Tunnel magnetoresistance in GaMnAs: going beyond Jullière formula

The relation between tunnel magnetoresistance (TMR) and spin polarization is explored for GaMnAs∕GaAlAs∕GaMnAs structures where the carriers experience strong spin–orbit interactions. TMR is calculated using the Landauer approach. The materials are described in the 6 band k⋅p model which includes spin–orbit interaction. Ferromagnetism is described in the virtual crystal mean field approximations. Our results indicate that TMR is a function of spin polarization and barrier thickness. As a result of the stong spin–orbit interactions, TMR also depends on the the angle between current flow direction and the electrode magnetization. These results compromise the validity of Julliere formula.

Spline for JavaVis 2

A Spline for camera movement in JavaVis.

Spline in JavaVis

A Spline for camera movement in JavaVis.

Measuring color differences in automotive samples with lightness flop: a test of the AUDI2000 color-difference formula

From a set of gonioapparent automotive samples from different manufacturers we selected 28 low-chroma color pairs with relatively small color differences predominantly in lightness. These color pairs were visually assessed with a gray scale at six different viewing angles by a panel of 10 observers. Using the Standardized Residual Sum of Squares (STRESS) index, the results of our visual experiment were tested against predictions made by 12 modern color-difference formulas. From a weighted STRESS index accounting for the uncertainty in visual assessments, the best prediction of our whole experiment was achieved using AUDI2000, CAM02-SCD, CAM02-UCS and OSA-GP-Euclidean color-difference formulas, which were no statistically significant different among them. A two-step optimization of the original AUDI2000 color-difference formula resulted in a modified AUDI2000 formula which performed both, significantly better than the original formula and below the experimental inter-observer variability. Nevertheless the proposal of a new revised AUDI2000 color-difference formula requires additional experimental data.

Growing Neural Gas approach for obtaining homogeneous maps by restricting the insertion of new nodes

The Growing Neural Gas model is used widely in artificial neural networks. However, its application is limited in some contexts by the proliferation of nodes in dense areas of the input space. In this study, we introduce some modifications to address this problem by imposing three restrictions on the insertion of new nodes. Each restriction aims to maintain the homogeneous values of selected criteria. One criterion is related to the square error of classification and an alternative approach is proposed for avoiding additional computational costs. Three parameters are added that allow the regulation of the restriction criteria. The resulting algorithm allows models to be obtained that suit specific needs by specifying meaningful parameters.

Enhancement of the Electrochemical Performance of SWCNT dispersed in a Silica Sol-gel Matrix by Reactive Insertion of a Conducting Polymer

The electroassisted encapsulation of Single-Walled Carbon Nanotubes was performed into silica matrices (SWCNT@SiO2). This material was used as the host for the potentiostatic growth of polyaniline (PANI) to yield a hybrid nanocomposite electrode, which was then characterized by both electrochemical and imaging techniques. The electrochemical properties of the SWCNT@SiO2-PANI composite material were tested against inorganic (Fe3+/Fe2+) and organic (dopamine) redox probes. It was observed that the electron transfer constants for the electrochemical reactions increased significantly when a dispersion of either SWCNT or PANI was carried out inside of the SiO2 matrix. However, the best results were obtained when polyaniline was grown through the pores of the SWCNT@SiO2 material. The enhanced reversibility of the redox reactions was ascribed to the synergy between the two electrocatalytic components (SWCNTs and PANI) of the composite material.

Chebanov law and Vakar formula in mathematical models of complex systems

Ecological models written in a mathematical language L(M) or model language, with a given style or methodology can be considered as a text. It is possible to apply statistical linguistic laws and the experimental results demonstrate that the behaviour of a mathematical model is the same of any literary text of any natural language. A text has the following characteristics: (a) the variables, its transformed functions and parameters are the lexic units or LUN of ecological models; (b) the syllables are constituted by a LUN, or a chain of them, separated by operating or ordering LUNs; (c) the flow equations are words; and (d) the distribution of words (LUM and CLUN) according to their lengths is based on a Poisson distribution, the Chebanov's law. It is founded on Vakar's formula, that is calculated likewise the linguistic entropy for L(M). We will apply these ideas over practical examples using MARIOLA model. In this paper it will be studied the problem of the lengths of the simple lexic units composed lexic units and words of text models, expressing these lengths in number of the primitive symbols, and syllables. The use of these linguistic laws renders it possible to indicate the degree of information given by an ecological model.