/jjTfe8JUef+ONN4w33njDrwT5mDFjjKefftr357vvvtsYMmSIsWHDBuPNN980SktLg5aFP++884zt27cbtbW1xplnnpmyZeFDHYcPP/zQGDNmjLF9+3a/57377ruGzWYz/vKXv/R4zWeffdZ46KGHjD179hjvvvuusWrVKuOEE04wKioqYv5+kk2kx/fAgQPGsmXLjNdff904ePCgsWHDBiM/P9+YMmWK7zldZeEvueQSY/fu3camTZuM4cOHp2RZ+EiObUtLi1FYWGiMGzfOOHDggF9J4o6ODsMwUvfcXbdunZGZmWk8+uijxjvvvGNcd911xpAhQ3yVMMvLy40lS5b42tfV1Rnp6enGfffdZ+zdu9e44447gpaF7+t7OFVEenzvvvtuIyMjw3jqqaf8ztOu372jR48aP/7xj41t27YZBw8eNKqrq43zzz/fOPPMM40vvvgiIe8xkSI9vnfeeafx17/+1XjvvfeMnTt3GnPmzDEGDx5svP322742nL9ekR7bLpMnTzbKysp6bOfc9Xf06FHfda0kY8WKFcYbb7xh/OMf/zAMwzCWLFlilJeX+9p3lYW/5ZZbjL179xorV64MWhY+1L9ZvBFwmcTVV19tSOrxePnll31t9K91c7p4PB7j9ttvN3Jzc43MzExj2rRpxv79+/1e97PPPjOuuOIKIzs723A4HMbcuXP9grhU0ddxOHjwYI/jbRiGsXTpUsPpdBqdnZ09XvMvf/mLMX78eCM7O9s48cQTjXPPPddYs2ZN0LZWF+nxbWhoMKZMmWIMHTrUyMzMNM444wzjlltu8VuHyzAM44MPPjAuvfRSIysryxg2bJixePFiv9LmqSDSY/vyyy8H/S6RZBw8eNAwjNQ+dx988EFj9OjRRkZGhnHBBRcYr776qm/fxRdfbFx99dV+7f/0pz8ZBQUFRkZGhvG1r33NeO655/z2h/M9nEoiOb5f/epXg56nd9xxh2EYhvH5558bl1xyiTF8+HBj0KBBxle/+lXj2muvTdgFVTKI5PjefPPNvra5ubnGt771LWPXrl1+r8f5+6VIvxv27dtnSDJeeOGFHq/Fueuvt9+lrmN69dVXGxdffHGP54wfP97IyMgw8vPz/a5/u4T6N4s3m2FYuM4vAAAAACQQc7gAAAAAIEYIuAAAAAAgRgi4AAAAACBGCLgAAAAAIEYIuAAAAAAgRgi4AAAAACBGCLgAAAAAIEYIuAAAAAAgRgi4AAAAACBGCLgAAAjDE088oaysLB06dMi3be7cuTrnnHPU0tKSwJ4BAJKZzTAMI9GdAAAg2RmGofHjx2vKlCl68MEHdccdd+iRRx7Rq6++qq985SuJ7h4AIEmlJ7oDAACYgc1m089//nP9+7//u/Ly8vTggw+qpqbGF2zNmjVLW7Zs0bRp0/TUU08luLcAgGRBhgsAgAicf/75evvtt/XCCy/o4osv9m3fsmWLjh49qscee4yACwDgwxwuAADCtGnTJu3bt0+dnZ3Kzc312zd16lSddNJJCeoZACBZEXABABCGXbt26bvf/a4efvhhTZs2TbfffnuiuwQAMAHmcAEA0IcPPvhAM2fO1E9+8hNdccUVys/PV1FRkXbt2qXzzz8/0d0DACQxMlwAAIRw+PBhzZgxQ6WlpVqyZIkkqbCwUJdeeql+8pOfJLh3AIBkR4YLAIAQhg4dqn379vXY/txzzyWgNwAAs6FKIQAAUVBSUqK///3vOn78uIYOHaonn3xSRUVFie4WACDBCLgAAAAAIEaYwwUAAAAAMULABQAAAAAxQsAFAAAAADFCwAUAAAAAMULABQAAAAAxQsAFAAAAADFCwAUAAAAAMULABQAAAAAxQsAFAAAAADFCwAUAAAAAMULABQAAAAAx8v8B3qi58XN4iVsAAAAASUVORK5CYII=", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plot_data_for_classification(Xpl, Ypl, xlabel=r\"$x_1$\", ylabel=r\"$x_2$\")\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "Propozycja hipotezy:\n", + "\n", + "$$ h_\\theta(x) = g(\\theta^T x) = g(\\theta_0 + \\theta_1 x_1 + \\theta_2 x_2 + \\theta_3 x_3 + \\theta_4 x_4 + \\theta_5 x_5) \\; , $$\n", + "\n", + "gdzie $g$ – funkcja logistyczna, $x_3 = x_1^2$, $x_4 = x_2^2$, $x_5 = x_1 x_2$." + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "slideshow": { + "slide_type": "notes" + } + }, + "outputs": [], + "source": [ + "def safeSigmoid(x, eps=0):\n", + " \"\"\"Funkcja sigmoidalna zmodyfikowana w taki sposób,\n", + " żeby wartości zawsz były odległe od asymptot o co najmniej eps\n", + " \"\"\"\n", + " y = 1.0 / (1.0 + np.exp(-x))\n", + " if eps > 0:\n", + " y[y < eps] = eps\n", + " y[y > 1 - eps] = 1 - eps\n", + " return y\n", + "\n", + "\n", + "def h(theta, X, eps=0.0):\n", + " \"\"\"Funkcja hipotezy\"\"\"\n", + " return safeSigmoid(X * theta, eps)\n", + "\n", + "\n", + "def J(h, theta, X, y, lamb=0):\n", + " \"\"\"Funkcja kosztu\"\"\"\n", + " m = len(y)\n", + " f = h(theta, X, eps=10**-7)\n", + " j = (\n", + " -np.sum(np.multiply(y, np.log(f)) + np.multiply(1 - y, np.log(1 - f)), axis=0)\n", + " / m\n", + " )\n", + " if lamb > 0:\n", + " j += lamb / (2 * m) * np.sum(np.power(theta[1:], 2))\n", + " return j\n", + "\n", + "\n", + "def dJ(h, theta, X, y, lamb=0):\n", + " \"\"\"Pochodna funkcji kosztu\"\"\"\n", + " g = 1.0 / y.shape[0] * (X.T * (h(theta, X) - y))\n", + " if lamb > 0:\n", + " g[1:] += lamb / float(y.shape[0]) * theta[1:]\n", + " return g\n", + "\n", + "\n", + "def classifyBi(theta, X):\n", + " \"\"\"Funkcja decyzji\"\"\"\n", + " prob = h(theta, X)\n", + " return prob\n" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "slideshow": { + "slide_type": "notes" + } + }, + "outputs": [], + "source": [ + "def GD(h, fJ, fdJ, theta, X, y, alpha=0.01, eps=10**-3, maxSteps=10000):\n", + " \"\"\"Metoda gradientu prostego dla regresji logistycznej\"\"\"\n", + " errorCurr = fJ(h, theta, X, y)\n", + " errors = [[errorCurr, theta]]\n", + " while True:\n", + " # oblicz nowe theta\n", + " theta = theta - alpha * fdJ(h, theta, X, y)\n", + " # raportuj poziom błędu\n", + " errorCurr, errorPrev = fJ(h, theta, X, y), errorCurr\n", + " # kryteria stopu\n", + " if abs(errorPrev - errorCurr) <= eps:\n", + " break\n", + " if len(errors) > maxSteps:\n", + " break\n", + " errors.append([errorCurr, theta])\n", + " return theta, errors\n" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "theta = [[ 1.59558981]\n", + " [ 0.12602307]\n", + " [ 0.65718518]\n", + " [-5.26367581]\n", + " [ 1.96832544]\n", + " [-6.97946065]]\n" + ] + } + ], + "source": [ + "# Uruchomienie metody gradientu prostego dla regresji logistycznej\n", + "theta_start = np.matrix(np.zeros(Xpl.shape[1])).reshape(Xpl.shape[1], 1)\n", + "theta, errors = GD(\n", + " h, J, dJ, theta_start, Xpl, Ypl, alpha=0.1, eps=10**-7, maxSteps=10000\n", + ")\n", + "print(r\"theta = {}\".format(theta))\n" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "slideshow": { + "slide_type": "notes" + } + }, + "outputs": [], + "source": [ + "def plot_decision_boundary(fig, theta, X):\n", + " \"\"\"Wykres granicy klas\"\"\"\n", + " ax = fig.axes[0]\n", + " xx, yy = np.meshgrid(np.arange(-1.0, 1.0, 0.02), np.arange(-1.0, 1.0, 0.02))\n", + " l = len(xx.ravel())\n", + " C = powerme(xx.reshape(l, 1), yy.reshape(l, 1), n)\n", + " z = classifyBi(theta, C).reshape(int(np.sqrt(l)), int(np.sqrt(l)))\n", + "\n", + " plt.contour(xx, yy, z, levels=[0.5], lw=3)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/tmp/ipykernel_539/3318422759.py:10: UserWarning: The following kwargs were not used by contour: 'lw'\n", + " plt.contour(xx, yy, z, levels=[0.5], lw=3);\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plot_data_for_classification(Xpl, Ypl, xlabel=r\"$x_1$\", ylabel=r\"$x_2$\")\n", + "plot_decision_boundary(fig, theta, Xpl)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "slideshow": { + "slide_type": "notes" + } + }, + "outputs": [], + "source": [ + "# Wczytanie danych\n", + "\n", + "alldata = pandas.read_csv(\"polynomial_logistic.tsv\", sep=\"\\t\")\n", + "data = np.matrix(alldata)\n", + "\n", + "m, n_plus_1 = data.shape\n", + "Xn = data[:, 1:]\n", + "\n", + "n = 10\n", + "Xpl = powerme(data[:, 1], data[:, 2], n)\n", + "Ypl = np.matrix(data[:, 0]).reshape(m, 1)\n", + "\n", + "theta_start = np.matrix(np.zeros(Xpl.shape[1])).reshape(Xpl.shape[1], 1)\n", + "theta, errors = GD(\n", + " h, J, dJ, theta_start, Xpl, Ypl, alpha=0.1, eps=10**-7, maxSteps=10000\n", + ")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/tmp/ipykernel_539/3318422759.py:10: UserWarning: The following kwargs were not used by contour: 'lw'\n", + " plt.contour(xx, yy, z, levels=[0.5], lw=3);\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Przykład dla większej liczby cech\n", + "fig = plot_data_for_classification(Xpl, Ypl, xlabel=r\"$x_1$\", ylabel=r\"$x_2$\")\n", + "plot_decision_boundary(fig, theta, Xpl)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "## 6.2. Problem nadmiernego dopasowania" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "### Obciążenie a wariancja" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "slideshow": { + "slide_type": "notes" + } + }, + "outputs": [], + "source": [ + "# Dane do prostego przykładu\n", + "\n", + "data = np.matrix(\n", + " [\n", + " [0.0, 0.0],\n", + " [0.5, 1.8],\n", + " [1.0, 4.8],\n", + " [1.6, 7.2],\n", + " [2.6, 8.8],\n", + " [3.0, 9.0],\n", + " ]\n", + ")\n", + "\n", + "m, n_plus_1 = data.shape\n", + "n = n_plus_1 - 1\n", + "Xn1 = data[:, 0:n]\n", + "Xn1 /= np.amax(Xn1, axis=0)\n", + "Xn2 = np.power(Xn1, 2)\n", + "Xn2 /= np.amax(Xn2, axis=0)\n", + "Xn3 = np.power(Xn1, 3)\n", + "Xn3 /= np.amax(Xn3, axis=0)\n", + "Xn4 = np.power(Xn1, 4)\n", + "Xn4 /= np.amax(Xn4, axis=0)\n", + "Xn5 = np.power(Xn1, 5)\n", + "Xn5 /= np.amax(Xn5, axis=0)\n", + "\n", + "X1 = np.matrix(np.concatenate((np.ones((m, 1)), Xn1), axis=1)).reshape(m, n + 1)\n", + "X2 = np.matrix(np.concatenate((np.ones((m, 1)), Xn1, Xn2), axis=1)).reshape(\n", + " m, 2 * n + 1\n", + ")\n", + "X5 = np.matrix(\n", + " np.concatenate((np.ones((m, 1)), Xn1, Xn2, Xn3, Xn4, Xn5), axis=1)\n", + ").reshape(m, 5 * n + 1)\n", + "y = np.matrix(data[:, -1]).reshape(m, 1)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plot_data(X1, y, xlabel=\"x\", ylabel=\"y\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": { + "scrolled": true, + "slideshow": { + "slide_type": "subslide" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plot_data(X1, y, xlabel=\"x\", ylabel=\"y\")\n", + "theta_start = np.matrix([0, 0]).reshape(2, 1)\n", + "theta, _ = gradient_descent(cost, gradient, theta_start, X1, y, eps=0.00001)\n", + "plot_fun(fig, polynomial_regression(theta), X1)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "Ten model ma duże **obciążenie** (**błąd systematyczny**, *bias*) – zachodzi **niedostateczne dopasowanie** (*underfitting*)." + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plot_data(X2, y, xlabel=\"x\", ylabel=\"y\")\n", + "theta_start = np.matrix([0, 0, 0]).reshape(3, 1)\n", + "theta, _ = gradient_descent(cost, gradient, theta_start, X2, y, eps=0.000001)\n", + "plot_fun(fig, polynomial_regression(theta), X1)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "Ten model jest odpowiednio dopasowany." + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plot_data(X5, y, xlabel=\"x\", ylabel=\"y\")\n", + "theta_start = np.matrix([0, 0, 0, 0, 0, 0]).reshape(6, 1)\n", + "theta, _ = gradient_descent(cost, gradient, theta_start, X5, y, alpha=0.5, eps=10**-7)\n", + "plot_fun(fig, polynomial_regression(theta), X1)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "Ten model ma dużą **wariancję** (*variance*) – zachodzi **nadmierne dopasowanie** (*overfitting*)." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "notes" + } + }, + "source": [ + "(Zwróć uwagę na dziwny kształt krzywej w lewej części wykresu – to m.in. efekt nadmiernego dopasowania)." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "notes" + } + }, + "source": [ + "Nadmierne dopasowanie występuje, gdy model ma zbyt dużo stopni swobody w stosunku do ilości danych wejściowych.\n", + "\n", + "Jest to zjawisko niepożądane.\n", + "\n", + "Możemy obrazowo powiedzieć, że nadmierne dopasowanie występuje, gdy model zaczyna modelować szum/zakłócenia w danych zamiast ich „głównego nurtu”. " + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "notes" + } + }, + "source": [ + "Zobacz też: https://pl.wikipedia.org/wiki/Nadmierne_dopasowanie" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "### Obciążenie (błąd systematyczny, *bias*)\n", + "\n", + "* Wynika z błędnych założeń co do algorytmu uczącego się.\n", + "* Duże obciążenie powoduje niedostateczne dopasowanie." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "### Wariancja (*variance*)\n", + "\n", + "* Wynika z nadwrażliwości na niewielkie fluktuacje w zbiorze uczącym.\n", + "* Wysoka wariancja może spowodować nadmierne dopasowanie (modelując szum zamiast sygnału)." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "## 6.3. Regularyzacja" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": { + "slideshow": { + "slide_type": "notes" + } + }, + "outputs": [], + "source": [ + "def SGD(\n", + " h,\n", + " fJ,\n", + " fdJ,\n", + " theta,\n", + " X,\n", + " Y,\n", + " alpha=0.001,\n", + " maxEpochs=1.0,\n", + " batchSize=100,\n", + " adaGrad=False,\n", + " logError=False,\n", + " validate=0.0,\n", + " valStep=100,\n", + " lamb=0,\n", + " trainsetsize=1.0,\n", + "):\n", + " \"\"\"Stochastic Gradient Descent - stochastyczna wersja metody gradientu prostego\n", + " (więcej na ten temat na następnym wykładzie)\n", + " \"\"\"\n", + " errorsX, errorsY = [], []\n", + " errorsVX, errorsVY = [], []\n", + "\n", + " XT, YT = X, Y\n", + "\n", + " m_end = int(trainsetsize * len(X))\n", + "\n", + " if validate > 0:\n", + " mv = int(X.shape[0] * validate)\n", + " XV, YV = X[:mv], Y[:mv]\n", + " XT, YT = X[mv:m_end], Y[mv:m_end]\n", + " m, n = XT.shape\n", + "\n", + " start, end = 0, batchSize\n", + " maxSteps = (m * float(maxEpochs)) / batchSize\n", + "\n", + " if adaGrad:\n", + " hgrad = np.matrix(np.zeros(n)).reshape(n, 1)\n", + "\n", + " for i in range(int(maxSteps)):\n", + " XBatch, YBatch = XT[start:end, :], YT[start:end, :]\n", + "\n", + " grad = fdJ(h, theta, XBatch, YBatch, lamb=lamb)\n", + " if adaGrad:\n", + " hgrad += np.multiply(grad, grad)\n", + " Gt = 1.0 / (10**-7 + np.sqrt(hgrad))\n", + " theta = theta - np.multiply(alpha * Gt, grad)\n", + " else:\n", + " theta = theta - alpha * grad\n", + "\n", + " if logError:\n", + " errorsX.append(float(i * batchSize) / m)\n", + " errorsY.append(fJ(h, theta, XBatch, YBatch).item())\n", + " if validate > 0 and i % valStep == 0:\n", + " errorsVX.append(float(i * batchSize) / m)\n", + " errorsVY.append(fJ(h, theta, XV, YV).item())\n", + "\n", + " if start + batchSize < m:\n", + " start += batchSize\n", + " else:\n", + " start = 0\n", + " end = min(start + batchSize, m)\n", + " return theta, (errorsX, errorsY, errorsVX, errorsVY)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": { + "slideshow": { + "slide_type": "notes" + } + }, + "outputs": [], + "source": [ + "# Przygotowanie danych do przykładu regularyzacji\n", + "\n", + "n = 6\n", + "\n", + "data = np.matrix(np.loadtxt(\"ex2data2.txt\", delimiter=\",\"))\n", + "np.random.shuffle(data)\n", + "\n", + "X = powerme(data[:, 0], data[:, 1], n)\n", + "Y = data[:, 2]\n" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": { + "slideshow": { + "slide_type": "notes" + } + }, + "outputs": [], + "source": [ + "def draw_regularization_example(\n", + " X, Y, lamb=0, alpha=1, adaGrad=True, maxEpochs=2500, validate=0.25\n", + "):\n", + " \"\"\"Rusuje przykład regularyzacji\"\"\"\n", + " plt.figure(figsize=(16, 8))\n", + " plt.subplot(121)\n", + " plt.scatter(\n", + " X[:, 2].tolist(),\n", + " X[:, 1].tolist(),\n", + " c=Y.tolist(),\n", + " s=100,\n", + " cmap=plt.cm.get_cmap(\"prism\"),\n", + " )\n", + "\n", + " theta = np.matrix(np.zeros(X.shape[1])).reshape(X.shape[1], 1)\n", + " thetaBest, err = SGD(\n", + " h,\n", + " J,\n", + " dJ,\n", + " theta,\n", + " X,\n", + " Y,\n", + " alpha=alpha,\n", + " adaGrad=adaGrad,\n", + " maxEpochs=maxEpochs,\n", + " batchSize=100,\n", + " logError=True,\n", + " validate=validate,\n", + " valStep=1,\n", + " lamb=lamb,\n", + " )\n", + "\n", + " xx, yy = np.meshgrid(np.arange(-1.5, 1.5, 0.02), np.arange(-1.5, 1.5, 0.02))\n", + " l = len(xx.ravel())\n", + " C = powerme(xx.reshape(l, 1), yy.reshape(l, 1), n)\n", + " z = classifyBi(thetaBest, C).reshape(int(np.sqrt(l)), int(np.sqrt(l)))\n", + "\n", + " plt.contour(xx, yy, z, levels=[0.5], lw=3)\n", + " plt.ylim(-1, 1.2)\n", + " plt.xlim(-1, 1.2)\n", + " plt.legend()\n", + " plt.subplot(122)\n", + " plt.plot(err[0], err[1], lw=3, label=\"Training error\")\n", + " if validate > 0:\n", + " plt.plot(err[2], err[3], lw=3, label=\"Validation error\")\n", + " plt.legend()\n", + " plt.ylim(0.2, 0.8)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": { + "scrolled": true, + "slideshow": { + "slide_type": "subslide" + } + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/tmp/ipykernel_539/1806277680.py:5: RuntimeWarning: overflow encountered in exp\n", + " y = 1.0/(1.0 + np.exp(-x))\n", + "/tmp/ipykernel_539/3540778240.py:19: UserWarning: The following kwargs were not used by contour: 'lw'\n", + " plt.contour(xx, yy, z, levels=[0.5], lw=3);\n", + "No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "draw_regularization_example(X, Y)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "### Regularyzacja\n", + "\n", + "Regularyzacja jest metodą zapobiegania zjawisku nadmiernego dopasowania (*overfitting*) poprzez odpowiednie zmodyfikowanie funkcji kosztu.\n", + "\n", + "Do funkcji kosztu dodawane jest specjalne wyrażenie (**wyrażenie regularyzacyjne** – zaznaczone na czerwono w poniższych wzorach), będące „karą” za ekstremalne wartości parametrów $\\theta$.\n", + "\n", + "W ten sposób preferowane są wektory $\\theta$ z mniejszymi wartosciami parametrów – mają automatycznie niższy koszt.\n", + "\n", + "Jak silną regularyzację chcemy zastosować? Możemy o tym zadecydować, dobierajac odpowiednio **parametr regularyzacji** $\\lambda$." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "notes" + } + }, + "source": [ + "Przedstawiona tu metoda regularyzacji to tzw. metoda L2 (*ridge*). Istnieją również inne metody regularyzacji, które charakteryzują się trochę innymi własnościami, np. L2 (*lasso*) lub *elastic net*. Więcej na ten temat można przeczytać np. tu:\n", + "* [L1 and L2 Regularization Methods](https://towardsdatascience.com/l1-and-l2-regularization-methods-ce25e7fc831c)\n", + "* [Ridge and Lasso Regression: L1 and L2 Regularization](https://towardsdatascience.com/ridge-and-lasso-regression-a-complete-guide-with-python-scikit-learn-e20e34bcbf0b)\n", + "* [Elastic Net Regression](https://towardsdatascience.com/elastic-net-regression-from-sklearn-to-tensorflow-3b48eee45e91)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "### Regularyzacja dla regresji liniowej – funkcja kosztu\n", + "\n", + "$$\n", + "J(\\theta) \\, = \\, \\dfrac{1}{2m} \\left( \\displaystyle\\sum_{i=1}^{m} h_\\theta(x^{(i)}) - y^{(i)} \\color{red}{ + \\lambda \\displaystyle\\sum_{j=1}^{n} \\theta^2_j } \\right)\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "* $\\lambda$ – parametr regularyzacji\n", + "* jeżeli $\\lambda$ jest zbyt mały, skutkuje to nadmiernym dopasowaniem\n", + "* jeżeli $\\lambda$ jest zbyt duży, skutkuje to niedostatecznym dopasowaniem" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "### Regularyzacja dla regresji liniowej – gradient\n", + "\n", + "$$\\small\n", + "\\begin{array}{llll}\n", + "\\dfrac{\\partial J(\\theta)}{\\partial \\theta_0} &=& \\dfrac{1}{m}\\displaystyle\\sum_{i=1}^m \\left( h_{\\theta}(x^{(i)})-y^{(i)} \\right) x^{(i)}_0 & \\textrm{dla $j = 0$ }\\\\\n", + "\\dfrac{\\partial J(\\theta)}{\\partial \\theta_j} &=& \\dfrac{1}{m}\\displaystyle\\sum_{i=1}^m \\left( h_{\\theta}(x^{(i)})-y^{(i)} \\right) x^{(i)}_j \\color{red}{+ \\dfrac{\\lambda}{m}\\theta_j} & \\textrm{dla $j = 1, 2, \\ldots, n $} \\\\\n", + "\\end{array} \n", + "$$" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "### Regularyzacja dla regresji logistycznej – funkcja kosztu\n", + "\n", + "$$\n", + "\\begin{array}{rtl}\n", + "J(\\theta) & = & -\\dfrac{1}{m} \\left( \\displaystyle\\sum_{i=1}^{m} y^{(i)} \\log h_\\theta(x^{(i)}) + \\left( 1-y^{(i)} \\right) \\log \\left( 1-h_\\theta(x^{(i)}) \\right) \\right) \\\\\n", + "& & \\color{red}{ + \\dfrac{\\lambda}{2m} \\displaystyle\\sum_{j=1}^{n} \\theta^2_j } \\\\\n", + "\\end{array}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "### Regularyzacja dla regresji logistycznej – gradient\n", + "\n", + "$$\\small\n", + "\\begin{array}{llll}\n", + "\\dfrac{\\partial J(\\theta)}{\\partial \\theta_0} &=& \\dfrac{1}{m}\\displaystyle\\sum_{i=1}^m \\left( h_{\\theta}(x^{(i)})-y^{(i)} \\right) x^{(i)}_0 & \\textrm{dla $j = 0$ }\\\\\n", + "\\dfrac{\\partial J(\\theta)}{\\partial \\theta_j} &=& \\dfrac{1}{m}\\displaystyle\\sum_{i=1}^m \\left( h_{\\theta}(x^{(i)})-y^{(i)} \\right) x^{(i)}_j \\color{red}{+ \\dfrac{\\lambda}{m}\\theta_j} & \\textrm{dla $j = 1, 2, \\ldots, n $} \\\\\n", + "\\end{array} \n", + "$$" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "### Implementacja metody regularyzacji" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "outputs": [], + "source": [ + "def J_(h, theta, X, y, lamb=0):\n", + " \"\"\"Funkcja kosztu z regularyzacją\"\"\"\n", + " m = float(len(y))\n", + " f = h(theta, X, eps=10**-7)\n", + " j = 1.0 / m * -np.sum(\n", + " np.multiply(y, np.log(f)) + np.multiply(1 - y, np.log(1 - f)), axis=0\n", + " ) + lamb / (2 * m) * np.sum(np.power(theta[1:], 2))\n", + " return j\n", + "\n", + "\n", + "def dJ_(h, theta, X, y, lamb=0):\n", + " \"\"\"Gradient funkcji kosztu z regularyzacją\"\"\"\n", + " m = float(y.shape[0])\n", + " g = 1.0 / y.shape[0] * (X.T * (h(theta, X) - y))\n", + " g[1:] += lamb / m * theta[1:]\n", + " return g\n" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": { + "slideshow": { + "slide_type": "notes" + } + }, + "outputs": [], + "source": [ + "slider_lambda = widgets.FloatSlider(\n", + " min=0.0, max=0.5, step=0.005, value=0.01, description=r\"$\\lambda$\", width=300\n", + ")\n", + "\n", + "\n", + "def slide_regularization_example_2(lamb):\n", + " draw_regularization_example(X, Y, lamb=lamb)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": { + "scrolled": false, + "slideshow": { + "slide_type": "subslide" + } + }, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "77f5c3dccbd04409b7873f54bfc535eb", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "interactive(children=(FloatSlider(value=0.01, description='$\\\\lambda$', max=0.5, step=0.005), Button(descripti…" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "widgets.interact_manual(slide_regularization_example_2, lamb=slider_lambda)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": { + "slideshow": { + "slide_type": "notes" + } + }, + "outputs": [], + "source": [ + "def cost_lambda_fun(lamb):\n", + " \"\"\"Koszt w zależności od parametru regularyzacji lambda\"\"\"\n", + " theta = np.matrix(np.zeros(X.shape[1])).reshape(X.shape[1], 1)\n", + " thetaBest, err = SGD(\n", + " h,\n", + " J,\n", + " dJ,\n", + " theta,\n", + " X,\n", + " Y,\n", + " alpha=1,\n", + " adaGrad=True,\n", + " maxEpochs=2500,\n", + " batchSize=100,\n", + " logError=True,\n", + " validate=0.25,\n", + " valStep=1,\n", + " lamb=lamb,\n", + " )\n", + " return err[1][-1], err[3][-1]\n", + "\n", + "\n", + "def plot_cost_lambda():\n", + " \"\"\"Wykres kosztu w zależności od parametru regularyzacji lambda\"\"\"\n", + " plt.figure(figsize=(16, 8))\n", + " ax = plt.subplot(111)\n", + " Lambda = np.arange(0.0, 1.0, 0.01)\n", + " Costs = [cost_lambda_fun(lamb) for lamb in Lambda]\n", + " CostTrain = [cost[0] for cost in Costs]\n", + " CostCV = [cost[1] for cost in Costs]\n", + " plt.plot(Lambda, CostTrain, lw=3, label=\"training error\")\n", + " plt.plot(Lambda, CostCV, lw=3, label=\"validation error\")\n", + " ax.set_xlabel(r\"$\\lambda$\")\n", + " ax.set_ylabel(\"cost\")\n", + " plt.legend()\n", + " plt.ylim(0.2, 0.8)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_cost_lambda()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "## 5.4. Krzywa uczenia się" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "* Krzywa uczenia pozwala sprawdzić, czy uczenie przebiega poprawnie.\n", + "* Krzywa uczenia to wykres zależności między wielkością zbioru treningowego a wartością funkcji kosztu.\n", + "* Wraz ze wzrostem wielkości zbioru treningowego wartość funkcji kosztu na zbiorze treningowym rośnie.\n", + "* Wraz ze wzrostem wielkości zbioru treningowego wartość funkcji kosztu na zbiorze walidacyjnym maleje." + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": { + "slideshow": { + "slide_type": "notes" + } + }, + "outputs": [], + "source": [ + "def cost_trainsetsize_fun(m):\n", + " \"\"\"Koszt w zależności od wielkości zbioru uczącego\"\"\"\n", + " theta = np.matrix(np.zeros(X.shape[1])).reshape(X.shape[1], 1)\n", + " thetaBest, err = SGD(\n", + " h,\n", + " J,\n", + " dJ,\n", + " theta,\n", + " X,\n", + " Y,\n", + " alpha=1,\n", + " adaGrad=True,\n", + " maxEpochs=2500,\n", + " batchSize=100,\n", + " logError=True,\n", + " validate=0.25,\n", + " valStep=1,\n", + " lamb=0.01,\n", + " trainsetsize=m,\n", + " )\n", + " return err[1][-1], err[3][-1]\n", + "\n", + "\n", + "def plot_learning_curve():\n", + " \"\"\"Wykres krzywej uczenia się\"\"\"\n", + " plt.figure(figsize=(16, 8))\n", + " ax = plt.subplot(111)\n", + " M = np.arange(0.3, 1.0, 0.05)\n", + " Costs = [cost_trainsetsize_fun(m) for m in M]\n", + " CostTrain = [cost[0] for cost in Costs]\n", + " CostCV = [cost[1] for cost in Costs]\n", + " plt.plot(M, CostTrain, lw=3, label=\"training error\")\n", + " plt.plot(M, CostCV, lw=3, label=\"validation error\")\n", + " ax.set_xlabel(\"trainset size\")\n", + " ax.set_ylabel(\"cost\")\n", + " plt.legend()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "### Krzywa uczenia a obciążenie i wariancja\n", + "\n", + "Wykreślenie krzywej uczenia pomaga diagnozować nadmierne i niedostateczne dopasowanie:\n", + "\n", + "\n", + "\n", + "Źródło: http://www.ritchieng.com/machinelearning-learning-curve" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_learning_curve()\n" + ] + } + ], + "metadata": { + "celltoolbar": "Slideshow", + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.6" + }, + "livereveal": { + "start_slideshow_at": "selected", + "theme": "white" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/wyk/bias2.png b/wyk/bias2.png new file mode 100644 index 0000000000000000000000000000000000000000..abe9a1161114a2029775866f9d184d85e757726b GIT binary patch literal 125272 zcmc$_cT`i`(>IO{6-5myNWT&~0zyJ>(gF!hLX&>!1PDk8z1*wxPN<Kp_-2 zZctF%xV|W^CMgstZr=Ep{%vpmOSfR-CPd-#Cr;lB_6zU04IZ{E3e>kidj%DewHa81W6gL4kZUJsw zwNtSC3-#vBTmJ(7zv$lG`*$dB-ln?sZ@=3U3X1DFZ{4_tdguNf03{v8jhnY_-=VyF z?>>O$=}RH1XKeD%fx_Arf77yq6kO>P;g$(6=sCbTZXa@pR_?i#1O`qn9uWy8Wv`Fu z#MHd%FC(IoD!O_GcBtek61Nyc-`d8bW>oy0XGl^?{_OATIq9##{NDjxtDn-ZUSz-yiFq{uWjM_^zVe6N;csy-+$kE26UTc2Z0sfmQ_2? zzbbw}Uy&&u-n!-n+yYR@QT+V%FYo`qbeChb`~O`8te+?z(Vj&3YF4fNcI|M>(x@{p zP*r|}Gbof0W;YC-NEB%L%8bwgC-0|csKum*M@Jw)3xtWL&aK9IryVzPag$vA(lOBm z3{!qIkNY7K?#!m-W$g7bfMeDDuuB4Al-s)lX;G0vJ}5T@a;R2&_LOh*F&lGBG~b z$_q}#8}Ko_@6wk#;QIBQbKtY%b9y4z3j@V+HYt?na0=LN>xbY+SuN5QbCWVqP2c03DcxNx7O{8Q^bbXUcs=MvP0#~u+GRwPunQkC z8(SeEe)P(*gqh?RpJlAG>SUn9zY+_~F3485bg!zq{BUd_E52ZTA?^r-8MS^=tp_(2 zMaiB=JkBr7sy4ILi65z8Pt8zhm;jy73?~9u9YBmfDd~ca9&=?(7N5NAHPN?S~bLt-2EL7Ed89C5$8SU~4mj0ofG%M&Sps zcRYf?h7W66yjmO!EjuLoX*S_EN3eNK32 z3d?T$###xYB$;h7Sf{0x61E$L1u>UceWTKGZOLrhx;OH}diMk@G80b#;!SyHrFZ>V zZxzfn2idDg&Fr|AQ;!X@H*HCDyT0E%(*X{zfvhvcbl!% z!4~Kftoa>dOF==a`ac$uTkXfI^Vm1P^A@`1h56j(BweZ!`ubM$ZF(WMw%f&hn&U;t737HyfV)I!$megYQTp zM*>=V*tWC+&)|(&O^fs2JotL*>s}%rTQ}4o=Azofm+epQdjreWbNb@jP_+-`Imn$tpp=+@P3WG3-A2z;!tr{+6tE3KM?0I+xiTu~(Kz z$1%&4=RBi7wOE&CaHquBGLKTerdpxrahK7gAr1=H`Y21ysj?6}+FUbDx3$vnupHs{ zVxdmIBcPWcS;ndHZkn5BCOS_zhMNpaNl6~D8%Zi1&VOmjJO4LH2D@2YwKUxDrgWBR zK9Sq&d5^mpnvaxGLwmaV?cRJPb4|MIA=$VXtO6UUMzZLAQ?mYPl&7|NrirYK_SrvQ z{$*@mE;eM&F+;(WI>YXr%IRNpad&@!XCB)fr1oL|g`laVOw&P59MDS5?;X7y;2&7F z9$fQP5#*yNZUnvgvPbjv{D5c(SE3rPOIJWi7;Jb&aV^|@ zE2Pz>46XfxUY{Z5gi{s9Rg{vTK`*PhAHkfox_YkS3KUH3_pkGNO^fV`6I(0(A(mx| zqUv}QgL+e}<=SSH-(wR{YbrvIDHF@xBtk%`t=L~F59faTv521z1+K^`0Ds`W4UupZS%!&ZB5@5#fD*c z&{pQrnZ!lQY@Sj(pNvg#4@6-7{8>%|{MF(2u2sQvx;TMy#jZ=YRs zTv4pvQF40Gd^e{nD7v*IPVuZYZuDH3O)j|guVFi)MFXv6Rf&GeD8t+Og5fQv&~_gK zB0TxkkASz0 z+3Sy5Z1=+^W7|{_No8Fo#)CD%Irl~Ai^9YGn_cXJR67GnrtTbOBxBp>^$8or5zQ~H zQ^-*)Sg2PrgO4zjLmC?!pz<8SaIT-7+35&s%@(R15=fu%*e8krx0P(A3p-jb9&EII z8lYQ6r~WmEXy~plY*bP*9$Ts_dsl5UZivgjPN5kkm4Qt){MCVZa7&@&dXu@kaoGci6i zFVy;rl9Kb2LIArEmA#ima>z%Cn#nZ*F$RG`yz0_JcZ6p4dhdHQV6_7Scn;3OAuYJo z5{Ak#PT8k5uiukVBl)YEJ3^q=0{7&O{QlO0=B2~M>fM>Q?fM6OPCt|2rd{^qh*b>3 zbB&O)2=xT%Y#&=i=R_9(O&z;x>l{JYirK592AMU1nhpuGXT0y4JN?TT-{t**O3Ys^vTr0t}e)FBB3^>!p*h zi6D*(H?v(O<=y!tOy-x({FP*pC@#jWTL}0wx1uV|;U*S~WQJH^XZ;gq!_?rHwUKH8 zDr%U=nYM$A4sN|#*>>?~hNF4~@@&6!)89#}YB2ri@Kq(ClVx=` znWr7fCYLy}E2v#-q`{jdUjWI4ThubVf;?%r-^jyJi=x?aJZ$@H*K~dxF-A5UCcVhe z5^QL;`zhs@OkBr5D|G=d&77>V-oqTVO;g;U{*RjKe;aV4xWb9+l3;gOuzuktg3Y^eaEfyt6ds?9zl}llJ{)MocCmGqrOV%M-(6TT8$hN>CB{ zgijX|j5jWqI@bFIVnS=_e6T}EfjpO7}HDL-xTr3*`VNeANjN0;&&ZScUj zqw*^X9sVQ92<=mE(0oqd1FTfeA@Yi1o%`3&WzwkJBq+pNwQFP3^onALRZY^n#LfUB z%_nM+qCO}=wp-MJA zk9r7O%e0#7r^uo;W0tv7T%ksYw|Y*kW~n;jXleu8);up7g_BV_4P?>!2;8+aIxHca zeZ-Q195zXF#;B5P>hJRS>i3l@HuYiry}_!yJ}w;Wwa;8LbvPYB$KHa|0+L6Sgji2p zS;-Ye?uGHCvgV85-x-odGEn7mj|Wl#&T5Dbzribt`{xeq?d9PDNV#A{QCCODzY(Fl$fp$D{iw*@j~l|1mQP2PV%WU=b~u@%8{ zyxu%h0$)Lnr1W65zr^v(ds_H&{r=P#Yzu|cR0JypPKMfbKReaG`_F3!w|6xTabqRP z;=yDnKGEtd4>00z07B4Md;c~sbzkmcM373o-z;xpjc>s9Sr90D#2l0!NUA(*4)81ySO z7K}(=ZisvnZxU~a1dWAOrdA_!yA-pMJ?gPvq((bEy|{A)S~ibW-TRitsV6D9j4iQH zL)OrHm)W#k4X;yLV#dLPd5pdn;mig?qDPc}@7fIA`KQ^^Ty0HDW2m1tj1*nV)8eVg&;Y$nj(+Sf)@`}4&(_3{1+yly_ZL#?yWR3(v3C)_bn zD;92@H>NpZ1nywi{<-|}&sU2Ar6ux{Et^H-D7|3kJ_k(xT;Qb=fk#!F@5?TX?UU-I;!-h7dlXOtYR;j3=9=Z+xTj+Gvi&M!V?HQ1-1 z)cEUvQ-%L$f3VI#nF19`Tc^P&XWp$}A5X5Crk|QeRSt(qIS+3luzOq(Ti}1XOl8vN!m#{VxeLu`m(3&pUw?h86xUd(l;y>Df2|0_8RBI*hPQd+VnzlCG0AZotI7n3D}Z?ClbS#Elg$ZqwJ?@XufC1gGY@qZiqgZ_av*X10YgFAt1r>pZsPH zv^ICTtE(YWO+_29kHNT^M5pC*SlesU-Ca}UgD1c`MAHY|$3ZfI??RJC($|c}qT4%# z7EhKvOGO|5B&jvvhD|Gii4s|xlOX;Ha1Hl?_)!R==w2PhhWVjpEoDtDKhsAeKWX=vO@Npl_hCN4 zkDN}f^y~7UleCphm^PJO(RVDI4aaOUOZqy^?aSaEJXZA8ss!i6KA$Qu^q`&fo2b$# zcKQf%QzGU!(aZ!mH{_m833WOP=BGbuAVAR`WhThj#)gSN8U7RQH6^1+abKp7f=3ek zRm-QhMCm>(oX4%EvRm7%@wB_U0-O;uekaF;kbvkh$H~X3E;e0ChAwdOn)<{3QPU<= zA>ZF;#mGDzXp*hKQG^hXX2SeOd}62zL){{mmV#DnPF)2;QR%^0&FE1H?dBgiQ}OkJ zotlW-c}B4edfP~LG{jM)%>)gT^ZDwywNUy>s$hezus38<@9Xg(#<{1ZJZy`veuX++ zPp4Q`NwfET|InNP)LY;|wpOgJ{}D6+s1;r34$K+Lme1)-F~K2(e|7gQLF6k2%JPgl zNdVT%n#}VS!2MwY!g1gz4YPXr^Kqcv-1obcsrea^waP81Rdl{a+O(wL$|DIq`6F6w zHZL8?PwF&r!2}lxrbN=O6gTf*W6M%YS|8^>GP7#=qQ0E!bUeET>5tSRlu0UJ^<=}; z6e3b|_xgO=1oA*2omhUA9&E+*KihY{_$+5rk{hyzt-gw$UxFH$CEe^~mh5&IO5*nmO%{oRHche~5Vqnb$k}j!~6;u^;XetQq0Nm{_@XFwAW6+p5C+ zRN0Rt`@i?KkCBOy;}s%y(@&quai^S1cer4FWAh}=7U(FRz6m3P6XKFP!-u6cm7`3&0S;SwU66(qap78tD%b9W`NrpmFi8^?mNjxb zfu_fF6dlom7IEP`=#DQ{w}SU3BK<=1STHJXxr;1eioP})`#CMuHfcye!`_ne7cg3c zp$Xt7!@@h7v8S{ddGYc~j;3n*Q1noz`!T_8^UDDv6i|TV$@#u_4B0klEL#{QcixA_?q~% zA~yIjJc)RIpFN>?=+K{7nc;Df*B|f+sfVn^tBE!{k22$iw`xD*Om(5^>P6yvE~@?$ zz_3XPN=8)%~= zc&Sq>HyIBRI23(+nau1IM>;Vt3F^krw~m zMmfIabXtsY?e=#X!EK}+6g52lh~YWi!r?T~da)NN(IrKu%(D>f z$p!!5;V1P|lCSGTp||d3?w6{q!s+If?a{Yw6}?F*K+=NfaDVf{qzKGu z_@hXE{s9g3?YYT>S1|_xg|C2?@J+r9#nH$N@Cx|S$2u4zjuuupaU#}E%+@=y+BWC; z{A4^i?61t6G*0&&Y6A>2Bpn98Z8in0KVEBx8iVok$}js?MV40-pF~!Bt|*T1Z?7m4 z#bxad<3HBvM~RsQnVuXuP(#&oOokoJwYq9QZ(8&`yQ0X~FQi`jwqX6VJp=q06 zWNia7*{-*WQ+%U978DtPw=ohU7Nxr%z-XzpV;ffl?668j*w zTsCFZU0bJ6NJePJ9&01;6wUw^k5$WlmbjZtC#!n#5arOX!4vn;f3Z(BeeI{rve0UH zT*)NGjl}o=V-5WOC4;zNUC`s$hsUhnZtN8{9IlM4yO3q7kO3ZV9qc}QX6^vIN9tQ- zhQ=E24+j*lC!7d+8@sW;UUeO@?zd!TAHkuITt0a5PM+zAPWk2Cb!25WNb?D9C>k(z z#iV@Uu4nV*>r>m{J1u|7D_G}BUL}t!OvZgn!>vu;APLZaHWbAh03S&_D!IXg*%#se zsFu}|C*qmpVBdcNe(@KtSx4+d)mm(Sp~Ee)_UQT0{B{k`_?8L!z2W5IjG;R#Cc8mC zX$8>(V4&vrVLR{b>}py3Xn0Mbj2(S=w6FK8W;Yj&8qY}AP5rzy6pzEybI)19>Cy-A zq7MBs`1@hoP%03wfqjb2u%;}MU~*#k(0yZb^%fT*PF2iIr7sN^b+aP9%0}}%CiY$2 z#KqG>HBJ&udco;iRXBrF^7n5akpdi43eP@5J(;P_WX{Yt4?N!Vyvuu_T2}!xWdAke zwW+o$QJE__gQtAagK)bb#s0CsHdho_9bBo74y+i z+J)_iukbPQ0%^iWXpzq7*zk8)(g*fL{46Inwb%BOm|$1>6-A+ao~~4^os`9Ew_r8> z!(!#W=YfBANvy=4*ThWRhC#tN$q?>3xCU1jB~VSW;X97mt}uJG*)m-RPnJB9?b3x* zu=~fojPk(Z8g*2E{Iio>nCSML9A@h`RXhW0u^nF%Y(k1oV141EWN0EnmZTIK0m)+r z6rFS@r|XFHsuxR#Er6%G*Dbm%dyNG?r6fYrndH$K+U~PZVPQFT|ByX^_%v(?4Ds}9 zdAzs~^dMFm;iu@Nt?@UfKo>>tWc}M0Dhua@hFG$1Ez0_=S3_TM8^@{g1G$I? zFdWB)eqa8eWi+LYVp?r?u=i7+1BLIUUB?iH>hb3??+Oju)lZZA?2LH@G``X+%ruqN_qo0%v7v6TJ{>Tx}f`c3FQ2;JMbK{PWW8><|Y0yBkeXy)n#9EX*C-95izO(kzIc>;3^ zG6QN-)?xs|#L`KXWc0o0gt3x(cG1x?M<;!E#sINnHOVC_(2Mnhpf?nH|8vcFcZaLT z_h#IO{e@?_P&ez>%zF*`lj4Ir#a0_J75?(_71~@k5?4CS?brPH}lel24y)3n^a~B zUE|VJi&V8*wgI%2(3A*(oigfnO*UeL9@ox8#X%F^9~~VXoF_Hg$Dlft`0|2TQFz&j zzfg*PBMV#A+-NhIumEm5STCsRe-YC#*I+E)u!}~+Ir?qu7agJpE_DlG68MwVD zd3}~N(P3%n4ww*6Tg&T@F`++xY)&b83F=Y0^$*XYIFx(nPk_vS^(7wc)23aoHa$zr?`bQSe^I=mpm_XrH&#_TzlkmZ|j5sL@phO!T;-Md^}F(pbzKCUc?QQ>p1NuV}I=aj;?0ABdx!X!KtTr}6}%<0&| z^>mTDcB0d7f6t~BzWatLwc-zsKd!Zzo4NOY=`=T$l|TRM=Kr|4u|g4;{l=SbPS*R{ zEDESHy~*-wBm`GSod{9WjgA6<`RY53ekB-%kFRZ&nVjhCJb|*YT~U0dwGDc53Sm#+ z`Vv&Ce%7>NnNgSWQ{u6D_SVGMGCbgND1I60$p=u!Mh3uuE3mQH-Vx;?#PYpn2*VyY ze5Ar?FkpJ}{hlFV*w+|&=B?H7&GY7XUqZxjcuO2WBnq zPuIaFnb$4HM3b#eC&M;~mE@3oFnWLYN#8@!LKf8MK8}#!<^YmYU<1mk^mA1ilpAFy z9^EUopXAc=#LD++$7WAK^X-qMLg`#xBb4&koTgNoy1+Xlwa>l;u1szdO3D~ol0?5% z{P5m%Gi`BaYJYc_Bz_ORP%_iqYcvUy1qw%N)+B17QHOy$q>lc6NI|BpOSDo@u^n^M zrKU4Wf+=*kWvV$qI^YNPBgF>tX5b=Yt^?4Qj~HfS{GPY?^Y5-^nwW=Q5%;)Q5dw6t zDy9>eh6=m%6tsQ!27hI`@{2mxm801fA$BWV10@7gmC3y~$CGM8K;iU|n}3A~7*f9) zfjjIzT+r}H3e?R$i>2||SAd%ZD>gaGJvH}PR-I71XSp6ytkL83?zykX&BB+9HB*Le z7Lt7eJod1pVDwnFE*ivky?yrmZ5lMIlc)*mc@Za#!b%U?NV0a0EEDFl-B%fvd@TXE z#ZAUP{pPi+!Fjczm?{CBAeFXcacSe7P@uLIM=kXu?&WT6Kn^b(TTtHgn6s!xQ?=ov zJmeXi{QfiQkC<2MlTaTu3X@n3B`*%sofip|Z2EaH)_``NN6%37{(?1=G4%eXrc6b3 zSldEJW)-AhWcBm;vSV6Y1=~uNhHIEnMdeHFS$SvevQ?TV0R`!x#9p-u^s07I;(V5u zpD}srn{$=hAfF3#B0Iu=s>WKf{lV8t=bWzGmtlI;-AFbIU?q2i*}i`j5v>6O3WI)$ zNO%wts@YEMc0cJ)JTeKSikjtiw{|=F-JOGtQ?Y@DxPKa4I$f4b&eD*R3Zrq~)GEf; z1|ZS6(t3p_MC>De6Mt?kUW4xFH)(t1_;1dEV+VdwM%@~``m z32PB;Mb-?Al?n9o(BHKdpVxZeM!@9|yawvGEgGDzTbyddctx>^$|2uvS_n{r)Cthx z2l^wdCth6u^<4$3!qU~s5^!}6#?GR-JZg4m!xtCTUDZbfNUjyxb(b=xNc*WR$*6ER zc07YOw$LIkHiez{X&DoG=Wt3y+@vHV6<+@j%gA8*`#W5A>K}vPubZo>8dd7bRtcy5 zyr5UT$h|C@8>Q0i2ZYEETzgq7pN|DIbEK7Me(ew zw*lWe9kQQSUhQn`5#Dm3TP{uZ9UHNgV4Gz}a7fO@_fmKEII~a5Gs$c?rC#tFk)y9D zj{n=?FF2ELeCb&27VwXdr_(>kNg^L@mSbD)_>1y!9eS{rarW7Ew=u7l0Ab#x##~qJ z{XilR3Sb`!K+2kNrn`zqblUpaf>KOG=Ew%k^WsbGD*l>m^hP^}QSLISAKr};U2I?N z&;k08!d7N(3+;*#!MPyyE=vH9)9d`-`AyZFx@yqGP&H_la*gcfsq%CXlkRp5XlyN^ zn09Xy~Z$4e3&P`j5}fNasFhXihIh0ahw;6@e~RrnX9Fx6S^!% z4Jx7QpK}bybmedEY}GW4Yl4@65}P~QdnZ2iPJ)|RD>^T2x;;fsJg!tiCir>dk0p;;tx$_c`aExo6e9V8|K`+tGLG3BcGST*^Py9BCUS4g@aB zK8))g{EjzcX=vW0?@ICYJ#P@n)|%l`Dd2i4>t_d;r9Wzj{mGb&kaLd~^+{Eu>my+z z=bgq^MBdG8>g1{#Nk&AdyX69fm&2|PL#_o$yd`lSI~H3{Xs#V&Ow1NBNU}5rb7ph@ zMiY2eQ9LjpxHF3RwzKSN0{w6FEDs02Z4w8J-{VYb^1=F3#DM$)Q+?4C(OMTF_PlhO zEkmVh&E5K}4aXzs*Eh36ADoxN4gM6KV)xVh$NXHvfqOZh6`Y0il;~7n=!8w*xy+){ zlO5^&kv)7GXgFdiiVk%AoV1Pr=jK+!rx#i~EOShiVky%T)f~o>GHpRJJAm=u$5o`L z4j0GmKJjQ|cG}PR-$sT}WJI@k5G!Qlj-PFS0;$rZgTvJ&Bl{*#_XZCXW{Rppj{V?B z|2`?w0QD;QrG0w+MJ{H*h=%46fi;rGPXQU*c&JotPu+yN1MyXoKSu{4xl90@x9@}F zXFBIZ81TFT__*ZQEJ#5LEoRPu>*XcNW&ik68>PM_q0KC<4dU%xQ=j0c_^Dt?iO^$V z(91&RjQyTEeY976rSOu(w^-lmooV=SV4Tb(mSNONjA1%+4Z}X<cprzUEB8a|Q@wU5!2C1_|UEw<~{*4jao1 z*1M*v>+}(E(w9DQ?)*k)0=$ll9kp@evuiy^C_G~3@I1rzxCU|HYf>;kgCAA3Pheg+ z??Kikf%KHuSV|+`#)=_rZb6Pucv~pxJOCVXnP4}Zu^{-3LcRVx? zx=L=F3;ht4`&KRGw^<$g8L1ziRx90LN2=}O#|iLOyp9;pFia(j!jYZ8lLASIi7dJH zdV5lL>nfcK)MnI5CzE7*8_d@-hw=m6#r41r94usbg__C@ADzS2uQ+i*5o<7Pulg*^& z-JIB@anww#7xpAf8$Tg`c1F-Kly!S)-~d0?EsJgX-2z(XV_Mp?jX9_6Gv=GfF`S7Y z%>g2*YnG#dXS4wEyAi1M6?nXrp1x@Bq;ewA&dEclAv85n{39BVZl`OKdA`*y~wWh%im&O7L(R zz@ImkZW4q%3#y4`uhy$p|CS)P*S!VM7d{(>sNDw>;zC&UhaYrJcgOIOJp_F(raJwX z+)udRw){quUtJeZdvgr=NC_8O*xM#gMmz~eyCa9{Q?4;M&-f1gEVD}o!U5-Ox54R* zp6KnOP4R^VLK|lyyRw?YdVp;Uj<9ZT(Y9F@VBjuea;7x-#;Vt>(8XyYv|3b_Ct=ov z`Nc`EUs8`2JsLWOK@l^kgkdzhrpskYFr;)si8w(s%SB3`6pm#T-^GwQ{NSTaq|$a< ztAn3C^|`XrR}}V_shrt93+j`a&T_U}S$UEy_%dU?-rLK#X0`g22SH7`Yl+My*4c;z4KN2@hS#z>ff?caON0< ze7~ls;l2KFGp?X&i2l+{CVynN<5$sr%L$@gw{=S0U{R(;Vp0(6XvRRz_v6#imtzSM zmRN)zY5?GvO__1z+YWvK)*A(OHOxP6O4C`{VHIW{iriPB?Jsz%GUop@c+D72Ln!G% zz%+;fSRbB%fy~m5YRtKe)KD-d5S+2>!fKXXk5t3X2%kJ&^<|BvjQ3)h@*`7BNdBs>s>!d2 zmcs0mUFUWAp?PZZk~)YSJX__wXAtra6q194_*tPcQZy2)hBKC%w0j?|SYMD>Bw5t9 zWBre1ZlR@q5lCMxFhSe88yiVX07!K4!1a|(k#!*+`6CFvvFZQ`qMdlAR%&rA0ls65 z%+3zHqM!}@b+WT}@BNu^4b&nO z$X=hV7gC39?X}r2%f7OsS>dM0`Y=~!+cR}P$hTh(av*bW_g7Ym*&_~w$mgF5eiSsU z=Eq0aD_C_~JTS~aHYH!XkoRqq>w@{jYb-fEBUWYQNCfagjcsMq_3CWBIC9>LRoeow ze&;~mZ`7xsZqyW5dKjSWJ5$e1lkvCT#BhG%ARJfLLg1;r7uC%Cm4nfFKYu6(0Y=B? zKF4F843DO3a%3TCWB#IeQum*&hW{`^E|N`Hcz!`H=lrJCYgu?R4*ACn<9p|CV@0p= zjYq^Caq0P`*J{lKbYWn zG5mgL;q}<^p-$iU@|I%`gL~P#R`pIJJel-hxfPMJ*Ld);ff8A)`ZuOwM@ep z5}dwcLYR5wa;eq8U^EB6%EFjGUZn?viRK{)l+@-=p!b`=J=&zSCMBcGNy{$kvtKKRR6$xj-DX`4SSm zqg->LTym3dQ+SRkVC>l%*5?3h?=uub;3+_B{+?rmH0-=P4D54I>hxb`Jn8Q*3~TBv zt3S##Vv{Zq?Xqw4F@|2J8(#;q`upx1vu@PQD|!iXZ6=CZn+2u3!(Q*y>@|YSxuDCn zv__b|t;1MLri-x^jitIJ3fWJ1p2|;tWEv(7g01ghfgeJCsjqE z&q&PQw7=MIssdHwWnZQw0&(F|DX(@?Yeyv}Eehr5O4Q&uLJ4Y(dU8ARDtxWy{6_?)Ygbl^x9E~ zJj|-Dc|VY@S%0`ilKrsPDPLET?5jrfD<*e{Ks{c#zC%TvSBs=1VYC>&kxcIaVS$Z! zgpPHH>yAhbTP5QX*L0doTbJlX<+1cdO!jjkhg0Ge#o)g=!dfrRf@0QDP=|HeX)>Mj zdU6!(ux`zxSdSD0ovqF7E5@UvsQ4nGNgjs_;CVD0X6OaiNPqTke2CSikavwy#oNd> z_&~n4{L?1==;X;Mk!rVSj;aK#TgwLa9GU77AfO`=y6&<>I;S3MlZ4a`i8D1ROUGJz z=eL7P>5xt_kv>>?U*7185<{@^U@FppXG56e;1l|mNb`7_9wmt9oG62Y(6d7MN+K3o z=?X<>5~Jr^*hEvLnKV35d{RarA*>Wqj&j`Neq~@30dyl1=RSES86=%@v9{DN@i18% z-&e$->nukv{A}*eg!C~bDh*Qk*4IL(xl{-4@3b!=kjxQu>Gj+JqvHe%gZ zqe1LteOVdE-m}rTX_-`>3v3=dv_u4-6l)G=!KIn*(WeyC=_;C26KT5goBMG}Gu@!Whd0ZNn*Vrq#EAE)(gt!v$nAx*SsFT%XLaISqWE zZybEqgVfHjrB9@ixF>63*!cCWwZ=X}4+K$lk*%S*=-nXI<;y%G8nzcJ(o`DBl%}OG z$YcO7e7n?%Sf=d@Pd}wesw)@^&QM#`u7j-twGt#fV$7cECytTQ_B$CI)k!+A8Gw+i zVP>0VOJ86fw=dt!eQ$G+Y&z7O5OF9xl}-Ssp@O>+E1PwWvQRbOmz^-x^TwBVx~30| zRKCz*SzqpzY(Ddo_KnPSVEHx0`X=QLY&~~c1XN;18&FBFsb`-o!m2~E{QPrF)n-`& zr8L3QIpu0cn%s>IE1*6N$nQDyr{x;%iK=CYw*47v zj{bg;sMBlEo;Tc3Sx=pheT9jn=d#@MSf|h$#lKtQ#tJE={-e=MA!=hc0 zql`k3QcXD%(e?XQ#PHOL1BYbk=}Z)lqjti}{JJ`qGP_?Hu%RuXx`6n@uS4n3zkMBV znb%W$#pZ#Y_P2VEvZP?-6y=@5CkjN@0&jt_lvUOdNrw|Qx!~8SbliUGfkR^kV>Zhd zKN;9+jY`cn;h3<1cl{Yi)iS~t50E5pinSU#w87XICM?Ea!`xz`rC2}c9SGFii)dFj zW){ml*o|pGO*`~E+OHwD0idV!>jbOmF`I@Ib`XCOGC=8q1)co?^&2w3wo zJg$Hp6$o^Bl}aYVnp3vN_#KTBlod5q#h!&o?sq+@ecJwR1gh?}AmFW=pNoA%sFHn+*T{gd{Z88%Xz52o>F%rX!M~B=P=&Y3|B%N9 zd~Zzw#T?|z$Vc%FoZa0IzhnQ7*x5KP>*CX7M+^HZg~ zl0V9{hK<#GD304Uhn@+0+k9@DgOG~vF`p4zg#S%dcxMd>VPlDVNfbR3$WKarlKX2o zR}L-=61dxKR^pVIuyIAP9emLjg@1Gw6XnS^SDDu`i)+9&^YaOZI`bv2>O7LW)8!4~ zc-aA6sz6FOPxIoE&u8kd>Q+1&Vl&5~C+y9yS|Ez=R|P(>yRVqPA04mSE|?soO&1*K zs!n?3#!?`N@M53fQ$QmMI2A8~(RzpXyQWi482ot(-yN(9h{p7!_Qmx(f)6E8r0mM3 zD+=(o9ChAQCz7F|rb*K(-xo4*G-$)?yh%)vo^DkC=CK_wYyZ5_BKRwV)hUxBaOS$I0BH1nrVzgI$^ybW z?dC*m+7IiQi)#b)XBvk(p{`vqa|?er?^g28l$`Xcn1&~3=4Y8c;VF0i?qbfRI{Y9% z9$KiN4mT0ag8DNr!n6!=O68$3tTr7~ToXUO&0xTVH7%mO;?AR?7o^0EwSYE1)4_cy zQ4jn>94XSdFgp~O9+UJskv;z#j=QnM6*i=je(IZ;sUt)x9pst?&^wkeB^G9FMsx*3 zyoO334I#btwIY5RFRm!Kt_v(GERCxw(ku6f52%z~i=##s=)SA|ITb$)PcC!9)v7nB zesgAc7(Q&ZetX1v0;`oR{Wy)kzr@4gC$Y_0M!5u%7U~`9zgTE&*M)~ae9TYR5mQjr#3X3#~F#b31-ZhyC{PYmnwtG?|$9hax>Q!?=;@BM0Ro5vS?#7~2T?eYX)rKh!(TJ7LAaY0N=I z&ISsLx-QOHUDJCMBb>)jCK^Y-ns8s4MyHfR6EtGNst{eT#j*a+3H~sk^{CGWxP1yc zoxe^|W@1%`9sC9Wm^fqQNKd!>w}uP?K?Wx+rte8XHB}~?6VXY^%O{AK%N{&c^+c_} z|6=Yv!av|;Rmf;XTbNKtwb5JE3Okd}lRnpCBeK&MPYc6PGYwd%gsb)Kh}b{lr(Z?a7}-Kz>o zaOO-;N3FStU;sef`BXzquVq*%@8$FZa!pr0(Hf;<0i_uY6>EK;o}W>DS#gSVW7WE+ zfi(qr=B)=wo|Y4nV-fpV#k2}DCND4bogR5R%ca*8om8k7jXUT|CZ7zt=BmVLW3%zd z8D{p~p{uGjg4gWsxoQd}_qdodqA4$?U3|FTD>LR;A;IanBqTq7ab!|mF;@q@W5DJW zn?694fZxX6h48cO)QuSOImfZVXEt{VE?@fXX!SNm44Sn$&n91i7po3BiKb(zN-*Ks zCWmz_rgi!8>D&Rr>D?Q?IOobaWxLEFU#c0|Z@<;sQGxD`05ZkKiavz%hK)CJF5i=a+`rrz`@Hd&A ztaK}^+tWe5@3@%ip2O_lWUWgLIM%MSzsVl&@CHxy;1JT$sSCgY0|$B4E{Gj4n@gJR zcR_Sh-R4NFUYS-fi2f#$jlhbVMrbd=o$s1eU}M-Yz(H(R%8RIF&oIvFeC^zGq~2xs zo4qgz{!0H|lvgson#YFxIt=qZN@)- z=kxSLqpwc0hU6i1IlDO>?iW7%#%J9CPpMZ1Q`JbYS_YW zIb+(-B0KZJ6X26g5GzNZ%8gUu?R&OyxYezMx8ITD=8egm721WRJX`Ud_AeSK6B3TT zhxjbB88Y$q+>Z)jCyjG-*XvH6Z10#RGiOs1#dsu>L(JlsLm4LyVJ+)&1PtdYSUk5* zNqJ=?PN$63s@!cZC~VK9)tRZwtus&9e}b`WxzCM|JR4X(qwe!UZ!v4f99GzGBTLQj zb<;E0903{JfwbPhD%R9l%<3=4WT0KGM#e`57JWiO5?zg3(~0g7ZP$y${}OlyC*(^uX^c~fswCr zJKSsx$_-K@4lG^-iwR7cx%3HSbEw#2NC>&R4w?z_nT zydjH*%5`4g+6kyjGU$o3hU>BdBNTz8q!5JqyKEg9zB1qiu-XA)uX2B!%ZQ#MiZMIy zN{oe9FQRKaw+B1sPwOK^)@;9DKc0vBF11WMofof5I1C%us4KY#-2RA<3$Y&7E!uRs zi0P^mGBbh|&lpTNrR^~bu7+;7$u;}wq-Yj_@}#`-O(?M-;4+^N6)uGa#?Hx0@v}EB zRxPaP>hloZF{aAX-3vBpAoi{_N{GFl<(48=51a;{FH>?Qh}0{UA9(3$HsOaE{3*Ef zT9RjtQ762bMff6*Zik06AvDi=-)36s3L6=G2zaB68$tEZt${Kb@3GSpdFcJG^@jze7#_00EYhR$k;QhbJ& zT0j?{s1dn)^|qH4F0Z~_!|cZ^j)QS??zXd&KWr$UW`4k8ZFi9QCxe=N%)z8^mZ|F2 z_zKx|#{bgd>HqSjn@Z-PWMoYAb7W++m~u93oN|8Zz*b07JCKO&u#-DjfqC9y*N zOLBQbibnj$;m)mJ|Ce9?*VET7$jJ6j1SS96Fw7iP>6J((p7_5)zED>a-fi?$k5Ar3&nFp?X3hU z?>HFa0aE=*B?c9*w?lvZobIOElXk)wCns%D%=UUI5ot?On@M4OPx23GQWinteGo*7 zpJSFQIW#^WYMn&SD@ptE^4{f3Z}TzDBtb;))1`D?F26W~>?y-1N1OHtIKcDavYzeu zgN6VV+mu-lFWhC;ueo0MA3Vk9)#@~tGi(&=7Q5C-aPv+qH#tZ!DRR)v5Q(l1U}Ht?STEJ6 zYTmMWa-t$4BPYGUYNct?f6m!ZBwusnq^Q`D02fq6Adv$vQUd}gG0DboDJ(CkJbZwa z*j1o<{dKTK#3PcemdrB@yNPWu&wk%|kF(ix{b8gzWCW5x!zuUOkUGx{4^UC$17#O1eF{ zj$}sOi0Axjp9%4anTL!1woq=VK7cLFf>%>?a9?EHCaDUbM#yPP^<_Sj7~GN-R(aZb zh*x*`ur~09CSn?(B2%)n6~2)Q9M|s%adNb97L(kliBfES?Nv{$)wI0ItcJRk%wpHH zc?QhGk^_Mv%P}F0YE6InpC1bwYjJXASo*FvofYVwp=f1DCb1jw!Zasdefw%&yFkE= z8(mE2>WrGYmBVDT>o~?XaRX(%9eSGD9T9=j&|Jr)@qw7a@5?HtsT=-r+l%l4qYKMM zr3G;1bnCn;zC@5|`fSo!OC|p+{(Z z^^n)d)>^Rm$FbernaAIbnYlLIa^E{aM22%9F%E{M{K1v_)>(X}_G3?c)A3ZI5Tm?# z5XO3%zI~})r^^qw4QaW(dtMonO<>7$hknesTtIXG>srF!Dp&-I_P8W^`e0BfcSfdYXgt& zkK#B7oH}z1I0V(_?A(U+162r(n-E$VWg&59__>j_{l$eojR{tL2#GM6R1c7a(xKH8NS-ya*aiSR(jiAv&qa z7+x?yj3IW#-_0~@|LOWjc`&0UCO^G7-yP_V_jF~NKJyXnYR;;xzhi_pFD{n5v!Dmj z{8irTX0~W&dUIK{VXy|xxc2oDWYiVk8ZigT)@Z8nJP{3mn|cOcp#v^=DRhlpT5H%Q z=abW5YNE*|^5VaZHw~NJZ1Tz(4`zgF0VaRw!-}7oe zON)65X}q4yA#OL8KZ0)~!D#JJVNEs8dFe;BVcw;?&NyY{iCc!L-@*xbLBG$j@Vg!@ zu2swAX>ZH2X~sktD6nF^t%Q&gVv$?C`nxsSg-)c*HhRbpztd=-4Y1ypn{aIQ8r@Rou+sX$A zKeP_9>yJ@ED)5)y#@?V^^2fF;=;gvY^d~$uC&w}>bTnR3E;cl(5TZXkyK`cA3sL@u z|8jJRm7@}vyIKW^f3*8v3}rAGc;8(|x!^Lny_PSjkEcSD=vv)hXOG?Z<=bi@|Ik{# ze@H+GMFc%h%&SAmuE}$;S3OGXiS9Q+kaJ|;6(r{{ze}oz@Xddnt^Y@5uC@8@|GOKK zZh13s)^p8@Z_R#ivKcsAgJ|$W6?-eusj zh_Y@so%2oNY>{Tl8evTdooxBaNkPW5UK3%yi{{(KoLXYJpvWXf+`MGER);w4aKj@UOaAGCP9WOAdXGKhK?~{ z(Y)5zM?WXvkhZViANTxsI?elkR|o&2-h$GSSFe1D<^jdU2vL*gD@=Cw0A8s$YCKU* zdR#Gm@ynm2{9eGS8yhEuyyt!jv{q{6LZgY8k5IRud~3mYJI7-u@KwElOe}-E23E-s zDX(0)`CtjQ!V|-fPy#DP^bR1e{rGlMzP!1uO2b*K3Kup_{nHRIWX{H6R%_i2R%WGx z8up0sg@=Gw8TC{;U$KiZV8Eb+>{`X2*Sd}49S8%K8JZ1SL*sDQpOxb(`Ew%CXe3QA zHw#xJm@5*_Zm7U;eAL6;!;T`^mD%vcVl=4m$!&A~;l~S6?@Zh?Y^D?WgVW~<%S%(B zN2JTyL8+#S4^2~w)VvJ-^WJ;|yL|syxJwGYu=90)IO5UBo4|UPB%0JY%R)jH2Wo6# zC&9C!CG@cB(4T7Re^iD3`RLldwY#6_XJxHTo%)X(sD*XC{j=8Q6$D^CY(A34h!WOHuec94_42~oU)u0vp- zeVAS@IAZFPe`@p?hNJiUZ1z}H=6+=jhGlZBtUpCS{8yh3tui_+#7q;TXXY8fWw6Kh4-pf@M$ zGUI-gCF@+r#5ji3L|Y6$h6ydM+U7>e$&!&x3g&rqq@QAjlZHCPS9O@|tzWF4sH_V)ij8{a5f*{+Im!DR41TT@3VRB!whg-&WjmJL3R z4$3_02h(l@=CjR41xCM0+#0L+Gm~oF=bKT-E}hR(_?lp&TUr=Lf8^$%iwt92@1amM z1zr6VQXo$7i>CR0zJfRF#oT7H9qNOw0h3cH0bc@4`Rfy^hIz)C ztDc_osmSLt&%4vwZQ{q)JYK;}y}7OO2AjQER@tX_M(2sTwrdkDCWFS&#g#4~NEg3@i0s9DQZ}JQhQRFa3m_w0RcvU7Qyi z&~EtCT17b9c{Z-Ro$I)@*1YI2m6?RzC^k8B-AJst>c;A3SjVd#0#SdiW7=l;NB^MF zh-O)$GwU=zLYDTlE1Qb8|F_EINH3IHH zMC^y7gI2KOH6xtzGnbuKXWo-Dst!xex)&NQBozP7M>9|m3@G&C+HJ3Z{27V%xgDxW zMv#y0_WXY4n?K}raVLNM3G#@m7J3`BTZ@oojh6;aZg4qxCC&X!CP9>3?^zRid5wgl z4JbGB9&D%qRB-uVvRP})1X?ssg#CnKGBh6CK?e zN!C-xZ*-wdxCFUtre=P1_T+7;igPggy4DnY0>q`dOoRxbc_MnP4|wbX;&9o7S4CNY z_JKVGgqVd*elL$(CP(o^R*t>E&-rv1>V5yh5&Q`I<6?UaGvX@ns&-C@U^HjWP_Rr zWqsFYK?_ORtn^`y6A}`PlM8&~nTB{mL@L`z#8(kHx?;vE1(ftXH{KJBDnMtffMyJ? zZp1=UgM%4+gU+>}j|g5r=DemRA61xqEgxXhlpXRu)X_cc<}MLB>3`m;7=V&Lh|mha zS#u|*>M4(8f7bnS9Wod0#+aG1smCk;v+ZzZ-<07H#~tj-+59L9ombiWY?%!rc_R#_q<0Vq)*~&#rs=bA$nQLBv^UAsd28Ck zEV(&BDZ$-5g%g;d@hKLo&zRn+YJt3*SPlb$f@o=Q_CJE`n`njgqRP$aY>aa!XPwa2 zvL{{7dIHFElm%-4!KDq9lsCVlS<{?}xK1dp*fTTGKlI9WlHA%AGa6=K^E6F+GmF5shHV0W<>BqnPm!FOB}^fhVmrt+w=Fx*47%D zKfvM7rw!v_$`H&&saZPIBNfv6Zp%H>IW}mJMY(K#j|4pI@ngo9ZVb~4Z@$~j;U&3- zRO%`iOd|f=E>qqlds@{PfEmaD9w>KQ0BYiM&#dO&i4Dn3kem^nFkT%JbMLdOt9z$O zMLi1{=^pMN!*fQnTsL6w?}eZQpZ9kG=aQ#L_AJ*@b)vwLklcf*q!kX*HKMJ()R!97 zR_nR1lDd)RcVqWL4@oRJ5r30Kn7_S#&!F(?OYxnq=^Ce}trx(t67~I5L-*f5@^V>O zKOY$EGq!YRQ5ATJ6KrS;PKTG}bA?n!&rTErszijENI&tu`Tb3R!==)tXPz1A+6;gZVrmTT99;8*P)bILm3#rJ(4xmx{J zpJogxsPNX!(&`KT41?>bMD^VM0gZ@?V?T0tm7AzeR9a}o)g<_QXFJP4inba{FEja1 zco+rHra49}L5Eb7OwWL1jyG>^<;hKW{Y^Fr=u*bxFoloqedL33OxL`l*C+rQfl+-=l$xxdFIZWKC}$;ViX+)bvS>dhAZutwMx)0o8%MdjHJ%F z`o-+g$19|G7^vPG`b5HY-r31SKd^gxgsum7aAp*aH}Ex6_z#l{?e93CY(~-V9feA)!zK?5+b0IjtWM#Ydp(5AN~~OIxgDP? zq$_wcbpcmvJg4x(bG97fx}PkKT4boz7G2HH7R&wPoAOfOq_~ITRb^cDlKuvYL0)ZE z99FEwaQEa{>Q>F*dg=~_1Z(*Qv~2qaH+aJIxOsbA%M_#FZ5|7pri0F8oCZo-0y;DE}U$ zz{`RoluR-C$tt4^33a(_%qXh8s0ggob-K)2){YdqltafFuN?d#AF|Q+>!P=qZgC8K zL$4~Aa{o{(_n4WApbp_k@Il8+WDmYV#jER>zhMT;o$pDroG&IQllg#z8Br`YDmETxsI>y&@r(p~4;MgTqg0cSSL4_XkS;a8Oeh6f=&@LQJ2ys(BquPs&}1 zSyfi~8hk#Y)FCFitIDS7!P7oTJ?wHFfjB@@#fq_A`=$>lVskwhnqxjfXZK!vQFeq? zA$U87tXRxd^tO=mMWQN>*v;8TPmGGU+!yDQm-t}|00;b{34O+e z5m0U8h$0OBAwd(l=iEhL1<(qw?0Mf(7I8&&%Rg#IuOff>8fd>qEi$W=hsl9>iI5n^ z=yZ=nr2v)5K#w_hPZ>iqblAd}SwXy0dQk36&8b(I1)-THv$9}LjK*>D_$Fv|UpaI$ z0`2=QvAE=Kvd^4P+F-C0*KJf;Gh82`@zkn8!$cEzLzlO<+oGs$Q}<1I0zI7h-j@q& z(e|jVJf0ZR$bLhpNcTs}@}=|K#fSRB)c#S-4lB#17E8C`M!-+|CFVfZ8Mkml#h~uD z%_|XuG3r<|&;cO{`uWX+r4sT_g_6#9ruDXbM{BV|onJz$$Wo%C}R6*1QV$c#_@#;#!OFe207b1&CKj)F@; zqr=a!(7MeVG-^LCwpv{M<;0hm`AJhnBRKc9*AzOK@4!sm&nq7f(;fG5`z`L_@eCFq zM04)RrKF-v*n~0HdMy;#x2Ks8qLIJd+1H!mH*Iayu~6qN+s2>$H$~C(jk?o|ys$*1 zS|2%pjSYc20qN9Mcg1daip;ie;NO`6if4j;LYhYhQH^KpkNZZ}Klj%z$v9 zN{|;)LmDMMfw#j^;v_h6VzV&)?X=yVl-Mf$_lHkc9W_kPxJEhmO@X8Q1N-y)`B_>V z);a7zZve&nI~d~_Xn*H41KiuLjeK+=0pxct*LQzBso}ZkYKB%q+K!FH>XS4lq4|+1@Z600Klau z6#v0M@XwF#s1IKRw;R9h)@SM~RL@ne+JWl^=oae}`z#V!GoNSyOcJbLR3!d#5XI=`U&a*auj&6MG*O<9_cQ4P-Tk%M{B zWH|BYwR~iOc8&;0u?8onF+l2-SBu5I|4_k`aNQHTgT6qNSa?c(N#rX9L+ zB=`&H{e=W}mYaKn<6`gE7dc(b&<81w)zq8R!$l`~$63D=eQsCR6pWZuP5cvg8M$Be z*@-&An}hN0Jb;5HIz)Uc-1If8^B}d1+dT0zU2p#Bqzt_0A|H8XqrPr24R} za&K@eZ_K{ixt2f>y z&E2UYRH`ur0>(za=+fPenx2+CZ)j7r{jx46i!U-~8?hg6*Uo`HT+C_@p^NBgh#%|D z@C=AqSrX7(Oue<^)VH1*;C0<>yJR4Ci~rJ5T6tp`4jx#sW~=qkueY64lRlkc_^>@4 z`Q^7WY*J`KeN*(TYh^myVEjO$&0EQb1MxKCcU{%Binp}Duv-1G(*{2G157<%v9%3< zP@>t{yQgi^HeITo94hO=>7?i*`+D|05x5qGmZ3tHT0R+>=JdMjpiVyJo2iD^BL)FZ z)0mYa*ZkqWlZT=Pzxzj}VHb~_Y3ePZ@gQTF(8PKI2!#H`K}M#v|?`BObF#IiIXN7-mp$10YWZenkQG`7fNDD9aO#UV*VG3pVwsBRp@*0NX#)-!i& zfY`;8VPa4JEdLy=7y33BzD>qC)K~KXYj#hey5@<^Pw!s~%((;c=?n9$4UL~7wRG64 z^g{a>#4kyKjk+5^!|&EMV~M4m1goQfFl*6#4)G)s#t3^)5JZZhusM3l?EJu1)}rva zh2qd_gI@)6xY7YFr5R4AWD=FU2-+|^;ezylivfvna*~LENNh`uFDC-cI*kl1(~FJA zTaeHDGe$5`IeA5~wjB?>Vy5ZXx8zIf>=FLC^fL*6)q$a=DR|CxipM+ zrG!0?WiHZKiHoF3S$)Aqe;XdZmjkWgJ zOmssbtU9wkiu4rm=>w&R7P7dH^gSbx=JeGs0aeE&?+%{;w8CCaudz~Ks@1#K2!4>T zmvot`gJw)T{^*9NA}Eiw-;d9{JAySW>9}EeRa6yQ<9y*%@UF5MTbsA(k3`$S)@EIU zvJDdc5c?Fe&MYmc_X}7yN$V`+ZtW;OV2tRo$tfbn5~F3wAsPMbbA@H4M)d%U4Xhnn z&<<5nQd0gI5sv%+w95;pI4RxuDMO+wBQ8` zcN?H-Mts55yp@Vb74<%$kOExamk^Fk8J8H{OW6~wiL;3W=N+NZ-F{ssVrH%Pd_wMU zyTLV}98ALEag(ip{1ZkvQiQeZ01s zWI|WL#6m2ur>L=_fs&){4AD917$YZ;-Gw1{lJ%;YtO;E673un1E^84pe7xteS~8B( z-Mv>lo~>RyamZM2$uFK;7{GNU?g+d2qvK~iNKyq37jDcveikA^V%$mZo<{kaT)V(v zJZA)qr{E+{hUO%!&ZsBDzkfbsLF?7+Eh_PmR(gTF`20w-GU6AhCb`;)s%8C+h0#;S z{N?D7l->HhdC!t3a6FroTHtI711?rT&>aSCNqfZuP2s7R$k2_svN++=Q26Zlo3mk< zwpPM<79#bshoOh*TfE+7Q5BwAAUpII*Q~^=+kxyUonWz}=}qo5G4b-ah+gl%$v7Q( zkwvL!5*He@;W)rkFG;&!vOPW|ftx|ibD? zx@$8k^+L;HWMJaNY>?Hxp(uo5p%($*^oV@SDmfdM_XTaJ2(=fjhVNi&NU~Av&#r%) zTWQH(I1=9m|wQTV%I zxV<_m&z~}Tj$8?!oVJ}@m^@D1`cclzja$u-dD_ivIb}uChEV%pvW=dcjqQHsf7;P+ z9H2NOT<1`Nij1&C#yQt6Bs7%7I%gXgs(i$_*Wa*77~VjOm*>srIOUm4P%`>r&msC+ zulCyCS6-D$&nwpP9(l`)s9kDMBat~m)xHm3R;rt${=1!GI$0a8 z-irHYz;WP>Oio!-Y9{PWxFLyTJdZZ~rM-i53}9z3CadS{_PGDLexBdztoNj~->TDE zx~*-!`)Xms4;KQaIPR`OU0GrQilOsP2qHU=)*i&kONvP_rT**a|1`4wCD#eEI^8J6#B zeuP-x4-J|`J#n3Q?fy8bMf|&Fjjrl-Nf9VAkfm5s3FUbtXac<3pur1~sJqYnCBt`- zxqUyxC;Wk0%56smhx`Qt1R}G`c(SNw@xp(Cv;$4xiH;xz1N#VdNJi+IH&6^e?vRvf zV418~{5BYG`K&1_Hq);H)KAF&oetu7b5H*!M_dK}WF}4SatPlO#Rfvx#RYyyUi)z+ z+5p4p&YEv3KHqW6wdf&5wL1r-0EAF7l^*-ekP;$zzxk!D_CM@RTh=JvHMY=7bbxgmW^C~w5XH+l|jSN_AG1f_iECH84RwQ)K8PRxfG z=IUG4(-lC9l$0XykBt}&@TGMsBs30yq^#82`^{?To_iBGd(Hw zfyrB?DPe_TDGwHH^JlyvPKCXB)byF4?!RlS| zBB37{u*B2GVTQu!dfiX&b4A>jI1b^ec0DcvBd5a?w(~j&i21k!P#<7YoNYBItaefK zyXa6Y4zu<*nFH8V3`^C>sbrS32oj?iB|OYuPK%kArmD0*mVT5acr}o+(vffJul4GU z*uB^!fr32%8!)3*aIUtDrP+aTeNyfR)fEAAem}vyTqG8Dnk4&& zL%VPT=trHl{_%MWcT#`!NS3hpB#!0f49fK3fV+?Fq>J@jIRd)zI!Z_1z;c)l)+ zS6ci^1#6riWeU=CKJHwi+l&DL*xA@Yo()sJGKo%--Kf-TBL12cVWnANrL#y-teZNe zkC(gOP`9u!x_KsjgaSIJQ&2w(RqI7A$FxnEykz`%>bYyZOG_068Z^MngT!lO)N2Ip z9@xz=yQL$Gl3K#zL-?$2FLG{#g4kb?dyFL}_?52W7G?|bJWUzH2yz!bq(vroK4~^b zQU9hCZE#bMn#XP*V|Wl8nJqKw|5#&=Lw|c&i_{%HfyC6I!10wUiK?3_Z$z$5zBsk& zW(@9r_(*)JS`rM?%6;p}q>W{<0ob&YqNt9`3| zm@Hk+hJ9JjOI?%*M)5#(`Pg?jC(PK4XrizbpnYo<({r{LOdJ2Gfd6{hckL7nafNe` z{;Y5$nC;pkm!7vyI$DG@N#rrkdH(ApaW|sH%EU)r8~w}AKl1h1aB%r2Ok95d^IyF6 z&f3+j#VKBrA&VEBbyb3tcUFZo1$Eo9w0IXqf|x3hZpoMRzRef`z=GI4E6~J8BfYt{ zq>Yg@sN3`I!N!Rz=B4A%H?~T7hnm#K1&Ivra15V>H6`1;7ox%sC{r|R5m8>5bBqFX ziEZMYY8!&&G<)^dSgU)RTYvR3 zHFP@bZUAS0RVm=Lu2|bV z8U5lcjzVE}UO`%{dv=FwQqBIcH11%l47UE3M1FE&Q_Mf+Wkoo(N>wNDQ723qw-m!S zwnwoV9;rFHuc4`0?Xig*X#j z7@By^ zN2p#Nr{^X`Pc%*n^Ga>i;PAhYK0?owQjm!)W06YYLSN(pEdn}TRIENXM<;$7Vzb1) z8;>%#pDvzB@;c}KqHf)r_>mJt60&78qUUTwMtr3^zT{j&jBJ1Q0gvWrV|_A*?Nb~K z`3@+x9UR3;kC}XtsuW)Q;eE8B0o@O)pbtWf^%%RW-G}!K;OWOs4M#K4 zL`gR}x_G@9?Md!$k>W8HZ6A4-iqcdOHH;i}B(`@8<+cQmW2_uipPl1{(r9MZv0MQK zOVU@$_%0wJr+r&GQXso$GZxFCHSoDofp)LSX5fhEG@6a?l{EOD7W1&Xsu^)KB*Ik{SapTWeR(EYZcXmq$%oTw zy#pYL$ce&nY14^D-3`?2a_e;mCUnKKDj+5I&)%`T)cCx@rRap1!$1;;bt#roVy4C< zS4~1r$GtNDIYzW#)rvv0IK`pbE2^7mx zfSww^*!kg*El2+(bn+FHF7Hf?n(7>*Vi=)ab&&h=}OHz?%Mfmg$_qdO`4@ae#Ezqdvg; zaC|a4x}64YQYK)l6pG=ng_GRg>;T3w4r_UP6Rwh>i_)qb(wfH}BwAppIi&x1_#7aA z&o%;I_?vQ-`*(I=5$jCXPN%t~Dw4R0mO|vw5 zfrPpKxaZd&paHY9e2t>EVxo-MI19S}+GD_Ws&+9)fF)clBH60TzJ5P3WpHqCNVTt! z^fEZu!;diWx=L~SR<%QMUs|6lg}TtA-$q)5A&y1{#vzVJd?B>~UN$xmH7WhI^8P=v z)SX3<=dc)*$g=n*IpH~SiChT`jsyW8tby4?2`~!9kK>dLs!5*GgUNCZ(uNXaw3;f8B=|cB3=;1 zfwH$QA`qzER{1gHd)*+n$=i$WeTNJ^u0!418F!3CeVHjnQUX^84lVG)K<@1F)Q>&d z@=RGwr);%-yhIAYWc)950+Sfbv8FuZh3TjHTB_B1w#(z=&}``{q$_dEva81FE=^xm z;D=iv1wsBDOdgUe_1tGc1HWinHO(d0ZLBsV#S&ir8{sfB$=Ub1awgwonlD`~e)|)9 zlr9mL5-}KgyWpXJ3dJD|u>5ULij{4uF08ZI`gfKWenWhR;zpH&erjG~6$_K?*gqPE zIXQ>Yb+gX%a3#MT`7--Ky)U^gZl->VrAI z?GxUcGe>1%$NFI&HwqZJ(!Rz>?YZWks1+O7v6^n~fEK7UR7^6G z;#JIB^|Vq)F3Ie^P>T)i&~Ia5>XKrJfLW@N7LNuEFkF6rx!aZdDwjlQVKsGf;x#iF zAR2dZYU9IsRX}!Y?z%>W#Q5|tb{curU)0^gmsxhi&2wmL?GI3yyl{rAO5yQ9CX@KS zQ%(tFNGY~V0MhV?B$@d)+4%gM_sqxttg^QOK@NYD-P>9Hh({gzxjQ^6>g*ibmZ1v% z;al!Gp8gXZLWyLD5-_}S;Gcar{j<1W;Hqy4#|O9!uZ+?s#V#6fo5yGX2Vb^e)~8g< z^upsbig~d@wB>!fhh=CdasSq*q@6tsCwE(^<{h2ybngLX^Qrpv!|VJX4Tn7=z_tUG z%Tfz@mPL^C1I=I++oVCLe#c=G8ja-zup7^9NQdGlY^Dc93~P?QI8b;FgzOsiXcMTi zHhNd}PJ(3Iw2dzXWJ6PQ4teVArJ;{|ZfkTAh&Ay~PkPAxuKoSBEs`Q>{on_P)a_M@>r7xdHEoJo!3KIOcY8y!6;8% zU+|)Wzw{J7fiY_VZ2%blu?+#$A1k|?tlZ~foul4W=f%=%;tUttS@j5ks~2joh!2|S zSs5z^K8X#DyY(h^vS945h#|Nx$7*V}%RJ(4v3UsGyjC6`zbz$p-7U_sCC}y3qubXf8b8dKt{b3& z1R_CCqdp`G3%>5DpJe#%F38bnX^2S6OdeAC_&T^HAEV;Qk@vjC=I8GOQaFXRHHkO5 z^8G(Mz`x1eec~RYY|9L>V>BO5Wp2vKGoK82UL;li4F90;U^SK(AJC3I0@6@1jc;2Bufv@`@U9_ddeiEYIG`8TEcUs<_( z!ArHJj53qA#@~EY|G>Zu<<_%#mTWB43^7We4x+ub_dav4c?#Fw9fsROw7(!oq+Pnw zCJ@VkS(kV%-k{CL$*nsq+ZhOTJ&M@ook_a5>cWSNCDnltOSZ9~g!i@Y6?FnIS8=Pw zn9_InyXVVW&u2F8UFzQqQ>u_?ondF^yyLvf{pqz>O1u6*X{ym58_}8NqicHaiFLKw zQ}?7)O`CYrpI>(64`6!)Oj0=&c!ipV!XJIxefiI#+!!y!FY5o4hZHH;svA8o#ZqTE zCeM}@Mkjvc_)Usa?d|=|@c1Gk`RD>fKr`7ih0Ss~a{zXQ-#;6Dc5nk*@aA6vj z#(yG}UW#?a3)~OiK3_=<^XzzNoYa@gpI@;jb&s`;vsH*zGoDCOM8N${B}TbgJ1c7? zM_QCLI+0AZ$&T zXTD6y=Ro|9P@;gmkDCfi1klfJJX2WXV8RcdF<*XcnIJGEV*{R5ha30h_lVUxjHbsqMX@&nUW0VwMN)A*j0;Bj@8iFNO*8kw5l=gwWPaT z5F#dhl%IIUP87sswSQ!=RVZUJpEdcm`vIW+NQC#oXAI-BsVQv{^bpeUhm9@8knK`P z_!^gnNIB=ch-ZyU0nH7*9nKv8w6LAD6r+n?i2Dh3x^?aAUTCtJvh%B-v5%VRQ9wMk z@dg;F5}-+ah(RIHMo<6k{og2EHLZx=xA~wyz>xeWZ4B=0h{oT~S89JUNXZxXt zq%{h=@L%A$0@Jj(elu*<@O8dNpN>Ak4f5SNc{e;loHHqB1O%+1eBkBG6eh4SX91>@ znw7orZNR7FawqfAs)cGNhY;ww8S9hUd<)dxC|jK!0Tu!VNXAcdQZqi;Fsg0yD0%OR z*|SIx6BFJvAUyG1kzJ=0e4^I(=p-Lstzo(kha(g?R?1?fbnRhWfs%ktb{6|Ft~28j z9rbbG(nKazw%qD~kfs;5Hx-eUEm)kA5kef&z& z)l0P(`F-2{t5?aaJUwpoby|=`9aSZg1EMLJU(epNa5ydT;7BL>51FKl6{A%e8-s31 zQ-D&Qs*u`ogRb!RHyb$QvjKUE`(c-E7NSdmt2mW6TdZHndfrVSMGF%9g8IEaAMA8H z1>%WYg7=5Zmly2MAF~QL0;+G@fcO@_i-oHNP;gcW_6M&v9YIbwIX!B6NLpKLO=N$u zohtP{{=k=(9Wy2NB-&bdEkmiUEbRZG>_5YrTG}vB7#k`@rAt=`AYD3A73sYrp-Bq_ z2+~3?Dx&m~03jf~gpQPi4ubSv0tlh^B1rGx$$sB&@BMz~oa;L0tRJlTL*|(^vu4)J zbC=SsKu$y^l|)WVXp^GiZ`gdGEmG`!MD_>busPyL+DT~_`pd{d612!3F}9YWxfywo z?yeJWdbRk6fPkDjsTw`hk@XJNDwaBC{9{sqSj}w@1kT}_EoK|tRklx;>4WRU;XfZZ z6%__mhz_k8HP63yK3;d zkMmio!