940 resultados para Integrated Crop-Livestock Systems
Resumo:
Emotion is generally argued to be an influence on the behavior of life systems, largely concerning flexibility and adaptivity. The way in which life systems acts in response to a particular situations of the environment, has revealed the decisive and crucial importance of this feature in the success of behaviors. And this source of inspiration has influenced the way of thinking artificial systems. During the last decades, artificial systems have undergone such an evolution that each day more are integrated in our daily life. They have become greater in complexity, and the subsequent effects are related to an increased demand of systems that ensure resilience, robustness, availability, security or safety among others. All of them questions that raise quite a fundamental challenges in control design. This thesis has been developed under the framework of the Autonomous System project, a.k.a the ASys-Project. Short-term objectives of immediate application are focused on to design improved systems, and the approaching of intelligence in control strategies. Besides this, long-term objectives underlying ASys-Project concentrate on high order capabilities such as cognition, awareness and autonomy. This thesis is placed within the general fields of Engineery and Emotion science, and provides a theoretical foundation for engineering and designing computational emotion for artificial systems. The starting question that has grounded this thesis aims the problem of emotion--based autonomy. And how to feedback systems with valuable meaning has conformed the general objective. Both the starting question and the general objective, have underlaid the study of emotion, the influence on systems behavior, the key foundations that justify this feature in life systems, how emotion is integrated within the normal operation, and how this entire problem of emotion can be explained in artificial systems. By assuming essential differences concerning structure, purpose and operation between life and artificial systems, the essential motivation has been the exploration of what emotion solves in nature to afterwards analyze analogies for man--made systems. This work provides a reference model in which a collection of entities, relationships, models, functions and informational artifacts, are all interacting to provide the system with non-explicit knowledge under the form of emotion-like relevances. This solution aims to provide a reference model under which to design solutions for emotional operation, but related to the real needs of artificial systems. The proposal consists of a multi-purpose architecture that implement two broad modules in order to attend: (a) the range of processes related to the environment affectation, and (b) the range or processes related to the emotion perception-like and the higher levels of reasoning. This has required an intense and critical analysis beyond the state of the art around the most relevant theories of emotion and technical systems, in order to obtain the required support for those foundations that sustain each model. The problem has been interpreted and is described on the basis of AGSys, an agent assumed with the minimum rationality as to provide the capability to perform emotional assessment. AGSys is a conceptualization of a Model-based Cognitive agent that embodies an inner agent ESys, the responsible of performing the emotional operation inside of AGSys. The solution consists of multiple computational modules working federated, and aimed at conforming a mutual feedback loop between AGSys and ESys. Throughout this solution, the environment and the effects that might influence over the system are described as different problems. While AGSys operates as a common system within the external environment, ESys is designed to operate within a conceptualized inner environment. And this inner environment is built on the basis of those relevances that might occur inside of AGSys in the interaction with the external environment. This allows for a high-quality separate reasoning concerning mission goals defined in AGSys, and emotional goals defined in ESys. This way, it is provided a possible path for high-level reasoning under the influence of goals congruence. High-level reasoning model uses knowledge about emotional goals stability, letting this way new directions in which mission goals might be assessed under the situational state of this stability. This high-level reasoning is grounded by the work of MEP, a model of emotion perception that is thought as an analogy of a well-known theory in emotion science. The work of this model is described under the operation of a recursive-like process labeled as R-Loop, together with a system of emotional goals that are assumed as individual agents. This way, AGSys integrates knowledge that concerns the relation between a perceived object, and the effect which this perception induces on the situational state of the emotional goals. This knowledge enables a high-order system of information that provides the sustain for a high-level reasoning. The extent to which this reasoning might be approached is just delineated and assumed as future work. This thesis has been studied beyond a long range of fields of knowledge. This knowledge can be structured into two main objectives: (a) the fields of psychology, cognitive science, neurology and biological sciences in order to obtain understanding concerning the problem of the emotional phenomena, and (b) a large amount of computer science branches such as Autonomic Computing (AC), Self-adaptive software, Self-X systems, Model Integrated Computing (MIC) or the paradigm of models@runtime among others, in order to obtain knowledge about tools for designing each part of the solution. The final approach has been mainly performed on the basis of the entire acquired knowledge, and described under the fields of Artificial Intelligence, Model-Based Systems (MBS), and additional mathematical formalizations to provide punctual understanding in those cases that it has been required. This approach describes a reference model to feedback systems with valuable meaning, allowing for reasoning with regard to (a) the relationship between the environment and the relevance of the effects on the system, and (b) dynamical evaluations concerning the inner situational state of the system as a result of those effects. And this reasoning provides a framework of distinguishable states of AGSys derived from its own circumstances, that can be assumed as artificial emotion.
