Tracking and erosion resistance of silicone rubber nanocomposites under positive and negative dc voltages

ASTM D2303 standard provides a method for evaluating the tracking and erosion resistance of polymeric insulators under ac voltages. In this paper, the above method has been extended for evaluating the performance of the insulators under dc stresses. Tests were conducted on polymeric silicone rubber (SR) insulators under positive and negative dc stresses. Micron sized Alumina trihydrate (uATH) and nano sized Alumina (nALU) were used as fillers in SR matrix to improve the resistance to tracking and erosion. Results suggest that SR composites perform better under negative dc than under positive dc voltages. Eroded mass and leakage current data support the above result. Samples with low concentration of nano alumina fillers performed on par with the samples with large loadings of uATH.

A Fast Linear Separability Test by Projection of Positive Points on Subspaces

A geometric and non parametric procedure for testing if two finite set of points are linearly separable is proposed. The Linear Separability Test is equivalent to a test that determines if a strictly positive point h > 0 exists in the range of a matrix A (related to the points in the two finite sets). The algorithm proposed in the paper iteratively checks if a strictly positive point exists in a subspace by projecting a strictly positive vector with equal co-ordinates (p), on the subspace. At the end of each iteration, the subspace is reduced to a lower dimensional subspace. The test is completed within r ≤ min(n, d + 1) steps, for both linearly separable and non separable problems (r is the rank of A, n is the number of points and d is the dimension of the space containing the points). The worst case time complexity of the algorithm is O(nr3) and space complexity of the algorithm is O(nd). A small review of some of the prominent algorithms and their time complexities is included. The worst case computational complexity of our algorithm is lower than the worst case computational complexity of Simplex, Perceptron, Support Vector Machine and Convex Hull Algorithms, if d

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.

Efficient Methods for Robust Classification Under Uncertainty in Kernel Matrices

In this paper we study the problem of designing SVM classifiers when the kernel matrix, K, is affected by uncertainty. Specifically K is modeled as a positive affine combination of given positive semi definite kernels, with the coefficients ranging in a norm-bounded uncertainty set. We treat the problem using the Robust Optimization methodology. This reduces the uncertain SVM problem into a deterministic conic quadratic problem which can be solved in principle by a polynomial time Interior Point (IP) algorithm. However, for large-scale classification problems, IP methods become intractable and one has to resort to first-order gradient type methods. The strategy we use here is to reformulate the robust counterpart of the uncertain SVM problem as a saddle point problem and employ a special gradient scheme which works directly on the convex-concave saddle function. The algorithm is a simplified version of a general scheme due to Juditski and Nemirovski (2011). It achieves an O(1/T-2) reduction of the initial error after T iterations. A comprehensive empirical study on both synthetic data and real-world protein structure data sets show that the proposed formulations achieve the desired robustness, and the saddle point based algorithm outperforms the IP method significantly.

Approximation of Spatio-Temporal Random Processes Using Tensor Decomposition

A new representation of spatio-temporal random processes is proposed in this work. In practical applications, such processes are used to model velocity fields, temperature distributions, response of vibrating systems, to name a few. Finding an efficient representation for any random process leads to encapsulation of information which makes it more convenient for a practical implementations, for instance, in a computational mechanics problem. For a single-parameter process such as spatial or temporal process, the eigenvalue decomposition of the covariance matrix leads to the well-known Karhunen-Loeve (KL) decomposition. However, for multiparameter processes such as a spatio-temporal process, the covariance function itself can be defined in multiple ways. Here the process is assumed to be measured at a finite set of spatial locations and a finite number of time instants. Then the spatial covariance matrix at different time instants are considered to define the covariance of the process. This set of square, symmetric, positive semi-definite matrices is then represented as a third-order tensor. A suitable decomposition of this tensor can identify the dominant components of the process, and these components are then used to define a closed-form representation of the process. The procedure is analogous to the KL decomposition for a single-parameter process, however, the decompositions and interpretations vary significantly. The tensor decompositions are successfully applied on (i) a heat conduction problem, (ii) a vibration problem, and (iii) a covariance function taken from the literature that was fitted to model a measured wind velocity data. It is observed that the proposed representation provides an efficient approximation to some processes. Furthermore, a comparison with KL decomposition showed that the proposed method is computationally cheaper than the KL, both in terms of computer memory and execution time.

