From 4b296ee1b089959d5bbdb0866fdd024284ddf2ff Mon Sep 17 00:00:00 2001 From: crangelsmith <camila.rangel.smith@gmail.com> Date: Tue, 30 Mar 2021 14:11:07 +0100 Subject: [PATCH] updating notebook --- pruebas_de_hipotesis.ipynb | 384 ++++++++++++++++--------------------- 1 file changed, 167 insertions(+), 217 deletions(-) diff --git a/pruebas_de_hipotesis.ipynb b/pruebas_de_hipotesis.ipynb index afa2955..c66c0c4 100644 --- a/pruebas_de_hipotesis.ipynb +++ b/pruebas_de_hipotesis.ipynb @@ -7,9 +7,16 @@ "# Pruebas de hipótesis" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Este notebook esta basado en el materia de [este repositorio](https://github.com/ethen8181/machine-learning/blob/master/ab_tests/frequentist_ab_test.ipynb) y ha sido traducido y adaptado para esta práctica." + ] + }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -24,7 +31,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -68,7 +75,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "metadata": {}, "outputs": [ { @@ -82,15 +89,15 @@ "source": [ "# generar algún número aleatorio que nos sirva de población\n", "np.random.seed(10)\n", - "population_ages1 = stats.poisson.rvs(loc = 18, mu = 35, size = 150000)\n", - "population_ages2 = stats.poisson.rvs(loc = 18, mu = 10, size = 100000)\n", - "population_ages = np.concatenate((population_ages1, population_ages2))\n", - "print('media de la población:', np.mean(population_ages))" + "poblacion_edad1 = stats.poisson.rvs(loc = 18, mu = 35, size = 150000)\n", + "poblacion_edad2 = stats.poisson.rvs(loc = 18, mu = 10, size = 100000)\n", + "poblacion_edad = np.concatenate((poblacion_edad1, poblacion_edad2))\n", + "print('media de la población:', np.mean(poblacion_edad))" ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "metadata": {}, "outputs": [ { @@ -103,8 +110,8 @@ ], "source": [ "np.random.seed(6)\n", - "sample_ages = np.random.choice(population_ages, size = 500)\n", - "print('media de la muestra:', np.mean(sample_ages))" + "muestra_edad = np.random.choice(poblacion_edad, size = 500)\n", + "print('media de la muestra:', np.mean(muestra_edad))" ] }, { @@ -137,7 +144,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "<Figure size 864x432 with 2 Axes>" ] @@ -149,11 +156,11 @@ "source": [ "fig = plt.figure(figsize = (12, 6))\n", "plt.subplot(1, 2, 1)\n", - "plt.hist(population_ages)\n", - "plt.title('Population')\n", + "plt.hist(poblacion_edad)\n", + "plt.title('Población')\n", "plt.subplot(1, 2, 2)\n", - "plt.hist(sample_ages)\n", - "plt.title('Sample')\n", + "plt.hist(muestra_edad)\n", + "plt.title('Muestra')\n", "plt.show()" ] }, @@ -187,7 +194,7 @@ "source": [ "np.random.seed(10)\n", "samples = 200\n", - "point_estimates = [np.random.choice(population_ages, size = 500).mean()\n", + "point_estimates = [np.random.choice(poblacion_edad, size = 500).mean()\n", " for _ in range(samples)]\n", "\n", "plt.hist(point_estimates)\n", @@ -218,7 +225,7 @@ } ], "source": [ - "population_ages.mean() - np.mean(point_estimates)" + "poblacion_edad.mean() - np.mean(point_estimates)" ] }, { @@ -260,7 +267,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 8, "metadata": {}, "outputs": [ { @@ -275,19 +282,19 @@ ], "source": [ "np.random.seed(10)\n", - "sample_size = 1000\n", - "sample = np.random.choice(population_ages, size = sample_size)\n", - "sample_mean = sample.mean()\n", - "\n", - "confidence = 0.95\n", - "z_critical = stats.norm.ppf(q = confidence + (1 - confidence) / 2)\n", - "print('valor z crÃtico:', z_critical) \n", - "\n", - "pop_stdev = population_ages.std()\n", - "margin_of_error = z_critical * (pop_stdev / np.sqrt(sample_size))\n", - "confint = sample_mean - margin_of_error, sample_mean + margin_of_error\n", - "print('parámetro estimado:', sample_mean)\n", - "print('Intervalo de confianza:', confint)" + "tamano_muestra = 1000\n", + "muestra = np.random.choice(poblacion_edad, size = tamano_muestra)\n", + "media_muestra = muestra.mean()\n", + "\n", + "intervalo_confianza = 0.95\n", + "z_critico = stats.norm.ppf(q = intervalo_confianza + (1 - intervalo_confianza) / 2)\n", + "print('valor z crÃtico:', z_critico) \n", + "\n", + "poblacion_stdev = poblacion_edad.std()\n", + "margen_error = z_critico * (poblacion_stdev / np.sqrt(tamano_muestra))\n", + "int_conf = media_muestra - margen_error, media_muestra + margen_error\n", + "print('parámetro estimado:', media_muestra)\n", + "print('Intervalo de confianza:', int_conf)" ] }, { @@ -315,29 +322,30 @@ ], "source": [ "np.random.seed(12)\n", - "confidence = 0.95\n", - "sample_size = 1000\n", + "intervalo_confianza = 0.95\n", + "tamano_muestra = 1000\n", "\n", - "intervals = []\n", - "sample_means = []\n", + "intervalos = []\n", + "muestras = []\n", "for sample in range(25):\n", - " sample = np.random.choice(population_ages, size = sample_size)\n", - " sample_mean = sample.mean()\n", - " sample_means.append(sample_mean)\n", - "\n", - " z_critical = stats.norm.ppf(q = confidence + (1 - confidence) / 2) \n", - " pop_std = population_ages.std()\n", - " margin_error = z_critical * (pop_stdev / np.sqrt(sample_size))\n", - " confint = sample_mean - margin_error, sample_mean + margin_error \n", - " intervals.append(confint)\n", + " muestra = np.random.choice(poblacion_edad, size = tamano_muestra)\n", + " media_muestra = muestra.mean()\n", + "\n", + " muestras.append(media_muestra)\n", + "\n", + " z_critico = stats.norm.ppf(q = intervalo_confianza + (1 - intervalo_confianza) / 2) \n", + " poblacion_stdev = poblacion_edad.std()\n", + " margen_error = z_critico * (poblacion_stdev / np.sqrt(tamano_muestra))\n", + " int_conf = media_muestra - margen_error, media_muestra + margen_error \n", + " intervalos.append(int_conf)\n", " \n", "\n", "plt.figure(figsize = (10, 8))\n", - "plt.errorbar(x = np.arange(0.1, 25, 1), y = sample_means, \n", - " yerr = [(top - bot) / 2 for top, bot in intervals], fmt = 'o')\n", + "plt.errorbar(x = np.arange(0.1, 25, 1), y = muestras, \n", + " yerr = [(top - bot) / 2 for top, bot in intervalos], fmt = 'o')\n", "\n", "plt.hlines(xmin = 0, xmax = 25,\n", - " y = population_ages.mean(), \n", + " y = poblacion_edad.mean(), \n", " linewidth = 2.0, color = red)\n", "plt.show()" ] @@ -402,19 +410,19 @@ "- $n$ es el número de lanzamientos de la moneda\n", "- $p$ es la probabilidad de obtener caras en cada tirada\n", "\n", - "El $\\binom{n}{k}$ nos dice cuántas formas hay de obtener $k$ caras de un número total de $n$ lanzamientos de la moneda\" y el $p^k(1-p)^{n-k}$ responde a la pregunta \"¿cuál es la probabilidad de obtener $k$ caras y $n-k$ colas?\", multiplÃquelos y obtendremos la probabilidad de obtener exactamente $k$ caras.\n", + "El $\\binom{n}{k}$ nos dice cuántas formas hay de obtener $k$ caras de un número total de $n$ lanzamientos de la moneda\" y el $p^k(1-p)^{n-k}$ responde a la pregunta \"¿cuál es la probabilidad de obtener $k$ caras y $n-k$ cruz?\", multiplÃquelos y obtendremos la probabilidad de obtener exactamente $k$ caras.\n", "\n", "Ahora que entendemos el método clásico, vamos a utilizarlo para comprobar si realmente estamos lanzando una moneda justa." ] }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 10, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", "text/plain": [ "<Figure size 576x432 with 1 Axes>" ] @@ -424,20 +432,20 @@ } ], "source": [ - "# Calculate the probability for every possible outcome\n", - "# of tossing a fair coin 30 k_range\n", + "# Calcular la probabilidad para cada resultado posible\n", + "# de lanzar una moneda justa 30 k_range\n", "\n", - "k_range = range(1, 31) # number of heads appearing\n", - "n = 30 # number of k_range tossing the coin\n", - "p = 0.5 # probability of coin appearing up as head\n", + "k_rango = range(1, 31) # rango del número de cabezas que aparecen\n", + "n = 30 # número de k_range lanzando la moneda\n", + "p = 0.5 # probabilidad de que la moneda salga cara\n", "\n", - "prob = stats.binom(n = n, p = p).pmf(k = k_range)\n", + "prob = stats.binom(n = n, p = p).pmf(k = k_rango)\n", "\n", "# Plot the probability distribution using the probabilities list \n", "# we created above.