Three-dimensional mapping of real environments for cognitive robots navigation

Abstract The development of cognitive robots needs a strong “sensorial” support which should allow it to perceive the real world for interacting with it properly. Therefore the development of efficient visual-processing software to be equipped in effective artificial agents is a must. In this project we study and develop a visual-processing software that will work as the “eyes” of a cognitive robot. This software performs a three-dimensional mapping of the robot’s environment, providing it with the essential information required to make proper decisions during its navigation. Due to the complexity of this objective we have adopted the Scrum methodology in order to achieve an agile development process, which has allowed us to correct and improve in a fast way the successive versions of the product. The present project is structured in Sprints, which cover the different stages of the software development based on the requirements imposed by the robot and its real necessities. We have initially explored different commercial devices oriented to the acquisition of the required visual information, adopting the Kinect Sensor camera (Microsoft) as the most suitable option. Later on, we have studied the available software to manage the obtained visual information as well as its integration with the robot’s software, choosing the high-level platform Matlab as the common nexus to join the management of the camera, the management of the robot and the implementation of the behavioral algorithms. During the last stages the software has been developed to include the fundamental functionalities required to process the real environment, such as depth representation, segmentation, and clustering. Finally the software has been optimized to exhibit real-time processing and a suitable performance to fulfill the robot’s requirements during its operation in real situations.

Multimodal integration of functional and structural brain connectivity. An application to the characterization of Mild Cognitive Impairment

La investigación para el conocimiento del cerebro es una ciencia joven, su inicio se remonta a Santiago Ramón y Cajal en 1888. Desde esta fecha a nuestro tiempo la neurociencia ha avanzado mucho en el desarrollo de técnicas que permiten su estudio. Desde la neurociencia cognitiva hoy se explican muchos modelos que nos permiten acercar a nuestro entendimiento a capacidades cognitivas complejas. Aun así hablamos de una ciencia casi en pañales que tiene un lago recorrido por delante. Una de las claves del éxito en los estudios de la función cerebral ha sido convertirse en una disciplina que combina conocimientos de diversas áreas: de la física, de las matemáticas, de la estadística y de la psicología. Esta es la razón por la que a lo largo de este trabajo se entremezclan conceptos de diferentes campos con el objetivo de avanzar en el conocimiento de un tema tan complejo como el que nos ocupa: el entendimiento de la mente humana. Concretamente, esta tesis ha estado dirigida a la integración multimodal de la magnetoencefalografía (MEG) y la resonancia magnética ponderada en difusión (dMRI). Estas técnicas son sensibles, respectivamente, a los campos magnéticos emitidos por las corrientes neuronales, y a la microestructura de la materia blanca cerebral. A lo largo de este trabajo hemos visto que la combinación de estas técnicas permiten descubrir sinergias estructurofuncionales en el procesamiento de la información en el cerebro sano y en el curso de patologías neurológicas. Más específicamente en este trabajo se ha estudiado la relación entre la conectividad funcional y estructural y en cómo fusionarlas. Para ello, se ha cuantificado la conectividad funcional mediante el estudio de la sincronización de fase o la correlación de amplitudes entre series temporales, de esta forma se ha conseguido un índice que mide la similitud entre grupos neuronales o regiones cerebrales. Adicionalmente, la cuantificación de la conectividad estructural a partir de imágenes de resonancia magnética ponderadas en difusión, ha permitido hallar índices de la integridad de materia blanca o de la fuerza de las conexiones estructurales entre regiones. Estas medidas fueron combinadas en los capítulos 3, 4 y 5 de este trabajo siguiendo tres aproximaciones que iban desde el nivel más bajo al más alto de integración. Finalmente se utilizó la información fusionada de MEG y dMRI para la caracterización de grupos de sujetos con deterioro cognitivo leve, la detección de esta patología resulta relevante en la identificación precoz de la enfermedad de Alzheimer. Esta tesis está dividida en seis capítulos. En el capítulos 1 se establece un contexto para la introducción de la connectómica dentro de los campos de la neuroimagen y la neurociencia. Posteriormente en este capítulo se describen los objetivos de la tesis, y los objetivos específicos de cada una de las publicaciones científicas que resultaron de este trabajo. En el capítulo 2 se describen los métodos para cada técnica que fue empleada: conectividad estructural, conectividad funcional en resting state, redes cerebrales complejas y teoría de grafos y finalmente se describe la condición de deterioro cognitivo leve y el estado actual en la búsqueda de nuevos biomarcadores diagnósticos. En los capítulos 3, 4 y 5 se han incluido los artículos científicos que fueron producidos a lo largo de esta tesis. Estos han sido incluidos en el formato de la revista en que fueron publicados, estando divididos en introducción, materiales y métodos, resultados y discusión. Todos los métodos que fueron empleados en los artículos están descritos en el capítulo 2 de la tesis. Finalmente, en el capítulo 6 se concluyen los resultados generales de la tesis y se discuten de forma específica los resultados de cada artículo. ABSTRACT In this thesis I apply concepts from mathematics, physics and statistics to the neurosciences. This field benefits from the collaborative work of multidisciplinary teams where physicians, psychologists, engineers and other specialists fight for a common well: the understanding of the brain. Research on this field is still in its early years, being its birth attributed to the neuronal theory of Santiago Ramo´n y Cajal in 1888. In more than one hundred years only a very little percentage of the brain functioning has been discovered, and still much more needs to be explored. Isolated techniques aim at unraveling the system that supports our cognition, nevertheless in order to provide solid evidence in such a field multimodal techniques have arisen, with them we will be able to improve current knowledge about human cognition. Here we focus on the multimodal integration of magnetoencephalography (MEG) and diffusion weighted magnetic resonance imaging. These techniques are sensitive to the magnetic fields emitted by the neuronal currents and to the white matter microstructure, respectively. The combination of such techniques could bring up evidences about structural-functional synergies in the brain information processing and which part of this synergy fails in specific neurological pathologies. In particular, we are interested in the relationship between functional and structural connectivity, and how two integrate this information. We quantify the functional connectivity by studying the phase synchronization or the amplitude correlation between time series obtained by MEG, and so we get an index indicating similarity between neuronal entities, i.e. brain regions. In addition we quantify structural connectivity by performing diffusion tensor estimation from the diffusion weighted images, thus obtaining an indicator of the integrity of the white matter or, if preferred, the strength of the structural connections between regions. These quantifications are then combined following three different approaches, from the lowest to the highest level of integration, in chapters 3, 4 and 5. We finally apply the fused information to the characterization or prediction of mild cognitive impairment, a clinical entity which is considered as an early step in the continuum pathological process of dementia. The dissertation is divided in six chapters. In chapter 1 I introduce connectomics within the fields of neuroimaging and neuroscience. Later in this chapter we describe the objectives of this thesis, and the specific objectives of each of the scientific publications that were produced as result of this work. In chapter 2 I describe the methods for each of the techniques that were employed, namely structural connectivity, resting state functional connectivity, complex brain networks and graph theory, and finally, I describe the clinical condition of mild cognitive impairment and the current state of the art in the search for early biomarkers. In chapters 3, 4 and 5 I have included the scientific publications that were generated along this work. They have been included in in their original format and they contain introduction, materials and methods, results and discussion. All methods that were employed in these papers have been described in chapter 2. Finally, in chapter 6 I summarize all the results from this thesis, both locally for each of the scientific publications and globally for the whole work.