Resumo:
En las últimas décadas, la agricultura sostenible ha sido objeto de gran interés y debate académico, no sólo en términos conceptuales, sino también en términos metodológicos. La persistencia de la inseguridad alimentaria y el deterioro de los recursos naturales en muchas regiones del mundo, ha provocado el surgimiento de numerosas iniciativas centradas en revitalizar la agricultura campesina así como renovadas discusiones sobre el rol que juega la agricultura como motor de desarrollo y principal actividad para alivio de la pobreza. Por ello, cuando hablamos de evaluar sistemas campesinos de montaña, debemos considerar tanto la dimensión alimentaria como las especificidades propias de los sistemas montañosos como base fundamental de la sostenibilidad. Al evaluar la contribución que han hecho alternativas tecnológicas y de manejo en la mejora de la sostenibilidad y la seguridad alimentaria de los sistemas campesinos de montaña en Mesoamérica, surgen tres preguntas de investigación: • ¿Se está evaluando la sostenibilidad de los sistemas campesinos teniendo en cuenta la variabilidad climática, la participación de los agricultores y las dinámicas temporales? • ¿Podemos rescatar tendencias comunes en estos sistemas y extrapolar los resultados a otras zonas? • ¿Son inequívocamente positivas las alternativas propuestas que se han llevado a cabo? En este trabajo se presentan tres evaluaciones de sostenibilidad que tratan de poner de manifiesto cuáles son los retos y oportunidades que enfrentan actualmente los sistemas campesinos de montaña. En primer lugar, se evalúan tres sistemas de manejo agrícola bajo dos años meteorológicamente contrastantes. Se determinó que durante el año que experimentó lluvias abundantes y temperaturas moderadas, los sistemas de bajos insumos, basados en el uso de abonos orgánicos y rotación de cultivos, obtuvieron los mejores resultados en indicadores ecológicos y similares resultados en los económicos y sociales que el sistema de altos insumos químicos. En el segundo año, con heladas tempranas y sequía invernal, la productividad se redujo para todos los sistemas pero los sistemas más diversificados (en variedades de maíz y/o siembra de otros cultivos) pudieron resistir mejor los contratiempos climáticos. En segundo lugar, se evalúa el grado de conocimiento (percepción) campesino para determinar los factores claves que determinan la sostenibilidad de sus sistemas y su seguridad alimentaria. Se determinó que los principales puntos críticos identificados por los campesinos (tamaño de parcela y pendiente del terreno) afectan de forma significativa a cuestiones de índole económica, pero no son capaces de explicar los desequilibrios alimenticios existentes. Realizando un análisis comparativo entre comunidades que presentaban buenos y malos resultados en cuanto a aporte energético y proteico, se determinó que la seguridad alimentaria estaba relacionada con la sostenibilidad de los sistemas y que concretamente estaba ligada a los atributos de equidad y autonomía. Otro resultado destacable fue que las comunidades más marginales y con mayor dificultad de acceso mostraron mayores niveles de inseguridad alimentaria, pero la variabilidad intergrupal fue muy alta. Eso demuestra que la seguridad alimentaria y nutricional forma parte de un complejo sistema de estrategias de autoabastecimiento ligada a la idiosincrasia misma de cada uno de los hogares. En tercer lugar, se evaluó el desempeño de las escuelas de campo de agricultores (ECAs) en la mejora de la sostenibilidad y la seguridad alimentaria de un sistema campesino de montaña. Para ver el efecto del impacto de estas metodologías a largo plazo, se estudiaron tres comunidades donde se habían implementado ECAs hace 8, 5 y 3 años. Encontramos que el impacto fue progresivo ya que fue la comunidad más antigua la que mejores valores obtuvo. El impacto de las ECAs fue rápido y persistente en los indicadores relacionados con la participación, el acceso a servicios básicos y la conservación de los recursos naturales. El estudio demostró un claro potencial de las ECAs en la mejora general de la sostenibilidad y la seguridad alimentaria de estos sistemas, sin embargo se observó una relación directa entre el aumento de producción agrícola y el uso de insumos externos, lo que puede suponer un punto crítico para los ideales sostenibles. ABSTRACT During the last decades, sustainable agriculture has been the subject of considerable academic interest and debate, not only in conceptual terms, but also in methodological ones. The persistence of high levels of environmental degradation and food insecurity in many regions has led to new initiatives focused on revitalizing peasant agriculture and renewed discussions of the role of sustainable agriculture as an engine for development, environmental conservation and poverty alleviation. Therefore, to assess mountain farming systems, we must consider food dimension and taking into account the specificities of the mountain systems as the foundation of sustainability. When evaluating contribution of technological and management alternative proposals in achieving sustainability and food security for peasant farming systems in Mesoamerican highlands, three research questions arise: • Is sustainability of peasant-farming systems being evaluated taking into account climate variability, participation of farmers and temporal dynamics? • Can we rescue common trends in these systems and extrapolate the results to other areas? • What alternative proposals that have been conducted are unequivocally positives? In this document, we present three evaluations of sustainability that try to highlight the challenges and opportunities that currently face mountain farming systems in Mesoamerica. First, we evaluate the sustainability of three agricultural management systems in two contrasting weather years. We determined that during the first year that exposed heavy rains and moderate temperatures, low-input systems, which are based on the use of organic fertilizers and crop rotation, provided better results in terms of ecological indicators and equal results in terms of economic and social indicators than those achieved using a high chemical input system. In the second year, which featured early frosts and a winter drought, productivity declined in all systems; however, the most diversified systems (in terms of the maize varieties grown and the sowing of other crops) more successfully resisted these climatic adversities. Second, we evaluate the farmers’ perception to determine the key drivers for achieving their sustainability and food and nutritional security. We determined that the key factors identified by farmers (landholding size and slope of cropland) exerted significant impacts on economic disparities but did not explain the malnutrition levels. We compared two contrasting hamlets according to their energy and protein supply, one namely Limón Timoté (LT), which did not present food problems and Limón Peña Blanca (LP), which did exhibit food insecurity. The results showed that FNS is linked to sustainability, and it is primarily related to the sustainability attributes of self-reliance and equity. Although the more marginated and inaccessible community exhibited more food insecurity, food and nutritional security depend upon a complex array of self-sufficiency strategies that remain linked to individual household idiosyncrasies. Third, we evaluated the impact of farmer field schools for improving the sustainability and food security of peasant mountain systems. In order to appreciate the long-term impact, we studied three communities where FFSs were implemented eight, five and three years ago, respectively. We found that FFSs have a gradual impact, as the community that first implemented FFSs scores highest. The impact of FFSs was broad and long-lasting for indicators related to participation, access to basic services and conservation of natural resources. This study demonstrates the potential of FFSs, but more attention will have to be paid to critical indicators in order to scale up their potential in the future. We observed a direct relationship between the increase in agricultural production and the use of external inputs, which is a critical point for sustainable ideals.
