Evolution of Nanocrystalline Ba2NaNb5O15 in 2BaO-0.5Na(2)O-2.5Nb(2)O(5)-4.5B(2)O(3) Glass System and Its Refractive Index and Band Gap Tunability

Monophasic Ba2NaNb5O15 was crystallized at nanometer scale (12-36 nm) in 2BaO-0.5Na(2)O-2.5Nb(2)O(5)- 4.5B(2)O(3) glass system. To begin with, optically transparent glasses, in this system, were fabricated via the conventional melt. quenching technique. The amorphous and glassy characteristics of the as-quenched samples were respectively confirmed by X-ray powder diffraction and differential thermal analyses. Nearly homogeneous distribution of Ba2NaNb5O15 (BNN) nanocrystals associated with tungsten bronze structure akin to their bulk parent structure was accomplished by subjecting the as-fabricated glasses to appropriate heat-treatment temperatures. Indeed transmission electron microscopy (TEM) carried out on these samples corroborated the presence of Ba2NaNb5O15 nanocrystals dispersed in a continuous glass matrix. The as-quenched glasses were similar to 75% transparent in the visible range of the electromagnetic spectrum. The optical band gap and refractive index were found to have crystallite size (at nanoscale) dependence. The optical band gap increased with the decrease in crystallite size. The refractive indices of the glass nanocrystal composites as determined by Brewster angle method were rationalized using different empirical models. The refractive index dispersion with wavelength of light was analyzed on the basis of the Sellmeier relations. At room temperature under UV excitation (355 nm) these glass nanocrystal composites displayed violet-blue emission which was ascribed to the defects states.

Asymmetric cell division in Mycobacterium tuberculosis and its unique features

Recently, several reports showed that about 80 % of mid-log phase Mycobacterium smegmatis, Mycobacterium marinum, and Mycobacterium bovis BCG cells divide symmetrically with 5-10 % deviation in the septum position from the median. However, the mode of cell division of the pathogenic mycobacterial species, Mycobacterium tuberculosis, remained unclear. Therefore, in the present study, using electron microscopy, fluorescence microscopy of septum- and nucleoid-stained live and fixed cells, and live cell time-lapse imaging, we show the occurrence of asymmetric cell division with unusually deviated septum/constriction in 20 % of the 15 % septating M. tuberculosis cells in the mid-log phase population. The remaining 80 % of the 15 % septating cells divided symmetrically but with 2-5 % deviation in the septum/constriction position, as reported for M. smegmatis, M. marinum, and M. bovis BCG cells. Both the long and the short portions of the asymmetrically dividing M. tuberculosis cells with unusually deviated septum contained nucleoids, thereby generating viable short and long cells from each asymmetric division. M. tuberculosis short cells were acid fast positive and, like the long cells, further readily underwent growth and division to generate micro-colony, thereby showing that they were neither mini cells, spores nor dormant forms of mycobacteria. The freshly diagnosed pulmonary tuberculosis patients' sputum samples, which are known for the prevalence of oxidative stress conditions, also contained short cells at the same proportion as that in the mid-log phase population. The probable physiological significance of the generation of the short cells through unusually deviated asymmetric cell division is discussed.

Multi-site downscaling of maximum and minimum daily temperature using support vector machine

Climate change impact assessment studies involve downscaling large-scale atmospheric predictor variables (LSAPVs) simulated by general circulation models (GCMs) to site-scale meteorological variables. This article presents a least-square support vector machine (LS-SVM)-based methodology for multi-site downscaling of maximum and minimum daily temperature series. The methodology involves (1) delineation of sites in the study area into clusters based on correlation structure of predictands, (2) downscaling LSAPVs to monthly time series of predictands at a representative site identified in each of the clusters, (3) translation of the downscaled information in each cluster from the representative site to that at other sites using LS-SVM inter-site regression relationships, and (4) disaggregation of the information at each site from monthly to daily time scale using k-nearest neighbour disaggregation methodology. Effectiveness of the methodology is demonstrated by application to data pertaining to four sites in the catchment of Beas river basin, India. Simulations of Canadian coupled global climate model (CGCM3.1/T63) for four IPCC SRES scenarios namely A1B, A2, B1 and COMMIT were downscaled to future projections of the predictands in the study area. Comparison of results with those based on recently proposed multivariate multiple linear regression (MMLR) based downscaling method and multi-site multivariate statistical downscaling (MMSD) method indicate that the proposed method is promising and it can be considered as a feasible choice in statistical downscaling studies. The performance of the method in downscaling daily minimum temperature was found to be better when compared with that in downscaling daily maximum temperature. Results indicate an increase in annual average maximum and minimum temperatures at all the sites for A1B, A2 and B1 scenarios. The projected increment is high for A2 scenario, and it is followed by that for A1B, B1 and COMMIT scenarios. Projections, in general, indicated an increase in mean monthly maximum and minimum temperatures during January to February and October to December.