On the Lyapunov transformation for stable matrices

The matrices studied here are positive stable (or briefly stable). These are matrices, real or complex, whose eigenvalues have positive real parts. A theorem of Lyapunov states that A is stable if and only if there exists H ˃ 0 such that AH + HA* = I. Let A be a stable matrix. Three aspects of the Lyapunov transformation L_A :H → AH + HA* are discussed.

1. Let C₁ (A) = {AH + HA* :H ≥ 0} and C₂ (A) = {H: AH+HA* ≥ 0}. The problems of determining the cones C₁(A) and C₂(A) are still unsolved. Using solvability theory for linear equations over cones it is proved that C₁(A) is the polar of C₂(A*), and it is also shown that C₁ (A) = C₁(A^-1). The inertia assumed by matrices in C₁(A) is characterized.

2. The index of dissipation of A was defined to be the maximum number of equal eigenvalues of H, where H runs through all matrices in the interior of C₂(A). Upper and lower bounds, as well as some properties of this index, are given.

3. We consider the minimal eigenvalue of the Lyapunov transform AH+HA*, where H varies over the set of all positive semi-definite matrices whose largest eigenvalue is less than or equal to one. Denote it by ψ(A). It is proved that if A is Hermitian and has eigenvalues μ₁ ≥ μ₂…≥ μ_n ˃ 0, then ψ(A) = -(μ₁-μ_n)²/(4(μ₁ + μ_n)). The value of ψ(A) is also determined in case A is a normal, stable matrix. Then ψ(A) can be expressed in terms of at most three of the eigenvalues of A. If A is an arbitrary stable matrix, then upper and lower bounds for ψ(A) are obtained.

Caracterização de Bacilos Gram-Negativos Não Fermentadores não usuais em bacteremias pelas técnicas de Matrix-Assisted Laser Desorption IonizationTime of Flight Mass Spectrometry, sequenciamento de DNA e método fenotípico convencional

Alguns Bastonetes Gram-negativos não fermentadores (BGNNF) costumam ser considerados clinicamente pouco significantes e a sua implicação em infecções é subestimada. Devido à similaridade fenotípica, mudanças taxonômicas, baixa reatividade bioquímica e limitações nos bancos de dados em sistemas comerciais, a identificação de BGNNF é frequentemente equivocada, culminando com a denominação de diferentes micro-organismos apenas como BGNNF, por falta de melhor diferenciação. O objetivo desse estudo foi avaliar, por métodos fenotípico convencional, proteômico e molecular, a identificação de BGNNF incomuns isolados em hemoculturas de pacientes atendidos em um hospital universitário no Rio de Janeiro. Foram selecionadas 78 amostras isoladas de hemoculturas caracterizadas no laboratório clinico como BGNNF para a identificação por sequenciamento dos genes 16S RNA e recA, por um conjunto amplo de testes fenotípicos manuais e por MALDI-TOF MS. Os micro-organismos predominantes na amostragem foram genotipados pela técnica de eletroforese em gel de campo pulsado (PFGE). Pelo sequenciamento do gene 16S rRNA, a maioria das amostras (n=31; 40%) foi incluída no gênero Burkholderia, seguido de Pseudomonas stutzeri (10%) e Delftia acidovorans (4%). Os demais isolados foram agrupados em 27 diferentes espécies. O sequencimento do gene recA identificou a maioria das espécies de Burkholderia como Burkholderia contaminans (n=19; 24%). Os testes fenotípicos incluíram as 31 amostras apenas no CBc e para as outras 47 amostras, a concordância com o sequenciamento do gene 16S rRNA em nível de espécie foi de 64% (n=30) e apenas em gênero a concordância foi de 17% (n=8). A análise comparativa geral da identificação por MALDI-TOF MS com o sequenciamento do gene16S rRNA mostrou que 42% (n=33) das 78 amostras foram concordantes em nível de espécie e 45% (n=35) apenas em gênero. Excluindo as amostras do CBc, houve um aumento da concordância em nível de espécie para 60%. As discordâncias parecem ser devido às diferenças nos perfis proteicos das amostras em relação às amostras-referência do banco de dados do equipamento e podem ser aprimorados com a atualização de perfis no sistema. A análise do polimorfismo genético de B. contaminans mostrou a ausência de um clone disseminado causando surto, além da provável origem ambiental das infecções. Os setores de nefrologia e hemodiálise contribuíram com maior número de pacientes com amostras positivas (5 pacientes e 9 amostras). Os grupos clonais BcoD e BcoE foram encontrados em pacientes assistidos no mesmo setor com diferença de quatro meses (BcoD, nefrologia) e 1,5 ano (BcoE, hemodilálise), entre as culturas, respectivamente. As discordâncias entre as técnicas ocorreram principalmente devido a dificuldade de identificação das espécies do CBc. Os BGNNF incomuns são de difícil caracterização independente da metodologia usada e nenhum método por si só foi capaz de identificar todas as amostras.

