tag:blogger.com,1999:blog-92045606679394242112023-06-20T05:12:59.159-07:00ESTADÍSTICA ENFERMERARocío Romero Castillohttp://www.blogger.com/profile/12000531683527549788noreply@blogger.comBlogger20125tag:blogger.com,1999:blog-9204560667939424211.post-58453768772404562782012-06-14T14:16:00.002-07:002012-06-14T14:16:49.840-07:00Tema 10. Parte 2. Regresión lineal.<br />
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Galton dijo: "Cada peculiaridad en un hombre es compartida por sus descendientes pero en media, en un grado menor". Él habló de la regresión a la media.<br />
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Hay varios modelos de regresión, nosotros en clase hemos visto el modelo de regresión lineal simple. Se trata de estudiar la asociación lineal entre dos variables cuantitativas. En la regresión lineal simple solo hay una variable independiente. Para construir un modelo de regresión lineal hace falta conocer un punto de intersección con el eje de coordenadas Bo y la pendiente de la recta B1. No hay modelos deterministas, hay una nube de puntos y buscamos la recta que mejor explica el comportamiento de la variable dependiente en función de la variable independiente.<br />
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Definimos algunos conceptos como:<br />
Coeficiente de correlación (Pearson y Spearman): número adimensional, entre -1 y 1, que mide la fuerza y el sentido de la relación lineal entre dos variables.<br />
Coeficiente de determinación: número adimensional, entre 0 y 1, que da idea de la relación entre las variables relacionadas linealmente.<br />
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Para verificar si una relación es o no significativa se realiza el test de hipótesis de Tau de Kendall. Se aplica una fórmula. Si obtenemos valores altos el test dice que hay relación y si obtenemos valores próximos a cero hay que aceptar la hipótesis nula.<br />
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Después de la teoría realizamos en clase una serie de ejercicios prácticos. Me parece que son entretenidos y veo que los entiendo, voy a hacerlos todos de nuevo para ver si me salen perfecto y con buena presentación que también cuenta.Rocío Romero Castillohttp://www.blogger.com/profile/12000531683527549788noreply@blogger.com0tag:blogger.com,1999:blog-9204560667939424211.post-83693530880709459482012-06-11T14:30:00.002-07:002012-06-11T14:33:14.248-07:00Seminario 6<br />
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Este es el último seminario de la asignatura. Hemos expuesto cada grupo de investigación nuestro trabajo. Creo que todos han estado bastante bien y que hemos alcanzado los objetivos que se pedían en la asignatura. Todavía queda redactar bien el trabajo con la precisa discusión y conclusión para posteriormente subirlo al Campus en el plazo de entrega.<br />
En concreto a nuestro grupo, el profesor José Antonio nos ha dicho que nuestro trabajo está bien, que le hubiese gustado que comparásemos la calidad de vida en pacientes en diálisis con otros pacientes crónicos pero no disponemos de los recursos ni del tiempo necesario. En lo que respecta a esta asignatura de Estadística y TIC hemos llegado a la meta.<br />
Nos ha dicho que en el trabajo no se pone el cronograma, eso sólo se incluye en el protocolo. Dijo que la introducción estaba un poco escueta pero la razón es porque sintetizamos bastante los antecedentes de nuestro trabajo para no aburrir a los oyentes. Tampoco pusimos referencias bibliográficas en la presentación, tal vez deberíamos haber puesto algunas referencias pero no hay problema porque todas están claras en el trabajo.<br />
Por lo demás estaba todo bien.<br />
Ha sido un trabajo que ha requerido mucho esfuerzo y tiempo, desde luego es el más complicado del curso y me atrevo a decir que de la carrera, exceptuando el trabajo de fin de Grado que será un poco similar.Rocío Romero Castillohttp://www.blogger.com/profile/12000531683527549788noreply@blogger.com0tag:blogger.com,1999:blog-9204560667939424211.post-35890946125250647042012-05-31T00:53:00.001-07:002012-05-31T00:53:41.364-07:00Seminario 5<br />
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En este seminario también estuvimos trabajando con el programa Epi Info. Analizamos varias variables de unos estudios. En primer lugar vimos qué alimento había ocasionado una enfermedad gastrointestinal en una fiesta de cumpleaños y descubrimos que había sido el helado de vainilla porque era el único en el que la p era menor de 0.05. Miramos la ODDS ratio, el intervalo de confianza y el porcentaje de error.<br />
Trabajamos con el test de chi cuadrado, el de la T de student y con la regresión lineal que la tenemos que ver hoy en clase.<br />
Era curioso que algunas variables se aproximaban mucho al error máximo de 0.05 pero si lo superaba por milésimas esta variable no influía, con lo cual aceptábamos la hipótesis nula.Rocío Romero Castillohttp://www.blogger.com/profile/12000531683527549788noreply@blogger.com1tag:blogger.com,1999:blog-9204560667939424211.post-16687489377401568482012-05-31T00:45:00.002-07:002012-05-31T00:47:50.917-07:00Seminario 4<br />
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En este seminario estuvimos utilizando aplicaciones del programa Epi Info. Aprendimos a realizar tablas de frecuencia en dicho programa y vimos cómo se hacían los gráficos. Se podían hacer varios tipos de gráficos y personalizarlos con los colores que quisiéramos. Estos gráficos se podían guardar en una carpeta que posteriormente era recuperada para copiar y pegar el gráfico en un documento word. <br />
Estuvimos analizando varias variables de un estudio que empezamos a trabajar en seminarios anteriores que consistía en ver qué alimento había ocasionado una enfermedad gastrointestinal en los asistentes a una fiesta de cumpleaños. Representamos el consumo de algunos alimentos en gráficos.Rocío Romero Castillohttp://www.blogger.com/profile/12000531683527549788noreply@blogger.com0tag:blogger.com,1999:blog-9204560667939424211.post-77658245641397331532012-05-26T08:33:00.001-07:002012-05-26T08:34:08.902-07:00Tema 10. Hipótesis estadísticas. Test de hipótesis.<br />
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Los test de hipótesis son herramientas estadísticas que permiten cuantificar la compatibilidad entre una hipótesis previamente establecida y los resultados obtenidos. Me hago la siguiente pregunta: ¿Rechazo o acepto la hipótesis nula? - El test te responde sí o no.<br />
La hipótesis nula es la que establece igualdad entre los grupos a comparar, o dicho de otro modo, la que no establece relación entre las variables de estudio.<br />
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Según el tipo de variables elegimos un tipo de análisis estadístico. Los que vamos a utilizar nosotros son chi-cuadrado y T student. Chi cuadrado es para variables cualitativa tanto dependiente como independiente y T student es para variables dependiente cuantitativa e independiente cualitativa.<br />
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El test de hipótesis mida la probabilidad de error que cometo si rechazo la hipótesis nula.<br />
El error alfa es la probabilidad de equivocarnos al rechazar la hipótesis nula.<br />
El error alfa más pequeño al que podemos rechazar Ho es el error p.<br />
Normalmente rechazamos Ho para un nivel alfa máximo del 5% (p< 0.05).<br />
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Tipos de errores en test de hipótesis<br />
Error alfa: se comete rechazando la hipótesis nula siendo esta verdadera.<br />
Error beta: se comete cuando acepto la hipótesis nula y resulta que es falsa.<br />
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Test de hipótesis Chi-cuadrado<br />
Suponemos la hipótesis cierta y estudiamos cómo es de probable que siendo iguales dos grupos a comparar se obtengan resultados como los obtenidos o haber encontrado diferencias más grandes por grupos.<br />
Se realiza una tabla de 2x2 con los resultados observados. Posteriormente se realiza otra tabla con los datos esperados.<br />
Se calcula chi-cuadrado mediante una fórmula. El valor resultante tiene correlación inversa con el valor de p.<br />
Sabemos que para una p= 0.05, chi-cuadrado vale 3.84. Si es superior a este valor rechazamos la Ho.<br />
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En clase realizamos aproximadamente unos cinco ejercicios relacionados con este test de hipótesis y estudiamos varias maneras de hacer los cálculos.<br />
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Test de hipótesis T de student.<br />
Se utiliza cuando la variable independiente es dicotómica y la variable dependiente es continua.<br />
También realizamos varios ejercicios acerca de este test.<br />
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Según tengo entendido este es el último tema de la asignatura. He entendido todos los temas. Ahora me queda practicar bien los ejercicios y estudiar detalladamente la teoría. En este parcial entran tres temas pero hay que tener claros los siete temas que vimos en el primer parcial. Tendré que darle un repaso a algunas fórmulas estadísticas. <br />
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<br />Rocío Romero Castillohttp://www.blogger.com/profile/12000531683527549788noreply@blogger.com0tag:blogger.com,1999:blog-9204560667939424211.post-46287182160642198372012-05-18T09:36:00.003-07:002012-05-18T11:40:28.670-07:00Tema 9. Estadística inferencial: muestreo y estimación.<br />
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La <b>inferencia estadística</b> es el conjunto de procedimientos estadísticos que permiten pasar de la muestra a la población.<br />
La población de estudio es el conjunto de pacientes sobre los que queremos estudiar algo.<br />
La muestra es el conjunto de individuos concretos que participan en el estudio.<br />
Siempre que utilizamos muestras hay que asumir un margen de error.<br />
En el muestreo probabilístico o aleatorio se elige por un procedimiento de azar y el error se puede evaluar, se denomina error aleatorio. En los muestreos no probabilístico no es posible evaluar el error.<br />
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La medida que queremos obtener se llama parámetro, pero casi nunca la vamos a conocer porque tendríamos que estudiar a la población entera. Lo que podemos obtener es el estimador, que se realiza sobre la muestra.<br />
Al proceso por el que a partir de un estimador, me aproximo al parámetro se denomina inferencia.<br />
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Posteriormente vimos el concepto de <b>error estándar.</b><br />
Mide el grado de variabilidad en los valores del estimador en las distintas muestras de un determinado tamaño que pudiésemos tomar de una población. Cuanto mayor sea el tamaño de la muestra, menor será el error estándar. Tenemos una fórmula para calcular el error estándar: para una media y para una proporción.<br />
