988 resultados para Field variables


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This doctoral thesis explores some of the possibilities that near-field optics can bring to photovoltaics, and in particular to quantum-dot intermediate band solar cells (QD-IBSCs). Our main focus is the analytical optimization of the electric field distribution produced in the vicinity of single scattering particles, in order to produce the highest possible absorption enhancement in the photovoltaic medium in their surroundings. Near-field scattering structures have also been fabricated in laboratory, allowing the application of the previously studied theoretical concepts to real devices. We start by looking into the electrostatic scattering regime, which is only applicable to sub-wavelength sized particles. In this regime it was found that metallic nano-spheroids can produce absorption enhancements of about two orders of magnitude on the material in their vicinity, due to their strong plasmonic resonance. The frequency of such resonance can be tuned with the shape of the particles, allowing us to match it with the optimal transition energies of the intermediate band material. Since these metallic nanoparticles (MNPs) are to be inserted inside the cell photovoltaic medium, they should be coated by a thin insulating layer to prevent electron-hole recombination at their surface. This analysis is then generalized, using an analytical separation-of-variables method implemented in Mathematica7.0, to compute scattering by spheroids of any size and material. This code allowed the study of the scattering properties of wavelengthsized particles (mesoscopic regime), and it was verified that in this regime dielectric spheroids perform better than metallic. The light intensity scattered from such dielectric spheroids can have more than two orders of magnitude than the incident intensity, and the focal region in front of the particle can be shaped in several ways by changing the particle geometry and/or material. Experimental work was also performed in this PhD to implement in practice the concepts studied in the analysis of sub-wavelength MNPs. A wet-coating method was developed to self-assemble regular arrays of colloidal MNPs on the surface of several materials, such as silicon wafers, amorphous silicon films, gallium arsenide and glass. A series of thermal and chemical tests have been performed showing what treatments the nanoparticles can withstand for their embedment in a photovoltaic medium. MNPs arrays are then inserted in an amorphous silicon medium to study the effect of their plasmonic near-field enhancement on the absorption spectrum of the material. The self-assembled arrays of MNPs constructed in these experiments inspired a new strategy for fabricating IBSCs using colloidal quantum dots (CQDs). Such CQDs can be deposited in self-assembled monolayers, using procedures similar to those developed for the patterning of colloidal MNPs. The use of CQDs to form the intermediate band presents several important practical and physical advantages relative to the conventional dots epitaxially grown by the Stranski-Krastanov method. Besides, this provides a fast and inexpensive method for patterning binary arrays of QDs and MNPs, envisioned in the theoretical part of this thesis, in which the MNPs act as antennas focusing the light in the QDs and therefore boosting their absorption

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We explore the near-field concentration properties of dielectric spheroidal scatterers with sizes close to the wavelength, using an analytical separation-of-variables method. Such particles act as mesoscopic lenses whose physical parameters are optimized here for maximum scattered light enhancement in photovoltaic applications.

