Surface chemical and adsorption studies using Thiobacillus ferrooxidans with reference to bacterial adhesion to sulfide minerals

Adhesion of Thiobacillus ferrooxidans to pyrite and chalcopyrite in relation to its importance in bioleaching and bioflotation has been studied. Electrokinetic studies as well as FT-IR spectra suggest that the surface chemistry of Thiobacillus ferrooxidans depends on bacterial growth conditions. Sulfur-,Pyrite- and chalcopyrite-grown Thiobacillus ferrooxidans were found to be relatively more hydrophobic. The altered surface chemistry of Thiobacillus ferrooxidans was due to secretion of newer and specific proteinaceous compounds. The adsorption density corresponds to a monolayer coverage in a horizontal orientation of the cells. The xanthate flotation of pyrite in presence of Thiobacillus ferrooxidans is strongly depressed where as the cells have insignificant effect on chalcopyrite flotation. This study demonstrate that: (a)Thiobacillus ferrooxidans cells can be used for selective flotation of chalcopyrite from pyrite and importantly at natural pH values. (b)Sulfur-grown cells exhibits higher leaching kinetics than ferrous ion-grown cells.

Recent Developments in the Chemistry and Biology of G-Quadruplexes with Reference to the DNA Groove Binders

DNA is the chemotherapeutic target for treating diseases of genetic origin. Besides well-known double-helical structures (A, B, Z, parallel stranded-DNA etc.), DNA is capable of forming several multi-stranded structures (triplex, tetraplex, i-motif etc.) which have unique biological significance. The G-rich 3'-ends of chromosomes, called telomeres, are synthesized by telomerase, a ribonucleoprotein, and over-expression of telomerase is associated with cancer. The activity of telomerase is suppressed if the G-rich region is folded into the four stranded structures, called G-quadruplexes (G4-DNAs) using small synthetic ligands. Thus design and synthesis of new G4-DNA ligands is an attractive strategy to combat cancer. G4-DNA forming sequences are also prevalent in other genomic regions of biological significance including promoter regions of several oncogenes. Effective gene regulation may be achieved by inducing a G4-DNA structure within the G-rich promoter sequences. To date, several G4-DNA stabilizing ligands are known. DNA groove binders interact with the duplex B-DNA through the grooves (major and minor groove) in a sequence-specific manner. Some of the groove binders are known to stabilize the G4-DNA. However, this is a relatively under explored field of research. In this review, we focus on the recent advances in the understanding of the G4-DNA structures, particularly made from the human telomeric DNA stretches. We summarize the results of various investigations of the interaction of various organic ligands with the G4-DNA while highlighting the importance of groove binder-G4-DNA interactions.

Statistical Methods for Accelerated Life Testing with Particular Reference to Resin Impregnated Paper Bushings

Electrical failure of insulation is known to be an extremal random process wherein nominally identical pro-rated specimens of equipment insulation, at constant stress fail at inordinately different times even under laboratory test conditions. In order to be able to estimate the life of power equipment, it is necessary to run long duration ageing experiments under accelerated stresses, to acquire and analyze insulation specific failure data. In the present work, Resin Impregnated Paper (RIP) a relatively new insulation system of choice used in transformer bushings, is taken as an example. The failure data has been processed using proven statistical methods, both graphical and analytical. The physical model governing insulation failure at constant accelerated stress has been assumed to be based on temperature dependent inverse power law model.

Classification, representation, and automatic extraction of deformation features in sheet metal parts

This paper presents classification, representation and extraction of deformation features in sheet-metal parts. The thickness is constant for these shape features and hence these are also referred to as constant thickness features. The deformation feature is represented as a set of faces with a characteristic arrangement among the faces. Deformation of the base-sheet or forming of material creates Bends and Walls with respect to a base-sheet or a reference plane. These are referred to as Basic Deformation Features (BDFs). Compound deformation features having two or more BDFs are defined as characteristic combinations of Bends and Walls and represented as a graph called Basic Deformation Features Graph (BDFG). The graph, therefore, represents a compound deformation feature uniquely. The characteristic arrangement of the faces and type of bends belonging to the feature decide the type and nature of the deformation feature. Algorithms have been developed to extract and identify deformation features from a CAD model of sheet-metal parts. The proposed algorithm does not require folding and unfolding of the part as intermediate steps to recognize deformation features. Representations of typical features are illustrated and results of extracting these deformation features from typical sheet metal parts are presented and discussed. (C) 2013 Elsevier Ltd. All rights reserved.

Unified Taxonomy for Reference Ontology of Shape Features in Product Model

This paper presents a unified taxonomy of shape features. Such taxonomy is required to construct ontologies to address heterogeneity in product/shape models. Literature provides separate classifications for volumetric, deformation and free-form surface features. The unified taxonomy proposed allows classification, representation and extraction of shape features in a product model. The novelty of the taxonomy is that the classification is based purely on shape entities and therefore it is possible to automatically extract the features from any shape model. This enables the use of this taxonomy to build reference ontology.