\n", - "plt.step(k_range, prob, where = 'mid', color = blue)\n", - "plt.xlabel('Number of heads')\n", - "plt.ylabel('Probability')\n", + "plt.step(k_rango, prob, where = 'mid', color = blue)\n", + "plt.xlabel('Número de caras')\n", + "plt.ylabel('Probabilidad')\n", "plt.plot((22, 22), (0, 0.1599), color = red)\n", "plt.annotate('0.8%', xytext = (25, 0.08), xy = (22, 0.08), \n", " va = 'center', color = red, size = 'large',\n", @@ -455,7 +463,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 11, "metadata": {}, "outputs": [ { @@ -504,7 +512,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 12, "metadata": {}, "outputs": [ { @@ -516,14 +524,14 @@ } ], "source": [ - "def compute_pvalue(n, k, p):\n", - " \"\"\"Returns the p-value for binomial distribution\"\"\"\n", - " k_range = range(k, n + 1)\n", - " pvalue = stats.binom(n = n, p = p).pmf(k = k_range).sum()\n", + "def calcular_pvalue(n, k, p):\n", + " \"\"\"Devuelve el valor p para la distribución binomial\"\"\"\n", + " k_rango = range(k, n + 1)\n", + " pvalue = stats.binom(n = n, p = p).pmf(k = k_rango).sum()\n", " return pvalue\n", "\n", "\n", - "pvalue = compute_pvalue(n = 30, k = 22, p = 0.5)\n", + "pvalue = calcular_pvalue(n = 30, k = 22, p = 0.5)\n", "print('P-value: {:0.1f}%'.format(pvalue * 100))" ] }, @@ -540,7 +548,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 13, "metadata": {}, "outputs": [ { @@ -552,8 +560,8 @@ } ], "source": [ - "# we can also use the binom_test function from scipy to\n", - "# perform the hypothesis testing\n", + "# también podemos utilizar la función binom_test de scipy para\n", + "# realizar la prueba de hipótesis\n", "pvalue = stats.binom_test(x = 22, n = 30, p = 0.5, alternative = 'greater')\n", "print('P-value: {:0.1f}%'.format(pvalue * 100))" ] @@ -562,7 +570,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Simulation" + "## Simulación o toys" ] }, { @@ -574,7 +582,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 14, "metadata": {}, "outputs": [ { @@ -586,23 +594,23 @@ } ], "source": [ - "def coin_toss(n_simulation = 100000):\n", + "def lanzamiento_moneda(n_toys = 100000):\n", " \"\"\"\n", - " computing a fair coin resulting in at\n", - " least 22 heads or more through simulation\n", + " calcular una moneda justa que dé como resultado al menos\n", + " al menos 22 caras o más a través de la simulación\n", " \"\"\"\n", " pvalue = 0\n", - " for i in range(n_simulation):\n", - " # trials: 1 denotes head, 0 denotes tail\n", - " trials = np.random.randint(2, size = 30)\n", - " if trials.sum() >= 22:\n", + " for i in range(n_toys):\n", + " # ensayos: 1 significa cara, 0 significa cruz\n", + " ensayos = np.random.randint(2, size = 30)\n", + " if ensayos.sum() >= 22:\n", " pvalue += 1\n", "\n", - " pvalue /= n_simulation\n", + " pvalue /= n_toys\n", " return pvalue\n", "\n", "\n", - "pvalue = coin_toss()\n", + "pvalue = lanzamiento_moneda()\n", "print('Simulated P-value: {:0.1f}%'.format(pvalue * 100))" ] }, @@ -637,7 +645,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 15, "metadata": {}, "outputs": [ { @@ -689,7 +697,7 @@ "1 B 4473 527" ] }, - "execution_count": 14, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -799,21 +807,21 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 16, "metadata": {}, "outputs": [], "source": [ - "def test_de_dos_proporciones(success_a, size_a, success_b, size_b):\n", + "def test_de_dos_proporciones(exito_a, tamano_a, exito_b, tamano_b):\n", " \"\"\"\n", " Prueba A/B para dos proporciones; dado un éxito un tamaño de prueba \n", " del grupo A y B calcular su puntuación z y su valor p\n", " \n", " Parametros\n", " ----------\n", - " success_a, success_b : int\n", + " exito_a, exito_b : int\n", " Número de éxitos en cada grupo\n", " \n", - " size_a, size_b : int\n", + " tamano_a, tamano_b : int\n", " Tamaño, o número de observaciones en cada grupo\n", " \n", " Returns\n", @@ -824,9 +832,9 @@ " pvalue : float\n", " p-value para el test estadÃstico de dos proporciones\n", " \"\"\"\n", - " prop_a = success_a / size_a\n", - " prop_b = success_b / size_b\n", - " prop_pooled = (success_a + success_b) / (size_a + size_b)\n", + " prop_a = exito_a / size_a\n", + " prop_b = exito_b / size_b\n", + " prop_pooled = (exito_a + exito_b) / (tamano_a + tamano_b)\n", " var = prop_pooled * (1 - prop_pooled) * (1 / size_a + 1 / size_b)\n", " zscore = np.abs(prop_b - prop_a) / np.sqrt(var)\n", " one_side = 1 - stats.norm(loc = 0, scale = 1).cdf(zscore)\n", @@ -840,18 +848,22 @@ "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "valor z = 1.359, pvalue = 0.174\n" + "ename": "NameError", + "evalue": "name 'success_a' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m<ipython-input-17-5ae74c47944f>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0mtamano_b\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m5000\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 6\u001b[0;31m \u001b[0mzscore\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpvalue\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtest_de_dos_proporciones\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msuccess_a\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msize_a\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msuccess_b\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msize_b\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 7\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'valor z = {:.3f}, pvalue = {:.3f}'\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mzscore\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mNameError\u001b[0m: name 'success_a' is not defined" ] } ], "source": [ - "success_a = 486\n", - "size_a = 5000\n", - "success_b = 527\n", - "size_b = 5000\n", + "exito_a = 486\n", + "tamano_a = 5000\n", + "exito_b = 527\n", + "tamano_b = 5000\n", "\n", "zscore, pvalue = test_de_dos_proporciones(success_a, size_a, success_b, size_b)\n", "print('valor z = {:.3f}, pvalue = {:.3f}'.format(zscore, pvalue))" @@ -859,17 +871,9 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "zscore = -1.359, pvalue = 0.174\n" - ] - } - ], + "outputs": [], "source": [ "# o podemos usar la implementación de statsmodels\n", "# donde pasamos el éxito (llaman al argumento counts)\n", @@ -904,11 +908,11 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ - "def test_de_dos_proporciones_cint(success_a, size_a, success_b, size_b, significance = 0.05):\n", + "def test_de_dos_proporciones_cint(exito_a, tamano_a, exito_b, tamano_b, significance = 0.05):\n", " \"\"\"\n", " Prueba A/B para dos proporciones;\n", " dado un éxito un tamaño de prueba del grupo A y B calcular\n", @@ -918,10 +922,10 @@ " \n", " Parametros\n", " ----------\n", - " success_a, success_b : int\n", + " exito_a, exito_b : int\n", " Número de éxitos en cada grupo\n", " \n", - " size_a, size_b : int\n", + " tamano_a, tamano_b : int\n", " Tamaño, o número de observaciones en cada grupo\n", " \n", " significance : float, default 0.05\n", @@ -938,9 +942,9 @@ " confint : 1d ndarray\n", " Intervalo de confianza del test estadÃstico de las dos proporciones\n", " \"\"\"\n", - " prop_a = success_a / size_a\n", - " prop_b = success_b / size_b\n", - " var = prop_a * (1 - prop_a) / size_a + prop_b * (1 - prop_b) / size_b\n", + " prop_a = exito_a / tamano_a\n", + " prop_b = exito_b / tamano_b\n", + " var = prop_a * (1 - prop_a) / tamano_a + prop_b * (1 - prop_b) / tamano_b\n", " se = np.sqrt(var)\n", " \n", " # z critical value\n", @@ -956,18 +960,9 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Diferencia estimada: 0.008199999999999999\n", - "Intervalo de confianza: [-0.00362633 0.02002633]\n" - ] - } - ], + "outputs": [], "source": [ "prop_diff, confint = test_de_dos_proporciones_cint(success_a, size_a, success_b, size_b)\n", "print('Diferencia estimada:', prop_diff)\n", @@ -1016,20 +1011,20 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ - "def plot_power(min_diff, prob_b, size_a, size_b, significance = 0.05):\n", + "def plot_poder_estadistico(min_diff, prob_b, tamano_a, tamano_b, significance = 0.05):\n", " \"\"\"illustrating power through a one-tailed hypothesis test\"\"\"\n", " \n", " # obtain the z-score for the minimum detectable\n", " # difference using proportion_ztest\n", " prob_a = prob_b + min_diff\n", - " count_a = size_a * prob_a\n", - " count_b = size_b * prob_b\n", + " count_a = tamano_a * prob_a\n", + " count_b = tamano_b * prob_b\n", " counts = np.array([count_a, count_b])\n", - " nobs = np.array([size_a, size_b])\n", + " nobs = np.array([tamano_a, tamano_b])\n", " zscore, _ = proportions_ztest(counts, nobs, alternative = 'larger')\n", "\n", " # distribution for the null hypothesis, h0\n", @@ -1056,7 +1051,7 @@ " alpha = 0.2, color = line[0].get_color())\n", " \n", " title = 'p1: {}, p2: {}, tamaño 1: {}, tamaño 2: {}, poder estadÃstico: {}'\n", - " plt.title(title.format(prob_a, prob_b, size_a, size_b, power))\n", + " plt.title(title.format(prob_a, prob_b, tamano_a, tamano_b, power))\n", " plt.legend()\n", " plt.tight_layout()\n", " plt.show()" @@ -1064,27 +1059,16 