On the monitoring of surface displacement in connection with volcano reactivation in Tenerife, Canary Islands, using space techniques

Geodetic volcano monitoring in Tenerife has mainly focused on the Las Cañadas Caldera, where a geodetic micronetwork and a levelling profile are located. A sensitivity test of this geodetic network showed that it should be extended to cover the whole island for volcano monitoring purposes. Furthermore, InSAR allowed detecting two unexpected movements that were beyond the scope of the traditional geodetic network. These two facts prompted us to design and observe a GPS network covering the whole of Tenerife that was monitored in August 2000. The results obtained were accurate to one centimetre, and confirm one of the deformations, although they were not definitive enough to confirm the second one. Furthermore, new cases of possible subsidence have been detected in areas where InSAR could not be used to measure deformation due to low coherence. A first modelling attempt has been made using a very simple model and its results seem to indicate that the deformation observed and the groundwater level variation in the island may be related. Future observations will be necessary for further validation and to study the time evolution of the displacements, carry out interpretation work using different types of data (gravity, gases, etc) and develop models that represent the island more closely. The results obtained are important because they might affect the geodetic volcano monitoring on the island, which will only be really useful if it is capable of distinguishing between displacements that might be linked to volcanic activity and those produced by other causes. One important result in this work is that a new geodetic monitoring system based on two complementary techniques, InSAR and GPS, has been set up on Tenerife island. This the first time that the whole surface of any of the volcanic Canary Islands has been covered with a single network for this purpose. This research has displayed the need for further similar studies in the Canary Islands, at least on the islands which pose a greater risk of volcanic reactivation, such as Lanzarote and La Palma, where InSAR techniques have been used already.

A simple genetic algorithm for calibration of stochastic rock discontinuity networks

Este artículo propone un método para llevar a cabo la calibración de las familias de discontinuidades en macizos rocosos. We present a novel approach for calibration of stochastic discontinuity network parameters based on genetic algorithms (GAs). To validate the approach, examples of application of the method to cases with known parameters of the original Poisson discontinuity network are presented. Parameters of the model are encoded as chromosomes using a binary representation, and such chromosomes evolve as successive generations of a randomly generated initial population, subjected to GA operations of selection, crossover and mutation. Such back-calculated parameters are employed to make assessments about the inference capabilities of the model using different objective functions with different probabilities of crossover and mutation. Results show that the predictive capabilities of GAs significantly depend on the type of objective function considered; and they also show that the calibration capabilities of the genetic algorithm can be acceptable for practical engineering applications, since in most cases they can be expected to provide parameter estimates with relatively small errors for those parameters of the network (such as intensity and mean size of discontinuities) that have the strongest influence on many engineering applications.

Optimizing Functional Network Representation of Multivariate Time Series

By combining complex network theory and data mining techniques, we provide objective criteria for optimization of the functional network representation of generic multivariate time series. In particular, we propose a method for the principled selection of the threshold value for functional network reconstruction from raw data, and for proper identification of the network's indicators that unveil the most discriminative information on the system for classification purposes. We illustrate our method by analysing networks of functional brain activity of healthy subjects, and patients suffering from Mild Cognitive Impairment, an intermediate stage between the expected cognitive decline of normal aging and the more pronounced decline of dementia. We discuss extensions of the scope of the proposed methodology to network engineering purposes, and to other data mining tasks.

Modelling of chloride transport in non-saturated concrete : from microscale to macroscale

