Ideas that kill

Reseña de: Fernández Soldevilla, Gaizka, La voluntad del Gudari. Génesis y metástasis de la violencia de ETA, Madrid, Tecnos, 2016, 366 p

Cognición y representación interna de entornos dinámicos en el cerebro de los mamíferos

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Ciencias Biológicas, leída el 07/05/2021El tiempo es una de las dimensiones fundamentales de la realidad. Paradójicamente, los fenómenos temporales del mundo natural contienen ingentes cantidades de información redundante, y a pesar de ello, codificar internamente el tiempo en el cerebro es imprescindible para anticiparse a peligros en ambientes dinámicos. No obstante, dedicar grandes cantidades de recursos cognitivos a procesar las características espacio-temporales de entornos complejos debería ser incompatible con la supervivencia, que requiere respuestas rápidas. Aun así, los animales son capaces de tomar decisiones en intervalos de tiempo muy estrechos. ¿Cómo consigue hacer esto el cerebro? Como respuesta al balance entre complejidad y velocidad, la hipótesis de la compactación del tiempo propone que el cerebro no codifica el tiempo explícitamente, sino que lo integra en el espacio. En teoría, la compactación del tiempo simplifica las representaciones internas del entorno, reduciendo significativamente la carga de trabajo dedicada a la planificación y la toma de decisiones. La compactación del tiempo proporciona un marco operativo que pretende explicar cómo las situaciones dinámicas, percibidas o producidas, se representan cognitivamente en forma de predicciones espaciales o representaciones internas compactas (CIR), que pueden almacenarse en la memoria y recuperarse más adelante para generar respuestas. Aunque la compactación del tiempo ya ha sido implementada en robots, hasta ahora no se había comprobado su existencia como mecanismo biológico y cognitivo en el cerebro...Time is one of the most prominent dimensions that organize reality. Paradoxically, there are loads of redundant information contained within the temporal features of the natural world, and yet internal coding of time in the brain seems to be crucial for anticipating time-changing, dynamic hazards. Allocating such significant brain resources to process spatiotemporal aspects of complex environments should apparently be incompatible with survival, which requires fast and accurate responses. Nonetheless, animals make decisions under pressure and in narrow time windows. How does the brain achieve this? An effort to resolve the complexity-velocity trade-off led to a hypothesis called time compaction, which states the brain does not encode time explicitly but embeds it into space. Theoretically, time compaction can significantly simplify internal representations of the environment and hence ease the brain workload devoted to planning and decision-making. Time compaction also provides an operational framework that aims to explain how perceived and produced dynamic situations are cognitively represented, in the form of spatial predictions or compact internal representations (CIRs) that can be stored in memory and be used later on to guide behaviour and generate action. Although successfully implemented in robots, time compaction still lacked assessment of its biological soundness as an actual cognitive mechanism in the brain...Fac. de Ciencias BiológicasTRUEunpu

Polymers in diffusion artistic styles epoch

Este trabajo plantea la llegada de las resinas sintéticas al hecho artístico tras la 2ª Guerra Mundial. Podremos conocer cuáles son las características específicas de algunos polímeros por las que algunos artistas se han sentido atraídos y han decidido hacerlos suyos para adecuarlos a lo que desean expresar en sus creaciones volumétricas o qué finalidad estética buscan con su empleo. Por lo general, los escultores han utilizado los plásticos cuyas propiedades más se adecuan al discurso narrativo plástico que buscan para ejecutar sus obras, y que no hubiera sido posible con otros materiales.This work raises the arrival of the synthetic resins to the artistic fact after 2 ª World War. We will be able to know which are the specific characteristics of some polymers for which some artist have felt attracted and have decided to make them his (yours) to adapt them to what they want to express in his volumetric creations or what aesthetic purpose they search with his employment. In general, the sculptors have used the plastic ones whose properties more are adapted to the narrative plastic speech for that they look to execute his works, and that had not been possible with other materials

Hierarchical x-fem applied to n-phase flow

In this work we proposed an extencion of the level set technique to track any number of free surfaces. This extension is based in a hierarchical ordering of several level set functions. To complete the X–FEM approach, the enrichment via partition of the unity method is also extended. The ridge function, base of the enriched interpolation, is restated to include several level sets and the hierarchy between them

Hierarchical X-FEM for n-phase flow (n > 2)

The eXtended Finite Element Method (X-FEM) has been successfully used in two-phase flow problems involving a moving interface. In order to simulate problems involving more than two phases, the X-FEM has to be further eXtended. The proposed approach is presented in the case of a quasi-static Stokes n-phase flow and it is based on using an ordered collection of level set functions to describe the location of the phases. A level set hierarchy allows describing triple junctions avoiding overlapping or “voids” between materials. Moreover, an enriched solution accounting for several simultaneous phases inside one element is proposed. The interpolation functions corresponding to the enriched degrees of freedom require redefining the associated ridge function accounting for all the level sets. The computational implementation of this scheme involves calculating integrals in elements having several materials inside. An adaptive quadrature accounting for the interfaces locations is proposed to accurately compute these integrals. Examples of the hierarchical X-FEM approach are given for a n-phase Stokes problem in 2 and 3 dimensions.Peer ReviewedPostprint (author’s final draft

Técnicas de depuración extrarrenal en Enfermedad Renal Crónica: Elección del tipo de diálisis y resultados.

