Rule Representation in Distributed Environments with Accepting Networks of Splicing Processors.

This paper presents the model named Accepting Networks of Evolutionary Processors as NP-problem solver inspired in the biological DNA operations. A processor has a rules set, splicing rules in this model,an object multiset and a filters set. Rules can be applied in parallel since there exists a large number of copies of objects in the multiset. Processors can form a graph in order to solve a given problem. This paper shows the network configuration in order to solve the SAT problem using linear resources and time. A rule representation arquitecture in distributed environments can be easily implemented using these networks of processors, such as decision support systems, as shown in the paper.

Multiple feature points representation in target localization of wireless visual sensor networks

This paper discusses the target localization problem in wireless visual sensor networks. Additive noises and measurement errors will affect the accuracy of target localization when the visual nodes are equipped with low-resolution cameras. In the goal of improving the accuracy of target localization without prior knowledge of the target, each node extracts multiple feature points from images to represent the target at the sensor node level. A statistical method is presented to match the most correlated feature point pair for merging the position information of different sensor nodes at the base station. Besides, in the case that more than one target exists in the field of interest, a scheme for locating multiple targets is provided. Simulation results show that, our proposed method has desirable performance in improving the accuracy of locating single target or multiple targets. Results also show that the proposed method has a better trade-off between camera node usage and localization accuracy.

