Exact relativistic models of thin disks around static black holes in a magnetic field

The exact superposition of a central static black hole with surrounding thin disk in presence of a magnetic field is investigated. We consider two models of disk, one of infinite extension based on a Kuzmin-Chazy-Curzon metric and other finite based on the first Morgan-Morgan disk. We also analyze a simple model of active galactic nuclei consisting of black hole, a Kuzmin-Chazy-Curzon disk and two rods representing jets, in presence of magnetic field. To explain the stability of the disks we consider the matter of the disk made of two pressureless streams of counterrotating charged particles (counterrotating model) moving along electrogeodesic. Using the Rayleigh criterion we derivate for circular orbits the stability conditions of the particles of the streams. The influence of the magnetic field on the matter properties of the disk and on its stability are also analyzed.Comment: 17 pages, 14 figures. arXiv admin note: text overlap with arXiv:gr-qc/0409109 by other author

Caracterización de placas de yeso con residuos de espuma de poliuretano reforzadas con fibras de polipropileno

Gypsum plasterboard that incorporates various combinations of polyurethane foam waste and polypropylene fibers in its matrix is studied. The prefabricated material was characterized in a series of standardized tests: bulk density, maximum breaking load under flexion stress, total water absorption, surface hardness, thermal properties, and reaction to fire performance. Polypropylene fibers were added to the polyurethane gypsum composites to improve the mechanical behavior of the plasterboard under loading. The results indicate that increased quantities of polymer waste led to significant reductions in the weight/surface ratio, the mechanical strength and the surface hardness of the gypsum, as well as improving its thermal resistance. The polypropylene fibers showed good adhesion to the polymer and the gypsum matrix, which enhanced the mechanical performance and the absorption capacity of these compounds. The non-combustibility test demonstrated the potential of the new material for use in internal linings.Este artículo presenta un estudio experimental basado en la reutilización de residuos de poliuretano en una matriz de yeso para elaborar una placa de yeso laminado. Las placas fueron caracterizadas mediante los ensayos normalizados de densidad aparente, carga de rotura máxima a flexión, absorción total de agua, dureza superficial y reacción al fuego. Se han introducido fibras de polipropileno en la matriz con el objetivo de aumentar la resistencia mecánica del material. Los resultados muestran que el incremento de residuo polimérico en el material implica importantes reducciones de peso, resistencia mecánica y dureza superficial, a la par que se mejora su resistencia térmica consiguiéndose valores similares a los comerciales. Las fibras de polipropileno mostraron una buena adhesión con el polímero, mejorando el comportamiento mecánico y la capacidad de absorción. El ensayo de reacción al fuego confirmó que los residuos de poliuretano pueden ser empleados en la fabricación de placas de yeso laminado en cumplimiento con la normativa

Effect of fermented, hardened, and dehulled of chickpea (Cicer arietinum) meals in digestibility and antinutrients in diets for tilapia (Oreochromis niloticus)

Among the most typical feed sources for tilapia, plants represent a low-cost source in substituting for traditional high-cost feed ingredients. Fermentation, hardening and dehulling are common grains processing techniques to make plant nutrients available and more digestible to fish. Apparent digestibility coefficients (ADC) of dry matter and protein, and antinutrients (phytic acid and tannins) in fermented, hardened and dehulled chickpea (Cicer arietinum) meals were determined for juvenile Nile tilapia (Oreochromis niloticus). The highest ADC was obtained with processed (fermented, hardened and dehulled) chickpea meals compared with non-processed. Results indicated that fermentation increased the protein content by 13.1%, decreased the content of ash and phytic acid (47.5 and 45%, respectively), and increased the ingredient apparent digestibility of dry matter (ADM) by 23.2%, and the ingredient apparent digestibility of protein (ADP) by 41.9%. Dehulling meal increased the protein (5.7%) and lipid (6.4%) content of chickpea grains; decreased fiber, ash and tannin content (75.3%, 19.1%, and 84.5%, respectively); and increased ADM by 12.8%, and ADP by 10.4%. We conclude that fermented, hardened and dehulled chickpea meals represent a potential alternative in diets for juvenile O. niloticus

Interest and Applicability of Meta-Heuristic Algorithms in the Electrical Parameter Identification of Multiphase Machines

Multiphase machines are complex multi-variable electro-mechanical systems that are receiving special attention from industry due to their better fault tolerance and power-per-phase splitting characteristics compared with conventional three-phase machines. Their utility and interest are restricted to the definition of high-performance controllers, which strongly depends on the knowledge of the electrical parameters used in the multiphase machine model. This work presents the proof-of-concept of a new method based on particle swarm optimization and standstill time-domain tests. This proposed method is tested to estimate the electrical parameters of a five-phase induction machine. A reduction of the estimation error higher than 2.5% is obtained compared with gradient-based approaches.Plan Estatal 2013-2016 Retos - Proyectos I+D+i DPI2013-44278-RPlan Estatal 2013-2016 Retos - Proyectos I+D+i DPI2016-76144-

Multi-GPU Development of a Neural Networks Based Reconstructor for Adaptive Optics

Aberrations introduced by the atmospheric turbulence in large telescopes are compensated using adaptive optics systems, where the use of deformable mirrors and multiple sensors relies on complex control systems. Recently, the development of larger scales of telescopes as the E-ELT or TMT has created a computational challenge due to the increasing complexity of the new adaptive optics systems. The Complex Atmospheric Reconstructor based on Machine Learning (CARMEN) is an algorithm based on artificial neural networks, designed to compensate the atmospheric turbulence. During recent years, the use of GPUs has been proved to be a great solution to speed up the learning process of neural networks, and different frameworks have been created to ease their development. The implementation of CARMEN in different Multi-GPU frameworks is presented in this paper, along with its development in a language originally developed for GPU, like CUDA. This implementation offers the best response for all the presented cases, although its advantage of using more than one GPU occurs only in large networks

An infinite family of magnetized Morgan-Morgan relativistic thin disks

Applying the Horsk\'y-Mitskievitch conjecture to the empty space solutions of Morgan and Morgan due to the gravitational field of a finite disk, we have obtained the corresponding solutions of the Einstein-Maxwell equations. The resulting expressions are simply written in terms of oblate spheroidal coordinates and the solutions represent fields due to magnetized static thin disk of finite extension. Now, although the solutions are not asymptotically flat, the masses of the disks are finite and the energy-momentum tensor agrees with the energy conditions. Furthermore, the magnetic field and the circular velocity show an acceptable physical behavior.Comment: Submitted to IJTP. This paper is a revised and extended version of a paper that was presented at arXiv:1006.203