Resumo:
Vivimos una época en la que el mundo se transforma aceleradamente. La globalización está siguiendo un curso imparable, la población mundial así como la población urbana siguen creciendo, y en los países emergentes los ingresos promedios aumentan, resultando en un cambio también acelerado de las dietas y hábitos alimentarios. En conjunto esos factores están causando un aumento fundamental de la demanda de alimentos. Junto con la apertura de los mercados agrícolas, estos procesos han provocado un crecimiento del comercio internacional de alimentos durante la última década. Dado que muchos países de América Latina están dotados de abundancia de recursos naturales, estas tendencias han producido un crecimiento rápido de las exportaciones de bienes primarios desde América Latina al resto del mundo. En sólo 30 años la participación en el mercado agrícola de América Latina casi se ha duplicado, desde 10% en 1980 a 18% en 2010. Este aumento del comercio agrícola ha dado lugar a un debate sobre una serie de cuestiones cruciales relacionadas con los impactos del comercio en la seguridad alimentaria mundial, en el medio ambiente o en la reducción de la pobreza rural en países en desarrollo. Esta tesis aplica un marco integrado para analizar varios impactos relacionados con la transformación de los mercados agrícolas y los mercados rurales debidos a la globalización y, en particular, al progresivo aumento del comercio internacional. En concreto, la tesis aborda los siguientes temas: En primer lugar, la producción mundial de alimentos tendrá que aumentar considerablemente para poder satisfacer la demanda de una población mundial de 9000 millones personas en 2050, lo cual plantea grandes desafíos sobre los sistemas de la producción de alimentos. Alcanzar este logro, sin comprometer la integridad del medio ambiente en regiones exportadoras, es un reto aún mayor. En este contexto, la tesis analiza los efectos de la liberalización del comercio mundial, considerando distintas tecnologías de producción agraria, sobre unos indicadores de seguridad alimentaria en diferentes regiones del mundo y sobre distintos indicadores ambientales, teniendo en cuenta escalas diferentes en América Latina y el Caribe. La tesis utiliza el modelo “International Model for Policy Analysis of Agricultural Commodities and Trade (IMPACT)” – un modelo dinámico de equilibrio parcial del sector agrícola a escala global – para modelar la apertura de los mercados agrícolas así como diferentes escenarios de la producción hasta el año 2050. Los resultados del modelo están vinculados a modelos biofísicos para poder evaluar los cambios en la huella hídrica y la calidad del agua, así como para cuantificar los impactos del cambio en el uso del suelo sobre la biodiversidad y los stocks de carbono en 2050. Los resultados indican que la apertura de los mercados agrícolas es muy importante para mejorar la seguridad alimentaria a nivel mundial, sin embargo, produce también presiones ambientales indeseables en algunas regiones de América Latina. Contrastando dos escenarios que consideran distintas modos de producción, la expansión de la tierra agrícola frente a un escenario de la producción más intensiva, se demuestra que las mejoras de productividad son generalmente superiores a la expansión de las tierras agrícolas, desde un punto de vista económico e ambiental. En cambio, los escenarios de intensificación sostenible no sólo hacen posible una mayor producción de alimentos, sino que también generan menos impactos medioambientales que los otros escenarios futuros en todas sus dimensiones: biodiversidad, carbono, emisiones de nitratos y uso del agua. El análisis muestra que hay un “trade-off” entre el objetivo de alcanzar la sostenibilidad ambiental y el objetivo de la seguridad alimentaria, independiente del manejo agrícola en el futuro. En segundo lugar, a la luz de la reciente crisis de los precios de alimentos en los años 2007/08, la tesis analiza los impactos de la apertura de los mercados agrícolas en la transmisión de precios de los alimentos en seis países de América Latina: Argentina, Brasil, Chile, Colombia, México y el Perú. Para identificar las posibles relaciones de cointegración entre los índices de precios al consumidor de alimentos y los índices de precios de agrarios internacionales, sujetos a diferentes grados de apertura de mercados agrícolas en los seis países de América Latina, se utiliza un modelo simple de corrección de error (single equation error correction). Los resultados indican que la integración global de los mercados agrícolas ha dado lugar a diferentes tasas de transmisión de precios en los países investigados. Sobre todo en el corto plazo, las tasas de transmisión dependen del grado de apertura comercial, mientras que en el largo plazo las tasas de transmisión son elevadas, pero en gran medida independientes del régimen de comercio. Por lo tanto, durante un período de shocks de precios mundiales una mayor apertura del comercio trae consigo más inestabilidad de los precios domésticos a corto plazo y la resultante persistencia en el largo plazo. Sin embargo, estos resultados no verifican necesariamente la utilidad de las políticas comerciales, aplicadas frecuentemente por los gobiernos para amortiguar los shocks de precios. Primero, porque existe un riesgo considerable de volatilidad de los precios debido a cambios bruscos de la oferta nacional si se promueve la autosuficiencia en el país; y segundo, la política de proteccionismo asume el riesgo de excluir el país de participar en las cadenas de suministro de alto valor del sector agrícola, y por lo tanto esa política podría obstaculizar el desarrollo económico. Sin embargo, es indispensable establecer políticas efectivas para reducir la vulnerabilidad de los hogares a los aumentos repentinos de precios de alimentos, lo cual requiere una planificación gubernamental precisa con el presupuesto requerido disponible. En tercer lugar, la globalización afecta a la estructura de una economía y, por medios distintos, la distribución de los ingreso en un país. Perú sirve como ejemplo para investigar más profundamente las cuestiones relacionadas con los cambios en la distribución de los ingresos en zonas rurales. Perú, que es un país que está cada vez más integrado en los mercados mundiales, consiguió importantes descensos en la pobreza extrema en sus zonas rurales, pero a la vez adolece de alta incidencia de pobreza moderada y de desigualdad de los ingresos en zonas rural al menos durante el periodo comprendido entre 2004 y 2012. Esta parte de la tesis tiene como objetivo identificar las fuerzas impulsoras detrás de estas dinámicas en el Perú mediante el uso de un modelo de microsimulación basado en modelos de generación de ingresos aplicado a nivel los hogares rurales. Los resultados indican que la fuerza principal detrás de la reducción de la pobreza ha sido el crecimiento económico general de la economía, debido a las condiciones macroeconómicas favorables durante el periodo de estudio. Estos efectos de crecimiento beneficiaron a casi todos los sectores rurales, y dieron lugar a la disminución de la pobreza rural extrema, especialmente