Estimating gene function with least squares nonnegative matrix factorization.

PubMed

Wang, Guoli; Ochs, Michael F

2007-01-01

Nonnegative matrix factorization is a machine learning algorithm that has extracted information from data in a number of fields, including imaging and spectral analysis, text mining, and microarray data analysis. One limitation with the method for linking genes through microarray data in order to estimate gene function is the high variance observed in transcription levels between different genes. Least squares nonnegative matrix factorization uses estimates of the uncertainties on the mRNA levels for each gene in each condition, to guide the algorithm to a local minimum in normalized chi2, rather than a Euclidean distance or divergence between the reconstructed data and the data itself. Herein, application of this method to microarray data is demonstrated in order to predict gene function.

Sparse non-negative matrix factorizations via alternating non-negativity-constrained least squares for microarray data analysis.

PubMed

Kim, Hyunsoo; Park, Haesun

2007-06-15

Many practical pattern recognition problems require non-negativity constraints. For example, pixels in digital images and chemical concentrations in bioinformatics are non-negative. Sparse non-negative matrix factorizations (NMFs) are useful when the degree of sparseness in the non-negative basis matrix or the non-negative coefficient matrix in an NMF needs to be controlled in approximating high-dimensional data in a lower dimensional space. In this article, we introduce a novel formulation of sparse NMF and show how the new formulation leads to a convergent sparse NMF algorithm via alternating non-negativity-constrained least squares. We apply our sparse NMF algorithm to cancer-class discovery and gene expression data analysis and offer biological analysis of the results obtained. Our experimental results illustrate that the proposed sparse NMF algorithm often achieves better clustering performance with shorter computing time compared to other existing NMF algorithms. The software is available as supplementary material.

Trust in Leadership DEOCS 4.1 Construct Validity Summary

DTIC Science & Technology

2017-08-01

Item Corrected Item- Total Correlation Cronbach’s Alpha if Item Deleted Four-point Scale Items I can depend on my immediate supervisor to meet...1974) were used to assess the fit between the data and the factor. The BTS hypothesizes that the correlation matrix is an identity matrix. The...to reject the null hypothesis that the correlation matrix is an identity, and to conclude that the factor analysis is an appropriate method to

University Organization. A Matrix Analysis of the Academic Professions.

ERIC Educational Resources Information Center

Bess, James L.

Using the latest research instruments, including questionnaires, interviews, factor analysis, and matrix construction, the present restraints on professorial effectiveness and the contributions of departmental and university structures to professorial malaise is examined for the purpose of improving ways that administrators can increase faculty…

The Incremental Multiresolution Matrix Factorization Algorithm

PubMed Central

Ithapu, Vamsi K.; Kondor, Risi; Johnson, Sterling C.; Singh, Vikas

2017-01-01

Multiresolution analysis and matrix factorization are foundational tools in computer vision. In this work, we study the interface between these two distinct topics and obtain techniques to uncover hierarchical block structure in symmetric matrices – an important aspect in the success of many vision problems. Our new algorithm, the incremental multiresolution matrix factorization, uncovers such structure one feature at a time, and hence scales well to large matrices. We describe how this multiscale analysis goes much farther than what a direct “global” factorization of the data can identify. We evaluate the efficacy of the resulting factorizations for relative leveraging within regression tasks using medical imaging data. We also use the factorization on representations learned by popular deep networks, providing evidence of their ability to infer semantic relationships even when they are not explicitly trained to do so. We show that this algorithm can be used as an exploratory tool to improve the network architecture, and within numerous other settings in vision. PMID:29416293

Technique for information retrieval using enhanced latent semantic analysis generating rank approximation matrix by factorizing the weighted morpheme-by-document matrix

DOEpatents

Chew, Peter A; Bader, Brett W

2012-10-16

A technique for information retrieval includes parsing a corpus to identify a number of wordform instances within each document of the corpus. A weighted morpheme-by-document matrix is generated based at least in part on the number of wordform instances within each document of the corpus and based at least in part on a weighting function. The weighted morpheme-by-document matrix separately enumerates instances of stems and affixes. Additionally or alternatively, a term-by-term alignment matrix may be generated based at least in part on the number of wordform instances within each document of the corpus. At least one lower rank approximation matrix is generated by factorizing the weighted morpheme-by-document matrix and/or the term-by-term alignment matrix.

Text mining factor analysis (TFA) in green tea patent data

NASA Astrophysics Data System (ADS)

Rahmawati, Sela; Suprijadi, Jadi; Zulhanif

2017-03-01

Factor analysis has become one of the most widely used multivariate statistical procedures in applied research endeavors across a multitude of domains. There are two main types of analyses based on factor analysis: Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA). Both EFA and CFA aim to observed relationships among a group of indicators with a latent variable, but they differ fundamentally, a priori and restrictions made to the factor model. This method will be applied to patent data technology sector green tea to determine the development technology of green tea in the world. Patent analysis is useful in identifying the future technological trends in a specific field of technology. Database patent are obtained from agency European Patent Organization (EPO). In this paper, CFA model will be applied to the nominal data, which obtain from the presence absence matrix. While doing processing, analysis CFA for nominal data analysis was based on Tetrachoric matrix. Meanwhile, EFA model will be applied on a title from sector technology dominant. Title will be pre-processing first using text mining analysis.

Boundary formulations for sensitivity analysis without matrix derivatives

NASA Technical Reports Server (NTRS)

Kane, J. H.; Guru Prasad, K.

1993-01-01

A new hybrid approach to continuum structural shape sensitivity analysis employing boundary element analysis (BEA) is presented. The approach uses iterative reanalysis to obviate the need to factor perturbed matrices in the determination of surface displacement and traction sensitivities via a univariate perturbation/finite difference (UPFD) step. The UPFD approach makes it possible to immediately reuse existing subroutines for computation of BEA matrix coefficients in the design sensitivity analysis process. The reanalysis technique computes economical response of univariately perturbed models without factoring perturbed matrices. The approach provides substantial computational economy without the burden of a large-scale reprogramming effort.

Low-dimensional Representation of Error Covariance

NASA Technical Reports Server (NTRS)

Tippett, Michael K.; Cohn, Stephen E.; Todling, Ricardo; Marchesin, Dan

2000-01-01

Ensemble and reduced-rank approaches to prediction and assimilation rely on low-dimensional approximations of the estimation error covariances. Here stability properties of the forecast/analysis cycle for linear, time-independent systems are used to identify factors that cause the steady-state analysis error covariance to admit a low-dimensional representation. A useful measure of forecast/analysis cycle stability is the bound matrix, a function of the dynamics, observation operator and assimilation method. Upper and lower estimates for the steady-state analysis error covariance matrix eigenvalues are derived from the bound matrix. The estimates generalize to time-dependent systems. If much of the steady-state analysis error variance is due to a few dominant modes, the leading eigenvectors of the bound matrix approximate those of the steady-state analysis error covariance matrix. The analytical results are illustrated in two numerical examples where the Kalman filter is carried to steady state. The first example uses the dynamics of a generalized advection equation exhibiting nonmodal transient growth. Failure to observe growing modes leads to increased steady-state analysis error variances. Leading eigenvectors of the steady-state analysis error covariance matrix are well approximated by leading eigenvectors of the bound matrix. The second example uses the dynamics of a damped baroclinic wave model. The leading eigenvectors of a lowest-order approximation of the bound matrix are shown to approximate well the leading eigenvectors of the steady-state analysis error covariance matrix.

In Spite of Indeterminacy Many Common Factor Score Estimates Yield an Identical Reproduced Covariance Matrix

ERIC Educational Resources Information Center

Beauducel, Andre

2007-01-01

It was investigated whether commonly used factor score estimates lead to the same reproduced covariance matrix of observed variables. This was achieved by means of Schonemann and Steiger's (1976) regression component analysis, since it is possible to compute the reproduced covariance matrices of the regression components corresponding to different…

Massive data compression for parameter-dependent covariance matrices

NASA Astrophysics Data System (ADS)

Heavens, Alan F.; Sellentin, Elena; de Mijolla, Damien; Vianello, Alvise

2017-12-01

We show how the massive data compression algorithm MOPED can be used to reduce, by orders of magnitude, the number of simulated data sets which are required to estimate the covariance matrix required for the analysis of Gaussian-distributed data. This is relevant when the covariance matrix cannot be calculated directly. The compression is especially valuable when the covariance matrix varies with the model parameters. In this case, it may be prohibitively expensive to run enough simulations to estimate the full covariance matrix throughout the parameter space. This compression may be particularly valuable for the next generation of weak lensing surveys, such as proposed for Euclid and Large Synoptic Survey Telescope, for which the number of summary data (such as band power or shear correlation estimates) is very large, ∼104, due to the large number of tomographic redshift bins which the data will be divided into. In the pessimistic case where the covariance matrix is estimated separately for all points in an Monte Carlo Markov Chain analysis, this may require an unfeasible 109 simulations. We show here that MOPED can reduce this number by a factor of 1000, or a factor of ∼106 if some regularity in the covariance matrix is assumed, reducing the number of simulations required to a manageable 103, making an otherwise intractable analysis feasible.

Pattern identification in time-course gene expression data with the CoGAPS matrix factorization.

PubMed

Fertig, Elana J; Stein-O'Brien, Genevieve; Jaffe, Andrew; Colantuoni, Carlo

2014-01-01

Patterns in time-course gene expression data can represent the biological processes that are active over the measured time period. However, the orthogonality constraint in standard pattern-finding algorithms, including notably principal components analysis (PCA), confounds expression changes resulting from simultaneous, non-orthogonal biological processes. Previously, we have shown that Markov chain Monte Carlo nonnegative matrix factorization algorithms are particularly adept at distinguishing such concurrent patterns. One such matrix factorization is implemented in the software package CoGAPS. We describe the application of this software and several technical considerations for identification of age-related patterns in a public, prefrontal cortex gene expression dataset.

Apparatus and system for multivariate spectral analysis

DOEpatents

Keenan, Michael R.; Kotula, Paul G.

2003-06-24

An apparatus and system for determining the properties of a sample from measured spectral data collected from the sample by performing a method of multivariate spectral analysis. The method can include: generating a two-dimensional matrix A containing measured spectral data; providing a weighted spectral data matrix D by performing a weighting operation on matrix A; factoring D into the product of two matrices, C and S.sup.T, by performing a constrained alternating least-squares analysis of D=CS.sup.T, where C is a concentration intensity matrix and S is a spectral shapes matrix; unweighting C and S by applying the inverse of the weighting used previously; and determining the properties of the sample by inspecting C and S. This method can be used by a spectrum analyzer to process X-ray spectral data generated by a spectral analysis system that can include a Scanning Electron Microscope (SEM) with an Energy Dispersive Detector and Pulse Height Analyzer.

The School Counseling Program Implementation Survey: Initial Instrument Development and Exploratory Factor Analysis

ERIC Educational Resources Information Center

Clemens, Elysia V.; Carey, John C.; Harrington, Karen M.

2010-01-01

This article details the initial development of the School Counseling Program Implementation Survey and psychometric results including reliability and factor structure. An exploratory factor analysis revealed a three-factor model that accounted for 54% of the variance of the intercorrelation matrix and a two-factor model that accounted for 47% of…

On the Extraction of Components and the Applicability of the Factor Model.

ERIC Educational Resources Information Center

Dziuban, Charles D.; Harris, Chester W.

A reanalysis of Shaycroft's matrix of intercorrelations of 10 test variables plus 4 random variables is discussed. Three different procedures were used in the reanalysis: (1) Image Component Analysis, (2) Uniqueness Rescaling Factor Analysis, and (3) Alpha Factor Analysis. The results of these analyses are presented in tables. It is concluded from…

Constrained low-rank matrix estimation: phase transitions, approximate message passing and applications

NASA Astrophysics Data System (ADS)

Lesieur, Thibault; Krzakala, Florent; Zdeborová, Lenka

2017-07-01

This article is an extended version of previous work of Lesieur et al (2015 IEEE Int. Symp. on Information Theory Proc. pp 1635-9 and 2015 53rd Annual Allerton Conf. on Communication, Control and Computing (IEEE) pp 680-7) on low-rank matrix estimation in the presence of constraints on the factors into which the matrix is factorized. Low-rank matrix factorization is one of the basic methods used in data analysis for unsupervised learning of relevant features and other types of dimensionality reduction. We present a framework to study the constrained low-rank matrix estimation for a general prior on the factors, and a general output channel through which the matrix is observed. We draw a parallel with the study of vector-spin glass models—presenting a unifying way to study a number of problems considered previously in separate statistical physics works. We present a number of applications for the problem in data analysis. We derive in detail a general form of the low-rank approximate message passing (Low-RAMP) algorithm, that is known in statistical physics as the TAP equations. We thus unify the derivation of the TAP equations for models as different as the Sherrington-Kirkpatrick model, the restricted Boltzmann machine, the Hopfield model or vector (xy, Heisenberg and other) spin glasses. The state evolution of the Low-RAMP algorithm is also derived, and is equivalent to the replica symmetric solution for the large class of vector-spin glass models. In the section devoted to result we study in detail phase diagrams and phase transitions for the Bayes-optimal inference in low-rank matrix estimation. We present a typology of phase transitions and their relation to performance of algorithms such as the Low-RAMP or commonly used spectral methods.

Method of multivariate spectral analysis

DOEpatents

Keenan, Michael R.; Kotula, Paul G.

2004-01-06

A method of determining the properties of a sample from measured spectral data collected from the sample by performing a multivariate spectral analysis. The method can include: generating a two-dimensional matrix A containing measured spectral data; providing a weighted spectral data matrix D by performing a weighting operation on matrix A; factoring D into the product of two matrices, C and S.sup.T, by performing a constrained alternating least-squares analysis of D=CS.sup.T, where C is a concentration intensity matrix and S is a spectral shapes matrix; unweighting C and S by applying the inverse of the weighting used previously; and determining the properties of the sample by inspecting C and S. This method can be used to analyze X-ray spectral data generated by operating a Scanning Electron Microscope (SEM) with an attached Energy Dispersive Spectrometer (EDS).

A tight and explicit representation of Q in sparse QR factorization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ng, E.G.; Peyton, B.W.

1992-05-01

In QR factorization of a sparse m{times}n matrix A (m {ge} n) the orthogonal factor Q is often stored implicitly as a lower trapezoidal matrix H known as the Householder matrix. This paper presents a simple characterization of the row structure of Q, which could be used as the basis for a sparse data structure that can store Q explicitly. The new characterization is a simple extension of a well known row-oriented characterization of the structure of H. Hare, Johnson, Olesky, and van den Driessche have recently provided a complete sparsity analysis of the QR factorization. Let U be themore » matrix consisting of the first n columns of Q. Using results from, we show that the data structures for H and U resulting from our characterizations are tight when A is a strong Hall matrix. We also show that H and the lower trapezoidal part of U have the same sparsity characterization when A is strong Hall. We then show that this characterization can be extended to any weak Hall matrix that has been permuted into block upper triangular form. Finally, we show that permuting to block triangular form never increases the fill incurred during the factorization.« less

A Note on Procrustean Rotation in Exploratory Factor Analysis: A Computer Intensive Approach to Goodness-of-Fit Evaluation.

ERIC Educational Resources Information Center

Raykov, Tenko; Little, Todd D.

1999-01-01

Describes a method for evaluating results of Procrustean rotation to a target factor pattern matrix in exploratory factor analysis. The approach, based on the bootstrap method, yields empirical approximations of the sampling distributions of: (1) differences between target elements and rotated factor pattern matrices; and (2) the overall…

Analysis on the hot spot and trend of the foreign assembly building research

NASA Astrophysics Data System (ADS)

Bi, Xiaoqing; Luo, Yanbing

2017-03-01

First of all, the paper analyzes the research on the front of the assembly building in the past 15 years. This article mainly adopts the method of CO word analysis, construct the co word matrix, correlation matrix, and then into a dissimilarity matrix, and on this basis, using factor analysis, cluster analysis and multi scale analysis method to study the structure of prefabricated construction field display. Finally, the results of the analysis are discussed, and summarized the current research focus of foreign prefabricated construction mainly concentrated in 7 aspects: embankment construction, wood construction, bridge construction, crane layout, PCM wall and glass system, based on neural network test, energy saving and recycling, and forecast the future trend of development study.

Analysis Matrix of Resilience in the Face of Disability, Old Age and Poverty

ERIC Educational Resources Information Center

Cardenas, Andrea; Lopez, Lucero

2010-01-01

The purpose of this article is to describe the process of the development of the "Resilience Theoretical Analysis Matrix" (RTAM) (or in its Spanish translation: MATR), a tool designed to facilitate a coherent and organised approach to the assessment of a wide spectrum of factors influencing the development of resilience in the face of disability,…

Inductively Coupled Plasma Optical Emission Spectrometry for Rare Earth Elements Analysis

NASA Astrophysics Data System (ADS)

He, Man; Hu, Bin; Chen, Beibei; Jiang, Zucheng

2017-01-01

Inductively coupled plasma optical emission spectrometry (ICP-OES) merits multielements capability, high sensitivity, good reproducibility, low matrix effect and wide dynamic linear range for rare earth elements (REEs) analysis. But the spectral interference in trace REEs analysis by ICP-OES is a serious problem due to the complicated emission spectra of REEs, which demands some correction technology including interference factor method, derivative spectrum, Kalman filtering algorithm and partial least-squares (PLS) method. Matrix-matching calibration, internal standard, correction factor and sample dilution are usually employed to overcome or decrease the matrix effect. Coupled with various sample introduction techniques, the analytical performance of ICP-OES for REEs analysis would be improved. Compared with conventional pneumatic nebulization (PN), acid effect and matrix effect are decreased to some extent in flow injection ICP-OES, with higher tolerable matrix concentration and better reproducibility. By using electrothermal vaporization as sample introduction system, direct analysis of solid samples by ICP-OES is achieved and the vaporization behavior of refractory REEs with high boiling point, which can easily form involatile carbides in the graphite tube, could be improved by using chemical modifier, such as polytetrafluoroethylene and 1-phenyl-3-methyl-4-benzoyl-5-pyrazone. Laser ablation-ICP-OES is suitable for the analysis of both conductive and nonconductive solid samples, with the absolute detection limit of ng-pg level and extremely low sample consumption (0.2 % of that in conventional PN introduction). ICP-OES has been extensively employed for trace REEs analysis in high-purity materials, and environmental and biological samples.

Matrix analysis and risk management to avert depression and suicide among workers

PubMed Central

2010-01-01

Suicide is among the most tragic outcomes of all mental disorders, and the prevalence of suicide has risen dramatically during the last decade, particularly among workers. This paper reviews and proposes strategies to avert suicide and depression with regard to the mind body medicine equation hypothesis, metrics analysis of mental health problems from a public health and clinical medicine view. In occupational fields, the mind body medicine hypothesis has to deal with working environment, working condition, and workers' health. These three factors chosen in this paper were based on the concept of risk control, called San-kanri, which has traditionally been used in Japanese companies, and the causation concepts of host, agent, and environment. Working environment and working condition were given special focus with regard to tackling suicide problems. Matrix analysis was conducted by dividing the problem of working conditions into nine cells: three prevention levels (primary, secondary, and tertiary) were proposed for each of the three factors of the mind body medicine hypothesis (working environment, working condition, and workers' health). After using these main strategies (mind body medicine analysis and matrix analysis) to tackle suicide problems, the paper talks about the versatility of case-method teaching, "Hiyari-Hat activity," routine inspections by professionals, risk assessment analysis, and mandatory health check-up focusing on sleep and depression. In the risk assessment analysis, an exact assessment model was suggested using a formula based on multiplication of the following three factors: (1) severity, (2) frequency, and (3) possibility. Mental health problems, including suicide, are rather tricky to deal with because they involve evaluation of individual cases. The mind body medicine hypothesis and matrix analysis would be appropriate tactics for suicide prevention because they would help the evaluation of this issue as a tangible problem. PMID:21054837

Chaos and random matrices in supersymmetric SYK

NASA Astrophysics Data System (ADS)

Hunter-Jones, Nicholas; Liu, Junyu

2018-05-01

We use random matrix theory to explore late-time chaos in supersymmetric quantum mechanical systems. Motivated by the recent study of supersymmetric SYK models and their random matrix classification, we consider the Wishart-Laguerre unitary ensemble and compute the spectral form factors and frame potentials to quantify chaos and randomness. Compared to the Gaussian ensembles, we observe the absence of a dip regime in the form factor and a slower approach to Haar-random dynamics. We find agreement between our random matrix analysis and predictions from the supersymmetric SYK model, and discuss the implications for supersymmetric chaotic systems.

Research on the recycling industry development model for typical exterior plastic components of end-of-life passenger vehicle based on the SWOT method.

PubMed

Zhang, Hongshen; Chen, Ming

2013-11-01

In-depth studies on the recycling of typical automotive exterior plastic parts are significant and beneficial for environmental protection, energy conservation, and sustainable development of China. In the current study, several methods were used to analyze the recycling industry model for typical exterior parts of passenger vehicles in China. The strengths, weaknesses, opportunities, and challenges of the current recycling industry for typical exterior parts of passenger vehicles were analyzed comprehensively based on the SWOT method. The internal factor evaluation matrix and external factor evaluation matrix were used to evaluate the internal and external factors of the recycling industry. The recycling industry was found to respond well to all the factors and it was found to face good developing opportunities. Then, the cross-link strategies analysis for the typical exterior parts of the passenger car industry of China was conducted based on the SWOT analysis strategies and established SWOT matrix. Finally, based on the aforementioned research, the recycling industry model led by automobile manufacturers was promoted. Copyright © 2013 Elsevier Ltd. All rights reserved.

3D tensor-based blind multispectral image decomposition for tumor demarcation

NASA Astrophysics Data System (ADS)

Kopriva, Ivica; Peršin, Antun

2010-03-01

Blind decomposition of multi-spectral fluorescent image for tumor demarcation is formulated exploiting tensorial structure of the image. First contribution of the paper is identification of the matrix of spectral responses and 3D tensor of spatial distributions of the materials present in the image from Tucker3 or PARAFAC models of 3D image tensor. Second contribution of the paper is clustering based estimation of the number of the materials present in the image as well as matrix of their spectral profiles. 3D tensor of the spatial distributions of the materials is recovered through 3-mode multiplication of the multi-spectral image tensor and inverse of the matrix of spectral profiles. Tensor representation of the multi-spectral image preserves its local spatial structure that is lost, due to vectorization process, when matrix factorization-based decomposition methods (such as non-negative matrix factorization and independent component analysis) are used. Superior performance of the tensor-based image decomposition over matrix factorization-based decompositions is demonstrated on experimental red-green-blue (RGB) image with known ground truth as well as on RGB fluorescent images of the skin tumor (basal cell carcinoma).

Formulas for Image Factor Scores

ERIC Educational Resources Information Center

Hakstian, A. Ralph

1973-01-01

Formulas are presented in this paper for computing scores associated with factors of G, the image covariance matrix, under three conditions. The subject of the paper is restricted to "pure" image analysis. (Author/NE)

Identification of regional activation by factorization of high-density surface EMG signals: A comparison of Principal Component Analysis and Non-negative Matrix factorization.

PubMed

Gallina, Alessio; Garland, S Jayne; Wakeling, James M

2018-05-22

In this study, we investigated whether principal component analysis (PCA) and non-negative matrix factorization (NMF) perform similarly for the identification of regional activation within the human vastus medialis. EMG signals from 64 locations over the VM were collected from twelve participants while performing a low-force isometric knee extension. The envelope of the EMG signal of each channel was calculated by low-pass filtering (8 Hz) the monopolar EMG signal after rectification. The data matrix was factorized using PCA and NMF, and up to 5 factors were considered for each algorithm. Association between explained variance, spatial weights and temporal scores between the two algorithms were compared using Pearson correlation. For both PCA and NMF, a single factor explained approximately 70% of the variance of the signal, while two and three factors explained just over 85% or 90%. The variance explained by PCA and NMF was highly comparable (R > 0.99). Spatial weights and temporal scores extracted with non-negative reconstruction of PCA and NMF were highly associated (all p < 0.001, mean R > 0.97). Regional VM activation can be identified using high-density surface EMG and factorization algorithms. Regional activation explains up to 30% of the variance of the signal, as identified through both PCA and NMF. Copyright © 2018 Elsevier Ltd. All rights reserved.

Compensation of matrix effects in gas chromatography-mass spectrometry analysis of pesticides using a combination of matrix matching and multiple isotopically labeled internal standards.

PubMed

Tsuchiyama, Tomoyuki; Katsuhara, Miki; Nakajima, Masahiro

2017-11-17

In the multi-residue analysis of pesticides using GC-MS, the quantitative results are adversely affected by a phenomenon known as the matrix effect. Although the use of matrix-matched standards is considered to be one of the most practical solutions to this problem, complete removal of the matrix effect is difficult in complex food matrices owing to their inconsistency. As a result, residual matrix effects can introduce analytical errors. To compensate for residual matrix effects, we have developed a novel method that employs multiple isotopically labeled internal standards (ILIS). The matrix effects of ILIS and pesticides were evaluated in spiked matrix extracts of various agricultural commodities, and the obtained data were subjected to simple statistical analysis. Based on the similarities between the patterns of variation in the analytical response, a total of 32 isotopically labeled compounds were assigned to 338 pesticides as internal standards. It was found that by utilizing multiple ILIS, residual matrix effects could be effectively compensated. The developed method exhibited superior quantitative performance compared with the common single-internal-standard method. The proposed method is more feasible for regulatory purposes than that using only predetermined correction factors and is considered to be promising for practical applications. Copyright © 2017 Elsevier B.V. All rights reserved.

The Construct Validity of Higher Order Structure-of-Intellect Abilities in a Battery of Tests Emphasizing the Product of Transformations: A Confirmatory Maximum Likelihood Factor Analysis.

ERIC Educational Resources Information Center

Khattab, Ali-Maher; And Others

1982-01-01

A causal modeling system, using confirmatory maximum likelihood factor analysis with the LISREL IV computer program, evaluated the construct validity underlying the higher order factor structure of a given correlation matrix of 46 structure-of-intellect tests emphasizing the product of transformations. (Author/PN)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yeung, Yu-Hong; Pothen, Alex; Halappanavar, Mahantesh

We present an augmented matrix approach to update the solution to a linear system of equations when the coefficient matrix is modified by a few elements within a principal submatrix. This problem arises in the dynamic security analysis of a power grid, where operators need to performmore » $N-x$ contingency analysis, i.e., determine the state of the system when up to $x$ links from $N$ fail. Our algorithms augment the coefficient matrix to account for the changes in it, and then compute the solution to the augmented system without refactoring the modified matrix. We provide two algorithms, a direct method, and a hybrid direct-iterative method for solving the augmented system. We also exploit the sparsity of the matrices and vectors to accelerate the overall computation. Our algorithms are compared on three power grids with PARDISO, a parallel direct solver, and CHOLMOD, a direct solver with the ability to modify the Cholesky factors of the coefficient matrix. We show that our augmented algorithms outperform PARDISO (by two orders of magnitude), and CHOLMOD (by a factor of up to 5). Further, our algorithms scale better than CHOLMOD as the number of elements updated increases. The solutions are computed with high accuracy. Our algorithms are capable of computing $N-x$ contingency analysis on a $778K$ bus grid, updating a solution with $x=20$ elements in $$1.6 \\times 10^{-2}$$ seconds on an Intel Xeon processor.« less

Multiway analysis methods applied to the fluorescence excitation-emission dataset for the simultaneous quantification of valsartan and amlodipine in tablets

NASA Astrophysics Data System (ADS)

Dinç, Erdal; Ertekin, Zehra Ceren; Büker, Eda

2017-09-01

In this study, excitation-emission matrix datasets, which have strong overlapping bands, were processed by using four different chemometric calibration algorithms consisting of parallel factor analysis, Tucker3, three-way partial least squares and unfolded partial least squares for the simultaneous quantitative estimation of valsartan and amlodipine besylate in tablets. In analyses, preliminary separation step was not used before the application of parallel factor analysis Tucker3, three-way partial least squares and unfolded partial least squares approaches for the analysis of the related drug substances in samples. Three-way excitation-emission matrix data array was obtained by concatenating excitation-emission matrices of the calibration set, validation set, and commercial tablet samples. The excitation-emission matrix data array was used to get parallel factor analysis, Tucker3, three-way partial least squares and unfolded partial least squares calibrations and to predict the amounts of valsartan and amlodipine besylate in samples. For all the methods, calibration and prediction of valsartan and amlodipine besylate were performed in the working concentration ranges of 0.25-4.50 μg/mL. The validity and the performance of all the proposed methods were checked by using the validation parameters. From the analysis results, it was concluded that the described two-way and three-way algorithmic methods were very useful for the simultaneous quantitative resolution and routine analysis of the related drug substances in marketed samples.

A GRAPHICAL DIAGNOSTIC METHOD FOR ASSESSING THE ROTATION IN FACTOR ANALYTICAL MODELS OF ATMOSPHERIC POLLUTION. (R831078)

EPA Science Inventory

Factor analytic tools such as principal component analysis (PCA) and positive matrix factorization (PMF), suffer from rotational ambiguity in the results: different solutions (factors) provide equally good fits to the measured data. The PMF model imposes non-negativity of both...

Generating Nonnormal Multivariate Data Using Copulas: Applications to SEM

ERIC Educational Resources Information Center

Mair, Patrick; Satorra, Albert; Bentler, Peter M.

2012-01-01

This article develops a procedure based on copulas to simulate multivariate nonnormal data that satisfy a prespecified variance-covariance matrix. The covariance matrix used can comply with a specific moment structure form (e.g., a factor analysis or a general structural equation model). Thus, the method is particularly useful for Monte Carlo…

Multilevel Factor Analysis by Model Segregation: New Applications for Robust Test Statistics

ERIC Educational Resources Information Center

Schweig, Jonathan

2014-01-01

Measures of classroom environments have become central to policy efforts that assess school and teacher quality. This has sparked a wide interest in using multilevel factor analysis to test measurement hypotheses about classroom-level variables. One approach partitions the total covariance matrix and tests models separately on the…

An analysis of thermal response factors and how to reduce their computational time requirement

NASA Technical Reports Server (NTRS)

Wiese, M. R.

1982-01-01

Te RESFAC2 version of the Thermal Response Factor Program (RESFAC) is the result of numerous modifications and additions to the original RESFAC. These modifications and additions have significantly reduced the program's computational time requirement. As a result of this work, the program is more efficient and its code is both readable and understandable. This report describes what a thermal response factor is; analyzes the original matrix algebra calculations and root finding techniques; presents a new root finding technique and streamlined matrix algebra; supplies ten validation cases and their results.

Impact of the Choice of Normalization Method on Molecular Cancer Class Discovery Using Nonnegative Matrix Factorization.

PubMed

Yang, Haixuan; Seoighe, Cathal

2016-01-01

Nonnegative Matrix Factorization (NMF) has proved to be an effective method for unsupervised clustering analysis of gene expression data. By the nonnegativity constraint, NMF provides a decomposition of the data matrix into two matrices that have been used for clustering analysis. However, the decomposition is not unique. This allows different clustering results to be obtained, resulting in different interpretations of the decomposition. To alleviate this problem, some existing methods directly enforce uniqueness to some extent by adding regularization terms in the NMF objective function. Alternatively, various normalization methods have been applied to the factor matrices; however, the effects of the choice of normalization have not been carefully investigated. Here we investigate the performance of NMF for the task of cancer class discovery, under a wide range of normalization choices. After extensive evaluations, we observe that the maximum norm showed the best performance, although the maximum norm has not previously been used for NMF. Matlab codes are freely available from: http://maths.nuigalway.ie/~haixuanyang/pNMF/pNMF.htm.

Rotational Uniqueness Conditions under Oblique Factor Correlation Metric

ERIC Educational Resources Information Center

Peeters, Carel F. W.

2012-01-01

In an addendum to his seminal 1969 article Joreskog stated two sets of conditions for rotational identification of the oblique factor solution under utilization of fixed zero elements in the factor loadings matrix (Joreskog in "Advances in factor analysis and structural equation models," pp. 40-43, 1979). These condition sets, formulated under…

Matrix Metallopeptidase 14 Plays an Important Role in Regulating Tumorigenic Gene Expression and Invasion Ability of HeLa Cells.

PubMed

Zhang, Ying-Hui; Wang, Juan-Juan; Li, Min; Zheng, Han-Xi; Xu, Lan; Chen, You-Guo

2016-03-01

The objectives of this study were to investigate the functional effect of matrix metallopeptidase 14 (MMP14) on cell invasion in cervical cancer cells (HeLa line) and to study the underlying molecular mechanisms. Expression vector of short hairpin RNA targeting MMP14 was treated in HeLa cells, and then, transfection efficiency was verified by a florescence microscope. Transwell assay was used to investigate cell invasion ability in HeLa cells. Quantitative polymerase chain reaction and Western blotting analysis were used to detect the expression of MMP14 and relative factors in messenger RNA and protein levels, respectively. Matrix metallopeptidase 14 short hairpin RNA expression vector transfection obviously decreased MMP14 expression in messenger RNA and protein levels. Down-regulation of MMP14 suppressed invasion ability of HeLa cells and reduced transforming growth factor β1 and vascular endothelial growth factor B expressions. Furthermore, MMP14 knockdown decreased bone sialoprotein and enhanced forkhead box protein L2 expression in both RNA and protein levels. Matrix metallopeptidase 14 plays an important role in regulating invasion of HeLa cells. Matrix metallopeptidase 14 knockdown contributes to attenuating the malignant phenotype of cervical cancer cell.

Dimensions of postconcussive symptoms in children with mild traumatic brain injuries.

PubMed

Ayr, Lauren K; Yeates, Keith Owen; Taylor, H Gerry; Browne, Michael

2009-01-01

The dimensions of postconcussive symptoms (PCS) were examined in a prospective, longitudinal study of 186 8 to 15 year old children with mild traumatic brain injuries (TBI). Parents and children completed a 50-item questionnaire within 2 weeks of injury and again at 3 months after injury, rating the frequency of PCS on a 4-point scale. Common factor analysis with target rotation was used to rotate the ratings to four hypothesized dimensions, representing cognitive, somatic, emotional, and behavioral symptoms. The rotated factor matrix for baseline parent ratings was consistent with the target matrix. The rotated matrix for baseline child ratings was consistent with the target matrix for cognitive and somatic symptoms but not for emotional and behavioral symptoms. The rotated matrices for ratings obtained 3 months after injury were largely consistent with the target matrix derived from analyses of baseline ratings, except that parent ratings of behavioral symptoms did not cluster as before. Parent and child ratings of PCS following mild TBI yield consistent factors reflecting cognitive and somatic symptom dimensions, but dimensions of emotional and behavioral symptoms are less robust across time and raters. (JINS, 2009, 15, 19-30.).

Approximate method of variational Bayesian matrix factorization/completion with sparse prior

NASA Astrophysics Data System (ADS)

Kawasumi, Ryota; Takeda, Koujin

2018-05-01

We derive the analytical expression of a matrix factorization/completion solution by the variational Bayes method, under the assumption that the observed matrix is originally the product of low-rank, dense and sparse matrices with additive noise. We assume the prior of a sparse matrix is a Laplace distribution by taking matrix sparsity into consideration. Then we use several approximations for the derivation of a matrix factorization/completion solution. By our solution, we also numerically evaluate the performance of a sparse matrix reconstruction in matrix factorization, and completion of a missing matrix element in matrix completion.

Constructing the tree-level Yang-Mills S-matrix using complex factorization

NASA Astrophysics Data System (ADS)

Schuster, Philip C.; Toro, Natalia

2009-06-01

A remarkable connection between BCFW recursion relations and constraints on the S-matrix was made by Benincasa and Cachazo in 0705.4305, who noted that mutual consistency of different BCFW constructions of four-particle amplitudes generates non-trivial (but familiar) constraints on three-particle coupling constants — these include gauge invariance, the equivalence principle, and the lack of non-trivial couplings for spins > 2. These constraints can also be derived with weaker assumptions, by demanding the existence of four-point amplitudes that factorize properly in all unitarity limits with complex momenta. From this starting point, we show that the BCFW prescription can be interpreted as an algorithm for fully constructing a tree-level S-matrix, and that complex factorization of general BCFW amplitudes follows from the factorization of four-particle amplitudes. The allowed set of BCFW deformations is identified, formulated entirely as a statement on the three-particle sector, and using only complex factorization as a guide. Consequently, our analysis based on the physical consistency of the S-matrix is entirely independent of field theory. We analyze the case of pure Yang-Mills, and outline a proof for gravity. For Yang-Mills, we also show that the well-known scaling behavior of BCFW-deformed amplitudes at large z is a simple consequence of factorization. For gravity, factorization in certain channels requires asymptotic behavior ~ 1/z2.

Carbon Dots and 9AA as a Binary Matrix for the Detection of Small Molecules by Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry

NASA Astrophysics Data System (ADS)

Chen, Yongli; Gao, Dan; Bai, Hangrui; Liu, Hongxia; Lin, Shuo; Jiang, Yuyang

2016-07-01

Application of matrix-assisted laser-desorption/ionization mass spectrometry (MALDI MS) to analyze small molecules have some limitations, due to the inhomogeneous analyte/matrix co-crystallization and interference of matrix-related peaks in low m/z region. In this work, carbon dots (CDs) were for the first time applied as a binary matrix with 9-Aminoacridine (9AA) in MALDI MS for small molecules analysis. By 9AA/CDs assisted desorption/ionization (D/I) process, a wide range of small molecules, including nucleosides, amino acids, oligosaccharides, peptides, and anticancer drugs with a higher sensitivity were demonstrated in the positive ion mode. A detection limit down to 5 fmol was achieved for cytidine. 9AA/CDs matrix also exhibited excellent reproducibility compared with 9AA matrix. Moreover, by exploring the ionization mechanism of the matrix, the influence factors might be attributed to the four parts: (1) the strong UV absorption of 9AA/CDs due to their π-conjugated network; (2) the carboxyl groups modified on the CDs surface act as protonation sites for proton transfer in positive ion mode; (3) the thin layer crystal of 9AA/CDs could reach a high surface temperature more easily and lower transfer energy for LDI MS; (4) CDs could serve as a matrix additive to suppress 9AA ionization. Furthermore, this matrix was allowed for the analysis of glucose as well as nucleosides in human urine, and the level of cytidine was quantified with a linear range of 0.05-5 mM (R2 > 0.99). Therefore, the 9AA/CDs matrix was proven to be an effective MALDI matrix for the analysis of small molecules with improved sensitivity and reproducibility. This work provides an alternative solution for small molecules detection that can be further used in complex samples analysis.

Simulating the effect of non-linear mode coupling in cosmological parameter estimation

NASA Astrophysics Data System (ADS)

Kiessling, A.; Taylor, A. N.; Heavens, A. F.

2011-09-01

Fisher Information Matrix methods are commonly used in cosmology to estimate the accuracy that cosmological parameters can be measured with a given experiment and to optimize the design of experiments. However, the standard approach usually assumes both data and parameter estimates are Gaussian-distributed. Further, for survey forecasts and optimization it is usually assumed that the power-spectrum covariance matrix is diagonal in Fourier space. However, in the low-redshift Universe, non-linear mode coupling will tend to correlate small-scale power, moving information from lower to higher order moments of the field. This movement of information will change the predictions of cosmological parameter accuracy. In this paper we quantify this loss of information by comparing naïve Gaussian Fisher matrix forecasts with a maximum likelihood parameter estimation analysis of a suite of mock weak lensing catalogues derived from N-body simulations, based on the SUNGLASS pipeline, for a 2D and tomographic shear analysis of a Euclid-like survey. In both cases, we find that the 68 per cent confidence area of the Ωm-σ8 plane increases by a factor of 5. However, the marginal errors increase by just 20-40 per cent. We propose a new method to model the effects of non-linear shear-power mode coupling in the Fisher matrix by approximating the shear-power distribution as a multivariate Gaussian with a covariance matrix derived from the mock weak lensing survey. We find that this approximation can reproduce the 68 per cent confidence regions of the full maximum likelihood analysis in the Ωm-σ8 plane to high accuracy for both 2D and tomographic weak lensing surveys. Finally, we perform a multiparameter analysis of Ωm, σ8, h, ns, w0 and wa to compare the Gaussian and non-linear mode-coupled Fisher matrix contours. The 6D volume of the 1σ error contours for the non-linear Fisher analysis is a factor of 3 larger than for the Gaussian case, and the shape of the 68 per cent confidence volume is modified. We propose that future Fisher matrix estimates of cosmological parameter accuracies should include mode-coupling effects.

Classification Techniques for Multivariate Data Analysis.

DTIC Science & Technology

1980-03-28

analysis among biologists, botanists, and ecologists, while some social scientists may refer "typology". Other frequently encountered terms are pattern...the determinantal equation: lB -XW 0 (42) 49 The solutions X. are the eigenvalues of the matrix W-1 B 1 as in discriminant analysis. There are t non...Statistical Package for Social Sciences (SPSS) (14) subprogram FACTOR was used for the principal components analysis. It is designed both for the factor

Analytical development of disturbed matrix eigenvalue problem applied to mixed convection stability analysis in Darcy media

NASA Astrophysics Data System (ADS)

Hamed, Haikel Ben; Bennacer, Rachid

2008-08-01

This work consists in evaluating algebraically and numerically the influence of a disturbance on the spectral values of a diagonalizable matrix. Thus, two approaches will be possible; to use the theorem of disturbances of a matrix depending on a parameter, due to Lidskii and primarily based on the structure of Jordan of the no disturbed matrix. The second approach consists in factorizing the matrix system, and then carrying out a numerical calculation of the roots of the disturbances matrix characteristic polynomial. This problem can be a standard model in the equations of the continuous media mechanics. During this work, we chose to use the second approach and in order to illustrate the application, we choose the Rayleigh-Bénard problem in Darcy media, disturbed by a filtering through flow. The matrix form of the problem is calculated starting from a linear stability analysis by a finite elements method. We show that it is possible to break up the general phenomenon into other elementary ones described respectively by a disturbed matrix and a disturbance. A good agreement between the two methods was seen. To cite this article: H.B. Hamed, R. Bennacer, C. R. Mecanique 336 (2008).

An Exploratory Analysis of Factors Affecting Participation in Air Force Knowledge Now Communities of Practice

DTIC Science & Technology

2004-03-01

reliability coefficients are presented in chapter four in the factor analysis section. Along with Crobach’s Alpha coefficients, the Kaiser - Meyer - Olkin ...the pattern of correlation coefficients > 0.300 in the correlation matrix • Kaiser - Meyer - Olkin Measure of Sampling Adequacy (MSA) > 0.700 • Bartlett’s...exploratory factor analysis. The Kaiser - Meyer - Olkin measure of sampling adequacy yielded a value of .790, and Bartlett’s test of sphericity yielded a

Analysis of IFE, EFE and QSPM matrix on business development strategy

NASA Astrophysics Data System (ADS)

Zulkarnain, A.; Wahyuningtias, D.; Putranto, T. S.

2018-03-01

IFE matrix, EFE matrix, and QSPM matrix are business strategy tools that can be used to identify the threat, opportunity, weakness, strength as internal, external business factors. The goal of Danti’s Deli Bakery is to provide pastry product and distribute to other food and beverage outlet all around Jakarta. Thus, Danti’s Deli Bakery requires development strategy in order to win the tight competition. Applied descriptive research and data collected from focus group discussion, questionnaire, interview, observation and literature review. The objectives of this paper are (1) to identify and evaluate internal and external factors, (2) to formulate alternative strategy toward business development program, and (3) to give effective recommendation. The result shows that Danti’s Deli Bakery should apply product differentiation strategy. Implementation of this study is providing the recommendation for pastry and bakery industry to establish a successful business.

Multichannel Compressive Sensing MRI Using Noiselet Encoding

PubMed Central

Pawar, Kamlesh; Egan, Gary; Zhang, Jingxin

2015-01-01

The incoherence between measurement and sparsifying transform matrices and the restricted isometry property (RIP) of measurement matrix are two of the key factors in determining the performance of compressive sensing (CS). In CS-MRI, the randomly under-sampled Fourier matrix is used as the measurement matrix and the wavelet transform is usually used as sparsifying transform matrix. However, the incoherence between the randomly under-sampled Fourier matrix and the wavelet matrix is not optimal, which can deteriorate the performance of CS-MRI. Using the mathematical result that noiselets are maximally incoherent with wavelets, this paper introduces the noiselet unitary bases as the measurement matrix to improve the incoherence and RIP in CS-MRI. Based on an empirical RIP analysis that compares the multichannel noiselet and multichannel Fourier measurement matrices in CS-MRI, we propose a multichannel compressive sensing (MCS) framework to take the advantage of multichannel data acquisition used in MRI scanners. Simulations are presented in the MCS framework to compare the performance of noiselet encoding reconstructions and Fourier encoding reconstructions at different acceleration factors. The comparisons indicate that multichannel noiselet measurement matrix has better RIP than that of its Fourier counterpart, and that noiselet encoded MCS-MRI outperforms Fourier encoded MCS-MRI in preserving image resolution and can achieve higher acceleration factors. To demonstrate the feasibility of the proposed noiselet encoding scheme, a pulse sequences with tailored spatially selective RF excitation pulses was designed and implemented on a 3T scanner to acquire the data in the noiselet domain from a phantom and a human brain. The results indicate that noislet encoding preserves image resolution better than Fouirer encoding. PMID:25965548

An improved semi-implicit method for structural dynamics analysis

NASA Technical Reports Server (NTRS)

Park, K. C.

1982-01-01

A semi-implicit algorithm is presented for direct time integration of the structural dynamics equations. The algorithm avoids the factoring of the implicit difference solution matrix and mitigates the unacceptable accuracy losses which plagued previous semi-implicit algorithms. This substantial accuracy improvement is achieved by augmenting the solution matrix with two simple diagonal matrices of the order of the integration truncation error.

Regulation of matrix metalloproteinases (MMPs) expression and secretion in MDA-MB-231 breast cancer cells by LIM and SH3 protein 1 (LASP1).

PubMed

Endres, Marcel; Kneitz, Susanne; Orth, Martin F; Perera, Ruwan K; Zernecke, Alma; Butt, Elke

2016-09-27

The process of tumor invasion requires degradation of extracellular matrix by proteolytic enzymes. Cancer cells form protrusive invadopodia, which produce and release matrix metalloproteinases (MMPs) to degrade the basement membrane thereby enabling metastasis. We investigated the effect of LASP1, a newly identified protein in invadopodia, on expression, secretion and activation of MMPs in invasive breast tumor cell lines.By analyzing microarray data of in-house generated control and LASP1-depleted MDA-MB-231 breast cancer cells, we observed downregulation of MMP1, -3 and -9 upon LASP1 depletion. This was confirmed by Western blot analysis. Conversely, rescue experiments restored in part MMP expression and secretion. The regulatory effect of LASP1 on MMP expression was also observed in BT-20 breast cancer cells as well as in prostate and bladder cancer cell lines.In line with bioinformatic FunRich analysis of our data, which mapped a high regulation of transcription factors by LASP1, public microarray data analysis detected a correlation between high LASP1 expression and enhanced c-Fos levels, a protein that is part of the transcription factor AP-1 and known to regulate MMP expression. Compatibly, in luciferase reporter assays, AP-1 showed a decreased transcriptional activity after LASP1 knockdown.Zymography assays and Western blot analysis revealed an additional promotion of MMP secretion into the extracellular matrix by LASP1, thus, most likely, altering the microenvironment during cancer progression.The newly identified role of LASP1 in regulating matrix degradation by affecting MMP transcription and secretion elucidated the migratory potential of LASP1 overexpressing aggressive tumor cells in earlier studies.

Rotation to a Partially Specified Target Matrix in Exploratory Factor Analysis: How Many Targets?

ERIC Educational Resources Information Center

Myers, Nicholas D.; Ahn, Soyeon; Jin, Ying

2013-01-01

The purpose of this study was to explore the influence of the number of targets specified on the quality of exploratory factor analysis solutions with a complex underlying structure and incomplete substantive measurement theory. Three Monte Carlo studies were performed based on the ratio of the number of observed variables to the number of…

Comparing direct and iterative equation solvers in a large structural analysis software system

NASA Technical Reports Server (NTRS)

Poole, E. L.

1991-01-01

Two direct Choleski equation solvers and two iterative preconditioned conjugate gradient (PCG) equation solvers used in a large structural analysis software system are described. The two direct solvers are implementations of the Choleski method for variable-band matrix storage and sparse matrix storage. The two iterative PCG solvers include the Jacobi conjugate gradient method and an incomplete Choleski conjugate gradient method. The performance of the direct and iterative solvers is compared by solving several representative structural analysis problems. Some key factors affecting the performance of the iterative solvers relative to the direct solvers are identified.

Mueller coherency matrix method for contrast image in tissue polarimetry

NASA Astrophysics Data System (ADS)

Arce-Diego, J. L.; Fanjul-Vélez, F.; Samperio-García, D.; Pereda-Cubián, D.

2007-07-01

In this work, we propose the use of the Mueller Coherency matrix of biological tissues in order to increase the information from tissue images and so their contrast. This method involves different Mueller Coherency matrix based parameters, like the eigenvalues analysis, the entropy factor calculation, polarization components crosstalks, linear and circular polarization degrees, hermiticity or the Quaternions analysis in case depolarisation properties of tissue are sufficiently low. All these parameters make information appear clearer and so increase image contrast, so pathologies like cancer could be detected in a sooner stage of development. The election will depend on the concrete pathological process under study. This Mueller Coherency matrix method can be applied to a single tissue point, or it can be combined with a tomographic technique, so as to obtain a 3D representation of polarization contrast parameters in pathological tissues. The application of this analysis to concrete diseases can lead to tissue burn depth estimation or cancer early detection.

Physiological Ranges of Matrix Rigidity Modulate Primary Mouse Hepatocyte Function In Part Through Hepatocyte Nuclear Factor 4 Alpha

PubMed Central

Desai, Seema S.; Tung, Jason C.; Zhou, Vivian X.; Grenert, James P.; Malato, Yann; Rezvani, Milad; Español-Suñer, Regina; Willenbring, Holger; Weaver, Valerie M.; Chang, Tammy T.

2016-01-01

Matrix rigidity has important effects on cell behavior and is increased during liver fibrosis; however, its effect on primary hepatocyte function is unknown. We hypothesized that increased matrix rigidity in fibrotic livers would activate mechanotransduction in hepatocytes and lead to inhibition of hepatic-specific functions. To determine the physiologically relevant ranges of matrix stiffness at the cellular level, we performed detailed atomic force microscopy analysis across liver lobules from normal and fibrotic livers. We determined that normal liver matrix stiffness was around 150Pa and increased to 1–6kPa in areas near fibrillar collagen deposition in fibrotic livers. In vitro culture of primary hepatocytes on collagen matrix of tunable rigidity demonstrated that fibrotic levels of matrix stiffness had profound effects on cytoskeletal tension and significantly inhibited hepatocyte-specific functions. Normal liver stiffness maintained functional gene regulation by hepatocyte nuclear factor 4 alpha (HNF4α) whereas fibrotic matrix stiffness inhibited the HNF4α transcriptional network. Fibrotic levels of matrix stiffness activated mechanotransduction in primary hepatocytes through focal adhesion kinase (FAK). In addition, blockade of the Rho/Rho-associated protein kinase (ROCK) pathway rescued HNF4α expression from hepatocytes cultured on stiff matrix. Conclusion Fibrotic levels of matrix stiffness significantly inhibit hepatocyte-specific functions in part by inhibiting the HNF4α transcriptional network mediated through the Rho/ROCK pathway. Increased appreciation of the role of matrix rigidity in modulating hepatocyte function will advance our understanding of the mechanisms of hepatocyte dysfunction in liver cirrhosis and spur development of novel treatments for chronic liver disease. PMID:26755329

Extracting factors for interest rate scenarios

NASA Astrophysics Data System (ADS)

Molgedey, L.; Galic, E.

2001-04-01

Factor based interest rate models are widely used for risk managing purposes, for option pricing and for identifying and capturing yield curve anomalies. The movements of a term structure of interest rates are commonly assumed to be driven by a small number of orthogonal factors such as SHIFT, TWIST and BUTTERFLY (BOW). These factors are usually obtained by a Principal Component Analysis (PCA) of historical bond prices (interest rates). Although PCA diagonalizes the covariance matrix of either the interest rates or the interest rate changes, it does not use both covariance matrices simultaneously. Furthermore higher linear and nonlinear correlations are neglected. These correlations as well as the mean reverting properties of the interest rates become crucial, if one is interested in a longer time horizon (infrequent hedging or trading). We will show that Independent Component Analysis (ICA) is a more appropriate tool than PCA, since ICA uses the covariance matrix of the interest rates as well as the covariance matrix of the interest rate changes simultaneously. Additionally higher linear and nonlinear correlations may be easily incorporated. The resulting factors are uncorrelated for various time delays, approximately independent but nonorthogonal. This is in contrast to the factors obtained from the PCA, which are orthogonal and uncorrelated for identical times only. Although factors from the ICA are nonorthogonal, it is sufficient to consider only a few factors in order to explain most of the variation in the original data. Finally we will present examples that ICA based hedges outperforms PCA based hedges specifically if the portfolio is sensitive to structural changes of the yield curve.

Statistical analysis of latent generalized correlation matrix estimation in transelliptical distribution.

PubMed

Han, Fang; Liu, Han

2017-02-01

Correlation matrix plays a key role in many multivariate methods (e.g., graphical model estimation and factor analysis). The current state-of-the-art in estimating large correlation matrices focuses on the use of Pearson's sample correlation matrix. Although Pearson's sample correlation matrix enjoys various good properties under Gaussian models, its not an effective estimator when facing heavy-tail distributions with possible outliers. As a robust alternative, Han and Liu (2013b) advocated the use of a transformed version of the Kendall's tau sample correlation matrix in estimating high dimensional latent generalized correlation matrix under the transelliptical distribution family (or elliptical copula). The transelliptical family assumes that after unspecified marginal monotone transformations, the data follow an elliptical distribution. In this paper, we study the theoretical properties of the Kendall's tau sample correlation matrix and its transformed version proposed in Han and Liu (2013b) for estimating the population Kendall's tau correlation matrix and the latent Pearson's correlation matrix under both spectral and restricted spectral norms. With regard to the spectral norm, we highlight the role of "effective rank" in quantifying the rate of convergence. With regard to the restricted spectral norm, we for the first time present a "sign subgaussian condition" which is sufficient to guarantee that the rank-based correlation matrix estimator attains the optimal rate of convergence. In both cases, we do not need any moment condition.

Coastal Benthic Boundary Layer Special Research Program. Program Direction and Workshop Recommendations

DTIC Science & Technology

1992-08-01

Faas, " Analysis of the relationship between acoustic reflectivity and sediment porosity," Geophysics 3 4, 546-553 (1969). M. A. Foda , J. Y.-H. Chang...properties, together with in situ measured mechanical, acoustic and electrical properties, should be subjected to factor analysis . Natural clusters could...properties. The mechanical 1 properties and remotely sensed properties are a matrix of information that can be subjected to factor analysis . One can

Factorization and fitting of molecular scattering information

DOE Office of Scientific and Technical Information (OSTI.GOV)

Goldflam, R.; Kouri, D.J.; Green, S.

1977-12-15

The factorization of cross sections of various kinds resulting from the infinite order sudden approximation is considered in detail. Unlike the earlier study of Goldflam, Green, and Kouri, we base the present analysis on the factored IOS T-matrix rather than on the S-matrix. This enables us to obtain somewhat simpler expressions. For example, we show that the factored IOS approximation to the Arthurs--Dalgarno T-matrix involves products of dynamical coefficients T/sup L//sub l/ and Percival--Seaton coefficients f/sub L/(jlvertical-barj/sub 0/l/sub 0/vertical-barJ). It is shown that an optical theorem exists for the T/sub l//sup L/ dynamical coefficients of the T-matrix. The differential scatteringmore » amplitudes are shown to factor into dynamical coefficients q/sub L/(chi) times spectroscopic factors that are independent of the dynamics (potential). Then a generalized form of the Parker--Pack result for ..sigma../sub j/(dsigma/dR)(j/sub 0/..-->..j) is derived. It is also shown that the IOS approximation for (dsigma/dR)(j/sub 0/..-->..j) factors into sums of spectroscopic coefficients times the differential cross sections out of j/sub 0/=0. The IOS integral cross sections factor into spectroscopic coefficients times the integral cross sections out of j/sub 0/=0. The factored IOS general phenomenological cross sections are rederived using the T-matrix approach and are shown to equal sums of Percival--Seaton coefficients timesthe inelastic integral cross section out of initial rotor state j/sub 0/ = 0. This suggests that experimental measurements of line shapes and/or NMR spin--lattice relaxation can be used to directly give inelastic state-to-state degeneracy averaged integral cross sections whenever the IOS is a good approximation. Factored IOS expressions for viscosity and diffusion are derived and shown to potentially yield additional information beyond that contained in line shapes.« less

Grapevine tissues and phenology differentially affect soluble carbohydrates determination by capillary electrophoresis.

PubMed

Moreno, Daniela; Berli, Federico; Bottini, Rubén; Piccoli, Patricia N; Silva, María F

2017-09-01

Soluble carbohydrates distribution depends on plant physiology and, among other important factors, determines fruit yield and quality. In plant biology, the analysis of sugars is useful for many purposes, including metabolic studies. Capillary electrophoresis (CE) proved to be a powerful green separation technique with minimal sample preparation, even in complex plant tissues, that can provide high-resolution efficiency. Matrix effect refers to alterations in the analytical response caused by components of a sample other than the analyte of interest. Thus, the assessment and reduction of the matrix factor is fundamental for metabolic studies in different matrices. The present study evaluated the source and levels of matrix effects in the determination of most abundant sugars in grapevine tissues (mature and young leaves, berries and roots) at two phenological growth stages. Sucrose was the sugar that showed the least matrix effects, while fructose was the most affected analyte. Based on plant tissues, young leaves presented the smaller matrix effects, irrespectively of the phenology. These changes may be attributed to considerable differences at chemical composition of grapevine tissues with plant development. Therefore, matrix effect should be an important concern for plant metabolomics. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Transformation Abilities: A Reanalysis and Confirmation of SOI Theory.

ERIC Educational Resources Information Center

Khattab, Ali-Maher; And Others

1987-01-01

Confirmatory factor analysis was used to reanalyze correlational data from selected variables in Guilford's Aptitudes Research Project. Results indicated Guilford's model reproduced the original correlation matrix more closely than other models. Most of Guilford's tests indicated high loadings on their hypothesized factors. (GDC)

Application of Haddon's matrix in qualitative research methodology: an experience in burns epidemiology.

PubMed

Deljavan, Reza; Sadeghi-Bazargani, Homayoun; Fouladi, Nasrin; Arshi, Shahnam; Mohammadi, Reza

2012-01-01

Little has been done to investigate the application of injury specific qualitative research methods in the field of burn injuries. The aim of this study was to use an analytical tool (Haddon's matrix) through qualitative research methods to better understand people's perceptions about burn injuries. This study applied Haddon's matrix as a framework and an analytical tool for a qualitative research methodology in burn research. Both child and adult burn injury victims were enrolled into a qualitative study conducted using focus group discussion. Haddon's matrix was used to develop an interview guide and also through the analysis phase. The main analysis clusters were pre-event level/human (including risky behaviors, belief and cultural factors, and knowledge and education), pre-event level/object, pre-event phase/environment and event and post-event phase (including fire control, emergency scald and burn wound management, traditional remedies, medical consultation, and severity indicators). This research gave rise to results that are possibly useful both for future injury research and for designing burn injury prevention plans. Haddon's matrix is applicable in a qualitative research methodology both at data collection and data analysis phases. The study using Haddon's matrix through a qualitative research methodology yielded substantially rich information regarding burn injuries that may possibly be useful for prevention or future quantitative research.

Recurrence quantity analysis based on matrix eigenvalues

NASA Astrophysics Data System (ADS)

Yang, Pengbo; Shang, Pengjian

2018-06-01

Recurrence plots is a powerful tool for visualization and analysis of dynamical systems. Recurrence quantification analysis (RQA), based on point density and diagonal and vertical line structures in the recurrence plots, is considered to be alternative measures to quantify the complexity of dynamical systems. In this paper, we present a new measure based on recurrence matrix to quantify the dynamical properties of a given system. Matrix eigenvalues can reflect the basic characteristics of the complex systems, so we show the properties of the system by exploring the eigenvalues of the recurrence matrix. Considering that Shannon entropy has been defined as a complexity measure, we propose the definition of entropy of matrix eigenvalues (EOME) as a new RQA measure. We confirm that EOME can be used as a metric to quantify the behavior changes of the system. As a given dynamical system changes from a non-chaotic to a chaotic regime, the EOME will increase as well. The bigger EOME values imply higher complexity and lower predictability. We also study the effect of some factors on EOME,including data length, recurrence threshold, the embedding dimension, and additional noise. Finally, we demonstrate an application in physiology. The advantage of this measure lies in a high sensitivity and simple computation.

Process Research On Polycrystalline Silicon Material (PROPSM)

NASA Technical Reports Server (NTRS)

Culik, J. S.; Wohlgemuth, J. H.

1982-01-01

Performance limiting mechanisms in polycrystalline silicon are investigated by fabricating a matrix of solar cells of various thicknesses from polycrystalline silicon wafers of several bulk resistivities. The analysis of the results for the entire matrix indicates that bulk recombination is the dominant factor limiting the short circuit current in large grain (greater than 1 to 2 mm diameter) polycrystalline silicon, the same mechanism that limits the short circuit current in single crystal silicon. An experiment to investigate the limiting mechanisms of open circuit voltage and fill factor for large grain polycrystalline silicon is designed. Two process sequences to fabricate small cells are investigated.

The Influences of Physical Attractiveness and Sex-Based Biases on Midshipman Performance Evaluations at the United States Naval Academy

DTIC Science & Technology

2004-06-01

Meyer - 54 55 Olkin (KMO) and Bartlett’s test yielded a KMO measure of sampling adequacy of .683. Based on a rotated factor matrix, two factors were...factor analysis was performed on the first four questionnaire items (concern for success, effectiveness, friendliness, and sociability). A Kaiser

eMBI: Boosting Gene Expression-based Clustering for Cancer Subtypes.

PubMed

Chang, Zheng; Wang, Zhenjia; Ashby, Cody; Zhou, Chuan; Li, Guojun; Zhang, Shuzhong; Huang, Xiuzhen

2014-01-01

Identifying clinically relevant subtypes of a cancer using gene expression data is a challenging and important problem in medicine, and is a necessary premise to provide specific and efficient treatments for patients of different subtypes. Matrix factorization provides a solution by finding checker-board patterns in the matrices of gene expression data. In the context of gene expression profiles of cancer patients, these checkerboard patterns correspond to genes that are up- or down-regulated in patients with particular cancer subtypes. Recently, a new matrix factorization framework for biclustering called Maximum Block Improvement (MBI) is proposed; however, it still suffers several problems when applied to cancer gene expression data analysis. In this study, we developed many effective strategies to improve MBI and designed a new program called enhanced MBI (eMBI), which is more effective and efficient to identify cancer subtypes. Our tests on several gene expression profiling datasets of cancer patients consistently indicate that eMBI achieves significant improvements in comparison with MBI, in terms of cancer subtype prediction accuracy, robustness, and running time. In addition, the performance of eMBI is much better than another widely used matrix factorization method called nonnegative matrix factorization (NMF) and the method of hierarchical clustering, which is often the first choice of clinical analysts in practice.

eMBI: Boosting Gene Expression-based Clustering for Cancer Subtypes

PubMed Central

Chang, Zheng; Wang, Zhenjia; Ashby, Cody; Zhou, Chuan; Li, Guojun; Zhang, Shuzhong; Huang, Xiuzhen

2014-01-01

Identifying clinically relevant subtypes of a cancer using gene expression data is a challenging and important problem in medicine, and is a necessary premise to provide specific and efficient treatments for patients of different subtypes. Matrix factorization provides a solution by finding checker-board patterns in the matrices of gene expression data. In the context of gene expression profiles of cancer patients, these checkerboard patterns correspond to genes that are up- or down-regulated in patients with particular cancer subtypes. Recently, a new matrix factorization framework for biclustering called Maximum Block Improvement (MBI) is proposed; however, it still suffers several problems when applied to cancer gene expression data analysis. In this study, we developed many effective strategies to improve MBI and designed a new program called enhanced MBI (eMBI), which is more effective and efficient to identify cancer subtypes. Our tests on several gene expression profiling datasets of cancer patients consistently indicate that eMBI achieves significant improvements in comparison with MBI, in terms of cancer subtype prediction accuracy, robustness, and running time. In addition, the performance of eMBI is much better than another widely used matrix factorization method called nonnegative matrix factorization (NMF) and the method of hierarchical clustering, which is often the first choice of clinical analysts in practice. PMID:25374455

A DEIM Induced CUR Factorization

DTIC Science & Technology

2015-09-18

CUR approximate matrix factorization based on the Discrete Empirical Interpolation Method (DEIM). For a given matrix A, such a factorization provides a...CUR approximations based on leverage scores. 1 Introduction This work presents a new CUR matrix factorization based upon the Discrete Empirical...SUPPLEMENTARY NOTES 14. ABSTRACT We derive a CUR approximate matrix factorization based on the Discrete Empirical Interpolation Method (DEIM). For a given

Physiological ranges of matrix rigidity modulate primary mouse hepatocyte function in part through hepatocyte nuclear factor 4 alpha.

PubMed

Desai, Seema S; Tung, Jason C; Zhou, Vivian X; Grenert, James P; Malato, Yann; Rezvani, Milad; Español-Suñer, Regina; Willenbring, Holger; Weaver, Valerie M; Chang, Tammy T

2016-07-01

Matrix rigidity has important effects on cell behavior and is increased during liver fibrosis; however, its effect on primary hepatocyte function is unknown. We hypothesized that increased matrix rigidity in fibrotic livers would activate mechanotransduction in hepatocytes and lead to inhibition of liver-specific functions. To determine the physiologically relevant ranges of matrix stiffness at the cellular level, we performed detailed atomic force microscopy analysis across liver lobules from normal and fibrotic livers. We determined that normal liver matrix stiffness was around 150 Pa and increased to 1-6 kPa in areas near fibrillar collagen deposition in fibrotic livers. In vitro culture of primary hepatocytes on collagen matrix of tunable rigidity demonstrated that fibrotic levels of matrix stiffness had profound effects on cytoskeletal tension and significantly inhibited hepatocyte-specific functions. Normal liver stiffness maintained functional gene regulation by hepatocyte nuclear factor 4 alpha (HNF4α), whereas fibrotic matrix stiffness inhibited the HNF4α transcriptional network. Fibrotic levels of matrix stiffness activated mechanotransduction in primary hepatocytes through focal adhesion kinase. In addition, blockade of the Rho/Rho-associated protein kinase pathway rescued HNF4α expression from hepatocytes cultured on stiff matrix. Fibrotic levels of matrix stiffness significantly inhibit hepatocyte-specific functions in part by inhibiting the HNF4α transcriptional network mediated through the Rho/Rho-associated protein kinase pathway. Increased appreciation of the role of matrix rigidity in modulating hepatocyte function will advance our understanding of the mechanisms of hepatocyte dysfunction in liver cirrhosis and spur development of novel treatments for chronic liver disease. (Hepatology 2016;64:261-275). © 2016 by the American Association for the Study of Liver Diseases.

Characterization of extracellular polymeric substances in biofilms under long-term exposure to ciprofloxacin antibiotic using fluorescence excitation-emission matrix and parallel factor analysis.

PubMed

Gu, Chaochao; Gao, Pin; Yang, Fan; An, Dongxuan; Munir, Mariya; Jia, Hanzhong; Xue, Gang; Ma, Chunyan

2017-05-01

The presence of antibiotic residues in the environment has been regarded as an emerging concern due to their potential adverse environmental consequences such as antibiotic resistance. However, the interaction between antibiotics and extracellular polymeric substances (EPSs) of biofilms in wastewater treatment systems is not entirely clear. In this study, the effect of ciprofloxacin (CIP) antibiotic on biofilm EPS matrix was investigated and characterized using fluorescence excitation-emission matrix (EEM) and parallel factor (PARAFAC) analysis. Physicochemical analysis showed that the proteins were the major EPS fraction, and their contents increased gradually with an increase in CIP concentration (0-300 μg/L). Based on the characterization of biofilm tightly bound EPS (TB-EPS) by EEM, three fluorescent components were identified by PARAFAC analysis. Component C1 was associated with protein-like substances, and components C2 and C3 belonged to humic-like substances. Component C1 exhibited an increasing trend as the CIP addition increased. Pearson's correlation results showed that CIP correlated significantly with the protein contents and component C1, while strong correlations were also found among UV 254 , dissolved organic carbon, humic acids, and component C3. A combined use of EEM-PARAFAC analysis and chemical measurements was demonstrated as a favorable approach for the characterization of variations in biofilm EPS in the presence of CIP antibiotic.

Changes in chemical composition of bone matrix in ovariectomized (OVX) rats detected by Raman spectroscopy and multivariate analysis

NASA Astrophysics Data System (ADS)

Oshima, Yusuke; Iimura, Tadahiro; Saitou, Takashi; Imamura, Takeshi

2015-02-01

Osteoporosis is a major bone disease that connotes the risk of fragility fractures resulting from alterations to bone quantity and/or quality to mechanical competence. Bone strength arises from both bone quantity and quality. Assessment of bone quality and bone quantity is important for prediction of fracture risk. In spite of the two factors contribute to maintain the bone strength, only one factor, bone mineral density is used to determine the bone strength in the current diagnosis of osteoporosis. On the other hand, there is no practical method to measure chemical composition of bone tissue including hydroxyapatite and collagen non-invasively. Raman spectroscopy is a powerful technique to analyze chemical composition and material properties of bone matrix non-invasively. Here we demonstrated Raman spectroscopic analysis of the bone matrix in osteoporosis model rat. Ovariectomized (OVX) rat was made and the decalcified sections of tibias were analyzed by a Raman microscope. In the results, Raman bands of typical collagen appeared in the obtained spectra. Although the typical mineral bands at 960 cm-1 (Phosphate) was absent due to decalcified processing, we found that Raman peak intensities of amide I and C-C stretching bands were significantly different between OVX and sham-operated specimens. These differences on the Raman spectra were statistically compared by multivariate analyses, principal component analysis (PCA) and liner discrimination analysis (LDA). Our analyses suggest that amide I and C-C stretching bands can be related to stability of bone matrix which reflects bone quality.

Statistical analysis of latent generalized correlation matrix estimation in transelliptical distribution

PubMed Central

Han, Fang; Liu, Han

2016-01-01

Correlation matrix plays a key role in many multivariate methods (e.g., graphical model estimation and factor analysis). The current state-of-the-art in estimating large correlation matrices focuses on the use of Pearson’s sample correlation matrix. Although Pearson’s sample correlation matrix enjoys various good properties under Gaussian models, its not an effective estimator when facing heavy-tail distributions with possible outliers. As a robust alternative, Han and Liu (2013b) advocated the use of a transformed version of the Kendall’s tau sample correlation matrix in estimating high dimensional latent generalized correlation matrix under the transelliptical distribution family (or elliptical copula). The transelliptical family assumes that after unspecified marginal monotone transformations, the data follow an elliptical distribution. In this paper, we study the theoretical properties of the Kendall’s tau sample correlation matrix and its transformed version proposed in Han and Liu (2013b) for estimating the population Kendall’s tau correlation matrix and the latent Pearson’s correlation matrix under both spectral and restricted spectral norms. With regard to the spectral norm, we highlight the role of “effective rank” in quantifying the rate of convergence. With regard to the restricted spectral norm, we for the first time present a “sign subgaussian condition” which is sufficient to guarantee that the rank-based correlation matrix estimator attains the optimal rate of convergence. In both cases, we do not need any moment condition. PMID:28337068

In-house validation of a liquid chromatography-tandem mass spectrometry method for the determination of selective androgen receptor modulators (SARMS) in bovine urine.

