Spatial Wavelet Approach to Local Matrix Crack Detection in Composite Beams with Ply Level Material Uncertainty

Wavelet coefficients based on spatial wavelets are used as damage indicators to identify the damage location as well as the size of the damage in a laminated composite beam with localized matrix cracks. A finite element model of the composite beam is used in conjunction with a matrix crack based damage model to simulate the damaged composite beam structure. The modes of vibration of the beam are analyzed using the wavelet transform in order to identify the location and the extent of the damage by sensing the local perturbations at the damage locations. The location of the damage is identified by a sudden change in spatial distribution of wavelet coefficients. Monte Carlo Simulations (MCS) are used to investigate the effect of ply level uncertainty in composite material properties such as ply longitudinal stiffness, transverse stiffness, shear modulus and Poisson's ratio on damage detection parameter, wavelet coefficient. In this study, numerical simulations are done for single and multiple damage cases. It is observed that spatial wavelets can be used as a reliable damage detection tool for composite beams with localized matrix cracks which can result from low velocity impact damage.

Synconset Waves and Chains: Spiking Onsets in Synchronous Populations Predict and Are Predicted by Network Structure

Synfire waves are propagating spike packets in synfire chains, which are feedforward chains embedded in random networks. Although synfire waves have proved to be effective quantification for network activity with clear relations to network structure, their utilities are largely limited to feedforward networks with low background activity. To overcome these shortcomings, we describe a novel generalisation of synfire waves, and define `synconset wave' as a cascade of first spikes within a synchronisation event. Synconset waves would occur in `synconset chains', which are feedforward chains embedded in possibly heavily recurrent networks with heavy background activity. We probed the utility of synconset waves using simulation of single compartment neuron network models with biophysically realistic conductances, and demonstrated that the spread of synconset waves directly follows from the network connectivity matrix and is modulated by top-down inputs and the resultant oscillations. Such synconset profiles lend intuitive insights into network organisation in terms of connection probabilities between various network regions rather than an adjacency matrix. To test this intuition, we develop a Bayesian likelihood function that quantifies the probability that an observed synfire wave was caused by a given network. Further, we demonstrate it's utility in the inverse problem of identifying the network that caused a given synfire wave. This method was effective even in highly subsampled networks where only a small subset of neurons were accessible, thus showing it's utility in experimental estimation of connectomes in real neuronal-networks. Together, we propose synconset chains/waves as an effective framework for understanding the impact of network structure on function, and as a step towards developing physiology-driven network identification methods. Finally, as synconset chains extend the utilities of synfire chains to arbitrary networks, we suggest utilities of our framework to several aspects of network physiology including cell assemblies, population codes, and oscillatory synchrony.

Differentially private stochastic gradient descent algorithm for multiparty classification

We consider the problem of developing privacy-preserving machine learning algorithms in a dis-tributed multiparty setting. Here different parties own different parts of a data set, and the goal is to learn a classifier from the entire data set with-out any party revealing any information about the individual data points it owns. Pathak et al [7]recently proposed a solution to this problem in which each party learns a local classifier from its own data, and a third party then aggregates these classifiers in a privacy-preserving manner using a cryptographic scheme. The generaliza-tion performance of their algorithm is sensitive to the number of parties and the relative frac-tions of data owned by the different parties. In this paper, we describe a new differentially pri-vate algorithm for the multiparty setting that uses a stochastic gradient descent based procedure to directly optimize the overall multiparty ob-jective rather than combining classifiers learned from optimizing local objectives. The algorithm achieves a slightly weaker form of differential privacy than that of [7], but provides improved generalization guarantees that do not depend on the number of parties or the relative sizes of the individual data sets. Experimental results corrob-orate our theoretical findings.

Effect of analyte concentration on the laser-induced plasma temperature and electron density in liquid matrix

In the present work, we report spectroscopic studies of laser-induced plasmas produced by focusing the second harmonic (532nm) of a Nd:YAG laser onto the laminar flow of a liquid containing chromium. The plasma temperature is determined from the coupled Saha-Boltzmann plot and the electron density is evaluated from the Stark broadening of an ionic line of chromium Cr(II)] at 267.7nm. Our results reveal a decrease in plasma temperature with an increase in Cr concentration up to a certain concentration level; after that, it becomes approximately constant, while the electron density increases with an increase in analyte (Cr) concentration in liquid matrix.

