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Institution

University of Seville

EducationSeville, Andalucía, Spain
About: University of Seville is a education organization based out in Seville, Andalucía, Spain. It is known for research contribution in the topics: Population & Model predictive control. The organization has 20098 authors who have published 47317 publications receiving 947007 citations. The organization is also known as: Universidad de Sevilla.


Papers
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Journal ArticleDOI
TL;DR: Comparisons of synaptic function of motor terminals in wild-type and severe SMA mice at different ages and in two proximal muscles show that mutant muscle fibers fire normal action potentials and that multi-innervated terminals are functional.
Abstract: Low levels of survival motor neuron (SMN) protein result in spinal muscular atrophy (SMA), a severe genetic disease characterized by motor impairment and premature lethality. Although SMN is a ubiquitous protein, motor neurons are much more vulnerable to low levels of SMN than other cells. To gain insight into the pathogenesis of SMA, we have compared synaptic function of motor terminals in wild-type and severe SMA mice at different ages and in two proximal muscles. Our results show that mutant muscle fibers fire normal action potentials and that multi-innervated terminals are functional. By studying the characteristics of the three main components of synaptic transmission in nerve terminals (spontaneous, evoked, and asynchronous release), we found that the kinetics of the postsynaptic potentials are slowed and evoked neurotransmitter release is decreased by ∼55%. In addition, asynchronous release is increased ∼300%, indicating an anomalous augmentation of intraterminal bulk Ca 2+ during repetitive stimulation. Together, these results show that the reduction of SMN affects synaptic maturation, evoked release, and regulation of intraterminal Ca 2+ levels.

160 citations

Journal ArticleDOI
01 Aug 2001-Geoforum
TL;DR: The National Water Plan (NWP) of 1993 as discussed by the authors is a very ambitious long distance water transfer scheme between water rich and water poor basins, which has not yet been approved by the Spanish Parliament.

160 citations

Journal ArticleDOI
TL;DR: In this paper, the effect of two different Sn loadings on this base have been examined for the DRM reaction over 20 h, before selecting the most appropriate Sn/Ni ratio and promoting the alumina base with 20 wt.% of CeO2.
Abstract: Carbon formation and sintering remain the main culprits regarding catalyst deactivation in the dry and bi-reforming of methane reactions (DRM and BRM, respectively). Nickel based catalysts (10 wt.%) supported on alumina (Al2O3) have shown no exception in this study, but can be improved by the addition of tin and ceria. The effect of two different Sn loadings on this base have been examined for the DRM reaction over 20 h, before selecting the most appropriate Sn/Ni ratio and promoting the alumina base with 20 wt.% of CeO2. This catalyst then underwent activity measurements over a range of temperatures and space velocities, before undergoing experimentation in BRM. It not only showed good levels of conversions for DRM, but exhibited stable conversions towards BRM, reaching an equilibrium H2/CO product ratio in the process. In fact, this work reveals how multicomponent Ni catalysts can be effectively utilised to produce flexible syngas streams from CO2/CH4 mixtures as an efficient route for CO2 utilisation.

159 citations

Journal ArticleDOI
TL;DR: Based on a sample of almost 5500 borrowers from a Peruvian microfinance institution, the results reveal that neural network models outperform the other three classic techniques both in terms of area under the receiver-operating characteristic curve (AUC) and as misclassification costs.
Abstract: Credit scoring systems are currently in common use by numerous financial institutions worldwide. However, credit scoring with the microfinance industry is a relatively recent application, and no model which employs a non-parametric statistical technique has yet, to the best of our knowledge, been published. This lack is surprising since the implementation of credit scoring should contribute towards the efficiency of microfinance institutions, thereby improving their competitiveness in an increasingly constrained environment. This paper builds several non-parametric credit scoring models based on the multilayer perceptron approach (MLP) and benchmarks their performance against other models which employ the traditional linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), and logistic regression (LR) techniques. Based on a sample of almost 5500 borrowers from a Peruvian microfinance institution, the results reveal that neural network models outperform the other three classic techniques both in terms of area under the receiver-operating characteristic curve (AUC) and as misclassification costs.

159 citations

Journal ArticleDOI
TL;DR: In this paper, a non-incremental finite element procedure that employs the mathematical definition of the slope and uses it to define the element coordinates instead of the infinitesimal and finite rotations is developed for large rotation and deformation problems.
Abstract: There are three basic finite element formulations which are used in multibody dynamics. These are the floating frame of reference approach, the incremental method and the large rotation vector approach. In the floating frame of reference and incremental formulations, the slopes are assumed small in order to define infinitesimal rotations that can be treated and transformed as vectors. This description, however, limits the use of some important elements such as beams and plates in a wide range of large displacement applications. As demonstrated in some recent publications, if infinitesimal rotations are used as nodal coordinates, the use of the finite element incremental formulation in the large reference displacement analysis does not lead to exact modeling of the rigid body inertia when the structures rotate as rigid bodies. In this paper, a simple non-incremental finite element procedure that employs the mathematical definition of the slope and uses it to define the element coordinates instead of the infinitesimal and finite rotations is developed for large rotation and deformation problems. By using this description and by defining the element coordinates in the global system, not only the need for performing coordinate transformation is avoided, but also a simple expression for the inertia forces is obtained. The resulting mass matrix is constant and it is the same matrix that appears in linear structural dynamics. It is demonstrated in this paper that this coordinate description leads to exact modeling of the rigid body inertia when the structures rotate as rigid bodies. Nonetheless, the stiffness matrix becomes nonlinear function even in the case of small displacements. The method presented in this paper differs from previous large rotation vector formulations in the sense that the inertia forces, the kinetic energy, and the strain energy are not expressed in terms of any orientation coordinates, and therefore, the method does not require interpolation offinite rotations. While the use of the formulation is demonstrated using a simple planar beam element, the generalization of the method to other element types and to the three dimensional case is straightforward. Using the finite element procedure presented in this paper, beams and plates can be treated as isoparametric elements.

159 citations


Authors

Showing all 20465 results

NameH-indexPapersCitations
Russel J. Reiter1691646121010
Aaron Dominguez1471968113224
Jose M. Ordovas123102470978
Detlef Lohse104107542787
Miroslav Krstic9595542886
María Vallet-Regí9571141641
John S. Sperry9316035602
Jose Rodriguez9380358176
Shun-ichi Amari9049540383
Michael Ortiz8746731582
Bruce J. Paster8426128661
Floyd E. Dewhirst8122942613
Joan Montaner8048922413
Francisco B. Ortega7950326069
Luis Paz-Ares7759231496
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023143
2022567
20213,357
20203,480
20193,032
20182,766