983 resultados para Taronges-Publicitat-Vila-real.


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To investigate the neural systems that contribute to the formation of complex, self-relevant emotional memories, dedicated fans of rival college basketball teams watched a competitive game while undergoing functional magnetic resonance imaging (fMRI). During a subsequent recognition memory task, participants were shown video clips depicting plays of the game, stemming either from previously-viewed game segments (targets) or from non-viewed portions of the same game (foils). After an old-new judgment, participants provided emotional valence and intensity ratings of the clips. A data driven approach was first used to decompose the fMRI signal acquired during free viewing of the game into spatially independent components. Correlations were then calculated between the identified components and post-scanning emotion ratings for successfully encoded targets. Two components were correlated with intensity ratings, including temporal lobe regions implicated in memory and emotional functions, such as the hippocampus and amygdala, as well as a midline fronto-cingulo-parietal network implicated in social cognition and self-relevant processing. These data were supported by a general linear model analysis, which revealed additional valence effects in fronto-striatal-insular regions when plays were divided into positive and negative events according to the fan's perspective. Overall, these findings contribute to our understanding of how emotional factors impact distributed neural systems to successfully encode dynamic, personally-relevant event sequences.

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Real-time polymerase chain reaction (PCR) has recently been described as a new tool to measure and accurately quantify mRNA levels. In this study, we have applied this technique to evaluate cytokine mRNA synthesis induced by antigenic stimulation with purified protein derivative (PPD) or heparin-binding haemagglutinin (HBHA) in human peripheral blood mononuclear cells (PBMC) from Mycobacterium tuberculosis-infected individuals. Whereas PPD and HBHA optimally induced IL-2 mRNA after respectively 8 and 16 to 24 h of in vitro stimulation, longer in vitro stimulation times were necessary for optimal induction of interferon-gamma (IFN-gamma) mRNA, respectively 16 to 24 h for PPD and 24 to 96 h for HBHA. IL-13 mRNA was optimally induced by in vitro stimulation after 16-48 h for PPD and after 48 to 96 h for HBHA. Comparison of antigen-induced Th1 and Th2 cytokines appears, therefore, valuable only if both cytokine types are analysed at their optimal time point of production, which, for a given cytokine, may differ for each antigen tested. Results obtained by real-time PCR for IFN-gamma and IL-13 mRNA correlated well with those obtained by measuring the cytokine concentrations in cell culture supernatants, provided they were high enough to be detected. We conclude that real-time PCR can be successfully applied to the quantification of antigen-induced cytokine mRNA and to the evaluation of the Th1/Th2 balance, only if the kinetics of cytokine mRNA appearance are taken into account and evaluated for each cytokine measured and each antigen analysed.

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En este documento, se presentarán las etapas para diseñar un Modelo Instruccional en ambientes virtuales interactivos para la enseñanza de los números Reales, que tiene en cuenta: la formación matemática de los estudiantes, sus “niveles”, sus ritmos de aprendizaje, sus obstáculos en el aprendizaje y el tiempo oficial propuesto por la institución educativa para abordar los temas. Además, se explicitan, organizan y relacionan muchos de los elementos que se conjugan, y se camuflan, en la enseñanza y el aprendizaje de los temas matemáticos. Este diseño plantea ciertos elementos para el análisis del Discurso Matemático, del discurso didáctico y toma ciertos resultados de las investigaciones en Educación Matemática (Taxonomía SOLO y la Teoría de Súperítemes entre otras) para poner en relación los niveles en el discurso didáctico con los niveles de abstracción de los estudiantes.

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Virtual manufacturing and design assessment increasingly involve the simulation of interacting phenomena, sic. multi-physics, an activity which is very computationally intensive. This chapter describes an attempt to address the parallel issues associated with a multi-physics simulation approach based upon a range of compatible procedures operating on one mesh using a single database - the distinct physics solvers can operate separately or coupled on sub-domains of the whole geometric space. Moreover, the finite volume unstructured mesh solvers use different discretization schemes (and, particularly, different ‘nodal’ locations and control volumes). A two-level approach to the parallelization of this simulation software is described: the code is restructured into parallel form on the basis of the mesh partitioning alone, that is, without regard to the physics. However, at run time, the mesh is partitioned to achieve a load balance, by considering the load per node/element across the whole domain. The latter of course is determined by the problem specific physics at a particular location.

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The parallelization of real-world compute intensive Fortran application codes is generally not a trivial task. If the time to complete the parallelization is to be significantly reduced then an environment is needed that will assist the programmer in the various tasks of code parallelization. In this paper the authors present a code parallelization environment where a number of tools that address the main tasks such as code parallelization, debugging and optimization are available. The ParaWise and CAPO parallelization tools are discussed which enable the near automatic parallelization of real-world scientific application codes for shared and distributed memory-based parallel systems. As user involvement in the parallelization process can introduce errors, a relative debugging tool (P2d2) is also available and can be used to perform nearly automatic relative debugging of a program that has been parallelized using the tools. A high quality interprocedural dependence analysis as well as user-tool interaction are also highlighted and are vital to the generation of efficient parallel code and in the optimization of the backtracking and speculation process used in relative debugging. Results of benchmark and real-world application codes parallelized are presented and show the benefits of using the environment

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This study investigates the use of computer modelled versus directly experimentally determined fire hazard data for assessing survivability within buildings using evacuation models incorporating Fractionally Effective Dose (FED) models. The objective is to establish a link between effluent toxicity, measured using a variety of small and large scale tests, and building evacuation. For the scenarios under consideration, fire simulation is typically used to determine the time non-survivable conditions develop within the enclosure, for example, when smoke or toxic effluent falls below a critical height which is deemed detrimental to evacuation or when the radiative fluxes reach a critical value leading to the onset of flashover. The evacuation calculation would the be used to determine whether people within the structure could evacuate before these critical conditions develop.

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The original article is available as an open access file on the Springer website in the following link: http://link.springer.com/article/10.1007/s10639-015-9388-2

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The AMSR-E satellite data and in-situ data were applied to retrieve sea surface air temperature (Ta) over the Southern Ocean. The in-situ data were obtained from the 24~(th) -26~(th) Chinese Antarctic Expeditions during 2008-2010. First, Ta was used to analyze the relativity with the bright temperature (Tb) from the twelve channels of AMSR-E, and no high relativity was found between Ta and Tb from any of the channels. The highest relativity was 0.38 (with 23.8 GHz). The dataset for the modeling was obtained by using in-situ data to match up with Tb, and two methods were applied to build the retrieval model. In multi-parameters regression method, the Tbs from 12 channels were used to the model and the region was divided into two parts according to the latitude of 50°S. The retrieval results were compared with the in-situ data. The Root Mean Square Error (RMS) and relativity of high latitude zone were 0.96℃and 0.93, respectively. And those of low latitude zone were 1.29 ℃ and 0.96, respectively. Artificial neural network (ANN) method was applied to retrieve Ta.The RMS and relativity were 1.26 ℃ and 0.98, respectively.