Corrosion of steel bars embedded in concrete has a great influence on structural performance and durability of reinforced concrete. Chloride penetration is considered to be a primary cause of concrete deterioration in a vast majority of structures. Therefore, modelling of chloride penetration into concrete has become an area of great interest. The present work focuses on modelling of chloride transport in concrete. The differential macroscopic equations which govern the problem were derived from the equations at the microscopic scale by comparing the porous network with a single equivalent pore whose properties are the same as the average properties of the real porous network. The resulting transport model, which accounts for diffusion, migration, advection, chloride binding and chloride precipitation, consists of three coupled differential equations. The first equation models the transport of chloride ions, while the other two model the flow of the pore water and the heat transfer. In order to calibrate the model, the material parameters to determine experimentally were identified. The differential equations were solved by means of the finite element method. The classical Galerkin method was employed for the pore solution flow and the heat transfer equations, while the streamline upwind Petrov Galerkin method was adopted for the transport equation in order to avoid spatial instabilities for advection dominated problems. The finite element codes are implemented in Matlab® . To retrieve a good understanding of the influence of each variable and parameter, a detailed sensitivity analysis of the model was carried out. In order to determine the diffusive and hygroscopic properties of the studied concretes, as well as their chloride binding capacity, an experimental analysis was performed. The model was successfully compared with experimental data obtained from an offshore oil platform located in Brazil. Moreover, apart from the main objectives, numerous results were obtained throughout this work. For instance, several diffusion coefficients and the relation between them are discussed. It is shown how the electric field set up between the ionic species depends on the gradient of the species’ concentrations. Furthermore, the capillary hysteresis effects are illustrated by a proposed model, which leads to the determination of several microstructure properties, such as the pore size distribution and the tortuosity-connectivity of the porous network. El fenómeno de corrosión del acero de refuerzo embebido en el hormigón ha tenido gran influencia en estructuras de hormigón armado, tanto en su funcionalidad estructural como en aspectos de durabilidad. La penetración de cloruros en el interior del hormigón esta considerada como el factor principal en el deterioro de la gran mayoría de estructuras. Por lo tanto, la modelización numérica de dicho fenómeno ha generado gran interés. El presente trabajo de investigación se centra en la modelización del transporte de cloruros en el interior del hormigón. Las ecuaciones diferenciales que gobiernan los fenómenos a nivel macroscópico se deducen de ecuaciones planteadas a nivel microscópico. Esto se obtiene comparando la red porosa con un poro equivalente, el cual mantiene las mismas propiedades de la red porosa real. El modelo está constituido por tres ecuaciones diferenciales acopladas que consideran el transporte de cloruros, el flujo de la solución de poro y la transferencia de calor. Con estas ecuaciones se tienen en cuenta los fenómenos de difusión, migración, advección, combinación y precipitación de cloruros. El análisis llevado a cabo en este trabajo ha definido los parámetros necesarios para calibrar el modelo. De acuerdo con ellas, se seleccionaron los ensayos experimentales a realizar. Las ecuaciones diferenciales se resolvieron mediante el método de elementos finitos. El método clásico de Galerkin se empleó para solucionar las ecuaciones de flujo de la solución de poro y de la transferencia de calor, mientras que el método streamline upwind Petrov-Galerkin se utilizó para resolver la ecuación de transporte de cloruros con la finalidad de evitar inestabilidades espaciales en problemas con advección dominante. El código de elementos finitos está implementado en Matlab® . Con el objetivo de facilitar la comprensión del grado de influencia de cada variable y parámetro, se realizó un análisis de sensibilidad detallado del modelo. Se llevó a cabo una campaña experimental sobre los hormigones estudiados, con el objeto de obtener sus propiedades difusivas, químicas e higroscópicas. El modelo se contrastó con datos experimentales obtenidos en una plataforma petrolera localizada en Brasil. Las simulaciones numéricas corroboraron los datos experimentales. Además, durante el desarrollo de la investigación se obtuvieron resultados paralelos a los planteados inicialmente. Por ejemplo, el análisis de diferentes coeficientes de difusión y la relación entre ellos. Así como también se observó que el campo eléctrico establecido entre las especies iónicas disueltas en la solución de poro depende del gradiente de concentración de las mismas. Los efectos de histéresis capilar son expresados por el modelo propuesto, el cual conduce a la determinación de una serie de propiedades microscópicas, tales como la distribución del tamaño de poro, además de la tortuosidad y conectividad de la red porosa.

Analysis and design of multiagent systems using MAS-CommonKADS

This article proposes an agent-oriented methodology called MAS-CommonKADS and develops a case study. This methodology extends the knowledge engineering methodology CommonKADSwith techniquesfrom objectoriented and protocol engineering methodologies. The methodology consists of the development of seven models: Agent Model, that describes the characteristics of each agent; Task Model, that describes the tasks that the agents carry out; Expertise Model, that describes the knowledge needed by the agents to achieve their goals; Organisation Model, that describes the structural relationships between agents (software agents and/or human agents); Coordination Model, that describes the dynamic relationships between software agents; Communication Model, that describes the dynamic relationships between human agents and their respective personal assistant software agents; and Design Model, that refines the previous models and determines the most suitable agent architecture for each agent, and the requirements of the agent network.

