Global pollution monitoring of polybrominated diphenyl ethers using skipjack tuna as a bioindicator

To elucidate the global distribution of polybrominated diphenyl ethers (PBDEs), these chemicals were determined in the muscle of skipjack tuna (Katsuwonus pelamis) collected from offshore waters of various regions in the world (Japan, Taiwan, Philippines, Indonesia, Seychelles, and Brazil, and the Japan Sea, East China Sea, South China Sea, Indian Ocean, and North Pacific Ocean). PBDEs were detected in almost all the skipjack tuna collected from the locations surveyed (from < 0.1 to 53 ng/g of lipid), indicating widespread contamination by these compounds in the marine environment. Residue levels of PBDEs in these samples from the northern hemisphere seem to be higher than those from the southern hemisphere, which is plausibly due to larger usage of these compounds in the northern hemisphere. Higher concentrations of PBDEs were detected in the samples from waters around the East China Sea (up to 53 ng/g of lipid). Developing countries around the East China Sea are supposedly the "hot spots" releasing these chemicals into the marine environment. With regard to the composition of PBDE congeners, the percentage contribution by lower brominated congeners (BDE15, -28, and -47) showed an increasing trend with increasing latitude. On the other hand, higher brominated congeners (BDE153, -154, and -183) showed a reverse trend. These patterns suggest that lower brominated congeners of PBDEs (di-, tri-, and tetra-BDEs) were preferentially transported from pollution sources to northern colder regions through the atmosphere. PBDEs may have a high potency to cause global pollution like PCBs.     

Analysis of unslotted direct-sequence spread spectrum multipleaccess network with packet combining

A packet combining scheme is investigated for an unslotted random access code division multiple access network over a frequency selective Rayleigh fading channel. It is shown that this simple diversity combining mechanism is highly advantageous for systems which can both tolerate a certain delay and operate over highly time-varying channels     

Some integrals involving the Q/sub m/(a/spl radic/x,b/spl radic/x) with application to error probability analysis of diversity receivers

This paper derives closed-form formulas for two integrals involving the generalized Marcum Q-function with linear arguments Q/sub m/(a/spl radic/x,b/spl radic/x). These integrals are known to arise in the analysis of multichannel diversity reception of differentially coherent and noncoherent digital communications in Rayleigh and Nakagami-m channels. Applications of the results for efficient performance evaluation of the average bit error rates of dual branch selection diversity combining and postdetection equal gain combining over independent and correlated fading channels are also presented.     

Bioaccumulation of organochlorines in crows from an indian open waste dumping site: evidence for direct transfer of dioxin-like congeners from the contaminated soil

To assess the significance of waste dumping sites as a source of chemical contamination to ecosystems, we analyzed the residue levels of polychlorinated dibenzo-p-dioxins (PCDDs), polychlorinated dibenzofurans (PCDFs), polychlorinated biphenyls (PCBs), and other organochlorines in the breast muscle of crows from a dumping site in the south of Chennai city, South India. Crows from the dumping site contained significantly higher total TEQs (60 +/- 27 pg/g lipid wt) than those from the reference sites (26 +/- 18 pg/g lipid wt). Especially, certain dioxin-like coplanar PCB congeners (Co-PCBs), such as CB-77 and CB-105, whose source is commercial PCBs,were significantly higher in crows from the dumping site than those from the reference sites. Profiles of PCDDs/DFs and Co-PCBs in crows from the dumping site were similar to those of soil at the same site, which was confirmed by principal component analysis. Furthermore, significant positive correlations were obtained between the congener-specific bioconcentration factors (BCFs) of PCDDs/DFs estimated from concentrations in crows and soil from the dumping site and the theoretical BCFs calculated from water-particle and lipid-water partitioning coefficients. On the other hand, the estimated BCFs had significant negative correlations with the molecular weight of PCDDs/DFs, indicating that molecular size limits their bioaccumulation. These results suggest that dioxin-like congeners in the soil of the dumping site were transferred directly to the crows through the ingestion of on-site garbage contaminated with soil, rather than through trophic transfer in the ecosystem. The present study provides insight into the ecological impacts of dumping sites.     