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<b>Intervalos de confianza</b>. Son un medio de conocer el parámetro en una población midiendo el error que tiene que ver con el azar.<br />
En clase realizamos varios ejemplos donde calculamos intervalos de confianza.<br />
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TIPOS DE MUESTREO<br />
<b>Probabilístico</b>. Todos los sujetos de la población tienen una probabilidad distinta de cero en la selección de la muestra.<br />
- <b>Aleatorio simple</b>. Cada unidad tiene la probabilidad equitativa de ser incluida en la muestra. No puede usarse cuando el universo es grande.<br />
- <b>Aleatorio sistemático</b>. Cada unidad del universo tiene la misma probabilidad de ser seleccionada. Se elije un número aleatorio y a este se le va sumando el cociente entre el número de sujetos de la población y el de la muestra.<br />
-<b> Estratificado</b>. Se caracteriza por la subdivisión de la población en subgrupos o estratos, debido a que las variables principales presentan cierta variabilidad.<br />
- <b>Conglomerado</b>. En la selección de la muestra se toman los subgrupos o conjuntos de unidades conglomerados. El investigador no conoce la distribución de la variable. Es menos fiable que el aleatorio.<br />
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No probabilístico<br />
No se sigue el proceso aleatorio. No puede considerarse que la muestra sea representativa de una población. El investigador decide, según sus objetivos, los elementos que integrarán la muestra: por conveniencia o intencional.<br />
Hay dos subtipos:<br />
Por cuotas. El investigador selecciona la muestra considerando algunos fenómenos o variables a estudiar.<br />
Accidental. Consiste en utilizar para el estudio las personas disponibles en un momento dado, según lo que interesa estudiar.<br />
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Se puede calcular, mediante una fórmula, el tamaño de una muestra para estimar la media de una población.<br />
También se puede calcular, mediante otra fórmula, el tamaño de una muestra cuando queremos estimar una proporción.<br />
Realizamos varios ejercicios para practicar esto. Me ha parecido un tema interesante, las últimas fórmulas no recuerdo haberlas estudiado el año pasado en estadística y las he visto bastante útiles.Rocío Romero Castillohttp://www.blogger.com/profile/12000531683527549788noreply@blogger.com0tag:blogger.com,1999:blog-9204560667939424211.post-66856806026529195412012-05-12T02:49:00.001-07:002012-05-12T02:50:02.112-07:00Tema 8. Medidas de tendencia central, posición y dispersión.<br />
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En este tema vimos, en primer lugar, dos grandes tipos de medidas estadísticas:<br />
- Medidas de posición o tendencia central: dan idea de la magnitud de los datos.<br />
- Medidas de dispersión o variabilidad: dan información acerca de la heterogeneidad de las observaciones.<br />
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<b><span style="color: black;">Medidas de tendencia central</span></b><br />
<b><span style="color: black;">- Media. </span></b><span style="color: black;">Es</span><b><span style="color: black;"> </span></b><span style="color: black;">la suma</span><b><span style="color: black;"> </span></b><span style="color: black;">de todos los valores de la variable entre el total de observaciones. Cuando los datos son agrupados, utilizamos como valor de referencia la marca de clase de cada intervalo.</span><br />
<span style="color: black;"><br /></span><br />
<span style="color: black;">-<b> Mediana</b>. Es el valor de la observación tal que un 50% de los datos es menor y otro 50% es mayor.</span><br />
<span style="color: black;">Si el valor de las observaciones es impar el valor de la mediana será la observación que ocupa la posición n+1/2.</span><br />
<span style="color: black;">Si el número de observaciones es par, el valor de la mediana es la media entre la observación n/2 y la observación n+1/2.</span><br />
<span style="color: black;">Tiene mejor comportamiento que la media cuando hay observaciones extremas.</span><br />
<span style="color: black;"><br /></span><br />
<span style="color: black;">- <b>Moda</b>. Es el valor que más se repite. Si los datos están agrupados se habla de clase modal y corresponde al intervalo en el que el cociente entre la frecuencia relativa y la amplitud es mayor.</span><br />
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<span style="color: black;">Después de ver esto hicimos un ejercicio práctico para aplicar estos conceptos.</span><br />
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<b>MEDIDAS DE POSICIÓN</b> <br />
<span style="color: black;"><b>Cuantiles. </b>Se calculan para variables cuantitativas y solo tienen en cuenta la posición de los valores de la muestra. Los cuantiles más utilizados son percentiles, deciles y cuartiles, según dividan la muestra ordenada en 100, 10 o 4 partes, respectivamente.</span><br />
<span style="color: black;"><b> </b></span><br />
<span style="color: black;"><b>Percentiles. </b>Para buscar la posición de un percentil es una serie de datos agrupados, buscamos el intervalo en el que la frecuencia relativa acumulada (Hi) sea superior al valor del percentil. El valor del P50 corresponde al valor de la mediana.</span><br />
<span style="color: black;"><br /></span><br />
<span style="color: black;"><b>Deciles</b><b>. </b>El valor de D5 corresponde al valor de la mediana y, por tanto, al del P50.</span><br />
<span style="color: black;"><br /></span><br />
<span style="color: black;"><b>Cuartiles. </b>El Q2 conincide con el valor de D5, con el valor de la mediana y del P50.</span><br />
<span style="color: black;">Por ejemplo el Q1 indica el valor que ocupa una posición en la serie numérica de forma que el 25% de las observaciones son menores y que el 75% son mayores.</span><br />
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<b><span style="color: black;">MEDIDAS DE DISPERSIÓN</span></b><br />
<b><span style="color: black;">Rango o recorrido</span></b><span style="color: black;">. Diferencia entre el mayor y el menor valor de la muestra.</span><br />
<span style="color: black;"><b>Desviación media</b>. Media aritmética de las distancias de cada observación con respecto a la media de la muestra. </span><b><span style="color: black;"></span></b><br />
<b><span style="color: black;">Desviación típica.</span></b><span style="color: black;"> Cuantifica el error que cometemos si representamos una muestra únicamente por su media.</span><br />
<span style="color: black;"><b>Varianza. </b>Expresa la misma información que la desviación típica en valores cuadráticos.</span><br />
<span style="color: black;"><b>Coeficiente de variación</b>. Es una medida de dispersión relativa (adimensional). Nos sirve para comparar la heterogeneidad de dos series numéricas con independencia de las unidades de medida.</span><br />
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<span style="color: black;">A continuación realizamos un ejercicio donde se pedía calcular las medidas estadísticas estudiadas anteriormente. Era un ejercicio fácil de entender aunque había que fijarse bien en los cálculos para no cometer errores. </span><br />
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<span style="color: black;"> Después vimos las distribuciones normales. Estas son las que con más frecuencia aparece en fenómenos reales y siguen unos principios básicos. Analizamos la campana de Gauss.</span><br />
<span style="color: black;">Posteriormente estudiamos las asimetrías y curtosis. </span><br />
<span style="color: black;">El coeficiente de asimetría de una variable es el grado de asimetría de la distribución de sus datos en torno a su media. </span><br />
<span style="color: black;">El coeficiente de apuntamiento o curtosis de una variable sirve para medir el grado de concentración de los valores que toma en torno a su media. Se elige como referencia una variable con distribución normal, de modo que para ella el coeficiente de curtosis es 0. </span><br />
<span style="color: black;">Estudiamos los resultados que se podían obtener y el tipo de distribución en función de éstos.</span><br />
<span style="color: black;">Asimetrías</span><br />
<span style="color: black;">g1 = 0 Distribución simétrica</span><br />
<span style="color: black;">g1 > 0 Distribución asimétrica positiva</span><br />
<span style="color: black;">g1 <0 Distribución asimétrica negativa</span><br />
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<span style="color: black;">Curtosis</span><br />
<span style="color: black;">g2 = 0 Distribución mesocúrtica</span><br />
<span style="color: black;">g2 > 0 Distribución leptocúrtica</span><br />
<span style="color: black;">g2 < 0 Distribución platicúrtica</span><br />
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<span style="color: black;"> Me ha parecido un tema entretenido y muy práctico, esencial en estadística. </span><br />
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<span style="color: black;"><br /></span>Rocío Romero Castillohttp://www.blogger.com/profile/12000531683527549788noreply@blogger.com0tag:blogger.com,1999:blog-9204560667939424211.post-31433543658059275732012-04-26T13:37:00.003-07:002012-04-26T13:45:00.371-07:00Tema 7. Introducción a la Bioestadística. Organización de datos.<br />
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La estadística es la ciencia que estudia la variabilidad. Parte del supuesto de que las características clínicas que se observan cambian de un paciente a otro.<br />
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Hay diferentes escalas de medida:<br />
<b>Escala nominal</b>. Con esta medida solo se puede comprobar si dos características son iguales o diferentes. Se mide por ejemplo, la raza, el género, la profesión, etc. Las categorías deben ser exhaustivas (los puedo clasificar a todos) y excluyentes (no puedo clasificar a un sujeto en dos grupos).<br />
<b>Escala ordinal. </b>Ante dos modalidades distintas determina cuál de ellas es mayor. Los números expresan relaciones de igualdad, desigualdad y orden. Ejemplo: grado de dolor, 1. nulo, 2. leve, 3. medio, 4. máximo.<br />
<b>Escala de intervalo. </b>Presentan las características propias de las dos escalas anteriores. Las distancias o intervalos representan distancias equivalentes. No se pueden sacar razones o proporciones. <br />
<b>Escala de razón. </b>Nivel más alto de medición. Establece relaciones de identidad, orden, existencia de intervalos equivalentes y cuántas veces una modalidad es superior a otra. <br />
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También estudiamos los tipos de variables:<br />
<b>Cualitativas</b>. Se refiere a propiedades que no pueden ser medidas, solo se pueden clasificar.<br />
<b> Nominales</b>.<br />
- Dicotómicas: 2 categorías (Ej: sexo).<br />