Knowledge Discovery in Spectral Data by Means of Complex Networks

In the last decade, complex networks have widely been applied to the study of many natural and man-made systems, and to the extraction of meaningful information from the interaction structures created by genes and proteins. Nevertheless, less attention has been devoted to metabonomics, due to the lack of a natural network representation of spectral data. Here we define a technique for reconstructing networks from spectral data sets, where nodes represent spectral bins, and pairs of them are connected when their intensities follow a pattern associated with a disease. The structural analysis of the resulting network can then be used to feed standard data-mining algorithms, for instance for the classification of new (unlabeled) subjects. Furthermore, we show how the structure of the network is resilient to the presence of external additive noise, and how it can be used to extract relevant knowledge about the development of the disease.

A methodology for the implementation and continuous improvement of social responsibility (RS) and financial responsibility

This work sets out an innovative methodology that aims to facilitate the implementation and continuous improvement of Social Responsibility. It is a methodology that takes account of strategic-economic, social and environmental questions and allows measuring the impact of each of these aspects on the stakeholders and on each of the value areas. It can be extrapolated to all kinds of organisations regardless of their size and sector and admits scaleable models. A marked feature that sets it aside from other methodologies is that it eliminates subjectivity from the qualitative aspects and introduces an algorithm to quantify them.

Modeling the evolution of item rating networks using time-domain preferential attachment

The understanding of the structure and dynamics of the intricate network of connections among people that consumes products through Internet appears as an extremely useful asset in order to study emergent properties related to social behavior. This knowledge could be useful, for example, to improve the performance of personal recommendation algorithms. In this contribution, we analyzed five-year records of movie-rating transactions provided by Netflix, a movie rental platform where users rate movies from an online catalog. This dataset can be studied as a bipartite user-item network whose structure evolves in time. Even though several topological properties from subsets of this bipartite network have been reported with a model that combines random and preferential attachment mechanisms [Beguerisse Díaz et al., 2010], there are still many aspects worth to be explored, as they are connected to relevant phenomena underlying the evolution of the network. In this work, we test the hypothesis that bursty human behavior is essential in order to describe how a bipartite user-item network evolves in time. To that end, we propose a novel model that combines, for user nodes, a network growth prescription based on a preferential attachment mechanism acting not only in the topological domain (i.e. based on node degrees) but also in time domain. In the case of items, the model mixes degree preferential attachment and random selection. With these ingredients, the model is not only able to reproduce the asymptotic degree distribution, but also shows an excellent agreement with the Netflix data in several time-dependent topological properties.

Nonlocal analysis of modular roles

We introduce a new methodology to characterize the role that a given node plays inside the community structure of a complex network. Our method relies on the ability of the links to reduce the number of steps between two nodes in the network, which is measured by the number of shortest paths crossing each link, and its impact on the node proximity. In this way, we use node closeness to quantify the importance of a node inside its community. At the same time, we define a participation coefficient that depends on the shortest paths contained in the links that connect two communities. The combination of both parameters allows to identify the role played by the nodes in the network, following the same guidelines introduced by Guimerà et al. [Guimerà & Amaral, 2005] but, in this case, considering global information about the network. Finally, we give some examples of the hub characterization in real networks and compare our results with the parameters most used in the literature.

