Controlling selective stimulations below a spinal cord hemisection using brain recordings with a neural interface system approach.

In this work we address the use of realtime cortical recordings for the generation of coherent, reliable and robust motor activity in spinal-lesioned animals through selective intraspinal microstimulation (ISMS). The spinal cord of adult rats was hemisectioned and groups of multielectrodes were implanted in both the central nervous system (CNS) and the spinal cord below the lesion level to establish a neural system interface (NSI). To test the reliability of this new NSI connection, highly repeatable neural responses recorded from the CNS were used as a pattern generator of an open-loop control strategy for selective ISMS of the spinal motoneurons. Our experimental procedure avoided the spontaneous non-controlled and non-repeatable neural activity that could have generated spurious ISMS and the consequent undesired muscle contractions. Combinations of complex CNS patterns generated precisely coordinated, reliable and robust motor actions

Implementation of a moving finite element mesh within the catenary-pantograph dynamic interaction

En este artículo se presenta la aplicación tecnológica a la interacción dinámica catenaria-pantógrafo de una metodología propuesta para estructuras flexibles sometidas a cargas móviles. En primer lugar se describe el modelado de una malla móvil de elementos finitos que se desplaza sobre el hilo de contacto de forma solidaria al pantógrafo que recorre la catenaria y, posteriormente, se presenta la comparación de esta metodología frente a un modelo de elementos finitos convencional de malla fija. El caso simulado corresponde al propuesto por la norma EN-50318, obteniendo resultados acordes a los intervalos de validación propuestos por dicha norma. La principal ventaja del método de malla móvil reside en que para precisiones análogas el tiempo de cálculo es del orden de 4 veces menor que el modelo clásico.This paper presents a technological application of a general methodology to analyze cable structures under moving loads, particularly on the catenary-pantograph dynamic interaction. This work firstly describes the modeling of a finite element moving mesh which integrally moves over the contact wire following the pantograph along the whole catenary, prior focusing on its comparison against the classical finite element mesh. The case study corresponds to the standard EN-50318 one, whose results fulfill the ranges proposed by this validation rule. The main advantage of the moving mesh method is presented in the falling of computational costs about 4 times lower than the classic model with similar precision.Peer Reviewe

Simulation of moving loads on structures using a moving finite element mesh

En este artículo se presenta una metodología para analizar la respuesta dinámica de estructuras sometidas a cargas móviles. Para ello se ha desarrollado un algoritmo de mallado adaptativo de elementos finitos que se mueve de forma solidaria a la carga móvil que actúa sobre la estructura. El algoritmo de mallado móvil se ha validado con la solución analítica de una carga móvil que recorre una viga simplemente apoyada.This paper presents a methodology to analyze the dynamic behavior of structures under moving loads. A finite element moving mesh algorithm has been developed in order to integrally move a part of the mesh following a moving load. This algorithm has been validated with the analytical solution of a moving load applied on a simply supported beam.Peer Reviewe

Autophagy and polyglutamine diseases

AbstractIn polyglutamine diseases, an abnormally elongated polyglutamine tract results in protein misfolding and accumulation of intracellular aggregates. The length of the polyglutamine expansion correlates with the tendency of the mutant protein to aggregate, as well as with neuronal toxicity and earlier disease onset. Although currently there is no effective cure to prevent or slow down the progression of these neurodegenerative disorders, increasing the clearance of mutant proteins has been proposed as a potential therapeutic approach. The ubiquitin–proteasome system and autophagy are the two main degradative pathways responsible for eliminating misfolded and unnecessary proteins in the cell. We will review some of the studies that have proposed autophagy as a strategy to reduce the accumulation of polyglutamine-expanded protein aggregates and protect against mutant protein neurotoxicity. We will also discuss some of the currently known mechanisms that induce autophagy, which may be beneficial for the treatment of these and other neurodegenerative disorders

AVOCADO: A Virtual Observatory Census to Address Dwarfs Origins

Dwarf galaxies are by far the most abundant of all galaxy types, yet their properties are still poorly understood -especially due to the observational challenge that their intrinsic faintness represents. AVOCADO aims at establishing firm conclusions on their formation and evolution by constructing a homogeneous, multiwavelength dataset for a statistically significant sample of several thousand nearby dwarfs (-18 < Mi < -14). Using public data and Virtual Observatory tools, we have built GALEX+SDSS+2MASS spectral energy distributions that are fitted by a library of single stellar population models. Star formation rates, stellar masses, ages and metallicities are further complemented with structural parameters that can be used to classify them morphologically. This unique dataset, coupled with a detailed characterization of each dwar's environment, allows for a fully comprehensive investigation of their origins and to track the (potential) evolutionary paths between the different dwarf types.Comment: 4 pages, 1 figure. To appear in the proceedings of IAU Symposium 277, "Tracing the Ancestry of Galaxies on the Land of our Ancestors", Carignan, Freeman, and Combes, ed

An investigation into the perspectives of providers and learners on MOOC accessibility

An effective open eLearning environment should consider the target learner’s abilities, learning goals, where learning takes place, and which specific device(s) the learner uses. MOOC platforms struggle to take these factors into account and typically are not accessible, inhibiting access to environments that are intended to be open to all. A series of research initiatives are described that are intended to benefit MOOC providers in achieving greater accessibility and disabled learners to improve their lifelong learning and re-skilling. In this paper, we first outline the rationale, the research questions, and the methodology. The research approach includes interviews, online surveys and a MOOC accessibility audit; we also include factors such the risk management of the research programme and ethical considerations when conducting research with vulnerable learners. Preliminary results are presented from interviews with providers and experts and from analysis of surveys of learners. Finally, we outline the future research opportunities. This paper is framed within the context of the Doctoral Consortium organised at the TEEM'17 conference

Finding the "Dark Matter'' in Human and Yeast Protein Network Prediction and Modelling

Accurate modelling of biological systems requires a deeper and more complete knowledge about the molecular components and their functional associations than we currently have. Traditionally, new knowledge on protein associations generated by experiments has played a central role in systems modelling, in contrast to generally less trusted bio-computational predictions. However, we will not achieve realistic modelling of complex molecular systems if the current experimental designs lead to biased screenings of real protein networks and leave large, functionally important areas poorly characterised. To assess the likelihood of this, we have built comprehensive network models of the yeast and human proteomes by using a meta-statistical integration of diverse computationally predicted protein association datasets. We have compared these predicted networks against combined experimental datasets from seven biological resources at different level of statistical significance. These eukaryotic predicted networks resemble all the topological and noise features of the experimentally inferred networks in both species, and we also show that this observation is not due to random behaviour. In addition, the topology of the predicted networks contains information on true protein associations, beyond the constitutive first order binary predictions. We also observe that most of the reliable predicted protein associations are experimentally uncharacterised in our models, constituting the hidden or "dark matter'' of networks by analogy to astronomical systems. Some of this dark matter shows enrichment of particular functions and contains key functional elements of protein networks, such as hubs associated with important functional areas like the regulation of Ras protein signal transduction in human cells. Thus, characterising this large and functionally important dark matter, elusive to established experimental designs, may be crucial for modelling biological systems. In any case, these predictions provide a valuable guide to these experimentally elusive regions