Drastic improvement of surface structure and current-carrying ability in YBa2Cu3O7 films by introducing multilayered structure

Much smoother surfaces and significantly improved superconducting properties of relatively thick YBa2Cu3O7 (YBCO) films have been achieved by introducing a multilayered structure with alternating main YBCO and additional NdBCO layers. The surface of thick (1 microm) multilayers has almost no holes compared to YBCO films. Critical current density (Jc) have been drastically increased up to a factor > 3 in 1 microm multilayered structures compared to YBCO films over entire temperature and applied magnetic filed range. Moreover, Jc values measured in thick multilayers are even larger than in much thinner YBCO films. The Jc and surface improvement have been analysed and attributed to growth conditions and corresponding structural peculiarities.Comment: Accepted to Appl. Phys. Lett. 88, June (2006), in press 4 pages, 3 figure

Investigation of Micro Porosity Sintered wick in Vapor Chamber for Fan Less Design

Micro Porosity Sintered wick is made from metal injection molding processes, which provides a wick density with micro scale. It can keep more than 53 % working fluid inside the wick structure, and presents good pumping ability on working fluid transmission by fine infiltrated effect. Capillary pumping ability is the important factor in heat pipe design, and those general applications on wick structure are manufactured with groove type or screen type. Gravity affects capillary of these two types more than a sintered wick structure does, and mass heat transfer through vaporized working fluid determines the thermal performance of a vapor chamber. First of all, high density of porous wick supports high transmission ability of working fluid. The wick porosity is sintered in micro scale, which limits the bubble size while working fluid vaporizing on vapor section. Maximum heat transfer capacity increases dramatically as thermal resistance of wick decreases. This study on permeability design of wick structure is 0.5 - 0.7, especially permeability (R) = 0.5 can have the best performance, and its heat conductivity is 20 times to a heat pipe with diameter (Phi) = 10mm. Test data of this vapor chamber shows thermal performance increases over 33 %.Comment: Submitted on behalf of TIMA Editions (http://irevues.inist.fr/tima-editions

The Forecasting Ability of Factor Models of the Term Structure of IRS Markets

Using estimated principal components as factors, three-factors models are shown to produce forecasts comparable to those of autoregressive models for 2 to 10 year zaero coupon interest rates IRS markets both, for short- and medium- term forecasting horizons. Evidence is provided for the Deutsche mark, Spanish peseta, Japanese yen and US Dollar. Forecast from factor models are also shown to preserve the correlation matrix of interest rates across a given term structure, an important proprerty regarding risk management. The result is quite striking, because factor models are purely static, and forecasts for the factors must be obtained in advance of interest rate forecast.factor modelsFactor models, Term structure of interest rates, Principal components, Swap markets, IRS

On the ability of spectroscopic SZ effect measurements to determine the temperature structure of galaxy clusters

(abridged) We explore in this paper the ability of spatially resolved spectroscopic measurements of the SZ effect (SZE) to determine the temperature profile of galaxy clusters. We derive a general formalism for the thermal SZE in galaxy clusters with a non-uniform temperature profile that can be applied to both cool-core clusters and non-cool core cluster with an isothermal or non-isothermal temperature structure. We derive an inversion technique through which the electron distribution function can be extracted from spectroscopic SZE observations over a wide frequency range. We study the fitting procedure to extract the cluster temperature from a set of simulated spatially resolved spectroscopic SZE observations in different bands of the spectrum, from 100 to 450 GHz. The results of our analysis for three different cluster prototypes (A2199 with a low-temperature cool core, Perseus with a relatively high-temperature cool core, Ophiuchus with an isothermal temperature distribution) provide both the required precision of the SZE observations and the optimal frequency bands for a determination of the cluster temperature similar or better than that obtainable from X-ray observations. The precision of SZE-derived temperature is also discussed for the outer regions of clusters. We also study the possibility to extract, from our method, the parameters characterizing the non-thermal SZE spectrum of the relativistic plasma contained in the lobes of radio galaxies as well as the spectrum of relativistic electrons co-spatially distributed with the thermal plasma in clusters with non-thermal phenomena. We find that the next generation SZE experiments with spectroscopic capabilities can provide precise temperature distribution measurements (...)Comment: Submitted to Astronomy & Astrophysic

Feature discovery and visualization of robot mission data using convolutional autoencoders and Bayesian nonparametric topic models

The gap between our ability to collect interesting data and our ability to analyze these data is growing at an unprecedented rate. Recent algorithmic attempts to fill this gap have employed unsupervised tools to discover structure in data. Some of the most successful approaches have used probabilistic models to uncover latent thematic structure in discrete data. Despite the success of these models on textual data, they have not generalized as well to image data, in part because of the spatial and temporal structure that may exist in an image stream. We introduce a novel unsupervised machine learning framework that incorporates the ability of convolutional autoencoders to discover features from images that directly encode spatial information, within a Bayesian nonparametric topic model that discovers meaningful latent patterns within discrete data. By using this hybrid framework, we overcome the fundamental dependency of traditional topic models on rigidly hand-coded data representations, while simultaneously encoding spatial dependency in our topics without adding model complexity. We apply this model to the motivating application of high-level scene understanding and mission summarization for exploratory marine robots. Our experiments on a seafloor dataset collected by a marine robot show that the proposed hybrid framework outperforms current state-of-the-art approaches on the task of unsupervised seafloor terrain characterization.Comment: 8 page

Making the Grade: A Scorecard for State Health Insurance Exchanges

Assesses states' progress in creating exchanges and grades established exchanges on policies regarding governance and structure, negotiating power and ability to drive value, consumer experience, and stability, including protection from adverse selection