La enfermedad renal crónica (ERC) es un término genérico que define un conjunto de enfermedades heterogéneas que afectan la estructura y función renal y que, debido a sus características y su tratamiento, supone un gran impacto sobre la calidad de vida de los pacientes que la padecen y sobre sus familias. Concepto de ERC La ERC se ha definido como la presencia persistente durante más de 3 meses de alteraciones estructurales o funcionales del riñón que tienen implicaciones para la salud y que se manifiestan por: a) indicadores de lesión renal, como alteraciones en estudios de laboratorio en sangre u orina, en estudios de imagen o en una biopsia, independientemente de que se acompañen o no de una disminución del filtrado glomerular (FG), y b) un FG menor de 60 mL/min por 1,73 m2 de superficie corporal, independientemente de que se acompañe o no de otros indicadores de lesión renal.Grado en Medicin

The implementation of universal design content on computer engineering and architecture in Spain

En base a la legislación vigente, y por tanto, a la obligación que las universidades españolas tienen de enseñar contenidos relacionados con el diseño universal o diseño para todos en aquellas titulaciones que se relacionen con la participación de todos los ciudadanos en la sociedad, este tr abajo tiene como objetivo fundamental hacer un análisis de cómo se está llevando a cabo este proceso en las titulaciones de ingeniería informática y arquitectura. Para ello, se ha contado con una muestra total de 159 guías docentes de asignaturas de ambas titulaciones de todas las universidades españolas. Los principales resultados del estudio demuestran que menos de la mitad de universidades estaría enseñando contenidos relacionados con el diseño universal y que existen un total de 59 titulaciones en las que se imparten contenidos relacionados con el diseño universal, aunque con diferencias significativas entre arquitectura e ingeniería informática. Finalmente, los autores discuten sobre la necesidad de cumplir la legislación vigente universitaria en la inc lusión de contenidos relacionados con el diseño para todas las personas

Generalized parametric solutions in Stokes flow

The final publication is available at Springer via https://doi.org/10.1016/j.cma.2017.07.016Design optimization and uncertainty quantification, among other applications of industrial interest, require fast or multiple queries of some parametric model. The Proper Generalized Decomposition (PGD) provides a separable solution, a computational vademecum explicitly dependent on the parameters, efficiently computed with a greedy algorithm combined with an alternated directions scheme and compactly stored. This strategy has been successfully employed in many problems in computational mechanics. The application to problems with saddle point structure raises some difficulties requiring further attention. This article proposes a PGD formulation of the Stokes problem. Various possibilities of the separated forms of the PGD solutions are discussed and analyzed, selecting the more viable option. The efficacy of the proposed methodology is demonstrated in numerical examples for both Stokes and Brinkman models.Peer ReviewedPostprint (author's final draft

Combinatorial k-means clustering as a machine learning tool applied to diabetes mellitus type 2

A new original procedure based on k-means clustering is designed to find the most appropriate clinical variables able to efficiently separate into groups similar patients diagnosed with diabetes mellitus type 2 (DMT2) and underlying diseases (arterial hypertonia (AH), ischemic heart disease (CHD), diabetic polyneuropathy (DPNP), and diabetic microangiopathy (DMA)). Clustering is a machine learning tool for discovering structures in datasets. Clustering has been proven to be efficient for pattern recognition based on clinical records. The considered combinatorial k-means procedure explores all possible k-means clustering with a determined number of descriptors and groups. The predetermined conditions for the partitioning were as follows: every single group of patients included patients with DMT2 and one of the underlying diseases; each subgroup formed in such a way was subject to partitioning into three patterns (good health status, medium health status, and degenerated health status); optimal descriptors for each disease and groups. The selection of the best clustering is obtained through the parameter called global variance, defined as the sum of all variance values of all clinical variables of all the clusters. The best clinical parameters are found by minimizing this global variance. This methodology has to identify a set of variables that are assumed to separate each underlying disease efficiently in three different subgroups of patients. The hierarchical clustering obtained for these four underlying diseases could be used to build groups of patients with correlated clinical data. The proposed methodology gives surmised results from complex data based on a relationship with the health status of the group and draws a picture of the prediction rate of the ongoing health status