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El estudio del comportamiento de la atmósfera ha resultado de especial importancia tanto en el programa SESAR como en NextGen, en los que la gestión actual del tránsito aéreo (ATM) está experimentando una profunda transformación hacia nuevos paradigmas tanto en Europa como en los EE.UU., respectivamente, para el guiado y seguimiento de las aeronaves en la realización de rutas más eficientes y con mayor precisión. La incertidumbre es una característica fundamental de los fenómenos meteorológicos que se transfiere a la separación de las aeronaves, las trayectorias de vuelo libres de conflictos y a la planificación de vuelos. En este sentido, el viento es un factor clave en cuanto a la predicción de la futura posición de la aeronave, por lo que tener un conocimiento más profundo y preciso de campo de viento reducirá las incertidumbres del ATC. El objetivo de esta tesis es el desarrollo de una nueva técnica operativa y útil destinada a proporcionar de forma adecuada y directa el campo de viento atmosférico en tiempo real, basada en datos de a bordo de la aeronave, con el fin de mejorar la predicción de las trayectorias de las aeronaves. Para lograr este objetivo se ha realizado el siguiente trabajo. Se han descrito y analizado los diferentes sistemas de la aeronave que proporcionan las variables necesarias para obtener la velocidad del viento, así como de las capacidades que permiten la presentación de esta información para sus aplicaciones en la gestión del tráfico aéreo. Se ha explorado el uso de aeronaves como los sensores de viento en un área terminal para la estimación del viento en tiempo real con el fin de mejorar la predicción de las trayectorias de aeronaves. Se han desarrollado métodos computacionalmente eficientes para estimar las componentes horizontales de la velocidad del viento a partir de las velocidades de las aeronaves (VGS, VCAS/VTAS), la presión y datos de temperatura. Estos datos de viento se han utilizado para estimar el campo de viento en tiempo real utilizando un sistema de procesamiento de datos a través de un método de mínima varianza. Por último, se ha evaluado la exactitud de este procedimiento para que esta información sea útil para el control del tráfico aéreo. La información inicial proviene de una muestra de datos de Registradores de Datos de Vuelo (FDR) de aviones que aterrizaron en el aeropuerto Madrid-Barajas. Se dispuso de datos de ciertas aeronaves durante un periodo de más de tres meses que se emplearon para calcular el vector viento en cada punto del espacio aéreo. Se utilizó un modelo matemático basado en diferentes métodos de interpolación para obtener los vectores de viento en áreas sin datos disponibles. Se han utilizado tres escenarios concretos para validar dos métodos de interpolación: uno de dos dimensiones que trabaja con ambas componentes horizontales de forma independiente, y otro basado en el uso de una variable compleja que relaciona ambas componentes. Esos métodos se han probado en diferentes escenarios con resultados dispares. Esta metodología se ha aplicado en un prototipo de herramienta en MATLAB © para analizar automáticamente los datos de FDR y determinar el campo vectorial del viento que encuentra la aeronave al volar en el espacio aéreo en estudio. Finalmente se han obtenido las condiciones requeridas y la precisión de los resultados para este modelo. El método desarrollado podría utilizar los datos de los aviones comerciales como inputs utilizando los datos actualmente disponibles y la capacidad computacional, para proporcionárselos a los sistemas ATM donde se podría ejecutar el método propuesto. Estas velocidades del viento calculadas, o bien la velocidad respecto al suelo y la velocidad verdadera, se podrían difundir, por ejemplo, a través del sistema de direccionamiento e informe para comunicaciones de aeronaves (ACARS), mensajes de ADS-B o Modo S. Esta nueva fuente ayudaría a actualizar la información del viento suministrada en los productos aeronáuticos meteorológicos (PAM), informes meteorológicos de aeródromos (AIRMET), e información meteorológica significativa (SIGMET). ABSTRACT The study of the atmosphere behaviour is been of particular importance both in SESAR and NextGen programs, where the current air traffic management (ATM) system is undergoing a profound transformation to the new paradigms both in Europe and the USA, respectively, to guide and track aircraft more precisely on more efficient routes. Uncertainty is a fundamental characteristic of weather phenomena which is transferred to separation assurance, flight path de-confliction and flight planning applications. In this respect, the wind is a key factor regarding the prediction of the future position of the aircraft, so that having a deeper and accurate knowledge of wind field will reduce ATC uncertainties. The purpose of this thesis is to develop a new and operationally useful technique intended to provide adequate and direct real-time atmospheric winds fields based on on-board aircraft data, in order to improve aircraft trajectory prediction. In order to achieve this objective the following work has been accomplished. The different sources in the aircraft systems that provide the variables needed to derivate the wind velocity have been described and analysed, as well as the capabilities which allow presenting this information for air traffic management applications. The use of aircraft as wind sensors in a terminal area for real-time wind estimation in order to improve aircraft trajectory prediction has been explored. Computationally efficient methods have been developed to estimate horizontal wind components from aircraft velocities (VGS, VCAS/VTAS), pressure, and temperature data. These wind data were utilized to estimate a real-time wind field using a data processing approach through a minimum variance method. Finally, the accuracy of this procedure has been evaluated for this information to be useful to air traffic control. The initial information comes from a Flight Data Recorder (FDR) sample of aircraft landing in Madrid-Barajas Airport. Data available for more than three months were exploited in order to derive the wind vector field in each point of the airspace. Mathematical model based on different interpolation methods were used in order to obtain wind vectors in void areas. Three particular scenarios were employed to test two interpolation methods: a two-dimensional one that works with both horizontal components in an independent way, and also a complex variable formulation that links both components. Those methods were tested using various scenarios with dissimilar results. This methodology has been implemented in a prototype tool in MATLAB © in order to automatically analyse FDR and determine the wind vector field that aircraft encounter when flying in the studied airspace. Required conditions and accuracy of the results were derived for this model. The method developed could be fed by commercial aircraft utilizing their currently available data sources and computational capabilities, and providing them to ATM system where the proposed method could be run. Computed wind velocities, or ground and true airspeeds, would then be broadcasted, for example, via the Aircraft Communication Addressing and Reporting System (ACARS), ADS-B out messages, or Mode S. This new source would help updating the wind information furnished in meteorological aeronautical products (PAM), meteorological aerodrome reports (AIRMET), and significant meteorological information (SIGMET).

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Este proyecto tiene como objetivo ampliar, mediante la caracterización espectral y multitemporal por técnicas de teledetección y medidas in situ, el estudio del corredor fluvial para el río Tinguiririca en Chile. Consiste en estudiar la cobertura del terreno, evaluar su dinámica de cambio e identificar zonas de acumulación de materiales de alteración hidrotermal arcillosos y óxidos de hierro, presentes en la cuenca durante las últimas tres décadas que puedan explicar su evolución temporal. Se pretenden obtener nuevas variables geoespaciales que ayuden a comprender las posibles causas de variación del cauce, elaborando cartografía para una posterior fase de investigación mediante modelización hidráulica que vaya dirigida a paliar el impacto de las riadas periódicas. Para ello, se han empleado, tratado y explotado imágenes de los sensores remotos TM, ETM+, OLI y TIRS tomadas en un período comprendido entre 1993 y 2014, que se han contrastado con perfiles batimétricos, datos GPS, supervisión y muestreo tomados sobre el terreno. Se ha realizado así mismo, un estudio prospectivo de caso sobre cómo afectarían las variables obtenidas por teledetección a la modelización hidráulica, en particular, la rugosidad, proponiendo un marco metodológico global de integración de las tres técnicas: sistemas de información geográfica, teledetección y modelización hidráulica. ABSTRACT This project aims to develop the study of Tinguiririca River corridor in Chile, through spectral characterization and multitemporal remote sensing and other measurements. This involves studying the land cover, its dynamic changes and identifies clayey materials and iron oxides accumulations of hydrothermal alteration, present in the basin during the last three decades to explain their evolution. It aims to obtain new geospatial variables in order to understand the possible causes of channel variation, developing mapping to a later research stage using hydraulic modeling so as to mitigate the impact of periodic floods. In this way, it has used processed and exploited images of TM, ETM +, OLI and TIRS remote sensing, taken in a period between 1993 and 2014 which it has been compared with bathymetric profiles, GPS, monitoring and sampling data collected in the field . It has done a prospective study about the variables obtained condition on hydraulic modeling, roughness in particular, proposing IX a complete methodological framework about the integration of the three techniques: geographic information systems, remote sensing and modeling hydraulics