On the economics of energy consumption in 4G networks: the case of Spain

Reducing energy consumption is one of the main challenges in most countries. For example, European Member States agreed to reduce greenhouse gas (GHG) emissions by 20% in 2020 compared to 1990 levels (EC 2008). Considering each sector separately, ICTs account nowadays for 2% of total carbon emissions. This percentage will increase as the demand of communication services and applications steps up. At the same time, the expected evolution of ICT-based developments - smart buildings, smart grids and smart transportation systems among others - could result in the creation of energy-saving opportunities leading to global emission reductions (Labouze et al. 2008), although the amount of these savings is under debate (Falch 2010). The main development required in telecommunication networks ?one of the three major blocks of energy consumption in ICTs together with data centers and consumer equipment (Sutherland 2009) ? is the evolution of existing infrastructures into ultra-broadband networks, the so-called Next Generation Networks (NGN). Fourth generation (4G) mobile communications are the technology of choice to complete -or supplement- the ubiquitous deployment of NGN. The risk and opportunities involved in NGN roll-out are currently in the forefront of the economic and policy debate. However, the issue of which is the role of energy consumption in 4G networks seems absent, despite the fact that the economic impact of energy consumption arises as a key element in the cost analysis of this type of networks. Precisely, the aim of this research is to provide deeper insight on the energy consumption involved in the usage of a 4G network, its relationship with network main design features, and the general economic impact this would have in the capital and operational expenditures related with network deployment and usage.

Modeling impact assessment of transport policies through a multiregional input-output integrated approach

El objetivo de esta investigación es desarrollar una metodología para estimar los potenciales impactos económicos y de transporte generados por la aplicación de políticas en el sector transporte. Los departamentos de transporte y otras instituciones gubernamentales relacionadas se encuentran interesadas en estos análisis debido a que son presentados comúnmente de forma errónea por la insuficiencia de datos o por la falta de metodologías adecuadas. La presente investigación tiene por objeto llenar este vacío haciendo un análisis exhaustivo de las técnicas disponibles que coincidan con ese propósito. Se ha realizado un análisis que ha identificado las diferencias cuando son aplicados para la valoración de los beneficios para el usuario o para otros efectos como aspectos sociales. Como resultado de ello, esta investigación ofrece un enfoque integrado que incluye un modelo Input-Output de múltiples regiones basado en la utilidad aleatoria (RUBMRIO), y un modelo de red de transporte por carretera. Este modelo permite la reproducción con mayor detalle y realismo del transporte de mercancías que por medio de su estructura sectorial identifica los vínculos de las compras y ventas inter-industriales dentro de un país utilizando los servicios del transporte de mercancías. Por esta razón, el modelo integrado es aplicable a diversas políticas de transporte. En efecto, el enfoque se ha aplicado para estudiar los efectos macroeconómicos regionales de la implementación de dos políticas diferentes en el sistema de transporte de mercancías de España, tales como la tarificación basada en la distancia recorrida por vehículo-kilómetro (€/km) aplicada a los vehículos del transporte de mercancías, y para la introducción de vehículos más largos y pesados de mercancías en la red de carreteras de España. El enfoque metodológico se ha evaluado caso por caso teniendo en cuenta una selección de la red de carreteras que unen las capitales de las regiones españolas. También se ha tenido en cuenta una dimensión económica a través de una tabla Input-Output de múltiples regiones (MRIO) y la base de datos de conteo de tráfico existente para realizar la validación del modelo. El enfoque integrado reproduce las condiciones de comercio observadas entre las regiones usando el sistema de transporte de mercancías por carretera, y que permite por comparación con los escenarios de políticas, determinar las contribuciones a los cambios distributivos y generativos. Así pues, el análisis estima los impactos económicos en cualquier región considerando los cambios en el Producto Interno Bruto (PIB) y el empleo. El enfoque identifica los cambios en el sistema de transporte a través de todos los caminos de la red de transporte a través de las medidas de efectividad (MOEs). Los resultados presentados en esta investigación proporcionan evidencia sustancial de que en la evaluación de las políticas de transporte, es necesario establecer un vínculo entre la estructura económica de las regiones y de los servicios de transporte. Los análisis muestran que para la mayoría de las regiones del país, los cambios son evidentes para el PIB y el empleo, ya que el comercio se fomenta o se inhibe. El enfoque muestra cómo el tráfico se desvía en ambas políticas, y también determina detalles de las emisiones de contaminantes en los dos escenarios. Además, las políticas de fijación de precios o de regulación de los sistemas de transporte de mercancías por carretera dirigidas a los productores y consumidores en las regiones promoverán transformaciones regionales afectando todo el país, y esto conduce a conclusiones diferentes. Así mismo, este enfoque integrado podría ser útil para evaluar otras políticas y otros países en todo el mundo. The purpose of this research is to develop a methodological approach aimed at assessing the potential economic and transportation impacts of transport policies. Transportation departments and other related government parties are interested in such analysis because it is commonly misrepresented for the insufficiency of data and suitable methodologies available. This research is directed at filling this gap by making a comprehensive analysis of the available techniques that match with that purpose. The differences when they are applied for the valuation of user benefits or for other impacts as social matters have been identified. As a result, this research presents an integrated approach which includes both a random utility-based multiregional Input-Output model (RUBMRIO), and a road transport network model. This model accounts for freight transport with more detail and realism because its commodity-based structure traces the linkages of inter-industry purchases and sales that use freight services within a given country. For this reason, the integrated model is applicable to various transport policies. In fact, the approach is applied to study the regional macroeconomic effects of implementing two different policies in the freight transport system of Spain, such as a distance-based charge in vehicle-kilometer (€/km) for Heavy Goods Vehicles (HGVs), and the introduction of Longer and Heavier Vehicles (LHVs) in the road network of Spain. The methodological approach has been evaluated on a case by case basis considering a selected road network of highways linking the capitals of the Spanish regions. It has also considered an economic dimension through a Multiregional Input Output Table (MRIO) and the existing traffic count database used in the model validation. The integrated approach replicates observed conditions of trade among regions using road freight transport systems that determine contributions to distributional and generative changes by comparison with policy scenarios. Therefore, the model estimates economic impacts in any given area by considering changes in Gross Domestic Product (GDP), employment (jobs), and in the transportation system across all paths of the transport network considering Measures of effectiveness (MOEs). The results presented in this research provide substantive evidence that in the assessment of transport policies it is necessary to establish a link between the economic structure of regions and the transportation services. The analysis shows that for most regions in the country, GDP and employment changes are noticeable when trade is encouraged or discouraged. This approach shows how traffic is diverted in both policies, and also provides details of the pollutant emissions in both scenarios. Furthermore, policies, such as pricing or regulation of road freight transportation systems, directed to producers and consumers in regions will promote different regional transformations across the country, and this lead to different conclusions. In addition, this integrated approach could be useful to assess other policies and countries worldwide.

