Matrix-vector multiplication and triangular linear solver using GPGPU for symmetric positive definite matrices derived from elliptic equations

The modern GPUs are well suited for intensive computational tasks and massive parallel computation. Sparse matrix multiplication and linear triangular solver are the most important and heavily used kernels in scientific computation, and several challenges in developing a high performance kernel with the two modules is investigated. The main interest it to solve linear systems derived from the elliptic equations with triangular elements. The resulting linear system has a symmetric positive definite matrix. The sparse matrix is stored in the compressed sparse row (CSR) format. It is proposed a CUDA algorithm to execute the matrix vector multiplication using directly the CSR format. A dependence tree algorithm is used to determine which variables the linear triangular solver can determine in parallel. To increase the number of the parallel threads, a coloring graph algorithm is implemented to reorder the mesh numbering in a pre-processing phase. The proposed method is compared with parallel and serial available libraries. The results show that the proposed method improves the computation cost of the matrix vector multiplication. The pre-processing associated with the triangular solver needs to be executed just once in the proposed method. The conjugate gradient method was implemented and showed similar convergence rate for all the compared methods. The proposed method showed significant smaller execution time.

Characterization and properties of blended cement matrices containing activated bamboo leaf wastes

The worldwide production of bamboo generates large volumes of leaf wastes, which are deposited in landfills or burned in an uncontrolled manner, with negative effects in the environment. The ash obtained by calcining of the bamboo leaf waste, shows good qualities as supplementary cementing material for the production of blended cements. The current paper shows a detailed scientific study of a Brazilian bamboo leaf ash (BLA) calcined at 600 degrees C in small scale condition, by using different techniques (XRF, XRD, SEM/EDX, FT-IR, TG/DTG) and technical study in order. to analyse the behaviour of this ash in blended cements elaborated with 10% and 20% by mass of BLA. The results stated that this ash shows a very high pozzolanic activity, with a reaction rate constant K of the order of 10(-1)/h and type I CSH gel was the main hydrated phase obtained from pozzolanic reaction. The BLA blended cements (10% and 20%) complied with the physical and mechanical requirements of the existing European standards. (c) 2012 Elsevier Ltd. All rights reserved.

Anderson-like Transition for a Class of Random Sparse Models in d >= 2 Dimensions

We show that the Kronecker sum of d >= 2 copies of a random one-dimensional sparse model displays a spectral transition of the type predicted by Anderson, from absolutely continuous around the center of the band to pure point around the boundaries. Possible applications to physics and open problems are discussed briefly.

Influence of the type of phospholipid head and of the conformation of the polyelectrolyte on the growth of calcium carbonate thin films on LB/LbL matrices

Calcium carbonate is one of the most important biominerals, and it is the main constituent of pearls, seashells, and teeth. The in vitro crystallization of calcium carbonate using different organic matrices as templates has been reported. In this work, the growth of calcium carbonate thin films on special organic matrices consisting of layer-by-layer (LbL) polyelectrolyte films deposited on a pre-formed phospholipid Langmuir-Blodgett (LB) film has been studied. Two types of randomly coiled polyelectrolytes have been used: lambda-carrageenan and poly(acrylic acid). A precoating comprised of LB films has been prepared by employing a negatively charged phospholipid, the sodium salt of dimyristoilphosphatidyl acid (DMPA), or a zwitterionic phospholipid, namely dimyristoilphosphatidylethanolamine (DMPE). This approach resulted in the formation of particulate calcium carbonate continuous films with different morphologies, particle sizes, and roughness, as revealed by scanning electron microscopy (SEM) and atomic force microscopy (AFM). The crystalline structure of the calcium carbonate particles was analyzed by Raman spectroscopy. The randomly coiled conformation of the polyelectrolytes seems to be the main reason for the formation of continuous films rather than CaCO3 isolated crystals. (C) 2012 Elsevier B.V. All rights reserved.

Miniversal deformations of matrices of bilinear forms

Arnold [V.I. Arnold, On matrices depending on parameters, Russian Math. Surveys 26 (2) (1971) 29-43] constructed miniversal deformations of square complex matrices under similarity; that is, a simple normal form to which not only a given square matrix A but all matrices B close to it can be reduced by similarity transformations that smoothly depend on the entries of B. We construct miniversal deformations of matrices under congruence. (C) 2011 Elsevier Inc. All rights reserved.

Workplace drug testing, different matrices different objectives

Drug testing is used by employers to detect drug use by employees or job candidates. It can identify recent use of alcohol, prescription drugs, and illicit drugs as a screening tool for potential health and safety and performance issues. Urine is the most commonly used sample for illicit drugs. It detects the use of a drug within the last few days and as such is evidence of recent use; but a positive test does not necessarily mean that the individual was impaired at the time of the test. Abstention from use for three days will often produce a negative test result. Analysis of hair provides a much longer window of detection, typically 1 to 3 months. Hence the likelihood of a falsely negative test using hair is very much less than with a urine test. Conversely, a negative hair test is a substantially stronger indicator of a non-drug user than a negative urine test. Oral fluid (saliva) is also easy to collect. Drugs remain in oral fluid for a similar time as in blood. The method is a good way of detecting current use and is more likely to reflect current impairment. It offers promise as a test in post-accident, for cause, and on-duty situations. Studies have shown that within the same industrial settings, hair testing can detect twice as many drug users as urine testing. Copyright (C) 2012 John Wiley & Sons, Ltd.