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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2X6ytxdqPXN8bzrrN19e3VR+zMU25BqWlpbZm0htvvLFZw9xacg0cPba0tJR33nmHxMRE3n33XVvT/tVXX81NN93EE088wYQJExwetu3h4cHTTz/NE088wYMPPoiHhwejRo1i2rRpXH/99XWG1F6ssLCQ+++/H39/f1JSUmzxFBUVUVZWxnfffWfXn15b7dqJtqAoCs8++ywffvghAwcO5PXXX7frNrzssstsH/a1zZo1i6+//podO3YQFxeHt7d3va+Ltb7A+po6up+jHn30Ue677z6ef/55/vGPf5CQkMDUqVP5/e9/32h/vaIoLFiwgOzsbN5991277sKcnBwKCwsbHBpe3+uybt06Fi1ahI+PD2+99RZhYWFNei5NOV9cXBxxcXF1jrnxxht55pln2LFjB7fddhve3t51ajzgwvX28fEBcHi/prp4+La12+rkyZOApUYqMjLSlhRaeXh4EBkZadtv0qRJvPjii2zfvp2ZM2eya9cuHnroIUJCQtiwYQNgaTVxc3OzdTU39TVs7ud9S67dBx98wNmzZ3n99de5/PLLAUtrTXx8PA899BCffPKJ3bB+ZyXJSSu7+A8CLH3NQL191S1l/XA5e/ZsnfsKCgrw9/evUwjX1hy9BufPn+fuu+8mNTWVWbNmsWTJkmb9mmrJNXD02AMHDmAwGLjmmmvsnoO7uzvXXnstL730EpmZmXYjVRpz7bXXMnHiRL777jt++OEHfv31V37++Wc++uijS87NYjQa+fOf/0xBQQEffvih3Qeg9TpPnz6d2bNn13t8Y91kLWEymVi8eDFr164lKSmJd955B39/f4eOtT4PaytSr169KCgoqLOfdZv1i9/R/RzVv39/Nm7cyE8//cSWLVv46aefePXVV1m5ciWrVq265NwmL7/8Mlu2bGHx4sV1fjWbTCaio6N56qmn6j324uv0ySefsGTJEgICAnj33Xeb9N6qT3PP5+7ujr+/v93rUlJSgsFgsHuP1ve6OLJfUzX0+WLtnr5Ua6jZbLYdHxsbS1hYGNu3b6dPnz6UlJQwatQoQkNDef/99zlx4gQ///wzw4YNs3UJN/U1bG6XeUuu3dGjR/Hx8bElJlYzZszA29ubnTt3dojkRLp1WllOTk6dbdnZ2bi6uhIREdHqj+fv709ERES9I1KOHDlCYmJiqz9mYxy5BuXl5bbE5M477+Tpp59udjNvS66Bo8daPyCsX/61WSv7a1f4N6aiooLdu3ej0Wi46aabWLZsGdu2beP2228nLS2Nn3/+ucFjn3/+eXbu3Mnjjz9uK7KzCg4OxsvLC6PRyLhx4+z+RUdHU1lZWW99TWt58sknWbt2LSNHjmTlypX1JiZ333038+bNq7PdOtOu9T0ycOBA0tPT64wYOXLkCJ6ensTGxjZpP0eYTCYOHz7MqVOnuPzyy3n22Wf54YcfSElJoaysjNWrVzd47DfffMObb77JVVddVe9ItIiICIqLixkzZozd6zJy5EiKi4vtEug1a9bw1FNPERISwn//+98WJyaOnO/ll1/m8ssvp7y83G57cXExhYWFtkLKhIQEFEUhNTXVbj/r/wcNGtSk/Zrq4pqswsJCysrKbEX24eHh5ObmUl1dbbefwWAgLy/PbjK5iRMnsn37dnbt2kVwcDAxMTGMGDECjUbDr7/+ys6dO+1a+ZryGrZES65dQ59ViqKgKEqTPqfUJMlJKzt48KDdFOznzp3jf//7H2PGjCEgIKBNHnPatGls27bNbsjkr7/+SlZWliqzMDpyDZ5++mlSU1O5/fbbWbx4cYsfsyXXwJFjY2Nj6d69O19++aVdF4Jer2fNmjUEBQU16Uvw2LFj3HrrrbZ+fLB8qFgLaxtqZVu9ejX//e9/SU5OtpsDwcrNzY1Jkybxww8/kJaWZnffCy+8wPz5820jElrbZ599xmeffcbQoUN56623GuxOCQwM5Oeff+bgwYO2bQaDgbfeegs/Pz/bl8H06dOprKzkyy+/tO1XWFjIN998w/Tp021dRY7u5wjr7LYXFw5ai0Yb+iWclpbG4sWLiYuLsxX0Xmzq1KkUFxfbRslYffLJJzz88MNs27YNsBQMW0fHfPDBBy2ehdbR84WFhZGXl2f3ngRsM8hee+21gKVbztPTkw8++MC2j9ls5qOPPiI8PNyWMDu6X1N9+OGHdq0j1lE6V155JWC5zuXl5fz3v/+1O+6jjz6ioqKCyZMn27ZNmjSJnJwcvvrqK1tLl/VvecWKFVRWVtrt7+hr2FItuXbjx4+noqKCr776ym772rVrqaqqqrNEhLOSbp1W5uHhwbx587jjjjvQarV89NFHmM1mHn300SafKzc3l99++41hw4Zdsil+3rx5rF27ljvvvJO77roLvV7P22+/TUJCgt0oC0fP15JYoPFrcPz4cdauXYu/vz8DBgxg7dq1dc5hjbs9roEjx7q6uvLkk0/y4IMPctNNN3HTTTdhNpv5/PPPyczMtA0pdjTmwYMHM2LECFJSUjh16hTx8fGcOnWKDz/8kL59+9bbp33kyBGWLFlCSEgIEydO5KuvvrL7FeTj48MVV1zBggUL2LFjB7feeiu33norYWFhbN26lS1btjBr1qwmJVFg6Wb59ttv6d27t90w1tpMJhOvvPIKAFOmTGHTpk119hk/fjwhISE88sgj/Pjjj8ydO5c5c+bg5+fH2rVrOXLkCP/85z9tSc3kyZMZPXo0S5YsITc3lx49eti+mP7f//t/tvM6up8jz8PDw4M5c+bwxhtvMH/+fCZOnIhOp2PVqlV4eXlx44031nt95s+fj16v5/e//z1btmyp04pz5ZVXcvPNN/Pll1/yzDPPcPjwYZKSkjh69CirVq0iISGB5ORkAJYvX47BYGDixIns37+f/fv3250rPj7e1vJhrSu61AgQR893ww038Omnn/LSSy9x4sQJ4uLi2LZtG5s2bWLWrFl2X9733HMPy5Yts80NsnHjRvbs2WNX/+Tofo4+D6sdO3Ywb948pkyZwv79+1m7di3XX389w4cPB7Bd5xdeeIGjR4+SmJjIoUOH+OKLLxgyZAg333yz7VzWIcUHDx60+5wYNWoUH374IeHh4XY1dI6+hpfiyHNtybW78cYbWbNmDY8//jgHDhygf//+HDlyhE8//ZQBAwY02N3rdNplHtouYsqUKcptt92mfPzxx8rEiROVIUOGKHPnzrWbzvtSx13s888/V+Li4pTPP/+80cc+fvy4MnfuXGXIkCHKmDFjlIULFyrnz59v8vlaGosj1+Cjjz6yTZXe0L/2vgaOHKsoivLrr78qt912mzJ48GBl8ODByh/+8Aflhx9+aNa1KioqUp555hll6tSpSmJiojJ+/Hjl8ccfVwoKCmz7LFy40HY9rOdt6F/tacdPnDihPPLII8ro0aOVQYMGKVdddZWycuXKS057XfuxasvNzVXi4uIuOd18RkZGo6/p9u3bbfunp6cr9957rzJ06FAlKSlJmTVrlrJ169Y65y0tLVWefPJJZdSoUcrQoUOVO+64Qzly5Eiz9nPkeSiKZZrwlStXKtdcc40yZMgQZfjw4cq8efOUgwcP2vaxvhbbt2+3nfdS/3JzcxVFUZSysjLlhRdeUKZMmaIkJCQoU6ZMUZ555hmlsLDQdu5x48Zd8lyvvvqqbd8pU6Y0Ot18U85XVFSkPPHEE8q4ceOUhIQEZcaMGcrKlSsVk8lkd06z2ay8/fbbypQpU5RBgwYp1157rbJhw4Y6j+3ofo48D+s1/+qrr5S77rpLGTRokDJ16lTl3//+d534rNf5sssuUxISEpTLL79c+b//+z+lqqqqznlvv/12JS4uzu4zasOGDUpcXJzy97//vc7+jryGtd8fzXmuitKya1deXm57/gMHDlQmTZqkPPPMM0ppaWmjj+ssNIrSgZYpdHJTp04lPDzcrimuM3n++edJSkrimmuuaXCfzn4NHOXItRLt77vvvuPHH3/k6aefVjsUUUtZWRk33XQTGzdubHCfL774gsWLF/P+++93mK4J0XxScyIccu7cOb7//ntVCmw7GrlWzslgMPDZZ581ecVr0fY++ugju8nlhJDkRDiksLCQhQsX1jvtvLAn18o5mc1mRo8eXW/diFCXr6+v3WymQkhBrHBIQxM0ibrkWjknrVZrm01UOJeLZ3MVQmpOhBBCCOFUOnzLidlspqKiAnd393ZfQ0YIIYQQTacoCtXV1fj4+NQ7f1CHT04qKirsFgoTQgghRMcQFxdX74rxHT45sU58FRcX5/Cia53JoUOHZFRIK5Dr2DrkOrYOuY6tQ65j62iL62gwGDh69Gi9ayVBJ0hOrF05Hh4eja7k2ll11efd2uQ6tg65jq1DrmPrkOvYOtrqOjZUjiFDiYUQQgjhVCQ5EUIIIYRTkeRECCGEEE5FkhMhhBBCOBVJToQQQgjhVDr8aB0hhBDOp7S0lIKCAqqrq1WLwc3NjdTUVNUev7No6nV0d3ene/fu+Pv7N/8xHd1x3bp1vPHGG+Tm5hIeHs69997L9ddf79Cxp06d4pprruHuu+/m/vvvt203Go0sX76cL7/8kuLiYhISEli0aJGsGiqEEB1YaWkpZ86cITw8HC8vL9Vm766oqMDHx0eVx+5MmnIdFUWhqqqKkydPAjQ7QXGoW2f9+vUsWLCACRMm8NprrzFq1CgWLlzIN99841Cgjz32GOXl5XXue+6553j33XeZN28eKSkpuLq6cuedd5Kbm9v0ZyKEEMIpFBQUEB4ejre3tywr0sVoNBq8vb0JDw+noKCg2edxqOUkJSWFmTNnsnjxYgAmTpxISUkJr7zyCjNmzLjksR999BGZmZl1tufl5bFq1SqeeOIJ/vCHPwAwYcIEpk+fzttvv82SJUua+lyEEEI4gerqary8vNQOQ6jIy8urRV16jbac5ObmkpOTw7Rp0+y2T58+nczMzEu2cuTm5vLPf/6TZ555ps5927dvx2QyMX36dNs2Dw8PJk+ezI8//tiU5yCEEMLJSItJ19bS17/R5MTa6tGnTx+77VFRUQBkZWXVe5zZbGbRokXMnDmTSZMm1XvegIAAgoOD65w3Pz8fnU7n2DMQQgghRKfSaLdOWVkZAL6+vnbbrcUx9dWSALz33nvk5eXx5ptv1nt/eXl5nXPWPm9FRQVarbax8IQQTkB/5gRl+7/H68xpdL0C0IbFqB1Sl2YyK2zdk0vumTL6hgfQPzqY0ED1ClOFaKpGkxNFUS55v4tL3caX48eP8/LLL/Pqq6/WuxSyI+dt6h/RoUOHmrR/Z7Jnzx61Q+gU5Do2kdmMe8FRPLN3416UA4AWyF+5B2NAOLqoEVT37A8ururG2UE19/14qsjAVzuKyC+07+/383IhMsSTkXE+9OnRtj/83NzcqKioaNPHcJSzxNHRNec6GgyGZr+PG01OrMnFxYFZW0wuTj5MJhOLFy9mxowZjB8/HqPRaLvPbDZjNBpxc3PD19e33idrPW99rSqXkpiY2CVXn9yzZw/Dhw9XO4wOT65j01Rm/MbZDW9jKj13YaPGBQUFjaLgVnIS3wMncc38kW7T78a3/1j1gu2AmvN+1OmNfLwpnTU/nsRsrvvjr6zKzJHcKtJP6vjbXaMZMaBHa4VbR2pqqlMM4ZWhxK2judfRw8ODwYMH13ufXq+/ZKNCozUn1lqTnJwcu+3Z2dl291udOnWK/fv3s2bNGhISEmz/AJYtW2a73bdvX4qLiykpKalz3oiICDw8PBoLTQihAv2ZE5z5/CVbYuKi9SFgzHVE3v8aJZfNJ3D8jbh4W+Y2MJUXUfDly+hOHlUz5E4v82QJ8/+5hS+2ZmA2K7hoNEwcEsZzfxrHn2cN5doJfUno2w1XFw0ms8Lz7+7kcOZ5tcPukL777jvi4+PZtGlTvffPnj2bqVOntnNU9hrrmegIGk1OoqKiiIiIqDOnyaZNm4iOjiYsLMxue/fu3fnss8/q/AP4wx/+YLs9btw4ADZu3Gg71mAwsHXrVtt9QgjnYtJVcObzl1CMBkBDt2l30fuB/9Dt8ttxD+yOovUnePIt9H7g34RcdZ+lS8ds5MznL2EsL1Y7/E6pSm/kH+/tpKCwEoDw7r48NGsoyZNj8da6E93Ln6kjIpn7u0TuuHogLhqoNppZ8vZ2jucVqxt8B5SWlgbAwIED69xnNptJS0sjLi6uWeeeOnUqjz/+eIvi27JlCwsXLmzROZyBQ/OczJ8/n8WLFxMQEMDkyZPZvHkzGzZsICUlBYDCwkJycnKIiYnB19eXQYMG1Xue7t272+4LDw/nhhtu4Nlnn6WyspKoqChWrlxJaWkpc+fObaWnJ4RoLYpi5uzaVzAWnQYgaPIfCBh5db37urh54D/0ChRTNec3vo2prJCCL/+PXrc+hUZqUFrViq8Oc/q8JTG5bGg4v5vYDxeX+mv2BvULYfaV8Xy0KZ0qvZEn/7ONFx+YSHho07rRu7KjR48SGBhIREREnfsyMzOpqqoiPj6+Wedevnx5g3WajnrvvfcwmUwtOoczcGiG2OTkZJYsWcLPP//M/Pnz2bVrF0uXLuWqq64CYOvWrcyaNYvDhw836cGffvppZs+ezX/+8x8efvhhTCYTK1eutA1TFkI4j+KfPqMyw1Lc5h03isBxNzR6jP/wGfgOugwAXc5hCr//oE1j7Gp+Syvgm20nAIju5c/vJjWcmFiNHNiTGy7rB0BphYG/vfEL50uq2jrUTiM9PZ0BAwbUe5/1O7C5ycnAgQOJjIxsdmydicNr68yePZvZs2fXe19ycjLJycmXPD49Pb3ONg8PDx577DEee+wxR8MQQqig8tgein76FAD34DC6/+4BNJrGf9toNBpCZt6LoSAHw5ksSnZ8hWdYLL4Dx7d1yJ1eeaWBV1btBcDD3YVbpsXj4uAox0lDI6jUG9m4PZtzJTpW/O8wf50zoi3D7RSqqqrIyclh+PDhtrrL2nbt2gU0PzmZOnUqY8eO5bnnngMso1BfeuklDh06hNlsZvDgwTz00EMMGTKk3uPnzJnDzp07bTG8//77LF68mGnTpnH48GH279/PjTfeyFNPPUV8fDx//vOf7da7W7ZsGW+88QZHjhyxbfv0009ZsWIFeXl5dO/endmzZzNv3rw2H5YuqxILIS7JWHqegv+9Aiho3LX0uOlRXDy9HT7exd2THjf9lZPvPIpZV87Zda/h2bMP7sFhjR8sGvTvLw9SWGqZrPKqcX0IDXL8NQGYPjqK0+cr2H/sHD/uO8mNU2PpGx7QFqF2GseOHcNsNvP555/z+eef17uPVqslOjq6xY9VXl7O3LlzGTNmDMuWLcNgMPDGG28wd+5ctm7dWu+I1qeeeopFixZhMpl46qmniImxzDf0wQcfMHfuXO655x4CAhx/jf/973+TkpLCLbfcwtSpUzl48CCvvvoqhYWFLFq0qMXP8VIkORFCXFLxr19g1lmG/Yde+//wCG16s7N7YA+6X/8Qpz95DqVaT9FPq+l+3Z9bO9Qu45cD+Wz9LQ+A2MhAJg0Jb/I5NBoNV4/vy8Hj5zGbFd5bf4Ql89puyPfRnCI++dZS69JeTCYTrq72NU5enm7MvjKeuN5BTT6ftQfgiSeeICQkpM79jz76KDExMXUeszkyMjIoKiri9ttvZ9iwYYBllOuqVauoqKioNzmx1n2aTCa71pXIyEgefvjhJj1+WVkZr7/+OrfeeiuPPPIIPj4+TJgwAW9vb5YuXcrtt99eZ0BMa5LkRAjRIGNZIWX7NgPg1W8ovgOa/+Xl3W8oPgPHUXHkF8oP/0zQpFm4B/VsrVC7jPJKA69/th+wfNHeMi2+2U3soYFejEnoya8HT/FbWgGHjp8jsV/dL93WsPbH4+w6cqZNzt1U3p7uLLit6fMapaWl4e7uzqxZs3B3d7e779y5c+j1ersunVdffZVvvvmGzMxM/vWvf3H11fUXkNcnNjaW4OBg/vSnPzFjxgwmTpzI+PHj+etf/9rkuBuqkbmUvXv3otPpmDp1Kkaj0TZn2dSpU3n++efZvn17o+UcLSHJiRCiQSU7/odissw0GjThphafL3BcMhVHfgHFTPGvXxJ69X0tPmdX8832bEorDAD8bmJfAv1aNtvrtNFR7Eo9Q7XRzMp1R/jngxPbpJ7gukn9qNIbnaLl5HeT+jbrfOnp6URFRdVJTMDS5QP29SZRUVE8/vjjvPLKK01+LB8fH/773//yxhtvsGHDBlatWoVWq+W6667jb3/7W5PmAvP2blqXH0BxcTEAd911V733FxQUNPmcTSHJiRCiXqaKEkp/s0w0pY1KRBvRv8Xn9OwRjXfcSCqP7qLswFaCJtyEW0Boi8/bVVQbzXz1k2Ux1tAgL0YntLzlKcDXk0lDwtm8O5ejOUXsPHya0Ym9Wnzei8X1DuLJu8e0+nkvpbVniD169Chjx9bfepiRkQHYJyfXXXcdQINrzDWmb9++vPTSS5hMJg4cOMDatWv5+OOPiY6ObjBpaAqz2Wz3/8rKSttt65DmlJQUQkND66x117179xY//qU4NJRYCNH1lOxch1KtB1qn1cQqcHzNucxGirevbbXzdgW/7D9pK4KdODi81Vo4po6IxMvT8lv1va+PYKpn+vuu7tSpU5SUlBAbG1vv/fW1nLTEt99+y5gxYzh79iyurq4MHTqUv//97/j7+3Pq1KkGj3O03sXX17fOeX777Tfb7cGDB+Pu7k5BQQEDBw5k0KBBDBo0CKPRSEpKCmfPnm3eE3OQtJwIIeowVZVTsnsDAJ7h8WijElvt3NqwGLz6DqEqcx9le78jcPyNuPk2vTixq1EUhTU/HgfAx8udsa3YuuGtdefyEZGs+yWL3IJyfvgtl6kjerfa+TsDazGsdQTMxTIyMujevTtBQa3zXh42bBiKojB//nzuuecefHx82LBhA+Xl5UybNq3B4/z8/Ni9ezfbtm2rdxZbq8mTJ/PVV18xaNAgoqKi+OKLL+yGRwcHB3PXXXeRkpJCYWEhY8eOJT8/n5SUFPz8/BpM0lqLtJwIIeoo3b0BxWCZmCtowo2tXoNgbYlRTNWU7Phfq567szp0/DzH8yxrkY1O6ImbW+t+fE8cEo6/j6WO4cMNaZhM5kaO6FqsyUlDX8oZGRmt1moC0K1bN9555x38/Px4/PHHuffeezl8+DDLli1j5MiRDR53yy234O7uzrx58/jll18a3G/x4sVMmTKFpUuX8uCDD+Lt7c1f/vIXu30efvhhFixYwMaNG5k3bx4pKSlMnDiR999/v80X2pWWEyGEHbO+ipJd6wDw6NEHr37DWv0xtJED0PZOQJdzmNI9mwgcewOuNYsFivqt+cHSauLmquGyoU0fOtwYD3dXrhzVm8+3ZHC2uIrf0gsYOVBGU1nde++93HvvvQ3eb538rCW+//57u/8nJibyzjvvNOkco0aNYsuWLbb/W2dyv1hISEi9hbo333yz7bZGo2HOnDkkJye3++rO0nIihLBT+ttGzFXlgKWFo61mggyccCMASrWOkp1ft8ljdBYnz5az84hlTaPBsaH4+7TNr9YRA3rgUdMis3F73RlQRdNUV1ej1+sxm812t0XjJDkRQtgoZhMluyyJgntIBN7xo9rssbyik/AMszSRl+75BsVY3WaP1dGtrak1AZg6vO3WXtF6uDEkzjJ6anfqGUrK9W32WF3BE088QVJSErt372bhwoUkJSXZprgXlybJiRDCRpdzBFNZIQABI692aP2c5tJoNASMskxKZdaVU3n8t0aO6JpKKwxs3pULWGaDDWvjFYRH1QxPNpkVtuzJbdPH6uxeeOEF0tPT7f6NHj1a7bA6BElOhBA2ZQd/tNxwdcNnwLg2fzzvuFFoPCzzJ5Qf+rHNH68j+mbbCQzVJgAmD4to88frGxZASKAXAJt25KAoMqxYtD9JToQQAJir9VSkbQPAO2Y4rl5t+wsdLIsC+vS3TMxVcWw3ppo1fISFoih8u9NS+9E9yIsB0cFt/pgajYZRA3sAkHumzDZCSIj2JMmJEAKAymO7bcOHfRMnttvj+iZOstwwGalI3dZuj9sRZOQVc/q8ZdbOEf17tPky9VYjB/TE+lAbd0hhrGh/kpwIIYAL3Sount54xzR9UbTm8opKxLVmEjbp2rH307582