entre los agricultores de papas y de maíz. En parte, estos agricultores probablemente se beneficiaron de la apertura de los mercados agrícolas, que es lo que podría haber provocado un aumento de los precios al productor en tiempos de altos precios mundiales de los alimentos. Sin embargo, los resultados también sugieren que para una gran parte de la población más pobre existían barreras de entrada a la hora de poder participar en el empleo asalariado fuera de la agricultura o en la producción de cultivos de alto valor. Esto podría explicarse por la falta de acceso a unos activos importantes: por ejemplo, el nivel de educación de los pobres era apenas mejor en 2012 que en 2004; y también las dotaciones de tierra y de mano de obra, sobre todo de los productores pobres de maíz y patata, disminuyeron entre 2004 y 2012. Esto lleva a la conclusión de que aún hay margen para aplicar políticas para facilitar el acceso a estos activos, que podría contribuir a la erradicación de la pobreza rural. La tesis concluye que el comercio agrícola puede ser un importante medio para abastecer una población mundial creciente y más rica con una cantidad suficiente de calorías. Para evitar adversos efectos ambientales e impactos negativos para los consumidores y de los productores pobres, el enfoque debe centrarse en las mejoras de la productividad agrícola, teniendo en cuenta los límites ambientales y ser socialmente inclusivo. En este sentido, será indispensable seguir desarrollando soluciones tecnológicas que garanticen prácticas de producción agrícola minimizando el uso de recursos naturales. Además, para los pequeños pobres agricultores será fundamental eliminar las barreras de entrada a los mercados de exportación que podría tener efectos indirectos favorables a través de la adopción de nuevas tecnologías alcanzables a través de mercados internacionales. ABSTRACT The world is in a state of rapid transition. Ongoing globalization, population growth, rising living standards and increasing urbanization, accompanied by changing dietary patterns throughout the world, are increasing the demand for food. Together with more open trade regimes, this has triggered growing international agricultural trade during the last decade. For many Latin American countries, which are gifted with relative natural resource abundance, these trends have fueled rapid export growth of primary goods. In just 30 years, the Latin American agricultural market share has almost doubled from 10% in 1980 to 18% in 2010. These market developments have given rise to a debate around a number of crucial issues related to the role of agricultural trade for global food security, for the environment or for poverty reduction in developing countries. This thesis uses an integrated framework to analyze a broad array of possible impacts related to transforming agricultural and rural markets in light of globalization, and in particular of increasing trade activity. Specifically, the following issues are approached: First, global food production will have to rise substantially by the year 2050 to meet effective demand of a nine billion people world population which poses major challenges to food production systems. Doing so without compromising environmental integrity in exporting regions is an even greater challenge. In this context, the thesis explores the effects of future global trade liberalization on food security indicators in different world regions and on a variety of environmental indicators at different scales in Latin America and the Caribbean, in due consideration of different future agricultural production practices. The International Model for Policy Analysis of Agricultural Commodities and Trade (IMPACT) –a global dynamic partial equilibrium model of the agricultural sector developed by the International Food Policy Research Institute (IFPRI)– is applied to run different future production scenarios, and agricultural trade regimes out to 2050. Model results are linked to biophysical models, used to assess changes in water footprints and water quality, as well as impacts on biodiversity and carbon stocks from land use change by 2050. Results indicate that further trade liberalization is crucial for improving food security globally, but that it would also lead to more environmental pressures in some regions across Latin America. Contrasting land expansion versus more intensified agriculture shows that productivity improvements are generally superior to agricultural land expansion, from an economic and environmental point of view. Most promising for achieving food security and environmental goals, in equal measure, is the sustainable intensification scenario. However, the analysis shows that there are trade-offs between environmental and food security goals for all agricultural development paths. Second, in light of the recent food price crisis of 2007/08, the thesis looks at the impacts of increasing agricultural market integration on food price transmission from global to domestic markets in six Latin American countries, namely Argentina, Brazil, Chile, Colombia, Mexico and Peru. To identify possible cointegrating relationships between the domestic food consumer price indices and world food price levels, subject to different degrees of agricultural market integration in the six Latin American countries, a single equation error correction model is used. Results suggest that global agricultural market integration has led to different levels of price path-through in the studied countries. Especially in the short-run, transmission rates depend on the degree of trade openness, while in the long-run transmission rates are high, but largely independent of the country-specific trade regime. Hence, under world price shocks more trade openness brings with it more price instability in the short-term and the resulting persistence in the long-term. However, these findings do not necessarily verify the usefulness of trade policies, often applied by governments to buffer such price shocks. First, because there is a considerable risk of price volatility due to domestic supply shocks if self-sufficiency is promoted. Second, protectionism bears the risk of excluding a country from participating in beneficial high-value agricultural supply chains, thereby hampering economic development. Nevertheless, to reduce households’ vulnerability to sudden and large increases of food prices, effective policies to buffer food price shocks should be put in place, but must be carefully planned with the required budget readily available. Third, globalization affects the structure of an economy and, by different means, the distribution of income in a country. Peru serves as an example to dive deeper into questions related to changes in the income distribution in rural areas. Peru, a country being increasingly integrated into global food markets, experienced large drops in extreme rural poverty, but persistently high rates of moderate rural poverty and rural income inequality between 2004 and 2012. The thesis aims at disentangling the driving forces behind these dynamics by using a microsimulation model based on rural household income