PubMed

Schmidt, Kathrin S; Mankertz, Joachim

2018-06-01

A sensitive and robust LC-MS/MS method allowing the rapid screening and confirmation of selective androgen receptor modulators in bovine urine was developed and successfully validated according to Commission Decision 2002/657/EC, chapter 3.1.3 'alternative validation', by applying a matrix-comprehensive in-house validation concept. The confirmation of the analytes in the validation samples was achieved both on the basis of the MRM ion ratios as laid down in Commission Decision 2002/657/EC and by comparison of their enhanced product ion (EPI) spectra with a reference mass spectral library by making use of the QTRAP technology. Here, in addition to the MRM survey scan, EPI spectra were generated in a data-dependent way according to an information-dependent acquisition criterion. Moreover, stability studies of the analytes in solution and in matrix according to an isochronous approach proved the stability of the analytes in solution and in matrix for at least the duration of the validation study. To identify factors that have a significant influence on the test method in routine analysis, a factorial effect analysis was performed. To this end, factors considered to be relevant for the method in routine analysis (e.g. operator, storage duration of the extracts before measurement, different cartridge lots and different hydrolysis conditions) were systematically varied on two levels. The examination of the extent to which these factors influence the measurement results of the individual analytes showed that none of the validation factors exerts a significant influence on the measurement results.

Clustering Tree-structured Data on Manifold

PubMed Central

Lu, Na; Miao, Hongyu

2016-01-01

Tree-structured data usually contain both topological and geometrical information, and are necessarily considered on manifold instead of Euclidean space for appropriate data parameterization and analysis. In this study, we propose a novel tree-structured data parameterization, called Topology-Attribute matrix (T-A matrix), so the data clustering task can be conducted on matrix manifold. We incorporate the structure constraints embedded in data into the non-negative matrix factorization method to determine meta-trees from the T-A matrix, and the signature vector of each single tree can then be extracted by meta-tree decomposition. The meta-tree space turns out to be a cone space, in which we explore the distance metric and implement the clustering algorithm based on the concepts like Fréchet mean. Finally, the T-A matrix based clustering (TAMBAC) framework is evaluated and compared using both simulated data and real retinal images to illus trate its efficiency and accuracy. PMID:26660696

Matrix precipitation: a general strategy to eliminate matrix interference for pharmaceutical toxic impurities analysis.

PubMed

Yang, Xiaojing; Xiong, Xuewu; Cao, Ji; Luan, Baolei; Liu, Yongjun; Liu, Guozhu; Zhang, Lei

2015-01-30

Matrix interference, which can lead to false positive/negative results, contamination of injector or separation column, incompatibility between sample solution and the selected analytical instrument, and response inhibition or even quenching, is commonly suffered for the analysis of trace level toxic impurities in drug substance. In this study, a simple matrix precipitation strategy is proposed to eliminate or minimize the above stated matrix interference problems. Generally, a sample of active pharmaceutical ingredients (APIs) is dissolved in an appropriate solvent to achieve the desired high concentration and then an anti-solvent is added to precipitate the matrix substance. As a result, the target analyte is extracted into the mixed solution with very less residual of APIs. This strategy has the characteristics of simple manipulation, high recovery and excellent anti-interference capability. It was found that the precipitation ratio (R, representing the ability to remove matrix substance) and the proportion of solvent (the one used to dissolve APIs) in final solution (P, affecting R and also affecting the method sensitivity) are two important factors of the precipitation process. The correlation between R and P was investigated by performing precipitation with various APIs in different solvent/anti-solvent systems. After a detailed mathematical reasoning process, P=20% was proved to be an effective and robust condition to perform the precipitation strategy. The precipitation method with P=20% can be used as a general strategy for toxic impurity analysis in APIs. Finally, several typical examples are described in this article, where the challenging matrix interference issues have been resolved successfully. Copyright © 2014 Elsevier B.V. All rights reserved.

Studies of social group dynamics under isolated conditions. Objective summary of the literature as it relates to potential problems of long duration space flight

NASA Technical Reports Server (NTRS)

Vinograd, S. P.

1974-01-01

Scientific literature which deals with the study of human behavior and crew interaction in situations simulating long term space flight is summarized and organized. A bibliography of all the pertinent U.S. literature available is included, along with definitions of the behavioral characteristics terms employed. The summarized studies are analyzed according to behavioral factors and environmental conditions. The analysis consist of two matrices. (1) The matrix of factors studied correlates each research study area and individual study with the behavioral factors that were investigated in the study. (2) The matrix of conclusions identifies those studies whose investigators appeared to draw specific conclusions concerning questions of importance to NASA.

An analysis of spectral envelope-reduction via quadratic assignment problems

NASA Technical Reports Server (NTRS)

George, Alan; Pothen, Alex

1994-01-01

A new spectral algorithm for reordering a sparse symmetric matrix to reduce its envelope size was described. The ordering is computed by associating a Laplacian matrix with the given matrix and then sorting the components of a specified eigenvector of the Laplacian. In this paper, we provide an analysis of the spectral envelope reduction algorithm. We described related 1- and 2-sum problems; the former is related to the envelope size, while the latter is related to an upper bound on the work involved in an envelope Cholesky factorization scheme. We formulate the latter two problems as quadratic assignment problems, and then study the 2-sum problem in more detail. We obtain lower bounds on the 2-sum by considering a projected quadratic assignment problem, and then show that finding a permutation matrix closest to an orthogonal matrix attaining one of the lower bounds justifies the spectral envelope reduction algorithm. The lower bound on the 2-sum is seen to be tight for reasonably 'uniform' finite element meshes. We also obtain asymptotically tight lower bounds for the envelope size for certain classes of meshes.

Singular boundary method for wave propagation analysis in periodic structures

NASA Astrophysics Data System (ADS)

Fu, Zhuojia; Chen, Wen; Wen, Pihua; Zhang, Chuanzeng

2018-07-01

A strong-form boundary collocation method, the singular boundary method (SBM), is developed in this paper for the wave propagation analysis at low and moderate wavenumbers in periodic structures. The SBM is of several advantages including mathematically simple, easy-to-program, meshless with the application of the concept of origin intensity factors in order to eliminate the singularity of the fundamental solutions and avoid the numerical evaluation of the singular integrals in the boundary element method. Due to the periodic behaviors of the structures, the SBM coefficient matrix can be represented as a block Toeplitz matrix. By employing three different fast Toeplitz-matrix solvers, the computational time and storage requirements are significantly reduced in the proposed SBM analysis. To demonstrate the effectiveness of the proposed SBM formulation for wave propagation analysis in periodic structures, several benchmark examples are presented and discussed The proposed SBM results are compared with the analytical solutions, the reference results and the COMSOL software.

Differential modulation of degradative and repair responses of interleukin-1-treated chondrocytes by platelet-derived growth factor.

PubMed Central

Harvey, A K; Stack, S T; Chandrasekhar, S

1993-01-01

Interleukin 1 (IL-1) plays a dual role in cartilage matrix degeneration by promoting extracellular proteinase action such as the matrix metalloproteinases (increased degradation) and by suppressing the synthesis of extracellular matrix molecules (inhibition of repair). Platelet-derived growth factor (PDGF) is a wound-healing hormone which is released along with IL-1 during the inflammatory response. Since previous studies have shown that PDGF enhances IL-1 alpha effects on metalloproteinase activity, in this report, we have examined whether PDGF modifies IL-1 beta effects on cartilage proteoglycan synthesis. Initially, we confirmed that rabbit articular chondrocytes treated with IL-1 beta + PDGF induced higher proteinase activity, in comparison with IL-1-treated cells. We further observed that the increased proteinase activity correlated with an increase in the synthesis of collagenase/stromelysin proteins and a corresponding increase in the steady-state mRNA levels for both the enzymes. Studies on IL-1 receptor expression suggested that PDGF caused an increase in IL-1 receptor expression which, by augmenting the IL-1 response, may have led to the increase in proteinase induction. Analysis of proteoglycan synthesis confirmed that IL-1 reduced the incorporation of sulphated proteoglycan, aggrecan, into the extracellular matrix of chondrocytes, whereas PDGF stimulated it. However, cells treated with IL-1 + PDGF synthesized normal levels of aggrecan. This is in contrast with cells treated with IL-1 + fibroblast growth factor, in which case only proteinase activity was potentiated. The results allow us to conclude that (a) the two effector functions that play a role in matrix remodelling, namely matrix lysis (proteinase induction) and matrix repair (proteoglycan synthesis), occur via distinct pathways and (b) PDGF may play a crucial role in cartilage repair by initially causing matrix degradation followed by promoting new matrix synthesis. Images Figure 1 Figure 2 Figure 5 Figure 6 PMID:8503839

Column Subset Selection, Matrix Factorization, and Eigenvalue Optimization

DTIC Science & Technology

2008-07-01

Pietsch and Grothendieck, which are regarded as basic instruments in modern functional analysis [Pis86]. • The methods for computing these... Pietsch factorization and the maxcut semi- definite program [GW95]. 1.2. Overview. We focus on the algorithmic version of the Kashin–Tzafriri theorem...will see that the desired subset is exposed by factoring the random submatrix. This factorization, which was invented by Pietsch , is regarded as a basic

Verification of an acoustic transmission matrix analysis of sound propagation in a variable area duct without flow

NASA Technical Reports Server (NTRS)

Miles, J. H.

1981-01-01

A predicted standing wave pressure and phase angle profile for a hard wall rectangular duct with a region of converging-diverging area variation is compared to published experimental measurements in a study of sound propagation without flow. The factor of 1/2 area variation used is sufficient magnitude to produce large reflections. The prediction is based on a transmission matrix approach developed for the analysis of sound propagation in a variable area duct with and without flow. The agreement between the measured and predicted results is shown to be excellent.

LRP1 protects the vasculature by regulating levels of connective tissue growth factor and HtrA1.

PubMed

Muratoglu, Selen C; Belgrave, Shani; Hampton, Brian; Migliorini, Mary; Coksaygan, Turhan; Chen, Ling; Mikhailenko, Irina; Strickland, Dudley K

2013-09-01

Low-density lipoprotein receptor-related protein 1 (LRP1) is a large endocytic and signaling receptor that is abundant in vascular smooth muscle cells. Mice in which the lrp1 gene is deleted in smooth muscle cells (smLRP1(-/-)) on a low-density lipoprotein receptor-deficient background display excessive platelet derived growth factor-signaling, smooth muscle cell proliferation, aneurysm formation, and increased susceptibility to atherosclerosis. The objectives of the current study were to examine the potential of LRP1 to modulate vascular physiology under nonatherogenic conditions. We found smLRP1(-/-) mice to have extensive in vivo aortic dilatation accompanied by disorganized and degraded elastic lamina along with medial thickening of the arterial vessels resulting from excess matrix deposition. Surprisingly, this was not attributable to excessive platelet derived growth factor-signaling. Rather, quantitative differential proteomic analysis revealed that smLRP1(-/-) vessels contain a 4-fold increase in protein levels of high-temperature requirement factor A1 (HtrA1), which is a secreted serine protease that is known to degrade matrix components and to impair elastogenesis, resulting in fragmentation of elastic fibers. Importantly, our study discovered that HtrA1 is a novel LRP1 ligand. Proteomics analysis also identified excessive accumulation of connective tissue growth factor, an LRP1 ligand and a key mediator of fibrosis. Our findings suggest a critical role for LRP1 in maintaining the integrity of vessels by regulating protease activity as well as matrix deposition by modulating HtrA1 and connective tissue growth factor protein levels. This study highlights 2 new molecules, connective tissue growth factor and HtrA1, which contribute to detrimental changes in the vasculature and, therefore, represent new target molecules for potential therapeutic intervention to maintain vessel wall homeostasis.

Non-Abelian integrable hierarchies: matrix biorthogonal polynomials and perturbations

NASA Astrophysics Data System (ADS)

Ariznabarreta, Gerardo; García-Ardila, Juan C.; Mañas, Manuel; Marcellán, Francisco

2018-05-01

In this paper, Geronimus–Uvarov perturbations for matrix orthogonal polynomials on the real line are studied and then applied to the analysis of non-Abelian integrable hierarchies. The orthogonality is understood in full generality, i.e. in terms of a nondegenerate continuous sesquilinear form, determined by a quasidefinite matrix of bivariate generalized functions with a well-defined support. We derive Christoffel-type formulas that give the perturbed matrix biorthogonal polynomials and their norms in terms of the original ones. The keystone for this finding is the Gauss–Borel factorization of the Gram matrix. Geronimus–Uvarov transformations are considered in the context of the 2D non-Abelian Toda lattice and noncommutative KP hierarchies. The interplay between transformations and integrable flows is discussed. Miwa shifts, τ-ratio matrix functions and Sato formulas are given. Bilinear identities, involving Geronimus–Uvarov transformations, first for the Baker functions, then secondly for the biorthogonal polynomials and its second kind functions, and finally for the τ-ratio matrix functions, are found.

Nucleon electromagnetic form factors using lattice simulations at the physical point

NASA Astrophysics Data System (ADS)

Alexandrou, C.; Constantinou, M.; Hadjiyiannakou, K.; Jansen, K.; Kallidonis, Ch.; Koutsou, G.; Vaquero Aviles-Casco, A.

2017-08-01

We present results for the nucleon electromagnetic form factors using an ensemble of maximally twisted mass clover-improved fermions with pion mass of about 130 MeV. We use multiple sink-source separations and three analysis methods to probe ground-state dominance. We evaluate both the connected and disconnected contributions to the nucleon matrix elements. We find that the disconnected quark loop contributions to the isoscalar matrix elements are small, giving an upper bound of up to 2% of the connected and smaller than its statistical error. We present results for the isovector and isoscalar electric and magnetic Sachs form factors and the corresponding proton and neutron form factors. By fitting the momentum dependence of the form factors to a dipole form or to the z expansion, we extract the nucleon electric and magnetic radii, as well as the magnetic moment. We compare our results to experiment as well as to other recent lattice QCD calculations.

Fast iterative image reconstruction using sparse matrix factorization with GPU acceleration

NASA Astrophysics Data System (ADS)

Zhou, Jian; Qi, Jinyi

2011-03-01

Statistically based iterative approaches for image reconstruction have gained much attention in medical imaging. An accurate system matrix that defines the mapping from the image space to the data space is the key to high-resolution image reconstruction. However, an accurate system matrix is often associated with high computational cost and huge storage requirement. Here we present a method to address this problem by using sparse matrix factorization and parallel computing on a graphic processing unit (GPU).We factor the accurate system matrix into three sparse matrices: a sinogram blurring matrix, a geometric projection matrix, and an image blurring matrix. The sinogram blurring matrix models the detector response. The geometric projection matrix is based on a simple line integral model. The image blurring matrix is to compensate for the line-of-response (LOR) degradation due to the simplified geometric projection matrix. The geometric projection matrix is precomputed, while the sinogram and image blurring matrices are estimated by minimizing the difference between the factored system matrix and the original system matrix. The resulting factored system matrix has much less number of nonzero elements than the original system matrix and thus substantially reduces the storage and computation cost. The smaller size also allows an efficient implement of the forward and back projectors on GPUs, which have limited amount of memory. Our simulation studies show that the proposed method can dramatically reduce the computation cost of high-resolution iterative image reconstruction. The proposed technique is applicable to image reconstruction for different imaging modalities, including x-ray CT, PET, and SPECT.

On the Evaluation of Certain Multivariate Normal Probabilities.

DTIC Science & Technology

1982-08-12

a "single- factor matrix" in one context of factor analysis. In this case, we have (Pk 111 n 0# td i-i 2./- jwk+lI. where the sumation is taken over...is an equicorrelation matrix with p > 0, Pk Q k .j * ~sP (t)dt For c O, we have p(n) T, tn % td Pn = tht () 1 1 -pad (3)1 it is well known that pM2 CO...ZI,*.*.,±Zn_ 1 ± Zn) and proceed as above. Another situation for which combinatorial arguments are known are for t with a j = JAJ Vij. This t is

Examining significant factors in micro and small enterprises performance: case study in Amhara region, Ethiopia

NASA Astrophysics Data System (ADS)

Cherkos, Tomas; Zegeye, Muluken; Tilahun, Shimelis; Avvari, Muralidhar

2017-07-01

Furniture manufacturing micro and small enterprises are confronted with several factors that affect their performance. Some enterprises fail to sustain, some others remain for long period of time without transforming, and most are producing similar and non-standard products. The main aim of this manuscript is on improving the performance and contribution of MSEs by analyzing impact of significant internal and external factors. Data was collected via a questionnaire, group discussion with experts and interviewing process. Randomly selected eight representative main cities of Amhara region with 120 furniture manufacturing enterprises are considered. Data analysis and presentation was made using SPSS tools (correlation, proximity, and T test) and impact-effort analysis matrix tool. The correlation analysis shows that politico-legal with infrastructure, leadership with entrepreneurship skills and finance and credit with marketing factors are those factors, which result in high correlation with Pearson correlation values of r = 0.988, 0.983, and 0.939, respectively. The study investigates that the most critical factors faced by MSEs are work premises, access to finance, infrastructure, entrepreneurship and business managerial problems. The impact of these factors is found to be high and is confirmed by the 50% drop-out rate in 2014/2015. Furthermore, more than 25% work time losses due to power interruption daily and around 65% work premises problems challenged MSEs. Further, an impact-effort matrix was developed to help the MSEs to prioritize the affecting factors.

Examining significant factors in micro and small enterprises performance: case study in Amhara region, Ethiopia

NASA Astrophysics Data System (ADS)

Cherkos, Tomas; Zegeye, Muluken; Tilahun, Shimelis; Avvari, Muralidhar

2018-07-01

Furniture manufacturing micro and small enterprises are confronted with several factors that affect their performance. Some enterprises fail to sustain, some others remain for long period of time without transforming, and most are producing similar and non-standard products. The main aim of this manuscript is on improving the performance and contribution of MSEs by analyzing impact of significant internal and external factors. Data was collected via a questionnaire, group discussion with experts and interviewing process. Randomly selected eight representative main cities of Amhara region with 120 furniture manufacturing enterprises are considered. Data analysis and presentation was made using SPSS tools (correlation, proximity, and T test) and impact-effort analysis matrix tool. The correlation analysis shows that politico-legal with infrastructure, leadership with entrepreneurship skills and finance and credit with marketing factors are those factors, which result in high correlation with Pearson correlation values of r = 0.988, 0.983, and 0.939, respectively. The study investigates that the most critical factors faced by MSEs are work premises, access to finance, infrastructure, entrepreneurship and business managerial problems. The impact of these factors is found to be high and is confirmed by the 50% drop-out rate in 2014/2015. Furthermore, more than 25% work time losses due to power interruption daily and around 65% work premises problems challenged MSEs. Further, an impact-effort matrix was developed to help the MSEs to prioritize the affecting factors.

Efficient multitasking of Choleski matrix factorization on CRAY supercomputers

NASA Technical Reports Server (NTRS)

Overman, Andrea L.; Poole, Eugene L.

1991-01-01

A Choleski method is described and used to solve linear systems of equations that arise in large scale structural analysis. The method uses a novel variable-band storage scheme and is structured to exploit fast local memory caches while minimizing data access delays between main memory and vector registers. Several parallel implementations of this method are described for the CRAY-2 and CRAY Y-MP computers demonstrating the use of microtasking and autotasking directives. A portable parallel language, FORCE, is used for comparison with the microtasked and autotasked implementations. Results are presented comparing the matrix factorization times for three representative structural analysis problems from runs made in both dedicated and multi-user modes on both computers. CPU and wall clock timings are given for the parallel implementations and are compared to single processor timings of the same algorithm.

Prognostic impact of a compartment-specific angiogenic marker profile in patients with pancreatic cancer.

PubMed

Kahlert, Christoph; Fiala, Maria; Musso, Gabriel; Halama, Niels; Keim, Sophia; Mazzone, Massimiliano; Lasitschka, Felix; Pecqueux, Mathieu; Klupp, Fee; Schmidt, Thomas; Rahbari, Nuh; Schölch, Sebastian; Pilarsky, Christian; Ulrich, Alexis; Schneider, Martin; Weitz, Juergen; Koch, Moritz

2014-12-30

Pancreatic cancer consists of a heterogenous bulk of tumor cells and stroma cells which contribute to tumor progression by releasing angiogenic factors. Those factors can be detected as circulating serum factors. We performed a compartment-specific analysis of tumor-derived and stroma-derived angiogenic factors to identify biomarkers and molecular targets for the treatment of pancreatic cancer. Kryo-frozen tissue from primary ductal adenocarcinomas (n = 51) was laser-microdissected to isolate tumor and stroma tissue. Expression of 17 angiogenic factors (angiopoietin-2, follistatin, GCSF, HGF, interleukin-8, leptin, PDGF-BB, PECAM-1, VEGF, matrix metalloproteinase -1, -2, -3, -7, -9, -10, -12, and -13) was analyzed using a multiplex elisa assay for tissue-derived proteins and corresponding serum. Our study reveals a compartment-specific expression profile for several angiogenic factors and matrix metalloproteinases. ROC analysis of corresponding serum samples reveals MMP-7 and MMP-12 as strong classifiers for the diagnosis of patients with pancreatic cancer vs. healthy control donors. High expression of tumor-derived PDGF-BB and MMP-1 correlates with prolonged survival in univariate and multivariate analysis. In conclusion, a distinct expression patterns for angiogenic cytokines and MMPs in pancreatic cancer and surrounding stroma may implicate them as novel targets for cancer treatment. Tumor-derived PDGF-BB and MMP-1 are significant and independent prognostic markers for poor survival.

Finding Imaging Patterns of Structural Covariance via Non-Negative Matrix Factorization

PubMed Central

Sotiras, Aristeidis; Resnick, Susan M.; Davatzikos, Christos

2015-01-01

In this paper, we investigate the use of Non-Negative Matrix Factorization (NNMF) for the analysis of structural neuroimaging data. The goal is to identify the brain regions that co-vary across individuals in a consistent way, hence potentially being part of underlying brain networks or otherwise influenced by underlying common mechanisms such as genetics and pathologies. NNMF offers a directly data-driven way of extracting relatively localized co-varying structural regions, thereby transcending limitations of Principal Component Analysis (PCA), Independent Component Analysis (ICA) and other related methods that tend to produce dispersed components of positive and negative loadings. In particular, leveraging upon the well known ability of NNMF to produce parts-based representations of image data, we derive decompositions that partition the brain into regions that vary in consistent ways across individuals. Importantly, these decompositions achieve dimensionality reduction via highly interpretable ways and generalize well to new data as shown via split-sample experiments. We empirically validate NNMF in two data sets: i) a Diffusion Tensor (DT) mouse brain development study, and ii) a structural Magnetic Resonance (sMR) study of human brain aging. We demonstrate the ability of NNMF to produce sparse parts-based representations of the data at various resolutions. These representations seem to follow what we know about the underlying functional organization of the brain and also capture some pathological processes. Moreover, we show that these low dimensional representations favorably compare to descriptions obtained with more commonly used matrix factorization methods like PCA and ICA. PMID:25497684

Regular approximate factorization of a class of matrix-function with an unstable set of partial indices

PubMed Central

Rogosin, S.

2018-01-01

From the classic work of Gohberg & Krein (1958 Uspekhi Mat. Nauk. XIII, 3–72. (Russian).), it is well known that the set of partial indices of a non-singular matrix function may change depending on the properties of the original matrix. More precisely, it was shown that if the difference between the largest and the smallest partial indices is larger than unity then, in any neighbourhood of the original matrix function, there exists another matrix function possessing a different set of partial indices. As a result, the factorization of matrix functions, being an extremely difficult process itself even in the case of the canonical factorization, remains unresolvable or even questionable in the case of a non-stable set of partial indices. Such a situation, in turn, has became an unavoidable obstacle to the application of the factorization technique. This paper sets out to answer a less ambitious question than that of effective factorizing matrix functions with non-stable sets of partial indices, and instead focuses on determining the conditions which, when having known factorization of the limiting matrix function, allow to construct another family of matrix functions with the same origin that preserves the non-stable partial indices and is close to the original set of the matrix functions. PMID:29434502

Regular approximate factorization of a class of matrix-function with an unstable set of partial indices.

PubMed

Mishuris, G; Rogosin, S

2018-01-01

From the classic work of Gohberg & Krein (1958 Uspekhi Mat. Nauk. XIII , 3-72. (Russian).), it is well known that the set of partial indices of a non-singular matrix function may change depending on the properties of the original matrix. More precisely, it was shown that if the difference between the largest and the smallest partial indices is larger than unity then, in any neighbourhood of the original matrix function, there exists another matrix function possessing a different set of partial indices. As a result, the factorization of matrix functions, being an extremely difficult process itself even in the case of the canonical factorization, remains unresolvable or even questionable in the case of a non-stable set of partial indices. Such a situation, in turn, has became an unavoidable obstacle to the application of the factorization technique. This paper sets out to answer a less ambitious question than that of effective factorizing matrix functions with non-stable sets of partial indices, and instead focuses on determining the conditions which, when having known factorization of the limiting matrix function, allow to construct another family of matrix functions with the same origin that preserves the non-stable partial indices and is close to the original set of the matrix functions.

METCAN-PC - METAL MATRIX COMPOSITE ANALYZER

NASA Technical Reports Server (NTRS)

Murthy, P. L.

1994-01-01

High temperature metal matrix composites offer great potential for use in advanced aerospace structural applications. The realization of this potential however, requires concurrent developments in (1) a technology base for fabricating high temperature metal matrix composite structural components, (2) experimental techniques for measuring their thermal and mechanical characteristics, and (3) computational methods to predict their behavior. METCAN (METal matrix Composite ANalyzer) is a computer program developed to predict this behavior. METCAN can be used to computationally simulate the non-linear behavior of high temperature metal matrix composites (HT-MMC), thus allowing the potential payoff for the specific application to be assessed. It provides a comprehensive analysis of composite thermal and mechanical performance. METCAN treats material nonlinearity at the constituent (fiber, matrix, and interphase) level, where the behavior of each constituent is modeled accounting for time-temperature-stress dependence. The composite properties are synthesized from the constituent instantaneous properties by making use of composite micromechanics and macromechanics. Factors which affect the behavior of the composite properties include the fabrication process variables, the fiber and matrix properties, the bonding between the fiber and matrix and/or the properties of the interphase between the fiber and matrix. The METCAN simulation is performed as point-wise analysis and produces composite properties which are readily incorporated into a finite element code to perform a global structural analysis. After the global structural analysis is performed, METCAN decomposes the composite properties back into the localized response at the various levels of the simulation. At this point the constituent properties are updated and the next iteration in the analysis is initiated. This cyclic procedure is referred to as the integrated approach to metal matrix composite analysis. METCAN-PC is written in FORTRAN 77 for IBM PC series and compatible computers running MS-DOS. An 80286 machine with an 80287 math co-processor is required for execution. The executable requires at least 640K of RAM and DOS 3.1 or higher. The package includes sample executables which were compiled under Microsoft FORTRAN v. 5.1. The standard distribution medium for this program is one 5.25 inch 360K MS-DOS format diskette. The contents of the diskette are compressed using the PKWARE archiving tools. The utility to unarchive the files, PKUNZIP.EXE, is included. METCAN-PC was developed in 1992.

The Circumplex Pattern of the Life Styles Inventory: A Reanalysis.

ERIC Educational Resources Information Center

Levin, Joseph

1991-01-01

A reanalysis of the intercorrelation matrix from a principal components analysis of the Life Styles Inventory was conducted using a Canadian sample. Using nonmetric multidimensional scaling, analyses show an almost perfect circumplex pattern. Results illustrate the inadequacy of factor analytic procedures for the analysis and representation of a…

Evaluating the MSCEIT V2.0 via CFA: comment on Mayer et al. (2003).

PubMed

Gignac, Gilles E

2005-06-01

This investigation uncovered several substantial errors in the confirmatory factor analysis results reported by J. D. Mayer, P. Salovey, D. R. Caruso, and G. Sitarenios (see record 2003-02341-015). Specifically, the values associated with the close-fit indices (normed fit index, Tucker-Lewis Index, and root-mean-square error of approximation) are inaccurate. A reanalysis of the Mayer et al. subscale intercorrelation matrix provided accurate values of the close-fit indices, which resulted in different evaluations of the models tested by J. D. Mayer et al. Contrary to J. D. Mayer et al., the 1-factor model and the 2-factor model did not provide good fit. Although the 4-factor model was still considered good fitting, the non-constrained 4-factor model yielded a non-positive definite matrix, which was interpreted to be due to the fact that two of the branch-level factors (Perceiving and Facilitating) were collinear, suggesting that a model with 4 factors was implausible.

Computing row and column counts for sparse QR and LU factorization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gilbert, John R.; Li, Xiaoye S.; Ng, Esmond G.

2001-01-01

We present algorithms to determine the number of nonzeros in each row and column of the factors of a sparse matrix, for both the QR factorization and the LU factorization with partial pivoting. The algorithms use only the nonzero structure of the input matrix, and run in time nearly linear in the number of nonzeros in that matrix. They may be used to set up data structures or schedule parallel operations in advance of the numerical factorization. The row and column counts we compute are upper bounds on the actual counts. If the input matrix is strong Hall and theremore » is no coincidental numerical cancellation, the counts are exact for QR factorization and are the tightest bounds possible for LU factorization. These algorithms are based on our earlier work on computing row and column counts for sparse Cholesky factorization, plus an efficient method to compute the column elimination tree of a sparse matrix without explicitly forming the product of the matrix and its transpose.« less

a Migration Well Model for the Binding of Ligands to Heme Proteins.

NASA Astrophysics Data System (ADS)

Beece, Daniel Kenneth

The binding of carbon monoxide and dioxygen to heme proteins can be viewed as occurring in distinct stages: diffusion in the solvent, migration through the matrix, and occupation of the pocket before the final binding step. A model is presented which can explain the dominant kinetic behavior of several different heme protein-ligand systems. The model assumes that a ligand molecule in the solvent sequentially encounters discrete energy barriers on the way to the binding site. The rate to surmount each barrier is distributed, except for the pseudofirst order rate corresponding to the step into the protein from the solvent. The migration through the matrix is equivalent to a small number of distinct jumps. Quantitative analysis of the data permit estimates of the barrier heights, preexponentials and solvent coupling factors for each rate. A migration coefficient and a matrix occupation factor are defined.

GC[Formula: see text]NMF: A Novel Matrix Factorization Framework for Gene-Phenotype Association Prediction.

PubMed

Zhang, Yaogong; Liu, Jiahui; Liu, Xiaohu; Hong, Yuxiang; Fan, Xin; Huang, Yalou; Wang, Yuan; Xie, Maoqiang

2018-04-24

Gene-phenotype association prediction can be applied to reveal the inherited basis of human diseases and facilitate drug development. Gene-phenotype associations are related to complex biological processes and influenced by various factors, such as relationship between phenotypes and that among genes. While due to sparseness of curated gene-phenotype associations and lack of integrated analysis of the joint effect of multiple factors, existing applications are limited to prediction accuracy and potential gene-phenotype association detection. In this paper, we propose a novel method by exploiting weighted graph constraint learned from hierarchical structures of phenotype data and group prior information among genes by inheriting advantages of Non-negative Matrix Factorization (NMF), called Weighted Graph Constraint and Group Centric Non-negative Matrix Factorization (GC[Formula: see text]NMF). Specifically, first we introduce the depth of parent-child relationships between two adjacent phenotypes in hierarchical phenotypic data as weighted graph constraint for a better phenotype understanding. Second, we utilize intra-group correlation among genes in a gene group as group constraint for gene understanding. Such information provides us with the intuition that genes in a group probably result in similar phenotypes. The model not only allows us to achieve a high-grade prediction performance, but also helps us to learn interpretable representation of genes and phenotypes simultaneously to facilitate future biological analysis. Experimental results on biological gene-phenotype association datasets of mouse and human demonstrate that GC[Formula: see text]NMF can obtain superior prediction accuracy and good understandability for biological explanation over other state-of-the-arts methods.

Population clustering based on copy number variations detected from next generation sequencing data.

PubMed

Duan, Junbo; Zhang, Ji-Gang; Wan, Mingxi; Deng, Hong-Wen; Wang, Yu-Ping

2014-08-01

Copy number variations (CNVs) can be used as significant bio-markers and next generation sequencing (NGS) provides a high resolution detection of these CNVs. But how to extract features from CNVs and further apply them to genomic studies such as population clustering have become a big challenge. In this paper, we propose a novel method for population clustering based on CNVs from NGS. First, CNVs are extracted from each sample to form a feature matrix. Then, this feature matrix is decomposed into the source matrix and weight matrix with non-negative matrix factorization (NMF). The source matrix consists of common CNVs that are shared by all the samples from the same group, and the weight matrix indicates the corresponding level of CNVs from each sample. Therefore, using NMF of CNVs one can differentiate samples from different ethnic groups, i.e. population clustering. To validate the approach, we applied it to the analysis of both simulation data and two real data set from the 1000 Genomes Project. The results on simulation data demonstrate that the proposed method can recover the true common CNVs with high quality. The results on the first real data analysis show that the proposed method can cluster two family trio with different ancestries into two ethnic groups and the results on the second real data analysis show that the proposed method can be applied to the whole-genome with large sample size consisting of multiple groups. Both results demonstrate the potential of the proposed method for population clustering.

Apparatus and method for quantitative assay of samples of transuranic waste contained in barrels in the presence of matrix material

DOEpatents

Caldwell, J.T.; Herrera, G.C.; Hastings, R.D.; Shunk, E.R.; Kunz, W.E.

1987-08-28

Apparatus and method for performing corrections for matrix material effects on the neutron measurements generated from analysis of transuranic waste drums using the differential-dieaway technique. By measuring the absorption index and the moderator index for a particular drum, correction factors can be determined for the effects of matrix materials on the ''observed'' quantity of fissile and fertile material present therein in order to determine the actual assays thereof. A barrel flux monitor is introduced into the measurement chamber to accomplish these measurements as a new contribution to the differential-dieaway technology. 9 figs.

The R-matrix investigation of 8Li(α, n)11B reaction below 6 MeV

NASA Astrophysics Data System (ADS)

Kilic, Ali Ihsan; Muecher, Dennis; Garret, Paul; Svensson, Carl

2017-09-01

The investigation of cross sections for the 8Li(α, n)11B reaction has important impact for both primordial nucleosynthesis in the inhomogeneous models as well as constraining the physical conditions characterizing the r-process. However, there are large discrepancies existing between inclusive and exclusive measurements of the cross section below 3 MeV. The R-Matrix technique is a powerful tool for the analysis of the nuclear data for the purpose of extracting level information of compound nucleus 12B and extrapolation of the astrophysical S-Factor to Gamow energies. We have applied the R-matrix calculations for the 8Li(α, n)11B reaction and will present results for both the reaction rates and the partial S-factor. Combining the direct reaction contribution with the results from our R-matrix calculations, we can well describe the experimental data from the inclusive measurements. However, new experiments are needed in order to understand the role of neutron detection close to the threshold, for which we describe our experimental plans at ISAC, TRIUMF, using the newly developed DESCANT array.

Efficient system modeling for a small animal PET scanner with tapered DOI detectors.

PubMed

Zhang, Mengxi; Zhou, Jian; Yang, Yongfeng; Rodríguez-Villafuerte, Mercedes; Qi, Jinyi

2016-01-21

A prototype small animal positron emission tomography (PET) scanner for mouse brain imaging has been developed at UC Davis. The new scanner uses tapered detector arrays with depth of interaction (DOI) measurement. In this paper, we present an efficient system model for the tapered PET scanner using matrix factorization and a virtual scanner geometry. The factored system matrix mainly consists of two components: a sinogram blurring matrix and a geometrical matrix. The geometric matrix is based on a virtual scanner geometry. The sinogram blurring matrix is estimated by matrix factorization. We investigate the performance of different virtual scanner geometries. Both simulation study and real data experiments are performed in the fully 3D mode to study the image quality under different system models. The results indicate that the proposed matrix factorization can maintain image quality while substantially reduce the image reconstruction time and system matrix storage cost. The proposed method can be also applied to other PET scanners with DOI measurement.

Solid matrix transformation and tracer addition using molten ammonium bifluoride salt as a sample preparation method for laser ablation inductively coupled plasma mass spectrometry.

PubMed

Grate, Jay W; Gonzalez, Jhanis J; O'Hara, Matthew J; Kellogg, Cynthia M; Morrison, Samuel S; Koppenaal, David W; Chan, George C-Y; Mao, Xianglei; Zorba, Vassilia; Russo, Richard E

2017-09-08

Solid sampling and analysis methods, such as laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS), are challenged by matrix effects and calibration difficulties. Matrix-matched standards for external calibration are seldom available and it is difficult to distribute spikes evenly into a solid matrix as internal standards. While isotopic ratios of the same element can be measured to high precision, matrix-dependent effects in the sampling and analysis process frustrate accurate quantification and elemental ratio determinations. Here we introduce a potentially general solid matrix transformation approach entailing chemical reactions in molten ammonium bifluoride (ABF) salt that enables the introduction of spikes as tracers or internal standards. Proof of principle experiments show that the decomposition of uranium ore in sealed PFA fluoropolymer vials at 230 °C yields, after cooling, new solids suitable for direct solid sampling by LA. When spikes are included in the molten salt reaction, subsequent LA-ICP-MS sampling at several spots indicate that the spikes are evenly distributed, and that U-235 tracer dramatically improves reproducibility in U-238 analysis. Precisions improved from 17% relative standard deviation for U-238 signals to 0.1% for the ratio of sample U-238 to spiked U-235, a factor of over two orders of magnitude. These results introduce the concept of solid matrix transformation (SMT) using ABF, and provide proof of principle for a new method of incorporating internal standards into a solid for LA-ICP-MS. This new approach, SMT-LA-ICP-MS, provides opportunities to improve calibration and quantification in solids based analysis. Looking forward, tracer addition to transformed solids opens up LA-based methods to analytical methodologies such as standard addition, isotope dilution, preparation of matrix-matched solid standards, external calibration, and monitoring instrument drift against external calibration standards.

The Shock and Vibration Digest. Volume 16, Number 1

DTIC Science & Technology

1984-01-01

investigation of the measure- ment of frequency band average loss factors of structural components for use in the statistical energy analysis method of...stiffness. Matrix methods Key Words: Finite element technique. Statistical energy analysis . Experimental techniques. Framed structures, Com- puter...programs In order to further understand the practical application of the statistical energy analysis , a two section plate-like frame structure is

Phase diagram of matrix compressed sensing

NASA Astrophysics Data System (ADS)

Schülke, Christophe; Schniter, Philip; Zdeborová, Lenka

2016-12-01

In the problem of matrix compressed sensing, we aim to recover a low-rank matrix from a few noisy linear measurements. In this contribution, we analyze the asymptotic performance of a Bayes-optimal inference procedure for a model where the matrix to be recovered is a product of random matrices. The results that we obtain using the replica method describe the state evolution of the Parametric Bilinear Generalized Approximate Message Passing (P-BiG-AMP) algorithm, recently introduced in J. T. Parker and P. Schniter [IEEE J. Select. Top. Signal Process. 10, 795 (2016), 10.1109/JSTSP.2016.2539123]. We show the existence of two different types of phase transition and their implications for the solvability of the problem, and we compare the results of our theoretical analysis to the numerical performance reached by P-BiG-AMP. Remarkably, the asymptotic replica equations for matrix compressed sensing are the same as those for a related but formally different problem of matrix factorization.

Spin-1 Particles and Perturbative QCD

NASA Astrophysics Data System (ADS)

de Melo, J. P. B. C.; Frederico, T.; Ji, Chueng-Ryong

2018-07-01

Due to the angular condition in the light-front dynamics (LFD), the extraction of the electromagnetic form factors for spin-1 particles can be uniquely determined taking into account implicitly non-valence and/or the zero-mode contributions to the matrix elements of the electromagnetic current. No matter which matrix elements of the electromagnetic current is used to extract the electromagnetic form factors, the same unique result is obtained. As physical observables, the electromagnetic form factors obtained from matrix elements of the current in LFD must be equal to those obtained in the instant form calculations. Recently, the Babar collaboration (Phys Rev D 78:071103, 2008) has analyzed the reaction e^+ + e^-→ ρ ^+ + ρ ^- at √{s}=10.58 GeV to measure the cross section as well as the ratios of the helicity amplitudes F_{λ 'λ }. We present our recent analysis of the Babar data for the rho meson considering the angular condition in LFD to put a stringent test on the onset of asymptotic perturbative QCD and predict the energy regime where the subleading contributions are still considerable.

THz spectral data analysis and components unmixing based on non-negative matrix factorization methods

NASA Astrophysics Data System (ADS)

Ma, Yehao; Li, Xian; Huang, Pingjie; Hou, Dibo; Wang, Qiang; Zhang, Guangxin

2017-04-01

In many situations the THz spectroscopic data observed from complex samples represent the integrated result of several interrelated variables or feature components acting together. The actual information contained in the original data might be overlapping and there is a necessity to investigate various approaches for model reduction and data unmixing. The development and use of low-rank approximate nonnegative matrix factorization (NMF) and smooth constraint NMF (CNMF) algorithms for feature components extraction and identification in the fields of terahertz time domain spectroscopy (THz-TDS) data analysis are presented. The evolution and convergence properties of NMF and CNMF methods based on sparseness, independence and smoothness constraints for the resulting nonnegative matrix factors are discussed. For general NMF, its cost function is nonconvex and the result is usually susceptible to initialization and noise corruption, and may fall into local minima and lead to unstable decomposition. To reduce these drawbacks, smoothness constraint is introduced to enhance the performance of NMF. The proposed algorithms are evaluated by several THz-TDS data decomposition experiments including a binary system and a ternary system simulating some applications such as medicine tablet inspection. Results show that CNMF is more capable of finding optimal solutions and more robust for random initialization in contrast to NMF. The investigated method is promising for THz data resolution contributing to unknown mixture identification.

Genetic Background is a Key Determinant of Glomerular Extracellular Matrix Composition and Organization

PubMed Central

Randles, Michael J.; Woolf, Adrian S.; Huang, Jennifer L.; Byron, Adam; Humphries, Jonathan D.; Price, Karen L.; Kolatsi-Joannou, Maria; Collinson, Sophie; Denny, Thomas; Knight, David; Mironov, Aleksandr; Starborg, Toby; Korstanje, Ron; Humphries, Martin J.; Long, David A.

2015-01-01

Glomerular disease often features altered histologic patterns of extracellular matrix (ECM). Despite this, the potential complexities of the glomerular ECM in both health and disease are poorly understood. To explore whether genetic background and sex determine glomerular ECM composition, we investigated two mouse strains, FVB and B6, using RNA microarrays of isolated glomeruli combined with proteomic glomerular ECM analyses. These studies, undertaken in healthy young adult animals, revealed unique strain- and sex-dependent glomerular ECM signatures, which correlated with variations in levels of albuminuria and known predisposition to progressive nephropathy. Among the variation, we observed changes in netrin 4, fibroblast growth factor 2, tenascin C, collagen 1, meprin 1-α, and meprin 1-β. Differences in protein abundance were validated by quantitative immunohistochemistry and Western blot analysis, and the collective differences were not explained by mutations in known ECM or glomerular disease genes. Within the distinct signatures, we discovered a core set of structural ECM proteins that form multiple protein–protein interactions and are conserved from mouse to man. Furthermore, we found striking ultrastructural changes in glomerular basement membranes in FVB mice. Pathway analysis of merged transcriptomic and proteomic datasets identified potential ECM regulatory pathways involving inhibition of matrix metalloproteases, liver X receptor/retinoid X receptor, nuclear factor erythroid 2-related factor 2, notch, and cyclin-dependent kinase 5. These pathways may therefore alter ECM and confer susceptibility to disease. PMID:25896609

THz spectral data analysis and components unmixing based on non-negative matrix factorization methods.

PubMed

Ma, Yehao; Li, Xian; Huang, Pingjie; Hou, Dibo; Wang, Qiang; Zhang, Guangxin

2017-04-15

In many situations the THz spectroscopic data observed from complex samples represent the integrated result of several interrelated variables or feature components acting together. The actual information contained in the original data might be overlapping and there is a necessity to investigate various approaches for model reduction and data unmixing. The development and use of low-rank approximate nonnegative matrix factorization (NMF) and smooth constraint NMF (CNMF) algorithms for feature components extraction and identification in the fields of terahertz time domain spectroscopy (THz-TDS) data analysis are presented. The evolution and convergence properties of NMF and CNMF methods based on sparseness, independence and smoothness constraints for the resulting nonnegative matrix factors are discussed. For general NMF, its cost function is nonconvex and the result is usually susceptible to initialization and noise corruption, and may fall into local minima and lead to unstable decomposition. To reduce these drawbacks, smoothness constraint is introduced to enhance the performance of NMF. The proposed algorithms are evaluated by several THz-TDS data decomposition experiments including a binary system and a ternary system simulating some applications such as medicine tablet inspection. Results show that CNMF is more capable of finding optimal solutions and more robust for random initialization in contrast to NMF. The investigated method is promising for THz data resolution contributing to unknown mixture identification. Copyright © 2017 Elsevier B.V. All rights reserved.

A methodology to predict damage initiation, damage growth and residual strength in titanium matrix composites

NASA Technical Reports Server (NTRS)

Bakuckas, J. G., Jr.; Johnson, W. S.

1994-01-01

In this research, a methodology to predict damage initiation, damage growth, fatigue life, and residual strength in titanium matrix composites (TMC) is outlined. Emphasis was placed on micromechanics-based engineering approaches. Damage initiation was predicted using a local effective strain approach. A finite element analysis verified the prevailing assumptions made in the formulation of this model. Damage growth, namely, fiber-bridged matrix crack growth, was evaluated using a fiber bridging (FB) model which accounts for thermal residual stresses. This model combines continuum fracture mechanics and micromechanics analyses yielding stress-intensity factor solutions for fiber-bridged matrix cracks. It is assumed in the FB model that fibers in the wake of the matrix crack are idealized as a closure pressure, and an unknown constant frictional shear stress is assumed to act along the debond length of the bridging fibers. This frictional shear stress was used as a curve fitting parameter to the available experimental data. Fatigue life and post-fatigue residual strength were predicted based on the axial stress in the first intact 0 degree fiber calculated using the FB model and a three-dimensional finite element analysis.

The multifacet graphically contracted function method. I. Formulation and implementation

NASA Astrophysics Data System (ADS)

Shepard, Ron; Gidofalvi, Gergely; Brozell, Scott R.

2014-08-01

The basic formulation for the multifacet generalization of the graphically contracted function (MFGCF) electronic structure method is presented. The analysis includes the discussion of linear dependency and redundancy of the arc factor parameters, the computation of reduced density matrices, Hamiltonian matrix construction, spin-density matrix construction, the computation of optimization gradients for single-state and state-averaged calculations, graphical wave function analysis, and the efficient computation of configuration state function and Slater determinant expansion coefficients. Timings are given for Hamiltonian matrix element and analytic optimization gradient computations for a range of model problems for full-CI Shavitt graphs, and it is observed that both the energy and the gradient computation scale as O(N2n4) for N electrons and n orbitals. The important arithmetic operations are within dense matrix-matrix product computational kernels, resulting in a computationally efficient procedure. An initial implementation of the method is used to present applications to several challenging chemical systems, including N2 dissociation, cubic H8 dissociation, the symmetric dissociation of H2O, and the insertion of Be into H2. The results are compared to the exact full-CI values and also to those of the previous single-facet GCF expansion form.

The multifacet graphically contracted function method. I. Formulation and implementation.

PubMed

Shepard, Ron; Gidofalvi, Gergely; Brozell, Scott R

2014-08-14

The basic formulation for the multifacet generalization of the graphically contracted function (MFGCF) electronic structure method is presented. The analysis includes the discussion of linear dependency and redundancy of the arc factor parameters, the computation of reduced density matrices, Hamiltonian matrix construction, spin-density matrix construction, the computation of optimization gradients for single-state and state-averaged calculations, graphical wave function analysis, and the efficient computation of configuration state function and Slater determinant expansion coefficients. Timings are given for Hamiltonian matrix element and analytic optimization gradient computations for a range of model problems for full-CI Shavitt graphs, and it is observed that both the energy and the gradient computation scale as O(N(2)n(4)) for N electrons and n orbitals. The important arithmetic operations are within dense matrix-matrix product computational kernels, resulting in a computationally efficient procedure. An initial implementation of the method is used to present applications to several challenging chemical systems, including N2 dissociation, cubic H8 dissociation, the symmetric dissociation of H2O, and the insertion of Be into H2. The results are compared to the exact full-CI values and also to those of the previous single-facet GCF expansion form.

Dynamics of fractional condensation of a substance on a probe for spectral analysis

NASA Astrophysics Data System (ADS)

Zakharov, Yu. A.; Kokorina, O. B.; Lysogorskiĭ, Yu. V.; Sevastianov, A. A.

2008-11-01

The fractional separation of trace metals on a cold tungsten probe from salt matrix vapor, which interferes with the spectral analysis, is studied. The spatial structure of the vapor flows of sodium chloride, potassium sulfate, and indium atoms is visualized at characteristic wavelengths as they interact with the probe. The vapor flow rate and the probe orientation were varied. It is found that the smoke of the matrix does not prevent the deposition of the metal on the probe because of spatial separation of these fractions and that the detrimental effect of thermal gas expansion and other factors is eliminated. The sensitivity of the atomic absorption analysis of indium impurities in these salts is increased by an order of magnitude.

Students' proficiency scores within multitrait item response theory

NASA Astrophysics Data System (ADS)

Scott, Terry F.; Schumayer, Daniel

2015-12-01

In this paper we present a series of item response models of data collected using the Force Concept Inventory. The Force Concept Inventory (FCI) was designed to poll the Newtonian conception of force viewed as a multidimensional concept, that is, as a complex of distinguishable conceptual dimensions. Several previous studies have developed single-trait item response models of FCI data; however, we feel that multidimensional models are also appropriate given the explicitly multidimensional design of the inventory. The models employed in the research reported here vary in both the number of fitting parameters and the number of underlying latent traits assumed. We calculate several model information statistics to ensure adequate model fit and to determine which of the models provides the optimal balance of information and parsimony. Our analysis indicates that all item response models tested, from the single-trait Rasch model through to a model with ten latent traits, satisfy the standard requirements of fit. However, analysis of model information criteria indicates that the five-trait model is optimal. We note that an earlier factor analysis of the same FCI data also led to a five-factor model. Furthermore the factors in our previous study and the traits identified in the current work match each other well. The optimal five-trait model assigns proficiency scores to all respondents for each of the five traits. We construct a correlation matrix between the proficiencies in each of these traits. This correlation matrix shows strong correlations between some proficiencies, and strong anticorrelations between others. We present an interpretation of this correlation matrix.

Finding imaging patterns of structural covariance via Non-Negative Matrix Factorization.

PubMed

Sotiras, Aristeidis; Resnick, Susan M; Davatzikos, Christos

2015-03-01

In this paper, we investigate the use of Non-Negative Matrix Factorization (NNMF) for the analysis of structural neuroimaging data. The goal is to identify the brain regions that co-vary across individuals in a consistent way, hence potentially being part of underlying brain networks or otherwise influenced by underlying common mechanisms such as genetics and pathologies. NNMF offers a directly data-driven way of extracting relatively localized co-varying structural regions, thereby transcending limitations of Principal Component Analysis (PCA), Independent Component Analysis (ICA) and other related methods that tend to produce dispersed components of positive and negative loadings. In particular, leveraging upon the well known ability of NNMF to produce parts-based representations of image data, we derive decompositions that partition the brain into regions that vary in consistent ways across individuals. Importantly, these decompositions achieve dimensionality reduction via highly interpretable ways and generalize well to new data as shown via split-sample experiments. We empirically validate NNMF in two data sets: i) a Diffusion Tensor (DT) mouse brain development study, and ii) a structural Magnetic Resonance (sMR) study of human brain aging. We demonstrate the ability of NNMF to produce sparse parts-based representations of the data at various resolutions. These representations seem to follow what we know about the underlying functional organization of the brain and also capture some pathological processes. Moreover, we show that these low dimensional representations favorably compare to descriptions obtained with more commonly used matrix factorization methods like PCA and ICA. Copyright © 2014 Elsevier Inc. All rights reserved.

Exploring syndrome differentiation using non-negative matrix factorization and cluster analysis in patients with atopic dermatitis.

PubMed

Yun, Younghee; Jung, Wonmo; Kim, Hyunho; Jang, Bo-Hyoung; Kim, Min-Hee; Noh, Jiseong; Ko, Seong-Gyu; Choi, Inhwa

2017-08-01

Syndrome differentiation (SD) results in a diagnostic conclusion based on a cluster of concurrent symptoms and signs, including pulse form and tongue color. In Korea, there is a strong interest in the standardization of Traditional Medicine (TM). In order to standardize TM treatment, standardization of SD should be given priority. The aim of this study was to explore the SD, or symptom clusters, of patients with atopic dermatitis (AD) using non-negative factorization methods and k-means clustering analysis. We screened 80 patients and enrolled 73 eligible patients. One TM dermatologist evaluated the symptoms/signs using an existing clinical dataset from patients with AD. This dataset was designed to collect 15 dermatologic and 18 systemic symptoms/signs associated with AD. Non-negative matrix factorization was used to decompose the original data into a matrix with three features and a weight matrix. The point of intersection of the three coordinates from each patient was placed in three-dimensional space. With five clusters, the silhouette score reached 0.484, and this was the best silhouette score obtained from two to nine clusters. Patients were clustered according to the varying severity of concurrent symptoms/signs. Through the distribution of the null hypothesis generated by 10,000 permutation tests, we found significant cluster-specific symptoms/signs from the confidence intervals in the upper and lower 2.5% of the distribution. Patients in each cluster showed differences in symptoms/signs and severity. In a clinical situation, SD and treatment are based on the practitioners' observations and clinical experience. SD, identified through informatics, can contribute to development of standardized, objective, and consistent SD for each disease. Copyright © 2017. Published by Elsevier Ltd.

Deep data analysis via physically constrained linear unmixing: universal framework, domain examples, and a community-wide platform.

PubMed

Kannan, R; Ievlev, A V; Laanait, N; Ziatdinov, M A; Vasudevan, R K; Jesse, S; Kalinin, S V

2018-01-01

Many spectral responses in materials science, physics, and chemistry experiments can be characterized as resulting from the superposition of a number of more basic individual spectra. In this context, unmixing is defined as the problem of determining the individual spectra, given measurements of multiple spectra that are spatially resolved across samples, as well as the determination of the corresponding abundance maps indicating the local weighting of each individual spectrum. Matrix factorization is a popular linear unmixing technique that considers that the mixture model between the individual spectra and the spatial maps is linear. Here, we present a tutorial paper targeted at domain scientists to introduce linear unmixing techniques, to facilitate greater understanding of spectroscopic imaging data. We detail a matrix factorization framework that can incorporate different domain information through various parameters of the matrix factorization method. We demonstrate many domain-specific examples to explain the expressivity of the matrix factorization framework and show how the appropriate use of domain-specific constraints such as non-negativity and sum-to-one abundance result in physically meaningful spectral decompositions that are more readily interpretable. Our aim is not only to explain the off-the-shelf available tools, but to add additional constraints when ready-made algorithms are unavailable for the task. All examples use the scalable open source implementation from https://github.com/ramkikannan/nmflibrary that can run from small laptops to supercomputers, creating a user-wide platform for rapid dissemination and adoption across scientific disciplines.

Algorithms for Solvents and Spectral Factors of Matrix Polynomials

DTIC Science & Technology

1981-01-01

spectral factors of matrix polynomials LEANG S. SHIEHt, YIH T. TSAYt and NORMAN P. COLEMANt A generalized Newton method , based on the contracted gradient...of a matrix poly- nomial, is derived for solving the right (left) solvents and spectral factors of matrix polynomials. Two methods of selecting initial...estimates for rapid convergence of the newly developed numerical method are proposed. Also, new algorithms for solving complete sets of the right

Bias and uncertainty in regression-calibrated models of groundwater flow in heterogeneous media

USGS Publications Warehouse

Cooley, R.L.; Christensen, S.

2006-01-01

Groundwater models need to account for detailed but generally unknown spatial variability (heterogeneity) of the hydrogeologic model inputs. To address this problem we replace the large, m-dimensional stochastic vector ?? that reflects both small and large scales of heterogeneity in the inputs by a lumped or smoothed m-dimensional approximation ????*, where ?? is an interpolation matrix and ??* is a stochastic vector of parameters. Vector ??* has small enough dimension to allow its estimation with the available data. The consequence of the replacement is that model function f(????*) written in terms of the approximate inputs is in error with respect to the same model function written in terms of ??, ??,f(??), which is assumed to be nearly exact. The difference f(??) - f(????*), termed model error, is spatially correlated, generates prediction biases, and causes standard confidence and prediction intervals to be too small. Model error is accounted for in the weighted nonlinear regression methodology developed to estimate ??* and assess model uncertainties by incorporating the second-moment matrix of the model errors into the weight matrix. Techniques developed by statisticians to analyze classical nonlinear regression methods are extended to analyze the revised method. The analysis develops analytical expressions for bias terms reflecting the interaction of model nonlinearity and model error, for correction factors needed to adjust the sizes of confidence and prediction intervals for this interaction, and for correction factors needed to adjust the sizes of confidence and prediction intervals for possible use of a diagonal weight matrix in place of the correct one. If terms expressing the degree of intrinsic nonlinearity for f(??) and f(????*) are small, then most of the biases are small and the correction factors are reduced in magnitude. Biases, correction factors, and confidence and prediction intervals were obtained for a test problem for which model error is large to test robustness of the methodology. Numerical results conform with the theoretical analysis. ?? 2005 Elsevier Ltd. All rights reserved.

Examining the Structural Validity of the Strengths and Difficulties Questionnaire (SDQ) in a U.S. Sample of Custodial Grandmothers

ERIC Educational Resources Information Center

Palmieri, Patrick A.; Smith, Gregory C.

2007-01-01

The authors examined the structural validity of the parent informant version of the Strengths and Difficulties Questionnaire (SDQ) with a sample of 733 custodial grandparents. Three models of the SDQ's factor structure were evaluated with confirmatory factor analysis based on the item covariance matrix. Although indices of fit were good across all…

Quantification of the effects of secondary matrix on the analysis of sandstone composition, and a petrographic-chemical technique for retrieving original framework grain modes of altered sandstones.

PubMed

Cox, R; Lowe, D R

1996-05-01

Most studies of sandstone provenance involve modal analysis of framework grains using techniques that exclude the fine-grained breakdown products of labile mineral grains and rock fragments, usually termed secondary matrix or pseudomatrix. However, the data presented here demonstrate that, when the proportion of pseudomatrix in a sandstone exceeds 10%, standard petrographic analysis can lead to incorrect provenance interpretation. Petrographic schemes for provenance analysis such as QFL and QFR should not therefore be applied to sandstones containing more than 10% secondary matrix. Pseudomatrix is commonly abundant in sandstones, and this is therefore a problem for provenance analysis. The difficulty can be alleviated by the use of whole-rock chemistry in addition to petrographic analysis. Combination of chemical and point-count data permits the construction of normative compositions that approximate original framework grain compositions. Provenance analysis is also complicated in many cases by fundamental compositional alteration during weathering and transport. Many sandstones, particularly shallow marine deposits, have undergone vigorous reworking, which may destroy unstable mineral grains and rock fragments. In such cases it may not be possible to retrieve provenance information by either petrographic or chemical means. Because of this, pseudomatrix-rich sandstones should be routinely included in chemical-petrological provenance analysis. Because of the many factors, both pre- and post-depositional, that operate to increase the compositional maturity of sandstones, petrologic studies must include a complete inventory of matrix proportions, grain size and sorting parameters, and an assessment of depositional setting.

Psychometric Evaluation of a Triage Decision Making Inventory

DTIC Science & Technology

2011-06-27

the correlation matrix and inter-item correlations were reviewed. The Bartlett’s test of sphericity and the Kaiser - Meyer Olkin (KMO) were examined to...nursing experience. Principal component factor analysis with Varimax rotation was conducted using SPSS version 16. The Kaiser - Meyer - Olkin Measure of...Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 7 iterations

Analysis of Hypersonic Vehicle Wakes

DTIC Science & Technology

2015-09-17

factor used with viscous Jacobian matrix of left eigenvectors for A R specific gas constant Re Reynolds number Recell cell Reynolds number......focus was shifted to characterizing other wake phenomena. The aerothermal phenomena of interest in the wake include: gas properties, chemical species

Gene Ranking of RNA-Seq Data via Discriminant Non-Negative Matrix Factorization.

PubMed

Jia, Zhilong; Zhang, Xiang; Guan, Naiyang; Bo, Xiaochen; Barnes, Michael R; Luo, Zhigang

2015-01-01

RNA-sequencing is rapidly becoming the method of choice for studying the full complexity of transcriptomes, however with increasing dimensionality, accurate gene ranking is becoming increasingly challenging. This paper proposes an accurate and sensitive gene ranking method that implements discriminant non-negative matrix factorization (DNMF) for RNA-seq data. To the best of our knowledge, this is the first work to explore the utility of DNMF for gene ranking. When incorporating Fisher's discriminant criteria and setting the reduced dimension as two, DNMF learns two factors to approximate the original gene expression data, abstracting the up-regulated or down-regulated metagene by using the sample label information. The first factor denotes all the genes' weights of two metagenes as the additive combination of all genes, while the second learned factor represents the expression values of two metagenes. In the gene ranking stage, all the genes are ranked as a descending sequence according to the differential values of the metagene weights. Leveraging the nature of NMF and Fisher's criterion, DNMF can robustly boost the gene ranking performance. The Area Under the Curve analysis of differential expression analysis on two benchmarking tests of four RNA-seq data sets with similar phenotypes showed that our proposed DNMF-based gene ranking method outperforms other widely used methods. Moreover, the Gene Set Enrichment Analysis also showed DNMF outweighs others. DNMF is also computationally efficient, substantially outperforming all other benchmarked methods. Consequently, we suggest DNMF is an effective method for the analysis of differential gene expression and gene ranking for RNA-seq data.

Applications of a Novel Clustering Approach Using Non-Negative Matrix Factorization to Environmental Research in Public Health

PubMed Central

Fogel, Paul; Gaston-Mathé, Yann; Hawkins, Douglas; Fogel, Fajwel; Luta, George; Young, S. Stanley

2016-01-01

Often data can be represented as a matrix, e.g., observations as rows and variables as columns, or as a doubly classified contingency table. Researchers may be interested in clustering the observations, the variables, or both. If the data is non-negative, then Non-negative Matrix Factorization (NMF) can be used to perform the clustering. By its nature, NMF-based clustering is focused on the large values. If the data is normalized by subtracting the row/column means, it becomes of mixed signs and the original NMF cannot be used. Our idea is to split and then concatenate the positive and negative parts of the matrix, after taking the absolute value of the negative elements. NMF applied to the concatenated data, which we call PosNegNMF, offers the advantages of the original NMF approach, while giving equal weight to large and small values. We use two public health datasets to illustrate the new method and compare it with alternative clustering methods, such as K-means and clustering methods based on the Singular Value Decomposition (SVD) or Principal Component Analysis (PCA). With the exception of situations where a reasonably accurate factorization can be achieved using the first SVD component, we recommend that the epidemiologists and environmental scientists use the new method to obtain clusters with improved quality and interpretability. PMID:27213413

Applications of a Novel Clustering Approach Using Non-Negative Matrix Factorization to Environmental Research in Public Health.

PubMed

Fogel, Paul; Gaston-Mathé, Yann; Hawkins, Douglas; Fogel, Fajwel; Luta, George; Young, S Stanley

2016-05-18

Often data can be represented as a matrix, e.g., observations as rows and variables as columns, or as a doubly classified contingency table. Researchers may be interested in clustering the observations, the variables, or both. If the data is non-negative, then Non-negative Matrix Factorization (NMF) can be used to perform the clustering. By its nature, NMF-based clustering is focused on the large values. If the data is normalized by subtracting the row/column means, it becomes of mixed signs and the original NMF cannot be used. Our idea is to split and then concatenate the positive and negative parts of the matrix, after taking the absolute value of the negative elements. NMF applied to the concatenated data, which we call PosNegNMF, offers the advantages of the original NMF approach, while giving equal weight to large and small values. We use two public health datasets to illustrate the new method and compare it with alternative clustering methods, such as K-means and clustering methods based on the Singular Value Decomposition (SVD) or Principal Component Analysis (PCA). With the exception of situations where a reasonably accurate factorization can be achieved using the first SVD component, we recommend that the epidemiologists and environmental scientists use the new method to obtain clusters with improved quality and interpretability.

An isometric muscle force estimation framework based on a high-density surface EMG array and an NMF algorithm

NASA Astrophysics Data System (ADS)

Huang, Chengjun; Chen, Xiang; Cao, Shuai; Qiu, Bensheng; Zhang, Xu

2017-08-01

Objective. To realize accurate muscle force estimation, a novel framework is proposed in this paper which can extract the input of the prediction model from the appropriate activation area of the skeletal muscle. Approach. Surface electromyographic (sEMG) signals from the biceps brachii muscle during isometric elbow flexion were collected with a high-density (HD) electrode grid (128 channels) and the external force at three contraction levels was measured at the wrist synchronously. The sEMG envelope matrix was factorized into a matrix of basis vectors with each column representing an activation pattern and a matrix of time-varying coefficients by a nonnegative matrix factorization (NMF) algorithm. The activation pattern with the highest activation intensity, which was defined as the sum of the absolute values of the time-varying coefficient curve, was considered as the major activation pattern, and its channels with high weighting factors were selected to extract the input activation signal of a force estimation model based on the polynomial fitting technique. Main results. Compared with conventional methods using the whole channels of the grid, the proposed method could significantly improve the quality of force estimation and reduce the electrode number. Significance. The proposed method provides a way to find proper electrode placement for force estimation, which can be further employed in muscle heterogeneity analysis, myoelectric prostheses and the control of exoskeleton devices.

Angiogenic Type I Collagen Extracellular Matrix Integrated with Recombinant Bacteriophages Displaying Vascular Endothelial Growth Factors.

PubMed

Yoon, Junghyo; Korkmaz Zirpel, Nuriye; Park, Hyun-Ji; Han, Sewoon; Hwang, Kyung Hoon; Shin, Jisoo; Cho, Seung-Woo; Nam, Chang-Hoon; Chung, Seok

2016-01-21

Here, a growth-factor-integrated natural extracellular matrix of type I collagen is presented that induces angiogenesis. The developed matrix adapts type I collagen nanofibers integrated with synthetic colloidal particles of recombinant bacteriophages that display vascular endothelial growth factor (VEGF). The integration is achieved during or after gelation of the type I collagen and the matrix enables spatial delivery of VEGF into a desired region. Endothelial cells that contact the VEGF are found to invade into the matrix to form tube-like structures both in vitro and in vivo, proving the angiogenic potential of the matrix. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Source apportionment and location by selective wind sampling and Positive Matrix Factorization.

PubMed

Venturini, Elisa; Vassura, Ivano; Raffo, Simona; Ferroni, Laura; Bernardi, Elena; Passarini, Fabrizio

2014-10-01

In order to determine the pollution sources in a suburban area and identify the main direction of their origin, PM2.5 was collected with samplers coupled with a wind select sensor and then subjected to Positive Matrix Factorization (PMF) analysis. In each sample, soluble ions, organic carbon, elemental carbon, levoglucosan, metals, and Polycyclic Aromatic Hydrocarbons (PAHs) were determined. PMF results identified six main sources affecting the area: natural gas home appliances, motor vehicles, regional transport, biomass combustion, manufacturing activities, and secondary aerosol. The connection of factor temporal trends with other parameters (i.e., temperature, PM2.5 concentration, and photochemical processes) confirms factor attributions. PMF analysis indicated that the main source of PM2.5 in the area is secondary aerosol. This should be mainly due to regional contributions, owing to both the secondary nature of the source itself and the higher concentration registered in inland air masses. The motor vehicle emission source contribution is also important. This source likely has a prevalent local origin. The most toxic determined components, i.e., PAHs, Cd, Pb, and Ni, are mainly due to vehicular traffic. Even if this is not the main source in the study area, it is the one of greatest concern. The application of PMF analysis to PM2.5 collected with this new sampling technique made it possible to obtain more detailed results on the sources affecting the area compared to a classical PMF analysis.

Symmetric nonnegative matrix factorization: algorithms and applications to probabilistic clustering.

PubMed

He, Zhaoshui; Xie, Shengli; Zdunek, Rafal; Zhou, Guoxu; Cichocki, Andrzej

2011-12-01

Nonnegative matrix factorization (NMF) is an unsupervised learning method useful in various applications including image processing and semantic analysis of documents. This paper focuses on symmetric NMF (SNMF), which is a special case of NMF decomposition. Three parallel multiplicative update algorithms using level 3 basic linear algebra subprograms directly are developed for this problem. First, by minimizing the Euclidean distance, a multiplicative update algorithm is proposed, and its convergence under mild conditions is proved. Based on it, we further propose another two fast parallel methods: α-SNMF and β -SNMF algorithms. All of them are easy to implement. These algorithms are applied to probabilistic clustering. We demonstrate their effectiveness for facial image clustering, document categorization, and pattern clustering in gene expression.

Differential effect of extracellular matrix derived from papillary and reticular fibroblasts on epidermal development in vitro.

PubMed

Janson, David; Rietveld, Marion; Mahé, Christian; Saintigny, Gaëlle; El Ghalbzouri, Abdoelwaheb

2017-06-01

Papillary and reticular fibroblasts have different effects on keratinocyte proliferation and differentiation. The aim of this study was to investigate whether these effects are caused by differential secretion of soluble factors or by differential generation of extracellular matrix from papillary and reticular fibroblasts. To study the effect of soluble factors, keratinocyte monolayer cultures were grown in papillary or reticular fibroblast-conditioned medium. To study the effect of extracellular matrix, keratinocytes were grown on papillary or reticular-derived matrix. Conditioned medium from papillary or reticular fibroblasts did not differentially affect keratinocyte viability or epidermal development. However, keratinocyte viability was increased when grown on matrix derived from papillary, compared with reticular, fibroblasts. In addition, the longevity of the epidermis was increased when cultured on papillary fibroblast-derived matrix skin equivalents compared with reticular-derived matrix skin equivalents. The findings indicate that the matrix secreted by papillary and reticular fibroblasts is the main causal factor to account for the differences in keratinocyte growth and viability observed in our study. Differences in response to soluble factors between both populations were less significant. Matrix components specific to the papillary dermis may account for the preferential growth of keratinocytes on papillary dermis.