+1hA9p2uvDaAv08ia9ZtffHvXm2biUh2oskJ0IITJWlVB7fC4DPgHG4uDm+qFhLaVxc8U2wtNTocg5jLGnbabE7CkVR+Hn/SQAie/jRzd+rXR/fWhhbqTOy/VDD06UL0RYkORFCUJH6K5gtv45t3SztqPZjlh/+ud0f3xmlZxdxtsjSzTY4NqTdH39Q3xC8tZZ5OmXOE9HeJDkRQlBW053i6h+CtveAdn98jx7RuIdG1sTyg4wQAX7ad9J2e0T/9uvSsXJzc2F4f0th7MGMcxQUVTZyhBCtR5ITIbq46qLT6PMs64b4JU5s07lNGqLRaPCraT2pPpuLoaBr/1I3Kwo/77fUm0T38ifAV9vIEW3DOmpHAb7fJXOeiPYjyYkQXVz5oZ9st9Xo0rHySZhgu11+6AfV4nAGOWcNFJbqABgSG6paHBHd/egVYllT5ZcD+Y3sLUTrkeREiC5MURTbCBmPHn3wCO2tWizuAd3R9rYs8V5+6GcUc9cdIXI429KFotHAMBW6dGob1K8bACdOldpqYIRoa5KcCNGF6U8dp7rQ8ou4Pec2aYi15cZUXogu+7DK0ajDZFY4kmtJAvqGBeDn3X4jp+qT2PdCMe6OwzJqR7QPSU6E6MKsM8KCBt+BEy65b3vw6T8WXC0jRCrStqscjToOHT9Hhc6ycq11ET41RXT3JcDHkiBtOyjJyXfffUd8fDybNm2q9/7Zs2czderUdo7KXmcoKJfkRIgurDLDstieZ1gMbv7dVI4GXL188eqdAEBlxp5O8SHbVNZROi4uGoY6QXKi0WhI6Gt5bxzOPE+lrmuvHp2WlgbAwIED69xnNptJS0sjLi6uWeeeOnUqjz/+eIvi27JlCwsXLmzROZyBJCdCdFHGkrNUn80BwDtmmMrRXGCNxVh6juqzXWuEiNFk5tcDltaJfuEB+Hip26VjlViTnJjMCr+lF6gcjbqOHj1KYGAgERF1F2HMzMykqqqK+Pj4Zp17+fLl/OlPf2pRfO+99x6nTnX8Fi5JToTooioz9thut+d09Y2pHUvtGLuCQ8fPUVZpAJyjS8cqNjIIT3dXAFvy1FWlp6czYED9cwEdPmypk2pucjJw4EAiIyObHVtn4nBysm7dOq6++mqSkpKYOXMma9asueT+BQUFLFiwgLFjxzJs2DDuv/9+srPt5y7YvXs38fHxdf7de++9zXoyQgjHWbt0XH0C8ejZR+VoLnAP7oV7cBjQ9ZKT3amWVgkN6g4hvpibmwvxUZa1dn5LO4PRZFY5InVUVVWRk5NDWFgY2dnZdf7t2rULaH5ycnG3zqFDh7jjjjsYPnw4Q4cO5c4772Tfvn0NHj9nzhy2bdvGzp07iY+PZ8eOHUydOpUXXniBOXPmkJSUxJIlS2wxvv7663bHL1u2rE531aeffsqNN95IYmIiU6dO5T//+U+7dLe6ObLT+vXrWbBgAXfccQcTJkzgu+++Y+HChWi1WmbMmFFnf71ez9y5c9Hr9Tz55JNotVpee+01brvtNr7++mv8/f0BSwbq7e3NypUr7Y633i+EaBvmaj1VJw4Clm4UNSZeuxTvmGGU7MxHl5eOqaocVy9ftUNqF7+lnwEgxN8Nb627ytHYS+zbjQMZ56jQGUnNKmRQTPtPqa+2Y8eOYTab+fzzz/n888/r3Uer1RIdHd3ixyovL2fu3LmMGTOGZcuWYTAYeOONN5g7dy5bt27F17fu38RTTz3FokWLMJlMPPXUU8TExADwwQcfMHfuXO655x4CAgIcjuHf//43KSkp3HLLLUydOpWDBw/y6quvUlhYyKJFi1r8HC/FoeQkJSWFmTNnsnjxYgAmTpxISUkJr7zySr3JyZYtW0hPT+fzzz8nMTERgNjYWC6//HI2btzIzTffDFgKi2JjYxkyZEgrPR0hhCN02YdQjJbuA2fq0rHyjhlOyc51oJipytyHb4L6I4naWkFhJblnygEID3GOWpPaBvTphkYDimIZtdPU5ER38hjFP6/GbNC1UYR1mUwmSlxd7ba5eGgJnHAz2vDYJp8vPd0yk/ITTzxBSEjd5//oo48SExOD60WP2RwZGRkUFRVx++23M2yYpQ6rb9++rFq1ioqKinqTk5iYGHx9fTGZTHbfq5GRkTz88MNNevyysjJef/11br31Vh555BF8fHyYMGEC3t7eLF26lNtvv52wsLAWPcdLaTQ5yc3NJScnh0ceecRu+/Tp09mwYQO5ubl1+sgmTJjAxx9/bEtMANzdLb8CDAaDbVtqamqDfXdCiLZj7dLBxQ2vPoPVDaYe2t4D0Hh4oRiqqMzY0yWSkz21Ck2juztfcuLr5U7fsACOnyxhx+FTzLs+EY1G4/DxJbvWqdJNV9/YIhdPb7ThDzX5XGlpabi7uzNr1izbd5rVuXPn0Ov1dl0658+f59FHH2X37t1ERkby7LPPOvxjPDY2luDgYP70pz8xY8YMJk6cyPjx4/nrX//a5Lib8z27d+9edDodU6dOxWg0YjQaAUvX0/PPP8/27dtJTk5u8nkd1WhykpmZCUCfPvZ90lFRUQBkZWXVSU58fX1tmV51dTXHjx9n6dKlBAUFceWVVwKWjPbYsWMEBQVxww03cOzYMUJCQrj99tv54x//2KQ3vRDCcYqi2L4kvHoPwMXTS+WI6tK4uuPVJ4nK9B1UHt+LYjahcWn5r1Fn9luapUvHx8ud0ADn6tKxSujbjeMnSygoqiLnTBlRPR3vgg8YeQ2KvqrdW04ubsVw8dDiP+qaZp0vPT2dqKioOokJWLp8wL7e5KmnniIyMpLXXnuNDRs28MADD7B582Y8PBpPPn18fPjvf//LG2+8wYYNG1i1ahVarZbrrruOv/3tbw6dw8rb29vhfa2Ki4sBuOuuu+q9v6CgbUdtNZqclJWVAdRpQvLxsay3UF5efsnjH3jgAbZs2YKLiwvPPfcc3btbpmI+ceIEOp2OrKwsHnnkEYKCgti8eTMvvvgi5eXlPPjgg016IocOHWrS/p3Jnj1dq2iwrXSV6+hSdpaAkrMAnNf2IL+Vn3drXUcP9xB8AHNVGfu/X4cpqO7Qzc7CaFJsyUl3fw0ajYbUtFSVo6rLC6Pt9hcb9zApsf7kxM3NjYqKCvuNgWH4XfPntgzPYSaoG58D0tPTGT16dL3HHjlyBLD8cK+oqKCiooItW7awYcMGTCYT06ZN48033+SHH35g3Lhx9Z7fbDZjNBpt5+/Rowd///vfMZlMHDp0iPXr17Nq1SrCwsKYM2dO/c/NZMJkMtnOcfE5a9PpdHbbS0pKAMu1sSZg//jHP+odQRQaGtroNTQYDM3+PGg0OWmsKtfF5dKFdPPmzeOOO+7gf//7n61mJTk5mR49evDWW28xYMAAQkMtVeljx45Fp9Px1ltvcdddd9Xbp9aQxMREPD09Hd6/s9izZw/DhztfzUBH05WuY/G2NRTW3I6fcp1tZExraM3raIzvS86hrwHo7VpOcCd+fQ5mnMNgtEy+NjopGihmQH/n7PLeengXZworyS1yafC1Tk1Ntf2AVVNFRUWrxXHq1ClKS0vp379/vee0jkYdPHgwPj4+nDhxAn9/f3r3vrBeVXx8PCdPnmwwJhcXF9zc3PDx8eHbb7/liSee4KuvviI0NJRx48Yxbtw4Nm7cyPnz5xs8h4eHBwaDwXZ/7XPW5uvrW+c8Bw9aiuR9fHwYPXo07u7ulJaWMnDgQNt+e/fuZdmyZTzyyCONFv56eHgweHD93cZ6vf6SjQqNJid+fn5A3SzT2mJivb8h1jfv2LFjOXnyJP/+979JTk7G19eXSZPqroA6efJkVq9eTVZWFoMGDWosPCFEE1m7dGoP2XVGbr5BePTsh+H0cSozfiN4yq1qh9Rm9tS0mgAM7NONvJxi9YJpRELfbpwprCQjt5iiMh1Bflq1Q2oX1mJY6wiYi2VkZNC9e3eCgixDrquqqur8wPb19XW4xWbYsGEoisL8+fO555578PHxYcOGDZSXlzNt2rQGj/Pz82P37t1s27at3llsrSZPnsxXX33FoEGDiIqK4osvvrCb7iM4OJi77rqLlJQUCgsLGTt2LPn5+aSkpODn50dsbNMLipui0fGD1lqTnJwcu+3WJ3FxLQpYmre+/vrrOtsTEhJs/VTp6el89NFHVFfblyvpdJb+SOsLLIRoPaaqcnS5lum3vZxwlM7FrLPFGgpOYCw9r3I0bcc662p4qI/qC/01ZmCfYAAUYP/Rs+oG046syUlDX8oZGRl29SZeXl71/qh3tCWnW7duvPPOO/j5+fH4449z7733cvjwYZYtW8bIkSMbPO6WW27B3d2defPm8csvvzS43+LFi5kyZQpLly7lwQcfxNvbm7/85S92+zz88MMsWLCAjRs3Mm/ePFJSUpg4cSLvv/9+m/dUNNpyEhUVRUREBN98842tmBVg06ZNREdH1zuUaPv27bz44osMGjTI1qRlMpnYvn27bc2B7OxslixZQo8ePbj88sttx65fv56IiAjCw8Nb/OSEEPaqMveBYplAy5mmrG+Id8xwin9eDVhafPyHNfyLsaM6X1JFVn4pAHGRzv+jLKqnPx7uLhiqzfyWXsDk4V1jRtN77733khOE7ty50+7/UVFRlJaWcu7cOduw42PHjtmm0qjP999/b/f/xMRE3nnnnSbFOWrUKLZs2WL7/1VXXVXvfiEhIbzyyit1tteOT6PRMGfOHJKTk9u9m86heU7mz5/P4sWLCQgIYPLkyWzevJkNGzaQkpICQGFhITk5ObYx1snJyXzwwQfcd999PPDAA2i1Wv773/9y9OhRVqxYAVialBISEnjiiScoLCykZ8+efPXVV3z//fcsW7ZMRusI0QasXToaDy1evRtu8nUWnmH9cPUJwFRR0mmTk721hhBbF9hzZm6uLvQLDyT1RCEHMs6hKIp8XtfD19eXyZMn8/rrr7Nw4UJbl8zo0aPVDq1DcGhayOTkZJYsWcLPP//M/Pnz2bVrF0uXLrVlZFu3bmXWrFm2dQUCAwP58MMPiYuL4+mnn+bPf/4zOp2O9957z/bCeHh48Pbbb3PFFVewfPly7r//fjIyMli+fLldC40QonUoipnKzH0AePUZjMbVOYer1qbRuODVbygAVScOohg734q4e9IsyYnW05U+YY7P3qmm2MhAAM6X6Dh1vumjXrqKv//972RnZzNq1Cjeeustli1b1qQhwF2ZQy0nALNnz2b27Nn13pecnFxnMpbw8HBby0pDgoODefrppx0NQQjRAoaCHMyVlu4D775D1A2mCbz7DqX8wFaUaj26/KN49U5QO6RWYzKZ2VdTt9EvPBAXl47RAlG7+2lf+lnCQrrG8gJNFRIS0uRuGWHhXAtqCCHajHUtHQCv6MRL7OlctFEXkhHdicMqRtL6juYUU15laQ0aEB2scjSO6xXqg4+XpeVt79G2nYxLdE2SnAjRReiyLXMKuPp1wy2ol8rROM7NNwj3EMsEbFXZBxvZu2PZk35hCHFi346TnLhoNMRGBAJw6Ph5zOa2X6VWdC2SnAjRBShmE1U5lhksvaKbtiaKM/CKsrT06E4exVytVzma1vNbTb1Jz27eBPh2rPlCYnsHAlBeVU1Wfom6wYhOR5ITIboA/eksFH0lcOGLviPxiq6ZkNFkRJ+Xrm4wraSiqprjecUAxNS0QnQkdnUnXWi+E9E+JDkRoguwdukAaDtQvYmVtncCYGntqV0705GlnijE2hvSEeY3uVi3AC3B/pbWnr31JCeNLX0iOreWvv6SnAjRBVSdsCQnboHdcQ/ornI0Tefq7YdHd8tK6FXZnaMo9mDGOQA0mgtDczsSjUZjizv1xHmqjWbbfe7u7lRVVakUmXAGVVVV9a7e7ChJToTo5BSTEV2uZYVbr6iOu16VdYSR/lQGZn3H/+I7eNySnPQK8UHr6fCsDk7F2uJjqDaTnl1o2969e3dOnjxJZWWltKB0MYqiUFlZycmTJ+nevfk/hDrmX4QQwmH6Uxko1ZY1qzpil46VNiqRkp3rwGxCl5vaIabfb0ilrprjJy1FpH16dYyJ1+pTu8Vn79GzJPazTNPu7+8PQH5+fp3109qTwWCQSc9aQVOvo7u7Oz169LC9D5pDkhMhOjlrlw50zGJYK6/eA0HjAoqZquxDHTo5OZJVaBt+G9+749WbWPn5eNArxIdT5yrYd/Qsc2YOsN3n7+/foi+n1rBnzx4GDx6sagydgRrXUbp1hOjkqmqKYd27heHm13Hm0riYi9YHz559AfsC347o0PEL9SYxHbDepDZr60lGXjGVus63vIBQhyQnQnRiZqPBNvRW24FbTays3VL601mYdB13TZdDx88D0KubD14dtN7Eylp3YjYrHM48r3I0orOQ5ESITkx/8iiK0QB07C4dK9tzUMzoaiaV62gqddUcq5nfpKMs9Hcp/cIDsC4JVHuFZSFaQpITITqxzlJvYqWN7A8ursCF7qqOJvXEhXqTjjiE+GJaTzd697TUlhw8Li0nonVIciJEJ2atzXAP7Y2rT8f/le7i4YVnWAwAug46GZu1S0ej6ZiTr9Wnb7jlvZV9ulTqTkSrkOREiE7KXK1Hd/IY0LFWIW6Mda4WQ0E2pspSlaNpOuv8Jj27+eCl7dj1JlZ9a7qnFAXSThSpHI3oDCQ5EaKT0uWmgdkIdI4uHavaiVZVTseaLbZKb+RYbjEAfXqpO8y2NfUJ88e6lKQ1+RKiJSQ5EaKTujDcVlOzNk3n4Bkeh8bVMi227kTHqjtJrTW/SVwHnt/kYt5ad3qG+ADIiB3RKiQ5EaKT0uWlAeDRPQpXL1+Vo2k9Lu6eF+pOOtgKxYcyL7QqdJZ6Eytr105GXjHVRpPK0YiOTpITITohxVSNPj8DqBnh0slYn5OhIBuzvlLlaBxnXeyvZzfvTlNvYmVNTqqNZo7nlagcjejoJDkRohPSn86yzW/SKZOTiJpp0hUzupNH1Q3GQbpa9SZ9O8H8JhfrE36hhkbqTkRLSXIiRCdkXYUYQBvR+ZITz4g42+3az9WZpZ4oxGSd36QT1ZtYBflpCfLzBOCQ1J2IFpLkRIhOSJdrqTdx9Q/BLSBU5Whan6uXH+6hkUDHqTs5nHXhC7szTL5WH+t8J2m1JpoTojkkORGik1EUxVYMq42IVzmatmNtEdKfPIpiMqocTeNSswoBCA3ywkfrrnI0bcPaXVWpM5J7pkzlaERHJsmJEJ1MdeEpzDWTk2kjBzSyd8dlraVRqvUYzpxQN5hGmExmjuZYJifr3cNP5WjajrXlBKRrR7SMJCdCdDKdvd7EqvZzs7YUOausU6XoDJbhtbW/wDubHsHe+NSMQpKiWNESkpwI0cnoa76oNR5eeHTvrXI0bcctsAeuvpbCUmuNjbNKO1Foux0TEaheIG1Mo9HYVlq2dmMJ0RySnAjRyVi/qLUR8WhqVvDtjDQaja1rR5ebiqI4bwGm9YvaW+tGaKCXytG0LWvLUGGpjoKijjMHjXAuDicn69at4+qrryYpKYmZM2eyZs2aS+5fUFDAggULGDt2LMOGDeP+++8nOzvbbh+j0cjLL7/MZZddxuDBg7nllls4cOBAs56IEAJMFSVUF+YDnbtLx8r6HE0VxRiLz6gcTcNSsy3JSe8efmg0mkb27tj61JrDRaayF83lUHKyfv16FixYwIQJE3jttdcYNWoUCxcu5Jtvvql3f71ez9y5czl48CBPPvkk//rXvygoKOC2226jtPTCKqLPPfcc7777LvPmzSMlJQVXV1fuvPNOcnNzW+fZCdHF1K696IyTr12sdsGvs3btnCuu4mxRFQDRnWixv4ZEdPfF3c3y1SJ1J6K5HJo/OSUlhZkzZ7J48WIAJk6cSElJCa+88gozZsyos/+WLVtIT0/n888/JzHRsoJobGwsl19+ORs3buTmm28mLy+PVatW8cQTT/CHP/wBgAkTJjB9+nTefvttlixZ0lrPUYguw5acaFzwDItVN5h24NEjGo27FqVahy4vDb+kyWqHVEdq7XqTTjq/SW1uri5E9fQnI6+YI5lSdyKap9GWk9zcXHJycpg2bZrd9unTp5OZmVlvK8eECRP4+OOPbYkJgLu7ZVy/wWCZUnv79u2YTCamT59u28fDw4PJkyfz448/Nu/ZCNHFWVsPPHv2xcVDq3I0bU/j4oo23JKEOetMsdbkxNVFQ+8enb/lBKBvzVT2J8+WU1phUDka0RE1mpxkZmYC0KdPH7vtUVFRAGRlZdU5xtfXl2HDhgFQXV1NWloaixYtIigoiCuvvNJ23oCAAIKDg+ucNz8/H51O14ynI0TXZa7Woz9l+Xv17AJdOlaeNXUn1efyMFU538RfqTUzw4aF+Ni6Ozq72msHpWVL64louka7dcrKLH/svr72S677+PgAUF5efsnjH3jgAbZs2YKLiwvPPfcc3bt3tx138Tlrn7eiogKt1vFffocOHXJ4385mz549aofQKXT06+hWmIOf2TJTar7Bg2yVnk97X0c3nRvWac0Ob/2a6u7O051lMJo5ftKyQq+/1kRqmuOtO03Z19kYjGbb7e9/PYxr1UnVYunof9fOot3/rhvbobHheS4ul/4lMG/ePO644w7+97//2WpWkpOTGz1vUyvaExMT8fT0bNIxncGePXsYPny42mF0eJ3hOhb9coKimtsDL7sKN9/2X1xOjeto1g/kxJ5VoJgJ96ymmxO9jgcyzqIoltFTwxOjGRDX3aHjUtNSGdC/Y8/u22vvbk6dr6BI56Ha31Zn+Lt2Bm1xHfV6/SUbFRpNTvz8LL9JKioq7LZbW0ys9zfE+oTGjh3LyZMn+fe//01ycjK+vr51zln7vPW1qgghGmatN3EL6qlKYqIWF08vPLpHYTiThd7JFgFM7SKTr9Unqpc/p85XcDyvBJPJjKtr1+jSEq2j0XeLtdYkJyfHbrt1zpKLa1EAjhw5wtdff11ne0JCAgUFBQD07duX4uJiSkpK6pw3IiICDw8PB5+CEEJRzOhPWr6Yu8L8JhezDpvW52egGKtVjuYC6+Rrwf6e+Hl3rc8067BpfbWJ7NPOVwsknFujyUlUVBQRERF15jTZtGkT0dHRhIWF1Tlm+/bt/OUvf7FLaEwmE9u3bycuLg6