generation models. Results provide evidence that the main force behind poverty reduction was overall economic growth of the economy due to generally favorable macroeconomic market conditions. These growth effects benefited almost all rural sectors, and led to declines in extreme rural poverty, especially among potato and maize farmers. In part, these farmers probably benefited from policy changes towards more open trade regimes and the resulting higher producer prices in times of elevated global food price levels. However, the results also suggest that entry barriers existed for the poorer part of the population to participate in well-paid wage-employment outside of agriculture or in high-value crop production. This could be explained by a lack of sufficient access to important rural assets. For example, poor people’s educational attainment was hardly better in 2012 than in 2004. Also land and labor endowments, especially of (poor) maize and potato growers, rather decreased than increased over time. This leads to the conclusion that there is still scope for policy action to facilitate access to these assets, which could contribute to the eradication of rural poverty. The thesis concludes that agricultural trade can be one important means to provide a growing and richer world population with sufficient amounts of calories. To avoid adverse environmental effects and negative impacts for poor food consumers and producers, the focus should lie on agricultural productivity improvements, considering environmental limits and be socially inclusive. In this sense, it will be crucial to further develop technological solutions that guarantee resource-sparing agricultural production practices, and to remove entry barriers for small poor farmers to export markets which might allow for technological spill-over effects from high-value global agricultural supply chains.
Resumo:
La investigación de esta tesis se centra en el estudio de técnicas geoestadísticas y su contribución a una mayor caracterización del binomio factores climáticos-rendimiento de un cultivo agrícola. El inexorable vínculo entre la variabilidad climática y la producción agrícola cobra especial relevancia en estudios sobre el cambio climático o en la modelización de cultivos para dar respuesta a escenarios futuros de producción mundial. Es información especialmente valiosa en sistemas operacionales de monitoreo y predicción de rendimientos de cultivos Los cuales son actualmente uno de los pilares operacionales en los que se sustenta la agricultura y seguridad alimentaria mundial; ya que su objetivo final es el de proporcionar información imparcial y fiable para la regularización de mercados. Es en este contexto, donde se quiso dar un enfoque alternativo a estudios, que con distintos planteamientos, analizan la relación inter-anual clima vs producción. Así, se sustituyó la dimensión tiempo por la espacio, re-orientando el análisis estadístico de correlación interanual entre rendimiento y factores climáticos, por el estudio de la correlación inter-regional entre ambas variables. Se utilizó para ello una técnica estadística relativamente nueva y no muy aplicada en investigaciones similares, llamada regresión ponderada geográficamente (GWR, siglas en inglés de “Geographically weighted regression”). Se obtuvieron superficies continuas de las variables climáticas acumuladas en determinados periodos fenológicos, que fueron seleccionados por ser factores clave en el desarrollo vegetativo de un cultivo. Por ello, la primera parte de la tesis, consistió en un análisis exploratorio sobre comparación de Métodos de Interpolación Espacial (MIE). Partiendo de la hipótesis de que existe la variabilidad espacial de la relación entre factores climáticos y rendimiento, el objetivo principal de esta tesis, fue el de establecer en qué medida los MIE y otros métodos geoestadísticos de regresión local, pueden ayudar por un lado, a alcanzar un mayor entendimiento del binomio clima-rendimiento del trigo blando (Triticum aestivum L.) al incorporar en dicha relación el componente espacial; y por otro, a caracterizar la variación de los principales factores climáticos limitantes en el crecimiento del trigo blando, acumulados éstos en cuatro periodos fenológicos. Para lleva a cabo esto, una gran carga operacional en la investigación de la tesis consistió en homogeneizar y hacer los datos fenológicos, climáticos y estadísticas agrícolas comparables tanto a escala espacial como a escala temporal. Para España y los Bálticos se recolectaron y calcularon datos diarios de precipitación, temperatura máxima y mínima, evapotranspiración y radiación solar en las estaciones meteorológicas disponibles. Se dispuso de una serie temporal que coincidía con los mismos años recolectados en las estadísticas agrícolas, es decir, 14 años contados desde 2000 a 2013 (hasta 2011 en los Bálticos). Se superpuso la malla de información fenológica de cuadrícula 25 km con la ubicación de las estaciones meteorológicas con el fin de conocer los valores fenológicos en cada una de las estaciones disponibles. Hecho esto, para cada año de la serie temporal disponible se calcularon los valores climáticos diarios acumulados en cada uno de los cuatro periodos fenológicos seleccionados P1 (ciclo completo), P2 (emergencia-madurez), P3 (floración) y P4 (floraciónmadurez). Se calculó la superficie interpolada por el conjunto de métodos seleccionados en la comparación: técnicas deterministas convencionales, kriging ordinario y cokriging ordinario ponderado por la altitud. Seleccionados los métodos más eficaces, se calculó a nivel de provincias las variables climatológicas interpoladas. Y se realizaron las regresiones locales GWR para cuantificar, explorar y modelar las relaciones espaciales entre el rendimiento del trigo y las variables climáticas acumuladas en los cuatro periodos fenológicos. Al comparar la eficiencia de los MIE no destaca una técnica por encima del resto como la que proporcione el menor error en su predicción. Ahora bien, considerando los tres indicadores de calidad de los MIE estudiados se han identificado los métodos más efectivos. En el caso de la precipitación, es la técnica geoestadística cokriging la más idónea en la mayoría de los casos. De manera unánime, la interpolación determinista en función radial (spline regularizado) fue la técnica que mejor describía la superficie de precipitación acumulada en los cuatro periodos fenológicos. Los resultados son más heterogéneos para la evapotranspiración y radiación. Los métodos idóneos para estas se reparten entre el Inverse Distance Weighting (IDW), IDW ponderado por la altitud y el Ordinary Kriging (OK). También, se identificó que para la mayoría de los casos en que el error del Ordinary CoKriging (COK) era mayor que el del OK su eficacia es comparable a la del OK en términos de error y el requerimiento computacional de este último es mucho menor. Se pudo confirmar que existe la variabilidad espacial inter-regional entre factores climáticos y el rendimiento del trigo blando tanto en España como en los Bálticos. La herramienta estadística GWR fue capaz de reproducir esta variabilidad con un