Numerical Error Prediction and its applications in CFD using tau-estimation

Nowadays, Computational Fluid Dynamics (CFD) solvers are widely used within the industry to model fluid flow phenomenons. Several fluid flow model equations have been employed in the last decades to simulate and predict forces acting, for example, on different aircraft configurations. Computational time and accuracy are strongly dependent on the fluid flow model equation and the spatial dimension of the problem considered. While simple models based on perfect flows, like panel methods or potential flow models can be very fast to solve, they usually suffer from a poor accuracy in order to simulate real flows (transonic, viscous). On the other hand, more complex models such as the full Navier- Stokes equations provide high fidelity predictions but at a much higher computational cost. Thus, a good compromise between accuracy and computational time has to be fixed for engineering applications. A discretisation technique widely used within the industry is the so-called Finite Volume approach on unstructured meshes. This technique spatially discretises the flow motion equations onto a set of elements which form a mesh, a discrete representation of the continuous domain. Using this approach, for a given flow model equation, the accuracy and computational time mainly depend on the distribution of nodes forming the mesh. Therefore, a good compromise between accuracy and computational time might be obtained by carefully defining the mesh. However, defining an optimal mesh for complex flows and geometries requires a very high level expertize in fluid mechanics and numerical analysis, and in most cases a simple guess of regions of the computational domain which might affect the most the accuracy is impossible. Thus, it is desirable to have an automatized remeshing tool, which is more flexible with unstructured meshes than its structured counterpart. However, adaptive methods currently in use still have an opened question: how to efficiently drive the adaptation ? Pioneering sensors based on flow features generally suffer from a lack of reliability, so in the last decade more effort has been made in developing numerical error-based sensors, like for instance the adjoint-based adaptation sensors. While very efficient at adapting meshes for a given functional output, the latter method is very expensive as it requires to solve a dual set of equations and computes the sensor on an embedded mesh. Therefore, it would be desirable to develop a more affordable numerical error estimation method. The current work aims at estimating the truncation error, which arises when discretising a partial differential equation. These are the higher order terms neglected in the construction of the numerical scheme. The truncation error provides very useful information as it is strongly related to the flow model equation and its discretisation. On one hand, it is a very reliable measure of the quality of the mesh, therefore very useful in order to drive a mesh adaptation procedure. On the other hand, it is strongly linked to the flow model equation, so that a careful estimation actually gives information on how well a given equation is solved, which may be useful in the context of _ -extrapolation or zonal modelling. The following work is organized as follows: Chap. 1 contains a short review of mesh adaptation techniques as well as numerical error prediction. In the first section, Sec. 1.1, the basic refinement strategies are reviewed and the main contribution to structured and unstructured mesh adaptation are presented. Sec. 1.2 introduces the definitions of errors encountered when solving Computational Fluid Dynamics problems and reviews the most common approaches to predict them. Chap. 2 is devoted to the mathematical formulation of truncation error estimation in the context of finite volume methodology, as well as a complete verification procedure. Several features are studied, such as the influence of grid non-uniformities, non-linearity, boundary conditions and non-converged numerical solutions. This verification part has been submitted and accepted for publication in the Journal of Computational Physics. Chap. 3 presents a mesh adaptation algorithm based on truncation error estimates and compares the results to a feature-based and an adjoint-based sensor (in collaboration with Jorge Ponsín, INTA). Two- and three-dimensional cases relevant for validation in the aeronautical industry are considered. This part has been submitted and accepted in the AIAA Journal. An extension to Reynolds Averaged Navier- Stokes equations is also included, where _ -estimation-based mesh adaptation and _ -extrapolation are applied to viscous wing profiles. The latter has been submitted in the Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering. Keywords: mesh adaptation, numerical error prediction, finite volume Hoy en día, la Dinámica de Fluidos Computacional (CFD) es ampliamente utilizada dentro de la industria para obtener información sobre fenómenos fluidos. La Dinámica de Fluidos Computacional considera distintas modelizaciones de las ecuaciones fluidas (Potencial, Euler, Navier-Stokes, etc) para simular y predecir las fuerzas que actúan, por ejemplo, sobre una configuración de aeronave. El tiempo de cálculo y la precisión en la solución depende en gran