AcePGAbBx40bbPgaDga1bt9ruE0I4pvrcScw6S0tkZ16JuCHWhEwxVaM/U7dIXw1ms0Jads1ifz27xiid2mrP6WItChbCUQ7NczJ//nwWL15MQEAAkydPZvPmzWzYsIGUlBQACgsLycnJISYmBl9fX5KTk/nggw+47777eOCBB9Bqtfz3v//l6NGjrFixAoDw8HBuuOEGnn32WSorK4mKimLlypWUlpYyd+7ctnvGQnRCupMXujO6YnLiGRFnu63LS0cbHneJvdtHbkEZFVWWVpw+vTrvYn8NCQ3ywtvTjUq9kSMnCrl6Ql+1QxIdiEPJSXJyMgaDgRUrVrB69WoiIyNZunQpV111FQBbt25l8eLFvP/++4wePZrAwEA+/PBD/vnPf/L0009TUVFBUlIS7733HiNGjLCd9+mnn8bf35///Oc/VFZWkpCQwMqVK23DlIUQjtGfPAZYFvtzD4lQOZr25+YfiqtvEKbyIvQnj6odDnDRYn+RXS85cdFoiOrlT+qJQtKzixo/QIhaHEpOAGbPns3s2bPrvS85OZnk5GS7beHh4baWlYZ4eHjw2GOP8dhjjzkahhCiHrqaL2RtWEynXuyvIRqNBs/wOCrTdzhNcnKkpt5E6+FKz24+Kkejjuia5ORMYSUl5XoCfLveiErRPFI+LUQHZ9ZXUn3WMlOzpxN0Z6jF2pVjLD2HsUz9ib+sLScRPfxw6eSL/TUkqlbdSXqOtJ4Ix0lyIkQHp8s/BljmDerKyYln+IXJ19RuPSkp15N/zlKgHNXz0tMtdGZRPfywpmVHZIVi0QSSnAjRwVnrTQC0XWCxv4Z49ooBjeUjTadycnK0VitBVBccqWOl9XSzdWnVnvNFiMZIciJEB2dtJXAL6omrT9crvLRycffEo0c0oH7LibUAVANEhHbtCSWtXTvWydiEcIQkJ0J0YIqiXCiG7cJdOlbWa6A/dRzFZFQtDmt9Rc9u3mg9HR530CnVnowt54xMxiYcI8mJEB2YsegU5pqVeLtyvYmV9RooRgOGgmxVYjCbFVu3Tu2C0K6q9mRs1hFMQjRGkhMhOrDatRXScmJ/DdSqO8krKKNSZ2m1iZbkxDYZG8ARmSlWOEiSEyE6MNvka24eeHSXyQvdgnri4mUZHaNW3UntCcckObkwGRsgk7EJh0lyIkQHpqtZhdezVz80rl27tgEsk7FZW0/Uajmx1pt4eXbdydcuZk3SrJOxCdEYSU6E6KDMBp2trkLqTS6wXgtj0WlMFSWN7N36rK0DsZFBuLh0zcnXLiaTsYmmkuREiA5Kf/o4KJahmVJvcoFd3Un+sUvs2foqddXknC4FID4qqF0f25nJZGyiqSQ5EaKDqj35mrScXOAZFgM1X4XtXXeSkVeM2TJZL/G9JTmxksnYRFNJciJEB2WtN3HzD8HNL1jlaJyHi6c3Ht0jgfavO6ld8BknLSd2bJOxnSzBZM3ghGiAJCdCdECKothaBaTVpC7PsJrJ2PKPoZhN7fa41uSke7A3QX7adnvcjsC6xpDeYCJPJmMTjZDkRIgOyFh6FlNFMSDJSX1sk7EZdFSfy2uXx1QUxVbs2V+6dOqovcZQWrZ07YhLk+REiA7IbrG/iHgVI3FOakzGVlBURXGZZZisdOnU1SPYG093V0DqTkTjJDkRogOy1pvg6oZnjz7qBuOE3EPCcfH0BkCX1z7JSXqt1gAZqVOXi4uGyB6Wrp2jMpxYNEKSEyE6IH3NEFnPHn3QuLmrHI3z0Whc8AyLBUCf307JSc0XrpurC/3Cu+7q0JdirTvJKyinSq/ewozC+UlyIkQHo5iqMZzOArB9AYu6rNem+txJzPrKNn88azFsv/AA3N1c2/zxOiJr3YmiWIZdC9EQSU6E6GD0Z7JRTNUAeIZLctKQC9dGQZ+f0aaPVW00cTzPMhut1Js0rHcvP9vtNKk7EZcgyYkQHYy+1qynWmk5aVDta6Nr4+Qk82QJRpNltl6ZfK1hAT6eBPp5ApKciEuT5ESIDsaanLh4+eIW1FPlaJyXq08AbgHdgbavO6m9XowUw16ate7kWG6xuoEIpybJiRAdjHUYsWevWDQaWVjuUqxdO/qTx1CUtpuV1FpvEuDrQY9g7zZ7nM7AWndSVKbnfEmVytEIZyXJiRAdiKmqnOrCfEDqTRxhLYo1VRRjKj3XZo9zLKcYgLjeQZIwNqJ3zwt1J7Wn+xeiNklOhOhA9Kcu1E5IvUnjtOFtX3dSUq7n1PkKwJKciEuL7O6HS03+JpOxiYZIciJEB2K3ErEkJ43y6NEHXCzDetuq7qR27YQkJ43zcHelV4gvIC0nomEOJyfr1q3j6quvJikpiZkzZ7JmzZpL7n/27Fn+9re/MWXKFIYOHUpycjIbNmyw2+f06dPEx8fX+XfNNdc068kI0dlZi2Hdgnri6u3XyN7Cxd0Tj+5RgH1i15pqz3YaFxnYJo/R2Vi7djLzZYViUT83R3Zav349CxYs4I477mDChAl89913LFy4EK1Wy4wZM+rsbzAYmDt3LmVlZTz44IN0796djRs38tBDD2EymWzJR1paGgArVqzAx8fHdrxWK6t5CnExRVHQ1SQn0qXjOG1YLIbTmehPZ6KYTWhcWneCNOtInfBQH3y9PVr13J1VVE9/th08hd5gIvdMGdG9/Bs/SHQpDiUnKSkpzJw5k8WLFwMwceJESkpKeOWVV+pNTn788UfS0tJYvXo1SUlJAIwfP578/Hzeeustu+QkJCSE8ePHt9bzEaLTMpYUYK4sBaQYtik8w2Pht40o1XoMZ3Px7BHdaudWFIVjNcmJdOk4Lqqn/WRskpyIizXarZObm0tOTg7Tpk2z2z59+nQyMzPJzc2tc4yPjw+zZs1i0KBBdtv79u1LTk6O7f+pqanEx8uKqkI4QupNmqf2tdK38grFp85XUFZpma1XJl9zXPdgb7QeskKxaFijyUlmZiYAffrYr3waFWXpx83KyqpzzNixY3n66afthtRVV1fzww8/EBt74YMiLS0NnU7HH/7wBwYNGsS4ceP417/+RXV1dfOejRCdmLVLBxc3PFrx139n594tzLZCce3ZdVvD0VoFnbGSnDjMRXNhheJjskKxqEejyUlZWRkAvr6+dtutNSLl5eUOPdBLL73EiRMnuOeeewCoqqoiJyeHzMxMbrrpJt555x1mz57NypUr+dvf/takJyFEV2CbfK1HNC5uUtvgKMsKxTFArQSvlRytGanj7uZCnzBZibgprJOx5Z2VFYpFXY3WnDQ2q6KLy6XzG0VReOmll3jvvfe4++67ueKKKwBwdXVlxYoVhIeH07t3bwBGjRqFu7s7L7/8Mvfddx/R0dEOPg04dOiQw/t2Nnv27FE7hE7Bqa+j2UTgqQw0QIl7AKedOFZnvI5ajS9egOFsLnt2/Apunq1y3t+OFADQI8CNA/v31rn/dJEBncGMh3vTZ21ITUttcXzOzMWkBywrFH+9eQd9erTNQAhnfD92RO19HRtNTvz8LE1vFRUVdtutLSbW++tjMBhYtGgRX3/9NXfffTePPvqo7T4PDw/Gjh1b55jJkyfz8ssvk5aW1qTkJDExEU/P1vnA6Uj27NnD8OHD1Q6jw3P266g/dZyTZhMAkUPG4zfIOWN11utY4WfmTOavaICBPfzwih7U6DGNqTaaOLNqPQBDB0YwfHjdc2bll1BeWY2Xp0NjD2xS01IZ0H9Ai2N0ZhGRBjb9tg0As0cow4fHtfpjOOv7saNpi+uo1+sv2ajQaDpvrTWpXcgKkJ2dbXf/xcrLy/njH//Ihg0beOyxx+wSE7AU2q5atYrCQvtiKJ1OB0BQkPTfCmGlq1UMq5WROk1mVxTbSl07WfmltpWIZaRO0/n5eBBkXaE4W4pihb1Gk5OoqCgiIiL45ptv7LZv2rSJ6OhowsLC6hxjMpm477772L9/PykpKdxxxx119iktLeXJJ59k3bp1dtvXr1+Pn58fAwcObOpzEaLTsq1ErPXFLaiXytF0PG6+gbgFhAL2iV5L1J58TUbqNE/vmrqTDFmhWFzEobbG+fPns3jxYgICApg8eTKbN29mw4YNpKSkAFBYWEhOTg4xMTH4+vryySefsHPnTmbNmkXPnj3Zt2+f7VwajYbBgweTkJDA1KlTSUlJwWw2Exsbyw8//MAHH3zAokWLLtldJERXY5163TMsRhaWaybPsFiMJWfR51tWKG7pdbROvubn7UHPbrIScXNE9fRj/7GzthWKuwV4qR2ScBIOJSfJyckYDAZWrFjB6tWriYyMZOnSpVx11VUAbN26lcWLF/P+++8zevRoNm7cCMCqVatYtWqV3blcXV05cuQIAP/61794/fXX+eCDDygoKKB3794888wz3Hzzza35HIXo0Ey6CqrP16xELPObNJtneCwVqb9iKi/CVHYeN/+QFp3vwuRrgZIwNtPFKxSPS5LkRFg4XKU1e/ZsZs+eXe99ycnJJCcn2/7//vvvO3ROb29vFixYwIIFCxwNQ4guR19rNV2pN2k+bdiFgktd/jF8W5CclFcaOHnWMkhAunSaz7pCsVmxTMY2LqlumYDommRVYiGcXO0CTmk5aT6Pnn1AY/nIa+kigEdzim23ZfK15pMVikVDJDkRwslZp1x3C+yBq7esQdJcdisUt3DEztHcWisRS3LSIr17yArFoi5JToRwYrVXIpbF/lrOeg31p46j1Mwb0xzWX/m9Qnzw95HZelsiqpclOdEbTOSdKVM5GuEsJDkRwokZS87aViLWSpdOi1mvoXWF4uZQFMU2jDguUlpNWqp3jwutgTLfibCS5EQIJ2ZXbxLe+jNodjW1r2Fzu3bOFFZSWmEAIC4qsDXC6tJ6BHvj6W5ZoTjthNSdCAtJToRwYtZ6E1mJuHW4dwtDY12huJlFsTL5WutycbmwQvFRWaFY1JDkRAgnZqs36RElKxG3Ao3GBW2vfkDzVyi2Tr7m5upC33BZibg1WOc7yS0oQycrFAskORHCaSkmI4bTWYAMIW5N1mtZfTYXs76qyccfrSmG7Rvuj7uba6vG1lVF1Uxjryhw/GSJytEIZyDJiRBOylCQg2K01DbISJ3Wc6HuREF/+niTjq02mm1fnjKEuPVE1ZopNu2EFMUKSU6EcFrW9XQAPMOkGLa1eIbF2G43te7kxKkSqo2WlYil3qT1BPh6EuBr6bZMleREIMmJEE5LZ1uJ2Af3YFmJuLW4+QbZ1tVpat3J0VqzmMZFSXLSmqxdOxl5xeoGIpyCJCdCOCnrmjqyEnHrs03G1sTkpPZKxL26+bR6XF2ZtSj2fImOolKdytEItUlyIoQTMusqqD53EpBi2LZg7SYzlRViLD3v8HFHZSXiNhNVazK2dBlS3OVJciKEE9KdygAs64xopd6k1dnVnTjYeiIrEbetyB5+WPM9qTsRkpwI4YRqF2rW/iIVrcOzVz/bCsWO1p3UXolY6k1an6eHKz1ruspkhWIhyYkQTsj6a94tsAeuPjLRV2uzW6HYwRE7tbsaZBhx27CtUHyyGLOsUNylSXIihJNRFMWuGFa0DWstj6MrFFvrTcJCfPDzltl620J0L0vdSZXeRF6BrFDclUlyIoSTMZaexVRRDIBWFvtrM9bET6nWUX0u75L7Kopi62qQLp2209tuMjbp2unKJDkRwsnY15vISJ22oq01666uka6d0+crKau0zNYrxbBtp2ewj22F4iMnHB9FJTofSU6EcDK20SMubnj07KNuMJ2Ye7dwNB5eQOMjdqTepH3ICsXCSpITIZyM9Ve8R3dZibgtaVxcbV07tZcKqM/RWisR9wnzv+S+omWie1mSk7yCcip11SpHI9QiyYkQTsSyEnEmANoIqTdpa9qabjPD2bxLrlBsnba+X3iArETcxmqvUCxT2XddkpwI4UQMZ07UWolYkpO2ZrvGihn9qYx696k2mi6sRCzFsG3OmpyATMbWlUlyIoQT0Z280L0gI3XaXu1rXPva15aVX4rRZFmJWOpN2p6fjwfB/lpARux0ZZKcCOFErIWZLt7+uAX2UDmazs/VJ8B2nfUNJCe1ZyuVkTrtI6rnhaJYRZHJ2LoiSU6EcCLWX+/asFhZWK6dWFtPdCeP1vtFaC2G9ffxoGc373aNrauydu2UVhg4W9RwLZDovCQ5EcJJmCpKMBadBqTepD1Zr7W5shRj8Zk696dlW+oe4qOCJGFsJ1G9LtSdWK+/6FocTk7WrVvH1VdfTVJSEjNnzmTNmjWX3P/s2bP87W9/Y8qUKQwdOpTk5GQ2bNhQZ7/33nuPK6+8kqSkJG644QZ++OGHJj8JITqD2gvQSb1J+6mdCF68zk5xmZ7T5ysBS3Ii2kd4qC+uLpZEUIpiuyaHkpP169ezYMECJkyYwGuvvcaoUaNYuHAh33zzTb37GwwG5s6dy6+//sqDDz7I8uXLSUxM5KGHHmLdunW2/d5++22WLl3KDTfcwLJly4iMjOT+++9n3759rfLkhOhILtQ8aGRNnXbk2SMKjas7ULcoNr3Wr/b+UcHtGldX5u7mQnioLyArFHdVbo7slJKSwsyZM1m8eDEAEydOpKSkhFdeeYUZM2bU2f/HH38kLS2N1atXk5SUBMD48ePJz8/nrbfe4pprrqGyspI333yTu+66i/vvvx+ASZMmMXv2bJYvX87bb7/dWs9RiA7Bmpy4h0bi4im1De1F4+qOR6++6PPS6xTFWmeGddFAbGSgCtF1XVG9/Mk5U0ZWfinVRjPublKF0JU0+mrn5uaSk5PDtGnT7LZPnz6dzMxMcnNz6xzj4+PDrFmzGDRokN32vn37kpOTA8D+/fspKyuzO69Go+HKK69k27ZtGAyGZj0hIToixWxCV7MSsXTptD/rNdefycJcrbdttw5l7d3TH2+tuyqxdVXWETtGk5ms/BKVoxHtrdHkJDPTMltlnz72a3xERUUBkJWVVeeYsWPH8vTTT9sVj1VXV/PDDz8QGxtrd96+ffvWOa/RaKw36RGis6o+dxLFYBmV4Bkui/21N1vdidmE4YzlM81kMnMs15KcSL1J+6tdFCt1J11Po8lJWVkZAL6+vnbbfXx8ACgvL3fogV566SVOnDjBPffcY3ec9TwXn7eiosKh8wrRGcjka+qqbzK27NNl6AwmQOpN1NDNX4uPl6W1SpKTrqfRmpPGJsBxcbl0fqMoCi+99BLvvfced999N1dccYVD523qkL1Dhw41af/OZM+ePWqH0CmoeR29D/2KJ6C4eXIwuwByzqoWS0t1yPejohDg6YuLvpzTh3Zw3C2cXccu/PAyluezZ0/TX5PTRQZ0BjMe7k2vl0hNS23yMZ1NN18NFVVwKONMs99XHfL96ITa+zo2mpz4+Vn6/S5uybC2fFjvr4/BYGDRokV8/fXX3H333Tz66KP1nrd2q4wj561PYmIinp6eTTqmM9izZw/Dhw9XO4wOT+3rmLvnA6oB78h4+o0YoVocLaX2dWyJ0ycSqEzfgVflOfoPH86PR38DivH1cmfa5NG4uDR9jpOs/BLKK6vx8nRo7IFNaloqA/oPaPLjdTZ5pdnknD1BSYWJmPhEAnyb9hnfkd+PzqQtrqNer79ko0Kj6by11sRayGqVnZ1td//FysvL+eMf/8iGDRt47LHH7BKTxs7r4eFBWFhYY6EJ0SmYdRVUn80DwDNMunTUYu3aMZWew1h63jaMOC4qqFmJiWi53rUWAbSOnBJdQ6PJSVRUFBEREXXmNNm0aRPR0dH1JhEmk4n77ruP/fv3k5KSwh133FFnn6FDh+Lt7c3GjRtt2xRF4dtvv2XkyJF4eHg05/kI0eFYRulYujml3kQ9tSdjK8o8wsmzltZiqTdRT+8efljTwiOZ51WNRbQvh9oa58+fz+LFiwkICGDy5Mls3ryZDRs2kJKSAkBhYSE5OTnExMTg6+vLJ598ws6dO5k1axY9e/a0m1RNo9EwePBgvLy8uOuuu3j99ddxdXVl8ODBfP755xw+fJj333+/TZ6sEM6o9twaMlJHPZ69+oHGBRQzBUcPAZYfXjJSRz1enm707ObDqfMVUhTbxTiUnCQnJ2MwGFixYgWrV68mMjKSpUuXctVVVwGwdetWFi9ezPvvv8/o0aNtrSGrVq1i1apVdudydXXlyJEjgCXpcXV15dNPP+Xtt98mJiaG119/XfoIRZdiHR3iFtQTV2//RvYWbcXF3ROPHtEYTmdSnX8MCEOjkZWI1Rbdy59T5yvIyCvGZDLj6iqTsXUFDldpzZ49m9mzZ9d7X3JyMsnJybb/O9ry4eLiwv3332+bIVaIrkZRFPT5NSsRS5eO6rThcRhOZ+JdcRIXzIR3D7ANZxXqiA7zZ9uhUxiqzWSdKiUmIlDtkEQ7kBRUCBUZi05hrrKMUJOViNVn7VZzw0iYaxH9pUtHdX1qT8aWJV07XYUkJ0KoSJcnk685k9qvQR+3AvpHSzGs2kICvWytV4ezpCi2q5DkRAgV6fLSANC4e+LRPUrlaIRbUC+M7pZ5l/q4nZViWCeg0WhsrSe1V4kWnZskJ0KoyJqceIbFonFt2kRdovVpNBrOeVhG6fRzP0tk96ZNBinaRnRNcnKuWMf5kiqVoxHtQZITIVRi0lVQfdaywKU2or/K0Qir9KpuAAS6VGAul24EZxAddqHuJC1bJmPrCiQ5EUIl+rx0221tRLyKkQir8qpq9hYH2P6vq/UaCfVE9vCzzdJ7+LgkjF2BJCdCqKT2F5+nJCdOIe1EIbnGbhgVy0ejtdtNqMvDzZWIUEstUOoJSU66AklOhFCJ9YvPPTQSV62PytEIgNQThRhxJddk6drR5UrLibOwdu1k5ZdiqDapHI1oa5KcCKECxWREn38MkHoTZ3KkZqjqec8IAAxnsjAbpADTGViLYk1mhYy8YnWDEW1OkhMhVGAoyEap1gOSnDiLaqOZoznFALj0rFnjSDGjz89QLyhh06fXhVogmYyt85PkRAgV1K5lkGJY55B5stjWXdA9bpBtuxTFOodAP08C/TwBmYytK5DkRAgVWL/wXH0CcAvqqXI0ArBb9bZ//2jb6yJFsc7jwmRsRSiKonI0oi1JciKECnS5NZOvRfRHo9GoHI0AOFLTVdAtQEtokBfaSEt3m/7kURTFrGZoooa17qS0wsCZwkqVoxFtSZITIdqZseQspjJLs7R06TgHRVFsdQwDooPRaDRowy2vjVlXQfXZPDXDEzWiwy7UnRyRrp1OTZITIdqZzm7yNSmGdQanzlVQXG4pUB7YxzKM2NpyAtK14yzCQ3xwd7N8bR3OlOSkM5PkRIh2Zlvsz9Udz559VY5GwIUuHYABfSwrEbuHROBSM/+MFMU6B1dXF3r3sKx3lHZCprHvzCQ5EaKdWb/oPHr1Q+PmrnI0Ai50EXh5utqKLjUaFzzD4wBpOXEmfWomY8stKKNSV61yNKKtSHIiRDsyG6ownDkB2HcbCHVZR+rE9w7G1fXCx6K1281YdBpjebEaoYmL9KmpO1EU+xFWonOR5ESIdqQ/eQxqRn5YCy6FukrK9eQVlAMwsKZLx6p2wbJeunacQp9eAVjHtx3IOKdqLKLtSHIiRDvSyUrETiftRN16EyvPsFjQ1CwCeFK6dpyBl9aNsJpFAGWF4s5LkhMh2pFtsb/gMFx9AhrZW7QHa9eAiwbiegfZ3efiocWzZx9AFgF0Jn3DLX87x2vN6is6F0lOhGgnitlkaznxlFYTp2EdqdMnPABvbd0CZc+auhP9qeOYa9ZDEuqyJidGk8LRHBm10xlJciJEOzGcOYFSs8KtV++BKkcjAAzVJo7lFgOWydfqY3utzEb0J4+2U2TiUvrVmozt4HGpO+mMJDkRop1U5Ry23dZKcuIUjuUWYzRZCpStk69dTBs5wHa7KudIu8QlLs3Px4PQIC8ADkndSackyYkQ7USXbflic/XrhltgD5WjEWA/FPXikTpWrj4BuIdEAKCrlWAKdfWtaT1JzynCZJK1jzobSU6EaAeKYkaXmwpYuglksT/nYJ0CvXuQF90CvBrcz6t3AmAZCq4YZeIvZ2CtO9EbTGTml6gcjWhtkpwI0Q4MBTmYdZa5NKRLxzmYzIptZtiEvvV36VhZXzPFaEB/KqPNYxON6xd+oe5EunY6H4eTk3Xr1nH11VeTlJTEzJkzWbNmjcMPsnTpUu68884623fv3k18fHydf/fee6/D5xaiI9DVqlWQ5MQ5ZOWXUKkzAjCoX8gl9639mkndiXMI9tcS4OsBwEGZjK3TcXNkp/Xr17NgwQLuuOMOJkyYwHfffcfChQvRarXMmDHjksd+8MEHrFixgrFjx9a5Lz09HW9vb1auXGm33d/fvwlPQQjnZ01OXH0Cce8WrnI0AuBQrVEeg2IunZy4+QXjFtQTY9FpS93J+BvbOjzRCI1GQ7/wQH5LLyD1RCGKokh3aSfiUHKSkpLCzJkzWbx4MQATJ06kpKSEV155pcHk5MyZM7z44ousX78ePz+/evdJS0sjNjaWIUOGNC96IToARVHQ5VqSE23vAfIB6iSsXQEhAVp6BHs3ur9X7wTKik6jy01HMZvQuLi2dYiiEX3DAvgtvYDyqmpyz5TRu6f8sO0sGu3Wyc3NJScnh2nTptltnz59OpmZmeTm5tZ7XEpKCkeOHGHlypUMGDCg3n1SU1OJj5fJqETnVn3+JKYKS8GeNlK6dJyByaxwqKYYNjEmxKGE0VZ3Uq1DfyqzTeMTjukbIXUnnVWjyUlmpuWPsE+fPnbbo6KiAMjKyqr3uLlz5/L1118zZsyYeu83mUwcO3aM06dPc8MNN5CYmMjkyZNZsWIFiqI06UkI4cxq15t4RSWoGImwOpFfQkWVZdRNY/UmVtqoC4mltSVMqKtHsDfeWksHwAGZjK1TabRbp6ysDABfX1+77T4+PgCUl5fXe1xMTMwlz3vixAl0Oh1ZWVk88sgjBAUFsXnzZl588UXKy8t58MEHHXoCVocOHWrS/p3Jnj171A6hU2ir6+i9/2c8AbO7FwdzzkJu5/4Q7Qjvx21pZRf+U3WaPXsce038tQG46ko4feBXjrtHNLr/6SIDOoMZD/emD4xMTUtt8jFdUai/C9k62H/0NLt3767TCtYR3o8dQXtfx0aTk8ZaMVxcmjcauUePHrz11lsMGDCA0NBQAMaOHYtOp+Ott97irrvuqpMQXUpiYiKenp7NiqUj27NnD8OHD1c7jA6vra6joijk/PImJsC3TyIxI0a0+mM4k47yftywfwdQQrcALVdeNsrhOqCCk0MoP/gD2tJ84ocOabTuJCu/hPLKarw8HSrvs0lNS2VA//q7w4W90xW5ZBdkUl5lJrLvQLv6oY7yfnR2bXEd9Xr9JRsVGs0srMWsFRUVdtutLSYNFbs2xtfXl0mTJtkSE6vJkydjMBga7C4SoiMxFp/BVGaZhVSGEDsHs1mxTb42qJ9j9SZW1tfQrK/EUJDTJvGJpqk938nhzM7dKtmVNJqcWGtNcnLs/xCzs7Pt7m+q9PR0PvroI6qr7Wdb1Ol0AAQFBdV3mBAdil29SW+pN3EG2adLKa+pN0nsd+nJ1y5We8FGmcreOYR397N1m+07elblaERraTQ5iYqKIiIigm+++cZu+6ZNm4iOjiYsLKxZD5ydnc2SJUv48ccf7bavX7+eiIgIwsNlLgjR8Vkn7NJ4eOHRI1rdYARgP2GXo8WwVm5BvXD1tfxwksnYnIOri8a2zo6sUNx5ONQROn/+fBYvXkxAQACTJ09m8+bNbNiwgZSUFAAKCwvJyckhJibG4TqRyZMnk5CQwBNPPEFhYSE9e/bkq6++4vvvv2fZsmUyF4ToFKy/rrWR/WVeDCdh/QIL9tfSK8SnScdqNBq0vQdSceQXdLmpMvGXk4jrHURadhHninWcPl9Bz25Ne12F83GomjU5OZklS5bw888/M3/+fHbt2sXSpUu56qqrANi6dSuzZs3i8GHHmzk9PDx4++23ueKKK1i+fDn3338/GRkZLF++nCuvvLJ5z0YIJ2IsPYexuACw7w4Q6mlJvYmV9bU0V5ZSfS6vVeMTzRMTGWi7vf+YdO10Bg6XkM+ePZvZs2fXe19ycjLJyckNHvvBBx/Uuz04OJinn37a0RCE6FCqsi8k61qpN3EK2adLKatsXr2JVe3Xsir7MB6hka0Sm2i+8FBfvD3dqNQb+S29gOljotUOSbSQrEosRBupOnEQAI27Fs9efVWORoB9TUJj6+k0xD0kAlcfS41D1YkDrRKXaBkXjcbWenLo+HmZyLMTkOREiDagKApVWZYvLq+oBDSu7ipHJODCFOfB/p6ENbHexEqj0eAVnQSALvsQitnUavGJ5outSU5KKwzknC679M7C6UlyIkQbqC48hanM8kWojR6kcjQCLPUm1uQksW/z6k2srK+pWVeB4bTMyeQMYiMvTD+xT+pOOjxJToRoA9ZWEwDvPkkqRiKscs6UUVZpACyL/bVE7ddUunacQ/cgLwJ8PADYm16gcjSipSQ5EaINWL+wXH0CcA/trXI0Auwn6EpqYXLiFhCKe3AvwD4RFerR1Ko7OZJViMlkVjcg0SKSnAjRyhSzCV1NMaxXdJLMg+Ek9h21/JoODfJqdr1Jbba6k9w0zNX6Fp9PtFxcTddOld7I8ZMlKkcjWkKSEyFamf5UJmZ9JQBe0qXjFKqNJg7W1JsMjeveKgmj9bVVTNXo8tJafD7RcrG15juxJqOiY5LkRIhWVrsGwUuKYZ1C6olCDNWWUTVD4kIb2dsx2qhEwJLkSNeOcwjy1xIS6AXAXllnp0OT5ESIVmb9onIPDsMtoHW+CEXL7E23fFFpNDA4tnVeE1cvXzx79QOgKutgq5xTtFxsRCAA6dlFVJtkvpOOSpITIVqRuVpva+KXLh3nsbemib9fRCD+NSM6WoP1NTaczsRUKXNrOIPY3oEAVBvN5J2TWqCOSpITIVqRLjcVTEbgQsGkUFdJuZ7MmuLIoa3UpWN1IQFVqMo+1KrnFs1jbTkBOH5KkpOOSpITIVqRrfZA44I2StbTcQb7j53FOpv50LjurXpuz4h4NG6WlhipO3EOvt4ettFYWWd0KkcjmkuSEyFakfULyrNXP1y9fFWORsCF+U20Hq70jw5qZO+mcXHzQBs5AJDJ2JyJdb6T/MJqKnXV6gYjmkWSEyFaiamyFMMZy1TmMkrHOSiKYpstNLFfCO5urq3+GNauHWPRaaqLz7T6+UXTxfW2JKGKAvuPnWtkb+GMJDkRopVYVyEGKYZ1FnkF5ZwrsTTtt3a9iVXt2iIZteMcYiMCcXO1DPPedeS0ytGI5pDkRIhWYu3S0bh54BkRr3I0Ai6M0oHWm9/kYh49o3Gp6cKTrh3n4OHuSkxNYeyetDMoigwp7mgkORGiFSiKYktOtL0H4OLWesNVRfNZ6026BWiJ7OHXJo+h0bjYuvGqThxEUWRNF2fQPzoYgMJSPTmnZZh3RyPJiRCtoPr8SYwlll/pXn0GqxyNAMs8FwczLPUGQ+JC23SNI68+QwAwV5aiz89os8cRjhtQk5wA7EqVWqCORpITIVpBZcYe223vmOEqRiKs0rML0RksU9a39hDii3n3G2q7Xfu9INQTGuiFv7elAHrXEUlOOhpJToRoBdYvJLfAHrh3C1c5GgH2a6u01pT1DXHz74ZHjz4AVGb81qaPJRyj0WiIDLF0r6ZlF8qQ4g5GkhMhWsisq0CXa5my3jtmeJt2HwjHWYcQ9w0PINDPs80fz9piZjidibGssM0fTzQuMtSSnJjNCvuPyUKAHYkkJ0K0UGXWfjBbug+8Y4apHI0AKCzVcSy3GIDh/du2S8fKO/ZCd560njiHsGAP3F0tX3M7pWunQ5HkRIgWqjxm6dLRuHvKlPVOonaNwaiBPdvlMT179cPF2x+QuhNn4eaqoV9EAAC/yZDiDkWSEyFaQFHMVB63/Er2ik6SIcROYudhy8RbAb4exPZu3SnrG6JxcbUVxlZlHUAxSo2DMxhQa0hxtgwp7jAkORGiBfT5GZgrSwH7Zn2hHn21iX019QUjB/TE1aX9aoCsdSdKtY6qnCPt9riiYQP6dLPdltliOw5JToRoAbshxP2k3sQZ7D92FkO1pQZoVEKPdn1sr75DQGP5WK3M2N2ujy3qFxroRUigFwC7Zb6TDkOSEyFawFr46NGjD27+3RrZW7QHa5eOm6sLQ9p4fpOLuWp9bKsUV2b8JjUOTsLatZOWXSRDijsIh5OTdevWcfXVV5OUlMTMmTNZs2aNww+ydOlS7rzzzjrbjUYjL7/8MpdddhmDBw/mlltu4cABWZtCdAzGskIMpzMBGaXjLMxmxVYMmxQbgpenW7vHYH0vGItOQ6l0IzgDa3JiNiu2JQ2Ec3MoOVm/fj0LFixgwoQJvPbaa4waNYqFCxfyzTffNHrsBx98wIoVK+q977nnnuPdd99l3rx5pKSk4Orqyp133klubm7TnoUQKqg9XNQ7doSKkQir4yeLKSy1rEI8OqF9RulczO69kCs/tpxBv4iAC0OKD0vC2BE4lJykpKQwc+ZMFi9ezMSJE1myZAkzZ87klVdeafCYM2fO8Je//IXnn38eP7+6C27l5eWxatUqFi5cyG233cbUqVN55513CAgI4O23327+MxKinVjrTVy8/fHs1U/laATAzsMXagpGDlAnOXHvFo5bYE13Uu5+VWIQ9jzcXIntHQjAziOnMZmlu83ZNZqc5ObmkpOTw7Rp0+y2T58+nczMzAZbOVJSUjhy5AgrV65kwIABde7fvn07JpOJ6dOn27Z5eHgwefJkfvzxx6Y+DyHalWKstq1C7N1vKBoXV5UjEmD54gHoGxZAaJCXKjFoNJoL6yudOQaGKlXiEPaSYixLGJRVVnMk67zK0YjGNJqcZGZa+tT79Oljtz0qKgqArKyseo+bO3cuX3/9NWPGjGnwvAEBAQQHB9ttj4qKIj8/H51O13j0QqikKucISrXlPSoL/TmHc8VVZJ4sAWBkO4/SuZjtPaGYcD0jQ4qdQULfblhHlf+yP1/dYESjGq0WKyuzTFrj6+trt93HxweA8vLyeo+LiYm55HnLy8vrnLP2eSsqKtBqtY2FZ3Po0CGH9+1s9uyR2ShbQ1Ouo9eRb9ACikbD0VJQ5DWwUev9uOvYhc8if5didf8uTEYCXd3RmKqpPPIDx43+TT5FalpqGwTW9dS+jj2D3MkvrObH37IZ0dsg62A1QXv/PTWanDQ2FM7FpXmjkRs7b1PfNImJiXh6tv3iXs5mz549DB8uv9xbqinXUTGbyPnpdUyAd3QS/caMb9vgOhA1349f/bYNgGB/T665Ygwu7Tj5Wn3O5I6gIm0bQeUnCIyNAVd3h49NTUtlQP+63eGiaS6+juf1J/l8SwZlVWb8u/cjrp1mD+7o2uLvWq/XX7JRodHMwlrMWlFRYbfd2mJSX7GrI3x9feucs/Z562tVEcIZ6PLSMFUUA+AzYKy6wQgAdHojBzLOATByYE/VExO48N7QGPWQf1jlaARAYr8Q2+2fpWvHqTWanFhrTXJycuy2Z2dn293fVH379qW4uJiSkpI6542IiMDDQ9YoEc6pItXyCx2NCz7xo9UNRgCw92gB1UYz0H4L/TXGO2aYrbVEc2KnytEIgEBfT6J7WbrYfj2QL5PkObFGk5OoqCgiIiLqzGmyadMmoqOjCQsLa9YDjxs3DoCNGzfathkMBrZu3Wq7TwhnoyhmKtK2A+AVlYCrd9NrCUTr+2mf5Vew1sOVpNiQRvZuHy4eXtC9pvYubz+YZGZSZ5AUY3l/nCmsJEcWAnRaDk2fOH/+fBYvXkxAQACTJ09m8+bNbNiwgZSUFAAKCwvJyckhJibG4e6Y8PBwbrjhBp599lkqKyuJiopi5cqVlJaWMnfu3OY/IyHakD4vHVN5EQA+AySJdgY6vdE2hHh0Qi+0Hu0/K2yDwhLgVCqaah3KqSMQMVjtiLq8Qf1C+N9PllGovxzIJ6qX/MBwRg79FScnJ2MwGFixYgWrV68mMjKSpUuXctVVVwGwdetWFi9ezPvvv8/o0Y43cz/99NP4+/vzn//8h8rKShISEli5cqVtmLIQzqY89VfLDenScRq7Us+gN1gW+ps4pHktuW2mRxyKxhWNYkJzYheKJCeqCwn0IizEh/xzFfxyIJ9bpvdXOyRRD4d/YsyePZvZs2fXe19ycjLJyckNHvvBBx/Uu93Dw4PHHnuMxx57zNEwhFBN7S4dbe+BuPoEqByRAPhp30kAfLRuDOvfvgv9NcrdE3O3aFzPHYfcfWAygqsTtex0UUkxIeSfqyDndBmnzlXQK8RH7ZDERWRVYiEcpD95FFNZIQC+MkrHKVTqqtmdapmyfnRiL9zdnG+mXlNoHACa6io4LXOXOAPrbLFg6doRzkeSEyEcVG4dpYMG7/j6Zz4W7WvH4dO2UTqThoarHE39TN36otQsbyCjdpxDz27ehAZaljf4VZITpyTJiRAOUBSzbQixtvdA3HwD1Q1IABe6dPy8PRgcG9rI3ipx84TQmoUhc/eB2ahqOMIyyad11M6x3GLOFcv6R85GkhMhHKDPz8BUZlksTCZecw7llQb2phcAMC6pF26uzvtxpvS0zFKqMVTC6TSVoxEASbWS2a2/5akYiaiP8/41C+FEKqyjdNDgI106TmHbwVMYTZZJtCYOds4uHZsecSgay8etJku6dpxBZHdfugd5A/D9rhyZkM3JSHIiRCPsunQi++PmJ+txOANrl06gnyeJMc4x8VqD3LW1unb2SteOE9BoNIwYYBndlVtQTlZ+qcoRidokORGiEbqcVIyllnVbZOI151BSrmd/zVo645PCcHWCtXQao/Sq1bVzsuuuou5MRvTvYbv93a6cS+wp2pskJ0I0ouzA95YbLm74JkxQNxgBWEZYmM01XTpDnLxLx6rnABTrWjvHflQ5GAEQ5K8lJiIQgB9/y8NkMqsbkLCR5ESISzDrq2xdOt6xw2UtHSdhXUunW4CWAdHBKkfjIDcP6DXQcvvkQdDJui7OYOQAS+tJSYWBvUfPqhyNsJLkRIhLKE/9FaVaD4Df4KkqRyMATp+v4OBxS5fOhMHhuHSALh0r6/T1GsUMmdsa2Vu0h6TYENzdLF+F0rXjPCQ5EeISyg9sAcDVJxDvfkNVjkYAfLvzwhfIlaN6qxhJMwT3RvG2FFRrjv0EMkJEdVoPNwb1sxRU7zx8mooqWT3aGUhyIkQDqgtPocu1TDfuO+gyNC7ONzV6V2MymfmuJjmJjwrqeCvKajQXWk9K8qFQfqk7A2vXTrXRLNPZOwlJToRoQFlNqwlIl46z2JNWQGGpDoBpozvo6uURSVjbSzQZUhjrDGJ7B+Hn7QHAZunacQqSnAhRD8VsouzAVgA8w2LxCIlQNyABwKYd2QB4ebp2nFE6F/MKgJC+lttZO8Ek3Qhqc3XRMLxmResjWYWcKaxUOSIhyYkQ9ag6cdA2Xb20mjiH8yVV7KpZgXjikAi8PN1Ujqj5bF07hkrI269yNAIudO0AbNmTq2IkAiQ5EaJe1i4djZsHvgPHqxyNAPh+d65tbpPpYzpol45Vz3gUN09A5jxxFmGhvoSF+ACWFjqTWYqV1STJiRAXMekqqEy3rH/iEz8aF62PyhEJs1mxdelE9/InNjJQ3YBaytUdwhItt/OPQGWRuvEIAMYO6gXA2aIq9qSdUTmark2SEyEuUnH4ZxSjAQDfwVNUjkYAHDx+jtPnLXUAV47ujUbTceY2aYgSWdO1gwLHf21kb9EeRgzogaeHZVTe/348rnI0XZskJ0LUoigKJXs2AODmH4JXVKLKEQm4UAjr7ubClOGRKkfTSgLCUHwt82to0reA2aRyQELr4caogT0B2H/sHHkFMouvWiQ5EaKWqqwDVJ+1FMP5j5gpc5s4gdIKA78eOAXAuEFhtiGfHZ5GgxI9ynKzssiyWrFQ3YSkMNvtdT9nqRhJ1ybJiRC1lOz8CgCNuyd+Q65QORoBlnknjDULsk0b08FmhG1MRBKKuxcAmsMbVQ5GAHQP9ia+t2UW3827cqjUyVBvNUhyIkQNw7k8qo5bfr36JU3B1ctX5YiE0WTmfz9lAhAe6kti3xCVI2plru7QexgAmnOZcC5T5YAEXFjpWmcw8f1uGVasBklOhKhRsutr223/kVerGImw+mnfSc4VVwFww+R+HWqRP0cp0SNQNJaPYs3hTSpHIwAGRAcT7K8F4KufM1FkDaR2J8mJEFgmwyqvmRHWO2Y4Ht3CLn2