- Policotómicas: más de 2 categorías (Ej: estado civil).<br />
<b>Ordinales</b>. Ej: nivel de dolor.<br />
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<b> Cuantitativas. </b>Se pueden medir en término numéricos.<br />
<b>Discretas</b>. Sólo pueden tomar un número finito de valores. Son números aislados.<br />
Ej: número de hijos.<br />
<b>Continuas.</b> El número está dentro de un rango. Ej: talla, peso.<br />
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Representación de datos.<br />
Tablas de frecuencia. Son la imagen de los datos que muestran frecuencia en columnas y las categorías de las variables en filas. <br />
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<a 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" 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Para variables discretas.<br />
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Para variables continuas tenemos que construir intervalos. El número de intervalos se calcula haciendo la raíz cuadrada del número de datos. El recorrido se calcula restando el dato menor al mayor. Para obtener la amplitud del intervalo dividimos el recorrido por el número de intervalos.<br />
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La representación es sencilla pero entretenida cuando hay muchos datos y hay que ser cauteloso y tener paciencia a la hora de contar para no equivocarse.<br />
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En una tabla tienen que aparecer: intervalos, marcas de clase, frecuencia absoluta, frecuencia absoluta acumulada, frecuencia relativa y frecuencia relativa acumulada.<br />
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" 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" 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+545JFHZFleu3Zto0aN5s+fP2jQoOeee45O3EVERFRXV/fq1SsiIuKll16itV5RUdG8efMHH3zwgQceuOWWW/x+/+eff/7UU09FRESkpKSoqkoHWmVlZc8++2xERESzZs0AYMOGDb///e8rKipyc3Nvv/12KkU1TfN6vU888cQTTzzRqFGjV155RVXVsWPHPvLII0899RTDMParMQwTERHx8ssv//GPf/zyyy8BgOf5pk2bPvDAA1SZXLdu3cMPP3z77bdTS9jKlSsfffTRiIiIzp07A8COHTtefPHFJk2a9OjRg96Q0q9du3Z33nknzVlVVfXZZ59RzXzEiBG2VWzr1q0PPfTQQw891Lx58/Ly8r///e8REREtWrTQdb2oqOihhx669dZbW7RoQW9LZ6QbN27897///b777ps4cSIAHD16tG3btjfccEPTpk0ty1q3bl1ERETLli1vueWW4uJiAOA47vHHH3/88ceHDBmiqurmzZtffvnlW265pU+fPnYJbNy48aGHHrrzzjuffvrp3bt3v/3226+//joEDXiNGzdOTk4GgJtvvjkvL2///v10XPDcc89t2bLl+PHjDz/88E033TRlyhQA+Oqrrx599NGmTZsOGTLENM3333//T3/6E7UyhPo50ddvmA6Gv1aK2rYi20pRWlqan59fWFi4ceNGW41ZsWLF2bNnLcsqLS1ds2aNbf7ds2fPvn37vvnmG6qvAsCaNWtM09yxY8eBAwf2799vWwUJIevWrcMYr1y5kp7ZuXPnDz/8AACWZRUXF9OyO3bs2O7du213508//RQAKioqqGGJ5qG/HjhwYM+ePZs2baJ327Jly6ZNm+zXsSwrIyPj/vvvP3HixKFDh2geXde/++67r776yn79zZs379q1y55eOnLkyLfffuv3++lN9u/fv3TpUk3TKDn9fj81NX/99dcVFRUbNmwAAGpW2bx5s22moqisrFy1ahU9rqqq2r59e2lpKf169uxZ+tjUsZkerFq1SpIk2pXY2b744guqNp85c6awsLC6uvq7776D4PD11KlTq1evtvOXlJQsXboUgpZVWkr79+8vKyvbs2fPwYMHt23btm3bNnpD+u4HDx48e/bsxo0bjx8/jhAqKSnZtWvXyZMnT5w4UV1dLUnSpk2baObq6uqysrINGzbQsvr222/37t1LKWo7hNlPUi8z2/WOXytFqTEQgiLCHk7YPrqKolCTnc1hytuLzqDYxqdQ+3tZWRn9o9A5AKo3yrJMv4ba9+nxhY4Tdt9M3Srs56GmEdrcQ9+FYRiqHELQo9Be7kCfjWa2VU0AAEwMwwBaSwQQQv5qH0KEniH0hYLGNV1XETItyzBN3TR1+4Hp/IQ9V0SbuL20gOahdtpQzy26YMAmLQQdmKhfEb2cGrpDXzy0oOgr2PO0kiTZPYtdbnY90pZpc4neP7SCqM+gnYGetC3qEHTTsb/aTlQNFvVAUTqlFtpn0/O0e6aKPlX26Hm7ydIqucQylOsQl5jCruUCAAKAa/+0E6IsxQDW+QlfMoXRICBJkiRJgwcPrjNFa/xEu3ZKTjqLHZqBCh/bfx+CndyvwmW/gYIAEHz+Jw4eX0A3AgAYwAym/4WoYVxj4OCCUMMwhgwZcpkU9fl8NfwwKQ9t3w7qcVbb5fTvwiC1L3SuJTsCYgBo533SRIyQZNqJQC2JoFpSGNcSEFy5QckydOjQOlOUDsBCZ5aOHj36008/AYDf7y8sLNyzZ4/tyEqCKwBDx4d04H5tC+JXC3QeLQNJuSCd+zVM0V8XKBkpX+icVp0pag+16RpfVVVLSkruvvtujPHo0aOnTJly7Ngx260cISRJEl20ZQtVu4cIg1xSW7kYEBDzfIEZki5CXe2SbAxTtMGB1j41gmqadvkWXdvh2+fzUTdXWZanTJnCMAw1dtPllPaYU9d125QPQQf3MC4DgGtPAQKboTQOIV6Yor8C0EUadCmVqqo9e/asM0Vt8yxdv0Y9s7p160ZlY3Fx8fz582keRVEOHjzYpUuXvn37Pvjgg3379p03b15GRkZBQUFOTs7yMJYvX758eUEtqCX7iuXLVi9f9mkgLV0bSIEzq5cvW7V82arly1csX76i5oU1sbRmKshbvnxp/b9hGHUBdWMkhFAt9RfNiyKETp061axZs+jo6Mcff/zTTz+l3irU/67G1NOQIUPsEantThAGOj/UWChqyU6QBcisPVkhCZGLpVCY5yWsI6xf8RcO45KgntgQHFEOHDiwzhSl08qhnlOSJL333nubNm0aM2bMwoUL6TSMGQzlRpcv9+zZ82fj3ITxvwAj0DVk6MQ0zk2UWAYQBASFTMGQ4GpVAhiBplpAQNcCRr6QKsAXTJyGcVVBq8numlesWEHP0EFi//79L0eKIoTsBbJ0luWnn36iMRBsXxzKYVmWaXiBMEXrDxgAG4aGEEJWwJPBNEL4GSAnooYiSlGa0zIBIwBS825hil5DXCmK2uECbDstDgnARx3E6LFNURJcoBim6C+ApVvVBCQCMgGVgEkAk6DHUTBhAhYBk4BOwLRMMA0wdNA1THCYog0O9U/R0DgdtmMklZl0JZQdYBYFw8CZptmrVy8SjKoapugvgEVAIuCrlk8TUP1KlaormMAFLAUCFgGLALbMwHeCAweqYp4tqwre8EKKhmvnqqL+KVpDUyVBF2fbSTr0VrZ3tU3RwAApjMuERUDFIPmVCgIWZaNpArJCRqEBXTeQ7PGqroGmBthshex3EUJRM0zRq4/6p2gNMYiCyzJC1+OFglK0d+/eEBJYsP5e8HoD9knVmqESgLIy38EDp/d/V/rdf8sOHVT2flu19xvv3m+r9n5btffbir17SvfuKd275/Sh78+cOF7p85qAwZaoF+i6YYpeM1wRKVojm2VZdL6VxlCmPxmGQeMp04DOoRS9Ii963YAQQAQUFSZOXPJG20FtWw9t12ZEp/YTOneY1Ln9x53bf9y5w6TOHSZ27jiuc8dx0ZHD2rZ6s/0b8VM/ni/7sWkEbEthijYcXBFzUei0Jw5ZuacoSmi8SZvACKEwResHBBAC3QSEYe6cnIRZ//l0RdV/VssZ4olled5lub5leV6aCnIrC/LKC5ae/M+awx9/zMydm0oALAQEQNcw1KyEcz5K1+S1rmfUP0VDV8TalqFevXr5fL74+Pj4+HgaHBVjTI29NBYjjQ+kKMp1G2W8ngCWCZiAZpljxiVOmbQ5jTM8giGyqiAogqAIgiQIisDrLk538YpL8HpcFRMnrR4/Zb4OugWAAAgdkBJECLKpaUHQvkTCVXM1EEqBUH+V+pGiEAxMTo8nT57coUOH8ePHnzhx4scffwwNFWmLzcGDB8Mld/UJ43+EoWPDMhGos+awSXMPp/OQxoHbBTwHrIBYAbE84VngWRBYEDjEOrUpU7+aNm+JAbIFFp1zMS0IrCANWoNRMIWVnGuLeqCo7bRAV6UVFRUlJycvXLhwxIgRhw4d+vrrr6dOnWqHpThx4oTD4WAY5oknnliyZElSUpLD4Vi8eLHb7U4N47LAc+4lqSmeTL5zTL9J43Z6OHCzwHO1UdR088bwEas6xvdwpi+elThz/sKkRYuXJCYmOhyJqc7E1NTUlFRnimNxsnNxsiM12eFMcVzrN7w+4AjCPpOSkpKSklI/UpQE99U5fvz4q6++euDAgXbt2n344YeHDx8uKiqigeFotsrKyvXr1xcWFkZGRq5fv3716tVr1qxZvXr1tm3b1odxWdi4YdMnaz79rHB1j17DZk7Zm+0G0QmLFsq1UTQ7HSZN+nzA0JFf7Vi3Zv0nhRs+37Dhi/WfrSssXFVYuKpw/Wfr169fX7hm3eefrCtcu67ws2v9ftcLCgsLCwsL7a/rgqgfilJHBb/ff/bsWVEUExIS/vWvf7322ms//fTTf//733feeQfOD9tlWdbgwYNtpfcq7DX0G0ZQNdVnJjDzZh30cOBiwOmwLkpRF4uYZOmjMesnTE20QCWAzwVPIQYQjVqICBgYDAwmhvBitKsEuKJj0dCYd16vV9M0j8djGMb777//7rvv0vP2xjvU1YGGOcfBHYEuff8wLgFFNhDBFlHGfDR34tgdbDK4WRD4iyu6LhblpMHUScUfT0tGYBEAywSsAZjBoEc4NAQZDtfKtYJN13ozF0HQE5DOsui6Tv3pzeAe9aZp0hEptSr16tULwlHF6gUECIBFlAmTk6ZP3sOnAJ8KjBPVQlHCJluTxhVNmcZYAITahUwAI8RAFLYRNQDUJ0Xpll41loNSnfbCqJx2+NmBAweG+vQ2zBDDvw4QMJFlEWX6LMesqd+lJmEuBbKzapOiJMsF82btm5XgkjRdVYMU1QGsGhQNG9uvGUIV4HqgaKgk1HXdZmMoS0Mj5dLzsbGxGGPbGnwVNpD/rcIyA2PRcRPm24quKNSq6Ga6YNL4L6fNXKKYkm5gwEF+mudYilEghKeFAyHna/xpeGBS76gxELWXdNePomvvSE2/0oh+VDCG1i69J0JI1/UePXoQQuimIKhh70vVwEEwYCAWUT6eljxnRkk6DxlirfOiLs70CNrY0Z98NGWWgqtMZFgmaFJAcmJkAgJTxxZSCagWUaqlCgAcWkdhcl411JsUpeEU6AiT7gkLQakYurc8CQl6r6pq7969qScDNPit4xo6ghbdyVMXT5v0LbMYXAxkpNcyL8rry5eSqdPXTJw10wAvAp2A7UaPASygvkSgI5ARqCbo1AeQLlGiLtZhll4d1BtF7aVnmqbZW0Xg87f9IMGdSyAocnv16mUTm/50hUK//OahKqaJLANJ4ybMnzLhaz7lUhZdgdd5vnrqjPUTExJ0kCzABgLJD7IEsmISAIwBY7AANGwEXOlRYAxiBmHrPmHUL6wgzBDU57wovcWxY8e++OILm3hbt279/vvvqVClNl5KY7qvHt2N53/sVMK4KDAKSNGJHy9MmL4/2w2CA+bOqazVAZDVJ0/f9uaAEeu2frV+0+6Nmw8Wbz+zvfjMhg0l27ef2LL5xLaiU9uKD3+5bf+2nUe+2LSnskqq8Y9hKXo1UT8UpXs8A8CpU6cmTZrkcDioX+706dOHDBly5MgRGgKUEGJZltfrra6upm70hmHQjTcRQkYYlwVvlSSriqxVjRwze+LYHdwS8PC1jkV5DjgORo37+oln43oPndApbmT7yI+6dUvsGje/S9zMbl1md3hjSudOs2Jip8XEfxwV+/GjT7yxZ89hn89nGIYkSTi4AQ+dSwvjSkAPglKjHihqe8/TbHQ7xw8//FDTtIkTJy5ZsoTKWDopam/RN27cOFt+hp3pfxEIIIINJM1MYBbMOcQtASYZu8RaKMpCajJMn+7r1HVR7qrvly4/k5l+tiAP5WaoK5fpK5fpmS5lWbaVl+1fuVJbtkwZMFAoOVBGK6iGrT6MK416G4sihEIjdOq63qJFC6rryrK8fv36efPm2YtI9+/fHxkZ2adPnyZNmnTq1Kl169axsbGdOnXq1q1bdBgBxEZHR0fHREbHdIyOiYyO7hwdHRsVHR8V3SUquktUdHxUTHRUTHSnmOio6NhOMfFxXXv/u2XHN3v2fbZ51NTJu7LSwJlqpKRoPE9YnrACYnkIpSiTClOnSK07JmfknUjPrFqyqNTFWG6GCE45w2WlsZDrAd6pZWWR3FzcrVvKi//s1LNnz+7du7/xxhudO0fGxER16NAhJiYuOjo2Oir+XKKPHR0dHR0dFR0bHR17kc+Y6Ojo6KiY6OjozlExnaOjaQojOjo6OiYE9smoqKg6U5RG1qQqKz1jG2bpp67r5eXlrVu3BgDDMHbu3Dly5EgImZKpEbvI9tTFYWCMz20xqAL4qvwnCeiGCYYFCINFwAIwAAzAOmADQAdQMGgEZBNmL1g3a85ul9u3aPHZjEzgecTzhC55oRSlxwIH06adaNN+cVZ+uZhW5RINnqHsNUTBEDiSJgLnBJY1s/OMzjEJO7cf0RQdMMHIBPBlnRwAACAASURBVLCAmAQFPHsVX2AeVfYhbAK1BiMMJoFznzjkkwAi2AQLEcMEA4GOiIGxda3LvEGgHuZFQzlpW2LpAjR7E9GysrL58+c7HI4ZM2YUFxfPmzcvMTERguvU7JjXYYrWCgSAgVigqFUAPgLST6Unp89cMmtmxqRJ6RMmp42f4hw/ddFH0+d/ND3xo6lLxk7lR4wXR0zIGD9tZfNXRowevy5nqcxwFSmp1TyPLuQnz4EgwLTph9q0X5yV5xXTqkWXyTHAs8BxliAaPAduEVgnsCzKztM6x8zYXvy9IsnI0kxDBtARkk1DIQhrMja1AEWJBYqkypJPUX2Uiia+IJ3bgw2bYJlgmGGKhqAGRXGQpXWgKB3IAsChQ4dOnjy5d+9eukNhDaW3sLBw9+7dAFBaWrpz5066Fz0100Nwj/QwRWsFAmQCYNB11bQUAlZR0Z5X//X2uFFZkz5aM2H8mvETC8ZPyvtocs5Hk/I+mrhy7MTVoyfkD/8oZ/rcL5q/PGbqrO1ZuTLLexcknT2PotzlUjR22s7d32u6HxHJsKoAfBb2mshLIOBS5vepmkbD4OsAEoCMCEYYfiYRbKcwKEgI7JN1o6htJHj66acPHjz47LPPJiUlYYzLy8spwSorK+myMuN8vyJ6IQ4GRqmNoiQMQkjI1th+2Wch2LrtQGT7MWtX+TPdVZluf0ZaRYanLD39THp6eXqalOap9uScEDIOFnzqbdNh/qy5/+XESneawfNmQMs9X4TyPKkrRb/bf4qABaBjUAAkAhKASsD0er20fRAAABOBn4p9QggmQHAgogoGcv4nnPv1/J0srnPYRKOwWVoHiqqqSidX8vLyWrVqlZaW1qFDh9BYJ/aQlQTDiAEApSW9O/XIDVP0UsAAGJAJiFiS4rcQfPdd+Vvxc9euQG5GdTstF2O4GE1kNZHBvBN4hrgzKpawJRm5ZS++MmPG7H286MvJhfR0uKiWW2eKxsza9fUpWUO6YVXLkm5qPtUvq4pmEdMEWQNJwj7Z8MuSBRoB2SeX2W9BCAGCCJhADAIGEIOACbS2ERAc+AxTlCKUaxR1pqh9bJrmyZMndV3fs2cPzen1eqnPkKZpJBiBITQ/HYVSxtZG0TACIKCqOgEdga5ZZM+e0m7x8zL4yjQGuZ3gZsDFgIsBgQHBAQIDngyFEU4sXaG/1mpxwtwjvKC43cTpNOuFopExc0oOEoQAYTBMQARMBBYChAEh0HWgPyECCMAkwYiBAY9C6puvAqgAMoAacNinv2IAZNvGwjgPodStG0Wzs7PpODM2NnblypV79+61d3CB81erUG8mhBDNQC+n3gthil4aBLBFNAI+ApKOtS1bS7rGz1qRq7icqujAogMJTiQ4MecALhVYBzgZHyucXbEa2nVwTZt+KCXV53BoKUv0c/z8JRSNTnqq6YC46JlxMdM6th8X1Xl8xw5jOnUcHxczLT5mVmT7ybHR01q+/n67du91e3PU7LkCCgTOxkBsfkoAEoCPjlQBzHMLx8MUrR2XSVGEUE5OzpAhQ0aNGlVdXd2yZUsIWYxmBDfqtjdZoiQ0DMNedAa1K7phAAAEtkhSCXgReBGYX2zaE9Vp8qrleobLShchXYQ0F0lzQZoIbgHcInC8yvLe3Hxo09bz8ZRDDGM4naYj1awfikYtmTh+S7qrzOM6xaR+L7CHWMdBznnI4zqVnV7p4k56XKecqftzc49MmVrw7tBFuv6zFNWBWOdJ0TAuhsukKP2UJOn111+PjY0tLi6m3LP1WBKcmzEMg1qJbK0agmKW/tOFURd+gRr/m4KFTYtoCCSNVCHAO78+GhM19ZMVpptTXCxycbrAa4Kg8IIeYJ2gs5yUkwtvvJE9bdoJlwsEHjiW8BxcJNVOUZ5HosvkOWAcwDhAECA9S4rr4hr54bZ0UedSq9KEapGtFJgK3lmZxss56XhJUtniBSfdQoUn7fS8edsGDeZ0CywDkGkhy0CWhiwVIT9CfoSqTbMKQJXlCgDLMnWCMGDAVngsGsBF+VnnsWhpaSkEnRBkWaZBqyk/SXCtmSAInTp12rdvnyzLXbt27devn6qqtvuRYRimacqyTGMXURrbAbLDwDgQw1bDkgayBbBt5/GozrPT3ZUuTnexROB1gdd4UeIFLWCz5U2WU3Ny/jeK1j7pclGKxnZ1Dx++wyMAmyq5eV1gFN4pcw7ZzWGPAILTTHehnExT4Eunz9jWtz8vqUBQcKhJgkosAQBMsAWAMTIRnVYCwBYK17sNm5MUl+O6QHOoqpqVldWvX79Ro0YlJCRQ5RYhRFeiVVRUrF692jTNLl26jBw58vvvvz958uSkSZPsOVUK0zSHDh1qdx447KNrg4BpgoWDOwcS2FJU1v1NJl1UXSy4GBA4InAmL2i8oLM8sDzwPGJZ/TyKCsBxuJ4o6hoxYnuaGzFOSRRVjpM4VmEZReRxmgtcArhdliD4nOzpBYv2jhhboFtgWYAREAuwBcQ+RmBogX3ZaKvCQCoryzVN+ZkCue5RNylKadatW7eKigrDMGwvPwg609NZmUmTJu3fv3/69Ok//vjjf//739GjR9M8siyfPXs2Kyvrk08+ad68eXZ2tiiK+fn5ubm59DOMnNxl6ZmrsnLWujJy8lesSc9ZP2Vabof2Sctzg1ZcFnie8LzJ8+bFKHrc5QJBwByHz3n//TKKDh9Z5E6zGMYnujSel1lOYRlFFElqsu5wGByj86IkuM7OnLvz360nerK+W7Fi38oVe1YW7F1ZsG9lwf5g2peetjU3Z9snn+xcVrDBnb70P4Ub8wuWLytYeq2LvKEgLy8vLy/P/poTRN0cANeuXfvqq6++8sorUVFR1KhbI+YQIaSqqiovL2/69Olhil4GcnKXpWcVZOaucmVk56/4JD33synTcjq0T1qeAy4nCE4QGDqkRCxPWA5YesypObnwRrvMadOPulxYECyOs87z0Q1xM6o7Rbe60nWGq+bdCif4nbzEMBrvIqIALA8cZ7GiIqZVfDy76PGn+48av/ztXot6v53cu0dq7x7O3t353t2F3t2F3t35oe9k9Om5+J1BC98ZPOvJp1qwYnZmfn5aZkZO3s8Xy/WAeqAoXS64atUqeoauzw7NFhrm77333gsrupcBAqAjurmKYQE2ALYUnX7rTdbj0gUWBCZAM7rELEhRk+WUnFx4o13GtOlHXW5LEA2Oow5G57P0sij64ehtrnTTwfmFNJ0VFYbXnCziRXCnAS+Ak8WpjMy6vHMXHWjTaV7O8tLsrJ9yMipyMrw56VKOR8/xmDlpKMejL83WeOao23Vg6bIDLdv29WlgAOgkbM3/GdRN0a2urpZlee/evU2bNt28eXNqaqq96oUqulVVVb169ercufPOnTvD5qLLACIWAt0CSYVSDSoNwNt2Hu0cNdvj9gkcoWuyeR6xgs4KiAkoumbAotvOM236EZfbFESd47WaFA1OwNSZoqN2iOmQyml8GmYE5OSxgwVehMVLYEkqMBxwLmBEbcrs/f9qMzcj3+sSK9y8z81pbha5GXA7Ayk7DQSmyi2eXrnqp1dfH6QD+EzQABAOVz3G9WIuMgwDYwwA77777oABA3bt2hUXF0d/okZdHIxORBGedAlB6Fb2iICBwSTE9mINrAwhYGIwDJAMqEbgVaHKArz96+Odo6esWqW7eEXgEM8jnjdZwWQFxAjACCGTLu0806Yf+hmK1t2i++GoXWI6OFiDdwPLEycHTgZ4EbKzQXABw4CDwylOaeL0vf9us2jZauA4SXCaghMJDhAcIKQGkocHzqE6U05lZ5/89+uDDQKVim4Bpu67gO1PFJIuWoa/TYRKTvskrtOkC3UzoPxOTk6eNGnSyZMnISTqgr39mU280Hhids7rzXUh4G9DQFWJhYCAZUEFAgljQAQIYJ1Um8SLQCKgmlg1kWEigwDWEdZM2P3N6U6dx2dnn3SJZwVBof7xLE9YnjACYUSTF7QLpGgtiu7lWXRH7XB5MMNoght4njAcsE4QqHsDD243MLzh9mgJiUdeaTEvNx/xPOFZYHlgA88JbLCDEDjiTDm7PL/ixRd6IQI6Vk3iDboEUr9ee4NwK7BBeOjMjX18HcBmad0mXWzj0Gefffbtt9+WlpaSEJcGCkmSqHEIQla32KCK7nVFURNZhol0HSwLEAICFoIKBJKFACEaC143QUVgIgATgyRhXQdCABHQDSjefqZrt5k5OSfcQqkgSAKHeI4SABiBsMLFKCpYHGfwPApQ9HyW1p2ixWkexDCaywU8TziWsE5wicAywPPE7SYcr7o9ytzEw6+0SMzNJywPLAsMD4yAGNFkRJMRgOEDYR+cKRXL86soRS1cbZFyAD245sUK+iTZyTo3SwNhiv4PY1FJkrxe76RJkzweD8/zH3zwAZzPT1tg2gHHKAzDoMNRct356GICJgEL4eBm2IAReEsO7dv3nf+Hg3D4sHrwh7KS70t/OFL1w2Hl4EH5xDF08rh1/Ih+7Cj+9mu/J23Xm90WZmeVunmvwOs0uAk1FLE8sAI6X9FtKBSlz8aIJkMV8otSFMkWqQwGw7fJqYekEKJeT76CoQpwnV0XACA+Pp5GUejZsycEY8/jYNBqEmLgpZd4vV4qV2mw3OtrMRqYklpJQNcM3bRAN4iJLJ9WNuHjKf/+17tvvD4psv24N9p+0Kb1B+3ajm7fdlLbVuM7vDGm9esf/PP5Pq1bDYvsMKHdG1M6d1zw6Spw8YrAEYEBngGWBZYSlScNkaLB7oMJpPMoumxp9Ysv9EMYTGRYuBpAA2KcS/Rr8CQBO5kEzAsGqL8dXMhPOq6s80qXu+66KyoqKi4urmfPnp9//nloHttTt6qqigQXdkOIaLW/XlcUVYxyArKFdXswpWFpwKARaULJsiz5k+XyyqWVy3OqCvLVFXlkRY6xKt+7dqX3s9XeTRvNlUsrJoz7vNdbuW7e52JRYN7lPIpCQ6MoNU1dnKIccaZULcv3v/j8IITAtMDEKgkNmQJmkI32Z430m2XpRflZN4pSYw81EeHgTKZlWaqqhs55VlRUHDt2zB61FhcXnz17FoLhiy5B0Sts075GIAYBiYBEwKT81A3LIPq4j+YtnLtHXOLPFpV0QXIzchpjprPgYcHDVLuZM27mlEcsFZhTHwxd16Pb0iwPcQX52cClKDUX8RzQ+IOUogGjEU9SU6uW5cvPP/+uhUA3wbQuEkUFn0sYYwsTAxMdEx0TFRP9txrrKJSu9sm6TbrQA2o0orAtQ/bI89ixY0OGDBk3bty0adMwxsnJye+///7WrVvtqPM+n+96oyiArBkVBlJUXdMNq6LSe7aqctiw2XOmfZO6QPKw2M0ibonBLwExBcRU8LDY5ZQyXUqG6M/L0MeP2dGj66osT8ABkFKUGkiDY9EGZS5C1KBlUzRg1A1M4ZLU1Kplecrzzd+3LNAN0E0wUc2ELEAWIBRcLx6IdUSJ+psNR3ZRftaZopIkUauPx+MpLi6mK11s0J0gqqqqTNPs1KkTAPTp08fj8VBOws8FRrl2hXMlQQxEJMOqJmApmkoFqUnwsOFz588+wKfgnDTIdoOHAw8PGQJkCMAmW6kL/WmsLjj9+Vlk4kd74mOWpruIEAyEa89wsgJiBb3hUdQUWBA4wvMk4Kh4PkWX5mvNm48wTNB00AwwLNAsMCwwTDBMMIMJ0WSdI2pAov5GUYOil+O6AABUZZ01a1bXrl3PnDlD92Wp4aZbXV29ZcuWpKQkAEAIrV+/3uFw0J8URdmyZUttoa5jf5uIjo6JjIuP6tSpU0xM3Jtv9Xjt9VZv9+354P81nz97v5sBl5O4WJLhAoEFkQOeAcEBIoM9PBJZNSNNHzW8KD4mLzMDBA4J9uJs6kkvaLyg8ILS4CjKkSBFCR+kaFo6OBxaakr1igL86CMDunad/9I/B7RsObhVm/datvmgVesPW7Ue0ar1iDatRrRpNaJN6w9fazEoJnpEs2btO3Xu16nTW337vRPZKapLt67XukKvFOoh1DUNtylJUnp6esuWLbt27Tp//nzKQxwcmtI8Y8aMKS0tpXfcv3//iBEjIBgj2x6OXj8bRoRur0AAVNOQdP/k6Q5KUZHBAoc8buB5RFeocE7MMyRNQDynZqSpI0ZujY3Nycy0BF4XuCDleJMXdF5QeFFqUBTNy0d0XauLDbI0OIsruoEVUKrDl5dvPf/8BKdzL8/vWb78eJrnoNtzyO05kpZ2JC3tmMd9zOM+kuH+Pifzh/yc/e++s2DTpiOSPzBlJSvaJYr6NwbKzLpJUeqLizH2+Xxnz56l4TnpeWq29Xq9//znPxMSElq1arV3796FCxeOHz/eNE0qfjHGhmFcZ9suWYqka7KlyKYs6QRAx4ZP9XbvPWJ+wnduBkTGEng9zYNYUeFcKsdrLIs4lrgExPGyJ10ePmpLTFxWRpZB14gGiCfovKDxotTwKGq5OM3FogBFA4NSYHlIdVpiGjgZSRC9TzUdIwrH0tOOZmef5rgfGe4Uw/3EsaUcc5ZnSnnmJ4H5UWAPpbsPtGszasvmU9gCWQYCoKj6ta7QK45ftO3S+vXrX3jhhejo6DZt2jz99NPPPfccDf8HAH6/3zAMACguLl61ahUNhJ2fn28Ep17sm1x3mxcGg2iZBtFNAwG2wBw5bt68hO9cLPCsxQu6K91kRYlz+xlBdrKI47AoIk7wp6XLw0dtionPzMiiOm2QoraW2yAp6mZNN2Upe46iCxb6BTcWRD0tXX32mY/d7lKeO5aSfJgXqjhe5niV5zSe00RWFTnZxVU5ko9kZZzs2H7CjuIqgqCsTLmenIvOoc7hxYqLi7t06QIAiqLYg0xVVenmS6GEpNSFoJGJBF0Ir7MtgAkgoPudAAHN0P2azwL93Q+mzkv4zsUAzxCeR650xLgU1i07BdXJIobDvAsxgt+VIQ8bHUJRGsCaJ0GW6pSoDYqibk65KEVTnabgxgwrp2eaLzRPyM6SczL9OVkax2sMhxmOcCxwLPAMERnLxcqZ7ur8nPIusbO3bStDGFCgCC2EfqtNpT62AMYY67qemJiYkJCwaNGiN998k/5qz4vSA1VVKffOnDkT2h+goMBUVbV37972fk3oty1IaTQ8AgBAAKuWbIL2zgdT5iXsFxjgGGB5ED3AiDrj1h2i5uAwwxHehRhBdmXIw0ZtiYnPDCi69h4Q5xuNGhpF01jdzZoulriC9i2WB1caCG68JMXrSlP/9rcZrKPCkfwTk+oVReAF4AXgeRB5EHlw8ZAmoJwMbXl+dfdu8zduPEYpqluyrFVdP56AdR6L2g6Asix/9dVXxcXFEFykBgCKotjBjSjxbClKxSYduFJpqet6jx49CCH2luxX8cWvOjAAAozAsixEDA1LFugfjE6YN/t7gQHOCSwHYhowAmFc2CFgBwtO3qaoOmzU1qj4LE+WFRChdMlIMEiKwDYs76K8fCuNky5KUZYnghs7GSkjEz//fKLLpbCOqpQl1SwPDAcMBywbmPIVWHBxJu8sX5pb0TV+1lebjtNQ2gRkAjKA9bNF/tvA5ZiL6MQmVWjtYJyh7K3xBxCyXJueLC8vp4SMjY3FGNvxdenfXQsgQlCIW1nQYRsD4AuXL4YuYgRi70qCa1vKCIQACdqtEegmViXdp2Jl8LBp8xIOBKQoBy43MDywIqYLphkOeBdhBPVnKMo0RIpeqOhSijIcFtOIw+l3ufXnnpuXnm6Ioux0SAwLDAMMA/SAY4BjgGdxultbtVLp0HHC5i3HEIBqaQRU3aomYF6ttnFt8IvmRSEoEinlQvdroXS1l57RA13XqcYbSkXq/EBd8EP3Dr6q88Q2iIFARSDTOfFza6EswDrdeMTUDR+ATuwt+bCFMWAEGAG2ggkFN3ogCCHTMAxV1U2DIAssyzItBUAycIWsVZlgWACD3puWtGCvSzQ5znAwFi+AkwPWZbAuw8kCx4AoEo5X09LV4RcquqEBrBucAyASeJ0GiDg3i8sBz4EoAsuaDqeUlw9PNp3q9ihOtlx0Ged5YoSsL3Wk+pculdt3nLC56JhfwxrSCWBC0LVpJ1ce9UBRRVHomQMHDnTv3r1du3afffYZ/VXXddvTqKysbNu2bXScuW/fvi+++IKacCGo+lImx8fHk+Buazbtr0XBGAj8CPyYGBgHV0QZAHQ/PsskWAcwNd1vIs0kmG5bQgADCYacDAaexBgIWJjoBHQA097dhGDQTYOAbIIfAbYAJBP6DpqetGCvSzR4TmMYixeAYYF1GZxosAylKJxPUY0XNJ43z4VQCAxHG9piNHTuIc9PolCDopKTLRddWmBtAI94QWMFk+UJdT8Weez2lHeInFi060cLAAEmBEzzt0xR+zjUhlQ3KUrXl7388svUOzcmJqa8vNx20PV6vcePH580adK4ceMWLlyYn58/a9asGTNmLF261DAMjDE1VRFCDMN499136dPANTYX0d0Z1MAIh+5iQFuEjnRZocYJqsrSERECE4FMwESAaVhqAoDA0kwvAkk1yyyoJiBZIOmWX9NNgsE0gNC7EtAtUEyYMDk7af4hl0B4FjNOwvPAMMCJmBMt1hmmKLAcuEVIS6/o/vb8r7YdohVy7RrJtUTdgnRKkkQIcbvdc+bMWbBgwfDhw+mv1J8h9L4DBw4cN27cmTNnDh48OGLECHtfiaqqqgULFvA8/9BDDyUlJc2aNSs5OXnRokXJyckJ1wazZs+dOnvu1ISEWQkJc+fNSpw3K3H+zMT5M+fzDo53MosXpkz5eHbifD4xMXN+4tJZs9OTkl1JS9ikZFfS4vSkRVlJi7KSFmcmJbsYIWvKzASHIDgEwcG7U1j3wiWupIWZCxesXrjg0+TkZYlJWUlJK6fPzE91bnjlXyMWzDvh4oFngHEAzwHDACcAJ+IwRSlFnama4CqN7Dx51EdJi1LZ2fMTZs+eM3nylGvUTq445s6dOycI++Ts2bMvZ/PCioqKzZs3b9iwgYTEDUMIUZvtyZMnd+/enZmZmZCQcODAgWPHjk2aNAmCQ1ZN0zZs2LBz587IyMiNGzeuWbNm06ZNX3755aZNm4qvDbYVbd9StH1LcXFxcfGOndt27dy2a+e2HTu37di2afO2r7YuWsD866XIcWNTR40Uxo3OGz1q2dgxBWPHrBg7es3YUWvHjlo/dtT6saM+Gzv6kzGjC+67r+O4cXkjRmQMH549auSyMaNWj/xw9cTR6z8auXriuPxxY7LHj13x/ntZM2ase/aZ4QvmlLu4CygqQJiilKKOFNWTUfl2rwXJzuUbNxdtLt6ye/c3O3fuvkbt5IpjexD2maKioqKiojpPusiy3LZtW7/f7/V6k5OTIWTFNj0wDGPUqFEA0K9fv/Ly8oqKimHDhvl8PnL+7sDvvfdeDYFefyaxuiFgkbX36kLUlovoxiRFW/fGRr23PL8kK/NITkZFRlq1m/e6eMnNaS6O2i2Rm9VdvLJiKTz+2KhVBSgzo9ojVmek6dkeki5YOS5TSCl1s8c9rhPZ6ZUccyIn+8y/W8xdkFDtYoELU7QWigocElylXbrNLvxyv45BQ7plYcvCP1efv1aEUiB0jHo5UpTjuBdeeKFfv34PPvigaZp0XIox1nVdkqQXX3xx2rRpL7300n/+85/x48ePHDly6dKl9EKazTRNRVGoixIOCd55lUblFwFgDAQBQQAIA7IAGYAMTVEtHTYWfhsbPTo364hHLE0XdTZV8YjYLYJHALcAHh7cAngEcIuwLBcef3zSsjxwu1WBUQTO5FKtlCQjLw3YxVoa58t0+7PceprgX56vvvh8woIEv01RkQMurOieT9G8HMhbqsTGz9j93zN0LIoQ0bTrZTEavrz1onQTbkmSHn300UOHDjkcDuq3YM+pGIZx/Pjxb7/9dv/+/Yqi7Nu3r6SkBM6fXKEeSDSObmi4hmsGUiNZACbdAxNbsPmrgwP7JaWJx9IEf046uDjgGMSyJufELHU8YIBjEMupoqj+vfmc9AxFdEtpaUZGBogcOJdAJg+pC5CHtdyc5lwss6nSp6uh5b9T58/xuzjgOMwwlsgDFzYXXTAWzV+mdoicuHXHMdnABjF/vip/i6gDRTHGNFJu3759+/Xrd+rUqTZt2kBQv0UI0SlQOsWiqio9r+u6LMsk6OILDTCObu0UJQi2bfsxLmZaXo7PzRsiC6wDeEFnXT5eUBhB5XjNySss73UKFZ7M6r/8bUzOUp9DPCW4K1PYs+40QxBASAXRAek88A4jjQfeqeVmGy3+vXj+nCoXDxyvMawsisCxRBANITzpEjLpkp3r7xT1cdGuH82gRfc3vWzxPNhCtc6KLpWHo0ePfvvtt3/44QfKw9Cc9iwoFdYX/vevg6JAdW/YtvVkTMzMvGy/yGOBBdYBrIBYUWFFjeE1hjecvOLkfU6hwp1V/Ze/jclaJjmE05zbm8JUiWlI4IFLBd4BHh5Yp5XGAes0snP0Fv9eNH9uuUsATvAzXJUoIo6zBFEPUzRMUYrLoSiVgZIkaZpWVVWlaRp1V7DVaFVV7SCAVIPVNK1G+D/4VVHUwrB126no2Jm5OQGKOh3BuF5cwG3NyYCTBSdnujPwX56alpUHDk7mRJziQKIIHAesAzgnuAVgGMPFA8MYWbn6q68lzZt/RhQRJ1QxXIXoMsMUDVPURqgZ6XLMRX6/v23btm+//faTTz5Z49aWZdk+gPYltiylZxpakE7ANRICYhKCgFCKnoyOnZ6d6xNEg+OCFGWBDXqWOp2UpdidDn95alZWHjhYjRMgJRVEATgWWAdwDLhcwDCGKFCKqq++ljhv/k+iy+TESoYvF0XEcVgQLEEIm4t+hqLXqp1caVzIT6qH1pmip0+fjo2NpccFBQUAUFlZSQiRZdkWoTZdQw8wxjRDg6MoNeYSdI6lBBFCKEU3W06UwwAAIABJREFUF52MipuWlV/JuWRWAAdzbocS6vDNMsCyJsupngzjr09NycnDDFctCJYj1XSLILDgdALDgeDGDlbjRXCwF1CUqxBFwrEg8CDw4UmX65qi9lfbrlvnzQsBYNCgQS1atOjcufPrr78OIVZZat01TXPPnj30zKFDh7766qt9+/ZRltq7MDWkCIAWwQbBBsEWwRYNNUcQxhgIUIr+GBU3JSu/jE3zMi7sYIHlA22OLkFmWcRyKsv7PJnyX5+ekJOvM1yFIOoOh+YWQeDAyQDDEcFthVCUKro/iS6TE6oYrloUgGNA4EDgwhT9GYpeo3ZyxRFKV/tknSddZFm2LKtjx46UrhkZGZSWXq8XYwwA5eXleXl5LVq0oLxNTU2dMWPGrl27QrXfhkdRnWAdkAHIAoTBAoIAIyAETAybin/sFD85a+lPrKecceupPOJ5Etjqk8U8izlG5ziJ4yvTM6ubPj02N19luXJRVJ2pShqlKAtOHgtuy8EqvAgOxsrINV55bVFwLOpnWNnFAe8AkQGRCSjGYYpetxS1z9R5XtR2dnc4HE899dSYMWPuvPPOGpotpWJ8fLxlWZqmjR49OjExkYpQagqWZbmhURSTgBQNRGulFMUBim4u+jEqfnJ2/k9cWjnr0h1ckKIcqUnRDH9tFGU4HKroZuRar7y2OEBRXmZYJUzRulAUMMYEhX7ic5/Ywtg690mMcwlbF6QGhBoUvfz1ooSQH3744YsvvhBFcdCgQThoCrIjl2GMu3btCgB+v1/TtOLi4sTERCpsCSHffPNNw4ujGx0bGx0bGxsXcy7FxsZ2jIxp265Lm7b9urw5Mye3NCtbT0nR8peea3M1Fd0M5aKKLusEjg2ai0TEsEpWDn7130vmzT8lugxK0bCie1HXhZw8qdtbc9p3HtAhKq5L967x8V2jomLiYuLjYuK7RHcN+YyPi4ntEhMbFxvdJaZzXGynLrGd4uI6dontGBfXPiR1DKTYTnGxneJiO8fFRsfFRgcrPZ6ma9UK6yGOrqZpPM+fPn26ZcuWGRkZw4YNo1H8bNciKiorKyv79etnBLf0/vrrr8eOHQsACCE7mH2DiqN7Xly5wJfAUk9EYMeO0716J7pdJzMzLY8LkhdhmyQcAxwLLINZVmc5yZOh/fXpSTn5JsNVCaLucBjnUVQEhjFEl8mw/qxsePXfqfMST4huheNVhlVEkXAsEfgwRc9RlHUaqc4f3+oxb1PRYepdJMtqoI7wxVJgzqzGPqX6xXZDNM9tMUxT6KxbgwFlZh0oSoeXLpcLIUQIkSRpwIAB1dXV1AikKArVcj/77LOXX3759OnTq1atmjRpUkJCAgDQGVS6zruhxdHVTUM3DcOwDMMydcPUDdPQDMPw+1SfBEVFJ9p3GLc03+tyKZkecKZCmKJXh6I5WZCZXd05esqOb05RRbe62i/LaqCOAskydcvUce3JMnWr9srXLpauMX5RHN2Kigqv1xsZGdm9e/fY2NjNmzdDiP8tCm4uun//fgDAGO/du9fr9VIxS72ONE1raHF0LyFFDQuKik50jBy/5lMjKel08kKNdYYpepUoyjj0ZQV6VMzUDZsO+DUrZEk3vrj0u6hoPU/AXlRU0hxWSGpY7hF1W9JN6XT06FFKS8o3O3aRHRulsrISIWRHALTh9XoRQg0tjq6FkYURQgQhgi2ELYSRiRAyDYIIbNly7PWWH+bnVfG8n2dA5MMUvXqL0bJz/bHxM7buOGYBlFdXAIBpmhjpwWRiZGIL0fkybAaTcV5C5vnJsndeIwghhEyETIR1hLVAunZxen9pHF2E0IQJE/r16zd58uQZM2YMHz78o48+or+ePn3azhy6C1PoMNWOnwINLI5ubVLUMgER+Oabs127zVy7xszJITwTVnSvqkU3Lb0iKmbq5uIjFoCk27HscK0jSVtsopBUm0QNwJai9jC1oUjROo9FTdNct27d2rVrT548OXXq1EGDBp04cQJjbM954uD0Ce0G/H4/DgmoS3koyzJqYHF0L6HoKhps2HCwfYdxuTkVKSnljiWWWwxT9OrFLsrJk6JjpxV+ud+OXeTz0U7/oupsSA2GMpZcRM8NSbZPmUXTr5iiGGPDMACAYZgNGzbY5+kBnfCkxzQbAJimSVXiUJstalhxdM9FXSAELnQA3Lnzp/YdxuXnVTGM1y2AIyVM0atEUZ610jOromKm7vz2tL2kG58LWUxbcDAMMhgEjGA85PNiHQdDHV+4G3jo+XPH16YVhuAXzYt++eWXUVFRrVu3njt37ogRI+666y7KQ8pJEvRAok5ItkduqLpL6arreq9evXRdpxfad7gmuPSky9atx+O7TM9IP5OZabl4ELgwRa8SRTnGZLhTcV1mfrn1BwtAxwYA6Bq6QFOlOqpqIh+ASkBR9UqEFTrF4pcqDSQRUC2iENB1y68afgImASsoPGs3JF1rUGbWgaKGYRQUFKxfv/7HH38sKSkpKSlhWZaOMEOjXUOIxgvnS1QqP2m4wLfffhuCFl16/ir3VTZqk6KmQSqqrM8/PxAXP23lCplhvKyDpLnCFL1KFE1Pg+UrjDe7/3/23jtYqiPLG9zYjf1n/tpvY3e/6Jn55tv4ZqKnp6eNWqa7ZYBuCSO89/b5hzcChDASIC/Mg/fKXH/LVz3Dc/BwQggEMnS3kKElIQkQAh7Plr8282ae/SOrLoXr6e4B9RcbyrhRUXUrb94055fn5MmT57z25onPTacg6Bo6uhEBgJnUA6JgUtABNADNoVkADcCgYAIgChYiOUzzFs5QsChYiBg2NjK55A3mefNJpztFFfguUiks6V9tRt/d3c3gxPZIbz/aksvlrly58vzzz2ezWcMwFi5cOHPmTHexCiXnvGfOnAklcvLfMP0JLoocOHOme8TItYl40udLBWT4ftPluxR01eDg2PFbXEGXUgBaIugWhgtTQMwZMuOWBGwK2KEYE4etNh3ADmDnRggBiihxblYqOUWXyP+TJBerf815UVdwdR0ssMQY5qlTpx5++GEAqKqq6unp6enp2bBhg6sQco/FLF26lOmX2U/H+Zt5GXcocSgpOhkj1GF2ngQjsBCcOdM9YeKWfS05SdIkHur30O8h+p1tuoSjmanTX/7gw6vMAyBCDtCbF5SUOBQ71HbAIoCY4GqY2HFucFrTBt0Eh4KJwESQ0x1EwAEW/AMQvfVy6H9EMfcn3cI//5q1qBugpTQxuLqKIuYOm3n3W758+SeffPLRRx9t2bIFikb23d3dkiRFo9GHH35YlmWv16soiiRJiUQi+DdKgVAwEAoGg+FgMBwKBEOBYCioBoPBWLQpEGp75ZXQhIlb9ndafn96x2vZ7/dFvzOI7t6ZDkczI5/esH7TXp+o8oqQSDT5fFwgGA4Ew2zUAiE1EFIDoWAgGO7oPFhXxzcmDgtcuyq9GVZPB8X3I8rvYpHfh0LvtbZ+HI6cisbeUYNHm/e94xea5eA+OdgkhxJyKCqHw3JYlcOqElYDob8NHYZKUoEyA4FAIPCXcdFsNsv4YSkDZPhkHJX9O2XKFEJIbW2tYRgXLlzYuHEju9/X13f9+vXm5ub29vYhQ4Y0NjaGw+G2trbGxsaurq62v1FqbW9rbW9ra+toa+tob21rb21rb9vX1tYWDsVjia5XXw2PHrOhqTEtSdqeXcb3EP0uN12a91nTZrzyRl10X+fBYCzU2XkgFou1tu9rbd/X2t7c2t7c2r6vtb2tta2jtfUgz8Ue+Nnw1ct3L62uW1mrVC8Qquapqxbvq1oUWDDHW10hVSzyLqn1L1r4enX1a//43x5t3vdOc+tbzW2Hm9v3N3fsa+5sat6faOloam3f9zehw/ZiKpBlSfpzIUqLR8ZukWxdN0W0aCQ4duxYAFiyZMlHH3309ddfP/PMM1BiJ8iyVVRUwN/aaIGlP63RPXu2f8rUbYl4MhJxAjJ46r+H6HdnAMgJ3RMnb2PWRVkj5zgUCioCywHkAHIAF5aRFAYHYdTI2raWr6Pq143BfsXbG/RnErIdV/WwmIoHUolQf3OsN6Se72i7/MQT5dgpbINiAAwYg4Eh74BG/+eIX/rXrEVdYz2XhbpwTaVSUAxYeODAgYkTJ/7ud78DgCVLlsycOZNZNjFrJijKxiNGjAAA9hcr5M8W2v/0kb/SU793OC5YWG06hBZPFbpPUQfc+5RgQsC24fTpS08+tToW7eP5dDgAsvg9RO8pRBW90ByBCkIheCHzOxOUnUgoOXbcxg9+960DQItmQIRaDhgs5KQDhkNtRAE5kM/Dww/N7ersk/0XA9yAyulRGYR6U/ZaKmcGBTMgZETfdW/9F0cPZX71y0U2AtsBRAABRmAgyCHIOaCVEBXc5bqFDu9Nugdr0b9iJij1ZE0pzefzDN6O48yfPx9u3p7589INi2fsmMwKrFRnXcITCQWbgk4hT2mOUg0A2ZYGFBzLZp7+CNKZv9ybrcNI8bASIQROn74wcfLGRKJXVrKyALz/e4jeW4jmOdG6EVbUD4IfRD/IfpD92bbG9ISxGz9493LhODfb7WRaIDAA8gBpgCwFywHoG4THh5bta70mid+oSkoQcpxfl0VHEm2eM0TBUgRLlfK872pz0/VHHl6AHMAUCCAKBtunAcA3qXTvZpF0gw7R/TO7/09pdP/MRAixLAshVBrD2zUU/qsgers5JcbYpsU42MimpuEUYn4W5l0LwAAwAJCu5YCCkTWpDYBBy6SBWtjUChC9YcxJgGI2WgWITtqciPfJcv57iN5ziApqlpN0v4Q4ATgOBB+IPpB9oPip6k+2NyYnjdlwpghRcPIAVmGwKALQXIhigL4BeGxo5b59fbzYLct5XjC9nC3IlJeIj0eCQEWRqKLN+XuaG/sfemQBdgADUDAB8gAaALphwVsg+ttMf+8A0ftl0/tdQNR9hHFt9z5zjFIK0T+78FsgiikgQjClTuEYHAWg4GBAGBwHEClshyEMGAEQyKQcI1dEIwUtO2hb2l3PLhEgDpw+dWXipK2JWFqWbJkH3leEx/cQvf8QbUsM3AxRHQAVpCiHyTss2jJggL5+eOyJ5ftacryQlEWH58DrA0EEXgQfRwQeRAFU0eF8/c2J5EMPl2MMmAITtQAsAHxj9O9o8fsdclFaku4vFy39WRpArdR3kQtRetd0d4NMQEzQJQSAAkbQ26s5DJbsIoAwIAwIAbbA0oFisA3IpoltFaZHdwPtBiMtYpg4cPrU1YkTtyVi2e8h+l1A1F+EKOfI3GBr48D4Mc++f/obNhwONoA4pdCg1CFAMQVEoKcPHnv8mZYWg+cL8o7XC4IAvAA+PwgciDyoAnDeVHMi/dBDVQgBIkCpQ8EEagOQIkSdoq0vpRRuMmYipbZHTmEnld4bs97b8ckWpfcRooZhEEJcKZeWHIJBCJW6F2Ng/ksgysCJ3bUom97Ofnhu08ad1dVvVFY1VFTtrqjaWVG1s7JiR2XFrsqKuuqK+kXz35g3Z/vq5bsXLVhLKWRzGgVSakxWeB9hby3hovGkLJsFQfd7iN5LiOY5yfSLzk0Q9YPCIcnf19rYN37Ms++f/pZBFGMbCL3BRQlQStkRFeTcBlEfeD0g8MDz4POB4AeRB5UHzpNrjucfemgxsgEx72RgA0VAaHFqdm42yqc3gEpvhuhNJvv/2XRHfN5fiJKSwITuF0qpbdsIoblz51JK2ZFRlvPuuq47a2hdGcMVcQ8fenvs6IV1e07s3H1m5+73d+5+f+eu93buem/nzt/tfOP3O17/XTh4ec+u06+83LH9xdDcBasxQM9APwIbgYXAcqjtFAt3KKYAmMCpdy8V1qJKVpK+X4veB3WRZPpFyvEFiApMV8Qjyd/X3Ng7buyzp09dYQjBmFBa8EzEfP85lCAKNgHTgZ5+eOyJlS0FQZfe4KIuRDkG0TyDqG0VIEqoVYAoBnCAEptQg1CLUKu4EUC+S40u/c/40f1LU09Pz7vvvsuid7uWSS5ECSFMu/sfQdRNt0C0cEoQY2IaDrLh7bc+mDVrTSh0SQ0OKIF+JdCvKv2qMqjKmYCUEXz9e3Zd4LwXwqEL0fjHo8fXMpTbYNiQs0FDoKGCNt9yqE0BMIVT7341Ycqz8cYrstovySbPf+9e7P5odG+FqCX6epsb+8eO3nD6VLdDgDhg20UrW0IIwWxKRZTYFEwCPQPw2JDallamLtJ5Hvt9VGKCrq8o6Ba4aPahh2psG2wHCMGEGpRYQJ0CZy5A1CiB6HfhzvOO+LzvEA0EAosWLWKHS11dLvOh9JdDFN8CUds2M5lMPq/rmo1scBC89eYHU6eskeTLvJjhxQwnZHk+z3M65zMFnylxdkhxOE9vLNpXt/f0xKnrdQyDumMCNsEwwbbBtgEjShAliIIDgCicfPfShCkb4o1XZLVPUnSexwWK/x6i9w2iIgcybwn+3ubEwNjRm06d6kMYsAOmVfBGzqxz2UjZjIsSuD4Ajw2pbmm7LkrfyEqGFwy/H0tMXcTWokLJWvThSgZRh1gENEoNoKgIUVxkodbNDnjvb7oFot/FvqhlWeXl5R6PB0pUR4ZhUEpzuVxlZaWbs3RX5u7pzm6gKIF8zkonLSBw5NC7FWWvBMMpSaW8hP2CzXGI56jIgyxASAWRpw11ybrdFyKxq9NmvZzWwaCFPRkDwCRgErCdwqUZYJjw5ltXFyzaG4leV9R0PAF76o3vuej9gCgzVyiBKArK2cbEYEUF/977eRsDwjAwCBgXFYHFy3bAxmBiuNYLk6dtk5QveP6bxiZHFMz6ekNVgBMoL4IsAc8TmUcCN9jSOPjAL+Y7BBwAAFTcFL2x6WIjHQCbVt608gBYN7Ilfli+63R/uSgAHD169IUXXmDfLcs6efLkpEmTamtr/+7v/m7MmDFTp04dOnTo3Llzx48fP/Y/SKPHjh09dtyowjV29LRp00aMGDV50ozqquVjR8948jcTRo+cuaS2LhjSJAV4Efw8ZYEARR4kHvwNEFSgKQrhgFlff/5/+d8emzb7xZ8+NP1Xv5n/6G/mPzps4WNDyx4bWvn4kMohT1QOeaLy178qG/abFUOHrZswsa69EwRR9zTY0vfnRe83RDkQORB55G3oaW3RR47c/sQTq4aPeObJp1aOHPXMk79dPGTo/CFD5w0dMm/I0PlDhix8fGjZ40MqHhtSPXb8lp8/WHP8bWhouLhjx7eREDQ1gtfjcKLDS1iWgedtmTcFvq+lqe+BX8x/evSCp8dNHDtu5Njxvxk37slxY0dNGD1x3OhJo0eNmTx58syZM8eOHTt16uTJkydOmDBu3LgxBQq8KY0fO3b8mLuku9Hxn87v/hxdTPcXorZtf/LJJ1u3boUSRmpZlmEYa9euZTG/WXIteO+USrcsS/1KASFg6BgVl6UH95+eMW1zMKRLMoMo3ICoAJwHeC8IXsffkJWl/gcfWtvW2ROMfxlu+jbc2B1J9MTivfFYfzzWn4j2J6K9jbG+oHJ1xbJDM6bFBd5sqEcNeyAc/l6je48hKoiWu3Yohahnb29Toz53nrxyZbOsfCFKf4wnLgfU84n45UT8clPs20T8aiLWnYh1J2I98XjPzh0fPvzwxkQ8L4gpVaYiB4IXFAk4EfGyJSuYF0xZ0AW+h0G0yEVxwQU2LXFHRgHZkMsacOPo5Z38JN3P5Mq99xGiR48eVVV1/fr1zHbXKfE9r2nalClToGghyFw33N33b4kbYqTbSGffLQthBJZJtBzJZSjF0NX57sJ5rwaDZhGilPMTRvqSAJ491N8Aoo/wXk2Vsw88sLGxqZ+TLvj46x5+wMcl/f4078sK3qzgS4reAd/e7njY3Lrlj9MmtUoChIMgS7B3z/cQvZ8Q5VyIOrGwIwr9v/3tjrVrjzY1JgX+Iue/KIvXRP9V0Xdd9PWKvn7ROyD4BgRfv+Dv9fuuPf7Ya03NRJIMSYCGOrJ3J/g9IAgOLxslEO1raRp44BcLTRNMGxByELKw7WALiA7YAGyCoUEuU3AsaFtE111X7Le4w8a2ja17lFiJt/i5/otdXf9F6csvvzx8+DAU+afrqcgwDMdxli1bZhiGruvMn/3twbxL0l25qIPBtorGBg50tJ6qWLQjHDAVGUQBeB7zfkvgbEkgsghhBUISKDz4GzTRl/nZv29uSuRlqVdQbEECQQJJBFkAVYCAQAMCkjlN5nLPrf9o9IiwIkH9HiII4P9+X/TeQ9QUBOc2iFJZshsbYew46blNH/DcdUkckIRkLIwCohkQUECgAR4Kl+Coor1l4ycPP/hKyz7guBznswU/SH6QeAZRS5YJz9sybwncYEtj5oEHqpENCAPBLOYzUBvABGoCIAAHqEtlFJBNMSY3U+N3l+77WlTXdYyx60SXTQyWZS1atGhwcJAUvQpalnX3TV3nxlViz2HbmM1zWg6S/RiZcKD9/UXz3wgHdUUGUSS8YPJ8XhA0STJkCfnrDZmjIRlCCsRD8PADr8YjesPebo/favCBxwseL/g84G8A3oMFjyH6coI3/fymT8ePj8ZjsGeP5vXB7jr7+7XodwFRDl5/7XokQidMiLz40hcil1Yl3d+QDUhE8FhCAxbqwb14D+a9WjyCf/3L1xU1ywvJSBgkAQQfREIgCO5alMicI/hzLQn9gZ8vTSchnYZcGnJpyKcgPwh6P+QHoP8qaBlwLDA16L2uGRoAhUxau8l+ppCA0rvuRNzNn/Wf1uje/vj9hSg7pAZFwZotOFlRzL2YYRiapv1H7v/urMsFAOIAKuGizfHjUyZujgR0VQZJwIKg8XxaEFOKlFElPaw4IYnKfuzfm5e8+gP/9kpLjCqiJirAKyDIIEogi6CIEBAhIFsBKRsL557fcmbMOL8kJ0U5F4xSUSHfb7rcd4gypa5IgwEycmRgw4ZPZcn2ew2fx1YlCLABEiAgMBZaGK/XX/1qyBOvtXXaXv+3Pn+fIGgChz0eSxCcgkaXA5kDwae3xPEDP1316CM1j/56zhO/nvrErycP+eXMIY8sGPZgzZCHqob+cv6wx+b8+uGJv3xw9G+HTixftNwyS48U//+Ii7IlqOtyvvT8t+M4EydOJDcfc7kbDy36qUHFq+D4VDcQBaAULAu0PFACRw79YcHcV8JBXZVAEojAMy6akyRNlUyJMyTO5L2GZ09W8Gg///Fr+xKgiraPc7wceDnw+YHzAecnvB+Jft3vGRCF/nVrTyxY1BxNmJKaaeAG/aIhFNWPBYhyzg2I/tvmWIL4uZwoYq8H3YCon0EUS5Lj57QbEJVNXjD8flOSgOduDl4oAs/bagCtXP3exMmRUMQWRF0Q0C3LNoGHEoiGtm67KCtYFDHP4wI+S3HCMYiSrdu+fmpkQySuSYouSU4RolSSqMCD30f9XhBFEozok6YGVq05owZIAaI88BxwPpBF4Pwg8KAowAuGEjBLIOrcWsPbIfqv25SA6eOSknKHRjEu2rDXiIZh5owD69Z+GgmBJBBZAM9exPuA94HoBd4Lohd4H4h+i+fzqpwZMuyNaDy3t+GyIKZk2RR5x+9zBB54EWQWHpIDwWs3x+nPf7qhrbW/o/VqZ9ulzrZLB/ZdPdDSe6ApfaAp2xbrbm++2pL4qrP9fEg9XlH2LKVgWoWIs7fZBjqYmoWLWJggTBzsUHZ4446Xg28PWuE4Dio1VyrepBjfTwNAlhg+S30FGoaBMWYeAB3HcTdF7ywtUILB0ZHmum/L6hpTvFkYHADDBoeCQ8G0YV/b8bnzXwoquiKBLIIsgSSCJIEkgSxS3o9kkYYC4PPoe/ekHnvUHwpS3m9JIggiCCJIQvEqjKgl8Ma6dR9NnNQUjlBJNkXJ8PkMWbyRTRRAFIko2YKoKwHzZz9/neN1RaGqAnt225IAqgSCH3g/+L2gKiCKxM/pioqHDuN37LwuSpasYI5D7I0CB7IAvgaQRQgo4PNiUcRrnvlo8pQWJWBKsinJSJKoJIJUUltZJj5/PhKF4SNCm7d81dCQ5zgUDsMt2dyL46ztL14cMUoJBDHHWaoCAgfeBhA4CCigKsD5SUOD2eDJyqo2aUr8mbUfqypIEgg8BBTwe0ESChQfUIHjHI831+Ad3L3n6mNDdkZi+A4vFUEq7Exiv9+MxuCf/vumRCOEwqS+IS1JxaqKN+UXeJAkmDChfdWqT8NhkGXgOMfvcwqt5kESQBZAkqgsIUk2X3/92wcefDUaA1GyfD7L02CHg6DKIHCFWY/nQJFBEnAsBv/8L88K4oAk9rElrsRnJM6QOFv2kZgKfIPpqevbvfMzjjs7bcZmzEAJtgMagRyBHKUaJRYzcnAgPWhcwpDFoA3mBxDQKz0DBoJkliQzcMuVyoBpQCZZUB0TB2ybSYW4FPyEEEIKMG5qaiFFIx+E0KJFi+4lRPP5vGv3526rkBInnaUBYO6YKICODMOxMJCUlsvbpuE4GCCtWXmLYgDdBt0GmwAGaO08PnP2CxKf4XzAe4HzAecBvxc4L/V5scARQXD8XqO+PhdQyYMP7WlrBZ/P8HsKS9Abnx7i82KRp5JEn133+YQJrQGVcLyhyEiSKOcBvwc4D+M2yOczfN6c15eJRuFH//ZyYxxkGRr22LwfFAH8HvDXgyyA6AfODw17DZ63E3EYMTLw6qvf+vx53m/V1xucl/q94N0LnBe4BvB7QOJA4CEUgNWrP5kyuTUWB78/6/Pn/V7D50N+D3Fr6/OYHK83N8HIUZEXtlwSBCTyjiBQvwf7vOT21omCtW37hadHReJxEPzU5yW++sLKrUD0IqgyDQRJOEwmTGxcsfz3PI85H/Z6kMRD/R7CeYDzgegH3g+eepPjDUHQdtVdeezxHS2t4PfgO/anwBGPx1Bl2tQEP/3JG7KCJdHy+81Cfg/xeUnxE/u8WOIhEICpkw+uXHlOFqnPZ4m8EwyAvwF8DeB/LvdPAAAgAElEQVRvAJ+XsP73+/I+f3b37t5Hflkfi4AkgchB/R4i86CIIPrAz/bbeBB56vFoiTg8+NAuQdB4wRA4m+cJm0YFHwhe8NRBSIFwEAJKdu/ej6bOeCGjQ84kBtYNJ2PjlI1TCOWQrTuWbdu2jvI2oN5sauLMOQ8/NvKhX4/72YPjf/Hw9CHDqocMqx0ydEnhGlY7ZFj1sGEVw56Y+6uHxjXG3tRy4GAwDQxALFsrCXxa8MvDrra2Dua1j+2JVFZW3hcuymKiEUKYFpcQwrwEsk0n15n9naRciihJaTl3GYpuXpXqNhgIbAKIQFvnyWUrPEFFV0UIiqCKEBBAEUHlQRaAa7AlgTTUZfbsTkeD8M//Y+uBdqjfk1V5kHm48SkUPhUeeD9as+Kj0aMSAQkLvKkIFuczAwIoAgQEpv6lsoQUwZIkIx6Bf/yHDa1NIPLOzldTsgBCA/jqwVcHMg+CB+rrjPpdWVlCjVF4/HFv3c4eWbIDEub9KCCCIoLsA1UEoQHqdxOunoochBVYuuSD8aPjsRiokilLtioiWaQqezsHsgANdRme01sS8Jth8uYNX0oCljnHU28W8rgtKrZO9BvPPXfut0PEeBQUHjx7kbeOqCLwDQUBUhIgGoRIGEIqGjkysH7NJwEFAiJIPIRl4L0Q4EEVQfaDtx7v3ZkTeFMW9Ndev/DIwy81N4Mq3Lk/G3ZrAodlHjUl4Ef/8qIoWJ49KUnAN9VTuOkzoMDkcZ1Lan/PNZgNezXRh0LqzSULVJaQKtqybO58/dqvftkQVqnPYyo81Nchbi/IPPjqgPOA5ANfA+IaTK8n1xiFf//3lxXRkERLEWxJIAoPEg+KHyQOvA2W15P11Hc3eL7ghA8XVryS1gpHa24chGP4cQAcyGbAxqAbMGfOzqbGK4lYT/s+7WAnNEXNpqjdFEFNEdQUtZuiZlPUbIn3HTv0TVXZhmNH/gAEkA3IpqWnoF0RmhTlxoMHDwOApmkMSveSi/b19dXW1paVlfX390PRTRE7LGqaZqmr6z/hZIwC7G0IzFu4asz4RU+PXTB1+pLZc1dNmbZ08tRlY8fVTpm6csbMdVOnPTN8ePW4cSuefnpJTZU/IGWYRl7licoThUMKZym8qfB6Ikwiqi36U5GA+bMfb+vqANGXUTikcI7ipwrnKJzj5o+HaEDU16363ZQJ0dYmaIqRaNDgPSmVxyoHxWy6zGdkPiXzycao/eMfbmpJQEi2Zb8ZlkHx03gAwhJEFVA4pPJ2SLab47QlQR775Ru737gk8ylVzAnerMJZKo8lr6NyEJYgwENYhrBMGiOwbvUH0yZFm+NYEVKKkFaErMLrCmcpHFL8VOFQQNRDSr6tGZ4eLr74/PmIakcDTlCyFN4sZCu0i7XRCkjZrZs/Hv4bb3MM4iGIqhCSIBEClYOQBEERh2QcC+J42IqFjIlj1XWrPwhKhioYMmeEJMo3mIqfBniIKBCSqOTXIwEzEszV1114/NHtrc1I4c079qfoy7U2gujLtLfAP//39a1NwHn6EhGs8KbCoUI29+LNWBASYZg5pfWZFb8LKygg6mEFxUNQLLzQ/4qQVYS0IqR2v3FpxG99zXHKNaSjKoQkGhIhqoDQgGMqNIZB4ayAaMZCdsc++OH/WC/6B0T/oOhPib6c6NVFryl6sOC1IwEqcul4TFOUa7xw7v/4L7+dMmX9iJHl06YtmzFt8cxpi2dOXTJryopZk1fNmfTMzEkb583aMWXyjvlzhf/9fx3FeS779l5t2NXN12dVzlL9SPU7qh+pnKVypsqZQaGnKXp28vjKtpa3GUSBgmUZeS19Ny4qyypjYwyi8+fPv2cQXbly5YULF86fP7958+ZbyrFtu7q62nUaSIvBS29PGMH8OS+/8fLbTZHLEeUr356zCve5yn8ZFL9uifbKvi+Fhi8i8rct0YFEsGdVbcfSqraWqM4msMaI0RgxEuF8IpxPRLIBqTcaHIiFBgX/JYm/PPKp1zpa86rYnQjnE2E9ETYTYT0R1t38QbkvpPQ+v/H03FlqR6veGBuIhnok7kpjxGiMWImwnohkE5FUPDIQj/TFIz0B+fKIJ19tjCVF/7fxcCYopQJiOhrQoqoeVnKqMBgJJENKbyTYu68pPW70Ts57Ph7pa4wlI4H+RCTbGDFiQb0xYilcKqLmE2E9KPfHw8ktG0/On6O2NA4mor2JaH8iOpiIpBKRrFvnsNqniJdbmzNTJnrqdp6LhfuDck9Q7ktEsoW2FNqlJ8JmIpINyFd2vPb7yRMa9jVlQ0p/NJCJqNloIMd7elVhMCAOKMJ1Wfg2IF9pjPXNmy29sPlkczzbGM3Gw5mWuB1Wcomw2RS1FT4ZDWSCcl840BMJXRWFz4c/taW1ZSARydyxP8PqQCw0KPgud7Tqv3xoY2tzhvd9HQ2V1DOSLbkyqtjTGM0umpd4fuPpRCSlSldDSm9j9EbDWf8nooPMGqy+7tOJ4/bubzd99RfC6mA8pEUDmswNyv5kNKA1Rc1IIBmUexTxSmeb9utHNjQnBpoTyeZEujmebY5rzTGrOYaao0Tl7ZDkRFQcVo2Imh3+m52y/5umaG9YvhiVLsbEizHxm7hwJc5fi/PXY8KVoPiFKp0LKV8OH/ZCRLnWGE5G5GQioCcCRkK1EgEjETASAT0RyCcC+cZQd3P8D+vWvHrqxCfIgmzGgoK3A9d23y4EOMWAEWAES5YssyzLZW/3kosuXbr0/PnzV65cee6551w23d/f39HR8e67744YMaKtra2pqamjo+PIkSOdd0vtx4f8umxZjVy1iFs4p37RXO+SKrWmTK6Yz1fMF5dUhpbXxOfP9M+fwS+tjA/91abhQ7bWlgdqKpTacqWmQqkpl6orpOoyvqqcX7U0WFPlX1LNV5Y3LK3h/+EHT296tnH5Urm6TKwqk6oXSVVlUnWZWFUusvw15dyqFYGpE7f/+Eez16+JLKn1r1qmrFkVqimXqsvlmjK5qpyvLvdWVXiqyvdWVtTVVnn+2z+M2bg+Ub6ofuWS0PIl4dVLG6vKlOU10RVLoisXR1ctj1SXeyvLGzZtiP/436bPmLq9qqK+psJbtnBvTblQXSFVLpBqKgLVi5QVS6JrVzQtqVGeWRkaN2bTz/59znMbItUV9VUV9dXlnqoKb3UZX1UuVi9SqsrFpTVCZfnejesTP/yX6VVlDWvXRBZXcdUVHGtFoUWsdYukqnJ++WJx4