A game theory based strategy for reducing energy consumption in cognitive WSN

Wireless sensor networks (WSNs) are one of the most important users of wireless communication technologies in the coming years and some challenges in this area must be addressed for their complete development. Energy consumption and spectrum availability are two of the most severe constraints of WSNs due to their intrinsic nature. The introduction of cognitive capabilities into these networks has arisen to face the issue of spectrum scarcity but could be used to face energy challenges too due to their new range of communication possibilities. In this paper a new strategy based on game theory for cognitive WSNs is discussed. The presented strategy improves energy consumption by taking advantage of the new change-communication-channel capability. Based on game theory, the strategy decides when to change the transmission channel depending on the behavior of the rest of the network nodes. The strategy presented is lightweight but still has higher energy saving rates as compared to noncognitive networks and even to other strategies based on scheduled spectrum sensing. Simulations are presented for several scenarios that demonstrate energy saving rates of around 65% as compared to WSNs without cognitive techniques.

Assessment methodology applied to demand measures to change urban mobility behavior

In order to minimize car-based trips, transport planners have been particularly interested in understanding the factors that explain modal choices. Transport modelling literature has been increasingly aware that socioeconomic attributes and quantitative variables are not sufficient to characterize travelers and forecast their travel behavior. Recent studies have also recognized that users’ social interactions and land use patterns influence travel behavior, especially when changes to transport systems are introduced; but links between international and Spanish perspectives are rarely dealt with. The overall objective of the thesis is to develop a stepped methodology that integrate diverse perspectives to evaluate the willingness to change patterns of urban mobility in Madrid, based on four steps: (1st) analysis of causal relationships between both objective and subjective personal variables, and travel behavior to capture pro-car and pro-public transport intentions; (2nd) exploring the potential influence of individual trip characteristics and social influence variables on transport mode choice; (3rd) identifying built environment dimensions on travel behavior; and (4th) exploring the potential influence on transport mode choice of extrinsic characteristics of individual trip using panel data, land use variables using spatial characteristics and social influence variables. The data used for this thesis have been collected from a two panel smartphone-based survey (n=255 and 190 respondents, respectively) carried out in Madrid. Although the steps above are mainly methodological, the application to the area of Madrid allows deriving important results that can be directly used to forecast travel demand and to evaluate the benefits of specific policies that might be implemented in the area. The results demonstrated, respectively: (1st) transport policy actions are more likely to be effective when pro-car intention has been disrupted first; (2nd) the consideration of “helped” and “voluntary” users as tested here could have a positive and negative impact, respectively, on the use of public transport; (3rd) the importance of density, design, diversity and accessibility underlying dimensions responsible for land use variables; and (4th) there are clearly different types of combinations of social interactions, land use and time frame on travel behavior studies. Finally, with the objective to study the impact of demand measures to change urban mobility behavior, those previous results have been considered in a unique way, a hybrid discrete choice model has been used on a 5th step. Then it can be concluded that urban mobility behavior is not only ruled by the maximum utility criterion, but also by a strong psychological-environment concept, developed without the mediation of cognitive processes during choice, i.e., many people using public transport on their way to work do not do it for utilitarian reasons, but because no other choice is available. Regarding built environment dimensions, the more diversity place of residence, the more difficult the use of public transport or walking.