Infection of Human Endothelial Cells by Japanese Encephalitis Virus: Increased Expression and Release of Soluble HLA-E

Japanese encephalitis virus (JEV) is a single stranded RNA virus that infects the central nervous system leading to acute encephalitis in children. Alterations in brain endothelial cells have been shown to precede the entry of this flavivirus into the brain, but infection of endothelial cells by JEV and their consequences are still unclear. Productive JEV infection was established in human endothelial cells leading to IFN-beta and TNF-alpha production. The MHC genes for HLA-A, -B, -C and HLA-E antigens were upregulated in human brain microvascular endothelial cells, the endothelial-like cell line, ECV 304 and human foreskin fibroblasts upon JEV infection. We also report the release/shedding of soluble HLA-E (sHLA-E) from JEV infected human endothelial cells for the first time. This shedding of sHLA-E was blocked by an inhibitor of matrix metalloproteinases (MMP). In addition, MMP-9, a known mediator of HLA solubilisation was upregulated by JEV. In contrast, human fibroblasts showed only upregulation of cell-surface HLA-E. Addition of UV inactivated JEV-infected cell culture supernatants stimulated shedding of sHLA-E from uninfected ECV cells indicating a role for soluble factors/cytokines in the shedding process. Antibody mediated neutralization of TNF-alpha as well as IFNAR receptor together not only resulted in inhibition of sHLA-E shedding from uninfected cells, it also inhibited HLA-E and MMP-9 gene expression in JEV-infected cells. Shedding of sHLA-E was also observed with purified TNF-alpha and IFN-beta as well as the dsRNA analog, poly (I:C). Both IFN-beta and TNF-alpha further potentiated the shedding when added together. The role of soluble MHC antigens in JEV infection is hitherto unknown and therefore needs further investigation.

Formation and Thermal Stability of Gold-Silica Nanohybrids: Insight into the Mechanism and Morphology by Electron Tomography

Gold-silica hybrids are appealing in different fields of applications like catalysis, sensorics, drug delivery, and biotechnology. In most cases, the morphology and distribution of the heterounits play significant roles in their functional behavior. Methods of synthesizing these hybrids, with variable ordering of the heterounits, are replete; however, a complete characterization in three dimensions could not be achieved yet. A simple route to the synthesis of Au-decorated SiO2 spheres is demonstrated and a study on the 3D ordering of the heterounits by scanning transmission electron microscopy (STEM) tomography is presentedat the final stage, intermediate stages of formation, and after heating the hybrid. The final hybrid evolves from a soft self-assembled structure of Au nanoparticles. The hybrid shows good thermal stability up to 400 degrees C, beyond which the Au particles start migrating inside the SiO2 matrix. This study provides an insight in the formation mechanism and thermal stability of the structures which are crucial factors for designing and applying such hybrids in fields of catalysis and biotechnology. As the method is general, it can be applied to make similar hybrids based on SiO2 by tuning the reaction chemistry as needed.

Finite size scaling in crossover among different random matrix ensembles in microscopic lattice models

Using numerical diagonalization we study the crossover among different random matrix ensembles (Poissonian, Gaussian orthogonal ensemble (GOE), Gaussian unitary ensemble (GUE) and Gaussian symplectic ensemble (GSE)) realized in two different microscopic models. The specific diagnostic tool used to study the crossovers is the level spacing distribution. The first model is a one-dimensional lattice model of interacting hard-core bosons (or equivalently spin 1/2 objects) and the other a higher dimensional model of non-interacting particles with disorder and spin-orbit coupling. We find that the perturbation causing the crossover among the different ensembles scales to zero with system size as a power law with an exponent that depends on the ensembles between which the crossover takes place. This exponent is independent of microscopic details of the perturbation. We also find that the crossover from the Poissonian ensemble to the other three is dominated by the Poissonian to GOE crossover which introduces level repulsion while the crossover from GOE to GUE or GOE to GSE associated with symmetry breaking introduces a subdominant contribution. We also conjecture that the exponent is dependent on whether the system contains interactions among the elementary degrees of freedom or not and is independent of the dimensionality of the system.

