Data Reduction Algorithm Using Nonnegative Matrix Factorization with Nonlinear Constraints

Science.gov (United States)

Sembiring, Pasukat

2017-12-01

Processing ofdata with very large dimensions has been a hot topic in recent decades. Various techniques have been proposed in order to execute the desired information or structure. Non- Negative Matrix Factorization (NMF) based on non-negatives data has become one of the popular methods for shrinking dimensions. The main strength of this method is non-negative object, the object model by a combination of some basic non-negative parts, so as to provide a physical interpretation of the object construction. The NMF is a dimension reduction method thathasbeen used widely for numerous applications including computer vision,text mining, pattern recognitions,and bioinformatics. Mathematical formulation for NMF did not appear as a convex optimization problem and various types of algorithms have been proposed to solve the problem. The Framework of Alternative Nonnegative Least Square(ANLS) are the coordinates of the block formulation approaches that have been proven reliable theoretically and empirically efficient. This paper proposes a new algorithm to solve NMF problem based on the framework of ANLS.This algorithm inherits the convergenceproperty of the ANLS framework to nonlinear constraints NMF formulations.

Fast Bayesian Non-Negative Matrix Factorisation and Tri-Factorisation

DEFF Research Database (Denmark)

Brouwer, Thomas; Frellsen, Jes; Liò, Pietro

We present a fast variational Bayesian algorithm for performing non-negative matrix factorisation and tri-factorisation. We show that our approach achieves faster convergence per iteration and timestep (wall-clock) than Gibbs sampling and non-probabilistic approaches, and do not require additional...... samples to estimate the posterior. We show that in particular for matrix tri-factorisation convergence is difficult, but our variational Bayesian approach offers a fast solution, allowing the tri-factorisation approach to be used more effectively....

Nonnegative Matrix Factorization with Rank Regularization and Hard Constraint.

Science.gov (United States)

Shang, Ronghua; Liu, Chiyang; Meng, Yang; Jiao, Licheng; Stolkin, Rustam

2017-09-01

Nonnegative matrix factorization (NMF) is well known to be an effective tool for dimensionality reduction in problems involving big data. For this reason, it frequently appears in many areas of scientific and engineering literature. This letter proposes a novel semisupervised NMF algorithm for overcoming a variety of problems associated with NMF algorithms, including poor use of prior information, negative impact on manifold structure of the sparse constraint, and inaccurate graph construction. Our proposed algorithm, nonnegative matrix factorization with rank regularization and hard constraint (NMFRC), incorporates label information into data representation as a hard constraint, which makes full use of prior information. NMFRC also measures pairwise similarity according to geodesic distance rather than Euclidean distance. This results in more accurate measurement of pairwise relationships, resulting in more effective manifold information. Furthermore, NMFRC adopts rank constraint instead of norm constraints for regularization to balance the sparseness and smoothness of data. In this way, the new data representation is more representative and has better interpretability. Experiments on real data sets suggest that NMFRC outperforms four other state-of-the-art algorithms in terms of clustering accuracy.

Nonnegative Matrix Factor 2-D Deconvolution for Blind Single Channel Source Separation

DEFF Research Database (Denmark)

Schmidt, Mikkel N.; Mørup, Morten

2006-01-01

We present a novel method for blind separation of instruments in polyphonic music based on a non-negative matrix factor 2-D deconvolution algorithm. Using a model which is convolutive in both time and frequency we factorize a spectrogram representation of music into components corresponding...

A flexible R package for nonnegative matrix factorization

Directory of Open Access Journals (Sweden)

Seoighe Cathal

2010-07-01

Full Text Available Abstract Background Nonnegative Matrix Factorization (NMF is an unsupervised learning technique that has been applied successfully in several fields, including signal processing, face recognition and text mining. Recent applications of NMF in bioinformatics have demonstrated its ability to extract meaningful information from high-dimensional data such as gene expression microarrays. Developments in NMF theory and applications have resulted in a variety of algorithms and methods. However, most NMF implementations have been on commercial platforms, while those that are freely available typically require programming skills. This limits their use by the wider research community. Results Our objective is to provide the bioinformatics community with an open-source, easy-to-use and unified interface to standard NMF algorithms, as well as with a simple framework to help implement and test new NMF methods. For that purpose, we have developed a package for the R/BioConductor platform. The package ports public code to R, and is structured to enable users to easily modify and/or add algorithms. It includes a number of published NMF algorithms and initialization methods and facilitates the combination of these to produce new NMF strategies. Commonly used benchmark data and visualization methods are provided to help in the comparison and interpretation of the results. Conclusions The NMF package helps realize the potential of Nonnegative Matrix Factorization, especially in bioinformatics, providing easy access to methods that have already yielded new insights in many applications. Documentation, source code and sample data are available from CRAN.

Approximate L0 constrained Non-negative Matrix and Tensor Factorization

DEFF Research Database (Denmark)

Mørup, Morten; Madsen, Kristoffer Hougaard; Hansen, Lars Kai

2008-01-01

Non-negative matrix factorization (NMF), i.e. V = WH where both V, W and H are non-negative has become a widely used blind source separation technique due to its part based representation. The NMF decomposition is not in general unique and a part based representation not guaranteed. However...... constraint. In general, solving for a given L0 norm is an NP hard problem thus convex relaxatin to regularization by the L1 norm is often considered, i.e., minimizing ( 1/2 ||V-WHk||^2+lambda|H|_1). An open problem is to control the degree of sparsity imposed. We here demonstrate that a full regularization......, the L1 regularization strength lambda that best approximates a given L0 can be directly accessed and in effect used to control the sparsity of H. The MATLAB code for the NLARS algorithm is available for download....

Multiple graph regularized nonnegative matrix factorization

KAUST Repository

Wang, Jim Jing-Yan

2013-10-01

Non-negative matrix factorization (NMF) has been widely used as a data representation method based on components. To overcome the disadvantage of NMF in failing to consider the manifold structure of a data set, graph regularized NMF (GrNMF) has been proposed by Cai et al. by constructing an affinity graph and searching for a matrix factorization that respects graph structure. Selecting a graph model and its corresponding parameters is critical for this strategy. This process is usually carried out by cross-validation or discrete grid search, which are time consuming and prone to overfitting. In this paper, we propose a GrNMF, called MultiGrNMF, in which the intrinsic manifold is approximated by a linear combination of several graphs with different models and parameters inspired by ensemble manifold regularization. Factorization metrics and linear combination coefficients of graphs are determined simultaneously within a unified object function. They are alternately optimized in an iterative algorithm, thus resulting in a novel data representation algorithm. Extensive experiments on a protein subcellular localization task and an Alzheimer\\'s disease diagnosis task demonstrate the effectiveness of the proposed algorithm. © 2013 Elsevier Ltd. All rights reserved.

Canonical polyadic decomposition of third-order semi-nonnegative semi-symmetric tensors using LU and QR matrix factorizations

Science.gov (United States)

Wang, Lu; Albera, Laurent; Kachenoura, Amar; Shu, Huazhong; Senhadji, Lotfi

2014-12-01

Semi-symmetric three-way arrays are essential tools in blind source separation (BSS) particularly in independent component analysis (ICA). These arrays can be built by resorting to higher order statistics of the data. The canonical polyadic (CP) decomposition of such semi-symmetric three-way arrays allows us to identify the so-called mixing matrix, which contains the information about the intensities of some latent source signals present in the observation channels. In addition, in many applications, such as the magnetic resonance spectroscopy (MRS), the columns of the mixing matrix are viewed as relative concentrations of the spectra of the chemical components. Therefore, the two loading matrices of the three-way array, which are equal to the mixing matrix, are nonnegative. Most existing CP algorithms handle the symmetry and the nonnegativity separately. Up to now, very few of them consider both the semi-nonnegativity and the semi-symmetry structure of the three-way array. Nevertheless, like all the methods based on line search, trust region strategies, and alternating optimization, they appear to be dependent on initialization, requiring in practice a multi-initialization procedure. In order to overcome this drawback, we propose two new methods, called [InlineEquation not available: see fulltext.] and [InlineEquation not available: see fulltext.], to solve the problem of CP decomposition of semi-nonnegative semi-symmetric three-way arrays. Firstly, we rewrite the constrained optimization problem as an unconstrained one. In fact, the nonnegativity constraint of the two symmetric modes is ensured by means of a square change of variable. Secondly, a Jacobi-like optimization procedure is adopted because of its good convergence property. More precisely, the two new methods use LU and QR matrix factorizations, respectively, which consist in formulating high-dimensional optimization problems into several sequential polynomial and rational subproblems. By using both LU

Sparse modeling of EELS and EDX spectral imaging data by nonnegative matrix factorization

Energy Technology Data Exchange (ETDEWEB)

Shiga, Motoki, E-mail: shiga_m@gifu-u.ac.jp [Department of Electrical, Electronic and Computer Engineering, Gifu University, 1-1, Yanagido, Gifu 501-1193 (Japan); Tatsumi, Kazuyoshi; Muto, Shunsuke [Advanced Measurement Technology Center, Institute of Materials and Systems for Sustainability, Nagoya University, Chikusa-ku, Nagoya 464-8603 (Japan); Tsuda, Koji [Graduate School of Frontier Sciences, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa 277-8561 (Japan); Center for Materials Research by Information Integration, National Institute for Materials Science, 1-2-1 Sengen, Tsukuba 305-0047 (Japan); Biotechnology Research Institute for Drug Discovery, National Institute of Advanced Industrial Science and Technology, 2-4-7 Aomi Koto-ku, Tokyo 135-0064 (Japan); Yamamoto, Yuta [High-Voltage Electron Microscope Laboratory, Institute of Materials and Systems for Sustainability, Nagoya University, Chikusa-ku, Nagoya 464-8603 (Japan); Mori, Toshiyuki [Environment and Energy Materials Division, National Institute for Materials Science, 1-1 Namiki, Tsukuba 305-0044 (Japan); Tanji, Takayoshi [Division of Materials Research, Institute of Materials and Systems for Sustainability, Nagoya University, Chikusa-ku, Nagoya 464-8603 (Japan)

2016-11-15

Advances in scanning transmission electron microscopy (STEM) techniques have enabled us to automatically obtain electron energy-loss (EELS)/energy-dispersive X-ray (EDX) spectral datasets from a specified region of interest (ROI) at an arbitrary step width, called spectral imaging (SI). Instead of manually identifying the potential constituent chemical components from the ROI and determining the chemical state of each spectral component from the SI data stored in a huge three-dimensional matrix, it is more effective and efficient to use a statistical approach for the automatic resolution and extraction of the underlying chemical components. Among many different statistical approaches, we adopt a non-negative matrix factorization (NMF) technique, mainly because of the natural assumption of non-negative values in the spectra and cardinalities of chemical components, which are always positive in actual data. This paper proposes a new NMF model with two penalty terms: (i) an automatic relevance determination (ARD) prior, which optimizes the number of components, and (ii) a soft orthogonal constraint, which clearly resolves each spectrum component. For the factorization, we further propose a fast optimization algorithm based on hierarchical alternating least-squares. Numerical experiments using both phantom and real STEM-EDX/EELS SI datasets demonstrate that the ARD prior successfully identifies the correct number of physically meaningful components. The soft orthogonal constraint is also shown to be effective, particularly for STEM-EELS SI data, where neither the spatial nor spectral entries in the matrices are sparse. - Highlights: • Automatic resolution of chemical components from spectral imaging is considered. • We propose a new non-negative matrix factorization with two new penalties. • The first penalty is sparseness to choose the number of components from data. • Experimental results with real data demonstrate effectiveness of our method.

Nonnegativity of uncertain polynomials

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Šiljak Dragoslav D.

1998-01-01

Full Text Available The purpose of this paper is to derive tests for robust nonnegativity of scalar and matrix polynomials, which are algebraic, recursive, and can be completed in finite number of steps. Polytopic families of polynomials are considered with various characterizations of parameter uncertainty including affine, multilinear, and polynomic structures. The zero exclusion condition for polynomial positivity is also proposed for general parameter dependencies. By reformulating the robust stability problem of complex polynomials as positivity of real polynomials, we obtain new sufficient conditions for robust stability involving multilinear structures, which can be tested using only real arithmetic. The obtained results are applied to robust matrix factorization, strict positive realness, and absolute stability of multivariable systems involving parameter dependent transfer function matrices.

Robust Nonnegative Matrix Factorization via Joint Graph Laplacian and Discriminative Information for Identifying Differentially Expressed Genes

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Ling-Yun Dai

2017-01-01

Full Text Available Differential expression plays an important role in cancer diagnosis and classification. In recent years, many methods have been used to identify differentially expressed genes. However, the recognition rate and reliability of gene selection still need to be improved. In this paper, a novel constrained method named robust nonnegative matrix factorization via joint graph Laplacian and discriminative information (GLD-RNMF is proposed for identifying differentially expressed genes, in which manifold learning and the discriminative label information are incorporated into the traditional nonnegative matrix factorization model to train the objective matrix. Specifically, L2,1-norm minimization is enforced on both the error function and the regularization term which is robust to outliers and noise in gene data. Furthermore, the multiplicative update rules and the details of convergence proof are shown for the new model. The experimental results on two publicly available cancer datasets demonstrate that GLD-RNMF is an effective method for identifying differentially expressed genes.

Alternating optimization method based on nonnegative matrix factorizations for deep neural networks

OpenAIRE

Sakurai, Tetsuya; Imakura, Akira; Inoue, Yuto; Futamura, Yasunori

2016-01-01

The backpropagation algorithm for calculating gradients has been widely used in computation of weights for deep neural networks (DNNs). This method requires derivatives of objective functions and has some difficulties finding appropriate parameters such as learning rate. In this paper, we propose a novel approach for computing weight matrices of fully-connected DNNs by using two types of semi-nonnegative matrix factorizations (semi-NMFs). In this method, optimization processes are performed b...

Semi-Supervised Half-Quadratic Nonnegative Matrix Factorization for Face Recognition

KAUST Repository

Alghamdi, Masheal M.

2014-05-01

Face recognition is a challenging problem in computer vision. Difficulties such as slight differences between similar faces of different people, changes in facial expressions, light and illumination condition, and pose variations add extra complications to the face recognition research. Many algorithms are devoted to solving the face recognition problem, among which the family of nonnegative matrix factorization (NMF) algorithms has been widely used as a compact data representation method. Different versions of NMF have been proposed. Wang et al. proposed the graph-based semi-supervised nonnegative learning (S2N2L) algorithm that uses labeled data in constructing intrinsic and penalty graph to enforce separability of labeled data, which leads to a greater discriminating power. Moreover the geometrical structure of labeled and unlabeled data is preserved through using the smoothness assumption by creating a similarity graph that conserves the neighboring information for all labeled and unlabeled data. However, S2N2L is sensitive to light changes, illumination, and partial occlusion. In this thesis, we propose a Semi-Supervised Half-Quadratic NMF (SSHQNMF) algorithm that combines the benefits of S2N2L and the robust NMF by the half- quadratic minimization (HQNMF) algorithm.Our algorithm improves upon the S2N2L algorithm by replacing the Frobenius norm with a robust M-Estimator loss function. A multiplicative update solution for our SSHQNMF algorithmis driven using the half- 4 quadratic (HQ) theory. Extensive experiments on ORL, Yale-A and a subset of the PIE data sets for nine M-estimator loss functions for both SSHQNMF and HQNMF algorithms are investigated, and compared with several state-of-the-art supervised and unsupervised algorithms, along with the original S2N2L algorithm in the context of classification, clustering, and robustness against partial occlusion. The proposed algorithm outperformed the other algorithms. Furthermore, SSHQNMF with Maximum Correntropy

Sparse Non-negative Matrix Factor 2-D Deconvolution for Automatic Transcription of Polyphonic Music

DEFF Research Database (Denmark)

Schmidt, Mikkel N.; Mørup, Morten

2006-01-01

We present a novel method for automatic transcription of polyphonic music based on a recently published algorithm for non-negative matrix factor 2-D deconvolution. The method works by simultaneously estimating a time-frequency model for an instrument and a pattern corresponding to the notes which...... are played based on a log-frequency spectrogram of the music....

Doubly Nonparametric Sparse Nonnegative Matrix Factorization Based on Dependent Indian Buffet Processes.

Science.gov (United States)

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.

ℓ2,1 Norm and Hessian Regularized Non-Negative Matrix Factorization with Discriminability for Data Representation

Directory of Open Access Journals (Sweden)

Peng Luo

2017-09-01

Full Text Available Matrix factorization based methods have widely been used in data representation. Among them, Non-negative Matrix Factorization (NMF is a promising technique owing to its psychological and physiological interpretation of spontaneously occurring data. On one hand, although traditional Laplacian regularization can enhance the performance of NMF, it still suffers from the problem of its weak extrapolating ability. On the other hand, standard NMF disregards the discriminative information hidden in the data and cannot guarantee the sparsity of the factor matrices. In this paper, a novel algorithm called ℓ 2 , 1 norm and Hessian Regularized Non-negative Matrix Factorization with Discriminability (ℓ 2 , 1 HNMFD, is developed to overcome the aforementioned problems. In ℓ 2 , 1 HNMFD, Hessian regularization is introduced in the framework of NMF to capture the intrinsic manifold structure of the data. ℓ 2 , 1 norm constraints and approximation orthogonal constraints are added to assure the group sparsity of encoding matrix and characterize the discriminative information of the data simultaneously. To solve the objective function, an efficient optimization scheme is developed to settle it. Our experimental results on five benchmark data sets have demonstrated that ℓ 2 , 1 HNMFD can learn better data representation and provide better clustering results.

Beyond cross-domain learning: Multiple-domain nonnegative matrix factorization

KAUST Repository

Wang, Jim Jing-Yan; Gao, Xin

2014-01-01

Traditional cross-domain learning methods transfer learning from a source domain to a target domain. In this paper, we propose the multiple-domain learning problem for several equally treated domains. The multiple-domain learning problem assumes that samples from different domains have different distributions, but share the same feature and class label spaces. Each domain could be a target domain, while also be a source domain for other domains. A novel multiple-domain representation method is proposed for the multiple-domain learning problem. This method is based on nonnegative matrix factorization (NMF), and tries to learn a basis matrix and coding vectors for samples, so that the domain distribution mismatch among different domains will be reduced under an extended variation of the maximum mean discrepancy (MMD) criterion. The novel algorithm - multiple-domain NMF (MDNMF) - was evaluated on two challenging multiple-domain learning problems - multiple user spam email detection and multiple-domain glioma diagnosis. The effectiveness of the proposed algorithm is experimentally verified. © 2013 Elsevier Ltd. All rights reserved.

Beyond cross-domain learning: Multiple-domain nonnegative matrix factorization

KAUST Repository

Wang, Jim Jing-Yan

2014-02-01

Traditional cross-domain learning methods transfer learning from a source domain to a target domain. In this paper, we propose the multiple-domain learning problem for several equally treated domains. The multiple-domain learning problem assumes that samples from different domains have different distributions, but share the same feature and class label spaces. Each domain could be a target domain, while also be a source domain for other domains. A novel multiple-domain representation method is proposed for the multiple-domain learning problem. This method is based on nonnegative matrix factorization (NMF), and tries to learn a basis matrix and coding vectors for samples, so that the domain distribution mismatch among different domains will be reduced under an extended variation of the maximum mean discrepancy (MMD) criterion. The novel algorithm - multiple-domain NMF (MDNMF) - was evaluated on two challenging multiple-domain learning problems - multiple user spam email detection and multiple-domain glioma diagnosis. The effectiveness of the proposed algorithm is experimentally verified. © 2013 Elsevier Ltd. All rights reserved.

Bidirectional Nonnegative Deep Model and Its Optimization in Learning

OpenAIRE

Xianhua Zeng; Zhengyi He; Hong Yu; Shengwei Qu

2016-01-01

Nonnegative matrix factorization (NMF) has been successfully applied in signal processing as a simple two-layer nonnegative neural network. Projective NMF (PNMF) with fewer parameters was proposed, which projects a high-dimensional nonnegative data onto a lower-dimensional nonnegative subspace. Although PNMF overcomes the problem of out-of-sample of NMF, it does not consider the nonlinear characteristic of data and is only a kind of narrow signal decomposition method. In this paper, we combin...

Improving the robustness of Surface Enhanced Raman Spectroscopy based sensors by Bayesian Non-negative Matrix Factorization

DEFF Research Database (Denmark)

Alstrøm, Tommy Sonne; Frøhling, Kasper Bayer; Larsen, Jan

2014-01-01

a Bayesian Non-negative Matrix Factorization (NMF) approach to identify locations of target molecules. The proposed method is able to successfully analyze the spectra and extract the target spectrum. A visualization of the loadings of the basis vector is created and the results show a clear SNR enhancement...

Decomposing the time-frequency representation of EEG using non-negative matrix and multi-way factorization

DEFF Research Database (Denmark)

Mørup, Morten; Hansen, Lars Kai; Parnas, Josef

2006-01-01

We demonstrate how non-negative matrix factorization (NMF) can be used to decompose the inter trial phase coherence (ITPC) of multi-channel EEG to yield a unique decomposition of time-frequency signatures present in various degrees in the recording channels. The NMF optimization is easily...... generalized to a parallel factor (PARAFAC) model to form a non-negative multi-way factorization (NMWF). While the NMF can examine subject specific activities the NMWF can effectively extract the most similar activities across subjects and or conditions. The methods are tested on a proprioceptive stimulus...... consisting of a weight change in a handheld load. While somatosensory gamma oscillations have previously only been evoked by electrical stimuli we hypothesized that a natural proprioceptive stimulus also would be able to evoke gamma oscillations. ITPC maxima were determined by visual inspection...

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

On the Equivalence of Nonnegative Matrix Factorization and K-means- Spectral Clustering

Energy Technology Data Exchange (ETDEWEB)

Ding, Chris; He, Xiaofeng; Simon, Horst D.; Jin, Rong

2005-12-04

We provide a systematic analysis of nonnegative matrix factorization (NMF) relating to data clustering. We generalize the usual X = FG{sup T} decomposition to the symmetric W = HH{sup T} and W = HSH{sup T} decompositions. We show that (1) W = HH{sup T} is equivalent to Kernel K-means clustering and the Laplacian-based spectral clustering. (2) X = FG{sup T} is equivalent to simultaneous clustering of rows and columns of a bipartite graph. We emphasizes the importance of orthogonality in NMF and soft clustering nature of NMF. These results are verified with experiments on face images and newsgroups.

Bidirectional Nonnegative Deep Model and Its Optimization in Learning

Directory of Open Access Journals (Sweden)

Xianhua Zeng

2016-01-01

Full Text Available Nonnegative matrix factorization (NMF has been successfully applied in signal processing as a simple two-layer nonnegative neural network. Projective NMF (PNMF with fewer parameters was proposed, which projects a high-dimensional nonnegative data onto a lower-dimensional nonnegative subspace. Although PNMF overcomes the problem of out-of-sample of NMF, it does not consider the nonlinear characteristic of data and is only a kind of narrow signal decomposition method. In this paper, we combine the PNMF with deep learning and nonlinear fitting to propose a bidirectional nonnegative deep learning (BNDL model and its optimization learning algorithm, which can obtain nonlinear multilayer deep nonnegative feature representation. Experiments show that the proposed model can not only solve the problem of out-of-sample of NMF but also learn hierarchical nonnegative feature representations with better clustering performance than classical NMF, PNMF, and Deep Semi-NMF algorithms.

Sparse Nonnegative Matrix Factorization Strategy for Cochlear Implants

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Hongmei Hu

2015-12-01

Full Text Available Current cochlear implant (CI strategies carry speech information via the waveform envelope in frequency subbands. CIs require efficient speech processing to maximize information transfer to the brain, especially in background noise, where the speech envelope is not robust to noise interference. In such conditions, the envelope, after decomposition into frequency bands, may be enhanced by sparse transformations, such as nonnegative matrix factorization (NMF. Here, a novel CI processing algorithm is described, which works by applying NMF to the envelope matrix (envelopogram of 22 frequency channels in order to improve performance in noisy environments. It is evaluated for speech in eight-talker babble noise. The critical sparsity constraint parameter was first tuned using objective measures and then evaluated with subjective speech perception experiments for both normal hearing and CI subjects. Results from vocoder simulations with 10 normal hearing subjects showed that the algorithm significantly enhances speech intelligibility with the selected sparsity constraints. Results from eight CI subjects showed no significant overall improvement compared with the standard advanced combination encoder algorithm, but a trend toward improvement of word identification of about 10 percentage points at +15 dB signal-to-noise ratio (SNR was observed in the eight CI subjects. Additionally, a considerable reduction of the spread of speech perception performance from 40% to 93% for advanced combination encoder to 80% to 100% for the suggested NMF coding strategy was observed.

Multiplicative algorithms for constrained non-negative matrix factorization

KAUST Repository

Peng, Chengbin

2012-12-01

Non-negative matrix factorization (NMF) provides the advantage of parts-based data representation through additive only combinations. It has been widely adopted in areas like item recommending, text mining, data clustering, speech denoising, etc. In this paper, we provide an algorithm that allows the factorization to have linear or approximatly linear constraints with respect to each factor. We prove that if the constraint function is linear, algorithms within our multiplicative framework will converge. This theory supports a large variety of equality and inequality constraints, and can facilitate application of NMF to a much larger domain. Taking the recommender system as an example, we demonstrate how a specialized weighted and constrained NMF algorithm can be developed to fit exactly for the problem, and the tests justify that our constraints improve the performance for both weighted and unweighted NMF algorithms under several different metrics. In particular, on the Movielens data with 94% of items, the Constrained NMF improves recall rate 3% compared to SVD50 and 45% compared to SVD150, which were reported as the best two in the top-N metric. © 2012 IEEE.

Label-Informed Non-negative Matrix Factorization with Manifold Regularization for Discriminative Subnetwork Detection.

Science.gov (United States)

Watanabe, Takanori; Tunc, Birkan; Parker, Drew; Kim, Junghoon; Verma, Ragini

2016-10-01

In this paper, we present a novel method for obtaining a low dimensional representation of a complex brain network that: (1) can be interpreted in a neurobiologically meaningful way, (2) emphasizes group differences by accounting for label information, and (3) captures the variation in disease subtypes/severity by respecting the intrinsic manifold structure underlying the data. Our method is a supervised variant of non-negative matrix factorization (NMF), and achieves dimensionality reduction by extracting an orthogonal set of subnetworks that are interpretable, reconstructive of the original data, and also discriminative at the group level. In addition, the method includes a manifold regularizer that encourages the low dimensional representations to be smooth with respect to the intrinsic geometry of the data, allowing subjects with similar disease-severity to share similar network representations. While the method is generalizable to other types of non-negative network data, in this work we have used structural connectomes (SCs) derived from diffusion data to identify the cortical/subcortical connections that have been disrupted in abnormal neurological state. Experiments on a traumatic brain injury (TBI) dataset demonstrate that our method can identify subnetworks that can reliably classify TBI from controls and also reveal insightful connectivity patterns that may be indicative of a biomarker.

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

Science.gov (United States)

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.

Predicting protein-protein interactions from multimodal biological data sources via nonnegative matrix tri-factorization.

Science.gov (United States)

Wang, Hua; Huang, Heng; Ding, Chris; Nie, Feiping

2013-04-01

Protein interactions are central to all the biological processes and structural scaffolds in living organisms, because they orchestrate a number of cellular processes such as metabolic pathways and immunological recognition. Several high-throughput methods, for example, yeast two-hybrid system and mass spectrometry method, can help determine protein interactions, which, however, suffer from high false-positive rates. Moreover, many protein interactions predicted by one method are not supported by another. Therefore, computational methods are necessary and crucial to complete the interactome expeditiously. In this work, we formulate the problem of predicting protein interactions from a new mathematical perspective--sparse matrix completion, and propose a novel nonnegative matrix factorization (NMF)-based matrix completion approach to predict new protein interactions from existing protein interaction networks. Through using manifold regularization, we further develop our method to integrate different biological data sources, such as protein sequences, gene expressions, protein structure information, etc. Extensive experimental results on four species, Saccharomyces cerevisiae, Drosophila melanogaster, Homo sapiens, and Caenorhabditis elegans, have shown that our new methods outperform related state-of-the-art protein interaction prediction methods.

Exploring Mixed Membership Stochastic Block Models via Non-negative Matrix Factorization

KAUST Repository

Peng, Chengbin

2014-12-01

Many real-world phenomena can be modeled by networks in which entities and connections are represented by nodes and edges respectively. When certain nodes are highly connected with each other, those nodes forms a cluster, which is called community in our context. It is usually assumed that each node belongs to one community only, but evidences in biology and social networks reveal that the communities often overlap with each other. In other words, one node can probably belong to multiple communities. In light of that, mixed membership stochastic block models (MMB) have been developed to model those networks with overlapping communities. Such a model contains three matrices: two incidence matrices indicating in and out connections and one probability matrix. When the probability of connections for nodes between communities are significantly small, the parameter inference problem to this model can be solved by a constrained non-negative matrix factorization (NMF) algorithm. In this paper, we explore the connection between the two models and propose an algorithm based on NMF to infer the parameters of MMB. The proposed algorithms can detect overlapping communities regardless of knowing or not the number of communities. Experiments show that our algorithm can achieve a better community detection performance than the traditional NMF algorithm. © 2014 IEEE.

Link Prediction via Convex Nonnegative Matrix Factorization on Multiscale Blocks

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Enming Dong

2014-01-01

Full Text Available Low rank matrices approximations have been used in link prediction for networks, which are usually global optimal methods and lack of using the local information. The block structure is a significant local feature of matrices: entities in the same block have similar values, which implies that links are more likely to be found within dense blocks. We use this insight to give a probabilistic latent variable model for finding missing links by convex nonnegative matrix factorization with block detection. The experiments show that this method gives better prediction accuracy than original method alone. Different from the original low rank matrices approximations methods for link prediction, the sparseness of solutions is in accord with the sparse property for most real complex networks. Scaling to massive size network, we use the block information mapping matrices onto distributed architectures and give a divide-and-conquer prediction method. The experiments show that it gives better results than common neighbors method when the networks have a large number of missing links.

Attributed community mining using joint general non-negative matrix factorization with graph Laplacian

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Chen, Zigang; Li, Lixiang; Peng, Haipeng; Liu, Yuhong; Yang, Yixian

2018-04-01

Community mining for complex social networks with link and attribute information plays an important role according to different application needs. In this paper, based on our proposed general non-negative matrix factorization (GNMF) algorithm without dimension matching constraints in our previous work, we propose the joint GNMF with graph Laplacian (LJGNMF) to implement community mining of complex social networks with link and attribute information according to different application needs. Theoretical derivation result shows that the proposed LJGNMF is fully compatible with previous methods of integrating traditional NMF and symmetric NMF. In addition, experimental results show that the proposed LJGNMF can meet the needs of different community minings by adjusting its parameters, and the effect is better than traditional NMF in the community vertices attributes entropy.

Asymptotics of the Perron-Frobenius eigenvalue of nonnegative Hessenberg-Toeplitz matrices

NARCIS (Netherlands)

Janssen, A.J.E.M.

1989-01-01

Asymptotic results for the Perron-Frobenius eigenvalue of a nonnegative Hessenberg-Toeplitz matrix as the dimension of the matrix tends to 8 are given. The results are used and interpreted in terms of source entropies in the case where the Hessenberg-Toeplitz matrix arises as the transition matrix

A Fast Gradient Method for Nonnegative Sparse Regression With Self-Dictionary

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Gillis, Nicolas; Luce, Robert

2018-01-01

A nonnegative matrix factorization (NMF) can be computed efficiently under the separability assumption, which asserts that all the columns of the given input data matrix belong to the cone generated by a (small) subset of them. The provably most robust methods to identify these conic basis columns are based on nonnegative sparse regression and self dictionaries, and require the solution of large-scale convex optimization problems. In this paper we study a particular nonnegative sparse regression model with self dictionary. As opposed to previously proposed models, this model yields a smooth optimization problem where the sparsity is enforced through linear constraints. We show that the Euclidean projection on the polyhedron defined by these constraints can be computed efficiently, and propose a fast gradient method to solve our model. We compare our algorithm with several state-of-the-art methods on synthetic data sets and real-world hyperspectral images.

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

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Chennubhotla, Chakra [University of Pittsburgh School of Medicine, Pittsburgh PA; Castro, Jason [Bates College

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. 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.

Greedy Algorithms for Nonnegativity-Constrained Simultaneous Sparse Recovery

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Kim, Daeun; Haldar, Justin P.

2016-01-01

This work proposes a family of greedy algorithms to jointly reconstruct a set of vectors that are (i) nonnegative and (ii) simultaneously sparse with a shared support set. The proposed algorithms generalize previous approaches that were designed to impose these constraints individually. Similar to previous greedy algorithms for sparse recovery, the proposed algorithms iteratively identify promising support indices. In contrast to previous approaches, the support index selection procedure has been adapted to prioritize indices that are consistent with both the nonnegativity and shared support constraints. Empirical results demonstrate for the first time that the combined use of simultaneous sparsity and nonnegativity constraints can substantially improve recovery performance relative to existing greedy algorithms that impose less signal structure. PMID:26973368

Graph regularized nonnegative matrix factorization for temporal link prediction in dynamic networks

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Ma, Xiaoke; Sun, Penggang; Wang, Yu

2018-04-01

Many networks derived from society and nature are temporal and incomplete. The temporal link prediction problem in networks is to predict links at time T + 1 based on a given temporal network from time 1 to T, which is essential to important applications. The current algorithms either predict the temporal links by collapsing the dynamic networks or collapsing features derived from each network, which are criticized for ignoring the connection among slices. to overcome the issue, we propose a novel graph regularized nonnegative matrix factorization algorithm (GrNMF) for the temporal link prediction problem without collapsing the dynamic networks. To obtain the feature for each network from 1 to t, GrNMF factorizes the matrix associated with networks by setting the rest networks as regularization, which provides a better way to characterize the topological information of temporal links. Then, the GrNMF algorithm collapses the feature matrices to predict temporal links. Compared with state-of-the-art methods, the proposed algorithm exhibits significantly improved accuracy by avoiding the collapse of temporal networks. Experimental results of a number of artificial and real temporal networks illustrate that the proposed method is not only more accurate but also more robust than state-of-the-art approaches.

ENDMEMBER EXTRACTION OF HIGHLY MIXED DATA USING L1 SPARSITY-CONSTRAINED MULTILAYER NONNEGATIVE MATRIX FACTORIZATION

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H. Fang

2018-04-01

Full Text Available Due to the limited spatial resolution of remote hyperspectral sensors, pixels are usually highly mixed in the hyperspectral images. Endmember extraction refers to the process identifying the pure endmember signatures from the mixture, which is an important step towards the utilization of hyperspectral data. Nonnegative matrix factorization (NMF is a widely used method of endmember extraction due to its effectiveness and convenience. While most NMF-based methods have single-layer structures, which may have difficulties in effectively learning the structures of highly mixed and complex data. On the other hand, multilayer algorithms have shown great advantages in learning data features and been widely studied in many fields. In this paper, we presented a L1 sparsityconstrained multilayer NMF method for endmember extraction of highly mixed data. Firstly, the multilayer NMF structure was obtained by unfolding NMF into a certain number of layers. In each layer, the abundance matrix was decomposed into the endmember matrix and abundance matrix of the next layer. Besides, to improve the performance of NMF, we incorporated sparsity constraints to the multilayer NMF model by adding a L1 regularizer of the abundance matrix to each layer. At last, a layer-wise optimization method based on NeNMF was proposed to train the multilayer NMF structure. Experiments were conducted on both synthetic data and real data. The results demonstrate that our proposed algorithm can achieve better results than several state-of-art approaches.

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

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Bin Ju

Full Text Available 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.

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

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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.

Hessian regularization based non-negative matrix factorization for gene expression data clustering.

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Liu, Xiao; Shi, Jun; Wang, Congzhi

2015-01-01

Since a key step in the analysis of gene expression data is to detect groups of genes that have similar expression patterns, clustering technique is then commonly used to analyze gene expression data. Data representation plays an important role in clustering analysis. The non-negative matrix factorization (NMF) is a widely used data representation method with great success in machine learning. Although the traditional manifold regularization method, Laplacian regularization (LR), can improve the performance of NMF, LR still suffers from the problem of its weak extrapolating power. Hessian regularization (HR) is a newly developed manifold regularization method, whose natural properties make it more extrapolating, especially for small sample data. In this work, we propose the HR-based NMF (HR-NMF) algorithm, and then apply it to represent gene expression data for further clustering task. The clustering experiments are conducted on five commonly used gene datasets, and the results indicate that the proposed HR-NMF outperforms LR-based NMM and original NMF, which suggests the potential application of HR-NMF for gene expression data.

Note Onset Detection via Nonnegative Factorization of Magnitude Spectrum

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Saeid Sanei

2008-06-01

Full Text Available A novel approach for onset detection of musical notes from audio signals is presented. In contrast to most commonly used conventional approaches, the proposed method features new detection functions constructed from the linear temporal bases that are obtained from the decomposition of musical spectra using nonnegative matrix factorization (NMF. Three forms of detection function, namely, first-order difference function, psychoacoustically motivated relative difference function, and constant-balanced relative difference function, are considered. As the approach works directly on input data, no prior knowledge or statistical information is therefore required. Practical issues, including the choice of the factorization rank and detection robustness to instruments, are also examined experimentally. Due to the scalability issue with the generated nonnegative matrix, the proposed method is only applied to relatively short, single instrument (or voice recordings. Numerical examples are provided to show the good performance of the proposed method, including comparisons between the three detection functions.

On the nonnegative inverse eigenvalue problem of traditional matrices

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Alimohammad Nazari

2014-07-01

Full Text Available In this paper, at first for a given set of real or complex numbers $\\sigma$ with nonnegativesummation, we introduce some special conditions that with them there is no nonnegativetridiagonal matrix in which $\\sigma$ is its spectrum. In continue we present some conditions forexistence such nonnegative tridiagonal matrices.

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

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Zhang, Le; Yu, Yu; Zhang, Pengjie, E-mail: lezhang@sjtu.edu.cn [Department of Astronomy, Shanghai Jiao Tong University, Shanghai, 200240 (China)

2017-10-10

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-negative 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.

Hyperspectral and multispectral data fusion based on linear-quadratic nonnegative matrix factorization

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Benhalouche, Fatima Zohra; Karoui, Moussa Sofiane; Deville, Yannick; Ouamri, Abdelaziz

2017-04-01

This paper proposes three multisharpening approaches to enhance the spatial resolution of urban hyperspectral remote sensing images. These approaches, related to linear-quadratic spectral unmixing techniques, use a linear-quadratic nonnegative matrix factorization (NMF) multiplicative algorithm. These methods begin by unmixing the observable high-spectral/low-spatial resolution hyperspectral and high-spatial/low-spectral resolution multispectral images. The obtained high-spectral/high-spatial resolution features are then recombined, according to the linear-quadratic mixing model, to obtain an unobservable multisharpened high-spectral/high-spatial resolution hyperspectral image. In the first designed approach, hyperspectral and multispectral variables are independently optimized, once they have been coherently initialized. These variables are alternately updated in the second designed approach. In the third approach, the considered hyperspectral and multispectral variables are jointly updated. Experiments, using synthetic and real data, are conducted to assess the efficiency, in spatial and spectral domains, of the designed approaches and of linear NMF-based approaches from the literature. Experimental results show that the designed methods globally yield very satisfactory spectral and spatial fidelities for the multisharpened hyperspectral data. They also prove that these methods significantly outperform the used literature approaches.

Validation of Spectral Unmixing Results from Informed Non-Negative Matrix Factorization (INMF) of Hyperspectral Imagery

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Wright, L.; Coddington, O.; Pilewskie, P.

2017-12-01

Hyperspectral instruments are a growing class of Earth observing sensors designed to improve remote sensing capabilities beyond discrete multi-band sensors by providing tens to hundreds of continuous spectral channels. Improved spectral resolution, range and radiometric accuracy allow the collection of large amounts of spectral data, facilitating thorough characterization of both atmospheric and surface properties. We describe the development of an Informed Non-Negative Matrix Factorization (INMF) spectral unmixing method to exploit this spectral information and separate atmospheric and surface signals based on their physical sources. INMF offers marked benefits over other commonly employed techniques including non-negativity, which avoids physically impossible results; and adaptability, which tailors the method to hyperspectral source separation. The INMF algorithm is adapted to separate contributions from physically distinct sources using constraints on spectral and spatial variability, and library spectra to improve the initial guess. Using this INMF algorithm we decompose hyperspectral imagery from the NASA Hyperspectral Imager for the Coastal Ocean (HICO), with a focus on separating surface and atmospheric signal contributions. HICO's coastal ocean focus provides a dataset with a wide range of atmospheric and surface conditions. These include atmospheres with varying aerosol optical thicknesses and cloud cover. HICO images also provide a range of surface conditions including deep ocean regions, with only minor contributions from the ocean surfaces; and more complex shallow coastal regions with contributions from the seafloor or suspended sediments. We provide extensive comparison of INMF decomposition results against independent measurements of physical properties. These include comparison against traditional model-based retrievals of water-leaving, aerosol, and molecular scattering radiances and other satellite products, such as aerosol optical thickness from

A Nonnegative Latent Factor Model for Large-Scale Sparse Matrices in Recommender Systems via Alternating Direction Method.

Science.gov (United States)

Luo, Xin; Zhou, MengChu; Li, Shuai; You, Zhuhong; Xia, Yunni; Zhu, Qingsheng

2016-03-01

Nonnegative matrix factorization (NMF)-based models possess fine representativeness of a target matrix, which is critically important in collaborative filtering (CF)-based recommender systems. However, current NMF-based CF recommenders suffer from the problem of high computational and storage complexity, as well as slow convergence rate, which prevents them from industrial usage in context of big data. To address these issues, this paper proposes an alternating direction method (ADM)-based nonnegative latent factor (ANLF) model. The main idea is to implement the ADM-based optimization with regard to each single feature, to obtain high convergence rate as well as low complexity. Both computational and storage costs of ANLF are linear with the size of given data in the target matrix, which ensures high efficiency when dealing with extremely sparse matrices usually seen in CF problems. As demonstrated by the experiments on large, real data sets, ANLF also ensures fast convergence and high prediction accuracy, as well as the maintenance of nonnegativity constraints. Moreover, it is simple and easy to implement for real applications of learning systems.

A Global Sampling Based Image Matting Using Non-Negative Matrix Factorization

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NAVEED ALAM

2017-10-01

Full Text Available Image matting is a technique in which a foreground is separated from the background of a given image along with the pixel wise opacity. This foreground can then be seamlessly composited in a different background to obtain a novel scene. This paper presents a global non-parametric sampling algorithm over image patches and utilizes a dimension reduction technique known as NMF (Non-Negative Matrix Factorization. Although some existing non-parametric approaches use large nearby foreground and background regions to sample patches but these approaches fail to take the whole image to sample patches. It is because of the high memory and computational requirements. The use of NMF in the proposed algorithm allows the dimension reduction which reduces the computational cost and memory requirement. The use of NMF also allow the proposed approach to use the whole foreground and background region in the image and reduces the patch complexity and help in efficient patch sampling. The use of patches not only allows the incorporation of the pixel colour but also the local image structure. The use of local structures in the image is important to estimate a high-quality alpha matte especially in the images which have regions containing high texture. The proposed algorithm is evaluated on the standard data set and obtained results are comparable to the state-of-the-art matting techniques

A global sampling based image matting using non-negative matrix factorization

International Nuclear Information System (INIS)

Alam, N.; Sarim, M.; Shaikh, A.B.

2017-01-01

Image matting is a technique in which a foreground is separated from the background of a given image along with the pixel wise opacity. This foreground can then be seamlessly composited in a different background to obtain a novel scene. This paper presents a global non-parametric sampling algorithm over image patches and utilizes a dimension reduction technique known as NMF (Non-Negative Matrix Factorization). Although some existing non-parametric approaches use large nearby foreground and background regions to sample patches but these approaches fail to take the whole image to sample patches. It is because of the high memory and computational requirements. The use of NMF in the proposed algorithm allows the dimension reduction which reduces the computational cost and memory requirement. The use of NMF also allow the proposed approach to use the whole foreground and background region in the image and reduces the patch complexity and help in efficient patch sampling. The use of patches not only allows the incorporation of the pixel colour but also the local image structure. The use of local structures in the image is important to estimate a high-quality alpha matte especially in the images which have regions containing high texture. The proposed algorithm is evaluated on the standard data set and obtained results are comparable to the state-of-the-art matting techniques. (author)

Manifold regularized discriminative nonnegative matrix factorization with fast gradient descent.

Science.gov (United States)

Guan, Naiyang; Tao, Dacheng; Luo, Zhigang; Yuan, Bo

2011-07-01

Nonnegative matrix factorization (NMF) has become a popular data-representation method and has been widely used in image processing and pattern-recognition problems. This is because the learned bases can be interpreted as a natural parts-based representation of data and this interpretation is consistent with the psychological intuition of combining parts to form a whole. For practical classification tasks, however, NMF ignores both the local geometry of data and the discriminative information of different classes. In addition, existing research results show that the learned basis is unnecessarily parts-based because there is neither explicit nor implicit constraint to ensure the representation parts-based. In this paper, we introduce the manifold regularization and the margin maximization to NMF and obtain the manifold regularized discriminative NMF (MD-NMF) to overcome the aforementioned problems. The multiplicative update rule (MUR) can be applied to optimizing MD-NMF, but it converges slowly. In this paper, we propose a fast gradient descent (FGD) to optimize MD-NMF. FGD contains a Newton method that searches the optimal step length, and thus, FGD converges much faster than MUR. In addition, FGD includes MUR as a special case and can be applied to optimizing NMF and its variants. For a problem with 165 samples in R(1600), FGD converges in 28 s, while MUR requires 282 s. We also apply FGD in a variant of MD-NMF and experimental results confirm its efficiency. Experimental results on several face image datasets suggest the effectiveness of MD-NMF.

Contribution of non-negative matrix factorization to the classification of remote sensing images

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Karoui, M. S.; Deville, Y.; Hosseini, S.; Ouamri, A.; Ducrot, D.

2008-10-01

Remote sensing has become an unavoidable tool for better managing our environment, generally by realizing maps of land cover using classification techniques. The classification process requires some pre-processing, especially for data size reduction. The most usual technique is Principal Component Analysis. Another approach consists in regarding each pixel of the multispectral image as a mixture of pure elements contained in the observed area. Using Blind Source Separation (BSS) methods, one can hope to unmix each pixel and to perform the recognition of the classes constituting the observed scene. Our contribution consists in using Non-negative Matrix Factorization (NMF) combined with sparse coding as a solution to BSS, in order to generate new images (which are at least partly separated images) using HRV SPOT images from Oran area, Algeria). These images are then used as inputs of a supervised classifier integrating textural information. The results of classifications of these "separated" images show a clear improvement (correct pixel classification rate improved by more than 20%) compared to classification of initial (i.e. non separated) images. These results show the contribution of NMF as an attractive pre-processing for classification of multispectral remote sensing imagery.

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

Science.gov (United States)

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.

Robust extraction of basis functions for simultaneous and proportional myoelectric control via sparse non-negative matrix factorization

Science.gov (United States)

Lin, Chuang; Wang, Binghui; Jiang, Ning; Farina, Dario

2018-04-01

Objective. This paper proposes a novel simultaneous and proportional multiple degree of freedom (DOF) myoelectric control method for active prostheses. Approach. The approach is based on non-negative matrix factorization (NMF) of surface EMG signals with the inclusion of sparseness constraints. By applying a sparseness constraint to the control signal matrix, it is possible to extract the basis information from arbitrary movements (quasi-unsupervised approach) for multiple DOFs concurrently. Main Results. In online testing based on target hitting, able-bodied subjects reached a greater throughput (TP) when using sparse NMF (SNMF) than with classic NMF or with linear regression (LR). Accordingly, the completion time (CT) was shorter for SNMF than NMF or LR. The same observations were made in two patients with unilateral limb deficiencies. Significance. The addition of sparseness constraints to NMF allows for a quasi-unsupervised approach to myoelectric control with superior results with respect to previous methods for the simultaneous and proportional control of multi-DOF. The proposed factorization algorithm allows robust simultaneous and proportional control, is superior to previous supervised algorithms, and, because of minimal supervision, paves the way to online adaptation in myoelectric control.

Positivity of Fundamental Matrix and Exponential Stability of Delay Differential System

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Alexander Domoshnitsky

2014-01-01

Full Text Available The classical Wazewski theorem established that nonpositivity of all nondiagonal elements pij  (i≠j,  i,j=1,…,n is necessary and sufficient for nonnegativity of the fundamental (Cauchy matrix and consequently for applicability of the Chaplygin approach of approximate integration for system of linear ordinary differential equations xi′t+∑j=1n‍pijtxjt=fit,   i=1,…,n. Results on nonnegativity of the Cauchy matrix for system of delay differential equations xi′t+∑j=1n‍pijtxjhijt=fit,   i=1,…,n, which were based on nonpositivity of all diagonal elements, were presented in the previous works. Then examples, which demonstrated that nonpositivity of nondiagonal coefficients pij is not necessary for systems of delay equations, were found. In this paper first sufficient results about nonnegativity of the Cauchy matrix of the delay system without this assumption are proven. A necessary condition of nonnegativity of the Cauchy matrix is proposed. On the basis of these results on nonnegativity of the Cauchy matrix, necessary and sufficient conditions of the exponential stability of the delay system are obtained.

Non-negative factor analysis supporting the interpretation of elemental distribution images acquired by XRF

International Nuclear Information System (INIS)

Alfeld, Matthias; Falkenberg, Gerald; Wahabzada, Mirwaes; Bauckhage, Christian; Kersting, Kristian; Wellenreuther, Gerd

2014-01-01

Stacks of elemental distribution images acquired by XRF can be difficult to interpret, if they contain high degrees of redundancy and components differing in their quantitative but not qualitative elemental composition. Factor analysis, mainly in the form of Principal Component Analysis (PCA), has been used to reduce the level of redundancy and highlight correlations. PCA, however, does not yield physically meaningful representations as they often contain negative values. This limitation can be overcome, by employing factor analysis that is restricted to non-negativity. In this paper we present the first application of the Python Matrix Factorization Module (pymf) on XRF data. This is done in a case study on the painting Saul and David from the studio of Rembrandt van Rijn. We show how the discrimination between two different Co containing compounds with minimum user intervention and a priori knowledge is supported by Non-Negative Matrix Factorization (NMF).

Structure constrained semi-nonnegative matrix factorization for EEG-based motor imagery classification.

Science.gov (United States)

Lu, Na; Li, Tengfei; Pan, Jinjin; Ren, Xiaodong; Feng, Zuren; Miao, Hongyu

2015-05-01

Electroencephalogram (EEG) provides a non-invasive approach to measure the electrical activities of brain neurons and has long been employed for the development of brain-computer interface (BCI). For this purpose, various patterns/features of EEG data need to be extracted and associated with specific events like cue-paced motor imagery. However, this is a challenging task since EEG data are usually non-stationary time series with a low signal-to-noise ratio. In this study, we propose a novel method, called structure constrained semi-nonnegative matrix factorization (SCS-NMF), to extract the key patterns of EEG data in time domain by imposing the mean envelopes of event-related potentials (ERPs) as constraints on the semi-NMF procedure. The proposed method is applicable to general EEG time series, and the extracted temporal features by SCS-NMF can also be combined with other features in frequency domain to improve the performance of motor imagery classification. Real data experiments have been performed using the SCS-NMF approach for motor imagery classification, and the results clearly suggest the superiority of the proposed method. Comparison experiments have also been conducted. The compared methods include ICA, PCA, Semi-NMF, Wavelets, EMD and CSP, which further verified the effectivity of SCS-NMF. The SCS-NMF method could obtain better or competitive performance over the state of the art methods, which provides a novel solution for brain pattern analysis from the perspective of structure constraint. Copyright © 2015 Elsevier Ltd. All rights reserved.

Feature selection and multi-kernel learning for adaptive graph regularized nonnegative matrix factorization

KAUST Repository

Wang, Jim Jing-Yan

2014-09-20

Nonnegative matrix factorization (NMF), a popular part-based representation technique, does not capture the intrinsic local geometric structure of the data space. Graph regularized NMF (GNMF) was recently proposed to avoid this limitation by regularizing NMF with a nearest neighbor graph constructed from the input data set. However, GNMF has two main bottlenecks. First, using the original feature space directly to construct the graph is not necessarily optimal because of the noisy and irrelevant features and nonlinear distributions of data samples. Second, one possible way to handle the nonlinear distribution of data samples is by kernel embedding. However, it is often difficult to choose the most suitable kernel. To solve these bottlenecks, we propose two novel graph-regularized NMF methods, AGNMFFS and AGNMFMK, by introducing feature selection and multiple-kernel learning to the graph regularized NMF, respectively. Instead of using a fixed graph as in GNMF, the two proposed methods learn the nearest neighbor graph that is adaptive to the selected features and learned multiple kernels, respectively. For each method, we propose a unified objective function to conduct feature selection/multi-kernel learning, NMF and adaptive graph regularization simultaneously. We further develop two iterative algorithms to solve the two optimization problems. Experimental results on two challenging pattern classification tasks demonstrate that the proposed methods significantly outperform state-of-the-art data representation methods.