Cognitive risk perception system for obstacle avoidance in outdoor mUAV missions

La robótica ha evolucionado exponencialmente en las últimas décadas, permitiendo a los sistemas actuales realizar tareas sumamente complejas con gran precisión, fiabilidad y velocidad. Sin embargo, este desarrollo ha estado asociado a un mayor grado de especialización y particularización de las tecnologías implicadas, siendo estas muy eficientes en situaciones concretas y controladas, pero incapaces en entornos cambiantes, dinámicos y desestructurados. Por eso, el desarrollo de la robótica debe pasar por dotar a los sistemas de capacidad de adaptación a las circunstancias, de entendedimiento sobre los cambios observados y de flexibilidad a la hora de interactuar con el entorno. Estas son las caracteristicas propias de la interacción del ser humano con su entorno, las que le permiten sobrevivir y las que pueden proporcionar a un sistema inteligencia y capacidad suficientes para desenvolverse en un entorno real de forma autónoma e independiente. Esta adaptabilidad es especialmente importante en el manejo de riesgos e incetidumbres, puesto que es el mecanismo que permite contextualizar y evaluar las amenazas para proporcionar una respuesta adecuada. Así, por ejemplo, cuando una persona se mueve e interactua con su entorno, no evalúa los obstáculos en función de su posición, velocidad o dinámica (como hacen los sistemas robóticos tradicionales), sino mediante la estimación del riesgo potencial que estos elementos suponen para la persona. Esta evaluación se consigue combinando dos procesos psicofísicos del ser humano: por un lado, la percepción humana analiza los elementos relevantes del entorno, tratando de entender su naturaleza a partir de patrones de comportamiento, propiedades asociadas u otros rasgos distintivos. Por otro lado, como segundo nivel de evaluación, el entendimiento de esta naturaleza permite al ser humano conocer/estimar la relación de los elementos con él mismo, así como sus implicaciones en cuanto a nivel de riesgo se refiere. El establecimiento de estas relaciones semánticas -llamado cognición- es la única forma de definir el nivel de riesgo de manera absoluta y de generar una respuesta adecuada al mismo. No necesariamente proporcional, sino coherente con el riesgo al que se enfrenta. La investigación que presenta esta tesis describe el trabajo realizado para trasladar esta metodología de análisis y funcionamiento a la robótica. Este se ha centrado especialmente en la nevegación de los robots aéreos, diseñando e implementado procedimientos de inspiración humana para garantizar la seguridad de la misma. Para ello se han estudiado y evaluado los mecanismos de percepción, cognición y reacción humanas en relación al manejo de riesgos. También se ha analizado como los estímulos son capturados, procesados y transformados por condicionantes psicológicos, sociológicos y antropológicos de los seres humanos. Finalmente, también se ha analizado como estos factores motivan y descandenan las reacciones humanas frente a los peligros. Como resultado de este estudio, todos estos procesos, comportamientos y condicionantes de la conducta humana se han reproducido en un framework que se ha estructurado basadandose en factores análogos. Este emplea el conocimiento obtenido experimentalmente en forma de algoritmos, técnicas y estrategias, emulando el comportamiento humano en las mismas circunstancias. Diseñado, implementeado y validado tanto en simulación como con datos reales, este framework propone una manera innovadora -tanto en metodología como en procedimiento- de entender y reaccionar frente a las amenazas potenciales de una misión robótica. ABSTRACT Robotics has undergone a great revolution in the last decades. Nowadays this technology is able to perform really complex tasks with a high degree of accuracy and speed, however this is only true in precisely defined situations with fully controlled variables. Since the real world is dynamic, changing and unstructured, flexible and non context-dependent systems are required. The ability to understand situations, acknowledge changes and balance reactions is required by robots to successfully interact with their surroundings in a fully autonomous fashion. In fact, it is those very processes that define human interactions with the environment. Social relationships, driving or risk/incertitude management... in all these activities and systems, context understanding and adaptability are what allow human beings to survive: contrarily to the traditional robotics, people do not evaluate obstacles according to their position but according to the potential risk their presence imply. In this sense, human perception looks for information which goes beyond location, speed and dynamics (the usual data used in traditional obstacle avoidance systems). Specific features in the behaviour of a particular element allows the understanding of that element’s nature and therefore the comprehension of the risk posed by it. This process defines the second main difference between traditional obstacle avoidance systems and human behaviour: the ability to understand a situation/scenario allows to get to know the implications of the elements and their relationship with the observer. Establishing these semantic relationships -named cognition- is the only way to estimate the actual danger level of an element. Furthermore, only the application of this knowledge allows the generation of coherent, suitable and adjusted responses to deal with any risk faced. The research presented in this thesis summarizes the work done towards translating these human cognitive/reasoning procedures to the field of robotics. More specifically, the work done has been focused on employing human-based methodologies to enable aerial robots to navigate safely. To this effect, human perception, cognition and reaction processes concerning risk management have been experimentally studied; as well as the acquisition and processing of stimuli. How psychological, sociological and anthropological factors modify, balance and give shape to those stimuli has been researched. And finally, the way in which these factors motivate the human behaviour according to different mindsets and priorities has been established. This associative workflow has been reproduced by establishing an equivalent structure and defining similar factors and sources. Besides, all the knowledge obtained experimentally has been applied in the form of algorithms, techniques and strategies which emulate the analogous human behaviours. As a result, a framework capable of understanding and reacting in response to stimuli has been implemented and validated.