D → π and D → K semileptonic form factors with Nf = 2 + 1 + 1 twisted mass fermions

NASA Astrophysics Data System (ADS)

Lubicz, Vittorio; Riggio, Lorenzo; Salerno, Giorgio; Simula, Silvano; Tarantino, Cecilia

2018-03-01

We present a lattice determination of the vector and scalar form factors of the D → π(K)lv semileptonic decays, which are relevant for the extraction of the CKM matrix elements |Vcd| and |Vcs| from experimental data. Our analysis is based on the gauge configurations produced by the European Twisted Mass Collaboration with Nf = 2 + 1 +1 flavors of dynamical quarks. We simulated at three different values of the lattice spacing and with pion masses as small as 210 MeV. The matrix elements of both vector and scalar currents are determined for a plenty of kinematical conditions in which parent and child mesons are either moving or at rest. Lorentz symmetry breaking due to hypercubic effects is clearly observed in the data and included in the decomposition of the current matrix elements in terms of additional form factors. After the extrapolations to the physical pion mass and to the continuum limit the vector and scalar form factors are determined in the whole kinematical region from q2 = 0 up to qmax2 = (MD - Mπ(K))2 accessible in the experiments, obtaining a good overall agreement with experiments, except in the region at high values of q2 where some deviations are visible.

Targeting extracellular matrix remodeling in disease: Could resveratrol be a potential candidate?

PubMed

Agarwal, Renu; Agarwal, Puneet

2017-02-01

Disturbances of extracellular matrix homeostasis are associated with a number of pathological conditions. The ability of extracellular matrix to provide contextual information and hence control the individual or collective cellular behavior is increasingly being recognized. Hence, newer therapeutic approaches targeting extracellular matrix remodeling are widely investigated. We reviewed the current literature showing the effects of resveratrol on various aspects of extracellular matrix remodeling. This review presents a summary of the effects of resveratrol on extracellular matrix deposition and breakdown. Mechanisms of action of resveratrol in extracellular matrix deposition involving growth factors and their signaling pathways are discussed. Involvement of phosphoinositol-3-kinase/Akt and mitogen-activated protein kinase pathways and role of transcription factors and sirtuins on the effects of resveratrol on extracellular matrix homeostasis are summarized. It is evident from the literature presented in this review that resveratrol has significant effects on both the synthesis and breakdown of extracellular matrix. The major molecular targets of the action of resveratrol are growth factors and their signaling pathways, phosphoinositol-3-kinase/Akt and mitogen-activated protein kinase pathways, transcription factors, and SIRT-1. The effects of resveratrol on extracellular matrix and the molecular targets appear to be related to experimental models, experimental environment as well as the doses.

Targeting extracellular matrix remodeling in disease: Could resveratrol be a potential candidate?

PubMed Central

Agarwal, Puneet

2016-01-01

Disturbances of extracellular matrix homeostasis are associated with a number of pathological conditions. The ability of extracellular matrix to provide contextual information and hence control the individual or collective cellular behavior is increasingly being recognized. Hence, newer therapeutic approaches targeting extracellular matrix remodeling are widely investigated. We reviewed the current literature showing the effects of resveratrol on various aspects of extracellular matrix remodeling. This review presents a summary of the effects of resveratrol on extracellular matrix deposition and breakdown. Mechanisms of action of resveratrol in extracellular matrix deposition involving growth factors and their signaling pathways are discussed. Involvement of phosphoinositol-3-kinase/Akt and mitogen-activated protein kinase pathways and role of transcription factors and sirtuins on the effects of resveratrol on extracellular matrix homeostasis are summarized. It is evident from the literature presented in this review that resveratrol has significant effects on both the synthesis and breakdown of extracellular matrix. The major molecular targets of the action of resveratrol are growth factors and their signaling pathways, phosphoinositol-3-kinase/Akt and mitogen-activated protein kinase pathways, transcription factors, and SIRT-1. The effects of resveratrol on extracellular matrix and the molecular targets appear to be related to experimental models, experimental environment as well as the doses. PMID:27798117

A novel culture device for the evaluation of three-dimensional extracellular matrix materials.

PubMed

Akhyari, Payam; Ziegler, Heiko; Gwanmesia, Patricia; Barth, Mareike; Schilp, Soeren; Huelsmann, Joern; Hoffmann, Stefanie; Bosch, Julia; Kögler, Gesine; Lichtenberg, Artur

2014-09-01

Cell-matrix interactions in a three-dimensional (3D) extracellular matrix (ECM) are of fundamental importance in living tissue, and their in vitro reconstruction in bioartificial structures represents a core target of contemporary tissue engineering concepts. For a detailed analysis of cell-matrix interaction under highly controlled conditions, we developed a novel ECM evaluation culture device (EECD) that allows for a precisely defined surface-seeding of 3D ECM scaffolds, irrespective of their natural geometry. The effectiveness of EECD was evaluated in the context of heart valve tissue engineering. Detergent decellularized pulmonary cusps were mounted in EECD and seeded with endothelial cells (ECs) to study EC adhesion, morphology and function on a 3D ECM after 3, 24, 48 and 96 h. Standard EC monolayers served as controls. Exclusive top-surface-seeding of 3D ECM by viable ECs was demonstrated by laser scanning microscopy (LSM), resulting in a confluent re-endothelialization of the ECM after 96 h. Cell viability and protein expression, as demonstrated by MTS assay and western blot analysis (endothelial nitric oxide synthase, von Willebrand factor), were preserved at maintained levels over time. In conclusion, EECD proves as a highly effective system for a controlled repopulation and in vitro analysis of cell-ECM interactions in 3D ECM. Copyright © 2012 John Wiley & Sons, Ltd.

Comparison of three-dimensional fluorescence analysis methods for predicting formation of trihalomethanes and haloacetic acids.

PubMed

Peleato, Nicolás M; Andrews, Robert C

2015-01-01

This work investigated the application of several fluorescence excitation-emission matrix analysis methods as natural organic matter (NOM) indicators for use in predicting the formation of trihalomethanes (THMs) and haloacetic acids (HAAs). Waters from four different sources (two rivers and two lakes) were subjected to jar testing followed by 24hr disinfection by-product formation tests using chlorine. NOM was quantified using three common measures: dissolved organic carbon, ultraviolet absorbance at 254 nm, and specific ultraviolet absorbance as well as by principal component analysis, peak picking, and parallel factor analysis of fluorescence spectra. Based on multi-linear modeling of THMs and HAAs, principle component (PC) scores resulted in the lowest mean squared prediction error of cross-folded test sets (THMs: 43.7 (μg/L)(2), HAAs: 233.3 (μg/L)(2)). Inclusion of principle components representative of protein-like material significantly decreased prediction error for both THMs and HAAs. Parallel factor analysis did not identify a protein-like component and resulted in prediction errors similar to traditional NOM surrogates as well as fluorescence peak picking. These results support the value of fluorescence excitation-emission matrix-principal component analysis as a suitable NOM indicator in predicting the formation of THMs and HAAs for the water sources studied. Copyright © 2014. Published by Elsevier B.V.

Genetic Background is a Key Determinant of Glomerular Extracellular Matrix Composition and Organization.

PubMed

Randles, Michael J; Woolf, Adrian S; Huang, Jennifer L; Byron, Adam; Humphries, Jonathan D; Price, Karen L; Kolatsi-Joannou, Maria; Collinson, Sophie; Denny, Thomas; Knight, David; Mironov, Aleksandr; Starborg, Toby; Korstanje, Ron; Humphries, Martin J; Long, David A; Lennon, Rachel

2015-12-01

Glomerular disease often features altered histologic patterns of extracellular matrix (ECM). Despite this, the potential complexities of the glomerular ECM in both health and disease are poorly understood. To explore whether genetic background and sex determine glomerular ECM composition, we investigated two mouse strains, FVB and B6, using RNA microarrays of isolated glomeruli combined with proteomic glomerular ECM analyses. These studies, undertaken in healthy young adult animals, revealed unique strain- and sex-dependent glomerular ECM signatures, which correlated with variations in levels of albuminuria and known predisposition to progressive nephropathy. Among the variation, we observed changes in netrin 4, fibroblast growth factor 2, tenascin C, collagen 1, meprin 1-α, and meprin 1-β. Differences in protein abundance were validated by quantitative immunohistochemistry and Western blot analysis, and the collective differences were not explained by mutations in known ECM or glomerular disease genes. Within the distinct signatures, we discovered a core set of structural ECM proteins that form multiple protein-protein interactions and are conserved from mouse to man. Furthermore, we found striking ultrastructural changes in glomerular basement membranes in FVB mice. Pathway analysis of merged transcriptomic and proteomic datasets identified potential ECM regulatory pathways involving inhibition of matrix metalloproteases, liver X receptor/retinoid X receptor, nuclear factor erythroid 2-related factor 2, notch, and cyclin-dependent kinase 5. These pathways may therefore alter ECM and confer susceptibility to disease. Copyright © 2015 by the American Society of Nephrology.

Development of a hybrid wave based-transfer matrix model for sound transmission analysis.

PubMed

Dijckmans, A; Vermeir, G

2013-04-01

In this paper, a hybrid wave based-transfer matrix model is presented that allows for the investigation of the sound transmission through finite multilayered structures placed between two reverberant rooms. The multilayered structure may consist of an arbitrary configuration of fluid, elastic, or poro-elastic layers. The field variables (structural displacements and sound pressures) are expanded in terms of structural and acoustic wave functions. The boundary and continuity conditions in the rooms determine the participation factors in the pressure expansions. The displacement of the multilayered structure is determined by the mechanical impedance matrix, which gives a relation between the pressures and transverse displacements at both sides of the structure. The elements of this matrix are calculated with the transfer matrix method. First, the hybrid model is numerically validated. Next a comparison is made with sound transmission loss measurements of a hollow brick wall and a sandwich panel. Finally, numerical simulations show the influence of structural damping, room dimensions and plate dimensions on the sound transmission loss of multilayered structures.

Investigation of colloidal graphite as a matrix for matrix-assisted laser desorption/ionisation mass spectrometry of low molecular weight analytes.

PubMed

Warren, Alexander D; Conway, Ulric; Arthur, Christopher J; Gates, Paul J

2016-07-01

The analysis of low molecular weight compounds by matrix-assisted laser desorption/ionisation mass spectrometry is problematic due to the interference and suppression of analyte ionisation by the matrices typically employed - which are themselves low molecular weight compounds. The application of colloidal graphite is demonstrated here as an easy to use matrix that can promote the ionisation of a wide range of analytes including low molecular weight organic compounds, complex natural products and inorganic complexes. Analyte ionisation with colloidal graphite is compared with traditional organic matrices along with various other sources of graphite (e.g. graphite rods and charcoal pencils). Factors such as ease of application, spectra reproducibility, spot longevity, spot-to-spot reproducibility and spot homogeneity (through single spot imaging) are explored. For some analytes, considerable matrix suppression effects are observed resulting in spectra completely devoid of matrix ions. We also report the observation of radical molecular ions [M(-●) ] in the negative ion mode, particularly with some aromatic analytes. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Implementation of hierarchical clustering using k-mer sparse matrix to analyze MERS-CoV genetic relationship

NASA Astrophysics Data System (ADS)

Bustamam, A.; Ulul, E. D.; Hura, H. F. A.; Siswantining, T.

2017-07-01

Hierarchical clustering is one of effective methods in creating a phylogenetic tree based on the distance matrix between DNA (deoxyribonucleic acid) sequences. One of the well-known methods to calculate the distance matrix is k-mer method. Generally, k-mer is more efficient than some distance matrix calculation techniques. The steps of k-mer method are started from creating k-mer sparse matrix, and followed by creating k-mer singular value vectors. The last step is computing the distance amongst vectors. In this paper, we analyze the sequences of MERS-CoV (Middle East Respiratory Syndrome - Coronavirus) DNA by implementing hierarchical clustering using k-mer sparse matrix in order to perform the phylogenetic analysis. Our results show that the ancestor of our MERS-CoV is coming from Egypt. Moreover, we found that the MERS-CoV infection that occurs in one country may not necessarily come from the same country of origin. This suggests that the process of MERS-CoV mutation might not only be influenced by geographical factor.

Fracture surface analysis in composite and titanium bonding

NASA Technical Reports Server (NTRS)

Devilbiss, T. A.; Wightman, J. P.

1985-01-01

To understand the mechanical properties of fiber-reinforced composite materials, it is necessary to understand the mechanical properties of the matrix materials and of the reinforcing fibers. Another factor that can affect the mechanical properties of a composite material is the interaction between the fiber and the matrix. In general, composites with strong fiber matrix bonding will give higher modulus, lower toughness composites. Composites with weak bonding will have a lower modulus and more ductility. The situation becomes a bit more complex when all possibilities are examined. To be considered are the following: the properties of the surface layer on the fiber, the interactive forces between polymer and matrix, the surface roughness and porosity of the fiber, and the morphology of the matrix polymer at the fiber surface. In practice, the surface of the fibers is treated to enhance the mechanical properties of a composite. These treatments include anodization, acid etching, high temperature oxidation, and plasma oxidation, to name a few. The goal is to be able to predict the surface properties of carbon fibers treated in various ways, and then to relate surface properties to fiber matrix bonding.

The multifacet graphically contracted function method. I. Formulation and implementation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shepard, Ron; Brozell, Scott R.; Gidofalvi, Gergely

2014-08-14

The basic formulation for the multifacet generalization of the graphically contracted function (MFGCF) electronic structure method is presented. The analysis includes the discussion of linear dependency and redundancy of the arc factor parameters, the computation of reduced density matrices, Hamiltonian matrix construction, spin-density matrix construction, the computation of optimization gradients for single-state and state-averaged calculations, graphical wave function analysis, and the efficient computation of configuration state function and Slater determinant expansion coefficients. Timings are given for Hamiltonian matrix element and analytic optimization gradient computations for a range of model problems for full-CI Shavitt graphs, and it is observed that bothmore » the energy and the gradient computation scale as O(N{sup 2}n{sup 4}) for N electrons and n orbitals. The important arithmetic operations are within dense matrix-matrix product computational kernels, resulting in a computationally efficient procedure. An initial implementation of the method is used to present applications to several challenging chemical systems, including N{sub 2} dissociation, cubic H{sub 8} dissociation, the symmetric dissociation of H{sub 2}O, and the insertion of Be into H{sub 2}. The results are compared to the exact full-CI values and also to those of the previous single-facet GCF expansion form.« less

Marketing Strategy Analysis for Small and Medium Scale Business Enterprise (SMEs) for Home Industry Furniture in Leilem, the Regency of Minahasa

NASA Astrophysics Data System (ADS)

Pangemanan, S. A.; Walukow, I. M.

2018-01-01

Leilem is a small village located in Minahasa Regency. This village is well known for furniture products made of Timber. Eventhough the village has been producing various furniture products with high quality since many decades ago, it has not been able to compete with other new entries such furniture from Java, Synthetic Ratan, Plywood and plastic based furniture. The monotonous design and the finishing works done on the furniture have been some of the major issues in the decline of home furniture. The research explores problems and challenges faced by the furniture home Industry. It will also aim at identifying the internal and external factors that prevent the home industry to compete and survive. In the end the research will develop the strategic positioning of the home industry in the midst of competition. The research methodology employs descriptive analysis in which data are collected through observation, interview, and questionnaire. This methodology is combined with IFE (Internal Factor Evaluation) and EFE (External Factor Evaluation) Matrix, SPACE Matrix and SWOT Analysis and QSPM (Quantitative Strategic Planning Matrix). The sample is 66 business people, of 823 craftsmen who are working in this business. The result shows this home industry is very competitive in terms of consistency, but in terms of promotion, product quality, price, product diversification, design training of furniture, management and economic scale, it is lagging behind. The home industry should be able to develop marketing networking, improve design and product quality, promotion and cost control, product diversification and these can only be done by intensive training in managing business and investment.

Decursin and decursinol angelate improve wound healing by upregulating transcription of genes encoding extracellular matrix remodeling proteins, inflammatory cytokines, and growth factors in human keratinocytes.

PubMed

Han, Jisu; Jin, Wook; Ho, Ngoc Anh; Hong, Jeongpyo; Kim, Yoon Ju; Shin, Yungyeong; Lee, Hanki; Suh, Joo-Won

2018-05-23

The coumarins decursin and decursinol angelate, which are found in Angelica gigas Nakai, have a variety of biological functions. Here, we show that treatment with these compounds improves wound healing by HaCaT human keratinocytes. Wound healing was increased by treatment with up to a threshold concentration of decursin, decursinol angelate, a mixture of both, and a nano-emulsion of these compounds, but inhibited by treatment with higher concentrations. Immunoblotting and fluorescence imaging of cells expressing an epidermal growth factor receptor (EGFR) biosensor demonstrated that these compounds did not stimulate wound healing by inducing EGFR phosphorylation. Rather, transcriptional analysis revealed that decursin and decursinol angelate improved wound healing by upregulating the expression of genes encoding extracellular matrix remodeling proteins, inflammatory cytokines, and growth factors. Copyright © 2018 Elsevier Inc. All rights reserved.

Construction fatality due to electrical contact in Ontario, Canada, 1997-2007.

PubMed

Kim, Hwan; Lewko, John; Garritano, Enzo; Sharma, Bhanu; Moody, Joel; Colantonio, Angela

2016-06-27

Electrical contact is a leading cause of occupational fatality in the construction industry. However, research on the factors that contribute to electricity-related fatality in construction is limited. To characterize, using an adapted Haddon's Matrix, the factors that contribute to electricity-related occupational fatalities in the construction industry in Ontario, Canada. Coroner's data on occupational electricity-related fatalities between 1997-2007 in the construction industry were acquired from the Ontario Ministry of Labour. Using an adapted Haddon's Matrix, we characterized worker, agent, and environmental characteristics of electricity-related occupational fatalities in the province through a narrative text analysis. Electrical contact was responsible for 15% of all occupational fatalities among construction workers in Ontario. Factors associated with said occupational fatalities included direct contact with electrical sources, lower voltage sources, and working outdoors. This study provides a profile of electricity-related occupational fatalities among construction workers in Ontario, and can be used to inform safety regulations.

Cluster structure of EU-15 countries derived from the correlation matrix analysis of macroeconomic index fluctuations

NASA Astrophysics Data System (ADS)

Gligor, M.; Ausloos, M.

2007-05-01

The statistical distances between countries, calculated for various moving average time windows, are mapped into the ultrametric subdominant space as in classical Minimal Spanning Tree methods. The Moving Average Minimal Length Path (MAMLP) algorithm allows a decoupling of fluctuations with respect to the mass center of the system from the movement of the mass center itself. A Hamiltonian representation given by a factor graph is used and plays the role of cost function. The present analysis pertains to 11 macroeconomic (ME) indicators, namely the GDP (x1), Final Consumption Expenditure (x2), Gross Capital Formation (x3), Net Exports (x4), Consumer Price Index (y1), Rates of Interest of the Central Banks (y2), Labour Force (z1), Unemployment (z2), GDP/hour worked (z3), GDP/capita (w1) and Gini coefficient (w2). The target group of countries is composed of 15 EU countries, data taken between 1995 and 2004. By two different methods (the Bipartite Factor Graph Analysis and the Correlation Matrix Eigensystem Analysis) it is found that the strongly correlated countries with respect to the macroeconomic indicators fluctuations can be partitioned into stable clusters.

Geometric control of capillary architecture via cell-matrix mechanical interactions.

PubMed

Sun, Jian; Jamilpour, Nima; Wang, Fei-Yue; Wong, Pak Kin

2014-03-01

Capillary morphogenesis is a multistage, multicellular activity that plays a pivotal role in various developmental and pathological situations. In-depth understanding of the regulatory mechanism along with the capability of controlling the morphogenic process will have direct implications on tissue engineering and therapeutic angiogenesis. Extensive research has been devoted to elucidate the biochemical factors that regulate capillary morphogenesis. The roles of geometric confinement and cell-matrix mechanical interactions on the capillary architecture, nevertheless, remain largely unknown. Here, we show geometric control of endothelial network topology by creating physical confinements with microfabricated fences and wells. Decreasing the thickness of the matrix also results in comparable modulation of the network architecture, supporting the boundary effect is mediated mechanically. The regulatory role of cell-matrix mechanical interaction on the network topology is further supported by alternating the matrix stiffness by a cell-inert PEG-dextran hydrogel. Furthermore, reducing the cell traction force with a Rho-associated protein kinase inhibitor diminishes the boundary effect. Computational biomechanical analysis delineates the relationship between geometric confinement and cell-matrix mechanical interaction. Collectively, these results reveal a mechanoregulation scheme of endothelial cells to regulate the capillary network architecture via cell-matrix mechanical interactions. Copyright © 2014 Elsevier Ltd. All rights reserved.

Using Dynamic Multi-Task Non-Negative Matrix Factorization to Detect the Evolution of User Preferences in Collaborative Filtering

PubMed Central

Ju, Bin; Qian, Yuntao; Ye, Minchao; Ni, Rong; Zhu, Chenxi

2015-01-01

Predicting what items will be selected by a target user in the future is an important function for recommendation systems. Matrix factorization techniques have been shown to achieve good performance on temporal rating-type data, but little is known about temporal item selection data. In this paper, we developed a unified model that combines Multi-task Non-negative Matrix Factorization and Linear Dynamical Systems to capture the evolution of user preferences. Specifically, user and item features are projected into latent factor space by factoring co-occurrence matrices into a common basis item-factor matrix and multiple factor-user matrices. Moreover, we represented both within and between relationships of multiple factor-user matrices using a state transition matrix to capture the changes in user preferences over time. The experiments show that our proposed algorithm outperforms the other algorithms on two real datasets, which were extracted from Netflix movies and Last.fm music. Furthermore, our model provides a novel dynamic topic model for tracking the evolution of the behavior of a user over time. PMID:26270539

Using Dynamic Multi-Task Non-Negative Matrix Factorization to Detect the Evolution of User Preferences in Collaborative Filtering.

PubMed

Ju, Bin; Qian, Yuntao; Ye, Minchao; Ni, Rong; Zhu, Chenxi

2015-01-01

Predicting what items will be selected by a target user in the future is an important function for recommendation systems. Matrix factorization techniques have been shown to achieve good performance on temporal rating-type data, but little is known about temporal item selection data. In this paper, we developed a unified model that combines Multi-task Non-negative Matrix Factorization and Linear Dynamical Systems to capture the evolution of user preferences. Specifically, user and item features are projected into latent factor space by factoring co-occurrence matrices into a common basis item-factor matrix and multiple factor-user matrices. Moreover, we represented both within and between relationships of multiple factor-user matrices using a state transition matrix to capture the changes in user preferences over time. The experiments show that our proposed algorithm outperforms the other algorithms on two real datasets, which were extracted from Netflix movies and Last.fm music. Furthermore, our model provides a novel dynamic topic model for tracking the evolution of the behavior of a user over time.

Performance Analysis of ICA in Sensor Array

PubMed Central

Cai, Xin; Wang, Xiang; Huang, Zhitao; Wang, Fenghua

2016-01-01

As the best-known scheme in the field of Blind Source Separation (BSS), Independent Component Analysis (ICA) has been intensively used in various domains, including biomedical and acoustics applications, cooperative or non-cooperative communication, etc. While sensor arrays are involved in most of the applications, the influence on the performance of ICA of practical factors therein has not been sufficiently investigated yet. In this manuscript, the issue is researched by taking the typical antenna array as an illustrative example. Factors taken into consideration include the environment noise level, the properties of the array and that of the radiators. We analyze the analytic relationship between the noise variance, the source variance, the condition number of the mixing matrix and the optimal signal to interference-plus-noise ratio, as well as the relationship between the singularity of the mixing matrix and practical factors concerned. The situations where the mixing process turns (nearly) singular have been paid special attention to, since such circumstances are critical in applications. Results and conclusions obtained should be instructive when applying ICA algorithms on mixtures from sensor arrays. Moreover, an effective countermeasure against the cases of singular mixtures has been proposed, on the basis of previous analysis. Experiments validating the theoretical conclusions as well as the effectiveness of the proposed scheme have been included. PMID:27164100

Using Separable Nonnegative Matrix Factorization Techniques for the Analysis of Time-Resolved Raman Spectra

NASA Astrophysics Data System (ADS)

Luce, R.; Hildebrandt, P.; Kuhlmann, U.; Liesen, J.

2016-09-01

The key challenge of time-resolved Raman spectroscopy is the identification of the constituent species and the analysis of the kinetics of the underlying reaction network. In this work we present an integral approach that allows for determining both the component spectra and the rate constants simultaneously from a series of vibrational spectra. It is based on an algorithm for non-negative matrix factorization which is applied to the experimental data set following a few pre-processing steps. As a prerequisite for physically unambiguous solutions, each component spectrum must include one vibrational band that does not significantly interfere with vibrational bands of other species. The approach is applied to synthetic "experimental" spectra derived from model systems comprising a set of species with component spectra differing with respect to their degree of spectral interferences and signal-to-noise ratios. In each case, the species involved are connected via monomolecular reaction pathways. The potential and limitations of the approach for recovering the respective rate constants and component spectra are discussed.

Excitation-emission matrix fluorescence spectroscopy in conjunction with multiway analysis for PAH detection in complex matrices.

PubMed

Nahorniak, Michelle L; Booksh, Karl S

2006-12-01

A field portable, single exposure excitation-emission matrix (EEM) fluorometer has been constructed and used in conjunction with parallel factor analysis (PARAFAC) to determine the sub part per billion (ppb) concentrations of several aqueous polycyclic aromatic hydrocarbons (PAHs), such as benzo(k)fluoranthene and benzo(a)pyrene, in various matrices including aqueous motor oil extract and asphalt leachate. Multiway methods like PARAFAC are essential to resolve the analyte signature from the ubiquitous background in environmental samples. With multiway data and PARAFAC analysis it is shown that reliable concentration determinations can be achieved with minimal standards in spite of the large convoluting fluorescence background signal. Thus, rapid fieldable EEM analyses may prove to be a good screening method for tracking pollutants and prioritizing sampling and analysis by more complete but time consuming and labor intensive EPA methods.

Large scale nanoparticle screening for small molecule analysis in laser desorption ionization mass spectrometry

DOE PAGES

Yagnik, Gargey B.; Hansen, Rebecca L.; Korte, Andrew R.; ...

2016-08-30

Nanoparticles (NPs) have been suggested as efficient matrixes for small molecule profiling and imaging by laser-desorption ionization mass spectrometry (LDI-MS), but so far there has been no systematic study comparing different NPs in the analysis of various classes of small molecules. Here, we present a large scale screening of 13 NPs for the analysis of two dozen small metabolite molecules. Many NPs showed much higher LDI efficiency than organic matrixes in positive mode and some NPs showed comparable efficiencies for selected analytes in negative mode. Our results suggest that a thermally driven desorption process is a key factor for metalmore » oxide NPs, but chemical interactions are also very important, especially for other NPs. Furthermore, the screening results provide a useful guideline for the selection of NPs in the LDI-MS analysis of small molecules.« less

Large scale nanoparticle screening for small molecule analysis in laser desorption ionization mass spectrometry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yagnik, Gargey B.; Hansen, Rebecca L.; Korte, Andrew R.

Nanoparticles (NPs) have been suggested as efficient matrixes for small molecule profiling and imaging by laser-desorption ionization mass spectrometry (LDI-MS), but so far there has been no systematic study comparing different NPs in the analysis of various classes of small molecules. Here, we present a large scale screening of 13 NPs for the analysis of two dozen small metabolite molecules. Many NPs showed much higher LDI efficiency than organic matrixes in positive mode and some NPs showed comparable efficiencies for selected analytes in negative mode. Our results suggest that a thermally driven desorption process is a key factor for metalmore » oxide NPs, but chemical interactions are also very important, especially for other NPs. Furthermore, the screening results provide a useful guideline for the selection of NPs in the LDI-MS analysis of small molecules.« less

Synthetic Division and Matrix Factorization

ERIC Educational Resources Information Center

Barabe, Samuel; Dubeau, Franc

2007-01-01

Synthetic division is viewed as a change of basis for polynomials written under the Newton form. Then, the transition matrices obtained from a sequence of changes of basis are used to factorize the inverse of a bidiagonal matrix or a block bidiagonal matrix.

A projection operator method for the analysis of magnetic neutron form factors

NASA Astrophysics Data System (ADS)

Kaprzyk, S.; Van Laar, B.; Maniawski, F.

1981-03-01

A set of projection operators in matrix form has been derived on the basis of decomposition of the spin density into a series of fully symmetrized cubic harmonics. This set of projection operators allows a formulation of the Fourier analysis of magnetic form factors in a convenient way. The presented method is capable of checking the validity of various theoretical models used for spin density analysis up to now. The general formalism is worked out in explicit form for the fcc and bcc structures and deals with that part of spin density which is contained within the sphere inscribed in the Wigner-Seitz cell. This projection operator method has been tested on the magnetic form factors of nickel and iron.

Recovering hidden diagonal structures via non-negative matrix factorization with multiple constraints.

PubMed

Yang, Xi; Han, Guoqiang; Cai, Hongmin; Song, Yan

2017-03-31

Revealing data with intrinsically diagonal block structures is particularly useful for analyzing groups of highly correlated variables. Earlier researches based on non-negative matrix factorization (NMF) have been shown to be effective in representing such data by decomposing the observed data into two factors, where one factor is considered to be the feature and the other the expansion loading from a linear algebra perspective. If the data are sampled from multiple independent subspaces, the loading factor would possess a diagonal structure under an ideal matrix decomposition. However, the standard NMF method and its variants have not been reported to exploit this type of data via direct estimation. To address this issue, a non-negative matrix factorization with multiple constraints model is proposed in this paper. The constraints include an sparsity norm on the feature matrix and a total variational norm on each column of the loading matrix. The proposed model is shown to be capable of efficiently recovering diagonal block structures hidden in observed samples. An efficient numerical algorithm using the alternating direction method of multipliers model is proposed for optimizing the new model. Compared with several benchmark models, the proposed method performs robustly and effectively for simulated and real biological data.

Micro-Mechanical Analysis About Kink Band in Carbon Fiber/Epoxy Composites Under Longitudinal Compression

NASA Astrophysics Data System (ADS)

Zhang, Mi; Guan, Zhidong; Wang, Xiaodong; Du, Shanyi

2017-10-01

Kink band is a typical phenomenon for composites under longitudinal compression. In this paper, theoretical analysis and finite element simulation were conducted to analyze kink angle as well as compressive strength of composites. Kink angle was considered to be an important character throughout longitudinal compression process. Three factors including plastic matrix, initial fiber misalignment and rotation due to loading were considered for theoretical analysis. Besides, the relationship between kink angle and fiber volume fraction was improved and optimized by theoretical derivation. In addition, finite element models considering fiber stochastic strength and Drucker-Prager constitutive model for matrix were conducted in ABAQUS to analyze kink band formation process, which corresponded with the experimental results. Through simulation, the loading and failure procedure can be evidently divided into three stages: elastic stage, softening stage, and fiber break stage. It also shows that kink band is a result of fiber misalignment and plastic matrix. Different values of initial fiber misalignment angle, wavelength and fiber volume fraction were considered to explore the effects on compressive strength and kink angle. Results show that compressive strength increases with the decreasing of initial fiber misalignment angle, the decreasing of initial fiber misalignment wavelength and the increasing of fiber volume fraction, while kink angle decreases in these situations. Orthogonal array in statistics was also built to distinguish the effect degree of these factors. It indicates that initial fiber misalignment angle has the largest impact on compressive strength and kink angle.

Factor Structure of the TOEFL® Internet-Based Test (iBT): Exploration in a Field Trial Sample. TOEFL iBT Research Report. TOEFL iBT-04. ETS RR-08-09

ERIC Educational Resources Information Center

Sawaki, Yasuyo; Stricker, Lawrence; Oranje, Andreas

2008-01-01

The present study investigated the factor structure of a field trial sample of the Test of English as a Foreign Language™ Internet-based test (TOEFL® iBT). An item-level confirmatory factor analysis (CFA) was conducted for a polychoric correlation matrix of items on a test form completed by 2,720 participants in the 2003-2004 TOEFL iBT Field…

Fuzzy Mathematical Models To Remove Poverty Of Gypsies In Tamilnadu

NASA Astrophysics Data System (ADS)

Chandrasekaran, A. D.; Ramkumar, C.; Siva, E. P.; Balaji, N.

2018-04-01

In the society there are several poor people are living. One of the sympathetic poor people is gypsies. They are moving from one place to another place towards survive of life because of not having any permanent place to live. In this paper we have interviewed 895 gypsies in Tamilnadu using a linguistic questionnaire. As the problems faced by them to improve their life at large involve so much of feeling, uncertainties and unpredictabilitys. I felt that it deem fit to use fuzzy theory in general and fuzzy matrix in particular. Fuzzy matrix is the best suitable tool where the data is an unsupervised one. Further the fuzzy matrix is so powerful to identify the main development factor of gypsies.This paper has three sections. In section one the method of application of CEFD matrix. In section two, we describe the development factors of gypsies. In section three, we apply these factors to the CEFD matrix and derive our conclusions. Key words: RD matrix, AFD matrix, CEFD matrix.

Critical factors determining the quantification capability of matrix-assisted laser desorption/ionization– time-of-flight mass spectrometry

PubMed Central

Wang, Chia-Chen; Lai, Yin-Hung; Ou, Yu-Meng; Chang, Huan-Tsung; Wang, Yi-Sheng

2016-01-01

Quantitative analysis with mass spectrometry (MS) is important but challenging. Matrix-assisted laser desorption/ionization (MALDI) coupled with time-of-flight (TOF) MS offers superior sensitivity, resolution and speed, but such techniques have numerous disadvantages that hinder quantitative analyses. This review summarizes essential obstacles to analyte quantification with MALDI-TOF MS, including the complex ionization mechanism of MALDI, sensitive characteristics of the applied electric fields and the mass-dependent detection efficiency of ion detectors. General quantitative ionization and desorption interpretations of ion production are described. Important instrument parameters and available methods of MALDI-TOF MS used for quantitative analysis are also reviewed. This article is part of the themed issue ‘Quantitative mass spectrometry’. PMID:27644968

Enamel Matrix Derivative Promotes Healing of a Surgical Wound in the Rat Oral Mucosa.

PubMed

Maymon-Gil, Tal; Weinberg, Evgeny; Nemcovsky, Carlos; Weinreb, Miron

2016-05-01

Enamel matrix proteins (EMPs) play a role in enamel formation and the development of the periodontium. Sporadic clinical observations of periodontal regeneration treatments with enamel matrix derivative (EMD), a commercial formulation of EMPs, suggest that it also promotes post-surgical healing of soft tissues. In vitro studies showed that EMD stimulates various cellular effects, which could potentially enhance wound healing. This study examines the in vivo effects of EMD on healing of an oral mucosa surgical wound in rats. A bilateral oral mucosa wound was created via a crestal incision in the anterior edentulous maxilla of Sprague-Dawley rats. Full-thickness flaps were raised, and, after suturing, EMD was injected underneath the soft tissues on one side, whereas the EMD vehicle was injected in the contralateral side. Animals were sacrificed after 5 or 9 days, and the wound area was subjected to histologic and immunohistochemical analysis of the epithelial gap, number of macrophages, blood vessels, proliferating cells, and collagen content in the connective tissue (CT). Gene expression analysis was also conducted 2 days post-surgery. EMD had no effect on the epithelial gap of the wound. On both days 5 and 9, EMD treatment increased significantly the number of blood vessels and the collagen content. EMD also enhanced (by 20% to 40%) the expression of transforming growth factors β1 and β2, vascular endothelial growth factor, interleukin-1β, matrix metalloproteinase-1, versican, and fibronectin. EMD improves oral mucosa incisional wound healing by promoting formation of blood vessels and collagen fibers in CT.

Application of texture analysis method for mammogram density classification

NASA Astrophysics Data System (ADS)

Nithya, R.; Santhi, B.

2017-07-01

Mammographic density is considered a major risk factor for developing breast cancer. This paper proposes an automated approach to classify breast tissue types in digital mammogram. The main objective of the proposed Computer-Aided Diagnosis (CAD) system is to investigate various feature extraction methods and classifiers to improve the diagnostic accuracy in mammogram density classification. Texture analysis methods are used to extract the features from the mammogram. Texture features are extracted by using histogram, Gray Level Co-Occurrence Matrix (GLCM), Gray Level Run Length Matrix (GLRLM), Gray Level Difference Matrix (GLDM), Local Binary Pattern (LBP), Entropy, Discrete Wavelet Transform (DWT), Wavelet Packet Transform (WPT), Gabor transform and trace transform. These extracted features are selected using Analysis of Variance (ANOVA). The features selected by ANOVA are fed into the classifiers to characterize the mammogram into two-class (fatty/dense) and three-class (fatty/glandular/dense) breast density classification. This work has been carried out by using the mini-Mammographic Image Analysis Society (MIAS) database. Five classifiers are employed namely, Artificial Neural Network (ANN), Linear Discriminant Analysis (LDA), Naive Bayes (NB), K-Nearest Neighbor (KNN), and Support Vector Machine (SVM). Experimental results show that ANN provides better performance than LDA, NB, KNN and SVM classifiers. The proposed methodology has achieved 97.5% accuracy for three-class and 99.37% for two-class density classification.

High-performance sparse matrix-matrix products on Intel KNL and multicore architectures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nagasaka, Y; Matsuoka, S; Azad, A

Sparse matrix-matrix multiplication (SpGEMM) is a computational primitive that is widely used in areas ranging from traditional numerical applications to recent big data analysis and machine learning. Although many SpGEMM algorithms have been proposed, hardware specific optimizations for multi- and many-core processors are lacking and a detailed analysis of their performance under various use cases and matrices is not available. We firstly identify and mitigate multiple bottlenecks with memory management and thread scheduling on Intel Xeon Phi (Knights Landing or KNL). Specifically targeting multi- and many-core processors, we develop a hash-table-based algorithm and optimize a heap-based shared-memory SpGEMM algorithm. Wemore » examine their performance together with other publicly available codes. Different from the literature, our evaluation also includes use cases that are representative of real graph algorithms, such as multi-source breadth-first search or triangle counting. Our hash-table and heap-based algorithms are showing significant speedups from libraries in the majority of the cases while different algorithms dominate the other scenarios with different matrix size, sparsity, compression factor and operation type. We wrap up in-depth evaluation results and make a recipe to give the best SpGEMM algorithm for target scenario. A critical finding is that hash-table-based SpGEMM gets a significant performance boost if the nonzeros are not required to be sorted within each row of the output matrix.« less

Exploratory factor analysis in Rehabilitation Psychology: a content analysis.

PubMed

Roberson, Richard B; Elliott, Timothy R; Chang, Jessica E; Hill, Jessica N

2014-11-01

Our objective was to examine the use and quality of exploratory factor analysis (EFA) in articles published in Rehabilitation Psychology. Trained raters examined 66 separate exploratory factor analyses in 47 articles published between 1999 and April 2014. The raters recorded the aim of the EFAs, the distributional statistics, sample size, factor retention method(s), extraction and rotation method(s), and whether the pattern coefficients, structure coefficients, and the matrix of association were reported. The primary use of the EFAs was scale development, but the most widely used extraction and rotation method was principle component analysis, with varimax rotation. When determining how many factors to retain, multiple methods (e.g., scree plot, parallel analysis) were used most often. Many articles did not report enough information to allow for the duplication of their results. EFA relies on authors' choices (e.g., factor retention rules extraction, rotation methods), and few articles adhered to all of the best practices. The current findings are compared to other empirical investigations into the use of EFA in published research. Recommendations for improving EFA reporting practices in rehabilitation psychology research are provided.

Uncertainty of relative sensitivity factors in glow discharge mass spectrometry

NASA Astrophysics Data System (ADS)

Meija, Juris; Methven, Brad; Sturgeon, Ralph E.

2017-10-01

The concept of the relative sensitivity factors required for the correction of the measured ion beam ratios in pin-cell glow discharge mass spectrometry is examined in detail. We propose a data-driven model for predicting the relative response factors, which relies on a non-linear least squares adjustment and analyte/matrix interchangeability phenomena. The model provides a self-consistent set of response factors for any analyte/matrix combination of any element that appears as either an analyte or matrix in at least one known response factor.

Astrophysical S factor for the {sup 15}N(p,{gamma}){sup 16}O reaction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mukhamedzhanov, A. M.; La Cognata, M.; Kroha, V.

2011-04-15

The R-matrix approach has proved to be very useful in extrapolating the astrophysical factor down to astrophysically relevant energies, since the majority of measurements are not available in this region. However, such an approach has to be critically considered when no complete knowledge of the reaction model is available. To get reliable results in such cases one has to use all the available information from independent sources and, accordingly, fix or constrain variations of the parameters. In this paper we present a thorough R-matrix analysis of the {sup 15}N(p,{gamma}){sup 16}O reaction, which provides a path from the CN cycle tomore » the CNO bi-cycle and CNO tri-cycle. The measured astrophysical factor for this reaction is dominated by resonant capture through two strong J{sup {pi}}=1{sup -} resonances at E{sub R}=312 and 962 keV and direct capture to the ground state. Recently, a new measurement of the astrophysical factor for the {sup 15}N(p,{gamma}){sup 16}O reaction has been published [P. J. LeBlanc et al., Phys. Rev. C 82, 055804 (2010)]. The analysis has been done using the R-matrix approach with unconstrained variation of all parameters including the asymptotic normalization coefficient (ANC). The best fit has been obtained for the square of the ANC C{sup 2}=539.2 fm{sup -1}, which exceeds the previously measured value by a factor of {approx_equal}3. Here we present a new R-matrix analysis of the Notre Dame-LUNA data with the fixed within the experimental uncertainties square of the ANC C{sup 2}=200.34 fm{sup -1}. Rather than varying the ANC we add the contribution from a background resonance that effectively takes into account contributions from higher levels. Altogether we present ten fits, seven unconstrained and three constrained. For the unconstrained fit with the boundary condition B{sub c}=S{sub c}(E{sub 2}), where E{sub 2} is the energy of the second level, we get S(0)=39.0{+-}1.1 keVb and normalized {chi}-tilde{sup 2}=1.84, i.e., the result which is similar to LeBlanc et al. From all our fits we get the range 33.1{<=}S(0){<=}40.1 keVb which overlaps with the result of LeBlanc et al. We address also the physical interpretation of the fitting parameters.« less

A Comparative Study of the Application of Fluorescence Excitation-Emission Matrices Combined with Parallel Factor Analysis and Nonnegative Matrix Factorization in the Analysis of Zn Complexation by Humic Acids

PubMed Central

Boguta, Patrycja; Pieczywek, Piotr M.; Sokołowska, Zofia

2016-01-01

The main aim of this study was the application of excitation-emission fluorescence matrices (EEMs) combined with two decomposition methods: parallel factor analysis (PARAFAC) and nonnegative matrix factorization (NMF) to study the interaction mechanisms between humic acids (HAs) and Zn(II) over a wide concentration range (0–50 mg·dm−3). The influence of HA properties on Zn(II) complexation was also investigated. Stability constants, quenching degree and complexation capacity were estimated for binding sites found in raw EEM, EEM-PARAFAC and EEM-NMF data using mathematical models. A combination of EEM fluorescence analysis with one of the proposed decomposition methods enabled separation of overlapping binding sites and yielded more accurate calculations of the binding parameters. PARAFAC and NMF processing allowed finding binding sites invisible in a few raw EEM datasets as well as finding totally new maxima attributed to structures of the lowest humification. Decomposed data showed an increase in Zn complexation with an increase in humification, aromaticity and molecular weight of HAs. EEM-PARAFAC analysis also revealed that the most stable compounds were formed by structures containing the highest amounts of nitrogen. The content of oxygen-functional groups did not influence the binding parameters, mainly due to fact of higher competition of metal cation with protons. EEM spectra coupled with NMF and especially PARAFAC processing gave more adequate assessments of interactions as compared to raw EEM data and should be especially recommended for modeling of complexation processes where the fluorescence intensities (FI) changes are weak or where the processes are interfered with by the presence of other fluorophores. PMID:27782078

Poster — Thur Eve — 03: Application of the non-negative matrix factorization technique to [{sup 11}C]-DTBZ dynamic PET data for the early detection of Parkinson's disease

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Dong-Chang; Jans, Hans; McEwan, Sandy

2014-08-15

In this work, a class of non-negative matrix factorization (NMF) technique known as alternating non-negative least squares, combined with the projected gradient method, is used to analyze twenty-five [{sup 11}C]-DTBZ dynamic PET/CT brain data. For each subject, a two-factor model is assumed and two factors representing the striatum (factor 1) and the non-striatum (factor 2) tissues are extracted using the proposed NMF technique and commercially available factor analysis software “Pixies”. The extracted factor 1 and 2 curves represent the binding site of the radiotracer and describe the uptake and clearance of the radiotracer by soft tissues in the brain, respectively.more » The proposed NMF technique uses prior information about the dynamic data to obtain sample time-activity curves representing the striatum and the non-striatum tissues. These curves are then used for “warm” starting the optimization. Factor solutions from the two methods are compared graphically and quantitatively. In healthy subjects, radiotracer uptake by factors 1 and 2 are approximately 35–40% and 60–65%, respectively. The solutions are also used to develop a factor-based metric for the detection of early, untreated Parkinson's disease. The metric stratifies healthy subjects from suspected Parkinson's patients (based on the graphical method). The analysis shows that both techniques produce comparable results with similar computational time. The “semi-automatic” approach used by the NMF technique allows clinicians to manually set a starting condition for “warm” starting the optimization in order to facilitate control and efficient interaction with the data.« less

MPI-FAUN: An MPI-Based Framework for Alternating-Updating Nonnegative Matrix Factorization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kannan, Ramakrishnan; Ballard, Grey; Park, Haesun

Non-negative matrix factorization (NMF) is the problem of determining two non-negative low rank factors W and H, for the given input matrix A, such that A≈WH. NMF is a useful tool for many applications in different domains such as topic modeling in text mining, background separation in video analysis, and community detection in social networks. Despite its popularity in the data mining community, there is a lack of efficient parallel algorithms to solve the problem for big data sets. The main contribution of this work is a new, high-performance parallel computational framework for a broad class of NMF algorithms thatmore » iteratively solves alternating non-negative least squares (NLS) subproblems for W and H. It maintains the data and factor matrices in memory (distributed across processors), uses MPI for interprocessor communication, and, in the dense case, provably minimizes communication costs (under mild assumptions). The framework is flexible and able to leverage a variety of NMF and NLS algorithms, including Multiplicative Update, Hierarchical Alternating Least Squares, and Block Principal Pivoting. Our implementation allows us to benchmark and compare different algorithms on massive dense and sparse data matrices of size that spans from few hundreds of millions to billions. We demonstrate the scalability of our algorithm and compare it with baseline implementations, showing significant performance improvements. The code and the datasets used for conducting the experiments are available online.« less

MPI-FAUN: An MPI-Based Framework for Alternating-Updating Nonnegative Matrix Factorization

DOE PAGES

Kannan, Ramakrishnan; Ballard, Grey; Park, Haesun

2017-10-30

Non-negative matrix factorization (NMF) is the problem of determining two non-negative low rank factors W and H, for the given input matrix A, such that A≈WH. NMF is a useful tool for many applications in different domains such as topic modeling in text mining, background separation in video analysis, and community detection in social networks. Despite its popularity in the data mining community, there is a lack of efficient parallel algorithms to solve the problem for big data sets. The main contribution of this work is a new, high-performance parallel computational framework for a broad class of NMF algorithms thatmore » iteratively solves alternating non-negative least squares (NLS) subproblems for W and H. It maintains the data and factor matrices in memory (distributed across processors), uses MPI for interprocessor communication, and, in the dense case, provably minimizes communication costs (under mild assumptions). The framework is flexible and able to leverage a variety of NMF and NLS algorithms, including Multiplicative Update, Hierarchical Alternating Least Squares, and Block Principal Pivoting. Our implementation allows us to benchmark and compare different algorithms on massive dense and sparse data matrices of size that spans from few hundreds of millions to billions. We demonstrate the scalability of our algorithm and compare it with baseline implementations, showing significant performance improvements. The code and the datasets used for conducting the experiments are available online.« less

Spatial operator factorization and inversion of the manipulator mass matrix

NASA Technical Reports Server (NTRS)

Rodriguez, Guillermo; Kreutz-Delgado, Kenneth

1992-01-01

This paper advances two linear operator factorizations of the manipulator mass matrix. Embedded in the factorizations are many of the techniques that are regarded as very efficient computational solutions to inverse and forward dynamics problems. The operator factorizations provide a high-level architectural understanding of the mass matrix and its inverse, which is not visible in the detailed algorithms. They also lead to a new approach to the development of computer programs or organize complexity in robot dynamics.

Matrix Effects in Quantitative Assessment of Pharmaceutical Tablets Using Transmission Raman and Near-Infrared (NIR) Spectroscopy.

PubMed

Sparén, Anders; Hartman, Madeleine; Fransson, Magnus; Johansson, Jonas; Svensson, Olof

2015-05-01

Raman spectroscopy can be an alternative to near-infrared spectroscopy (NIR) for nondestructive quantitative analysis of solid pharmaceutical formulations. Compared with NIR spectra, Raman spectra have much better selectivity, but subsampling was always an issue for quantitative assessment. Raman spectroscopy in transmission mode has reduced this issue, since a large volume of the sample is measured in transmission mode. The sample matrix, such as particle size of the drug substance in a tablet, may affect the Raman signal. In this work, matrix effects in transmission NIR and Raman spectroscopy were systematically investigated for a solid pharmaceutical formulation. Tablets were manufactured according to an experimental design, varying the factors particle size of the drug substance (DS), particle size of the filler, compression force, and content of drug substance. All factors were varied at two levels plus a center point, except the drug substance content, which was varied at five levels. Six tablets from each experimental point were measured with transmission NIR and Raman spectroscopy, and their concentration of DS was determined for a third of those tablets. Principal component analysis of NIR and Raman spectra showed that the drug substance content and particle size, the particle size of the filler, and the compression force affected both NIR and Raman spectra. For quantitative assessment, orthogonal partial least squares regression was applied. All factors varied in the experimental design influenced the prediction of the DS content to some extent, both for NIR and Raman spectroscopy, the particle size of the filler having the largest effect. When all matrix variations were included in the multivariate calibrations, however, good predictions of all types of tablets were obtained, both for NIR and Raman spectroscopy. The prediction error using transmission Raman spectroscopy was about 30% lower than that obtained with transmission NIR spectroscopy.

A Study of the Critical Factors Controlling the Synthesis of Ceramic Matrix Composites from Preceramic Polymers.

DTIC Science & Technology

1988-04-15

physical properties of a polycarbosilane preceramic polymer as a function of temperature to derive synthesis methodology for SiC matrix composites , (2...investigate the role of interface modification in creating tough carbon fiber reinforced SiC matrix composites . RESEARCH PROGRESS Preceramic Polymer ...Classfication) A STUDY OF THE CRITICAL FACTORS CONTROLLING THE SYNTHESIS OF CERAMIC MATRIX COMPOSITES FROM PRECERAMIC POLYMERS 12. PERSONAL AUTHOR(S

A fast efficient implicit scheme for the gasdynamic equations using a matrix reduction technique

NASA Technical Reports Server (NTRS)

Barth, T. J.; Steger, J. L.

1985-01-01

An efficient implicit finite-difference algorithm for the gasdynamic equations utilizing matrix reduction techniques is presented. A significant reduction in arithmetic operations is achieved without loss of the stability characteristics generality found in the Beam and Warming approximate factorization algorithm. Steady-state solutions to the conservative Euler equations in generalized coordinates are obtained for transonic flows and used to show that the method offers computational advantages over the conventional Beam and Warming scheme. Existing Beam and Warming codes can be retrofit with minimal effort. The theoretical extension of the matrix reduction technique to the full Navier-Stokes equations in Cartesian coordinates is presented in detail. Linear stability, using a Fourier stability analysis, is demonstrated and discussed for the one-dimensional Euler equations.

Generating Nonnormal Multivariate Data Using Copulas: Applications to SEM.

PubMed

Mair, Patrick; Satorra, Albert; Bentler, Peter M

2012-07-01

This article develops a procedure based on copulas to simulate multivariate nonnormal data that satisfy a prespecified variance-covariance matrix. The covariance matrix used can comply with a specific moment structure form (e.g., a factor analysis or a general structural equation model). Thus, the method is particularly useful for Monte Carlo evaluation of structural equation models within the context of nonnormal data. The new procedure for nonnormal data simulation is theoretically described and also implemented in the widely used R environment. The quality of the method is assessed by Monte Carlo simulations. A 1-sample test on the observed covariance matrix based on the copula methodology is proposed. This new test for evaluating the quality of a simulation is defined through a particular structural model specification and is robust against normality violations.

Matrix-effect free multi-residue analysis of veterinary drugs in food samples of animal origin by nanoflow liquid chromatography high resolution mass spectrometry.

PubMed

Alcántara-Durán, Jaime; Moreno-González, David; Gilbert-López, Bienvenida; Molina-Díaz, Antonio; García-Reyes, Juan F

2018-04-15

In this work, a sensitive method based on nanoflow liquid chromatography high-resolution mass spectrometry has been developed for the multiresidue determination of veterinary drugs residues in honey, veal muscle, egg and milk. Salting-out supported liquid extraction was employed as sample treatment for milk, veal muscle and egg, while a modified QuEChERS procedure was used in honey. The enhancement of sensitivity provided by the nanoflow LC system also allowed the implementation of high dilution factors as high as 100:1. For all matrices tested, matrix effects were negligible starting from a dilution factor of 100, enabling, thus, the use of external standard calibration instead of matrix-matched calibration of each sample, and the subsequent increase of laboratory throughput. At spiked levels as low as 0.1 or 1 µg kg -1 before the 1:100 dilution, the obtained signals were still significantly higher than the instrumental limit of quantitation (S/N 10). Copyright © 2017 Elsevier Ltd. All rights reserved.

On non-negative matrix factorization algorithms for signal-dependent noise with application to electromyography data

PubMed Central

Devarajan, Karthik; Cheung, Vincent C.K.

2017-01-01

Non-negative matrix factorization (NMF) by the multiplicative updates algorithm is a powerful machine learning method for decomposing a high-dimensional nonnegative matrix V into two nonnegative matrices, W and H where V ~ WH. It has been successfully applied in the analysis and interpretation of large-scale data arising in neuroscience, computational biology and natural language processing, among other areas. A distinctive feature of NMF is its nonnegativity constraints that allow only additive linear combinations of the data, thus enabling it to learn parts that have distinct physical representations in reality. In this paper, we describe an information-theoretic approach to NMF for signal-dependent noise based on the generalized inverse Gaussian model. Specifically, we propose three novel algorithms in this setting, each based on multiplicative updates and prove monotonicity of updates using the EM algorithm. In addition, we develop algorithm-specific measures to evaluate their goodness-of-fit on data. Our methods are demonstrated using experimental data from electromyography studies as well as simulated data in the extraction of muscle synergies, and compared with existing algorithms for signal-dependent noise. PMID:24684448

Discriminative non-negative matrix factorization (DNMF) and its application to the fault diagnosis of diesel engine

NASA Astrophysics Data System (ADS)

Yang, Yong-sheng; Ming, An-bo; Zhang, You-yun; Zhu, Yong-sheng

2017-10-01

Diesel engines, widely used in engineering, are very important for the running of equipments and their fault diagnosis have attracted much attention. In the past several decades, the image based fault diagnosis methods have provided efficient ways for the diesel engine fault diagnosis. By introducing the class information into the traditional non-negative matrix factorization (NMF), an improved NMF algorithm named as discriminative NMF (DNMF) was developed and a novel imaged based fault diagnosis method was proposed by the combination of the DNMF and the KNN classifier. Experiments performed on the fault diagnosis of diesel engine were used to validate the efficacy of the proposed method. It is shown that the fault conditions of diesel engine can be efficiently classified by the proposed method using the coefficient matrix obtained by DNMF. Compared with the original NMF (ONMF) and principle component analysis (PCA), the DNMF can represent the class information more efficiently because the class characters of basis matrices obtained by the DNMF are more visible than those in the basis matrices obtained by the ONMF and PCA.

Decomposing Time Series Data by a Non-negative Matrix Factorization Algorithm with Temporally Constrained Coefficients

PubMed Central

Cheung, Vincent C. K.; Devarajan, Karthik; Severini, Giacomo; Turolla, Andrea; Bonato, Paolo

2017-01-01

The non-negative matrix factorization algorithm (NMF) decomposes a data matrix into a set of non-negative basis vectors, each scaled by a coefficient. In its original formulation, the NMF assumes the data samples and dimensions to be independently distributed, making it a less-than-ideal algorithm for the analysis of time series data with temporal correlations. Here, we seek to derive an NMF that accounts for temporal dependencies in the data by explicitly incorporating a very simple temporal constraint for the coefficients into the NMF update rules. We applied the modified algorithm to 2 multi-dimensional electromyographic data sets collected from the human upper-limb to identify muscle synergies. We found that because it reduced the number of free parameters in the model, our modified NMF made it possible to use the Akaike Information Criterion to objectively identify a model order (i.e., the number of muscle synergies composing the data) that is more functionally interpretable, and closer to the numbers previously determined using ad hoc measures. PMID:26737046

A short-term and long-term comparison of root coverage with an acellular dermal matrix and a subepithelial graft.

PubMed

Harris, Randall J

2004-05-01

Obtaining predictable and esthetic root coverage has become important. Unfortunately, there is only a limited amount of information available on the long-term results of root coverage procedures. The goal of this study was to evaluate the short-term and long-term root coverage results obtained with an acellular dermal matrix and a subepithelial graft. An a priori power analysis was done to determine that 25 was an adequate sample size for each group in this study. Twenty-five patients treated with either an acellular dermal matrix or a subepithelial graft for root coverage were included in this study. The short-term (mean 12.3 to 13.2 weeks) and long-term (mean 48.1 to 49.2 months) results were compared. Additionally, various factors were evaluated to determine whether they could affect the results. This study was a retrospective study of patients in a fee-for-service private periodontal practice. The patients were not randomly assigned to treatment groups. The mean root coverages for the short-term acellular dermal matrix (93.4%), short-term subepithelial graft (96.6%), and long-term subepithelial graft (97.0%) were statistically similar. All three were statistically greater than the long-term acellular dermal matrix mean root coverage (65.8%). Similar results were noted in the change in recession. There were smaller probing reductions and less of an increase in keratinized tissue with the acellular dermal matrix than the subepithelial graft. None of the factors evaluated resulted in the acellular dermal graft having a statistically significant better result than the subepithelial graft. However, in long-term cases where multiple defects were treated with an acellular dermal matrix, the mean root coverage (70.8%) was greater than the mean root coverage in long-term cases where a single defect was treated with an acellular dermal matrix (50.0%). The mean results with the subepithelial graft held up with time better than the mean results with an acellular dermal matrix. However, the results were not universal. In 32.0% of the cases treated with an acellular dermal matrix, the results improved or remained stable with time.

POLYMAT-C: a comprehensive SPSS program for computing the polychoric correlation matrix.

PubMed

Lorenzo-Seva, Urbano; Ferrando, Pere J

2015-09-01

We provide a free noncommercial SPSS program that implements procedures for (a) obtaining the polychoric correlation matrix between a set of ordered categorical measures, so that it can be used as input for the SPSS factor analysis (FA) program; (b) testing the null hypothesis of zero population correlation for each element of the matrix by using appropriate simulation procedures; (c) obtaining valid and accurate confidence intervals via bootstrap resampling for those correlations found to be significant; and (d) performing, if necessary, a smoothing procedure that makes the matrix amenable to any FA estimation procedure. For the main purpose (a), the program uses a robust unified procedure that allows four different types of estimates to be obtained at the user's choice. Overall, we hope the program will be a very useful tool for the applied researcher, not only because it provides an appropriate input matrix for FA, but also because it allows the researcher to carefully check the appropriateness of the matrix for this purpose. The SPSS syntax, a short manual, and data files related to this article are available as Supplemental materials that are available for download with this article.

Convex Banding of the Covariance Matrix

PubMed Central

Bien, Jacob; Bunea, Florentina; Xiao, Luo

2016-01-01

We introduce a new sparse estimator of the covariance matrix for high-dimensional models in which the variables have a known ordering. Our estimator, which is the solution to a convex optimization problem, is equivalently expressed as an estimator which tapers the sample covariance matrix by a Toeplitz, sparsely-banded, data-adaptive matrix. As a result of this adaptivity, the convex banding estimator enjoys theoretical optimality properties not attained by previous banding or tapered estimators. In particular, our convex banding estimator is minimax rate adaptive in Frobenius and operator norms, up to log factors, over commonly-studied classes of covariance matrices, and over more general classes. Furthermore, it correctly recovers the bandwidth when the true covariance is exactly banded. Our convex formulation admits a simple and efficient algorithm. Empirical studies demonstrate its practical effectiveness and illustrate that our exactly-banded estimator works well even when the true covariance matrix is only close to a banded matrix, confirming our theoretical results. Our method compares favorably with all existing methods, in terms of accuracy and speed. We illustrate the practical merits of the convex banding estimator by showing that it can be used to improve the performance of discriminant analysis for classifying sound recordings. PMID:28042189

Convex Banding of the Covariance Matrix.

PubMed

Bien, Jacob; Bunea, Florentina; Xiao, Luo

2016-01-01

We introduce a new sparse estimator of the covariance matrix for high-dimensional models in which the variables have a known ordering. Our estimator, which is the solution to a convex optimization problem, is equivalently expressed as an estimator which tapers the sample covariance matrix by a Toeplitz, sparsely-banded, data-adaptive matrix. As a result of this adaptivity, the convex banding estimator enjoys theoretical optimality properties not attained by previous banding or tapered estimators. In particular, our convex banding estimator is minimax rate adaptive in Frobenius and operator norms, up to log factors, over commonly-studied classes of covariance matrices, and over more general classes. Furthermore, it correctly recovers the bandwidth when the true covariance is exactly banded. Our convex formulation admits a simple and efficient algorithm. Empirical studies demonstrate its practical effectiveness and illustrate that our exactly-banded estimator works well even when the true covariance matrix is only close to a banded matrix, confirming our theoretical results. Our method compares favorably with all existing methods, in terms of accuracy and speed. We illustrate the practical merits of the convex banding estimator by showing that it can be used to improve the performance of discriminant analysis for classifying sound recordings.

Factors associated with multidisciplinary case conference outcomes in children admitted to a regional hospital in Hong Kong with suspected child abuse: a retrospective case series with internal comparison.

PubMed

Lo, W C; Fung, G Pg; Cheung, P Ch

2017-10-01

In all cases of suspected child abuse, accurate risk assessment is vital to guide further management. This study examined the relationship between risk factors in a risk assessment matrix and child abuse case conference outcomes. Records of all children hospitalised at United Christian Hospital in Hong Kong for suspected child abuse from January 2012 to December 2014 were reviewed. Outcomes of the hospital abuse work-up as concluded in the Multi-Disciplinary Case Conference were categorised as 'established', 'high risk', or 'not established'. All cases of 'established' and 'high risk' were included in the positive case conference outcome group and all cases of 'not established' formed the comparison group. On the other hand, using the Risk Assessment Matrix developed by the California State University, Fresno in 1990, each case was allotted a matrix score of low, intermediate, or high risk in each of 15 matrix domains, and an aggregate matrix score was derived. The effect of individual matrix domain on case conference outcome was analysed. Receiver operating characteristic curve analysis was used to examine the relationship between case conference outcome and aggregate matrix score. In this study, 265 children suspected of being abused were included, with 198 in the positive case conference outcome group and 67 in the comparison group. Three matrix domains (severity and frequency of abuse, location of injuries, and strength of family support systems) were significantly associated with case conference outcome. An aggregate cut-off score of 23 yielded a sensitivity of 91.4% and specificity of 38.2% in relation to outcome of abuse categorisation. Risk assessment should be performed when handling suspected child abuse cases. A high aggregate score should arouse suspicion in all disciplines managing child abuse cases.

Directional variance adjustment: bias reduction in covariance matrices based on factor analysis with an application to portfolio optimization.

PubMed

Bartz, Daniel; Hatrick, Kerr; Hesse, Christian W; Müller, Klaus-Robert; Lemm, Steven

2013-01-01

Robust and reliable covariance estimates play a decisive role in financial and many other applications. An important class of estimators is based on factor models. Here, we show by extensive Monte Carlo simulations that covariance matrices derived from the statistical Factor Analysis model exhibit a systematic error, which is similar to the well-known systematic error of the spectrum of the sample covariance matrix. Moreover, we introduce the Directional Variance Adjustment (DVA) algorithm, which diminishes the systematic error. In a thorough empirical study for the US, European, and Hong Kong stock market we show that our proposed method leads to improved portfolio allocation.

Directional Variance Adjustment: Bias Reduction in Covariance Matrices Based on Factor Analysis with an Application to Portfolio Optimization

PubMed Central

Bartz, Daniel; Hatrick, Kerr; Hesse, Christian W.; Müller, Klaus-Robert; Lemm, Steven

2013-01-01

Robust and reliable covariance estimates play a decisive role in financial and many other applications. An important class of estimators is based on factor models. Here, we show by extensive Monte Carlo simulations that covariance matrices derived from the statistical Factor Analysis model exhibit a systematic error, which is similar to the well-known systematic error of the spectrum of the sample covariance matrix. Moreover, we introduce the Directional Variance Adjustment (DVA) algorithm, which diminishes the systematic error. In a thorough empirical study for the US, European, and Hong Kong stock market we show that our proposed method leads to improved portfolio allocation. PMID:23844016

Systematic R -matrix analysis of the 13C(p ,γ )14N capture reaction

NASA Astrophysics Data System (ADS)

Chakraborty, Suprita; deBoer, Richard; Mukherjee, Avijit; Roy, Subinit

2015-04-01

Background: The proton capture reaction 13C(p ,γ )14N is an important reaction in the CNO cycle during hydrogen burning in stars with mass greater than the mass of the Sun. It also occurs in astrophysical sites such as red giant stars: the asymptotic giant branch (AGB) stars. The low energy astrophysical S factor of this reaction is dominated by a resonance state at an excitation energy of around 8.06 MeV (Jπ=1-,T =1 ) in 14N. The other significant contributions come from the low energy tail of the broad resonance with Jπ=0-,T =1 at an excitation of 8.78 MeV and the direct capture process. Purpose: Measurements of the low energy astrophysical S factor of the radiative capture reaction 13C(p ,γ )14N reported extrapolated values of S (0 ) that differ by about 30 % . Subsequent R -matrix analysis and potential model calculations also yielded significantly different values for S (0 ) . The present work intends to look into the discrepancy through a detailed R -matrix analysis with emphasis on the associated uncertainties. Method: A systematic reanalysis of the available decay data following the capture to the Jπ=1-,T =1 resonance state of 14N around 8.06 MeV excitation had been performed within the framework of the R -matrix method. A simultaneous analysis of the 13C(p ,p0 ) data, measured over a similar energy range, was carried out with the capture data. The data for the ground state decay of the broad resonance state (Jπ=0-,T =1 ) around 8.78 MeV excitations was included as well. The external capture model along with the background poles to simulate the internal capture contribution were used to estimate the direct capture contribution. The asymptotic normalization constants (ANCs) for all states were extracted from the capture data. The multichannel, multilevel R -matrix code azure2 was used for the calculation. Results: The values of the astrophysical S factor at zero relative energy, resulting from the present analysis, are found to be consistent within the error bars for the two sets of capture data used. However, it is found from the fits to the elastic scattering data that the position of the Jπ=1-,T =1 resonance state is uncertain by about 0.6 keV, preferring an excitation energy value of 8.062 MeV. Also the extracted ANC values for the states of 14N corroborate the values from the transfer reaction studies. The reaction rates from the present calculation are about 10 -15 % lower than the values of the NACRE II compilation but compare well with those from NACRE I. Conclusion: The precise energy of the Jπ=1-,T =1 resonance level around 8.06 MeV in 14N must be determined. Further measurements around and below 100 keV with precision are necessary to reduce the uncertainty in the S -factor value at zero relative energy.

Neutrinoless ββ decay mediated by the exchange of light and heavy neutrinos: the role of nuclear structure correlations

NASA Astrophysics Data System (ADS)

Menéndez, J.

2018-01-01

Neutrinoless β β decay nuclear matrix elements calculated with the shell model and energy-density functional theory typically disagree by more than a factor of two in the standard scenario of light-neutrino exchange. In contrast, for a decay mediated by sterile heavy neutrinos the deviations are reduced to about 50%, an uncertainty similar to the one due to short-range effects. We compare matrix elements in the light- and heavy-neutrino-exchange channels, exploring the radial, momentum transfer and angular momentum-parity matrix element distributions, and considering transitions that involve correlated and uncorrelated nuclear states. We argue that the shorter-range heavy-neutrino exchange is less sensitive to collective nuclear correlations, and that discrepancies in matrix elements are mostly due to the treatment of long-range correlations in many-body calculations. Our analysis supports previous studies suggesting that isoscalar pairing correlations, which affect mostly the longer-range part of the neutrinoless β β decay operator, are partially responsible for the differences between nuclear matrix elements in the standard light-neutrino-exchange mechanism.

Dynamics of VEGF matrix-retention in vascular network patterning

NASA Astrophysics Data System (ADS)

Köhn-Luque, A.; de Back, W.; Yamaguchi, Y.; Yoshimura, K.; Herrero, M. A.; Miura, T.

2013-12-01

Vascular endothelial growth factor (VEGF) is a central regulator of blood vessel morphogenesis, although its role in patterning of endothelial cells into vascular networks is not fully understood. It has been suggested that binding of soluble VEGF to extracellular matrix components causes spatially restricted cues that guide endothelial cells into network patterns. Yet, current evidence for such a mechanism remains indirect. In this study, we quantitatively analyse the dynamics of VEGF retention in a controlled in vitro situation of human umbilical vascular endothelial cells (HUVECs) in Matrigel. We show that fluorescent VEGF accumulates in pericellular areas and colocalizes with VEGF binding molecules. Analysis of fluorescence recovery after photobleaching reveals that binding/unbinding to matrix molecules dominates VEGF dynamics in the pericellular region. Computational simulations using our experimental measurements of kinetic parameters show that matrix retention of chemotactic signals can lead to the formation of reticular cellular networks on a realistic timescale. Taken together, these results show that VEGF binds to matrix molecules in proximity of HUVECs in Matrigel, and suggest that bound VEGF drives vascular network patterning.

