{ "cells": [ { "cell_type": "markdown", "id": "7ba05a39", "metadata": {}, "source": [ "# Simulationsstudie: Diebstahlerkennung eines Autos in Echtzeit\n", "\n", "**Name:** Yann Ahlgrim\n", "**MatNr.:** 818296 \n", "\n", "In dieser Simulationsstudie wird ein Modell entwickelt, das anhand von Fahrverhaltensdaten erkennt, ob ein anderer Fahrer als üblich am Steuer sitzt. Ziel ist es, eine Wahrscheinlichkeit für einen Fahrerwechsel zu schätzen und bei hoher Wahrscheinlichkeit eine Diebstahlwarnung auszugeben. Die Studie umfasst die Generierung einer synthetischen Grundgesamtheit, die Simulation der Data Scientist Perspektive und die Analyse der Modellgüte." ] }, { "cell_type": "markdown", "id": "a5fe9381", "metadata": {}, "source": [ "### Datengrundlage\n", "\n", "#### Erklärende Variablen:\n", "\n", "1. **Durchschnittsgeschwindigkeit (metrisch):** \n", " Die Werte verteilen sich natürlicherweise ungefähr normal um ca. 47 km/h (29 mph) mit großer Streuung. Aggressive Fahrer tendieren zu höheren Durchschnittsgeschwindigkeiten. Diese Variable ist erklärend, da ein anderer Fahrer oft abweichende Geschwindigkeitsprofile aufweist. \n", " → Die Verteilung basiert auf: [NHTSA 100-Car Naturalistic Driving Study](https://www.nhtsa.gov/sites/nhtsa.gov/files/100carmain.pdf)\n", "\n", "2. **Schaltverhalten (ordinal):** \n", " Charakteristisches Schaltmuster bei Handschaltgetrieben, insbesondere der Drehzahlbereich beim Hochschalten. Fahrer unterscheiden sich deutlich: \n", " - *frueh* (ökonomisches Fahren), \n", " - *normal*, \n", " - *spaet* (sportliches/aggressives Fahren). \n", " Diese Variable dürfte prädiktiv sein, da Schaltgewohnheiten fahrerspezifisch sind. Studien zeigen, dass sie zur Fahreridentifikation genutzt werden können. \n", " → Quelle: [Driver Identification Based on Gear Shift Events and Attention-Based Bidirectional Long Short-Term Memory for Manual Transmission System)](https://ieeexplore.ieee.org/document/10034086)\n", "\n", "3. **Harte Bremsmanöver (metrisch):** \n", " Anzahl starker Bremsvorgänge mit hoher Verzögerung (>0,3 g). Modellierung z.B. als Poisson-verteilte Zufallsvariable mit geringem Mittelwert (wenige Ereignisse pro 100 km). Harte Bremsmanöver korrelieren mit aggressiver Fahrweise und sind prädiktiv für Fahrerwechsel. \n", " → Quelle: [Tesla Safety Score Definition](https://www.findmyelectric.com/blog/tesla-safety-score-beta-explained)\n", "\n", "4. **Geschwindigkeitsüberschreitungen (ordinal, 3 Kategorien):** \n", " haeufigkeit bzw. Ausmaß, mit dem Tempolimits überschritten werden. Kategorisierung z.B. in: \n", " - *selten*, \n", " - *manchmal*, \n", " - *haeufig* zu schnell. \n", " Diese Variable ist prädiktiv, da ein fremder Fahrer oft ein anderes Risikoverhalten beim Speeding zeigt.\n", " Laut einer AAA-Verkehrssicherheitsstudie geben nahezu 50 % der Fahrer an, auf Autobahnen im letzten Monat ~15 mph (~24 km/h) über dem Tempolimit gefahren zu sein.\n", " → Quelle: [87 Percent of Drivers Engage in Unsafe Behaviors While Behind the Wheel](https://newsroom.aaa.com/2016/02/87-percent-of-drivers-engage-in-unsafe-behaviors-while-behind-the-wheel/)\n", "\n", "---\n", "\n", "#### Nicht erklärende Variablen:\n", "\n", "\n", "5. **Wetterbedingungen (nominal, 3 Kategorien):** \n", " - *trocken* (~70–75 %) \n", " - *nass* (~20–25 %) \n", " - *winterlich* (<5 %) \n", " → Modelliert als Multinomial. Kontextvariable. \n", "\n", "6. **Fahrstrecke (metrisch):** \n", " Länge der Fahrt (z.B. lognormalverteilt um 16 km). Kontextvariable, nicht direkt erklärend. \n", " → Quelle: [Mobilität in Deutschland 2017 – Ergebnisbericht](https://www.bmv.de/SharedDocs/DE/Anlage/G/mid-ergebnisbericht.pdf)\n", "\n", " \n", "7. **Straßentyp (nominal, 3 Kategorien):** \n", " - *Autobahn* (~30–33 %) \n", " - *Außerorts* (~43 %) \n", " - *Innerorts* (~24–27 %) \n", " → Modelliert als Multinomialverteilung. Kontextvariable ohne direkte Prädiktionswirkung. \n", " → Quelle: [Klimaschutzinstrumente im Verkehr](https://openumwelt.de/server/api/core/bitstreams/07bd23f9-ff0a-41e5-b89b-8d7baf0a5c36/content)\n", "\n", "8. **Wochentag (nominal, 2–3 Kategorien):** \n", " Z.B. *Werktag* vs *Wochenende* oder *Mo–Fr*, *Sa*, *So*. Modellierung als kategorische Variable. Kontextvariable. \n", " → Quelle: [Mobilität in Deutschland 2017 – Ergebnisbericht](https://www.bmv.de/SharedDocs/DE/Anlage/G/mid-ergebnisbericht.pdf)\n" ] }, { "cell_type": "markdown", "id": "1468207b", "metadata": {}, "source": [ "### Bibliotheken Imports" ] }, { "cell_type": "code", "execution_count": 207, "id": "97ba29a9", "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "import seaborn as sns\n", "import statsmodels.api as sm\n", "from statsmodels.stats.outliers_influence import variance_inflation_factor\n", "\n", "np.random.seed(11)\n", "N = 1_000_000" ] }, { "cell_type": "markdown", "id": "27947656", "metadata": {}, "source": [ "### Verteilungen der Variablen" ] }, { "cell_type": "code", "execution_count": 208, "id": "61247da5", "metadata": {}, "outputs": [], "source": [ "# 1. Durchschnittsgeschwindigkeit (metrisch, normalverteilt)\n", "avg_speed = np.clip(np.random.normal(loc=47, scale=10, size=N), 10, 130)\n", "\n", "# 2. Schaltverhalten (ordinal, 3 Kategorien)\n", "shift_behavior = np.random.choice(['frueh', 'normal', 'spaet'], size=N, p=[0.4, 0.4, 0.2])\n", "\n", "# 3. Harte Bremsmanöver (metrisch, Poisson)\n", "hard_brakes = np.random.poisson(lam=2, size=N)\n", "\n", "# 4. Geschwindigkeitsüberschreitungen (ordinal, 3 Kategorien) – Abhängigkeit von avg_speed\n", "def softmax(x):\n", " e_x = np.exp(x - np.max(x, axis=1, keepdims=True))\n", " return e_x / e_x.sum(axis=1, keepdims=True)\n", "\n", "speed_scaled = (avg_speed - avg_speed.min()) / (avg_speed.max() - avg_speed.min())\n", "strength = 0.18\n", "logits = np.zeros((N, 3))\n", "logits[:, 0] = 1 - strength * speed_scaled # selten\n", "logits[:, 1] = 1 # manchmal\n", "logits[:, 2] = 1 + strength * speed_scaled # haeufig\n", "probs = softmax(logits)\n", "speeding = [np.random.choice(['selten', 'manchmal', 'haeufig'], p=p) for p in probs]\n", "\n", "# 5. Wetterbedingungen (nominal, Kontext)\n", "weather = np.random.choice(['trocken', 'nass', 'winterlich'], size=N, p=[0.75, 0.2, 0.05])\n", "\n", "# 6. Fahrstrecke (metrisch, lognormal)\n", "mu, sigma = np.log(16), 0.7\n", "trip_distance = np.random.lognormal(mean=mu, sigma=sigma, size=N)\n", "\n", "# 7. Straßentyp (nominal, Kontext) – Abhängigkeit von trip_distance mit Softmax-Funktion\n", "dist_scaled = (trip_distance - trip_distance.min()) / (trip_distance.max() - trip_distance.min())\n", "road_strength = 0.18\n", "road_logits = np.zeros((N, 3))\n", "road_logits[:, 0] = 1 - road_strength * dist_scaled # Innerorts\n", "road_logits[:, 1] = 1 # Außerorts\n", "road_logits[:, 2] = 1 + road_strength * dist_scaled # Autobahn\n", "road_probs = softmax(road_logits)\n", "road_type = [np.random.choice(['Innerorts', 'Außerorts', 'Autobahn'], p=p) for p in road_probs]\n", "\n", "# 8. Wochentag (nominal, Kontext)\n", "weekday = np.random.choice(['Mo-Fr', 'Sa', 'So'], size=N, p=[0.7, 0.15, 0.15])" ] }, { "cell_type": "markdown", "id": "defebcc1", "metadata": {}, "source": [ "### Zusammenführen der Daten in ein DataFrame" ] }, { "cell_type": "code", "execution_count": 209, "id": "f8e0efb0", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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avg_speedshift_behaviorhard_brakesspeedingweathertrip_distanceroad_typeweekday
064.494547frueh2manchmaltrocken40.599949InnerortsMo-Fr
144.139270frueh3haeufigtrocken15.881471AutobahnMo-Fr
242.154349spaet2seltentrocken8.114740AutobahnMo-Fr
320.466814normal5haeufigtrocken7.643579InnerortsMo-Fr
446.917154spaet2seltentrocken9.675677AußerortsMo-Fr
\n", "
" ], "text/plain": [ " avg_speed shift_behavior hard_brakes speeding weather trip_distance \\\n", "0 64.494547 frueh 2 manchmal trocken 40.599949 \n", "1 44.139270 frueh 3 haeufig trocken 15.881471 \n", "2 42.154349 spaet 2 selten trocken 8.114740 \n", "3 20.466814 normal 5 haeufig trocken 7.643579 \n", "4 46.917154 spaet 2 selten trocken 9.675677 \n", "\n", " road_type weekday \n", "0 Innerorts Mo-Fr \n", "1 Autobahn Mo-Fr \n", "2 Autobahn Mo-Fr \n", "3 Innerorts Mo-Fr \n", "4 Außerorts Mo-Fr " ] }, "execution_count": 209, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df = pd.DataFrame({\n", " 'avg_speed': avg_speed,\n", " 'shift_behavior': shift_behavior,\n", " 'hard_brakes': hard_brakes,\n", " 'speeding': speeding,\n", " 'weather': weather,\n", " 'trip_distance': trip_distance,\n", " 'road_type': road_type,\n", " 'weekday': weekday\n", "})\n", "\n", "df.head()\n" ] }, { "cell_type": "markdown", "id": "f06e7c4d", "metadata": {}, "source": [ "### VIF der Abhängigkeiten prüfen (<5)" ] }, { "cell_type": "code", "execution_count": 210, "id": "6bfb199a", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Variance Inflation Factor (VIF) für ausgewählte Variabeln:\n", " features VIF Factor\n", "0 avg_speed 2.570716\n", "1 speeding_manchmal 1.819868\n", "2 speeding_selten 1.750848\n" ] } ], "source": [ "vif = pd.DataFrame()\n", "columns = ['avg_speed', 'speeding']\n", "vif_df = pd.get_dummies(df[columns], drop_first=True)\n", "vif_df = vif_df.astype(float)\n", "vif['features'] = vif_df.columns\n", "vif['VIF Factor'] = [variance_inflation_factor(vif_df.values, i) for i in range(vif_df.shape[1])]\n", "vif = vif.sort_values('VIF Factor', ascending=False).reset_index(drop=True)\n", "print(\"\\nVariance Inflation Factor (VIF) für ausgewählte Variabeln:\")\n", "print(vif)" ] }, { "cell_type": "code", "execution_count": 211, "id": "1d3df64a", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Variance Inflation Factor (VIF) für ausgewählte Variabeln:\n", " features VIF Factor\n", "0 trip_distance 1.677148\n", "1 road_type_Außerorts 1.342378\n", "2 road_type_Innerorts 1.334770\n" ] } ], "source": [ "vif = pd.DataFrame()\n", "columns = ['road_type', 'trip_distance']\n", "vif_df = pd.get_dummies(df[columns], drop_first=True)\n", "vif_df = vif_df.astype(float)\n", "vif['features'] = vif_df.columns\n", "vif['VIF Factor'] = [variance_inflation_factor(vif_df.values, i) for i in range(vif_df.shape[1])]\n", "vif = vif.sort_values('VIF Factor', ascending=False).reset_index(drop=True)\n", "print(\"\\nVariance Inflation Factor (VIF) für ausgewählte Variabeln:\")\n", "print(vif)" ] }, { "cell_type": "code", "execution_count": 212, "id": "49045ee5", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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avg_speedshift_behaviorhard_brakesspeedingweathertrip_distanceroad_typeweekday
064.494547frueh2manchmaltrocken40.599949InnerortsMo-Fr
144.139270frueh3haeufigtrocken15.881471AutobahnMo-Fr
242.154349spaet2seltentrocken8.114740AutobahnMo-Fr
320.466814normal5haeufigtrocken7.643579InnerortsMo-Fr
446.917154spaet2seltentrocken9.675677AußerortsMo-Fr
\n", "
" ], "text/plain": [ " avg_speed shift_behavior hard_brakes speeding weather trip_distance \\\n", "0 64.494547 frueh 2 manchmal trocken 40.599949 \n", "1 44.139270 frueh 3 haeufig trocken 15.881471 \n", "2 42.154349 spaet 2 selten trocken 8.114740 \n", "3 20.466814 normal 5 haeufig trocken 7.643579 \n", "4 46.917154 spaet 2 selten trocken 9.675677 \n", "\n", " road_type weekday \n", "0 Innerorts Mo-Fr \n", "1 Autobahn Mo-Fr \n", "2 Autobahn Mo-Fr \n", "3 Innerorts Mo-Fr \n", "4 Außerorts Mo-Fr " ] }, "execution_count": 212, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.head()" ] }, { "cell_type": "markdown", "id": "d27de9c5", "metadata": {}, "source": [ "### Dummies erzeugen" ] }, { "cell_type": "code", "execution_count": 213, "id": "4ad287b1", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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constavg_speedhard_brakestrip_distanceshift_fruehshift_normalshift_spaetspeeding_haeufigspeeding_manchmalspeeding_seltenweather_nassweather_trockenweather_winterlichroad_Autobahnroad_Außerortsroad_Innerortsweekday_Mo-Frweekday_Saweekday_So
01.064.4945472.040.5999491.00.00.00.01.00.00.01.00.00.00.01.01.00.00.0
11.044.1392703.015.8814711.00.00.01.00.00.00.01.00.01.00.00.01.00.00.0
21.042.1543492.08.1147400.00.01.00.00.01.00.01.00.01.00.00.01.00.00.0
31.020.4668145.07.6435790.01.00.01.00.00.00.01.00.00.00.01.01.00.00.0
41.046.9171542.09.6756770.00.01.00.00.01.00.01.00.00.01.00.01.00.00.0
\n", "
" ], "text/plain": [ " const avg_speed hard_brakes trip_distance shift_frueh shift_normal \\\n", "0 1.0 64.494547 2.0 40.599949 1.0 0.0 \n", "1 1.0 44.139270 3.0 15.881471 1.0 0.0 \n", "2 1.0 42.154349 2.0 8.114740 0.0 0.0 \n", "3 1.0 20.466814 5.0 7.643579 0.0 1.0 \n", "4 1.0 46.917154 2.0 9.675677 0.0 0.0 \n", "\n", " shift_spaet speeding_haeufig speeding_manchmal speeding_selten \\\n", "0 0.0 0.0 1.0 0.0 \n", "1 0.0 1.0 0.0 0.0 \n", "2 1.0 0.0 0.0 1.0 \n", "3 0.0 1.0 0.0 0.0 \n", "4 1.0 0.0 0.0 1.0 \n", "\n", " weather_nass weather_trocken weather_winterlich road_Autobahn \\\n", "0 0.0 1.0 0.0 0.0 \n", "1 0.0 1.0 0.0 1.0 \n", "2 0.0 1.0 0.0 1.0 \n", "3 0.0 1.0 0.0 0.0 \n", "4 0.0 1.0 0.0 0.0 \n", "\n", " road_Außerorts road_Innerorts weekday_Mo-Fr weekday_Sa weekday_So \n", "0 0.0 1.0 1.0 0.0 0.0 \n", "1 0.0 0.0 1.0 0.0 0.0 \n", "2 0.0 0.0 1.0 0.0 0.0 \n", "3 0.0 1.0 1.0 0.0 0.0 \n", "4 1.0 0.0 1.0 0.0 0.0 " ] }, "execution_count": 213, "metadata": {}, "output_type": "execute_result" } ], "source": [ "shift_dummies = pd.get_dummies(shift_behavior, prefix='shift')\n", "speeding_dummies = pd.get_dummies(speeding, prefix='speeding')\n", "weather_dummies = pd.get_dummies(weather, prefix='weather')\n", "road_dummies = pd.get_dummies(road_type, prefix='road')\n", "weekday_dummies = pd.get_dummies(weekday, prefix='weekday')\n", "\n", "X = pd.DataFrame({\n", " 'const': np.ones(N), # fuer konstante\n", " 'avg_speed': avg_speed,\n", " 'hard_brakes': hard_brakes,\n", " 'trip_distance': trip_distance\n", "})\n", "X = pd.concat([X, shift_dummies, speeding_dummies, weather_dummies, road_dummies, weekday_dummies], axis=1)\n", "\n", "X = X.astype(float)\n", "\n", "X.head()" ] }, { "cell_type": "markdown", "id": "1f6ee727", "metadata": {}, "source": [ "### Zielvariable erzeugen" ] }, { "cell_type": "code", "execution_count": 214, "id": "75318d77", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Anzahl Diebstähle: 218290\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "betas = np.array([\n", " -18, # konstante\n", " 0.3, # avg_speed\n", " 0.6, # hard_brakes\n", " 0., # trip_distance\n", " -0.8, # shift_frueh\n", " -0.8, # shift_normal\n", " 1.5, # shift_spaet\n", " 1.5, # speeding_haeufig\n", " -0.8, # speeding_manchmal\n", " -0.8, # speeding_selten\n", " 0., # weather_nass\n", " 0., # weather_trocken\n", " 0., # weather_winterlich\n", " 0., # road_Autobahn\n", " 0., # road_Außerorts\n", " 0., # road_Innerorts\n", " 0., # weekday_Mo-Fr\n", " 0., # weekday_Sa\n", " 0. # weekday_So\n", "])\n", "\n", "# Sicherstellen, dass die Dimension passt\n", "X_model = X.iloc[:, :len(betas)]\n", "\n", "X_model = X_model.astype(float)\n", "rauschen = np.random.normal(0, 0.2, size=N)\n", "\n", "# Linearkombination + Rauschen\n", "lin_comb = X_model.values @ betas + rauschen\n", "\n", "# Logistische Funktion\n", "pi = 1 / (1 + np.exp(-lin_comb))\n", "\n", "# Zielvariable simulieren\n", "target = np.random.binomial(1, pi)\n", "\n", "print(\"Anzahl Diebstähle:\", np.sum(target))\n", "\n", "plt.figure(figsize=(10, 6))\n", "sns.countplot(x=target, palette='viridis')\n", "plt.title('Verteilung der Zielvariable (Diebstahl: ja/nein)')\n", "plt.xlabel('Diebstahl')\n", "plt.ylabel('Anzahl')\n", "plt.xticks([0, 1], ['Nein', 'Ja'])\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 215, "id": "76948d4a", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Mittelwert der pi-Werte: 0.2179\n", "Standardabweichung der pi-Werte: 0.3093\n" ] }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Verteilung der pi-Werte\n", "mean_pi = np.mean(pi)\n", "std_pi = np.std(pi)\n", "print(f\"Mittelwert der pi-Werte: {mean_pi:.4f}\")\n", "print(f\"Standardabweichung der pi-Werte: {std_pi:.4f}\")\n", "\n", "plt.figure(figsize=(10, 6))\n", "sns.histplot(pi, bins=50, kde=True, color='blue')\n", "plt.title('Verteilung der pi-Werte')\n", "plt.xlabel('pi-Werte')\n", "plt.ylabel('Häufigkeit')\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "825cc812", "metadata": {}, "source": [ "### Verteilungen der Variablen\n", "\n", "- **Durchschnittsgeschwindigkeit (`avg_speed`)**: normalverteilt mit Mittelwert 47 km/h und Standardabweichung 10, begrenzt auf den Bereich [10, 130].