Density matrix renormalization group algorithm for Bethe lattices of spin-1/2 or spin-1 sites with Heisenberg antiferromagnetic exchange

A density matrix renormalization group (DMRG) algorithm is presented for the Bethe lattice with connectivity Z = 3 and antiferromagnetic exchange between nearest-neighbor spins s = 1/2 or 1 sites in successive generations g. The algorithm is accurate for s = 1 sites. The ground states are magnetic with spin S(g) = 2(g)s, staggered magnetization that persists for large g > 20, and short-range spin correlation functions that decrease exponentially. A finite energy gap to S > S(g) leads to a magnetization plateau in the extended lattice. Closely similar DMRG results for s = 1/2 and 1 are interpreted in terms of an analytical three-site model.

A novel ``pro-sensitizer'' based sensing of enzymes using Tb(III) luminescence in a hydrogel matrix

Chemically synthesized ``pro-sensitizers'' release the sensitizer in the presence of lipase or beta-glucosidase, triggering a significant luminescence response from a lanthanide based hydrogel.

Ag@AgI, Core@Shell Structure in Agarose Matrix as Hybrid: Synthesis, Characterization, and Antimicrobial Activity

A novel in situ core@shell structure consisting of nanoparticles of Ag (Ag Nps) and AgI in agarose matrix (Ag@ AgI/agarose) has been synthesized as a hybrid, in order to have an efficient antibacterial agent for repetitive usage with no toxicity. The synthesized core@shell structure is very well characterized by XRD, UV-visible, photoluminescence, and TEM. A detailed antibacterial studies including repetitive cycles are carried out on Gram-negative Escherichia coli (E. coli) and Gram-positive Staphylococcus aureus (S. aureus) bacteria in saline water, both in dark and on exposure to visible light. The hybrid could be recycled for the antibacterial activity and is nontoxic toward human cervical cancer cells (HeLa cells). The water insoluble Ag@AgI in agarose matrix forms a good coating on quartz, having good mechanical strength. EPR and TEM studies are carried out on the Ag@AgI/agarose and the bacteria, respectively, to elucidate a possible mechanism for killing of the bacteria.

How good are the simulations of tropical SST-rainfall relationship by IPCC AR4 atmospheric and coupled models?

The failure of atmospheric general circulation models (AGCMs) forced by prescribed SST to simulate and predict the interannual variability of Indian/Asian monsoon has been widely attributed to their inability to reproduce the actual sea surface temperature (SST)-rainfall relationship in the warm Indo-Pacific oceans. This assessment is based on a comparison of the observed and simulated correlation between the rainfall and local SST. However, the observed SSTconvection/rainfall relationship is nonlinear and for this a linear measure such as the correlation is not an appropriate measure. We show that the SST-rainfall relationship simulated by atmospheric and coupled general circulation models in IPCC AR4 is nonlinear, as observed, and realistic over the tropical West Pacific (WPO) and the Indian Ocean (IO). The SST-rainfall pattern simulated by the coupled versions of these models is rather similar to that from the corresponding atmospheric one, except for a shift of the entire pattern to colder/warmer SSTs when there is a cold/warm bias in the coupled version.

On the microstructure-tensile property correlations in bulk metallic glass matrix composites with crystalline dendrites