Automatic finite element formulation and assembly of hyperelastic higher order structural models

The formulation of higher order structural models and their discretization using the finite element method is difficult owing to their complexity, especially in the presence of non-linearities. In this work a new algorithm for automating the formulation and assembly of hyperelastic higher-order structural finite elements is developed. A hierarchic series of kinematic models is proposed for modeling structures with special geometries and the algorithm is formulated to automate the study of this class of higher order structural models. The algorithm developed in this work sidesteps the need for an explicit derivation of the governing equations for the individual kinematic modes. Using a novel procedure involving a nodal degree-of-freedom based automatic assembly algorithm, automatic differentiation and higher dimensional quadrature, the relevant finite element matrices are directly computed from the variational statement of elasticity and the higher order kinematic model. Another significant feature of the proposed algorithm is that natural boundary conditions are implicitly handled for arbitrary higher order kinematic models. The validity algorithm is illustrated with examples involving linear elasticity and hyperelasticity. (C) 2013 Elsevier Inc. All rights reserved.

Defect induced plasticity and failure mechanism of boron nitride nanotubes under tension

The effects of Stone-Wales (SW) and vacancy defects on the failure behavior of boron nitride nanotubes (BNNTs) under tension are investigated using molecular dynamics simulations. The Tersoff-Brenner potential is used to model the atomic interaction and the temperature is maintained close to 300 K. The effect of a SW defect is studied by determining the failure strength and failure mechanism of nanotubes with different radii. In the case of a vacancy defect, the effect of an N-vacancy and a B-vacancy is studied separately. Nanotubes with different chiralities but similar diameter is considered first to evaluate the chirality dependence. The variation of failure strength with the radius is then studied by considering nanotubes of different diameters but same chirality. It is observed that the armchair BNNTs are extremely sensitive to defects, whereas the zigzag configurations are the least sensitive. In the case of pristine BNNTs, both armchair and zigzag nanotubes undergo brittle failure, whereas in the case of defective BNNTs, only the zigzag ones undergo brittle failure. An interesting defect induced plastic behavior is observed in defective armchair BNNTs. For this nanotube, the presence of a defect triggers mechanical relaxation by bond breaking along the closest zigzag helical path, with the defect as the nucleus. This mechanism results in a plastic failure. (C) 2014 AIP Publishing LLC.

A Smooth Discretization Bridging Finite Element and Mesh-free Methods Using Polynomial Reproducing Simplex Splines

This work sets forth a `hybrid' discretization scheme utilizing bivariate simplex splines as kernels in a polynomial reproducing scheme constructed over a conventional Finite Element Method (FEM)-like domain discretization based on Delaunay triangulation. Careful construction of the simplex spline knotset ensures the success of the polynomial reproduction procedure at all points in the domain of interest, a significant advancement over its precursor, the DMS-FEM. The shape functions in the proposed method inherit the global continuity (Cp-1) and local supports of the simplex splines of degree p. In the proposed scheme, the triangles comprising the domain discretization also serve as background cells for numerical integration which here are near-aligned to the supports of the shape functions (and their intersections), thus considerably ameliorating an oft-cited source of inaccuracy in the numerical integration of mesh-free (MF) schemes. Numerical experiments show the proposed method requires lower order quadrature rules for accurate evaluation of integrals in the Galerkin weak form. Numerical demonstrations of optimal convergence rates for a few test cases are given and the method is also implemented to compute crack-tip fields in a gradient-enhanced elasticity model.

Genetic diversity and proviral DNA load in different neural compartments of HIV-1 subtype C infection

In India, the low prevalence of HIV-associated dementia (HAD) in the Human immunodeficiency virus type 1 (HIV-1) subtype C infection is quite paradoxical given the high-rate of macrophage infiltration into the brain. Whether the direct viral burden in individual brain compartments could be associated with the variability of the neurologic manifestations is controversial. To understand this paradox, we examined the proviral DNA load in nine different brain regions and three different peripheral tissues derived from ten human subjects at autopsy. Using a highly sensitive TaqMan probe-based real-time PCR, we determined the proviral load in multiple samples processed in parallel from each site. Unlike previously published reports, the present analysis identified uniform proviral distribution among the brain compartments examined without preferential accumulation of the DNA in any one of them. The overall viral DNA burden in the brain tissues was very low, approximately 1 viral integration per 1000 cells or less. In a subset of the tissue samples tested, the HIV DNA mostly existed in a free unintegrated form. The V3-V5 envelope sequences, demonstrated a brain-specific compartmentalization in four of the ten subjects and a phylogenetic overlap between the neural and non-neural compartments in three other subjects. The envelope sequences phylogenetically belonged to subtype C and the majority of them were R5 tropic. To the best of our knowledge, the present study represents the first analysis of the proviral burden in subtype C postmortem human brain tissues. Future studies should determine the presence of the viral antigens, the viral transcripts, and the proviral DNA, in parallel, in different brain compartments to shed more light on the significance of the viral burden on neurologic consequences of HIV infection.