LOXL4 Is Induced by Transforming Growth Factor β1 through Smad and JunB/Fra2 and Contributes to Vascular Matrix Remodeling

PubMed Central

Busnadiego, Oscar; González-Santamaría, José; Lagares, David; Guinea-Viniegra, Juan; Pichol-Thievend, Cathy; Muller, Laurent

2013-01-01

Transforming growth factor β1 (TGF-β1) is a pleiotropic factor involved in the regulation of extracellular matrix (ECM) synthesis and remodeling. In search for novel genes mediating the action of TGF-β1 on vascular ECM, we identified the member of the lysyl oxidase family of matrix-remodeling enzymes, lysyl oxidase-like 4 (LOXL4), as a direct target of TGF-β1 in aortic endothelial cells, and we dissected the molecular mechanism of its induction. Deletion mapping and mutagenesis analysis of the LOXL4 promoter demonstrated the absolute requirement of a distal enhancer containing an activator protein 1 (AP-1) site and a Smad binding element for TGF-β1 to induce LOXL4 expression. Functional cooperation between Smad proteins and the AP-1 complex composed of JunB/Fra2 accounted for the action of TGF-β1, which involved the extracellular signal-regulated kinase (ERK)-dependent phosphorylation of Fra2. We furthermore provide evidence that LOXL4 was extracellularly secreted and significantly contributed to ECM deposition and assembly. These results suggest that TGF-β1-dependent expression of LOXL4 plays a role in vascular ECM homeostasis, contributing to vascular processes associated with ECM remodeling and fibrosis. PMID:23572561

Characterization of solid polymer dispersions of active pharmaceutical ingredients by 19F MAS NMR and factor analysis

NASA Astrophysics Data System (ADS)

Urbanova, Martina; Brus, Jiri; Sedenkova, Ivana; Policianova, Olivia; Kobera, Libor

In this contribution the ability of 19F MAS NMR spectroscopy to probe structural variability of poorly water-soluble drugs formulated as solid dispersions in polymer matrices is discussed. The application potentiality of the proposed approach is demonstrated on a moderately sized active pharmaceutical ingredient (API, Atorvastatin) exhibiting extensive polymorphism. In this respect, a range of model systems with the API incorporated in the matrix of polvinylpyrrolidone (PVP) was prepared. The extent of mixing of both components was determined by T1(1H) and T1ρ(1H) relaxation experiments, and it was found that the API forms nanosized domains. Subsequently it was found out that the polymer matrix induces two kinds of changes in 19F MAS NMR spectra. At first, this is a high-frequency shift reaching 2-3 ppm which is independent on molecular structure of the API and which results from the long-range polarization of the electron cloud around 19F nucleus induced by electrostatic fields of the polymer matrix. At second, this is broadening of the signals and formation of shoulders reflecting changes in molecular arrangement of the API. To avoid misleading in the interpretation of the recorded 19F MAS NMR spectra, because both the contributions act simultaneously, we applied chemometric approach based on multivariate analysis. It is demonstrated that factor analysis of the recorded spectra can separate both these spectral contributions, and the subtle structural differences in the molecular arrangement of the API in the nanosized domains can be traced. In this way 19F MAS NMR spectra of both pure APIs and APIs in solid dispersions can be directly compared. The proposed strategy thus provides a powerful tool for the analysis of new formulations of fluorinated pharmaceutical substances in polymer matrices.

Reduction of interferences in the analysis of Children's Dimetapp using ultraviolet spectroscopy data and target factor analysis

NASA Astrophysics Data System (ADS)

Msimanga, Huggins Z.; Lam, Truong Thach Ho; Latinwo, Nathaniel; Song, Mihyang Kristy; Tavakoli, Newsha

2018-03-01

A calibration matrix has been developed and successfully applied to quantify actives in Children's Dimetapp®, a cough mixture whose active components suffer from heavy spectral interference. High-performance liquid chromatography/photodiode array instrument was used to identify the actives and any other UV-detectable excipients that might contribute to interferences. The instrument was also used to obtain reference data on the actives, instead of relying on the manufacturer's claims. Principal component analysis was used during the developmental stages of the calibration matrix to highlight any mismatch between the calibration and sample spectra, making certain that "apples" were not compared with "oranges". The prediction model was finally calculated using target factor analysis and partial least squares regression. In addition to the actives in Children's Dimetapp® (brompheniramine maleate, phenylephrine hydrogen chloride, and dextromethorphan hydrogen bromide), sodium benzoate was identified as the major and FD&C Blue #1, FD&C Red #40, and methyl anthranilate as minor spectral interferences. Model predictions were compared before and after the interferences were included into the calibration matrix. Before including interferences, the following results were obtained: brompheniramine maleate = 481.3 mg L- 1 ± 134% RE; phenylephrine hydrogen chloride = 1041 mg L- 1 ± 107% RE; dextromethorphan hydrogen bromide = 1571 mg L- 1 ± 107% RE, where % RE = percent relative error based on the reference HPLC data. After including interferences, the results were as follows: brompheniramine maleate = 196.3 mg L- 1 ± 4.4% RE; phenylephrine hydrogen chloride = 501.3 mg L- 1 ± 0.10% RE; dextromethorphan hydrogen bromide = 998.7 mg L- 1 ± 1.6% RE as detailed in Table 6.

Determination of the thermodynamic correction factor of fluids confined in nano-metric slit pores from molecular simulation

NASA Astrophysics Data System (ADS)

Collell, Julien; Galliero, Guillaume

2014-05-01

The multi-component diffusive mass transport is generally quantified by means of the Maxwell-Stefan diffusion coefficients when using molecular simulations. These coefficients can be related to the Fick diffusion coefficients using the thermodynamic correction factor matrix, which requires to run several simulations to estimate all the elements of the matrix. In a recent work, Schnell et al. ["Thermodynamics of small systems embedded in a reservoir: A detailed analysis of finite size effects," Mol. Phys. 110, 1069-1079 (2012)] developed an approach to determine the full matrix of thermodynamic factors from a single simulation in bulk. This approach relies on finite size effects of small systems on the density fluctuations. We present here an extension of their work for inhomogeneous Lennard Jones fluids confined in slit pores. We first verified this extension by cross validating the results obtained from this approach with the results obtained from the simulated adsorption isotherms, which allows to determine the thermodynamic factor in porous medium. We then studied the effects of the pore width (from 1 to 15 molecular sizes), of the solid-fluid interaction potential (Lennard Jones 9-3, hard wall potential) and of the reduced fluid density (from 0.1 to 0.7 at a reduced temperature T* = 2) on the thermodynamic factor. The deviation of the thermodynamic factor compared to its equivalent bulk value decreases when increasing the pore width and becomes insignificant for reduced pore width above 15. We also found that the thermodynamic factor is sensitive to the magnitude of the fluid-fluid and solid-fluid interactions, which softens or exacerbates the density fluctuations.

Determination of the thermodynamic correction factor of fluids confined in nano-metric slit pores from molecular simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Collell, Julien; Galliero, Guillaume, E-mail: guillaume.galliero@univ-pau.fr

2014-05-21

The multi-component diffusive mass transport is generally quantified by means of the Maxwell-Stefan diffusion coefficients when using molecular simulations. These coefficients can be related to the Fick diffusion coefficients using the thermodynamic correction factor matrix, which requires to run several simulations to estimate all the elements of the matrix. In a recent work, Schnell et al. [“Thermodynamics of small systems embedded in a reservoir: A detailed analysis of finite size effects,” Mol. Phys. 110, 1069–1079 (2012)] developed an approach to determine the full matrix of thermodynamic factors from a single simulation in bulk. This approach relies on finite size effectsmore » of small systems on the density fluctuations. We present here an extension of their work for inhomogeneous Lennard Jones fluids confined in slit pores. We first verified this extension by cross validating the results obtained from this approach with the results obtained from the simulated adsorption isotherms, which allows to determine the thermodynamic factor in porous medium. We then studied the effects of the pore width (from 1 to 15 molecular sizes), of the solid-fluid interaction potential (Lennard Jones 9-3, hard wall potential) and of the reduced fluid density (from 0.1 to 0.7 at a reduced temperature T* = 2) on the thermodynamic factor. The deviation of the thermodynamic factor compared to its equivalent bulk value decreases when increasing the pore width and becomes insignificant for reduced pore width above 15. We also found that the thermodynamic factor is sensitive to the magnitude of the fluid-fluid and solid-fluid interactions, which softens or exacerbates the density fluctuations.« less

An Efficient Scheme for Updating Sparse Cholesky Factors

NASA Technical Reports Server (NTRS)

Raghavan, Padma

2002-01-01

Raghavan had earlier developed the software package DCSPACK which can be used for solving sparse linear systems where the coefficient matrix is symmetric and positive definite (this project was not funded by NASA but by agencies such as NSF). DSCPACK-S is the serial code and DSCPACK-P is a parallel implementation suitable for multiprocessors or networks-of-workstations with message passing using MCI. The main algorithm used is the Cholesky factorization of a sparse symmetric positive positive definite matrix A = LL(T). The code can also compute the factorization A = LDL(T). The complexity of the software arises from several factors relating to the sparsity of the matrix A. A sparse N x N matrix A has typically less that cN nonzeroes where c is a small constant. If the matrix were dense, it would have O(N2) nonzeroes. The most complicated part of such sparse Cholesky factorization relates to fill-in, i.e., zeroes in the original matrix that become nonzeroes in the factor L. An efficient implementation depends to a large extent on complex data structures and on techniques from graph theory to reduce, identify, and manage fill. DSCPACK is based on an efficient multifrontal implementation with fill-managing algorithms and implementation arising from earlier research by Raghavan and others. Sparse Cholesky factorization is typically a four step process: (1) ordering to compute a fill-reducing numbering, (2) symbolic factorization to determine the nonzero structure of L, (3) numeric factorization to compute L, and, (4) triangular solution to solve L(T)x = y and Ly = b. The first two steps are symbolic and are performed using the graph of the matrix. The numeric factorization step is of dominant cost and there are several schemes for improving performance by exploiting the nested and dense structure of groups of columns in the factor. The latter are aimed at better utilization of the cache-memory hierarchy on modem processors to prevent cache-misses and provide execution rates (operations/second) that are close to the peak rates for dense matrix computations. Currently, EPISCOPACY is being used in an application at NASA directed by J. Newman and M. James. We propose the implementation of efficient schemes for updating the LL(T) or LDL(T) factors computed in DSCPACK-S to meet the computational requirements of their project. A brief description is provided in the next section.

HIGH DIMENSIONAL COVARIANCE MATRIX ESTIMATION IN APPROXIMATE FACTOR MODELS.

PubMed

Fan, Jianqing; Liao, Yuan; Mincheva, Martina

2011-01-01

The variance covariance matrix plays a central role in the inferential theories of high dimensional factor models in finance and economics. Popular regularization methods of directly exploiting sparsity are not directly applicable to many financial problems. Classical methods of estimating the covariance matrices are based on the strict factor models, assuming independent idiosyncratic components. This assumption, however, is restrictive in practical applications. By assuming sparse error covariance matrix, we allow the presence of the cross-sectional correlation even after taking out common factors, and it enables us to combine the merits of both methods. We estimate the sparse covariance using the adaptive thresholding technique as in Cai and Liu (2011), taking into account the fact that direct observations of the idiosyncratic components are unavailable. The impact of high dimensionality on the covariance matrix estimation based on the factor structure is then studied.

Electrical Spin Driving by g -Matrix Modulation in Spin-Orbit Qubits

NASA Astrophysics Data System (ADS)

Crippa, Alessandro; Maurand, Romain; Bourdet, Léo; Kotekar-Patil, Dharmraj; Amisse, Anthony; Jehl, Xavier; Sanquer, Marc; Laviéville, Romain; Bohuslavskyi, Heorhii; Hutin, Louis; Barraud, Sylvain; Vinet, Maud; Niquet, Yann-Michel; De Franceschi, Silvano

2018-03-01

In a semiconductor spin qubit with sizable spin-orbit coupling, coherent spin rotations can be driven by a resonant gate-voltage modulation. Recently, we have exploited this opportunity in the experimental demonstration of a hole spin qubit in a silicon device. Here we investigate the underlying physical mechanisms by measuring the full angular dependence of the Rabi frequency, as well as the gate-voltage dependence and anisotropy of the hole g factor. We show that a g -matrix formalism can simultaneously capture and discriminate the contributions of two mechanisms so far independently discussed in the literature: one associated with the modulation of the g factor, and measurable by Zeeman energy spectroscopy, the other not. Our approach has a general validity and can be applied to the analysis of other types of spin-orbit qubits.

Eigenvalue-eigenvector decomposition (EED) analysis of dissimilarity and covariance matrix obtained from total synchronous fluorescence spectral (TSFS) data sets of herbal preparations: Optimizing the classification approach

NASA Astrophysics Data System (ADS)

Tarai, Madhumita; Kumar, Keshav; Divya, O.; Bairi, Partha; Mishra, Kishor Kumar; Mishra, Ashok Kumar

2017-09-01

The present work compares the dissimilarity and covariance based unsupervised chemometric classification approaches by taking the total synchronous fluorescence spectroscopy data sets acquired for the cumin and non-cumin based herbal preparations. The conventional decomposition method involves eigenvalue-eigenvector analysis of the covariance of the data set and finds the factors that can explain the overall major sources of variation present in the data set. The conventional approach does this irrespective of the fact that the samples belong to intrinsically different groups and hence leads to poor class separation. The present work shows that classification of such samples can be optimized by performing the eigenvalue-eigenvector decomposition on the pair-wise dissimilarity matrix.

Multivariate methods on the excitation emission matrix fluorescence spectroscopic data of diesel-kerosene mixtures: a comparative study.

PubMed

Divya, O; Mishra, Ashok K

2007-05-29

Quantitative determination of kerosene fraction present in diesel has been carried out based on excitation emission matrix fluorescence (EEMF) along with parallel factor analysis (PARAFAC) and N-way partial least squares regression (N-PLS). EEMF is a simple, sensitive and nondestructive method suitable for the analysis of multifluorophoric mixtures. Calibration models consisting of varying compositions of diesel and kerosene were constructed and their validation was carried out using leave-one-out cross validation method. The accuracy of the model was evaluated through the root mean square error of prediction (RMSEP) for the PARAFAC, N-PLS and unfold PLS methods. N-PLS was found to be a better method compared to PARAFAC and unfold PLS method because of its low RMSEP values.

Normal and radial impact of composites with embedded penny-shaped cracks

NASA Technical Reports Server (NTRS)

Sih, G. C.

1979-01-01

A method is developed for the dynamic stress analysis of a layered composite containing an embedded penny-shaped crack and subjected to normal and radial impact. The material properties of the layers are chosen such that the crack lies in a layer of matrix material while the surrounding material possesses the average elastic properties of a two-phase medium consisting of a large number of fibers embedded in the matrix. Quantitatively, the time-dependent stresses near the crack border can be described by the dynamic stress intensity factors. Their magnitude depends on time, on the material properties of the composite and on the relative size of the crack compared to the composite local geometry. Results obtained show that, for the same material properties and geometry of the composite, the dynamic stress intensity factors for an embedded (penny-shaped) crack reach their peak values within a shorter period of time and with a lower magnitude than the corresponding dynamic stress intensity factors for a through-crack.

Analytical quality assurance in veterinary drug residue analysis methods: matrix effects determination and monitoring for sulfonamides analysis.

PubMed

Hoff, Rodrigo Barcellos; Rübensam, Gabriel; Jank, Louise; Barreto, Fabiano; Peralba, Maria do Carmo Ruaro; Pizzolato, Tânia Mara; Silvia Díaz-Cruz, M; Barceló, Damià

2015-01-01

In residue analysis of veterinary drugs in foodstuff, matrix effects are one of the most critical points. This work present a discuss considering approaches used to estimate, minimize and monitoring matrix effects in bioanalytical methods. Qualitative and quantitative methods for estimation of matrix effects such as post-column infusion, slopes ratios analysis, calibration curves (mathematical and statistical analysis) and control chart monitoring are discussed using real data. Matrix effects varying in a wide range depending of the analyte and the sample preparation method: pressurized liquid extraction for liver samples show matrix effects from 15.5 to 59.2% while a ultrasound-assisted extraction provide values from 21.7 to 64.3%. The matrix influence was also evaluated: for sulfamethazine analysis, losses of signal were varying from -37 to -96% for fish and eggs, respectively. Advantages and drawbacks are also discussed considering a workflow for matrix effects assessment proposed and applied to real data from sulfonamides residues analysis. Copyright © 2014 Elsevier B.V. All rights reserved.

Planning and Analysis of Fractured Rock Injection Tests in the Cerro Brillador Underground Laboratory, Northern Chile

NASA Astrophysics Data System (ADS)

Fairley, J. P., Jr.; Oyarzún L, R.; Villegas, G.

2015-12-01

Early theories of fluid migration in unsaturated fractured rock hypothesized that matrix suction would dominate flow up to the point of matrix saturation. However, experiments in underground laboratories such as the ESF (Yucca Mountain, NV) have demonstrated that liquid water can migrate significant distances through fractures in an unsaturated porous medium, suggesting limited interaction between fractures and unsaturated matrix blocks and potentially rapid transmission of recharge to the sat- urated zone. Determining the conditions under which this rapid recharge may take place is an important factor in understanding deep percolation processes in arid areas with thick unsaturated zones. As part of an on-going, Fondecyt-funded project (award 11150587) to study mountain block hydrological processes in arid regions, we are plan- ning a series of in-situ fracture flow injection tests in the Cerro Brillador/Mina Escuela, an underground laboratory and teaching facility belonging to the Universidad la Serena, Chile. Planning for the tests is based on an analytical model and curve-matching method, originally developed to evaluate data from injection tests at Yucca Mountain (Fairley, J.P., 2010, WRR 46:W08542), that uses a known rate of liquid injection to a fracture (for example, from a packed-off section of borehole) and the observed rate of seepage discharging from the fracture to estimate effective fracture aperture, matrix sorptivity, fracture/matrix flow partitioning, and the wetted fracture/matrix interac- tion area between the injection and recovery points. We briefly review the analytical approach and its application to test planning and analysis, and describe the proposed tests and their goals.

Effects of the antirheumatic remedy hox alpha--a new stinging nettle leaf extract--on matrix metalloproteinases in human chondrocytes in vitro.

PubMed

Schulze-Tanzil, G; de, Souza P; Behnke, B; Klingelhoefer, S; Scheid, A; Shakibaei, M

2002-04-01

Inflammatory joint diseases are characterized by enhanced extracellular matrix degradation which is predominantly mediated by cytokine-stimulated upregulation of matrix metalloproteinase (MMP) expression. Besides tumour necrosis factor-alpha (TNF-alpha), Interleukin-1beta (IL-1beta) produced by articular chondrocytes and synovial macrophages, is the most important cytokine stimulating MMP expression under inflammatory conditions. Blockade of these two cytokines and their downstream effectors are suitable molecular targets of antirheumatic therapy. Hox alpha is a novel stinging nettle (Urtica dioica/Urtica urens) leaf extract used for treatment of rheumatic diseases. The aim of the present study was to clarify the effects of Hox alpha and the monosubstance 13-HOTrE (13-Hydroxyoctadecatrienic acid) on the expression of matrix metalloproteinase-1, -3 and -9 proteins (MMP-1, -3, -9). Human chondrocytes were cultured on collagen type-II-coated petri dishes, exposed to IL-1beta and treated with or without Hox alpha and 13-HOTrE. A close analysis by immunofluorescence microscopy and western blot analysis showed that Hox alpha and 13-HOTrE significantly suppressed IL-1beta-induced expression of matrix metalloproteinase-1, -3 and -9 proteins on the chondrocytes in vitro. The potential of Hox alpha and 13-HOTrE to suppress the expression of matrix metalloproteinases may explain the clinical efficacy of stinging nettle leaf extracts in treatment of rheumatoid arthritis. These results suggest that the monosubstance 13-HOTrE is one of the more active antiinflammatory substances in Hox alpha and that Hox alpha may be a promising remedy for therapy of inflammatory joint diseases.

Cost analysis of composite fan blade manufacturing processes

NASA Technical Reports Server (NTRS)

Stelson, T. S.; Barth, C. F.

1980-01-01

The relative manufacturing costs were estimated for large high technology fan blades prepared by advanced composite fabrication methods using seven candidate materials/process systems. These systems were identified as laminated resin matrix composite, filament wound resin matrix composite, superhybrid solid laminate, superhybrid spar/shell, metal matrix composite, metal matrix composite with a spar and shell, and hollow titanium. The costs were calculated utilizing analytical process models and all cost data are presented as normalized relative values where 100 was the cost of a conventionally forged solid titanium fan blade whose geometry corresponded to a size typical of 42 blades per disc. Four costs were calculated for each of the seven candidate systems to relate the variation of cost on blade size. Geometries typical of blade designs at 24, 30, 36 and 42 blades per disc were used. The impact of individual process yield factors on costs was also assessed as well as effects of process parameters, raw materials, labor rates and consumable items.

Tensile behavior of unidirectional and cross-ply CMC`s

DOE Office of Scientific and Technical Information (OSTI.GOV)

Herrmann, R.K.; Kampe, S.L.

1996-12-31

The tensile behavior of two ceramic matrix composites (CMC`s) was observed. The materials of interest in this study were a glass-ceramic matrix composite (GCMC) and a Blackglas{trademark} matrix composite, both reinforced with Nicalon (SiC) fibers. Both composites were produced in laminate form with a symmetric cross-ply layup. Microstructural observations indicated the presence of significant porosity and some cracking in the Blackglas{trademark} samples, while the GCMC samples showed considerably less damage. From the observed tensile behavior of the cross-ply composites, a {open_quote}back-out{close_quote} factor for determining the unidirectional, 0{degrees} ply data of the composites was calculated using Classical Lamination Theory (CLT) andmore » compared to actual data. While the tensile properties obtained from the Blackglas{trademark} composites showed good correlation with the back-calculated values, those from the GCMC did not. Analysis indicates that the applicability of this technique is strongly influenced by the initial matrix microstructure of the composite, i.e., porosity and cracking present following processing.« less

Designing Feature and Data Parallel Stochastic Coordinate Descent Method forMatrix and Tensor Factorization

DTIC Science & Technology

2016-05-11

AFRL-AFOSR-JP-TR-2016-0046 Designing Feature and Data Parallel Stochastic Coordinate Descent Method for Matrix and Tensor Factorization U Kang Korea...maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or   any other aspect...Designing Feature and Data Parallel Stochastic Coordinate Descent Method for Matrix and Tensor Factorization 5a.  CONTRACT NUMBER 5b.  GRANT NUMBER FA2386

Genetic and environmental variance in content dimensions of the MMPI.

PubMed

Rose, R J

1988-08-01

To evaluate genetic and environmental variance in the Minnesota Multiphasic Personality Inventory (MMPI), I studied nine factor scales identified in the first item factor analysis of normal adult MMPIs in a sample of 820 adolescent and young adult co-twins. Conventional twin comparisons documented heritable variance in six of the nine MMPI factors (Neuroticism, Psychoticism, Extraversion, Somatic Complaints, Inadequacy, and Cynicism), whereas significant influence from shared environmental experience was found for four factors (Masculinity versus Femininity, Extraversion, Religious Orthodoxy, and Intellectual Interests). Genetic variance in the nine factors was more evident in results from twin sisters than those of twin brothers, and a developmental-genetic analysis, using hierarchical multiple regressions of double-entry matrixes of the twins' raw data, revealed that in four MMPI factor scales, genetic effects were significantly modulated by age or gender or their interaction during the developmental period from early adolescence to early adulthood.

Adaptive multi-view clustering based on nonnegative matrix factorization and pairwise co-regularization

NASA Astrophysics Data System (ADS)

Zhang, Tianzhen; Wang, Xiumei; Gao, Xinbo

2018-04-01

Nowadays, several datasets are demonstrated by multi-view, which usually include shared and complementary information. Multi-view clustering methods integrate the information of multi-view to obtain better clustering results. Nonnegative matrix factorization has become an essential and popular tool in clustering methods because of its interpretation. However, existing nonnegative matrix factorization based multi-view clustering algorithms do not consider the disagreement between views and neglects the fact that different views will have different contributions to the data distribution. In this paper, we propose a new multi-view clustering method, named adaptive multi-view clustering based on nonnegative matrix factorization and pairwise co-regularization. The proposed algorithm can obtain the parts-based representation of multi-view data by nonnegative matrix factorization. Then, pairwise co-regularization is used to measure the disagreement between views. There is only one parameter to auto learning the weight values according to the contribution of each view to data distribution. Experimental results show that the proposed algorithm outperforms several state-of-the-arts algorithms for multi-view clustering.

Characterizing fluorescent dissolved organic matter in a membrane bioreactor via excitation-emission matrix combined with parallel factor analysis.

PubMed

Maqbool, Tahir; Quang, Viet Ly; Cho, Jinwoo; Hur, Jin

2016-06-01

In this study, we successfully tracked the dynamic changes in different constitutes of bound extracellular polymeric substances (bEPS), soluble microbial products (SMP), and permeate during the operation of bench scale membrane bioreactors (MBRs) via fluorescence excitation-emission matrix (EEM) combined with parallel factor analysis (PARAFAC). Three fluorescent groups were identified, including two protein-like (tryptophan-like C1 and tyrosine-like C2) and one microbial humic-like components (C3). In bEPS, protein-like components were consistently more dominant than C3 during the MBR operation, while their relative abundance in SMP depended on aeration intensities. C1 of bEPS exhibited a linear correlation (R(2)=0.738; p<0.01) with bEPS amounts in sludge, and C2 was closely related to the stability of sludge. The protein-like components were more greatly responsible for membrane fouling. Our study suggests that EEM-PARAFAC can be a promising monitoring tool to provide further insight into process evaluation and membrane fouling during MBR operation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Using Separable Nonnegative Matrix Factorization Techniques for the Analysis of Time-Resolved Raman Spectra.

PubMed

Luce, Robert; Hildebrandt, Peter; Kuhlmann, Uwe; Liesen, Jörg

2016-09-01

The key challenge of time-resolved Raman spectroscopy is the identification of the constituent species and the analysis of the kinetics of the underlying reaction network. In this work we present an integral approach that allows for determining both the component spectra and the rate constants simultaneously from a series of vibrational spectra. It is based on an algorithm for nonnegative matrix factorization that is applied to the experimental data set following a few pre-processing steps. As a prerequisite for physically unambiguous solutions, each component spectrum must include one vibrational band that does not significantly interfere with the vibrational bands of other species. The approach is applied to synthetic "experimental" spectra derived from model systems comprising a set of species with component spectra differing with respect to their degree of spectral interferences and signal-to-noise ratios. In each case, the species involved are connected via monomolecular reaction pathways. The potential and limitations of the approach for recovering the respective rate constants and component spectra are discussed. © The Author(s) 2016.

The Comparison Between Nmf and Ica in Pigment Mixture Identification of Ancient Chinese Paintings

NASA Astrophysics Data System (ADS)

Liu, Y.; Lyu, S.; Hou, M.; Yin, Q.

2018-04-01

Since the colour in painting cultural relics observed by our naked eyes or hyperspectral cameras is usually a mixture of several kinds of pigments, the mixed pigments analysis will be an important subject in the field of ancient painting conservation and restoration. This paper aims to find a more effective method to confirm the types of every pure pigment from mixture on the surface of paintings. Firstly, we adopted two kinds of blind source separation algorithms, which are independent component analysis and non-negative matrix factorization, to extract the pure pigment component from mixed spectrum respectively. Moreover, we matched the separated pure spectrum with the pigments spectra library built by our team to determine the pigment type. Furthermore, three kinds of data including simulation data, mixed pigments spectral data measured in laboratory, and the spectral data of an ancient painting were chosen to evaluate the performance of the different algorithms. And the accuracy was compared between the two algorithms. Finally, the experimental results show that non-negative matrix factorization method is more suitable for endmember extraction in the field of ancient painting conservation and restoration.

Clonorchis sinensis excretory-secretory products regulate migration and invasion in cholangiocarcinoma cells via extracellular signal-regulated kinase 1/2/nuclear factor-κB-dependent matrix metalloproteinase-9 expression.

PubMed

Pak, Jhang Ho; Shin, Jimin; Song, In-Sung; Shim, Sungbo; Jang, Sung-Wuk

2017-01-01

Matrix metalloproteinase-9 plays an important role in the invasion and metastasis of various types of cancer cells. We have previously reported that excretory-secretory products from Clonorchis sinensis increases matrix metalloproteinase-9 expression. However, the regulatory mechanisms through which matrix metalloproteinase-9 expression affects cholangiocarcinoma development remain unclear. In the current study, we examined the potential role of excretory-secretory products in regulating the migration and invasion of various cholangiocarcinoma cell lines. We demonstrated that excretory-secretory products significantly induced matrix metalloproteinase-9 expression and activity in a concentration-dependent manner. Reporter gene and chromatin immunoprecipitation assays showed that excretory-secretory products induced matrix metalloproteinase-9 expression by enhancing the activity of nuclear factor-kappa B. Moreover, excretory-secretory products induced the degradation and phosphorylation of IκBα and stimulated nuclear factor-kappa B p65 nuclear translocation, which was regulated by extracellular signal-regulated kinase 1/2. Taken together, our findings indicated that the excretory-secretory product-dependent enhancement of matrix metalloproteinase-9 activity and subsequent induction of IκBα and nuclear factor-kappa B activities may contribute to the progression of cholangiocarcinoma. Copyright © 2016 Australian Society for Parasitology. Published by Elsevier Ltd. All rights reserved.

Normalization Of Thermal-Radiation Form-Factor Matrix

NASA Technical Reports Server (NTRS)

Tsuyuki, Glenn T.

1994-01-01

Report describes algorithm that adjusts form-factor matrix in TRASYS computer program, which calculates intraspacecraft radiative interchange among various surfaces and environmental heat loading from sources such as sun.

Quantitative evaluation of the matrix effect in bioanalytical methods based on LC-MS: A comparison of two approaches.

PubMed

Rudzki, Piotr J; Gniazdowska, Elżbieta; Buś-Kwaśnik, Katarzyna

2018-06-05

Liquid chromatography coupled to mass spectrometry (LC-MS) is a powerful tool for studying pharmacokinetics and toxicokinetics. Reliable bioanalysis requires the characterization of the matrix effect, i.e. influence of the endogenous or exogenous compounds on the analyte signal intensity. We have compared two methods for the quantitation of matrix effect. The CVs(%) of internal standard normalized matrix factors recommended by the European Medicines Agency were evaluated against internal standard normalized relative matrix effects derived from Matuszewski et al. (2003). Both methods use post-extraction spiked samples, but matrix factors require also neat solutions. We have tested both approaches using analytes of diverse chemical structures. The study did not reveal relevant differences in the results obtained with both calculation methods. After normalization with the internal standard, the CV(%) of the matrix factor was on average 0.5% higher than the corresponding relative matrix effect. The method adopted by the European Medicines Agency seems to be slightly more conservative in the analyzed datasets. Nine analytes of different structures enabled a general overview of the problem, still, further studies are encouraged to confirm our observations. Copyright © 2018 Elsevier B.V. All rights reserved.

HIGH DIMENSIONAL COVARIANCE MATRIX ESTIMATION IN APPROXIMATE FACTOR MODELS

PubMed Central

Fan, Jianqing; Liao, Yuan; Mincheva, Martina

2012-01-01

The variance covariance matrix plays a central role in the inferential theories of high dimensional factor models in finance and economics. Popular regularization methods of directly exploiting sparsity are not directly applicable to many financial problems. Classical methods of estimating the covariance matrices are based on the strict factor models, assuming independent idiosyncratic components. This assumption, however, is restrictive in practical applications. By assuming sparse error covariance matrix, we allow the presence of the cross-sectional correlation even after taking out common factors, and it enables us to combine the merits of both methods. We estimate the sparse covariance using the adaptive thresholding technique as in Cai and Liu (2011), taking into account the fact that direct observations of the idiosyncratic components are unavailable. The impact of high dimensionality on the covariance matrix estimation based on the factor structure is then studied. PMID:22661790

Modulation of cardiac fibrosis by Krüppel-like factor 6 through transcriptional control of thrombospondin 4 in cardiomyocytes

PubMed Central

Sawaki, Daigo; Hou, Lianguo; Tomida, Shota; Sun, Junqing; Zhan, Hong; Aizawa, Kenichi; Son, Bo-Kyung; Kariya, Taro; Takimoto, Eiki; Otsu, Kinya; Conway, Simon J.; Manabe, Ichiro; Komuro, Issei; Friedman, Scott L.; Nagai, Ryozo; Suzuki, Toru

2015-01-01

Aims Krüppel-like factors (KLFs) are a family of transcription factors which play important roles in the heart under pathological and developmental conditions. We previously identified and cloned Klf6 whose homozygous mutation in mice results in embryonic lethality suggesting a role in cardiovascular development. Effects of KLF6 on pathological regulation of the heart were investigated in the present study. Methods and results Mice heterozygous for Klf6 resulted in significantly diminished levels of cardiac fibrosis in response to angiotensin II infusion. Intriguingly, a similar phenotype was seen in cardiomyocyte-specific Klf6 knockout mice, but not in cardiac fibroblast-specific knockout mice. Microarray analysis revealed increased levels of the extracellular matrix factor, thrombospondin 4 (TSP4), in the Klf6-ablated heart. Mechanistically, KLF6 directly suppressed Tsp4 expression levels, and cardiac TSP4 regulated the activation of cardiac fibroblasts to regulate cardiac fibrosis. Conclusion Our present studies on the cardiac function of KLF6 show a new mechanism whereby cardiomyocytes regulate cardiac fibrosis through transcriptional control of the extracellular matrix factor, TSP4, which, in turn, modulates activation of cardiac fibroblasts. PMID:25987545

Structural analysis and design of multivariable control systems: An algebraic approach

NASA Technical Reports Server (NTRS)

Tsay, Yih Tsong; Shieh, Leang-San; Barnett, Stephen

1988-01-01

The application of algebraic system theory to the design of controllers for multivariable (MV) systems is explored analytically using an approach based on state-space representations and matrix-fraction descriptions. Chapters are devoted to characteristic lambda matrices and canonical descriptions of MIMO systems; spectral analysis, divisors, and spectral factors of nonsingular lambda matrices; feedback control of MV systems; and structural decomposition theories and their application to MV control systems.

Synthesis and characterization of new nanocomposites films using alanine-Cu-functionalized graphene oxide as nanofiller and PVA as polymeric matrix for improving of their properties

NASA Astrophysics Data System (ADS)

Abdolmaleki, Amir; Mallakpour, Shadpour; Karshenas, Azam

2017-09-01

In the synthesis of polymer-graphene nanocomposites, for improving properties of nanocomposites, two factors dispersion and strong interfacial interactions between graphene and the polymer, are essential. In the present work, poly(vinyl alcohol) PVA/GO-Cu-alanine nanocomposite films were manufactured using concentrations 0, 1, 3 and 5 wt% of GO-Cu-alanine in water solution. For this purpose, L-alanine amino acid was located on the surface and edges of GO through copper(II) ion as a coordinating function. Then, flexible PVA/GO-Cu-alanine nanocomposite films were fabricated using GO-Cu-alanine as filler and PVA as matrix. Due to the existence of affective interaction between GO-Cu-alanine and PVA matrix, the acquired PVA/GO-Cu-alanine nanocomposites demonstrated great thermal and mechanical properties. Properties of manufactured materials were characterized by Fourier transform infrared, X-ray photoelectron spectroscopies (XPS), X-ray diffraction (XRD), Thermal gravimetric analysis, elemental analysis, field emission scanning electron microscopy, transmission electron microscopy and energy dispersive X-ray spectroscopy (EDX).

Transcriptomic signatures in cartilage ageing

PubMed Central

2013-01-01

Introduction Age is an important factor in the development of osteoarthritis. Microarray studies provide insight into cartilage aging but do not reveal the full transcriptomic phenotype of chondrocytes such as small noncoding RNAs, pseudogenes, and microRNAs. RNA-Seq is a powerful technique for the interrogation of large numbers of transcripts including nonprotein coding RNAs. The aim of the study was to characterise molecular mechanisms associated with age-related changes in gene signatures. Methods RNA for gene expression analysis using RNA-Seq and real-time PCR analysis was isolated from macroscopically normal cartilage of the metacarpophalangeal joints of eight horses; four young donors (4 years old) and four old donors (>15 years old). RNA sequence libraries were prepared following ribosomal RNA depletion and sequencing was undertaken using the Illumina HiSeq 2000 platform. Differentially expressed genes were defined using Benjamini-Hochberg false discovery rate correction with a generalised linear model likelihood ratio test (P < 0.05, expression ratios ± 1.4 log2 fold-change). Ingenuity pathway analysis enabled networks, functional analyses and canonical pathways from differentially expressed genes to be determined. Results In total, the expression of 396 transcribed elements including mRNAs, small noncoding RNAs, pseudogenes, and a single microRNA was significantly different in old compared with young cartilage (± 1.4 log2 fold-change, P < 0.05). Of these, 93 were at higher levels in the older cartilage and 303 were at lower levels in the older cartilage. There was an over-representation of genes with reduced expression relating to extracellular matrix, degradative proteases, matrix synthetic enzymes, cytokines and growth factors in cartilage derived from older donors compared with young donors. In addition, there was a reduction in Wnt signalling in ageing cartilage. Conclusion There was an age-related dysregulation of matrix, anabolic and catabolic cartilage factors. This study has increased our knowledge of transcriptional networks in cartilage ageing by providing a global view of the transcriptome. PMID:23971731

Identification of the sources of PM10 in a subway tunnel using positive matrix factorization.

PubMed

Park, Duckshin; Lee, Taejeong; Hwang, Doyeon; Jung, Wonseok; Lee, Yongil; Cho, KiChul; Kim, Dongsool; Lees, Kiyoung

2014-12-01

The level of particulate matter of less than 10 μm diameter (PM10) at subway platforms can be significantly reduced by installing a platform screen-door system. However, both workers and passengers might be exposed to higher PM10 levels while the cars are within the tunnel because it is a more confined environment. This study determined the PM10 levels in a subway tunnel, and identified the sources of PM10 using elemental analysis and receptor modeling. Forty-four PM10 samples were collected in the tunnel between the Gireum and Mia stations on Line 4 in metropolitan Seoul and analyzed using inductively coupled plasma-atomic emission spectrometry and ion chromatography. The major PM10 sources were identified using positive matrix factorization (PMF). The average PM10 concentration in the tunnels was 200.8 ± 22.0 μg/m3. Elemental analysis indicated that the PM10 consisted of 40.4% inorganic species, 9.1% anions, 4.9% cations, and 45.6% other materials. Iron was the most abundant element, with an average concentration of 72.5 ± 10.4 μg/m3. The PM10 sources characterized by PMF included rail, wheel, and brake wear (59.6%), soil combustion (17.0%), secondary aerosols (10.0%), electric cable wear (8.1%), and soil and road dust (5.4%). Internal sources comprising rail, wheel, brake, and electric cable wear made the greatest contribution to the PM10 (67.7%) in tunnel air. Implications: With installation of a platform screen door, PM10 levels in subway tunnels were higher than those on platforms. Tunnel PM10 levels exceeded 150 µg/m3 of the Korean standard for subway platform. Elemental analysis of PM10 in a tunnel showed that Fe was the most abundant element. Five PM10 sources in tunnel were identified by positive matrix factorization. Railroad-related sources contributed 68% of PM10 in the subway tunnel.

Passive beam forming and spatial diversity in meteor scatter communication systems

NASA Astrophysics Data System (ADS)

Akram, Ammad; Cannon, Paul S.

1996-03-01

The method of passive beam formation using a four-element Butler matrix to improve the signal availability of meteor scatter communication systems is investigated. Signal availability, defined as the integrated time that the signal-to-noise ratio (snr) exceeds some snr threshold, serves as an important indicator of system performance. Butler matrix signal availability is compared with the performance of a single four-element Yagi reference system using ˜6.5 hours of data from a 720 km north-south temperate latitude link. The signal availability improvement factor of the Butler matrix is found to range between 1.6-1.8 over the snr threshold range of 20-30 dB in a 300-Hz bandwidth. Experimental values of the Butler matrix signal availability improvement factor are compared with analytical predictions. The experimental values show an expected snr threshold dependency with a dramatic increase at high snr. A theoretical analysis is developed to describe this increase. The signal availability can be further improved by ˜10-20% in a system employing two four-element Butler matrices with squinted beams so as to illuminate the sky with eight high-gain beams. Space diversity is found to increase the signal availability of a single antenna system by ˜10-15%, but the technique has very little advantage in a system already employing passive beam formation.

Defective Endochondral Ossification-Derived Matrix and Bone Cells Alter the Lymphopoietic Niche in Collagen X Mouse Models

PubMed Central

Sweeney, Elizabeth; Roberts, Douglas; Lin, Angela; Guldberg, Robert

2013-01-01

Despite the appreciated interdependence of skeletal and hematopoietic development, the cell and matrix components of the hematopoietic niche remain to be fully defined. Utilizing mice with disrupted function of collagen X (ColX), a major hypertrophic cartilage matrix protein associated with endochondral ossification, our data identified a cytokine defect in trabecular bone cells at the chondro-osseous hematopoietic niche as a cause for aberrant B lymphopoiesis in these mice. Specifically, analysis of ColX transgenic and null mouse chondro-osseous regions via micro-computed tomography revealed an altered trabecular bone environment. Additionally, cocultures with hematopoietic and chondro-osseous cell types highlighted impaired hematopoietic support by ColX transgenic and null mouse derived trabecular bone cells. Further, cytokine arrays with conditioned media from the trabecular osteoblast cocultures suggested an aberrant hematopoietic cytokine milieu within the chondro-osseous niche of the ColX deficient mice. Accordingly, B lymphopoiesis was rescued in the ColX mouse derived trabecular osteoblast cocultures with interlukin-7, stem cell factor, and stromal derived factor-1 supplementation. Moreover, B cell development was restored in vivo after injections of interlukin-7. These data support our hypothesis that endrochondrally-derived trabecular bone cells and matrix constituents provide cytokine-rich niches for hematopoiesis. Furthermore, this study contributes to the emerging concept that niche defects may underlie certain immuno-osseous and hematopoietic disorders. PMID:23656481

Defective endochondral ossification-derived matrix and bone cells alter the lymphopoietic niche in collagen X mouse models.

PubMed

Sweeney, Elizabeth; Roberts, Douglas; Lin, Angela; Guldberg, Robert; Jacenko, Olena

2013-10-01

Despite the appreciated interdependence of skeletal and hematopoietic development, the cell and matrix components of the hematopoietic niche remain to be fully defined. Utilizing mice with disrupted function of collagen X (ColX), a major hypertrophic cartilage matrix protein associated with endochondral ossification, our data identified a cytokine defect in trabecular bone cells at the chondro-osseous hematopoietic niche as a cause for aberrant B lymphopoiesis in these mice. Specifically, analysis of ColX transgenic and null mouse chondro-osseous regions via micro-computed tomography revealed an altered trabecular bone environment. Additionally, cocultures with hematopoietic and chondro-osseous cell types highlighted impaired hematopoietic support by ColX transgenic and null mouse derived trabecular bone cells. Further, cytokine arrays with conditioned media from the trabecular osteoblast cocultures suggested an aberrant hematopoietic cytokine milieu within the chondro-osseous niche of the ColX deficient mice. Accordingly, B lymphopoiesis was rescued in the ColX mouse derived trabecular osteoblast cocultures with interlukin-7, stem cell factor, and stromal derived factor-1 supplementation. Moreover, B cell development was restored in vivo after injections of interlukin-7. These data support our hypothesis that endrochondrally-derived trabecular bone cells and matrix constituents provide cytokine-rich niches for hematopoiesis. Furthermore, this study contributes to the emerging concept that niche defects may underlie certain immuno-osseous and hematopoietic disorders.

Stochastic quasi-Newton molecular simulations

NASA Astrophysics Data System (ADS)

Chau, C. D.; Sevink, G. J. A.; Fraaije, J. G. E. M.

2010-08-01

We report a new and efficient factorized algorithm for the determination of the adaptive compound mobility matrix B in a stochastic quasi-Newton method (S-QN) that does not require additional potential evaluations. For one-dimensional and two-dimensional test systems, we previously showed that S-QN gives rise to efficient configurational space sampling with good thermodynamic consistency [C. D. Chau, G. J. A. Sevink, and J. G. E. M. Fraaije, J. Chem. Phys. 128, 244110 (2008)10.1063/1.2943313]. Potential applications of S-QN are quite ambitious, and include structure optimization, analysis of correlations and automated extraction of cooperative modes. However, the potential can only be fully exploited if the computational and memory requirements of the original algorithm are significantly reduced. In this paper, we consider a factorized mobility matrix B=JJT and focus on the nontrivial fundamentals of an efficient algorithm for updating the noise multiplier J . The new algorithm requires O(n2) multiplications per time step instead of the O(n3) multiplications in the original scheme due to Choleski decomposition. In a recursive form, the update scheme circumvents matrix storage and enables limited-memory implementation, in the spirit of the well-known limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) method, allowing for a further reduction of the computational effort to O(n) . We analyze in detail the performance of the factorized (FSU) and limited-memory (L-FSU) algorithms in terms of convergence and (multiscale) sampling, for an elementary but relevant system that involves multiple time and length scales. Finally, we use this analysis to formulate conditions for the simulation of the complex high-dimensional potential energy landscapes of interest.

CD147 and matrix-metalloproteinase-2 expression in metastatic and non-metastatic uveal melanomas.

PubMed

Lüke, Julia; Vukoja, Vlatka; Brandenbusch, Tim; Nassar, Khaled; Rohrbach, Jens Martin; Grisanti, Salvatore; Lüke, Matthias; Tura, Aysegül

2016-06-03

Extracellular matrix remodelling regulated by matrix-metalloproteinase (MMP) inducer (CD147) is a crucial process during tumor cell invasion and regulation of blood supply. In this study, we evaluated the correlation of CD147 and MMP-2 expression with major prognostic factors for uveal melanoma and the development of metastasis. The expression of CD147 and MMP-2 was analyzed in 49 samples of uveal melanomas. Triple immunofluorescence stainings using markers against glial cells (GFAP), endothelial cells (CD34) and macrophages (CD68) were performed to further analyse the exact localisation of CD147 and MMP-2 positivity. In 28 cases clinical metastatic disease were found. The remaining 21 cases showed no signs of metastatic disease for an average follow-up of 10 years. Correlation analysis (Pearson correlation) was performed to analyse the association of CD147 and MMP-2 expression with known prognostic factors, vasculogenic mimicry (VM), the mature vasculature (von Willebrand Factor) and tumor induced angiogenesis (by means of Endoglin expression). CD147 and MMP-2 were expressed in 47 (96.0 %) of the uveal melanomas. CD147 up-regulation was significantly correlated with a higher MMP-2 expression. The overall expression analysis revealed no significant difference in the metastatic (p = 0.777) and non-metastatic subgroup (p = 0.585). No correlation of CD147 expression and any system of blood supply was evident. In the non-metastatic sub-group a significant correlation of clustered CD147 positive cells with largest basal diameter (p = 0.039), height (p = 0.047) and TNM-stage (p = 0.013) was evident. These data may indicate that CD147 regulates MMP-2 expression in uveal melanoma cells.

Extracellular matrix metalloproteinase inducer (EMMPRIN) is a potential biomarker of angiogenesis in proliferative diabetic retinopathy.

PubMed

Abu El-Asrar, Ahmed M; Ahmad, Ajmal; Alam, Kaiser; Siddiquei, Mohammad Mairaj; Mohammad, Ghulam; Hertogh, Gert De; Mousa, Ahmed; Opdenakker, Ghislain

2017-11-01

Extracellular matrix metalloproteinase inducer (EMMPRIN) promotes angiogenesis through matrix metalloproteinases (MMPs) and vascular endothelial growth factor (VEGF) production. We investigated the expression levels of EMMPRIN and correlated these levels with VEGF, MMP-1 and MMP-9 in proliferative diabetic retinopathy (PDR). In addition, we examined the expression of EMMPRIN in the retinas of diabetic rats and the effect of EMMPRIN on the induction of angiogenesis regulatory factors in human retinal microvascular endothelial cells (HRMECs). Vitreous samples from 40 PDR and 19 non-diabetic patients, epiretinal membranes from 12 patients with PDR, retinas of rats and HRMECs were studied by enzyme-linked immunosorbent assay (ELISA), immunohistochemistry, Western blot analysis, zymography analysis and RT-PCR. We showed a significant increase in the expression of EMMPRIN, VEGF, MMP-1 and MMP-9 in vitreous samples from PDR patients compared with non-diabetic controls (p < 0.0001; p = 0.001; p = 0.009; p < 0.0001, respectively). Significant positive correlations were found between the levels of EMMPRIN and the levels of VEGF (r = 0.38; p = 0.003), MMP-1 (r = 0.36; p = 0.005) and MMP-9 (r = 0.46; p = 0.003). In epiretinal membranes, EMMPRIN was expressed in vascular endothelial cells and stromal cells. Significant increase of EMMPRIN mRNA was detected in rat retinas after induction of diabetes. EMMPRIN induced hypoxia-inducible factor-1α, VEGF and MMP-1 expression in HRMEC. These results suggest that EMMPRIN/MMPs/VEGF pathway is involved in PDR angiogenesis. © 2016 Acta Ophthalmologica Scandinavica Foundation. Published by John Wiley & Sons Ltd.

Analysis of the Aspergillus fumigatus Biofilm Extracellular Matrix by Solid-State Nuclear Magnetic Resonance Spectroscopy.

PubMed

Reichhardt, Courtney; Ferreira, Jose A G; Joubert, Lydia-Marie; Clemons, Karl V; Stevens, David A; Cegelski, Lynette

2015-11-01

Aspergillus fumigatus is commonly responsible for lethal fungal infections among immunosuppressed individuals. A. fumigatus forms biofilm communities that are of increasing biomedical interest due to the association of biofilms with chronic infections and their increased resistance to antifungal agents and host immune factors. Understanding the composition of microbial biofilms and the extracellular matrix is important to understanding function and, ultimately, to developing strategies to inhibit biofilm formation. We implemented a solid-state nuclear magnetic resonance (NMR) approach to define compositional parameters of the A. fumigatus extracellular matrix (ECM) when biofilms are formed in RPMI 1640 nutrient medium. Whole biofilm and isolated matrix networks were also characterized by electron microscopy, and matrix proteins were identified through protein gel analysis. The (13)C NMR results defined and quantified the carbon contributions in the insoluble ECM, including carbonyls, aromatic carbons, polysaccharide carbons (anomeric and nonanomerics), aliphatics, etc. Additional (15)N and (31)P NMR spectra permitted more specific annotation of the carbon pools according to C-N and C-P couplings. Together these data show that the A. fumigatus ECM produced under these growth conditions contains approximately 40% protein, 43% polysaccharide, 3% aromatic-containing components, and up to 14% lipid. These fundamental chemical parameters are needed to consider the relationships between composition and function in the A. fumigatus ECM and will enable future comparisons with other organisms and with A. fumigatus grown under alternate conditions. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Construction of the energy matrix for complex atoms. Part VIII: Hyperfine structure HPC calculations for terbium atom

NASA Astrophysics Data System (ADS)

Elantkowska, Magdalena; Ruczkowski, Jarosław; Sikorski, Andrzej; Dembczyński, Jerzy

2017-11-01

A parametric analysis of the hyperfine structure (hfs) for the even parity configurations of atomic terbium (Tb I) is presented in this work. We introduce the complete set of 4fN-core states in our high-performance computing (HPC) calculations. For calculations of the huge hyperfine structure matrix, requiring approximately 5000 hours when run on a single CPU, we propose the methods utilizing a personal computer cluster or, alternatively a cluster of Microsoft Azure virtual machines (VM). These methods give a factor 12 performance boost, enabling the calculations to complete in an acceptable time.

Scleraxis is required for cell lineage differentiation and extracellular matrix remodeling during murine heart valve formation in vivo.

PubMed

Levay, Agata K; Peacock, Jacqueline D; Lu, Yinhui; Koch, Manuel; Hinton, Robert B; Kadler, Karl E; Lincoln, Joy

2008-10-24

Heart valve structures, derived from mesenchyme precursor cells, are composed of differentiated cell types and extracellular matrix arranged to facilitate valve function. Scleraxis (scx) is a transcription factor required for tendon cell differentiation and matrix organization. This study identified high levels of scx expression in remodeling heart valve structures at embryonic day 15.5 through postnatal stages using scx-GFP reporter mice and determined the in vivo function using mice null for scx. Scx(-/-) mice display significantly thickened heart valve structures from embryonic day 17.5, and valves from mutant mice show alterations in valve precursor cell differentiation and matrix organization. This is indicated by decreased expression of the tendon-related collagen type XIV, increased expression of cartilage-associated genes including sox9, as well as persistent expression of mesenchyme cell markers including msx1 and snai1. In addition, ultrastructure analysis reveals disarray of extracellular matrix and collagen fiber organization within the valve leaflet. Thickened valve structures and increased expression of matrix remodeling genes characteristic of human heart valve disease are observed in juvenile scx(-/-) mice. In addition, excessive collagen deposition in annular structures within the atrioventricular junction is observed. Collectively, our studies have identified an in vivo requirement for scx during valvulogenesis and demonstrate its role in cell lineage differentiation and matrix distribution in remodeling valve structures.

Optimization of a novel wax matrix system using aminoalkyl methacrylate copolymer E and ethylcellulose to suppress the bitter taste of acetaminophen.

PubMed

Shiino, Kai; Iwao, Yasunori; Miyagishima, Atsuo; Itai, Shigeru

2010-08-16

The purpose of the present study was to design and evaluate a novel wax matrix system containing various ratios of aminoalkyl methacrylate copolymer E (AMCE) and ethylcellulose (EC) as functional polymers in order to achieve the optimal acetaminophen (APAP) release rate for taste masking. A two factor, three level (3(2)) full factorial study design was used to optimize the ratios of AMCE and EC, and the release of APAP from the wax matrix was evaluated using a stationary disk in accordance with the paddle method. The disk was prepared by congealing glyceryl monostearate (GM), a wax with a low melting point, with various ratios of polymers and APAP. The criteria for release rate of APAP from the disk at pH 4.0 and pH 6.5 were calculated to be more than 0.5017 microg/(mlxmin) and less than 0.1414 microg/(mlxmin), respectively, under the assumption that the particle size of spherical matrix should be 100 microm. In multiple regression analysis, the release of APAP at pH 4.0 was found to increase markedly as the concentration of AMCE increased, whereas the release of APAP at pH 6.5 decreased as the EC concentration increased, even when a high level of AMCE was incorporated. Using principle component analysis, it was found that the viscosity of the matrix affects the pH-dependent release of APAP at pH 4.0 and pH 6.5. Furthermore, using multiple regression analysis, the optimum ratio of APAP:AMCE:EC:GM was found to be 30:7:10:53, and the release pattern of APAP from the optimum wax formulation nearly complied with the desired criteria. Therefore, the present study demonstrated that the incorporation of AMCE and EC into a wax matrix system enabled the appropriate release of APAP as a means of taste masking. Copyright (c) 2010 Elsevier B.V. All rights reserved.

Detection of Amine Impurity and Quality Assessment of the MALDI Matrix α-Cyano-4-Hydroxy-Cinnamic Acid for Peptide Analysis in the amol Range

NASA Astrophysics Data System (ADS)

Rechthaler, Justyna; Pittenauer, Ernst; Schaub, Tanner M.; Allmaier, Günter

2013-05-01

We have studied sample preparation conditions to increase the reproducibility of positive UV-MALDI-TOF mass spectrometry of peptides in the amol range. By evaluating several α-cyano-4-hydroxy-cinnamic acid (CHCA) matrix batches and preparation protocols, it became apparent that two factors have a large influence on the reproducibility and the quality of the generated peptide mass spectra: (1) the selection of the CHCA matrix, which allows the most sensitive measurements and an easier finding of the "sweet spots," and (2) the amount of the sample volume deposited onto the thin crystalline matrix layer. We have studied in detail the influence of a contaminant, coming from commercial CHCA matrix batches, on sensitivity of generated peptide mass spectra in the amol as well as fmol range of a tryptic peptide mixture. The structure of the contaminant, N, N-dimethylbutyl amine, was determined by applying MALDI-FT-ICR mass spectrometry experiments for elemental composition and MALDI high energy CID experiments utilizing a tandem mass spectrometer (TOF/RTOF). A recrystallization of heavily contaminated CHCA batches that reduces or eliminates the determined impurity is described. Furthermore, a fast and reliable method for the assessment of CHCA matrix batches prior to tryptic peptide MALDI mass spectrometric analyses is presented.

A symmetrical subtraction combined with interpolated values for eliminating scattering from fluorescence EEM data

NASA Astrophysics Data System (ADS)

Xu, Jing; Liu, Xiaofei; Wang, Yutian

2016-08-01

Parallel factor analysis is a widely used method to extract qualitative and quantitative information of the analyte of interest from fluorescence emission-excitation matrix containing unknown components. Big amplitude of scattering will influence the results of parallel factor analysis. Many methods of eliminating scattering have been proposed. Each of these methods has its advantages and disadvantages. The combination of symmetrical subtraction and interpolated values has been discussed. The combination refers to both the combination of results and the combination of methods. Nine methods were used for comparison. The results show the combination of results can make a better concentration prediction for all the components.

Block LU factorization

NASA Technical Reports Server (NTRS)

Demmel, James W.; Higham, Nicholas J.; Schreiber, Robert S.

1992-01-01

Many of the currently popular 'block algorithms' are scalar algorithms in which the operations have been grouped and reordered into matrix operations. One genuine block algorithm in practical use is block LU factorization, and this has recently been shown by Demmel and Higham to be unstable in general. It is shown here that block LU factorization is stable if A is block diagonally dominant by columns. Moreover, for a general matrix the level of instability in block LU factorization can be founded in terms of the condition number kappa(A) and the growth factor for Gaussian elimination without pivoting. A consequence is that block LU factorization is stable for a matrix A that is symmetric positive definite or point diagonally dominant by rows or columns as long as A is well-conditioned.

Study of Erosive Wear Behaviour on SIC/SIC Composites

NASA Astrophysics Data System (ADS)

Suh, Min-Soo

In the field of aerospace propulsion system, erosive wear on continuous silicon carbide (SiC) fibre-reinforced SiC (SiC/SiC) composites is of significant issue to achieve high energy efficiency. This paper proposes a crucial factor and a design guideline of SiC/SiC composites for higher erosion performance regarding cost effectiveness. Fabrication and evaluation of impacts and wear on SiC/SiC composites are successfully carried out. Erosive wear behaviours of the CVI and the LPS composites evidently show that the crucial fabrication factor against solid particle erosion (SPE). Erosive wear mechanisms on various SiC/SiC composites are determined based on the analysis of erosive wear behaviour. Designing guideline for the SiC/SiC composites for pursuit of high erosion performance is also proposed as focusing on the followings; volume fraction of matrix, strength of the matrix, bonding strength, and PyC interface.

Characterizing muscular activities using non-negative matrix factorization from EMG channels for driver swings in golf.

PubMed

Ozaki, Yasunori; Aoki, Ryosuke; Kimura, Toshitaka; Takashima, Youichi; Yamada, Tomohiro

2016-08-01

The goal of this study is to propose a data driven approach method to characterize muscular activities of complex actions in sports such as golf from a lot of EMG channels. Two problems occur in a many channel measurement. The first problem is that it takes a lot of time to check the many channel data because of combinatorial explosion. The second problem is that it is difficult to understand muscle activities related with complex actions. To solve these problems, we propose an analysis method of multi EMG channels using Non-negative Matrix Factorization and adopt the method to driver swings in golf. We measured 26 EMG channels about 4 professional coaches of golf. The results show that the proposed method detected 9 muscle synergies and the activation of each synergy were mostly fitted by sigmoid curve (R2=0.85).

Effects of religion, economics, and geography on genetic structure of Fogo Island, Newfoundland.

PubMed

Crawford, M H; Koertevlyessy, T; Huntsman, R G; Collins, M; Duggirala, R; Martin, L; Keeping, D

1995-01-01

The population structure of Fogo Island, Newfoundland is described using geography, religious affiliation, economic factors (such as the presence of a fish-packing plant), and genetic markers. Five different analytic methods, R-matrix analysis, r ii VS. mean per locus heterozygosity, predicted kinship (ϕ), mean first passage time, and Mantel matrix comparisons, were applied to the Fogo Island genetic and demographic data. The results suggest that geography plays a role on Fogo Island in the distribution of genes, while religion, ethnicity, and economic factors play less significant roles. The communities with fish-packing plants and tourism serve as migratory "sinks" for Fogo islanders seeking employment. Reproductively, the most isolated village on Fogo Island is Tilting, and this is reflected in its genetic uniqueness, initially caused by Irish settlement and subsequently the action of stochastic processes. © 1995 Wiley-Liss, Inc. Copyright © 1995 Wiley-Liss, Inc., A Wiley Company.

TETRA-COM: a comprehensive SPSS program for estimating the tetrachoric correlation.

PubMed

Lorenzo-Seva, Urbano; Ferrando, Pere J

2012-12-01

We provide an SPSS program that implements descriptive and inferential procedures for estimating tetrachoric correlations. These procedures have two main purposes: (1) bivariate estimation in contingency tables and (2) constructing a correlation matrix to be used as input for factor analysis (in particular, the SPSS FACTOR procedure). In both cases, the program computes accurate point estimates, as well as standard errors and confidence intervals that are correct for any population value. For purpose (1), the program computes the contingency table together with five other measures of association. For purpose (2), the program checks the positive definiteness of the matrix, and if it is found not to be Gramian, performs a nonlinear smoothing procedure at the user's request. The SPSS syntax, a short manual, and data files related to this article are available as supplemental materials from brm.psychonomic-journals.org/content/supplemental.

Structure and dynamics of Ebola virus matrix protein VP40 by a coarse-grained Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Pandey, Ras; Farmer, Barry

Ebola virus matrix protein VP40 (consisting of 326 residues) plays a critical role in viral assembly and its functions such as regulation of viral transcription, packaging, and budding of mature virions into the plasma membrane of infected cells. How does the protein VP40 go through structural evolution during the viral life cycle remains an open question? Using a coarse-grained Monte Carlo simulation we investigate the structural evolution of VP40 as a function of temperature with the input of a knowledge-based residue-residue interaction. A number local and global physical quantities (e.g. mobility profile, contact map, radius of gyration, structure factor) are analyzed with our large-scale simulations. Our preliminary data show that the structure of the protein evolves through different state with well-defined morphologies which can be identified and quantified via a detailed analysis of structure factor.

Amperometric Glucose Sensor Using Thermostable Co-Factor Binding Glucose Dehydrogenase

NASA Astrophysics Data System (ADS)

Nakazawa, Yukie; Yamazaki, Tomohiko; Tsugawa, Wakako; Ikebukuro, Kazunori; Sode, Koji

A thermostable mediator-type enzyme glucose sensor was constructed. The electrode was fabricated using chemically cross-linked thermostable co-factor binding glucose dehydrogenase (GDH) from thermophilic bacteria in carbon paste matrix. The electrode responded directly proportional to D-glucose concentration from 0.01 mM to 3 mM in stirred buffer containing 1 mM 1-methoxyphenazinemethosulfate as a mediator with the steady-state mode. The storage stability was examined by incubating the enzyme electrode at 50oC during the measurement. The cross-linked GDH immobilized electrode showed good storage stability. Ninety percent of its initial response was retained after incubation in buffer solution for 9 days at 50oC. The flow injection analysis (FIA) glucose sensing system was also constructed by immobilizing the cross-linked GDH and ferrocene as a mediator in the carbon paste matrix. The FIA system was able to measure 600 samples for 100 h.

Categorical dimensions of human odor descriptor space revealed by non-negative matrix factorization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chennubhotla, Chakra; Castro, Jason

2013-01-01

In contrast to most other sensory modalities, the basic perceptual dimensions of olfaction remain un- clear. Here, we use non-negative matrix factorization (NMF) - a dimensionality reduction technique - to uncover structure in a panel of odor profiles, with each odor defined as a point in multi-dimensional descriptor space. The properties of NMF are favorable for the analysis of such lexical and perceptual data, and lead to a high-dimensional account of odor space. We further provide evidence that odor di- mensions apply categorically. That is, odor space is not occupied homogenously, but rather in a discrete and intrinsically clustered manner.more » We discuss the potential implications of these results for the neural coding of odors, as well as for developing classifiers on larger datasets that may be useful for predicting perceptual qualities from chemical structures.« less

Scalar and vector form factors of D →π (K )ℓν decays with Nf=2 +1 +1 twisted fermions

NASA Astrophysics Data System (ADS)

Lubicz, V.; Riggio, L.; Salerno, G.; Simula, S.; Tarantino, C.; ETM Collaboration

2017-09-01

We present a lattice determination of the vector and scalar form factors of the D →π ℓν and D →K ℓν semileptonic decays, which are relevant for the extraction of the CKM matrix elements |Vc d| and |Vc s| from experimental data. Our analysis is based on the gauge configurations produced by the European Twisted Mass Collaboration with Nf=2 +1 +1 flavors of dynamical quarks, at three different values of the lattice spacing (a ≃0.062 ,0.082 ,0.089 fm ) and with pion masses as small as 210 MeV. Quark momenta are injected on the lattice using nonperiodic boundary conditions. The matrix elements of both vector and scalar currents are determined for plenty of kinematical conditions in which parent and child mesons are either moving or at rest. Lorentz symmetry breaking due to hypercubic effects is clearly observed in the data and included in the decomposition of the current matrix elements in terms of additional form factors. After the extrapolations to the physical pion mass and to the continuum limit, we determine the vector and scalar form factors in the whole kinematical region from q2=0 up to qmax2=(MD-Mπ (K ))2 accessible in the experiments, obtaining a good overall agreement with experiments, except in the region at high values of q2 where some deviations are visible. A set of synthetic data points, representing our results for f+Dπ (K )(q2) and f0D π (K )(q2) for several selected values of q2, is provided and also the corresponding covariance matrix is available. At zero four-momentum transfer, we get f+D→π(0 )=0.612 (35 ) and f+D→K(0 )=0.765 (31 ). Using the experimental averages for |Vc d|f+D→π(0 ) and |Vc s|f+D→K(0 ), we extract |Vc d|=0.2330 (137 ) and |Vc s|=0.945 (38 ), respectively. The second row of the CKM matrix is found to be in agreement with unitarity within the current uncertainties: |Vc d|2+|Vc s|2+|Vc b|2=0.949 (78 ).

Application of Analytic Hierarchy Process (AHP) in the analysis of the fuel efficiency in the automobile industry with the utilization of Natural Fiber Polymer Composites (NFPC)

NASA Astrophysics Data System (ADS)

Jayamani, E.; Perera, D. S.; Soon, K. H.; Bakri, M. K. B.

2017-04-01

A systematic method of material analysis aiming for fuel efficiency improvement with the utilization of natural fiber reinforced polymer matrix composites in the automobile industry is proposed. A multi-factor based decision criteria with Analytical Hierarchy Process (AHP) was used and executed through MATLAB to achieve improved fuel efficiency through the weight reduction of vehicular components by effective comparison between two engine hood designs. The reduction was simulated by utilizing natural fiber polymer composites with thermoplastic polypropylene (PP) as the matrix polymer and benchmarked against a synthetic based composite component. Results showed that PP with 35% of flax fiber loading achieved a 0.4% improvement in fuel efficiency, and it was the highest among the 27 candidate fibers.

Simultaneous pre-concentration and separation on simple paper-based analytical device for protein analysis.

PubMed

Niu, Ji-Cheng; Zhou, Ting; Niu, Li-Li; Xie, Zhen-Sheng; Fang, Fang; Yang, Fu-Quan; Wu, Zhi-Yong

2018-02-01

In this work, fast isoelectric focusing (IEF) was successfully implemented on an open paper fluidic channel for simultaneous concentration and separation of proteins from complex matrix. With this simple device, IEF can be finished in 10 min with a resolution of 0.03 pH units and concentration factor of 10, as estimated by color model proteins by smartphone-based colorimetric detection. Fast detection of albumin from human serum and glycated hemoglobin (HBA1c) from blood cell was demonstrated. In addition, off-line identification of the model proteins from the IEF fractions with matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS) was also shown. This PAD IEF is potentially useful either for point of care test (POCT) or biomarker analysis as a cost-effective sample pretreatment method.

Eigenvalue-eigenvector decomposition (EED) analysis of dissimilarity and covariance matrix obtained from total synchronous fluorescence spectral (TSFS) data sets of herbal preparations: Optimizing the classification approach.

PubMed

Tarai, Madhumita; Kumar, Keshav; Divya, O; Bairi, Partha; Mishra, Kishor Kumar; Mishra, Ashok Kumar

2017-09-05

The present work compares the dissimilarity and covariance based unsupervised chemometric classification approaches by taking the total synchronous fluorescence spectroscopy data sets acquired for the cumin and non-cumin based herbal preparations. The conventional decomposition method involves eigenvalue-eigenvector analysis of the covariance of the data set and finds the factors that can explain the overall major sources of variation present in the data set. The conventional approach does this irrespective of the fact that the samples belong to intrinsically different groups and hence leads to poor class separation. The present work shows that classification of such samples can be optimized by performing the eigenvalue-eigenvector decomposition on the pair-wise dissimilarity matrix. Copyright © 2017 Elsevier B.V. All rights reserved.

PLE in the analysis of plant compounds. Part I. The application of PLE for HPLC analysis of caffeine in green tea leaves.

PubMed

Dawidowicz, Andrzej L; Wianowska, Dorota

2005-04-29

A broad spectrum of sample preparation methods is currently used for the isolation of pharmacologically active compounds from plant and herbal materials. The paper compares the effectiveness of infusion, microwave assisted solvent extraction (MASE), matrix solid-phase dispersion (MSPD) and pressurised liquid extraction (PLE) as sample preparation methods for the isolation of caffeine from green tea leaves. The effect of PLE variables, such as extraction temperature, pressure and time, on the yield of caffeine from the investigated matrix is discussed. The obtained results revealed that PLE, in comparison with other sample preparation methods applied, has significantly lower efficacy for caffeine isolation from green tea leaves. The evaluation of PLE conditions leads to the conclusion that elevated pressure applied in the PLE process is the factor hindering the extraction.

Non-negative Matrix Factorization for Self-calibration of Photometric Redshift Scatter in Weak-lensing Surveys

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Le; Yu, Yu; Zhang, Pengjie, E-mail: lezhang@sjtu.edu.cn

Photo- z error is one of the major sources of systematics degrading the accuracy of weak-lensing cosmological inferences. Zhang et al. proposed a self-calibration method combining galaxy–galaxy correlations and galaxy–shear correlations between different photo- z bins. Fisher matrix analysis shows that it can determine the rate of photo- z outliers at a level of 0.01%–1% merely using photometric data and do not rely on any prior knowledge. In this paper, we develop a new algorithm to implement this method by solving a constrained nonlinear optimization problem arising in the self-calibration process. Based on the techniques of fixed-point iteration and non-negativemore » matrix factorization, the proposed algorithm can efficiently and robustly reconstruct the scattering probabilities between the true- z and photo- z bins. The algorithm has been tested extensively by applying it to mock data from simulated stage IV weak-lensing projects. We find that the algorithm provides a successful recovery of the scatter rates at the level of 0.01%–1%, and the true mean redshifts of photo- z bins at the level of 0.001, which may satisfy the requirements in future lensing surveys.« less

Efficient l1 -norm-based low-rank matrix approximations for large-scale problems using alternating rectified gradient method.

PubMed

Kim, Eunwoo; Lee, Minsik; Choi, Chong-Ho; Kwak, Nojun; Oh, Songhwai

2015-02-01

Low-rank matrix approximation plays an important role in the area of computer vision and image processing. Most of the conventional low-rank matrix approximation methods are based on the l2 -norm (Frobenius norm) with principal component analysis (PCA) being the most popular among them. However, this can give a poor approximation for data contaminated by outliers (including missing data), because the l2 -norm exaggerates the negative effect of outliers. Recently, to overcome this problem, various methods based on the l1 -norm, such as robust PCA methods, have been proposed for low-rank matrix approximation. Despite the robustness of the methods, they require heavy computational effort and substantial memory for high-dimensional data, which is impractical for real-world problems. In this paper, we propose two efficient low-rank factorization methods based on the l1 -norm that find proper projection and coefficient matrices using the alternating rectified gradient method. The proposed methods are applied to a number of low-rank matrix approximation problems to demonstrate their efficiency and robustness. The experimental results show that our proposals are efficient in both execution time and reconstruction performance unlike other state-of-the-art methods.