=z#LBR^PnoaSuQzc4aG(2~*|cmP`m8*j*)KkDsp+6SR1%WmJYdIBh+-8uUp zA`L_2@l=9Ly^X|M?MgF4-E1s8@YYBS``a?FcKbDgH*|8H(sg6u7EbVG!;JsD6gPFJ zD+Z@&qyodiVv6p-a^95r6>8o76&=Sph=WN$g+9>3S*2YwUXzoz$(#=G>`X55s{)Wf z;B#CR{6m%W2fQosXaH=Cd@4(1m$j%=eqyZC(-h&oa`u20%KPJJSD{row8ER<-a88* zLBD63ljiD$H6Io0ixJDrl#!m;4FTnzs>IXPbn#k1mX)rl01tlZQN<^ZLaJ?ndfZ~r z5cPbEL=~M)D%IC~h9#4NKs-GgnkAOS+vbLwArg6lO%E}3GbeF>dCLUoVRFI0wb%H- zXx2?8#r?|m{PW$f=Y30)2-U$_!6^~u&)MBVVp(|o>U2332fZR*SR{81VR-q#JkYTA zus1HvR5mx8G9s{-Z|2SRm3fWIXyccATVm0ivm- zAuDM~H?jWtZ7y9yGcQaq#_(MWR6ryizF|xT7@OWWRgP?}`QNGMzvUZS1F7T*q?@14 zqB^60IJln78b2j{5&_qZ54;x|+Sm78D8QU%mPrDz zcRK&4-02>*0MDfDZF#(8cNpgmEeUBxp+^Z8jWe4`yZE^D6U8VgF*wrC1$>Bp23x2! zs8hLnvCklvT~T_kJFhP?Oe0sR{J%ry?-tz{M&Hl>MUhKlq&q+t(-ZF}GnT`O981PF z;cV;%)s(doq&8~=)s)$I?G`wNc3DImE!=sBWLxMRELY|)b;K6TvxFE)#&imlWY_XN zM0{K#Yjgpsf?%-F?o{ZV)B;8z7@>sW+Sf!KBve}KgeKq;TntPsb@dgxF+V^7-4B9v zstS}&?vq6=io7afE}Cj~!mT~ko-K4@L`Saz3dE)&mY8SWF&stHM8qv>0kjMZkv)3 zyq_FO+y`b_i~xIPWMugBq*rkC>Y{aTk83ZA49MLq0OsQBOX;j}8GaJ=PU=NM9u7=l zv6TVP5GYG6vI44Gu~)R};FJaqIXGCUqkWq?`BO7d2{jVjT>yq-=q6W6gUi@ z!Kd&lAGbS2CiP;j!fb%ra4j^?l!2gxOq*|jbe?wld^{l3ZT{AHf(ARryz@EW_Bw^O44+7|C&tlnO z7JYd<%WRO0s}~$3y=iJ)P2X=5_@>PnDX&an(?0!zyfSfZhIqXtM(S_Y(eke`=IA$c zd0#_1jA=OLZA)0+(PWZZn-R4qChEZLY~Jj^sYndq;GzsuSG*z@>kiEOcX2JBN{EEQ zfq-tLNKtCjp>65K+Y*Q|cy*>h8wZ-Ei(gMIj3i%6AIqz-k7FK8FLIT-JiCE>>4?4p z>||r4LW~aYCbMmFQ!2{TKIRvksB=7AB_692fhz2|n3BJVH@he2&4*5Bm9+PQHVQcU zF63L$={jNv-(-mO4}Wn}5YVsxm~3M~4*QV?s4#CF*N|5cPVQ!uf64j%uR(u@G9XaY5jfrXjcYw%x)k^S6fvZ&+W!k=h`+^$66b~ z<)}JqpqTiMxl_wWWx-{%JF`75qej4&fMBsqO?0da6J_|lX?q>&%jTSRNz~4j(IU~- zRrUmj_X`Q6Okh)lvmUY1UE?}7>qJ||e)WH?v~3YJl&wJ`TsGvki<%tu4%?8mqCcTy z0R@ku6fw0zB7**x0Enn44}0UNFnfs)IM4uLJE1z)?HQ$zlKyDcsVMWDw3FnbJXP&0 zZ7v$=`E}QJXrU-rSMR&-dk)6Zqk&Yv4MRfZx@XKUZRnk|Stfg_gA3L@gWco=oo%2` z`ugwd)<7$kuS>9T=>UJ7|MbIOeewV9x^)VQk1J5>WXiiKJnN-jD@pSf7oBWc{?s(sT!mfeI>w_i;!rEkL`Y5CGfiEar-$3c zS{wpnNc=q&Xwu*_ny{;rD>coAa>(ytz%@W22^1w+X zgXCA-DyptKB<`KPw%cncy%&1MqU}Z6;w6HIVuUDsvoxVn4?~n0Tr`ROz#twNYz?LZ zG@pgW%vb@s6_*nbsw%|uiD2PK)^JSeK;1}}aKH9%6Ti`SwAhXNDIoAH&ebB*6Na}F z)r|!OsjIWdP%brUkR^|pjh{=n9nW4^{;U&7e>31Cah{qW)V~v7_7p^)n)RYm{Z!WD z^BgSr4g(;Lv5EK-YkptsM+MDWUh7*uJ3`= z&?T^qnqg|dPa}Dvu?JcGeGLNIqSBN6zJytv^P$kE5@y6Z=Tp7Q(|5V%|{f-+rW2}e)2sSc$}i^ zofv|DC(drJRPDUEk5nkpW7q^A$8=_%$-!*Ex|H%cyj*|f!9yio{(W*2foq4|Dc+9s z%)f;!zeDSFl;~Qq*k=&h_y{+(Zh5+qq4cU{TJ}l08j%9jqe&N-K>3Yv_Xix`4w|@X zc1v}tafLW9Gja{~dQBgx+|x2lUaHc30GA9&L)@yZ~KJego}amv3B*jhr8ot>bD>XZ7sF*>T-+UvM6AnCKEkuD4sYLj&A5M3+St zmbE*0XHeyNv{nM~w|}GmZ|POa@QTTWK&|CA8A>helx953wyu5d%}4)Qr=P=@V{1jr zaGwhC67m`jjZR%fRTdhmem8BNUe8Rg83Rww!#aHqkUpx{B^GPH4H#c4(m4g>a^h1k zWcOr2#8$P1UxO385Ir7WCi7Q&3Wm#hUTotDfp7HJH1d^IwR%+(_i5O$=g&q)Lyq5@ zcz>bz`Iwa&S7S|S;-s^kVi-k-kjqolx*tRPx%-~htX(Ufz{&29+y_ZM|KDc7(I<6m z^|?jk@Z40XC9rX@cD0{;kroARUxg@g_zwY&E+>W))$+<;aq(2db?MWQcyvl>e~SqlxFsa5JL9g#hR3km9W^?u^#g4Xc&GmRVggiLHOw5+=N2LpIoKT?wF$H|>NptNZs{0WBf=XFwY54>y5(1G4+pR$( z6SFye{~HY?>tZtEMg1D0ZDSC^G}ncaB^lZ<*LE#7t=OzxUEP2L|GrZw_7_*Wc8JmY zc0mN)q#^=$ZF>mrz)%No6r=58-kTxW2 z1TUsZ8?co0??bv#nyUL$^36`RqhnnxEclBED?3%xS30F1bTMu@k@@JAIByjRGgot$ zQ#s}ScG`kgdg{l`#>sCweQ_gW2f0oKwA@*2lsT|%5?I+&5FL|E) z8`%GI=?2~Ji2S09N9!fitRHjI_jA+u9w$vO2;%Y*s`>Ik*f4)Y;z*nMMe3a51P*U^ zZ~WTAbCaS}`m#t&?GHhzv4r$DGS%F;bUm&{?)4pIpS#EUPNT7j`sO8dw#zZ!iHTK{ z-M>{u4s!HP8hUw!y25zeb*jNlmG*uf0iPU7DMdI}j|GsXKZgm15 z*S`ds)uN>n`n$=V#dQ}dkaJ$6O$+J*$iRD}Ey<}qqpE5jWni1em(O%!tr~~KZZvuf z6Hbj>!?u%70<#5|wmw9bhy}8P`)L4IZke6GGCEW^K@L}0v0(oD9>bHK%edr@A%ial z1qRNwUgJhhc~p8lw!VuJg<`zQm+A23$?!>JZqkMfKD~-p^jtU5TlacqZC&R0+hkM0 zMCU9~NY}ZVIvQBHVNOGh`v@2MRne-#IQwvmQL7Cl2{xYkyEXr(`>pmiHf)MBAU=VH zP|-9l%5KdG;_*u%1?8xvq0jYchR1xY!b@r~S=}8<%~Kr-Ki5*Rl`)CIf;k0ZP0785 z5h`Lk7lKSto?%LL&nmWyU{TbWn)nq=_>>|$cig68QG*-Y#uJ$s0_cnSOH9+|t+XH4 zL6w_Ax@wmpRriC+*QI*MbfqG_9E$Q)MZ7`u4F1?Lr+|xLooN<;QQav{P+H3=BTW<8n8s-g&}-WD*Ir6jA}K) z!6x7C2-|BYz;58_O4A3Y49iwQ5UGbC3W%+leu_qOearW5W*#=q(}vW^JD8ED&`OC> zvy!sq0aXIJ<;WE-Z*yh=P{4~H4#Z}9@ZX-LG?4?3+kbN}I?fpjA}wM+9&!-9j(V<% zg6k>T4&M3x^V$Cd6?P&tL2dgXcKZsAIZdE8&!~`BP==fMz87zzcVy$E|@j!##u#bhb5@yYFcf2HU2hrZ#1kc9PkOu6j@qP1I9ZnNFkrZ zd^|(0{r|0j|FrMMh9N#^+pZEs!6%JC ziqb7SoJVrE3Bw1A)*1Y|EN z_GR>k8GPp#RhC92DbdMC zGPMf%LgRg11NZ>27GcZ|Cm z5s6q7kX=Jz8MfcFONmD&V|Ge5rZ$EK1jbCMs&x5q#$SqbCbjNI={qKJJXhEUsDck^ zP@fPVzP|i7CXeYkWbu`(b=aBV1gKL36{`(u%6`DtQ?IpI2Yb$#xdmV1RIn2~gE@q?UP{JFVlK>#tp4HQId&$9F( z3jG2KHpUC!FRi4vlyFk#qFRLxKks-T8VNr@yFKNrge(1Ky?`r&rh@o9`3Z%`&$8TX z4_w@fF3u>1^LsH{3|i7E{01~H;JW8I?NeIiOUpc!gj>ET?Cgdyw|^PNFm+jR zq(;-afO7M%wBnA+opr#}?Ki0!-;F*Fxk;k9)EY(xd#y7ir}7MPAAfQH2n~&BA-gwP zCVN){yai6`{49`O+Ap#tVX9OSbMNb!=H9;JiQhwe>h{Umy-L@xje$VLnw=?kG>28* zss@YjJx-S?waVA1$ua4wQS?y=qAKhrk5|%+9JDp2jux#1dmk{Hxa4E$sHBr99TY?bjbn(op8 zl~u^t?yKs;Sn$fdoT$*@q^9FR3*O^%nzq?WvuyhF+KijK@}}?OE_DvigvbdOaEseB z7>|=*+b?Z9?aZTIbCUj~{z{Q-5=-i9g*-LGHD9Jx-#`TLBokg( zDvQu=<&mV`r}U4qu_H?5?4}zgB4k0Qez&gWtv$O{_Lg=S8x%NE1-%wTgB>h(tE;0` zQ|xvffo0DL9;5$#)A5)h!+s=a^m~%$)_~Y@Q~QGf%$niWgME2$6jeym20~Wm(_=X1 zZX3cZy*ig$`-LjM#z}gqYMM^NGA%P-S5d<|#reT*KqjR*#k!)yd_y$<)We!BFQ$m? zeul{eF{=qEeIlgKooc=3e4IrsQLEoCW}VW0AXhQ)Uh1Vny`zafJ=Y}47*q11M!!d% z&{8iGFO>6{?v*GG%wGe8v0M|pc=S)WH%b{4?wEXc1{+`@T@@*)8SWXrVF9RcL?Q2l zKL*B$Mqh9BwJs+|+je`Aq^d@2J@Rq)>DRYqV9e{$yfrFx2{Ju$t9-k}^o5k`1B)@O zYGHnF4}BPY%|>ktj2c3Fx(wQ;2EV4W_fn(QjNfB059dWH$g?jORJ?}gF!L!VEzm?S z{VwT5>~Ff9?tLf8|0lBlYvFlQlZRep_05s(?mVZogKxMZK_n&pN4g+j#+b284fOFQ zE2~;@9UfOv2Xpu<7ZBn3X1>qH)SshGNJ7{5e|@KQC0ROa;fJju;wfu(4kh_c*j=T;q2eH9mn0N5Tdz5F|Dd`ci^8KvyEWH-Y@dr?xJ&Px<%R+)`o z){6w!hQ~0&R~%_BNW2%uh6;1WPlET=S?|tn_D|_dn|}@5@g5W{cQPB*Ti`YEqF2&N zT529qbEb4>kyYS_&40JZ_`8z7?$1}}eKYdbE9H?&`slmKs=tavoz5MYmU7RoD&`3|ag~KqjJncqmT7mGs4EFiP991E)*%JMD_dNPSSuUWN|J3re2FDKN=|8bNY<232 zKaCzp=fr0xD@_I^7XHdk!gV7r@rS2UNmp&0je)?fla<=H5Nj0hApY`0L19%muWBWu zY3Xd0bw+9lR%=HnI^YxFbjRx}0Lclsh1x!mPpyl_aQoFQk0)LWeY4XqVdU1f$++N- z#(i#A-Pn*N{Dpdi0m|GP!6_=5Vx~TKbQ-iKc`<_z$V}b{QR22oAoZ$Yba1)%6WIbu zuS7ozU9GsJX(+8Ig6x+2JTv}@{yzoA2ZXub*wnP)hq=T&I$yi6y{^fJIN8~nA{-@5O6Eav7&YUHdM7G#_aq~xUXuIf7C!j?`k zBA&KF@cA$eRUsLzkEhxRC8ke_biBU*r?wm7JAN6b$!DY17?El>uAg0)T#X0>xrI(l zoFLj_2iKV}s;}DeLMdkkQi8ywhRBAD=1X;VjI3c;4;X;+Bd$^U^K&YYdy*>S%wj zwt*9-#2KQ;w?_-VgE@)wj~gQCT9~xYJ^V%p)$8^D%uR`RoE~o zklQM9cxVeC?muU<{)ElPIjSC&Wu%7N^-r#5V{RVC#0%soFyA|;YnapTc&xQkN$2k1 z7_%V}oe4~ z=)3HzSrlrCbZC34sGnWigFfV0LWz!b5}d`#5n7-FFyDQ&#K(?gz$2JuSN_`kDy`cH z(VT$Smm7khr9${B_EYg5nx9^0mIR9icTe%RAz3bm?=Mk=Ippxsuv!-y(kV0?R&>8M-ws}d#D!5-#b;yf-){yq9Zv+s{+qc5o}X_4x5@wZ@RABZpb?sJ*I^^%Um-?b0$Gj7p57_c`k}dr+ z-6p0Xqk78_;i)O1*NvmwUXh*Xz)j3R@~RC3ewpm9V73YnK%0Asf4y z{9JvvW4d|%+5t13XaAf-4_ELbd9*y$CKY@a`G9d;dcGg4|fwi>e;I-FsX(O^#q(zdOeDTkzzq)iNcTpA!4facBB^D|u zy0OyfUX&ggEGYaY%a6p_RxyXrinSVa44*u#g+BGZkfqgKA6xmLjCQk`<`=;Y%w{xc z{`ep~5}+ZR({x6sTyqE=w5YPyxL^btkl?moOd}odlMPncd-We#Bb)K-wm&Rn+_u0m?-_)yNnyD zBs;Jloa~=a%zs{*>Lv=qoQ@WqQM|ArZW5j{K?9ES4NExl^KfWj#41?pzRSobytD`~ z20Mruoq@Z4MQ_VNnBQPTxC_kQRlDdo9$7_BkVhXJEUG21*uBP|?C$6tYv!nGSv&$aDu|MzUb4Q9dElw;R&g; z>52Tp@WpE=H8K~$J~CjX?Z97iZitt`yYo0rVl=zRq~qY2HRyh5RCbSyEStD}l(|D6 z5 z6T%8#)@}nSDs*-^-koF!==Ai+5MJsv7W11RA2F=dc`CE3)DqC%joh`s=N_Wc$kLfe zz-{u1#ft(Ir@uebQ3#cW9tlB{i8Ia5ubH<6>yK$Im^&?24_NtfCZdZ5w({^l~g|*tj|l;6x$>{ zxB}}wDwQ!M{+oA#Ut2}S*|Y5Flt$9zu``1>eKqRAbmL#*r9^7Q&vS)a0{O(1otmj) z@88uj#qSMyVhW9AOP01dN6b2Y9@*^)Ug1OlE56ot7p2d;tM4luumQT9o~Y0>Y)s9M zex4K`K?J2lo6{snzX?rd4CFV(ez?q!s%(2x$N z_Gsa>=zuBkT`!-3;iimYK31`AQs_D?zpu%<-@pQl`3Nu4=jDB5N`l^dp`1NfZ>i$n zoPn#j4~e_xVtGQ7fA6N}@8s4|7CoJ5IM_7A5=Y9cei;$5^SC;forQQ@Juwpo_+dQ( z*VVUOYT4&z@t88K%ah@nNT%7qmv`PyFO1wMvj1 zM-`)|aX4#~lfw_P&azS8TEGhr9BOCZ7$Wn@0VRPLw_WawfSpBL{vFiq-iE+*vO?+7 z%0xPO1zABu89Zl6_~U7U_Ip_Rqlg`$INGe`#ut=Bmu&J8+Tp)w%ZIl3MeTj6DS8ay zeE7u*8~NUfw-HLPT3E#&il*VSloj0Tj89H50LyrPT?SokFt0ahqV{QHUzrbJk%pf` zoFSY8vDN0^Yg_j^3tfK*8CR3%)$;D!ZOTu#kp=08nrHkS8=mZZ2dxc^JdW5Y99{cO znJNz6zr*=CK$XpRA+dnVFFmd>t%WrP=|eO0;aKYx9E)xnWOo|$kKAHW>fRwd%J%lA-FNWR8kQl zwe=}Jr&cHbl!d?HyU+VDcg6E5tqdE^$Mj0aXk39*0%O3#sU$Q>PWa}=iaS9#jPp=~~N?P$@s*x$U%L>F-!8`+=0Heul^%cm!2ABJWwQ$g;ngKnOX zA1_Nf52MQ!GFMEE{2Qa)OJDftm1`R1ik-I$D#69wLL-in9=d^{A>1)2@~=(v@QQ89t5F zPipdeo+Z>xzt4b&1QPFvJR6BGP@vu!^Ml~>ugLXIq}qWUStdq_&tu;$^z~Y*J2>qZ zC94m=(z_>95C#K5>hH9!0MI4!@$iO44V1H5wYxMF>n^&}Q77ZwM!Bx*n)Y=QOH&ZP z^wCMD1P_yD!+DLJT(uEXSlKl7yHk63FlWwdPi$lun8P`ND|J! zuZ((8O?Ek1Fy6nY)&1~^E~~{k#hMBps1vO45ZRt-t6X(CY1zSlU#}uE!$@mKgv-&X z=;OZ1evmimd;E}GEF-QP`vy@>*!G{+22%pnIY0)R3Ha2QuyTLS_*Q96B>>MxqfL%H zWqEp4U%F+)3`EmUoz*@WUatz(>?<5|(2Z^LcEza_bf&t3{@OE$&_#BIhB`WsNJVYm zUj`K=bd9AL$s3|=5SpkO%^&H>cAZ{71`r{Y3J|QfR)|#2zCTa1;XN&OD`NO_qu-6- z4LglV+U?r3?pQ}84cSmp&-?nV8NYUk`CL8HEEE0shD5_(xsq;vQ2560EMA*q>yvy=2xH*lURB)IHcIw%aQI-TRQbtvOL8iR$-`&A8cnw&j~n z`P4cP<*$7uRdg)qh5ooI>3-!n%m^^kWkK8*M!^qnr$y`+ zapGw0TXr)#w5EGOb&4#ZqS6X6oSIH|XDonqWPa8@TD>bJFS{So*X=#jx zt&QwcmGGnB5qxnX1$+_~vSi^ZZsw_SwQZB+Ul4n?=tKzgNY6PXkjgx*)Mq7(=jrNT zdU|UGQ>jOLywk>~G6oJ;k1J;HDKrtob=AHZ()FvQKVopfrLFPTg)Pyz?i4X`>6(xR za6Gf8s?c@3RKInD!bUF^Po!y7wEsi!A(mM9?@8+tK|mn&@FNQ=vq<37m?m-Ea@%2I z?o-{z9o#;v%GZFWP+I(&wkre)I%Ss$J!mXX=9jXR`GER`Rx95@eSNzz!3!EacNVtE z#d415%lbr3Z#gA?l-cyvkS~*R@eLn0st7LN4Oo--oCQ^B;GSUY7l~JdjJAY=q@G13 zN7a;1I#(#$#zXPuG3NScUd7xJ2PuA)CN%Fga1VZd(<(NV&{1AF2Zx{2UX)})^enY6BJE1 zSYioUQg`5xJ7?)E2za&>i3urShXEM@xwoh8-=BwTI0Syjt}0fr>IhfnpYsWnvILn< z9lc{_UwSLa zbu~kXDCjvtYk%U^&&*|r(UkGK_%KLjH+ zOJ*2%v(j=JENL$Gl!eZBoO!rx+%15xQRU(@-FW|kcDlq;ybMtM zQ%`G(u?>na(*!R=xFN&`S|rM7P&1&B8jsL7Sf9mg2e{kv%KoMkoVR~Js%u-(dZ&BBk zig@yPjHyR=8w`$fPlHd+f<{DZ#YS+=42HHlckhxJ)2h*$9GMJs=2}s2@(p~&0Aatk zit;NqtvMIvMtXG3DOwY&kg=F%nWo770lS>F>MioT$c|_<$TPaBCaEXj7|@%_4XRkf zd*Mz6U52((Y=Z&K4ZV1<^QFPdKLiMjM8{;>pl8K#X+4)v)mD83Q8gc}Yib>Yu9OI} zj(*V7z)4uw8Z9|P1eDA_qlJ=p-)HGcsd5@FHXApNi`+>aWSLAVr^?YUz}yicVUg?Z z7#^8x)Hv74?O7LcRpE5aT}K|Q>b)DlZ?egWmT(Qe+5 z7>d01>UXKd2btq^Wlk~gm~CH@fVQY=gMTYw>|-$(uY*E*N<6=(ex?tv&MEk4KOH5x zA!bB5Hq??|XBf=h0Ekj7FSlCmi|lhOvTv+pvUv6xsGls~`E{_vZJ*#q%Gs=K z9)s{QhA=MKLUUgWPz<9ge2vCZkfd z<#{ICCK-^MbEbA+_KI`xHT%7IGZnE%mJ>8_&{xfOR*W*hbDXA0Uz84!&Uy~CM4!9c zYWC~~) z$t_{)^im_DWC~OKh~?7Y`Y)@r3PumE0))oK z=isxiL!oZp@l9vxH`~79VDW<2_xli&f;qupIlYj=oZ}A_U1zJcq8V-ZyMOLWu`b2PmwKkkNex>ZK!M+FdG*6`x5kLA!V zEQGF`ONjM#M9C-Hdi+~vu7~FBe`mk<+0udHwz6BbRrhPtz_{;#qPda{c2oLdRhwy5 zUAu)*7S>ndi=RD*`HJ^;>O69-H#=$AI`U6SNNY=4eQc_qG$}&5LKh=iN)SU^T!Oox z$=zGr@Bit@4`TCR@x(7EGtZa&Uhoho&AVn`0U|``odJUcM58oNenFZc@=AuB=4awb z*$-Fu*-_w!PFNC${+oep!_YZ~BUO~xVeoB>7+-GxKvs@*M}a=9VuS#-Z-Mj#-$925 z*Yv1}o6ThsNy7&1)iOFiX735D{y(+frowPM9`w-g0?#lTktbX=ewk_zv(~{ z-yD$-DuN1z^7kDC8}^RWg;56AIZ4rtsobI{N2jwe?rK`t=7}HFF{>2MoTC4&?@+PA zX7`7{*EQ?%v+0cQ#kGcK8Htq5)|kUZ8H8#vc#I9*%A& zaV0~fEJVk*`f2ViD8l$-o7x@{Bp|P{&-OvwwVJKTX14hdTKB0U!@||vItwp>#{kz& z{(rlTfYIxjElEI#z>yuVZBbA9I}^hz>27r43?8~ACHg2$ADw?iynBSlA;SfqmKHfr zV0Zoy=&o3JZR4Per1bTy)lNXlv_fcSqBUR;S($#7L#NjiYAMCJOpDw*a;AAvI2EAg zrO`?3yxKK*6MU|~w>+4qx>Ap6+VgAYnvs#>k_2ltDDwkAW`xQ>dYxaIl+WV3Ab;@+ zS-*{#Sbo-4c@1Wnhs7g4;yJY}PZ*VMgV*kYzc9XR1NyYPK0d0wJjnhMiB2?cAC!L_Y~ z2Kl=@y1IE0(JyqPo~gzgztueBc2-wQKI()xI*QID^rCSOLPJkCzZaLFwYPhaHE3xg z+m9+W(-Dp41-r+N!+E@$hMqU@3`t_T5IzrGD~MtxCsE! z8Ve^cfj+JmbhEKJ#P;ac4A2&Rs`FRMpq>?4aE7m5sl|^i_EY&jC9yBY`$iw`ZQiPu<#JNefRk5iVamq#!7r*>_=)SDa!$i{5V8V`&4@0+W<57!SVTazF zIy;ZK)fH1^lXci-fr0YqK$i1IgH;v|Sk$&sfGx3UXeo(>NyhB)RuBKr9+UyAgyY_F zQ^p)$&?B1X4+Q&bHzpc0RU0`8?a0eCtenit%yA{~F#Ny_b$cs8og+LG0(JjV_>)-s zSkj9s8)ynOcs8i!6R+}12Dc51?-?q+-!TM|_ot<~+f5t0J^ueC>qT%kJdB$a&lgsj z@4B|`BCrk+-w@KGQ_P&EZc5qnCsstb&ybhWHHs#oh$J@2@83Qs!Q|4tQGwepeoH!(xNuTwi`as)MH08?*O^0Mq$_8{0LsGjn^6 z$CR8hF;2a@)Vp%ZbyS8to);pB{%hl3?|-(`HA|Kguc)^F8XNI4^Og6CT(*Mk5B@0; zT27-rOnE&NNb;Odp02R9`8c$4~;QWPH?#YYV=k91VE-J zZ|8jol;Pf|1D<4Bzt880Ni`cY)5fQO{GIJihNTNx$~PXSX3^_p1)^8=DpBfLx(le> z{J6(pUf~|%Wju*WCFn*!8SR;j)CaQ5rUh_PxSOE>qg{vHKwxT<(@BcE<^isU>Fu3C zrk8T_e~;t8?j-cJ?JnB^n4`O{c)8gRpPakz%eGVcsPZ4h4#+voDy#@q9p_L6&kqur zhV7j&zF3q!{qAO>G1RPxsTqx;sUE_7v&~1rPs9u5ZTYXsBeks`K@NLZ*SYUi%rQP| z6CF{DsVQ*nu=u;q8+R5Lxlg8E^-NgF2!0bTdWTch2@)+hLTyR~QLuOYAz-1&2o}~l z@3;icK?mO)M?VKMuNERil&-(g{EI$+*rA@kYh5d-w*kqEb%b_OwQ9ro)cXd9LO(tH zh2N-I^u6H+I9q!^?R1V(TcIoQUT%s`=*;*YeWo%}RXuAa7mkb0tV}IeuJX(n4d4o+BB|IR$K;iep3{$j zi(c&7pzKq-P@&0!h187VXLpXRX1x5AFKW0G^8#h7?yUav^EXMmzG_S7 z6yuqhvN?3hr6Xt82&-l$E#|Fdb2$=h%$T2Cvb}5b+P9FMki*Nauc3iK0zUsnM-bVV z3EVKLf9`NIbE4C&Pu@IeZdJ)H=5oH^Tgkl=Co!;zbW?hENhq0b;Lfz?aOe3a$8F)d zJW+{(o_E-J9g3wLi7VllYXPt4J#=86j8NDon6AS9{M~f_-f(6FpU@fCE?Xv#2)&T(&{PTq?DwEdq(-YQ)El_}ry z)9QD>(Nmh?@qlufYT1GSw#f+E&WW{^T}+^o13BR}g3%B=*{q!alnTKd)Lh~52j+R$ zFTm)Hpj(i!xNE|<;$|PpNgW1og|mZ`v_BAmYdyt%>464@(Fy8EBZ~mI3Nw4+D9sEk z{-DK2aH;5nQ*=yTkyV@xc;I`*_GuUB4ogq2+{fM^TM{&B-jKp6xvsqA_y6|9k%Rs^ zm9O7ncn)<=dwkC%oc1`(9*U+RlEag+|B@-W^1-`ld=TX_{Y86A7E&&ev$cD8gv@(c zF$JsC8{YOUvenBIUC8gl+Rntvm%aY$OXF!kD8D8t`}lFl5wBAAl^%`eg9=BHPh#tb zH9I|@N5ikng?171{4f6-0bY*xcnia^pMc@Z_!Y0TBP~X1nzla2uz${3Rx^0*dXMs6 z=Tvzl()UfbD^2HvrSqPL=^eyvw{o{b{QnSe);rI0pLNzpkGafLT_(5>PB03}dNi}a zBKB#qD)kgyFX&}97TS^fZw78kUEj9-Ly&LyPsLBB@q}2(>tT>*PC)tysrVFBQ#SW! zzDm^K`6*3oFz=6TKXoHXd%=ZmO1-ZZ%tG7+`+Px9{%3+9Aou~S=t`dGjIS}!VBSdV z>*iwzpd7Fl>1>kkx;e;(CmqBn&v>OAS6YRj9lCH;e zmC{_L*(K0oE+St0hG)~Snm14YT59Z0$<_Z5+<=_1%%GZW)YXBG(*BYdr3Hm0_`Ec6 zOOXBOtk7}eH^%Y=VxpZpSq!NkogeRyv|HBZOTfU=3fM1z3JgoHoCaZnOX!vn5#N1< zWk@j13XgjV50Ro_n^?Q(GN$O;C|`_8cCXrAZbg~GQ?L;0S=?n;R~KGS;DJSD(t7bA zZ>=487h$~|dV29b=F`FVmJ1ljbQ={wv_gW*b7VaXzrbuOt(tf=yXmJ@hjzvPwq>Sh z%%PjzMoewH9z0^Mn5f-ZsE?YOwA=<81*vgTw<~^40Uck_glTNW?lYZ)2R)wzNzPPZ zel(CvhMvSkDI(|qRa@H-?=oPU`jxCPaIagr;Skx`{H`A}|Mw{SpZg7ooeecJJBJzN z?~dC+PZ4@y{0+k@ur=m%<*d(K6C%Y&2U$)(Y&slkR;;N_ADJi}Mr}HM?rL5jSoEAM zs&s)&yx$rgoKFdXfbU%s=P2j|bqKvdV07w|8ZdFA3FeYBV7o`!^T=xfD;5F7vJ)~; zF7xl|ZxDj<2_401ysTLXkyq>XV1&St)%_rqq`uzJ%0C1@jBXx0GSKe%ahwQtH?+ax znLtVpf5-($9u%BBl^$HQWn9`jc|?r;`{xMmYGT>B!&09!?tKC^X$bikA4$;TH&m|# z7i$>?_c?A4ej_wOCSrnH-5k~FsU*#(%yJDrHxq{+v8Z8Zr+SwI$YRUpv#6CPqQf1? zJWpp30+4OjZmt0M*X0+9&x3*%Yz^+JWzFYSWS{zuY=L2k6rHc7ieh5mq+kAy;iG`V zSW08IRFR*8g+2p)-Z@n|=biQNDCdm2@@Ip;Pe8h+0kaBU@};(;gxf!rroLLGk1EtC zw;N6`7-z4s-K`q&!NVt~Tz74ffC%?q6t=l6>sqbg1fd@aY}+~k>FMc zZpFP=fD)v|-Cf_C_nhywGtM3N8#jOU+IwVV&pG$nD{IX)pXcGDHL=DW-6YuoB?**i z)-WyI(6P0js-EfTBq zT2+xNu4KfVHRMvMh8x!(h84HwjX5|!Jo}LM?T?_~yh>WV;@c*DN9AM;jm`_N_xiaa zDa3W}rh+2Te>r1a7}ZS}U#l-v9Y*W0oRIBkJ_`hCT&d)0`n7+=!pQ&p1UKbeD2HLQuY6hB*&n1{~(>Y{f~>vzZy`Ds=BxiondHEh~^KBjBcBO6Oyrrc-iH@Jr? z*#9{8SLcoGU@8sXf2+(q{Flm%*`52a$dv328QUwi6n!5aN#ia7w?f=0cjb-_SOGil zp|MQCRj>=y5r#asEA*Hzxf<56LL=e|^VwXzQ^`KaA~sN1Z^t9y>u2>Qw_pN`g%k6p zcpxQ2{y%=c*lDT?cyA@Fc-mEP@FZSUvP9MeV=g(qSBR988zI6sGg7f@&Yk9w6pI-0 zX9D0A*~Rhl+mV(?%4ZrnH(03TMXo(!8lDNb1%?83<{$`$yT%UqGazvQMC@=hI53}> zpP_L@r6-QkZAT}GoAyzQ{dg>xnPv2xJBONYXg_*r;4d&0pHV%Jm9|l6CE2{Xj5>CHk!td7=4oGq;qzhb<)UW^{N&sKq~ z0gPi5R5k0?=ezj`iF7HBnPp|LeZ_zM;Rn+u<{!{bPmQj(t?Gl>)%)Az@vtO^k)1tV z%P480k1>Bf`B&AHK78BkOH>HCy^*7javx65hYY~Gib`Y&l(>8V^ft-LM$mi z+JTyYfiR&c%tPan;}r#hU)TNS+plf%>&Q&n1>w_)f&~-H=*GpeRUUfG@W{>6f$4XX z$J~x@l1z>|;~qMvIM(;8AT~`jPZ(P8Icxu?khuab9;263m+Od`DNL7xUeE4Qm0tk;f@5IfusJwb&WTBLu z^7UNv&P-NfoLATuYBkG{qw8_dWw8~QctM5`QCie=wUDkGLjq*hp11bY&_2O%qZHcb zv1OIeeW8-gJkTzm_)ws4bF+$n5kmTxh`8l5)BbAg7--Xv3D-!I`5bR;4~b(na!uW+ z1IVnwM`sgLjhFRCxOn$B8ik7iGq9rm0H7n6a5p(5A~HI7)-IQqrxELBs!Vb(u>z3^6qZ7({{`qX3fHQ7S;87?!q`mnXdfrO2``S z2~Kvq^mrpcAOwuqNKlT54or46+*aGH6kZFr75R!fbph3s5=6T5!x|jMGBm*JP$T$(DrJJ4mQiHRQo_d-}rdfeiuIJxmR|^OSZI)`t zItw27s1P3`pkQ*iZUU~AIx!aiU4m!hRiSM?d@mDRwMW(jFQ}=ir1Rd2(TF{aOODN> zV)WVdQVKj`1CHu)1V>gtAYje(EFBSR)20?{eal_Z{8>J6CoL}ROOfxP>gCX?ywN&< zm7S8FF6hFYN7sRBR*myoV1i-7$k<)b{c%ywj1 zyR~+k>aStv&P3rDgEqv`>X;nZbMQl-x7x1}TNIpdLK$s_^IB>!4Fq-d>n10JENX#! zif7_ywH_YBe#A}nf|Q%(Rj7^b%{)s(XkDc)8=9{BzB=L=8CQYUsD*daZL5@YM~eX- zv}E^6nE6S`ZT)f2+qkpVH~!NBR$gy8c+l>3uE@wuq6B}J26%Ec6SDm#%s2wX<4qF1 zPtg5xA35gcN zTx5=wgy;8jn;#h-LNqo%r?4DTE5h68w%M_;lmPXdel!+@EdJ-Pi0;lJo&l@U+k{vNg@Dzu>Vr9%3=Jdg4x*-L7 zTCYL3uIsSPZ#XXx$s(UGOjz|T%d2n$0UQp>=+gY1Gk|^|!e#>clryC)a>(^OINa26 zn_3gll%~3zJ%sTK!*&>E?p+LpE>O)JW1g@U#5Iu#Y5N(+sgX0SEC3heum(3WFw0_V9l zWorEyX{4mPPoy|1Aa5tB^fWIBTV$|XW`b04#02s|lqmR{F<4Fr79Ym=>yywQofKOK zNOKa(D|XCgE#6J4>)7B%r&l&yOzk1PY+R_BXg+bq%Qj#V^Gi3LEa`Q(kR&x7X1_Pt z95;?CP1W)$)s;#~CGP;F7|2&^S_%ztjbvSerj}j{b>x2^oSatV(W0%_(;^C6rFYD0 z-cZY^ji}@E`|H*?{-_9ZKfBeUhRL?+uY8>!p{U&g5@Z(wtcRU-5`is@c@&MZ@TPbp zA`vd31*bRsje=VG*<eCjzv+J44Y=fGxspvVw z!3b+~4gk0`;m9#m*-am9e1~)^^fOg&iro6d3KVR#WsLW#$+9 zFbN34vW5Q}y7DUhduCilCVqml^{>=6-HGF`@x2-GO>@OtIoNV%e+#zg_74<)!P*{B zYvo-9*{$c&{Foe<>p!dC?s6$G3I%1l7QIPPzuxq!kG)|wIe#3DB81Iomww(>f&D+oC{ ziAi{rNxx+*J*%wJx)d1Uls;BtyHNYnIB_BOP-teFmw5`&9M+du(Xyw-4bAdk5m-7x$IQ_e?53q`m#=-c(gsr?%eP z$lp;%+>~X-236;lx=}VRm^ZE2d727gpQYnAjMuaFhql)E9=S09D71zVJa6-@m7 zbLVfh-`Ki?+s1vqByIJamYd;XP_eNZuE%3b;|eC~Xx4i3L(oGedGoW+&3Es_8#-yz z4NJY~av+ginR2$2{4vwv& zzYFKp;6HzeanS76>2>wsSF2JEB2J=&E`;Aqg-M}C{cchGl9F~T_2|%1Kz;BG_~5`s7eg zYrZ|C8iUO=y?bLmxiGn=i5A%Qm9U7MdThax#p?mazzmT^3DowVWlMuZ;-IHfPba%f zI+8DgvN+t#rmBh5@`kpD&HD5bbH^DwTuoSC1T3ZKO~3C-U0-LzgC!3P=AN~<{f2Y$ z>BueOD9>x18kl4o8RN)({5s}!ir7@F28Z(lFgTaFeyKVdwG=f{ACG}S1)lfX5)+f? zFkLcIzg=!fQSY5;;LxqKI#DT6N_s@!pWcfq+y*HrMI42!t2@>Xl-CT~?g2GQk?i2e zyih9Np=lkk<&KFjKW)=lmv}+v!O)|(8BJ-8UZ(q}!a9u(hgC$`b?5KBqOa5U#uLgf zjE^MIqWhcL)zQD<2y0MF%(bmoZ(Sp+9%_X<9t&M_8%$HMt}WxyVb@Rcj( z-*Eisx1-Nrr^=fuss5Nw*@LmUa$8%G$|QS6#tN=mkCeKzfHzQE=gtqtfmM28Bo;<% z9sX;e&vBFm%Ty#&>~*?Sqj8F7Cf9STo|im4T2*#X*C^Dby@2hT*=!lHxLpU0p&a<3 znwUy1DNoKsZcfb)``XvT2^d}OH}|X4?lAI|6`N|6x4&> zlry_#Al3XJI%jG%;|?_OHyq3>%xj*g?U|*OFZ1n*$CSa;o#-E+7>BQd+;GX(7gRuc zW-J@T&tS1eN)e!x0#7ve5qE+3cT3`Fn=Xer%Xz}%?5T~>s=a}sQa0lG$&E4X(Zt!O zPMEyVFjCJ+p4Zg}$U|i=|COX&EzW3@G#%?X7RgpOV`DY&WUCANz!{JHRZSq~W^guK zVN77zezvHl=nW@KyZG`WH+4x{0cyG=uW^c!I-;Z|4JND5OLEbVctw1*VWpv)_>~qOd((f@ar-b|u0Uvv1jFo-*-^(*J-K(q)_d`II%-XPtj>HL zUqwG@o{D8#v3vYn^C10iIUP-S03qz{+*%y&-`c-iyQ zREYnPkOe~)kC$&y11zd3Q<=Yh&{3YQPh{oZr{rJimzzO^7E9E@)V>A=Y&ypwLg;L8 zRxMNjX=tUNqnhG&FWeVmZLcCE=!6lZHf1#xUx>x>N7z&e5v*v<+enQCnkj+mKp0(; zX+0HAMs<5*NpXj@P5Q+$=y&-S!PqHR5vjt zSg_pZZiy=G4sTOUaqQ4E6T@yN!%bueizBX|R9tqR{BeUj69pPyCOCFSp`TM?$dx#; z^y8mFG9~%7U`^~EJeKS7Qw7d5+7N4vJvn6jNpX`|eez0*qePG9U64I`sUMWTS@lq& zS*@>5rtDe&&?|;}Lz(zz)WOqUeV430NHC-8ZN zQL?r+$qDNuwM}KA(@=FmotskW#bTP}({mqT=VBkSaPHH?Feiga@)olw?jC_cZ|8kF zLLsWB=2@5UKw@HFSjf9+m@t8NC7B;sL2h zBtMjJkvMgVB0<#*(aPST-=_Hu=hV=eT7x>b7J;yxtdAFxm%?7&PK5C_B++5$VdXF33p7=K=Q`G*1j*It57))aS(@rCkuiWnNF14)- zN%_!S9|!Xn)wGPOtHV`zZ0`x0Ty#)Ek?iJEtf}F7)Nl(x6VvmnB#nfTdq>3QLNxvk z7c@ue)y)KFQe z77+if^76l&#KC!5$+zYwFBX!FefT-W)}H)sP3MI+#EQpXl6+dn7_Cst)~x$ zMZO=OF2jg>%vzCEO7QTOAb=3MNYuCD73*uB}CrGvUFi z5vMFzB`n@={~>UFXSjCfAxpO1_xc@Z(F+K=C#paHJG?^1;RlShhDI-Xgab&Kblt%K z3uQlU9JI7h`Ci5;z7M5J>;o5RV=SJHF%+q$DyU^u%+tdGkeXOyCZz%Z4}q8d<}!8t zc3ZVACJ|I$d;Un%O~Vzz6}~U2Ts_u4-Uo*pl?XqML|!jHJ3HF9G#P-H&!<}2nb5e% z*{0cH(2A%qX58ih_n0ZA=heoo4}iWe#s7*G-ldE3?)4xwY?S~rFyxjX+f`+pmAotPzP?Nr~-;|Y%EVEZT<%f+0?pY6q2{iaojp`Lvbvo0TaANy2e#4n~{~Hcq^{e!6IJHn|ZSj%zBT3)^^zv~-ENc>LWTB2lZ zK`5|foW*GSq4o2W#>RO!72MT_>l;|rD)NP0OJPe14)3uFBev0?*B=d$K$&4q=PjgD zW>-9d>F|bR9w;S&l*JM`0svC?zCnMTpI^7`bG2UGm~crTlDF6NJQhjEa<@cFxbH%w z?Ni@I2p2_2;%;VDvgdr$j~1shlzQbSPN(!xW`Mn?RtFRkZ~QP6$j|Ue08*YiQU9pd zX2k$6xBB6Bh`i>s|8h}ZVT&67^;$1{A?5vdQJxJFReK9V1Im~mUGkvSC0uz~zYv|R zfdLr&CzO%RT|TMkoln6rVIeTNWkAo^q{bbK4;(6H*f?6!*uYLJ;6}bAbgVQ>pVLuP zUbg4LB$av>mEr6><+H@&+AT$=0M*Z3Gr5$~|gTK&_u z=5@uvv9Ar&4KcoU!GtRudlc|ekpXE z4L^Uh0Pqt$=a*OFg9nbpvf6(J^4<~j!%Dth$elrJxwssf^*-YJa5kC=cYQ2 z`m9D_2+{y}U-ZTOA!8U}qVY4a;D>`h`oZpw(?f|C>n4@fhA3C4CMed$-Q^Q0S~lzW z^{6+}N}3(3Rm%tf&^G?%&40Fr{Fl1wkKS6=6Rji!FOA!>E*Lyr+VaT@m<-L=?--3emvT!#KB*k8+TgWGF(@WATnl1Ov@ZUL1YE`{zDoKt^anVRlQ7-!CNd}_s{5>T_MFW$= zrlidLI_^IT0(9o3mv0xPJ{R@5pk0KumW<3TMNE=wJn+eulJdc4z{paT$Bo!8dQ-;; zP4|ooGaFpI>m`M;&ce$|Q|uHSoUAG}jhX8x#~JRmdh_)dz563#FM=1ucu~T)N3Iuh zsdL?GfhDilwv!LN5h%U(hiqTI!+>XSSaU4pQ4&>(V0JpWsqhCpeXBIcET&^Li^1Y7 zNM+z@SNU~Z61!>=X-v_u8fx*Hk7j=LDGi*A+f>X828P408MGvS4-%a~! z76I}*l-#tc<2Zu2HP&*nWR+s75hppV{LIBY5$M+ay}bIbep8b^Uq8dd3@=S*h@mLx ztYp$raw{TCJ9}A#0+wny)qjnx?;9Y* zY-)hj*%cTSB?oJrKqLnfKUVcmUUH<2aFDmZ-+oY4Lr8mUu$PCBT$cU#8fgd66NHoz1J4924zPmL6ILJ0hKYCj^fFtVzDM^Ht#-NsP6)8On1EPeT0xPe z3qQh2frvA~EM-T?f?HHv{>=JP$lI5HSSvvTt4Yz|sm79P2C>NXQu=gBe8a6s*qy!w z4V<|+90@k7J2x&&Zl9FRlk}U(KbVnjB@ppz=$_na7Kmr*mQ9Rim`Hnt<&f0n;AG-a z?CD2G@6!75EGXNh^F_K5tZ)gDwOh}iCg16>kK@)SCD69b1ErJb2V&*re;-BxOjO4m zqHdg98gW+j3gcDF8g)lsoi!1v?V{=B>kW(@K9f)`|-B@Or<@S*ULl;TBA=;Ne{D4OinTp zV;Ab!iD#umyiMNP@#S?kBeD*R(O+S@V2*j%)konfj&JbrM$s<^P`7#!5qQigOj^*62#RQ+a z#)PkZck1L!O;=%iHk!@06q8gu2n0pME=J$C#hlt*CII8pI#Z9?+-f{F@VN(V%i?#{ zG)X&*H9$c(ssx%D5LCk5QbGd~Pii@Xzqxgr`=^qW@zY(o?%bJY=X5G)$!-eDAIk8d zf;>(Om~wonL}oRk8`?G@7@a#X5X7H5@W^c4P3^=e^=kue7;UtTOqRwI6ft*Kc13(| z=l(|3Q8L<3kbP){ae!cnWjLOd{=CUd5qc_hiXZWZgorr?pV-w#m?Gs(a`UGYfAP zJbvo?q&sV3FYJt|=$cXUxNfyG{9hO|%_i{XFzZ!6tT|rLD+MiAuuZ?#%sQOb>tB&n zDLl@-X%tX_uJotljg^VWZnwbmZEL1o;~Zb=n0VpaotGM@xv)z!PY)j4j{MWITipgH zv$ywaILUp+<-@^9t#=JXd8(;xh9(+BUxpV|8H~t-uyPo{GXOtBsfy&xsZh6PHge6B zPbU{NdZJM(5^>90i88GJVJnJ32oq|Hc9#=wp&R^{%@76e8d4t;T;&a}Pnv<{lCL0#vH ztEY6oIk#1cEmkpiLI)>wPin3D!2`%7YOA>X)${V;KoOLyVHN6@-5M!gZw<7@>oi!Q zu`s-Bxi}KM4BqivoGF-$wOoGw47>3)nMJ(1&23SdQoS>C8h@{z3o|?sbcDr26g&?n zW^X7BhWjqswl2lb;(ngGX(MHol{ar~%sDPvlKZn_9_!fyCLe38zyLWpKc<0f+%VDw zYI_O|*Fg{)G%2ILB(rL-B<#I^U>&fR<IM!Ku{e{>vr1Ssns@}4a>=JuYeti zhP}8Gb}$oWz&6-dVps+bQ=S7)BikBaC6!0FyfNA(O(uHie!7vI%G(I}yh_}pdx3j1 zR$E_EU^xjr@YtO2J%--@9`C=${vYj0i?Vd>AD0EXmx1jIJS=FAm)#yCz%yN>j{Z`< z)}*g2f+yd$w)F9|uUg#m;EpcA@wtSr=_uzBPlz?&%iZbI5@L*ZC-SbXy#1L5K!3GW ztiKnwM0vrD3Z1st)>zscqBFQ49!D)aU(M6q*4GJ-dVXFD@u3;r9CYzkveh(sRiLn1 zivWj8c6`SFqeLHTp-V(V2%oQKmsYWOvJKQ_(AwaQ7EzT`Wx(^ru6^jenGEOmD-qXZ8}*U2G#BR%ffW5;La&3~ zH;#w8kVY2he!92hDK}|7@q?`(uKo$Sg%(>XAB)(_k^%yyey0`weYTu*w$*Fyu!KsW zcEF9x#Byq3DQB9^o_Y78ZuCdLD-~``nhyjhcTK8*UJW$b$GLEcQ=RB~9#Y~O%k=?x zNUnTi&lu+`G{RrByp+S}&wYBhRGdJqnB z6hnrh#zJ|Z-1yt=$n9nrCCZx;+8bv-X?Pmm|IDD0$fwn@kAFk|(4x40hF?9o9v@jD zNC{UQ7-%QAQnTU8qhC%C+^pqMjE-}m)(L?Lzg3b?=8h&d^B!GOkDCu31%b7m^`yDQ zQ68PrZdQKyTPW_CAE}MDemEFxxmP>#p}=)vB&g{NE!C8mQI_VzY@r|(;Zo>AeWXiRM-cU4 zE(ho=Zszl1aC$bsl3C#4Uc{d;hCl5VoMu>txirF8dKo_j9jEc3+e%T`D|9tx>QRGSg2-BT6`H(3fv&G1vCs>3guh@1temR zos&3J3OWu9U-IYU8AD*UvwGcQ5n-&(NY?PAec1bHY5r;Jd9HB%@I9Iw=BBr?fr#w_ z>08I#9D=R`op1iM3+E2~hPCoruD6Lsm3d8yrnMAuc}Au+Qc0rs_wpMvSK<*YfP+U1 zO8Ee=avc-HgXy}TnqCw$j~%2?w$K}$(c(~8d!Sg`i@H0h~G& zzSPLvzW~dzsr3}BXQ5lkR;sZDN$4J(@25tJ-CZHs1nBBgX-|i!Q)$QjTN6N`^~3RV z>z%$nAs=A|Q|q=A<1Z78j9Q$P@~NSG7J#f}9)V2@h@RRm6M&{?GV-w6HSc7nkyG!( zl-^3<_(SKa?~MXgZfMOED5{E{r$NETa*$51aZlDKKngAuKg~MCwYKY?2G|Jx4d-T6 zIYz1Ueeom(lI*!;?7}szrpBks;rLRje1Xy@RvN5OFn;kc`~_LKZ0UDy2nlkZWslI{Ggn z3#!fP@kuui9+=fvb2>A;|ZLUBOx5g5ZL*n0)TcYF4UA4j#b&tWBwLb;* z`YwE#t4J8*v-P|)RjadBb2=H2D#D9t&me96V?^u$Q#D)RzLK1`3hpZTRcAz=itO3e z&zFp64BE2amuQIxa^rrzH_fl2DHhHeG`1~7uj5;qJANs=+8oCo z?GM&tQsaVkB>s5!H%I5Np2XBv`@NO5@AS=?_ z&fy1VX=WF-7mK80DbB#C3=Z(4fYQ8xB zIL0SLK93N469Ud%Kg$}*modHna2vPkbi3mzypo>A)+^5-D3|MNH!!ftLw&Yj+9^%? zhE31^(^C(rM{&lw6YdJC*Nk!BY4~e%d3d#fB7oB zFPlbll}5A9*0aZOI-f^UYdlknNJ#RjJO&MC2^6>7VW2bL4iK8^(Q!P8;^`tQ=Jm*s zY-qVVQ^5_1JY2fa4>PAmNK2%!dS89hd-g0~THi&PWfi19HGBM)fd2V(-8B8!j-C7B z2#==v6g;D2)W~=KT5fEc^DRrK^^^7c&$_MKE$s}1$>{Vuj0IzJL`F6JKJMK3#v5SOec$^F1Mr}!>r}YkaHt?njD-(6HnGN@T_OP zASb86(XB2>mZ7262$7R6L4&TS5~m%%{H+Gs-*Cvp4a0kdW}8H%1?tptGuc`%+?{Kg z_!JG%%Ll}InZpbz26_Y$@2Ocx4`ZW>X+xdNVq^Bwwv>tC#DJBza!Mw}PY zc4?%-!Nmo}5BbS+rZpka0)F3Hzr3)xh>i};Gvh+dQ##5mxy}$)xH9A|KlMzU{QkbS zN;GcXTl4Z0ivmQzld+BokgKl0@?7AUn7xjTkdr4TSy}((olZOu2@s?h(nw6vhvZ;Rd?>>V$sayK$Z)gygU2s-*w6JQd^NF4!KDG!OR$w2D`aJ& z-bJn`ImdG))5+|l$U~}h1fHDpC8h)PL}uy2RK}_|i;o>rKoa(MZsRBe*t)l{}l?exMy*C8L6lm-IJK z=&aj#C0m>QB18VY0YMDu=Au8Z7f{Hb_pWK$SGUX2v?_IeOk~|bpBA@j=pLP zQtpfr=lE;2W|wHxxXD$AC|!Wdn`Mtk-Rh04?_sCsr4>j9BkbzA{DB|CrL?}s_|D{k zYC4B-S4L@pLi;H>PSet~EqfDCYGFVW)H`K!0Z%XV- z6^8c)TlcZ>XeaU{xa>Ea>t0xu|Ng1*k86oRUabbdRUb;4x~mUHrk&Ox5^Fsy3k-t) zh~XaZZ7*3-)OVgYlesu;BhhWC?X}J3tqh8n^_x*F96J5^h(&aWJJ)-C`WJgm?$(>? zqN7|JE7?#3QNlj01~x41_5CsM5Rm@YYTn&DY)~D~>x!eVZ^ebq$GOQHTngGP1moTz z`~6F=q7ihvIB7zu(lKIIyd5U|=A?411iUc5O_?GhCwK9rG%l@;0pls`CB zq6R=F@s{sG?bL;Xx-%+Y9dVtj^gqhAMlCWeAyhuy@T$VtdUH~MB{WH-sqW-Y|K53V za0uOYoV*MhLZBvb74aE6czo;?CSA2I3a(>@0)?M!T##Mt`S#5neIMaUdE?LN)se7* z@BGzkdY3ozHf*R?`Kp3kM?HSl`08YE2X?C0upNvXO1b#WL*fkcgJE1 zn*^&|e|yvUr4y;nuDQZ-piKU7mZqKI%|m}lZwCl`X?`;G@_*$u4vt7l z*FI{0xj?;nw+K#16|NAtg=x|&;CQa^i55jQ<1tBYh9!by;#beOD|;t=;2c2-S$#5j z=xWuNIek)6rsSGwSghuRtQ`+o<^%trb)S(*;Ld4B|O^b8XLH+oejLg>uCh0WzK%^cV}c4@|f# zYZNGVaO>j#5`Z?$$?y%^47JKJOk&v$`AT@s)~Ct|Je1{Ar(+r?S0HO25&1}2El<0$>A7~|v(JbB+9KGGFfT0#sW8*DulFvM5&?&VT<$Sbj5m(J!-Jeg zTSD=#sz+z6s-k7e-rH=O$4jAc`8@=#zD6wb26egDGNa!+TJAnMr$NH%5$Y7W%;+qk z8GFvp{}&Jc^YX1oL0I7oSC)#jL2@FRb|OsWt4*8mQVBE2S1AvRvwt?wP*z{5WTh|& z;!zGq@U$mY3OygIeqOq=HRb)XdRrfwURTvOtG*L#3dl&hLTB?cBk`EP=o}=oMHbUX zR6_{B^?)kii>*vCK99?N+^MQZK4aQcCBmciDad&Wb3?>lp0<%mg*O5MP=UjPjX*>6NrO?SCAG$ub?2k>wLz@>FWNhBfhu)Uuek*tUR z>DK@D{1(5hWDQw%>GbPxXUu6t(H*|GBvHuFgHA#k)tbD7bj;axqk{Xor&t|m)bj9G zx7u{OV@eIT@ga(%44+d-6kU>uUs_}bzkt+4FdxY2Wr_JRD`1~NZup{EubFup*_c`A zuDweAi@9I52N{ZuoG$o!XQ&k)mPp4)RP&(4SOEp@r^R}C`P@OEnnM6UDG+|i1)@=W z^Wj+&yRCZi9*;E=w%Jg{nPP2Lw{hxi7r(x?HBBj+lf=T>A1s@wMY_yf8@A4*7ybn? z1F16l@c(w4ue8VolDADVuUGoTg+FFqpS+VrLX-y_soLk>bHUUNktjKxY=!H;qKXcX z5@7-m&0FhGunP;P3K*B@U+~8`kA8pU{c{K(TX`Q zv69;nnTcOb1yrj0AwZHhfeC?F=CvA=D2Q=TXY4*jHd9_p)k&HOc`Tuz#?(Xtq7!yMFt8e6c`Rv-g~6)g_>Hc*}C-A)qJs&pt5r$2KWsp zxlrePo*znke?EvphS@?MF36olL_zZ2puL$+FAKV;J3$B@8KW(GBd37>Yh%-}PBZd&7`_i%IfQ}J_u6vl8kuo5GChKMN{W!*H|7MrnZI%rDvI>2fGK*W>o z{lr8!SlxOfKHJ%{iStE;Eh2$QMzg;LyU?8|QbrkSJz(d-pBpyph@od$&Xw=$Ub=EM z2jm~O>^9$|NM1ac&TSjK!W=`wk}=N#K@XgL(}4FbScT5ZPDK7L9I>fLUhf#xciK0 zEFeHnX~I>oV0~9Y2>xpE@<7R)sJ7J83k{8NpvxJJZUeHaQXUhtm<7D~i)Hw~#m~8T zKVO*vxdoHvgVJ-3Jij!FkFwCV9vh?0k|O9u9eCF+)M9xfne?LD6o~&sgrsfA1a^z2{~Kpn5#2@E^)VA z^wFpg()rNhQNg#&&3XN}Ysmt{`m0Ml2^61BI?g?py#ey{5E@=zrN!TF!lvxG@lf8h z)}RFYNrThy?q@TH*p$5!=`hp`b)s zfRPXJ^K12ybz5GOj|{X8f?pKLmd2@c66zzoodRS%udHlwBPuC03{DHlg# zGlA@poUh>)^4MJ-re7~9qJAW2PH!9*SQ^Hbc{)?Eyw=N|^)zW_E#8JU1bf$RvmEMZ z(SiRbkF28vLs(D~-eR??bc>XR=3e-zCdtnh&qpjOGpbk;F2%-zVv4SE?rXJc36Zr$ z^6>3b;pY#-0sO_^{t>Z%oZte+Rm)LhSvLAyfDHsd-DcXCkCIVETY;$GK0JNEg0#QF z2yg_;DKM52xrLC0lo(EPU#TF52s@b?U{h+VzfL}65k8oJ1_@feiC;a$fv#;<;mJuk5b2e~s6 z&}YpS7P-coSR0Cmn9CosX40GW5gPtj2_uZ^YrKqmNEIGTf~_N9kyR62HojH6YMAp6 z|Ns9^_*{!n=E!aPMK%Yb!g3_ZVWtR@BN!S%?@JnNKs}Q4toO(F{l(f*c&UWbx4vh0 z3`-!NTqVo3!2+VOS_P>xq`mKpYmC?@C28R|&^QBi=VpJ#`R9E+)L7|C7Rm#_9KtPa zq${@!@$EEDwJHR#+`?X@HEuU18vt&-B zgRa~=XuI0U@~#?;i#@#P^)-~Zs4b34$s%F#clhz>s9y*{`5j}9X$^;_N4!6)YbO`S zH?^hX%hPj!8?zia6xnYIi}!^{NDSb5XNcYdB>kOZYcKKNaFmI1KQ-|DJg3I19)Z*L zObnPd*evIb)z_hpQohzVj|f!9X7PAP;|SfpLk?-s!zfIUJ>J9^qkU4m%i}}4F*RHR zEsT8h=N5Q|6OVe`9XO<=0ysYWGy2D?%AeFiw$2Yy%!8?g={zR!*kR27uAU1YV!iX@ z7X1dkk0HvQrSmFvjDPX~;Z=_m#%*gyPuhAG*MyJ9<`Q$n&)gK13h_;CJo4VQV_sNq z0iEO~Jn!`-_O_TZe_Mxc{S8NwE}VKJTf%rLm%YFB{OFdA1;Okm)TxO|ALTUr@bgR8 zTTVPRj#^ZoC|hvN(rYwjq5p@y_l|0++t!D%VMPT63{s>7r3LAT6r}`0fJo?}DV;zN zkY0V2UL_D9RHcWi^p4Vd38986O+xRT_lxJ=d){--z4!Z_@%{OYU&eqj_a=<7=G<%T zJ@=Z=d>-jLesR$(6L4E`>S<|&-QO82zc9)--H|MGu7Z8+d zEkhX#k7l1aL?~J}ozPf^*N`}!N2FiWI6p_T^AzNL6o4J%nq9$0;htJ8pTUJBqX42A zHF%!@+0pF5S@`E~(5#n8Nvj^#EcUMhtW=`tSuSPhkKY<(^q;RqU$MoR4hw2BsjZvG zlM-S(2WTg=W!x0xv|B1m1f?fIA(2C4Y=ZpZjd}^6)Tl)Z6`BKx)|ZLa|J8}i{NkU3 z{=Xkxx@p7zwugP?xECSOJ9-oAFvw5I$mf7uA*>gF9#iy;^6aZ?72_gMcWM{Rg8#dTls zNzJcR#K@(}*6xO^u_MkKCt67mv~}l~iPD3hDp3s84rnV1;AqR$90%-(I;5reaoj>o zR6rbj5djZrr&_s628Hk9SGrK@xuqMDaW%cK2Ut^R8>`{P5G*~1iS=9Alk#7hCq!?X z1Wu#kbQa#9D3yD~nP97i#6Y7E1@;taN}{(^1~omW&kNfJm#?TyBSYV3i&?MZ(r+bZ z-w3W&Ngj}h&kMnST28$ji`<>(4eLJL%xXu24RUlU={2kEhD6GaO|vHUtfqzWY+}Ii zp+(MUPT%TT;Sy2InHDv`tDW*+15Snz@{qMeqSzW7hS>&Z<$S6KZ9AT3g1(Xke9*Ho@S9B1Hth;3{NqavjsUF`mw#s^K0+lD|z+dx}2I<5K6DF}aqxh{h)Od-YOxM8-SK&%( zXvVj&hC0tG%9MN4{rlSory-uqdZi*)UIe=-y496m`B zs*2N&3Zd1`DD{=*eCgg>FVoF`@qmK*O6D5FYL83TG2f((hSj@Ih1mNih2y#S1$Cn%mH8}Yo}{mKjw;wz_c0Sv9gAFjzRzE2tgXsc z+Q#UDBn)SyN7e+=mdq>yO`=G0Ke|KPx2NHl&-(P0uiY7Hymu9>CwT?W(S+j^Hup{8~xs|A$r ztOp`X7#qH&LGD260$to}kE1JM#e~kw7`q$35-#zK98mTv6m=LJPdDFRPc7Rx0>$>R zv=zR*W$nEYTq^o(g(uKKQu9v=+j_PyhE!U2whurXGM^TH>5HvBx7&0&t9+WC-<>7t0w-F*uFKy0!BPK{ZI|WqHQKIAIIX5Rb$k6}N^C7?gZXSE&OWn`3i{e~>nwk$~Iw$sYcm(|s>1PBOgE30WE^ zPpqnT@HXl!%wBHv?G$bCSCtW#n z3^weayZQdD^+0iHB$bj%?Oy44m}rKgcM0lnqg+`oNN@(9k@}IHpYcJ|yW!>1V1?QLSwND+lP2P*XyleEUZp+<3TR2-eJi1>K7?u(0;q^c@j55^7u>T^q&98!r~ zluE@tl$C0Poi#5Q$skRj3!527OPefTkbOS2bn;V<<2wxI?cwfm`aiIizjlAuhKOX`Ic%Uz{soy(oqhl)=L?i{RWm{{T&{j>Z0942dPR1RD;5g+mZht|E|ACL zd9IdG(zdnoNsg}U8)Y9aZ<5VhURw*rzBUCC|EkFC9@()KB-AMgS7ZN%mcjeBg-{km z@O0`8_)?*9;_B*A1jIMvVUX!FriQXzDz{uRLEat5$L^;AQZiOuZ}ZB)y$LAWzJ!#e z%v(S6`E?WQc-A59=6{zUl| zTA4;(-hi6^3&n@Hs`Ev?aHEY(sz^a0>g3IYDf>F>ShUH`ud*f)>63<#S6-1| z03*9rnXZA=VXo!c%Lx0E;^Kvg?{Z?6rK)AC5_9D)4>~HeUsonKCnFkGYvFunJAc<$HcYzuhvZRD7&)227KkQujWS1dt2EGmp|bjPTO3 z?9tZCfy&~`6_PQYq~n5NBeVKB2^%Hy^A>RTJeyoDu5ewUrC zBeUAsWxB8Yx_C?K`rA~k3sGz?w=Kf-12cZkF#m*L={h=WG10&kM@EaIC(*WKK=X5auJdI1OX$ba4IEO_aH+~ z2jBD#MBen!bA4bdc-Q7CN)=|}LcM7CLxzFLB&2V;yVJ7}yLEo>>*C=B&}%AEc`kua zZtWIrsC{qf`ifLNMf&swL)o?M18Ndu$iSy7vD2PY<=!YySrG4^6zS~Bq8)K$?Ks$(>9L3W^!R(@ z8Sj~`vLA!XyZgx|%`4~9YflczQ}Okq^z;*`w%E1oDTG)9yV!n2o@$l#J*HC{TU@Ks zpA^A&W>;Lj!nEbXDoPY;JX_v&hqRJ)JZY@?NwPVDfl23=3tt$0f8@Ne7V<5j#-pu2 zB6BmH&o^Ahu3PPNTta$BrPDEWh3#nb10Wmrym~Dq7Rw)(qym^!85ieF+(i_cG2~s{ zQPB_#hmc?#X0wTFJRd=yX&1Bi(le>(5kN0e_AAl4aG1jl@oBZ8yTqMabs9_`7M5@D z|0?xonc;&6{w^CfXgfYj!ZRFBoJM4cycz_d&BKp$~9t$Bwc6{zs>j%J}n6 z37SE}8FzGpnU-Lyn!Eh`Dh`Xxt;~BXVHCmYcx^l)ZRbbvIPH&33zNzV6wK2nHKdZg zWQX;P+INbdygI%*RlGcYl*oR>StXv7;3Elea@b+&yKQ@~%!Q*;Ms20qGBT<#?iNOH zxeKEwCfNbySER$PIDF9Qiz!cK>!x7T$~GT6JP#NuGeJ0Y0!5$Mw@5@^sO%Oyw?Rd5 zG_W!L#VbZuN>I(Ax^C5`6~z>eqv9RaNt=Q}x-0qI`a0ik*}Y7!9y{k!XZZ_dvFZS`T|@+qGtmiLEC1U$F!1bnSMAq{uBV^(i8t+nfBKFOd07VOENYIbxva zVl<@T;o$uRV&A#HVd3Zc!H_po3(vp`^NF^{F=pmFtmF1mr^kR=ev7B;85xEW?(KG1 zptg})#l&a6rlp81i)Y=6i6Zt89j9uBba8@3`bHxrYJbrLoe&aJ zK6Q^SdN~X$IdekPyhinFN7ymK%fGdjijC2 zz~(7ujA4o^PKjQWaa-LhNX(|%Buz^~-D}r6OncN*Imb;Q@YL)*>?usJ>`CYcW$62g ziiD1Fl|uQ}n(k!@TtG%0tH2wJn+p6oyb>i@UL0r3X&So=ynVA4vMTLCJx~b6=!4q~ ztqr_h=~jaqrzm&)Is+|2&EQ?WW@v>pz_|NIYl_P@VC;`UN&A|ixg@7kIV zw0gAa9Q`32nksVPT*?Ion5(y{lyC6Jd?oR7WD~{!)LVUw6giZ1Lxr=)T>Z&cL?(5S z%A+NkD^jDSRXa6h0IS`FAQkj{y}{u^IRV(3zqVch(CcXzE2U!ix$Ij~QJ__#-;k@` zcUn5f?~=(7>Q7w^-cjt-R3r%*MTxritA+EB+K1^LodFx>pHJn?p9YIKcZHaed72{3 zQdBXiSNhBn+2{HxS->R3{t!Ndd6Z~s;P|BIFcMRC^~o9%ka6C%`VxdI!OAR)D#=`( zac8&f=@wB+PprJX<|;)Of3znR=`^UUT68_Nt|V7NO%*+G%%BaCmiAFNr{IvJ{RSF( zaHHhdP!Ugi@mFPRnu}If)bL)%vx8c1hr+Z9wErRh6J@s}du|fd#g8^{>}TSAai?Db zQG?9)uXUJbg|7d812Fy`_>Ya=m#!lpqs}gqdY^X?v_E}28)4lRG*nBs{fb@aE0QnA z$MsttWSR+CQM^wcb)5dus>M{kw~{1$#u~kNrH+zh*k&v03tHgLvAb96RpnIcXe=%A|=mz%Bz*i>SVKCbB$VrPTe;S}4l(RBChSPA!n)Va9HMAlwW zpW2Q?@Ue*^4yIKR&LSTR5*NeLq=Q^(S*tjIq~?VcC=55AFO*xWdxa^2)*j~>-gnm7 z_Zcy?7)x)JF1I(bc3z1Xa0V_j3#|wxLf>wPk`>F2$sCz}??3SJt^IrhZA|s6up4xC zRUNS%>Esh##XZ}_L>aiwJJ|42m;b<0=Z}AatWiht^(qX>6{;5|2$R8}=!JWSpwEq1?@ZY|98C8H9NjIr24yXO~?tWF`9+gx| zdhxIAj%rlyz}E4a%iB@EP7kzqx}dXHMtxDGfBdWCm?6>RUFVP`i%HdmPARPI_su=E zlE>-QOO$3^d~qP@ttb|#Y9>^N`C79|?-w!oNu19{I^v3=ia4|J$8NC}T96UFq zDWD8=B}m^Y(e{vCcxPUH=D$VZKTn9CgiKTvG2H6XUi;jH8|0=QZazkVxs6Sr%Aoti zaB@u#LXJED@L-wU=k71d+xW+_;(-K+ygb5qNYHwKm=Ud z;P5Hn0cF|L$I5^XzNBiE&{U0ay+0Oy!Rg@qtIpTzRLk7ByXm4&vYQGrLL-PMKYgFv5he96|0Eq-Manm(1EqMkvJ$`e8E8l-`>?`rl&q*ZB)U zd%lHCe7}SM{CuQzehrj|NjEVY{3+c91%F9@SS#KWRRbKHufNZ6xD-88C72?jQ9Zfh zuow~$;F90c|L(Sx|DLO=qh==CKwF29@Img5{^ne>Ss`n&_nIn1#>2-|Asn^@E4-Hj z=lu-(c}u1C$e7d{bN)2Zoode{M=Ec3hAN0@JKy}Mj(8I?EB27TG2rc#Hsf2_W2D5* zgcwbF#;&(3*MgOG@@(U6ldftv9mUZi?=TGPa8kDm=Vc8SDRA8nS)em9js#wvYmEM7 zW@ZhC`2!)sIYI61F8?mt?q4JOx8n;dJ&80}sLIxwNFHoq zA*G+TRKe?M_r=3V=Q6h{TlDoYjB=(jTrZM_OdTq|62aTS_vJSV6H84Eh#&4zu1k{o z+?AqGVy0@6DKb>4!QD)3g!7U_to_ zs4CljR!$~{V5P8Fc6oE@AlZ8}^%j;S3k%B*Z2anr|1nJec=A!5I?6NlskR|*WzcdZ zAl1}tEW&f>D8!P#%-XD!qes~edf6;qBNF2TeVaX}zQ^DhA;JIRf+%XIDu87qlldD` z=q({%GS9qP-BFFD23n$50i?fdVI|1#7M3n3I{&#^QyIqL&+-y(qBbFCo9mO8CyY|H z?s~*ShvaUy9eKULZ7Ngt($P{SS5)3y^ipktrawBoK3$j$02@rHpY+6NIkP)!?}q0Y z*eAWoS-Bxd>#oaR(~T@O^3c%Dkg)LCyD&I&$`CV6SpKA4*F36pLJFYvjF?|sZ(RO$-H~0XCy@Y#^$3&`7#C`Jy%7M}+cX67zX4*doxnf3h zOeDb%A;9uP)MW_jI)s`=iHzV2dhf*d#QLgQ0&|noDODD)DXgrZ+PB$Z_A_C(Ei5RG z6WY1p$f9$lD*}*n$hP!>jW^*xLuR2c-=^J+O{ZQW3IOP@n^iLrU$~eB6%3F_ze zMJ5f{qa>>yPHV*d=$&n*44XKO@z*^knoBp<=k(v{3a<0IJ3u7@zLah$f$m8*Bv(EO z_l`wggK<0iZN}jhcXp}5DcZ(O2-eEKIhMDSqg2}DWN$b_$_;-$j=hpC` zV7~In*Z(@jC@3y%dk2^o{|$3i84V53C+pLm0st(yI|K@wCQ;N-j#Qnas=l7SP}3U$ zq+qX$8vb-SIn-knwu9!9JQdE3yfXJWI9nWIFCT3^Zu~OQ-+ISB-VH$IJblkM!gD8BaX=@)wAL@y)zZ}l0d z%H&ebNvqB%?;kKmJdbU9#14`plPl^3TnS6fvnAeqak;HRZC*Q~^4Czex5sFSL#uTg z{@zWlpUNkh8w5Q``a8u%C*1dv&S;?LI_{G z%l?ebX{;zS%e2@pA(k|p&L#^-3yA=tsHw4$PBt2^=uwmPqFF15hmB&I#};wlFt5`s ziTj~IRqo@wa}(LRRyuXT8`;-G81CvaKS5~ zvWPEf^kw1l^5k+ed5s^AmP@6EtyXJ4Z!2$R;G+zLA*q<7RKj9So5JuAs?za$WS9nd z-PO!-H8&BN*9l;nt zltn!G1*s`1$Yr>INn`Uy3&X3bNtCgCU}F;~OoD|Ag3k2dakO4DdcRwvezy~EmA z$6gyDqbs@X@H4N;f9py0trIf*bx?c%4-pnNu8x@AkZ-DOL^wi3G_1>^2%P00Lz@+5g5LW?rMCq$ zQJV+`5K))OKOB&k)b{e^CJ4Fxzoz{K9y`UV`zR*G&#xx{Z}>S#S2?)U9b7=~H`-W@ zAXFMIkLobuj&c+iKJ(iv z_n=4#R|8SjjG@a!4Fe@Mjx1S-mpck+7e96rrfX6Z;9D;vCe_%3^%ZH7@0#YxEa7P7 zXPFV_%?WPf0y9 z0LgmPUN@Z5cb#0ugS{)qJP9KI%d8>H`lHyIMiNg=II8D$SLL^b7G4rVz+lUxN|o(% zmzgw?eZ3r3N!;+gMq>y|U%#mEB^K*YjY=8aQQ40<1ro+lpyz6HA+SLbHO!yYDAb(5 z(%jXq!=Q#x!GA})TUA<6d7&q9krA$ml|1$xa!t^$k zDChf8pFfTZ?&W9!=8C$%Zuxn&$f#~vKN7XQiv*<$bYDWEecC@W2LGdj|8MqdruMxdnfo~gLNlQj9)#|*>COkEbWtWm+2cx221D%8vsmTA~%N3E|P zO7cNC&>cYSfAO%1p=yF2EOEE|#>!B{mo?%uP^q14R!`hyPA|yq%;+8mjz;qExO}Ls z?>!)ivi|3~Le+lBGi_obDtD|b!|fxcOa$%{NVP4asFw~VC7o~@(-;Cd!Yb!OqfQ=M z_c)OB%rz!pE@UN}ppE95tCw4m-RY%@D@<);kAZ47OI-o}9^T)1lNxf?q?Y&Nc8A@2 zhf&eD1_0BpneZPN z=!LNkCxI~Kr0WoM?^Z?9({poT*URyMph|27_^@|z1+vANXV&N_=XIRGyms(VriGjR zLLAo+x3|$HEeXv+5_Smzx*iG`LFF&aLfQ^gtNlG!!R z55^|m%w_L7dPt^wJKnr_e&MF6)cz*0!BejBBzShE4eGj^nW#Q%{-oLI#z%jWeO_2x zwUSjsC+`@@oo!xUljlRA^MJ{Oc8dj2IrW)e-3_nn5O*xqlPcx@Qa~m|a92=>{ldok zf1Ia(xJnNi=?z-E_OEsEUlX&OE;p1+TlBn`+IcT(jqXq^Q8>Cuwk1F)_xGL`Yyej2-JRj)A zFq%<1)sYy?Hh}_Of+A9@{-pTf7qctd=DL%)fIb_3M1V+U)OV6a-&M=U63W&7aeRNb zMJ6jz-N%s3leCC{JoSke)i=vhuUD%Rxj+2;InO&Px?fvCuFqD77tPgEp)2?Pa zX=+$@M*lh&RpN)5pQtL~(i*gxwUIJ;wMjPaKWK<1WCgL9?a6N|OoMVPkZ*0*va6#}R~}Wzz!(TWs}M?SH&nH; z##!Kk0d89re}R~W+Xgzpt*O@XWULWFr2|4Hyc3kZ73M*IE>m1w5Ut&c7!oykSXxjj;VOG^0>ndb|6Q4ccnn#P3@HqpT2TPV2ER#UD3N=#lP}mYy@`_$~qGR zm!y}jW%cQ8XItMyR9d{;w#A~g&g{q9KRNeQDNKjHt1J0Jb$brsqSiMeF_tLmFQFff z=OsNxP?0jt_kEuH5@w+iHr6dcs01CM?%0q2NimUjkY==NcnwvimT7$K*ML(>y!cWQ zHjs}L@{2xulq(UD5p9OaR4JLC5_xo}&Q&TEExJZ5d1!T&f$*lW($dJCZYO!SP@_}l zYMW+tZpb`gCr?NS<(Ckn`V?%9;`FsfIv{VbW{PLwv*GfEsX;+UY%<@^P5&#yR2gR` z8uj9h!1c~7QG$k0E(?QjP4}+E#}oZTB;0y($`t-na4dnf#k#Zj^Tre^Sa7Sav(xl5feb1r#)@`#=FL&EXW7#T@8|Z~a7*%;$a%M8p z@Hk~KKovJ0>m#34y|)+mr3s~}H?-qG8A4=CeL5xD(OezS9y|xvv@m33*6v9t#SbT% zGOo#zWLv%wIh_Bb=tGU%PC@d+m!az%1j}tUcA=x|Om#^jTsh9(e3gqUM;}fe*Vb5= z93&K@=A+28&~s0#Jm4C?pa^{Wo(wzN8^hr8uzNH=DrYm7m zWQgtvUA5EU@Z;G2QlSy^fKOMfL8^UXVFE4qWh&HG-|0rC7F1^<^3v6f1V579cw>70y{Le6|Pa>LhM zF!K$;T8qBHyY)6D@(Mbn>ls&x9`))oH)6QbO!;>4^sXU;#5 zYnL?Thn}t<4rGb@4n-V)A~kS?TnN6^X->l~8TSxzT?ug~CMU9=T(1kb)1z;;HkVV` zWhwG29iTJmz?tfcv1pcWras>7KwWod`IX~$AVk)*h!97Rjvw{`Dqyt2ypy4)3G+u? z*|=W!<6j!FCvQb9Nz+{HrxeDIM9!UHRvJnMx#7+~ne_G5YflPH#C}PQZbJvIITtR7 zpSp?gRte3VTRfM(JFNo|10JzlMy`K!vM%AQ*~BC#EH{7!1iUtpfpD22pfDK(omW6v z56yhU_lddonFCUtA(c{@IbsLm5Qo*{0zD$rW2w}VH{Ah%JFowKTl{US!NPiB>Gn~pJ9A6-gY!^~ zgZ~IkmED9>Ik&KK^Hq;AEG?PiLgM2|IH%&l*&GHp_*xrR%tedz6in+fx9toCra4q3 zsxxT%XBv@N+XR1eTZjx~SeNX3jC?2`t>dhny3|7pa4rzh21+0;i1}QGWBUoiMa38{ zi&MA|$m96hghPu{K>Le-a^c@Oa3hQNu&Pzh0=Yn%7GBi!Q>F&vGH>+D*7>w2BIc|X zXKw)nowKu_M8;_%*DO;e5lhOjMzk^n9MJ%5lnDLO8s_RvDydh_)s1x-XD}_~2I&y$ zw1_SuvNGI;RVY>|=iEl}&Tq6sxN3F>ATi5II_r?uC&eBtf?vN~CcG7xb3JQ(-}$x_ zcPO=_^F2O}=;0DJP{n<(0vj0~L`?d&#ig2m@}o^6b;u`q*EDEpiBHWuMC*&KhDK8v zL;3{QlDH6*R~RkEAz64QGYg-Ydi96f10iGmwC{uA2WogwtUz9suX>z5lgqGBMmrla z=Ev6gy?iD1Qt&2L8!VmpMfw!uvk^xvRzdz7s~YEy zaY{nJ{QNVHpxd+^nGlC`c2HEJlV?d*pwl~tKPk9NZ9O?pI*JXsXl<*a7n2?5l6e;Y zq^ND5PtQ4%{=#?2FL@mD&y7Y`jXFltA1u~@EX2FT*8`o2dzYPHUnZQgESf*1R-q&@ zKx6DRi>0waJ}c4;CQej?U|N}`-^Z=0bA75$DNomV;TY?pnJEKxP$ca-vyh4Q`Qq4L z&s=05jM&nw5Ihr7O8hj_nUY*WD}Umo6vx=CR9@H;h4#SFI-NmV(}mAudwAFp`s@x~ zpDHLN2-mIZZ7=hb^0-11-Fj$B2Xh4{VeK{$`sp!(o&8cZt~hy$>Sc zy5->sn`$q!3`H}W?q=X^oUj~of)8aVjXkuZ*_A(~0a?lH_ta5QF8zN^mIn>G$FG`? zX9iVgGxJBF2MJfEAqI*Dvezd44*Ui9$Xz%){J@G=zIfZJ`6^Z!+m+nzJRe;hZT~%Y zbyDxRJ5I#T=xueTvw>!lqHy(&p^<@|rXvKWxaCTNRDWEFrVASB-Ow&;NoSmlILK=j zenvwd?p7|;!kI9D>s$yF*^Q25&{!CGtpw-zTJ#FT^f!ysw}Q z2j{s9NLJ2ivXAY~>3bAAn4|u8=4d(eU#|Rz#ppcXNZeN~Q?Feo5s)bE=qt-*%3&kH z z9pEDG#PL@K@=~yd6ZUXgg+q+v6^e(A{?R)TufEhU=gAgj9hHQ18x;*;iQ>m3lBCnp8BzIMbdW z8!SI4tvW)Z@MAk*a-+s&Z6w_3QaJL}tiih?$x!#+V|}g#o{w|6hFS`aNcSNuw!BkS znKPbUxI9{>v`oD0^3@Dm7XAI#+w}d)6BHLVe1To zu}vr!?hwtmvDRStewCqzIS;_Emjr>&9X+OWDR#fxT>k``)r#rLSsmKp?L}; zT5kkw^Eyo?;-24C^X`3^)n|-(u7ntB;!ox5zyggyU&ku%P$r=k@hfUH=(PD5j3e0C z{lVYp7cS7*SUNp#o$8*RpdznR@~iK40komEWFSF%?+;o7`i2pX3Uc2uyNYJ2bKjMj zVZ6burThXXYcf~!H@$b70A=9CON9^bhj=JW=V+U|{p5X8@S9VwyOyI8CYggz(S$<` z9yZ!#86fVD$A)iuO`o8&%&P#Lvmw6o@k?cLKzcG)<+SY~T(vp%66dcGs}+43bIlcY z1XkI?jlh^egYh+_M#qcJvOHcdRbna5E{+yrLqMy&a@vWH?~fM0P-74r50tH@an}Le zX^i49-1dmmZXeNT)2htn=h=^_kyg|Q7D?sIC?neT9Vq=%;r&vU#hT3PHDz5#0iQ1d zv{fGZ_{caMy$CBV%-P`wAD8pv{^F&^!A7)?QhVDw3WhBlN-s~U!Lq^Ewjn1yTff78 zIyLLGLRvv>7`udnWOX4TRJjIs+HSz_m(e58A7;$z9@(9Q?`Z4VKqLy9%O)-)ZfP;hhlQs5rz%&zM61d+J@}}HpvRxr3m~@Was<4TPbnwFaI}}P zC9l%SD$%bp*#p@n!SY@ihtlHeT#^}0{O^Zr5buYFJ1}nA!xe9D48Ox~&$9uAo^f8B zuI6Qf2lI&;Tc-&n->>30*}hrTC#BGtXl5(jTEE(zZmA*2EMC1lG){%Q_l}D;SH8JD zTu`DbMq)6C+*)krMaE(+zWDp?h4RY8N4eODnPb&T;UfbacN7Ain5#RY!D$_3H!=sP zqWp{>+~VlpXe^8da%D3@0M55|DS+OYWp%DLkJaE-SUfrbWZ6=djk+~}%0Xik3KS02 z;50_hX+FuHAYnhYe)Dx6(Y_clnkh&bOY|Q-`9^FPj~`)6;&sKvCV&88#E5%N`r*@2 zjF#a7$@WKr=1Q{AxLd8w`VJMZ;t=*R7N6fGPKI(tNxHOV13KYCovebzR z>MqS@@m@f`8ds_k;Zpo9qR`##d68|}QfOMUfLndn@FRCXE0oYO@{nn~>ut2=6ZoGL zr2IWFVij3j%Y(v7eBFdwOVh zc%3TP!bipBANIa4+*%niKC0g91(t(HnHRKrh8`3&cpJmhV?w04Gm0WCRX43&9MQh& zcaMaGfccfn%13;C&RuZ@iLFz_#23i$R|GZnpbB=FL;bvp@5`kug(jIFXvmdLUD?nT zrn$yL&g5=}i~VHaN#FIy_f3ktawupTHP1}O-^qOTqD zW8)o;FA$?IuN|0bzSgxP*y)e|LTeO*UR9fU4!NwPSXgAw*B5FkkwlyX74Z?UA#ho) z-~VutF3ilKs{KVt5Qw^cnmYM*6|_Ua@RPt9x)VDL;QUr(h+DgkvEfV?Cjlx{?%oL! z32-|m6lUor|1GvRM%kj&}3bDkxJ&jb zFtAA5*tUQ6>34}j`tHiESEE_eJ%>iyf%b?B1-@MW+uttq>Z8fbx-!!6 zG--IolVAv(EEy*#2qOHKzn6mR@@w?j$I851z53^do?u93Alo<5|#0iNre*;aV6`3qnRX<1LLVb z5k)NJk)HYkseeD~kp`Fjc%a%x+G08N_}>gMvd|wuE(n=rG3aVN1%;GsmWGC=mi7H% zWz#5p<3coWQUju%^T}o|8p04`W|V|InIsq2vs_DLax^#APOCY^2lrkc(nV!UJ=0sxe8mM3sXxhEhvupnGc6ZS&4eG_1~_J> zPCy_)a$`65-@N(l(La86^MpOLS|FIWI?E2(FOvc7J6}{H;`Bb@@z(k_vOygXb--`T zUljJi@bIheM~Nmjojy5EP`lv`CXl9Ol^AG7*G4m#?j`SWN+EGseLMEv7T=-QZj_^W zqniN=dx!pR92`X!g3$aOS@0#?%<61#+2ddCM4?Nw_$7b zl1HJL&2b&S6_ejn1niv^t&TWb#H>Y@OR#DSWg5{K)owiFbHzO$7kcJrA5>U(w?> zMx145n4~lNdx5Fkr?j)#ycNm^T`qeS^LS(d4YYu&_M@V6iA*u+R)>{NuC`xJ?Wef% z7kyZUxxpS^d5^bnX{(Q>TQfftf{ zU)ow!1Sef1#pKO7=U`eehkASlbaIOF>XDa4joMI79KJ)@i0*X+iA)1rY$q^2Dh~B= zK+U|jjKzrdQ*@_bx~Q3tyA@eI@+R+JV|>lmUN&U)yF!*?o2zb6WDsp$BH!j>D=VU0 zRd^kYYJA^$Z;J=#OH-}XohaKK)EyKlg@e3gh)HAP=d|2rSQsdfIay8gpLiHE6_K8Nz4w2O_n)oPDf8?x4gPYnwgvfN zLe_sdQ|eljd2ylOIh^GnLSzNjs&3@S99_ob$dzZEt<@}P=~Zh{^zLP90N38_TSV9> zijaDF{8bsh`9}cqPYPw-Q2lZH8sVCxoRlNfWK4?!+G?(j7B8qFh*gi;mF&XF<>+)M zft0$?&z3CCVCG%b9d%BudDRE?i#-xL56jm>LMJj^flQE>pC{ZdM#W=a%!4!Vu z$G+=Pmf@Ch_x?G5x~Xt*!;+K{x!~9va)D{L^KneZ+64$heS2x#-7on zN;(&`aC?q74iv24#63^G|5?u0#If|BiHZdDwJ0Il?h8Cb> z;M!)>lJrbm&aI8{7k&mlbiO=i^E+n&uyB}3zNb+2^jm-V`WFIgr{@Hv$&7NGdYOZf z0hsWhcGEJAqxxD&v1aCUJm#Ir=;B{5sgF-{5=`-#gQIcMDV34co!YyKbQl~4K%GDZ z5n>mVVT{7MZC)a$2!DMTojdGa@jvwNPIpmf(_Ge4vTMc-BB}8^G;`I_a^d3s)R|WB z`_{r(@>X$FxSRFGOx>{^1A+aHcCF>28G|Y|RhWu1sq~{$!FVd?JW+K7vy{=}J({f8 zfv)kYoC_Q*zVP9Ix_=?G5*)|l;aSW57LHWbcYY394eT^0I*%^e_^ZFM7KCdOQ|@H6 z6UNDSn7mJb{>!*hqtc>eqvbTMx||29gYUpkirR~J_yAlSiO%tsgBw8*hc3ZH4rzam z;1ZF_7)RBRe6mwu{V>$vr)^QW%#}YWUWm!_Jces)f(TrAXd2dQ@a9Lu+h0EjK1S$q z1ZPM7w3bf=;{C<`c)X#P!{_#j%Y%iuaz%%CQe{Z$=WTtSshHUpO{lN40)kF~nrQhE zDzMKlKkDcJYcU$IA;v=0*XBfIQZMtl=~_gPR@kzRUtH1iUZ^1n%#%^oCIV>tk@@aE z#<5vrzPpDTt`dIj9mAyO?GAj3M0wezawAQghKP`bB~jMNRt zY0GU9auE{`Rn|`?vbuI25Ec$4};Q~BF{k1EkrdEud#i zMnF({7(#{;h7cHDN%u3k?{If$kN#enu|0_=lw7&33PcSxKXlANp*8!noXt1*V*W1{ z65f;AO%9FkCGadmp;6x+?hX4@3ATyM06{~F1gJZ=upd#7OZ!(FW}y^LwhJ925a+g# z^)9uw#4UYl`=1zpM^teg5m_OSy+c3Ennl_5C(~JmeqFl$A3RTcoOXMgbq*P~5xCJJ z(nBlGxj5oU>)s6u=&EX4gFt=b#VhNyR3 z^j?T{)Lg`{yzzrlATW7pFuIY7OG2;$L``IYEC|t`fMipUgWO5K)zTbO%%Qtv0OmbI zpq=~jBtQWUuRzv<2pQ`(k)^en_Dz7S8tS2i~opGpD~`5hc`7Z#z$Y zMFM0H@&<(^7S*q6%1yqf~Ezaxe-PoqX9iY;VICFfXbCq!a&- z<6TQEEK_mkKjRf%uXkn2%`#LnQ(Z5g($2=uzNAq2_CW!6r5g02I}jl<^@~*+IxaAZ zMV=QV$=R@=e~iChKi?%9_lj@xmg+ii@n(C&BQVe7c?H}V;vFl%&;N!X0vnP3z4!5@dd1?Cf;wV`#N`MIr*Z4{fq-LE~yxuJD7-z5%zr~maN)H!35 zd2@Zz^GAXNh@0>rxc34e>=F1Kl5d;QJBtk;W}e)+D~4* z48GdP&Z_gREVv-)#UmIOaP?G|<1B0f-r8hncQeqWl?`y^IAfwd$I%^x;e`$R^~bLF znBqNj#-jGZe^atd!xep%+<@!{_K>5R_57v0$Gf-O-&3$=g>NZ~2zHEKd1({O|Ks4W`{c9(^;aT}$AyRQ6b?0&4$qS++Ozj6=I-77!+Y%%( z!^Kdx04po*|CsE5mbf_&ui0L&DaUVoLBS^Tv(mF!Ra_orj@g ztOuE6c9C4HBvdkK9`oUgCeU~9Y%cTP=1=WalvFCC?6wuJxp`e|34toH}um8vo8RLH%(#c^^ttx+5(bdsl;h)CGR$ z+3FfnD(QUzcU+b(?0^|6S5R74`hbU8siC%W{L|0Wt07fnX(P>&A^Y?OG|xc-x)x(0 z9;N*7Xz%Eif$vrq6y{Gqdxy?$wg_CWJ4uYz*ArJP@`Av)*p`0_C(HF^J09Oqgfo z0&*y8Wv=I!!Go%CfBSc>?!9?t=J4W0u~`Id+WQh6wnC(zapJ1Ph<9o6D%;U|G*xOs zE~oOkIvY+>zE%*FnDOKP*ES1iJ$lon2PDu>dCWh5o_w=Wtf7}^T*-!^O4w!s#UDq| z6sP32G9M_;oe6BP6eYmiac}t6EqjXu>z^MR>1?C;HU?}(BW0f$mF09abd)NB)~y_G zlX0UoprhVWxT&s_^cExc{&qy57>_1vBJLYOE3%^!p-`^6r@c+`Q zCC1FHafo_S`O&v=c!x3(saE=SO_y~7Mpa9^=Pw=9dJFsJ@8sg$+xP!~tDbM77jAI6 zhqs;%@{b(kR_5PafZ%`dT)~GoZ}k|obJvW2_#o}p|KK$xu#yEU%4~cc=d;2l2>CFO*vo;LOYm zH|OweH8yDu8bJ+Zis~N>`KQIKEBYGNI$|14*YCJ-uW}FDjo%YFsp3oXyYoBmsX{(O zQnwC_+O;aD8@nzW3MB*?=-y4(GivK29JN)djam!C%7bCCroS>P7K;~zZxKc*E@q0) z#&^J*hga*oO2pydysn%PMl{=tJT1&u`nQ~qvg9EDn0iJ;bap~Z^2N!*)~~nZR=j)L zeNJX8QoYKNNI|R1SMAKLl2`g?<6z% zrp>kKNEF7I7;nFK(Z|I~`Yu}#q*Vfiex|nw_RUSzp>0ppi(S|988fV?=TBN}I#dM@ z%`>6_tldNMlX|J)fyfHI{lP9@cKe{5I*Z1m$MHhdT!P#g&S3kDhOL147uv}}oq_8q zo-7GTsT+$UIKMuARnKt8qXkYnGeHIe?bw|ZQ+0R)Yb-#&Tg&WNWl@sf~smDf3 z1IUZ$G&VCf56ZnH#EAvMeuc{CGxdA1tY&;jwa#H~ZMv#o*D)(M+v8 zE1>GAB+VDUhu^tUG&x5As;32epkXWE17pc7!$kKf%P0f(9FC^WW=i2mFJtwcNhT*c z{?L>&hh`tcnn@qE0uReTl{yW{{^64FRov zN2*G-G(Z(OUZChvtM!>3m3mZAtH$vbop0*is%T zF+SlyW8#G$n{gO$&bIUUadxB6YX^BmhW4R;f<2iSLgjlLGfUjl{y-R8&QgCp41dEI ze(R9s@aip&hbi~6s;@*O^ABEWB=@tB;269IO8;i7+xM~j(%m;}lM5qv{@@w(O6<&Z zkjca2!ltQ{6#1**#|QvxLDK=FcL?9aI8%erYY!VeKZ8E1o3lnk_p7W%T{kL*6B(wf zptZkE-g#oXshQCDY^{=gBdGwTw3Q|RRk)*mo$@p^M@8ZB^?^)^!!!0?pET7`7pUUK*Gv2Lf5rwf2xva zsD_U+*VDJVQT3O4f?B~9(#rX5b=OrYUyas>zhU6^O_Wyt zjO4gr_1-S1C!o<=V5M`mPO&CPt(W zQrsX(Pi$Q6Q}(ArvSku_17VNyJA&e3-hOq-FWQ<%?KtLam(*V0ESrYDcU+t!mK#w= zQ*T5>S1J~XSFW2D4tarq8vD3{%vK1w(-SA!+b-I;{jOEQ%6j2&gm_mi&dH+DwCdfq z4dlzYN*RDDV#1S|Rd^b=fmez!LDq=A@Kz$#^|w5yR1g`&Pz9cdR%TU&xNb!<(gEb% zz)_4g!FTH-#v$Rb`!N!KLm&$k-F_nxX>caHmT8EUOqoeUc zH9;($U2+x*3JPz8u(e->XN(qeu;*jKYZhZj$d>8B$~e_7!2NEhunkvFyx0&&qEJFu z`n?bg%#5@*yhOnuw&anH#0v+#h*RnB=8Lu$wBFL5Bf*TkFP+87R10$+ple(f zQ+q?91@*C`*|M3$XxcpC*y8jD-?oT!F&5c73%LW<5Y_KL0Xr(Vd#cyT8dOXF+*47p z;-69{SSxE~kBsVKaXPbG2qT&STXxAJ} z!<4w|Z?q|Qge=1F^~VMi%XC!g30ewJHNyf+?Ycd#`tg>nX^33Fh6Vo(_KSXl2dA_H zu`wjtiv1mhU!tgFr%S!pRL5vBcVe-oT3%N^yKt}aC~9L!q5#VEWf)-o2k)apV4bZd zB6CQU$H6T{?XyBYKOnaiXMjy+P{S(hf9r~C9wz&E*wmqq=T_D9%+e>+p!q7fQ&qZEJ)8pYU z`)hno_|O{pNVLtE1^!#NETuX->`YR$+CpKKIoYrMGwEj`{i|I>|6Y9Kx_fg;13O3o zj~JC%q=?@rju5v{z+Qx(RN1^0RR3adb;k1gjFM@r`*cduFuYVH1@xBdb^V(ZEnhYt zk~|3_kDkjXrhpT7J3SQJ@Aq1pk7%lC!eXTskpMj(5FJu0S9Mc≈2RjOCO5+~2|B zu|}>}i|PzTO-$%A>utE|%7X$fge^M4{EfCv3#xuZPV&v@lQY+MOm#(MWT^^)grGS- z*1417dTSLg#)Y~Z1WzD9SvhCp8{Q`S8vn3f;AJV}s}9H4q*i^_yDjh}E0E> zXf@6K%iKemC4jP0bPH1YQ`4KjF{so>+rPG5vlz{u5Rs2(f4<@qz^b*S9=cYv0(G{` z_neXbH7|UU8B&5Gr7O`eO`^3s#!(_TBx5|~kdebFCORl*? zPspB9S5ea0@)XV}3~fP^k9_7$ov9Me@@ntYPw3Q$(={JYIuEjMT}9TB(-HpTHa_-6 zkeBQrezYu>`~i{{`nh6-u&#WifFnWtt2A=ZNPhfR=K*zKa$shz_+q#Ko0m8MvI|nJ z1iVPV-K!p8jIv*z#DCBDRS_2k0| zay(elA2;Feqa~{QIISyar{8_(beH7zCbaO*%wqejf`Z2_#H14IRPyrG11w&#DqsQ& zLME*`BVt?l-O9}`6>96lf?6_;`hz$()eWqYa!WvU?6C|xQcEM%wEg?GKfaenihqz8 zBji&>>rkNB%~q`o@(X)nWk0N&lQ$8gG->it35cP19Fzcnh^P@@#9AMn3Dvv+t$&}4 zrWWM14%re?l2rmYCgif>FhaNk!QoF&QjZ3=A53&z*o;l>5*azCN+C2H9?}=uiT=SW zM1SiPjWZ4d#;*5IiMpvWA%#`_w__;|s`S*!xp7+eT!Z|c6aeiwrMx}0d*H0yAWSa3w!bW=I1)y3lzX@nuV{HL7a)1Lw z4$3DA>m51fDy>=LQc{@imF`+FWi#|NrdT-Tvf<>FGPrnXN>JJ(zsUwC{8KO~97krM zfQ`cczf6SpoS1bV(YWt=FW3DKo-VqwF-xUq)J)QGi0ehsTKBNEw7ldd(&8-)$x?en zdG^`enPuM4&I+#Yl(uzEoHpH2UCXhjNU;263$)A7S0&j>W^ksQpg7lyfAsgm!Mjst zZs#e}Gv2iHi&9y99VSm;&XygO>6IMUI^kGze#Ontd?_h3chPxq=KHvsZtME3Fo$Iz|?eCmVcQEq_(N-iUt36>(zB7MQ#gY$E>C7 zC_B+_)_#ru&!3 z$B&%V`fdzh0n<*XT$LoYpd>C$Un@?7BO)Rqr1P9=hoSOkUA1IRJpC}evq0n+mYw5R z`*37)WW*6}JU`OUzD@SvCUlbFSv^_T|Wz+XQUo9C`om%O7sfvQy zdXeUiY-(GxU|)zB^Qw0zShj)!4|4zU5Gv@5*4_fweVOI9EYY$w_AV*p{ZLCE|Jkm# z;xe)o0qz&vu|su7quP-1jNR-B@lrY)eu6CQQ2{B}aXdOUGLjzRp|h5Z#=Sqi8;R3K zJ2JF@j~uNx-U7;s<4Pa)#2vOIWBp>PhOO5wfhY=?U03F@S~=9i<*OyFv$>{DkDMAn z|9)>A+F;XFPQm|a@KU?TaLLiGphT~noQFdS+@Q^DrrJT=D>1bL(A%Fke!9AJesv-$ zTrc-iJh!PzI=0CCRx#{W=t++A*id}Y8+Py5IK{Qa@+tj>i^~*tOlR~uy;c&VoU>N` zJ1q1YW?{6HG>&PhxA*$~*P_!`CkA_&-w&~qEkkNf1tzpi>0%zZSoZ@} zeku1*7e6LW6Oz~4i2<_0J^4sd=+PKdQ@W+CoS9#IR9uP6dVUek=)mIRD!p_WMZ<~C z534DfNr^76o{sBvv4yryG~L3o38&Ol01h$l(jE%&C!Ep@ejeV>5w`v~cL+f3D&E5T7ZA@+XE(+EF7fj;c|ym zW|m}Zjv?1kvDsL=c6AA|%-7bn>WaDL;JjY-_Tt3TNoIttIxV;#M`e4BXJ-)rem!T8B12(jS(F7CRO;oeP*R^n4%+oCy$GpF zKqW`OdWy-q`b19!XA2(#Nr3DUOF%(Z8Hj>?fOw^=0Z%`c#D zeS^}f`#(A^4b@w~gXiL^-Mwyx$Lxk%|c9n|GCn@>)DhoCgRa5i7t zp{~_t)I@UI)yqRZ_2+nuAO1~ac&@~6j1?nZ%5TTjXWX-&6y|~(A9<4)xWmuxpd(1? zSRJ=Bs$7X3S$(;J0(LrL{71PYbC_;s@XQ`tF0|dKp)7~Do9vFfe?@4k!JB6h&7$!B znO9f8B3=?;s`v&Y%Z^rMLE^d$1e1_`|2jG*{-PU_z8{XdUX5WV_-DO2atE^xy! z9#3F6c4>DJ+pH1ui=0ctU#qT8eaXUyXzHzpRoFGoGFp4eeC!Ioo-~dU|AW_cd8{T6 z%s*UT!vD9>#={e;Zz#EK z(?Dv70e|+!GN`v`^+kquy(^&L!3&ONMeD~>i)5RoN#-q$9CM7-dqE^Gu`2-}RpqsZ zv)6}oTD#xE?6Kbdix-&>5lot~X#8tYsp22yBM7%4V%4QF8CtMRl@ z{v0^@_zfoGj=#6F6lqAYRRLUo5@W3N>fKy(YX{CyXZ9ilHp?qE7bB+{EApPTrVYzSneBSxwVKXsJbt zM@@Fr#ek$@ECc8GP&X`bU)9r4nA;R#5R2&Sj9mLot(6BMajAjV${}J@lkZ4FN}er+ zT*}*Tzl-*sfK^#qohgb;#e$ZI7H-E69^u=TC5UP&lPNLl?X&!+PLFk4-t3t`)Dp(V zWR@9IzpUGMjE1;D$hvm~ib~MNs*HCJ1CcJPm-cQdBRz`!8nLlySEwRU&OtZ5)`@!A z%h?a3`y;=sv(_<}s-ep1?ofUQBw1ZXHOIgtLS;kKYMv!gWSs+}^j0#dX1ny{TYqY7 z<%?_8T}`86i2L@Y>!i{1Ha+qrNH!KBsSHpl7E)qc(VqS=5X6Z|O;ZNhQ#Ht`+_N91 zC$Dn_y2#B8yK|K=VZVW0T*toqaU->`hBS18S`(6Cz02?xCS27YEZ*CcKR*`=!8)B? z^7eN54Lnl$oGK`PyTo>_d#s4fFyI3QY+#+@Y{tD@R|2S6LJday=j3mi^ zm2Ok_V5Nl?U+5NY?mjp2cJNE5lkd@C35c7H)%JuqJs-h|^$A)O+>!!QnA+5s*w)tVfe7Jr?UTGH*ryH_#ADim6h`_o*T<8I}KGk;CI@?ck~L_<}j z^ydz~TZa=RQ}SxV?aQ7p6>)>|($V8P@4IwvXu31?B1HX5sf&<#FSV;RRerzf+0Ji(x{@#`ek{t5V_uBD z1N)mZp6cv-d?9e1te0L4Ex#=ECLd*&eM>3X6GW$p(Z=NxrW}| z+AJa;;7VkTJ-iskoKWn4JQQ#lHIC^_QSLQkUgVCZ?@?AQJSH@J)vBBSxB?XozhY$Z z79UFpUo`I})`E@91VDQcH9^-1TI%#pL-tdr@wxwUUc628U3!&rQms=2D?c=SiST;; zW0gMK4c~X1VG`gf9UDIIwpQ%s(@8A9Ie6x%%yulU3kNTO9~t)=}Sdb zq7qYX*s?Wl%pP9Kk?#)n!33{m%kpcjDk zX?JKKbM!IZ)|-F3e;y8C=>CIO{R@{4U61V=aW*sS&X$kS&xs!bD@40 z4)xdet&8X@YCbqq&woN8Avh5K&_!5Xa@|vv@YBxXTB4Gz5(o+DqBN`n2#;`(dim4^ zzh|cybhLmeb*CvtCt-G7Xtu#uGP~%p$i0PB7R&{o2ZSj0+MaSk{+VdG)HY{TWTy4e&F17%p6XZeHooXVTtaPNTpvuyJ^lBJ_mV*$e)%OELo z2ykq;y5a~HdiiKXcVelpQs~l0{M2dv%m%AfopRW-p7%Z2|1k7@|Bt^@_`Kwk0?5HMI<-MQGNA5U*|}U0T%O*f>ll$HKW(vxSY*C-ZbGE zefZnR|Htobn;BJ$nc=z^kgq!7l=(HzZwr*|Ib9J|cQWb~ohM{rYeZBx8koO=06_}E z4~1g!wrTuONmZ1AV8v`Fa+LfZJWS0Z-$Q1UuL&jnl)irr&86V?MC9}4;hbN(H|1%c z{s!QVF7x6}AsSq-Kb)vKIpKgm$r^Xo)MnZ-gzOclIbP4!73 zrQL>}_6@sj*-T8z>hns~hiU={iv|fdle+VxAN5e=k#$Fhq%fEGxbYR`Ljd@WF?TOk zYLSSWNz<&WU{WhJDA-kFMFjS466rjfe_2_eLB$azp^}2=2>=Ev+;06|*2B#?p;a6m z#alo=iSKqtvtT4lE1{7dVoCZx$G-v~61P{+wEANQktxY9B4kGYmG>dWSpwooc82 z&*5(@Ksg@MYj%ykTkUbwKDphlaw+Til|HdbRW%3vtc*a5RoDRYQ!D=C757e|*&5+J zbEx~`9>Tjj)G&udv?H)`_Hn;4Hfb^Px3Da9+c>;Z0>yT#!CsGIMd^1ge*edY4gM~) zVbxk?{nCQ9Q?lwpRaxQ@ zRx!)T7>EMe+Cj3E*vB!kcGLoI2<28w{WM%HJ8?7>pmMSt!%eIgK87JSqWBJa+ez$`S6%us6twJMc>{ zjN3)JSSfO8w>SaH-rCSnhd-X5M*kM%JX(Z6vEQKX(=h^fAv~$@!h4{7I}dkUzMQtRU^LNjA~Y8bVmiE0<)w74W0yFBlN{L zv8li`G(Fz2{;EZMU-@MiJ?}+gNM1tq1 zEo=)x(TlI;Q2~7L2MBqlKX?&FrbLs2#yJv6wzHJV`)q7FsG=giQ?3krwEq4THNV%t zEks>^qb^a7tkn6Ir%CVhsI(1CsHxbJX5VR^Pjp62kuCkB_k93?y;%Sy653d)_Av6v zEX-+9yv+tIXOQxnBMRp?dpLh23Uda9Fz6qe`CWzB~inQ zC&9<$x05r!+KN5ugKGl)9!$LGiu-9}JdniD458~-qADgzX-QGhn~NCY}~Vy*8y;#c^7<-FC}^a@5A;J+e^I7 zjh<42WG_|ywD(n;{exv-rp?bg!adF()i__L#HuPlT}g>?1gu;+1%qS8w)~on+PvAJ zQDyTH5>_{Sb1sdmkauqFxu!!-=}Nv+g3z( zG+oZ~>#aKzI>WV6OF*_66UVhXPP1^~oBOjd^Ef=fo*Y0Kz@ZF!3;XoHbNe=F{m5Gd z%>?qJ%(n4@T`6z+1g$*pb@Nxf1f(z_W^*4a9f>=i-NcWalM=x@ah5Ir`ylS;4)I2_ z)~lx~N1d)kq6&J7JinZ2k>vPh3hU|;cqwZFGUI9D68$`_pgPi4I>GIN8s>H8;$B@( zCbns+n1>-(&oH+x&Fk(;3?CV|94gh_(yZIuW=4M>6IpJ4keQ_f@N=@v>!3~$o_w} zjQ1h)XT71+StR36selnp6R1O*BaljsfOO{%U_GN@uQ83h^-$H%3~S4$L!2uNjo1qtaxwcOV=j{;TD2!JTQ*0F%IZ4;*6kri&;PEC=V?g! zXy05KP&KPza_v*4r)&G2S7f1>&CsWhqZqqz8ep>iK@0$-Ez)~PZkXW@4$Lpi9z<^ zQukI}1HECimTU$7wj9% zIrCIEKoWP?W$mI9Q;_mQnI!eWJmJtys16vlL_U~!f1Wq4ATr%761%oVW8iXf;YXh- zw%9?7H`=cDyY`N^?T&q@+j#?GGW7#Wm29gg9opvhXyGlRBv$95X7Sqq1h#~zdr&!7 zYd4f4alhp~H>q_R$$+E6gYR=-os8;RFV`?Ow!S>yCp-lO|4|jP$Q8>G=1~SESXfwi z9oCjeMsA%gAycF&2D!$h!glIfbB#m-Dbf=q9;^HI7b9i)3Q9gQu;ef&M_*Q}_1zw8Kvk8mi3`fE9R1p7lSakc&&*}RUu2L9 z?o4C*ZTu)qUYL}ZC=8N_LJV=PGwr;XaY97`_yX%lt9|31q7sDCJVgDqL=$J!7QYQS zKctq3nix$~{x)eP<`(D!H-97s3FabHZfepv-w>3M^a{KaU~~NX?o$7<@#OmsO5s&) zcfv-7TUxtR5n~1ACQLNJB3Re^AJXJqSNe!wF)nB{cEKELnLjc^4Q6shZv7l>S0AP4 z3TC*q+C^fk8)Oj;^wpkZUEfX>XPHI0}+Dp>rSww_Dykxt8-pFFLK_HXYz z&%~BYUIz`@IF0<9#iOfu{cqcCe*itiFyOYtm1dz;KaI~X;Hw7$V4=W$O|T%*dTA6W5) zs%zOqxId9U+=%M^vbaw%QVAX0y0nK|VF%*r;lMzQ82{kfFwgUtK-iwL(kJJ?q2YK2 zRYgZdlcxH~XN!~KTx&692hMrZa@KrTKsNv6#=GR%$Nn7NyS7|^@YH$v&GnKmhHyOj zLRIy*vG05zNN*smR`>b6KK);NiRk7kc%xeg#*p!A9p*Pjk-E_SL0DI};8kcmKTHVh z-qEQq-gbJVeOztOoQAY=I69#e4Y4^f1|klVAv);>N*Rm zqGu1c_GGv}L20JS5D*jQ9f!17_g#wDV~2MdwcZn zCV>lwQw7hDyP&O1mz~D{w)#(oM)~T{&rTlqN&t;`=>)JfMIdLR^v1cmXNijG7Rx%Z z&u+SCIpwNZULsPJsZb zKX72Bvkc+JmV!8(#4oKb!-I%;xZnxR&<$&erOI_IXHsL4Lz`Auu4xf-7OFG6mDH$I zEawcTkuq9M#ma(1c+d<<3HH&H*%XdVvui)QFwDW>BP4fHoV1~poE6jFU#_{4=ze7* zFvMtUEOUa|006tYIsayxA*b+nh!CU20`Pbl&}0)??+ocq>tSsaSuEh2vE=y$3nnJg zd#QY$6&Pml?+YjRe4YC+KFXf9GIp1^fqBGqNkXK>FR19@XL}WBk#9HtoA}$W3Gx&Y znOs#J#D}O^u5DQ|ANEeJ2%neu+OGD!U#&|T#p)Y`gu2VgXrvu_tDb%^<9Ot(9Mu}q z2`?6tL*RTfk|H8{hY(^*KI%30p?kcELX~-jg+iN9o>U7xOk>T+GSkP#ji44n>Jd;O zCa=CjfQ4i6rG@2OcrGVP)&l^6&519sA(h}aWnQYGzSQj;=kb*=H?xY(UN_sL&2KSE zsoMZTCVk9eNio)?GY*P~iBq(iwBL9_u?n_XeL$5&vF>d+x(F7Jsp4GvWg5WgE0mt0 zs7O#JFW-bf%m`(%47Xb!d>yj2!cJU42)yg{h!Ba_jH+4ajhiI>E0!N=mnh4A`BqOXC0n&rU!1LSGtfaj z3jGaJDX+jiYf?=KjL=ARrPngxTxRchM7fbw>Bx}ov8`xMGO2zadN+Yma!-Cu`VDSY zpBTj?UKlrLe&1nJi4^%N(cyAWeaBhlm1Yg!k%x3|(Ax8o?Ea%uF!fe{L`uzw;=9;w zq2_DW0VK&HCoPUaG&6_4@$cfmlaBHY^1s6{c=hoFM^+bV1MhU36)gq497Ljat9g^j z-sjTgj1u$Q1XA4$P9C`%XnZ^^v61foaWTWRCzpNh!N52<(1kK0KS|g;k7gP9jbCqL z zo^sf6cksui^kN5tlm|(xKHnun@T`x+Zi!}FyVy41+BIQt+Z_5i-{*67-O1buG));@ zAs-IRKlP!bM3HJCD2S-gX|Z z3oEM$$Ev_BloBq|oyh<*2e2%b{=tM-RNOLt3YWR-EoA-8V^utsJ0?+CR+J7!;%i8( zHuejtJ@*$wMpZy93oE9SPKr!s!#fKkVJoQrZez-vQ(0W8&zttdO2nrV`@y<-#3^b?CjDI4GAIx9hd^Q2P$x8Chm`65*SY9upu6|Mew zEUZDh$Z9xbW`DNl=lpRrLAOm+p`lv}Q@DOUzW{AJMQ=?-3OluDE(s32qTPj){D46G z9!9uIGUn60UeB9Ov|R7Mt9OFWW;dL|n_`aDuy&e_v0_Q{do1}Nx65sWt{597p;=p0!QQEl8Bs(kEN0YAlV=dRX^y2Ti^apQ&v53Kj#{Jn9RoDfM`dTDbW8xHCQkpW#=$M=~r2y5o zKv1Q`B%AM`*fd&paUi0>C-^AAm`PeHXEkSHW6ILty`UT6$*?%GUwA4=#<|QGz3}Rz zHbeR`7ZM;BEKzRkGrIBKiG&_dVY9|t#ZjjcU1Vl7n7KlwZWoDn1OH%NPJPi>ssOFG zFK0}`l^#6Ak*iClR|~ z_sm~{((A1$hC3;HpdumaFY|8A=cj(m#IQ0CA5Xv)xa?1=^gUAfxLavoM34{kTbF9Sc zhumIaw(GGfwi~}czc+A8>{9StA*Oi7q7Yia5d zby1aNUPF(7amc>pkP#55?pcbsQsqNdQzAW>UnJwbd{pf=KIGQGUoFtmi=zIfhVr5` zoj%EFR@5mGjUUFkWpHM1m>~uNw)db6(AP>*aSPDACDrYd#jjzHblL`lgTmM0y7YVH zGhBv$@JN}|TbGAtq<(1(sVghx6yWsTKqLLkrg*m>hHevXTk47KkLH$2{Cuiq!=G+y zo}aq!s+NS-2dVN3?P@+!6u`-=18P?@C8O@CgG;@osPDBZh6!C4*K-9~DHN&}DrOC{ zVG1qjy3~=U?|!lb8_4?FN+rb@a`MR>uYSIURkZvPDSBT7sY3fnKDv$ZTl^`n# ze7bdlm<)M;HuFx>rkVEV2r^o0R`~AZL53a9_7ENH2@@qO^BzoHBB&AZgwf+ac&dGA zV;0oJ>$js>NlScRn^kp1n}cTfIQ`r`x;E;U`)OYv1I~IjpESjdbKo6w3e}ktq)-RR z=P3pgK7C+HD;5zCeL18Q_jMpJmK0|nBPVA-LU|`^BOh>vlO5M7$u9w#)xd;{-Ycug zQE_S7zuZtynl-^t@dU^CffgPn7y&aMb{>e~9a*_}P#jaR-i{j%qIjsY*bb~9+X$^< ziHj31?gL8QZ(^lNxkyQg_V~MM`~)E7q~c3Gp2R{!