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Energía termosolar (de concentración) es uno de los nombres que hacen referencia en español al término inglés “concentrating solar power”. Se trata de una tecnología basada en la captura de la potencia térmica de la radiación solar, de forma que permita alcanzar temperaturas capaces de alimentar un ciclo termodinámico convencional (o avanzado); el futuro de esta tecnología depende principalmente de su capacidad para concentrar la radiación solar de manera eficiente y económica. La presente tesis está orientada hacia la resolución de ciertos problemas importantes relacionados con este objetivo. La mencionada necesidad de reducir costes en la concentración de radiación solar directa, asegurando el objetivo termodinámico de calentar un fluido hasta una determinada temperatura, es de vital importancia. Los colectores lineales Fresnel han sido identificados en la literatura científica como una tecnología con gran potencial para alcanzar esta reducción de costes. Dicha tecnología ha sido seleccionada por numerosas razones, entre las que destacan su gran libertad de diseño y su actual estado inmaduro. Con el objetivo de responder a este desafío se desarrollado un detallado estudio de las propiedades ópticas de los colectores lineales Fresnel, para lo cual se han utilizado métodos analíticos y numéricos de manera combinada. En primer lugar, se han usado unos modelos para la predicción de la localización y la irradiación normal directa del sol junto a unas relaciones analíticas desarrolladas para estudiar el efecto de múltiples variables de diseño en la energía incidente sobre los espejos. Del mismo modo, se han obtenido analíticamente los errores debidos al llamado “off-axis aberration”, a la apertura de los rayos reflejados en los espejos y a las sombras y bloqueos entre espejos. Esto ha permitido la comparación de diferentes formas de espejo –planos, circulares o parabólicos–, así como el diseño preliminar de la localización y anchura de los espejos y receptor sin necesidad de costosos métodos numéricos. En segundo lugar, se ha desarrollado un modelo de trazado de rayos de Monte Carlo con el objetivo de comprobar la validez del estudio analítico, pero sobre todo porque este no es preciso en el estudio de la reflexión en espejos. El código desarrollado está específicamente ideado para colectores lineales Fresnel, lo que ha permitido la reducción del tiempo de cálculo en varios órdenes de magnitud en comparación con un programa comercial más general. Esto justifica el desarrollo de un nuevo código en lugar de la compra de una licencia de otro programa. El modelo ha sido usado primeramente para comparar la intensidad de flujo térmico y rendimiento de colectores Fresnel, con y sin reflector secundario, con los colectores cilíndrico parabólicos. Finalmente, la conjunción de los resultados obtenidos en el estudio analítico con el programa numérico ha sido usada para optimizar el campo solar para diferentes orientaciones –Norte-Sur y Este-Oeste–, diferentes localizaciones –Almería y Aswan–, diferentes inclinaciones hacia el Trópico –desde 0 deg hasta 32 deg– y diferentes mínimos de intensidad del flujo en el centro del receptor –10 kW/m2 y 25 kW/m2–. La presente tesis ha conducido a importantes descubrimientos que deben ser considerados a la hora de diseñar un campo solar Fresnel. En primer lugar, los espejos utilizados no deben ser plano, sino cilíndricos o parabólicos, ya que los espejos curvos implican mayores concentraciones y rendimiento. Por otro lado, se ha llegado a la conclusión de que la orientación Este-Oeste es más propicia para localizaciones con altas latitudes, como Almería, mientras que en zonas más cercanas a los trópicos como Aswan los campos Norte-Sur conducen a mayores rendimientos. Es de destacar que la orientación Este-Oeste requiere aproximadamente la mitad de espejos que los campos Norte-Sur, puediendo estar inclinados hacia los Trópicos para mejorar el rendimiento, y que alcanzan parecidos valores de intensidad térmica en el receptor todos los días a mediodía. Sin embargo, los campos con orientación Norte-Sur permiten un flujo más constante a lo largo de un día. Por último, ha sido demostrado que el uso de diseños pre-optimizados analíticamente, con anchura de espejos y espaciado entre espejos variables a lo ancho del campo, pueden implicar aumentos de la energía generada por metro cuadrado de espejos de hasta el 6%. El rendimiento óptico anual de los colectores cilíndrico parabólicos es 23 % mayor que el rendimiento de los campos Fresnel en Almería, mientras que la diferencia es de solo 9 % en Aswan. Ello implica que, para alcanzar el mismo precio de electricidad que la tecnología de referencia, la reducción de costes de instalación por metro cuadrado de espejo debe estar entre el 10 % y el 25 %, y que los colectores lineales Fresnel tienen más posibilidades de ser desarrollados en zonas de bajas latitudes. Como consecuencia de los estudios desarrollados en esta tesis se ha patentado un sistema de almacenamiento que tiene en cuenta la variación del flujo térmico en el receptor a lo largo del día, especialmente para campos con orientación Este-Oeste. Este invento permitiría el aprovechamiento de la energía incidente durante más parte del año, aumentando de manera apreciable los rendimientos óptico y térmico. Abstract Concentrating solar power is the common name of a technology based on capturing the thermal power of solar radiation, in a suitable way to reach temperatures able to activate a conventional (or advanced) thermodynamic cycle to generate electricity; this quest mainly depends on our ability to concentrate solar radiation in a cheap and efficient way. The present thesis is focused to highlight and help solving some of the important issues related to this problem. The need of reducing costs in concentrating the direct solar radiation, but without jeopardizing the thermodynamic objective of heating a fluid up to the required temperature, is of prime importance. Linear Fresnel collectors have been identified in the scientific literature as a technology with high potential to reach this cost reduction. This technology has been selected because of a number of reasons, particularly the degrees of freedom of this type of concentrating configuration and its current immature state. In order to respond to this challenge, a very detailed exercise has been carried out on the optical properties of linear Fresnel collectors. This has been done combining analytic and numerical methods. First, the effect of the design variables on the ratio of energy impinging onto the reflecting surface has been studied using analytically developed equations, together with models that predict the location and direct normal irradiance of the sun at any moment. Similarly, errors due to off-axis aberration, to the aperture of the reflected energy beam and to shading and blocking effects have been obtained analytically. This has allowed the comparison of different shapes of mirrors –flat, cylindrical or parabolic–, as well as a preliminary optimization of the location and width of mirrors and receiver with no need of time-consuming numerical models. Second, in order to prove the validity of the analytic results, but also due to the fact that the study of the reflection process is not precise enough when using analytic equations, a Monte Carlo Ray Trace model has been developed. The developed code is designed specifically for linear Fresnel collectors, which has reduced the computing time by several orders of magnitude compared to a wider commercial software. This justifies the development of the new code. The model has been first used to compare radiation flux intensities and efficiencies of linear Fresnel collectors, both multitube receiver and secondary reflector receiver technologies, with parabolic trough collectors. Finally, the results obtained in the analytic study together with the numeric model have used in order to optimize the solar field for different orientations –North-South and East-West–, different locations –Almería and Aswan–, different tilts of the field towards the Tropic –from 0 deg to 32 deg– and different flux intensity minimum requirements –10 kW/m2 and 25 kW/m2. This thesis work has led to several important findings that should be considered in the design of Fresnel solar fields. First, flat mirrors should not be used in any case, as cylindrical and parabolic mirrors lead to higher flux intensities and efficiencies. Second, it has been concluded that, in locations relatively far from the Tropics such as Almería, East-West embodiments are more efficient, while in Aswan North- South orientation leads to a higher annual efficiency. It must be noted that East-West oriented solar fields require approximately half the number of mirrors than NS oriented fields, can be tilted towards the Equator in order to increase the efficiency and attain similar values of flux intensity at the receiver every day at midday. On the other hand, in NS embodiments the flux intensity is more even during each single day. Finally, it has been proved that the use of analytic designs with variable shift between mirrors and variable width of mirrors across the field can lead to improvements in the electricity generated per reflecting surface square meter up to 6%. The annual optical efficiency of parabolic troughs has been found to be 23% higher than the efficiency of Fresnel fields in Almería, but it is only around 9% higher in Aswan. This implies that, in order to attain the same levelized cost of electricity than parabolic troughs, the required reduction of installation costs per mirror square meter is in the range of 10-25%. Also, it is concluded that linear Fresnel collectors are more suitable for low latitude areas. As a consequence of the studies carried out in this thesis, an innovative storage system has been patented. This system takes into account the variation of the flux intensity along the day, especially for East-West oriented solar fields. As a result, the invention would allow to exploit the impinging radiation along longer time every day, increasing appreciably the optical and thermal efficiencies.

