Effect of copper, cadmium and Cu.Cd mixture on amino acid content in the poslarvae of penaeid shrimp, Penaeus monodon and P. penicillatus

This study document effects of short-term (96h) sublethal levels of copper, cadmium and their mixture on the amino acid composition of postlarvae of the penaeid shrimp, P.monodon and P.penicillatus . All experimental conditions were kept constant, temperature between 25-27•C and salinity 21-22 ppt. The estimated LD50 for Cu was 200 ug/L, for Cd 177.5 ug/L and for Cu.Cd mixture 250ug/L. In P. penicillatus at the same concentration of each metal, there was significant reduction in amino acid content, which was 8.01% higher than the control. Almost similar reduction in some amino acids was observed in P.monodon. At the maximum concentration of 400 ug/L, cadmium caused higher reduction in amino acid composition than did copper. Thus, amino acid composition may be regarded as a sensitive biochemical indicator of Cu and Cd toxicity because of the effect of these metals on protein synthesis, a signal of physiological stress in marine organisms subjected to heavy metal pollution.

Gaussian mixture modeling with Gaussian process latent variable models

Density modeling is notoriously difficult for high dimensional data. One approach to the problem is to search for a lower dimensional manifold which captures the main characteristics of the data. Recently, the Gaussian Process Latent Variable Model (GPLVM) has successfully been used to find low dimensional manifolds in a variety of complex data. The GPLVM consists of a set of points in a low dimensional latent space, and a stochastic map to the observed space. We show how it can be interpreted as a density model in the observed space. However, the GPLVM is not trained as a density model and therefore yields bad density estimates. We propose a new training strategy and obtain improved generalisation performance and better density estimates in comparative evaluations on several benchmark data sets. © 2010 Springer-Verlag.

Image sequence segmentation using mixture-models with uniqueness and spatio-temporal consistency constraints

The use of mixture-model techniques for motion estimation and image sequence segmentation was discussed. The issues such as modeling of occlusion and uncovering, determining the relative depth of the objects in a scene, and estimating the number of objects in a scene were also investigated. The segmentation algorithm was found to be computationally demanding, but the computational requirements were reduced as the motion parameters and segmentation of the frame were initialized. The method provided a stable description, in whichthe addition and removal of objects from the description corresponded to the entry and exit of objects from the scene.

Ferroelectric liquid crystal mixture integrated into optical waveguides

We report an on-chip integrated ferroelectric liquid crystal (FLC) waveguide structure suitable for telecommunication applications. Single gaps with different widths of 5, 10, and 20 μ m inside individual silica waveguides were filled with an FLC mixture. The waveguide devices operate as a binary switch or an attenuator in a temperature range from 30 °C to 60 °C. The FLC mixture exhibited a good alignment quality in these gaps without alignment layers. A good extinction ratio of up to 33.9 dB and a low insertion loss of <4.3 dB at λ = 1550 nm were observed. Switching times of <100 μs were obtained for the low electric fields applied in this experiment. © 2012 IEEE.