YI3/u2H0zc911RbwddWKUurgktrQmVz/bWV6tLqQE0lX1PhXbqY2/hs5IGfzx3y6NLaaq6mnKss45ZUqWXzuZoytaYiULlAWLE0smKxunyptHqFuGTx3v/r/3x043Ph6jL/Hftz3arYgnm7l9WKmzc2/+D/HrV8qVBb6VtSKxTaUiZWlfPFOvNV5f7Khd51a+KP/KJy4vgX1qwIVpY3LKsVnlvfXNoW1v/VFfVVlXtqKhv+4QdPb9vSVlXhXV4bWLU8tmpJomy+sLwmurgqsHppfO3qxLJace7sNzZtiP/9D0bUVnlqqjy1lb6aKn9thVhTKdeWB2rKQ/NmK8+sObxoYXTF0vZ5s6Uf/NdZiytjiyvCtQsDtQsDixcEFi8ILZkfZtfihdKCua8sWbL72Wflv//BUwvn76yq8FaV8yuXxmorg8VLra1Saquk2iphcXXDM6t2jH167pZNr+9rPrivpfP48RMtLS1dXfv3H2jbf6C1c39rZ2d7Z2dnR8f+jvaujvauyZOnspUgQsiyrHvJRV944YWLFy++9957L774IsNnMpm8fv26x+NJJBI/+clPRFHcvXu33+8XRTEYDAp3TtIjjwzhuJCiNDU3H4rFOv3+sCw1NTcdlqWWYKA9Gjko8M1NibeOHPrDqhUvLlqwNhY+EQm/Ew2dDIdORkNvh0LHI8FjodCxWOSYJB1QpANqoCsUOPjTnz0ZCR1W1UOR4PFQ8EQkeCIUPBEJHnfzh4NHQqGjWzY1TJpcHVAO8EJrNHwkFjvOSo4ET7A8wdChcPBgMHRAlTt//sDwROyYJB0Q/J2KcjQePq0qxxXhzXDoZCz8TiRyXBI6eaEtGj781PAZnvp4MHQwGj6iKAcjwWPh8Nsh5e1w6J2gfDwYeDsWfkdRDkfDb65d98a0KTWR6KFI6FAofCgSOhwKHY0Ej4VCxyOBk6HgiaB6SBDbGuNvjRm7aOcbgWj0rYBykOPaWSuKLTpRaGPoeDR85NXXpHFjFiYajweVI4HAMVk4wnOHJP6wqrwVUo8pyuGg2hUMHWyMH5sxc+mm5+qi0bcioaOBwNFE9B1ZejMSOBkJn1LEo8HgWwH5cCh8OBw60OCNPPboqHD0QCR47I79GQ2/6fO1qnJXPPHWL34+QlY6Q4GDinKwmMf9PMbyK9KBSOTYvDlrnt2wKxw8JIjtqrw/Gn2rpC3HIqGjofDhSOhQKNwlcPsef2JSPPqmJB0IqUcV5WgkcFLgjwTl47L0ZiR4IhY7EQ2/6fE2xSJHHvjFU0H1gBo4EFS7VPVQUDmiqm8G5eOqeoRTWiLNXZzSFG3skgNtTwybFI4cFMS2UKArFOgKF6794cD+iLo/HGyr9wq8Eow07nvit6PizQfD8f2B8IFI/GggfLB4HQiEOwOR9kCkLRhui0Y6582pra5cLQlRgVebm/cFg8FgUBUlvyj5RZEXRZ5RPs/JPCfPmjWHAYppdGfPnn3PIFpeXt7d3d3d3b127Vr3JttiyWaz5eXllmW5toF3L4ZU1ZYRMClYzMexhbVi8Dl2EcPSMXFsjBqbm6KxRDHGGTB/FqQYOJISYJ6SKQCy6azZc1PJnGk5xAHHAYLBcaDw3QGHsENJ9OSJd31+UddsGzlAwUbsvD9QciOn41BMHEJg9px5uaxBATJpU9cJq4OpgxsviL09lcqsWLUymUyzWlk2ZfXE9k01RwgwguNvnxIEKZPLEgLsZHPhs1hnoGAjByPYtbv+7Ief2oiyet6e083/4dmPX331dcPErFa2Cem0XfCcSIA5gnIImKYtSsofz51nrksxBiBgWUCdG/W0LUoBEHIufnNh69bn09nM3frTNBwKkMsahomnT5vNxuLWGt7W/6oSfvvEaQcDoWDbOJc3b89JCDiU9PcPbnl+azqVNy1CCdze/xgX+t8wrCnTpgLcoAdwaQYAg5XD/Rg0EzQMaH75ApuwbnPtF5gb14JzSQx5DJpBszMWTE1qSYsiDMSiTolSk2BAGCwMlgMYY4hFOg51nQAKlukw/92ElJrlkILpEgFCgDniY7Iu3Nu1aE9Pz6JFi6qqqi5evAglflIY1962bZuLzGw261o4QFG1C8VYTM9v3WLaBgHHoYQCIAcPJAddb2yWTSy7ECXygzMfdu7vKnYiKW43IdvSWPtNK4eR7hAT2dqrr211F+iOgwr5KWLueQeTvbalAaDP/vjR2yeOAiDdSAEg7BgAxLbNQoFGFsACsGycAbC2bd8IYGHHQLbuEMu2DFYsxraD2SMI4TyAtbfhtYGBq+xZ08qxemJkARD26WDTtPIA6KOPPxDFBnagVdOThWMZgAEwcRAAsa08gAXUbmyKXL1yMZdPAiCEDQBs2RoARtgAIKyNNtIB0Gefn21o2MHKIQQT7BBCCC64V0um+orttSJR9cvz59j5Sd3IFlrEaIECQhYlNqPX3v5vGhpeL3ijZc5Oi2SnaxkAnMsmARBxTOwYe/fs0PQk63/L1LPZNHskn8sAYOJYAMgycwBof+e+3/3+FOsow0gBIAebbGSxY1JiFfvEMIzUrt2vAFgI64VWUweAsF4ijpXJDgIgG+U0bXDj5tWE6G4YUuJYxWpjBywHLNMxHCBZ3VjzzAbKPFzRQrtNU2cRTQ1rAEBzwMiayayRfvG17QbWHSAWsZk61qbIAWJg3QHkgJW30whsCnDi7fffPHqCOAAUcjnNNFmLGF0RQrBrb5fJ5Orq6txQvewM9r3cdMlms8w+nlJ6N7XtLVujriUDO6pGCLGQTQEy2bxpIQqAMKEAec2wkWPZmIHTMLFpOYaJMWZIsx1sEsfMZgaKdJBjXzDOF4BhpgGsTKYXqA2AsplBQ8+wPL09VwAQJRYA0vVkKnUdwEIoh1AO47xt5Vm2TKYXwBocvGZZKQDDNJOmmQQwCdENPWMaWQBkW3mGTNPI5nL9up40zTSbfSnVCMkjlAOw0qk+Rr7pVB8lNirsklmWlQGwHCfH8gMY2WwfgEUck1XDwUbBATRY/f1X2BeM9NJWa/mUgw0AZBo5AOQ4GoDF6kkcEwBbJqskQbZumfkii7Byuf7iQS2GQ6Tl09e7v7XMPEZGOjXImuZgg/WqaSYBDAcblpkDwBjplplj/cBKII7JSh4cvMa+EKIzGGv5NKtGIX9xgCwrA2BgnGWdZlkMpQbLQ6kBYBnGIPs3k7nOngJAyNaSgz257CBGRi47WGyUyQpMJq+yMlkJAEjX0raV1/S0jQ0HMAUYTKaZ+ZphAKWg68S0GBfBNs5oRi9A1kKDmJoOEAeAGdXYxMmblgNgIFy8STQ7n8onHUC6qTElEIO7w2LyAdi2SQg2Td00dQCi67phGJaFoGhQQCllLK2iouIe74tCSRRgtxz2VnZw1P3pnnfRdb00AgUA9PZeL8WwG00YSvZU2U9N04ACthFjspZhIstmsV1RwQk9AAVdy7H5lQWPYDcJdtw8+WwOKNz4i7FZWggRjW2UGkwChUyqMP2bhsY+HWwX+AwFyzBLvziIOTsnlGAtn3UZJivWQdg2LZafOoQ1wdB0Vn4qOQBAMukk+2loupbLl5ZZLIqdK8i7n6yBDsKswoUDVqaVTqbcn7lMPp3MAAUtpwMF6gBQ0PMaUMimM6xWyLKxjWyz0LGGZgKF5EDKrXBp9wKF3ut9QGhhLAh1+40VVWAalgEULMOmDmTTOffZG9+B6FrOMnWgDgBm/JMNjaHpbp7BgT5Xbirt/9IL28jUDZa/wOQdxIbVNDQ2+r3Xe4CCaeo2ttLpNIuVSAkjGGSZDgDktXQm2weQR6TXQFcBspggCmBajHPYhulQCrm8xbju9Z5BXAwsnkxlmFANALmcls/nXWjYts1Q4Ia3L6VqQoh7815C1LZtSqlt2wxOrq0fqwopOuZkh2C6urrefPPNQCBw8OBBt64Mcul0kslpGNsXL34NQCh1mpoS7e2tAETX85Q6GNtFYbVAYfms8cdPvwgo4QOdhw50Hvrjp18wLAAFZBGgQDBYBgYKPd3931y8gizS3Nh67OjbQKG/N1kkZadIkQX6+/KLCy1NbbFIY9f+w2fe/0MREuYNB9kUrl3pAQpn//CJg8DQ7Fik0Tadvp5BghmtUAcxDFipwSxQuPj15QXzyiZPnDZ61LiJ46dIgmrqyC6NGF+sDLLIthdeGuxPL1+6au7sBfs7DrKigIKpIwdBOplzq/3px5/NmjF33JiJ06bMnDVj7mfnzlMHTB25J60s3THyCAgsrl4OBBbOq5g9Y35by/7UQM6xCxkYPbNs+Yy5ctkzE8dNnTR+2vgxk9eteY7l0bIWEOi7njQ17Ngw0JcCCqtWPKPnrRXLVs+aMVfkFdbVrPlazjR1xHoAKFy+eG30yPHz51RMnzJ76qSZx46cQCYFCplUvrT5el57+63jkVA0nzVmzZg7dvSEr85fRBbJZXQ23FrOZG9ho3yg89DwJ0dNmTT9qd+OnD511vVrfaz/tZzplpkcyACFZ9dtpA689eaJBfPKZs+cx0gdIYetyQ0dFecCaG5unjBxTFn5nAmTnhw5+pfnPj9JIFtYfyGgAJZNbQQIw+46z6Vvrv3hw08rq5bMnDXPMDFblN2OIk3TXMmRsR/2nVkTGIaRTqfZOTAGonnz5t17LgpFr39QIta6W7GGYVRWVoqiWFdXFwgEdu7cWVdX51bUXa8yy94XX3zxyJEj27dv7eraL4p8LBYxTZ0QjJDlOAghC6DQp7msuXrV+mAgpiqRgBp9bsPzJ0+8p+VtoGAaDlBgKwHLJCtXrO1oPxgOJWLR5m1bX0nE9wEtiiKMRRT8LIOWt5/b8HwwEIuEG2PR5mfXbz586C23KKBg6Nj98qN//em3l69v2rg1Hmt5Zs2GfM5KDt5gFJZZmOmTg7lXX9n50dk/5nMFFjp1yiz2dvZJCaSSeV1D7PF/+Pv/d9bM+YMDWaDg84qHDh5z8I2quhVwMAwd8hRrKUZg6PinP3mwtEXEKeybA4VfPPDrcWOn9lxPAYVIuLmleT9QMPSbeFE2Y7W1HuS5gHvH65HeOXkGI7AMYNNjLoPZ63QNPf7YbyaMn/rF5xeAQuu+/bIUcl8HFDJpnfUbJTBr5kLLhJ7uDPtrxPBxjGsBBV0r4cwAf/jD2VGjRk8YP8W2qGk4L7/0xpfnLyH7xmCxgWA9+cTjv8WoYKADFMrLaliZ7F/WUaxLn9/y4vhxU+r3+nuuD1qmM3/uAqDgIEIdwLYDFGyLWBbCmLDY1tgxs7lBw0xPmTaagu1QzBRtyCksu1KZdN3ePRMnT1q7fp1pWwPJwUXlZRQgr2sUQNNyjM3YtukKg5qmTZ8+XVGUSCTintwsTQyApmne47VoJpPRNI1ZJrA7LPISg6hpmlevXgWAUaNGsX8dx0kmk3PnzoUSKdcwDAZUQsiHH344b968YDCYzaY1LTd9+lTT1NkiG4BYlsHiuwwMJM+d+2zp0uXsJK5p2s3N+1pb2zXNcCnYNDBQMA189Wr3vHkL1q17FgA0zVi9+pn+/kGMSeEULwXbIozy0ql8eVm1e7r32LHjHo8PY1IEsMW+2DamFDo69v/whz/66qsLANDb2z958tR8Xs/lNFYmULBMh1HPyZOn1qxZW1lZvWTJsnXrnt25c3cymTZN27IQW43c4CSaDRS8Xv/AQBIAOjr2v/zyq8QBZN8IKw8UWA05Tli7dv2aNWvXrFm7evUzjY3Nvb39jkOBArIhndLYbMWqLfAKo+YzH3y4ZfM2F+rplIZs6Lk+CBS+vdy9ZPGKmuqlSxavWLN6fW3Nsm8uXWWAz+cQJTdAksnkACAUirD6f/31xbKyCgDI5/VSLLFO6DpwdNHCqtde3bVm9bNVlYvr9/oyaQ3ffMI/l8shhABIb29vW1sbG9OlS5e/994HAJDLGu4wMXFU04w9e+qXLFlWVlZRVVWzaFF5Z+cBgEKwH/bqwYEMUMjnTAA4efLUlSvXNM0gBGZMm5nL5E29MGOmk5lCzQHq6z2VldUrV67evPn5ysrqtrYOAHAoQY7NmmVji+0yUMCfnPu4t79nINlPgYwZN5YC2BhRICUuoAuEdPny5Wg0unnzZq/XG41GI5EIAKTTaYyxG7aXwYEQco/XoqWrUOacHooirjt/UErPnj07f/78qVOnTps2raamJp/PuxNJJlOYXNkySc8bQCGTyrI12IvbtgMFILRUhesQk4KVzPS072+av2j25Gnjx4wf+cL2TZhYFHAmlyzdsHGoTQHZTj5vJB0wKKBtL20x7Jzt6Cy/Q23T1ihgAggT1N65b/qsyVOmj5s2c9LaZ1dZSKeATdugQCiQVGaAArax4YBlO7rt5ClY7Hrl9e0UUCaXzOZTxbEkhpVnb6GAkpm+gVR3Jt+vmSkKFqZmyd4SYY8k0/3FOyzGpkEBOdTGpJATEwsTSzdzFDAixteXvvj92fc///LTz85/VKwJMm2DYZnVwaEYOaaNjbyeoYCT6UGmv2RTPqM89nbD0geSvdl8qm/g+rnPPqbAHrQoFFR6FAATJ2+kKVjdvd9gqlNAhp2jgDA1KWDNyLKeJICQYzoUOxQblu5Q/NWFL69dv8r6k9WEHd9ncQopWIhorAmIaIadQcSggJBjIsdkNaRAWMPZs7qVtXBOt9IXL3/x3pkTFBAihkNt1kaHYgoEOSarDMtPwTr/5blMOgnYAQqkqNEoUKBmUAKXv+n+8vxlbMM3F/uZf3qnRNpwKGFLU83IU4B0NkMBcnk9mcoVMhBghkQIGw6xNC3nOAgAEEJbt24fPXrs+vUb4IbTaaaHByjxFH8v90XdR26J5uKyR3df9Jboacw1NrhSLuN7iAAFbDtffHa+eAczBQC2katbz2tpAMuwUxQsBwxMdQvnKFgETDZI7qduZTGxKCAK1qVvP3fAIGB+fekzCpbt5BHRioSF3EcY3X977WuWh4JlO7puZQmgnJZm4M/kB1mZFKxrPZeudH/1xVefsJ+pbC8rjWHetDUCCBFjMN27fFXNnPnT5i2cMWHyyM6uFs1M6VbadvIsf5FkMQW8r73xqZHDxk8aNWX6uFXPLMnpg4adKyFoiwIyUZ4CMuyMO0FQsEyUdsAwEWs1xgQVZwec1ZIulkpnsXQ2ZSEdOSYmloV0C+lygJ8zf8bBI50OWE+NHJbODdjY0IwsQ4hh6RQwBYuC8cVXn4yfNMrL1X177etVzyzx8XtYrdhFwKaADCvP+mH6zCmfnz8XCMlzF8x894OTFJBmZnQrbaIsIhqmeQqWhTOpbO+uPS/7+D0Xvvl8+qyJouLNaklEDBsbrMLIMSmgdG6AgjV91sSZcybXLl30L//6T0N/++tEc4hNGWyyYNjGxHLACsfUx4Y8vHrt0hFPD/t//ut/WbK4Bijk0xmgkE4NItuEgt4ONm/aChSamzonjp/Vtf9ELgtWgdeCZWNNN03bQg52KJFVZSA5OJAcnDJ1+pKlyykAKtrem6bONrHcXRZd199+++3u7h5dZ1YDeQYfzFRfJdgBgOrq6vuyFr0lEVJQK7OfQ4cOXbFixZo1a77++mt253Zx3DCMVCq1Y8eOcePGrV+/vrm5mVLK0O6qgi3Lcjctu7uvbt36/KpVK95558TixTUrVy4/c+b94r6w427c2bZ5+vQ7q1Yve/bZdceOHa2urty06TmMbUIwk5xZToQsjG1dz69Zs2rZsiu1h74AAA7/SURBVCU/+tEPFy1acOnSBYQstrQgBDsOyuUybsnRaLi6uvLJp4aOGzemo6PN5fMY2whZTNHFpkmPp/6tt94EILlcBgDPnTtb03Js8Jgu3q1DMjmwcOF8Sh2mG+vq2i8IXIkEcdPl8dRv2bJp5crlixfXbNmy6dHHHinoPB3ElgOZTIpp2tasWfXii9uWLl28YsWysrKFL7ywxdW9uTvGmpbr6trPcT7HQWvWrGpo2Ltly6YzZ95nrSgd20wmhbAxYcI4x0HHjh2dPXvmqVMnN2xYf7d6zp49kxC8ZEntxo0bELKGD3/SXbnYtomQxYJrZbKDR48e9nMNn3768T/90z8CkA0b1p8+/Q47DO12OxsCx0GffXZu8+aNR452nThxvLOz3S0TY7t0ZcRg8NJL21evXqnr+aqqCgAwTdMyTCjZAmRC349//JM1a9Y2NjZbpqMq4abGVqBg24VtTHaQi9HqSy+9VFtbW1NTQwi5cOHCpk1bwBWzARgRlq7+9u/f/+CDD65fv/5HP/rR22+/nU6nS4nftWwHgAULFnwXEL0lTZo0CQDOnj27evXqGTNmHDhwgN13geqqpDdv3jw4OPjVV1+1t7fPnTt3z549g4ODbjkuf85msz09Pc8991wmk5k9e/bly5e7urqam5uZlsxVJrPMr7/++uXLly9dujRixAhd16uqqpjHM9eew32kp6dnwYIFAJBOp9etW7dt27be3l6WgflMY1VlC+xHH32U/bV8+XKPx3Ps2LErV67cUk/W6YcPH37ppZc8Ho+qqoqilJWVsUa5ywQ3Pno6na6oqEgkEhzHRaPRTZs27d+//269+vHHHz///PP9/f1ffPHFxx9//Oqrr5qmWbr0YGoC0zQjkUggELh48WJ/f//hw4c7OztZBrdv2R71Z599tmLFCtYnmUzmgQceOHfu3O3NYdsDq1atOn/+PPururqaEdUd0xtvvJFIJADg8uXLCCF2SlHX9VLhi53v/+CDDzZt2gRF5Gzfvv306dNQ3DtgtWLVYz320UcfcRw3Y8YMRVEYPWuados7WLbKJYQcPHhwy5YtU6dOLfWzxUpjj+i6Pjg4uGnTJoTQ4OAgQmjMmDHMVR9CiFXANb+5evVqY2Pjhx9+CAAY4yeffNKNusCyuS5HWMUMw6irq0un0/v27btw4QIpxvsspdXvDqKuJzHW/mw2y/z5uuNx7tw518WuYRisg1j99u7dW1ZWxgoZHBzs6elhfg1ZS9i4Msrr7+/ftWtXWVnZtWvXNm7cuGrVqmvXrrEy3U0gpme+du3a3LlzX375ZfaF4zg2SG6T3c61bVtV1dmzZ48ePfrq1aunT5/2eDxuvwOAi9hcLnf27Nnp06ePGjUqGAxijJn3/Ww2yxrC1ABuOnz4cFNTU2trayKRYFr4Uv17qd1Vf3//m2++GQwGGxsbGULulthTbNXATEdYhzOquiUnpYU9dPb2YsDWwoi42T766CP2JZfLffbZZ64jSfcVbvf29vZ2d3ez+7Ztf/vtt3erp2ma165dc/nGmTNnSonN1fyz9PHHH7Mzxslk8uLFiz09Pe7o3G5Gyjr5wIED7EupkQzLzO4QQhi9ffPNN++99x6UgNNtOIuiUPqK/v7+Tz755I7NcZ/KZrPs52effeb2ZKkhnZsMw9i2bduIESN27drF7jCLXPb9b8ZFdV1nw8lMERBC+Xze7Z3SZrgETQixbdudYplrMrfjXCp0K+w6fXHvl05m7h24+cyq4ziM37r33TnPMIzSMXAfyefzbjVYbHL2Rnakjlk4urvPbI5ntpCpVKo0eJw7a7oavNIJhT3ISL+0mXdLpf6i2GdfX5/7r8tUXc8YtxfI2AXzpQo372mzWvX19ZX6pirtyVKC/tP1dP91m5bL5UrnEdu2GYrYzVIn6SwxCLk/3VF2daGlEllpzqIna4Ci4wGW091EYH+VOpG1LIsNpSs33d5GNqalTdA0zV2XlTaceVRIJBInTpwAAFEUXSkGIVTqke+7g2jpDO0245Ypit1kgGS1zGQyzAXwLY2EIvm6P5nc4hbiejlzPZu5T7kDYFmWC/tb+JsrwJRO59lsljEH9pO9opQ9suOv7hm/O7bdrcnZs2c7OjpCoZDH4/H7/ZMmTSrFDNxM67Ist7W1JRIJVVUXLFjQ0tJyt35+6623WltbZVlWVVWW5WnTprH7pTyTpebm5lgs5vF4AoHA1q1bd+zYUToK7tu/+eablpYWWZbZyaTZs2d//vnnt3QpFNlmKBTq7OzctWuXKIq7du0qPTN8Szp16lQikejs7Kyrq4tEIkOGDLnl7aXGZB0dHYIg1NfXx2Kx6dOnnzlzxm1UaR0QQh0dHYFAoKGhQVXVnTt3vvLKK8yXNBMy2QCxR44fP97R0SHL8t69e1VVHT58OBSnezZYDMaWZXV0dHg8ns7Ozqampl27dq1btw6KtHHLtv/nn38eCoW6urp2797t9Xoff/xx9lcp6SKEbNtmBNPW1lZbW+vxeNauXfvFF1/AzZPO34aLmqbZ39/P6t3T08NuYoyZwOPyQNb1rI/YTV3X3cEzTdNdBELJet00zd7e3lJR7W7qZUZ/7lTKpmeGkNJtIfYU03KVMj13YfMnDuuwns1kMu5BAijSMQCkUqn+/v6nnnoqHo9LknTq1KkFCxYw3uv2gLsoyOfzy5Yt83g88Xi8q6tr+/btf2IteujQoVmzZp06dYrn+ZaWluXLl2ezWVd8cg/NZzKZTZs2rVu3bt++fQcOHJAkSZKk20u7fv06IWT48OGHDh1iMnlFRYUrabt94nbv888/X1FRcezYsaamJp/P58b1uT199dVXw4YNa2tra29v7+jomDNnTl9fHxOp4Gax8L333ps8eXI4HD569Gg8Hq+qqmL6RSYlsVe7e3s7duxYsWJFV1fX/v37vV7v66+/Xio6siFmEtbFixcfeeSRkydPhsPh9vb2J5980uWTbNDdpQFbZ7W3tzc2NgaDwfXr17vNZ+PF/Lk7jvPll1+OGDFCkqSOjo5Dhw5NnjzZMIx8Pl9K3rf02HvvvdfS0tLd3Z3L5VxpxSUD+C4h6uLB5WNMLVHKOtw8jPTZTKNpGrvvOM4ti37LslzuV/rXLZohVsjtnu//v/auJKSZJAr/R08KXgTFi3c9CHrx6knUo3gYlBgaN9BOEBXXGARXRAPGBRU39KBEVBA3FBVxCVEU16hJENG4a7rbdGhN/Yc3vqlpf2bmMONAqO+UXlJd/bpevVffe1