Shear horizontal wave propagation in periodically layeredcomposites

The transverse resonance approach to guided wave analysis is applied to shear horizontal (SH) wave propagation in periodically layered composites. It is found for SH waves that at high values of the guided wavevector β, the wave energy is trapped in the slower of the two media and propagates accordingly at the slower wavespeed. At low values of β, however, the modes demonstrate a clustering behavior, indicative of the underlying Floquet wave structure. The number of modes in a cluster is observed to correlate with the number of unit cells in the layered plate. New physical insights into the behavior of these systems are obtained by analyzing the partial waves of the guided SH modes in terms of Floquet waves. We show that the fast and slow shear waves in the periodically layered composite play an analogous role to the longitudinal and shear partial waves comprising Lamb waves in a homogeneous plate     

Mean residence time of gas in mechanically agitated gas–liquid contactors

In the present study of gas–liquid contactors, mean residence/contact time was calculated from knowledge of superficial velocity and the gas phase hold-up, for various gas rates and impeller geometry and speeds, and compared with values obtained from RTD measurements. A new correlation, involving Flow Number, Froude Number, system geometry and the physical properties, is proposed. This uses the authors data and those available in literature.     

A Neural Network Approach for Signal Detection in Digital Communications

In this paper, we propose a new approach for signal detection in wireless digital communications based on the neural network with transient chaos and time-varying gain (NNTCTG), and give a concrete model of the signal detector after appropriate transformations and mappings. It is well known that the problem of the maximum likelihood signal detection can be described as a complex optimization problem that has so many local optima that conventional Hopfield-type neural networks fail to solve. By refraining from the serious local optima problem of Hopfield-type neural networks, the NNTCTG makes use of the time-varying parameters of the recurrent neural network to control the evolving behavior of the network so that the network undergoes the transition from chaotic behavior to gradient convergence. It has richer and more flexible dynamics rather than conventional neural networks only with point attractors, so that it can be expected to have much ability to search for globally optimal or near-optimal solutions. After going through a transiently inverse-bifurcation process, the NNTCTG can approach the global optimum or the neighborhood of global optimum of our problem. Simulation experiments have been performed to show the effectiveness and validation of the proposed neural network based method for the signal detection in digital communications.     

Densification involved in the UV-based photosensitivity of silicaglasses and optical fibers

A comprehensive survey of photosensitivity in silica glasses and optical fiber is reviewed. Recent work on understanding the mechanisms contributing to germanium or aluminum doped fiber photosensitivity is discussed within the framework of photoelastic densification models     

Role of the hemobiologist in the detection and prevention of post-transfusional hepatitis

To prevent post-transfusional hepatitis B and C, two epidemiologic studies were performed. The first, based on the frequencies distribution of hepatitis B virus serological markers versus sex and classes of age, has permitted the assessment of the profile of the infection in a population composed of 573 north vietnamese blood donors. There is no significant difference between men and women frequencies of HBs antigen (11.5%), anti-HBs antibody (70.2%) and anti-HBc antibody alone (3.8%), but a significant difference of no-marker frequencies: 7.8% and 17.9% in men and women respectively (X2 = 9.11; p = 0.010). The percentage of no-marker decreases when the mean age of each class increases. The second, using the increase of the serum alanine aminotransferase (ALAT) activity as an indirect marker of non-A, non-B hepatitis for determining in a population of more than 25,000 parisian blood donors, the percentage of donors eliminated. They are between 0.70 and 0.76 in women and 2.26 and 2.46 in men. These investigations can be applied to prevent the hepatitis B transmission in a population of 102 south vietnamese women in age to procreate or to determine the percentage of blood donors eliminated (3.12%) in a population of 2,950 Parisians composed in majority (50.9%) of new donors. The hemobiologist will have an important role to elaborate strategies for orientation of blood gifts with hepatitis B and C virus markers.     

Dimer interface of glutathione S-transferase from Arabidopsis thaliana: influence of the G-site architecture on the dimer interface and implications for classification

The three-dimensional structure of glutathione S-transferase from Arabidopsis thaliana has been solved at 2.2 A resolution (Reinemer et al., 1996). The enzyme forms a dimer of two identical subunits. The structure shows a new G-site architecture and a novel and unique dimer interface. Each monomer of the protein forms a separate G-site. Therefore, the requirements on the dimer interface are reduced. As a consequence, the interactions between the monomers are weaker and residues at the dimer interface are more variable. Thus, the dimer interface looses its relevance for a classification of plant glutathione S-transferases and the formation of heterodimers becomes even more difficult to predict.     

Quantization effects in digitally behaving circuit implementationsof Kohonen networks

Implementing a neural network on a digital or mixed analog and digital chip yields the quantization of the synaptic weights dynamics. This paper addresses this topic in the case of Kohonen's self-organizing maps. We first study qualitatively how the quantization affects the convergence and the properties, and deduce from this analysis the way to choose the parameters of the network (adaptation gain and neighborhood). We show that a spatially decreasing neighborhood function is far more preferable than the usually rectangular neighborhood function, because of the weight quantization. Based on these results, an analog nonlinear network, integrated in a standard CMOS technology, and implementing this spatially decreasing neighborhood function is then presented. It can be used in a mixed analog and digital circuit implementation.