Rule-based modelling of iron homeostasis in tuberculosis

To establish itself within the host system, Mycobacterium tuberculosis (Mtb) has formulated various means of attacking the host system. One such crucial strategy is the exploitation of the iron resources of the host system. Obtaining and maintaining the required concentration of iron becomes a matter of contest between the host and the pathogen, both trying to achieve this through complex molecular networks. The extent of complexity makes it important to obtain a systems perspective of the interplay between the host and the pathogen with respect to iron homeostasis. We have reconstructed a systems model comprising 92 components and 85 protein-protein or protein-metabolite interactions, which have been captured as a set of 194 rules. Apart from the interactions, these rules also account for protein synthesis and decay, RBC circulation and bacterial production and death rates. We have used a rule-based modelling approach, Kappa, to simulate the system separately under infection and non-infection conditions. Various perturbations including knock-outs and dual perturbation were also carried out to monitor the behavioral change of important proteins and metabolites. From this, key components as well as the required controlling factors in the model that are critical for maintaining iron homeostasis were identified. The model is able to re-establish the importance of iron-dependent regulator (ideR) in Mtb and transferrin (Tf) in the host. Perturbations, where iron storage is increased, appear to enhance nutritional immunity and the analysis indicates how they can be harmful for the host. Instead, decreasing the rate of iron uptake by Tf may prove to be helpful. Simulation and perturbation studies help in identifying Tf as a possible drug target. Regulating the mycobactin (myB) concentration was also identified as a possible strategy to control bacterial growth. The simulations thus provide significant insight into iron homeostasis and also for identifying possible drug targets for tuberculosis.

Pixel based fusion using IKONOS imagery

Pixel based image fusion entails combining geometric details of a high-resolution Panchromatic (PAN) image and spectral information of a low-resolution Multispectral (MS) image to produce images with highest spatial content while preserving the spectral information. This work reviews and implements six fusion techniques – À Trous algorithm based wavelet transform (ATW), Mulitresolution Analysis based Intensity Modulation, Gram Schmidt fusion, CN Spectral, Luminance Chrominance and High pass fusion (HPF) on IKONOS imagery having 1 m PAN and 4 m MS channels. Comparative performance analysis of techniques by various methods reveals that ATW followed by HPF perform best among all the techniques.

Fuzzy Clustering Based Ad Recommendation for TV Programs

Advertisements(Ads) are the main revenue earner for Television (TV) broadcasters. As TV reaches a large audience, it acts as the best media for advertisements of products and services. With the emergence of digital TV, it is important for the broadcasters to provide an intelligent service according to the various dimensions like program features, ad features, viewers’ interest and sponsors’ preference. We present an automatic ad recommendation algorithm that selects a set of ads by considering these dimensions and semantically match them with programs. Features of the ad video are captured interms of annotations and they are grouped into number of predefined semantic categories by using a categorization technique. Fuzzy categorical data clustering technique is applied on categorized data for selecting better suited ads for a particular program. Since the same ad can be recommended for more than one program depending upon multiple parameters, fuzzy clustering acts as the best suited method for ad recommendation. The relative fuzzy score called “degree of membership” calculated for each ad indicates the membership of a particular ad to different program clusters. Subjective evaluation of the algorithm is done by 10 different people and rated with a high success score.

Inhibition of peroxynitrite- and peroxidase-mediated protein tyrosine nitration by imidazole-based thiourea and selenourea derivatives

In the present study, the synthesis and characterization of a series of N-methylimidazole-based thiourea and selenourea derivatives are described. The new compounds were also studied for their ability to inhibit peroxynitrite (PN)- and peroxidase-mediated nitration of protein tyrosine residues. It has been observed that the selenourea derivatives are more efficient than the thiourea-based compounds in the inhibition of protein nitration. The higher activity of selenoureas as compared to that of the corresponding thioureas can be ascribed to the zwitterionic nature of the selenourea moiety. Single crystal X-ray diffraction studies on some of the thiourea and selenourea derivatives reveal that the C S bonds in thioureas possess more of double bond character than the C=Se bonds in the corresponding selenoureas. Therefore, the selenium compounds can react with PN or hydrogen peroxide much faster than their sulfur analogues. The reactions of thiourea and selenourea derivatives with PN or hydrogen peroxide produce the corresponding sulfinic or seleninic acid derivatives, which upon elimination of sulfurous/selenous acids produce the corresponding N-methylimdazole derivatives.

Exploring the spectral enantiodiscrimination potential of a DNA-based orienting medium using deuterium NMR spectroscopy

(2)H-{(1)H} 1D and 2D-NMR spectroscopy is used to evaluate the enantiodiscrimination potential of DNA-based, lyotropic chiral mesophases on a series of (pro) chiral amino acids.