#P(tfT{xhavxS9Ups~k&8gMDM zHg>=orbt5O%;E6`rr9St{D2n(qFPClJzPu7(~N%AaxMgCZSkZ$8{6rbIV?=?EAX8t zeDPx4GwjTM`j@RI`^wO_xVduHCchTt81)*2KOkF5#qR#!?(y!u84`g_XhCM&;h}m3QFP4{THR$khH@sIzeLNk_Gk^Za$%4k#@Mt_Y@# zsgBKI6!BL-ncq`1>2y?Y8T)8z3WPgrx8? z-Rs)=eO;)s(f74p9jT7IG`#Kl@Pt>@F-=D_egY#z zx|8oC3yBCHJOy+=qxxdH4rHB6PjhI1fEaY+rCl^c;`rDs%qsOW2kkM3g^ISzb`yrb zV7Eyy$Mp$Y;w2QCxZ+l`yf4#pzeUV~*W}mKiEEDc8!pvln_-(lfUi6?62F!>_WGKe znfHy7yKxmy%*e3{?sH8RQ0Zd}>yoI&RnluuH5em6-!~JHpK$56|+Yj3$6qZWfET_65(eb@5={@d)2(oZ#$^jDz`qnDi#qIJ3yJ6q{ z;FWEXhV%z838iEaa{uB`CdHZkkWk*0KcIi}_ch~Oz7iz6)AVpo5<+n0i0FXJhz8h_ z^t)RTLhzhx39D!ddYWMc;b`ap3>2%8{B_p#{Ar$4X+A_L<{)7!SiQxyCYK5)jmPkS ziBo1t|JY%h=pD~Vf-_Ge>-_3QB^jL4V!hTcD=*0?_~xOt8lu083XXqB$@`|6N7B$_ z^ZL5j{QIbk8Om68FpDoz&p=-Mg;ETPd+c{IytE=?#*X+o5nM!0#ZuqxhT@sgNu9Q zlnG?AD!zb^HfoVdvbNh*nN!u&UJ^WU7&)w3x$~4eF~Pt$wR+ykE%E=Sy6=u^>f6@E zhKQh26hQ&$9i$^wI!Op6H0eqY5PFfW(z}E}q_>0?0!j^CkY1z(5JFLkbdV+;U(UJX zoZmU`-f`c3@4uHn*lTZ+G3H!*?X}mM^PAsi%bP(p<;|O-2Bf#*_Zf9`pL}c#*9k+# z5ov!_RP3xxDs6~$I+kqZIa>Zzj;j&lWe0tTP@ntC;zJ2Lsl&k!I`7x%E}auMCyBR( z#+8{~GOC+f;5j-EZkHq_c(o>G771~_h%9oIfN2h612|(+fV{icoD$f3XEY2>g zxsJReAZ+28QA&np7R;Oo+C|%B!rbT_E1(7=edf^|RjfwZ5F>)`JFZ(?KlniLx!ivr zG|XYW?$8m&9Pxw7F9IdqS?*>Ww}|NFp(Pa+76p3={)|Ky@paxjdIw}$W#^B;{%yAK zvSmYdkrck1HA(s^q0c?G7e7Snj>KWUSyi_^gQoQ4}RGT3qLwap%0AL&WKUyd@lO*ALE#Wcu2bS zsX~IEQtU6`2WOQZ)=yaR@vKR10lF1Bn1kZ|?}Ov0|8;06`Ec7n*N1o+zv zp2$D=%X;0V70oC(>$Cs6W~i{A6b(WU(KH#-LtzKLrXt@*Yw;sQHL^XC?|~IRA0vwDYspb+YcNNoCnPv%~T$8i42*yq!Q19gQrZZ+MTE=-(~^OxeLQ8`=F zIpuq!zSVS_Ki6LQ8#mVEfK!4gi<_w&tRZs~~ zI;9PNg0IF!&rb=@HtJBWJLc53IQ86@N$g<#f>Tfb49|YM_xlg$@ z%9aRV3(ug6JabrhfYPJ7wQl88;nt6)S%`z2>Ff|0IMi1l}LBII^r#T&%{pnrl4 zSfcJhLZ#pyft~9J9}fs%F}d4oTwtk+E%BmHa(33f>I614vl;DJALvO?Q{lu1Qsblc z7=ylM2ZZS2Rp->DgNM?x%z;BQQ8@`*yIry?6vw#4*$vlydsn7!$2;4ut*`f3r$cmS zLiPpR|BzH=Gkp5Z9CDVu&YXB@SlfDFAY6@I=1`BWAuXWe1i?_h#@pXX(zP+9X#4R9 zDTs=)vYw>9A5Z*rMNs(LbYv8SAQ^*!324Im%iu746asqqeITy>{O&e`Tb5Mfa^i_n zrb@_Nt&rJc3ExJ>=o+*#iE95D)+9BPAl;wsI$~$WzS}ZWNApuwrCTKEumMabJc8Gv zVRr;12Nr5~5E8a+>n}br5vB?NhQArw-=CI{Co~iiQsMxb zpq~P5K8)hH5X}LXEFn7Wezh^23p3BBl!=g)NSpovIg}ot0O+bMpujPQR zC7?1hmqK!K*;NBeZ%Oc%A87tL2b}H&ac+tqbYW@!`n3Ip(KRP)?I}eAP4yRelP$iz z3i3>?DuaR=h9U;j0fr2{1TlQXtpkB<%6T8bWHF%y0wfvp`PactRD5m6zV8;JKd_-8 zWo)rV!2Dcxk>*$#$e=R2;tLMl>4a*Fyh!1KrR#U%F8O-hvXmY=%!;^A+f*J;K^>I_ zZ`*2hLJ)Pg>L}F;=6;T3)NK7BY2;Wm?8oJI#yhN#2Vod)%(_kxU1fU7v@>Do2-W`!y{d;TEU5{R?;28}}%0`U4hGX0pd4Ka22 zu}bL#v{}M6T5+>2M?u!q$zi)FFVQhI12u5V&%lM3GTF_*G`Kv0awy+CPwolf1B~hk zeyU~c4qq5*PSFjKhQ1+fl(BKf=y3KTQ#+_B88)H}3XR3n1&F&!dl*HHa^AttZjOHIG*Z|^oYqkyKys3lp%1Hohn`OeLJwZ$eMP&U@QSZ~YfaJ3Yu`9_>SxU@L zh%+5bBlYOW(MwyBS}sV<;y!t#pwqKawu12twzI&e4hbvTa#gTOR;x zArLKIyjxIRWEpgHiwt^8P#?{GPAtDAYD7{7z^a(kmP}S#>)tl9HEcz?avI8xvD*&^ z-2}cG14CM-m=j9iw_q%R)V&A+w1>)b0j$*bfV-d%cLv9@g+jmO8cQqzosW%_=Nh^;0V&^vj#D@nq`0=~jL z%sr9~j60`#wq)K;GMKr(7!qg@F)j4E)~h$pQF5ytzSmby-gXu)FN40+Enf4`v)@~P zN*7cC({=85%(5rwAE*>Ta>eiD+;6SyCuVr2Z~tOP#qK?R^Oq4MByYu6bGBXQi~!P& zFE6IklGrBQww9ls`^s%qptv{p_kVf{9xL=%T8YnR+?+LzgvpHVciEsUzNMP+Cs~7F zjG%bkd|5q82i83&sa5zp*8TqQa}wj{(h}+W;nJ!Bi}5`+}S zyEKjpYg`qm{w1ggVwQ8wiy zW!Mla2uY2uFgcH5GGnue*iWOe^1@|~vX!?Od)s9Pmj*`<>j5eRu)%L{QI8ERnA}7q zV6%oyxDoLW)BcO2lyhkC)VJF1GMj-&57mNUfm7>4hH*pBW{NK{eU#l6CM^IUq(I^O z)yMM>e&amRTnsSgC@1YYA4lm`NAc+k*~^Al8zpxUJ{pAW4@M0oYg9^`%#1gCAoA*3 zwE&+>TlJccK!%!ChDQF_)LT$dmpaJZT4YLMOhX6`2}4D-EZj@|>Z3YUT9)$uD1Y$x z`3LX7zWjn$eR6=uGOpIg2|4vBVmi*Qz8tmOpxS3}sKtKl*5gca{cXkI&6VaaqPCbw z4;Q^~mC*}{Yu++@Be|gWgN{cSmVJqm%2`(SDor4S5W~)g?etJn394f#-2y?recX!i zPPR4uSVHTs!kIT(qW`VLN>*x+sPriy@$PRa4{8AW-xj*ho|8~z<7(%7Cz)~`8pF3{ z19Zz|kJKby&S;czbPQMCpewn)Ed4P;1MdhVi!b2;;IhMtmPV(lNNz5*XG`4kfWX~` z&D$0C;0igU!6*eC;tjZRWhXsnx&2dNe3KR3>wOFVB8~c&{%3=AN`P@*+wP%+8SAC< zd#%^6#OeDt{C+F6nNV<)VF^4gypPsc7c}L|ZVEmT{yn}Ac~Tp-P32FIB%;**{zcS~!9HBlL9vrS-Zv7N+|_ z0;%CygeSiHo|xG5tO!Xp)@Jb{ZQu}S z`hH9Cm5V13j7+PsP2Vz=(=oQnvsxsiUS|Mf zq>o%FcIf(E>Xhe@x-M1f@IX}4c_@(`K}YY{GkxoHJ=Sg{`XWT_Q;qOuDQu+_Ydh&3 zl;j#1N?Yzf&09yAtXisSl_RMAWscQzcJOz`YvMkW+bvaX;q<}$moXKmSbKpdPOaeM zKO_LUacQih^`@tV6!DotTDxE4iM7)k86q|<+5jr(6@QDm`4hC=`X*0LVF`u@u)FJo)|3wpxZ*( zltUh_0D^FOMJB3y$jr%2Sy$^nDmX=ko%t3l=kc>uuto|~$2otWI?Dv(-Q+4j?gbC4 zp27vGA=u-;0BP5=Ah%QvG2PiWf5pO=h9-Xs(Y4r3%~{jPU5Hc&__@bd=PRmIX5gQ)7H^<+kdt6gaK4foXq8o-OWKzf`s~ z?U1-ktf6{)6p~wASn^?Rk&jDMpz_yphKV=-W8~{SXrwq;7ID1n>i6rp1o^c+D`k;1 z&8Q)ct_e8gLFf`feJL)kStB_2A11JD%^Wm-;5n4h^8(-3xuXSZgGp~3aGw_){KV^~ zmx|Fvv)e7iGrD~Gp@!5ry^V#6%{;mG2r8tHOE&TMu0E7`=R%8zWi%kt-lrA_ZrWZT zt!3e&tA0fQm{hhlT0__Gke=O1S=w~`BGy|~Z^Do_zdsqx|H+NTul;M`$2yuszQhuN z{N;!~jnh|61wi&{__5|Flvga+Q+N(j*2XxOi+S?=d>2>|R4U8zOe0Da(+~tWd(^{I=#l&1-fpbpb?NYEbcv1^&uUnVJ6LP=A?vPHO zwycTMRvm83Ew7pGnZi!+#Y%GWcTSMr>%#NP#bBfGAjfa0PvG3qS8V9wBx6Mu%A%iv z?6JLjL~)UUftMH65@#p}uDf`KMxmRoW|&}nLNjtt^I)HMv8=wgxMv`0jJ_Pr5`kk? z@{_*>vK0I9mrHlmn#~HP51!S@bwcbI<+JYh>iyKP1UZXLgF)_U!C?S4Q3YHW-=`aQ z>e9;iYZ`9sUiryqlF?xi^@F_j9k=+rr5<~;OL&b5^J5P`Y%G0N6F zerEkm8<_TNne{sPusJXk6tYmJPYd63uDXd!N%PZg;;>{f{}Bkb{cfi2^!?l&d?XV* zRQF?~I7z#==7A`WZNBJ94)AvJNe<_=>c5O8whkSu8(=GsVddO{oi--a!~) zDo}{N`nsB$jqP!w1IhCMnsLV$oU;QNMsuE79wmhXNLI?K9iX@j=SXS#IxUo3bkEMg z{eZcIJpt53u0WNvpzi8?_n(sH+f(wB7Zj&@au2* zBsDc9^%*_axR&3>t{wvQ%k8L@bVlwxv)@>NO}d0${*$N_^^zw8$#bg!j%cnnR4iNo$dAL^7M3MP`CDE0c|r7$z1*!%$5nKvqG` z?iWKQ5$&fhzuX^Gwl|B^t}8q9$@b(;sV~1UG2I>2U|pJZw}S#7DKcb2;E1HOBrK;%S`pL~(ve(ZFp(ZRHwCz2%J5hAHMd()sd*Y|K1L21AJSlqV8u zfA#mjwyv4^ua=J=*-caj6$*PBD!D(9@n`%}nvt5mi>A>;XzOiB%m6OxW)$VvLfJsD zUqFu9+VSK%g=cFg zXo_+?hy~OZj|epSr!i5GQDwxF(n{Q_EvTFZaKp&7uOraJ1(*d{R8&CjKmC!8@EfSL z%leoyo4qGC@0&a2Gt)Qws-w7`d-sFsS8BgQT{uNli=B<7FrlmUs0lM(BVh6+K;=cv z%@Ii*x)=@{uDr6|zMvEh6Ha`lI9)1Y?|r{O+Al3;_g2|o*Qz&#B88k3lwghu!m1K` zqlq@=qzhJJqT0OJ%YebG)ET zv>0v-TNW?KLgcmodldDhLhaz7i$(3`?Uq5@D}xeojrjgT{k2N?In;dyz*A@9P6~A= z2PDCx2I3OokE15C`ir(8o9-T8`x}^QFjJY>J2dWQmgdFw#NAfwY%8F z1$uZDm^2d?OtGfvS`&g9-rZ4oD*}ScF}9Pg{qm7a@7B=A+HPv@OCQS_<90pFY8N2o z6p0BGabNx;aQ)Bj`gomgzoj;yf0Y zVKL+2QA}c%&+>#_;I?O|ybTZ0Sea>w=lDXE7>!23>L*|C*WJu6T-6U_CjO#{su-u& zrwwUQG0UD0csbpmQ89kVoGC)l^r@I{q*7)>&`cBgdNeRNPs?fZ^SgvwJhm;**o!dj zrb@hj4FTe2hGmBhGZ0-QAg=f&9j4$nnAVP)jgMxLSc8Ad;%=}k;qFgX*7*jRm!ya% zvvk6=zp>hSh{JZ)+4N?F4j46C2a*kx8HGOxHqI~*0!YFYGgA%>Bi$S^>m4*DVBd!{zivUR`P+1!m$o=8N;9d;WZv$^wncfNk|h~_Wb7{1Q?D&g8kyN)7Oq!vCw zO^xKpC-r43U~_z1ruByNf^ca$z%3EcbUO{rXWT!Qnl#azKu$BebNroLx8JEx4@2bb z344?^P}8Rg1{M`MmSiyYKx%3td$<&u0TMB)R)ZxHbq(}{F&1qp{51b5Dsa=nfA8ap z=?l*3OoPYQ-td8cHI&BwmgMlO;Bg;kKm8CBh`wbs$cfgVw1zbo2Z(an#yRQCL@YHH ztZ6@k3mfbJ9fuvyh*;gR zELBdM19cOlJ9whBcm-O`99$i$5H{_VMLF?iP3oG?v4X+Fa%6_rR`TjmIL64e{DxgD zcNSFrY_P0lOp7a#?}Y<@;bsBkpv-sA@7ZyCaB24EF6e zjkZT8N9eDHL1U=G_)9S}ObP>dOcBkgq9xGswxoHqG9k~SSy}0k)ELxg4)98y>9k)Y zX|DPcMy)(W`fN!pdMtKftJAft0Ul&iPKc)%s{1-E<*P_5-P}#ytk>d^wYmoEHTK`M z^sn;hlczXMwX^H6NuzTSxr=58EKQUfzFLJf*4g=v-uxlq{DO)xO9Du5n>yH??cEME1<-M# z>5o}i_j@L{M+d-@oR})6Jzo_g1LcMsL)p*JAX0OTJd(rwq7>n+Rb$e6IE&!D*AjG%4DcGJzYl?`ySe#h=UK-yy^NcR{u|$jG{VH ze2*PH$!1Lg`VZLgTNz#9tSQD(b}Hzndz7RozQphjqCi&VUJ3^@(I8I@X^}G7TT5yfQP6p{Y>-Km-c*AXMyU6W8QmIk9Vt1x$uQlj; zzzwq-I<+pRK+ezZHYywBOQV~6U9k4*S#U~1rHW!RC9lX#jGsvy>eL{X~3pZCz4v;`1h*3?ASUlx61)^T0n6<*YCs=hO0t#m^B4GVh-y7of?luM6 zrdmm;<3k~)yS;w*4w|#XuM|wVn#;&K#Wcsg;y7%1Vak3aD8s6lmL6ZIvzA%{odRU-)q0n4P@;MJumc z){nL;wT@x9ww6Vb55!PhB}6ylg!4)ddPRvh(SE$Q#MQuFbD3eg8sbLr&nH^$_Pd4L zX)mZG$B1dPW|6YPY?^!^qOzY7S(-|OdvhG8MQuEF-KZm#ZJ3M`exO=zclIsnVy?gK z0pUotdmu4^deiC%BL7;DazWwqjpCaHJ=}-dR;1!uwr-+ zCz^_+oo3w>wL^*;ahTW|LBXU4MR^WQVut6`nyi?&MS4BbY4`*+@CABv5#}BIqx@NH z4vk<2+Kx{j3sZN&(i3@=`5wBRfO4?vrPMR(B_SkxQ;0aOfQSJmQUF%w{@W9G7lI+u zhLymb#M5JiS-vFHEd$|eEVU*|V4w-U;ue64J}u`RE5i{Xg3{7s%X#)um*q!h{va1o ziJs9}L2J%zDAbEkG8068;9*^2Du8*XE0R*1FMrRPFssfr-#{3m1t*Jjd-fLfHkK5Z zt&8jxVis!nzvi!prJS%27JF!-xq6d9%Nk-b_>7!~)*!k&*6B>_U4{ex;`J~H+Zeak z2k4LDq!-Q^P!y7=3rLs4wSVQ?^MCW85IKG177Je~2>n$+??s|cP;jE-v>#Bg98)XBf2iNNIzc|xH$2f|pbMcn zO@X$&7XKt64OsAe$HAW^!m6z;K{ok&{kV$FVMU5?Hog||4XI!90#T9Yd6=fD-tA*d zTB!%8&QS%u2`OVy?-oGy0#}{#41cos5yNiMiwvZ89Y>lbv&60Li<05LZ*>b~-EaL>!>nr3UKnAi+)rxeziV<)DrSeZvZ40%c&X^>Z_qt~;{ z@Ku`ou0J-}-YHTK#NYT5$y!T7LakO_KAHWDKqU(Vq@!w80`=$b0iH)N9XTO1*;oJ;g31c&_Ob0YUtj)Hz}bbFJn znKOPyPkvhmwM3Zthyc**NbRZm!3)-rc%hJ+|+yow<0f3_rMoyJrDKoRZd;* z$QNPrNHNi-$^oPyKUXP5gE)I;bRXg(0Ym;iZRv$w`yYSj3(Jx3);iue9b|3QQi*85 ziEvTj&8iptL_tv^CfdF95AUr0Z?aht&3ZLjbq7+GKp11itz7|J=3{4?Y{X&kH1PJQ z?6Z#G3$R1%2)Fp2eQ$B_Ze4wI_23^8nX~fM+gz`V@|iUULSc~1hRtqj%OS+^Exj`D zpnO{x4?u`CFzL;=hZK5+&2Fn_FAhAgYXJ}+*sp1mZ3Tw;3Xy~2-ajNhi9_C@dlrv@ z+C6=r|6}xBi)wbo@I5jWag~ksgA|Ls*4Rihz~W6}>BBBIyvNv4tu#*`1Q9>&XMfLk=pCpq-s--2IiINv79cPnWO3bSx9Gw=GdHPIKz% z|Iz-8Hxori`=MVuyh~j$je+2q4OwsqdH_={$fB6!T#5^D)ZZ?Pe<5lR!oOrvx?v;^ zwln7yAADW!fKX9^+GGH6f*M0T=+9nYnYFrWYm&5jZowJ5=Bz_CCERP_>IGe^>P9#4 z8!__w`=#IGwaV}{IVtoXc3%ERNB;fqwTh+lWUC)Do@V{eq?Z%b>I6zPW3oK30zm>Q zQD5vf%8M@-fSTuiXOS-%7A9eKpBg!9^0x%yc(qg6x)a-Qhk72*y?SY+jODaz9=R)g zm9M55`W1+-J?BPDXXtnm6c-!!4g3s$&t>R7*i84f7gSVzblWuLdJyc>%a3dI_iz`J zh4rU|Ob<1+X}FCR1Mm+C6PhzkD^HJ2w;2D^N;#5|LN%6{b}nR40`MqN=Md+{zf&PI z{qu$NFW&qgnv~F4yWgFsb0KWqkZ+?}dF7QCT((SXR%a86Nwf<>YS5~sqh(()J2+7>c9|)g$ysd)$g|h{G9sg_-_Y)~H{wnZ(KfvkT1@niUDPDw< zSe|^=L<3p0Y_%3?$Mb)8;QDweW3JEm1X$6RGAp@;ffN#hiopn$8a9&uenqnP|9%h6rcuChR%#J9>A9)d3t3z@G{a9Ik&Sl8u znfa^4DtpYZyg#$JM}%^cKLhB^1Wq29g|dpC9K?PjQG_-Hp#$s>9lIWmj1PzK=s(I{ zdXp^FNo``B^oQh{2$L#Ot|0P~^dJcR^X{puO?m?{pUB?5Wbyp!ZCl40Hf-b!$MhKy z(=|w68^UPuY-5!0fn^N1+ae@PWQ08~?t?R4OLm1Fpy=MqNglN(i=}nEyem^{Olmj+n5R)w5 z&tHkFp{xUJ7vxg}xc-nhFV~hA&3s27Fa_V2rkzE)CZ=zdITYPB*bW@=y-!HrOR+pi z7Me~n?Wd{UOBYdz(ng)8AsN5ktv&;> zV{d;yFZ!Dp+|%CAPqu2rJ<~sS*=AG+|Cm%9=$nX_UA8(86+(z31j0PPno0=!LB%lC z2unHGei*&C0xG}V@s|_C*3FpF6x3)n5l2F*zG~e=0&I9crQkHEKN+Ga;`1I`Y(ypP z%DP(Bh$lw|oR^~XQv2p~gSNdXtO5k>&J|C)Vvb_*w(np>f#y*mlMd6-B)UYEI_lgh zdal#LAA3S?uG}C}WCf3?Df}UsN&Rl(-y_%h>C`W(5E9V35=8&x_&oGre_FS$CvW2E zo%e!tG#et}uV-|oEq|$`f>lD&Vuwi-BU6J4>MaeslEmt0FQk{2{J(@*CXyxg?DDBk z>$iXk8<7VguS8laF^&YB9!qhVy7t@#8j<^9u^!q~lh-%d(mgE`(g93Ti?dkyS38Qoh0uiL6){a9{M*3!AD=w!YB+cnc64Lx zQ2mNsF*O5pQdeRYx8}5^51TG9%k+=qitX2~E?A0d;*QraBBnTgx?Q=wHD6xVZ)Ha( zQ9DzMW@2)y%PS$U9&P=Go)|_=F{=Vu6T4f`JPNPlhje*(b*Yl1G#W@rXKuP~isLNk zT_4*-{v6&o0Q8nxpTAY~tTL)D9sK3|HENfb2SgwaC3|VYRMgwx`k9aNnmeil6$W-C zhGr#b`Fth1U-osiEV9)o^?iKwOYcd=JCNS%#pZj*@&(JcSVdv~$_Dh`b-;RkhN#t` zj8)%H*dTIHe!2!$d^^JwJI=IfC(3h@GYAwF0qVesv<5(knw?5;c5cn>h-z%)M%s>! zF?Ej9w9lq!l0g|h^9N;7Hgy=PUay=-4WR76W`ei*d#;6#`sMj}^Y)88$3@eJr)Ya< z_P6YqRE9Qhyce*^Qaja!{7iMRs_jsi;sgM%mp2vFe}CaM66N8t@BcQ>g$+aC%v1cF zYO6f&^&?^|P)PWN5j!G{zlCNasq)oH@PeP*e4~iR9Pt^E>-}%HQ~qV z&TbI{q|FSdtz9shvuJRVzCS5`l`*R%(EDL4fP3)#UiqnCpn%aDuL!HZC`!c%2ud}y zQ$rxH8$M4vVk9JtOxotDHDH~(3>5|puUC~=Ie$`7r@@{qujB;=&pm4LYGyP;14K{W z6q2ZA1h^RcEpEj;ai82H^{$Mkx%d7W}+fS78L2g${Z zy`IZ=-3PyJ(qS7t2=Dd0E{cFLXYr+r+U5^xMxSe|1 zbJB)iElr0kwLaPf4nw{h@eMT?qg4HK-BO)F`lKKfE|>Cf0guo9wG>>I0Qc z`&jsL5hTUUCeY2sKKb*1-*coilM*cl%XPKvTKf1K!+YjA+<7JwSo%c&GP9Z+Zs7K} zw2380#0+8!KwFmq58r!Agg&?@IxRy@cnM$VvOV!vW9vjhfgv&X)766HkIb`^SL4E% zIo*5B$LYP89VU_$JXHc9e@Hm$Umn(#&!GG;x(1}uA)s|luTd%FP!NBG1RwY6IQn(WAi( zx;|4&{it{#^wHh_-cOP%3NF{`?C#I7J${~NsmCiZyXXWy1wCHse>KVD2KrhAUf4Ag9Nu#Gpqa4N*;ym++@m7Y;n|j>};C>9XM;Qf|~-8I5-Pf zRmgKlvzKhW&>#iOA{JGC^6*H{-}JLd&zBU)0 zNt+YuO`3wbpm<~Rgkdbve`>Q%5dr_R8miF**=a>#6O+lDr z6eU)`s>@+UJw6)x_02T~sF0x)mnn`lvUpa?lEMfUvmvM1lo-C6NVjFx<1~&W7_}FU zFC`AaMMQh8Ef}gsU0xGnWhQ+^2ojyajcVo1JLzF#vywmT)@_>VO;EKK^rf}tKnS%N zKroPDV07ECCjh_dGBP~KZ2mhz(PJ}zHlZ-b#zbEtAf@lnJCH-nFrSW3v)zrDb3l$? z6o>+nKG?+jI}ymX*1{h5pG2tCkJ$rNB?hY;u)gb)ss{5EdOx08(v)M>RP4KN32`0& zW@MUcK=v}Y*H$!JSjC9Phm2c4wPyYH zb?7IOaV=Z>Ybj;1nrs1ducl42&U_zM7jRG!E1yIivuS1!fpEhdBL4$aqsO0Yx}|;8 z_J=OM*11QVzqR-_I$LnF&8IpU4iMSDlirQc%i~H0nmC1ue2*Js599p!?<42`;p_^n zBgVmDysS;sn8-Ov_wkNb5NBzPMf?px!cjC;dgJ|4*UkBL-JFeEg6m+lDlS^U;@dA7 zJrf_xRf^VpUpq^Gz1~B^c;wG`kmeZN(TKPFs#t>QP^Ax4XVOioRfFqg0ay9(-p-8? zpCoeKFO+FlC}1j$0;L%9`{eh(fL+Y&`xf@0%6BH z)yRiIDe(6Tn)O6^qwjx1W%UGHv!IsvJW)R9Y0)U*hL06AF7eg|jQKz_I160e?0XB7 zb=IHhce)RO>>ObrBSE2e-+eNlwHV$<&%2BLA;Ep+!goL1mxI$ z?97v^{7K{x4X)fC4SXCjJw#rsMWx^Hrt zh3_pP6Mxne4<(S{SXuc?|BD{_PnWKBs-z^L0c>o)Y(j*|R?PEV0~JzA(;KI63bnWU zJt%B_-N4T?j6aMIz*)S`y3)EUnb;eEx8k7V717paQ+6xZZ>i3T5?12NjwNYDYd2!z!?`+?UK9?DLsWKuO?+G;PgZ(JW|X zRmH#RY}9sW{g7{TcQL^%klRX|KbI&XJMh_AMU(o# z=4Hv?fRU{C^I}X?RXU_eA|Il^vR%vn+XDI(T0mCD6^fs`6v6-zxCO5 z0xn`*T9Kem*WX;Vtsb%b8Q0}Ar-1HLu4&l#sRpj@u#&IN1G2IOsesvXc$a$OWbQPJ zZ-x0BwBNBk|H5jvR)uEGu$!tjY&>+zFWrgY`Sn34deX3fRdg{7nSAcmnzC!CG>z2t zNjPjsj*p%mpeH>^mM=p2JL^C03lb^RRNv7J2y!%dmG4@rlKl?a*|6Y$vXr%BVll>a z`Y6ZIU+eob_}7A$^?LLkjG^93yjDeDKdzR)mLPH+Hc@lpl251OMwK!-E&!6%4X>vfYyc`gOu}>EL$!*s z90yk|GP>^QZHF#9FCOSH!pL#1#N(=( zeLV%LoQ*cB9XIAqiotSY!4F&tLH#MEAlo157+XA=g`)$$(pEMoI3=w&&Ut?#`+A+X zKvCmI%meJ;y}7sC1c_NFR5x#e$@#o?--QE)y}62FE^)J?fB0`V_5b_95{5q{#m*UiYr&-#i`8ni zJN)a+ZaG7$osFwll^BwdNATu5Uxry4b*EEFck`;EIensD z!tE(NO=<)4sQeS$7K38Gmlsta$ZepfUY_ijNKio|i1dvjSibNaad~BKJiU$s&-HCR zia*rFkiAX}7vI){kM%>e+YUHXhX(YNDI8;61@3MDsTUlPAVb@qdl_5#B?bi&2Bf;( zk0pg$(kMf6D`|8$!F0EnTVV6J@_@FWoYNfVI-jh5nEF|Lp@B@+S6Mn_vn)v~$@BH< z<^pHRb_Zim@YHE)+l6DfQ*Z&)5KR@LJcHj9qdz~5O~i$OyyE*m`FWPWqCH~yYku^8 zOC_>V&Z2hdO5cA0+P1GOrTAS5c=IlK>#oD}6sy+jvF-d_Yhpn4q0^I>4H$CkosA=# z7RzsT&oK7WqEjXtiUFxj4pjGtfEidF$Lhn}%VkbYwSm^B55C>9OKk2MG3XjxHI1{< zr~5;aU_rH*^IIA!yd&h7RcNAZQpeQ()1vi`${YKOuvPMx*CQ?GtL#CZm^I4wT|$GrH_aAB-M z0gJl4F7AK<2X*v?LC^fi-J;^$`6?xMCRv!*E|ouey|oz-N{F{dOTvB@CT@u>O-euM z5*50>aotIAFOd1V&~2sus!v<>48tF>yta3eZnZ>tm5Pxrs=ZS1U~q`$5&9hEk;}ft z?cACt$7`Yb;p^w(rOfnw)aGUd(h-Am+G(*!0agr4l%@7H*rL<@6EhxnkG z59{#Jc-W7!LZo1Zoa&yPLXf&(dh%}Hv}vro)T0|D441Cn0)9{)OH~)oS`K`t#51qP z6t9CCbN!oS&6fVm(bc~}Lr8%A+IRa|UYDY}gqpLb2a_06`Bwec$KcvS^%=*G5D_Wr z-V%Q#dNv42Qhn!M({N-y;mG9VhQSKUa1uUyIQ zrRO8Ptg0(qPg|kpsMzJRTE>X`5k6@&Q_sqy%yL`Q4~u%;kM7D(R(rp_|HV^mJf}qX z4@qAgq#9G%8p-%gW933E#O?Odb()Lc0wLD4@WW@H1Yt!i%(cEWGx*ps_}OsOwn)L* zu?QRU=V4j3K%5WRhz1+hLcj#v%UHvZvf+j(#BcK?j~vB%ZJE3~G;BZmES)=-a( z3XJ(Xql9!UFZzb+xgMveon_jcHQ-#g!+In80l4cEHFXG&QJLZ0Ge+Hq77j(ZU-QCko>_0m~ZYwGHj7bcels6exURa^D7T)@`<>Y{}PQ|Sz(+4h~Dh7@fdNc5x4{8@m9 zhr-{RadlRB@&@mart#oel)_nnskVd|$Q|anLBPn(Awt|ei2TD>dk3c9wfTG2+z(ti zA9R`$v)NPEYj7I*{?yKr9eapEguEpxPLgf6wtgk;tucOJI5X|p=bwf%@zd?y3~`dX z^Ok<^1X!j8a(>!Hr(E@8_MK02ClVq8CcI_tlMG?^5S-~XPxc&mpT7q(;l%2m zMxDq*MwnUK^M+R^207)f&J=VOeU6%vq^5Yd22Itmh*qLj0kED$y?MUzS!UHKUUpqn zuQoN+IW3r}%B{dsb5^S|xUAJA=}?$SD0zgMxCiTv>qli}|NcWVlJ&A;z%$g^Xa~t& zs6T@YY4Prl(a+!CxhY`@Ni$BP%6XZt&945r_-{|+O|)A6sKB=yfLus{QcO4&+!e_v zAdw7-cN76?M8)CJ+?V^J3LlQ1|KB~j|ATM4)p5#nAHh${&mJTi$Y(z*(PIedp4~-t zi;)P&TdSH#;WBrO4$|UQgeJ>vBejSnjWwDd4oruc!lsPev+i4|Fjw$&9keT4ko3Q~ zR-oh6U$|jfbYQKWDkoF4c@|zmnXM41tRjOTdkRgWBF&;K-mJ}jWE&Ap1_-`xK^FY| ze_-N&|CMWR>xErJn#}a-f~E5e3|p&9Q&^CLmK_txjDpy_3pyk7XZNwJRwpjZJAEH{ z%9($cgwkt}SQ(1l&2uQ_Vq2}Fk;s?VAaskhi(Gcyw9AF|Ya7-v7d&JdC_K2xajRJn u?f$jq9O*^EjBprP5cx3jLK&Rf03i_BHbC2~LW-wv{(JlWfBWyBss9D$8`Mw$ literal 0 HcmV?d00001 diff --git a/wyk/curves.jpg b/wyk/curves.jpg new file mode 100644 index 0000000000000000000000000000000000000000..6d8d874b340db79bd8484f7fb45503491fc98acf GIT binary patch literal 96290 zcmeFZcU%)s_b=tjL)D2s@Bn`i+Mi zu*`=$Q8Dp-1cJJ@}8NdX~1 zL`dkWw2+9juqeB*l(e`g7y#J;iX^h1^^r&bkVO7_xnvtj6n})D?lXeN5i*M3WIOU# z`N_`yDL)zOU*!jN@td4v+~j|hed^B7;s6!!x-av=mGpNVs_auqSm4A#TPzec05Z}N zKywfStRL>@B#i)1fD=cL9;G^Zf{N+{-SK0`>F8-soS>yYcltE_>C@-vP8=M+U4BOX z=b4Q9_;G3)>XS4yC(qE((45&n(VY32h3>y8fb4=Knl0_1dL6m(>yF|gT3 zN%ds%pp=Kn4h~S@{euEDkVA)$P#&c^b{sT=zbBFbEjFP=Uu^61T(eF;A4bghVT zT1~n=4pY>nhq#Naavj+hfRbDMb2lhN3WK$hzJv$#`yV3wX9;-z6oE7hoS-5KaeQMf+&v+C)E%GkMY=EwMSu?9>F;N2> z(B9uy(p^RZQW5iaB35F12g07*EPW&V{A-K6m}%u=r+Ac4pO1^}9HXQAyKY3>WYZ&*!N%RhZ9S7}j*)1QiMZF3wVnRd51h5enPoS_ zaK6mTUAr*bbv+XB*(Zt3Aik;tq1{r{kVh?mm@QS#op}ZsT}I3}k$@ac-6EBuGU4({ zxvyVYSJ)Ypt3ILPs#+YWCiG`A4DpIr+=t4xn3&Dw=g%)Q$*OH>!wA$C$r}Qj0;VsS zOqe)7KEIY2qGqnwo+5!R+KxK*K2rEo&#AqH_`F?>3B!z?MG|lru(^m zLEJj{$E+j=GbQb91E!{2122DhmsX372?C}dc=N%=iKw9%`=%zx90uWz$YQTM+hto7 z1NrT^B_gc9Zn?{cE%|mpUS%*{uZUtRuBc%e>$DqGNJW@k^v&Hxq>upRU9q>=B%`)& zTr4&#mp^0}Gy0tkzkI(cAw~Y%mLUl^R}!=73vDZksgf~v6yTS*y2QuTnYFeIml&Ki zFWI|70>1iq7^V{(#%C+z$b3EH%Vm@0U-!%A<&l7u7q}!?#;jUqV)UE6i60E|nfm=^ zqXrP`-nPU$OC^@h(3DXxNHw0tYYs;YB~~qbcQSc=Pcx%BBfNXQDeJA&*0ESsuX#QJ z`FO%Y?&!q*U4$lTMJ}xJ(9snQBz@c&u{`gHPe&KdtKG5?ike#?pr+(WUpMt*HXXTN zBm_Rju(F<4g3C!cE;u@tSCryow`8+coSVIjFyhtS1fOV!{U)Ccg=GJ5PUsc7U9&caQS?-8V)x}uA=Hv=bhF`h z4bJ9!7u;j)9yE$l>SbW2&4l)hT;O?(=;%h>*i#bV#{2cPKX&?T*%%2B?>8j+Z>~T=ET4Oe{y04ENW~%Hrcpix#t9y6%SUZE4WG;ZB{<_nJ=nOLvjTZ;PXkcX_0VPdRV^d03zj~n&NrWdGN0;Dr`}pa~uhHr>c=yF?pLgq%n+ZN}Jm6 zCBm&`Y_GI#B$${`us-sAW}CR_i5PJx*Saxp?Bz2gcAPEu)a=nnADW@EFD{tc5czfY zWJ;+o^fm9iuC}JWR^40v!I?hT@mUaRwcCo7akRV7g|;myOJdt#OD6##xb*YeTxnmp zle>z|SO@nmj3^^kI*5*Y7YmfH&uz%SueRIw!(A!e&2{&#o9}A0`4STew(B7lMbd^z z1Vl;cfPI_-XViJ;xZDRa}{CJ)vD;B7x3u*alg+pcNh zTCua*kuTX{s+{tsZ@D-&X1}4i(-^eEWPQF*Lu1pWWCQNo?|<%r|BV@&O@m#%{z)4_jjusx zh%@JAzAVYn`WI@G-KEkE+xKG-S zgbY(k|HwG{tZ9t(UTg+M*>@8Y!pMSGcVna1`il)Wx5CAn^`BFKYP9T-@c^>h!V;Ee zGjTr~HM5W%f(t;h7HEdlZXu+c%Vkfik#8JbE#%)s>tG7b{wQR-mHnf4DwsOo=8C!r zzQCO}!v?ajxkLgE8;DEn#h8}#idPSm+_$ZIyDnUY71$yHa$|M%3fh7bPFDjLS%NYg z!O0v|*@P;c*keBia*pym!HQ8v9J8am@_T^ATB~GaiKv69Fy*IY>~ytbWMzi9ZV_R# zBw${?`^t0f6)n&PftpurGwAJZ1gU4)$DRZTZfbmbjP}tjY##0>KJTx9_)E$omWkm# zB;b)jH3K2I2epzXzk?0QP_u^DW$xC0Wo`_ntoqVB%;qcGV^OrUD?1;}YQSH~Ta zt9VX{+SB39AJx5m!tmITh&}sR-vs9>?8|bAfn~(DmO7E@aP`Zl$maB6p9-xWW@7gj zW_|aq>B4{?#u5QY(H%A?I0GW1qxK~H!@Y|bw=4t=q$uBmjaDaQDYhe ztiGCIny+_OK_ZX@*cGWqf0lRWxH1wRK>|$i^b!ck0NGZB z0U;IZ!AZG(#|_N^Nw2StWrSI7zT#$D8K%sj(>&TmBYSbOC~(l!IF8L;V%_C8%8nFe zJ6m2}9ca`q3?PicvGKFGgm7} z(oyAh4>U3J0954<-KkcK@OMnBD<9el63!3nvM$8mtQm4a`_seO6^7{ELf2mVy+o0E zH%9$Vn3=ki2Sv(X7{TJMK3?*2a(~z8z7tY#v+&jPM3z}UR}5O3ej`# zc$}JD!Z#{iiO#xvp-5t)APKN4AOYQ30S#yppcO>|iVQ)+)XT*277a>DS}+<61-|!s zu(g5?aInbWSvTQC^QdeQXJ>g4MXn^E2Yd=H>XU$7ebH*UD<)=(@5;-PRiz9c0!s+B z2=54shb}=TTGbs#h58?%yIHZsflPlS3mTq#_QS*Og$wl$m-SO{{^h(c=Fdfn$;L=& zK_2qEyDhN?X0nIsCWO9_YHB3`gE=H%BioFlvs2%d4Hw5lU2JY1+54T9tALXN@-!cj z0n0Mj`!ck+$LOUWCVBR*^%6fV#O%oAt^{6|$0=)~WgN^OQn6@;*w{hf=@G<;+v6`o zCi$CMIqIPnt0X`zf`5|r?ya~uw+dR{<6aIDCq1#dq8NWc(}|irwmA|osb}KONhwk+ z8~4mT7@0>sxSWFBs0EAN7B}4zkl*z~?S-Jga?n z#LdT}Gv_5PIoG$VMW7|p@r>NJf9EBy9G~ZY0-QwI*0vG->y`=IIsc;hcw^L1(#O+Zwk0k9v3P;sD+LML%Yj^(c-`5x8ctOYH^M#v$x(v#bis#1M#}?KCd0 z$lGlA!}_8grG_OU5R39dI2XKa3MQbaasCBz(Ro8Y7B9a|Tj(E3?BT&6iuP>K!?ymu zwQMQ#K72^!by>j~iCy`0ylvW+MZZ7&`mX9_TpMaA@m{su*cP(PH^nw@VJ~|3ZmO?8 zZPDT`VpscE=U`oe!Sb-F1a(*OMW($|vZ(e&B4lVwo-iPIRFz9!SG%ICzy(`#6BfV9 zHYuys4co)ch5pbB)7{ij-@lNCNZ4~H|3ttPWx#T*x%BA zVrk^RVQSYmwhnyh!qU(V(qSFr($)1?~*yIiaMxU%J)-4UAJ;!aZQhP#371r3cg+BmjC3 z?n8fLKK7G&pR%8#>TJsnUjARVp91dYq^D%02Uhi)a`%=0cZ!C)E%a}cBbH7cdX~0- zqtQU1U_Pj~hpM}Zp2lq}7|dzEz@xvD|He#Z2XpgLaI&}kT~o9_8?W*^8O%v(4Yjd^ zJ9&UXDo?1J$G>4W_?`TB_TyHziZCab+h3GR_p|&P%6}w)SpZF#%f7CuJYe^=;2!SK zzZ%XlC(w}og?hpY<^dYiztE3^U2OM1*$?i*Gy4@CnCj0b+ll??seSX_SI!Ya$ z@o|JmS@X!t9lIufP!vB{48M)NlLyqzogL~9k-ey>b8$b}TN+GphI&}CdpkS1xJ!G> z@*HH42E+SgK_2!477s^R9wUuA>>eOc>1gl4E+TMMK!jgZl#kuU4P4{p1#@#`7Zwob z0gH6AwvpDkdF!_V!I&)1Zw>SE@)Gb86@a<3ld1e@b#f8WC%=E80X!rvaUJaD+ZwX}$^h!9jr zN|fK)Qq+cDSlAlEe^o+CoZm_kA}TH{3K0?&5#u?={(HME?`vrM`x<}m0cU4HuvT{V zYal^GL;5BR0(XYGc&Of#`>8Q&7zC{L{_pFWr7fkzBq0z8bYB4Ie-Pl>e*gZxFtAyI z`zriPyTG>oq=9M$6)gBir|paL|Ni(@$v@KZFLnJ=*FVz0KVtr6UBA@zk2LU)n15N< zFLnJR4g4eKU)J?YUH?b}|A_gQb^TJ;KhnTIV*X`aztr`QH1Lm@|NmMSi0}N43PD{! zD98)Md`REPud6C5THMjmx}|zs=>WhY7gD%+Lx~(*H0bQ&;ijW}gWbs3gq^YzT)(*Q z^9>%B5cm5EckbNY54-$a=(QjG{QyC*t^S{D-g@}=%lbXxzq}rU+;`hwn??ZtBGw>e z1A<=rV3?zq$9<4aw(lu^#>(*^T(}>0)6-D|>Gfck#`b5pcRy_PGd#T?b^{v$@@(w$ z+a83;_tCU7RzJhc`(Y1ojU9Le6k+!t9IQG69n7Vq*cA?(&~+cUdqADt*;QR2Ft_`# z-`5%bly5&5K=+ezUt^cRj8`uoQ2#HU_WR*yaqHR#`XxKt_9yMniXd<|&);HX z|1SP#8Sl;kfL0o~sE+U_P3$G;PtOP9nh}4}xWPrDCj|kZ?%iK}*{_3j{`6)4=_&qS zoyq?^DE>J9l5^j4oBWT2|2A;o%TD%`Y=eRfbpHO+mt7w8WlsjhJVFloWB+kb9zAmS z5EaES(98cgNIpUV*8fK$m_$KIew2&~IClIbKu$&hdb3mPOGJKz3Qh*DrK3B1>c|Dk z(-(oG!ePkFb4NJbM=dN^1 zQWsOXs3)U@=B%&hFvvhs?`s_OcNMs!niOK)HQz~IpE^pBa@xp~aS<`!;yXBTY# zzW4nhio=Hv9XfL4urnw!9q4_3SojEV@w9?ArHJJj*P}NcalE0|d2e-Al&XmHQ|ivOn{zKW5Z_p|8C%BI1&Z7Ee_`v=csvZ|Vg=686d)l3|GLSnP4TZS>a ze|MLkn3|}@-Nh}{4%Ffc;L8CEW4?bOcqkFg5JDv2l|1cXnu+n9w)E{KmWIhd>kS42 z$g2(P-h{aUfc~UhHpkibJU!2oRXTR(a`IaA0Q&c6ds6bRM#Hz{E9r~ z#S?sQTVah)$y*@hRm!*rPBLPLL#b@<%P7q4j*`90HPh!*+rE?^Y2Ub2S8}JkdL`H0 z(OE5#J~Y~Qm3h1`Yt$4${VsEaDKeH<7G1&J3dzd(@yT|cJt6&=S^otLwXB{!XGnNs z%ehAgt5((Fnf~D)N#3z4eIZv<(vxT+&!_O)eNKPE8hqA}{{htAbF2GCcYQwOwf5KI z!1o_HDNVYbY8;iCSHvo-RpU_brP}2&-vVFU-G%YJfoj?sN1x9AG5w+1P;~_wgPePt zTkGScgDua;V^6%ro4Qz+y#A`C%k0*yMQ#1|q6FN)+JKW>2~?_wiQHvEUK=5VXfYAoX997yJ}cuClaB*{Z3O|xF`tgU!xwKnHE%@9&*0(sjZ#Cjf6bO{oc9G z_8FEK|8#AnAOP5M4(OT7d-{Cm!Rl0@Z}X|w$lA~5d)gAv(B=K?I@UX5byI9v2y#99WbS{b@EuK1nEQL)tsL0~a2yB^)fY90%P z=^N@SnGA<8YUm!dPJ30@jTF7fA-&%xRuZt5YjToIYZ(u4Gx+Vv0T#&WLY1iR1+O~V zn!=rTo?}Da?FA*pD|)yFgS&~8FEN^}QnKiaS`T9%3`7K9>r zwq8w7pje1EJV=0t(^#B77tQLZIUKb$KG*2XSeeDybd4$9&*lbVX?^dBmh|4YCt}B} zO_O-Q-qm2CT6dfz0WD5T3*godOm!L?whxvxUNY*rEYccm+4PK8`B9&VxD|9Q-c$bY z+uUrkn`Nz&Y7GWy_WtBIMnUtO`-=a~M*qcV|CfZhAP-pE?Fkn@?9RX{c?INqVWrkH z8Ql`~-NoTC8d#ntjYpNZgj*-l8BNYz7Md^5_;i%rF5_J<=hNs5XTc8XdcKSd zV;v$lURuyHg{PW>{4S&w+@_@-44eY{#%VLJZJ z`N#7HpiSob>Q1B3{y4>6W7&vtbFCUz&~2Z_GXPmI0($T{+1TOTWD7#$#H&zUeYfO! zw9hVwyL`7#%gk3hE!wSgy7WD{c(nKoD$8*}d>0i4xW%6(-DF6k5?7HO)n{O@aU++ETs=~;dqS18}+6=b|mZf@Qx z(erM*(;Lte5#9wpX_8v){T479$W`6^02RObB~(Z)hhps&QSU4-f&S%MR86%ZPwe|q zd?-D#9=;5PCXck%iO`08q2m3Po-V4ZkJddKRwxRZ!kpI^LdJGarL+hlJX(`DzgU1) zyRCHBr{IHK4TFPLpPu&%f7RrI{JaU(2pP99Uf#*Abt+!^l+3+!axE?JxmV?f*il+V z|FG#Tm|$b9LFd%;*ju?31h&pr*Z6$%ilAW=dBd+zKf`w1)L{EvsBU#jVK1NCwc9KT zI#giw-v4Pd`PbnkY8)SyV(Tb+zdOZo3qlqmT1<6{PRz>Bqj+HVf~T{fy0Z z5`^jW8;_rhuXlZ^qoS|+_2C;s2W=%KRf^=7t86<@{O<1{4|{SHRM05eZ`F;RYN*}i zD7i$_f!&KSSBE$0PM4?oC74BspU5^)%cjiEcrmEbRrQs8G_TVS)gIDi)Y0W)zn50} z<>s97$vcGW58m=o9(j+xUZ;)|jM$mH%ToU1{WwQKsQuNIB@T}7hpCp1-8ViC+#lAI zz9!dbuEO%yVfH{V2-4U8JQ(*^S#;#gQm)f%Pbuk_`-o;b?sldW>y?&P(MCjH&cfx} z*e@h2Wi{w3X{d8CXttl}E~PRI4{`{J)aGJdDa0Y`R^1cj-F9Wmn@h{;+CEZvr>Zo5 zxSo`HzQM@B<V%Z3?v{7 zsp@>prFc|!A$A-4=%c45ChvV1ays7~wS{OV)-P3xygjAoa=Y)=%E#x(yNtJ=8}SNX z-s)~L^8ftdO%w!XD-mj0u2HMiI?pL+@QFWaQAwq_PSyJ~gLNV#sEt=at9nKnBwpa2SvcnWBV^*Wb5+(_L~rGG&th0^vQ}om#$&V zf7D=?-G-bB9t1;~0#+tJsJrsEoqBPDnCw}eMpk5E5R;)_W4<=AQ=AUFfCN2-dE0B` zB$(s<`Hz?&qT(&j(0iQJYiD8c%}iczEc2MlCwn0@V3jm_6uVO}rXcnPjrFr(uRkKW zGEEWqxe70Tp;wnj2Hz{d6(VSpEELQxJc|9uep>N!6&vsFqkh-5f}L_R#9+RJ6ysaA zoi@$tyHpID%u>hEGmR5HpxbR8D+YAR6$vJ`g5zJ3PsL{Ecy$O~2Bx)Z{D}ly-*g^~ zS-=!|59j8QTNOuK-IZE1s>JkMV3nwI@Se_1Qrk`mlI~5(w0UtmGl$*$I^euy@I2Kn z#U9di`HotDsaR7%Jk6Ea-l5}aEA{J2$yQ0l0|t>CSIi88>5~drA0gkOwr(eK$gdvq zT;3)D?ee4Y$j%CBuRL&n1JHwdEo+YT6Y-A4xf-PCC_-8|F5Hd4JUr50bGWq5i;yua z>#rK#1c&@cM_Wp-lMR*1C>}1?N!EGuJEU1c8VH)d&1A>)7 z4txC#x4@?W><%C!c`o(?cY+-6o79Ccadn`;nAqI+Bv^h zxAK!KxGYw9auytOa-cpT+10}ZNFynX17SN7;C9jKje;CrM0A9Ov!6i0!mHw;L4p!nQ~T33CKoT8&lCQg<2B)w>gs2AM`T1; zQ7N52a=gqPl%C~}Y`SLae-OPX3r^%Dwu0@k9r>RTLYrgY-V*NKdEky3$0UdG+A@ki zm`#fdrj#3V`xwx#-j2n=P`(A!rQk^H-(FGP?+a5O15t4iiu6}7>{E~+J(S%e_a8H9Ri%+k@zQCcjR+gSFtJp;?2UO!;j3Uab zfwJj#!EG$IooQP1?ND2P^w?^Tw6dE0066W25Kz8oCdtmkCwuCTmpUJz+Dc$3H0x{w ze4>RdWXwa_cUr5yBm48>UO`xDJt2H(%&QI;rQ1-9m#(3I`AO%F-lwNcJxga!HQbEl zrWo_hD*)U5FGJ~nLCEcB+Ci^UPDZU45n&UHeS{E92e{9IiYeueR~?!qrYg&G0+%K+ zpuDubj(sZbY0~w~ul-V@0=K-h#R51%$smsJn6E5*BSaBTRGL9?oipqCP5bFzD1;3fo~Go zn;qN}Bjy(Cv^xm|?~kWfM!p-aKg6)bCNgslZ7ZWKC2_it>Q<gbdz(6u3XRybN+FBH@-aVO$&llb*`dj>a;MlHy_nOk%z(jROFYJ3aeMN#YckjwJn1)WE2 z(zCMD!?T3n=xKkYT^r6;USx@m5PN$Z;?olA*7cbW;Tp^e-k}`g=J6|0(~|AT>7gK^ zX_Y|wC_W=OyT;LLt6f?7j%C>07u#+VEM5WVj?E13PZgIf6ALil+<3ZtjGAVs6Rq)v zD6GI4s=@S$18fAQwC)NnpR#}`h2Un1i0t&cvE3e@GKWkse_mYYL74bt>xD4eY%s)& zocAxO-bG|cJQ<7cHGiNBzOz$uKA_4GJ&(9{PVM}~l#pAQZ`j6sGtGIb0%Tx_K#Mj} zCmcfyUw%*O2&!Y<8YjmzEqIsUJ+cwUkXI}d5}qN6R3gMIEr*yQFVL_#6XX~9$I516 zAGqBfY$ckw46W)=k6xtK~`hb6c@L7(^YCR5; z=PNs3Vv0Xsx@%GC+3Pz{Sp7pL$M(BzR!eFPLQt=8av>!oNeM43SdBA1;rnmiT;@x} z_20bz0?oO<-8uEZ;TqK6K#&^udI}XfZ9fl<3_VY{@!ljMcp0N@wXSkZsX+HQ1-2^o zW{_bJzuQwTgVNsXpL@UQea{GHjj4P9dHjGqxIX?)gxb^IkEa;4KlZxnJ~G+Vo}IB+ z*Ewp0xRg_=a}%*Rw=ux)_+)^c*PXgTMNq}ae{6-P@N}J^K1XYl*rb~Pm zgqU}91P3R$jZ74L%Rn@J&9}#8({8l3M7@w^674ZGZse!Z40C;=w!FlETgs*q(kpKb zS0bpUh@rKjG{Y#XF3v2thT280O*pMeY9A?redq1h5MTMABlc=(%p)U_CatDsY?vj; z5pSN@I377-GQ6E#oz`VR*~oEyX>s*(MrW{ok{lEvPEID@B2oXymDqvMSV3?Q`A|q# z^d@SQ1Q58`aM}k_KSzL4BPQvK*sJ4EF?G*R;@`)mKak*btY^*FqYF9~p# zOK6_f=0urOY};wM&mA}D7EQHYVL9h~ZFZ?_X1-#0Dd4NWz!+zCaXY?cSc{5kDf~u$ z#!n_DG?f*T2o}QIUMoVRsq}vRswzqfe6_P@nA~#A7uw%*QR*NkGJS&o;JJ zdM)-^(8P{;X`L&a$7D;hp-Cr;NY7~+7IArItWi?q%y!F@>`3*9bh@g(WwxEkokX{? z@COtAC84kn5A|WXZWSR$gMPAK@HejVoh^jGJh?GMz6HMK)nBV~ncSVp7yUBKX4v`hIZddG@7y z7m=s6UuC9+gqF`F81LN~R9VdM2H7rgc(e}>uT3C<6qo?d4 zTDp&$$nFZX`7rn%U!trU9XMv{&RsviM4m-)-{)o@#W965Rh(OqFOF!6h_aS*;N;=q zdw+W~A$9%hOUa>H;qfu~H4b~j<+`v%mWm-$MTQR*85V|1)OluQ+ZgkyftnDM1MI|^ zu%|b83wPR_icV3!GTKl-eN9A}!?(bLAH3}`XVsZrwM{L!O8Fe)%fG^&$DdQy&D5Lhl_byb4l}ey5?;TOYD$S$Er*S#QM^tTkcXS4~Tb^(nckr49MYViH6B zb3}$>k@7|QydCXXnT!z*MMbJCLXNthGzX$awJY&3*V3`pT3>h-5j$$shaFDuhJ`CD zPVSN?J!K<*zl5P1^G~fFT+WzbbC5)iF_o}rIrKRm4+%K?>gA;2L*Cpo2%DntoE*1d z{^~df=g0}|Z^`5B6)R|O<+AZ=jWX8xs~AY-X_#ubezP34+qkxh1Mu!shDA2<#}%z? ziSh}vlXtfrzuV=%^k6JCl!hB>xT_h;YMhlfa>}Fm&cPJ?BtbCPg0{X}e6DXSMc)I{ ze%Wl}{Z>kv`QLhPAJ295P}QD#b5>>AK$Qbd^Xk>HV(CKOmKG<4Z%8oJ@^M&XY@{@= zgM*LHCCf7_-3ljMbs98t-rswbAZ`>!uSx#!3=Kax`lrWY%Yt(o)n9}}TfHeVJ|W9u zb87HKIwO)xvv-s7@SFEW4uzY?QpMbKi$zpIzC`Q~kLem&gcQ6kPt9%!ayq!fzh_M{ zWmmpz7hfeY^R<0L(hMuGijAM>Id8une=$JYFB%PXi_598s~!-!mrEw>t?Ewy_Kk+w z+Q}B;!kGEJ#;JbkL8ZedLocp1zka6kk)t5YyI!~1lA6+*EsqT z!5kNcBnwIFlsgrjqiZ=KeE6a@6N6^UG2NJJm#!D@D@(l@`?4&q5n31%UmMsuS@K;W zzTSFOjDEZAYXn5~mdWGn1QWB@5f|@_Tl*_qmsbGQmTR<^Rwm5<-0$w-$l$<7NZOZg ziEK|ByUH2pq+X^sSeYcmioQhO{`%hTLf7dt40kC({3XS?J+xTDW5*{xrKCI`guUs5 zFC=7+#QD+%CQ9B_4>ymBIRSKb4W$Rj_5TtCoDV`dI=@I$ zH?ZECq2w^agly_>zwn2u=Q^Acx5r$bj)*t|kX@q%8?W5Fm=_m2vdN?_T3X&=>d+Ue z@BA)-lHQ^Mqa3Ygl0vPoDj;n+OSY$-XoMQrpYF>jJ#YB(0(qQ9l8uIuQ4HPiJmgiv zHETV(dUmyQbEkyW-r65MdhzJVOJ#ZcnreLfq*YZaB~A3JGN+y>qxbDn?c2|pySi0V z%&)nj8FLP?3*Dim0AFOxF!otF7knJ5y?L{K6ow_FUz!cNp39=xz*{UAbw>$($O2@# z9c});bZg88#!=x}H}-K_Qv81NlG>sG15;@3=y~?EBZ`vxiW-M@Oujuq@?kk6B~bgC zpV<;<8m$~=mY5nEF_aH(G*o!o_`Sr}moB1lYR#i#t;gEV&M|W~Ej2$Q%)mNU%$P3v zwZcA(t2^TCj1CvQf+cXYR%RuojGmIH+ z?mu`u9DBeAkGOsNmD`&-vJgT(j@AWcrtF6hl>;YFHWg*AWo-4HD9x#`0=iYNY%b6K zQd5|v%G=PI?8}SUo5q)Pq+g>@hZYZ|^N-Y4B*H(0`r=Nz@6A?S&c4pee_@BugO%q! zU-mgahk6Ih`CB+#hMu@F>H--%O|#ufQpgx=Gp^=$CXWW z>9s$2l+1%uVZ-HZje!TAoomgDE~o`L+?YoU>M5d4{R2KFMH=t-9K-$z?$s{$aQxJw zi3#7Afgm$ImW7JL%qL5v8Jqh+TH& zt>+k;l4mwvRN0)gxRrtH5oeh0#tOkW^c><1`zEh=p46&L^rpEp{jx>QVAy$fqV{7% zDY|@+_Uyeu;#jZr$HNXEgWd{yJ<&TQas~WgQDZ2Be_Gbu!PM7R!S4$_+9!amVmmUS zMW{)k51U6Grt6}@u2S4NZTv952`Xe{7HLW=H{N0`Y=l{iBu~$dEzh8`FjPIU866VR z!tEnnRaACLjGyl&`hte~C)Syl#WR?7=aHplC&vCQBf9CQG3M_*@0eU%7;co{QWvzp zm_nJ!;8|8$G$wiF3UvdF&$99jN4)+Uo0rVlYMI}psm@Ry`zR84t7(2@cqw%EUv3vz zE3_z@*+5Gwwji~^vT$&>t=#nT>&#bSflM#Zx~j$&7N+{5oMOFiJqkaBsZ8@;3{%;E z0^K$}94X=seeU09vPg-7a9+f;gHQj1lw zSXgdh=kX7297l8%_J^Meu#|uM*|qyrMXB@@%iy*^V!?!|4zkQkuCD`@S2dt7HR>VL zDODoTp-lgL)HH*>!aCC|&69%iZHIPGpT6>G#Y27C9EG-b{0FMd@&D$%>hJdZyNUdZ zN^ac4E9Xl}>`s_lR#f!&wr>d<^eX zj|+VCXVx2wKV1{KaG6u5elp?_d!Q@$U`!2gFW$vDEt`k-A-<-F2hjfI9h;7o(#B-i0Y(sKK-17&Kq>BIf*+Ruk%XYKF z7qLu}{TUXY6S-JdSMTgc+#NI`%t#k_IiFy~o!2c{8$ps$D^3?~V>^W4>5uKFZf4_+ z{h+1$AEwOzqmutc>(J2{=12~htw^O4%dMGKi0gSqg3V}ZPTKqIPV38;xe}1HTBc^r z%Bpg=lEt4|zkT+#cI43_%Cn}XaJb^i2z6C~;QL48SLq`dZS}dV3 zv?(bb_43dE;yQM!6_)V*>W@metr3UUv2_u4fd$5}A9@b=E{S%T&7oq(EJq*2lpk@3 z676N_c?CJ*n1Sb|{T7$Nm{wO5nDGAc98O%gtSc)|lqc`Kev!~bg&erwwwIg*if`#; zXVLnGM!I=9!CM!@dZ*;D@u%i~vc0Aacaz@5^He;(oM^u9{z5L5Q zI9g={zsfeo#x*^cA;X>$M&H7X&i7yYS160r^Y>@1rYr@aR>m!5C*3cBXpQ3cy45mX z<#3yx@`fMPP@GPUJ(Whk5&(c$Z4;Fm8P>WO0y}oML zlP|+ZEpGQH(zpl?zms)D9SL75_uuw?vcptfC+Kl^WCtEMG!iwPKfVxO`*=yVwb0Sc zm?ftY_v&KYw*TF4N%^gi`$fy@id z5$2)oa=sZT^P#%iWHHK;Q|D&j1=cxe`t9`IFO9n&6VEe;K;&z6sy{#u$>Es4;6jJ_ zmUP2%KhV0|M&!ZonJ)wEjtqy$xJvK!BgyBw<#hsyM3l_gQI9@bdYx{(Ca4GDtDKzy>u^+F_VM_7X48pW8 z^Uo)&_o&Kg?eR=Y>R&Srq>sD(I7sal-E}gnHYhe=b z!bpq1VKnw_>Epe8%9m#z&9%~VDCih)0ixt}c;9rqFL6eFo=_L`7k$qq9(zk)8ogYp(Ywt})^4U&G5zIfc1PqYE}t?~okl;4HNQR| z5lw!bb@r}STwK1C=Vur1;-bLVqXbrY>J}l#M^F@vXoO~9JyYz&!o6VVkIxh z){aUZPtejyI8;%DW@)89UQn;{TtQX*>3jM+R6ux_O3s*k+e-&bKQg=SO7pEU{VU3x zHB$l4ty7KP>0V2^{!ne@F#o)T_BGm!N;&`8Wow>j(=`NlG(|k;=(t{fpYK*j~~mc~bO;$)-u8I!E1+BO66eS}sjioG*_x(w`Q%P;pV zJ2{6>Imv%KjYUn!`}!f8B*Wzw)7OcQ=a)z2-4b_URXAc(u6$?LT9SC4;;kXhbmT?* z%N;kQdBW7h@`T=JtEqD9#mqJL>;7{os0q%dLhpdzG^fMUqbc@pr9qXLDS zSYm^1Bqn)|R2xaa&TzIigdrUvCi0{C5eh=xXceWjk$qFqh}GyIPl?%CfT zNqB8#lRTD^=}Te16m!MVG0TDJV-c198#NyA%MQo4#C2dvD^8XKtOnCpxSz{K=tB^Z z0Zlt>YZ(k06~dzWdVUd0FZX!N7soOBQQg;^k{CSVB zlGEO*K%-{tzp|JP;&Z69R+fKAHrCCg4>_AZ1=n$SvbC@wbrgq9Ur&4aT#u2?<=&l> zTGJQX&=)xq;$J26#b1XET&H8APWT+41M7U5c+NMfIKXkyB4|W?2IcA(jZLUa8DV41 z05|52dhMszU~PYi$PY&=Y`7fH_vH=u(VN|RjdWXPnTV|)Pz}v!>FTMk&d_D6#;GzZ zuWRj;@vJTG$kutf5bKxk61V3GozfPQ2s6)F4?;k}93jzRa~9$WL&x$mBRxI1mFYv8 z;f+&ypS%v=68X^e)hhcXpRl2Bw~n658E}T-X@}>S9zZWAqL_V{YGpDq@atY$gt|JI zSNYbm`9SxWe>a`Lx8d3^z2I9fg+`^&l&h^zYesnx?fqEZ?d0a(V;G043k!rz?JEV< zxSKL5Bp{}s`Gi*!+e0nMj(Iug6w#RQ^vi~={~~|N3c>@9_~QI*q{j+Y+pHS3U9wgp z+V9J7xi$(qyH&4OIbG1cWQ;Qq(lF`LtthpugV$@g9mtCOD-|$nSL{foV|w?C$CB-mLU(Xk?p#L3JARn(H8_J`>_C5&*6ajFu5C4-h4=E~8$@ zsZTPvb^B>%?$EByq5@?7;Nuqj7|FAkxZ+}e!vQ>H>XuWyf8G5NHo6brNBU|Kg~L0n zatt0z1~aHMI=i#MmvUQoZWD5r*xs7646BaQ8?#K+?1Ep|(3;=y-7er7A+l#Xm;1Lz zUB*ZE5Mz}Ah2xbUG&~2gIwmD0R~GZQ#4I3ZAq;x<*yG7yml(u=M*YVUzJHl?{Z7cU zl<0IK)MA!rp@eb7kluD+IZ+?MxBvp=-@QtfXv3IHrkLa7Uy#K0R`4bL{M+-#mP!nTs)Lck^>#}HrlW{c&cDn5UxWzboo?kNh; zb2<}x`sq^U%Fv089hSJzA=A1*VP+)fV0D{bVZ*(!2LW~98(f82K*!F=I@=Fi(^Ay- zkF`Jt!mS0ZKwq{gO_92z)of7DaYd9&NlkTZT-BB2an!_Rd(L55@iNbGb(R+<8kOL( z!m`tS>Su2Vp5U!p7}J*BvOB9=uTeFn_4ND*6dr5tsT!Pl9)A~#WO)X@8<*op5Ry%UY7QTWZAo7P$&EJnQ}AD(z& zm!S$3d-roIPOH%x99GT*9P*>-gaqjNJz2n(^vY<-4v&n`jYj)V498DJFZkWWhtxQ0 zMSoJZ2pR5O>(lMlZ*$$AWE(4j!Ixeqo(+(wvG7=VREmIr3W$P$N>c(vML?uWm)>gt1rkai3JQV( z(wl&a^j-r5h!hDO=_MqgBP9t5LJ|q_yV>LHJ@)hN{eI`{bN=jc#`zm%jeD&%+coDk z=Q7pmsa#)kZ_)#SEq45QT>W={e8Sb_Ssfl(5$ynL-2H;BcYi z=nSwcynKqkzyrG4E%;{LibfGSP9fXP)mtyGx6U$nc`(z+hx<7vd!{awFUHZ|@m9&5 zszn7I7MeNbTi)mdthV-jS8rQ}G1=7W1I_99&6b1L}DpZXWn*CVgM@on|-{6>%92i?}LJHZ@f&*HJa9Sx?~-KUh>!NR;`c0J70%x?jP8n2}Z1 zRBt6r!o@djqr|Q^R`R<9>n|eJh26a)v5N}PVb#*IX3STQ`j`EYfID`%vO`(iAn=@) zQ`fn+o+F@VE;Bl!XI*(WH=_9SwUvYuZtj1SH09ndI$#JFpgfZ68a=KJR~+$lFcmdw zIrF~rj|V9qMgF)~#P&0P03t{o_g?a=x_vGF{W1S{l@rFAhteb;huypSA|6w`48N7NBjqSmH+qh{K?D&K`3p};14?|sK^f15u8p#Syucd)8&d2yLb}~0NHAqX zR`PC^fakc4o!X@Tc*806>0%=1OpIY%+tPF6?+{+t`>v>C^0|_y?{-U_r;uQBW*XNsetF)carJv5`f1iH6{LRXSV7LGde+z3%>I?@!o{C9JzE_(!sCv8ALpA% z6Kn5~)NbU=vitL$fvn6qO*UTD98ySo-L!oo)~d#{iO}qSDs@Eb;sXK6qNH!?(k1uU z-d{6YdU5JLv96%rG?Q5sT!A9(S|WcA8Us3;;j3)=pt}FTo8FBZU(f63vL%R{t~^wx zq)+L5V1OrVPRrv|r0!aHdS5{ChuZD&2*gK>s&aRge=LBLR4*lRJ=5gVJ1m#+uyX7s zg3!I+i(XEd4IwN`J*YD?Zp~h@w$^}`x3occPwEICR^JNKi zWX@m$&|>qTP?$p0M{9$$aFRm1Mcvv_?cXN|*uj<<0kQg(M3Esa%1n%IVy$!nMI ztsZLL6MWq7;;8%fB!WYyHOKp^hM(QCJ+i1*gNL}yrJVr}?E?E{+wFZLb946%L9cjw z!@b zPTFs_JsLF>@WoRH+$pQS{=D?!KKCW+pJ08BC85wO4N8hzB7CvRXQig-a`n&mK6_2m zcbcdO{=G`>bedH6YaUlp)Ja~!)L_qK*Q&ej?ghWu6e*=nJ(5@Y186bL8?@)sWMssu zjR&o$(J-e?3{%Tl-ykwpHc%wyMiwjv#FxNRZ#2XKjHCl*!7vV2StTy($dyYPm z6`Bgr+!r1aqvrNbLVwzS)j#5j(XctBm!8*V=LX|`kSf`5z3R>nne?aP;Q6t@8=bN~ zn1qTi7>4s6pL_4Oz;gnSMU#`h9(&z7)e>|lu2o=SO$>MLi1`<_@70evj|)60cu+GQ zHnw&w+sZ+TD1}woXdJ4UQEvTCJ12Vln9vHi^^mVxUK3)(TYV16gHrqVU3nUxCO zj_`1LOfA&=spIvUz|ev2Qw7h7gQcW*U3^|0Yh^EIlLurQXLZ4(2QB_CTZ}^PVl^N; zIQ(W4y&Uzu`K(9sXHG& z?CdlM7EGgEIK8>sryG@aP4dI;YCWo67C)}w6*AeB$?QU>lC6KU-6BO`e#Y(*_^~DK zKK$D!(a;K~o!T+K%tcSrk%jF{Lth7qTwQ#VS}cA)1SNCfVswbe=k6Y#M+Sfk{kVt* zr{L5{M2?u2MT*7J)dhMW)`s_&1(=fSwp{<4?Ww0Ae!9^nE;w2z*BERw>3OC-obIfG zK5kP*8MUV-C4Q5<8BA(exi|_qC7nn?6PFqhlmrBS2&{; zGNX%%szw6ci3*yRT9~3=#eCOyR$N^A<~)%ZxN1MpqBL#kyxjE!^78a~ zjR4cZ!QOB84sPpOBtsD~2a(LrDDv7Dhc`+T&J`a}J9c?ioR%h1sSEe^LzSH`|TD7VozRFzZHa58k65 zoyOzJ%q2<^8(AI4e1qAAsR>wmd2r4)DIYk zzL&r->%GD;j^TwsX7w zETHMm*|U7=DQpChkp0$N*p9{yr|6{%q9TbXDdC!|JSvovN?>c@=n z&xWZ={>MUbDA3&+A75MXq6Nzsqx4_eivuR&=3$RsXgD3zYTt@=gO}AN2$yKm+h=E| zTgM3ep#_X6CTyJ}7Q2$k^Y-i5{mC@loX@zQW@X>%PFt#LN0{C~wW=3JSEd=YH%a;e zT2M@3RK?Ba@Uz@@xykFe4rYgnl;fVu$0lzlvfvQCh9Vxhl4{B94ll0?B(}Wlu=klF z#y5-7*Qlwb&&H*rFe}uRi;&PO)!8P|5A%-#2fzK!6}PQYx!6|*7kivNZf4~+xXpYjMz(fieGNi3$8@U((%j$E^bc4JZdRu$ zAc&tdjM+gxCBHG~@*L23ke1zU%38bQn(L)5;;Gn<_0ySSoMz2O#-i(t{fy}YnOu$) z`dX#iw<|t!0D5%jH``rAinlhLx`}w(5;q~(sSx(5w~vrXD7{jF`OL!q?8;{L=wh`nTZ3-!Jw-|sc+c3-szx|3$c^M znVzG>@z5e1_zWy%epBTO0cA?hR%y+-Yo-wE%=az=EXMg$PXEapzry%5Ae)grL+Cr- zP{6oP*u^;QqN+0F#T2ep z!3&BmK;hrE-ZIw2@R2i{Y6p7rD|aTyh=`Q5K#AatER zPMKUOCzTTrH$uUl%IOmfN{fQmTBpM<+0CV?pq8d0RS@_yLZhLcC4NESynggfhM}aI z_{e|+7*LlK<#1*d&5NTRX5$UN!U&)G&Gu*Ye#xY=)A;@*knXbZNBeK$Xm8fa%AwNc zWbLcMb=Nk;6;*Cke9O z@=Q56>_U7CNDt;nTXpb06{F*1Vye&t%P01sCY%+H%?+528IRpOYuGtLFItE=5-kEq zgX=%m-45c2QT4fk{_#0qKa{Vq)|*+mJMWTJPD)s4FxBID(=%dSDd{Jg5eY)A`MG6| z@$+M?YEO_nyWxIseR4c!?Pk0ZP7lw;+r>{l#aw?P41FBq9;Ys0P!5kfPbNRl^wY>AS=k@S{$gzdRpGe5c89u8k0&yOaQ#p0 znqZxpSI4pE!j~Rf#Z_nJch0XBU1W_mbq~Mi6MaP?3k3?3R%;-8?c2ykRR8QG>G&l& z&6eNwPq~vG?jC$c?mqbXT6tJRuE1QH#DRYc$I0JSM(-xtg(oUkatUcUK5A;bc+wgl zttE4Z{#Bgs%OgkLAG>U9m2+p3@Dm|4EbH|37s6zhApr{_)iQGt#ifc>rI-80@1Km<0ra z8HmO19k;+`fdMSFRKKz*Ri9vfT|xc42buJ}*OaI{EO6A)r`6EQ$yku1Id5C_s3qh` z*ImDo;0pg5B;bAi#)5l9Zv8qHVpaDXwNV4BAKoa74}0n|=q*5NyouFtpHHZ-&Jj>& zSamc=JfpvRKE5Qr5GE|!Es|lRhPufPWD^z$`RC5km5P1gGK=jvJKh0cpBdl^b5WM@Z2XIYK=KUzO|^Kile>olpjcfCA+ zeVte5O;crqy!@3pfXTCw`j2P*?_>Klv}DS+xo3elR(wU{I_z#9(5D=3rIZ$6>?wDe z{gsl_Po-#GHW!giy7PEiT@ zSMBOu_c|L?g-8Sc%kL3e!acTgn(}OCG)1=94pI!%>gtFmyk>ut ze&MnWJaV?}$N^CY{qI-&SDC)5`*XS@pu#F^x?aOpWjZnF>bJX_W_anE&%GMqsZgn@ zy^2Lhy~99%62$t_o`KQA71jeD;9?$o|Bux)V~Sd!5qqC1dNx~z!f<9xlet-bz3b*L zdJUG{C@27H7gt*3crA(KW;o>z5SingV|7W@ZW$Q?(;~*U8V47{`d@-n|Nde&{*j${ zVEJ7kOcWwz(hDQeGvkCtcWEi4DC>xnqdOqlQ(`chCTNX&wn zOD8lj$FLi@AaBlb&OkV~ZbUtw_G?{i&xF2_W>mNAHF3L`g?NYJf}#j%pxl@F@1$EKf;O{1-GLh(b$K|l zBoi_)(a`b@Ffh2Ua9GDc6J^^NmIpylDSe|mmPvnDzCJ_QJJX0ux7t>s_rDggJ|7+S zxO>^j@31B?gy5qG94KSztsJinb#Or^?TB)iJE>UgBE07IY!=BqJ$LW*u(&4x;;9(zjuEt#{~kguGVdqC-%u(CFi%>r0^-I z!{_HXqK`#pEMsks@2>VnY@A-z`aX>>U5hQwY^90ywPcN&Gx7W~DdqkCN=ai$!Csb4 z4yOKmuiR@i&WU7i;Mmav1;8$4Avw&ZR&7sRI^*a#KhoP15s&z@CQFa%;kI*3!P%?z z$F#*z3zYl3&&~v6-IB*vGj7AGZ*0H7AfhMVIU?`}QsuPZ>!PB(6t_`;iEw_IXIqXW zP(|&i3_U-s7{P@@nFW`CLveVn#3U7U8xyJ!9a22+&BFZE3tFD3A)zZ4GC0PthK-nKSl zl&V?+WF))}FYf(Bn9(W*bf*|0lni8n-TF%%nx!_qbjtzU~m?^Z}@FgB(;0nR{_7;675pY{=@U86gJUr&rP{4ioDR zp>e43;U~#6A#IdJnJHXF)ov&uF1QV;ILhBj4K@``;?*%%{BX(rDc>U(8(9pXcugD` zzuEdTi&d^MLs_07<1+#R4XoQR>pA*f)1LIa_3T>Bn?8WaC!Ms1btaxc&7ydgu6RGj z4WakEZ4Gv%&R@EfT<%Zy`&p@<_Bk1_l=5Is6nPcagU&|WmLJe_{@IG5zuu}? z*7Yb5o30Hpx5y&0eiRJ&>3+jaWwlr|uOoHN2vzv(v4fgzdw#Q>EBM$w>5O;D^~;Mm zB+|Np10!yGc0l#|^p@4OD#TCW0tsm0J#Y)i^so7h$N-4VE1a>yGh#@3=8Hrfs~6>@ zi{%qNMkD7ko!Mk)zMA>X1`d^n2jwj8wqZzviS&+I z6?qaNT^TvMBdhF%T9q-SI$NdQ>GL}#HpWp(S%Wx4+EfDot;P!4r+ z6P*1kk&r_CCA2(EAuLUHD3?*eL2zWwLf0naSruiUh+5ly?F?EB@z**1FxaAK>%su~ zLs9=g_E1^1-Mh@zW&ckHMM^{El)LkX-=^A>Z(E z_#C+)cBfcWhN4tfNN)Ak?MY0H9fK{QMO__zr|}|mtQ<4GsHNR24)mgaNp(diWY27H zL=rB5S0z+<$b)?hQ)*&Wkgx-sy3v0I5#o3C@aJEvhZ6{QvuXGiq52vb$0~s}y}FNi zokNuo=2btj(PdXtid@@X0GmBo^qVbHsQ1$(qFMizBN{p)OPq2=0%x-?=JZ?yfY*T+3L$Q!{J;X=-p+kUID2QtTaZ5)ga%U4cJl z*&{A1;CYq>RSQFH;h`)Sh8L3lY09dxF337A7slQ(l!{edvi=@@SANpiDHP;XEHZ13 z&m}k)er;5I<5o@I{BX;lG#;G?shu|^Q@vVgv3mk7t@a@ILEk7 zDFIRXo-?Hxc9e<$|B2Cjym#z6sS=+&&L4>k`o*5#Gfy3Hd_QzwgtIPwNi5n;Sa1W! zN&3hN5ZKAWz}*<&G+^8lq4wI|c3n^^*OX14VTFnu^r*_t+F%9=hl|0=@+xOiuPuo` z&)leQf^jrltKpCFplr=mU)QraeZ}z2+EOZz<<+C|pwMaF{a&wF?)$^TA?Oi-XOxmf zWAA>%TaezO$@*GG8KFVt{$dcn{i=MNKRIh2XG5@R`LLlx3RYs6)n`d5@G1-3{FLt* zHYP$^#08h=(9gD3Dw{I%R4(m$AxOGY8*#u>@*@^xh27!f5@*<5{f^;gd4-Q$dMRpv zStLBBz$yV-H*V9hjbJ4BM|MiZvb?gs0cxK`Z^Nd?z99(2Y-M`?obGb^6~3s@6SG~j z8`?ID6<$*Geq1)(3VLh5uy^ugO8=J->9MJNen{8)?kFiN$tq@Kfp#8s4Pk7~F8HlV3bWrUX@iM!jf+Sgy<=YoSL9T zp2n)0F*}hSyG%ca`c@0scVlJdk38(d?`K^31vLMcX@>GL$&BM$;Q*;ga)wb6kJEdL z2l#`4A1d4sY$UagtP$Iirhl{X1Ys*cC9O4C<7lMR40dl+G>gTa@tFT`U6uB;SM#5%NOG?BxLa%G+i~mokm+N7t|vm;uv>OQCYKI1^?t9%rsM zIh_xy( z=^OY4mNSAc)Ifg(&Q08>Sf!THhtugeYRTfH;~Yg-;n?s1^XVW-Nzg@k9MtDDHaTp# zx*?j|O)QOoy4kTlr)H=BcNhFP#&u{G><+)mM4wSy?FGgGm6zrV6~!byhGugHbnW z!=-WyiZ+1TO=bROW4P}q41|nM^VbxfZ>Du&aG=rZ8ju;pD)mLT7x7bl4aGS(CE@sL z&w5yNN_3!o%xYmA23SvVU2jE#Ik3)>hwHIymGiJ*!P^4HEh;WMzuDSDd+2S|zodnu z6NBcf5yH0-Tnb>g0qu+_!f|`g6fx;tYS}m=iPnkr7Q9y63l4A*l+IdNDUH|31W_O#qw9jqHp}X zL#IwXmhaOtFjpcy^o#ERH__A-QH*3ruU;}Xn2|r}8I*)kU|xlRsK!k_61^y|=%M6b z;aluBn2dyTY8SD+{#}xRZ*mSFXS)0p0@BgH*)E_n^#Xsh)g0a$;%aSmhX*lI-!THG z%&f~u;8=hW5?-l@l%z;Mhn^YjU4=TYZ;<-Bon-v2;wSdB0`y0TxDJ)2*b}LbyEi@s zczp+Gu)6zt%)wA&fLWS+XCMqJTu3=J?XIgA?tag$_CET z2K^8DioZcM{C|e-evjhF%T_Qq2Nf9_N$-mc?+5m0i$Rf<&jl>fv8WSqwc8E*`>OS~ zjV+$Q^(>Y|BI4kazuEYr&k9Ou7(B&%3;q{7tG6Sz9YM-pC$$O;F~5K_C50fE+Dh5| zMD7uK9nu$MVzs6hS5Po3hxHcOPkfn?do;dBLsU&6AtKgnKHgwn{YfkEaV<|Dhns3@ z8QB)*$;obw@wqp28XK*+PN*K$zMrOHaHdQODQ~N`51f@S5bHdpA=+KgL>y=cFlsI< zVAeh}2iSiVLRR{f)#~v6q$+bBkrE-m(Pv%SCd%Fmj^nide7a;icX8$V^`$`wyi5MI zO&=Dk$8k@z-4t^wIr&Pq$bCs2NzU8B75*Ls_E7hqk=uXJv6Z1ZKLwvvTYv*cG<8zj z98cZy%5K3ov~gM#R4CNTD?mF*Efvxd#)+TLt2m`L)OBwjk12}vRu_C-R zletRn)E%N18Ba0Jd=ZFxzv0;;X16FmaE4NbHP@{nN~X>PM5pae=!w4h*e9xP=+to} zzE3}DF*#}+A_k<6_NrP%5V9A~>`pUqYfRiI!gEt6? zdYQ5S&pxxHXt2iw3p)Hse(+oBGaU_c%Ie{n7!8ogY52sP;TWTggZ6h2aNGHncReuwea0WEYXhM7Q1>W9n{_V}*F1q0bbR&~nV} zTkmZOPSE$>4BSWEqzevAr%U!#K2IboanrcWiO#w3V%N~2PiW0neDo0qw)r*B;oTRRTM)qdA-Pq<%r#T1d?}Snw*|d{*+zcn3*aW^84mK;f$Db1hThapTKp0{~IC@XlGL zP#un98wm+OWh)fA*u>w0N-b2(EoE6c)5N;UN@fI1aj23)AGu&(S6Vi9Ln+lBQm`J| z-{n9ZHyZvX=pqr35l$>}cXQb@N^Y5KN^JqBT-~%vqzEaGB5s0Az2J@XKvp7;3qW!% z73JvGM!PTUjYYRoW(3Bow*$+{j?GVl$kInet&X0N7L5YgYx|#b5WH5@=?%z9@|MP& z{2KlB6yZj2W)(}*%O;_vYMTemyEjIaV7@4P=U* zir0w2JlfWImzy8UQ(T&8r3y$&CRzHW^1LzC0>Lb&TTs_juJ5`8dY+D(w7FCnjLMa# zb?Y{4ngw;;_{Q;c_o@WM2^rDWO%xoRHq&V{j*G3j%@xr6`p+=&rsJo?S8>5b7QPJk zVLJsE>K1+)9dFe#jVhV5-X!lcY*2g7U%X?8giO?up1IflOB6M@*DlJvnJxI zfyFz_Vv*y=kGWx|{FU@aJKrf!Hu2VTw3p@9s%XL&8HX}w6TK~AgF21F!KQ&b`4&fY z^un=eDybXF9TPH(3%zRZGYY^uEzc~X&Baa3uD9axa<>l`23Pn!fTmIdHpL|yM-jXz z{uL4#01wMp%0^|q33HwN_O4X+Oh9aVuYFU_vk?+LbzKF^;L>bZe;)FBti`d(%fK}AqdJC@J1$W!5NZXIO-?BjivLDi|YRGQOZ1I}oI#H1h zrV3_&pMIKEb>H-udgFFd>*-g?2>&aFD#eLHu{~vgSV$833rdiXW7~Ai?eGdH-Zzj0 z5NI!pPdB#N-R@R zUEQYEkIwK{9DQ9dtYutZU1yd=y{ed>oVR`8Ml($rp77Q+JeofF=7;o(f>jN2NFDCc z1~{m5dxrDp*-TOtTJL21U_tZYn+z}4YJEDc%xyew=fb9 zSX&N9#C6gHojk70{*oTKoeJM!hxi|Zp=t8KP&^c>1j=IlAjk9OBw9=ec5SZhonLf5 z@4G`9#>Pb9WrzFfM88gcAA>XriSj9H8xB+eaO<5I)h^u2UyaL}efikRSNP~RcqbkV zssy@c>S>0amh$Jh2*JPEoK(m6hB!1S>luZc!y~AI5?jlw8r~P<%Sw4l60dr29AwZ{ zRX~hD=1Y8tFV!S$1r10XIHi zPY>n$YUa(|GKjpO@f-dHuIjX+2L{Q;$d5fw2x`ed0lyTRDnZ zfqEMNLq3LS45Cx%IjIIrkEsw;Wl*@cU8p=nFuJ^dlm@e$@V^Qirqwv=CU!D#8OhR< zm~4F9q*sNJI($Zaov(6Kw*4{>Fl}}p#H>(xv||naq9~}h0-7=B2uEK;T7Mt#&(Va0 zR<`X-!d9R*7N%|S8&dH^=_Gy!7$yyurB<6Mq@ii7bsxFKIK>iAclB6bdeOHGCNs5 zhKE~Gc@*%4#OKKleyD?ZO~&}n6flz&Gv;)q^EjR}#W?CiA@mQxz!t|(gL@+HPAVUt z+}EsT*^)fDX>>F-v8Gj<$wPXon=vEy3?BNMO)EY0YcH8pzNvKDda1OXw%dn43(bbU z6(1M+DlUF)-QG+`W;8d)pA-p4P^pYV&A$jsWzyX?E9dd3juw^s^YYy65GdlY1Ni%~ zPC8C?Je^Dq?eU6PD}`?0&5D)sLWvG4Yu(FKb8+JM{Q?0)5kK)tAg>(H@4&EtB5ZeA z%Vh7&oEtw>9`4@A;ogf}P;V<~fopNEnjV!Y3E_IqdTC4Oli zExV9WpL#q>@^1b|j$8gfa+M6fKwoSLy#hB`BgB9R4GU!V*rb^|t&KDLVOhTK*4Ng9 z_S_8G!lv$6#!hvT1P0WkOuZrQC)^c3yeK*ypK-O&^|Q-0z>}1Fb+Qby*06WP39+~= z=2w`D1CytmG$XjAe1A$=sE(G?U3>~EQ#(i8^fs_>HCsg{J6pfCx2NgcHXJsMsmCTn z{`odGqQ&0$J>XGrEr`TOPnSxtoT9KZd~3GFZHv6h;RH+d*|jm6`^90myqC(`%zE%- zK-!+j)abrQS||x@niR|S&)F=%#-(d}m3rQNbb0g&V7R?hWDwH*1!}Y*OXgd=)xv)6 z6u-orh6R(SU+w-xt#UAuCdY2EE3Xl%4|P(xeHz!~gk_wHQMNR?y^!Lb_E)F#(>R+b zV2giJYl?ART$G~r`l!b1w6qq$N?Y6Tww{BJl5~eyKEQ0(?ZYAPhiiirmO~4rR-wGRoWAiA zA6Pay$Gad{@ zIAqYPyU5*R`{vJwHoYt~!(3y;ueR#pmOq#EZab;hil~K-ad5Q7oAr8%_&n%(jqWWo zbEE>C&ls5J!>N}b2@!SwxzN57wR%~Rl0d&d(?CG>e|P!tmik0QwqZK!YqE~ zeOsXYfD}o7*J9TcEXIh1Pce{9^>|-TqNNmO!#m9C5cfit$vhQQ;QEt<@ZFX6hpKUL z`Q7ZhI)W3xw8RQ?7$JcnhV|CfSH2rPAOp#gqJskDe~JYEIad5VhBI9u+tPRpnTib6 zX@cM`){8}*5;#3$fhyXaaj;O3G7Ytrhgyi%&qW@KCTACFCo5_S{1G-j7{+$|JqLh+ zJkCxRZRHk+@<nhOEm^M>C(<#{|F<;r)nmK{*^vf*h@{5rbm1`Ns4 zEw-;6kmyP;I8z6-1-%;fB1TEKhfb|C&oJ6ZWyGpbGvYI zHF0G?^hjMT*Uu`=U(HERB#IT|H?Q|v_NXvU6H_)^B^y(|b;9(clTWFcJc{a56{o3> zi@gzve{y`u3(~j(3hD5|Z<>r|)~_8geSad!RQQS3anHKuKHPbu4_qSghE**!;%wACZUo&hn+$}@<=|v;YM@cH*N(Y_HRA1%ecZ@V`G$)e+`O+QEVvH{`f|BB`Wj1l8);y$^dYHQH_mhbL|9re1( zaq8$Ds<9Wxf_cMKZ|zk7HGex`qxdX`NswN_uSL5Z^^VUaU7N9W(|f-5kc*+J(kVle z`oxx!s4wkyZW1!->$9;Q(uR7mpJS}^%RjqErE$kkM*;9WZwUQgPQCndh5O&o(f`9g zLH{1dm8_gLA%CJ5Q00*ouoPH@!j916T{RO7f!{gT{>kcY`BuS9x@P@^_j$0Zqt8A} z!0C+JC4ZKjsb-9P?e@c0-K`rq{kVI(IYFK)Qv&nN=y`eGwN|UsMX$Wt864vPPU)LT z1fyu5x>S$N6YfavW^SKE30ut@IhNTEipIFZubRgnsQ~U{Fey>XKvT;=SvJX6Pw&*I zLH}@bZFL`CbJ9rj4T{ox5SRUzBH^$D%EFg}eH#PJ9{(A@-}3`qf6^f|(&*ZH`D8zY zBi%-#28Dq@%zxa(qGYOlS_meYnYZ+w(r2b?>Vk#c#!Qy3|FCq=a+|q;R}Oj+oJJE{ z-Y@VWK;+|!vqeqf^I9vPHZ` z@t@WCuqFwX9lS7OC08S^vY=^XdGJY>-NE+h{me;5uX0Z{Yz5azDyzu)81Ipw(gD)ektkktchf#gk&74?5WBjCg)133>N^iMjtYHwJ z<#m8#yWy^8`}Oww-mkZ-->d#1^`~&yp9gjzbpP*E{U3Gk62@yv!Mu>sa&XBqkjXrg zv$6TK@1nV6pN(hsT#v@_tegB`FM~Xjc|0gKkDH?J;8t9mW>tISR0mM(c&fm$eH@?` z40*_;Zg4E$pUjM$%W2arDY?ntw@UUk(0je9v+*trn%}EB&Pm@bN#rqBI+}cacX48A zK1mGcT)8}R3-E>Ah#P?9*lZOr+$v~fk2w$2lRh_iyyH|8Ld z8KTM;`fs*Y*qQasxcL1^6tsSN8Z7Wj!NUX^=kv~MxyNu=3;5UJwny&r_`Y`i9#Ow> zE{K4dm84RB#EJZv@sP=;>H`=5Zyc%L6L_8_viV$a&SG5fj?`K&x;)R$%&wM|szn(B8|C0~B-n|sDtCuv}Ks&4Gj@I!AUn^hj*p3PM5z@s+d zE>??8s6zDoV=K4p4br=cwb+<^LNJ!$WLqp>>I)S$S)9hn#96Q7GLZuH$a*1=LFGnO z68636xWh_zjLGMg)nscMe-iS;m3`Y5E85S$UAYn8b1@5*WE%U>)_540 z7JB5bkRLC;hKX}Ly>wH&y*MDYEco;kLZDR|D)tC2iw(B=)d&K!PX*$$x)ywd1t$E{ zPq!q3QlXo(UQWf$oT&B^`X=Mivv!cCb~UHdWntT91uTao!IPQi4f)yUlTgbhc|}wg z`Hqk2V&GGor-X66G^HSAzAVsZyX2vz_r;=N#ly+?eqtwH0qh!G{qH>Gj%b~?D5@%F}?n)TEnMJ{_I3!rguVH!3 zK9zS(be$YE{u<}ZRs^7KAUm0i?v+}kLkK(Q9zDhjQtu|s)$_(F2H^!lgeH`53eks% zx${ZMET+mZxhTQx3rVW1%Yg53u~_=L%a=p_1#N8wb3>x<^2$ zRa()Fe*YX!XL;mYLutW{>{`{J&MqFFWsOY=^-sM}o%Z#ECMED)?v*b4YR379Z$x6A zandI&J$*zx;K%h_{@IjZ==6O+m{4t+0qpQR$R!+HKuawQ~f%g@J-vR9qRZ(u*w#COAb=5|R`QFT!3 zd<#HwvpD*)jR=>LfDk{(i+K@exm8lRUVWXb8Vh(Q#m}R9!tndzGqYy6?9V&Q5CJ8R zi~1dW8hqD`*-iq+V{H=1E&VOH`Zq;9uulgCi2rUsOz=g&xqd0TxH!PA$n8_Y=luN7 z4hgTo3O9SjbF$N5Hg+eG+ zsBa|v8HtFJS|E{=ta3!sRemypXUBD#P#twOe{Tryeuf$<~4J8xKwras$FkVGa6^+&))#_ilLZ}5zM}8B=#O>2QmXwm{OHEPgw47yxDbBkcyR75s>32_o@ExyQ+_Q}2Y!OS z!9-VQwV6|e3Sb=Hyh^)v1T9)zX$nC^<+> z(w;+FkKj=fVuGpy@$Jrw5rIWlx(x$eJwBf>$&bi48;CM}Vnw#a(&(OxttK4aK8X*1 z_%&(r7K)F_78WCm6Tg0cLAyomnjHAcOtn!WO42L0A>z?sx^Rk&e)pK{n0VQ{62W7y zB!B&8t5e*lbEB!5S^-ZzZG}6MtuT|Ix~=55#`|~zNWIj+OQ#}POJZcXit9$n4NsMK zrC&<^Ffk)R`7>tg3DAT$&H*`^<>`M7fB(g$6l7CR=C|HLde;#&6tRO_nqMX#R%Iwb ze)I;!^*aEQn(A=8{!fJlgc-gN#EQgsqhM2k#)5V41OerS>w6Xpux`&wDVctLXg}g^ z1nN+7xbVYc+C=STr&FAa46_XC*CHhkn(SDA_6F_tkojzmZWX;i7)VHRR*v-FtX zLWLaXHinWzv{~YJwns-?bK79qU-S9wd;BMz4BxDeJk{|VOO`uyHs;39+e3iRaRGtZ zfJ)GrO8U^~Z?;4A)~=(#WyLrC2-c`uTN4)$cWd$}f360_UunFO%WFDI;&$>9`CO;6&F9R8#n&Ge9Opi91%aS`l%3z<|Zc4XFwgRs~Ev*%+CU99UwS3 zC)Qp6&G=Ex_XHbp(1yEz>ne_M=X$fzUQYF=*$bQOwqCQHRf&P(x5u3?t=xg%I(i@2 zSQ^t@k8W`FCwU;MnPoYKkR+wiaXLvZn`d&?XQUZp;#6Fa1u^8+;d{f46T zQ|jV53vuc9)9bwrArWUk5RKgE3^ zZbIEkK546K-Kw2+p!&6ch-Qo^ri6w=nFma7)U$6cC-QdXANUxg(abBjCv!6aTn2xJS3V9S-?~4Wp)HT0)3IZ3@bqPIK8woD9-HO%>r79Ir2wWXm70&j97 zg`z)x?$S3bj}E#Ra)Z;zN99 z$bk^y(kff=D-R1|RkcY6?7HBJV(+6L-TwT`^#Dg9yJ`Mo-f@6$@)lPh5JBXU|52Qv=LpZKe-^A&5-B>`svtow(Y=p*T z!_xw%PYcLGB-Mb9+j z3EQIM6)|#2Pv}T_E^qg98PCgYOz)?GdQWcS_&#V8(tWc2T0{NZIW6Z>Gy zqD`nD9*T5zxQWXf#l5Yp4g>~?MJD=qmMU|v%>-I1tGoEweHtVNQZHCO^mon=7!{36 zeE6{J;f*720b5##6WZ=;xkcSc#S8$GS5BM*x>7zD6u13kwG;6emLaZ4V;l?6uw&xo zC-{$QQiFx3Q7*Z(l!eli`0Kf)Z?6}K-8t%<9e5H9TyoNgsJ35H)r4-c+_Ta4WaC?^ zyOc4bQumsni+oF4BGqASa`NvXz&sV;N)NJM|0HVj6h44j2=p&QS9r{tSKkjDy$+1C z9+*j&tV%5W96w*t)$;WCt?5#~s-CmjDJLaPaV0HfsRZyCPs}BeQOX53A^Z^oK^&u& z5A{dil&f-NRGv~QmWhqJn`l?P5)H zi77`;qeZJh2<2Ij0+&H8jC&1hF8(g-81*AI@IGu);_iozD=Hf&l3WZ8E!OH(AWAnX-O?qXA~AFg9V#6&lyoTwNOwzjH$x-R-8l?M z4H84wP@aeP?DxIC_k7>pXPY)|S6OGA?A zEWKw|05v;(jJ4tLRDP~b7d6bRWyMXTz5tZ1Micrq(^Q936nOOw0nYDFcePGTXF7JN zA{+OJST%!&fI%u2unM^CX;nK*Q3BEj4BE((4pIlHi~ub7^P7CK0EEf^JTvp}TUq?S z`5nbdNTthBH)pgnL^SV9!S{9d{xu~)OzU*ba|znw^T@Mu=0FuDjEu@8oReGo8Ng>I zT=9t;c|=7zl5|*HHd!Dyt2vV{$*wi7dS^Y?1Fub52d71RcD$2RU$Hdsq}z4c8&bDm zqml~z9PiFXH`UNcdDRS7EWWeq?kl+KW;sgUJy8KV1k?nQ8cp*@95@+RU zgK7_(yHK+kOKK`LV-yHVy?@MRCrSQk9IOGB-y(ecwv6|nGLw}DL&h~Z@q}7&mJ=PG z2oo$mu`-^dt0cdbgoR0;5{UgZy|Ds2J?h>Y4z)E7qxIBxa3Rf@+Q2f{MK7-;&YR-y zK*mq%V62pxFOpb^K0a;__!%6i4$=w^E1krZj89JWcX2``8St!jPXa4-r;XL*UhDfK z$VytVB~)Ov1Ct#lK|ao|aZF=U{1JHXQg!A_u2xnDd(lOaxz%g#vq5cGa6J5-QQ4Q8 z+;1~<@Sb#PFqlGE%JPfCvZ*cSc16FgUlj=P%xiH9bwm9O+>0}|~p zyq)>n4~%ik#@-|+2Z-&>p`q2bvu{4*^D2M+ni*7Bhyhl zdTv3s8YRWCvu!!F-BATtihTglO{C_!tBgVa0D!;85N60csVR?)v)BX86%ATBOk4a_NZhep@HW)R;2KST^uRZM?s!W3 zdNPg$*~`zlhw{?`k-Y#o8H)xW;lCp%t$lJsU;|9b$G0uo-3N>x0MA#B^9_Le#WX{S zBCqTgo3UW@7Yz`^6jcg1w9`9#fS)M!{`!KbWJ+FM&pmFACiPeu*>ulWrREgJaVzCE z?&6`M*{Wxn{QaubWM8RS%DzRE;~FlptCE0?hU^VY;iph7q-ekOF+Auv%oFuqf&JKwY)fA zBTK<~u=A9cxt)m+rU{%@HR`Rs`7;FG7AGPPq~}km&ukb1VjaA zWI}>S@@2*Fo&D?)rH94kgE)oMLLVX@(na=!V3*T9{zD0S^Nj!hps7?B4{5KhYG^1= z7iQ0t_Nq$9*TN4uc4WDmokz8V!}+H+De3i|!fY>tht-s@IC^IiSX?#ARn^s1C#K(G z^2St`vH)5i|jH2Cym z^7S1Gg3|JGnkxKpwJ~+$ry-m{anaq9fJjM`6FBCZobc<#&ZC7{PnwEKiVIKhWLsc% zYBZIEL~urapXupccSc6|QY{jbM7BgsnlGWKTKR1)Rv=s7=LAgjR;m*o6z#N?=o(~3 zY~J@ZG9yYmH)4$GS*ZO%&y30^?g8-YcY-Io@FBoXJ&6si6kD=lg?_T?96QAX`59uF zwCt+o7e=a9KQl3oP4*Qlym-^u%<8z4S`Fyl+n`u3hjipS@$}bBa}bqFdlRwynh-J= z_teOhpV(gR<8GCg%0(qquaryaR0$hnRu_ceu}>RMDWch}*HgWT*mA~gKLqNDR(umS z*NuHDf<=?N&Y9dUJ-hALiBX|HhzhkvIym`ZUj_ zthz0hyRDG%$joiTMxio!-F!!Mtx_ON$$F$sSF$#%V1A5E*j(QJ1<>9tBr86Xo)Wq) z*Vt-3laoSsoy0j9kH}T?q=X;XlvbojhAz0ui}KdZmmX(jqE(Zpsmk}!!k_t!S=5-R z$a$^tZ9f7xqG4#>r!?8-T|p&bH81$+%vz7ATB|-cze^R|DRIYE+`y0PGW)+o;P8{>3$_39=+h65<@&r1AP;1P}YiN_+7 zm*l0|ZlSgFX_d8X%J_(T6_#%ruFqmC1^_vqP++v;~}LzkWqM9K9o;b zae_T_is(3Gxay~vF)Rwd{4hKDu{bVl?$xsUl2^BQQ2OVNV`}?#ZfJLMeR6bt2-0{)1Z4?M!ob|=Ky08Ug))64ee#2B`cU&Hu8dQ5fHzeSdC-D6wfT+DHZR^dx z7 zvk?{rv6bj_!>ro>7s012ZO8`cjqrpmpl#OTFEc7!IHu7d?=1}@#Ob)Xa@AITW3(xh zsPM*+Q6kTVy0M&CZJiLz+Qb2Og4Irr16Sh6ld|22fKUPOgY3g=pU2Yrvy7l1TOs*% zJC7*T=Hjk+uTpGtEUn3fLnExjc+fDiuouZ{R$BZ6MQ$B4bVTZ6=JJj>%DJG(!qOP1 zG5T-r*i8ok6R|R{wGcIX&ruyU*xz(W##VB7X7+-|!pM?a8(6Adb^E=4+t}HMI7$yN zJ7)Ey!-jtgY)1b)^(a$f&<~fDc}^FJxlrTbX36 z;)Y{l>LSiU)55l~3(Wdf_jHxjr^JblaL|phD(fzc~VBh4xw9C zDF3Cp!9K3SPRdgqRjZ(<+BwYR`C-i8c%%uyQ`|+**bV&fjHo~TbDIUQ|3nb1mu>)V zzI(}Q{(EO|X>G$rccYbcYcsd7WQtI|A@$t>)BXW4YNPzjOq+l!DW^2hBrBWwX+fdP z^2m90n&VD&0h%i4>^OXjCbAxP^m4|_b7!Gud+`(E^?~7%7Z2>(#@R!c6{)c!4>R3X ziuNYuq4L(&^(|RIhn_Y&r7~hg%$@aYIOuu`@TT5>AA~^wFv7>@NaOr1M8HdT`zo_; zv4Ocm>FP>Ox_aE=sP|0zPHP^~JPP!tPjpc^X7s@wAb}f}Jd zsLZ^`vFikAFy{H;w;a83!r=#N(OExGP|GH0?he|b)a6hX9G%?jv`o5Qh?>vwQA z9+ljEQ_n;p_gLnxkAKPQ^(pc2=Cukh*^k2p&H=j9o;#!43iZ+{8KCupj}4LHmo37<=tvKn!H>?ya@sY{ zP}*m5Ep9yZCqLahFGlsdKjErWyVIDOFz05M0SlXoZwt@4tbfr|Zi=)DQz9G%YDQT= z#Ik<)0Ofhy(1?kKdcP3d;5R&^J1cliDB|P#DeL=X(MF#Q6~`2selnK3Tkeq?<>W2D zs)+HfT?8;+wG+RBl|lT#y_>3BeA@ESBmNqa(%$5C&zorwp)#FD!w*%26dg*SGgQZwRBBFQ zX|IQ@^1YZfCFozePgilPD~`5UhB<~M>VXvac<-`B191$vkat_|dDvVVh*Et0WfPjr z#eaSGft0TE&OmYGnh0h!EM}j@#ChF#C(fUIu($po>b6|DteaK|7MrqK=34;jQicPe z@P-i>vA3)1SzU?%EgXykl_E>^IDBh)Mr9e>ZOBy4lww(q@W!^UEXE_jS1QV|h zYd)xD(w<>-_*WMa)3QAP*+zAEI6_U zT&;Q=e!%G`d~|(+f^tFHV0GS7a((RkA%Y=1SQBq)K7{#*{z;<#jb;UG_aG;R zuP=qrk_d!Ab=IP1$pqrzoTuM(qm+(p@fV>%c=d^sA)jA%ez$VvwDCq^;ZdG7 z(jnRAUP3>rp&K9Ij8c_IvT&O-_R2u`-&ISko=Oyl~OFWAwJ1OhG zF@mcOX?|mPT`K{XMECyxO8#VqCU5Tos)Hxa!!k!E{C%P}p=iDtPd~Y8pxXf%F>06< zF|GG*;XCsjHdInmfkcNLEJ)EwK&=S2GWV-MGFdz83WS!WKwyX%ITq$F=Y zul5;p#AvjDaqX^!pK72ULnTzTQa7q zEL>_1f3_6<;HUDHkgb=s+>1Q5WrohfU02ihWW8T32BOJe>mAo8*`rdsF*%&tksCWd z^0j76&Kt|)d*#%yWQVaRYjByvWL>Q+3Y(`J)V*1Dk(&PKtI3Nph!ewDK0xXuwNh3| zl!(3au$aGpL=jxlNJBn0GFbQGBUrT;9K8iu6Q!&XOq#HW6#Y2N7Jfg@&~c~a=JEY^ zsujm1yie`|V%cawgk5=Rx;T@JY5bn`lwo&4q=*^x1>Wd@8T`4>>Y(1E#G`ynMP>ZW zmnxA*)>yq5K-?)NUfwp0UfjzRg~x6geCczd>Ev8(g;jwQ6vxrHM0`%8yEJKK!9|wx zE#Egb<-a_h-d+eRiemI>rGKeYxH3ugrvF(oi4t%}dw>C`Ytf_b&ali`&nLhPCjYLc zqqO1jN(U-5qt?8WkBCiftDv+bKQgCuz>K?wZIWmfyVtCwv@jBxs!i`?1Pu1||5;8x z+-<&?O=h(=VruX%*}5R85D3$ET37%SFj3oxoR>$3N*t(d$~rp+5y*%4U+c9da|@H@ znN8ilF3t~`B6ket*h46d+-vXK*vnHhv20KqlM*AJ7Z1{RA~(oKYTRP3^47#a zNXWs-`n-Wdu-WQW!~FcbTEhVf>=P_^zW~HxLWf=P0N*mUkl4?4Y6b#K+;GgbpD^qM zd)c_L*_R>_F=uY_So}uJY-1Bj^bF7aG*ZLD5@er#!Jx_v)V{J_=xEA<9p0Vncb5#{ zv&nKmGA#q+-t|xDSlPbB(Hp%Y0$V;Yzh$C4fJrc-mLkBRi$LeO&%27pCtI!snwHdL z$sbm8VGv359h*62IKRZ?0;4cNV+BhLeF0 zZYSY3Hs!_@4;&XsD@BJn)6avvfvf~I3wO;)2edSnI!S>{8>wzV6j!lthp~C9R5o2H zP$u>|B2`p(?El#L690b`w9@5PX}X81&_Yv_DcW;0eVbSHVpcX#YfmTzy^8O=yMqHt zzJ}k%2C7h%npxvSAQW7hLoNJO#+#ynBCDM4Vy6>!NW5?XU85j#?>;F4GpoK+yj^lQJ|*k#^C>q&3@PT;wxX3J!RfRnULPUm@ z2&b)!&>ww6D1*(>AF}lmA)3l}(>1buv3=jLD!)>L?Yb+jIX6H~NQ&s!LVSeAg|keR z`zVx&aO!bbvVDM$5Hu$oLHn|}y@CN(-CRY;i$ z07bVOmg&ENzH8JG4L)d37bE-_wui<&(5)y>F`0yO#P=E|^vfET_OBvAk9e#hdTh7l zbAKV~d$YJkjqGP1H7>w|blB{e`s-l{oinVY3> zz^bZ+F8)9%&!s*(y23?jEhS9uh66NELD-TwkGmqf$^Dcu z0JJ&2`)_`34|=Jqc_MW?6i0q%iC|ojiy2p$@M_hu zN>`^jQ^9hiX#wWI8(dDZi{yIufV&8o_4VBLXnzY7KOyPBRK*4+{YnR^&Zt*>OAN=d z_+e1p(>tzKa|%UsTPfoo7e!|l*8<|5dWcObV44E%#X0%45i%t0pFtU^7G$zgN&y;t zDoP(9mo1aCa2qHTcQ$rWdq9jKDww^A$5usk&6)ZQ9UyS)(@Q6Q~8LWWl8mu=B*6logQ$#5Nn($6V(PK_N=!MhOfcw;8 zwe@3&uKr+qlZI_owZ?ul9G^F2s7;b(z_Kg%6FHVyRg3S{zr=QbrR?9+a0vhnb&`r1 zt`xa-dtJUct2odsq{(pq{=wmDB_aOFj5|-`!C5hsr_9#VH6?e(J(+7-kbM?&;x`5n z!o_V)Z-{K8U@h0*OeGIMdk;%CDE)urY!(x*T&phbCF&8TB(gvhQ}ve)@X9_6ICZIE z(h16bbLuM|ywoJR3a;C*dahMCNIL~?))rGWG4ck)zj$38dqx#|{c>^=biC>nAjvm2 zl2ZF^WBT5_s|uu;UD6bIY<@|Z?d$a`)b4^3So1o5qo_vHb0y9K=^yyvp`p;DQZ&#i2rsQ z=QyugDX+XQ(-7#E4%_I4zGw|LH*Rt)+s}2Z^#snOIh!nVs2VlpujbLFFA+pQ>t`gY zTJ?>u+Uvmn<*KtLF9)pXZe)4Ao3M2lD`#LyZtsT!m-C)DH`zijQfR)R5^Rm$+4Z`F4b)Ht7(q*fIx&VA#~i5Y^hraGMj&O zF#qx8{qt-5?JWN>6E~#(Kfoo*xr0yrbpk{4pwKUMMdkH!S7AwK%wt&s4T1qL(*G zD$nTMy$WP|4OO_wT&+>vJR({5V{mt!1KmN4axTbN$dx)Nv8i`c5Xt`2;qFC~jjwf0 zrEX&)J@LutnZ{nghaXHvcYcMk<`Cz8!a2%1fs6|L?@!4H~0* zT|aGl5^sIPY2kSCeZEq2^27U1pm$hRIpe`Iv6e5Pv0T8y$}&Y}nSsmxQkD1XL#BH` z^{98jxWs6GlBVeal%I!a6Vy=Mg8TGxx4bu-&05*MG*^q4kcM}OE^UCg0rK;Z}A!5mE>@znrMI$r=l3oo~7-G{bldhZSu z-cT@I)BsBTC-s4EOqWrW%Rm?fmxNq&$J#H;{X}`l$0rk`#$1y}2dWw)Q);p$M3U_K zyd{)hzZYdamJDx@qjZp_<4!kEk$Go-|M{0E$op*@^%+6S%@~!iJkN*;dMusr zbR=9caPdc4$i?`w#^^S6Vw$@$bSI+IiNlC*zlwx&9|W_}bBtR7_p3YRu9TJ1SVVNA z6uQ;asGrL`Ebne8{_?mYT`fk)?J$nr<|M9(0P@gw(DH#1ot?N{U~k*~j$av~O)@_| zDLuCb!m82{t9NI$ilZT*q0zZy$7&!NT} zZ8SpFd>JPuX%mh#*;6uFJDvWa2p^D4yEgW|?*!q`nOp5KWIvc*IYIap?9YT;-;UNp zUw(We?EJN7hd6M~S`#1$9$k9vUT2`?#@#Vn-DusHF7OH)d2Gg@qB#vOssi5?W*4Yd zjcTeTt1nk21XV}HwfJWk6=oFs%P_o+;#UERx$b`}=Ki@z`7b5^3arpU-u!)rVJW^o zXS#dsC5uSTLnaitlzu4CV6#-e8k*U(hP-83uNISmTCyZC^FQkOF+LOv0f{QGo9K~i zuV&@OS^;y?%Hr|P2eCyP)C2vO>*%G~Czq|)CZ3TX&vrPv!9m>cBLi`vkcTIDKg)7T zO>K00ukHOv~=oA zncH~*1{hHoWWQh@pJr3wv%V0=T|H>SBiPneJK*29p<7{B11#Xpc4MP_p7I{9?RzsR~!|e5o$wd(!)T1Djt9J19?2>svC1!cao~zFn!T=&M&SP5v2N%emsZT zR$J$1%?C0SJ>F3i4Y#{dFQXgs+F^!%p}t|b{b~}{6MRv>E?lFxgIA;%36ChQEle^q zlD17h5`}D2QO|yV&yN(-*~ouE`pt_x$U4VULzAAJgFA{v*p>CbacodKqSz(lu6B-7 zlr()plxMHI2EwKamFzTbdB9gw{Q#egDm$Xsl1Q#+wWE0vU-`Qvn)s;Us>#X4~GTobsMRuMs3$lN$&&=?nSuGdeP>gXvO}pXu~-t z89hXOQYf^)j@6#`Y$2)7m4&RZh(E!;7jKr>nP| z{AfNvFGJZ4H0_u9B|j{k5^2abBsIw%^TiJ1vWrY~KE@%8@V07p*sW=TRUJ4@R-wYJ zs!+&p$2-`z2&q)(zRt* z;DJ@`w!4mg%c2DZoyNF9UMRF8OFCN`2m7Fh*7d=iPwHe!@$TU~pU-ABCq)(EjkX@~ zbGqH4uott4Nd*{lZL`zlkN4bTp>5IfPO{9l5#IR8!z#BEgTDJP=_9fI<5SOfU>Dxi z+y{nq$*BHsY^AwA%uwQ6)>ESrv@XLLzHeJ-w;Zz~f}T7CNitPjG+V==Te}La;tpr< zlQ7Uc+t0eBhZ=QOF%3!P0pnf9A%XCArAGq7x19Frz#(zNz9_vGJX??aVz|CS+&m(> zstO?)-v6^gWb2uJFv30F{`h(}ddJ+~?M|1qLPafYkHEs95=Eeeg>j+Fz+n2K^|}?R z(ebp@Gb<9=h(xt)S%Kb%9Y}{EmzTTdHx0==L`2+e*E>I|k_*n6s;(<3K)(S}>165h zlZ(YV;**#0^*Yco$(OZU*|oJ()2Fm@XE-J;_4QogSak0*wNcN3$}<8owm^xiHS4b$4B0xJm|E$^=k6g=;)6kb^i3!S#Q=xO-{*? z#tWB^NKC6^0dLcj)RFHKV>S&TU02_sxNCt0rEs+T)Pvf!N7M>62}PMM%X=DpdM{qu z4+IU26qs>dz=vSv?iK@p)byE-_JKIhJY47dhTFJ-r09h89*E6QF_OYn`@RBqA{hH+ zP_g{Gl|)b9Rd!%b!%J;#(QaqA`TH8HZc+W@wgv?mYI{w+E{NWf> z*8oOjDg&Aoe(?p0IG)sJlxP*U`LHWr+h0}~;Hc3(C$eN_&(A7N?u=ODjSt`NgorDGC4v^f7l)O1yL)#$hcAhvZH;RK z3|DB|)~2leX(pO$7hv4Ll;DGR<>B=}Zo}{n<2j(il4-#s_a?j$Uut!