Asymptotic integral kernel for ensembles of random normal matrices with radial potentials

The method of steepest descent is used to study the integral kernel of a family of normal random matrix ensembles with eigenvalue distribution P-N (z(1), ... , z(N)) = Z(N)(-1)e(-N)Sigma(N)(i=1) V-alpha(z(i)) Pi(1 <= i<j <= N) vertical bar z(i) - z(j)vertical bar(2), where V-alpha(z) = vertical bar z vertical bar(alpha), z epsilon C and alpha epsilon inverted left perpendicular0, infinity inverted right perpendicular. Asymptotic formulas with error estimate on sectors are obtained. A corollary of these expansions is a scaling limit for the n-point function in terms of the integral kernel for the classical Segal-Bargmann space. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.3688293]

Composites from a forest biorefinery byproduct and agrofibers: Lignosulfonate-phenolic type matrices reinforced with sisal fibers

The replacement of phenol with sodium lignosulfonate and formaldehyde with glutaraldehyde in the preparation of resins resulted in a new resol-type phenolic resin, sodium lignosulfonate-glutaraldehyde resin, in addition to sodium lignosulfonate-formaldehyde and phenol-formaldehyde resins. These resins were then used to prepare thermosets and composites reinforced with sisal fibers. Different techniques were used to characterize raw materials and/or thermosets and composites, including inverse gas chromatography, thermogravimetric analysis, and mechanical impact and flexural tests. The substitution of phenol by sodium lignosulfonate in the formulation of the composite matrices increased the impact strength of the respective composites from approximately 400 Jm(-1) to 800 J m(-1) and 1000 J m(-1), showing a considerable enhancement from the replacement of phenol with sodium lignosulfonate. The wettability of the sisal fibers increased when the resins were prepared from sodium lignosulfonate, generating composites in which the adhesion at the fiber-matrix interface was stronger and favored the transference of load from the matrix to the fiber during impact. Results suggested that the composites experienced a different mechanism of load transfer from the matrix to the fiber when a bending load was applied, compared to that experienced during impact. The thermogravimetric analysis results demonstrated that the thermal stability of the composites was not affected by the use of sodium lignosulfonate as a phenolic-type reagent during the preparation of the matrices.

IDM - A New Parallel Methodology to Calculate the Determinant of Matrices of the Order n, with Computational Complexity O(n)

This paper presents a new parallel methodology for calculating the determinant of matrices of the order n, with computational complexity O(n), using the Gauss-Jordan Elimination Method and Chio's Rule as references. We intend to present our step-by-step methodology using clear mathematical language, where we will demonstrate how to calculate the determinant of a matrix of the order n in an analytical format. We will also present a computational model with one sequential algorithm and one parallel algorithm using a pseudo-code.

Modeling gene expression regulatory networks with the sparse vector autoregressive model

Abstract Background To understand the molecular mechanisms underlying important biological processes, a detailed description of the gene products networks involved is required. In order to define and understand such molecular networks, some statistical methods are proposed in the literature to estimate gene regulatory networks from time-series microarray data. However, several problems still need to be overcome. Firstly, information flow need to be inferred, in addition to the correlation between genes. Secondly, we usually try to identify large networks from a large number of genes (parameters) originating from a smaller number of microarray experiments (samples). Due to this situation, which is rather frequent in Bioinformatics, it is difficult to perform statistical tests using methods that model large gene-gene networks. In addition, most of the models are based on dimension reduction using clustering techniques, therefore, the resulting network is not a gene-gene network but a module-module network. Here, we present the Sparse Vector Autoregressive model as a solution to these problems. Results We have applied the Sparse Vector Autoregressive model to estimate gene regulatory networks based on gene expression profiles obtained from time-series microarray experiments. Through extensive simulations, by applying the SVAR method to artificial regulatory networks, we show that SVAR can infer true positive edges even under conditions in which the number of samples is smaller than the number of genes. Moreover, it is possible to control for false positives, a significant advantage when compared to other methods described in the literature, which are based on ranks or score functions. By applying SVAR to actual HeLa cell cycle gene expression data, we were able to identify well known transcription factor targets. Conclusion The proposed SVAR method is able to model gene regulatory networks in frequent situations in which the number of samples is lower than the number of genes, making it possible to naturally infer partial Granger causalities without any a priori information. In addition, we present a statistical test to control the false discovery rate, which was not previously possible using other gene regulatory network models.

Femtosecond laser processing of glassy and polymeric matrices containing metals and semiconductor nanostructures

Tailoring properties of materials by femtosecond laser processing has been proposed in the last decade as a powerful approach for technological applications, ranging from optics to biology. Although most of the research output in this field is related to femtosecond laser processing of single either organic or inorganic materials, more recently a similar approach has been proposed to develop advanced hybrid nanomaterials. Here, we report results on the use of femtosecond lasers to process hybrid nanomaterials, composed of polymeric and glassy matrices containing metal or semiconductor nanostructures. We present results on the use of femtosecond pulses to induce Cu and Ag nanoparticles in the bulk of borate and borosilicate glasses, which can be applied for a new generation of waveguides. We also report on 3D polymeric structures, fabricated by two-photon polymerization, containing Au and ZnO nanostructures, with intense two-photon fluorescent properties. The approach based on femtosecond laser processing to fabricate hybrid materials containing metal or semiconductor nanostructures is promising to be exploited for optical sensors and photonics devices.