Aspects of a phased array radar feed and bias network design

Radar technologies have been developed to improve the efficiency when detecting targets. Radar is a system composed by several devices connected and working together. Depending on the type of radar, the improvements are focused on different functionalities of the radar. One of the most important devices composing a radar is the antenna, that sends the radio-frequency signal to the space in order to detect targets. This project is focused on a specific type of radar called phased array radar. This type of radar is characterized by its antenna, which consist on a linear array of radiating elements, in this particular case, eight dipoles working at the frequency band S. The main advantage introduced by the phased array antenna is that using the fundamentals of arrays, the directivity of the antenna can change by shifting the phase of the signal at the input of each radiating element. This can be done using phase shifters. Phase shifter consists on a device which produces a phase shift in the radio-frequency input signal depending on a control DC voltage. Using a phased array antenna allows changing the directivity of the antenna without a mechanical rotating system. The objective of this project is to design the feed network and the bias network of the phased antenna. The feed network consists on a parallel-fed network composed by power dividers that sends the radio-frequency signal from the source to each radiating element of the antenna. The bias network consists on a system that generates the control DC voltages supplied to the phase shifters in order to change the directivity. The architecture of the bias network is composed by a software, implemented in Matlab and run in a laptop which is connected to a micro-controller by a serial communication port. The software calculates the control DC voltages needed to obtain a determined directivity or scan angle. These values are sent by the serial communication port to the micro-controller as data. Then the micro-controller generates the desired control DC voltages and supplies them to the phase shifters. In this project two solutions for bias network are designed. Each one is tested and final conclusions are obtained to determine the advantages and disadvantages. Finally a graphic user interface is developed in order to make the system easy to use. RESUMEN. Las tecnologías empleadas por lo dispositivos radar se han ido desarrollando para mejorar su eficiencia y usabilidad. Un radar es un sistema formado por varios subsistemas conectados entre sí. Por lo que dependiendo del tipo de radar las mejoras se centran en los subsistemas correspondientes. Uno de los elementos más importantes de un radar es la antena. Esta se emplea para enviar la señal de radiofrecuencia al espacio y así poder detectar los posibles obstáculos del entorno. Este proyecto se centra en un tipo específico de radar llamado phased array radar. Este tipo de radar se caracteriza por la antena que es un array de antenas, en concreto para este proyecto se trata de un array lineal de ocho dipolos en la banda de frequencia S. El uso de una antena de tipo phased array supone una ventaja importante. Empleando los fundamentos de radiación aplicado a array de antenas se obtiene que la directividad de la antena puede ser modificada. Esto se consigue aplicando distintos desfasajes a la señal de radiofrecuencia que alimenta a cada elemento del array. Para aplicar los desfasajes se emplea un desplazador de fase, este dispositivo aplica una diferencia de fase a su salida con respecto a la señal de entrada dependiendo de una tensión continua de control. Por tanto el empleo de una antena de tipo phased array supone una gran ventaja puesto que no se necesita un sistema de rotación para cambiar la directividad de la antena. El objetivo principal del proyecto consiste en el diseño de la red de alimentación y la red de polarización de la antena de tipo phased array. La red de alimentación consiste en un circuito pasivo que permite alimentar a cada elemento del array con la misma cantidad de señal. Dicha red estará formada por divisores de potencia pasivos y su configuración será en paralelo. Por otro lado la red de polarización consiste en el diseño de un sistema automático que permite cambiar la directividad de la antena. Este sistema consiste en un programa en Matlab que es ejecutado en un ordenador conectado a un micro-controlador mediante una comunicación serie. El funcionamiento se basa en calcular las tensiones continuas de control, que necesitan los desplazadores de fase, mediante un programa en Matlab y enviarlos como datos al micro-controlador. Dicho micro-controlador genera las tensiones de control deseadas y las proporciona a cada desplazador de fase, obteniendo así la directividad deseada. Debido al amplio abanico de posibilidades, se obtienen dos soluciones que son sometidas a pruebas. Se obtienen las ventajas y desventajas de cada una. Finalmente se implementa una interfaz gráfica de usuario con el objetivo de hacer dicho sistema manejable y entendible para cualquier usuario.

Functional and effective connectivity in MEG. Application to the study of epilepsy