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

Science.gov (United States)

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.

A characterization of trace zero bisymmetric nonnegative $5 \\times 5$ matrices

OpenAIRE

Somphotphisut, Somchai; Wiboonton, Keng

2017-01-01

Let $\\lambda_1 \\geq \\lambda_2 \\geq \\lambda_3 \\geq \\lambda_4 \\geq \\lambda_5 \\geq -\\lambda_1$ be real numbers such that $\\sum_{i=1}^5 \\lambda_i =0$. In \\cite{oren}, O. Spector prove that a necessary and sufficient condition for $\\lambda_1, \\lambda_2, \\lambda_3, \\lambda_4, \\lambda_5$ to be the eigenvalues of a symmetric nonnegative $5 \\times 5$ matrix is "$\\lambda_2+\\lambda_5

Predicting and understanding comprehensive drug-drug interactions via semi-nonnegative matrix factorization.

Science.gov (United States)

Yu, Hui; Mao, Kui-Tao; Shi, Jian-Yu; Huang, Hua; Chen, Zhi; Dong, Kai; Yiu, Siu-Ming

2018-04-11

Drug-drug interactions (DDIs) always cause unexpected and even adverse drug reactions. It is important to identify DDIs before drugs are used in the market. However, preclinical identification of DDIs requires much money and time. Computational approaches have exhibited their abilities to predict potential DDIs on a large scale by utilizing pre-market drug properties (e.g. chemical structure). Nevertheless, none of them can predict two comprehensive types of DDIs, including enhancive and degressive DDIs, which increases and decreases the behaviors of the interacting drugs respectively. There is a lack of systematic analysis on the structural relationship among known DDIs. Revealing such a relationship is very important, because it is able to help understand how DDIs occur. Both the prediction of comprehensive DDIs and the discovery of structural relationship among them play an important guidance when making a co-prescription. In this work, treating a set of comprehensive DDIs as a signed network, we design a novel model (DDINMF) for the prediction of enhancive and degressive DDIs based on semi-nonnegative matrix factorization. Inspiringly, DDINMF achieves the conventional DDI prediction (AUROC = 0.872 and AUPR = 0.605) and the comprehensive DDI prediction (AUROC = 0.796 and AUPR = 0.579). Compared with two state-of-the-art approaches, DDINMF shows it superiority. Finally, representing DDIs as a binary network and a signed network respectively, an analysis based on NMF reveals crucial knowledge hidden among DDIs. Our approach is able to predict not only conventional binary DDIs but also comprehensive DDIs. More importantly, it reveals several key points about the DDI network: (1) both binary and signed networks show fairly clear clusters, in which both drug degree and the difference between positive degree and negative degree show significant distribution; (2) the drugs having large degrees tend to have a larger difference between positive degree

Encoding of rat working memory by power of multi-channel local field potentials via sparse non-negative matrix factorization

Institute of Scientific and Technical Information of China (English)

Xu Liu; Tiao-Tiao Liu; Wen-Wen Bai; Hu Yi; Shuang-Yan Li; Xin Tian

2013-01-01

Working memory plays an important role in human cognition.This study investigated how working memory was encoded by the power of multi-channel local field potentials (LFPs) based on sparse nonnegative matrix factorization (SNMF).SNMF was used to extract features from LFPs recorded from the prefrontal cortex of four Sprague-Dawley rats during a memory task in a Y maze,with 10 trials for each rat.Then the power-increased LFP components were selected as working memory-related features and the other components were removed.After that,the inverse operation of SNMF was used to study the encoding of working memory in the timefrequency domain.We demonstrated that theta and gamma power increased significantly during the working memory task.The results suggested that postsynaptic activity was simulated well by the sparse activity model.The theta and gamma bands were meaningful for encoding working memory.

Nonnegative matrix factorization with the Itakura-Saito divergence: with application to music analysis.

Science.gov (United States)

Févotte, Cédric; Bertin, Nancy; Durrieu, Jean-Louis

2009-03-01

This letter presents theoretical, algorithmic, and experimental results about nonnegative matrix factorization (NMF) with the Itakura-Saito (IS) divergence. We describe how IS-NMF is underlaid by a well-defined statistical model of superimposed gaussian components and is equivalent to maximum likelihood estimation of variance parameters. This setting can accommodate regularization constraints on the factors through Bayesian priors. In particular, inverse-gamma and gamma Markov chain priors are considered in this work. Estimation can be carried out using a space-alternating generalized expectation-maximization (SAGE) algorithm; this leads to a novel type of NMF algorithm, whose convergence to a stationary point of the IS cost function is guaranteed. We also discuss the links between the IS divergence and other cost functions used in NMF, in particular, the Euclidean distance and the generalized Kullback-Leibler (KL) divergence. As such, we describe how IS-NMF can also be performed using a gradient multiplicative algorithm (a standard algorithm structure in NMF) whose convergence is observed in practice, though not proven. Finally, we report a furnished experimental comparative study of Euclidean-NMF, KL-NMF, and IS-NMF algorithms applied to the power spectrogram of a short piano sequence recorded in real conditions, with various initializations and model orders. Then we show how IS-NMF can successfully be employed for denoising and upmix (mono to stereo conversion) of an original piece of early jazz music. These experiments indicate that IS-NMF correctly captures the semantics of audio and is better suited to the representation of music signals than NMF with the usual Euclidean and KL costs.

Matrix Metalloproteinase Enzyme Family

Directory of Open Access Journals (Sweden)

Ozlem Goruroglu Ozturk

2013-04-01

Full Text Available Matrix metalloproteinases play an important role in many biological processes such as embriogenesis, tissue remodeling, wound healing, and angiogenesis, and in some pathological conditions such as atherosclerosis, arthritis and cancer. Currently, 24 genes have been identified in humans that encode different groups of matrix metalloproteinase enzymes. This review discuss the members of the matrix metalloproteinase family and their substrate specificity, structure, function and the regulation of their enzyme activity by tissue inhibitors. [Archives Medical Review Journal 2013; 22(2.000: 209-220

Multivariate Matrix-Exponential Distributions

DEFF Research Database (Denmark)

Bladt, Mogens; Nielsen, Bo Friis

2010-01-01

be written as linear combinations of the elements in the exponential of a matrix. For this reason we shall refer to multivariate distributions with rational Laplace transform as multivariate matrix-exponential distributions (MVME). The marginal distributions of an MVME are univariate matrix......-exponential distributions. We prove a characterization that states that a distribution is an MVME distribution if and only if all non-negative, non-null linear combinations of the coordinates have a univariate matrix-exponential distribution. This theorem is analog to a well-known characterization theorem...

NMF-mGPU: non-negative matrix factorization on multi-GPU systems.

Science.gov (United States)

Mejía-Roa, Edgardo; Tabas-Madrid, Daniel; Setoain, Javier; García, Carlos; Tirado, Francisco; Pascual-Montano, Alberto

2015-02-13

In the last few years, the Non-negative Matrix Factorization ( NMF ) technique has gained a great interest among the Bioinformatics community, since it is able to extract interpretable parts from high-dimensional datasets. However, the computing time required to process large data matrices may become impractical, even for a parallel application running on a multiprocessors cluster. In this paper, we present NMF-mGPU, an efficient and easy-to-use implementation of the NMF algorithm that takes advantage of the high computing performance delivered by Graphics-Processing Units ( GPUs ). Driven by the ever-growing demands from the video-games industry, graphics cards usually provided in PCs and laptops have evolved from simple graphics-drawing platforms into high-performance programmable systems that can be used as coprocessors for linear-algebra operations. However, these devices may have a limited amount of on-board memory, which is not considered by other NMF implementations on GPU. NMF-mGPU is based on CUDA ( Compute Unified Device Architecture ), the NVIDIA's framework for GPU computing. On devices with low memory available, large input matrices are blockwise transferred from the system's main memory to the GPU's memory, and processed accordingly. In addition, NMF-mGPU has been explicitly optimized for the different CUDA architectures. Finally, platforms with multiple GPUs can be synchronized through MPI ( Message Passing Interface ). In a four-GPU system, this implementation is about 120 times faster than a single conventional processor, and more than four times faster than a single GPU device (i.e., a super-linear speedup). Applications of GPUs in Bioinformatics are getting more and more attention due to their outstanding performance when compared to traditional processors. In addition, their relatively low price represents a highly cost-effective alternative to conventional clusters. In life sciences, this results in an excellent opportunity to facilitate the

Perron–Frobenius theorem for nonnegative multilinear forms and extensions

OpenAIRE

Friedland, S.; Gaubert, S.; Han, L.

2013-01-01

We prove an analog of Perron-Frobenius theorem for multilinear forms with nonnegative coefficients, and more generally, for polynomial maps with nonnegative coefficients. We determine the geometric convergence rate of the power algorithm to the unique normalized eigenvector.

Adaptive Multiview Nonnegative Matrix Factorization Algorithm for Integration of Multimodal Biomedical Data

Directory of Open Access Journals (Sweden)

Bisakha Ray

2017-08-01

Full Text Available The amounts and types of available multimodal tumor data are rapidly increasing, and their integration is critical for fully understanding the underlying cancer biology and personalizing treatment. However, the development of methods for effectively integrating multimodal data in a principled manner is lagging behind our ability to generate the data. In this article, we introduce an extension to a multiview nonnegative matrix factorization algorithm (NNMF for dimensionality reduction and integration of heterogeneous data types and compare the predictive modeling performance of the method on unimodal and multimodal data. We also present a comparative evaluation of our novel multiview approach and current data integration methods. Our work provides an efficient method to extend an existing dimensionality reduction method. We report rigorous evaluation of the method on large-scale quantitative protein and phosphoprotein tumor data from the Clinical Proteomic Tumor Analysis Consortium (CPTAC acquired using state-of-the-art liquid chromatography mass spectrometry. Exome sequencing and RNA-Seq data were also available from The Cancer Genome Atlas for the same tumors. For unimodal data, in case of breast cancer, transcript levels were most predictive of estrogen and progesterone receptor status and copy number variation of human epidermal growth factor receptor 2 status. For ovarian and colon cancers, phosphoprotein and protein levels were most predictive of tumor grade and stage and residual tumor, respectively. When multiview NNMF was applied to multimodal data to predict outcomes, the improvement in performance is not overall statistically significant beyond unimodal data, suggesting that proteomics data may contain more predictive information regarding tumor phenotypes than transcript levels, probably due to the fact that proteins are the functional gene products and therefore a more direct measurement of the functional state of the tumor. Here, we

HPC-NMF: A High-Performance Parallel Algorithm for Nonnegative Matrix Factorization

Energy Technology Data Exchange (ETDEWEB)

2016-08-22

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 distributed algorithms to solve the problem for big data sets. We propose a high-performance distributed-memory parallel algorithm that computes the factorization by iteratively solving alternating non-negative least squares (NLS) subproblems for $\\WW$ and $\\HH$. 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). As opposed to previous implementation, our algorithm is also flexible: It performs well for both dense and sparse matrices, and allows the user to choose any one of the multiple algorithms for solving the updates to low rank factors $\\WW$ and $\\HH$ within the alternating iterations.

A max version of Perron--Frobenius theorem for nonnegative tensor

OpenAIRE

Afshin, Hamid Reza; Shojaeifard, Ali Reza

2015-01-01

In this paper we generalize the max algebra system of nonnegative matrices to the class of nonnegative tensors and derive its fundamental properties. If $\\mathbb{A} \\in \\Re_ + ^{\\left[ {m,n} \\right]}$ is a nonnegative essentially positive tensor such that satisfies the condition class NC, we prove that there exist $\\mu \\left( \\mathbb{A} \\right)$ and a corresponding positive vector $x$ such that $\\mathop {\\max }\\limits_{1 \\le{i_2}\\cdots {i_m} \\le n} \\left\\{ {{a_{i{i_2}\\cdots {i_m}}}{x_{{i_2}}}...

Local hyperspectral data multisharpening based on linear/linear-quadratic nonnegative matrix factorization by integrating lidar data

Science.gov (United States)

Benhalouche, Fatima Zohra; Karoui, Moussa Sofiane; Deville, Yannick; Ouamri, Abdelaziz

2015-10-01

In this paper, a new Spectral-Unmixing-based approach, using Nonnegative Matrix Factorization (NMF), is proposed to locally multi-sharpen hyperspectral data by integrating a Digital Surface Model (DSM) obtained from LIDAR data. In this new approach, the nature of the local mixing model is detected by using the local variance of the object elevations. The hyper/multispectral images are explored using small zones. In each zone, the variance of the object elevations is calculated from the DSM data in this zone. This variance is compared to a threshold value and the adequate linear/linearquadratic spectral unmixing technique is used in the considered zone to independently unmix hyperspectral and multispectral data, using an adequate linear/linear-quadratic NMF-based approach. The obtained spectral and spatial information thus respectively extracted from the hyper/multispectral images are then recombined in the considered zone, according to the selected mixing model. Experiments based on synthetic hyper/multispectral data are carried out to evaluate the performance of the proposed multi-sharpening approach and literature linear/linear-quadratic approaches used on the whole hyper/multispectral data. In these experiments, real DSM data are used to generate synthetic data containing linear and linear-quadratic mixed pixel zones. The DSM data are also used for locally detecting the nature of the mixing model in the proposed approach. Globally, the proposed approach yields good spatial and spectral fidelities for the multi-sharpened data and significantly outperforms the used literature methods.

Extremal extensions for the sum of nonnegative selfadjoint relations

NARCIS (Netherlands)

Hassi, Seppo; Sandovici, Adrian; De Snoo, Henk; Winkler, Henrik

2007-01-01

The sum A + B of two nonnegative selfadjoint relations (multivalued operators) A and B is a nonnegative relation. The class of all extremal extensions of the sum A + B is characterized as products of relations via an auxiliary Hilbert space associated with A and B. The so-called form sum extension

A Poisson nonnegative matrix factorization method with parameter subspace clustering constraint for endmember extraction in hyperspectral imagery

Science.gov (United States)

Sun, Weiwei; Ma, Jun; Yang, Gang; Du, Bo; Zhang, Liangpei

2017-06-01

A new Bayesian method named Poisson Nonnegative Matrix Factorization with Parameter Subspace Clustering Constraint (PNMF-PSCC) has been presented to extract endmembers from Hyperspectral Imagery (HSI). First, the method integrates the liner spectral mixture model with the Bayesian framework and it formulates endmember extraction into a Bayesian inference problem. Second, the Parameter Subspace Clustering Constraint (PSCC) is incorporated into the statistical program to consider the clustering of all pixels in the parameter subspace. The PSCC could enlarge differences among ground objects and helps finding endmembers with smaller spectrum divergences. Meanwhile, the PNMF-PSCC method utilizes the Poisson distribution as the prior knowledge of spectral signals to better explain the quantum nature of light in imaging spectrometer. Third, the optimization problem of PNMF-PSCC is formulated into maximizing the joint density via the Maximum A Posterior (MAP) estimator. The program is finally solved by iteratively optimizing two sub-problems via the Alternating Direction Method of Multipliers (ADMM) framework and the FURTHESTSUM initialization scheme. Five state-of-the art methods are implemented to make comparisons with the performance of PNMF-PSCC on both the synthetic and real HSI datasets. Experimental results show that the PNMF-PSCC outperforms all the five methods in Spectral Angle Distance (SAD) and Root-Mean-Square-Error (RMSE), and especially it could identify good endmembers for ground objects with smaller spectrum divergences.

A Necessary Condition for the Spectrum of Nonnegative Symmetric $ 5 \\times 5 $ Matrices

OpenAIRE

Loewy, Raphael; Spector, Oren

2016-01-01

Let $A$ be a nonnegative symmetric $ 5 \\times 5 $ matrix with eigenvalues $ \\lambda_1 \\geq \\lambda_2 \\geq \\lambda_3 \\geq \\lambda_4 \\geq \\lambda_5 $. We show that if $ \\sum_{i=1}^{5} \\lambda_{i} \\geq \\frac{1}{2} \\lambda_1 $ then $ \\lambda_3 \\leq \\sum_{i=1}^{5} \\lambda_{i} $. McDonald and Neumann showed that $ \\lambda_1 + \\lambda_3 + \\lambda_4 \\geq 0 $. Let $ \\sigma = \\left( \\lambda_1, \\lambda_2, \\lambda_3, \\lambda_4, \\lambda_5 \\right) $ be a list of decreasing real numbers satisfying: 1. $ \\su...

Joint Dictionary Learning-Based Non-Negative Matrix Factorization for Voice Conversion to Improve Speech Intelligibility After Oral Surgery.

Science.gov (United States)

Fu, Szu-Wei; Li, Pei-Chun; Lai, Ying-Hui; Yang, Cheng-Chien; Hsieh, Li-Chun; Tsao, Yu

2017-11-01

Objective: This paper focuses on machine learning based voice conversion (VC) techniques for improving the speech intelligibility of surgical patients who have had parts of their articulators removed. Because of the removal of parts of the articulator, a patient's speech may be distorted and difficult to understand. To overcome this problem, VC methods can be applied to convert the distorted speech such that it is clear and more intelligible. To design an effective VC method, two key points must be considered: 1) the amount of training data may be limited (because speaking for a long time is usually difficult for postoperative patients); 2) rapid conversion is desirable (for better communication). Methods: We propose a novel joint dictionary learning based non-negative matrix factorization (JD-NMF) algorithm. Compared to conventional VC techniques, JD-NMF can perform VC efficiently and effectively with only a small amount of training data. Results: The experimental results demonstrate that the proposed JD-NMF method not only achieves notably higher short-time objective intelligibility (STOI) scores (a standardized objective intelligibility evaluation metric) than those obtained using the original unconverted speech but is also significantly more efficient and effective than a conventional exemplar-based NMF VC method. Conclusion: The proposed JD-NMF method may outperform the state-of-the-art exemplar-based NMF VC method in terms of STOI scores under the desired scenario. Significance: We confirmed the advantages of the proposed joint training criterion for the NMF-based VC. Moreover, we verified that the proposed JD-NMF can effectively improve the speech intelligibility scores of oral surgery patients. Objective: This paper focuses on machine learning based voice conversion (VC) techniques for improving the speech intelligibility of surgical patients who have had parts of their articulators removed. Because of the removal of parts of the articulator, a patient

On Improving Convergence Rates for Nonnegative Kernel Density Estimators

OpenAIRE

Terrell, George R.; Scott, David W.

1980-01-01

To improve the rate of decrease of integrated mean square error for nonparametric kernel density estimators beyond $0(n^{-\\frac{4}{5}}),$ we must relax the constraint that the density estimate be a bonafide density function, that is, be nonnegative and integrate to one. All current methods for kernel (and orthogonal series) estimators relax the nonnegativity constraint. In this paper we show how to achieve similar improvement by relaxing the integral constraint only. This is important in appl...

Inverse Interval Matrix: A Survey

Czech Academy of Sciences Publication Activity Database

Rohn, Jiří; Farhadsefat, R.

2011-01-01

Roč. 22, - (2011), s. 704-719 E-ISSN 1081-3810 R&D Projects: GA ČR GA201/09/1957; GA ČR GC201/08/J020 Institutional research plan: CEZ:AV0Z10300504 Keywords : interval matrix * inverse interval matrix * NP-hardness * enclosure * unit midpoint * inverse sign stability * nonnegative invertibility * absolute value equation * algorithm Subject RIV: BA - General Mathematics Impact factor: 0.808, year: 2010 http://www.math.technion.ac.il/iic/ ela / ela -articles/articles/vol22_pp704-719.pdf

Efficient non-negative constrained model-based inversion in optoacoustic tomography

International Nuclear Information System (INIS)

Ding, Lu; Luís Deán-Ben, X; Lutzweiler, Christian; Razansky, Daniel; Ntziachristos, Vasilis

2015-01-01

The inversion accuracy in optoacoustic tomography depends on a number of parameters, including the number of detectors employed, discrete sampling issues or imperfectness of the forward model. These parameters result in ambiguities on the reconstructed image. A common ambiguity is the appearance of negative values, which have no physical meaning since optical absorption can only be higher or equal than zero. We investigate herein algorithms that impose non-negative constraints in model-based optoacoustic inversion. Several state-of-the-art non-negative constrained algorithms are analyzed. Furthermore, an algorithm based on the conjugate gradient method is introduced in this work. We are particularly interested in investigating whether positive restrictions lead to accurate solutions or drive the appearance of errors and artifacts. It is shown that the computational performance of non-negative constrained inversion is higher for the introduced algorithm than for the other algorithms, while yielding equivalent results. The experimental performance of this inversion procedure is then tested in phantoms and small animals, showing an improvement in image quality and quantitativeness with respect to the unconstrained approach. The study performed validates the use of non-negative constraints for improving image accuracy compared to unconstrained methods, while maintaining computational efficiency. (paper)

Learning Microbial Community Structures with Supervised and Unsupervised Non-negative Matrix Factorization.

Science.gov (United States)

Cai, Yun; Gu, Hong; Kenney, Toby

2017-08-31

Learning the structure of microbial communities is critical in understanding the different community structures and functions of microbes in distinct individuals. We view microbial communities as consisting of many subcommunities which are formed by certain groups of microbes functionally dependent on each other. The focus of this paper is on methods for extracting the subcommunities from the data, in particular Non-Negative Matrix Factorization (NMF). Our methods can be applied to both OTU data and functional metagenomic data. We apply the existing unsupervised NMF method and also develop a new supervised NMF method for extracting interpretable information from classification problems. The relevance of the subcommunities identified by NMF is demonstrated by their excellent performance for classification. Through three data examples, we demonstrate how to interpret the features identified by NMF to draw meaningful biological conclusions and discover hitherto unidentified patterns in the data. Comparing whole metagenomes of various mammals, (Muegge et al., Science 332:970-974, 2011), the biosynthesis of macrolides pathway is found in hindgut-fermenting herbivores, but not carnivores. This is consistent with results in veterinary science that macrolides should not be given to non-ruminant herbivores. For time series microbiome data from various body sites (Caporaso et al., Genome Biol 12:50, 2011), a shift in the microbial communities is identified for one individual. The shift occurs at around the same time in the tongue and gut microbiomes, indicating that the shift is a genuine biological trait, rather than an artefact of the method. For whole metagenome data from IBD patients and healthy controls (Qin et al., Nature 464:59-65, 2010), we identify differences in a number of pathways (some known, others new). NMF is a powerful tool for identifying the key features of microbial communities. These identified features can not only be used to perform difficult

A non-negative Wigner-type distribution

International Nuclear Information System (INIS)

Cartwright, N.D.

1976-01-01

The Wigner function, which is commonly used as a joint distribution for non-commuting observables, is shown to be non-negative in all quantum states when smoothed with a gaussian whose variances are greater than or equal to those of the minimum uncertainty wave packet. (Auth.)

A Fast Newton-Shamanskii Iteration for a Matrix Equation Arising from M/G/1-Type Markov Chains

Directory of Open Access Journals (Sweden)

Pei-Chang Guo

2017-01-01

Full Text Available For the nonlinear matrix equations arising in the analysis of M/G/1-type and GI/M/1-type Markov chains, the minimal nonnegative solution G or R can be found by Newton-like methods. We prove monotone convergence results for the Newton-Shamanskii iteration for this class of equations. Starting with zero initial guess or some other suitable initial guess, the Newton-Shamanskii iteration provides a monotonically increasing sequence of nonnegative matrices converging to the minimal nonnegative solution. A Schur decomposition method is used to accelerate the Newton-Shamanskii iteration. Numerical examples illustrate the effectiveness of the Newton-Shamanskii iteration.

Projective-Dual Method for Solving Systems of Linear Equations with Nonnegative Variables

Science.gov (United States)

Ganin, B. V.; Golikov, A. I.; Evtushenko, Yu. G.

2018-02-01

In order to solve an underdetermined system of linear equations with nonnegative variables, the projection of a given point onto its solutions set is sought. The dual of this problem—the problem of unconstrained maximization of a piecewise-quadratic function—is solved by Newton's method. The problem of unconstrained optimization dual of the regularized problem of finding the projection onto the solution set of the system is considered. A connection of duality theory and Newton's method with some known algorithms of projecting onto a standard simplex is shown. On the example of taking into account the specifics of the constraints of the transport linear programming problem, the possibility to increase the efficiency of calculating the generalized Hessian matrix is demonstrated. Some examples of numerical calculations using MATLAB are presented.

On Convergence with respect to an Ideal and a Family of Matrices

Directory of Open Access Journals (Sweden)

Jan-David Hardtke

2014-01-01

Full Text Available P. Das et al. recently introduced and studied the notions of strong AI-summability with respect to an Orlicz function F and AI-statistical convergence, where A is a nonnegative regular matrix and I is an ideal on the set of natural numbers. In this paper, we will generalise these notions by replacing A with a family of matrices and F with a family of Orlicz functions or moduli and study the thus obtained convergence methods. We will also give an application in Banach space theory, presenting a generalisation of Simons' sup-limsup-theorem to the newly introduced convergence methods (for the case that the filter generated by the ideal I has a countable base, continuing some of the author's previous work.

Audio Source Separation in Reverberant Environments Using β-Divergence-Based Nonnegative Factorization

DEFF Research Database (Denmark)

Fakhry, Mahmoud; Svaizer, Piergiorgio; Omologo, Maurizio

2017-01-01

-maximization algorithm and used to separate the signals by means of multichannel Wiener filtering. We propose to estimate these parameters by applying nonnegative factorization based on prior information on source variances. In the nonnegative factorization, spectral basis matrices can be defined as the prior...... information. The matrices can be either extracted or indirectly made available through a redundant library that is trained in advance. In a separate step, applying nonnegative tensor factorization, two algorithms are proposed in order to either extract or detect the basis matrices that best represent......In Gaussian model-based multichannel audio source separation, the likelihood of observed mixtures of source signals is parametrized by source spectral variances and by associated spatial covariance matrices. These parameters are estimated by maximizing the likelihood through an expectation...

Identification of necessary and sufficient conditions for real non-negativeness of rational matrices

International Nuclear Information System (INIS)

Saeed, K.

1982-12-01

The necessary and sufficient conditions for real non-negativeness of rational matrices have been identified. A programmable algorithm is developed and is given with its computer flow chart. This algorithm can be used as a general solution to test the real non-negativeness of rational matrices. The computer program assures the feasibility of the suggested algorithm. (author)

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

Energy Technology Data Exchange (ETDEWEB)

Lee, Dong-Chang [CancerCare Manitoba, Winnipeg, MB (Canada); Jans, Hans; McEwan, Sandy; Riauka, Terence [Department of Oncology, University of Alberta, Edmonton, AB (Canada); Cross Cancer Institute, Alberta Health Services, Edmonton, AB (Canada); Martin, Wayne; Wieler, Marguerite [Division of Neurology, University of Alberta, Edmonton, AB (Canada)

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. 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.

When to call a linear system nonnegative

NARCIS (Netherlands)

Nieuwenhuis, J.W.

1998-01-01

In this paper we will consider discrete time invariant linear systems that allow for an input-state-output representation with a finite dimensional state space, and that have a finite number of inputs and outputs. The basic issue in this paper is when to call these systems nonnegative. An important

ℓ1/2-norm regularized nonnegative low-rank and sparse affinity graph for remote sensing image segmentation

Science.gov (United States)

Tian, Shu; Zhang, Ye; Yan, Yiming; Su, Nan

2016-10-01

Segmentation of real-world remote sensing images is a challenge due to the complex texture information with high heterogeneity. Thus, graph-based image segmentation methods have been attracting great attention in the field of remote sensing. However, most of the traditional graph-based approaches fail to capture the intrinsic structure of the feature space and are sensitive to noises. A ℓ-norm regularization-based graph segmentation method is proposed to segment remote sensing images. First, we use the occlusion of the random texture model (ORTM) to extract the local histogram features. Then, a ℓ-norm regularized low-rank and sparse representation (LNNLRS) is implemented to construct a ℓ-regularized nonnegative low-rank and sparse graph (LNNLRS-graph), by the union of feature subspaces. Moreover, the LNNLRS-graph has a high ability to discriminate the manifold intrinsic structure of highly homogeneous texture information. Meanwhile, the LNNLRS representation takes advantage of the low-rank and sparse characteristics to remove the noises and corrupted data. Last, we introduce the LNNLRS-graph into the graph regularization nonnegative matrix factorization to enhance the segmentation accuracy. The experimental results using remote sensing images show that when compared to five state-of-the-art image segmentation methods, the proposed method achieves more accurate segmentation results.

Low-rank matrix approximation with manifold regularization.

Science.gov (United States)

Zhang, Zhenyue; Zhao, Keke

2013-07-01

This paper proposes a new model of low-rank matrix factorization that incorporates manifold regularization to the matrix factorization. Superior to the graph-regularized nonnegative matrix factorization, this new regularization model has globally optimal and closed-form solutions. A direct algorithm (for data with small number of points) and an alternate iterative algorithm with inexact inner iteration (for large scale data) are proposed to solve the new model. A convergence analysis establishes the global convergence of the iterative algorithm. The efficiency and precision of the algorithm are demonstrated numerically through applications to six real-world datasets on clustering and classification. Performance comparison with existing algorithms shows the effectiveness of the proposed method for low-rank factorization in general.

Adaptive and neuroadaptive control for nonnegative and compartmental dynamical systems

Science.gov (United States)

Volyanskyy, Kostyantyn Y.

Neural networks have been extensively used for adaptive system identification as well as adaptive and neuroadaptive control of highly uncertain systems. The goal of adaptive and neuroadaptive control is to achieve system performance without excessive reliance on system models. To improve robustness and the speed of adaptation of adaptive and neuroadaptive controllers several controller architectures have been proposed in the literature. In this dissertation, we develop a new neuroadaptive control architecture for nonlinear uncertain dynamical systems. The proposed framework involves a novel controller architecture with additional terms in the update laws that are constructed using a moving window of the integrated system uncertainty. These terms can be used to identify the ideal system weights of the neural network as well as effectively suppress system uncertainty. Linear and nonlinear parameterizations of the system uncertainty are considered and state and output feedback neuroadaptive controllers are developed. Furthermore, we extend the developed framework to discrete-time dynamical systems. To illustrate the efficacy of the proposed approach we apply our results to an aircraft model with wing rock dynamics, a spacecraft model with unknown moment of inertia, and an unmanned combat aerial vehicle undergoing actuator failures, and compare our results with standard neuroadaptive control methods. Nonnegative systems are essential in capturing the behavior of a wide range of dynamical systems involving dynamic states whose values are nonnegative. A sub-class of nonnegative dynamical systems are compartmental systems. These systems are derived from mass and energy balance considerations and are comprised of homogeneous interconnected microscopic subsystems or compartments which exchange variable quantities of material via intercompartmental flow laws. In this dissertation, we develop direct adaptive and neuroadaptive control framework for stabilization, disturbance

How quantum are non-negative wavefunctions?

International Nuclear Information System (INIS)

Hastings, M. B.

2016-01-01

We consider wavefunctions which are non-negative in some tensor product basis. We study what possible teleportation can occur in such wavefunctions, giving a complete answer in some cases (when one system is a qubit) and partial answers elsewhere. We use this to show that a one-dimensional wavefunction which is non-negative and has zero correlation length can be written in a “coherent Gibbs state” form, as explained later. We conjecture that such holds in higher dimensions. Additionally, some results are provided on possible teleportation in general wavefunctions, explaining how Schmidt coefficients before measurement limit the possible Schmidt coefficients after measurement, and on the absence of a “generalized area law” [D. Aharonov et al., in Proceedings of Foundations of Computer Science (FOCS) (IEEE, 2014), p. 246; e-print arXiv.org:1410.0951] even for Hamiltonians with no sign problem. One of the motivations for this work is an attempt to prove a conjecture about ground state wavefunctions which have an “intrinsic” sign problem that cannot be removed by any quantum circuit. We show a weaker version of this, showing that the sign problem is intrinsic for commuting Hamiltonians in the same phase as the double semion model under the technical assumption that TQO-2 holds [S. Bravyi et al., J. Math. Phys. 51, 093512 (2010)

How quantum are non-negative wavefunctions?

Energy Technology Data Exchange (ETDEWEB)

Hastings, M. B. [Station Q, Microsoft Research, Santa Barbara, California 93106-6105, USA and Quantum Architectures and Computation Group, Microsoft Research, Redmond, Washington 98052 (United States)

2016-01-15

We consider wavefunctions which are non-negative in some tensor product basis. We study what possible teleportation can occur in such wavefunctions, giving a complete answer in some cases (when one system is a qubit) and partial answers elsewhere. We use this to show that a one-dimensional wavefunction which is non-negative and has zero correlation length can be written in a “coherent Gibbs state” form, as explained later. We conjecture that such holds in higher dimensions. Additionally, some results are provided on possible teleportation in general wavefunctions, explaining how Schmidt coefficients before measurement limit the possible Schmidt coefficients after measurement, and on the absence of a “generalized area law” [D. Aharonov et al., in Proceedings of Foundations of Computer Science (FOCS) (IEEE, 2014), p. 246; e-print arXiv.org:1410.0951] even for Hamiltonians with no sign problem. One of the motivations for this work is an attempt to prove a conjecture about ground state wavefunctions which have an “intrinsic” sign problem that cannot be removed by any quantum circuit. We show a weaker version of this, showing that the sign problem is intrinsic for commuting Hamiltonians in the same phase as the double semion model under the technical assumption that TQO-2 holds [S. Bravyi et al., J. Math. Phys. 51, 093512 (2010)].

Family-Centered Early Intervention Visual Impairment Services through Matrix Session Planning

Science.gov (United States)

Ely, Mindy S.; Gullifor, Kateri; Hollinshead, Tara

2017-01-01

Early intervention visual impairment services are built on a model that values family. Matrix session planning pulls together parent priorities, family routines, and identified strategies in a way that helps families and early intervention professionals outline a plan that can both highlight long-term goals and focus on what can be done today.…

Nonnegative constraint quadratic program technique to enhance the resolution of γ spectra

Science.gov (United States)

Li, Jinglun; Xiao, Wuyun; Ai, Xianyun; Chen, Ye

2018-04-01

Two concepts of the nonnegative least squares problem (NNLS) and the linear complementarity problem (LCP) are introduced for the resolution enhancement of the γ spectra. The respective algorithms such as the active set method and the primal-dual interior point method are applied to solve the above two problems. In mathematics, the nonnegative constraint results in the sparsity of the optimal solution of the deconvolution, and it is this sparsity that enhances the resolution. Finally, a comparison in the peak position accuracy and the computation time is made between these two methods and the boosted L_R and Gold methods.

On nonnegative solutions of second order linear functional differential equations

Czech Academy of Sciences Publication Activity Database

Lomtatidze, Alexander; Vodstrčil, Petr

2004-01-01

Roč. 32, č. 1 (2004), s. 59-88 ISSN 1512-0015 Institutional research plan: CEZ:AV0Z1019905 Keywords : second order linear functional differential equations * nonnegative solution * two-point boundary value problem Subject RIV: BA - General Mathematics

Matrix-exponential distributions in applied probability

CERN Document Server

Bladt, Mogens

2017-01-01

This book contains an in-depth treatment of matrix-exponential (ME) distributions and their sub-class of phase-type (PH) distributions. Loosely speaking, an ME distribution is obtained through replacing the intensity parameter in an exponential distribution by a matrix. The ME distributions can also be identified as the class of non-negative distributions with rational Laplace transforms. If the matrix has the structure of a sub-intensity matrix for a Markov jump process we obtain a PH distribution which allows for nice probabilistic interpretations facilitating the derivation of exact solutions and closed form formulas. The full potential of ME and PH unfolds in their use in stochastic modelling. Several chapters on generic applications, like renewal theory, random walks and regenerative processes, are included together with some specific examples from queueing theory and insurance risk. We emphasize our intention towards applications by including an extensive treatment on statistical methods for PH distribu...

Nonnegative definite EAP and ODF estimation via a unified multi-shell HARDI reconstruction.

Science.gov (United States)

Cheng, Jian; Jiang, Tianzi; Deriche, Rachid

2012-01-01

In High Angular Resolution Diffusion Imaging (HARDI), Orientation Distribution Function (ODF) and Ensemble Average Propagator (EAP) are two important Probability Density Functions (PDFs) which reflect the water diffusion and fiber orientations. Spherical Polar Fourier Imaging (SPFI) is a recent model-free multi-shell HARDI method which estimates both EAP and ODF from the diffusion signals with multiple b values. As physical PDFs, ODFs and EAPs are nonnegative definite respectively in their domains S2 and R3. However, existing ODF/EAP estimation methods like SPFI seldom consider this natural constraint. Although some works considered the nonnegative constraint on the given discrete samples of ODF/EAP, the estimated ODF/EAP is not guaranteed to be nonnegative definite in the whole continuous domain. The Riemannian framework for ODFs and EAPs has been proposed via the square root parameterization based on pre-estimated ODFs and EAPs by other methods like SPFI. However, there is no work on how to estimate the square root of ODF/EAP called as the wavefuntion directly from diffusion signals. In this paper, based on the Riemannian framework for ODFs/EAPs and Spherical Polar Fourier (SPF) basis representation, we propose a unified model-free multi-shell HARDI method, named as Square Root Parameterized Estimation (SRPE), to simultaneously estimate both the wavefunction of EAPs and the nonnegative definite ODFs and EAPs from diffusion signals. The experiments on synthetic data and real data showed SRPE is more robust to noise and has better EAP reconstruction than SPFI, especially for EAP profiles at large radius.

A Matrix Splitting Method for Composite Function Minimization

KAUST Repository

Yuan, Ganzhao

2016-12-07

Composite function minimization captures a wide spectrum of applications in both computer vision and machine learning. It includes bound constrained optimization and cardinality regularized optimization as special cases. This paper proposes and analyzes a new Matrix Splitting Method (MSM) for minimizing composite functions. It can be viewed as a generalization of the classical Gauss-Seidel method and the Successive Over-Relaxation method for solving linear systems in the literature. Incorporating a new Gaussian elimination procedure, the matrix splitting method achieves state-of-the-art performance. For convex problems, we establish the global convergence, convergence rate, and iteration complexity of MSM, while for non-convex problems, we prove its global convergence. Finally, we validate the performance of our matrix splitting method on two particular applications: nonnegative matrix factorization and cardinality regularized sparse coding. Extensive experiments show that our method outperforms existing composite function minimization techniques in term of both efficiency and efficacy.

A Matrix Splitting Method for Composite Function Minimization

KAUST Repository

Yuan, Ganzhao; Zheng, Wei-Shi; Ghanem, Bernard

2016-01-01

Composite function minimization captures a wide spectrum of applications in both computer vision and machine learning. It includes bound constrained optimization and cardinality regularized optimization as special cases. This paper proposes and analyzes a new Matrix Splitting Method (MSM) for minimizing composite functions. It can be viewed as a generalization of the classical Gauss-Seidel method and the Successive Over-Relaxation method for solving linear systems in the literature. Incorporating a new Gaussian elimination procedure, the matrix splitting method achieves state-of-the-art performance. For convex problems, we establish the global convergence, convergence rate, and iteration complexity of MSM, while for non-convex problems, we prove its global convergence. Finally, we validate the performance of our matrix splitting method on two particular applications: nonnegative matrix factorization and cardinality regularized sparse coding. Extensive experiments show that our method outperforms existing composite function minimization techniques in term of both efficiency and efficacy.

A New Matrix Theorem: Interpretation in Terms of Internal Trade Structure and Implications for Dynamic Systems

NARCIS (Netherlands)

Steenge, A.E.; Thissen, M.J.P.M.

2005-01-01

Economic systems often are described in matrix form as x = Mx. We present a new theorem for systems of this type where M is square, nonnegative and indecomposable. The theorem discloses the existence of additional economic relations that have not been discussed in the literature up to now, and gives

Gene Module Identification from Microarray Data Using Nonnegative Independent Component Analysis

Directory of Open Access Journals (Sweden)

Ting Gong

2007-01-01

Full Text Available Genes mostly interact with each other to form transcriptional modules for performing single or multiple functions. It is important to unravel such transcriptional modules and to determine how disturbances in them may lead to disease. Here, we propose a non-negative independent component analysis (nICA approach for transcriptional module discovery. nICA method utilizes the non-negativity constraint to enforce the independence of biological processes within the participated genes. In such, nICA decomposes the observed gene expression into positive independent components, which fi ts better to the reality of corresponding putative biological processes. In conjunction with nICA modeling, visual statistical data analyzer (VISDA is applied to group genes into modules in latent variable space. We demonstrate the usefulness of the approach through the identification of composite modules from yeast data and the discovery of pathway modules in muscle regeneration.

Non-negative Feynman endash Kac kernels in Schroedinger close-quote s interpolation problem

International Nuclear Information System (INIS)

Blanchard, P.; Garbaczewski, P.; Olkiewicz, R.

1997-01-01

The local formulations of the Markovian interpolating dynamics, which is constrained by the prescribed input-output statistics data, usually utilize strictly positive Feynman endash Kac kernels. This implies that the related Markov diffusion processes admit vanishing probability densities only at the boundaries of the spatial volume confining the process. We discuss an extension of the framework to encompass singular potentials and associated non-negative Feynman endash Kac-type kernels. It allows us to deal with a class of continuous interpolations admitted by general non-negative solutions of the Schroedinger boundary data problem. The resulting nonstationary stochastic processes are capable of both developing and destroying nodes (zeros) of probability densities in the course of their evolution, also away from the spatial boundaries. This observation conforms with the general mathematical theory (due to M. Nagasawa and R. Aebi) that is based on the notion of multiplicative functionals, extending in turn the well known Doob close-quote s h-transformation technique. In view of emphasizing the role of the theory of non-negative solutions of parabolic partial differential equations and the link with open-quotes Wiener exclusionclose quotes techniques used to evaluate certain Wiener functionals, we give an alternative insight into the issue, that opens a transparent route towards applications.copyright 1997 American Institute of Physics

Analysis Sparse Representation for Nonnegative Signals Based on Determinant Measure by DC Programming

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Yujie Li

2018-01-01

Full Text Available Analysis sparse representation has recently emerged as an alternative approach to the synthesis sparse model. Most existing algorithms typically employ the l0-norm, which is generally NP-hard. Other existing algorithms employ the l1-norm to relax the l0-norm, which sometimes cannot promote adequate sparsity. Most of these existing algorithms focus on general signals and are not suitable for nonnegative signals. However, many signals are necessarily nonnegative such as spectral data. In this paper, we present a novel and efficient analysis dictionary learning algorithm for nonnegative signals with the determinant-type sparsity measure which is convex and differentiable. The analysis sparse representation can be cast in three subproblems, sparse coding, dictionary update, and signal update, because the determinant-type sparsity measure would result in a complex nonconvex optimization problem, which cannot be easily solved by standard convex optimization methods. Therefore, in the proposed algorithms, we use a difference of convex (DC programming scheme for solving the nonconvex problem. According to our theoretical analysis and simulation study, the main advantage of the proposed algorithm is its greater dictionary learning efficiency, particularly compared with state-of-the-art algorithms. In addition, our proposed algorithm performs well in image denoising.

Rotationally invariant family of Levy-like random matrix ensembles

International Nuclear Information System (INIS)

Choi, Jinmyung; Muttalib, K A

2009-01-01

We introduce a family of rotationally invariant random matrix ensembles characterized by a parameter λ. While λ = 1 corresponds to well-known critical ensembles, we show that λ ≠ 1 describes 'Levy-like' ensembles, characterized by power-law eigenvalue densities. For λ > 1 the density is bounded, as in Gaussian ensembles, but λ < 1 describes ensembles characterized by densities with long tails. In particular, the model allows us to evaluate, in terms of a novel family of orthogonal polynomials, the eigenvalue correlations for Levy-like ensembles. These correlations differ qualitatively from those in either the Gaussian or the critical ensembles. (fast track communication)

Computation of a numerically satisfactory pair of solutions of the differential equation for conical functions of non-negative integer orders

NARCIS (Netherlands)

T.M. Dunster (Mark); A. Gil (Amparo); J. Segura (Javier); N.M. Temme (Nico)

2014-01-01

textabstractWe consider the problem of computing satisfactory pair of solutions of the differential equation for Legendre functions of non-negative integer order $\\mu$ and degree $-\\frac12+i\\tau$, where $\\tau$ is a non-negative real parameter. Solutions of this equation are the conical functions

Link predication based on matrix factorization by fusion of multi class organizations of the network.

Science.gov (United States)

Jiao, Pengfei; Cai, Fei; Feng, Yiding; Wang, Wenjun

2017-08-21

Link predication aims at forecasting the latent or unobserved edges in the complex networks and has a wide range of applications in reality. Almost existing methods and models only take advantage of one class organization of the networks, which always lose important information hidden in other organizations of the network. In this paper, we propose a link predication framework which makes the best of the structure of networks in different level of organizations based on nonnegative matrix factorization, which is called NMF 3 here. We first map the observed network into another space by kernel functions, which could get the different order organizations. Then we combine the adjacency matrix of the network with one of other organizations, which makes us obtain the objective function of our framework for link predication based on the nonnegative matrix factorization. Third, we derive an iterative algorithm to optimize the objective function, which converges to a local optimum, and we propose a fast optimization strategy for large networks. Lastly, we test the proposed framework based on two kernel functions on a series of real world networks under different sizes of training set, and the experimental results show the feasibility, effectiveness, and competitiveness of the proposed framework.

Inferring Aggregated Functional Traits from Metagenomic Data Using Constrained Non-negative Matrix Factorization: Application to Fiber Degradation in the Human Gut Microbiota.

Science.gov (United States)

Raguideau, Sébastien; Plancade, Sandra; Pons, Nicolas; Leclerc, Marion; Laroche, Béatrice

2016-12-01

Whole Genome Shotgun (WGS) metagenomics is increasingly used to study the structure and functions of complex microbial ecosystems, both from the taxonomic and functional point of view. Gene inventories of otherwise uncultured microbial communities make the direct functional profiling of microbial communities possible. The concept of community aggregated trait has been adapted from environmental and plant functional ecology to the framework of microbial ecology. Community aggregated traits are quantified from WGS data by computing the abundance of relevant marker genes. They can be used to study key processes at the ecosystem level and correlate environmental factors and ecosystem functions. In this paper we propose a novel model based approach to infer combinations of aggregated traits characterizing specific ecosystemic metabolic processes. We formulate a model of these Combined Aggregated Functional Traits (CAFTs) accounting for a hierarchical structure of genes, which are associated on microbial genomes, further linked at the ecosystem level by complex co-occurrences or interactions. The model is completed with constraints specifically designed to exploit available genomic information, in order to favor biologically relevant CAFTs. The CAFTs structure, as well as their intensity in the ecosystem, is obtained by solving a constrained Non-negative Matrix Factorization (NMF) problem. We developed a multicriteria selection procedure for the number of CAFTs. We illustrated our method on the modelling of ecosystemic functional traits of fiber degradation by the human gut microbiota. We used 1408 samples of gene abundances from several high-throughput sequencing projects and found that four CAFTs only were needed to represent the fiber degradation potential. This data reduction highlighted biologically consistent functional patterns while providing a high quality preservation of the original data. Our method is generic and can be applied to other metabolic processes in

Inferring Aggregated Functional Traits from Metagenomic Data Using Constrained Non-negative Matrix Factorization: Application to Fiber Degradation in the Human Gut Microbiota.

Directory of Open Access Journals (Sweden)

Sébastien Raguideau

2016-12-01

Full Text Available Whole Genome Shotgun (WGS metagenomics is increasingly used to study the structure and functions of complex microbial ecosystems, both from the taxonomic and functional point of view. Gene inventories of otherwise uncultured microbial communities make the direct functional profiling of microbial communities possible. The concept of community aggregated trait has been adapted from environmental and plant functional ecology to the framework of microbial ecology. Community aggregated traits are quantified from WGS data by computing the abundance of relevant marker genes. They can be used to study key processes at the ecosystem level and correlate environmental factors and ecosystem functions. In this paper we propose a novel model based approach to infer combinations of aggregated traits characterizing specific ecosystemic metabolic processes. We formulate a model of these Combined Aggregated Functional Traits (CAFTs accounting for a hierarchical structure of genes, which are associated on microbial genomes, further linked at the ecosystem level by complex co-occurrences or interactions. The model is completed with constraints specifically designed to exploit available genomic information, in order to favor biologically relevant CAFTs. The CAFTs structure, as well as their intensity in the ecosystem, is obtained by solving a constrained Non-negative Matrix Factorization (NMF problem. We developed a multicriteria selection procedure for the number of CAFTs. We illustrated our method on the modelling of ecosystemic functional traits of fiber degradation by the human gut microbiota. We used 1408 samples of gene abundances from several high-throughput sequencing projects and found that four CAFTs only were needed to represent the fiber degradation potential. This data reduction highlighted biologically consistent functional patterns while providing a high quality preservation of the original data. Our method is generic and can be applied to other

Solution of the Stieltjes truncated matrix moment problem

Directory of Open Access Journals (Sweden)

Vadim M. Adamyan

2005-01-01

Full Text Available The truncated Stieltjes matrix moment problem consisting in the description of all matrix distributions \\(\\boldsymbol{\\sigma}(t\\ on \\([0,\\infty\\ with given first \\(2n+1\\ power moments \\((\\mathbf{C}_j_{n=0}^j\\ is solved using known results on the corresponding Hamburger problem for which \\(\\boldsymbol{\\sigma}(t\\ are defined on \\((-\\infty,\\infty\\. The criterion of solvability of the Stieltjes problem is given and all its solutions in the non-degenerate case are described by selection of the appropriate solutions among those of the Hamburger problem for the same set of moments. The results on extensions of non-negative operators are used and a purely algebraic algorithm for the solution of both Hamburger and Stieltjes problems is proposed.

Decoding the encoding of functional brain networks: An fMRI classification comparison of non-negative matrix factorization (NMF), independent component analysis (ICA), and sparse coding algorithms.

Science.gov (United States)

Xie, Jianwen; Douglas, Pamela K; Wu, Ying Nian; Brody, Arthur L; Anderson, Ariana E

2017-04-15

Brain networks in fMRI are typically identified using spatial independent component analysis (ICA), yet other mathematical constraints provide alternate biologically-plausible frameworks for generating brain networks. Non-negative matrix factorization (NMF) would suppress negative BOLD signal by enforcing positivity. Spatial sparse coding algorithms (L1 Regularized Learning and K-SVD) would impose local specialization and a discouragement of multitasking, where the total observed activity in a single voxel originates from a restricted number of possible brain networks. The assumptions of independence, positivity, and sparsity to encode task-related brain networks are compared; the resulting brain networks within scan for different constraints are used as basis functions to encode observed functional activity. These encodings are then decoded using machine learning, by using the time series weights to predict within scan whether a subject is viewing a video, listening to an audio cue, or at rest, in 304 fMRI scans from 51 subjects. The sparse coding algorithm of L1 Regularized Learning outperformed 4 variations of ICA (pcoding algorithms. Holding constant the effect of the extraction algorithm, encodings using sparser spatial networks (containing more zero-valued voxels) had higher classification accuracy (pcoding algorithms suggests that algorithms which enforce sparsity, discourage multitasking, and promote local specialization may capture better the underlying source processes than those which allow inexhaustible local processes such as ICA. Negative BOLD signal may capture task-related activations. Copyright © 2017 Elsevier B.V. All rights reserved.

An Analysis and Application of Fast Nonnegative Orthogonal Matching Pursuit for Image Categorization in Deep Networks

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Bo Wang

2015-01-01

Full Text Available Nonnegative orthogonal matching pursuit (NOMP has been proven to be a more stable encoder for unsupervised sparse representation learning. However, previous research has shown that NOMP is suboptimal in terms of computational cost, as the coefficients selection and refinement using nonnegative least squares (NNLS have been divided into two separate steps. It is found that this problem severely reduces the efficiency of encoding for large-scale image patches. In this work, we study fast nonnegative OMP (FNOMP as an efficient encoder which can be accelerated by the implementation of QR factorization and iterations of coefficients in deep networks for full-size image categorization task. It is analyzed and demonstrated that using relatively simple gain-shape vector quantization for training dictionary, FNOMP not only performs more efficiently than NOMP for encoding but also significantly improves the classification accuracy compared to OMP based algorithm. In addition, FNOMP based algorithm is superior to other state-of-the-art methods on several publicly available benchmarks, that is, Oxford Flowers, UIUC-Sports, and Caltech101.