~ zr0Fbczcd6I`8`LQ`&ZrM)#uGU;#(R0XMexj`&sWN4pfWdDTgzYH2orL2E%Pfu+EmaGos7<22AJeq&csjo8B=ZnMLkS zoK}}r7fGIrDPAzZajI`A33#WR>8 zYwPJc_@*p3`o{w2FADFbl#_HuGQL7yOCM=015AVm^1Q!_3w#!OG2!{yr)Sz|eJ&-Z zvamJ8dOl2&DJR5ukHFaI!rG6mpG{3=m@&QX4W`Fz#oz!1duMFU3Vesp@{MD7M>w>Me7}#OJ2b=&C%)4^*%7qkpnx z?-v+0$gs{a`JUkrS^>@FS}u&}qkK2wBZ)_T+d@ZuteL_Zf0tmp(YUG2GGf=1Xg`va zJMbh{3;WJZ#x`ifRXj{3zqQlKL8qQm|Zru#))?uu633>2&PsB2+W8M&K!$(Hy*Aont}OOb{38oz&xT(NxC3D<}GjqcQ9u(ut6t7cY#eT)I8&AB7n|B^|sSR_0&A(HWjnb8C{xK1^&)5nl zb}Wz8eElX}-d|tw!MV$Y)<~(+L0Zd&M%%X2X-~W^xZ~RurE{FS$@0ctNiAZsWYOMl zD1B+>$1)YmD-!&P5*g#`^RuNHwBq*m6$(^!E>T&L5-(X>;IsgkQY{O~pUSB%l{5R5 zb)pdYaA)?gffW`jzSRs_%WbuOO;+r{`(r<|5}UJ;@I^bJ?t~JwcigGF!h#5}etiBC z#4xA9NyX= z^aUM@fzf`uj~vgV$cT91^-&LVv|>mj$P1#!TgfkYOko`a4Xpe=;h`7qbxv`v`(!V3 zte`AZivb-=wWWq6Q~;<@Qcm7-uOv@5_Gg{!CR#- z$*i5G>ibm7SVfyzQ|8=nE{#}(!bR?Y1@yog5Xm{2fuT8w?7Mi`tCE**&-uVn3zRyjY}0@@iI^g{)AH}8sox1GkCif|{0 ziT651W4E5;N9t7@w^E2t zVgrzQe^l~yX3T@so*%S)v#YAZq&|xF70jL zdjh&l0$>tNi*PFc{#nq`0|4nf0#d(TTGKs2Pu#_w1*^H!WGnDkDxFQ;K-3#E@*_Xx zY*5BG-#z~g+K`R#Xe!45gs134qi@;Xl}$bDWC@|`UIT2}vN;Nvx^Q>hv4CkH;YZ0F z3eAR}=IfJK8qV|W94j@)zgNhHzNC*D09gQ7u!*w3sM(%`7OD$wWmX{;DzZeNRum^ni_kwS*BamG4tWp(q%6;ldHb<`o&VdE65;UFsr~7z2 zB&SAa>!+9&-cEqKdi)#vdg+QYVEOcnoL3DN?yRhIzAO!3-mT~(k~HZH_@)P5S>t&crs0Wr zlZR5#z6Z_td5YVyvuaASH!zNZw_bX%liGBqaM12~X`f!u>)bMYhK5sw7ZfnrS$*qC zIsQ898Z?h3#dCjiBe`!><42Y1XiNlHT`JPt(+v+mlZKZ8@wr@A`Uh(C_1@n|hNxDi z+%JAIDgrYuuJ_D61{MTM;twSR#MG*4#d~){9d)%-P?s%xgMgs0s-lkh1c@`Y?z95c z7{~8c%J7_SSi~!}d{(%H2m~v^icVsPL0$7=tDt7MLgv^}x zfit(Ms}_ayAoNP_A=ok9dAu3EAi%W%^GfBoOBr1!Tc^o zf?wIualg2$PWe(R+_sD;KcC!JT5p4fA94}bHZWgp+EDZPlC|-%9WQ?QUGr(o?k}g< z`?A1td9I@q{!Pih5tR9fIG%TPd>V;jGqQS@4?a2yUd9PLQ^1AXedAM0l3ScnnpFT| z-u$(>v1+~+BxxK;T6Fut4UCzLuRhPK6JHYbY;9;!zSNt87uB``)J1vvMZ2Bk(fz<>t4ox1Z2 zbqc%SEW99jpit-JbOh(~b`BaavUFsoRqa-j)R$JFXaj>(D8cHETp*nNZZ;?|^*NIF zUrxMYUBC7S+~5pKQD_tyUKKZic;x~5qqkPhkMOO&HKsmftbQdAy>jbNW z`)0aC%T(mnld^E+KDBgu%CxNXD9njkZxNkmr=J&hVwHR~(6#g2hd)l?NrAH`(}S^~ zhdj2JfxqtU7>13VcAd_(ZrpPPPaZkV=J?XQev}NoP4AkCjODr*nHeIvb{MrT8e0;;!|z{)EMHn)6es@=PkA+ zf-GSrjC94Hbd2f4+c2gq$uPl{&^Ot3nV<5%rUTP=w{{HQ%8b&6-tGeamX7fb<1Pl~ zr%ilkSE|*>ewmIaPyyX)lp=^Ra4W6R(cs?~Dcu~xpTXd-*2V8}cc$GzkD8amb-eru#i=VXydjo5gN2H-w zx*VuQ!%jD8i=A(A4+ih<_DOv0oWu?SwQSR?Ke`4)8wIbC7v$n~g+aC6HF<|qZRDL; zdJBXHlM?tZgDJsy&S0GHm{w_JKs3y`sXh(x&g8MM$GlmCEI-o<^$VPND#N(3RK|F zEAC%`n)rvtLpNK*oJ@g?s8;X9Xas(5aVN?;6j-#^-5c47EDC(F8a&ElZv6DI^CMt> zv_soKYMK(}m6rZ1u_lSPsGC{k>f0wP5b1=dX2AUon4-lj`V0d9qU78slH?sM6Nwyh ziK>+3lDzJF_b|H@^hnnBr-x_gd8FGv9^EFpBQCLGP!&Z~R!)ymC1DLA-x1NoK6q49 z1>CU*R+&;Aih8Xkr*}><|X9xh@kSk$a^KO@j=~-abI?JSuDM{#d*?M-f0wS{Bt2g+Ox1CnZo={ z!tAfOfSKb6`oAhv7FJw;pczaChGM?+)HaNKfN}PuCFtkw8M$#T!DPp4*LDoL23Eg} zE*ApE{2pX?XW;DXfg!V&zXHv(V#Z!;?7uVu)@so2U!cL4{^;g8xHNM5uz3iw(}{qa z(ZQ2frVn;!Cn5U#W-D~yd;MX>i!S@33is?!Iz@%li}Q=48mTMqO2;)kxuc#6%!xyk zl(6U?kBznC^6~LONj8}$NDjk-AL^7o*jCNl%g3~ ztsV5+YPCVm&d)crP^gtV)lq%h6(#0xm?8Gm6B>fQ1QD&2!2Tp>YRp=ZhkQv3T368$ zGQgB#@j+L_Hf~ORrmIesdoBZ$GV)aPO(h$TMxr07T*s|3W#$%ll`01%Q54`7A~3!< zhx(P<_d`Kk8X{O)REC2$`E5l)uBbgnqgnw|% z29lQ3t;_!L;UM|}vBd{JLO@jHO(9{ua-uOlcOig(Y`b;NCr_v4{+Gvs5{9o?6@8tAn5N0!QX`9vkW{3G^%+z6Ws`|99 zmj~11?_sG!C57R@4y|5Q^Vqm*$f8ZejIGiO#bEsKXec(os#9+Tsxf@<`mlB4 zQM8r_47~ze1ppHq@+enxegWuMo2&g*$$lAy0^!jGMP0?w2ave`=quIAPUdHc4>~6R zIt*|*#ROK;b}b^g#(4GN`@>ExvPp3nwl}i}K1}6T$>SFbbT-Sn1XWJa3hbr}!y|)) z!4wO!vcE%aTp|Kp=c=Fx8Ahqtc@JX-Ew0ro&siFFr2X{|J8P@YaKk~v)%8Py#f!Y(B(emk0qiew0VwB`s}P|W*lYpk-N++uhl?|i#I-8 zKEMPx%^J`C?oWap#eP7eiGBj8z^ipU0$erLg?54=kzBa`9*<9*`L;xuB=s31{j!TTzKQ zGk$HCB&?i(mP}Gn=fK@{lDl&XH-lKYD(_Vh-LmmoJ*e#-{MOntHs5PE=pO8(tD6xg zlbOM={FC#9cuT(Ls8qHH>qDhj8%jy=5RcwLye>k!6VjWkdYv;l5PZi$Ugn{drJ;a; zg3i~>JD)^?Caos%-dbZr7Y9ybJ;jvlPKc!`Kz{A30vwVDM!r@-p0jbV-b{s}YyNS7>Mu9st9dd$`Z>pW_B8YD>=)7Us z9=K}Lj@j8l7(mkC&9J#GPxBtOb-OIiBk#PL_)OM;%Tm~X0le@A+E)ezw9 zl?;Hl=w_~&1ej|sZ}VOryoCM6SVT46ln#HJYyMjp``g=;==^+#1U|bqr~2U;0^--l zF`I1LsV#P!{fD_3sWwl(YiUj3n=ApbTltNfAjHOXb}@a5<4HYvgI zWab9g>h9}xCVoxt<0iW)u}9&25xMzA@W#dWYb+sI0@I=aAz4wa1cGte_%B9fv@-jd zG-F)jAO{q1s;K4!@sE#--rtXlY^%w%FbRA=ny~)tiSJf zHhPE*ip|{)jnwjwUYQ=0Ct}NNC^B+Royv<#CX#D#z$H!)z|Xd?0fAVIgB*kDK>%Xg zy{z+2cGkI^?cd=H*Ke$JFeLC!AW@Z|r*XLyMUjcMJC10qe2|DlAT%S3Wz8EoOSTAu z5?Gmhhn3{mY=m9t@(OR9V-bJWfPed6{)xK(35Ng6f0(rJenEq5+-F5Q0gK+lCg)wl zzVD{&(PnRQ23-k+K&}oR)>JtTS?o=a;sysh7j_!iJ9fNHWQ)wna>9wIKJ@zxT(Tk$ z@$ZYsdzZ^Rf##H%|pYJJo+Ktc01N_?x&yG!^LIdJ$VW+@mSNWf~5cvOnD zT1*vnzutW|&}0Cayc-*4<&EO$8R!PORCxc;rTVA`WFdO~+P$5`2Afh_*Ou=h_H3WG z0b21BZ@_!UQmNEb>2B0~E!0(&vgKFLr1Y{SIRWoPdR)9>Akp(=Jf~X7McQHnTFs_z z{yIi{dZ9h<*S7xaQJkn~keM?%j*6vmuXXlk2L0|?$Z5Q2b@+UkJ%Ziov)kx3syxkb z8mdxti@rlSpMlkUVv}GvgZ|8@G@FeMMV+%%5?t?GdpHNzqzOT!1jh-Ltk*wOpF&o} zCaKT{d4#=jD@@?3?kC+F{V_WB2CB+OHxI6`7htiU+8q$N9;}jnblNav(vVtw(ASl~ zu{}^xBJ$x)1#@3IW4hssi_b$Z$1ClJ*>@X{#t*IsZGO(ePqJUogXoPy!8%d}(>(sM zzcC0R?!DoxFnje^D*5-{{y&q=zy8D@F4Q{%x!X2j`lxbNx1{hE3xPb9lSfm98?smZ z5>?FZ25BNSl`gYx=u>}?j;}?_wrupNq=gt2*MESs{hf*3%9# zu8mr8_ysJFVH%e<3yWme_D8KM$FOtbjYpY-JKMGWzkqqSgoWWYlk@3Hr^h9W_12E2 z5;Tb&(3I|w5=*!G!7gBX4a~7q#mKI%2`YlC1Oj~pmXT$4sw&gjjf|~WSgiQ?rv?c^ z@Kq(`$cx{5KEuEa2Oyr(P0i4}xR=m+;pqSHHwH1FC%y*!k`@8vSMudXt^S{Tt?r68 zGnyN@jeD)Ru|BMH(C>V-P*6B?mU6}CC2nDMiiPdU#3d3;8xWO7uOO#Q>OvbMQ-o8= zD)hu(tRJRUFAZDhuk3ud)5b~~l|dGO^&y)w=#wRrOu_AD!d+>nV9R;awO{Ou?oXoe z2URHQewL~iDFYwCpi}>B;4>WP&BVXkms**Rm~eLxoxa#LgR+GiI5Vn4`z)9Rl)xvc z3qgr6>f!#P=aRZO&r4Z?SbA)5O$hg8d8>HMwfio6?{T9BKSsPHDew7^N^-W8Xi-2h z{gq|G@^xE27G?5a?fhbm=(4V8%gUV++`+~m(dHkwO8J*mBKq2wRdH_>`bunrMqqzS zAU9X2u=DyuYhTgI`r)Gvi05D(t1}JABYo2~o*igitSu@{iothUGUwI9j>lDmh) z^AQvvR(P)%b>;gfc(khhAm!f}wxYoLAL{h~!P{F$#nmrs!X$)1kO=Ms5AG0XB!uAZ z?k-KEP4FZH2<~pd-5VMw1PkukGz8a%;1DFU-fE6A$wd)qtjkP;e7P%W)FF&7o`tm!wuO6tMD z?gxivhLG$JHQv@C+3^x<0sxY73i~{=>cvSz($u(RO41~F?@lA1{N0v2=`77i+>$8v zBWnro`?jn{^+2cXIc%~bb_A!*O{Oa`_OHZ$>VLOF{=@J5k1sqDf9sdD!xc{Dn0oju zo~pUl$Fj1<(E&Br$p=eyU~$mb&+T2a-?aH*dzzFkSKL1?rD>?KoSFw+2fUiWAGFy( zZpfDO?c&}ZRQDuhZx9fI3&bzqWA1Z)wq<=1VLKw9vNR9X{Zv)IHYc-bels$l&02m} zWk?sV8FDu4s*PO@yoPd$D~#K(0j#%JgEk;dqNlq@f6$UMHl}BxDZ{F-BKCwrm}@c12;p5ZSu7IaZSUOdZ<|5OZe4{*SYuzPDGpWAETtwyDSRYIm!w zEbAzb+~@tGeWC9|kA8A|C-ESJ<`@x-z-V;UEDDE5^kGRU^TES*G03Ai%`Qg>nQs^+ zYss4a7i`SocueVpf}2y1%hCPet&0@n8S{Iw@%5rYgmFsCMn$(Xb?;J~PA>(pA1Ggp zby~JIw@Cl(+$=w@)*wkgRZwu~UE3v}_a&E4$5JDwuAP6SoI+Qiivi0~G4A75M~epH zkDdV)!TO8oTF>|Dy_!3w4#cMqD4Z9DDOaibTPKIfx4{ih1Ugon)M8V-92S+2!2+M2 z?~~6NPM0zfID?IA>vtG?!D8*75w8bMh_3aIuPCjFnWCMFG;;S&^vUc?%s;WPmG2es zDzjj0xI-Ck5}{EEHuD@NLzat`6$gvDi3L0ba#nE>^0ZoLBv8hzFXfc+K3}}DZv3`D zO-Gk^Yg-rRw9$<5-X^*)-sRFq@+AXkmWYswl^YEh(OW2%7W+4%{NL(xfq&+fjy5rW z*!^B7X>S>G)P|toh-OH1`xK&;AYk=3L7W`CslH6E>Ay}+bkB{{Hj$cBl{e1+fTfu(krezZH-44m-U$C$yrw86b2q0PxXX# zJuGy11>EyhK+V$siwNOAL^uyB=$P8Mm!Id>&YsE6{$1gsm~Fdjf`t&Uu!d9wueb5k zgTQ^gqR%Qf8=W5?BmPMu`}8T@5JAD03cxz%G+Ax|-QQH%lc-^9Uy|!LNAlu|w=zz_ zHi6!OY@KnS!A5)N414chUG=e0(<$GGaYG$G2-F=mpkNXI*2FS7D?iMCuBE2>lj*4L z8uKXSovCWz^Q9c}dt-2E23cnZ)opyAkbzeSa!jMI(p2_C&({5DLX90A!vN)cN_v5& zeR5H9irQc4cl}>A?SGl{?cg7c#T%m^+nUW?#Qa!Z+aFDuC*2Gb+&(a#3P)%W5#)ss zlEQvyNo!{eDVJcC?5t;(+0beTGCTwDgW9s~b-!Qx^=WM7KCtm5>(>!zK10J{FcVnN z36xJFWxPu6Sy101f2pRzDrW(6{z1EOspRC3g0uJ0&Hhs|ES_1tB6n1_}o6XUTmW9Nufweagm)Wu^O21~4Gh zcXKUq|7Uqi`G~5QX>zeO$i4UD*kPKBUiwmjue+mKm8$F3MnQ0)k`3|4!jC{#yi+dy z+dUj=xeN8q!^&ExjG~ha>zRGTn-eUKgr01Ryu8=(`I>MHBC?(R6hV(Iyc@gu6)3Dm zvHbIwC1Z(D2o@A=fd2!J+*HK#r=@sJT?J?oU&YhSqVXiyt52 z4PW<_Wt68+>Tj0qzf-65aeX^nPUl++Mo|wVBshG{J$;*z3r{dEP&~g@J5rOr*24ew? zYpeP%-tlJ~A$whNPBU=7bd|NhPeUf|_%q zD)a8Y&r$ysxjeA_K8Chi?inwrAIJT^=iJIC)b}rqIVfYjZiKEU2hq#xry#r)B9*N% zOjwKE)?TJZ=g^i;Mi=RA#*qmL+W*1vg?e2ZX8=je^<+pzvbPK9V}J7>MR?S0{+@Y_qrn3Exjbh90Gc?UC5 zhAZ2@kDeGJ{O~EBQ2@;jy~v@e$$ZD*p|kpy(3XELbG@-44Z@3$7c<#ta)sM9aixodWk)EEq~wF&pMOxNto zXMn|2jafk-cOQ&&%C`Ef_=2gwEjD93lWcC3+30p|?=<@S7*9T}OJ{DqOsn+qF1?FC z@Gq+XDE>ECLnm};bKa@-(?Lkr?&9%}eQ>SZld>h>OV6K;0oa+W$(G`#E_3U($NG}u zrI_ddme3kN()`NH+02^r4Q@Ft@LOzh1%c50f$Q}LVr(ic`Wgua|g7)HG6}q-f}$A$?R7H zv278rW&mUwp1}a&7FF0JQ(nFq>VQG>Z6yYgoAqR3$*;Pi9ud2%riO;*_mA|^0$S1l@eMq$>Hj;4^&q+kFs-wh zCu;D2CR+z*x~MKG>|b?&n>hG@3!}n)R_X_A9c_BL3^kLC2pvxRGi8KI;zWI>SLXRL zxvuL}^qO-JcF>y+^Q2F2=kVjeRECPfTikt;#PU&c?2<$!ld_pHa5p1Agd^mzVRYMi z=motz@8b7LFIufRN-Rbzy*BqkKU-XSow>qLH6O()AzcHMNIKs60wSkTDBG7yyXlg1 zYYC8Wd8BV}Wxtj|0^{Z%WD)F}$~7=!vCHQwNQPRBzEMPNvp_`i>qa2MekZ*Rkb){wJn?CYB)E)-?U%TRTthue^|VyLBz$ zDmPdC$ZcjOLnvxVaQB<1js!T9=?*o>E@;Up$!IgZug`auL?!~CkV5lN2(#4xpA2-9 zSOTycyhZ%Yt;GDO!_Hx5D=nm+i@tuv#Y z{=2MAg@#Bzx?fvsjv{?AJY2-eE9Gv!2fhs$qrzYED2~WKXiorMAFgNCd2DlU2<&>e zK;8qkJ}(R0@=r^T|M_#0lz5La8C`DIZ4+Ekx^OtVw9_5$Vj4bRX&hyKKVf!qCUBN? z+?#|*E3wHNFh4ogXdu!v=Id8gJ9#_AntP$!Zg8jz0FsW0W`CxQZ|~i9bg{n$y{*7v z{bmp0enS7!LwQ)xw{f+8dGWvyK7Kfy|2^aF52B#Q`ShQ#YcME?9)uZv9QQibt+{`5 z)c!Fc|5|8j{G7}Az`s|!{_@d0ZacMm6^Pc({?(qnFHMExWR+8!p{k3twyS(xIQby? z=XlInO?Am3p&Jw`GHlpab@H(0howaYIg8x`{O=BiQo5^VWXh72BJ3M?V`)NEjapkH zvHB35lhmdB$00sw@5afKe=T?7d>C{ng6)j@zBpt5kDrQsYzBz|Wp>V6-~U&xw;nPx9}zE59VFMMNRp>dl4pv)@MUx1yA z`Bd@5RNn_QUAY1TKz2FNZF7hCmrc# zZK+!?gsap2=iTheUH?i#weQ?w#x)mxy}dtTIa8yQIT!nYQMM%6i_NDS@$w9R{jS`g ze`e&8o%Ya6Baf=NjQ1DN{XUcup&JK3{w%CsXJfyhCX^z$XQE#{am1RLX+TvGw_a#Y z`J?!EqwO)HQq;v5)7{9;w2q-$`okI9xTeqH40sH6Gz?MtrJ4#4eaPLI;hEcqCO0IU zKwV1ges56!lNy8E>jC~MomUp7y$n@f#2hEtnp)r-D>+egmxgQI7rxA;U z<)KThmk`~Fw`Yc)Z~@f_f%=lnR{x*HU$n+3LzsBxbIcF@HV{W{7bDSwQ<+DN9eS}> zDRGFG(Z2IkS_RY~4MVNmHc@XX(^-r@|nr!yU?18P(2hSb;PmVN zi%=P?ZQP+KKWp^YlzQ=e1$C3+D}Ckvnypc^5O8jwK>l)q(OqTzvO58TTU z;C-BSy^OK+)WQ5|l`yv|_>>Kk_;6XP)zQ!D@}3Xk?7t3&mZ>rd(05Bo#a9KP)+%rq z+=YN?c(79>>hbP^uavt*0q@!+_1rgG*Sbu<)C7*lrbP0w`LSz7wkf10*}1BSS`NH3 zd^rFzOy&cY{g-mP1u*?JOUiYt-A$Gnj*iG#pPP)p0_ir5}Cb#0K5G zf>W@SKgpI3*J4%RkwpvF*0YvddnPBO+(CtKZbvvXB++IIzMW`}md0h#@*J#L!#Z78 zkB)%!W;b7hCOt9`=3aB|;DFP;k($*0-R#L>_1V?d7Ui}$9m*<#mPcB(V9HGsWN}Cq zOT9;3p^mgtymn6v#Qe|zah+geI7D^o6@KaTeiM2&?nlsTA$ey+xRJ8+(k7HKEjN31& z&7GFYRZ>wC_3ll`-k|dMWKBFR?u}Y)BK}G-_CXD~bH}LQRP+N$_@N+0WrbI(^?@!i z*g({YN}1cOAUuX=bG+CQ**J1ID%NkiMB7s1vm4K>E2Z?DOr8kykt?-7M|Ta+}Woa2!C3tCi?!+yp$*gMF?3P&hcoUiU z!PxcndD3E!Xl<-)lZonkOQiRzFiq^W#lBDW>}l81;q(=;p^K(Gx+-0q*q|%%_$Nd9 z9t|u4SileE`Wt`dCX+RH>+D{LxAi($P)R)R51KnW8v!FsxomOf_OJ@Oq%U>p#dvPw zE_Kc51(dJJ9ifu|nkN+%)l=?F9nsR+w7=M7&?cB6ySN~4De~haVG(V>9MV@-rP2x~ zQu>T07Fq4zvH^^1a|oZhEof|~p?*H^X0JG5$0p0r;sKFb#3l(`Ycat>+ z(xqR%@oa!h8k|JUbfvG6YSTG}vX&RES!t)+CBB-%jptX8r)BjaYL9Ap@UIWRzjKG_ zpQ&Ynjr)_`fVQjE<(usdusCP^*T%odH?QUrKD~yKwK`+ln8gL*%WO_K7Qh$uSqz#H z`vk(!(i2`r;?w{qdp6rp!p=hw(Ri4D5Mq)L$f9bkd6 z%M1>P4M}1KRvqoI8}MwHI^tO?JhjQ*JfECaAB-VG!+Z2s8l&=8fd4l;6#l_R|8^no z!K3F`bUoCPn0r{aK|qww3!BTq5}_{v?SoEmN_Y?nWv8v(WQqB}++fWml?rAN{6d$J z0iWq;32Bb23RgMq=jZrYou?qgq))ESCJZrGe5$-4Sb1W6=^)Qxlcc9esG_s1VZZ$A zR%C7Hs(<8o@u+BgIh#6HOHF@VMsWXBrT zZ%4D0v`z+OUt>;+HBVDmxA$_TJ>8y!OlHsWro4y$@g8Jb6GoUu9`{yMduWSMvqo z;6@djc`hd~W0qxO+tj+js8QKhE>b2kvgp|OXROKS`KJf&({cYf8vmz}Z_)%jp=cVi z)X>Unq;fWd+8CUOxY`;cjrLJ+W?)!&`Q-GW`BzkK!Z4&E_dg(^y?!N#_E~ zkIm6S?=^24=hGxyT>;)wLRZJ*zPM|uLVv8%D%s5q|CbJ4^zq)}o4xOp4W47Cr(>e&>udVo7dnB~O^Izm=1TWY z+83@eetQUB66eTJ)%y4IQQm6Wu;R+)^VglsznT_{ zC}zJLd_(*N4DLK3C+pXs6IFuPY+Sxl*S=TPxhrW-kc0I8By>yulD?wpA=`P9~@A@t0F%EaZj2Ele&t8D(%7xh<@brvmzVYOq*^r~e zRCE>+n@bTkat6&5v?lL9n=WeKs&O=h@daZF^i;$IdhN`@nu>Lr#L@ZN#sbab{ z5|h?DzUZ7*{NW?Ja|~r%awU3xS)2j+3pG1CA4pR3dWvu_dGG#${!Xld(LBoP zQQsU%T`)YDLY}-qPU}`dB;y)$0Tk^xPmtxElMPid+)yQ3|6M*5?7d;PyT;M*8RKx< zv!w6K^tFUy^w9p}!@JNg2vCMA{WBS0$5 zT*@f3KdVW9}&FXopjRMsVrIT*9lBi#;+OM`d3wTT>r(z&8;>+qp|s>v@CRD? z*(}|;EKtL4qpdzlRAvm3IN2`$wfBvBIh&1^L1eNSjvZPcFhM#bfW}2%%fLGM0TfJ)>b+JUlZgtFNxAvWk3O&l;;rJqS0xw3(kI z^U9iCo)vzAZSDD{2Rjz$g~nqahUMmjlxyeLOj~$+vx6*pWn=|%-OpLyrqC7O#)^c^ z0K+aV&sy#3y{WSg1F8>xbJUgHMEi$z2yX2f;X)|m`#H^BuF0EuY85F})VHvzUceFx z7Bg(QoeU?HnI_r{jS2$E!r%Ez?7|XM$I6^;r-qEWsCrt7|Df4=Q%aD9*lkQ~BMYNr z?d+7^|-3c$u!a z>0hkhzs97BvG|wnn*Q_0|7T`V>N>{n>%pzg$-cyg6{-%dgQFz>nUkUNn-sUhtl~vv zzV6f=s9s$B;5Br4cI74^;IK`GK%%*P#nr|aohIaK|5|CU;)vEsTP=g7DWK1IbK42D zt4N$gTt`eJjs!Y7lT6jlxS$@oP@s(^TH>Y8hr{-f_F6+W`0oXmhHJaVzRTY2S}lrx z`)wDB6tcwr4g7R;cA{Kk&wK&^{0@7-U}yZWX{|VRLYT*|$*H#~6L?~xj)XiM10t4D zXe12tf3e0A|Nq35zl%IIg#x1P%9@nV3#H$LIWWt`*<_jF)>KTEg(kkOdK^}+-`A`s){e!xmDN<8j2o@1Hbh8+Z^PO(5CQcz zTdyc61&B(1Xega#(aWLL9hxl(mqXH@2y&W)+z(04cDxQTo4F;Q?vobN!*`A0qqakO z&pBom>A)R z>4m!+xX@=FXVFX3N*M)q^@3r}F7Vh>$@sE7`l^W0JQk@Y#n;-9PQ-$fMCau^b>E{% z{<3vL=`4N-jrY)-T%6S?<{ms zB07g*r<|>YqNQcMA%P5+h|EDbqs2ANsE-&snMIk?9i4JN<9oqjq1udQcj-s;xI=^x z?*ZlaDg@Ip#J%8Q7bUUUdk57p$IX(bl{M~xY^NG>fMkimvK?AoKVAJ-QJg~0LcfMr z)lx~)$^s0^>bmL}>{wc&Gx+_u3dWya+A~;7vmc-}Z)EtsPPQ|P91<;yd&>9)O&6V+ z(sewKl&LAs0v?>L*`-Cyl*a$C7+nmby%mrfFRGazZuG_MfOE*WGv87?`M8ft%Un)7 zC{mhI)`Cq;tg#e?L>Z8hPtGW+;$6)Jh<&==&uOfBgQ$dDa=_i%lGjYJN!crbE>(U0 z zRiQLLX7$NE|C@y7h*a-Zi?$^%74^2wo1(Z$tiyCNCY~LQgf>?Y)@aeo@2C<&0TDgw z_A$!ZA)}OGK|`B~(OJVfMcp_x!0Xx5K+{8nu9g zxAWYkEK(gU`uBIZD#jTZ>62eUZH+BtRN@`5^P~2~%FMc8A@NYP^E#cnhAcTx+=rC8 zD9&vdODRLuTNvpx6Bh|3KKp`SA#G*Pi;hN$K90!p-(G}Q8MJO> z%UqNLdRMxcebzjEa~YpI2*OBumZ}<5l^vcuuXq_=S{DDL=#uaJ(fR*P>HRxpg}KAZ}eyWdO^pWMflb$5PsaFUq9AsdN#%{AtBiG!eyr^CS!~7; zwzc9wK4hFeTtcJx6yd%JYW#ww4!nOoH`Q&@CcXSJJ^-t0+w(X{}GC zZ?Q;=W(}LfzBM!>o1Mjq>>G!^{Coj(tDItFbY<%!M91e)C&QCu*5N;swH7#sw+MP= zY_mw$E~x@4drq~YnuY8AMfQ&--#upuCed(l5}dRm9!03Cs(hIe z4WEJY9pbz7)AOC;f*g>Gd;>oXpHvwKKdc}g!2J>zo1|&OyvB zt&WiR<#>BJP04#fS{n*da2%BOojwyc{T2yyK*z9}k}h>ir7tATydKqE3J&zQnHutU z>}XGf%UdZA8qjLY$$Za2pbb`%889k^h)=dtntsUIOgto4LF6WE+>c*NGyNMeB6#Uyseb=#DfF2U=*i z^xz=7EPmlHU2f?gr&G9hA~{F{GBC(P%EGIqs=?kN;1jVuzL8(f7qJ60AzK7sZ|Xvk z^;Y<=HEr6^U6H(f@&@c`9h!r{>72hqil%>N7lyVjd&hDXj?%L*PT78jK-LI-BPzv( zy(Icakd62H1536~45Luu-}aE_#HP+u=Xm70?f$q(Fs1aKqh*wa4K*1KW(-hk@;qK& z#{}rvtGTpm+RTNt>P?KyvTLyu5Y#Vy`PkX@lu3^pH1-}v6}XV!pZXz-b#`4TXQ;r*J?;+UYZG9;bsP(2?trLZlNJ(56r$vhNLX>Nz9Q z7{g${SE8oQCs1N#E{f9~(IyK2U4g{}+E#tv42rw7-n;{pusba59t}BKTY7r2$@ByZ zgwsEt*8YG;muVAJDikLcyB+8P4HJ%WN^q#(EXc}pY`yzFI!F}vww{AI%^J))sPZMf zp;uW}QMB=3IjyP`yfSBquTZ&}+%;k40>Y^;W14SxF|8}F!q|7%ADtj1h+h^SuTQP_ z*)4u|y=kTdtLhRUKwUO!J5Q=PS|L-2g4l(X1e-mhN{w}V(k#MSs}X$<2cl_oLDBXh zia@bHXgb$Z>Dt~lI4R+4H(>1!87(|{4oN#54=8q7Z=yZegMU&oFs5B<0jN40arPcm z<{zinTf+m0L#Y_KWId5G%uRYqCV8m&(ewqE8!R2Yw+F>_Fd(H8z93YU3jZA>fYoqxFh!)Se&;FN~j*f~Xr z%cK5^cL|nUBKfEQdRQdzRu)@J=felIXWd5<%{R=iz@lk@HSra*%^Sws7$9Sdp&h?F0fBGJM=UNXRtQ_!ihut>6AG>Rq1asO-#yoi+J(cN zMGSoGj^F?GLDe^N3maEW6ZEsmv#V>9B}=0*#c0)bBHa0F5P{m4IC4yHJ=u@>^271y zN(Kj%em!oWWJ#q@ue=`IW3v~Qg4V%Xbu3@Dgl)<@D${F-w5UzTvntDCTkn^-1v2m; zr4t5jKOp?|(+`~#4jszC?c)o|y~N{4{-!I246wST!wsVyo6B{@z6@QGLy?1mH-m=F zM7d(CQClzd6npD=L;2B@iq8$Uzm^`%KS&SOZ=#ZwW3Wlu9Z7a}jId01wt>|r1gJj$ zTyOiU0Go|eQw+QHmq>IHgO>&jQ$%R<{u;&EowxtA>&pD3IG3+MZ@5VMQs-vzMpk$l zh6*b(2(z;~7)fY7o&RWPWF#w37G{upRd>U(&|G)vwxsFUv57Z2Xi;z#PsdM{2Rn|N z*ZQTdlpQ7iqJ(sXt1#qNkem*V3rn1B>W~FpSMyc=&-)|5+7b`Q8IPL9HMIDs95^lN}?j1A|$LRWF(exw0R>Kgc|N@Rl_F z`L`(XhJMxQ29KoLCp%@Odp{vl0_+ph?^d!I!m^&xtfS67T}w%cu5Aln?Y^9$2r*T2 zoQ{F+A^$siiU_I`ftjv48hRliX-IoDlA<#onDXpLO|)LB3?egR!3U@*;qv8HnS5)T zmz6z7ekP_k{2ZSv(@3E462V|i~G zB7^#8L%#~WcC%`m@Ek%!W#0*|G^6SU7&Q9gemJrR5NKQLNX^R)W;2g|rf>O!_VXN! zX|wK|(;gsw(K#SKuxKdt{-C3_dU?L`BMjQ9w|;pq<_hZOX@o*dz)`J{IiB0c>Xi)F z*t4Z6s0U#WS%hTG2O!kz)JN^77_;k5y@YY!t@QHc-sLMrhT*@Q9a_{6L-k_H364Rm zBA^leTjKU@NTBN|`4zc#$ZJ&3P?1jbYfH&Bk&F6T%VM;rLH@0`O}tcwvd6zWzuqfA z0!mlfDJBwbUCWn~3^C1)uDp)4N182=#~N0R9ozX%G6ZgxaKb=W<=8^THxSl!SKWLn+sDuWgQFNQz^21v}U%nG!u7n$cKt)wp z`K8VT$}jn;li+O%w6s_Ar?0K;#gh_mHkW1xhWui3ja2FNsM*=&{tla)I1w}d!SVLmp;U>`ik%mi<;5tZ4b%;H&ENtbwqM6B0s;mWuPy>jI3YLr z4HwHpi-fz9(S>;>OP=*wT3XXOv)YQUW?sE}hl#-CP=qZX8aA%CiXEPM)RzBHr&Eh_ z7!RYg_<;8=UXhPnYy81@M$)wmIK~ADADQz_aNWY031djhk0yH2UEUr2I*(in&q+Tm zYksow4W`V>e0gs5-+>QcbY*27;2i$$;(u$~nOR9$VSyy0wi4kF<)CS0%2&$YYV64* zh3M}(8w;~ZNwlU|xyqkop6S2woV%_svEC{Iz%_du`^>d={YsJ zQDnKMl%zqrWjw!{*dT+8V5t}=l@SDW&2;Y)YwJb@iYll}!;PWNi&(~ljL z#Ur4A?X%%L)54~3S2CZZrxrHoI?09a$EQB-0AQ6MtN9gpJJVayZLy#3STxS_oDj0zFang|B31i!f0ID`y}3o3Tmf*T92gEZh2@Rt2rKG*TBDLNj_DQ&AA zL0D5_czWYLLmo7Wka(sz#}zrYOtM%WV3v@Sw|rP7)YB?BMoCOE`8ic0WN?zP_6vp| z@l)MV*dDWWe{aGe!DQ$iZ^nm@MB!%xhfl?Kt7ST8Z3R&6AP;nA!v1n z@roIT^;+@x>nuOu-HY&G$v%QrpI67W!+U*oJ3|l2LM)N7tmLYqvJuokB;wrB9?(Zl6pyddP zeOg|AL7U>1t{1ORWBmL}ZdyUCuDSu29aD#~?H>51wH4=qX&Mr#+VVTR4z~iPMM||E zk4VGKR-{gxK9x?PLAGV#}K1sGUnz`CHX^-dcdHkF)AE3KVAvt}ClL?N8o-QWW} zY85?L9qhZ@^zxqnr^blRHlibLy~g8ux57}?3P6>nTnsgWkkT~8`m!2q6t33(=F}wA z7ny==>`vj*wOH})cHO#Yyd(B?q)=qY{HRJuR>l0jtAv)nmN4I=5p~~iFxs7hL)?E9 zH8S-+{dGBkm~sO&dve5@?+EnG-YP<<*=~RHJ2^wt?D#vsY{hu~7z<9{O=_2|H0aFc znA_n64%ST100azXPe`6B2rJgH^FRy0I0TAiU;E*H`vamm)Z5JbzS`EqDJQ(7LE zq+hWq)VL9%7GSH=BlBWqw1HjOy5G~_4uIek;yhb!&%y(9Iz;d^d(G-RxfIt)5Ot6? zW@x4)qJFM1)upO6K6OPb{4$awM-A@)k#a2xrYvPUorv6UMy34aXqQYbS8$61o4q{b=hhCAo1VTCN~?wXrrVd679tCG^GU>7I@CGp4%1 z17)3%Ec%wYwXy!HuR~o;K1Zd%Jnm9r&DbM~9F*;l^ZWd=kELaw4n>hNih_9BAebAC z7?QLc{|WUEZ>fbqN8zU@R6|L^OoMYCk=*)cFgP|Tk%KCq{3~`~yl3xQtizKX+0l+0 z-_Ap(70$6y(LZQSCQem@Bj8etMn*l}*=3Aq>e&a0c6qT_x#+n!OF7euf0z9JonIB) zbeZ=<(U034>n)Aorkto-+u6Gj#<*HmWmmD}Iz|gqBa%srr6?!Ziu2KA55xrcpBvFe zuMx)cZG7Xt3&}6QbnwX0@Cx`|x_7v=-(EZ~=B;yeZM|@l@Z4Q*pOzKfF9KxATE{>DyNOzu8rvd z86|AmS8~+SeqVB_jcLWjZxybNjt%e@@7b2RG{ zB@`Z>)kz?RO;|CJv*17S_j2iB!4jm_-n`c%ajZd=JJly~5@mkU`D&i_X|i~=&@nqg z*f!qVG(qQD*w$Y0U9&YWhCM0Io44bj8UqIjETSsMaW?5+f;l*gj9)m|)#1tOZ)V}khN-8%(zFCLX~FfPLao8=qgOA^ z23AS)IC7q8IUKx=d^|ZLOqa!usBF%jGK*hvL4qN|u?*?fzYIwANBlTk%Udz1a?cv% z9({Nwi792>nJRVExthatVcSy{&_Zgk8`z#j(+)DockA#b&$P4;Y{}Snl#+oFp$*yu zu3_Xo@YrXFu?7*g{f797Tf-KELxNVo44dZ`LGQv8DCb&f#J^lSL)@cRfywgdLBSEs za}LHPu4;1GP~Hbp>6ey-)lc)i0t5Zv`vKnu%tg9?7C}0GALh`6m-HRoHJo6U3EHUA z8*9rk4UUTsECbEbY_IxQE3R~8%B@S#T6T%4_uG!z=HQ3V9wP?0{NWe|3Mp!R^7Kul z8@c2vY(~danyJDmS&fyGir{=isSrmAYf=^$c+Ent9GwtmUa-~@T}3~Yo6*pkFED+l z7;~`jTcR06!}A&;pRkvm)Adtm%+i9jzP9)BxB=Z+Nsxw7xzRQ*zR|&8K<9@EEnUXV zYot(EV`Z7xK%?PMSaf)ob2-DHVYEP5EI^*bl$7k;c&}_PK=t6z&3#~PqlKV9lI|wT#=^WlOCJ^ z7Ep%D#7HQ=WeJ~d!>KgM7DD3-*)O*nu_dcG^f z=5FOTMYUhl)uP9b`?V6)YM4Cz>J$KKvcK<3;1;a#we7GZd!LdnhoX6zt+J^trQilhur%CgV?vVLh9zv5$J>f73MDbxIm$Yd0yT`>3c0d1%> zjv0?xhi8!wrEmXcXx~v35rsucCn&?hQ}kxoD#MZKY*;qzUa$$8r<6Y-`sK&K+Xd1` z!QsIt)%7FWX^l@!96gsW?ZD}39*+DoMd_s%TDqtm+0N4#wv&2;VjhT#K5RAoeN?fU zfdf6|<6MK^XRvwyg=w+eIW`2+cfpt0%hSGSSVzLlT!@&r+OA6xzEK(h($vi|_!yHP zipNNqS6b-t9BaNK_Q^%nkoO{-qw}&ddL6eFOnO!J^Xn7icMW#@<9n4XN@uOkD;LTL z$GgkM!^TrEp@ogECg~HkjdnYJwY^fp+-iM6TThP_OYKTblZ!e1qrvSWhn~EJj8jMF zaCrWk$a6*2pust%=^u40oR4Ek-N!ohk3iyUU4nPBi(ZBHlqFl)FrC-e=lf61=Dl=Z zpnQ>q!=H8Hlqo~9VKPiP;wjZhy}i1(;z~)6Jb&Y>*7*#2lpp_Cv9O^j~Rw8viFrgefotad60{etGT7(N?WNKFp@6@wpt#h^X&IR76=}ndIp+=Xh z_IkUjBuZ}F8yxs5jUt}uqFQj*ER^x51Wp_DDMzU@NE>ooZ!l8BL?J)mbSA#rL)i)x zW(^z4m%hmxO+`rO1T2{S{X#)9W29i!U_!Z~OR*#u#J{a!yS{~@)1}$hJbap#*}XX) zowMC^p50}5(r#)Q4a1X*eD$*Gav9=((2o@6tY1cYC7fF22H8O3J`^k^gwx(D3zPaS z+mfk1R*uT!)nemfoRJO_+zhZ<5{@zV-`Y=v@rw5-ACjD$Q#CyuK-z~9&83-Ux>?xBUc$D@!8axfn9Qi>#c7S-g?O%Iy{utHS zQ@&~-U4QsIEVTwhx@VRCO_`#Dc@}@6Dlpo()Ja>@ENU#IFqts0rPX!!Buxw4$+wcmujW2wml%R?x#eGGAkqTLWzMR-xjd`V+yX?L`w z{8;i_rbfYtXtYvF;1M?7yX=*NjhtOl?HHE@LdA@#>PlSfA!nM_Q?V=PBBwchg)rCTZW!2C5M7DmAo>q z5TB{|#a<1=zEd-h?Wp@kjX43)b*YOpRma{MrZ3ZpCYr~en0vsxt5B&&>+nzt(O&)1 z;IyP+0q#F~gg9^dLbiK6Nc@?G82__HBf#B&-w)E^Uh8}D5-^CF%;YN*#DfZ zsD!@!Ri6p%^g6n3NrBAY5|KNz7dGYemOF|huknw|0L=$4gESn~`spCl{a^$; zphw4W`gnVo2})ZjM9RU@Bcl6u$5(iR_wlrT!|u!Q2TIje-=JVsU8*)@P+0#(L59Cw zPHpWCZ?=<|_-ft$$mBt0v`$`H=^iP4WpC)WLRh8%0m#*p>(T-16&|8fch-`{V zHmqTkyddAGQoE$LL>6{#(?E0lYVGtfIu8+w{JM;Cv7(FxjBl*54dwANKaS^TUr#OG z0i8yn&Ko(l^z%X(Sw>6uXKn3q`Pe^uG+b&w^pq3hln{RH5)-&kl{`}UhD<^PQJt8! z{yxIfSC)JP0$FGsWI`#Z&k}cW&k2(}Z=@L0c;}kztxvRGKV8mvrTwJ26Ttz@xOhcG z^-Up1Ef$@O)o>h{8lw3pzv5S1Ov>vDSn4pVcYQ_U+~|Y~J0>;<%-OYFs3u)T4GP6Y zZJsO-@PC}ID=+YJ?Uw5$^5|>N7hs5IcCLa)c%4t4FH3n}JQfk`TRlDp^@E-58@F!D zoa75^s}fw+etyiW91>u@HjieI|6Iji;`kuoa`45`QjxIAQL2|-Y&Rj;3*utd4#812 z8Y2%EZ3)yW`>>d*hOYAA=9%!oP}`b!-&pcRSf(<6gsr<1C%bO%+&kivdTlzq-?XWT ztVIRki8&g60gL{^vBR4#pnMpdBLEtm9@635eb7GFVWC%Q8=uFVmpiIE7SlhSk{FUq z8n@ujfQYebi$aAA{oq?hf?G#VyN-S6a0SiTHwi}fu0@6hYih`675lE006%_>m5fA|(B0{7F2qE-{ z2uSY)2uXy{2?-&RLP$6-_s-mzJ?ERbXYM)Q%sq3ye=?KF%3AAv*R$5Mp7#4Or`JJD zgG}=6YKF6Pa!%pvSuIh;(2v0+CCR0$WhUjnMKjwZ|HPVxQvRVQd7KwEa2802RVDf~Tv-^|xCkIx#v_5a~U_Y?4I^J>xz$7xu%uQ8R za!+`ty(`b|<+ks_x5!M#sjfTZiP1-qw{i8O^q_k$CJs)=I&J#BLDAl-ZO2Y8s~wx; zts`1GZ*{lpC6T+;0wkEU8k4wK&GNoWDrcS@xWO(fwLc;wopogIS>5&ugnj3TEvL_y zl2d_5R<*ghqCxiD9R0O_K;Nu=U$>;%+jlx?Cm!wxwu#oNu)edsme^iux?P=Nk2tHd z^&R!#xczZZNv!SOO&VCqbgBSIT}-=QtP}rUov?$xMdeoa8OF!S=jU;|CAQuVxSo_{ z2haIy{zUBK1MVyC@H_}<TLXUeGRj5?h>Y4jC;vNP%$@v+3H9l!-swiNOyqu0wz2x*XF4;d>+~(VQ zpIINW|KfHd&BX2c$14&RA=^V(6Y5Qw+0=7fDZ90xIloHU?jHMzEK2(EqKZsXw^3}X z;yF@J)7!>7U*_F&3*$0mF57P!^bO|P5SB4#7PX-+c!msumvsErgHM{0zvq9^k>9fz zme?wkXR%b%lNqY&K=ts^rx&SFTkQ59-V=}exKKk(NofQp)Ql3#^s=)mnz^)8vp+o4 zk5*&a{A#uCltoHda^JUk%~wqSY{ccrpWTxux@mXmlu0RK<%b-)LmOMk(vu5-o`0_9 zH2Bi`PvyAUZ4gh)m0OLAQAY#p$4@R0m&deaWAY13ZeF>w-}=(&g|F_6%{_r|z8uYqqY{wAw!$8U2}Tdof=%k%+8l>T<{8-F|^26-ixn3VyZNa=5JGt-2t&JbZKM z^F8Kgu6;W4+oof>bs*5a*sz8EQ!T_87bH7VwcmnN6GaHnNU!j<9Zbr|9t)2l@21P{ zk-qyt4KQO(WFrmKB$OirqaXilpHWU@?g4q;nW~X=UCnYg=r64HKAGwCxc{aX`%w8% z6-LhC@m!qqlsqmuq69|Jj!X3Vk~!`5ZLUZoxOi0M%lt-zj~eK$1#_YH3cW31y@Gag zFprIFg5I)2K9_Va$RF34?iye;ji$P!+bU_f{0Z^oCS1eHOD%qm4tH%eRy3*kI7Xk5 zXGnp+pG|+$leu`+K;qD6&+$IV1E60D3KX;SAJk(r%sbXAhUXqrUJwjcJ6vTid+p%| zMq0h!;y>#uIMA1YAKMMH9)zA2g6Vel)D-oT*I`k3-G!ijW^Y2=3tbaVQVq{<`n6Y- z(Ce@i{;h#VNT495cO)9E(d;)0(lcJNMbLxI8!O7@^U~%;ps~#dxf@gylSO zQzAXRxFYZP;Fm_Z^TBE5{Z`4c<5@XM?85?UqC%ks0T`s^1>$c{;e%ZlsWOTmGuD=99N7 zJqEp$P!7=>K5CZ97o6x75r#}-T8*4vj#4(gTL@pUe)snLIn5-&j~W%o^PHUA_mTP@ zFN~BWl&w}p$-WhG3qHX`^#KwYl;;wEIUl^0<`y|o7Oikm^Pu3Dc{|y&65%jA*3zkU zpvKKUzr~}+#6r*H_JuE5^hoPCodv1Ty8tv)raH>Do89Og_9vyzZcY6VH&{GEk*~tn z9PxOkBYbhZ!GT&uB9{+KaiijPoEvbTUV z&MfqYHK|vhWde1So~4~-vp098s=1>b=y|b+4K{x6=^Pfe)N4gq^e|&%`VT5lnJ>Q} zN;_6ORB-3W2exWm#W50*#oHtN7?4qOE^yZPdeHknc}0yjHwo@_;tTtsd;$onq%^qd?LvuA&v@;z%Sn7UwiTWhpoO+ zl+f{6Ztg*Q%Sz~>JJ`Epbv3NekJYl>D(w}uA%XL0O3#vu0^h&NP1`xJbHL`w9N?+0 zZK~VV+aZ^()vtIZa3OQYkju@2tSom64e5ccK|3E9Y*|?Q%9TFlOR(~bdoFlhw%iYo zXPyKj{iI@@SF?+?w+2?Beh%o=UR@zu`N_Eh^}^rH<-^3k+o#r+@q5l~bw{6Z2-36Y zYN}~ej~y?J_fmg4WB;c8nD^lwKin@}OWXO&%%Fp86QU&&Py@{pCf z1Olx0BEPVCQpxqZPxMvLQ>h~xS!HJcjGv(OzJI?&UX-;e0*R9?2Fw?El?Wv|>TMi@ zl`m08F_@|I7iC}K=+UXoElfGjJKXEYAoos%(E{<(V4sntCG_4~vrn9(_UFEnEP)|_ zDtCSWYUbWLD2&H~i`0p6Xwf|&tBph)?_39Eq=-1QI^wT-u`X&QWg`f@4vNwiBcQzQ z2%z4wPsj&M#{bRvAeN&EMo=^ZA%J{k&Z1-1K~4Z%P!Q{1z5naY{7Yv3wVVE1oCGJe zF`P}}2lDaw3*>zz#PN%%2AneFb**fvs){(Kpn)ClzgW}|o$n%jajZ*9ouJIF(mh04 zxuW40wYpKZWM{}0Sa2Ezm%>Vi?T9<-W#P0b!3UQ9>L3$7)tDl18lq`eqw!_Zoy94t zctgV#aedExD(-EKk;D~^0gjo5QC#Lht9~?qrTqwS{&)(aQH?$*oaH)50#$<=`5}}* zF#xrcE011-G7Lun-xY1b5JHEz!SPCLncD*2@d}~bZ z;sQB$W%BEb%c9GoFF%>Xyo$U4B!iQ_#!tyEaRgx%mXCs(NuAuNA4SxYd5rFN@^dME zt%4oHI^O)R9rh0Juv&|gl#i{gC{>x0x~ETC5&e04)sp~C=vfbxSg#NKPhXS2$;SHN zKlgR?K}vWUWED4f#+0SGbkNnl5n+13r7Ifo`!y5Y9^k7S^X?^Y*7vtHIC9l(2M7Qz zbe(@1azPMEya9iu1y?uRR$WU5&41A#ftEL%l8*m%zBZ1f2At}Yq zh#_BJ&rWmAcJRY+tT$*ug2S_k0zA?xoEZ&VU=S$*r|CI<&PbfhF}TSjK`4zKKv9q1Y^jm;$LU z@T3l#iRFFWrq2q6UWU|4?8rbcxkY783;4eQ4zNArzls|cEzo_k`=$Z>@ELM=DgiC_%a9P+ra z6E8xR4!s>#FlzxYY_EQ}BBPRrJmm?ycAbYlT6q~p@DI4{bKc+9YKm~UBTC-XdLj=i znY-o9St0;{B71@8?X71yRk68L+o7dH>Q-2A{=$5;em!lmO)gh38j5@nlwruD9I{Lh z`W%%sjLQ9t`QoMgU?L>-*bg^5pVVH{%>Xx5pmCQ}6#CSXGwtEpBY|e0OY74G$4PX_ zLl@L=jgS8&-08QOxup-&ldMRsYG4U#<0~3H_FZ|V*88usP38*$sHtn|`vj3;hZZGA z8-5u(uT}F|M7@}R#cEYbMfJjc#8CT~9{R!J*t@;*okj@_bhcASZu`y*yj7}n^oLgM z;fr5-$8|*jET=a|uqHFmFs*Gk+j$2uO(qYwF@{hNJj*oRzdpH7>UHj0+=+MXQxEsq z^w9k)S4~`xqfr0`>dwkn#NDrnWe zFkwxd0_+SU;7s)|FNIMLNxccjvfYa-x|#*rm8-ID(+EJzxjnSDSkv>IK)R}Ub8D+O z&$5SI7{82sz%MPgECP&g$0E*QdO(jQr&!WB5OQwN9_>*bK7`+m%% zIcSo+^k^Nv%PTTVJFJJ5 z0MUOW?nr6D4cZyZ>k;#%%&n(98wR=EJfSZtJKuLui)Dbad4+z2+9%#5b5-IOB(hfZ zV!}hzi>D=&!*Ts3X z;YB=tRt2ml?P)&khG}A62?{WBasK1s%had9mEyJb5A-|ep?XDF;ngL9HkIPi8yfIn z3cQ0*7M@yrR_LU?&GmG|bhi8xOsj2^Lt4S-97C_ZG@Wa^S10>E2!Y2yKMWh>qj0Od zyWFmMfl-ehvQSUO*OP~KVXbw;e0>o;v~&mW9-F&7HKeEKJkFnvRMXpP4Wqc?6)-3 z8|yG@^c3_`)3TZOusGxIq|A=f_*quBB41JXZ zeEerUBB=GDf3D)}v7vzo#>mrFPVu(fBRjXYp1SV=0!5e_0^&G?769%79q5#R-6*&c zc4=V@69!{82=;RI;aOMD>RzO^$}?QLi_!kYCs^y#E#HTG6F8D{-WrTS}lw`P723E zOLLYq2Fm+kJ7cH)UmT=ln<^c$Dtl}RtR@*uCz`jel@rI+DxE^$Zg%cGa7QTBs`p;)wKlHhNMWj+4|{UrF{N0Hdo8Tw2s+^b_WeiyX720O^nQ+N&2;t zEOpfDH0`V9b34ExWvc#O9ye$ppC-P?XO;mJsg1b%1a!N^RE>}6APq%?UP& ziZ#%zCAgAegf%vGM;V0{*P(j|Q_0JYX*-o$CG_{S1p$-W%wXmYJ8u_UMSXjKOFxB0 zOb?BREl%KVg-jgR+SCh@ipgQu#uS_75Y z_3I!532YU?_^Uo)1Xk2kuS@Vj@|q~3<(NCLYko#L8C2+gE%h*8SU2sxiI(`piB{$r z-_YZ-njU5^wgB8+eFIs>H-1nTDEoEe2KYG6K0)D{5*4yZ`+z-9p<^EY3azq))~MN@ zqqHPomSAS%zK^7zl4p}Xhwg(se#Nc3PERlQk5B#%ODmW>7kF`X1cJg z4Y#5xKny7iDCLOIrAX?)XG-XWAk??&kgoKHiyx@x3YJpWcFcuiG=5cu?D*sz7PmL| zW{?v-NmG9=@Xh%PfKHqJOYEB-Dvb{%3+Vl@LV3xt?|$l&mIGBERt)#aZ#yoZ(KVqL zSz8jQqyH>0kbT2`+F$rcChky%t7G0@&61BnKo_^=@k^LVj34T_TBX>zN}-|?K`=s4 zPn9Bv^zusgYlNcdDc@s>?Cz2ZLJ*^vozrA}V^X({*F4oR{-8xF^QKvCCd^3jyh-d4 z;O1V7M762KjG%uw<0B-ekz5tg2RTSbxUigH++3}$3HN6JXK|`I_a0)BT5~v4y9)-3 zx>D*Hbu3^o!RS?j^3iDJsLcBl@E|4@IT2w~h)Ch|iha^gsh{j2*JTaYL6+dCmFC~d zQeLIMN!;CPVm7PF-~yN2Mf?UqKBh;%@I! zk9PS?yr2b8`eNUt`_Oqvw~+SA2+Lp04hAt&lu@pIa&Z_RO3%gBLxBj{DC1W%jIY0~IA-_Ws&4J^;lcP(tw9GP3}vufDqNII-6{NHaPZiFKwU z4Ya=lC1`=^&Qd4)1g}W%uQzE{8RYblg=J+ore0UOq0Wfrtlj;wD zi2~O_UFuT@j8@Rsd4vXq83uSNyDuoTF#zZf+6Y|jQLsg}izO9u8VR#>9=t6no-dAS z@z6@348D)Xf9fW=?@jwu^yvk1!(2J|KlaNfuQjZKI5op(L`N1QVyG`p3( z3)qCoL%cclDJgaVW|g;T1f^O%Es-kfSWqa-iQh9ul+cUBu9_RXWHLztqn9m{T;{@X zy3gk7dZBF99B)g2+I0Km9lXM&RHtxKHO93lS4V29A0KfT(cJ-!6-rHQ^^9nUra`3< zDc|I}0L)|0U}Bn8*sGKv^Wk8fg$OgoVoMdFP#ArXW6i2MXM4~Z|M^r~c`My;ffD|k z*WORMW{&gI(wf%&-;ySA)u%paPS>JPzr_vVR90QDg9ldYv$E1LQGk zH~YSb1@I9i@z+oVmNKhsz(C8cB_8 zR#jopc;Fs&70M)y-qt|;A(I)m)KpJ^>JAp9UxfNlOA$>1yzX{6PR)<`c23V;z(Y{)Jl8 z<`+SEQNk$Em{6VmLBwOD0Ts+ZNv{e31zjgD0B&SvM@1yDbX@=1cK)ff7`_EDYGb(g z^Xni~ zmb9U=Ax!lp;=~HEnOI5uYS_rsMz*1*HR{-D0oI{NG0CzvFA)=A* z8p%a{6Vn*_A!G+~I7VO?e}aXHp>cra&jlEq7Z%|Bl1GrZTq2*~BjyCR#5-__ar`15 zfXLHp)gNe;&l1CvL`Dv4ctb=#f(s3F(*h2eLxjojsI&zj7|la^xobIFbtwC2H4jr{ zF#r)ua!&=$!onq`zE*4xYZ66af95poIJ|G&(#U znG(@|TUkX}iL=*TBSHRh*|RM#DQ~s`J673vRZ-0K^Fd{!S=~!*Qmj~F4TReLlX??1 zj-tW^VW>Yi{CXOb=;InIN8XT+SCASo)kL586;%)Zc0ve0wFE%zpIQP}E16!qGi<#o_!^`8(5jaVZ}Nffq<>4qG8th5MO zj|SQUh)f;c(D*XIDJeCz&xVK#O^Y-z-QIm+;JvTH(1?y-TDKd9UtRS3X zw0K7H!ri&_-Tv=CjA;&PzxaIPl2>;%&psw*9b}9ib3{Ew1weW+OQrxGB6JB@UtU0y z`WQc=U-T8VWodzg;cCni4**io??+t+T_)bfL8?)+3;cU!kXeqfPBbdq6}%zR7x-|2 zK|Rf3Occ*m$Ho9w;QaONqJuyIxG~RN_*^9Jw-l|2H;brZ-t3^*Tr?{Ni>J#0t6Q5F z2Au;|sCc_b26%SOLD5$rFbHnw0w#z=^?{cpPOiemV#}Ya>c2$k8`6aWTK^4@>pz}r M^?!oe#PyMX1A9{B@Bjb+ literal 0 HcmV?d00001 diff --git a/wyk/data-metrics.tsv b/wyk/data-metrics.tsv new file mode 100644 index 0000000..c50b5e7 --- /dev/null +++ b/wyk/data-metrics.tsv @@ -0,0 +1,50 @@ +0 -0.9410633308036449 0.46518252113944425 +1 0.4700636553691919 -0.3970321538875541 +1 -0.01609299859794966 0.23161453968628254 +0 -0.9966154155058933 0.06419313152355421 +0 0.8000009607150127 0.44133107977776875 +0 0.389227379480078 -0.8415416694237676 +0 -0.7786281038890375 0.2833716839963434 +1 -0.10150562150521569 -0.02968754639839366 +1 -0.14995353486391494 0.30921523116923866 +0 0.3150219624148183 0.4186143523577863 +0 -0.5542734031872467 0.9291684810885719 +0 -0.44750469543445215 -0.8240387195698262 +0 -0.7875312310670415 0.27475695030524894 +0 0.20470154428730747 -0.8122722630746713 +0 0.07472783793361693 0.8936381678688297 +0 -0.6016285994197443 -0.9783927694535444 +0 0.4235345463350013 -0.23977977886239832 +0 0.256790496684171 -0.5587059709121811 +0 -0.2172656054288027 0.8015306542483966 +0 0.2009238354275602 0.9376873763906164 +0 -0.8760038215191506 0.015194717659306356 +0 -0.1512141038160364 -0.9575528046526418 +0 -0.6378974241766098 0.35900665963616696 +0 -0.6219617077011876 0.04019896541474166 +0 -0.2533778634666939 -0.8576798720089458 +0 -0.9398823073223508 0.806594859009744 +0 -0.24161324930138606 -0.6982896600554984 +0 -0.967724402993285 0.15651783268628372 +0 0.9587968810951801 -0.3382309645563397 +1 0.18040441263417084 -0.026706542719935777 +0 -0.2403226372749332 -0.2694487472698215 +0 -0.49494412803453747 -0.6833825934742561 +0 -0.32266963833818574 0.6299706350061482 +0 -0.716450532167108 0.7792499086149187 +1 -0.5661825812948427 -0.3045016769669948 +0 -0.9014952263862088 0.19697267011506714 +1 0.3192734822128551 -0.3145295901019187 +1 -0.4386590899062277 0.6119229005694005 +0 -0.6306933372350818 0.4721301354446683 +0 0.3302936606411402 -0.3047093070118343 +1 -0.38049655790356285 -0.609474130471132 +1 0.32069301644263426 0.17266197471996692 +1 0.8349752241994568 0.4408717276862013 +0 -0.26741723386938343 -0.4919294757003996 +0 -0.7786699335922747 -0.47305795528791905 +0 0.723410510517891 -0.010095862311693793 +0 0.0902826080483603 -0.6805262097228113 +0 -0.9286972617786873 0.7200430642275493 +0 -0.0623197964184079 0.8187639325432745 +0 -0.20572090815735944 -0.6655000969777327 diff --git a/wyk/data_flats_with_outliers.tsv b/wyk/data_flats_with_outliers.tsv new file mode 100644 index 0000000..607342a --- /dev/null +++ b/wyk/data_flats_with_outliers.tsv @@ -0,0 +1,4186 @@ +476118.0 False 3 1 Centrum 78 +349000.0 False 5 0 4 103 +390000.0 False 4 1 Naramowice 100 +530000.0 True 4 3 Jeżyce 70 +364000.0 False 5 0 4 126 +294000.0 False 2 0 Grunwald 46 +277806.0 False 2 1 Dolna 47 +571229.15 False 2 4 Wilda 39 +346777.0 False 3 1 Grunwald 10 +279924.0 False 2 2 Dolna 2 +304000.0 False 2 1 Wilda 95 +604836.0 False 4 5 Grunwald 40 +268229.0 False 2 1 Grunwald 90 +325000.0 False 3 1 Grunwald 54 +274200.0 False 2 0 Grunwald 57 +333694.0 False 3 0 Podolany 38 +249964.0 False 3 0 Nowe 41 +833018.0 False 5 5 Dolna 31 +399406.0 False 3 2 Wilda 89 +277823.0 False 2 4 Podolany 70 +427202.0 False 3 3 Dolna 79 +242751.0 False 2 1 Wilda 40 +324387.0 False 2 9 Grunwald 49 +408707.0 False 3 1 Grunwald 13 +656936.0 False 2 4 Wilda 29 +275000.0 True 2 1 Sołacz 50 +245000.0 True 2 0 Piątkowo 40 +305000.0 True 2 0 Łazarz 60 +861000.0 True 4 1 Łazarz 23 +260000.0 True 2 0 MDM 80 +319000.0 True 2 1 Grunwald 52 +279000.0 True 2 2 Rataje 44 +369000.0 True 2 2 Centrum 51 +329000.0 True 2 3 Nowe 50 +499000.0 True 3 1 Malta 50 +439000.0 True 3 3 Piątkowo 70 +220000.0 True 2 1 Jeżyce 60 +411000.0 True 3 2 Winogrady 50 +305000.0 True 2 1 Winiary 48 +850000.0 True 10 0 Wola 400 +235000.0 True 2 1 Nowe 47 +419000.0 True 2 0 Malta 55 +265000.0 True 3 10 Nowe 48 +385000.0 True 2 2 Piątkowo 50 +714000.0 True 3 2 Malta 84 +289000.0 True 2 3 Winogrady 10 +459000.0 True 2 3 Jeżyce 32 +420000.0 True 3 1 Jeżyce 60 +375000.0 True 3 3 Wilda 30 +310000.0 True 4 1 Winogrady 90 +306000.0 True 3 4 Grunwald 20 +399000.0 True 3 0 Pokrzywno 90 +355000.0 True 2 0 Podolany 93 +415000.0 True 4 3 Jeżyce 78 +350000.0 True 2 3 Grunwald 50 +350000.0 True 3 0 Naramowickie 10 +490000.0 True 4 1 Naramowice 99 +289000.0 True 2 2 Jeżyce 54 +360000.0 True 3 1 Sołacz 65 +329000.0 True 2 3 Nowe 90 +294990.0 True 2 4 Jeżyce 6 +314990.0 True 2 4 Jeżyce 82 +330000.0 True 2 3 Chwaliszewo 56 +395000.0 True 3 3 Wilda 75 +245000.0 True 2 2 Dębiec 45 +229000.0 True 2 0 Bonin 80 +247000.0 True 3 3 Grunwald 49 +1650000.0 True 4 0 Jeżyce 158 +400000.0 False 4 0 Grunwald 81 +400000.0 False 4 0 Grunwald 60 +239000.0 True 2 0 Rataje 36 +350000.0 True 2 11 Rataje 45 +270000.0 True 3 4 Rataje 20 +265999.0 True 2 3 Grunwald 50 +303867.0 False 2 2 Wilda 7 +375000.0 True 3 3 Stare 50 +299000.0 True 3 0 Podolany 94 +385000.0 True 2 1 Rataje 48 +249000.0 True 2 2 Grunwald 46 +288000.0 True 3 4 Winogrady 30 +332000.0 True 3 8 Rataje 63 +347193.0 False 3 11 Grunwald 7 +225000.0 True 2 2 Wilda 50 +255000.0 True 3 0 Grunwald 53 +419000.0 True 3 4 Dębiec 60 +330000.0 True 3 3 Winiary 53 +249441.0 False 2 2 Winogrady 51 +304133.0 False 3 3 Winogrady 27 +250100.0 False 2 1 Winogrady 41 +238948.0 False 2 4 Winogrady 54 +345800.0 False 3 1 Jeżyce 53 +264256.0 False 2 2 Jeżyce 29 +310000.0 True 2 2 Stare 74 +295000.0 True 3 4 Grunwald 45 +399000.0 True 4 3 Stare 40 +489000.0 True 4 2 Centrum 120 +384000.0 True 4 0 Grunwald 42 +290000.0 True 3 2 Winogrady 60 +270000.0 True 2 6 Piątkowo 46 +345000.0 False 5 1 Komorniki 97 +368000.0 True 2 1 Grunwald 33 +339000.0 True 2 1 Grunwald 66 +260000.0 True 2 5 Nowe 42 +780000.0 True 5 0 Winogrady 54 +398000.0 True 3 1 Jeżyce 72 +720000.0 True 3 1 Grunwald 60 +280000.0 True 2 4 Łazarz 20 +495000.0 False 4 0 Nowe 7 +384000.0 True 3 2 Piątkowo 69 +219900.0 True 2 3 Wilda 45 +249000.0 True 2 1 Wilda 65 +325000.0 True 2 3 Stare 50 +265000.0 True 2 11 Rataje 80 +384000.0 True 3 2 Piątkowo 90 +290000.0 True 3 2 Winogrady 47 +209000.0 True 2 0 Dębiec 37 +289000.0 True 3 0 Rataje 50 +310000.0 True 3 4 Rataje 62 +699000.0 True 2 1 Grunwald 68 +195000.0 True 2 1 Grunwald 31 +339000.0 True 3 1 Nowe 88 +359000.0 True 3 4 Nowe 10 +299000.0 True 2 0 Jeżyce 60 +460000.0 True 4 2 Sołacz 68 +355647.0 False 3 3 Dolna 89 +363000.0 False 3 0 Junikowo 45 +343400.0 True 2 1 Wilda 68 +259000.0 True 2 2 Nowe 40 +525000.0 True 4 3 Nowe 88 +289000.0 True 2 7 Winiary 49 +445000.0 False 5 0 Plewiska 104 +305000.0 True 3 4 Rataje 63 +309000.0 True 3 9 Rataje 64 +355000.0 False 3 0 Junikowo 64 +429000.0 True 3 0 Jeżyce 30 +487000.0 True 3 0 Stare 83 +350000.0 True 4 1 Stare 50 +270000.0 True 2 2 Sołacz 49 +439000.0 True 2 3 Jeżyce 60 +350000.0 False 4 0 Plewiska 80 +479000.0 True 3 3 Grunwald 23 +695000.0 True 3 2 Jeżyce 71 +249000.0 True 2 1 Grunwald 56 +295000.0 True 2 0 Winogrady 36 +240000.0 True 2 5 Rataje 43 +847000.0 True 4 2 Piątkowo 113 +298000.0 True 3 1 Rataje 30 +406550.0 True 3 1 Jeżyce 23 +349000.0 True 2 4 Jeżyce 89 +299000.0 True 2 2 Grunwald 35 +529900.0 True 4 1 Podolany 103 +779000.0 True 3 2 Stary 113 +297600.0 False 2 3 Winogrady 47 +336474.0 False 3 4 Winogrady 27 +285678.0 False 2 2 Winogrady 42 +290970.0 False 2 0 Winogrady 60 +295120.0 False 2 1 Winogrady 60 +285200.0 False 2 1 Winogrady 46 +291838.0 False 2 1 Starołęka 55 +348750.0 False 2 3 Centrum 47 +349668.0 False 2 1 Garbary 44 +244071.0 False 2 2 Starołęka 52 +311515.0 False 2 4 Grunwald 49 +296810.0 False 2 2 Grunwald 30 +321656.0 False 2 1 Winogrady 88 +286445.0 False 2 2 Winogrady 49 +299513.0 False 2 1 Starołęka 85 +349785.0 False 3 1 Malta 52 +442827.0 False 4 2 Starołęka 14 +302176.0 False 2 2 Malta 45 +285383.0 False 2 4 Winogrady 37 +377200.0 False 3 3 Grunwald 66 +327584.0 False 3 3 Grunwald 21 +308039.0 False 2 0 Winogrady 21 +377917.0 False 3 2 Grunwald 44 +277039.0 False 2 1 Malta 66 +285678.0 False 2 2 Winogrady 42 +186600.0 False 2 2 Starołęka 62 +156085.0 False 2 2 Głuszyna 54 +225316.0 False 2 0 Starołęka 33 +303287.0 False 2 3 Grunwald 13 +280860.0 False 2 1 Winogrady 30 +272800.0 False 2 5 Winogrady 44 +357000.0 True 3 3 Rataje 90 +210000.0 True 2 2 Grunwald 40 +399000.0 True 3 5 Grunwald 81 +363000.0 True 3 2 Grunwald 77 +400000.0 True 3 3 Stare 70 +420000.0 True 3 1 Podolany 85 +375000.0 False 5 0 Plewiska 96 +465000.0 False 5 0 Plewiska 117 +259000.0 True 3 4 Piątkowo 60 +229000.0 True 4 3 Wilda 54 +330000.0 True 2 3 Wilda 53 +389000.0 True 3 3 Stare 49 +275000.0 True 2 9 Winogrady 10 +289000.0 True 2 2 Naramowice 50 +279000.0 True 3 4 Stare 50 +139000.0 True 3 1 Nowe 56 +275000.0 True 2 4 Jeżyce 90 +229000.0 True 2 4 Grunwald 30 +378000.0 True 2 4 Wilda 52 +299000.0 True 2 2 Grunwald 35 +299000.0 True 2 4 Centrum 50 +695000.0 True 5 0 Jeżyce 150 +323000.0 True 2 0 Jeżyce 54 +235000.0 True 2 12 Stare 38 +335000.0 True 3 1 Grunwald 70 +416000.0 True 3 3 Nowe 64 +275000.0 True 2 9 Stare 10 +315000.0 True 3 4 Winogrady 54 +275000.0 True 2 1 Sołacz 39 +249000.0 True 2 4 Grunwald 43 +268000.0 True 3 4 Jeżyce 43 +179000.0 True 3 2 Wilda 35 +429000.0 True 3 4 Świerczewo 60 +399000.0 True 3 1 Bonin 67 +290000.0 True 3 2 Stare 48 +799000.0 True 4 2 Stare 114 +375000.0 False 4 0 Plewiska 96 +354000.0 True 3 1 Piątkowo 60 +185000.0 True 2 8 Dębiec 50 +385000.0 True 4 3 Stare 80 +549000.0 True 4 5 Jeżyce 98 +326000.0 True 2 1 Winogrady 39 +263000.0 True 2 10 Śródka 48 +643000.0 True 4 0 Naramowice 60 +379000.0 True 3 1 Naramowice 20 +219000.0 True 2 1 Łazarz 35 +299000.0 True 2 0 Dębiec 52 +365000.0 True 2 5 Wilda 30 +410000.0 True 2 9 Rataje 50 +385000.0 True 2 1 Nowe 48 +310000.0 True 3 0 Grunwald 60 +375000.0 True 3 4 Wilda 40 +389000.0 True 3 0 Wilda 69 +269965.0 False 3 0 Nowe 81 +233000.0 True 2 3 Grunwald 70 +240000.0 True 2 3 Grunwald 80 +319000.0 True 3 4 Rataje 63 +315000.0 True 2 4 Jeżyce 25 +351648.0 True 3 4 Jeżyce 28 +305000.0 True 2 4 Jeżyce 55 +379000.0 True 3 0 Naramowice 64 +379000.0 True 3 0 Piątkowo 64 +250000.0 True 3 3 Rataje 53 +214000.0 True 2 3 Wilda 43 +390000.0 True 2 0 Nowe 61 +185000.0 True 2 11 Wilda 38 +435000.0 True 3 1 Junikowo 70 +395000.0 True 2 0 Grunwald 52 +390000.0 True 3 2 Podolany 68 +275000.0 True 2 5 Naramowice 45 +369000.0 True 3 0 Piątkowo 64 +295000.0 True 2 0 Stare 44 +275000.0 True 2 13 Rataje 80 +245000.0 True 2 12 Rataje 50 +429000.0 True 4 1 Rataje 70 +339000.0 True 3 1 Rataje 67 +290000.0 True 3 3 Rataje 50 +235000.0 True 2 0 Wilda 55 +449000.0 True 4 2 Grunwald 90 +695000.0 True 3 2 Jeżyce 25 +555000.0 True 4 0 Stare 20 +182000.0 True 2 2 Stare 70 +380000.0 True 4 6 Stare 90 +450000.0 True 6 4 Wilda 90 +283500.0 True 2 0 Stare 50 +350550.0 True 3 4 Stare 50 +395000.0 True 3 0 Grunwald 70 +425000.0 True 4 6 Rataje 85 +590000.0 True 4 3 Rataje 90 +349000.0 True 4 0 Rataje 84 +695000.0 True 3 2 Jeżyce 25 +329000.0 True 3 3 Piątkowo 60 +265000.0 True 3 10 Śródka 49 +229000.0 True 2 1 Stare 37 +399000.0 True 3 5 Łazarz 68 +249000.0 True 2 1 Nowe 49 +305000.0 True 2 1 Winiary 48 +326000.0 True 2 1 Sołacz 39 +415000.0 True 4 7 Piątkowo 63 +295000.0 True 2 2 Grunwald 50 +519000.0 True 4 3 Wilda 104 +105000.0 True 2 3 Nowe 50 +375000.0 True 3 0 Naramowice 68 +330000.0 True 3 4 Rataje 59 +487000.0 True 3 0 Naramowice 83 +899000.0 True 4 0 Stare 100 +218000.0 True 2 7 Winogrady 38 +395000.0 True 3 1 Grunwald 100 +345000.0 True 3 1 Winogrady 17 +489000.0 True 2 5 Centrum 53 +978000.0 True 4 5 Centrum 106 +339000.0 True 3 1 Żegrze 88 +350000.0 True 3 0 Winogrady 10 +259000.0 True 2 3 Żegrze 49 +265000.0 True 2 0 Dębiec 50 +569000.0 True 4 0 Wilda 50 +275000.0 True 2 1 Sołacz 50 +382280.0 True 3 3 Centrum 80 +259000.0 True 2 3 Łazarz 47 +425000.0 True 4 6 Rataje 85 +429000.0 True 3 4 Rataje 79 +382280.0 True 3 3 Stare 30 +325000.0 True 2 3 Stare 56 +289000.0 True 2 2 Jeżyce 42 +779000.0 True 3 2 Centrum 114 +445000.0 True 2 3 Jeżyce 60 +390000.0 True 3 3 Wilda 50 +339000.0 True 3 10 Rataje 10 +235000.0 True 2 0 Śródka 47 +655000.0 True 3 4 Stare 60 +655000.0 True 2 2 Jeżyce 10 +283340.0 True 2 0 Stare 70 +640000.0 True 3 2 Stare 47 +370000.0 True 3 4 Stare 84 +425000.0 True 2 9 Nowe 50 +282880.0 True 2 3 Stare 20 +561000.0 True 2 4 Stare 50 +360000.0 True 4 0 Grunwald 66 +429000.0 True 3 4 Wilda 47 +359400.0 True 3 1 Stare 72 +1115000.0 True 2 2 Grunwald 7 +497400.0 True 3 0 Wilda 48 +604395.0 True 5 1 Wilda 31 +1199000.0 True 8 3 Stare 282 +405000.0 True 3 1 Stare 80 +330615.0 True 2 2 Stare 79 +255000.0 True 2 3 Wilda 52 +300000.0 True 2 1 Stare 23 +850000.0 True 2 7 Stare 69 +480000.0 True 3 0 Stare 30 +350000.0 True 2 0 Stare 50 +1140000.0 True 6 0 Stare 40 +290970.0 True 2 0 Stare 60 +800000.0 True 4 3 Stare 103 +345000.0 True 2 3 Jeżyce 50 +514000.0 True 4 1 Jeżyce 120 +451000.0 True 3 2 Wilda 30 +659500.0 True 4 0 Grunwald 44 +558000.0 True 5 1 Wilda 2 +649000.0 True 4 0 Winogrady 80 +319000.0 True 2 4 Grunwald 54 +290000.0 True 2 4 Wilda 35 +325000.0 True 3 14 Rataje 80 +249000.0 True 2 5 Centrum 36 +224000.0 True 2 0 Łazarz 39 +295000.0 True 3 0 Grunwald 53 +379000.0 True 3 0 Rataje 30 +305000.0 True 2 1 Winogrady 48 +269000.0 True 2 1 Centrum 30 +240000.0 True 2 16 Rataje 36 +269000.0 True 2 2 Dolna 38 +448995.0 True 2 3 Jeżyce 66 +350000.0 True 2 3 Jeżyce 70 +469000.0 False 4 0 Plewiska 30 +369000.0 True 2 2 Jeżyce 90 +350000.0 True 2 0 Naramowice 60 +330000.0 True 3 4 Rataje 59 +315000.0 True 2 1 Grunwald 60 +349000.0 True 2 3 Piątkowo 60 +309000.0 True 2 0 Grunwald 55 +375000.0 True 3 1 Nowe 62 +280000.0 True 3 9 Jeżyce 49 +570000.0 True 3 5 Grunwald 60 +439000.0 True 4 2 Łazarz 40 +449000.0 True 4 1 Górczyn 90 +550000.0 True 4 2 Grunwald 107 +249000.0 True 2 5 Garbary 20 +519000.0 True 3 0 Nowe 99 +548000.0 True 3 1 Grunwald 84 +299000.0 True 3 2 Grunwald 48 +720000.0 True 4 7 Grunwald 91 +368000.0 True 2 2 Wilda 67 +325000.0 True 3 0 Grunwald 64 +499000.0 True 4 1 Naramowice 96 +269000.0 True 3 4 Rataje 48 +229000.0 True 2 1 Stare 40 +319000.0 True 2 2 Jeżyce 56 +200000.0 True 2 2 Dębiec 40 +240000.0 True 3 4 Dębiec 44 +235000.0 True 2 0 Nowe 47 +240000.0 True 3 4 Dębiec 44 +240000.0 True 3 4 Dębiec 44 +235000.0 True 2 0 Nowe 47 +745000.0 True 6 2 Grunwald 149 +399900.0 True 4 2 Nowe 66 +480000.0 True 3 1 Grunwald 40 +268000.0 True 3 4 Jeżyce 50 +308000.0 True 3 0 Piątkowo 63 +270000.0 True 3 4 Rataje 48 +250000.0 True 2 6 Sołacz 71 +349000.0 True 3 3 Rataje 63 +229000.0 True 2 12 Winogrady 10 +299000.0 True 3 2 Dębiec 70 +329000.0 True 3 3 Piątkowo 60 +289000.0 True 4 4 Winogrady 48 +590000.0 True 7 1 Smochowice 150 +479000.0 True 5 2 Centrum 142 +318400.0 True 3 1 Jeżyce 48 +500203.0 True 4 10 Grunwald 84 +339957.0 True 4 1 Stare 58 +329538.0 True 3 4 Jeżyce 50 +244969.0 True 2 0 Stare 42 +296277.0 True 3 0 Stare 49 +389610.0 True 4 4 Jeżyce 60 +337303.0 True 4 2 Stare 57 +245876.0 True 2 1 Jeżyce 38 +342900.0 True 3 3 Stare 57 +324608.0 True 3 2 Jeżyce 51 +277823.0 True 2 4 Jeżyce 50 +368569.0 True 3 4 Jeżyce 68 +295362.0 True 3 5 Stare 48 +286858.0 True 2 7 Winogrady 49 +292101.0 True 2 1 Grunwald 51 +279554.0 True 2 4 Jeżyce 43 +266320.0 True 2 4 Jeżyce 41 +327584.0 True 3 6 Grunwald 56 +339201.0 True 3 3 Jeżyce 53 +530000.0 True 2 5 Piątkowo 10 +269000.0 True 2 0 Grunwald 46 +237000.0 True 2 2 Dębiec 44 +275000.0 True 2 13 Rataje 49 +384000.0 True 3 2 Piątkowo 70 +339000.0 True 3 0 Rataje 47 +348000.0 True 3 9 Rataje 65 +460000.0 True 3 0 Rataje 73 +330000.0 True 3 4 Rataje 59 +350000.0 True 3 1 Rataje 63 +85000.0 True 3 4 Stare 70 +690000.0 True 4 1 Grunwald 60 +380000.0 True 3 4 Naramowice 52 +309978.0 False 2 2 Centrum 16 +1.0 False 5 0 4 126 +355000.0 True 2 0 Podolany 93 +225000.0 True 2 0 Grunwald 17 +259500.0 True 2 0 Grunwald 55 +289000.0 True 2 6 Winogrady 48 +230000.0 True 2 3 Nowe 47 +1000000.0 False 5 0 4 126 +339000.0 True 3 3 Nowe 90 +949000.0 True 3 4 Śródka 98 +520000.0 True 4 1 Wilda 129 +305000.0 True 2 1 Winiary 48 +318000.0 True 2 4 Piątkowo 20 +385000.0 True 2 0 Nowe 48 +860000.0 True 4 0 Centrum 103 +269000.0 True 2 3 Centrum 37 +445000.0 False 5 0 Luboń 104 +299000.0 True 3 10 Grunwald 10 +325000.0 True 3 7 Rataje 90 +305000.0 True 2 1 Winiary 49 +333000.0 True 3 4 Wilda 8 +275000.0 True 2 4 Rataje 63 +375570.0 False 2 4 Centrum 5 +542141.0 False 3 4 Centrum 53 +365546.0 False 2 4 Centrum 82 +698508.0 False 4 4 Centrum 59 +394787.0 False 2 4 Centrum 71 +597184.0 False 3 4 Centrum 61 +354177.0 False 2 3 Centrum 25 +353537.0 False 2 3 Centrum 17 +509468.0 False 3 3 Centrum 53 +652026.0 False 4 3 Centrum 89 +353457.0 False 2 3 Centrum 16 +356818.0 False 2 3 Centrum 58 +558745.0 False 3 3 Centrum 62 +349668.0 False 2 2 Centrum 15 +481903.0 False 3 2 Centrum 53 +389528.0 False 2 2 Centrum 87 +374216.0 False 2 2 Centrum 71 +534523.0 False 3 2 Centrum 62 +377418.0 False 2 1 Centrum 87 +372651.0 False 2 1 Centrum 5 +505032.0 False 3 1 Centrum 62 +469000.0 True 2 1 Winogrady 30 +339000.0 True 3 1 Rataje 88 +349000.0 True 3 1 Śródka 63 +466395.0 False 4 1 Dolna 65 +468406.0 False 4 2 Dolna 64 +275000.0 True 2 0 Łazarz 52 +395000.0 True 2 1 Naramowice 30 +339000.0 True 3 9 Nowe 65 +177000.0 True 2 2 Dębiec 33 +525000.0 True 4 3 Jeżyce 70 +309000.0 True 2 0 Jeżyce 28 +339000.0 True 2 2 Naramowice 49 +325000.0 True 2 3 Stare 60 +380000.0 True 4 4 Winogrady 80 +368110.44 True 3 2 Nowe 31 +324800.0 True 2 1 Nowe 56 +270000.0 True 2 2 Łazarz 100 +169000.0 True 2 1 Łazarz 44 +460000.0 True 3 4 Wilda 69 +199650.0 True 2 5 Nowe 93 +557338.0 True 3 3 Centrum 7 +290970.0 True 2 4 Górczyn 70 +412438.0 True 3 2 Winogrady 11 +360343.59 True 2 0 Centrum 60 +327127.5 True 2 0 Centrum 50 +194500.0 True 2 3 Nowe 90 +495000.0 True 4 0 Jeżyce 10 +293436.0 False 2 11 Grunwald 16 +333232.0 False 3 7 Grunwald 21 +333232.0 False 3 7 Grunwald 21 +296810.0 False 2 2 Grunwald 30 +296810.0 False 2 2 Grunwald 30 +771672.0 False 4 7 Grunwald 68 +339000.0 True 3 7 Jeżyce 50 +319000.0 True 2 4 Grunwald 20 +290000.0 True 2 4 Grunwald 36 +295000.0 True 2 3 Stare 30 +380931.0 False 3 3 Starołęka 82 +300680.0 False 2 2 Starołęka 54 +300680.0 False 2 2 Starołęka 54 +349668.0 False 2 2 Stare 15 +384000.0 True 3 2 Piątkowo 90 +339000.0 True 3 1 Rataje 88 +285678.0 False 2 1 Winogrady 42 +211190.0 False 2 0 Podolany 78 +247705.0 False 2 1 Piątkowo 74 +211190.0 False 2 0 Piątkowo 78 +247705.0 False 2 1 Podolany 74 +449000.0 False 5 0 Szczepankowo 68 +771672.0 False 4 4 Górczyn 66 +442080.0 False 3 1 Starołęka 68 +302887.0 False 2 4 Górczyn 25 +294840.0 False 2 4 Winogrady 50 +282994.0 False 2 0 Starołęka 59 +442080.0 False 3 1 Starołęka 68 +370597.0 False 2 4 Stare 4 +302887.0 False 2 4 Górczyn 25 +294840.0 False 2 4 Winogrady 50 +225228.0 False 2 5 Rataje 91 +282994.0 False 2 0 Starołęka 59 +242731.0 False 2 0 Podolany 74 +522235.0 False 3 2 Stare 62 +370597.0 False 2 4 Stare 4 +674695.0 False 3 4 Stare 59 +349000.0 False 4 0 Szczepankowo 29 +259015.0 False 2 0 Ogrody 53 +411684.0 False 3 3 Winogrady 17 +282944.0 False 2 0 Starołęka 59 +424377.0 False 4 2 Starołęka 14 +277823.0 False 2 2 Podolany 70 +277823.0 False 2 2 Podolany 70 +460499.0 False 3 1 Stare 51 +460499.0 False 3 1 Stare 51 +557338.0 False 3 3 Stare 4 +481903.0 False 3 2 Centrum 53 +361998.0 False 3 15 Grunwald 20 +310584.0 False 2 1 Nowe 26 +557338.0 False 3 3 Stare 4 +557338.0 False 3 3 Stare 4 +350506.0 False 3 11 Grunwald 20 +368110.0 False 3 2 Nowe 31 +557338.0 False 3 3 Stare 4 +342021.0 False 2 4 Nowe 93 +353379.0 False 3 12 Grunwald 20 +429699.0 False 3 15 Grunwald 62 +350506.0 False 3 11 Grunwald 20 +341682.0 False 2 10 Grunwald 7 +361998.0 False 3 15 Grunwald 20 +341682.0 False 2 10 Grunwald 7 +481903.0 False 3 2 Centrum 53 +310584.0 False 2 1 Nowe 26 +368110.0 False 3 2 Nowe 31 +162525.0 False 2 0 Głuszyna 55 +311488.0 False 3 2 Jeżyce 24 +336804.0 False 2 3 Jeżyce 4 +382074.0 False 3 2 Jeżyce 89 +195000.0 True 2 1 Łazarz 31 +385000.0 True 3 0 Grunwald 66 +495000.0 True 4 0 Jeżyce 86 +399000.0 True 2 1 Jeżyce 28 +369000.0 True 2 5 Winogrady 62 +172000.0 True 2 0 Starołęka 32 +599000.0 True 3 3 Grunwald 60 +620000.0 True 3 2 Naramowice 98 +495000.0 True 5 1 Naramowice 98 +460000.0 True 3 4 Wilda 69 +270000.0 True 2 0 Nowe 41 +263581.0 True 2 5 Stare 43 +279554.0 True 2 4 Jeżyce 43 +295000.0 True 2 1 Jeżyce 30 +779000.0 True 3 2 Stare 113 +305000.0 True 2 1 Sołacz 48 +385000.0 True 3 5 Centrum 50 +1040000.0 True 2 10 Centrum 79 +570000.0 True 4 0 Centrum 137 +468000.0 True 2 3 Grunwald 60 +1200000.0 True 4 2 Jeżyce 188 +233000.0 True 2 3 Grunwald 38 +315000.0 True 2 7 Rataje 47 +359000.0 True 3 2 Podolany 56 +269000.0 True 2 1 Centrum 34 +240000.0 True 2 3 Grunwald 38 +442150.0 True 2 3 Stare 75 +328000.0 True 3 0 Winogrady 48 +399700.0 True 3 1 Puszczykowo 74 +499000.0 True 3 3 Centrum 109 +529000.0 True 4 0 Piątkowo 115 +565000.0 True 3 1 Stary 95 +499000.0 True 3 1 Suchy 95 +517000.0 True 4 1 Centrum 138 +539000.0 True 4 2 Jeżyce 110 +330000.0 True 2 4 Wilda 50 +349000.0 True 3 3 Piątkowo 60 +359000.0 True 3 2 Podolany 10 +339000.0 True 4 5 Grunwald 74 +219000.0 True 2 2 Grunwald 38 +279000.0 True 2 2 Wilda 30 +489000.0 True 2 8 Centrum 4 +409000.0 True 3 1 Nowe 90 +245000.0 True 2 0 Piątkowo 40 +315000.0 True 2 7 Rataje 47 +395000.0 True 4 0 Grunwald 60 +239000.0 True 2 0 Rataje 48 +280250.0 True 2 0 Górczyn 50 +316355.0 True 2 4 Centrum 67 +276610.0 True 2 4 Centrum 80 +442002.0 True 2 3 Centrum 73 +316498.0 True 2 2 Centrum 77 +300160.0 True 2 3 Winogrady 90 +347090.0 True 3 1 Winogrady 90 +286091.0 True 2 3 Winogrady 49 +442150.0 True 2 2 Centrum 75 +270000.0 True 3 1 Starołęka 30 +319900.0 True 2 1 Grunwald 52 +695000.0 True 3 2 Jeżyce 71 +250000.0 True 2 6 Grunwald 31 +350000.0 True 3 7 Piątkowo 63 +475000.0 True 3 1 Naramowice 68 +535000.0 True 2 2 Stare 55 +425000.0 True 3 1 Piątkowo 74 +349000.0 True 3 3 Rataje 63 +495000.0 True 3 1 Łazarz 64 +495000.0 True 4 1 Naramowice 98 +499000.0 True 5 0 Grunwald 130 +659200.0 True 4 3 Łazarz 103 +510000.0 True 5 1 Naramowice 98 +360000.0 True 2 5 Grunwald 41 +249000.0 True 2 5 Centrum 36 +1950000.0 True 3 5 Centrum 143 +313000.0 True 2 4 Piątkowo 49 +250000.0 True 2 3 Wilda 39 +430000.0 True 2 2 Wilda 46 +239000.0 True 2 8 Winogrady 10 +312259.0 True 2 6 Winogrady 51 +329539.0 True 3 4 Jeżyce 50 +242134.0 True 2 0 Jeżyce 38 +246553.0 True 2 1 Stare 40 +345241.0 True 4 3 Stare 58 +242730.0 True 2 0 Jeżyce 50 +295000.0 True 2 1 Nowe 40 +555000.0 True 4 0 Stare 123 +350000.0 True 3 0 Stare 72 +310584.0 False 2 1 Nowe 26 +162525.0 False 2 0 Głuszyna 55 +289170.0 False 2 0 Winogrady 90 +332940.0 False 2 2 Winogrady 70 +334610.0 False 2 1 Winogrady 9 +298980.0 False 2 5 Winogrady 30 +318645.0 False 2 2 Winogrady 23 +228144.0 False 3 2 Głuszyna 56 +557338.0 False 3 3 Stare 4 +557338.0 False 3 3 Stare 4 +533745.0 False 5 2 Starołęka 4 +321285.0 False 2 4 Winogrady 30 +269000.0 True 2 3 Jeżyce 81 +279000.0 True 2 5 Jeżyce 53 +449000.0 False 5 0 Szczepankowo 68 +460499.0 False 3 1 Stare 51 +557338.0 False 3 3 Stare 4 +455348.0 False 3 0 Stare 61 +460499.0 False 3 1 Stare 51 +368712.0 False 2 5 Stare 90 +302887.0 False 2 4 Górczyn 25 +282994.0 False 2 0 Starołęka 59 +522235.0 False 3 2 Stare 62 +370597.0 False 2 4 Stare 4 +674695.0 False 3 4 Stare 59 +442080.0 False 3 1 Starołęka 68 +771672.0 False 4 4 Górczyn 66 +302887.0 False 2 4 Górczyn 25 +225228.0 False 2 5 Rataje 91 +284618.0 False 2 3 Nowe 55 +297420.0 False 2 3 Grunwald 24 +370597.0 False 2 4 Stare 4 +242731.0 False 2 0 Podolany 74 +368568.0 False 3 4 Podolany 38 +522235.0 False 3 2 Stare 62 +442080.0 False 3 1 Starołęka 68 +305676.0 False 2 5 Winogrady 52 +460499.0 False 3 1 Stare 51 +429699.0 False 3 15 Grunwald 62 +341682.0 False 2 10 Grunwald 7 +481903.0 False 3 2 Centrum 53 +368110.0 False 3 2 Nowe 31 +332940.0 False 2 2 Winogrady 70 +162525.0 False 2 0 Głuszyna 55 +318645.0 False 2 2 Winogrady 23 +228144.0 False 3 2 Głuszyna 56 +318645.0 False 2 2 Winogrady 23 +325000.0 True 3 1 Nowe 90 +319000.0 True 2 1 Jeżyce 67 +339000.0 True 3 9 Rataje 65 +310000.0 True 2 3 Nowe 38 +756000.0 True 4 2 Grunwald 100 +265000.0 True 2 10 Śródka 49 +350000.0 True 2 0 Naramowice 49 +244970.0 True 2 0 Stare 42 +238948.0 True 2 4 Stare 39 +377652.0 True 4 6 Jeżyce 57 +324609.0 True 3 2 Jeżyce 51 +339000.0 True 3 9 Nowe 65 +435000.0 True 3 1 Grunwald 10 +395000.0 True 4 0 Grunwald 60 +310000.0 True 2 2 Jeżyce 55 +235000.0 True 2 1 Starołęka 47 +210000.0 True 2 2 Grunwald 40 +299000.0 True 2 0 Dębiec 52 +305000.0 True 3 10 Piątkowo 40 +180000.0 True 2 6 Dębiec 50 +245488.0 True 2 0 Jeżyce 37 +242407.0 True 2 0 Jeżyce 36 +347095.0 True 3 1 Winogrady 57 +285383.0 True 2 4 Winogrady 48 +289172.0 True 2 0 Stare 46 +301620.0 True 2 5 Stare 46 +247706.0 True 2 1 Jeżyce 50 +278048.0 True 2 3 Jeżyce 50 +333693.0 True 3 1 Jeżyce 68 +235000.0 True 2 1 Głuszyna 47 +369000.0 True 2 3 Wilda 46 +350000.0 True 2 4 Jeżyce 56 +319000.0 True 2 4 Grunwald 47 +279000.0 True 2 1 Podolany 63 +290000.0 True 3 2 Winogrady 48 +235000.0 True 2 1 Nowe 47 +446000.0 True 2 1 Rataje 52 +225288.0 False 2 1 Rataje 91 +287882.0 False 2 1 Starołęka 85 +349000.0 False 4 0 Szczepankowo 29 +285678.0 False 2 1 Winogrady 42 +353275.0 False 2 4 Grunwald 49 +297421.0 False 2 3 Grunwald 24 +156085.0 False 2 4 Nowe 54 +286445.0 True 2 2 Winogrady 55 +285678.0 True 2 1 Winogrady 42 +302985.59 True 2 4 Grunwald 18 +302038.41 True 3 1 Grunwald 2 +495782.25 True 4 7 Grunwald 99 +405103.97 True 4 1 Grunwald 34 +426416.78 True 4 6 Grunwald 20 +319047.97 True 3 3 Grunwald 21 +380480.0 