Nuestro cerebro contiene cerca de 1014 sinapsis neuronales. Esta enorme cantidad de conexiones proporciona un entorno ideal donde distintos grupos de neuronas se sincronizan transitoriamente para provocar la aparición de funciones cognitivas, como la percepción, el aprendizaje o el pensamiento. Comprender la organización de esta compleja red cerebral en base a datos neurofisiológicos, representa uno de los desafíos más importantes y emocionantes en el campo de la neurociencia. Se han propuesto recientemente varias medidas para evaluar cómo se comunican las diferentes partes del cerebro a diversas escalas (células individuales, columnas corticales, o áreas cerebrales). Podemos clasificarlos, según su simetría, en dos grupos: por una parte, la medidas simétricas, como la correlación, la coherencia o la sincronización de fase, que evalúan la conectividad funcional (FC); mientras que las medidas asimétricas, como la causalidad de Granger o transferencia de entropía, son capaces de detectar la dirección de la interacción, lo que denominamos conectividad efectiva (EC). En la neurociencia moderna ha aumentado el interés por el estudio de las redes funcionales cerebrales, en gran medida debido a la aparición de estos nuevos algoritmos que permiten analizar la interdependencia entre señales temporales, además de la emergente teoría de redes complejas y la introducción de técnicas novedosas, como la magnetoencefalografía (MEG), para registrar datos neurofisiológicos con gran resolución. Sin embargo, nos hallamos ante un campo novedoso que presenta aun varias cuestiones metodológicas sin resolver, algunas de las cuales trataran de abordarse en esta tesis. En primer lugar, el creciente número de aproximaciones para determinar la existencia de FC/EC entre dos o más señales temporales, junto con la complejidad matemática de las herramientas de análisis, hacen deseable organizarlas todas en un paquete software intuitivo y fácil de usar. Aquí presento HERMES (http://hermes.ctb.upm.es), una toolbox en MatlabR, diseñada precisamente con este fin. Creo que esta herramienta será de gran ayuda para todos aquellos investigadores que trabajen en el campo emergente del análisis de conectividad cerebral y supondrá un gran valor para la comunidad científica. La segunda cuestión practica que se aborda es el estudio de la sensibilidad a las fuentes cerebrales profundas a través de dos tipos de sensores MEG: gradiómetros planares y magnetómetros, esta aproximación además se combina con un enfoque metodológico, utilizando dos índices de sincronización de fase: phase locking value (PLV) y phase lag index (PLI), este ultimo menos sensible a efecto la conducción volumen. Por lo tanto, se compara su comportamiento al estudiar las redes cerebrales, obteniendo que magnetómetros y PLV presentan, respectivamente, redes más densamente conectadas que gradiómetros planares y PLI, por los valores artificiales que crea el problema de la conducción de volumen. Sin embargo, cuando se trata de caracterizar redes epilépticas, el PLV ofrece mejores resultados, debido a la gran dispersión de las redes obtenidas con PLI. El análisis de redes complejas ha proporcionado nuevos conceptos que mejoran caracterización de la interacción de sistemas dinámicos. Se considera que una red está compuesta por nodos, que simbolizan sistemas, cuyas interacciones se representan por enlaces, y su comportamiento y topología puede caracterizarse por un elevado número de medidas. Existe evidencia teórica y empírica de que muchas de ellas están fuertemente correlacionadas entre sí. Por lo tanto, se ha conseguido seleccionar un pequeño grupo que caracteriza eficazmente estas redes, y condensa la información redundante. Para el análisis de redes funcionales, la selección de un umbral adecuado para decidir si un determinado valor de conectividad de la matriz de FC es significativo y debe ser incluido para un análisis posterior, se convierte en un paso crucial. En esta tesis, se han obtenido resultados más precisos al utilizar un test de subrogadas, basado en los datos, para evaluar individualmente cada uno de los enlaces, que al establecer a priori un umbral fijo para la densidad de conexiones. Finalmente, todas estas cuestiones se han aplicado al estudio de la epilepsia, caso práctico en el que se analizan las redes funcionales MEG, en estado de reposo, de dos grupos de pacientes epilépticos (generalizada idiopática y focal frontal) en comparación con sujetos control sanos. La epilepsia es uno de los trastornos neurológicos más comunes, con más de 55 millones de afectados en el mundo. Esta enfermedad se caracteriza por la predisposición a generar ataques epilépticos de actividad neuronal anormal y excesiva o bien síncrona, y por tanto, es el escenario perfecto para este tipo de análisis al tiempo que presenta un gran interés tanto desde el punto de vista clínico como de investigación. Los resultados manifiestan alteraciones especificas en la conectividad y un cambio en la