Wind Noise Reduction using Non-negative Sparse Coding

DEFF Research Database (Denmark)

Schmidt, Mikkel N.; Larsen, Jan; Hsiao, Fu-Tien

2007-01-01

We introduce a new speaker independent method for reducing wind noise in single-channel recordings of noisy speech. The method is based on non-negative sparse coding and relies on a wind noise dictionary which is estimated from an isolated noise recording. We estimate the parameters of the model ...... and discuss their sensitivity. We then compare the algorithm with the classical spectral subtraction method and the Qualcomm-ICSI-OGI noise reduction method. We optimize the sound quality in terms of signal-to-noise ratio and provide results on a noisy speech recognition task....

Detecting the Community Structure and Activity Patterns of Temporal Networks: A Non-Negative Tensor Factorization Approach

Science.gov (United States)

Gauvin, Laetitia; Panisson, André; Cattuto, Ciro

2014-01-01

The increasing availability of temporal network data is calling for more research on extracting and characterizing mesoscopic structures in temporal networks and on relating such structure to specific functions or properties of the system. An outstanding challenge is the extension of the results achieved for static networks to time-varying networks, where the topological structure of the system and the temporal activity patterns of its components are intertwined. Here we investigate the use of a latent factor decomposition technique, non-negative tensor factorization, to extract the community-activity structure of temporal networks. The method is intrinsically temporal and allows to simultaneously identify communities and to track their activity over time. We represent the time-varying adjacency matrix of a temporal network as a three-way tensor and approximate this tensor as a sum of terms that can be interpreted as communities of nodes with an associated activity time series. We summarize known computational techniques for tensor decomposition and discuss some quality metrics that can be used to tune the complexity of the factorized representation. We subsequently apply tensor factorization to a temporal network for which a ground truth is available for both the community structure and the temporal activity patterns. The data we use describe the social interactions of students in a school, the associations between students and school classes, and the spatio-temporal trajectories of students over time. We show that non-negative tensor factorization is capable of recovering the class structure with high accuracy. In particular, the extracted tensor components can be validated either as known school classes, or in terms of correlated activity patterns, i.e., of spatial and temporal coincidences that are determined by the known school activity schedule. PMID:24497935

Wigner weight functions and Weyl symbols of non-negative definite linear operators

NARCIS (Netherlands)

Janssen, A.J.E.M.

1989-01-01

In this paper we present several necessary and, for radially symmetric functions, necessary and sufficient conditions for a function of two variables to be a Wigner weight function (Weyl symbol of a non-negative definite linear operator of L2(R)). These necessary conditions are in terms of spread

Admissible solutions for a class of nonlinear parabolic problem with non-negative data

Czech Academy of Sciences Publication Activity Database

Feireisl, Eduard; Petzeltová, Hana; Simondon, F.

2001-01-01

Roč. 131, č. 5 (2001), s. 857-883 ISSN 0308-2105 R&D Projects: GA AV ČR IAA1019703 Keywords : admissible solutions%nonlinear parabolic problem * admissible solutions * comparison principle * non-negative data Subject RIV: BA - General Mathematics Impact factor: 0.441, year: 2001

Aspect-Aided Dynamic Non-Negative Sparse Representation-Based Microwave Image Classification

Directory of Open Access Journals (Sweden)

Xinzheng Zhang

2016-09-01

Full Text Available Classification of target microwave images is an important application in much areas such as security, surveillance, etc. With respect to the task of microwave image classification, a recognition algorithm based on aspect-aided dynamic non-negative least square (ADNNLS sparse representation is proposed. Firstly, an aspect sector is determined, the center of which is the estimated aspect angle of the testing sample. The training samples in the aspect sector are divided into active atoms and inactive atoms by smooth self-representative learning. Secondly, for each testing sample, the corresponding active atoms are selected dynamically, thereby establishing dynamic dictionary. Thirdly, the testing sample is represented with ℓ 1 -regularized non-negative sparse representation under the corresponding dynamic dictionary. Finally, the class label of the testing sample is identified by use of the minimum reconstruction error. Verification of the proposed algorithm was conducted using the Moving and Stationary Target Acquisition and Recognition (MSTAR database which was acquired by synthetic aperture radar. Experiment results validated that the proposed approach was able to capture the local aspect characteristics of microwave images effectively, thereby improving the classification performance.

MR-NTD: Manifold Regularization Nonnegative Tucker Decomposition for Tensor Data Dimension Reduction and Representation.

Science.gov (United States)

Li, Xutao; Ng, Michael K; Cong, Gao; Ye, Yunming; Wu, Qingyao

2017-08-01

With the advancement of data acquisition techniques, tensor (multidimensional data) objects are increasingly accumulated and generated, for example, multichannel electroencephalographies, multiview images, and videos. In these applications, the tensor objects are usually nonnegative, since the physical signals are recorded. As the dimensionality of tensor objects is often very high, a dimension reduction technique becomes an important research topic of tensor data. From the perspective of geometry, high-dimensional objects often reside in a low-dimensional submanifold of the ambient space. In this paper, we propose a new approach to perform the dimension reduction for nonnegative tensor objects. Our idea is to use nonnegative Tucker decomposition (NTD) to obtain a set of core tensors of smaller sizes by finding a common set of projection matrices for tensor objects. To preserve geometric information in tensor data, we employ a manifold regularization term for the core tensors constructed in the Tucker decomposition. An algorithm called manifold regularization NTD (MR-NTD) is developed to solve the common projection matrices and core tensors in an alternating least squares manner. The convergence of the proposed algorithm is shown, and the computational complexity of the proposed method scales linearly with respect to the number of tensor objects and the size of the tensor objects, respectively. These theoretical results show that the proposed algorithm can be efficient. Extensive experimental results have been provided to further demonstrate the effectiveness and efficiency of the proposed MR-NTD algorithm.

Unambiguous results from variational matrix Pade approximants

International Nuclear Information System (INIS)

Pindor, Maciej.

1979-10-01

Variational Matrix Pade Approximants are studied as a nonlinear variational problem. It is shown that although a stationary value of the Schwinger functional is a stationary value of VMPA, the latter has also another stationary value. It is therefore proposed that instead of looking for a stationary point of VMPA, one minimizes some non-negative functional and then one calculates VMPA at the point where the former has the absolute minimum. This approach, which we call the Method of the Variational Gradient (MVG) gives unambiguous results and is also shown to minimize a distance between the approximate and the exact stationary values of the Schwinger functional

Discrete conservation of nonnegativity for elliptic problems solved by the hp-FEM

Czech Academy of Sciences Publication Activity Database

Šolín, P.; Vejchodský, Tomáš; Araiza, R.

2007-01-01

Roč. 76, 1-3 (2007), s. 205-210 ISSN 0378-4754 R&D Projects: GA ČR GP201/04/P021 Institutional research plan: CEZ:AV0Z10190503 Keywords : discrete nonnegativity conservation * discrete Green's function * elliptic problems * hp-FEM * higher-order finite element methods * Poisson equation * numerical experimetns Subject RIV: BA - General Mathematics Impact factor: 0.738, year: 2007

Online multi-modal robust non-negative dictionary learning for visual tracking.

Science.gov (United States)

Zhang, Xiang; Guan, Naiyang; Tao, Dacheng; Qiu, Xiaogang; Luo, Zhigang

2015-01-01

Dictionary learning is a method of acquiring a collection of atoms for subsequent signal representation. Due to its excellent representation ability, dictionary learning has been widely applied in multimedia and computer vision. However, conventional dictionary learning algorithms fail to deal with multi-modal datasets. In this paper, we propose an online multi-modal robust non-negative dictionary learning (OMRNDL) algorithm to overcome this deficiency. Notably, OMRNDL casts visual tracking as a dictionary learning problem under the particle filter framework and captures the intrinsic knowledge about the target from multiple visual modalities, e.g., pixel intensity and texture information. To this end, OMRNDL adaptively learns an individual dictionary, i.e., template, for each modality from available frames, and then represents new particles over all the learned dictionaries by minimizing the fitting loss of data based on M-estimation. The resultant representation coefficient can be viewed as the common semantic representation of particles across multiple modalities, and can be utilized to track the target. OMRNDL incrementally learns the dictionary and the coefficient of each particle by using multiplicative update rules to respectively guarantee their non-negativity constraints. Experimental results on a popular challenging video benchmark validate the effectiveness of OMRNDL for visual tracking in both quantity and quality.

Asymptotic theory for the sample covariance matrix of a heavy-tailed multivariate time series

DEFF Research Database (Denmark)

Davis, Richard A.; Mikosch, Thomas Valentin; Pfaffel, Olivier

2016-01-01

In this paper we give an asymptotic theory for the eigenvalues of the sample covariance matrix of a multivariate time series. The time series constitutes a linear process across time and between components. The input noise of the linear process has regularly varying tails with index α∈(0,4) in...... particular, the time series has infinite fourth moment. We derive the limiting behavior for the largest eigenvalues of the sample covariance matrix and show point process convergence of the normalized eigenvalues. The limiting process has an explicit form involving points of a Poisson process and eigenvalues...... of a non-negative definite matrix. Based on this convergence we derive limit theory for a host of other continuous functionals of the eigenvalues, including the joint convergence of the largest eigenvalues, the joint convergence of the largest eigenvalue and the trace of the sample covariance matrix...

Link predication based on matrix factorization by fusion of multi class organizations of the network

OpenAIRE

Jiao, Pengfei; Cai, Fei; Feng, Yiding; Wang, Wenjun

2017-01-01

Link predication aims at forecasting the latent or unobserved edges in the complex networks and has a wide range of applications in reality. Almost existing methods and models only take advantage of one class organization of the networks, which always lose important information hidden in other organizations of the network. In this paper, we propose a link predication framework which makes the best of the structure of networks in different level of organizations based on nonnegative matrix fac...

BJUT at TREC 2015 Microblog Track: Real-Time Filtering Using Non-negative Matrix Factorization

Science.gov (United States)

2015-11-20

query accurate ambiguity intergration Tweets Vector Preprocessing W-d matrix Feature vector Similarity ranking Recommended twittres Get...recommendation tech- nique based on product category attributes[J]. Expert Systems with Applications, 2009, 36(9): 11480-11488. [5] Sobecki J, Babiak E,Sanina M

Nonnegative least-squares image deblurring: improved gradient projection approaches

Science.gov (United States)

Benvenuto, F.; Zanella, R.; Zanni, L.; Bertero, M.

2010-02-01

The least-squares approach to image deblurring leads to an ill-posed problem. The addition of the nonnegativity constraint, when appropriate, does not provide regularization, even if, as far as we know, a thorough investigation of the ill-posedness of the resulting constrained least-squares problem has still to be done. Iterative methods, converging to nonnegative least-squares solutions, have been proposed. Some of them have the 'semi-convergence' property, i.e. early stopping of the iteration provides 'regularized' solutions. In this paper we consider two of these methods: the projected Landweber (PL) method and the iterative image space reconstruction algorithm (ISRA). Even if they work well in many instances, they are not frequently used in practice because, in general, they require a large number of iterations before providing a sensible solution. Therefore, the main purpose of this paper is to refresh these methods by increasing their efficiency. Starting from the remark that PL and ISRA require only the computation of the gradient of the functional, we propose the application to these algorithms of special acceleration techniques that have been recently developed in the area of the gradient methods. In particular, we propose the application of efficient step-length selection rules and line-search strategies. Moreover, remarking that ISRA is a scaled gradient algorithm, we evaluate its behaviour in comparison with a recent scaled gradient projection (SGP) method for image deblurring. Numerical experiments demonstrate that the accelerated methods still exhibit the semi-convergence property, with a considerable gain both in the number of iterations and in the computational time; in particular, SGP appears definitely the most efficient one.

Single-Trial Decoding of Bistable Perception Based on Sparse Nonnegative Tensor Decomposition

Science.gov (United States)

Wang, Zhisong; Maier, Alexander; Logothetis, Nikos K.; Liang, Hualou

2008-01-01

The study of the neuronal correlates of the spontaneous alternation in perception elicited by bistable visual stimuli is promising for understanding the mechanism of neural information processing and the neural basis of visual perception and perceptual decision-making. In this paper, we develop a sparse nonnegative tensor factorization-(NTF)-based method to extract features from the local field potential (LFP), collected from the middle temporal (MT) visual cortex in a macaque monkey, for decoding its bistable structure-from-motion (SFM) perception. We apply the feature extraction approach to the multichannel time-frequency representation of the intracortical LFP data. The advantages of the sparse NTF-based feature extraction approach lies in its capability to yield components common across the space, time, and frequency domains yet discriminative across different conditions without prior knowledge of the discriminating frequency bands and temporal windows for a specific subject. We employ the support vector machines (SVMs) classifier based on the features of the NTF components for single-trial decoding the reported perception. Our results suggest that although other bands also have certain discriminability, the gamma band feature carries the most discriminative information for bistable perception, and that imposing the sparseness constraints on the nonnegative tensor factorization improves extraction of this feature. PMID:18528515

Enterasys Networks delivers 10-Gigabit ethernet for the enterprise with new matrix E1 switching family

CERN Multimedia

2001-01-01

Enterasys Networks Inc., today announced its new Matrix E1 family of 10-Gigabit and Gigabit Ethernet switches. The Matrix E1 Optical Access Switch (OAS) enables organizations to deliver applications at 10-Gb speeds across a single fibre optic pair. Jacques Altaber, deputy leader of IT at CERN said "High-bandwith solutions are essential to leveraging more computing power, so 10-Gb Ethernet is the next logical step for us...The Matrix E1 allows us to provide the networking support that our scientists need and gives us a certain future for bandwidth and computing expansion".

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

Directory of Open Access Journals (Sweden)

Patrycja Boguta

2016-10-01

Full Text Available 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.

KPII: Cauchy-Jost function, Darboux transformations and totally nonnegative matrices

Science.gov (United States)

Boiti, M.; Pempinelli, F.; Pogrebkov, A. K.

2017-07-01

Direct definition of the Cauchy-Jost (known also as Cauchy-Baker-Akhiezer) function is given in the case of a pure solitonic solution. Properties of this function are discussed in detail using the Kadomtsev-Petviashvili II equation as an example. This enables formulation of the Darboux transformations in terms of the Cauchy-Jost function and classification of these transformations. Action of Darboux transformations on Grassmanians—i.e. on the space of soliton parameters—is derived and the relation of the Darboux transformations with the property of total nonnegativity of elements of corresponding Grassmanians is discussed. To the memory of our friend and colleague Peter P Kulish

A locally conservative non-negative finite element formulation for anisotropic advective-diffusive-reactive systems

Science.gov (United States)

Mudunuru, M. K.; Shabouei, M.; Nakshatrala, K.

2015-12-01

Advection-diffusion-reaction (ADR) equations appear in various areas of life sciences, hydrogeological systems, and contaminant transport. Obtaining stable and accurate numerical solutions can be challenging as the underlying equations are coupled, nonlinear, and non-self-adjoint. Currently, there is neither a robust computational framework available nor a reliable commercial package known that can handle various complex situations. Herein, the objective of this poster presentation is to present a novel locally conservative non-negative finite element formulation that preserves the underlying physical and mathematical properties of a general linear transient anisotropic ADR equation. In continuous setting, governing equations for ADR systems possess various important properties. In general, all these properties are not inherited during finite difference, finite volume, and finite element discretizations. The objective of this poster presentation is two fold: First, we analyze whether the existing numerical formulations (such as SUPG and GLS) and commercial packages provide physically meaningful values for the concentration of the chemical species for various realistic benchmark problems. Furthermore, we also quantify the errors incurred in satisfying the local and global species balance for two popular chemical kinetics schemes: CDIMA (chlorine dioxide-iodine-malonic acid) and BZ (Belousov--Zhabotinsky). Based on these numerical simulations, we show that SUPG and GLS produce unphysical values for concentration of chemical species due to the violation of the non-negative constraint, contain spurious node-to-node oscillations, and have large errors in local and global species balance. Second, we proposed a novel finite element formulation to overcome the above difficulties. The proposed locally conservative non-negative computational framework based on low-order least-squares finite elements is able to preserve these underlying physical and mathematical properties

A PET reconstruction formulation that enforces non-negativity in projection space for bias reduction in Y-90 imaging

Science.gov (United States)

Lim, Hongki; Dewaraja, Yuni K.; Fessler, Jeffrey A.

2018-02-01

Most existing PET image reconstruction methods impose a nonnegativity constraint in the image domain that is natural physically, but can lead to biased reconstructions. This bias is particularly problematic for Y-90 PET because of the low probability positron production and high random coincidence fraction. This paper investigates a new PET reconstruction formulation that enforces nonnegativity of the projections instead of the voxel values. This formulation allows some negative voxel values, thereby potentially reducing bias. Unlike the previously reported NEG-ML approach that modifies the Poisson log-likelihood to allow negative values, the new formulation retains the classical Poisson statistical model. To relax the non-negativity constraint embedded in the standard methods for PET reconstruction, we used an alternating direction method of multipliers (ADMM). Because choice of ADMM parameters can greatly influence convergence rate, we applied an automatic parameter selection method to improve the convergence speed. We investigated the methods using lung to liver slices of XCAT phantom. We simulated low true coincidence count-rates with high random fractions corresponding to the typical values from patient imaging in Y-90 microsphere radioembolization. We compared our new methods with standard reconstruction algorithms and NEG-ML and a regularized version thereof. Both our new method and NEG-ML allow more accurate quantification in all volumes of interest while yielding lower noise than the standard method. The performance of NEG-ML can degrade when its user-defined parameter is tuned poorly, while the proposed algorithm is robust to any count level without requiring parameter tuning.

Non-negative Tensor Factorization with missing data for the modeling of gene expressions in the Human Brain

DEFF Research Database (Denmark)

Nielsen, Søren Føns Vind; Mørup, Morten

2014-01-01

Non-negative Tensor Factorization (NTF) has become a prominent tool for analyzing high dimensional multi-way structured data. In this paper we set out to analyze gene expression across brain regions in multiple subjects based on data from the Allen Human Brain Atlas [1] with more than 40 % data m...

Spectral multipliers on spaces of distributions associated with non-negative self-adjoint operators

DEFF Research Database (Denmark)

Georgiadis, Athanasios; Nielsen, Morten

2018-01-01

and Triebel–Lizorkin spaces with full range of indices is established too. As an application, we obtain equivalent norm characterizations for the spaces mentioned above. Non-classical spaces as well as Lebesgue, Hardy, (generalized) Sobolev and Lipschitz spaces are also covered by our approach.......We consider spaces of homogeneous type associated with a non-negative self-adjoint operator whose heat kernel satisfies certain upper Gaussian bounds. Spectral multipliers are introduced and studied on distributions associated with this operator. The boundedness of spectral multipliers on Besov...

Reduction of Non-stationary Noise using a Non-negative Latent Variable Decomposition

DEFF Research Database (Denmark)

Schmidt, Mikkel Nørgaard; Larsen, Jan

2008-01-01

We present a method for suppression of non-stationary noise in single channel recordings of speech. The method is based on a non-negative latent variable decomposition model for the speech and noise signals, learned directly from a noisy mixture. In non-speech regions an over complete basis...... is learned for the noise that is then used to jointly estimate the speech and the noise from the mixture. We compare the method to the classical spectral subtraction approach, where the noise spectrum is estimated as the average over non-speech frames. The proposed method significantly outperforms...

Asymptotic behaviour of a non-commutative rational series with a nonnegative linear representation

Directory of Open Access Journals (Sweden)

Philippe Dumas

2007-01-01

Full Text Available We analyse the asymptotic behaviour in the mean of a non-commutative rational series, which originates from differential cryptanalysis, using tools from probability theory, and from analytic number theory. We derive a Fourier representation of a first-order summation function obtained by interpreting this rational series as a non-classical rational sequence via the octal numeration system. The method is applicable to a wide class of sequences rational with respect to a numeration system essentially under the condition that they admit a linear representation with nonnegative coefficients.

Multiple graph regularized nonnegative matrix factorization

KAUST Repository

Wang, Jim Jing-Yan; Bensmail, Halima; Gao, Xin

2013-01-01

algorithm, thus resulting in a novel data representation algorithm. Extensive experiments on a protein subcellular localization task and an Alzheimer's disease diagnosis task demonstrate the effectiveness of the proposed algorithm. © 2013 Elsevier Ltd. All

Facial Expression Recognition via Non-Negative Least-Squares Sparse Coding

Directory of Open Access Journals (Sweden)

Ying Chen

2014-05-01

Full Text Available Sparse coding is an active research subject in signal processing, computer vision, and pattern recognition. A novel method of facial expression recognition via non-negative least squares (NNLS sparse coding is presented in this paper. The NNLS sparse coding is used to form a facial expression classifier. To testify the performance of the presented method, local binary patterns (LBP and the raw pixels are extracted for facial feature representation. Facial expression recognition experiments are conducted on the Japanese Female Facial Expression (JAFFE database. Compared with other widely used methods such as linear support vector machines (SVM, sparse representation-based classifier (SRC, nearest subspace classifier (NSC, K-nearest neighbor (KNN and radial basis function neural networks (RBFNN, the experiment results indicate that the presented NNLS method performs better than other used methods on facial expression recognition tasks.

Extended biorthogonal matrix polynomials

Directory of Open Access Journals (Sweden)

Ayman Shehata

2017-01-01

Full Text Available The pair of biorthogonal matrix polynomials for commutative matrices were first introduced by Varma and Tasdelen in [22]. The main aim of this paper is to extend the properties of the pair of biorthogonal matrix polynomials of Varma and Tasdelen and certain generating matrix functions, finite series, some matrix recurrence relations, several important properties of matrix differential recurrence relations, biorthogonality relations and matrix differential equation for the pair of biorthogonal matrix polynomials J(A,B n (x, k and K(A,B n (x, k are discussed. For the matrix polynomials J(A,B n (x, k, various families of bilinear and bilateral generating matrix functions are constructed in the sequel.

Blind separation of positive sources by globally convergent gradient search.

Science.gov (United States)

Oja, Erkki; Plumbley, Mark

2004-09-01

The instantaneous noise-free linear mixing model in independent component analysis is largely a solved problem under the usual assumption of independent nongaussian sources and full column rank mixing matrix. However, with some prior information on the sources, like positivity, new analysis and perhaps simplified solution methods may yet become possible. In this letter, we consider the task of independent component analysis when the independent sources are known to be nonnegative and well grounded, which means that they have a nonzero pdf in the region of zero. It can be shown that in this case, the solution method is basically very simple: an orthogonal rotation of the whitened observation vector into nonnegative outputs will give a positive permutation of the original sources. We propose a cost function whose minimum coincides with nonnegativity and derive the gradient algorithm under the whitening constraint, under which the separating matrix is orthogonal. We further prove that in the Stiefel manifold of orthogonal matrices, the cost function is a Lyapunov function for the matrix gradient flow, implying global convergence. Thus, this algorithm is guaranteed to find the nonnegative well-grounded independent sources. The analysis is complemented by a numerical simulation, which illustrates the algorithm.

Application of Nonnegative Tensor Factorization for neutron-gamma discrimination of Monte Carlo simulated fission chamber’s output signals

Directory of Open Access Journals (Sweden)

Mounia Laassiri

Full Text Available For efficient exploitation of research reactors, it is important to discern neutron flux distribution inside the reactor with the best possible precision. For this reason, fission and ionization chambers are used to measure the neutron field. In these arrays, the sequences of the neutron interaction points in the fission chamber can correctly be identified in order to obtain true neutron energies emitted by nuclei of interest. However, together with the neutrons, gamma-rays are also emitted from nuclei and thereby affect neutron spectra. The originality of this study consists in the application of tensor based blind source separation methods to extract independent components from signals recorded at the fission chamber preamplifier’s output. The objective is to achieve software neutron-gamma discrimination using Nonnegative Tensor Factorization tools. For reasons of nuclear safety, we first simulate the neutron flux inside the TRIGA Mark II Reactor using Monte Carlo methods under Geant4 platform linked to Garfield++. Geant4 simulations allow the fission chamber construction whereas linking the model to Garfield++ permits to simulate drift parameters from the ionization of the filling gas, which is not possible otherwise. Keywords: Fission chamber (FC, Geant4, Garfield++, Neutron-gamma discrimination, Nonnegative Tensor Factorization (NTF

Usefulness of FC-TRIPLEX Chagas/Leish IgG1 as confirmatory assay for non-negative results in blood bank screening of Chagas disease.

Science.gov (United States)

Campos, Fernanda Magalhães Freire; Repoles, Laura Cotta; de Araújo, Fernanda Fortes; Peruhype-Magalhães, Vanessa; Xavier, Marcelo Antônio Pascoal; Sabino, Ester Cerdeira; de Freitas Carneiro Proietti, Anna Bárbara; Andrade, Mariléia Chaves; Teixeira-Carvalho, Andréa; Martins-Filho, Olindo Assis; Gontijo, Célia Maria Ferreira

2018-04-01

A relevant issue in Chagas disease serological diagnosis regards the requirement of using several confirmatory methods to elucidate the status of non-negative results from blood bank screening. The development of a single reliable method may potentially contribute to distinguish true and false positive results. Our aim was to evaluate the performance of the multiplexed flow-cytometry anti-T. cruzi/Leishmania IgG1 serology/(FC-TRIPLEX Chagas/Leish IgG1) with three conventional confirmatory criteria (ELISA-EIA, Immunofluorescence assay-IIF and EIA/IIF consensus criterion) to define the final status of samples with actual/previous non-negative results during anti-T. cruzi ELISA-screening in blood banks. Apart from inconclusive results, the FC-TRIPLEX presented a weak agreement index with EIA, while a strong agreement was observed when either IIF or EIA/IIF consensus criteria were applied. Discriminant analysis and Spearman's correlation further corroborates the agreement scores. ROC curve analysis showed that FC-TRIPLEX performance indexes were higher when IIF and EIA/IIF consensus were used as a confirmatory criterion. Logistic regression analysis further demonstrated that the probability of FC-TRIPLEX to yield positive results was higher for inconclusive results from IIF and EIA/IIF consensus. Machine learning tools illustrated the high level of categorical agreement between FC-TRIPLEX versus IIF or EIA/IIF consensus. Together, these findings demonstrated the usefulness of FC-TRIPLEX as a tool to elucidate the status of non-negative results in blood bank screening of Chagas disease. Copyright © 2018. Published by Elsevier B.V.

A Perron–Frobenius theory for block matrices associated to a multiplex network

International Nuclear Information System (INIS)

Romance, Miguel; Solá, Luis; Flores, Julio; García, Esther; García del Amo, Alejandro; Criado, Regino

2015-01-01

The uniqueness of the Perron vector of a nonnegative block matrix associated to a multiplex network is discussed. The conclusions come from the relationships between the irreducibility of some nonnegative block matrix associated to a multiplex network and the irreducibility of the corresponding matrices to each layer as well as the irreducibility of the adjacency matrix of the projection network. In addition the computation of that Perron vector in terms of the Perron vectors of the blocks is also addressed. Finally we present the precise relations that allow to express the Perron eigenvector of the multiplex network in terms of the Perron eigenvectors of its layers

A Perron-Frobenius theory for block matrices associated to a multiplex network

Science.gov (United States)

Romance, Miguel; Solá, Luis; Flores, Julio; García, Esther; García del Amo, Alejandro; Criado, Regino

2015-03-01

The uniqueness of the Perron vector of a nonnegative block matrix associated to a multiplex network is discussed. The conclusions come from the relationships between the irreducibility of some nonnegative block matrix associated to a multiplex network and the irreducibility of the corresponding matrices to each layer as well as the irreducibility of the adjacency matrix of the projection network. In addition the computation of that Perron vector in terms of the Perron vectors of the blocks is also addressed. Finally we present the precise relations that allow to express the Perron eigenvector of the multiplex network in terms of the Perron eigenvectors of its layers.

Some Inheritance Properties for Complementary Basic Matrices

Czech Academy of Sciences Publication Activity Database

Fiedler, Miroslav; Hall, F.J.

2010-01-01

Roč. 433, 11-12 (2010), s. 2060-2069 ISSN 0024-3795 Institutional research plan: CEZ:AV0Z10300504 Keywords : subdiagonal rank * zig-zag shape * factorization * CB-matrix * sign pattern matrix * sign nonsingular matrix * companion matrix * P-matrix * totally nonnegative matrix * oscillatory matrix Subject RIV: BA - General Mathematics Impact factor: 1.005, year: 2010

Learning a Nonnegative Sparse Graph for Linear Regression.

Science.gov (United States)

Fang, Xiaozhao; Xu, Yong; Li, Xuelong; Lai, Zhihui; Wong, Wai Keung

2015-09-01

Previous graph-based semisupervised learning (G-SSL) methods have the following drawbacks: 1) they usually predefine the graph structure and then use it to perform label prediction, which cannot guarantee an overall optimum and 2) they only focus on the label prediction or the graph structure construction but are not competent in handling new samples. To this end, a novel nonnegative sparse graph (NNSG) learning method was first proposed. Then, both the label prediction and projection learning were integrated into linear regression. Finally, the linear regression and graph structure learning were unified within the same framework to overcome these two drawbacks. Therefore, a novel method, named learning a NNSG for linear regression was presented, in which the linear regression and graph learning were simultaneously performed to guarantee an overall optimum. In the learning process, the label information can be accurately propagated via the graph structure so that the linear regression can learn a discriminative projection to better fit sample labels and accurately classify new samples. An effective algorithm was designed to solve the corresponding optimization problem with fast convergence. Furthermore, NNSG provides a unified perceptiveness for a number of graph-based learning methods and linear regression methods. The experimental results showed that NNSG can obtain very high classification accuracy and greatly outperforms conventional G-SSL methods, especially some conventional graph construction methods.

q-Virasoro constraints in matrix models

Energy Technology Data Exchange (ETDEWEB)

Nedelin, Anton [Dipartimento di Fisica, Università di Milano-Bicocca and INFN, sezione di Milano-Bicocca, Piazza della Scienza 3, I-20126 Milano (Italy); Department of Physics and Astronomy, Uppsala university,Box 516, SE-75120 Uppsala (Sweden); Zabzine, Maxim [Department of Physics and Astronomy, Uppsala university,Box 516, SE-75120 Uppsala (Sweden)

2017-03-20

The Virasoro constraints play the important role in the study of matrix models and in understanding of the relation between matrix models and CFTs. Recently the localization calculations in supersymmetric gauge theories produced new families of matrix models and we have very limited knowledge about these matrix models. We concentrate on elliptic generalization of hermitian matrix model which corresponds to calculation of partition function on S{sup 3}×S{sup 1} for vector multiplet. We derive the q-Virasoro constraints for this matrix model. We also observe some interesting algebraic properties of the q-Virasoro algebra.

Trends in global warming and evolution of matrix protein 2 family from influenza A virus.

Science.gov (United States)

Yan, Shao-Min; Wu, Guang

2009-12-01

The global warming is an important factor affecting the biological evolution, and the influenza is an important disease that threatens humans with possible epidemics or pandemics. In this study, we attempted to analyze the trends in global warming and evolution of matrix protein 2 family from influenza A virus, because this protein is a target of anti-flu drug, and its mutation would have significant effect on the resistance to anti-flu drugs. The evolution of matrix protein 2 of influenza A virus from 1959 to 2008 was defined using the unpredictable portion of amino-acid pair predictability. Then the trend in this evolution was compared with the trend in the global temperature, the temperature in north and south hemispheres, and the temperature in influenza A virus sampling site, and species carrying influenza A virus. The results showed the similar trends in global warming and in evolution of M2 proteins although we could not correlate them at this stage of study. The study suggested the potential impact of global warming on the evolution of proteins from influenza A virus.

Redesigning Triangular Dense Matrix Computations on GPUs

KAUST Repository

Charara, Ali; Ltaief, Hatem; Keyes, David E.

2016-01-01

A new implementation of the triangular matrix-matrix multiplication (TRMM) and the triangular solve (TRSM) kernels are described on GPU hardware accelerators. Although part of the Level 3 BLAS family, these highly computationally intensive kernels

INDEFINITE COPOSITIVE MATRICES WITH EXACTLY ONE POSITIVE EIGENVALUE OR EXACTLY ONE NEGATIVE EIGENVALUE

NARCIS (Netherlands)

Jargalsaikhan, Bolor

Checking copositivity of a matrix is a co-NP-complete problem. This paper studies copositive matrices with certain spectral properties. It shows that an indefinite matrix with exactly one positive eigenvalue is copositive if and only if the matrix is nonnegative. Moreover, it shows that finding out

Detecting overlapping community structure of networks based on vertex–vertex correlations

International Nuclear Information System (INIS)

Zarei, Mina; Izadi, Dena; Samani, Keivan Aghababaei

2009-01-01

Using the NMF (non-negative matrix factorization) method, the structure of overlapping communities in complex networks is investigated. For the feature matrix of the NMF method we introduce a vertex–vertex correlation matrix. The method is applied to some computer-generated and real-world networks. Simulations show that this feature matrix gives more reasonable results

Hierarchical subtask discovery with non-negative matrix factorization

CSIR Research Space (South Africa)

Earle, AC

2018-04-01

Full Text Available Hierarchical reinforcement learning methods offer a powerful means of planning flexible behavior in complicated domains. However, learning an appropriate hierarchical decomposition of a domain into subtasks remains a substantial challenge. We...

Performance analysis of alpha divergence in nonnegative matrix ...

African Journals Online (AJOL)

This is achieved by using a suitable cost function to determine the optimal factorization. Most work in this field has focused on the use of Euclidean and Kullback-Liebler (KL) divergence. This study looks into the use of α-divergence based non negative factorization in the context of single channel musical sound separation.

Hierarchical subtask discovery with non-negative matrix factorization

CSIR Research Space (South Africa)

Earle, AC

2017-08-01

Full Text Available Hierarchical reinforcement learning methods offer a powerful means of planning flexible behavior in complicated domains. However, learning an appropriate hierarchical decomposition of a domain into subtasks remains a substantial challenge. We...

Performance analysis of alpha divergence in nonnegative matrix ...

African Journals Online (AJOL)

user

The paper also looks into the performance of the algorithm as important ... a larger framework of the class of unsupervised learning algorithms used in estimation of ...... His major research interests are Signal Processing, Machine Learning and.

Expression of most matrix metalloproteinase family members in breast cancer represents a tumor-induced host response.

Science.gov (United States)

Heppner, K. J.; Matrisian, L. M.; Jensen, R. A.; Rodgers, W. H.

1996-01-01

Matrix metalloproteinase (MMP) family members have been associated with advanced-stage cancer and contribute to tumor progression, invasion, and metastasis as determined by inhibitor studies. In situ hybridization was performed to analyze the expression and localization of all known MMPs in a series of human breast cancer biopsy specimens. Most MMPs were localized to tumor stroma, and all MMPs had very distinct expression patterns. Matrilysin was expressed by morphologically normal epithelial ducts within tumors and in tissue from reduction mammoplasties, and by epithelial-derived tumor cells. Many family members, including stromelysin-3, gelatinase A, MT-MMP, interstitial collagenase, and stromelysin-1 were localized to fibroblasts of tumor stroma of invasive cancers but in quite distinct, and generally widespread, patterns. Gelatinase B, collagenase-3, and metalloelastase expression were more focal; gelatinase B was primarily localized to endothelial cells, collagenase-3 to isolated tumor cells, and metalloelastase to cytokeratin-negative, macrophage-like cells. The MMP inhibitor, TIMP-1, was expressed in both stromal and tumor components in most tumors, and neither stromelysin-2 nor neutrophil collagenase were detected in any of the tumors. These results indicate that there is very tight and complex regulation in the expression of MMP family members in breast cancer that generally represents a host response to the tumor and emphasize the need to further evaluate differential functions for MMP family members in breast tumor progression. Images Figure 1 Figure 2 Figure 3 PMID:8686751

Non-Negative Tensor Factorization for Human Behavioral Pattern Mining in Online Games

Directory of Open Access Journals (Sweden)

Anna Sapienza

2018-03-01

Full Text Available Multiplayer online battle arena is a genre of online games that has become extremely popular. Due to their success, these games also drew the attention of our research community, because they provide a wealth of information about human online interactions and behaviors. A crucial problem is the extraction of activity patterns that characterize this type of data, in an interpretable way. Here, we leverage the Non-negative Tensor Factorization to detect hidden correlated behaviors of playing in a well-known game: League of Legends. To this aim, we collect the entire gaming history of a group of about 1000 players, which accounts for roughly 100K matches. By applying our framework we are able to separate players into different groups. We show that each group exhibits similar features and playing strategies, as well as similar temporal trajectories, i.e., behavioral progressions over the course of their gaming history. We surprisingly discover that playing strategies are stable over time and we provide an explanation for this observation.

Multifaceted role of matrix metalloproteinases (MMPs)

OpenAIRE

Singh, Divya; Srivastava, Sanjeev K.; Chaudhuri, Tapas K.; Upadhyay, Ghanshyam

2015-01-01

Matrix metalloproteinases (MMPs), a large family of calcium-dependent zinc-containing endopeptidases, are involved in the tissue remodeling and degradation of the extracellular matrix. MMPs are widely distributed in the brain and regulate various processes including microglial activation, inflammation, dopaminergic apoptosis, blood-brain barrier disruption, and modulation of ?-synuclein pathology. High expression of MMPs is well documented in various neurological disorders including Parkinson...

Weighted nonnegative tensor factorization for atmospheric tomography reconstruction

Science.gov (United States)

Carmona-Ballester, David; Trujillo-Sevilla, Juan M.; Bonaque-González, Sergio; Gómez-Cárdenes, Óscar; Rodríguez-Ramos, José M.

2018-06-01

Context. Increasing the area on the sky over which atmospheric turbulences can be corrected is a matter of wide interest in astrophysics, especially when a new generation of extremely large telescopes (ELT) is to come in the near future. Aims: In this study we tested if a method for visual representation in three-dimensional displays, the weighted nonnegative tensor factorization (WNTF), is able to improve the quality of the atmospheric tomography (AT) reconstruction as compared to a more standardized method like a randomized Kaczmarz algorithm. Methods: A total of 1000 different atmospheres were simulated and recovered by both methods. Recovering was computed for two and three layers and for four different constellations of laser guiding stars (LGS). The goodness of both methods was tested by means of the radial average of the Strehl ratio across the field of view of a telescope of 8m diameter with a sky coverage of 97.8 arcsec. Results: The proposed method significantly outperformed the Kaczmarz in all tested cases (p ≤ 0.05). In WNTF, three-layers configuration provided better outcomes, but there was no clear relation between different LGS constellations and the quality of Strehl ratio maps. Conclusions: The WNTF method is a novel technique in astronomy and its use to recover atmospheric turbulence profiles was proposed and tested. It showed better quality of reconstruction than a conventional Kaczmarz algorithm independently of the number and height of recovered atmospheric layers and of the constellation of laser guide star used. The WNTF method was shown to be a useful tool in highly ill-posed AT problems, where the difficulty of classical algorithms produce high Strehl value maps.

Exploring manifold structure of face images via multiple graphs

KAUST Repository

Alghamdi, Masheal

2013-01-01

Geometric structure in the data provides important information for face image recognition and classification tasks. Graph regularized non-negative matrix factorization (GrNMF) performs well in this task. However, it is sensitive to the parameters selection. Wang et al. proposed multiple graph regularized non-negative matrix factorization (MultiGrNMF) to solve the parameter selection problem by testing it on medical images. In this paper, we introduce the MultiGrNMF algorithm in the context of still face Image classification, and conduct a comparative study of NMF, GrNMF, and MultiGrNMF using two well-known face databases. Experimental results show that MultiGrNMF outperforms NMF and GrNMF for most cases.

Exploring manifold structure of face images via multiple graphs

KAUST Repository

Alghamdi, Masheal

2013-12-24

Geometric structure in the data provides important information for face image recognition and classification tasks. Graph regularized non-negative matrix factorization (GrNMF) performs well in this task. However, it is sensitive to the parameters selection. Wang et al. proposed multiple graph regularized non-negative matrix factorization (MultiGrNMF) to solve the parameter selection problem by testing it on medical images. In this paper, we introduce the MultiGrNMF algorithm in the context of still face Image classification, and conduct a comparative study of NMF, GrNMF, and MultiGrNMF using two well-known face databases. Experimental results show that MultiGrNMF outperforms NMF and GrNMF for most cases.

Extracellular matrix structure.

Science.gov (United States)

Theocharis, Achilleas D; Skandalis, Spyros S; Gialeli, Chrysostomi; Karamanos, Nikos K

2016-02-01

Extracellular matrix (ECM) is a non-cellular three-dimensional macromolecular network composed of collagens, proteoglycans/glycosaminoglycans, elastin, fibronectin, laminins, and several other glycoproteins. Matrix components bind each other as well as cell adhesion receptors forming a complex network into which cells reside in all tissues and organs. Cell surface receptors transduce signals into cells from ECM, which regulate diverse cellular functions, such as survival, growth, migration, and differentiation, and are vital for maintaining normal homeostasis. ECM is a highly dynamic structural network that continuously undergoes remodeling mediated by several matrix-degrading enzymes during normal and pathological conditions. Deregulation of ECM composition and structure is associated with the development and progression of several pathologic conditions. This article emphasizes in the complex ECM structure as to provide a better understanding of its dynamic structural and functional multipotency. Where relevant, the implication of the various families of ECM macromolecules in health and disease is also presented. Copyright © 2015 Elsevier B.V. All rights reserved.

Dimensionality Reduction in Big Data with Nonnegative Matrix Factorization

Science.gov (United States)

2017-06-20

Multiplicative Update Rule(MUR), Projected Gradient Meth- ods (PrG), Block Principal Pivoting method(BlP), Fast Active-set-like method(AcS), Fast...16], one of the robust ensemble meth- ods , to classify the testing datasets. The proposed algorithm outperforms the other algorithms and PCA over all

Hierarchy of Poisson brackets for elements of a scattering matrix

International Nuclear Information System (INIS)

Konopelchenko, B.G.; Dubrovsky, V.G.

1984-01-01

The infinite family of Poisson brackets [Ssub(i1k1) (lambda 1 ), Ssub(i2k2) (lambda 2 )]sub(n) (n=0, 1, 2, ...) between the elements of a scattering matrix is calculated for the linear matrix spectral problem. (orig.)

Matrix metalloproteinase 2 and membrane type 1 matrix metalloproteinase co-regulate axonal outgrowth of mouse retinal ganglion cells

DEFF Research Database (Denmark)

Gaublomme, Djoere; Buyens, Tom; De Groef, Lies

2014-01-01

regenerative therapies, an improved understanding of axonal outgrowth and the various molecules influencing it, is highly needed. Matrix metalloproteinases (MMPs) constitute a family of zinc-dependent proteases that were sporadically reported to influence axon outgrowth. Using an ex vivo retinal explant model......, but not MMP-9, are involved in this process. Furthermore, administration of a novel antibody to MT1-MMP that selectively blocks pro-MMP-2 activation revealed a functional co-involvement of these proteinases in determining RGC axon outgrowth. Subsequent immunostainings showed expression of both MMP-2 and MT1...... nervous system is lacking in adult mammals, thereby impeding recovery from injury to the nervous system. Matrix metalloproteinases (MMPs) constitute a family of zinc-dependent proteases that were sporadically reported to influence axon outgrowth. Inhibition of specific MMPs reduced neurite outgrowth from...

Polymorphisms in the estrogen receptor 1 and vitamin C and matrix metalloproteinase gene families are associated with susceptibility to lymphoma.

Directory of Open Access Journals (Sweden)

Christine F Skibola

Full Text Available BACKGROUND: Non-Hodgkin lymphoma (NHL is the fifth most common cancer in the U.S. and few causes have been identified. Genetic association studies may help identify environmental risk factors and enhance our understanding of disease mechanisms. METHODOLOGY/PRINCIPAL FINDINGS: 768 coding and haplotype tagging SNPs in 146 genes were examined using Illumina GoldenGate technology in a large population-based case-control study of NHL in the San Francisco Bay Area (1,292 cases 1,375 controls are included here. Statistical analyses were restricted to HIV- participants of white non-Hispanic origin. Genes involved in steroidogenesis, immune function, cell signaling, sunlight exposure, xenobiotic metabolism/oxidative stress, energy balance, and uptake and metabolism of cholesterol, folate and vitamin C were investigated. Sixteen SNPs in eight pathways and nine haplotypes were associated with NHL after correction for multiple testing at the adjusted q<0.10 level. Eight SNPs were tested in an independent case-control study of lymphoma in Germany (494 NHL cases and 494 matched controls. Novel associations with common variants in estrogen receptor 1 (ESR1 and in the vitamin C receptor and matrix metalloproteinase gene families were observed. Four ESR1 SNPs were associated with follicular lymphoma (FL in the U.S. study, with rs3020314 remaining associated with reduced risk of FL after multiple testing adjustments [odds ratio (OR = 0.42, 95% confidence interval (CI = 0.23-0.77 and replication in the German study (OR = 0.24, 95% CI = 0.06-0.94. Several SNPs and haplotypes in the matrix metalloproteinase-3 (MMP3 and MMP9 genes and in the vitamin C receptor genes, solute carrier family 23 member 1 (SLC23A1 and SLC23A2, showed associations with NHL risk. CONCLUSIONS/SIGNIFICANCE: Our findings suggest a role for estrogen, vitamin C and matrix metalloproteinases in the pathogenesis of NHL that will require further validation.

Computation of ancestry scores with mixed families and unrelated individuals.

Science.gov (United States)

Zhou, Yi-Hui; Marron, James S; Wright, Fred A

2018-03-01

The issue of robustness to family relationships in computing genotype ancestry scores such as eigenvector projections has received increased attention in genetic association, and is particularly challenging when sets of both unrelated individuals and closely related family members are included. The current standard is to compute loadings (left singular vectors) using unrelated individuals and to compute projected scores for remaining family members. However, projected ancestry scores from this approach suffer from shrinkage toward zero. We consider two main novel strategies: (i) matrix substitution based on decomposition of a target family-orthogonalized covariance matrix, and (ii) using family-averaged data to obtain loadings. We illustrate the performance via simulations, including resampling from 1000 Genomes Project data, and analysis of a cystic fibrosis dataset. The matrix substitution approach has similar performance to the current standard, but is simple and uses only a genotype covariance matrix, while the family-average method shows superior performance. Our approaches are accompanied by novel ancillary approaches that provide considerable insight, including individual-specific eigenvalue scree plots. © 2017 The Authors. Biometrics published by Wiley Periodicals, Inc. on behalf of International Biometric Society.

Matrix metalloproteinases in inflammatory bowel disease : expression, regulation and clinical relevance

NARCIS (Netherlands)

Meijer, Martin Jan-Willem

2009-01-01

Crohn’s disease (CD) is characterized by chronic, patchy, transmural inflammation of the entire gastrointestinal tract, while ulcerative colitis (UC) is manifested by chronic, continuous, superficial inflammation of the colon. Matrix metalloproteinases (MMPs) constitute a family of matrix degrading

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

Science.gov (United States)

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.

Fitting a circular distribution based on nonnegative trigonometric sums for wind direction in Malaysia

Science.gov (United States)

Masseran, Nurulkamal; Razali, Ahmad Mahir; Ibrahim, Kamarulzaman; Zaharim, Azami; Sopian, Kamaruzzaman

2015-02-01

Wind direction has a substantial effect on the environment and human lives. As examples, the wind direction influences the dispersion of particulate matter in the air and affects the construction of engineering structures, such as towers, bridges, and tall buildings. Therefore, a statistical analysis of the wind direction provides important information about the wind regime at a particular location. In addition, knowledge of the wind direction and wind speed can be used to derive information about the energy potential. This study investigated the characteristics of the wind regime of Mersing, Malaysia. A circular distribution based on Nonnegative Trigonometric Sums (NNTS) was fitted to a histogram of the average hourly wind direction data. The Newton-like manifold algorithm was used to estimate the parameter of each component of the NNTS model. Next, the suitability of each NNTS model was judged based on a graphical representation and Akaike's Information Criteria. The study found that the NNTS model with six or more components was able to fit the wind directional data for the Mersing station.

Integrins and extracellular matrix in mechanotransduction

Directory of Open Access Journals (Sweden)

Ramage L

2011-12-01

Full Text Available Lindsay RamageQueen’s Medical Research Institute, University of Edinburgh, Edinburgh, UKAbstract: Integrins are a family of cell surface receptors which mediate cell–matrix and cell–cell adhesions. Among other functions they provide an important mechanical link between the cells external and intracellular environments while the adhesions that they form also have critical roles in cellular signal-transduction. Cell–matrix contacts occur at zones in the cell surface where adhesion receptors cluster and when activated the receptors bind to ligands in the extracellular matrix. The extracellular matrix surrounds the cells of tissues and forms the structural support of tissue which is particularly important in connective tissues. Cells attach to the extracellular matrix through specific cell-surface receptors and molecules including integrins and transmembrane proteoglycans. Integrins work alongside other proteins such as cadherins, immunoglobulin superfamily cell adhesion molecules, selectins, and syndecans to mediate cell–cell and cell–matrix interactions and communication. Activation of adhesion receptors triggers the formation of matrix contacts in which bound matrix components, adhesion receptors, and associated intracellular cytoskeletal and signaling molecules form large functional, localized multiprotein complexes. Cell–matrix contacts are important in a variety of different cell and tissue properties including embryonic development, inflammatory responses, wound healing, and adult tissue homeostasis. This review summarizes the roles and functions of integrins and extracellular matrix proteins in mechanotransduction.Keywords: ligand binding, α subunit, ß subunit, focal adhesion, cell differentiation, mechanical loading, cell–matrix interaction

PARTITIONING TUNGSTEN BETWEEN MATRIX PRECURSORS AND CHONDRULE PRECURSORS THROUGH RELATIVE SETTLING

Energy Technology Data Exchange (ETDEWEB)

Hubbard, Alexander, E-mail: ahubbard@amnh.org [American Museum of Natural History, New York, NY (United States)

2016-08-01

Recent studies of chondrites have found a tungsten isotopic anomaly between chondrules and matrix. Given the refractory nature of tungsten, this implies that W was carried into the solar nebula by at least two distinct families of pre-solar grains. The observed chondrule/matrix split requires that the distinct families were kept separate during the dust coagulation process, and that the two families of grain interacted with the chondrule formation mechanism differently. We take the co-existence of different families of solids in the same general orbital region at the chondrule-precursor size as given, and explore the requirements for them to have interacted with the chondrule formation process at significantly different rates. We show that this sorting of families of solids into chondrule- and matrix-destined dust had to have been at least as powerful a sorting mechanism as the relative settling of aerodynamically distinct grains at least two scale heights above the midplane. The requirement that the chondrule formation mechanism was correlated in some fashion with a dust-grain sorting mechanism argues strongly for spatially localized chondrule formation mechanisms such as turbulent dissipation in non-thermally ionized disk surface layers, and argues against volume-filling mechanisms such as planetesimal bow shocks.

PARTITIONING TUNGSTEN BETWEEN MATRIX PRECURSORS AND CHONDRULE PRECURSORS THROUGH RELATIVE SETTLING

International Nuclear Information System (INIS)

Hubbard, Alexander

2016-01-01

Recent studies of chondrites have found a tungsten isotopic anomaly between chondrules and matrix. Given the refractory nature of tungsten, this implies that W was carried into the solar nebula by at least two distinct families of pre-solar grains. The observed chondrule/matrix split requires that the distinct families were kept separate during the dust coagulation process, and that the two families of grain interacted with the chondrule formation mechanism differently. We take the co-existence of different families of solids in the same general orbital region at the chondrule-precursor size as given, and explore the requirements for them to have interacted with the chondrule formation process at significantly different rates. We show that this sorting of families of solids into chondrule- and matrix-destined dust had to have been at least as powerful a sorting mechanism as the relative settling of aerodynamically distinct grains at least two scale heights above the midplane. The requirement that the chondrule formation mechanism was correlated in some fashion with a dust-grain sorting mechanism argues strongly for spatially localized chondrule formation mechanisms such as turbulent dissipation in non-thermally ionized disk surface layers, and argues against volume-filling mechanisms such as planetesimal bow shocks.

Physiology and pathophysiology of matrix metalloproteases

NARCIS (Netherlands)

Klein, T.; Bischoff, R.