Exploring strategic farming choices to respond to mitigation and adaptation to climate change

Las alteraciones del sistema climático debido al aumento de concentraciones de gases de efecto invernadero (GEI) en la atmósfera, tendrán implicaciones importantes para la agricultura, el medio ambiente y la sociedad. La agricultura es una fuente importante de emisiones de gases de efecto invernadero (globalmente contribuye al 12% del total de GEI), y al mismo tiempo puede ser parte de la solución para mitigar las emisiones y adaptarse al cambio climático. Las acciones frente al desafío del cambio climático deben priorizar estrategias de adaptación y mitigación en la agricultura dentro de la agenda para el desarrollo de políticas. La agricultura es por tanto crucial para la conservación y el uso sostenible de los recursos naturales, que ya están sometidos a impactos del cambio climático, al mismo tiempo que debe suministrar alimentos para una población creciente. Por tanto, es necesaria una coordinación entre las actuales estrategias de política climática y agrícola. El concepto de agricultura climáticamente inteligente ha surgido para integrar todos estos servicios de la producción agraria. Al evaluar opciones para reducir las amenazas del cambio climático para la agricultura y el medio ambiente, surgen dos preguntas de investigación: • ¿Qué información es necesaria para definir prácticas agrarias inteligentes? • ¿Qué factores influyen en la implementación de las prácticas agrarias inteligentes? Esta Tesis trata de proporcionar información relevante sobre estas cuestiones generales con el fin de apoyar el desarrollo de la política climática. Se centra en sistemas agrícolas Mediterráneos. Esta Tesis integra diferentes métodos y herramientas para evaluar las alternativas de gestión agrícola y políticas con potencial para responder a las necesidades de mitigación y adaptación al cambio climático. La investigación incluye enfoques cuantitativos y cualitativos e integra variables agronómicas, de clima y socioeconómicas a escala local y regional. La investigación aporta una recopilación de datos sobre evidencia experimental existente, y un estudio integrado sobre el comportamiento de los agricultores y las posibles alternativas de cambio (por ejemplo, la tecnología, la gestión agrícola y la política climática). Los casos de estudio de esta Tesis - el humedal de Doñana (S España) y la región de Aragón (NE España) - permiten ilustrar dos sistemas Mediterráneos representativos, donde el uso intensivo de la agricultura y las condiciones semiáridas son ya una preocupación. Por este motivo, la adopción de estrategias de mitigación y adaptación puede desempeñar un papel muy importante a la hora de encontrar un equilibrio entre la equidad, la seguridad económica y el medio ambiente en los escenarios de cambio climático. La metodología multidisciplinar de esta tesis incluye una amplia gama de enfoques y métodos para la recopilación y el análisis de datos. La toma de datos se apoya en la revisión bibliográfica de evidencia experimental, bases de datos públicas nacionales e internacionales y datos primarios recopilados mediante entrevistas semi-estructuradas con los grupos de interés (administraciones públicas, responsables políticos, asesores agrícolas, científicos y agricultores) y encuestas con agricultores. Los métodos de análisis incluyen: meta-análisis, modelos de gestión de recursos hídricos (modelo WAAPA), análisis multicriterio para la toma de decisiones, métodos estadísticos (modelos de regresión logística y de Poisson) y herramientas para el desarrollo de políticas basadas en la ciencia. El meta-análisis identifica los umbrales críticos de temperatura que repercuten en el crecimiento y el desarrollo de los tres cultivos principales para la seguridad alimentaria (arroz, maíz y trigo). El modelo WAAPA evalúa el efecto del cambio climático en la gestión del agua para la agricultura de acuerdo a diferentes alternativas políticas y escenarios climáticos. El análisis multicriterio evalúa la viabilidad de las prácticas agrícolas de mitigación en dos escenarios climáticos de acuerdo a la percepción de diferentes expertos. Los métodos estadísticos analizan los determinantes y las barreras para la adopción de prácticas agrícolas de mitigación. Las herramientas para el desarrollo de políticas basadas en la ciencia muestran el potencial y el coste para reducir GEI mediante las prácticas agrícolas. En general, los resultados de esta Tesis proporcionan información sobre la adaptación y la mitigación del cambio climático a nivel de explotación para desarrollar una política climática más integrada y ayudar a los agricultores en la toma de decisiones. Los resultados muestran las temperaturas umbral y la respuesta del arroz, el maíz y el trigo a temperaturas extremas, siendo estos valores de gran utilidad para futuros estudios de impacto y adaptación. Los resultados obtenidos también aportan una serie de estrategias flexibles para la adaptación y la mitigación a escala local, proporcionando a su vez una mejor comprensión sobre las barreras y los incentivos para su adopción. La capacidad de mejorar la disponibilidad de agua y el potencial y el coste de reducción de GEI se han estimado para estas estrategias en los casos de estudio. Estos resultados podrían ayudar en el desarrollo de planes locales de adaptación y políticas regionales de mitigación, especialmente en las regiones Mediterráneas. ABSTRACT Alterations in the climatic system due to increased atmospheric concentrations of greenhouse gas emissions (GHG) are expected to have important implications for agriculture, the environment and society. Agriculture is an important source of GHG emissions (12 % of global anthropogenic GHG), but it is also part of the solution to mitigate emissions and to adapt to climate change. Responses to face the challenge of climate change should place agricultural adaptation and mitigation strategies at the heart of the climate change agenda. Agriculture is crucial for the conservation and sustainable use of natural resources, which already stand under pressure due to climate change impacts, increased population, pollution and fragmented and uncoordinated climate policy strategies. The concept of climate smart agriculture has emerged to encompass all these issues as a whole. When assessing choices aimed at reducing threats to agriculture and the environment under climate change, two research questions arise: • What information defines smart farming choices? • What drives the implementation of smart farming choices? This Thesis aims to provide information on these broad questions in order to support climate policy development focusing in some Mediterranean agricultural systems. This Thesis integrates methods and tools to evaluate potential farming and policy choices to respond to mitigation and adaptation to climate change. The assessment involves both quantitative and qualitative approaches and integrates agronomic, climate and socioeconomic variables at local and regional scale. The assessment includes the collection of data on previous experimental evidence, and the integration of farmer behaviour and policy choices (e.g., technology, agricultural management and climate policy). The case study areas -- the Doñana coastal wetland (S Spain) and the Aragón region (NE Spain) – illustrate two representative Mediterranean regions where the intensive use of agriculture and the semi-arid conditions are already a concern. Thus the adoption of mitigation and adaptation measures can play a significant role for reaching a balance among equity, economic security and the environment under climate change scenarios. The multidisciplinary methodology of this Thesis includes a wide range of approaches for collecting and analysing data. The data collection process include revision of existing experimental evidence, public databases and the contribution of primary data gathering by semi-structured interviews with relevant stakeholders (i.e., public administrations, policy makers, agricultural advisors, scientist and farmers among others) and surveys given to farmers. The analytical methods include meta-analysis, water availability models (WAAPA model), decision making analysis (MCA, multi-criteria analysis), statistical approaches (Logistic and Poisson regression models) and science-base policy tools (MACC, marginal abatement cost curves and SOC abatement wedges). The meta-analysis identifies the critical temperature thresholds which impact on the growth and development of three major crops (i.e., rice, maize and wheat). The WAAPA model assesses the effect of climate change for agricultural water management under different policy choices and climate scenarios. The multi-criteria analysis evaluates the feasibility of mitigation farming practices under two climate scenarios according to the expert views. The statistical approaches analyses the drivers and the barriers for the adoption of mitigation farming practices. The science-base policy tools illustrate the mitigation potential and cost effectiveness of the farming practices. Overall, the results of this Thesis provide information to adapt to, and mitigate of, climate change at farm level to support the development of a comprehensive climate policy and to assist farmers. The findings show the key temperature thresholds and response to extreme temperature effects for rice, maize and wheat, so such responses can be included into crop impact and adaptation models. A portfolio of flexible adaptation and mitigation choices at local scale are identified. The results also provide a better understanding of the stakeholders oppose or support to adopt the choices which could be used to incorporate in local adaptation plans and mitigation regional policy. The findings include estimations for the farming and policy choices on the capacity to improve water supply reliability, abatement potential and cost-effective in Mediterranean regions.