Bulk metallic glass (BMG) matrix composites with crystalline dendrites as reinforcements exhibit a wide variance in their microstructures (and thus mechanical properties), which in turn can be attributed to the processing route employed, which affects the size and distribution of the dendrites. A critical investigation on the microstructure and tensile properties of Zr/Ti-based BMG composites of the same composition, but produced by different routes, was conducted so as to identify ``structure-property'' connections in these materials. This was accomplished by employing four different processing methods-arc melting, suction casting, semi-solid forging and induction melting on a water-cooled copper boat-on composites with two different dendrite volume fractions, V-d. The change in processing parameters only affects microstructural length scales such as the interdendritic spacing, lambda, and dendrite size, delta, whereas compositions of the matrix and dendrite are unaffected. Broadly, the composite's properties are insensitive to the microstructural length scales when V-d is high (similar to 75%), whereas they become process dependent for relatively lower V-d (similar to 55%). Larger delta in arc-melted and forged specimens result in higher ductility (7-9%) and lower hardening rates, whereas smaller dendrites increase the hardening rate. A bimodal distribution of dendrites offers excellent ductility at a marginal cost of yield strength. Finer lambda result in marked improvements in both ductility and yield strength, due to the confinement of shear band nucleation sites in smaller volumes of the glassy phase. Forging in the semi-solid state imparts such a microstructure. (c) 2012 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Recapitulating tumour microenvironment in chitosan-gelatin three-dimensional scaffolds: an improved in vitro tumour model

Owing to the reduced co-relationship between conventional flat Petri dish culture (two-dimensional) and the tumour microenvironment, there has been a shift towards three-dimensional culture systems that show an improved analogy to the same. In this work, an extracellular matrix (ECM)-mimicking three-dimensional scaffold based on chitosan and gelatin was fabricated and explored for its potential as a tumour model for lung cancer. It was demonstrated that the chitosan-gelatin (CG) scaffolds supported the formation of tumoroids that were similar to tumours grown in vivo for factors involved in tumour-cell-ECM interaction, invasion and metastasis, and response to anti-cancer drugs. On the other hand, the two-dimensional Petri dish surfaces did not demonstrate gene-expression profiles similar to tumours grown in vivo. Further, the three-dimensional CG scaffolds supported the formation of tumoroids, using other types of cancer cells such as breast, cervix and bone, indicating a possible wider potential for in vitro tumoroid generation. Overall, the results demonstrated that CG scaffolds can be an improved in vitro tool to study cancer progression and drug screening for solid tumours.

Nonlocal continuum mechanics based ultrasonic flexural wave dispersion characteristics of a monolayer graphene embedded in polymer matrix

Wave propagation in graphene sheet embedded in elastic medium (polymer matrix) has been a topic of great interest in nanomechanics of graphene sheets, where the equivalent continuum models are widely used. In this manuscript, we examined this issue by incorporating the nonlocal theory into the classical plate model. The influence of the nonlocal scale effects has been investigated in detail. The results are qualitatively different from those obtained based on the local/classical plate theory and thus, are important for the development of monolayer graphene-based nanodevices. In the present work, the graphene sheet is modeled as an isotropic plate of one-atom thick. The chemical bonds are assumed to be formed between the graphene sheet and the elastic medium. The polymer matrix is described by a Pasternak foundation model, which accounts for both normal pressure and the transverse shear deformation of the surrounding elastic medium. When the shear effects are neglected, the model reduces to Winkler foundation model. The normal pressure or Winkler elastic foundation parameter is approximated as a series of closely spaced, mutually independent, vertical linear elastic springs where the foundation modulus is assumed equivalent to stiffness of the springs. For this model, the nonlocal governing differential equations of motion are derived from the minimization of the total potential energy of the entire system. An ultrasonic type of flexural wave propagation model is also derived and the results of the wave dispersion analysis are shown for both local and nonlocal elasticity calculations. From this analysis we show that the elastic matrix highly affects the flexural wave mode and it rapidly increases the frequency band gap of flexural mode. The flexural wavenumbers obtained from nonlocal elasticity calculations are higher than the local elasticity calculations. The corresponding wave group speeds are smaller in nonlocal calculation as compared to local elasticity calculation. The effect of y-directional wavenumber (eta(q)) on the spectrum and dispersion relations of the graphene embedded in polymer matrix is also observed. We also show that the cut-off frequencies of flexural wave mode depends not only on the y-direction wavenumber but also on nonlocal scaling parameter (e(0)a). The effect of eta(q) and e(0)a on the cut-off frequency variation is also captured for the cases of with and without elastic matrix effect. For a given nanostructure, nonlocal small scale coefficient can be obtained by matching the results from molecular dynamics (MD) simulations and the nonlocal elasticity calculations. At that value of the nonlocal scale coefficient, the waves will propagate in the nanostructure at that cut-off frequency. In the present paper, different values of e(0)a are used. One can get the exact e(0)a for a given graphene sheet by matching the MD simulation results of graphene with the results presented in this article. (c) 2012 Elsevier Ltd. All rights reserved.