WlKApyOSBE2u/1f64AjIf0H+ERLy8vXq8XA79QGdRbuEQ/F/UWawU/3G43NA7suaEQ7ImwYvBolc2nIQgCDIegBJWfAj0UPYqDG9BtgUaJLolKXHgPDurQG3p9fYUPiimfz8/Pf7H53fv7uyzL+F5fd/cB+ataIKoi3RiwEEmScHYILWFRFGkhgF+NfAdUEl+cfBo6ugRCrQ6NdNrHxwd+fawJ3o9NTjUKw6qOjY3hMGR2dhZ6QygcbRX5ZiuKQiF/lgjd4CRJQk+dUM1dUZRfjp3g/XGyG+xliuexZ0IgWYcNVFUUfQbEjXfSdcZqwyG2DOxNaEeXXkgNRQFfF7+oqnBC7bVBv7LX61X5wyqghqDBJNRqqejAg1jwPDiWXwWFFcZBBBaO3AFKnq7/361j/scjsF+mbTItQEmSsIXgIlhYCIjR/2VOFRxCt4JahFYXLSRWGE0i3X6QiVCJSzXapAunvw7aQxpQ1PHxcVBQUE5OjlarzcrKio2NnZubUxFg/3/QhYHhvwNqDh1shCgAXkL9UXVPoIG3t7egHkAloOYAW47RBJqEh+RWIL2wfyRfpl56PB6fz7e1tcXzPM/zbrf79vYWKT1UcqaiDAEOHCZA66epPmRNkZggn7ohiqKiKBUVFQ6HA8cUKmOo4pbRc/H7/aWlpVarVTVMoHJsfndh6NGmTqfLzc212+3wLDrYRpiKMgQq0Cl1Op3b29vLy8twODAwADM2z8/PW1paHh4eFEUZHBy0WCw+nw9Mbl5e3vX1NSHEarXiiNHpdEIazOXl5dDQ0NTU1Ozs7Nvbm9lshpJnZma6urp8Pp/BYNjY2EC+F/oCWsnBM/f5fH19fQ0NDVVVVf39/R6Ph07IIUxFGQIegiAMDw+HhIRMTExwHCcIgl6vNxqN2dnZfr8/LS2tu7vbbre3traOjo52dXUNDg6Kori4uAhEtM1mg0Su7OzskZGR4ODgpaUljuPa2toaGhoSExMdDkdNTU1xcXFdXd3GxkZ+fn5ZWZnL5SKEpKWlESoETTu6GONNSEhoamrq6OhwuVy9vb37+/twAx1TIExFGQIVyOikpqYqiqLX62VZjo+PN5vN4+Pjj4+PFoulqKjo5uaG4zhCyNnZmU6nI4RsbW1VV1cLgrC2tmYwGGRZTkpKen5+hvW+tFrtx8fH6enp2NiYKIqFhYV9fX1Go1GSpPr6+sbGRkEQbDZbSUkJUk2QfAbppeTThJ6dnUVHRzc3N1dWVjY3N6ekpHwNpDEVZQhw3N3deb3euLi4pqamvLw8j8fT1tbW09PT2dlJCElOTtbpdFdXV2azubW1taKiApRkdXW1traWEHJ0dGQwGNrb20tLS1dXV6Oiok5OTmJiYmprayMjI00mU0ZGhslkmpqaioiIWF9fLykpSU9PF0Xx7u6O53lImQC1xFlcQF/Tk6LhBzDqkiTRaXNMRRkCGRiG0ev1u7u7sB7l29vb5OQkIcTj8UxPT0MO7f39/eHh4fr6Opx3u91GoxFyfY6PjxcWFmRZvri42Nvbe3h4WFlZOTg42NzcnJmZuby8lGV5fn5+f3/f4XDs7Oy4XK6np6fy8nKcvEW7uLjmHjwIw8h0OjohhN6ugTAVZQhUgKM7MjISFhaGRgx5VKRYIY3k/XMXbbhNFEWe5+12O6GS2+C/Xq8XbCBE7+l0aHBoy8rKIPsKUx1gwzFMUSRf+GEA5CcBVwzU7i9UFKLAMCWFpqcZGBi+GeQzwxHSsDQazY+amhpIxQBKGtX1X+7cGBgY/hnAUoKpLygo+BEeHs7zvEajycrK4jiO47j8/HyNRvMbAwPDt0Or1XIcl5mZmZubm5OTExoa+hNn/HESyjoKRwAAAABJRU5ErkJggg==" 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Gráfico de tronco y hojas. Forma híbrida entre tabla e histograma.<br />
Gráfico para datos bidimensionales. Estudia el comportamiento de una variable en función de otra, haciendo una evolución histórica.<br />
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" /><br />
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Gráfico de sectores. Para variables cualitatitavas dicotómicas. <br />
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<img alt="" 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" /><br />
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Gráfico para datos multidimensionales: diagrama de estrellas.<br />
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Me ha resultado un tema sencillo, en el que hay que tener claro algunos conceptos y ponerlos en práctica para la elaboración de tablas y gráficos. <br />
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<br />Rocío Romero Castillohttp://www.blogger.com/profile/12000531683527549788noreply@blogger.com0tag:blogger.com,1999:blog-9204560667939424211.post-8457552457391893782012-04-26T10:31:00.000-07:002012-04-26T10:31:17.054-07:00Tareas individuales<br />
Realizamos dos supuestos prácticos unas dos semanas antes del parcial para ver si manejábamos lo que se había visto en clase. Los problemas no me parecieron complicados, creía que los había hecho bien pero cuando estudié los temas a fondo y vi algunos ejemplos resueltos me di cuenta de que había cometido algunos errores en la resolución de los problemas. Una vez que lo comprendí empecé a hacerlos correctamente y creo que en el examen lo hice bien.Rocío Romero Castillohttp://www.blogger.com/profile/12000531683527549788noreply@blogger.com0tag:blogger.com,1999:blog-9204560667939424211.post-73062015366076922722012-04-04T04:04:00.002-07:002012-04-04T04:04:29.265-07:00Tema 6. La etapa empírica de la investigación: diseño, material y métodos.<br />
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Cuando la población de estudio es muy grande tenemos que hacer un muestreo lo suficientemente amplio como para que la probabilidad de inferencia no sea mayor de 0.5. El muestreo puede ser aleatorio simple (al azar), sistemático, estratificado... <br />
La recogida de datos se puede realizar por observación directa, por fuentes documentales, a través de entrevistas, cuestionarios, formularios.<br />
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<b>Medidas de frecuencia </b>(en estudios descriptivos).<br />
La<b> prevalencia</b> describe una proporción. Es adimensional y adopta valores entre 0 y 1.<br />
Prevalencia= Nº de individuos con la enfermedad en un tiempo específico/ Nº de individuos en la población en un punto en el tiempo.<br />
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La<b> incidencia </b>describe la frecuencia de nuevos casos que ocurren durante un periodo de tiempo. Es el flujo de sanos a enfermos. Es una magnitud dimensional.<br />
Incidencia= Nº de nuevos casos detectados durante el seguimiento que desarrollan la enfermedad/ Nº de sujetos libre de enfermedad al comienzo del seguimiento.<br />
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Vimos que hay dos formas de incidencia: incidencia acumulada y densidad de incidencia.<br />
Ia= Nº casos nuevos que suceden en un período de tiempo/ total de población en riesgo de padecer la enfermedad al inicio del seguimiento.<br />
D.I= Nº casos nuevos que suceden en un período de tiempo/ suma de los tiempos en los que cada sujeto del estudio permanece en riesgo de padecer la enfermedad.<br />
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En clase realizamos un ejercicio donde teníamos que calcular la densidad de incidencia y la incidencia acumulada. Es fácil de calcular una vez que has entendido los conceptos.<br />
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<b>Medidas de asociación</b><br />
Magnitud de asociación---> <b>razón de prevalencia</b> (compara prevalencias en estudios descriptivos transversales)<br />
Rp= P.e/ P.ne.<br />
(Prevalencia en no expuestos= Nº de casos entre los no expuestos/ Nº total de individuos no expuestos= P.ne<br />
Prevalencia en expuestos= Nº de casos entre los expuestos/ Nº total de individuos expuestos= P.e)<br />
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<b>Riesgo relativo</b> o razón de incidencias. Cuantifica el incremento de riesgo con la exposición.<br />
R.R= I.e/ I.ne<br />
(I.e= Nº de casos entre los expuestos/ Nº total de individuos expuestos.<br />
I.ne= Nº de casos entre los no expuesto/ Nº total de individuos no expuestos.)<br />
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Después estudiamos la estimación de la magnitud de asociación en estudios de casos y controles. Se trata de relacionar la ODDS o ventaja de los casos con la ODDS o ventaja de los controles.<br />
Valores posibles:<br />
>1, significa que hay mayor riesgo en casos que en controles<br />
=1, hay el mismo riesgo entre casos y controles. Se acepta la hipótesis nula.<br />
De 0 a 1, los controles tienen más riesgo que los casos. Se acepta la hipótesis inversa a la que pensábamos.<br />
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Por último realizamos ejercicios prácticos muy completos en los que se pedía describir las hipótesis y variables, identificar el tipo de estudio y hacer diversos cálculos con los conceptos y fórmulas aprendidas. <br />
Es un tema complejo, donde se han incluido muchos detalles y hay que estudiarlo todo detenidamente para no cometer errores en la resolución de problemas.<br />
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<br />Rocío Romero Castillohttp://www.blogger.com/profile/12000531683527549788noreply@blogger.com0tag:blogger.com,1999:blog-9204560667939424211.post-76173977758962729402012-04-02T07:38:00.000-07:002012-04-02T07:39:38.569-07:00Seminario 3<br />
En el tercer seminario estuvimos realizando cuestionarios. En primer lugar aprendimos a descargarnos el programa que utilizaremos en la asignatura: Epi Info. Hay que seguir unos pasos para poner el programa en esapañol, que están indicados en el campus por el profesor.<br />
Después de esto vimos los apartados del programa y las utilidades y comenzamos a realizar un cuestionario. Aprendimos a colocar los datos en la plantilla. Se quería realizar un estudio sobre una población que había asistido a una fiesta de cumpleaños en la cual muchos de los invitados habían adquirido una enfermedad toxiinfecciosa por haber tomado algo en la fiesta. Nuestro objetivo sería averiguar qué alimento estaba en mal estado, para ello sería necesario pasar el cuestionario a todos los asistentes a la celebración.<br />
En el seminario escribimos los datos de cinco personas y pudimos ver que una vez que los datos se registraban se podían localizar las personas que habian consumido un determinado alimento.<br />
Este programa lo utilizaremos en nuestro trabajo de investigación y tendremos que escribir los datos de 55 sujetos. Será un trabajo lento, pero hay que tener paciencia, pudimos comprobar que el programa nos facilita un poco la tarea.Rocío Romero Castillohttp://www.blogger.com/profile/12000531683527549788noreply@blogger.com0tag:blogger.com,1999:blog-9204560667939424211.post-59026498958152237512012-03-22T16:04:00.000-07:002012-03-22T16:04:32.524-07:00Tema 5. El marco teórico y los objetivos de la investigación. Hipótesis de investigación.<br />
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Creo que este tema tiene muchos contenidos fundamentales en la asignatura.<br />
Cuando realizamos un proyecto de investigación tenemos que definir y formular objetivos. En el caso de estudios analíticos o experimentales hay que elaborar una hipótesis. Ésta es un enunciado de las expectativas de la investigación acerca de relaciones entre variables que se indagan. Se debe formular en términos de hipótesis nula.<br />
En clase estuvimos viendo las variables, la hipótesis nula y las hipótesis alternativas de dos estudios.<br />
Después se explicó cómo se construye el marco teórico de una investigación y cómo se formulan preguntas.<br />
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Estudiamos los diseños cuantitativos (epidemiológicos).<br />
<b>Diseño descriptivo</b>, con el estudio de la prevalencia. Consiste en retratar lo que está ocurriendo en un momento concreto, por ejemplo saber cuántos obesos hay en España. No hay una hipótesis porque te limitas a observar, son los que tienen menos fiabilidad. <br />
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<b>Diseño analítico</b>, dentro de éste encontramos el estudio de <b>cohortes</b> o de seguimiento, que a su vez se subdivide en <b>prospectivo</b> y <b>retrospectivo</b>. <br />
Los estudios prospectivos son observacionales a lo largo de un período de tiempo, como si estuviésemos viendo una "película". Son más fiables que los descriptivos.<br />
Los estudios retrospectivos son cohortes históricas, nos fijamos en un registro pasado.<br />