medida de los modelos utilizados, así como de la dimensión espacial del problema considerado. Mientras que modelos simples basados en flujos perfectos, como modelos de flujos potenciales, se pueden resolver rápidamente, por lo general aducen de una baja precisión a la hora de simular flujos reales (viscosos, transónicos, etc). Por otro lado, modelos más complejos tales como el conjunto de ecuaciones de Navier-Stokes proporcionan predicciones de alta fidelidad, a expensas de un coste computacional mucho más elevado. Por lo tanto, en términos de aplicaciones de ingeniería se debe fijar un buen compromiso entre precisión y tiempo de cálculo. Una técnica de discretización ampliamente utilizada en la industria es el método de los Volúmenes Finitos en mallas no estructuradas. Esta técnica discretiza espacialmente las ecuaciones del movimiento del flujo sobre un conjunto de elementos que forman una malla, una representación discreta del dominio continuo. Utilizando este enfoque, para una ecuación de flujo dado, la precisión y el tiempo computacional dependen principalmente de la distribución de los nodos que forman la malla. Por consiguiente, un buen compromiso entre precisión y tiempo de cálculo se podría obtener definiendo cuidadosamente la malla, concentrando sus elementos en aquellas zonas donde sea estrictamente necesario. Sin embargo, la definición de una malla óptima para corrientes y geometrías complejas requiere un nivel muy alto de experiencia en la mecánica de fluidos y el análisis numérico, así como un conocimiento previo de la solución. Aspecto que en la mayoría de los casos no está disponible. Por tanto, es deseable tener una herramienta que permita adaptar los elementos de malla de forma automática, acorde a la solución fluida (remallado). Esta herramienta es generalmente más flexible en mallas no estructuradas que con su homóloga estructurada. No obstante, los métodos de adaptación actualmente en uso todavía dejan una pregunta abierta: cómo conducir de manera eficiente la adaptación. Sensores pioneros basados en las características del flujo en general, adolecen de una falta de fiabilidad, por lo que en la última década se han realizado grandes esfuerzos en el desarrollo numérico de sensores basados en el error, como por ejemplo los sensores basados en el adjunto. A pesar de ser muy eficientes en la adaptación de mallas para un determinado funcional, este último método resulta muy costoso, pues requiere resolver un doble conjunto de ecuaciones: la solución y su adjunta. Por tanto, es deseable desarrollar un método numérico de estimación de error más asequible. El presente trabajo tiene como objetivo estimar el error local de truncación, que aparece cuando se discretiza una ecuación en derivadas parciales. Estos son los términos de orden superior olvidados en la construcción del esquema numérico. El error de truncación proporciona una información muy útil sobre la solución: es una medida muy fiable de la calidad de la malla, obteniendo información que permite llevar a cabo un procedimiento de adaptación de malla. Está fuertemente relacionado al modelo matemático fluido, de modo que una estimación precisa garantiza la idoneidad de dicho modelo en un campo fluido, lo que puede ser útil en el contexto de modelado zonal. Por último, permite mejorar la precisión de la solución resolviendo un nuevo sistema donde el error local actúa como término fuente (_ -extrapolación). El presenta trabajo se organiza de la siguiente manera: Cap. 1 contiene una breve reseña de las técnicas de adaptación de malla, así como de los métodos de predicción de los errores numéricos. En la primera sección, Sec. 1.1, se examinan las estrategias básicas de refinamiento y se presenta la principal contribución a la adaptación de malla estructurada y no estructurada. Sec 1.2 introduce las definiciones de los errores encontrados en la resolución de problemas de Dinámica Computacional de Fluidos y se examinan los enfoques más comunes para predecirlos. Cap. 2 está dedicado a la formulación matemática de la estimación del error de truncación en el contexto de la metodología de Volúmenes Finitos, así como a un procedimiento de verificación completo. Se estudian varias características que influyen en su estimación: la influencia de la falta de uniformidad de la malla, el efecto de las no linealidades del modelo matemático, diferentes condiciones de contorno y soluciones numéricas no convergidas. Esta parte de verificación ha sido presentada y aceptada para su publicación en el Journal of Computational Physics. Cap. 3 presenta un algoritmo de adaptación de malla basado en la estimación del error de truncación y compara los resultados con sensores de featured-based y adjointbased (en colaboración con Jorge Ponsín del INTA). Se consideran casos en dos y tres dimensiones, relevantes para la validación en la industria aeronáutica. Este trabajo ha sido presentado y aceptado en el AIAA Journal. También se incluye una extensión de estos métodos a las ecuaciones RANS (Reynolds Average Navier- Stokes), en donde adaptación de malla basada en _ y _ -extrapolación son aplicados a perfiles con viscosidad de alas. Este último trabajo se ha presentado en los Actas de la Institución de Ingenieros Mecánicos, Parte G: Journal of Aerospace Engineering. Palabras clave: adaptación de malla, predicción del error numérico, volúmenes finitos