Wavelet based spectral finite element modelling and detection of de-lamination in composite beams

In this paper, a model for composite beam with embedded de-lamination is developed using the wavelet based spectral finite element (WSFE) method particularly for damage detection using wave propagation analysis. The simulated responses are used as surrogate experimental results for the inverse problem of detection of damage using wavelet filtering. The WSFE technique is very similar to the fast fourier transform (FFT) based spectral finite element (FSFE) except that it uses compactly supported Daubechies scaling function approximation in time. Unlike FSFE formulation with periodicity assumption, the wavelet-based method allows imposition of initial values and thus is free from wrap around problems. This helps in analysis of finite length undamped structures, where the FSFE method fails to simulate accurate response. First, numerical experiments are performed to study the effect of de-lamination on the wave propagation characteristics. The responses are simulated for different de-lamination configurations for both broad-band and narrow-band excitations. Next, simulated responses are used for damage detection using wavelet analysis.

A galvanic sensor for SO3/SO2 based on CaF2/CaSO4 couple

Measurements on the solid state cell, View the MathML source using single crystal CaF2 as the solid electrolyte and CaSO4 as an auxiliary electrode, indicate that the EMF is in agreement with that predicted by the Nernst equation when equilibrium is assumed in the gas phase near the electrodes. The cell can be used to measure the View the MathML source content of gases at temperatures near 1200 K, where approximately 2 h ate required to obtain a steady EMF, without the use of catalysts to improve the kinetics of exchange reaction in the auxiliary electrode. For most applications, the cell EMF will be affected by the presence of water vapour in the gas phase. The cell is well suited for thermodynamic measurements on sulfates, pyrosulfates and their solid and liquid solutions.

Variation of the gas and radiation content in the sub-Keplerian accretion disk around black holes and its impact to the solutions

We investigate the variation of the gas and the radiation pressure in accretion disks during the infall of matter to the black hole and its effect to the flow. While the flow far away from the black hole might be non-relativistic, in the vicinity of the black hole it is expected to be relativistic behaving more like radiation. Therefore, the ratio of gas pressure to total pressure (beta) and the underlying polytropic index (gamma) should not be constant throughout the flow. We obtain that accretion flows exhibit significant variation of beta and then gamma, which affects solutions described in the standard literature based on constant beta. Certain solutions for a particular set of initial parameters with a constant beta do not exist when the variation of beta is incorporated appropriately. We model the viscous sub-Keplerian accretion disk with a nonzero component of advection and pressure gradient around black holes by preserving the conservations of mass, momentum, energy, supplemented by the evolution of beta. By solving the set of five coupled differential equations, we obtain the thermo-hydrodynamical properties of the flow. We show that during infall, beta of the flow could vary up to similar to 300%, while gamma up to similar to 20%. This might have a significant impact to the disk solutions in explaining observed data, e.g. super-luminal jets from disks, luminosity, and then extracting fundamental properties from them. Hence any conclusion based on constant gamma and beta should be taken with caution and corrected. (C) 2011 Elsevier B.V. All rights reserved.

Designing copper-zirconium based nanowires for improving yield strength and plasticity by configuring surface atoms

Epitaxial-Bain-Path and Uniaxial-Bain-Path studies reveal that a B2-CuZr nanowire with Zr atoms on the surface is energetically more stable compared to a B2-CuZr nanowire with Cu atoms on the surface. Nanowires of cross-sectional dimensions in the range of similar to 20-50 are considered. Such stability is also correlated with the initial state of stress in the nanowires. It is also demonstrated here that a more stable structure, i.e., B2-CuZr nanowire with Zr atoms at surface shows improved yield strength compared to B2-CuZr nanowire with Cu atoms at surface site, over range of temperature under both the tensile and the compressive loadings. Nearly 18% increase in the average yield strength under tensile loading and nearly 26% increase in the averaged yield strength under compressive loading are observed for nanowires with various cross-sectional dimensions and temperatures. It is also observed that the B2-CuZr nanowire with Cu atom at the surface site shows a decrease in failure/plastic strain with an increase in temperature. On the other hand, B2-CuZr nanowires with Zr at the surface site shows an improvement in failure/plastic strain, specially at higher temperature as compared to the B2-CuZr nanowires which are having Cu atoms at the surface site. Finally, a possible design methodology for an energetically stable nano-structure with improved thermo-mechanical properties via manipulating the surface atom configuration is proposed.

