Preliminary studies using hybrid mediated electrochemical oxidation (HMEO) for the removal of persistent organic pollutants (POPs).

This study investigates the hybrid mediated electrochemical oxidation (HMEO) technology, which is a newly developed non thermal electrochemical oxidation process for organic destruction. A combination of ozone and ultrasonication processes to the mediated electrochemical oxidation (MEO) process is termed as hybrid mediated electrochemical oxidation. The electrochemical cell was developed in this laboratory. In the present study, several organic compounds, such as phenol, benzoquinone and ethylenediaminetetraacetic acid (EDTA), were chosen as the model organic pollutants to be destructed by the hybrid process. The organic destruction was monitored based on the CO2 generation and total organic carbon (TOC) reduction. The HMEO process was found to be extremely effective in the destruction of all the target organics chosen in this study. The information obtained from this study will provide an insight in adopting this technique for dealing with more recalcitrant organics (POPs).     

On the improvement of detection characteristics of trans-stilbene crystals by improving crystal perfection

Organic molecular scintillating crystals are noted for their good timing and particle discrimination process. Trans-stilbene is one such candidate noted for its good particle detection characteristics for the past five decades. Progressive strengthening of detection characteristics of trans-stilbene has been attempted by improving crystal perfection. A series of timing resolution studies have been carried out for the Bridgman grown trans-stilbene crystals under different experimental conditions. The results were compared with the previously reported values. Pulse shape discrimination process has been carried out for ²⁴¹Am and ²⁵²Cf sources and good discrimination has been obtained for gamma-alpha and gamma-neutron sources from the grown organic phosphor crystal. Electronic Publication     

Characterization of poly(vinyl alcohol)/sodium bromide polymer electrolytes for electrochemical cell applications

Sodium‐ion conducting polymer electrolytes based on poly(vinyl alcohol) complexed with sodium bromide were prepared with a solution‐casting technique. The structure of these films was determined with X‐ray diffraction, and the complexation of the salt with the polymer was confirmed with Fourier transform infrared spectroscopy studies. Electrical conductivity was measured with an alternating‐current impedance analyzer in the frequency range of 100 Hz to 1 MHz and in the temperature range of 303–373 K. It was observed that the magnitude of conductivity increased with the increase in the salt concentration as well as the temperature. The nature of the charge transport in these polymer electrolyte films was determined with both Wagner's polarization technique and the Watanabe technique. The dominant conducting species were found to be ions, particularly anions. Optical absorption studies were performed in the wavelength range of 200–600 nm, and the absorption edge, direct band gap, and indirect band gap values were evaluated. Electrochemical cells were fabricated, and their discharge characteristics were studied. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

H.264/SVC mode decision based on mode correlation and desired mode list

Design of video encoders involves implementation of fast mode decision (FMD) algorithm to reduce computation complexity while maintaining the performance of the coding. Although H.264/scalable video coding (SVC) achieves high scalability and coding efficiency, it also has high complexity in implementing its exhaustive computation. In this paper, a novel algorithm is proposed to reduce the redundant candidate modes by making use of the correlation among layers. A desired mode list is created based on the probability to be the best mode for each block in base layer and a candidate mode selection in the enhancement layer by the correlations of modes among reference frame and current frame. Our algorithm is implemented in joint scalable video model (JSVM) 9.19.15 reference software and the performance is evaluated based on the average encoding time, peak signal to noise ration (PSNR) and bit rate. The experimental results show 41.89% improvement in encoding time with minimal loss of 0.02 dB in PSNR and 0.05% increase in bit rate.     

Mobile application-based computer-aided diagnosis of skin tumours from dermal images

Skin tumour is defined as the enormous growth of cells in the skin. The aim is to design standalone application for diagnosis of skin tumours. The dermal images of three different types obtained from the authorized PH2 database are used to analyse the defined image processing algorithm. In this algorithm, pre-processing was performed to remove hair cells. Contour-based level set is used to segment lesion from which clinical and morphological features are extracted for classification. Significant features are obtained with the feature selection technique, Random subset. Classification is performed with three classifiers. The efficiency of the classifier obtained with different trials of classification is analysed with the ANOVA test. With these results, the Multiclass Support vector machine was configured as a suitable classifier to categorize dermal images. Therefore, an application is developed for the analysis of images acquired through mobile with the help of a magnification set-up. Thus, extracted features, segmented and original images are transferred to a database for storage.     