Cognitive strategies for reducing energy consumption in wireless sensor networks

El consumo energético de las Redes de Sensores Inalámbricas (WSNs por sus siglas en inglés) es un problema histórico que ha sido abordado desde diferentes niveles y visiones, ya que no solo afecta a la propia supervivencia de la red sino que el creciente uso de dispositivos inteligentes y el nuevo paradigma del Internet de las Cosas hace que las WSNs tengan cada vez una mayor influencia en la huella energética. Debido a la tendencia al alza en el uso de estas redes se añade un nuevo problema, la saturación espectral. Las WSNs operan habitualmente en bandas sin licencia como son las bandas Industrial, Científica y Médica (ISM por sus siglas en inglés). Estas bandas se comparten con otro tipo de redes como Wi-Fi o Bluetooth cuyo uso ha crecido exponencialmente en los últimos años. Para abordar este problema aparece el paradigma de la Radio Cognitiva (CR), una tecnología que permite el acceso oportunista al espectro. La introducción de capacidades cognitivas en las WSNs no solo permite optimizar su eficiencia espectral sino que también tiene un impacto positivo en parámetros como la calidad de servicio, la seguridad o el consumo energético. Sin embargo, por otra parte, este nuevo paradigma plantea algunos retos relacionados con el consumo energético. Concretamente, el sensado del espectro, la colaboración entre los nodos (que requiere comunicación adicional) y el cambio en los parámetros de transmisión aumentan el consumo respecto a las WSN clásicas. Teniendo en cuenta que la investigación en el campo del consumo energético ha sido ampliamente abordada puesto que se trata de una de sus principales limitaciones, asumimos que las nuevas estrategias deben surgir de las nuevas capacidades añadidas por las redes cognitivas. Por otro lado, a la hora de diseñar estrategias de optimización para CWSN hay que tener muy presentes las limitaciones de recursos de estas redes en cuanto a memoria, computación y consumo energético de los nodos. En esta tesis doctoral proponemos dos estrategias de reducción de consumo energético en CWSNs basadas en tres pilares fundamentales. El primero son las capacidades cognitivas añadidas a las WSNs que proporcionan la posibilidad de adaptar los parámetros de transmisión en función del espectro disponible. La segunda es la colaboración, como característica intrínseca de las CWSNs. Finalmente, el tercer pilar de este trabajo es teoría de juegos como algoritmo de soporte a la decisión, ampliamente utilizado en WSNs debido a su simplicidad. Como primer aporte de la tesis se presenta un análisis completo de las posibilidades introducidas por la radio cognitiva en materia de reducción de consumo para WSNs. Gracias a las conclusiones extraídas de este análisis, se han planteado las hipótesis de esta tesis relacionadas con la validez de usar capacidades cognitivas como herramienta para la reducción de consumo en CWSNs. Una vez presentada las hipótesis, pasamos a desarrollar las principales contribuciones de la tesis: las dos estrategias diseñadas para reducción de consumo basadas en teoría de juegos y CR. La primera de ellas hace uso de un juego no cooperativo que se juega mediante pares de jugadores. En la segunda estrategia, aunque el juego continúa siendo no cooperativo, se añade el concepto de colaboración. Para cada una de las estrategias se presenta el modelo del juego, el análisis formal de equilibrios y óptimos y la descripción de la estrategia completa donde se incluye la interacción entre nodos. Con el propósito de probar las estrategias mediante simulación e implementación en dispositivos reales hemos desarrollado un marco de pruebas compuesto por un simulador cognitivo y un banco de pruebas formado por nodos cognitivos capaces de comunicarse en tres bandas ISM desarrollados en el B105 Lab. Este marco de pruebas constituye otra de las aportaciones de la tesis que permitirá el avance en la investigación en el área de las CWSNs. Finalmente, se presentan y discuten los resultados derivados de la prueba de las estrategias desarrolladas. La primera estrategia proporciona ahorros de energía mayores al 65% comparados con una WSN sin capacidades cognitivas y alrededor del 25% si la comparamos con una estrategia cognitiva basada en el sensado periódico del espectro para el cambio de canal de acuerdo a un nivel de ruido fijado. Este algoritmo se comporta de forma similar independientemente del nivel de ruido siempre que éste sea espacialmente uniformemente. Esta estrategia, a pesar de su sencillez, nos asegura el comportamiento óptimo en cuanto a consumo energético debido a la utilización de teoría de juegos en la fase de diseño del comportamiento de los nodos. La estrategia colaborativa presenta mejoras respecto a la anterior en términos de protección frente al ruido en escenarios de ruido más complejos