Terminological Importation for Adapting Reusable Knowledge Representation Components in the KSM Environment

This paper describes the adaptation approach of reusable knowledge representation components used in the KSM environment for the formulation and operationalisation of structured knowledge models. Reusable knowledge representation components in KSM are called primitives of representation. A primitive of representation provides: (1) a knowledge representation formalism (2) a set of tasks that use this knowledge together with several problem-solving methods to carry out these tasks (3) a knowledge acquisition module that provides different services to acquire and validate this knowledge (4) an abstract terminology about the linguistic categories included in the representation language associated to the primitive. Primitives of representation usually are domain independent. A primitive of representation can be adapted to support knowledge in a given domain by importing concepts from this domain. The paper describes how this activity can be carried out by mean of a terminological importation. Informally, a terminological importation partially populates an abstract terminology with concepts taken from a given domain. The information provided by the importation can be used by the acquisition and validation facilities to constraint the classes of knowledge that can be described using the representation formalism according to the domain knowledge. KSM provides the LINK-S language to specify terminological importation from a domain terminology to an abstract one. These terminologies are described in KSM by mean of the CONCEL language. Terminological importation is used to adapt reusable primitives of representation in order to increase the usability degree of such components in these domains. In addition, two primitives of representation can share a common vocabulary by importing common domain CONCEL terminologies (conceptual vocabularies). It is a necessary condition to make possible the interoperability between different, heterogeneous knowledge representation components in the framework of complex knowledge - based architectures.

Timed mind maps using MINDMANAGER & MS-PROJECT for educational innovation

The adaptation to the European Higher Education Area (EHEA) is becoming a great challenge for the University Community, especially for its teaching and research staff, which is involved actively in the teaching-learning process. It is also inducing a paradigm change for lecturers and students. Among the methodologies used for processes of teaching innovation, system thinking plays an important role when working mainly with mind maps, and is focused to highlighting the essence of the knowledge, allowing its visual representation. In this paper, a method for using these mind maps for organizing a particular subject is explained. This organization is completed with the definition of duration, precedence relationships and resources for each of these activities, as well as with their corresponding monitoring. Mind maps are generated by means of the MINDMANAGER package whilst Ms-PROJECT is used for establishing tasks relationships, durations, resources, and monitoring. Summarizing, a procedure and the necessary set of applications for self organizing and managing (timed) scheduled teaching tasks has been described in this paper.

The Economic Value of Residential Land in Historical Areas: An Application of the Residual Method to the Secondary Market

Land value bears significant weight in house prices in historical town centers. An essential aim for regulating the mortgage market, particularly in the financial and property crisis that countries such as Spain are undergoing, is to have at hand objective procedures for its valuation, whatever the conditions (location, construction, planning). Of all the factors contributing to house price make-up, the land is the only one whose value does not depend on acquisition cost, but rather on the location-time binomial. That is to say, the specific circumstances at that point and at the exact moment of valuation. For this reason, the most commonly applied procedure for land valuation in town centers is the use of the residual method: once the selling price of new housing in a district is known, the other necessary costs and expenses of development are deducted, including those of building and the developer’s profit. The value left is that of the land. To apply these procedures it is vital to have figures such as building costs, technical fees, tax costs, etc. But, above all, it is essential to obtain the selling price of the new housing. This is not always feasible, on account of the lack of newbuild development in this location. This shortage of information occurs in historical town cities, where urban renewal is slight due to the heritage-protection policies, and where, nevertheless there is substantial activity in the secondary market. In these circumstances, as an alternative for land valuation in consolidated urban areas, we have the adaptation of the residual method to the particular characteristics of the secondary market. To these ends, there is the proposal for the appreciation of the dwelling which follows, in a backwards direction, the application of traditional depreciation methods proposed by the various valuation manuals and guidelines. The reliability of the results obtained is analyzed by contrasting it with published figures for newly-built properties, according to different rules applied in administrative appraisals in Spain and the incidence of an eventual correction due to conservation state.