Some adsorption-nucleation-based models for electrochemical phase formation

A new class of models which are based on adsorption, nucleation growth and their coupling is discussed. In particular, the potentiostatic response of a model that involves nucleative phase growth via direct incorporation and adsorptive discharge of metal ions on the free area is analysed for both instantaneous and progressive nucleation. This model is able to predict certain experimental features in the potentiostatic transient, like the initial fall, shoulder or maximum (as well as minimum) which have not been predicted by models analysed hitherto.Limiting behaviour for short and long times as well as a description of the above-mentioned features in terms of model parameters are given.A special case of the above model, viz. a reversible adsorption–nucleation model, wherein the adsorption is very fast, is shown to give rise to transients which can be distinguished from the pure nucleation-growth transients only by its parametric dependence, but not by the form.

Scale effects on buckling analysis of orthotropic nanoplates based on nonlocal two-variable refined plate theory

This article presents the buckling analysis of orthotropic nanoplates such as graphene using the two-variable refined plate theory and nonlocal small-scale effects. The two-variable refined plate theory takes account of transverse shear effects and parabolic distribution of the transverse shear strains through the thickness of the plate, hence it is unnecessary to use shear correction factors. Nonlocal governing equations of motion for the monolayer graphene are derived from the principle of virtual displacements. The closed-form solution for buckling load of a simply supported rectangular orthotropic nanoplate subjected to in-plane loading has been obtained by using the Navier's method. Numerical results obtained by the present theory are compared with first-order shear deformation theory for various shear correction factors. It has been proven that the nondimensional buckling load of the orthotropic nanoplate is always smaller than that of the isotropic nanoplate. It is also shown that small-scale effects contribute significantly to the mechanical behavior of orthotropic graphene sheets and cannot be neglected. Further, buckling load decreases with the increase of the nonlocal scale parameter value. The effects of the mode number, compression ratio and aspect ratio on the buckling load of the orthotropic nanoplate are also captured and discussed in detail. The results presented in this work may provide useful guidance for design and development of orthotropic graphene based nanodevices that make use of the buckling properties of orthotropic nanoplates.

Biologically triggered exploding protein based microcapsules for drug delivery

Biologically triggered exploding microcapsules were synthesized by layer-by-layer assembly of biopolymers. The microcapsules showed controlled rupturing behaviour upon exposure to a pathologically relevant biomolecule, trypsin. These microcapsules offer significant potential for clinical applications.

DNA-binding and nuclease activity of1,10-phenanthroline-based thiocyanato, acetato, azido and benzoato bridged dinuclear copper(II) complexes

The mononuclear Cu(II) complex [Cu(phen)(H2O)(NO3)(2)] (1), obtained by the reaction of 1,10-phenanthroline with Cu(NO3)(2)center dot 3H(2)O in methanol solution, reacts with anionic ligands SCN-, AcO-, N-3(-) and PhCO2- in MeOH solution to form the stable binuclear complexes [Cu-2(H2O)(2)(phen)(2)(mu-X)(2)](2) (NO3)(2), where X = SCN- (2), AcO- (3), N-3(-) (4) or PhCO2- (5). The molecular structure of complex 3 was determined by single-crystal X-ray diffraction studies. These complexes were characterized by electronic, IR, ESR, magnetic moments and conductivity measurements. The electrochemical behaviour of the complexes was investigated by cyclic voltammetry. The interactions of these complexes with calf thymus DNA have been investigated using absorption spectrophotometry. Their DNA cleavage activity was studied on double-stranded pBR322 plasmid DNA using gel electrophoresis experiments in the absence and presence of H2O2 as oxidant.

A Long Memory Process Based Parametric Modeling and Recognition of PD Signal

We address the problem of recognition and retrieval of relatively weak industrial signal such as Partial Discharges (PD) buried in excessive noise. The major bottleneck being the recognition and suppression of stochastic pulsive interference (PI) which has similar time-frequency characteristics as PD pulse. Therefore conventional frequency based DSP techniques are not useful in retrieving PD pulses. We employ statistical signal modeling based on combination of long-memory process and probabilistic principal component analysis (PPCA). An parametric analysis of the signal is exercised for extracting the features of desired pules. We incorporate a wavelet based bootstrap method for obtaining the noise training vectors from observed data. The procedure adopted in this work is completely different from the research work reported in the literature, which is generally based on deserved signal frequency and noise frequency.

Time Series Classification for Online Tamil Handwritten Character Recognition – A Kernel Based Approach

In this paper, we consider the problem of time series classification. Using piecewise linear interpolation various novel kernels are obtained which can be used with Support vector machines for designing classifiers capable of deciding the class of a given time series. The approach is general and is applicable in many scenarios. We apply the method to the task of Online Tamil handwritten character recognition with promising results.