Relative roles of instruction count and cycles per instruction in WCET estimation

Most of the existing WCET estimation methods directly estimate execution time, ET, in cycles. We propose to study ET as a product of two factors, ET = IC * CPI, where IC is instruction count and CPI is cycles per instruction. Considering directly the estimation of ET may lead to a highly pessimistic estimate since implicitly these methods may be using worst case IC and worst case CPI. We hypothesize that there exists a functional relationship between CPI and IC such that CPI=f(IC). This is ascertained by computing the covariance matrix and studying the scatter plots of CPI versus IC. IC and CPI values are obtained by running benchmarks with a large number of inputs using the cycle accurate architectural simulator, Simplescalar on two different architectures. It is shown that the benchmarks can be grouped into different classes based on the CPI versus IC relationship. For some benchmarks like FFT, FIR etc., both IC and CPI are almost a constant irrespective of the input. There are other benchmarks that exhibit a direct or an inverse relationship between CPI and IC. In such a case, one can predict CPI for a given IC as CPI=f(IC). We derive the theoretical worst case IC for a program, denoted as SWIC, using integer linear programming(ILP) and estimate WCET as SWIC*f(SWIC). However, if CPI decreases sharply with IC then measured maximum cycles is observed to be a better estimate. For certain other benchmarks, it is observed that the CPI versus IC relationship is either random or CPI remains constant with varying IC. In such cases, WCET is estimated as the product of SWIC and measured maximum CPI. It is observed that use of the proposed method results in tighter WCET estimates than Chronos, a static WCET analyzer, for most benchmarks for the two architectures considered in this paper.

Fast acoustic likelihood computation using low-rank matrix approximation

Acoustic modeling using mixtures of multivariate Gaussians is the prevalent approach for many speech processing problems. Computing likelihoods against a large set of Gaussians is required as a part of many speech processing systems and it is the computationally dominant phase for LVCSR systems. We express the likelihood computation as a multiplication of matrices representing augmented feature vectors and Gaussian parameters. The computational gain of this approach over traditional methods is by exploiting the structure of these matrices and efficient implementation of their multiplication.In particular, we explore direct low-rank approximation of the Gaussian parameter matrix and indirect derivation of low-rank factors of the Gaussian parameter matrix by optimum approximation of the likelihood matrix. We show that both the methods lead to similar speedups but the latter leads to far lesser impact on the recognition accuracy. Experiments on a 1138 word vocabulary RM1 task using Sphinx 3.7 system show that, for a typical case the matrix multiplication approach leads to overall speedup of 46%. Both the low-rank approximation methods increase the speedup to around 60%, with the former method increasing the word error rate (WER) from 3.2% to 6.6%, while the latter increases the WER from 3.2% to 3.5%.

The Relationship of Solid-State Plasticity to Mechanochromic Luminescence in Difluoroboron Avobenzone Polymorphs

In solid-state mechanochromic luminescence (ML) materials, it remains a challenge to establish the origin of fluorescence color changes upon mechanical action and to determine why only some fluorophores exhibit ML behavior. The study of mechanical properties by nanoindentation, followed by ML experiments on green- and cyan-emitting polymorphs of difluoroboron avobenzone reveals that upon smearing, the plastically deformable cyan form shows a prominent color change to yellow, while in the harder green form the redshifted emission is barely detectable. Crystal structure analysis reveals the presence of slip planes in the softer cyan form that can facilitate the formation of recoverable and low energy defects in the structure. Hence, the cyan form exhibits prominent and reversible ML behavior. This suggests a potential design strategy for efficient ML materials.