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La presente Tesis constituye un avance en el conocimiento de los efectos de la variabilidad climática en los cultivos en la Península Ibérica (PI). Es bien conocido que la temperatura del océano, particularmente de la región tropical, es una de las variables más convenientes para ser utilizado como predictor climático. Los océanos son considerados como la principal fuente de almacenamiento de calor del planeta debido a la alta capacidad calorífica del agua. Cuando se libera esta energía, altera los regímenes globales de circulación atmosférica por mecanismos de teleconexión. Estos cambios en la circulación general de la atmósfera afectan a la temperatura, precipitación, humedad, viento, etc., a escala regional, los cuales afectan al crecimiento, desarrollo y rendimiento de los cultivos. Para el caso de Europa, esto implica que la variabilidad atmosférica en una región específica se asocia con la variabilidad de otras regiones adyacentes y/o remotas, como consecuencia Europa está siendo afectada por los patrones de circulaciones globales, que a su vez, se ven afectados por patrones oceánicos. El objetivo general de esta tesis es analizar la variabilidad del rendimiento de los cultivos y su relación con la variabilidad climática y teleconexiones, así como evaluar su predictibilidad. Además, esta Tesis tiene como objetivo establecer una metodología para estudiar la predictibilidad de las anomalías del rendimiento de los cultivos. El análisis se centra en trigo y maíz como referencia para otros cultivos de la PI, cultivos de invierno en secano y cultivos de verano en regadío respectivamente. Experimentos de simulación de cultivos utilizando una metodología en cadena de modelos (clima + cultivos) son diseñados para evaluar los impactos de los patrones de variabilidad climática en el rendimiento y su predictibilidad. La presente Tesis se estructura en dos partes: La primera se centra en el análisis de la variabilidad del clima y la segunda es una aplicación de predicción cuantitativa de cosechas. La primera parte está dividida en 3 capítulos y la segundo en un capitulo cubriendo los objetivos específicos del presente trabajo de investigación. Parte I. Análisis de variabilidad climática El primer capítulo muestra un análisis de la variabilidad del rendimiento potencial en una localidad como indicador bioclimático de las teleconexiones de El Niño con Europa, mostrando su importancia en la mejora de predictibilidad tanto en clima como en agricultura. Además, se presenta la metodología elegida para relacionar el rendimiento con las variables atmosféricas y oceánicas. El rendimiento de los cultivos es parcialmente determinado por la variabilidad climática atmosférica, que a su vez depende de los cambios en la temperatura de la superficie del mar (TSM). El Niño es el principal modo de variabilidad interanual de la TSM, y sus efectos se extienden en todo el mundo. Sin embargo, la predictibilidad de estos impactos es controversial, especialmente aquellos asociados con la variabilidad climática Europea, que se ha encontrado que es no estacionaria y no lineal. Este estudio mostró cómo el rendimiento potencial de los cultivos obtenidos a partir de datos de reanálisis y modelos de cultivos sirve como un índice alternativo y más eficaz de las teleconexiones de El Niño, ya que integra las no linealidades entre las variables climáticas en una única serie temporal. Las relaciones entre El Niño y las anomalías de rendimiento de los cultivos son más significativas que las contribuciones individuales de cada una de las variables atmosféricas utilizadas como entrada en el modelo de cultivo. Además, la no estacionariedad entre El Niño y la variabilidad climática europea se detectan con mayor claridad cuando se analiza la variabilidad de los rendimiento de los cultivos. La comprensión de esta relación permite una cierta predictibilidad hasta un año antes de la cosecha del cultivo. Esta predictibilidad no es constante, sino que depende tanto la modulación de la alta y baja frecuencia. En el segundo capítulo se identifica los patrones oceánicos y atmosféricos de variabilidad climática que afectan a los cultivos de verano en la PI. Además, se presentan hipótesis acerca del mecanismo eco-fisiológico a través del cual el cultivo responde. Este estudio se centra en el análisis de la variabilidad del rendimiento de maíz en la PI para todo el siglo veinte, usando un modelo de cultivo calibrado en 5 localidades españolas y datos climáticos de reanálisis para obtener series temporales largas de rendimiento potencial. Este estudio evalúa el uso de datos de reanálisis para obtener series de rendimiento de cultivos que dependen solo del clima, y utilizar estos rendimientos para analizar la influencia de los patrones oceánicos y atmosféricos. Los resultados muestran una gran fiabilidad de los datos de reanálisis. La distribución espacial asociada a la primera componente principal de la variabilidad del rendimiento muestra un comportamiento similar en todos los lugares estudiados de la PI. Se observa una alta correlación lineal entre el índice de El Niño y el rendimiento, pero no es estacionaria en el tiempo. Sin embargo, la relación entre la temperatura del aire y el rendimiento se mantiene constante a lo largo del tiempo, siendo los meses de mayor influencia durante el período de llenado del grano. En cuanto a los patrones atmosféricos, el patrón Escandinavia presentó una influencia significativa en el rendimiento en PI. En el tercer capítulo se identifica los patrones oceánicos y atmosféricos de variabilidad climática que afectan a los cultivos de invierno en la PI. Además, se presentan hipótesis acerca del mecanismo eco-fisiológico a través del cual el cultivo responde. Este estudio se centra en el análisis de la variabilidad del rendimiento de trigo en secano del Noreste (NE) de la PI. La variabilidad climática es el principal motor de los cambios en el crecimiento, desarrollo y rendimiento de los cultivos, especialmente en los sistemas de producción en secano. En la PI, los rendimientos de trigo son fuertemente dependientes de la cantidad de precipitación estacional y la distribución temporal de las mismas durante el periodo de crecimiento del cultivo. La principal fuente de variabilidad interanual de la precipitación en la PI es la Oscilación del Atlántico Norte (NAO), que se ha relacionado, en parte, con los cambios en la temperatura de la superficie del mar en el Pacífico Tropical (El Niño) y el Atlántico Tropical (TNA). La existencia de cierta predictibilidad nos ha animado a analizar la posible predicción de los rendimientos de trigo en la PI utilizando anomalías de TSM como predictor. Para ello, se ha utilizado un modelo de cultivo (calibrado en dos localidades del NE de la PI) y datos climáticos de reanálisis para obtener series temporales largas de rendimiento de trigo alcanzable y relacionar su variabilidad con anomalías de la TSM. Los resultados muestran que El Niño y la TNA influyen en el desarrollo y rendimiento del trigo en el NE de la PI, y estos impactos depende