Dentro del estudio analítco también tenemos <b>estudios de casos y controles, </b>en estos buscamos el efecto.<br />
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<b>Diseño experimental</b>. Engloba <b>ensayo clínico</b> y<b> diseño cuasiexperimental</b>. Es el más fiable de todos. Se elige una muestra aleatoria y se realiza un estudio simple ciego, cuanto más ciego sea, más fiabilidad tiene el estudio.<br />
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Por último estudiamos los cuatro niveles de evidencia, de estos surgen grados de recomendación, aplicables como criterios de calidad a distintos niveles.Rocío Romero Castillohttp://www.blogger.com/profile/12000531683527549788noreply@blogger.com0tag:blogger.com,1999:blog-9204560667939424211.post-53945108210785463752012-03-22T15:18:00.000-07:002012-03-22T15:18:54.079-07:00Tema 4. Fuentes de información y revisión bibliográfica. Información documental e información de campo.<br />
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En este tema estuvimos viendo las utilidades de la revisión bibliográfica y la importancia que tiene la búsqueda de antecedentes. Vimos el concepto de fuente documental primaria y secundaria. Las fuentes documentales primarias son los manuscritos directos y las secundarias son catálogos de las fuentes primarias, listados, bases de datos en la red. Aprendimos cuáles eran las bases de datos que debemos utilizar en el trabajo de investigación y el procedimiento que se tiene que seguir para la selección de la información.<br />
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Le dedicamos un rato a analizar los descriptores de búsqueda. Al principio parecía un tanto abstracto pero en la práctica es sencillo. Después estudiamos las fuentes de información de campo: observación directa, entrevistas y cuestionarios, registro por el propio paciente, informador directo y registros previos.<br />
En la observación directa tenemos que tener en cuenta tres aspectos: los observadores, el instrumento utilizado y el fenómeno observado.<br />
Existen dos tipos de entrevistas: las estructuradas y las no estructuradas, cada una de ellas con sus ventajas e inconvenientes.<br />
En cuanto al cuestionario es imprescindible que tenga fiabilidad y validez. Para elaborarlo hay que seguir una serie de etapas. Se hacen preguntas abiertas y cerradas, cada una de las cuales tiene su parte positiva y negativa.<br />
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En este tema para lo que tuve más dificultad fue para entender las estrategias de búsqueda mediante descriptores pero lo comprendí bien en el seminario cuando comenzamos a realizar búsquedas bibliográficas.Rocío Romero Castillohttp://www.blogger.com/profile/12000531683527549788noreply@blogger.com0tag:blogger.com,1999:blog-9204560667939424211.post-90109287160419240562012-03-18T06:50:00.004-07:002012-03-18T06:52:52.617-07:00Tareas individuales<br />
El primer cuestionario que se ha colgado en el campus abarca los tres primeros temas.<br />
Antes de comenzar a responder las preguntas leí los temas e intenté quedarme con los contenidos más importantes. Algunas preguntas las contesté sin dudar y en otras me tuve que detener a reflexionar un poco más. Saqué una calificación de 9. Fallé en una pregunta en la que estaba dudosa pero ya me ha quedado claro y no se me olvidará.Rocío Romero Castillohttp://www.blogger.com/profile/12000531683527549788noreply@blogger.com0tag:blogger.com,1999:blog-9204560667939424211.post-17624823433249548542012-03-15T03:18:00.000-07:002012-03-15T03:18:46.974-07:00Seminario 2<br />
En el segundo seminario aprendimos a realizar correctamente búsquedas bibliográficas. En primer lugar vimos que buscar en Google directamente no era recomendable, para una búsqueda más específica se debe utilizar Google académico.<br />
Después entramos en Cuiden, donde todos los artículos están en español, por tanto hay un número reducido. En Medline la gama de artículos de investigación es mucho más amplia, es el sitio donde más información científica se puede encontrar. Lo que ocurre con estas páginas es que solo tienen un trozo del texto, para poder leer la revista completa hay que entrar en la página de la Universidad de Sevilla donde sí podemos acceder a la revista.<br />
El seminario estuvo entretenido, al principio nos costó trabajo hacer lo que nos explicaba el profesor, algunos no podíamos ver la revista porque no teníamos contraseña para entrar en la biblioteca de la US.<br />
Finalmente gracias a la paciencia del profesor y nuestra atención aprendimos el proceso para realizar una búsqueda bibliográfica. Comenzamos a buscar acerca del tema elegido para el proyecto de investigación.<br />Rocío Romero Castillohttp://www.blogger.com/profile/12000531683527549788noreply@blogger.com1tag:blogger.com,1999:blog-9204560667939424211.post-16998614108756010202012-03-10T03:39:00.001-08:002012-03-15T01:26:38.190-07:00Seminario 1<br />
En el primer seminario el profesor nos dividió en grupos de cuatro personas para realizar el proyecto de investigación. En primer lugar hay que elaborar el protocolo de investigación, estuvimos viendo cómo se realizaba y las partes que lo constituían. Se hizo referencia a la importancia de la bibliografía.<br />
Para el próximo seminario es conveniente tener planeado el tema que queremos investigar porque vamos a proceder a la búsqueda bibliográfica. Rocío Romero Castillohttp://www.blogger.com/profile/12000531683527549788noreply@blogger.com0tag:blogger.com,1999:blog-9204560667939424211.post-19362392548393551752012-03-10T03:32:00.001-08:002012-03-15T01:23:08.699-07:00Tema 3. La etapa conceptual de la investigación.<br />
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Una buena investigación tiene que partir de unas buenas ideas. Depende de la capacidad del profesional para generarlas y para formular interrogantes. Es imprescindible realizar una búsqueda bibliográfica. También es importante analizar la pertinencia del estudio y la viabilidad o factibilidad. El profesor dijo que no estudiemos un tema que esté sobradamente investigado y comprobado, como por ejemplo la relación entre tabaco y problemas del aparato respiratorio. Tampoco debemos elegir un tema del que se sepa poco porque no encontraremos suficiente información ni cuestionarios efectivos.<br />
En este tema también vimos los puntos de guía para el desarrollo de la investigación, los aspectos a valorar en la justificación de un proyecto: pertinencia; y un decálogo con el que debemos contar a la hora de planear el tema de investigación.<br />
Comentamos que tenemos poco tiempo para realizar el estudio, esto nos limita algunos temas. Hay que ver con qué instalaciones y ayuda contamos. Otros factores de los que carecemos son recursos económicos y experiencia. En algunos estudios habrá que tener en cuenta las consideraciones éticas, tal vez haya que pedir permiso al centro.Rocío Romero Castillohttp://www.blogger.com/profile/12000531683527549788noreply@blogger.com1tag:blogger.com,1999:blog-9204560667939424211.post-82434344505073792292012-03-10T02:59:00.004-08:002012-03-15T01:27:18.765-07:00Tareas del campus<br />
El profesor nos puso la primera tarea en el campus. Consistía en identificar las etapas y los pasos dados en un artículo de investigación. Le dediqué mucho tiempo a esta actividad porque no tengo experiencia en analizar estos artículos. Pensé que la mejor forma de hacerlo era ir identificando en el artículo los pasos que se habían dado. Algunos pasos me resultaron un poco confusos.Rocío Romero Castillohttp://www.blogger.com/profile/12000531683527549788noreply@blogger.com0tag:blogger.com,1999:blog-9204560667939424211.post-4991513884639188372012-03-10T02:47:00.000-08:002012-03-15T01:23:08.705-07:00Tema 2. Fases del proceso de investigación.<br />
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El proceso de investigación se divide en tres etapas: conceptual, empírica e interpretativa. Cada una de las etapas tiene a su vez una serie de pasos que hay que seguir.<br />
La etapa conceptual es la fase teórica, esta etapa tenemos que seguir para elaborar el protocolo, que es la primera parte de nuestro proyecto de investigación.<br />
La etapa empírica es la más práctica del proceso, en ella tenemos que obtener los resultados y definir el enfoque o estrategia de abordaje del problema de investigación. Tenemos que elegir bien la población de estudio y hacer un muestreo en caso de que la población sea muy grande. Después se procede a la recogida y análisis de los datos.<br />
Por último tenemos la etapa interpretativa, en la que hay que convalidar los métodos empleados y los resultados, relacionar los hallazgos con los objetivos e hipótesis y tenemos de extraer conclusiones.<br />
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Después de esto vimos los errores que se podían producir en los estudios. Existen los errores aleatorios, que se cometen al azar, y los errores sistemáticos (sesgos). Nos detuvimos un tiempo en las medidas de control de los errores aleatorios.<br />
En los errores sistemáticos o sesgos estudiamos tres tipos: sesgos de selección de clasificación y de confusión.<br />
Se explicó la validez interna y externa de un estudio. Era muy importante que un estudio tuviera previamente validez interna, que consiste en la ausencia de sesgos para la población estudiada. La validez externa consiste en la capacidad de extrapolar los resultados del estudio en otras poblaciones.<br />
Después vimos la precisión y exactitud de un estudio.<br />
Finalmente se terminó el tema con el apartado de ética e investigación. Debemos respetar los principios éticos en el diseño, ejecución, análisis y difusión. Hay que tener en cuenta que para ciertos estudios se debe contar con la autorización de los comités éticos de los centros.Rocío Romero Castillohttp://www.blogger.com/profile/12000531683527549788noreply@blogger.com0tag:blogger.com,1999:blog-9204560667939424211.post-54212258492728818112012-03-10T02:25:00.000-08:002012-03-15T01:23:08.710-07:00Tema 1<br />
En este tema vimos las fuentes del conocimiento humano. En primer lugar estudiamos las "verdades aceptadas", que no están basadas en un conocimiento científico. Después se explicó en qué consistía el método científico. Estuvimos un rato hablando sobre la ciencia: pura o formal y aplicada o fáctica. Pienso que en esta asignatura nos vamos a centrar en la aplicada o fáctica que es la que se ocupa de la realidad y sus hipótesis se adecuan a los hechos. El método utilizado es la observación y experimentación.<br />
Estudiamos también las características del conocimiento científico y vimos que nos podíamos encontrar con cuatro problemas: complejidad, medición, control y ética.<br />
Vimos la metodología de investigación y analizamos un artículo original que trataba sobre un experimento donde se estudiaba qué era más efectivo: si una solución acuosa o un gel.Rocío Romero Castillohttp://www.blogger.com/profile/12000531683527549788noreply@blogger.com0