\n", "- **Schaltverhalten (`shift_behavior`)**: ordinal skaliert mit 3 Kategorien, gezogen aus einer Multinomialverteilung (Wahrscheinlichkeiten: 40% früh, 40% normal, 20% spät).\n", "- **Harte Bremsmanöver (`hard_brakes`)**: metrisch, modelliert mit einer Poisson-Verteilung (λ = 2).\n", "- **Geschwindigkeitsüberschreitungen (`speeding`)**: ordinal skaliert mit 3 Stufen, abhängig von `avg_speed` über eine Softmax-basierte Wahrscheinlichkeitsverteilung.\n", "- **Wetterbedingungen (`weather`)**: nominal skaliert, zufällig verteilt mit 75% trocken, 20% nass und 5% winterlich.\n", "- **Fahrstrecke (`trip_distance`)**: lognormal verteilt mit μ = ln(12) und σ = 0.7.\n", "- **Straßentyp (`road_type`)**: abhängig von `trip_distance`, mit kategorialer Softmax-Verteilung (Innerorts, Außerorts, Autobahn).\n", "- **Wochentag (`weekday`)**: nominal mit festgelegter Verteilung (70% Werktage, je 15% Samstag und Sonntag).\n", "\n", "### Modellierte Abhängigkeiten\n", "\n", "Die Variablen `speeding` und `road_type` wurden nicht rein zufällig erzeugt, sondern basieren auf skalierter Eingangsvariablen - `avg_speed` bzw. `trip_distance` - und einem gewichteten Softmax-Verfahren für realistischere Zusammenhänge.\n", "\n", "### Zielvariable und 𝑝ᵢ-Werte\n", "\n", "Die Zielvariable, die eine Diebstahlwahrscheinlichkeit beschreibt, wurde aus diesen Features modelliert. Die 𝑝ᵢ-Werte repräsentieren dabei individuelle Wahrscheinlichkeiten für Fahrerwechsel und wurden anhand von Beta-Verteilungen erzeugt.\n", "\n", "### Wahl und Begründung der Beta-Werte\n", "\n", "Die Beta-Gewichte wurden bewusst so gewählt, dass sie realistische Zusammenhänge zwischen den Merkmalen und dem Auftreten eines möglichen Diebstahls modellieren, ohne die Zielvariable künstlich zu verzerren. Das Ziel war ein realistischer, aber nicht übermäßig häufiger positiver Klassenanteil.\n", "\n", "- **Konstante (-18):** Sorgt für eine niedrige Grundwahrscheinlichkeit für Diebstahl, wenn keine auffälligen Merkmale vorliegen. Dadurch bleibt die Zielvariable realistisch balanciert.\n", "- **avg_speed (0.3):** Ein positiver Zusammenhang, da eine ungewöhnlich hohe Durchschnittsgeschwindigkeit auf einen anderen Fahrstil und damit auf einen möglichen Fahrerwechsel hindeuten kann.\n", "- **hard_brakes (0.6):** Ein deutlicher positiver Effekt, da häufige harte Bremsmanöver ein Indiz für einen ungewohnten oder riskanten Fahrstil sind, der auf einen Fahrerwechsel hindeuten kann.\n", "- **trip_distance (0):** Kein Einfluss, da die reine Fahrstrecke keine Aussage über den Fahrerwechsel zulässt.\n", "- **shift_frueh (-0.8), shift_normal (-0.8), shift_spaet (1.5):** Das Schaltverhalten ist ein starker Prädiktor für den Fahrer. Besonders „spät\" schalten wird mit einem hohen positiven Beta gewichtet, da es einen aggressiveren Fahrstil beschreibt. „Früh\" und „normal\" schalten erhalten einen negativen Einfluss, da sie auf einen defensiveren oder gewohnten Fahrstil hindeuten.\n", "- **speeding_selten (-0.8), speeding_manchmal (-0.8), speeding_haeufig (1.5):** Die Häufigkeit von Geschwindigkeitsüberschreitungen ist ein wichtiger Indikator für den Fahrstil. Besonders „häufig\" zu schnell fahren (1.5) ist ein starkes Signal für einen Fahrerwechsel, da dies ein sehr auffälliges Verhalten ist. „Selten\" und „manchmal\" werden negativ gewichtet, da sie auf einen defensiveren Fahrstil hindeuten.\n", "- **weather_nass, weather_trocken, weather_winterlich (je 0):** Wetterbedingungen haben keinen Einfluss auf die Wahrscheinlichkeit eines Fahrerwechsels, da sie unabhängig vom Fahrer sind.\n", "- **road_Außerorts, road_Autobahn, road_Innerorts (je 0):** Der Straßentyp ist nicht prädiktiv für einen Fahrerwechsel, da er nicht vom Fahrverhalten abhängt.\n", "- **weekday_Mo-Fr, weekday_Sa, weekday_So (je 0):** Der Wochentag hat keinen Einfluss auf die Wahrscheinlichkeit eines Fahrerwechsels.\n", "\n", "```visualisierung\n", "Die grafische Darstellung zeigt, dass rund 22 % der Fahrten als potenzielle Diebstähle klassifiziert wurden.\n", "```\n", "\n" ] }, { "cell_type": "markdown", "id": "adbc166b", "metadata": {}, "source": [ "## Simulation der Perspektive des Data Scientist" ] }, { "cell_type": "markdown", "id": "f8abd5f5", "metadata": {}, "source": [ "### Stichprobe entnehmen" ] }, { "cell_type": "code", "execution_count": 216, "id": "706ff5c6", "metadata": {}, "outputs": [], "source": [ "sample_size = 20_000\n", "sample_indices = np.random.choice(X.index, size=sample_size, replace=False)\n", "X_sample = X.loc[sample_indices]\n", "target_sample = target[sample_indices]" ] }, { "cell_type": "markdown", "id": "9b67610e", "metadata": {}, "source": [ "### Datenexploration und -vorverarbeitung\n", "\n", "Zunächst verschafft sich der Data Scientist einen Überblick über die Stichprobe, prüft die Verteilung der Zielvariable und der erklärenden Variablen, erkennt potenzielle Ausreißer und prüft auf fehlende Werte. Außerdem werden die Variablentypen für die Modellierung vorbereitet (z.B. One-Hot-Encoding für kategoriale Variablen)." ] }, { "cell_type": "code", "execution_count": 217, "id": "9f12d325", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Form der Stichprobe: (20000, 19)\n", "Anteil Zielvariable (Diebstahl):\n", "0 0.7829\n", "1 0.2171\n", "dtype: float64\n" ] }, { "data": { "text/html": [ "
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constavg_speedhard_brakestrip_distanceshift_fruehshift_normalshift_spaetspeeding_haeufigspeeding_manchmalspeeding_seltenweather_nassweather_trockenweather_winterlichroad_Autobahnroad_Außerortsroad_Innerortsweekday_Mo-Frweekday_Saweekday_So
count20000.020000.00000020000.00000020000.00000020000.00000020000.00000020000.00000020000.00000020000.00000020000.00000020000.00000020000.00000020000.00000020000.00000020000.00000020000.00000020000.00000020000.00000020000.000000
mean1.046.9554311.98730020.4008660.3967500.4051000.1981500.3654500.3283000.3062500.1981000.7530000.0489000.3391500.3347500.3261000.6996000.1479500.152450
std0.09.9839391.40632116.3705940.4892360.4909240.3986160.4815680.4696060.4609460.3985780.4312780.2156640.4734330.4719150.4687960.4584430.3550590.359466
min1.010.0000000.0000001.0193500.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.000000
25%1.040.2107041.0000009.9234350.0000000.0000000.0000000.0000000.0000000.0000000.0000001.0000000.0000000.0000000.0000000.0000000.0000000.0000000.000000
50%1.046.9336762.00000015.8961430.0000000.0000000.0000000.0000000.0000000.0000000.0000001.0000000.0000000.0000000.0000000.0000001.0000000.0000000.000000
75%1.053.7267143.00000025.5385781.0000001.0000000.0000001.0000001.0000001.0000000.0000001.0000000.0000001.0000001.0000001.0000001.0000000.0000000.000000
max1.081.66563810.000000228.8501601.0000001.0000001.0000001.0000001.0000001.0000001.0000001.0000001.0000001.0000001.0000001.0000001.0000001.0000001.000000
\n", "
" ], "text/plain": [ " const avg_speed hard_brakes trip_distance shift_frueh \\\n", "count 20000.0 20000.000000 20000.000000 20000.000000 20000.000000 \n", "mean 1.0 46.955431 1.987300 20.400866 0.396750 \n", "std 0.0 9.983939 1.406321 16.370594 0.489236 \n", "min 1.0 10.000000 0.000000 1.019350 0.000000 \n", "25% 1.0 40.210704 1.000000 9.923435 0.000000 \n", "50% 1.0 46.933676 2.000000 15.896143 0.000000 \n", "75% 1.0 53.726714 3.000000 25.538578 1.000000 \n", "max 1.0 81.665638 10.000000 228.850160 1.000000 \n", "\n", " shift_normal shift_spaet speeding_haeufig speeding_manchmal \\\n", "count 20000.000000 20000.000000 20000.000000 20000.000000 \n", "mean 0.405100 0.198150 0.365450 0.328300 \n", "std 0.490924 0.398616 0.481568 0.469606 \n", "min 0.000000 0.000000 0.000000 0.000000 \n", "25% 0.000000 0.000000 0.000000 0.000000 \n", "50% 0.000000 0.000000 0.000000 0.000000 \n", "75% 1.000000 0.000000 1.000000 1.000000 \n", "max 1.000000 1.000000 1.000000 1.000000 \n", "\n", " speeding_selten weather_nass weather_trocken weather_winterlich \\\n", "count 20000.000000 20000.000000 20000.000000 20000.000000 \n", "mean 0.306250 0.198100 0.753000 0.048900 \n", "std 0.460946 0.398578 0.431278 0.215664 \n", "min 0.000000 0.000000 0.000000 0.000000 \n", "25% 0.000000 0.000000 1.000000 0.000000 \n", "50% 0.000000 0.000000 1.000000 0.000000 \n", "75% 1.000000 0.000000 1.000000 0.000000 \n", "max 1.000000 1.000000 1.000000 1.000000 \n", "\n", " road_Autobahn road_Außerorts road_Innerorts weekday_Mo-Fr \\\n", "count 20000.000000 20000.000000 20000.000000 20000.000000 \n", "mean 0.339150 0.334750 0.326100 0.699600 \n", "std 0.473433 0.471915 0.468796 0.458443 \n", "min 0.000000 0.000000 0.000000 0.000000 \n", "25% 0.000000 0.000000 0.000000 0.000000 \n", "50% 0.000000 0.000000 0.000000 1.000000 \n", "75% 1.000000 1.000000 1.000000 1.000000 \n", "max 1.000000 1.000000 1.000000 1.000000 \n", "\n", " weekday_Sa weekday_So \n", "count 20000.000000 20000.000000 \n", "mean 0.147950 0.152450 \n", "std 0.355059 0.359466 \n", "min 0.000000 0.000000 \n", "25% 0.000000 0.000000 \n", "50% 0.000000 0.000000 \n", "75% 0.000000 0.000000 \n", "max 1.000000 1.000000 " ] }, "execution_count": 217, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Überblick über die Stichprobe\n", "print(\"Form der Stichprobe:\", X_sample.shape)\n", "print(\"Anteil Zielvariable (Diebstahl):\")\n", "print(pd.Series(target_sample).value_counts(normalize=True))\n", "\n", "# Merkmale\n", "X_sample.describe(include='all')" ] }, { "cell_type": "code", "execution_count": 218, "id": "30bfcdde", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Fehlende Werte pro Spalte:\n", "const 0\n", "avg_speed 0\n", "hard_brakes 0\n", "trip_distance 0\n", "shift_frueh 0\n", "shift_normal 0\n", "shift_spaet 0\n", "speeding_haeufig 0\n", "speeding_manchmal 0\n", "speeding_selten 0\n", "weather_nass 0\n", "weather_trocken 0\n", "weather_winterlich 0\n", "road_Autobahn 0\n", "road_Außerorts 0\n", "road_Innerorts 0\n", "weekday_Mo-Fr 0\n", "weekday_Sa 0\n", "weekday_So 0\n", "dtype: int64\n" ] } ], "source": [ "# Prüfung auf fehlende Werte\n", "print(\"Fehlende Werte pro Spalte:\")\n", "print(X_sample.isnull().sum())" ] }, { "cell_type": "markdown", "id": "201bca58", "metadata": {}, "source": [ "### Feature Engineering\n", "\n", "Für die Modellierung werden kategoriale Variablen in numerische Dummy-Variablen umgewandelt. Dies ist notwendig, damit die Regressionsmodelle die Informationen nutzen können. In unserem Fall sind die kategorischen Variablen schon aus dem vorherigen Schritt One-Hot Encoded, weil wir aus den Variablen das logistische Regressionsproblem erstellt haben. \n", "\n", "Die Daten werden in Trainings- und Testdaten im Verhältnis 80:20 aufgeteilt" ] }, { "cell_type": "code", "execution_count": 219, "id": "b71ab517", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Trainingsdaten: (16000, 19)\n", "Testdaten: (4000, 19)\n", "Anteil Zielvariable in Trainingsdaten:\n", "0 0.782875\n", "1 0.217125\n", "dtype: float64\n", "Anteil Zielvariable in Testdaten:\n", "0 0.783\n", "1 0.217\n", "dtype: float64\n" ] } ], "source": [ "from sklearn.model_selection import train_test_split\n", "\n", "# Zielvariable\n", "y = target_sample\n", "\n", "X_train, X_test, y_train, y_test = train_test_split(X_sample, y, test_size=0.2, random_state=22, stratify=y)\n", "\n", "print(\"Trainingsdaten:\", X_train.shape)\n", "print(\"Testdaten:\", X_test.shape)\n", "print(\"Anteil Zielvariable in Trainingsdaten:\")\n", "print(pd.Series(y_train).value_counts(normalize=True))\n", "print(\"Anteil Zielvariable in Testdaten:\")\n", "print(pd.Series(y_test).value_counts(normalize=True))" ] }, { "cell_type": "markdown", "id": "103a8399", "metadata": {}, "source": [ "### Visualisierung der Variablen" ] }, { "cell_type": "markdown", "id": "d423f20f", "metadata": {}, "source": [ "Um weiteres Verständnis über den Datensatz zu bekommen, visualisieren wir nun die Variablen. Kategorische Variablen werden als Balkendiagramme dargestellt, weil wir eine Anzahl diskreter Werte haben und Metrische Variablen werden in Histogrammen veranschaulicht, um die Verteilung dieser zu erkennen." ] }, { "cell_type": "code", "execution_count": 220, "id": "b748cb80", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "def plot_dummy_counts_grid(df, prefixes):\n", " n_prefixes = len(prefixes)\n", " n_rows = (n_prefixes + 2) // 3\n", "\n", " fig, axes = plt.subplots(n_rows, 3, figsize=(15, 5 * n_rows))\n", "\n", " if n_rows == 1:\n", " axes = axes.reshape(1, -1)\n", " axes = axes.flatten()\n", "\n", " for i, prefix in enumerate(prefixes):\n", " dummy_cols = [col for col in df.columns if col.startswith(prefix)]\n", " counts = df[dummy_cols].sum().sort_values(ascending=False)\n", "\n", " sns.barplot(x=counts.index, y=counts.values, palette='viridis', ax=axes[i])\n", " axes[i].set_title(f'Anzahl der