del estado concurrente de la NAO. Aunque la relación cultivo-TSM no es igual durante todo el periodo analizado, se puede explicar por un mecanismo eco-fisiológico estacionario. Durante la segunda mitad del siglo veinte, el calentamiento (enfriamiento) en la superficie del Atlántico tropical se asocia a una fase negativa (positiva) de la NAO, que ejerce una influencia positiva (negativa) en la temperatura mínima y precipitación durante el invierno y, por lo tanto, aumenta (disminuye) el rendimiento de trigo en la PI. En relación con El Niño, la correlación más alta se observó en el período 1981 -2001. En estas décadas, los altos (bajos) rendimientos se asocian con una transición El Niño - La Niña (La Niña - El Niño) o con eventos de El Niño (La Niña) que están finalizando. Para estos eventos, el patrón atmosférica asociada se asemeja a la NAO, que también influye directamente en la temperatura máxima y precipitación experimentadas por el cultivo durante la floración y llenado de grano. Los co- efectos de los dos patrones de teleconexión oceánicos ayudan a aumentar (disminuir) la precipitación y a disminuir (aumentar) la temperatura máxima en PI, por lo tanto el rendimiento de trigo aumenta (disminuye). Parte II. Predicción de cultivos. En el último capítulo se analiza los beneficios potenciales del uso de predicciones climáticas estacionales (por ejemplo de precipitación) en las predicciones de rendimientos de trigo y maíz, y explora métodos para aplicar dichos pronósticos climáticos en modelos de cultivo. Las predicciones climáticas estacionales tienen un gran potencial en las predicciones de cultivos, contribuyendo de esta manera a una mayor eficiencia de la gestión agrícola, seguridad alimentaria y de subsistencia. Los pronósticos climáticos se expresan en diferentes formas, sin embargo todos ellos son probabilísticos. Para ello, se evalúan y aplican dos métodos para desagregar las predicciones climáticas estacionales en datos diarios: 1) un generador climático estocástico condicionado (predictWTD) y 2) un simple re-muestreador basado en las probabilidades del pronóstico (FResampler1). Los dos métodos se evaluaron en un caso de estudio en el que se analizaron los impactos de tres escenarios de predicciones de precipitación estacional (predicción seco, medio y lluvioso) en el rendimiento de trigo en secano, sobre las necesidades de riego y rendimiento de maíz en la PI. Además, se estimó el margen bruto y los riesgos de la producción asociada con las predicciones de precipitación estacional extremas (seca y lluviosa). Los métodos predWTD y FResampler1 usados para desagregar los pronósticos de precipitación estacional en datos diarios, que serán usados como inputs en los modelos de cultivos, proporcionan una predicción comparable. Por lo tanto, ambos métodos parecen opciones factibles/viables para la vinculación de los pronósticos estacionales con modelos de simulación de cultivos para establecer predicciones de rendimiento o las necesidades de riego en el caso de maíz. El análisis del impacto en el margen bruto de los precios del grano de los dos cultivos (trigo y maíz) y el coste de riego (maíz) sugieren que la combinación de los precios de mercado previstos y la predicción climática estacional pueden ser una buena herramienta en la toma de decisiones de los agricultores, especialmente en predicciones secas y/o localidades con baja precipitación anual. Estos métodos permiten cuantificar los beneficios y riesgos de los agricultores ante una predicción climática estacional en la PI. Por lo tanto, seríamos capaces de establecer sistemas de alerta temprana y diseñar estrategias de adaptación del manejo del cultivo para aprovechar las condiciones favorables o reducir los efectos de condiciones adversas. La utilidad potencial de esta Tesis es la aplicación de las relaciones encontradas para predicción de cosechas de la próxima campaña agrícola. Una correcta predicción de los rendimientos podría ayudar a los agricultores a planear con antelación sus prácticas agronómicas y todos los demás aspectos relacionados con el manejo de los cultivos. Esta metodología se puede utilizar también para la predicción de las tendencias futuras de la variabilidad del rendimiento en la PI. Tanto los sectores públicos (mejora de la planificación agrícola) como privados (agricultores, compañías de seguros agrarios) pueden beneficiarse de esta mejora en la predicción de cosechas. ABSTRACT The present thesis constitutes a step forward in advancing of knowledge of the effects of climate variability on crops in the Iberian Peninsula (IP). It is well known that ocean temperature, particularly the tropical ocean, is one of the most convenient variables to be used as climate predictor. Oceans are considered as the principal heat storage of the planet due to the high heat capacity of water. When this energy is released, it alters the global atmospheric circulation regimes by teleconnection1 mechanisms. These changes in the general circulation of the atmosphere affect the regional temperature, precipitation, moisture, wind, etc., and those influence crop growth, development and yield. For the case of Europe, this implies that the atmospheric variability in a specific region is associated with the variability of others adjacent and/or remote regions as a consequence of Europe being affected by global circulations patterns which, in turn, are affected by oceanic patterns. The general objective of this Thesis is to analyze the variability of crop yields at climate time scales and its relation to the climate variability and teleconnections, as well as to evaluate their predictability. Moreover, this Thesis aims to establish a methodology to study the predictability of crop yield anomalies. The analysis focuses on wheat and maize as a reference crops for other field crops in the IP, for winter rainfed crops and summer irrigated crops respectively. Crop simulation experiments using a model chain methodology (climate + crop) are designed to evaluate the impacts of climate variability patterns on yield and its predictability. The present Thesis is structured in two parts. The first part is focused on the climate variability analyses, and the second part is an application of the quantitative crop forecasting for years that fulfill specific conditions identified in the first part. This Thesis is divided into 4 chapters, covering the specific objectives of the present research work. Part I. Climate variability analyses The first chapter shows an analysis of potential yield variability in one location, as a bioclimatic indicator of the El Niño teleconnections with Europe, putting forward its importance for improving predictability in both climate and agriculture. It also presents the chosen methodology to relate yield with atmospheric and oceanic variables. Crop yield is partially determined by atmospheric climate variability, which in turn depends on changes in the sea surface temperature (SST). El Niño is the leading mode of SST interannual variability, and its impacts extend worldwide. Nevertheless, the predictability of these