Series-connected substrate-integrated lead-carbon hybrid ultracapacitors with voltage-management circuit

Cell voltage for a fully charged-substrate-integrated lead-carbon hybrid ultracapacitor is about 2.3 V. Therefore, for applications requiring higher DC voltage, several of these ultracapacitors need to be connected in series. However, voltage distribution across each series-connected ultracapacitor tends to be uneven due to tolerance in capacitance and parasitic parallel-resistance values. Accordingly, voltage-management circuit is required to protect constituent ultracapacitors from exceeding their rated voltage. In this study, the design and characterization of the substrate-integrated lead-carbon hybrid ultracapacitor with co-located terminals is discussed. Voltage-management circuit for the ultracapacitor is presented, and its effectiveness is validated experimentally.

Maximum likelihood analysis of multi-stress accelerated life test data of series systems with competing log-normal causes of failure

This article presents frequentist inference of accelerated life test data of series systems with independent log-normal component lifetimes. The means of the component log-lifetimes are assumed to depend on the stress variables through a linear stress translation function that can accommodate the standard stress translation functions in the literature. An expectation-maximization algorithm is developed to obtain the maximum likelihood estimates of model parameters. The maximum likelihood estimates are then further refined by bootstrap, which is also used to infer about the component and system reliability metrics at usage stresses. The developed methodology is illustrated by analyzing a real as well as a simulated dataset. A simulation study is also carried out to judge the effectiveness of the bootstrap. It is found that in this model, application of bootstrap results in significant improvement over the simple maximum likelihood estimates.

Nonvanishing of Koecher-Maass series attached to Siegel cusp forms

We prove a nonvanishing result for Koecher-Maass series attached to Siegel cusp forms of weight k and degree n in certain strips on the complex plane. When n = 2, we prove such a result for forms orthogonal to the space of the Saito-Kurokawa lifts `up to finitely many exceptions', in bounded regions. (C) 2015 Elsevier Inc. All rights reserved.

La erodabilidad de cuatro series de suelos determinada por el mini-simulador de lluvia y el nomograma de Wischmeier

Se realizó un estudio con el propósito de obtener información acerca de le Erodabilidad del suelo, así como distinguir un método confiable y sencillo pera la determinación de ésta. Se seleccionaron cuatro Series de suelos (San Ignacio, Nejapa, Esquipulas y Zambrano), ubicadas en le Cuenca Sur del Lago de Managua, en base a una recopilación de información existente (topografía, reconocimiento y caracterización del terreno), se procedió a obtener les pérdidas de suelo, escurrimiento superficial, concentración de sedimentos y el Índice de Erodabilidad de cada Serie de suelos, por medio de un Mini-simulador de lluvia de Erodabilidad por Kamphorst (1987). El factor de erodabilidad (K) se obtuvo a través de cuatro propiedades del suelo (textura, materia orgánica, estructura y permeabilidad), cuyos valores son introducidos en el Nomograma de Wischmeier (1971). Una vez obtenidos los Índices de erodabilidad (I.K.) y Factor de erodabilidad (K) se determinó que las cuatro Series muestran diferentes grados de susceptibilidad e le erosión. Además, las pérdidas de suelo, escurrimiento superficial, concentración de sedimentos, el índice de erodabilidad y el Factor de erodabilidad son influenciadas por la materia orgánica. Así también se comprobó que el comparar el Índice y el Factor de erodabilidad, tienen un alto valor de correlación. Se pudo observar que le textura no tiene una influencia directa sobre les pérdidas de suelo, escurrimiento superficial, Índice de erodabilidad y Factor de erodabilidad.

Reversible jump sampler for autoregressive time series

We use reversible jump Markov chain Monte Carlo (MCMC) methods to address the problem of model order uncertainty in autoregressive (AR) time series within a Bayesian framework. Efficient model jumping is achieved by proposing model space moves from the full conditional density for the AR parameters, which is obtained analytically. This is compared with an alternative method, for which the moves are cheaper to compute, in which proposals are made only for new parameters in each move. Results are presented for both synthetic and audio time series.

Bayesian model selection for time series using Markov chain Monte Carlo

We present a stochastic simulation technique for subset selection in time series models, based on the use of indicator variables with the Gibbs sampler within a hierarchical Bayesian framework. As an example, the method is applied to the selection of subset linear AR models, in which only significant lags are included. Joint sampling of the indicators and parameters is found to speed convergence. We discuss the possibility of model mixing where the model is not well determined by the data, and the extension of the approach to include non-linear model terms.

Microstructural modelling in friction stir welding of 2000 series aluminium alloys

Simple process models are applied to predict microstructural changes due to the thermal cycle imposed in friction stir welding. A softening model developed for heat-treatable aluminium alloys of the 6000 series is applied to the aerospace alloy 2014 in the peak-aged (T6) condition. It is found that the model is not readily applicable to alloy 2024 in the naturally aged (T3) temper, but the softening behaviour can still be described semi-empirically. Both analytical and numerical (finite element) thermal models are used to predict the thermal histories in trial welds. These are coupled to the microstructural model to investigate: (a) the hardness profile across the welded plate; (b) alloy softening ahead of the approaching welding tool. By incorporating the softening model applied to 6082-T6 alloy, the hardness profile of friction stir welds in dissimilar alloys is also predicted. © AFM, EDP Sciences 2005.

Don Ramón Vega, enigmático rebelde de la ópera mexicana

Resumen: Un fortuito hallazgo del libreto manuscrito de la ópera El grito de Dolores, de Ramón Vega, compositor mexicano del siglo XIX, protagonizado por esta autora, desencadenó una serie de preguntas que hasta el presente no han sido respondidas a cabalidad por los estudios dedicados a la historia de la música en México. La investigación desarrollada con el propósito de situar el manuscrito encontrado en el contexto social y cultural del siglo de la Independencia y la exhaustiva pesquisa realizada en diferentes archivos históricos fructificaron en el descubrimiento de un vasto corpus de fuentes documentales actualmente desconocidas. La información que arrojó el análisis de estos documentos completó el conocimiento existente sobre la vida de Ramón Vega, permitió enderezar algunas ideas falibles en torno a su producción operística, así como construir y sustentar la hipótesis de que El grito de Dolores puede calificarse como el primer intento de creación de una ópera mexicana “enteramente nacional”.

Predicting chaotic time-series with wavelet networks

A new technique, wavelet network, is introduced to predict chaotic time series. By using this technique, firstly, we make accurate short-term predictions of the time series from chaotic attractors. Secondly, we make accurate predictions of the values and bifurcation structures of the time series from dynamical systems whose parameter values are changing with time. Finally we predict chaotic attractors by making long-term predictions based on remarkably few data points, where the correlation dimensions of predicted attractors are calculated and are found to be almost identical to those of actual attractors.