Biodegradation of acrylamide by acrylamidase from Stenotrophomonas acidaminiphila MSU12 and analysis of degradation products by MALDI-TOF and HPLC

The present study examines an improved detoxification and rapid biological degradation of toxic pollutant acrylamide using a bacterium. The acrylamide degrading bacterium was isolated from the soil followed by its screening to know the acrylamide degrading capability. The minimal medium containing acrylamide (30 mM) served as a sole source of carbon and nitrogen for their active growth. The optimization of three different factors was analyzed by using Response Surface Methodology (RSM). The bacteria actively degraded the acrylamide at a temperature of 32 degrees C, with a maximum growth at 30 mM substrate (acrylamide) concentration at a pH of 7.2. The acrylamidase activity and degradation of acrylamide was determined by High Performance Liquid Chromatography (HPLC) and Matrix Assisted Laser Desorption and Ionization Time of Flight mass spectrometer (MALDI-TOF). Based on 168 rRNA analysis the selected strain was identified as Gram negative bacilli Stenotrophomonas acidaminiphila MSU12. The acrylamidase was isolated from bacterial extract and was purified by HPLC, whose mass spectrum showed a molecular mass of 38 kDa. (C) 2014 Elsevier Ltd. All rights reserved.

Matrix-Assisted Refolding, Purification and Activity Assessment Using a `Form Invariant' Assay for Matrix Metalloproteinase 2 (MMP2)

Matrix metalloproteinases expression is used as biomarker for various cancers and associated malignancies. Since these proteinases can cleave many intracellular proteins, overexpression tends to be toxic; hence, a challenge to purify them. To overcome these limitations, we designed a protocol where full length pro-MMP2 enzyme was overexpressed in E. coli as inclusion bodies and purified using 6xHis affinity chromatography under denaturing conditions. In one step, the enzyme was purified and refolded directly on the affinity matrix under redox conditions to obtain a bioactive protein. The pro-MMP2 protein was characterized by mass spectrometry, CD spectroscopy, zymography and activity analysis using a simple in-house developed `form invariant' assay, which reports the total MMP2 activity independent of its various forms. The methodology yielded higher yields of bioactive protein compared to other strategies reported till date, and we anticipate that using the protocol, other toxic proteins can also be overexpressed and purified from E. coli and subsequently refolded into active form using a one step renaturation protocol.

SnO2 nanowire anchored graphene nanosheet matrix for the superior performance of Li-ion thin film battery anode

All solid state batteries are essential candidate for miniaturizing the portable electronics devices. Thin film batteries are constructed by layer by layer deposition of electrode materials by physical vapour deposition method. We propose a promising novel method and unique architecture, in which highly porous graphene sheet embedded with SnO2 nanowire could be employed as the anode electrode in lithium ion thin film battery. The vertically standing graphene flakes were synthesized by microwave plasma CVD and SnO2 nanowires based on a vapour-liquid-solid (VLS) mechanism via thermal evaporation at low synthesis temperature (620 degrees C). The graphene sheet/SnO2 nanowire composite electrode demonstrated stable cycling behaviours and delivered a initial high specific discharge capacity of 1335 mAh g(-1) and 900 mAh g(-1) after the 50th cycle. Furthermore, the SnO2 nanowire electrode displayed superior rate capabilities with various current densities.

OPTIMALITY OF THE PRODUCT-MATRIX CONSTRUCTION FOR SECURE MSR REGENERATING CODES

In this paper, we consider the security of exact-repair regenerating codes operating at the minimum-storage-regenerating (MSR) point. The security requirement (introduced in Shah et. al.) is that no information about the stored data file must be leaked in the presence of an eavesdropper who has access to the contents of l(1) nodes as well as all the repair traffic entering a second disjoint set of l(2) nodes. We derive an upper bound on the size of a data file that can be securely stored that holds whenever l(2) <= d - k +1. This upper bound proves the optimality of the product-matrix-based construction of secure MSR regenerating codes by Shah et. al.