Matrix metalloproteases (MMPs) comprise a family of enzymes that cleave protein substrates based on a conserved mechanism involving activation of an active site-bound water molecule by a Zn(2+) ion. Although the catalytic domain of MMPs is structurally highly similar, there are many differences with

Physiology and pathophysiology of matrix metalloproteases

NARCIS (Netherlands)

Klein, T; Bischoff, Rainer

2010-01-01

Matrix metalloproteases (MMPs) comprise a family of enzymes that cleave protein substrates based on a conserved mechanism involving activation of an active site-bound water molecule by a Zn(2+) ion. Although the catalytic domain of MMPs is structurally highly similar, there are many differences with

The DLGAP family

DEFF Research Database (Denmark)

Rasmussen, Andreas H; Rasmussen, Hanne B; Silahtaroglu, Asli

2017-01-01

downstream signalling in the neuron. The postsynaptic density, a highly specialized matrix, which is attached to the postsynaptic membrane, controls this downstream signalling. The postsynaptic density also resets the synapse after each synaptic firing. It is composed of numerous proteins including a family...... in the postsynapse, the DLGAP family seems to play a vital role in synaptic scaling by regulating the turnover of both ionotropic and metabotropic glutamate receptors in response to synaptic activity. DLGAP family has been directly linked to a variety of psychological and neurological disorders. In this review we...... focus on the direct and indirect role of DLGAP family on schizophrenia as well as other brain diseases....

The noncommutative family Atiyah-Patodi-Singer index theorem

Science.gov (United States)

Wang, Yong

2016-12-01

In this paper, we define the eta cochain form and prove its regularity when the kernel of a family of Dirac operators is a vector bundle. We decompose the eta form as a pairing of the eta cochain form with the Chern character of an idempotent matrix and we also decompose the Chern character of the index bundle for a fibration with boundary as a pairing of the family Chern-Connes character for a manifold with boundary with the Chern character of an idempotent matrix. We define the family b-Chern-Connes character and then we prove that it is entire and give its variation formula. By this variation formula, we prove another noncommutative family Atiyah-Patodi-Singer index theorem. Thus, we extend the results of Getzler and Wu to the family case.

Nonnegative Tensor Factorization Approach Applied to Fission Chamber’s Output Signals Blind Source Separation

Science.gov (United States)

Laassiri, M.; Hamzaoui, E.-M.; Cherkaoui El Moursli, R.

2018-02-01

Inside nuclear reactors, gamma-rays emitted from nuclei together with the neutrons introduce unwanted backgrounds in neutron spectra. For this reason, powerful extraction methods are needed to extract useful neutron signal from recorded mixture and thus to obtain clearer neutron flux spectrum. Actually, several techniques have been developed to discriminate between neutrons and gamma-rays in a mixed radiation field. Most of these techniques, tackle using analogue discrimination methods. Others propose to use some organic scintillators to achieve the discrimination task. Recently, systems based on digital signal processors are commercially available to replace the analog systems. As alternative to these systems, we aim in this work to verify the feasibility of using a Nonnegative Tensor Factorization (NTF) to blind extract neutron component from mixture signals recorded at the output of fission chamber (WL-7657). This last have been simulated through the Geant4 linked to Garfield++ using a 252Cf neutron source. To achieve our objective of obtaining the best possible neutron-gamma discrimination, we have applied the two different NTF algorithms, which have been found to be the best methods that allow us to analyse this kind of nuclear data.

Efficient Multiplicative Updates for Support Vector Machines

DEFF Research Database (Denmark)

Potluru, Vamsi K.; Plis, Sergie N; Mørup, Morten

2009-01-01

(NMF) problem. This allows us to derive a novel multiplicative algorithm for solving hard and soft margin SVM. The algorithm follows as a natural extension of the updates for NMF and semi-NMF. No additional parameter setting, such as choosing learning rate, is required. Exploiting the connection......The dual formulation of the support vector machine (SVM) objective function is an instance of a nonnegative quadratic programming problem. We reformulate the SVM objective function as a matrix factorization problem which establishes a connection with the regularized nonnegative matrix factorization...... between SVM and NMF formulation, we show how NMF algorithms can be applied to the SVM problem. Multiplicative updates that we derive for SVM problem also represent novel updates for semi-NMF. Further this unified view yields algorithmic insights in both directions: we demonstrate that the Kernel Adatron...

Discovering perturbation of modular structure in HIV progression by integrating multiple data sources through non-negative matrix factorization.

Science.gov (United States)

Ray, Sumanta; Maulik, Ujjwal

2016-12-20

Detecting perturbation in modular structure during HIV-1 disease progression is an important step to understand stage specific infection pattern of HIV-1 virus in human cell. In this article, we proposed a novel methodology on integration of multiple biological information to identify such disruption in human gene module during different stages of HIV-1 infection. We integrate three different biological information: gene expression information, protein-protein interaction information and gene ontology information in single gene meta-module, through non negative matrix factorization (NMF). As the identified metamodules inherit those information so, detecting perturbation of these, reflects the changes in expression pattern, in PPI structure and in functional similarity of genes during the infection progression. To integrate modules of different data sources into strong meta-modules, NMF based clustering is utilized here. Perturbation in meta-modular structure is identified by investigating the topological and intramodular properties and putting rank to those meta-modules using a rank aggregation algorithm. We have also analyzed the preservation structure of significant GO terms in which the human proteins of the meta-modules participate. Moreover, we have performed an analysis to show the change of coregulation pattern of identified transcription factors (TFs) over the HIV progression stages.

Development of an integrated system for activity-based profiling of matrix metallo-proteases

NARCIS (Netherlands)

Freije, Jan Robert

2006-01-01

Matrix metallo-proteases constitute a family of extracellular zinc-dependent endopeptidases that are involved in degradation of extracellular matrix (ECM) components and other bioactive non-ECM molecules. A plethora of studies have implicated important roles for MMPs in many diseases (including

Non-negative matrix factorization techniques advances in theory and applications

CERN Document Server

2016-01-01

This book collects new results, concepts and further developments of NMF. The open problems discussed include, e.g. in bioinformatics: NMF and its extensions applied to gene expression, sequence analysis, the functional characterization of genes, clustering and text mining etc. The research results previously scattered in different scientific journals and conference proceedings are methodically collected and presented in a unified form. While readers can read the book chapters sequentially, each chapter is also self-contained. This book can be a good reference work for researchers and engineers interested in NMF, and can also be used as a handbook for students and professionals seeking to gain a better understanding of the latest applications of NMF.

Do flavor conservation and spontaneous CP nonconservation lead to a real Kobayashi-Maskawa matrix?

International Nuclear Information System (INIS)

Gronau, M.; Kfir, A.; Ecker, G.; Grimus, W.; Neufeld, H.

1988-01-01

We reexamine the implication of flavor conservation in tree-level neutral-Higgs-boson exchange for multi-Higgs-scalar SU(2) x U(1) models of spontaneous CP nonconservation . Contrary to a previous claim, we show that in such models for an arbitrary number of fermion families the quark mixing matrix does not have to be real. However, the complex structure derived for the Kobayashi-Maskawa matrix in the three-family model is shown to be in conflict with experiment

Matrix metalloproteinases in acute coronary syndromes: current perspectives.

Science.gov (United States)

Kampoli, Anna-Maria; Tousoulis, Dimitris; Papageorgiou, Nikolaos; Antoniades, Charalambos; Androulakis, Emmanuel; Tsiamis, Eleftherios; Latsios, George; Stefanadis, Christodoulos

2012-01-01

Matrix metalloproteinases (MMPs) are a family of zinc metallo-endopeptidases secreted by cells and are responsible for much of the turnover of matrix components. Several studies have shown that MMPs are involved in all stages of the atherosclerotic process, from the initial lesion to plaque rupture. Recent evidence suggests that MMP activity may facilitate atherosclerosis, plaque destabilization, and platelet aggregation. In the heart, matrix metalloproteinases participate in vascular remodeling, plaque instability, and ventricular remodelling after cardiac injury. The aim of the present article is to review the structure, function, regulation of MMPs and to discuss their potential role in the pathogenesis of acute coronary syndromes, as well as their contribution and usefullness in the setting of the disease.

An integrable coupling family of Merola-Ragnisco-Tu lattice systems, its Hamiltonian structure and related nonisospectral integrable lattice family

Energy Technology Data Exchange (ETDEWEB)

Xu Xixiang, E-mail: xu_xixiang@hotmail.co [College of Science, Shandong University of Science and Technology, Qingdao, 266510 (China)

2010-01-04

An integrable coupling family of Merola-Ragnisco-Tu lattice systems is derived from a four-by-four matrix spectral problem. The Hamiltonian structure of the resulting integrable coupling family is established by the discrete variational identity. Each lattice system in the resulting integrable coupling family is proved to be integrable discrete Hamiltonian system in Liouville sense. Ultimately, a nonisospectral integrable lattice family associated with the resulting integrable lattice family is constructed through discrete zero curvature representation.

An integrable coupling family of Merola-Ragnisco-Tu lattice systems, its Hamiltonian structure and related nonisospectral integrable lattice family

International Nuclear Information System (INIS)

Xu Xixiang

2010-01-01

An integrable coupling family of Merola-Ragnisco-Tu lattice systems is derived from a four-by-four matrix spectral problem. The Hamiltonian structure of the resulting integrable coupling family is established by the discrete variational identity. Each lattice system in the resulting integrable coupling family is proved to be integrable discrete Hamiltonian system in Liouville sense. Ultimately, a nonisospectral integrable lattice family associated with the resulting integrable lattice family is constructed through discrete zero curvature representation.

Downregulation of membrane type-matrix metalloproteinases in the inflamed or injured central nervous system

DEFF Research Database (Denmark)

Toft-Hansen, Henrik; Babcock, Alicia A; Millward, Jason M

2007-01-01

BACKGROUND: Matrix metalloproteinases (MMPs) are thought to mediate cellular infiltration in central nervous system (CNS) inflammation by cleaving extracellular matrix proteins associated with the blood-brain barrier. The family of MMPs includes 23 proteinases, including six membrane type-MMPs (M...

Modeling Polio Data Using the First Order Non-Negative Integer-Valued Autoregressive, INAR(1), Model

Science.gov (United States)

Vazifedan, Turaj; Shitan, Mahendran

Time series data may consists of counts, such as the number of road accidents, the number of patients in a certain hospital, the number of customers waiting for service at a certain time and etc. When the value of the observations are large it is usual to use Gaussian Autoregressive Moving Average (ARMA) process to model the time series. However if the observed counts are small, it is not appropriate to use ARMA process to model the observed phenomenon. In such cases we need to model the time series data by using Non-Negative Integer valued Autoregressive (INAR) process. The modeling of counts data is based on the binomial thinning operator. In this paper we illustrate the modeling of counts data using the monthly number of Poliomyelitis data in United States between January 1970 until December 1983. We applied the AR(1), Poisson regression model and INAR(1) model and the suitability of these models were assessed by using the Index of Agreement(I.A.). We found that INAR(1) model is more appropriate in the sense it had a better I.A. and it is natural since the data are counts.

Clustering via Kernel Decomposition

DEFF Research Database (Denmark)

Have, Anna Szynkowiak; Girolami, Mark A.; Larsen, Jan

2006-01-01

Methods for spectral clustering have been proposed recently which rely on the eigenvalue decomposition of an affinity matrix. In this work it is proposed that the affinity matrix is created based on the elements of a non-parametric density estimator. This matrix is then decomposed to obtain...... posterior probabilities of class membership using an appropriate form of nonnegative matrix factorization. The troublesome selection of hyperparameters such as kernel width and number of clusters can be obtained using standard cross-validation methods as is demonstrated on a number of diverse data sets....

On a simplified inelastic analysis of structures

International Nuclear Information System (INIS)

Zarka, J.; Engel, J.J.; Inglebert, G.

1980-01-01

In this paper two main problems are considered: the derivation of cyclic constitutive relations during inelastic regime where hardening, softening and creep can occur, and the development of the eventual periodical state in the structure during cyclic thermodynamical loadings. We give a very simple and practical framework to solve these problems in one unique manner. Its essential feature consits in the introduction of a family of internal parameters which characterize local inelastic mechanisms and the family of transformed internal parameters which are linearly linked to the previous ones through a symmetrical non-negative matrix and are indeed the opposite of the associated residual stresses. Thanks to that, the treatment of the local plastic or viscoplastic yield conditions can be easily made from only the classical simple purely elastic (or viscoelastic) analysis. This property allows important results during cyclic loadings: conditions for elastic shakedown, plastic shakedown, ratcheting and bounds for the limiting state. Several examples are given in the text. (orig.)

Efficiency criterion for teleportation via channel matrix, measurement matrix and collapsed matrix

Directory of Open Access Journals (Sweden)

Xin-Wei Zha

Full Text Available In this paper, three kinds of coefficient matrixes (channel matrix, measurement matrix, collapsed matrix associated with the pure state for teleportation are presented, the general relation among channel matrix, measurement matrix and collapsed matrix is obtained. In addition, a criterion for judging whether a state can be teleported successfully is given, depending on the relation between the number of parameter of an unknown state and the rank of the collapsed matrix. Keywords: Channel matrix, Measurement matrix, Collapsed matrix, Teleportation

Rotation in correspondence analysis

NARCIS (Netherlands)

van de Velden, Michel; Kiers, Henk A.L.

2005-01-01

In correspondence analysis rows and columns of a nonnegative data matrix are depicted as points in a, usually, two-dimensional plot. Although such a two-dimensional plot often provides a reasonable approximation, the situation can occur that an approximation of higher dimensionality is required.

Structure and evolutionary aspects of matrix metalloproteinases: a brief overview.

Science.gov (United States)

Das, Sudip; Mandal, Malay; Chakraborti, Tapati; Mandal, Amritlal; Chakraborti, Sajal

2003-11-01

The matrix metalloproteinases (MMPs) are zinc dependent endopeptidases known for their ability to cleave one or several extracellular matrix (ECM) constituents, as well as non-matrix proteins. They comprise a large family of proteinases that share common structural and functional elements and are products of different genes. All members of this family contain a signal peptide, a propeptide and a catalytic domain. The catalytic domain contains two zinc ions and at least one calcium ion coordinated to various residues. All MMPs, with the exception matrilysin, have a hemopexin/vitronectin-like domain that is connected to the catalytic domain by a hinge or linker region. The hemopexin-like domain influences tissue inhibitor of metalloproteinases (TIMP) binding, the binding of certain substrates, membrane activation, and some proteolytic activities. It has been proposed that the origin of MMPs could be traced to before the emergence of vertebrates from invertebrates. It appears conceivable that the domain assemblies occurred at an early stage of the diversification of different MMPs and that they progressed through the evolutionary process independent of one another, and perhaps parallel to each other.

Targeting functional motifs of a protein family

Science.gov (United States)

Bhadola, Pradeep; Deo, Nivedita

2016-10-01

The structural organization of a protein family is investigated by devising a method based on the random matrix theory (RMT), which uses the physiochemical properties of the amino acid with multiple sequence alignment. A graphical method to represent protein sequences using physiochemical properties is devised that gives a fast, easy, and informative way of comparing the evolutionary distances between protein sequences. A correlation matrix associated with each property is calculated, where the noise reduction and information filtering is done using RMT involving an ensemble of Wishart matrices. The analysis of the eigenvalue statistics of the correlation matrix for the β -lactamase family shows the universal features as observed in the Gaussian orthogonal ensemble (GOE). The property-based approach captures the short- as well as the long-range correlation (approximately following GOE) between the eigenvalues, whereas the previous approach (treating amino acids as characters) gives the usual short-range correlations, while the long-range correlations are the same as that of an uncorrelated series. The distribution of the eigenvector components for the eigenvalues outside the bulk (RMT bound) deviates significantly from RMT observations and contains important information about the system. The information content of each eigenvector of the correlation matrix is quantified by introducing an entropic estimate, which shows that for the β -lactamase family the smallest eigenvectors (low eigenmodes) are highly localized as well as informative. These small eigenvectors when processed gives clusters involving positions that have well-defined biological and structural importance matching with experiments. The approach is crucial for the recognition of structural motifs as shown in β -lactamase (and other families) and selectively identifies the important positions for targets to deactivate (activate) the enzymatic actions.

Relativistic elliptic matrix tops and finite Fourier transformations

Science.gov (United States)

Zotov, A.

2017-10-01

We consider a family of classical elliptic integrable systems including (relativistic) tops and their matrix extensions of different types. These models can be obtained from the “off-shell” Lax pairs, which do not satisfy the Lax equations in general case but become true Lax pairs under various conditions (reductions). At the level of the off-shell Lax matrix, there is a natural symmetry between the spectral parameter z and relativistic parameter η. It is generated by the finite Fourier transformation, which we describe in detail. The symmetry allows one to consider z and η on an equal footing. Depending on the type of integrable reduction, any of the parameters can be chosen to be the spectral one. Then another one is the relativistic deformation parameter. As a by-product, we describe the model of N2 interacting GL(M) matrix tops and/or M2 interacting GL(N) matrix tops depending on a choice of the spectral parameter.

Sparse-matrix factorizations for fast symmetric Fourier transforms

International Nuclear Information System (INIS)

Sequel, J.

1987-01-01

This work proposes new fast algorithms computing the discrete Fourier transform of certain families of symmetric sequences. Sequences commonly found in problems of structure determination by x-ray crystallography and in numerical solutions of boundary-value problems in partial differential equations are dealt with. In the algorithms presented, the redundancies in the input and output data, due to the presence of symmetries in the input data sequence, were eliminated. Using ring-theoretical methods a matrix representation is obtained for the remaining calculations; which factors as the product of a complex block-diagonal matrix times as integral matrix. A basic two-step algorithm scheme arises from this factorization with a first step consisting of pre-additions and a second step containing the calculations involved in computing with the blocks in the block-diagonal factor. These blocks are structured as block-Hankel matrices, and two sparse-matrix factoring formulas are developed in order to diminish their arithmetic complexity

The survey of preconditioners used for accelerating the rate of convergence in the Gauss-Seidel method

Science.gov (United States)

Niki, Hiroshi; Harada, Kyouji; Morimoto, Munenori; Sakakihara, Michio

2004-03-01

Several preconditioned iterative methods reported in the literature have been used for improving the convergence rate of the Gauss-Seidel method. In this article, on the basis of nonnegative matrix, comparisons between some splittings for such preconditioned matrices are derived. Simple numerical examples are also given.

The positronium and the dipositronium in a Hartree-Fock approximation of quantum electrodynamics

DEFF Research Database (Denmark)

Sok, Jérémy Vithya

2016-01-01

The Bogoliubov-Dirac-Fock (BDF) model is a no-photon approximation of quantum electrodynamics. It allows to study relativistic electrons in interaction with the Dirac sea. A state is fully characterized by its one-body density matrix, an infinite rank non-negative projector. We prove the existence...

PaTux

DEFF Research Database (Denmark)

Abou-Zleikha, Mohamed; Shaker, Noor

2014-01-01

We present a demonstration of PaTux, an authoring tool for designing levels in SuperTux game through combining patterns. PaTux allows game designers to specify the design of their levels using patterns extracted from training level samples. The Non-negative Matrix Factorisation (NMF) method...

Testing Constancy of the Error Covariance Matrix in Vector Models against Parametric Alternatives using a Spectral Decomposition

DEFF Research Database (Denmark)

Yang, Yukay

I consider multivariate (vector) time series models in which the error covariance matrix may be time-varying. I derive a test of constancy of the error covariance matrix against the alternative that the covariance matrix changes over time. I design a new family of Lagrange-multiplier tests against...... to consider multivariate volatility modelling....

Clustering of scientific citations in Wikipedia

DEFF Research Database (Denmark)

Nielsen, Finn Årup

The instances of templates in Wikipedia form an interesting data set of structured information. Here I focus on the cite journal template that is primarily used for citation to articles in scientific journals. These citations can be extracted and analyzed: Non-negative matrix factorization...... is performed on a (article x journal) matrix resulting in a soft clustering of Wikipedia articles and scientific journals, each cluster more or less representing a scientific topic....

Lot-Order Assignment Applying Priority Rules for the Single-Machine Total Tardiness Scheduling with Nonnegative Time-Dependent Processing Times

Directory of Open Access Journals (Sweden)

Jae-Gon Kim

2015-01-01

Full Text Available Lot-order assignment is to assign items in lots being processed to orders to fulfill the orders. It is usually performed periodically for meeting the due dates of orders especially in a manufacturing industry with a long production cycle time such as the semiconductor manufacturing industry. In this paper, we consider the lot-order assignment problem (LOAP with the objective of minimizing the total tardiness of the orders with distinct due dates. We show that we can solve the LOAP optimally by finding an optimal sequence for the single-machine total tardiness scheduling problem with nonnegative time-dependent processing times (SMTTSP-NNTDPT. Also, we address how the priority rules for the SMTTSP can be modified to those for the SMTTSP-NNTDPT to solve the LOAP. In computational experiments, we discuss the performances of the suggested priority rules and show the result of the proposed approach outperforms that of the commercial optimization software package.

Strategy BMT Al-Ittihad Using Matrix IE, Matrix SWOT 8K, Matrix SPACE and Matrix TWOS

Directory of Open Access Journals (Sweden)

Nofrizal Nofrizal

2018-03-01

Full Text Available This research aims to formulate and select BMT Al-Ittihad Rumbai strategy to face the changing of business environment both from internal environment such as organization resources, finance, member and external business such as competitor, economy, politics and others. This research method used Analysis of EFAS, IFAS, IE Matrix, SWOT-8K Matrix, SPACE Matrix and TWOS Matrix. our hope from this research it can assist BMT Al-Ittihad in formulating and selecting strategies for the sustainability of BMT Al-Ittihad in the future. The sample in this research is using purposive sampling technique that is the manager and leader of BMT Al-IttihadRumbaiPekanbaru. The result of this research shows that the position of BMT Al-Ittihad using IE Matrix, SWOT-8K Matrix and SPACE Matrix is in growth position, stabilization and aggressive. The choice of strategy after using TWOS Matrix is market penetration, market development, vertical integration, horizontal integration, and stabilization (careful.

Hecke algebraic properties of dynamical R-matrices. Application to related quantum matrix algebras

International Nuclear Information System (INIS)

Khadzhiivanov, L.K.; Todorov, I.T.; Isaev, A.P.; Pyatov, P.N.; Ogievetskij, O.V.

1998-01-01

The quantum dynamical Yang-Baxter (or Gervais-Neveu-Felder) equation defines an R-matrix R cap (p), where p stands for a set of mutually commuting variables. A family of SL (n)-type solutions of this equation provides a new realization of the Hecke algebra. We define quantum antisymmetrizers, introduce the notion of quantum determinant and compute the inverse quantum matrix for matrix algebras of the type R cap (p) a 1 a 2 = a 1 a 2 R cap. It is pointed out that such a quantum matrix algebra arises in the operator realization of the chiral zero modes of the WZNW model

Exploring Mixed Membership Stochastic Block Models via Non-negative Matrix Factorization

KAUST Repository

Peng, Chengbin; Wong, Ka Chun

2014-01-01

in our context. It is usually assumed that each node belongs to one community only, but evidences in biology and social networks reveal that the communities often overlap with each other. In other words, one node can probably belong to multiple

On the construction of symmetric nonnegative matrix with prescribed Ritz values

Directory of Open Access Journals (Sweden)

Alimohammad Nazari

2014-09-01

Full Text Available In this paper for a given prescribed Ritz values that satisfy inthe some  special conditions,  we find a symmetric nonnegativematrix, such that  the given set be its Ritz values.

The central role of vascular extracellular matrix and basement membrane remodeling in metabolic syndrome and type 2 diabetes: the matrix preloaded

Directory of Open Access Journals (Sweden)

Tyagi Suresh C

2005-06-01

Full Text Available Abstract The vascular endothelial basement membrane and extra cellular matrix is a compilation of different macromolecules organized by physical entanglements, opposing ionic charges, chemical covalent bonding, and cross-linking into a biomechanically active polymer. These matrices provide a gel-like form and scaffolding structure with regional tensile strength provided by collagens, elasticity by elastins, adhesiveness by structural glycoproteins, compressibility by proteoglycans – hyaluronans, and communicability by a family of integrins, which exchanges information between cells and between cells and the extracellular matrix of vascular tissues. Each component of the extracellular matrix and specifically the capillary basement membrane possesses unique structural properties and interactions with one another, which determine the separate and combined roles in the multiple diabetic complications or diabetic opathies. Metabolic syndrome, prediabetes, type 2 diabetes mellitus, and their parallel companion (atheroscleropathy are associated with multiple metabolic toxicities and chronic injurious stimuli. The adaptable quality of a matrix or form genetically preloaded with the necessary information to communicate and respond to an ever-changing environment, which supports the interstitium, capillary and arterial vessel wall is individually examined.

On Poisson Nonlinear Transformations

Directory of Open Access Journals (Sweden)

Nasir Ganikhodjaev

2014-01-01

Full Text Available We construct the family of Poisson nonlinear transformations defined on the countable sample space of nonnegative integers and investigate their trajectory behavior. We have proved that these nonlinear transformations are regular.

Matrix proteins as centralized organizers of negative-sense RNA virions.

Science.gov (United States)

Liljeroos, Lassi; Butcher, Sarah J

2013-01-01

Matrix proteins are essential components of most negative-sense RNA, enveloped viruses. They serve a wide range of duties ranging from self-driven membrane budding and coordination of other viral components to modulation of viral transcription. The functional similarity between these proteins is striking, despite major differences in their structures. Whereas biochemical and structural studies have partly been hindered by the inherent aggregation properties of these proteins, their cellular functions are beginning to be understood. In this review we summarize the current knowledge on negative-sense RNA virus matrix proteins and their interactions with other viral and cellular proteins. We also discuss the similarities and differences in matrix protein functions between the different families within the negative-sense RNA viruses.

Analytic families of eigenfunctions on a reductive symmetric space

NARCIS (Netherlands)

Ban, E.P. van den; Schlichtkrull, H.

2000-01-01

In harmonic analysis on a reductive symmetric space X an important role is played by families of generalized eigenfunctions for the algebra D (X) of invariant dierential operators. Such families arise for instance as matrix coeÆcients of representations that come in series, such as the (generalized)

Monomial strategies for concurrent reachability games and other stochastic games

DEFF Research Database (Denmark)

Frederiksen, Søren Kristoffer Stiil; Miltersen, Peter Bro

2013-01-01

We consider two-player zero-sum finite (but infinite-horizon) stochastic games with limiting average payoffs. We define a family of stationary strategies for Player I parameterized by ε > 0 to be monomial, if for each state k and each action j of Player I in state k except possibly one action, we...... have that the probability of playing j in k is given by an expression of the form c ε d for some non-negative real number c and some non-negative integer d. We show that for all games, there is a monomial family of stationary strategies that are ε-optimal among stationary strategies. A corollary...... is that all concurrent reachability games have a monomial family of ε-optimal strategies. This generalizes a classical result of de Alfaro, Henzinger and Kupferman who showed that this is the case for concurrent reachability games where all states have value 0 or 1....

Characterizing the influence of matrix ductility on damage phenomenology in continuous fiber-reinforced thermoplastic laminates undergoing quasi-static indentation

KAUST Repository

Yudhanto, Arief; Wafai, Husam; Lubineau, Gilles; Yaldiz, R.; Verghese, N.

2017-01-01

The use of thermoplastic matrix was known to improve the impact properties of laminated composites. However, different ductility levels can exist in a single family of thermoplastic matrix, and this may consequently modify the damage phenomenology

Metal matrix composites. Part 1. Types, properties, applications

International Nuclear Information System (INIS)

Edil da Costa, C.; Velasco Lopez, F.; Torralba Castello, M.

2000-01-01

An overview on the state of the art of metal matrix composites used in the automotive and aerospace industries is made. These materials usually are based on light alloys (Al, Ti and Mg) and reinforced with fibres or particles. In this review, it is presented a general scope on the different MMCs families, about their properties and their main applications. (Author) 61 refs

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

Science.gov (United States)

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.

Matrix completion by deep matrix factorization.

Science.gov (United States)

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.

The ECM-Cell Interaction of Cartilage Extracellular Matrix on Chondrocytes

Directory of Open Access Journals (Sweden)

Yue Gao

2014-01-01

Full Text Available Cartilage extracellular matrix (ECM is composed primarily of the network type II collagen (COLII and an interlocking mesh of fibrous proteins and proteoglycans (PGs, hyaluronic acid (HA, and chondroitin sulfate (CS. Articular cartilage ECM plays a crucial role in regulating chondrocyte metabolism and functions, such as organized cytoskeleton through integrin-mediated signaling via cell-matrix interaction. Cell signaling through integrins regulates several chondrocyte functions, including differentiation, metabolism, matrix remodeling, responses to mechanical stimulation, and cell survival. The major signaling pathways that regulate chondrogenesis have been identified as wnt signal, nitric oxide (NO signal, protein kinase C (PKC, and retinoic acid (RA signal. Integrins are a large family of molecules that are central regulators in multicellular biology. They orchestrate cell-cell and cell-matrix adhesive interactions from embryonic development to mature tissue function. In this review, we emphasize the signaling molecule effect and the biomechanics effect of cartilage ECM on chondrogenesis.

Redesigning Triangular Dense Matrix Computations on GPUs

KAUST Repository

Charara, Ali

2016-08-09

A new implementation of the triangular matrix-matrix multiplication (TRMM) and the triangular solve (TRSM) kernels are described on GPU hardware accelerators. Although part of the Level 3 BLAS family, these highly computationally intensive kernels fail to achieve the percentage of the theoretical peak performance on GPUs that one would expect when running kernels with similar surface-to-volume ratio on hardware accelerators, i.e., the standard matrix-matrix multiplication (GEMM). The authors propose adopting a recursive formulation, which enriches the TRMM and TRSM inner structures with GEMM calls and, therefore, reduces memory traffic while increasing the level of concurrency. The new implementation enables efficient use of the GPU memory hierarchy and mitigates the latency overhead, to run at the speed of the higher cache levels. Performance comparisons show up to eightfold and twofold speedups for large dense matrix sizes, against the existing state-of-the-art TRMM and TRSM implementations from NVIDIA cuBLAS, respectively, across various GPU generations. Once integrated into high-level Cholesky-based dense linear algebra algorithms, the performance impact on the overall applications demonstrates up to fourfold and twofold speedups, against the equivalent native implementations, linked with cuBLAS TRMM and TRSM kernels, respectively. The new TRMM/TRSM kernel implementations are part of the open-source KBLAS software library (http://ecrc.kaust.edu.sa/Pages/Res-kblas.aspx) and are lined up for integration into the NVIDIA cuBLAS library in the upcoming v8.0 release.

An Efficient Technique for Bayesian Modelling of Family Data Using the BUGS software

Directory of Open Access Journals (Sweden)

Harold T Bae

2014-11-01

Full Text Available Linear mixed models have become a popular tool to analyze continuous data from family-based designs by using random effects that model the correlation of subjects from the same family. However, mixed models for family data are challenging to implement with the BUGS (Bayesian inference Using Gibbs Sampling software because of the high-dimensional covariance matrix of the random effects. This paper describes an efficient parameterization that utilizes the singular value decomposition of the covariance matrix of random effects, includes the BUGS code for such implementation, and extends the parameterization to generalized linear mixed models. The implementation is evaluated using simulated data and an example from a large family-based study is presented with a comparison to other existing methods.

Transcriptional profiling of the human fibrillin/LTBP gene family, key regulators of mesenchymal cell functions

DEFF Research Database (Denmark)

Davis, Margaret R.; Andersson, Robin; Severin, Jessica

2014-01-01

in the structure of the extracellular matrix and controlling the bioavailability of TGFβ family members. Genes encoding these proteins show differential expression in mesenchymal cell types which synthesize the extracellular matrix. We have investigated the promoter regions of the seven gene family members using...... of the family members were expressed in a range of mesenchymal and other cell types, often associated with use of alternative promoters or transcription start sites within a promoter in different cell types. FBN3 was the lowest expressed gene, and was found only in embryonic and fetal tissues. The different...

Matrix metalloproteinases in stem cell regulation and cancer

OpenAIRE

Kessenbrock, K; Wang, CY; Wang, CY; Werb, Z

2014-01-01

© 2015. Since Gross and Lapiere firstly discovered matrix metalloproteinases (MMPs) as important collagenolytic enzymes during amphibian tadpole morphogenesis in 1962, this intriguing family of extracellular proteinases has been implicated in various processes of developmental biology. However, the pathogenic roles of MMPs in human diseases such as cancer have also garnered widespread attention. The most straightforward explanation for their role in cancer is that MMPs, through extracellular ...

Parallel family trees for transfer matrices in the Potts model

Science.gov (United States)

Navarro, Cristobal A.; Canfora, Fabrizio; Hitschfeld, Nancy; Navarro, Gonzalo

2015-02-01

The computational cost of transfer matrix methods for the Potts model is related to the question in how many ways can two layers of a lattice be connected? Answering the question leads to the generation of a combinatorial set of lattice configurations. This set defines the configuration space of the problem, and the smaller it is, the faster the transfer matrix can be computed. The configuration space of generic (q , v) transfer matrix methods for strips is in the order of the Catalan numbers, which grows asymptotically as O(4m) where m is the width of the strip. Other transfer matrix methods with a smaller configuration space indeed exist but they make assumptions on the temperature, number of spin states, or restrict the structure of the lattice. In this paper we propose a parallel algorithm that uses a sub-Catalan configuration space of O(3m) to build the generic (q , v) transfer matrix in a compressed form. The improvement is achieved by grouping the original set of Catalan configurations into a forest of family trees, in such a way that the solution to the problem is now computed by solving the root node of each family. As a result, the algorithm becomes exponentially faster than the Catalan approach while still highly parallel. The resulting matrix is stored in a compressed form using O(3m ×4m) of space, making numerical evaluation and decompression to be faster than evaluating the matrix in its O(4m ×4m) uncompressed form. Experimental results for different sizes of strip lattices show that the parallel family trees (PFT) strategy indeed runs exponentially faster than the Catalan Parallel Method (CPM), especially when dealing with dense transfer matrices. In terms of parallel performance, we report strong-scaling speedups of up to 5.7 × when running on an 8-core shared memory machine and 28 × for a 32-core cluster. The best balance of speedup and efficiency for the multi-core machine was achieved when using p = 4 processors, while for the cluster

Joint probabilities reproducing three EPR experiments on two qubits

NARCIS (Netherlands)

Roy, S. M.; Atkinson, D.; Auberson, G.; Mahoux, G.; Singh, V.

2007-01-01

An eight-parameter family of the most general non-negative quadruple probabilities is constructed for EPR-Bohm-Aharonov experiments when only three pairs of analyser settings are used. It is a simultaneous representation of three different Bohr-incompatible experimental configurations involving

[Preparation of acellular matrix from antler cartilage and its biological compatibility].

Science.gov (United States)

Fu, Jing; Zhang, Wei; Zhang, Aiwu; Ma, Lijuan; Chu, Wenhui; Li, Chunyi

2017-06-01

To study the feasibility of acellular matrix materials prepared from deer antler cartilage and its biological compatibility so as to search for a new member of the extracellular matrix family for cartilage regeneration. The deer antler mesenchymal (M) layer tissue was harvested and treated through decellular process to prepare M layer acellular matrix; histologic observation and detection of M layer acellular matrix DNA content were carried out. The antler stem cells [antlerogenic periosteum (AP) cells] at 2nd passage were labelled by fluorescent stains and by PKH26. Subsequently, the M layer acellular matrix and the AP cells at 2nd passage were co-cultured for 7 days; then the samples were transplanted into nude mice to study the tissue compatibility of M layer acellular matrix in the living animals. HE and DAPI staining confirmed that the M layer acellular matrix did not contain nucleus; the DNA content of the M layer acellular matrix was (19.367±5.254) ng/mg, which was significantly lower than that of the normal M layer tissue [(3 805.500±519.119) ng/mg]( t =12.630, P =0.000). In vitro co-culture experiments showed that AP cells could adhere to or even embedded in the M layer acellular matrix. Nude mice transplantation experiments showed that the introduced AP cells could proliferate and induce angiogenesis in the M layer acellular matrix. The deer antler cartilage acellular matrix is successfully prepared. The M layer acellular matrix is suitable for adhesion and proliferation of AP cells in vitro and in vivo , and it has the function of stimulating angiogenesis. This model for deer antler cartilage acellular matrix can be applied in cartilage tissue engineering in the future.

Matrix Metalloproteinases Are Differentially Regulated and Responsive to Compression Therapy in a Red Duroc Model of Hypertrophic Scar.

Science.gov (United States)

Travis, Taryn E; Ghassemi, Pejhman; Prindeze, Nicholas J; Moffatt, Lauren T; Carney, Bonnie C; Alkhalil, Abdulnaser; Ramella-Roman, Jessica C; Shupp, Jeffrey W

2018-01-01

Objective: Proteins of the matrix metalloproteinases family play a vital role in extracellular matrix maintenance and basic physiological processes in tissue homeostasis. The function and activities of matrix metalloproteinases in response to compression therapies have yet to be defined. Here, a swine model of hypertrophic scar was used to profile the transcription of all known 26 matrix metalloproteinases in scars treated with a precise compression dose. Methods: Full-thickness excisional wounds were created. Wounds underwent healing and scar formation. A subset of scars underwent 2 weeks of compression therapy. Biopsy specimens were preserved, and microarrays, reverse transcription-polymerase chain reaction, Western blotting, and immunohistochemistry were performed to characterize the transcription and expression of various matrix metalloproteinase family members. Results: Microarray results showed that 13 of the known 26 matrix metalloproteinases were differentially transcribed in wounds relative to the preinjury skin. The predominant upregulation of these matrix metalloproteinases during early wound-healing stages declined gradually in later stages of wound healing. The use of compression therapy reduced this decline in 10 of the 13 differentially regulated matrix metalloproteinases. Further investigation of MMP7 using reverse transcription-polymerase chain reaction confirmed the effect of compression on transcript levels. Assessment of MMP7 at the protein level using Western blotting and immunohistochemistry was concordant. Conclusions: In a swine model of hypertrophic scar, the application of compression to hypertrophic scar attenuated a trend of decreasing levels of matrix metalloproteinases during the process of hypertrophic wound healing, including MMP7, whose enzyme regulation was confirmed at the protein level.

Genetic Variation in the Matrix Metalloproteinase Genes and Diabetic Nephropathy in Type 1 Diabetes

OpenAIRE

Kure, Masahiko; Pezzolesi, Marcus G.; Poznik, G. David; Katavetin, Pisut; Skupien, Jan; Dunn, Jonathon S.; Mychaleckyj, Josyf C.; Warram, James H.; Krolewski, Andrzej S.

2011-01-01

Genetic data support the notion that polymorphisms in members of the matrix metalloproteinase (MMP) family of genes play an important role in extracellular matrix remodeling and contribute to the pathogenesis of vascular disease. To identify novel genetic markers for diabetic nephropathy (DN), we examined the relationship between MMP gene polymorphisms and DN in the Genetics of Kidneys in Diabetes (GoKinD) population. Genotypic data from the Genetic Association Information Network (GAIN) type...

A Family of Integrable Rational Semi-Discrete Systems and Its Reduction

International Nuclear Information System (INIS)

Xu Xixiang

2010-01-01

Within framework of zero curvature representation theory, a family of integrahle rational semi-discrete systems is derived from a matrix spectral problem. The Hamiltonian forms of obtained semi-discrete systems are constructed by means of the discrete trace identity. The Liouville integrability for the obtained family is demonstrated. In the end, a reduced family of obtained semi-discrete systems and its Hamiltonian form are worked out. (general)

Fourth SM family, breaking of mass democracy, and the CKM mixings

International Nuclear Information System (INIS)

Atag, S.; Celikel, A.; Ciftci, A.K.; Sultansoy, S.; Yilmaz, U.O.

1996-01-01

We consider the violation of the democratic mass matrix in the framework of the four-family standard model. Predictions of fourth-family fermion masses as well as quark and lepton CKM mixings are presented. Production and decay modes of new fermions are discussed. copyright 1996 The American Physical Society

Model for particle masses, flavor mixing, and CP violation, based on spontaneously broken discrete chiral symmetry as the origin of families

International Nuclear Information System (INIS)

Adler, S.L.

1999-01-01

We construct extensions of the standard model based on the hypothesis that Higgs bosons also exhibit a family structure and that the flavor weak eigenstates in the three families are distinguished by a discrete Z 6 chiral symmetry that is spontaneously broken by the Higgs sector. We study in detail at the tree level models with three Higgs doublets and with six Higgs doublets comprising two weakly coupled sets of three. In a leading approximation of S 3 cyclic permutation symmetry the three-Higgs-doublet model gives a open-quotes democraticclose quotes mass matrix of rank 1, while the six-Higgs-doublet model gives either a rank-1 mass matrix or, in the case when it spontaneously violates CP, a rank-2 mass matrix corresponding to nonzero second family masses. In both models, the CKM matrix is exactly unity in the leading approximation. Allowing small explicit violations of cyclic permutation symmetry generates small first family masses in the six-Higgs-doublet model, and first and second family masses in the three-Higgs-doublet model, and gives a nontrivial CKM matrix in which the mixings of the first and second family quarks are naturally larger than mixings involving the third family. Complete numerical fits are given for both models, flavor-changing neutral current constraints are discussed in detail, and the issues of unification of couplings and neutrino masses are addressed. On a technical level, our analysis uses the theory of circulant and retrocirculant matrices, the relevant parts of which are reviewed. copyright 1998 The American Physical Society

Bayesian Nonnegative Matrix Factorization with Volume Prior for Unmixing of Hyperspectral Images

DEFF Research Database (Denmark)

Arngren, Morten; Schmidt, Mikkel Nørgaard; Larsen, Jan

2009-01-01

based unmixing algorithms are based on sparsity regularization encouraging pure spectral endmembers, but this is not optimal for certain applications, such as foods, where abundances are not sparse. The pixels will theoretically lie on a simplex and hence the endmembers can be estimated as the vertices...

Dependence of the fundamental time eigenvalue of linear transport operator on the system size and other parameters - An application of the Perron-Frobenius theorem

International Nuclear Information System (INIS)

Sahni, D.C.

1991-01-01

Many papers have been devoted to the study of the spectral properties of the linear (neutron) transport equation. Most of the theoretical investigations have concentrated on the existence (or otherwise) of a continuous spectrum, point spectrum, a leading/dominant eigenvalue, and a corresponding positive eigenvector. It is shown that the fundamental time eigenvalue of the linear transport operator increases with the size of the system. This follows from the increase in the largest eigenvalue of a non-negative irreducible matrix whenever any matrix element his increased. This result of matrix analysis is generalized to more general Krein-Rutman operators that leave a cone of vectors invariant

Algorithm for Optimizing Bipolar Interconnection Weights with Applications in Associative Memories and Multitarget Classification

Science.gov (United States)

Chang, Shengjiang; Wong, Kwok-Wo; Zhang, Wenwei; Zhang, Yanxin

1999-08-01

An algorithm for optimizing a bipolar interconnection weight matrix with the Hopfield network is proposed. The effectiveness of this algorithm is demonstrated by computer simulation and optical implementation. In the optical implementation of the neural network the interconnection weights are biased to yield a nonnegative weight matrix. Moreover, a threshold subchannel is added so that the system can realize, in real time, the bipolar weighted summation in a single channel. Preliminary experimental results obtained from the applications in associative memories and multitarget classification with rotation invariance are shown.

Weighted A-statistical convergence for sequences of positive linear operators.

Science.gov (United States)

Mohiuddine, S A; Alotaibi, Abdullah; Hazarika, Bipan

2014-01-01

We introduce the notion of weighted A-statistical convergence of a sequence, where A represents the nonnegative regular matrix. We also prove the Korovkin approximation theorem by using the notion of weighted A-statistical convergence. Further, we give a rate of weighted A-statistical convergence and apply the classical Bernstein polynomial to construct an illustrative example in support of our result.

Theory of quark mixing matrix and invariant functions of mass matrices

International Nuclear Information System (INIS)

Jarlskog, C.

1987-10-01

The outline of this talk is as follows: The origin of the quark mixing matrix. Super elementary theory of flavour projection operators. Equivalences and invariances. The commutator formalism and CP violation. CP conditions for any number of families. The 'angle' between the quark mass matrices. Application to Fritzsch and Stech matrices. References. (author)

Matrix metalloproteinases (MMPs), the main extracellular matrix (ECM) enzymes in collagen degradation, as a target for anticancer drugs.

Science.gov (United States)

Jabłońska-Trypuć, Agata; Matejczyk, Marzena; Rosochacki, Stanisław

2016-01-01

The main group of enzymes responsible for the collagen and other protein degradation in extracellular matrix (ECM) are matrix metalloproteinases (MMPs). Collagen is the main structural component of connective tissue and its degradation is a very important process in the development, morphogenesis, tissue remodeling, and repair. Typical structure of MMPs consists of several distinct domains. MMP family can be divided into six groups: collagenases, gelatinases, stromelysins, matrilysins, membrane-type MMPs, and other non-classified MMPs. MMPs and their inhibitors have multiple biological functions in all stages of cancer development: from initiation to outgrowth of clinically relevant metastases and likewise in apoptosis and angiogenesis. MMPs and their inhibitors are extensively examined as potential anticancer drugs. MMP inhibitors can be divided into two main groups: synthetic and natural inhibitors. Selected synthetic inhibitors are in clinical trials on humans, e.g. synthetic peptides, non-peptidic molecules, chemically modified tetracyclines, and bisphosphonates. Natural MMP inhibitors are mainly isoflavonoids and shark cartilage.

Ubuntu and Social Capital factors in Family Businesses

Directory of Open Access Journals (Sweden)

William Venter

2008-12-01

Full Text Available The current study is an investigation of social capital, and more particularly the support of the concept of ubuntu in large family businesses in South Africa. Insights into the social responsibility activities of some of the largest family businesses in South Africa, obtained through semi-structured interviews, clearly indicate the important role which the social responsibility ubuntu activities of these businesses play in caring for the community. As South Africa has a mainly “individualistic economic community”, it is interesting to observe how the collectivistic notion of ubuntu is practised in the social responsibility activities of family business groups. Key words and phrases: ubuntu, social responsibility, social capital, family business, conditional matrix

Matrix product operators, matrix product states, and ab initio density matrix renormalization group algorithms

Science.gov (United States)

Chan, Garnet Kin-Lic; Keselman, Anna; Nakatani, Naoki; Li, Zhendong; White, Steven R.

2016-07-01

Current descriptions of the ab initio density matrix renormalization group (DMRG) algorithm use two superficially different languages: an older language of the renormalization group and renormalized operators, and a more recent language of matrix product states and matrix product operators. The same algorithm can appear dramatically different when written in the two different vocabularies. In this work, we carefully describe the translation between the two languages in several contexts. First, we describe how to efficiently implement the ab initio DMRG sweep using a matrix product operator based code, and the equivalence to the original renormalized operator implementation. Next we describe how to implement the general matrix product operator/matrix product state algebra within a pure renormalized operator-based DMRG code. Finally, we discuss two improvements of the ab initio DMRG sweep algorithm motivated by matrix product operator language: Hamiltonian compression, and a sum over operators representation that allows for perfect computational parallelism. The connections and correspondences described here serve to link the future developments with the past and are important in the efficient implementation of continuing advances in ab initio DMRG and related algorithms.

The classical trigonometric r-matrix for the quantum-deformed Hubbard chain

Energy Technology Data Exchange (ETDEWEB)

Beisert, Niklas, E-mail: nbeisert@aei.mpg.de [Max-Planck-Institut fuer Gravitationsphysik, Albert-Einstein-Institut, Am Muehlenberg 1, 14476 Potsdam (Germany)

2011-07-01

The one-dimensional Hubbard model is an exceptional integrable spin chain which is apparently based on a deformation of the Yangian for the superalgebra gl(2|2). Here we investigate the quantum deformation of the Hubbard model in the classical limit. This leads to a novel classical r-matrix of trigonometric kind. We derive the corresponding one-parameter family of Lie bialgebras as a deformation of the affine gl(2|2) Kac-Moody superalgebra. In particular, we discuss the affine extension as well as discrete symmetries, and we scan for simpler limiting cases, such as the rational r-matrix for the undeformed Hubbard model.

Optical supervised filtering technique based on Hopfield neural network

Science.gov (United States)

Bal, Abdullah

2004-11-01

Hopfield neural network is commonly preferred for optimization problems. In image segmentation, conventional Hopfield neural networks (HNN) are formulated as a cost-function-minimization problem to perform gray level thresholding on the image histogram or the pixels' gray levels arranged in a one-dimensional array [R. Sammouda, N. Niki, H. Nishitani, Pattern Rec. 30 (1997) 921-927; K.S. Cheng, J.S. Lin, C.W. Mao, IEEE Trans. Med. Imag. 15 (1996) 560-567; C. Chang, P. Chung, Image and Vision comp. 19 (2001) 669-678]. In this paper, a new high speed supervised filtering technique is proposed for image feature extraction and enhancement problems by modifying the conventional HNN. The essential improvement in this technique is to use 2D convolution operation instead of weight-matrix multiplication. Thereby, neural network based a new filtering technique has been obtained that is required just 3 × 3 sized filter mask matrix instead of large size weight coefficient matrix. Optical implementation of the proposed filtering technique is executed easily using the joint transform correlator. The requirement of non-negative data for optical implementation is provided by bias technique to convert the bipolar data to non-negative data. Simulation results of the proposed optical supervised filtering technique are reported for various feature extraction problems such as edge detection, corner detection, horizontal and vertical line extraction, and fingerprint enhancement.

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

Science.gov (United States)

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.

THE COMPARISON BETWEEN NMF AND ICA IN PIGMENT MIXTURE IDENTIFICATION OF ANCIENT CHINESE PAINTINGS

Directory of Open Access Journals (Sweden)

Y. Liu

2018-04-01

Full Text Available 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.

Semi-supervised spectral algorithms for community detection in complex networks based on equivalence of clustering methods

Science.gov (United States)

Ma, Xiaoke; Wang, Bingbo; Yu, Liang

2018-01-01

Community detection is fundamental for revealing the structure-functionality relationship in complex networks, which involves two issues-the quantitative function for community as well as algorithms to discover communities. Despite significant research on either of them, few attempt has been made to establish the connection between the two issues. To attack this problem, a generalized quantification function is proposed for community in weighted networks, which provides a framework that unifies several well-known measures. Then, we prove that the trace optimization of the proposed measure is equivalent with the objective functions of algorithms such as nonnegative matrix factorization, kernel K-means as well as spectral clustering. It serves as the theoretical foundation for designing algorithms for community detection. On the second issue, a semi-supervised spectral clustering algorithm is developed by exploring the equivalence relation via combining the nonnegative matrix factorization and spectral clustering. Different from the traditional semi-supervised algorithms, the partial supervision is integrated into the objective of the spectral algorithm. Finally, through extensive experiments on both artificial and real world networks, we demonstrate that the proposed method improves the accuracy of the traditional spectral algorithms in community detection.

Structural differences of matrix metalloproteinases. Homology modeling and energy minimization of enzyme-substrate complexes

DEFF Research Database (Denmark)

Terp, G E; Christensen, I T; Jørgensen, Flemming Steen

2000-01-01

Matrix metalloproteinases are extracellular enzymes taking part in the remodeling of extracellular matrix. The structures of the catalytic domain of MMP1, MMP3, MMP7 and MMP8 are known, but structures of enzymes belonging to this family still remain to be determined. A general approach...... to the homology modeling of matrix metalloproteinases, exemplified by the modeling of MMP2, MMP9, MMP12 and MMP14 is described. The models were refined using an energy minimization procedure developed for matrix metalloproteinases. This procedure includes incorporation of parameters for zinc and calcium ions...... in the AMBER 4.1 force field, applying a non-bonded approach and a full ion charge representation. Energy minimization of the apoenzymes yielded structures with distorted active sites, while reliable three-dimensional structures of the enzymes containing a substrate in active site were obtained. The structural...

Highly sensitive bacterial susceptibility test against penicillin using parylene-matrix chip.

Science.gov (United States)

Park, Jong-Min; Kim, Jo-Il; Song, Hyun-Woo; Noh, Joo-Yoon; Kang, Min-Jung; Pyun, Jae-Chul

2015-09-15

This work presented a highly sensitive bacterial antibiotic susceptibility test through β-lactamase assay using Parylene-matrix chip. β-lactamases (EC 3.5.2.6) are an important family of enzymes that confer resistance to β-lactam antibiotics by catalyzing the hydrolysis of these antibiotics. Here we present a highly sensitive assay to quantitate β-lactamase-mediated hydrolysis of penicillin into penicilloic acid. Typically, MALDI-TOF mass spectrometry has been used to quantitate low molecular weight analytes and to discriminate them from noise peaks of matrix fragments that occur at low m/z ratios (m/ztest was carried out using Parylene-matrix chip and MALDI-TOF mass spectrometry. The Parylene-matrix chip was successfully used to quantitate penicillin (m/z: [PEN+H](+)=335.1 and [PEN+Na](+)=357.8) and penicilloic acid (m/z: [PA+H](+)=353.1) in a β-lactamase assay with minimal interference of low molecular weight noise peaks. The β-lactamase assay was carried out with an antibiotic-resistant E. coli strain and an antibiotic-susceptible E. coli strain, revealing that the minimum number of E. coli cells required to screen for antibiotic resistance was 1000 cells for the MALDI-TOF mass spectrometry/Parylene-matrix chip assay. Copyright © 2015 Elsevier B.V. All rights reserved.