rendimiento lo suficientemente significativo como para considerarla una herramienta válida en futuros estudios. No obstante, se identificaron ciertas limitaciones en la misma respecto a la información que devuelve el programa a nivel local y que no permite desgranar todo el detalle sobre la ejecución del mismo. Los indicadores y periodos fenológicos que mejor pudieron reproducir la variabilidad espacial del rendimiento en España y Bálticos, arrojaron aún, una mayor credibilidad a los resultados obtenidos y a la eficacia del GWR, ya que estaban en línea con el conocimiento agronómico sobre el cultivo del trigo blando en sistemas agrícolas mediterráneos y norteuropeos. Así, en España, el indicador más robusto fue el balance climático hídrico Climatic Water Balance) acumulado éste, durante el periodo de crecimiento (entre la emergencia y madurez). Aunque se identificó la etapa clave de la floración como el periodo en el que las variables climáticas acumuladas proporcionaban un mayor poder explicativo del modelo GWR. Sin embargo, en los Bálticos, países donde el principal factor limitante en su agricultura es el bajo número de días de crecimiento efectivo, el indicador más efectivo fue la radiación acumulada a lo largo de todo el ciclo de crecimiento (entre la emergencia y madurez). Para el trigo en regadío no existe ninguna combinación que pueda explicar más allá del 30% de la variación del rendimiento en España. Poder demostrar que existe un comportamiento heterogéneo en la relación inter-regional entre el rendimiento y principales variables climáticas, podría contribuir a uno de los mayores desafíos a los que se enfrentan, a día de hoy, los sistemas operacionales de monitoreo y predicción de rendimientos de cultivos, y éste es el de poder reducir la escala espacial de predicción, de un nivel nacional a otro regional. ABSTRACT This thesis explores geostatistical techniques and their contribution to a better characterization of the relationship between climate factors and agricultural crop yields. The crucial link between climate variability and crop production plays a key role in climate change research as well as in crops modelling towards the future global production scenarios. This information is particularly important for monitoring and forecasting operational crop systems. These geostatistical techniques are currently one of the most fundamental operational systems on which global agriculture and food security rely on; with the final aim of providing neutral and reliable information for food market controls, thus avoiding financial speculation of nourishments of primary necessity. Within this context the present thesis aims to provide an alternative approach to the existing body of research examining the relationship between inter-annual climate and production. Therefore, the temporal dimension was replaced for the spatial dimension, re-orienting the statistical analysis of the inter-annual relationship between crops yields and climate factors to an inter-regional correlation between these two variables. Geographically weighted regression, which is a relatively new statistical technique and which has rarely been used in previous research on this topic was used in the current study. Continuous surface values of the climate accumulated variables in specific phenological periods were obtained. These specific periods were selected because they are key factors in the development of vegetative crop. Therefore, the first part of this thesis presents an exploratory analysis regarding the comparability of spatial interpolation methods (SIM) among diverse SIMs and alternative geostatistical methodologies. Given the premise that spatial variability of the relationship between climate factors and crop production exists, the primary aim of this thesis was to examine the extent to which the SIM and other geostatistical methods of local regression (which are integrated tools of the GIS software) are useful in relating crop production and climate variables. The usefulness of these methods was examined in two ways; on one hand the way this information could help to achieve higher production of the white wheat binomial (Triticum aestivum L.) by incorporating the spatial component in the examination of the above-mentioned relationship. On the other hand, the way it helps with the characterization of the key limiting climate factors of soft wheat growth which were analysed in four phenological periods. To achieve this aim, an important operational workload of this thesis consisted in the homogenization and obtention of comparable phenological and climate data, as well as agricultural statistics, which made heavy operational demands. For Spain and the Baltic countries, data on precipitation, maximum and minimum temperature, evapotranspiration and solar radiation from the available meteorological stations were gathered and calculated. A temporal serial approach was taken. These temporal series aligned with the years that agriculture statistics had previously gathered, these being 14 years from 2000 to 2013 (until 2011 for the Baltic countries). This temporal series was mapped with a phenological 25 km grid that had the location of the meteorological stations with the objective of obtaining the phenological values in each of the available stations. Following this procedure, the daily accumulated climate values for each of the four selected phenological periods were calculated; namely P1 (complete cycle), P2 (emergency-maturity), P3 (flowering) and P4 (flowering- maturity). The interpolated surface was then calculated using the set of selected methodologies for the comparison: deterministic conventional techniques, ordinary kriging and ordinary cokriging weighted by height. Once the most effective methods had been selected, the level of the interpolated climate variables was calculated. Local GWR regressions were calculated to quantify, examine and model the spatial relationships between soft wheat production and the accumulated variables in each of the four selected phenological periods. Results from the comparison among the SIMs revealed that no particular technique seems more favourable in terms of accuracy of prediction. However, when the three quality indicators of the compared SIMs are considered, some methodologies appeared to be more efficient than others. Regarding precipitation results, cokriging was the most accurate geostatistical technique for the majority of the cases. Deterministic interpolation in its radial function (controlled spline) was the most accurate technique for describing the accumulated precipitation surface in all phenological periods. However, results are more heterogeneous for the evapotranspiration and radiation methodologies. The most appropriate technique for these forecasts are the Inverse Distance Weighting (IDW), weighted IDW by height and the Ordinary Kriging (OK). Furthermore, it was found that for the majority of the cases where the Ordinary CoKriging (COK) error was larger than that of the OK, its efficacy was comparable to that of the OK in terms of error while the computational demands of the latter was much lower. The existing spatial