AaHOKovDFlgwAAv08O08h7MW0/tBroOV2zh6oKFQ3HoGLi4YJgy2fAflnK9h/7KzKEXU9kpwIAXjm7rMNHw4YdY3K0QiAvUfPcuJUKQDXTOiDh3vnLU5W+owGQKOY0aR9r3I0AmBUQk/c3SxfkdauRdF+JDkRXZ5iqsYzZzcAHt17o40epHJEAuDLmlYTrYcrV43ro3I0bSwwDCWopmXo6A9oTAZ14xH4aN0Z3t8ypf3u1DOcPl+hckRdi8PJybp167j66qtJSkpi5syZrFmz5pL7V1RUsGTJEsaPH8/QoUOZN28eJ06csNtn9+7dxMfH1/l37733Nue5CNEsFanbcdGXA+A/8ppOMcFXR3c8r5h9NU3pV46O6jzDhy/B1npSXUnguSMqRyMAJtZ07SgKfLb5mMrRdC0OrZy1fv16FixYwB133MGECRP47rvvWLhwIVqtlhkzZtR7zMMPP8zBgwd59NFH8fHxYfny5dx+++18/fXX+Pn5AZCeno63tzcrV660O9bf37+FT0sIxyiKYhs+7OLtj2/iRJUjEgBfbrXMzuniouG6Sf1Ujqad9IxH8QpEU1VMt9O7QZkFGmncVlNYqC8D+wRzJKuQ73bl8Psr4+ge5K12WF2CQ8lJSkoKM2fOZPHixQBMnDiRkpISXnnllXqTk927d/PDDz/w1ltvMWnSJABGjBjB5Zdfzscff8w999wDQFpaGrGxsQwZMqSVno4QTVOVdQD9KcsXof+w6bi4df5f6M6uoLCSn/afBCwTYvUI7iJfBhoXlOiRaFK/xVNfjDnnN4gaoXZUXd70MdEcySrEZFZY/d1R5t88RO2QuoRG0/Lc3FxycnKYNm2a3fbp06eTmZlJbm7dMeC//PILPj4+jB9/YTXX4OBgRo4cyY8/XliBMzU1lfj4+JbEL0SzKYpC0daPLLddPQgYMVPliATA2p+O21YfvmFKjMrRtLPeQy9Myrb3SzCbVQ5I9O7hx8A+wQB8uzOHgqJKlSPqGhpNTjIzLVXKffrYF6RFRVmWLM/Kqju9b2ZmJlFRUbi62lfX9+7d27a/yWTi2LFjnD59mhtuuIHExEQmT57MihUrZEy5aBeVR3ehP2UputRFj8TVJ0DliERRmY5N2y3r6CTFhBATEahuQO3NzROln+VHnab0NGRtVzkgATB9tOX7ztp6Itpeo8lJWZll4SNfX/vZMn18LMvIl5eX1zmmvLy8zv7WY6z7nzhxAp1OR1ZWFvPmzeOtt97iiiuu4MUXX2TZsmVNfyZCNIGimCn68WMAXLQ+6KNHqxyRAPhkUzo6g2UBvJsvj1U5GpVEj8DoVtN6sm8NmIzqxiPo3dOfAdEXWk/OFlWpHFHn12jNSWOtGC4udfObSx1j3b9Hjx689dZbDBgwgNDQUADGjh2LTqfjrbfe4q677qo3wWnIoUOHHN63s9mzZ4/aIXQ47vmH8S3IAaAiciSKu1auYytp7nU8X1rNN9vOANC3pyemslz27OnYU4cX5p3EpKvE1dOzScf5hyYSemoXmorznPplNUXdh7RNgF1Aalpqq5wnvqdC6glL68nrn/zCNaOCWuW8HUV7fz42mpxYR9ZUVNiP8ba2gFjvr83X15e8vLw62ysqKmwJh6+vr61YtrbJkyezevVqsrKyGDTI8fkmEhMT8WziB0BnsGfPHoYPH652GB2KYjaRt3Ml1YCrTwADrp/H3oOH5Tq2gpa8H194fxc1pSY8+Icx9OsEXTqZnp5UlZTgWdPS7Kgss4mQ4mNoqorpdWYXPcfdCFKs3WSpaakM6D+gVc41AEg/fZDUE4Xszazk/tnjCQ3yapVzO7u2+J7R6/WXbFRotFvHWmuSk5Njtz07O9vu/ouPyc3NrdOCkp2dbds/PT2djz76iOpq+xUfdTodAEFBXSsrFe2n7MAWqgtPARA4LhkXD63KEYmjOUX8sj8fgMnDIjpFYtIiLq4osZYfb5qqEkjfonJAAuxrTz7dLLUnbanR5CQqKoqIiAi++eYbu+2bNm0iOjqasLC6a5BMmDCB0tJSfv31V9u2wsJCdu/ezbhx4wBLorJkyRK70TtgmVMlIiKC8PDwZj0hIS5FMVZT/NNqAFz9uuE3bFojR4i2pigKK9cdBsDN1YVbZ/RXOSInET4IxacbAJpDX0O11DmoLarXhdqTTduzya5ZXkG0PofmOZk/fz6LFy8mICCAyZMns3nzZjZs2EBKSgpgSTxycnKIiYnB19eXkSNHMmrUKB555BEWLFhAYGAgy5Ytw8/Pjz/84Q+ApfsmISGBJ554gsLCQnr27MlXX33F999/z7Jly2SWTtEmSvduwlh6DoCgiTfLvCZOYE9aAYeOnwfgqvHR9OzWtC6QTsvFBSXuMjR7v0Cjr0A58i0M/p3aUXV514zvQ3p2IWZF4Y0vDvCP+8fL91UbcGj6weTkZJYsWcLPP//M/Pnz2bVrF0uXLuWqq64CYOvWrcyaNYvDhw/bjlm+fDlTp07lxRdfZNGiRfTs2ZN3332XgADLcE0PDw/efvttrrjiCpYvX879999PRkYGy5cv58orr2yDpyq6OmN5EUU/fAKAW1BP/JKmqByRMJkV3q1pNfHWuvH7y+NUjsjJ9BqI4m9Z30VzaD2Uyeq4agsL9WX8YEvL/uHM8/y076TKEXVODrWcAMyePZvZs2fXe19ycjLJycl22wICAvjHP/7BP/7xjwbPGRwczNNPP+1oCEK0yPlvV2LWWyZQ6nblH9G4Ovz2F23k+105ZJ+2TFdw09RYAny7XlH7JWk0KAOno9n+PhpTNez4EOXyh0B+qatq5pho9qYXUF5VzdtrDzFiQA+8te5qh9WpyMINokuoPL6XiiO/AODTfww+sTItuNqKSnWs+MrSahLsr+XaiX1VjshJdYtCiRgMgCb/EGTvVjkg4aV149oJlvdrUZmeT75NVzmizkeSE9Hpmav1nPvmPwBoPLzoduVdKkckAN788gDlVZbRen9KHoTWQ1qyGqIMuALFw7LGkGbnR2CQKdTVNmJgD6J7WRap/d+PmeSeKVM5os5FkhPR6RX//BnG4gIAgiffgpt/N5UjEr8cyOfXA5bh3OMHhzF2UN1Rf6IWD2+UAVcAoNGVotn7hcoBCReNhhunxKDBUjv15hcHZOmVViTJiejUDGdzKN6+FgDPXv3wHz5d5YhEWaWBN784AICftzv33uD4ZItdWngSSrBlng3St8K5TFXDERDR3Y9xSZbE+kDGObb+VnfyUdE8kpyITktRzJxd/28wm0DjQsjMP6FxcW38QNGm3l57iOIyPQDzrh9EkJ9MgucQjQZl0FUoGlc0KGi2vWd5bwtVzRwXja+XpRj2jc8PcPp8RSNHCEdIciI6rZJta9DnpQEQMPIqPHtJwaXadqee4fvdlvVyRgzoweRhESpH1MH4hkBMzarFRXmWhQGFqny07sy+Mh6AKr2Rlz7cjdFkVjmqjk+SE9EpVWUfpnCrZdVht6CeBE2qfxi8aD+lFQZe+2w/AF6ebtx/42CZvKoZlH7jUfy6AzVzn+TtVzkikdC3GxOHWOY+OZpTzEcb01SOqOOT5ER0OsbyYgq+/D9QzGhc3emRvAAXz66xQJezMpnMvPTBbs4VW6Zg/+O1CV1m0bRW5+qGMuwmFFfL7Maan9+G8nMqByWundCXXiGW2Y0/23yMAxkyYV5LSHIiOhXFbKJg7cuYKooB6Db9bjx71l2cUrSvDzaksu+Y5cN6wuAwZoyJUjmiDs63G0rSNQBoDJVofnwTTEaVg+ra3N1cuH3mANzdXFCAf/33N0orDGqH1WFJciI6laKfVqM7cRAA38RJ+A25QuWIxE/7TvL5lgwAonv58+dZQ6U7pzWEJaBEWSYT1JzLQrNntcoBiZ7dfLh+Uj8ACkt1pHz8GyazDC9uDklORKdReXwvxT9/BoB7SAQhM++VL0GVnThVyiur9gLg4+XOY3eOQuspk621FmXAlSgBvQDQpH0ns8c6gbGDepEUEwJYCsDfXnNQ5j9pBklORKegz8/gzBf/AhQ07p6WOhMPGaKqprJKA8+t3IHeYEKjgb/eNtzWJy9aiasbyrAbUdws73XNz2/DGZlKXU0ajYbZV8TTs5tlRt91v2TxRU3LoXCcJCeiwzOczeXUJ8+iGKoADaHXzMcjNFLtsLq0Kr2RZ1fs4PR5yzTrc2YOYHj/HipH1Ul5B6EMvR5Fo0Fjqkaz+VU4f0LtqLo0L60b916fRICvpWj53a+PsGVPrspRdSySnIgOrbr4DKc+ehpzlWVdi5AZc/EdOF7lqLo2nd7Ikre3cySrEIDxSWHcNDVW5ag6ue6xKEm/A0Bj1KH5LgWK81UOqmsL9PPk3huS8Krpxnzlk73sTS9QOaqOQ5IT0WEZy4o49d8lmMotX4LBU27Ff/gMlaPq2gxGM0+/s4PDmecBy0Rrf7l1mNT+tIeIJMwJlve/Rl+O5tt/yRBjlfXq5sPd1ybg6qLBZFZ4/t2dpGcXqh1WhyDJieiQjOVFnPr4aYzFZwAIGHs9geOSVY6qa9MZjHz8w3kOHrd8IQ7r353Fd4zE3U2WDGg30SMxx08BQFNVjGbTP6H8vMpBdW39IgK5bcYANIDOYOLxN35ld+oZtcNyepKciA7HUJBN/spFVJ/NAcBv6DSCp9ymclRdW6WumudW7CTrjGXNnKFxoTx+5yg83CUxaXf9xqP0HQuApvwsmvXPwrkslYPq2obEhXLz5XFoNKCvNvHMih1s3pWjdlhOTZIT0aFUHt/Lyfcex1hq+XXuN+QKQmbMlW4DFZ08W85fXvnRNsnakNhQHr9rtCQmatFoUPpfjtJntOW/ulI0G5dC9h6VA+vaxg7qxZ1XJ+DmqsFsVnj5k7189v0xGWbcAElORIdRsnsDp1c9XzMqB4KnziHkKllpWE27jpzmkZd/IK+gHIC4MC2P3zUKT0lM1KXRoAychjlhBgqWUTwuP7wOh9aDfBmqJikmhPuSB+Plafn7eO/rI7z5xQGqjbK69MUkORFOz2yo4uz6Nzm/8W3LejluHvS48a8Ejr1eWkxUoigKn353lGdW7KBSZ5k2fdYVccy+rBtaD5lkzWlEj0QZOdu2Do/Lb59b5kIxVKocWNfVNzyAB34/1DbMeP2vJ/jLKz+Sc7pU5ciciyQnwqlVZR8i761HKNv7LQCuPoH0mvMMPv3HqBxZ13X6fAV/f2s7H2xIRVFA6+HKojtGctvMAbhIsuh8usegjLsTResPgCZrO5r/PQEnD6ocWNfVq5sPf541lIjuvgBk5ZfycMoPfP1LlnTz1JCfOMIpmQ06Crd8SOnuDbZt2t4D6f67B3ELCFUxsq7LZDKz9sfj/HdjOoZqSzN0z27e/O2Po4nq5a9ydOKS/HugjL8b9q9Fcy4TTWUxms0vo8RMQBkxCzy81Y6wywny0/LQrKF8sz2bzbtyMBjNvPnFAXannmH+TYMJCezaq3ZLciKciqKYqUjdRuGW/9qGCWvcPAieOgf/ETPQaKSxTw1Hc4p4bfV+MvNLbNuuHNWbu65NwNfbQ8XIhMO0viijbkHJ3YfmyCY0JgOajJ8h/zDK0GToMwZc5O+rPbm6unD1+D70jwriw2/SKC7Xszv1DPe+sJnrL+vHjVNi8Na6qx2mKiQ5EU5BURQqM/ZQtPVjDAUnbNu1kQMIvWY+7sG91AuuC8vIK+bT746y7eAp27bwUF/+382DSewXomJkolk0Gug9FCW0L+z/Cs35LDSVRWh+eQfl0HqUIddD72EgPwLaVb+IQB69bQSrtxxlb/pZDNUmPv3uKBu3neCWGf2ZNjoKN9eu9ZpIciJUpZhNVB3fR9Evn6E/edS23cXbn6AJN0triUrSswv55NujdpNFublquPnyOG6+PFYmVuvovAJQRt9qaUVJ34LGUIGm5BSaH95ACe6NknQtRAwGGQnXbry0btw+cyDjBxWz5sfj5BWUU1Jh4I3PD7Bm63GuntCHy0f2xtera7SkSHIiVGEsPUfZvu8p3b8ZU+mFKbZdPL0JGHMdASOvxsWza/e5trfyqmp+3neSzbtySMsusm13ddEwZXgkN18RS1iIr4oRilZlbUUJT0Q5sQvN8V/QVOvQFOag2foailcAxExAiZkIflLn1V76RQTy8B+Gse/oWdb9nElRmZ5T5yt4e+0hPtyQypThkVw9vk+nr/OS5ES0G2N5MVXHf6MibTuVx/eCYrbdp3HXEjDyKgLG/A5XLz8Vo+xa9NUmDhw7y5Y9eWw/dIpq44XXxM1VwxWjorhpaiw9gqVgstNydYd+41B6D0fJ2mEZzWPUo6kqgYNfw8H10GsAStQIiEgC7yC1I+70XDQahsV3J6lfCNsOneKHvXmcL9GhM5jYsO0EG7adoG94AOMG9WJcUhiRPTrfZ6bDycm6det44403yM3NJTw8nHvvvZfrr7++wf0rKir45z//yaZNm6isrGTEiBE8/vjjREdH2/YxGo0sX76cL7/8kuLiYhISEli0aBFJSUkteU7CSSgmI/ozJ6jK3Eflsd3o8zMA+2FyHj364D/0SnwTJ+LiKV+AbU1RFPIKytmTVsDe9AIOHT+HoVZCAtAtQGv7ddbVRwx0Ke6eEDcJpe8YlFNH0GTvtnT1oMCpI2hOHQFA6RaFEjEYwhIgOMqS3Ig24ebmwsQh4YwfHMbR7CJ+3JdH6glLq2bmyRIyT5bw4TdpRHT3ZXRCTxL6dmNAn26douvHoeRk/fr1LFiwgDvuuIMJEybw3XffsXDhQrRaLTNm1L8K7MMPP8zBgwd59NFH8fHxYfny5dx+++18/fXX+PlZsrznnnuOL7/8kgULFhAWFsbKlSu58847Wbt2LZGRka33LEWbU8wmjMVnMBTkoDt5FP3Jo+hPHUcxGurs6+Lli0///9/evcdGUb4LHP/Obnd72e0VKUivXNUfcrOAAQqigKX1FqsJqZgQgxENxiASpQSC3AIFYrmKAZRofoqcehI9KgWFcDEao9TQ30GwiEAvwMFC6b3dy8ycP7a7dLuFFmy7u/B8kslu33dm9plpO/vMO++8M46oUdMIvXegH6K9O+i6TnWdjT8rqvmzrJo/y69xpqKamnrf34nZZGT8sHt5bHQSwwf3xmiQ8UruWiFmSBqJnjQSvfYySmkRXDqF4nAN3KZcLUW5WgrF/4NuCIFeKdB7IPo9AyA2yXUJSPqqdCmDonB/ahz3p8ZxpbqJX07+H/85c4XLVa7fScXf9VT8fYb/PnQGRYGUvlEMHdCLQYnRpNwbRVKfyKAbHLFT0ebn55OZmUlubi4AEydOpKamho0bN7abnBw7dowjR46wY8cOJk2aBMDo0aOZMmUKu3fv5pVXXqGiooI9e/awZMkScnJyAEhPTycjI4OdO3eybNmyrtpG0UU0hw1n7RWcNVdw1lbirKnEUXUJx5UKHFcvoquOGy5ruieRiMGjsQweTWjCEBlyvovYHSpVtc1cqW7iSk0zl682UFFZz8XKei78XU9Dy+it7ekdG85D98Xz0H3xjBzS+669ZVHcRFQf9GFZ8GAmevUFlMslcPlPlHrXc5QUzQmVf0HlX7jTWd1ghKi+EN3PtbwlDiy9wP1qCvXf9twB7okJJ2t8f7LG96fyWiPFZ67wnz8rqaisR9ddTyc4f6mW85eujzirKK6B35L7RtInzkKfuAj69IqgT2wEvaLDsISbAm607Q6Tk/LycsrKypg/f75XeUZGBoWFhZSXl/u0cvz4449YLBYmTJjgKYuLi2PMmDEcPXqUV155hZ9//hlVVcnIyPDMYzabmTx5MocPH/6HmyV0XQddQ1edoDrRVSe66kB3uibNaUd3NKM7bGgOG7q9Gc3WiNbciGZrQLM1ojbWoTbWojbWoDbUeJ5p0yHFgDk+hbDE+whNGEJY0v2YYvp07wYHCVXTUVUNp6rhcF5/tTtUbA4Vm13F7tBotjtpsjlpbHbS2OygsdlJfZOD2gYbtQ12r6mzEnpbGZwUw5DkWEYO6U1ivDXgDkgiQCkKxCaixybC/VPQm2qgqgylqhyqK6CuEqWlD5miqVB9wTUBbf/C9JBQCIuCsEjXFGp1DQJnCkc3h4MpHExhrhackFDXq9HsunxkCHG9GkNcrTMGIyhGV3x3od6xEUwdk8zUMck025ycv1TLn+XV/HWhhorKOlTVdRld1+HilQYuXmlodz0hRgMxVjMxUWHEWEOxhpuwhJuwhpuwRpixcuOTnO7SYXJy9uxZAPr37+9VnpKSAsC5c+d8kpOzZ8+SkpKC0eh9dpycnExhYaFnnujoaOLi4nzWe/HiRZqbmwkLC7vFzek6P/3Xv1H++onWfSSU2xxWWGnTz6Ltz63LWte1LVPQvSYAs67y+z4woHnKDWgY0ehuOlCvWKlS4qgyuKZrSiyVht4460xwCjil0/KmWz6/U/O1nVF3v1yvaGxsIvzQoVbLuGqvL6t7zkpAR9Nd69Fb3uu6jq7paLqOprmSENd73fVe01A1vUeeuRYXFUpC70gS4q0k9LbS/94oBibF3BHXoUWACI+GhGHoCcNcP6sO9NrLriSl7m+oq4SGK9Bc73v8c9qgvtI1tXG7KYauuBMVxTVGi8EIioEhqopywuxas6Jcr3d/mrusdQRK60iUVkG1ia7dhKgTW9BNeVQ48EDLRCToVjwnPw6Hir3lZEhV9faPnTpQ0zK1Kf5fbRBTJo3t0ZOZDpOTuro6AKxW71sILRYLAPX19T7L1NfX+8zvXsY9/83mAVeH2ltJTk6cONHpeTuiaxrW03uxKrYuW2cwadZDaNbNNGpm6vQw6rUw6vUw6rQwqjUL11qmai0ClfYuzwTpQ8Wqb3xZyt+MBggzG4gIdU9GIkINRIYbiYq4PkVHGAk1uQ++TqAaZ101JSfLeizWoqKiHvusQFdVcQF7bRWK4dav95/+veuOaT3HBCRAZAJEArqGydlEiNqE2dmAydmIUbVhVG2EqDaMmh2D5sCgOTHqt392rugqqL5P9jUBONpvLbjTKYC5ZfIqvI2uJ32o47eioh5toeowzI4eQmRoZ7jjmy3jnr+j9d5qhvbggw8SGtp11zKPVeZQcfKHdk67O46r3S1rsz2t20eu/+x+r7Saz5XZt9d2gqJgszswmUPRMKAr7nYTA5piQMeIprh+VpUQNMWIihFVCUFVQnAqJpyKyfPeroTiUELROxj0LKZlCgSd/TNR2vze2i5XXVNNbExMS53iNZ9n2ZaTKIOrEAXFdZKmKCiK+1XBYFAwKLheDQpGgwGjQcFovP7eFGLwnoxGQkONhIYYCTUbMZuMRISFEB4aQkRYSNAMelZUVERaWpq/wwgY9YMHY2vq5OXQVk7+fpJ/Df1XN0QUuHRNA0czur0J3WlDd9jBaUd32Fyvqr3lErXDc7kaTUXXnKBpoDldx2tdc61L16i5do3o6ChPuft47vr+0Vsd39u897y0OZq7l293AzrTLBp8D/XTdIXmqP6kjR7dpeu12Ww3bVToMDlx31nT0OCdfbpbQNz1rVmtVioqKnzKGxoaPK0lVqvVZ52t19teq0pPGp31FGQ95dcYOkO+DLqG7EfRHaxRUVijbn2wrIiKCnr1kX5a/9TfRUUkyf/1P1blh9bQDscFd/c1KSvzbhYuLS31qm+7THl5uU/rSGlpqWf+AQMGUF1dTU1Njc88iYmJmM3yMDEhhBDibtRhcpKSkkJiYiL79u3zKv/uu+9ITU2lX79+Psukp6dTW1vLTz/95Cmrqqri2LFjjB8/HsDzun//fs88drudw4cPe+qEEEIIcffpVNeYuXPnkpubS3R0NJMnT+bgwYMUFhaSn58PuBKPsrIyBg0ahNVqZcyYMYwdO5b58+ezYMECYmJi2Lx5M5GRkZ4xTRISEnj22WdZuXIljY2NpKSksGvXLmpra3n55Ze7b4uFEEIIEdA6lZxkZ2djt9v56KOPKCgoICkpiby8PLKysgA4fPgwubm5fPLJJzz88MMAbNmyhTVr1rB27Vo0TSMtLY0NGzYQHR3tWe/y5cuJiopi+/btNDY2MnToUHbt2uW5TVkIIYQQdx9F7+i2mQDn7vHb1XfrBAvpyNk1ZD92DdmPXUP2Y9eQ/dg1umM/dvTd3WGfEyGEEEKIniTJiRBCCCECiiQnQgghhAgokpwIIYQQIqBIciKEEEKIgCLJiRBCCCECiiQnQgghhAgot/Hw5MDiHqbFbrf7ORL/sdls/g7hjiD7sWvIfuwash+7huzHrtHV+9H9nX2jodaCfhC2uro6Tp8+7e8whBBCCHGLhgwZQmRkpE950CcnmqbR0NCAyWRCURR/hyOEEEKIDui6jsPhwGKxYDD49jAJ+uRECCGEEHcW6RArhBBCiIAiyYkQQgghAookJ0IIIYQIKJKcCCGEECKgSHIihBBCiIAiyYkQQgghAookJ0IIIYQIKJKc3IEuXbpEWloa77//vr9DCTqVlZUsXryYRx99lFGjRpGdnU1hYaG/wwp433zzDU888QTDhw8nMzOTL7/80t8hBR1N09i9ezdPPfUUo0aNYurUqaxevZr6+np/hxbUXn/9daZNm+bvMILSr7/+Sk5ODiNGjCA9PZ0VK1bQ0NDQI58d9M/WEd50XWfRokVyQLsNdrudl19+mbq6Ot544w3i4+PZv38/8+bNQ1VVnnzySX+HGJD27t3LggULmDVrFunp6Rw4cIB33nmHsLAwpk+f7u/wgsbOnTvZsGEDs2fPZty4cZw7d45NmzZx5swZPvzwQ3+HF5S++uorvv/+e5KTk/0dStA5fvw4L730Eo899hjbtm2jtLSU9957j6qqKvLz87v98yU5ucN89tlnnD171t9hBKWjR4/yxx9/UFBQwPDhwwGYMGECFy9eZMeOHZKc3EB+fj6ZmZnk5uYCMHHiRGpqati4caMkJ52k6zo7d+5kxowZvPXWWwCMHz+e2NhY3nzzTU6dOsUDDzzg5yiDy+XLl1m1ahV9+/b1dyhBaf369YwcOZKNGzeiKArjx49H0zR27dpFU1MT4eHh3fr5clnnDlJeXs769etZsWKFv0MJShaLhRkzZjBs2DCv8gEDBlBWVuanqAJbeXk5ZWVlPP74417lGRkZnD17lvLycj9FFlwaGhp4+umnfRLgAQMGAMjf321YvHgxEyZMYNy4cf4OJehUVVVx7NgxcnJyvJ5ZN3PmTA4cONDtiQlIcnLH0DSNhQsXkpmZyaRJk/wdTlAaN24cy5cv9/pndDgcHDlyhMGDB/sxssDlbqXr37+/V3lKSgoA586d6/GYgpHVamXx4sWkpaV5lR84cACAQYMG+SOsoFVQUMDvv//OkiVL/B1KUDp9+jS6rhMdHc28efMYOXIkaWlpLF26lObm5h6JQS7rBDin00lBQcEN6+Pj45kyZQoff/wxFRUVfPDBBz0YXfDo7H5sa926dZw/f56tW7d2Z3hBq66uDnB9ubZmsVgApO/TP1BcXMz27duZOnUqAwcO9Hc4QePChQusXr2a1atXExcX5+9wglJVVRUACxcuZNq0aWzbto2SkhI2bNiAzWZjzZo13R6DJCcBzmaz8e67796wfuzYsaSmprJhwwY2bdpEZGRkzwUXRDqzH1snJ7qus27dOj7++GNmz57N1KlTeyDK4NPRQ83bexS66FhRURGvvvoqiYmJrFy50t/hBA33DQGPPPIIGRkZ/g4naDkcDgAeeughli5dCrhalnVdJy8vj7lz55KUlNStMUhyEuAsFgslJSU3rFdVlZycHKZPn86ECRNwOp2eOk3TcDqdhITIr7mj/dia3W5n4cKFfPvtt8yePZu33367m6MLXu5kuO3the4WE0mWb93evXtZuHAhqamp7Ny5k9jYWH+HFDQ+/fRTSkpK+Prrrz3HQncC7XQ6MRqNXpdtRfvcLZ9tuwikp6ezZs0aSkpKJDkRN3fp0iWKi4spLi72GVti8+bNbN68udNfysL1pTpnzhx+++03Fi1axKxZs/wdUkBz9zUpKyvjvvvu85SXlpZ61YvO2bVrF3l5eYwdO5atW7dKcneL9u/fz7Vr10hPT/epGzp0KKtXryY7O9sPkQWX1NRUwHWi1pq7RaUnEjxJToJcfHw8X3zxhU/5888/T05ODs8995wfogpOqqry2muvUVxcTH5+vtwG2wkpKSkkJiayb98+r4GuvvvuO1JTU+nXr58fowsuBQUFrFmzhqysLPLy8jCbzf4OKegsW7bMpxVv69atnDp1ii1btpCYmOinyILLwIEDSUhIYO/evbzwwgue8kOHDhESEsKoUaO6PQZJToKc2Wz2ufXVLT4+/oZ1wtfnn3/OL7/8wowZM+jbty/Hjx/31CmKwogRI/wXXACbO3cuubm5REdHM3nyZA4ePEhhYWGPDNR0p7h69SqrVq0iISGBmTNncvLkSa/65ORk6dzZCe5br1uLiYm56XFS+FIUhQULFjB//nwWLFhAdnY2J06cYNu2bbz44os98rcoyYkQLfbv3w/Anj172LNnj1ed0Wj0+cIQLtnZ2djtdj766CMKCgpISkoiLy+PrKwsf4cWNH744Qeampq4cOECM2fO9Klfu3YtzzzzjB8iE3errKwszGYzW7duZc6cOfTq1Yu5c+cyZ86cHvl8Re+ou70QQgghRA+S+/yEEEIIEVAkORFCCCFEQJHkRAghhBABRZITIYQQQgQUSU6EEEIIEVAkORFCCCFEQJHkRAghhBABRZITIYQQQgQUSU6EEEIIEVD+H7DtT7r5ddRxAAAAAElFTkSuQmCC\n", - "text/plain": [ - "<Figure size 576x432 with 1 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "prob_b = 0.08\n", "min_diff = 0.02\n", - "size_a = 2500\n", - "size_b = 2500\n", + "tamano_a = 2500\n", + "tamano_b = 2500\n", "\n", - "plot_power(min_diff, prob_b, size_a, size_b)" + "plot_poder_estadistico(min_diff, prob_b, size_a, size_b)" ] }, { @@ -1096,48 +1080,26 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 576x432 with 1 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "# smaller N\n", "prob_b = 0.08\n", "min_diff = 0.02\n", - "size_a = 1250\n", - "size_b = 1250\n", + "tamano_a = 1250\n", + "tamano_b = 1250\n", "\n", - "plot_power(min_diff, prob_b, size_a, size_b)" + "plot_poder_estadistico(min_diff, prob_b, size_a, size_b)" ] }, { "cell_type": "code", - "execution_count": 26, + "execution_count": null, "metadata": { "scrolled": true }, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 576x432 with 1 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "# smaller probability difference\n", "prob_b = 0.08\n", @@ -1159,7 +1121,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Determining Sample Size" + "## Determinando el tamaño de la muestra" ] }, { @@ -1184,14 +1146,14 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import statsmodels.stats.api as sms\n", "\n", "\n", - "def compute_sample_size(prop1, min_diff, significance = 0.05, power = 0.8):\n", + "def calcula_tamano_muestra(prop1, min_diff, significance = 0.05, poder = 0.8):\n", " \"\"\"\n", " Calcula el tamaño de la muestra requerido para una prueba A/B de dos proporciones;\n", " el resultado coincide con pwr.2p.test de R del paquete pwr\n", @@ -1230,29 +1192,21 @@ " - https://stackoverflow.com/questions/15204070/is-there-a-python-scipy-function-to-determine-parameters-needed-to-obtain-a-ta\n", " \"\"\"\n", " prop2 = prop1 + min_diff\n", - " effect_size = sms.proportion_effectsize(prop1, prop2)\n", - " sample_size = sms.NormalIndPower().solve_power(\n", - " effect_size, power = power, alpha = significance, ratio = 1)\n", + " tamano_efecto = sms.proportion_effectsize(prop1, prop2)\n", + " tamano_muestra = sms.NormalIndPower().solve_power(\n", + " tamano_efecto, power = poder, alpha = significance, ratio = 1)\n", " \n", - " return sample_size" + " return tamano_muestra" ] }, { "cell_type": "code", - "execution_count": 29, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "tamaño de la muestra requerido para obtener un resultado significativo: 3834.5957398840183\n" - ] - } - ], + "outputs": [], "source": [ - "sample_size = compute_sample_size(prop1 = 0.1, min_diff = 0.02)\n", - "print('tamaño de la muestra requerido para obtener un resultado significativo:', sample_size)" + "tamano_muestra = calcula_tamano_muestra(prop1 = 0.1, min_diff = 0.02)\n", + "print('tamaño de la muestra requerido para obtener un resultado significativo:', tamano_muestra)" ] }, { @@ -1271,30 +1225,19 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<Figure size 576x432 with 1 Axes>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ - "# calculate the the required sample size\n", - "# for a range of minimum detectable difference\n", - "sample_sizes = []\n", + "# calcular el tamaño de la muestra requerido\n", + "# para un rango de diferencia mÃnima detectable\n", + "tamano_muestras = []\n", "min_diffs = np.arange(0.01, 0.03, 0.001)\n", "for min_diff in min_diffs:\n", - " sample_size = compute_sample_size(prop1 = 0.1, min_diff = min_diff)\n", - " sample_sizes.append(sample_size)\n", + " tamano_muestra = calcula_tamano_muestra(prop1 = 0.1, min_diff = min_diff)\n", + " tamano_muestras.append(tamano_muestras)\n", "\n", - "plt.plot(min_diffs, sample_sizes)\n", + "plt.plot(min_diffs, tamano_muestras)\n", "plt.title('Tamaño de la muestra necesaria para detectar la diferencia mÃnima')\n", "plt.ylabel('Tamaño de la muestra')\n", "plt.xlabel('Diferencia mÃnima')\n", @@ -1318,9 +1261,9 @@ "Todos vimos la pelÃcula del Titanic y vimos la parte en la que los ricos empezaron a dar dinero para tener prioridad en los botes de seguridad. Podemos entonces formular la hipótesis de que los ricos del Titanic tenÃan una tasa de supervivencia más alta que los demás. Como no podemos confiar sólo en una pelÃcula para sacar conclusiones, debemos obtener datos.\n", "Vamos a utilizar el conjunto de datos que proporciona [Kaggle aquÃ](https://www.kaggle.com/c/titanic/data). \n", "\n", - "1. Subir los datos al notabook\n", - "2. Hacer una exploración de las variables\n", - "3. Usar los conceptos y funciones definidas en este notebook para realizar una prueba de hipotesis, que pruebe o desmienta si los pasajeros mas ricos del Titanic tenian mayor probabilidad de sobrevivir." + "1. Subir los datos al notebook\n", + "2. Hacer una exploración de las variables presentes en el conjunto de datos.\n", + "3. Usar los conceptos y funciones definidas en este notebook para realizar una prueba de hipotesis, que pruebe o desmienta si los pasajeros mas ricos del Titanic tenian mayor tasa de supervivencia." ] }, { @@ -1346,6 +1289,13 @@ "- [Paper: R. Kohavi, A. Deng, B. Frasca, R. Longbotham, T. Walker, Y. Xu (2012) Trustworthy Online Controlled Experiments: Five Puzzling Outcomes Explained](http://notes.stephenholiday.com/Five-Puzzling-Outcomes.pdf)\n", "- [Slideshare: 4 Steps Toward Scientific A/B Testing](https://www.slideshare.net/RJMetrics/4-steps-toward-scientific-ab-testing)" ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { -- GitLab