The nuclear matrix of Euglena gracilis (Euglenophyta): A stage of nuclear matrix evolution?

Euglena gracilis cell was extracted sequentially with CSK-Triton buffer, RSB-Magik solution and DNase-As solution. DGD embedment-free electron microscopy showed that in the extracted nucleus there was a residual non-chromatin fibrous network. That it could not be removed by hot trichloroacetic acid further supported the idea that it was a non-histone, non-chromatin fibrous protein network, and should be the internal network of the nuclear matrix. After the sequential extraction, the nuclear membrane was removed, leaving behind a layer of lamina; the chromatin was digested and eluted from the dense chromosomes and residual chromosomal structures that should be chromosomal scaffold were revealed. Western blot analysis with antiserum against rat lamins showed that nuclear lamina of the cell possessed two positive polypeptides, a major one and a minor one, which had molecular masses similar to lamin B and lamin A, respectively. Comparing these data with those of the most primitive eukaryote Archezoa and of higher eukaryotes, it was suggested that the lower unicellular eukaryote E. gracillis already had the nuclear matrix structure, and its nuclear matrix (especially the lamina) might represent a stage of evolutionary history of the nuclear matrix. (C) 2000 Editions scientifiques et medicales Elsevier SAS.

Low-rank optimization for distance matrix completion

This paper addresses the problem of low-rank distance matrix completion. This problem amounts to recover the missing entries of a distance matrix when the dimension of the data embedding space is possibly unknown but small compared to the number of considered data points. The focus is on high-dimensional problems. We recast the considered problem into an optimization problem over the set of low-rank positive semidefinite matrices and propose two efficient algorithms for low-rank distance matrix completion. In addition, we propose a strategy to determine the dimension of the embedding space. The resulting algorithms scale to high-dimensional problems and monotonically converge to a global solution of the problem. Finally, numerical experiments illustrate the good performance of the proposed algorithms on benchmarks. © 2011 IEEE.

Riemannian metric and geometric mean for positive semidefinite matrices of fixed rank

This paper introduces a new metric and mean on the set of positive semidefinite matrices of fixed-rank. The proposed metric is derived from a well-chosen Riemannian quotient geometry that generalizes the reductive geometry of the positive cone and the associated natural metric. The resulting Riemannian space has strong geometrical properties: it is geodesically complete, and the metric is invariant with respect to all transformations that preserve angles (orthogonal transformations, scalings, and pseudoinversion). A meaningful approximation of the associated Riemannian distance is proposed, that can be efficiently numerically computed via a simple algorithm based on SVD. The induced mean preserves the rank, possesses the most desirable characteristics of a geometric mean, and is easy to compute. © 2009 Society for Industrial and Applied Mathematics.

Fixed-rank matrix factorizations and Riemannian low-rank optimization

Motivated by the problem of learning a linear regression model whose parameter is a large fixed-rank non-symmetric matrix, we consider the optimization of a smooth cost function defined on the set of fixed-rank matrices. We adopt the geometric framework of optimization on Riemannian quotient manifolds. We study the underlying geometries of several well-known fixed-rank matrix factorizations and then exploit the Riemannian quotient geometry of the search space in the design of a class of gradient descent and trust-region algorithms. The proposed algorithms generalize our previous results on fixed-rank symmetric positive semidefinite matrices, apply to a broad range of applications, scale to high-dimensional problems, and confer a geometric basis to recent contributions on the learning of fixed-rank non-symmetric matrices. We make connections with existing algorithms in the context of low-rank matrix completion and discuss the usefulness of the proposed framework. Numerical experiments suggest that the proposed algorithms compete with state-of-the-art algorithms and that manifold optimization offers an effective and versatile framework for the design of machine learning algorithms that learn a fixed-rank matrix. © 2013 Springer-Verlag Berlin Heidelberg.