Vorkommen für {prefix} Dummies')\n", " axes[i].set_xlabel('Dummy Variablen')\n", " axes[i].set_ylabel('Anzahl')\n", " axes[i].tick_params(axis='x', rotation=45)\n", "\n", " for i in range(n_prefixes, len(axes)):\n", " axes[i].set_visible(False)\n", "\n", " plt.tight_layout()\n", " plt.show()\n", "\n", "prefixes = ['shift', 'speeding', 'weather', 'road', 'weekday']\n", "plot_dummy_counts_grid(X_train, prefixes)" ] }, { "cell_type": "code", "execution_count": 221, "id": "3ffbfe79", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Deskriptive Statistiken für metrische Variablen:\n", " avg_speed hard_brakes trip_distance\n", "count 16000.000000 16000.000000 16000.000000\n", "mean 46.961020 1.994813 20.440570\n", "std 9.964064 1.409489 16.525250\n", "min 10.000000 0.000000 1.019350\n", "25% 40.184449 1.000000 9.975654\n", "50% 46.937734 2.000000 15.938285\n", "75% 53.689642 3.000000 25.467816\n", "max 81.665638 10.000000 228.850160\n" ] }, { "data": { "image/png": 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"text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "def plot_metric_variables(df):\n", " metric_vars = ['avg_speed', 'hard_brakes', 'trip_distance']\n", "\n", " fig, axes = plt.subplots(2, 3, figsize=(18, 12))\n", "\n", " for i, var in enumerate(metric_vars):\n", " sns.histplot(df[var], kde=True, ax=axes[0, i], bins=30, alpha=0.7)\n", " axes[0, i].set_title(f'Verteilung von {var}')\n", " axes[0, i].set_xlabel(var)\n", " axes[0, i].set_ylabel('Häufigkeit')\n", "\n", " for i, var in enumerate(metric_vars):\n", " sns.boxplot(y=df[var], ax=axes[1, i])\n", " axes[1, i].set_title(f'Boxplot von {var}')\n", " axes[1, i].set_ylabel(var)\n", "\n", " plt.tight_layout()\n", " plt.show()\n", "\n", "metric_vars = ['avg_speed', 'hard_brakes', 'trip_distance']\n", "print(\"Deskriptive Statistiken für metrische Variablen:\")\n", "print(X_train[metric_vars].describe())\n", "\n", "plot_metric_variables(X_train)" ] }, { "cell_type": "markdown", "id": "ab122f01", "metadata": {}, "source": [ "Man kann die Verteilungen deutlich erkennen:\n", "\n", "- **avg_speed**: Normalverteilung mit einem Mittelwert um 47 km/h und einer Standardabweichung von etwa 10. Die Histogramm zeigt die charakteristische Glockenform einer Normalverteilung. Der Boxplot bestätigt eine symmetrische Verteilung mit wenigen Ausreißern.\n", "\n", "- **hard_brakes**: Poisson-Verteilung mit λ ≈ 2, erkennbar an der rechtschiefen Verteilung mit einem Peak bei niedrigen Werten (0-2 harte Bremsmanöver). Die meisten Fahrten haben wenige bis gar keine harten Bremsmanöver, was realistisch ist.\n", "\n", "- **trip_distance**: Lognormalverteilung mit deutlicher Rechtsschiefe. Die meisten Fahrten sind kurz (um 16 km), aber es gibt einen langen Schwanz mit wenigen sehr langen Fahrten. Dies entspricht typischen Fahrtmustern, bei denen viele kurze Fahrten und wenige lange Strecken gefahren werden.\n", "\n", "Die Boxplots zeigen zusätzlich die Quartile und identifizieren Ausreißer, die bei allen drei Variablen vorhanden sind, aber besonders bei trip_distance aufgrund der Lognormalverteilung." ] }, { "cell_type": "markdown", "id": "761c0673", "metadata": {}, "source": [ "### Modellierung der Korrelationen" ] }, { "cell_type": "markdown", "id": "14d31bfe", "metadata": {}, "source": [ "Wir prüfen nun, wie hoch die lineare Korrelation zwischen den einzelnen Variablen sind, denn wir wollen aus unabhängigen Variablen eine abhängige Zielvariable vorhersagen. Besteht eine zu große Korrelation zwischen den erklärenden Variablen, treffen wir auf ein Multikolinearitätsproblem." ] }, { "cell_type": "code", "execution_count": 222, "id": "8a320b4c", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Korrelationsmatrix\n", "plt.figure(figsize=(12, 10))\n", "sns.heatmap(X_train.corr(), annot=True, fmt=\".2f\", cmap='coolwarm', square=True, cbar_kws={\"shrink\": .8})\n", "plt.title('Korrelationsmatrix der Merkmale')\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "684d6fee", "metadata": {}, "source": [ "Man kann erkennen das die kategorischen Variablen natürlich eine stärkere Korrelation haben, weil sie schon in Dummies umgewandelt wurden. Ansonsten gibt es keine stärkeren Korrelationen, sodass wir sehr wahrscheinlich kein Multikolinearitätsproblem haben." ] }, { "cell_type": "markdown", "id": "2127272a", "metadata": {}, "source": [ "### Schrittweise Variablenselektion: Backward Selection\n", "\n", "Um herauszufinden, welche Variablen tatsächlich erklärend für die Zielvariable sind, wird eine schrittweise Backward Selection durchgeführt. Dabei startet man mit allen potenziellen erklärenden Varriablen und entfernt schrittweise die am wenigsten signifikanten Variablen, bis nur noch signifikante Prädiktoren übrig bleiben. Dies hilft, ein einfaches und interpretierbares Modell zu erhalten. Da die Zielvariable binär ist, wird eine logistische Regression verwendet. Das Modell wird auf den Trainingsdaten trainiert und die Modellgüte auf den Testdaten evaluiert." ] }, { "cell_type": "code", "execution_count": 223, "id": "19c7e28c", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Entfernte Variablen und zugehörige p-Werte:\n", "weather_winterlich: p=1.0000\n", "speeding_haeufig: p=1.0000\n", "weather_trocken: p=0.7351\n", "shift_spaet: p=1.0000\n", "weekday_So: p=1.0000\n", "weather_nass: p=0.6532\n", "weekday_Sa: p=0.1450\n", "road_Innerorts: p=1.0000\n", "road_Autobahn: p=0.9322\n", "road_Außerorts: p=0.2163\n", "trip_distance: p=0.1324\n", "weekday_Mo-Fr: p=0.1222\n", "\n", "Verbleibende Variablen im Modell:\n", "['const', 'avg_speed', 'hard_brakes', 'shift_frueh', 'shift_normal', 'speeding_manchmal', 'speeding_selten']\n", "\n", "Zusammenfassung des finalen Modells:\n", " Logit Regression Results \n", "==============================================================================\n", "Dep. Variable: y No. Observations: 16000\n", "Model: Logit Df Residuals: 15993\n", "Method: MLE Df Model: 6\n", "Date: Sat, 05 Jul 2025 Pseudo R-squ.: 0.5252\n", "Time: 19:12:56 Log-Likelihood: -3975.1\n", "converged: True LL-Null: -8371.9\n", "Covariance Type: nonrobust LLR p-value: 0.000\n", "=====================================================================================\n", " coef std err z P>|z| [0.025 0.975]\n", "-------------------------------------------------------------------------------------\n", "const -14.4135 0.279 -51.618 0.000 -14.961 -13.866\n", "avg_speed 0.2880 0.005 52.931 0.000 0.277 0.299\n", "hard_brakes 0.5842 0.022 27.104 0.000 0.542 0.626\n", "shift_frueh -2.2629 0.079 -28.492 0.000 -2.419 -2.107\n", "shift_normal -2.2808 0.080 -28.661 0.000 -2.437 -2.125\n", "speeding_manchmal -2.2350 0.075 -29.701 0.000 -2.382 -2.087\n", "speeding_selten -2.1359 0.077 -27.851 0.000 -2.286 -1.986\n", "=====================================================================================\n" ] } ], "source": [ "import statsmodels.api as sm\n", "\n", "def backward_selection(X, y, significance_level=0.05):\n", " X_ = X.copy().astype(float)\n", " removed_features = []\n", " while True:\n", " X_with_const = sm.add_constant(X_)\n", " model = sm.Logit(y, X_with_const).fit(disp=0)\n", " pvalues = model.pvalues.drop('const')\n", " max_pval = pvalues.max()\n", " if max_pval > significance_level:\n", " excluded_feature = pvalues.idxmax()\n", " removed_features.append((excluded_feature, max_pval))\n", " X_ = X_.drop(columns=[excluded_feature])\n", " else:\n", " break\n", " return X_, removed_features, model\n", "\n", "X_selected, removed_features, final_model = backward_selection(X_train, y_train)\n", "\n", "print(\"Entfernte Variablen und zugehörige p-Werte:\")\n", "for feat, pval in removed_features:\n", " print(f\"{feat}: p={pval:.4f}\")\n", "\n", "print(\"\\nVerbleibende Variablen im Modell:\")\n", "print(list(X_selected.columns))\n", "\n", "print(\"\\nZusammenfassung des finalen Modells:\")\n", "print(final_model.summary())" ] }, { "cell_type": "markdown", "id": "e9fd3cbc", "metadata": {}, "source": [ "Die Backward Selection funktioniert wie erwartet: Alle erklärenden Variablen werden im Modell beibehalten, während die nicht-erklärenden Variablen (Wetter, Straßentyp, Wochentag, Fahrstrecke) aufgrund ihrer statistischen Insignifikanz entfernt werden.\n", "\n", "Ein wichtiges Detail ist die Behandlung der kategorialen Variablen: Bei den ordinalen Features wird jeweils eine Dummy-Variable entfernt. Dies ist methodisch korrekt, da bei k Kategorien nur k-1 Dummy-Variablen benötigt werden, um alle Informationen zu kodieren." ] }, { "cell_type": "markdown", "id": "a0db711e", "metadata": {}, "source": [ "### Modellevaluation auf Testdaten\n", "\n", "Nachdem das optimale Modell auf den Trainingsdaten entwickelt wurde, wird es nun auf den Testdaten evaluiert. Dies gibt uns eine Einschätzung der Modellgüte und zeigt, wie gut das Modell auf ungesehenen Daten performt." ] }, { "cell_type": "code", "execution_count": 224, "id": "a1c9fc7f", "metadata": {}, "outputs": [ { "data": { "image/png": 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4hPnzpffeiz4uVUpavlx68UXjMgEAAADPimaMRKFihzRt+PDo60WKSD/9dJWuawAAHEn79tLLL1uvv/ee9OuvFLIBAACANIrObKRJUXOyT56MXhs1ymJcIAAAYGWx2HereHhIy5ZJp09LDRoYlwsAAABICszMThT+9JCmBAVJxYtL/v7W8SJms3W9WDHmYAMAYLg//pBefVU6fNh+vWhRCtkAAAAAKGYjbXi0iB1TsWLWTR0BAIBBLBZpxgzplVekffuk1q2l+/eNTgUAAAAkPZMp+S+pGMVspGpPK2IHBUnHj9OVDQCAYUJCpCZNpD59pAcPrGuurtZ1AAAAAIiBmdlItYKCrEXsR0V1YlPABgDAYOvXSx07Sv/+G7323nvS+PGSl5dhsQAAAIDkYkrlndPJjc5spCpRndh588YuZNOJDQCAg3jwQOrXzzoHO6qQ7esr/fCDNGUKhWwAAAAAcaIzG6nG4zqxo26jgA0AgAM4dsw6EzvmJo8NG0rz50s5cxqXCwAAAEgBdGYnDp3ZSBXiKmT7+UV3Y1PIBgDAQdy6JR09ar3u6SlNmyZ99x2FbAAAAABPRWc2nF5chWwK2AAAOKiKFaWRI6WVK6Vly6RSpYxOBAAAAKQcGrMThc5sOKUnzcamkA0AgAPZvVuKjLRfGzJE2rePQjYAAACABKGYDacQs3gdVcA+cUK6dCn2eRSyAQBwAGFhUv/+0muvSePG2d/m6somjwAAAEiTTCZTsl9SM4rZcArDh0cXrx8tYDMbGwAAB3PsmPTqq9KUKdbjkSOj52QDAAAAwDNiZjYcUlCQtYB9+7b1+PJl639dXKTcua3Xvb2lMWMoYAMA4DAsFmnmTGnAAOnBA+uap6c0YYJUooSx2QAAAAAHkNo7p5MbxWw4lKgi9okTcd9epIh0/HjKZgIAAPFw5YrUpYu0bl302osvSsuXMxsbAAAAQJKgmA3DxezCfnSEiGQdIyJFd2IDAAAHs3Gj9PbbUnBw9Nq771o7stOlMy4XAAAA4GDozE4citkw3OM6sYsVY4wIAAAOb80aqUWL6OMcOaTAQKlRI+MyAQAAAA6KYnbisAEkDBUUFF3IdnGx38zx+HEK2QAAOLwGDaLnYdevLx0+TCEbAAAAQLKgMxuGCQqS/P2jj5mHDQCAE0qXzjoXe9s2qU8f62+nkepMmzYt3uf27ds3GZMAAAA4OQdrzB43bpzWrFmjEydOKF26dKpcubI++eQTFS1a1HZOx44dtXDhQrv7vfrqq9q7d6/tOCwsTAMHDtTy5ct1//591apVS1988YXy5s1rO+fGjRvq27ev1q5dK0lq2rSppk+frsyZM8c7L8VsGOLRQrbEPGwAABzelSvWgvWoUVKMD7cqXdp6Qao1efLkeJ1nMpkoZgMAADiRHTt2qHfv3nrllVcUERGhoUOHqm7dujp27JgyZMhgO69+/foKDAy0HXt4eNg9Tr9+/bRu3TqtWLFC2bJl04ABA9S4cWPt379frq6ukqQ2bdro4sWLWr9+vSSpe/fuat++vdbF3ET+KShmI0VFbfb46IzsoCBGigAA4NA2bZI6dLBu8vj339Lu3dIjH2CRep05c8boCAAAAKmCo83MjiosRwkMDJSvr6/279+vqlWr2tY9PT2VK1euOB8jNDRU8+bN0+LFi1W7dm1J0pIlS5QvXz5t3rxZ9erV0/Hjx7V+/Xrt3btXr776qiRpzpw5qlSpkv7880+7TvAn4XugSDFR3dgUsgEAcCJhYdKAAVLdutZCtiSdOyedPGlsLgAAAABxCgsL061bt+wuYWFh8bpvaGioJClr1qx269u3b5evr6+KFCmibt26KSQkxHbb/v379fDhQ9WtW9e2lidPHpUsWVK7d++WJO3Zs0c+Pj62QrYkVaxYUT4+PrZz4oPObCS7x3VjFytmHS1CIRsAAAd1/LjUpo106FD0Wr160oIF0mO6MpD6RUZGasGCBdqyZYtCQkJkNpvtbt+6datByQAAABxfSnRmjxs3TqNGjbJbGzFihEaOHPnE+1ksFgUEBOh///ufSpYsaVtv0KCB3nzzTRUoUEBnzpzRsGHDVLNmTe3fv1+enp4KDg6Wh4eHsmTJYvd4OXPmVPB/DTHBwcHy9fWN9Zy+vr62c+KDYjaSHWNFAABwMhaL9OWXUkCAdP++dc3DQ/rkE6lvXzZ5TOPee+89LViwQI0aNVLJkiUd7quyAAAAad2QIUMUEBBgt+bp6fnU+7377rs6fPiwdu3aZbfeqlUr2/WSJUuqfPnyKlCggL7//ns1b978sY9nsVjsPivG9bnx0XOehmI2kt3t29b/urhIRYrQjQ0AgEO7elXq2lX69tvotRIlpGXLpJdeMi4XHMaKFSv01VdfqWHDhkZHAQAAcDop0Qjg6ekZr+J1TH369NHatWu1c+dO5c2b94nn5s6dWwUKFNBff/0lScqVK5fCw8N148YNu+7skJAQVa5c2XbOv//+G+uxrly5opw5c8Y7J201SFZBQdKlS9bruXNbv61MIRsAAAd29Ki0dm30ca9e0r59FLJh4+HhocKFCxsdAwAAAEnAYrHo3Xff1Zo1a7R161YVLFjwqfe5du2aLly4oNy5c0uSypUrJ3d3d23atMl2zuXLl/XHH3/YitmVKlVSaGiofv31V9s5v/zyi0JDQ23nxAfFbCSr4cOjr3t7G5cDAADEU7Vq0vvvS9mzW7uzP/9cSp/e6FRwIAMGDNDUqVNlsViMjgIAAOB0TCZTsl8Sonfv3lqyZImWLVsmb29vBQcHKzg4WPf/Gzd4584dDRw4UHv27NHZs2e1fft2NWnSRNmzZ1ezZs0kST4+PurSpYsGDBigLVu26ODBg2rXrp1KlSql2rVrS5KKFy+u+vXrq1u3btq7d6/27t2rbt26qXHjxipatGi88zJmBMkiatPHkyej18aMMS4PAAB4jDNnpAIF7Odgjx4tvfcemzzC5tFZiFu3btWPP/6oF198Ue7u7na3rVmzJiWjAQAAIBFmzpwpSapevbrdemBgoDp27ChXV1cdOXJEixYt0s2bN5U7d27VqFFDK1eulHeMztXJkyfLzc1N/v7+un//vmrVqqUFCxbI1dXVds7SpUvVt29f1a1bV5LUtGlTzZgxI0F5KWYjWTy66WOxYowXAQDAoVgs0uzZUv/+0scfW/8bxd2dQjbs+Pj42B1HdeEAAAAggRxs7+ynfdsuXbp02rBhw1Mfx8vLS9OnT9f06dMfe07WrFm1ZMmSBGeMiWI2kkVcmz4CAAAH8egmjx98INWqJZUubWwuOKzAwECjIwAAAAAUs5H04tr0EQAAOIjNm6UOHaTLl6PXunSR2NAPAAAASHYJnWkNexSzkWhR87GjurGjCtkSmz4CAOAwwsOloUOliROj17Jlk+bPl5o2NS4XnNKqVav01Vdf6fz58woPD7e77cCBAwalAgAAQGrn8vRTgMcLCpL8/a3zsS9dsi9kS4wXAQDAIZw4IVWsaF/IrlNHOnKEQjYSbNq0aerUqZN8fX118OBBVahQQdmyZdPp06fVoEEDo+MBAAA4NJPJlOyX1IxiNhJl+HD7Yz8/66VYMWuhm00fAQAw2Pbt0ssvSwcPWo/d3aXPPpPWr7fOAwMS6IsvvtDs2bM1Y8YMeXh4aPDgwdq0aZP69u2r0NBQo+MBAAAgFWPMCBIlarSIRPEaAACHVK6clCePdOqU9bfNy5ZJZcsanQpO7Pz586pcubIk6+72t//7QNi+fXtVrFhRM2bMMDIeAACAQ0vtndPJjc5sPLOYGz36+VHIBgDAIXl7WwvY77wj7d9PIRuJlitXLl27dk2SVKBAAe3du1eSdObMGVksFiOjAQAAIJWjmI1nFnPECBs9AgDgAMLDpf/7P+nMGfv1ChWkL76Q0qc3JhdSlZo1a2rdunWSpC5duqh///6qU6eOWrVqpWbNmhmcDgAAwMGZUuCSijFmBAkWFGQtZJ88Gb3GRo8AABjszz+ltm2t3dfbt1svbnzUQ9KbPXu2zGazJKlnz57KmjWrdu3apSZNmqhnz54GpwMAAEBqxk84SLDhw6UTJ6KPixVjxAgAAIaxWKS5c6V+/aR796xrv/4q7dsnVapkaDSkThcvXlS+fPlsx/7+/vL395fFYtGFCxeUP39+A9MBAAA4NmZmJw5jRhBvQUFS8eLRHdkuLtZCNl3ZAAAY5No1qUULqXv36EJ20aLS3r0UspFsChYsqCtXrsRav379ugoWLGhAIgAAAKQVdGYjXoKCJH9/+7UiRaTjx43JAwBAmrd1q9ShQ/RuzJK1qD1pkpQhg3G5kOpZLJY4O4ru3LkjLy8vAxIBAAA4DzqzE4diNuIl5maPEh3ZAAAYJjxcGjZM+vRT64gRScqa1TpqhM33kIwCAgIkWX8AGzZsmNLH2FA0MjJSv/zyi8qUKWNQOgAAAKQFFLPxVEFB9jOyg4KYkQ0AgGF275YmTIg+rlVLWrRIypPHuExIEw4ePCjJ2pl95MgReXh42G7z8PDQSy+9pIEDBxoVDwAAwCnQmZ04FLPxVDG7stnsEQAAg1WvLvXpI82aJX38sTRggHUjCyCZbdu2TZLUqVMnTZ06VZkyZTI4EQAAANIaitl4qtu3o68zWgQAgBR265bk7S3F7OCYMEHq0kV66SXjciHNCgwMtDu+deuWtm7dqmLFiqlYsWIGpQIAAHAOdGYnDm08iDc/P7qyAQBIUdu2SSVKSHPm2K97eVHIhmH8/f01Y8YMSdL9+/dVvnx5+fv7q1SpUlq9erXB6QAAAJCaUczGEwUFSZcuGZ0CAIA0Jjxc+uAD6zzsS5ekfv3sN7AADLRz505VqVJFkvT111/LYrHo5s2bmjZtmj766COD0wEAADg4UwpcUjGK2YhTUJBUvLjk7x+95u1tXB4AANKMkyelypWlTz6RLBbrWqVK/EMMhxEaGqqsWbNKktavX68WLVooffr0atSokf766y+D0wEAACA1o5iNWIKCrEXsRxvAmJcNAEAyslikefOksmWl/futa+7u1vnYmzZZ530BDiBfvnzas2eP7t69q/Xr16tu3bqSpBs3bsjLy8vgdAAAAI7NZDIl+yU1YwNI2IkqZMdUrJi1kM28bAAAksn161L37lLMecNFikjLlknlyhmXC4hDv3791LZtW2XMmFEFChRQ9erVJVnHj5QqVcrYcAAAAEjVKGZDkrWIPXx47G7soCCK2AAAJKvff5caN5YuXoxe69ZNmjxZypDBuFzAY/Tq1UsVKlTQhQsXVKdOHbm4WL/s+fzzzzMzGwAA4ClSe+d0cqOYjTi7saPWKWQDAJDM8ueXoj7QZs0qzZ0rNWtmbCbgKcqXL6/y5cvLYrHIYrHIZDKpUaNGRscCAABAKsfMbGj4cPvjYsUoZAMAkGKyZJGWLJHq1JEOH6aQDacwb948lSxZUl5eXvLy8lLJkiU1d+5co2MBAAA4PGZmJw6d2WlcUJD9aBGK2AAAJCOLRVq8WKpdW8qTJ3q9alVpw4boDm3AgQ0bNkyTJ09Wnz59VKlSJUnSnj171L9/f509e5ZRIwAAAEg2FLPTuJhd2cWKUcgGACDZ3Lgh9ehh/c1x7drW4rVLjC/JUciGk5g5c6bmzJmj1q1b29aaNm2q0qVLq0+fPhSzAQAAnoSP/Yli+JiRL774QgULFpSXl5fKlSunn3766YnnL126VC+99JLSp0+v3Llzq1OnTrp27VoKpU1dHu3KHjPGuCwAAKRqO3ZIL71k/cdXkjZvljZuNDYT8IwiIyNVvnz5WOvlypVTRESEAYkAAACQVhhazF65cqX69eunoUOH6uDBg6pSpYoaNGig8+fPx3n+rl271KFDB3Xp0kVHjx5VUFCQ9u3bp65du6Zw8tSBrmwAAJLZw4fS0KFSjRrShQvWtSxZpFWrpPr1jc0GPKN27dpp5syZsdZnz56ttm3bGpAIAADAeTAzO3EMHTMyadIkdenSxVaMnjJlijZs2KCZM2dq3Lhxsc7fu3evnnvuOfXt21eSVLBgQfXo0UMTJkxI0dzOLijIWsg+eTJ6ja5sAACSluuZMzI1bSrt2xe9WKOGtGiRlDevccGAZxAQEGC7bjKZNHfuXG3cuFEVK1aUZP2cfuHCBXXo0MGoiAAAAEgDDCtmh4eHa//+/frggw/s1uvWravdu3fHeZ/KlStr6NCh+uGHH9SgQQOFhIRo1apVatSoUUpETjWGD7cfL0JXNgAASchikQIDla1vX5nu3bOuublJH30kDRwouboamw94BgcPHrQ7LleunCTp1KlTkqQcOXIoR44cOnr0aIpnAwAAcCapvXM6uRlWzL569aoiIyOVM2dOu/WcOXMqODg4zvtUrlxZS5cuVatWrfTgwQNFRESoadOmmj59+mOfJywsTGFhYbbjW7duSZLMZrPMZnMSvBLnc/u2SZJJLi4WFSkijRplURr9o7BjNptlsVjS7PsCj8d7A4/DewNx2rNHLjFGoFleeEGWxYulV16xLvB+SdOc9e+Lbdu2GR0BAAAAMHbMiBT7txEWi+Wxv6E4duyY+vbtq+HDh6tevXq6fPmyBg0apJ49e2revHlx3mfcuHEaNWpUrPUrV64oPDw88S/ACZnNOSS5KmdOs7ZtuyJJCgkxNpMjMJvNCg0NlcVikYuL4XujwoHw3sDj8N5AnAoVknfr1sqwfLnuvvWW7nz0kSwZMvCPLSRJoaGhRkdIMn///bdOnTqlqlWrKl26dE/8HI+0a2Dnunqj5ksq8lxO3Q97qF9+P62hU7/VX+ei/070zeqtj957XbUrFZdPxnTadeBvBUwI0qnzV2znbJjznqqWf8HusYM27FeHDwLt1ur/70V92L2BSr6QR3fvh+vnA3/rrYFzk/dFAkhW+3/bpwXz5+n4sT905coVTZ72uWrWqm27/aUXi8Z5v/4DBqlj5+gGg98PHdT0qZN15Mhhubu5qWix4vp81hx5eXkl+2sAYuLzUuIYVszOnj27XF1dY3Vhh4SExOrWjjJu3Di99tprGjRokCSpdOnSypAhg6pUqaKPPvpIuXPnjnWfIUOG2M34u3XrlvLly6ccOXIoc+bMSfeCnIiLi+m//7rI19fX4DSOw2w2y2QyKUeOHBSlYIf3Bh6H9wYkSRER1jEiMZhnztT1evWUqW1bpeO9gRg8PDyMjpBo165dk7+/v7Zt2yaTyaS//vpLzz//vLp27arMmTPrs88+MzoiHEiVlwtr1sqd2n/0nNzcXDWydxN9N/NdlW3+ke49sDYXfTW5ux5GROrNfl/q1t0H6tuupn6Y1cfuHEmat/pnjZn5ne34fthDu+d6o1YZfT6stUbMWKftv56UySSVfCFPyrxQAMnm/v17Klq0qF5v1lwD+vWJdfuW7bvsjnft2qmRw4aqdp16trXfDx1Urx5d1blrD30wdJjc3d118sQJPsMDTsiwYraHh4fKlSunTZs2qVmzZrb1TZs26fXXX4/zPvfu3ZPbIz8suv43d9JiscR5H09PT3l6esZad3FxSZN/aQUFSZcuRR2ZbIVtWJlMpjT73sCT8d7A4/DeSOP+/ltq21bq00dq1y563dtb4fXq8d5ALKnh/dC/f3+5u7vr/PnzKl68uG29VatW6t+/P8Vs2Hn93S/sjnuMXKILW8erbIl8+vnAKRXO76tXSxfUyy0+0vHT1kan98at1Pkt4+XfoJwWfL3Hdt/7D8L177XbcT6Pq6uLJg5qoQ+nfKOF30TfJ2YHOADn9L8q1fS/KtUee3v2HDnsjrdv3aJXKryqvPny2dY+/WScWrdtry7dutvWChR4LsmzAvFBZ3biGPppOiAgQHPnztX8+fN1/Phx9e/fX+fPn1fPnj0lWbuqY+6I3qRJE61Zs0YzZ87U6dOn9fPPP6tv376qUKGC8uThN+7xMXx49HVvb+NyAADg1CwWacECqWxZ6ddfpV69pNOnjU4FpIiNGzfqk08+Ud68ee3WX3jhBZ07d86gVHAWmTJav85/I9S6Qa6nh7VZ6UF4hO0cs9mi8IcRqlymkN19WzUsrwtbx2v/qqEa17+ZMqaPbloqWyyf/HJmkdls0Z7l7+v0xo/1zYx3VPz5XMn9kgA4kGtXr+qnnTvUrHnL6LVr13Tk8O/Kmi2bOrR9SzWqVlbnt9vpwP7fDEwK4FkZOjO7VatWunbtmkaPHq3Lly+rZMmS+uGHH1SgQAFJ0uXLl3X+/Hnb+R07dtTt27c1Y8YMDRgwQJkzZ1bNmjX1ySefGPUSnEpQkHTiRPTxmDHGZQEAwGnduCH17Cl99VX0Ws6c0u24uwWB1Obu3btKnz59rPWrV6/G+Y1IIKZPBrTQzwf+1rFTlyVJf54N1rl/rmlMn6Z696Pluns/XO+1r6ncOXyUK7uP7X4rftins/9c079Xb+nFwnk0uk8TlSrip8bvzJAkFcybXZL0fz0b6v3P1ujcP9f0Xvta2ji3n0q/MVo3bt1L+RcLIMWt/fZrpU+fQbXq1LWtXbp4QZI06/MZChg0WEWLFdd3336j7l06avW339GhjZRHY3aiGL4BZK9evdSrV684b1uwYEGstT59+qhPn9gzkvBkQUGSv3/0cbFiUsuWjz8fAADEYedO6ziRCxei1zp3lqZOlTJmNC4XkIKqVq2qRYsWacx/nREmk0lms1mffvqpatSo8dT7h4WFKSwszG7NYo6UycU1WfLCcUz+wF+lXsijWp0m29YiIsxqPXCuZo5oq8s7P1VERKS2/vKn1u86anffwK93264fO3VZf58P0e5l76tMsbw6dOKiXP77yvYnczfomy2HJEndRyzR3xvGqHmdspq3+ufkf4EADPfN16vVsHETu1+ums1mSVJL/1Z6o1kLSVLx4iX0yy979M2a1Xqv/wBDsgJ4NoYXs5G8goKso0VidmRLdGUDAJAgDx9Ko0dLY8dK//1ApMyZpdmzpTffNDQakNI+/fRTVa9eXb/99pvCw8M1ePBgHT16VNevX9fPPz+9YDhu3DiNGjXKbs015ytyz10huSLDAUx6/001rlZKtbtM0aWQm3a3HTx+QRXfGq9MGb3k4e6mqzfuaOeigdp/7HzcD/bffcIfRqhwfl8dOnFRl6+GSpJOnL5sOyf8YYTOXrymfLmyJstrAuBYDuz/TWfPnNGEiVPs1qNmaj9fyH50UcHnCyn48j8pFQ+wYWZ24jj/DjR4rKhu7EcL2UFBdGUDABBv589LVapIH30UXciuVk06fJhCNtKkEiVK6PDhw6pQoYLq1Kmju3fvqnnz5jp48KAKPVIoiMuQIUMUGhpqd3HLWS4FksMok99/U6/XfEn1e0zTuX+uPfa8W3ce6OqNOyqUP4deLpFf320//NhzSxTKLQ93N1sR++DxC3oQ9lAvPJfTdo6bm4vy58mq85evJ92LAeCwvl69SiVefFFFixWzW/fzy6scvr46e+aM3fq5s2eVO49fSkYEkATozE6lHh0rIllHi4wZQyEbAIAE8fKSzp61Xndzk0aNkt5/X3JlJALSrly5csXqro4vT0/PWLO1GTGSek0Z4q9WDcrrzf6zdefuA+XMZt2FPvTOAz0IeyhJal67rK7cuKMLwddV8oU8mjiopdZtP6wte61dOQXzZtdbDctrw65junrjjooXyqXx/Zvr4PEL2nPIuvnu7bsPNHfVLg3r2VAXg2/o/OXr6v92bUnSmk0HDHjlAJLKvbt37fZTu3Txok4cPy4fHx/lzpNHknTnzh1t3LheAwa9H+v+JpNJHTt10czPp6to0WIqWqy41n77tc6eOa3PJk9LsdcBRKEzO3EoZqdSw4fbH9ONDQDAM/L1lRYulPr0kZYskSowCgFpz+HDh1WyZEm5uLjo8OHHd8tKUunSpVMoFZxBD/+qkqRNc/vZrXcbvlhL1v0iScqVI5M+GdBcvtm8FXz1lpZ+94vGzV5vO/fhwwjVqFBUvVvXUMb0HroYfFPrd/2hj7/8UWazxXbekClfKyLSrHkfdVA6T3ft++OcGnSfppu37yf/CwWQbI4e/UNdO3WwHU+cME6S1PT1Zhozdrwkaf0P30sWixo0bBznY7Tr0FFhYeH6dMI4hYaGqmjRYpo1Z77y5c+f/C8AQJIyWSwWy9NPSz1u3bolHx8f3bhxQ5kzZzY6TrJ4tCubQnb8mM1mhYSEyNfXVy4uTOBBNN4beBzeG6nUrl1S0aLSf/MVbR4+lNzd4/UQvDfwODdv3lSWLFkUGhqqTJkyGR0n3lxcXBQcHGx7T5tMJsX1Y4TJZFJkZGSCHz9d2XeTIiaANOTGvhlGRwDgZLwcpKW38MAfk/05/p7YINmfwygO8r8RSSGuzR6LFaOQDQBAvMTc5LFRI+nbb6WYXwGMZyEbSI3OnDmjHP/9gufMIzNHAQAAgJRCMTsVebSQLVlnZAMAgKc4dUpq21b6xfqVd61bJ61ezW+Egf8UKFAgzusAAABIGGZmJw7F7FTk9m3rf11cpCJF2OwRAICnslikxYul3r2lO3esa66u1k0emzUzNhvgoLZu3ao1a9bo7NmzMplMKliwoFq2bKmqVasaHQ0AAACpHMXsVCIoSLp0yXo9d27p+HFj8wAA4PBu3pTeeUdasSJ67fnnpWXLpFdfNSwW4Mh69uyp2bNnK0uWLCpSpIgsFot2796tzz//XL169dL06dONjggAAODQaMxOHHYkSiWGD4++7u1tXA4AAJzCrl1SmTL2hey335YOHaKQDTzG119/rcDAQM2fP19Xr17Vnj17tHfvXl25ckVz5szR7NmztXbtWqNjAgAAIBWjMzuViBoxIjEnGwCAJzp8WKpWTTKbrcc+PtKXX0qtWhmbC3BwgYGBCggIUMeOHe3WXVxc1LlzZ/3555+aN2+emjZtakxAAAAAJ8DM7MShM9vJBQVJxYtLly9bj/38mJMNAMATlSol+ftbr1epIv3+O4VsIB4OHDigZk+YJd+iRQvt378/BRMBAAAgraEz28kNHy6dOBF9zIgRAACewmSSZs6UKlSQ+va1bvgI4KmuXr0qPz+/x97u5+ena9eupWAiAAAA50NjduLQme3kosaLuLhIxYoxYgQAADuhoVLbttKaNfbrmTNL/ftTyAYSIDw8XB4eHo+93c3NTeHh4SmYCAAAAGkNndlOLChIunTJej13bun4cWPzAADgUH7+2VrIPndOWr/eurHjE7pKATzdsGHDlD59+jhvu3fvXgqnAQAAcD4uLrRmJwbFbCc2fHj0dcaLAADwn4gI61eVPvooepPHyEjrXC6K2cAzq1q1qv7888+nngMAAAAkF4rZTigoyFrIPnkyeo3xIgAASDpzxtqNvWdP9Nr//ictWSIVKGBcLiAV2L59u9ERAAAAnB4zsxOHmdlOKGrTx6hms2LFpJYtjc0EAIDhliyRXnopupDt6iqNHi1t20YhGwAAAABSATqznUxQkLWQLVk3fSxShK5sAEAaFxoq9e4tLV0avVawoPW4UiXjcgEAAADAI0y0ZicKxWwnEhQk+ftHHxcpwqaPAADozh3pxx+jj9u3l2bMkDJlMi4TAAAAACDJMWbEicTc8FGiIxsAAEnWTR3nzrUWr5ctkxYtopANAAAAwCGZTMl/Sc3ozHYSMceLRB0zJxsAkCadPStlzmy9RGnWTKpaVcqWzaBQAAAAAIDkRjHbScTsymbDRwBAmrVsmfTOO1KDBtLy5fZtBxSygRRz8+ZN/frrrwoJCZE5alfy/3To0MGgVAAAAI6PmdmJQzHbSdy+HX2d8SIAgDTn1i3rJo9LlliPV66U3nhDeustQ2MBadG6devUtm1b3b17V97e3nY/kJlMJorZAAAASDYUs52Mnx9d2QCANGbPHqltW+nMmei19u2lhg2NywSkYQMGDFDnzp01duxYpU+f3ug4AAAAToXO7MRhA0gAAOCYIiKk0aOlKlWiC9mZMklLl7LJI2CgS5cuqW/fvhSyAQAAkOLozHYCQUHSpUtGpwAAIAWdPSu1ayf9/HP0WuXK1jEjBQsaFguAVK9ePf322296/vnnjY4CAADgdGjMThyK2U4g5uaP3t7G5QAAIEX8/bdUrpx1TrYkubhY/zEcOlRy46MLYLRGjRpp0KBBOnbsmEqVKiV3d3e725s2bWpQMgAAAKR2/ETo4IKCpBMnoo/Z/BEAkOoVKiRVry6tXSs995x1rEjlykanAvCfbt26SZJGjx4d6zaTyaTIyMiUjgQAAOA0mJmdOMzMdnAxu7KLFWPzRwBAGmAySfPmSb17S4cOUcgGHIzZbH7shUI2AAAAkhPFbAd3+3b0dbqyAQCpTmSk9R+4DRvs17Nnl2bMkHx8jMkFAAAAAMnAZEr+S2rGmBEHFnPjRz8/urIBAKnMuXPWTR537ZJy5pQOH5Z8fY1OBSAO06ZNU/fu3eXl5aVp06Y98dy+ffumUCoAAACkNRSzHRgbPwIAUq0VK6SePaXQUOvxlSvS1q3SW28ZmwtAnCZPnqy2bdvKy8tLkydPfux5JpOJYjYAAMATMDM7cShmOzBGjAAAUp3bt6V335UWLYpee+45ackS6bXXDIsF4MnOnDkT53UAAAAgJTEz2wkwYgQAkCr88otUpox9IbttW+smjxSyAacTHh6uP//8UxEREUZHAQAAcBrMzE4citkOKua8bAAAnFpkpPTRR9aC9enT1jVvb2nxYmtHNps8Ak7l3r176tKli9KnT68XX3xR58+fl2SdlT1+/HiD0wEAACA1o5jtoJiXDQBINf75R/r0U2tRW5IqVbJ2Y7drZ2gsAM9myJAh+v3337V9+3Z5eXnZ1mvXrq2VK1camAwAAMDxmUymZL+kZhSzHRTzsgEAqUa+fNIXX0guLtbf1u7cKT3/vNGpADyjb775RjNmzND//vc/ux+WSpQooVOnThmYDAAAAKkdG0A6oJgjRpiXDQBwOrdvWwvXGTJEr7VtK5UvLxUtalwuAEniypUr8vX1jbV+9+7dVN8JBAAAkFh8XEocOrMdTFCQ5O8ffcyIEQCAU/n1V6lsWem992LfRiEbSBVeeeUVff/997bjqAL2nDlzVKlSJaNiAQAAOAXGjCQOndkOJuasbIkRIwAAJxEZKY0fL40YYb1+6pRUvz5fLwJSoXHjxql+/fo6duyYIiIiNHXqVB09elR79uzRjh07jI4HAACAVIzObAcTc1Z2UBA1AACAEzh/XqpZU/q//4ve5LFiRenll43NBSBZVK5cWT///LPu3bunQoUKaePGjcqZM6f27NmjF154weh4AAAADs1kSv5LakYx20ExKxsA4BS++kp66SXrpo6SdVb2sGFs8gikQhMnTrRdL1WqlBYuXKg//vhDx44d05IlS1SgQAHVrVvXwIQAAABI7ShmAwCAhLt9W+rUSWrVSrp507qWP7+0fbs0erTk7m5kOgDJYNiwYQoMDIzztjt37qhevXq6detWCqcCAABwLo42M3vcuHF65ZVX5O3tLV9fX73xxhv6888/7c6xWCwaOXKk8uTJo3Tp0ql69eo6evSo3TlhYWHq06ePsmfPrgwZMqhp06a6ePGi3Tk3btxQ+/bt5ePjIx8fH7Vv3143o36ejCeK2QAAIGH++ce6yeOCBdFrb70l/f67VKWKYbEAJK/FixerV69e+uabb+zW79y5o7p16+r69evatm2bMeEAAADwTHbs2KHevXtr79692rRpkyIiIlS3bl3dvXvXds6ECRM0adIkzZgxQ/v27VOuXLlUp04d3Y4xL7lfv376+uuvtWLFCu3atUt37txR48aNFRk1ilJSmzZtdOjQIa1fv17r16/XoUOH1L59+wTlZQNIBxIUJF26ZHQKAACeIlcu6wiRU6ekjBmlzz+X2rdP/cPZgDSuZcuWunnzptq0aaPvv/9eNWrU0J07d1S/fn1dvXpVO3bsUM6cOY2OCQAA4NAc7cem9evX2x0HBgbK19dX+/fvV9WqVWWxWDRlyhQNHTpUzZs3lyQtXLhQOXPm1LJly9SjRw+FhoZq3rx5Wrx4sWrXri1JWrJkifLly6fNmzerXr16On78uNavX6+9e/fq1VdflSTNmTNHlSpV0p9//qmiRYvGKy+d2Q5k+PDo697exuUAAOCJXFykhQulRo2kQ4ekDh0c7xMZgGTRtWtXjRw5Um+88Ya2b9+uBg0aKDg4WNu2bVPu3LmNjgcAAABZR37cunXL7hIWFhav+4aGhkqSsmbNKkk6c+aMgoOD7fZG8fT0VLVq1bR7925J0v79+/Xw4UO7c/LkyaOSJUvaztmzZ498fHxshWxJqlixonx8fGznxAfFbAcQFCQVLy6dPBm9NmaMcXkAALATFBS9wWOU3Lml776TChUyJhMAwwwePFi9evVSrVq19M8//2j79u3y8/MzOhYAAIBTSImZ2ePGjbPNpY66jBs37qnZLBaLAgIC9L///U8lS5aUJAUHB0tSrG/g5cyZ03ZbcHCwPDw8lCVLliee4+vrG+s5fX19befEB2NGHMDw4dKJE9HHxYpJLVsalwcAAEnSnTtS375SYKCUN690+LD0yIcTAGlH1NdKo7i7uyt79uzq27ev3fqaNWtSMhYAAAAeMWTIEAUEBNiteXp6PvV+7777rg4fPqxdu3bFuu3RjSUtFstTN5t89Jy4zo/P48REMdsBRM1Kd3GRihShKxsA4AD27ZPatJH+/tt6fPGitHixtbgNIE3y8fGxO27durVBSQAAAJxXSkxo9PT0jFfxOqY+ffpo7dq12rlzp/LmzWtbz5UrlyRrZ3XMsXIhISG2bu1cuXIpPDxcN27csOvODgkJUeXKlW3n/Pvvv7Ge98qVKwnad4VitsFibvqYO7d0/LixeQAAaVxkpDRhgvVrQxER1rWMGaUZM6yzsQGkWYGBgUZHAAAAQBKzWCzq06ePvv76a23fvl0FCxa0u71gwYLKlSuXNm3apLJly0qSwsPDtWPHDn3yySeSpHLlysnd3V2bNm2Sv7+/JOny5cv6448/NGHCBElSpUqVFBoaql9//VUVKlSQJP3yyy8KDQ21Fbzjg2K2wdj0EQDgMC5ckNq3l3bsiF6rUEFaulQqXNi4XAAAAACQSiRkpEZK6N27t5YtW6Zvv/1W3t7etvnVPj4+SpcunUwmk/r166exY8fqhRde0AsvvKCxY8cqffr0atOmje3cLl26aMCAAcqWLZuyZs2qgQMHqlSpUqpdu7YkqXjx4qpfv766deumL7/8UpLUvXt3NW7cWEWLFo13XorZBosaMSIxXgQAYKBVq6Tu3aUbN6zHJpP04YfSiBGSu7ux2QAAAAAAyWLmzJmSpOrVq9utBwYGqmPHjpKsG4Dfv39fvXr10o0bN/Tqq69q48aN8o7RmTt58mS5ubnJ399f9+/fV61atbRgwQK5urrazlm6dKn69u2runXrSpKaNm2qGTNmJCivyWKxWJ7hdTqtW7duycfHRzdu3FDmzJmNjqO8ea1jRvz8rONIYRyz2ayQkBD5+vrKxcXF6DhwILw38Dip5r0RHCw9/7x0/771OF8+ackSqWpVY3M5sVTz3kCSu3nzprJkyaLQ0FBlypTJ6DgOI13Zd42OAMDJ3NiXsOIHAHg5SEtv1Uk/J/tz7Ax4Ldmfwyj8dAUAQFqXK5c0ebL1ur+/9PvvFLIBAAAAAA7HQX4nAQAAUkxkpPXi4RG91r27tTu7du2U2V4bAAAAANIgftxKHDqzDRQUZB0xAgBAirl40VqwHjjQft1kkurU4ZMVAAAAAMBh0ZltoOHDo6/HmJcOAEDyWL1a6tbNusnj9u1S/fpSw4ZGpwIAAACANMNEA1Gi0JltoNu3o6+PGWNcDgBAKnfnjtS1q9SypbWQLVl3IOY3qQAAAAAAJ0JntkFijhjx87PWFwAASHK//Sa1aSP99Vf02ptvSl9+KWXJYlwuAAAAAEiDaMxOHDqzDRAUJPn7Rx/TGAcASHJms/TJJ1KlStGF7AwZpPnzpZUrKWQDAAAAAJwOndkGiDkrW2LECAAgid24IbVoIW3bFr1Wvry0bJn0wgvG5QJgqL///lunTp1S1apVlS5dOlksFmY2AgAApDA+fyUOndkGiDkrOyiIESMAgCTm7S2Fh1uvm0zSkCHS7t0UsoE06tq1a6pdu7aKFCmihg0b6vLly5Kkrl27asCAAQanAwAAAOKPYnYKY1Y2ACDZublJS5ZIL74obd0qjR0rubsbnQqAQfr37y83NzedP39e6dOnt623atVK69evNzAZAABA2mMyJf8lNWPMSAqLOWKEWdkAgCSxf7/1v+XKRa8995x0+LDkwu+tgbRu48aN2rBhg/LmzWu3/sILL+jcuXMGpQIAAAASjp9wU1BQkHTiRPQxs7IBAIliNksTJlg3eWzVyn6OlUQhG4Ak6e7du3Yd2VGuXr0qT09PAxIBAACkXS4mU7JfUrNn+ik3IiJCmzdv1pdffqnb//3g/M8//+jOnTtJGi41CQqS/P2jj4sVY8QIACARLl2S6tSR3n9fevhQOnVKmjTJ6FQAHFDVqlW1aNEi27HJZJLZbNann36qGjVqGJgMAAAASJgEjxk5d+6c6tevr/PnzyssLEx16tSRt7e3JkyYoAcPHmjWrFnJkdPpxRwvItGVDQBIhK+/lrp2la5ftx6bTNLgwdaNHgHgEZ9++qmqV6+u3377TeHh4Ro8eLCOHj2q69ev6+effzY6HgAAQJqSyhunk12CO7Pfe+89lS9fXjdu3FC6dOls682aNdOWLVuSNFxqEvOb30FBdGUDAJ7B3btS9+5S8+bRhWw/P2nLFmn8eMnDw9h8ABxSiRIldPjwYVWoUEF16tTR3bt31bx5cx08eFCFChUyOh4AAAAQbwnuzN61a5d+/vlneTzyA3OBAgV06dKlJAuWWvn5UcgGADyDAwekNm2kP/+MXmvRQpo9W8qa1bhcAJxCrly5NGrUKKNjAAAApHkmWrMTJcGd2WazWZGRkbHWL168KG9v7yQJldoEBVlHmwIA8Exu3JCqVYsuZKdPL82da/0HhkI2gKdYv369du3aZTv+/PPPVaZMGbVp00Y3btwwMBkAAACQMAkuZtepU0dTpkyxHZtMJt25c0cjRoxQw4YNkzJbqhFzXjb1fgBAgmXJIo0ebb1erpx08KDUpQvD1gDEy6BBg3Tr1i1J0pEjRxQQEKCGDRvq9OnTCggIMDgdAABA2uJiSv5LapbgMSOTJ09WjRo1VKJECT148EBt2rTRX3/9pezZs2v58uXJkdHpxZyXzcaPAIB4sVjsi9XvvSdlzCi9/TazsQEkyJkzZ1SiRAlJ0urVq9WkSRONHTtWBw4coBkFAAAATiXBxew8efLo0KFDWrFihfbv3y+z2awuXbqobdu2dhtCIjbmZQMAnuruXSkgwDo+ZNy46HUXF6lbN+NyAXBaHh4eunfvniRp8+bN6tChgyQpa9asto5tAAAApAxmZidOgovZO3fuVOXKldWpUyd16tTJth4REaGdO3eqatWqSRoQAIA04+BBqXVr62xsk0mqW1eqUcPoVACc3P/+9z8FBATotdde06+//qqVK1dKkk6ePKm8efManA4AAACIvwTPzK5Ro4auX78eaz00NFQ1+IEbAICEM5ulzz6TXn01epPHdOmk4GBjcwFIFWbMmCE3NzetWrVKM2fOlJ+fnyTpxx9/VP369Q1OBwAAkLaYTMl/Sc0S3JltsVjibIe/du2aMmTIkCShUpOgIOnSJaNTAAAc1j//WOdgb94cvfbyy9KyZVLRosblApBq5M+fX999912s9cmTJxuQBgAAAHh28S5mN2/eXJJ1rkvHjh3l6elpuy0yMlKHDx9W5cqVkz6hkxs+PPq6t7dxOQAADujbb6UuXaRr16zHJpM0aJB1t2A2eQSQRA4cOCB3d3eVKlVKkvTtt98qMDBQJUqU0MiRI+XB3zcAAAApxqRU3jqdzOI9ZsTHx0c+Pj6yWCzy9va2Hfv4+ChXrlzq3r27lixZkpxZnU5QkHTiRPTxmDHGZQEAOJD796V33pHeeCO6kJ0nj7U7+5NPKGQDSFI9evTQyZMnJUmnT5/WW2+9pfTp0ysoKEiDBw82OB0AAAAQf/HuzA4MDJQkPffccxo4cCAjReIhZld2sWJSy5bGZQEAOBBXV2nfvujjZs2kOXOkbNmMywQg1Tp58qTKlCkjSQoKClLVqlW1bNky/fzzz3rrrbc0ZcoUQ/MBAACkJS40ZidKgjeAHDFiBIXseLp9O/o6XdkAABsPD2npUilHDmn2bGn1agrZAJKNxWKR2WyWJG3evFkNGzaUJOXLl09Xr141MhoAAACQIAneAFKSVq1apa+++krnz59XeHi43W0HDhxIkmCpiZ8fXdkAkKZdvizdumW/oWPRotLZs1L69IbFApA2lC9fXh999JFq166tHTt2aObMmZKkM2fOKGfOnAanAwAASFtMJlqzEyPBndnTpk1Tp06d5Ovrq4MHD6pChQrKli2bTp8+rQYNGiRHRgAAnNfatVKpUlLz5tZZ2TFRyAaQAqZMmaIDBw7o3Xff1dChQ1W4cGFJ1gYVNnAHAACAM0lwZ/YXX3yh2bNnq3Xr1lq4cKEGDx6s559/XsOHD9f169eTI6NTCgqSLl0yOgUAwDD37kkDB0r/dUDq2jVp9Ghp3DhjcwFIc0qXLq0jR47EWv/000/l6upqQCIAAIC0i8bsxElwZ/b58+dtHRzp0qXT7f8GQ7dv317Lly9P2nROLObmj97exuUAABjg99+l8uWjC9mS9MYb1uI2ADgILy8vubu7Gx0DAAAAiLcEF7Nz5cqla9euSZIKFCigvXv3SrLO3LNYLEmbzomx+SMApEFmszR5slShgnT8uHUtXTrpyy+lNWvY5BGAISIjIzVx4kRVqFBBuXLlUtasWe0uAAAASDkuJlOyX1KzBBeza9asqXXr1kmSunTpov79+6tOnTpq1aqVmjVrluAAX3zxhQoWLCgvLy+VK1dOP/300xPPDwsL09ChQ1WgQAF5enqqUKFCmj9/foKfN6Ww+SMApBGXL0sNGkgBAVLU5shly0oHDkjdu/NdMgCGGTVqlCZNmiR/f3+FhoYqICBAzZs3l4uLi0aOHGl0PAAAACDeEjwze/bs2TKbzZKknj17KmvWrNq1a5eaNGminj17JuixVq5cqX79+umLL77Qa6+9pi+//FINGjTQsWPHlD9//jjv4+/vr3///Vfz5s1T4cKFFRISooiIiIS+DAAAks7du1K5ctaCdpSBA6WPPpI8PY3LBQCSli5dqjlz5qhRo0YaNWqUWrdurUKFCql06dLau3ev+vbta3REAACANIM+p8RJcDHbxcVFLi7RDd3+/v7y9/eXJF26dEl+fn7xfqxJkyapS5cu6tq1qyTrTusbNmzQzJkzNS6ODbLWr1+vHTt26PTp07avRD733HMJfQkAACStDBmkXr2kYcOk3LmlRYuk2rWNTgUAkqTg4GCVKlVKkpQxY0aFhoZKkho3bqxhw4YZGQ0AAABIkAQXs+MSHBysjz/+WHPnztX9+/fjdZ/w8HDt379fH3zwgd163bp1tXv37jjvs3btWpUvX14TJkzQ4sWLlSFDBjVt2lRjxoxRunTp4rxPWFiYwsLCbMe3bt2SJJnNZluHefIw/XexyGxmlrgzMJvNslgsyfy+gDPivYHHsXtvvP++TGFhsvTpI2XPbp2fjTSLvzfwOEa8J/LmzavLly8rf/78Kly4sDZu3KiXX35Z+/btkyffHgEAAEhRJlqzEyXexeybN2+qd+/e2rhxo9zd3fXBBx/o3Xff1ciRIzVx4kS9+OKLCZpdffXqVUVGRipnzpx26zlz5lRwcHCc9zl9+rR27dolLy8vff3117p69ap69eql69evP/a5x40bp1GjRsVav3LlisKjZpomsXXrPHXpUhZJ1h9YQkKuJMvzIGmZzWaFhobKYrHYffsA4L0BO2az0s+ZI9PDh7rdq5f9e6N3b2sROyTE6JQwGH9v4HGiuqJTUrNmzbRlyxa9+uqreu+999S6dWvNmzdP58+fV//+/VM8DwAAAPCs4l3M/vDDD7Vz5069/fbbWr9+vfr376/169frwYMH+vHHH1WtWrVnCvDobyMsFstjf0NhNptlMpm0dOlS+fj4SLKOKmnZsqU+//zzOLuzhwwZooCAANvxrVu3lC9fPuXIkUOZM2d+psxPM2lSdH4fHxf