donde aporta una mejora del 50% comparada con la estrategia anterior. ABSTRACT Energy consumption in Wireless Sensor Networks (WSNs) is a known historical problem that has been addressed from different areas and on many levels. But this problem should not only be approached from the point of view of their own efficiency for survival. A major portion of communication traffic has migrated to mobile networks and systems. The increased use of smart devices and the introduction of the Internet of Things (IoT) give WSNs a great influence on the carbon footprint. Thus, optimizing the energy consumption of wireless networks could reduce their environmental impact considerably. In recent years, another problem has been added to the equation: spectrum saturation. Wireless Sensor Networks usually operate in unlicensed spectrum bands such as Industrial, Scientific, and Medical (ISM) bands shared with other networks (mainly Wi-Fi and Bluetooth). To address the efficient spectrum utilization problem, Cognitive Radio (CR) has emerged as the key technology that enables opportunistic access to the spectrum. Therefore, the introduction of cognitive capabilities to WSNs allows optimizing their spectral occupation. Cognitive Wireless Sensor Networks (CWSNs) do not only increase the reliability of communications, but they also have a positive impact on parameters such as the Quality of Service (QoS), network security, or energy consumption. These new opportunities introduced by CWSNs unveil a wide field in the energy consumption research area. However, this also implies some challenges. Specifically, the spectrum sensing stage, collaboration among devices (which requires extra communication), and changes in the transmission parameters increase the total energy consumption of the network. When designing CWSN optimization strategies, the fact that WSN nodes are very limited in terms of memory, computational power, or energy consumption has to be considered. Thus, light strategies that require a low computing capacity must be found. Since the field of energy conservation in WSNs has been widely explored, we assume that new strategies could emerge from the new opportunities presented by cognitive networks. In this PhD Thesis, we present two strategies for energy consumption reduction in CWSNs supported by three main pillars. The first pillar is that cognitive capabilities added to the WSN provide the ability to change the transmission parameters according to the spectrum. The second pillar is that the ability to collaborate is a basic characteristic of CWSNs. Finally, the third pillar for this work is the game theory as a decision-making algorithm, which has been widely used in WSNs due to its lightness and simplicity that make it valid to operate in CWSNs. For the development of these strategies, a complete analysis of the possibilities is first carried out by incorporating the cognitive abilities into the network. Once this analysis has been performed, we expose the hypotheses of this thesis related to the use of cognitive capabilities as a useful tool to reduce energy consumption in CWSNs. Once the analyses are exposed, we present the main contribution of this thesis: the two designed strategies for energy consumption reduction based on game theory and cognitive capabilities. The first one is based on a non-cooperative game played between two players in a simple and selfish way. In the second strategy, the concept of collaboration is introduced. Despite the fact that the game used is also a non-cooperative game, the decisions are taken through collaboration. For each strategy, we present the modeled game, the formal analysis of equilibrium and optimum, and the complete strategy describing the interaction between nodes. In order to test the strategies through simulation and implementation in real devices, we have developed a CWSN framework composed by a CWSN simulator based on Castalia and a testbed based on CWSN nodes able to communicate in three different ISM bands. We present and discuss the results derived by the energy optimization strategies. The first strategy brings energy improvement rates of over 65% compared to WSN without cognitive techniques. It also brings energy improvement rates of over 25% compared with sensing strategies for changing channels based on a decision threshold. We have also seen that the algorithm behaves similarly even with significant variations in the level of noise while working in a uniform noise scenario. The collaborative strategy presents improvements respecting the previous strategy in terms of noise protection when the noise scheme is more complex where this strategy shows improvement rates of over 50%.

Modelo de integración del conocimiento-acción a través del Proyecto de Comunicación para el Desarrollo: 25 años de experiencia en comunidades indígenas andinas en Ecuador