Analysis of Potential Radical Chemistry on Kuiper Belt Objects

NASA Astrophysics Data System (ADS)

Yanez, Maya Danielle; Hodyss, Robert; Cable, Morgan; Johnson, Paul

2017-10-01

Kuiper Belt Objects (KBOs) are of high interest following the New Horizons encounter with the Pluto system and the extended mission to 2014MU69. We aimed to clarify questions raised concerning the possible presence of organic radicals formed from photolysis on the surface of KBOs and other Trans-Neptunian Objects, and obtain laboratory spectra of these radicals for comparison to remote sensing data. We explored the photochemical generation of methyl radical from matrix-isolated CH3I in an attempt to create sufficient amounts of the methyl radical to obtain spectra in the near infrared. Both Ar and N2 matrices were studied, as well as varying guest:matrix ratios. Hydrogen lamp irradiation was found to be more effective than mercury lamp irradiation. The irradiation time was a significant factor when we switched matrices: methyl radical depleted rapidly in the N2 matrix with prolonged irradiation (~10 hours) whereas it survived for over 48 hours in some experiments with the Ar matrix. Reaction of the methyl radical with the N2 matrix to form HCN was observed. Future experiments will focus on alternate methods of radical generation in order to increase the yield of trapped radical.

Anisotropic properties of the enamel organic extracellular matrix.

PubMed

do Espírito Santo, Alexandre R; Novaes, Pedro D; Line, Sérgio R P

2006-05-01

Enamel biosynthesis is initiated by the secretion, processing, and self-assembly of a complex mixture of proteins. This supramolecular ensemble controls the nucleation of the crystalline mineral phase. The detection of anisotropic properties by polarizing microscopy has been extensively used to detect macromolecular organizations in ordinary histological sections. The aim of this work was to study the birefringence of enamel organic matrix during the development of rat molar and incisor teeth. Incisor and molar teeth of rats were fixed in 2% paraformaldehyde/0.5% glutaraldehyde in 0.2 M phosphate-buffered saline (PBS), pH 7.2, and decalcified in 5% nitric acid/4% formaldehyde. After paraffin embedding, 5-microm-thick sections were obtained, treated with xylene, and hydrated. Form birefringence curves were obtained after measuring optical retardations in imbibing media, with different refractive indices. Our observations showed that enamel organic matrix of rat incisor and molar teeth is strongly birefringent, presenting an ordered supramolecular structure. The birefringence starts during the early secretion phase and disappears at the maturation phase. The analysis of enamel organic matrix birefringence may be used to detect the effects of genetic and environmental factors on the supramolecular orientation of enamel matrix and their effects on the structure of mature enamel.

Epilobium angustifolium extract demonstrates multiple effects on dermal fibroblasts in vitro and skin photo-protection in vivo.

PubMed

Ruszová, Ema; Cheel, José; Pávek, Stanislav; Moravcová, Martina; Hermannová, Martina; Matějková, Ilona; Spilková, Jiřina; Velebný, Vladimír; Kubala, Lukáš

2013-09-01

Stress-induced fibroblast senescence is thought to contribute to skin aging. Ultraviolet light (UV) radiation is the most potent environmental risk factor in these processes. An Epilobium angustifolium (EA) extract was evaluated for its capacity to reverse the senescent response of normal human dermal fibroblasts (NHDF) in vitro and to exhibit skin photo-protection in vivo. The HPLC-UV-MS analysis of the EA preparation identified three major polyphenol groups: tannins (oenothein B), phenolic acids (gallic and chlorogenic acids) and flavonoids. EA extract increased the cell viability of senescent NHDF induced by serum deprivation. It diminished connective tissue growth factor and fibronectin gene expressions in senescent NHDF. Down-regulation of the UV-induced release of both matrix metalloproteinase-1 and -3 and the tissue inhibitor of matrix metalloproteinases-1 and -2, and also down-regulation of the gene expression of hyaluronidase 2 were observed in repeatedly UV-irradiated NHDF after EA extract treatment. Interestingly, EA extract diminished the down-regulation of sirtuin 1 dampened by UV-irradiation. The application of EA extract using a sub-irritating dose protected skin against UV-induced erythema formation in vivo. In summary, EA extract diminished stress-induced effects on NHDF, particularly on connective tissue growth factor, fibronectin and matrix metalloproteinases. These results collectively suggest that EA extract may possess anti-aging properties and that the EA polyphenols might account for these benefits.

Removing non-stationary noise in spectrum sensing using matrix factorization

NASA Astrophysics Data System (ADS)

van Bloem, Jan-Willem; Schiphorst, Roel; Slump, Cornelis H.

2013-12-01

Spectrum sensing is key to many applications like dynamic spectrum access (DSA) systems or telecom regulators who need to measure utilization of frequency bands. The International Telecommunication Union (ITU) recommends a 10 dB threshold above the noise to decide whether a channel is occupied or not. However, radio frequency (RF) receiver front-ends are non-ideal. This means that the obtained data is distorted with noise and imperfections from the analog front-end. As part of the front-end the automatic gain control (AGC) circuitry mainly affects the sensing performance as strong adjacent signals lift the noise level. To enhance the performance of spectrum sensing significantly we focus in this article on techniques to remove the noise caused by the AGC from the sensing data. In order to do this we have applied matrix factorization techniques, i.e., SVD (singular value decomposition) and NMF (non-negative matrix factorization), which enables signal space analysis. In addition, we use live measurement results to verify the performance and to remove the effects of the AGC from the sensing data using above mentioned techniques, i.e., applied on block-wise available spectrum data. In this article it is shown that the occupancy in the industrial, scientific and medical (ISM) band, obtained by using energy detection (ITU recommended threshold), can be an overestimation of spectrum usage by 60%.

Fullerenes, nanotubes, and graphite as matrices for collision mechanism in secondary ion mass spectrometry: determination of cyclodextrin.

PubMed

Stupavska, Monika; Jerigova, Monika; Michalka, Miroslav; Hasko, Daniel; Szoecs, Vojtech; Velic, Dusan

2011-12-01

A technique for improving the sensitivity of high mass molecular analysis is described. Three carbon species, fullerenes, single walled carbon nanotubes, and highly ordered pyrolytic graphite are introduced as matrices for the secondary ion mass spectrometry analysis of cyclodextrin (C(42)H(70)O(35), 1134 u). The fullerene and nanotubes are deposited as single deposition, and 10, 20, or 30 deposition films and cyclodextrin is deposited on top. The cyclodextrin parent-like ions and two fragments were analyzed. A 30 deposition fullerene film enhanced the intensity of cationized cyclodextrin with Na by a factor of 37. While the C(6)H(11)O(5) fragment, corresponding to one glucopyranose unit, increased by a factor of 16. Although fragmentation on fullerene is not suppressed, the intensity is twice as low as the parent-like ion. Deprotonated cyclodextrin increases by 100× and its C(8)H(7)O fragment by 10×. While the fullerene matrix enhances secondary ion emission, the nanotubes matrix film generates a basically constant yield. Graphite gives rise to lower intensity peaks than either fullerene or nanotubes. Scanning electron microscopy and atomic force microscopy provide images of the fullerene and nanotubes deposition films revealing flat and web structured surfaces, respectively. A "colliding ball" model is presented to provide a plausible physical mechanism of parent-like ion enhancement using the fullerene matrix. © American Society for Mass Spectrometry, 2011

Patterns of Drug Usage Among Vietnam Veterans.

ERIC Educational Resources Information Center

Fisher, Allan H., Jr.; And Others

A factor analysis was performed on an intercorrelation matrix of reported drug usage frequencies for seven drug categories at two consecutive periods of time. Subjects were 1,010 Army Vietnam veterans in pay grade E6 or below, aged 26 years or less. Retrospective reporting identified drug usage prior to a tour of Vietnam and during the tour. Four…

Recursive flexible multibody system dynamics using spatial operators

NASA Technical Reports Server (NTRS)

Jain, A.; Rodriguez, G.

1992-01-01

This paper uses spatial operators to develop new spatially recursive dynamics algorithms for flexible multibody systems. The operator description of the dynamics is identical to that for rigid multibody systems. Assumed-mode models are used for the deformation of each individual body. The algorithms are based on two spatial operator factorizations of the system mass matrix. The first (Newton-Euler) factorization of the mass matrix leads to recursive algorithms for the inverse dynamics, mass matrix evaluation, and composite-body forward dynamics for the systems. The second (innovations) factorization of the mass matrix, leads to an operator expression for the mass matrix inverse and to a recursive articulated-body forward dynamics algorithm. The primary focus is on serial chains, but extensions to general topologies are also described. A comparison of computational costs shows that the articulated-body, forward dynamics algorithm is much more efficient than the composite-body algorithm for most flexible multibody systems.

Direct Solve of Electrically Large Integral Equations for Problem Sizes to 1M Unknowns

NASA Technical Reports Server (NTRS)

Shaeffer, John

2008-01-01

Matrix methods for solving integral equations via direct solve LU factorization are presently limited to weeks to months of very expensive supercomputer time for problems sizes of several hundred thousand unknowns. This report presents matrix LU factor solutions for electromagnetic scattering problems for problem sizes to one million unknowns with thousands of right hand sides that run in mere days on PC level hardware. This EM solution is accomplished by utilizing the numerical low rank nature of spatially blocked unknowns using the Adaptive Cross Approximation for compressing the rank deficient blocks of the system Z matrix, the L and U factors, the right hand side forcing function and the final current solution. This compressed matrix solution is applied to a frequency domain EM solution of Maxwell's equations using standard Method of Moments approach. Compressed matrix storage and operations count leads to orders of magnitude reduction in memory and run time.

Multivariate analysis of fears in dental phobic patients according to a reduced FSS-II scale.

PubMed

Hakeberg, M; Gustafsson, J E; Berggren, U; Carlsson, S G

1995-10-01

This study analyzed and assessed dimensions of a questionnaire developed to measure general fears and phobias. A previous factor analysis among 109 dental phobics had revealed a five-factor structure with 22 items and an explained total variance of 54%. The present study analyzed the same material using a multivariate statistical procedure (LISREL) to reveal structural latent variables. The LISREL analysis, based on the correlation matrix, yielded a chi-square of 216.6 with 195 degrees of freedom (P = 0.138) and showed a model with seven latent variables. One was a general fear factor correlated to all 22 items. The other six factors concerned "Illness & Death" (5 items), "Failures & Embarrassment" (5 items), "Social situations" (5 items), "Physical injuries" (4 items), "Animals & Natural phenomena" (4 items). One item (opposite sex) was included in both "Failures & Embarrassment" and "Social situations". The last factor, "Social interaction", combined all the items in "Failures & Embarrassment" and "Social situations" (9 items). In conclusion, this multivariate statistical analysis (LISREL) revealed and confirmed a factor structure similar to our previous study, but added two important dimensions not shown with a traditional factor analysis. This reduced FSS-II version measures general fears and phobias and may be used on a routine clinical basis as well as in dental phobia research.

Filling gaps in large ecological databases: consequences for the study of global-scale plant functional trait patterns

NASA Astrophysics Data System (ADS)

Schrodt, Franziska; Shan, Hanhuai; Fazayeli, Farideh; Karpatne, Anuj; Kattge, Jens; Banerjee, Arindam; Reichstein, Markus; Reich, Peter

2013-04-01

With the advent of remotely sensed data and coordinated efforts to create global databases, the ecological community has progressively become more data-intensive. However, in contrast to other disciplines, statistical ways of handling these large data sets, especially the gaps which are inherent to them, are lacking. Widely used theoretical approaches, for example model averaging based on Akaike's information criterion (AIC), are sensitive to missing values. Yet, the most common way of handling sparse matrices - the deletion of cases with missing data (complete case analysis) - is known to severely reduce statistical power as well as inducing biased parameter estimates. In order to address these issues, we present novel approaches to gap filling in large ecological data sets using matrix factorization techniques. Factorization based matrix completion was developed in a recommender system context and has since been widely used to impute missing data in fields outside the ecological community. Here, we evaluate the effectiveness of probabilistic matrix factorization techniques for imputing missing data in ecological matrices using two imputation techniques. Hierarchical Probabilistic Matrix Factorization (HPMF) effectively incorporates hierarchical phylogenetic information (phylogenetic group, family, genus, species and individual plant) into the trait imputation. Advanced Hierarchical Probabilistic Matrix Factorization (aHPMF) on the other hand includes climate and soil information into the matrix factorization by regressing the environmental variables against residuals of the HPMF. One unique opportunity opened up by aHPMF is out-of-sample prediction, where traits can be predicted for specific species at locations different to those sampled in the past. This has potentially far-reaching consequences for the study of global-scale plant functional trait patterns. We test the accuracy and effectiveness of HPMF and aHPMF in filling sparse matrices, using the TRY database of plant functional traits (http://www.try-db.org). TRY is one of the largest global compilations of plant trait databases (750 traits of 1 million plants), encompassing data on morphological, anatomical, biochemical, phenological and physiological features of plants. However, despite of unprecedented coverage, the TRY database is still very sparse, severely limiting joint trait analyses. Plant traits are the key to understanding how plants as primary producers adjust to changes in environmental conditions and in turn influence them. Forming the basis for Dynamic Global Vegetation Models (DGVMs), plant traits are also fundamental in global change studies for predicting future ecosystem changes. It is thus imperative that missing data is imputed in as accurate and precise a way as possible. In this study, we show the advantages and disadvantages of applying probabilistic matrix factorization techniques in incorporating hierarchical and environmental information for the prediction of missing plant traits as compared to conventional imputation techniques such as the complete case and mean approaches. We will discuss the implications of using gap-filled data for global-scale studies of plant functional trait - environment relationship as opposed to the above-mentioned conventional techniques, using examples of out-of-sample predictions of foliar Nitrogen across several species' ranges and biomes.

Application of fiber bridging models to fatigue crack growth in unidirectional titanium matrix composites

NASA Technical Reports Server (NTRS)

Bakuckas, J. G., Jr.; Johnson, W. S.

1992-01-01

Several fiber bridging models were reviewed and applied to study the matrix fatigue crack growth behavior in center notched (0)(sub 8) SCS-6/Ti-15-3 and (0)(sub 4) SCS-6/Ti-6Al-4V laminates. Observations revealed that fatigue damage consisted primarily of matrix cracks and fiber matrix interfacial failure in the (0)(sub 8) SCS-6/Ti-15-3 laminates. Fiber-matrix interface failure included fracture of the brittle reaction zone and cracking between the two carbon rich fiber coatings. Intact fibers in the wake of the matrix cracks reduce the stress intensity factor range. Thus, an applied stress intensity factor range is inappropriate to characterize matrix crack growth behavior. Fiber bridging models were used to determine the matrix stress intensity factor range in titanium metal matrix composites. In these models, the fibers in the wake of the crack are idealized as a closure pressure. An unknown constant frictional shear stress is assumed to act along the debond or slip length of the bridging fibers. The frictional shear stress was used as a curve fitting parameter to available data (crack growth data, crack opening displacement data, and debond length data). Large variations in the frictional shear stress required to fit the experimental data indicate that the fiber bridging models in their present form lack predictive capabilities. However, these models provide an efficient and relatively simple engineering method for conducting parametric studies of the matrix growth behavior based on constituent properties.

ROBNCA: robust network component analysis for recovering transcription factor activities.

PubMed

Noor, Amina; Ahmad, Aitzaz; Serpedin, Erchin; Nounou, Mohamed; Nounou, Hazem

2013-10-01

Network component analysis (NCA) is an efficient method of reconstructing the transcription factor activity (TFA), which makes use of the gene expression data and prior information available about transcription factor (TF)-gene regulations. Most of the contemporary algorithms either exhibit the drawback of inconsistency and poor reliability, or suffer from prohibitive computational complexity. In addition, the existing algorithms do not possess the ability to counteract the presence of outliers in the microarray data. Hence, robust and computationally efficient algorithms are needed to enable practical applications. We propose ROBust Network Component Analysis (ROBNCA), a novel iterative algorithm that explicitly models the possible outliers in the microarray data. An attractive feature of the ROBNCA algorithm is the derivation of a closed form solution for estimating the connectivity matrix, which was not available in prior contributions. The ROBNCA algorithm is compared with FastNCA and the non-iterative NCA (NI-NCA). ROBNCA estimates the TF activity profiles as well as the TF-gene control strength matrix with a much higher degree of accuracy than FastNCA and NI-NCA, irrespective of varying noise, correlation and/or amount of outliers in case of synthetic data. The ROBNCA algorithm is also tested on Saccharomyces cerevisiae data and Escherichia coli data, and it is observed to outperform the existing algorithms. The run time of the ROBNCA algorithm is comparable with that of FastNCA, and is hundreds of times faster than NI-NCA. The ROBNCA software is available at http://people.tamu.edu/∼amina/ROBNCA

Positive Matrix Factorization Model for environmental data analyses

EPA Pesticide Factsheets

Positive Matrix Factorization is a receptor model developed by EPA to provide scientific support for current ambient air quality standards and implement those standards by identifying and quantifying the relative contributions of air pollution sources.

Difficulty Factors, Distribution Effects, and the Least Squares Simplex Data Matrix Solution

ERIC Educational Resources Information Center

Ten Berge, Jos M. F.

1972-01-01

In the present article it is argued that the Least Squares Simplex Data Matrix Solution does not deal adequately with difficulty factors inasmuch as the theoretical foundation is insufficient. (Author/CB)

A multi-element screening method to identify metal targets for blood biomonitoring in green sea turtles (Chelonia mydas).

PubMed

Villa, C A; Finlayson, S; Limpus, C; Gaus, C

2015-04-15

Biomonitoring of blood is commonly used to identify and quantify occupational or environmental exposure to chemical contaminants. Increasingly, this technique has been applied to wildlife contaminant monitoring, including for green turtles, allowing for the non-lethal evaluation of chemical exposure in their nearshore environment. The sources, composition, bioavailability and toxicity of metals in the marine environment are, however, often unknown and influenced by numerous biotic and abiotic factors. These factors can vary considerably across time and space making the selection of the most informative elements for biomonitoring challenging. This study aimed to validate an ICP-MS multi-element screening method for green turtle blood in order to identify and facilitate prioritisation of target metals for subsequent fully quantitative analysis. Multi-element screening provided semiquantitative results for 70 elements, 28 of which were also determined through fully quantitative analysis. Of the 28 comparable elements, 23 of the semiquantitative results had an accuracy between 67% and 112% relative to the fully quantified values. In lieu of any available turtle certified reference materials (CRMs), we evaluated the use of human blood CRMs as a matrix surrogate for quality control, and compared two commonly used sample preparation methods for matrix related effects. The results demonstrate that human blood provides an appropriate matrix for use as a quality control material in the fully quantitative analysis of metals in turtle blood. An example for the application of this screening method is provided by comparing screening results from blood of green turtles foraging in an urban and rural region in Queensland, Australia. Potential targets for future metal biomonitoring in these regions were identified by this approach. Copyright © 2014 Elsevier B.V. All rights reserved.

Factors affecting fixation of heavy metals in solidified/stabilized matrix: a review.

PubMed

Malviya, Rachana; Chaudhary, Rubina

2010-07-01

In this paper, an effort has been made to understand the factors, which affect fixation of heavy metals in solidified/stabilized matrix. Various aspects related to the solidification/stabilization of different heavy metals (Ar, Ba, Cu, Cr, Pb, Zn, Hg) are reviewed. A comparative study of different binders for the fixation of each metal has also been carried out to suggest the most suitable binder, pretreatment required for the metal. Valence, speciation, pH and other factors are also considered while reviewing metal retention capacity of different matrix.

Fiber pushout and interfacial shear in metal-matrix composites

NASA Technical Reports Server (NTRS)

Koss, Donald A.; Hellmann, John R.; Kallas, M. N.

1993-01-01

Recent thin-slice pushout tests have suggested that MMC matrix-fiber interface failure processes depend not only on such intrinsic factors as bond strength and toughness, and matrix plasticity, but such extrinsic factors as specimen configuration, thermally-induced residual stresses, and the mechanics associated with a given test. After detailing the contrasts in fiber-pullout and fiber-pushout mechanics, attention is given to selected aspects of thin-slice fiber pushout behavior illustrative of the physical nature of interfacial shear response and its dependence on both intrinsic and extrinsic factors.

Fossil Signatures Using Elemental Abundance Distributions and Bayesian Probabilistic Classification

NASA Technical Reports Server (NTRS)

Hoover, Richard B.; Storrie-Lombardi, Michael C.

2004-01-01

Elemental abundances (C6, N7, O8, Na11, Mg12, Al3, P15, S16, Cl17, K19, Ca20, Ti22, Mn25, Fe26, and Ni28) were obtained for a set of terrestrial fossils and the rock matrix surrounding them. Principal Component Analysis extracted five factors accounting for the 92.5% of the data variance, i.e. information content, of the elemental abundance data. Hierarchical Cluster Analysis provided unsupervised sample classification distinguishing fossil from matrix samples on the basis of either raw abundances or PCA input that agreed strongly with visual classification. A stochastic, non-linear Artificial Neural Network produced a Bayesian probability of correct sample classification. The results provide a quantitative probabilistic methodology for discriminating terrestrial fossils from the surrounding rock matrix using chemical information. To demonstrate the applicability of these techniques to the assessment of meteoritic samples or in situ extraterrestrial exploration, we present preliminary data on samples of the Orgueil meteorite. In both systems an elemental signature produces target classification decisions remarkably consistent with morphological classification by a human expert using only structural (visual) information. We discuss the possibility of implementing a complexity analysis metric capable of automating certain image analysis and pattern recognition abilities of the human eye using low magnification optical microscopy images and discuss the extension of this technique across multiple scales.

Streptococcus pyogenes degrades extracellular matrix in chondrocytes via MMP-13

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sakurai, Atsuo; Okahashi, Nobuo; Maruyama, Fumito

2008-08-29

Group A streptococcus (GAS) causes a wide range of human diseases, including bacterial arthritis. The pathogenesis of arthritis is characterized by synovial proliferation and the destruction of cartilage and subchondral bone in joints. We report here that GAS strain JRS4 invaded a chondrogenic cell line ATDC5 and induced the degradation of the extracellular matrix (ECM), whereas an isogenic mutant of JRS4 lacking a fibronectin-binding protein, SAM1, failed to invade the chondrocytes or degrade the ECM. Reverse transcription-PCR and Western blot analysis revealed that the expression of matrix metalloproteinase (MMP)-13 was strongly elevated during the infection with GAS. A reporter assaymore » revealed that the activation of the AP-1 transcription factor and the phosphorylation of c-Jun terminal kinase participated in MMP-13 expression. These results suggest that MMP-13 plays an important role in the destruction of infected joints during the development of septic arthritis.« less

Study on the Preparation Process and Influential Factors of Large Area Environment-friendly Molten Carbonate Fuel Cell Matrix

NASA Astrophysics Data System (ADS)

Zhang, Ruiyun; Xu, Shisen; Cheng, Jian; Wang, Hongjian; Ren, Yongqiang

2017-07-01

Low-cost and high-performance matrix materials used in mass production of molten carbonate fuel cell (MCFC) were prepared by automatic casting machine with α-LiAlO2 powder material synthesized by gel-solid method, and distilled water as solvent. The single cell was assembled for generating test, and the good performance of the matrix was verified. The paper analyzed the factors affecting aqueous tape casting matrix preparation, such as solvent content, dispersant content, milling time, blade height and casting machine running speed, providing a solid basis for the mass production of large area environment-friendly matrix used in molten carbonate fuel cell.

Factor analysis of the Zung self-rating depression scale in a large sample of patients with major depressive disorder in primary care.

PubMed

Romera, Irene; Delgado-Cohen, Helena; Perez, Teresa; Caballero, Luis; Gilaberte, Immaculada

2008-01-14

The aim of this study was to examine the symptomatic dimensions of depression in a large sample of patients with major depressive disorder (MDD) in the primary care (PC) setting by means of a factor analysis of the Zung self-rating depression scale (ZSDS). A factor analysis was performed, based on the polychoric correlations matrix, between ZSDS items using promax oblique rotation in 1049 PC patients with a diagnosis of MDD (DSM-IV). A clinical interpretable four-factor solution consisting of a core depressive factor (I); a cognitive factor (II); an anxiety factor (III) and a somatic factor (IV) was extracted. These factors accounted for 36.9% of the variance on the ZSDS. The 4-factor structure was validated and high coefficients of congruence were obtained (0.98, 0.95, 0.92 and 0.87 for factors I, II, III and IV, respectively). The model seemed to fit the data well with fit indexes within recommended ranges (GFI = 0.9330, AGFI = 0.9112 and RMR = 0.0843). Our findings suggest that depressive symptoms in patients with MDD in the PC setting cluster into four dimensions: core depressive, cognitive, anxiety and somatic, by means of a factor analysis of the ZSDS. Further research is needed to identify possible diagnostic, therapeutic or prognostic implications of the different depressive symptomatic profiles.

Factor analysis of the Zung self-rating depression scale in a large sample of patients with major depressive disorder in primary care

PubMed Central

Romera, Irene; Delgado-Cohen, Helena; Perez, Teresa; Caballero, Luis; Gilaberte, Immaculada

2008-01-01

Background The aim of this study was to examine the symptomatic dimensions of depression in a large sample of patients with major depressive disorder (MDD) in the primary care (PC) setting by means of a factor analysis of the Zung self-rating depression scale (ZSDS). Methods A factor analysis was performed, based on the polychoric correlations matrix, between ZSDS items using promax oblique rotation in 1049 PC patients with a diagnosis of MDD (DSM-IV). Results A clinical interpretable four-factor solution consisting of a core depressive factor (I); a cognitive factor (II); an anxiety factor (III) and a somatic factor (IV) was extracted. These factors accounted for 36.9% of the variance on the ZSDS. The 4-factor structure was validated and high coefficients of congruence were obtained (0.98, 0.95, 0.92 and 0.87 for factors I, II, III and IV, respectively). The model seemed to fit the data well with fit indexes within recommended ranges (GFI = 0.9330, AGFI = 0.9112 and RMR = 0.0843). Conclusion Our findings suggest that depressive symptoms in patients with MDD in the PC setting cluster into four dimensions: core depressive, cognitive, anxiety and somatic, by means of a factor analysis of the ZSDS. Further research is needed to identify possible diagnostic, therapeutic or prognostic implications of the different depressive symptomatic profiles. PMID:18194524

A fast, preconditioned conjugate gradient Toeplitz solver

NASA Technical Reports Server (NTRS)

Pan, Victor; Schrieber, Robert

1989-01-01

A simple factorization is given of an arbitrary hermitian, positive definite matrix in which the factors are well-conditioned, hermitian, and positive definite. In fact, given knowledge of the extreme eigenvalues of the original matrix A, an optimal improvement can be achieved, making the condition numbers of each of the two factors equal to the square root of the condition number of A. This technique is to applied to the solution of hermitian, positive definite Toeplitz systems. Large linear systems with hermitian, positive definite Toeplitz matrices arise in some signal processing applications. A stable fast algorithm is given for solving these systems that is based on the preconditioned conjugate gradient method. The algorithm exploits Toeplitz structure to reduce the cost of an iteration to O(n log n) by applying the fast Fourier Transform to compute matrix-vector products. Matrix factorization is used as a preconditioner.

A new technique for ordering asymmetrical three-dimensional data sets in ecology.

PubMed

Pavoine, Sandrine; Blondel, Jacques; Baguette, Michel; Chessel, Daniel

2007-02-01

The aim of this paper is to tackle the problem that arises from asymmetrical data cubes formed by two crossed factors fixed by the experimenter (factor A and factor B, e.g., sites and dates) and a factor which is not controlled for (the species). The entries of this cube are densities in species. We approach this kind of data by the comparison of patterns, that is to say by analyzing first the effect of factor B on the species-factor A pattern, and second the effect of factor A on the species-factor B pattern. The analysis of patterns instead of individual responses requires a correspondence analysis. We use a method we call Foucart's correspondence analysis to coordinate the correspondence analyses of several independent matrices of species x factor A (respectively B) type, corresponding to each modality of factor B (respectively A). Such coordination makes it possible to evaluate the effect of factor B (respectively A) on the species-factor A (respectively B) pattern. The results obtained by such a procedure are much more insightful than those resulting from a classical single correspondence analysis applied to the global matrix that is obtained by simply unrolling the data cube, juxtaposing for example the individual species x factor A matrices through modalities of factor B. This is because a single global correspondence analysis combines three effects of factors in a way that cannot be determined from factorial maps (factor A, factor B, and factor A x factor B interaction) whereas the applications of Foucart's correspondence analysis clearly discriminate two different issues. Using two data sets, we illustrate that this technique proves to be particularly powerful in the analyses of ecological convergence which include several distinct data sets and in the analyses of spatiotemporal variations of species distributions.

Comparative Effect of Physicomechanical and Biomolecular Cues on Zone-Specific Chondrogenic Differentiation of Mesenchymal Stem Cells

PubMed Central

Moeinzadeh, Seyedsina; Shariati, Seyed Ramin Pajoum; Jabbari, Esmaiel

2016-01-01

Current tissue engineering approaches to regeneration of articular cartilage rarely restore the tissue to its normal state because the generated tissue lacks the intricate zonal organization of the native cartilage. Zonal regeneration of articular cartilage is hampered by the lack of knowledge for the relation between physical, mechanical, and biomolecular cues and zone-specific chondrogenic differentiation of progenitor cells. This work investigated in 3D the effect of TGF-β1, zone-specific growth factors, optimum matrix stiffness, and adding nanofibers on the expression of chondrogenic markers specific to the superficial, middle, and calcified zones of articular cartilage by the differentiating human mesenchymal stem cells (hMSCs). Growth factors included BMP-7, IGF-1, and hydroxyapatite (HA) for the superficial, middle, and calcified zones, respectively; optimum matrix stiffness was 80 kPa, 2.1 MPa, and 320 MPa; and nanofibers were aligned horizontal, random, and perpendicular to the gel surface. hMSCs with zone-specific cell densities were encapsulated in engineered hydrogels and cultured with or without TGF-β1, zone-specific growth factor, optimum matrix modulus, and fiber addition and cultured in basic chondrogenic medium. The expression of encapsulated cells was measured by mRNA, protein, and biochemical analysis. Results indicated that zone-specific matrix stiffness had a dominating effect on chondrogenic differentiation of hMSCs to the superficial and calcified zone phenotypes. Addition of aligned nanofibers parallel to the direction of gel surface significantly enhanced expression of Col II in the superficial zone chondrogenic differentiation of hMSCs. Conversely, biomolecular factor IGF-1 in combination with TGF-β1 had a dominating effect on the middle zone chondrogenic differentiation of hMSCs. Results of this work could potentially lead to the development of multilayer grafts mimicking the zonal organization of articular cartilage. PMID:27038568

Social cognition in schizophrenia: cognitive and affective factors.

PubMed

Ziv, Ido; Leiser, David; Levine, Joseph

2011-01-01

Social cognition refers to how people conceive, perceive, and draw inferences about mental and emotional states of others in the social world. Previous studies suggest that the concept of social cognition involves several abilities, including those related to affect and cognition. The present study analyses the deficits of individuals with schizophrenia in two areas of social cognition: Theory of Mind (ToM) and emotion recognition and processing. Examining the impairment of these abilities in patients with schizophrenia has the potential to elucidate the neurophysiological regions involved in social cognition and may also have the potential to aid rehabilitation. Two experiments were conducted. Both included the same five tasks: first- and second-level false-belief ToM tasks, emotion inferencing, understanding of irony, and matrix reasoning (a WAIS-R subtest). The matrix reasoning task was administered to evaluate and control for the association of the other tasks with analytic reasoning skills. Experiment 1 involved factor analysis of the task performance of 75 healthy participants. Experiment 2 compared 30 patients with schizophrenia to an equal number of matched controls. Results. (1) The five tasks were clearly divided into two factors corresponding to the two areas of social cognition, ToM and emotion recognition and processing. (2) Schizophrenics' performance was impaired on all tasks, particularly on those loading heavily on the analytic component (matrix reasoning and second-order ToM). (3) Matrix reasoning, second-level ToM (ToM2), and irony were found to distinguish patients from controls, even when all other tasks that revealed significant impairment in the patients' performance were taken into account. The two areas of social cognition examined are related to distinct factors. The mechanism for answering ToM questions (especially ToM2) depends on analytic reasoning capabilities, but the difficulties they present to individuals with schizophrenia are due to other components as well. The impairment in social cognition in schizophrenia stems from deficiencies in several mechanisms, including the ability to think analytically and to process emotion information and cues.

Genetic polymorphism of matrix metalloproteinase family and chronic obstructive pulmonary disease susceptibility: a meta-analysis.

PubMed

Zhou, Hongbin; Wu, Yinfang; Jin, Yan; Zhou, Jiesen; Zhang, Chao; Che, Luanqing; Jing, Jiyong; Chen, Zhihua; Li, Wen; Shen, Huahao

2013-10-02

Matrix metalloproteinase (MMP) family is considered to be associated with chronic obstructive pulmonary disease (COPD) pathogenesis, however, no consistent results have been provided by previous studies. In this report, we performed Meta analysis to investigate the association between four kinds of MMP single nucleotide polymorphisms (SNP, MMP1 -1607 1G/2G, MMP3 -1171 5A/6A, MMP9 -1562 C/T, MMP12 -82 A/G) and COPD risk from 21 studies including 4184 cases and 5716 controls. Both overall and subgroup association between SNP and COPD susceptibility were tested. There was no evident association between MMP polymorphisms and COPD susceptibility in general population. On the other hand, subgroup analysis suggested that MMP9 -1562 C/T polymorphism was related to COPD, as we found that C allele carriers were at lower risk in some subgroups stratified by lung function, age and genotype identification method, compared with TT homozygotes. Our results indicated the genotype TT might be one genetic risk factor of severe COPD.

Lanczos eigensolution method for high-performance computers

NASA Technical Reports Server (NTRS)

Bostic, Susan W.

1991-01-01

The theory, computational analysis, and applications are presented of a Lanczos algorithm on high performance computers. The computationally intensive steps of the algorithm are identified as: the matrix factorization, the forward/backward equation solution, and the matrix vector multiples. These computational steps are optimized to exploit the vector and parallel capabilities of high performance computers. The savings in computational time from applying optimization techniques such as: variable band and sparse data storage and access, loop unrolling, use of local memory, and compiler directives are presented. Two large scale structural analysis applications are described: the buckling of a composite blade stiffened panel with a cutout, and the vibration analysis of a high speed civil transport. The sequential computational time for the panel problem executed on a CONVEX computer of 181.6 seconds was decreased to 14.1 seconds with the optimized vector algorithm. The best computational time of 23 seconds for the transport problem with 17,000 degs of freedom was on the the Cray-YMP using an average of 3.63 processors.

Evaluation of non-negative matrix factorization of grey matter in age prediction.

PubMed

Varikuti, Deepthi P; Genon, Sarah; Sotiras, Aristeidis; Schwender, Holger; Hoffstaedter, Felix; Patil, Kaustubh R; Jockwitz, Christiane; Caspers, Svenja; Moebus, Susanne; Amunts, Katrin; Davatzikos, Christos; Eickhoff, Simon B

2018-06-01

The relationship between grey matter volume (GMV) patterns and age can be captured by multivariate pattern analysis, allowing prediction of individuals' age based on structural imaging. Raw data, voxel-wise GMV and non-sparse factorization (with Principal Component Analysis, PCA) show good performance but do not promote relatively localized brain components for post-hoc examinations. Here we evaluated a non-negative matrix factorization (NNMF) approach to provide a reduced, but also interpretable representation of GMV data in age prediction frameworks in healthy and clinical populations. This examination was performed using three datasets: a multi-site cohort of life-span healthy adults, a single site cohort of older adults and clinical samples from the ADNI dataset with healthy subjects, participants with Mild Cognitive Impairment and patients with Alzheimer's disease (AD) subsamples. T1-weighted images were preprocessed with VBM8 standard settings to compute GMV values after normalization, segmentation and modulation for non-linear transformations only. Non-negative matrix factorization was computed on the GM voxel-wise values for a range of granularities (50-690 components) and LASSO (Least Absolute Shrinkage and Selection Operator) regression were used for age prediction. First, we compared the performance of our data compression procedure (i.e., NNMF) to various other approaches (i.e., uncompressed VBM data, PCA-based factorization and parcellation-based compression). We then investigated the impact of the granularity on the accuracy of age prediction, as well as the transferability of the factorization and model generalization across datasets. We finally validated our framework by examining age prediction in ADNI samples. Our results showed that our framework favorably compares with other approaches. They also demonstrated that the NNMF based factorization derived from one dataset could be efficiently applied to compress VBM data of another dataset and that granularities between 300 and 500 components give an optimal representation for age prediction. In addition to the good performance in healthy subjects our framework provided relatively localized brain regions as the features contributing to the prediction, thereby offering further insights into structural changes due to brain aging. Finally, our validation in clinical populations showed that our framework is sensitive to deviance from normal structural variations in pathological aging. Copyright © 2018 Elsevier Inc. All rights reserved.

Estimating historical respirable crystalline silica exposures for Chinese pottery workers and iron/copper, tin, and tungsten miners.

PubMed

Zhuang, Z; Hearl, F J; Odencrantz, J; Chen, W; Chen, B T; Chen, J Q; McCawley, M A; Gao, P; Soderholm, S C

2001-11-01

Collaborative studies of Chinese workers, using over four decades of dust monitoring data, are being conducted by the National Institute for Occupational Safety and Health (NIOSH) and Tongji Medical University in China. The goal of these projects is to establish exposure-response relationships for the development of diseases such as silicosis or lung cancer in cohorts of pottery and mine workers. It is necessary to convert Chinese dust measurements to respirable silica measurements in order to make results from the Chinese data comparable to other results in the literature. This article describes the development of conversion factors and estimates of historical respirable crystalline silica exposure for Chinese workers. Ambient total dust concentrations (n>17000) and crystalline silica concentrations (n=347) in bulk dust were first gathered from historical industrial hygiene records. Analysis of the silica content in historical bulk samples revealed no trend from 1950 up to the present. During 1988-1989, side-by-side airborne dust samples (n=143 pairs) were collected using nylon cyclones and traditional Chinese samplers in 20 metal mines and nine pottery factories in China. These data were used to establish conversion factors between respirable crystalline silica concentrations and Chinese total dust concentrations. Based on the analysis of the available evidence, conversion factors derived from the 1988-1989 sampling campaign are assumed to apply to other time periods in this paper. The conversion factors were estimated to be 0.0143 for iron/copper, 0.0355 for pottery factories, 0.0429 for tin mines, and 0.0861 for tungsten mines. Conversion factors for individual facilities within each industry were also calculated. Analysis of variance revealed that mean conversion factors are significantly different among facilities within the iron/copper industry and within the pottery industry. The relative merits of using facility-specific conversion factors, industry-wide conversion factors, or a weighted average of the two are discussed. The exposure matrix of the historical Chinese total dust concentrations was multiplied by these conversion factors to obtain an exposure matrix of historical respirable crystalline silica concentrations.

Development of gastro intestinal sustained release tablet formulation containing acryl-EZE and pH-dependent swelling HPMC K 15 M.

PubMed

Lamoudi, Lynda; Chaumeil, Jean Claude; Daoud, Kamel

2012-05-01

The aim of this study was to evaluate physical properties and release from matrix tablets containing different ratios of HPMC 15 M and Acryl-EZE. A further aim is to assess their suitability for pH dependent controlled release. Matrix tablets containing HPMC 15 M and Acryl-EZE were manufactured using a fluidized bed. The release from this matrix using Sodium Diclofenac (SD) as model drug is studied in two dissolution media (0.1 N HCl or pH = 6.8 phosphate buffer solution); the release rate, mechanism, and pH dependence were characterized by fitting four kinetic models and by using a similarity factor analysis. The obtained results revealed that the presence of Acryl-EZE in the matrix tablets is effective in protecting the dosage forms from release in acid environments such as gastric fluid. In pH = 6.8 phosphate buffer, the drug release rate and mechanism of release from all matrices is mainly controlled by HPMC 15 M. The model of Korsmeyer-Peppas was found to fit experimental dissolution results.

Field-scale effective matrix diffusion coefficient for fractured rock: results from literature survey.

PubMed

Zhou, Quanlin; Liu, Hui-Hai; Molz, Fred J; Zhang, Yingqi; Bodvarsson, Gudmundur S

2007-08-15

Matrix diffusion is an important mechanism for solute transport in fractured rock. We recently conducted a literature survey on the effective matrix diffusion coefficient, D(m)(e), a key parameter for describing matrix diffusion processes at the field scale. Forty field tracer tests at 15 fractured geologic sites were surveyed and selected for the study, based on data availability and quality. Field-scale D(m)(e) values were calculated, either directly using data reported in the literature, or by reanalyzing the corresponding field tracer tests. The reanalysis was conducted for the selected tracer tests using analytic or semi-analytic solutions for tracer transport in linear, radial, or interwell flow fields. Surveyed data show that the scale factor of the effective matrix diffusion coefficient (defined as the ratio of D(m)(e) to the lab-scale matrix diffusion coefficient, D(m), of the same tracer) is generally larger than one, indicating that the effective matrix diffusion coefficient in the field is comparatively larger than the matrix diffusion coefficient at the rock-core scale. This larger value can be attributed to the many mass-transfer processes at different scales in naturally heterogeneous, fractured rock systems. Furthermore, we observed a moderate, on average trend toward systematic increase in the scale factor with observation scale. This trend suggests that the effective matrix diffusion coefficient is likely to be statistically scale-dependent. The scale-factor value ranges from 0.5 to 884 for observation scales from 5 to 2000 m. At a given scale, the scale factor varies by two orders of magnitude, reflecting the influence of differing degrees of fractured rock heterogeneity at different geologic sites. In addition, the surveyed data indicate that field-scale longitudinal dispersivity generally increases with observation scale, which is consistent with previous studies. The scale-dependent field-scale matrix diffusion coefficient (and dispersivity) may have significant implications for assessing long-term, large-scale radionuclide and contaminant transport events in fractured rock, both for nuclear waste disposal and contaminant remediation.

SparRec: An effective matrix completion framework of missing data imputation for GWAS

NASA Astrophysics Data System (ADS)

Jiang, Bo; Ma, Shiqian; Causey, Jason; Qiao, Linbo; Hardin, Matthew Price; Bitts, Ian; Johnson, Daniel; Zhang, Shuzhong; Huang, Xiuzhen

2016-10-01

Genome-wide association studies present computational challenges for missing data imputation, while the advances of genotype technologies are generating datasets of large sample sizes with sample sets genotyped on multiple SNP chips. We present a new framework SparRec (Sparse Recovery) for imputation, with the following properties: (1) The optimization models of SparRec, based on low-rank and low number of co-clusters of matrices, are different from current statistics methods. While our low-rank matrix completion (LRMC) model is similar to Mendel-Impute, our matrix co-clustering factorization (MCCF) model is completely new. (2) SparRec, as other matrix completion methods, is flexible to be applied to missing data imputation for large meta-analysis with different cohorts genotyped on different sets of SNPs, even when there is no reference panel. This kind of meta-analysis is very challenging for current statistics based methods. (3) SparRec has consistent performance and achieves high recovery accuracy even when the missing data rate is as high as 90%. Compared with Mendel-Impute, our low-rank based method achieves similar accuracy and efficiency, while the co-clustering based method has advantages in running time. The testing results show that SparRec has significant advantages and competitive performance over other state-of-the-art existing statistics methods including Beagle and fastPhase.

The successive projection algorithm as an initialization method for brain tumor segmentation using non-negative matrix factorization.

PubMed

Sauwen, Nicolas; Acou, Marjan; Bharath, Halandur N; Sima, Diana M; Veraart, Jelle; Maes, Frederik; Himmelreich, Uwe; Achten, Eric; Van Huffel, Sabine

2017-01-01

Non-negative matrix factorization (NMF) has become a widely used tool for additive parts-based analysis in a wide range of applications. As NMF is a non-convex problem, the quality of the solution will depend on the initialization of the factor matrices. In this study, the successive projection algorithm (SPA) is proposed as an initialization method for NMF. SPA builds on convex geometry and allocates endmembers based on successive orthogonal subspace projections of the input data. SPA is a fast and reproducible method, and it aligns well with the assumptions made in near-separable NMF analyses. SPA was applied to multi-parametric magnetic resonance imaging (MRI) datasets for brain tumor segmentation using different NMF algorithms. Comparison with common initialization methods shows that SPA achieves similar segmentation quality and it is competitive in terms of convergence rate. Whereas SPA was previously applied as a direct endmember extraction tool, we have shown improved segmentation results when using SPA as an initialization method, as it allows further enhancement of the sources during the NMF iterative procedure.

A multi-platform evaluation of the randomized CX low-rank matrix factorization in Spark

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gittens, Alex; Kottalam, Jey; Yang, Jiyan

We investigate the performance and scalability of the randomized CX low-rank matrix factorization and demonstrate its applicability through the analysis of a 1TB mass spectrometry imaging (MSI) dataset, using Apache Spark on an Amazon EC2 cluster, a Cray XC40 system, and an experimental Cray cluster. We implemented this factorization both as a parallelized C implementation with hand-tuned optimizations and in Scala using the Apache Spark high-level cluster computing framework. We obtained consistent performance across the three platforms: using Spark we were able to process the 1TB size dataset in under 30 minutes with 960 cores on all systems, with themore » fastest times obtained on the experimental Cray cluster. In comparison, the C implementation was 21X faster on the Amazon EC2 system, due to careful cache optimizations, bandwidth-friendly access of matrices and vector computation using SIMD units. We report these results and their implications on the hardware and software issues arising in supporting data-centric workloads in parallel and distributed environments.« less

Notch Sensitivity of Woven Ceramic Matrix Composites Under Tensile Loading: An Experimental, Analytical, and Finite Element Study

NASA Technical Reports Server (NTRS)

Haque, A.; Ahmed, L.; Ware, T.; Jeelani, S.; Verrilli, Michael J. (Technical Monitor)

2001-01-01

The stress concentrations associated with circular notches and subjected to uniform tensile loading in woven ceramic matrix composites (CMCs) have been investigated for high-efficient turbine engine applications. The CMC's were composed of Nicalon silicon carbide woven fabric in SiNC matrix manufactured through polymer impregnation process (PIP). Several combinations of hole diameter/plate width ratios and ply orientations were considered in this study. In the first part, the stress concentrations were calculated measuring strain distributions surrounding the hole using strain gages at different locations of the specimens during the initial portion of the stress-strain curve before any microdamage developed. The stress concentration was also calculated analytically using Lekhnitskii's solution for orthotropic plates. A finite-width correction factor for anisotropic and orthotropic composite plate was considered. The stress distributions surrounding the circular hole of a CMC's plate were further studied using finite element analysis. Both solid and shell elements were considered. The experimental results were compared with both the analytical and finite element solutions. Extensive optical and scanning electron microscopic examinations were carried out for identifying the fracture behavior and failure mechanisms of both the notched and notched specimens. The stress concentration factors (SCF) determined by analytical method overpredicted the experimental results. But the numerical solution underpredicted the experimental SCF. Stress concentration factors are shown to increase with enlarged hole size and the effects of ply orientations on stress concentration factors are observed to be negligible. In all the cases, the crack initiated at the notch edge and propagated along the width towards the edge of the specimens.

Discrimination Factors and Incorporation Rates for Organic Matrix in Shark Teeth Based on a Captive Feeding Study.

PubMed

Zeichner, S S; Colman, A S; Koch, P L; Polo-Silva, C; Galván-Magaña, F; Kim, S L

Sharks migrate annually over large distances and occupy a wide variety of habitats, complicating analysis of lifestyle and diet. A biogeochemical technique often used to reconstruct shark diet and environment preferences is stable isotope analysis, which is minimally invasive and integrates through time and space. There are previous studies that focus on isotopic analysis of shark soft tissues, but there are limited applications to shark teeth. However, shark teeth offer an advantage of multiple ecological snapshots and minimum invasiveness during removal because of their distinct conveyor belt tooth replacement system. In this study, we analyze δ 13 C and δ 15 N values of the organic matrix in leopard shark teeth (Triakis semifasciata) from a captive experiment and report discrimination factors as well as incorporation rates. We found differences in tooth discrimination factors for individuals fed different prey sources (mean ± SD; Δ 13 C squid = 4.7‰ ± 0.5‰, Δ 13 C tilapia = 3.1‰ ± 1.0‰, Δ 15 N squid = 2.0‰ ± 0.7‰, Δ 15 N tilapia = 2.8‰ ± 0.6‰). In addition, these values differed from previously published discrimination factors for plasma, red blood cells, and muscle of the same leopard sharks. Incorporation rates of shark teeth were similar for carbon and nitrogen (mean ± SE; λ C = 0.021 ± 0.009, λ N = 0.024 ± 0.007) and comparable to those of plasma. We emphasize the difference in biological parameters on the basis of tissue substrate and diet items to interpret stable isotope data and apply our results to stable isotope values from blue shark (Prionace glauca) teeth to illustrate the importance of biological parameters to interpret the complex ecology of a migratory shark.

A real time spectrum to dose conversion system

NASA Technical Reports Server (NTRS)

Farmer, B. J.; Johnson, J. H.; Bagwell, R. G.

1972-01-01

A system has been developed which permits the determination of dose in real time or near real time directly from the pulse-height output of a radiation spectrometer. The technique involves the use of the resolution matrix of a spectrometer, the radiation energy-to-dose conversion function, and the geometrical factors, although the order of matrix operations is reversed. The new technique yields a result which is mathematically identical to the standard method while requiring no matrix manipulations or resolution matrix storage in the remote computer. It utilizes only a single function for each type dose required and each geometric factor involved.

Factors associated with continuance commitment to FAA matrix teams.

DOT National Transportation Integrated Search

1993-11-01

Several organizations within the FAA employ matrix teams to achieve cross-functional coordination. Matrix team members typically represent different organizational functions required for project accomplishment (e.g., research and development, enginee...

Matrix Theory of Small Oscillations

ERIC Educational Resources Information Center

Chavda, L. K.

1978-01-01

A complete matrix formulation of the theory of small oscillations is presented. Simple analytic solutions involving matrix functions are found which clearly exhibit the transients, the damping factors, the Breit-Wigner form for resonances, etc. (BB)

Proposed framework for thermomechanical life modeling of metal matrix composites

NASA Technical Reports Server (NTRS)

Halford, Gary R.; Lerch, Bradley A.; Saltsman, James F.

1993-01-01

The framework of a mechanics of materials model is proposed for thermomechanical fatigue (TMF) life prediction of unidirectional, continuous-fiber metal matrix composites (MMC's). Axially loaded MMC test samples are analyzed as structural components whose fatigue lives are governed by local stress-strain conditions resulting from combined interactions of the matrix, interfacial layer, and fiber constituents. The metallic matrix is identified as the vehicle for tracking fatigue crack initiation and propagation. The proposed framework has three major elements. First, TMF flow and failure characteristics of in situ matrix material are approximated from tests of unreinforced matrix material, and matrix TMF life prediction equations are numerically calibrated. The macrocrack initiation fatigue life of the matrix material is divided into microcrack initiation and microcrack propagation phases. Second, the influencing factors created by the presence of fibers and interfaces are analyzed, characterized, and documented in equation form. Some of the influences act on the microcrack initiation portion of the matrix fatigue life, others on the microcrack propagation life, while some affect both. Influencing factors include coefficient of thermal expansion mismatch strains, residual (mean) stresses, multiaxial stress states, off-axis fibers, internal stress concentrations, multiple initiation sites, nonuniform fiber spacing, fiber debonding, interfacial layers and cracking, fractured fibers, fiber deflections of crack fronts, fiber bridging of matrix cracks, and internal oxidation along internal interfaces. Equations exist for some, but not all, of the currently identified influencing factors. The third element is the inclusion of overriding influences such as maximum tensile strain limits of brittle fibers that could cause local fractures and ensuing catastrophic failure of surrounding matrix material. Some experimental data exist for assessing the plausibility of the proposed framework.

Positive semidefinite tensor factorizations of the two-electron integral matrix for low-scaling ab initio electronic structure.

PubMed

Hoy, Erik P; Mazziotti, David A

2015-08-14

Tensor factorization of the 2-electron integral matrix is a well-known technique for reducing the computational scaling of ab initio electronic structure methods toward that of Hartree-Fock and density functional theories. The simplest factorization that maintains the positive semidefinite character of the 2-electron integral matrix is the Cholesky factorization. In this paper, we introduce a family of positive semidefinite factorizations that generalize the Cholesky factorization. Using an implementation of the factorization within the parametric 2-RDM method [D. A. Mazziotti, Phys. Rev. Lett. 101, 253002 (2008)], we study several inorganic molecules, alkane chains, and potential energy curves and find that this generalized factorization retains the accuracy and size extensivity of the Cholesky factorization, even in the presence of multi-reference correlation. The generalized family of positive semidefinite factorizations has potential applications to low-scaling ab initio electronic structure methods that treat electron correlation with a computational cost approaching that of the Hartree-Fock method or density functional theory.

Matrix completion by deep matrix factorization.

PubMed

Fan, Jicong; Cheng, Jieyu

2018-02-01

Conventional methods of matrix completion are linear methods that are not effective in handling data of nonlinear structures. Recently a few researchers attempted to incorporate nonlinear techniques into matrix completion but there still exists considerable limitations. In this paper, a novel method called deep matrix factorization (DMF) is proposed for nonlinear matrix completion. Different from conventional matrix completion methods that are based on linear latent variable models, DMF is on the basis of a nonlinear latent variable model. DMF is formulated as a deep-structure neural network, in which the inputs are the low-dimensional unknown latent variables and the outputs are the partially observed variables. In DMF, the inputs and the parameters of the multilayer neural network are simultaneously optimized to minimize the reconstruction errors for the observed entries. Then the missing entries can be readily recovered by propagating the latent variables to the output layer. DMF is compared with state-of-the-art methods of linear and nonlinear matrix completion in the tasks of toy matrix completion, image inpainting and collaborative filtering. The experimental results verify that DMF is able to provide higher matrix completion accuracy than existing methods do and DMF is applicable to large matrices. Copyright © 2017 Elsevier Ltd. All rights reserved.

Random matrix theory filters in portfolio optimisation: A stability and risk assessment

NASA Astrophysics Data System (ADS)

Daly, J.; Crane, M.; Ruskin, H. J.

2008-07-01

Random matrix theory (RMT) filters, applied to covariance matrices of financial returns, have recently been shown to offer improvements to the optimisation of stock portfolios. This paper studies the effect of three RMT filters on the realised portfolio risk, and on the stability of the filtered covariance matrix, using bootstrap analysis and out-of-sample testing. We propose an extension to an existing RMT filter, (based on Krzanowski stability), which is observed to reduce risk and increase stability, when compared to other RMT filters tested. We also study a scheme for filtering the covariance matrix directly, as opposed to the standard method of filtering correlation, where the latter is found to lower the realised risk, on average, by up to 6.7%. We consider both equally and exponentially weighted covariance matrices in our analysis, and observe that the overall best method out-of-sample was that of the exponentially weighted covariance, with our Krzanowski stability-based filter applied to the correlation matrix. We also find that the optimal out-of-sample decay factors, for both filtered and unfiltered forecasts, were higher than those suggested by Riskmetrics [J.P. Morgan, Reuters, Riskmetrics technical document, Technical Report, 1996. http://www.riskmetrics.com/techdoc.html], with those for the latter approaching a value of α=1. In conclusion, RMT filtering reduced the realised risk, on average, and in the majority of cases when tested out-of-sample, but increased the realised risk on a marked number of individual days-in some cases more than doubling it.

Engineered living blood vessels: functional endothelia generated from human umbilical cord-derived progenitors.

PubMed

Schmidt, Dörthe; Asmis, Lars M; Odermatt, Bernhard; Kelm, Jens; Breymann, Christian; Gössi, Matthias; Genoni, Michele; Zund, Gregor; Hoerstrup, Simon P

2006-10-01

Tissue-engineered living blood vessels (TEBV) with growth capacity represent a promising new option for the repair of congenital malformations. We investigate the functionality of TEBV with endothelia generated from human umbilical cord blood-derived endothelial progenitor cells. Tissue-engineered living blood vessels were generated from human umbilical cord-derived myofibroblasts seeded on biodegradable vascular scaffolds, followed by endothelialization with differentiated cord blood-derived endothelial progenitor cells. During in vitro maturation the TEBV were exposed to physiologic conditioning in a flow bioreactor. For functional assessment, a subgroup of TEBV was stimulated with tumor necrosis factor-alpha. Control vessels endothelialized with standard vascular endothelial cells were treated in parallel. Analysis of the TEBV included histology, immunohistochemistry, biochemistry (extracellular matrix analysis, DNA), and biomechanical testing. Endothelia were analyzed by flow cytometry and immunohistochemistry (CD31, von Willebrand factor, thrombomodulin, tissue factor, endothelial nitric oxide synthase). Histologically, a three-layered tissue organization of the TEBV analogous to native vessels was observed, and biochemistry revealed the major matrix constituents (collagen, proteoglycans) of blood vessels. Biomechanical properties (Young's modulus, 2.03 +/- 0.65 MPa) showed profiles resembling those of native tissue. Endothelial progenitor cells expressed typical endothelial cell markers CD31, von Willebrand factor, and endothelial nitric oxide synthase comparable to standard vascular endothelial cells. Stimulation with tumor necrosis factor-alpha resulted in physiologic upregulation of tissue factor and downregulation of thrombomodulin expression. These results indicate that TEBV with tissue architecture and functional endothelia similar to native blood vessels can be successfully generated from human umbilical cord progenitor cells. Thus, blood-derived progenitor cells obtained before or at birth may enable the clinical realization of tissue engineering constructs for pediatric applications.

SPECIAL ISSUE ON OPTICAL PROCESSING OF INFORMATION: Analysis of the precision parameters of an optoelectronic vector-matrix processor of digital information

NASA Astrophysics Data System (ADS)

Odinokov, S. B.; Petrov, A. V.

1995-10-01

Mathematical models of components of a vector-matrix optoelectronic multiplier are considered. Perturbing factors influencing a real optoelectronic system — noise and errors of radiation sources and detectors, nonlinearity of an analogue—digital converter, nonideal optical systems — are taken into account. Analytic expressions are obtained for relating the precision of such a multiplier to the probability of an error amounting to one bit, to the parameters describing the quality of the multiplier components, and to the quality of the optical system of the processor. Various methods of increasing the dynamic range of a multiplier are considered at the technical systems level.

Partial Least Squares Regression Models for the Analysis of Kinase Signaling.

PubMed

Bourgeois, Danielle L; Kreeger, Pamela K

2017-01-01

Partial least squares regression (PLSR) is a data-driven modeling approach that can be used to analyze multivariate relationships between kinase networks and cellular decisions or patient outcomes. In PLSR, a linear model relating an X matrix of dependent variables and a Y matrix of independent variables is generated by extracting the factors with the strongest covariation. While the identified relationship is correlative, PLSR models can be used to generate quantitative predictions for new conditions or perturbations to the network, allowing for mechanisms to be identified. This chapter will provide a brief explanation of PLSR and provide an instructive example to demonstrate the use of PLSR to analyze kinase signaling.

Sparse nonnegative matrix factorization with ℓ0-constraints

PubMed Central

Peharz, Robert; Pernkopf, Franz

2012-01-01

Although nonnegative matrix factorization (NMF) favors a sparse and part-based representation of nonnegative data, there is no guarantee for this behavior. Several authors proposed NMF methods which enforce sparseness by constraining or penalizing the ℓ1-norm of the factor matrices. On the other hand, little work has been done using a more natural sparseness measure, the ℓ0-pseudo-norm. In this paper, we propose a framework for approximate NMF which constrains the ℓ0-norm of the basis matrix, or the coefficient matrix, respectively. For this purpose, techniques for unconstrained NMF can be easily incorporated, such as multiplicative update rules, or the alternating nonnegative least-squares scheme. In experiments we demonstrate the benefits of our methods, which compare to, or outperform existing approaches. PMID:22505792

[Application of risk-based approach for determination of critical factors in technology transfer of production of medicinal products].

PubMed

Beregovykh, V V; Spitskiy, O R

2014-01-01

Risk-based approach is used for examination of impact of different factors on quality of medicinal products in technology transfer. A general diagram is offered for risk analysis execution in technology transfer from pharmaceutical development to production. When transferring technology to full- scale commercial production it is necessary to investigate and simulate production process application beforehand in new real conditions. The manufacturing process is the core factorfor risk analysis having the most impact on quality attributes of a medicinal product. Further importantfactors are linked to materials and products to be handled and manufacturing environmental conditions such as premises, equipment and personnel. Usage of risk-based approach in designing of multipurpose production facility of medicinal products is shown where quantitative risk analysis tool RAMM (Risk Analysis and Mitigation Matrix) was applied.

Enhanced osteoprogenitor elongated collagen fiber matrix formation by bioactive glass ionic silicon dependent on Sp7 (osterix) transcription.

PubMed

Varanasi, Venu G; Odatsu, Tetsurou; Bishop, Timothy; Chang, Joyce; Owyoung, Jeremy; Loomer, Peter M

2016-10-01

Bioactive glasses release ions, those enhance osteoblast collagen matrix synthesis and osteogenic marker expression during bone healing. Collagen matrix density and osteogenic marker expression depend on osteogenic transcription factors, (e.g., Osterix (OSX)). We hypothesize that enhanced expression and formation of collagen by Si(4+) depends on enhanced expression of OSX transcription. Experimental bioactive glass (6P53-b) and commercial Bioglass(TM) (45S5) were dissolved in basal medium to make glass conditioned medium (GCM). ICP-MS analysis was used to measure bioactive glass ion release rates. MC3T3-E1 cells were cultured for 20 days, and gene expression and extracellular matrix collagen formation was analyzed. In a separate study, siRNA was used to determine the effect of OSX knockdown on impacting the effect of Si(4+) on osteogenic markers and matrix collagen formation. Each bioactive glass exhibited similar ion release rates for all ions, except Mg(2+) released by 6P53-b. Gene expression results showed that GCM markedly enhanced many osteogenic markers, and 45S5 GCM showed higher levels of expression and collagen matrix fiber bundle density than 6P53-b GCM. Upon knockdown of OSX transcription, collagen type 5, alkaline phosphatase, and matrix density were not enhanced as compared to wild type cells. This study illustrates that the enhancement of elongated collagen fiber matrix formation by Si(±) depends on OSX transcription. © 2016 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 104A: 2604-2615, 2016. © 2016 Wiley Periodicals, Inc.

A Literature Review and Experimental Plan for Research on the Display of Information on Matrix-Addressable Displays.

DTIC Science & Technology

1987-02-01

Factors Laboratory, Department of Industria AREA 6 WORK UNIT NUAE1 Engineering and Operations Research, Virginia Pol - technic Institute & State Univ...Symbolic Research 105 Experiment 14: Multichromatic Optimum Character Symbolic 105 Summary 105 Quality Metrics Analysis 105 REFERENCES 107 ANNOTATED...17.52 12.26 9.43 7.66 6.45 5.57 An analysis of variance was performed on accuracy and response time data. For accuracy data there was a significant

Matrix Assisted Laser Desorption Ionization Mass Spectrometric Analysis of Bacillus anthracis: From Fingerprint Analysis of the Bacterium to Quantification of its Toxins in Clinical Samples

NASA Astrophysics Data System (ADS)

Woolfitt, Adrian R.; Boyer, Anne E.; Quinn, Conrad P.; Hoffmaster, Alex R.; Kozel, Thomas R.; de, Barun K.; Gallegos, Maribel; Moura, Hercules; Pirkle, James L.; Barr, John R.

A range of mass spectrometry-based techniques have been used to identify, characterize and differentiate Bacillus anthracis, both in culture for forensic applications and for diagnosis during infection. This range of techniques could usefully be considered to exist as a continuum, based on the degrees of specificity involved. We show two examples here, a whole-organism fingerprinting method and a high-specificity assay for one unique protein, anthrax lethal factor.

A Regional Assessment of Marine Vessel PM2.5 Impacts in the U.S. Pacific Northwest Using a Receptor Based Source Apportionment Method

EPA Science Inventory

This work reports the results of a regional receptor-based source apportionment analysis using the Positive Matrix Factorization (PMF) model on chemically speciated PM2.5 data from 36 urban and rural monitoring sites within the U.S. Pacific Northwest. The approach taken is to mo...

Labor Markets: Segments and Shelters. Conservation of Human Resources Series.

ERIC Educational Resources Information Center

Freedman, Marcia; Maclachlan, Gretchen

Utilizing Federal census data from 1960 and 1970, this study provides (1) an overview of the job structure of the entire American economy as of 1970, by arranging the jobs in a new occupational-industrial matrix and ranking them in terms of average annual earnings; and (2) an analysis of the structural factors that distinguish the better from the…

Investigation of noise in gear transmissions by the method of mathematical smoothing of experiments

NASA Technical Reports Server (NTRS)

Sheftel, B. T.; Lipskiy, G. K.; Ananov, P. P.; Chernenko, I. K.

1973-01-01

A rotatable central component smoothing method is used to analyze rotating gear noise spectra. A matrix is formulated in which the randomized rows correspond to various tests and the columns to factor values. Canonical analysis of the obtained regression equation permits the calculation of optimal speed and load at a previous assigned noise level.

Thalidomide Accelerates the Degradation of Extracellular Matrix in Rat Hepatic Cirrhosis via Down-Regulation of Transforming Growth Factor-β1

PubMed Central

Meng, Qingshun; Liu, Jie; Wang, Chuanfang

2015-01-01

Purpose The degradation of the extracellular matrix has been shown to play an important role in the treatment of hepatic cirrhosis. In this study, the effect of thalidomide on the degradation of extracellular matrix was evaluated in a rat model of hepatic cirrhosis. Materials and Methods Cirrhosis was induced in Wistar rats by intraperitoneal injection of carbon tetrachloride (CCl4) three times weekly for 8 weeks. Then CCl4 was discontinued and thalidomide (100 mg/kg) or its vehicle was administered daily by gavage for 6 weeks. Serum hyaluronic acid, laminin, procollagen type III, and collagen type IV were examined by using a radioimmunoassay. Matrix metalloproteinase-13 (MMP-13), tissue inhibitor of metalloproteinase-1 (TIMP-1), and α-smooth muscle actin (α-SMA) protein in the liver, transforming growth factor β1 (TGF-β1) protein in cytoplasm by using immunohistochemistry and Western blot analysis, and MMP-13, TIMP-1, and TGF-β1 mRNA levels in the liver were studied using reverse transcriptase polymerase chain reaction. Results Liver histopathology was significantly better in rats given thalidomide than in the untreated model group. The levels of TIMP-1 and TGF-β1 mRNA and protein expressions were decreased significantly and MMP-13 mRNA and protein in the liver were significantly elevated in the thalidomide-treated group. Conclusion Thalidomide may exert its effects on the regulation of MMP-13 and TIMP-1 via inhibition of the TGF-β1 signaling pathway, which enhances the degradation of extracellular matrix and accelerates the regression of hepatic cirrhosis in rats. PMID:26446639

Second derivative time integration methods for discontinuous Galerkin solutions of unsteady compressible flows

NASA Astrophysics Data System (ADS)

Nigro, A.; De Bartolo, C.; Crivellini, A.; Bassi, F.

2017-12-01

In this paper we investigate the possibility of using the high-order accurate A (α) -stable Second Derivative (SD) schemes proposed by Enright for the implicit time integration of the Discontinuous Galerkin (DG) space-discretized Navier-Stokes equations. These multistep schemes are A-stable up to fourth-order, but their use results in a system matrix difficult to compute. Furthermore, the evaluation of the nonlinear function is computationally very demanding. We propose here a Matrix-Free (MF) implementation of Enright schemes that allows to obtain a method without the costs of forming, storing and factorizing the system matrix, which is much less computationally expensive than its matrix-explicit counterpart, and which performs competitively with other implicit schemes, such as the Modified Extended Backward Differentiation Formulae (MEBDF). The algorithm makes use of the preconditioned GMRES algorithm for solving the linear system of equations. The preconditioner is based on the ILU(0) factorization of an approximated but computationally cheaper form of the system matrix, and it has been reused for several time steps to improve the efficiency of the MF Newton-Krylov solver. We additionally employ a polynomial extrapolation technique to compute an accurate initial guess to the implicit nonlinear system. The stability properties of SD schemes have been analyzed by solving a linear model problem. For the analysis on the Navier-Stokes equations, two-dimensional inviscid and viscous test cases, both with a known analytical solution, are solved to assess the accuracy properties of the proposed time integration method for nonlinear autonomous and non-autonomous systems, respectively. The performance of the SD algorithm is compared with the ones obtained by using an MF-MEBDF solver, in order to evaluate its effectiveness, identifying its limitations and suggesting possible further improvements.

Study on invadopodia formation for lung carcinoma invasion with a microfluidic 3D culture device.

PubMed

Wang, Shanshan; Li, Encheng; Gao, Yanghui; Wang, Yan; Guo, Zhe; He, Jiarui; Zhang, Jianing; Gao, Zhancheng; Wang, Qi

2013-01-01

Invadopodia or invasive feet, which are actin-rich membrane protrusions with matrix degradation activity formed by invasive cancer cells, are a key determinant in the malignant invasive progression of tumors and represent an important target for cancer therapies. In this work, we presented a microfluidic 3D culture device with continuous supplement of fresh media via a syringe pump. The device mimicked tumor microenvironment in vivo and could be used to assay invadopodia formation and to study the mechanism of human lung cancer invasion. With this device, we investigated the effects of epidermal growth factor (EGF) and matrix metalloproteinase (MMP) inhibitor, GM6001 on invadopodia formation by human non-small cell lung cancer cell line A549 in 3D matrix model. This device was composed of three units that were capable of achieving the assays on one control group and two experimental groups' cells, which were simultaneously pretreated with EGF or GM6001 in parallel. Immunofluorescence analysis of invadopodia formation and extracellular matrix degradation was conducted using confocal imaging system. We observed that EGF promoted invadopodia formation by A549 cells in 3D matrix and that GM6001 inhibited the process. These results demonstrated that epidermal growth factor receptor (EGFR) signaling played a significant role in invadopodia formation and related ECM degradation activity. Meanwhile, it was suggested that MMP inhibitor (GM6001) might be a powerful therapeutic agent targeting invadopodia formation in tumor invasion. This work clearly demonstrated that the microfluidic-based 3D culture device provided an applicable platform for elucidating the mechanism of cancer invasion and could be used in testing other anti-invasion agents.

ICAN: Integrated composites analyzer

NASA Technical Reports Server (NTRS)

Murthy, P. L. N.; Chamis, C. C.