Timed mind maps using mindmanager & msproject for educational innovation

The adaptation to the European Higher Education Area (EHEA) is becoming a great challenge for the University Community, especially for its teaching and research staff, which is involved actively in the teaching-learning process. It is also inducing a paradigm change for lecturers and students. Among the methodologies used for processes of teaching innovation, system thinking plays an important role when working mainly with mind maps, and is focused to highlighting the essence of the knowledge, allowing its visual representation. In this paper, a method for using these mind maps for organizing a particular subject is explained. This organization is completed with the definition of duration, precedence relationships and resources for each of these activities, as well as with their corresponding monitoring. Mind maps are generated by means of the MINDMANAGER package whilst Ms-PROJECT is used for establishing tasks relationships, durations, resources, and monitoring. Summarizing, a procedure and the necessary set of applications for self organizing and managing (timed) scheduled teaching tasks has been described in this paper

Using modular neural networks to model self-consciousness and self-representation for artificial entities

Self-consciousness implies not only self or group recognition, but also real knowledge of one’s own identity. Self-consciousness is only possible if an individual is intelligent enough to formulate an abstract self-representation. Moreover, it necessarily entails the capability of referencing and using this elf-representation in connection with other cognitive features, such as inference, and the anticipation of the consequences of both one’s own and other individuals’ acts. In this paper, a cognitive architecture for self-consciousness is proposed. This cognitive architecture includes several modules: abstraction, self-representation, other individuals'representation, decision and action modules. It includes a learning process of self-representation by direct (self-experience based) and observational learning (based on the observation of other individuals). For model implementation a new approach is taken using Modular Artificial Neural Networks (MANN). For model testing, a virtual environment has been implemented. This virtual environment can be described as a holonic system or holarchy, meaning that it is composed of autonomous entities that behave both as a whole and as part of a greater whole. The system is composed of a certain number of holons interacting. These holons are equipped with cognitive features, such as sensory perception, and a simplified model of personality and self-representation. We explain holons’ cognitive architecture that enables dynamic self-representation. We analyse the effect of holon interaction, focusing on the evolution of the holon’s abstract self-representation. Finally, the results are explained and analysed and conclusions drawn.

Computational model for local damage assesment of structures

In the last years many studies have been developed to analyze the seismic behavior throug the damage concept. In fact, the evaluation of the structural damage is important in order to quantify the safety of new and existing structures and, also, to establish a framework for seismic retrofitting decision making of structures. Most proposed models are based on a post-earthquake evaluation in such a way they uncouple the computation of the structural response from that of damage. However, there are other models which include explicity the existing coupling between the degradation and the structural mechanical beaviour. Those models are closer to the physical reality and its formulation is based on the principles of Continuum Damage Mechanics. In the present work, a coupled model is formulated using a simplified application of the Continuum Damage Mechanics to the analysis of frames and allows its representation in standard finite element programs. This work is part of the activities developed by the Structural Mechanics Department (UPM) within ICONS (European Research Project on Innovative Seismic Design Concepts for New and Existing Structures).

Functional characterization of YODA, a mitogen-activated protein kinase kinase kinase (MAP3K) that regulates a novel innate immunity pathway in Arabidopsis thaliana