topología de las redes en cerebros epilépticos, desplazando la importancia del ‘foco’ a la ‘red’, enfoque que va adquiriendo relevancia en las investigaciones recientes sobre epilepsia. ABSTRACT There are about 1014 neuronal synapses in the human brain. This huge number of connections provides the substrate for neuronal ensembles to become transiently synchronized, producing the emergence of cognitive functions such as perception, learning or thinking. Understanding the complex brain network organization on the basis of neuroimaging data represents one of the most important and exciting challenges for systems neuroscience. Several measures have been recently proposed to evaluate at various scales (single cells, cortical columns, or brain areas) how the different parts of the brain communicate. We can classify them, according to their symmetry, into two groups: symmetric measures, such as correlation, coherence or phase synchronization indexes, evaluate functional connectivity (FC); and on the other hand, the asymmetric ones, such as Granger causality or transfer entropy, are able to detect effective connectivity (EC) revealing the direction of the interaction. In modern neurosciences, the interest in functional brain networks has increased strongly with the onset of new algorithms to study interdependence between time series, the advent of modern complex network theory and the introduction of powerful techniques to record neurophysiological data, such as magnetoencephalography (MEG). However, when analyzing neurophysiological data with this approach several questions arise. In this thesis, I intend to tackle some of the practical open problems in the field. First of all, the increase in the number of time series analysis algorithms to study brain FC/EC, along with their mathematical complexity, creates the necessity of arranging them into a single, unified toolbox that allow neuroscientists, neurophysiologists and researchers from related fields to easily access and make use of them. I developed such a toolbox for this aim, it is named HERMES (http://hermes.ctb.upm.es), and encompasses several of the most common indexes for the assessment of FC and EC running for MatlabR environment. I believe that this toolbox will be very helpful to all the researchers working in the emerging field of brain connectivity analysis and will entail a great value for the scientific community. The second important practical issue tackled in this thesis is the evaluation of the sensitivity to deep brain sources of two different MEG sensors: planar gradiometers and magnetometers, in combination with the related methodological approach, using two phase synchronization indexes: phase locking value (PLV) y phase lag index (PLI), the latter one being less sensitive to volume conduction effect. Thus, I compared their performance when studying brain networks, obtaining that magnetometer sensors and PLV presented higher artificial values as compared with planar gradiometers and PLI respectively. However, when it came to characterize epileptic networks it was the PLV which gives better results, as PLI FC networks where very sparse. Complex network analysis has provided new concepts which improved characterization of interacting dynamical systems. With this background, networks could be considered composed of nodes, symbolizing systems, whose interactions with each other are represented by edges. A growing number of network measures is been applied in network analysis. However, there is theoretical and empirical evidence that many of these indexes are strongly correlated with each other. Therefore, in this thesis I reduced them to a small set, which could more efficiently characterize networks. Within this framework, selecting an appropriate threshold to decide whether a certain connectivity value of the FC matrix is significant and should be included in the network analysis becomes a crucial step, in this thesis, I used the surrogate data tests to make an individual data-driven evaluation of each of the edges significance and confirmed more accurate results than when just setting to a fixed value the density of connections. All these methodologies were applied to the study of epilepsy, analysing resting state MEG functional networks, in two groups of epileptic patients (generalized and focal epilepsy) that were compared to matching control subjects. Epilepsy is one of the most common neurological disorders, with more than 55 million people affected worldwide, characterized by its predisposition to generate epileptic seizures of abnormal excessive or synchronous neuronal activity, and thus, this scenario and analysis, present a great interest from both the clinical and the research perspective. Results revealed specific disruptions in connectivity and network topology and evidenced that networks’ topology is changed in epileptic brains, supporting the shift from ‘focus’ to ‘networks’ which is gaining importance in modern epilepsy research.