impacts is controversial, especially those associated with European climate variability, which have been found to be non-stationary and non-linear. The study showed how potential2 crop yield obtained from reanalysis data and crop models serves as an alternative and more effective index of El Niño teleconnections because it integrates the nonlinearities between the climate variables in a unique time series. The relationships between El Niño and crop yield anomalies are more significant than the individual contributions of each of the atmospheric variables used as input in the crop model. Additionally, the non-stationarities between El Niño and European climate variability are more clearly detected when analyzing crop-yield variability. The understanding of this relationship allows for some predictability up to one year before the crop is harvested. This predictability is not constant, but depends on both high and low frequency modulation. The second chapter identifies the oceanic and atmospheric patterns of climate variability affecting summer cropping systems in the IP. Moreover, hypotheses about the eco-physiological mechanism behind crop response are presented. It is focused on an analysis of maize yield variability in IP for the whole twenty century, using a calibrated crop model at five contrasting Spanish locations and reanalyses climate datasets to obtain long time series of potential yield. The study tests the use of reanalysis data for obtaining only climate dependent time series of simulated crop yield for the whole region, and to use these yield to analyze the influences of oceanic and atmospheric patterns. The results show a good reliability of reanalysis data. The spatial distribution of the leading principal component of yield variability shows a similar behaviour over all the studied locations in the IP. The strong linear correlation between El Niño index and yield is remarkable, being this relation non-stationary on time, although the air temperature-yield relationship remains on time, being the highest influences during grain filling period. Regarding atmospheric patterns, the summer Scandinavian pattern has significant influence on yield in IP. The third chapter identifies the oceanic and atmospheric patterns of climate variability affecting winter cropping systems in the IP. Also, hypotheses about the eco-physiological mechanism behind crop response are presented. It is focused on an analysis of rainfed wheat yield variability in IP. Climate variability is the main driver of changes in crop growth, development and yield, especially for rainfed production systems. In IP, wheat yields are strongly dependent on seasonal rainfall amount and temporal distribution of rainfall during the growing season. The major source of precipitation interannual variability in IP is the North Atlantic Oscillation (NAO) which has been related in part with changes in the Tropical Pacific (El Niño) and Atlantic (TNA) sea surface temperature (SST). The existence of some predictability has encouraged us to analyze the possible predictability of the wheat yield in the IP using SSTs anomalies as predictor. For this purpose, a crop model with a site specific calibration for the Northeast of IP and reanalysis climate datasets have been used to obtain long time series of attainable wheat yield and relate their variability with SST anomalies. The results show that El Niño and TNA influence rainfed wheat development and yield in IP and these impacts depend on the concurrent state of the NAO. Although crop-SST relationships do not equally hold on during the whole analyzed period, they can be explained by an understood and stationary ecophysiological mechanism. During the second half of the twenty century, the positive (negative) TNA index is associated to a negative (positive) phase of NAO, which exerts a positive (negative) influence on minimum temperatures (Tmin) and precipitation (Prec) during winter and, thus, yield increases (decreases) in IP. In relation to El Niño, the highest correlation takes place in the period 1981-2001. For these decades, high (low) yields are associated with an El Niño to La Niña (La Niña to El Niño) transitions or to El Niño events finishing. For these events, the regional associated atmospheric pattern resembles the NAO, which also influences directly on the maximum temperatures (Tmax) and precipitation experienced by the crop during flowering and grain filling. The co-effects of the two teleconnection patterns help to increase (decrease) the rainfall and decrease (increase) Tmax in IP, thus on increase (decrease) wheat yield. Part II. Crop forecasting The last chapter analyses the potential benefits for wheat and maize yields prediction from using seasonal climate forecasts (precipitation), and explores methods to apply such a climate forecast to crop models. Seasonal climate prediction has significant potential to contribute to the efficiency of agricultural management, and to food and livelihood security. Climate forecasts come in different forms, but probabilistic. For this purpose, two methods were evaluated and applied for disaggregating seasonal climate forecast into daily weather realizations: 1) a conditioned stochastic weather generator (predictWTD) and 2) a simple forecast probability resampler (FResampler1). The two methods were evaluated in a case study where the impacts of three scenarios of seasonal rainfall forecasts on rainfed wheat yield, on irrigation requirements and yields of maize in IP were analyzed. In addition, we estimated the economic margins and production risks associated with extreme scenarios of seasonal rainfall forecasts (dry and wet). The predWTD and FResampler1 methods used for disaggregating seasonal rainfall forecast into daily data needed by the crop simulation models provided comparable predictability. Therefore both methods seem feasible options for linking seasonal forecasts with crop simulation models for establishing yield forecasts or irrigation water requirements. The analysis of the impact on gross margin of grain prices for both crops and maize irrigation costs suggests the combination of market prices expected and the seasonal climate forecast can be a good tool in farmer’s decision-making, especially on dry forecast and/or in locations with low annual precipitation. These methodologies would allow quantifying the benefits and risks of a seasonal weather forecast to farmers in IP. Therefore, we would be able to establish early warning systems and to design crop management adaptation strategies that take advantage of favorable conditions or reduce the effect of adverse conditions. The potential usefulness of this Thesis is to apply the relationships found to crop forecasting on the next cropping season, suggesting opportunity time windows for the prediction. The methodology can be used as well for the prediction of future trends of IP yield variability. Both public (improvement of agricultural planning) and private (decision support to farmers, insurance companies) sectors may benefit from such an improvement of crop forecasting.