True 3 4 Grunwald 60 +244071.0 False 2 1 Nowe 93 +156085.0 False 2 4 Nowe 54 +404000.0 True 3 2 Rataje 70 +315000.0 True 3 11 Stare 50 +345000.0 True 2 3 Jeżyce 50 +321904.0 False 2 4 Winogrady 92 +270000.0 True 2 0 Zawady 41 +230000.0 True 2 6 Dębiec 45 +349000.0 True 4 3 Centrum 20 +277000.0 True 3 0 Centrum 40 +338700.0 True 3 2 Jeżyce 45 +619000.0 True 3 2 Winogrady 100 +486243.0 True 2 1 Łazarz 60 +413044.03 True 3 12 Grunwald 62 +324387.0 True 2 9 Grunwald 49 +338111.0 True 2 15 Grunwald 62 +293436.0 True 2 1 Grunwald 16 +333212.88 True 2 7 Grunwald 21 +267702.41 True 2 3 Grunwald 22 +903965.44 True 4 0 Centrum 80 +1366410.0 True 4 0 Centrum 71 +1155974.38 True 4 1 Centrum 28 +285383.0 True 2 4 Winogrady 37 +260000.0 True 2 0 Stare 79 +270000.0 True 2 2 Jeżyce 49 +1140000.0 True 6 0 Stare 40 +333232.0 False 3 7 Grunwald 21 +297421.0 False 2 3 Grunwald 24 +200460.0 False 2 0 Głuszyna 55 +377418.0 False 2 1 Stare 87 +289800.0 False 2 0 Winogrady 46 +505032.0 False 3 1 Stare 62 +374216.0 False 2 2 Stare 71 +1156054.0 False 4 0 Stare 41 +904041.0 False 3 0 Stare 2 +460849.0 False 3 2 Grunwald 13 +771672.0 False 4 7 Grunwald 68 +296810.0 False 2 2 Grunwald 30 +460499.0 False 3 1 Stare 51 +349668.0 False 2 2 Stare 15 +325206.0 False 2 10 Grunwald 62 +557338.0 False 3 3 Centrum 4 +380931.0 False 3 3 Starołęka 82 +295549.0 False 2 0 Starołęka 59 +302887.0 False 2 4 Górczyn 25 +225228.0 False 2 5 Rataje 91 +302887.0 False 2 4 Górczyn 25 +284618.0 False 2 3 Nowe 55 +297420.0 False 2 3 Grunwald 24 +370597.0 False 2 4 Stare 4 +242731.0 False 2 0 Podolany 74 +522235.0 False 3 2 Stare 62 +368568.0 False 3 4 Podolany 38 +442080.0 False 3 1 Starołęka 68 +305676.0 False 2 5 Winogrady 52 +294840.0 False 2 4 Winogrady 50 +460499.0 False 3 1 Stare 51 +299999.0 True 2 0 Wilda 51 +325000.0 True 3 7 Rataje 64 +395000.0 True 2 0 Grunwald 52 +315000.0 True 2 2 Zawady 52 +299000.0 True 3 2 Winogrady 48 +339000.0 True 3 1 Rataje 67 +290000.0 True 2 4 Grunwald 53 +369000.0 True 3 1 Piątkowo 65 +339000.0 True 3 0 Rataje 47 +265000.0 True 3 1 Winogrady 53 +315000.0 True 3 2 Winogrady 53 +345000.0 True 2 3 Jeżyce 50 +270000.0 True 3 4 Rataje 48 +375000.0 True 3 1 Nowe 62 +1050000.0 True 5 2 Centrum 161 +515000.0 True 3 0 Rataje 69 +428000.0 True 3 3 Centrum 43 +288000.0 True 3 4 Winogrady 47 +240000.0 True 2 2 Dębiec 48 +530000.0 True 2 5 Piątkowo 66 +510000.0 True 5 1 Naramowice 98 +360000.0 True 3 0 Wilda 112 +360000.0 True 4 4 Jeżyce 60 +330000.0 True 2 1 Jeżyce 53 +365000.0 True 2 2 Rataje 45 +460000.0 True 3 0 Rataje 73 +375000.0 True 3 3 Wilda 49 +380000.0 True 4 0 Piątkowo 74 +335000.0 True 3 9 Nowe 65 +379000.0 True 3 4 Rataje 63 +369000.0 True 2 3 Grunwald 64 +275000.0 True 2 2 Naramowice 45 +259000.0 True 2 2 Nowe 42 +299000.0 True 2 4 Nowe 47 +275000.0 True 2 0 Dębiec 50 +950000.0 True 3 4 Nowe 99 +315000.0 True 3 0 Piątkowo 63 +270000.0 True 2 10 Nowe 48 +430000.0 True 3 2 Rataje 64 +413500.0 True 5 4 Winogrady 64 +359000.0 True 3 2 Rataje 65 +410000.0 True 2 5 Rataje 53 +365000.0 True 4 3 Grunwald 68 +295555.0 True 2 1 Jeżyce 45 +224000.0 True 2 0 Górczyn 38 +315000.0 True 2 2 Winogrady 38 +265000.0 True 2 1 Wilda 44 +299000.0 True 2 3 Grunwald 44 +379000.0 True 3 1 Piątkowo 78 +249000.0 True 2 4 Grunwald 43 +295000.0 True 3 0 Grunwald 53 +510000.0 True 3 6 Grunwald 50 +350000.0 True 2 1 Rataje 54 +450000.0 True 4 1 Grunwald 101 +365000.0 True 2 1 Stare 50 +430000.0 True 2 1 Centrum 72 +385560.0 True 2 3 Piątkowo 57 +299000.0 True 2 1 Junikowo 33 +370000.0 True 4 4 Piątkowo 76 +336000.0 True 2 1 Naramowice 46 +369000.0 True 2 3 Jeżyce 55 +595000.0 True 3 0 Naramowice 94 +429000.0 True 3 4 Nowe 79 +489000.0 True 3 0 Jeżyce 65 +295000.0 True 3 2 Grunwald 49 +499000.0 True 4 2 Wilda 120 +305000.0 True 3 3 Winogrady 48 +325000.0 True 3 4 Jeżyce 64 +299817.0 True 2 3 Górczyn 59 +495000.0 True 4 1 Naramowice 98 +370000.0 True 2 13 Rataje 48 +487000.0 True 3 0 Naramowice 72 +299000.0 True 2 5 Grunwald 59 +269000.0 True 3 10 Grunwald 50 +380000.0 True 4 6 Piątkowo 73 +273875.0 True 2 1 Górczyn 13 +275000.0 True 2 13 Rataje 49 +1000000.0 True 5 1 Jeżyce 128 +379999.0 True 2 5 Jeżyce 61 +315000.0 True 3 4 Winogrady 53 +275000.0 True 2 9 Rataje 38 +259000.0 True 2 2 Jeżyce 48 +295000.0 True 2 0 Naramowice 36 +3200.0 True 4 0 Centrum 75 +260000.0 True 2 0 Rataje 46 +1612000.0 True 7 5 Jeżyce 166 +220000.0 True 2 3 Jeżyce 37 +549000.0 True 3 2 Jeżyce 106 +549000.0 True 3 2 Jeżyce 106 +330000.0 True 3 0 Bonin 56 +399000.0 True 2 0 Podolany 63 +220000.0 True 2 4 Grunwald 43 +290000.0 True 2 4 Winogrady 38 +270000.0 True 3 4 Rataje 48 +245000.0 True 2 3 Grunwald 30 +305000.0 True 2 1 Winiary 48 +235000.0 True 2 0 Łazarz 52 +289000.0 True 2 6 Winogrady 48 +495000.0 True 4 1 Naramowice 98 +270000.0 True 3 4 Rataje 48 +510000.0 True 5 1 Naramowice 98 +390000.0 True 3 3 Stare 48 +269000.0 True 2 0 Grunwald 46 +480000.0 True 2 2 Garbary 56 +320000.0 True 2 2 Piątkowo 48 +240000.0 True 2 16 Rataje 36 +355000.0 True 3 3 Łazarz 62 +240000.0 True 2 8 Dębiec 37 +565964.0 True 2 5 Centrum 49 +289000.0 True 2 2 Jeżyce 42 +350000.0 True 2 3 Rataje 50 +550000.0 True 3 1 Grunwald 73 +345000.0 True 3 1 Rataje 78 +259000.0 True 2 5 Grunwald 46 +491520.0 True 4 1 Górczyn 92 +305739.0 True 2 2 Górczyn 53 +269000.0 True 2 2 Dębiec 48 +295000.0 True 2 0 Centrum 44 +384000.0 True 3 2 Piątkowo 69 +375000.0 True 3 2 Rataje 79 +355000.0 True 3 2 Piątkowo 66 +420000.0 True 2 3 Naramowice 59 +237000.0 True 2 2 Dębiec 44 +330000.0 True 3 4 Rataje 59 +405000.0 True 3 1 Antoninek 68 +249900.0 True 2 9 Winogrady 38 +315000.0 True 2 7 Rataje 47 +510000.0 True 3 6 Grunwald 50 +349000.0 True 3 1 Winogrady 51 +339000.0 True 3 1 Rataje 67 +287000.0 True 2 4 Wilda 37 +585000.0 True 3 4 Jeżyce 59 +335000.0 True 3 7 Rataje 63 +289000.0 True 3 4 Winogrady 47 +263000.0 True 3 4 Grunwald 48 +279000.0 True 2 0 Naramowice 43 +292000.0 True 3 2 Winogrady 48 +399000.0 True 2 3 Centrum 60 +320000.0 True 3 0 Rataje 56 +287000.0 True 2 10 Winogrady 46 +350000.0 True 3 6 Jeżyce 64 +999000.0 True 3 4 Nowe 99 +510660.0 True 4 1 Górczyn 11 +363258.0 True 2 1 Górczyn 59 +650000.0 True 4 8 Rataje 100 +245000.0 True 3 0 Grunwald 45 +200000.0 True 3 4 Nowe 44 +237000.0 True 2 10 Górczyn 38 +259000.0 True 2 3 Rataje 49 +310000.0 True 2 2 Zawady 52 +289000.0 True 2 2 Nowe 48 +405000.0 True 4 2 Rataje 71 +747000.0 True 3 7 Rataje 84 +379000.0 True 3 2 Podolany 56 +495000.0 True 5 1 Naramowice 98 +265000.0 True 2 4 Grunwald 43 +289575.0 True 2 0 Jeżyce 43 +495000.0 True 3 0 Centrum 63 +380000.0 True 4 1 Piątkowo 76 +250000.0 True 2 4 Rataje 44 +335000.0 True 3 4 Winogrady 56 +580000.0 True 4 3 Sołacz 96 +549000.0 True 3 2 Jeżyce 106 +200000.0 True 2 0 Rataje 30 +736933.0 True 3 0 Jeżyce 67 +275000.0 True 2 0 Naramowice 50 +290000.0 True 2 2 Dębiec 40 +620000.0 True 3 2 Naramowice 98 +299000.0 True 2 0 Dębiec 48 +275000.0 True 2 1 Sołacz 38 +279000.0 True 2 1 Naramowice 52 +379999.0 True 3 2 Wilda 67 +354454.0 True 2 3 Górczyn 17 +379000.0 True 3 2 Podolany 56 +800000.0 True 3 3 Chwaliszewo 70 +350000.0 True 3 0 Naramowice 59 +420000.0 True 2 5 Rataje 63 +260000.0 True 3 4 Centrum 44 +470000.0 True 3 1 Rataje 70 +360000.0 True 2 0 Winogrady 48 +320000.0 True 2 3 Chwaliszewo 56 +260000.0 True 2 0 Rataje 46 +397000.0 True 3 2 Jeżyce 74 +439000.0 True 3 1 Junikowo 70 +430000.0 True 3 5 Grunwald 60 +349000.0 True 3 2 Górczyn 55 +450000.0 True 3 0 Winogrady 70 +290000.0 True 2 6 Jeżyce 49 +499000.0 True 3 1 Rataje 64 +319000.0 True 3 1 Piątkowo 63 +489780.0 True 4 2 Górczyn 63 +453600.0 True 2 3 Naramowice 56 +525000.0 True 4 3 Jeżyce 104 +950000.0 True 3 4 Nowe 99 +459000.0 True 3 4 Dębiec 60 +370000.0 True 4 11 Rataje 74 +830000.0 True 3 1 Grunwald 91 +385500.0 True 2 6 Dębiec 38 +409000.0 True 3 1 Malta 61 +275000.0 True 3 7 Wilda 53 +300000.0 True 2 4 Winogrady 53 +335400.0 True 2 1 Łazarz 51 +560000.0 True 2 8 Grunwald 55 +855000.0 True 4 5 Jeżyce 96 +399000.0 True 3 1 Winiary 66 +750000.0 True 4 0 Kobylepole 105 +459000.0 True 3 4 Dębiec 60 +275000.0 True 2 0 Naramowice 50 +925000.0 True 5 1 Stare 105 +350000.0 True 3 3 Jeżyce 70 +550000.0 True 2 1 Naramowice 57 +345000.0 True 2 0 Centrum 42 +576520.0 True 2 5 Centrum 50 +285000.0 True 2 4 Naramowice 42 +395000.0 True 3 10 Piątkowo 67 +516000.0 True 3 3 Naramowice 75 +620000.0 True 3 2 Naramowice 98 +240000.0 True 2 3 Grunwald 38 +350000.0 True 2 0 Naramowice 48 +390000.0 True 3 2 Podolany 68 +339000.0 True 3 9 Rataje 65 +659000.0 True 5 0 Podolany 135 +670000.0 True 4 3 Grunwald 81 +390000.0 True 3 2 Podolany 68 +420000.0 True 2 1 Naramowice 62 +288000.0 True 3 4 Winogrady 47 +326000.0 True 2 0 Jeżyce 55 +450000.0 True 3 0 Grunwald 75 +354000.0 True 3 1 Naramowice 60 +279000.0 True 2 0 Piątkowo 48 +449900.0 True 3 0 Naramowice 71 +285000.0 True 2 11 Winogrady 47 +690000.0 True 4 5 Grunwald 107 +380000.0 True 3 0 Centrum 55 +329000.0 True 2 3 Nowe 50 +510000.0 True 5 1 Naramowice 98 +325000.0 True 3 1 Głuszyna 63 +269000.0 True 2 3 Grunwald 47 +215000.0 True 2 0 Wilda 36 +285000.0 True 2 4 Wilda 35 +390000.0 True 4 4 Piątkowo 74 +295000.0 True 2 4 Stare 33 +245000.0 True 2 0 Stare 44 +490000.0 True 4 3 Sołacz 83 +200000.0 True 2 0 Głuszyna 52 +379000.0 True 2 0 Nowe 56 +290000.0 True 2 5 Winogrady 42 +235000.0 True 2 3 Winogrady 38 +750000.0 True 2 9 Centrum 54 +385000.0 True 2 0 Naramowice 50 +489000.0 True 3 3 Grunwald 104 +290000.0 True 3 2 Winogrady 60 +280000.0 True 3 2 Winogrady 47 +280000.0 True 3 2 Winogrady 47 +385000.0 True 2 1 Nowe 48 +378000.0 True 2 1 Grunwald 50 +460499.0 True 3 1 Centrum 51 +481103.0 True 3 1 Centrum 51 +455348.0 True 3 0 Centrum 61 +348750.0 True 2 3 Centrum 50 +194000.0 True 2 2 Nowe 80 +360288.0 True 2 1 Centrum 60 +368712.0 True 2 0 Centrum 90 +244071.0 True 2 2 Nowe 93 +390312.0 True 2 3 Centrum 60 +430000.0 True 2 2 Wilda 38 +225000.0 True 2 3 Grunwald 41 +720000.0 True 4 0 Centrum 163 +475000.0 True 4 1 Grunwald 90 +585000.0 True 3 1 Centrum 16 +319000.0 True 3 4 Winogrady 53 +949000.0 True 3 4 Śródka 98 +233000.0 True 2 3 Grunwald 39 +299000.0 True 2 1 Centrum 11 +211743.0 False 2 4 Starołęka 33 +208382.0 False 2 3 Starołęka 33 +311283.0 False 3 4 Starołęka 3 +413592.0 False 3 2 Starołęka 72 +345000.0 True 4 3 Grunwald 70 +317880.0 False 2 2 Grunwald 98 +317880.0 False 2 2 Grunwald 98 +317880.0 False 2 2 Grunwald 98 +495723.0 False 4 9 Grunwald 99 +317880.0 False 2 2 Grunwald 98 +495723.0 False 3 9 Grunwald 99 +429699.0 False 3 15 Grunwald 62 +470000.0 True 3 2 Sołacz 68 +302887.0 False 2 4 Górczyn 25 +284618.0 False 2 3 Nowe 55 +225228.0 False 2 5 Rataje 91 +282994.0 False 2 0 Starołęka 59 +522235.0 False 3 2 Stare 62 +294840.0 False 2 4 Winogrady 50 +460499.0 False 3 1 Stare 51 +305676.0 False 2 5 Winogrady 52 +442080.0 False 3 1 Starołęka 68 +242731.0 False 2 0 Podolany 74 +370597.0 False 2 4 Stare 4 +297420.0 False 2 3 Grunwald 24 +342021.0 False 2 4 Nowe 93 +429699.0 False 3 15 Grunwald 62 +341682.0 False 2 10 Grunwald 7 +368110.0 False 3 2 Nowe 31 +162525.0 False 2 0 Głuszyna 55 +228144.0 False 3 2 Głuszyna 56 +557338.0 False 3 3 Stare 4 +557338.0 False 3 3 Stare 4 +310584.0 False 2 1 Nowe 26 +210000.0 True 2 2 Zawady 42 +85000.0 True 2 0 Zawady 40 +145000.0 True 2 1 Zawady 61 +339000.0 True 3 9 Nowe 65 +384000.0 True 3 2 Piątkowo 70 +215000.0 True 2 2 Łazarz 34 +295000.0 True 3 0 Grunwald 20 +295000.0 True 3 0 Grunwald 20 +339000.0 True 3 1 Rataje 67 +247000.0 True 3 3 Raszyn 70 +245000.0 True 2 3 Grunwald 30 +245000.0 True 2 2 Dębiec 30 +305000.0 True 3 4 Rataje 53 +308000.0 True 3 0 Piątkowo 63 +247000.0 True 3 3 Grunwald 70 +155481.0 True 2 0 Stare 88 +350000.0 True 2 0 Stare 60 +240000.0 True 2 3 Grunwald 37 +339000.0 True 3 1 Rataje 88 +265000.0 True 2 1 Jeżyce 66 +259999.0 True 2 4 Rataje 44 +225288.0 False 2 1 Rataje 91 +247000.0 True 3 3 Grunwald 70 +315000.0 True 3 4 Winogrady 50 +239000.0 True 2 8 Winogrady 10 +255000.0 True 2 1 Centrum 48 +382000.0 True 3 3 Centrum 50 +240000.0 True 2 3 Dębiec 50 +930000.0 True 2 2 Malta 75 +239000.0 True 2 10 Grunwald 42 +235000.0 True 2 5 Winogrady 38 +399000.0 True 2 2 Stare 62 +920000.0 True 5 2 Grunwald 177 +499000.0 True 3 0 Centrum 12 +492000.0 True 3 4 Centrum 96 +349000.0 True 2 4 Centrum 11 +317880.0 True 2 2 Grunwald 98 +407208.0 True 3 2 Grunwald 44 +410665.0 True 4 2 Grunwald 7 +410780.0 True 3 3 Grunwald 44 +328476.0 True 2 4 Grunwald 98 +273951.0 True 2 0 Nowe 97 +321285.0 True 2 4 Winogrady 30 +318645.0 True 2 2 Winogrady 30 +886860.06 True 3 5 Centrum 80 +473770.0 True 2 5 Centrum 7 +798966.0 True 2 5 Centrum 33 +163563.75 True 2 0 Centrum 25 +314089.0 True 2 5 Grunwald 49 +297420.81 True 2 3 Grunwald 24 +455712.0 True 3 0 Grunwald 64 +746787.0 True 4 7 Grunwald 53 +322276.0 True 2 3 Winogrady 98 +286327.0 True 2 3 Winogrady 53 +312259.0 True 2 6 Winogrady 19 +256417.0 True 2 3 Nowe 33 +193950.0 True 2 1 Nowe 79 +226239.0 True 2 0 Nowe 93 +487000.0 True 3 0 Naramowice 83 +313028.0 True 2 4 Centrum 4 +292664.5 True 2 4 Centrum 11 +440496.0 True 3 4 Centrum 96 +358092.0 True 2 4 Centrum 84 +288216.5 True 2 4 Centrum 47 +410215.0 True 2 4 Centrum 11 +383760.0 True 3 6 Grunwald 60 +299000.0 True 2 0 Wilda 53 +299000.0 True 3 3 Jeżyce 56 +674000.0 True 5 2 Centrum 40 +270000.0 True 3 4 Nowe 48 +303287.0 True 2 3 Grunwald 13 +156986.0 True 2 1 Nowe 62 +162525.0 True 2 0 Nowe 55 +247831.0 True 3 5 Nowe 73 +222050.0 True 2 3 Nowe 41 +204450.0 True 3 1 Nowe 50 +188190.0 True 2 0 Nowe 90 +192750.0 True 2 4 Nowe 55 +247549.0 True 3 4 Nowe 67 +285678.0 False 2 1 Winogrady 42 +308237.0 False 2 1 Nowe 85 +349000.0 False 4 0 Szczepankowo 29 +297421.0 False 2 3 Grunwald 24 +297421.0 False 2 3 Grunwald 24 +244071.0 False 2 1 Nowe 93 +156085.0 False 2 4 Nowe 54 +265000.0 True 2 1 Jeżyce 66 +235000.0 True 2 0 Dębiec 43 +305000.0 True 2 8 Ogrody 44 +435000.0 True 3 1 Grunwald 70 +395000.0 True 2 0 Grunwald 11 +449000.0 False 5 0 Szczepankowo 68 +211190.0 False 2 0 Piątkowo 78 +771672.0 False 4 4 Górczyn 66 +771672.0 False 4 4 Górczyn 66 +302887.0 False 2 4 Górczyn 25 +282994.0 False 2 0 Starołęka 59 +771672.0 False 4 4 Górczyn 66 +302887.0 False 2 4 Górczyn 25 +225228.0 False 2 5 Rataje 91 +442080.0 False 3 1 Starołęka 68 +370597.0 False 2 4 Stare 4 +771672.0 False 4 4 Górczyn 66 +242731.0 False 2 0 Podolany 74 +225228.0 False 2 5 Rataje 91 +460499.0 False 3 1 Stare 51 +284618.0 False 2 3 Nowe 55 +356251.0 False 3 14 Grunwald 20 +297420.0 False 2 3 Grunwald 24 +428090.0 False 3 2 Nowe 85 +347090.0 False 3 1 Winogrady 41 +375529.0 False 2 3 Centrum 71 +429699.0 False 3 15 Grunwald 62 +332940.0 False 2 2 Winogrady 70 +162525.0 False 2 0 Głuszyna 55 +557338.0 False 3 3 Stare 4 +317880.0 False 2 11 Grunwald 98 +293436.0 False 2 11 Grunwald 16 +317880.0 False 2 2 Grunwald 98 +297421.0 False 2 3 Grunwald 16 +297421.0 False 2 3 Grunwald 16 +317880.0 False 2 2 Grunwald 98 +297421.0 False 2 3 Grunwald 16 +297421.0 False 2 3 Grunwald 16 +270000.0 True 2 2 Jeżyce 49 +470000.0 True 2 4 Centrum 42 +293436.0 False 2 11 Grunwald 16 +347193.0 False 3 11 Grunwald 7 +347193.0 False 3 11 Grunwald 7 +321904.0 False 2 4 Winogrady 92 +455348.0 False 3 0 Centrum 61 +331226.0 False 3 2 Starołęka 95 +557338.0 False 3 3 Centrum 4 +460499.0 False 3 1 Centrum 51 +245000.0 True 2 3 Grunwald 30 +597184.0 False 3 4 Stare 61 +597184.0 False 3 4 Stare 61 +557338.0 False 3 3 Centrum 4 +157039.0 False 2 4 Nowe 63 +522235.0 False 3 2 Stare 62 +294840.0 False 2 4 Winogrady 50 +442080.0 False 3 1 Starołęka 68 +370597.0 False 2 4 Stare 4 +460499.0 False 3 1 Stare 51 +242731.0 False 2 0 Podolany 74 +771672.0 False 4 4 Górczyn 66 +460499.0 False 3 1 Stare 51 +302887.0 False 2 4 Górczyn 25 +225228.0 False 2 5 Rataje 91 +284618.0 False 2 3 Nowe 55 +356251.0 False 3 14 Grunwald 20 +297420.0 False 2 3 Grunwald 24 +297421.0 False 2 3 Grunwald 16 +317880.0 False 2 2 Grunwald 98 +297421.0 False 2 3 Grunwald 16 +156085.0 False 2 3 Głuszyna 45 +362459.0 False 3 0 Starołęka 80 +285678.0 False 2 1 Winogrady 42 +308237.0 False 2 1 Nowe 85 +244071.0 False 2 1 Nowe 93 +156085.0 False 2 4 Nowe 54 +308237.0 False 2 1 Nowe 85 +244071.0 False 2 1 Nowe 93 +245000.0 True 2 5 Nowe 42 +308237.0 False 2 1 Nowe 85 +156085.0 False 2 3 Głuszyna 45 +297421.0 False 2 3 Grunwald 24 +244071.0 False 2 1 Nowe 93 +290000.0 True 3 2 Jeżyce 81 +279000.0 True 2 2 Wilda 30 +489000.0 True 2 8 Centrum 4 +395000.0 True 4 0 Grunwald 60 +239000.0 True 2 0 Rataje 48 +330000.0 True 3 4 Nowe 59 +370000.0 True 4 4 Stare 76 +380000.0 True 4 0 Stare 74 +319000.0 True 3 4 Rataje 63 +480000.0 True 4 1 Grunwald 64 +478000.0 True 3 3 Centrum 78 +304865.0 False 3 3 Zawady 43 +185000.0 True 2 8 Dębiec 50 +410000.0 True 2 9 Nowe 51 +439000.0 True 2 3 Centrum 86 +319000.0 True 3 3 Wilda 53 +399000.0 True 3 3 Stare 68 +870000.0 True 5 0 Grunwald 156 +335000.0 True 3 0 Centrum 65 +278000.0 True 3 2 Rataje 47 +249000.0 True 2 4 Grunwald 43 +379000.0 True 3 0 Wilda 96 +275000.0 True 2 9 Rataje 38 +319000.0 True 2 0 Grunwald 45 +295000.0 True 2 4 Grunwald 53 +195000.0 True 2 2 Nowe 42 +530000.0 True 2 5 Piątkowo 66 +380000.0 True 3 3 Centrum 67 +395000.0 True 2 0 Grunwald 52 +249000.0 True 2 5 Rataje 36 +379000.0 True 3 0 Rataje 30 +399000.0 True 3 1 Grunwald 65 +648263.0 True 3 2 Łazarz 84 +308220.0 True 2 5 Winogrady 70 +288000.0 True 3 4 Winogrady 30 +292020.0 True 2 1 Winogrady 10 +510000.0 True 2 5 Centrum 91 +310000.0 True 3 4 Rataje 10 +333694.0 True 3 0 Jeżyce 68 +232408.0 True 2 0 Stare 38 +392181.0 True 3 4 Winogrady 69 +285382.0 True 2 4 Winogrady 48 +245830.0 True 2 2 Grunwald 40 +410000.0 True 4 2 Nowe 71 +330000.0 True 2 0 Grunwald 68 +350000.0 True 3 4 Jeżyce 20 +245000.0 True 2 5 Rataje 42 +290000.0 True 2 4 Łazarz 36 +360000.0 True 3 0 Centrum 30 +399000.0 False 3 2 Winogrady 98 +348750.0 False 2 3 Centrum 50 +356448.0 False 2 4 Stare 5 +342021.0 False 2 4 Nowe 93 +342021.0 False 2 4 Nowe 93 +342021.0 False 2 4 Nowe 93 +342021.0 False 2 4 Nowe 93 +342021.0 False 2 4 Nowe 93 +638175.0 False 4 3 Nowe 9 +458208.0 False 3 3 Nowe 92 +428090.0 False 3 2 Nowe 85 +428090.0 False 3 1 Nowe 85 +280463.0 False 2 4 Nowe 55 +280000.0 True 3 2 Rataje 20 +347090.0 False 3 1 Winogrady 41 +347090.0 False 3 1 Winogrady 41 +285678.0 False 2 1 Winogrady 82 +347090.0 False 3 1 Winogrady 41 +321656.0 False 2 4 Winogrady 38 +312259.0 False 2 6 Winogrady 60 +317880.0 False 2 2 Grunwald 98 +225228.0 False 2 5 Rataje 91 +356251.0 False 3 14 Grunwald 20 +297420.0 False 2 3 Grunwald 24 +370597.0 False 2 4 Stare 4 +284618.0 False 2 3 Nowe 55 +544008.0 False 4 2 Starołęka 4 +302887.0 False 2 4 Górczyn 25 +156085.0 False 2 4 Nowe 54 +522235.0 False 3 2 Stare 62 +771672.0 False 4 4 Górczyn 66 +442080.0 False 3 1 Starołęka 68 +460499.0 False 3 1 Stare 51 +368712.0 False 2 0 Stare 80 +242731.0 False 2 0 Podolany 74 +560000.0 True 4 0 Naramowice 20 +359000.0 True 3 0 Grunwald 69 +287000.0 True 3 1 Wilda 73 +270000.0 True 2 2 Jeżyce 95 +285000.0 True 2 0 Grunwald 80 +350000.0 True 4 4 Stare 60 +389000.0 True 3 0 Wilda 96 +695000.0 True 3 2 Jeżyce 25 +270000.0 True 2 6 Piątkowo 47 +305000.0 True 2 1 Winogrady 49 +439000.0 True 3 1 Grunwald 10 +415000.0 True 4 7 Piątkowo 63 +268000.0 True 3 4 Jeżyce 42 +270000.0 True 3 4 Rataje 48 +269000.0 True 2 0 Grunwald 46 +360000.0 True 3 1 Rataje 69 +205000.0 True 2 1 Jeżyce 34 +405000.0 True 3 1 Antoninek 70 +295000.0 True 2 0 Winogrady 36 +295000.0 True 2 0 Naramowice 36 +339000.0 True 3 9 Rataje 65 +475000.0 True 4 4 Wilda 120 +359000.0 True 4 0 Winogrady 90 +368567.0 True 3 1 Jeżyce 68 +211189.0 True 2 0 Jeżyce 38 +391729.0 True 3 2 Winogrady 69 +285678.0 True 2 4 Winogrady 48 +469000.0 True 4 2 Jeżyce 87 +259000.0 True 3 4 Stare 60 +470092.78 True 2 3 Centrum 21 +244000.0 True 2 5 Śródka 43 +215000.0 True 2 4 Nowe 14 +488631.0 True 2 5 Centrum 22 +233000.0 True 2 4 Śródka 99 +485017.66 True 2 5 Centrum 77 +450000.0 True 2 3 Centrum 88 +410666.0 True 4 2 Grunwald 71 +327585.0 True 3 6 Grunwald 56 +263000.0 True 2 1 Rataje 45 +270000.0 True 3 4 Rataje 48 +405000.0 True 4 2 Rataje 71 +297421.0 False 2 1 Grunwald 16 +415000.0 True 3 0 Jeżyce 5 +297421.0 False 2 3 Grunwald 16 +991380.0 False 5 1 Starołęka 94 +319998.0 False 3 1 Starołęka 95 +288405.0 False 2 1 Górczyn 37 +375529.0 False 2 3 Centrum 71 +225228.0 False 2 0 Rataje 71 +357692.0 False 3 1 Nowe 31 +310584.0 False 2 1 Nowe 26 +368568.0 False 3 4 Podolany 38 +460499.0 False 3 1 Stare 51 +156085.0 False 2 4 Nowe 54 +771672.0 False 4 4 Górczyn 66 +522235.0 False 3 2 Stare 62 +302887.0 False 2 4 Górczyn 25 +242731.0 False 2 0 Podolany 74 +225228.0 False 2 5 Rataje 91 +356251.0 False 3 14 Grunwald 20 +297420.0 False 2 3 Grunwald 24 +544008.0 False 4 2 Starołęka 4 +284618.0 False 2 3 Nowe 55 +285678.0 False 2 2 Winogrady 42 +174375.0 True 2 3 Centrum 25 +350000.0 True 4 4 Piątkowo 76 +380000.0 True 4 0 Piątkowo 74 +315000.0 True 2 0 Górczyn 48 +362000.0 True 2 1 Centrum 50 +344206.0 True 4 4 Stare 58 +300987.0 True 3 1 Stare 50 +235094.0 True 2 0 Stare 39 +549000.0 True 3 2 Jeżyce 18 +239000.0 True 2 1 Grunwald 44 +379000.0 True 3 1 Naramowice 20 +320000.0 True 2 1 Naramowice 50 +269000.0 True 3 1 Wilda 80 +295000.0 True 3 0 Grunwald 20 +249999.0 True 2 9 Winogrady 38 +330000.0 True 2 3 Piątkowo 50 +360000.0 True 3 2 Rataje 20 +412438.0 True 3 2 Winogrady 71 +291721.0 True 2 5 Stare 44 +354421.0 True 2 5 Stare 54 +399952.0 True 4 1 Grunwald 71 +280000.0 True 2 2 Centrum 40 +200000.0 True 2 2 Dębiec 40 +289000.0 True 2 7 Winiary 49 +279000.0 True 3 10 Rataje 56 +333232.0 True 3 7 Grunwald 56 +489000.0 True 3 0 Jeżyce 10 +375000.0 True 2 1 Piątkowo 48 +259000.0 True 2 2 Centrum 48 +335000.0 True 2 0 Centrum 54 +288000.0 True 3 4 Winogrady 30 +289000.0 True 2 7 Winiary 49 +380000.0 True 3 3 Wilda 67 +419000.0 True 3 4 Wilda 50 +247705.0 True 2 0 Jeżyce 50 +333696.0 True 3 0 Jeżyce 68 +409000.0 True 3 1 Rataje 90 +239000.0 True 2 3 Grunwald 60 +289000.0 True 2 6 Winogrady 48 +326000.0 True 2 1 Winogrady 39 +269000.0 True 2 2 Winogrady 48 +489000.0 True 4 2 Wilda 120 +350000.0 True 4 4 Piątkowo 76 +322663.41 True 2 1 Centrum 14 +368019.41 True 2 4 Centrum 18 +674695.13 True 4 4 Centrum 59 +375000.0 True 4 2 Centrum 72 +378128.09 True 2 3 Centrum 77 +349668.0 True 2 2 Centrum 15 +344296.75 True 2 1 Centrum 5 +353456.63 True 2 3 Centrum 16 +347193.0 False 3 11 Grunwald 7 +557338.0 False 3 3 Centrum 4 +228144.0 False 3 2 Głuszyna 56 +247705.0 False 2 1 Podolany 74 +228144.0 False 3 2 Głuszyna 56 +222050.0 False 2 3 Głuszyna 41 +158682.0 False 2 2 Głuszyna 94 +194000.0 False 2 2 Głuszyna 80 +289170.0 False 2 0 Winogrady 90 +399000.0 False 3 2 Winogrady 98 +305670.0 False 2 3 Grunwald 30 +305670.0 False 2 3 Grunwald 30 +294840.0 False 2 4 Winogrady 50 +597184.0 False 3 4 Stare 61 +460499.0 False 3 1 Stare 51 +347010.0 False 2 10 Grunwald 80 +356251.0 False 3 14 Grunwald 20 +225228.0 False 2 5 Rataje 91 +297420.0 False 2 3 Grunwald 24 +284618.0 False 2 3 Nowe 55 +544008.0 False 4 2 Starołęka 4 +522235.0 False 3 2 Stare 62 +370597.0 False 2 4 Stare 4 +674695.0 False 3 4 Stare 59 +442080.0 False 3 1 Starołęka 68 +771672.0 False 4 4 Górczyn 66 +302887.0 False 2 4 Górczyn 25 +294840.0 False 2 4 Winogrady 50 +305676.0 False 2 5 Winogrady 52 +305676.0 False 2 5 Winogrady 52 +242731.0 False 2 0 Podolany 74 +460499.0 False 3 1 Stare 51 +156085.0 False 2 4 Nowe 54 +242731.0 False 2 0 Podolany 74 +368568.0 False 3 4 Podolany 38 +499000.0 True 3 1 Rataje 50 +275000.0 True 3 1 Wilda 48 +307000.0 True 3 2 Rataje 48 +485000.0 True 2 3 Nowe 50 +288000.0 True 2 4 Naramowice 44 +405000.0 True 4 7 Piątkowo 63 +299000.0 True 2 4 Grunwald 60 +235000.0 True 2 0 Nowe 47 +288000.0 True 3 4 Stare 30 +225288.0 False 2 1 Rataje 91 +287882.0 False 2 1 Starołęka 85 +225288.0 False 2 1 Rataje 91 +652026.0 True 4 3 Stare 89 +476118.0 True 3 1 Stare 78 +349668.0 True 2 2 Stare 15 +318645.0 True 2 2 Stare 30 +290970.0 True 2 0 Stare 60 +354000.0 True 3 1 Stare 60 +260000.0 True 2 0 Stare 47 +670000.0 True 5 1 Stare 152 +360380.0 True 4 4 Wilda 97 +329000.0 True 2 3 Nowe 90 +249000.0 True 2 5 Centrum 20 +319000.0 True 2 3 Jeżyce 40 +493422.0 True 3 1 Centrum 62 +236000.0 True 2 3 Nowe 43 +257697.0 True 2 3 Śródka 21 +234000.0 True 2 2 Śródka 20 +233643.0 True 2 2 Nowe 99 +296810.0 True 2 2 Grunwald 30 +335988.0 True 2 1 Grunwald 41 +453526.5 True 3 6 Grunwald 33 +637135.0 True 3 7 Grunwald 65 +771672.0 True 4 7 Grunwald 68 +329000.0 True 3 8 Piątkowo 63 +399000.0 False 5 0 Szczepankowo 68 +369000.0 True 2 4 Rataje 49 +404000.0 True 2 0 Rataje 49 +389000.0 True 3 4 Rataje 62 +507060.0 True 2 3 Grunwald 77 +390910.0 True 3 1 Grunwald 14 +690000.0 True 6 2 Centrum 170 +355000.0 True 2 0 Podolany 93 +369000.0 True 16 2 Piątkowo 90 +339000.0 True 3 9 Rataje 65 +398000.0 True 2 3 Umultowo 59 +289000.0 True 2 6 Stare 80 +389000.0 True 3 3 Stare 49 +270000.0 True 2 6 Piątkowo 46 +353000.0 True 3 2 Grunwald 73 +413484.5 True 3 4 Grunwald 83 +311046.0 True 2 6 Grunwald 12 +1020000.0 True 3 1 Grunwald 50 +292383.0 True 2 0 Grunwald 41 +307190.0 True 2 4 Grunwald 20 +311975.5 True 2 1 Grunwald 13 +335000.0 True 3 1 Naramowice 60 +289000.0 True 2 1 Winogrady 48 +449000.0 False 5 0 Szczepankowo 68 +285678.0 False 2 1 Winogrady 42 +247705.0 False 2 0 Podolany 74 +211190.0 False 2 0 Podolany 78 +278047.0 False 2 4 Podolany 74 +333694.0 False 3 0 Podolany 38 +333024.0 False 2 1 Stare 51 +319998.0 False 3 1 Starołęka 97 +354420.0 False 2 5 Winogrady 70 +348750.0 False 2 3 Centrum 50 +269000.0 True 2 8 Rataje 90 +370597.0 False 2 4 Stare 4 +242731.0 False 2 0 Podolany 74 +370597.0 False 2 4 Stare 4 +460499.0 False 3 1 Stare 51 +302887.0 False 2 4 Górczyn 25 +225228.0 False 2 5 Rataje 91 +356251.0 False 3 14 Grunwald 20 +156085.0 False 2 4 Nowe 54 +156085.0 False 2 4 Nowe 54 +156085.0 False 2 4 Nowe 54 +544008.0 False 4 2 Starołęka 4 +302887.0 False 2 4 Górczyn 25 +284618.0 False 2 3 Nowe 55 +242731.0 False 2 0 Podolany 74 +546462.0 False 4 0 Jeżyce 74 +493966.0 False 4 0 Jeżyce 79 +332691.0 False 3 0 Jeżyce 58 +335920.0 False 3 0 Jeżyce 68 +334360.0 False 3 1 Jeżyce 44 +329000.0 True 3 3 Jeżyce 54 +299000.0 True 2 3 Naramowice 49 +349000.0 True 3 3 Piątkowo 64 +297421.0 False 2 3 Grunwald 24 +244071.0 False 2 1 Nowe 93 +287882.0 False 2 1 Starołęka 85 +297421.0 False 2 3 Grunwald 24 +297421.0 False 2 3 Grunwald 24 +156085.0 False 2 3 Głuszyna 45 +244071.0 False 2 1 Nowe 93 +330000.0 True 3 1 Dębiec 88 +364000.0 True 3 2 Jeżyce 69 +365000.0 True 3 1 Wilda 46 +380000.0 True 4 0 Piątkowo 74 +270000.0 True 2 6 Piątkowo 46 +330000.0 True 3 4 Rataje 59 +260000.0 True 2 0 Naramowice 47 +425000.0 True 3 1 Rataje 70 +239000.0 True 2 3 Rataje 44 +250000.0 True 2 9 Winogrady 10 +307000.0 True 2 4 Piątkowo 49 +300000.0 True 3 2 Grunwald 49 +295361.0 True 3 2 Stare 48 +242133.0 True 2 0 Jeżyce 38 +391730.0 True 3 2 Winogrady 69 +286860.0 True 2 7 Winogrady 49 +476119.0 True 3 1 Stare 59 +652026.0 True 4 3 Stare 79 +289171.0 True 2 0 Stare 46 +293700.0 True 2 5 Stare 45 +342405.0 True 3 11 Grunwald 54 +297420.0 True 2 1 Grunwald 50 +292100.0 True 2 1 Grunwald 51 +333690.0 True 3 1 Jeżyce 68 +242731.0 True 2 0 Jeżyce 50 +211200.0 True 2 0 Jeżyce 38 +288000.0 True 3 4 Winogrady 30 +245000.0 True 2 0 Naramowice 50 +359600.0 True 2 5 Górczyn 58 +332940.0 True 2 2 Winogrady 70 +248337.0 True 2 3 Winogrady 38 +209000.0 True 2 0 Śródka 14 +341803.78 True 2 8 Winogrady 10 +285000.0 True 2 3 Łazarz 58 +217000.0 True 2 4 Wilda 30 +379000.0 True 4 3 Winogrady 65 +235000.0 True 2 0 Śródka 10 +597184.0 False 3 4 Stare 61 +460499.0 False 3 1 Stare 51 +347010.0 False 2 10 Grunwald 80 +282994.0 False 2 0 Starołęka 59 +297420.0 False 2 3 Grunwald 24 +522235.0 False 3 2 Stare 62 +368568.0 False 3 4 Podolany 38 +242731.0 False 2 0 Podolany 74 +460499.0 False 3 1 Stare 51 +771672.0 False 4 4 Górczyn 66 +302887.0 False 2 4 Górczyn 25 +350000.0 True 4 4 Piątkowo 76 +375000.0 True 3 1 Nowe 62 +260000.0 True 2 0 Naramowice 79 +315000.0 True 2 1 Grunwald 49 +375000.0 True 3 1 Rataje 62 +229000.0 True 2 11 Stare 38 +365000.0 True 3 1 Wilda 46 +299000.0 True 2 3 Górczyn 37 +259000.0 True 2 2 Jeżyce 48 +289000.0 True 2 1 Piątkowo 46 +310000.0 True 3 0 Piątkowo 63 +209000.0 True 2 4 Dębiec 6 +249000.0 True 2 0 Nowe 21 +287882.09 True 2 1 Nowe 85 +434201.0 True 4 1 Nowe 54 +482423.0 True 5 2 Nowe 4 +297789.5 True 2 2 Nowe 54 +149000.0 True 2 0 Grunwald 35 +299000.0 True 2 9 Stare 80 +365000.0 True 3 1 Wilda 46 +329000.0 True 2 3 Rataje 90 +337000.0 True 4 4 Rataje 62 +597184.0 False 3 4 Stare 61 +347010.0 False 2 10 Grunwald 80 +460499.0 False 3 1 Stare 51 +597184.0 False 3 4 Stare 61 +300680.0 False 2 2 Starołęka 54 +347010.0 False 2 10 Grunwald 80 +294840.0 False 2 4 Winogrady 50 +368568.0 False 3 4 Podolany 38 +242731.0 False 2 0 Podolany 74 +674695.0 False 3 4 Stare 59 +442080.0 False 3 1 Starołęka 68 +302887.0 False 2 4 Górczyn 25 +294840.0 False 2 4 Winogrady 50 +460499.0 False 3 1 Stare 51 +365000.0 True 3 0 Wilda 10 +195000.0 True 2 0 Winiary 35 +325000.0 True 4 1 Rataje 58 +303287.0 False 2 3 Grunwald 13 +375000.0 True 3 1 Rataje 62 +384000.0 True 3 2 Piątkowo 69 +297421.0 False 2 3 Grunwald 24 +244071.0 False 2 1 Nowe 93 +255000.0 True 2 2 Centrum 90 +285000.0 True 2 0 Grunwald 80 +300000.0 True 3 1 Grunwald 48 +330000.0 True 3 5 Grunwald 58 +330000.0 True 3 5 Grunwald 58 +330000.0 True 3 5 Grunwald 58 +315000.0 True 2 0 Centrum 60 +290000.0 True 2 4 Centrum 36 +245000.0 True 2 7 Ogrody 90 +289000.0 True 2 1 Piątkowo 46 +359000.0 True 2 4 Nowe 90 +339000.0 True 3 1 Nowe 88 +285385.0 True 2 4 Winogrady 48 +308039.0 True 2 0 Winogrady 52 +298982.0 True 2 3 Stare 45 +289170.0 True 2 0 Stare 46 +368568.0 True 3 4 Jeżyce 68 +211195.0 True 2 0 Jeżyce 38 +315000.0 True 2 2 Podolany 52 +267704.0 True 2 3 Grunwald 45 +325313.0 True 3 3 Grunwald 53 +260000.0 True 2 0 Naramowice 47 +349000.0 True 2 3 Jeżyce 56 +499000.0 True 3 1 Rataje 50 +239000.0 True 2 0 Wilda 57 +487000.0 True 3 0 Naramowice 73 +319000.0 True 2 2 Centrum 53 +344152.0 True 3 0 Nowe 80 +357692.0 True 3 2 Nowe 31 +277098.0 True 2 0 Nowe 59 +301794.13 True 2 1 Nowe 26 +533745.0 False 5 2 Starołęka 4 +333694.0 False 3 1 Podolany 32 +333694.0 False 3 1 Piątkowo 38 +380931.0 False 3 3 Starołęka 82 +597184.0 False 3 4 Stare 61 +460499.0 False 3 1 Stare 51 +300680.0 False 2 2 Starołęka 54 +305670.0 False 2 3 Grunwald 30 +390301.0 False 2 4 Stare 61 +370597.0 False 2 4 Stare 4 +192750.0 False 2 1 Głuszyna 55 +460499.0 False 3 1 Stare 51 +242731.0 False 2 0 Podolany 74 +303287.0 False 2 3 Grunwald 13 +318645.0 False 2 2 Winogrady 23 +370597.0 False 2 4 Stare 4 +674695.0 False 3 4 Stare 59 +442080.0 False 3 1 Starołęka 68 +771672.0 False 4 4 Górczyn 66 +771672.0 False 4 4 Górczyn 66 +294840.0 False 2 4 Winogrady 50 +368712.0 False 2 5 Stare 90 +480000.0 True 3 3 Stare 46 +237000.0 True 2 2 Wilda 44 +359000.0 True 4 3 Grunwald 74 +369000.0 True 3 0 Grunwald 87 +369000.0 True 3 0 Grunwald 87 +695000.0 True 3 2 Jeżyce 25 +321239.09 True 2 3 Winogrady 30 +331899.09 True 2 2 Winogrady 30 +334564.09 True 2 1 Winogrady 30 +289800.0 True 2 0 Winogrady 46 +289170.0 True 2 0 Winogrady 90 +345000.0 True 3 3 Stare 50 +499000.0 True 2 8 Centrum 39 +399000.0 True 2 1 Jeżyce 58 +1049000.0 True 3 9 Nowe 113 +729000.0 True 4 3 Stare 130 +254457.0 True 2 5 Nowe 52 +249000.0 True 2 6 Winogrady 48 +320000.0 True 3 3 Nowe 40 +333692.0 True 3 2 Jeżyce 68 +410665.0 True 4 2 Grunwald 71 +293436.0 True 2 1 Grunwald 50 +481904.0 True 3 2 Stare 62 +332940.0 True 2 2 Stare 54 +325249.0 True 3 3 Jeżyce 49 +347096.0 True 3 1 Winogrady 57 +297421.0 False 2 2 Grunwald 24 +570000.0 True 4 3 Centrum 137 +351475.0 False 3 0 Starołęka 80 +294840.0 False 2 4 Winogrady 50 +460499.0 False 3 1 Stare 51 +300680.0 False 2 2 Starołęka 54 +460499.0 False 3 1 Stare 51 +353275.0 False 2 14 Grunwald 74 +294840.0 False 2 4 Winogrady 50 +297420.0 False 2 3 Grunwald 24 +294840.0 False 2 4 Winogrady 50 +302887.0 False 2 4 Górczyn 25 +442080.0 False 3 1 Starołęka 68 +289000.0 True 2 6 Winogrady 48 +289000.0 True 2 6 Winogrady 48 +674695.0 False 3 4 Stare 59 +269000.0 True 2 6 Stare 49 +347010.0 False 2 10 Grunwald 80 +296279.0 True 3 2 Stare 49 +238947.0 True 2 6 Stare 39 +289000.0 True 2 1 Piątkowo 46 +774618.0 False 4 5 Wilda 31 +741099.0 False 4 5 Wilda 22 +460688.0 False 3 4 Wilda 25 +300723.0 False 2 4 Wilda 97 +349610.0 False 2 4 Wilda 59 +564000.0 False 5 0 Biedrusko 90 +618933.0 False 4 4 Wilda 37 +399000.0 False 4 0 Biedrusko 34 +564000.0 False 5 0 Biedrusko 90 +359000.0 False 3 0 Biedrusko 80 +524808.0 False 3 4 Wilda 92 +359000.0 False 4 1 Biedrusko 86 +360000.0 True 3 3 Jeżyce 62 +499000.0 False 2 2 Stare 45 +664443.0 False 3 3 Stare 24 +526049.0 False 2 3 Stare 45 +709116.0 False 3 4 Stare 88 +347182.0 False 4 1 Biedrusko 70 +335925.0 False 4 1 Biedrusko 70 +335925.0 False 4 1 Biedrusko 70 +335925.0 False 4 1 Biedrusko 70 +335925.0 False 4 1 Biedrusko 70 +453929.0 False 3 3 Wilda 26 +387000.0 False 4 1 Biedrusko 86 +309276.0 False 2 3 Wilda 12 +486720.0 False 3 3 Wilda 60 +325440.0 False 3 0 Biedrusko 80 +484068.0 False 3 3 Wilda 6 +306675.0 False 3 0 Biedrusko 20 +663205.0 False 4 3 Wilda 85 +447038.0 False 3 2 Wilda 25 +306675.0 False 3 0 Biedrusko 20 +306675.0 False 3 0 Biedrusko 20 +481522.0 False 3 2 Wilda 82 +306675.0 False 3 0 Biedrusko 20 +356400.0 False 2 2 Wilda 52 +325440.0 False 3 0 Biedrusko 80 +510984.0 False 3 2 Wilda 97 +272000.0 False 3 2 Biedrusko 31 +289000.0 False 3 1 Biedrusko 39 +289000.0 False 3 1 Biedrusko 39 +319000.0 False 3 0 Biedrusko 49 +329000.0 False 3 0 Biedrusko 49 +289000.0 True 2 1 Piątkowo 46 +289000.0 True 2 1 Piatkowo 46 +125000.0 True 5 3 Grunwald 22 +625000.0 True 5 3 Grunwald 105 +643000.0 True 4 0 Naramowice 60 +215000.0 True 2 2 Centrum 39 +399000.0 True 4 0 Centrum 70 +435000.0 True 3 1 Grunwald 10 +289000.0 True 3 4 Naramowice 40 +515000.0 True 3 0 Rataje 71 +310000.0 True 2 4 Jeżyce 55 +348000.0 True 3 9 Rataje 65 +340000.0 True 3 8 Rataje 65 +325248.0 True 3 1 Jeżyce 49 +262875.0 True 2 4 Jeżyce 40 +325248.0 True 3 1 Jeżyce 49 +262874.0 True 2 4 Jeżyce 40 +253498.0 True 2 4 Jeżyce 38 +253193.0 True 2 6 Jeżyce 38 +253193.0 True 2 4 Jeżyce 38 +220000.0 True 2 1 Łazarz 45 +230000.0 True 2 2 Rataje 49 +293848.0 True 3 4 Winogrady 49 +305000.0 True 3 4 Jeżyce 84 +245000.0 True 2 2 Jeżyce 62 +205000.0 True 2 0 Jeżyce 43 +269000.0 True 2 13 Piątkowo 50 +249000.0 True 2 2 Strzeszyn 34 +330000.0 True 3 6 Rataje 80 +200000.0 True 2 0 Wilda 32 +270000.0 True 3 4 Rataje 48 +617360.0 True 3 3 Grunwald 77 +279554.0 True 2 4 Jeżyce 68 +279554.0 True 2 4 Jeżyce 68 +550000.0 True 3 1 Grunwald 73 +355000.0 True 2 8 Ogrody 52 +210000.0 True 2 10 Ogrody 38 +234000.0 True 2 0 Wilda 37 +375000.0 True 3 2 Wilda 90 +345000.0 True 3 6 Winogrady 10 +320000.0 True 3 4 Piątkowo 63 +239000.0 True 2 8 Winogrady 38 +350000.0 True 4 4 Piątkowo 74 +295363.0 True 3 1 Stare 48 +285384.0 True 2 4 Winogrady 48 +392861.0 True 3 3 Winogrady 69 +399000.0 True 2 0 Podolany 63 +518000.0 True 2 4 Centrum 2 +495000.0 True 3 0 Rataje 69 +405000.0 True 3 3 Jeżyce 63 +269000.0 True 2 1 Rataje 50 +481903.0 True 3 2 Stare 62 +269000.0 True 2 4 Grunwald 38 +404000.0 True 3 2 Piątkowo 60 +549000.0 True 3 2 Dąbrowskiego 106 +489000.0 True 3 0 Stare 70 +358000.0 True 4 3 Grunwald 74 +379000.0 True 3 1 Naramowice 20 +269000.0 True 3 11 Grunwald 50 +197000.0 True 2 3 Grunwald 40 +362459.0 False 3 0 Starołęka 80 +353275.0 False 2 14 Grunwald 74 +351475.0 False 3 0 Starołęka 80 +225228.0 False 2 5 Rataje 91 +394000.0 False 4 0 Szczepankowo 77 +287882.0 False 2 1 Starołęka 85 +349000.0 True 3 4 Wilda 75 +255000.0 True 2 3 Rataje 46 +460040.0 True 3 5 Górczyn 20 +321656.0 True 2 1 Winogrady 88 +326000.0 True 2 1 Winiary 39 +285000.0 True 2 3 Naramowice 5 +399000.0 True 4 0 Stary 70 +349000.0 True 3 3 Nowe 87 +585000.0 True 4 1 Stare 100 +510000.0 True 3 2 Stare 68 +409000.0 True 4 3 Centrum 111 +310000.0 True 2 0 Grunwald 60 +308039.0 True 2 0 Winogrady 21 +286858.0 True 2 7 Winogrady 62 +279000.0 True 3 0 Piątkowo 50 +347090.0 False 3 1 Winogrady 90 +241187.0 True 2 7 Stare 39 +350875.0 True 3 1 Rataje 56 +296279.0 True 3 3 Stare 49 +293900.0 True 3 4 Stare 49 +315812.0 True 4 8 Stare 52 +374791.0 True 4 5 Jeżyce 57 +278048.0 True 2 4 Jeżyce 50 +371931.0 True 4 4 Jeżyce 57 +242000.0 True 2 1 Jeżyce 38 +308220.0 False 2 5 Stare 70 +339000.0 True 3 1 Rataje 66 +460499.0 False 3 1 Stare 51 +349668.0 False 2 2 Stare 15 +300680.0 False 2 2 Starołęka 54 +557338.0 False 3 3 Stare 4 +349332.0 True 3 0 Jeżyce 16 +271236.0 True 2 2 Jeżyce 41 +329000.0 True 3 1 Jeżyce 112 +199000.0 True 2 2 Grunwald 38 +475000.0 True 3 1 Naramowice 68 +379000.0 True 5 3 Winogrady 65 +270000.0 True 2 2 Stare 95 +210000.0 True 2 2 Dębiec 40 +379000.0 True 2 3 Winogrady 48 +440000.0 True 2 2 Stare 90 +750000.0 True 5 2 Jeżyce 136 +425000.0 True 4 6 Nowe 85 +539000.0 True 4 1 Centrum 110 +1300000.0 True 2 1 Grunwald 100 +340000.0 True 3 0 Grunwald 98 +360000.0 True 3 4 Jeżyce 50 +259000.0 True 2 0 Grunwald 52 +295000.0 True 2 1 Wilda 51 +487000.0 True 3 0 Naramowice 73 +487000.0 True 3 0 Naramowice 73 +285000.0 True 3 2 Rataje 10 +605000.0 True 3 0 Grunwald 98 +209000.0 True 3 3 Grunwald 49 +242406.0 True 2 0 Jeżyce 36 +380000.0 True 2 2 Wilda 10 +268000.0 True 3 4 Jeżyce 50 +286446.0 True 2 2 Winogrady 49 +392181.0 True 3 4 Winogrady 69 +300987.0 True 3 3 Stare 50 +240876.0 True 2 7 Stare 39 +298980.0 True 2 5 Stare 45 +293700.0 True 2 5 Stare 45 +375960.0 True 4 2 Grunwald 71 +377918.0 True 3 2 Grunwald 71 +292100.0 True 2 1 Grunwald 51 +476118.0 True 3 1 Stare 59 +396248.0 True 2 4 Stare 52 +278046.0 True 2 1 Jeżyce 50 +211191.0 True 2 0 Jeżyce 38 +362458.0 True 3 0 Nowe 68 +288523.0 True 2 0 Nowe 54 +282998.0 True 2 0 Nowe 55 +247705.0 False 2 1 Podolany 74 +637135.0 False 3 7 Grunwald 65 +349000.0 False 4 0 Szczepankowo 29 +285678.0 False 2 1 Winogrady 42 +277823.0 False 2 2 Podolany 70 +424377.0 False 4 2 Starołęka 14 +282944.0 False 2 0 Starołęka 59 +460499.0 False 3 1 Stare 51 +289170.0 False 2 0 Winogrady 90 +339000.0 True 3 9 Nowe 65 +351475.0 False 3 0 Starołęka 80 +349000.0 True 3 3 Nowe 63 +349000.0 False 4 0 Szczepankowo 29 +247831.0 False 2 5 Głuszyna 73 +353275.0 False 2 14 Grunwald 74 +353275.0 False 2 14 Grunwald 74 +349000.0 False 4 0 Szczepankowo 29 +225288.0 False 2 1 Rataje 91 +285678.0 False 2 1 Winogrady 42 +225228.0 False 2 5 Rataje 91 +297421.0 False 2 3 Grunwald 24 +294840.0 False 2 4 Winogrady 50 +300680.0 False 2 2 Starołęka 54 +349668.0 False 2 2 Stare 15 +476780.0 True 2 2 Centrum 90 +239000.0 True 2 10 Rataje 44 +359000.0 True 3 2 Jeżyce 58 +207000.0 True 2 2 Zawady 42 +282995.0 True 2 0 Starołęka 59 +626800.0 True 3 7 Stare 68 +439000.0 True 4 2 Grunwald 92 +569000.0 True 4 0 Wilda 30 +313000.0 True 2 4 Stare 20 +396565.0 True 3 2 Jeżyce 61 +405860.0 True 2 1 Jeżyce 44 +519000.0 True 3 3 Grunwald 104 +265000.0 True 3 1 Winogrady 53 +530000.0 True 4 3 Naramowice 102 +390000.0 True 3 2 Podolany 68 +305000.0 True 2 1 Winiary 48 +215000.0 True 2 2 Łazarz 39 +250000.0 True 2 3 Centrum 33 +489000.0 True 2 4 Nowe 51 +495000.0 True 3 1 Centrum 86 +499000.0 True 3 2 Rataje 64 +339000.0 True 3 9 Rataje 65 +319000.0 True 3 1 Piątkowo 64 +310000.0 True 3 0 Piątkowo 50 +270000.0 True 3 4 Rataje 48 +330000.0 True 4 0 Naramowice 68 +255000.0 True 2 0 Grunwald 48 +333000.0 True 3 7 Rataje 78 +255000.0 True 2 2 Dębiec 48 +225000.0 True 2 3 Nowe 36 +326000.0 True 2 1 Winiary 39 +480000.0 True 3 2 Grunwald 87 +399000.0 True 3 3 Centrum 50 +980000.0 True 6 0 Naramowice 193 +350000.0 True 3 5 Stare 48 +410000.0 True 5 0 Łazarz 114 +279000.0 True 2 1 Podolany 45 +357693.0 True 3 2 Nowe 64 +424379.0 True 4 2 Nowe 74 +533746.0 True 5 2 Nowe 95 +282997.0 True 2 0 Nowe 55 +232049.0 True 2 0 Stare 36 +289800.0 True 2 0 Stare 46 +289170.0 True 2 0 Stare 46 +300988.0 True 3 1 Stare 50 +223752.0 True 2 0 Stare 37 +285680.0 True 2 4 Winogrady 48 +391730.0 True 3 2 Winogrady 69 +318383.0 True 3 3 Jeżyce 48 +266320.0 True 2 5 Jeżyce 41 +242407.0 True 2 0 Jeżyce 36 +245000.0 True 2 2 Winogrady 38 +239000.0 True 2 4 Rataje 38 +258000.0 True 2 1 Wilda 49 +269000.0 True 2 9 Nowe 49 +410000.0 True 2 5 Malta 53 +349000.0 True 3 2 Górczyn 55 +210000.0 True 2 2 Zawady 42 +329000.0 True 3 3 Piątkowo 60 +539000.0 True 3 1 Nowe 70 +335000.0 True 4 4 Rataje 50 +305000.0 True 2 1 Sołacz 48 +239000.0 True 2 3 Winogrady 10 +269000.0 True 2 0 Grunwald 20 +269000.0 True 3 1 Wilda 68 +429000.0 True 3 3 Centrum 102 +219000.0 True 2 2 Rataje 38 +1200000.0 True 4 2 Jeżyce 188 +350000.0 True 3 0 Winogrady 48 +250000.0 True 2 4 Rataje 44 +410000.0 True 2 9 Rataje 51 +485000.0 False 2 4 Łazarz 80 +409240.0 False 2 3 Piątkowo 67 +454960.0 False 2 1 Łazarz 87 +384500.0 False 2 3 Piątkowo 50 +392420.0 False 2 3 Piątkowo 70 +295020.0 False 2 2 Piątkowo 70 +298320.0 False 2 2 Piątkowo 20 +295020.0 False 2 1 Piątkowo 70 +298320.0 False 2 1 Piątkowo 20 +297000.0 False 2 1 Piątkowo 45 +286080.0 False 2 0 Piątkowo 70 +293800.0 False 2 0 Piątkowo 20 +292500.0 False 2 0 Piątkowo 45 +300950.0 False 2 0 Piątkowo 30 +227500.0 False 2 3 Piątkowo 20 +427060.0 False 2 3 Piątkowo 50 +699000.0 True 4 2 Naramowice 92 +409240.0 False 2 3 Piątkowo 67 +287760.0 False 2 2 Piątkowo 60 +278720.0 False 2 2 Piątkowo 60 +287100.0 False 2 2 Piątkowo 50 +240000.0 True 2 0 Grunwald 60 +295020.0 False 2 2 Piątkowo 70 +287760.0 False 2 1 Piątkowo 60 +278720.0 False 2 1 Piątkowo 60 +287100.0 False 2 1 Piątkowo 50 +360000.0 True 2 5 Grunwald 41 +304920.0 False 2 1 Piątkowo 20 +295020.0 False 2 1 Piątkowo 70 +239000.0 True 2 4 Rataje 38 +360000.0 True 3 1 Jeżyce 20 +350000.0 True 4 4 Stare 60 +450000.0 True 2 2 Stare 40 +211190.0 False 2 0 Piątkowo 78 +294840.0 False 2 4 Winogrady 50 +399000.0 False 3 2 Winogrady 98 +299514.0 False 2 1 Starołęka 85 +299000.0 True 2 4 Grunwald 37 +287000.0 True 2 16 Rataje 49 +420000.0 True 4 3 Łazarz 104 +274900.0 True 2 13 Nowe 80 +720000.0 True 4 0 Centrum 163 +339000.0 True 3 1 Rataje 66 +480000.0 True 2 2 Grunwald 10 +283400.0 False 2 0 Piątkowo 60 +282750.0 False 2 0 Piątkowo 50 +300300.0 False 2 0 Piątkowo 20 +286080.0 False 2 0 Piątkowo 70 +210000.0 True 2 2 Zawady 42 +320000.0 True 2 4 Winogrady 57 +410000.0 True 2 5 Rataje 50 +315000.0 True 3 0 Stare 63 +365000.0 True 2 1 Jeżyce 56 +340000.0 True 3 9 Rataje 30 +339000.0 True 3 9 Rataje 65 +325000.0 True 3 7 Rataje 90 +349000.0 True 3 2 Górczyn 55 +375000.0 True 4 2 Centrum 72 +269000.0 True 3 3 Winogrady 48 +495000.0 True 4 3 Naramowice 104 +329000.0 True 3 3 Wilda 82 +385000.0 True 3 0 Łazarz 80 +395000.0 True 2 1 Stare 30 +285000.0 True 2 3 Wilda 43 +325000.0 True 2 3 Centrum 57 +305000.0 True 2 1 Sołacz 48 +339000.0 True 3 0 Rataje 20 +480000.0 True 3 1 Grunwald 40 +630000.0 True 4 0 Stare 84 +275000.0 True 2 2 Plewiska 62 +350000.0 True 2 4 Jeżyce 56 +488000.0 True 3 3 Grunwald 70 +305000.0 True 2 1 Winiary 48 +255000.0 True 2 4 Rataje 70 +285000.0 True 3 0 Wilda 61 +282995.0 True 2 0 Starołęka 59 +263000.0 True 3 4 Grunwald 48 +380931.0 False 3 3 Starołęka 82 +329000.0 True 2 3 Rataje 49 +325000.0 True 3 7 Rataje 90 +350000.0 True 3 0 Starołęka 44 +268000.0 True 2 0 Rataje 43 +253000.0 True 2 4 Grunwald 42 +269000.0 True 2 1 Rataje 50 +325000.0 True 3 7 Rataje 63 +300000.0 True 3 6 Wilda 50 +329000.0 True 3 1 Piątkowo 63 +415000.0 True 2 5 Nowe 53 +270000.0 True 3 4 Rataje 47 +300000.0 True 3 6 Wilda 50 +690000.0 True 5 1 Jeżyce 70 +250000.0 True 2 5 Wilda 12 +344000.0 True 2 2 Wilczak 50 +329000.0 True 3 3 Piątkowo 60 +978009.0 False 4 7 Grunwald 2 +864244.5 False 4 7 Grunwald 71 +329000.0 True 3 1 Piątkowo 63 +255000.0 True 2 2 Dębiec 48 +279999.0 True 2 1 Piątkowo 90 +245000.0 True 2 2 Winogrady 20 +510000.0 True 3 3 Grunwald 79 +380000.0 True 2 1 Centrum 67 +355000.0 False 3 0 Stare 61 +355000.0 False 3 0 Podolany 61 +430000.0 False 4 0 Stare 75 +430000.0 False 4 0 Podolany 75 +475000.0 False 4 0 Stare 72 +475000.0 False 4 0 Podolany 72 +455000.0 False 4 0 Stare 72 +455000.0 False 4 0 Podolany 72 +495000.0 False 4 0 Stare 7 +495000.0 False 4 0 Podolany 7 +652100.0 False 4 3 Stare 79 +476200.0 False 3 1 Stare 59 +476200.0 False 3 1 Chwaliszewo 59 +349700.0 False 2 2 Stare 15 +349700.0 False 2 2 Centrum 15 +340000.0 True 3 0 Stare 80 +555000.0 True 5 3 Piątkowo 125 +255000.0 True 2 2 Dębiec 48 +295000.0 True 3 2 Os 20 +295000.0 True 3 2 Os 20 +210000.0 True 2 0 Wilda 36 +239000.0 True 2 1 Grunwald 60 +269000.0 True 2 1 Stare 70 +460040.0 False 3 5 Grunwald 20 +399000.0 False 5 0 Szczepankowo 68 +372651.0 True 2 1 Stare 5 +349668.0 True 2 2 Stare 15 +282390.0 True 2 3 Stare 64 +597184.0 True 2 4 Stare 61 +320000.0 True 2 1 Grunwald 30 +269000.0 True 2 16 Rataje 49 +359000.0 True 2 1 Jeżyce 40 +285000.0 True 3 0 Dębiec 50 +290000.0 True 2 3 Stare 60 +320000.0 True 3 1 Grunwald 78 +344000.0 True 2 2 Wilczak 50 +395000.0 True 2 1 Stare 30 +299000.0 True 2 0 Dębiec 52 +495000.0 True 4 3 Jeżyce 107 +319000.0 True 2 1 Grunwald 52 +395000.0 True 2 1 Naramowice 30 +319000.0 True 2 1 Grunwald 52 +269000.0 True 2 0 Grunwald 46 +380000.0 True 4 6 Piątkowo 90 +297297.0 False 2 4 Podolany 82 +33760350.0 False 3 4 Podolany 71 +420000.0 True 3 1 Stare 60 +3559725.0 False 3 4 Podolany 85 +3559725.0 False 3 4 Podolany 85 +259000.0 True 2 1 Stare 60 +465000.0 True 3 3 Nowe 71 +282994.0 False 2 0 Starołęka 59 +300680.0 False 2 2 Starołęka 54 +349000.0 False 4 0 Szczepankowo 29 +277823.0 False 2 2 Podolany 70 +424377.0 False 4 2 Starołęka 14 +282944.0 False 2 0 Starołęka 59 +380000.0 True 3 3 Piątkowo 90 +270000.0 True 3 1 Starołęka 30 +365000.0 True 2 2 Grunwald 51 +550000.0 True 3 2 Stare 101 +300000.0 True 2 1 Naramowice 52 +450000.0 True 4 1 Grunwald 113 +490000.0 True 4 0 Naramowice 40 +216500.0 True 2 3 Nowe 30 +244071.0 True 2 1 Nowe 93 +192750.0 True 2 1 Nowe 55 +156562.0 True 2 1 Nowe 54 +350000.0 True 4 4 Piątkowo 76 +329000.0 True 3 3 Piątkowo 60 +298000.0 True 2 4 Wilda 45 +374000.0 True 3 4 Wilczak 30 +460000.0 True 2 2 Centrum 56 +288000.0 True 3 4 Winogrady 30 +400000.0 True 2 1 Świerczewo 60 +220000.0 True 2 4 Grunwald 43 +290000.0 True 2 4 Grunwald 53 +298000.0 True 2 4 Wilda 45 +439000.0 True 2 3 Jeżyce 60 +237000.0 True 2 2 Dębiec 44 +180000.0 True 3 2 Wilda 35 +330000.0 True 2 1 Jeżyce 50 +348000.0 True 3 9 Rataje 65 +439000.0 True 4 2 Grunwald 89 +269000.0 True 2 6 Rataje 70 +360000.0 True 3 3 Stare 63 +1000000.0 True 4 1 Centrum 103 +649400.0 False 3 4 Rataje 50 +311570.0 False 2 4 Rataje 51 +386883.0 False 3 4 Rataje 7 +383928.0 False 3 3 Rataje 46 +294906.0 False 2 3 Rataje 74 +309741.0 False 2 3 Rataje 89 +295734.0 False 2 3 Rataje 86 +384540.0 False 3 3 Rataje 55 +377947.0 False 3 2 Rataje 41 +310707.0 False 2 2 Rataje 3 +296631.0 False 2 2 Rataje 99 +380091.0 False 3 2 Rataje 73 +375672.0 False 3 1 Rataje 92 +293352.0 False 2 1 Rataje 14 +307156.0 False 2 1 Rataje 17 +293352.0 False 2 1 Rataje 14 +535000.0 True 2 3 Łazarz 59 +375606.0 False 3 1 Rataje 91 +293488.0 False 3 0 Rataje 94 +293488.0 False 2 0 Rataje 57 +260000.0 True 2 3 Rataje 38 +307428.0 False 2 0 Rataje 21 +293488.0 False 2 0 Rataje 16 +375408.0 False 3 0 Rataje 88 +325000.0 True 2 0 Rataje 47 +405000.0 True 3 2 Rataje 70 +360000.0 True 3 2 Rataje 20 +275000.0 True 2 13 Rataje 49 +410000.0 True 2 5 Rataje 30 +243828.0 False 2 4 Podolany 68 +398853.0 False 3 3 Podolany 18 +421258.0 False 4 3 Podolany 1 +348835.0 False 3 3 Podolany 63 +273546.0 False 2 3 Podolany 76 +256171.0 False 2 3 Podolany 79 +298116.0 False 2 3 Podolany 96 +306247.0 False 2 3 Podolany 35 +337602.0 False 3 3 Podolany 71 +357084.0 False 3 3 Podolany 4 +244647.0 False 2 3 Podolany 82 +641000.0 True 3 3 Łazarz 75 +277000.0 True 2 10 Nowe 80 +450000.0 True 2 2 Grunwald 70 +242000.0 True 2 1 Grunwald 52 +310000.0 True 3 4 Jeżyce 50 +475000.0 True 3 4 Wilda 66 +475000.0 True 3 4 Wilda 66 +120000.0 True 3 3 Grunwald 35 +120000.0 True 3 3 Grunwald 35 +1850000.0 True 5 1 Grunwald 196 +350000.0 True 4 4 Grunwald 50 +280000.0 True 4 4 Grunwald 40 +490000.0 True 4 4 Grunwald 70 +495000.0 True 3 1 Naramowice 70 +545000.0 True 3 0 Rataje 71 +310000.0 True 3 10 Rataje 80 +209000.0 True 2 0 Wilda 36 +295000.0 True 2 4 Garbary 33 +200000.0 True 2 8 Dębiec 50 +359900.0 True 4 4 Rataje 74 +320000.0 True 3 3 Jeżyce 70 +300000.0 True 2 1 Naramowice 23 +535000.0 True 4 2 Wilda 120 +620000.0 True 3 2 Naramowice 60 +495000.0 True 4 1 Naramowice 10 +240000.0 True 2 10 Rataje 36 +597000.0 True 3 0 Naramowice 60 +260000.0 True 2 0 Rataje 40 +399000.0 True 3 0 Winogrady 62 +275000.0 True 3 7 Wilda 20 +350000.0 True 2 2 Piątkowo 50 +429000.0 True 3 0 Grunwald 75 +380000.0 True 3 8 Rataje 80 +295000.0 True 2 1 Rataje 30 +339000.0 True 3 1 Rataje 88 +382000.0 True 3 3 Centrum 30 +299000.0 True 2 2 Sołacz 58 +499000.0 True 3 1 Grunwald 64 +549000.0 True 3 2 Jeżyce 106 +239000.0 True 2 1 Grunwald 36 +295000.0 True 3 2 Grunwald 49 +470000.0 True 4 2 Sołacz 87 +413000.0 True 3 3 Łazarz 46 +259000.0 True 2 1 Jeżyce 47 +348000.0 True 3 9 Nowe 65 +259000.0 True 2 0 Ławica 60 +269000.0 True 2 9 Rataje 49 +224000.0 True 2 0 Łazarz 50 +260000.0 True 3 4 Grunwald 49 +315000.0 True 3 0 Piątkowo 60 +379999.0 True 3 3 Wilda 67 +350000.0 True 2 1 Rataje 63 +270000.0 True 2 4 Grunwald 38 +250000.0 True 3 3 Rataje 53 +439000.0 True 4 2 Łazarz 92 +499000.0 True 3 1 Rataje 50 +290000.0 True 2 2 Dębiec 66 +320000.0 True 2 4 Łazarz 80 +379000.0 True 3 0 Wilda 67 +399000.0 True 3 2 Dębiec 91 +220000.0 True 2 4 Grunwald 43 +268000.0 True 3 4 Jeżyce 50 +399000.0 True 3 1 Bonin 68 +329000.0 True 3 4 Rataje 63 +353457.0 False 2 3 Stare 16 +347900.0 True 3 3 Nowe 10 +237000.0 True 2 2 Dębiec 44 +399000.0 True 3 1 Sołacz 66 +488000.0 True 3 3 Grunwald 70 +220000.0 True 2 4 Grunwald 43 +390000.0 True 3 2 Podolany 68 +299000.0 True 2 0 Wilda 52 +320000.0 True 3 4 Winogrady 50 +370000.0 True 4 4 Piątkowo 73 +339000.0 True 3 9 Rataje 65 +348000.0 True 3 9 Rataje 65 +420000.0 False 4 0 Grunwald 82 +495000.0 True 4 1 Stare 98 +329000.0 True 2 1 Stare 54 +699000.0 True 3 2 Stare 92 +487000.0 True 3 0 Stare 73 +375000.0 True 3 0 Naramowice 69 +270000.0 True 3 4 Rataje 48 +230000.0 True 2 1 Dębiec 38 +498000.0 True 4 4 Centrum 85 +390000.0 True 3 2 Podolany 68 +330000.0 True 4 2 Rataje 62 +299000.0 True 3 6 Jeżyce 70 +270000.0 True 3 4 Rataje 48 +390000.0 True 3 2 Podolany 68 +269000.0 True 2 2 Sołacz 49 +270000.0 True 3 4 Rataje 48 +232034.0 True 2 1 Starołęka 86 +265000.0 True 2 4 Winiary 10 +475000.0 True 2 4 Centrum 54 +585000.0 True 4 1 Piątkowo 100 +260000.0 True 2 0 Naramowice 46 +350000.0 True 4 4 Stare 76 +430000.0 True 2 5 Wilda 57 +366770.0 True 3 1 Winogrady 10 +285200.0 True 2 1 Winogrady 46 +319055.0 True 3 3 Grunwald 21 +307881.0 True 3 0 Grunwald 16 +267702.0 True 2 2 Grunwald 22 +239592.0 True 2 5 Grunwald 59 +375529.0 False 2 3 Stare 71 +247705.0 False 2 1 Podolany 74 +247705.0 False 2 1 Piątkowo 74 +411684.0 False 3 3 Winogrady 17 +349000.0 False 4 0 Szczepankowo 29 +277823.0 False 2 2 Podolany 70 +424377.0 False 4 2 Starołęka 14 +282944.0 False 2 0 Starołęka 59 +270000.0 True 3 0 Grunwald 48 +350000.0 True 4 1 Wilda 80 +340000.0 True 4 4 Winogrady 90 +599000.0 True 4 4 Centrum 109 +369000.0 True 3 0 Wilda 30 +549000.0 True 3 3 Grunwald 60 +345865.0 True 3 2 Jeżyce 21 +261000.0 