Las cascadas de señalización mediadas por proteína quinasas activadas por mitógeno (MAP quinasas) son capaces de integrar y transducir señales ambientales en respuestas celulares. Entre estas señales se encuentran los PAMPs/MAMPs (Pathogen/Microbe-Associated Molecular Patterns), que son moléculas de patógenos o microorganismos, o los DAMPs (Damaged-Associated Molecular Patterns), que son moléculas derivadas de las plantas producidas en respuesta a daño celular. Tras el reconocimiento de los PAMPs/DAMPs por receptores de membrana denominados PRRs (Pattern Recognition Receptors), como los receptores con dominio quinasa (RLKs) o los receptores sin dominio quinasa (RLPs), se activan respuestas moleculares, incluidas cascadas de MAP quinasas, que regulan la puesta en marcha de la inmunidad activada por PAMPs (PTI). Esta Tesis describe la caracterización funcional de la MAP quinasa quinasa quinasa (MAP3K) YODA (YDA), que actúa como un regulador clave de la PTI en Arabidopsis. Se ha descrito previamente que YDA controla varios procesos de desarrollo, como la regulación del patrón estomático, la elongación del zigoto y la arquitectura floral. Hemos caracterizado un alelo mutante hipomórfico de YDA (elk2 o yda11) que presenta una elevada susceptibilidad a patógenos biótrofos y necrótrofos. Notablemente, plantas que expresan una forma constitutivamente activa de YDA (CA-YDA), con una deleción en el dominio N-terminal, presentan una resistencia de amplio espectro frente a diferentes tipos de patógenos, incluyendo hongos, oomicetos y bacterias, lo que indica que YDA juega un papel importante en la regulación de la resistencia de las plantas a patógenos. Nuestros datos indican que esta función es independiente de las respuestas inmunes mediadas por los receptores previamente caracterizados FLS2 y CERK1, que reconocen los PAMPs flg22 y quitina, respectivamente, y que están implicados en la resistencia de Arabidopsis frente a bacterias y hongos. Hemos demostrado que YDA controla la resistencia frente al hongo necrótrofo Plectosphaerella cucumerina y el patrón estomático mediante su interacción genética con la RLK ERECTA (ER), un PRR implicado en la regulación de estos procesos. Por el contrario, la interacción genética entre ER y YDA en la regulación de otros procesos de desarrollo es aditiva en lugar de epistática. Análisis genéticos indicaron que MPK3, una MAP quinasa que funciona aguas abajo de YDA en el desarrollo estomático, es un componente de la ruta de señalización mediada por YDA para la resistencia frente a P. cucumerina, lo que sugiere que el desarrollo de las plantas y la PTI comparten el módulo de transducción de MAP quinasas asociado a YDA. Nuestros experimentos han revelado que la resistencia mediada por YDA es independiente de las rutas de señalización reguladas por las hormonas de defensa ácido salicílico, ácido jasmónico, ácido abscísico o etileno, y también es independiente de la ruta de metabolitos secundarios derivados del triptófano, que están implicados en inmunidad vegetal. Además, hemos demostrado que respuestas asociadas a PTI, como el aumento en la concentración de calcio citoplásmico, la producción de especies reactivas de oxígeno, la fosforilación de MAP quinasas y la expresión de genes de defensa, no están afectadas en el mutante yda11. La expresión constitutiva de la proteína CA-YDA en plantas de Arabidopsis no provoca un aumento de las respuestas PTI, lo que sugiere la existencia de mecanismos de resistencia adicionales regulados por YDA que son diferentes de los regulados por FLS2 y CERK1. En línea con estos resultados, nuestros datos transcriptómicos revelan una sobre-representación en plantas CA-YDA de genes de defensa que codifican, por ejemplo, péptidos antimicrobianos o reguladores de muerte celular, o proteínas implicadas en la biogénesis de la pared celular, lo que sugiere una conexión potencial entre la composición e integridad de la pared celular y la resistencia de amplio espectro mediada por YDA. Además, análisis de fosfoproteómica indican la fosforilación diferencial de proteínas relacionadas con la pared celular en plantas CA-YDA en comparación con plantas silvestres. El posible papel de la ruta ER-YDA en la regulación de la integridad de la pared celular está apoyado por análisis bioquímicos y glicómicos de las paredes celulares de plantas er, yda11 y CA-YDA, que revelaron cambios significativos en la composición de la pared celular de estos genotipos en comparación con la de plantas silvestres. En resumen, nuestros datos indican que ER y YDA forman parte de una nueva ruta de inmunidad que regula la integridad de la pared celular y respuestas defensivas, confiriendo una resistencia de amplio espectro frente a patógenos. ABSTRACT Plant mitogen-activated protein kinase (MAPK) cascades transduce environmental signals and developmental cues into cellular responses. Among these signals are the pathogen- or microbe-associated molecular patterns (PAMPs or MAMPs) and the damage-associated molecular patterns (DAMPs). These PAMPs/DAMPs, upon recognition by plant pattern recognition receptors (PRRs), such as Receptor-Like Kinases (RLKs) and Receptor-Like Proteins (RLPs), activate molecular responses, including MAPK cascades, which regulate the onset of PAMP-triggered immunity (PTI). This Thesis describes the functional characterization of the MAPK kinase kinase (MAP3K) YODA (YDA) as a key regulator of Arabidopsis PTI. YDA has been previously described to control several developmental processes, such as stomatal patterning, zygote elongation and inflorescence architecture. We characterized a hypomorphic, non-embryo lethal mutant allele of YDA (elk2 or yda11) that was found to be highly susceptible to biotrophic and necrotrophic pathogens. Remarkably, plants expressing a constitutive active form of YDA (CA-YDA), with a deletion in the N-terminal domain, showed broad-spectrum resistance to different types of pathogens, including fungi, oomycetes and bacteria, indicating that YDA plays a relevant function in plant resistance to pathogens. Our data indicated that this function is independent of the immune responses regulated by the well characterized FLS2 and CERK1 RLKs, which are the PRRs recognizing flg22 and chitin PAMPs, respectively, and are required for Arabidopsis resistance to bacteria and fungi. We demonstrate that YDA controls resistance to the necrotrophic fungus Plectosphaerella cucumerina and stomatal patterning by genetically interacting with ERECTA (ER) RLK, a PRR involved in regulating these processes. In contrast, the genetic interaction between ER and YDA in the regulation of other ER-associated developmental processes was additive, rather than epistatic. Genetic analyses indicated that MPK3, a MAP kinase that functions downstream of YDA in stomatal development, also regulates plant resistance to P. cucumerina in a YDA-dependent manner, suggesting that the YDA-associated MAPK transduction module is shared in plant development and PTI. Our experiments revealed that YDA-mediated resistance was independent of signalling pathways regulated by defensive hormones like salicylic acid, jasmonic acid, abscisic acid or ethylene, and of the tryptophan-derived metabolites pathway, which are involved in plant immunity. In addition, we showed that PAMP-mediated PTI responses, such as the increase of cytoplasmic Ca2+ concentration, reactive oxygen species (ROS) burst, MAPK phosphorylation, and expression of defense-related genes are not impaired in the yda11 mutant. Furthermore, the expression of CA-YDA protein does not result in enhanced PTI responses, further suggesting the existence of additional mechanisms of resistance regulated by YDA that differ from those regulated by the PTI receptors FLS2 and CERK1. In line with these observations, our transcriptomic data revealed the over-representation in CA-YDA plants of defensive genes, such as those encoding antimicrobial peptides and cell death regulators, and genes encoding cell wall-related proteins, suggesting a potential link between plant cell wall composition and integrity and broad spectrum resistance mediated by YDA. In addition, phosphoproteomic data revealed an over-representation of genes encoding wall-related proteins in CA-YDA plants in comparison with wild-type plants. The putative role of the ER-YDA pathway in regulating cell wall integrity was further supported by biochemical and glycomics analyses of er, yda11 and CA-YDA cell walls, which revealed significant changes in the cell wall composition of these genotypes compared with that of wild-type plants. In summary, our data indicate that ER and YDA are components of a novel immune pathway that regulates cell wall integrity and defensive responses, which confer broad-spectrum resistance to pathogens.