A survey and taxonomy on energy efficient resource allocation techniques for cloud computing systems

In a cloud computing paradigm, energy efficient allocation of different virtualized ICT resources (servers, storage disks, and networks, and the like) is a complex problem due to the presence of heterogeneous application (e.g., content delivery networks, MapReduce, web applications, and the like) workloads having contentious allocation requirements in terms of ICT resource capacities (e.g., network bandwidth, processing speed, response time, etc.). Several recent papers have tried to address the issue of improving energy efficiency in allocating cloud resources to applications with varying degree of success. However, to the best of our knowledge there is no published literature on this subject that clearly articulates the research problem and provides research taxonomy for succinct classification of existing techniques. Hence, the main aim of this paper is to identify open challenges associated with energy efficient resource allocation. In this regard, the study, first, outlines the problem and existing hardware and software-based techniques available for this purpose. Furthermore, available techniques already presented in the literature are summarized based on the energy-efficient research dimension taxonomy. The advantages and disadvantages of the existing techniques are comprehensively analyzed against the proposed research dimension taxonomy namely: resource adaption policy, objective function, allocation method, allocation operation, and interoperability.     

On classification with incomplete data

We address the incomplete-data problem in which feature vectors to be classified are missing data (features). A (supervised) logistic regression algorithm for the classification of incomplete data is developed. Single or multiple imputation for the missing data is avoided by performing analytic integration with an estimated conditional density function (conditioned on the observed data). Conditional density functions are estimated using a Gaussian mixture model (GMM), with parameter estimation performed using both expectation-maximization (EM) and variational Bayesian EM (VB-EM). The proposed supervised algorithm is then extended to the semisupervised case by incorporating graph-based regularization. The semisupervised algorithm utilizes all available data-both incomplete and complete, as well as labeled and unlabeled. Experimental results of the proposed classification algorithms are shown     

Fold-recognition and comparative modeling of human beta3GalT I, II, IV, V and VI and beta3GalNAcT I: prediction of residues conferring acceptor substrate specificity

beta3GalTs are type II transmembrane proteins that transfer galactose from UDP-Gal donor substrate to acceptor GlcNAc, GalNAc or Gal in beta1-->3-linkage. beta1-->3-linked galactose have been found to be a part of many glycans like glycosphingolipids, core tetrasaccharide of proteoglycans, type 1 chains. The 3-D structure of none of the beta3GalTs is known to date. In this study, the 3-D structures of human beta3GalT I, II, IV, V, VI and beta3GalNAcT I have been modeled using fold-recognition and comparative modeling methods. Residues that constitute the UDP-Gal binding site have been predicted. The models are able to qualitatively rationalize data from the site-directed mutagenesis experiments reported in the literature. Residues likely to be involved in conferring differential acceptor substrate specificity have been predicted by a combination of specificity determining positions prediction (SDPs) and subsequent mapping on the generated 3-D models.     

Beta-hairpins with native-like and non-native hydrogen bonding patterns could form during the refolding of staphylococcal nuclease

Refolding of staphylococcal nuclease has been studied recently by hydrogen-deuterium exchange and NMR spectroscopy. These studies infer that beta-hairpin formed by strand 2 and strand 3 connected by reverse turn forms early during the refolding of nuclease. Typically, hydrogen-deuterium exchange NMR techniques are usually carried out on a time scale of milliseconds whereas beta-hairpins are known to fold on a much shorter time scale. It follows that in the experiments, the hydrogen-deuterium exchange protection patterns could be arising from a significant population of fully formed hairpins. In order to demonstrate it is the fully formed hairpins which gives rise to the hydrogen-deuterium exchange protection patterns, we have considered molecular dynamics simulation of the peptide (21)DTVKLMYKGQPMTFR(35) from staphylococcal nuclease corresponding to the beta-hairpin region, using GROMOS96 force field under NVT conditions. Starting from unfolded conformational states, the peptide folds into hairpin conformations with native-like and non-native hydrogen bonding patterns. Subsequent to folding, equilibrium conditions prevail. The computed protection factors and atom depth values, at equilibrium, of the various amide protons agree qualitatively with experimental observations. A collection of molecules following the trajectories observed in the simulations can account for experimental observations. These simulations provide a molecular picture of the formed hairpins and their conformational features during the refolding experiments on nuclease, monitored by hydrogen-deuterium exchange.