5+vomy/MgaUW9v3LkyEHhAXZ4b8Dm8mWZOnWSadMmWVxdla5ePZkKF+a9gVj4ewOP4+HhkeLPOX78eNv1li1bKm/evNq9e7cKFy6spk2bpngeAACAtIzG7MSJdzH7+++/V2BgoGrXrq1evXqpcOHCKlKkiKZMmfJMT5w9e3a5urrG6sIOCQmJ1a0dJXfu3PLz87MVsiWpePHislgsunjxol544YVY9/H09Izz65OPzv5OSrdvR18fM8YkFxfepc7CZDIl63sDzov3BvTdd1KnTtLVq5IkU2SkXPbskemFF3hvIE78vYG4OML7oWLFiqpYsaLRMQAAAIAEi3cx+59//lGJEiUkSc8//7y8vLxsGzc+Cw8PD5UrV06bNm1Ss2bNbOubNm3S66+/Hud9XnvtNQUFBenOnTvKmDGjJOnkyZNycXFR3rx5nzlLcvHzk1q2NDoFACBR7t+XBg2SPv88ei1XLmnhQusmj4wUAeCA1q5dG+9z6c4GAABIOS60ZidKvIvZZrNZ7u7utmNXV1dlyJAhUU8eEBCg9u3bq3z58qpUqZJmz56t8+fPq2fPnpKsI0IuXbqkRYsWSZLatGmjMWPGqFOnTho1apSuXr2qQYMGqXPnzo/dADKlBQVJly4ZnQIAkCQOH5batJGOHo1ea9pUmjePTR4BOLQ33ngjXueZTCZFRkYmbxgAAAAgicS7mG2xWNSxY0fbyI4HDx6oZ8+esQraa9asifeTt2rVSteuXdPo0aN1+fJllSxZUj/88IMKFCggSbp8+bLOnz9vOz9jxozatGmT+vTpo/Llyytbtmzy9/fXRx99FO/nTG7Dh0df9/Y2LgcAIBEsFmnaNOn996WwMOtaunTSpElSjx4MOQPg8Mz8sg0AAMAh8dNk4sS7mP3222/bHbdr1y5JAvTq1Uu9evWK87YFCxbEWitWrJg2bdqUJM+dHOznZRuXAwCQCGFh0pw50YXsl16Sli+Xihc3NhcAJMAff/yhkiVLPvGc8ePH64MPPkihRAAAAEDixLuYHRgYmJw5Uh3mZQOAE/PykpYtk159VerVSxo7VopjM2EAcGT16tXTzz//rOeeey7O2z/55BONGDGCYjYAAEAKMvFN30Qxfjv1VIR52QDgpO7fly5etF8rXVr6+2/ps88oZANwSlWqVFGdOnUUEsdGtZ9++qmGDRumJUuWGJAMAAAAeDYUs5MQ87IBwAkdPiy98or0+utSeLj9bX5+xmQCgCSwZMkSFS5cWHXr1lVoaKht/bPPPtOHH36oRYsW6c033zQwIQAAQNrjYkr+S2pGMTsJMS8bAJyIxSJNnSpVqCAdPSodOCCNGGF0KgBIMm5ublqzZo0yZsyoxo0b68GDB5oyZYo++OADLVy4UG+99ZbREQEAAIAEiffMbMQf87IBwMH9+6/UsaO0fn30WunSUhJtbgwAjiJdunT6/vvvVa1aNZUrV04nT55UYGCg2rRpY3Q0AACANImZ2YlDMRsAkLZ8/73UqZN05Ur0Wr9+0rhx1o0fASCVWLt2re36O++8o/fee0/NmjVTpkyZ7G5r2rSpEfEAAACABHumYvbixYs1a9YsnTlzRnv27FGBAgU0ZcoUFSxYUK+//npSZ3QKbP4IAA7u/n1p8GBpxozotZw5pQULpPr1DYsFAMnljTfeiLW2atUqrVq1ynZsMpkUGRmZgqkAAADSNhqzEyfBM7NnzpypgIAANWzYUDdv3rR9+M2cObOmTJmS1PmcBps/AoADCwuTKlWyL2Q3biwdOUIhG0CqZTabn3qhkA0AAABnkuBi9vTp0zVnzhwNHTpUrq6utvXy5cvryJEjSRrOmbD5IwA4ME9PqWFD63UvL2tRe+1aKUcOY3MBAAAAANIUk8mU7JfULMFjRs6cOaOyZcvGWvf09NTdu3eTJJQzY/NHAHBQo0ZJ//wjDRokvfii0WkAAAAAAEACJbiYXbBgQR06dEgFChSwW//xxx9VokSJJAvmTJiXDQAO5scfpYsXpW7dotfc3a3zsQEAAAAAMIhL6m6cTnYJLmYPGjRIvXv31oMHD2SxWPTrr79q+fLlGjdunObOnZscGR0e87IBwEE8eCC9/740bZrk4SG98opUpozRqQAAAAAAQBJIcDG7U6dOioiI0ODBg3Xv3j21adNGfn5+mjp1qt56663kyOjQgoKkEyeij5mXDQAG+eMPqU0b66aOkhQeLs2fby1sAwAAAADgAFL7TOvkluBitiR169ZN3bp109WrV2U2m+Xr65vUuZxGzK7sYsWYlw0AKc5ikT7/XBo4UAoLs655ekoTJ0q9exubDQAcxM2bN7Vq1SqdOnVKgwYNUtasWXXgwAHlzJlTfn5+RscDAAAA4iXBxexRo0apXbt2KlSokLJnz54cmZzK7dvR1+nKBoAUFhIide4sff999FrJktLy5db/AgB0+PBh1a5dWz4+Pjp79qy6deumrFmz6uuvv9a5c+e0aNEioyMCAACkGfRlJ45LQu+wevVqFSlSRBUrVtSMGTN05cqV5MjlFGJu/OjnR1c2AKSo9eul0qXtC9l9+0r79lHIBoAYAgIC1LFjR/3111/y8vKyrTdo0EA7d+40MBkAAACQMAkuZh8+fFiHDx9WzZo1NWnSJPn5+alhw4ZatmyZ7t27lxwZHRYbPwKAQR4+tBau//3XeuzrK/3wgzR1qhSjUAMAkPbt26cePXrEWvfz81NwcLABiQAAANIuF5Mp2S+pWYKL2ZL04osvauzYsTp9+rS2bdumggULql+/fsqVK1dS53NojBgBAIO4u0tLl0publLDhtLhw1KDBkanAgCH5OXlpVu3bsVa//PPP5UjRw4DEgEAAADP5pmK2TFlyJBB6dKlk4eHhx4+fJgUmZwOI0YAIJlZLFJoqP3aK69Ie/dK330n5cxpTC4AcAKvv/66Ro8ebfusbjKZdP78eX3wwQdq0aKFwekAAADSFpMp+S+p2TMVs8+cOaOPP/5YJUqUUPny5XXgwAGNHDmSrykCAJJeSIjUtKm1Azsiwv62cuVS/7/UAJBIEydO1JUrV+Tr66v79++rWrVqKly4sLy9vfXxxx8bHQ8AAACIN7eE3qFSpUr69ddfVapUKXXq1Elt2rSRn59fcmQDAKR1GzZIb78dPRv7o4+kkSMNjQQAziZTpkzatWuXtm7dqgMHDshsNuvll19W7dq1jY4GAACQ5phoyEqUBBeza9Sooblz5+rFF19MjjxOIyhIunTJ6BQAkEo9eCANGSJNmRK95usrVahgWCQAcHY1a9ZUzZo1jY4BAAAAPLMEF7PHjh2bHDmczvDh0de9vY3LAQCpzrFjUuvW1k0dozRoIAUGMhsbAJ7Rli1btGXLFoWEhMhsNtvdNn/+fINSAQAApD00ZidOvIrZAQEBGjNmjDJkyKCAgIAnnjtp0qQkCebobt+Ovj5mjHE5ACDVsFikmTOlAQOsndmS5Okpffqp9O67/IsPAM9o1KhRGj16tMqXL6/cuXPz1VYAAAA4rXgVsw8ePGjb/fzgwYPJGsjZ+PlJLVsanQIAnFxEhNSihbR2bfTaiy9Ky5dLpUoZlwsAUoFZs2ZpwYIFat++vdFRAAAA0jwXGgsSJV7F7G3btsV5HQCAJOHmJj33XPTxu+9KEyZI6dIZFgkAUovw8HBVrlzZ6BgAAABAorkk9A6dO3fW7ZgzNv5z9+5dde7cOUlCOTo2fwSAZPDJJ1KtWtJ330nTp1PIBoAk0rVrVy1btszoGAAAAJB1gmZyX1KzBG8AuXDhQo0fP17ej+x6eP/+fS1atCjVbyATFCT5+0cfs/kjADyDY8ek48eto0WieHlJmzcblwkAUpGY+9yYzWbNnj1bmzdvVunSpeXu7m53blrZ8wYAAADOL97F7Fu3bslischisej27dvy8vKy3RYZGakffvhBvr6+yRLSkQwfbn/M5o8AkAAWizRrlhQQYP11cYkSUvHiRqcCgFTn0X1uypQpI0n6448/7NbZDBIAACBl8fkrceJdzM6cObNMJpNMJpOKFCkS63aTyaRRo0YlaThHFHPCSlAQmz8CQLxduSJ17Wq/yePo0dZNHgEASYp9bgAAAJAaxbuYvW3bNlksFtWsWVOrV69W1qxZbbd5eHioQIECypMnT7KEdER+fhSyASDeNm2SOnSQgoOj13r3lj791LhMAJBGhIaGKjIy0u7zuyRdv35dbm5uypQpk0HJov27Z5rREQA4mfPX7hkdAYCTKZIzvdERJD3DBoawE+9idrVq1SRJZ86cUf78+dNkSzwbPwJAAoWFSR9+KMWcx5ojhzR/vtS4sXG5ACANeeutt9SkSRP16tXLbv2rr77S2rVr9cMPPxiUDAAAAEiYeBWzDx8+rJIlS8rFxUWhoaE6cuTIY88tXbp0koVzNDHnZbPxIwA8xfHjUps20qFD0Wv160uBgVKuXIbFAoC05pdffolzk8fq1atr6NChBiQCAABIu9Jig3BSilcxu0yZMgoODpavr6/KlCkjk8kki8US6zyTyaTIyMgkD+koYs7LZuNHAHgCs1lq3lw6ccJ67OEhffKJ1Lev5MKXqgAgJYWFhSkiIiLW+sOHD3X//n0DEgEAAKRdLtSyEyVexewzZ84oR44ctutpHfOyAeApXFykL7+UatSQihWTli2TXnrJ6FQAkCa98sormj17tqZPn263PmvWLJUrV86gVAAAAEDCxauYXaBAgTivAwBgExEhucX4Z6VqVenbb6VataR06YzLBQBp3Mcff6zatWvr999/V61atSRJW7Zs0b59+7Rx40aD0wEAAKQtdGYnToK/671w4UJ9//33tuPBgwcrc+bMqly5ss6dO5ek4QAATiAsTBo4UGrY0DpeJKbGjSlkA4DBXnvtNe3Zs0f58uXTV199pXXr1qlw4cI6fPiwqlSpYnQ8AAAAIN4SXMweO3as0v1XmNizZ49mzJihCRMmKHv27Orfv3+SB3QUQUHSpUtGpwAAB3PihFSpkvTZZ9KmTdb/AgAcTpkyZbR06VIdPXpUv/32m+bPn68XXnjB6FgAAABpjslkSvZLQuzcuVNNmjRRnjx5ZDKZ9M0339jd3rFjx1iPX7FiRbtzwsLC1KdPH2XPnl0ZMmRQ06ZNdfHiRbtzbty4ofbt28vHx0c+Pj5q3769bt68meA/vwQXsy9cuKDChQtLkr755hu1bNlS3bt317hx4/TTTz8lOICzGD48+rq3t3E5AMAhWCzWmdgvvywdPGhd8/CQvLyMzQUAkCTdunXL7vqTLgAAAEi77t69q5deekkzZsx47Dn169fX5cuXbZcffvjB7vZ+/frp66+/1ooVK7Rr1y7duXNHjRs3VmRkpO2cNm3a6NChQ1q/fr3Wr1+vQ4cOqX379gnOG6+Z2TFlzJhR165dU/78+bVx40ZbN7aXl1eq3Q09KMjafBhlzBjjsgCA4a5dk7p2lWL+trZ4cesmj2XKGJUKABBDlixZdPnyZfn6+ipz5sxxduhYLBaZTCa7HzIAAACQvBxtZnaDBg3UoEGDJ57j6empXLlyxXlbaGio5s2bp8WLF6t27dqSpCVLlihfvnzavHmz6tWrp+PHj2v9+vXau3evXn31VUnSnDlzVKlSJf35558qWrRovPMmuJhdp04dde3aVWXLltXJkyfVqFEjSdLRo0f13HPPJfThnELMruxixaSWLY3LAgCG2rJF6tBB+uef6LV33pEmTpTSpzcuFwDAztatW5U1a1ZJ0rZt2wxOAwAAAGe2fft2W5NEtWrV9PHHH8vX11eStH//fj18+FB169a1nZ8nTx6VLFlSu3fvVr169bRnzx75+PjYCtmSVLFiRfn4+Gj37t3JW8z+/PPP9X//93+6cOGCVq9erWzZstmCt27dOqEP5xRu346+Tlc2gDTJYpHef99atLZYrGvZs0vz5klNmxqbDQAQS7Vq1eK8DgAAAGMlcKT1MwkLC1NYWJjdmqenpzw9PRP8WA0aNNCbb76pAgUK6MyZMxo2bJhq1qyp/fv3y9PTU8HBwfLw8FCWLFns7pczZ04FBwdLkoKDg23F75h8fX1t58RXgovZmTNnjnOGyqhRoxL6UE4h5saPfn50ZQNIo0wm6caN6EJ2nTrSwoVS7tzG5gIAxOnw4cPxPrd06dLJmAQAAAApbdy4cbFqtSNGjNDIkSMT/FitWrWyXS9ZsqTKly+vAgUK6Pvvv1fz5s0fe7+okXZRnjT2LiESXMyWpJs3b2revHk6fvy4TCaTihcvri5dusjHx+dZHs6hsfEjAPxn8mRp716pUyepXz/JJcF7CAMAUkiZMmVkMplkifol5GMwMxsAACBluaRAa/aQIUMUEBBgt/YsXdlxyZ07twoUKKC//vpLkpQrVy6Fh4frxo0bdt3ZISEhqly5su2cf//9N9ZjXblyRTlz5kzQ8ye4mP3bb7+pXr16SpcunSpUqCCLxaLJkydr7Nix2rhxo15++eWEPqRDY8QIgDTp2jXp8GGpRo3otYwZpYMHJbdn+j0oACAFnTlzxugIAAAAMMizjhSJj2vXrunChQvK/d83tcuVKyd3d3dt2rRJ/v7+kqTLly/rjz/+0IQJEyRJlSpVUmhoqH799VdVqFBBkvTLL78oNDTUVvCOrwRXJPr376+mTZtqzpw5cvuvoBEREaGuXbuqX79+2rlzZ0If0ikwYgRAmhG1yePt29KhQ9Lzz0ffRiEbAJxCgQIFjI4AAACAODjad5zv3Lmjv//+23Z85swZHTp0SFmzZlXWrFk1cuRItWjRQrlz59bZs2f14YcfKnv27GrWrJkkycfHR126dNGAAQOULVs2Zc2aVQMHDlSpUqVUu3ZtSVLx4sVVv359devWTV9++aUkqXv37mrcuHGCNn+UnrEzO2YhW5Lc3Nw0ePBglS9fPqEPBwBwFOHh0v/9n/0mj337St99Z2wuAECinTx5Utu3b1dISIjMZrPdbcNjztUDAABAmvLbb7+pRoxvZUeNJ3n77bc1c+ZMHTlyRIsWLdLNmzeVO3du1ahRQytXrpR3jHnMkydPlpubm/z9/XX//n3VqlVLCxYskKurq+2cpUuXqm/fvqpbt64kqWnTpnHuy/g0CS5mZ8qUSefPn1exYsXs1i9cuGD3IgAATuTPP6U2baQDB6LXateWZs82LhMAIEnMmTNH77zzjrJnz65cuXLF2oiHYjYAAEDKSYGR2QlSvXr1J+6zsmHDhqc+hpeXl6ZPn67p06c/9pysWbNqyZIlz5QxpgQXs1u1aqUuXbpo4sSJqly5skwmk3bt2qVBgwapdevWiQ4EAEhBFos0b5703nvSvXvWNXd3adw4qX9/NnkEgFTgo48+0scff6z333/f6CgAAABAoiS4mD1x4kSZTCZ16NBBERERkiR3d3e98847Gj9+fJIHBAAkk+vXpW7dpDVroteKFZOWLZPKljUuFwAgSd24cUNvvvmm0TEAAAAgycXRWrOdTIJb7jw8PDR16lTduHFDhw4d0sGDB3X9+nVNnjw52XbJBAAkMYtFqlfPvpDdo4e0fz+FbABIZd58801t3LjR6BgAAABAosW7M/vevXsaNGiQvvnmGz18+FC1a9fWtGnTlD179uTMBwBIDiaT9NFHUv36UrZs0ty50htvGJ0KAJBEpk2bZrteuHBhDRs2THv37lWpUqXk7u5ud27fvn1TOh4AAECaRWN24sS7mD1ixAgtWLBAbdu2lZeXl5YvX6533nlHQUFByZkPAJBc6tWzbvDYqJGUJ4/RaQAASWjy5Ml2xxkzZtSOHTu0Y8cOu3WTyUQxGwAAAE4j3sXsNWvWaN68eXrrrbckSe3atdNrr72myMhIubq6JltAIwUFSZcuGZ0CABIpapPHLVus87Bj/hq4WzfjcgEAks2ZM2eMjgAAAIA4uNCZnSjxnpl94cIFValSxXZcoUIFubm56Z9//kmWYI5g+PDo697exuUAgGd2/brUsqW1aL1ihTRzptGJAAAAAAAAnkm8i9mRkZHy8PCwW3Nzc1NERESSh3IUt29HXx8zxrgcAPBMtm2TSpe23+Txzz+NywMAMETLli01fvz4WOuffvqp3nzzTQMSAQAApF0uJlOyX1KzeI8ZsVgs6tixozw9PW1rDx48UM+ePZUhQwbb2pqYRZNUws/P2tgIAE4hPNz61ZIJE6wjRiQpa1brJo/NmhmbDQCQ4nbs2KERI0bEWq9fv74mTpxoQCIAAADg2cS7mP3222/HWmvXrl2ShgEAJNLJk1KbNtL+/dFrNWtKixZZfzMHAEhz7ty5E+sblpLk7u6uW7duGZAIAAAg7UrljdPJLt7F7MDAwOTMAQBIDItFmj9f6ttXunfPuubuLn38sTRggOQS76lSAIBUpmTJklq5cqWGx9wQRtKKFStUokQJg1IBAAAACRfvYjYAwMFt2RJdyC5SRFq2TCpXzthMAADDDRs2TC1atNCpU6dUs2ZNSdKWLVu0fPlyBQUFGZwOAAAgbXGhMztRKGYDQGpgMkkzZ0q7d0t160qTJ0sx9jMAAKRdTZs21TfffKOxY8dq1apVSpcunUqXLq3NmzerWrVqRscDAAAA4o1iNgA4o4cPpePHpdKlo9d8fKSDB6UsWYzLBQBwSI0aNVKjRo2MjgEAAJDmmURrdmIwRPUxgoKkS5eMTgEAcfjrL6lyZal6deniRfvbKGQDAAAAAIBUimL2Y8TcH8fb27gcAGATtclj2bLSb79JN25IXboYnQoA4OAiIyM1ceJEVahQQbly5VLWrFntLgAAAEg5Lqbkv6Rmz1TMXrx4sV577TXlyZNH586dkyRNmTJF3377bZKGM9Lt29HXx4wxLgcASLIWrlu1shav7961rr3wgvTxx8bmAgA4pObNm+vWrVuSpFGjRmnSpEny9/dXaGioAgIC1Lx5c7m4uGjkyJHGBgUAAAASIMHF7JkzZyogIEANGzbUzZs3FRkZKUnKnDmzpkyZktT5DOfnJ7VsaXQKAGnajh3W2dhBQdFrXbpIBw5I5csblwsA4LB8fHxkMlnbcpYuXarZs2dr4MCBcnNzU+vWrTV37lwNHz5ce/fuNTgpAABA2kJnduIkuJg9ffp0zZkzR0OHDpWrq6ttvXz58jpy5EiShgOANO3hQ+nDD6UaNaJnY2fJIq1aJc2dK2XMaGw+AIDDCgwMlPd/s/IuX76s0v9tGJwxY0aFhoZKkho3bqzvv//esIwAAABAQiW4mH3mzBmVLVs21rqnp6fuRn31HQCQeK+/Lo0bZ52VLVk3fPz9d6lFC0NjAQAcn6urq0JCQiRJefPmVXBwsCSpcOHC2rhxoyRp37598vT0NCwjAABAWmQymZL9kpoluJhdsGBBHTp0KNb6jz/+qBIlSiRFJsMFBUmXLhmdAkCa17279b9ubtL48dLmzVK+fMZmAgA4hTVr1ihLliySpCZNmmjDhg2SpPfee0/Dhg3TCy+8oA4dOqhz585GxgQAAAASxC2hdxg0aJB69+6tBw8eyGKx6Ndff9Xy5cs1btw4zZ07Nzkyprjhw6Ov//ftTABIeW+8IY0eLdWvL73yitFpAABO5PXXX7dd/+yzz2zXW7Zsqbx582r37t0qXLiwmjZtakQ8AACANCu1z7RObgkuZnfq1EkREREaPHiw7t27pzZt2sjPz09Tp07VW2+9lRwZU9zt29HXx4wxLgeANGTnTunrr6VJk6SYXwkaNsy4TACAVKlixYqqWLGi0TEAAACABEvwmBFJ6tatm86dO6eQkBAFBwfrwoUL6tKlS1JnM5yfn9SypdEpAKRqDx9KQ4da52FPmSItXGh0IgBAKrNw4UK7jR4HDx6szJkzq3Llyjp37pyByQAAANIekyn5L6nZMxWzo2TPnl2+vr5JlQUA0pZTp6T//U8aOzZ6k8fVq6OvAwCQBMaOHat06dJJkvbs2aMZM2ZowoQJyp49u/r3729wOgAAACD+EjxmpGDBgk/cFfP06dOJCgQAqZ7FIi1aJL37rnTnjnXNzc0612jQoNT/a1QAQIq6cOGCChcuLEn65ptv1LJlS3Xv3l2vvfaaqlevbmw4AACANMaFn/kTJcHF7H79+tkdP3z4UAcPHtT69es1aNCgpMoFAKnTzZtSz57SypXRa4ULS8uWsckjACBZZMyYUdeuXVP+/Pm1ceNGWze2l5eX7t+/b3A6AAAAIP4SXMx+77334lz//PPP9dtvvyU6EACkWj/9JLVrJ50/H73WubM0daqUMaNxuQAAqVqdOnXUtWtXlS1bVidPnlSjRo0kSUePHtVzzz1nbDgAAIA0xoXG7ERJ1MzsmBo0aKDVq1cn1cMBQOozZUp0ITtzZumrr6R58yhkAwCS1eeff65KlSrpypUrWr16tbJlyyZJ2r9/v1q3bm1wOgAAACD+EtyZ/TirVq1S1qxZk+rhDBMUJF26ZHQKAKnSl19Ke/ZIRYpIixdL+fIZnQgAkAbcunVL06ZNk4uLfR/LyJEjdeHCBYNSAQAApE2MzE6cBBezy5Yta7cBpMViUXBwsK5cuaIvvvgiScMZYfjw6Ove3sblAODkLBbp8mUpT57otezZraNGnntOcnU1LBoAIG0pWLCgLl++LF9fX7v169evq2DBgoqMjDQoGQAAAJAwCS5mv/HGG3bHLi4uypEjh6pXr65ixYolVS7D3L4dfX3MGONyAHBiUZs8btsmHT4s5cwZfVuhQobFAgCkTRaLJc71O3fuyMvLK4XTAAAApG0uojU7MRJUzI6IiNBzzz2nevXqKVeuXMmVySH4+UktWxqdAoDTeXSTx06dpO+/53tEAIAUFxAQIEkymUwaPny40qdPb7stMjJSv/zyi8qUKWNQOgAAACDhElTMdnNz0zvvvKPjx48nVx4AcE4REdLo0dLHH0tms3Utc2apY0cK2QAAQxw8eFCStTP7yJEj8vDwsN3m4eGhl156SQMHDjQqHgAAQJpEiSBxEjxm5NVXX9XBgwdVoECB5MgDAM7n9GmpbVtp797otapVrZs85s9vXC4AQJq2bds2SVKnTp00depUZcqUyeBEAAAAQOIkuJjdq1cvDRgwQBcvXlS5cuWUIUMGu9tLly6dZOEAwKFZLNKSJVLv3tED911drR3a77/PJo8AAIcQGBhodAQAAAD8x4XO7ESJdzG7c+fOmjJlilq1aiVJ6tu3r+02k8kki8Uik8nEbugA0o5evaRZs6KPCxWSli2TKlQwLhMAAHHYt2+fgoKCdP78eYWHh9vdtmbNGoNSAQAAAAnjEt8TFy5cqAcPHujMmTOxLqdPn7b9N6G++OILFSxYUF5eXipXrpx++umneN3v559/lpubG5vWADBOlSrR1zt2lA4epJANAHA4K1as0GuvvaZjx47p66+/1sOHD3Xs2DFt3bpVPj4+RscDAABIU1xMpmS/pGbx7sy2WCySlKSzsleuXKl+/frpiy++0GuvvaYvv/xSDRo00LFjx5T/CXNmQ0ND1aFDB9WqVUv//vtvkuUBgARp00bavdta1P7vWysAADiasWPHavLkyerdu7e8vb01depUFSxYUD169FDu3LmNjgcAAADEW7w7syXrOJGkNGnSJHXp0kVdu3ZV8eLFNWXKFOXLl08zZ8584v169OihNm3aqFKlSkmaBwAex/XcOenTT2PfMGMGhWwAgEM7deqUGjVqJEny9PTU3bt3ZTKZ1L9/f82ePdvgdAAAAGmLyZT8l9QsQcXsIkWKKGvWrE+8xFd4eLj279+vunXr2q3XrVtXu3fvfuz9AgMDderUKY0YMSIh0QHg2S1Zomy1a8vlgw+koCCj0wAAkCBZs2bV7f82Kvbz89Mff/whSbp586bu3btnZDQAAAAgQeI9ZkSSRo0alWRz9a5evarIyEjlzJnTbj1nzpwKDg6O8z5//fWXPvjgA/30009yc4tf9LCwMIWFhdmOb926JUkym80ym81x3MP038Uis9kSr+dA6mA2m2WxWB7zvkCaFBoqU+/eclm+3LZk+eQTWZo3T/2/6kS88PcGHof3Bh4nJd8TnTt31tSpU1WlShVt2rRJpUqVkr+/v9577z1t3bpVmzZtUq1atVIsDwAAAJTqZ1ontwQVs9966y35+vomaYBHR5dYLJY4x5lERkaqTZs2GjVqlIoUKRLvxx83bpxGjRoVa/3KlSuxdnKXJLM5hyRXmc1mhYRciffzwPmZzWaFhobKYrHIxSVBX1pAKuT+66/yefdduV24YFu717Klbo8dK8sV/m6AFX9v4HF4b+BxQkNDU+y5Fi5cqPHjx2vGjBl68OCBJGnIkCFyd3fXrl271Lx5cw0bNizF8gAAAACJFe9idlLPy86ePbtcXV1jdWGHhITE6taWpNu3b+u3337TwYMH9e6770qK7npyc3PTxo0bVbNmzVj3GzJkiAICAmzHt27dUr58+ZQjRw5lzpzZ7tygIOnyZesPnC4uLkleuIdjM5vNMplMypEjB4WHtCwiQqaPP5Y++kim/7rnLD4+ujlunLy7dVMO3huIgb838Di8N/A4Hh4eKfZcURu4xxwF6OLiosGDB2vw4MEplgMAAADRaMxOnHgXs6M+DCcVDw8PlStXTps2bVKzZs1s65s2bdLrr78e6/xMmTLpyJEjdmtffPGFtm7dqlWrVqlgwYJxPo+np6c8PT1jrbu4uMT64XLkyOjr3t4mubjw7kprTCZTnO8NpBFnzkjt2kkx5/b/73+yLFqksHTp5MN7A3Hg7w08Du8NxCWl3w9J3ZACAAAAGCnexezkmO8XEBCg9u3bq3z58qpUqZJmz56t8+fPq2fPnpKsXdWXLl3SokWL5OLiopIlS9rd39fXV15eXrHWn9V/++JIksaMSZKHBOBMBg2KLmS7ulp/wzVkiPXXpiEhhkYDAOBZFClS5KkF7evXr6dQGgAAANDqkjgJmpmd1Fq1aqVr165p9OjRunz5skqWLKkffvhBBQoUkCRdvnxZ58+fT/Fcfn5Sy5Yp/rQAjDZ9urR9u5Qpk7RsmVSxonWdDdwAAE4qKTdwBwAAAIxmsiT1/BAHd+vWLfn4+OjGjRuxZmbnzStdumQtZl+8aEw+GMe66WeIfH19+Up4WnHvnpQ+vf3avn1S0aLWgvZ/eG/gcXhv4HF4b+Bxbt68qSxZsig0NFSZYvxbkxxcXFwUHBzsFPvA3HrAL44BJExw6AOjIwBwMkVypn/6SSlg4W8Xkv053i6fL9mfwyj8dAUg7YmIsI4QefFF6dGvVr/yil0hGwAAZ8W8bAAAAKQ2FLMBpC1nz0rVqkmjRlmv9+ghpa0vqAAA0og09gVMAAAAp2BKgUtqZujMbABIUcuWSe+8I926ZT12dZVKlbIWs+leAwCkMsmxgTsAAABgJIrZAFK/W7ek3r2lJUui1woWlJYulSpVMi4XAAAAAABIU1xopksUxowASN1275bKlLEvZLdrJx06RCEbAAAAAADAiVDMBpB6TZggVa0qnTljPc6UydqNvXgxmzwCAADg/9u777isyv+P468bkCFLHAwXaO6RM2empoJ7pDkwR5plbk0tNbdpubNMy1S0nJWa5ci9rRRXjp+puYNIU9wgcH5/8PXGW0BFhJvxfvY4jzjXuc45n3NzwHN/uO7PJSIikupUMzt5VGbkf777Di5ftnYUIvJceXhAdHTs19WqxY7OLlDAujGJiIiIiIiIiMgzUTL7f0aMiPva1dV6cYjIc/TWW7BxI5QsCcOGgZ1+5YmIiIiIiIiI9ahkdvIos/M/N2/GfT12rPXiEJFndOMG/PQTtG8f12YywbJl+pdCRERERERERCQDUDL7EXnyQKtW1o5CRJJk797YJPbZs5AtGzRqFLdNiWwRERERERERSSNMylMkiyaAFJH0Kzo69qMUNWrETfLYty9ERVk3LhERERERERERee40MltE0qfz5+GNN2DXrri2qlVjJ3lUbWwRERERERERSYM0sjh59PqJSPqzdCmUKROXyLaxgZEjYccOKFjQurGJiIiIiIiIiEiK0PBFEUk/bt6EXr1g4cK4Nl9fWLQIqle3XlwiIiIiIiIiIk9BNbOTRyOzRST96NHDMpEdGAiHDyuRLSIiIiIiIiKSCSiZLSLpx7hx4O4Orq7wzTexI7Ld3a0dlYiIiIiIiIjIUzGlwpKRqcyIiKRdhgEPf/zG1xeWL4dChVQbW0REREREREQkk9HIbBFJm5Ytg5deiq2T/TB/fyWyRURERERERCRdMplMKb5kZEpmA999B5cvWzsKEQFik9edO0PbthAcHDvho4iIiIiIiIiIZHoqMwKMGBH3taur9eIQyfR++w3at4czZ+La7t+PXbJksV5cIiIiIiIiIiLPgUYWJ49ePyyrGIwda704RDKt6Gj46COoXj0uke3qCgsXxk7yqES2iIiIiIiIiEimp5HZD8mTB1q1snYUIpnMhQvQoQPs2BHXVqVKbBJbtbFFREREREREJAPJ6DWtU5pGZouI9Xz/PZQpE5fItrGB4cNj15XIFhERERERERGRh2hktohYz6VLcP167Nf588O330KNGlYNSUREREREREQkpWhcdvIomS0i1tOnD6xfDx4eMGsWZMtm7YhERERERERERCSNUjJbRFJHdHRs+ZDatePabGxg5UpwdATVjBIRERERERGRDE7pj+RRzWwRSXkXL0KdOrHLli2W25yc9JtcRERERERERDIFG0wpvmRkSmaLSMr67jt48UXYvh0MAzp3hogIa0clIiIiIiIiIiLpjMqMiEjKuHUrtib2/PlxbQ8meXRwsF5cIiIiIiIiIiJWog+nJ4+S2SLy/O3bB4GBcPp0XFubNjB7tiZ5FBERERERERGRZ6IyIyLy/ERHw8cfQ7VqcYlsFxcICoIlS5TIFhEREREREZFMzZQK/2VkGpktIs9P//7w2Wdx65Urw6JF8MIL1otJREREnosBAwY8dd+pU6emYCQiIiIikllpZLaIPD+9e0PWrLEFoIYNg507lcgWERHJIA4ePPhUy6FDh6wdqoiIiEiaZTKl/JIUO3bsoEmTJuTOnRuTycSqVassthuGwahRo8idOzdOTk7UqlWLY8eOWfSJiIigd+/e5MyZE2dnZ5o2bcqlS5cs+ly7do0OHTrg7u6Ou7s7HTp04Pr160l+/TQyW0Sen8KFYyd89PaGV16xdjQiIiLyHG3dutXaIYiIiIjIc3b79m3KlCnDm2++ScuWLeNtnzhxIlOnTiUoKIgiRYowbtw46tWrx8mTJ3F1dQWgX79+/PTTTyxdupQcOXLw3nvv0bhxY4KDg7G1tQUgMDCQS5cusX79egDefvttOnTowE8//ZSkeJXMFpFns38/jBsHixfHjsZ+oHVr68UkIiIiIiIiIpKG2aSxmtYNGjSgQYMGCW4zDIPp06czbNgwXnvtNQAWLFiAl5cXixcv5p133iE8PJy5c+fyzTffULduXQC+/fZb8uXLx6ZNmwgICODEiROsX7+eX3/9lcqVKwMwZ84cqlatysmTJylatOhTx5vpy4x89x1cvmztKETSkQeTPFatCj/+CAMHWjsiERERSWW3b99m+PDhVKtWjUKFClGwYEGLRURERETSv7NnzxIaGoq/v7+5zcHBgZo1a7Jnzx4AgoODuX//vkWf3LlzU6pUKXOfvXv34u7ubk5kA1SpUgV3d3dzn6eV6UdmjxgR9/X/RsaLSGIuXYIOHWDbtri24GC4execnKwWloiIiKSut956i+3bt9OhQwd8fHwwJbU4o4iIiEgmlRqPTREREURERFi0OTg44ODgkKTjhIaGAuDl5WXR7uXlxfnz58197O3t8fDwiNfnwf6hoaF4enrGO76np6e5z9PK9Mnsmzfjvh471npxiKR5P/wA3brBtWux6yYTDBkCo0ZBlixWDU1ERERS17p161izZg3Vq1e3digiIiIi8ogJEyYwevRoi7aRI0cyatSoZzreowMXDMN44mCGR/sk1P9pjvOoTJ/MfiBPHmjVytpRiKRBt29Dv37w9ddxbXnzwrffQs2aVgtLRERErMfDw4Ps2bNbOwwRERGRdCc1RmYPGTKEAQMGWLQldVQ2gLe3NxA7strHx8fcHhYWZh6t7e3tTWRkJNeuXbMYnR0WFka1atXMff755594x//333/jjfp+kkxfM1tEHiM4GMqXt0xkv/46HDmiRLaIiEgmNnbsWEaMGMGdO3esHYqIiIiIPMLBwQE3NzeL5VmS2QUKFMDb25uNGzea2yIjI9m+fbs5UV2hQgWyZMli0SckJISjR4+a+1StWpXw8HB+//13c5/ffvuN8PBwc5+npZHZIpK4DRvgzz9jv3Z2hs8+g86dU+fPiCIiIpKmlCtXzuJjoKdPn8bLyws/Pz+yPFJy7MCBA6kdnoiIiEi6YCJt5VRu3brF6dOnzetnz57l0KFDZM+enfz589OvXz/Gjx9P4cKFKVy4MOPHjydr1qwEBgYC4O7uTteuXXnvvffIkSMH2bNnZ+DAgZQuXZq6desCULx4cerXr0+3bt348ssvAXj77bdp3LgxRYsWTVK8SmaLSOIGD4b162MneFy0CAoXtnZEIiIiYiXNmze3dggiIiIi8pzt37+f2rVrm9cflCfp1KkTQUFBDB48mLt379KjRw+uXbtG5cqV2bBhA66uruZ9pk2bhp2dHa1bt+bu3bvUqVOHoKAgbG1tzX0WLVpEnz598Pf3B6Bp06Z8/vnnSY7XZBiG8awXmx7duHEDd3d3rl27RrZs2cibFy5fjq2ZfemStaMTa4qJiSEsLAxPT09sbDJpBZ6TJ+HRv4hduQLu7pl6kkfdG5IY3RuSGN0bkpjr16/j4eFBeHg4bm5u1g4nzbhxL8baIYhIOhMafs/aIYhIOlPEK6u1QwBg8/9dSfFz1CmWM8XPYS16dyUisZM8dusGJUvC3r2W23LmzNSJbBERERERERERSRtUZkQkswsOhsDAuNrYgYFw9GhsjWwRERGRBERHRzNt2jSWL1/OhQsXiIyMtNj+33//WSkyERERkbQtrdXMTm80Mlsks4qJgYkToWrVuER21qzw4Yex/xcRERFJxOjRo5k6dSqtW7cmPDycAQMG8Nprr2FjY8OoUaOsHZ6IiIiIZFCZemT2d9/F1ssWyXQuX4ZOnWDz5ri2ihVjJ3ksUsR6cYmIiEi6sGjRIubMmUOjRo0YPXo07dq144UXXuDFF1/k119/pU+fPtYOUURERCRNMmlgdrJk6pHZI0bEff3QBJwiGduqVfDii3GJbJMJPvgAdu9WIltERESeSmhoKKVLlwbAxcWF8PBwABo3bsyaNWusGZqIiIiIZGCZOpl982bc12PHWi8OkVTz8cfQogU8qGOZJ09sUnvCBLC3t25sIiIikm7kzZuXkJAQAAoVKsSGDRsA2LdvHw4ODtYMTURERCRNM6XCfxlZpk5mP5AnD7RqZe0oRFJB48bw4A1my5Zw5AjUrm3dmERERCTdadGiBZv/9ymvvn37Mnz4cAoXLkzHjh3p0qWLlaMTERERkYwqU9fMFsl0SpWCGTPA1ha6dFGhJhEREXkmH3/8sfnrVq1akS9fPnbv3k2hQoVo2rSpFSMTERERSdtslIpJFo3MFsmoLl+G3r0hIsKy/e23oWtXJbJFRETkme3YsYOoqCjzeuXKlRkwYAANGzZkx44dVoxMRERERDIyjcwWyYhWrYpNWP/3Hzg6wqRJ1o5IREREMpDatWsTEhKCp6enRXt4eDi1a9cmOjraSpGJiIiIpG0ZvaZ1StPIbJGM5PZteOcdy0kely6FGzesG5eIiIhkKIZhYErgU15Xr17F2dnZChGJiIiISGagkdkiGcXBg9CuHZw8GdfWogXMmQNubtaLS0RERDKM1157DQCTyUTnzp1xeDCxNBAdHc2RI0eoVq2atcKTdGD+3K/Yunkj58/+hYODIy+WLUevfu/h51fA3OelMsUT3LdP/4F06NwVgBXfL+eXdT9z8sRxbt++zZadv+GqZ16RDGnxvNksCfrSoi1b9hx8s2oTANf+u0rQ7E85tG8vt27dolSZ8rzTdzC58/kC8E/I37zVplGCx35/9ERerl0vZS9A5BGq+po8SmaLpHcxMTB1KgwdCvfvx7ZlzQrTp8Nbb+m3pIiIiDw37u7uQOzIbFdXV5ycnMzb7O3tqVKlCt26dbNWeJIOHNi/j9fbBFKiZCmio6OZ9dl0enfvyvIVP+OUNSsA6zZb1l3fs2sn40Z9SO26/ua2e/fuUrVaDapWq8HMGVNT9RpEJPXlL/AC46bONq/b2MYWGjAMg4+G9cfO1o5h46eT1dmZVcu+5cMB3fli4QocnZzI6enFwpUbLY63/qcfWLFkARUqV0/V6xCR5FMyWyQ9+/tv6NQJNm2KaytfHhYvhqJFrReXiIiIZEjz588HwM/Pj4EDB6qkiCTZZ7PmWKyPGDMe/9rVOXHiGOUrvARAzpy5LPrs2LaFCi9VJm/efOa2wDc6ARC87/cUjlhE0gJbW1s8cuSM1/73pQucPPYHny/4Ht8CLwDw7oAhdGhWh+2b1xHQ+LUE9/1151Zq1PY3/xFNJDVpyGHyqGa2SHo2d25cIttkgsGDYe9eJbJFREQkRQ0ePNiiZvb58+eZPn06GzZssGJUkh7dunUTADc39wS3X716hV07t9OsRcvUDEtE0pi/L12gU4t6dG3diImj3if070sA3I+MBGI/HfSAra0tdnZZOH7kUILHOn3yOH+dOkm9Rs1TOmwRSQFKZoukZx98AJUqQe7csUntTz6Bh/4RFxEREUkJzZo1Y+HChQBcv36dSpUqMWXKFJo1a8asWbOsHJ2kF4ZhMG3yJ5QtV4FChYsk2GfN6lU4Z3Wmdh3VtBXJrIqUKEX/oWMZPfkLeg8ezrX/rjKoR2duhF8nr68fnt4+LPjqM27dvMH9+/f57tt5XPvvCteuXknweBvWrCKfbwGKly6buhci8j82JlOKLxmZktki6cm1a5brWbLA8uVw5Ai8+qp1YhIREZFM58CBA9SoUQOA77//Hm9vb86fP8/ChQuZMWPGY/eNiIjgxo0bFktERERqhC1pzMQJYzl96iTjPpmcaJ/Vq1ZQv2Fji8lGRSRzqVjlZarXqovfC4UpW7EKIz/5DIAt63/Czi4LQ8ZO5u+L52nXqCat/Kty9FAwFSpXx8YmfsorIuIeOzat06hskXRMyWyR9CAmBqZMgfz54eBBy22+vpAjh3XiEhERkUzpzp07uLq6ArBhwwZee+01bGxsqFKlCufPn3/svhMmTMDd3d1imTrp49QIW9KQSRPGsWPbVmbNWYCXl3eCfQ4e2M/5c2dp9lqrVI5ORNIyRycn/AoW4u9LFwAoVLQEM+YtY+naHSxcuYHRk2dy80Y4Xj554u27e9smIu7d49X6jVM7bBEzUyosGZmS2SJpXUgI1K8PAwfCrVsQGAh37lg7KhEREcnEChUqxKpVq7h48SK//PIL/v7+AISFheHm5vbYfYcMGUJ4eLjFMmDQB6kRtqQBhmEwcfxYtm7eyKw588mTN2+ifX9c+QPFS5SkSNFiqRihiKR19yMjuXj+bLxJHZ1dXHHPlp2/L57n9MnjVH65Vrx9N65ZRaXqNXHPlj2VohWR583O2gGIyGOsXg1dusDVq3FtjRuDra31YhIREZFMb8SIEQQGBtK/f39effVVqlatCsSO0i5Xrtxj93VwcIhXMuLGvZgUi1XSlk/Gj+GXdWuYPP1zsjo7c+XKvwC4uLji6Oho7nfr1i02b/iFfu8NTvA4V678y9UrV7h4MfaTAKdP/0nWrM54+/jg7p4txa9DRFLP3JlTqVT9FXJ5+hB+/T+WLfyaO7dvU6d+EwB2bd2IezYPcnl5c+7MKeZ8NonKL9eifKWqFsf5+9IFjh0+wMiJn1njMkTiZPSh0yks0yazV66Ey5etHYVIIu7ciR2J/fAESj4+sHAh1K1rvbhEREREgFatWvHyyy8TEhJCmTJlzO116tShRYsWVoxM0rofli8FoHvXThbtI8aMp0mzuHtnw/q1GBgENGiU4HFWfLeMObNnmtfffrNDgscRkfTv6r//MHn0EG6EX8ctmwdFS5Rm8uwFeHrnBuC/q/8y9/MpXL92FY8cOXk1oDFtOr0d7zib1v5IjpyelHuparxtIpJ+mAzDMKwdRGq6ceMG7u7uFC58nVOn3AEoVgxOnLByYGJ1MTExhIWF4enpmeBEEanm8GFo187ypmzWDL7+GnLmTHw/STFp5t6QNEf3hiRG94Yk5vr163h4eBAeHv7EchzpxcWLFzGZTOR9TLmIJ9HIbBFJqtDwe9YOQUTSmSJeWa0dAgC/nQlP8XNUfsE9xc9hLZn23dWtW3Ffjx1rvThELCxcCJUqxSWynZxg9uzYjxIokS0iIiJpRFRUFMOHD8fd3R0/Pz98fX1xd3fnww8/5P79+9YOT0REREQyqExbZuSBPHmglSbHlrSieHGI+d/IpLJlYfHi2DYRERGRNKRXr16sXLmSiRMnmutl7927l1GjRnHlyhVmz55t5QhFRERE0iaTamYnS6ZPZoukKS+9BB99BGFhsf9/ZHIkERERkbRgyZIlLF26lAYNGpjbXnzxRfLnz0/btm2VzBYRERGRFKFktoi13LkDX3wB/fqB3UM/ioMTnrFdREREJK1wdHTEz88vXrufnx/29vapH5CIiIhIOqGB2cmTaWtmi1jV4cNQsSIMGqSi7SIiIpLu9OzZk7FjxxIREWFui4iI4KOPPqJXr15WjExEREREMjKNzBZJTTEx8Omn8MEHEBkZ2zZ1KvTurQkeRUREJE177bXXLNY3bdpE3rx5KVOmDACHDx8mMjKSOnXqWCM8ERERkfRBQ7OTRclskdQSGgqdO8Mvv8S1PZjkUYlsERERSePc3d0t1lu2bGmxni9fvtQMR0REREQyISWzRVLDzz9Dly7w779xbe+9p0keRUREJN2YP3++tUMQERERSfdMGpqdLKqZLZKS7t6FXr2gSZO4RLaPD2zYAJMnK5EtIiIi6VZUVBSbNm3iyy+/5ObNmwD8/fff3Lp1y8qRiYiIiEhGpZHZIinp009h5sy49aZNYe5clRURERGRdO38+fPUr1+fCxcuEBERQb169XB1dWXixIncu3eP2bNnWztEERERkTTJpIHZyaKR2SIpqV8/ePFFcHKCWbNg1SolskVERCTd69u3LxUrVuTatWs4OTmZ21u0aMHmzZutGJmIiIiIZGQamS3yPN2/D1myxK07OsKyZWAYULy49eISEREReY527drF7t27sbe3t2j39fXl8uXLVopKREREJO3TwOzk0chskedlzRooXBiOH7dsL1ZMiWwRERHJUGJiYoiOjo7XfunSJVxdXa0QkYiIiIhkBkpmiyTX3bvQuzc0bgznz0NgIEREWDsqERERkRRTr149pk+fbl43mUzcunWLkSNH0rBhQ+sFJiIiIpLWmVJhycBUZkQkOf74IzZ5ffRoXFu+fHDnDjg4WC8uERERkRQ0bdo0ateuTYkSJbh37x6BgYGcOnWKnDlzsmTJEmuHJyIiIiIZVKZNZoeEZPA/U0jKMgz47DMYPDhuFLajI0yZAu++q6lpRUREJEPLnTs3hw4dYsmSJRw4cICYmBi6du1K+/btLSaEFBERERFLpow+dDqFZdpk9gMq6SdJ9s8/8OabsG5dXNuLL8LixVCypPXiEhEREUlFTk5OdOnShS5dulg7FBERERHJJDJ9MnvsWGtHIOnKpk3Qvj2EhcW19e8PEyaorIiIiIhkaKtXr6ZBgwZkyZKF1atXP7Zv06ZNUykqERERkfRFH+ZPnkydzM6TB1q1snYUkq44OsKVK7Ffe3nBggUQEGDdmERERERSQfPmzQkNDcXT05PmzZsn2s9kMhEdHZ16gYmIiIhIppGpk9kiSfbyyzBsGBw8CPPmQa5c1o5IREREJFXExMQk+LWIiIiIPD0NzE4eJbNFEmMY8P330LIl2NjEtY8cGbuuz4WIiIhIJhQTE0NQUBArVqzg3LlzmEwmChYsSMuWLenQoQMmPSOJiIiISAqxeXKXlPXFF19QoEABHB0dqVChAjt37ky074oVK6hXrx65cuXCzc2NqlWr8ssvv6RitJJp/PMPNGoErVvD5MmW22xtlcgWERGRTMkwDJo2bcpbb73F5cuXKV26NCVLluTcuXN07tyZFi1aWDtEERERkbTNlApLBmbVZPayZcvo168fw4YN4+DBg9SoUYMGDRpw4cKFBPvv2LGDevXqsXbtWoKDg6lduzZNmjTh4MGDqRy5ZGhr18KLL8K6dbHrw4fD5cvWjUlEREQkDQgKCmLHjh1s3ryZgwcPsmTJEpYuXcrhw4fZtGkTW7ZsYeHChdYOU0REREQyKJNhGIa1Tl65cmXKly/PrFmzzG3FixenefPmTJgw4amOUbJkSdq0acOIESOeqv+NGzdwd3cHwsmTx41Ll54lcsmIYu7c4W6fPjjPnRvX6OUFQUFQv77V4hLri4mJISwsDE9PT2xsrP6BFklDdG9IYnRvSGKuX7+Oh4cH4eHhuLm5WTucJPP39+fVV1/lgw8+SHD7+PHj2b59e5I/PXnjnmpwi0jShIbfs3YIIpLOFPHKau0QADhy8VaKn+PFfC4pfg5rsVrN7MjISIKDg+M9CPv7+7Nnz56nOkZMTAw3b94ke/bsifaJiIggIiLCvH7jxo2HthrExFgtly9pydGjmNq3x/noUXOT0bAhxty54OkJmuQoU4uJicEwDE12JfHo3pDE6N6QxKT3e+LIkSNMnDgx0e0NGjRgxowZqRiRiIiIiGQmVktmX7lyhejoaLy8vCzavby8CA0NfapjTJkyhdu3b9O6detE+0yYMIHRo0cnuC121NS/Tx+0ZDyGQdb583EdMwbT//7oYTg6cnPECO507hzbJyzMevFJmhATE0N4eDiGYWiEpVjQvSGJ0b0hiQkPD7d2CMny33//xXt+f5iXlxfXrl1LxYhERERE0hdNw5Y8VktmP/DobOeGYTzVDOhLlixh1KhR/Pjjj3h6eibab8iQIQwYMMC8fuPGDfLlyweAjY3NY/eVTGDmTGyGDTOv3i9eHNOSJbiULk3G/UCGJFVMTAwmk4lcuXIpKSUWdG9IYnRvSGLs7e2tHUKyREdHY2eX+FsIW1tboqKiUjEiEREREclMrJbMzpkzJ7a2tvFGYYeFhT12tAfEThzZtWtXvvvuO+rWrfvYvg4ODjg4OCSy1YSNjf4ckql16QIzZ8LJkxh9+nC1f3888+dX4kHiMZlM2NjY6N6QeHRvSGJ0b0hC0vv9YBgGnTt3TvT5+uHyfiIiIiISnzKRyWO1ZLa9vT0VKlRg48aNtGjRwty+ceNGmjVrluh+S5YsoUuXLixZsoRGjRqlRqiSkRiG5ec5nJ1h8WL45x+MgACVFBERERF5jE6dOj2xT8eOHVMhEhERERHJjKxaZmTAgAF06NCBihUrUrVqVb766isuXLhA9+7dgdgSIZcvX2bhwoVAbCK7Y8eOfPrpp1SpUsU8qtvJyQl3d3erXYekE0ePQvfusGABvPBCXHv58rH/T+cTMomIiIiktPnz51s7BBEREZH0TUOzk8Wqn3Ns06YN06dPZ8yYMZQtW5YdO3awdu1afH19AQgJCeHChQvm/l9++SVRUVH07NkTHx8f89K3b19rXYKkB4YBn38OL70Eu3dD+/Zw/761oxIREREREREREZEksPoEkD169KBHjx4JbgsKCrJY37ZtW8oHJBlLWFhsXew1a+Labt+Obc+Tx3pxiYiIiIiIiIhIpmPS0OxkSd8z0Ig8zvr18OKLlons3r3h99+VyBYREREREREREUlnrD4yW+S5u3cPPvgAPv00rs3TE+bPh4YNrReXiIiIiIiIiIhkaiYNzE4WJbMlYzl2DAID4ciRuLYGDWIT2V5e1otLREREREREREREkkVlRiRj+fvvuES2g0Ps6Ow1a5TIFhERERERERERqzOlwpKRaWS2ZCz16sGAAfDLL7BkCZQube2IRERERERERERE5DnQyGxJ3/btA8OwbBs/PrZdiWwREREREREREUlLNDQ7WZTMlvQpIgL694dKleCLLyy3OTiAk5N14hIREREREREREZEUoWS2pD/Hj0PlyjB9euz6wIHw119WDUlERERERERERORJTKnwX0amZLakH4YBs2ZBhQpw+HBsm709fPwx+PlZNTQRERERERERERFJWZoAUtKHf/+Frl3hp5/i2kqUiJ3k8cUXrReXiIiIiIiIiIjIUzJl7IHTKU4jsyXt27AhNmH9cCK7Z0/Yv1+JbBERERERERERkUxCI7MlbVuyBAID49Zz5oT586FxY+vFJCIiIiIiIiIi8gw0MDt5NDJb0raGDePqYQcEwB9/KJEtIiIiIiIiIiKSCWlktqRt7u7w7bewbx/06QM2+vuLiIiIiIiIiIikUxqanSzKDEraceUKdOwIFy9atlevDv36KZEtIiIiIiIiIiKSiWlktqQNGzdCp04QEhKbzN60CWxtrR2ViIiIiIiIiIjIc2PS0Oxk0VBXsa6ICBg4EPz9YxPZAEePwpkz1o1LRERERERERERE0hSNzBbr+b//g3bt4NChuLaAAAgKAm9va0UlIiIiIiIiIiKSIkwamJ0sGpktqc8w4MsvoXz5uES2vT1MmwZr1yqRLSIiIiIiIiIiIvFoZLakritX4K234Mcf49qKF4fFi6FsWauFJSIiIiIiIiIiktI0MDt5NDJbUtfevZaJ7Hffhf37lcgWEREREREREZGMz5QKSwamZLakriZN4J13IEeO2KT2F19A1qzWjkpERERERERERETSOCWzJWVduhRbI/thU6fCkSPQtKl1YhIREREREREREbECUyr8l5EpmS0pwzDgq6+gSBFYsMByW9askDu3deISERERERERERGRdEnJbHn+rl6Fli1jy4ncvQu9esGZM9aOSkRERERERERExKpMppRfMjI7awcgGczmzdCxI/z9d1xbx47g42O9mERERERERERERCTd08hseT4iI2HwYKhXLy6RrUkeRUREREREREREzEypsCTFqFGjMJlMFou3t7d5u2EYjBo1ity5c+Pk5EStWrU4duyYxTEiIiLo3bs3OXPmxNnZmaZNm3Lp0qUkRvJ0lMyW5Dt5EqpWhUmT4iZ7rFcP/vhDkzyKiIiIiIiIiIikYSVLliQkJMS8/PHHH+ZtEydOZOrUqXz++efs27cPb29v6tWrx82bN819+vXrx8qVK1m6dCm7du3i1q1bNG7cmOjo6Oceq8qMSPJs2AAtWsCdO7HrWbLAxx9Dv35go7+ViIiIiIiIiIiImKXBmtZ2dnYWo7EfMAyD6dOnM2zYMF577TUAFixYgJeXF4sXL+add94hPDycuXPn8s0331C3bl0Avv32W/Lly8emTZsICAh4rrEq2yjJU748uLvHfl2sGPz2GwwYoES2iIiIiIiIiIhIOnDq1Cly585NgQIFaNu2LX/99RcAZ8+eJTQ0FH9/f3NfBwcHatasyZ49ewAIDg7m/v37Fn1y585NqVKlzH2eJ43MluTJmRO++Qa++w6mTlVtbBERERERERERkUSYUmFodkREBBERERZtDg4OODg4xOtbuXJlFi5cSJEiRfjnn38YN24c1apV49ixY4SGhgLg5eVlsY+Xlxfnz58HIDQ0FHt7ezw8POL1ebD/86Ths/L0IiNh9Gj45x/L9jp1YPZsJbJFRERERERERESsbMKECbi7u1ssEyZMSLBvgwYNaNmyJaVLl6Zu3bqsWbMGiC0n8oDJZJmANwwjXtujnqbPs1AyW57On39CtWowahR06RI30aOIiIiIiIiIiIg8FZMp5ZchQ4YQHh5usQwZMuSp4nN2dqZ06dKcOnXKXEf70RHWYWFh5tHa3t7eREZGcu3atUT7PE9KZsvjGQZ8/TWUKwfBwbFtGzfCoUNWDUtERERERERERETic3BwwM3NzWJJqMRIQiIiIjhx4gQ+Pj4UKFAAb29vNm7caN4eGRnJ9u3bqVatGgAVKlQgS5YsFn1CQkI4evSouc/zpJrZkrj//oO334YffohrK1oUFi+OTW6LiIiIiIiIiIjIU0v5itlJM3DgQJo0aUL+/PkJCwtj3Lhx3Lhxg06dOmEymejXrx/jx4+ncOHCFC5cmPHjx5M1a1YCAwMBcHd3p2vXrrz33nvkyJGD7NmzM3DgQHPZkudNyWxJ2Nat0KEDXL4c1/b227GTPDo7Wy8uEREREREREREReS4uXbpEu3btuHLlCrly5aJKlSr8+uuv+Pr6AjB48GDu3r1Ljx49uHbtGpUrV2bDhg24urqajzFt2jTs7Oxo3bo1d+/epU6dOgQFBWFra/vc4zUZRuYqfnzjxg3c3d2BcPLkcePSJWtHlMZERsKIETBxYlxd7OzZY0uNtGhh3dhSWExMDGFhYXh6emJjowo8Ekf3hiQmrd0bMTExREZGWjsMIfZ7cfXqVXLkyJEm7g1JPVmyZHnsQ/v169fx8PAgPDwcNze3VIwsbbtxL8baIYhIOhMafs/aIYhIOlPEK6u1QwDg0rWIFD9HXo+nKymSHmlktljasAE++SRu/dVXYeFCyJPHejGJiMgTRUZGcvbsWWJilBBKCwzDICYmhps3b6bIDN6StmXLlg1vb29970VEREREnjMls8VS48bwxhuwbBl89BG89x5oRJmISJpmGAYhISHY2tqSL18+jQROAwzDICoqCjs7OyU0MxHDMLhz5w5hYWEA+Pj4WDkiEREREUl79P4gOZTMzuxu345fA3vmTOjfH8qXt05MIiKSJFFRUdy5c4fcuXOTNWva+OhcZqdkdubl5OQEYC5BlBJ1AkVEREREMisN3crMtm2DYsVg+XLLdjc3JbJFRNKR6OhoAOzt7a0ciYgA5j8q3b9/38qRiIiIiEhaYzKl/JKRKZmdGd2/D0OGxNbDvnQJ3nkHLlywdlQiIpJMGgEskjboZ1FEREREJGWozEhmc+oUBAbC/v1xbeXLg51uBRERERERERERkZSkYQ/Jo5HZmYVhwLx5UK5cXCLbzg4++QQ2boTcua0bn4iIiCTJli1bKFasGDExMdYOJVMZOHAgffr0sXYYIiIiIiKZkpLZmcG1a9CmDXTtGjvhI0CRIvDrrzB4MNjoNhARkdTXuXNnTCYTJpMJOzs78ufPz7vvvsu1a9fi9d2zZw8NGzbEw8MDR0dHSpcuzZQpU8z1wh+2detWGjZsSI4cOciaNSslSpTgvffe4/Lly4nG4ufnx/Tp083rhmHw3nvv4erqypYtW57L9T5vgwcPZtiwYdg88u/43bt38fDwIHv27Ny9ezfefiaTiVWrVsVr79evH7Vq1bJoCw0NpXfv3hQsWBAHBwfy5ctHkyZN2Lx58/O8lHi2b99OhQoVcHR0pGDBgsyePfuJ+2zevJlq1arh6uqKj48P77//PlFRUQn2PX36NK6urmTLli3J5x48eDDz58/n7Nmzz3RtIiIiIpK5qWZ28iiLmdEdOABlysB338W1vfVWbHuFCtaLS0REBKhfvz4hISGcO3eOr7/+mp9++okePXpY9Fm5ciU1a9Ykb968bN26lf/7v/+jb9++fPTRR7Rt2xbDMMx9v/zyS+rWrYu3tzc//PADx48fZ/bs2YSHhzNlypSniik6OpquXbuycOFCtmzZwquvvvpM1xYZGflM+z2NPXv2cOrUKV5//fV423744QdKlSpFiRIlWLFixTOf49y5c1SoUIEtW7YwceJE/vjjD9avX0/t2rXp2bNncsJ/rLNnz9KwYUNq1KjBwYMHGTp0KH369OGHH35IdJ8jR47QsGFD6tevz8GDB1m6dCmrV6/mgw8+iNf3/v37tGvXjho1ajzTuT09PfH393+qBLuIiIiIiDxfKpSc0fn4wINRWR4eMGcOtGxp3ZhERET+x8HBAW9vbwDy5s1LmzZtCAoKMm+/ffs23bp1o2nTpnz11Vfm9rfeegsvLy+aNm3K8uXLadOmDZcuXaJPnz706dOHadOmmfv6+fnxyiuvcP369SfGExERQbt27di3bx87duygePHiANSqVYuyZctajN5u3rw52bJlM8fr5+fHW2+9xenTp1m5ciVNmzbl9OnT1KxZk48//ti837///kvu3LnZsGEDtWvXJjIykg8//JBFixZx/fp1SpUqxSeffBJvlPTDli5dir+/P46OjvG2zZ07lzfeeAPDMJg7dy7t27d/4nUnpEePHphMJn7//XecnZ3N7SVLlqRLly7PdMynMXv2bPLnz29+rYsXL87+/fuZPHkyLRN5hlm6dCkvvvgiI0aMAKBQoUJMmDCBdu3aMXLkSFxdXc19P/zwQ4oVK0adOnXYs2fPM527adOmDB8+nE8++eQ5XrmIiIiIZAYmVc1OFo3Mzuh8fGJrZdeuDUeOKJEtIpJJVKwIefOm/lKx4rPH/Ndff7F+/XqyZMlibtuwYQNXr15l4MCB8fo3adKEIkWKsGTJEgC+++47IiMjGTx4cILHT6ikxMNu3bpFo0aNOHbsGLt37zYnspNi0qRJlCpViv379zN06FACAwNZsmSJxejxZcuW4eXlRc2aNQF488032b17N0uXLuXIkSO8/vrr1K9fn1OnTiV6nh07dlAxgRf7zJkz7N27l9atW9O6dWv27NnDX3/9leTr+O+//1i/fj09e/a0SGQ/8LjXctGiRbi4uDx2WbRoUaL77927F39/f4u2gIAA9u/fz/379xPcJyIiIl5i38nJiXv37hEcHGxu27JlC9999x0zZ85M1rkrVarExYsXOX/+fKLXISIiIiIiz59GZmckhgGLF0ODBpA9e1x7kybQuHHGL5ojIiJmoaHwmBLRacbPP/+Mi4sL0dHR3Lt3D4CpU6eat//5558AiSaWixUrZu5z6tQp3Nzc8PHxeaZYxo4di6urK8ePH8fT0/OZjvHqq68ycOBADMMgKiqKHDlyMGDAAHbt2mUua7F48WICAwOxsbHhzJkzLFmyhEuXLpH7f5MxDxw4kPXr1zN//nzGjx+f4HnOnTtn7v+wefPm0aBBAzw8PIDYMi7z5s1j3LhxSbqO06dPYxgGxYoVS9J+EDtquXLlyo/t4+Xllei20NDQeNu9vLyIioriypUrCX5/AwICmD59OkuWLKF169aEhoaarzkkJASAq1ev0rlzZ7799lvc3NySde48efIAsd8HX1/fx16riIiIiIgFpeeSRcnsjOLaNXjnndja2C1bxv7/4eS1EtkiIpnK/yp3pPnz1q5dm1mzZnHnzh2+/vpr/vzzT3r37h2v38Mjmx9tN/3v37iHv34W/v7+bNq0ifHjx1uUE0mKR0dL58qVi3r16rFo0SJq1KjB2bNn2bt3L7NmzQLgwIEDGIZBkSJFLPaLiIggR44ciZ7n7t278UYiR0dHs2DBAj799FNz2xtvvEH//v0ZPXo0tra2T30dD17vZ3k9XV1dLcp6PItHz/ukePz9/Zk0aRLdu3enQ4cOODg4MHz4cHbt2mW+7m7duhEYGMgrr7yS7HM7OTkBcOfOnSRclYiIiIiIJJeS2RnB9u3QoQNcvBi7/sMPsHMnPOHNmoiIZFz791s7gqfj7OxMoUKFAJgxYwa1a9dm9OjRjB07FsCc5D1x4gTVqlWLt////d//UaJECXPf8PBwQkJCnml0dp06dejTpw/NmjUjOjqazz77zLzNxsYmXkI9oZIXCZXkaN++PX379uWzzz5j8eLFlCxZkjJlygAQExODra0twcHB8ZLNLi4uicaaM2dOrl27ZtH2yy+/cPnyZdq0aWPRHh0dzYYNG2jQoAEQm2wODw+Pd8zr16/j7u4OQOHChTGZTJw4cYLmzZsnGkdCFi1axDvvvPPYPl9++WWitby9vb0JDQ21aAsLC8POzu6xCf4BAwbQv39/QkJC8PDw4Ny5cwwZMoQCBQoAsSVGVq9ezeTJk4HYJHVMTAx2dnZ89dVXdOnS5anP/d9//wGxf6wQEREREUkKDTdNHtXMTs/u34dhw2LrYT9IZGfLFjsqW4lsERFJh0aOHMnkyZP5+++/gdgRt9mzZ2fKlCnx+q5evZpTp07Rrl07AFq1aoW9vT0TJ05M8NhPMwFkvXr1+Pnnn5k3bx49e/Y0J7Bz5cplLlcBsQnio0ePPtU1NW/enHv37rF+/XoWL17MG2+8Yd5Wrlw5oqOjCQsLo1ChQhaL92OGuZcrV47jx49btM2dO5e2bdty6NAhi6V9+/bMnTvX3K9YsWLs27fPYl/DMAgODqZo0aIAZM+enYCAAGbOnMnt27fjnf9xr2XTpk3jxfDo0rRp00T3r1q1Khs3brRo27BhAxUrVrSop54Qk8lE7ty5cXJyYsmSJeTLl4/y5csDsfWwH45hzJgxuLq6cujQIVq0aJGkcx89epQsWbJQsmTJx8YjIiIiIiLPl0Zmp1enT0P79vD773FttWrBwoWQL5/VwhIREUmOWrVqUbJkScaPH8/nn3+Os7MzX375JW3btuXtt9+mV69euLm5sXnzZgYNGkSrVq1o3bo1APny5WPatGn06tWLGzdu0LFjR/z8/Lh06RILFy7ExcUlwaT4o1599VXWrFlD48aNMQyDmTNn8uqrrzJgwADWrFnDCy+8wLRp054qOQ6xo7WbNWvG8OHDOXHiBIGBgeZtRYoUoX379nTs2JEpU6ZQrlw5rly5wpYtWyhdujQNGzZM8JgBAQEsWLDAvP7vv//y008/sXr1akqVKmXRt1OnTjRq1Ih///2XXLlyMXDgQDp16kSxYsXw9/fn7t27fPXVV5w5c4aePXua9/viiy+oVq0alSpVYsyYMbz44otERUWxceNGZs2axYkTJxKMLbllRrp3787nn3/OgAED6NatG3v37mXu3LnmiT4BVq5cyZAhQ/i///s/c9ukSZOoX78+NjY2rFixgo8//pjly5ebR7w/Wnd9//792NjYWLxeT3NugJ07d1KjRg1zuRERERERkaelSsDJo5HZ6Y1hQFAQlCsXl8i2s4MJE2DTJiWyRUQk3RswYABz5szh4v8+ddSqVSu2bt3KxYsXeeWVVyhatChTp05l2LBhLF261KKWcY8ePdiwYQOXL1+mRYsWFCtWjLfeegs3NzcGDhz41DHUqlWLtWvX8s033/Duu+/SpUsXOnXqRMeOHalZsyYFChSgdu3aT3289u3bc/jwYWrUqEH+/Pktts2fP5+OHTvy3nvvUbRoUZo2bcpvv/1Gvsf8m/7GG29w/PhxTp48CcDChQtxdnamTp068frWrl0bV1dXvvnmGwBat25NUFAQCxYs4KWXXsLf358zZ86wc+dOi8kMCxQowIEDB6hduzbvvfcepUqVol69emzevNlc8zslFChQgLVr17Jt2zbKli3L2LFjmTFjBi1btjT3CQ8PN1/7A+vWraNGjRpUrFiRNWvW8OOPPya5RMrTnBtgyZIldOvW7ZmvUUREREREno3JSGxGpQzqxo0b/6sHGU6ePG5cumTtiJJo0yaoVy9uvVAhWLwYXnrJejFlEDExMYSFheHp6YmNjf7OI3F0b0hi0sq9ce/ePc6ePUuBAgXiTQoo1mEYBlFRUdjZ2SVrUsrHGTx4MOHh4Xz55ZcpcnxJ2Jo1axg0aBBHjhzBzi7hDzk+7mfy+vXreHh4EB4ejpubW2qEnC7cuBdj7RBEJJ0JDb9n7RBEJJ0p4pXV2iEA8O/NqBQ/Ry7XjFuMQ1mZ9KZOHXjttdivu3SBgweVyBYREcmEhg0bhq+vL9HR0dYOJVO5ffs28+fPTzSRLSIiIiIiKSdTP4Uno5xj6omJgYdH+5lMMGdObL3sB0ltERERyXTc3d0ZOnSotcPIdB7UaBcREREReSaqmZ0smXpk9tix1o7gCc6cgWrV4OefLduzZ1ciW0RERERERERERDKVTJvM9vExaNXK2lEkwjBgwQIoWxZ++w3efBNCQ60dlYiIiIiIiIiIiCSDKRWWjCzTJrPTrOvXoV076NwZbt2KbXN3hytXrBmViIiIiIiIiIiIiFVl6prZac7OnfDGG3DhQlxb584wY0Y6KfAtIiIiIiIiIiIiiTFl9KHTKUwjs9OC+/dh+HCoVSsuke3uDsuWwfz5SmSLiIiIiIiIiIhIpqeR2dZ27hy0bRtbG/uBGjXg228hf36rhSUiIiIiIiIiIiLPlynDV7VOWRqZbW02NvB//xf7ta0tjBsHW7cqkS0iIiIiIiIiIiLyECWzrS1/fvjyS3jhBdi9G4YNi01qi4iIyFP76quvyJcvHzY2NkyfPv2p9vHz87PoazKZWLVq1WP3uXr1Kp6enpw7d+6ZY81MwsLCyJUrF5cvX7Z2KCIiIiIiaYLJlPJLRqZkdmrbuxdu3LBsa9MGjh6FypWtE5OIiEgq27ZtGyaTKdGldu3aT32sGzdu0KtXL95//30uX77M22+/nWJxT5gwgSZNmuDn5xdvm7+/P7a2tvz666/xttWqVYt+/frFa1+1ahWmR542IyMjmThxImXKlCFr1qzkzJmT6tWrM3/+fO7fv/+8LiWeCxcu0KRJE5ydncmZMyd9+vQhMjLysfvUqlUr3veubdu25u2enp506NCBkSNHpljcIiIiIiKSeahmdmqJioKxY2PLiLzxBixYYLnd0dE6cYmIiFhBtWrVCAkJide+evVqunfvTo8ePZ76WBcuXOD+/fs0atQIHx+f5xmmhbt37zJ37lzWrl2bYAx79+6lV69ezJ07l8rP+AfqyMhIAgICOHz4MGPHjqV69eq4ubnx66+/MnnyZMqVK0fZsmWTeSXxRUdH06hRI3LlysWuXbu4evUqnTp1wjAMPvvss8fu261bN8aMGWNed3Jystj+5ptvUqlSJSZNmoSHh8dzj11ERERERDIPjcxODX/9FTup45gxEBMDCxfC+vXWjkpERMRq7O3t8fb2tliuXbvGoEGDGDp0KK+//joAQUFBZMuWzWLfh0czBwUFUbp0aQAKFiyIyWTi3LlznDlzhmbNmuHl5YWLiwsvvfQSmzZtSlbM69atw87OjqpVq8bbNn/+fBo3bsy7777LsmXLuH379jOdY/r06ezYsYPNmzfTs2dPypYtS8GCBQkMDOS3336jcOHCybqGxGzYsIHjx4/z7bffUq5cOerWrcuUKVOYM2cONx79RNkjsmbNavF9dHd3t9heunRpvL29WblyZYrELiIiIiIimYeS2Snt22+hbFl48JHjB5M81qtn1bBERCQTmDoV8uZ98tK0afx9mzZ9un2nTn0uoV6/fp3mzZtTs2ZNxo4d+9T7tWnTxpyk/v333wkJCSFfvnzcunWLhg0bsmnTJg4ePEhAQABNmjThwoULzxzjjh07qFixYrx2wzCYP38+b7zxBsWKFaNIkSIsX778mc6xaNEi6tatS7ly5eJty5IlC87Ozgnud+HCBVxcXB67dO/ePdHz7t27l1KlSpE7d25zW0BAABEREQQHBz8x5pw5c1KyZEkGDhzIzZs34/WpVKkSO3fufOxxREREREQyA9XMTh6VGUkp4eHQowcsXhzXVrBg7LpqY4uISGq4cQOeZuK9fPnit/3779Pt+4RRu08jJiaGwMBAbG1t+fbbb+PVkH4cJycncuTIAUCuXLnw9vYGoEyZMpQpU8bcb9y4caxcuZLVq1fTq1evZ4rz3LlzFsneBzZt2sSdO3cICAgA4I033mDevHl06NAhyec4deoUtWrVSvJ+uXPn5tChQ4/t4+bmlui20NBQvLy8LNo8PDywt7cnNDQ00f3at29PgQIF8Pb25ujRowwZMoTDhw+zceNGi3558uTh4MGDT74QERERERGRx1AyOyXs3g3t28P583FtnTrBZ5+Bq6v14hIRkczFzQ3y5Hlyv1y5Em57mn0fkyB9WkOHDmXv3r38/vvvj024JsXt27cZPXo0P//8M3///TdRUVHcvXs3WSOz7969i2MCc1zMnTuXNm3aYGcX+1jVrl07Bg0axMmTJylZsmSSzmEYRpKS+Q/Y2dlRqFChJO/3sITO+6R4unXrZv66VKlSFC5cmIoVK3LgwAHKly9v3ubk5MSdO3eSFZ+IiIiISEZgIoMPnU5hSmY/b7/9Bq+8ElsbG8DdHb78Etq0sW5cIiKS+QwYELs8i9Wrn28siVi2bBmTJ09mzZo1CdaDtrGxwTAMi7b79+8/8biDBg3il19+YfLkyRQqVAgnJydatWpFZGTkM8eaM2dOrl27ZtH233//sWrVKu7fv8+sWbPM7dHR0QQFBTFp0iQgdlR0eHh4vGNev37dIoFfpEgRTpw4keTYLly4QIkSJR7b54033mD27NkJbvP29ua3336zaLt27Rr379+PN2L7ccqXL0+WLFk4deqURTL7v//+I1dCfzQRERERERFJAiWzn7dKlcDfP3aCx5dfjq2Z7etr7ahERETSnEOHDtGlSxc+/vhjc4mOR+XKlYubN29y+/Ztc73oJ5XTANi5cyedO3emRYsWANy6dYtz584lK95y5crx7bffWrQtWrSIvHnzsmrVKov2TZs28fHHHzNhwgSyZMlCsWLFWLduXbxj7tu3j6JFi5rXAwMDGTp0KAcPHoxXNzsqKoqIiIgE62Ynt8xI1apV+eijjwgJCcHHxweInRTSwcGBChUqPPa4Dzt27Bj37983H+OBo0ePPlP5FBERERGRjCaj17ROaZoA8nkzmSAoCCZOhG3blMgWERFJwJUrV2jevDm1atXijTfeIDQ01GL5999/AahcuTJZs2Zl6NChnD59msWLFxMUFPTE4xcqVIgVK1Zw6NAhDh8+TGBgIDEPPjX1jAICAjh27JjF6Oy5c+fSqlUrSpUqZbF06dKF69evs2bNGgB69OjBmTNn6NmzJ4cPH+bPP/9k5syZzJ07l0GDBpmP169fP6pXr06dOnWYOXMmhw8f5q+//mL58uVUrlyZU6dOJRjbgzIjj1s8PT0TvTZ/f39KlChBhw4dOHjwIJs3b2bgwIF069bNnAS/fPkyxYoV4/fffwfgzJkzjBkzhv3793Pu3DnWrl3L66+/Trly5ahevbr52Hfu3CE4OBh/f/9nf/FFRERERERQMjt5wsOhY0fYvNmy3csLBg0CW1vrxCUiIpLGrVmzhvPnz7N27Vp8fHziLS+99BIA2bNn59tvv2Xt2rWULl2aJUuWMGrUqCcef9q0aXh4eFCtWjWaNGlCQECARdmLZ1G6dGkqVqzI8uXLAQgODubw4cO0bNkyXl9XV1fq1q3LvHnzAPDz82Pnzp2cOXMGf39/XnrpJYKCgggKCuL111837+fg4MDGjRsZPHgwX375JVWqVOGll15ixowZ9OnTh1KlSiXrGhJja2vLmjVrcHR0pHr16rRu3ZrmzZszefJkc5/79+9z8uRJc+1re3t7Nm/eTEBAAEWLFqVPnz74+/uzadMmbB96Bvrxxx/Jnz8/NWrUSJHYRURERETSE1MqLBmZyXi0EGUGd+PGDdzd3fHxuc7ff7s/+4H27Imd5PHcOcidG44cgRw5nluckvpiYmIICwvD09MTGxv9nUfi6N6QxKSVe+PevXucPXuWAgUKJDhBoTw/a9euZeDAgRw9evSx33PDMIiKisLOzu6ZJnTMSCpVqkS/fv0IDAy0diip5nE/k9evX8fDw4Pw8PDnNuFpRnDjXvI+OSEimU9o+D1rhyAi6UwRr6zWDgGAm6nw3OPqmHFzFxn3ylJKVBSMHh07yeOD2pu3b8OxY1YNS0RERFJew4YNeeedd7h8+bK1Q0kXwsLCaNWqFe3atbN2KCIiIiIiaYOGZieLJoBMinPnYkdj79kT16ZJHkVERDKVvn37WjuEdMPT05PBgwdbOwwREREREckgNDL7aS1eDGXKxCWybW1hzBjYulWJbBEREREREREREXkiUyr8l5FpZPaT3LgBPXvGjr5+oEABWLQIqla1XlwiIiIiIiIiIiIimYiS2U/yzz+wcmXceocO8PnnoAl7REQkjclkczqLpFn6WRQRERGRxGTy+eGTTWVGnqRwYZgxIzZ5vXgxLFyoRLaIiKQptra2AERGRlo5EhEBuHPnDgBZsmSxciQiIiIiIhmLRmY/6vx5yJULsmaNa3vzTWjUCLy8rBeXiIhIIuzs7MiaNSv//vsvWbJkwcZGf6u2NsMwiIqKws7ODpOGXmQahmFw584dwsLCyJYtm/kPTSIiIiIiD+jdQfIomf2wJUuge3do3x6++CKu3WRSIltERNIsk8mEj48PZ8+e5fz589YOR4hNasbExGBjY6NkdiaULVs2vL29rR2GiIiIiEiGo2Q2xE7y2KsXfPNN7PqsWdC4MTRsaN24REREnpK9vT2FCxdWqZE0IiYmhqtXr5IjRw6NlM9ksmTJohHZIiIiIpI4jXVJFqsns7/44gsmTZpESEgIJUuWZPr06dSoUSPR/tu3b2fAgAEcO3aM3LlzM3jwYLp37/7sAfz6a+xI7L/+imtr3x6qV3/2Y4qIiFiBjY0Njo6O1g5DiE1mZ8mSBUdHRyWzRUREREREnhOrvrtatmwZ/fr1Y9iwYRw8eJAaNWrQoEEDLly4kGD/s2fP0rBhQ2rUqMHBgwcZOnQoffr04YcffkjyuW2MaBg7Fl5+OS6R7eoK334bu7i7J+fSRERERERERERERCyYUuG/jMxkGIZhrZNXrlyZ8uXLM2vWLHNb8eLFad68ORMmTIjX//3332f16tWcOHHC3Na9e3cOHz7M3r17n+qcN27cwN3dnc1ZqvDq/V/jNlStCosWQYECz35Bkq7FxMQQFhaGp6enRtGJBd0bkhjdG5IY3RuSmOvXr+Ph4UF4eDhubm7WDifNuHEvxtohiEg6Exp+z9ohiEg6U8Qrq7VDAODu/ZQ/h1OWlD+HtVjt3VVkZCTBwcH4+/tbtPv7+7Nnz54E99m7d2+8/gEBAezfv5/795N2J1R8kMi2sYGRI2HHDiWyRUREREREREREJMWYTCm/ZGRWq5l95coVoqOj8fLysmj38vIiNDQ0wX1CQ0MT7B8VFcWVK1fw8fGJt09ERAQRERHm9fDwcABuAEa+fBhffQVVqsCtW8m8IknvYmJiuHHjBvb29hpFJxZ0b0hidG9IYnRvSGKuX78OgBU/HCkiIiIikm5ZfQJI0yN/LjAMI17bk/on1P7AhAkTGD16dLz2fAAXL0KDBkkLWEREREQkma5evYq75mgxc3PUH30kvoiICCZMmMCQIUNwcHCwdjiSxrg5po1yAZK26PeGpAeOVs/Gpm9We/ly5syJra1tvFHYYWFh8UZfP+Dt7Z1gfzs7O3LkyJHgPkOGDGHAgAHm9evXr+Pr68uFCxf0BkIs3Lhxg3z58nHx4kXVsBQLujckMbo3JDG6NyQx4eHh5M+fn+zZs1s7FJE0LyIigtGjRzNgwAAlpUTkqej3hkjGZ7Vktr29PRUqVGDjxo20aNHC3L5x40aaNWuW4D5Vq1blp59+smjbsGEDFStWJEuWhCubOzg4JPgLzN3dXW8uJUFubm66NyRBujckMbo3JDG6NyQxKj8jIiIiIpJ0Vn2KHjBgAF9//TXz5s3jxIkT9O/fnwsXLtC9e3cgdlR1x44dzf27d+/O+fPnGTBgACdOnGDevHnMnTuXgQMHWusSRERERERERERERCQVWLVKS5s2bbh69SpjxowhJCSEUqVKsXbtWnx9fQEICQnhwoUL5v4FChRg7dq19O/fn5kzZ5I7d25mzJhBy5YtrXUJIiIiIiIiIiIiIpIKrF5yvEePHvTo0SPBbUFBQfHaatasyYEDB575fA4ODowcOVK1kyQe3RuSGN0bkhjdG5IY3RuSGN0bIk9PPy8iklT6vSGS8ZkMwzCsHYSIiIiIiIiIiIiIyONo5hkRERERERERERERSfOUzBYRERERERERERGRNE/JbBEREREREUmQn58f06dPT5VznTt3DpPJxKFDh556n1q1atGvX78UiykxnTt3pnnz5o/tk5qvnUh6ZTKZWLVq1VP3f5qfvZQwatQoypYt+9g+1vp9JJLZZMhk9hdffEGBAgVwdHSkQoUK7Ny587H9t2/fToUKFXB0dKRgwYLMnj07lSKV1JaUe2PFihXUq1ePXLly4ebmRtWqVfnll19SMVpJTUn9vfHA7t27sbOze+KDjaRfSb03IiIiGDZsGL6+vjg4OPDCCy8wb968VIpWUlNS741FixZRpkwZsmbNio+PD2+++SZXr15NpWgltezYsYMmTZqQO3fup36DrmdRSSkJJX2+//57HB0dmThx4lMdY9++fbz99tvJiqNWrVqYTCZMJhMODg7kyZOHJk2asGLFCot++fLlIyQkhFKlSiXrfEmNTcknkeevc+fO5p/7LFmy4OXlRb169Zg3bx4xMTHmfiEhITRo0CBV47JGMlxEnp8Ml8xetmwZ/fr1Y9iwYRw8eJAaNWrQoEEDLly4kGD/s2fP0rBhQ2rUqMHBgwcZOnQoffr04YcffkjlyCWlJfXe2LFjB/Xq1WPt2rUEBwdTu3ZtmjRpwsGDB1M5cklpSb03HggPD6djx47UqVMnlSKV1PYs90br1q3ZvHkzc+fO5eTJkyxZsoRixYqlYtSSGpJ6b+zatYuOHTvStWtXjh07xnfffce+fft46623UjlySWm3b9+mTJkyfP7550/VX8+ikpq+/vpr2rdvz+eff87gwYOfap9cuXKRNWvWZJ+7W7duhISEcPr0aX744QdKlChB27ZtLRLltra2eHt7Y2dnl+zziYj11a9fn5CQEM6dO8e6deuoXbs2ffv2pXHjxkRFRQHg7e2Ng4ODlSMVkXTFyGAqVapkdO/e3aKtWLFixgcffJBg/8GDBxvFihWzaHvnnXeMKlWqpFiMYh1JvTcSUqJECWP06NHPOzSxsme9N9q0aWN8+OGHxsiRI40yZcqkYIRiLUm9N9atW2e4u7sbV69eTY3wxIqSem9MmjTJKFiwoEXbjBkzjLx586ZYjGJ9gLFy5crH9tGzqKSkTp06Gc2aNTMMwzA++eQTw8HBwfj+++8t+uzevduoUaOG4ejoaOTNm9fo3bu3cevWLfN2X19fY9q0aeZ1wJgzZ47RvHlzw8nJyShUqJDx448/PjaOmjVrGn379o3XPm/ePAMwNm7caBiGYZw9e9YAjIMHD5r7HDt2zGjQoIHh7OxseHp6Gm+88Ybx77//Why7Z8+eRs+ePQ13d3cje/bsxrBhw4yYmBhzn5kzZxqFChUyHBwcDE9PT6Nly5bm1wewWM6ePWtERUUZXbp0Mfz8/AxHR0ejSJEixvTp0xN8bSdNmmR4e3sb2bNnN3r06GFERkYm+tqJZCYP//552ObNm82/Rwwj/r+Vly5dMlq3bm1ky5bNyJ49u9G0aVPj7Nmz8Y47atQoI1euXIarq6vx9ttvGxEREeY+3333nVGqVCnD0dHRyJ49u1GnTh3j1q1bxsiRI+P9zG/dutUwjNh/jwsXLmw4OTkZBQoUMD788EOLn+cH7/kWLlxo+Pr6Gm5ubkabNm2MGzdumPsk9rtORJ6vDDUyOzIykuDgYPz9/S3a/f392bNnT4L77N27N17/gIAA9u/fz/3791MsVkldz3JvPComJoabN2+SPXv2lAhRrORZ74358+dz5swZRo4cmdIhipU8y72xevVqKlasyMSJE8mTJw9FihRh4MCB3L17NzVCllTyLPdGtWrVuHTpEmvXrsUwDP755x++//57GjVqlBohSxqmZ1FJDR988AFjx47l559/pmXLlub2P/74g4CAAF577TWOHDnCsmXL2LVrF7169Xrs8UaPHk3r1q05cuQIDRs2pH379vz3339JjqtTp054eHjEKzfyQEhICDVr1qRs2bLs37+f9evX888//9C6dWuLfgsWLMDOzo7ffvuNGTNmMG3aNL7++msA9u/fT58+fRgzZgwnT55k/fr1vPLKKwB8+umnVK1a1TxqPCQkhHz58hETE0PevHlZvnw5x48fZ8SIEQwdOpTly5dbnHfr1q2cOXOGrVu3smDBAoKCgggKCkry6yCSmbz66quUKVMmwZ/7O3fuULt2bVxcXNixYwe7du3CxcWF+vXrExkZae63efNmTpw4wdatW1myZAkrV65k9OjRQOzvjXbt2tGlSxdOnDjBtm3beO211zAMg4EDB9K6dWvziPGQkBCqVasGgKurK0FBQRw/fpxPP/2UOXPmMG3aNIv4zpw5w6pVq/j555/5+eef2b59Ox9//HEKvloikpAM9fmtK1euEB0djZeXl0W7l5cXoaGhCe4TGhqaYP+oqCiuXLmCj49PisUrqedZ7o1HTZkyhdu3b8d7eJb07VnujVOnTvHBBx+wc+dOfQw2A3uWe+Ovv/5i165dODo6snLlSq5cuUKPHj3477//VDc7A3mWe6NatWosWrSINm3acO/ePaKiomjatCmfffZZaoQsaZieRSWlrVu3jh9//JHNmzfz6quvWmybNGkSgYGB5prRhQsXZsaMGdSsWZNZs2bh6OiY4DE7d+5Mu3btABg/fjyfffYZv//+O/Xr109SbDY2NhQpUoRz584luH3WrFmUL1+e8ePHm9vmzZtHvnz5+PPPPylSpAgQW2t72rRpmEwmihYtyh9//MG0adPo1q0bFy5cwNnZmcaNG+Pq6oqvry/lypUDwN3dHXt7e7JmzYq3t7f5HLa2tubEGECBAgXYs2cPy5cvt3gv4OHhweeff46trS3FihWjUaNGbN68mW7duiXpdRDJbIoVK8aRI0fitS9duhQbGxu+/vprTCYTEDuIKFu2bGzbts38x197e3vmzZtH1qxZKVmyJGPGjGHQoEGMHTuWkJAQoqKieO211/D19QWgdOnS5nM4OTkRERFh8TMP8OGHH5q/9vPz47333mPZsmUWJZliYmIICgrC1dUVgA4dOrB582Y++uij5/TKiMjTyFAjsx948EvvAcMw4rU9qX9C7ZL+JfXeeGDJkiWMGjWKZcuW4enpmVLhiRU97b0RHR1NYGAgo0ePNr+BkowtKb83YmJiMJlMLFq0iEqVKtGwYUOmTp1KUFCQRmdnQEm5N44fP06fPn0YMWIEwcHBrF+/nrNnz9K9e/fUCFXSOD2LSkp68cUX8fPzY8SIEdy8edNiW3BwMEFBQbi4uJiXgIAAYmJiOHv27GOP+YCzszOurq6EhYU9U3yP+90ZHBzM1q1bLeJ7MA/FmTNnzP2qVKlicYyqVaty6tQpoqOjqVevHr6+vhQsWJAOHTqwaNEi7ty588S4Zs+eTcWKFcmVKxcuLi7MmTMn3rwIJUuWxNbW1rzu4+PzzK+DSGaS2M99cHAwp0+fxtXV1fwznz17du7du2fxM/9gQu0Hqlatyq1bt7h48SJlypShTp06lC5dmtdff505c+Zw7dq1J8b0/fff8/LLL+Pt7Y2LiwvDhw+P9zPv5+dnTmSDfuZFrCVDJbNz5syJra1tvFFRYWFh8Ua8PODt7Z1gfzs7O3LkyJFisUrqepZ744Fly5bRtWtXli9fTt26dVMyTLGCpN4bN2/eZP/+/fTq1Qs7Ozvs7OwYM2YMhw8fxs7Oji1btqRW6JLCnuX3ho+PD3ny5MHd3d3cVrx4cQzD4NKlSykar6SeZ7k3JkyYQPXq1Rk0aBAvvvgiAQEBfPHFF8ybN4+QkJDUCFvSKD2LSkrLkycP27dvJyQkhPr161sktGNiYnjnnXc4dOiQeTl8+DCnTp3ihRdeSPSYWbJksVg3mUzExMQkObbo6GhOnTpFgQIFEtweExNDkyZNLOI7dOgQp06dMpcKeRJXV1cOHDjAkiVL8PHxYcSIEZQpU4br168nus/y5cvp378/Xbp0YcOGDRw6dIg333zToswBPL/XQSSzOXHiRII/9zExMVSoUCHez/yff/5JYGDgE49rMpmwtbVl48aNrFu3jhIlSvDZZ59RtGjRx/6B7tdff6Vt27Y0aNCAn3/+mYMHDzJs2DD9zIukURkqmW1vb0+FChXYuHGjRfvGjRvNdZAeVbVq1Xj9N2zYQMWKFeP9opL061nuDYgdkd25c2cWL16suqYZVFLvDTc3N/744w+Lh6vu3btTtGhRDh06ROXKlVMrdElhz/J7o3r16vz999/cunXL3Pbnn39iY2ND3rx5UzReST3Pcm/cuXMHGxvLx64Ho/kejMKVzEnPopIa8ufPz/bt2wkLC8Pf358bN24AUL58eY4dO0ahQoXiLfb29ike14IFC7h27ZpFHe+HPYjPz88vXnzOzs7mfr/++qvFfr/++iuFCxc2/561s7Ojbt26TJw4kSNHjnDu3DnzAAR7e3uio6Mt9t+5cyfVqlWjR48elCtXjkKFClmMChWRZ7dlyxb++OOPBH/uy5cvz6lTp/D09Iz3M//wYJHDhw9bfOrx119/xcXFxfy8bTKZqF69OqNHj+bgwYPY29uzcuVKIOGf+d27d+Pr68uwYcOoWLEihQsX5vz58ylx+SLyHGSoZDbAgAED+Prrr5k3bx4nTpygf//+XLhwwfwx3iFDhtCxY0dz/+7du3P+/HkGDBjAiRMnmDdvHnPnzmXgwIHWugRJIUm9N5YsWULHjh2ZMmUKVapUITQ0lNDQUMLDw611CZJCknJv2NjYUKpUKYvF09MTR0dHSpUqZfHGStK/pP7eCAwMJEeOHLz55pscP36cHTt2MGjQILp06YKTk5O1LkNSQFLvjSZNmrBixQpmzZrFX3/9xe7du+nTpw+VKlUid+7c1roMSQG3bt0y/7ET4OzZsxw6dMj8UWU9i4q15M2bl23btnH16lX8/f0JDw/n/fffZ+/evfTs2dM84nn16tX07t37uZ//zp07hIaGcunSJX777Tfef/99unfvzrvvvkvt2rUT3Kdnz578999/tGvXjt9//52//vqLDRs20KVLF4tk1MWLFxkwYAAnT55kyZIlfPbZZ/Tt2xeAn3/+mRkzZnDo0CHOnz/PwoULiYmJoWjRokBs2YDffvuNc+fOceXKFWJiYihUqBD79+/nl19+4c8//2T48OHs27fvub8mIhldREQEoaGhXL58mQMHDjB+/HiaNWtG48aNLf4tfKB9+/bkzJmTZs2asXPnTs6ePcv27dvp27evxaccIyMj6dq1K8ePH2fdunWMHDmSXr16YWNjw2+//cb48ePZv38/Fy5cYMWKFfz7778UL14ciP2ZP3LkCCdPnuTKlSvcv3+fQoUKceHCBZYuXcqZM2eYMWOGOfktImlPhpu5rE2bNly9epUxY8YQEhJCqVKlWLt2rbnwf0hIiEXdowIFCrB27Vr69+/PzJkzyZ07NzNmzEh0dICkX0m9N7788kuioqLo2bMnPXv2NLd36tRJs5RnMEm9NyTzSOq94eLiwsaNG+nduzcVK1YkR44ctG7dmnHjxlnrEiSFJPXe6Ny5Mzdv3uTzzz/nvffeI1u2bLz66qt88skn1roESSH79++3SMwNGDAAiHt+0LOoWNODkiO1a9emXr16bNiwge3btzNs2DBq1KiBYRi88MILtGnT5rmfe86cOcyZMwd7e3ty5MhBhQoVWLZsGS1atEh0n9y5c7N7927ef/99AgICiIiIwNfXl/r161t82qVjx47cvXuXSpUqYWtrS+/evXn77bcByJYtGytWrGDUqFHcu3ePwoULs2TJEkqWLAnAwIED6dSpEyVKlODu3bvm+QwOHTpEmzZtMJlMtGvXjh49erBu3brn/rqIZGTr16/Hx8cHOzs7PDw8KFOmDDNmzKBTp07xPrEGkDVrVnbs2MH777/Pa6+9xs2bN8mTJw916tTBzc3N3K9OnToULlyYV155hYiICNq2bcuoUaOA2E/S7tixg+nTp3Pjxg18fX2ZMmUKDRo0AKBbt25s27aNihUrcuvWLbZu3UqzZs3o378/vXr1IiIigkaNGjF8+HDzMUUkbTEZ+myriIiIiIiIiIiIiKRxGa7MiIiIiIiIiIiIiIhkPEpmi4iIiIiIiIiIiEiap2S2iIiIiIiIiIiIiKR5SmaLiIiIiIiIiIiISJqnZLaIiIiIiIiIiIiIpHlKZouIiIiIiIiIiIhImqdktoiIiIiIiIiIiIikeUpmi4iIiIiIiIiIiEiap2S2iEgqCwoKIlu2bNYO45n5+fkxffr0x/YZNWoUZcuWTZV4REREROTJ0vszaHpz7tw5TCYThw4dsnYoIiIZipLZIiLPoHPnzphMpnjL6dOnrR0aQUFBFjH5+PjQunVrzp49+1yOv2/fPt5++23zuslkYtWqVRZ9Bg4cyObNm5/L+RLz6HV6eXnRpEkTjh07luTj6I2diIiIpAVNmjShbt26CW7bu3cvJpOJAwcOpHJUGUfnzp1p3rx5so+TUKL65s2b1KpVi2LFinHx4sVkn0NERBKmZLaIyDOqX78+ISEhFkuBAgWsHRYAbm5uhISE8Pfff7N48WIOHTpE06ZNiY6OTvaxc+XKRdasWR/bx8XFhRw5ciT7XE/y8HWuWbOG27dv06hRIyIjI1P83CIiIiLPW9euXdmyZQvnz5+Pt23evHmULVuW8uXLJ/m4KflsdP/+/RQ7dnrx77//Urt2bW7dusWuXbvIly+ftUMSEcmwlMwWEXlGDg4OeHt7Wyy2trZMnTqV0qVL4+zsTL58+ejRowe3bt1K9DiHDx+mdu3auLq64ubmRoUKFdi/f795+549e3jllVdwcnIiX7589OnTh9u3bz82NpPJhLe3Nz4+PtSuXZuRI0dy9OhR88jxWbNm8cILL2Bvb0/RokX55ptvLPYfNWoU+fPnx8HBgdy5c9OnTx/ztofLjPj5+QHQokULTCaTef3hMiO//PILjo6OXL9+3eIcffr0oWbNms/tOitWrEj//v05f/48J0+eNPd53Pdj27ZtvPnmm4SHh5tHeI8aNQqIfdM3ePBg8uTJg7OzM5UrV2bbtm2PjUdEREQkORo3boynpydBQUEW7Xfu3GHZsmV07doVgB9++IGSJUvi4OCAn58fU6ZMsejv5+fHuHHj6Ny5M+7u7nTr1s287ZdffqF48eK4uLiYB2c8bP78+RQvXhxHR0eKFSvGF198Yd72YETy8uXLqVWrFo6Ojnz77bdERUXRp08fsmXLRo4cOXj//ffp1KmTxShowzCYOHEiBQsWxMnJiTJlyvD999+bt1+7do327duTK1cunJycKFy4MPPnzzdvf//99ylSpAhZs2alYMGCDB8+PF4ifdy4cXh6euLq6spbb73FBx98YH4mHTVqFAsWLODHH380P/c9eLa7fPkybdq0wcPDgxw5ctCsWTPOnTv3VN+zixcvUqNGDVxdXdm6dSs5c+ZMsF90dDRdu3alQIECODk5UbRoUT799FOLPtu2baNSpUo4OzuTLVs2qlevbv7DRkq8ZxARSY+UzBYRec5sbGyYMWMGR48eZcGCBWzZsoXBgwcn2r99+/bkzZuXffv2ERwczAcffECWLFkA+OOPPwgICOC1117jyJEjLFu2jF27dtGrV68kxeTk5ATEjpxZuXIlffv25b333uPo0aO88847vPnmm2zduhWA77//nmnTpvHll19y6tQpVq1aRenSpRM87r59+4DYNz0hISHm9YfVrVuXbNmy8cMPP5jboqOjWb58Oe3bt39u13n9+nUWL14MYH794PHfj2rVqjF9+nTzCO+QkBAGDhwIwJtvvsnu3btZunQpR44c4fXXX6d+/fqcOnXqqWMSERERSQo7Ozs6duxIUFAQhmGY27/77jsiIyNp3749wcHBtG7dmrZt2/LHH38watQohg8fHi8BPmnSJEqVKkVwcDDDhw8HYpPikydP5ptvvmHHjh1cuHDB/OwDMGfOHIYNG8ZHH33EiRMnGD9+PMOHD2fBggUWx37//ffp06cPJ06cICAggE8++YRFixYxf/58du/ezY0bN+KVofvwww+ZP38+s2bN4tixY/Tv35833niD7du3AzB8+HCOHz/OunXrOHHiBLNmzbJIDLu6uhIUFMTx48f59NNPmTNnDtOmTTNvX7RoER999BGffPIJwcHB5M+fn1mzZpm3Dxw4kNatW1t8urJatWrcuXOH2rVr4+Liwo4dO9i1a5c50f+kEe0nT56kevXqFCtWjPXr1+Pq6ppo35iYGPLmzcvy5cs5fvw4I0aMYOjQoSxfvhyAqKgomjdvTs2aNTly5Ah79+7l7bffxmQyAanznkFEJF0wREQkyTp16mTY2toazs7O5qVVq1YJ9l2+fLmRI0cO8/r8+fMNd3d387qrq6sRFBSU4L4dOnQw3n77bYu2nTt3GjY2Nsbdu3cT3OfR41+8eNGoUqWKkTdvXiMiIsKoVq2a0a1bN4t9Xn/9daNhw4aGYRjGlClTjCJFihiRkZEJHt/X19eYNm2aeR0wVq5cadFn5MiRRpkyZczrffr0MV599VXz+i+//GLY29sb//33X7KuEzCcnZ2NrFmzGoABGE2bNk2w/wNP+n4YhmGcPn3aMJlMxuXLly3a69SpYwwZMuSxxxcRERFJjhMnThiAsWXLFnPbK6+8YrRr184wDMMIDAw06tWrZ7HPoEGDjBIlSpjXfX19jebNm1v0efDsdPr0aXPbzJkzDS8vL/N6vnz5jMWLF1vsN3bsWKNq1aqGYRjG2bNnDcCYPn26RR8vLy9j0qRJ5vWoqCgjf/78RrNmzQzDMIxbt24Zjo6Oxp49eyz269q1q/m6mjRpYrz55puPeWUsTZw40ahQoYJ5vXLlykbPnj0t+lSvXt3imbRTp07mmB6YO3euUbRoUSMmJsbcFhERYTg5ORm//PJLgud+8DrY29sbtWrVMqKiohLtc/DgwUSvoUePHkbLli0NwzCMq1evGoCxbdu2BPs+7/cMIiLplUZmi4g8o9q1a3Po0CHzMmPGDAC2bt1KvXr1yJMnD66urnTs2JGrV68m+jG/AQMG8NZbb1G3bl0+/vhjzpw5Y94WHBxMUFAQLi4u5iUgIICYmJjHTugYHh6Oi4uLubRGZGQkK1aswN7enhMnTlC9enWL/tWrV+fEiRMAvP7669y9e5eCBQvSrVs3Vq5cSVRUVLJeq/bt27Nt2zb+/vtvIHbkTMOGDfHw8EjWdbq6unLo0CGCg4OZPXs2L7zwArNnz7bok9TvB8CBAwcwDIMiRYpYxLR9+3aL74+IiIjI81asWDGqVavGvHnzADhz5gw7d+6kS5cuAIk+y506dcpifpSKFSvGO3bWrFl54YUXzOs+Pj6EhYUBsXWfL168SNeuXS2ef8aNGxfv+efhY4eHh/PPP/9QqVIlc5utrS0VKlQwrx8/fpx79+5Rr149i2MvXLjQfOx3332XpUuXUrZsWQYPHsyePXsszvn999/z8ssv4+3tjYuLC8OHD+fChQvm7SdPnrSIAYi3npDg4GBOnz6Nq6urOa7s2bNz7969Jz73NWvWjF27dll8AvFxZs+eTcWKFcmVKxcuLi7MmTPHfA3Zs2enc+fOBAQE0KRJEz799FOLEjAp8Z5BRCQ9srN2ACIi6ZWzszOFChWyaDt//jwNGzake/fujB07luzZs7Nr1y66du2a6OQ4o0aNIjAwkDVr1rBu3TpGjhzJ0qVLadGiBTExMbzzzjsWNasfyJ8/f6Kxubq6cuDAAWxsbPDy8sLZ2dli+4OPKz5gGIa5LV++fJw8eZKNGzeyadMmevTowaRJk9i+fbtF+Y6kqFSpEi+88AJLly7l3XffZeXKlRY1EJ/1Om1sbMzfg2LFihEaGkqbNm3YsWMH8Gzfjwfx2NraEhwcjK2trcU2FxeXJF27iIiISFJ17dqVXr16MXPmTObPn4+vry916tQBLJ/bHjAeKknywKPPf0C8ZzmTyWTeNyYmBogtNVK5cmWLfo8+DyV07MfF9ODYa9asIU+ePBb9HBwcAGjQoAHnz59nzZo1bNq0iTp16tCzZ08mT57Mr7/+Stu2bRk9ejQBAQG4u7uzdOnSeLXCn+Z1eVRMTAwVKlRg0aJF8bblypXrsfsOHTqUF198kfbt22MYBm3atEm07/Lly+nfvz9TpkyhatWquLq6MmnSJH777Tdzn/nz59OnTx/Wr1/PsmXL+PDDD9m4cSNVqlRJkfcMIiLpkZLZIiLP0f79+4mKimLKlCnY2MR++OVBHbzHKVKkCEWKFKF///60a9eO+fPn06JFC8qXL8+xY8fiJc2f5OEk76OKFy/Orl276Nixo7ltz549FC9e3Lzu5ORE06ZNadq0KT179qRYsWL88ccflC9fPt7xsmTJYjEKKDGBgYEsWrSIvHnzYmNjQ6NGjczbnvU6H9W/f3+mTp3KypUradGixVN9P+zt7ePFX65cOaKjowkLC6NGjRrJiklEREQkqVq3bk3fvn1ZvHgxCxYsoFu3buZEbYkSJdi1a5dF/z179lCkSJF4Seek8PLyIk+ePPz111/meU2ehru7O15eXvz+++/m56bo6GgOHjxonnyxRIkSODg4cOHCBYsJwB+VK1cuOnfuTOfOnalRowaDBg1i8uTJ7N69G19fX4YNG2bu+2BixAeKFi3K77//TocOHcxtD0+QCAk/95UvX55ly5bh6emJm5vbU1/3Ax9++CF2dna0b9+emJgY2rVrl2C/nTt3Uq1aNXr06GFuS2jkd7ly5ShXrhxDhgyhatWqLF68mCpVqgDP/z2DiEh6pDIjIiLP0QsvvEBUVBSfffYZf/31F9988028shcPu3v3Lr169WLbtm2cP3+e3bt3s2/fPnNi+f3332fv3r307NmTQ4cOcerUKVavXk3v3r2fOcZBgwYRFBTE7NmzOXXqFFOnTmXFihXmyX+CgoKYO3cuR48eNV+Dk5MTvr6+CR7Pz8+PzZs3ExoayrVr1xI9b/v27Tlw4AAfffQRrVq1wtHR0bzteV2nm5sbb731FiNHjsQwjKf6fvj5+XHr1i02b97MlStXuHPnDkWKFKF9+/Z07NiRFStWcPbsWfbt28cnn3zC2rVrkxSTiIiISFK5uLjQpk0bhg4dyt9//03nzp3N29577z02b97M2LFj+fPPP1mwYAGff/65xUSOz2rUqFFMmDCBTz/9lD///JM//viD+fPnM3Xq1Mfu17t3byZMmMCPP/7IyZMn6du3L9euXTMn4F1dXRk4cCD9+/dnwYIFnDlzhoMHDzJz5kzz5JIjRozgxx9/5PTp0xw7doyff/7Z/ExcqFAhLly4wNKlSzlz5gwzZsxg5cqV8WKYO3cuCxYs4NSpU4wbN44jR45YjNb28/PjyJEjnDx5kitXrnD//n3at29Pzpw5adasGTt37uTs2bNs376dvn37cunSpad63T744AMmTJhAhw4dEhzh/eAa9u/fzy+//MKff/7J8OHDLSZPP3v2LEOGDGHv3r2cP3+eDRs28Oeff1K8eHGrvGcQEUmzrFatW0QkHUto8pgHpk6davj4+BhOTk5GQECAsXDhQgMwrl27ZhiG5YSDERERRtu2bY18+fIZ9vb2Ru7cuY1evXpZTNTy+++/G/Xq1TNcXFwMZ2dn48UXXzQ++uijRGNLaELDR33xxRdGwYIFjSxZshhFihQxFi5caN62cuVKo3Llyoabm5vh7OxsVKlSxdi0aZN5+6MTQK5evdooVKiQYWdnZ/j6+hqGEX8CyAdeeumleBMaPe/rPH/+vGFnZ2csW7bMMIwnfz8MwzC6d+9u5MiRwwCMkSNHGoZhGJGRkcaIESMMPz8/I0uWLIa3t7fRokUL48iRI4nGJCIiIvK87NmzxwAMf3//eNu+//57o0SJEkaWLFmM/PnzW0y+aBjxn9cMI+Fnp5UrVxqPpgUWLVpklC1b1rC3tzc8PDyMV155xVixYoVhGIlPanj//n2jV69ehpubm+Hh4WG8//77xuuvv260bdvW3CcmJsb49NNPjaJFixpZsmQxcuXKZQQEBBjbt283DCN2osnixYsbTk5ORvbs2Y1mzZoZf/31l3n/QYMGGTly5DBcXFyMNm3aGNOmTYt3PWPGjDFy5sxpuLi4GF26dDH69OljVKlSxbw9LCzM/LwJGFu3bjUMwzBCQkKMjh07Gjlz5jQcHByMggULGt26dTPCw8PjvfaPex2mTJli2NraGgsXLozX5969e0bnzp0Nd3d3I1u2bMa7775rfPDBB+Zn5tDQUKN58+aGj4+PYW9vb/j6+hojRowwoqOjU+Q9g4hIemUyjKcoIiUiIiIiIiIi8hRiYmIoXrw4rVu3ZuzYsVaLo169enh7e/PNN99YLQYREXm+VDNbRERERERERJ7Zg7IYNWvWJCIigs8//5yzZ88SGBiYajHcuXOH2bNnExAQgK2tLUuWLGHTpk1s3Lgx1WIQEZGUp2S2iIiIiIiIiDwzGxsbgoKCGDhwIIZhUKpUKTZt2mQxwXhKM5lMrF27lnHjxhEREUHRokX54YcfqFu3bqrFICIiKU9lRkREREREREREREQkzbOxdgAiIiIiIiIiIiIiIk+iZLaIiIiIiIiIiIiIpHlKZouIiIiIiIiIiIhImqdktoiIiIiIiIiIiIikeUpmi4iIiIiIiIiIiEiap2S2iIiIiIiIiIiIiKR5SmaLiIiIiIiIiIiISJqnZLaIiIiIiIiIiIiIpHlKZouIiIiIiIiIiIhImvf/Oee/2eeRIX4AAAAASUVORK5CYII=", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from sklearn.metrics import roc_auc_score, roc_curve, confusion_matrix\n", "import matplotlib.pyplot as plt\n", "import seaborn as sns\n", "\n", "X_test_selected = X_test[X_selected.columns]\n", "X_test_with_const = sm.add_constant(X_test_selected)\n", "y_pred_proba = final_model.predict(X_test_with_const)\n", "y_pred = (y_pred_proba > 0.5).astype(int)\n", "auc_score = roc_auc_score(y_test, y_pred_proba)\n", "\n", "fig, axes = plt.subplots(1, 2, figsize=(15, 6))\n", "# ROC-Kurve\n", "fpr, tpr, thresholds = roc_curve(y_test, y_pred_proba)\n", "axes[0].plot(fpr, tpr, color='blue', lw=2, label=f'ROC Kurve (AUC = {auc_score:.3f})')\n", "axes[0].plot([0, 1], [0, 1], color='red', lw=2, linestyle='--', label='Zufall (AUC = 0.5)')\n", "axes[0].set_xlim([0.0, 1.0])\n", "axes[0].set_ylim([0.0, 1.05])\n", "axes[0].set_xlabel('False Positive Rate')\n", "axes[0].set_ylabel('True Positive Rate')\n", "axes[0].set_title('ROC-Kurve')\n", "axes[0].legend(loc=\"lower right\")\n", "axes[0].grid(True, alpha=0.3)\n", "\n", "# Confusion Matrix\n", "cm = confusion_matrix(y_test, y_pred)\n", "sns.heatmap(cm, annot=True, fmt='d', cmap='Blues', ax=axes[1],\n", " xticklabels=['Kein Diebstahl', 'Diebstahl'],\n", " yticklabels=['Kein Diebstahl', 'Diebstahl'])\n", "axes[1].set_xlabel('Vorhergesagte Klasse')\n", "axes[1].set_ylabel('Tatsächliche Klasse')\n", "axes[1].set_title('Confusion Matrix')\n", "\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "2bff1bcb", "metadata": {}, "source": [ "Die ROC-Kurve zeigt mit einem AUC-Wert von 0,94 eine exzellente Diskriminierungsfähigkeit des Modells. Die Confusion Matrix zeigt ebenfalls eine gute Klassifikationsleistung: Das Modell erkennt normale Fahrten zuverlässig aber hat tendentiell mehr Schwierigkeiten bei Diebstählen. " ] }, { "cell_type": "markdown", "id": "4194adef", "metadata": {}, "source": [ "### Vergleich mit dem Generierungsmodell (Verlassen der Anwenderperspektive)\n", "\n", "Abschließend wird das trainierte Modell mit dem tatsächlich zur Generierung der Zielvariable verwendeten Modell verglichen. Die geschätzten Koeffizienten sollten – abgesehen von Zufallsschwankungen – mit den wahren Koeffizienten übereinstimmen. Dies zeigt, dass das systematische Vorgehen des Data Scientist erfolgreich war und das zugrundeliegende Modell korrekt rekonstruiert wurde." ] }, { "cell_type": "code", "execution_count": 225, "id": "bfa82528", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Modellkoeffizienten:\n", "const -14.413538\n", "avg_speed 0.288037\n", "hard_brakes 0.584179\n", "shift_frueh -2.262930\n", "shift_normal -2.280777\n", "speeding_manchmal -2.234968\n", "speeding_selten -2.135921\n", "dtype: float64\n" ] } ], "source": [ "coefficients = final_model.params\n", "print(\"\\nModellkoeffizienten:\")\n", "print(coefficients)" ] }, { "cell_type": "code", "execution_count": 226, "id": "621f7016", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Vergleich der geschätzten und wahren Koeffizienten:\n", " Geschätzte Koeffizienten Wahre Koeffizienten\n", "const -14.413538 -18.0\n", "avg_speed 0.288037 0.3\n", "hard_brakes 0.584179 0.6\n", "shift_frueh -2.262930 0.0\n", "shift_normal -2.280777 -0.8\n", "speeding_manchmal -2.234968 -0.8\n", "speeding_selten -2.135921 0.0\n" ] } ], "source": [ "true_betas_dict = {\n", " 'const': -18,\n", " 'avg_speed': 0.3,\n", " 'hard_brakes': 0.6,\n", " 'trip_distance': 0.,\n", " 'shift_normal': -0.8,\n", " 'shift_spaet': 1.5,\n", " 'speeding_manchmal': -0.8,\n", " 'speeding_haeufig': 1.5,\n", " 'weather_trocken': 0.,\n", " 'weather_winterlich': 0.,\n", " 'road_Außerorts': 0.,\n", " 'road_Innerorts': 0.,\n", " 'weekday_Sa': 0.,\n", " 'weekday_So': 0.\n", "}\n", "\n", "true_betas = pd.Series({var: true_betas_dict.get(var, 0) for var in coefficients.index})\n", "\n", "print(\"Vergleich der geschätzten und wahren Koeffizienten:\")\n", "comparison = pd.DataFrame({\n", " 'Geschätzte Koeffizienten': coefficients,\n", " 'Wahre Koeffizienten': true_betas\n", "})\n", "print(comparison)" ] }, { "cell_type": "markdown", "id": "c16e59df", "metadata": {}, "source": [ "Die geschätzten Koeffizienten sind nicht deckend gleich aber nähern sich den Koeffizienten des erstellten logistischen Regressionsmodells" ] }, { "cell_type": "markdown", "id": "7516554c", "metadata": {}, "source": [ "## Güte der Modellparameter" ] }, { "cell_type": "markdown", "id": "c1bb79ce", "metadata": {}, "source": [ "### Einfluss des Stichprobenumfangs\n", "\n", "In diesem Abschnitt wird untersucht, wie sich der Stichprobenumfang auf die Schätzgüte der Modellparameter auswirkt. Dazu werden jeweils k = 1.000 zufällige Stichproben aus der Grundgesamtheit gezogen, mit Stichprobenumfängen n von 1.000 bis 50.000 (Schrittweite 5.000). Für jede Stichprobe wird das optimale Modell aus Abschnitt 3 trainiert und der geschätzte Beta-Wert einer erklärenden Variable (z.B. `avg_speed`) gespeichert. Die Verteilungen der geschätzten Beta-Werte werden für drei ausgewählte Stichprobenumfänge verglichen und der funktionale Zusammenhang zwischen n und der Standardabweichung der Schätzungen analysiert." ] }, { "cell_type": "code", "execution_count": 227, "id": "616ae484", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Stichprobenumfang: 0%| | 0/10 [00:00" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(12, 6))\n", "for n in [1000, 11000, 46000]:\n", " sns.kdeplot(betas_by_n[n][~np.isnan(betas_by_n[n])], label=f\"n={n}\")\n", "plt.title(\"Verteilung des geschätzten Beta-Werts für avg_speed bei verschiedenen Stichprobenumfängen\")\n", "plt.xlabel(\"Geschätzter Beta-Wert für avg_speed\")\n", "plt.ylabel(\"Dichte\")\n", "plt.legend()\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "990bb2a0", "metadata": {}, "source": [ "Mit wachsendem Stichprobenumfang werden die Verteilungen der geschätzten Beta-Werte schmaler und konzentrieren sich stärker um den wahren Wert. Kleine Stichproben führen zu einer größeren Streuung und damit zu unsichereren Schätzungen." ] }, { "cell_type": "markdown", "id": "50ea2928", "metadata": {}, "source": [ "### Funktionaler Zusammenhang zwischen n und der Standardabweichung des geschätzten Beta-Werts\n", "\n", "Für jeden Stichprobenumfang wird die Standardabweichung der geschätzten Beta-Werte berechnet und gegen n aufgetragen. Zusätzlich wird die theoretische Entwicklung der Standardabweichung nach der Formel $\\sigma(\\hat{\\beta}) \\propto 1/\\sqrt{n}$ eingezeichnet." ] }, { "cell_type": "code", "execution_count": 229, "id": "cf7a7e61", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "stds = np.array([np.nanstd(betas_by_n[n]) for n in n_values])\n", "\n", "plt.figure(figsize=(10, 6))\n", "plt.plot(n_values, stds, marker='o', label='Empirische Standardabweichung')\n", "plt.plot(n_values, stds[0]*np.sqrt(n_values[0]/n_values), '--', label=r'$\\propto 1/\\sqrt{n}$')\n", "plt.xlabel('Stichprobenumfang n')\n", "plt.ylabel('Standardabweichung des geschätzten Beta-Werts')\n", "plt.title('Zusammenhang zwischen Stichprobenumfang und Schätzgenauigkeit')\n", "plt.legend()\n", "plt.grid(True)\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "10afcd69", "metadata": {}, "source": [ "Die Standardabweichung der Schätzung eines Modellparameters nimmt mit wachsendem Stichprobenumfang näherungsweise proportional zu $1/\\sqrt{n}$ ab. Das bedeutet: Je mehr Daten zur Verfügung stehen, desto präziser und stabiler werden die Parameterschätzungen. Die Lernqualität eines Modells steigt also mit der Datenmenge, wobei der Zugewinn mit zunehmender Datenmenge abnimmt (abnehmender Grenznutzen)." ] } ], "metadata": { "kernelspec": { "display_name": "base", "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": "3.10.9" } }, "nbformat": 4, "nbformat_minor": 5 }