Strong Connectivity in Directed Hypergraphs and its Application to the Atomic Decomposition of Ontologies

Los hipergrafos dirigidos se han empleado en problemas relacionados con lógica proposicional, bases de datos relacionales, linguística computacional y aprendizaje automático. Los hipergrafos dirigidos han sido también utilizados como alternativa a los grafos (bipartitos) dirigidos para facilitar el estudio de las interacciones entre componentes de sistemas complejos que no pueden ser fácilmente modelados usando exclusivamente relaciones binarias. En este contexto, este tipo de representación es conocida como hiper-redes. Un hipergrafo dirigido es una generalización de un grafo dirigido especialmente adecuado para la representación de relaciones de muchos a muchos. Mientras que una arista en un grafo dirigido define una relación entre dos de sus nodos, una hiperarista en un hipergrafo dirigido define una relación entre dos conjuntos de sus nodos. La conexión fuerte es una relación de equivalencia que divide el conjunto de nodos de un hipergrafo dirigido en particiones y cada partición define una clase de equivalencia conocida como componente fuertemente conexo. El estudio de los componentes fuertemente conexos de un hipergrafo dirigido puede ayudar a conseguir una mejor comprensión de la estructura de este tipo de hipergrafos cuando su tamaño es considerable. En el caso de grafo dirigidos, existen algoritmos muy eficientes para el cálculo de los componentes fuertemente conexos en grafos de gran tamaño. Gracias a estos algoritmos, se ha podido averiguar que la estructura de la WWW tiene forma de “pajarita”, donde más del 70% del los nodos están distribuidos en tres grandes conjuntos y uno de ellos es un componente fuertemente conexo. Este tipo de estructura ha sido también observada en redes complejas en otras áreas como la biología. Estudios de naturaleza similar no han podido ser realizados en hipergrafos dirigidos porque no existe algoritmos capaces de calcular los componentes fuertemente conexos de este tipo de hipergrafos. En esta tesis doctoral, hemos investigado como calcular los componentes fuertemente conexos de un hipergrafo dirigido. En concreto, hemos desarrollado dos algoritmos para este problema y hemos determinado que son correctos y cuál es su complejidad computacional. Ambos algoritmos han sido evaluados empíricamente para comparar sus tiempos de ejecución. Para la evaluación, hemos producido una selección de hipergrafos dirigidos generados de forma aleatoria inspirados en modelos muy conocidos de grafos aleatorios como Erdos-Renyi, Newman-Watts-Strogatz and Barabasi-Albert. Varias optimizaciones para ambos algoritmos han sido implementadas y analizadas en la tesis. En concreto, colapsar los componentes fuertemente conexos del grafo dirigido que se puede construir eliminando ciertas hiperaristas complejas del hipergrafo dirigido original, mejora notablemente los tiempos de ejecucion de los algoritmos para varios de los hipergrafos utilizados en la evaluación. Aparte de los ejemplos de aplicación mencionados anteriormente, los hipergrafos dirigidos han sido también empleados en el área de representación de conocimiento. En concreto, este tipo de hipergrafos se han usado para el cálculo de módulos de ontologías. Una ontología puede ser definida como un conjunto de axiomas que especifican formalmente un conjunto de símbolos y sus relaciones, mientras que un modulo puede ser entendido como un subconjunto de axiomas de la ontología que recoge todo el conocimiento que almacena la ontología sobre un conjunto especifico de símbolos y sus relaciones. En la tesis nos hemos centrado solamente en módulos que han sido calculados usando la técnica de localidad sintáctica. Debido a que las ontologías pueden ser muy grandes, el cálculo de módulos puede facilitar las tareas de re-utilización y mantenimiento de dichas ontologías. Sin embargo, analizar todos los posibles módulos de una ontología es, en general, muy costoso porque el numero de módulos crece de forma exponencial con respecto al número de símbolos y de axiomas de la ontología. Afortunadamente, los axiomas de una ontología pueden ser divididos en particiones conocidas como átomos. Cada átomo representa un conjunto máximo de axiomas que siempre aparecen juntos en un modulo. La decomposición atómica de una ontología es definida como un grafo dirigido de tal forma que cada nodo del grafo corresponde con un átomo y cada arista define una dependencia entre una pareja de átomos. En esta tesis introducimos el concepto de“axiom dependency hypergraph” que generaliza el concepto de descomposición atómica de una ontología. Un modulo en una ontología correspondería con un componente conexo en este tipo de hipergrafos y un átomo de una ontología con un componente fuertemente conexo. Hemos adaptado la implementación de nuestros algoritmos para que funcionen también con axiom dependency hypergraphs y poder de esa forma calcular los átomos de una ontología. Para demostrar la viabilidad de esta idea, hemos incorporado nuestros algoritmos en una aplicación que hemos desarrollado para la extracción de módulos y la descomposición atómica de ontologías. A la aplicación la hemos llamado HyS y hemos estudiado sus tiempos de ejecución usando una selección de ontologías muy conocidas del área biomédica, la mayoría disponibles en el portal de Internet NCBO. Los resultados de la evaluación muestran que los tiempos de ejecución de HyS son mucho mejores que las aplicaciones más rápidas conocidas. ABSTRACT Directed hypergraphs are an intuitive modelling formalism that have been used in problems related to propositional logic, relational databases, computational linguistic and machine learning. Directed hypergraphs are also presented as an alternative to directed (bipartite) graphs to facilitate the study of the interactions between components of complex systems that cannot naturally be modelled as binary relations. In this context, they are known as hyper-networks. A directed hypergraph is a generalization of a directed graph suitable for representing many-to-many relationships. While an edge in a directed graph defines a relation between two nodes of the graph, a hyperedge in a directed hypergraph defines a relation between two sets of nodes. Strong-connectivity is an equivalence relation that induces a partition of the set of nodes of a directed hypergraph into strongly-connected components. These components can be collapsed into single nodes. As result, the size of the original hypergraph can significantly be reduced if the strongly-connected components have many nodes. This approach might contribute to better understand how the nodes of a hypergraph are connected, in particular when the hypergraphs are large. In the case of directed graphs, there are efficient algorithms that can be used to compute the strongly-connected components of large graphs. For instance, it has been shown that the macroscopic structure of the World Wide Web can be represented as a “bow-tie” diagram where more than 70% of the nodes are distributed into three large sets and one of these sets is a large strongly-connected component. This particular structure has been also observed in complex networks in other fields such as, e.g., biology. Similar studies cannot be conducted in a directed hypergraph because there does not exist any algorithm for computing the strongly-connected components of the hypergraph. In this thesis, we investigate ways to compute the strongly-connected components of directed hypergraphs. We present two new algorithms and we show their correctness and computational complexity. One of these algorithms is inspired by Tarjan’s algorithm for directed graphs. The second algorithm follows a simple approach to compute the stronglyconnected components. This approach is based on the fact that two nodes of a graph that are strongly-connected can also reach the same nodes. In other words, the connected component of each node is the same. Both algorithms are empirically evaluated to compare their performances. To this end, we have produced a selection of random directed hypergraphs inspired by existent and well-known random graphs models like Erd˝os-Renyi and Newman-Watts-Strogatz. Besides the application examples that we mentioned earlier, directed hypergraphs have also been employed in the field of knowledge representation. In particular, they have been used to compute the modules of an ontology. An ontology is defined as a collection of axioms that provides a formal specification of a set of terms and their relationships; and a module is a subset of an ontology that completely captures the meaning of certain terms as defined in the ontology. In particular, we focus on the modules computed using the notion of syntactic locality. As ontologies can be very large, the computation of modules facilitates the reuse and maintenance of these ontologies. Analysing all modules of an ontology, however, is in general not feasible as the number of modules grows exponentially in the number of terms and axioms of the ontology. Nevertheless, the modules can succinctly be represented using the Atomic Decomposition of an ontology. Using this representation, an ontology can be partitioned into atoms, which are maximal sets of axioms that co-occur in every module. The Atomic Decomposition is then defined as a directed graph such that each node correspond to an atom and each edge represents a dependency relation between two atoms. In this thesis, we introduce the notion of an axiom dependency hypergraph which is a generalization of the atomic decomposition of an ontology. A module in the ontology corresponds to a connected component in the hypergraph, and the atoms of the ontology to the strongly-connected components. We apply our algorithms for directed hypergraphs to axiom dependency hypergraphs and in this manner, we compute the atoms of an ontology. To demonstrate the viability of this approach, we have implemented the algorithms in the application HyS which computes the modules of ontologies and calculate their atomic decomposition. In the thesis, we provide an experimental evaluation of HyS with a selection of large and prominent biomedical ontologies, most of which are available in the NCBO Bioportal. HyS outperforms state-of-the-art implementations in the tasks of extracting modules and computing the atomic decomposition of these ontologies.