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Each year, thousands of adolescents are processed through the juvenile justice system -- a system that is complicated, expensive, and inadequately addressing the needs of the youth in its care. While there is extensive literature available in support of interventions for youthful offenders that are clinically superior to current care and more cost-effective than the existing structure, there is a gap between research and practice that is preventing their implementation. The use of Evidence-Based Practice in Psychology (EBPP) as defined by the American Psychological Association is presented as one method to bridge this gap. This paper identifies and discusses each of five barriers to effective use of EBPP: cost, fragmentation of the mental health system, historical and systemic variables, research methodology, and clinician variables. These barriers are first defined and then illustrated using examples from the author's experience working in the juvenile justice field. Finally, recommendations for the field are presented.

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This data set describes the distribution of a total of 90 plant species growing on field margins of an agricultural landscape in the Haean-myun catchment in South Korea. We conducted our survey between July and August 2011 in 100 sampling plots, covering the whole catchment. In each plot we measured three environmental variables: slope, width of the field margin, and management type (i.e. "managed" for field margins that had signs of management activities from the ongoing season such as cutting or spraying herbicides and "unmanaged" for field margins that had been left untouched in the season). For the botanical survey each plot was sampled using three subplots of one square meter per subplot; subplots were 4 m apart from each other. In each subplot, we estimated three different vegetation characteristics: vegetation cover (i.e. the percentage of ground covered by vegetation), species richness (i.e. the number of observed species) and species abundance (i.e. the number of observed individuals / species). We calculated the percentage of the non-farmed habitats by creating buffer zones of 100, 200, 300, 400 and 500 m radii around each plot using data provided by (Seo et al. 2014). Non-farmed habitats included field margins, fallows, forest, riparian areas, pasture and grassland.