Weighted A-Statistical Convergence for Sequences of Positive Linear Operators

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S. A. Mohiuddine

2014-01-01

Full Text Available We introduce the notion of weighted A-statistical convergence of a sequence, where A represents the nonnegative regular matrix. We also prove the Korovkin approximation theorem by using the notion of weighted A-statistical convergence. Further, we give a rate of weighted A-statistical convergence and apply the classical Bernstein polynomial to construct an illustrative example in support of our result.

Bee venom induces apoptosis and suppresses matrix metaloprotease-2 expression in human glioblastoma cells

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Mohsen Sisakht

Full Text Available Abstract Glioblastoma is the most common malignant brain tumor representing with poor prognosis, therapy resistance and high metastasis rate. Increased expression and activity of matrix metalloproteinase-2, a member of matrix metalloproteinase family proteins, has been reported in many cancers including glioblastoma. Inhibition of matrix metalloproteinase-2 expression has resulted in reduced aggression of glioblastoma tumors in several reports. In the present study, we evaluated effect of bee venom on expression and activity of matrix metalloproteinase-2 as well as potential toxicity and apoptogenic properties of bee venom on glioblastoma cells. Human A172 glioblastoma cells were treated with increasing concentrations of bee venom. Then, cell viability, apoptosis, matrix metalloproteinase-2 expression, and matrix metalloproteinase-2 activity were measured using MMT assay, propidium iodide staining, real time-PCR, and zymography, respectively. The IC50 value of bee venom was 28.5 µg/ml in which it leads to decrease of cell viability and induction of apoptosis. Incubation with bee venom also decreased the expression of matrix metalloproteinase-2 in this cell line (p < 0.05. In zymography, there was a reverse correlation between bee venom concentration and total matrix metalloproteinase-2 activity. Induction of apoptosis as well as inhibition of matrix metalloproteinase-2 activity and expression can be suggested as molecular mechanisms involved in cytotoxic and antimetastatic effects of bee venom against glioblastoma cells.

Collagen matrix as a tool in studying fibroblastic cell behavior.

Science.gov (United States)

Kanta, Jiří

2015-01-01

Type I collagen is a fibrillar protein, a member of a large family of collagen proteins. It is present in most body tissues, usually in combination with other collagens and other components of extracellular matrix. Its synthesis is increased in various pathological situations, in healing wounds, in fibrotic tissues and in many tumors. After extraction from collagen-rich tissues it is widely used in studies of cell behavior, especially those of fibroblasts and myofibroblasts. Cells cultured in a classical way, on planar plastic dishes, lack the third dimension that is characteristic of body tissues. Collagen I forms gel at neutral pH and may become a basis of a 3D matrix that better mimics conditions in tissue than plastic dishes.

Vacuum states and the S matrix in dS/CFT

International Nuclear Information System (INIS)

Spradlin, Marcus; Volovich, Anastasia

2002-01-01

We propose a definition of dS/CFT correlation functions by equating them to S-matrix elements for scattering particles from I - to I + . In planar coordinates, which cover half of de Sitter space, we consider instead the S vector obtained by specifying a fixed state on the horizon. We construct the one-parameter family of de Sitter invariant vacuum states for a massive scalar field in these coordinates, and show that the vacuum obtained by analytic continuation from the sphere has no particles on the past horizon. We use this formalism to provide evidence that the one-parameter family of vacua corresponds to marginal deformations of the CFT by computing a three-point function

Ceramic matrix composite article and process of fabricating a ceramic matrix composite article

Science.gov (United States)

Cairo, Ronald Robert; DiMascio, Paul Stephen; Parolini, Jason Robert

2016-01-12

A ceramic matrix composite article and a process of fabricating a ceramic matrix composite are disclosed. The ceramic matrix composite article includes a matrix distribution pattern formed by a manifold and ceramic matrix composite plies laid up on the matrix distribution pattern, includes the manifold, or a combination thereof. The manifold includes one or more matrix distribution channels operably connected to a delivery interface, the delivery interface configured for providing matrix material to one or more of the ceramic matrix composite plies. The process includes providing the manifold, forming the matrix distribution pattern by transporting the matrix material through the manifold, and contacting the ceramic matrix composite plies with the matrix material.

The family experience of care in chronic situation

Directory of Open Access Journals (Sweden)

Roseney Bellato

2016-06-01

Full Text Available An essay that aims to reflect on the family experience of care in chronic situation, increasing the understanding of the family as the primary caregiver. It is based on comprehensive approach in studies conducted in three matrix searches from family care experiences. We have taken three axes to organize our reflections: a conformation of family care in chronic situation, highlighting the multiple costs incurred to the family, which can exhaust the potential of care and establish or increase its vulnerability if it is not backed by networks support and sustenance; b family rearrangements for the care, giving visibility to care cores in which many loved family members share the care, dynamic, plural and changeable way; c self care modeling family care, pointing to the range of possibilities of the person taking care of diseased conditions supported by people close to them. We learn that the family takes care of itself in everyday life and in the illness experience, creating networks that can provide you support and sustenance. Thus, professionals in health practices should shape up in a longitudinal and very personal way, by reference to the family care, supporting him in what is his own.

Matrix metalloproteinases: structures, evolution, and diversification.

Science.gov (United States)

Massova, I; Kotra, L P; Fridman, R; Mobashery, S

1998-09-01

A comprehensive sequence alignment of 64 members of the family of matrix metalloproteinases (MMPs) for the entire sequences, and subsequently the catalytic and the hemopexin-like domains, have been performed. The 64 MMPs were selected from plants, invertebrates, and vertebrates. The analyses disclosed that as many as 23 distinct subfamilies of these proteins are known to exist. Information from the sequence alignments was correlated with structures, both crystallographic as well as computational, of the catalytic domains for the 23 representative members of the MMP family. A survey of the metal binding sites and two loops containing variable sequences of amino acids, which are important for substrate interactions, are discussed. The collective data support the proposal that the assembly of the domains into multidomain enzymes was likely to be an early evolutionary event. This was followed by diversification, perhaps in parallel among the MMPs, in a subsequent evolutionary time scale. Analysis indicates that a retrograde structure simplification may have accounted for the evolution of MMPs with simple domain constituents, such as matrilysin, from the larger and more elaborate enzymes.

Puiseux monoids and transfer homomorphisms

OpenAIRE

Gotti, Felix

2017-01-01

There are several families of atomic monoids whose arithmetical invariants have received a great deal of attention during the last two decades. The factorization theory of finitely generated monoids, strongly primary monoids, Krull monoids, and C-monoids are among the most systematically studied. Puiseux monoids, which are additive submonoids of $\\mathbb{Q}_{\\ge 0}$ consisting of nonnegative rational numbers, have only been studied recently. In this paper, we provide evidence that this family...

Raney Distributions and Random Matrix Theory

Science.gov (United States)

Forrester, Peter J.; Liu, Dang-Zheng

2015-03-01

Recent works have shown that the family of probability distributions with moments given by the Fuss-Catalan numbers permit a simple parameterized form for their density. We extend this result to the Raney distribution which by definition has its moments given by a generalization of the Fuss-Catalan numbers. Such computations begin with an algebraic equation satisfied by the Stieltjes transform, which we show can be derived from the linear differential equation satisfied by the characteristic polynomial of random matrix realizations of the Raney distribution. For the Fuss-Catalan distribution, an equilibrium problem characterizing the density is identified. The Stieltjes transform for the limiting spectral density of the singular values squared of the matrix product formed from inverse standard Gaussian matrices, and standard Gaussian matrices, is shown to satisfy a variant of the algebraic equation relating to the Raney distribution. Supported on , we show that it too permits a simple functional form upon the introduction of an appropriate choice of parameterization. As an application, the leading asymptotic form of the density as the endpoints of the support are approached is computed, and is shown to have some universal features.

The strongly generalized double difference χ sequence spaces defined by a modulus - doi: 10.4025/actascitechnol.v35i4.16184

Directory of Open Access Journals (Sweden)

Subramanian Nagarajan

2013-10-01

Full Text Available In this paper we introduce the strongly generalized difference sequence spaces of modulus function and is a non-negative four dimensional matrix of complex numbers and (pi(mn is a sequence of positive real numbers. We also give natural relationship between strongly generalized difference summable sequences with respect of modulus. We examine some topological properties of the above spaces and investigate some inclusion relations between these spaces.  

Ceramic matrix and resin matrix composites - A comparison

Science.gov (United States)

Hurwitz, Frances I.

1987-01-01

The underlying theory of continuous fiber reinforcement of ceramic matrix and resin matrix composites, their fabrication, microstructure, physical and mechanical properties are contrasted. The growing use of organometallic polymers as precursors to ceramic matrices is discussed as a means of providing low temperature processing capability without the fiber degradation encountered with more conventional ceramic processing techniques. Examples of ceramic matrix composites derived from particulate-filled, high char yield polymers and silsesquioxane precursors are provided.

Ceramic matrix and resin matrix composites: A comparison

Science.gov (United States)

Hurwitz, Frances I.

1987-01-01

The underlying theory of continuous fiber reinforcement of ceramic matrix and resin matrix composites, their fabrication, microstructure, physical and mechanical properties are contrasted. The growing use of organometallic polymers as precursors to ceramic matrices is discussed as a means of providing low temperature processing capability without the fiber degradation encountered with more conventional ceramic processing techniques. Examples of ceramic matrix composites derived from particulate-filled, high char yield polymers and silsesquioxane precursors are provided.

Metamotifs - a generative model for building families of nucleotide position weight matrices

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Down Thomas A

2010-06-01

Full Text Available Abstract Background Development of high-throughput methods for measuring DNA interactions of transcription factors together with computational advances in short motif inference algorithms is expanding our understanding of transcription factor binding site motifs. The consequential growth of sequence motif data sets makes it important to systematically group and categorise regulatory motifs. It has been shown that there are familial tendencies in DNA sequence motifs that are predictive of the family of factors that binds them. Further development of methods that detect and describe familial motif trends has the potential to help in measuring the similarity of novel computational motif predictions to previously known data and sensitively detecting regulatory motifs similar to previously known ones from novel sequence. Results We propose a probabilistic model for position weight matrix (PWM sequence motif families. The model, which we call the 'metamotif' describes recurring familial patterns in a set of motifs. The metamotif framework models variation within a family of sequence motifs. It allows for simultaneous estimation of a series of independent metamotifs from input position weight matrix (PWM motif data and does not assume that all input motif columns contribute to a familial pattern. We describe an algorithm for inferring metamotifs from weight matrix data. We then demonstrate the use of the model in two practical tasks: in the Bayesian NestedMICA model inference algorithm as a PWM prior to enhance motif inference sensitivity, and in a motif classification task where motifs are labelled according to their interacting DNA binding domain. Conclusions We show that metamotifs can be used as PWM priors in the NestedMICA motif inference algorithm to dramatically increase the sensitivity to infer motifs. Metamotifs were also successfully applied to a motif classification problem where sequence motif features were used to predict the family of

Feature selection and multi-kernel learning for adaptive graph regularized nonnegative matrix factorization

KAUST Repository

Wang, Jim Jing-Yan; Huang, Jianhua Z.; Sun, Yijun; Gao, Xin

2014-01-01

by regularizing NMF with a nearest neighbor graph constructed from the input data set. However, GNMF has two main bottlenecks. First, using the original feature space directly to construct the graph is not necessarily optimal because of the noisy and irrelevant

M(atrix) theory: matrix quantum mechanics as a fundamental theory

International Nuclear Information System (INIS)

Taylor, Washington

2001-01-01

This article reviews the matrix model of M theory. M theory is an 11-dimensional quantum theory of gravity that is believed to underlie all superstring theories. M theory is currently the most plausible candidate for a theory of fundamental physics which reconciles gravity and quantum field theory in a realistic fashion. Evidence for M theory is still only circumstantial -- no complete background-independent formulation of the theory exists as yet. Matrix theory was first developed as a regularized theory of a supersymmetric quantum membrane. More recently, it has appeared in a different guise as the discrete light-cone quantization of M theory in flat space. These two approaches to matrix theory are described in detail and compared. It is shown that matrix theory is a well-defined quantum theory that reduces to a supersymmetric theory of gravity at low energies. Although its fundamental degrees of freedom are essentially pointlike, higher-dimensional fluctuating objects (branes) arise through the non-Abelian structure of the matrix degrees of freedom. The problem of formulating matrix theory in a general space-time background is discussed, and the connections between matrix theory and other related models are reviewed

Muscle synergies during bench press are reliable across days.

Science.gov (United States)

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.

Matrix product states for lattice field theories

Energy Technology Data Exchange (ETDEWEB)

Banuls, M.C.; Cirac, J.I. [Max-Planck-Institut fuer Quantenoptik (MPQ), Garching (Germany); Cichy, K. [Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany). John von Neumann-Inst. fuer Computing NIC; Poznan Univ. (Poland). Faculty of Physics; Jansen, K. [Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany). John von Neumann-Inst. fuer Computing NIC; Saito, H. [Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany). John von Neumann-Inst. fuer Computing NIC; Tsukuba Univ., Ibaraki (Japan). Graduate School of Pure and Applied Sciences

2013-10-15

The term Tensor Network States (TNS) refers to a number of families of states that represent different ansaetze for the efficient description of the state of a quantum many-body system. Matrix Product States (MPS) are one particular case of TNS, and have become the most precise tool for the numerical study of one dimensional quantum many-body systems, as the basis of the Density Matrix Renormalization Group method. Lattice Gauge Theories (LGT), in their Hamiltonian version, offer a challenging scenario for these techniques. While the dimensions and sizes of the systems amenable to TNS studies are still far from those achievable by 4-dimensional LGT tools, Tensor Networks can be readily used for problems which more standard techniques, such as Markov chain Monte Carlo simulations, cannot easily tackle. Examples of such problems are the presence of a chemical potential or out-of-equilibrium dynamics. We have explored the performance of Matrix Product States in the case of the Schwinger model, as a widely used testbench for lattice techniques. Using finite-size, open boundary MPS, we are able to determine the low energy states of the model in a fully non-perturbativemanner. The precision achieved by the method allows for accurate finite size and continuum limit extrapolations of the ground state energy, but also of the chiral condensate and the mass gaps, thus showing the feasibility of these techniques for gauge theory problems.

Reduction of multipartite qubit density matrixes to bipartite qubit density matrixes and criteria of partial separability of multipartite qubit density matrixes

OpenAIRE

Zhong, Zai-Zhe

2004-01-01

The partial separability of multipartite qubit density matrixes is strictly defined. We give a reduction way from N-partite qubit density matrixes to bipartite qubit density matrixes, and prove a necessary condition that a N-partite qubit density matrix to be partially separable is its reduced density matrix to satisfy PPT condition.

Coding theory on the m-extension of the Fibonacci p-numbers

International Nuclear Information System (INIS)

Basu, Manjusri; Prasad, Bandhu

2009-01-01

In this paper, we introduce a new Fibonacci G p,m matrix for the m-extension of the Fibonacci p-numbers where p (≥0) is integer and m (>0). Thereby, we discuss various properties of G p,m matrix and the coding theory followed from the G p,m matrix. In this paper, we establish the relations among the code elements for all values of p (nonnegative integer) and m(>0). We also show that the relation, among the code matrix elements for all values of p and m=1, coincides with the relation among the code matrix elements for all values of p [Basu M, Prasad B. The generalized relations among the code elements for Fibonacci coding theory. Chaos, Solitons and Fractals (2008). doi: 10.1016/j.chaos.2008.09.030]. In general, correct ability of the method increases as p increases but it is independent of m.

Why threefold-replication of families?

Science.gov (United States)

Fitzpatrick, Gerald L.

1998-04-01

In spite of the many successes of the standard model of particle physics, the observed proliferation of matter-fields, in the form of ``replicated'' generations or families, is a major unsolved problem. In this paper, I explore some of the algebraic, geometric and physical consequences of a new organizing principle for fundamental fermions (quarks and leptons)(Gerald L. Fitzpatrick, phThe Family Problem--New Internal Algebraic and Geometric Regularities), Nova Scientific Press, Issaquah, Washington, 1997. Read more about this book (ISBN 0--9655695--0--0) and its subject matter at: http://www.tp.umu.se/TIPTOP and/or amazon.com>http://www.amazon.com.. The essence of the new organizing principle is the idea that the standard-model concept of scalar fermion numbers f can be generalized. In particular, a ``generalized fermion number,'' which consists of a 2× 2 matrix F that ``acts'' on an internal 2-space, instead of spacetime, is taken to describe certain internal properties of fundamental fermions. This generalization automatically introduces internal degrees of freedom that ``explain,'' among other things, family replication and the number (three) of families observed in nature.

Symmetry breaking in the double-well hermitian matrix models

CERN Document Server

Brower, R C; Jain, S; Tan, C I; Brower, Richard C.; Deo, Nevidita; Jain, Sanjay; Tan, Chung-I

1993-01-01

We study symmetry breaking in $Z_2$ symmetric large $N$ matrix models. In the planar approximation for both the symmetric double-well $\\phi^4$ model and the symmetric Penner model, we find there is an infinite family of broken symmetry solutions characterized by different sets of recursion coefficients $R_n$ and $S_n$ that all lead to identical free energies and eigenvalue densities. These solutions can be parameterized by an arbitrary angle $\\theta(x)$, for each value of $x = n/N < 1$. In the double scaling limit, this class reduces to a smaller family of solutions with distinct free energies already at the torus level. For the double-well $\\phi^4$ theory the double scaling string equations are parameterized by a conserved angular momentum parameter in the range $0 \\le l < \\infty$ and a single arbitrary $U(1)$ phase angle.

NASA's Astronant Family Support Office

Science.gov (United States)

Beven, Gary; Curtis, Kelly D.; Holland, Al W.; Sipes, Walter; VanderArk, Steve

2014-01-01

During the NASA-Mir program of the 1990s and due to the challenges inherent in the International Space Station training schedule and operations tempo, it was clear that a special focus on supporting families was a key to overall mission success for the ISS crewmembers pre-, in- and post-flight. To that end, in January 2001 the first Family Services Coordinator was hired by the Behavioral Health and Performance group at NASA JSC and matrixed from Medical Operations into the Astronaut Office's organization. The initial roles and responsibilities were driven by critical needs, including facilitating family communication during training deployments, providing mission-specific and other relevant trainings for spouses, serving as liaison for families with NASA organizations such as Medical Operations, NASA management and the Astronaut Office, and providing assistance to ensure success of an Astronaut Spouses Group. The role of the Family Support Office (FSO) has modified as the ISS Program matured and the needs of families changed. The FSO is currently an integral part of the Astronaut Office's ISS Operations Branch. It still serves the critical function of providing information to families, as well as being the primary contact for US and international partner families with resources at JSC. Since crews launch and return on Russian vehicles, the FSO has the added responsibility for coordinating with Flight Crew Operations, the families, and their guests for Soyuz launches, landings, and Direct Return to Houston post-flight. This presentation will provide a summary of the family support services provided for astronauts, and how they have changed with the Program and families the FSO serves. Considerations for future FSO services will be discussed briefly as NASA proposes one year missions and beyond ISS missions. Learning Objective: 1) Obtain an understanding of the reasons a Family Support Office was important for NASA. 2) Become familiar with the services provided for

Expression, purification and crystallization of a lyssavirus matrix (M) protein

Energy Technology Data Exchange (ETDEWEB)

Assenberg, René [Division of Structural Biology and Oxford Protein Production Facility, The Henry Wellcome Building for Genomic Medicine, Oxford University, Roosevelt Drive, Oxford OX3 7BN (United Kingdom); Delmas, Olivier [UPRE Lyssavirus Dynamics and Host Adaptation, WHO Collaborating Centre for Reference and Research on Rabies, Institut Pasteur, 28 Rue du Docteur Roux, 75724 Paris CEDEX 15 (France); Graham, Stephen C.; Verma, Anil; Berrow, Nick; Stuart, David I.; Owens, Raymond J. [Division of Structural Biology and Oxford Protein Production Facility, The Henry Wellcome Building for Genomic Medicine, Oxford University, Roosevelt Drive, Oxford OX3 7BN (United Kingdom); Bourhy, Hervé [UPRE Lyssavirus Dynamics and Host Adaptation, WHO Collaborating Centre for Reference and Research on Rabies, Institut Pasteur, 28 Rue du Docteur Roux, 75724 Paris CEDEX 15 (France); Grimes, Jonathan M., E-mail: jonathan@strubi.ox.ac.uk [Division of Structural Biology and Oxford Protein Production Facility, The Henry Wellcome Building for Genomic Medicine, Oxford University, Roosevelt Drive, Oxford OX3 7BN (United Kingdom)

2008-04-01

The expression, purification and crystallization of the full-length matrix protein from three lyssaviruses is described. The matrix (M) proteins of lyssaviruses (family Rhabdoviridae) are crucial to viral morphogenesis as well as in modulating replication and transcription of the viral genome. To date, no high-resolution structural information has been obtained for full-length rhabdovirus M. Here, the cloning, expression and purification of the matrix proteins from three lyssaviruses, Lagos bat virus (LAG), Mokola virus and Thailand dog virus, are described. Crystals have been obtained for the full-length M protein from Lagos bat virus (LAG M). Successful crystallization depended on a number of factors, in particular the addition of an N-terminal SUMO fusion tag to increase protein solubility. Diffraction data have been recorded from crystals of native and selenomethionine-labelled LAG M to 2.75 and 3.0 Å resolution, respectively. Preliminary analysis indicates that these crystals belong to space group P6{sub 1}22 or P6{sub 5}22, with unit-cell parameters a = b = 56.9–57.2, c = 187.9–188.6 Å, consistent with the presence of one molecule per asymmetric unit, and structure determination is currently in progress.

Expression, purification and crystallization of a lyssavirus matrix (M) protein

International Nuclear Information System (INIS)

Assenberg, René; Delmas, Olivier; Graham, Stephen C.; Verma, Anil; Berrow, Nick; Stuart, David I.; Owens, Raymond J.; Bourhy, Hervé; Grimes, Jonathan M.

2008-01-01

The expression, purification and crystallization of the full-length matrix protein from three lyssaviruses is described. The matrix (M) proteins of lyssaviruses (family Rhabdoviridae) are crucial to viral morphogenesis as well as in modulating replication and transcription of the viral genome. To date, no high-resolution structural information has been obtained for full-length rhabdovirus M. Here, the cloning, expression and purification of the matrix proteins from three lyssaviruses, Lagos bat virus (LAG), Mokola virus and Thailand dog virus, are described. Crystals have been obtained for the full-length M protein from Lagos bat virus (LAG M). Successful crystallization depended on a number of factors, in particular the addition of an N-terminal SUMO fusion tag to increase protein solubility. Diffraction data have been recorded from crystals of native and selenomethionine-labelled LAG M to 2.75 and 3.0 Å resolution, respectively. Preliminary analysis indicates that these crystals belong to space group P6 1 22 or P6 5 22, with unit-cell parameters a = b = 56.9–57.2, c = 187.9–188.6 Å, consistent with the presence of one molecule per asymmetric unit, and structure determination is currently in progress

Tau anomaly and vectorlike families

International Nuclear Information System (INIS)

Babu, K.S.; Pati, J.C.; Zhang, X.

1992-01-01

The implications of a recently indicated increase in τ lifetime are discussed. It is stressed that the available experimental constraints (from δρ,ε 3 , and N ν , etc.) are satisfied most naturally if the indicated τ anomaly is attributed to the mixing of the τ family with a heavy vectorlike family Q L, R ' with masses ∼200 GeV to 2 TeV, which is a doublet of SU(2) R and singlet of SU(2) L , rather than with a heavy fourth family with standard chiral couplings. L↔R symmetry would imply that Q L, R ' is accompanied by the parity-conjugate family Q L, R which is a doublet of SU(2) L and singlet of SU(2) R . Two such vectorlike families, together with an increase in τ τ , are, in fact, crucial predictions of a recently proposed supersymmetric composite model that possesses many attractive features, in particular, explanations of the origin of diverse scales and family replication. In the context of such a model, it is noted that 3 an increase in τ τ due to mixing involving vectorlike families will necessarily imply a correlated decrease in neutrino counting N ν from the CERN e + e- collider LEP from 3. Such a decrease in N ν would be absent, however, if the τ anomaly is attributed to a mixing involving a standard fourth family with chiral couplings. Because of the seesaw nature of the mass matrix of the three chiral and two vectorlike families, that arises naturally in the model, departures from universality in the first two families as well as in bar bb and τ + τ - channels (linked to down flavors) are strongly suppressed, in accord with observations

*K-means and Cluster Models for Cancer Signatures

OpenAIRE

Kakushadze, Zura; Yu, Willie

2017-01-01

We present *K-means clustering algorithm and source code by expanding statistical clustering methods applied in https://ssrn.com/abstract=2802753 to quantitative finance. *K-means is statistically deterministic without specifying initial centers, etc. We apply *K-means to extracting cancer signatures from genome data without using nonnegative matrix factorization (NMF). *K-means’ computational cost is a fraction of NMF’s. Using 1389 published samples for 14 cancer types, we find that 3 cancer...

Matrix theory

CERN Document Server

Franklin, Joel N

2003-01-01

Mathematically rigorous introduction covers vector and matrix norms, the condition-number of a matrix, positive and irreducible matrices, much more. Only elementary algebra and calculus required. Includes problem-solving exercises. 1968 edition.

Bargmann Symmetry Constraint for a Family of Liouville Integrable Differential-Difference Equations

International Nuclear Information System (INIS)

Xu Xixiang

2012-01-01

A family of integrable differential-difference equations is derived from a new matrix spectral problem. The Hamiltonian forms of obtained differential-difference equations are constructed. The Liouville integrability for the obtained integrable family is proved. Then, Bargmann symmetry constraint of the obtained integrable family is presented by binary nonliearization method of Lax pairs and adjoint Lax pairs. Under this Bargmann symmetry constraints, an integrable symplectic map and a sequences of completely integrable finite-dimensional Hamiltonian systems in Liouville sense are worked out, and every integrable differential-difference equations in the obtained family is factored by the integrable symplectic map and a completely integrable finite-dimensional Hamiltonian system. (general)

Fuzzy vulnerability matrix

International Nuclear Information System (INIS)

Baron, Jorge H.; Rivera, S.S.

2000-01-01

The so-called vulnerability matrix is used in the evaluation part of the probabilistic safety assessment for a nuclear power plant, during the containment event trees calculations. This matrix is established from what is knows as Numerical Categories for Engineering Judgement. This matrix is usually established with numerical values obtained with traditional arithmetic using the set theory. The representation of this matrix with fuzzy numbers is much more adequate, due to the fact that the Numerical Categories for Engineering Judgement are better represented with linguistic variables, such as 'highly probable', 'probable', 'impossible', etc. In the present paper a methodology to obtain a Fuzzy Vulnerability Matrix is presented, starting from the recommendations on the Numerical Categories for Engineering Judgement. (author)

Green's matrix for a second-order self-adjoint matrix differential operator

International Nuclear Information System (INIS)

Sisman, Tahsin Cagri; Tekin, Bayram

2010-01-01

A systematic construction of the Green's matrix for a second-order self-adjoint matrix differential operator from the linearly independent solutions of the corresponding homogeneous differential equation set is carried out. We follow the general approach of extracting the Green's matrix from the Green's matrix of the corresponding first-order system. This construction is required in the cases where the differential equation set cannot be turned to an algebraic equation set via transform techniques.

Binding of matrix metalloproteinase inhibitors to extracellular matrix: 3D-QSAR analysis.

Science.gov (United States)

Zhang, Yufen; Lukacova, Viera; Bartus, Vladimir; Nie, Xiaoping; Sun, Guorong; Manivannan, Ethirajan; Ghorpade, Sandeep R; Jin, Xiaomin; Manyem, Shankar; Sibi, Mukund P; Cook, Gregory R; Balaz, Stefan

2008-10-01

Binding to the extracellular matrix, one of the most abundant human protein complexes, significantly affects drug disposition. Specifically, the interactions with extracellular matrix determine the free concentrations of small molecules acting in tissues, including signaling peptides, inhibitors of tissue remodeling enzymes such as matrix metalloproteinases, and other drug candidates. The nature of extracellular matrix binding was elucidated for 63 matrix metalloproteinase inhibitors, for which the association constants to an extracellular matrix mimic were reported here. The data did not correlate with lipophilicity as a common determinant of structure-nonspecific, orientation-averaged binding. A hypothetical structure of the binding site of the solidified extracellular matrix surrogate was analyzed using the Comparative Molecular Field Analysis, which needed to be applied in our multi-mode variant. This fact indicates that the compounds bind to extracellular matrix in multiple modes, which cannot be considered as completely orientation-averaged and exhibit structural dependence. The novel comparative molecular field analysis models, exhibiting satisfactory descriptive and predictive abilities, are suitable for prediction of the extracellular matrix binding for the untested chemicals, which are within applicability domains. The results contribute to a better prediction of the pharmacokinetic parameters such as the distribution volume and the tissue-blood partition coefficients, in addition to a more imminent benefit for the development of more effective matrix metalloproteinase inhibitors.

Collagen cross-linking: insights on the evolution of metazoan extracellular matrix.

Science.gov (United States)

Rodriguez-Pascual, Fernando; Slatter, David Anthony

2016-11-23

Collagens constitute a large family of extracellular matrix (ECM) proteins that play a fundamental role in supporting the structure of various tissues in multicellular animals. The mechanical strength of fibrillar collagens is highly dependent on the formation of covalent cross-links between individual fibrils, a process initiated by the enzymatic action of members of the lysyl oxidase (LOX) family. Fibrillar collagens are present in a wide variety of animals, therefore often being associated with metazoan evolution, where the emergence of an ancestral collagen chain has been proposed to lead to the formation of different clades. While LOX-generated collagen cross-linking metabolites have been detected in different metazoan families, there is limited information about when and how collagen acquired this particular modification. By analyzing telopeptide and helical sequences, we identified highly conserved, potential cross-linking sites throughout the metazoan tree of life. Based on this analysis, we propose that they have importantly contributed to the formation and further expansion of fibrillar collagens.

Alternativas metodológicas para la estratificación de familias según situación de salud familiar Methodological alternatives for the stratification of families according to family health situation

Directory of Open Access Journals (Sweden)

Isabel Louro Bernal

2008-12-01

situation is an important aspect of comprehensive health care at the primary level. The stratification of the families according to the health family situation is useful for planning community interventions. METHODS: 294 families from the selected municipalities of the country were studied in 2004. They were stratified according to the family health situation by using the family health matrix and the non-hierarchical analysis of conglomerates. The foundation of the matrix is the theoretical-methodological model to evaluate the health of the family group that includes the family functioning perception test and the inventory of risk family characteristics. Both results were considered and each family was located in the matrix representing gradients of affectation of the family health situation. With the data resulting from the application of the above mentioned instruments, the non-hierarchical analysis of conglomerates was used to stratify the families. The concordance bwtween both techniques was determined by Kappa's index. RESULTS: 51 % of the families classified in the zone of family adjustment, 14.3 % in the zone of elevated sociofamiliar criticity and good intrafamily functioning, 28.6 % presented dysfunctional intrafamily relations with low sociofamiliar criticity and 6.1 % had affectation of extreme severity with high sociofamiliar criticity and dysfunctionality. CONCLUSIONS: there was an elevated concordance between the methods used to stratify the families. The family health matrix and the application of the analysis by conglomerates are useful procedures for stratifying the families according to the family health situation for research and for the family categorization in a territory.

Matrix calculus

CERN Document Server

Bodewig, E

1959-01-01

Matrix Calculus, Second Revised and Enlarged Edition focuses on systematic calculation with the building blocks of a matrix and rows and columns, shunning the use of individual elements. The publication first offers information on vectors, matrices, further applications, measures of the magnitude of a matrix, and forms. The text then examines eigenvalues and exact solutions, including the characteristic equation, eigenrows, extremum properties of the eigenvalues, bounds for the eigenvalues, elementary divisors, and bounds for the determinant. The text ponders on approximate solutions, as well

Neutrino mass matrix

International Nuclear Information System (INIS)

Strobel, E.L.

1985-01-01

Given the many conflicting experimental results, examination is made of the neutrino mass matrix in order to determine possible masses and mixings. It is assumed that the Dirac mass matrix for the electron, muon, and tau neutrinos is similar in form to those of the quarks and charged leptons, and that the smallness of the observed neutrino masses results from the Gell-Mann-Ramond-Slansky mechanism. Analysis of masses and mixings for the neutrinos is performed using general structures for the Majorana mass matrix. It is shown that if certain tentative experimental results concerning the neutrino masses and mixing angles are confirmed, significant limitations may be placed on the Majorana mass matrix. The most satisfactory simple assumption concerning the Majorana mass matrix is that it is approximately proportional to the Dirac mass matrix. A very recent experimental neutrino mass result and its implications are discussed. Some general properties of matrices with structure similar to the Dirac mass matrices are discussed

Mothers in "incest families": a critique of blame and its destructive sequels.

Science.gov (United States)

Green, J

1996-09-01

This paper critically reviewed the blame-oriented explanations of mothers' roles in father-daughter incest, which was contrasted with feminist reassessments in a sociopolitical context. The concept of the dysfunctional family forms the matrix in which views of blaming the mother take life. The mother is characterized as the ¿cornerstone¿ of the family dynamics that create and maintain the incestuous behavior of the spouse. Several categories of maternal behavior were reported to set up conditions in the family for father-daughter incest, including the contention that the mother colludes in the abuse either by unconscious passivity or by active conscious involvement in arranging the act. In addition, the mother's alleged inadequacies in the areas of intimacy and sexuality are often viewed as central factors in the dynamics of father-daughter incest. Identified as additional victims in the complex matrix of family and community, mothers are revictimized by the clinical establishment that upholds the unconscious patriarchal ideology underlying violence against women. Clinicians need to validate and support mothers in their ¿disenfranchised grief¿ so they can help their daughters to heal, and to design and lobby for programs that will promote social changes that are necessary for a more egalitarian society.

Stromal-dependent tumor promotion by MIF family members.

Science.gov (United States)

Mitchell, Robert A; Yaddanapudi, Kavitha

2014-12-01

Solid tumors are composed of a heterogeneous population of cells that interact with each other and with soluble and insoluble factors that, when combined, strongly influence the relative proliferation, differentiation, motility, matrix remodeling, metabolism and microvessel density of malignant lesions. One family of soluble factors that is becoming increasingly associated with pro-tumoral phenotypes within tumor microenvironments is that of the migration inhibitory factor family which includes its namesake, MIF, and its only known family member, D-dopachrome tautomerase (D-DT). This review seeks to highlight our current understanding of the relative contributions of a variety of immune and non-immune tumor stromal cell populations and, within those contexts, will summarize the literature associated with MIF and/or D-DT. Copyright © 2014 Elsevier Inc. All rights reserved.

Advanced Takagi‒Sugeno fuzzy systems delay and saturation

CERN Document Server

Benzaouia, Abdellah

2014-01-01

This monograph puts the reader in touch with a decade’s worth of new developments in the field of fuzzy control specifically those of the popular Takagi-Sugeno (T-S) type. New techniques for stabilizing control analysis and design based on multiple Lyapunov functions and linear matrix inequalities (LMIs), are proposed. All the results are illustrated with numerical examples and figures and a rich bibliography is provided for further investigation. Control saturations are taken into account within the fuzzy model. The concept of positive invariance is used to obtain sufficient asymptotic stability conditions for the fuzzy system with constrained control inside a subset of the state space. The authors also consider the non-negativity of the states. This is of practical importance in many chemical, physical and biological processes that involve quantities that have intrinsically constant and non-negative sign: concentration of substances, level of liquids, etc. Results for linear systems are then extended to l...

Helicobacter pylori and gastritis: the role of extracellular matrix metalloproteases, their inhibitors, and the disintegrins and metalloproteases--a systematic literature review.

Science.gov (United States)

Sampieri, Clara L

2013-10-01

Helicobacter pylori (H. pylori) is the etiologic agent of gastritis; it has been estimated that 50 % of the world's population could be infected by this bacteria. Gastritis may progress to chronic atrophic gastritis, a condition associated with the development of gastric cancer (GC). Several matrix metalloproteases (MMP) and tissue inhibitors of MMPs (TIMP) as well as disintegrins and metalloproteases (ADAM) have been reported as being involved in gastritis. Among other processes, these protein families participate in remodeling the extracellular matrix, cell signaling, immune response, angiogenesis, inflammation and epithelial mesenchymal transition. This systematic review analyzes the scientific evidence surrounding the relationship between members of the MMP, TIMP and ADAM families and infection by H. pylori in gastritis, considering both in vitro and in vivo studies. Given the potential clinical value of certain members of the MMP, TIMP and ADAM families as molecular markers in gastritis and the association of gastritis with GC, the need for further study is highlighted.

Fuzzy risk matrix

International Nuclear Information System (INIS)

Markowski, Adam S.; Mannan, M. Sam

2008-01-01

A risk matrix is a mechanism to characterize and rank process risks that are typically identified through one or more multifunctional reviews (e.g., process hazard analysis, audits, or incident investigation). This paper describes a procedure for developing a fuzzy risk matrix that may be used for emerging fuzzy logic applications in different safety analyses (e.g., LOPA). The fuzzification of frequency and severity of the consequences of the incident scenario are described which are basic inputs for fuzzy risk matrix. Subsequently using different design of risk matrix, fuzzy rules are established enabling the development of fuzzy risk matrices. Three types of fuzzy risk matrix have been developed (low-cost, standard, and high-cost), and using a distillation column case study, the effect of the design on final defuzzified risk index is demonstrated

Human 2'-phosphodiesterase localizes to the mitochondrial matrix with a putative function in mitochondrial RNA turnover

DEFF Research Database (Denmark)

Poulsen, Jesper Buchhave; Andersen, Kasper Røjkjær; Kjær, Karina Hansen

2011-01-01

. Interestingly, 2′-PDE shares both functionally and structurally characteristics with the CCR4-type exonuclease–endonuclease–phosphatase family of deadenylases. Here we show that 2′-PDE locates to the mitochondrial matrix of human cells, and comprise an active 3′–5′ exoribonuclease exhibiting a preference...

ON-LINE NONLINEAR CHROMATICITY CORRECTION USING OFF-MOMENTUM TUNE RESPONSE MATRIX

International Nuclear Information System (INIS)

LUO, Y.; FISCHER, W.; MALISKY, N.; TEPIKIAN, S.; TROBJEVIC, D.

2007-01-01

In this article, we propose a method for the online nonlinear chromaticity correction at store in the Relativistic Heavy Ion Collider (RHIC). With 8 arc sextupole families in each RHIC ring, the nonlinear chromaticities can be minimized online by matching the off-momentum tunes onto the wanted tunes given by the linear chromaticities. The Newton method is used for this multi-dimensional nonlinear optimization, where the off-momentum tune response matrix with respect to sextupole strength changes is adopted. The off-momentum tune response matrix can be calculated with the online accelerator optics model or directly measured with the real beam. In this article, the correction algorithm for the RHIC is presented. Simulations are also carried out to verify the method. The preliminary results from the beam experiments taken place in the RHIC 2007 Au run are reviewed

The European Portuguese WHOQOL-OLD module and the new facet Family/Family life: reliability and validity studies.

Science.gov (United States)

Vilar, Manuela; Sousa, Liliana B; Simões, Mário R

2016-09-01

The aim of this study was to examine the psychometric properties of the European Portuguese version of the World Health Organization Quality of Life-Older Adults Module (WHOQOL-OLD). The European Portuguese WHOQOL-OLD includes a new identified facet, Family/Family life. A convenience sample of older adults was recruited (N = 921). The assessment protocol included demographics, self-perceived health, depressive symptoms (GDS-30), cognitive function (ACE-R), daily life activities (IAFAI), health status (SF-12) and QoL (WHOQOL-Bref, EUROHIS-QOL-8 and WHOQOL-OLD). The internal consistency was excellent for the total 24-item WHOQOL-OLD original version and also for the final 28-item European Portuguese WHOQOL-OLD version. The test-retest reliability for total scores was good. The construct validity of the European Portuguese WHOQOL-OLD was supported in the correlation matrix analysis. The results indicated good convergent/divergent validity. The WHOQOL-OLD scores differentiated groups of older adults who were healthy/unhealthy and without/mild/severe depressive symptoms. The new facet, Family/Family life, presented evidence of good reliability and validity parameters. Comparatively to international studies, the European Portuguese WHOQOL-OLD version showed similar and/or better psychometric properties. The new facet, Family/Family life, introduces cross-cultural specificity to the study of QoL of older adults and generally improves the psychometric robustness of the WHOQOL-OLD.

Molecular dynamics simulations of matrix assisted laser desorption ionization: Matrix-analyte interactions

International Nuclear Information System (INIS)

Nangia, Shivangi; Garrison, Barbara J.

2011-01-01

There is synergy between matrix assisted laser desorption ionization (MALDI) experiments and molecular dynamics (MD) simulations. To understand analyte ejection from the matrix, MD simulations have been employed. Prior calculations show that the ejected analyte molecules remain solvated by the matrix molecules in the ablated plume. In contrast, the experimental data show free analyte ions. The main idea of this work is that analyte molecule ejection may depend on the microscopic details of analyte interaction with the matrix. Intermolecular matrix-analyte interactions have been studied by focusing on 2,5-dihydroxybenzoic acid (DHB; matrix) and amino acids (AA; analyte) using Chemistry at HARvard Molecular Mechanics (CHARMM) force field. A series of AA molecules have been studied to analyze the DHB-AA interaction. A relative scale of AA molecule affinity towards DHB has been developed.

Musical Instrument Classification Based on Nonlinear Recurrence Analysis and Supervised Learning

Directory of Open Access Journals (Sweden)

R.Rui

2013-04-01

Full Text Available In this paper, the phase space reconstruction of time series produced by different instruments is discussed based on the nonlinear dynamic theory. The dense ratio, a novel quantitative recurrence parameter, is proposed to describe the difference of wind instruments, stringed instruments and keyboard instruments in the phase space by analyzing the recursive property of every instrument. Furthermore, a novel supervised learning algorithm for automatic classification of individual musical instrument signals is addressed deriving from the idea of supervised non-negative matrix factorization (NMF algorithm. In our approach, the orthogonal basis matrix could be obtained without updating the matrix iteratively, which NMF is unable to do. The experimental results indicate that the accuracy of the proposed method is improved by 3% comparing with the conventional features in the individual instrument classification.

Massively parallel red-black algorithms for x-y-z response matrix equations

International Nuclear Information System (INIS)

Hanebutte, U.R.; Laurin-Kovitz, K.; Lewis, E.E.

1992-01-01

Recently, both discrete ordinates and spherical harmonic (S n and P n ) methods have been cast in the form of response matrices. In x-y geometry, massively parallel algorithms have been developed to solve the resulting response matrix equations on the Connection Machine family of parallel computers, the CM-2, CM-200, and CM-5. These algorithms utilize two-cycle iteration on a red-black checkerboard. In this work we examine the use of massively parallel red-black algorithms to solve response matric equations in three dimensions. This longer term objective is to utilize massively parallel algorithms to solve S n and/or P n response matrix problems. In this exploratory examination, however, we consider the simple 6 x 6 response matrices that are derivable from fine-mesh diffusion approximations in three dimensions

Thermal and mechanical behavior of metal matrix and ceramic matrix composites

Science.gov (United States)

Kennedy, John M. (Editor); Moeller, Helen H. (Editor); Johnson, W. S. (Editor)

1990-01-01

The present conference discusses local stresses in metal-matrix composites (MMCs) subjected to thermal and mechanical loads, the computational simulation of high-temperature MMCs' cyclic behavior, an analysis of a ceramic-matrix composite (CMC) flexure specimen, and a plasticity analysis of fibrous composite laminates under thermomechanical loads. Also discussed are a comparison of methods for determining the fiber-matrix interface frictional stresses of CMCs, the monotonic and cyclic behavior of an SiC/calcium aluminosilicate CMC, the mechanical and thermal properties of an SiC particle-reinforced Al alloy MMC, the temperature-dependent tensile and shear response of a graphite-reinforced 6061 Al-alloy MMC, the fiber/matrix interface bonding strength of MMCs, and fatigue crack growth in an Al2O3 short fiber-reinforced Al-2Mg matrix MMC.

Sons and daughters' perception of parents as a couple: distinguishing characteristics of a measurement model

OpenAIRE

Ziviani,Cilio; Féres-Carneiro,Terezinha; Magalhães,Andrea Seixas

2011-01-01

Perceptions and memories that youths may have of their parents' marital relationship were addressed by a self-report questionnaire, composed by 26 Likert scale items which were taken to constitute the "Perception of Parents as a Couple" instrument. Answers from 1,612 male and female youths produced a matrix of non-negative correlations. The sample was randomly split into calibrating and validating subsamples of 806 people each. Exploratory factor and principal component analyses present a cir...

Error analysis of Newmark's method for the second order equation with inhomogeneous term

International Nuclear Information System (INIS)

Chiba, F.; Kako, T.

2000-01-01

For the second order time evolution equation with a general dissipation term, we introduce a recurrence relation of Newmark's method. Deriving an energy inequality from this relation, we consider the stability and the convergence criteria of Newmark's method. We treat a dissipation term under the assumption that the coefficient-damping matrix is constant in time and non-negative. We can relax however the assumptions for the dissipation and the rigidity matrices to be arbitrary symmetric matrices. (author)

Study of ionization process of matrix molecules in matrix-assisted laser desorption ionization

Energy Technology Data Exchange (ETDEWEB)

Murakami, Kazumasa; Sato, Asami; Hashimoto, Kenro; Fujino, Tatsuya, E-mail: fujino@tmu.ac.jp

2013-06-20

Highlights: ► Proton transfer and adduction reaction of matrix in MALDI were studied. ► Hydroxyl group forming intramolecular hydrogen bond was related to the ionization. ► Intramolecular proton transfer in the electronic excited state was the initial step. ► Non-volatile analytes stabilized protonated matrix in the ground state. ► A possible mechanism, “analyte support mechanism”, has been proposed. - Abstract: Proton transfer and adduction reaction of matrix molecules in matrix-assisted laser desorption ionization were studied. By using 2,4,6-trihydroxyacetophenone (THAP), 2,5-dihydroxybenzoic acid (DHBA), and their related compounds in which the position of a hydroxyl group is different, it was clarified that a hydroxyl group forming an intramolecular hydrogen bond is related to the ionization of matrix molecules. Intramolecular proton transfer in the electronic excited state of the matrix and subsequent proton adduction from a surrounding solvent to the charge-separated matrix are the initial steps for the ionization of matrix molecules. Nanosecond pump–probe NIR–UV mass spectrometry confirmed that the existence of analyte molecules having large dipole moment in their structures is necessary for the stabilization of [matrix + H]{sup +} in the electronic ground state.

Studies on the optimization of deformation processed metal metal matrix composites

Energy Technology Data Exchange (ETDEWEB)

Ellis, Tim W. [Iowa State Univ., Ames, IA (United States)

1994-01-04

A methodology for the production of deformation processed metal metal matrix composites from hyper-eutectic copper-chromium alloys was developed. This methodology was derived from a basic study of the precipitation phenomena in these alloys encompassing evaluation of microstructural, electrical, and mechanical properties. The methodology developed produces material with a superior combination of electrical and mechanical properties compared to those presently available in commercial alloys. New and novel alloying procedures were investigated to extend the range of production methods available for these material. These studies focused on the use of High Pressure Gas Atomization and the development of new containment technologies for the liquid alloy. This allowed the production of alloys with a much more refined starting microstructure and lower contamination than available by other methods. The knowledge gained in the previous studies was used to develop two completely new families of deformation processed metal metal matrix composites. These composites are based on immissible alloys with yttrium and magnesium matrices and refractory metal reinforcement. This work extends the physical property range available in deformation processed metal metal matrix composites. Additionally, it also represents new ways to apply these metals in engineering applications.

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

Science.gov (United States)

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.

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

Energy Technology Data Exchange (ETDEWEB)

Hoy, Erik P.; Mazziotti, David A., E-mail: damazz@uchicago.edu [Department of Chemistry and The James Franck Institute, The University of Chicago, Chicago, Illinois 60637 (United States)

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.

Communication: satisfying fermionic statistics in the modeling of open time-dependent quantum systems with one-electron reduced density matrices.

Science.gov (United States)

Head-Marsden, Kade; Mazziotti, David A

2015-02-07

For an open, time-dependent quantum system, Lindblad derived the most general modification of the quantum Liouville equation in the Markovian approximation that models environmental effects while preserving the non-negativity of the system's density matrix. While Lindblad's modification is correct for N-electron density matrices, solution of the Liouville equation with a Lindblad operator causes the one-electron reduced density matrix (1-RDM) to violate the Pauli exclusion principle. Consequently, after a short time, the 1-RDM is not representable by an ensemble N-electron density matrix (not ensemble N-representable). In this communication, we derive the necessary and sufficient constraints on the Lindbladian matrix within the Lindblad operator to ensure that the 1-RDM remains N-representable for all time. The theory is illustrated by considering the relaxation of an excitation in several molecules F2, N2, CO, and BeH2 subject to environmental noise.

Matrix Metalloproteinase Inhibitors (MMPIs from Marine Natural Products: the Current Situation and Future Prospects

Directory of Open Access Journals (Sweden)

Se-Kwon Kim

2009-03-01

Full Text Available Matrix metalloproteinases (MMPs are a family of more than twenty five secreted and membrane-bound zinc-endopeptidases which can degrade extracellular matrix (ECM components. They also play important roles in a variety of biological and pathological processes. Matrix metalloproteinase inhibitors (MMPIs have been identified as potential therapeutic candidates for metastasis, arthritis, chronic inflammation and wrinkle formation. Up to present, more than 20,000 new compounds have been isolated from marine organisms, where considerable numbers of these naturally occurring derivatives are developed as potential candidates for pharmaceutical application. Eventhough the quantity of marine derived MMPIs is less when compare with the MMPIs derived from terrestrial materials, huge potential for bioactivity of these marine derived MMPIs has lead to large number of researches. Saccharoids, flavonoids and polyphones, fatty acids are the most important groups of MMPIs derived from marine natural products. In this review we focus on the progress of MMPIs from marine natural products.

Multi-threaded Sparse Matrix-Matrix Multiplication for Many-Core and GPU Architectures.

Energy Technology Data Exchange (ETDEWEB)

Deveci, Mehmet [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Rajamanickam, Sivasankaran [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Trott, Christian Robert [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-12-01

Sparse Matrix-Matrix multiplication is a key kernel that has applications in several domains such as scienti c computing and graph analysis. Several algorithms have been studied in the past for this foundational kernel. In this paper, we develop parallel algorithms for sparse matrix-matrix multiplication with a focus on performance portability across different high performance computing architectures. The performance of these algorithms depend on the data structures used in them. We compare different types of accumulators in these algorithms and demonstrate the performance difference between these data structures. Furthermore, we develop a meta-algorithm, kkSpGEMM, to choose the right algorithm and data structure based on the characteristics of the problem. We show performance comparisons on three architectures and demonstrate the need for the community to develop two phase sparse matrix-matrix multiplication implementations for efficient reuse of the data structures involved.

The nuclear reaction matrix

International Nuclear Information System (INIS)

Krenciglowa, E.M.; Kung, C.L.; Kuo, T.T.S.; Osnes, E.; and Department of Physics, State University of New York at Stony Brook, Stony Brook, New York 11794)

1976-01-01

Different definitions of the reaction matrix G appropriate to the calculation of nuclear structure are reviewed and discussed. Qualitative physical arguments are presented in support of a two-step calculation of the G-matrix for finite nuclei. In the first step the high-energy excitations are included using orthogonalized plane-wave intermediate states, and in the second step the low-energy excitations are added in, using harmonic oscillator intermediate states. Accurate calculations of G-matrix elements for nuclear structure calculations in the Aapprox. =18 region are performed following this procedure and treating the Pauli exclusion operator Q 2 /sub p/ by the method of Tsai and Kuo. The treatment of Q 2 /sub p/, the effect of the intermediate-state spectrum and the energy dependence of the reaction matrix are investigated in detail. The present matrix elements are compared with various matrix elements given in the literature. In particular, close agreement is obtained with the matrix elements calculated by Kuo and Brown using approximate methods

Matrix metalloproteinases outside vertebrates.