Floating zone stability

The present state of de preparation of an experiment on floating liquid zones to be performed in the first Spacelab flight is presented. In this experiment,a liquid bridge is to be placed between two parallel coaxial disks (in the Fluid Physics Module)and subjected to very precise disturbances in order to check the theoretical predictions about its stability limits and behavior under mechanical inputs: stretching of the zone, filling or removing the liquid,axial vibration, rotation, disalignment, etc. Several aspects of the research are introduced:1) Relevance of the study. 2) Theoretical predictions of the liquid behavior regarding the floating-zone stability limits and the expected response to vibrational and rotational disturbances. 3) Ground support experiments using the Plateau technique or the small scale simulation. 4) Instrumental aspects of the experimentation: the Fluid Physics Module utilization and post-flight data analysis.5)Research program for future flights.

A new boundary condition solved with B.I.E.M.

Among the classical operators of mathematical physics the Laplacian plays an important role due to the number of different situations that can be modelled by it. Because of this a great effort has been made by mathematicians as well as by engineers to master its properties till the point that nearly everything has been said about them from a qualitative viewpoint. Quantitative results have also been obtained through the use of the new numerical techniques sustained by the computer. Finite element methods and boundary techniques have been successfully applied to engineering problems as can be seen in the technical literature (for instance [ l ] , [2], [3] . Boundary techniques are especially advantageous in those cases in which the main interest is concentrated on what is happening at the boundary. This situation is very usual in potential problems due to the properties of harmonic functions. In this paper we intend to show how a boundary condition different from the classical, but physically sound, is introduced without any violence in the discretization frame of the Boundary Integral Equation Method. The idea will be developed in the context of heat conduction in axisymmetric problems but it is hoped that its extension to other situations is straightforward. After the presentation of the method several examples will show the capabilities of modelling a physical problem.

Merging person-specific bio-markers for predicting oral cancer recurrence through an ontology

One of the major problems related to cancer treatment is its recurrence. Without knowing in advance how likely the cancer will relapse, clinical practice usually recommends adjuvant treatments that have strong side effects. A way to optimize treatments is to predict the recurrence probability by analyzing a set of bio-markers. The NeoMark European project has identified a set of preliminary bio-markers for the case of oral cancer by collecting a large series of data from genomic, imaging, and clinical evidence. This heterogeneous set of data needs a proper representation in order to be stored, computed, and communicated efficiently. Ontologies are often considered the proper mean to integrate biomedical data, for their high level of formality and for the need of interoperable, universally accepted models. This paper presents the NeoMark system and how an ontology has been designed to integrate all its heterogeneous data. The system has been validated in a pilot in which data will populate the ontology and will be made public for further research.

MEDVIR: 3D visual interface applied to gene profile analisys.

The origins for this work arise in response to the increasing need for biologists and doctors to obtain tools for visual analysis of data. When dealing with multidimensional data, such as medical data, the traditional data mining techniques can be a tedious and complex task, even to some medical experts. Therefore, it is necessary to develop useful visualization techniques that can complement the expert’s criterion, and at the same time visually stimulate and make easier the process of obtaining knowledge from a dataset. Thus, the process of interpretation and understanding of the data can be greatly enriched. Multidimensionality is inherent to any medical data, requiring a time-consuming effort to get a clinical useful outcome. Unfortunately, both clinicians and biologists are not trained in managing more than four dimensions. Specifically, we were aimed to design a 3D visual interface for gene profile analysis easy in order to be used both by medical and biologist experts. In this way, a new analysis method is proposed: MedVir. This is a simple and intuitive analysis mechanism based on the visualization of any multidimensional medical data in a three dimensional space that allows interaction with experts in order to collaborate and enrich this representation. In other words, MedVir makes a powerful reduction in data dimensionality in order to represent the original information into a three dimensional environment. The experts can interact with the data and draw conclusions in a visual and quickly way.