El desarrollo como política de las naciones marca el período de la postguerra, que en América Latina se concreta en múltiples programas de Desarrollo Rural. El modelo inicial de crecimiento económico se va enriqueciendo con visiones centradas en el ser humano y sus múltiples concepciones de desarrollo. En este entender el desarrollo desde la diversidad cultural y antropológica de los pueblos de América Latina, surge la comunicación radiofónica como camino común para la persuasión, socialización y apropiación colectiva de conocimientos y ámbito participativo para consensuar objetivos y acordar actividades. El activismo de los años setenta y ochenta produjo un número considerable de experiencias. La mayoría de ellas han llegado hasta nuestros días, pero el giro tomado por las sociedades digitalizadas y las prioridades medioambientales han dado un nuevo rostro a aquellas primeras experiencias centradas en el desarrollo rural endógeno. Este estudio investiga el complejo práctico-teórico que integra comunicación y desarrollo en contextos territoriales interculturales con población marginal y aplicación de políticas de desarrollo rural. En el capítulo I se recogen las modalidades de cómo se ha aplicado la comunicación en programas de desarrollo, para profundizar en el concepto de comunicación para el desarrollo, conocer sus actores y resultados, y concluir que el desarrollo “con rostro humano” se hace con personas no con políticas oficiales. El capítulo II presenta a los Pueblos Indígenas de la Sierra Ecuatoriana como actores de su proceso de desarrollo hacia el Sumak Kawsay. Los temas tratados en este capítulo muestran los valores y capacidades de las comunidades indígenas de la Sierra Ecuatoriana para la autogestión de su desarrollo, y deja constancia y denuncia de la lectura negativa que se ha venido haciendo de su cosmovisión. Se encuentra respuesta conceptual y metodológica en el Workng With People para optimizar aportes culturales de los Pueblos Indígenas al proceso comunicacional y participativo para mejorar las condiciones de vida y lograr mayores espacios de autonomía y libertad El conocimiento que explica la realidad sin cambiarla no tiene sentido para los pobres. La realidad requiere ser comprendida para construir el conocimiento que la explique y la cambie: ese es el aporte del modelo conocimiento/acción que se presenta en el capítulo III. En este capítulo se exponen metodologías abiertas a la creatividad y flexibles que responden a los principios del modelo conocimiento/acción. La comunicación para el desarrollo se abre a todas ellas como ágora pluricultural que requiere un lenguaje común que se construye desde el aprendizaje social. Los conceptos expuestos en el capítulo III se vinculan en una propuesta metodológica que integra el conocimiento y la acción con los principios del Working With People, propuesta que se expone en el capítulo IV. El modelo del Proyecto de Comunicación para el Desarrollo junta en un modelo de comunicación popular y prácticas liberadoras con métodos cognitivos de la realidad para planificar el cambio desde la población y con la población. Finalmente, el capítulo V recoge la experiencia de la Casa Campesina Cayambe ejecutora del Proyecto de Comunicación para el Desarrollo en la adaptación ejecutada con Radio Mensaje. La riqueza de la experiencia tiende a escaparse de los límites conceptuales y los esquemas dejan espacios de vida ignotos; pero los conceptos y esquemas constituyen el camino para que la experiencia pase a ser objeto conocido y conocimiento socializado. El Proyecto de Comunicación para el Desarrollo es resultado de un proceso de desarrollo construido desde la acción de la Casa Campesina Cayambe durante 25 años en Cayambe. En el capítulo V se describe el contexto del territorio de Cayambe, la identidad de la Casa Campesina Cayambe y de Radio Mensaje, y termina describiendo los logros de 25 años trabajando con la gente. El estudio concluye que la comunicación participativa, como ámbito de aprendizaje social aplicado en procesos de desarrollo rural, integra el conocimiento/acción e incorpora nuevos conocimientos en la población con los que se desarrollan competencias locales para planificar el desarrollo endógeno con flexibilidad y de abajo-arriba. La Figura 0-1 grafica los elementos bases sobre los que se construye el proceso de desarrollo. ABSTRACT Development as a policy of nations marks the postwar period which created several Rural Development Programs in Latin America. The initial model of economic growth was enriched with approaches focused on human beings and their multiple conceptions of development. In this regard, the development from cultural and anthropological diversity in Latin America, radio communication emerges as a common means for persuasion, socialization and collective appropriation of knowledge and scope for participation in order to agree on objectives and activities. Activism of the seventies and eighties generated a considerable number of experiences, most of which are present today. However, a turn taken by digitalized societies and environmental priorities has given those first experiences which focused on endogenous rural development a new face. This study researches the theoretical-practical status that integrates communication and development in intercultural contexts with marginal population and the use of rural development policies. Chapter one shows the modalities of how communication in development programs have been applied to deepen the concept of communication for development, to know those who are involved and its findings, and conclude that development “with a human face” is done with people not with official policies. Chapter two presents Indigenous communities in the Ecuadorian highlands, as people involved in their development process towards Sumak Kawsay. The topics in this chapter show the values and capacities indigenous communities in the Ecuadorian highlands have to self-manage their development, and proves, as well as denounces, that their cosmovision has been negatively perceived. A conceptual and methodological response is found in Working With People in order to optimize cultural contributions of Indigenous People to the communicational and participative process to improve life conditions and have greater spaces of autonomy and freedom. Knowledge which explains reality without changing it does not make any sense for the poor. Reality need to be understood in order to build the knowledge that will explain it and change it: that is the contribution of the knowledge/action model presented in chapter three. This chapter presents open methodologies to creativity which are flexible to respond to the principles of the knowledge/action model. Communication for development is open to all of them as pluricultural agora which requires a common language that is built from social learning. The concepts presented in chapter three are linked in a methodological proposal which integrates knowledge and action with principles of Working With People, proposal which is presented chapter four. The model of the Communication for Development Project includes popular communication elements and liberating practices with cognitive methods of reality to plan change from the population and with the population. Finally, chapter five presents the experiences from the Cayambe Country House, which conducted the Communication for Development Project in the adaptation implemented with Radio Mensaje. The wealth of experience tends to scape from the conceptual limits and the schemes leave gaps of unexplored life; but the concepts and schemes constitute the way so that experience becomes a known object and socialized knowledge. The Communication for Development Project is the result of a development process built from the actions of the Cayambe Country House during 25 years in Cayambe. Chapter five describes the context of Cayambe, the identity of the Cayambe Country House and Radio Mensaje, and the achievements after 25 years of working with its people. The study concludes that participatory communication, as an area of social learning applied to rural development processes, integrates knowledge/action and incorporates new knowledge in communities to develop local competencies to plan endogenous development with flexibility and from the bottom – up.