True 2 2 Jeżyce 57 +410000.0 True 3 2 Jeżyce 74 +339000.0 True 2 2 Centrum 53 +399000.0 True 3 1 Grunwald 65 +410000.0 True 2 2 Jeżyce 74 +295000.0 True 2 2 Raszyn 50 +240000.0 True 2 16 Rataje 36 +250000.0 True 2 4 Rataje 23 +245000.0 True 2 4 Rataje 44 +269000.0 True 2 9 Rataje 49 +240000.0 True 2 2 Dębiec 48 +262000.0 True 2 4 Grunwald 60 +349000.0 True 3 1 Grunwald 57 +365000.0 True 3 1 Rataje 67 +409000.0 True 3 1 Malta 90 +298000.0 True 2 1 Łazarz 55 +599000.0 True 3 3 Grunwald 83 +289000.0 True 2 2 Jeżyce 42 +390000.0 True 3 3 Naramowice 48 +270000.0 True 2 2 Bonin 49 +250000.0 True 2 0 Naramowice 40 +350000.0 True 3 1 Naramowice 51 +270000.0 True 2 2 Sołacz 49 +260000.0 True 2 0 Rataje 46 +339000.0 True 3 9 Rataje 65 +348000.0 True 3 9 Rataje 65 +329000.0 True 3 2 Rataje 59 +230000.0 True 2 1 Dębiec 37 +238000.0 True 2 2 Grunwald 37 +392000.0 True 4 0 Piątkowo 74 +200000.0 True 2 0 Rataje 30 +370000.0 True 4 2 Piątkowo 74 +347000.0 True 3 1 Naramowice 47 +432000.0 True 2 5 Centrum 40 +435000.0 True 3 1 Piątkowo 84 +389000.0 True 2 1 Podolany 46 +799999.0 True 3 1 Sołacz 90 +248000.0 True 3 0 Jeżyce 74 +266000.0 True 2 2 Piątkowo 49 +316498.0 True 2 2 Stare 77 +519000.0 True 3 1 Rataje 50 +442150.0 True 2 2 Stare 75 +395000.0 True 3 2 Centrum 74 +599000.0 True 2 1 Centrum 70 +550.0 True 5 3 Naramowice 15 +499000.0 True 3 0 Grunwald 10 +499000.0 True 3 0 Grunwald 10 +459000.0 True 2 1 Centrum 48 +365000.0 True 3 2 Jeżyce 50 +375000.0 True 3 2 Jeżyce 50 +450000.0 True 3 11 Jeżyce 50 +289000.0 True 2 4 Ogrody 41 +230000.0 True 2 5 Winogrady 60 +440000.0 True 2 4 Centrum 55 +599000.0 True 3 2 Centrum 80 +343200.0 True 3 4 Winogrady 52 +435000.0 True 3 5 Wilda 70 +385000.0 True 2 1 Centrum 60 +300000.0 True 3 3 Centrum 88 +550000.0 True 3 1 Junikowo 84 +529000.0 True 4 4 Centrum 85 +460000.0 True 4 2 Bonin 87 +335000.0 True 3 3 Wilda 82 +405000.0 True 4 2 Nowe 71 +379000.0 True 3 0 Wilda 67 +379000.0 True 3 3 Winiary 55 +360000.0 True 3 4 Rataje 69 +495000.0 True 4 1 Grunwald 64 +285000.0 True 2 3 Wilda 60 +379999.0 True 3 3 Wilda 67 +370000.0 True 2 13 Rataje 67 +700000.0 True 4 1 Górczyn 160 +479000.0 True 3 3 Górczyn 70 +385000.0 True 3 0 Łazarz 80 +550000.0 True 4 1 Łazarz 50 +260000.0 True 3 4 Grunwald 47 +755000.0 True 4 2 Łazarz 90 +319000.0 True 2 0 Górczyn 54 +485000.0 True 2 2 Centrum 55 +485000.0 True 2 2 Centrum 55 +576500.0 True 2 5 Centrum 50 +576500.0 True 2 5 Chwaliszewo 50 +339000.0 True 2 5 Górczyn 41 +438503.0 True 3 2 Centrum 57 +419000.0 True 2 0 Rataje 55 +354454.0 False 2 3 Grunwald 17 +363258.0 False 2 1 Górczyn 59 +489780.0 False 4 2 Górczyn 63 +491520.0 False 4 1 Górczyn 92 +273875.5 False 2 1 Grunwald 13 +267000.0 True 2 2 Dębiec 35 +260000.0 True 2 2 Piątkowo 90 +587000.0 True 4 3 Łazarz 38 +460000.0 True 3 1 Naramowice 110 +695000.0 True 4 1 Rataje 70 +506657.0 True 4 11 Grunwald 73 +338325.0 True 2 13 Grunwald 5 +249641.0 True 2 0 Ogrody 54 +298250.0 True 2 5 Grunwald 38 +297421.0 True 2 2 Grunwald 24 +275000.0 True 2 9 Nowe 38 +249641.0 True 2 0 Jeżyce 54 +344141.0 True 2 8 Winogrady 47 +318384.0 True 3 6 Jeżyce 24 +269984.0 True 3 4 Winogrady 76 +447000.0 True 3 4 Grunwald 20 +450000.0 True 3 2 Strzeszyn 70 +690000.0 True 4 5 Górczyn 25 +334000.0 True 2 4 Sołacz 50 +289476.0 False 2 3 Jeżyce 84 +533745.0 False 5 2 Starołęka 4 +333694.0 False 3 1 Podolany 32 +333694.0 False 3 1 Piątkowo 38 +310000.0 True 2 2 Centrum 74 +310000.0 True 2 1 Grunwald 52 +250000.0 True 2 2 Łazarz 36 +265000.0 True 2 4 Jeżyce 43 +558745.0 False 3 3 Stare 62 +298000.0 True 2 5 Centrum 50 +347090.0 False 3 1 Winogrady 90 +362459.0 False 3 0 Starołęka 80 +754000.0 True 7 1 Stare 116 +247705.0 False 2 1 Podolany 74 +313000.0 True 2 4 Piątkowo 49 +339000.0 True 3 8 Nowe 78 +207000.0 True 2 2 Wilda 33 +295000.0 True 2 4 Grunwald 50 +330000.0 True 3 0 Jeżyce 78 +324500.0 True 2 5 Wilda 65 +429000.0 True 3 4 Wilda 47 +275000.0 True 2 9 Rataje 38 +365000.0 True 4 1 Nowe 54 +259000.0 True 2 6 Winogrady 38 +369000.0 True 2 3 Piątkowo 60 +414225.0 True 3 3 Centrum 23 +269000.0 True 3 3 Winogrady 48 +320000.0 True 2 3 Rataje 20 +288465.0 True 2 1 Starołęka 77 +321845.0 False 3 1 Grunwald 55 +389000.0 True 3 4 Piątkowo 16 +289000.0 True 2 7 Winiary 80 +249000.0 True 2 0 Komorniki 53 +391729.0 True 3 2 Winogrady 21 +285383.0 True 2 1 Winogrady 37 +228144.0 True 3 2 Nowe 56 +204450.0 True 2 1 Nowe 33 +496573.0 False 3 2 Stare 78 +286000.0 True 2 5 Centrum 49 +269000.0 True 2 1 Ogrody 50 +114642.0 True 2 0 Łazarz 46 +286000.0 True 2 5 Centrum 49 +390000.0 True 2 0 Świerczewo 60 +320000.0 True 4 1 Jeżyce 40 +706655.0 False 3 2 Nowe 45 +754000.0 False 5 0 Morasko 42 +259000.0 True 3 4 Winogrady 60 +289000.0 True 2 7 Winogrady 80 +350000.0 True 3 0 Rataje 63 +260000.0 True 2 1 Łazarz 54 +319990.0 True 2 3 Jeżyce 70 +228144.0 False 3 2 Głuszyna 56 +156085.0 False 2 2 Głuszyna 45 +350000.0 True 4 4 Stare 60 +394000.0 False 4 0 Szczepankowo 77 +287882.0 False 2 1 Starołęka 85 +445000.0 True 4 3 Piątkowo 65 +229000.0 True 2 1 Grunwald 16 +220000.0 True 2 3 Jeżyce 37 +285000.0 True 3 2 Antoninek 61 +550000.0 True 3 1 Jeżyce 73 +504326.0 True 4 4 Stare 26 +371930.0 True 4 2 Jeżyce 57 +255000.0 True 3 2 Grunwald 20 +279000.0 True 2 3 Piątkowo 30 +325000.0 True 2 0 Nowe 80 +604395.0 True 5 1 Wilda 31 +558000.0 True 5 1 Wilda 2 +1007500.0 False 4 1 Starołęka 94 +1203616.0 False 5 0 Starołęka 71 +298980.0 False 2 5 Winogrady 30 +263140.0 False 2 0 Naramowice 5 +281988.0 False 2 7 Naramowice 76 +349000.0 False 4 0 Szczepankowo 29 +277823.0 False 2 2 Podolany 70 +424377.0 False 4 2 Starołęka 14 +282944.0 False 2 0 Starołęka 59 +282944.0 False 2 0 Starołęka 59 +349668.0 False 2 2 Stare 15 +321904.0 False 2 4 Winogrady 92 +367000.0 True 3 1 Centrum 30 +350000.0 True 3 1 Nowe 63 +350000.0 True 2 1 Rataje 63 +399000.0 True 3 5 Grunwald 98 +429000.0 True 3 3 Centrum 102 +451000.0 True 3 2 Wilda 30 +565000.0 True 4 0 Sołacz 90 +285000.0 True 3 2 Antoninek 61 +350000.0 True 2 1 Rataje 54 +299000.0 True 2 5 Centrum 50 +269000.0 True 2 9 Rataje 49 +249000.0 True 2 2 Grunwald 46 +285000.0 True 3 2 Antoninek 10 +250000.0 True 2 4 Wilda 54 +269000.0 True 3 1 Wilda 68 +350000.0 True 4 4 Piątkowo 76 +360000.0 True 3 1 Grunwald 49 +260000.0 True 2 0 Rataje 46 +350000.0 True 2 4 Jeżyce 56 +263000.0 True 2 1 Rataje 44 +285000.0 True 2 2 Centrum 52 +285000.0 True 2 2 Łazarz 52 +429000.0 True 4 2 Grunwald 92 +211190.0 False 2 0 Podolany 78 +219000.0 True 2 3 Wilda 40 +820000.0 True 4 1 Grunwald 133 +299000.0 True 2 1 Centrum 11 +288000.0 True 2 4 Naramowice 44 +820000.0 True 4 1 Grunwald 133 +470000.0 True 4 2 Sołacz 87 +364000.0 True 3 4 Nowe 90 +706655.0 False 3 2 Nowe 45 +425000.0 True 3 1 Rataje 70 +248000.0 True 2 2 Winogrady 80 +260000.0 True 3 10 Śródka 48 +289000.0 True 2 0 Grunwald 80 +389000.0 True 3 4 Nowe 84 +253000.0 True 2 0 Łazarz 10 +449000.0 False 5 0 Szczepankowo 68 +225288.0 False 2 1 Rataje 91 +389528.0 False 2 2 Stare 87 +481903.0 False 3 2 Stare 53 +349000.0 False 4 0 Szczepankowo 29 +534523.0 False 3 2 Stare 62 +465538.0 False 3 1 Stare 78 +263000.0 True 2 0 Wilda 75 +370000.0 True 4 4 Piątkowo 76 +305000.0 True 3 3 Winogrady 60 +180000.0 True 3 2 Wilda 35 +189000.0 True 2 4 Wilda 35 +357692.0 False 3 2 Starołęka 31 +282994.0 False 2 0 Starołęka 59 +211190.0 False 2 0 Piątkowo 78 +349000.0 False 4 0 Szczepankowo 29 +277823.0 False 2 2 Podolany 70 +424377.0 False 4 2 Starołęka 14 +282944.0 False 2 0 Starołęka 59 +282944.0 False 2 0 Starołęka 59 +245000.0 True 2 7 Rataje 44 +570000.0 True 4 0 Jeżyce 90 +720000.0 True 4 7 Jeżyce 90 +237000.0 True 2 2 Dębiec 44 +329000.0 True 3 3 Piątkowo 60 +270000.0 True 3 3 Stare 47 +487000.0 True 3 0 Naramowice 83 +271000.0 True 2 3 Stare 37 +372000.0 False 4 1 Grunwald 87 +487000.0 True 3 0 Stare 11 +326000.0 True 2 1 Sołacz 39 +270000.0 True 2 10 Śródka 48 +349000.0 True 3 3 Rataje 63 +285000.0 True 2 2 Grunwald 52 +262500.0 True 4 0 Wilda 75 +350000.0 True 2 1 Rataje 80 +199000.0 True 2 3 Grunwald 35 +349000.0 False 4 0 Szczepankowo 29 +250000.0 True 2 3 Wilda 10 +234000.0 True 2 7 Wilda 46 +210000.0 True 2 1 Wilda 65 +249000.0 True 2 10 Grunwald 43 +469000.0 True 2 1 Winogrady 30 +235000.0 True 2 0 Nowe 10 +265000.0 True 2 0 Centrum 40 +329000.0 True 3 13 Rataje 65 +265000.0 True 2 2 Piątkowo 70 +350000.0 True 3 0 Stare 10 +307000.0 True 2 4 Stare 49 +315000.0 True 3 0 Stare 63 +350000.0 True 3 0 Rataje 63 +690000.0 True 2 1 Stare 20 +423000.0 True 2 2 Wilda 49 +250000.0 True 2 6 Grunwald 31 +292000.0 True 3 2 Winogrady 47 +249000.0 True 2 10 Grunwald 42 +350000.0 True 2 3 Rataje 52 +780000.0 True 3 0 Grunwald 87 +1000000.0 True 15 5 Wilda 50 +535000.0 True 2 2 Centrum 55 +285200.0 True 2 0 Stare 46 +434201.0 True 4 1 Nowe 54 +344152.0 True 3 0 Nowe 80 +396000.0 True 3 1 Wilda 50 +240000.0 True 2 16 Rataje 36 +390000.0 True 3 4 Piątkowo 74 +288000.0 True 2 4 Naramowice 22 +518000.0 True 4 0 Wilda 41 +320000.0 True 4 3 Stare 40 +449000.0 True 5 3 Wilda 97 +249000.0 True 2 10 Grunwald 42 +289000.0 True 3 4 Winogrady 48 +289000.0 True 2 7 Jeżyce 80 +330715.0 True 2 2 Wilda 13 +97000.0 True 2 4 Wilda 80 +285000.0 True 2 2 Łazarz 20 +389000.0 True 3 4 Piątkowo 69 +249000.0 True 2 4 Rataje 44 +409000.0 True 3 1 Rataje 62 +240000.0 True 2 2 Dębiec 48 +289000.0 True 3 4 Stare 47 +270000.0 True 3 10 Grunwald 52 +389000.0 True 3 4 Piątkowo 69 +179000.0 True 2 0 Grunwald 34 +364000.0 False 3 6 Grunwald 64 +410000.0 True 2 4 Jeżyce 43 +590000.0 True 3 3 Jeżyce 30 +325000.0 True 3 2 Jeżyce 64 +398000.0 True 3 3 Łazarz 96 +255000.0 True 2 2 Wilda 72 +329000.0 True 2 1 Naramowice 40 +290000.0 True 2 6 Winiary 49 +319875.0 False 2 8 Grunwald 18 +356251.9 False 3 13 Grunwald 20 +319875.0 False 2 7 Grunwald 18 +350557.33 False 2 13 Grunwald 58 +338325.0 False 2 13 Grunwald 5 +329763.26 False 2 9 Grunwald 94 +324400.97 False 2 7 Grunwald 94 +388352.0 False 3 7 Grunwald 60 +347633.0 False 3 10 Grunwald 20 +409713.0 False 3 11 Grunwald 62 +330368.0 False 2 12 Grunwald 62 +347839.75 False 2 12 Grunwald 58 +347193.22 False 3 11 Grunwald 7 +350506.16 False 3 11 Grunwald 20 +342405.13 False 2 11 Grunwald 58 +319875.0 False 2 9 Grunwald 18 +341703.96 False 3 8 Grunwald 21 +336969.98 False 2 10 Grunwald 58 +413044.0 False 3 12 Grunwald 62 +341703.96 False 3 9 Grunwald 21 +325206.0 False 2 10 Grunwald 62 +338111.0 False 2 15 Grunwald 62 +424977.14 False 4 5 Grunwald 20 +327787.0 False 2 11 Grunwald 62 +353378.74 False 3 12 Grunwald 20 +332949.0 False 2 13 Grunwald 62 +383760.0 False 3 6 Grunwald 60 +335530.0 False 2 14 Grunwald 62 +387040.0 False 3 5 Grunwald 60 +302985.6 False 2 4 Grunwald 18 +421375.5 False 4 4 Grunwald 20 +410780.0 False 3 3 Grunwald 44 +417773.83 False 4 3 Grunwald 20 +303286.5 False 2 3 Grunwald 13 +302038.4 False 2 3 Grunwald 2 +319055.27 False 3 3 Grunwald 21 +414352.0 False 3 4 Grunwald 44 +417807.03 False 4 4 Grunwald 7 +414172.54 False 4 2 Grunwald 20 +352390.0 False 2 12 Grunwald 80 +377200.0 False 3 3 Grunwald 60 +314089.0 False 2 5 Grunwald 49 +339072.0 False 2 9 Grunwald 98 +321812.5 False 2 8 Grunwald 49 +500203.02 False 4 10 Grunwald 73 +355080.0 False 2 13 Grunwald 80 +325184.0 False 2 11 Grunwald 81 +297420.8 False 2 3 Grunwald 24 +506566.5 False 4 11 Grunwald 73 +335722.5 False 2 12 Grunwald 5 +349700.0 False 2 11 Grunwald 80 +330517.5 False 2 10 Grunwald 5 +495722.51 False 4 9 Grunwald 99 +426416.8 False 4 6 Grunwald 20 +327081.85 False 2 8 Grunwald 94 +307080.0 False 2 5 Grunwald 18 +305793.0 False 2 4 Grunwald 13 +380480.0 False 3 4 Grunwald 60 +312198.0 False 2 6 Grunwald 18 +410665.2 False 4 2 Grunwald 7 +333231.99 False 3 7 Grunwald 21 +514939.5 False 4 13 Grunwald 73 +317880.0 False 2 2 Grunwald 98 +510753.0 False 4 12 Grunwald 73 +333120.0 False 2 11 Grunwald 5 +324387.0 False 2 9 Grunwald 49 +311514.5 False 2 4 Grunwald 49 +495722.51 False 4 8 Grunwald 99 +331125.0 False 2 5 Grunwald 98 +495782.26 False 4 7 Grunwald 99 +328476.0 False 2 4 Grunwald 98 +316848.0 False 2 6 Grunwald 52 +442803.77 False 4 5 Grunwald 7 +315819.0 False 2 5 Grunwald 13 +293436.18 False 2 1 Grunwald 15 +435784.0 False 3 5 Grunwald 44 +414235.76 False 4 3 Grunwald 7 +407208.0 False 3 2 Grunwald 44 +579000.0 True 4 3 Naramowice 97 +410000.0 True 2 5 Rataje 53 +199000.0 True 2 4 Grunwald 20 +375000.0 True 2 3 Grunwald 51 +350000.0 True 3 0 Naramowice 59 +289000.0 True 3 4 Winogrady 47 +240000.0 True 2 16 Rataje 36 +350000.0 True 3 1 Naramowice 51 +238000.0 True 3 2 Warszawskie 48 +277823.0 False 2 2 Podolany 70 +372000.0 True 4 1 Nadolnik 125 +410000.0 True 2 5 Rataje 53 +249000.0 True 2 4 Rataje 44 +420000.0 True 2 1 Naramowice 50 +420000.0 True 2 3 Naramowice 50 +339000.0 True 2 2 Stare 53 +298000.0 True 3 1 Nowe 30 +250000.0 True 3 0 Stare 45 +475000.0 True 4 4 Naramowice 50 +329000.0 True 3 1 Jeżyce 112 +439000.0 True 3 3 Grunwald 10 +250000.0 True 2 6 Winogrady 42 +259000.0 True 3 1 Grunwald 48 +375000.0 True 2 7 Piątkowo 90 +295000.0 True 2 7 Stare 10 +370000.0 True 4 4 Piątkowo 60 +325000.0 True 3 3 Łazarz 62 +375000.0 True 3 1 Nowe 63 +390000.0 True 4 4 Piątkowo 74 +288000.0 True 3 4 Stare 30 +468000.0 True 2 3 Grunwald 60 +250000.0 True 2 6 Winogrady 42 +350000.0 True 2 2 Jeżyce 46 +292000.0 True 3 2 Winogrady 30 +310000.0 True 2 1 Nowe 40 +289000.0 True 3 4 Winogrady 47 +405900.0 True 3 2 Stare 82 +149000.0 True 3 5 Nowe 56 +326000.0 True 2 1 Sołacz 39 +350000.0 True 2 2 Jeżyce 47 +224343.0 False 2 4 Starołęka 35 +362220.0 False 3 3 Starołęka 60 +287394.0 False 2 2 Starołęka 50 +320739.0 False 3 1 Starołęka 56 +177000.0 True 2 2 Dębiec 25 +313000.0 True 2 1 Górczyn 48 +313000.0 True 2 1 Dębiec 48 +429000.0 True 3 4 Rataje 79 +643720.0 True 4 0 Stare 60 +325000.0 True 2 3 Stare 60 +319000.0 True 2 0 Grunwald 20 +364000.0 True 3 1 Nowe 67 +285000.0 True 2 2 Łazarz 52 +339000.0 True 2 2 Centrum 53 +279000.0 True 2 0 Naramowice 43 +350000.0 True 2 4 Jeżyce 53 +419000.0 True 3 1 Piątkowo 74 +195000.0 True 2 3 Zawady 35 +390000.0 True 2 0 Centrum 60 +177000.0 True 2 2 Dębiec 70 +279000.0 True 2 1 Stare 60 +489000.0 True 4 2 Wilda 120 +299000.0 True 2 1 Jeżyce 32 +205000.0 True 2 4 Wilda 27 +362000.0 True 2 1 Centrum 50 +285000.0 True 2 2 Łazarz 52 +998000.0 True 6 2 Stare 161 +259000.0 True 3 2 Grunwald 45 +439000.0 True 2 3 Rataje 53 +550000.0 True 4 1 Górczyn 90 +310000.0 True 3 10 Nowe 40 +355000.0 True 3 2 Stare 64 +252000.0 True 2 9 Grunwald 50 +659000.0 True 3 2 Nowe 60 +307000.0 True 2 4 Piątkowo 49 +347900.0 True 3 3 Nowe 10 +229000.0 True 2 3 Stare 56 +569000.0 True 4 0 Wilda 50 +136000.0 True 2 1 Nowe 43 +102500.0 True 2 3 Nowe 80 +485000.0 True 4 2 Grunwald 89 +360000.0 True 3 3 Nowe 63 +339000.0 True 3 3 Stare 90 +285000.0 True 2 0 Łazarz 49 +299000.0 True 2 1 Centrum 52 +429999.0 True 3 3 Centrum 20 +429999.0 True 3 3 Centrum 20 +395000.0 True 3 3 Wilda 75 +307000.0 True 2 4 Piątkowo 49 +326000.0 True 2 4 Łazarz 80 +382280.0 True 3 3 Centrum 50 +233239.0 False 2 2 Podolany 87 +400608.0 False 3 2 Podolany 48 +422604.0 False 4 2 Podolany 24 +350064.0 False 3 2 Podolany 84 +349420.0 False 3 2 Podolany 73 +275008.0 False 2 2 Podolany 1 +255762.0 False 2 2 Podolany 72 +257400.0 False 2 2 Podolany 44 +307710.0 False 2 2 Podolany 60 +338188.0 False 3 2 Podolany 81 +258336.0 False 2 2 Podolany 16 +370948.0 False 4 2 Podolany 41 +358605.0 False 3 2 Podolany 30 +245934.0 False 2 2 Podolany 4 +233941.0 False 2 1 Podolany 99 +401544.0 False 3 1 Podolany 64 +424008.0 False 4 1 Podolany 48 +350181.0 False 3 1 Podolany 86 +349537.0 False 3 1 Podolany 75 +275710.0 False 2 1 Podolany 13 +256756.0 False 2 1 Podolany 89 +258102.0 False 2 1 Podolany 12 +255000.0 True 2 3 Jeżyce 38 +300222.0 False 2 1 Podolany 22 +308412.0 False 2 1 Podolany 72 +338305.0 False 3 1 Podolany 83 +259038.0 False 2 1 Podolany 28 +371884.0 False 4 1 Podolany 57 +359541.0 False 3 1 Podolany 46 +234636.0 False 2 1 Podolany 16 +234234.0 False 2 0 Podolany 4 +401719.0 False 3 0 Podolany 67 +423715.0 False 4 0 Podolany 43 +350181.0 False 3 0 Podolany 86 +249537.0 False 3 0 Podolany 75 +276061.0 False 2 0 Podolany 19 +257341.0 False 2 0 Podolany 99 +258453.0 False 2 0 Podolany 18 +220837.0 False 2 0 Podolany 75 +419000.0 True 2 7 Grunwald 20 +419000.0 True 3 4 Wilda 60 +379000.0 True 2 3 Winogrady 48 +315000.0 True 3 0 Piątkowo 60 +339000.0 True 3 1 Rataje 67 +270000.0 True 2 4 Grunwald 38 +268000.0 True 2 5 Rataje 42 +1500000.0 True 3 5 Centrum 68 +264000.0 True 3 4 Nowe 53 +432000.0 True 4 1 Grunwald 72 +449900.0 True 3 2 Stare 81 +295000.0 True 2 1 Nowe 39 +290000.0 True 2 6 Sołacz 49 +307000.0 True 2 4 Piątkowo 49 +285000.0 True 2 3 Piątkowo 49 +285000.0 True 2 3 Wilda 60 +519000.0 True 3 1 Rataje 50 +264000.0 True 3 4 Rataje 53 +318000.0 True 2 4 Piątkowo 49 +325000.0 True 3 3 Sołacz 40 +377685.0 False 2 4 Podolany 4 +377685.0 False 3 4 Podolany 67 +423715.0 False 4 0 Podolany 43 +350181.0 False 3 0 Podolany 86 +349537.0 False 3 0 Podolany 75 +276061.0 False 2 0 Podolany 19 +242990.0 False 2 0 Podolany 18 +283645.0 False 2 0 Podolany 39 +308763.0 False 2 0 Podolany 78 +338305.0 False 3 0 Podolany 83 +480000.0 True 2 2 Centrum 56 +499000.0 True 2 2 Nowe 36 +299000.0 True 2 16 Rataje 49 +355000.0 True 3 2 Stare 64 +210000.0 True 2 0 Grunwald 52 +277098.0 True 2 0 Nowe 59 +410000.0 True 3 1 Górczyn 82 +399000.0 True 3 2 Górczyn 91 +390000.0 True 3 1 Łazarz 75 +370000.0 True 2 0 Górczyn 65 +239000.0 True 2 3 Piątkowo 59 +185000.0 True 2 8 Wilda 38 +432000.0 True 3 0 Wilda 72 +360000.0 True 3 4 Rataje 69 +259330.0 False 2 0 Podolany 33 +372996.0 False 4 0 Podolany 76 +360000.0 True 3 2 Rataje 69 +370000.0 True 4 4 Piątkowo 76 +338579.0 False 3 0 Podolany 56 +231550.0 False 2 0 Podolany 10 +325000.0 True 2 1 Jeżyce 56 +355000.0 True 2 4 Jeżyce 56 +275000.0 True 2 1 Sołacz 50 +355000.0 True 3 2 Piątkowo 66 +224000.0 True 2 0 Górczyn 50 +499000.0 True 3 1 Grunwald 65 +1300000.0 True 2 3 Wilda 90 +399000.0 True 2 4 Grunwald 49 +349999.0 True 4 4 Stare 60 +390000.0 True 3 3 Stare 48 +325000.0 True 3 4 Jeżyce 30 +360000.0 True 3 2 Rataje 69 +389000.0 True 3 4 Stare 74 +450000.0 True 3 2 Naramowice 66 +660000.0 True 4 2 Winogrady 110 +313000.0 True 2 4 Jeżyce 50 +289000.0 True 2 6 Jeżyce 86 +279000.0 True 3 3 Rataje 54 +282000.0 True 2 1 Jeżyce 38 +282000.0 True 2 1 Strzeszyn 38 +225000.0 True 2 2 Grunwald 38 +339000.0 True 3 0 Jeżyce 24 +519000.0 True 3 1 Nowe 64 +189000.0 True 2 2 Grunwald 35 +275000.0 True 3 2 Grunwald 60 +1550000.0 True 6 1 Grunwald 170 +290000.0 True 2 6 Jeżyce 49 +185000.0 True 2 8 Dębiec 80 +270000.0 True 2 4 Grunwald 38 +349000.0 True 3 0 Grunwald 60 +349000.0 True 3 0 Grunwald 60 +360000.0 True 3 2 Nowe 69 +575000.0 True 4 4 Jeżyce 94 +360000.0 True 2 1 Centrum 50 +327000.0 True 4 3 Dębiec 75 +499000.0 True 2 2 Stare 43 +379000.0 True 3 0 Rataje 56 +379000.0 True 3 3 Jeżyce 55 +359000.0 True 2 3 Rataje 48 +205000.0 True 2 2 Starołęka 40 +280000.0 True 2 1 Stare 30 +359000.0 True 3 2 Piątkowo 50 +465374.0 False 3 2 Stare 62 +250000.0 True 2 6 Sołacz 42 +237000.0 True 2 10 Grunwald 38 +365000.0 True 2 1 Centrum 50 +449000.0 True 3 1 Naramowice 89 +329000.0 True 3 7 Rataje 80 +390000.0 True 3 3 Piątkowo 48 +275000.0 True 2 2 Piątkowo 58 +365000.0 True 3 1 Stare 64 +280000.0 True 3 9 Jeżyce 48 +425000.0 True 3 0 Piątkowo 50 +1500000.0 True 3 0 Grunwald 100 +310000.0 True 2 2 Centrum 73 +235000.0 True 2 3 Grunwald 38 +286000.0 True 2 4 Centrum 49 +350000.0 True 2 4 Jeżyce 56 +225000.0 True 2 0 Górczyn 50 +360000.0 True 4 0 Piątkowo 60 +409000.0 True 3 1 Malta 90 +313000.0 True 2 4 Piątkowo 49 +259000.0 True 2 5 Grunwald 45 +279000.0 True 2 5 Centrum 42 +314900.0 True 2 2 Naramowice 41 +635000.0 True 4 3 Grunwald 70 +300000.0 True 3 1 Rataje 80 +390000.0 True 4 1 Jeżyce 70 +615000.0 True 4 1 Jeżyce 130 +525000.0 True 4 3 Jeżyce 70 +199000.0 True 2 6 Grunwald 20 +299000.0 True 3 2 Grunwald 49 +300000.0 True 3 2 Grunwald 49 +259000.0 True 2 3 Rataje 49 +375000.0 True 3 1 Rataje 62 +365000.0 True 4 1 Wilda 79 +248000.0 True 2 14 Rataje 49 +340000.0 True 2 0 Junikowo 62 +280000.0 True 3 1 Jeżyce 58 +475000.0 True 4 0 Górczyn 102 +379000.0 True 3 0 Wilda 67 +399000.0 True 4 0 Nowe 69 +404000.0 True 4 0 Nowe 69 +339000.0 True 3 13 Nowe 65 +369000.0 True 2 3 Stare 49 +370000.0 True 2 4 Rataje 80 +382280.0 True 3 3 Stare 30 +259000.0 True 2 3 Żegrze 49 +329000.0 True 3 7 Rataje 66 +410000.0 True 5 0 Łazarz 111 +295000.0 True 2 4 Wilda 35 +349000.0 True 2 2 Stare 33 +239000.0 True 2 3 Rataje 53 +275000.0 True 2 13 Rataje 49 +495000.0 True 4 1 Naramowice 98 +239000.0 True 2 0 Naramowice 80 +384000.0 True 4 0 Grunwald 93 +289000.0 True 2 2 Zawady 48 +210000.0 True 2 3 Grunwald 38 +329000.0 True 2 3 Rataje 50 +439000.0 True 4 2 Grunwald 92 +235000.0 True 2 3 Grunwald 50 +398000.0 True 2 1 Grunwald 32 +150000.0 True 2 2 Nowe 50 +650000.0 True 3 2 Centrum 101 +191000.0 True 2 0 Górczyn 42 +238000.0 True 2 8 Jeżyce 37 +550000.0 True 3 1 Grunwald 73 +210000.0 True 2 0 Grunwald 65 +308000.0 True 3 0 Jeżyce 70 +620000.0 True 4 1 Smochowice 82 +565000.0 True 4 0 Sołacz 90 +259000.0 True 2 5 Górczyn 45 +259000.0 True 2 4 Grunwald 50 +395000.0 True 4 1 Wilda 80 +300000.0 True 2 1 Centrum 8 +245000.0 True 2 2 Centrum 8 +250000.0 True 2 4 Nowe 23 +399000.0 False 5 0 Szczepankowo 77 +399000.0 False 5 0 Szczepankowo 77 +399000.0 False 5 0 Szczepankowo 77 +402000.0 False 5 0 Szczepankowo 77 +402000.0 False 5 0 Szczepankowo 77 +402000.0 False 5 0 Szczepankowo 77 +402000.0 False 5 0 Szczepankowo 77 +375000.0 True 3 4 Winogrady 65 +248000.0 True 2 14 Rataje 49 +1017445.0 False 6 8 Nowe 53 +316357.0 False 2 7 Nowe 82 +316547.0 False 2 5 Nowe 85 +316674.0 False 2 1 Nowe 87 +356933.0 False 3 1 Nowe 21 +317944.0 False 2 7 Nowe 7 +318198.0 False 2 4 Nowe 11 +318452.0 False 2 3 Nowe 15 +318452.0 False 2 2 Nowe 15 +318071.0 False 2 1 Nowe 9 +350583.0 False 3 1 Nowe 21 +603948.0 False 4 5 Nowe 11 +606171.0 False 4 3 Nowe 46 +606171.0 False 4 2 Nowe 46 +324800.0 False 2 3 Nowe 56 +324800.0 False 2 1 Nowe 56 +460184.0 False 4 7 Nowe 47 +460248.0 False 4 6 Nowe 48 +484314.0 False 4 4 Nowe 27 +484505.0 False 4 3 Nowe 30 +484505.0 False 4 2 Nowe 30 +483616.0 False 4 1 Nowe 16 +424370.0 False 4 3 Nowe 83 +424370.0 False 4 2 Nowe 83 +549211.0 False 4 1 Nowe 49 +359000.0 True 2 4 Grunwald 40 +439000.0 True 4 2 Łazarz 92 +402000.0 False 5 0 Szczepankowo 77 +327000.0 True 3 3 Stare 64 +349000.0 True 4 2 Rataje 20 +380000.0 True 3 4 Nowe 100 +300000.0 True 2 2 Winogrady 58 +339000.0 True 3 3 Stare 37 +664443.3 False 2 2 Stare 57 +308000.0 True 3 4 Rataje 70 +240000.0 True 2 6 Grunwald 42 +270000.0 True 3 0 Grunwald 48 +320000.0 True 3 8 Rataje 78 +319000.0 True 2 2 Jeżyce 55 +335400.0 True 2 1 Łazarz 52 +250000.0 True 3 3 Nowe 53 +355000.0 True 4 0 Stare 88 +360000.0 True 4 0 Grunwald 66 +495000.0 True 3 0 Centrum 63 +268900.0 True 3 10 Grunwald 56 +379000.0 True 2 3 Stare 16 +287000.0 True 2 10 Winogrady 80 +250000.0 True 2 4 Rataje 44 +279000.0 True 4 3 Rataje 62 +265000.0 True 3 0 Rataje 48 +225000.0 True 2 0 Grunwald 50 +290000.0 True 3 8 Osiedle 70 +228000.0 True 4 4 Swarzędz 64 +330000.0 True 4 0 Grunwald 50 +495000.0 True 3 1 Grunwald 64 +307000.0 True 2 4 Piątkowo 50 +225000.0 True 2 7 Ogrody 53 +340000.0 True 2 2 Naramowice 16 +245000.0 True 2 9 Rataje 38 +439000.0 True 3 3 Piątkowo 77 +499000.0 True 4 4 Stare 85 +249000.0 True 3 4 Rataje 53 +410000.0 True 5 0 Łazarz 8 +379000.0 True 2 5 Grunwald 50 +300000.0 True 3 1 Grunwald 48 +1780000.0 True 4 0 Stare 86 +459000.0 True 3 1 Grunwald 81 +450000.0 True 3 2 Stare 67 +1040000.0 True 2 10 Centrum 79 +320000.0 True 2 1 Naramowice 23 +430000.0 True 3 3 Łazarz 96 +380000.0 True 2 6 Dębiec 55 +240000.0 True 2 11 Rataje 42 +275000.0 True 2 2 Naramowice 60 +265000.0 True 2 1 Wilda 60 +515000.0 True 4 2 Jeżyce 87 +420000.0 True 4 3 Grunwald 50 +349000.0 True 2 3 Jeżyce 50 +253000.0 True 2 9 Stare 38 +259500.0 True 2 0 Łazarz 90 +460000.0 True 3 1 Antoninek 8 +379000.0 True 3 0 Rataje 57 +379000.0 True 3 0 Rataje 57 +480000.0 True 4 1 Grunwald 64 +325000.0 True 3 0 Stare 78 +379000.0 True 3 0 Nowe 56 +365000.0 True 2 1 Centrum 50 +349000.0 True 2 3 Centrum 56 +399000.0 True 2 1 Rataje 54 +420000.0 True 3 1 Jeżyce 38 +569000.0 True 4 0 Wilda 118 +302000.0 True 2 3 Winogrady 49 +460000.0 True 3 0 Grunwald 65 +450000.0 True 3 1 Grunwald 84 +269000.0 True 2 4 Rataje 40 +945000.0 True 6 2 Stare 126 +900000.0 True 6 1 Stare 120 +1845000.0 True 12 1 Stare 246 +360000.0 True 3 2 Grunwald 58 +473120.0 True 2 2 Grunwald 14 +458175.0 True 3 0 Grunwald 9 +538229.0 True 3 3 Grunwald 12 +439000.0 True 3 3 Piątkowo 70 +365000.0 True 3 2 Rataje 65 +640174.0 True 3 0 Grunwald 7 +289000.0 True 3 3 Rataje 48 +442612.0 True 2 4 Grunwald 11 +321845.0 False 3 1 Grunwald 55 +349000.0 True 3 5 Rataje 78 +439000.0 True 4 2 Grunwald 92 +395000.0 True 4 4 Stare 84 +390000.0 False 2 2 Grunwald 53 +320000.0 True 3 0 Rataje 56 +480000.0 True 2 1 Stare 44 +315000.0 True 3 1 Nowe 62 +379000.0 True 3 1 Piątkowo 78 +249000.0 True 2 4 Rataje 44 +419000.0 True 3 2 Piątkowo 20 +375000.0 True 3 4 Winogrady 65 +320000.0 True 3 6 Rataje 56 +527150.0 True 4 3 Winogrady 10 +444600.0 True 3 2 Winogrady 40 +360000.0 True 2 1 Centrum 50 +210000.0 True 2 0 Dębiec 37 +747000.0 True 3 7 Nowe 83 +760000.0 True 4 1 Stare 96 +354000.0 True 4 0 Jeżyce 71 +354000.0 True 4 0 Jeżyce 71 +595000.0 True 7 1 Jeżyce 136 +369000.0 True 3 3 Centrum 63 +279000.0 True 2 1 Naramowice 51 +379000.0 True 3 0 Rataje 57 +358000.0 True 3 2 Nowe 90 +350000.0 True 3 1 Starołęka 15 +529000.0 True 4 2 Centrum 107 +840000.0 True 4 0 Centrum 100 +311500.0 True 2 1 Wilda 89 +280000.0 True 2 5 Naramowice 41 +243656.0 True 2 1 Jeżyce 64 +259000.0 True 2 0 Grunwald 40 +260127.0 True 2 1 Ogrody 41 +210000.0 True 2 0 Dębiec 37 +417231.0 True 2 2 Stare 50 +290000.0 True 20 2 Stare 80 +209000.0 True 2 10 Rataje 38 +353000.0 True 3 2 Grunwald 52 +406100.0 True 3 2 Grunwald 61 +389000.0 True 4 0 Nowe 75 +295850.0 True 3 2 Ostrów 33 +295660.0 True 2 1 Ostrów 87 +241940.0 True 2 1 Jeżyce 51 +480000.0 True 4 4 Wilda 80 +449000.0 True 3 2 Wilda 104 +1850000.0 True 7 1 Sołacz 206 +394000.0 False 4 1 Nowe 69 +469000.0 True 3 2 Grunwald 40 +280000.0 True 3 9 Jeżyce 48 +325000.0 True 2 1 Jeżyce 56 +425000.0 True 4 6 Nowe 85 +510000.0 True 3 3 Grunwald 70 +220000.0 True 2 0 Grunwald 50 +319000.0 True 2 3 Podolany 40 +315000.0 True 3 3 Rataje 56 +234400.0 True 2 0 Górczyn 50 +235000.0 True 2 4 Winogrady 68 +229000.0 True 2 8 Winogrady 62 +820000.0 True 4 0 Jeżyce 41 +239000.0 True 2 5 Winogrady 68 +450000.0 True 3 2 Naramowice 67 +310000.0 True 2 2 Centrum 73 +239900.0 True 2 4 Rataje 38 +364520.0 False 3 1 Jeżyce 8 +285285.0 False 3 3 Jeżyce 89 +439000.0 True 3 0 Szczepankowo 77 +224000.0 True 2 0 Łazarzm 50 +820000.0 True 4 3 Centrum 59 +255200.0 True 2 0 Jeżyce 13 +253000.0 True 2 2 Jeżyce 2 +246000.0 True 2 1 Jeżyce 12 +235000.0 True 2 4 Rataje 38 +365000.0 True 4 1 Nowe 54 +299000.0 True 2 2 Grunwald 35 +319000.0 True 2 4 Łazarz 46 +263000.0 True 2 2 Dębiec 48 +1555200.0 True 4 2 Jeżyce 144 +265000.0 True 2 2 Rataje 38 +279000.0 True 2 1 Stare 60 +655000.0 True 3 4 Stare 60 +307000.0 True 2 4 Piątkowo 20 +569000.0 True 4 0 Wilda 40 +310000.0 True 3 1 Piątkowo 60 +430000.0 True 2 3 Grunwald 70 +259000.0 True 2 2 Stare 49 +487000.0 True 3 0 Naramowice 83 +298500.0 True 2 1 Jeżyce 28 +420000.0 True 5 0 Łazarz 8 +680000.0 True 3 0 Stare 89 +669000.0 True 2 0 Łazarz 70 +359000.0 True 2 2 Jeżyce 50 +299900.0 True 2 2 Jeżyce 60 +760000.0 True 5 1 Centrum 73 +604836.0 True 4 6 Grunwald 40 +263400.0 True 2 0 Grunwald 90 +340166.0 True 3 0 Grunwald 10 +480000.0 True 3 0 Rataje 69 +320000.0 True 2 3 Stare 55 +420000.0 True 3 3 Łazarz 95 +690000.0 True 5 1 Stare 100 +568000.0 True 4 0 Centrum 114 +520000.0 True 4 1 Nowe 91 +299000.0 True 2 2 Jeżyce 61 +680000.0 True 3 0 Stare 89 +290000.0 True 2 5 Winogrady 80 +177000.0 True 2 2 Wilda 34 +360000.0 True 3 4 Nowe 63 +820000.0 True 5 1 Winogrady 128 +339000.0 True 3 3 Jeżyce 80 +439000.0 True 3 3 Stare 70 +335000.0 True 3 9 Rataje 66 +599000.0 True 3 3 Górczyn 60 +720000.0 True 4 2 Grunwald 144 +263000.0 True 3 3 Grunwald 48 +270000.0 True 2 0 Jeżyce 20 +339000.0 True 3 4 Winogrady 90 +250000.0 True 2 6 Rataje 23 +340000.0 True 2 2 Garbary 48 +250000.0 True 2 1 Winogrady 38 +487000.0 True 3 0 Stare 83 +268001.0 True 2 2 Sołacz 60 +729000.0 True 4 1 Sołacz 10 +533000.0 True 3 9 Rataje 72 +325000.0 True 3 0 Wola 65 +320000.0 True 3 1 Grunwald 74 +549000.0 True 3 3 Grunwald 60 +345000.0 True 3 1 Rataje 78 +239000.0 True 3 2 Wilda 40 +425000.0 True 4 6 Rataje 90 +332339.0 False 2 5 Dolna 67 +308481.0 False 2 5 Dolna 74 +315537.0 False 2 5 Dolna 45 +319927.0 False 2 5 Dolna 49 +491139.0 False 4 5 Dolna 50 +1500000.0 True 3 5 Stare 68 +292981.0 False 2 5 Dolna 2 +309465.0 False 2 5 Dolna 56 +309838.0 False 2 5 Dolna 39 +457004.0 False 4 5 Dolna 25 +498921.0 False 4 5 Dolna 65 +296180.0 False 2 5 Dolna 47 +300204.0 False 2 5 Dolna 70 +309246.0 False 2 5 Dolna 99 +484168.0 False 3 5 Dolna 8 +306666.0 False 2 4 Dolna 45 +310923.0 False 2 4 Dolna 49 +284921.0 False 2 4 Dolna 2 +300495.0 False 2 4 Dolna 56 +301128.0 False 2 4 Dolna 39 +444872.0 False 4 4 Dolna 25 +484149.0 False 4 4 Dolna 65 +288032.0 False 2 4 Dolna 47 +291765.0 False 2 4 Dolna 70 +412908.0 False 3 4 Dolna 78 +431187.0 False 3 4 Dolna 43 +304231.0 False 2 4 Dolna 99 +469840.0 False 3 4 Dolna 8 +866623.0 False 5 3 Dolna 26 +308005.0 False 2 3 Dolna 49 +472873.0 False 4 3 Dolna 50 +282503.0 False 2 3 Dolna 2 +298253.0 False 2 3 Dolna 56 +298306.0 False 2 3 Dolna 39 +439966.0 False 4 3 Dolna 25 +480336.0 False 4 3 Dolna 65 +285180.0 False 2 3 Dolna 47 +289032.0 False 2 3 Dolna 70 +405142.0 False 3 3 Dolna 78 +750062.0 False 4 6 Wilda 42 +555180.0 False 3 6 Wilda 44 +555180.0 False 3 6 Wilda 44 +855063.0 False 5 3 Dolna 59 +750013.0 False 4 6 Wilda 69 +333852.0 False 2 5 Wilda 70 +525525.0 False 3 5 Wilda 50 +241574.0 False 2 5 Wilda 56 +466175.0 False 3 3 Dolna 8 +670380.0 False 4 5 Wilda 85 +670380.0 False 4 5 Wilda 85 +350719.0 False 2 5 Wilda 11 +399772.0 False 3 5 Wilda 98 +399772.0 False 3 5 Wilda 98 +318202.0 False 2 4 Wilda 85 +316272.0 False 2 4 Wilda 92 +292691.0 False 2 4 Wilda 61 +295370.0 False 2 4 Wilda 43 +393624.0 False 3 4 Wilda 64 +393624.0 False 3 4 Wilda 64 +295370.0 False 2 4 Wilda 43 +295370.0 False 2 4 Wilda 43 +353048.0 False 2 4 Wilda 9 +247217.0 False 2 4 Wilda 99 +316866.0 False 2 3 Wilda 1 +314355.0 False 2 3 Wilda 92 +276293.0 False 2 3 Wilda 75 +278813.0 False 2 3 Wilda 14 +385453.0 False 3 3 Wilda 64 +385453.0 False 3 3 Wilda 64 +293783.0 False 2 3 Wilda 14 +293454.0 False 2 3 Wilda 14 +351450.0 False 2 3 Wilda 25 +245769.0 False 2 3 Wilda 13 +245769.0 False 2 3 Wilda 13 +310696.0 False 2 2 Wilda 17 +311019.0 False 2 2 Wilda 22 +285966.0 False 2 2 Wilda 88 +288567.0 False 2 2 Wilda 27 +399406.0 False 3 2 Wilda 89 +288567.0 False 2 2 Wilda 27 +288567.0 False 2 2 Wilda 27 +345075.0 False 2 2 Wilda 50 +217361.0 False 2 2 Wilda 91 +309586.0 False 2 1 Wilda 32 +310826.0 False 2 1 Wilda 34 +276016.0 False 2 1 Wilda 2 +278518.0 False 2 1 Wilda 41 +384128.0 False 3 1 Wilda 2 +384128.0 False 3 1 Wilda 2 +277824.0 False 2 1 Wilda 41 +277824.0 False 2 1 Wilda 41 +344376.0 False 2 1 Wilda 75 +242751.0 False 2 1 Wilda 40 +360000.0 True 3 2 Grunwald 60 +227012.0 False 2 1 Wilda 4 +456960.0 False 3 5 Jeżyce 20 +765451.0 False 5 5 Jeżyce 81 +473754.0 False 3 5 Jeżyce 66 +445900.0 False 3 5 Jeżyce 70 +310170.0 False 2 5 Jeżyce 31 +747600.0 False 5 5 Jeżyce 80 +558693.0 False 4 5 Jeżyce 97 +558486.0 False 4 5 Jeżyce 94 +497628.0 False 3 5 Jeżyce 12 +412297.0 False 2 5 Jeżyce 7 +392231.0 False 2 5 Jeżyce 26 +332253.0 False 3 5 Jeżyce 59 +310170.0 False 3 5 Jeżyce 31 +413236.0 False 3 5 Jeżyce 77 +459151.0 False 3 4 Jeżyce 53 +388600.0 False 3 4 Jeżyce 58 +357204.0 False 3 4 Jeżyce 53 +542365.0 False 4 4 Jeżyce 95 +406065.0 False 3 4 Jeżyce 85 +368628.0 False 3 4 Jeżyce 21 +362372.0 False 3 4 Jeżyce 29 +257250.0 False 2 4 Jeżyce 75 +542298.0 False 4 4 Jeżyce 94 +485013.0 False 3 4 Jeżyce 39 +413567.0 False 3 4 Jeżyce 14 +370260.0 False 3 4 Jeżyce 45 +325244.0 False 2 4 Jeżyce 83 +324921.0 False 2 4 Jeżyce 9 +454986.0 False 3 4 Jeżyce 94 +323004.0 False 2 4 Jeżyce 94 +297145.0 False 2 4 Jeżyce 35 +383977.0 False 3 4 Jeżyce 31 +382800.0 False 3 3 Jeżyce 58 +452298.0 False 3 3 Jeżyce 53 +400180.0 False 3 3 Jeżyce 85 +351951.0 False 3 3 Jeżyce 53 +363207.0 False 3 3 Jeżyce 21 +257250.0 False 2 3 Jeżyce 75 +534600.0 False 4 3 Jeżyce 81 +534270.0 False 4 3 Jeżyce 95 +357043.0 False 3 3 Jeżyce 29 +477774.0 False 3 3 Jeżyce 39 +410410.0 False 3 3 Jeżyce 14 +320461.0 False 2 3 Jeżyce 83 +364815.0 False 3 3 Jeżyce 45 +320280.0 False 2 3 Jeżyce 10 +448392.0 False 3 3 Jeżyce 94 +318110.0 False 2 3 Jeżyce 94 +292710.0 False 2 3 Jeżyce 35 +378246.0 False 2 3 Jeżyce 31 +448871.5 False 3 2 Jeżyce 53 +377000.0 False 3 2 Jeżyce 58 +394295.0 False 3 2 Jeżyce 85 +344071.5 False 3 2 Jeżyce 53 +253575.0 False 2 2 Jeżyce 75 +530222.5 False 4 2 Jeżyce 95 +357786.0 False 3 2 Jeżyce 21 +351648.0 False 3 2 Jeżyce 28 +530550.0 False 4 2 Jeżyce 81 +474154.5 False 3 2 Jeżyce 39 +407382.0 False 3 2 Jeżyce 16 +359370.0 False 3 2 Jeżyce 45 +320461.0 False 2 2 Jeżyce 83 +317925.0 False 2 2 Jeżyce 10 +211830.0 False 2 2 Jeżyce 70 +441798.0 False 3 2 Jeżyce 94 +318110.0 False 2 2 Jeżyce 94 +290427.0 False 2 2 Jeżyce 34 +377000.0 False 3 1 Jeżyce 58 +375380.5 False 3 2 Jeżyce 31 +444925.0 False 3 1 Jeżyce 45 +394295.0 False 3 1 Jeżyce 85 +346698.0 False 3 1 Jeżyce 53 +357786.0 False 3 1 Jeżyce 21 +249900.0 False 2 1 Jeżyce 75 +526500.0 False 4 1 Jeżyce 81 +526175.0 False 4 1 Jeżyce 95 +351714.0 False 3 1 Jeżyce 29 +470470.0 False 3 1 Jeżyce 38 +407253.0 False 3 1 Jeżyce 14 +320796.0 False 2 1 Jeżyce 88 +315637.0 False 2 1 Jeżyce 11 +435798.0 False 3 1 Jeżyce 3 +359238.0 False 3 1 Jeżyce 43 +288340.0 False 2 1 Jeżyce 36 +315727.5 False 2 1 Jeżyce 95 +372515.0 False 3 1 Jeżyce 31 +448413.0 False 3 0 Jeżyce 46 +418470.0 False 3 0 Jeżyce 38 +453960.0 False 3 0 Jeżyce 84 +444080.0 False 3 0 Jeżyce 32 +309487.5 False 2 0 Jeżyce 25 +423150.0 False 3 0 Jeżyce 10 +334230.0 False 2 0 Jeżyce 42 +453260.0 False 3 0 Jeżyce 20 +452121.0 False 3 2 Dolna 60 +296290.0 False 2 2 Dolna 57 +420388.0 False 3 2 Dolna 11 +321845.0 False 3 1 Grunwald 55 +286082.0 False 2 2 Dolna 20 +457458.0 False 4 2 Dolna 37 +293768.0 False 2 2 Dolna 56 +295485.0 False 2 2 Dolna 39 +436530.0 False 4 2 Dolna 25 +475052.0 False 4 2 Dolna 65 +282980.0 False 2 2 Dolna 47 +286299.0 False 2 2 Dolna 70 +840000.0 True 6 1 Winogrady 129 +442612.0 True 2 4 Grunwald 11 +324558.0 True 2 4 Grunwald 61 +620000.0 True 3 2 Grunwald 73 +265000.0 True 3 4 Łazarz 55 +393789.0 False 3 2 Dolna 78 +298381.0 False 2 2 Dolna 99 +461040.0 False 3 2 Dolna 8 +443502.0 False 3 1 Dolna 60 +485000.0 True 5 2 Łazarz 87 +215000.0 True 2 0 Wilda 36 +412342.0 False 3 1 Dolna 11 +298885.0 False 2 1 Dolna 96 +459470.0 False 4 1 Dolna 50 +289283.0 False 2 1 Dolna 56 +289842.0 False 2 1 Dolna 39 +431316.0 False 4 1 Dolna 25 +280833.0 False 2 1 Dolna 70 +381420.0 False 3 1 Dolna 78 +396421.0 False 3 1 Dolna 79 +483194.0 False 4 1 Dolna 71 +306880.0 False 2 1 Dolna 27 +374734.0 False 3 1 Dolna 43 +760000.0 True 4 1 Centrum 95 +292530.0 False 2 1 Dolna 99 +452976.0 False 3 1 Dolna 8 +446521.0 False 2 0 Dolna 60 +268373.0 False 2 0 Dolna 57 +260000.0 True 2 0 Naramowice 47 +266788.0 False 2 0 Dolna 21 +399355.0 False 3 0 Dolna 11 +290270.0 False 2 0 Dolna 96 +294964.0 False 2 0 Dolna 32 +463973.0 False 4 0 Dolna 50 +282449.0 False 2 0 Dolna 56 +283698.0 False 2 0 Dolna 39 +364073.0 False 3 0 Dolna 4 +376181.0 False 3 0 Dolna 7 +284140.0 False 2 0 Dolna 94 +290853.0 False 2 0 Dolna 80 +336456.0 False 3 0 Dolna 63 +530000.0 True 3 0 Grunwald 63 +135000.0 True 2 4 skiej 86 +799000.0 True 4 0 Grunwald 118 +329000.0 True 3 1 Jeżyce 112 +260000.0 True 2 0 Naramowice 47 +550000.0 True 3 1 Rataje 81 +443102.0 False 3 0 Dolna 80 +549000.0 True 3 2 Jeżyce 106 +499000.0 True 5 4 Jeżyce 93 +404000.0 True 3 2 Piątkowo 90 +387645.0 False 3 5 Grunwald 10 +294810.0 False 2 5 Grunwald 50 +229000.0 True 2 2 Jeżyce 34 +487000.0 True 3 0 Naramowice 83 +367211.0 False 3 4 Grunwald 10 +367211.0 False 3 4 Grunwald 10 +273497.0 False 2 4 Grunwald 90 +289695.0 False 2 4 Grunwald 50 +367211.0 False 3 3 Grunwald 10 +273497.0 False 2 3 Grunwald 90 +289695.0 False 2 3 Grunwald 50 +284711.0 False 2 3 Grunwald 70 +360600.0 False 3 3 Grunwald 10 +360600.0 False 3 2 Grunwald 10 +360000.0 True 3 4 Rataje 69 +273497.0 False 2 2 Grunwald 90 +289695.0 False 2 2 Grunwald 50 +284711.0 False 2 2 Grunwald 70 +353989.0 False 3 1 Grunwald 10 +284115.0 False 2 1 Grunwald 50 +279227.0 False 2 1 Grunwald 70 +346777.0 False 3 1 Grunwald 10 +279000.0 False 2 0 Grunwald 50 +340166.0 False 2 0 Grunwald 70 +340166.0 False 3 0 Grunwald 10 +279594.0 False 2 2 Grunwald 10 +289738.0 False 2 2 Grunwald 70 +346798.0 False 3 2 Grunwald 70 +235545.0 True 3 0 Plewiska 57 +274302.0 False 2 1 Grunwald 10 +284254.0 False 2 1 Grunwald 70 +420000.0 True 3 3 Grunwald 96 +340234.0 False 3 1 Grunwald 70 +269010.0 False 2 0 Grunwald 10 +279594.0 False 2 5 Grunwald 10 +340781.0 False 3 4 Grunwald 70 +284088.0 False 2 4 Grunwald 60 +274743.0 False 2 4 Grunwald 10 +340781.0 False 3 3 Grunwald 70 +284088.0 False 2 3 Grunwald 60 +274743.0 False 2 3 Grunwald 10 +340781.0 False 3 2 Grunwald 70 +284088.0 False 2 2 Grunwald 60 +274743.0 False 2 2 Grunwald 10 +328200.0 False 3 1 Grunwald 70 +273600.0 False 2 1 Grunwald 60 +264600.0 False 2 1 Grunwald 10 +334217.0 False 3 0 Grunwald 70 +800000.0 True 4 3 Stare 103 +317000.0 True 3 3 Naramowice 53 +392181.0 False 4 4 Stare 25 +275000.0 True 2 13 Rataje 49 +330000.0 True 3 2 Grunwald 60 +290000.0 True 4 3 Rataje 50 +215000.0 True 2 0 Wilda 36 +368520.0 True 2 2 Jeżyce 50 +275000.0 True 3 1 Grunwald 90 +439000.0 True 4 2 Łazarz 92 +370000.0 True 3 3 Wilda 78 +962376.0 False 4 5 Centrum 9 +369000.0 True 3 1 Piątkowo 90 +445000.0 True 3 1 Grunwald 69 +250000.0 True 2 10 Grunwald 42 +439000.0 True 4 2 Łazarz 92 +187000.0 True 2 3 Zawady 35 +265000.0 True 3 10 Grunwald 53 +389900.0 True 3 10 Winogrady 67 +387645.0 False 3 5 Grunwald 10 +294810.0 False 2 5 Grunwald 50 +367211.0 False 3 4 Grunwald 10 +289695.0 False 2 4 Grunwald 50 +295000.0 True 2 4 Naramowice 58 +330000.0 True 2 3 Wilda 53 +187000.0 True 2 2 Zawady 35 +273497.0 False 2 3 Grunwald 90 +289695.0 False 2 3 Grunwald 50 +284711.0 False 2 3 Grunwald 70 +367211.0 False 3 2 Grunwald 10 +273497.0 False 2 2 Grunwald 90 +289695.0 False 2 2 Grunwald 50 +284711.0 False 2 2 Grunwald 70 +360600.0 False 3 2 Grunwald 10 +263400.0 False 2 1 Grunwald 90 +279000.0 False 2 1 Grunwald 50 +274200.0 False 2 1 Grunwald 70 +263400.0 False 2 0 Grunwald 9 +279000.0 False 2 0 Grunwald 50 +1725000.0 True 3 0 Stare 136 +279594.0 False 2 2 Grunwald 10 +340234.0 False 3 2 Grunwald 70 +274302.0 False 2 1 Grunwald 10 +284254.0 False 2 1 Grunwald 70 +333670.0 False 3 1 Grunwald 70 +310000.0 True 3 1 Wilda 88 +475000.0 True 3 1 Stare 68 +335000.0 True 2 4 Centrum 45 +279594.0 False 2 2 Grunwald 10 +289738.0 False 2 2 Grunwald 70 +340234.0 False 3 2 Grunwald 70 +274302.0 False 2 1 Grunwald 10 +399000.0 True 2 2 Łazarz 51 +333670.0 False 3 1 Grunwald 70 +499000.0 True 3 1 Rataje 50 +269010.0 False 2 0 Grunwald 10 +230000.0 True 3 4 Centrum 52 +230000.0 True 2 4 Stare 52 +250000.0 True 2 4 Rataje 50 +289000.0 True 2 2 Ogrody 44 +215000.0 True 2 8 Rataje 42 +239000.0 True 2 2 Rataje 38 +293000.0 True 3 1 Wilda 79 +339000.0 True 3 1 Grunwald 54 +307000.0 True 2 4 Stare 48 +280000.0 True 3 4 Rataje 48 +595000.0 True 5 4 Wilda 54 +379000.0 True 3 1 Stare 90 +569000.0 True 2 2 Stare 20 +445000.0 True 2 1 Stare 80 +475000.0 True 3 0 Stare 66 +420000.0 True 3 1 Centrum 60 +259500.0 True 2 0 Grunwald 90 +259500.0 True 2 0 Grunwald 90 +230000.0 True 2 0 Centrum 46 +99000.0 True 2 2 Wilda 52 +329000.0 True 4 4 Rataje 72 +295000.0 True 3 2 Rataje 54 +225000.0 True 2 1 Rataje 42 +285000.0 True 2 3 Wilda 60 +1600000.0 True 3 2 Górczyn 79 +333000.0 True 3 4 Wilda 8 +1600000.0 True 3 2 Górczyn 79 +333000.0 True 3 4 Wilda 8 +2192000.0 True 4 1 Grunwald 21 +339000.0 True 3 4 Winogrady 90 +3233000.0 True 5 1 Grunwald 28 +489000.0 True 2 8 Centrum 39 +336000.0 True 2 3 Istnieje 48 +359000.0 True 3 1 Świerczewo 70 +239000.0 True 2 3 Winogrady 38 +240000.0 True 2 2 Dębiec 48 +439000.0 True 3 0 Jeżyce 75 +404000.0 True 2 2 Centrum 50 +361300.0 False 3 1 Grunwald 66 +385000.0 True 2 1 Centrum 50 +244000.0 False 2 3 Jeżyce 40 +215000.0 True 2 1 Jeżyce 70 +465000.0 True 3 0 Grunwald 60 +329000.0 True 2 0 Naramowice 51 +309000.0 True 3 1 Rataje 20 +420000.0 True 2 3 Stare 50 +480000.0 True 4 3 Centrum 94 +620000.0 True 4 3 Centrum 50 +342000.0 True 3 4 Winogrady 87 +326000.0 True 3 6 Winogrady 1 +330000.0 True 3 7 Piątkowo 40 +315000.0 True 3 0 Nowe 63 +360000.0 True 4 0 Grunwald 66 +360000.0 True 3 3 Nowe 65 +325000.0 True 2 2 Grunwald 47 +531000.0 True 2 1 Grunwald 59 +377000.0 True 3 1 Piątkowo 63 +640000.0 True 3 2 Centrum 80 +150000.0 True 2 2 Nowe 50 +640000.0 True 3 2 Stare 80 +499000.0 True 4 2 Naramowice 85 +250000.0 True 2 10 Grunwald 42 +250000.0 True 3 3 Rataje 53 +333200.0 True 3 4 Wilda 68 +385000.0 True 2 1 Jeżyce 46 +248000.0 True 2 10 Grunwald 42 +389999.0 True 3 4 Grunwald 82 +204999.0 True 2 7 Malta 30 +410000.0 True 5 0 Łazarz 114 +370000.0 True 3 4 Stare 84 +225000.0 True 2 4 Warszawskie 50 +349000.0 True 3 3 Wilda 20 +289000.0 True 3 1 Grunwald 45 +1330000.0 True 3 0 Malta 100 +235000.0 True 3 2 Starołęka 51 +549000.0 True 2 8 Centrum 39 +498000.0 True 4 4 Centrum 86 +525000.0 True 4 3 Nowe 88 +550000.0 True 3 5 Grunwald 73 +410000.0 True 5 0 Łazarz 114 +399000.0 True 3 4 Jeżyce 63 +289000.0 True 3 0 Nowe 10 +308039.0 True 2 0 Stare 52 +322497.0 True 2 6 Stare 51 +220000.0 True 2 1 Łazarz 35 +309000.0 True 3 14 Rataje 80 +293760.0 True 2 3 Winogrady 90 +392181.0 True 3 4 Stare 69 +307257.0 True 2 2 Stare 50 +263140.0 True 2 0 Stare 45 +281881.0 True 2 1 Stare 46 +399000.0 True 5 4 Centrum 10 +511000.0 True 4 1 Stare 104 +428400.0 True 3 0 Piątkowo 60 +260000.0 True 2 2 Jeżyce 10 +369000.0 True 3 1 Stare 90 +379000.0 True 3 1 Piątkowo. 78 +346320.0 True 2 3 Grunwald 40 +440700.0 True 3 3 Grunwald 50 +321285.0 False 2 4 Stare 30 +385000.0 True 3 0 Grunwald 80 +569000.0 True 4 0 Wilda 50 +296033.0 True 2 3 Stare 49 +295362.0 True 2 2 Stare 48 +295362.0 True 2 1 Stare 48 +420000.0 True 5 0 Łazarz 8 +273875.0 True 2 1 Grunwald 13 +450000.0 True 2 2 Jeżyce 41 +379000.0 True 3 1 Piątkowo 78 +270000.0 True 3 3 Rataje 48 +278460.0 True 2 0 Winogrady 10 +298980.0 True 2 5 Stare 30 +369000.0 True 3 1 Piątkowo 78 +450000.0 True 3 0 Winogrady 70 +219000.0 True 2 0 Wilda 36 +345000.0 True 3 5 Rataje 77 +371930.0 False 4 2 Jeżyce 20 +313566.0 False 3 3 Jeżyce 50 +365000.0 True 3 4 Rataje 63 +297000.0 True 2 7 Bonin 49 +350805.0 False 2 2 Rynek 97 +365000.0 True 4 3 Grunwald 68 +405000.0 True 4 2 Rataje 71 +259000.0 True 2 2 Nowe 40 +340000.0 True 3 0 Centrum 10 +275000.0 True 2 0 Dębiec 50 +435000.0 True 3 0 Stare 25 +750000.0 True 2 1 Stare 80 +570000.0 True 4 3 Grunwald 137 +290000.0 True 2 5 Winogrady 42 +360000.0 True 3 14 Rataje 80 +770000.0 True 4 1 Centrum 142 +285000.0 True 2 0 Łazarz 49 +263553.0 True 2 0 Winogrady 67 +475000.0 True 4 4 Wilda 84 +414566.0 False 3 1 Malta 1 +422000.0 False 3 1 Malta 66 +425402.0 False 3 0 Malta 75 +440224.0 False 3 4 Malta 8 +440224.0 False 3 4 Malta 8 +416214.0 False 3 2 Malta 75 +633832.0 False 4 4 Malta 73 +422670.0 False 3 3 Malta 75 +420174.0 False 3 2 Malta 75 +423922.0 False 3 1 Malta 75 +633344.0 False 4 4 Malta 65 +422372.0 False 3 2 Malta 74 +499000.0 True 3 1 Rataje 64 +410110.0 False 3 2 Malta 49 +424178.0 False 3 1 Malta 79 +229000.0 True 2 0 Rataje 38 +422322.0 False 3 1 Malta 73 +411628.0 False 3 0 Malta 68 +438016.0 False 3 4 Malta 10 +441084.0 False 3 4 Malta 10 +380931.0 True 3 3 Nowe 83 +365000.0 True 4 3 Grunwald 68 +365000.0 True 4 3 Grunwald 68 +350000.0 True 3 7 Piątkowo 63 +47475.0 True 2 11 Wilda 75 +289000.0 True 3 0 Winogrady 48 +520000.0 False 4 3 Grunwald 10 +520000.0 False 4 4 Grunwald 12 +520000.0 False 4 3 Grunwald 12 +520000.0 False 4 2 Grunwald 11 +475000.0 True 5 4 Grunwald 23 +281576.0 False 2 2 Stare 16 +380900.0 True 3 3 Nowe 67 +485000.0 True 5 2 Łazarz 88 +239000.0 True 2 4 Rataje 38 +250000.0 True 2 6 Nowe 45 +429000.0 True 4 2 Jeżyce 110 +370000.0 True 4 0 Wilda 80 +275000.0 True 3 4 Wilda 77 +850000.0 True 5 1 Grunwald 135 +265000.0 True 2 4 Rataje 38 +349000.0 True 3 2 Rataje 64 +229000.0 True 2 0 Grunwald 47 +320000.0 True 3 4 Rataje 60 +430000.0 True 3 2 Rataje 64 +389000.0 True 3 4 Rataje 80 +619000.0 True 4 0 Jeżyce 99 +329900.0 True 2 1 Naramowice 20 +430000.0 True 3 2 Rataje 64 +520000.0 True 4 1 Centrum 50 +369000.0 True 3 0 Stare 64 +505877.0 False 2 5 Centrum 22 +619000.0 True 5 1 Jeżyce 146 +389740.0 True 2 2 Łazarz 96 +434525.0 True 2 2 Łazarz 85 +552955.0 True 3 2 Łazarz 7 +350805.0 True 2 2 Łazarz 97 +279000.0 True 2 0 Piątkowo 10 +460135.0 True 3 0 Łazarz 79 +392790.0 True 3 5 Stare 30 +309000.0 True 4 4 Grunwald 70 +219000.0 True 2 2 Dębiec 30 +1345500.0 True 5 1 Grunwald 117 +690000.0 True 4 5 Grunwald 24 +886860.0 False 3 5 Centrum 80 +372000.0 False 4 0 Grunwald 49 +502136.0 False 2 5 Centrum 77 +342000.0 False 3 1 Grunwald 27 +372000.0 False 4 0 Grunwald 49 +342000.0 False 3 1 Grunwald 27 +473770.0 False 2 5 Centrum 7 +798966.0 False 2 5 Centrum 33 +561663.0 False 3 4 Centrum 69 +396248.0 False 2 4 Centrum 77 +278000.0 True 2 0 Piątkowo 45 +368019.0 False 2 4 Centrum 18 +369000.0 True 3 0 Stare 64 +380000.0 True 4 1 Piątkowo 75 +1345500.0 False 5 1 Grunwald 117 +365000.0 True 2 1 Centrum 50 +659000.0 True 4 1 Rataje 78 +344000.0 True 3 3 Nowe 65 +310000.0 True 2 4 Winogrady 45 +275000.0 True 2 0 Centrum 44 +328000.0 True 4 2 Grunwald 75 +382156.0 False 2 4 Centrum 21 +383676.0 False 2 4 Centrum 4 +387597.0 False 2 4 Centrum 49 +1555200.0 True 4 2 Jeżyce 144 +378128.0 False 2 3 Centrum 77 +649999.0 True 4 1 Stare 90 +584000.0 True 3 1 Centrum 89 +229000.0 True 2 0 Winogrady 38 +238900.0 True 2 0 Grunwald 47 +239000.0 True 2 0 Raszyn 47 +254000.0 True 2 1 Nowe 44 +469000.0 True 3 0 Naramowice 52 +215000.0 True 2 3 Centrum 38 +495000.0 True 3 1 Grunwald 37 +490000.0 True 4 2 Centrum 90 +268000.0 True 2 4 Winogrady 37 +262000.0 True 2 2 Rataje 50 +321845.0 False 3 1 Grunwald 55 +265000.0 True 2 0 Wilda 50 +329000.0 True 4 4 Nowe 20 +360000.0 True 3 3 Naramowice 63 +341776.0 False 2 2 Centrum 14 +356774.0 False 2 1 Centrum 10 +230000.0 True 2 0 Rataje 38 +270000.0 True 2 0 Dębiec 50 +330255.0 False 2 1 Centrum 14 +275000.0 True 2 0 Dębiec 50 +210000.0 True 2 0 Wilda 36 +291000.0 True 4 1 Wilda 70 +1465000.0 True 6 3 Łazarz 38 +579000.0 True 3 1 Łazarz 3 +401000.0 True 3 1 Łazarz 49 +626000.0 True 3 1 Łazarz 59 +558000.0 True 4 1 Wilda 93 +533000.0 True 2 2 Łazarz 19 +595000.0 True 2 2 Łazarz 70 +269000.0 True 2 6 Rataje 50 +520000.0 True 4 7 Nowe 98 +269000.0 True 2 6 Rataje 49 +750000.0 True 4 0 Naramowice 133 +370000.0 True 2 1 Nowe 53 +499000.0 True 3 1 Jeżyce 40 +545000.0 True 2 4 Centrum 49 +420000.0 True 3 3 Łazarz 47 +569000.0 True 4 0 Wilda 50 +370000.0 True 2 2 Naramowice 70 +345000.0 True 3 0 Nowe 60 +207000.0 True 2 1 Dębiec 45 +215000.0 True 2 1 Ogrody 38 +250000.0 True 3 3 Nowe 53 +420000.0 True 2 2 Łazarz 51 +269000.0 True 2 6 Rataje 50 +350000.0 True 2 3 Jeżyce 70 +225200.0 True 2 1 Nowe 39 +348000.0 True 3 3 Piątkowo 63 +260000.0 True 2 0 Naramowice 47 +449000.0 True 6 3 Stare 74 +260000.0 True 2 0 Stare 79 +288000.0 True 2 0 Jeżyce 50 +175000.0 True 2 4 Głuszyna 38 +289000.0 True 2 1 Wilda 47 +439000.0 True 4 2 Grunwald 92 +289000.0 True 3 3 Nowe 63 +184000.0 True 2 0 Grunwald 34 +450000.0 True 3 2 Naramowice 66 +360000.0 True 4 3 Grunwald 70 +379999.0 True 2 5 Jeżyce 61 +368712.0 False 2 5 Centrum 34 +348750.0 False 2 4 Centrum 54 +348750.0 False 2 3 Centrum 58 +393120.0 False 2 3 Centrum 52 +368712.0 False 2 2 Centrum 73 +362880.0 False 2 1 Centrum 37 +368712.0 False 2 0 Centrum 89 +362880.0 False 2 0 Centrum 72 +326430.0 False 2 0 Centrum 40 +480000.0 True 3 3 Stare 94 +360000.0 True 4 3 Grunwald 61 +525000.0 True 4 3 Jeżyce 104 +249000.0 True 2 4 Grunwald 38 +333775.0 True 2 1 Stare 35 +339822.0 True 3 3 Jeżyce 10 +360486.0 True 2 4 Jeżyce 10 +365000.0 True 2 1 Stare 10 +310000.0 True 3 1 Piątkowo 60 +339000.0 True 3 0 Rataje 63 +649000.0 True 4 1 Jeżyce 70 +356000.0 True 3 2 Naramowice 80 +345000.0 True 4 11 Grunwald 40 +499000.0 True 4 3 Stare 103 +269000.0 True 2 1 Rataje 49 +285000.0 True 2 4 Jeżyce 56 +308736.0 True 3 1 Jeżyce 24 +346689.0 True 3 2 Jeżyce 3 +241939.0 True 2 4 Jeżyce 51 +377622.0 True 4 4 Jeżyce 94 +245616.0 True 2 1 Jeżyce 8 +366208.0 True 3 6 Jeżyce 22 +195000.0 True 2 4 Grunwald 70 +262656.0 True 2 5 Stare 4 +458000.0 True 3 4 Centrum 87 +1115000.0 True 2 2 Grunwald 7 +285000.0 True 2 3 Wilda 50 +240000.0 True 2 8 Dębiec 38 +390000.0 True 3 3 Grunwald 87 +259500.0 True 2 0 Łazarz 90 +420000.0 True 2 3 Wilda 70 +560000.0 True 4 1 Naramowice 156 +429000.0 True 3 4 Nowe 79 +340000.0 True 3 0 Stare 70 +340000.0 True 3 0 Stare 70 +270000.0 True 2 2 Rataje 49 +428000.0 True 3 3 Centrum 43 +190000.0 True 2 8 Dębiec 50 +240000.0 True 2 8 Dębiec 38 +315000.0 True 2 2 Piątkowo 48 +404000.0 True 3 0 Warszawskie 52 +249000.0 True 2 0 Jeżyce 33 +350000.0 True 2 3 Grunwald 53 +239000.0 True 2 3 Rataje 49 +245000.0 True 2 9 Rataje 38 +706655.0 False 3 2 Nowe 45 +269973.0 False 3 1 Nowe 50 +249984.0 False 3 1 Nowe 64 +229990.0 False 3 1 Nowe 80 +269967.0 False 3 1 Nowe 30 +269973.0 False 3 1 Nowe 50 +189990.0 False 2 1 Nowe 12 +259993.0 False 3 1 Nowe 18 +199990.0 False 2 1 Nowe 95 +290000.0 True 2 2 Winogrady 41 +259993.0 False 3 1 Nowe 18 +279989.0 False 3 1 Nowe 58 +410000.0 True 3 1 Stare 60 +325000.0 True 2 4 Nowe 49 +285000.0 True 2 3 Wilda 60 +415000.0 True 3 2 Jeżyce 10 +245000.0 True 2 3 Naramowice 45 +260000.0 True 2 2 Rataje 38 +285000.0 True 2 3 Wilda 43 +269000.0 True 2 6 Rataje 50 +345000.0 True 3 5 Rataje 77 +259988.0 False 3 0 Nowe 73 +259980.0 False 3 0 Nowe 52 +189991.0 False 2 0 Nowe 40 +239994.0 False 3 0 Nowe 80 +259980.0 False 3 0 Nowe 52 +259988.0 False 3 0 Nowe 73 +349000.0 True 3 1 Nowe 108 +398000.0 True 3 2 Stare 20 +198789.0 False 2 0 Nowe 15 +198789.0 False 2 0 Nowe 15 +189661.0 False 2 0 Nowe 49 +255000.0 True 2 6 Rataje 49 +310576.0 True 3 3 Stare 55 +330680.0 True 2 1 Stare 59 +1214533.0 True 5 0 Grunwald 50 +550000.0 True 3 1 Grunwald 84 +230000.0 True 2 3 Rataje 36 +389000.0 True 3 2 Jeżyce 10 +300000.0 True 2 2 Winogrady 30 +435000.0 True 4 0 Dębiec 89 +1990000.0 True 3 1 Stare 150 +531000.0 True 2 1 Grunwald 59 +550000.0 True 3 1 Grunwald 84 +230000.0 True 2 3 Rataje 36 +389000.0 True 3 2 Jeżyce 10 +300000.0 True 2 2 Winogrady 30 +310576.0 True 3 3 Stare 55 +330680.0 True 2 1 Stare 59 +1214533.0 True 5 0 Grunwald 50 +550000.0 True 3 1 Grunwald 84 +259988.0 False 3 0 Nowe 73 +259980.0 False 3 0 Nowe 52 +189991.0 False 2 0 Nowe 40 +239994.0 False 3 0 Nowe 80 +259980.0 False 3 0 Nowe 52 +259988.0 False 3 0 Nowe 73 +349000.0 True 3 1 Nowe 108 +398000.0 True 3 2 Stare 20 +198789.0 False 2 0 Nowe 15 +198789.0 False 2 0 Nowe 15 +189661.0 False 2 0 Nowe 49 +255000.0 True 2 6 Rataje 49 +310576.0 True 3 3 Stare 55 +330680.0 True 2 1 Stare 59 +1214533.0 True 5 0 Grunwald 50 +550000.0 True 3 1 Grunwald 84 +230000.0 True 2 3 Rataje 36 +389000.0 True 3 2 Jeżyce 10 +300000.0 True 2 2 Winogrady 30 +435000.0 True 4 0 Dębiec 89 +1990000.0 True 3 1 Stare 150 +531000.0 True 2 1 Grunwald 59 +779000.0 True 3 2 Stare 113 +350000.0 True 2 3 Grunwald 53 +350000.0 True 2 1 Zawady 53 +260000.0 True 3 1 Grunwald 48 +350000.0 True 3 3 Nowe 67 +449000.0 True 3 1 Stare 110 +280000.0 True 3 4 Rataje 48 +280000.0 True 3 4 Rataje 48 +390000.0 True 3 3 Grunwald 87 +390000.0 True 3 3 Wilda 70 +462000.0 True 2 3 Winogrady 70 +220000.0 True 2 3 Rataje 42 +368000.0 True 3 2 Winiary 51 +368000.0 True 3 2 Winiary 51 +368000.0 True 3 2 Winiary 51 +402000.0 True 3 1 Winogrady 27 +289000.0 True 2 7 Winiary 48 +320000.0 True 2 2 Zawady 53 +233361.0 True 2 4 Jeżyce 60 +245000.0 True 2 3 Stare 50 +299500.0 False 3 0 Junikowo 59 +462000.0 True 2 3 Winogrady 57 +378000.0 False 4 0 Junikowo 35 +225000.0 True 4 3 Wilda 60 +249000.0 True 2 4 Winiary 49 +569000.0 True 4 0 Wilda 40 +308736.0 True 2 2 Jeżyce 48 +356000.0 True 3 2 Naramowice 63 +349000.0 True 3 1 Stare 83 +1650000.0 True 4 0 Sołacz 70 +330000.0 True 2 3 Wilda 53 +346689.0 True 3 4 Jeżyce 55 +363347.0 True 4 5 Jeżyce 57 diff --git a/wyk/ex2data2.txt b/wyk/ex2data2.txt new file mode 100644 index 0000000..a888992 --- /dev/null +++ b/wyk/ex2data2.txt @@ -0,0 +1,118 @@ +0.051267,0.69956,1 +-0.092742,0.68494,1 +-0.21371,0.69225,1 +-0.375,0.50219,1 +-0.51325,0.46564,1 +-0.52477,0.2098,1 +-0.39804,0.034357,1 +-0.30588,-0.19225,1 +0.016705,-0.40424,1 +0.13191,-0.51389,1 +0.38537,-0.56506,1 +0.52938,-0.5212,1 +0.63882,-0.24342,1 +0.73675,-0.18494,1 +0.54666,0.48757,1 +0.322,0.5826,1 +0.16647,0.53874,1 +-0.046659,0.81652,1 +-0.17339,0.69956,1 +-0.47869,0.63377,1 +-0.60541,0.59722,1 +-0.62846,0.33406,1 +-0.59389,0.005117,1 +-0.42108,-0.27266,1 +-0.11578,-0.39693,1 +0.20104,-0.60161,1 +0.46601,-0.53582,1 +0.67339,-0.53582,1 +-0.13882,0.54605,1 +-0.29435,0.77997,1 +-0.26555,0.96272,1 +-0.16187,0.8019,1 +-0.17339,0.64839,1 +-0.28283,0.47295,1 +-0.36348,0.31213,1 +-0.30012,0.027047,1 +-0.23675,-0.21418,1 +-0.06394,-0.18494,1 +0.062788,-0.16301,1 +0.22984,-0.41155,1 +0.2932,-0.2288,1 +0.48329,-0.18494,1 +0.64459,-0.14108,1 +0.46025,0.012427,1 +0.6273,0.15863,1 +0.57546,0.26827,1 +0.72523,0.44371,1 +0.22408,0.52412,1 +0.44297,0.67032,1 +0.322,0.69225,1 +0.13767,0.57529,1 +-0.0063364,0.39985,1 +-0.092742,0.55336,1 +-0.20795,0.35599,1 +-0.20795,0.17325,1 +-0.43836,0.21711,1 +-0.21947,-0.016813,1 +-0.13882,-0.27266,1 +0.18376,0.93348,0 +0.22408,0.77997,0 +0.29896,0.61915,0 +0.50634,0.75804,0 +0.61578,0.7288,0 +0.60426,0.59722,0 +0.76555,0.50219,0 +0.92684,0.3633,0 +0.82316,0.27558,0 +0.96141,0.085526,0 +0.93836,0.012427,0 +0.86348,-0.082602,0 +0.89804,-0.20687,0 +0.85196,-0.36769,0 +0.82892,-0.5212,0 +0.79435,-0.55775,0 +0.59274,-0.7405,0 +0.51786,-0.5943,0 +0.46601,-0.41886,0 +0.35081,-0.57968,0 +0.28744,-0.76974,0 +0.085829,-0.75512,0 +0.14919,-0.57968,0 +-0.13306,-0.4481,0 +-0.40956,-0.41155,0 +-0.39228,-0.25804,0 +-0.74366,-0.25804,0 +-0.69758,0.041667,0 +-0.75518,0.2902,0 +-0.69758,0.68494,0 +-0.4038,0.70687,0 +-0.38076,0.91886,0 +-0.50749,0.90424,0 +-0.54781,0.70687,0 +0.10311,0.77997,0 +0.057028,0.91886,0 +-0.10426,0.99196,0 +-0.081221,1.1089,0 +0.28744,1.087,0 +0.39689,0.82383,0 +0.63882,0.88962,0 +0.82316,0.66301,0 +0.67339,0.64108,0 +1.0709,0.10015,0 +-0.046659,-0.57968,0 +-0.23675,-0.63816,0 +-0.15035,-0.36769,0 +-0.49021,-0.3019,0 +-0.46717,-0.13377,0 +-0.28859,-0.060673,0 +-0.61118,-0.067982,0 +-0.66302,-0.21418,0 +-0.59965,-0.41886,0 +-0.72638,-0.082602,0 +-0.83007,0.31213,0 +-0.72062,0.53874,0 +-0.59389,0.49488,0 +-0.48445,0.99927,0 +-0.0063364,0.99927,0 +0.63265,-0.030612,0 diff --git a/wyk/fit.png b/wyk/fit.png new file mode 100644 index 0000000000000000000000000000000000000000..3d758e6172b6c69ff19da3d07e295c5f247dee63 GIT binary patch literal 141779 zcmeFZcUY6zwm2NSg32HuQdO#iCP=R;HM9sMgw7}+9i(?qM-W0A0twQk1`;4rLKRSY zMtatCV*Is+=)pkw?Prm|wQd0&g z1J0ZQ0M3yA0H-4W1;E)e-^=&w+3)52x$oBt=g*%zfAPY_i@*I}x^nsAr7M>%Uc5|s z`3lANLcY67Npbc2!