1984-01-01

The ICAN computer program performs all the essential aspects of mechanics/analysis/design of multilayered fiber composites. Modular, open-ended and user friendly, the program can handle a variety of composite systems having one type of fiber and one matrix as constituents as well as intraply and interply hybrid composite systems. It can also simulate isotropic layers by considering a primary composite system with negligible fiber volume content. This feature is specifically useful in modeling thin interply matrix layers. Hygrothermal conditions and various combinations of in-plane and bending loads can also be considered. Usage of this code is illustrated with a sample input and the generated output. Some key features of output are stress concentration factors around a circular hole, locations of probable delamination, a summary of the laminate failure stress analysis, free edge stresses, microstresses and ply stress/strain influence coefficients. These features make ICAN a powerful, cost-effective tool to analyze/design fiber composite structures and components.

Coherent states, 6j symbols and properties of the next to leading order asymptotic expansions

NASA Astrophysics Data System (ADS)

Kamiński, Wojciech; Steinhaus, Sebastian

2013-12-01

We present the first complete derivation of the well-known asymptotic expansion of the SU(2) 6j symbol using a coherent state approach, in particular we succeed in computing the determinant of the Hessian matrix. To do so, we smear the coherent states and perform a partial stationary point analysis with respect to the smearing parameters. This allows us to transform the variables from group elements to dihedral angles of a tetrahedron resulting in an effective action, which coincides with the action of first order Regge calculus associated to a tetrahedron. To perform the remaining stationary point analysis, we compute its Hessian matrix and obtain the correct measure factor. Furthermore, we expand the discussion of the asymptotic formula to next to leading order terms, prove some of their properties and derive a recursion relation for the full 6j symbol.

Fluorescence excitation-emission matrix (EEM) spectroscopy and cavity ring-down (CRD) absorption spectroscopy of oil-contaminated jet fuel using fiber-optic probes.

PubMed

Omrani, Hengameh; Barnes, Jack A; Dudelzak, Alexander E; Loock, Hans-Peter; Waechter, Helen

2012-06-21

Excitation emission matrix (EEM) and cavity ring-down (CRD) spectral signatures have been used to detect and quantitatively assess contamination of jet fuels with aero-turbine lubricating oil. The EEM spectrometer has been fiber-coupled to permit in situ measurements of jet turbine oil contamination of jet fuel. Parallel Factor (PARAFAC) analysis as well as Principal Component Analysis and Regression (PCA/PCR) were used to quantify oil contamination in a range from the limit of detection (10 ppm) to 1000 ppm. Fiber-loop cavity ring-down spectroscopy using a pulsed 355 nm laser was used to quantify the oil contamination in the range of 400 ppm to 100,000 ppm. Both methods in combination therefore permit the detection of oil contamination with a linear dynamic range of about 10,000.

Liarozole inhibits transforming growth factor-β3–mediated extracellular matrix formation in human three-dimensional leiomyoma cultures

PubMed Central

Levy, Gary; Malik, Minnie; Britten, Joy; Gilden, Melissa; Segars, James; Catherino, William H.

2014-01-01

Objective To investigate the impact of liarozole on transforming growth factor-β3 (TGF-β3) expression, TGF-β3 controlled profibrotic cytokines, and extracellular matrix formation in a three-dimensional (3D) leiomyoma model system. Design Molecular and immunohistochemical analysis in a cell line evaluated in a three-dimensional culture. Setting Laboratory study. Patient(s) None. Intervention(s) Treatment of leiomyoma and myometrial cells with liarozole and TGF-β3 in a three-dimensional culture system. Main Outcome Measure(s) Quantitative real-time reverse-transcriptase polymerase chain reaction and Western blotting to assess fold gene and protein expression of TGF-β3 and TGF-β3 regulated fibrotic cytokines: collagen 1A1 (COL1A1), fibronectin, and versican before and after treatment with liarozole, and confirmatory immunohistochemical stains of treated three-dimensional cultures. Result(s) Both TGF-β3 gene and protein expression were elevated in leiomyoma cells compared with myometrium in two-dimensional and 3D cultures. Treatment with liarozole decreased TGF-β3 gene and protein expression. Extracellular matrix components versican, COL1A1, and fibronectin were also decreased by liarozole treatment in 3D cultures. Treatment of 3D cultures with TGF-β3 increased gene expression and protein production of COL1A1, fibronectin, and versican. Conclusion(s) Liarozole decreased TGF-β3 and TGF-β3–mediated extracellular matrix expression in a 3D uterine leiomyoma culture system. PMID:24825427

Human kidney stone matrix: Latent potential to restrain COM induced cytotoxicity and inflammatory response.

PubMed

Narula, Shifa; Tandon, Simran; Baligar, Prakash; Singh, Shrawan Kumar; Tandon, Chanderdeep

2017-12-25

Kidney stone disease is a multi-factorial disorder resulting from the interplay of various risk factors including lifestyle, environment and genetics along with metabolic activities inside the body. However, it is difficult to determine how these factors converge to promote stone disease. Extensive investigations of kidney stone composition at the molecular level have been carried out however; its impact on the complex mechanism of stone formation is still obscure. Hence, an in vitro study was designed to investigate the attenuation of calcium oxalate toxicity by human kidney stone matrix proteins on NRK-52E cells using flowcytometry, Western blotting, RT-PCR and immunofluorescence assays. Morphological alterations in cell-crystal interaction were assessed using scanning electron microscopy. Microscopic studies showed profound impairment of COM crystal structure as a consequence of protein-crystal interactions. RT-PCR analysis and immunocytochemistry of NRK-52E cells revealed the up-regulation of inflammatory and stress biomarkers OPN and HSP-70, respectively, in response to COM toxicity; which diminished significantly in the presence of kidney stone matrix proteins. The results of present study propose that the mechanism undertaken by matrix proteins to attenuate COM induced cytotoxicity could be attributed to the modulation of crystal structure, which subsequently restraint the inflammatory response and apoptotic cell death. The inference drawn through this study could provide better understanding of the intricate process of kidney stone formation. Copyright © 2017 Elsevier B.V. All rights reserved.

New Factorization Techniques and Fast Serial and Parrallel Algorithms for Operational Space Control of Robot Manipulators

NASA Technical Reports Server (NTRS)

Fijany, Amir; Djouani, Karim; Fried, George; Pontnau, Jean

1997-01-01

In this paper a new factorization technique for computation of inverse of mass matrix, and the operational space mass matrix, as arising in implementation of the operational space control scheme, is presented.

Optical factors determined by the T-matrix method in turbidity measurement of absolute coagulation rate constants.

PubMed

Xu, Shenghua; Liu, Jie; Sun, Zhiwei

2006-12-01

Turbidity measurement for the absolute coagulation rate constants of suspensions has been extensively adopted because of its simplicity and easy implementation. A key factor in deriving the rate constant from experimental data is how to theoretically evaluate the so-called optical factor involved in calculating the extinction cross section of doublets formed during aggregation. In a previous paper, we have shown that compared with other theoretical approaches, the T-matrix method provides a robust solution to this problem and is effective in extending the applicability range of the turbidity methodology, as well as increasing measurement accuracy. This paper will provide a more comprehensive discussion of the physical insight for using the T-matrix method in turbidity measurement and associated technical details. In particular, the importance of ensuring the correct value for the refractive indices for colloidal particles and the surrounding medium used in the calculation is addressed, because the indices generally vary with the wavelength of the incident light. The comparison of calculated results with experiments shows that the T-matrix method can correctly calculate optical factors even for large particles, whereas other existing theories cannot. In addition, the data of the optical factor calculated by the T-matrix method for a range of particle radii and incident light wavelengths are listed.

A symmetrical subtraction combined with interpolated values for eliminating scattering from fluorescence EEM data.

PubMed

Xu, Jing; Liu, Xiaofei; Wang, Yutian

2016-08-05

Parallel factor analysis is a widely used method to extract qualitative and quantitative information of the analyte of interest from fluorescence emission-excitation matrix containing unknown components. Big amplitude of scattering will influence the results of parallel factor analysis. Many methods of eliminating scattering have been proposed. Each of these methods has its advantages and disadvantages. The combination of symmetrical subtraction and interpolated values has been discussed. The combination refers to both the combination of results and the combination of methods. Nine methods were used for comparison. The results show the combination of results can make a better concentration prediction for all the components. Copyright © 2016 Elsevier B.V. All rights reserved.

Analysis of facial motion patterns during speech using a matrix factorization algorithm

PubMed Central

Lucero, Jorge C.; Munhall, Kevin G.

2008-01-01

This paper presents an analysis of facial motion during speech to identify linearly independent kinematic regions. The data consists of three-dimensional displacement records of a set of markers located on a subject’s face while producing speech. A QR factorization with column pivoting algorithm selects a subset of markers with independent motion patterns. The subset is used as a basis to fit the motion of the other facial markers, which determines facial regions of influence of each of the linearly independent markers. Those regions constitute kinematic “eigenregions” whose combined motion produces the total motion of the face. Facial animations may be generated by driving the independent markers with collected displacement records. PMID:19062866

Estimating Depolarization with the Jones Matrix Quality Factor

NASA Astrophysics Data System (ADS)

Hilfiker, James N.; Hale, Jeffrey S.; Herzinger, Craig M.; Tiwald, Tom; Hong, Nina; Schöche, Stefan; Arwin, Hans

2017-11-01

Mueller matrix (MM) measurements offer the ability to quantify the depolarization capability of a sample. Depolarization can be estimated using terms such as the depolarization index or the average degree of polarization. However, these calculations require measurement of the complete MM. We propose an alternate depolarization metric, termed the Jones matrix quality factor, QJM, which does not require the complete MM. This metric provides a measure of how close, in a least-squares sense, a Jones matrix can be found to the measured Mueller matrix. We demonstrate and compare the use of QJM to other traditional calculations of depolarization for both isotropic and anisotropic depolarizing samples; including non-uniform coatings, anisotropic crystal substrates, and beetle cuticles that exhibit both depolarization and circular diattenuation.

Acellular fetal bovine dermal matrix for treatment of chronic ulcerations of the midfoot associated with Charcot neuroarthropathy.

PubMed

Kavros, Steven J

2012-08-01

Gross deformity of the foot in Charcot neuroarthropathy can lead to collapse and subsequent ulceration, infection, amputation, or premature death. This study evaluated healing of midfoot ulcerations of Charcot neuroarthropathy using PriMatrix, a novel acellular fetal bovine dermal matrix. In this retrospective analysis, 20 patients with ulcerations of the midfoot associated with Charcot neuroarthropathy were treated with either PriMatrix in addition to standard wound care (PriMatrix group,n = 12) or standard wound care alone (control group, n = 8). All patients had chronic, nonhealing foot ulcerations of at least 2250 mm(3) for a minimum of 30 days duration. All foot ulcerations were full thickness with subcutaneous involvement. Ankle brachial index ≥0.90 and/or transcutaneous oximetry (TcPo(2)) ≥40 mm Hg at the periulcer site was necessary for inclusion. Patients were excluded if they had acute or chronic osteomyelitis of the foot. Demography, risk factors, baseline severity of Charcot neuroarthropathy, and wound volume (control 4078 mm(3), PriMatrix 3737.5 mm(3), P = nonsignificant) were similar between treatment groups. Mean time to healing in the PriMatrix group (116 days, 95% CI = 109-123) was significantly shorter than in the control group (180 days, 95% confidence interval [CI] = 171-188); P < .0001. A significantly faster rate of healing was observed with PriMatrix (87.9 mm(3)/wk, 95% CI = 115.2% to 60.6%) compared with control (59.0 mm(3)/wk, 95% CI = 72.8% to 45.3%); P < .0001). The significantly faster rate of healing and steeper slope of volume reduction in the PriMatrix group warrants further investigation into its effects on healing of neuropathic ulcerations and potential limb salvage.

Pure endmember extraction using robust kernel archetypoid analysis for hyperspectral imagery

NASA Astrophysics Data System (ADS)

Sun, Weiwei; Yang, Gang; Wu, Ke; Li, Weiyue; Zhang, Dianfa

2017-09-01

A robust kernel archetypoid analysis (RKADA) method is proposed to extract pure endmembers from hyperspectral imagery (HSI). The RKADA assumes that each pixel is a sparse linear mixture of all endmembers and each endmember corresponds to a real pixel in the image scene. First, it improves the re8gular archetypal analysis with a new binary sparse constraint, and the adoption of the kernel function constructs the principal convex hull in an infinite Hilbert space and enlarges the divergences between pairwise pixels. Second, the RKADA transfers the pure endmember extraction problem into an optimization problem by minimizing residual errors with the Huber loss function. The Huber loss function reduces the effects from big noises and outliers in the convergence procedure of RKADA and enhances the robustness of the optimization function. Third, the random kernel sinks for fast kernel matrix approximation and the two-stage algorithm for optimizing initial pure endmembers are utilized to improve its computational efficiency in realistic implementations of RKADA, respectively. The optimization equation of RKADA is solved by using the block coordinate descend scheme and the desired pure endmembers are finally obtained. Six state-of-the-art pure endmember extraction methods are employed to make comparisons with the RKADA on both synthetic and real Cuprite HSI datasets, including three geometrical algorithms vertex component analysis (VCA), alternative volume maximization (AVMAX) and orthogonal subspace projection (OSP), and three matrix factorization algorithms the preconditioning for successive projection algorithm (PreSPA), hierarchical clustering based on rank-two nonnegative matrix factorization (H2NMF) and self-dictionary multiple measurement vector (SDMMV). Experimental results show that the RKADA outperforms all the six methods in terms of spectral angle distance (SAD) and root-mean-square-error (RMSE). Moreover, the RKADA has short computational times in offline operations and shows significant improvement in identifying pure endmembers for ground objects with smaller spectrum differences. Therefore, the RKADA could be an alternative for pure endmember extraction from hyperspectral images.

Inelastic deformation of metal matrix composites

NASA Technical Reports Server (NTRS)

Lissenden, C. J.; Herakovich, C. T.; Pindera, M-J.

1993-01-01

A theoretical model capable of predicting the thermomechanical response of continuously reinforced metal matrix composite laminates subjected to multiaxial loading was developed. A micromechanical model is used in conjunction with nonlinear lamination theory to determine inelastic laminae response. Matrix viscoplasticity, residual stresses, and damage to the fiber/matrix interfacial zone are explicitly included in the model. The representative cell of the micromechanical model is considered to be in a state of generalized plane strain, enabling a quasi two-dimensional analysis to be performed. Constant strain finite elements are formulated with elastic-viscoplastic constitutive equations. Interfacial debonding is incorporated into the model through interface elements based on the interfacial debonding theory originally presented by Needleman, and modified by Tvergaard. Nonlinear interfacial constitutive equations relate interfacial tractions to displacement discontinuities at the interface. Theoretical predictions are compared with the results of an experimental program conducted on silicon carbide/titanium (SiC/Ti) unidirectional, (O4), and angle-ply, (+34)(sub s), tubular specimens. Multiaxial loading included increments of axial tension, compression, torque, and internal pressure. Loadings were chosen in an effort to distinguish inelastic deformation due to damage from matrix plasticity and separate time-dependent effects from time-independent effects. Results show that fiber/matrix debonding is nonuniform throughout the composite and is a major factor in the effective response. Also, significant creep behavior occurs at relatively low applied stress levels at room temperature.

Study on the Algorithm of Judgment Matrix in Analytic Hierarchy Process

NASA Astrophysics Data System (ADS)

Lu, Zhiyong; Qin, Futong; Jin, Yican

2017-10-01

A new algorithm is proposed for the non-consistent judgment matrix in AHP. A primary judgment matrix is generated firstly through pre-ordering the targeted factor set, and a compared matrix is built through the top integral function. Then a relative error matrix is created by comparing the compared matrix with the primary judgment matrix which is regulated under the control of the relative error matrix and the dissimilar degree of the matrix step by step. Lastly, the targeted judgment matrix is generated to satisfy the requirement of consistence and the least dissimilar degree. The feasibility and validity of the proposed method are verified by simulation results.

Geometry of modified release formulations during dissolution--influence on performance of dosage forms with diclofenac sodium.

PubMed

Dorożyński, Przemysław; Kulinowski, Piotr; Jamróz, Witold; Juszczyk, Ewelina

2014-12-30

The objectives of the work included: presentation of magnetic resonance imaging (MRI) and fractal analysis based approach to comparison of dosage forms of different composition, structure, and assessment of the influence of the compositional factors i.e., matrix type, excipients etc., on properties and performance of the dosage form during drug dissolution. The work presents the first attempt to compare MRI data obtained for tablet formulations of different composition and characterized by distinct differences in hydration and drug dissolution mechanisms. The main difficulty, in such a case stems from differences in hydration behavior and tablet's geometry i.e., swelling, cracking, capping etc. A novel approach to characterization of matrix systems i.e., quantification of changes of geometrical complexity of the matrix shape during drug dissolution has been developed. Using three chosen commercial modified release tablet formulations with diclofenac sodium we present the method of parameterization of their geometrical complexity on the base of fractal analysis. The main result of the study is the correlation between the hydrating tablet behavior and drug dissolution - the increase of geometrical complexity expressed as fractal dimension relates to the increased variability of drug dissolution results. Copyright © 2014 Elsevier B.V. All rights reserved.

The optimal fiber volume fraction and fiber-matrix property compatibility in fiber reinforced composites

NASA Technical Reports Server (NTRS)

Pan, Ning

1992-01-01

Although the question of minimum or critical fiber volume fraction beyond which a composite can then be strengthened due to addition of fibers has been dealt with by several investigators for both continuous and short fiber composites, a study of maximum or optimal fiber volume fraction at which the composite reaches its highest strength has not been reported yet. The present analysis has investigated this issue for short fiber case based on the well-known shear lag (the elastic stress transfer) theory as the first step. Using the relationships obtained, the minimum spacing between fibers is determined upon which the maximum fiber volume fraction can be calculated, depending on the fiber packing forms within the composites. The effects on the value of this maximum fiber volume fraction due to such factors as fiber and matrix properties, fiber aspect ratio and fiber packing forms are discussed. Furthermore, combined with the previous analysis on the minimum fiber volume fraction, this maximum fiber volume fraction can be used to examine the property compatibility of fiber and matrix in forming a composite. This is deemed to be useful for composite design. Finally some examples are provided to illustrate the results.

Experimental observations and finite element analysis of the initiation of fiber microbuckling in notched composite laminates

NASA Technical Reports Server (NTRS)

Guynn, E. Gail; Bradley, Walter L.; Ochoa, Ozden O.

1990-01-01

A better understanding of the factors that affect the semi-circular edge-notched compressive strength is developed, and the associated failure mode(s) of thermoplastic composite laminates with multidirectional stacking sequences are identified. The primary variables in this investigation are the resin nonlinear shear constitutive behavior, stacking sequence (orientation of plies adjacent to the 0 degree plies), resin-rich regions between the 0 degree plies and the off-axis supporting plies, fiber/matrix interfacial bond strength, and initial fiber waviness. Two thermoplastic composite material systems are used in this investigation. The materials are the commercial APC-2 (AS4/PEEK) and a poor interface experimental material, AU4U/PEEK, designed for this investigation. Notched compression specimens are studied at 21, 77, and 132 C. Geometric and material nonlinear two-dimensional finite element analysis is used to model the initiation of fiber microbuckling of both the ideal straight fiber and the more realistic initially wavy fiber. The effects of free surface, fiber constitutive properties, matrix constitutive behavior, initial fiber curvature, and fiber/matrix interfacial bond strength on fiber microbuckling initiation strain levels are considered.

The nuclear matrix protein NMP-1 is the transcription factor YY1.

PubMed Central

Guo, B; Odgren, P R; van Wijnen, A J; Last, T J; Nickerson, J; Penman, S; Lian, J B; Stein, J L; Stein, G S

1995-01-01

NMP-1 was initially identified as a nuclear matrix-associated DNA-binding factor that exhibits sequence-specific recognition for the site IV regulatory element of a histone H4 gene. This distal promoter domain is a nuclear matrix interaction site. In the present study, we show that NMP-1 is the multifunctional transcription factor YY1. Gel-shift and Western blot analyses demonstrate that NMP-1 is immunoreactive with YY1 antibody. Furthermore, purified YY1 protein specifically recognizes site IV and reconstitutes the NMP-1 complex. Western blot and gel-shift analyses indicate that YY1 is present within the nuclear matrix. In situ immunofluorescence studies show that a significant fraction of YY1 is localized in the nuclear matrix, principally but not exclusively associated with residual nucleoli. Our results confirm that NMP-1/YY1 is a ubiquitous protein that is present in both human cells and in rat osteosarcoma ROS 17/2.8 cells. The finding that NMP-1 is identical to YY1 suggests that this transcriptional regulator may mediate gene-matrix interactions. Our results are consistent with the concept that the nuclear matrix may functionally compartmentalize the eukaryotic nucleus to support regulation of gene expression. Images Fig. 2 Fig. 3 Fig. 4 Fig. 5 Fig. 6 PMID:7479833

A Deep Stochastic Model for Detecting Community in Complex Networks

NASA Astrophysics Data System (ADS)

Fu, Jingcheng; Wu, Jianliang

2017-01-01

Discovering community structures is an important step to understanding the structure and dynamics of real-world networks in social science, biology and technology. In this paper, we develop a deep stochastic model based on non-negative matrix factorization to identify communities, in which there are two sets of parameters. One is the community membership matrix, of which the elements in a row correspond to the probabilities of the given node belongs to each of the given number of communities in our model, another is the community-community connection matrix, of which the element in the i-th row and j-th column represents the probability of there being an edge between a randomly chosen node from the i-th community and a randomly chosen node from the j-th community. The parameters can be evaluated by an efficient updating rule, and its convergence can be guaranteed. The community-community connection matrix in our model is more precise than the community-community connection matrix in traditional non-negative matrix factorization methods. Furthermore, the method called symmetric nonnegative matrix factorization, is a special case of our model. Finally, based on the experiments on both synthetic and real-world networks data, it can be demonstrated that our algorithm is highly effective in detecting communities.

Exploratory factor analysis of the Oral Health Impact Profile.

PubMed

John, M T; Reissmann, D R; Feuerstahler, L; Waller, N; Baba, K; Larsson, P; Celebić, A; Szabo, G; Rener-Sitar, K

2014-09-01

Although oral health-related quality of life (OHRQoL) as measured by the Oral Health Impact Profile (OHIP) is thought to be multidimensional, the nature of these dimensions is not known. The aim of this report was to explore the dimensionality of the OHIP using the Dimensions of OHRQoL (DOQ) Project, an international study of general population subjects and prosthodontic patients. Using the project's Learning Sample (n = 5173), we conducted an exploratory factor analysis on the 46 OHIP items not specifically referring to dentures for 5146 subjects with sufficiently complete data. The first eigenvalue (27·0) of the polychoric correlation matrix was more than ten times larger than the second eigenvalue (2·6), suggesting the presence of a dominant, higher-order general factor. Follow-up analyses with Horn's parallel analysis revealed a viable second-order, four-factor solution. An oblique rotation of this solution revealed four highly correlated factors that we named Oral Function, Oro-facial Pain, Oro-facial Appearance and Psychosocial Impact. These four dimensions and the strong general factor are two viable hypotheses for the factor structure of the OHIP. © 2014 John Wiley & Sons Ltd.

Determination of Flavonol Aglycones in Ginkgo biloba Dietary Supplement Crude Materials and Finished Products by High-Performance Liquid Chromatography: Single Laboratory Validation

PubMed Central

Gray, Dean; LeVanseler, Kerri; Pan, Meide

2008-01-01

A single laboratory validation (SLV) was completed for a method to determine the flavonol aglycones quercetin, kaempferol, and isorhamnetin in Ginkgo biloba products. The method calculates total glycosides based on these aglycones formed following acid hydrolysis. Nine matrixes were chosen for the study, including crude leaf material, standardized dry powder extract, single and multiple entity finished products, and ethanol and glycerol tinctures. For the 9 matrixes evaluated as part of this SLV, the method appeared to be selective and specific, with no observed interferences. The simplified 60 min oven heating hydrolysis procedure was effective for each of the matrixes studied, with no apparent or consistent differences between 60, 75, and 90 min at 90°C. A Youden ruggedness trial testing 7 factors with the potential to affect quantitative results showed that 2 factors (volume hydrolyzed and test sample extraction/hydrolysis weight) were the most important parameters for control during sample preparation. The method performed well in terms of precision, with 4 matrixes tested in triplicate over a 3-day period showing an overall repeatability (relative standard deviation, RSD) of 2.3%. Analysis of variance testing at α = 0.05 showed no significant differences among the within- or between-group sources of variation, although comparisons of within-day (Sw), between-day (Sb), and total (St) precision showed that a majority of the standard deviation came from within-day determinations for all matrixes. Accuracy testing at 2 levels (approximately 30 and 90% of the determined concentrations in standardized dry powder extract) from 2 complex negative control matrixes showed an overall 96% recovery and RSD of 1.0% for the high spike, and 94% recovery and RSD of 2.5% for the low spike. HorRat scores were within the limits for performance acceptability, ranging from 0.4 to 1.3. Based on the performance results presented herein, it is recommended that this method progress to the collaborative laboratory trial. PMID:16001841

Factor analysis and multiple regression between topography and precipitation on Jeju Island, Korea

NASA Astrophysics Data System (ADS)

Um, Myoung-Jin; Yun, Hyeseon; Jeong, Chang-Sam; Heo, Jun-Haeng

2011-11-01

SummaryIn this study, new factors that influence precipitation were extracted from geographic variables using factor analysis, which allow for an accurate estimation of orographic precipitation. Correlation analysis was also used to examine the relationship between nine topographic variables from digital elevation models (DEMs) and the precipitation in Jeju Island. In addition, a spatial analysis was performed in order to verify the validity of the regression model. From the results of the correlation analysis, it was found that all of the topographic variables had a positive correlation with the precipitation. The relations between the variables also changed in accordance with a change in the precipitation duration. However, upon examining the correlation matrix, no significant relationship between the latitude and the aspect was found. According to the factor analysis, eight topographic variables (latitude being the exception) were found to have a direct influence on the precipitation. Three factors were then extracted from the eight topographic variables. By directly comparing the multiple regression model with the factors (model 1) to the multiple regression model with the topographic variables (model 3), it was found that model 1 did not violate the limits of statistical significance and multicollinearity. As such, model 1 was considered to be appropriate for estimating the precipitation when taking into account the topography. In the study of model 1, the multiple regression model using factor analysis was found to be the best method for estimating the orographic precipitation on Jeju Island.

THE U.S. ENVIRONMENTAL PROTECTION AGENCY VERSION OF POSITIVE MATRIX FACTORIZATION

EPA Science Inventory

The abstract describes some of the special features of the EPA's version of Positive Matrix Factorization that is freely distributed. Features include descriptions of the Graphical User Interface, an approach for estimating errors in the modeled solutions, and future development...

Representation learning via Dual-Autoencoder for recommendation.

PubMed

Zhuang, Fuzhen; Zhang, Zhiqiang; Qian, Mingda; Shi, Chuan; Xie, Xing; He, Qing

2017-06-01

Recommendation has provoked vast amount of attention and research in recent decades. Most previous works employ matrix factorization techniques to learn the latent factors of users and items. And many subsequent works consider external information, e.g., social relationships of users and items' attributions, to improve the recommendation performance under the matrix factorization framework. However, matrix factorization methods may not make full use of the limited information from rating or check-in matrices, and achieve unsatisfying results. Recently, deep learning has proven able to learn good representation in natural language processing, image classification, and so on. Along this line, we propose a new representation learning framework called Recommendation via Dual-Autoencoder (ReDa). In this framework, we simultaneously learn the new hidden representations of users and items using autoencoders, and minimize the deviations of training data by the learnt representations of users and items. Based on this framework, we develop a gradient descent method to learn hidden representations. Extensive experiments conducted on several real-world data sets demonstrate the effectiveness of our proposed method compared with state-of-the-art matrix factorization based methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

Postconcussive Symptoms in OEF-OIF Veterans: Factor Structure and Impact of Posttraumatic Stress

DTIC Science & Technology

2009-06-03

correlations between NSI full items are presented in Appendix A. Visual inspection of the correlation matrix, the Kaiser - Meyer - Olkin coefficient of .92, and...Spearman rho correlations between NSI residuals are pre- sented in Appendix B. Again, visual inspection of the correla- tion matrix, the Kaiser - Meyer ... Olkin coefficient of .83, and Bartlett’s test of sphericity (x2 5 1,936.0, p , .01) suggested that the matrix could be factored. Principal-components

Underutilization of cervical cancer prevention services in low and middle income countries: a review of contributing factors

PubMed Central

Chidyaonga-Maseko, Fresier; Chirwa, Maureen Leah; Muula, Adamson Sinjani

2015-01-01

This review aims at identifying barriers to utilization of cervical cancer prevention services in low- and middle-income countries. An electronic search was conducted using the following key words, HPV vaccination, screening, barriers, utilization and low and middle income/developed countries. Using the Garrard (1999) Matrix method approach, a modified matrix was designed and used as a data collection tool and data related to each category listed on the tool were entered into a matrix containing columns reflecting the categories. Constant comparative analysis was used to identify thematic categories. 31 articles published between 2001 and 2014 were yielded from the search. Analysis of the contents of the articles showed that the underutilization of cervical cancer screening services in low and middle-income countries is the result of barriers in accessing and utilizing of the prevention services. Though not mutually exclusive, the barriers were categorized in three categories; individual, community and health system related. Individual barriers include lack of awareness and knowledge about risk factors and prevention of cervical cancer. Age, marital status, diffidence, social economic status, cultural and religious belief of the women also determine the women's' willingness to utilize the services. In some communities there is stigma attached to discussing reproductive health issues and this limits the young women's awareness of cervical cancer and its prevention. Understanding individual, community and health system barriers that hinder women's utilization of cervical cancer prevention services is very crucial in designing effective cervical cancer control programs in low- and middle-income countries. PMID:26523173

Downregulation of connective tissue growth factor by three-dimensional matrix enhances ovarian carcinoma cell invasion.

PubMed

Barbolina, Maria V; Adley, Brian P; Kelly, David L; Shepard, Jaclyn; Fought, Angela J; Scholtens, Denise; Penzes, Peter; Shea, Lonnie D; Stack, M Sharon

2009-08-15

Epithelial ovarian carcinoma (EOC) is a leading cause of death from gynecologic malignancies, due mainly to the prevalence of undetected metastatic disease. The process of cell invasion during intraperitoneal anchoring of metastatic lesions requires concerted regulation of many processes, including modulation of adhesion to the extracellular matrix and localized invasion. Exploratory cDNA microarray analysis of early response genes (altered after 4 hr of 3D collagen culture) coupled with confirmatory real-time reverse-transcriptase polymerase chain reaction, multiple 3D cell culture matrices, Western blot, immunostaining, adhesion, migration and invasion assays were used to identify modulators of adhesion pertinent to EOC progression and metastasis. cDNA microarray analysis indicated a dramatic downregulation of connective tissue growth factor (CTGF) in EOC cells placed in invasion- mimicking conditions (3D Type I collagen). Examination of human EOC specimens revealed that CTGF expression was absent in 46% of the tested samples (n = 41), but was present in 100% of normal ovarian epithelium samples (n = 7). Reduced CTGF expression occurs in many types of cells and may be a general phenomenon displayed by cells encountering a 3D environment. CTGF levels were inversely correlated with invasion such that downregulation of CTGF increased, while its upregulation reduced collagen invasion. Cells adhered preferentially to a surface comprised of both collagen I and CTGF relative to either component alone using alpha6beta1 and alpha3beta1 integrins. Together these data suggest that downregulation of CTGF in EOC cells may be important for cell invasion through modulation of cell-matrix adhesion.

Downregulation of Connective Tissue Growth Factor by Three-Dimensional Matrix Enhances Ovarian Carcinoma Cell Invasion

PubMed Central

Barbolina, Maria V.; Adley, Brian P.; Kelly, David L.; Shepard, Jaclyn; Fought, Angela J.; Scholtens, Denise; Penzes, Peter; Shea, Lonnie D.; Sharon Stack, M

2010-01-01

Epithelial ovarian carcinoma (EOC) is a leading cause of death from gynecologic malignancy, due mainly to the prevalence of undetected metastatic disease. The process of cell invasion during intra-peritoneal anchoring of metastatic lesions requires concerted regulation of many processes, including modulation of adhesion to the extracellular matrix and localized invasion. Exploratory cDNA microarray analysis of early response genes (altered after 4 hours of 3-dimensional collagen culture) coupled with confirmatory real-time RT-PCR, multiple three-dimensional cell culture matrices, Western blot, immunostaining, adhesion, migration, and invasion assays were used to identify modulators of adhesion pertinent to EOC progression and metastasis. cDNA microarray analysis indicated a dramatic downregulation of connective tissue growth factor (CTGF) in EOC cells placed in invasion-mimicking conditions (3-dimensional type I collagen). Examination of human EOC specimens revealed that CTGF expression was absent in 46% of the tested samples (n=41), but was present in 100% of normal ovarian epithelium samples (n=7). Reduced CTGF expression occurs in many types of cells and may be a general phenomenon displayed by cells encountering a 3D environment. CTGF levels were inversely correlated with invasion such that downregulation of CTGF increased, while its upregulation reduced, collagen invasion. Cells adhered preferentially to a surface comprised of both collagen I and CTGF relative to either component alone using α6β1 and α3β1 integrins. Together these data suggest that downregulation of CTGF in EOC cells may be important for cell invasion through modulation of cell-matrix adhesion. PMID:19382180

Fast and anisotropic flexibility-rigidity index for protein flexibility and fluctuation analysis

NASA Astrophysics Data System (ADS)

Opron, Kristopher; Xia, Kelin; Wei, Guo-Wei

2014-06-01

Protein structural fluctuation, typically measured by Debye-Waller factors, or B-factors, is a manifestation of protein flexibility, which strongly correlates to protein function. The flexibility-rigidity index (FRI) is a newly proposed method for the construction of atomic rigidity functions required in the theory of continuum elasticity with atomic rigidity, which is a new multiscale formalism for describing excessively large biomolecular systems. The FRI method analyzes protein rigidity and flexibility and is capable of predicting protein B-factors without resorting to matrix diagonalization. A fundamental assumption used in the FRI is that protein structures are uniquely determined by various internal and external interactions, while the protein functions, such as stability and flexibility, are solely determined by the structure. As such, one can predict protein flexibility without resorting to the protein interaction Hamiltonian. Consequently, bypassing the matrix diagonalization, the original FRI has a computational complexity of O(N^2). This work introduces a fast FRI (fFRI) algorithm for the flexibility analysis of large macromolecules. The proposed fFRI further reduces the computational complexity to O(N). Additionally, we propose anisotropic FRI (aFRI) algorithms for the analysis of protein collective dynamics. The aFRI algorithms permit adaptive Hessian matrices, from a completely global 3N × 3N matrix to completely local 3 × 3 matrices. These 3 × 3 matrices, despite being calculated locally, also contain non-local correlation information. Eigenvectors obtained from the proposed aFRI algorithms are able to demonstrate collective motions. Moreover, we investigate the performance of FRI by employing four families of radial basis correlation functions. Both parameter optimized and parameter-free FRI methods are explored. Furthermore, we compare the accuracy and efficiency of FRI with some established approaches to flexibility analysis, namely, normal mode analysis and Gaussian network model (GNM). The accuracy of the FRI method is tested using four sets of proteins, three sets of relatively small-, medium-, and large-sized structures and an extended set of 365 proteins. A fifth set of proteins is used to compare the efficiency of the FRI, fFRI, aFRI, and GNM methods. Intensive validation and comparison indicate that the FRI, particularly the fFRI, is orders of magnitude more efficient and about 10% more accurate overall than some of the most popular methods in the field. The proposed fFRI is able to predict B-factors for α-carbons of the HIV virus capsid (313 236 residues) in less than 30 seconds on a single processor using only one core. Finally, we demonstrate the application of FRI and aFRI to protein domain analysis.

Fast and anisotropic flexibility-rigidity index for protein flexibility and fluctuation analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Opron, Kristopher; Xia, Kelin; Wei, Guo-Wei, E-mail: wei@math.msu.edu

Protein structural fluctuation, typically measured by Debye-Waller factors, or B-factors, is a manifestation of protein flexibility, which strongly correlates to protein function. The flexibility-rigidity index (FRI) is a newly proposed method for the construction of atomic rigidity functions required in the theory of continuum elasticity with atomic rigidity, which is a new multiscale formalism for describing excessively large biomolecular systems. The FRI method analyzes protein rigidity and flexibility and is capable of predicting protein B-factors without resorting to matrix diagonalization. A fundamental assumption used in the FRI is that protein structures are uniquely determined by various internal and external interactions,more » while the protein functions, such as stability and flexibility, are solely determined by the structure. As such, one can predict protein flexibility without resorting to the protein interaction Hamiltonian. Consequently, bypassing the matrix diagonalization, the original FRI has a computational complexity of O(N{sup 2}). This work introduces a fast FRI (fFRI) algorithm for the flexibility analysis of large macromolecules. The proposed fFRI further reduces the computational complexity to O(N). Additionally, we propose anisotropic FRI (aFRI) algorithms for the analysis of protein collective dynamics. The aFRI algorithms permit adaptive Hessian matrices, from a completely global 3N × 3N matrix to completely local 3 × 3 matrices. These 3 × 3 matrices, despite being calculated locally, also contain non-local correlation information. Eigenvectors obtained from the proposed aFRI algorithms are able to demonstrate collective motions. Moreover, we investigate the performance of FRI by employing four families of radial basis correlation functions. Both parameter optimized and parameter-free FRI methods are explored. Furthermore, we compare the accuracy and efficiency of FRI with some established approaches to flexibility analysis, namely, normal mode analysis and Gaussian network model (GNM). The accuracy of the FRI method is tested using four sets of proteins, three sets of relatively small-, medium-, and large-sized structures and an extended set of 365 proteins. A fifth set of proteins is used to compare the efficiency of the FRI, fFRI, aFRI, and GNM methods. Intensive validation and comparison indicate that the FRI, particularly the fFRI, is orders of magnitude more efficient and about 10% more accurate overall than some of the most popular methods in the field. The proposed fFRI is able to predict B-factors for α-carbons of the HIV virus capsid (313 236 residues) in less than 30 seconds on a single processor using only one core. Finally, we demonstrate the application of FRI and aFRI to protein domain analysis.« less

Multivariate Granger causality: an estimation framework based on factorization of the spectral density matrix

PubMed Central

Wen, Xiaotong; Rangarajan, Govindan; Ding, Mingzhou

2013-01-01

Granger causality is increasingly being applied to multi-electrode neurophysiological and functional imaging data to characterize directional interactions between neurons and brain regions. For a multivariate dataset, one might be interested in different subsets of the recorded neurons or brain regions. According to the current estimation framework, for each subset, one conducts a separate autoregressive model fitting process, introducing the potential for unwanted variability and uncertainty. In this paper, we propose a multivariate framework for estimating Granger causality. It is based on spectral density matrix factorization and offers the advantage that the estimation of such a matrix needs to be done only once for the entire multivariate dataset. For any subset of recorded data, Granger causality can be calculated through factorizing the appropriate submatrix of the overall spectral density matrix. PMID:23858479

RECEPTOR MODELING OF AMBIENT PARTICULATE MATTER DATA USING POSITIVE MATRIX FACTORIZATION REVIEW OF EXISTING METHODS

EPA Science Inventory

Methods for apportioning sources of ambient particulate matter (PM) using the positive matrix factorization (PMF) algorithm are reviewed. Numerous procedural decisions must be made and algorithmic parameters selected when analyzing PM data with PMF. However, few publications docu...

Matrix factorization-based data fusion for gene function prediction in baker's yeast and slime mold.

PubMed

Zitnik, Marinka; Zupan, Blaž

2014-01-01

The development of effective methods for the characterization of gene functions that are able to combine diverse data sources in a sound and easily-extendible way is an important goal in computational biology. We have previously developed a general matrix factorization-based data fusion approach for gene function prediction. In this manuscript, we show that this data fusion approach can be applied to gene function prediction and that it can fuse various heterogeneous data sources, such as gene expression profiles, known protein annotations, interaction and literature data. The fusion is achieved by simultaneous matrix tri-factorization that shares matrix factors between sources. We demonstrate the effectiveness of the approach by evaluating its performance on predicting ontological annotations in slime mold D. discoideum and on recognizing proteins of baker's yeast S. cerevisiae that participate in the ribosome or are located in the cell membrane. Our approach achieves predictive performance comparable to that of the state-of-the-art kernel-based data fusion, but requires fewer data preprocessing steps.

Structure of collagen-glycosaminoglycan matrix and the influence to its integrity and stability.

PubMed

Bi, Yuying; Patra, Prabir; Faezipour, Miad

2014-01-01

Glycosaminoglycan (GAG) is a chain-like disaccharide that is linked to polypeptide core to connect two collagen fibrils/fibers and provide the intermolecular force in Collagen-GAG matrix (C-G matrix). Thus, the distribution of GAG in C-G matrix contributes to the integrity and mechanical properties of the matrix and related tissue. This paper analyzes the transverse isotropic distribution of GAG in C-G matrix. The angle of GAGs related to collagen fibrils is used as parameters to qualify the GAGs isotropic characteristic in both 3D and 2D rendering. Statistical results included that over one third of GAGs were perpendicular directed to collagen fibril with symmetrical distribution for both 3D matrix and 2D plane cross through collagen fibrils. The three factors tested in this paper: collagen radius, collagen distribution, and GAGs density, were not statistically significant for the strength of Collagen-GAG matrix in 3D rendering. However in 2D rendering, a significant factor found was the radius of collagen in matrix for the GAGs directed to orthogonal plane of Collagen-GAG matrix. Between two cross-section selected from Collagen-GAG matrix model, the plane cross through collagen fibrils was symmetrically distributed but the total percentage of perpendicular directed GAG was deducted by decreasing collagen radius. There were some symmetry features of GAGs angle distribution in selected 2D plane that passed through space between collagen fibrils, but most models showed multiple peaks in GAGs angle distribution. With less GAGs directed to perpendicular of collagen fibril, strength in collagen cross-section weakened. Collagen distribution was also a factor that influences GAGs angle distribution in 2D rendering. True hexagonal collagen packaging is reported in this paper to have less strength at collagen cross-section compared to quasi-hexagonal collagen arrangement. In this work focus is on GAGs matrix within the collagen and its relevance to anisotropy.

Selection of representative embankments based on rough set - fuzzy clustering method

NASA Astrophysics Data System (ADS)

Bin, Ou; Lin, Zhi-xiang; Fu, Shu-yan; Gao, Sheng-song

2018-02-01

The premise condition of comprehensive evaluation of embankment safety is selection of representative unit embankment, on the basis of dividing the unit levee the influencing factors and classification of the unit embankment are drafted.Based on the rough set-fuzzy clustering, the influence factors of the unit embankment are measured by quantitative and qualitative indexes.Construct to fuzzy similarity matrix of standard embankment then calculate fuzzy equivalent matrix of fuzzy similarity matrix by square method. By setting the threshold of the fuzzy equivalence matrix, the unit embankment is clustered, and the representative unit embankment is selected from the classification of the embankment.

Factor analysis of the Hamilton Depression Rating Scale in Parkinson's disease.

PubMed

Broen, M P G; Moonen, A J H; Kuijf, M L; Dujardin, K; Marsh, L; Richard, I H; Starkstein, S E; Martinez-Martin, P; Leentjens, A F G

2015-02-01

Several studies have validated the Hamilton Depression Rating Scale (HAMD) in patients with Parkinson's disease (PD), and reported adequate reliability and construct validity. However, the factorial validity of the HAMD has not yet been investigated. The aim of our analysis was to explore the factor structure of the HAMD in a large sample of PD patients. A principal component analysis of the 17-item HAMD was performed on data of 341 PD patients, available from a previous cross sectional study on anxiety. An eigenvalue ≥1 was used to determine the number of factors. Factor loadings ≥0.4 in combination with oblique rotations were used to identify which variables made up the factors. Kaiser-Meyer-Olkin measure (KMO), Cronbach's alpha, Bartlett's test, communality, percentage of non-redundant residuals and the component correlation matrix were computed to assess factor validity. KMO verified the sample's adequacy for factor analysis and Cronbach's alpha indicated a good internal consistency of the total scale. Six factors had eigenvalues ≥1 and together explained 59.19% of the variance. The number of items per factor varied from 1 to 6. Inter-item correlations within each component were low. There was a high percentage of non-redundant residuals and low communality. This analysis demonstrates that the factorial validity of the HAMD in PD is unsatisfactory. This implies that the scale is not appropriate for studying specific symptom domains of depression based on factorial structure in a PD population. Copyright © 2014 Elsevier Ltd. All rights reserved.

Modelling and analysis of FMS productivity variables by ISM, SEM and GTMA approach

NASA Astrophysics Data System (ADS)

Jain, Vineet; Raj, Tilak

2014-09-01

Productivity has often been cited as a key factor in a flexible manufacturing system (FMS) performance, and actions to increase it are said to improve profitability and the wage earning capacity of employees. Improving productivity is seen as a key issue for survival and success in the long term of a manufacturing system. The purpose of this paper is to make a model and analysis of the productivity variables of FMS. This study was performed by different approaches viz. interpretive structural modelling (ISM), structural equation modelling (SEM), graph theory and matrix approach (GTMA) and a cross-sectional survey within manufacturing firms in India. ISM has been used to develop a model of productivity variables, and then it has been analyzed. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) are powerful statistical techniques. CFA is carried by SEM. EFA is applied to extract the factors in FMS by the statistical package for social sciences (SPSS 20) software and confirming these factors by CFA through analysis of moment structures (AMOS 20) software. The twenty productivity variables are identified through literature and four factors extracted, which involves the productivity of FMS. The four factors are people, quality, machine and flexibility. SEM using AMOS 20 was used to perform the first order four-factor structures. GTMA is a multiple attribute decision making (MADM) methodology used to find intensity/quantification of productivity variables in an organization. The FMS productivity index has purposed to intensify the factors which affect FMS.

The General Factor of Personality: A General Critique.

PubMed

Revelle, William; Wilt, Joshua

2013-10-01

Recently, it has been proposed that all non-cognitive measures of personality share a general factor of personality. A problem with many of these studies is a lack of clarity in defining a general factor. In this paper we address the multiple ways in which a general factor has been identified and argue that many of these approaches find factors that are not in fact general. Through the use of artificial examples, we show that a general factor is not: The first factor or component of a correlation or covariance matrix.The first factor resulting from a bifactor rotation or biquartimin transformationNecessarily the result of a confirmatory factor analysis forcing a bifactor solution We consider how the definition of what constitutes a general factor can lead to confusion, and we will demonstrate alternative ways of estimating the general factor saturation that are more appropriate.

The General Factor of Personality: A General Critique

PubMed Central

Revelle, William; Wilt, Joshua

2013-01-01

Recently, it has been proposed that all non-cognitive measures of personality share a general factor of personality. A problem with many of these studies is a lack of clarity in defining a general factor. In this paper we address the multiple ways in which a general factor has been identified and argue that many of these approaches find factors that are not in fact general. Through the use of artificial examples, we show that a general factor is not: The first factor or component of a correlation or covariance matrix.The first factor resulting from a bifactor rotation or biquartimin transformationNecessarily the result of a confirmatory factor analysis forcing a bifactor solution We consider how the definition of what constitutes a general factor can lead to confusion, and we will demonstrate alternative ways of estimating the general factor saturation that are more appropriate. PMID:23956474

Contrasting recovery patterns of 2, 4-dinitrophenylhydrazones (DNPH) derivative of carbonyls between liquid and gas phase standards using HPLC-based analysis

NASA Astrophysics Data System (ADS)

Saha, Subbroto Kumar; Jo, Sang-Hee; Song, Hee-Nam; Brown, Richard J. C.; Kim, Ki-Hyun

2012-12-01

This study evaluates the relative recovery (RR) of five different carbonyls (CCs) (i.e., acetaldehyde, propionaldehyde, butyraldehyde, isovaleraldehyde, and valeraldehyde) following their reaction as 2, 4-dinitrophenylhydrazine (DNPH) derivatives when using gas phase and liquid phase standards. To this end, relative efficiency of CC-DNPH derivatization is compared between two liquid-phase standards (commercially available vs. lab made mixture) and between liquid and gas-phase standard. If the results are compared in terms of response factors (RF) derived for five carbonyls from all different standard phases, the recovery of gaseous CC standard was distinguished from that of liquid counterparts. The RR of the heavier carbonyls (propionaldehyde, butyraldehyde, isovaleraldehyde, and valeraldehyde) was approximately 60% low relative to their liquid counterparts; however, it was not the case for the lighter carbonyls (acetaldehyde) with the RR of ˜92%. This study thus suggests that the quantification of heavy carbonyls in ambient air, unless made by standards of the same matrix (i.e., gas phase) or compensated by the proper correction factor, may be subject to a large bias due to difference in derivatization reaction efficiency between matrix types. Hence, consideration of the matrix effect at the calibration stage is of particular importance to measure CC quantitatively.

Persistence of an intact endometrial matrix and vessels structure in women exposed to VA-2914, a selective progesterone receptor modulator.

PubMed

Ravet, S; Munaut, C; Blacher, S; Brichant, G; Labied, S; Beliard, A; Chabbert-Buffet, N; Bouchard, P; Foidart, J-M; Pintiaux, A

2008-11-01

VA-2914 is a selective progesterone receptor modulator with potential contraceptive activity that induces amenorrhea, whereas progestins cause endometrial spotting and bleeding. This abnormal bleeding due to progestins is a consequence of focal stromal proteolysis by an increase in naked vessel size and density. Our objective was to quantify the effects of VA-2914 on endometrial vascularization, fibrillar matrix, and vascular endothelial growth factor (VEGF)-A expression in endometrial biopsies from 41 women before and after 12 wk daily treatment with a placebo, or 2.5, 5, or 10 mg VA-2914. Collagen fibrillar network was stained by silver impregnation. Vessel area, density, and structure were quantified with a computer-assisted image analysis system after double immunostaining using an anti-von Willebrand factor (endothelial cells) and an anti-alpha smooth muscle actin (vascular smooth muscle cells) marker antibody. VEGF-A mRNAs were quantified by RT-PCR and localized by immunohistochemistry. The endometrial vessels, collagen network, and mRNA levels of VEGF-A were identical during the luteal phase at baseline and in VA-2914 treated women. VEGF-A distribution was unchanged. VA-2914 does not alter the endometrial matrix and cells, and does not modify the endometrial vessel morphology as compared with baseline biopsies.

The association between MMP2 -1306 C > T (rs243865) polymorphism and risk of prostate cancer.

PubMed

Shajarehpoor Salavati, L; Tafvizi, F; Manjili, H K

2017-02-01

Prostate cancer is the second most common cancer in men. Matrix metalloproteinase-2 (MMP2) is the most important member of the matrix metalloproteinase family. MMP2 digests the basement membrane and causes changes in the extracellular matrix which in turn facilitate cancer invasion. It, therefore, has a major role in tumor angiogenesis. Previous studies have identified a single-nucleotide polymorphism C/T at position -1306 of MMP2 gene promoter which is a key regulatory factor in cancer progression. The present study aimed to determine the association between MMP2 polymorphism and the risk of prostate cancer in Iranian men. This case-control study was performed on 50 paraffin-embedded prostate cancer tissue samples and 54 blood samples from healthy men. Genotyping of the samples was performed using high-resolution melting analysis (HRM). Finally, 20 % of the genotypes were confirmed by sequencing. No significant associations were found between CT and TT genotypes and the risk of prostate cancer. However, there were no significant relationships between the genotypes and the studied factors, e.g., age, pathological stage, and Gleason Score. MMP2 -1306 C > T (rs243865) polymorphism was not significantly related with prostate cancer susceptibility in Iranian men.

Factors underlying the psychological and behavioral characteristics of Office of Strategic Services candidates: the assessment of men data revisited.

PubMed

Lenzenweger, Mark F

2015-01-01

During World War II, the Office of Strategic Services (OSS), the forerunner of the Central Intelligence Agency, sought the assistance of clinical psychologists and psychiatrists to establish an assessment program for evaluating candidates for the OSS. The assessment team developed a novel and rigorous program to evaluate OSS candidates. It is described in Assessment of Men: Selection of Personnel for the Office of Strategic Services (OSS Assessment Staff, 1948). This study examines the sole remaining multivariate data matrix that includes all final ratings for a group of candidates (n = 133) assessed near the end of the assessment program. It applies the modern statistical methods of both exploratory and confirmatory factor analysis to this rich and highly unique data set. An exploratory factor analysis solution suggested 3 factors underlie the OSS assessment staff ratings. Confirmatory factor analysis results of multiple plausible substantive models reveal that a 3-factor model provides the best fit to these data. The 3 factors are emotional/interpersonal factors (social relations, emotional stability, security), intelligence processing (effective IQ, propaganda skills, observing and reporting), and agency/surgency (motivation, energy and initiative, leadership, physical ability). These factors are discussed in terms of their potential utility for personnel selection within the intelligence community.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smentkowski, Vincent S., E-mail: smentkow@ge.com

Changes in the oxidation state of an element can result in significant changes in the ionization efficiency and hence signal intensity during secondary ion mass spectrometry (SIMS) analysis; this is referred to as the SIMS matrix effect [Secondary Ion Mass Spectrometry: A Practical Handbook for Depth Profiling and Bulk Impurity Analysis, edited by R. G. Wilson, F. A. Stevie, and C. W. Magee (Wiley, New York, 1990)]. The SIMS matrix effect complicates quantitative analysis. Quantification of SIMS data requires the determination of relative sensitivity factors (RSFs), which can be used to convert the as measured intensity into concentration units [Secondarymore » Ion Mass Spectrometry: A Practical Handbook for Depth Profiling and Bulk Impurity Analysis, edited by R. G. Wilson, F. A. Stevie, and C. W. Magee (Wiley, New York, 1990)]. In this manuscript, the authors report both: RSFs which were determined for quantification of B in Si and SiO{sub 2} matrices using a dual beam time of flight secondary ion mass spectrometry (ToF-SIMS) instrument and the protocol they are using to provide quantitative ToF-SIMS images and line scan traces. The authors also compare RSF values that were determined using oxygen and Ar ion beams for erosion, discuss the problems that can be encountered when bulk calibration samples are used to determine RSFs, and remind the reader that errors in molecular details of the matrix (density, volume, etc.) that are used to convert from atoms/cm{sup 3} to other concentration units will propagate into errors in the determined concentrations.« less

COMPADRE: an R and web resource for pathway activity analysis by component decompositions.

PubMed

Ramos-Rodriguez, Roberto-Rafael; Cuevas-Diaz-Duran, Raquel; Falciani, Francesco; Tamez-Peña, Jose-Gerardo; Trevino, Victor

2012-10-15

The analysis of biological networks has become essential to study functional genomic data. Compadre is a tool to estimate pathway/gene sets activity indexes using sub-matrix decompositions for biological networks analyses. The Compadre pipeline also includes one of the direct uses of activity indexes to detect altered gene sets. For this, the gene expression sub-matrix of a gene set is decomposed into components, which are used to test differences between groups of samples. This procedure is performed with and without differentially expressed genes to decrease false calls. During this process, Compadre also performs an over-representation test. Compadre already implements four decomposition methods [principal component analysis (PCA), Isomaps, independent component analysis (ICA) and non-negative matrix factorization (NMF)], six statistical tests (t- and f-test, SAM, Kruskal-Wallis, Welch and Brown-Forsythe), several gene sets (KEGG, BioCarta, Reactome, GO and MsigDB) and can be easily expanded. Our simulation results shown in Supplementary Information suggest that Compadre detects more pathways than over-representation tools like David, Babelomics and Webgestalt and less false positives than PLAGE. The output is composed of results from decomposition and over-representation analyses providing a more complete biological picture. Examples provided in Supplementary Information show the utility, versatility and simplicity of Compadre for analyses of biological networks. Compadre is freely available at http://bioinformatica.mty.itesm.mx:8080/compadre. The R package is also available at https://sourceforge.net/p/compadre.

Genetic algorithm and graph theory based matrix factorization method for online friend recommendation.

PubMed

Li, Qu; Yao, Min; Yang, Jianhua; Xu, Ning

2014-01-01

Online friend recommendation is a fast developing topic in web mining. In this paper, we used SVD matrix factorization to model user and item feature vector and used stochastic gradient descent to amend parameter and improve accuracy. To tackle cold start problem and data sparsity, we used KNN model to influence user feature vector. At the same time, we used graph theory to partition communities with fairly low time and space complexity. What is more, matrix factorization can combine online and offline recommendation. Experiments showed that the hybrid recommendation algorithm is able to recommend online friends with good accuracy.

Quantitative determination of conformational, dynamic, and kinetic parameters of a ligand-protein/DNA complex from a complete relaxation and conformational exchange matrix analysis of intermolecular transferred NOESY.

PubMed

Moseley, H N; Lee, W; Arrowsmith, C H; Krishna, N R

1997-05-06

We report a quantitative analysis of the 13C-edited intermolecular transferred NOESY (inter-TrNOESY) spectrum of the trp-repressor/operator complex (trp-rep/op) with [ul-13C/15N]-L-tryptophan corepressor using a computer program implementing complete relaxation and conformational exchange matrix (CORCEMA) methodology [Moseley et al. (1995) J. Magn. Reson. 108B, 243-261]. Using complete mixing time curves of three inter-TrNOESY peaks between the tryptophan and the Trp-rep/op, this self-consistent analysis determined the correlation time of the bound species (tauB = 13.5 ns) and the exchange off-rate (k(off) = 3.6 s(-1)) of the corepressor. In addition, the analysis estimated the correlation time of the free species (tauF approximately 0.15 ns). Also, we demonstrate the sensitivity of these inter-TrNOESY peaks to several factors including the k(off) and orientation of the tryptophan corepressor within the binding site. The analysis indicates that the crystal structure orientation for the corepressor is compatible with the solution NMR data.

Factorization-based texture segmentation

DOE PAGES

Yuan, Jiangye; Wang, Deliang; Cheriyadat, Anil M.

2015-06-17

This study introduces a factorization-based approach that efficiently segments textured images. We use local spectral histograms as features, and construct an M × N feature matrix using M-dimensional feature vectors in an N-pixel image. Based on the observation that each feature can be approximated by a linear combination of several representative features, we factor the feature matrix into two matrices-one consisting of the representative features and the other containing the weights of representative features at each pixel used for linear combination. The factorization method is based on singular value decomposition and nonnegative matrix factorization. The method uses local spectral histogramsmore » to discriminate region appearances in a computationally efficient way and at the same time accurately localizes region boundaries. Finally, the experiments conducted on public segmentation data sets show the promise of this simple yet powerful approach.« less

Insights into the interaction between carbamazepine and natural dissolved organic matter in the Yangtze Estuary using fluorescence excitation-emission matrix spectra coupled with parallel factor analysis.

PubMed

Wang, Ying; Zhang, Manman; Fu, Jun; Li, Tingting; Wang, Jinggang; Fu, Yingyu

2016-10-01

The interaction between carbamazepine (CBZ) and dissolved organic matter (DOM) from three zones (the nearshore, the river channel, and the coastal areas) in the Yangtze Estuary was investigated using fluorescence quenching titration combined with excitation emission matrix spectra and parallel factor analysis (PARAFAC). The complexation between CBZ and DOM was demonstrated by the increase in hydrogen bonding and the disappearance of the C=O stretch obtained from the Fourier transform infrared spectroscopy analysis. The results indicated that two protein-like substances (component 2 and component3) and two humic-like substances (component 1 and 4) were identified in the DOM from the Yangtze Estuary. The fluorescence quenching curves of each component with the addition of CBZ and the Ryan and Weber model calculation results both demonstrated that the different components exhibited different complexation activities with CBZ. The protein-like components had a stronger affinity with CBZ than did the humic-like substances. On the other hand, the autochthonous tyrosine-like C2 played an important role in the complexation with DOM from the river channel and coastal areas, while C3 influenced by anthropogenic activities showed an obvious effect in the nearshore area. DOMs from the river channel have the highest binding capacity for CBZ, which may ascribe to the relatively high phenol content group in the DOM.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fast, J; Zhang, Q; Tilp, A

Significantly improved returns in their aerosol chemistry data can be achieved via the development of a value-added product (VAP) of deriving OA components, called Organic Aerosol Components (OACOMP). OACOMP is primarily based on multivariate analysis of the measured organic mass spectral matrix. The key outputs of OACOMP are the concentration time series and the mass spectra of OA factors that are associated with distinct sources, formation and evolution processes, and physicochemical properties.

On the Assessment of Psychometric Adequacy in Correlation Matrices.

ERIC Educational Resources Information Center

Dziuban, Charles D.; Shirkey, Edwin C.

Three techniques for assessing the adequacy of correlation matrices for factor analysis were applied to four examples from the literature. The methods compared were: (1) inspection of the off diagonal elements of the anti-image covariance matrix S(to the 2nd) R(to the -1) and S(to the 2nd); (2) the Measure of Sampling Adequacy (M.S.A.), and (3)…

A Block Coordinate Descent Method for Multi-Convex Optimization with Applications to Nonnegative Tensor Factorization and Completion

DTIC Science & Technology

2012-08-01

model appears in cosmic microwave background analysis [10] which solves min A,Y λ 2 trace ( (ABY − X)>C−1(ABY − X) ) + r(Y), subject to A ∈ D (1.5...and “×n” represent outer product and tensor-matrix multiplication, respectively. (The necessary background of tensor is reviewed in Sec. 3) Most

Evaluation of different rotary devices on bone repair in rabbits.

PubMed

Ribeiro Junior, Paulo Domingos; Barleto, Christiane Vespasiano; Ribeiro, Daniel Araki; Matsumoto, Mariza Akemi

2007-01-01

In oral surgery, the quality of bone repair may be influenced by several factors that can increase the morbidity of the procedure. The type of equipment used for ostectomy can directly affect bone healing. The aim of this study was to evaluate bone repair of mandible bone defects prepared in rabbits using three different rotary devices. Fifteen New Zealand rabbits were randomly assigned to 3 groups (n=5) according to type of rotary device used to create bone defects: I--pneumatic low-speed rotation engine, II--pneumatic high-speed rotation engine, and III--electric low-speed rotation engine. The anatomic pieces were surgically obtained after 2, 7 and 30 days and submitted to histological and morphometric analysis. The morphometric results were expressed as the total area of bone remodeling matrix using an image analysis system. Increases in the bone remodeling matrix were noticed with time along the course of the experiment. No statistically significant differences (p>0.05) were observed among the groups at the three sacrificing time points considering the total area of bone mineralized matrix, although the histological analysis showed a slightly advanced bone repair in group III compared to the other two groups. The findings of the present study suggest that the type of rotary device used in oral and maxillofacial surgery does not interfere with the bone repair process.

Regulation of matrix metalloproteinase-9 expression between gingival fibroblast cells from old and young rats

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Su-Jung; Chung, Yong-Koo; Chung, Tae-Wook

2009-01-09

Gingival fibroblast cells (rGF) from aged rats have an age-related decline in proliferative capacity compared with young rats. We investigated G1 phase cell cycle regulation and MMP-9 expression in both young and aged rGF. G1 cell cycle protein levels and activity were significantly reduced in response to interleukin-1{beta} (IL-1{beta}) stimulation with increasing in vitro age. Tumor necrosis factor-{alpha} (TNF-{alpha})-induced matrix metalloproteinase-9 (MMP-9) expression was also decreased in aged rGF in comparison with young rGF. Mutational analysis and gel shift assays demonstrated that the lower MMP-9 expression in aged rGF is associated with lower activities of transcription factors NF-{kappa}B and AP-1.more » These results suggest that cell cycle dysregulation and down-regulation of MMP-9 expression in rGF may play a role in gingival remodeling during in vitro aging.« less

Community detection enhancement using non-negative matrix factorization with graph regularization

NASA Astrophysics Data System (ADS)

Liu, Xiao; Wei, Yi-Ming; Wang, Jian; Wang, Wen-Jun; He, Dong-Xiao; Song, Zhan-Jie

2016-06-01

Community detection is a meaningful task in the analysis of complex networks, which has received great concern in various domains. A plethora of exhaustive studies has made great effort and proposed many methods on community detection. Particularly, a kind of attractive one is the two-step method which first makes a preprocessing for the network and then identifies its communities. However, not all types of methods can achieve satisfactory results by using such preprocessing strategy, such as the non-negative matrix factorization (NMF) methods. In this paper, rather than using the above two-step method as most works did, we propose a graph regularized-based model to improve, specialized, the NMF-based methods for the detection of communities, namely NMFGR. In NMFGR, we introduce the similarity metric which contains both the global and local information of networks, to reflect the relationships between two nodes, so as to improve the accuracy of community detection. Experimental results on both artificial and real-world networks demonstrate the superior performance of NMFGR to some competing methods.

Scale Free Reduced Rank Image Analysis.

ERIC Educational Resources Information Center

Horst, Paul

In the traditional Guttman-Harris type image analysis, a transformation is applied to the data matrix such that each column of the transformed data matrix is the best least squares estimate of the corresponding column of the data matrix from the remaining columns. The model is scale free. However, it assumes (1) that the correlation matrix is…

Weighted graph based ordering techniques for preconditioned conjugate gradient methods

NASA Technical Reports Server (NTRS)

Clift, Simon S.; Tang, Wei-Pai

1994-01-01

We describe the basis of a matrix ordering heuristic for improving the incomplete factorization used in preconditioned conjugate gradient techniques applied to anisotropic PDE's. Several new matrix ordering techniques, derived from well-known algorithms in combinatorial graph theory, which attempt to implement this heuristic, are described. These ordering techniques are tested against a number of matrices arising from linear anisotropic PDE's, and compared with other matrix ordering techniques. A variation of RCM is shown to generally improve the quality of incomplete factorization preconditioners.

Growth factor transgenes interactively regulate articular chondrocytes.

PubMed

Shi, Shuiliang; Mercer, Scott; Eckert, George J; Trippel, Stephen B

2013-04-01

Adult articular chondrocytes lack an effective repair response to correct damage from injury or osteoarthritis. Polypeptide growth factors that stimulate articular chondrocyte proliferation and cartilage matrix synthesis may augment this response. Gene transfer is a promising approach to delivering such factors. Multiple growth factor genes regulate these cell functions, but multiple growth factor gene transfer remains unexplored. We tested the hypothesis that multiple growth factor gene transfer selectively modulates articular chondrocyte proliferation and matrix synthesis. We tested the hypothesis by delivering combinations of the transgenes encoding insulin-like growth factor I (IGF-I), fibroblast growth factor-2 (FGF-2), transforming growth factor beta1 (TGF-β1), bone morphogenetic protein-2 (BMP-2), and bone morphogenetic protien-7 (BMP-7) to articular chondrocytes and measured changes in the production of DNA, glycosaminoglycan, and collagen. The transgenes differentially regulated all these chondrocyte activities. In concert, the transgenes interacted to generate widely divergent responses from the cells. These interactions ranged from inhibitory to synergistic. The transgene pair encoding IGF-I and FGF-2 maximized cell proliferation. The three-transgene group encoding IGF-I, BMP-2, and BMP-7 maximized matrix production and also optimized the balance between cell proliferation and matrix production. These data demonstrate an approach to articular chondrocyte regulation that may be tailored to stimulate specific cell functions, and suggest that certain growth factor gene combinations have potential value for cell-based articular cartilage repair. Copyright © 2012 Wiley Periodicals, Inc.

Leukocyte- and platelet-rich fibrin (L-PRF) for long-term delivery of growth factor in rotator cuff repair: review, preliminary results and future directions.

PubMed

Zumstein, Matthias A; Berger, Simon; Schober, Martin; Boileau, Pascal; Nyffeler, Richard W; Horn, Michael; Dahinden, Clemens A

2012-06-01

Surgical repair of the rotator cuff repair is one of the most common procedures in orthopedic surgery. Despite it being the focus of much research, the physiological tendon-bone insertion is not recreated following repair and there is an anatomic non-healing rate of up to 94%. During the healing phase, several growth factors are upregulated that induce cellular proliferation and matrix deposition. Subsequently, this provisional matrix is replaced by the definitive matrix. Leukocyte- and platelet-rich fibrin (L-PRF) contain growth factors and has a stable dense fibrin matrix. Therefore, use of LPRF in rotator cuff repair is theoretically attractive. The aim of the present study was to determine 1) the optimal protocol to achieve the highest leukocyte content; 2) whether L-PRF releases growth factors in a sustained manner over 28 days; 3) whether standard/gelatinous or dry/compressed matrix preparation methods result in higher growth factor concentrations. 1) The standard L-PRF centrifugation protocol with 400 x g showed the highest concentration of platelets and leukocytes. 2) The L-PRF clots cultured in medium showed a continuous slow release with an increase in the absolute release of growth factors TGF-β1, VEGF and MPO in the first 7 days, and for IGF1, PDGF-AB and platelet activity (PF4=CXCL4) in the first 8 hours, followed by a decrease to close to zero at 28 days. Significantly higher levels of growth factor were expressed relative to the control values of normal blood at each culture time point. 3) Except for MPO and the TGFβ-1, there was always a tendency towards higher release of growth factors (i.e., CXCL4, IGF-1, PDGF-AB, and VEGF) in the standard/gelatinous- compared to the dry/compressed group. L-PRF in its optimal standard/gelatinous-type matrix can store and deliver locally specific healing growth factors for up to 28 days and may be a useful adjunct in rotator cuff repair.

Uncertainty assessment of source attribution of PM(2.5) and its water-soluble organic carbon content using different biomass burning tracers in positive matrix factorization analysis--a case study in Beijing, China.

PubMed

Tao, Jun; Zhang, Leiming; Zhang, Renjian; Wu, Yunfei; Zhang, Zhisheng; Zhang, Xiaoling; Tang, Yixi; Cao, Junji; Zhang, Yuanhang

2016-02-01

Daily PM2.5 samples were collected at an urban site in Beijing during four one-month periods in 2009-2010, with each period in a different season. Samples were subject to chemical analysis for various chemical components including major water-soluble ions, organic carbon (OC) and water-soluble organic carbon (WSOC), element carbon (EC), trace elements, anhydrosugar levoglucosan (LG), and mannosan (MN). Three sets of source profiles of PM2.5 were first identified through positive matrix factorization (PMF) analysis using single or combined biomass tracers - non-sea salt potassium (nss-K(+)), LG, and a combination of nss-K(+) and LG. The six major source factors of PM2.5 included secondary inorganic aerosol, industrial pollution, soil dust, biomass burning, traffic emission, and coal burning, which were estimated to contribute 31±37%, 39±28%, 14±14%, 7±7%, 5±6%, and 4±8%, respectively, to PM2.5 mass if using the nss-K(+) source profiles, 22±19%, 29±17%, 20±20%, 13±13%, 12±10%, and 4±6%, respectively, if using the LG source profiles, and 21±17%, 31±18%, 19±19%, 11±12%, 14±11%, and 4±6%, respectively, if using the combined nss-K(+) and LG source profiles. The uncertainties in the estimation of biomass burning contributions to WSOC due to the different choices of biomass burning tracers were around 3% annually and up to 24% seasonally in terms of absolute percentage contributions, or on a factor of 1.7 annually and up to a factor of 3.3 seasonally in terms of the actual concentrations. The uncertainty from the major source (e.g. industrial pollution) was on a factor of 1.9 annually and up to a factor of 2.5 seasonally in the estimated WSOC concentrations. Copyright © 2015 Elsevier B.V. All rights reserved.