Hydromorphic change and biotic response challenge efficient river rehabilitation

From an extensive literature review and meta-analyses, this study has i) identified the most important hydromorphological process related to river degradation and rehabilitation, ii) conceptually linked it to evolutionary and functional response chains of aquatic biota, and iii) provided empirical evidence and ecological data for the respective hydromorphological requirements, preferences and limitations of aquatic plants, benthic invertebrates, lampreys, and freshwater fishes.

Use of phosphorous mapping and sea-level change data in assessing coastal activity zones and establishing site chronology : A case study from the Icelandic multi-period site of Vatnsfjörður

This paper forms part of Lukasz Mikolajczyk's PhD dissertation, which is supervised by Karen Milek

Rapid elimination of mature autoreactive B cells demonstrated by Cre-induced change in B cell antigen receptor specificity in vivo

Developing autoreactive B cells edit their B cell antigen receptor (BCR) in the bone marrow and are clonally deleted when they fail to reexpress an innocent BCR. Here, inducible Cre-loxP-mediated gene inversion is used to change the specificity of the BCR on mature IgM+ IgD+ B cells in vivo to address the fate of lymphocytes encountering self-antigens at this developmental stage. Expression of an autoreactive BCR on mature B cells leads to their rapid elimination from the periphery, a process that is inhibited by constitutive bcl-2 transgene expression in an antigen dose-dependent manner. Thus, selection of mature B cells into the long-lived peripheral pool does not prevent their deletion upon encounter of self-antigens.

Permanence or change? The meaning of genetic variation

Selected aspects of the evolutionary process and more specifically of the genetic variation are considered, with an emphasis in studies performed by my group. One key aspect of evolution seems to be the concomitant occurrence of dichotomic, contradictory (dialect) processes. Genetic variation is structured, and the dynamics of change at one level is not necessarily paralleled by that in another. The pathogenesis-related protein superfamily can be cited as an example in which permanence (the maintenance of certain key genetic features) coexists with change (modifications that led to different functions in different classes of organisms). Relationships between structure and function are exemplified by studies with hemoglobin Porto Alegre. The genetic structure of tribal populations may differ in important aspects from that of industrialized societies. Evolutionary histories also may differ when considered through the investigation of patrilineal or matrilineal lineages. Global evaluations taking into consideration all of these aspects are needed if we really want to understand the meaning of genetic variation.

Long-term change in the organization of inventive activity

Relying on a quantitative analysis of the patenting and assignment behavior of inventors, we highlight the evolution of institutions that encouraged trade in technology and a growing division of labor between those who invented new technologies and those who exploited them commercially over the nineteenth and early-twentieth centuries. At the heart of this change in the organization of inventive activity was a set of familiar developments which had significant consequences for the supply and demand of inventions. On the supply side, the growing complexity and capital intensity of technology raised the amount of human and physical capital required for effective invention, making it increasingly desirable for individuals involved in this activity to specialize. On the demand side, the growing competitiveness of product markets induced firms to purchase or otherwise obtain the rights to technologies developed by others. These increasing incentives to differentiate the task of invention from that of commercializing new technologies depended for their realization upon the development of markets and other types of organizational supports for trade in technology. The evidence suggests that the necessary institutions evolved first in those regions of the country where early patenting activity had already been concentrated. A self-reinforcing process whereby high rates of inventive activity encouraged the evolution of a market for technology, which in turn encouraged greater specialization and productivity at invention as individuals found it increasingly feasible to sell and license their discoveries, appears to have been operating. This market trade in technological information was an important contributor to the achievement of a high level of specialization at invention well before the rise of large-scale research laboratories in the twentieth century.

Global and local implications of biotechnology and climate change for future food supplies

The development of improved technology for agricultural production and its diffusion to farmers is a process requiring investment and time. A large number of studies of this process have been undertaken. The findings of these studies have been incorporated into a quantitative policy model projecting supplies of commodities (in terms of area and crop yields), equilibrium prices, and international trade volumes to the year 2020. These projections show that a “global food crisis,” as would be manifested in high commodity prices, is unlikely to occur. The same projections show, however, that in many countries, “local food crisis,” as manifested in low agricultural incomes and associated low food consumption in the presence of low food prices, will occur. Simulations show that delays in the diffusion of modern biotechnology research capabilities to developing countries will exacerbate local food crises. Similarly, global climate change will also exacerbate these crises, accentuating the importance of bringing strengthened research capabilities to developing countries.

Rapid genome change in synthetic polyploids of Brassica and its implications for polyploid evolution.

Although the evolutionary success of polyploidy in higher plants has been widely recognized, there is virtually no information on how polyploid genomes have evolved after their formation. In this report, we used synthetic polyploids of Brassica as a model system to study genome evolution in the early generations after polyploidization. The initial polyploids we developed were completely homozygous, and thus, no nuclear genome changes were expected in self-fertilized progenies. However, extensive genome change was detected by 89 nuclear DNA clones used as probes. Most genome changes involved loss and/or gain of parental restriction fragments and appearance of novel fragments. Genome changes occurred in each generation from F2 to F5, and the frequency of change was associated with divergence of the diploid parental genomes. Genetic divergence among the derivatives of synthetic polyploids was evident from variation in genome composition and phenotypes. Directional genome changes, possibly influenced by cytoplasmic-nuclear interactions, were observed in one pair of reciprocal synthetics. Our results demonstrate that polyploid species can generate extensive genetic diversity in a short period of time. The occurrence and impact of this process in the evolution of natural polyploids is unknown, but it may have contributed to the success and diversification of many polyploid lineages in both plants and animals.