Science.gov (United States)

Marino-Puertas, Laura; Goulas, Theodoros; Gomis-Rüth, F Xavier

2017-11-01

The matrix metalloproteinase (MMP) family belongs to the metzincin clan of zinc-dependent metallopeptidases. Due to their enormous implications in physiology and disease, MMPs have mainly been studied in vertebrates. They are engaged in extracellular protein processing and degradation, and present extensive paralogy, with 23 forms in humans. One characteristic of MMPs is a ~165-residue catalytic domain (CD), which has been structurally studied for 14 MMPs from human, mouse, rat, pig and the oral-microbiome bacterium Tannerella forsythia. These studies revealed close overall coincidence and characteristic structural features, which distinguish MMPs from other metzincins and give rise to a sequence pattern for their identification. Here, we reviewed the literature available on MMPs outside vertebrates and performed database searches for potential MMP CDs in invertebrates, plants, fungi, viruses, protists, archaea and bacteria. These and previous results revealed that MMPs are widely present in several copies in Eumetazoa and higher plants (Tracheophyta), but have just token presence in eukaryotic algae. A few dozen sequences were found in Ascomycota (within fungi) and in double-stranded DNA viruses infecting invertebrates (within viruses). In contrast, a few hundred sequences were found in archaea and >1000 in bacteria, with several copies for some species. Most of the archaeal and bacterial phyla containing potential MMPs are present in human oral and gut microbiomes. Overall, MMP-like sequences are present across all kingdoms of life, but their asymmetric distribution contradicts the vertical descent model from a eubacterial or archaeal ancestor. This article is part of a Special Issue entitled: Matrix Metalloproteinases edited by Rafael Fridman. Copyright © 2017 Elsevier B.V. All rights reserved.

Consequences of an Abelian family symmetry

International Nuclear Information System (INIS)

Ramond, P.

1996-01-01

The addition of an Abelian family symmetry to the Minimal Super-symmetric Standard Model reproduces the observed hierarchies of quark and lepton masses and quark mixing angles, only if it is anomalous. Green-Schwarz compensation of its anomalies requires the electroweak mixing angle to be sin 2 θ ω = 3/8 at the string scale, without any assumed GUT structure, suggesting a superstring origin for the standard model. The analysis is extended to neutrino masses and the lepton mixing matrix

Global unitary fixing and matrix-valued correlations in matrix models

International Nuclear Information System (INIS)

Adler, Stephen L.; Horwitz, Lawrence P.

2003-01-01

We consider the partition function for a matrix model with a global unitary invariant energy function. We show that the averages over the partition function of global unitary invariant trace polynomials of the matrix variables are the same when calculated with any choice of a global unitary fixing, while averages of such polynomials without a trace define matrix-valued correlation functions, that depend on the choice of unitary fixing. The unitary fixing is formulated within the standard Faddeev-Popov framework, in which the squared Vandermonde determinant emerges as a factor of the complete Faddeev-Popov determinant. We give the ghost representation for the FP determinant, and the corresponding BRST invariance of the unitary-fixed partition function. The formalism is relevant for deriving Ward identities obeyed by matrix-valued correlation functions

Abnormal secretion or extracellular matrix incorporation of fibrillin by dermal fibroblasts from patients with thoracic aortic aneurysms

Energy Technology Data Exchange (ETDEWEB)

Milewicz, D.; Cao, S.; Cosselli, J. [Univ. of Texas Medical School, Houston, TX (United States)

1994-09-01

Abnormal synthesis, secretion, and extracellular matrix incorporation of fibrillin is observed in the majority of fibroblast cell strains obtained from individuals with the Marfan syndrome (>85%). These fibrillin protein abnormalities are due to mutations in the FBN1 gene. We have screened fibroblast cell strains from patients with thoracic aortic aneurysms (TAA) without skeletal or ocular features of the Marfan syndrome for defects in fibrillin synthesis or processing. Dermal fibroblasts obtained from biopsies were pulse labeled with [{sup 35}S]cysteine for 30 minutes and then chased for 0, 4, and 20 hours. The media, cell lysate and extracellular matrix were harvested separately, then analyzed by SDS-PAGE. We selected fibroblasts from 17 TAA patients to study based on the development of a TAA at a young age or a family history of TAAs. Cells from 3 patients synthesized and secreted fibrillin normally, but did not incorporate the fibrillin in the extracellular matrix. None of the cell strains were found to have diminished synthesis of fibrillin when compared with control cells. We were unable to detect abnormalities in the synthesis, secretion, or matrix incorporation of fibrillin by cells from 9 of the 17 patients. These results indicate that fibrillin protein defects are found in a significant number of patients with TAAs who are young or have a family history of TAAs. Analysis of the FBN1 gene for mutations in these patients with fibrillin protein defects will determine if the observed protein abnormalities are the result of FBN1 gene mutations.

Matrix Information Geometry

CERN Document Server

Bhatia, Rajendra

2013-01-01

This book is an outcome of the Indo-French Workshop on Matrix Information Geometries (MIG): Applications in Sensor and Cognitive Systems Engineering, which was held in Ecole Polytechnique and Thales Research and Technology Center, Palaiseau, France, in February 23-25, 2011. The workshop was generously funded by the Indo-French Centre for the Promotion of Advanced Research (IFCPAR).  During the event, 22 renowned invited french or indian speakers gave lectures on their areas of expertise within the field of matrix analysis or processing. From these talks, a total of 17 original contribution or state-of-the-art chapters have been assembled in this volume. All articles were thoroughly peer-reviewed and improved, according to the suggestions of the international referees. The 17 contributions presented  are organized in three parts: (1) State-of-the-art surveys & original matrix theory work, (2) Advanced matrix theory for radar processing, and (3) Matrix-based signal processing applications.  

Matrix Metalloproteinase Responsive Delivery of Myostatin Inhibitors.

Science.gov (United States)

Braun, Alexandra C; Gutmann, Marcus; Ebert, Regina; Jakob, Franz; Gieseler, Henning; Lühmann, Tessa; Meinel, Lorenz

2017-01-01

The inhibition of myostatin - a member of the transforming growth factor (TGF-β) family - drives regeneration of functional skeletal muscle tissue. We developed a bioresponsive drug delivery system (DDS) linking release of a myostatin inhibitor (MI) to inflammatory flares of myositis to provide self-regulated MI concentration gradients within tissues of need. A protease cleavable linker (PCL) - responding to MMP upregulation - is attached to the MI and site-specifically immobilized on microparticle surfaces. The PCL disintegrated in a matrix metalloproteinase (MMP) 1, 8, and particularly MMP-9 concentration dependent manner, with MMP-9 being an effective surrogate biomarker correlating with the activity of myositis. The bioactivity of particle-surface bound as well as released MI was confirmed by luciferase suppression in stably transfected HEK293 cells responding to myostatin induced SMAD phosphorylation. We developed a MMP-responsive DDS for MI delivery responding to inflammatory flare of a diseased muscle matching the kinetics of MMP-9 upregulation, with MMP-9 kinetics matching (patho-) physiological myostatin levels. ᅟ: Graphical Abstract Schematic illustration of the matrix metalloproteinase responsive delivery system responding to inflammatory flares of muscle disease. The protease cleavable linker readily disintegrates upon entry into the diseased tissue, therby releasing the mystatin inhibitor.

Engineering a collagen matrix that replicates the biological properties of native extracellular matrix.

Science.gov (United States)

Nam, Kwangwoo; Sakai, Yuuki; Funamoto, Seiichi; Kimura, Tsuyoshi; Kishida, Akio

2011-01-01

In this study, we aimed to replicate the function of native tissues that can be used in tissue engineering and regenerative medicine. The key to such replication is the preparation of an artificial collagen matrix that possesses a structure resembling that of the extracellular matrix. We, therefore, prepared a collagen matrix by fibrillogenesis in a NaCl/Na(2)HPO(4) aqueous solution using a dialysis cassette and investigated its biological behavior in vitro and in vivo. The in vitro cell adhesion and proliferation did not show any significant differences. The degradation rate in the living body could be controlled according to the preparation condition, where the collagen matrix with high water content (F-collagen matrix, >98%) showed fast degradation and collagen matrix with lower water content (T-collagen matrix, >80%) showed no degradation for 8 weeks. The degradation did not affect the inflammatory response at all and relatively faster wound healing response was observed. Comparing this result with that of collagen gel and decellularized cornea, it can be concluded that the structural factor is very important and no cell abnormal behavior would be observed for quaternary structured collagen matrix.

Exploring matrix factorization techniques for significant genes identification of Alzheimer’s disease microarray gene expression data

Directory of Open Access Journals (Sweden)

Hu Xiaohua

2011-07-01

Full Text Available Abstract Background The wide use of high-throughput DNA microarray technology provide an increasingly detailed view of human transcriptome from hundreds to thousands of genes. Although biomedical researchers typically design microarray experiments to explore specific biological contexts, the relationships between genes are hard to identified because they are complex and noisy high-dimensional data and are often hindered by low statistical power. The main challenge now is to extract valuable biological information from the colossal amount of data to gain insight into biological processes and the mechanisms of human disease. To overcome the challenge requires mathematical and computational methods that are versatile enough to capture the underlying biological features and simple enough to be applied efficiently to large datasets. Methods Unsupervised machine learning approaches provide new and efficient analysis of gene expression profiles. In our study, two unsupervised knowledge-based matrix factorization methods, independent component analysis (ICA and nonnegative matrix factorization (NMF are integrated to identify significant genes and related pathways in microarray gene expression dataset of Alzheimer’s disease. The advantage of these two approaches is they can be performed as a biclustering method by which genes and conditions can be clustered simultaneously. Furthermore, they can group genes into different categories for identifying related diagnostic pathways and regulatory networks. The difference between these two method lies in ICA assume statistical independence of the expression modes, while NMF need positivity constrains to generate localized gene expression profiles. Results In our work, we performed FastICA and non-smooth NMF methods on DNA microarray gene expression data of Alzheimer’s disease respectively. The simulation results shows that both of the methods can clearly classify severe AD samples from control samples, and

Carbonate fuel cell matrix

Science.gov (United States)

Farooque, Mohammad; Yuh, Chao-Yi

1996-01-01

A carbonate fuel cell matrix comprising support particles and crack attenuator particles which are made platelet in shape to increase the resistance of the matrix to through cracking. Also disclosed is a matrix having porous crack attenuator particles and a matrix whose crack attenuator particles have a thermal coefficient of expansion which is significantly different from that of the support particles, and a method of making platelet-shaped crack attenuator particles.

Method of forming a ceramic matrix composite and a ceramic matrix component

Science.gov (United States)

de Diego, Peter; Zhang, James

2017-05-30

A method of forming a ceramic matrix composite component includes providing a formed ceramic member having a cavity, filling at least a portion of the cavity with a ceramic foam. The ceramic foam is deposited on a barrier layer covering at least one internal passage of the cavity. The method includes processing the formed ceramic member and ceramic foam to obtain a ceramic matrix composite component. Also provided is a method of forming a ceramic matrix composite blade and a ceramic matrix composite component.

Analysis of soda-lime glasses using non-negative matrix factor deconvolution of Raman spectra

OpenAIRE

Woelffel , William; Claireaux , Corinne; Toplis , Michael J.; Burov , Ekaterina; Barthel , Etienne; Shukla , Abhay; Biscaras , Johan; Chopinet , Marie-Hélène; Gouillart , Emmanuelle

2015-01-01

International audience; Novel statistical analysis and machine learning algorithms are proposed for the deconvolution and interpretation of Raman spectra of silicate glasses in the Na 2 O-CaO-SiO 2 system. Raman spectra are acquired along diffusion profiles of three pairs of glasses centered around an average composition of 69. 9 wt. % SiO 2 , 12. 7 wt. % CaO , 16. 8 wt. % Na 2 O. The shape changes of the Raman spectra across the compositional domain are analyzed using a combination of princi...

Hamiltonian formalism, quantization and S matrix for supergravity. [S matrix, canonical constraints

Energy Technology Data Exchange (ETDEWEB)

Fradkin, E S; Vasiliev, M A [AN SSSR, Moscow. Fizicheskij Inst.

1977-12-05

The canonical formalism for supergravity is constructed. The algebra of canonical constraints is found. The correct expression for the S matrix is obtained. Usual 'covariant methods' lead to an incorrect S matrix in supergravity since a new four-particle interaction of ghostfields survives in the Lagrangian expression of the S matrix.

Predictors of Family Conflict at the End of Life: The Experience of Spouses and Adult Children of Persons with Lung Cancer

Science.gov (United States)

Kramer, Betty J.; Kavanaugh, Melinda; Trentham-Dietz, Amy; Walsh, Matthew; Yonker, James A.

2010-01-01

Purpose: Guided by an explanatory matrix of family conflict at the end of life, the purpose of this article was to examine the correlates and predictors of family conflict reported by 155 spouses and adult children of persons with lung cancer. Design and Methods: A cross-sectional statewide survey of family members of persons who died from lung…

The Matrix Cookbook

DEFF Research Database (Denmark)

Petersen, Kaare Brandt; Pedersen, Michael Syskind

Matrix identities, relations and approximations. A desktop reference for quick overview of mathematics of matrices.......Matrix identities, relations and approximations. A desktop reference for quick overview of mathematics of matrices....

The plasma and peritoneal fluid concentrations of matrix metalloproteinase-9 are elevated in patients with endometriosis.

Science.gov (United States)

Liu, Haiping; Wang, Jianye; Wang, Haiyu; Tang, Ning; Li, Yunfei; Zhang, Yan; Hao, Tianyu

2016-09-01

Enzyme matrix metalloproteinase-9 is a member of the matrix metalloproteinase family, which is critical to normal tissue remodelling during embryogenesis and wound healing. In patients with endometriosis, increased expression and activity of matrix metalloproteinase-9 have been observed in ectopic endometrium, but the plasma and peritoneal fluid concentrations of matrix metalloproteinase-9 in patients with endometriosis and their relation to disease severity have not been clear. The aim of the study was to investigate the concentrations of matrix metalloproteinase-9 in plasma and peritoneal fluid of patients with endometriosis. A prospective case-control study was conducted in Jinan Military General Hospital between January 2010 and December 2013. Fifty patients with proven endometriosis and 26 endometriosis-free controls were enrolled in this study. Patients with endometriosis were evaluated and divided into moderate/severe endometriosis group (stage I-II, n = 26) and minimal/mild endometriosis group (stage III-IV, n = 24) according to the revised criteria of the American Society for Reproductive Medicine. Blood samples and peritoneal fluid were obtained from both patients and controls. Matrix metalloproteinase-9 was measured using enzyme-linked immunosorbent assay in plasma and peritoneal fluid. The concentration of matrix metalloproteinase-9 between different groups was compared and its correlation to disease severity was analysed. Plasma and peritoneal fluid concentrations of matrix metalloproteinase-9 in patients with endometriosis were higher than that in controls. In addition, those patients with moderate/severe endometriosis had significantly higher plasma and peritoneal fluid concentrations of matrix metalloproteinase-9 compared to those with minimal/mild endometriosis. Matrix metalloproteinase-9 concentrations in plasma and peritoneal fluid were both positively correlated with severity of endometriosis and plasma matrix metalloproteinase-9

Analysis of Enzymatic Activity of Matrix Metalloproteinase (MMP) by Collagen Zymography in Melanoma.

Science.gov (United States)

Walia, Vijay; Samuels, Yardena

2018-01-01

Protein zymography is the most commonly used technique to study the enzymatic activity of matrix metalloproteinases (MMPs) and their inhibitors. MMPs are proteolytic enzymes that promote extracellular matrix degradation. MMPs are frequently mutated in malignant melanomas as well as other cancers and are linked to increasing incidence of tumor metastasis. Substrate zymography characterizes MMP activity by their ability to degrade preferred substrates. Here we describe the collagen zymography technique to measure the active or latent form of MMPs using MMP-8 as an example, which is a frequently mutated MMP family member in malignant melanomas. The same technique can be used with the modification of substrate to detect metalloproteinase activity of other MMPs. Both wild-type and mutated forms of MMPs can be analyzed using a single gel using this method.

Multi-threaded Sparse Matrix Sparse Matrix Multiplication for Many-Core and GPU Architectures.

Energy Technology Data Exchange (ETDEWEB)

Deveci, Mehmet [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Trott, Christian Robert [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Rajamanickam, Sivasankaran [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2018-01-01

Sparse Matrix-Matrix multiplication is a key kernel that has applications in several domains such as scientific computing and graph analysis. Several algorithms have been studied in the past for this foundational kernel. In this paper, we develop parallel algorithms for sparse matrix- matrix multiplication with a focus on performance portability across different high performance computing architectures. The performance of these algorithms depend on the data structures used in them. We compare different types of accumulators in these algorithms and demonstrate the performance difference between these data structures. Furthermore, we develop a meta-algorithm, kkSpGEMM, to choose the right algorithm and data structure based on the characteristics of the problem. We show performance comparisons on three architectures and demonstrate the need for the community to develop two phase sparse matrix-matrix multiplication implementations for efficient reuse of the data structures involved.

Parallelism in matrix computations

CERN Document Server

Gallopoulos, Efstratios; Sameh, Ahmed H

2016-01-01

This book is primarily intended as a research monograph that could also be used in graduate courses for the design of parallel algorithms in matrix computations. It assumes general but not extensive knowledge of numerical linear algebra, parallel architectures, and parallel programming paradigms. The book consists of four parts: (I) Basics; (II) Dense and Special Matrix Computations; (III) Sparse Matrix Computations; and (IV) Matrix functions and characteristics. Part I deals with parallel programming paradigms and fundamental kernels, including reordering schemes for sparse matrices. Part II is devoted to dense matrix computations such as parallel algorithms for solving linear systems, linear least squares, the symmetric algebraic eigenvalue problem, and the singular-value decomposition. It also deals with the development of parallel algorithms for special linear systems such as banded ,Vandermonde ,Toeplitz ,and block Toeplitz systems. Part III addresses sparse matrix computations: (a) the development of pa...

Extracellular Matrix components regulate cellular polarity and tissue structure in the developing and mature Retina

Directory of Open Access Journals (Sweden)

Shweta Varshney

2015-01-01

Full Text Available While genetic networks and other intrinsic mechanisms regulate much of retinal development, interactions with the extracellular environment shape these networks and modify their output. The present review has focused on the role of one family of extracellular matrix molecules and their signaling pathways in retinal development. In addition to their effects on the developing retina, laminins play a role in maintaining Müller cell polarity and compartmentalization, thereby contributing to retinal homeostasis. This article which is intended for the clinical audience, reviews the fundamentals of retinal development, extracellular matrix organization and the role of laminins in retinal development. The role of laminin in cortical development is also briefly discussed.

Constraints on dephasing widths and shifts in three-level quantum systems

International Nuclear Information System (INIS)

Berman, P.R.; O'Connell, Ross C.

2005-01-01

It is shown that the density matrix equations for a three-level quantum system interacting with external radiation fields can lead to negative populations if arbitrary dephasing rates and shifts are included in these equations. To guarantee non-negative populations, the equations themselves impose certain restrictions on the dephasing widths and shifts. The constraints on the widths are shown to be identical to those that can be derived from a model of Markovian dephasing events, independent of any atom-field interaction

Neutrino mass matrix and hierarchy

International Nuclear Information System (INIS)

Kaus, Peter; Meshkov, Sydney

2003-01-01

We build a model to describe neutrinos based on strict hierarchy, incorporating as much as possible, the latest known data, for Δsol and Δatm, and for the mixing angles determined from neutrino oscillation experiments, including that from KamLAND. Since the hierarchy assumption is a statement about mass ratios, it lets us obtain all three neutrino masses. We obtain a mass matrix, Mν and a mixing matrix, U, where both Mν and U are given in terms of powers of Λ, the analog of the Cabibbo angle λ in the Wolfenstein representation, and two parameters, ρ and κ, each of order one. The expansion parameter, Λ, is defined by Λ2 = m2/m3 = √(Δsol/Δatm) ≅ 0.16, and ρ expresses our ignorance of the lightest neutrino mass m1, (m1 ρΛ4m3), while κ scales s13 to the experimental upper limit, s13 = κΛ2 ≅ 0.16κ. These matrices are similar in structure to those for the quark and lepton families, but with Λ about 1.6 times larger than the λ for the quarks and charged leptons. The upper limit for the effective neutrino mass in double β-decay experiments is 4 x 10-3eV if s13 = 0 and 6 x 10-3eV if s13 is maximal. The model, which is fairly unique, given the hierarchy assumption and the data, is compared to supersymmetric extension and texture zero models of mass generation

The Exopolysaccharide Matrix

Science.gov (United States)

Koo, H.; Falsetta, M.L.; Klein, M.I.

2013-01-01

Many infectious diseases in humans are caused or exacerbated by biofilms. Dental caries is a prime example of a biofilm-dependent disease, resulting from interactions of microorganisms, host factors, and diet (sugars), which modulate the dynamic formation of biofilms on tooth surfaces. All biofilms have a microbial-derived extracellular matrix as an essential constituent. The exopolysaccharides formed through interactions between sucrose- (and starch-) and Streptococcus mutans-derived exoenzymes present in the pellicle and on microbial surfaces (including non-mutans) provide binding sites for cariogenic and other organisms. The polymers formed in situ enmesh the microorganisms while forming a matrix facilitating the assembly of three-dimensional (3D) multicellular structures that encompass a series of microenvironments and are firmly attached to teeth. The metabolic activity of microbes embedded in this exopolysaccharide-rich and diffusion-limiting matrix leads to acidification of the milieu and, eventually, acid-dissolution of enamel. Here, we discuss recent advances concerning spatio-temporal development of the exopolysaccharide matrix and its essential role in the pathogenesis of dental caries. We focus on how the matrix serves as a 3D scaffold for biofilm assembly while creating spatial heterogeneities and low-pH microenvironments/niches. Further understanding on how the matrix modulates microbial activity and virulence expression could lead to new approaches to control cariogenic biofilms. PMID:24045647

A short walk in quantum probability

Science.gov (United States)

Hudson, Robin

2018-04-01

This is a personal survey of aspects of quantum probability related to the Heisenberg commutation relation for canonical pairs. Using the failure, in general, of non-negativity of the Wigner distribution for canonical pairs to motivate a more satisfactory quantum notion of joint distribution, we visit a central limit theorem for such pairs and a resulting family of quantum planar Brownian motions which deform the classical planar Brownian motion, together with a corresponding family of quantum stochastic areas. This article is part of the themed issue `Hilbert's sixth problem'.

A short walk in quantum probability.

Science.gov (United States)

Hudson, Robin

2018-04-28

This is a personal survey of aspects of quantum probability related to the Heisenberg commutation relation for canonical pairs. Using the failure, in general, of non-negativity of the Wigner distribution for canonical pairs to motivate a more satisfactory quantum notion of joint distribution, we visit a central limit theorem for such pairs and a resulting family of quantum planar Brownian motions which deform the classical planar Brownian motion, together with a corresponding family of quantum stochastic areas.This article is part of the themed issue 'Hilbert's sixth problem'. © 2018 The Author(s).

Characterizing the influence of matrix ductility on damage phenomenology in continuous fiber-reinforced thermoplastic laminates undergoing quasi-static indentation

KAUST Repository

Yudhanto, Arief

2017-12-12

The use of thermoplastic matrix was known to improve the impact properties of laminated composites. However, different ductility levels can exist in a single family of thermoplastic matrix, and this may consequently modify the damage phenomenology of thermoplastic composites. This paper focuses on the effect of matrix ductility on the out-of-plane properties of thermoplastic composites, which was studied through quasi-static indentation (QSI) test that may represent impact problem albeit the speed difference. We evaluated continuous glass-fiber reinforced polypropylene thermoplastic composites (GFPP), and selected homopolymer PP and copolymer PP that represent ductile and less ductile matrices, respectively. Several cross-ply laminates were selected to study the influence of ply thicknesses and relative orientation of interfaces on QSI properties of GFPP. It is expected that GFPP with ductile matrix improves energy absorption of GFPP. However, the damage mechanism is completely different between GFPP with ductile and GFPP with less ductile matrices. GFPP with ductile matrix exhibits smaller damage zone in comparison to the one with less ductile matrix. Higher matrix ductility inhibits the growth of ply cracking along the fiber, and this causes the limited size of delamination. The stacking sequence poses more influence on less ductile composites rather than the ductile one.

Which family physician should I choose? The analytic hierarchy process approach for ranking of criteria in the selection of a family physician.

Science.gov (United States)

Kuruoglu, Emel; Guldal, Dilek; Mevsim, Vildan; Gunvar, Tolga

2015-08-05

Choosing the most appropriate family physician (FP) for the individual, plays a fundamental role in primary care. The aim of this study is to determine the selection criteria for the patients in choosing their family doctors and priority ranking of these criteria by using the multi-criteria decision-making method of the Analytic Hierarchy Process (AHP) model. The study was planned and conducted in two phases. In the first phase, factors affecting the patients' decisions were revealed with a qualitative research. In the next phase, the priorities of FP selection criteria were determined by using AHP model. Criteria were compared in pairs. 96 patient were asked to fill the information forms which contains comparison scores in the Family Health Centres. According to the analysis of focus group discussions FP selection criteria were congregated in to five groups: Individual Characteristics, Patient-Doctor relationship, Professional characteristics, the Setting, and Ethical Characteristics. For each of the 96 participants, comparison matrixes were formed based on the scores of their information forms. Of these, models of only 5 (5.2 %) of the participants were consistent, in other words, they have been able to score consistent ranking. The consistency ratios (CR) were found to be smaller than 0.10. Therefore the comparison matrix of this new model, which was formed based on the medians of scores only given by these 5 participants, was consistent (CR = 0.06 < 0.10). According to comparison results; with a 0.467 value-weight, the most important criterion for choosing a family physician is his/her 'Professional characteristics'. Selection criteria for choosing a FP were put in a priority order by using AHP model. These criteria can be used as measures for selecting alternative FPs in further researches.

Matrix with Prescribed Eigenvectors

Science.gov (United States)

Ahmad, Faiz

2011-01-01

It is a routine matter for undergraduates to find eigenvalues and eigenvectors of a given matrix. But the converse problem of finding a matrix with prescribed eigenvalues and eigenvectors is rarely discussed in elementary texts on linear algebra. This problem is related to the "spectral" decomposition of a matrix and has important technical…

Elementary matrix theory

CERN Document Server

Eves, Howard

1980-01-01

The usefulness of matrix theory as a tool in disciplines ranging from quantum mechanics to psychometrics is widely recognized, and courses in matrix theory are increasingly a standard part of the undergraduate curriculum.This outstanding text offers an unusual introduction to matrix theory at the undergraduate level. Unlike most texts dealing with the topic, which tend to remain on an abstract level, Dr. Eves' book employs a concrete elementary approach, avoiding abstraction until the final chapter. This practical method renders the text especially accessible to students of physics, engineeri

Effect of Fiber Poisson Contraction on Matrix Multicracking Evolution of Fiber-Reinforced Ceramic-Matrix Composites

Science.gov (United States)

Longbiao, Li

2015-12-01

An analytical methodology has been developed to investigate the effect of fiber Poisson contraction on matrix multicracking evolution of fiber-reinforced ceramic-matrix composites (CMCs). The modified shear-lag model incorporated with the Coulomb friction law is adopted to solve the stress distribution in the interface slip region and intact region of the damaged composite. The critical matrix strain energy criterion which presupposes the existence of an ultimate or critical strain energy limit beyond which the matrix fails has been adopted to describe matrix multicracking of CMCs. As more energy is placed into the composite, matrix fractures and the interface debonding occurs to dissipate the extra energy. The interface debonded length under the process of matrix multicracking is obtained by treating the interface debonding as a particular crack propagation problem along the fiber/matrix interface. The effects of the interfacial frictional coefficient, fiber Poisson ratio, fiber volume fraction, interface debonded energy and cycle number on the interface debonding and matrix multicracking evolution have been analyzed. The theoretical results are compared with experimental data of unidirectional SiC/CAS, SiC/CAS-II and SiC/Borosilicate composites.

Expression, purification and crystallization of a lyssavirus matrix (M) protein

Science.gov (United States)

Assenberg, René; Delmas, Olivier; Graham, Stephen C.; Verma, Anil; Berrow, Nick; Stuart, David I.; Owens, Raymond J.; Bourhy, Hervé; Grimes, Jonathan M.

2008-01-01

The matrix (M) proteins of lyssaviruses (family Rhabdoviridae) are crucial to viral morphogenesis as well as in modulating replication and transcription of the viral genome. To date, no high-resolution structural information has been obtained for full-length rhabdovirus M. Here, the cloning, expression and purification of the matrix proteins from three lyssaviruses, Lagos bat virus (LAG), Mokola virus and Thailand dog virus, are described. Crystals have been obtained for the full-length M protein from Lagos bat virus (LAG M). Successful crystallization depended on a number of factors, in particular the addition of an N-terminal SUMO fusion tag to increase protein solubility. Diffraction data have been recorded from crystals of native and selenomethionine-labelled LAG M to 2.75 and 3.0 Å resolution, respectively. Preliminary analysis indicates that these crystals belong to space group P6122 or P6522, with unit-cell parameters a = b = 56.9–57.2, c = 187.9–188.6 Å, consistent with the presence of one molecule per asymmetric unit, and structure determination is currently in progress. PMID:18391421

EISPACK, Subroutines for Eigenvalues, Eigenvectors, Matrix Operations

International Nuclear Information System (INIS)

Garbow, Burton S.; Cline, A.K.; Meyering, J.

1993-01-01

1 - Description of problem or function: EISPACK3 is a collection of 75 FORTRAN subroutines, both single- and double-precision, that compute the eigenvalues and eigenvectors of nine classes of matrices. The package can determine the Eigen-system of complex general, complex Hermitian, real general, real symmetric, real symmetric band, real symmetric tridiagonal, special real tridiagonal, generalized real, and generalized real symmetric matrices. In addition, there are two routines which use the singular value decomposition to solve certain least squares problem. The individual subroutines are - Identification/Description: BAKVEC: Back transform vectors of matrix formed by FIGI; BALANC: Balance a real general matrix; BALBAK: Back transform vectors of matrix formed by BALANC; BANDR: Reduce sym. band matrix to sym. tridiag. matrix; BANDV: Find some vectors of sym. band matrix; BISECT: Find some values of sym. tridiag. matrix; BQR: Find some values of sym. band matrix; CBABK2: Back transform vectors of matrix formed by CBAL; CBAL: Balance a complex general matrix; CDIV: Perform division of two complex quantities; CG: Driver subroutine for a complex general matrix; CH: Driver subroutine for a complex Hermitian matrix; CINVIT: Find some vectors of complex Hess. matrix; COMBAK: Back transform vectors of matrix formed by COMHES; COMHES: Reduce complex matrix to complex Hess. (elementary); COMLR: Find all values of complex Hess. matrix (LR); COMLR2: Find all values/vectors of cmplx Hess. matrix (LR); CCMQR: Find all values of complex Hessenberg matrix (QR); COMQR2: Find all values/vectors of cmplx Hess. matrix (QR); CORTB: Back transform vectors of matrix formed by CORTH; CORTH: Reduce complex matrix to complex Hess. (unitary); CSROOT: Find square root of complex quantity; ELMBAK: Back transform vectors of matrix formed by ELMHES; ELMHES: Reduce real matrix to real Hess. (elementary); ELTRAN: Accumulate transformations from ELMHES (for HQR2); EPSLON: Estimate unit roundoff

RSAT matrix-clustering: dynamic exploration and redundancy reduction of transcription factor binding motif collections.

Science.gov (United States)

Castro-Mondragon, Jaime Abraham; Jaeger, Sébastien; Thieffry, Denis; Thomas-Chollier, Morgane; van Helden, Jacques

2017-07-27

Transcription factor (TF) databases contain multitudes of binding motifs (TFBMs) from various sources, from which non-redundant collections are derived by manual curation. The advent of high-throughput methods stimulated the production of novel collections with increasing numbers of motifs. Meta-databases, built by merging these collections, contain redundant versions, because available tools are not suited to automatically identify and explore biologically relevant clusters among thousands of motifs. Motif discovery from genome-scale data sets (e.g. ChIP-seq) also produces redundant motifs, hampering the interpretation of results. We present matrix-clustering, a versatile tool that clusters similar TFBMs into multiple trees, and automatically creates non-redundant TFBM collections. A feature unique to matrix-clustering is its dynamic visualisation of aligned TFBMs, and its capability to simultaneously treat multiple collections from various sources. We demonstrate that matrix-clustering considerably simplifies the interpretation of combined results from multiple motif discovery tools, and highlights biologically relevant variations of similar motifs. We also ran a large-scale application to cluster ∼11 000 motifs from 24 entire databases, showing that matrix-clustering correctly groups motifs belonging to the same TF families, and drastically reduced motif redundancy. matrix-clustering is integrated within the RSAT suite (http://rsat.eu/), accessible through a user-friendly web interface or command-line for its integration in pipelines. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Proteomics of Fuchs' Endothelial Corneal Dystrophy support that the extracellular matrix of Descemet's membrane is disordered

DEFF Research Database (Denmark)

Poulsen, Ebbe Toftgaard; Dyrlund, Thomas F; Runager, Kasper

2014-01-01

Fuchs' endothelial corneal dystrophy (FECD) is a major corneal disorder affecting the innermost part of the cornea, leading to visual impairment. As the morphological changes in FECD are mainly observed in the extracellular matrix of the Descemet's membrane/endothelial layer we determined...... that the morphological changes observed in FECD is caused in part by an aberrant assembly of the extracellular matrix within the Descemet's membrane/endothelial layer......., respectively, of which 10 were significantly regulated. The results indicated that the level of type VIII collagen was unaltered even though the protein previously has been implicated in familial early onset forms of the disease. Using the second relative quantitation method iTRAQ we identified 22...

Matrix algebra for linear models

CERN Document Server

Gruber, Marvin H J

2013-01-01

Matrix methods have evolved from a tool for expressing statistical problems to an indispensable part of the development, understanding, and use of various types of complex statistical analyses. This evolution has made matrix methods a vital part of statistical education. Traditionally, matrix methods are taught in courses on everything from regression analysis to stochastic processes, thus creating a fractured view of the topic. Matrix Algebra for Linear Models offers readers a unique, unified view of matrix analysis theory (where and when necessary), methods, and their applications. Written f

Triangularization of a Matrix

Indian Academy of Sciences (India)

Much of linear algebra is devoted to reducing a matrix (via similarity or unitary similarity) to another that has lots of zeros. The simplest such theorem is the Schur triangularization theorem. This says that every matrix is unitarily similar to an upper triangular matrix. Our aim here is to show that though it is very easy to prove it ...

Blind decomposition of Herschel-HIFI spectral maps of the NGC 7023 nebula

Science.gov (United States)

Berné, O.; Joblin, C.; Deville, Y.; Pilleri, P.; Pety, J.; Teyssier, D.; Gerin, M.; Fuente, A.

2012-12-01

Large spatial-spectral surveys are more and more common in astronomy. This calls for the need of new methods to analyze such mega- to giga-pixel data-cubes. In this paper we present a method to decompose such observations into a limited and comprehensive set of components. The original data can then be interpreted in terms of linear combinations of these components. The method uses non-negative matrix factorization (NMF) to extract latent spectral end-members in the data. The number of needed end-members is estimated based on the level of noise in the data. A Monte-Carlo scheme is adopted to estimate the optimal end-members, and their standard deviations. Finally, the maps of linear coefficients are reconstructed using non-negative least squares. We apply this method to a set of hyperspectral data of the NGC 7023 nebula, obtained recently with the HIFI instrument onboard the Herschel space observatory, and provide a first interpretation of the results in terms of 3-dimensional dynamical structure of the region.

Experimental study on mechanical behavior of fiber/matrix interface in metal matrix composite

International Nuclear Information System (INIS)

Wang, Q.; Chiang, F.P.

1994-01-01

The technique SIEM(Speckle Interferometry with Electron Microscopy) was employed to quantitatively measure the deformation on the fiber/matrix interface in SCS-6/Ti-6-4 composite at a microscale level. The displacement field within the fiber/matrix interphase zone was determined by in-situ observation with sensitivity of 0.003(microm). The macro-mechanical properties were compared with micro-mechanical behavior. It is shown that the strength in the interphase zone is weaker than the matrix tensile strength. The deformation process can be characterized by the uniform deformation, interface strain concentration and debond, and matrix plastic deformation

An Efficient GPU General Sparse Matrix-Matrix Multiplication for Irregular Data

DEFF Research Database (Denmark)

Liu, Weifeng; Vinter, Brian

2014-01-01

General sparse matrix-matrix multiplication (SpGEMM) is a fundamental building block for numerous applications such as algebraic multigrid method, breadth first search and shortest path problem. Compared to other sparse BLAS routines, an efficient parallel SpGEMM algorithm has to handle extra...... irregularity from three aspects: (1) the number of the nonzero entries in the result sparse matrix is unknown in advance, (2) very expensive parallel insert operations at random positions in the result sparse matrix dominate the execution time, and (3) load balancing must account for sparse data in both input....... Load balancing builds on the number of the necessary arithmetic operations on the nonzero entries and is guaranteed in all stages. Compared with the state-of-the-art GPU SpGEMM methods in the CUSPARSE library and the CUSP library and the latest CPU SpGEMM method in the Intel Math Kernel Library, our...

The Complex Interaction of Matrix Metalloproteinases in the Migration of Cancer Cells through Breast Tissue Stroma

Directory of Open Access Journals (Sweden)

Kerry J. Davies

2014-01-01

Full Text Available Breast cancer mortality is directly linked to metastatic spread. The metastatic cell must exhibit a complex phenotype that includes the capacity to escape from the primary tumour mass, invade the surrounding normal tissue, and penetrate into the circulation before proliferating in the parenchyma of distant organs to produce a metastasis. In the normal breast, cellular structures change cyclically in response to ovarian hormones leading to regulated cell proliferation and apoptosis. Matrix metalloproteinases (MMPs are a family of zinc dependent endopeptidases. Their primary function is degradation of proteins in the extracellular matrix to allow ductal progression through the basement membrane. A complex balance between matrix metalloproteinases and their inhibitors regulate these changes. These proteinases interact with cytokines, growth factors, and tumour necrosis factors to stimulate branching morphologies in normal breast tissues. In breast cancer this process is disrupted facilitating tumour progression and metastasis and inhibiting apoptosis increasing the life of the metastatic cells. This paper highlights the role of matrix metalloproteinases in cell progression through the breast stroma and reviews the complex relationships between the different proteinases and their inhibitors in relation to breast cancer cells as they metastasise.

Combinatorial matrix theory

CERN Document Server

Mitjana, Margarida

2018-01-01

This book contains the notes of the lectures delivered at an Advanced Course on Combinatorial Matrix Theory held at Centre de Recerca Matemàtica (CRM) in Barcelona. These notes correspond to five series of lectures. The first series is dedicated to the study of several matrix classes defined combinatorially, and was delivered by Richard A. Brualdi. The second one, given by Pauline van den Driessche, is concerned with the study of spectral properties of matrices with a given sign pattern. Dragan Stevanović delivered the third one, devoted to describing the spectral radius of a graph as a tool to provide bounds of parameters related with properties of a graph. The fourth lecture was delivered by Stephen Kirkland and is dedicated to the applications of the Group Inverse of the Laplacian matrix. The last one, given by Ángeles Carmona, focuses on boundary value problems on finite networks with special in-depth on the M-matrix inverse problem.

A survey of matrix theory and matrix inequalities

CERN Document Server

Marcus, Marvin

2010-01-01

Written for advanced undergraduate students, this highly regarded book presents an enormous amount of information in a concise and accessible format. Beginning with the assumption that the reader has never seen a matrix before, the authors go on to provide a survey of a substantial part of the field, including many areas of modern research interest.Part One of the book covers not only the standard ideas of matrix theory, but ones, as the authors state, ""that reflect our own prejudices,"" among them Kronecker products, compound and induced matrices, quadratic relations, permanents, incidence

Exponential Family Functional data analysis via a low-rank model.

Science.gov (United States)

Li, Gen; Huang, Jianhua Z; Shen, Haipeng

2018-05-08

In many applications, non-Gaussian data such as binary or count are observed over a continuous domain and there exists a smooth underlying structure for describing such data. We develop a new functional data method to deal with this kind of data when the data are regularly spaced on the continuous domain. Our method, referred to as Exponential Family Functional Principal Component Analysis (EFPCA), assumes the data are generated from an exponential family distribution, and the matrix of the canonical parameters has a low-rank structure. The proposed method flexibly accommodates not only the standard one-way functional data, but also two-way (or bivariate) functional data. In addition, we introduce a new cross validation method for estimating the latent rank of a generalized data matrix. We demonstrate the efficacy of the proposed methods using a comprehensive simulation study. The proposed method is also applied to a real application of the UK mortality study, where data are binomially distributed and two-way functional across age groups and calendar years. The results offer novel insights into the underlying mortality pattern. © 2018, The International Biometric Society.

Efficient sparse matrix-matrix multiplication for computing periodic responses by shooting method on Intel Xeon Phi

Science.gov (United States)

Stoykov, S.; Atanassov, E.; Margenov, S.

2016-10-01

Many of the scientific applications involve sparse or dense matrix operations, such as solving linear systems, matrix-matrix products, eigensolvers, etc. In what concerns structural nonlinear dynamics, the computations of periodic responses and the determination of stability of the solution are of primary interest. Shooting method iswidely used for obtaining periodic responses of nonlinear systems. The method involves simultaneously operations with sparse and dense matrices. One of the computationally expensive operations in the method is multiplication of sparse by dense matrices. In the current work, a new algorithm for sparse matrix by dense matrix products is presented. The algorithm takes into account the structure of the sparse matrix, which is obtained by space discretization of the nonlinear Mindlin's plate equation of motion by the finite element method. The algorithm is developed to use the vector engine of Intel Xeon Phi coprocessors. It is compared with the standard sparse matrix by dense matrix algorithm and the one developed by Intel MKL and it is shown that by considering the properties of the sparse matrix better algorithms can be developed.

Parallel R-matrix computation

International Nuclear Information System (INIS)

Heggarty, J.W.

1999-06-01

For almost thirty years, sequential R-matrix computation has been used by atomic physics research groups, from around the world, to model collision phenomena involving the scattering of electrons or positrons with atomic or molecular targets. As considerable progress has been made in the understanding of fundamental scattering processes, new data, obtained from more complex calculations, is of current interest to experimentalists. Performing such calculations, however, places considerable demands on the computational resources to be provided by the target machine, in terms of both processor speed and memory requirement. Indeed, in some instances the computational requirements are so great that the proposed R-matrix calculations are intractable, even when utilising contemporary classic supercomputers. Historically, increases in the computational requirements of R-matrix computation were accommodated by porting the problem codes to a more powerful classic supercomputer. Although this approach has been successful in the past, it is no longer considered to be a satisfactory solution due to the limitations of current (and future) Von Neumann machines. As a consequence, there has been considerable interest in the high performance multicomputers, that have emerged over the last decade which appear to offer the computational resources required by contemporary R-matrix research. Unfortunately, developing codes for these machines is not as simple a task as it was to develop codes for successive classic supercomputers. The difficulty arises from the considerable differences in the computing models that exist between the two types of machine and results in the programming of multicomputers to be widely acknowledged as a difficult, time consuming and error-prone task. Nevertheless, unless parallel R-matrix computation is realised, important theoretical and experimental atomic physics research will continue to be hindered. This thesis describes work that was undertaken in

Modeling the formation of cell-matrix adhesions on a single 3D matrix fiber.

Science.gov (United States)

Escribano, J; Sánchez, M T; García-Aznar, J M

2015-11-07

Cell-matrix adhesions are crucial in different biological processes like tissue morphogenesis, cell motility, and extracellular matrix remodeling. These interactions that link cell cytoskeleton and matrix fibers are built through protein clutches, generally known as adhesion complexes. The adhesion formation process has been deeply studied in two-dimensional (2D) cases; however, the knowledge is limited for three-dimensional (3D) cases. In this work, we simulate different local extracellular matrix properties in order to unravel the fundamental mechanisms that regulate the formation of cell-matrix adhesions in 3D. We aim to study the mechanical interaction of these biological structures through a three dimensional discrete approach, reproducing the transmission pattern force between the cytoskeleton and a single extracellular matrix fiber. This numerical model provides a discrete analysis of the proteins involved including spatial distribution, interaction between them, and study of the different phenomena, such as protein clutches unbinding or protein unfolding. Copyright © 2015 Elsevier Ltd. All rights reserved.

Symmetry breaking in the double-well hermitian matrix models

International Nuclear Information System (INIS)

Brower, R.C.; Deo, N.; Jain, S.; Tan, C.I.

1993-01-01

We study symmetry breaking in Z 2 symmetric large N matrix models. In the planar approximation for both the symmetric double-well φ 4 model and the symmetric Penner model, we find there is an infinite family of broken symmetry solutions characterized by different sets of recursion coefficients R n and S n that all lead to identical free energies and eigenvalue densities. These solutions can be parameterized by an arbitrary angle θ(x), for each value of x=n/N 4 theory the double scaling string equations are parameterized by a conserved angular momentum parameter in the range 0≤l<∞ and a single arbitrary U(1) phase angle. (orig.)

Dielectric matrix, dynamical matrix and phonon dispersion in hcp transition metal scandium

International Nuclear Information System (INIS)

Singh, Joginder; Singh, Natthi; Prakash, S.

1976-01-01

Complete dielectric matrix is evaluated for hcp transition metal scandium using the non-interacting s- and d-band model. The local field corrections which are consequence of the non-diagonal part of the dielectric matrix are calculated explicitly. The free electron approximation is used for the s-electrons and the simple tight-binding approximation is used for the d-electrons. The theory developed by Singh and others is used to invert the dielectric matrix and the explicit expressions for the dynamical matrix are obtained. The phonon dispersion relations are investigated by using the renormalized Animalu transition metal model potential (TMMP) for bare ion potential. The contribution due to non-central forces which arise due to local fields is found to be 20%. The results are found in resonably good agreement with the experimental values. (author)

Resources, attractiveness, family commitment; reproductive decisions in human mate choice.

Science.gov (United States)

Bereczkei, T; Voros, S; Gal, A; Bernath, L

1997-08-01

This study of reproductive decisions in human mate selection used data from "lonely hearts" advertisements to examine a series of predictions based on the mate preferences of male and females relating to age; physical appearance; financial condition and socioeconomic status; family commitment and personal traits; short- and long-term mating; and marital status and preexisting children. The sample consisted of 1000 personal advertisements (500 male) placed in two daily, national papers between February and October 1994 in Hungary. The research procedure included a pilot study of 150 advertisers (75 male) to refine the categories examined. Analysis was performed using 1) a matrix with one axis referring to offers and the other to demands of males and females separately; 2) a matrix of offers only to derive correlated traits of claims by males and females; and 3) a matrix with columns describing sex, offers, demands, advertiser's age, and required age and a row for each of the 1000 samples. It was found that men preferred younger mates, while women preferred older ones. Men were more likely to seek physical attractiveness, while women were more likely to seek financial resources (ranked 7th) and high status (ranked 6th). Women strongly preferred male domestic virtue and family commitment, and twice as many women as men demanded long-term relationships. Women more frequently declared preexisting children, and men exhibited a reluctance to accept these children. Both males and females employed "trade-off" strategies, making greater demands if they felt they had attractive offers.

Neutrino tri-bi-maximal mixing from a non-Abelian discrete family symmetry

CERN Document Server

Varzielas, I M; Ross, Graham G

2007-01-01

The observed neutrino mixing, having a near maximal atmospheric neutrino mixing angle and a large solar mixing angle, is close to tri-bi-maximal. We argue that this structure suggests a family symmetric origin in which the magnitude of the mixing angles are related to the existence of a discrete non-Abelian family symmetry. We construct a model in which the family symmetry is the non-Abelian discrete group $\\Delta(27)$, a subgroup of $SU(3)$ in which the tri-bi-maximal mixing directly follows from the vacuum structure enforced by the discrete symmetry. In addition to the lepton mixing angles, the model accounts for the observed quark and lepton masses and the CKM matrix. The structure is also consistent with an underlying stage of Grand Unification.

Polychoric/Tetrachoric Matrix or Pearson Matrix? A methodological study

Directory of Open Access Journals (Sweden)

Dominguez Lara, Sergio Alexis

2014-04-01

Full Text Available The use of product-moment correlation of Pearson is common in most studies in factor analysis in psychology, but it is known that this statistic is only applicable when the variables related are in interval scale and normally distributed, and when are used in ordinal data may to produce a distorted correlation matrix . Thus is a suitable option using polychoric/tetrachoric matrices in item-level factor analysis when the items are in level measurement nominal or ordinal. The aim of this study was to show the differences in the KMO, Bartlett`s Test and Determinant of the Matrix, percentage of variance explained and factor loadings in depression trait scale of Depression Inventory Trait - State and the Neuroticism dimension of the short form of the Eysenck Personality Questionnaire -Revised, regarding the use of matrices polychoric/tetrachoric matrices and Pearson. These instruments was analyzed with different extraction methods (Maximum Likelihood, Minimum Rank Factor Analysis, Unweighted Least Squares and Principal Components, keeping constant the rotation method Promin were analyzed. Were observed differences regarding sample adequacy measures, as well as with respect to the explained variance and the factor loadings, for solutions having as polychoric/tetrachoric matrix. So it can be concluded that the polychoric / tetrachoric matrix give better results than Pearson matrices when it comes to item-level factor analysis using different methods.

A Constrained Algorithm Based NMFα for Image Representation

Directory of Open Access Journals (Sweden)

Chenxue Yang

2014-01-01

Full Text Available Nonnegative matrix factorization (NMF is a useful tool in learning a basic representation of image data. However, its performance and applicability in real scenarios are limited because of the lack of image information. In this paper, we propose a constrained matrix decomposition algorithm for image representation which contains parameters associated with the characteristics of image data sets. Particularly, we impose label information as additional hard constraints to the α-divergence-NMF unsupervised learning algorithm. The resulted algorithm is derived by using Karush-Kuhn-Tucker (KKT conditions as well as the projected gradient and its monotonic local convergence is proved by using auxiliary functions. In addition, we provide a method to select the parameters to our semisupervised matrix decomposition algorithm in the experiment. Compared with the state-of-the-art approaches, our method with the parameters has the best classification accuracy on three image data sets.

MatrixPlot: visualizing sequence constraints

DEFF Research Database (Denmark)

Gorodkin, Jan; Stærfeldt, Hans Henrik; Lund, Ole

1999-01-01

MatrixPlot: visualizing sequence constraints. Sub-title Abstract Summary : MatrixPlot is a program for making high-quality matrix plots, such as mutual information plots of sequence alignments and distance matrices of sequences with known three-dimensional coordinates. The user can add information...

POLLA-NESC, Resonance Parameter R-Matrix to S-Matrix Conversion by Reich-Moore Method

International Nuclear Information System (INIS)

Saussure, G. de; Perez, R.B.

1975-01-01

1 - Description of problem or function: The program transforms a set of r-matrix nuclear resonance parameters into a set of equivalent s-matrix (or Kapur-Peierls) resonance parameters. 2 - Method of solution: The program utilizes the multilevel formalism of Reich and Moore and avoids diagonalization of the level matrix. The parameters are obtained by a direct partial fraction expansion of the Reich-Moore expression of the collision matrix. This approach appears simpler and faster when the number of fission channels is known and small. The method is particularly useful when a large number of levels must be considered because it does not require diagonalization of a large level matrix. 3 - Restrictions on the complexity of the problem: By DIMENSION statements, the program is limited to maxima of 100 levels and 5 channels

Fast Tree: Computing Large Minimum-Evolution Trees with Profiles instead of a Distance Matrix

OpenAIRE

N. Price, Morgan

2009-01-01

Gene families are growing rapidly, but standard methods for inferring phylogenies do not scale to alignments with over 10,000 sequences. We present FastTree, a method for constructing large phylogenies and for estimating their reliability. Instead of storing a distance matrix, FastTree stores sequence profiles of internal nodes in the tree. FastTree uses these profiles to implement neighbor-joining and uses heuristics to quickly identify candidate joins. FastTree then uses nearest-neighbor i...

FastTree: Computing Large Minimum Evolution Trees with Profiles instead of a Distance Matrix

OpenAIRE

Price, Morgan N.; Dehal, Paramvir S.; Arkin, Adam P.

2009-01-01

Gene families are growing rapidly, but standard methods for inferring phylogenies do not scale to alignments with over 10,000 sequences. We present FastTree, a method for constructing large phylogenies and for estimating their reliability. Instead of storing a distance matrix, FastTree stores sequence profiles of internal nodes in the tree. FastTree uses these profiles to implement Neighbor-Joining and uses heuristics to quickly identify candidate joins. FastTree then uses nearest neighbor in...

Entanglement and quantum phase transitions in matrix-product spin-1 chains

International Nuclear Information System (INIS)

Alipour, S.; Karimipour, V.; Memarzadeh, L.