Modeling analysis on germination and seedling growth using ultrasound seed pretreatment in switchgrass.

PubMed

Wang, Quanzhen; Chen, Guo; Yersaiyiti, Hayixia; Liu, Yuan; Cui, Jian; Wu, Chunhui; Zhang, Yunwei; He, Xueqing

2012-01-01

Switchgrass is a perennial C4 plant with great potential as a bioenergy source and, thus, a high demand for establishment from seed. This research investigated the effects of ultrasound treatment on germination and seedling growth in switchgrass. Using an orthogonal matrix design, conditions for the ultrasound pretreatment in switchgrass seed, including sonication time (factor A), sonication temperature (factor B) and ultrasound output power (factor C), were optimized for germinating and stimulating seedling growth (indicated as plumular and radicular lengths) through modeling analysis. The results indicate that sonication temperature (B) was the most effective factor for germination, whereas output power (C) had the largest effect on seedling growth when ultrasound treatment was used. Combined with the analyses of range, variance and models, the final optimal ultrasonic treatment conditions were sonication for 22.5 min at 39.7°C and at an output power of 348 W, which provided the greatest germination percentage and best seedling growth. For this study, the orthogonal matrix design was an efficient method for optimizing the conditions of ultrasound seed treatment on switchgrass. The electrical conductivity of seed leachates in three experimental groups (control, soaked in water only, and ultrasound treatment) was determined to investigate the effects of ultrasound on seeds and eliminate the effect of water in the ultrasound treatments. The results showed that the electrical conductivity of seed leachates during either ultrasound treatment or water bath treatment was significantly higher than that of the control, and that the ultrasound treatment had positive effects on switchgrass seeds.

Simultaneous tensor decomposition and completion using factor priors.

PubMed

Chen, Yi-Lei; Hsu, Chiou-Ting; Liao, Hong-Yuan Mark

2014-03-01

The success of research on matrix completion is evident in a variety of real-world applications. Tensor completion, which is a high-order extension of matrix completion, has also generated a great deal of research interest in recent years. Given a tensor with incomplete entries, existing methods use either factorization or completion schemes to recover the missing parts. However, as the number of missing entries increases, factorization schemes may overfit the model because of incorrectly predefined ranks, while completion schemes may fail to interpret the model factors. In this paper, we introduce a novel concept: complete the missing entries and simultaneously capture the underlying model structure. To this end, we propose a method called simultaneous tensor decomposition and completion (STDC) that combines a rank minimization technique with Tucker model decomposition. Moreover, as the model structure is implicitly included in the Tucker model, we use factor priors, which are usually known a priori in real-world tensor objects, to characterize the underlying joint-manifold drawn from the model factors. By exploiting this auxiliary information, our method leverages two classic schemes and accurately estimates the model factors and missing entries. We conducted experiments to empirically verify the convergence of our algorithm on synthetic data and evaluate its effectiveness on various kinds of real-world data. The results demonstrate the efficacy of the proposed method and its potential usage in tensor-based applications. It also outperforms state-of-the-art methods on multilinear model analysis and visual data completion tasks.

Semileptonic decays of B and D mesons in the light-front formalism

NASA Astrophysics Data System (ADS)

Jaus, W.

1990-06-01

The light-front formalism is used to present a relativistic calculation of form factors for semileptonic D and B decays in the constituent quark model. The quark-antiquark wave functions of the mesons can be obtained, in principle, from an analysis of the meson spectrum, but are approximated in this work by harmonic-oscillator wave functions. The predictions of the model are consistent with the experimental data for B decays. The Kobayashi-Maskawa (KM) matrix element ||Vcs|| is determined by a comparison of the experimental and theoretical rates for D0-->K-e+ν, and is consistent with a unitary KM matrix for three families. The predictions for D-->K* transitions are in conflict with the data.

Physical principles of monolithic high-contrast gratings

NASA Astrophysics Data System (ADS)

Dems, Maciej

2017-02-01

In this work I present visually the results of a numerical analysis of the transition between classical High-Contrast Gratings (HCGs) and Monolithic High-Contrast Gratings (MHCGs) and I identify the source of the differences between the scatterless reflection peaks and those that either show strong scattering or do not occur in MHCGs. I show that the key property of MHCGs is the independence of the peak reflectivity wavelength on the substrate refractive index, which results from the modal interference inside the grating and the special form of its impedance/admittance matrix. This form of matrix can be obtained for any wavelength and in almost any material system by tuning the geometrical parameters of the grating—its pitch, fill-factor, and height.

Solution algorithms for nonlinear transient heat conduction analysis employing element-by-element iterative strategies

NASA Technical Reports Server (NTRS)

Winget, J. M.; Hughes, T. J. R.

1985-01-01

The particular problems investigated in the present study arise from nonlinear transient heat conduction. One of two types of nonlinearities considered is related to a material temperature dependence which is frequently needed to accurately model behavior over the range of temperature of engineering interest. The second nonlinearity is introduced by radiation boundary conditions. The finite element equations arising from the solution of nonlinear transient heat conduction problems are formulated. The finite element matrix equations are temporally discretized, and a nonlinear iterative solution algorithm is proposed. Algorithms for solving the linear problem are discussed, taking into account the form of the matrix equations, Gaussian elimination, cost, and iterative techniques. Attention is also given to approximate factorization, implementational aspects, and numerical results.

EFFECT OF GROWTH FACTOR-FIBRONECTIN MATRIX INTERACTION ON RAT TYPE II CELL ADHESION AND DNA SYTHESIS

EPA Science Inventory

ABSTRACT

Type II cells attach, migrate and proliferate on a provisional fibronectin-rich matrix during alveolar wall repair after lung injury. The combination of cell-substratum interactions via integrin receptors and exposure to local growth factors are likely to initiat...

Computation of the Distribution of the Fiber-Matrix Interface Cracks in the Edge Trimming of CFRP

NASA Astrophysics Data System (ADS)

Wang, Fu-ji; Zhang, Bo-yu; Ma, Jian-wei; Bi, Guang-jian; Hu, Hai-bo

2018-04-01

Edge trimming is commonly used to bring the CFRP components to right dimension and shape in aerospace industries. However, various forms of undesirable machining damage occur frequently which will significantly decrease the material performance of CFRP. The damage is difficult to predict and control due to the complicated changing laws, causing unsatisfactory machining quality of CFRP components. Since the most of damage has the same essence: the fiber-matrix interface cracks, this study aims to calculate the distribution of them in edge trimming of CFRP, thereby to obtain the effects of the machining parameters, which could be helpful to guide the optimal selection of the machining parameters in engineering. Through the orthogonal cutting experiments, the quantitative relation between the fiber-matrix interface crack depth and the fiber cutting angle, cutting depth as well as cutting speed is established. According to the analysis on material removal process on any location of the workpiece in edge trimming, the instantaneous cutting parameters are calculated, and the formation process of the fiber-matrix interface crack is revealed. Finally, the computational method for the fiber-matrix interface cracks in edge trimming of CFRP is proposed. Upon the computational results, it is found that the fiber orientations of CFRP workpieces is the most significant factor on the fiber-matrix interface cracks, which can not only change the depth of them from micrometers to millimeters, but control the distribution image of them. Other machining parameters, only influence the fiber-matrix interface cracks depth but have little effect on the distribution image.

Z-sinapinic acid: the change of the stereochemistry of cinnamic acids as rational synthesis of a new matrix for carbohydrate MALDI-MS analysis.

PubMed

Salum, María L; Itovich, Lucia M; Erra-Balsells, Rosa

2013-11-01

Successful application of matrix-assisted laser desorption/ionization (MALDI) MS started with the introduction of efficient matrices such as cinnamic acid derivatives (i.e. 3,5-dimethoxy-4-hydroxycinnamic acid, SA; α-cyano-4-hydroxycinnamic acid). Since the empirical founding of these matrices, other commercial available cinnamic acids with different nature and location of substituents at benzene ring were attempted. Rational design and synthesis of new cinnamic acids have been recently described too. Because the presence of a rigid double bond in its molecule structure, cinnamic acids can exist as two different geometric isomers, the E-form and Z-form. Commercial available cinnamic acids currently used as matrices are the geometric isomers trans or E (E-cinnamic and trans-cinnamic acids). As a new rational design of MALDI matrices, Z-cinnamic acids were synthesized, and their properties as matrices were studied. Their performance was compared with that of the corresponding E-isomer and classical crystalline matrices (3,5-dihydroxybenzoic acid; norharmane) in the analysis of neutral/sulfated carbohydrates. Herein, we demonstrate the outstanding performance for Z-SA. Sulfated oligosaccharides were detected in negative ion mode, and the dissociation of sulfate groups was almost suppressed. Additionally, to better understand the quite different performance of each geometric isomer as matrix, the physical and morphological properties as well as the photochemical stability in solid state were studied. The influence of the E/Z photoisomerization of the matrix during MALDI was evaluated. Finally, molecular modeling (density functional theory study) of the optimized geometry and stereochemistry of E-cinnamic and Z-cinnamic acids revealed some factors governing the analyte-matrix interaction. Copyright © 2013 John Wiley & Sons, Ltd.

Positive matrix factorization of PM2.5 - eliminating the effects of gas/particle partitioning of semivolatile organic compounds.

PubMed

Xie, M; Barsanti, K C; Hannigan, M P; Dutton, S J; Vedal, S

2013-01-01

Gas-phase concentrations of semi-volatile organic compounds (SVOCs) were calculated from gas/particle (G/P) partitioning theory using their measured particle-phase concentrations. The particle-phase data were obtained from an existing filter measurement campaign (27 January 2003-2 October 2005) as a part of the Denver Aerosol Sources and Health (DASH) study, including 970 observations of 71 SVOCs (Xie et al., 2013). In each compound class of SVOCs, the lighter species (e.g. docosane in n alkanes, fluoranthene in PAHs) had higher total concentrations (gas + particle phase) and lower particle-phase fractions. The total SVOC concentrations were analyzed using positive matrix factorization (PMF). Then the results were compared with source apportionment results where only particle-phase SVOC concentrations were used (particle only-based study; Xie et al., 2013). For the particle only-based PMF analysis, the factors primarily associated with primary or secondary sources ( n alkane, EC/sterane and inorganic ion factors) exhibit similar contribution time series ( r = 0.92-0.98) with their corresponding factors ( n alkane, sterane and nitrate+sulfate factors) in the current work. Three other factors (light n alkane/PAH, PAH and summer/odd n alkane factors) are linked with pollution sources influenced by atmospheric processes (e.g. G/P partitioning, photochemical reaction), and were less correlated ( r = 0.69-0.84) with their corresponding factors (light SVOC, PAH and bulk carbon factors) in the current work, suggesting that the source apportionment results derived from particle-only SVOC data could be affected by atmospheric processes. PMF analysis was also performed on three temperature-stratified subsets of the total SVOC data, representing ambient sampling during cold (daily average temperature < 10 °C), warm (≥ 10 °C and ≤ 20 °C) and hot (> 20 °C) periods. Unlike the particle only-based study, in this work the factor characterized by the low molecular weight (MW) compounds (light SVOC factor) exhibited strong correlations ( r = 0.82-0.98) between the full data set and each sub-data set solution, indicating that the impacts of G/P partitioning on receptor-based source apportionment could be eliminated by using total SVOC concentrations.

Anisotropic resonator analysis using the Fourier-Bessel mode solver

NASA Astrophysics Data System (ADS)

Gauthier, Robert C.

2018-03-01

A numerical mode solver for optical structures that conform to cylindrical symmetry using Faraday's and Ampere's laws as starting expressions is developed when electric or magnetic anisotropy is present. The technique builds on the existing Fourier-Bessel mode solver which allows resonator states to be computed exploiting the symmetry properties of the resonator and states to reduce the matrix system. The introduction of anisotropy into the theoretical frame work facilitates the inclusion of PML borders permitting the computation of open ended structures and a better estimation of the resonator state quality factor. Matrix populating expressions are provided that can accommodate any material anisotropy with arbitrary orientation in the computation domain. Several example of electrical anisotropic computations are provided for rationally symmetric structures such as standard optical fibers, axial Bragg-ring fibers and bottle resonators. The anisotropy present in the materials introduces off diagonal matrix elements in the permittivity tensor when expressed in cylindrical coordinates. The effects of the anisotropy of computed states are presented and discussed.

UDU/T/ covariance factorization for Kalman filtering

NASA Technical Reports Server (NTRS)

Thornton, C. L.; Bierman, G. J.

1980-01-01

There has been strong motivation to produce numerically stable formulations of the Kalman filter algorithms because it has long been known that the original discrete-time Kalman formulas are numerically unreliable. Numerical instability can be avoided by propagating certain factors of the estimate error covariance matrix rather than the covariance matrix itself. This paper documents filter algorithms that correspond to the covariance factorization P = UDU(T), where U is a unit upper triangular matrix and D is diagonal. Emphasis is on computational efficiency and numerical stability, since these properties are of key importance in real-time filter applications. The history of square-root and U-D covariance filters is reviewed. Simple examples are given to illustrate the numerical inadequacy of the Kalman covariance filter algorithms; these examples show how factorization techniques can give improved computational reliability.

Resolving and quantifying overlapped chromatographic bands by transmutation

PubMed

Malinowski

2000-09-15

A new chemometric technique called "transmutation" is developed for the purpose of sharpening overlapped chromatographic bands in order to quantify the components. The "transmutation function" is created from the chromatogram of the pure component of interest, obtained from the same instrument, operating under the same experimental conditions used to record the unresolved chromatogram of the sample mixture. The method is used to quantify mixtures containing toluene, ethylbenzene, m-xylene, naphthalene, and biphenyl from unresolved chromatograms previously reported. The results are compared to those obtained using window factor analysis, rank annihilation factor analysis, and matrix regression analysis. Unlike the latter methods, the transmutation method is not restricted to two-dimensional arrays of data, such as those obtained from HPLC/DAD, but is also applicable to chromatograms obtained from single detector experiments. Limitations of the method are discussed.

[Quantitative surface analysis of Pt-Co, Cu-Au and Cu-Ag alloy films by XPS and AES].

PubMed

Li, Lian-Zhong; Zhuo, Shang-Jun; Shen, Ru-Xiang; Qian, Rong; Gao, Jie

2013-11-01

In order to improve the quantitative analysis accuracy of AES, We associated XPS with AES and studied the method to reduce the error of AES quantitative analysis, selected Pt-Co, Cu-Au and Cu-Ag binary alloy thin-films as the samples, used XPS to correct AES quantitative analysis results by changing the auger sensitivity factors to make their quantitative analysis results more similar. Then we verified the accuracy of the quantitative analysis of AES when using the revised sensitivity factors by other samples with different composition ratio, and the results showed that the corrected relative sensitivity factors can reduce the error in quantitative analysis of AES to less than 10%. Peak defining is difficult in the form of the integral spectrum of AES analysis since choosing the starting point and ending point when determining the characteristic auger peak intensity area with great uncertainty, and to make analysis easier, we also processed data in the form of the differential spectrum, made quantitative analysis on the basis of peak to peak height instead of peak area, corrected the relative sensitivity factors, and verified the accuracy of quantitative analysis by the other samples with different composition ratio. The result showed that the analytical error in quantitative analysis of AES reduced to less than 9%. It showed that the accuracy of AES quantitative analysis can be highly improved by the way of associating XPS with AES to correct the auger sensitivity factors since the matrix effects are taken into account. Good consistency was presented, proving the feasibility of this method.

Human umbilical cord derived matrix: A scaffold suitable for tissue engineering application.

PubMed

Dan, Pan; Velot, Émilie; Mesure, Benjamin; Groshenry, Guillaume; Bacharouche, Jalal; Decot, Véronique; Menu, Patrick

2017-01-01

Human tissue derived natural extracellular matrix (ECM) has great potential in tissue engineering. We sought to isolate extracellular matrix derived from human umbilical cord and test its potential in tissue engineering. An enzymatic method was applied to isolate and solubilized complete human umbilical cord derived matrix (hUCM). The obtained solution was analyzed for growth factors, collagen and residual DNA contents, then used to coat 2D and 3D surfaces for cell culture application. The hUCM was successfully isolated with trypsin digestion to acquire a solution containing various growth factors and collagen but no residual DNA. This hUCM solution can form a coating on 2D and 3D substrates suitable cell culture. We developed a new matrix derived from human source that can be further used in tissue engineering.

Joint Procrustes Analysis for Simultaneous Nonsingular Transformation of Component Score and Loading Matrices

ERIC Educational Resources Information Center

Adachi, Kohei

2009-01-01

In component analysis solutions, post-multiplying a component score matrix by a nonsingular matrix can be compensated by applying its inverse to the corresponding loading matrix. To eliminate this indeterminacy on nonsingular transformation, we propose Joint Procrustes Analysis (JPA) in which component score and loading matrices are simultaneously…

Enhanced expression by the brain matrix of P-glycoprotein in brain capillary endothelial cells.

PubMed

Tatsuta, T; Naito, M; Mikami, K; Tsuruo, T

1994-10-01

P-glycoprotein (PGP), an active efflux pump of antitumor agents in multidrug-resistant tumor cells, exists in brain capillary endothelium and could be functionally involved in the blood-brain barrier. To study the regulatory mechanism of PGP expression in brain capillary endothelium, various mouse tissue matrices were tested for their abilities to enhance the expression of PGP in mouse brain capillary endothelial cells (MBEC), which express relatively small amounts of PGP. Of the four tissue matrices we examined, PGP expression in MBEC cultured on the brain matrix increased 2.0-fold. The PGP-inducing activity was similarly detected in bovine brain matrix, and the activity was enriched in the fraction of pl 9.0 by isoelectric focusing. The fraction, named PIC-fraction (PGP-inducing component), increased the PGP expression in MBEC 3.5-fold. By Northern blot analysis, a 3.3-fold enhancement of mdr gene expression was observed in MBEC cultured on the PIC-fraction. The PGP-inducing activity of the PIC-fraction was reduced by the treatment with trypsin but not with collagenase, suggesting that a proteinaceous factor distinct from type I collagen might be responsible for the PGP-inducing activity of PIC-fraction. Although the PIC-fraction increased the PGP expression in other mouse brain capillary endothelial cells, the PIC-fraction did not increase PGP expression in mouse aortic endothelial cells and KB carcinoma cell lines expressing various amounts of PGP. These observations suggest that PGP expression in brain capillary endothelium is specifically regulated by a tissue-specific factor in the brain matrix.

Muscle-tendon units localization and activation level analysis based on high-density surface EMG array and NMF algorithm

NASA Astrophysics Data System (ADS)

Huang, Chengjun; Chen, Xiang; Cao, Shuai; Zhang, Xu

2016-12-01

Objective. Some skeletal muscles can be subdivided into smaller segments called muscle-tendon units (MTUs). The purpose of this paper is to propose a framework to locate the active region of the corresponding MTUs within a single skeletal muscle and to analyze the activation level varieties of different MTUs during a dynamic motion task. Approach. Biceps brachii and gastrocnemius were selected as targeted muscles and three dynamic motion tasks were designed and studied. Eight healthy male subjects participated in the data collection experiments, and 128-channel surface electromyographic (sEMG) signals were collected with a high-density sEMG electrode grid (a grid consists of 8 rows and 16 columns). Then the sEMG envelopes matrix was factorized into a matrix of weighting vectors and a matrix of time-varying coefficients by nonnegative matrix factorization algorithm. Main results. The experimental results demonstrated that the weightings vectors, which represent invariant pattern of muscle activity across all channels, could be used to estimate the location of MTUs and the time-varying coefficients could be used to depict the variation of MTUs activation level during dynamic motion task. Significance. The proposed method provides one way to analyze in-depth the functional state of MTUs during dynamic tasks and thus can be employed on multiple noteworthy sEMG-based applications such as muscle force estimation, muscle fatigue research and the control of myoelectric prostheses. This work was supported by the National Nature Science Foundation of China under Grant 61431017 and 61271138.

Monocyte-specific Accessibility of a Matrix Attachment Region in the Tumor Necrosis Factor Locus*

PubMed Central

Biglione, Sebastian; Tsytsykova, Alla V.; Goldfeld, Anne E.

2011-01-01

Regulation of TNF gene expression is cell type- and stimulus-specific. We have previously identified highly conserved noncoding regulatory elements within DNase I-hypersensitive sites (HSS) located 9 kb upstream (HSS−9) and 3 kb downstream (HSS+3) of the TNF gene, which play an important role in the transcriptional regulation of TNF in T cells. They act as enhancers and interact with the TNF promoter and with each other, generating a higher order chromatin structure. Here, we report a novel monocyte-specific AT-rich DNase I-hypersensitive element located 7 kb upstream of the TNF gene (HSS−7), which serves as a matrix attachment region in monocytes. We show that HSS−7 associates with topoisomerase IIα (Top2) in vivo and that induction of endogenous TNF mRNA expression is suppressed by etoposide, a Top2 inhibitor. Moreover, Top2 binds to and cleaves HSS−7 in in vitro analysis. Thus, HSS−7, which is selectively accessible in monocytes, can tether the TNF locus to the nuclear matrix via matrix attachment region formation, potentially promoting TNF gene expression by acting as a Top2 substrate. PMID:22027829

Solute Migration from the Aquifer Matrix into a Solution Conduit and the Reverse.

PubMed

Li, Guangquan; Field, Malcolm S

2016-09-01

A solution conduit has a permeable wall allowing for water exchange and solute transfer between the conduit and its surrounding aquifer matrix. In this paper, we use Laplace Transform to solve a one-dimensional equation constructed using the Euler approach to describe advective transport of solute in a conduit, a production-value problem. Both nonuniform cross-section of the conduit and nonuniform seepage at the conduit wall are considered in the solution. Physical analysis using the Lagrangian approach and a lumping method is performed to verify the solution. Two-way transfer between conduit water and matrix water is also investigated by using the solution for the production-value problem as a first-order approximation. The approximate solution agrees well with the exact solution if dimensionless travel time in the conduit is an order of magnitude smaller than unity. Our analytical solution is based on the assumption that the spatial and/or temporal heterogeneity in the wall solute flux is the dominant factor in the spreading of spring-breakthrough curves, and conduit dispersion is only a secondary mechanism. Such an approach can lead to the better understanding of water exchange and solute transfer between conduits and aquifer matrix. Euler and Lagrangian approaches are used to solve transport in conduit. Two-way transfer between conduit and matrix is investigated. The solution is applicable to transport in conduit of persisting solute from matrix. © 2016, National Ground Water Association.

Composition of fibrin glues significantly influences axial vascularization and degradation in isolation chamber model.

PubMed

Arkudas, Andreas; Pryymachuk, Galyna; Hoereth, Tobias; Beier, Justus P; Polykandriotis, Elias; Bleiziffer, Oliver; Gulle, Heinz; Horch, Raymund E; Kneser, Ulrich

2012-07-01

In this study, different fibrin sealants with varying concentrations of the fibrin components were evaluated in terms of matrix degradation and vascularization in the arteriovenous loop (AVL) model of the rat. An AVL was placed in a Teflon isolation chamber filled with 500 μl fibrin gel. The matrix was composed of commercially available fibrin gels, namely Beriplast (Behring GmbH, Marburg, Germany) (group A), Evicel (Omrix Biopharmaceuticals S.A., Somerville, New Jersey, USA) (group B), Tisseel VH S/D (Baxter, Vienna, Austria) with a thrombin concentration of 4 IU/ml and a fibrinogen concentration of 80 mg/ml [Tisseel S F80 (Baxter), group C] and with an fibrinogen concentration of 20 mg/ml [Tisseel S F20 (Baxter), group D]. After 2 and 4 weeks, five constructs per group and time point were investigated using micro-computed tomography, and histological and morphometrical analysis techniques. The aprotinin, factor XIII and thrombin concentration did not affect the degree of clot degradation. An inverse relationship was found between fibrin matrix degradation and sprouting of blood vessels. By reducing the fibrinogen concentration in group D, a significantly decreased construct weight and an increased generation of vascularized connective tissue were detected. There was an inverse relationship between matrix degradation and vascularization detectable. Fibrinogen as the major matrix component showed a significant impact on the matrix properties. Alteration of fibrin gel properties might optimize formation of blood vessels.

Receptor control in mesenchymal stem cell engineering

NASA Astrophysics Data System (ADS)

Dalby, Matthew J.; García, Andrés J.; Salmeron-Sanchez, Manuel

2018-03-01

Materials science offers a powerful tool to control mesenchymal stem cell (MSC) growth and differentiation into functional phenotypes. A complex interplay between the extracellular matrix and growth factors guides MSC phenotypes in vivo. In this Review, we discuss materials-based bioengineering approaches to direct MSC fate in vitro and in vivo, mimicking cell-matrix-growth factor crosstalk. We first scrutinize MSC-matrix interactions and how the properties of a material can be tailored to support MSC growth and differentiation in vitro, with an emphasis on MSC self-renewal mechanisms. We then highlight important growth factor signalling pathways and investigate various materials-based strategies for growth factor presentation and delivery. Integrin-growth factor crosstalk in the context of MSC engineering is introduced, and bioinspired material designs with the potential to control the MSC niche phenotype are considered. Finally, we summarize important milestones on the road to MSC engineering for regenerative medicine.

Heat transfer and fluid flow analysis of self-healing in metallic materials

NASA Astrophysics Data System (ADS)

Martínez Lucci, J.; Amano, R. S.; Rohatgi, P. K.

2017-03-01

This paper explores imparting self-healing characteristics to metal matrices similar to what are observed in biological systems and are being developed for polymeric materials. To impart self-healing properties to metal matrices, a liquid healing method was investigated; the met hod consists of a container filled with low melting alloy acting as a healing agent, embedded into a high melting metal matrix. When the matrix is cracked; self-healing is achieved by melting the healing agent allowing the liquid metal to flow into the crack. Upon cooling, solidification of the healing agent occurs and seals the crack. The objective of this research is to investigate the fluid flow and heat transfer to impart self-healing property to metal matrices. In this study, a dimensionless healing factor, which may help predict the possibility of healing is proposed. The healing factor is defined as the ratio of the viscous forces and the contact area of liquid metal and solid which prevent flow, and volume expansion, density, and velocity of the liquid metal, gravity, crack size and orientation which promote flow. The factor incorporates the parameters that control self-healing mechanism. It was observed that for lower values of the healing factor, the liquid flows, and for higher values of healing factor, the liquid remains in the container and healing does not occur. To validate and identify the critical range of the healing factor, experiments and simulations were performed for selected combinations of healing agents and metal matrices. The simulations were performed for three-dimensional models and a commercial software 3D Ansys-Fluent was used. Three experimental methods of synthesis of self-healing composites were used. The first method consisted of creating a hole in the matrices, and liquid healing agent was poured into the hole. The second method consisted of micro tubes containing the healing agent, and the third method consisted of incorporating micro balloons containing the healing agent in the matrix. The observed critical range of the healing factor is between 407 and 495; only for healing factor values below 407 healing was observed in the matrices.

A plasma-based biomatrix mixed with endothelial progenitor cells and keratinocytes promotes matrix formation, angiogenesis, and reepithelialization in full-thickness wounds.

PubMed

Vermeulen, Pieter; Dickens, Stijn; Degezelle, Karlien; Van den Berge, Stefaan; Hendrickx, Benoit; Vranckx, Jan Jeroen

2009-07-01

In search of an autologous vascularized skin substitute, we treated full-thickness wounds (FTWs) with autologous platelet-rich plasma gel (APG) in which we embedded endothelial progenitor cells (EPCs) and basal cell keratinocytes (KCs). We cultivated autologous KCs in low-serum conditions and expanded autologous EPCs from venous blood. FTWs (n = 55) were created on the backs of four pigs, covered with wound chambers, and randomly assigned to the following treatments: (1) APG, (2) APG + KCs, (3) APG + EPCs, (4) APG + KCs + EPCs, and (5) saline. All wounds were biopsied to measure neovascularization (lectin Bandeiraea Simplicifolia-1 (BS-1), alpha smooth muscle actin [alphaSMA], and membrane type 1 matrix metalloproteinase (MT1-MMP)), matrix deposition (fibronectin, collagen type I/III, and alphavbeta3), and reepithelialization. Wound fluids were analyzed for protein expression. All APG-treated wounds showed more vascular structures (p < 0.001), and the addition of EPCs further improved neovascularization, as confirmed by higher lectin, alphaSMA, and MT1-MMP. APG groups had higher collagen I/III (p < 0.05), alphavbeta3, and fibronectin content (p < 0.001), and they exhibited higher concentrations of platelet-derived growth factor subunit bb, basic fibroblast growth factor, hepatocyte growth factor, insulin growth factor-1, transforming growth factor-beta1 and -beta3, matrix metalloproteinase-1 and -z9, and tissue-inhibiting matrix metalloproteinase-1 and -2. Applying APG + KCs resulted in the highest reepithelialization rates (p < 0.001). No differences were found for wound contraction by planimetry. In this porcine FTW model, APG acts as a supportive biomatrix that, along with the embedded cells, improves extracellular matrix organization, promotes angiogenesis, and accelerates reepithelialization.

Ranking the strategies for Indian medical tourism sector through the integration of SWOT analysis and TOPSIS method.

PubMed

Ajmera, Puneeta

2017-10-09

Purpose Organizations have to evaluate their internal and external environments in this highly competitive world. Strengths, weaknesses, opportunities and threats (SWOT) analysis is a very useful technique which analyzes the strengths, weaknesses, opportunities and threats of an organization for taking strategic decisions and it also provides a foundation for the formulation of strategies. But the drawback of SWOT analysis is that it does not quantify the importance of individual factors affecting the organization and the individual factors are described in brief without weighing them. Because of this reason, SWOT analysis can be integrated with any multiple attribute decision-making (MADM) technique like the technique for order preference by similarity to ideal solution (TOPSIS), analytical hierarchy process, etc., to evaluate the best alternative among the available strategic alternatives. The paper aims to discuss these issues. Design/methodology/approach In this study, SWOT analysis is integrated with a multicriteria decision-making technique called TOPSIS to rank different strategies for Indian medical tourism in order of priority. Findings SO strategy (providing best facilitation and care to the medical tourists at par to developed countries) is the best strategy which matches with the four elements of S, W, O and T of SWOT matrix and 35 strategic indicators. Practical implications This paper proposes a solution based on a combined SWOT analysis and TOPSIS approach to help the organizations to evaluate and select strategies. Originality/value Creating a new technology or administering a new strategy always has some degree of resistance by employees. To minimize resistance, the author has used TOPSIS as it involves group thinking, requiring every manager of the organization to analyze and evaluate different alternatives and average measure of each parameter in final decision matrix.

Simultaneous factor analysis of organic particle and gas mass spectra: AMS and PTR-MS measurements at an urban site

NASA Astrophysics Data System (ADS)

Slowik, J. G.; Vlasenko, A.; McGuire, M.; Evans, G. J.; Abbatt, J. P. D.

2009-03-01

During the winter component of the SPORT (Seasonal Particle Observations in the Region of Toronto) field campaign, particulate non-refractory chemical composition and concentration of selected volatile organic compounds (VOCs) were measured by an Aerodyne time-of-flight aerosol mass spectrometer (AMS) and a proton transfer reaction-mass spectrometer (PTR-MS), respectively. Sampling was performed in downtown Toronto ~15 m from a major road. The mass spectra from the AMS and PTR-MS were combined into a unified dataset, which was analyzed using positive matrix factorization (PMF). The two instruments were given equal weight in the PMF analysis by application of a scaling factor to the uncertainties of each instrument. A residual based metric, Δesc, was used to evaluate the relative weight. The PMF analysis yielded a 5-factor solution that included factors characteristic of regional transport, local traffic emissions, charbroiling, and oxidative processing. The unified dataset provides information on particle and VOC sources and atmospheric processing that cannot be obtained from the datasets of the individual instruments, such as apportionment of oxygenated VOCs to direct emission sources vs. secondary reaction products, improved correlation of oxygenated aerosol factors with photochemical age, and increased detail regarding the composition of oxygenated organic aerosol factors. This analysis represents the first application of PMF to a unified AMS/PTR-MS dataset.

LC-MS/MS signal suppression effects in the analysis of pesticides in complex environmental matrices.

PubMed

Choi, B K; Hercules, D M; Gusev, A I

2001-02-01

The application of LC separation and mobile phase additives in addressing LC-MS/MS matrix signal suppression effects for the analysis of pesticides in a complex environmental matrix was investigated. It was shown that signal suppression is most significant for analytes eluting early in the LC-MS analysis. Introduction of different buffers (e.g. ammonium formate, ammonium hydroxide, formic acid) into the LC mobile phase was effective in improving signal correlation between the matrix and standard samples. The signal improvement is dependent on buffer concentration as well as LC separation of the matrix components. The application of LC separation alone was not effective in addressing suppression effects when characterizing complex matrix samples. Overloading of the LC column by matrix components was found to significantly contribute to analyte-matrix co-elution and suppression of signal. This signal suppression effect can be efficiently compensated by 2D LC (LC-LC) separation techniques. The effectiveness of buffers and LC separation in improving signal correlation between standard and matrix samples is discussed.

Quantification of various growth factors in different demineralized bone matrix preparations.

PubMed

Wildemann, B; Kadow-Romacker, A; Haas, N P; Schmidmaier, G

2007-05-01

Besides autografts, allografts, and synthetic materials, demineralized bone matrix (DBM) is used for bone defect filling and treatment of non-unions. Different DBM formulations are introduced in clinic since years. However, little is known about the presents and quantities of growth factors in DBM. Aim of the present study was the quantification of eight growth factors important for bone healing in three different "off the shelf" DBM formulations, which are already in human use: DBX putty, Grafton DBM putty, and AlloMatrix putty. All three DBM formulations are produced from human donor tissue but they differ in the substitutes added. From each of the three products 10 different lots were analyzed. Protein was extracted from the samples with Guanidine HCL/EDTA method and human ELISA kits were used for growth factor quantification. Differences between the three different products were seen in total protein contend and the absolute growth factor values but also a large variability between the different lots was found. The order of the growth factors, however, is almost comparable between the materials. In the three investigated materials FGF basic and BMP-4 were not detectable in any analyzed sample. BMP-2 revealed the highest concentration extractable from the samples with approximately 3.6 microg/g tissue without a significant difference between the three DBM formulations. In DBX putty significantly more TGF-beta1 and FGFa were measurable compared to the two other DBMs. IGF-I revealed the significantly highest value in the AlloMatrix and PDGF in Grafton. No differences were accessed for VEGF. Due to the differences in the growth factor concentration between the individual samples, independently from the product formulation, further analyzes are required to optimize the clinical outcome of the used demineralized bone matrix. Copyright 2006 Wiley Periodicals, Inc.

Rephasing invariants of the Cabibbo-Kobayashi- Maskawa matrix

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pérez R, H.; Kielanowski, P., E-mail: kiel@fis.cinvestav.mx; Juárez W, S. R., E-mail: rebeca@esfm.ipn.mx

2016-03-15

The paper is motivated by the importance of the rephasing invariance of the CKM (Cabibbo-Kobayashi-Maskawa) matrix observables. These observables appear in the discussion of the CP violation in the standard model (Jarlskog invariant) and also in the renormalization group equations for the quark Yukawa couplings. Our discussion is based on the general phase invariant monomials built out of the CKM matrix elements and their conjugates. We show that there exist 30 fundamental phase invariant monomials and 18 of them are a product of 4 CKM matrix elements and 12 are a product of 6 CKM matrix elements. In the mainmore » theorem we show that a general rephasing invariant monomial can be expressed as a product of at most five factors: four of them are fundamental phase invariant monomials and the fifth factor consists of powers of squares of absolute values of the CKM matrix elements. We also show that the imaginary part of any rephasing invariant monomial is proportional to the Jarlskog’s invariant J or is 0.« less

Reusable launch vehicle model uncertainties impact analysis

NASA Astrophysics Data System (ADS)

Chen, Jiaye; Mu, Rongjun; Zhang, Xin; Deng, Yanpeng

2018-03-01

Reusable launch vehicle(RLV) has the typical characteristics of complex aerodynamic shape and propulsion system coupling, and the flight environment is highly complicated and intensely changeable. So its model has large uncertainty, which makes the nominal system quite different from the real system. Therefore, studying the influences caused by the uncertainties on the stability of the control system is of great significance for the controller design. In order to improve the performance of RLV, this paper proposes the approach of analyzing the influence of the model uncertainties. According to the typical RLV, the coupling dynamic and kinematics models are built. Then different factors that cause uncertainties during building the model are analyzed and summed up. After that, the model uncertainties are expressed according to the additive uncertainty model. Choosing the uncertainties matrix's maximum singular values as the boundary model, and selecting the uncertainties matrix's norm to show t how much the uncertainty factors influence is on the stability of the control system . The simulation results illustrate that the inertial factors have the largest influence on the stability of the system, and it is necessary and important to take the model uncertainties into consideration before the designing the controller of this kind of aircraft( like RLV, etc).

EVALUATION OF THE EXTRACELLULAR MATRIX OF INJURED SUPRASPINATUS IN RATS

PubMed Central

Almeida, Luiz Henrique Oliveira; Ikemoto, Roberto; Mader, Ana Maria; Pinhal, Maria Aparecida Silva; Munhoz, Bruna; Murachovsky, Joel

2016-01-01

ABSTRACT Objective: To evaluate the evolution of injuries of the supraspinatus muscle by immunohistochemistry (IHC) and anatomopathological analysis in animal model (Wistar rats). Methods: Twenty-five Wistar rats were submitted to complete injury of the supraspinatus tendon, then subsequently sacrificed in groups of five animals at the following periods: immediately after the injury, 24h after the injury, 48h after, 30 days after and three months after the injury. All groups underwent histological and IHC analysis. Results: Regarding vascular proliferation and inflammatory infiltrate, we found a statistically significant difference between groups 1(control group) and 2 (24h after injury). IHC analysis showed that expression of vascular endothelial growth factor (VEGF) showed a statistically significant difference between groups 1 and 2, and collagen type 1 (Col-1) evaluation presented a statistically significant difference between groups 1 and 4. Conclusion: We observed changes in the extracellular matrix components compatible with remodeling and healing. Remodeling is more intense 24h after injury. However, VEGF and Col-1 are substantially increased at 24h and 30 days after the injury, respectively. Level of Evidence I, Experimental Study. PMID:26997907

Quantitative image analysis for investigating cell-matrix interactions

NASA Astrophysics Data System (ADS)

Burkel, Brian; Notbohm, Jacob

2017-07-01

The extracellular matrix provides both chemical and physical cues that control cellular processes such as migration, division, differentiation, and cancer progression. Cells can mechanically alter the matrix by applying forces that result in matrix displacements, which in turn may localize to form dense bands along which cells may migrate. To quantify the displacements, we use confocal microscopy and fluorescent labeling to acquire high-contrast images of the fibrous material. Using a technique for quantitative image analysis called digital volume correlation, we then compute the matrix displacements. Our experimental technology offers a means to quantify matrix mechanics and cell-matrix interactions. We are now using these experimental tools to modulate mechanical properties of the matrix to study cell contraction and migration.

Content analysis of 100 consecutive media reports of amusement ride accidents.

PubMed

Woodcock, Kathryn

2008-01-01

Accident investigations influence public perceptions and safety management strategies by determining the amount and type of information learned about the accident. To examine the factors considered in investigations, this study used a content analysis of 100 consecutive media reports of amusement ride accidents from an online media archive. Fatalities were overrepresented in the media dataset compared with U.S. national estimates. For analysis of reports, a modified "Haddon matrix" was developed using human-factors categories. This approach was useful to show differences between the proportions and types of factors considered in the different accident stages and between employee and rider accidents. Employee injury accounts primarily referred to the employee's task and to the employee. Rider injury reports were primarily related to the ride device itself and rarely referred to the rider's "task", social influences, or the rider's own actions, and only some reference to their characteristics. Qualitatively, it was evident that more human factors analysis is required to augment scant pre-failure information about the task, social environment, and the person, to make that information available for prevention of amusement ride accidents. By design, this study reflected information reported by the media. Future work will use the same techniques with official reports.

Determining the trophic guilds of fishes and macroinvertebrates in a seagrass food web

USGS Publications Warehouse

Luczkovich, J.J.; Ward, G.P.; Johnson, J.C.; Christian, R.R.; Baird, D.; Neckles, H.; Rizzo, W.M.

2002-01-01

We established trophic guilds of macroinvertebrate and fish taxa using correspondence analysis and a hierarchical clustering strategy for a seagrass food web in winter in the northeastern Gulf of Mexico. To create the diet matrix, we characterized the trophic linkages of macroinvertebrate and fish taxa present in Halodule wrightii seagrass habitat areas within the St. Marks National Wildlife Refuge (Florida) using binary data, combining dietary links obtained from relevant literature for macroinvertebrates with stomach analysis of common fishes collected during January and February of 1994. Heirarchical average-linkage cluster analysis of the 73 taxa of fishes and macroinvertebrates in the diet matrix yielded 14 clusters with diet similarity ??? 0.60. We then used correspondence analysis with three factors to jointly plot the coordinates of the consumers (identified by cluster membership) and of the 33 food sources. Correspondence analysis served as a visualization tool for assigning each taxon to one of eight trophic guilds: herbivores, detritivores, suspension feeders, omnivores, molluscivores, meiobenthos consumers, macrobenthos consumers, and piscivores. These trophic groups, cross-classified with major taxonomic groups, were further used to develop consumer compartments in a network analysis model of carbon flow in this seagrass ecosystem. The method presented here should greatly improve the development of future network models of food webs by providing an objective procedure for aggregating trophic groups.

MATRIX FACTORIZATION-BASED DATA FUSION FOR GENE FUNCTION PREDICTION IN BAKER’S YEAST AND SLIME MOLD

PubMed Central

ŽITNIK, MARINKA; ZUPAN, BLAŽ

2014-01-01

The development of effective methods for the characterization of gene functions that are able to combine diverse data sources in a sound and easily-extendible way is an important goal in computational biology. We have previously developed a general matrix factorization-based data fusion approach for gene function prediction. In this manuscript, we show that this data fusion approach can be applied to gene function prediction and that it can fuse various heterogeneous data sources, such as gene expression profiles, known protein annotations, interaction and literature data. The fusion is achieved by simultaneous matrix tri-factorization that shares matrix factors between sources. We demonstrate the effectiveness of the approach by evaluating its performance on predicting ontological annotations in slime mold D. discoideum and on recognizing proteins of baker’s yeast S. cerevisiae that participate in the ribosome or are located in the cell membrane. Our approach achieves predictive performance comparable to that of the state-of-the-art kernel-based data fusion, but requires fewer data preprocessing steps. PMID:24297565

Evaluation of Yogurt Microstructure Using Confocal Laser Scanning Microscopy and Image Analysis.

PubMed

Skytte, Jacob L; Ghita, Ovidiu; Whelan, Paul F; Andersen, Ulf; Møller, Flemming; Dahl, Anders B; Larsen, Rasmus

2015-06-01

The microstructure of protein networks in yogurts defines important physical properties of the yogurt and hereby partly its quality. Imaging this protein network using confocal scanning laser microscopy (CSLM) has shown good results, and CSLM has become a standard measuring technique for fermented dairy products. When studying such networks, hundreds of images can be obtained, and here image analysis methods are essential for using the images in statistical analysis. Previously, methods including gray level co-occurrence matrix analysis and fractal analysis have been used with success. However, a range of other image texture characterization methods exists. These methods describe an image by a frequency distribution of predefined image features (denoted textons). Our contribution is an investigation of the choice of image analysis methods by performing a comparative study of 7 major approaches to image texture description. Here, CSLM images from a yogurt fermentation study are investigated, where production factors including fat content, protein content, heat treatment, and incubation temperature are varied. The descriptors are evaluated through nearest neighbor classification, variance analysis, and cluster analysis. Our investigation suggests that the texton-based descriptors provide a fuller description of the images compared to gray-level co-occurrence matrix descriptors and fractal analysis, while still being as applicable and in some cases as easy to tune. © 2015 Institute of Food Technologists®

[Mobbing: a meta-analysis and integrative model of its antecedents and consequences].

PubMed

Topa Cantisano, Gabriela; Depolo, Marco; Morales Domínguez, J Francisco

2007-02-01

Although mobbing has been extensively studied, empirical research has not led to firm conclusions regarding its antecedents and consequences, both at personal and organizational levels. An extensive literature search yielded 86 empirical studies with 93 samples. The matrix correlation obtained through meta-analytic techniques was used to test a structural equation model. Results supported hypotheses regarding organizational environmental factors as main predictors of mobbing.

A Multitrait (ADHD-IN, ADHD-HI, ODD toward Adults, Academic and Social Competence) by Multisource (Mothers and Fathers) Evaluation of the Invariance and Convergent/Discriminant Validity of the Child and Adolescent Disruptive Behavior Inventory with Thai Adolescents

ERIC Educational Resources Information Center

Burns, G. Leonard; Desmul, Chris; Walsh, James A.; Silpakit, Chatchawan; Ussahawanitchakit, Phapruke

2009-01-01

Confirmatory factor analysis was used with a multitrait (attention-deficit/hyperactivity disorder-inattention, attention-deficit/hyperactivity disorder-hyperactivity/impulsivity, oppositional defiant disorder toward adults, academic competence, and social competence) by multisource (mothers and fathers) matrix to test the invariance and…

Muscle synergies during bench press are reliable across days.

PubMed

Kristiansen, Mathias; Samani, Afshin; Madeleine, Pascal; Hansen, Ernst Albin

2016-10-01

Muscle synergies have been investigated during different types of human movement using nonnegative matrix factorization. However, there are not any reports available on the reliability of the method. To evaluate between-day reliability, 21 subjects performed bench press, in two test sessions separated by approximately 7days. The movement consisted of 3 sets of 8 repetitions at 60% of the three repetition maximum in bench press. Muscle synergies were extracted from electromyography data of 13 muscles, using nonnegative matrix factorization. To evaluate between-day reliability, we performed a cross-correlation analysis and a cross-validation analysis, in which the synergy components extracted in the first test session were recomputed, using the fixed synergy components from the second test session. Two muscle synergies accounted for >90% of the total variance, and reflected the concentric and eccentric phase, respectively. The cross-correlation values were strong to very strong (r-values between 0.58 and 0.89), while the cross-validation values ranged from substantial to almost perfect (ICC3, 1 values between 0.70 and 0.95). The present findings revealed that the same general structure of the muscle synergies was present across days and the extraction of muscle synergies is thus deemed reliable. Copyright © 2016 Elsevier Ltd. All rights reserved.

Bilinear Factor Matrix Norm Minimization for Robust PCA: Algorithms and Applications.

PubMed

Shang, Fanhua; Cheng, James; Liu, Yuanyuan; Luo, Zhi-Quan; Lin, Zhouchen

2017-09-04

The heavy-tailed distributions of corrupted outliers and singular values of all channels in low-level vision have proven effective priors for many applications such as background modeling, photometric stereo and image alignment. And they can be well modeled by a hyper-Laplacian. However, the use of such distributions generally leads to challenging non-convex, non-smooth and non-Lipschitz problems, and makes existing algorithms very slow for large-scale applications. Together with the analytic solutions to Lp-norm minimization with two specific values of p, i.e., p=1/2 and p=2/3, we propose two novel bilinear factor matrix norm minimization models for robust principal component analysis. We first define the double nuclear norm and Frobenius/nuclear hybrid norm penalties, and then prove that they are in essence the Schatten-1/2 and 2/3 quasi-norms, respectively, which lead to much more tractable and scalable Lipschitz optimization problems. Our experimental analysis shows that both our methods yield more accurate solutions than original Schatten quasi-norm minimization, even when the number of observations is very limited. Finally, we apply our penalties to various low-level vision problems, e.g. moving object detection, image alignment and inpainting, and show that our methods usually outperform the state-of-the-art methods.

PEDF Is Associated with the Termination of Chondrocyte Phenotype and Catabolism of Cartilage Tissue.

PubMed

Klinger, P; Lukassen, S; Ferrazzi, F; Ekici, A B; Hotfiel, T; Swoboda, B; Aigner, T; Gelse, K

2017-01-01

Objective. To investigate the expression and target genes of pigment epithelium-derived factor (PEDF) in cartilage and chondrocytes, respectively. Methods. We analyzed the expression pattern of PEDF in different human cartilaginous tissues including articular cartilage, osteophytic cartilage, and fetal epiphyseal and growth plate cartilage, by immunohistochemistry and quantitative real-time (qRT) PCR. Transcriptome analysis after stimulation of human articular chondrocytes with rhPEDF was performed by RNA sequencing (RNA-Seq) and confirmed by qRT-PCR. Results. Immunohistochemically, PEDF could be detected in transient cartilaginous tissue that is prone to undergo endochondral ossification, including epiphyseal cartilage, growth plate cartilage, and osteophytic cartilage. In contrast, PEDF was hardly detected in healthy articular cartilage and in the superficial zone of epiphyses, regions that are characterized by a permanent stable chondrocyte phenotype. RNA-Seq analysis and qRT-PCR demonstrated that rhPEDF significantly induced the expression of a number of matrix-degrading factors including SAA1, MMP1, MMP3, and MMP13. Simultaneously, a number of cartilage-specific genes including COL2A1, COL9A2, COMP, and LECT were among the most significantly downregulated genes. Conclusions. PEDF represents a marker for transient cartilage during all neonatal and postnatal developmental stages and promotes the termination of cartilage tissue by upregulation of matrix-degrading factors and downregulation of cartilage-specific genes. These data provide the basis for novel strategies to stabilize the phenotype of articular cartilage and prevent its degradation.

Stability-driven nonnegative matrix factorization to interpret spatial gene expression and build local gene networks.

PubMed

Wu, Siqi; Joseph, Antony; Hammonds, Ann S; Celniker, Susan E; Yu, Bin; Frise, Erwin

2016-04-19

Spatial gene expression patterns enable the detection of local covariability and are extremely useful for identifying local gene interactions during normal development. The abundance of spatial expression data in recent years has led to the modeling and analysis of regulatory networks. The inherent complexity of such data makes it a challenge to extract biological information. We developed staNMF, a method that combines a scalable implementation of nonnegative matrix factorization (NMF) with a new stability-driven model selection criterion. When applied to a set ofDrosophilaearly embryonic spatial gene expression images, one of the largest datasets of its kind, staNMF identified 21 principal patterns (PP). Providing a compact yet biologically interpretable representation ofDrosophilaexpression patterns, PP are comparable to a fate map generated experimentally by laser ablation and show exceptional promise as a data-driven alternative to manual annotations. Our analysis mapped genes to cell-fate programs and assigned putative biological roles to uncharacterized genes. Finally, we used the PP to generate local transcription factor regulatory networks. Spatially local correlation networks were constructed for six PP that span along the embryonic anterior-posterior axis. Using a two-tail 5% cutoff on correlation, we reproduced 10 of the 11 links in the well-studied gap gene network. The performance of PP with theDrosophiladata suggests that staNMF provides informative decompositions and constitutes a useful computational lens through which to extract biological insight from complex and often noisy gene expression data.

General Linewidth Formula for Steady-State Multimode Lasing in Arbitrary Cavities

NASA Astrophysics Data System (ADS)

Chong, Y. D.; Stone, A. Douglas

2012-08-01

A formula for the laser linewidth of arbitrary cavities in the multimode nonlinear regime is derived from a scattering analysis of the solutions to semiclassical laser theory. The theory generalizes previous treatments of the effects of gain and openness described by the Petermann factor. The linewidth is expressed using quantities based on the nonlinear scattering matrix, which can be computed from steady-state ab initio laser theory; unlike previous treatments, no passive cavity or phenomenological parameters are involved. We find that low cavity quality factor, combined with significant dielectric dispersion, can cause substantial deviations from the Shawlow-Townes-Petermann theory.

Analysis of photonic band gap in novel piezoelectric photonic crystal

NASA Astrophysics Data System (ADS)

Malar Kodi, A.; Doni Pon, V.; Joseph Wilson, K. S.

2018-03-01

The transmission properties of one-dimensional novel photonic crystal having silver-doped novel piezoelectric superlattice and air as the two constituent layers have been investigated by means of transfer matrix method. By changing the appropriate thickness of the layers and filling factor of nanocomposite system, the variation in the photonic band gap can be studied. It is found that the photonic band gap increases with the filling factor of the metal nanocomposite and with the thickness of the layer. These structures possess unique characteristics enabling one to operate as optical waveguides, selective filters, optical switches, integrated piezoelectric microactuators, etc.

Re-analysis of correlations among four impulsivity scales.

PubMed

Gallardo-Pujol, David; Andrés-Pueyo, Antonio

2006-08-01

Impulsivity plays a key role in normal and pathological behavior. Although there is some consensus about its conceptualization, there have been many attempts to build a multidimensional tool due to the lack of agreement in how to measure it. A recent study claimed support for a three-dimensional structure of impulsivity, however with weak empirical support. By re-analysing those data, a four-factor structure was found to describe the correlation matrix much better. The debate remains open and further research is needed to clarify the factor structure. The desirability of constructing new measures, perhaps analogously to the Wechsler Intelligence Scale, is emphasized.

Doubly Nonparametric Sparse Nonnegative Matrix Factorization Based on Dependent Indian Buffet Processes.

PubMed

Xuan, Junyu; Lu, Jie; Zhang, Guangquan; Xu, Richard Yi Da; Luo, Xiangfeng

2018-05-01

Sparse nonnegative matrix factorization (SNMF) aims to factorize a data matrix into two optimized nonnegative sparse factor matrices, which could benefit many tasks, such as document-word co-clustering. However, the traditional SNMF typically assumes the number of latent factors (i.e., dimensionality of the factor matrices) to be fixed. This assumption makes it inflexible in practice. In this paper, we propose a doubly sparse nonparametric NMF framework to mitigate this issue by using dependent Indian buffet processes (dIBP). We apply a correlation function for the generation of two stick weights associated with each column pair of factor matrices while still maintaining their respective marginal distribution specified by IBP. As a consequence, the generation of two factor matrices will be columnwise correlated. Under this framework, two classes of correlation function are proposed: 1) using bivariate Beta distribution and 2) using Copula function. Compared with the single IBP-based NMF, this paper jointly makes two factor matrices nonparametric and sparse, which could be applied to broader scenarios, such as co-clustering. This paper is seen to be much more flexible than Gaussian process-based and hierarchial Beta process-based dIBPs in terms of allowing the two corresponding binary matrix columns to have greater variations in their nonzero entries. Our experiments on synthetic data show the merits of this paper compared with the state-of-the-art models in respect of factorization efficiency, sparsity, and flexibility. Experiments on real-world data sets demonstrate the efficiency of this paper in document-word co-clustering tasks.

Toxoplasma infection and milk consumption: Meta-analysis of assumptions and evidences.

PubMed

Boughattas, Sonia

2017-09-02

Toxoplasmosis is the most widespread infection worldwide. It occurs within congenital contamination, organ transplant or immune system depression. Primary infection is mainly foodborne with the ingestion of raw or undercooked meat, unwashed fruit-vegetables, unhygienic water or contaminated milk. Gaps in current knowledge about the risk assessment of Toxoplasma gondii by milk consumption are noted. Contradictory data are observed within risk assessment of milk consumption and toxoplasmosis occurrence. While some papers reported positive correlations between drinking milk and infection transmission to human, other studies stated nonsignificant influence of milk or milk products consumption. New debate about the detection of the parasite in the milk matrix from different hosts raised interrogations. To figure out the real contribution and the potential correlations of milkborne way in toxoplasmic infection, meta-analysis approach was investigated. Overall analysis showed heterogeneous responses and led to state that statistically dairy matrix (other than milk), Bovidae products, agricultural population and countries in Africa, Europe and Southeast Asia are not linked to milkborne toxoplasmosis. The most involved factors are Capridae products, immune-depressed population and North America, Middle East, and Latin territories. The current work advanced those parameters that could affect the public health and should be envisioned in further epidemiological analysis.

Design and Analyze a New Measuring Lift Device for Fin Stabilizers Using Stiffness Matrix of Euler-Bernoulli Beam

PubMed Central

Liang, Lihua; Sun, Mingxiao; Shi, Hongyu; Luan, Tiantian

2017-01-01

Fin-angle feedback control is usually used in conventional fin stabilizers, and its actual anti-rolling effect is difficult to reach theoretical design requirements. Primarily, lift of control torque is a theoretical value calculated by static hydrodynamic characteristics of fin. However, hydrodynamic characteristics of fin are dynamic while fin is moving in waves. As a result, there is a large deviation between actual value and theoretical value of lift. Firstly, the reasons of deviation are analyzed theoretically, which could avoid a variety of interference factors and complex theoretical derivations. Secondly, a new device is designed for direct measurement of actual lift, which is composed of fin-shaft combined mechanism and sensors. This new device can make fin-shaft not only be the basic function of rotating fin, but also detect actual lift. Through analysis using stiffness matrix of Euler-Bernoulli beam, displacement of shaft-core end is measured instead of lift which is difficult to measure. Then quantitative relationship between lift and displacement is defined. Three main factors are analyzed with quantitative relationship. What is more, two installation modes of sensors and a removable shaft-end cover are proposed according to hydrodynamic characteristics of fin. Thus the new device contributes to maintenance and measurement. Lastly, the effectiveness and accuracy of device are verified by contrasting calculation and simulation on the basis of actual design parameters. And the new measuring lift method can be proved to be effective through experiments. The new device is achieved from conventional fin stabilizers. Accordingly, the reliability of original equipment is inherited. The alteration of fin stabilizers is minor, which is suitable for engineering application. In addition, the flexural properties of fin-shaft are digitized with analysis of stiffness matrix. This method provides theoretical support for engineering application by carrying out finite element analysis with computers. PMID:28046122

Failure of Non-Circular Composite Cylinders

NASA Technical Reports Server (NTRS)

Hyer, M. W.

2004-01-01

In this study, a progressive failure analysis is used to investigate leakage in internally pressurized non-circular composite cylinders. This type of approach accounts for the localized loss of stiffness when material failure occurs at some location in a structure by degrading the local material elastic properties by a certain factor. The manner in which this degradation of material properties takes place depends on the failure modes, which are determined by the application of a failure criterion. The finite-element code STAGS, which has the capability to perform progressive failure analysis using different degradation schemes and failure criteria, is utilized to analyze laboratory scale, graphite-epoxy, elliptical cylinders with quasi-isotropic, circumferentially-stiff, and axially-stiff material orthotropies. The results are divided into two parts. The first part shows that leakage, which is assumed to develop if there is material failure in every layer at some axial and circumferential location within the cylinder, does not occur without failure of fibers. Moreover before fibers begin to fail, only matrix tensile failures, or matrix cracking, takes place, and at least one layer in all three cylinders studied remain uncracked, preventing the formation of a leakage path. That determination is corroborated by the use of different degradation schemes and various failure criteria. Among the degradation schemes investigated are the degradation of different engineering properties, the use of various degradation factors, the recursive or non-recursive degradation of the engineering properties, and the degradation of material properties using different computational approaches. The failure criteria used in the analysis include the noninteractive maximum stress criterion and the interactive Hashin and Tsai-Wu criteria. The second part of the results shows that leakage occurs due to a combination of matrix tensile and compressive, fiber tensile and compressive, and inplane shear failure modes in all three cylinders. Leakage develops after a relatively low amount of fiber damage, at about the same pressure for three material orthotropies, and at approximately the same location.

Matrix detachment and proteasomal inhibitors diminish Sulf-2 expression in breast cancer cell lines and mouse xenografts

PubMed Central

Khurana, Ashwani; Jung-Beom, Deok; He, Xiaoping; Kim, Sung-Hoon; Busby, Robert C.; Lorenzon, Laura; Villa, Massimo; Baldi, Alfonso; Molina, Julian; Goetz, Matthew P.; Shridhar, Viji

2013-01-01

Sulfatase 2 (Sulf-2) has been previously shown to be upregulated in breast cancer. Sulf-2 removes sulfate moieties on heparan sulfate proteoglycans which in turn modulate heparin binding growth factor signaling. Here we report that matrix detachment resulted in decreased Sulf-2 expression in breast cancer cells and increased cleavage of poly ADP-ribose polymerase. Silencing of Sulf-2 promotes matrix detachment induced cell death in MCF10DCIS cells. In an attempt to identify Sulf-2 specific inhibitor, we found that proteasomal inhibitors such as MG132, Lactacystin and Bortezomib treatment abolished Sulf-2 expression in multiple breast cancer cell lines. Additionally, we show that Bortezomib treatment of MCF10DCIS cell xenografts in mouse mammary fat pads significantly reduced tumor size, caused massive apoptosis and more importantly reduced Sulf-2 levels in vivo. Finally, our immunohistochemistry analysis of Sulf-2 expression in cohort of patient derived breast tumors indicates that Sulf-2 is significantly upregulated in autologous metastatic lesions compared to primary tumors (p < 0.037, Pearson correlation, Chi-Square analysis). In all, our data suggest that Sulf-2 might play an important role in breast cancer progression from ductal carcinoma in situ into an invasive ductal carcinoma potentially by resisting cell death. PMID:23412907

Reconstructing impairment of secretory ameloblast function in porcine teeth by analysis of morphological alterations in dental enamel

PubMed Central

Witzel, Carsten; Kierdorf, Uwe; Dobney, Keith; Ervynck, Anton; Vanpoucke, Sofie; Kierdorf, Horst

2006-01-01

We studied the relationship between the macroscopic appearance of hypoplastic defects in the dental enamel of wild boar and domestic pigs, and microstructural enamel changes, at both the light and the scanning electron microscopic levels. Deviations from normal enamel microstructure were used to reconstruct the functional and related morphological changes of the secretory ameloblasts caused by the action of stress factors during amelogenesis. The deduced reaction pattern of the secretory ameloblasts can be grouped in a sequence of increasingly severe impairments of cell function. The reactions ranged from a slight enhancement of the periodicity of enamel matrix secretion, over a temporary reduction in the amount of secreted enamel matrix, with reduction of the distal portion of the Tomes' process, to either a temporary or a definite cessation of matrix formation. The results demonstrate that analysis of structural changes in dental enamel allows a detailed reconstruction of the reaction of secretory ameloblasts to stress events, enabling an assessment of duration and intensity of these events. Analysing the deviations from normal enamel microstructure provides a deeper insight into the cellular changes underlying the formation of hypoplastic enamel defects than can be achieved by mere inspection of tooth surface characteristics alone. PMID:16822273

[Tissue engineering of urinary bladder using acellular matrix].

PubMed

Glybochko, P V; Olefir, Yu V; Alyaev, Yu G; Butnaru, D V; Bezrukov, E A; Chaplenko, A A; Zharikova, T M

2017-04-01

Tissue engineering has become a new promising strategy for repairing damaged organs of the urinary system, including the bladder. The basic idea of tissue engineering is to integrate cellular technology and advanced bio-compatible materials to replace or repair tissues and organs. of the study is the objective reflection of the current trends and advances in tissue engineering of the bladder using acellular matrix through a systematic search of preclinical and clinical studies of interest. Relevant studies, including those on methods of tissue engineering of urinary bladder, was retrieved from multiple databases, including Scopus, Web of Science, PubMed, Embase. The reference lists of the retrieved review articles were analyzed for the presence of the missing relevant publications. In addition, a manual search for registered clinical trials was conducted in clinicaltrials.gov. Following the above search strategy, a total of 77 eligible studies were selected for further analysis. Studies differed in the types of animal models, supporting structures, cells and growth factors. Among those, studies using cell-free matrix were selected for a more detailed analysis. Partial restoration of urothelium layer was observed in most studies where acellular grafts were used for cystoplasty, but no the growth of the muscle layer was observed. This is the main reason why cellular structures are more commonly used in clinical practice.

Global financial indices and twitter sentiment: A random matrix theory approach

NASA Astrophysics Data System (ADS)

García, A.

2016-11-01

We use Random Matrix Theory (RMT) approach to analyze the correlation matrix structure of a collection of public tweets and the corresponding return time series associated to 20 global financial indices along 7 trading months of 2014. In order to quantify the collection of tweets, we constructed daily polarity time series from public tweets via sentiment analysis. The results from RMT analysis support the fact of the existence of true correlations between financial indices, polarities, and the mixture of them. Moreover, we found a good agreement between the temporal behavior of the extreme eigenvalues of both empirical data, and similar results were found when computing the inverse participation ratio, which provides an evidence about the emergence of common factors in global financial information whether we use the return or polarity data as a source. In addition, we found a very strong presumption that polarity Granger causes returns of an Indonesian index for a long range of lag trading days, whereas for Israel, South Korea, Australia, and Japan, the predictive information of returns is also presented but with less presumption. Our results suggest that incorporating polarity as a financial indicator may open up new insights to understand the collective and even individual behavior of global financial indices.

Texture analysis as a predictor of radiation-induced xerostomia in head and neck patients undergoing IMRT.

PubMed

Nardone, Valerio; Tini, Paolo; Nioche, Christophe; Mazzei, Maria Antonietta; Carfagno, Tommaso; Battaglia, Giuseppe; Pastina, Pierpaolo; Grassi, Roberta; Sebaste, Lucio; Pirtoli, Luigi

2018-06-01

Image texture analysis (TA) is a heterogeneity quantifying approach that cannot be appreciated by the naked eye, and early evidence suggests that TA has great potential in the field of oncology. The aim of this study is to evaluate parotid gland texture analysis (TA) combined with formal dosimetry as a factor for predicting severe late xerostomia in patients undergoing radiation therapy for head and neck cancers. We performed a retrospective analysis of patients treated at our Radiation Oncology Unit between January 2010 and December 2015, and selected the patients whose normal dose constraints for the parotid gland (mean dose < 26 Gy for the bilateral gland) could not be satisfied due to the presence of positive nodes close to the parotid glands. The parotid gland that showed the higher V30 was contoured on CT simulation and analysed with LifeX Software©. TA parameters included features of grey-level co-occurrence matrix (GLCM), neighbourhood grey-level dependence matrix (NGLDM), grey-level run length matrix (GLRLM), grey-level zone length matrix (GLZLM), sphericity, and indices from the grey-level histogram. We performed a univariate and multivariate analysis between all the texture parameters, the volume of the gland, the normal dose parameters (V30 and Mean Dose), and the development of severe chronic xerostomia. Seventy-eight patients were included and 25 (31%) developed chronic xerostomia. The TA parameters correlated with severe chronic xerostomia included V30 (OR 5.63), Dmean (OR 5.71), Kurtosis (OR 0.78), GLCM Correlation (OR 1.34), and RLNU (OR 2.12). The multivariate logistic regression showed a significant correlation between V30 (0.001), GLCM correlation (p: 0.026), RLNU (p: 0.011), and chronic xerostomia (p < 0.001, R2:0.664). Xerostomia represents an important cause of morbidity for head and neck cancer survivors after radiation therapy, and in certain cases normal dose constraints cannot be satisfied. Our results seem promising as texture analysis could enhance the normal dose constraints for the prediction of xerostomia.

Leuconostoc strains isolated from dairy products: Response against food stress conditions.

PubMed

D'Angelo, Luisa; Cicotello, Joaquín; Zago, Miriam; Guglielmotti, Daniela; Quiberoni, Andrea; Suárez, Viviana

2017-09-01

A systematic study about the intrinsic resistance of 29 strains (26 autochthonous and 3 commercial ones), belonging to Leuconostoc genus, against diverse stress factors (thermal, acidic, alkaline, osmotic and oxidative) commonly present at industrial or conservation processes were evaluated. Exhaustive result processing was made by applying one-way ANOVA, Student's test (t), multivariate analysis by Principal Component Analysis (PCA) and Matrix Hierarchical Cluster Analysis. In addition, heat adaptation on 4 strains carefully selected based on previous data analysis was assayed. The strains revealed wide diversity of resistance to stress factors and, in general, a clear relationship between resistance and Leuconostoc species was established. In this sense, the highest resistance was shown by Leuconostoc lactis followed by Leuconostoc mesenteroides strains, while Leuconostoc pseudomesenteroides and Leuconostoc citreum strains revealed the lowest resistance to the stress factors applied. Heat adaptation improved thermal cell survival and resulted in a cross-resistance against the acidic factor. However, all adapted cells showed diminished their oxidative resistance. According to our knowledge, this is the first study regarding response of Leuconostoc strains against technological stress factors and could establish the basis for the selection of "more robust" strains and propose the possibility of improving their performance during industrial processes. Copyright © 2017 Elsevier Ltd. All rights reserved.

Content analysis of antiretroviral adherence enhancing interview reports.

PubMed

Kamal, Susan; Nulty, Paul; Bugnon, Olivier; Cavassini, Matthias; Schneider, Marie P

2018-05-17

To identify factors associated with low or high antiretroviral (ARV) adherence through computational text analysis of an adherence enhancing programme interview reports. Using text from 8428 interviews with 522 patients, we constructed a term-frequency matrix for each patient, retaining words that occurred at least ten times overall and used in at least six interviews with six different patients. The text included both the pharmacist's and the patient's verbalizations. We investigated their association with an adherence threshold (above or below 90%) using a regularized logistic regression model. In addition to this data-driven approach, we studied the contexts of words with a focus group. Analysis resulted in 7608 terms associated with low or high adherence. Terms associated with low adherence included disruption in daily schedule, side effects, socio-economic factors, stigma, cognitive factors and smoking. Terms associated with high adherence included fixed medication intake timing, no side effects and positive psychological state. Computational text analysis helps to analyze a large corpus of adherence enhancing interviews. It confirms main known themes affecting ARV adherence and sheds light on new emerging themes. Health care providers should be aware of factors that are associated with low or high adherence. This knowledge should reinforce the supporting factors and try to resolve the barriers together with the patient. Copyright © 2018 Elsevier B.V. All rights reserved.

An inflammation-responsive transcription factor in the pathophysiology of osteoarthritis.

PubMed

Ray, Alpana; Ray, Bimal K

2008-01-01

A number of risk factors including biomechanical stress on the articular cartilage imposed by joint overloading due to obesity, repetitive damage of the joint tissues by injury of the menisci and ligaments, and abnormal joint alignment play a significant role in the onset of osteoarthritis (OA). Genetic predisposition can also lead to the formation of defective cartilage matrix because of abnormal gene expression in the cartilage-specific cells. Another important biochemical event in OA is the consequence of inflammation. It has been shown that synovial inflammation triggers the synthesis of biological stimuli such as cytokines and growth factors which subsequently reach the chondrocyte cells of the articular cartilage activating inflammatory events in the chondrocytes leading to cartilage destruction. In addition to cartilage degradation, hypertrophy of the subchondral bone and osteophyte formation at the joint margins also takes place in OA. Both processes involve abnormal expression of a number of genes including matrix metalloproteinases (MMPs) for cartilage degradation and those associated with bone formation during osteophyte development. To address how diverse groups of genes are activated in OA chondrocyte, we have studied their induction mechanism. We present evidence for abundant expression of an inflammation-responsive transcription factor, SAF-1, in moderate to severely damaged OA cartilage tissues. In contrast, cells in normal cartilage matrix contain very low level of SAF-1 protein. SAF-1 is identified as a major regulator of increased synthesis of MMP-1 and -9 and pro-angiogenic factor, vascular endothelial growth factor (VEGF). While VEGF by stimulating angiogenesis plays a key role in new bone formation in osteophyte, increase of MMP-1 and -9 is instrumental for cartilage erosion in the pathogenesis of OA. Increased expression in degenerated cartilage matrix and in the osteophytes indicate for a key regulatory role of SAF-1 in directing catabolic matrix degrading and anabolic matrix regenerating activities.