inter-regional variability between climate factors and soft wheat production was confirmed for both Spain and the Baltic countries. The GWR statistic tool reproduced this variability with an outcome significative enough as to be considered a valid tool for future studies. Nevertheless, this tool also had some limitations with regards to the information delivered by the programme because it did not allow for a detailed break-down of its procedure. The indicators and phenological periods that best reproduced the spatial variability of yields in Spain and the Baltic countries made the results and the efficiency of the GWR statistical tool even more reliable, despite the fact that these were already aligned with the agricultural knowledge about soft wheat crop under mediterranean and northeuropean agricultural systems. Thus, for Spain, the most robust indicator was the Climatic Water Balance outcome accumulated throughout the growing period (between emergency and maturity). Although the flowering period was the phase that best explained the accumulated climate variables in the GWR model. For the Baltic countries where the main limiting agricultural factor is the number of days of effective growth, the most effective indicator was the accumulated radiation throughout the entire growing cycle (between emergency and maturity). For the irrigated soft wheat there was no combination capable of explaining above the 30% of variation of the production in Spain. The fact that the pattern of the inter-regional relationship between the crop production and key climate variables is heterogeneous within a country could contribute to one is one of the greatest challenges that the monitoring and forecasting operational systems for crop production face nowadays. The present findings suggest that the solution may lay in downscaling the spatial target scale from a national to a regional level.
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LLas nuevas tecnologías orientadas a la nube, el internet de las cosas o las tendencias "as a service" se basan en el almacenamiento y procesamiento de datos en servidores remotos. Para garantizar la seguridad en la comunicación de dichos datos al servidor remoto, y en el manejo de los mismos en dicho servidor, se hace uso de diferentes esquemas criptográficos. Tradicionalmente, dichos sistemas criptográficos se centran en encriptar los datos mientras no sea necesario procesarlos (es decir, durante la comunicación y almacenamiento de los mismos). Sin embargo, una vez es necesario procesar dichos datos encriptados (en el servidor remoto), es necesario desencriptarlos, momento en el cual un intruso en dicho servidor podría a acceder a datos sensibles de usuarios del mismo. Es más, este enfoque tradicional necesita que el servidor sea capaz de desencriptar dichos datos, teniendo que confiar en la integridad de dicho servidor de no comprometer los datos. Como posible solución a estos problemas, surgen los esquemas de encriptación homomórficos completos. Un esquema homomórfico completo no requiere desencriptar los datos para operar con ellos, sino que es capaz de realizar las operaciones sobre los datos encriptados, manteniendo un homomorfismo entre el mensaje cifrado y el mensaje plano. De esta manera, cualquier intruso en el sistema no podría robar más que textos cifrados, siendo imposible un robo de los datos sensibles sin un robo de las claves de cifrado. Sin embargo, los esquemas de encriptación homomórfica son, actualmente, drás-ticamente lentos comparados con otros esquemas de encriptación clásicos. Una op¬eración en el anillo del texto plano puede conllevar numerosas operaciones en el anillo del texto encriptado. Por esta razón, están surgiendo distintos planteamientos sobre como acelerar estos esquemas para un uso práctico. Una de las propuestas para acelerar los esquemas homomórficos consiste en el uso de High-Performance Computing (HPC) usando FPGAs (Field Programmable Gate Arrays). Una FPGA es un dispositivo semiconductor que contiene bloques de lógica cuya interconexión y funcionalidad puede ser reprogramada. Al compilar para FPGAs, se genera un circuito hardware específico para el algorithmo proporcionado, en lugar de hacer uso de instrucciones en una máquina universal, lo que supone una gran ventaja con respecto a CPUs. Las FPGAs tienen, por tanto, claras difrencias con respecto a CPUs: -Arquitectura en pipeline: permite la obtención de outputs sucesivos en tiempo constante -Posibilidad de tener multiples pipes para computación concurrente/paralela. Así, en este proyecto: -Se realizan diferentes implementaciones de esquemas homomórficos en sistemas basados en FPGAs. -Se analizan y estudian las ventajas y desventajas de los esquemas criptográficos en sistemas basados en FPGAs, comparando con proyectos relacionados. -Se comparan las implementaciones con trabajos relacionados New cloud-based technologies, the internet of things or "as a service" trends are based in data storage and processing in a remote server. In order to guarantee a secure communication and handling of data, cryptographic schemes are used. Tradi¬tionally, these cryptographic schemes focus on guaranteeing the security of data while storing and transferring it, not while operating with it. Therefore, once the server has to operate with that encrypted data, it first decrypts it, exposing unencrypted data to intruders in the server. Moreover, the whole traditional scheme is based on the assumption the server is reliable, giving it enough credentials to decipher data to process it. As a possible solution for this issues, fully homomorphic encryption(FHE) schemes is introduced. A fully homomorphic scheme does not require data decryption to operate, but rather operates over the cyphertext ring, keeping an homomorphism between the cyphertext ring and the plaintext ring. As a result, an outsider could only obtain encrypted data, making it impossible to retrieve the actual sensitive data without its associated cypher keys. However, using homomorphic encryption(HE) schemes impacts performance dras-tically, slowing it down. One operation in the plaintext space can lead to several operations in the cyphertext space. Because of this, different approaches address the problem of speeding up these schemes in order to become practical. One of these approaches consists in the use of High-Performance Computing (HPC) using FPGAs (Field Programmable Gate Array). An FPGA is an integrated circuit designed to be configured by a customer or a designer after manufacturing - hence "field-programmable". Compiling into FPGA means generating a circuit (hardware) specific for that algorithm, instead of having an universal machine and generating a set of machine instructions. FPGAs have, thus, clear differences compared to CPUs: - Pipeline architecture, which allows obtaining successive outputs in constant time. -Possibility of having multiple pipes for concurrent/parallel computation. Thereby, In this project: -We present different implementations of FHE schemes in FPGA-based systems. -We analyse and study advantages and drawbacks of the implemented FHE schemes, compared to related work.