Expression of major cold shock proteins and genes by Yersinia enterocolitica in synthetic medium and foods

Yersinia enterocolitica is a psychrotrophic foodborne pathogen that has been implicated in outbreaks of foodborne illness involving cold-stored foods, especially milk and pork. A major mechanism bacteria use to adapt to cold is expression of cold shock proteins. The objective of this research was to study the expression of major cold shock proteins of Y. enterocolitica in Luria-Bertani (LB) broth, milk, and pork following a temperature downshift from 30 to 4 degrees C. Y. enterocolitica was inoculated into 10 ml of LB broth, sterile skim milk, or pork, and the samples were stored at 4 degrees C (cold shock) or 30 degrees C (control) for 0, 4, 8, 12, and 24 h. At each sampling time, total protein and total RNA were extracted from Y. enterocolitica harvested from LB broth, milk, and pork and subjected to two-dimensional gel electrophoresis and dot blot analysis. Two major cold shock proteins (CspA1 and CspA2) of approximately 7 kDa and their genes were expressed by Y. enterocolitica following cold shock. However, the CspA1 and CspA2 proteins were not expressed by Y. enterocolitica at 30 degrees C. Y. enterocolitica CspA1 and CspA2 were observed as early as 2 h of cold shock in cultures from LB broth and milk and at 8 h of cold shock in cultures from pork.     

Neural network prediction of bioleaching of metals from waste computer printed circuit boards using Levenberg-Marquardt algorithm

The applicability of artificial neural network (ANN) to predict the bioleaching of metals using from computer printed circuit boards (CPCB) and the influence of process parameters were studied. The influence of process parameters initial pH (1.6-2.4), pulp density (2%-13%), and the initial volume of Inoculum (5%-25%) were investigated on the rate of bioleaching of metals from CPCB. Network inputs were fed as initial pH, pulp density, and inoculum volume and with the extraction of Cu, Ag, and Au as output. The ANN was developed using the Levenberg-Marquardt algorithm and trained for modeling and prediction. The most fitting architectures for Cu, Ag, and Au were [4-5-5-2-1], [4-7-5-2-1], [4-7-1-1-1] trained with Levenberg-Marquardt algorithm, respectively. The R values were observed to be 0.996, 0.997, and 0.993 for Cu, Ag, and Au extraction predictions, respectively. The genetic algorithm model defined by ANN was used to achieve maximum extraction rates for Cu, Au, and Ag. The predicted data showed that there is a great capability of using ANN for the prediction of Cu, Ag, and Au extraction from CPCB through bioleaching process. Hence, the ANN model can be used to control the operational conditions for improved metals extraction through bioleaching.     

Processing and Thermal Conductivity of Lead Telluride Microwires

We present a unique method for producing continuous PbTe microwires which may be spooled for commercial use, and provide evidence that such wires tend to form single crystals with diameters less than 10 μm. Because PbTe microwires can, potentially, be used to fabricate miniature thermoelectric generators, a commercial fiber optic draw tower was used to produce such wires. In general, the thermoelectric figure of merit of a semiconductor is expected to decrease if its thermal conductivity increases. Because PbTe microwires with diameters less than 10 μm contain no grain boundaries and have fewer other defects, for example cracks and pores, their thermal conductivity was expected to be high, as a result of reduced phonon scattering. Accordingly, it was of interest to determine how the thermal conductivity of PbTe microwires behaved in two diameter ranges, i.e., those with diameters <10 μm and those with substantially larger diameters. We report thermal conductivity data for such microwires, at 725 K, determined by use of the 3ω method. Special attention was paid to minimizing conduction and radiation losses which are sources of error at high temperatures. The results prove that the thermal conductivity of PbTe microwires remains invariant in the diameter range 1.6–60 μm.     

Clustering Gene Expression Data Through Modified Agglomerative M-CURE Hierarchical Algorithm

Gene expression refers to the process in which the gene information is used in the functional gene product synthesis. They basically encode the proteins which in turn dictate the functionality of the cell. The first step in gene expression study involves the clustering usage. This is due to the reason that biological networks are very complex and the genes volume increases the comprehending challenges along with the data interpretation which itself inhibit vagueness, noise and imprecision. For a biological system to function, the essential cellular molecules must interact with its surrounding including RNA, DNA, metabolites and proteins. Clustering methods will help to expose the structures and the patterns in the original data for taking further decisions. The traditional clustering techniques involve hierarchical, model based, partitioning, density based, grid based and soft clustering methods. Though many of these methods provide a reliable output in clustering, they fail to incorporate huge data of gene expressions. Also, there are statistical issues along with choosing the right method and the choice of dissimilarity matrix when dealing with gene expression data. We propose to use a modified clustering algorithm using representatives (M-CURE) in this work which is more robust to outliers as compared to K-means clustering and also able to find clusters with size variances.