2007-01-01

We consider a one-parameter family of matrix-product states of spin-1 particles on a periodic chain and study in detail the entanglement properties of such a state. In particular, we calculate exactly the entanglement of one site with the rest of the chain, and the entanglement of two distant sites with each other, and show that the derivative of both these properties diverge when the parameter g of the states passes through a critical point. Such a point can be called a point of quantum phase transition, since at this point the character of the matrix-product state, which is the ground state of a Hamiltonian, changes discontinuously. We also study the finite size effects and show how the entanglement depends on the size of the chain. This later part is relevant to the field of quantum computation where the problem of initial state preparation in finite arrays of qubits or qutrits is important. It is also shown that the entanglement of two sites have scaling behavior near the critical point

A random matrix model for elliptic curve L-functions of finite conductor

International Nuclear Information System (INIS)

Dueñez, E; Huynh, D K; Keating, J P; Snaith, N C; Miller, S J

2012-01-01

We propose a random-matrix model for families of elliptic curve L-functions of finite conductor. A repulsion of the critical zeros of these L-functions away from the centre of the critical strip was observed numerically by Miller (2006 Exp. Math. 15 257–79); such behaviour deviates qualitatively from the conjectural limiting distribution of the zeros (for large conductors this distribution is expected to approach the one-level density of eigenvalues of orthogonal matrices after appropriate rescaling). Our purpose here is to provide a random-matrix model for Miller’s surprising discovery. We consider the family of even quadratic twists of a given elliptic curve. The main ingredient in our model is a calculation of the eigenvalue distribution of random orthogonal matrices whose characteristic polynomials are larger than some given value at the symmetry point in the spectra. We call this sub-ensemble of SO(2N) the excised orthogonal ensemble. The sieving-off of matrices with small values of the characteristic polynomial is akin to the discretization of the central values of L-functions implied by the formulae of Waldspurger and Kohnen–Zagier. The cut-off scale appropriate to modelling elliptic curve L-functions is exponentially small relative to the matrix size N. The one-level density of the excised ensemble can be expressed in terms of that of the well-known Jacobi ensemble, enabling the former to be explicitly calculated. It exhibits an exponentially small (on the scale of the mean spacing) hard gap determined by the cut-off value, followed by soft repulsion on a much larger scale. Neither of these features is present in the one-level density of SO(2N). When N → ∞ we recover the limiting orthogonal behaviour. Our results agree qualitatively with Miller’s discrepancy. Choosing the cut-off appropriately gives a model in good quantitative agreement with the number-theoretical data. (paper)

Matrix thermalization

International Nuclear Information System (INIS)

Craps, Ben; Evnin, Oleg; Nguyen, Kévin

2017-01-01

Matrix quantum mechanics offers an attractive environment for discussing gravitational holography, in which both sides of the holographic duality are well-defined. Similarly to higher-dimensional implementations of holography, collapsing shell solutions in the gravitational bulk correspond in this setting to thermalization processes in the dual quantum mechanical theory. We construct an explicit, fully nonlinear supergravity solution describing a generic collapsing dilaton shell, specify the holographic renormalization prescriptions necessary for computing the relevant boundary observables, and apply them to evaluating thermalizing two-point correlation functions in the dual matrix theory.

Matrix thermalization

Science.gov (United States)

Craps, Ben; Evnin, Oleg; Nguyen, Kévin

2017-02-01

Matrix quantum mechanics offers an attractive environment for discussing gravitational holography, in which both sides of the holographic duality are well-defined. Similarly to higher-dimensional implementations of holography, collapsing shell solutions in the gravitational bulk correspond in this setting to thermalization processes in the dual quantum mechanical theory. We construct an explicit, fully nonlinear supergravity solution describing a generic collapsing dilaton shell, specify the holographic renormalization prescriptions necessary for computing the relevant boundary observables, and apply them to evaluating thermalizing two-point correlation functions in the dual matrix theory.

Matrix thermalization

Energy Technology Data Exchange (ETDEWEB)

Craps, Ben [Theoretische Natuurkunde, Vrije Universiteit Brussel (VUB), and International Solvay Institutes, Pleinlaan 2, B-1050 Brussels (Belgium); Evnin, Oleg [Department of Physics, Faculty of Science, Chulalongkorn University, Thanon Phayathai, Pathumwan, Bangkok 10330 (Thailand); Theoretische Natuurkunde, Vrije Universiteit Brussel (VUB), and International Solvay Institutes, Pleinlaan 2, B-1050 Brussels (Belgium); Nguyen, Kévin [Theoretische Natuurkunde, Vrije Universiteit Brussel (VUB), and International Solvay Institutes, Pleinlaan 2, B-1050 Brussels (Belgium)

2017-02-08

Matrix quantum mechanics offers an attractive environment for discussing gravitational holography, in which both sides of the holographic duality are well-defined. Similarly to higher-dimensional implementations of holography, collapsing shell solutions in the gravitational bulk correspond in this setting to thermalization processes in the dual quantum mechanical theory. We construct an explicit, fully nonlinear supergravity solution describing a generic collapsing dilaton shell, specify the holographic renormalization prescriptions necessary for computing the relevant boundary observables, and apply them to evaluating thermalizing two-point correlation functions in the dual matrix theory.

Regularity increases middle latency evoked and late induced beta brain response following proprioceptive stimulation

DEFF Research Database (Denmark)

Arnfred, Sidse M.; Hansen, Lars Kai; Parnas, Josef

2008-01-01

as an indication of increased readiness. This is achieved through detailed analysis of both evoked and induced responses in the time-frequency domain. Electroencephalography in a 64 channels montage was recorded in four-teen healthy subjects. Two paradigms were explored: A Regular alternation between hand......). After initial exploration of the AvVVT and Induced collapsed files of all subjects using two-way factor analyses (Non-Negative Matrix Factorization), further data decomposition was performed in restricted windows of interest (WOI). Main effects of side of stimulation, onset or offset, regularity...

Multi-site and multi-depth in vivo cancer localization enhancement after auto-fluorescence removal

International Nuclear Information System (INIS)

Montcuquet, A.S.; Herve, L.; Navarro, F.; Dinten, J.M.; Mars, J.I.

2011-01-01

Fluorescence imaging in diffusive media locates tumors tagged by injected fluorescent markers in NIR wavelengths. For deep embedded markers, natural auto-fluorescence of tissues comes to be a limiting factor to tumor detection and accurate FDOT reconstructions. A spectroscopic approach coupled with Non-negative Matrix Factorization source separation method is explored to discriminate fluorescence sources according to their fluorescence spectra and remove unwanted auto-fluorescence. We successfully removed auto-fluorescence from acquisitions on living mice with a single subcutaneous tumor or two capillary tubes inserted at different depths. (authors)

NMF on positron emission tomography

DEFF Research Database (Denmark)

Bödvarsson, Bjarni; Hansen, Lars Kai; Svarer, Claus

2007-01-01

In positron emission tomography, kinetic modelling of brain tracer uptake, metabolism or binding requires knowledge of the cerebral input function. Traditionally, this is achieved with arterial blood sampling in the arm or as shown in (Liptrot, M, et al., 2004) by non-invasive K-means clustering....... We propose another method to estimate time-activity curves (TAC) extracted directly from dynamic positron emission tomography (PET) scans by non-negative matrix factorization (NMF). Since the scaling of the basis curves is lost in the NMF the estimated TAC is scaled by a vector alpha which...

Castsearch - Context Based Spoken Document Retrieval

DEFF Research Database (Denmark)

Mølgaard, Lasse Lohilahti; Jørgensen, Kasper Winther; Hansen, Lars Kai

2007-01-01

The paper describes our work on the development of a system for retrieval of relevant stories from broadcast news. The system utilizes a combination of audio processing and text mining. The audio processing consists of a segmentation step that partitions the audio into speech and music. The speech...... is further segmented into speaker segments and then transcribed using an automatic speech recognition system, to yield text input for clustering using non-negative matrix factorization (NMF). We find semantic topics that are used to evaluate the performance for topic detection. Based on these topics we show...

A pseudo-Voigt component model for high-resolution recovery of constituent spectra in Raman spectroscopy

DEFF Research Database (Denmark)

Alstrøm, Tommy Sonne; Schmidt, Mikkel Nørgaard; Rindzevicius, Tomas

2017-01-01

Raman spectroscopy is a well-known analytical technique for identifying and analyzing chemical species. Since Raman scattering is a weak effect, surface-enhanced Raman spectroscopy (SERS) is often employed to amplify the signal. SERS signal surface mapping is a common method for detecting trace...... to directly and reliably identify the Raman modes, with overall performance similar to the state of the art non-negative matrix factorization approach. However, the model provides better interpretation and is a step towards enabling the use of SERS in detection of trace amounts of molecules in real-life...

Dentin matrix degradation by host Matrix Metalloproteinases: inhibition and clinical perspectives towards regeneration.

Directory of Open Access Journals (Sweden)

Catherine eChaussain

2013-11-01

Full Text Available Bacterial enzymes have long been considered solely accountable for the degradation of the dentin matrix during the carious process. However, the emerging literature suggests that host-derived enzymes, and in particular the matrix metalloproteinases (MMPs contained in dentin and saliva can play a major role in this process by their ability to degrade the dentin matrix from within. These findings are important since they open new therapeutic options for caries prevention and treatment. The possibility of using MMP inhibitors to interfere with dentin caries progression is discussed. Furthermore, the potential release of bioactive peptides by the enzymatic cleavage of dentin matrix proteins by MMPs during the carious process is discussed. These peptides, once identified, may constitute promising therapeutical tools for tooth and bone regeneration.

Hartree--Fock density matrix equation

International Nuclear Information System (INIS)

Cohen, L.; Frishberg, C.

1976-01-01

An equation for the Hartree--Fock density matrix is discussed and the possibility of solving this equation directly for the density matrix instead of solving the Hartree--Fock equation for orbitals is considered. Toward that end the density matrix is expanded in a finite basis to obtain the matrix representative equation. The closed shell case is considered. Two numerical schemes are developed and applied to a number of examples. One example is given where the standard orbital method does not converge while the method presented here does

Hacking the Matrix.

Science.gov (United States)

Czerwinski, Michael; Spence, Jason R

2017-01-05

Recently in Nature, Gjorevski et al. (2016) describe a fully defined synthetic hydrogel that mimics the extracellular matrix to support in vitro growth of intestinal stem cells and organoids. The hydrogel allows exquisite control over the chemical and physical in vitro niche and enables identification of regulatory properties of the matrix. Copyright © 2017 Elsevier Inc. All rights reserved.

The chiral Gaussian two-matrix ensemble of real asymmetric matrices

International Nuclear Information System (INIS)

Akemann, G; Phillips, M J; Sommers, H-J

2010-01-01

We solve a family of Gaussian two-matrix models with rectangular N x (N + ν) matrices, having real asymmetric matrix elements and depending on a non-Hermiticity parameter μ. Our model can be thought of as the chiral extension of the real Ginibre ensemble, relevant for Dirac operators in the same symmetry class. It has the property that its eigenvalues are either real, purely imaginary or come in complex conjugate eigenvalue pairs. The eigenvalue joint probability distribution for our model is explicitly computed, leading to a non-Gaussian distribution including K-Bessel functions. All n-point density correlation functions are expressed for finite N in terms of a Pfaffian form. This contains a kernel involving Laguerre polynomials in the complex plane as a building block which was previously computed by the authors. This kernel can be expressed in terms of the kernel for complex non-Hermitian matrices, generalizing the known relation among ensembles of Hermitian random matrices. Compact expressions are given for the density at finite N as an example, as well as its microscopic large-N limits at the origin for fixed ν at strong and weak non-Hermiticity.

Matrix interdiction problem

Energy Technology Data Exchange (ETDEWEB)

Pan, Feng [Los Alamos National Laboratory; Kasiviswanathan, Shiva [Los Alamos National Laboratory

2010-01-01

In the matrix interdiction problem, a real-valued matrix and an integer k is given. The objective is to remove k columns such that the sum over all rows of the maximum entry in each row is minimized. This combinatorial problem is closely related to bipartite network interdiction problem which can be applied to prioritize the border checkpoints in order to minimize the probability that an adversary can successfully cross the border. After introducing the matrix interdiction problem, we will prove the problem is NP-hard, and even NP-hard to approximate with an additive n{gamma} factor for a fixed constant {gamma}. We also present an algorithm for this problem that achieves a factor of (n-k) mUltiplicative approximation ratio.

Matrix transformations and sequence spaces

International Nuclear Information System (INIS)

Nanda, S.

1983-06-01

In most cases the most general linear operator from one sequence space into another is actually given by an infinite matrix and therefore the theory of matrix transformations has always been of great interest in the study of sequence spaces. The study of general theory of matrix transformations was motivated by the special results in summability theory. This paper is a review article which gives almost all known results on matrix transformations. This also suggests a number of open problems for further study and will be very useful for research workers. (author)

An extracellular-matrix-specific GEF-GAP interaction regulates Rho GTPase crosstalk for 3D collagen migration.

Science.gov (United States)

Kutys, Matthew L; Yamada, Kenneth M

2014-09-01

Rho-family GTPases govern distinct types of cell migration on different extracellular matrix proteins in tissue culture or three-dimensional (3D) matrices. We searched for mechanisms selectively regulating 3D cell migration in different matrix environments and discovered a form of Cdc42-RhoA crosstalk governing cell migration through a specific pair of GTPase activator and inhibitor molecules. We first identified βPix, a guanine nucleotide exchange factor (GEF), as a specific regulator of migration in 3D collagen using an affinity-precipitation-based GEF screen. Knockdown of βPix specifically blocks cell migration in fibrillar collagen microenvironments, leading to hyperactive cellular protrusion accompanied by increased collagen matrix contraction. Live FRET imaging and RNAi knockdown linked this βPix knockdown phenotype to loss of polarized Cdc42 but not Rac1 activity, accompanied by enhanced, de-localized RhoA activity. Mechanistically, collagen phospho-regulates βPix, leading to its association with srGAP1, a GTPase-activating protein (GAP), needed to suppress RhoA activity. Our results reveal a matrix-specific pathway controlling migration involving a GEF-GAP interaction of βPix with srGAP1 that is critical for maintaining suppressive crosstalk between Cdc42 and RhoA during 3D collagen migration.

VIP: Vortex Image Processing Package for High-contrast Direct Imaging

Science.gov (United States)

Gomez Gonzalez, Carlos Alberto; Wertz, Olivier; Absil, Olivier; Christiaens, Valentin; Defrère, Denis; Mawet, Dimitri; Milli, Julien; Absil, Pierre-Antoine; Van Droogenbroeck, Marc; Cantalloube, Faustine; Hinz, Philip M.; Skemer, Andrew J.; Karlsson, Mikael; Surdej, Jean

2017-07-01

We present the Vortex Image Processing (VIP) library, a python package dedicated to astronomical high-contrast imaging. Our package relies on the extensive python stack of scientific libraries and aims to provide a flexible framework for high-contrast data and image processing. In this paper, we describe the capabilities of VIP related to processing image sequences acquired using the angular differential imaging (ADI) observing technique. VIP implements functionalities for building high-contrast data processing pipelines, encompassing pre- and post-processing algorithms, potential source position and flux estimation, and sensitivity curve generation. Among the reference point-spread function subtraction techniques for ADI post-processing, VIP includes several flavors of principal component analysis (PCA) based algorithms, such as annular PCA and incremental PCA algorithms capable of processing big datacubes (of several gigabytes) on a computer with limited memory. Also, we present a novel ADI algorithm based on non-negative matrix factorization, which comes from the same family of low-rank matrix approximations as PCA and provides fairly similar results. We showcase the ADI capabilities of the VIP library using a deep sequence on HR 8799 taken with the LBTI/LMIRCam and its recently commissioned L-band vortex coronagraph. Using VIP, we investigated the presence of additional companions around HR 8799 and did not find any significant additional point source beyond the four known planets. VIP is available at http://github.com/vortex-exoplanet/VIP and is accompanied with Jupyter notebook tutorials illustrating the main functionalities of the library.

Quantum mechanics in matrix form

CERN Document Server

Ludyk, Günter

2018-01-01

This book gives an introduction to quantum mechanics with the matrix method. Heisenberg's matrix mechanics is described in detail. The fundamental equations are derived by algebraic methods using matrix calculus. Only a brief description of Schrödinger's wave mechanics is given (in most books exclusively treated), to show their equivalence to Heisenberg's matrix  method. In the first part the historical development of Quantum theory by Planck, Bohr and Sommerfeld is sketched, followed by the ideas and methods of Heisenberg, Born and Jordan. Then Pauli's spin and exclusion principles are treated. Pauli's exclusion principle leads to the structure of atoms. Finally, Dirac´s relativistic quantum mechanics is shortly presented. Matrices and matrix equations are today easy to handle when implementing numerical algorithms using standard software as MAPLE and Mathematica.

Ellipsoids and matrix-valued valuations

OpenAIRE

Ludwig, Monika

2003-01-01

We obtain a classification of Borel measurable, GL(n) covariant, symmetric-matrix-valued valuations on the space of n-dimensional convex polytopes. The only ones turn out to be the moment matrix corresponding to the classical Legendre ellipsoid and the matrix corresponding to the ellipsoid recently discovered by E. Lutwak, D. Yang, and G. Zhang.

Minimal solution for inconsistent singular fuzzy matrix equations

Directory of Open Access Journals (Sweden)

M. Nikuie

2013-10-01

Full Text Available The fuzzy matrix equations $Ailde{X}=ilde{Y}$ is called a singular fuzzy matrix equations while the coefficients matrix of its equivalent crisp matrix equations be a singular matrix. The singular fuzzy matrix equations are divided into two parts: consistent singular matrix equations and inconsistent fuzzy matrix equations. In this paper, the inconsistent singular fuzzy matrix equations is studied and the effect of generalized inverses in finding minimal solution of an inconsistent singular fuzzy matrix equations are investigated.

Drawing a different picture with pencil lead as matrix-assisted laser desorption/ionization matrix for fullerene derivatives.

Science.gov (United States)

Nye, Leanne C; Hungerbühler, Hartmut; Drewello, Thomas

2018-02-01

Inspired by reports on the use of pencil lead as a matrix-assisted laser desorption/ionization matrix, paving the way towards matrix-free matrix-assisted laser desorption/ionization, the present investigation evaluates its usage with organic fullerene derivatives. Currently, this class of compounds is best analysed using the electron transfer matrix trans-2-[3-(4-tert-butylphenyl)-2-methyl-2-propenylidene] malononitrile (DCTB), which was employed as the standard here. The suitability of pencil lead was additionally compared to direct (i.e. no matrix) laser desorption/ionization-mass spectrometry. The use of (DCTB) was identified as the by far gentler method, producing spectra with abundant molecular ion signals and much reduced fragmentation. Analytically, pencil lead was found to be ineffective as a matrix, however, appears to be an extremely easy and inexpensive method for producing sodium and potassium adducts.

Matrix groups for undergraduates

CERN Document Server

Tapp, Kristopher

2005-01-01

Matrix groups touch an enormous spectrum of the mathematical arena. This textbook brings them into the undergraduate curriculum. It makes an excellent one-semester course for students familiar with linear and abstract algebra and prepares them for a graduate course on Lie groups. Matrix Groups for Undergraduates is concrete and example-driven, with geometric motivation and rigorous proofs. The story begins and ends with the rotations of a globe. In between, the author combines rigor and intuition to describe basic objects of Lie theory: Lie algebras, matrix exponentiation, Lie brackets, and maximal tori.

Deviation from bimaximal mixing and leptonic CP phases in S4 family symmetry and generalized CP

International Nuclear Information System (INIS)

Li, Cai-Chang; Ding, Gui-Jun

2015-01-01

The lepton flavor mixing matrix having one row or one column in common with the bimaximal mixing up to permutations is still compatible with the present neutrino oscillation data. We provide a thorough exploration of generating such a mixing matrix from S 4 family symmetry and generalized CP symmetry H CP . Supposing that S 4 ⋊H CP is broken down to Z 2 ST 2 SU ×H CP ν in the neutrino sector and Z 4 TST 2 U ⋊H CP l in the charged lepton sector, one column of the PMNS matrix would be of the form (1/2,1/√2,1/2) T up to permutations, both Dirac CP phase and Majorana CP phases are trivial to accommodate the observed lepton mixing angles. The phenomenological implications of the remnant symmetry K 4 (TST 2 ,T 2 U) ×H CP ν in the neutrino sector and Z 2 SU ×H CP l in the charged lepton sector are studied. One row of PMNS matrix is determined to be (1/2,1/2,−i/√2), and all the three leptonic CP phases can only be trivial to fit the measured values of the mixing angles. Two models based on S 4 family symmetry and generalized CP are constructed to implement these model independent predictions enforced by remnant symmetry. The correct mass hierarchy among the charged leptons is achieved. The vacuum alignment and higher order corrections are discussed.

Random Matrix Theory of the Energy-Level Statistics of Disordered Systems at the Anderson Transition

OpenAIRE

Canali, C. M.

1995-01-01

We consider a family of random matrix ensembles (RME) invariant under similarity transformations and described by the probability density $P({\\bf H})= \\exp[-{\\rm Tr}V({\\bf H})]$. Dyson's mean field theory (MFT) of the corresponding plasma model of eigenvalues is generalized to the case of weak confining potential, $V(\\epsilon)\\sim {A\\over 2}\\ln ^2(\\epsilon)$. The eigenvalue statistics derived from MFT are shown to deviate substantially from the classical Wigner-Dyson statistics when $A

Development of a Java Package for Matrix Programming

OpenAIRE

Lim, Ngee-Peng; Ling, Maurice HT; Lim, Shawn YC; Choi, Ji-Hee; Teo, Henry BK

2003-01-01

We had assembled a Java package, known as MatrixPak, of four classes for the purpose of numerical matrix computation. The classes are matrix, matrix_operations, StrToMatrix, and MatrixToStr; all of which are inherited from java.lang.Object class. Class matrix defines a matrix as a two-dimensional array of float types, and contains the following mathematical methods: transpose, adjoint, determinant, inverse, minor and cofactor. Class matrix_operations contains the following mathematical method...

Studies on the immobilization of simulated HLW in NaTi2(PO4)3 (NTP) matrix

International Nuclear Information System (INIS)

Raja Madhavan, R.; Govindan Kutty, K.V.; Gandhi, A.S.

2015-01-01

Immobilization of high level nuclear waste (HLW) is a big challenge faced by the nuclear industry today. The HLW has to be contained and isolated from the biosphere for geological timescales. NZP family of compounds is very versatile monophasic hosts for HLW immobilization. Their crystal structure can accommodate nearly all the cations known to be present in HLW due to its open structure with voids of different size. In the present study a systematic investigation on NaTi 2 (PO 4 ) 3 belonging to the NZP family; as a potential host for HLW immobilization was carried out. A simulated HLW expected from Fast Breeder Test Reactor, India (FBTR) (150Gwd/T burnup, 1 year cooling) was used. Simulated NTP waste forms with 5, 10, 15 wt. % waste loading were prepared by employing a wet chemical method and characterized. Single phase simulated NTP waste forms with up to 5 wt.% waste loading could be prepared for samples sintered in air and above 5 wt.% waste loading, monazite phase is observed as a minor secondary phase. It was found that when sintering is done in Ar/10%H 2 , NTP matrix accepts up to 10 wt.% waste loading without formation of any second phase. From the SEM studies, it was observed that samples sintered in air as well as Ar/10%H 2 palladium segregated as a metal phase and uniformly distributed throughout the waste matrix. The elemental mapping revealed retention of some of the fission products like Ru, Mo, Cs that are volatile during sintering above 1173 K and are homogenously distributed in the matrix. (author)

A framework for general sparse matrix-matrix multiplication on GPUs and heterogeneous processors

DEFF Research Database (Denmark)

Liu, Weifeng; Vinter, Brian

2015-01-01

General sparse matrix-matrix multiplication (SpGEMM) is a fundamental building block for numerous applications such as algebraic multigrid method (AMG), breadth first search and shortest path problem. Compared to other sparse BLAS routines, an efficient parallel SpGEMM implementation has to handle...... extra irregularity from three aspects: (1) the number of nonzero entries in the resulting sparse matrix is unknown in advance, (2) very expensive parallel insert operations at random positions in the resulting sparse matrix dominate the execution time, and (3) load balancing must account for sparse data...... memory space and efficiently utilizes the very limited on-chip scratchpad memory. Parallel insert operations of the nonzero entries are implemented through the GPU merge path algorithm that is experimentally found to be the fastest GPU merge approach. Load balancing builds on the number of necessary...

The R-matrix theory

International Nuclear Information System (INIS)

Descouvemont, P; Baye, D

2010-01-01

The different facets of the R-matrix method are presented pedagogically in a general framework. Two variants have been developed over the years: (i) The 'calculable' R-matrix method is a calculational tool to derive scattering properties from the Schroedinger equation in a large variety of physical problems. It was developed rather independently in atomic and nuclear physics with too little mutual influence. (ii) The 'phenomenological' R-matrix method is a technique to parametrize various types of cross sections. It was mainly (or uniquely) used in nuclear physics. Both directions are explained by starting from the simple problem of scattering by a potential. They are illustrated by simple examples in nuclear and atomic physics. In addition to elastic scattering, the R-matrix formalism is applied to inelastic and radiative-capture reactions. We also present more recent and more ambitious applications of the theory in nuclear physics.

Moment realizability and the validity of the Navier - Stokes equations for rarefied gas dynamics

International Nuclear Information System (INIS)

Levermore, C.D.; Morokoff, W.J.; Nadiga, B.T.

1998-01-01

We present criteria for monitoring the validity of the Navier - Stokes approximation during the simulation of a rarefied gas. Our approach is based on an underlying kinetic formulation through which one can construct nondimensional non-negative definite matrices from moments of the molecular distribution. We then identify one such 3x3 matrix that can be evaluated intrinsically in the Navier - Stokes approximation. Our criteria are based on deviations of the eigenvalues of this matrix from their equilibrium value of unity. Not being tied to a particular benchmark problem, the resulting criteria are portable and may be applied to any Navier - Stokes simulation. We study its utility here by comparing stationary planar shock profiles computed using the Navier - Stokes equations with those computed using Monte Carlo simulations. copyright 1998 American Institute of Physics

Matrix comparison, Part 2

DEFF Research Database (Denmark)

Schneider, Jesper Wiborg; Borlund, Pia

2007-01-01

The present two-part article introduces matrix comparison as a formal means for evaluation purposes in informetric studies such as cocitation analysis. In the first part, the motivation behind introducing matrix comparison to informetric studies, as well as two important issues influencing such c...

Omentin-1 prevents cartilage matrix destruction by regulating matrix metalloproteinases.

Science.gov (United States)

Li, Zhigang; Liu, Baoyi; Zhao, Dewei; Wang, BenJie; Liu, Yupeng; Zhang, Yao; Li, Borui; Tian, Fengde

2017-08-01

Matrix metalloproteinases (MMPs) play a crucial role in the degradation of the extracellular matrix and pathological progression of osteoarthritis (OA). Omentin-1 is a newly identified anti-inflammatory adipokine. Little information regarding the protective effects of omentin-1 in OA has been reported before. In the current study, our results indicated that omentin-1 suppressed expression of MMP-1, MMP-3, and MMP-13 induced by the proinflammatory cytokine interleukin-1β (IL-1β) at both the mRNA and protein levels in human chondrocytes. Importantly, administration of omentin-1 abolished IL-1β-induced degradation of type II collagen (Col II) and aggrecan, the two major extracellular matrix components in articular cartilage, in a dose-dependent manner. Mechanistically, omentin-1 ameliorated the expression of interferon regulatory factor 1 (IRF-1) by blocking the JAK-2/STAT3 pathway. Our results indicate that omentin-1 may have a potential chondroprotective therapeutic capacity. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Bulk metallic glass matrix composites

International Nuclear Information System (INIS)

Choi-Yim, H.; Johnson, W.L.

1997-01-01

Composites with a bulk metallic glass matrix were synthesized and characterized. This was made possible by the recent development of bulk metallic glasses that exhibit high resistance to crystallization in the undercooled liquid state. In this letter, experimental methods for processing metallic glass composites are introduced. Three different bulk metallic glass forming alloys were used as the matrix materials. Both ceramics and metals were introduced as reinforcement into the metallic glass. The metallic glass matrix remained amorphous after adding up to a 30 vol% fraction of particles or short wires. X-ray diffraction patterns of the composites show only peaks from the second phase particles superimposed on the broad diffuse maxima from the amorphous phase. Optical micrographs reveal uniformly distributed particles in the matrix. The glass transition of the amorphous matrix and the crystallization behavior of the composites were studied by calorimetric methods. copyright 1997 American Institute of Physics

A matrix model for WZW

International Nuclear Information System (INIS)

Dorey, Nick; Tong, David; Turner, Carl

2016-01-01

We study a U(N) gauged matrix quantum mechanics which, in the large N limit, is closely related to the chiral WZW conformal field theory. This manifests itself in two ways. First, we construct the left-moving Kac-Moody algebra from matrix degrees of freedom. Secondly, we compute the partition function of the matrix model in terms of Schur and Kostka polynomials and show that, in the large N limit, it coincides with the partition function of the WZW model. This same matrix model was recently shown to describe non-Abelian quantum Hall states and the relationship to the WZW model can be understood in this framework.

On Chern-Simons Matrix Models

CERN Document Server

Garoufalidis, S; Garoufalidis, Stavros; Marino, Marcos

2006-01-01

The contribution of reducible connections to the U(N) Chern-Simons invariant of a Seifert manifold $M$ can be expressed in some cases in terms of matrix integrals. We show that the U(N) evaluation of the LMO invariant of any rational homology sphere admits a matrix model representation which agrees with the Chern-Simons matrix integral for Seifert spheres and the trivial connection.

Characterization and control of the fiber-matrix interface in ceramic matrix composites

Energy Technology Data Exchange (ETDEWEB)

Lowden, R.A.

1989-03-01

Fiber-reinforced SiC composites fabricated by thermal-gradient forced-flow chemical-vapor infiltration (FCVI) have exhibited both composite (toughened) and brittle behavior during mechanical property evaluation. Detailed analysis of the fiber-matrix interface revealed that a silica layer on the surface of Nicalon Si-C-O fibers tightly bonds the fiber to the matrix. The strongly bonded fiber and matrix, combined with the reduction in the strength of the fibers that occurs during processing, resulted in the observed brittle behavior. The mechanical behavior of Nicalon/SiC composites has been improved by applying thin coatings (silicon carbide, boron, boron nitride, molybdenum, carbon) to the fibers, prior to densification, to control the interfacial bond. Varying degrees of bonding have been achieved with different coating materials and film thicknesses. Fiber-matrix bond strengths have been quantitatively evaluated using an indentation method and a simple tensile test. The effects of bonding and friction on the mechanical behavior of this composite system have been investigated. 167 refs., 59 figs., 18 tabs.

Investigation of the Matrix Metalloproteinase-2 Gene in Patients with Non-Syndromic Mitral Valve Prolapse

Directory of Open Access Journals (Sweden)

Maëlle Perrocheau

2015-07-01

Full Text Available Non-syndromic mitral valve prolapse (MVP is a common degenerative valvulopathy, predisposing to arrhythmia and sudden death. The etiology of MVP is suspected to be under genetic control, as supported by familial cases and its manifestation in genetic syndrome (e.g., Marfan syndrome. One candidate etiological mechanism is a perturbation of the extracellular matrix (ECM remodeling of the valve. To test this hypothesis, we assessed the role of genetic variants in the matrix metalloproteinase 2 gene (MMP2 known to regulate the ECM turnover by direct degradation of proteins and for which transgenic mice develop MVP. Direct sequencing of exons of MMP2 in 47 unrelated patients and segregation analyses in families did not reveal any causative mutation. We studied eight common single nucleotide polymorphisms (TagSNPs, which summarize the genetic information at the MMP2 locus. The association study in two case controls sets (NCases = 1073 and NControls = 1635 provided suggestive evidence for the association of rs1556888 located downstream MMP2 with the risk of MVP, especially in patients with the fibroelastic defiency form. Our study does not support the contribution of MMP2 rare variation in the etiology to MVP in humans, though further genetic and molecular investigation is required to confirm our current suggestive association of one common variant.

QUEUEING DISCIPLINES BASED ON PRIORITY MATRIX

Directory of Open Access Journals (Sweden)

Taufik I. Aliev

2014-11-01

Full Text Available The paper deals with queueing disciplines for demands of general type in queueing systems with multivendor load. A priority matrix is proposed to be used for the purpose of mathematical description of such disciplines, which represents the priority type (preemptive priority, not preemptive priority or no priority between any two demands classes. Having an intuitive and simple way of priority assignment, such description gives mathematical dependencies of system operation characteristics on its parameters. Requirements for priority matrix construction are formulated and the notion of canonical priority matrix is given. It is shown that not every matrix, constructed in accordance with such requirements, is correct. The notion of incorrect priority matrix is illustrated by an example, and it is shown that such matrixes do not ensure any unambiguousness and determinacy in design of algorithm, which realizes corresponding queueing discipline. Rules governing construction of correct matrixes are given for canonical priority matrixes. Residence time for demands of different classes in system, which is the sum of waiting time and service time, is considered as one of the most important characteristics. By introducing extra event method Laplace transforms for these characteristics are obtained, and mathematical dependencies are derived on their basis for calculation of two first moments for corresponding characteristics of demands queueing

Use and abuse of the Fisher information matrix in the assessment of gravitational-wave parameter-estimation prospects

International Nuclear Information System (INIS)

Vallisneri, Michele

2008-01-01

The Fisher-matrix formalism is used routinely in the literature on gravitational-wave detection to characterize the parameter-estimation performance of gravitational-wave measurements, given parametrized models of the waveforms, and assuming detector noise of known colored Gaussian distribution. Unfortunately, the Fisher matrix can be a poor predictor of the amount of information obtained from typical observations, especially for waveforms with several parameters and relatively low expected signal-to-noise ratios (SNR), or for waveforms depending weakly on one or more parameters, when their priors are not taken into proper consideration. In this paper I discuss these pitfalls; show how they occur, even for relatively strong signals, with a commonly used template family for binary-inspiral waveforms; and describe practical recipes to recognize them and cope with them. Specifically, I answer the following questions: (i) What is the significance of (quasi-)singular Fisher matrices, and how must we deal with them? (ii) When is it necessary to take into account prior probability distributions for the source parameters? (iii) When is the signal-to-noise ratio high enough to believe the Fisher-matrix result? In addition, I provide general expressions for the higher-order, beyond-Fisher-matrix terms in the 1/SNR expansions for the expected parameter accuracies

Sirtuin 6 prevents matrix degradation through inhibition of the NF-κB pathway in intervertebral disc degeneration

Energy Technology Data Exchange (ETDEWEB)

Kang, Liang [Department of Orthopaedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022 (China); Hu, Jia [Department of Nuclear Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022 (China); Weng, Yuxiong [Department of Hand Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022 (China); Jia, Jie [Department of Orthopaedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022 (China); Zhang, Yukun, E-mail: zhangyukuncom@126.com [Department of Orthopaedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022 (China)

2017-03-15

Intervertebral disc degeneration (IDD) is marked by imbalanced metabolism of the extracellular matrix (ECM) in the nucleus pulposus (NP) of intervertebral discs. This study aimed to determine whether sirtuin 6 (SIRT6), a member of the sirtuin family of nicotinamide adenine dinucleotide-dependent deacetylases, protects the NP from ECM degradation in IDD. Our study showed that expression of SIRT6 markedly decreased during IDD progression. Overexpression of wild-type SIRT6, but not a catalytically inactive mutant, prevented IL-1β-induced NP ECM degradation. SIRT6 depletion by RNA interference in NP cells caused ECM degradation. Moreover, SIRT6 physically interacted with nuclear factor-κB (NF-κB) catalytic subunit p65, transcriptional activity of which was significantly suppressed by SIRT6 overexpression. These results suggest that SIRT6 prevented NP ECM degradation in vitro via inhibiting NF-κB-dependent transcriptional activity and that this effect depended on its deacetylase activity. - Highlights: • SIRT6 expression is decreased in degenerative nucleus pulposus (NP) tissues. • SIRT6 overexpression lowers IL-1β-induced matrix degradation of NP. • SIRT6 inhibition induces matrix degradation of NP. • SIRT6 prevents matrix degradation of NP via the NF-κB signaling pathway.

Sirtuin 6 prevents matrix degradation through inhibition of the NF-κB pathway in intervertebral disc degeneration

International Nuclear Information System (INIS)

Kang, Liang; Hu, Jia; Weng, Yuxiong; Jia, Jie; Zhang, Yukun

2017-01-01

Intervertebral disc degeneration (IDD) is marked by imbalanced metabolism of the extracellular matrix (ECM) in the nucleus pulposus (NP) of intervertebral discs. This study aimed to determine whether sirtuin 6 (SIRT6), a member of the sirtuin family of nicotinamide adenine dinucleotide-dependent deacetylases, protects the NP from ECM degradation in IDD. Our study showed that expression of SIRT6 markedly decreased during IDD progression. Overexpression of wild-type SIRT6, but not a catalytically inactive mutant, prevented IL-1β-induced NP ECM degradation. SIRT6 depletion by RNA interference in NP cells caused ECM degradation. Moreover, SIRT6 physically interacted with nuclear factor-κB (NF-κB) catalytic subunit p65, transcriptional activity of which was significantly suppressed by SIRT6 overexpression. These results suggest that SIRT6 prevented NP ECM degradation in vitro via inhibiting NF-κB-dependent transcriptional activity and that this effect depended on its deacetylase activity. - Highlights: • SIRT6 expression is decreased in degenerative nucleus pulposus (NP) tissues. • SIRT6 overexpression lowers IL-1β-induced matrix degradation of NP. • SIRT6 inhibition induces matrix degradation of NP. • SIRT6 prevents matrix degradation of NP via the NF-κB signaling pathway.

Machining of Metal Matrix Composites

CERN Document Server

2012-01-01

Machining of Metal Matrix Composites provides the fundamentals and recent advances in the study of machining of metal matrix composites (MMCs). Each chapter is written by an international expert in this important field of research. Machining of Metal Matrix Composites gives the reader information on machining of MMCs with a special emphasis on aluminium matrix composites. Chapter 1 provides the mechanics and modelling of chip formation for traditional machining processes. Chapter 2 is dedicated to surface integrity when machining MMCs. Chapter 3 describes the machinability aspects of MMCs. Chapter 4 contains information on traditional machining processes and Chapter 5 is dedicated to the grinding of MMCs. Chapter 6 describes the dry cutting of MMCs with SiC particulate reinforcement. Finally, Chapter 7 is dedicated to computational methods and optimization in the machining of MMCs. Machining of Metal Matrix Composites can serve as a useful reference for academics, manufacturing and materials researchers, manu...

Unitarity of CKM Matrix

CERN Document Server

Saleem, M

2002-01-01

The Unitarity of the CKM matrix is examined in the light of the latest available accurate data. The analysis shows that a conclusive result cannot be derived at present. Only more precise data can determine whether the CKM matrix opens new vistas beyond the standard model or not.

Occupational Therapy in Multidisciplinary Residency in Family and Community Health

Directory of Open Access Journals (Sweden)

Luzianne Feijó Alexandre Paiva

2013-12-01

Full Text Available In this study, we report the experiences of occupational therapist during the Multidisciplinary Residency Program in Family and Community Health in Fortaleza, Ceará state, Brazil. With the creation of the Support Center for Family Health – NASF, occupational therapists began to participate more effectively in the Family Health Strategy of the Brazilian National Health System. Given this rocess, the category, which historically has trained its professionals following the biomedical model, is faced with the challenge to build a new field of knowledge. Objective: To analyze the inclusion of occupational therapy in the Family Health Strategy within the scope of Multidisciplinary Residency. Methodology: This is a descriptive study of qualitative approach, which was based on the experience of four occupational therapy resident students, performed through the documental analysis of field diaries, scientific papers, and case studies produced between 2009 and 2011. Results: The occupational therapists as well as the other NASF professionals operated the logic of Matrix Support to the Family Health teams, sharing their knowledge and assisting in resolving complex cases of the families, groups, and communities served. In this context, we found people with different relationships with their doings and a reduced repertoire of activities. The occupational therapists invested in the creation or consolidation of groups in the Family Health Centers and in the territory, which also stood as living and socializing spaces, focusing on prevention and health promotion.

Characterization of the astacin family of metalloproteases in C. elegans

Directory of Open Access Journals (Sweden)

Zapf Richard

2010-01-01

Full Text Available Abstract Background Astacins are a large family of zinc metalloproteases found in bacteria and animals. They have diverse roles ranging from digestion of food to processing of extracellular matrix components. The C. elegans genome contains an unusually large number of astacins, of which the majority have not been functionally characterized yet. Results We analyzed the expression pattern of previously uncharacterized members of the astacin family to try and obtain clues to potential functions. Prominent sites of expression for many members of this family are the hypodermis, the alimentary system and several specialized cells including sensory sheath and sockets cells, which are located at openings in the body wall. We isolated mutants affecting representative members of the various subfamilies. Mutants in nas-5, nas-21 and nas-39 (the BMP-1/Tolloid homologue are viable and have no apparent phenotypic defects. Mutants in nas-6 and nas-6; nas-7 double mutants are slow growing and have defects in the grinder of the pharynx, a cuticular structure important for food processing. Conclusions Expression data and phenotypic characterization of selected family members suggest a diversity of functions for members of the astacin family in nematodes. In part this might be due to extracellular structures unique to nematodes.

2016 MATRIX annals

CERN Document Server

Praeger, Cheryl; Tao, Terence

2018-01-01

MATRIX is Australia’s international, residential mathematical research institute. It facilitates new collaborations and mathematical advances through intensive residential research programs, each lasting 1-4 weeks. This book is a scientific record of the five programs held at MATRIX in its first year, 2016: Higher Structures in Geometry and Physics (Chapters 1-5 and 18-21); Winter of Disconnectedness (Chapter 6 and 22-26); Approximation and Optimisation (Chapters 7-8); Refining C*-Algebraic Invariants for Dynamics using KK-theory (Chapters 9-13); Interactions between Topological Recursion, Modularity, Quantum Invariants and Low-dimensional Topology (Chapters 14-17 and 27). The MATRIX Scientific Committee selected these programs based on their scientific excellence and the participation rate of high-profile international participants. Each program included ample unstructured time to encourage collaborative research; some of the longer programs also included an embedded conference or lecture series. The artic...

Dynamic Matrix Rank

DEFF Research Database (Denmark)

Frandsen, Gudmund Skovbjerg; Frandsen, Peter Frands

2009-01-01

We consider maintaining information about the rank of a matrix under changes of the entries. For n×n matrices, we show an upper bound of O(n1.575) arithmetic operations and a lower bound of Ω(n) arithmetic operations per element change. The upper bound is valid when changing up to O(n0.575) entries...... in a single column of the matrix. We also give an algorithm that maintains the rank using O(n2) arithmetic operations per rank one update. These bounds appear to be the first nontrivial bounds for the problem. The upper bounds are valid for arbitrary fields, whereas the lower bound is valid for algebraically...... closed fields. The upper bound for element updates uses fast rectangular matrix multiplication, and the lower bound involves further development of an earlier technique for proving lower bounds for dynamic computation of rational functions....

MATLAB matrix algebra

CERN Document Server

Pérez López, César

2014-01-01

MATLAB is a high-level language and environment for numerical computation, visualization, and programming. Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming languages, such as C/C++ or Java. MATLAB Matrix Algebra introduces you to the MATLAB language with practical hands-on instructions and results, allowing you to quickly achieve your goals. Starting with a look at symbolic and numeric variables, with an emphasis on vector and matrix variables, you will go on to examine functions and operations that support vectors and matrices as arguments, including those based on analytic parent functions. Computational methods for finding eigenvalues and eigenvectors of matrices are detailed, leading to various matrix decompositions. Applications such as change of bases, the classification of quadratic forms and ...

Lax representations for matrix short pulse equations

Science.gov (United States)

Popowicz, Z.

2017-10-01

The Lax representation for different matrix generalizations of Short Pulse Equations (SPEs) is considered. The four-dimensional Lax representations of four-component Matsuno, Feng, and Dimakis-Müller-Hoissen-Matsuno equations are obtained. The four-component Feng system is defined by generalization of the two-dimensional Lax representation to the four-component case. This system reduces to the original Feng equation, to the two-component Matsuno equation, or to the Yao-Zang equation. The three-component version of the Feng equation is presented. The four-component version of the Matsuno equation with its Lax representation is given. This equation reduces the new two-component Feng system. The two-component Dimakis-Müller-Hoissen-Matsuno equations are generalized to the four-parameter family of the four-component SPE. The bi-Hamiltonian structure of this generalization, for special values of parameters, is defined. This four-component SPE in special cases reduces to the new two-component SPE.

Patience of matrix games

DEFF Research Database (Denmark)

Hansen, Kristoffer Arnsfelt; Ibsen-Jensen, Rasmus; Podolskii, Vladimir V.

2013-01-01

For matrix games we study how small nonzero probability must be used in optimal strategies. We show that for image win–lose–draw games (i.e. image matrix games) nonzero probabilities smaller than image are never needed. We also construct an explicit image win–lose game such that the unique optimal...

Optimized Projection Matrix for Compressive Sensing

Directory of Open Access Journals (Sweden)

Jianping Xu

2010-01-01

Full Text Available Compressive sensing (CS is mainly concerned with low-coherence pairs, since the number of samples needed to recover the signal is proportional to the mutual coherence between projection matrix and sparsifying matrix. Until now, papers on CS always assume the projection matrix to be a random matrix. In this paper, aiming at minimizing the mutual coherence, a method is proposed to optimize the projection matrix. This method is based on equiangular tight frame (ETF design because an ETF has minimum coherence. It is impossible to solve the problem exactly because of the complexity. Therefore, an alternating minimization type method is used to find a feasible solution. The optimally designed projection matrix can further reduce the necessary number of samples for recovery or improve the recovery accuracy. The proposed method demonstrates better performance than conventional optimization methods, which brings benefits to both basis pursuit and orthogonal matching pursuit.

Newborn screening by matrix-assisted laser desorption/ionization mass spectrometry based on parylene-matrix chip.

Science.gov (United States)

Kim, Jo-Il; Noh, Joo-Yoon; Kim, Mira; Park, Jong-Min; Song, Hyun-Woo; Kang, Min-Jung; Pyun, Jae-Chul

2017-08-01

Newborn screening for diagnosis of phenylketonuria, homocystinuria, and maple syrup urine disease have been conducted by analyzing the concentration of target amino acids using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-ToF MS) based on parylene-matrix chip. Parylene-matrix chip was applied to MALDI-ToF MS analysis reducing the matrix peaks significantly at low mass-to-charge ratio range (m/z  0.98) and the LODs were ranging from 9.0 to 22.9 μg/mL. Effect of proteins in serum was estimated by comparing MALDI-ToF mass spectra of amino acids-spiked serum before and after the methanol extraction. Interference of other amino acids on analysis of target analyte was determined to be insignificant. From these results, MALDI-ToF MS based on parylene-matrix chip could be applicable to medical diagnosis of neonatal metabolic disorders. Copyright © 2017 Elsevier Inc. All rights reserved.

On matrix fractional differential equations

OpenAIRE

Adem Kılıçman; Wasan Ajeel Ahmood

2017-01-01

The aim of this article is to study the matrix fractional differential equations and to find the exact solution for system of matrix fractional differential equations in terms of Riemann–Liouville using Laplace transform method and convolution product to the Riemann–Liouville fractional of matrices. Also, we show the theorem of non-homogeneous matrix fractional partial differential equation with some illustrative examples to demonstrate the effectiveness of the new methodology. The main objec...

Immobilization of cellulase using porous polymer matrix

International Nuclear Information System (INIS)

Kumakura, M.; Kaetsu, I.

1984-01-01

A new method is discussed for the immobilization of cellulase using porous polymer matrices, which were obtained by radiation polymerization of hydrophilic monomers. In this method, the immobilized enzyme matrix was prepared by enzyme absorbtion in the porous polymer matrix and drying treatment. The enzyme activity of the immobilized enzyme matrix varied with monomer concentration, cooling rate of the monomer solution, and hydrophilicity of the polymer matrix, takinn the change of the nature of the porous structure in the polymer matrix. The leakage of the enzymes from the polymer matrix was not observed in the repeated batch enzyme reactions

Biochemical and biomechanical properties of the pacemaking sinoatrial node extracellular matrix are distinct from contractile left ventricular matrix.

Directory of Open Access Journals (Sweden)

Jessica M Gluck

Full Text Available Extracellular matrix plays a role in differentiation and phenotype development of its resident cells. Although cardiac extracellular matrix from the contractile tissues has been studied and utilized in tissue engineering, extracellular matrix properties of the pacemaking sinoatrial node are largely unknown. In this study, the biomechanical properties and biochemical composition and distribution of extracellular matrix in the sinoatrial node were investigated relative to the left ventricle. Extracellular matrix of the sinoatrial node was found to be overall stiffer than that of the left ventricle and highly heterogeneous with interstitial regions composed of predominantly fibrillar collagens and rich in elastin. The extracellular matrix protein distribution suggests that resident pacemaking cardiomyocytes are enclosed in fibrillar collagens that can withstand greater tensile strength while the surrounding elastin-rich regions may undergo deformation to reduce the mechanical strain in these cells. Moreover, basement membrane-associated adhesion proteins that are ligands for integrins were of low abundance in the sinoatrial node, which may decrease force transduction in the pacemaking cardiomyocytes. In contrast to extracellular matrix of the left ventricle, extracellular matrix of the sinoatrial node may reduce mechanical strain and force transduction in pacemaking cardiomyocytes. These findings provide the criteria for a suitable matrix scaffold for engineering biopacemakers.

The effect of tomatine on metastasis related matrix metalloproteinase (MMP) activities in breast cancer cell model.

Science.gov (United States)

Yelken, Besra Özmen; Balcı, Tuğçe; Süslüer, Sunde Yılmaz; Kayabaşı, Çağla; Avcı, Çığır Biray; Kırmızıbayrak, Petek Ballar; Gündüz, Cumhur

2017-09-05

Breast cancer is one of the most common malignancies in women and metastasis is the cause of morbidity and mortality in patients. In the development of metastasis, the matrix metalloproteinase (MMP) family has a very important role in tumor development. MMP-2 and MMP-9 work together for extracellular matrix (ECM) cleavage to increase migration. Tomatine is a secondary metabolite that has a natural defense role against plants, fungi, viruses and bacteria that are synthesized from tomato. In additıon, tomatine is also known that it breaks down the cell membrane and is a strong inhibitor in human cancer cells. In this study, it was aimed to evaluate the effect of tomatine on cytotoxicity, apoptosis and matrix metalloproteinase inhibition in MCF-7 cell lines. Human breast cancer cell line (MCF-7) was used as a cell line. In MCF-7 cells, the IC 50 dose of tomatine was determined to be 7.07μM. According to the control cells, apoptosis increased 3.4 fold in 48thh. Activation of MMP-2, MMP-9 and MMP-9\\NGAL has been shown to decrease significantly in cells treated with tomatine by gelatin zymography compared to the control. As a result, matrix metalloproteinase activity and cell proliferation were suppressed by tomatine and this may provide support in treatment methods. Copyright © 2017 Elsevier B.V. All rights reserved.

Family in historical and regional perspective

Directory of Open Access Journals (Sweden)

Tripković Gordana D.

2002-01-01

Full Text Available In this article author gives try to provide a frame suitable for researches of regional and multicultural characteristics of family, specially in Vojvodina region. Starting with the thesis that there is no perfect analytical model to be applied in investigation of regionalization and multiculturality, for the gap between monocultural and multicultural epistemology could not be bridged over, author is paying attention to the opportunities for regionalization to pervert in regionalism in the sense of ideology and policy that neglect specific regional needs of family. This dispels a negative consequences concerning the self development of the family as a very reason for regionalization to be accomplished. In spite of attractive ideas that regionalization is addressed to, regionalization of this kind realizes on the matrix above, of deciding 'in the people's name'. In this fashion regionalization is followed with the violence and confrontations as probable outcomes of changes within multicultural society. Exaggeration in emphasizing of differences. a s well as its neglecting, would cause more or less open confrontations and thus provide the causes of dissolution of the communities. In this context main problem is how family could retained its stability if it persists under the pressure of contrary forces concerning identity. This would be resolved only if identity is conceived as an open complex and ever unfinished on lay - in endless process of building. Regionalization in this sense of the term could be perceived as a defining of the proper game rules as well as it forceful adjustment and completion.