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometric analysis of phospholipase A(2) and fibrinolytic enzyme, two enzymes obtained from Chinese Agkistrodon blomhoffii Ussurensis venom

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOFMS) was used to analyze two enzymes, phospholipase AZ and fibrinolytic enzyme isolated from Chinese Agkistrodon blomhoffii Ussurensis venom. Using sinapinic acid as the matrix, positive ion mass spectra of the enzymes were obtained, In addition to the dominant protein [M+H](+) ions, multimeric and multiply charged ions were also observed in the mass spectra, The higher the concentration of the enzymes, the more multiply charged polymer and multimeric ions were detected, Our results indicate that MALDI-TOFMS can provide a rapid and accurate method for molecular weight determination of snake venom enzymes, Mass accuracies of 0.1 and 0.3 % were achieved by analysis of highly dialyzed phospholipase A2 and fibrinolytic enzyme, and these results are much better than those obtained using sodium dodecyl sulfate-palyacrylamide gel electrophoresis. MALDI-TOFMS thus provides a reliable method to determine the purity and molecular weight of these enzymes, which are of potential use as therapeutants, Copyright (C) 1999 John Wiley & Sons, Ltd.

Studies on extracting solutions of endohedral rare-earth metallofullerenes by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

Thirteen extracting solutions of rare-earth metallofullerenes containing La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm and Yb respectively have been investigated by means of matrix-assisted laser desorption/ionization time-of-night, mass spectrometry. The influences of the positive-ion/negative-ion mode, laser intensity, matrix and mass discrimination to the analytical results are studied, based on which the optimal analytical conditions have been determined. The results show that the extracting solutions contain large quantities of rare-earth metallofullerenes brs;des empty fullerenes, On the basis of comparing their relative intensities, the different structure stabilities and solubilities of metallofullerenes with different rare-earth metals encapsulated into the fullerene cages, as well as some possible reasons to those differences, are discussed.

Seasonal and spatial distribution of matrix-bound phosphine and its relationship with the environment in the Changjiang River Estuary, China

Sediment is commonly considered as a source of phosphine, which is a highly toxic and reactive atmospheric trace gas. This study aims to investigate the seasonal and spatial distribution of matrix-bound phosphine (MBP) and its relationship with the environment in the Changjiang River Estuary. A total of 43 surface sediments were collected in four seasons of 2006, and concentrations of MBP and relative environmental factors were analyzed. MBP ranged from 1.93 to 94.86 ng kg(-1) dry weight (dw) with an average concentration of 17.14 ng kg(-1) dw. The concentrations of MBP in the tipper estuary were, higher than those in the lower estuary, which could be attributed to greater pollutant inputs in the upper estuary. The concentrations of MBP also varied with season, with November > August > May > February. Significant correlations existed between MBP and total phosphorus (TP), organic phosphorus (OP), inorganic phosphorus (W), organic carbon (OC), total nitrogen (TN), the grain size, and redox potential (Eh), suggesting that these sedimentary environmental characteristics played an important role in controlling the MBP levels in the sediments. Notably, there were positive linear relationships between the concentrations of soluble reactive phosphorus (SRP), TP, and chlorophyll a (Chl a) in bottom water and MBP in sediments. These relationships might be very complicated and need further exploration. This work is the first comprehensive study of the seasonal and spatial distribution of MBP in sediments and its relationships with environmental factors in a typical estuary, and will lead to deeper understanding of the phosphorus (P) biogeochemical cycle. (C) 2008 Elsevier Ltd. All rights reserved.

A probabilistic index for completely positive maps and an application

Gohm, Rolf, (2003) 'A probabilistic index for completely positive maps and an application', Journal of Operator Theory 54(2) pp.339-361 RAE2008