Bivariate frequency analysis of floods using a diffusion based kernel density estimator

Recent focus of flood frequency analysis (FFA) studies has been on development of methods to model joint distributions of variables such as peak flow, volume, and duration that characterize a flood event, as comprehensive knowledge of flood event is often necessary in hydrological applications. Diffusion process based adaptive kernel (D-kernel) is suggested in this paper for this purpose. It is data driven, flexible and unlike most kernel density estimators, always yields a bona fide probability density function. It overcomes shortcomings associated with the use of conventional kernel density estimators in FFA, such as boundary leakage problem and normal reference rule. The potential of the D-kernel is demonstrated by application to synthetic samples of various sizes drawn from known unimodal and bimodal populations, and five typical peak flow records from different parts of the world. It is shown to be effective when compared to conventional Gaussian kernel and the best of seven commonly used copulas (Gumbel-Hougaard, Frank, Clayton, Joe, Normal, Plackett, and Student's T) in estimating joint distribution of peak flow characteristics and extrapolating beyond historical maxima. Selection of optimum number of bins is found to be critical in modeling with D-kernel.

Average Modelling of a Voltage Source Inverter with Dead-Time in a Synchronous Reference Frame

Voltage source inverters are an integral part of renewable power sources and smart grid systems. Computationally efficient and fairly accurate models for the voltage source inverter are required to carry out extensive simulation studies on complex power networks. Accuracy requires that the effect of dead-time be incorporated in the inverter model. The dead-time is essentially a short delay introduced between the gating pulses to the complementary switches in an inverter leg for the safety of power devices. As the modern voltage source inverters switch at fairly high frequencies, the dead-time significantly influences the output fundamental voltage. Dead-time also causes low-frequency harmonic distortion and is hence important from a power quality perspective. This paper studies the dead-time effect in a synchronous dq reference frame, since dynamic studies and controller design are typically carried out in this frame of reference. For the sake of computational efficiency, average models are derived, incorporating the dead-time effect, in both RYB and dq reference frames. The average models are shown to consume less computation time than their corresponding switching models, the accuracies of the models being comparable. The proposed average synchronous reference frame model, including effect of dead-time, is validated through experimental results.

Performance evaluation of typical approximation algorithms for nonconvex l(p)-minimization in diffuse optical tomography

The sparse estimation methods that utilize the l(p)-norm, with p being between 0 and 1, have shown better utility in providing optimal solutions to the inverse problem in diffuse optical tomography. These l(p)-norm-based regularizations make the optimization function nonconvex, and algorithms that implement l(p)-norm minimization utilize approximations to the original l(p)-norm function. In this work, three such typical methods for implementing the l(p)-norm were considered, namely, iteratively reweighted l(1)-minimization (IRL1), iteratively reweighted least squares (IRLS), and the iteratively thresholding method (ITM). These methods were deployed for performing diffuse optical tomographic image reconstruction, and a systematic comparison with the help of three numerical and gelatin phantom cases was executed. The results indicate that these three methods in the implementation of l(p)-minimization yields similar results, with IRL1 fairing marginally in cases considered here in terms of shape recovery and quantitative accuracy of the reconstructed diffuse optical tomographic images. (C) 2014 Optical Society of America

Skip Decision and Reference Frame Selection for Low-Complexity H.264/AVC Surveillance Video Coding

H. 264/advanced video coding surveillance video encoders use the Skip mode specified by the standard to reduce bandwidth. They also use multiple frames as reference for motion-compensated prediction. In this paper, we propose two techniques to reduce the bandwidth and computational cost of static camera surveillance video encoders without affecting detection and recognition performance. A spatial sampler is proposed to sample pixels that are segmented using a Gaussian mixture model. Modified weight updates are derived for the parameters of the mixture model to reduce floating point computations. A storage pattern of the parameters in memory is also modified to improve cache performance. Skip selection is performed using the segmentation results of the sampled pixels. The second contribution is a low computational cost algorithm to choose the reference frames. The proposed reference frame selection algorithm reduces the cost of coding uncovered background regions. We also study the number of reference frames required to achieve good coding efficiency. Distortion over foreground pixels is measured to quantify the performance of the proposed techniques. Experimental results show bit rate savings of up to 94.5% over methods proposed in literature on video surveillance data sets. The proposed techniques also provide up to 74.5% reduction in compression complexity without increasing the distortion over the foreground regions in the video sequence.

Solar photovoltaic assistance for LHB rail coaches

Awareness for the need of sustainable and eco-friendly mobility has been increasing and various innovations are taking place in this regard. A study was carried out to assess the feasibility of installing solar photovoltaic (PV) modules atop train coaches. Most long-distance trains having LHB coaches do not have self-generating systems, thus making power cars mandatory to supply the required power for lighting loads. Feasibility of supplementing diesel generator sets with power from solar PV modules installed on coach rooftops has been reported in this communication. Not only is there a conservation of fuel, there is also a significant reduction in CO2 emissions. This work has shown that the area available on coach rooftops is more than sufficient to generate the required power, during sunlight hours, for the electrical loads of a non-A/C coach even during winter. All calculations were done keeping a standard route as the reference. Taking the cost of diesel to be Rs 66/litre, it was estimated that there will be annual savings of Rs 5,900,000 corresponding to 90,800 litres diesel per rake per year by implementing this scheme. The installation cost of solar modules would be recovered within 2-3 years. Implementation of this scheme would also amount to an annual reduction of 239 tonnes of CO2 emissions.