Matrix theory selected topics and useful results

CERN Document Server

Mehta, Madan Lal

1989-01-01

Matrices and operations on matrices ; determinants ; elementary operations on matrices (continued) ; eigenvalues and eigenvectors, diagonalization of normal matrices ; functions of a matrix ; positive definiteness, various polar forms of a matrix ; special matrices ; matrices with quaternion elements ; inequalities ; generalised inverse of a matrix ; domain of values of a matrix, location and dispersion of eigenvalues ; symmetric functions ; integration over matrix variables ; permanents of doubly stochastic matrices ; infinite matrices ; Alexander matrices, knot polynomials, torsion numbers.

A Rhizobium leguminosarum CHDL- (Cadherin-Like-) Lectin Participates in Assembly and Remodeling of the Biofilm Matrix

DEFF Research Database (Denmark)

Vozza, Nicolás F.; Abdian, Patricia L; Russo, Daniela M

2016-01-01

In natural environments most bacteria live in multicellular structures called biofilms. These cell aggregates are enclosed in a self-produced polymeric extracellular matrix, which protects the cells, provides mechanical stability and mediates cellular cohesion and adhesion to surfaces. Although...... important advances were made in the identification of the genetic and extracellular factors required for biofilm formation, the mechanisms leading to biofilm matrix assembly, and the roles of extracellular proteins in these processes are still poorly understood. The symbiont Rhizobium leguminosarum requires...... the synthesis of the acidic exopolysaccharide and the PrsDE secretion system to develop a mature biofilm. PrsDE is responsible for the secretion of the Rap family of proteins that share one or two Ra/CHDL (cadherin-like-) domains. RapA2 is a calcium-dependent lectin with a cadherin-like β sheet structure...

Random Correlation Matrix and De-Noising

OpenAIRE

Ken-ichi Mitsui; Yoshio Tabata

2006-01-01

In Finance, the modeling of a correlation matrix is one of the important problems. In particular, the correlation matrix obtained from market data has the noise. Here we apply the de-noising processing based on the wavelet analysis to the noisy correlation matrix, which is generated by a parametric function with random parameters. First of all, we show that two properties, i.e. symmetry and ones of all diagonal elements, of the correlation matrix preserve via the de-noising processing and the...

Matrix algebra for higher order moments

NARCIS (Netherlands)

Meijer, Erik

2005-01-01

A large part of statistics is devoted to the estimation of models from the sample covariance matrix. The development of the statistical theory and estimators has been greatly facilitated by the introduction of special matrices, such as the commutation matrix and the duplication matrix, and the

Symmetries and Interactions in Matrix String Theory

NARCIS (Netherlands)

Hacquebord, F.H.

1999-01-01

This PhD-thesis reviews matrix string theory and recent developments therein. The emphasis is put on symmetries, interactions and scattering processes in the matrix model. We start with an introduction to matrix string theory and a review of the orbifold model that flows out of matrix string theory

Phenomenology of the CKM matrix

International Nuclear Information System (INIS)

Nir, Y.

1989-01-01

The way in which an exact determination of the CKM matrix elements tests the standard Model is demonstrated by a two-generation example. The determination of matrix elements from meson semileptonic decays is explained, with an emphasis on the respective reliability of quark level and meson level calculations. The assumptions involved in the use of loop processes are described. Finally, the state of the art of the knowledge of the CKM matrix is presented. 19 refs., 2 figs

HABP2 p.G534E variant in patients with family history of thyroid and breast cancer

DEFF Research Database (Denmark)

Pinheiro, Maísa; Drigo, Sandra Aparecida; Tonhosolo, Renata

2017-01-01

Familial Papillary Thyroid Carcinoma (PTC) has been described as a hereditary predisposition cancer syndrome associated with mutations in candidate genes including HABP2. Two of 20 probands from families with history of PTC and breast carcinoma (BC) were evaluated by whole exome sequencing (WES...... familial PTC cases. Genes potentially associated with deregulation of the extracellular matrix organization pathway (CTSB, TNXB, COL4A3, COL16A1, COL24A1, COL5A2, NID1, LOXL2, MMP11, TRIM24 and MUSK) and DNA repair function (NBN and MSH2) were detected by WES, suggesting that other cancer-associated genes...

Basic matrix algebra and transistor circuits

CERN Document Server

Zelinger, G

1963-01-01

Basic Matrix Algebra and Transistor Circuits deals with mastering the techniques of matrix algebra for application in transistors. This book attempts to unify fundamental subjects, such as matrix algebra, four-terminal network theory, transistor equivalent circuits, and pertinent design matters. Part I of this book focuses on basic matrix algebra of four-terminal networks, with descriptions of the different systems of matrices. This part also discusses both simple and complex network configurations and their associated transmission. This discussion is followed by the alternative methods of de

Numerical study on optimal Stirling engine regenerator matrix designs taking into account the effects of matrix temperature oscillations

International Nuclear Information System (INIS)

Andersen, Stig Kildegard; Carlsen, Henrik; Thomsen, Per Grove

2006-01-01

A new regenerator matrix design that improves the efficiency of a Stirling engine has been developed in a numerical study of the existing SM5 Stirling engine. A new, detailed, one-dimensional Stirling engine model that delivers results in good agreement with experimental data was used for mapping the performance of the engine, for mapping the effects of regenerator matrix temperature oscillations, and for optimising the regenerator design. The regenerator matrix temperatures were found to oscillate in two modes. The first mode was oscillation of a nearly linear axial matrix temperature profile while the second mode bended the ends of the axial matrix temperature profile when gas flowed into the regenerator with a temperature significantly different from the matrix temperature. The first mode of oscillation improved the efficiency of the engine but the second mode reduced both the work output and efficiency of the engine. A new regenerator with three differently designed matrix sections that amplified the first mode of oscillation and reduced the second improved the efficiency of the engine from the current 32.9 to 33.2% with a 3% decrease in power output. An efficiency of 33.0% was achievable with uniform regenerator matrix properties

Family Structure and Family Processes in Mexican American Families

OpenAIRE

Zeiders, Katharine H.; Roosa, Mark W.; Tein, Jenn-Yun

2011-01-01

Despite increases in single-parent families among Mexican Americans (MA), few studies have examined the association of family structure and family adjustment. Utilizing a diverse sample of 738 Mexican American families (21.7% single parent), the current study examined differences across family structure on early adolescent outcomes, family functioning, and parent-child relationship variables. Results revealed that early adolescents in single parent families reported greater school misconduct,...

Information matrix estimation procedures for cognitive diagnostic models.

Science.gov (United States)

Liu, Yanlou; Xin, Tao; Andersson, Björn; Tian, Wei

2018-03-06

Two new methods to estimate the asymptotic covariance matrix for marginal maximum likelihood estimation of cognitive diagnosis models (CDMs), the inverse of the observed information matrix and the sandwich-type estimator, are introduced. Unlike several previous covariance matrix estimators, the new methods take into account both the item and structural parameters. The relationships between the observed information matrix, the empirical cross-product information matrix, the sandwich-type covariance matrix and the two approaches proposed by de la Torre (2009, J. Educ. Behav. Stat., 34, 115) are discussed. Simulation results show that, for a correctly specified CDM and Q-matrix or with a slightly misspecified probability model, the observed information matrix and the sandwich-type covariance matrix exhibit good performance with respect to providing consistent standard errors of item parameter estimates. However, with substantial model misspecification only the sandwich-type covariance matrix exhibits robust performance. © 2018 The British Psychological Society.

Fluoride-Salt-Cooled High-Temperature Reactor (FHR) with Silicon-Carbide-Matrix Coated-Particle Fuel

International Nuclear Information System (INIS)

Forsberg, C. W.; Snead, Lance Lewis; Katoh, Yutai

2012-01-01

The FHR is a new reactor concept that uses coated-particle fuel and a low-pressure liquid-salt coolant. Its neutronics are similar to a high-temperature gas-cooled reactor (HTGR). The power density is 5 to 10 times higher because of the superior cooling properties of liquids versus gases. The leading candidate coolant salt is a mixture of 7 LiF and BeF 2 (FLiBe) possessing a boiling point above 1300 C and the figure of merit ρC p (volumetric heat capacity) for the salt slightly superior to water. Studies are underway to define a near-term base-line concept while understanding longer-term options. Near-term options use graphite-matrix coated-particle fuel where the graphite is both a structural component and the primary neutron moderator. It is the same basic fuel used in HTGRs. The fuel can take several geometric forms with a pebble bed being the leading contender. Recent work on silicon-carbide-matrix (SiCm) coated-particle fuel may create a second longer-term fuel option. SiCm coated-particle fuels are currently being investigated for use in light-water reactors. The replacement of the graphite matrix with a SiCm creates a new family of fuels. The first motivation behind the effort is to take advantage of the superior radiation resistance of SiC compared to graphite in order to provide a stable matrix for hosting coated fuel particles. The second motivation is a much more rugged fuel under accident, repository, and other conditions.

T2 and T2* mapping in patients after matrix-associated autologous chondrocyte transplantation: initial results on clinical use with 3.0-Tesla MRI

International Nuclear Information System (INIS)

Welsch, Goetz H.; Trattnig, Siegfried; Quirbach, Sebastian; Hughes, Timothy; Olk, Alexander; Blanke, Matthias; Marlovits, Stefan; Mamisch, Tallal C.

2010-01-01

To use T2 and T2* mapping in patients after matrix-associated autologous chondrocyte transplantation (MACT) of the knee, and to compare and correlate both methodologies. 3.0-Tesla MRI was performed on 30 patients (34.6 ± 9.9 years) with a follow-up period of 28.1 ± 18.8 months after MACT. Multi-echo, spin-echo-based T2 mapping using six echoes and gradient-echo-based T2* mapping using six echoes were prepared. T2 and T2* maps were obtained using a pixel-wise, mono-exponential, non-negative least-squares fit analysis. Region-of-interest analysis was performed for mean (full-thickness) as well as deep and superficial aspects of the cartilage repair tissue and control cartilage sites. Mean T2 values (ms) were comparable for the control cartilage (53.4 ± 11.7) and the repair tissue (55.5 ± 11.6) (p > 0.05). Mean T2* values (ms) for control cartilage (30.9 ± 6.6) were significantly higher than those of the repair tissue (24.5 ± 8.1) (p < 0.001). Zonal stratification was more pronounced for T2* than for T2. The correlation between T2 and T2* was highly significant (p < 0.001), with a Pearson coefficient between 0.276 and 0.433. T2 and T2* relaxation time measurements in the evaluation of cartilage repair tissue and its zonal variation show promising results, although the properties visualised by T2 and T2* may differ. (orig.)

Standard Errors for Matrix Correlations.

Science.gov (United States)

Ogasawara, Haruhiko

1999-01-01

Derives the asymptotic standard errors and intercorrelations for several matrix correlations assuming multivariate normality for manifest variables and derives the asymptotic standard errors of the matrix correlations for two factor-loading matrices. (SLD)

Form of multicomponent Fickian diffusion coefficients matrix

International Nuclear Information System (INIS)

Wambui Mutoru, J.; Firoozabadi, Abbas

2011-01-01

Highlights: → Irreversible thermodynamics establishes form of multicomponent diffusion coefficients. → Phenomenological coefficients and thermodynamic factors affect sign of diffusion coefficients. → Negative diagonal elements of diffusion coefficients matrix can occur in non-ideal mixtures. → Eigenvalues of the matrix of Fickian diffusion coefficients may not be all real. - Abstract: The form of multicomponent Fickian diffusion coefficients matrix in thermodynamically stable mixtures is established based on the form of phenomenological coefficients and thermodynamic factors. While phenomenological coefficients form a symmetric positive definite matrix, the determinant of thermodynamic factors matrix is positive. As a result, the Fickian diffusion coefficients matrix has a positive determinant, but its elements - including diagonal elements - can be negative. Comprehensive survey of reported diffusion coefficients data for ternary and quaternary mixtures, confirms that invariably the determinant of the Fickian diffusion coefficients matrix is positive.

High-frequency matrix converter with square wave input

Science.gov (United States)

Carr, Joseph Alexander; Balda, Juan Carlos

2015-03-31

A device for producing an alternating current output voltage from a high-frequency, square-wave input voltage comprising, high-frequency, square-wave input a matrix converter and a control system. The matrix converter comprises a plurality of electrical switches. The high-frequency input and the matrix converter are electrically connected to each other. The control system is connected to each switch of the matrix converter. The control system is electrically connected to the input of the matrix converter. The control system is configured to operate each electrical switch of the matrix converter converting a high-frequency, square-wave input voltage across the first input port of the matrix converter and the second input port of the matrix converter to an alternating current output voltage at the output of the matrix converter.

Maximal quantum Fisher information matrix

International Nuclear Information System (INIS)

Chen, Yu; Yuan, Haidong

2017-01-01

We study the existence of the maximal quantum Fisher information matrix in the multi-parameter quantum estimation, which bounds the ultimate precision limit. We show that when the maximal quantum Fisher information matrix exists, it can be directly obtained from the underlying dynamics. Examples are then provided to demonstrate the usefulness of the maximal quantum Fisher information matrix by deriving various trade-off relations in multi-parameter quantum estimation and obtaining the bounds for the scalings of the precision limit. (paper)

How to get the Matrix Organization to Work

DEFF Research Database (Denmark)

Burton, Richard M.; Obel, Børge; Håkonsson, Dorthe Døjbak

2015-01-01

a matrix to work, taking a multi-contingency perspective. We translate the matrix concept for designers and managers who are considering a matrix organization and argue that three factors are critical for its success: (1) Strong purpose: Only choose the matrix structure if there are strong reasons...... for doing so, (2) Alignment among contingencies: A matrix can only be successful if key contingencies are aligned with the matrix’s purpose, and (3) Management of junctions: The success of a matrix depends on how well activities at the junctions of the matrix are managed....

Computing Nash equilibria through computational intelligence methods

Science.gov (United States)

Pavlidis, N. G.; Parsopoulos, K. E.; Vrahatis, M. N.

2005-03-01

Nash equilibrium constitutes a central solution concept in game theory. The task of detecting the Nash equilibria of a finite strategic game remains a challenging problem up-to-date. This paper investigates the effectiveness of three computational intelligence techniques, namely, covariance matrix adaptation evolution strategies, particle swarm optimization, as well as, differential evolution, to compute Nash equilibria of finite strategic games, as global minima of a real-valued, nonnegative function. An issue of particular interest is to detect more than one Nash equilibria of a game. The performance of the considered computational intelligence methods on this problem is investigated using multistart and deflection.

On a Markov chain roulette-type game

International Nuclear Information System (INIS)

El-Shehawey, M A; El-Shreef, Gh A

2009-01-01

A Markov chain on non-negative integers which arises in a roulette-type game is discussed. The transition probabilities are p 01 = ρ, p Nj = δ Nj , p i,i+W = q, p i,i-1 = p = 1 - q, 1 ≤ W < N, 0 ≤ ρ ≤ 1, N - W < j ≤ N and i = 1, 2, ..., N - W. Using formulae for the determinant of a partitioned matrix, a closed form expression for the solution of the Markov chain roulette-type game is deduced. The present analysis is supported by two mathematical models from tumor growth and war with bargaining

Integrated optic vector-matrix multiplier

Science.gov (United States)

Watts, Michael R [Albuquerque, NM

2011-09-27

A vector-matrix multiplier is disclosed which uses N different wavelengths of light that are modulated with amplitudes representing elements of an N.times.1 vector and combined to form an input wavelength-division multiplexed (WDM) light stream. The input WDM light stream is split into N streamlets from which each wavelength of the light is individually coupled out and modulated for a second time using an input signal representing elements of an M.times.N matrix, and is then coupled into an output waveguide for each streamlet to form an output WDM light stream which is detected to generate a product of the vector and matrix. The vector-matrix multiplier can be formed as an integrated optical circuit using either waveguide amplitude modulators or ring resonator amplitude modulators.

P-matrix description of charged particles interaction

International Nuclear Information System (INIS)

Babenko, V.A.; Petrov, N.M.

1992-01-01

The paper deals with formalism of the P-matrix description of two charged particles interaction. Separation in the explicit form of the background part corresponding to the purely Coulomb interaction in the P-matrix is proposed. Expressions for the purely Coulomb P-matrix, its poles, residues and purely Coulomb P-matrix approach eigenfunctions are obtained. (author). 12 refs

Inverse Operation of Four-dimensional Vector Matrix

OpenAIRE

H J Bao; A J Sang; H X Chen

2011-01-01

This is a new series of study to define and prove multidimensional vector matrix mathematics, which includes four-dimensional vector matrix determinant, four-dimensional vector matrix inverse and related properties. There are innovative concepts of multi-dimensional vector matrix mathematics created by authors with numerous applications in engineering, math, video conferencing, 3D TV, and other fields.

Deposition of matrix-free fullerene films with improved morphology by matrix-assisted pulsed laser evaporation (MAPLE)

DEFF Research Database (Denmark)

Canulescu, Stela; Schou, Jørgen; Fæster, Søren

2013-01-01

Thin films of C60 were deposited by matrix-assisted pulsed laser evaporation (MAPLE) from a frozen target of anisole with 0.67 wt% C60. Above a fluence of 1.5 J/cm2 the C60 films are strongly non-uniform and are resulting from transfer of matrix-droplets containing fullerenes. At low fluence...... the fullerene molecules in the films are intact, the surface morphology is substantially improved and there are no measurable traces of the matrix molecules in the film. This may indicate a regime of dominant evaporation at low fluence which merges into the MAPLE regime of liquid ejection of the host matrix...

Elementary matrix algebra

CERN Document Server

Hohn, Franz E

2012-01-01

This complete and coherent exposition, complemented by numerous illustrative examples, offers readers a text that can teach by itself. Fully rigorous in its treatment, it offers a mathematically sound sequencing of topics. The work starts with the most basic laws of matrix algebra and progresses to the sweep-out process for obtaining the complete solution of any given system of linear equations - homogeneous or nonhomogeneous - and the role of matrix algebra in the presentation of useful geometric ideas, techniques, and terminology.Other subjects include the complete treatment of the structur

Numerical study on optimal Stirling engine regenerator matrix designs taking into account the effects of matrix temperature oscillations

DEFF Research Database (Denmark)

Andersen, Stig Kildegård; Carlsen, Henrik; Thomsen, Per Grove

2006-01-01

A new regenerator matrix design that improves the efficiency of a Stirling engine has been developed in a numerical study of the existing SM5 Stirling engine. A new, detailed, one-dimensional Stirling engine model that delivers results in good agreement with experimental data was used for mapping...... the per- formance of the engine, for mapping the effects of regenerator matrix temperature oscillations, and for optimising the regenerator design. The regenerator matrix temperatures were found to oscillate in two modes. The first mode was oscillation of a nearly linear axial matrix temperature profile...... while the second mode bended the ends of the axial matrix temperature profile when gas flowed into the regenerator with a temperature significantly different from the matrix temperature. The first mode of oscillation improved the efficiency of the engine but the second mode reduced both the work output...

Ubiquitination of specific mitochondrial matrix proteins

International Nuclear Information System (INIS)

Lehmann, Gilad; Ziv, Tamar; Braten, Ori; Admon, Arie; Udasin, Ronald G.; Ciechanover, Aaron

2016-01-01

Several protein quality control systems in bacteria and/or mitochondrial matrix from lower eukaryotes are absent in higher eukaryotes. These are transfer-messenger RNA (tmRNA), The N-end rule ATP-dependent protease ClpAP, and two more ATP-dependent proteases, HslUV and ClpXP (in yeast). The lost proteases resemble the 26S proteasome and the role of tmRNA and the N-end rule in eukaryotic cytosol is performed by the ubiquitin proteasome system (UPS). Therefore, we hypothesized that the UPS might have substituted these systems – at least partially – in the mitochondrial matrix of higher eukaryotes. Using three independent experimental approaches, we demonstrated the presence of ubiquitinated proteins in the matrix of isolated yeast mitochondria. First, we show that isolated mitochondria contain ubiquitin (Ub) conjugates, which remained intact after trypsin digestion. Second, we demonstrate that the mitochondrial soluble fraction contains Ub-conjugates, several of which were identified by mass spectrometry and are localized to the matrix. Third, using immunoaffinity enrichment by specific antibodies recognizing digested ubiquitinated peptides, we identified a group of Ub-modified matrix proteins. The modification was further substantiated by separation on SDS-PAGE and immunoblots. Last, we attempted to identify the ubiquitin ligase(s) involved, and identified Dma1p as a trypsin-resistant protein in our mitochondrial preparations. Taken together, these data suggest a yet undefined role for the UPS in regulation of the mitochondrial matrix proteins. -- Highlights: •Mitochondrial matrix contains ubiquitinated proteins. •Ubiquitination occurs most probably in the matrix. •Dma1p is a ubiquitin ligase present in mitochondrial preparations.

Fibre-Matrix Interaction in Soft Tissue

International Nuclear Information System (INIS)

Guo, Zaoyang

2010-01-01

Although the mechanical behaviour of soft tissue has been extensively studied, the interaction between the collagen fibres and the ground matrix has not been well understood and is therefore ignored by most constitutive models of soft tissue. In this paper, the human annulus fibrosus is used as an example and the potential fibre-matrix interaction is identified by careful investigation of the experimental results of biaxial and uniaxial testing of the human annulus fibrosus. First, the uniaxial testing result of the HAF along the axial direction is analysed and it is shown that the mechanical behaviour of the ground matrix can be well simulated by the incompressible neo-Hookean model when the collagen fibres are all under contraction. If the collagen fibres are stretched, the response of the ground matrix can still be described by the incompressible neo-Hookean model, but the effective stiffness of the matrix depends on the fibre stretch ratio. This stiffness can be more than 10 times larger than the one obtained with collagen fibres under contraction. This phenomenon can only be explained by the fibre-matrix interaction. Furthermore, we find that the physical interpretation of this interaction includes the inhomogeneity of the soft tissue and the fibre orientation dispersion. The dependence of the tangent stiffness of the matrix on the first invariant of the deformation tensor can also be explained by the fibre orientation dispersion. The significant effect of the fibre-matrix interaction strain energy on mechanical behaviour of the soft tissue is also illustrated by comparing some simulation results.

Ubiquitination of specific mitochondrial matrix proteins

Energy Technology Data Exchange (ETDEWEB)

Lehmann, Gilad [The Janet and David Polak Tumor and Vascular Biology Research Center and the Technion Integrated Cancer Center (TICC), The Rappaport Faculty of Medicine and Research Institute, Haifa, 31096 (Israel); Ziv, Tamar [The Smoler Proteomics Center, Faculty of Biology – Technion-Israel Institute of Technology, Haifa, 32000 (Israel); Braten, Ori [The Janet and David Polak Tumor and Vascular Biology Research Center and the Technion Integrated Cancer Center (TICC), The Rappaport Faculty of Medicine and Research Institute, Haifa, 31096 (Israel); Admon, Arie [The Smoler Proteomics Center, Faculty of Biology – Technion-Israel Institute of Technology, Haifa, 32000 (Israel); Udasin, Ronald G. [The Janet and David Polak Tumor and Vascular Biology Research Center and the Technion Integrated Cancer Center (TICC), The Rappaport Faculty of Medicine and Research Institute, Haifa, 31096 (Israel); Ciechanover, Aaron, E-mail: aaroncie@tx.technion.ac.il [The Janet and David Polak Tumor and Vascular Biology Research Center and the Technion Integrated Cancer Center (TICC), The Rappaport Faculty of Medicine and Research Institute, Haifa, 31096 (Israel)

2016-06-17

Several protein quality control systems in bacteria and/or mitochondrial matrix from lower eukaryotes are absent in higher eukaryotes. These are transfer-messenger RNA (tmRNA), The N-end rule ATP-dependent protease ClpAP, and two more ATP-dependent proteases, HslUV and ClpXP (in yeast). The lost proteases resemble the 26S proteasome and the role of tmRNA and the N-end rule in eukaryotic cytosol is performed by the ubiquitin proteasome system (UPS). Therefore, we hypothesized that the UPS might have substituted these systems – at least partially – in the mitochondrial matrix of higher eukaryotes. Using three independent experimental approaches, we demonstrated the presence of ubiquitinated proteins in the matrix of isolated yeast mitochondria. First, we show that isolated mitochondria contain ubiquitin (Ub) conjugates, which remained intact after trypsin digestion. Second, we demonstrate that the mitochondrial soluble fraction contains Ub-conjugates, several of which were identified by mass spectrometry and are localized to the matrix. Third, using immunoaffinity enrichment by specific antibodies recognizing digested ubiquitinated peptides, we identified a group of Ub-modified matrix proteins. The modification was further substantiated by separation on SDS-PAGE and immunoblots. Last, we attempted to identify the ubiquitin ligase(s) involved, and identified Dma1p as a trypsin-resistant protein in our mitochondrial preparations. Taken together, these data suggest a yet undefined role for the UPS in regulation of the mitochondrial matrix proteins. -- Highlights: •Mitochondrial matrix contains ubiquitinated proteins. •Ubiquitination occurs most probably in the matrix. •Dma1p is a ubiquitin ligase present in mitochondrial preparations.

Convergence of Transition Probability Matrix in CLVMarkov Models

Science.gov (United States)

Permana, D.; Pasaribu, U. S.; Indratno, S. W.; Suprayogi, S.

2018-04-01

A transition probability matrix is an arrangement of transition probability from one states to another in a Markov chain model (MCM). One of interesting study on the MCM is its behavior for a long time in the future. The behavior is derived from one property of transition probabilty matrix for n steps. This term is called the convergence of the n-step transition matrix for n move to infinity. Mathematically, the convergence of the transition probability matrix is finding the limit of the transition matrix which is powered by n where n moves to infinity. The convergence form of the transition probability matrix is very interesting as it will bring the matrix to its stationary form. This form is useful for predicting the probability of transitions between states in the future. The method usually used to find the convergence of transition probability matrix is through the process of limiting the distribution. In this paper, the convergence of the transition probability matrix is searched using a simple concept of linear algebra that is by diagonalizing the matrix.This method has a higher level of complexity because it has to perform the process of diagonalization in its matrix. But this way has the advantage of obtaining a common form of power n of the transition probability matrix. This form is useful to see transition matrix before stationary. For example cases are taken from CLV model using MCM called Model of CLV-Markov. There are several models taken by its transition probability matrix to find its convergence form. The result is that the convergence of the matrix of transition probability through diagonalization has similarity with convergence with commonly used distribution of probability limiting method.

Octonionic matrix representation and electromagnetism

Energy Technology Data Exchange (ETDEWEB)

Chanyal, B. C. [Kumaun University, S. S. J. Campus, Almora (India)

2014-12-15

Keeping in mind the important role of octonion algebra, we have obtained the electromagnetic field equations of dyons with an octonionic 8 x 8 matrix representation. In this paper, we consider the eight - dimensional octonionic space as a combination of two (external and internal) four-dimensional spaces for the existence of magnetic monopoles (dyons) in a higher-dimensional formalism. As such, we describe the octonion wave equations in terms of eight components from the 8 x 8 matrix representation. The octonion forms of the generalized potential, fields and current source of dyons in terms of 8 x 8 matrix are discussed in a consistent manner. Thus, we have obtained the generalized Dirac-Maxwell equations of dyons from an 8x8 matrix representation of the octonion wave equations in a compact and consistent manner. The generalized Dirac-Maxwell equations are fully symmetric Maxwell equations and allow for the possibility of magnetic charges and currents, analogous to electric charges and currents. Accordingly, we have obtained the octonionic Dirac wave equations in an external field from the matrix representation of the octonion-valued potentials of dyons.

48 CFR 2152.370 - Use of the matrix.

Science.gov (United States)

2010-10-01

... 48 Federal Acquisition Regulations System 6 2010-10-01 2010-10-01 true Use of the matrix. 2152.370... CONTRACT CLAUSES Provision and Clause Matrix 2152.370 Use of the matrix. (a) The matrix in this section... clause is to be used only when the applicable conditions are met. FEGLI Program Clause Matrix Clause No...

Multiscale Modeling of Ceramic Matrix Composites

Science.gov (United States)

Bednarcyk, Brett A.; Mital, Subodh K.; Pineda, Evan J.; Arnold, Steven M.

2015-01-01

Results of multiscale modeling simulations of the nonlinear response of SiC/SiC ceramic matrix composites are reported, wherein the microstructure of the ceramic matrix is captured. This micro scale architecture, which contains free Si material as well as the SiC ceramic, is responsible for residual stresses that play an important role in the subsequent thermo-mechanical behavior of the SiC/SiC composite. Using the novel Multiscale Generalized Method of Cells recursive micromechanics theory, the microstructure of the matrix, as well as the microstructure of the composite (fiber and matrix) can be captured.

Measuring methods of matrix diffusion

International Nuclear Information System (INIS)

Muurinen, A.; Valkiainen, M.

1988-03-01

In Finland the spent nuclear fuel is planned to be disposed of at large depths in crystalline bedrock. The radionuclides which are dissolved in the groundwater may be able to diffuse into the micropores of the porous rock matrix and thus be withdrawn from the flowing water in the fractures. This phenomenon is called matrix diffusion. A review over matrix diffusion is presented in the study. The main interest is directed to the diffusion of non-sorbing species. The review covers diffusion experiments and measurements of porosity, pore size, specific surface area and water permeability

Approximating the minimum cycle mean

Directory of Open Access Journals (Sweden)

Krishnendu Chatterjee

2013-07-01

Full Text Available We consider directed graphs where each edge is labeled with an integer weight and study the fundamental algorithmic question of computing the value of a cycle with minimum mean weight. Our contributions are twofold: (1 First we show that the algorithmic question is reducible in O(n^2 time to the problem of a logarithmic number of min-plus matrix multiplications of n-by-n matrices, where n is the number of vertices of the graph. (2 Second, when the weights are nonnegative, we present the first (1 + ε-approximation algorithm for the problem and the running time of our algorithm is ilde(O(n^ω log^3(nW/ε / ε, where O(n^ω is the time required for the classic n-by-n matrix multiplication and W is the maximum value of the weights.

Video based object representation and classification using multiple covariance matrices.

Science.gov (United States)

Zhang, Yurong; Liu, Quan

2017-01-01

Video based object recognition and classification has been widely studied in computer vision and image processing area. One main issue of this task is to develop an effective representation for video. This problem can generally be formulated as image set representation. In this paper, we present a new method called Multiple Covariance Discriminative Learning (MCDL) for image set representation and classification problem. The core idea of MCDL is to represent an image set using multiple covariance matrices with each covariance matrix representing one cluster of images. Firstly, we use the Nonnegative Matrix Factorization (NMF) method to do image clustering within each image set, and then adopt Covariance Discriminative Learning on each cluster (subset) of images. At last, we adopt KLDA and nearest neighborhood classification method for image set classification. Promising experimental results on several datasets show the effectiveness of our MCDL method.

Effect of matrix constitution on interface of aluminium/δ-Al2O3 and strength of metal matrix composites

International Nuclear Information System (INIS)

Johansson, P.; Hutchinson, B.; Savage, S.J.

1992-06-01

Aluminium based fiber composites have been made by squeeze casting. The 'saffil' pre-forms used in the work employed aluminium oxide binder or silica binder. Two families of alloys have been used based either on high purity aluminium or 3% copper containing alloys. These were both alloyed with a range of magnesium contents from 0.1% to 5% with the aim of varying the degree of reaction and bonding between the matrix and the reinforcing fibres. Studies of macro- and micro structures have been performed as well as non-destructive testing by X-ray radiography. Tensile testing, three point bend tests on notched bars and wetting studies in a wetting balance are also included in the investigation. The structure of the squeeze cast products shows different zones. The extension and appearance of the zones are dependent on the alloy constitution. In general the surface of the casting have small equiaxed grains. This surface zone is replaced by a columnar grain zone which, in the center, transforms to an equiaxed crystal zone. Defects such as pores, fibre-free zones, and 'pockets' in the interface matrix/fiber have been found. Of these defects, only pores can be detected by X-ray radiography. Evaluation of tensile testing shows a relatively large scatter of results. The results reveal a dominant role of matrix composition on strength level. For the 20 vol% reinforced metals, with performs with silica binder, the maximum measured elongation was 3.5%. With alumina binder approximately half of the above mentioned ductility is obtained. The use of grain-refiner, Al-5Ti-B, decreases the ductility of the composite below 2%, independent of the type of binder. From 3-point bend tests fracture energies are estimated to vary between 0.3 and 0.6 Joule. The toughness is low. Studies of the wetting between pieces of ceramic pre-forms and molten Al-2Mg show that generally the wetting is poor. At the same time, the wettability of d-alumina with silicon oxide as binding medium was slightly

Analytic matrix elements with shifted correlated Gaussians

DEFF Research Database (Denmark)

Fedorov, D. V.

2017-01-01

Matrix elements between shifted correlated Gaussians of various potentials with several form-factors are calculated analytically. Analytic matrix elements are of importance for the correlated Gaussian method in quantum few-body physics.......Matrix elements between shifted correlated Gaussians of various potentials with several form-factors are calculated analytically. Analytic matrix elements are of importance for the correlated Gaussian method in quantum few-body physics....

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

Science.gov (United States)

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.

Construction of Short-length High-rates Ldpc Codes Using Difference Families

OpenAIRE

Deny Hamdani; Ery Safrianti

2007-01-01

Low-density parity-check (LDPC) code is linear-block error-correcting code defined by sparse parity-check matrix. It isdecoded using the massage-passing algorithm, and in many cases, capable of outperforming turbo code. This paperpresents a class of low-density parity-check (LDPC) codes showing good performance with low encoding complexity.The code is constructed using difference families from combinatorial design. The resulting code, which is designed tohave short code length and high code r...

Matrix Metalloproteinases: Inflammatory Regulators of Cell Behaviors in Vascular Formation and Remodeling

Directory of Open Access Journals (Sweden)

Qishan Chen

2013-01-01

Full Text Available Abnormal angiogenesis and vascular remodeling contribute to pathogenesis of a number of disorders such as tumor, arthritis, atherosclerosis, restenosis, hypertension, and neurodegeneration. During angiogenesis and vascular remodeling, behaviors of stem/progenitor cells, endothelial cells (ECs, and vascular smooth muscle cells (VSMCs and its interaction with extracellular matrix (ECM play a critical role in the processes. Matrix metalloproteinases (MMPs, well-known inflammatory mediators are a family of zinc-dependent proteolytic enzymes that degrade various components of ECM and non-ECM molecules mediating tissue remodeling in both physiological and pathological processes. MMPs including MMP-1, MMP-2, MMP-3, MMP-7, MMP-8, MMP-9, MMP-12, and MT1-MMP, are stimulated and activated by various stimuli in vascular tissues. Once activated, MMPs degrade ECM proteins or other related signal molecules to promote recruitment of stem/progenitor cells and facilitate migration and invasion of ECs and VSMCs. Moreover, vascular cell proliferation and apoptosis can also be regulated by MMPs via proteolytically cleaving and modulating bioactive molecules and relevant signaling pathways. Regarding the importance of vascular cells in abnormal angiogenesis and vascular remodeling, regulation of vascular cell behaviors through modulating expression and activation of MMPs shows therapeutic potential.

High resolution in situ zymography reveals matrix metalloproteinase activity at glutamatergic synapses.

Science.gov (United States)

Gawlak, M; Górkiewicz, T; Gorlewicz, A; Konopacki, F A; Kaczmarek, L; Wilczynski, G M

2009-01-12

Synaptic plasticity involves remodeling of extracellular matrix. This is mediated, in part, by enzymes of the matrix metalloproteinase (MMP) family, in particular by gelatinase MMP-9. Accordingly, there is a need of developing methods to visualize gelatinolytic activity at the level of individual synapses, especially in the context of neurotransmitters receptors. Here we present a high-resolution fluorescent in situ zymography (ISZ), performed in thin sections of the alcohol-fixed and polyester wax-embedded brain tissue of the rat (Rattus norvegicus), which is superior to the current ISZ protocols. The method allows visualization of structural details up to the resolution-limit of light microscopy, in conjunction with immunofluorescent labeling. We used this technique to visualize and quantify gelatinolytic activity at the synapses in control and seizure-affected rat brain. In particular, we demonstrated, for the first time, frequent colocalization of gelatinase(s) with synaptic N-methyl-D-aspartic acid (NMDA)- and AMPA-type glutamate receptors. We believe that our method represents a valuable tool to study extracellular proteolytic processes at the synapses, it could be used, as well, to investigate proteinase involvement in a range of physiological and pathological phenomena in the nervous system.

Response matrix method for large LMFBR analysis

International Nuclear Information System (INIS)

King, M.J.

1977-06-01

The feasibility of using response matrix techniques for computational models of large LMFBRs is examined. Since finite-difference methods based on diffusion theory have generally found a place in fast-reactor codes, a brief review of their general matrix foundation is given first in order to contrast it to the general strategy of response matrix methods. Then, in order to present the general method of response matrix technique, two illustrative examples are given. Matrix algorithms arising in the application to large LMFBRs are discussed, and the potential of the response matrix method is explored for a variety of computational problems. Principal properties of the matrices involved are derived with a view to application of numerical methods of solution. The Jacobi iterative method as applied to the current-balance eigenvalue problem is discussed

The requirement of matrix ATP for the import of precursor proteins into the mitochondrial matrix and intermembrane space

NARCIS (Netherlands)

Stuart, Rosemary A.; Gruhler, Albrecht; Klei, Ida van der; Guiard, Bernard; Koll, Hans; Neupert, Walter

1994-01-01

The role of ATP in the matrix for the import of precursor proteins into the various mitochondrial subcompartments was investigated by studying protein translocation at experimentally defined ATP levels. Proteins targeted to the matrix were neither imported or processed when matrix ATP was depleted.

Multivariate extended skew-t distributions and related families

KAUST Repository

Arellano-Valle, Reinaldo B.

2010-12-01

A class of multivariate extended skew-t (EST) distributions is introduced and studied in detail, along with closely related families such as the subclass of extended skew-normal distributions. Besides mathematical tractability and modeling flexibility in terms of both skewness and heavier tails than the normal distribution, the most relevant properties of the EST distribution include closure under conditioning and ability to model lighter tails as well. The first part of the present paper examines probabilistic properties of the EST distribution, such as various stochastic representations, marginal and conditional distributions, linear transformations, moments and in particular Mardia’s measures of multivariate skewness and kurtosis. The second part of the paper studies statistical properties of the EST distribution, such as likelihood inference, behavior of the profile log-likelihood, the score vector and the Fisher information matrix. Especially, unlike the extended skew-normal distribution, the Fisher information matrix of the univariate EST distribution is shown to be non-singular when the skewness is set to zero. Finally, a numerical application of the conditional EST distribution is presented in the context of confidential data perturbation.

Multivariate extended skew-t distributions and related families

KAUST Repository

Arellano-Valle, Reinaldo B.; Genton, Marc G.

2010-01-01

A class of multivariate extended skew-t (EST) distributions is introduced and studied in detail, along with closely related families such as the subclass of extended skew-normal distributions. Besides mathematical tractability and modeling flexibility in terms of both skewness and heavier tails than the normal distribution, the most relevant properties of the EST distribution include closure under conditioning and ability to model lighter tails as well. The first part of the present paper examines probabilistic properties of the EST distribution, such as various stochastic representations, marginal and conditional distributions, linear transformations, moments and in particular Mardia’s measures of multivariate skewness and kurtosis. The second part of the paper studies statistical properties of the EST distribution, such as likelihood inference, behavior of the profile log-likelihood, the score vector and the Fisher information matrix. Especially, unlike the extended skew-normal distribution, the Fisher information matrix of the univariate EST distribution is shown to be non-singular when the skewness is set to zero. Finally, a numerical application of the conditional EST distribution is presented in the context of confidential data perturbation.

Inequalities Involving Upper Bounds for Certain Matrix Operators

Indian Academy of Sciences (India)

Home; Journals; Proceedings – Mathematical Sciences; Volume 116; Issue 3. Inequalities Involving Upper Bounds for Certain Matrix Operators. R Lashkaripour D Foroutannia. Volume ... Keywords. Inequality; norm; summability matrix; Hausdorff matrix; Hilbert matrix; weighted sequence space; Lorentz sequence space.

On matrix fractional differential equations

Directory of Open Access Journals (Sweden)

Adem Kılıçman

2017-01-01

Full Text Available The aim of this article is to study the matrix fractional differential equations and to find the exact solution for system of matrix fractional differential equations in terms of Riemann–Liouville using Laplace transform method and convolution product to the Riemann–Liouville fractional of matrices. Also, we show the theorem of non-homogeneous matrix fractional partial differential equation with some illustrative examples to demonstrate the effectiveness of the new methodology. The main objective of this article is to discuss the Laplace transform method based on operational matrices of fractional derivatives for solving several kinds of linear fractional differential equations. Moreover, we present the operational matrices of fractional derivatives with Laplace transform in many applications of various engineering systems as control system. We present the analytical technique for solving fractional-order, multi-term fractional differential equation. In other words, we propose an efficient algorithm for solving fractional matrix equation.

Risk matrix model for rotating equipment

Directory of Open Access Journals (Sweden)

Wassan Rano Khan

2014-07-01

Full Text Available Different industries have various residual risk levels for their rotating equipment. Accordingly the occurrence rate of the failures and associated failure consequences categories are different. Thus, a generalized risk matrix model is developed in this study which can fit various available risk matrix standards. This generalized risk matrix will be helpful to develop new risk matrix, to fit the required risk assessment scenario for rotating equipment. Power generation system was taken as case study. It was observed that eight subsystems were under risk. Only vibration monitor system was under high risk category, while remaining seven subsystems were under serious and medium risk categories.

A Generalization of the Alias Matrix

DEFF Research Database (Denmark)

Kulahci, Murat; Bisgaard, S.

2006-01-01

The investigation of aliases or biases is important for the interpretation of the results from factorial experiments. For two-level fractional factorials this can be facilitated through their group structure. For more general arrays the alias matrix can be used. This tool is traditionally based...... on the assumption that the error structure is that associated with ordinary least squares. For situations where that is not the case, we provide in this article a generalization of the alias matrix applicable under the generalized least squares assumptions. We also show that for the special case of split plot error...... structure, the generalized alias matrix simplifies to the ordinary alias matrix....

Multi-cut solutions in Chern-Simons matrix models

Science.gov (United States)

Morita, Takeshi; Sugiyama, Kento

2018-04-01

We elaborate the Chern-Simons (CS) matrix models at large N. The saddle point equations of these matrix models have a curious structure which cannot be seen in the ordinary one matrix models. Thanks to this structure, an infinite number of multi-cut solutions exist in the CS matrix models. Particularly we exactly derive the two-cut solutions at finite 't Hooft coupling in the pure CS matrix model. In the ABJM matrix model, we argue that some of multi-cut solutions might be interpreted as a condensation of the D2-brane instantons.

Matrix transformation of Fibonacci band matrix on generalized $bv$-space and its dual spaces

Directory of Open Access Journals (Sweden)

Anupam Das

2018-07-01

Full Text Available In this paper we introduce a new sequence space $bv(\\hat{F}$ by using the Fibonacci band matrix $\\hat{F}.$ We also establish a few inclusion relations concerning this space and determine its $\\alpha-,\\beta-,\\gamma-$duals. Finally we characterize some matrix classes on the space $bv(\\hat{F}.$

Cell–material interactions on biphasic polyurethane matrix

Science.gov (United States)

Dicesare, Patrick; Fox, Wade M.; Hill, Michael J.; Krishnan, G. Rajesh; Yang, Shuying; Sarkar, Debanjan

2013-01-01

Cell–matrix interaction is a key regulator for controlling stem cell fate in regenerative tissue engineering. These interactions are induced and controlled by the nanoscale features of extracellular matrix and are mimicked on synthetic matrices to control cell structure and functions. Recent studies have shown that nanostructured matrices can modulate stem cell behavior and exert specific role in tissue regeneration. In this study, we have demonstrated that nanostructured phase morphology of synthetic matrix can control adhesion, proliferation, organization and migration of human mesenchymal stem cells (MSCs). Nanostructured biodegradable polyurethanes (PU) with segmental composition exhibit biphasic morphology at nanoscale dimensions and can control cellular features of MSCs. Biodegradable PU with polyester soft segment and hard segment composed of aliphatic diisocyanates and dipeptide chain extender were designed to examine the effect polyurethane phase morphology. By altering the polyurethane composition, morphological architecture of PU was modulated and its effect was examined on MSC. Results show that MSCs can sense the nanoscale morphology of biphasic polyurethane matrix to exhibit distinct cellular features and, thus, signifies the relevance of matrix phase morphology. The role of nanostructured phases of a synthetic matrix in controlling cell–matrix interaction provides important insights for regulation of cell behavior on synthetic matrix and, therefore, is an important tool for engineering tissue regeneration. PMID:23255285

Active site specificity profiling datasets of matrix metalloproteinases (MMPs 1, 2, 3, 7, 8, 9, 12, 13 and 14

Directory of Open Access Journals (Sweden)

Ulrich Eckhard

2016-06-01

Full Text Available The data described provide a comprehensive resource for the family-wide active site specificity portrayal of the human matrix metalloproteinase family. We used the high-throughput proteomic technique PICS (Proteomic Identification of protease Cleavage Sites to comprehensively assay 9 different MMPs. We identified more than 4300 peptide cleavage sites, spanning both the prime and non-prime sides of the scissile peptide bond allowing detailed subsite cooperativity analysis. The proteomic cleavage data were expanded by kinetic analysis using a set of 6 quenched-fluorescent peptide substrates designed using these results. These datasets represent one of the largest specificity profiling efforts with subsequent structural follow up for any protease family and put the spotlight on the specificity similarities and differences of the MMP family. A detailed analysis of this data may be found in Eckhard et al. (2015 [1]. The raw mass spectrometry data and the corresponding metadata have been deposited in PRIDE/ProteomeXchange with the accession number http://www.ebi.ac.uk/pride/archive/projects/PXD002265.

Better Metrics to Automatically Predict the Quality of a Text Summary

Directory of Open Access Journals (Sweden)

Judith D. Schlesinger

2012-09-01

Full Text Available In this paper we demonstrate a family of metrics for estimating the quality of a text summary relative to one or more human-generated summaries. The improved metrics are based on features automatically computed from the summaries to measure content and linguistic quality. The features are combined using one of three methods—robust regression, non-negative least squares, or canonical correlation, an eigenvalue method. The new metrics significantly outperform the previous standard for automatic text summarization evaluation, ROUGE.

Involvement of extracellular matrix constituents in breast cancer

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Lochter, Andre; Bissell, Mina J

1995-06-01

It has recently been established that the extracellular matrix is required for normal functional differentiation of mammary epithelia not only in culture, but also in vivo. The mechanisms by which extracellular matrix affects differentiation, as well as the nature of extracellular matrix constituents which have major impacts on mammary gland function, have only now begun to be dissected. The intricate variety of extracellular matrix-mediated events and the remarkable degree of plasticity of extracellular matrix structure and composition at virtually all times during ontogeny, make such studies difficult. Similarly, during carcinogenesis, the extracellular matrix undergoes gross alterations, the consequences of which are not yet precisely understood. Nevertheless, an increasing amount of data suggests that the extracellular matrix and extracellular matrix-receptors might participate in the control of most, if not all, of the successive stages of breast tumors, from appearance to progression and metastasis.

Causal Inference and Explaining Away in a Spiking Network

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Moreno-Bote, Rubén; Drugowitsch, Jan

2015-01-01

While the brain uses spiking neurons for communication, theoretical research on brain computations has mostly focused on non-spiking networks. The nature of spike-based algorithms that achieve complex computations, such as object probabilistic inference, is largely unknown. Here we demonstrate that a family of high-dimensional quadratic optimization problems with non-negativity constraints can be solved exactly and efficiently by a network of spiking neurons. The network naturally imposes the non-negativity of causal contributions that is fundamental to causal inference, and uses simple operations, such as linear synapses with realistic time constants, and neural spike generation and reset non-linearities. The network infers the set of most likely causes from an observation using explaining away, which is dynamically implemented by spike-based, tuned inhibition. The algorithm performs remarkably well even when the network intrinsically generates variable spike trains, the timing of spikes is scrambled by external sources of noise, or the network is mistuned. This type of network might underlie tasks such as odor identification and classification. PMID:26621426

The Perron-Frobenius theorem for multi-homogeneous mappings

OpenAIRE

Gautier, Antoine; Tudisco, Francesco; Hein, Matthias

2018-01-01

The Perron-Frobenius theory for nonnegative matrices has been generalized to order-preserving homogeneous mappings on a cone and more recently to nonnegative multilinear forms. We unify both approaches by introducing the concept of order-preserving multi-homogeneous mappings, their associated nonlinear spectral problems and spectral radii. We show several Perron-Frobenius type results for these mappings addressing existence, uniqueness and maximality of nonnegative and positive eigenpairs. We...

The Virasoro algebra in integrable hierarchies and the method of matrix models

International Nuclear Information System (INIS)

Semikhatov, A.M.

1992-01-01

The action of the Virasoro algebra on hierarchies of nonlinear integrable equations, and also the structure and consequences of Virasoro constraints on these hierarchies, are studied. It is proposed that a broad class of hierarchies, restricted by Virasoro constraints, can be defined in terms of dressing operators hidden in the structure of integrable systems. The Virasoro-algebra representation constructed on the dressing operators displays a number of analogies with structures in conformal field theory. The formulation of the Virasoro constraints that stems from this representation makes it possible to translate into the language of integrable systems a number of concepts from the method of the 'matrix models' that describe nonperturbative quantum gravity, and, in particular, to realize a 'hierarchical' version of the double scaling limit. From the Virasoro constraints written in terms of the dressing operators generalized loop equations are derived, and this makes it possible to do calculations on a reconstruction of the field-theoretical description. The reduction of the Kadomtsev-Petviashvili (KP) hierarchy, subject to Virasoro constraints, to generalized Korteweg-deVries (KdV) hierarchies is implemented, and the corresponding representation of the Virasoro algebra on these hierarchies is found both in the language of scalar differential operators and in the matrix formalism of Drinfel'd and Sokolov. The string equation in the matrix formalism does not replicate the structure of the scalar string equation. The symmetry algebras of the KP and N-KdV hierarchies restricted by Virasoro constraints are calculated: A relationship is established with algebras from the family W ∞ (J) of infinite W-algebras

Quantitative image analysis for investigating cell-matrix interactions

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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.

High matrix metalloproteinase activity is a hallmark of periapical granulomas.

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de Paula-Silva, Francisco Wanderley Garcia; D'Silva, Nisha J; da Silva, Léa Assed Bezerra; Kapila, Yvonne Lorraine

2009-09-01

The inability to distinguish periapical cysts from granulomas before performing root canal treatment leads to uncertainty in treatment outcomes because cysts have lower healing rates. Searching for differential expression of molecules within cysts or granulomas could provide information with regard to the identity of the lesion or suggest mechanistic differences that may form the basis for future therapeutic intervention. Thus, we investigated whether granulomas and cysts exhibit differential expression of extracellular matrix (ECM) molecules. Human periapical granulomas, periapical cysts, and healthy periodontal ligament tissues were used to investigate the differential expression of ECM molecules by microarray analysis. Because matrix metalloproteinases (MMP) showed the highest differential expression in the microarray analysis, MMPs were further examined by in situ zymography and immunohistochemistry. Data were analyzed by using one-way analysis of variance followed by the Tukey test. We observed that cysts and granulomas differentially expressed several ECM molecules, especially those from the MMP family. Compared with cysts, granulomas exhibited higher MMP enzymatic activity in areas stained for MMP-9. These areas were composed of polymorphonuclear cells (PMNs) in contrast to cysts. Similarly, MMP-13 was expressed by a greater number of cells in granulomas compared with cysts. Our findings indicate that high enzymatic MMP activity in PMNs together with MMP-9 and MMP-13 stained cells could be a molecular signature of granulomas unlike periapical cysts.

[Penile augmentation using acellular dermal matrix].

Science.gov (United States)

Zhang, Jin-ming; Cui, Yong-yan; Pan, Shu-juan; Liang, Wei-qiang; Chen, Xiao-xuan

2004-11-01

Penile enhancement was performed using acellular dermal matrix. Multiple layers of acellular dermal matrix were placed underneath the penile skin to enlarge its girth. Since March 2002, penile augmentation has been performed on 12 cases using acellular dermal matrix. Postoperatively all the patients had a 1.3-3.1 cm (2.6 cm in average) increase in penile girth in a flaccid state. The penis had normal appearance and feeling without contour deformities. All patients gained sexual ability 3 months after the operation. One had a delayed wound healing due to tight dressing, which was repaired with a scrotal skin flap. Penile enlargement by implantation of multiple layers of acellular dermal matrix was a safe and effective operation. This method can be performed in an outpatient ambulatory setting. The advantages of the acellular dermal matrix over the autogenous dermal fat grafts are elimination of donor site injury and scar and significant shortening of operation time.