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We show that the projected Gross-Pitaevskii equation (PGPE) can be mapped exactly onto Hamilton's equations of motion for classical position and momentum variables. Making use of this mapping, we adapt techniques developed in statistical mechanics to calculate the temperature and chemical potential of a classical Bose field in the microcanonical ensemble. We apply the method to simulations of the PGPE, which can be used to represent the highly occupied modes of Bose condensed gases at finite temperature. The method is rigorous, valid beyond the realms of perturbation theory, and agrees with an earlier method of temperature measurement for the same system. Using this method we show that the critical temperature for condensation in a homogeneous Bose gas on a lattice with a uv cutoff increases with the interaction strength. We discuss how to determine the temperature shift for the Bose gas in the continuum limit using this type of calculation, and obtain a result in agreement with more sophisticated Monte Carlo simulations. We also consider the behavior of the specific heat.

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This study determined the relationship between two measures of field fertility of I I high-use Australian artificial insemination (AI) dairy bulls and thirty standard laboratory assessments of spermatozoal post-thaw viability. The two measures of field fertility used, conception rates (cCR) and non-return rates (cNRR), were both corrected for all major non-bull variables. Sperm viability assessments were conducted on semen collected within the same season as that used to derive the field fertility estimates. These assessments measured sperm concentration, motility, morphology and membrane integrity at thawing, after 2 h incubation and after the swim-up sperm selection procedure. Derivations of these measures and in vitro embryo fertilizing and developmental capacity were also determined. The Genstat Statistical Package [Genstat 5 Release 4.2 Reference Manual, VSN International, Oxford, 20001 was used to conduct an analysis of variance on the viability parameters across semen straws and bulls, and to calculate the strength of correlation between each semen parameter, cNRR and cCR in a correlation matrix. Step forward multiple regression identified the combination of semen parameters that were most highly correlated with cCR and with cNRR. The sperm parameters identified as being most predictive of cCR were the percentage of morphologically normal sperm immediately post-thaw (zeroNorm), the number of morphologically normal sperm after the swim-up procedure (nSuNorm), and the rate of zygote cleavage in vitro (Clv); the predictive equation formed by these parameters accounted for 70% of variance. The predictive equation produced for cNRR contained the variables zeroNorm, the proportion of membrane intact sperm after 2 h incubation at 37 degreesC (twoMem) and Clv and accounted for 76.5% of the variation. ZeroNorm was found to be consistent across straws and semen batches within-bull and the sperm parameter with the strongest individual predictive capacity for both cCR (P = 0.1) and cNRR (P = 0.001). Post-thaw sperm parameters can be used to predict field fertility of Australian dairy sires; the calculated predictive equations are particularly useful for identifying and monitoring bulls of very high and very low potential fertility within a group. (C) 2003 Elsevier B.V. All rights reserved.

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In many problems in spatial statistics it is necessary to infer a global problem solution by combining local models. A principled approach to this problem is to develop a global probabilistic model for the relationships between local variables and to use this as the prior in a Bayesian inference procedure. We show how a Gaussian process with hyper-parameters estimated from Numerical Weather Prediction Models yields meteorologically convincing wind fields. We use neural networks to make local estimates of wind vector probabilities. The resulting inference problem cannot be solved analytically, but Markov Chain Monte Carlo methods allow us to retrieve accurate wind fields.

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A major problem in modern probabilistic modeling is the huge computational complexity involved in typical calculations with multivariate probability distributions when the number of random variables is large. Because exact computations are infeasible in such cases and Monte Carlo sampling techniques may reach their limits, there is a need for methods that allow for efficient approximate computations. One of the simplest approximations is based on the mean field method, which has a long history in statistical physics. The method is widely used, particularly in the growing field of graphical models. Researchers from disciplines such as statistical physics, computer science, and mathematical statistics are studying ways to improve this and related methods and are exploring novel application areas. Leading approaches include the variational approach, which goes beyond factorizable distributions to achieve systematic improvements; the TAP (Thouless-Anderson-Palmer) approach, which incorporates correlations by including effective reaction terms in the mean field theory; and the more general methods of graphical models. Bringing together ideas and techniques from these diverse disciplines, this book covers the theoretical foundations of advanced mean field methods, explores the relation between the different approaches, examines the quality of the approximation obtained, and demonstrates their application to various areas of probabilistic modeling.

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In many problems in spatial statistics it is necessary to infer a global problem solution by combining local models. A principled approach to this problem is to develop a global probabilistic model for the relationships between local variables and to use this as the prior in a Bayesian inference procedure. We show how a Gaussian process with hyper-parameters estimated from Numerical Weather Prediction Models yields meteorologically convincing wind fields. We use neural networks to make local estimates of wind vector probabilities. The resulting inference problem cannot be solved analytically, but Markov Chain Monte Carlo methods allow us to retrieve accurate wind fields.

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The first part of the thesis compares Roth's method with other methods, in particular the method of separation of variables and the finite cosine transform method, for solving certain elliptic partial differential equations arising in practice. In particular we consider the solution of steady state problems associated with insulated conductors in rectangular slots. Roth's method has two main disadvantages namely the slow rate of con­vergence of the double Fourier series and the restrictive form of the allowable boundary conditions. A combined Roth-separation of variables method is derived to remove the restrictions on the form of the boundary conditions and various Chebyshev approximations are used to try to improve the rate of convergence of the series. All the techniques are then applied to the Neumann problem arising from balanced rectangular windings in a transformer window. Roth's method is then extended to deal with problems other than those resulting from static fields. First we consider a rectangular insulated conductor in a rectangular slot when the current is varying sinusoidally with time. An approximate method is also developed and compared with the exact method.The approximation is then used to consider the problem of an insulated conductor in a slot facing an air gap. We also consider the exact method applied to the determination of the eddy-current loss produced in an isolated rectangular conductor by a transverse magnetic field varying sinusoidally with time. The results obtained using Roth's method are critically compared with those obtained by other authors using different methods. The final part of the thesis investigates further the application of Chebyshdev methods to the solution of elliptic partial differential equations; an area where Chebyshev approximations have rarely been used. A poisson equation with a polynomial term is treated first followed by a slot problem in cylindrical geometry.

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Purpose: The aims of this study were to develop an algorithm to accurately quantify Vigabatrin (VGB)-induced central visual field loss and to investigate the relationship between visual field loss and maximum daily dose, cumulative dose and duration of dose. Methods: The sample comprised 31 patients (mean age 37.9 years; SD 14.4 years) diagnosed with epilepsy and exposed to VGB. Each participant underwent standard automated static visual field examination of the central visual field. Central visual field loss was determined using continuous scales quantifying severity in terms of area and depth of defect and additionally by symmetry of defect between the two eyes. A simultaneous multiple regression model was used to explore the relationship between these visual field parameters and the drug predictor variables. Results: The regression model indicated that maximum VGB dose was the only factor to be significantly correlated with individual eye severity (right eye: p = 0.020; left eye: p = 0.012) and symmetry of visual field defect (p = 0.024). Conclusions: Maximum daily dose was the single most reliable indicator of those patients likely to exhibit visual field defects due to VGB. These findings suggest that high maximum dose is more likely to result in visual field defects than high cumulative doses or those of long duration.