Experimental solubilities of two lipid derivatives in supercritical carbon dioxide and new correlations based on activity coefficient models

The solubilities of two lipid derivatives, geranyl butyrate and 10-undecen-1-ol, in SCCO2 (supercritical carbon dioxide) were measured at different operating conditions of temperature (308.15 to 333.15 K) and pressure (10 to 18 MPa). The solubilities (in mole fraction) ranged from 2.1 x 10(-3) to 23.2 x 10(-3) for geranyl butyrate and 2.2 x 10(-3) to 25.0 x 10(-3) for 10-undecen-1-ol, respectively. The solubility data showed a retrograde behavior in the pressure and temperature range investigated. Various combinations of association and solution theory along with different activity coefficient models were developed. The experimental data for the solubilities of 21 liquid solutes along with geranyl butyrate and 10-undecen-1-ol were correlated using both the newly derived models and the existing models. The average deviation of the correlation of the new models was below 15%.

Residue proximity information and protein model discrimination using saturation-suppressor mutagenesis

Identification of residue-residue contacts from primary sequence can be used to guide protein structure prediction. Using Escherichia coli CcdB as the test case, we describe an experimental method termed saturation-suppressor mutagenesis to acquire residue contact information. In this methodology, for each of five inactive CcdB mutants, exhaustive screens for suppressors were performed. Proximal suppressors were accurately discriminated from distal suppressors based on their phenotypes when present as single mutants. Experimentally identified putative proximal pairs formed spatial constraints to recover >98% of native-like models of CcdB from a decoy dataset. Suppressor methodology was also applied to the integral membrane protein, diacylglycerol kinase A where the structures determined by X-ray crystallography and NMR were significantly different. Suppressor as well as sequence co-variation data clearly point to the Xray structure being the functional one adopted in vivo. The methodology is applicable to any macromolecular system for which a convenient phenotypic assay exists.

Material response and failure mechanism of unidirectional metal matrix composites under impulsive shear loading

The material response and failure mechanism of unidirectional metal matrix composite under impulsive shear loading are investigated in this paper. Both experimental and analytical studies were performed. The shear strength of unidirectional C-f/A356.0 composite and A356.0 aluminum alloy at high strain rate were measured with a modified split Hopkinson torsional bar technique. The results indicated that the carbon fibers did not improve the shear strength of aluminum matrix if the fiber orientation aligned with the shear loading axis. The microscopic inspection of the fractured surface showed a multi-scale zigzag feature which implied a complicated shear failure mechanism in the composite. In addition to testing, the micromechanical stress field in the composite was analyzed by the generalized Eshelby equivalent method (GEEM). The influence of cracking in matrix on the micromechanical stress field was investigated as well. The results showed that the stress distribution in the composite is quite nonhomogeneous and very high shear stress concentrations are found in some regions in the matrix. The high shear stress concentration in the matrix induces tensile cracking at 45 degrees to the shear direction. This in turn aggravates the stress concentration at the fiber/matrix interface and finally leads to a catastrophic failure in the composite. From the correlation between the analysis and experimental results, the shear failure mechanism of unidirectional C-f/A356.0 composite can be elucidated qualitatively.

Sequential Monte Carlo computation of the score and observed information matrix in state-space models with application to parameter estimation

Sequential Monte Carlo (SMC) methods are popular computational tools for Bayesian inference in non-linear non-Gaussian state-space models. For this class of models, we propose SMC algorithms to compute the score vector and observed information matrix recursively in time. We propose two different SMC implementations, one with computational complexity $\mathcal{O}(N)$ and the other with complexity $\mathcal{O}(N^{2})$ where $N$ is the number of importance sampling draws. Although cheaper, the performance of the $\mathcal{O}(N)$ method degrades quickly in time as it inherently relies on the SMC approximation of a sequence of probability distributions whose dimension is increasing linearly with time. In particular, even under strong \textit{mixing} assumptions, the variance of the estimates computed with the $\mathcal{O}(N)$ method increases at least quadratically in time. The $\mathcal{O}(N^{2})$ is a non-standard SMC implementation that does not suffer from this rapid degrade. We then show how both methods can be used to perform batch and recursive parameter estimation.