6 resultados para transition set

em Archivo Digital para la Docencia y la Investigación - Repositorio Institucional de la Universidad del País Vasco


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In this work we show the results obtained applying a Unified Dark Matter (UDM) model with a fast transition to a set of cosmological data. Two different functions to model the transition are tested, and the feasibility of both models is explored using CMB shift data from Planck [1], Galaxy Clustering data from [2] and [3], and Union2.1 SNe Ia [4]. These new models are also statistically compared with the ACDM and quiessence models using Bayes factor through evidence. Bayesian inference does not discard the UDM models in favor of ACDM.

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La tesis se ha centrado en la síntesis y caracterización estructural de materiales tipo perovskita: SrLnMRuO6 (Ln=La,Pr,Nd; M=Zn,Co,Mg,Ni,Fe) y ALn2CuTi2O9 (A=Ca,Ba; Ln=La,Pr,Nd,Sm). El estudio de las estructuras de los materiales se ha realizado mediante el análisis de los patrones de difracción en polvo de rayos-X, sincrotrón y/o neutrones. En el refinamiento por el método de Rietveld de las estructuras se han sustituido las coordenadas atómicas (el método más común), por coordenadas colectivas: las amplitudes de los modos que describen la distorsión de la fase prototipo. Los resultados generales para la serie SrLnMRuO6 (Ln=La,Pr,Nd; M=Zn,Co,Mg,Ni) a temperatura ambiente se ha recogido en un diagrama en el que se han indicado las amplitudes de los modos que transforman de acuerdo a las irreps en función del factor de tolerancia, ya que todos ellos cristalizan en la misma fase monoclínica (P21/n); y a temperaturas altas se ha construido un diagrama de fase. Los materiales SrLnFeRuO6 ( Ln=La,Pr,Nd) y CaLn2CuTi2O9 cristalizan en la fase ortorrómbica Pbnm a temperatura ambiente; mientras que BaLn2CuTi2O9 tienen una estructura más simétrica, I4/mcm. A altas temperaturas se han identificado las transiciones de fase inducidas por el cambio de temperatura.A temperaturas bajas se han analizado las estructuras magnéticas de algunos de los compuestos mediante difracción de neutrones.

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This paper analyzes the use of artificial neural networks (ANNs) for predicting the received power/path loss in both outdoor and indoor links. The approach followed has been a combined use of ANNs and ray-tracing, the latter allowing the identification and parameterization of the so-called dominant path. A complete description of the process for creating and training an ANN-based model is presented with special emphasis on the training process. More specifically, we will be discussing various techniques to arrive at valid predictions focusing on an optimum selection of the training set. A quantitative analysis based on results from two narrowband measurement campaigns, one outdoors and the other indoors, is also presented.

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In this work, a study of the nematic (N)-isotropic (I) phase transition has been made in a series of odd non-symmetric liquid crystal dimers, the alpha-(4-cyanobiphenyl-4'-yloxy)-omega-(1-pyrenimine-benzylidene-4'-oxy) alkanes, by means of accurate calorimetric and dielectric measurements. These materials are potential candidates to present the elusive biaxial nematic (N-B) phase, as they exhibit both molecular biaxiality and flexibility. According to the theory, the uniaxial nematic (N-U)-isotropic (I) phase transition is first-order in nature, whereas the N-B-I phase transition is second-order. Thus, a fine analysis of the critical behavior of the N-I phase transition would allow us to determine the presence or not of the biaxial nematic phase and understand how the molecular biaxiality and flexibility of these compounds influences the critical behavior of the N-I phase transition.