}mshfA#EzbLTElT)KGaH<16;<@6JP`trG3mrKr_VFR3{K68%x z%xMFFm5k)sv**aD0sbhLE?>NI=IjNE^XJIl2mS;&bMD+(a<5meP+Xv-q@V|!IeYH> zg^QP{FWSXa5su%oo5bKipo>KJU(4 zKl8a2)gM7QwgGp{er!wT2S|`C;O}n#Ci34b_4fk$hh+KxPF#TI#w0eoUL5_xP`X%V zHCsG&b2)>*%)Dgi+W6dCh>i|)Kx^=hTSr=pEl|3~lWU0?3;_$H?!7#GBu^_+zpzDl z>~Q(~-gnu3{!s(^=Ju%c>^r%H;SzRn0&~<8+k&44^U5_!LuQ;l=Juw0wsZDRDp4AS znClI~aTw*MDKiSIhOf-l+w*%cqu>n1j^;hhzoHPJ2=@0vO!!kxm5JhE7?jBPkS%^m3N>(Ee zHU>@sZzL|6odSkcok}kp#n*(imwjDy&82bLe1Wa6ofVj&JZz`$Y)hSI*Ky1+xtWED zwW(`LhOS70kr+&BS+iT5#AT$?5vYP9i(tC=ScVHqD%`@^i!CX+8#nK~ta?~`)2(=6 z>)Nr^t@8)J`#>oAn&?SYb@IK+;6oN~zCuH^n*Q-C>+6ZJdPAJ^-cYM<<8 zrgXsv$pq4fW8$wK@1K<(J58k>Xy?XJgcfQ9Ue2!SohpcC0tMvdVsnE*7{ky`X&VMj z3J$f^CEvFq;jRcei*KbHIPq>iCBCxoT9-a~+K*bC0?vcla z=ciIe(1z+JqAb7gHQKF;+e-nn{8@^8K)Gzer6^A5Zia>0+eQw15?nH?J7^OMDoIDYwPIiy0=EVcWzxk{uzU_djR)Ye@=+^V@|LuyJRC zuua0eK|5utYLQULPV!psVT7Pkq-S?~XShwc)o|C|dXrn1sy};|bGGyJI`>POPYju# z{*3cqdwOW>eZr&^kScTvSS7?PoN=DpbD%r$Yd!^3>44vVZ~Kgzv=PtoVa@>)sPvem z=h3}XCwR}eitaJgAlKHG$(HBIp|;KOZoZ#XeK;$upMT zFn8)*8@+G}06TwdX3fb-WUVw_z~s{sKd5Wc$!sS#Y;o3BgDiqJD%gSzm~J$M0b7cU z#AI0so=TdPK*3N_qZA~wf-|<)j+bh@Xnix)r*Of&y`2fW~0W~jBxrvMOx z{IdH@QKQW?<>uJr?FDx32tB&vEX}-6(xHizTFjYMhm-q%>Mltw)?dD}OnJ$>8c3u&d&9SHO zd9)$HfEk-u=5}3iUGeCUIX#_QVVGzK%bC;BtQHMmkwFZxa-@HVZUKD#$0+|iihu9v z{H5V5duiFX!SBqLtU>EP%9ek4JucWz#qB-bGdS^$Kgr#$?&gu8&facCfN}Ry{c4Mrj0og#>+LA8FmTA($hWp2 zL6j|U+_#q2+Ntg+Ywv+1;70t{@4ft1uJuh* zvp=PHU`Wyb?Rsm*-W&Se2P}vc6Qp({2r(`UtPr4!lk!49;3)=ZnB-F{e{l|;5_^Lz zJ^W1-;GW^l<+sYXan1N9B_q$sTU>c{PH{Z_21^c|ah6#q6<{SOS4TC&fEBY~?&buO zJzmVL39D6J+YhHPyB{_S3vTwUo3@?VBN;iq8yR1PxNA7LNYM+%$0#oR?6RLIjDz1@ z=~Tln`q-4tR4pO1Q?FIotJE(kH4Z}phq{?gmMhiexyQr@u2~rsoB}RLIS@!W*y*zF z!pVgbJ8Ocy@KDkqhi|Sxi8kT$crkKCMU)=ddBPim0SZDOkS*3}KOb(eYn3Tcxe(*_gc&aL83FU^Bx?Jl0iGJsozi(^u z_bI=gG1#j!*&CU>Yg~JBL)d9>snxR7WqYD?3R3W89-l3J+yxjm`txN=E5t`Uq{*qLka-!D#4>eeY%V)^HVu+&_ZX6py1Q zV}Ls9TFNI-7vC=TA#Ox8O-EA>QcmL_kv54fq^Wyai_$NQsdao&zW zL5*Hg@6;%F6YDk&#`gGX&+5AsipnuX%S*ircETC*W)pc-au|!F44!+AE4Y4qbZ%^J zh;f%K_p5a9fnV0xYLTs+0#dTQDrd}ek%D$_Xw6n@rKq_6Ygf@pAPvW-ZC%xp(%ZfZ z;|co9;bu37SDYV)%`LSMCbmPc?{Ye-n9 zQ@btiNPCq9-oSQoaP4-rn~)^S*BS~mWU5}Vf(XP7NGXd}RoVrMnrSlWPQ%*I8HR4H z^`Vq zr#lq;^-v_Udc_658pe68k_~@xzJ~Ys4akI>&JYHYb>P$M)JT6V>gN`|x*~4H#&wkM zg6V~*uAQG4&s!quHf(R#hIYyj66Oni1_kuH)Mi_Xo_RwldSGQ$F8C!TV@w;04L$j@ zUm=he%9=9+-GROpV~uKF_kGZoBrvJ#ZX>G0>q(#Fh0jE6*l>X!P8QgWbP$!4w$hUj z3}62{_WqZ@`-z@4Fu2DI-4S?*=Q#MYy8OH9p~ou1zE)10)RHGX-`5Sq{Zxs-UDo9U zQx5w+sco+3cRZ<74XF=@fcZ~o0@2>!L zhx+x^9_4bl&X^@HTI4H1_f#$?RdJnMvRvPg($)qE1lba;O!F|Bq|%X%F0?dv!;5eD zP6%W}3w>w)YnWS>5!$dUW`4O~<~`15MxWrQ8B>*_w7aZ%0^?N6E7(KeLqPL6)#8KU z<&iW z&?(?s$-*dZTtBdrnR^b|&UIKCsJOmyZtJYB%pauutM$L6b<5u}@gi?6o*RVlMBFKW z9mn~)Z9~RRypS->;0{MkE9iBp!PQ!fI9$r6^s3U4hvBqJ)2?qKYowxMyiNfMI8LNv zTk?~Q%zlPtZYdX?uzJJn5({dNB4?U<%T*>+3cqri&Fm;%KT9KY*Q0~zIcWpTie@sQ zWSZ6#>q}=x#XB)et)FtVP{!^iRo?QSk0Pwx9U7dOV$)1{ndhW}!NTmz|P1}Ukgq{;7S@1l7gZKMl!4^5bXJN*` zljT8ePBjY$s*W)*(K$UA%FX%bEKy&kODP+^l{*cYC>9)+!L(M@Qhk-Qsv6I`X2ve@ zg>@|a9A}LZu|QZFQeizcVNJY!{Pn33Gv6pP^1Zd>@SVAqEav8sCR52d$=f#+_#P;+ z;UnF2AEZd6b}~8if50inBo$^0$7trQ#HRQi%Ca&rCRwc4j&=hsJbp+&n5f+BQ=PZcf0hm2@VemvVpQAlO)0Ecpa&Lq8-2<5 zOUx$xTo^BgaxF4g>nn)JiqQ0lb=Xrd^HOs+{3fNczfonhnO`#N-Jubu1uRM+ z@zypChU7%Rao*x%dRT{q_*tY~O`;uT!ObJ-yU)h>HdR;-8uf|6HALQ#j=@EqiQ*}! z<08?;etS<7CT?lm>7m5d=`pDS#$#5Ll6#4xLVmMdO{MiI<~pS*B;^L5+6tItfu*K2 z(xg*U+9GIl1S>w&O2x4txV*FOG=JdjFk`2@*d5YMUz3;82RAwer0`zZYkg)|A?KL} zWUrx8l2BT#;#yRAmr_AuGzci1-=)>SS0H*e1V*(z40jFPXn#`Vq09}gq^e`}MXyGfi>UFWpD#&aB9iFkW?MRm`) z;f~oiCO)CSS#H6j2D3i_#8Jp!dc3^uuy+NRb~K6Z?{9J3UZaAE6w0P$=wRN1HKbB;wT^~r_HW0%> z4pW{v^AG@#IYKnrwl33^lNKY8v`7N(HRcLal|{sgUIlgw2uurl(d}Q}zwkyPTfu;1 zH{29s$3F}j@a9CsACGW*c8h>$$$FIqhlpm)Zo!Eq+o6v1xhWr#t*f_nF_za+k5%W*2Bn65=XOZp+HfM&Q2nBdy&*n%>Rsq_&a3wop~7t}7Z} z{~-2Xt^a466#&SWc^Y8!k^Pv%Vxn*W(N2f{b2=knT`T15o*Q7pHJqM`kf&93rCSKj zRGm#aTW{h}-X~^l%WihFx_}&#=*UqL%cF$tJ#!PObb5j95IKlEZ!TmPp|~TCedda( zROQ8R`C{4Z{CG%O8!`;S>B2W0OnRzirY%WOC|j~bYp(qOv^EaDZn$lc3M5g95mANIuD(!%Jox2z{lK_3?AlOk2eXbGEW6(v5fqMwea4=-!Tj2W#k z*K%0t2({yf^*)7Uvne8rL_2VObTO!Q%KHMIdET~%aki8)2q>9Xu8S5v*=5U!ugueV zyfY_%lfS{C`KLC1AEkzf6zS_A*XS<>YqT%amSk5}oP_fpEaz(SMl;W3#kX>+u(Jq@ ze>8=f!rFDUx-*Va-+nG?DEF5xmqPKk=9OJq;lO*H+{+^J<%vz93Z7oN>dWCI%?uCw znuF$;RlTkVftZB=F3YnNI$wJqmpIGwW?`&YxWQ2zUR5e70xKO^a&YN~fOK`$b%qjV z)hWPyQIXaI@eFK=A5OLr?Z_90*%dX{9BN36Snslal7at$I(~z1LpIhewOR=bR;QBM zlKs%9`*Ds+e7PRSjbuit^`uyC_U%1NvJRjY&W zqO2dCqJX0J-yr~i3+qhiCTI2`rkg5N7K&rghw}VQ(+YMOsG4b=mY+l6`_GZ{{Y?Z- zVjH%Hnp%8JZN(~zXS(|yrpiKuT6bQP_Yey$$d13w<s$V+n<&64SP#;kNb>itC#2+9}Hu=+;T98UM*I_rF5iP60HWr+^Laky8L6 z@Hp(~q}k9`%9hbXyQgk2!(2NrB4UW_;bUX-x=Z;?&y>UMV)oWA&wN~MI-PA+iK2s9 z#^OyQi}{_o@msAbdP9b@EiJPMt<`kSS^cDbDOPKgLG}(*as8w(`I~0xhR8}m@<(H1 z+VqWgAE$Y(7E3mZ4tC^R(zl}$1<3++G|J1XkGW54W2tco;=)K7X@H!Vt+sH#3Abtl z(H2Aky==a!U@AI-Q7H-6H%9od6fOBtA6G~2iqZ$`^ zhO;=O$7~hjTdY4N>Uy;cY?*Fn!y_yZlTzxk-3;d5N&7$!*QCWZ5yuHC$8Q{tt7{3E zz1eNYW8G~Qj-VnTb04;h7)vF#WH|@j`uS6U+1)&?MBuX4inW-n4B6vvbbP13<3243oSHdJWVJL zGQ!hEXiwD;t=%@{Is?zZ-k+$Uafk0MWENYrFR3P~X_O{cVqxu8H z1`EG2n>l_cata7m&#VC(i@yyIk^z9p-gS$n7rztp-@TssbL1`aLUZb532b5O_Q?uJ z?&bGZFIY{}Z%#~#A9%)|w2Xlig2dD3XPn6vlZ9t_?Un%E;S|urb|Mt`qnAO$Lbe5{?OMNaq0%e}o-zaZZc12~`U^$*;Ej_{Y0tI9$q z8(d!D|(>Wu3+c!C5TNG{TspIh8amzH~Is zk|NmkwSNXZPbl~6)0jS2GEw9J`8a}g`B-}gvF2waBP@(S`o7D}U3fZYYE{Z;=;MWg zk_=K>IcLJiY`gD9mCD;%%x{i_f0%Gme`Mp@hk5eFNsDj_5GAr6A+dAzEt$z>rq!N0 z9eY7)+oX4ybHT%gAI%vCSOu?Gt|hVUQolw^xzV2_=`@G+8*FHn@3VgZ#a}FL zs#VbqCv#0Zx2UW!(;5yFmXAVxQGXNyK}3$w|o^tKd=!5k*Xl?O>jy=cXC4&^PE zy&c&%74K7B6EW9^7u^!Om<;AOh+cAUe?BwxkBRxK)sNW+406Bz7&-*}9=0J{jQ^B; z@Xx`+Ph=#{?7x)4I1L1(O3skp1wTm92Nue-)q`Bi^y&(U+IpXc*y6*c-~(*w=u?3H z4w711YG*%qWTh=xPAEg)>O;~(r<&k3+k`Q>cb2}-FX58d(g`+KcTGT_*xiZc}fmLC?PkQ8r2i&D!0xd9bln!9;9HH zI~=-j*ia?yJ`^S_Y7EMAbF}rejRZ%~B80>HQ-(pGRx9b4cptQ)tk*2u zgQHNEd4Oxh)ua;WXZ_Gv{O5zGsWXPrsKslg!G}rGk`*IGw!UpykkYn$Xg`l({i(Rb zal%?z7XM@A20IIP#TX!OmP<<1h4m>9TjMQ?UY{nySBY=#+K%$SrolqRJgo)#Q$2cpzceGy2-jQlxFb_PLo;j$%Tq6U6*@`fU1Y+i%ve{K+mzxQ0s7bjhFIrl_z@o|j`6)sXm1VAFy^v-B zPJm^%w=&|ZT4qHjir;EpDSB~;&JEKUz3o~BBg#$3&OqXWJReU?e4t?>9At8i4 zp~AwZ24&@@ET0HsK%}&L;M>G~K@kW2CK<8UwFz2eLH|6Vt=j-kR9a3!#JMxD^EPZ4 zdtPX=7P_j_d7);^KGRb40t=sJqy!sTT`^}&W()}l3Eg7F@akHQ0_`WNPx^wO>mv@K zy`ZPJijy#!ZD9Vzk+I^+bU`?P>fv|#k=YJ15)igu$ttFuqkof5RE7cNWK+_re`2U? zTp;wYSg@hNHzqz%Xc_2&hjq{Lo&v7wE63R0UOfc}bo1XFIdRZV9OECt3NqtejfQAf zEmYkxEI9+coml!=s|QrZ+^jytiMY4`?n(my zRI~ZBw)mda6sDgp8oWRFB~5COl%f;!(m z8olPOsW_|LMu_e|lW&U=j8ceWH^#tIQ|H){?-A51y}_8k{KI_8Qklp3;aTl(8S+4~ zkeK;_;Dyx$O_AQ`ve}i1ua>Sek%Liou{x&wbe%rE{XH5{&nlwyWU*!A)lqhXvjSaq z?`A8gwY7zBqTv`vy$D!u$Ml;qrH{_gdQ))&_d-*&VJEbY5-QcoKQvFU9m@}g;q%Hx zbCQ=;6ZM2bQiIKz_vf_8ejZ{t*GP_!XLO%Q-hizb#HfJQ#Z^Vbkxbay!JKMsa-pNU zZUc#Nq|rz0iH-&EqB{x$pK2lRjTwR3!c%Jm_bjJ}RyZ;BntZ=}y4E8DaZDl0oQJ=0 z%D;K}7Xm8*_j~-x_B5ay$73YQ$mLrl4x>%-NZ0w#~jzPcu&!CNFy;C4%9wO6h1F_mFm(el(uZ9Es?irPQ0W`V-U zc?eG{4-<^Zia!V^Nf#CEXwq(zPhCC2fh?~6peyR*#n-DmabaU!R|o>#FwL~gRU4f) zF1#k82O$RaQTr>1iS7S!92m97zYF8_rzMwhEcYQ4dt<*~J(+ z&@yyZQf3vY2l?Ky#}mfJ_|T1!gmAX1&Bcl91LOK1iZTm#J%@!>1 zg~@epn=&i?=dq(kau=fJpf^WFKS22i1m|Wjc&&}m3RCb!cOc*5S_HQJY{NWbxc$9` zp4|EcZM3#BIN_EP@0BfctCTgN?;Axpy_40#f_Aw&NB}m+%on&qa%zlud1dkoL*t!) zlgIx2+L<#RuLAfMtomk|4!VT>?+APmY)s}m@T(6rXgc$|k_|XpvJtfJxE{3~9dpub zs?MjEa=(^;ocaVI9QZvw;3Zj+%&o-Wb<^5*OhcS2F@l;c1H4mV8qVSAlOZ}^W;}=6 zIU*bmclqJ{qZy?Y`a{$)aw+0$pqAOHO4~|By9CTwQewOEcy+yPtWgt=g+A)ztWLP6 zMO;Tp;C&Ug?76Tv&j+(JrwEcYl)vhd4HTdoD!3+6%R{4aEB(kiC+CmVN@XJ>wthF3 z^NK{PNMAkJeby(z?%tfm-rL!8pSHI*wwT4~34G71u5}h3Natfn8jHR`H8sga_1ZKs zRzk}zKuJtkY1-R7QQb-T*vdzwYav2hkoGk>qLhNg7USW&tgY)~O;sYlX1 zhk~Dw9u|t@nA$eVqSeTgbjjZE6uqd*iJeV>;SGw?jco@WT_^qO)F`(jz1tdJ8@Jo_ zKCqZH_ucut271yjUy035;Qp+uBE`o0J||ew{#UiJz6A1?S{9IFaVQAi^A159?wR6k zuk8$Dvke?fDRX``>PNg4Db`ithO~);mJ2PU9Fj=H5(*LB~W>x2eXCL)AmYew(2T?$|_%DgW=^0z?pYAS=!Z+R&fFXi}& z&!ci?G&_nNWYRHJS?oL$ay!rN|_WB}9ocxwBJEC`+>J)^ehQ zAZO7ob50|u1TPJ^97*Q7{|n`>XSb09sPoCX&0B8r*G>*?n)rwYECCwHK;1Rqf%R#&Amq2`0^%hyRvy7GkvMDj{ghDOP57AhxOPCwo zV84~f#?|sm9Oe{YV@ipVI2QBvbXmnpPE#r(hB%ANqC5-c0z3W@b^L99SfEn4Z)vaQ zMn&g6&=v(9u9}kRn95eQHqfdN_G?0Ra->Vql~kI9Vnw1a@z%+6wAV_^q`>|Zx3Ie@ zT9&CVjgvAg%x0@6F>EyvJQZnqtM!>W_hj?N5*PRLtfs<5SqSuyXc^7ZqvuU6Yl8nTlR?zG#f zx>N?{N*rIh4a<3V%zQn%-xgi4R;^Q5g=3F%#|GsVq4(OgIqZ**gBD5`Q@B-{TFv#d zYGk^I0yoV{R{l~`s)ZtFAc)!K_?VNFq$ZGosxZ@h&E+-LmW$h}dx0!r_VO>3b_6u-+v@lc(0QEUR`%#&?PF4(3dW{(;VU`I_|w0?dj5q}$C8a#1Cd%cP66l&6>@F| zqU3_!Rh)K?_|ZkO_vIuqIMVDSM>*+dx9ONSwF}?0582&0{D1Nk$g?F09J6=XAZz3M zrFCn2F)E@<&EuwcZ#?eyCVCxl)cO#hsx6`D6!v7UU=BLrFz_i{*p$yLhP4eR;ZQBO zd(h$Hp%4>5a)!5OdW4!VajDv}XfpK_d+MlgyCk-RM@Q-{f5WssChs)?k^IwsZl?12 z-NG@SxiL7hn{-FvjjI_^W|k`Z2sF=C2vJeW8m^BtLnDwtCa`@~Jzpz%L=5J36(dAC zdN)lZCafquElE_{hi#>-LwPfEYS#z>$4m(`Bv=yx#f;&+IMyFDR zEZ31@mXHeK8mNUeUxheKR#8;KEjn_fDQdS-A+Qyr@XeV%#*}|gQD2MOgoFO5G{4kW z>^L($dI~%Lk1ibnIf_$)X1crXY1EO zP`vvMLAKvmEf^svQ2Z5JKuTohzK7oo>;h7SXLtL__#4kQ+J?Ne8q!1$@#ByX{bv07tW; z{ZTatIPyaynbKpLz#_49cKx}gIXn%Tceuty85|Lq7k1pRr~J@o*z|m~eW6CKs_+w7HrIdBr2sNcvv8}qBmI&Uh{*ZVtv zifF#sKh7{^sT^szRJ^QITv#+kH^7zEMWm>*l7nN?T9ACt1jVc8e55TP784hKEeOn% z8p^Jmj%EmJ zzUi^teLnY2Oi3F~T7MkfH={S0u(}gcl_~lJ_X+dX-R$K_{+vtG{OHFS=9ug)mhWyW zCU3@5fG>WEnp9zomp=%@ZDrMx-BuGou+61_TE_jze25v9QXg52+-IT+HGe^MY_~;FK;mtYMTkpQO34LM@1^HHnT_j(b2AovWucM z2cWZXn1}dH7t?6#eqBwG0k{6B=Hi~oi~}#g6^i#iG9dY$*%A9SSx%H9e;q0T*-PAy z-4s5WzScLw7tiI6GO{n-L*6hv#Jjnz7s5W%Z30E*^BxN)RXi&?;3RBJ@)ZxNu#x>; z50&og>ras04!`4Y(rP4FITqa;|-Q`a37x1 zXgYpiLw~|lRNRzmiv=I)LTwUi+YD31fruifKJ>e4=LVaxtyYEWF6|C;Caw`561@im zZw>fO;BHqK*7eKvN19RT$<1sYnKFJ^PL%+pKlv|+Cdt^;OdLWmSfw1 zYbF9U>6HJ9Y=&Ho(5n$I9LY$S#iXZiL!ft)scJ2Z#h?HB0*9do!V_5(Dnzh+<^3E{ zxL1W0Yb69(4;NxzkvNulrQgQ`f7FfOA#%UPl;JePADFtSP)|{62>6)AfekdTxjFcA z_72Ir8aQCgqu2FxK}EZ|^}GfgPD389)E+;=IQ>LeWWD=HlXDzHA^MuK zk+~~6cK06BZqAS%!wuC0>}cCSG1j-Nm483lgX7J#j-=W0A?=z2(7;$qcYraw)MhcE zZ3rFf5)$HCB&gfivDLw@l~>Rzdg(rXaHYeAeW_q)qwg`%>^!U`hhWwlXm7^XxMjr0 zz{T|ImoWz-|126;N-XlS1YaBe2E}%zJ*-JD*{^_9^cHGxGp(#f|@JQvQp% z`u*d7K3o20-RH}1K>0F1pBVdb27-&ChIn&1Z76TBSQGV$KJADn9jV!UirpvKnRZQ7 zq~Zv+n!6?#9e_mjt}tv0UUt3>fd6LFx#{yIO&D`7K36dbtgA zFjX@-x%Ngan8xgAF_fZFu}eW#iP2o8G0;4i!Yi4hx7x#wkuU~@O(`nr0w&=jG6yb| zp&r@30tQIGvNi%T38xG$tDbTZG?~t}r*=OD*ll@nY&+UC-6+G}oa9Q0q9S&Q*7t15 z-ruy=FSAqgjQ*Cf*jR&zGxp+GKM;%mWqmhoZ}$Cy>~O7cuVK=&G4BrE)jfAaI#8X5Hq|ssuP_|2DLRXdkYIx5zg?Y~oJKPN+_@xt{*z#biVBDp`j0t2Dow!)2(Z zw+uJQspt?g9aI;v(-Dy{QAzV0J3akq?D*&NlSM%H^}P;P-I8X?em>!1aPbIG&j_m@ z%5L;v3dN0Y`KC@=h>>HswQV=V&OA^^K6#<7P5b(rOJ#-oWJu|eb7XhzFB2PxwiAl$ z;~SEFaV8}CBkk@k$p%!^H6FfblPVv9g)$`x-=3TzS#9dvnnlHLVNKQZ(=^O2&WtOM zO6rTP1^Y2@uLAxk_aXcfwY?$sghXy%8l)LfPYeUBx<# z7-GK(V_EyC8YU_&Sjtl}_J!)i>w}>9=X#PI7S57J5A52?u#1glBUFKMlR&7e zR1XAI;0*>}o{O*PY4V-4jMqYTjoA|5$sQntpU-Oshj-FFo|cNXGlmJ@_K`)h5s~8D z;m*80P%ch?B8}6M%#rWy;;B+b8FQ90-JT~;bcItQBT=-G_kMSXk45L(X;V{6v9aAf z+}EbD0N*~VuY!_V-QD6b9p!}&y>4JDq#NR|Uh^C)JxKm^$?_k|>3YGC*uqz3W91@a zJ-$GL+_<=1Zg2C|>w7CZx2JYw+K+<8l(lL*W48Db3P!hzKKk^brp2!s9;*(`lO3+Q z&`)bu*rPE6qJdJtw1z3t#Tr(BIm<-Gjnb;{ajZlDPoC(SX2x!zc87}7RATNB9kqv< z(Crr^(Ix_wRu`pXh;qJNqPqMETYR;Fe1z2*`=ygZMipVdUi8~ncha#)YOp!yy=-Uq z$9e-and2{pyH$p8mnsGUZjb+C*}n*@O+CEyAmBj|bfkVeMfqvcq>ry<3}@G7yE|%v zGMW=trPmCmr1PUTW6RJz=w@fo%xSdTbC+@8MEPExF_WLaTzeypG!-AolQi_K_5R0{ z*K3YBN~^pp$nczC%~}LmCIvoD$$)weY0E#1wPbLqz746XCo;dJ0zdo@EdKSI^B0CM z>=kFFg5NnUNwjYN7{UDU{4~W{)7s^QQ@}Jk*Y_ihP(yeX5*^Mt647;oj_lv9Q`RJ( ztmd?lNSU1F>pNm?&wIDz#N(`X=}CUSfCUyxQnNJK*Rg~uu9nS>X^U}WJ+5x@XJ)Ev zuXCcTT8=c%U>U!1{yYRSc81}1DfoQ=Ox%&50Oa2}WEHatdgk*sLT{36$0@m&jOHeT z%^b^hg{^I$x!BLjMk(1PkZDFYTr#cWWmMKTQlb-y27Y$fUZB-CvGl2&wvWgO>Fp-DHQ`tOvGUo>;2B*o8{l2)%N z+fDQx_{*qYuS*^i*Xf*NEEiwm91Fa$Npze-Www2Hve`$d2({$o&gvq}@BN7>uERq} zL$%bGh=c1#F_GRd2xH7BzZa)WrK^I8bbq21p>tO&{W8?I0+^8Z-h75+z!ti!j5U(U z*>CPHvNx{`%}Q{`iiIpo#RM7QASJ|WIa!g@YD3bY(R4S+yH(+Qq>HPlwuejhF{I4W znbHR_>%hZRRA$hGtr@iA<-sEnQqeBzEUc=kJ!Q+_Xn*XgZY{EoA26a0SVQ3Sdgc0zaHDk~+dp8)}RR34vn*P64cN zaCL_0-^3*+Z9879TjTmJk4zXZO6R@uA^-bV|-Myy>sy8{rH6IMuqLPDJ zvfVq~#5xDA?H)0ddmoruY??VMX5B!dr3XtWU5rnRHp&;rgrpT&lqH##Mh=;9U_vQ` zv#p2wGvWEFqbGW8I9ufcnCMMC@U<8WUANv|YEOjE7rXvM8z0C_g_ucHyHnXyVM8>! zT(?{IMqv%vVGwq#EZmGCJF=+`qS?)LmXumXo*s`tly(k#+VBgzIo18N46!|7=*=*wDANY~sah&yj zGOT9&o6-dG`2^atR_s{p!HL5+h}jpAVG!9jrz(m>#`eS9$C#V6QQh2>Wn%5qUw=;6 zO)}jGS7!FSlFSrifzQWJ=M-ifR?OHT`>?Q##H$)8PqyPt#rzEyhEaIvI#Sm{b6|_w zF|pJHLToSn0NIiwS{UT%BXG(s`98h}S#omT8TS0piRZl)M!nGSYLLvm{E1di5qqA` zngcn-jCK;d50Mi*pq|6wj~u^J449wV3*+ zm3~kC0PF#Gx7+zTgixdd6_|oT%5-6;b|}o)a68*?u~8`tGqdNI75BVU(FrnybE-F| zQhB`N5oP$|o^V4k)KEZ3?Ld81-mI*~0osG(BlK==L+w7Yj*<1C)>{SU!=z4XsckS- zQn345`fBTMS=_Yc3X2wHrDJO*O3e!i3pb{f8bkah?I9kng)tPFj{Kt2%#;<5SFXV}a-cX!98g{k*>>TjGrRrwn6P><3J#*(# zQDDN*ZGK)sN58A-C`G4FYOVK%1bt81J~XQ0_IPjPz4C1+fraw1_4(8cE?1Z!vLy<{ zfODcqY7B^VgP_}%>f6!09Su*!k4y6`er0q*9~eA!KREgWYU$|r?HOJif)TcX9_A0%y+oDA4)9kI}tsz|W zuR#-zFB#4^BatNiS;`1wSNpy@=_Lj$B0Bvhj&Y2rdN2q~1Krf*i-OqO+c6fvfaLs0 zO!P`v*ckiAQHR)_*dfmJ;C)>d*~r7dMmuY3UQ$e^cB%K2oqiE8T^ZrxiJ8riM7D$- zNR%~fUTs%cvUct;HCiT!he3NYZoiF5SyESdfyU%y*sA64HjMJ{ zS_3M^`OFxt9w^?C|to2l~6gvuf~3(ppr2*^xJIj*6t=>D|7xTU7lU` z>a@oI)#UbSPOgNSL5wCk=t9tv+(=nmP)N0BqYsk%ifEDzI&3-Yexk#d+jVfB_Ze`; zP?Sm$7k&*gWIUsVJpiwo%QE~7p!%Ps%by|se1!1-@fSA?C8|f-o4vL5 zhC^ogf^=-MD8x?+*{_eg^2TrA>|6S)(m07rrB@G+B#&At&%eiCW6G;23r(cF_>k6< zGU4!sJlUNX=y{_zu`E!1)MM`UeN0(YCJlFjUliQL>1+u#>7Ufvi(ypM%IjBb3D*eD zh%tjsmPR1p>eD5=+Rd8GQkCJ0%~d=IVffIqV+&Nu==F#2mTW& zQfg;TO^oL6U#9S#;F$>7yVJ?gHNl|ow7;55=BH-A<8}Aw$v2sf58pY45*GKQy2oud z)WG3wWyb7Eq-t2_)t3)9*7lqa>b_o|lPVPHmL^TL2j>uh*b)W55%?j%+O94F^t0^%x97_V zG#7R{qF@*c4UY&vHxJXZfTIkqC(osWY(u!e@1F}d-^L+fJ!=Co5VPu}5zYkIY?=#q zA56tVOjlpJnVG(7>{H)a#zZlUUo=u<;hLm;DscRCh7Rhi5KcWm-FO6CENHBF z7Ud75iv1069w^Oa`X{ywYQk{cg`XWrXSTzYx|EJDREf2UkGjoV_8JtDIh0ys>V;GIpqh8(+3~U zoF2~{-K?`ME+?`q=8w8YiW@Gtv0YL6eb?8|Rma9Q-@MGx-ng1`4r810Cdx!?e#Sn{ z1BE2UEXFDtRZ6(?;UhG5Vm46h?CfS-%azABRqU+3mWjbVpXqIVOsetBd(x7)G+>O7 zzw?OBsdal3s8Ob%nHt#P8yKOdQ4PQxaM4GEQ#`~ZlwDx9o^mH4)5dfDJ4SBP$>BDf z_(~-YUWbs)3b~u19v~wCc5XX+2nl^^pq#(>s*-bMYSAyZ+ zef7hyR7fWk%r?y>IJ+USzZ9OMRiS>|5nDv_S`%c_rm+UHVzXpHk9KQEk7zw!#gwW1 z@}YL5I!ds-!@#GwQ^jik@*GTrJ*Yuqb~%aO6k&ksM)%JcPzsUP4CK0G-oH$9XF&1s z7QE)U<{pl40<`-k82S*FbGgh}m+p`6&@;uA`*(`!@_aCPI%j9=p*yvm>-e^w78zf@ zIOROs#?b7i{ZKbjdfOqb|6|msee@2>`mr#`M zCP@cmAmVNSi?~3=URrnCgQv#Nw`57LZ@G)_+sFYdu{)?pCT~Y zQNjQ|tE7V`YY)Diec_}cu9+XMnNNig*j3oi%vrU(P8!1y0eZNau<~@_TDjA!_i76m zVMnki9Ai{OL$@(mA|ZiRnG%~;5h`oJ1yzyNQ4$Y#XSdXFN0p^DHHH-|POn@Q9&fwb zxClj`*rcQ|Lg+`Y8EauqSmS+?@O|}LiXc9w20#?kZ=mC3UmxBIhT%jKO&mf}pv`?v zv}qYwU1m?7-+GN^$la9C5oj1JyUNX2U(hjX(Wzw?lDWNzMV`dSfM=6fQ4@UaAD6UA znC(!3#iFE0r$+@S=8*VCF>?a~S1D=@=$TvWRe%_vs$QTF8|=iYhuG7< zhGPeSi+n&7Yj}2$xdECm5L#Iealf=)N1LuvvwFiH_wYy>U8eRUIHMtG+R&=kPi@ox zdH-<1gX32SHl8MmWL~?3kxy)u>Xr)SGui>FUA8?+ryk#$%ZREHdB|B(aIibtCeWKH zXQv=rzBD~G957$H$D7V`?Sk{7PNbf6@1$-SV?WmDY(D1WUR>(l&BXV`WqA)oSUEWq zsMr<6RIfg)X&SS$9q7?{JAysdZMEda;qjx=6;{t3jYcja36t?qD+%;bw{>rXb_7O0 zJ7*>FBrFOCSJEg+YPxK8y@j+xEIHP2+rtChERX2UZyz3_s>6n=>fII@d3XvXFZ98k z@_`q$zQF55tZ@3-@Ga#-amzv!x8lup(KWjJ9g@bX!!OAk=`k_8zKFzjTupCuYN@YO zTf%nm%GL_qbkA_zLE{q}emiS2;`P^vEB~%Z57G9spWb22Qle%?l9^M;^K}|qlOOPY zy!`ltOoEPUUN-S10+A89BQ2OoDDP5E=WS&T^XA7>TnZfTDD7o#V@wf-Cw@ z!1gvr%^Tcv33Q`gg%S^B|E-0S<4*WgTF>^<*%j_0Z`c~R9C4yG550$m1{dA9sKzt*H{cMheobNdUQ>;sTxEqzfD<#%9 znMa#xNkZpUOoumdK@1fnNvFm+7sRSh>q{FtWoL%ot-#RU!R};5xxl*LmPam{oCV?u zW`yEsphs%Ty-d3Kg~jm(!%7{ye(`(=-;_XU*>b_Y*55aR zx9vae|AJyO=%RXNM@}*6$4f;8cIizvrPC)HMq#2tp(d|jW8Y7DuVOn|3U=eH_WIpv z-#R`oi*275EQ(KnNzfhmIN|ZFIDV5liP9cNE&aLP7Rb1#6u3uxuc5hML#AD-`xBdm z=&`#1fV*rV9dJ8@oU<@QyV#`8Rq|7tlig((hwT^CcEz_XN-yuRx@u4knyNU~6h;u| zC$P*Ap!l}*NL?~aKaZL+in6Plka7y}S4)^#GkY0f--8_!Uh5bmKfl+llVrLRSe?BI z8MW{pubVOU)_au1Jf`$xkDG3#FT0;&z|v6rQ1WTsPI=_&*-}&9xN&<52!iy?X-?O{ zl|=Mks=uNuWJ_wgaIMxRkl>BqGP%3xb!A)s88N@fSaLME_@&E%Wq|tgh<+66+rE%X zqi(e>iam=1jt?anC`HUprxx;q5!c2W`0;}%U3(9tVFkY(X;f-_&CV4og;lX4T&lW~ z$+c=%_!0iKQYSH_)DO~6^qo?s_MC*}gfkm-el`L3yEaJ5WG#|%!vYC|o=YRl07C&! zBNl;!LTFPFlj!SUY{%t-yQe+uRWuz=Z3PN1`ES-^5VGo1=81giUf7=M4Jl(+s@rRU zHfg4Z;SFPiOW9zC#i-NvapPn-Mo(lW^|)9%A*nHmrkS1qOl@JH^Q${P{F(+)Q*cdG zo+h=}RyWPwz{jDE@2AsG-!upYeLq@p^|5E51S3V4F%YZ4c@xtl6scKE1xkcb0qh*@ zUmM1}dJ`IjXN)4=M>gMrrG4o(%%+*&Xv*I+`PH$x35(=dKs zP&P{|y_0ZtZytS(vVX@wB<|iQT*tmXotl{!^wLZ|g~xtCHw4)&K@Y#$cSPq!WQtbh zB}KmMKK=65lIFS{v%dI^YSJ~xYLYEqM$?67J&tSQ^n!Kws_To1$alsl{f62PPj@G@ zbRdbkP4eMUZn94L7a{gVQMInEyF(=`JFB=#=oTW#?sgX$r}d;xf3ZY?l9f`mTfFdz z4YFCb#*)#=>{_(wHRko|JK5H&CpV}hF3A2$HQZgri}DJ}E!SKLZuEb?g|aG}oGXyz z{ppTLATE-(8YuXO9o8!oyK9%otFT^XLqb_7<)PM7$}cw@hJ}cvoAjnZ*~($IhrIrAORa?W=Q^~B@`I$5GAr6xOBWig`X#{1Bi%I{y< zza8f6&NqMDOvQ>Tovbo9A{wrS5gvF?J zC$`s~CTXMD+YruJ@#feO!eD_vA`w(S6rt{(renZW9+^m~5l|DQ1c+Q&ciQK@>jd)5 z-#)IqI5KLPN22B%xt+{ni~(+6jerhZ4#_XPIiVR2~Q9bsjj?FaIZ8(Exv4 zxqLRzB$eXuD}}X1Tdk?iwi(AxM*3&ZCvu?LvoIBT4i|;sZt|Kp6w=ZZvYJzzv!FR9 z@cZ*#M=i1j2zPMROjj$zyGff?Zjen=sX8b) z=W&}0C5rTY`Y)bAV$n*;f?=Y?`K?x&{UDQOhPMu<=Sdg=t@%R zA3t-nUhL$sNdmi53Y}9GIcGIpl-1^g`|kU7JnbzG%jzP^Z$9jmT7?%y!yCSl%JM6F zFgF~(?I^!K!bs7d8@pz}@q+Rq(Ha%vWBzo<8a`RU9x%%Qi^cc=BViumtDe9^4eQDq z##;&=Y>xZY59s2;e?(@kECg!Gn5A=K#X`vt>aSfV+XIg+E> zq4$Ei)&}FHjwG+;lVyDl<+{me3O#cJgFTRleCep)nU~L*lDHpq^hD?2;s?00NK@{4 zb7hM-R!Ordj?%9sjBRIGAm822cp#sX5v#+O-78Jia4QA!4TOS@-j&iVC29j6qCha(X1DkX^ch{rfdrlH7m0FVb z!fLDwzIH14@%le-?Z3ONzg+!aQdve1Q?mGJ@vNZaS*GWB&0%-!96#t(NR)=T34ZQL z#$~A2ft1fyPF!n`Tb{ZsSAg~-EP8Y$xi&yfx3{v76jQO^G9Foms-;>6w16NfEdA6i z2d-8PgGw`rk+Ah`3B4hu7-4KrcHwzZ(TVW5133G3ychAd{70$oJ@Zq}*#QeLvNYRJ z3S(d!x17x6Pi(xCgm(Y9_GvO9-5bW#s>LrKQA96S0aI`3oN?DPO^P8XPm#4jCt&i; zjZNv_#v}i*+o7!Hu#!#ohVK}5ajbKclgm1^?>cRKmLo1#UfWIJ={op2>p1Qz%+fill;CD@cm z*>I8Yv1euqez=Vlo8U8)8+*)j-&l~4XO%eRjyieY06@8P-H1OG(OsiY8uAQb!iFq& zGpj*u6QNaKM@%$b8u{S*}lbP?DjB+8>GP1H521dK_7K3vFQGdqd{dyt<&Xt{FHY5yKVEDI!g4T}}qh}d`W|Y+9E&f^hmEKg&#NZ9$L7MFN z_S)2#)Q7;BAb>PN3WL*CweM;seqyt2beIJKf2BUanf)lZ_bp|b;G0L0^FiPlvB3|3 z%KZo-7q6uY<`Hofk$+qoKSX$X^-S9G&VXl`(dL?RZu#w~#ZLHQWIJ z87brV0I!tD;JSPP4UAbz@zB&|S;TX0xw$@cNc;X}I?r~`Y>TaMs`#AWzM3V`NHf&( zd9q)H{ar_7K1vB*=|Sf3Z&04btb_OGZ2XrfiOD~>EW_M_g_Zb;zL>yr{j?a%I7!S$h?)m@5Q)u9T-oPr_2R>&px16BXWFH+;yy(2!c&3i_(k3UiN%Q7Ix znyEcr{3+1=%_{SLo&CQOnoh}tUb#UuOsdrQysFH5%r(WM7clTYd2GTKb zTGVeEnmdIlK4;>E;kxXc#H;63WzjPi-a~aDznQBt*-=fsc^7ALmCQb8a}hL7xqnyE zqgyR%+kr6D{vtQr7Z-|Yf4W5Veh3tXD=D7Lmq(#AW>?wG9XK|g7+)&ZC;FG2LkXQr zqAI9cgZ$TSF%P^In{+qlXv<>zXN85Y^d+;mdgGnZ4}I*Gs*JZ|m&phOifnf*H?w~; zvUHJ|t46xVk@ofVzni4|_V*OqfR4oPDs3+x`%R^a?N4lFmVYX>{q?u|KR>=IsbxE= z4(ks5;2Q~%sC5n4F0adgJ|t-Is6nK z)+A`MNaS)Ng4{CHHHL$Ac;_rm`DnU4mqo8;i72KTnkH*pOECT35+$E(7O`D4LvBIA zTc5H*U;|+*iH(aXKd!eEk3cW5*S0}H1+z+Yo|}|@j`Sj|4XU4~eYM?FD2L&6vK`CxvSRgn z5ua~0*7{p?BGS^5t21nhMk#Z*N{grt!W|TUD8=E;K|+5<`+Mi7$;h*ypMJByprrW9 z&=cjiEyP5ghGhTjEP#zk*2rk4)469O?zlY#FSHCgpCfm<>8v30e2#!%91$4-tqH9V z>8rfB%wv__gX%XcggoonOm6QU{~m}G6+sRlqL@OmB|`yV%Qlw>qBBsHbi-PGp= zsMrsO9e5JcL@l0o7FDIY=(8vBB?+wGV_9PK1Y42SA z%)ZnMu0$IY@a?mf9=UjVuU>+5ub1VqAGgO+k276^5Ss@|hudeiEzZ?4ttDnszY$46 z7p~hT+z*|pQ^6Mzp{d?7A|-8F>RW2(nZfu16eBV1toOuyhH$&I~`yqOM zUn--V0ezD0hZ7JO=Xk1mx$ontio2DemFZ$FGV^YO61}=gTy?0sv4PKt%-m!_lXHfU zij}49DD3;m@Vt1d@Lr{FM;ZqjDo_Sx;Qe65uvy8Bw{s!F{JXK+Z!z7iA580Lw&|HA zy_)3(uQ&DaK!+Qho-gnLosa{10~jH;29iB;-@64!Cv_!8^bCcB1B=*nHYNx>h#&#bjgG zrRqjZ=YN4O5;-;qC0s2)Y#IG1^Ap?H(ys-mG%>CbBZ-6$_0Avore0HbqfC?KPFuX~ zPtwA?Ta#KD3fy8p5YNNkjVc*!*kI2pDc(-j>JCs0D@Q4+5Si3ZY;}g6NbS*slp;Vf zQ0Ep{9HwDT>G{NVje7{QtySkq|3;fKWO0HVYqUSK$uy8xkm_i;AtSomu0ko~EGypZ zoAj@7B~k`?i%QM6c1&+)ST(;v$t1%3`J>h_}6JdvO)kVM!$5B`BN4PC7A3vZlzQFiS5Z= zecTLF*b5b7Bafq-=4+ZvW#*N%AV+4wkTJ3&yhJ87wUTI~sonFq&B{VS$hkn5lEV=B z#CB!UCCnr>z1_~lqN{{-#PGEKS+@w`$8q6*?5kFZPe}8n?{Pj7c}m>_Z7MCO&6pBi ztL*vID#)akEYTdF>bI-}_K|E(Ir^mLz}CO<-fn(wS6)SvG`?>jZ+TMFyQ@CjXpWt{ zO;(Y_d%$I2CC@uJX!BKx;{rn!5#6VJi)>#iS{B=|%eMsio33yhwcEaJU98+r^d&Pf zImtq&M$@=K7ipxWAb=w3K%_2iA6CAYa?lgd#SCU~?wcB@XP;&_KzJac5ORO8>|bwu zAuRuI$eR86nkqwK7YbOh_DTLiMcut`dtcAk&&<7dBy@bHuUPy{Ux5dxFgQc)in@(_ zd@IqTMd<>saPI;t21?-0#nRiou_ZyCC8!GaCHu7HW&5~Na)FTB^`1#%@+hFH_Gpe} z$4Rb-sV4LT@3J{=(DXwux#svS|GHe#4yivYVL3-yLaet!vDe>hTm0NX|ELCX&NQ>q zXZRGV@&zS(#{LIC!7&0zZL=|vgd7He+=hvMV9#{|?d3{;xIJzu@|NrT#}1BG>eKo` zx7;A>h@i#1sqG4NXAL|pdDy@*o(6y+p63R2z|Tqw&&fUfzSyphGv;PNAC?lhXxlP# zcgj?_8RrcV^k`{~;i&RTzmx4III^Uj5kGu7P@MdU%{Ohid$fPQT+eW9!-Y#V#FY8! zs-2ZrN*C5cXZiUUuI&QbJl`{7sE~_>2AmT?pQ${qZ|(SJEB}q{zf7VWMX^TnLQQCLIfpdqUgay%-dC~nn&laHx5=*7mAmd+J+~MY{gRg_?7KJ zDzjX^BT}t(SCV1`qx?U zmQ){gbB;Vv>4lUX7n;O&%6~i>9b!p06Xc|iy&D#|=0d+!qo?r=5U=Cq1<$9x;CYgp za;Y*nX)VduGI}&GadgTv&|HDbFh(w-$xH8;|4Lk~@!2raQ6tEc2-Oc7ay@Dnm&!#z6)FrV|%%eX2O?S#7 z)lHC0Y++hwVe*qvsLo1JXV&z<#ii-@2k;LcVOLkTfaF9^R`KeC53c}leLizVhjS5%nkoGrYu2-KhJ2)%|hr-bQ8U>zHwcXR}`*20l^DW z2V8vR!fC-{za}e0%)fVyX)U@cQA;fQ*wp~BBVO&ezxatQ2~Tm$6e_#=!aW3u^dWLr zMu+XlwK7gceM8xOo~%8nQ|kO-jO=^Em~qX*rBF+1tsk!0{8)WAO1B@ep8hOPf6Zk$ zHnG2eE~Q6IIS%B>I>LdJYEqq#0i403bHN4Dxzx18+|FjfC%Su>I>HK@h+MG`XM}o4 zN2d;q_H}0K(OZ2I+qZ(Y+kldPfDyC)_8*M$Z#P_TW-vD(6 z?0!hjqLGEmZ z_H9R4<=ZG>wQgXd$1sx>MvHN}#Saq31Ppt+^k7154!sxFQfOXueXTWBBbF5bbZlWl z*ZXofEOBlnHF1Wa(8<>kuTfk&*5fc$FuQrs0?#uMbS^e>**;J0oHU{%=ab|arAg07 zI0uo;tN_PYEtzvIXLUoxpJ}D@luy1MW|lXms9m~dT%lRE%Dv5{fAIxI1#(euk>3mJ z)9lQ7R`-LwaiZaX{iSRQX*x=0>~Tbt`C{(lF2(W=mc2ezou#=rwtCKm-1Yd%9Sxmn zuoQ&n&eF;V!`3_Q9D znu3cFyjz68eVz0^xh=`=g#0X__g*-Ls&P*WJ zJSqk$DR|JDSGihelOK*aLxiyvT+4|rImv@-J`@B}(FDI3FD`C>nIJchx=g+GOKcfu zY3W*5%h1pz@Gk)%IfQ^`#9eFk0R8oaNmw@y)@gtd_8tZMmQUK{2FP0_r23FL^2;`Z z1QSiky(i3Zw~Yo-oZv0(55C5N7eO~qqZNFztO!auz84F-xVQ~0`g4B;0Iorq%&M~~ zQWwQXmopEFN>-ybOI)5uE0tKUDmj-ektfy(M;@BHwW(BTkjigPUisroya_uPfxN-Lj$rB*1U?r*0A$u`f#;~UbBnP||?mk8; zgp1K;KcZ)6x@10z~%HSmyP;+-jvo>WRq99TfYlV3I< zJZTZ%=zy1t95G<`3NLIzB4zP?@XZqjFJT4^iA1}0E2m0R3&C_JCt7}V-3Zjn9n^+W zcazev-_%$Y+5j=7beeblC*YCpDR-y2d$xZ%Z2RM{&HJSve>E0YvH@aSj>#C8=TtsK zb;DN3O1@w`Bh$tvyNc_hx;P_icBNdmuTFAw?(s@d>cL(-kVxMBJ__#s4wD7E1o-chkC)(A?tWo%x;QoH;>)2k0|`Rdp-T^ zYF5#FFTbQwfav+F03gXY*Va>ATzGS?nCpCmqZ?g`58q}u7y|VO+C!kFLG1h`D7fKN2P9(?fMb+#cjhh4YSN3>(v#3K+TBs8^!EU`hC>%Mb_J{ z>01H;$Gt^bNu>g!Pek9~ZKd|OyjVzWd9&`T%w*ZFL>2Ev-S$N^SaC|5Jk3BCa3*NX zJ+qY|DVGPG@HV&(b%1x)DX2B!D%*sI@&h%AY9<>SB$eX#y{kc3<*ZbMh?eMsjc+$r zP#;Af-?x`MK{@vg%f$1!sT94hd1lbUF4ub1JA7se@|^N?(j3p6OK~64uK)#K>lssW zXGPgjyJx5HI#~rkEv?^|So)vme3^^Ve`RtE;mBa2WK{m^;e!*rogD#@$cRhvLXk)-KJppY-~!i{YV%Pb#C8F4w9z}y z-pJ;rwOO`#&?6q?iB{*$`sWWU73-6-UR8}0%SCnT$QldObR02TbWDnz3>GBP)RCfv z;oL*@Q2D?St`G~2&cga3w1Gu_cyOPS;F$9uelkHp@37br^bdEMq!+@OizV0>33`Ei zo~wHBL*v%PCnH4K&Nkz>3*!Z~1jFt;7>{i|bGrDB*A-@rSB{5V3>7s;sI9dM&i{_Q zJ$z<78VhY6w!f*F^G#PA%OhS5<=iBg7U)sjGuM!*Dmddna{ReTPFl4|+%?B+yAeoY z=W}tB3qI$OtjZ|2vR=&9%hdCPO&PUED#qr~6K#1C%?!r}GJ^Bt6jYK}k9rmJpU%Y< z()vx7yxBlEZ~wD3{^QD-Glzj+hrog0^92(Xe^a}l6Zt24TwYNmhk6H6SN&)>fOWyj z+DUhRgSrzc9p#;0JUb2h;QLI^MD~GFDJjyJM1mA@|<;VPb!a5W&A)|8|XmFZ%xC3r*oOtvX zDri>GLU8`cv)#p#w{N5O8cxBt$!Zq+xY(kFgjkDR0+{Wql>hiVe?ItsFZcb2D}BXc zUCB~RoY;Joa_3G4!(>UWBkPsv{44-zxU5R)tKAvF_Z2r%@PPiEM!&Y0hr7iUlS)1R zv4YB*4M(%dmP|X(gW2I0TquXFL`wdmIa&Y!nm=9&I4cGKc(sf?kbvIxI-h`o6CIxX zEyeKJKx~^Mpe41ddSc5=vmyzrB8G@7J|l!WPni51At!gLaMVU@T7)b>3}uugbm&OtM1OKx z^4kHKL7`9(Qd-dfdpJ8gmrTM4DBh0Gi;QP)d^)Km8vV?{#)K@gG9qyJ_+57!O_7@vfM&8R;$Zce$?oy zo$u8Va~-{ah7*$5qehd~pG(inNb&l$Q@7aIu0acL%O9v(M{(p`QA;V4zNDR``Cbg@A3qHyJ=3!ZXRQK28L z$U{ZJ`e-BWl^plScwBEk0d?=I^;^-eG2S>A-O_>`_TO1+;1NV@{6JZrRWj8}jE?5s z1m;`$g1M+Ek5nR6rIU6Jst)zDajU=n!%Op58-L|We3qQ~oaz3De){9sKk27`rqcT2 z<(tNoZ`qCl(`4CFu}urxx>u&ND39OvTm#}?0#H!aC$RH5{sraTaN1IZOnft&sZ{Et zlgGJ}2~~^i9Zq3ww-KYX=U#~=0jdVY1{H5*(&M(9Eb)ZpVUG9x9}{xAoinWJzPWET zu>L?x<6hmuwq9}qwd91b>W5(vN+?+RH79F?ima8%{`{5M7hC-EiC;jpOp~gTG(THK0*Xz;dp_&A?5(lJAiseI^uT}X zYF`~ewvo1$R1Nb`=vZZz=9yFSu^nzmO$Ic@c6cluEFFg`xrx^dEBj-H#Xo%dD<_4F-n?% zUsi?ZUj_9fNiu`!+LHmX^KA^JY`)1Aw+2CgEt0W0*si5SeQ;+$>~^gzOre%aS2pJ- zRL@fB_-|)_!GX*-JWn+72%6LjwPjBk@eUh8DLOS+eSs>%KYNkL!v_ zQjY!;-OxI37cI~ywo>8Ao44nAJ6F@USJe^uDTu#in*aM*(|_EKW9oNohbRjX8i>^q zar)4Me$|w9rw~d4g{uYuL!7YS%P$4-^+EjaA6 ztKKIp{=#)!IrWS*V)ET1&(o&$M}27SVDk5@)nb&ghla*VX7h2Y@%`_5(GB{vsqON_GK3tnz1Sdr z5;j>UGtfvb&@5)>c6n8HcXl2#?pUUEIK|rAZF#HVY#E5A?#_|6siCr;bN=PjJC>Jd z^k8~!$&j4|+*D82+d97jz;z?Wk*Lc~r!L2;v`jw~2g^ ziP`B=AX>)NY&S9op#@syVt$Gf>4R@J%|9N9B*S;+;W~R8UGREk(W#2Kv2Z!ZzmZ`3 z?V-P*YT-{E7y6I=+Am*Xynmjf7Cv*Tl%bdJ zBxSwBEw2eE8Cy6f4=u7HydgrU0Yz)C1s9d26wU+Hs{j;N&IOSio9BIWQMfP88ONG; zc|K;Hc%K=ixt0EW0|@|?NtW)HzR>2so%X+Gt^8Y8J003NxU)a?745m|!K{``kCQ6N zVJ*qTw#OvRBPpErcqY_9eG@+3T%Xlk!7C`>m$vOM89XtydV(pBghkkbuDnm^9rr3G z8qJRltMUY$y4%48FZ4g1ey4YT@O<)GXJ2;)K|FVo5cYmbHHR7LKma7k(4~|x<{6j3 zxM@RSLf%`aJIn0ywS{F*mLo8ZEihJ7r?+`{M2=JWAW|T3ouZ_7i8UI}E^l6z^oDh3 zsbs$?k2(Pq=A_&ajyWLjkkWS+I!9~SwExbK{zrnuu0JY%{`lE|0B$63*KLLP@z)GQ zCJ}<+8jX`WX3@QnzNI;53`8D(Yx(*z)9YZeIQ?*sd_6TJD=p_@X=C3)D8JrWBeUg5 zyV>;cN)O{cXM9Ei6BZpuJNV{At+TXOi-+^3#_cQ}=c1ow#_n1I6E-mg@>!?J%&UQ+ zp^N|6WydXtVcKzq$#X17Llt>x zOOH1i=a8@zp`nk*2W_gm@j)+y(Lb_1%j6aX66N@GSn<^x5W&(JCxpxS40h#F9)Gh> zY@?R*olcu>+M!%kB=_@I@=q_B5LRg9{aex_S*Wx5~a!VCdr7b{zGzjSiZM$FZu}PvV?q2O$gTC-|3Y;7MP&g}B)m!Di8%He* z7!Xj`Qb;QeII6i^@N-49`MLzhi-?YTm0nW>)^yoF$kP#1cQFcj z{qV(@mjABn1IXkJx&TVC08r~#!=~t&S9gpxWHZxWb>||Wk?4vlj(3xD4aEk0eWK{n zY%=qt!wp%-2NQZ0SqWj75u8!kApBl(tApB1cUiE1Up{pvJf4c}RFc=!?HK3&#D>Hs zRb_;4mT^{^*k>0P!l?yFi~M>;Fm(kiNb8*ji*JNYVX~TpOm}o^VVwm!zs)i8+ZX>VepmM=zvw^w`+s=|@P>eV30KW8M^gg} z2HgCy`d5SLh~CcL>ofLb@CzNm1W{240POuI0fIJuG@U`H3DiJ!{5U_Cw^Lh?TVOXl zKAyA8*{>MYj{sAu0iyFvBATB`<|QX2iuX({7nCX>SLWCa2A2y6%}F-vg{IJ|`PNd0 zVDnx{9^ErO6^MPrLN^RImVT~V;&wIEFd@@5@nOHIOEjZw0AgumKOjME{UO|A?X$LbrQy-tKul4k>PDIneSDSYCe3J;{rJ2^uD|<<0@(*SfS=kwI85wIG zF!zCpe&YV6x3LE7ek5$GH&Sk^lX70w8RQp`FO$i$1D@@(vlF%I(zXo`4ij>NM%wQt z^{6;;^gt?2?Q-h?9khpH4dB4(;0ND81POyK{5N5!(bD)t?U5Y%k|l+q@LfYsK*iR6 zumyp1kGNPhf+^t>+o8r(?CCX}+SBykeZ6~M`in*R4*x-v^k=RM!6BU%q}JfQVxbSe z+8&e>whZu=<^85|Ax<`VRk>g4qkE8w1L(;Nf79LjAC2_yckp8<0(qg_uH3x&JF8BZ ztkFcSW^$@wXt$p|&7Ql&Vluy2b?p;ddD`yJ(Q!CzrR)XfO@T;5kMZ4~%!G`_%T1=! zqcpSTYNHfn+o&7Ve(w_-aaI^$-5s^+G{T3DCnixK zae<%Mq@T{99kAI-T6bEUJLQ!=g!%KjJ>|A*)eF%ya3H_5K1Z=1 z05@Jdf|W2k6(yGTnYb2+&7c6{7bK5FyhUpLP%T)_^%?*Y9L8O0x>7E8ol{AQY$lIF zVtoSgQZ}E^<-Pq(v2q3tE>=9D#WZgLaej_WxppH3mZnm2*>cj|-tyai!#067QV4{O zYr1u?m+N31gzStaUr3}YQEV4>%(C&>lq4Gb5fczub$23gIMLs|@w|BL^8SaV)~@?& zMgc@mETAow#(zZ~y=Lt$9gmi*$b*VIavo<{3IRy=H@Y&bP*fv`qoeIZCs}x!tK1JqQ`9 z;OQTr@U`U3m!Qc0zktroewT{BeeR2Wuz$Ay(dk34578FwJy!%zIlUadx3_rl zyDKn;Ny5C)>4yUJuG(n;LJMA34Yv>6e_OUa(_I%F5H7z=)KMlXj0U%YsQ${uux(hJ zd#F~zRqC-tNns~rIJc?XmfcKWO&+W_dtd$pE9X){m$f|PktY&WwA!JAIJ6rt?qUy6 z3+;9SI)g#(+mdr-J_NNhBX>2kN_4<{)Vej3P|CgSika{iIXeiXX>><(b`<=qZ{kS4 zqA3SEE@o;)yG9F^VQ>YNc!I_3qkp)U(+7d<6I4syrMQ6P9q@mC~oIIsW*k*P| z_o;z{7-PQ`=MBHA(AEo6A9W(i3y{)W7e=QlZ@wLeq}-$KyTV5*FsWRZN|u!c9241& z-CX%+^Z&)le=R@#ukPdOk+}|sMhW7%ur|hVhHkdSDGdpA?JeB~QAom8-mg6oS6bT7 zi<(h$E~i#y@*eLway>H_Ef(!IO@3oHkr5V@{-#^{bnhO4+d^iBl?ZD_C*u{;(|7WwfWQACWXITan5DlvX)_*ImVw# zK_+xW89`F@FgGVh-z%D~*#Ce%00F_9cD%u@m;Hr< zCppx*%~Qmd={YDTcPS)`xcs=KK;F~8OK!SLmj^lcc^-4dgcyFJXWA-h>HUD4Mf1kA zxsHxk^_0kKj}W72OPv#)ZSLM$f+ZS&B&Wn*Lb<s$r@ss5TGU;4}K@Hf|evT}LbB~8sPQbeCd9sHh@oCU?)kw`! zl@@vn1Dv)yAeN0WYi=^IY_&7ii7^7aoS!?T>CRN91>TS`1 zbeApmh{AW0?=;pDpNgLwhQgdEsUy3>lvrW+rQS*$2GB&s${nXA2*H>@mv;3O;|8>G z_dv}euePf&sx)I!WYgucOGcS(5j`;FLch?~hFA0b|3ln+$2FDz>Ebv#qoboELPVN{ zP5@CLbZ}Hc6(W$(14@<9qy&&UV};P9OA8uW3JFp|2~DMUDIv6g^d6*F@g8Ts-~G+Z z-QVury?b}hALIn`3g>*JIL_o_t8`5gNRK!u>)7x5g!@GO=?ni&IxAy zzAK{|H-JEZo7sLPNypf%Rn~!9)2gVO+&%Dr#%1|Gsr3CTUS#w)IO*SM_kZQjfTU}x zj`K!HG30glN`3>1u+lfrp%9p+BkPnTzsz`a#lFzzE1Rp)tulJ=h?p%YCnc^)$jw{G zmKBZ4ox|7oz`0H;yFBCULq9As%L#9fQ^=j00;Jl2{D2?}M4W!1O}Iv!$L@_773J0$ zk6m3;Dv6_A$oA_JlET<@fZ5$lJA!Z62;SZw<(f3G5tqh!?li~!`u~~FvmN2dwT zI@srSMl6z6Fn5E0Xw{|2u+6J-iTU1cV$j)X z1^7bRg+}rG0Mm?q^|5CQ(6~iI-bdNbnds+EkXoKBK4SRCmNI0`{{9);UJI0;QKE%3 zNT7GsOyvm8t^EI|PM#O%j|ZCZe{^a5CVmU!|CMdL=0x61h2;bHgrbjD4<@nPStfwr zM^@?<(UlCh#$W(L&ycKW$Aa`@)7%bcJ8%BBQ1hE%OYnGOPy6$ZbL(As3a1|b5@m~q zm-e+(-t!$9d8=Ffp+LfLqosZF%Eubv4TjBYO4-C_{9XI=_Td%sS033KGhMy4=_U;b z7>%SbI8p>ba)x2%#suZPn!`qcg;D3%h5p|rc>wt(iQvXO{?-Tc{SxXn_S%Csw=h*B z_yU&{Nfe9p6B*!%Qi0lY7U=T&@jQ=~jlD-apDT;2UkFdskJ8Tr?8AalYl(9fWgR%# zX~gt!-D~9bpejfEZMemH>iiD~{og$KBileUGs6<)G|lE=XJV{%q&-M-c0~-uPm}(D z>aFzA?C2z%yK_wsq~WY816lTRr$gtmUlO>NX-u_l-G$cbT)wvxTh7yvPlp7c78G`S z|6lQ^`Zi;Zd?-NH&fEZPePy$6AVatg;#T!MUgt#F6UpR^Lg*=uhAu#GpRi8MBrnu{ z!JVG)k_5Z?^`MXr`Oo>3ws{}-Xn7LN@Wdj-cCp*tPC7i=!9>0KW7E|+>QBFQ7ytw# zv*I_rsRwaxk_tG6#wgbRJ>PU2-)_*L*!&@R-jQONTjgw>ZRVw`EyS87zGZ&O|K=?$ z+!@}fVUuzve3(_abJn`Bn2qY`lFM;F5*KlorDxHW_F$-wNNAYI3+N*oFildG%Ra6t zjRmR}Qi&Oh-Mu)GLp49;%Ccv|1`k_}&FjW|s~7b@SNfby@=6(CLkRufyMz8KtIfan zt0Q#-j6ySf8rYxjS9t+dowd1(xw$F*?jta9VqB0B!sa(OGTdCG>_FdcE9hhHmm9%R z?D*zbhXlCEx_d{;oH_Cv=_m?(krnnt}9bVa+zvw(XBi596Y)n5%E;WNU9}wWE69<|topOP0$L zcaY+`>a)6KZDY{>7{L=i{A11}<;PEK4jjMM@c+X0tN$8ux*PtLZFM*1E1Pe2CQs&Z zV%~3X|IJQ`t3$ImWj9A#vRbjJq$%%G^Kz1C>)xw*f!*C6y4&Qke%<276GH>zc}&+3jZsDIs|`G8!I0bE=sq3 zqe2WSW#|XJ)~`Kf{GEJsfk#SV>DZoiZ7vMTR2H2TR12JKC~}oH<)%UHo4Id#dj}!4 ztg&0u2Q5YmI$RUliP}U-$*o7*u7{d0PH!$40F7ZJ--Dg0C_=ofWJe&#Cq8upfPZ#qPBkUE3bMyE)LN=C&b8>CYvO{!wC%1=%5o=$q zR-I@xiZe8C!7Q4TPAW^;y}_6F_A!_Re&;OP?H88z)O0(B-^SAk#%e9!+wv$Es=&;?8=$K6{jk0`DjH4_^W3gIF0Di`fav0T;mMNpTRAwIx zfu7o+1+OJzPFt4Lw`J&w=DwGTiE7^Gk23}ATGvB|ArhS4dfmi&*7)KGX-r0e(p;@> z`#l$8UC%vYHRJ|N7Bx}gZ?C@M{*|rd%Wl5M!S&#C7CHsav!;9(9GzY(t6}dp=*7){ zp*f4oTkw>>W}(FSus=V4uxtOUWyYJ24vUN_RMYO-IBG&3;-;8?kKAiYgzL8dtbotf ztVsN^6G)IiI-}Ub!J29B@8U^*tuZ$KBwX**_`3g%92;Jm9lB4&8j^#Mut1o#NBs}rh-~oz| zl_VPE=55&W1@i(j7r@0WIpLBbN~7odlNDG)bMBrJmMHm>4B>ET6N|Fsur_JaegozE zwh|P}FP}tT+`VP@-=8x4Tdx6cL-Z19kC$&t(Pp(k8XTH{gpnQKXAB>-AOm4nhP=`F z<_(gC+;>Gk#Xn;hGYeDglk_ObR#PVV9V|v-DX~IW^KNYl`?((t`&e^fC1WRVc``#} z6Op~d5HIoGDE*CK9%e|Tt5tC=*>Ok*!04&3YW=iocu;y-nq1jD%y5^}INb<1$agV^ z2U3>qwR-aQL+TwuEn3yG0KEKZhV*J<=Z<$Oe!6{xR3@GNfhuu(m0y#b+p@dhrX*Y) z?UpA}Qc-BqBUoh?Z9=k-3II0<+VCdw5b1E}o#XtBYP0SoGA*#d{rXY2_3AM%$gL)W z{9?L5M;l1Z${=>lasfd>xlf~2F=?fa6)i`D5d3PQtMe<%8&Z`#3iF*U3uRA2%3>tG zOjQQz73&oF!q`H^z?X^P#W!WGn-qL2C`^#LTGzrId%&vxe{Wqy-+dp|shuzOAD#_26<(%yGL zQoZedCS;3sZ-U4$vvgP$V`!!axWl%5ysZ8a)^PgTUJ$@WvAhL)dVJ`|oj19cV6SWz zAN(Tv?%VbMc}vXw4Ih&J{Ooh_!M5xd%_9!KeEY)xO!Wk1 zpHCsJEh#G*_A8={M5fMHfJlg6SRTI?xi+>P&1h>=y@RSQY*Ub{srCa(??2?JAo$W& zy0sT>8eG`j3O*%o>RnWhFzV98c6{ShIFFU)s^kP@JY7`JFyDmfuXK+rCAS43e1`^x z$U3$G0yq+ay~9R^Y6v1?FkyJSz2yqy%Q3E(RuBB4bQqK0v?l&opKFpBMFvMAthTjx zxO(amYFFTNufo_$`$4KPq^-6_$lFPA%9X4m=sQQCiBF4Hh~&`5*4Kh>$h838O=2C0 zEVB3_S8ck@E^Z@0a&Gl`%p9BWzeR1isE&MY8}KBWet)-L;iezeq>$U(y`o3PUsMC` zC72Zpq6``WOdp*1jB`z-v%$-oh#y`#)3F~CS$2y|R9O?pf>qxj3GgYbwMS^oAO@AM zBzhG*#=H2cAQl_bva|cF7nK#p_&cra(mzeHJ@i4tk=wA&5Q*iP!DtIqL2^LzJV9)J z45F_=87$Q7Gga!ekr5C8Hl`l$;bV1^0?WZcDa^I^uQ@%mps}3``LP@YQn@J|KJ8xq zZmQAGGYo^w<%pR9c^pB7y&+hKH06^s3G`?kzfBp{mlk8XB4NVGyM7`SMj2L2V{3R=_p9z<(`t z10r;g8Q86SXg8phBpy=Ld6iU23P%h}L%W4>dhaC#i$q%90#ptDv%j)^|6j?G`!>pt zG&WDo81vB6&u1FT4ekC)N2ve6B**v49$D3Nicai` zT+I>cUGUS*pQA@x|6zXY@wM6h6tf|}hO47+XzUIO>PyYlG>Bhk?BmUv&M+x@;h z{-K$gDE%u}3JpD`i z>6th`R#g_$nU)i2!NtD%mJak0?;WkYDoTqH=^?cjwgl-PImp?{+ zV?1aG9I={S}J587D{TthL0(!F2ZDrkc<^Oi>I(!VG*Thl!`kh zgY&>|QMf>`7-1$2k0fM&lXkhLn^vklLI=zVWpKm`(q~KqbJVY!<_rqMtt z))jpZk>vLGJBr;M*Bi@S%aE(5)u`rq?EnqL$Gzv{M;URaZHC+&qk2!hDo}Q`-{z_Id&AJzRiiz-LCV5VytL(|W|hiqdk@ zDA8p!cdYxIE?|d!=k8xj*E6;MESmKz?DZe*_IJ5X+f20ZQ1*jhsEX)Sm-LJ~#pvNLC+`JRzVALVbd#lxV=qZl|pQPzeZ3(JTZ{FikKB!~&`6RGAJ> zfp(nfa~zf^(r2v8pmsp*UM+VU2F>YkH(CNLD5wfaxs2@@e^<(nQrpkN?YX= z^AD8V7E7s#K^M2C^UW?6=_#OsDl@vp@*xNzTZv!bus={ex1qCZd5x&B5&Am1JgU1g znmn!_!X78}M7pT2sFtI-=PDXUifW#+4@;AnpVrKm)uMUV2@cbwCE|F9dW`3bdFbJ_ zRk`wDl&nGj_yot`;(}gw$$XC)?E2i0MnqZKJxr9w`YY?Gh3Nu>E8Vl@=c<)bFuiPQ z%lu-56s<7drC-5qf^mJdxyfH$>B7d`q?|!`TU%K}Uz|+jM5+UL13ZlIAxfFff7^Qn z8@xM;yZn1&obH|cmqz)^iF@V+rm6zlAq2s0)LVn|qvqQotY#_AVOX@0+&GK77!}cU z7O`Xi6P*F#@}&_duxcY+Ty|brPlJ{ohdJjR7s05gL7u*Eek#pjx0m5-d$o-A zp08}D>b|mdm`)!9uuz@Qt(}*!KeH?TR_uB`_1nGtmp{pY?}QHZM?70N56YL)C(OGW z6pq?M_lGQ>r10qy4jgow=XyhBtv7eJ;|DeZ1Y?5?Ih&}kAKvtJs8xOPs8vPLG%|!DT+VRZM!0a}F*Ls;=WRHPGrAC1mXnNDxNnz;>{dVl6>n zqJ`CX3FjDC?;VEzmSwsh!hbU3-mXpjX4Y(hLYxlwOSXhgHnubP6`3ndyDEH?7Fu4T z-Ci1YxTNb?h2yq%PLlEorL4SX3UN3D-1T9h>Y5tMjtA?fbauK0>aY||FwQ_>($8Bu z3p1-D6~G93F#64h3!{NoISY}}fzt1=pEhhBy{otuiFuKODy6>a%>yNsZ*^YE0IEW&{>>(&}Z_VYxg9(t2?*T0X z;AS35pzO4|Zc9{k!1lrX2UZJV#_dnD7$L;!J9?I%mC4#Yi=|SoczdqnA6g^yEr)5w z{qMFq^ku%XrO0{K9{vc@7?ES5BC6E$ok#F}A=$|iYr#Q}tc8+&B8!9f3euOBOBd_{ z^fP)F+|$jAi6~R!FFmiLot=ejUcdzM>cYpSug}d$chY6#3v8avs2CaPP;x9v@^0l5 zI_@`=FdWOY?j7lV_iga~`Mwqa%jtn-Nrd_JZnmGC|}tQUe;%3+>I_R8CuC} zy7iUqq`Sgrd|8ASKssIwIrcKjCLk+xHFTYwajJPpRej%1V-cD$RtDQ%OxV2i#VoGE zkew&^18Vn^$G^OC+sbo32aYB0yKL z{lC*7|7QdJ8?VPr!LFnk4ME5%I-`nE)!N9TE(daK{orgaq4NwsOV z67`V9$3ZU7!>-{MuJ4;DxEAJM^7M1FZ2OI}Y+3wH=t7PvpGps|>K=&cN;h9L6e+>0 zjF?x_J(o74$KIH-u!j9|{`|wuE9pc2`ckq5`?yejhJ(gIlhmLe^o!WNplg%nA^deL z?uc2R_1nI$o5U}ZbMYA>aTy&^>{o)qh;d5c#h_uz0v*W+Zr|i6ka=`)5;Wf!^~gBF zNQatOT*vg6(QZo>r#^XkoApLZZ^2=o$u8IHtynm9jDNkuj>;Uu#~im=LxLa1`Uc>lH;NFS?#O)LB2l?&2ss9 zL@PsLg-Sb2rdactqj1UYA}xiQl_}P4l4w?_Nt{DJ^1;OOP2!%Z=3ctd*o!(RQk!!( z0s7KJO1Fzw+#WiblTetS*4}4UK}w7aOm9i;z#M>?L*6;UVVb(RMiCy|nBJ^*&*Y>u z7asBa@|=eB5feV%x+mtahWxqJk|dtaDDJISi%G|ciI9E?sg}O7#oKoKl~Gnav8Ka_ zgXYdX5VD(MawAS-REeE9qcq>wPB#sK!)~O%N5g*k>~^=@Xu9~eRDoDYosjRH(!PEz z8xO7J&VeZtqOyYP=mTtY)B&NLJ}CbgzZrV1dw0ChlS`lDf%PFPO||R;xvb?=)b=n4 z@xb0|m*J1_)rjSrihOUJAV>I}p?Pa#S!#t#E$z|b@tT0O+EHsB9baerr1(1gjda=f z#yon*$bo#!Zj0sayN6F3E%jBe{bdR$At*7y2VTTL^c7vWZ(C!Y z?FGq4i7XIF-RvBcDddAm%NM+Kx1tNhs3DZfw5wbx?`9icK~~AgY)W&pKyEqgDBzJs zF)0|j-=EAj8|FJsQKi&1Xya{Xa1=yYN<-RWh zK34ysJf_g`k;!i}1C8l-wrp4z$iZqU-EcqHcH8{uKzG5R04b53f5y7TjwVO9D173t zpM!0Z8n<7SP;4BpVfyXIJnY-^=iSy%8lx2(_Q?;gG~IbApElNZsXCCJVk8t(HDeCq zE>pM#8w9cYLYXJ`rP-~{4k+FWQ93Hw67g|z(ZN00a42>Ei8-HI*NCPC&*-j`hQYY_ zId!+gGs9@1PQJne2K&dKL_vM#7t0oXrEbFfR=_HZ!1077*Rc5;gCIT(W@QrWF)Qbh zKW~^dFZg5Kxkk|_Px^gHyE|mhL;|14NMXW8XU2*3Fg4{Cxnx7$Ms>_2m2oNuR6Ck- zDDE6}-ik=)QR>cjMaFKH5NB(?XM&dF9w>a-jJEF%cQD~&T+C|qjL1eLfHpc(O+mfYY2Z$&sKyMd5_yBa}=OaPNzxp7M$@cSwPZvU}=P3!ux$8lx<4EHG+HIkY z^SmHz?xcy7{K+W0$_L8j?c3 z&~hG2Om!?pIR{n-j3 zBe%9+OLfiLxbkoy`oxsx_I#DQ#R~|<&u7Y&Q94ZA6s#?KRvn@(lEhKRl#h3wqgv~1 z>tK816M!f7$Pyd)+@B@@aC+*~&m9j7vP-%}(@Tf!} zZs}KD4z;dga@pTVbZ~%tFPWGaUnKU%E>kE@iKid0 zoEankeAr011SqIYh5k~&pTsX4pYP-czbbWZ{fhrW}Q?@HcpYR@h(8HO_-m^Ce^ zv5ke!z0*2|Y0Rq!H<_xTtA>wzFXBCY7ct#XsQg=-{uh(1fp0wW=?MKsTsAVYU`KZ1yA_Ncmv9**cfZhi z&@?gequ`bNDAkS`r|M~q`S$Ad(z$72{w*ZkZ{Qsu{dcz7rclf)T{+63*%LK`%=awD zbqGC}O3DmX2tGCa;wxM0%8UR$Q(A`UvYWi)^J#&`;U5KU9UfGhSnoa8XyZ!B4gM_8 zOBt5N5GL>KCMMsgCl4km7?0f@nddgt7szeR_Y%N?A0;Xb8n@%|ftIW^aEO;iuQ`J$j&$}82maTW5x9R(}9yL|Y^|$FSq&}WGyK2GLIVfddtRM4n_`y;!eLJq} zVIVJ`Ty!F61dte{uCef8-z1GecV;z9)(?2^b8hKYzNmFa%cxVfy}f}-o2)@|ns6Y#1%Y`XG-^yZ{q7cS+y%w&yMrapP~M`cPz zz2{;+Cx1%gw09}lJljpHn zO0-!px-;hIs%bJCJUUUcRABIGi(MmDx}Hi!gQpIO=R@yyBL~&7_)U zS@Iexn1Ty5G&IK061fShfpyacwGOHk?S1_Rl-%}qug!-=CPu^V-W?pDp1m~D<8Yof zPm(X?&)nbJh{&`>yZG6h%Q-HDE!Usas#s2zW>PHu>$$$N#eJV}1O!rm9vAVyeD$Mr zLx$vDP+h2bBP{#-q3?H!b24GCJQfw-iT)$5H^E-3l^SI~jFSl+SZr~?^fvxk8u;zE zW$iz8SQ83oZ-5%JtI7nEFX4h4V%OxW`y$O#yQZ?XW`<`*HVhQ}WN;$mx`v$>k97Td z0$+3T*MIp(N3&y_WFHAfQJ{198P*F&Dp@}@4RERB-Ol?=d6Qdi+@fV^&|;g2X%URY zlf4o0aJY@kf!3VjtViQ_UXev%n!~S^{LY|@kvooLpYp}gCRncN$!H56Uz~uFTO8Qq z77Kpx!{Qxc2Jd$@I;QHqQnvM*%Hjk!7WVOqMp&{{$UK*)D_Alyt~F3 z(Ha9!x@j(b!(}i(kGxp&_K?B~7nZS_Q*fxaog71DNZTomp%;_|1M*_(Z_zFG<3I21 zxoC09E$P8GW4ni`Cwp%TeAM0LN(@JGJW3kf^jh1FM&u!ex0^?{>hJhaedq~G_?*O| z>m6EFTuQW`4Ayg%{cIoWM| zX7S1V%*~rgqh5=g3G#gBQXvjQx&+&4jQHHNX4kF4>UMK}6~XN?Fbx_LpA!Suu(_m= ze#qY4-C(qbCuF%6XlOO}5ng+-aBPv={kJTqk+w){gmMV9H?@ThZ%ppZHH5 zM?1f?O-A^A>CU|YT{$#>g$8zKY)dzEmC29E&t{F!C_)j3Voa|0cNN6#q!oGiRI>cW z9M-WW=9tOBMkSjU)1|sDQAM*l!jKP-OMhrPt#J-wu`>nu@-2HK3@r#nIO0W8Dv{Ld zqco-Q8Fu7Z&Ttj*TnYC)l7|R*lwA5CPOAvV^m*eYQ^YXm zS$}V-CxF{Ft`mSPg|ro?(SaO<=T#oGv9dj#Pj&UES2Xfwqxgk+R^hvWD=m11sp!R{ zyr0cG@lmOq2ggP_7J1*qS-f?RtPn09JpB1{a7|#DXI_I8b6OP~d$=Y6XaVD^c()ij zs^p7;GNQl!_(=g4S#lo``?TMQj)U@bm}u7n8l74SKE~y20s=l71OHpM97mQSYe_Q# zoicA14z^#Ub*kxLbYA|Fm^4JHQQR`M@y5473X?K z2#|ifKd79A4VNsuFdC&Ft1MEV$ikcE5_%#GBRov7mO4Hcu(r#i3~$jF#kZ%jQVSTy*Qpr*aKNawZb7fp>ejHUzCGNGS<&D?Lr%0Gt> z?*&-UF`JY0oc(!p?~vu;R>y?vsx=9S39ru}23BFrB1orduHfv)O%gnj$Jv= zpFk5CQ*Tl_ZyGsqUO7ERytaFoyx}RCh^A7dFk)udtKRAOC|CyksqC<$cVl8_=1;G4 z_7k&YiZcbu4dS54B(E0U6s=>ZaHi#yMxbLNfV28a`|%paNwx`*l+CA@^UoMvMPE>e zqVcb60m<3KU2(0UcuRlbei&|NT%=zo2XuY)c-rmyQ&T#g0Vl@JW2s!J%B5;mMNH#K z9Sahl#9?gt5@Aq2*21GSWQEj z3x^M@tNW4+J8WcQ0aucC{EM{LDb%*Ra>VXfo2>9;`|!T9a-4n|2(23ZI468v{=t;S zZtPDD2);_`$Fa{di1$+0lbsI;%pRMRGf+nt8pLYKP0ijFwq_sAZB^S!7EH2}+n?Y2 zf|ir|%2rlL&{^Tr4;D(s8n1{qrQ3=UJ`Z#SBcpS#JJ=r`rd2y>pFZq4lgoP^8@UXOx7tl3_V=Jmx8`<>>jW3V^B_T(gc`Ni7${ zMH6#E2Xiz9l)kd%7@BTmRvY?3m6)pUvP7mu#*AM755|v28t2l=BmC1_Wrx6bv<&2C z!48inGaR}Hvzw8c@ik1{R$byy@&|^rbj_vj`CfjQ6-?tRmeG=d+cwVYC?FPR*Dqk- zI-e0Fm#b<1n5s?_vrh$MRGtxQER=^%z8Z?k$D+S%QR0<5BTN(!Ffc zMyf~b2KBnKW6LG48O<+%BfYgRO=&g88c9EaeexWfmV5tx+h&A?jO*~W1af65V9+Z% zE-sFzb9q&s_yGU<892wq-VdzT!NErmv~!KL8gn8;`nWbgPRJm!S2vqM7S zQD-oHl>*~6IAzie|9J_Ytyv>-ZpdO~(qr`4sK){^7OZ^SH7xuL>*Xu1G#oLn)3da> z(r2f6_C%K{ZIImU-oHi7BNmEPPi(?E{8r6evNQs-RCVXEr6ca;r8mqCZ^llpm8wR7 zs(O`^Cfx$7&TAv--IWegSV)k}5{Y*-yy6O4W6;#++8534AQi*eyefozAYgwTu`MA$ zZH_hRChlYj4f+96I6MkjS$?ajxj*YrES|ifBIL0WV&uMoWeLlb(+00o%x}vE0UVMm zUZH)Am4gt!cPrD46j!Z_aX$TEH>TS+24rjJ=)P=WYk=eFJju=J0B`A^ov+56jyJ+7 zo$&+czG@&hNU#bRpJ!jFTOTL{NFi4M`zFAX!zS`@A#CNGw|GO|b1ycg`Za%$uOie& z`FjI=-gvWgf22u+WrDrJ34)l^MjX5!VX&NXOcGVG;EO&nFYRjXuD?1r-Lx4q=Mbw z#@(x5BmLkJIlL}uF$;1lT84rgXhp}}TRz3&x72E7sLi$6#n!FWMF!3uQ9S;^Sl+tN z{)&;43Qq&<052X1pdg9uf1sA|_rdrr?Z}2HPi#gX>A6osF)1G#w*}*bV;xO&n11dJ#Y;bI*Fk#u=u&F*pi;{4RUNk?`*Mo@ z%Rc1miY8A=9?n4nM)HX_hTjxwk5$Pl71bK0b}N~PLPcFfqHUEYpC3-HwNT_*PP;-% zhcmE~Qo?REMO@wuhR3>zN-?NBIC5Z%loe>hJKAJ-K7YFnZPciM!3EOEHs*>4HY8MGG)z zv~}wQ1Yf1|2r`knklLM>We&R~Ki+Fe3CO!gYNDRvwF*^i64jL~eK+k@B)-L@a&~!% zhU&?N24UcrAFi(5>K7aAUv*m|_^AjW=7a#34MKNnU$yh2^+k$MO!P@L& zuF(Y`-Pxz)KawK?B_eWCoqg#!$%790wZ}Zg@l`UO8gOK9X#0JOK?1@eGztohGL)$l zs)6VH0CDjm3T+xdt(}(X0#W#Rd%u*}%1(R)OT;fcWWw06_e%Eu(?ygOH`=`WvIQch zYNdjaCo1}3Y(lX52-Pt)CT_$(jIMIda;Cti#2<<^K*tR`%tGzs1iL|r5Z%TuL0_m{ zV3?`jty$#^>j!P!WZqr7&`=HM0mIxZ2_ix9c5ZO)7G^QJX!u8uq~bJZ^>jmLUk+G= zQC|)5O^7j)7>M4x*oPJ8-J*^c_77z$O9$B8H`Hl~r}`K_COm(qVTW94-!d z676D8ZEEBpRaN}*NH_Np&)FR}&|Xl}SGGzc04Zw994|4QU%zy?tfLMrCjW03Eo^N3 z$eF>={B^H8HvH|9>yv}}&yyx^8v)uw%0s?woaA+CJCNy7ceveSO&b3wE#2_xx14W# zU74API;0{0prX-u)1^uy8#kWoF}ID~y_A^(7L!A<#=%KK@F8J+1_@vvX9AqSVMUawXc4rZmIyF`8|am(1+Gn)sKh{#iX_^}}MlS)^@JGJDML|ln2Mv$nUxJ~Qu zy`N0Y8q}S)x|GNeN*)|_O0M!D3R16 z@s=ZvM%KiDIc)Xk4gay9wF-slbmmZpc?G1@GQgLiD8PiileUsmZXsEqiMtL6A#)II zINr`&6Kd$2TlwC`5~ek(N%aUypt9FEYIja|MD439XjU!zcu!tTPg{b@A990PDNzyE z`qi9TWE~nv)%!7)?w*D{MmNow>LT6J%Wc8M1oA7X;cQUkV$Upqd{L4wv)$Rf9q?YUrZfrHezGW^3RC+)o&6x z4Xk|EhE#|+G@4dn3A?&D<05QfK2qb@D=tz&h7Nl-b$;I03=U&HjC_1??eU^VY8>T; za)Tf!`mn)BId#Z_jPDalCfQ9>$M{>xrY1(sbHX8Qbas}L|JbF+Ta*P1reesw_V~oAF}}q>d|RO6 zjS6ZlN2=GQF60HkfjRrfEdW0e1C!{T+7d7tdgBLZXz_$E&j?AVyg|#O%t+7J(p06? z{%j-NdvtnT00J^yzbG`UBROUN#p^&UJuMUzz|u+=&GvqvmbA>1%PFV-ATWMIxy~RDCC~|9TNC%T98dI-nF0elq zA&KNT9C*KSawRjaXn2{EWSq6CRdvH09^OBBoN0-WkGjKbYse|J#k=Uc$&rLr5jDpz2~cm6whP4II4hwVP$Cd|RT2=~_pH zQsoyw_|nnk4ku0CxVM4q^;lMH)Zm z0fbPOO^G5mSn4_tk}D`>6$lWZiVF8eSkQf7T2R2?b6{icmvL|?b9p$gvg~7@sgH+^ z)GYPDCG;S9Mf#FU!;&MaaufPlnHApaUdw*OZfG$-U3Fyst@Ty6wr*Ce94!{ z)HVdiql{Ci%R#yuFy%b;{YP6eNt9ucI^2Qu;w_Z7&rBYFf6j5@`{N838_tA*I|Ed% zlbckF-}nXR=ZW@J##&J@qwvg`Iy-oF0>s5Hp-1zsLqt>#d z`N{yvsz+62xr$GftgZ7dfA{9{|0GNIALF`)&7aK&xxG-WooBt_0;w1k+a%qRK5HpU z5?0BIKFO#kQCQHYw|V4iZfZ&-B01+GgjF#Vlv+$GcaA;W2DHAZ1Yh?kn^R2Z?7y^s zUXryiXo_&2EQY~*yK`x|WrAP6V;neHdlE5i!QUftx19*vNrn;33z3v!lPtr|$BsDS zRUiYRO*fmeOB3V+gr5MJ%VZ~y)ty-1f;k9!MLeh9jh|+0CY$Ch_-u1gw+R~X#wC5a z%*37U{Tkt&-c;uFVROcIY2GfL*^}YiNL8Yj186~CJGMRYP6SszKFY<7xEW{%$ml2g zXR}5NTQh&qq#{V&hJsH=Y=nUL4e(%G9Gmu98yYP^(s4nV)%+uuGR?|Ls=JWZ?%$z* zF>v_xAC2|T7hC1AJW2ZU}^|Gkv?T->xC<0J<~H6ypLL8LJBfkitX%s zdne9Pv)?F+XRpO~u5epGvUHr@yHlmiJ}*>hPA17r>o^((YDzr1fwL^_(J77nG#_&2 z%blc#I%KrPpd3Ssu$;7*vy31|T&?J?W99&vyHRYaCRC`EKJBxt8$vjJ`+Pe!-@V=A zv8Vpil-{bNVDM)AW=d+Lz zIeQDI&~eJ_MN6MD;Uv8TQ?Py0RBFz0j_&im?3x{2KV=O#s%|V#Mxd$p71rmr!Tlco zD~%fynZN@v28Mjxu1s1nN*_s9J<`7 zt^LaOGR~~t&Z2)e-YuMj+%p+JA=aeX)48|p0nJbyo!*Oxe-11Zt+0_k(@$MqOI2TlJJ}Mw8 zkH^kd!~yyhumqtNF*aSN$A8w^wBP$nNz8Y_e>Ca$e^c80dri#W#>jv6?ZwM%S{8+r zv2xYMjvO<0E}Qsi#)1Wg#tRj!ObrOoMnokMDTEFaW6kI|c?egk4&QQ?-L8;HsFXY- zu<<4yZE=&R>}(otUuYROd6Q!?&HT1sww9o9TpR&Ex@sHvYEUpxFg9b!ecGg%A)QR< zKiJks6Hoipm+V!7ORbjJ&1Ebda?N^Z;V<>&`ZgbGNxT{ytk!5x44VoyOYaK>zd0y$ zbfR^Ux7=Wr&dj>=jfE0Odz12&k;sBd6NI0e_x`I<)&y2@(ko;Kzk3Pr6y!Z8nRfS$ zlZ4!eiIS!F%w__$9_}5f@NB8<`Eofqd1iRLVX(a9`;4Q?>_g|0a(o)>`w*x(Uhw~}AO5CmZn$O9^;jvoq zn(G`_qH$%Eby0RbKK<}YfJj>(=3(S2^P3?1XQ`plerl^(g7vD4_OLh(M!ox@ zz_pBrdHLDYVOFWjX3lc-mxw8o*&ZvYBCtsF4ztq1c2l$KRQ6*7Q$H^?cAf7*#Olzu zb(_+f*O+=}sn&7M4K9+O%#aMPRYr%~Ny_k=c32f)vWEztn;UCQU-A-Zlwn%5`#2J$ zRDZe6S&H_`x%$XG&s*G(qr>w2;)+7(q@NjoE0J_&IdaLWWgBGfteTJ@#(r#YEth!o^ebYrG=Y zqlO(D-wwwJ^$(_)6f0Y%zXVI5vQ0m{EbQ@?=X`b$Mo(N=>CQH56wI4Fld%pRJc7ZPLq0ZH*wf_yzhmL!C6@y2()Y}`*@v$6e^(E8t3xBREccidF4bO9@JiZCR5J9Wgl zINfA=`}nm|jeM#-d}D4l8&%b&ucBaZn9)Y>Rx&R5fGV70dV!*OI zce$HxA{rjN zuOjS%92Lk0_p2%Gq9w2B<~ZiYe{d7|oHm!%y5pcw^vF@l;6dKr`$gyIDyy~hy;`kJ zX?;?mBrf{dRnCNBgggba2yO3I$3+vu!ogaC!+fzoeK~J>gNc_OXH1-e`$F1T7RL|S z3x_pEs2Qz1h(AR(VscYX@xV0PESZ;#uzyR#IbV*lO8BhVYL;5>z2AbA!^}-;XPJvg zrAE}uR^7?~qj9g}+(ddF>1@HIb9ou!rL>F2GtRRkzW-`i2tn%Ng9xX#HUfthpK% zu38`8l!5aRob}5@dy{IWyGmTP_!%YUSz~g-gqAe5wu3qU4@(9PWD}l=W4hiG@D<5 zoei%Z6GrCAa9>E|*MvWK711Rz7D2%YSq_k+kk=b!YcoMU##eigns8CIVT3z(@Uzt$ zXIHCRL~I7gN8bGpw(kRN;tG(K(T=VTLecrr(e@yDmmKbfa~uZ+dDe^e%~BPKXNxZ* zFIF`%8JJVK&z;Z<3}AjC}18GkZ|Nsr-jfD`hG-ll4g53(J2B0Gdh zURj>iLWvg7o`mNs?xu9q|IYv5lUUPcm0C(Q8A2%l5Ztf%hVN4siEO+Rl591%9YKnP zbe>t`mwm$hl*>mCd?}hf4NopElZO4?-*Ie_8c4R^+c_gXmyQUka7b)-Z6D8Z(r>I3 zUgE_LZdRV(6RLpw8;N>q-6mlTy*?EoHLf--G1ky>YK%QoDu(Cf9o~#FNS$=g>Hb{h zl9fk-fg{qD!6JWmymJw8(&yjF?;(HB(x&N2W7yFE#CgvfX`xLR+U=niCN zCEEC1<2>OTNtv59X;f&$dOPDWhk^7dxow}7#p%aPR`;y9UITWR68?ROLtX%SdhPro`_j$&yosdo=9L4}&_jRSs-x{8baZv_?OuPrOMeBu_L259h@AdeiO_^VGzDTB4ZwT19r`V&i z-a6(Sp>z|KSvYoKd^r%PRr-W}kp>;kWe8<`5UDjr*k^S{IJuS08=lG{*4RZQ7Du~) z^0;WbGXiNxaDnR+I3+c!GSy#)7|Vf@JCgZrD;E5YCF3?G`L23W)_pC)iQ;X%4vx(S zf~JiTyiD9l&&|&$qHOM50rs00$WYSlRkHFW&ADijl{DlR;$A`Ppde93L0(V>Xj+a{ z&YX(laJjy_+Ba-g9eopYq5SHkhv61}wk+5k8G1PJYV+fPG#sC0Ah#IfR*7C)2`EL& z(@(>d8=lY)b4I_gJUZ_{smrI_3dnD)z?GT6926G1Dh@Ld^w$q)Fr(F3gYx~T==+BA z2ukuPpp;SY3j26T+?}&%z>0B0!KCOWbBp8~6l6+c5~dapUoA@iALrJepZ@?ukzz6x{XiFAt5M8_2MbdTRcg2Q%g6LySj;*^3QJB(s+#&oLwB7Ee)@a2rM zMN!)h6Y%PAzO2-_S~!EY|A8yn|Ff*nLBq-h;h&G!Ey$n6}#F^M|9Ku3qJiYSs95INyAG zFA!-1Vioq+9jqZ59uS6B4(tG~)J7D^FbRK88#ZTHBd1@svoZqvWoo3g6)8bkS2c+$ z3si;aysL*X-nFck+nre-XC6Y-Jun-gRS*-C51lSV0Fjqh$fI#y70jls$`JqpM`iV* zI*rFrgtBq(w$|cf=QB-tUdv3CH4uVqMaTd@sk8>9T;}X9Quc`rrtvi51ey4eAY0#l zLVo`_Defyl;Wikd5vrpipj7Gc9&pwRraO+n09Mus$#QP<_o6^AC02H)jgvfO(wb7} ziwI26rBKbv$N9UnpsgbNObg*PVW*A}mkEiU4w$n~Wb11R$r56*vADrRrA;-It}UhS zTE97=&z($A=S8VmyBgTzQA?F5ib>DHps38R)tv?yxF2XD{&fxJ`AGGEw%qP}6(R#j;DYKUdgF$z( zjpSER_JU$hZ?y`pP>84AxsX|R6Ix9zdf|?D=puorfO}`?V_A08a=LXO6=-t4AG&mc z`sFaAel7{oaY}y!S3*&OcW_vQl`YVL(r-oL?B7yTHavrH$>58;MCUZ}(a+<>hyuv4 zTte!W=;-Q`S1H?e-Nrg(tDw~F^qao;CCvv1A|fw}?I~87Sl>)j#%NfEdB%gKw4ed{ z5`#EP%&UY+y2jQL2x(myoYAVvaQhz9uDOU%tjH#p1-%cOXqr+5BE(>)btNzj4PyW- z&oVO&gxT{jJ((v6zmNI(+{?F2P!$lt_qJ0)(yho=#3A2uN^rLo&>4gSfL@goL z?%MHwg+*XW-(4DvQ06U>3~5c5$qr5vYohBte1)2I5gA1;NGE`;rFJ|!zT3#0#ELUb zX^Bi21cGC}R)2?%4#?3%2EzwUPEJ(1xS<0=8jC%8!3On|FDw$4^I{A-m)|H;NfYX6qismUe)J-K$C!0Q`3Nn2}MbE1a9Qo_=DWwcI|BzwvWZIq2z zC*hOI&*{^SPL(?9RqQ{Ur|$f$#@K1||a<%F2)VxGrM{*WCRPxI+l`cg>F zw_jM+^|gOJl{>YU9oR8l`u=rmWZ#~rX;T>dJ-v4RzVQ6EP2ZG|roV?Y&c)5{$dsu& zeTwSybUuxNVNe8FM#&I;@bj&uQqF@zT#>O{dk$ z?eaxpoKC|cHI+E88UpKtF<0C_G7({ZkH_Om6m9gJlBPSFQ>m0=jJf81UfINp+4<96 z|8N9D&t4x8vXsQOpPf)8yF8nfZWPM5UKaFd-fl2re?K^@OKODec@H9CvsUCKS9#NG zJ@tchMt_dI5y?)S+UYjfne*7!SXpLK)$d4p!I74d2kUaJI@Uvf)SY4R`rEVQn*Jk8 z_>H$Oa3W71$F&E!GBu}AzpH!oubaC{ow?^r-@kQ^8N<<>UN*-G=T&qOWo<_sG-QP0c*U6gc+;IkW8=Q7_;#6{QsFrR6O($e4}Yvz|5v0D|6B;a`u2Ux+|Mj( zYZSM^Ey9$uIf+T)R4mgN&p#uxKW18zWkNZQ8fywU1111>_(IDNP!Vylpd$BtM` zkp7z#&JwwES_+O<=dt;#Xa~#m z^RF`Sp9~Ru*E}<_b2bn9aYetQJ0VuSmXZa^(oK<`H}Xvpp=13_vGzU1j@TeTr%T?h z-o7fP7}b$oPFEu|jT$(YO((*l(P5^Uzhq^;Lt*qV1tL0fY5_f>uI&gxp+2Y9LpQ@l z;^MgG9gN`%6B}G{Z`>GptFyY50-(0*X2)jDL&%t5`o&)D^#>=bV@ zRo8vvb-4klP|My_!W!093}992H*n;txCTVcDyv)bxM zstudNC$oXsO71tz8n0c;S?`INckd*N-9Z%bRdQg1X@e|g%^iK82Gz`G@wSnt69+As zpWFhoh&m7T-3^j1g#J{vW4Y_K-M?FYwm>aoT@HrZ?g<*&h$%L7w&@GjTh-$^Ymm{i z5XNsnL~A`rm$V&kf4*7CH*Y4Q&h85{LRHUeF`U#%^as5BQ+7YgjdWF3tQJqhd;zO= zLG?ku!GZgUsbkHxa__J}h_O0&11j4*LnjUjuD)>7CzACHeFu$_0Z?*9*$(1Pp~BXd zcEyFy-~4cCvY+J&DwohUCwpSvAzr%nVC{frj{`m~=^xO~JAO0e{e@*tj%zrthiL^O z&a^tiLx&XjNJ*m2QUf)>Qw?^Q4kO{<3(KcuwbN&)Waua`@8ZM4P$TwXa)u=1qzyvv zu2Kut>=|=7S1?ga9wNBl&D4E;q9O`{hzB%l6tR{kImpMj+b04nXb%WbSgUC&(wEiq zxm9QiThh-ecdLz56*9UN9$ftkm)(j*hw>K|pz*`56FGzZJs~aOL2CJwZ&-kLo|)Yi zUiS;jb|>KI>P~-oy>=5Y@Z^R_$r{HNUn*!{=?e??rEvDSihn3A`!A*+f3+k1{jD#( zinvgPj)Y^94>>gcwXF+67j-^LJ#MV5ExY*$%wgDcSF72R$y2;M%H1YOX?kr}6!~d2 zz3KI|D)1gspaj-BL|Ae`aIu?b@DX3_C)#k};##8}GJzI-DL%jndqByPwb%5mBT*dE zw7_(he7&l-BgX31TX@Y=Opfk=2oZgLtY$w~cYK%Jt7>sGVAg?Wc1{lx8vnU)QDlls z+^|kZ-^9Q|tk93~`M41CS?t%_?5O~v`rO4CI>+=CoA?i#o5#eu zXH$EUUAHUc(4#JIvBlFCqQ~#+IJh=7{g#RqiPc&{4cX#e1>WT$FM2_lU6f5+T4ieg z@WW>i+ko7ZbB2$yCQZciV{-JHi?rzgWwB7f9lChhMU!kZv5$Mie*C5>)W1$-SwgmH z=iF8Dyh>UfU?nLfM6ry4Q3Q)VH6Pj4hBH#g%~Tl^S}-&89!}bnYJ}tbS$o&0*9QzS}2R9KnW{IBL zVAQQaSFg2;KnqayI44K~3@g^jqX-vOZm7d&y_PNMsnxKHvm;zl=Ez)y4AK13I+2er zZGYMY4@l~b-))iZ78;4!&|!+?1psg|DA8`BJA3<0DxSLYOy8_@by0;5lGB?)j&vD$ zOxbGncCH9V3b2UE|IEVjwce3jYvR|u( zIaY$6G;JDiuE1e6@2a^SgRNT};!q1&D4oh!hcQ&jGGTK1SaXJJ7QJ>Sy){ZTWU}I0- zbpIq9UJ#Ohd1QB3l&=+Xpd(dW1&{=Vl5FPaZ^OriE* z$Br3vcxd2axm?-u%x9|-rf(=Z$9`{mA2xU}8yi0Bwxz(68Un4t8 zK4MGdFbk490=CMsaFPkEm{-2s^h5RdFYjlrlU$og2II8qBFI2*mr!u?SPK`gus$hb zLw8oEs2%9%CUag*-aTnGCS`Q>x{U*0;foNhMXB!$gTAovZxYiemu|-pz)dSeQ8aFz6XWL zgsYSdSle@>GKI#tl;we*B;fD3Z9}QCV-#U4HM89K3O*%rX5ez;CxiHDWpm_XiMOu( zWay^QG)7r;VU8&tpV1}Tx@;~j<<;Sp7x{PvgSwFCu878M)_wQDta)dY)I31k-jDpr zD6_%0b7(2;y?v(~UhIaXVvSFuatlK>DBEWsy z%#!|i8tK&CI3q`a9z2C}Wuvqie2f<^(n^!yjgU5INstoUnHcYUE{@KNpA4oUAP1Uj z+I5;SH;UDD3T?c?1dB#;Xcn76Z^UIO{SGM;qb}DAkbTV9l^-nP5RZTM8nfD3eZDD$ z)%hx`h9XJe=60z33){&)Fy3@}-@dmssPeF4t3KZLJ|&%>Tqa^I<^k z$W~RT_7O4FrMiz-l>yn;o2efHs#>Ps?59*qph`{ zdK~2XsnzXY3&&R4a#eWoiDY6Xscw8O;I@E1p`YRTSVE(7i z^#A5Bl#E~f@s|l`!(LgdCRA>mb~%n4 zeqWW&MkVGHSbP)?rT&Ck7-*@b)eHN^<8^pN;jtsL{}YQ zYtL$8sEH7aGdRl%NBo$0@l||&a^{G)LFS=V>|*HIM$6{>Ye5Lk{N!jPC?DM-)< z=!L5UtBIamweLeu4-SjrizjlIgmc10AmWG=!G^VnW|}SRAmQX_g{E|hqj&TZK|KJ( zg{sn$yvCIBGF#c`;g6_J@A&dpEIGP=_RhbGhxwll&2>_VOSM+vqV1g=E;H5JR-vU` zI*IR@0g$sMYM?dRHpa9P%(N&Ng$wCN-Vfnu zY&Z-qJ!;b#EnsG7Bt8q*5Zy?_PFzy$Y>s(27ift892jJX$5adVE_)le#Z3dBo_yc6R!$QNho(+dGy$e<=oppZv4LyAn^Bb zm|R8<RbSaxG7aZuF zeuy;{Q%K405o{X=fdw5)-<;zdIqO&Kpz5pXr=8;9%UL>@_h2PC<|&R_zB;10iZq(y zvsAX&-wBTvj&=z42QJdi*M!|zsi;0I5$Zl3n0#jFO$;@hLiK&e-fd>ICy}AP=;V;h z*Xfm)CTugB<+ZvK^t#vAEf0`T)@i~h8lC7niH^$Fy4UQ&%5G-@2_cs*X8NrL z?*Ym{hFFg5YiXBymYqTQiC1%Tnj{mpFB21A4ff}IX4*)^sR^aem=$);Y8c+`y9^ji z8f0)8z15a&#c;jLs~+euT73L=Zr;*7^S1)H24aR8gR7<&Aga4e6-{(O?$ouhwBj;%9 zVPS#_g<1^ar z#@qZc@58>ym=im^((sAOG`Kl7bCWM8~Vt1cX3aSVg{$3aMRt|U%rX^>NY`NHQ1!_tIE}FkzVb*V7vDMf8EJnWAfMR`nToa zujk~iwd=1{_+Pl6uy1JB>u+zqsH=9%+|2@gD*xeF172||jwe^?I&kg}fRZ5(onWT< zz3DgDC&r-qLpG8onVB&`ZwM~wxdbYJkKXsDljB!`@3=iq97q0K+RtqiE^mJpm}XY~ zIe&-M*>{Sz5aKpmNl_&-rFB_~;I`KW!FiICS}6yGTojemz^NYYB@(>u`@|tv%Lp7# zM9%&$>~V7e6k}$;hvjh|xTEO$1JknNM=$^W&gZ=n*lklFJ!|6ZBT!j@k=VY=Fn8U*x{4w>yL5P3;bXta%FE%0}pN)@>_`myW2V-4i^kBDQO z8F4@|09SZIZ>`%|Jw74Cd>sIMz0J!E&+e4Pj>P`|X@#Zv_}?#_CDgb}d5m#^_a1%E&osXrp%?~zq$T)` zy}$-qXZU_zcMu@fh|dYveibEMrAIumtD8F$4|aMZc3}hwud;GpD;PxTT=2*tWXHpe zHdP&-3pBYBQ*gMQhZj`-I0jtAH^z9paQVU_FeW)6KUOp7i1Tfeiy$Wj{|@bu7-%F$ zfm(A@h>B)zdkfk5vQp6Q6YfDIoGaFj~nNjZ4d{6w)4V41$S;lEM*E>?GT zbv7=w`Bhc1s`79v>fH4IQBP!k)$Mq0FmYL zfAyIDbtiv&8vYuSzaLEgi7Uomv+J+f^?z?a`fGOm_nTdKfj!