Study of the validity of a job-exposure matrix for psychosocial work factors: results from the national French SUMER survey.

PubMed

Niedhammer, Isabelle; Chastang, Jean-François; Levy, David; David, Simone; Degioanni, Stéphanie; Theorell, Töres

2008-10-01

To construct and evaluate the validity of a job-exposure matrix (JEM) for psychosocial work factors defined by Karasek's model using national representative data of the French working population. National sample of 24,486 men and women who filled in the Job Content Questionnaire (JCQ) by Karasek measuring the scores of psychological demands, decision latitude, and social support (individual scores) in 2003 (response rate 96.5%). Median values of the three scores in the total sample of men and women were used to define high demands, low latitude, and low support (individual binary exposures). Job title was defined by both occupation and economic activity that were coded using detailed national classifications (PCS and NAF/NACE). Two JEM measures were calculated from the individual scores of demands, latitude and support for each job title: JEM scores (mean of the individual score) and JEM binary exposures (JEM score dichotomized at the median). The analysis of the variance of the individual scores of demands, latitude, and support explained by occupations and economic activities, of the correlation and agreement between individual measures and JEM measures, and of the sensitivity and specificity of JEM exposures, as well as the study of the associations with self-reported health showed a low validity of JEM measures for psychological demands and social support, and a relatively higher validity for decision latitude compared with individual measures. Job-exposure matrix measure for decision latitude might be used as a complementary exposure assessment. Further research is needed to evaluate the validity of JEM for psychosocial work factors.

Multivariate analysis: A statistical approach for computations

NASA Astrophysics Data System (ADS)

Michu, Sachin; Kaushik, Vandana

2014-10-01

Multivariate analysis is a type of multivariate statistical approach commonly used in, automotive diagnosis, education evaluating clusters in finance etc and more recently in the health-related professions. The objective of the paper is to provide a detailed exploratory discussion about factor analysis (FA) in image retrieval method and correlation analysis (CA) of network traffic. Image retrieval methods aim to retrieve relevant images from a collected database, based on their content. The problem is made more difficult due to the high dimension of the variable space in which the images are represented. Multivariate correlation analysis proposes an anomaly detection and analysis method based on the correlation coefficient matrix. Anomaly behaviors in the network include the various attacks on the network like DDOs attacks and network scanning.

Thermal form-factor approach to dynamical correlation functions of integrable lattice models

NASA Astrophysics Data System (ADS)

Göhmann, Frank; Karbach, Michael; Klümper, Andreas; Kozlowski, Karol K.; Suzuki, Junji

2017-11-01

We propose a method for calculating dynamical correlation functions at finite temperature in integrable lattice models of Yang-Baxter type. The method is based on an expansion of the correlation functions as a series over matrix elements of a time-dependent quantum transfer matrix rather than the Hamiltonian. In the infinite Trotter-number limit the matrix elements become time independent and turn into the thermal form factors studied previously in the context of static correlation functions. We make this explicit with the example of the XXZ model. We show how the form factors can be summed utilizing certain auxiliary functions solving finite sets of nonlinear integral equations. The case of the XX model is worked out in more detail leading to a novel form-factor series representation of the dynamical transverse two-point function.

[Preparation of hydrophilic matrix sustained release tablets of total lactones from Andrographis paniculata and study on its in vitro release mechanism].

PubMed

Xu, Fang-Fang; Shi, Wei; Zhang, Hui; Guo, Qing-Ming; Wang Zhen-Zhong; Bi, Yu-An; Wang, Zhi-Min; Xiao, Wei

2015-01-01

In this study, hydrophilic matrix sustained release tablets of total lactones from Andrographis paniculata were prepared and the in vitro release behavior were also evaluated. The optimal prescription was achieved by studying the main factor of the type and amount of hydroxypropyl methylcellulose (HPMC) using single factor test and evaluating through cumulative release of three lactones. No burst drug release from the obtained matrix tablets was observed. Drug release sustained to 14 h. The release mechanism of three lactones from A. paniculata was accessed by zero-order, first-order, Higuchi and Peppas equation. The release behavior of total lactones from A. paniculata was better agreed with Higuchi model and the drug release from the tablets was controlled by degradation of the matrix. The preparation of hydrophilic matrix sustained release tablets of total lactones from A. paniculata with good performance of drug release was simple.

Proteomic analysis of cellular soluble proteins from human bronchial smooth muscle cells by combining nondenaturing micro 2DE and quantitative LC-MS/MS. 2. Similarity search between protein maps for the analysis of protein complexes.

PubMed

Jin, Ya; Yuan, Qi; Zhang, Jun; Manabe, Takashi; Tan, Wen

2015-09-01

Human bronchial smooth muscle cell soluble proteins were analyzed by a combined method of nondenaturing micro 2DE, grid gel-cutting, and quantitative LC-MS/MS and a native protein map was prepared for each of the identified 4323 proteins [1]. A method to evaluate the degree of similarity between the protein maps was developed since we expected the proteins comprising a protein complex would be separated together under nondenaturing conditions. The following procedure was employed using Excel macros; (i) maps that have three or more squares with protein quantity data were selected (2328 maps), (ii) within each map, the quantity values of the squares were normalized setting the highest value to be 1.0, (iii) in comparing a map with another map, the smaller normalized quantity in two corresponding squares was taken and summed throughout the map to give an "overlap score," (iv) each map was compared against all the 2328 maps and the largest overlap score, obtained when a map was compared with itself, was set to be 1.0 thus providing 2328 "overlap factors," (v) step (iv) was repeated for all maps providing 2328 × 2328 matrix of overlap factors. From the matrix, protein pairs that showed overlap factors above 0.65 from both protein sides were selected (431 protein pairs). Each protein pair was searched in a database (UniProtKB) on complex formation and 301 protein pairs, which comprise 35 protein complexes, were found to be documented. These results demonstrated that native protein maps and their similarity search would enable simultaneous analysis of multiple protein complexes in cells. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Source identification of PM10 pollution in subway passenger cabins using positive matrix factorization

NASA Astrophysics Data System (ADS)

Park, Duckshin; Oh, Miseok; Yoon, Younghun; Park, Eunyoung; Lee, Kiyoung

2012-03-01

Monitoring the air quality in subway passenger cabins is important because of the large number of passengers and potentially high levels of air pollution. This report characterized PM10 levels in subway cabins in Seoul, Korea, and identified PM10 sources using elemental analysis and receptor modeling. PM10 levels in subway cabins were continuously measured using a light scattering monitor during rush and non-rush hours. A total of 41 measurements were taken during rush and non-rush hours, and the measurements were repeated in all four seasons. Filter samples were also collected for elemental composition analysis. Major PM10 sources were identified using positive matrix factorization (PMF). The in-cabin PM10 concentrations were the highest in the winter at 152.8 μg m-3 during rush hours and 90.2 μg m-3 during non-rush hours. While PM10 levels were higher during rush hours than during non-rush hours in three seasons (excluding summer), these levels were not associated with number of passenger. Elemental analysis showed that the PM10 was composed of 52.5% inorganic elements, 10.2% anions, and 37.3% other. Fe was the most abundant element and significantly correlated (p < 0.01) with Mn (r = 0.97), Ti (r = 0.91), Cr (r = 0.88), Ni (r = 0.89), and Cu (r = 0.88). Fe, Mn, Cr, and Cu are indicators of railroad-related PM10 sources. The PM10 sources characterized by PMF were soil and road dust sources (27.2%), railroad-related sources (47.6%), secondary nitrate sources (16.2%), and a chlorine factor mixed with a secondary sulfate source (9.1%). Overall, railroad-related sources contributed the most PM10 to subway cabin air.

The acousto-ultrasonic approach

NASA Technical Reports Server (NTRS)

Vary, Alex

1987-01-01

The nature and underlying rationale of the acousto-ultrasonic approach is reviewed, needed advanced signal analysis and evaluation methods suggested, and application potentials discussed. Acousto-ultrasonics is an NDE technique combining aspects of acoustic emission methodology with ultrasonic simulation of stress waves. This approach uses analysis of simulated stress waves for detecting and mapping variations of mechanical properties. Unlike most NDE, acousto-ultrasonics is less concerned with flaw detection than with the assessment of the collective effects of various flaws and material anomalies. Acousto-ultrasonics has been applied chiefly to laminated and filament-wound fiber reinforced composites. It has been used to assess the significant strength and toughness reducing effects that can be wrought by combinations of essentially minor flaws and diffuse flaw populations. Acousto-ultrasonics assesses integrated defect states and the resultant variations in properties such as tensile, shear, and flexural strengths and fracture resistance. Matrix cure state, porosity, fiber orientation, fiber volume fraction, fiber-matrix bonding, and interlaminar bond quality are underlying factors.

Triangular covariance factorizations for. Ph.D. Thesis. - Calif. Univ.

NASA Technical Reports Server (NTRS)

Thornton, C. L.

1976-01-01

An improved computational form of the discrete Kalman filter is derived using an upper triangular factorization of the error covariance matrix. The covariance P is factored such that P = UDUT where U is unit upper triangular and D is diagonal. Recursions are developed for propagating the U-D covariance factors together with the corresponding state estimate. The resulting algorithm, referred to as the U-D filter, combines the superior numerical precision of square root filtering techniques with an efficiency comparable to that of Kalman's original formula. Moreover, this method is easily implemented and involves no more computer storage than the Kalman algorithm. These characteristics make the U-D method an attractive realtime filtering technique. A new covariance error analysis technique is obtained from an extension of the U-D filter equations. This evaluation method is flexible and efficient and may provide significantly improved numerical results. Cost comparisons show that for a large class of problems the U-D evaluation algorithm is noticeably less expensive than conventional error analysis methods.

PM 10 metal concentrations and source identification using positive matrix factorization and wind sectoring in a French industrial zone

NASA Astrophysics Data System (ADS)

Alleman, Laurent Y.; Lamaison, Laure; Perdrix, Esperanza; Robache, Antoine; Galloo, Jean-Claude

2010-06-01

The elemental composition data of ambient aerosols collected upon selected wind sectors in the highly industrialised harbour of Dunkirk (France) were interpreted using pollution roses, elemental ratios, Enrichment Factors (EF), Principal Component Analysis (PCA) and Positive Matrix Factorization (PMF) receptor model. The objective was to identify the possible sources of PM10 aerosols, their respective chemical tracers and to determine their relative contribution at the sampling site. PM10 particles samples were collected from June 2003 to March 2005 in order to analyse up to 35 elements (Ag, Al, As, Ba, Bi, Ca, Cd, Ce, Co, Cr, Cs, Cu, Eu, Fe, K, La, Mg, Mn, Mo, Na, Ni, Pb, Rb, S, Sb, Sc, Si, Sm, Sr, Th, Ti, U, V, Zn and Zr) using Inductively Coupled Plasma (ICP)-Atomic Emission Spectrometry (AES) and ICP-Mass Spectrometry (MS). A significant effort has been made on estimating the total uncertainty of each result by regularly analysing blanks, quality controls and SRM NIST standards. Based on this procedure, a selected set of 24 "robust" elements was compared to the 35-element matrix in order to evaluate the sturdiness of our PMF statistical treatment. Eight source factors were resolved by PCA for all the wind sectors explaining 90% of the total data variance. The PMF results confirmed that eight physically interpretable factors contributed to the ambient particulate pollution at the sampling site: crustal dust (11%), marine aerosols (12%), petrochemistry activities (9.2%), metallurgical sintering plant (8.6%), metallurgical coke plant (12.6%), ferromanganese plant (6.6%), road transport (15%) and a less clearly interpretable profile probably associated to dust resuspension (13%). These weighted contributions against wind direction frequencies demonstrate that industrial sources are the most important contributors to this site (37%) followed by the natural sources (detrital and marine sources) (23%) and the road transport (15%).

Assessment of phytoplankton class abundance using fluorescence excitation-emission matrix by parallel factor analysis and nonnegative least squares

NASA Astrophysics Data System (ADS)

Su, Rongguo; Chen, Xiaona; Wu, Zhenzhen; Yao, Peng; Shi, Xiaoyong

2015-07-01

The feasibility of using fluorescence excitation-emission matrix (EEM) along with parallel factor analysis (PARAFAC) and nonnegative least squares (NNLS) method for the differentiation of phytoplankton taxonomic groups was investigated. Forty-one phytoplankton species belonging to 28 genera of five divisions were studied. First, the PARAFAC model was applied to EEMs, and 15 fluorescence components were generated. Second, 15 fluorescence components were found to have a strong discriminating capability based on Bayesian discriminant analysis (BDA). Third, all spectra of the fluorescence component compositions for the 41 phytoplankton species were spectrographically sorted into 61 reference spectra using hierarchical cluster analysis (HCA), and then, the reference spectra were used to establish a database. Finally, the phytoplankton taxonomic groups was differentiated by the reference spectra database using the NNLS method. The five phytoplankton groups were differentiated with the correct discrimination ratios (CDRs) of 100% for single-species samples at the division level. The CDRs for the mixtures were above 91% for the dominant phytoplankton species and above 73% for the subdominant phytoplankton species. Sixteen of the 85 field samples collected from the Changjiang River estuary were analyzed by both HPLC-CHEMTAX and the fluorometric technique developed. The results of both methods reveal that Bacillariophyta was the dominant algal group in these 16 samples and that the subdominant algal groups comprised Dinophyta, Chlorophyta and Cryptophyta. The differentiation results by the fluorometric technique were in good agreement with those from HPLC-CHEMTAX. The results indicate that the fluorometric technique could differentiate algal taxonomic groups accurately at the division level.

Acousto-ultrasonics to Assess Material and Structural Properties

NASA Technical Reports Server (NTRS)

Kautz, Harold E.

2002-01-01

This report was created to serve as a manual for applying the Acousto-Ultrasonic NDE method, as practiced at NASA Glenn, to the study of materials and structures for a wide range of applications. Three state of the art acousto-ultrasonic (A-U) analysis parameters, ultrasonic decay (UD) rate, mean time (or skewing factor, "s"), and the centroid of the power spectrum, "f(sub c)," have been studied and applied at GRC for NDE interrogation of various materials and structures of aerospace interest. In addition to this, a unique application of Lamb wave analysis is shown. An appendix gives a brief overview of Lamb Wave analysis. This paper presents the analysis employed to calculate these parameters and the development and reasoning behind their use. It also discusses the planning of A-U measurements for materials and structures to be studied. Types of transducer coupling are discussed including contact and non-contact via laser and air. Experimental planning includes matching transducer frequency range to material and geometry of the specimen to be studied. The effect on results of initially zeroing the DC component of the ultrasonic waveform is compared with not doing so. A wide range of interrogation problems are addressed via the application of these analysis parameters to real specimens is shown for five cases: Case 1: Differences in density in [0] SiC/RBSN ceramic matrix composite. Case 2: Effect of tensile fatigue cycling in [+/-45] SiC/SiC ceramic matrix composite. Case 3: Detecting creep life, and failure, in Udimet 520 Nickel-Based Super Alloy. Case 4: Detecting Surface Layer Formation in T-650-35/PMR-15 Polymer Matrix Composites Panels due to Thermal Aging. Case 5: Detecting Spin Test Degradation in PMC Flywheels. Among these cases a wide range of materials and geometries are studied.

MATRIX METALLOPROTEINS (MMP)-MEDIATED PHOSPHORYLATION OF THE EPIDERMAL GROWTH FACTOR RECEPTOR (EGFR) IN HUMAN AIRWAY EPITHELIAL CELLS (HAEC) EXPOSED TO ZINC (ZN)

EPA Science Inventory

Matrix Metalloproteinase (MMP)-Mediated Phosphorylation of The Epidermal Growth Factor Receptor (EGFR) in Human Airway Epithelial Cells (HAEC) Exposed to Zinc (Zn)
Weidong Wu, James M. Samet, Robert Silbajoris, Lisa A. Dailey, Lee M. Graves, and Philip A. Bromberg
Center fo...

A Transfer Learning Approach for Applying Matrix Factorization to Small ITS Datasets

ERIC Educational Resources Information Center

Voß, Lydia; Schatten, Carlotta; Mazziotti, Claudia; Schmidt-Thieme, Lars

2015-01-01

Machine Learning methods for Performance Prediction in Intelligent Tutoring Systems (ITS) have proven their efficacy; specific methods, e.g. Matrix Factorization (MF), however suffer from the lack of available information about new tasks or new students. In this paper we show how this problem could be solved by applying Transfer Learning (TL),…

SOURCE APPORTIONMENT OF PM 2.5 AND CARBON IN SEATTLE USING CHEMICAL MASS BALANCE AND POSITIVE MATRIX FACTORIZATION

EPA Science Inventory

Three years of PM2.5 speciated data were collected and chemically analyzed using the IMPROVE protocol at the Beacon Hill site in Seattle. The data were analyzed by the Chemical Mass Balance Version 8 (CMB8) and Positive Matrix Factorization (PMF) source apportionment models. T...

The matrix exponential in transient structural analysis

NASA Technical Reports Server (NTRS)

Minnetyan, Levon

1987-01-01

The primary usefulness of the presented theory is in the ability to represent the effects of high frequency linear response with accuracy, without requiring very small time steps in the analysis of dynamic response. The matrix exponential contains a series approximation to the dynamic model. However, unlike the usual analysis procedure which truncates the high frequency response, the approximation in the exponential matrix solution is in the time domain. By truncating the series solution to the matrix exponential short, the solution is made inaccurate after a certain time. Yet, up to that time the solution is extremely accurate, including all high frequency effects. By taking finite time increments, the exponential matrix solution can compute the response very accurately. Use of the exponential matrix in structural dynamics is demonstrated by simulating the free vibration response of multi degree of freedom models of cantilever beams.

Collagen Membranes Adsorb the Transforming Growth Factor-β Receptor I Kinase-Dependent Activity of Enamel Matrix Derivative.

PubMed

Stähli, Alexandra; Miron, Richard J; Bosshardt, Dieter D; Sculean, Anton; Gruber, Reinhard

2016-05-01

Enamel matrix derivative (EMD) and collagen membranes (CMs) are simultaneously applied in regenerative periodontal surgery. The aim of this study is to evaluate the ability of two CMs and a collagen matrix to adsorb the activity intrinsic to EMD that provokes transforming growth factor (TGF)-β signaling in oral fibroblasts. Three commercially available collagen products were exposed to EMD or recombinant TGF-β1, followed by vigorous washing. Oral fibroblasts were either seeded directly onto collagen products or were incubated with the respective supernatant. Expression of TGF-β target genes interleukin (IL)-11 and proteoglycan 4 (PRG4) was evaluated by real time polymerase chain reaction. Proteomic analysis was used to study the fraction of EMD proteins binding to collagen. EMD or TGF-β1 provoked a significant increase of IL-11 and PRG4 expression of oral fibroblasts when seeded onto collagen products and when incubated with the respective supernatant. Gene expression was blocked by the TGF-β receptor I kinase inhibitor SB431542. Amelogenin bound most abundantly to gelatin-coated culture dishes. However, incubation of palatal fibroblasts with recombinant amelogenin did not alter expression of IL-11 and PRG4. These in vitro findings suggest that collagen products adsorb a TGF-β receptor I kinase-dependent activity of EMD and make it available for potential target cells.

Bone resorption analysis of platelet-derived growth factor type BB application on collagen for bone grafts secured by titanium mesh over a pig jaw defect model

PubMed Central

Herford, Alan Scott; Cicciù, Marco

2012-01-01

Purpose: The aim of this investigation was to evaluate whether the addition of the platelet derived growth factor type BB (PDGF-BB) to a collagen matrix applied on a titanium mesh would favor healing and resorption onto the grafted bone. A histologic and radiographic study of two different groups (test and control) was performed. Designs: A surgical procedure was performed on 8 pigs to obtain 16 bilateral mandibular alveolar defects. All the defects were then reconstructed with a mixture of autogenous bovine bone using titanium mesh positioning. Two groups, with a total of 16 defects were created: The first to study collagen sponge and PDGF-BB and the second to control collagen only. The collagen matrix was positioned directly over the mesh and soft tissue was closed without tensions onto both groups without attempting to obtain primary closure. Possible exposure of the titanium mesh as well as the height and volume of the new bone was recorded. Results: New bone formation averaged about 6.68 mm in the test group studied; the control group had less regenerated bone at 4.62 mm. Conclusion: PDGF-BB addition to the collagen matrix induced a strong increase in hard and soft tissue healing and favored bone formation, reducing bone resorption even if the mesh was exposed. PMID:23833493

A unified statistical approach to non-negative matrix factorization and probabilistic latent semantic indexing

PubMed Central

Wang, Guoli; Ebrahimi, Nader

2014-01-01

Non-negative matrix factorization (NMF) is a powerful machine learning method for decomposing a high-dimensional nonnegative matrix V into the product of two nonnegative matrices, W and H, such that V ∼ W H. It has been shown to have a parts-based, sparse representation of the data. NMF has been successfully applied in a variety of areas such as natural language processing, neuroscience, information retrieval, image processing, speech recognition and computational biology for the analysis and interpretation of large-scale data. There has also been simultaneous development of a related statistical latent class modeling approach, namely, probabilistic latent semantic indexing (PLSI), for analyzing and interpreting co-occurrence count data arising in natural language processing. In this paper, we present a generalized statistical approach to NMF and PLSI based on Renyi's divergence between two non-negative matrices, stemming from the Poisson likelihood. Our approach unifies various competing models and provides a unique theoretical framework for these methods. We propose a unified algorithm for NMF and provide a rigorous proof of monotonicity of multiplicative updates for W and H. In addition, we generalize the relationship between NMF and PLSI within this framework. We demonstrate the applicability and utility of our approach as well as its superior performance relative to existing methods using real-life and simulated document clustering data. PMID:25821345

A unified statistical approach to non-negative matrix factorization and probabilistic latent semantic indexing.

PubMed

Devarajan, Karthik; Wang, Guoli; Ebrahimi, Nader

2015-04-01

Non-negative matrix factorization (NMF) is a powerful machine learning method for decomposing a high-dimensional nonnegative matrix V into the product of two nonnegative matrices, W and H , such that V ∼ W H . It has been shown to have a parts-based, sparse representation of the data. NMF has been successfully applied in a variety of areas such as natural language processing, neuroscience, information retrieval, image processing, speech recognition and computational biology for the analysis and interpretation of large-scale data. There has also been simultaneous development of a related statistical latent class modeling approach, namely, probabilistic latent semantic indexing (PLSI), for analyzing and interpreting co-occurrence count data arising in natural language processing. In this paper, we present a generalized statistical approach to NMF and PLSI based on Renyi's divergence between two non-negative matrices, stemming from the Poisson likelihood. Our approach unifies various competing models and provides a unique theoretical framework for these methods. We propose a unified algorithm for NMF and provide a rigorous proof of monotonicity of multiplicative updates for W and H . In addition, we generalize the relationship between NMF and PLSI within this framework. We demonstrate the applicability and utility of our approach as well as its superior performance relative to existing methods using real-life and simulated document clustering data.

Accuracy of whole-genome prediction using a genetic architecture-enhanced variance-covariance matrix.

PubMed

Zhang, Zhe; Erbe, Malena; He, Jinlong; Ober, Ulrike; Gao, Ning; Zhang, Hao; Simianer, Henner; Li, Jiaqi

2015-02-09

Obtaining accurate predictions of unobserved genetic or phenotypic values for complex traits in animal, plant, and human populations is possible through whole-genome prediction (WGP), a combined analysis of genotypic and phenotypic data. Because the underlying genetic architecture of the trait of interest is an important factor affecting model selection, we propose a new strategy, termed BLUP|GA (BLUP-given genetic architecture), which can use genetic architecture information within the dataset at hand rather than from public sources. This is achieved by using a trait-specific covariance matrix ( T: ), which is a weighted sum of a genetic architecture part ( S: matrix) and the realized relationship matrix ( G: ). The algorithm of BLUP|GA (BLUP-given genetic architecture) is provided and illustrated with real and simulated datasets. Predictive ability of BLUP|GA was validated with three model traits in a dairy cattle dataset and 11 traits in three public datasets with a variety of genetic architectures and compared with GBLUP and other approaches. Results show that BLUP|GA outperformed GBLUP in 20 of 21 scenarios in the dairy cattle dataset and outperformed GBLUP, BayesA, and BayesB in 12 of 13 traits in the analyzed public datasets. Further analyses showed that the difference of accuracies for BLUP|GA and GBLUP significantly correlate with the distance between the T: and G: matrices. The new strategy applied in BLUP|GA is a favorable and flexible alternative to the standard GBLUP model, allowing to account for the genetic architecture of the quantitative trait under consideration when necessary. This feature is mainly due to the increased similarity between the trait-specific relationship matrix ( T: matrix) and the genetic relationship matrix at unobserved causal loci. Applying BLUP|GA in WGP would ease the burden of model selection. Copyright © 2015 Zhang et al.

Endothelial cell-derived matrix promotes the metabolic functional maturation of hepatocyte via integrin-Src signalling.

PubMed

Guo, Xinyue; Li, Weihong; Ma, Minghui; Lu, Xin; Zhang, Haiyan

2017-11-01

The extracellular matrix (ECM) microenvironment is involved in the regulation of hepatocyte phenotype and function. Recently, the cell-derived extracellular matrix has been proposed to represent the bioactive and biocompatible materials of the native ECM. Here, we show that the endothelial cell-derived matrix (EC matrix) promotes the metabolic maturation of human adipose stem cell-derived hepatocyte-like cells (hASC-HLCs) through the activation of the transcription factor forkhead box protein A2 (FOXA2) and the nuclear receptors hepatocyte nuclear factor 4 alpha (HNF4α) and pregnane X receptor (PXR). Reducing the fibronectin content in the EC matrix or silencing the expression of α5 integrin in the hASC-HLCs inhibited the effect of the EC matrix on Src phosphorylation and hepatocyte maturation. The inhibition of Src phosphorylation using the inhibitor PP2 or silencing the expression of Src in hASC-HLCs also attenuated the up-regulation of the metabolic function of hASC-HLCs in a nuclear receptor-dependent manner. These data elucidate integrin-Src signalling linking the extrinsic EC matrix signals and metabolic functional maturation of hepatocyte. This study provides a model for studying the interaction between hepatocytes and non-parenchymal cell-derived matrix. © 2017 The Authors. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine.

Proteomic analysis of knock-down HLA-G in invasion of human trophoblast cell line JEG-3

PubMed Central

Liu, Haiyan; Liu, Xueyuan; Jin, Hong; Yang, Fengying; Gu, Weirong; Li, Xiaotian

2013-01-01

Previous studies showed that aberrant HLA-G expression in trophoblast cells plays important roles in trophoblast invasion; however, the mechanisms remain to be explored. In this study, we found that suppressed HLA-G expression could dramatically decrease the mRNA and protein expression levels of matrix metalloproteinase 2 and matrix metalloproteinase 9, and in the proteome assay, there were 3 identified proteins namely, prefoldin 1, eukaryotic translation elongation factor 2 and malate dehydrogenase 2, which were verified by Western blot and known to be associated with invasion, cell cycle and cell metabolism, respectively. Collectively, our study indicated a potential involvement of HLA-G in autocrine networks that may regulate prefoldin, MMPs and trophoblast invasion at the maternal-fetal interface in human pregnancy. PMID:24228107

Transcriptomic analysis of Propionibacterium acnes biofilms in vitro.

PubMed

Jahns, Anika C; Eilers, Hinnerk; Alexeyev, Oleg A

2016-12-01

Propionibacterium acnes is a well-known commensal of the human skin connected to acne vulgaris and joint infections. It is extensively studied in planktonic cultures in the laboratory settings but occurs naturally in biofilms. In this study we have developed an in vitro biofilm model of P. acnes and studied growth features, matrix composition, matrix penetration by fluorescent-labeled antibiotics as well as gene expression. Antibiotic susceptibility of biofilms was studied and could be enhanced by increased glucose concentrations. Biofilm cells were characterized by up-regulated stress-induced genes and up-regulation of genes coding for the potential virulence-associated CAMP factors. P. acnes can generate persister cells showing a reversible tolerance to 50 fold MIC of common antibiotics. Copyright © 2016 Elsevier Ltd. All rights reserved.

Cavity-enhanced Faraday rotation measurement with auto-balanced photodetection.

PubMed

Chang, Chia-Yu; Shy, Jow-Tsong

2015-10-01

Optical cavity enhancement for a tiny Faraday rotation is demonstrated with auto-balanced photodetection. This configuration is analyzed using the Jones matrix formalism. The resonant rotation signal is amplified, and thus, the angular sensitivity is improved. In the experiment, the air Faraday rotation is measured with an auto-balanced photoreceiver in single-pass and cavity geometries. The result shows that the measured Faraday rotation in the single-pass geometry is enhanced by a factor of 85 in the cavity geometry, and the sensitivity is improved to 7.54×10(-10)  rad Hz(-1/2), which agrees well with the Jones matrix analysis. With this verification, we propose an AC magnetic sensor whose magnetic sensitivity is expected to achieve 10  pT Hz(-1/2).

Extending injury prevention methodology to chemical terrorism preparedness: the Haddon Matrix and sarin.

PubMed

Varney, Shawn; Hirshon, Jon Mark; Dischinger, Patricia; Mackenzie, Colin

2006-01-01

The Haddon Matrix offers a classic epidemiological model for studying injury prevention. This methodology places the public health concepts of agent, host, and environment within the three sequential phases of an injury-producing incident-pre-event, event, and postevent. This study uses this methodology to illustrate how it could be applied in systematically preparing for a mass casualty disaster such as an unconventional sarin attack in a major urban setting. Nineteen city, state, federal, and military agencies responded to the Haddon Matrix chemical terrorism preparedness exercise and offered feedback in the data review session. Four injury prevention strategies (education, engineering, enforcement, and economics) were applied to the individual factors and event phases of the Haddon Matrix. The majority of factors identified in all phases were modifiable, primarily through educational interventions focused on individual healthcare providers and first responders. The Haddon Matrix provides a viable means of studying an unconventional problem, allowing for the identification of modifiable factors to decrease the type and severity of injuries following a mass casualty disaster such as a sarin release. This strategy could be successfully incorporated into disaster planning for other weapons attacks that could potentially cause mass casualties.

A novel mathematical model considering change of diffusion coefficient for predicting dissolution behavior of acetaminophen from wax matrix dosage form.

PubMed

Nitanai, Yuta; Agata, Yasuyoshi; Iwao, Yasunori; Itai, Shigeru

2012-05-30

From wax matrix dosage forms, drug and water-soluble polymer are released into the external solvent over time. As a consequence, the pore volume inside the wax matrix particles is increased and the diffusion coefficient of the drug is altered. In the present study, we attempted to derive a novel empirical mathematical model, namely, a time-dependent diffusivity (TDD) model, that assumes the change in the drug's diffusion coefficient can be used to predict the drug release from spherical wax matrix particles. Wax matrix particles were prepared by using acetaminophen (APAP), a model drug; glyceryl monostearate (GM), a wax base; and aminoalkyl methacrylate copolymer E (AMCE), a functional polymer that dissolves below pH 5.0 and swells over pH 5.0. A three-factor, three-level (3(3)) Box-Behnken design was used to evaluate the effects of several of the variables in the model formulation, and the release of APAP from wax matrix particles was evaluated by the paddle method at pH 4.0 and pH 6.5. When comparing the goodness of fit to the experimental data between the proposed TDD model and the conventional pure diffusion model, a better correspondence was observed for the TDD model in all cases. Multiple regression analysis revealed that an increase in AMCE loading enhanced the diffusion coefficient with time, and that this increase also had a significant effect on drug release behavior. Furthermore, from the results of the multiple regression analysis, a formulation with desired drug release behavior was found to satisfy the criteria of the bitter taste masking of APAP without lowering the bioavailability. That is to say, the amount of APAP released remains below 15% for 10 min at pH 6.5 and exceeds 90% within 30 min at pH 4.0. The predicted formulation was 15% APAP loading, 8.25% AMCE loading, and 400 μm mean particle diameter. When wax matrix dosage forms were prepared accordingly, the predicted drug release behavior agreed well with experimental values at each pH level. Therefore, the proposed model is feasible as a useful tool for predicting drug release behavior, as well as for designing the formulation of wax matrix dosage forms. Copyright © 2012 Elsevier B.V. All rights reserved.

A micromechanics-based strength prediction methodology for notched metal matrix composites

NASA Technical Reports Server (NTRS)

Bigelow, C. A.

1992-01-01

An analytical micromechanics based strength prediction methodology was developed to predict failure of notched metal matrix composites. The stress-strain behavior and notched strength of two metal matrix composites, boron/aluminum (B/Al) and silicon-carbide/titanium (SCS-6/Ti-15-3), were predicted. The prediction methodology combines analytical techniques ranging from a three dimensional finite element analysis of a notched specimen to a micromechanical model of a single fiber. In the B/Al laminates, a fiber failure criteria based on the axial and shear stress in the fiber accurately predicted laminate failure for a variety of layups and notch-length to specimen-width ratios with both circular holes and sharp notches when matrix plasticity was included in the analysis. For the SCS-6/Ti-15-3 laminates, a fiber failure based on the axial stress in the fiber correlated well with experimental results for static and post fatigue residual strengths when fiber matrix debonding and matrix cracking were included in the analysis. The micromechanics based strength prediction methodology offers a direct approach to strength prediction by modeling behavior and damage on a constituent level, thus, explicitly including matrix nonlinearity, fiber matrix debonding, and matrix cracking.

A micromechanics-based strength prediction methodology for notched metal-matrix composites

NASA Technical Reports Server (NTRS)

Bigelow, C. A.

1993-01-01

An analytical micromechanics-based strength prediction methodology was developed to predict failure of notched metal matrix composites. The stress-strain behavior and notched strength of two metal matrix composites, boron/aluminum (B/Al) and silicon-carbide/titanium (SCS-6/Ti-15-3), were predicted. The prediction methodology combines analytical techniques ranging from a three-dimensional finite element analysis of a notched specimen to a micromechanical model of a single fiber. In the B/Al laminates, a fiber failure criteria based on the axial and shear stress in the fiber accurately predicted laminate failure for a variety of layups and notch-length to specimen-width ratios with both circular holes and sharp notches when matrix plasticity was included in the analysis. For the SCS-6/Ti-15-3 laminates, a fiber failure based on the axial stress in the fiber correlated well with experimental results for static and postfatigue residual strengths when fiber matrix debonding and matrix cracking were included in the analysis. The micromechanics-based strength prediction methodology offers a direct approach to strength prediction by modeling behavior and damage on a constituent level, thus, explicitly including matrix nonlinearity, fiber matrix debonding, and matrix cracking.

Matrix metalloproteinase 10 is associated with disease severity and mortality in patients with peripheral arterial disease.

PubMed

Martinez-Aguilar, Esther; Gomez-Rodriguez, Violeta; Orbe, Josune; Rodriguez, Jose A; Fernández-Alonso, Leopoldo; Roncal, Carmen; Páramo, Jose A

2015-02-01

Peripheral arterial disease (PAD) is associated with poor prognosis in terms of cardiovascular (CV) morbidity and mortality. Matrix metalloproteinases (MMPs) contribute to vascular remodeling by degrading extracellular matrix components and play a role in atherosclerosis as demonstrated for MMP-10 (stromelysin-2). This study analyzed MMP-10 levels in PAD patients according to disease severity and CV risk factors and evaluated the prognostic value of MMP-10 for CV events and mortality in lower limb arterial disease after a follow-up period of 2 years. MMP-10 was measured by enzyme-linked immunosorbent assay in 187 PAD patients and 200 sex-matched controls. PAD patients presented with increased levels of MMP-10 (702 ± 326 pg/mL control vs 946 ± 473 pg/mL PAD; P < .001) and decreased levels of tissue inhibitor of matrix metalloproteinase 1 (312 ± 117 ng/mL control vs 235 ± 110 ng/mL PAD; P < .001) compared with controls. Among PAD patients, those with critical limb ischemia (n = 88) showed higher levels of MMP-10 (1086 ± 478 pg/mL vs 822 ± 436 pg/mL; P < .001) compared with those with intermittent claudication (n = 99), whereas the MMP-10/tissue inhibitor of matrix metalloproteinase 1 ratio remained similar. The univariate analysis showed an association between MMP-10, age (P = .015), hypertension (P = .021), and ankle-brachial index (P = .006) in PAD patients that remained significantly associated with PAD severity after adjustment for other CV risk factors. Patients with the highest MMP-10 tertile had an increased incidence of all-cause mortality and CV mortality (P < .03). Our results suggest that MMP-10 is associated with severity and poor outcome in PAD. Copyright © 2015 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

[In situ analysis of pathomechanisms of human intervertebral disc degeneration].

PubMed

Weiler, C

2013-11-01

Low back pain is one of the major causes of pain and disability in the western world, with a constantly rising life-time prevalence of approximately 60-85 %. Degeneration of the intervertebral disc is believed to be a major cause of low back pain. Semiquantitative macroscopic and microscopic changes of the intervertebral disc were assessed and classified. Furthermore additional methods, such as immunohistochemistry, in situ hybridization and in situ zymography were used to analyze phenotypic cellular and matrix changes. We have developed and tested a practicable, valid and reliable histological classification system for lumbar discs which can serve as a morphological reference framework to allow more sophisticated molecular biological studies on the pathogenesis of ageing and degeneration of discs. Secondly, we were able to demonstrate that intrinsic (genetic) and extrinsic (e.g. overweight) factors have a profound effect on the process of disc degeneration. Cells with a notochord-like phenotype are present in a considerable fraction of adult lumbar intervertebral discs. The presence of these cells is associated with distinct features of (early) age-related disc degeneration. During the process of disc degeneration, the intervertebral disc shows a progressive and significant reduction in height due to tissue resorption. This matrix loss is related to an imbalance between matrix synthesis and degradation. During this process an inflammatory reaction takes place and resident disc cells are causatively involved. In summary, disc degeneration is a multifactorial disease with a strong intrinsic (hereditary) and extrinsic (e.g. mechanical factors) background. The process starts as early as in the second decade of life and shows high interindividual differences. The loss of regenerative capacity in the intervertebral disc is probably related to the loss of stem cells, e.g. notochord-like cells. Resident disc cells are involved in the inflammatory reaction with increased matrix degradation, resorption and reduced matrix synthesis.

Matrix modulation and heart failure: new concepts question old beliefs.

PubMed

Deschamps, Anne M; Spinale, Francis G

2005-05-01

Myocardial remodeling is a complex process involving several molecular and cellular factors. Extracellular matrix has been implicated in the remodeling process. Historically, the myocardial extracellular matrix was thought to serve solely as a means to align cells and provide structure to the tissue. Although this is one of its important functions, evidence suggests that the extracellular matrix plays a complex and divergent role in influencing cell behavior. This paper characterizes some of the notable studies on this dynamic entity and on adverse myocardial remodeling that have been published over the past year, which further question the belief that the extracellular matrix is a static structure. Progress has been made in understanding how the extracellular matrix is operative in the three major conditions (myocardial infarction, left ventricular hypertrophy due to overload, and dilated cardiomyopathy) that involve myocardial remodeling. Several studies have examined plasma profiles of matrix metalloproteinases and tissue inhibitors of matrix metalloproteinases following myocardial infarction and during left ventricular hypertrophy as surrogate markers of remodeling/remodeled myocardium. It has been demonstrated that bioactive signaling molecules and growth factors, proteases, and structural proteins influence cell-matrix interactions in the context of left ventricular hypertrophy. Finally, studies that either removed or added tissue inhibitor of metalloproteinases species in the myocardium demonstrated the importance of this regulatory protein in the remodeling process. Understanding the cellular and molecular triggers that in turn give rise to changes in the extracellular matrix could provide opportunities to modify the remodeling process.

Graphene as a Novel Matrix for the Analysis of Small Molecules by MALDI-TOF MS

PubMed Central

Dong, Xiaoli; Cheng, Jinsheng; Li, Jinghong; Wang, Yinsheng

2010-01-01

Graphene was utilized for the first time as matrix for the analysis of low-molecular weight compounds using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). Polar compounds including amino acids, polyamines, anticancer drugs and nucleosides could be successfully analyzed. Additionally, nonpolar compounds including steroids could be detected with high resolution and sensitivity. Compared with conventional matrix, graphene exhibited high desorption/ionization efficiency for nonpolar compounds. The graphene matrix functions as substrate to trap analytes, and it transfers energy to the analytes upon laser irradiation, which allowed for the analytes to be readily desorbed/ionized and interference of intrinsic matrix ions to be eliminated. The use of graphene as matrix avoided the fragmentation of analytes and provided good reproducibility and high salt tolerance, underscoring the potential application of graphene as matrix for MALDI-MS analysis of practical samples in complex sample matrices. We also demonstrated that the use of graphene as adsorbent for the solid-phase extraction of squalene could improve greatly the detection limit. This work not only opens a new field for applications of graphene, but also offers a new technique for high-speed analysis of low-molecular weight compounds in areas such as metabolism research and natural products characterization. PMID:20565059

Movement behaviour within and beyond perceptual ranges in three small mammals: effects of matrix type and body mass.

PubMed

Prevedello, Jayme Augusto; Forero-Medina, Germán; Vieira, Marcus Vinícius

2010-11-01

1. For animal species inhabiting heterogeneous landscapes, the tortuosity of the dispersal path is a key determinant of the success in locating habitat patches. Path tortuosity within and beyond perceptual range must differ, and may be differently affected by intrinsic attributes of individuals and extrinsic environmental factors. Understanding how these factors interact to determine path tortuosity allows more accurate inference of successful movements between habitat patches. 2. We experimentally determined the effects of intrinsic (body mass and species identity) and extrinsic factors (distance to nearest forest fragment and matrix type) on the tortuosity of movements of three forest-dwelling didelphid marsupials, in a fragmented landscape of the Atlantic Forest, Brazil. 3. A total of 202 individuals were captured in forest fragments and released in three unsuitable matrix types (mowed pasture, abandoned pasture and manioc plantation), carrying spool-and-line devices. 4. Twenty-four models were formulated representing a priori hypotheses of major determinants of path tortuosity, grouped in three scenarios (only intrinsic factors, only extrinsic factors and models with combinations of both), and compared using a model selection approach. Models were tested separately for individuals released within the perceptual range of the species, and for individuals released beyond the perceptual range. 5. Matrix type strongly affected path tortuosity, with more obstructed matrix types hampering displacement of animals. Body mass was more important than species identity to determine path tortuosity, with larger animals moving more linearly. Increased distance to the fragment resulted in more tortuous paths, but actually reflects a threshold in perceptual range: linear paths within perceptual range, tortuous paths beyond. 6. The variables tested explained successfully path tortuosity, but only for animals released within the perceptual range. Other factors, such as wind intensity and direction of plantation rows, may be more important for individuals beyond their perceptual range. 7. Simplistic scenarios considering only intrinsic or extrinsic factors are inadequate to predict path tortuosity, and to infer dispersal success in heterogeneous landscapes. Perceptual range represents a fundamental threshold where the effects of matrix type, body mass and individual behaviour change drastically. © 2010 The Authors. Journal compilation © 2010 British Ecological Society.

The AdS{sub 5}xS{sup 5} superstring worldsheet S matrix and crossing symmetry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Janik, Romuald A.

2006-04-15

An S matrix satisfying the Yang-Baxter equation with symmetries relevant to the AdS{sub 5}xS{sup 5} superstring recently has been determined up to an unknown scalar factor. Such scalar factors are typically fixed using crossing relations; however, due to the lack of conventional relativistic invariance, in this case its determination remained an open problem. In this paper we propose an algebraic way to implement crossing relations for the AdS{sub 5}xS{sup 5} superstring worldsheet S matrix. We base our construction on a Hopf-algebraic formulation of crossing in terms of the antipode and introduce generalized rapidities living on the universal cover of themore » parameter space which is constructed through an auxillary, coupling-constant dependent, elliptic curve. We determine the crossing transformation and write functional equations for the scalar factor of the S matrix in the generalized rapidity plane.« less

A novel edge-preserving nonnegative matrix factorization method for spectral unmixing

NASA Astrophysics Data System (ADS)

Bao, Wenxing; Ma, Ruishi

2015-12-01

Spectral unmixing technique is one of the key techniques to identify and classify the material in the hyperspectral image processing. A novel robust spectral unmixing method based on nonnegative matrix factorization(NMF) is presented in this paper. This paper used an edge-preserving function as hypersurface cost function to minimize the nonnegative matrix factorization. To minimize the hypersurface cost function, we constructed the updating functions for signature matrix of end-members and abundance fraction respectively. The two functions are updated alternatively. For evaluation purpose, synthetic data and real data have been used in this paper. Synthetic data is used based on end-members from USGS digital spectral library. AVIRIS Cuprite dataset have been used as real data. The spectral angle distance (SAD) and abundance angle distance(AAD) have been used in this research for assessment the performance of proposed method. The experimental results show that this method can obtain more ideal results and good accuracy for spectral unmixing than present methods.

Joint refinement model for the spin resolved one-electron reduced density matrix of YTiO3 using magnetic structure factors and magnetic Compton profiles data.

PubMed

Gueddida, Saber; Yan, Zeyin; Kibalin, Iurii; Voufack, Ariste Bolivard; Claiser, Nicolas; Souhassou, Mohamed; Lecomte, Claude; Gillon, Béatrice; Gillet, Jean-Michel

2018-04-28

In this paper, we propose a simple cluster model with limited basis sets to reproduce the unpaired electron distributions in a YTiO 3 ferromagnetic crystal. The spin-resolved one-electron-reduced density matrix is reconstructed simultaneously from theoretical magnetic structure factors and directional magnetic Compton profiles using our joint refinement algorithm. This algorithm is guided by the rescaling of basis functions and the adjustment of the spin population matrix. The resulting spin electron density in both position and momentum spaces from the joint refinement model is in agreement with theoretical and experimental results. Benefits brought from magnetic Compton profiles to the entire spin density matrix are illustrated. We studied the magnetic properties of the YTiO 3 crystal along the Ti-O 1 -Ti bonding. We found that the basis functions are mostly rescaled by means of magnetic Compton profiles, while the molecular occupation numbers are mainly modified by the magnetic structure factors.

Predicting drug-target interactions by dual-network integrated logistic matrix factorization

NASA Astrophysics Data System (ADS)

Hao, Ming; Bryant, Stephen H.; Wang, Yanli

2017-01-01

In this work, we propose a dual-network integrated logistic matrix factorization (DNILMF) algorithm to predict potential drug-target interactions (DTI). The prediction procedure consists of four steps: (1) inferring new drug/target profiles and constructing profile kernel matrix; (2) diffusing drug profile kernel matrix with drug structure kernel matrix; (3) diffusing target profile kernel matrix with target sequence kernel matrix; and (4) building DNILMF model and smoothing new drug/target predictions based on their neighbors. We compare our algorithm with the state-of-the-art method based on the benchmark dataset. Results indicate that the DNILMF algorithm outperforms the previously reported approaches in terms of AUPR (area under precision-recall curve) and AUC (area under curve of receiver operating characteristic) based on the 5 trials of 10-fold cross-validation. We conclude that the performance improvement depends on not only the proposed objective function, but also the used nonlinear diffusion technique which is important but under studied in the DTI prediction field. In addition, we also compile a new DTI dataset for increasing the diversity of currently available benchmark datasets. The top prediction results for the new dataset are confirmed by experimental studies or supported by other computational research.

Positive matrix factorization and trajectory modelling for source identification: A new look at Indian Ocean Experiment ship observations

NASA Astrophysics Data System (ADS)

Bhanuprasad, S. G.; Venkataraman, Chandra; Bhushan, Mani

The sources of aerosols on a regional scale over India have only recently received attention in studies using back trajectory analysis and chemical transport modelling. Receptor modelling approaches such as positive matrix factorization (PMF) and the potential source contribution function (PSCF) are effective tools in source identification of urban and regional-scale pollution. In this work, PMF and PSCF analysis is applied to identify categories and locations of sources that influenced surface concentrations of aerosols in the Indian Ocean Experiment (INDOEX) domain measured on-board the research vessel Ron Brown [Quinn, P.K., Coffman, D.J., Bates, T.S., Miller, T.L., Johnson, J.E., Welton, E.J., et al., 2002. Aerosol optical properties during INDOEX 1999: means, variability, and controlling factors. Journal of Geophysical Research 107, 8020, doi:10.1029/2000JD000037]. Emissions inventory information is used to identify sources co-located with probable source regions from PSCF. PMF analysis identified six factors influencing PM concentrations during the INDOEX cruise of the Ron Brown including a biomass combustion factor (35-40%), three industrial emissions factors (35-40%), primarily secondary sulphate-nitrate, balance trace elements and Zn, and two dust factors (20-30%) of Si- and Ca-dust. The identified factors effectively predict the measured submicron PM concentrations (slope of regression line=0.90±0.20; R2=0.76). Probable source regions shifted based on changes in surface and elevated flows during different times in the ship cruise. They were in India in the early part of the cruise, but in west Asia, south-east Asia and Africa, during later parts of the cruise. Co-located sources include coal-fired electric utilities, cement, metals and petroleum production in India and west Asia, biofuel combustion for energy and crop residue burning in India, woodland/forest burning in north sub-Saharan Africa and forest burning in south-east Asia. Significant findings are equivalent contributions of biomass combustion and industrial emissions to the measured aerosol surface concentrations, the origin of carbonaceous aerosols largely from biomass combustion and the identification of probable source regions in Africa, west Asia, the Arabian peninsula and south-east Asia, in addition to India, which affected particulate matter concentrations over parts of the INDOEX domain covered by the Ron Brown cruise.

Isolation and Identification of Proteins Secreted by Cells Cultured within Synthetic Hydrogel-Based Matrices

PubMed Central

2018-01-01

Cells interact with and remodel their microenvironment, degrading large extracellular matrix (ECM) proteins (e.g., fibronectin, collagens) and secreting new ECM proteins and small soluble factors (e.g., growth factors, cytokines). Synthetic mimics of the ECM have been developed as controlled cell culture platforms for use in both fundamental and applied studies. However, how cells broadly remodel these initially well-defined matrices remains poorly understood and difficult to probe. In this work, we have established methods for widely examining both large and small proteins that are secreted by cells within synthetic matrices. Specifically, human mesenchymal stem cells (hMSCs), a model primary cell type, were cultured within well-defined poly(ethylene glycol) (PEG)-peptide hydrogels, and these cell-matrix constructs were decellularized and degraded for subsequent isolation and analysis of deposited proteins. Shotgun proteomics using liquid chromatography and mass spectrometry identified a variety of proteins, including the large ECM proteins fibronectin and collagen VI. Immunostaining and confocal imaging confirmed these results and provided visualization of protein organization within the synthetic matrices. Additionally, culture medium was collected from the encapsulated hMSCs, and a Luminex assay was performed to identify secreted soluble factors, including vascular endothelial growth factor (VEGF), endothelial growth factor (EGF), basic fibroblast growth factor (FGF-2), interleukin 8 (IL-8), and tumor necrosis factor alpha (TNF-α). Together, these methods provide a unique approach for studying dynamic reciprocity between cells and synthetic microenvironments and have the potential to provide new biological insights into cell responses during three-dimensional (3D) controlled cell culture. PMID:29552635

Isolation and Identification of Proteins Secreted by Cells Cultured within Synthetic Hydrogel-Based Matrices.

PubMed

Sawicki, Lisa A; Choe, Leila H; Wiley, Katherine L; Lee, Kelvin H; Kloxin, April M

2018-03-12

Cells interact with and remodel their microenvironment, degrading large extracellular matrix (ECM) proteins (e.g., fibronectin, collagens) and secreting new ECM proteins and small soluble factors (e.g., growth factors, cytokines). Synthetic mimics of the ECM have been developed as controlled cell culture platforms for use in both fundamental and applied studies. However, how cells broadly remodel these initially well-defined matrices remains poorly understood and difficult to probe. In this work, we have established methods for widely examining both large and small proteins that are secreted by cells within synthetic matrices. Specifically, human mesenchymal stem cells (hMSCs), a model primary cell type, were cultured within well-defined poly(ethylene glycol) (PEG)-peptide hydrogels, and these cell-matrix constructs were decellularized and degraded for subsequent isolation and analysis of deposited proteins. Shotgun proteomics using liquid chromatography and mass spectrometry identified a variety of proteins, including the large ECM proteins fibronectin and collagen VI. Immunostaining and confocal imaging confirmed these results and provided visualization of protein organization within the synthetic matrices. Additionally, culture medium was collected from the encapsulated hMSCs, and a Luminex assay was performed to identify secreted soluble factors, including vascular endothelial growth factor (VEGF), endothelial growth factor (EGF), basic fibroblast growth factor (FGF-2), interleukin 8 (IL-8), and tumor necrosis factor alpha (TNF-α). Together, these methods provide a unique approach for studying dynamic reciprocity between cells and synthetic microenvironments and have the potential to provide new biological insights into cell responses during three-dimensional (3D) controlled cell culture.

Volatile organic compounds (VOCs) in urban air: How chemistry affects the interpretation of positive matrix factorization (PMF) analysis

NASA Astrophysics Data System (ADS)

Yuan, Bin; Shao, Min; de Gouw, Joost; Parrish, David D.; Lu, Sihua; Wang, Ming; Zeng, Limin; Zhang, Qian; Song, Yu; Zhang, Jianbo; Hu, Min

2012-12-01

Volatile organic compounds (VOCs) were measured online at an urban site in Beijing in August-September 2010. Diurnal variations of various VOC species indicate that VOCs concentrations were influenced by photochemical removal with OH radicals for reactive species and secondary formation for oxygenated VOCs (OVOCs). A photochemical age-based parameterization method was applied to characterize VOCs chemistry. A large part of the variability in concentrations of both hydrocarbons and OVOCs was explained by this method. The determined emission ratios of hydrocarbons to acetylene agreed within a factor of two between 2005 and 2010 measurements. However, large differences were found for emission ratios of some alkanes and C8 aromatics between Beijing and northeastern United States secondary formation from anthropogenic VOCs generally contributed higher percentages to concentrations of reactive aldehydes than those of inert ketones and alcohols. Anthropogenic primary emissions accounted for the majority of ketones and alcohols concentrations. Positive matrix factorization (PMF) was also used to identify emission sources from this VOCs data set. The four resolved factors were three anthropogenic factors and a biogenic factor. However, the anthropogenic factors are attributed here to a common source at different stages of photochemical processing rather than three independent sources. Anthropogenic and biogenic sources of VOCs concentrations were not separated completely in PMF. This study indicates that photochemistry of VOCs in the atmosphere complicates the information about separated sources that can be extracted from PMF and the influence of photochemical processing must be carefully considered in the interpretation of source apportionment studies based upon PMF.

Monocyte activation by smooth muscle cell-derived matrices.

PubMed

Kaufmann, J; Jorgensen, R W; Martin, B M; Franzblau, C

1990-12-01

Mononuclear phagocytes adhere to and penetrate the vessel wall endothelium and contact the subendothelial space prior to the development of the atherosclerotic plaque. In an attempt to model the early events of plaque development we used an elastin-rich, multicomponent, cell-derived matrix from neonatal rat aortic smooth muscle cells as a substratum for monocytes. Using this model, we show that human monocyte morphology and metabolism are markedly altered by the matrix substratum. When a mixed mononuclear cell population is seeded on matrix or plastic, only monocytes adhere to the matrix surface. In contrast, lymphocytes as well as monocytes adhere to the plastic surface. The matrix-adherent monocytes develop large intracellular granules and form extensive clusters of individual cells. Metabolically, these cells develop sodium fluoride resistant non-specific esterase activity and their media contain more growth factor activity and PGE2. Although total protein synthesis is equivalent in both cultures, the matrix contact induces an increase in specific proteins in the media. We also show that a purified alpha-elastin substratum induces some, but not all, of the monocyte changes seen when using the matrix substratum. Using the alpha-elastin substratum, there is selective adhesion of monocytes and increased growth factor activity, however, the cells are morphologically different from the matrix-adherent cells. Thus, the use of the smooth muscle cell-derived matrix, in conjunction with purified matrix components, serves as a model that can provide insight into the mechanisms of monocyte adhesion and stimulation by the matrix environment that exists in vivo. Such mechanisms may be particularly important in atherogenesis.

Access of Hydrogen-Radicals to the Peptide-Backbone as a Measure for Estimating the Flexibility of Proteins Using Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry

PubMed Central

Takayama, Mitsuo; Nagoshi, Keishiro; Iimuro, Ryunosuke; Inatomi, Kazuma

2014-01-01

A factor for estimating the flexibility of proteins is described that uses a cleavage method of “in-source decay (ISD)” coupled with matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS). The MALDI-ISD spectra of bovine serum albumin (BSA), myoglobin and thioredoxin show discontinuous intense ion peaks originating from one-side preferential cleavage at the N-Cα bond of Xxx-Asp, Xxx-Asn, Xxx-Cys and Gly-Xxx residues. Consistent with these observations, Asp, Asn and Gly residues are also identified by other flexibility measures such as B-factor, turn preference, protection and fluorescence decay factors, while Asp, Asn, Cys and Gly residues are identified by turn preference factor based on X-ray crystallography. The results suggest that protein molecules embedded in/on MALDI matrix crystals partly maintain α-helix and that the reason some of the residues are more susceptible to ISD (Asp, Asn, Cys and Gly) and others less so (Ile and Val) is because of accessibility of the peptide backbone to hydrogen-radicals from matrix molecules. The hydrogen-radical accessibility in MALDI-ISD could therefore be adopted as a factor for measuring protein flexibility. PMID:24828203

Local delamination in laminates with angle ply matrix cracks. Part 1: Tension tests and stress analysis

NASA Technical Reports Server (NTRS)

Obrien, T. Kevin; Hooper, S. J.

1991-01-01

Quasi-static tension tests were conducted on AS4/3501-6 graphite epoxy laminates. Dye penetrant enhanced x-radiography was used to document the onset of matrix cracking and the onset of local delaminations at the intersection of the matrix cracks and the free edge. Edge micrographs taken after the onset of damage were used to verify the location of the matrix cracks and local delamination through the laminate thickness. A quasi-3D finite element analysis was conducted to calculate the stresses responsible for matrix cracking in the off-axis plies. Laminated plate theory indicated that the transverse normal stresses were compressive. However, the finite element analysis yielded tensile transverse normal stresses near the free edge. Matrix cracks formed in the off-axis plies near the free edge where in-plane transverse stresses were tensile and had their greatest magnitude. The influence of the matrix crack on interlaminar stresses is also discussed.

Association between matrix metalloproteinase-10 concentration and smoking in individuals without cardiovascular disease.

PubMed

Páramo, José A; Beloqui, Oscar; Rodríguez, José A; Diez, Javier; Orbe, Josune

2008-12-01

Smoking is an important cardiovascular risk factor whose underlying mechanism is incompletely understood. However, it has been suggested that alterations in the balance between synthesis and degradation of the extracellular matrix (ECM) may play a role. The aim of this study was to determine whether there is an independent association between smoking and the concentration of circulating metalloproteinases (MMPs) in individuals without cardiovascular disease. Metabolic parameters, the carotid intima-media thickness (IMT), inflammatory markers (fibrinogen, C-reactive protein and interleukin-6), markers of endothelial damage (e.g., von Willebrand factor), and the concentration of MMP-1, -9 and -10 and tissue inhibitor of metalloproteinase-1 (TIMP-1) were assessed in 400 asymptomatic individuals with cardiovascular risk factors. Subjects were divided into non-smokers (n=195), smokers (n=118) and former smokers (n=87). In addition, global cardiovascular risk was determined from PROCAM and REGICOR scores. Both MMP-1 and MMP-10 concentrations were significantly higher in smokers than non-smokers (P< .05 and P< .001, respectively), though there was no difference in the levels of MMP-9, TIMP-1, IMT and other inflammatory parameters. There were positive correlations between the MMP-10 concentration and PROCAM and REGICOR scores (P< .001). Multivariate analysis showed that there was still an association between smoking and the MMP-10 concentration after adjustment for age, sex and other cardiovascular risk factors (P< .001). Multiple regression analysis showed that smoking accounted for 28% of the variability in the MMP-10 concentration. There was an independent association between smoking and the MMP-10 concentration in asymptomatic individuals. This relationship between MMP-10 and the ECM may indicate a mechanism through which this MMP contributes to smoking-related atherosclerosis.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Yaping; Williams, Brent J.; Goldstein, Allen H.

Here, we present a rapid method for apportioning the sources of atmospheric organic aerosol composition measured by gas chromatography–mass spectrometry methods. Here, we specifically apply this new analysis method to data acquired on a thermal desorption aerosol gas chromatograph (TAG) system. Gas chromatograms are divided by retention time into evenly spaced bins, within which the mass spectra are summed. A previous chromatogram binning method was introduced for the purpose of chromatogram structure deconvolution (e.g., major compound classes) (Zhang et al., 2014). Here we extend the method development for the specific purpose of determining aerosol samples' sources. Chromatogram bins are arrangedmore » into an input data matrix for positive matrix factorization (PMF), where the sample number is the row dimension and the mass-spectra-resolved eluting time intervals (bins) are the column dimension. Then two-dimensional PMF can effectively do three-dimensional factorization on the three-dimensional TAG mass spectra data. The retention time shift of the chromatogram is corrected by applying the median values of the different peaks' shifts. Bin width affects chemical resolution but does not affect PMF retrieval of the sources' time variations for low-factor solutions. A bin width smaller than the maximum retention shift among all samples requires retention time shift correction. A six-factor PMF comparison among aerosol mass spectrometry (AMS), TAG binning, and conventional TAG compound integration methods shows that the TAG binning method performs similarly to the integration method. However, the new binning method incorporates the entirety of the data set and requires significantly less pre-processing of the data than conventional single compound identification and integration. In addition, while a fraction of the most oxygenated aerosol does not elute through an underivatized TAG analysis, the TAG binning method does have the ability to achieve molecular level resolution on other bulk aerosol components commonly observed by the AMS.« less

A multitrait-multisource confirmatory factor analytic approach to the construct validity of ADHD and ODD rating scales with Malaysian children.

PubMed

Gomez, Rapson; Burns, G Leonard; Walsh, James A; Hafetz, Nina

2005-04-01

Confirmatory factor analysis (CFA) was used to model a multitrait by multisource matrix to determine the convergent and discriminant validity of measures of attention-deficit hyperactivity disorder (ADHD)-inattention (IN), ADHD-hyperactivity/impulsivity (HI), and oppositional defiant disorder (ODD) in 917 Malaysian elementary school children. The three trait factors were ADHD-IN, ADHDHI, and ODD. The two source factors were parents and teachers. Similar to earlier studies with Australian and Brazilian children, the parent and teacher measures failed to show convergent and discriminant validity with Malaysian children. The study outlines the implications of such strong source effects in ADHD-IN, ADHD-HI, and ODD measures for the use of such parent and teacher scales to study the symptom dimensions.

Analysis and fifteen-year projection of the market for LANDSAT data

NASA Technical Reports Server (NTRS)

1981-01-01

The potential market for LANDSAT products through the 1990's was determined. Results are presented in a matrix format. Improved resolution is a major factor in the marketability of LANDSAT data, the 10 meter resolution (projected for 1995) having a significant impact on the federal, private, and international users, and on the agricultural, minerals, and national defense applications. Data delivery time and competition from the French remote sensing system are considered.

Perceived sexual harassment at work: meta-analysis and structural model of antecedents and consequences.

PubMed

Topa Cantisano, Gabriela; Morales Domínguez, J F; Depolo, Marco

2008-05-01

Although sexual harassment has been extensively studied, empirical research has not led to firm conclusions about its antecedents and consequences, both at the personal and organizational level. An extensive literature search yielded 42 empirical studies with 60 samples. The matrix correlation obtained through meta-analytic techniques was used to test a structural equation model. Results supported the hypotheses regarding organizational environmental factors as main predictors of harassment.

Identifying apparent local stable isotope equilibrium in a complex non-equilibrium system.

PubMed

He, Yuyang; Cao, Xiaobin; Wang, Jianwei; Bao, Huiming

2018-02-28

Although being out of equilibrium, biomolecules in organisms have the potential to approach isotope equilibrium locally because enzymatic reactions are intrinsically reversible. A rigorous approach that can describe isotope distribution among biomolecules and their apparent deviation from equilibrium state is lacking, however. Applying the concept of distance matrix in graph theory, we propose that apparent local isotope equilibrium among a subset of biomolecules can be assessed using an apparent fractionation difference (|Δα|) matrix, in which the differences between the observed isotope composition (δ') and the calculated equilibrium fractionation factor (1000lnβ) can be more rigorously evaluated than by using a previous approach for multiple biomolecules. We tested our |Δα| matrix approach by re-analyzing published data of different amino acids (AAs) in potato and in green alga. Our re-analysis shows that biosynthesis pathways could be the reason for an apparently close-to-equilibrium relationship inside AA families in potato leaves. Different biosynthesis/degradation pathways in tubers may have led to the observed isotope distribution difference between potato leaves and tubers. The analysis of data from green algae does not support the conclusion that AAs are further from equilibrium in glucose-cultured green algae than in the autotrophic ones. Application of the |Δα| matrix can help us to locate potential reversible reactions or reaction networks in a complex system such as a metabolic system. The same approach can be broadly applied to all complex systems that have multiple components, e.g. geochemical or atmospheric systems of early Earth or other planets. Copyright © 2017 John Wiley & Sons, Ltd.

IL-9 exhibits elevated expression in osteonecrosis of femoral head patients and promotes cartilage degradation through activation of JAK-STAT signaling in vitro.

PubMed

Geng, Wei; Zhang, Wen; Ma, Jinzhu

2018-05-15

Osteonecrosis of the femoral head (ONFH) often causes severe symptoms in young people and limits the mobility of the hip joint. Interleukin-9 (IL-9) is a multi-functional inflammatory factor that participates in lumbar disk herniation and arthritis and has been reported in many studies. However, the correlation between IL-9 and ONFH is unclear. The present study aimed to determine the role of IL-9 in the pathogenetic mechanism of osteonecrosis. To assess IL-9 expression in ONFH and femoral neck fracture patients, cartilage tissue was examined through western blot analysis and immunohistochemistry. Human primary chondrocytes were stimulated with IL-9, and inflammation-related cytokines and cartilage matrix-degrading enzymes were assessed via real-time PCR. After being treated with IL-9, Janus kinase-signal transducers and activators of transcription (JAK-STAT) signaling were tested through western blot analysis. Our results showed a significant increase in the expression of IL-9 in ONFH patients. IL-9 raised the level of inflammation-related cytokines and cartilage matrix-degrading enzymes and enhanced the activation of JAK-STAT signaling. Furthermore, blocking the JAK-STAT signaling pathway reduced the secretion of inflammation-related cytokines and cartilage matrix-degrading enzymes and markedly alleviated the degradation of the cartilage matrix. These findings provide new insights into the role that IL-9 plays in the pathogenetic mechanism of osteonecrosis and also provide a potential treatment for ONFH. Copyright © 2018 Elsevier B.V. All rights reserved.

The Effect of Multi Wall Carbon Nanotubes on Some Physical Properties of Epoxy Matrix

NASA Astrophysics Data System (ADS)

Al-Saadi, Tagreed M.; hammed Aleabi, Suad; Al-Obodi, Entisar E.; Abdul-Jabbar Abbas, Hadeel

2018-05-01

This research involves using epoxy resin as a matrix for making a composite material, while the multi wall carbon nanotubes (MWNCTs) is used as a reinforcing material with different fractions (0.0,0.02, 0.04, 0.06) of the matrix weight. The mechanical ( hardness ), electrical ( dielectric constant, dielectric loss factor, dielectric strength, electrical conductivity ), and thermal properties (thermal conductivity ) were studied. The results showed the increase of hardness, thermal conductivity, electrical conductivity and break down strength with the increase of MWCNT concentration, but the behavior of dielectric loss factor and dielectric constant is opposite that.

Application of the matrix exponential kernel

NASA Technical Reports Server (NTRS)

Rohach, A. F.

1972-01-01

A point matrix kernel for radiation transport, developed by the transmission matrix method, has been used to develop buildup factors and energy spectra through slab layers of different materials for a point isotropic source. Combinations of lead-water slabs were chosen for examples because of the extreme differences in shielding properties of these two materials.

Evidence-Based Practice: A Matrix for Predicting Phonological Generalization

ERIC Educational Resources Information Center

Gierut, Judith A.; Hulse, Lauren E.

2010-01-01

This paper describes a matrix for clinical use in the selection of phonological treatment targets to induce generalization, and in the identification of probe sounds to monitor during the course of intervention. The matrix appeals to a set of factors that have been shown to promote phonological generalization in the research literature, including…

The improved Apriori algorithm based on matrix pruning and weight analysis

NASA Astrophysics Data System (ADS)

Lang, Zhenhong

2018-04-01

This paper uses the matrix compression algorithm and weight analysis algorithm for reference and proposes an improved matrix pruning and weight analysis Apriori algorithm. After the transactional database is scanned for only once, the algorithm will construct the boolean transaction matrix. Through the calculation of one figure in the rows and columns of the matrix, the infrequent item set is pruned, and a new candidate item set is formed. Then, the item's weight and the transaction's weight as well as the weight support for items are calculated, thus the frequent item sets are gained. The experimental result shows that the improved Apriori algorithm not only reduces the number of repeated scans of the database, but also improves the efficiency of data correlation mining.

Active subspace: toward scalable low-rank learning.

PubMed

Liu, Guangcan; Yan, Shuicheng

2012-12-01

We address the scalability issues in low-rank matrix learning problems. Usually these problems resort to solving nuclear norm regularized optimization problems (NNROPs), which often suffer from high computational complexities if based on existing solvers, especially in large-scale settings. Based on the fact that the optimal solution matrix to an NNROP is often low rank, we revisit the classic mechanism of low-rank matrix factorization, based on which we present an active subspace algorithm for efficiently solving NNROPs by transforming large-scale NNROPs into small-scale problems. The transformation is achieved by factorizing the large solution matrix into the product of a small orthonormal matrix (active subspace) and another small matrix. Although such a transformation generally leads to nonconvex problems, we show that a suboptimal solution can be found by the augmented Lagrange alternating direction method. For the robust PCA (RPCA) (Candès, Li, Ma, & Wright, 2009 ) problem, a typical example of NNROPs, theoretical results verify the suboptimality of the solution produced by our algorithm. For the general NNROPs, we empirically show that our algorithm significantly reduces the computational complexity without loss of optimality.

Strain intensity factor approach for predicting the strength of continuously reinforced metal matrix composites

NASA Technical Reports Server (NTRS)

Poe, Clarence C., Jr.

1989-01-01

A method was previously developed to predict the fracture toughness (stress intensity factor at failure) of composites in terms of the elastic constants and the tensile failing strain of the fibers. The method was applied to boron/aluminum composites made with various proportions of 0 deg and +/- 45 deg plies. Predicted values of fracture toughness were in gross error because widespread yielding of the aluminum matrix made the compliance very nonlinear. An alternate method was develolped to predict the strain intensity factor at failure rather than the stress intensity factor because the singular strain field was not affected by yielding as much as the stress field. Far-field strains at failure were calculated from the strain intensity factor, and then strengths were calculated from the far-field strains using uniaxial stress-strain curves. The predicted strengths were in good agreement with experimental values, even for the very nonlinear laminates that contained only +/- 45 deg plies. This approach should be valid for other metal matrix composites that have continuous fibers.