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This paper analyses the effects of policy making for air pollution abatement in Spain between 2000 and 2020 under an integrated assessment approach with the AERIS model for number of pollutants (NOx/NO2, PM10/PM2.5, O3, SO2, NH3 and VOC). The analysis of the effects of air pollution focused on different aspects: compliance with the European limit values of Directive 2008/50/EC for NO2 and PM10 for the Spanish air quality management areas; the evaluation of impacts caused by the deposition of atmospheric sulphur and nitrogen on ecosystems; the exceedance of critical levels of NO2 and SO2 in forest areas; the analysis of O3-induced crop damage for grapes, maize, potato, rice, tobacco, tomato, watermelon and wheat; health impacts caused by human exposure to O3 and PM2.5; and costs on society due to crop losses (O3), disability-related absence of work staff and damage to buildings and public property due to soot-related soiling (PM2.5). In general, air quality policy making has delivered improvements in air quality levels throughout Spain and has mitigated the severity of the impacts on ecosystems, health and vegetation in 2020 as target year. The findings of this work constitute an appropriate diagnosis for identifying improvement potentials for further mitigation for policy makers and stakeholders in Spain.
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This paper presents a work whose objective is, first, to quantify the potential of the triticale biomass existing in each of the agricultural regions in the Madrid Community through a crop simulation model based on regression techniques and multiple correlation. Second, a methodology for defining which area has the best conditions for the installation of electricity plants from biomass has been described and applied. The study used a methodology based on compromise programming in a discrete multicriteria decision method (MDM) context. To make a ranking, the following criteria were taken into account: biomass potential, electric power infrastructure, road networks, protected spaces, and urban nuclei surfaces. The results indicate that, in the case of the Madrid Community, the Campiña region is the most suitable for setting up plants powered by biomass. A minimum of 17,339.9 tons of triticale will be needed to satisfy the requirements of a 2.2 MW power plant. The minimum range of action for obtaining the biomass necessary in Campiña region would be 6.6 km around the municipality of Algete, based on Geographic Information Systems. The total biomass which could be made available in considering this range in this region would be 18,430.68 t.
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An integrated understanding of molecular and developmental biology must consider the large number of molecular species involved and the low concentrations of many species in vivo. Quantitative stochastic models of molecular interaction networks can be expressed as stochastic Petri nets (SPNs), a mathematical formalism developed in computer science. Existing software can be used to define molecular interaction networks as SPNs and solve such models for the probability distributions of molecular species. This approach allows biologists to focus on the content of models and their interpretation, rather than their implementation. The standardized format of SPNs also facilitates the replication, extension, and transfer of models between researchers. A simple chemical system is presented to demonstrate the link between stochastic models of molecular interactions and SPNs. The approach is illustrated with examples of models of genetic and biochemical phenomena where the UltraSAN package is used to present results from numerical analysis and the outcome of simulations.
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Eventually to understand the integrated function of the cell cycle regulatory network, we must organize the known interactions in the form of a diagram, map, and/or database. A diagram convention was designed capable of unambiguous representation of networks containing multiprotein complexes, protein modifications, and enzymes that are substrates of other enzymes. To facilitate linkage to a database, each molecular species is symbolically represented only once in each diagram. Molecular species can be located on the map by means of indexed grid coordinates. Each interaction is referenced to an annotation list where pertinent information and references can be found. Parts of the network are grouped into functional subsystems. The map shows how multiprotein complexes could assemble and function at gene promoter sites and at sites of DNA damage. It also portrays the richness of connections between the p53-Mdm2 subsystem and other parts of the network.
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Recent predictions of growth in human populations and food supply suggest that there will be a need to substantially increase food production in the near future. One possible approach to meeting this demand, at least in part, is the control of pests and diseases, which currently cause a 30–40% loss in available crop production. In recent years, strategies for controlling pests and diseases have tended to focus on short-term, single-technology interventions, particularly chemical pesticides. This model frequently applies even where so-called integrated pest management strategies are used because in reality, these often are dominated by single technologies (e.g., biocontrol, host plant resistance, or biopesticides) that are used as replacements for chemicals. Very little attention is given to the interaction or compatibility of the different technologies used. Unfortunately, evidence suggests that such approaches rarely yield satisfactory results and are unlikely to provide sustainable pest control solutions for the future. Drawing on two case histories, this paper demonstrates that by increasing our basic understanding of how individual pest control technologies act and interact, new opportunities for improving pest control can be revealed. This approach stresses the need to break away from the existing single-technology, pesticide-dominated paradigm and to adopt a more ecological approach built around a fundamental understanding of population biology at the local farm level and the true integration of renewable technologies such as host plant resistance and natural biological control, which are available to even the most resource-poor farmers.