@!mB0dNww&^Gp^aCb*73?O;^i>ISjdOP+rtJhFsnjw6F^PHIqwBJ-6$6= z2Y(*)0RNJtI{zJyP6g)eLVDIBGxZ9YEsKN~yy@6{nmEWKzGM%FbGAQkj_=DBs}VJ= zNmep17vYU{j%C@iyiq`_Vq4_>oEzbgnDKdPD76DR4DtDO{Ygw~O=rkOVo=-7 z@859UPrMmcp2z9W>D<8s%ObFcv=5Dy)|O^^aH$%q%+t(gG2xN0r~-jlaVgXmUR-Zd zDro0Edi=JE3lwO3Yu)4Ou~g~gh1A$qXp5T(tWrvon;x{=agWq9qgEu5_7+soWF0qA=wm^&&`xE#*YdW1F z+pz8~uVU0JZ=F8j{5JNXm!B48(TZO~3f90hg(!>zGYNfSCQrT!q%z833LqWD-agOvU*yY!zaX{0V9vh) z+kXSK|ALhU(=M%VR-s;_ zO98^Y%JmwEmg^J`*Wo{6xAn7;fc0|9b3Nw^+Y=qmL^@xmMo%60Qu?F1E0|$VrgS#{ z{l2JRK7bd`)rJd@PH5EucR875p7R6f`avEC8Q_ZnYMG}Id!*Z>GfvLqe-#uuqmaUjt3E89pN46tE006+c1_D`8p^ITQ+zmaP`UM^hkvd`^J4%{Bxtq!S2+N zpR7U^VUj5T?=N|d_?VpXD z@!9|IPi*a9btxtzmW9tX;`48<6K7Qq$^~O2_5-^D;_4QkhwmsU_-e+<|*a&4%O~``<)%u@$;J@>FD1!nf!?1ECh9%XKQ6` z#kv2KztHsbe1$Hx4Vdnj;As%&sBo#n4Dr<8>yCjz`Dca`V>W&b7j2%u@1>+WCvZ{y za=_0$(LdoRo>JME0^|O+PjWD)KES#Jj$2x6u2bS+W z?|tWRiCS4fD9hw59#;-3MceFzeP=>Uw7ZY7l{*sY(~>EI`*cOeTvfyiI^D_&fx65Y z`X?&K(CpiDi9|=^=pqoHvSka$9(F`JQQGgg<~Ov<4O=k$lxp}yJZDh9T_*>2(*MXW zAUhA!q;!-Gljp#KOsIwOYI|1<`}XiFtcS~2I|Ir)E3W3`POZlOX!ZOW5Tb_~oc*D> zl`(qn(Qo!~OEPO{!3T^NiffF5Xf>iBpey*JYvxDVPJwIwWTUx>@z{=vFXC?T@0eJp z8trcC zU5JBBZpw zG14Gn0McjDkS>GPZ^;@R7TtLyS?ets^K#=}eL4HK z;-J<|GWB}CedOBCfi!tiTdS3R%2$5X@m;?S zkm4emfxM;|+T!Z7sJYtqxC#gXd)Qa=9&I^z?HN#TUQ{?Ejn#U0Z(Y4`U*_`gRZcFA zAcm7MGN-nlYxHdOU@_?MR$a0uEqAXFt5mWf8(8>#VW~3p z*k_b1O6{}q9AClz0P}9iL>Yr}qHE9faFLK|@=+%Af{=06v0pP%Zz@^*Ir7{%cb0QN zuYMK$`EowU zL`V{eeu1C5xuZZ`)sG8XMV7UFVL>{Ck5{JPj%GGCM5o8(_-;lRjmWtPlf%Td8=gKl zv()JDRb>fC7I~IKH*Dl#h`D3+-i`Odn+?@~G;4?1<_3E+Mo-DV<&kOI zs!|-;K%|HcuA#t7$OI9{WugeA!`OD0=x;#(>VM~Agh`qF_`#bk-se;m@0KiPjyXi=) z%!z-_GWWNuFtxA#*zBVFrdhtB1g!q;hkx#VEG&P9Iaj#Gs2=^QmepLKI)9sX`B$t@ z>QsDxTkhT@ zxSYE-K>^61WPZzYzpz37W$*5o+00>6qbbPq8E{>E%D3FmbJJchYPA7Wa3aJSuA(exs5luul18SL+H&bl$~LvR2P4bN-C=$1->N^9 zjlTYVkz{vgEwvc)QVE4Zxk#1=i-kmJTDBIf!k@oa)4KsU7FEZ&o{WUD%h&N`@gbjs zCw(6+5Q%ZvR%Cck|6HO)e|!{%NBvoJ55xz;S4XxpB1<#nQQSUwtA|d7*zSpB+=8FI ztG9M>e>w)#r%UJ&M#7yI=U~HrQ0N1n6yr;66%?7Jk;1UKVdIg!}>QOikewvjJ_hPpg&yi!9{ubc0fIWmT(GX&Ty<~4d2Ev7xu~?i>a?Jr6)VN!qH7ZmIyZJfg#(bqD-IcOH^IBQU z_diPFV5&bi<@SGusiXlqavynBOwNmYv>(lEX1hQNuB#l`YJ~}WKdlUNUz*nzahvNw zV!pRw`WAH&lW*lXZe?Dx;I50JhjCD3?lWNSy<^;Db*V;)RgE*q7dKH>1r>}gsWM_; zS0H78+?)UU6IfmN=`~3`cAcsM|G$Sd2Zam;tv^np5!^3@e zON*F?SiCJRTu?xaId5-Iv2Y4f%tr(eiQD%zmc2FWyrGFdE%)~M?bYg?&RN@MP`|LK z$F-F&DvBlhx%rX&ntH#mys(v3Y)sOX<(YBQxs}~=5B#w7haK}YunziubRrmRs+YdF zXC~OhF63b7wIN&IbS?BXpABUCLN5ETSEM7Gjb~K(wSu^~!Jg_)B;0)=vXvCQVes9n zTw)WmW}L<~P!T?yVzo%Q8H6f`g-aGnE{`llrS=z!oVyK@wei!!gNb?N%El@-eZ>9O z9?sm?+^4;tN%FoL8M#d$nNg9rn%)oeWUf$+LVWIwAFND>oT($0?dsW>!J9gJ|NilOWW>_< z==q(^k#$XQlZUUYGS)H}xOy@9dInFKGT>c~``G}4DdX}y70L#D!;r7}%` zt12u>jFi91NEuKz;D@f+LjBsRj8ONXKu}htKn!rH_DzOam|8Si5@;7i0jMH?4)pM_)Ah6S?6AP-EiLE*3B17ugzum*+ZW0f$s4p zIn|J|i*SYQB&g!j$leH*IC6)m{*tAM{V384=Z}T%E8aG|XdT^GG%s>W`f}uoaM>>U$w1}Kcn=8C;n~_aTB5GV zF<9xy7=O%ogiN#@5^-m|nuQ^UC4+0J^S(7AyFq>!+1m14Vo#FwBNDbyQ+X^#al@*o zvTez4VStzHiFD*k<5_@E|yTH^DyNRnBfRHOb8rWJa&I~ zZv7-Xx<7B%=Go_=v%QQX2d3bSrsLMwV`>BJ<%F;A!(!dk86*?SG!;~3I~N&;SZ0aJZ?G(sQ|LxH~5B`xdd>q!~@g)&AiT-OIVEKV?$ zRg)#u=eng7u{0n00_IviquTebzTDDaj{J*It_k^kA)ZQzrI$t{?T(pwZh{ZF{QMN! z7dEWQGYbs2O}pyQK?8>g%^8<+l$XN3|rkAf-4w5C&{jZpn znT8C0-b4&a_UFBz?k+)`Z*ZhRlLSQEwu|H(?T*+lwJUVr&#ex+!|66Ur-fx2M*FVc zo0-4ZlM)6TIg6NN6iQV!>DlE!bSSpVBp6dzqxYaWmRWHS_b)8)`MFVdcPejf{MgYX zyI^(oyHuSmKtQcpMEK!v<-53%rqwdfGHwZROnTl=MXdu?X!Eu()gerFU~j>7eXW6!Q>wh1 z>bU>&#V}s)eobJ@LVlULq7Z{rZji9Z$=OX-_8y=2xo>>h^R`AL_+hbh4{0Ec+eyp} zrk7)$UN|JaPJNJDRA5rjnRe4NEpo6X-f02a-gsQ2nC(+@|Q671fdF`fdC> zih|E#1Dy%Q_B#*du(R@&sv^0LMcP$9)})y&v4Gi8@3}#cf_q!8hMoPG)}U>kxZ7T} z9b14Uw5jIOJ+u2ZJp8na_%Ya>E9O)Q3d!t7m+XwLPzEj4^Sh2zoc!^=vr5j zb7ol3WQej>#r50>3ezE0b=@vinG&z30U}zu%=@&j~k;TJ>T`D_6Jal;Zd1!^!JR%9WF;~;}8148} zd@h&t+`)CUxkTb|>%Uc9@|D6sU|HG0p$)nCUFUh!e1 z@?A)gi6miMGa3p~<*i}7A|U|#qKg|D1=T@Vwmn75h+H1Rh#)J*K(i zS8F4ZPfS4^`HgM1&Z|yj8}9kcEKL^qN3SP8vHIj8?yUvgigLemw>UqmcX)axW6G0O zn=&n%T5jPJ`z^^0uS(PKYJ&(07Gqa}pJJK1y-?R!AOxbBM=!L#vsBBz?&rGeI-YlX ziRh7EWVbo0P)&z7PR;LmWMwC-^+7&T_sF*kyz`d$piJgudJvL>Gu#FTH#IVLDC2bp3LmL{N2<_BaAGt9M|RUN8Cra;7LU_0F(=OqnSoE@kPet@SV@4 z_e77vpG(0fPB(^Yr-|*#Wo9KF504alY|Ct~E9Qyhc6Z#XzGIO1ISEyo3oriM!k&ZG zA?9>Oo3f&9QY3c$L=Yt)}lP`grQo*z~hSkQh(-?#L z`@*YvDp4^`hX$RCW2R#q{0+x<@u@VO=TlYANAFU*ZqW>#1|%a5RQ$)XMZDKyvW5TlY%0OIVPV3JIkfoWcALXlbHB3GC+)TRsOXLt6VQI%)#n>5+_Qj?Y3s%r>S zD@ejnF5SG{L7adm#4IQu`s)8ygz~gvKb$MOZZ#wH1MuXSIajfMc!l ztS94AkB-QJUB)DzAMT(*R;&$1BLa z7*121=*diM`{!eU+Ute4?@aw<5g*E(WH!t}Bk(}eK*h>U-cxxmc)4h<%AG>%YHD+} zagT|chqvcIA=WX8+~Fw>N@Zg!d)VtFQ`A0!fVbD;K?VLX-?qptJ&^gk8IaxYcP)T9 zwV!8?6`DlXm&=>%mTDFysbRdedKC4rs@$}Rl=!62*y!#nB4qy}htlz*cbE=?iZP$n zt~51T!f+lS(FIxHRh`>9ct7J?wVa<9W$2|j5oGCUqz&l+gE&;7KRpY5eJG0 zzb|#E($?NZ6}a?fFY@^;k@52?(^E&H+d9QR33xuT8+%irr1+lloN38C>KVC5Ld1v8go2T@Q ziama_(1&hob~{(kgvlB@>pJ!wjXq8@Pn6D|)1&p&CiAW_-P@H$lZ|@knc%O zjDg&2P_UYV|B1d?F``rulTyg+z5-+z}i}&6d9CO=k6_-|4TX6XtQPq`>gE}zJ z9hE`13bAY6vnVw#gYd_AHa5NTI-lVzFF~0(-IUXKgX%1b7~xoQ!wvJKCHIi#->L0I zgD!yrEBo8?z?|DfP@UNrJ;xb;;bzpUSw`fb!@1wrFKNm6Ec8^;B#*Abqjok#)AV2G z%uVAqw1_T57bL+UKP%Um=I&vale0%Pxqe47YU4~hw=UmAFYiAD)eyPZE(Y%5+C(OAT zP}!EtKhQ?!=&Z&^Z)4ge)peg-niuew3htE4$KUGwG0XBYig-c%F~NClyfq-u9;Br5 z|FHJnQB7^@yD z5CTL*dJ~d>l+b(cp?kB>KIi-0d%rQh@%!$%>yMSSM&_JjC7F5W^S<+apC>uNg|DG) zT-Nxtt?l5nY&9`;cCIDfYWr24JasK?R_zi3Jgp-4lLdBAk~vqgG|$0{Ejds$ng5O4 zn`A}D1;&%+GuLYYc+&(kIazl0;y@y@l6&*D)#+35Z|_6E z`cs5!Ed;H@Ko2>i@|Kgn1_pG*htUDWSCA{>e_dH<-m(k3ff(Yc%I-}V8q>NBj)C_}XQ06$aFn7}QCB@Xgdycqr7;RmWO2!QttKc9SnpeZ!CmmB^iH=?x*J)c2@22mU$ynALIy0PZCJN32|DKxYhjpjeA1#~?zchWyNOoS zFYdmVGe-8#!22!GBM``1`KZsX1+pX7^43TP)uC$s_3F&r+)OGI^l|h~Q2plkP#}JH z`206|&rycUb=FR7rXydq<|zV4T?RVPG1y>e-`^6a2Bmpnp^@`a*r>kdU=T+Z%S zzaB6h`gzcs!zlX4p#h|t5q#WR6a#D&BDxg2WK4M_o7(TSjCp9Xv#Vh;Tpxn+=KSB} zU4`A|cb;72jTd6=c70@GS{?+wH64+mWTk z%JB1e#+u<-<(q|(8eBUYN{H8R4v9SU(gD9&Eve2sVkr)Ddv0Zm8P&L=nQMO+(4H)!1n3Xfy$RczERss4 zEl-}DQ-cGn(m3`UZ`T_-x$4k6VyiRFr1MppAZt!AaoDme0a90D%pUc*M#G+IpyYwZgkZ@`R38EdTs@d-Q_{;r%=Ck^J#H? zfa<9j93SDqZ#!QY$hYIADPI*q%8rAM@$Fo!et{cj-~P$+V|fIQ3uDLFFs>Y%FR?jV zA{oQ`*zXSbT`xtbB9jd?(Vc2g*IT5oTD(64GMF}fMyrdzMe?5RC?H%xj8^sZW=DOn zq!c9@VtiF|eIDXWF}hLT&3{kE%BjO|l!!dQa61+kQ%&8H;-0hiaEJ0Lx|T^5<%k_9 z(n5Bx?@roDxR-r;y3T{qe382LdTZ50-!w%|>l7W-@+~|k!7DVUI2!|J=j=hh4I(-E zC`ou{gwGD-#id-|HUWX;T@n@cN9O^8QK_>pwp-70gyl9T3ZQSfFWj!bs@xW8=u60MPB@b##~)-KWNGiXBmt7%_x)vn zO}!GRr8IYQSCU7xI+x@Hnp7de7Nx10Y#h0YhOL(4mcQF>WE%@qRxTKor;A+wT#;835@HhGQ(~11wn#~= z#Rn-%B@r!)P#$LvW_@9?l37@b*7j;^A)oYJo$tl+8 z6ZMC~z^+@F1@Z!VnE}(W!ae2TG%gn^Ke_K zWxig~R;@*Qj4-^SlMO;)ye%ho3=r)am<&~@0oTv%=DvZ#Aeq-aNy(x~ZvH$z)l7D+ zfX$_tX#NS=iGdvepdq#2UlFNbkA)u2q{D+PrUJ5>66H6&HttsYBzajWe=$u4E^4LB zC=ht-Q~M;O6v~LgcIPDe%%Sqijr>)Mto)4LeWOHIU){v|PLuxGkcooFzRK~hb^`;$ z>TMMr93EkWQ;n7b>+KoDFk%PObF2pe3pMNbKm4#hlTXxisb0qUaePJ?P z$-KWODOv*x3fjG5#$TnQm6*XcdF@C95QkJ9p39I3LzROyWS0E=)X;M|en@P{!hlng zOSHjEaK3*Ua3sK?&F)Xr%d*h30a964-$1yT;*_5fS1lboV~iDii}g)9yKiq2N;=}` z6x3!~R?tu=+^lz553ZJYFGC?r!$oVV>sHY%LJW*WMg9K{IJu?0&cmcN{p);&M%=;- z6OM(m26y89n69nmQZVmN7Mo|xgr3$Ds+JAOiu@`Se3}f^-t34posM2+6WF%-$x{1f zJQDqrC3%A>j&v+&>9l=`8SpE?t_R8vR&4W(pU@Vxt?doojKY7ilpZb~&-0(oe#@w* zwr)f@|70=R5y0StAO7W13`7Q;`X@4>;#A<%pDe#SL^EL{@TxSE5Vnt*Q*^}l2LF@g z^DL9XCi;5>Dk!9x>!grZnN3GBoX5H}yIfBwIeO_;l$%y5<|oUFYV;WW^yRE}1%BU9 z!FMsN{jfz&`}69d`uL2KA-~g4mOrCBXjuWyKF6s>TFXj_@XWDTdm)swnH2iuR;rK| z=ZB%Y+{KuA9c!Ywc8AkDIxKQ2I?L0J{wzx6S@5Y@n>HCL8`Z`XeyKY3J&_Z}oL+Y{ zUWzwddxl=}Sm{Q@A%g2ayJuKE7_0}~7z?3yjL#s~V5^&Ge9j=b)@#aQ9$gpIzaS#g zl+}$)zwp$^HMr6EwYML&S8U!U9iFcoK<3T(Vg>s4B?$jY|jd>Z+>Ws%rz-r;5VTJIv?-pbd0 zjA;B`r01{aoC#{NrC+eSg!c{7`dBxh6uKlltKPgP&y(A-yW!j3`a#;CBw0m^&eD^7 zHSN41Xs3P3gwmnW@axpvvE!oGl>{jmK0aGRjt~_fmJztTExw^)*?-!HUDU*Rdh|*X zJWsFRHaK{_+W8S#9aQRdmaA-w0HtyO1O+3+h8J(mE^ZUe3M16-R8I|adUr_2%^<6$ zzEi2ep0!(YnYUJxHNph*mFXm>uZ@`T1HF+$9isxRNrZ?>%o-q%Za+XK~Qv6q!uY33;|Uw<_IQ z7Jj>GFZyZvo2fv8<%pN;yYiu1IK$zVw$@TcsAUENDc$y#ga}+5uw!V|=V?SdSH%vk zcEhz^`wtuh zi}F@W+xObti|QbX;)aWfbj1~rOn?cO+@6KURwti*+2~55OAeieVOYVH&0>Q|i_tklay)$cXY0=b=RN4+bNBA})TzrX-iRC{!2gqFTEg(?cgm7Ex%s$tB(m&u zj+rntavaALaBH#JKDNc01*#qk)KvG^pI=%|{v$j!>Esn5{Lq@YmZlnboG$tAYy0^Y zgUk^0d@({!bPm9}7XB$vMke?bqXz z8Wb`r-fX$p40BOK`$4|=G1I7BoXb7Y07pAK@Y@pz$Il$MjiTO7UAi=lU!}gEeKe6(lV=G%^C$KENw6PoWBIT?2Ka&#%M_mtX!uO z+>wvo6`_(jdpjk&qQ+;kU<|4Juj0uv&4mnsf$P(5Q43*t2vqq?bIot+zT4yU%8vI;Xqe`>_RqSSgvXItoDRClv0@Bx(?jVSY~z(niL! zH+1J)@9lO3;h=ho?5Y5~$)JS7N-HnM5CszLa zL*MW(1N}>*VT>TMrM~6!IHU(va*Htd0gi)pV9Hy@vI8DoW>|k{?n!;if455{`E(oi zO`>=Lf@(B;g7!`VIvj%lLgR=KG0?W7jDItJkIiGHzqt$mo{1d%1&8@O=1D82C3)tW zn-=E0hWgn*M!0URTf=1e zpTi0)Ba^v7K{`tfV*M2$p4M-t+@OFRg?`Wgwfx3Y=LSPp7&EUzbP0{=V|p~sHj${B z$<#FLv#-*2lg6l1o&HaYF72Yjj3_uxX(%e~5nIdDxk!J&-ftn_fXU%I3moc-D!nmH< zl=gKij9q6XBt?BvCWm)Cew1#t!?9z`MhzDxgdJ~Ew;%};K;$+zDrlH8){WTI9${;g zxqK7gnRd_(4bExTt}l5mrHnYj!%_+YOlRBqQtlSgEg8hygZnEqtw@qtpuX5Zp8D=p zV1*PHX_4Ns?T5^ZP&;jQ^Z7@3&#x^N1Y2Ih76F?H#x9PnlB(vM3U2?ZuB2i+apwF> zrcd;b%)#pZ0vTI)%k|CxBH4A$x~rtl4~<;B98rea3Z`4%&n0=0y{_P8PWS(r_;7zu z&g$BWH>K`+)CTFAcK=|~_y;fp z+aU9;I$4*be&e4k#bj!{5?-mDJQ=+xkx!KP$>O*>a!{pwvYc5fZ=5%SKM5c7o%=D) zz_~AUYgdi$ay#Aq$x_6nheK?4ifY%m2uoXY3qj(6SN1FHT+NlIZ86 zS+$rpw%#_{vQNM`egf4kP|JFHJ@PR#gkFA%LP$h1O++4-d9Px_237+Ku(+`?)Jl0mZeWfT%}Vp(hsz(QQ-W`n4gaYztcNvH6=IJ?*Q^ z&tJlX%kd`$Tb;+k(M=`1_%VVTyr55HB`71LAfIf>P zFgv0T^iS@-_-72C<$MRv@BiVV^LO`OBGmqm}N(a>a6beO{2>WvvA?K<3rT z)MUX<=)wM<>%c(nFbbmalL ze2}wxnksSyf3;aLX)rm+&@>Hkh}s(5&<-X(8MNE;`ik@aWQ|^25^RKhKuhtjk5T#u z%hqjdw}m%=hSjZVsq@TFdA{GzbBK{bzFl=RE%GIUVfI9i0NN5!cUUjBbOkwvd6-mK zw&=BPa?6ZnJsDK9R|W?HY=n&fM@8u)W=u?SZi~`tEzDGDybG5N{mGIr;d2=Bv?Sqs zH=koG!F&Yv&RA|XG&~J z?Qd{kflRh-IAU-pJ_R}PSl0XygJj&ex~lwT|LH{Mo8^>dYi$4HnM|NU@A~zj^YSG} zB|!^&jq(!Xg1&vvz+`q(>%NUYxabxJtWp=Ly-s&d{;O<~o%%H*uOY=^?S!tNd zE4!QeZmm8Fdm|>dqOMWyb2=yFf5PgV{F)X?8<6oYm^x!5f6+CpZ_rth`dra&!@>ZN zEkxsq<~DlESjf9bi}+D@yIxCtuQt~Zdn+HXlI8?pJdLm^-2q`hGtFHJ~*xx zt^DZsPz(b^Eqbak4O+e-=jg`r?i<@9g-vgx^m>87FB0e#3h)%)`r))}4|`dV~ZWI*6$`Eg0Hmt)n<@sFF&_GO_(WI+ZQh zvRsr0P_GyE_4Zf0>2&$+SP&u1pjGt9n-oC56k(k>zKOn;V56&dH3WsUx;Nrmrts_m zcciGJW7h7_>G{sVYf9>x)0HIUmNl#W*^lT!<6K2u(Gl5=+HDCd%~YRcFgo`t`Y4iL zY*+A#1^U)Kz`}e<;62va{Az)x4+qXsnf5bNOx@z z^&x*%`{cgU0r@Pb>~u2x6xC_Xt^IX1FM9I@?gTcyWXp6^y0yR|C8s>z%$WE)?%?GN z0gHA{6FK?hH~p&zxzWJ`dWgsYkJIL1nUmk@qQ6<*93%pdU;E>W;_$Te z>2nO*{3D)cW2oU82xWmiyZC$L5NI`&qZmmb&wQsf~ED zZ}H{-$^yk4LM_>qTYKJCS`2{Jb?jbSUaxV<3akZJEOf9|LQ zcKZdI<$j;4Mn}wIjmm2KgploiaE03;>f5h*@S(-4MM=?g|5q8^A|pT$#t1)_uar(k zTkR{MChV>fs84J}G<#C8Pn-F8f%Q+4Z=)AIyyJzFhE$QMxyw_e{K1&SwuW9ut|?S0 zmMC>Y|Qq&H)$qa7%5L^UA|7+dzdSGDZEq&J44pmQkG$GrJxFi&}5=BX6#X}z4h zAs_Gb?2w#+A~4p#gpgL>>5yT4V%S)l@q(^^RgCFNGY3tBu5*znjwMUHm0RCyZyylY z!f^EAmg1ct<{vy?GBSUN8{Iq1RzQ^MFCZ2qSxLg$g=oCV1n9k87#blcdW2r@Q`Sn@ zpITXHs@XyyTM4XhPi&k07FJJpN}Hc+WaY(-z)S;!HGy*do#U#?Iz!eO?x;q(GNARe z$fIJB=~u6{m*#y2M<3m|zvmJEyn)+@jD&UTz7xrj3R}#;x2>(^8c`#88RP};#yEQQ zL4wdxX+(OHEqYk_4aMP8WXHI39f;Pac+`HGv)ic66&9M@gUaMQSu{Z`oIkt${Gjka zI@zv~mU>6yT%O)7OzbazdY z%GYs;+pEW>b46-bG#&GQOebyG;E+SD86)#mD8Nu@Y*;1~;8>A_z^&fb6#W6q%88q+^Qx;RE3032_D~jUb?%;YQ0)bNL0$Kb5-&6oXmV7u zSTc6t$c)IClTi82*iE)I7nPf|2pr~Ke?*f6rFy^spVAA-19S$MfdRb$J6C2)shh2IVfRBh<8ygCpZkZ$c3`Tw^b2;qN*(zji&kQS zXfBhjQwQd0ZF~(9Y zNV+3##eyV&O*GP)5*6+a)DK+ufT4G++DJRwJF=?}SNJDTcKe^(YcPX0GNF=#2PIb7 zSABx(ut2{?!*d!wvnai8(e{4;#6o`T1$8w4APgIRQj_`kVdQx?M}JN<2SJE9@RGk$ zSD$nIxLVl6)I%n>vlgFg8Zvlmf^jVUnxJBwm16-eO#NyTYEl>27b5@RF%BmJB9Iuf z$m6=J*;+%6XUnC}?SF6c;R-og+$gQB3Lju~;L`XkrBLo~Y(Uc);(x>_g^Y705n(&Y z%Jq?1T8qZ4geL#k~;ofCmvw*_HFKpPjm=|l+~>3 zUlrRdaIyB67WWLZf@7vmf%JX1ba(3SLyik5L@@-Q6c+lSc;8hA#H_=C4yq>7asJkJ zhp*SncGQ+bBdy?@esG%wr`qzAqa@4G8D`Y3L0?1;5Z!np(h1dUR6()6MqM{C;uV*Q zP;EUk-Ooiq{xeJoFe-(JVY}m<;McNL>nL`n|;K)lIf&#ZdD=~a8Uj6 z?)PT8enT71#SP}$7Z(zlRLlL%nyYp)WHovkl1XJ8=TWQZfK~z1vL??8(&>*F<+X)^ za8TFl;4wX8jh^}S;aSGMDzk9n+D21g2o~_c zP+_B%fNQw8{31TQz<4*WcgQKz4qE+8d`Y?*BPCUPvq-NN8Bp_3uH~Ck15Ecaen_K_ z7}0#50XT5f^qQJ~EbH}p_y$zjo;$^^#5Jg=!~imF%bw?ERgfICITE;`JG`@uB5qEO z$9ktS%yD&3{jS2zZf!NhsIP_U+VWpASo6?7<6cc7dgz#19c1OR$4#Bi@x0Iwx>L}( zfxENY(;HabmHOCzHPfLy50Ry_k)nFjM_;ym6M@LOB_H=Z-1HalSN{w}{d8)88EdOU z-4*Bp6>A|aG1N-7KT1fcZu)ZS-+PN)&6BxH561cDtR}N-Ea}%NJUeH0g*W0vyJXPh zK9xH#9Bmgt&0Y!Sd&yhY^6j;#t9jI3?zo&F0xv(t6ls6um;D7)kpQu>DaYMa3}!9Y z8a|ZB(?(_LDmKK;wMxJ{Er!J10!Rfk^q8wNLUh%Mb4KWrV+OpFwx0B*`aC>SGDJXi z*tl55JGc150NUieC1rXUpBC&vhq&oA^9#_C-Q%ib7pNXzK^s2~OA}W8&D%(8F%{%p z35WdX|7Y#8Yq%Q1UH#lI$=*-WH}=G_TM85)Yw_J~_p11dN&Zjobafc{A_~S=b#-Rx z;GB|jF^5ysDw9?&!eT70I<;HzonkEoZxUBI39|3;_0*1GYE5-St`+;H*P5Q)7&*I} zTwY!QEOA4k#wWE@79>cmf)NJgvfR;~X7Apev^RKqMG2G+M;zD;w?Wh6U*0H>P!&v3 z`#>`%g($k13yNR|jP`*6(bwB{3H)+brZ_IuwLAn+&4^#)5tJGNnFN$Mhimo^gQ-wf5Y!nKpE z5eI#S*qZ!HMSBp`m7Ljb<(#dBJWGebkvZw77T9N|+QjO_gTo4E)@lGg8~UcbnaBaBq zo2}?fAunZSGAK)}Q&G?gGp;a@?Ore@(@(LSR*}vh(0yJ%iuM2+d;(jM@^XV6>$hah zEtA<@ty-2%JaNUukrJ;ZsnkA0bJKR=0<;z5vqUntOSDkVnCm!GMG(2z2U1I0{{!0O z$hLp6>k}>fjPyaer)jIwOTiA;*mmfgNlxWwotAPjK)`&k#@o0VeS~UTwR&Ti%ZT$e);811vKy5btt zR&^)rr2@gy@b}G%3{z;D!sQf4P`Z1!p#>HaeKWi^l)w60vy*JY6_H8_&Z+3%VJ9qI zqa{9_-ip_U=3Ur(Pyz3NuHCwe-Fyd*`RdmYHtWR5315x|3%47nYiiTp#P2|*FuvDh z@v4WK3Rs6BVVK--qDyiZ0)hAx8shsstA~GQHDIs8L7x6#wlreXNs)JxEwVYmO19)` zB-gcVSyk24Ozx5T4x9tUXT5UNs5Q<>Z)w0xTqLHfg07KA1}gM~sXi^XQsuvuaMYZY6_PP$CmI^?+R>b)34(z-ulpcG>uX8B(YxFZyO%v~_ z^S@@S)t{A)>r1y;;z(coy&2?aW!y2>)=je}!SM-9r5Vz$INwPJ4;v=hD8|n$rwCt1 ze@6E%0KfKa9{1@a_cBujOxNFSXlc8h`zC*>?_{AAHBKMA>QQak{x}!V6Hpa-IhuYx zsN{KXNra-+hELN#D70sd(Q&9&m$;oslS9)z3sJ?1?x+SAddj1NY|c;{bb=`~5P|_O zVb`M7@9%q0XxsP`raXj8%fNCYBEkW|9pSFK$(G$_!nn1W#M~6)jegKjHv}P}w%Ra9 zoml})d~IzUxZk*!L2)QMw67|sD}k~klWAjXJ_YEw0I#Ctx_7!ZReG`sv2n97{aV~X z#wB`UWWL57X6X|u>^!v2$usm;rs)$Zaj+D-0gsmp4p={!a5da!AMwlk#j_FcLr*>> zH8M3!#;$xs7dKqcvEyZ(^ZPAVy!>eKa$^eH z61Ap>@kK#*7t#|OicTCfs3`=y9!xFzTbVzx$NwM)U8r$pl`WyD-k7gV`GF6CR=N}J z(O_Ywh5+w~II<58BsDH?9po&o*D9=(cWz#aNCFJ74v0Tbmzw|V_t?HcI-aA@HE zdR(qB@3wjf_sh83H2x>6Z>hXdJ&xV)w6>qM!d^$%4ul84tj+W>*ztLot^_z5PJ&xz zI?kj=ZGIMVv6gV%W9GfU{0bGU_kbS9E;AYG7Ev6Dy>XV`sp{J%k`#i*_zJ|^<5kqf z5U+`7vkcP^CHZj(znq5>aL(!U%3Ka>Vlsme#lWk#>BPA zD!R6)&~jlcwk~K;O!jC_HNa8RI^$7tK1YP?;{{(=$I!1Wf7mX$$21jW7&{=dZm2GK z<)pzR6RldS6}E}4u$5d_IEX!hXTG(2 zH4DI~lCa4ZWOylWMbY3R>GkB%PgtmI7%~Nb=GC`oT32ct;*IaBY(G;yq&!DwXE)h@ zZvDgTOY}Kg6RiSUzwkUScwbk_$ofIEPN1=Gn0N6~SV%$Qh0!>wzpIs+mGm**q=)_~ z^6jWZ&|3)TO1a0)U-jeN6sVF2JaJn7K?3pj-p0bsZoWRpZy+yMU%(cwXI`(h)8*wR z^q0nvY&f^7E;6SmfzwMT!;A<2N1BAyr*=uH{Ose)8Lx5F#0!e)6^|5zj1|kXezK&y z-}uR*$(BVo7MejALBvcXym+8s4}{L%mTD+`#5*qk!k?PdUmvD;B&@fShLuYs^y7nLTAhaYLSc=EF(RvZCwje@tzV8fjZ%ipZKw5*cZ5Do^#aA9$BJa zhL9M3jPzN95%Q*8c|;3H?U*--?{%}PabJrOxU`DW6YE{&&{G@+2C9Mw*<>VLq~K1Y znd3fOLk-m~siT5Ekq+femL>-C$EtT?jOL7X%+wSqI&lrqP4dm!?mo+)ecmNXlE3v= zrKH*C9$=GZX|fAXEf9zz*~lA5^6NZnxSOI2)fbe>RUR@PDX8_gF0A$QrgYE^+hGSj z?~-wC6_?u3(x9Av;zEVtWpmjMYOo+cR*RLdVYwEs?TIg~L9xSWb@|wL$g+2mzH35N zD2o)o6pFuu8OuNR#kZTA9LE;JMJs+B$uCPX)COA3L%UXiRr@r{&?2vK^<>VuL>~MC zpp~f5<{dyBt8%9CK!WTsK32SFBQc{`$LDq zJ-1u;Hxs^HHxcG&TaFYNl&|hI`#lLb=cZv=E%8)$sJO1Ab|o8)x4cdv`&)j!o#d8w zFqgWii~rHQlp27nvyoSi6nSJ&QeNN|H=3veTqq#}H?>+?V>d9-6$Eb)B>1c?oNREK6-YTb1SM#Jd(NX_cj9 zFy1q$*zJ_d&2|czKOY!I{J6(|p=7GlhMDVELmzLDm$U@Dh&u?@)7hs1mMk*CGr`L0 z#2ekC19%;1*nOO=DtV_R!c3kwm(cp9>FM+G7b=+c=_VO&PAw@TSoo_cyWLjLGJmC{z zRHK+{de#Ofyx$?fBQDYlTSf`)I2I7>6c;P&IdJg@trx{5YUahQ1^C~h&3OgWwJ!aj zTleRjx8LbMDC8|jYz}TMmk6j-4i8wGG5o}|3W*RzS^HEXq#&y}QCC;TQg(D?cr#?Q zFQU)VV&tlRPH4Ov0GKAy=c2xt(0x5TD@uOnd))fW&1zQwT z)iZp#kDJd7kshqmRppbGlNpPL$}8=VsqOr*UY{^-+}$u+KypaR!Or0`CjxMYo9$XS;))Pt ze{kCF(nLYbu;CVSSKhGLqp%|Ckf1!=+LF>=4NbHWicunttn%f{J5&d4O-!G}A4iWo zZ>vNskN6b#J0}1WA-s~XXK4CAqCc0H42rdL2JLH*h}i+Nzy-78b3ytW;X@0HzK8np zgAQ9AHPvAbJ*3Kn^@-k9?Owscl2R7&&9!*23NN2 z!^jm>nFh5aB>t*u&h7GNTnW)R46$Q&c1dk@`tX6O8g4{D)8F4}YbtO_qr*%xB~8dE z>%|Z+hVl4VK>4vsM9coS=GAA*dFSoZyW(tq%5#y|BKo z+G`~1ireyX;b5(J&cdTV6AUHT&7q2H`qYl*O?~}Gr5-(SG&I;QAc<{oRj^&b%>1sC zxobx$L5Y;(?T}A@)a*=*Kek35cL!&h^K?C_yYSrWkLNs1pwu^PS|p%-2{xry(`T&w zSAET|NKXghRL#Zv@@*H-aAce<5hqeo!(GQW zx#z$1)ZlW_tH0QwpVrG6r$s$+VxnfXs2*sy_X8$smSdvko`0d{nSZ0^LBzDFQ6?`lTcuP%z0_ofB9dF|$lbHI~IwoTbnVbz3gNf9bhVzvN z!~RV%*%m(*J**mL9p`HyBWWcK{Xn20X%;va)Q0Kkann;Q`QEfYw6fZ~KbOw?XgZee z{LOoXp!I@$lXCo3BC=|pNhsrw{urrIq7LWp97F*Gy(6%@vkAd`cEH6xGpTwvv15xv zCS{~Z-18h%FK8*9!%hSlc{2Xzb`mzUK}`8so^# zjtQQFR7?sYk5GRysGbl1Y8v$3;e-WN>PVHC{yCrTdco*F85!Dmb{(7Aw02{ z%y1phW#-PGV{WIHy^fujF0Z~eks(B|SLltW2atYvZ+7xav!=~e?kXuViIt*%lolps zz#Z{AE?GIN5Zn=;z%v#6rKxnF_~UGg!Yo=iSU0$Dar?K|yp?MxOJ3tvAOHRIg1{MF z9Yv|N&oDbht(Zkoekp&8Y3uaCfkxx5oSqn7tFrZxR@Z<{)S?nT)pkiv12&n|6oISK zYKQ~7+xy_X0G`|{R*W*$Zhs5C^)8wfS`fkHc72R>W2i;Q`Ca{>t~qEbt@5JNmsKF3 zGvzv$t5Pa(_4ruld!c=9WQw#Q!DMS`*lVh6 zKY5+_xXs&g!>3rKPB}yXRzPhBEIqRT+B(1RisW-n?%vcRet-0~Aux8Fy)q-v>2{ur z6IgXEa33-`eb>JCK~3Eh4?D3w_7<&X&BwPeq7Sj&E*1>cNzO*dNK~7BD8B{XP}grB zlX})9lViSg%I#ZiZfxxIYo6Qtk%pCW9cRD*X0dP`&K}>VYRPC_i?8)@Nwl}|yCNYG zCm&G}8fxd66g7_R*!x~$l=Z4EicCFdn%dSX>ks;{q*pWoxM>ST4v>mkZVE*=X5C%u zCkMa;cYvmGZyU7ym-1+S2-1l7T2)8!JgVf+6iP2=Uso~{;rWBq0L()in{;AC_88vx z5-ksFWQwS*JoT&*Seb7Qxnk%O7W!=f?{-~)n78%u+jboyuXYIPt8SlSsmm{E%$f?f zt8i$qpl<{Nfs~_%%_>fupR0==m}RB3U~YEAts}?f-%^TkMIgLaWDt$~tTkX&|rIugeeTex3^M5z|&(BIa8^8a1lwZolUi|y|jO*qP z@4SB%Au%6}PcY;+mjAiIzZ?F?uYZ35{~G3(@`&I6;}QSQ2ly-NGQ9qzb@nfm=F4I+V1~O&;O~-`9D~z=z3pH&63}jxu*cVz;v2@ zJ-e17z`njPqdQ>ADD_R$xt*<4WhB9VGAcaJ9^k~EH=>tAb-=*#2rEg@^(2CI{TFuRQ@7gP?^Q{<&?$Sv3d8?fDm zQ#p?E$0h-etayL9U`1)D!=+2p@aADwn0Z)j2; z!)!2xA1nGAkl6I)2!cF@Z@Qh!02g-LmaqNi@B8l=zpI>PI{;+)?@hiD3+zii{1{o}%Vj(rWsC;2C3?dwpdD%VFuy-H)mJW(g@2 z%nh=fWC|cU2YH^qrjAezy4%Sr?t^zEfA5;2VMcy*V8x%d^2_H`#*>D!zf~dqyuQxf zu7-TIyBSCvldu^MSLB;`k$0oWW`xgt%V0io3AaQ#mZ}@UzSaf$_E@epoz-1ov#Bl&QA1AT^!@v%{)-{?Uk4v5 zX5!!1f4{1sF=6;W9aXAURVN?5Y(q=g4tS3=m~eP^nekgu2MTHfve9yxYKYUrIW)?u zpziW|tkka^`!6aUKi#X3=y)ElA1*ka`KI=UgtR$YOwtgzr@FHc7f%+9P=Fz_@>laG zj31~d*FNEiWcyTO{xHRIusINkBN~Fnj7>iSOcUXtw)xFqk zax83(WvubQ25{!6(cIkdFi2ciLvogkSl-lYBPrL6kv8WG2Ty>ti@RDXolsjvT;hwo zdK%z!dEQ0y-mtQ4awwd~9TCB`U_%&zGAo=`-6e{&4Pk>$#>!Qt)j~nS@pm! zb55VWpi!#t1)}M5%sG`h6k1(O=LgHh|8=tbckY(wbb|Az)C?v4Wc#~?%z5K*FkD;g zX32OX=~%Bk+$3a(iWA%I&#q8^S<4U}RL>vn>R_135df~sy=gr=As7?00pdsd2eO^t* zx9>!y0K$+mgfcvI{<1&Cu_8Kon$|waB(!Yt07^$h5r%R)tFtNg=@NBus*qSjiqyz> zagZ~N-ij{)O_J%0+#}5l51(Xn<%eIX_W!ax~p2?i~5n;V*UDs_HSR*^`=a+3~VKh8z8aD$$3;QAV+h%pP#pJ6X zotcih&zd$#iB8dIZ?5aLHzCXagSz*QYC3JVhJBvVnGxF{0!kgJ(nScpj6$de1QL1~ z=>!PUJB$T|KtQ^5rIS!3Kmvq>k=~ImgkC~TLJ!^dH}jnLeCIvi^PaW7KfnBU|A56x zR_=XY`?~kFH{e&!C0%XHkfON5^#1Wh`wD6a^9*5Az~$*cBXlO4DnZm+5EYcdLY(x* zdo|aI!txbJ21iN2G9|T}uLqgI@JAGZp3E^poVuy3NBALD$&K+6RwjL!w8=?_fHP7d zYxZeANm$ZsQg|eXaPMK&`cAB<ox?Q-27?Wd$R|xNysxy`UH?#rG4;#RSlf#;om3fK z-LE#&hhTf96Jb8cXBn>>h)SlcMhIc&__^cNUW z&#*CMeHz1J6r37t-mV2WYznw$c|>D8tfMJF+fFKeeKDNd0KR{xOwCLnGjt!~#2HXm z6zas0+ncmLbkL!*^wvPc&pkHhQSq4S-R>kD60Ec7O3`$(X)N#@XNqRnQvZda6ijC6 zN|OAHy0(UCljnSJiK7=QE?1`B5zh!>^R%sPKyY)OHcEy0C+@Gs3=4J5?&`ppL({9* zVrHluTP{xy3jVpssVkn@T^y($Zs9emYox=-=U=iJmMy=Z2O#HJk8AA z(eClJ^I@uP5W0o`qm7gR{Tm#kraIBcV|G6+Fo$S~Y=Tc63UO|||3tLzzE)QD?Cr7Y z>LZ1yMP;2Js}V~gY&;vs2|;Is)+d@}hBTzIT3u!?u@DI89a3Rt?I|5c7Y6>xV9BJm zr?PIE?%nw1-Sv?Z+KS)l+<}4r@Ddw+wJakq=v!{iR3}z=2WMef5v*Hp)KbTbvy0`R z2_GfohlNtVoV%4Z96wtck*{9?5)N1h9dDm8Cj&zBs^}2+195-`~hez9)EOu z-^@Dg;kJ794s^tsBQnbo1oBH71M5aR7@P9*#TfAlB%!f)hX{agjnGV<7$IKw@p@& z#gksx!$e)D+F>k{CB(~Iq-+tA#pT)LQ&+af$9I1(OlxD89R2K79!AkK&SN~sH~WZJ z_3#yiHa?@5vYpj2br$()|F`y;Xw0fcaydMQ9C94rIjlPPF#-F>C7wV2`V#!$w>^F7 z(hU0-t-tbD{>_UU7P4E_#<~{MxX+28MVnMkO7h82rN8#dyory65$t4gv8^}H<#e-4ODn*lGZUv3KgnYEbpt&Yq%v47KNsl11on}=((w;N{q}$Q zjeel;Bhn#ZRC$Ff9*M(c&ZitU2DA8?3am|3Xe0*A+?_ROelx>*yN*m8ie%og84e}A zd2aI6m$m_SbLY#j*b%_+C$g_DpI<4QpR1O73t?-0Aeng{GwhO){kaf-uTmj`CA_IfYgQqY0YU^3XCoDIf^kJ9mE+GKCC|V(=D?s zyHgG$hbLnF)($_Uu7!Vm=FbZ5KNGvVYhh>l99q&T`Dy*R;LV{;deGc*MDAr}OIc1- zR;=u~=brt&#+GCL4w^qCHMJZr+TaFf=13N^%KzuT;74%5Uh2oSJS8wb+aY3!Y)UzQBXZOmIM&hrm@Z_Z1pRUqh?uo?z`~)()DqX zvaHJuk|6CDr6u-K;>Nw#Y!Brl2>hvCd5_qGL6Cs3X(bYbe+a7x}KQ$m;t!-yt_Wl<3m*kv2sT@8y{zJ|W;;1_e~DqbtDBCqGhmmXxR&aFqH_ zM^1}6TOWGu%X_R?4)w@y5(^VGsifogZ4`pn&0W}xJPMtzjQ#1YnAFYbdrRqollHOq z``sK!c9`3;bVuFf%uGSMJ033-W4h-P{E#`eg|d>HJIa$SDGhETL$zs+XR|S`C$}ev zRo-n8tB9Sb4E-?A{PmnjbG`~~DrD*P8+X)|UKHZWulS`vjufOaMeO|}XHAmmtaGF5 zxGmJD&@fDt2Ke)Xjb~nrv%Xd=kJ-qUn{T+fXoCG%I*1m0h&&Ea zQAIQb4ahTyMM0+c^&Gk$h-rvBJonryDXHDiOhL61jyvV zo>0Ow&iu_5Eu4A`>t8rNTFRIavo5>ySzDdFEzJzoJCT62 zJogU}3Ha#KX#`EI3aQmQ^dMRz*V4n6(w)GXzKn)YoX!%z zF}+)`k%H~LtzL6XO`x{WLY5bPaE!@il6y*t_HdtOBRU38lQHtP)H*!@Pc{cU7&3}6 zA3rVxo8nCKJ^LsPa=ME5d@WIP`A2MP<0ZB!@W(5ll=h-Au^!Pvb#%Ci@};Z#zx^BN z`X3(sqho=nshQ zFJwW%v;+`eQHqjFA#{ZJxmPuO7OQ6WYE_!=E$iHpW>Vy)bp1+i-9n9bM9okr<48Q! zOOm^ya5KPyu|;y0q6O{4CY>u?RJ50wyNv|XUMbr&7JpJ48v_|wxTJCsL)#pmg6)u> zB4j+R@_~6tjyqP<=S#AOxmPRM3ti~xVY9eEq6KcPt877YZXl0Xb%16sK{(E+@y*>V z;NVhA;m3vB2mAMLy97Y#1)qQ5HBBFdvMYcx7D{4}b{>1ivs1oS8mo_;sJZa;iUie%6GSxNw zB}n=FX(>Awjkt}Y&s?+eGsn%P&u-Ae0`rzn=d#X{5)P}pM@pt&n5>Vja&$=6pEJ1L zZtABv1iGf@z6w-Jcl5~O(-|{gh8(&NIoLYO7oT=7Z@Y)7$jPqIUhliJf2mJuKQQ6N zgY}Iv%!~9}Gm2fkME( z2XU{kqD+S@Rv36xCmuh;Tn-nGShkJrXZn8W&R9iAd63gR3CGdfHe@6~tK2y=1Hx{D zO0afAVcqXksU;tKe3{O!y|QJKx$%4Mw+qWtA~x6673hA8$LY*xYD-%qvxwDvTR?DP zPjyeg+3J)-UT4$}=!?WEJ2~;-gffT7e}|3>aaktf>>&n-pt&> zx_0F4$QS?8jwp7ogvDf%hxJa{;elh1s=^7mtHOD7OBCE=yzVwDHLmwaW>NbMXAzlW zB3z}3qLBS{VoBGtx6~QqqvZT3|3^@gSnh=8imm2c#!d$TF)BJcMy$pAf3nc+H2wT} z!rFgi&?IKyq^JgsdC+@rMc0A!=wLABMZN!`l~z#M2;dnt#MN_+h%+nqzpiO&sQpN2 z^ZJnTg4X_wlBh>%DFt0;WTtNBk>$6&BWw7L*rxjZlIGF3&x_L2xn!Pz${O1TW1C&a z))S4HP_K8&PFmHhVVq(kM;$$(&I+%3{C;@3*>1oN14;CX)oUcQ+Wok;VP4`9pV3vu zK!0xMXAU#61yH}{rj&uT$gG3sM1og@k<_)t=CGO^z1W-g29yP}3)sd0lyoa=E+$a&UGSU?nS8-2GFSC+e#k>3= z-qV$Sz4>9YJ;?Uf$EGEJmIn5-^dUKCbeJAGb|;@j>-7$`#fycl{4F4kAwsOcNbvRa zlisK+5R$0E3SGH@>!d#407jb|V=tZwn2{fP_j4MCO{yb}C_ihyBS>;V`AOo4!Sz&FLZVLnQIgV4s?Z%g1BZHar z`f(wk9(2}`2>mLNw8%!QS?MTqQ0&pag>LO;zuLUWo+`+cO)6-s4c=Uef5Y1bWZqnE z{I#1J6kukOH){`bcimAK+ApQzy+96!QRXDBA#rrxFMpm|)wbllvQ&FmH{8pLv?5M5 z#&^a{!HIh?>mz4hPA>Sq%cBA#)?HCh#athHyn>H9yAY{;6frI?^I)itV-hvI!e*H^ zG37BDS5mB7md6oT9utkSZ>RyWazrDm>9`FvR@*-BpWk?Y;qYrbZ?h45M25U26_31G zG>f8B_jM|D;c(s`@D9_Ao>G*LC&BsvY)iG!8$XS;u^s!EZKAu0V&kx&ku8}Aqj&D^ zcmYE=f;fx_?qCG1T~>UtR+)c}#+{meda(&{Z{NgZT|V$*pA;1>{jkaxh>pExB`>h26?*!K_9fricI`=F2^eMl@AMEMmxX$%VbJR>po7fZGkv66Vi&o&k?g1550UG zO(U+>p8l$*=l1bcvut9j2&a=7;mk5k8xcJYVrlk~0#l+Qk=Ca(^jiyO6AG!?;$XK* zZ&dYSudMsdH70-bY`30thcqfeKm2O!|Hi#ruMq#g!##c?Ce#hF`2?FBU-A5TW&LJJ zZb@>^fxZjO)F@4+C#f^cX*2Kk!V78}E^f!9~EaMOi+2x$ho_VF(LJp=?rv)Uh0c$6=W!3WyU_QUDQKDb#XH+#a$RYbUIa8+K1;#(9;FeFV2C?mhRdqj&etm8Bq`eCoj*Z zsXjG1zeeoRP*GL1p&VvbE&_rfdV2m*Df!P%mT5tXQt*pKWr(Dig2w^-b(ds0e50%6 zGtJ{){oqM7<^V3r=fr?BW_yJ(FIHG8QGxE_S zN5(dJ8jN#CJ(YrN){b6V50nLClLVgJ(Jsj07tO>c` zHy&7-dA1*aQ)%f|L}n(NJhq9_$K{PWS>C!Nk@*u7d~*h%Ip0n+E>6R~UjkpPb=p1` zsw57(oF^3W((!})&pz-1-jgd{{ozk%CB9#hz^okKR&SU(d%xRUsF!ejgE=zH%;^F9 z|MA3xj?(AdmTgW`*VOp4dByMi`z2FFBNiuPW-9YnxEgFM zFcA)C0)3Y;oUN%C^GO1KXX6O>WMc%#x6>^ie*_0hnv_XGdPCh zoOmq6OPbT6aEIyR9hgb{1~=nPQ!a(H-F4r8j>9owo!bLq7^VpXt9Lw!5t_Y94-B3z zCNo>d^yT`ldTG=5UbJ?e=aQ0wMHbsY8ngbKs)|G^H~fnX;BdRiu54D7W0)@|X5B%H zWfa}2VIb&HUwVU1nlD%H1~GvCQABw@da8SMs5#kdSGfc_eaVwo>wln9|Mo|uOP2s$ zy~^L@DtV*mFLJf=Qlh@q4!8NDbS6=eIpUOH5S*$)jcUKjP-zr9Eg$P!jXpyvit;*r zLQZ;>mKsEaWR{56bj8~e7as}nRkc5BzLyeO(63wOc{5|3RhF*fluM#p@JfC0{qXH$ zRN&E&K;B8W%k+iA9e^?+*lYiTGO7MWncV)9GVy}kP3U>9a9ygdEJ^qD0BFI`T^PBF zT62u&o1mq*sy~TG(!SnMAJv@@O%4*VN;paOIf8F`a!hkA#i@5rAz~~KE;dWY8_uWp;oN}dG zUueH&K1bA!J0CAcw;?1PfXo0Fbp*9eW{b8yFeB$+d923rHxcXnywg23A{YfyRDSfy zI_ZTv&7&E<8Cr-7ANQ?K6q+5i?K_n}!w<7aRd}d(9dg z19gKe26*K+k4B9=&(>|OPl18YR0^5+Q(m+K)oUwM!tR>GHDFy>FLhmg6;qo7m0MA zeCg6?G#a>`zmuR!Eyg?DLj_#@B6aQF+s}sXA#xO^*i15^i;|eb(fxQC54BQqTIZ^#>0y(&VpQ6!fwxchd1z=F`gkdhHYvdAGu|4fAXfK2V#ILd=jjm~<+z#uZ*d9aY)_MI%G9T&oDb>f>eZKgX(V9$iK6_wQsqKnY1J2LHMcu#P(~Bh_jjL z=x#RW8YeS#XU&)iA`}emA^gS6YJYlp+HSyVqAJlTTJ?_iE$PP4X!XD(uX3UZ9rhfl z#dnn71u!#=+Um6%og2G1Oa{@OeM#$JefXzBw6EG7zrDZ65r#tX`vv&^5Nqpk4;7HgmR{2y5NKWb=yhv{h3xr7?p?bohPhX??w@;X zR8Jw{+iI!2I4Y$);wy%|HB&IvWKo#Q{T1zww7C62l!J=uqMvD4VhXjH{Jf^){q*gh z_F9r^JaglG(8U)_@Lqgq)H%<>srl!=0RnuD_|7@@(jjN9y(NaY`7sCP%hYF~rl# zJf@N~P`>Zfa-dIVL#)6HMH7rXY!b#n5t=3qTie&JjZyS&fa@miT6jTxE6Mk2H@z|B zyReVLd$X2wTx_e)`b?EvT*RQsd%Mcoedrx1t+c$nJcAGUb0%`Ni_u_ocT^JydYoit z(#;DPA!D;U2tUlHN5!?83)eNL{TuWPwFgfIz#ys5X8~$fm9#8}xLW)D(tUuNmCaZ6 z3pfGrXQ~|;YurU0;^@c+0-62(hCg7i!ASW(;19TsXUTki-Sot{amnno4quphfE=Zx zoopF_sso1VvvnM!lNE3QG%XMhx^IyG=GUDZPOrc4uh&(BVx4~{@3AR!UY*D{%>7#whKZKIjnL}Kp1OTiZN8Sueo{sC~@JRn|>YsWJ9TY zX@at#qaG`tjeF?X_)LY3UmYy?8mNFd$})rz=3PmyV>0^I{GY8OBkNhRPyoh-Fw{T; z7?k#ZYaO*)Ap|Yov6%W778Y%FdsX%ta$i4b(%O7y+mfS;exGi`V!1#iN8a&zZiYZd z87yMzFj}%K&*naHz+TTD=s(L6Td;O#v2S<}mB)NcbH;(`EKW0to%~sVwiI66c|Z+W z;@NCbzh-i=Ac@gUcRIM{{u!!uURVgnXXclY{7hw>>r7g79qgp996lV~c4(crg&HGj zPc;4W^)p}H;-ocvIS#2b#Ub~U(h2DmC|w)s89467iltI1a|FbM=&V8ARz(@)G1%F7 zW@RfW#0BFeRJ5}7$(s`n5z%$R*E-C#;9}gFH!1<}N6F1;nt4$688x63O0iyNB zTAC9%LQ7wQoj*IK5zQCzMne7adBK^Ice7Vof}!LATX|Ca&BFzxEvy{l7`lb+C`C^$ z&K>pHkO{$41CHQ}6LRI*CHKSB+5O08N9iLRn~=ko`(wX!XIYI|qVxW#B^A2u=+Iz0 zAq@33GWqi>Ep5Zuq4h1!@<7Iro>)X?B^K7!K~uTDj`}DX^-=7%jvT#Y%$z3s6HUJ8 zu_~k@xWk$JT?P$o{CXyA@Evb$4h~kYmoeogLSGM+3rzfZVoP?MiQvykPhb7E^I056 z&RZ~zqYPZY_1kewQ)W`RiVhyAi_ZI7w5Fas=6$-zQuY4(Z1`gXWz{E@-Hk_E{$_mp zGwRaA6@#A2!=NK;3~p9=%XN|P^b}E8^)I@W3ec_I6zfFAz$3!NTPNxnRroI2C(XeZKU#WGwls8KJTR{)(uJmr%2gM008 zWjUXWdgL*Wq1-v*9E_M*95uH!($Hu`$wD*K)>Yg;HRzyHbmOSZF`V_zm`$swkQN#% zuiHbT0*>r9Jp?aO@4T;YPnJX3Dc3TB76@sAj?THECitnEOPqHXlHZWS?p@)zW@yB{ zDi$+6exkck7~33{T*rF*0r|39BLb_QgVGiiI>z%%g_7Od4CKumKmECd3)3o=FESN- z<+xq(bVt=>#=J?S6`;a_ZRMpxbf*)Xo#Zzj$Md!nIEFxju&`pRKE ziH4WUYU6BUyZK@0ECljh*N!beNBYAe+w4?<-4prvSsu$gsg9#J=hq6>mOqI*LmZy2 zUQ_kk2>*Gzx%EPg=*X|k}Uz?Fbr zT)Wd&>(a)%_zJdMdc?=#kA2?V8Tu(!>+(9em0)vpJ{Sf?8kn82!b}_GOQ4gz&UkY8 zL|?d*;z-#Q1(o7tTSEt*mLj5+juOwn!zStCpY?0CAFtJ;=2w+Q+*}D$bM;9RK*ZC6 zTw{jvQLtHmA0^QJLVr5f=a0}lHBmI+mqgl5O|hPsy?0rPu=F(XoWCL_h93PP@2JZ% z$#XuJVW*rzR(;BB_``fgG=+#x0P-0DC+yeS^xf^hSZ3qjEYttrv&>vV7ItYLE`gRb z+tF8Z7n^t3StnSgAeNeJd6D62_tauuwz)TX+GX4{EK)c!__206||Jy?)yb~A< z0@2Dm-{X;^=4VzEz6 z-H#gNQQcI_KwMaImTi6g+NBUNpZ7zH4S0HDY;vh_=6Gpx)66vI3>7)h7NUKeuPIy$ zg{gx`nb*Rv0}hM@4oIQuIL)dg$keJYMABNT>Cm!g3B2VJJ+l~a?URSoylN;-_#t_~jU z$qYXwANUOv6xw@X^~zUf-dAPpk!}(dLq1(TJl-h?>+-*u_4?^;hJb0P%EJj~iQ;6h z2vg#1bCEfGEWbS#f}b2rl!q*WrM#S1uYP0vJT2ky&5T z%Qv~bny(O|x!%ijA?Z^o!HGW8qj(odTKdg$n)l_s^?gIgIH(e{wmTnw-6`5vL{hm; z7T|n;_{lr5mD`ECHJCe})9;-lduGDH7_s2%>z&=Z2rem#%mCv)pKy&!|Yd z7FA5wkPz&7Ta?|Gdyk_clvT~oWHs;~tyU!}FD(3yla(|-Z`6Sru&Q!qf$T!k5gB*iOnlK3D>wu zmRB*y;&%<27FgV7Y^=*z1s50sH!$d%1)^KrYNqLEr zjX+=-MniqTUIJB2@nbMMs-5KIq}MUX=-pETiJ=QDzum}Y^8)k@v` zIGfB|N5H`qT?SSDF(|qV^zO|@Kd85|3WFIrMO&>orS`0z4<_cUC|hHey2@ldj|$>t z_wIbZgl~<$UZAo#EO9N|dg$9{ck636c%hDCsYY_a!q5wOx))ORsDT?lClVU7qux0A zq(Z`ar#CmlVgd+TJ+I)Mv+9_Sb7=1PXRP zFY?%kX{_T|iC5cUHVJs-#wrgvd)6sUn{6a2jEYuBF0sEkz2Nlun95&iWn&jED{0dJ z8y&k56Iut><|p$vBpO*Fky+&U!82v_VU-6pf72)kQ}(_Zzj2ef!jd!AF%_q@Axie_pd#YoZ{j~CRqr5ZO(@F%MP?N? zvoPn*z4&YO&qlMr+^-cE7>$R0Pamc#>>n8A-9-L2!^=A8QehN1+DR$ErUW?1jk zcv(f8VfTAe8w8d}N~^+QqPvGD`t}gTZuF`GZ!iCLMzcA(V*q*u)~3Mm!Bu!G=huGvt+_>s55+; z+|u;3sX6@oa$-eD_anbqxqSY>jb$G($YbZbPMi8i?;G7{KLw6Tgn#lg2bdPy_bds4xMUck*sO7TRM%yAg?}l+)76$aC|g#pRj3R^_2yPUarM z6GF8SOOq~Fr7zaQOQDmcCS_e$IA?0xQbKwu&1K5Y8|W#OwigMaLbUHOaC5Cct#0*G zp@mC5=bE_R|0Y zuUAGjmLna6(h8iekksc2-K|(m+RZ0adoay@Gl|6DQtexo?Ev7}6b0T00RT@tp!~l8 zUK!iJ2Rv5;8YRV*tfxQRuY$+wTQ5Cr@|;PBtx%&uwX>5DQ{^Y(3TP1W_Xw&NU5-am+NWG4N*vUl&~Py^leWg0HVmWb=h9V=$?F zg-vS9scD^x0h;upWz^^?`lz82#ms8M|Ew-<$?COGjpJe~1W=2r2g-fF1b17)Iq)u= zsEH>V1^M?&$JW(I)X0(cKM*Oom3J%M#3p5?-zyp+_dUFzHVwJ!+>2nf|#8 z-c?yi3Kk1vVH@bu=+PN#baXVjG)jJpbCLJ{I1h`v?1V%ksj|wDR_2wTX@<#7JH9t- zQrAOLK_+X>Ar-#m+SditdOvJ3@y5q*Tk+(7vH#P1`c=|9zWPDyE|K9zGmt3UDGV7m zl`D_oh~Ey;KPxcUi`GIhA<`7l&%x?kaNu)aT-qCNlhmt|aSnO`W^3mw0NZZ|(gyJYC6;R6XgcOH^ab577))Xw&sV^<~ zulv8`5b8u379uv*uQb7R^Rae1IaK_PH`mF>NMu=&UzeI67jeZXac@yKp#=VCbu;X?RBibHYa($-4qGW7V!Z z>1|g%eM4)`c>iM)+(}LVRxiI_^56M;m0^e5 z_?v1zzaZzGH(mU=A58M@%j=P~xnLr^P^Xc8RduaD^#&GRfEDq;zgDM+D&SXnzeY^| z>ra>iZ5U^3K1hH90=C>*guC7m^3nvvC#ie4R|owL*xEXq1LZA|=^imAa|{uccvIn) z*ep-{`VwBhW9+Cg!WW)G6nxNM?j-zfMD>Q1a)!+_7#Ejs4$p}SH*T*a8(CAy;zu_+ z%4k!_@21J?((gjB#qpi)ep{A5Dn&T@Kj|o^SQzn?#`fd2fbPzn)Ub1wvWbkq8O^d5 zPhSa>o;{kO!jnQSXKb#Tp%^7#k|XDrrHCx$!A0N3-Luu#Wg$^9>smhrjb?AqdakL) z&q;W8RD##JjOwfj!a2Y^4htHcFAQUK;dtho++x}6%_kc}4(CqH$q%-hegjP%@3ov} znWxT$_DJ1m-U**euwm?Zc#iyWrd9J)L3re;^Y=>z8+u4_A*9}#3mD$Yzu@=ScgG8iSoZmN<+$Yar*~NX=&J}Rkg>9AFmLxwhu1eT zE1}Q2M^DUS{Tz%Ulit}mE#2KdR%`k;7|u>HIaQRm++8fk2OZ<{CSH=i$QkyzTH$^ojme5ytcE;oix0RHs0tuSHNJ2<1cX$vsUCFpLF6)JY4X zh;Tv0lMv~w^X0sDwtDFFk-yOQOHop9-^SP1<{nHoOm*9oS%zMI{}mh-`)g5tj8R3| z#|i^D8W^~?$Dr*EV;!Lz(TLWYz2X)$L680&_gGPCdT1C3cT#$B=qhNhCSTH5;Ul#U zlA^^uT$4BfVo6s$qAX8~ML>5FCgp%+RoMC-z0UAN9o(~JI>wZv1IW1B)@UHZ%o48B z@|vfN$_>=pKqa9I=T-s8`H#2$QMx`>|E-3<#je^IsY(m2x&uzkmqu^$sRU ze7JO?vHsitjg0@>=l=*1n&%GC^e&C`b7Jj1Q(fO59vCYK5PtTJe-8&O3skByyaG-b zJcDiTQ5S4Tb4r;#46P{(kTZJ;$B3>zL4qOLs~T3C6B&uBX^GtvCIZ);18RX(2}S*P zzEU$uk?+Pbnrv^DTtlZF*$HJG^SN({)DMpbL`=G^Qz+qrC#!d;E70YTQ6)&@(HVPP zNSIT1pv}bI9jWQVmG`#wilim3e%-Cfb`$GydSj=AstO8rF1o*dmUPM&=0?$gkMQ~x zB`g5p^PQK|<*yZ=T@+WS4)f>-FgjA~pXR~Y<>+SOZf9;LvvKe$ing-XUP}7;AlB+E zMlx1wJ0>H`bR@|+EwO-C5+1_!HzoqqVKQF@qjWz%5))XKAVR~P)e!PH7JET$1m zFV;LNw2P512@O1&9o_qIt6^*L?Ff>RAf!z48y_kM`-@N3Cp zpqV8Uu#upxnW&d_<|b>rzsHAPdh(7vB7SP1Jk37Ehj3DM{^jUGV^&d@(%VY`#xLl;58`1 zVt8R9Z3x5UJr-c8hOx*0&Yi4s$<5Z^bu^pv@$L9M`+BgAJ0`%;FXMi$JpYFaUAT3p zM`>(LqRFSlfX;1d+79a%!CCSvE8)r}2l=~FqiH9mVuctFiNvI8ltHDBhIpk`zG#Da zbWG!?)IzSH!a8{lOZntcq!}uodW$v@hV* zE0fvh)KDp1^i2ZcU3L!yx>DKy+eTL1FosdTghI^>LN{?2&c#5T7}J=F9>z9SW3=wZ zvAET}NjCR9t?gD-GW8tAm)yY;Jp}NEt0>6B!~5P|aobC6?T9O-W~H8o*DvBlSu67# z4nWmy!(deuS;+%xSd0N$dlJ$JSr-GtzKqIJG+BF{oe5iDv zeRrc$z{Bn5w-`VAALr6k*NN$>m}x`ifDdkPGhOW`xF933UHCW+3xpwvRUnK>PY*ky$%83#x6whT^(B0mpP3?DETT<~ocIw@yhL%Jnm z^_F!1CRf?6a0!~+(mGj3QmXnv_;m+mnB@(-s!EgWPVVXcpq*;ZKmI(7u?-rf%A-eB zBxhu*t(-qXSMZ@JpQQqC@R@cST{fU-9{DQXZG#_7+EQ^SvKKfy27CXNEBj3j>DHT9 z*|J?DuIW0|VPR>ee^!RoJwkh6`^CoW#11tLTtv}8kU>{;OpYhzqCn&Ax7N2)q9Uu9 zaPr8utb)^O={9%bM zgr#to1lJ9!6^BEL#VbZ}y%V!q^5&aZ@Z zJ6=T)r8sB(ak`1|Y(=uNzji^sP7&lnHd7=dIMHh7)9RG`+UgTv9~PnM`1#mKxBH6Q z_}-xsTC1EVul<~JcHDpNLNDI^n!E!x0_bjzf?r70e#_4HOZw{RPP|<8d2HFLQ_``; z8n;*LD=I}*GG|ognn&eibtbJxZLyCuwJ_Ovq5Ron7ov@0CCCH00=HK57lU774PByu zf&ZZeM%vE*-h$Jn=jvM@=6}$aiPb9ned-Ebxj&vHx@qHp4K3`x{MTH|uD&rv*-6tT z8<}&%Ie@-=U`A7?$swacu-$Q1uIp0=U`_WAb=UB1Sp&@_zR!sttpl7m+&(OY@x3Ur z)3+g@O#@l&*7E0 z35k7#)GM^lm+%yb9mooj571}IkIdN-*=q{?+S8%-(*BoR9yYdqRe}>=I$KnehnVrF zJDIw@S0!dMb~fj&x$kTxZjFx;dD`o41O@rUhIhJFUK6IZ(6>+5?(s?K6&fxDC#pXR zx~CT)5#Y|Boc>NbWGM*9m`gN#KF9Sfw{$J4Im%;6DE@lqZO8YMZX3mu6Z#H;e&NGa zb4qv2w8{<2xI6-(l$GWP9^Q2|WKQ#qh7yj?C0zP8>2~9VXOgK=GjT$n*tV005ct7O zU@tdi{K%wjN#A}-4b*N=~M9jh-Ye8*jf|%XU zA>KT~f9Uk$N}XI&f=uNh9FRx)Vg%e+_iY4`Y)t^6^GIFMZIFhsnzZ*Oa6z_ohtWoY z|0{xsQ(DF&(MBE1uA&NB)|?^=(S=&2kR3J2eeVK>aRz>Cg(;Q;Y;1OhviLoz;iw|c zcLpiOX^*y(b_Z0Cv&~+4%huF7L~QwmJ?tqNpz0k%>*qrjlLgch2-?&22yliFclW|9G`+;2&9VwH#ZK za<;IJ8LQyZ(t$N$N53Jc^lpPge8oWI7x2-8G1w8Rn=kAR1>`9y?5{Dbck`A)>vrp4 zQ?o;`~;H5FoAdca}fd`hOwu7LH9cJ_Ss`_FtbL9$z3?T#^4>Bl+?$;llK6 zVzhs8Zg&bu6B7u{sp`HZcA^R7TfHA*KTtdRXuImZtI>0jD5}0J3qHS)E_1l}F@3jl zEn0#7tTL~8W59qXrU!%nu)MBZ2-3KR z;cTQbv}_L564nDP1E^;yYC*LnypeZuKAH9~Df^5*{s2$Lh<g%72e z2~6~>XIf0vBHA`MFGmFQq)M*B*5^yBkI#A+R_o5A*qQWZ2YV${SbWuz&V7;2yJ#O( zIJeMDSj4p{qS~W73~dez3EO)>>8h>2{clTGfm^7S- zb10pP>JBVVlf95Fqicc8_V{z~$331R; zCys_l@KJI|AU+aBHB@w`aycG3bWB}P`cYwXwIdT)V#!BL-V{EHopjt%*HAfPTH!y_Ch@w z1feCWbJk`7|H3x1S<3>^$~%A58M)g(a$#}b{CxO^r$EMdsuda9o-1ZErTZ)VOsIO; zxWF2aP*tzxQOaCGudBaaKw!Om!ihzBKERKi8+{DPYBhHeH{vEObH zQ!xLqu5{xoP!+I`3C%^m=BtCUb64pt0%u02h+4&Z?)vI0zXsv$xx580T;2t0C3Xd=+)$>cWjr-y3o!_C*S$N;=@6;K{DCuhnO#k^@f) z4_|surnr$DP}``MoR+_8O0l~Cv8K!lC=$D-t7V;N?D=3p9C!GIXi0weta!s9+Y~ez zfsG(d-sHy8`053ltX}9l9!$hJFI_oFn$hRX5wv>l5tkYV_xDY@2PEt=!+P2@A!9cJ z4}ab9ihJ>|sxq+N^XMWH%z6z|GRgmHfn~aOAaRpX9vCbedgQCqZj;Dr;yW4Og<6le zYL&fVpbvTMQS(fxnCg!{r#<-AL0d%!Ckv}9l@RnS-83$s*X+HWl*%&K9O=jf`mW94$2WHHKQz&jq z-V^Aqje6&IN$be=n$*vZTfh6INN18wT1e~Lx(z2Qx+`}AaCeYTCCEFjkmq;P?0&2F z9*Vg8!nJlnV_Q$3wIWFzi@V~xQkH7sl;&oOKDNX1`6>c)g_@Jh%#sEJ6)Oiy2LM6c zNTcFWCjy^iXjFtkatTxQ3NkpY!Rw1dNm#~|u$U2Z7zaFShA%>XUH!ta36RmoO${GK zyoQqgu08*QGCFzHHt)`zB}#FcFTldmPZHG+FJC-yJC~}D%;%#LE}TT9em7he${Rj? zcfuz*4D6Xv535ZV{bT-%l+Z8gD}aW~26AcVAlbtA=19}jYTgJi$;1|UgLU|)fpQBG zkr`Iy%mf$H{C19fQGde$PgBYE*?y7d+W2>@HY1UpoSo<5<7WS>xc820Biq(Q-KQPe z0k<(0nA}Y?!ax&52Dc3Y0|qRR$RL|&Bt%AFVmkmP36qULV3QFDj6ei|gl%#*L5L(U zIT?|2=uw|J=gypa-`qQI-h02Ne@a!QU)5ICUVDFgt#5q`rSsNyr#wCuyKQQ;^S-ON z*u$&?N6zi<7cpVokjL;AMZKMH@O3oJNrvxT8fSz0=w?O%_%E1A{0nA6l-76I;%+LM zg8=>si8&yfx#Lm3h4M|<6zJ1aB!u?CN}^W=Z%B;~?QZ@5*aWNpCllmlnPAvImvtfk zVOjUTHbE1s?~Rr~L9#-}3VyfJ=p)H||JLmum;+Clk)7+xO%T*L9>FRF_f%mo4E=O3 zWRvalJtVVvV)$3>|%{wu%WM;R2sr7X|{jg9D z=u*zBjHnDRZ+SuzT)B&OJ*@Q#EBkBIZK`K2BFw{1-QD457L)guoeCBh;|C{mQmw2v zZsqh@G1d&Bi82R(hjUbfTD|tVqd)`Y9xt1XZ$;q=mLlWMO0zy#I*ML1Jv_t`#+XUm zfTx}&G^%L|-mcTnG_h`wX;1m>#8~iC1=9WJC~IplqUy007?p>dn0xutyM)$eb0Gfv zaE?2xxNPytdX3qi=ODK{VS)69?1*4<$r)$71Z!P>wWQ3e#RDZnNxzFpylu-1QL$^c z<+aIRm9+&kO#M<$)J@BqBN9=0XDW9eCj%j|?>}NKtX<~^+ozSxa!SIgWc;a1QFQ~w zM9oWiLEDl5jxvTJpE=rcueJ}a-tQWI2-#*$6&q2gRWg44&vVY{X*D#I%k3}81z3iQ zagrq57Djq)BT+a1ogAFrKn(~>?(h3~3;V3`RG&$Q@86}KI#`D-=l+kq@v!Cmd*e#* zy}^Tf?Y*a!EU7l+y;mo3OLr4w>>SUkemdA+nmemxsmHFEqsa#>2WtKPFsSAX>%yvI z;I{YvTjry0+|*pxo*8VDOScrQ1{)o_^%AXX2+$IgOjU%{^&Q-4yugERWS45ZRZH;V z@&0h9U;y=SSl9rmjqHCUg8` zS4qAzBbdYDY_TwWm4@j_+H^>=#+^5Rr#WN4Dg?Yc^gTroCigt0grzP9xEFUVYGJi9 zG-mo+mUyrjPTxi@*@ep6mVpXRkK6N3o^IL}ZOE{*4!tC8o53O=O>Rms%5SsElLs#f z-}{21<183-53<~P#m)=)aXzDe{BFfFC^lTGnrMwS-KwlfKoPKa<#fh_B7ovb8?CC3hc=MDD7BirZUH+FXD+ z?vX>3zTB71H&xCF@c;3jLFRvdj^8drr#@J>R}5qhahOF+!IOqT&bhRQd9~0AC9seC z!*XvS@z!Vx$Bv+``*>Q~tkz-@#!aX)5_8X|MC*<vS_ryD#$?!fg;yC^!R;+EEgihyx$IorgdGu;8}okBp`DVJidL zwW0%H@u-4~@vLl*E-Ty7B%3tVsm;REl2wmuox>j_g;<`_1emUYjEt;3GHO32_o zqr`#Xha_1Qu0En(XUR!HoqFp^kZJ&~a?{~UgiO(7*EBFx8h z{rTCo9^*Ov!TGZ;8r;A5f!&au7rpX8e*WOmDHl&|q3KxCk>c5NaZB}k53)75)~7*) zBmbn`&g=(U0e)~fX7DC`cwpjKzp&PNgp~l?CxZT`%kjFNRc-tB#H70UA~)~ygQ|p*{dI?97PCcrm5f@9AxMzMI1CyUxIqR zqmwFazttIMTjMJQ9>E+A6z*X%nKwPXTI*egtriV=b@@Ue`Bsy8!}eJe-$7N@3}V!h z)uTb)m|;={cmMA0i2uvCq;!H4JZwb&HBH$2ZbLkK%$uafA`72`L??Uv3iQ_YdAK2) zT|6fS3oP9VsBH>M8k-&Rct?gS$V>%M+z2o8-SJiM)ch-7C{g)+R8d)Qd{7EIK^qKX zaffb9;Zj};r<+E%y*!DlwcI#*YZ9kiwb##1XFK89nExUwIu;X&Q+^bZHu^Mi_0MxK z;0i;vIsV}p;1Llh9Mrbs-oa9BjQ5EDncMkNi=)*sKk>Qj_sMZXUgS7WsV9A~`7JfQ zGdr;4mRD!ST2KAnRJ~VF?fqE;$idJ|qf&!w(5OJvbakuM(#m2@j$UBBs&*LFQaCBS z^dU=MhO*vY9^R{Msp!F6GoG>j-8bm|!XUrdAo(tHAFDJOFnK{9W^1d82UXTtZcHNu z2xB@xy*{EWB$UIumcSdtAzxk=$&L|XF*mA||jYq;+%)XFD^zA@qHWiu;6w)dJ;|DzbVyn#)!d!KkdDmp8m&e89Js$Lg_j#o7A zWWwVTKpkX_TO(>2l`!?C=rCYlz@2YSAO%B=qAV|;n|lvJoK-V*L+e<&lLp-`)H1={ z86U@cj!9nKopJR%RvsB^jkWWtXHG8mMwFewpWhq2;J>Py4Xyxg)s%0Vo?hxr{g=Zb zt6@FHJGaA}SkB$}!|eXs!I#dQ{1>RiUyOzx<&@m~b_vQ%W|?!+?Zo(i6!zx`flmK` z!|D|O!#G>?Z=P*UE`YI?)MfgOkxLAgkcmV8gp}+lOWU3K9Kp+1awa8$I6WRYI}Aki zt1>eJXZH0ace}z*_8)#<(=~@zAUdrBB@ZD8Gx583N;du9^qe_p+g$Wg@%+{nJ${ie zQM{5kZU7N&yz|}xCXyKK@j}kKJmy^kG1nZ$xC%i_+L57W{U$iyOg^u&(cM(PK{ST? zRbQb@YQ@l5qG5MX@_%j5{{N@;9P@X3o+|T%JnsK=xGE_r_HgE+{e~+(rBJPaZmAjGQZk zb%962+>=eHv^bh4P8(PfP5}>pj;m2Y3tx zYFPI(ZW$P9d0@;SHiB;_fI)eQptxhXz{pBJWM;lhL65u{e8b2N8NCCv#9#%men$F3)Wb5GAk>;F7QV)=n} zc2uU%Om)@aogTYb85UBhC(%#4WEw4or;b?3>Ho5OTFHu;qFDGmaxJ6r*phV}4~-0& zbWJ~%d1F;K2(?v!Gk`Rm^XhSWi=w!948_MSfMGOS2Wo6Bp^)@h{N%UT4Thyh-Z>qic_QKq8DkSQvi*AW9*oQ$B za>r90EE;TA#R||>o7{pwW&-Uv`4!qEEg@OXUP9#5;%@&bW_Ea7Jouplc+AzbVJcA} zfhZ`TZn9DcI4V(c{`1_AB;09hvEcQB1y7BTRp-2^RD@FsRY0AH_k%&h>+AY-#sqFC zKOD%qrtmUeZ>KXsU~UZAGa1kilukjs!DNAre~uz-u#}V3SL$xY%)q?DbEP<`0}2kGl<7d~$b3)PT{TJ%Kb_4sxdj9~UP>)1JiU7SPCV}va^5;o6hCESw33_tYsC;q5wXvN71_(Ylmx0xy;`uZ2wrl}cujd$ zvw5}2nX9z=C{=GC{rNo2Fzz_d@6M#&?9{AdPeS&_Bf&~J&zce)yCJ7?io^V?MP(4k zrNv!p$_6x-aWt2ZLQxfek!#1Wu2K^C8pF8dwMA$YAbr{go^F-$Gg%QvA@L=pw~IiM zd6<&c?+xbQkXetaMTyp`>19hu(xR&q394Np64K3ARSY4ARfs$;Wkq|3V9Lk3+%~G5 zn~W~a5ZP_;dKKtafJ3~cLL-M8fBXn2^wQ{JVY0ufGgu>pAJzhi9kuC}yx_k5Qr1A2$ErYz;9#juA%wvSOCpMa+IyKf{*qrg2p`7$6h|D~~zw$@`$6M|ey8`G1`WQNQ;cQU{zs;~nYXM*T)j~_3_+5+0w|YBOT8j!MkY*jCz{=FNKUMAE?eDzOa%!y7;ZE183CEnlULpp zrk#kz%|E1>cwtA&=?@lfOb;o?fp{_q*oh(O$UP#u%693=U~E|AnA_y{=7$;HrJqYE z+x0l2sz;E)tvgYREJ@Zuf0^inDgI3M&C|3+3-_SXs{Pn?6Q3iiV#)8fPm2-uZOiX{ z*&=X`uL5!r{=MejYaHf&3kk43+bLn5j2v0j!~W|W-7$0zfKbWjlpax@T_>^ZRiiT* zQ3=oIu=mR_f`pXpba~$-(xo!Da-Agj!0n^8w2hv1RUc-85H!m)-byHi3viR9Rv5Lcn%@QHwO~4rPF{gqv457Ap4?VkbDKkoeV-2Geqt(b8q3&~$5m2z_Mz>1aV=pw4G*s02_ zb+tp(LDHk0N{#MyJ(H=RE{zPH+kMd89jbUG+c9G6T;p_tIymbQSW5G z@5%k-WI%(>cZ|9ooLzKNzVxAp!4gY>gAWU+;i});zqiJ`W+fb~xi`v-(5@Z}u8-}e z4C=aJzze}%?JP3I-99^FH}ziNWM*%g+M3REqiJo)x3lAXD=k|N4ua)y%4Wm)TVim_R~l>-ua77f-OG;gE!A_5@ka<#A*iAoDRp9&}U5nCyGm1S)Thj@0f|pAtHvAV^ZCitbl%{ z67NF!6@lXZzJ$(2{E7SWpo2;xr+)Tz#ro}n<6Eft(Vx3K9fzO%^IRUQ%I1Mu^PG3CIl3UM zY~<(bX%uzx#KEg(FGQwyYP4P%$r5l)I^rjYl6lEw_7A2le9_S{)eJO{<;X?@44+KT zg1RcOSB@T;3lGJF8*#I>_y?_3R4Y3qn1`0s^YgHhZ@=W1C{K=0=#S;w1-DdfmRh+Y z8S2aBI#$&mLLB^mGAdVhN{J+Y=`|}a3;%shr}Ln8cGmQ+xw_gP3@f6;2bO6x8D=4w0E-;fLRz3d>8S^pPLUmyLWz!#a!FHC^>xp4`*fD z1)2$UtMMyX!7I0V)a**TQruDzKDv}u+8Zx}yWD6LFue9|CRAil<8Ggi+5og>a;wj| zwP@Ll?Z`tkNMhD1Y`;yPk=9q&0M+)7@mHBg21Bk{sb7RrV0JdR)NG8V&b5DU%$?tx zU4CK`h8gbEwuF`N)A;?h!0zSTYF(jiP35_yX#;tBX=Qo*WKE%3e!4Pa`qG72m;0+b z{=XGj0n0Xl-<96YEQVCqy(#8vs4tX<@hz}Y@z#Q>p|+VxSH$H!YN57+9xIA2t{!Ue z`r4z~)_b;ri**$qE)OPOB}i+FHkU7sYa=fV1*$g zA9#b0mibK-&yKE;ilt-%O)Z(gg!JEBUZ36gSg$R zkCsi_{8IXsXG#{8N*hXM-ZW-{-ryj`N7t-u{sy&vTrPU4Ka8rWBX_J>Jmmes?6Gmp z0``us^P&^lzfd)N-oJI2CH7b}cy^4eF`qE28>W{$H_OTKS7Ds$D}4j;lTNnTV595NGCL)CJEM0*J_?fctQMWDC*H&k~?jXXBX2g)c` zp>t)1ELv=ToIDS5?}(eJ+PzyXxBQZ>T86hA2Bli^^68HZKFdYO@~vO6bFUYhKMJ-E ze&+e61#Aa3q>9KLL|zYmz?YN(>Ge#!Gdb3~6_el7nRRf|V~U2Xmfr}z@x-4YN@M=b zFNaL`p%MlXm*bb$+$yysb1>Z8BHq;sW~i$GKuM#yuU$m&sCN$qJ`hP zgH!^nH1H^kOa;5FzctuMZZrC;l%Vnq`s0R!@S z8-a7#LS17mes?QR#8k_}E^Ge$9H8zx3^wl|>);QTH}y%Py3Ct58)JC4`#sU(*#H)Eao2kn<}=yY7BpEFgqvAZG4FM9 zrI~s&@~co%Pj%G59*o`4z58EEsk4apr-dckXBqr|T*!U&U!d0ic>1TLxL#gVgXKm? z%Ck5V?ar5KNxjHdALY%Zd9<4MT)*@_zq&?yenB`@ z71;Mm#9T6HGVycQf{m_uqn*BQ7KVZA$xb26vz<;)vd%!I>mLybP4mt1=$k6 zFXX)QzsLu7ZR1gu@Sw$VqMJ+z4?Tv>jpDI%i>Qt1u!yy7(y_Q2jLXq>EOD=s0zsQv zdFIWx8UaNYlE!LN?RWu(}Tz@nad~u5aTeq3cf$2*<*eU(H30G_ccEm3nv8 zF$<1~M7FuSlzNaq{3Ygilz+xBP;jhctl$5`DMoyrKcdmj z`E9`WZ}IUHjjByP45z{dm%ya#0h%8C$w#Zyg1e#EOTUk}4nI_iRxAvj_m}Pm`P;by zY<7vKnWx#5q9YE+h*8fO9Y(=Bg5l>BQf&!pr-oe2U;lixa-_m^n^Y9Nln+}a*Z3+L z*GSgz)|opQHD;#LUyYBM`{hbF9W?mUOX&5VhXVM?WWR~LsVspJ2C}@CV4F|L9@bR% z4U~jcS6_8^iC49XHCZ=_VMtCyO_~}Lf%_)jtSXtnif&{AfZb~CH|M|~T6HgCUjbHs z`6SOLz3o~Ie-2*~!YcP4yOmsU5Zd#h)x4A7cqb?MA1A*G=@q#g4)h_=AV_p9f82c$mE=ZR9i`?)kx(3dj zh=^m&XY+xbtocl5mjzBc#J{Avlv|3y1t}gz{svy`>=brIxEx=O43KGAIo(gn&d;2f zuXfxHr}GoNP+wrc1RNr# z^ftv3L`@i%>7{Gc>~Rlc(JNlZuWc+fE#FxXkDMuLoz@E)=YfRn9L>02p>X~b|C6q7 z9^5+{lu*8F(8KY%7pv4Cn{eyK?sUyxHm_Ob^5y3wS`*B`T30{32@B}{0q>eT-*2u(1iU1XafEf zXjZf6;5AnYKYDIr=MQ?=Lc}BzR={6!*&=4@DSIR1e6sB&jW7l#&fJml)Pz}whHXes zj2gsPo2KX~7bLZ+l8O-uNH1xgVp^7b@|b~*2G4e@p(WaUQ?R-4B98|=ho|S0bEWyH zbG;tit=_`-jHtJqE$M)qVI|x*`vz5}^I^=zRx5Zm00SP=*Ys(Xv*!V?QpPB6#2wCjwJClr?}H*L{CaKXQal# zMG~l=m}OsWC{t`zZxD3P%_iX4j#-J58|OryfG_EG{$xHE*}RUUp&;84#>|^{`JxST zct;lk3X#U1{2iIHf&LAd4*nZ5-TM#7^yggdgOeYzElULO;ZPUlTXGrl2;uFSW=1|Z zJnlTvef@amrm06N60hJ_sE*w0-n@6yH7nJn4z~uhUVrXV=>YXDxp=CSNJ-u#+&iAl zckf!982Q=R*jZRv*NTA}UY(UQgtYUp$WnB&iy=Qzg)4otO(gq@WfsLLJveliqQa1B z*4Ek49u02y9e#go&&*4?xa0qcU*5k*Du7#-3Y1EAyqg)+Fn6Xtu4n@_)l!maiE z1~Uq@FirAP?p+n*zA3jVKgDdof%56DaN@3Gh97v|lAXP4=Nb)ad|t&&s1UyPKw9|o z65J4K%z6MP!7+SV5sznn(+>ny!U>QMhQF)<)*yK~1p|aTw9?jHVQ$92LdWtbg5rMhfR6lYQHDd}KRaayG;q<|Zp^ zo?b=RF6-0DHB~@SbQp z=U|cfK+L&w7)}e9#CAU%AdUsWjZC-1;Dj$XuhkN218<6$);313TM32Dy4N zfd=sB&B`IV*Y#;mclP>SdI<35txY~-o=+9nYckh~rq(EQ=fh>x&Mhxtp~CPuor*X_ z0INdKik~)%%F1%JeGlWoMhB|;)65=?=VL2gA^2PrXso{NbJqMUF|U0p)v%t|Cr2qxJndK$2=1} zWiV=xDxfxh>NTZxlK^Tyi1i|GCYKwOr$C*kuwR zx%&EVo09f*5*A(3HWl*g!shq^sG5h8TK3Jlu(T_@4;B~g&kccc>f;=Yt>ML|bX*vCS^Zhckhn5J_tgaoHK~d*#~$Lkhl1*CGRlsR zLK*BZ^g*PgO>}fKy!UbW=i<)g2}s84tb@~FBad1`-p)>9QY;;|)fde~te>BWsaC2I z8eoVwSK%22d%PKH^$TGa?^)iT7^njXPIST4Qkc-?uD{(a!e?JsU@V*bM(w^XyL;8j zW5hYu6}J$CR!O2kOr6c2h0YI9s&-AZ$5IW13gu4DdshPzdJcO|b0MlAc1>BL_+*Z_ zX=lUDl)$&eCf+FbZR*IDfh}q1WzG4xA)%6?Wb6^z02TCB{KAoZ>txz^LGjFXboAX7 zy*t7$F&!Rl-=cw+NMTpkn=ujy8^ThRz z^EF2breRv+o1##0(A~i*p<+0x(>`yOi(ShZBMa?}-qY)JYrN2NGM~ZZMg=`kn9po; z$!rXI-fKWp_9G$T_tk3;s>ebGU3#nIy?$<8yr6{b;(X`y+?@+@cYJtcm4Nt2hK;IZ z>%lnECw;XS%zWH3+%5Ul`?H42SXxq&Vs(g%1}>lKhgGNjsNaI2wz!y!0jxA#7@KN}Z5iWn+zM zn~3q(pxQV?BIYZ`&({q*3T;VBE)0oP2Set+xAJMsvlsVAyr zd$hTclz_vgELLF7OYw(u4#7+)B1gOx(e;AhTECZze%Dqs0Unk`DLZB1H(yOl%Bf11f|ch565P9mL_TWj#*-p=GuwY2g^jJaZBi$ey8HQz0KSC z1p;Q}pZ%C-L$g6FZnG94VPqZKQp_1(ee*7=qu427X-cuLG|skq97RXPFT1V?u+%A4nWa>m;mMZH&~fw0xL|Kk2%9#NAAHN$fqGaT2jDttpSsXsEL)e> zw+%dNB1h|U$r(%?VsYQbYue22ebFenGBY#yth}vEo``kB(!lFhB|($*B3l*wjIJxd zLOD>Ww;0pNNjr{Ck70G->%8y_+1I9xO-TZawn!_y_;l@1isAvIoA3}1e21~HX{i66 zKtV%o$tk%tKk6x?@B^hmd~Lpaz1aGsxgDs5!`-R`uxIH)TB>$h0{g)IjXKke9Q}hm z=n6d3nWmA;^S;U)O3<#V@@hWJo)yLpfxXW{YNV_rJCpH{%-tA01KxQjLSPOf+2a`< zN72t56U&CB4huGk_hHPNJOsF%@e`z%xvvfNUaon!J2!MqEU&fIV+!yp9)hm7+mH|Y^UPr; zRWxaofpA8p?Ed|_m z*5N}2io4aSt5&7bDQF{?0hsoJKaO1`C39SCJXP0N!G%;pk}HVrD6@KzIJzOd%c`2} zQ9W#ZCqE9rM+bv{{8fLkV4Uoxh&l^SZ-%a zc4>p#WH&^i?q0a-!8^h0HX5#lR|CPW{UN|AGM0vjbV_y7H8z*qP0Vo-5?7D+XEES7 za)dxdar*SJ!O;{Y9%Y(z(ejV3?}r|-Vsg<}(oOD^L!aSy@_p#JqR7nosMSjUAndNT zw?-NmqCP2%Iy&r8>jH9BX#l{5k9=E4zPoh}Pnu1>Xrs0M7ChTOd*bM+SIpKfA$u}z zOyqI0Fe$Dw9rXXMD^&8ldafuOR#YE+hd~TTy=1KXdM$4jf6$f-& zNU(@33(Ft;66rV|GTK`f=>DcHfVXB2y!k{MA-2>c7XO3qsh(L<6ObGrtEG0?skM(_AH z*;MPbs0PRjsdeV!@H<-TRcg;sFqqhQBt4g z6cvr}_~K*B-?_4W4<0)$%u;{Uo|*;PS$8sD<>k%d#-{iwbAArMN2x#((ySxSPQvVibx+r%|05$*9j^L#t-Fz%89J+Gb8o}=P2<^9 zR@%v`;O{oYjgvWNFWQITpFhM1R#we?#CKilE3f>Bp*aR0F{;K%&Zi#Op5RXbuL*fY z_Qae-JS{j;g=5CYh6ZLOXoy$%yk4EUHgP9^U9)9{U}@*#<@aSB?3wEefWDOvC@!9J zNZ_OCeoB)0!f3acEQjB6ICywL?>**++ z)sVZN8R)50*x>tYc88T*nNodBqcDqGwm7x=M9KNq#GFEKu(7swkkV=;Ows3dv39Kq z?Yf$pusdx`ru;<7(b7G`(CX-&^t-(4rB1gnP%svYE)@3{mtHki@?N87e*@MDRH@x6;}v zw-y0tO|dU1$oCJr5Pj+N#4YUAqPK5wR6hqA1OxPjFdim_#u=}u2^EaXyyS;e#JY!W zni-k4a*T?8OAF2nX&Ru%S#2$PjXGS`JYcGVlssSu7%pGL$&_qou6cQ@=^4#kvv9ip ze9ZkSBTILyij3A|G;atY24qO(wq+cz*1N9|>--(1HqFZwI}`ACYy4%a-!JS2iPWIJ zCwLRAd?m<90S2aUb?X7gkUaiUC4Pm$<+&`3!FP*OQ5(J9PSq^tS5?imbh7hU~Mlw7z%bTtM_)H(zX;&_3U*=i+i9w;u4`*WB)es`URSFT0OXg1_A-`$0szvZqvq#V2sPY? zov`$OP>s!6stPMc@`=MT5-fQM_oWB|kKb$;D2pnwZ|vJ^-Cul&K^wpMoBfmje(&pL zEBFXZLTc`57iEjUAZfZa`rD`2+*G-#(QvtqZB2SDkLDEJ^kO6G;US)@9<#vEtZm|R zKVT^AUjFgkv|GfmqCJZ}rFznopx&c>dO*10c6JoB;j}{m%?-9e3-|UQ-7ojR)&t3G`+X>!kI3-;nx4N^4XVS?Vj6z?mW$x_| zsnouQc;?JS=HWb4+joExdW$ICQ9psFu&cAP%NrHbo2P@9%6<*!@hndY{zx+U4Y2*)0_!gL!tZpJ>)R22xZ15nU&ghG3?9eW%-}J zkIe?f9Oqwzjd?WtIg~y&>Wo;fR)Mz9ra)kjB!Zk=7RdOzvj|ZVhE9nY8nFj);XyYR zLz3E>W**Qq`T6;ule2#Ih+Iq>@$9&_j_*WPduC_dlkaNwQup|=_1SL|njMBH(zt{} z!Ta~Q;lj~boJuLNNYk9ZoGZSg5c6&yvJBL=@%|S)1#SG}hvGp|Mhs-s3Pnv=lZNxI0`&7)A4NZDw=9OUHfR@Q96y>_dAV1`P6`$ zxK`x7c2)Hu28>LYSSG7*q_}|G&+d2<7>e4)XLW2=&{f@3q-4$F^fxbMojg9L%Kh7R z;Y*y!o>PTYfwsBIAyU|Wz52x4y!8tS5cYx2-2;>Mda-qH{Eqg9wsw!Y`uO$esW(6& zvGG68S;~E}P!Crgd>PAma|tu~OX!o!|DoOg#Q{ZQR^Ct(sOCXc%^QMR`9P0-Gb>5c z`eo>`;p1pbv^InHuCa0WtvCich!u=ILFi1}@{BL$6NF6eOqRTnjDWvXe3*9`y2;HTvFSUzgj%1IR50^rN|-+9i`%0(5z7<54eZ~NBN91AA?qC ziI;ONCf^j(xKg@k>TEKbmq#_)1TXSrpWUqW%BMOG*Q4zFo^S2w- zhcHOjO;wQLK6JsXfQj2geN}-3x7zMs%?(l>>WUriafeVoerT2`8d|Qj&Nbu-8!H^! zj}RJ>QAJuN50NI`jGtu=iLCv3PShmfBd~lCY+}=V5WcoLlOIc*#_FL41NGn?8b^&h z)<}ESpv;>(vz+f8ys16EIyh^H6B0XxlpI}$)bDy2ck3EQz*>Rk8Fm4OOw-7#wGo&Z zi^CH?p#MdUcY8fQ^}(B6Zj62K9AcOjM<&Q!?T%06b$~ULq2%-zRcwhRYHdKb-Z-~s zWxCeqp)68?_#1@pL0UHey)hbgzfeC;Rbl9tk7=t@3$BlA@=*d7GMa1qZp?F{ci9ru zZ~XnyJ|zaY{U`n6{keeWj7FLIX{8{$AKo@Sqe91>qx=1ebM@aWtz@=5T=3N|N))y! z!ZVK6DlTqBjxzq(SWKoP-QUjx0$I9`0)v2wxRhxyay5tIGu~9GlRX?nA>J?c& zC9dMx8;a8Am1tb39G6Ze9?z0reH!5ZnN42--zkUflP;+anssAw9sZBT;va|s|FGl# d+h5-fDoJvv<|`z}A!5>ElGB_uw#hwg_!AbiFs zeGCM$iw%M7P~E!|MDED)D}kq7Ub^PG5C}bm_qW?_FqiN^Vay?ra2W{X=3NM64TNrf zfj~l3Ads0$5D4M{1ajnRe#1pAkZ7{Tjsr^~jy#e0 z1kSy~-PA}Q61Q6n1t$BhqU?hpkb|w;&mFG<$}fW;Pq4AM0nZ1X<9lRJRn9jbf-{8y@?8~b#6gh7%B-QtBo@+X5>LqFHm4lZ_w?D16wH3g}fb4dsc3^Ds7xC5W z4EKF2gWA?ROu!2N=22&GRDPn?OQh@WcgW2kjOpzG*;xq#0P1C)Wci9YWddbGDvsdQ6HTmpU!HC)L3}>j1=V zuF3;wj69U}k{WPZB4HNe80mOi8J49`${d@@Bm`PrAv=A(pYid?`jt) zBViObI4Oqx>=dPlK_?kTmd$ccUczBof!0^K-_fHi?gzDWsDr2xpdSiQQg0nI=A-h7 z`QAPkXi*luVla!ht(b2rSP;EBi_!D-Kqb9Hzhk{V?~3tloR2TS@S?r_JM099DG`W* z#+SZ4pLj>+8{I!H305YZfd6&Q(?WJPKf>Ixa=97CG*QwlVtjNrx0@qC&weolW?srq z92#*kLo6%ViU_`sEHwwb{kF!rM?`NongVS;Gll4A17IbN?^V+=-@iNzEXra}FpStS)4v`j z5%;rhVnw z@lnoB)u%Vn$r*m!KN%I#2GCnNvna%H`}?pMoxCUiJ)UTpw?#4ZDj*rIgkDGA<~&8ik+X+=!<*MJjnDl~zH73c ztbIc#v(_aUd2GX6XJhz<2)V)F&=gV(ClUomMraN$1&@=i=W#mfGAV}MO>MczZ>8+3 zc@dPC-c9Yf@8{@j%RJaN^D;Miu91BuSkyRAap0)`QA%GKJ{#Jqan35~?VdPzQy3cK z@eXHOp~^W=CrkCBfdeBn6x>8qc`*26mOOphB8(RKkOqhS!Fbpn8+?&8 zXyae#KaIhugd>0E0~s3O_TbJnc+tPv-(4<}xe>_n1xugwyf;X2kbM#+&nUD?V#z4L z4yH>m4r;$_tW3kKbKiM^nmQ}|W1Q*I^WzkyDC8b$YwQ$jdg2wXF}*%J#qXO194#7B z5gmrreP)z`e3uF^)=f&j_((t4My%-3 zR3Lv_;8Ix-w^`oDvtFP32WUwcMC(U)f4MUY_ANm#pNp8&UouKW)+xgO=vAwG`ux%j z#GNvs+wXKdc1SZ!#bN2W8%01mp({RMuRd_qs3I^|)U*8w@dUh1X+X25sAhs%kP3A& zhx4$VU{n_0A^d|T_TE$v&yWV5V*Vf#I6A1Fh8~k#```mw`8`9R`-}Ned}Ku`Yu6$C zBN$j?s3w;>K;Vq>@|E?J(6+aO?=9fzhMl)&QcbvBq`o*U9s0b87Kgl%2J8Vcg!_1i zm?V}QY`c&gj2dwWlNVI6WzI=C<(8F53pmG|3ITk@W0&s?IqPodr&>Znit+EzHexF z>A#?YQbVn;FxcG~HiWWjg+0ng*@0Osr>Q_OcfL``el!>?@qbX3AZ27_zG`Q^t=6@` zNI^9+giW?5(^B|H9cGP{+omYwWIs7rMhyF*D@7pDr)z(yB>X&ZJo6uQq{1Jn*V+m# zm@V82&bJelWM^ix?FEOR(7;aMT3FeC{4;t<%>^G6-yRg)25xU(1VVR=lPt|Fv6}xH z`9b&zusHI+is#3$FO^$cIS6J5TUn3>PmL}>DdvvYU@g+mM~tdl>`QGmFMLpy{Qi<~ z63*2AyWmrS??mi>O_hsQ&bY4GreXbQIGe4h}OCfN|Jq?}&IRd)`DUytE zdjWulWVl3!QkqxG4?bs3J%IM{T-y4`WXB;Pp7*w2Lp(ig1n~ds{qoI1JHtNY7Na9t zN4&StSu71!-CHataLQt@G{o-t^&`fT_mmtQ#EM}xof8sWo^fo*Gbm+almFB#FQyTJ zX*^jwckuO&XZo1+Nn(~oUNWX}NlWSsc}-uOoX!ahdB;mB4IBK_lC3jej7KVsO;e&; z657ryZ^7ahb#zcWDq4ssZbGlU3@VOvtxO2(ZoXqRKAqI^Z>wE@c*E(byQ})iY>vu+ zSB1rr+abzS{C$Ip_V+-@uP(_WHVT_fG~3uw`(YMtJ+MG$(bK1RPWjE2w)pa<()c>w zZpJn;@BnhGBMWKI!|hsG3sjX9Zn>;?-yxoYw89tjx1yB99b`+{hc`^^jLC>zFNGG4 zys{c`e?8YABwNmvUfqBaX`(GpQlJajd~-Q7Y6G%sD*0??V_8d~skx~yJ&}>t*&S0H z^eN>`sm#`EAKw$?2gVhp*HIUg;CM|v<#uZ#1=$ySi$qSAcOv8-^`bnrmV)EE9~%G* z#y`Y=`7zO__+uwCg<^%SQv5|{e)-bzC(S!Dc5MNjsVJv!L~Gl#m) z;5kQc;Z1>wn8|B%FI)!uxDVp(9xt5}V400qH#yu>crk@&FJPATy-m{0P`2$qMYBqO zdxx7nCSR{Qlsu*8n_zu}eNftr{lzp@eP#Xis`5v2YObAPPN>`%ln&kTW^jQnbm8EH^luv_BjhVeFGsZ8j#TN5)Upp_N0khPOEX+Dn%CwtV z?iwAoKOn$r$GlR%a%|lt6l+A$wj5p*qw=M0itN+Q-^}`{_1Y`o*xt!&&+?_)ub!>i z%?!B_L1l|{O;09zRICiS;X@r>syBY7`CX=*%}_qlKdxN#sy{lLo!<%iewAvK*Kg29 zwb|1-f!}Ykm7AiDt5y~Z^Z2VW(7?gcuFNH(=@FdEb zia8D29yrQ+q`|3l2Z-!Z<7^mLXM1T{ECA&xE3fm%Q-+M5*DTy6X=&D<5~01Z>Qs|` zsUae}ruEuXv z`%W*&t39mB?{E)PSP*a27q3r6%6}%*X}u6XV~WK!t{F=g}BX5DW7FD!4XU<IlDfUl zx%haZ=BQXiiTNUa7BhQYx?D%q->Jf{&01W|IKi#@mnRc!?~SgUe)Tfm=A5UR&GK}7 z8s(*LkNH&@=PFXmc4Jqjt>SQZhzxPdU#u>xm-m=l>yZj-NrIS3vop~4w$3kneR5TG z4llKnF3+gB8s7r-pIL#IiXfC3$K4%T9&{Er>HGsp;C(m62c+vZBk_RphPPY@j~bj1?xy zFcVX_DBf%xOPJEVot0#DE`zo|e9@z>hwHWK<4|Bz3oZ~oog<|RZUmt4u2uYHQ8U1KMRA3C8~@7sNx@@r`77K3oAqpx%o|6XFB7jEAdmwfQ@7oQ7$gcJue}u@MvSGu>7Kv z*W|;`Ijru*UIT5R>>K60VVxSj^NuYf51r`;Gdw+Go^$z|_SG6AEfS2#u_!{oTRVC# zduAU6p259yzW66J?*qEQ$#`odJ9v~BHL0)LpF8V1Xu~P!oK8B1O1crRO8Hw&)MHPW z6IrX=9-%ZMdgpfW-wE>30$xAr`aVlj&W8T*Z&6jsqDIqihb>R7>Sj_gu-dm5fmMK- zV;#xdSKIQ7xw7P1|Lfyg^t1DC?6-U&^hknVN3q_Wxo;O?UxBM1hb{=YL zICI6t>6$fo2|e>J$|qXGu+IGgGe6#~1~nA1H8Y&Y@2*Cf0dZ;lp29rZWSwZsr!MCz zrH67F6wX|){{1QJljTNdqN|1Ia^>BL>Gzsknws_2l`@WQ&tpVDZS|aOyy`79DR|t) zHTlY8pXLB8r7zQheekf=m_go#g3?+=B)=Hv#0$gq<=sGQeBIZN?eX{85d%<6FJ)9_ zCI?UF1lG@{B=R1as8{g6xil0ijxTjZS{`i6tv|TAxcdC*%g&Za5#nG6!h&`xa{2At zsg*0eI>Bb*0mR_csOUv|7vsjYfN72Rz$>rd-@iHX#3uWQ&!sE(&-)^&9%p?PP_Qwh zN0iXm0+7)8L--)O_J#b|P4Gw=&>FpXK#Wz$k##1G_eP4?W-4v2e0b?Oc6WYKdnhK^ zCtxnUs=kaE`C`svjk&H@&q5NS{-3|-v8y_g9+_jycYj_2ozlSucEOk3f;|x)*F3=! z259}N I3zu&H2lXLQzyJUM literal 0 HcmV?d00001 diff --git a/wyk/polynomial_logistic.tsv b/wyk/polynomial_logistic.tsv new file mode 100644 index 0000000..87337f2 --- /dev/null +++ b/wyk/polynomial_logistic.tsv @@ -0,0 +1,100 @@ +1 0.25777005758108174 0.601012316037165 +1 0.3659669567447452 -0.11214686303429633 +0 0.49453050141627375 0.47110655546911206 +0 0.7029060372914113 -0.9225798301680093 +0 0.46658862037642423 -0.6226973935055724 +0 0.8793946243263941 -0.11408014657778076 +0 -0.3311850002119068 0.8444766749977881 +0 -0.5435170087333634 0.8851383010436487 +0 0.9197924083397226 0.41607011737177735 +0 0.28011742147804797 0.6143115673056148 +0 0.9475436344725683 -0.7830731144606005 +0 0.4904989452188586 0.649356142549592 +0 -0.865983500565505 0.9896361556274065 +0 -0.8579184997717257 0.3062253122060574 +0 0.08082005095746103 -0.7736760810964189 +0 -0.3363842450225085 -0.8802992880290186 +0 0.4748472924067402 0.9756949850919965 +0 -0.7956979203895616 0.8751067723304518 +1 0.06752895667287606 -0.7683056187589332 +0 -0.5825898275446799 0.8068359661366173 +1 0.1109238791315652 -0.2034825016864903 +0 0.5011542085506828 0.9366868642789181 +0 0.2011359606302785 0.4800561245801245 +1 -0.38620580274071115 0.4003933803256208 +1 -0.1722113915778094 0.3926707935387965 +0 0.6575404624823169 -0.7070032890943085 +1 -0.2832309098070882 0.034184675674787446 +1 -0.16828017341376333 -0.1628482245819587 +0 -0.6552618226108893 -0.3159705063754401 +0 -0.6466772083696701 -0.07116372625398881 +0 0.848711325640519 0.2132898335742659 +1 -0.35490315474701606 -0.0025105634256454845 +0 -0.36568446532837817 0.5637325774329354 +0 -0.5089179414092766 0.8086671779253405 +0 0.9609295951994559 -0.12114542304082354 +0 0.055563338045806265 0.8532855304613407 +0 -0.8937129542754998 -0.02555660184206876 +0 0.40678784672410284 -0.5480665560665205 +0 -0.7683896050204841 0.9475293644451854 +0 -0.515467982993429 -0.5389177617277066 +0 0.9693903475176826 -0.9765032993967369 +0 -0.5476549714934908 -0.018838768427513974 +0 0.5262277827151787 -0.9936327305281174 +1 0.9394838829593151 0.9962891110157359 +0 -0.935709119652979 -0.6940925482964921 +0 0.6161569745665239 -0.044448545050667976 +0 -0.08521587367561922 0.9636255303204684 +0 0.9073344675416231 -0.08813265618067079 +1 -0.1563237189794715 0.05022859605451302 +0 -0.9785642881644829 -0.5076719844587916 +0 -0.5494648865481802 -0.6044852696776528 +0 -0.7170122682018529 -0.6250685449461151 +1 0.5333872877810009 0.1395189003073396 +0 -0.49270328980187905 0.9081426529064955 +1 0.07777642690144848 -0.44188199856981347 +0 0.8328452661100116 0.5508441451500428 +1 -0.33275827507477573 -0.15434344174028314 +0 -0.9057550401714867 0.6324599729071743 +0 -0.8476574433184823 0.5739140088331203 +0 -0.37393930555231103 0.7361874446899226 +1 0.6610910543790163 0.0036185958785315275 +0 0.49147748571126004 -0.6155167984371757 +0 0.31992462553488177 -0.38253832622755657 +0 0.7398386519468336 -0.915886088774648 +0 0.5915392280694003 0.011422405850611383 +0 -0.5818860867200502 -0.44086037005029377 +0 -0.9066322824076023 0.21754010215910524 +1 0.12243932470792318 -0.3830697406526009 +0 0.40607941790742297 0.5626829623336307 +1 -0.1210920179663808 -0.20552144405177608 +0 0.48099006522554233 0.9583656149315158 +0 -0.059491720260914205 0.6161097510891897 +1 -0.053220979060695006 0.07562497263502688 +0 -0.8742304482942296 -0.13488952315510616 +0 0.7362712712103594 0.6087347685508093 +0 0.025549937023763736 -0.6202087182389777 +0 0.6755333538371804 0.7047713746899604 +0 -0.3954771867034055 0.3567082570178153 +1 0.24896928809009156 -0.17106278785061302 +0 0.6133735778535989 -0.6297261231852487 +1 -0.35955189872833593 -0.2086164112593747 +0 0.646544898896497 0.8858921579510579 +0 0.6459228334265068 -0.9141274779126995 +0 -0.5279127041052518 -0.11119649758918437 +0 -0.47141090620857784 -0.29849889702571786 +1 0.1901970467567704 -0.5049996808415897 +0 -0.5497623652380574 -0.49032403671408553 +0 -0.5759454285366339 0.445122514716527 +0 -0.7800687910859982 -0.4823078816937112 +0 0.39722150362989095 0.5827352140491311 +1 0.018540458464545218 -0.20805328372207677 +0 -0.14419638252986933 -0.8679481460173017 +1 -0.15012196110925857 0.5474017473230433 +1 -0.11028545705088533 0.5371497474265077 +0 -0.46577855502057375 -0.9226883886539352 +0 0.4843595022265692 0.47692504895620713 +0 0.4330264545403766 -0.40096944878062857 +0 -0.7401024435876022 0.758623363044544 +0 0.20470935356917574 -0.7551473328272353 +0 0.1877078820888327 -0.3377139504156679