Remediation of crude oil contaminated soils by means of bitumen emulsions

Effective remediation of contaminated sites with oils, heavy metals and other chemical agents is one of the most important environmental problems all over the world. Contaminated soils by petroleum from different sites and origins, might contaminate groundwater aquifers and then be spread by rain. Many years and the requirement of remedial techniques may be needed to remediate them. However, previous experiences show the uselessness of these methods for the solution of all problems. As any case of soil contamination is different, specific studies with relevant factors at financial aspects, legal limits and waste and soil characteristics are needed. In this work, a study of the use of bitumen asphalt emulsion to remediate contaminated soils by crude oils is exposed. By means of the soil stabilization technology, using the contaminated soils as aggregates and the tailor made emulsion as binder, the feasibility of the mix application to produce stable and resistant pavements is demonstrated

An Architecture forRepresenting Biological Processes based on Networks of Bio-inspired Processors

n this paper we propose the use of Networks of Bio-inspired Processors (NBP) to model some biological phenomena within a computational framework. In particular, we propose the use of an extension of NBP named Network Evolutionary Processors Transducers to simulate chemical transformations of substances. Within a biological process, chemical transformations of substances are basic operations in the change of the state of the cell. Previously, it has been proved that NBP are computationally complete, that is, they are able to solve NP complete problems in linear time, using massively parallel computations. In addition, we propose a multilayer architecture that will allow us to design models of biological processes related to cellular communication as well as their implications in the metabolic pathways. Subsequently, these models can be applied not only to biological-cellular instances but, possibly, also to configure instances of interactive processes in many other fields like population interactions, ecological trophic networks, in dustrial ecosystems, etc.