Synthesis of a new tungsten-free gamma-gamma ` cobalt-based superalloy by tuning alloying additions

The paper presents the synthesis of a new class of gamma-gamma' cobalt-based superalloy that is free of tungsten as an alloying addition. It has much lower density and higher specific strength than the existing cobalt-based superalloys. The current superalloys have a base composition of Co-10Al and are further tuned by the addition of a binary combination of molybdenum and niobium, with the optimum composition of Co-10Al-5Mo-2Nb. The solvus temperature of the alloy (866 degrees C) can be further enhanced above 950 C by the addition of Ni to give the form Co-xNi-10Al-5Mo-2Nb, where x can be from 0 to 30 at.%. After heat treatment, these alloys exhibit a duplex microstructure with coherent cuboidal L1(2)-ordered precipitates (gamma') throughout the face-centred cubic matrix (gamma), yielding a microstructure that is very similar to nickel-based superalloys as well as recently developed Co-Al-W-based alloys. We show that the stability of the gamma' phase improves significantly with the nickel addition, which can be attributed to the increase in solvus temperature. A very high specific 0.2% proof stress of 94.3 MPa g(-1) cm(-3) at room temperature and 63.8 MPa g(-1) cm(-3) at 870 degrees C were obtained for alloy Co-30Ni-10Al-5Mo-2Nb. The remarkably high specific strength of these alloys makes this class of alloy a promising material for use at high temperature, including gas turbine applications. (C) 2014 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Facile green fabrication of iron-doped cubic ZrO2 nanoparticles by Phyllanthus acidus: Structural, photocatalytic and photoluminescent properties

Cubic ZrO2: Fe3+ (0.5-4 mol%) nanoparticles (NPs) were synthesized via bin-inspired, inexpensive and simple route using Phyllanthus acidus as fuel. PXRD, SEM, TEM, FTIR, UV absorption and PL studies were performed to ascertain the formation of NPs. Rietveld analysis confirmed the formation of cubic structure. The influence of Fe3+ on the structure, morphology, UV absorption, PL emission and photocatalytic activity of NPs were investigated. The CIE chromaticity coordinates (0.36, 0.41) show that NPs could be a promising candidate for white LEDs. The influence of Fe3+ on ZrO2 matrix for photocatalytic degradation of AO7 was evaluated under UVA and Sunlight irradiation. The enhanced photocatalytic activity of spherical shaped ZrO2: Fe3+ (2 mol%) under UVA light was attributed to dopant concentration, crystallite size, narrow band gap, textural properties and capability for reducing the electron-hole pair recombination. The trend of inhibitory effect in the presence of different radical scavengers were followed the order SO42- > Cl- > C2H5OH > HCO3- > CO32-. The recycling catalytic ability of the ZrO2: Fe3+ (2 mol%) was also evaluated with a negligible decrease in the degradation efficiency even after the sixth successive run. (C) 2014 Elsevier B.V. All rights reserved.

Low-Wear High-Friction Behavior of Copper Matrix Composites Dispersed With an In Situ Polymer Derived Ceramic

We show that copper-matrix composites that contain 20 vol. % of an in situ processed, polymer-derived, ceramic phase constituted from Si-C-N have unusual friction-and-wear properties. They show negligible wear despite a coefficient of friction (COF) that approaches 0.7. This behavior is ascribed to the lamellar structure of the composite such that the interlamellar regions are infused with nanoscale dispersion of ceramic particles. There is significant hardening of the composite just adjacent to the wear surface by severe plastic deformation.

A matrix model for QCD: QCD color is mixed

We use general arguments to show that colored QCD states when restricted to gauge invariant local observables are mixed. This result has important implications for confinement: a pure colorless state can never evolve into two colored states by unitary evolution. Furthermore, the mean energy in such a mixed colored state is infinite. Our arguments are confirmed in a matrix model for QCD that we have developed using the work of Narasimhan and Ramadas(3) and Singer.(2) This model, a (0 + 1)-dimensional quantum mechanical model for gluons free of divergences and capturing important topological aspects of QCD, is adapted to analytical and numerical work. It is also suitable to work on large N QCD. As applications, we show that the gluon spectrum is gapped and also estimate some low-lying levels for N = 2 and 3 (colors). Incidentally the considerations here are generic and apply to any non-Abelian gauge theory.