Hybrid online non-negative matrix factorization for clustering of documents

When document corpus is very large, we often need to reduce the number of features. But it is not possible to apply conventional Non-negative Matrix Factorization(NMF) on billion by million matrix as the matrix may not fit in memory. Here we present novel Online NMF algorithm. Using Online NMF, we reduced original high-dimensional space to low-dimensional space. Then we cluster all the documents in reduced dimension using k-means algorithm. We experimentally show that by processing small subsets of documents we will be able to achieve good performance. The method proposed outperforms existing algorithms.

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.

A Guided Wave approach for the detection of damage in a structure having elements with periodic damage

A wave propagation based approach for the detection of damage in components of structures having periodic damage has been proposed. Periodic damage pattern may arise in a structure due to periodicity in geometry and in loading. The method exploits the Block-Floquet band formation mechanism, a feature specific to structures with periodicity, to identify propagation bands (pass bands) and attenuation bands (stop bands) at different frequency ranges. The presence of damage modifies the wave propagation behaviour forming these bands. With proper positioning of sensors a damage force indicator (DFI) method can be used to locate the defect at an accuracy level of sensor to sensor distance. A wide range of transducer frequency may be used to obtain further information about the shape and size of the damage. The methodology is demonstrated using a few 1-D structures with different kinds of periodicity and damage. For this purpose, dynamic stiffness matrix is formed for the periodic elements to obtain the dispersion relationship using frequency domain spectral element and spectral super element method. The sensitivity of the damage force indicator for different types of periodic damages is also analysed.

Shape-function-relationship (SFR) framework for semantic interoperability of product model

The problem of semantic interoperability arises while integrating applications in different task domains across the product life cycle. A new shape-function-relationship (SFR) framework is proposed as a taxonomy based on which an ontology is developed. Ontology based on the SFR framework, that captures explicit definition of terminology and knowledge relationships in terms of shape, function and relationship descriptors, offers an attractive approach for solving semantic interoperability issue. Since all instances of terms are based on single taxonomy with a formal classification, mapping of terms requires a simple check on the attributes used in the classification. As a preliminary study, the framework is used to develop ontology of terms used in the aero-engine domain and the ontology is used to resolve the semantic interoperability problem in the integration of design and maintenance. Since the framework allows a single term to have multiple classifications, handling context dependent usage of terms becomes possible. Automating the classification of terms and establishing the completeness of the classification scheme are being addressed presently.

Melting and solidification behavior of Pb-Sn embedded alloy nano-particles

Nano-sized bimetallic dispersoids consisting of (Pb) and beta-(Sn) phases of eutectic composition (Pb26.1Sn73.9) embedded in aluminum and Al-Cu-Fe quasicrystalline matrices have been prepared by rapid solidification processing. The two phases, face centered cubic (Pb) and body center tetragonal, beta-(Sn) solid solution co-exist in all the embedded nanoparticles at room temperature. The phases bear crystallographic orientation relationship with the matrix. In situ TEM study has been carried out for the alloy particles to study the melting and the solidification behavior. The detailed microscopic observations indicate formation of a single-phase metastable fcc (Pb) in the nano-particles prior to the melting during heating. Solidification of these particles begins with nucleation of fcc (Pb), which phase separates into fcc (Pb) and beta-(Sn) lamellae in the solid state. In situ X-ray diffraction study is carried out to obtain lattice parameter of metastable fcc (Pb) and thereby an estimate of amount of Sn dissolved in the metastable (Pb) prior to the melting. The results are discussed in terms of a metastable phase diagram between fcc Pb and fcc Sn and invoking the size effect on the metastable phase diagram. The size factor is found to play a critical role in deciding the pathway of phase transformation as well as the extension of solid solubility of Sn in fcc (Pb) in the nano-particles.